{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "38ab9776",
   "metadata": {},
   "source": [
    "# Automatic differentiation with forward mode\n",
    "\n",
    "> **NOTE**\n",
    ">\n",
    "> autodiff system in `pespace` and `tiwave` is still under active development. If errors occur when running this notebook, try using the commit tagged [`autodiff`](https://github.com/nnrui/pespace/tree/autodiff) may solve the problem.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "302186ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Taichi] version 1.7.4, llvm 15.0.4, commit b4b956fd, linux, python 3.10.19\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[I 02/02/26 11:42:21.678 84923] [shell.py:_shell_pop_print@23] Graphical python shell detected, using wrapped sys.stdout\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Taichi] Starting on arch=x64\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import bilby\n",
    "\n",
    "import taichi as ti\n",
    "ti.init(\n",
    "    arch=ti.cpu,\n",
    "    default_fp=ti.f64,\n",
    "    cpu_max_num_threads=1,\n",
    "    offline_cache=False,\n",
    "    # debug=True,\n",
    ")\n",
    "\n",
    "import os\n",
    "os.environ['PATH'] = \"/home/nrui/.local/texlive/2025/bin/x86_64-linux:\" + os.environ['PATH']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c53ac2aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pespace.detector.antenna import InterferometerAntenna, FDResponseModelMarset2018\n",
    "from pespace.detector.tdi import TDIChannelData, FDMichelsonConstantEqualArm\n",
    "from pespace.detector.orbit import available_orbit_models\n",
    "from tiwave.waveforms import IMRPhenomXAS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c8b43880",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sample num:  65536.0\n",
      "duration:  655360.0\n",
      "duration(day):  7.5851851851851855\n",
      "{'total_mass': 3000000.0, 'mass_ratio': 0.6, 'chi_1': 0.75, 'chi_2': 0.62, 'luminosity_distance': 56000.0, 'inclination': 0.4, 'reference_phase': 1.3, 'ecliptic_longitude': 1.375, 'ecliptic_latitude': -1.2108, 'polarization': 2.659, 'coalescence_time': np.float64(524288.0), 'mass_1': 1875000.0, 'mass_2': 1125000.0, 'chirp_mass': 1256226.717491785, 'symmetric_mass_ratio': np.float64(0.234375)}\n"
     ]
    }
   ],
   "source": [
    "tdi_gen = \"2.0\"\n",
    "tdi_chan = (\"A\", \"E\", \"T\")\n",
    "DAYJUL_SI = 86400.0\n",
    "\n",
    "delta_time = 10\n",
    "num_tsamples = 2 ** np.ceil(np.log2(7 * DAYJUL_SI / delta_time))\n",
    "duration = num_tsamples * delta_time\n",
    "print(\"sample num: \", num_tsamples)\n",
    "print(\"duration: \", duration)\n",
    "print(\"duration(day): \", duration/DAYJUL_SI)\n",
    "\n",
    "f_min = 1e-4\n",
    "f_ref = f_min\n",
    "f_max = 0.5*(1/delta_time)\n",
    "\n",
    "t_start = 0.0\n",
    "before_tc = 0.8 * duration\n",
    "after_tc = 0.2 * duration\n",
    "tc = t_start + before_tc\n",
    "\n",
    "params = dict(\n",
    "    total_mass=3e6,\n",
    "    mass_ratio=0.6,\n",
    "    chi_1=0.75,\n",
    "    chi_2=0.62,\n",
    "    luminosity_distance=56000.0,\n",
    "    inclination=0.4,\n",
    "    reference_phase=1.3,\n",
    "    ecliptic_longitude=1.375,\n",
    "    ecliptic_latitude=-1.2108,\n",
    "    polarization=2.659,\n",
    "    coalescence_time=tc,\n",
    ")\n",
    "params = bilby.gw.conversion.generate_mass_parameters(params)\n",
    "print(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7bdbb11a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/nrui/disk_ext/workspace/tiwave/tiwave/waveforms/base_waveform.py:74: UserWarning: check_parameters is disable, make sure all parameters passed in are valid.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "tdi_data = TDIChannelData()\n",
    "tdi_data.set_fd_data_from_zero(\n",
    "    tdi_chan,\n",
    "    duration,\n",
    "    delta_time,\n",
    "    start_time=t_start,\n",
    "    minimum_frequency=f_min,\n",
    "    maximum_frequency=f_max,\n",
    ")\n",
    "\n",
    "orbit_model = available_orbit_models['LISA_analytic']\n",
    "response_model = FDResponseModelMarset2018()\n",
    "tdi_combination = FDMichelsonConstantEqualArm(generation=tdi_gen, orthogonal=True)\n",
    "\n",
    "lisa = InterferometerAntenna(\n",
    "    name=\"lisa\",\n",
    "    tdi_data=tdi_data,\n",
    "    orbit_model=orbit_model,\n",
    "    response_model=response_model,\n",
    "    tdi_combination=tdi_combination,\n",
    "    needs_dual=True,\n",
    ")\n",
    "waveform_tiw = IMRPhenomXAS(\n",
    "    tdi_data.frequency_samples, \n",
    "    f_ref, \n",
    "    )\n",
    "waveform_tiw.update_waveform(params)\n",
    "lisa.update_detector_response(\n",
    "    waveform_tiw.waveform_container,\n",
    "    params['ecliptic_longitude'],\n",
    "    params[\"ecliptic_latitude\"],\n",
    "    params[\"polarization\"],\n",
    "    params[\"coalescence_time\"],\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7256df36",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # abs\n",
    "# plt.figure()\n",
    "# plt.loglog(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     np.abs(lisa.tdi_response_numpy[\"A\"]),\n",
    "#     label=\"A\",\n",
    "# )\n",
    "# plt.loglog(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     np.abs(lisa.tdi_response_numpy[\"E\"]),\n",
    "#     label=\"E\",\n",
    "# )\n",
    "# plt.loglog(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     np.abs(lisa.tdi_response_numpy[\"T\"]),\n",
    "#     label=\"T\",\n",
    "# )\n",
    "# plt.xlim(f_min, f_max)\n",
    "# plt.legend()\n",
    "\n",
    "# # real part\n",
    "# plt.figure()\n",
    "# plt.semilogx(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     lisa.tdi_response_numpy[\"A\"].real,\n",
    "#     label=\"A real\",\n",
    "# )\n",
    "# plt.semilogx(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     lisa.tdi_response_numpy[\"E\"].real,\n",
    "#     label=\"E real\",\n",
    "# )\n",
    "# plt.semilogx(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     lisa.tdi_response_numpy[\"T\"].real,\n",
    "#     label=\"T real\",\n",
    "# )\n",
    "# plt.xlim(f_min, f_max)\n",
    "# plt.legend()\n",
    "\n",
    "# # imag part\n",
    "# plt.figure()\n",
    "# plt.semilogx(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     lisa.tdi_response_numpy[\"A\"].imag,\n",
    "#     label=\"A imag\",\n",
    "# )\n",
    "# plt.semilogx(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     lisa.tdi_response_numpy[\"E\"].imag,\n",
    "#     label=\"E imag\",\n",
    "# )\n",
    "# plt.semilogx(\n",
    "#     lisa.tdi_data.data_info.frequency_samples_array,\n",
    "#     lisa.tdi_response_numpy[\"T\"].imag,\n",
    "#     label=\"T imag\",\n",
    "# )\n",
    "# plt.xlim(f_min, f_max)\n",
    "# plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0b535015",
   "metadata": {},
   "outputs": [],
   "source": [
    "field_names = [\n",
    "    'link12_re', \n",
    "    'link12_im', \n",
    "    'link21_re', \n",
    "    'link21_im', \n",
    "    'link23_re', \n",
    "    'link23_im', \n",
    "    'link32_re', \n",
    "    'link32_im', \n",
    "    'link31_re', \n",
    "    'link31_im', \n",
    "    'link13_re', \n",
    "    'link13_im', \n",
    "    ]\n",
    "loss = {key: ti.field(dtype=ti.f64, shape=tdi_data.frequency_samples.shape, needs_dual=True) for key in field_names}\n",
    "# print(loss)\n",
    "# print(loss['link12_re'])\n",
    "\n",
    "# @ti.kernel\n",
    "# def test():\n",
    "#     print(ti.get_addr(loss['link12_re'], 0))\n",
    "#     print(ti.get_addr(loss['link12_im'], 0))\n",
    "#     print(ti.get_addr(loss['link21_re'], 0))\n",
    "#     print(ti.get_addr(loss['link21_im'], 0))\n",
    "#     print(ti.get_addr(loss['link23_re'], 0))\n",
    "#     print(ti.get_addr(loss['link23_im'], 0))\n",
    "#     print(ti.get_addr(loss['link32_re'], 0))\n",
    "#     print(ti.get_addr(loss['link32_im'], 0))\n",
    "#     print(ti.get_addr(loss['link31_re'], 0))\n",
    "#     print(ti.get_addr(loss['link31_im'], 0))\n",
    "#     print(ti.get_addr(loss['link13_re'], 0))\n",
    "#     print(ti.get_addr(loss['link13_im'], 0))\n",
    "# test()\n",
    "\n",
    "\n",
    "@ti.kernel\n",
    "def get_loss():\n",
    "    for i in lisa.single_link_response:\n",
    "        loss['link12_re'][i] = lisa.single_link_response[i]['link12'][0]\n",
    "        loss['link12_im'][i] = lisa.single_link_response[i]['link12'][1]\n",
    "\n",
    "        loss['link21_re'][i] = lisa.single_link_response[i]['link21'][0]\n",
    "        loss['link21_im'][i] = lisa.single_link_response[i]['link21'][1]\n",
    "\n",
    "        loss['link23_re'][i] = lisa.single_link_response[i]['link23'][0]\n",
    "        loss['link23_im'][i] = lisa.single_link_response[i]['link23'][1]\n",
    "\n",
    "        loss['link32_re'][i] = lisa.single_link_response[i]['link32'][0]\n",
    "        loss['link32_im'][i] = lisa.single_link_response[i]['link32'][1]\n",
    "\n",
    "        loss['link31_re'][i] = lisa.single_link_response[i]['link31'][0]\n",
    "        loss['link31_im'][i] = lisa.single_link_response[i]['link31'][1]\n",
    "\n",
    "        loss['link13_re'][i] = lisa.single_link_response[i]['link13'][0]\n",
    "        loss['link13_im'][i] = lisa.single_link_response[i]['link13'][1]\n",
    "\n",
    "get_loss()\n",
    "\n",
    "# print(loss['link12_re'])\n",
    "# print(loss['link12_im'])\n",
    "# print(loss['link21_re'])\n",
    "# print(loss['link21_im'])\n",
    "# print(loss['link23_re'])\n",
    "# print(loss['link23_im'])\n",
    "# print(loss['link32_re'])\n",
    "# print(loss['link32_im'])\n",
    "# print(loss['link31_re'])\n",
    "# print(loss['link31_im'])\n",
    "# print(loss['link13_re'])\n",
    "# print(loss['link13_im'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6f75a0a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "loss_list = list(loss.values())\n",
    "# print(loss_list)\n",
    "# @ti.kernel\n",
    "# def test():\n",
    "#     print(ti.get_addr(loss_list[0], 0)-  ti.get_addr(loss['link12_re'], 0))\n",
    "#     print(ti.get_addr(loss_list[1], 0)-  ti.get_addr(loss['link12_im'], 0))\n",
    "#     print(ti.get_addr(loss_list[2], 0)-  ti.get_addr(loss['link21_re'], 0))\n",
    "#     print(ti.get_addr(loss_list[3], 0)-  ti.get_addr(loss['link21_im'], 0))\n",
    "#     print(ti.get_addr(loss_list[4], 0)-  ti.get_addr(loss['link23_re'], 0))\n",
    "#     print(ti.get_addr(loss_list[5], 0)-  ti.get_addr(loss['link23_im'], 0))\n",
    "#     print(ti.get_addr(loss_list[6], 0)-  ti.get_addr(loss['link32_re'], 0))\n",
    "#     print(ti.get_addr(loss_list[7], 0)-  ti.get_addr(loss['link32_im'], 0))\n",
    "#     print(ti.get_addr(loss_list[8], 0)-  ti.get_addr(loss['link31_re'], 0))\n",
    "#     print(ti.get_addr(loss_list[9], 0)-  ti.get_addr(loss['link31_im'], 0))\n",
    "#     print(ti.get_addr(loss_list[10], 0)- ti.get_addr(loss['link13_re'], 0))\n",
    "#     print(ti.get_addr(loss_list[11], 0)- ti.get_addr(loss['link13_im'], 0))\n",
    "# test()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "223f8ef8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'link12_re': array([-8.49490177e-18,  8.97838709e-18,  1.04649853e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link12_im': array([-4.07607627e-18, -2.12022433e-18,  8.98819846e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_re': array([-8.49493389e-18,  8.97841965e-18,  1.04650619e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_im': array([-4.07608753e-18, -2.12023581e-18,  8.98823266e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_re': array([ 1.22286651e-17, -1.84576347e-17,  3.74647530e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_im': array([ 1.34622121e-17, -2.19153240e-18, -1.85876021e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_re': array([ 1.22286205e-17, -1.84575651e-17,  3.74645995e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_im': array([ 1.34621617e-17, -2.19152322e-18, -1.85875307e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_re': array([-9.89016235e-18, -1.27974159e-17,  3.01154492e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_im': array([ 3.09011604e-17, -2.94919898e-17, -1.03816627e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_re': array([-9.89017769e-18, -1.27973963e-17,  3.01154463e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_im': array([ 3.09011497e-17, -2.94919902e-17, -1.03816423e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with ti.ad.FwdMode(\n",
    "    loss=loss_list,\n",
    "    param=lisa.params.lam,\n",
    "    clear_gradients=True,\n",
    "    ): \n",
    "    lisa.update_input_params(\n",
    "        params['ecliptic_longitude'],\n",
    "        params['ecliptic_latitude'],\n",
    "        params['polarization'],\n",
    "        params['coalescence_time'],\n",
    "    )\n",
    "    lisa.response_model._update_geometry_terms()\n",
    "    lisa.response_model._loop_frequencies(waveform_tiw.waveform_container)\n",
    "    get_loss()\n",
    "\n",
    "dlinks_dlam = {key: loss[key].dual.to_numpy() for key in field_names}\n",
    "display(dlinks_dlam)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "26de196e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'link12_re': array([ 1.74292183e-17, -1.54531410e-17, -6.72871199e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link12_im': array([ 3.49193585e-18,  8.39199199e-18, -1.60499126e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_re': array([ 1.74292849e-17, -1.54531990e-17, -6.72874374e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_im': array([ 3.49194400e-18,  8.39202916e-18, -1.60499757e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_re': array([-1.27180069e-17,  1.57120126e-18,  1.76435171e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_im': array([ 1.23954677e-17, -1.77758035e-17,  3.09839795e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_re': array([-1.27179742e-17,  1.57119864e-18,  1.76434702e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_im': array([ 1.23954336e-17, -1.77757562e-17,  3.09839123e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_re': array([ 2.05466738e-18,  7.04665982e-20, -4.09424760e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_im': array([-2.83442664e-18,  3.81499045e-18, -4.89672838e-19, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_re': array([ 2.05473360e-18,  7.04009315e-20, -4.09427170e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_im': array([-2.83440563e-18,  3.81501909e-18, -4.89742538e-19, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with ti.ad.FwdMode(\n",
    "    loss=loss_list,\n",
    "    param=lisa.params.beta,\n",
    "    clear_gradients=True,\n",
    "    ): \n",
    "    lisa.update_input_params(\n",
    "        params['ecliptic_longitude'],\n",
    "        params['ecliptic_latitude'],\n",
    "        params['polarization'],\n",
    "        params['coalescence_time'],\n",
    "    )\n",
    "    lisa.response_model._update_geometry_terms()\n",
    "    lisa.response_model._loop_frequencies(waveform_tiw.waveform_container)\n",
    "    get_loss()\n",
    "\n",
    "dlinks_dbeta = {key: loss[key].dual.to_numpy() for key in field_names}\n",
    "display(dlinks_dbeta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ce324950",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'link12_re': array([-1.10271623e-17,  7.03944628e-18,  7.36166411e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link12_im': array([ 2.00917615e-18, -8.34250435e-18,  7.69148073e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_re': array([-1.10272051e-17,  7.03947456e-18,  7.36169471e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_im': array([ 2.00918395e-18, -8.34253787e-18,  7.69151271e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_re': array([ 8.57510576e-18, -1.37165243e-17,  3.38739088e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_im': array([ 1.03804313e-17, -2.23595995e-18, -1.39027787e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_re': array([ 8.57507399e-18, -1.37164724e-17,  3.38737782e-18, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_im': array([ 1.03803928e-17, -2.23595150e-18, -1.39027251e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_re': array([-1.09757867e-17, -1.50925982e-17,  3.45831495e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_im': array([ 3.53884296e-17, -3.36857897e-17, -1.24831449e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_re': array([-1.09757848e-17, -1.50925946e-17,  3.45831391e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_im': array([ 3.53884234e-17, -3.36857817e-17, -1.24831411e-17, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with ti.ad.FwdMode(\n",
    "    loss=loss_list,\n",
    "    param=lisa.params.psi,\n",
    "    clear_gradients=True,\n",
    "    ): \n",
    "    lisa.update_input_params(\n",
    "        params['ecliptic_longitude'],\n",
    "        params['ecliptic_latitude'],\n",
    "        params['polarization'],\n",
    "        params['coalescence_time'],\n",
    "    )\n",
    "    lisa.response_model._update_geometry_terms()\n",
    "    lisa.response_model._loop_frequencies(waveform_tiw.waveform_container)\n",
    "    get_loss()\n",
    "\n",
    "dlinks_dpsi = {key: loss[key].dual.to_numpy() for key in field_names}\n",
    "display(dlinks_dpsi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b4b97d8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'link12_re': array([ 3.47582264e-21, -2.24881505e-21, -2.39497177e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link12_im': array([-6.39347795e-22,  2.67370770e-21, -2.49479841e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_re': array([ 3.47583612e-21, -2.24882409e-21, -2.39498173e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link21_im': array([-6.39350273e-22,  2.67371844e-21, -2.49480878e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_re': array([-2.70230965e-21,  4.40593580e-21, -1.12289457e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link23_im': array([-3.29786288e-21,  7.36201860e-22,  4.53049074e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_re': array([-2.70229964e-21,  4.40591915e-21, -1.12289024e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link32_im': array([-3.29785066e-21,  7.36199080e-22,  4.53047327e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_re': array([ 3.46233528e-21,  4.88221890e-21, -1.13029852e-20, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link31_im': array([-1.12380909e-20,  1.08451503e-20,  4.10133955e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_re': array([ 3.46233467e-21,  4.88221775e-21, -1.13029818e-20, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,)),\n",
       " 'link13_im': array([-1.12380889e-20,  1.08451477e-20,  4.10133833e-21, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with ti.ad.FwdMode(\n",
    "    loss=loss_list,\n",
    "    param=lisa.params.tc,\n",
    "    clear_gradients=True,\n",
    "    ): \n",
    "    lisa.update_input_params(\n",
    "        params['ecliptic_longitude'],\n",
    "        params['ecliptic_latitude'],\n",
    "        params['polarization'],\n",
    "        params['coalescence_time'],\n",
    "    )\n",
    "    lisa.response_model._update_geometry_terms()\n",
    "    lisa.response_model._loop_frequencies(waveform_tiw.waveform_container)\n",
    "    get_loss()\n",
    "\n",
    "dlinks_dtc = {key: loss[key].dual.to_numpy() for key in field_names}\n",
    "display(dlinks_dtc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4be86cd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "links_name = [\n",
    "    'link12', 'link21', 'link23', 'link32', 'link31', 'link13'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f3bfe678",
   "metadata": {},
   "outputs": [],
   "source": [
    "stacked_dlinks_dlam = {\n",
    "    key: np.stack((dlinks_dlam[f'{key}_re'], dlinks_dlam[f'{key}_im']), axis=-1) for key in links_name\n",
    "}\n",
    "stacked_dlinks_dbeta = {\n",
    "    key: np.stack((dlinks_dbeta[f'{key}_re'], dlinks_dbeta[f'{key}_im']), axis=-1) for key in links_name\n",
    "}\n",
    "stacked_dlinks_dpsi = {\n",
    "    key: np.stack((dlinks_dpsi[f'{key}_re'], dlinks_dpsi[f'{key}_im']), axis=-1) for key in links_name\n",
    "}\n",
    "stacked_dlinks_dtc = {\n",
    "    key: np.stack((dlinks_dtc[f'{key}_re'], dlinks_dtc[f'{key}_im']), axis=-1) for key in links_name\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3b370e93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'A': array([-7.10068803e-21+1.66449185e-20j, -5.56315182e-21-1.76462038e-20j,\n",
       "         1.84627577e-20-4.08498861e-21j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'E': array([-1.14813652e-20-9.35828789e-21j,  1.54238995e-20-2.49107373e-22j,\n",
       "        -1.25955113e-21+1.59975704e-20j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'T': array([-4.79289871e-29+6.33746301e-29j, -3.54035743e-30-8.63423893e-29j,\n",
       "         9.36272322e-29+6.03547618e-30j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'A': array([-3.14946505e-22-6.78548779e-21j,  4.65475384e-21+5.43661196e-21j,\n",
       "        -6.31036552e-21+4.12401224e-21j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'E': array([ 1.63555490e-20-5.16059499e-21j, -9.29442891e-21+1.48896665e-20j,\n",
       "        -1.43237935e-20-1.08193201e-20j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'T': array([-5.42725447e-30-1.12252591e-28j,  8.19435763e-29+8.81232541e-29j,\n",
       "        -1.02078427e-28+7.82089273e-29j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'A': array([-5.80158628e-21+1.85021096e-20j, -7.97536192e-21-1.82895613e-20j,\n",
       "         1.94104900e-20-6.64176125e-21j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'E': array([-1.07773430e-20-4.36898635e-21j,  1.16035954e-20-3.65158227e-21j,\n",
       "         2.53928108e-21+1.24604035e-20j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'T': array([-2.40736848e-29+4.97428060e-29j, -1.32239375e-29-5.91944225e-29j,\n",
       "         6.62004769e-29-6.53900078e-30j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'A': array([ 1.82941921e-24-5.87450826e-24j,  2.58026074e-24+5.88673999e-24j,\n",
       "        -6.34222092e-24+2.18316638e-24j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'E': array([ 3.39694478e-24+1.38796247e-24j, -3.72054353e-24+1.15931654e-24j,\n",
       "        -8.14018032e-25-4.05398969e-24j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,)),\n",
       " 'T': array([ 7.64444793e-33-1.56719091e-32j,  4.17530253e-33+1.89786331e-32j,\n",
       "        -2.15377567e-32+2.05440990e-33j, ...,\n",
       "         0.00000000e+00+0.00000000e+00j,  0.00000000e+00+0.00000000e+00j,\n",
       "         0.00000000e+00+0.00000000e+00j], shape=(32703,))}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lisa.single_link_response.from_numpy(stacked_dlinks_dlam)\n",
    "lisa.tdi_combination.update_tdi_response()\n",
    "dtdi_dlam = lisa.tdi_response_numpy\n",
    "\n",
    "lisa.single_link_response.from_numpy(stacked_dlinks_dbeta)\n",
    "lisa.tdi_combination.update_tdi_response()\n",
    "dtdi_dbeta = lisa.tdi_response_numpy\n",
    "\n",
    "lisa.single_link_response.from_numpy(stacked_dlinks_dpsi)\n",
    "lisa.tdi_combination.update_tdi_response()\n",
    "dtdi_dpsi = lisa.tdi_response_numpy\n",
    "\n",
    "lisa.single_link_response.from_numpy(stacked_dlinks_dtc)\n",
    "lisa.tdi_combination.update_tdi_response()\n",
    "dtdi_dtc = lisa.tdi_response_numpy\n",
    "\n",
    "display(dtdi_dlam)\n",
    "display(dtdi_dbeta)\n",
    "display(dtdi_dpsi)\n",
    "display(dtdi_dtc)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "76b1e933",
   "metadata": {},
   "outputs": [],
   "source": [
    "tdi_data.set_fd_noise_power_density_from_model(\"LISA_SciRDv1\", tdi_generation=tdi_gen)\n",
    "psds = lisa.tdi_data.fd_noise_power_density_numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fb218da4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fisher_matrix(derivative_data, psd_data, df):\n",
    "    size = len(derivative_data)\n",
    "    fm = np.zeros((size, size))\n",
    "    for i in range(size):\n",
    "        for j in range(size):\n",
    "            inner_prod = np.vdot(derivative_data[i], derivative_data[j]/psd_data).real\n",
    "            inner_prod *= 4*df\n",
    "            fm[i, j] = inner_prod\n",
    "    return fm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "96bffb20",
   "metadata": {},
   "outputs": [],
   "source": [
    "fm_A = get_fisher_matrix(\n",
    "    [dtdi_dlam['A'], dtdi_dbeta['A'], dtdi_dpsi['A'], dtdi_dtc['A']], \n",
    "    psds['A'], \n",
    "    tdi_data.data_info.delta_frequency,\n",
    "    )\n",
    "fm_E = get_fisher_matrix(\n",
    "    [dtdi_dlam['E'], dtdi_dbeta['E'], dtdi_dpsi['E'], dtdi_dtc['E']], \n",
    "    psds['E'], \n",
    "    tdi_data.data_info.delta_frequency,\n",
    "    )\n",
    "fm_T = get_fisher_matrix(\n",
    "    [dtdi_dlam['T'], dtdi_dbeta['T'], dtdi_dpsi['T'], dtdi_dtc['T']], \n",
    "    psds['T'], \n",
    "    tdi_data.data_info.delta_frequency,\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "106201b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 2.26317548e+07  1.01433958e+07 -1.08414299e+07  1.87855891e+05]\n",
      " [ 1.01433958e+07  6.30512570e+06 -6.48278949e+06  9.30059279e+04]\n",
      " [-1.08414299e+07 -6.48278949e+06  7.71973533e+06 -1.05111160e+05]\n",
      " [ 1.87855891e+05  9.30059279e+04 -1.05111160e+05  1.66041851e+03]]\n",
      "[[ 3.49566764e-06 -9.50811498e-07 -3.97684000e-06 -5.93983332e-04]\n",
      " [-9.50811498e-07  1.56888845e-06  1.81335752e-06  1.34486412e-04]\n",
      " [-3.97684000e-06  1.81335752e-06  5.87109893e-06  7.20021991e-04]\n",
      " [-5.93983332e-04  1.34486412e-04  7.20021991e-04  1.05851374e-01]]\n"
     ]
    }
   ],
   "source": [
    "fm_comb_AET = fm_A + fm_E + fm_T\n",
    "print(fm_comb_AET)\n",
    "cov_AET = np.linalg.inv(fm_comb_AET)\n",
    "print(cov_AET)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "548e0202",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 2.26313505e+07  1.01431890e+07 -1.08412685e+07  1.87852599e+05]\n",
      " [ 1.01431890e+07  6.30500845e+06 -6.48270061e+06  9.30042086e+04]\n",
      " [-1.08412685e+07 -6.48270061e+06  7.71966395e+06 -1.05109804e+05]\n",
      " [ 1.87852599e+05  9.30042086e+04 -1.05109804e+05  1.66039146e+03]]\n",
      "[[ 3.49569527e-06 -9.50840551e-07 -3.97689180e-06 -5.93988594e-04]\n",
      " [-9.50840551e-07  1.56892288e-06  1.81341322e-06  1.34491746e-04]\n",
      " [-3.97689180e-06  1.81341322e-06  5.87120082e-06  7.20032112e-04]\n",
      " [-5.93988594e-04  1.34491746e-04  7.20032112e-04  1.05852410e-01]]\n"
     ]
    }
   ],
   "source": [
    "fm_comb_AE = fm_A + fm_E\n",
    "print(fm_comb_AE)\n",
    "cov_AE = np.linalg.inv(fm_comb_AE)\n",
    "print(cov_AE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "43a43288",
   "metadata": {},
   "outputs": [],
   "source": [
    "samples = np.random.multivariate_normal(\n",
    "    [params['ecliptic_longitude'], \n",
    "     params['ecliptic_latitude'], \n",
    "     params['polarization'], \n",
    "     params['coalescence_time']], \n",
    "    cov_AET, \n",
    "    size=10000)\n",
    "\n",
    "samples_pd = pd.DataFrame(\n",
    "    dict(ecliptic_longitude=samples[:,0], \n",
    "         ecliptic_latitude=samples[:,1], \n",
    "         polarization=samples[:,2], \n",
    "         coalescence_time=samples[:,3], \n",
    "         )\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "12737a28",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib \n",
    "params = {\n",
    "    'font.family': 'serif',\n",
    "    'font.serif': 'Computer Modern',\n",
    "    'legend.fontsize': 28,\n",
    "    'text.usetex': True,\n",
    "    }\n",
    "matplotlib.rcParams.update(params)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "48ceb04c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8LplqXlcQb+nrCdR49Kn6WZJjZGglCncSWFNGts1zSSiWau5HN2Ga/JK3AK5vIoGhmW0TlomIiEKcBAUJWhIK5A92qbC2dJqtPKas7WuLLUB84WzcuHF+3V/CrZxk/asEEl+FWYJV7aAhIUTCp4QlGaOGmuzIfeQ1S9W2rmqgfK+ESV8FtHZw9XU+lsepXamsScbUt59rXeR6qdBK4KqLPL9UkesK4fL65b3zbRvU0uDlT3Xa9374grjwBVR/fg5b+noCPR59ArhWO9h0Xt/HDxQySkpKEB8fj+LiYsTFxaHDcJQDT2pVR6m0rnxgeqtUWhdk5eHNBR/hc8sDwM0r2i60iqJcwFaAJVvysWjpcjxvfikgx5Bfase4J5aqSuvmdl5p7bD/PojCWGVlpfojrHfv3oiI0Pas9henB7eP6cFS4fJNdawrRNWsakk4kBDXlOqq7/Eb01CVLRCkmivBwzfd1F++KqCMjZzqm0rrm+4q96lvuq7vGPypyPlCUn1j0lh1Um6TANzQ8/iOuXbkkCArAUy+v6GpyvKzG6j3zd/H8h2zhHm5f82Kt2+MZZukmsGypa+nNcZjWiPvbzB+pzcXGzERtSWpqKaMRJE1HTu8qRx7IqJGyB9oMrWVp+aPQbADa00SAqT6V/skAcx3amrgq0nCk4Sjmif5g10eM1BrVhviq2o197nk+32VtLr4An9D1bOmVOKkUlqzeldbY69Dvrehtaq+Y67rgwpf5bux4/RVGOur1rYmCad1dYH2hdlAvp7WGA+r1erXhznhgKGVOozMPUWqypqxu3384yUiIiL49Ye7hOBly5a1+nAFIiC0ZDq0BBlfAyF/+O5Xew2nvySMynTmxgJU7VAsU27l+eS1NhaMfdOmfQ2q2po/H6C09PW09ngUtYPgytBKHSawznh5Fe6dvw4LMnKCfThERETUxiQQSIOhttCS52nJfrS+aaxNqfT67itrYJvKt65WQqlMFZZzqU7WVnu6q686689r9d2nvu2KQkFLX09rjUdi1c9hWzQga23h1UqOqJl2F9ggk6Nmju+N8WlWDPHGAZ9xOImIiDqShsKcVCibUqWsi3QCbux5WpNv2nBTQrPcVypxzalkShVSApd0vPVNWfVVXeVDAhnLurbo8R2ndMltaDp0zcAVjGqhvx8gtPT1tNZ4WIP0c9gaGFopdOhNsJ/2MBauy8OY2FTVOCLQJLDOHJ0C5B1GeyJjdeKArjB4nbD3exgW2d9Wbwr2YREREYUUCVD1kQphSyuxSUlJQZ2O2ZI1tc2txkkwlXXDElYlwMo4yuuXACYnuV6mZtec9uw7Tgm9DXVBrktjW+iIhhpVNUVT9sNt7usJxPe352nBPgytFDqMZlgm/w5XTgauDPaxhJmYCCPev15b4wCcEOSjISIiCk0NrU+USmOgtsUJ1nRMX+OdpoQV37G2NLBLgyBfEyF5fgmvsjWPBFdZhykh0le5bM5x1gzJ/oTWttSS1xOI72/t9zYUMLRSh5GCI7AWZWtV1iPbgn04REREFEJkjWBLw47v+4NV4ZLnl5DYlNDsO9aG9mOtj0wLrr0dTM3mV3KSDwKk0ZBUEGUbnuYep4/vMUJJS15PIL6/I0wTZiMmCh0eN5x71+DrJV/jvxm5cLg8AXvoSFsellruxbSVM4BXJwMf3QSYooAobRpPuJOxej8zT42bjCH2r1XjSURERP4JRND0hYNgVVp927M0Voms6zU3Z5sh6RzcGAmrMi41Gwf5jlOCWnvQ0tfTWuNRVLU3cnvA0Eqhw1UJ0+tTcOaqWXjkowwUVzgD9tAWRyGidHasHj0XuHmFdro9Q9s3tR2Qsbrvw3Vq3GQMMe90NZ5ERETUOFl3GYgppb7HCMR6yuaQ6bkSUiT8+BPCfZ1+JbA29/XX1S24tlmzZtV5nBKu/f2woLEGRcHU0tfTWuOxJgCzB0IFQyt1KCUxfYCUkdqpnQRWIiIiahmpBgYytPpb6Qw0CT7z5s1TlxvbO1XImlPh+57m8KdxkFSex44dW+dx+rOOWF6Lb3/SUNTS19Na41FUVHTcuIczhlYiIiIialW+6lFrrfVs7uPK902bNk2FzOas6ayvUVAwp73WXEva0PRdWWcqxylrUuubQupvtbahaquvKVPtyqDvOCWANfT98t5IV2Jfk6e2+Blszs9rS19PoMcjq+pnUH6+2wOGViIiIiJqNTWDk0xXDHQVsvbjN8YXoiTUJSQkVAeEmluytIQvBDfF/Pnzqy83FFhqvtaGKqkSRGfPnq0aJdV1P3ntUmWV+zW0ltV3XL4tbOprjCSnugKyjMOUKVNUNbau8fUdp4yZhOi6Xq98b13Nnpqq5hg3thb3gw8+qD5+f6Y/B+r1BHI81lT9W2jJvsOhROf1er3BPgg6XklJCeLj41FcXIy4uLiOMzyOcuDJFHVxcOXrWPnAdCTHWgLy0EuWL1FNmJacshDTTg/+J04LsvLw5oKP8LnlAW19rUxXboH8UjvGPbEUkajE5ojrtSvvzwPM0WhvOuy/D6IwVllZiZycHPTu3RsRERHBPhxqIzqdrsHb5Y9pqRi11uM3Vc0tWVrCt8WLvLbGAoOEk/pCkVTSfJ1ypUpZX0iV0FlfiJHQJSFHAoxv2xOZqiuNf3zrKOsiYbe+YFfzdcnx+95DOT5f1bbmFisSkBsb19rH6TsuOc7mNIjy97XUft/lfWuoSu5vbGrp6wnEeMycOVO9ltZYXx2M3+kMrSGow/5R3kFDqxxTkTUdaUlRGNereR3eGFqJKJQxtFJHI1ONJVz4s96TqDUkJCTgvvvuU5Xb9vA7ndODiYJAAqrPc0u24t756zDj5VXI3BOcfd2IiIgocKQy6s92MEStIauqe3RLq9ShhKGVQofeBMek2Xg/+moM6dUVkSYD2iupqM6dMUJd/vOJJtwz1IFUHMHuAluzHk/GakRasho3GUNM/pMaTyIiImp7MvW2qeshiQLlqaeeUlO428t2N8IY7AMgqmY0wzztAVw+Dbi8AwxLet80wBSFCVmzMUH+B2exYLntCwDaFOmmiIkw4pPfjq/6alLAj5WIiIj8J2sQfWtS20sjHAoPRUVFqsq/du1atCcMrdS+FeUCtgLElQVnv7QGyT6xt2eo41u9ZrUKrxZHYbCPioiIiAJA1rPKukKpuLaniheFfpV1xowZAeuGHSoYWil0eDxwHdqMH3KKUBbXF2cM6gyjUd+ywPrieMBpU5VMm9cCuzkBIRdcrT1QEpPfoodxuTxYvPUI4PXgjKQCGA16oNNAQM8VAERERMGqtkpwlfWtLemSTNSUKqt0cW5vVVbBv2gpdLgqYHxlIk5ZfA7+8M4qFFY4W/Z4tgIVWHHxPNWhd6r9WVRENX3qbTiQsbrt7Uw1bjKGeOkENZ5EREQUPL7OrWzKRG1h5syZmDdvXrus7LPSSu1fpwEocnVGHhzBPhIiIiLqYGTvUtn/U6ZrtscwQaFh7ty56uerPXUMromVViIiIiKiVpwmLNODZZqwTN8kCrSlS5ciMzNTNf5qrxhaqd1bsiUfGbv5PwkiIiIKDqmASaCQ9YZEgbZkyRJV0W/POD2Y2pXMPUXVe53ac/fjKgDPLdmKbK8DXgBpSVHBPkQiIiLqoMHVt8aVKJCeeeaZdj+gDK3UrgLrjJdXQVf1dbouB1dZgMtP6A1Lj1EqsI7rZQ3yURIRERERUVMwtFK7IRVWCawzx/fG+DQrrEVmYCVw1bhUIKV9dg0mIiIiImrvGFopdOhNcIy/A59sOIDeCcmINBma9TASWGeOTgHyDqvQ2hHIWA1ISYTR64Sj/x0wG3VqPImIiIiIwh1DK4UOoxnmc57AzHOAmcE+ljATE2HE4rtOrPrqlCAfDRERERFR4LB7MBEREREREYUsVlopdHg8cB3diw0HSmCPTsW4ngkwGvm5ij9cLg8yc4sBrwfj4kphNOiA+B6AnuNHREREROGNoZVCh6sCxn+OwGgAgytfx8oHpiM51oKOvnWPP12PCyucuPyVHxCJSmyOuF678v48wBzdFodLRERERNRqGFqJQnzrHtlfduGtk7hdDxERERF1SJw7SBTCW/fISS77qq5ERERERB0NQytRiJKte+RERERERNSRMbQSERERERFRyOKaVmpXUnAE1qJsIO8wcGRbsA+HiIiIiIhaiKGV2o1IWx6WWu5F1Eo7sLLqSlMUEJUU5CMjIiIiIqLmYmil0KE3wjH6enz+yyGkxiYiwtS02esWRyGidHasHj0XE8ZO0K6UwGrtgXARV7ZLnafrchBp64KKqBS/vk/GqlfneJi8UXD0vx5mg16NJxERERFRuONftRQ6jBaYz/87LjofuKgFD1MS0wdIGYlwYjcnwOa1YELWbPX1NAvg+iYSX522yK/vj40wYcXvT6r66rRWPFIiIiIiorbF0EoUAqSiOtX+LGYNjVNf52zKwPPml1T1mIiIiIioI2NopdDh9cJTlo+cggq4IxLRr3M09PqO0eA6LSkK+9EJz23Uvk7XpTbp+z0eD3bk29QY9ouu0MZNpkbrZJdXIiIiIqLwxdBKocNpg/6v/dEXwODK17HygelIjrWgIxjXy4qFt07C7gKb+nqINw74zP/vLyh34oy/r0AkKrE54nrtyvvzAHN0Kx0xEREREVHbYGglCqHgKidFtuwhIiIKcwkJCQF7rJycHFitVf+fbGWvvvoqlixZgl27dqGoqEhdt3PnzjZ5biL6NYZWIiIiImoVEjSPHj2KpUuX4pZbblHXjR49GgsWLEBiYmKd3yP3l7AooVHCoy80ynXyvbXJ7YEOs3Jsffr0QVZWlnpeuUxEwdMxFgwSERERUZuTMCmB7+abb66+buzYseo6ua2uk9w2depUPPPMMygsLFSXfWG2tmnTpqlq7pw5cwJ63DNmzFDPL+GaiIKPoZWIiIiIWl1zq6G+4CgVz9oVVqngCqnItgZWWIlCA0MrEREREYV02JVKbe01pXL97Nmz1blURYmo/WJoJSIiIqKQJuthfWtba/JNIa45/ZiI2h82YqLQoTfCOfQyfL35MJKsVkSY+JmKv2SsuiTEwuSNgLPfZTAZ9Go8iYiI2gNpwFR7ejARdRz8q5ZCh9EC04xXMB1QJ/JfbIQJq+ecUvXVFA4dEREREbUbLGURERERUciYO3dundezKRJRx8XQSqHD64WnshT5R48iv6QSHo8n2EcUNmSs8kvt2rhVlgKOcjWeRERE4Ub2Z63LK6+80ubHQkShgdODKXQ4bdA/3R3JAAZXvo6VD0xHcqwl2EcVFgrKnRj3xFJEohKbI67Xrrw/DzBHB/vQiIiI/FZXs6W6yFY3EmJlnavve2p3F659f9k6p2/fvigoKKj+HtnnVfZklfP6wnJtWVlZ1QF6zZo16rHkMe677z6/t/XxHb98r3yPvA6pJMtjyPrduqrPcnyyV63cV/au9W0FJLfJa/KNhTwuq9LU3jC0EoWwuLJdSNc5YS0yA0VuwNoj2IdERNS2ZNaI08ZRbwlTFKDThcUYzp8/36/7JSYmqmAmAVLCWkNhUQKpnOqq1ErgkyDrb5Mn39Tlmo8l3ztmzBi1V2xOTk6jwXXmzJnquCV01gyo8v3yOPLYtbshy2uV+8p9agZ7eSxf0J0zZ446Pum07G8AJwoXDK0U9jL3FGF3gQ3788owDe1EVJL6I2NC1mx8LsXmlQB+jAJuz2BwJaKORQLrkynBPorwFgYzbySISSCT4CVVxMZISJOTBDQJnfWRx/Pt51oXuV4qtPLcjVm4cGH1nrG1A6VsvSPH8tRTTzW4Z6yEZ6nO1hVu5XFlHORxfF/7SCXXVxGWk/AF1Loqs0TtDde0UtgH1hkvr8K989dhSfZ+dV1KfATCnlRUb8/AklMW4lz7E1g9eq72h5utINhHRkRE1CISEHU63XGnhIQEFTCbSiqujT2XL+TVx5/nlWm5dVVAfXxBW4JtQ8ci04IbmkbsC9f1HZNv2q+E28zMzOMCvoRlqbD6pg0TtSestFJYkwqrTHiaOb43zrCaVUUyvVss2gVrDxRZDcj2OlASYw720RARBW9qq1QKqWVjGEIk+NWeqitTbCXwNTW4NjYVV8KdBLn6wqYvCDa2BrRmBbS+xxANTTP2vbaGjsV3uwRcOdV3X98a3dr8qVIThSOGVmoXxqdZMa2rQ5tGS0RE7YesxQzxqa3UchL6fFXGQK7HlMeVMNxQABQNBVKflkzDlam8EnzlMRoL2rKuVaxdu7bB+8l0YaKOgtODiYiIiCgkNFaFbCrf+lIJpTIFWc6lSllbfWtea2pJR15fEPfnMXz3kbWvRKRhpZVCh84A58Dz8e22I4iLiYHZwM9U/CVjlRAbBbPXCGff82Ey6NR4EhERhRN/t4zxl1QjJTBKl11fsydf0yWpesp02qZsVdNcvmnD0jW4saqurJ9tbPsfbmlDHQ1DK4UOUwRMl7+tOgA3pQtwCo7AWpQNGAvRUcVHmbDugdOqvjozyEdDRETUfI01TmoqCaaFhYUqrEqAlUqrBEIJkHKS65ctW9aqXXh9oVVCdEPdhf3V2iGbKNSwlEVhLdKWh6WWezFt5Qzgo5u0ZhOyXQwRERGFJX+m6jZ36rE0L5IAKyffPqkSYGUdqb97tbYkZDZUPSWi+jG0UlizOAoRpbNrW8LcvIL7mBIREVE1mRZcX4iUqqc0O/KF5EBUQBubzuub+ktETcPQSqHDUQ48HK9Og//0IfJL7X5/a0lMHyBlpLa/aQckY5X2p8/VuPnGUI0nERFRB9bQvqk+ElYlxLZm46NLL71Unct0ZCJqOoZWCguZe4qwICuv+iRfExERETWmrm7Btc2aNatVB1KmJkswlinI/k4R9mcbHqKOgo2YKORJQJ3x8iroalznlU9Pb52EDufINu1c1u120KoyERFRU0glVZoxNUSm7Y4dO7bVBlYC67x589R05Tlz5uCVV15p8P7SHMq3XysRsdJKYWB3gU0F1pnje+PZWaPUuXw9f20esvPK0BHYzQlakylpNvXqZODF8UBRbrAPi4iIyG++CmMg13X6U7WUSmtD1VZ5DLm9tSubsoZWThJIGzoeqcZKl+O69qz1vV42dKKOhtODKWyMT7Ni5ugUzBqToiqtCzJysCR7v7otJT4C7VlFVIrWZEqaTV08D3DaAFtBsA+LiIioyWtLJbAFam3n/Pnz1blvC5u6SFVTTnWtb5WAOGXKFFWNrWvLG9/j+467PjUf27cPbF2kY7E0fpJtfebOnVvn48ixyP3q8sEHH1Qftz/TnonaC04PprAzrpdVTQ2WCqy1yAysBNK7xaLdk+nAnBJMRERhRKerubhH49tixkdCWlO3uZFptrVDqO8xpUrpmw4s51KxlJOESQmLMlU3MTGx+vskIPq6+/rI/WqHQt/+sfJYvum9Up2tHVLlOjlJVbWu8CmvV26XczlmORbfljjSsKmuqcNyv9qhvOZ+tl6vfJxP1H4xtFLYBlc5Ie+wCq1EREQUelorTNVXiaxNAqyPL7w29fsa4qviNpWE5KZ8n2zNQ9SRMbRS6NAZ4OwzFT/uKkRkZDTMBs5e95eMVUxUJMxeA5y9p8IkY6cztOrbRURERETUFhhaKXSYImC65kOcIvuYBftYwkx8lAkb/3x61VdnBfloiIiIiIgCh6UsIiIiIiIiClkMrURERERERBSyOD2YQoejHN65/VDhdGO0/WV898B0JMdagn1UYSG/1I6xTyxFJCqxOeYOqGaN9+4AzNHBPjQiIiIiohZhpZVCis5lQ5TOjl83yCeRuacIS7bkq8tyLl9Xj53v5LJp+7gSEREREbUDrLQShYGM3UXILazE80s2Y6guB9MswHNLtmLjYofaszYtMTLYh0hERERE1CoYWin8FOUCtgLt8pFtaM/SkqIgO9wtyMipvu7yE3oD64Bp6anI3gjsLrAxtBIRERFRu8XQSuEXWF8cf/z0V1MUEJWE9mhcL6uqpEow9YXYcabdKrSmp8QAGx3BPkQiIiIiolbF0ErhRSqsElgvngd0GqBdJ4HV2gPtlQRXOVXLC+bREBERERG1LYZWCk8SWFNGoiOLK9uFdJ0T1iIz9CV9gn04REREREStgqGVQodOD2ePicjaWwSTxQKjgT2E6ySVZVMUJmTNxueyI9BKwPtjFNIsf8VRxKkxNOn1ajyJiIiIiMIdQyuFDlMkTDd8iQkANgT7WEKZTIW+PQNLsraoDsJ/PtGkAuy3twypqj5PD/YREhEREREFDEMrhbxIWx7SdTlqGiyMhcE+nNBg7YEiqwHZXgdKYszBPhoiIiIiolbD0EqhrSgXZ30zHdMtFWoabHvvFkxE1J55vbKJFxERhTNvEH6XM7RS6HCUw/P3YSi0OTDJ/g9898C5SLYVwOiuwN2O2zB96umYNii53XcLbq5zX1iFnd5d2JTwR+hlOfA9vwDm6GAfFhERDAaDGgW3283RICIKc+6q3+W+3+1tgaGVQoq+ogBJOkCH4z/B2eFNRZE1HUhJCdqxhT6vGjcZQyKiUCJ/2Oj1elRUVCAmJibYh0NERC0gv8vld3pbhla2F6WQ9XNuMZZsyQ/2YRARUQvJHzdxcXEoLi7mFGEiojCfGlxUVKR+p8vv9rbC0Eoh68a3MlV3XJ+0pKigHg8RETVffHw8nE4nCgvZUI+IKFwVFhbC5XLBarW26fMytFLIkmWZ09JT1eW5M0ZgXK+2/cdBRESBExkZiYSEBBw6dAiHDx9mxZWIKMwqrIcPH1a/w+V3eURERJs+P9e0UkhLT4kBdgDp3WKDfShERNQCOp0OXbp0gclkUn/4yKf10dHRao2rXCfTzOQ+REQUGiHV4/GoGTJlZWUoLy9XX3fu3BmJiYlt/vuaoZVCxtq9xRhT42tpxZQS37af4hARUeuRP3KSkpJUWC0tLVV/CB04cIBDTkQU4jNlEhMTERsb2+YVVh+GVgoZuwsrYfT0UZe9ehPeuGY80uP2B/uwwobRYIQeZri6joRR9rzRcfY/EYUm+aNHTsnJyWrrBDnJJ/hERBQ69FUdgtuyS3B9GFopZHgMEbjA8TienTUKW/q4Adt+4Mi2YB9W2PjkthOAlJEAzgv2oRAR+S1U/iAiIqLQxdBKISfSlge8eB7gtGlXmKKAqKRgHxYREREREQUBQyuFHIujUAusF88DOg3QAqu1R7APi4iIiIiIgoChlUKGwVWB7y13wbTCpfa7KYruDaua7kr+OPefP2Cndzeykx+EQTq63b4aMHNvWyIiIiIKbwytFEK86K47cuwraR9MfuuHXFhQCUNJbvV4EhERERGFO4ZWojCXcdiAU/UReN780vE3FO8DkgcG67CIiIiIiAKCoZUoTKUlRala6ryfK/A55iJBVwoLHPjI8oi6fdOuvRjC0EpEREREYY6hlShMjetlxcJbJ2F3gQ2llU48+ulGRKKy+vbyvC1AXjIbWRERERFRWGNoJQrz4Cqn/FK7Cq3H3bb+QWB91ZZBt2ewAzMRERERhSV9sA+AiFrHsknvaNsGyfZBtgIOMxERERGFJVZaKYTosM2TCguc6KU/DNm1hfyj1+mgMxjUP+nC6L7IL61EcfwQoFMph5CIiIiIwhorrRQy3MZInOF4FttO1brgWiNNwT6ksJEUY0bOE2dh8xMXYOmURWocZTyJiIiIiMIdQysRERERERGFLE4PptBQlAtr0Rak63IQV8YKKxERERERaRhaKfiKcoEXx2Oa04ZpFgBZgM1rhh1xSAj2sYWJgjIHxj61HBGw4wfrI1hsrsRG12fBPiwiIiIiohbj9GAKPuls67Qhc8Tj1VdNtz8BV2xqUA8rnHi8XnjdbsDtQkL5TgzQ7wfgDfZhERERERG1GEMrhYySmLTqyweQFNRjISIiIiKi0MDQSkRERERERCGLoZWIiIiIiIhCFkMrUTu1Zm8xlmzJV5ezD5QG+3CIiIiIiJqFoZWonfrfmt14bslWdXn2wvXI3FMU7EMiIiIiImoybnlDIUSHfd5OquetV2eAXqcL9gGFDTVWOj28MMAd1wMujxdPnDMSsWVxwErtPrsLbBjXyxrsQyUiIiIiahKGVgre3qyy1Y04sk2deQwWnGT/B56dNQpbRqfwnWmCpBgzdj91dtVXF8IA4GK5mFdaHVqJiIiIiMIRQysFJ7C+OF7tzVrNFAW7OQHAIb4jRERERERUjaGV2lz2zt1Id9qwevRcxKQOQXq3WCAqCRW7pD7I0Noa+un2w1qUDeQdVmMNa49WeR4iIiIiokBjaKU2Jc2AHl64Hp9bgEd/dGKjtwQLbx2GcVYr9O5d+MT8IPAxkP7Ro/j+/jOREGXmO+SHQpsD4578FhbYsb77X2DU64DrvlQB1WWIxPPml4CVctKq2rg9g8GViIiIiMICuwdTm5JmQD7T0lOhq3GdzuvBCP0udfK4HHC5pSUT+UPGyuVyqnEzHvwZyFsHeD0qmH512iKca38CS05ZCFw8T5uW7VtPTEREREQU4lhppbZTlAtr0RY1VVWkp8QAGx3I2K1txbJub7HWPIgCqiIqBdne3iiypgOdDnN0iYiIiCisMLRSmzZfmua0YZoZaspq5y4p8GI3FmTkYEEGEIlKPBnBN6S1yIcD1qJ8TOMQExEREVEYYWiltiHTUauaL8la1lvPPQHT09Ox8NbU6unBBpcN+IJvSKClJUWpvW/lw4FNuhxMswA7t6xDX98d2JiJiIiIiEIYQyu1qZKYPsj2OtSUVTGul1WdFEc5Q2srkPFdeOsk9eHAtm2RsG22oO/Ke47t38rGTEREREQUwtiIiaiDBNeZo1MwYMAgTLU/qzVlunkFGzMRERERUchjpZVCiicySW3f4lV9hakpZMzkJGMoO97UJw+dtKZMKVq1m4iIiIgolDG0UugwR0M/ZxeSAGwJ9rGEmeRYC/Y8fU7VV+zBTERERETtB6cHU5vIPlCqneeVccSJiIiIiMhvDK3U6jL3FGH2wvXq8pLs/aqTrXS0JSIiIiIiagynB1Or821pI+6ZNhDWvuOOdQyuyVkB51sXI2tvEW7CA1gx5wwkRJn5DvlB1gGf8MwKWGDH2p4vwqTXA1ctBEyR/o3fkW3aObe/ISIiIqIQw9BKbWraoGQgpY7AKrwemHJ/wAQd4Ky0w+WWmiz5Q8bKbndAD7saQ9941idjd5E6H2AxYYRsefPRTdoN3P6GiIiIiEIMQyu1nqJcwFYAa1E++un2c6RDgEzLlo8CFmTkYEGGdBwGHjx5IdIibYgr24UJWbPVewZrj2AfKhERERGRwtBKrRdYXxwPOG2YJhVWM+AyRMIo008paGRa9sJbJ6kp27mFlXh+yWY88Z1WdU3XOfG5BXgncz8sPTqrgFvnNG4iIiIiojbE0EqtQ6p1Thtw8TwsOZKA55Zsxa3nnoDprOAFnQRRXxg9uV9i9Zpjey6AdUDm6u+x46ccdd2TV52GEenpQT1eIiIiIurYGFopYNZnZ+PwoTx1WU01lW7BRxKwuCgV2V4HKqJSONohHGDRxw33L5F4Hi9V3+76KBJIzeR0YSIiIiIKGoZWClhg7T//NIzQ2auvs3kteGhxHvLg4DY34cDaA4Y7MlWVfMmWfCxauhzPm1/iGlciIiIiCiqGVgpIs6XKnasRpbPjvR4PI7n3UHWT3ZyA31VVV/1dH+k1RqHC6VYhl5rG6zsZo6DTNXP0ZPq2tQeKDuZhh3cr3wIiIiIiCjqGVgpIs6UJVZXVuIEnY9pJY5v3eOZo6B48gCgAW/i+NElyrAV7nj636qtLOHpERERE1G7og30A1E6aLZ2yEFPtz3LdKhERERERBRQrrdRynQagyNVZrV2l9kfWt8p0YR9uhUNEREREbYmhlZq1hlU5si2wo+eshPP9K/HjrkLco5uNb+6dgvgoE98hPxTbnJj0l+9g9jqwuvc8mAx6YNbbgCmiWeMnwdRHtiuS7s8+sm5W9nrlHq5ERERE1BYYWqlZa1h93MZIfLnLhYzDRS0fSa8bpl1LcQqAiopyONwevjt+krEqs1UgEpVqDH3j2VwSSOfOGAF8Bvz5RBNKYsyqsdaKw1FYkJGj9nZlaCUiIiKitsDQSk1ew7rzlOewC91xqNSBF388ggOLDlVX4GpW6Ci8pfdNA0xRmJA1W7vCFIW4Mc9jk+4w9m9yYJGth1rDzOnCRERERNSaGFrJrz1YDx/KQ1zZLtUl+K4l5dXTRb3ohLunDUaPhAiGl/ZGtr+5PUP7sMJ2BPjgapzy0004xQJgB2DbblHNt/ajU53ThTP3FKmKrA/DLRERERE1B0Mr1ckXOIoO5ODKjIswQmdX18u2Nke9sbiLQbVjqNq3VakKsNkHSlG2f5OqwN7R/yje3VGKop1mIH4QMotjq39uPv5+XfXDFHpj6w23REREREQNYWjtqGo2VKpFQsnDC9ery/10+xFltuOLgU/A1GWgWtf4jx79GDw6cIBNTwEgU4d/eRhX5D6MK6TyuhJwfh+Bf1TeDR2Af5mew00W7YMO4dBF4NSKuVwLS0RERERNxtDanoJnVJIKFXVOy4wvPXbfqqmeNRsq1ZQO4HMJIjWaLZ1z9gXHKm5EVVOHs3fuxuyF65GkK1FB9W3zM2psXIZIbJ3yFgam9VJdps0f3YRx+i2wFqUAeYcbHr+qn2MiIiIiIsHQGoK8XmlpBJSUlNR/p6J9wLzTAFfFseuMkdh+ynN44Mt9x901QVeKlywvw+Q9Vvly6iy4zX63mrZZ08xxaSgoc2D55jzcdlp/nD6gExCZCOjj5YDQqhzlgF177W67DaUlJbB4a6RnqldpqR0euw1uVKJEp42her/Mze8g3Ch9PHr0H4E/XtkLe49WYFHFRPSKqMTgrjHqZ6abtTvUT4zLDJfTgse8LwJLXkTJkkYe1xgJ3PQNYO1e582+fxe+fydERERE1L7pvPzLL+Ts27cPPXqw0kTUkNzcXHTvXnewJSIiIqL2g6E1BHk8HuTl5SE2NhY6nawQbJxUnyToyh/ycXFxrX6M7QXHLfzGTD5nKy0tRUpKCvR6fZs/PxERERG1LU4PDkHyh3hzK0gSIhhaOW5tIZg/a/Hx8UF5XiIiIiJqeyxTEBERERERUchiaCUiIiIiIqKQxdDaTlgsFjz00EPqnDhu/FkjIiIiovaCjZiIiIiIiIgoZLHSSkRERERERCGLoZWIiIiIiIhCFre8aSf7tBJ1FP7u08p/R0Qt/3dEREQUChhaQ5AE1h49egT7MIhCWm5uboP7GfPfEVHL/x0RERGFAobWECQVVt8fE3FxccE+HKKQUlJSoj7U8f076VD/jjxuOHN+wuIt+TgYPwJXn9ALZiOrZE0ZP+xdDafbi7cOpMCrM+CaCd075Bj6+++IiIgoFDC0hiDflGD5Q7vd/LFNFGCNTZ1vt/+ORp2Ny0cF+yDCmPUsdfY7jqHCJShERBQOOt7Hy0RERERERBQ2WGklIgoXbiccq1/D/KwDWBl/Pp67dASizPw13pTxw9o34XC5ccfOcXDrjHhhVjrHkIiIKMTxrx0KfY5ywGEDzFGAOTrYR0MUPG4HzIvn4CoAT+wbjnL7UAauJo4fvvgjzAC+q3wdFYhA+QWDOIZEREQhjtODKfRJYPW4tHMiIiIiIupQGFop9EmFVW/UzgNZvS3L186JiIiIiChkcXowhT6ZEhzoacE1q7ecckxEREREFLIYWqljkqqtb50sEQVc5p4i7C44NqU/LSkK43pZOdJERETUZAyt1DG1RvWWiKoD64yXV6HmTrpeAAtvncTgSkRERE3GNa1UzeZw4YFPt+DODzbicIm91Ufm4/UHceUbWZi/No/vAlE7IhVWCawzx/fGs7NGqXP5umbllYiIiMhfrLQSPB4PfvfhJnySlQt4PWpEPl23F+P6dsY7145ChNkQ0FF6J2MfnvhiCyoqtWC8ausBPPr5Zjx90VBMH9al5U/ALXKovTJY4Jj1X3yy4SCuS0hHrCW0f4WPT7Ni5ugUdXlBRmiMH66YD4fLg+tye8OrM4b8GBIRERFDKwFYtrUAn6zdo8bCAx10Oh10Xg/W7DyEJ77egcfOGxjQcXrgf7+ox/d6AaPJBJfTiTJbJe6Zvx7Th53R8idgkyVqrwxGmIecjZlDgn0gYcpgBAacqfZpnc0xJCIiChucHkwosDmrA+urV43G278ZC4PRpK4rrtBuCyhJqwCumdQX71w3BueM7KG+drm1Km+dW9I0ZYua1tgih4iIiIiIgoLzoqiaDjrER2ph1WjQw+1q3cHpHCv1DsBa9ZwNVkubUj1lkyVqr9xO2Ne9j4VZB7DGeiaeuHAoosz8Nd6U8cOG+bC73fjTruHw6Ix46oJBHEMiIqIQx0orVfPCi9JKF1wez/FVz1ZSUO5Q58WVrsarpayeEgFuByyL7sSVeU/iq6ydKLe7OSpN4XYAn9ymxlDGT5ZFcAyJiIhCHz+i72jqaFI0unucmrGr13nx2/d+RoTJCLdLmxbs176KDTU+quM2i9kEh8OB17/fhYw9RdiYW6A+PYmPstRfLWX1lIiIiIioQ2KltaOpOc22yoAuMfjj2UPUmlaP2wVbZaUKseeN6oWrJ3RvfE1pHY/Z0G3v3TAORqMJenixqSqwms1mLLhpXOu8ZiIiIiIiClsMrR1NPdNs7zy1N9676QTVzRc6PR69aAReuHSof8G0oam7ddw2tpcVa+8/Dd0SY9XXydYYZP7pVBWeiSi0Ze4pwoKsPHWSy0REREStjdODO5oGptme1DcR2x6ZCo8HMBprfZ4hodM3zbcJj1nfbfFGB368bTD2luvRs0tS814LEbUpCakzXl4FXdXX0gd84a2T6l1GEGnLA/IOw1qUjxQcadNjJSIiovaDoZWOo9froa+r/h7oNaVVldue0fwRJAoXuwtsKrDOHN9bfb0gI0ddV1dolZB61jc3AEsrMA3AJIsFy21fqFuIiIiImoLTgyk42qIbcFP2diUiv41Ps6pTQxJ0pTC6K4CL52H16LmI0tlhcRRylImIiKjJWOai4GiLbsA11+HK/ow7lwG7VwGJvYERVwDRnJZMYcZggeOi1/Hh+oOYaR2EWEsY/ArvNAAlR/IREgwWYOabcLg8mLlnkNqnNSzGkIiIqIPj/60pfDW01Y4wRQJZbwObPgb2ZQDeGnvPLn0EGHoxcOLtQLcRLXseorZiMMI84hJc3siPbDDXvMp04YzdIdqgyWAE0i+CGcCjITqGRERE9GsMrdQm8kvtKCh3IinahOTYGvuxBqqSWjtMul3A4geBtW8cuy6+hxZQD28Gju4ENnwAbPwQuPYzoNfE5j0PUQcja1WtRdnqcrouB5G2Lura2k2a0n0XiIiIiFqIoZXahARWu8ujzv0KrQ1UN1/5fg9+3FWI5y/ojXhD1frYmuylwILrgB1LAPkTevilQL+pQGzXY/c5sh3IehM4sB5YeB1w0zdAXD0NYurpnGxzuPB2xn5cNLwrOsf5GcRZtaWWcLvg2PiJmh682Xoq7j9rECLM8o+gbUg34KWWexG10q6+nmYBXN9EAkMzsbvAUN2kSda7DvHGAZ8htMiHWVs+U9ODH6+aHvzgmf3adAyJiIio6RhaqU1IhVVVWs0OrTlSY1Nta1U3X1yxG/PX7sOe/NLqab5nHCjB6jmnHP99xfuB9y8FDv6irV875Y9AzxN//fid+gOn/R/w2Z1A6QHgq/uAWf/xe/3tL3kluOiln+ByOfHkomxM7N8Fz88c2nh4ZdWWWsJth/l/1+NyAIMrX8edp7Vt4JJGStJQSRorlcT0waKly/G8+SXAVgCgs7qPBNaZo1PUVjchx20HFvxGTQ9eUPk6KhCBu09NY2glIiIKceweTG1CqquDusYg2ew+Fkb96C7scntw5nPf4dkvs7HncPFx61IPFpZi7Z4iNfUY5Ue04PmPUVpgjbACZz5Zd2D1MUUAJ/0e0Om1da+bPmn8hTjK8cWaHZj+wioVWIUOXvy4/SDGPbkMt7y3Ifhdk4lamQTWIms6dnhTm/R9cWW7gLyftVNRbqsdHxEREbUvDK3UttvD+BvazNEo1Mdj3AsbsfVgibrKGhuFs0f0wAuXj4YHOjUVcVFWDrzf/Q14bhjw00taJaXTQOCcvwDJAxs/ns6DgaGXaJc//wNgOwp4vcDOb4C3LgDeOEcblyovrdiN3y7cCp3XA69Ojz+cORgTB3RTlyW8fr0hF3/8aFODrwsxyfVXmblND7WH9a4SSo9sq77ebk6AzWvBhKzZwKuTtdOL4xlciYiIyC+cHkxNn7ZqLwNyVgKHNgIDzgK6DQ/4VjfbDpXh3H/+AKfTqTLkKYO74baTe1Xf3jPajQsqP8VNG76C1auFWiT2BUZfC6SMAnRN6AIj29/s/QkozoVzwY3Ytncf0t1bj93+7iXAtYtw+8d7sGjdXuh10oTUhGcuTkdqfATG9ozHzZN64P5PtyCvoAQLVufgpL6JuHBEjTW0/uL0YQpHR7ahy+Ftx9a7rqy63hQFRCWhIsqAqfZn8cgZKZg2KFkLtB/dpE0rtvYI8sETERFRqGNopQabDR2n7DCw/n1gzRtAYY523TdPAH1OBSbeBfQ9vWlhsR7S4MgXWKWiesUJabhguHQoBXRuO7r/8iKWeF5HpMkGeAHEdAVGXgn0maxN9W0KScQGkzp+75ezYcpZhnQAlV4TFrgn4/KoTBgPrIf33ZlYvP1W6HQmRERY8I+ZwxAbceyfj8Wox9PnD8JN762H3W7HY59vaV5o9ed9IAoRhd5YuAyRMH50E2R1uQ0WrDxhHk4ZPkC7Q1RSVSjNQx46qSnFSKmn4RkRERFRPRhayb8KqKwTnTdFm36rfnIigE4DtGrrrm+1U79pwEWvaGtF5Xa9oVndci95dU1VYAV+N20gTkizqipw0t6vkZL9L8Qc1bbb2OZJxYuuC3Dv1GnoHm9q+ju5fy2wci5w6n2Yuy8dBucluMa4BAvdp+A11zk4gnisNU3Fc55HoMv9CW9GOXCr7VaUOY2INP86HJuMekwb3AWLft6LwvKqcWoqPyvRRKFAguhXpy3C9D5GLNmSj4cW5+F3nU9iMCUiIqKAYmgl/zgrjwVWceG/gOhOQNkhIPtjtY2E2mLm2T7H7pM8CJjykDZd1889Tv+6dCc27ytANCpwWT8PpntXIHLdNiTv+hgW2wHtTtIV+MTbcOaysfB6dUjdBswe14w30uMGzn4Wb2YV4MVtFdDpLsa/MAPvTY/EoRw33txQif8V9MSfp92PxB8ewyR3Fj4wP4pZjofwRfYRnD9M65Za08Au0VgkTUrdLng8Huj1XDZO7YA0TbIVaI2UaqmISlEhteigVFMdQTk8IiIiat8YWsk/PcYBM14H/vdbwO0AlvwfcPqfgbhuwIRbtErqxg+1dbE++VuA/14BjLkWOP3B+sNw9v+AHUtRXrAf5+/fixssRbDqyoF90E4+0hF44NnAgLOBqER0XV2BA6VOLN/rxuxxTa+07rOOxe+/qcDqPKua1dwl1ohlMyIQY9ZjVGcd/vOLXnUrvjhzEN4/+Wl0/ukxDK7Mxcumv+P+rY/XGVrTu0arGcfyeL/klWFE9zg0l3RFVtsERZv829uW2j+DGfbpL2Bh1gGcZe2LaIuhbQKrNE1y2jBBpgB7LaqxUlgymIELXoLd7cZZu/qqfVrbZAyJiIioRRhayX/SZTehtxZEi3OBL36vNT7qfyYw6mrtJNVLj1ObFvzzu8D2xcDaN4Gc74CT7gGS+gHWntpa0sx/A+vertrjEZA6bH99rZAalwrEpwJdhgJpJ2vrT6uM62rAp6VO5BS7m/wu3v2NAx9vq1QdiCVgxloMWDErAhFG7QCMej1mDTbjg02V2F3kxIlfdUW67l5VaT3JkI37nC8A3nm/WsMra1t9iiq0LXGUZkyTlsBqd3nUOUMrKQYTLGOvwZVjgSvbakjk36fTBlw8D0uOJGhTgKW6Go7k98eoKyEfAf19bLAPhoiIiPzF0BpOmhF8Ai51NHDTN1pwzcsCfvwn4KwA0i/Sbpd1rHKSNa3SnKnnROCHfwBHdwKf3lnnQ5aZOuHfFZOxy9MN+d543HJiF5w6sDNgjmnwUM5I0+PT7UCl0w2HywNzjcBYH5fHg/M+dmBzvqMqsOoxY5AZj000VgdWn2dONsPtARZs0cJttjcNdzjvwr9Nf8HZruXIX/V77DzxaXhlunKVQ6XO6hw7PDW2RV2BpcLqq7QSBV2nAShydQ7IFODsA6Wq4Zmsg5VpxWlJURjXyxqQwyQiIqL2h6E1nITAdihqyqotFkkzP0byqoeBNa9r03sHTT+uClqt+1jgwpeAXxZq21xIB2LbEfU67EmD8WTZdLxdNBwenQFe6PCnEyJw6jD/QtrUnvrqqbjf7PPgzLSGQ2thpQdTFlTiqE2bwjyssxn/u8Csqqr1+ctkM54+2YhKF+D0AHb3SfDsdwI//QPJOZ/A6CjGllNf1faeBZBTYFPn8loSoswt6gos1VVWWOk4bhccW5fgkw0HkZNwIu46rT8izOEzvTVjdxFyCyuxbOl6fG4BnluyFdleh2oCvvDWSa0fXN0uYOcy9SHXc7m94dUZcfepvcNqDImIiDoihtZwEgLboVRPWYUByWc9DWz5Aig7COz+Ttvypi5SMR3zm+ovl+9x4G8/luCX/WZVwZT/pMSZsPA8C1Ji/G9cJJVRi8kAh8uNm7+ywWjUQqzso5oYqUevOD16x+uxp8SD3cUeHCxzQwevus8lgyLwt1NrhMoGSKiNqXnXAVOA2CRg2WNI2P8t0tY8jt3jH1Y35RVrzap+1YCJXYEpENx2mOdfhpkABle+jusmhkfgkkqqBNMFGdpWWelVsxHumTYQi4tS1fW7C2xtEFrtwHuzIP+c36h8HRWIwPUn9giLMSQiIurIGFrDSWsHHz+mHx83ZdVoASbcDCx7VKu29jmtwX1abU4PTltQiUOlUuk0V0/PvXmkBfeNb94U2DN6G7Fou1s9rVvm8kpTYACHyzw4XAZk5h27rzyf/OF8/8RI3DK8hVNuu40ETv4D8O2T6Lb1LTiiU5CXfjP6ddbGzeN2o9DmOL7aGk7TwIkCSMKoVFIlmIoh3jjgM2DaoGQUHbRiQQaHm4iIiOrH0EqNTz+uEaKSY6OPn7I65jpgxTNAYY42/Td5YJ0jWuny4KT/alNzpdIZF2nAjcPMuHOkoUXbwvzjVBOGJOpxtNILi1GHCANwpMKLTQUeVWEttnsRa9YhLV6PYZ30uHyQAQMSAlRV6TVRqyCvfRO9sp6GpSwX3tEPwAMd9DovPlx3EDdO6hmW08CJWiO4VldS8w4fd1sKjsBalH3s+qgkwNqDbwIREREpDK3U+PTjhkJUVCIw6Dxg40IgZ2W9oXXKAnt1YL1tTCTmNGOLmrpI4L1tZBD3Qk2/RG2Lg6y30XXbu4jNX4cxETdgXWU3LN58+Neh1eNRa+qw6WMgeTAw7gbAFBly08CJ2kqkLQ9LLfciaqUdWFl1pSkKuD2DwZWIiIgUhlZqfPpxYyFq2AwttMq61rHXa92Da3h/iwv7S5wqsF4/IiJggTUkyLzkYbMAay9g1fOILtyEBZiD5wwX4eUd5+OpxTswsHMMhiR4cGjVO+iz8z/o4T62+az3xxehkz1sR1x2bNy4/pU6EIujEFE6O1aPnosJYydoMzY+uknbaofVViIiImJoJb80FqIiE7TziqNA/mZtT9UanlqtbZHRNdaIh05sxhrPcNBjAnDBi8CPL8KY+xP+aFqAm42fw7VKj2hUwqJzYVDVXUu8kVjkPgGTDRuQWpoHfHIbsPYN4MoFx8aSqIMpiekDpIwM9mEQERFRCGKllZpvfxbw7dPA9q+1r2XbF5nWV8O/f3GipFKbFvzESTXWwrZHEjhPewDI+RaOH19BnKvsuJt3ebriI+PZKOoxFbmVEXh4TymuNSzGHcaPEb8vE/jkDuDSdxpsZkVERERE1NEwtFLTu9keytY6Bm/7Srtdp9c6Bw+/FIhLUVcVV3pw/WIH1uQ5VAbrEmvE1F4dYFsJebF9ToO5+3igeJ/WYdkUBZsuAmkR0fij4dgYrDloxHVfXYAfHOn4n/nPMG9ZBPz8DjDq6qC+BAphBjMcZzyD+VkHcHJ8GqItYf5v6sg2xJUVtt3zGczAOX9R22SdvDMNbp0x/MeQiIioA2BoDYDS0lIUFRWhR4922u3S14ip5CCw9nVg9b+0ryWs9p6srceMS4XL48GXO11YuN2NFXsdkPKqZLhIswGfXxSBDkXCfY2mVHWtBh7b1YD110RixNv98A/nxWpKMb78E9BvGhDbtU0Pl8KEwQTzxN/iqonAVQhj0h1YZmV8dBMmyHZYXgvs5jaYGm8wAeNvUvu0vjqx9Z+OiIiIAoOhtYU2bNiAtWvXYuPGjRg+fDiuvfZatDtSYd3zI/DJ7UDZQe26lNFa06WENCza5cLDn9qQX+6GTu2EqvFCh8uGWPDUJGOLtrVpz7Tux2b89afzcKYhE8Mcu4F5pwPn/QPoPzXYh0fUOqTBknQHthVgyZZ8PLQ4D7+L0mZpEBEREdXG0NrCwHrw4EFcd9118Hq9eOyxx5Cbm4vU1NQmhTS73a5OPiUlJQgpu1YAC34DuO2qoorxNwOpY5B9xI0b3rPhQIlLVVRlJaasXZXpdqO6GPH3ySZ0jmZYbcwtwwx4NsOMu5134L9Rz6JzyX7g3UuA8/8JjOZUYarB44Zz1yp8kX0YB6yjcf2kNJiN+vANrtYeKDqYhzw4kLG7SF09xFuK9NZ6To8b2PMDnG4vXtvfHV6dATdM7BG+Y0hERNRBMLS2wOHDh3HGGWeoyzqdDiNGjEB8fDxsNhtiYmL8fpynnnoKjzzyCNpsTWpTZP4b3s/vhQ4e/KAbhbuL70HZ4gh4vOWodEplVVvGmRBpxB2jTLh8kAFRpuD/AfjzYTfe3eLGxiMeTO1pwN2jDTCGaLVXPuCY0suEJTkpmFL5DH5J/6+2Xvizu4H4VKDv6a37HlP4cFXC9M55uADA4MrXccnoVCTHBr7BWeaeIuwusLV+iASQlhSl5mcsyMjBggwgXZeDz1urZ5urEvjPdMimW89Xvo4KRGDGqK6tMoZEREQUOAytLSDrWG+99VZMnjwZBQUFmDdvHm6//XZERkbi9NNPV0G0a9fG1ybed999+P3vf39cpbXB9bFNDSi+Nanqe/y5fzk8lWVY8u5cnHno3yqYvu86DQ+6rocb0rTEre4m1xsNejw8MQJXDQnej5LH48HyXC8+2enG2kNu5JW6tJJvlc35wAtZOozvZsKjE00YlNS0xiuVLg8OlQP5FV4U2r1we4GuUTqkxugQawa+3efBN7ke/JLvQadIHZ4+2YSUmKYF5NtHGrEkx44Slxl7Bt+KXs4KIGcF8N8rgRsWA12HBfY9JmogsM54eZX69y1aNUQCGNfLioW3TlIhWaqtmzJz+N4QERHRcRham6iiogKFhYVISUnBjBkz8OOPP+Kvf/2rasY0aNAgXHHFFZg0aRIWLVqEb7/9Fpdddlmjj2mxWNTJb00NKBJufSHXD99sPoTff5SNTLyukulzzovxAmaifycTBibqIc02zQagc5QOvx1mCOrUumcynXgpq/K4tbRCMqvJqEdipB6HylzQeb3IyHPgzIUO/OmESNw6wqRNFaws0raqkaZStfyS78Y93zqwo8DZpF1oTnzXjtFdzXj+NDN6xvk3NiM7G6BTx+DBm5vdeGjSPbCX5sNyZBPcr58Nw3VfAN2GB+w9JqqPhEf5cZ85vrf6ui1CpARXOWnPx/eGiIiIjsfQ2gTZ2dkqiK5ZswZGo1FVViWwip9++gkJCQkYOFDrGDtx4kQ8+eSTOHLkCDp16oSAampAkWDrZ/Xt0S+24bUV23GSIRtGswdHdQmYfvE1uCcxtH5UpLp62ecOrN6vbakjITXCbEAfqwEnpxpw1WBDdWAsrPTg0R9dWL6jCEOxHbbM7Vjzy3aM1m2H3mUD4roDg6dr03Cr9pl9M9uFh76zaWt1qwKrKt76wqu3xvXywYNRj87RBuwvcQNeD9YddODk9x3459QonNfXv7FLsxqQU+jB6xsqsXCrAaj8Hd62PI2Rjp0o+deZ+G/ao5h+0dVIsUa06D0m8sf4NIZIIiIiCg2hlURCmHQIzs/PV9N/pWmSTAm+4IILVDBNT09HeXk5Vq1aVR1aZY1rWloaYmNjA38wrRRQvttRoAKrhLFTTJvVdYl9RiMxxAKr7AE7dWEl8su1BlA94k1YdL4B8SXbcGBbBlyH9qO7I0oLoKZIJFQU4u/FWwHzvmMPos1w1pTsU9v42DPeQEXvMxEx+jI8+oNePbZMf751pAW3DDcgxqw/LjQfqQCOVHoxIEFXvV7W4fLg4Z9ceG+TXVV371leidN6RB33vfWZOcCIuaudKheX2t2ALhpXOu7D6+a/YIJ+C27cfS/+9uxPWJR4Le47ezDOHJIc2IElIiIiIgpBodmZJgTJljZSPRUylff777+H0+nEPffco6qs0oRJmi998cUXqhHTm2++iZNOOqlp036DyOXy4Ka312lBzWTClVYttKLbSISSTQVujH1HttdxqcrnVT0L8F3PfyP+k2uAr/+EbjkfoUfhauh2fQNs/RzYuBDYuQwo1gKrNyIemyJH4yHnb3CO/UkMr3wVf3Zei12errB47bDu+hQlC27D2fgBXnjx1SWRsFqAg+XeXzVPks7IQ5KOb/AkU6WfPMmMLy6R5jI6uD0eXPmFw6/XdttIE3pZTeqxh3U2499nRSP7lq6wn/44vrKcCb3Oiz+aFuKPRY/j9rd+wJCHl2LF9oIAjzARkIIjsBZlq1M/3X4OCREREQVVaJXQQpBsZSNV0z179mD69On49NNPYbVa1fRguSzXzZkzB5988glGjx6tAuz+/fsxZcoU9OrVC+HijgUbUWm3qyD48vAcxGRvBQwWIGUUQsUnO124e2mFmpBrghPvpH2JCYfnA4c96vYCbyxWeEbgZ09fWOBEjK4CnQ3lOCulEglJnYHYFOjMURgC4AEPsHC/CeuKndhQfgourTgdQ50b8YDhXfTT5+FF8z9wtW4Ebv7wOuxyd8aj0kU1WdapmjAgofFGThJmr0q34N3sSvx80IEF24yqktqYFZdG/uq6U3pFAL3uhGfbQHh/egnTDavVGt67Ku/ENa+txqvXjGPVlQIm0paHpZZ7EbVS24Zrmhlw6CKweJcLGYe1bWmIiIiI2hJDawOk4VJZWZnq5PvnP/8Z+/btU11+X3jhBURHR6vgKg2Xxo8fj/vvvx8vvfQSxo0bB5fLpW4LecX7gYMbgJ4n4utf8tRV/TpF4JTdz2m3D70EiNTWtQWTy+PBJZ86VPiTSvCJ+mz8O/4NRB/SjhkJvfFUxUWYVzQabujx1JD9eG5XFxyuNAIu4K2CSnw5YNtxjymzda/oUaBOxxiwt+xa/Lh9HcaVLMUJ3vX43Dgbj3ivxn89p2NzvgPTPnCgp9WEGQOMuH6oAbENTPt94iQzvsxx4ajNhQe/t/sVWhuiH3AGEJUAfPMEzkUGyvEa5jhvxC1vr8HK2aeiZ8KvAy+1M3oT7Kc9jIXr8jAmNhWRpqZ1wvaHxVGIKJ0dq0fPRUzqEMxeuB6F3ljkLTqkbvdWbVPj2xInrOhNwLRHYXd5MGZHKtw6U6uMIREREQVWGCSr4JDpv3PnzsXevXvVulSpql566aV49tlncffdd+O5555T04ElnEoH4ZtuukltVRMXFxf6gbWyGFj+BLDmdcDjVGs/n4w9B08Wn4Vziv8HizEPiE4Ghl6MUHDexw4VGPvq8/Cg5b84HWsAKbjKut6+U4HkQdi2rg880CPB7FZBdGpyMcavkJoqcEJCmd/P1TPGi56jRgK2nvhh9SpM1GfjafNruCZ2M645eh2OuKORW+zE3zOd+FsmYI004rJBJtw7tu59YF8/04ILPnLB7nTjnU2ulm8N1H0ccMpsYMXTmGX4FqXeSDzmugrnvfgT1t0/WU0tVor2AjuXAwU7tD/UR10NxHZhs6ZwZzTDMvl3uHIycGUrP1VJTB9MGHMyHu407LiAKoFVOv2GZWg1moFJd0MWbbwzOdgHQ0RERP4K8XQVHFlZWcjLy1PrUg8dOqS2trn22mtVcJXq62uvvYarrroKb7zxhuoYLE15ZCpwREQdXV1D0dJHgDWvaZctsYC9FJdjITymQpyn/1G7fsxvAGPwX89dy7XAOkW/Fi+aX0AEZH2oTpu23PuU6mPsH1OJb/JjUerUqiZzNh3b5/a+AVUV2aaISsT/Gf+AKfYlmG36AENKf0CmJQNZSdPx16JTsKq0m5qiW1zhwivrXHj1Zx2m9TbjqZNMSIrUH7eVTdc4Iw6VuvC3tY7A7GfbayIw8W5g1d9xg/FLfOkehzVlg3DtW+vx9qxewPLHgLX/Abw1uk0dygYuePHXobWpe/5Sh1NzO5q6yN6qNc+JiIiIAo2NmGpxu92qS/DUqVORmJiIwYMH4+2330ZOTo6aHiwdg6XS2q1bN5x//vkq3H788ce4+eabYTabERYGngPoqqbEyV6lQm+Eech0REBbx3bT+r4Ittd+ceKTbZW41vA1XjX/TQus1p7AuBuB/mccF6qHxVZUTSUGZmT0w/J8rWvzmV1K1FTg5jixUzledZ+HiysfxkFjCnQeF8bkf4z3nL/H7tT/w0eDvsHIJKeaLilrnxfvsmP0W2W4+ku7+iDD58EJ2s9FQbkLP+bVbFvcAv2mqGnd4txOB9X5ys15KHzrKq2CLoG18xAg7RTt/tsXA2Xa9M569/yl0Odxw7l3Db5e8jX+m5GrulUHi1Rc5Wd/QUYO7p2/Tp37pg6HLPl9t3+tGkMZv/cz84I6hkREROQfhtZaDAaDWq968sknq6nBQqqoJpMJO3bsUOdy28svv4wLL7xQNV4aM2aMWvcaNvpPBS5/X5s26rQBljjg2kWYefn1KNfHqLvsOVx0XPBqazsLPXj0h0rcbvwYj5j+A4P8OdxtBDDsUiAq6Vf3PympVP3BLGte1xRGqW1j5Osnh+Q2+xh+0+OIeowN6IcTy+biRvvvscQ9Bi7ooSvYgdG75+Fjz++w/rRfcFqaRT25PO93e+0Y/U4l9pV6kHXYjQ+2akFVjm1b4fFdiBsi+8v+cYUD6w/XE3QT+6izc5KPwGQ242TDL0g4uEp9AIEzngDOngtMng2kjtVGI+s/v34MqbDK/f3d85eCy1UJ0+tTcOaqWXjkowwUVzgD9tCZe4qwICsP2Xn+TaeX6uvCWyfh2Vmjqk/ydUNV2aBzVQLzTldjKON334frAjqGRERE1Do4PbgOY8eOVdOBJbRKGE1KSlL7s3bu3FndfvjwYfTu3Rt/+MMfEFZyM4A1b2jTakdeDvymakuYE26tDkDx1iSgsBhxsOHnI16M1l5ym7vi8wrcbfgQvzct1K5IOxnoOVFLfnWQtayvjtyNv+zopr6ONbrx2OB9SDI3v7LZL8aON0bn4PFtqcgpN2OpdyyWOsci0VmCi0yrMCdqEcwVR2H98Sm80eMEuK66HTd/F4VlOXYUVbgw6b0yFWJ9ZL3p5QP9+5xIPjCYuqASBTYXFmzR4f8mRuDGYabj72TVulNHF23D/WOAE9a+o77+JeksDJOA75N+IbB/jRZaT7sfiExo9T1/KbxIYJ3x8ir185qu2497pHF4fESLpw4TERERBQJDax1kbers2bOPu06m/kpYHTJkiNqLdf369Xj11VcRFnzrFrd8rjUi2fa1Flp7TtBOPm4X9PYSdVEPL1bt92B057bvrPnVDhvm2F/AxabvtStkiqus42yETAWWUyCdnlyK05O3qMu/FEfilT2d8VlePF5zno23i6fgs5T/YODRb4Hcn2A8sg2vn/4g3unRBw98V6HWvMoWQhaTAZO6G/HwCSa1j6s/7vnWpQKrkMd5bFUFMg568Oq0Gvv+JmlTuGOObsR1R2eoeRMl3kjckHc+fvB4jjWG6jpCC7hFe4CtX2nvPVEN0lRJAuvM8b1xhtUMrATSu2lT7IPmSFXHb5lZYQ2jmSxEREQUcJwe3AhZqyhkb9aUlBS1Bc7DDz+spgaHDd+6RZlaG9sNmHRX3ffb9Q1gO4Kj3lis8/bH5qNtPD3YaYNn82cY+P3duNj4PVxePdBvml+BtS0Mi6/AP4fvwaujdquvHTDjjP034Xznk8hBClBxFJWf34eK/Rtw2RALRnQx49OLo7Hthmi8caYFveL9++cma+w+2V6pLkeZZWK0ThWYZc3sm9lakFViugADzqr6QoeSLhNwmeP/cNgdg+ezalSY5ZtTx2iXc38K1HBQOzQ+zYppg5KDegyyvY7sC4uPbgJenQy8OB4oav40fyIiIgp/DK01gmlddFXTUWUv1szMTPTv3191FT7nnHMQNnzrFhN7Aaf+CUgdXff9qtY8fuKeCCeMODm1jaqsZYeBjFeA/14JfcYr6K07gEJvDH7p9ZtjYSuESDX3m5O2IMboUXlwg7sXplc+hlXudNXI6ur9j+Hwlh+x/pADf1zpaPLaYCnGJkRqkyBsDreqtPqmF4/pXGt69ITfalvgXPQK4s76P+w1a9XXPSW1fqY7D9bO965u/gsnamXSxGk/OuHUirk41/4E7nbcpq27t9XcT5mIiIg6mg47PVi2ryktLcWVV16pgqkEV19ArYtMDb766quxaNGi8Aqs/q5bzHob2PyZurjQfYqq8F0+qA1+PA78DCx9qLqL8U5PN7zlPgM7Y8find77Eap6Rzuw4bSNWHggAWuLYpBjM+NB2z14yPsSTtWtw6umv+FV97lYX9gXc/7XBc+e1VVtowNd458TSTjNuCICF3zqwKbDDjWl+OqhZtw/3vjrvWDlwwhZo+z7supn2FX7g5jkqtCavxmoKDx+XStRiPA1d5LpyrKFzqbM5cE+JCIiIgoBHTa0yvY1d955J8rLy9V2NfUFV991w4YNw7Zt29CvXz+0O9uXAJ9pU4b/4bwQ2d7euH9MG2zfI1P+ZM9YCaxxqbir5HJ85hgJnU6PDWM2ItRJfpyVWqhO1TxTga0OmA5n43bjp9p10ox1IeCOSIRh4FnAgDPr7IBckwTVLy+OQEGFGQkWLcj6w1D14/urXTwirUBcd6BkH7B7FTB4etNeLFEbqdncaVMmh52IiIg6aGg9ePAgTjrpJHz99dfVVdO6gqvL5cLq1atRVFSEc889t30G1v1ZwAdXAV4Pdnc6FX/bN1NdfWHfVp4aXFkMLJPA6lRhao7xXnxamawaFz0xZL+aehuW9AZg0HQgIQ0o2I5tBU7EeoqRjCIYK48C698D1r+vrdMdNhNIavhnKimyaTP4LVX/oveUaONX5vDgjWw3pvXUY5B0FJbQmrOi/tDqa9olU8rZVTj06E1wTJqND38+gCFduiLS1PaN0sKabPM1+U9q3fiQHV3h0pk4hkRERGGgQ4bWhIQEFU6HDx+OZcuW4fTTT68zuEpo/c9//oM77rgDYau+ECLXH94MvHOJtndht5HoOvlO4D8OKS/j5qUOfHxB41teNIvbCXzzBFB2EIiIx6Kk6/DfTclqfeiw+Epc1SPM16/JC+k6TJ36eYA5m3rgk/0xOFOfiauNSzBevxXYswrY8wMw9BJg5JWAodZ2Ns00tZcR72x0YcsRF6YtrMC2ApdaE/uXDB3mDU7HGfgc2PVt40271M8Mt8IJOUYzzNMewOXTAPaAbt744bT7IPNIPpwW+LeHiIiIWkeHbMRksVjQrVs3FUpPPvlkLF++XO3D6tvCRgKrNM+RrW9eeOEFFW7DVs0QUvv6ZY8ClUXa16fejwiLBVela1uqrDvoQPaR5u9x2iAJbIc3qYt7+16JOzYPVjkv2ujBRxOqtrloJ2RW77NDc/HjaduwI2Y0Ztofwpn2p/GZ6wSZfK72yd33vba/aiD8brRRtW2SoLq9wFm97Y6c/2FTP7jkcyrZSmTjhw037ZJz6lBScATWouxjW80QERERhYgOGVp9jEYj3G73ccH19ddfV7ctXrwYTqdTBdywVl8Ika9l707RfVz17Y+eaITRoFd7Nl7/tb11jslQtV42MhEX/nJi9dVfnLAV5nb6E5lkduPLE7fhHyP2YpeuJ+503YXZzpu023I+wznv5qkpiy1+nkg9hiSbVVCNizDillGR+PGqGCRFGVGqi8FrrjO1O350S92dhKW6GpPMKmuo8njgOpCNlT+swhcbD8IVgJ8ZEWnLw1LLvZi2coa21YwpqtF112FJOnkf3qzGUMbvi+zDARtDIiIiaj3tNCL4z2AwVAfXjIwM3HjjjTjttNMwcOBAmEyBmbIZVPWFEPl64Nna5dKD1VdLw5/7T7Co0HOozIXff+sI/DFVbb/irTgKu10LxnOH5qJXtBPt3QXdirB1ygb1enNix+NnT19E6hyYUfkRTv6gEq4mbo9TF2nglHNzDDZcG4X7xpuQEqNH5pURGJtixjOuy/G1e4y2lvjdGUDBzoC8LmojrgoYX5mIUxafgz+8swqFFYH5N2NxFCJKZ8fq0XOBm1cAt2cA1h5od1wVwEsnqDGU8bvt7cyAjSERERG1ng4dWiWs+oKrGDVqFC6//HI8/PDD6N27N9q9HhO08+JcoLKk+urrh5owuptWDf1wSyWeWO0MSBWwmmy3EtNFVXNHGXaqfUmP68Dbzvm6Di+YsBMjR4xV111hWAZTeR5O+cAekOBau9uwfD3/XDMiLSbc47wdm3R9AXuJFlxrfGhBHVtJTB8gZWT7DKxEREQUtjpsaN21axe+/fZbta7VZ926dXjqqacwefJkdAjRSUBSf+3yka3H3fSBBByzQa01nfdzBQa8Xq6mC8ta30DwJPZR5/11+zAl+Vhg7nCky3B8d0TonPjE/H8YV/YNTp9f2SpPJcH1jlFmVCACV9v+CGdUZ+DoLuD1s4Difa3ynERERERELdUhQ+v27dvx4osvokuXLmpdq8/IkSPRs2dPtGvSNbgsXzsX3bVKX+3mK7JP6JIZkWpdpOL1YvluO5blBia07irRqtsyDfmxQR04MMmnAgPOAaKTkaQrxfPml/CY7XGs2LK/VZ7ulmEGGAx6FOji8UDUQ6rijcIc4M1ztX1ziUKR/H7K+1k78eeUiIiow9F3xMAqzZauvvpqDB069LjbfPuztmu1uwmnjtHO84+vtIp/bXChuMJVHS4HdTJjSo/A/MjsrdpHNM7sReeIY9XuDikqERj9GyDtFNi9Jkw2bMCk1bdr+9hu+wqwHQ1otXVcV+2DiC+PdALOfKoquO4G3ji7zp8DomAp9MbCZYjUmkO9OlmdXC+Mw6Lv1yBzT1XncyIiImr39B0xsM6aNUtVVTuk2t2EfaG1VqV1Z6EHb2+0q0JgjMWAN86JxleXRPxqrWRzyJrNcqcWWofGVbT48doFvQHoNRGX4Qn86B4CI1zAvkzgx38CC64Bvr4PKD8SkKe6ZIAWWksq3bBZOgFnPQ3EdNXWNr9/GeDu4B8iUMjIQyd8ddoi1Rwq+7xFuNtxG4zuCrz8+U+Y8fIqBlciIqIOosOE1m3btuGNN95QgVUaLnVYtbsJ+86l+irl1Co3LrGrvT0lpGZcGYnTe2rTeQPhnc0epOm05j8nd22lvWCboMylx5PbuuG+7O54Oaczvj4Uh3x74F5vU1RaOuFy5wO4VveEqrwitpt2w8FfgM9/DxTsaPFzXNRPDy90qhHWe1vcamqyCq7yYYascS3pwNO1KeRURKWo5lDSPGyHN1VdNy09Vf387i6otf80ERERtUvHFnS2Y7t372Zgrc/hTdq5tae2vrLKwXKtEjq5pwlRpsB+tvFGVhGu1u1RlyMTtT9Cg2F9cRT+vDkVPxdHqj+Aa5L8fnbXErw0fLfq9ttWxlrLsbkkAt/aeuOH2DMwsddEwFYAZP8PsB0BvvgDcMocVZVtLqNej/gIA0oqXfjxgAc3DpOmXJ0ASxxQcRSoKAISAvqyKFD0JjjG34FPNhxA74RkRJqC8+FKsKWnxAAbm7Edl94ETLwTDpcXvbcnw6UzddgxJCIiCicdIrRGRkbimmuuweDB2v6gVMPhLdq5tddxw5IWb8DmfDe2Hg3gVjcAMg+60bNiMwwWL8qMiYixxAbl7bguqzeWH45VOV0Cq9SYIwxeONw6eLxafv/qUBxO+n4IvjxhC+LNHsApU5m9gDHyuIAfSA8N3I/5+xNhd+tw47o0bDxtI/RRScCoq4BNn2hNk759Ehh/MzD4/GY/T1KkDiWVQF7Zseo6LDFaaK0sDsyLocAzmmE+5wnMPAeYyfFt1vjhjMchG3p9wfEjIiIKGx0itEqXYDlRLdJB+MD6Y5XWGk5OldAKHCgN7PTd+75z4BpDlrock5QSlLfk0a0p1YHVbPBiRkoh7h+QhxijFtBlV58r1vZFRkEEUit34N3vs3FtdAaiKw8cq9ZExGunbiOBTlXbBgWA7Fn78ojduG5tb9hcevwhuyf+PmwvYIwAhs0EdiwF8rKAjHlA9/FAbNdmPU/XaD1yCoF8W40PJcwx2vmhbKBPB9n2qSOTLrxSxZeGaGW7gn00RERERB07tFI9pINweb52WdY11nDpAANe/VmmyXrw2i9O3DDM1OJhdLg8KD56GJdavtWu6HJ89+a28N2RWLyW00kF1l5RDnwzacvx03+dFdAf3YX/xnyKyoocRHirGkXV3DrV49Sm6srp6E6gyzCg31TAaAnIMZ6eXIoTk8rx09FofLTfipmpRzExsQzQ6YH+Z2gNmYr3Aru/04JsM/SO1+HHfcARmxs2p0ebAp48SJsuvvgBwF4KnPwHwMBfESHF44Hr6F5sOFACe3QqxvVMgFE+6WhOYH1xPODU1oROAGDzWmA3t/N54fKJVHEuXG4vMkti1b+pcT3imzeGRERE1Gb4F2lHJh2EKwq1y7KesYa+CXokRxuRX+7C4z9WYkZ/A+IjWvaHnfxdeItxESw6J4oie8Faa0pyq8jfApTkqYsujxfbczvhz6bvYdR5cWWXfOh3erSKs70McJQB9pLqb42QDOvV4yv3OHzjGYWVnhGI9Nqw0PIIuuiP3Q+HfgGK9gCDpv+qYt1cb47aiWHfDIc0Wb4isw/eGbsLJyWVaTd2GdLi0HrTMCPezdZB5/Xiii8c+PiCCGDEZdqHGPK4MgVZqroXvwIk9gnIa6IAcFXA+M8RGA1gcOXrWPnAdCTHNuPDEqmwSmC9eB7QaQCWbMnHQ4vz8DtpetSeuSqA54er//FdX/k6KhCBzAemNm8MiYiIqM3w4+WOTDoH+9YvRhwfWsWH50eoLrNerxdXfdmMpie16O3FuMqwVF1eEz+t1daF+hzd+j2w6WNgX4Y6GfMycb3hS9xg/BLXGr6C8cBaIG+dtt1Pad5xgdXHpPNgin4dtnlSkO+NR66uG8bbX8asyvuxxd392B3le9e/B+z9EfC2fB1whBF4f+yxTsFXrumDrw7Fa190Gii7Cmudfov2Nuvxe8frMXOQ9of6zwcdePhHB2CKAk6ZrVVY5bKM20sTgT0/tvj1UIjqNEB15i2ypqvtZYiIiIhCEUNrR+ertPrWM9bQM06P3wzTgs2GQw58tbuF+3euexsROifWefohS9e6U4NvzuiMxIPfq8vzXZPxiutc/Mt1Hl52nYdlrhFNeqwovQOLIv6MPxv/owKpTqdDBobiTMdcDK/4F152nHPszjkrgJ/frV4r2BJjE2z47ITt0Fc1i7rl5174KC8BMEUeq36ueBqo/HXY9sdfJpuRZtWmfb+xvhLvbXFpHyT0OQ04/59A8mCtMiV7xBIRERERBQlDa0fmlr1Zqxot1bMe86ETjIixGFSWeT6rBaE1fyuwfbG6+LjzSpS6W2+biSWH4+Au3q8ub/ek4AnnZXjJeR5ecp6LFa6hOE1f1XyqiW4wfY11lltwkW4FTF6HGpMSXRye8VyF4RUvY6unamplyX4gc55WdfW0rJHVsPgKLJm0VU2tluD6u1964LU9nYB+07QPGqTSuvQhbX1yM3x1iQXRVe/vfStseF+Cq4jpDJz+oLZ3q1Sj92vNs4iIiIiI2hpDa0fmqtFdyFB3oyW9Xo/JPbSlzzlFzQxgMl129b/UxQ/dJ2OtdyC6WlpYtW3AI1tTMUqvTa3tp8vD+shbsT7yt9gQ+Vv8N+KpFu27mqAvx98tr2B75G/wN+M/kYZ9ak/XEl08zrD/BZdW3ocCb+yxquuafwMFx6b5NkffaDu+PWlzdXB9dHMKbt02Ehh+GWAwAwXbgRVPNSsgRxj1WDYzEmajQT32n1bY8H+rqqaCS3fkXpPUxY/+/SQGPrQEY59agbP/+RPu+OAXHCyu2Z2KqHVk7C7Cgqw8dU5EREQdE0NrRyHNhsrytXMfl/3Y5V8WAFXVydrOStOqohVOt+oA3GTbl2jBSm/EU87L1VWpkTWeO4C2lEYgt9yEkTotKLbmstmLjT/g24jZ+LfpWcR4y9RzrcYwjLH/C3McN6DUG6FNv964UJsyXLi72c/VPdKJH0/JRqLZrZ7ny4NxmJx1EoqGXAXoDFo1NPt/zd7+5vvLIhFp1oLr2xsrMW1hBQorPXi4YIq6z1melTDYS3CkuAyb9xVg0bq9GP/UclzwrwzkFDSvykvUkLSkKLV/8oKMHNw7f506JyIioo6JobWjkOmjHtfx00ilkpaQpl3e8AHw8S3AZ3cDGa8AOSurt8M5s5de/fEogebLPc0IrbKNinTi7TYG+V6rupwW2fLGTnW565deKtTZdW3XDXSacR02Rt6M3+k/QKy3FF6vDh94puBE+z+x0HWSdqfiXGDDf7WOvPI+NEOyxY01k7MxLsGmqrt7bGaMyJiKuW7tg4CKvc2fwts5Wo91V0diUCez+np7gROj/lOGNw/3RYXXjCidHef0NWNw9yR0ToiFV6eH/FSs352Pyc9+g6veXAePbCdCFCDjelmx8NZJeHbWqOrT3BlNW49ORERE7QO3vOlI29tIYJVzH9mD89Yfga1fAFlvaVudyL6jctr8mXaf1DEwn/5/iLUYUGZ3473NLlzQt4k/Nk5tr9Mfbd1VoJQAPDQu8NW5g5UmbC2xqOc4kjQWKGzbdZh3mz/B3fgEq90DcJ/zBuxCD/zBeRv66fZjpKGqSrR/jbZdzeALgKikJj+HTG1eMH4HntrWDa/kJKvXusbZG7AAhw4fwkVv2XDJACPuGW1EjFnf5KnCX10SgYd/1OPNDcem/lp0Wsi+7IR+cEZ1VpedLg/+k7EfyzcfhN7jxvdb8jDmqSJ8eceJ6BovmwVRq9Ab4Rh9PT7/5RBSYxMRIfvrtoBsdVN0MHSn3kpwlVO1vMMte0BZoz3uRjjcHqRuT4RTZ2rxGBIREVGIhtbdu3ejqKgII0eODPwRUettbyOnX/ECvSdrp/IjQN5a4MB6IDcDOLgB2L8W+GUhTup+Eb7a6UbWwWZUCWU/SACrSrSQ1jXCpdZnBtrfdnZVIU4qwjPTE4C1Cce6I7ehCYZtWKqbgyH211Cpi8RvHffgp8i7j92h7LDWqGnw+UDnIc16jvsGHMCcfgfwv4MJ+GpPDOAAuukKUFThwL/XuzBvvQ6/HxeBu0fXvVa5IQ+faMZhmxef73DgysEG6HO0CqrHeCyMmox63DixB35zQir+vnw31u46jMJSG0585lvMu2Yspg7i9imtwmiB+fy/46LzgYua8e2Ze4qwu8AGe+5+XAXguSVbke3VZj14q6bktmvScO7cv0LmE2ibbxEREVE40Dc1rPbv3x99+/bFmDFjYDAYcNlll6nrKcynDYsug4FRVwHnPAvcsgK46BXt+l8W4NaqHWpkTeuOwiY2/JFtUwDsqdD+IJ7WuWpv2ADz7WM6NL4SeoMOSB2LYJGK6J+Nb6vLB5CMj10n/PpOmz8Five16DkuSSnEvAlH1ORtqYiqqcPQye66+FtGBW5f1ry1wy9NsSDnpmg8eeKxXxFG+6+rcUa9HvdO7YPrTu4Ljzyrx43r31yN9zLrXh9NwSOBdcbLq9T60Pd/0ir/l5/Qu3rqrUzFPa6qSURERBRuldbi4mKMHj0aiYmJuOmmm3D06FFkZWVh/vz5WLp0KZYtW4YRI46tN5Igu3DhQmRmZqqqbJ8+fVTYnTFjBtLSqtZRUouUVjrx9+U5KHccC5FXjE3FiO5xx+4kjZd804LrqrTWNW3Yp8d47dzrwYguJuj1TrVu8c1Nbjw+qQlb1kRJ1W0ruuu0NbI39NTOA6nQYUCxQ68qrTf3qppCGJmAYLrC9C2edc1Coc6Ku513Ihp2tf71OFs/B8Zcp3UBbi69ATBFqGnY86c5URodjdPnVyK/3IXPd9hR4gDePrvpa3ylczT0kUCXocChjUhb+yS2nqp1ga7tzMHJGNg5Bg9+uglwOfHAx79gxqhuMLdGSb0j83rhKctHTkEF3BGJ6Nc5Wnuf/CAVVjULYXxvnGE1AyuBq8alAilVWzV1BLIY3Fagfo/tKI9Undr6JUf5PYZEREQUHH7/n/rpp5/GzTffjB07duBf//qXCqtyefHixYiPj8fpp5+O0tJSdd9LL71UBdQ5c+ZgwYIFWLJkCV555RX1tVx/1llnYc+ePa35ujqEGfPW4PWV2/HBT7uqT+f98zss2ZxfdwOmujoIS5CNSa470Bbs1M5juwE6PdLitaC6IreJldaE3upssF57z52ewLf0fTu3U/V62XO7FP26O3KQvGN+GjqvdPzV4UbnvZhjv/74O8j05V3ftvyJjJHauaMUsWY9Vl8RgcHJWhD+bq8dV3/ZgrGYcKvqUJyYuxgJufVPqkxLisSzFw+FTCb2ut24/9MtzX9OqpvTBv1f+6Pvm8NxwXOLUVDubPJIjU+zYtqg5I45wrJU4dm+agxl/M74+4pmjSERERGFaGiVqqoE19qmTp2KnTt3qtA6e/ZsjBs3TgXVSy65RN1fLj/zzDMq8I4aNQper1cFXQmv//tf87boICCvqBKb9x9VQ2EwmmAym6s6ugI3v70Wh0uqQopUUKX5iK+iWruDcEOO7tLO47qpsym9tMJ8bomreaFVt1ed76kIfGffLw/HV6+XrS6a1NyHtgVyPJ3R3Ma46Ya9WGKeDbPXrkL1B96pGFfxAvZ5ajRhyssCjrZwOw/fetPyAnUmlaPPLzRjVFctuK7cY8fHO5q5N25CLyBdW0HZ56f70GnXx9DXM7bd4i0YlJqoLi/M3AObo/X24yUiIiKijsHv6cFSTW2IhNN+/fohISFBhdjevbWgUltOTo6q1D777LNqqvCrr76KG264oelH3sE9+uU27RMHnQFvXjtKrS3cXVCBOR9tUN1cL5mXie/+cNKvGzDVNxW4ga1qEJeqzq4ebMCr62T1pBdrDroxtqufU4Tjte/vqdOm7e6taMFU2HpsL9NC26SkMu0Kt0Pbu7SFXnacg288I1GIWCyJuK9Zj9HPcAAbLDfhMsf9WOcdhHxdEibZ/4F+uly8YHoRQwy5wPavgLE3AoamN05SLLGATHT4/q9AyX4g/ULoTVH48DwzRr3jQXGFC7NX2HFhv2Y2DB9+GZD7E8zF+9B/1e/hynwE+X0uwtHuU2FLHAyX5dhU7NtO7oW73z8KHTx48LOt+Nsl6dVrKhf9cqj6fjEWI26f3AtRZjYxJyIiIqL6+f3XokxvbIysW/3tb39bb2AVcptUXu+//37ceOONqgI7duzY49bDUuMqHFrpT6fXVZfLYywG7X3yemF3upvQQbgee37QzjsPVmc94/Sqa6zL7cGC7U0IrWrSLuCuOtKd5REB3+pGXq689CtSj2jr1mQbn/IWbo8hjX4RiWJEw4FmhskqEXoXPo54FP9xTsFDruug0+mxEz1xifMRLNHdi+6VBdp495ncvCfoO0UL6oU5wPr3VPMsDDkf+kHn4ZGJVtyzzAW7q4nTumuSNbPn/FU1j3JtXQxjRT66bXlTncQhXSfsNPbDJzGXYf6hFPVeCPkwRfzjmxz89atN1df7fL+jAJ/cWrV2mshPcWW7kK5zItLWBUAHWpNLRETUQfk9PVim9TZGmjNJ4yV/K7dSnb344otVeKWm+b+z+6ts5nW7cPP7v+DW9zfg7vkboPN61DTh965vYefcg78A+VVrEmtsy9IzTguqGQeaEIDc2hRRl850XFU0UN7fn1QdhsYm2FRFsPrYW+he84d43PQffG5+ICCPd61pGX6x3Igb9Z8h2VsAmzcCj7iuVbe59/7U/C16IuKAYbO0/V+lAZXHCWz8EFh4HYZuexFmyLq95q8llq7Rf9tgxugNF6D/0b/jWsccfOo+EXs82r6tXbxHMNH5Ex4/+gdcpftCrWudMS4Ncy8ajL8t21UdWOVnU6az62SPYAA/7zmCgjJtyxWiRsnexqYoTMiajc8tD+Csb6YDRbkcOCIionbO70qrNFf697//3WDAlEqrrH1tCt+04p9//pn7vjaBdA3t2TkeufnFKLdpW8oICbJPXDxM3d4iK+Zq57JtTMSxqeETuhmwq9CJ3JImhFYJUHIGLfDuqwzs9ODl+Vq35M4RLqA4F8hZEdDHH2fYFtDHi9VX4kHz+3gQ76PYE4VT7c9ihXs4Jhs2wLbtW0SNaM4OnGo6hFYVTx4EFOwA9mWo8eiXvwT3Gk14ynON3w/1/hYXXlnvREGlB+UOL9we2dDG9zx6rPSOQpZ+NGLMOnQ1V6CXaw+mO7/EVM+PeMz0Ju44IQldzjsXc5fsxItLt6hDi4yIwAuXDkW02Qiny4Or31yjPmSRKcQvXz6sea+ZOhZrD+D2DCzJ2oJFS5fjefNLqhuwup6IiIjaLb9DqzRWmjVrFqZNm4ZevXoF9CCkYZN0F3755ZcD+rjt3fvXj8GfF21FRY2pwJeOScWFI7q27IGlu7Cz4ljglCRcVcq8sJ8B72+CCh2lDo/qVNsou9ZV2mXQKqx5FUaUOvWINTWzu1Ete2xaCO4bbQcOb0Y4idfb8Jnlz7jOca8KrZbCbdr4N2Uad23yXnXqr52kYr71c1xiWIm/667269tlO5A/rdC2R6l+yKpJ3n0STLhjlAmX9K/5q0PWSCcB3lHAxoVA1n/QZf0/gSl34MVlW9XhREVG4J+zhiKyav2qTDMf2j0B2bkFWL7lIACG1tYWactDui4H1iIzYGxmRT8UWHugyGrADu/WYB8JERERtZEmdUCRpknSLfi1116rcw2q7Mc6ZsyYJh+ENGSSda7UNN0TIvH61SObNWz5pXa11UNStAnJsbW6+UqzplPu1SqWB9YDe1YBaSepm8Z1kTZMWi5alefBWWl+hFaphMjfmjFR8JZrAegvO7vhkUH7EQh9ou34uSgSPxdJeAq/qYLd9QUYrtuJnz19MVK/U5vanNr0f0d16jwEpVu/QaKuDGfGSDfoxteOF9qPTSSe1MOCkZ31SE/U4eTu+oY/pJAfiqEzgN3faZ2nM1+D0TgcbpcLE3onVQdWn15J0Sq0uj2NLz2gKnojnEMvw9ebDyPJakWEyc8VHkW5airtdEuF2p9VMUVp0207EumkPuIKON0eJO2wwqkz+T+GREREFB6h1Wq1YunSpariKuH0qaeeOu522cqmuaTrMLUdCax2l0ed/yq0SnfhxD7AiXcA3/8NWPMa0H2s2lZFtlIxGbRmTBkHJbTC79AaGRmNIXGV2FwSgY/yEgIWWuf0z8PlmX3hdjnhLcv/VbOfcPAb42L8z32KCq2VBzYjIkChVaZkf+sejvMMP+GK2Cy/QmtB5bEQ+cYZJpiNTfijXgY//WLgu78AGa+gX+Kr2HrYhewDJb+6q9utVdr14fiGBYvRAtOMVzAdUCe/2QpgdFfgbsdtmD71dG2fVgmsHW1ardECXPSyaqv2fbCPhYiIiPzW5I+YJbhKOJX1q2eeeSY++ugjBII/3YkpcKTCajHq1fmvyNTUmGSt2hrXHSjPB3Z9W32zNUL7sck65Of03qrQCksM7u6jbXlS4tBjeX5sIF4KTkwsR6TBi176wyozhWPhbphhDz53jYPHq0NE+b7qKdUt9fHBBHzj1qrxo13r/fqegqqZ4TIrvEmB1adr1VTf8nxcnrRDXcwvObbu2sdZ9Ubxn37rkW2GFmTlYcmWfPX1Dm8qiqzpQMrIjhdYiYiIKGw1e17UTTfdhPnz56s9WWXLmltvvRXLly9v9oH4052YAkeqq4O6xvy6ylq74jroHO1ymfZHrxierDVUWnfAgUnvV+C1X5xqHWS9KoqqHi8GZ3UphtngVUHluqze+Pfu5IC8nku7F2C/txMqvGbo5bEr/4DnHRfA4fF3W57gs8OEbG/VevHifQF5zL/s6IYN3j7qsqE0T0uijYiv8SOxrbCehlteD7BzOXDg5+Mfs/wIsLiq03J0Mvr21zpPu6s6SNfk8YXWFnQ17nC8XngqS5F/9CjySyob/HcngXXGy6tw7/x1eG7JsfWfaUl+7tPcHsnPqqNcG8OSSrVMosHfXURERBQSWrSYR7atuffee7FmzRq136pUYCXAjhs3Dvfdd58KsSUlv54WWFdn4j/96U8tOZSOR5r1SJCU89Yk26eo5ztW+XtpigmJUUYVPPeXOPHYDxXo8+9y3Luynq1LKn2hVftj+cNxOyAFPIkqj23phie3dWvxYT48KA9XpJXha8849fUZxiz83XMp+tvfwsuOquAd4ooRg3We/toXJS2fOr2+OAr7bUbs81Z9MOC0AY6yRr9vSJIBBr1evb//XFdPaM3+SJs6vvhB4Is/ALkZQNkh4Ks/aYE7LgW47H2Yk/uqu+v4mVRgOG3QP90dyf/ojVOe/FxN76/P7gKtmdbM8b1xz7SB6rq5M0ZgXC8rOiz5N/BkihpDGb9xTyxtcAyJiIgoNASsA8WoUaNUF2AJsLJXqzRskhArTZZ8IVamEvtCrJxLqJWQK6fTTz89UIfSMUizJI9LO2+L0FpjumqEUY81V0Zg9oRIdI01qsZMUsGYv6kSD/1QR3CtLNbOTVpH3GHxFVg9ORtWs1sFo1d2JQdkqvCDA/Nw/iitUnmBYRWiveVq2vnT7itR4AnMVOTWUuiJVutPs6pDa16LH3N2dg9turTBfKwbcal06m3c8M7acvcle+r4g16aLK1751hjmyPbgOWPAh/eAJQdBKy9gOu+AnqMQ0Rk/V2QuSSgbYxPs2prWAGkdwvtfwdEREREdWm1tolTpkxRIVaCq4RYad4kU4klxEozH2m8dMstt6i9X6VaS00kVUsJDFXVy1bj6y7qq5ZWkffwtpEm/HRFFNZcHYMe8SYVkN7cUIk9xbWm2/mmj0qgqZJkduOHkzfBUjVV+Pqs3qoy2FJ6WacXlYQonQOrLberaawSjm5y3INQtsIzTI2DdBBWyg/7NZW3PrKl0JYSbZ7vdT2PHHsfa6xNbsg9o7W1zhUON/aW1Ho/9/6kfWCSMhr4/WZg0t2qSZeS0Bu49F0gQfvwINqsTc+W17bzyPEfsEgjMCIiIiKixrRZr3+pxEo4lRAra4gkyMqU4tmzZ6uGTrUrsdQIX7Okluzn6Q+pmjVSoUuO0mPZDItKJhJOPtlVa0rpkAu08x3LgIMbqq+OMnqxcJzWqEdc+FM//FIc2bLjlQPocYK6GKN34Df6L9Xltd7B2OvphFA1Sr9TZdSDSNSukFDotjf78T46kKiGQmLvvf0OAD1O1G7Y/ClwNKfx79+hvYde6JBYlUerSRMfcWQ7YIkFpj0K/GELMOMN4JpPgSRtDa3o0ykSRqMWgB//Yutx6wez9hxV5z2SWvlnmIiIiIjCWtA2qBs9enR1iP3666+Pq8TKdGJp7CQhdvfu3cE6xA5LmpNsOVimztXWN74GO+76135Jl9mECK2q9mNerQrawHOAvlNUBMLWL7RKXVUVUaYKvzdulwpXcjrvp/54qqVrXLukA5Fa+HvQ9B50Xm0a8l2O2xCqeunzkaI7jEpYUOatSoktWK+8+HC8Oo83edT6YST2BjrJukYv8P1fG1wzK8Hysx3aNO8TU02Iqb03a/Ig1WRJrXPevvjYNPKhFwMJPY/7IEUq8s9dOkK93ZV2O55cvBPf7SzExxsOoaJSC+X3nVk1JZqIiIiIqA4hs6t6zUqsrworIdZXiaXg7OGK6E6AWdbBeRvtaNsvQftx2l6746zeAEy6Bxh6ifZ1zrdAzorq4DoxsQzvjt1VffdXcpIxbPlQ5JSbm/cCdHog7SR10aj34kb9InV5nXdQSFdb/2hcoM4PerV1xBkHJUA277GyS7Xgmx5bY6uZflMAgwko3A18fBuw65s6v/flDW4VXOXteeZkc93j2/sU7fJX9wO/LARc9VeFpw/rgjF9OmvHlVuAl5ZvxQerc9QHCREWC04fGLrvCYUBWVOd97N2KsoN9tEQERFRew6t9YVY2VZHKrEUpD1cJVl0H6PdsHFhg9/XJVrbuqTUUcdaTHmcMdcBY2/Qvs79Cdj+FeDWKnonJZXhp8mbMTDWrsKSrMmcumoQ9trq2EfWH8mDgWgtKN1n/gA6r0sdwquu0O0kfIlxFeK8JThcFVrf3WlCnyXD8eDm1CY/VplLq3qnRtaojlvigDE3aFO+vW7gu78CP7973NrZSpcHf1ujBdBeCSb0iq/nV4RUzo0WoGSf1oDpr4O0AFt2uM67//eGMUiKi1bTjX0nCb+/n9a/bbthdzApOAJrUbYW7NqZQm8sXIZI4KObgFcna6cXxzO4EhERtUNai1CiGmTv1uP2b51wK7BrhVYdlam+Mv22DhkHtAprH2sDe6OmX6RVXjNeBQ6sBwr3AIOmA/Hd0TXCia8nbsXHB6y4e0NPuL3A5Wv6YdUpm5v+/khC7X8m8PPbat/Wf5v/hrucd2KXt+Xb67SmHyx3V++rmqo7os7f3pOEvAozXh/d+FpUn77Rdmwttfy6K3OkFRh+mVbtzl0NrH9f6+58gjZ1+rqvHXC7PWqq9r+m1l3pXn/YjQ+2dcXNp76ItPxlwPYlgO0I8NOLwKb/ARe+on3QUWOasEwfX3v/qf51w27tddrhTGeAc+D5+HbbEcTFxMBsqP9zx0hbHpZa7kXUyqoquCnqWEOudiAPnfDVaYswvU/V/8YkmEuAtRUA0pCtLjqDWmPvdHsRtzMGETpzg2NIREREoYGhlfyrWg4+T2viI/tyDjgLGD7r2HY4VesgD5W51b6Q5/dtILSKwecD1p7A989pYUeqfT0maFNOdXpc2K0IBQ4jHtuSgn02E+bvT8Cs1MKmv1PxqcCAs4FtX2KK4Wd8rPszHndeHtLveIzejonQQvpd3bfjiyMO7C43q/B5/k8D8PH4bdD78Tf2b3oewX3ZqSiwG1DgMKhuzccF+j6naet+t32prTNO6odvIqbgh1yHuvnCARFqv9ba/rbGiefXVqj3+d2NUYiLvBDn9r4Y/9d9A6LXv6FVXt+bBZz/AjB8pv8vXLpgq8Dayt2ww50pAqbL38Y0QJ0aYnEUIkpnx+rRczFh7AQtsNYX5sJURVQKkJLi/zeYIoBZb0Hmb6xuzQMjIiKigOJHzB1VU6ZjxnQCTv8/oOdEwOMEtnwGfDn72P6rAD7P8ahJn1Khu2pwI6FVdBsJXPBPoK/sz+vVpgtvPLY28oZeR5Bs0ab0PrKl6dNjjz3PCGDU1SjUWdFfvx9zzf9GuIhwlmD5xC0YbdW2itlQHIHrfz7Wmbchl6YUqHMZv4e3dK9/bNKq1qb++CIe+uZoVcdhHa5NP/49LKjwYNrCCjy/Rgus8j7LfUsr3fjvZidGLE9H8ZS5QNfhgKsC+PjW43621uwpwqgnvkHafV9Wn3rf/xVe+2Fv23bD7oBKYvpoHZ/bWWAVGbuLsCArT52yDxzbS5qIiIjaF4bWjqrmdMzGSJBIHgBc94W2pYlUSUsPAMsfr16TesimrYuUPVFja3ebrfdxY4CTfg9M/pM2be/oLuDndwC7tu3RZd21LVFs7hb+mMal4j+d/ogcTxd00R2/32xI0+lVVfWjCTuQUFUpPVjp3xpf+b5xCdp7+2lePJ7YmoKXczrj1d3J+LmoRjWz54laBc7rxhnGLO1p4cVFH5Vj7Ds2der/WhlGv1WG7QVObYlzvAkbro3BK2dGYXgXswqwLrcH078wAaOv0R5XKqbGCHgqS3H3e2tw8curUFhqU/vm+k5ejxtPfbnluG1wiPyRlhSlfu4WZOTg3vnr1Gn2wvUcPCIionaKobWjklChNzZtOqaaVjoZuHKhFmTzNwObPlU39YrTmjB5azT18Zt0+j3nL0CEFSjPB7LeUvvC7irXOuBGG1oeavomGPEn580IKzKVsUppVWOlMVb/GxW9PXoHzAavetvm7e6EZ7Z1xZNbu+GCn/rhkS1VUyrlRrUVDvBA10zcNSYSFpNBXX2k3KVOTpdU0bUK7C2jIvH9ZZGIj9DjzDQjPr0wAveMjVS9nHKLnfjip5+1x+11Ej7LPoIRc1fjkw2H1C8avcGIWRN644aT++OyCb3V97icTrz8XVW1lRon1euH49Vp8J8+1Lal6oDG9bJi4a2T8OysUeo0c3zvZo1f2p8+77BjSEREFE4YWjuqlkzHTB4InPaAdvlwtjrrXRVa5b82ZzNCZqf+wLl/06q4jjJVcY0p1/boTay5HrOZJiSU4SfPYKxwD0fYMGihVTopO6uG4Owu/leKI4zA/LE7EWfyqGZU2tRf7fz13Z3wUo7WXRmdBqgz3b5M/H6EG1uvj8afJ0VicLIZk3pYcO2wCMw9NQobro3GfeN/Xen93RiTqriKqPwN6vyJLZ1x57trUGrTukEPSE3E69eMxkXDu2DqoCRcMLwLOidoTaJe/GZHCweKOmpwnTk6RZ3Gp1mDfThERETUitiIiZpH1i6Kkv3qzCSpqEq+DegV34zHjOkMnD0X+OZJ4OAG/N79L3yNZ9AjsuWfrXSOcKkps8+7LsZkgxasQp4lRp3d/HPv6sA5MaGsSQ8x0mrDhtM3Vn9d6QImfDcUxQ49/rq9K27rfRiI6QIYI7W1qMW56gOE64ea1MlfC84z49K3duIkvfZcKxyDVFiNiYrA9RN7YWKfY027fG45qSce+ywbtko7svNKkZ5Sq9Mx+SVzTxF2F9iOmzorgY6IiIiovWBopeaxVAWMqsZJf13rUud6vR49WpI9ZJ3rlIew+927kKbbj8dMb6DvgDMD8i7FGD3Icg5ApmksxjnXIKTJ9iRdh+PRrSn4oSBahdapnUv96hzcWPX1XyNycHlmX7g8WoiNMOq09c2+8W/O4+q9eM7yKowuDxa5J2CrpwcePn8YBnWtv5Kf3i0WXp1OraHdVWBjaG2Gn3OLceNbmWqGg498uCFTZ4mIiIjaC04PpuZ1GzZWrbesasS0dI9TnY/ualTBtSX+s9WAO+23wuk14DzDTxhSoTUIaimrSZtj+w/dVQh1X0RfgDMyR+K1nE4qsPaKcmDeCP/3aW3IOGu5qoLK464uitXeQ+kK7dvHtTl2LkNv106UeCPxiPMaGIzGBgOrjzTuEodKuK6wOXKLtG7OsqbTt7ZTvq5ZeSUiIiIKdwyt1Lxuw1VNglxOh9oKxebQAuE9o/2fUlqfx36sxC/ePnjTcIl2xfavjttep7m6WLRgtt2RCAw8F6FGQrrIcA/E7QfPxbZSiwqWUUYPvj5xS4urrD5GPWCoeqxVR2OOvacGy7EPI5pq+9fq7N+uc5GPBCTG+Pc4hqoXdbhU+/CDmkfWdHJtJxEREbVXDK3UrG7Db6zV9gHVux3YXqAFjhiLASel+rFHawNk+xOnW+tA/EXMJVpnW7cTyP4IqNS2wmmu/tGV6vyIwwh0GQok+rfnaVso8kTBpHPD7jXh/1zXwQs9UiJdmNW9EBmTN6lpvYEUVdWR+UClWVvL6pvyXVX5bLKqbWsSdNpemUfLKv3aysZXaXW4ue0NEREREdWNoZWa3G14dU4h5i7VpqrqdV4kR3hxRXoEvrssssWjKVOLr0y3qMtZh9z4sNvvAIMZKDsErPm3tpdrM53XTeu8K514C51GIP1iLbwG2V5PJ1j1NlVpvdV5F6b3s2D3mRvwwymbMDc9V63FDTTfxkRGnew7UzU1tynbH9WyqeuF6vw649e4QP89PG4XXl+tNelqiNsXdiNbXqHvEHQGOPtMxUqMQWRkdHWlmo5ZsiVfNaeqb/zQ/ww1hjJ+MVGRMPumHRAREVHIYiMmapJKhxtXv7EGbmhbnIjMywyA5djXLfX4RCM+32VEcYULv8+Iw8H053F70V+AozuBX+YDPScCvSbJxp9NetwTrGXVW758dCABN/Q6ok0Tju4M7Fre5OPM8yTgM/eJOMuQiV76fDRHprs/xhm2w+PV4Q/O3+KqkYk4PfkQWpsvtBp0x9Ylq+ZPzXT9tnG43nUubjZ+jr+YX8VBexKWZutx5ZhuiDTX/2tG9vWVQ0iMZmj1iykCpms+xCnyoY50bc7Ka/Z71p5Ix2Sf55ZsxcbFDtWM6lddlGVZw5ULID9tgVkpT0RERG2BoZWa5Imvd8DhcMDrNcClt8DosWvb3iQPCthISrV1ySUROG1BBcrtbszNjscZM55G/+2vA9u+BPb+oFVeh14C6PyvkkhRymryoNipx193dMV5XYrUVjjoMR6I7qQF4ioHvVZ84R6Pn919kKorUNNe9WrSrgdrPAOw0jMCpYhRAfhJ11XojAJcb/gStxi/8Hvt6UZ3TxVYxX3um3DXiZ3QL0abXtva7G7tIE06D1BRqF3ZnD17AbyZ7cKBEhee0l2Os5KPomfhj3jb/CRed5+NVYt3Yfop42GP7g6vVMxrcLo88Ho9KrQmxQTuQw/qeCSczp0xAvgMmJaeiuyNWjMqbv1DRETUPjC0UpNMHdQJb32/Q4W1H80TcXLlN8DqfwHn/LXJlc+GdI7WI/PKSAx5o1xtifK/HCNmn3g70CUd+P5vWtU15zugz+QmPe6dfQ7hsS3dYHPpceLKITghsRz9YyrQO6oTlhjGYop9Gc43/ICuuiJcb1wMl0GPrz1j8R/XmcjwSjCvWvOp0y6pSqFOh3wk4RnPVfirfRaWWe71q/LqqZqd/4r7PPzf5E6IMbZNB92XczpDlg1LB+FLu+YBW1drN3Qf3+TH2lPswUPfV6ifh6RoM3qe80dg5VyYc1fjt8ZFQOEi4BPAq9OjtNMobD/5H3BEd1Pf+/mmfDUCUms9pW9ioF9mhxRpy0O6LgfWIjPiypo/lT4cyRZK6jwlBtjoQMbuY1OEuXctERFReGNoDRBfeGnvJvdPwqlDUrFi8378vnAGvo1ajeiCHXBv/hSG9IsC+lxRJj06RRlwpNyFzIPSndgE9DlVu/G7vwC5PwIxnYHOg/1+zBvT8hFh8OCBTakquK0qiFYnn+9xLZ71XIG74lZikv07DMM2nGvIUKfNnh74r+s0LPeMQFccxY3GLzFNn4X/uk/FS+7zkevtCpfOjDPszyDDcgfi9Q1vOzLcsFtNC85LnIAYYxnayvM7u6jztGgHRhYvB5w2IK470Iz9cB9Y5VQfKkhqXXRRhNaa+LQHUb7zB3y3cgnSdIeQpj+MCK8dcflrkb74cmSf8S4c0alYtkUL9imJMYgJdKep9spRDu/cfqhwujHa/jJmnz/22G1FuTjrm+mYbqkAVmpX2bwW2M0J6EhS4iPghQMLMnKwIOP4vWvHdTMBz/ZTH9gMLvsnKhCBNQ9MRXKsto6eiIiIQhP/UgwAp9OJsrIyJCR0jD8OX7tyOIY9fgT5lQl43HE5njK9Bk/mm5i3Ebj0nGlIiI0J2HMNSNBC647CGs2IJLhKQybpKLx1ERCVCMRoQcwfV/UoUJ2EH9uaigN2E4qdBjg90lHXi5t75+Pu3geh1ycDuBgoOwzkZQEHfsZgfS4eMb+FR2o93hX6b3GF6Vt84joBdznvgl0Xgan2Z5AZeef/s3cW4FGcXRu+17PxEAIkuEtwd4oVWmhpi1SoO3V317/tV3c3WoqUlhYoRYu7E9wlQEJIiK7vf70zCQQIkmQDCTn3901n1mff7AzzvOec55xyH3b4KlHbmMQcXzNurn/u2r18uTMGh9egXbR/3GANbMq9qm97i+4OXUgW7NPbCF1c20qVkNy8aIOBkHpdGL+jLVO3q+ixn7bBSfwa9BZBmbuJ//dalvcdR9KRLC3SOrRNtYB+xwsdgyeb4NxI/3Fkp2D25vCg6x4G9uml3fXi1EQeDo6jvEVcx41odrRXrYq4KgGrpQvHRmiTNGrs8hZBEARBEEo/YptYTGbNmsWwYcPo0qULd9xxB+UBs9nIgie6079FdSbbLmWxr5HWruVux7dYfr+ZNRM/gdSdAfmshhX0y8pM1wkOuq1vgrhW4PPCunHgLFwtaIcKWUzstJnlFyWwte8advVbw4Y+a3m4rhKs+Z6oIrkN+kPnh6Bubz0ieQoGmRfxkul7bTvZEM1eX/Qpnxtr0OtIx/t7UTvk3InW73YpMQ41Qtw0964Dv0+vRy5CavARh+9oW5sHW50seL/obaFDVSt+v4Fl2ZXpdvhZEqlEUNZepo37UqsRVqnBd3erEYBvJuSx1V+VqWn6kkjF8jcwhzbTzrKToXW80rtWEARBEC4QJNJaDJYuXUpycjLvvfceW7ZsYejQoQQHB/Phhx8W6n2cTqe25JGeXrx+pCWOK4soXzZfDK4L1uZkpLVk2ui3qL1vIvWMiTRPmQJ/TSEnpiX2LndBRPUif1Sa3loVq/mEmIiqn+3+JPzzGBzZC+vGQovhYC6hND/lOlqtnb64siBlq3ZxTPreYy1jVMsX6zSsHq9Wp7rDX4Vq6P1sTyTI4NYMndZYmgObORcofXnAYdaiS9dVSwFnbkpyhbpF6s8aks87yWYq2FBr9MAgfl5v5uUFDg56o1nkbcBVpiQsfn3M6lSOIPg07sJC0VCRxby02PzOuhc0wdG6A/b43MlDtX2vyiQIXK29IAiCIAjnB4m0FiMleP/+/VqUtXbt2lx88cX89NNPTJ8+nYMHD2o1rmfLm2++SURExNGlevWii7xzgisbfB59DYRFVqTvXe8Q/PAKHg5+Q3Pd9fiN2JNX4ZlwP6z65VhblUJyyKGPo/1E0aqwhULvl3ShqtJ41/+pR15LGuWyG9sCmg3VI7BtboV6fY9GYYebZzLL+ohWz3kq5vhbcZvrMWLt52B/c1maFpJrHgXXVE0BV65oVenVJ7A+xcvDs1wkZ5+6R6zZaNTeS5F2Gg+pG5qY2XhrMDc0DSIqSP87VokKpX29yvxwY6vifi3hBJSL7jvDWmlLgW1fLlQiq+si9c7ZcNXXeq12dsGTRoIgCIIglC1EtBYRi8WC1+ulb9++eDwe7b7mzZsfjZwqU6b80dPT8fTTT3PkyJGjy549eyjVWIP1+ke1zkdclJ33n7iX5AHf09P9ITO8rTD7PbB6FKlj78d3uPApw2m5ojXEcopIYFgV6Pd/euQ1dYfeEqcQEwbFRkUoVQpx1TbQ6not2vuftwUmg5/qxkMFviSlWl9udD7GEUKpE3JuHIMVv+/XxanFBFFW7zHRaj+5FvvS37P5Y7ODXmNzTv+mhjOL1jyB+2oXKz2r6aec2zrXZMztbalZXqKA57imc2jrOG0pN4I1v3CNawkVG5zvPREEQRAEIYCIaC1ilFXRtWtXGjVqxIoVept6FXG9+uqrMZn0dLRDhwoWLSdis9kIDw8/binVqEijEqwq0qpSZU/gpo7VmPjctbxb+U1GOB/koD+SKOc+0v56mqf/3sKOI6eO3p1ImFVXRRmu0wjRivU1x1pNQR1cBztmc96IrM5jxse41PkGP5qu0utF7bmRzKAI5lUfQZutt2j7qr7RTdXP3BonUPxzMEJbNwjNzbk+Ku4LnhBQDxcY4T4hBVixOvks/6aevHxvEauCIAiCIAjC2SGitRDMmzfvuChrTEwMH3/8Me3atTv6nKCgIC09WDFq1Cit3vWC5IQU4eQMJxsPZGprRUSwhcn3deLGOx/m9tDPWOWrQwVDBg+nvMzNo7dw6XgH2/I7Ap+ClpX0n2ia4wzPVbWmnR/Qt/csgh1zzm3ENR/dK2aw3l+LV3OGQJMroP2d0O0xHg9+neGbu2nPUXv2ectdNAg7N5HWtUfspLv0sXys3n79Tlvu5Ej2yZMrIwcE06CihR/6n75GuIJdf89lB88yzTlHN6AqjNuzkA+DEXf1ziz2N8Fisx2dNBDOjHIR/n31QdKrdNTGUI2fzWbFbBIPYUEQBEEo7YgDylmSkZHBY489pm0vWrRIi6aqiKsSsCoVWLmoqgtIVY9aq1YtsrKyePXVVxkzZgwXJHmR1tyIWUqWG6fHp63z9zzsVDuKvx8fwMGDrdn73QCqObfxq/UNhiW/QK8xMXSsamXUpdZTXnx3q2rksxXg9fpweHwEqT6gp6J+X91FePl3sHsBeJ1Qt0+RTIaKw201khi/LxKPD25bWRunz8Da9GCOuIzargSbffzVYQv1Qs9davAbm+O0z7Ya/fSKyXVatoXp66yTo71dq5qYNsR+xvetE2EkJQu2nDgB4XVDxn6IPMEZWERr8bDYsdz2Dx2ANcpwaUUicRwiMi0BzLkTAsIxDm2miT+DeMMO5i85xNglFfHzgFbru6a8pU4LgiAIQhlGpukLIVp//PFH7HY7bdu21e5TgjWvnjVPdLVu3ZrZs2dTr149fv31V/r168cFiUoRDo3R10B0iAWb2aitj6JShzOTtXXlyrFUu/9f/NH1qWpI4W3r11pS6uJ9Lv63/NRRunZV9DRaJbi+XnsW0bymV0GHu/Xtfcvh4FrONfHhDvKCNzOSwph3KFQTrIrmEQ5W9Vx3TgXrwsMhLDis/50urpzPmTpPtBbDrKZjrJ4Kn5zlJSUnV7gqN+Wpz8KEe2DX/ONf4Diir0P01jtC8bBnJzLd9jh95wzRXXOVY65y0S3v5HMSjv97IJNszzIn5EnuaGnXzjt5PVwFQRAEQSgbiGg9A3kuwImJiVStWlXryxoZGXlUuJrN5qPCVZGUlMTgwYP5/vvvGTBgAOUFFV1tVCX0uCjriSnESuQarhutbXY2radesF4PO2HrsfEryMCnVqQuhN9d6uCBmS4ycnu2quj239s83DvDycTt+d6j0UBoOVzf3rPkvKQJ31Yr+WhkM9rmpX6Yk6cb7uevjpuxnsOjblpSODcsr6tdqKsg9ZuN85l8KXfV/GnCRWBEC5M2o6CmFh6b49bdm+f+D5LW609YM/r48VcRWIXlzFFc4czYXKkEG5wsbv227pqr3HOVGVF5J7+TcK6bsNmbQ/tK586tWxAEQRCEwCHpwachNTVVS/OtVq3aUZGqUG1t+vTpQ5s2bVi+fLkmXPNQz1u1atVRJ+FyzQkpxBrRdbV2MYb9q7mzwgqeyO52LEJ3Ct7tYWXwBA8Gv5+/tjiYsMVATIhJi+7pcViYuAVeCzfzWR8brSuZoPHlumBS9ZrKVbhCHc4lzzTYry3ng11ZFt7ZFse/B8Nx+/SQrxqlX9psI8ySb6zzIqwRequeohBsMdKvtpV/tzuZudOJa9G3WHcv1N2lDSY4vB32r4K4vNY2pzd/Es6AKwvf+81IzXbRxfkRb12ki//00Dq6a65wvHA9QcAbvQ6W20YQ/I+ZRmPeI4cglj3b+/jJNkEQBEEQSh0SaT2N6dJNN93EwIED6d69O2lpadr9DofjqHCNioo6Tsxu2LBBSx8WwVpwCvFxkVCgg2+Vts5x+7So6aloW8XE3GtD6FTNhh89qncoy6OtVRDPbNJrRQ9keLhyfBYvLXTpn9lowLFo6wWOCj6/tTmWpjOa0n1uYybuj9AEqxqfcIuP95rtoUOFE5yesw/r6/Cqxfrst7tZtL/L7aZJWLdM1gWp6pPZ9pZj0VYVYc3fQ9cgp56iYsxJIdqQcXTCRigcauzs7lRt/GQMBUEQBKFsIFeOBaBa2Kh04B9++EFzAD58+DDDhg076g6clw6shGuVKlW0tjevvfYaoaGhlDvy1a2eNUF665VYUjRRpS4cx205fbS1RriRUQNsbLg1hKubBNGskpUH2thZdXMoW28P5bVuwVjNunj9frWDuXu9erRVCai0nZCyjQuVxBwLjac35/MdMWR69DEwGqBThSwmdtrCml7rGByXerIhUuYBfftEs6RCEhFkpEcNK9eZZmq3Mzs8rNcWd7xHj7aqNkSTH4Vpz+svMAdJyxtBEARBEAThrBHRegKqlU1ycrKW/luhQgUaN27MTz/9pNWqbt26VXuOSgdWz1NMnDhRa3HTq1cvzTm43InSE+tWz4TXA4u/1DattTsSE6qnVn+6KrfW8SzSUd/qZuXvK4N4pK2FqCD9J3x9EzPrbgomyGLSRNtz8116WxXVckaxdSp4XVyIPJZQA69fLx2tH+rkm1Y72X7xGka120aziJyCX7R9Fvh9ENe62KJV8VlvC6v89bTtf9bk1s1G1YTB3+g1sypN+MAaXbBe8rbUtAqCIAiCIAhnjYjWE1CtbEJCQujWrRu7d+/W7qtZs6bmDqyirwpV56qep1KFp02bxuLFi+ncuTMXJGcSpapeVdUv5q9bPR2rf4XD23Qh02ggN8XrJks709yknqkX6xlQkdYHWlv190t1szXVCy2v051qlWvtiU62FwDZHgPzU/T068vijjCtyyb6VMrnEJyPNzbHUvPf5tw3W28FokWh294WkP0ItRoxVtf7FTfLWsR7M7brD9TqBjdPgoaXQvUOcP0f0GzI6d9MpREf2gJJG48tOXp6viAIgiAIglD+ENFaAKpOVdWzKtGq3IOjo6O59957qVixovb4oUOHjqYKd+3alQYNGnDBciZReqq61YJQocDZ7+jbTQdrLSk091mtThWumVT8NjB3Nzdhyq1xHfiHg70O27EWOKq2VUX8LiC+2VVJGztV3fh6o3zOwCcw+1AYX+2IIYIs7veN1O9seIkeDQ0Qg7q2QVljNTLuYdq0f3j+70367yYsVo+43jYVanUu+LeSF9E/mAAftYRP2sJnHY4t7zaCfSsCtq+CIAiCIAhC2UFEawEoMfrEE09ogtSg1I/SZlarliKclxJ85513atvKeOmCpjCi9HQoUZJxUIXR9Ns752n3qZY218Xrzp2bDrkZMb14wlVFxJ/vFKSJOIfbS/ffsvn4UGsc1bvp0m7tWNj0DxnblzJr/T6eXmymxcwmWgSy9tTmdJvbmKcTqrExI4iyQI5XP4QtRoiwnjpS3TI8i27BuxllfY2Gxr14jEHH2gIFCKM9An9cG237R9vbzJk/l8cn7jq734+K5KtF9RpNUxkOBj0an9eOx5MDy74N6P4KgiAIgiAIZQMRrWfZp1X1Zo2LiyMzM5OXXnqJK67IrZUUzg4tvdgPV36tC5GULTDlScg8yBtdrbSorKf1/rPNSa8xOUd7sRaFm+PNvNcrWPMGVa7E7y7JoenmO/jT11XfhwOrCdszg57JP/Om4zV+MrxEG8NmLRC8J9vCqL0V6De/gZZOW9oJNuf2rD2dkazfT0TyUn72P0u8cReYbJgHvHPUECuQmLs/ii+yFpUMafxie5PZi5fz8LiEM79QRWTnvqNHWtXvY8h3cM2v+tLv//TnrP8L3Keo0S0vGIx4qrRkjb8uRrMVg7gwF3YAWe2rw6HweG38zGYLZpO0XxIEQRCE0o6I1nzCtCDyIq3t27dn6dKl1K9fX3MVvvTSS8/dX+lCSjOOawG3TNZNklJ3wsSHNXfZPy630qCiXt+6PdVNy5+yWZucr0VKIRlc38yoy4KpFGrWxKvHYOYh1wjucj3MR54r+MPbhWW+BmT7bbQwbme87SX+jnyPDiEHNOdd9Wf/cnsMf+6PpDQTbPKeXrSqWt41v8HWaeD3QpXmcMXnUKF2yeyQLQzjxa/iD69KNcMhPrF9zISl23h/5hnSsrdOh5U/69tdH9brkPOo3ES/7UyHzVMo11jsmO+eTfOXV5Dw2mXYVYhdOGt8JhuDXK8x66Jx2vhtfe1iooL1CTNBEARBEEov5faK56+//uKXX345KkxPJ1wVKjX4hhtu4Ntvv2XAgNz+n0LR0oyrNIM7ZuoCSgmRKU9jXPIlUwd6uauVXROZXq+Py//IZsI2vb1QUegcZ2LJ8GB23RXG6MtDGNrYTlC9bkR1upnWg5+k7S3vEXz1N1Cvr/b8Zo5ljPY/yfrWf2kRTCVcH1lbQ2sjU1ppGKr3DVY/3+MEdlYybJwIi7+AtF1665n2d8HFr0FopZLdKXsUht4v4rfYaW/cxMfWj5m29tT1ttrOT3rsWK1zNd3Q6Sgqmli7h769cVIJ7ngZIW0PJK7SlvDMC6tGWxAEQRAEoSD0fiPlkL1793L//fdrTsCqPjVPuOZFVvPIu69Zs2Zs3ryZevX0th5CMYmoBrdOgUmPwupRsGkS7JrH021uocfAHlw30aGN/QPTsvm/xRY+72OlZSVl2lQ0OsSatOUk7FHQ5UHd3Xbx55qrbtD6Mfzb0ETXhAFaBHP4srpM6LiF0kjX6EwqWL0cdpl4fF11elg3EZU4R3dozkNNDnS8FyKqnrsdC4/D0PUxXDPfYIBpCY3cL4Pjj4JTkjP2Q1aSLk5bXl/w+5n1umeV2kx5F6yftge37ubdQTlI+204rVHne8/KBErkxxvc2LMrA3Hne3cEQRAEQThLSm8IqQQ5cOCAZrL077//ct999/HVV18VGHH1eDwsWLCASZP06I4I1gCjoq5XfgE3/Q0VG+qprPM/oPOaZ5nS+yAVgs1atHN/hptB47PoNTaH8VuKHnk9LRXrQ/+3oHpHrX9p9e2jeL3Sf9pDq9Ls/J5YekXBJy12EeHP4GXjt0Ss/SFXsBqgZhe49F3o98a5Fay5JFZox82uJ8nw26mbuRy+6QMrfzm5LjV5k74OqwImPUX8JDQTL6BCLco16fs0wZriD+Mq18tM6DiGPs53yAkWAXZagqM1t/IOK55gku1ZBkzvQ8+nv6XW0/+Qknlh9m8WBEEQhAuJcilao6KiiImJoU+fPsyYMUNrZ1OQcFWi9ccff6R69erneY8vcGp3h7vnQZ+XwRwESetptPAxVvTdystdg7X+q0q8bj/s5pGZ2bT6KZsFiUWvdz0lSjBd9BTU7KoJ1+HpX3ODdTYGg1+LYpbWNOHO3uUsCX6Q68wzMRr8TKQbXPkVXPQ0xDQ8b/v143ovC/xNucb9PARF6r1hJ9yjt6/55ylY/gPMeAUm3Ku/IKrOqd9MRWO155RQLW5ZIffcFG3IYIOvOinhjUhEb8UlnIbI6nDvEmZ00ds9GfATxRHtOPedoTREEARBEITzT+m8Ci9hbDYbsbGxmijt1q0bM2fOPEm4KtdZ1frm448/pnnz5ud7ly98zFbo+hDcvxzq9ASfRxM0N1XcyMZbgrm3jZ0ou1m7Zk/N8XDtX1lcOcFRLJfhAlFmUd0fhzoXaRe2rxq/ZKL1WfobFnHjstqlM/K2YQI2v4OUoJoMcz7PvY578Cmjq/PM5O16VDw9rD4M+hRa3wghlcCRpqdi//0gzH1X/w7h1aDNzad+s8zcSGtk4PrKCuWMyOociWh8vvdCEARBEIQiUC5Fax5msxmv13uccP3uu++0x6ZOnYrb7dYErnCOa12vHaWJRjwOmP4SxuT1PN7Wwsobg/mobzB2q0mLvK484KL5D9l8ucYd2H0wmqDLw9DiWk3ENjXu5DPrR7yT8wJrN2zIbd9TClDRx9W/adEizbxo4Pss9jXWxPbG1PMfPdqTrovWS2qb9VrWZsPgqq+h94t6GnZsS72WWBlEDXhXTw8uCJ8Xcg4f+30IgiAIgiAI5YpyLVoVJpPpqHBdsmQJt99+Oz179qRhw4ZYLKeorxNKjOQMJxtTvCT3/1yvycwVrhxYpz0+qK6ZhJvsXBcfpLkM+/0+3lyYQ7/fc7ToeECFa8vhMPQn/M2v4Qgh1DXup1nSBPwLP4Y1o+HAWnBmnPItMtwleHhlHNANrHxuqNQEuj9BdIgVg+rXA8zaE+AIdD4cHh9z954+PXvWHq+Wyqoi47c3NR0/rkpg93pOdzLueA80vkyvbz7lB6bpwlw5IJe087EgCIIgCIJQ6ii37sEKJVaVaFWLolWrVlx77bWam3Dt2qUwFbQckJLlxunxkeZ2EXP5p/D3fbBzHkx7DjrdD/V6YzQaeaOrlbubmxk+2cmeI242HXIzbJKBcZcFBXaHgsIxtLqe3ZUH8fvkyVxlmkdz4w5IzV2050TqtaPRDbSIos8URJ/FTdmeaUXFO4NNfmLtbq6umsJdtZILvw9K+akeq163vmQfgvV/gtcFMY2gz0ta/05tV8xGHG4v29JKJtKamOmjx+hs3B4f4UFmvuhr01oL5WdrqpfbpuhmS8E2E5VCiineM5P0dVisLnoFQRAEQRCEckW5Fa3bt29nx44d9OjRQ0sTVqxcuZI333yTGjVqnO/dK7dEh1g04RoZHA5WLwz9ESY9AusnwPz39chrI71Pbo1wI3OvsXPrv0Zm7nSyLNHFg7OMfNjTGvD9ahYXxsTmV3HZikuoY9zP9SGLuTVsKYbUnXokcM9ifclNX/jbb2OftSIzfK35x9ueNZl1eHNTLD/trsjodlupZi84pVkFiw84LexzWDiU5aNC6kriM+YT6j508pOV43KfVzRX1PxRUEWjCse3bgoESVk+LhqdowlWRbpD1RZ7aBNn5damer1xphuenevQot4qEv5Bz7NMr3dlQvJmOLRJdxM+skePriry3IZjpbZcEARBEAShPFIuReuWLVv44osvuOWWW44KVkXLli1P6tMqnFtiwmzachxKuP77DCz6TDfw8eRA0yFHH/6un41LxvvZkOziz00OaoQZeLRt4FO7n25v4UCWnz83xfJq5hV8ZxzK7Gt8mPev1KLB/gNr8TnTMeEnxOCkgWEfDYz7GGH+mwNUYIqnLf85W9B7ThMGVs3B6TOwPcvGQadFSyV2+QwE+3O0GtpLTPMZYppDmOH49jAuvwmXwUZq5Y5U730PWI5Flo84fPh9qq8wdK0a2NTklBwf3Ufn4PJ4tejx8Pggxm92a1HdFftd2pIfJVi/7R9Mn5qniYym74c9i2D3IkjecEykns4gq7yTe37a5a8EJnXuKvcVHoUdQHb5KlHTmITBaMSACaOc8wVBEASh1GMuj4JVmS3dcMMNNG3a9LjHRLCWUtRFpeo1quoe57yjt0rZsxQqNdbTcqu04O8rguj0q4/kLA8fLcuhXpRBq38NNCqKazbCuA0O9qW7aT/GTJPoduzNaMPeTC9er4dQfw7X1XPzdL1dsGsB7F1KFc9hbjZP5Wam4vRbWJLUkAP+ClyUO0cSZHLS2Lyb2oYDWtuaPLb64vje259JnvZkGoLx5B2yu6DCbz5uindTM9xARbuBVxe5tKFSr24UFdjJl0v/cGgCVb33692Cub6Jmdc6m3l2voffNriozy6eN//Mfn806wz1GNShMW1iq0GOW+srqkVL0xMhbRek7QYVoc5rY5OHamej6l2rtYUqzY8T5Jrr8HnoNVvqUC2hgJp3jWVDXEvGrkg833tUpvCa7dzjflDr1fr7vRdBXMvzvUuCIAiCIJwF5vIoWIcNG6ZFVYUyhFJjyrxHCVdlzJSUoC/aYybM0fWYX68R96+tzRJfIw5m6TWeJcG7PayYDDB6vYPD2R7mZesuuQq/38glTaJ5urtKUa4BtbqBxwn7V8HeZXj3LseWnUQ3k24sVRDe4IoYYxpiqN+PenGteN1g4PXcaOfnqz2M3ewhLdujffb7S499dh6VQ81a3W8gSXfqQrpjVasmWBXqM97sZuXNDh6Y9JHeugYYxmxYhr6cDoMRanWFRgOh4SUQKWn5+Vm6K42dKbpTda3oYNrVjAzo37S8M21jMmkHEmVsBUEQBKEMUG5E6+bNm/nhhx80waoMl4QySvs7oUYXOLBKdxTeNR9Stmq1kNZDm/jSCjl+K77wZ4E2JbYbb3e30jDKwIcr3FiMaGZDtcINXFHPRL9aJxxWZhtU76AtJlX4mb4X9q/R05zzUM64EdUhuh4me8HiJNpu5LmOVm35eKWbz1e5cHj8eH3KqMmPyWTkxqZWnusQ+MO6QZSJ1Qe97DhyQgqv+j7KTTlXsNL2Nji8TXdWzk7R0jGxBoM1DMLjoEpTiGkMlRpBXCuwRwV8Xy8UwTrk8/lq9DTUlMG4EV1oJ4bmxUKJ/zw+mLaJBL/r2NjKpIAgCIIglFrKhWjduXMn33//vQjWCwHVIzWyOlSorQtYReouzQRp/eKp2PbM01rTsOD/IPwtqFCnxHbltmYWbSl0xFiJU7UUg/tbWbQlD2V8FOjoan561VCiVZkxndDqZtMk2DlXF923ToHq7Y+JWWWa5cjQnY9VTWpoTInt34WGirAqwTq0ve5iPnbJDu2+dhUd2u1dXw6lv+d/PD6g9Xne07JFu1grv0d/CZlgM3jwY8Tg9+ljK6JVEARBEEot5cLFw263c+ONN0qE9UJARe2UAFLrPKJqQvNhfBT6AJe4/o/F/ni9hlKlEee1S7nAKUnBqri6oUnToeo/qqWNRso2WPqNvn3xq8cEa544V214bCEn/72Es6Z9rUhtOYr2R4CahiTwelixJ01Gs1D4Ccrcnbvp0wSrIAiCIAiln3IhWitXrkzjxo3P924IgUDVtKqInVqfwKYDGbiw8HzI82RH1IecwzD9RXCka49nu33aIhSeKqrXam6u6o70XKMoZTLl80DtHtDxnkL/vYTiM3Hlbi29NX/aqyAIgiAIwoVGuRCtQvlgf5peI1qxYmU29P4eZ3Cs3u9z1mu8vshJ4++ytOXLNcf3SE11+HhlkYspO082NRJOdtc+kJV7R166rzJUkrYhJUoch9i3fjFLVxzvbvXC5U2lHlMQBEEQhAueclHTKpQPcpwuLRhYLyaYZGMk39Z5j1sTbiEoaT1r967EQBPteW8syOG7dW66VTUzd5+HAxke7XXfroJ2Va381N9KsHJXEo7DZDTg9fpJzMqNtEbX09fKGVmlrYpwLREa2FKZbnuc4K3Okx67rFmVk/saC2dFXUMiTpTLN9izK2tTA4IgCIIglE5EtAoXVF2n3+flh/nb+XGeX9NQkebOXGeeydXGWRyu0II0h5+kTA8HMzyM26hHVvMcWtXzlyW6aPqDh7d6BDG0gRwe+YkMMpKS5eOX9W6eVDa2kTX1etWcVL3vqjLHEgJOiyg3GJwsbv02mfY4es+/XkY5ALxj/frotmeWHZou1U3eBEEQBEEodUg4SbhgeHtIc1TFqhFdsPox8Jf5Yu2xy63LmHq5gUXXBvFCFztx4RZMRiO1oyw808nO1jtCGdo4SHuNcuJ9bGY2by45Po24vPNGV6sWUE13eHh7qRtMFqjYUH9w7bhTv9CVBZnJ+vps7hcKpEPbDvTu0UtGJ0Bc5XyRAc7XedB1D2ZvDuxeSMLyuUybOY2J85ZpbYcEQRAEQSgdSChJKP0oUaNa3Wj9Pk9t6DO0dRzBVhPztqVySZOKdK9fUU9b/egLTCoSuHcJxtrdubWpkVubntyq5p3uVm6LNzFsolMTZl+szKFptIHL6spholD9ZxvGWNh8yM1nKx2MaGEirEF/SEqA5d9D14fBVMBYqb+dMmzS/oYhZ75fOA0GvOHV2X8kB7/BhFFSsguJajlVA6/fz/rkOlpP51R/GB6THfP4O4gHbcn22+jtfIehfbtRPSpIe6Uyu5K2OIIgCIJwfpCrcaH0UwhxM6BpZW05irqobzoY5r4LO+ZA7e6nfX2jaBOLrgui9c85ONxe7pueQ47HzrCGcqgofuhno9MvHgx+P/fMcPPzxV1h2TeQvg82TYYml588qGqyIW/S4WzuF06NNRjTI+uoBmyUcSo86rf28FpMueM3dkUij49ZyZSeE7G5Uvlg2iaG13Nz3Z6XqGDI4KNpG46+VFVyjxvRRYSrIAiCIJwH5EpcKP0UV9zkida9S/WlWruTn+N1w7YZkLSB4MjqzOrRgL4z48j0WXn8v2z+t8ysBW19fqgaZuTn/lYigsp2dv2OIz4W7fcRalHfyUDNMANGg97SZk+GH6cHrqhrxGo+9j3jQo1cVNPK7F1OFid6wBQCVZrDzrmwZvQpRGtIwZMNp7pfEM4xs5PUuSWYBL+LmNpW2KPKDVqw3lBXe3zJzjTGLtnBzpRsEa2CIAiCcB4Q0SqUfk4lbs4ybZjK8bpwXfc7zHodWlwLlZpAhbp6XeaWqbBuHGQlH31JrCrTtBqZ52/GPc77Sco8JphTsqHjKC+zhtn1/qVlhORsHw/OcrPioIcctw+DFjs6PU/NMfJQWxsPtDqWTn1fS7MmWp1uL4nr/iNOCVZFjU5F/xsJwnlApfyqo0AJUoXajovQ04HjY8OIjzvmKDx2ifyJBEEQBOF8IaJVKLsUpibyyi/1566fACt/Pna/xQ5uvb8rYbHQfBgc3gH7lmNI30c3w2p+i/yc10OexGg04fb5WbTPRY7LS7dR2ay9OZigfJHIQKHMoFYd8rMtzc+A2sZit+B5eq6LX9c7jwrVPMdkZTylb+jmVbmbue1r/Np+vLckh6/XuPhvmJ1ou5F2VUyaiVVL/wZiln+ov6j1zdD2lpM/WOpWA4s7B8+3/Vm/P4NrvS8z75l+RAXrbVuEsxs/vr8Ej89Pi72P4cTG9ze3JyXbfVTExlt2ylAKgiAIQilDRKtQKknOcJKS5SY6xHLqPpSFSRtWEdXB30GNb/RU1sRVkL5Xv4gNi9NNhFrfCBY9yqKxZyn8cCnxjuX8Wm8MtLlZu3vURjNPzc7G7fXx60avZuwUKB6c5WLiNhcer4qEHot2/nypnc5xqhKvcCjROXSii+X79R62SoxeXNtKr+omelU3Uik3Uqyel5Sjpz9XCdbbB21L9XHHdCfbUtxkOLzcN9PFL/0t+Pcu4Qvzv3Q0JGDBDQ0HwMD3wFjA/kndapGwZycSb9hBZJoVzKnHHvD7MB9YRXODmoNRv5MzR8uFfPh9kLhS+4dPGz+MNKsafvw5JlFGTBAEQRBKGyJahVKJEqxOj09bn1q0FrImUjnbdrxbXxRZhyB1l54+nF+s5lG9HQz6DMbfrqcPR9eDWl25tpGZp+eonjp+TAF0b/11o4c/Nzm0IKcW58zVI16vj2v/zuLuVnaebn+y6/GpOOLw0fd3h9aXVtGwooU/LrcVGLVVIrVK2nJY/yfU7Ar1+lA3ysTMoXbummbk3+0OnPvWseSn3+ho3Ejf3Lc4HNWCCoO/LliwKqRutfCk7aH/rIEMtOXAnNz7LMEQHF2ENxMEQRAEQSj7iGgVSiUqwpoXaS0xQirqy+loPhT2r4KFn8D8DyCiOkTV1ASlEpZhAcrMzHb7eG6uLlij7Gbe7mGlU6yRjYf9XDsxR4vqfrkyh//2ePj1UpuWpns61iZ7uWqC/jq1r/3r2viy7ynEv2L3Ipj9f3oKdeJKWP8HtLoR4lrzbtx/3L9vEk0Net2fw2/hB29/dlTsyWM3XyO1qoEmO0XrG6r6hw7s04u+jWJ0wRpZXXraCoIgCIJQLhHRKpRKVHT1lBHWc02fl+HAGr1lzvQX4KJncq2a4EBW8dMzVWruwD+c2lq92+jLbDSI0iOXbavAyhuDuexPJztS3Ww65Kb1Tx4G1LPyXg9LgfW0365188oCh1a/qt7viY527m15GvG/az7Mfhv8XqjZRXNQ5she+O8NMJoJ9XloqgLLRgv7ag5iXPhNJBljeH1AQ8wlUM8r6Gz1VyUtMh7ymQEJgiAIgiCUR0S0CsLZpBUP+V4zcOHQZpjyJNcG3cNvjo68tdhBnUgD/WsV7VBSKbyXT3CyK003grmmSdBRwZpHqNWoORW/ssjEd6t1M6XJW51M3uaiQbSZLnEmrqhrYvRmL2M3urToqooCGwxGfrzETo/qp0jd9Th0R2XVqkbV+jUbCld8Ae4sWPAxzHlHj7xG1ID2t2NoeT3VQqJ5SH4xQnlAHesKLS278PXkgiAIgiAEDhGtgnA2qDTi22fAnyNg40T+j48IMx/ma8+l3DUlm6oRFj7qaaVtlQIubo/sgx3/QXoiuDK1JSfHwUxnI17LGMh+orUU3gH1bbzV7dT5xi90tPJwazP3zXTz3y4XBr+fzYfc2vL9mmPPU+8VF27h1wE2akcUEAlVT1BmVMu/P9bmp8V1MOgTvTbVFAG1e+iiVdHjCWh9w9kbZAlCWUaJVFVDPP4O/bYlGHuPv8/3XgmCIAhCuUZEqyCcLUHhMOxn+OcJWPo1z5pHMsC8hGnulvyX0YIhf9akRSULf/RzYHQegYMJsH3WsYhNPuzAAHbR1zadMd6L2F9nKI/3rHbGXQizGvmxv40DWRbeWeZhyX4v+zK8uanFBlpVsfBGVwtNok0Fi9XkjbpYTVqv3xdRnfRuL5BY9RKiszzE2BywaxGMHn7sder5DfprTsApWf4zG2QJRSNtj1bPWtDvJT8+ezSp2a5j7YqEwhEcrblk+x2GgsdQ1Q7fu+TY32L8Hdhc+RycBUEQBEE454hoFYTCYDRCjyfBHgVz/0dL/2ZaWjbzOGPI9AdhT3diHHdCnavBSGpcd45U6cz0XV6WJOrtZ262TKOTYR3Xm2fA3tmwqB80vxqCK5x+H9zZVDG6eLezDUxWLTqalOUj3EbBPWMPbYHtM3WzpbzIqskG3R+DzveTmOI9JkRTVsO4m8CTAzGN9Yv2fct1AV45nuiQ8JI3yCqvgvXT9trfVuEx2Un1h538PGsIxie3oxJWN577vSz7KDfrJ7ZjPNP4KeGqFkEQBEEQSgUiWgWhsKjeo+3v1J2Fd86DLdPxb/+PUFULqiJhfgMeewWcYTU5VHMAKbUG4rbHMH97Kh/v2aQ5BDeuFk2n+16CXQvgv/+DHbNh0yTYMhXqXwxNBukpyUaL1ltVa8+ze6G+HFyn16AePYrtVGp6FTS/5uR9VZFVFRnOe74Sq+q5vZ6DCD2yGx1yLOWXiS+BMwMqNoC+L+uOyWofN/6ttQCKsZYig6wLCRXVU4L1qq+1sZ+y3UPixIPne68EQRAEQRBKBSJaBaGw5PUeDY3RxV3bWzF4nOxcM5+hoxM5bAhnQJPaXNv2mOvrwQwnH8/coulPm83GhLvb6w/U7Aw3/QU75sKMV2DvEl28qkVhMII56GgErkBUVHTVL5B9GDrcfaxnqjMTln6jC1blCtzpPqhzkS66T+XUrISs2gcVZVV1ffbcqK8Sz4XpiSsUDfV7imtJzoFE9auRUSwlhGduJ97gJjLNCmleicIKgiAIwjlGRKsgBORIslGraQei5qwg+UA6f6/eR++G0YTZTExYm8TENfsx+H34DUZG3tIG64lpvLW7wW1TdYMkZYCk2usolODUBKsBqneAxgOh0QCIrKW7/7pzIGE8TH4cNv+jGz11fQSO7IFZb0DmAT26qkyWKtQ58/doPkx/v51zNDGuCWFFblRWOM+4c3D/dBUrdqdxB88y+8mLiQoOULPg8oA6XkYOwe3z0Wb3vTixsejJHqcew1xTpg4rnmCSmtdRh+XCYL3mVdKHBUEQBOGcIaJVEAKFNYQPrm5J/w/nYPR5eWD0avx+n1Y/l+eD9L9hLWhXK6rg16swbO3u+uL16K1nXGrJBnukni583OcF56Yq36FfXCu3UyV6VUqw4wh4XRBZA4b9dLxgzXtP7fUnRE/r9tajqzmHYf9qyEnR74+qKb+Tc0DC/gzWH0hkyc60gp/g92HZs4AOBnA7nHi8xe8TXK5Qk0C75qEqst3O21ENpE47hrmmTNNWbOSDaZt4oZNFE7BaOreIVkEQBEE4Z4hoFYQA0iQ2jPevbs3Do1di9Ov9UpVDac2YcB7tW49BzaucfW9Y1XomKOLsnq/qVNWn/Xn3MbOl+v3gyi9ONnZSglX1X9WE6wmi1WzV30ulFSvn48zc91LGU0LJuAUrch2Dnxi3mgR/uratpFSt6ONTuYXzQGR10iJNJPhdpIdKVFsQBEEQzgciWgUhwAxuFUvlcBsfztxOvyaVuLFDtWPpwKeLchaXBhfD8HGwdTpUaQbxV+luxyeiPjtvHwqi2bBjojWPsGP1uULg3YLzOwYPbV+b9rUiNcHarmakDHcpIiExk765EfF4OSQEQRAE4ZwholUQSoCudStoy0mcLspZXNT7qdpYtZyKnfP1frNK1J6K6u0hsiak7dJvh1aGsMqB3ddyzNJdaaRt20hfdzaLW79Neqieur0kyUTiqhxNsA5tLYqoNKEmEFTke1rCPh6y6RHxlyo2k0kFQRAEQThHiGgVhHPJmaKcJUnSBvjhUrCoXpXbwGI/dW2tMmRShlCKSo3FOThArE5I4KWRs6hn2EdfK7yy0K2lneYhKcGlExXxHjeiC2nbrLoZk5r/SckW0SoIgiAI5wgRrYIQaE6XApzXLieQ73mWpG9fSrjaUAZPGftP7yaszKDyRGtYbJE+TziBtD3Ej+/NJFvO0XTgEQM6khN8LKoqKcGlFy1V2xJzVLSeGD1XIlYhf0NBEARBCDwiWgUh0JRECnAA3jMrJ0cXrWf8rCy9x+tRlJ2UUGyyUzB7c3jQdQ8D+/Sib+tGDCyCA63fHEyO26tFZYUiYAnWnLzV+BV1DFWkPDItQevZuvRIGEM+n3/0KFHvqaKyUo8sCIIgCIFDRKsglLIUYJ/Ph/FEA6UApBWH2E+RDlygQPYW+XOE07PVX5W0yHiILELdqjUEw3P7Ub+CjTLQRRo/nt2vCcwijV9wtBYh/9D6Gcz5DM98O1Pr/6q9nzLQUoxdskNShwVBEAQhwBRgLSoIQrEvjENjCh0RTUjMoPFL06nz7L98NW9XQN4zP+Fh+eKshtMc+koYmyxn91zhzC7Biav0JbetjVCGiaxOwlUzGOB8XYuYq8j5gtXrtejqsDZxmomWIAiCIAiBRyKtglAK+G15Ik+OW43B79Nuv/73OpbtSuOLa5udHHUtKrW6Qb2+EFIRImqcwYW4OzS4BFJ3QMtrA/P55Y3TtLURyi4t4uN56e6qpG1bqkVbH+rbkMi67bR04IN7thJv2EFkmlVLHVYiVxAEQRCE4iOiVRDOM8kZTp4YuwqjitcYTIQEWcjKcTB17V4+jg3nwV562mGxCYmG68ed3XNVtPW63wLzueWV7BRNsG7r/gHbqXZcW5si43bgHjWchdtTecjwBLMe701EcL6ouHDG8WPMDbi9PjrsuAOXwcr8x7oVegzzmzL1rZgKlp2w9RD9Z13PQGW0pcyaFgbDvUtEuAqCIAhCABDRKgjnmfUHMjXBqsxhPrm2BRWCzdw6cjVOp5Nlu9PO9+4JRe7Fmkxf4IFpWYFra+P3Ytk+ne5ATk4WLq8emRfOfvzYMhUlUXMc15GDt+hjGBytmTox/o5j95ns3Oh6kns7RtNhxRP6xIVEWwVBEASh2IhoFYRSgt8AFUOt2rbVbMLpBJdHDJHKei9WxQN9G1M9KkjblpYoFwhKjKpIqhKmuUzZ7mHOxIPckHscC4IgCIIQGES0CkIpweCHtGw34UEmLX1R4fJKY5Oy3ov1jet70iL+ND1xhbItXPNFUnMOJAIHSUjM1KLs0zYmk6bdpyMTFoIgCIJQNES0CsJ5pkKIXk9nMMBdv6zQjZdyW85E2qVesTSnAO9MycaenYjNlardF565nQ4n9GJtIemh5QYlStU007SEfTxkgw+mbTqaGh7HIaIMGVzbsTaVw/RIbFxEEPGxYXqqsfxOBEEQBOGUiGgVhPNMs7hwrcfj2KW7MCr3YJ8Xnx8aV6vAB0Piz/fuCadJAY42pPOF5QOCDc6jj2X7bSzxNeL6uu0gUlqglCeUQdO4EV1I22bVzJhe6GQhPdSqTWp0WvIEFp8DVp78OhWR39b7SxrWqlmggM2bIFFItFYQBEEoj4hoFYRSwDtXNeHVgQ155Z/NHEh38mz/+tSNKXpPVuHsyS8I8qMiqLXtOXokTPXR3Z9B4hGHJkA6Lr6fSTbHUcExp93XOK1R2m21/qh6Pd1hVih3aH/3iEaae7BmxpSHJZhNfX5it0M34TqY4WLUoh1HJz4aTr3x6O9pQbuPiI6J1X576nf30rjVx33G20NanByhVS2W8tXXSvRWEARBuJAQ0VoK8SsbWSA9Pf1874pwjnmqZ9XcLa/8/U9B3nGRd5wU5zhavjuNG79djOGE+6uQwl+25wg2uMh7tZIGefGvw34rD7of5JHLO9O4dg1aRlY75X4GFFcWOPXv5XVmk5Gejs1vC/znXKicMH4+fCUzhsYIuGEG5Bw+dp+9ArGR1YjN97SqdZux+3AO3xxsy8SFq6lgyOADy2e0nH279nh67m9u1InvP05/DLMdrvpKv2/8neDJ105JPXbHLCjgt1mY40gQBEEQSgMGv/yLVerYu3cv1atLU3pBOB179uyhWrWCL8jlOBKEwBxHgiAIglAaENFaCvH5fCQmJhIWFoZBufOUAtSsvBLS6gInPDyc8oyMxfkdCzXPlpGRQVxcnG5aVYaOo9KC/IZl3M72OBIEQRCE0oCkB5dC1AVEaZ35VsKkvIvWPGQszt9YRERElOnjqLQgv+HyPW5ncxwJgiAIQmlAplcFQRAEQRAEQRCEUouIVkEQBEEQBEEQBKHUIqJVOCtsNhsvvviiti7vyFjIWJR15Dcs4yYIgiAIZQkxYhIEQRAEQRAEQRBKLRJpFQRBEARBEARBEEotIloFQRAEQRAEQRCEUou0vCmFSH9JQTg10qdVEIqPHEeCcO6OI0EQio+I1lJIYmIi1atXP9+7IQilmj179py2D6scR4Igx5EglIZ/jwRBKD4iWkshYWFhR0+Cp2tgP3tLCq//swmHy3v0voax4Xw4NJ5gq/xphQuT9PR0bVIn7zgp7nEknB+mbUjGZjHRvV4F+ROcB8r9ceTz4t6xiKkbkzkQ0YIbOtbEapZIWWFxeXz8vGgXVY6s5uJGMVhqdwSjifLC2R5HgiAUH3EPLqUnwYiICI4cOXLKi+3FO1IZ9uVCDPhPesxoMvPW4GYMbR13DvZWEErf8VGY5wnnls/n7OLDGVtwOJ3a7bAQO89e2ohr2sj56lwix5EgnLvjSBCE4iPTimWU20eu1AWr0UTzmjHaUj+uAj4M+LweHhu9ksQ0x/neTUEQhKP8unQfb01epwlWv1/Vg0FGVg5PjlnJwh2pMlKCIAiCIBSI5JCWUbIcbm19WYuqXNf2WIRi1+Ecnhy3GoMB9qTmEBcZdB73UhAE4RhbkrO0td9g5KXL4sl0eXjn340YDX62JmXRqXaUDJdwbvC6cS3+ljEr9jMn4nI+uLqFlNUUgWyXh4dGr6b7kb8Y1joWa4fbwGQJ/N9LEIRyj4jWMo7FdHywvGYF+3nbF0EQhLPBbDLRqEqItm1QM2wq5CoI5xKvC+vUJ7keeH1vc7KcTUW0FoEsp5e5CTv5KugDmAq0vUFEqyAIJYKIVkEQBEE4FUpQOzMgKxkcR6BSE7BIBosgCIIgnEtEtJZRjAYDPi0dOPu4+39dlqilBivCguTPKwhC6SE895zkcbv5esEeUrPdqjE1GCAyuJSlFKbuhD9GQOIK8OTzBwivCgPehYaXnDe31pt+XEnikZyj9ym3+C+Ht6BGlGTaCIIgCBcmYsRURmlXJ1pbL92ezNrEDDYeyGLsygP8tWK3dn+VCmE0iRULdkEQSg8jutYkxB6kTazNTNjHyh1J2nblqFAGxMdQqlj2PexecEywmoPAEgzp+2DaC+dtt+4etYaFWw6wK+nI0WXD3hTu+mX1edsnQRAEQShpJBRXRvnsmma0fDUJo9/HG5MSjt6vLgBDg4OY+VDnwr+pKwtc2WANBqtebyYIghAogqwmVj7bk8s+X8ymfYe1zNvODavwy82tMBpL2RyqVze7o1Y36PygnhKctAH+eVyrhzwf59P1+zOYnrBPm22OCA2mQoiV1GwXaRnZrN+Xisfjwyy9Ri8Ilu5KY2eKnklVKzqYdjUjz/cuCYIgnFdEtJZRooKt3NatLt/O2XqciUlEqJ0ZD3UpmqGEK5uUjGwOO7KIrGgmJsyWe7+IWUEQAoPVbOTf+zvx5bxdRNgtpbM/qzrnuXNLL0IrF62GVQlWnydXuAZGtN7y00pNsBpMZj4e2hSL2UiGw8PtPy/TJjC/WrCbe7rXCshnCedXsA75fL7KmtdQ/8KPG9FFhKsgCOUaEa1lmBcubaAtAcMarAlWB0GkZLnzidbAX3wJglC+uatrTUot6lznV64BgDP92P1+79m/h4qw5kVaA8SBtCxNyMRGBmuCNc+7wGQy4/d6WJeYEbDPEs4fKsKq/s5D29fWbo9dskO7T6KtgiCUZ0S0lkVKKvJpDdEirEqwRodYSvTiSxAEodSiznVRuRHLLVPh0Gao0UlfKyKqn8V7hAR8km9w2xqMX7qTfYfSeWf6dqJDrKRkuTTBqhJuRnQvxRMBpQ2TDdew35iw5gC3RMUTZit9l0M9KmVjc6Wy3rCDyDQrpHkh8ix+e+cQNW639IxnbOoHDGpeBaspd7JbEAQhwJS+s7RwZkow8qmiq0cjrKe6+JJ0YUEQLmTU+a7TfXBgLaz/U3cSVovCYILuTwTmcwp5Ln1vcDzzthwiKS2TFTuSjnusUlQozeLCA7Nf5QGTGWuTSxjahFJJHIfoP+s2zN4c+qp/kucAC4Ph6p8huCIERx8VsOez/lXVqT/RrxGgFkEQhJJDRGtZ5HxHPiVdWBCECx2zFYZ+D1n/gy3/wsZJsHshtL8TqrU5b+fSv0Z0YOBni0nPcR1XJ/z+0GaB2SehVBBlyNAE6+LWb/PKQjdP9qhE9+UPwsjB+hOUk/W9S1h6JEzqXwVBKBeIaC2LlEDaWeE+X9KFBUEoJ4REQ8vr9KUUnEurRASx7Okegd+X8obXjXPlKMat2M+yyH68fkXTohkYljDpoXVI8Ls4WKmVJlLJTtHT1MffoW3vTDGd1/rXbJeHZ/9cR9u0fxnSOhZbq2vBVMp6LguCcEFQynoMCCWCSkHLTNbXRWX9BHi/KUx5Rp/hDY0RUyZBEMofgTif5qEmH+Vcen7wurBNvJ/hiW8wZcU2spyFMNk6X6h04LiWUPFkA8b2tSK15Vyjxk2NnxpHNZ5n1Q5KEAShCIhoLQ/kT0ErLF4PTHsBxtwIR/bAok9h7v9KYi8FQRBKHnUe9DjPz/lUEARBEIQiIaK1PKBSz4zmwtfAqouykVfC/A/123Gt9fXM12DlyMDvpyAIQklFNTdMhM86w5tV4aNWcDDh3J5PBSHQHNpMZFoC8YYd2LMTZXwFQbigEdFaHihqCtrqUbBjDpiDoMeT0PcViL9Kf2zWmyWyq4IgCCUS1Zz0KCQl6P1X0/fBkq+L9j6S0iucb5RzsCrTGX8HfecMYZLtWfrPGijCVRCEC5rS5zoglA5UZCNxpb7daADU6qZvNxsGCeMhfS84jkBQhHb3r0v3sSU5i2CLiVCbGZvFiMfrw+PzYzYauLp1HBHBYs4gCMI5Nn07vBP2LYc+L8KfI47dX72D/CmEsomqbc01ZZq2MZmJ02fyofUzraerIAjChYqIVqFg1IXi4e36dnjVY/fbQvUecdmHIGkDnrj29P90EVv3n/4fyzcmb+Cly+MZEF/p5D6wgiAIAXJKT85wkpLlJjrEop9rfr8N9i2DLg/DnbN14RpcARoPLJVjftL+CxceaXt0F2BFvn6rhUK9JrI6aQcS2erfdMqn5e/hej76uAqCIAQKEa3CKX4ZNji05WTRqoiqqYvW/at5ZFHoUcFqNJnxo7Lv/Kj/KQwY8Pl9GH1eXvhzLVGG2gxqVUOchwVBKBGU4HO6vWRtX0lM4kRdsCrmvw+1usA9C0+dXZIX1S1uS7FivJe2/x6fthbReoEK1k/bgzv7uH6rRRKuZ0AJ1iGfz9da4uSh/mUeN6KLCFdBEMocIlqFk8lJg/F3QlaSbjgSWfP4xyvFa+l2/pmvsTTzbaVqqRsbxWsDGxY4mjtTcnj6z3WacH14wi461YigUux57DMrCMIFS5WUxQT/+wjW9J0nPzjqWrj2Nw5U6sp13y9n16FMokJs1KsURrtYKxWDDTi8BhyGYKxmIze0r0pokLl4tbgFidbTiFoVYc2LtAoliMmG68rv+H31AYZGNiLMdo4uh1SEVQnWq3JrqnP7rZaEaFUR1rwerqodzpKdaQHv46rGbWjnRoxKe4PBLapgNUl2gCAIJYOI1vLGmSIAiatg7M2QugNMVujykJ4SnJ/4K2DXPAyHt/OJ6V2u8TzHvd1qnfIja0Xbee7SRrwycT34vPT+egNLn6pMkNVUAl9QEIRyeT5TEavFXxD57zO62ZLKFqnWAWp3g6ptYPbbsGcRnl+v4SnXI2z3ttDe4tARD4eOZLEoN7EkP/83OYE6lSO4p0dtBresgtFoDEwt7mlErYqunjbCGsiIcHnGZMbaYjDX6j+Dc08BvVZLCiVYh7aO07bHLgnse6t/x1+5PF5dGAT2jQVBEE5AROuFTv4LHFWjuugL3UBJNQBXF01qbQ0FW5h+AbTmN3DnQEgM9HwWouud/J5KzPZ4ivQ/HqaNcQtvh/xClfCup92N+NgwbutWl+/mbCUj20GfjxYw55EuZ38RKAjChUlxRFie+MtOhVmPwepf9fvr9ISO94DFfvSpGZ0eZ+W+t+juW8In5g/p5PuEpvXrkJLpIjEth0yHC7/fr5U0qP/7fD6M+NlxMI3Hx6zk+Qk2Zj7clbjIoOLX4hbHYOpMUVyh7HFo87FtVeOKTOgKgiCciIjWC528CxzV6/DbfuA+i36HlZtqohT7qdOHMoKqcJ/zPn6wvs2Vvqk4x3chtVofUmoNID2mrSpwPek1FzeqSGKagylr9rL3UDo3/7yan25qVdxvKAjChXCOStkOaTuhQX8wnWVqrBJ9WSkwYQTsnAcGI7S9DRpfDoZjlXxKgPYZ7yUl+z4mWp+lkXEPy8KfIM3al8Mt+mjV97asRG2x5CRhdmdicGWQcSQVjyMDuz+HEBwEf+AEq/3YRF9ULbjkLYiuW+IGU/m/81dzd7H5sBtMydpdkXYzj/WuK9krhcHrwbVugpYevCHyIp7p36jEx0/VmKZtS6YvkLA/g/i6tY62rsnDY7KzuX7u5EsZwOHy8saUjTRO+09PD246SItiC4IgBBo5s1zo5M3o24P0C0G3KvpqDjW7gCVIr1lVkVX1HCVo7RWgQT/9/tMwP9HHHH8LnvPcwuv2X7FlH6DK5pHa4rJXIqXmpWRWbIHR48Doycbk0U0nngk10T4mjV2pThZsiOf9mRE83KvOORoMQRBK5TkqcTX8di040vTz06BPILbFGR12K5qyqPjX7bBnsd5PuudzENfypOffPs3NwUwPfr+ZJTXvpFHSO9ich6m8dbS2nIqovI38TjauTH3JPAApW+D7tXDTXxBTcE1/QCPNriye/XszvyxNPOmhjQezGHmzTAKeNV4n1j9u5VqgseM77u9Zr0RFa54pUlPDDvra4Ilxq3np7ma0u3cJCdt2arfrGfZprWuS1kyjXv7fHGj1qKXRATjD6WHsgo1sCHoGVMOBxokiWgVBKBFEtF7o5J/Rb341LPlSv+Cq2+u41LnCsmi/T1uP4WLeuGag5iTMrvmweyHWnCRiN/5wytfepv6jAikWWPdfTbakDaN+n9sgPLbI+yMIQhl2U80TrIoDa+CbvtDvdWh3+3ER0zyUYPWm7yd0yg1weIMe+ez9IlRqfNJzv1rjZsYOp/Y23WrYuLFXK/D9BAfW6ees/av0aJcqiQiNAXu0fs5U50d1v7a2c8tMAxsOG7EaPPxyMVS3ZcPSryF1J3x7MdwyGSrHl2i678ItB/l5aSKqqMJgMmMx6f2wfV4P8zYdwOPxYTZLyUVpJM8UqW98Vdh67L52Nauz3mAiwZ9O5xZN8Gz5XhOuGpZgKlWOw89OzUAprx5VOQA/2Lcx1aOCjhOzgiAIFzIiWi908s/id75fr1lVta2z/w96vVBgGu+ZOJDl4/fNKmQLFexGvca1Wjt96XgvJK7UjJrIOqSboagIiFrUVaPPB34vnuw0fPvX0NS4C9a8A2vfhcaXQYe7oUanAi9UBUG4wEjeDN/10wVrVG3o+jAs+1afBJv8GCz/EWp21p1VVa2f38++lCMkbN5Hj9TfCXLvJ8sShafnK0RUqn3S2ycc8vL6Qod2OqkYYuan/rlpxyqTREVkC4jKnooPLvPR8qds/H4fV80zs/T6YLj4DZj2PBzepn+PW6ZAlaaFG4NC1LfePHqbJlhVe7Fvb2hFkMXEkRw3d45cjtHv4+M5OyVzpZQTHxd6VLSeSIMGjTD3X3pcD9cWkdUZN6Lq0V6re1IdfDhtAx9N23DsPeWfS0EQygEiWi908s/iqwu/68fD95dqLWtYNRJa33TKl25N9fLobF2cBlsMBFtgdZKX5EzPUU3ZOPoE0atSkKu315cz/PBGTDpEhf1zuNI0j7bGzbB+gr7ENIbWN0Kdi/TIiQhYQbgwmfTIMcF68esQFA59X4WNE2H5D3Bwrb7kQ3WNHpy7vdNXmeszn2bvXxWZcIWXFpVMx9Wx3jjFiQG/Zvj27+CgYhm/RQQZeb17EM/MziYp08PudB81wsP1/Z7+gm6mM/d/MPTUWSbFqW9VUVSHy61F62LC7ZpgVYTZTBgNJm0ycPfhnKJ+PaG0oP6dPqH9jUoFzp8O3K1ehaMiVtHEHw5/n9O9FARBOOeIaL3QOXEWv1pbuPJzGHcrrB2r91xV9xXAbVNd7ErTRWt+lIY0GAx0iLPwdZ+i9RIcv8XD5L1WDPRhZYVLmdzzAGz4C7bPhuQN8O/T+hODK0KtLtDyemhwcZE+SxCEUsj+NbBzrm6e1Ot5XbAq1G1lpKTq7g+shZStkJMKzgwWH/CT5jbhxEyaIZJPvVdwwB+uCdOrJuQw/7pgqoQYdeOlcaruVdWxwhvdgohWWSHF5LpGZp6do97Hx7frPLzc2aq3BFP7qwRr9mFKCpX2e2OXuvw8fysHUzN45Pf1Wg/ZDIdbE6w+PzzcW/wBygMnilgSk87n7giCIJwTRLRe6BQ0i990MOxaqNdjzXsXLvsYQioe9xSHx8fONI82q18h2IzFCA4vRNsN3NHMwtUNjEWOWiw94OXhmTnae6toweiBVrDWgs4PQNtbYdtM2LMUktZD9qHcCOxfcPlHegRWEITSy9kaC83/UF8rcRpa6eTHVTqwyrZQC/DxSjfvbtcjife0tvNEOwvqbDBvn5fhE7Px+nz0GpPDkuF2LhnvZM8RfcLt0no2rmkUuH/qakeZ2H7Yx5hNbp7vaMaszoN5xnXekyf5Ajlmr17WkEXbU9iyP5X9h9OP36/KkdSIKrpPgSAIgiCUZkS0lgcKuCBK7vwCYTsWEnRonZ6K1+bm417yywavFr1Qhg/zrgkiWKnWAHH9ZEfuexuYOsROmDXfe1tzoxZqUReAyp1z87+wbQb8dT8YLdBS+T0KglAqKcBYSLn9rknMYP7WwzzX0YJx3ThIGK8/v9nQM77l3gwf/1uizhtQPcKiCdY8ulY18VYPO0/+l022y0v8d5laNoiKsA5qEMRHvawB/XrPd7Ry8yQ3OS4vDb7NpmG0mfuiDQxQD6q+10XpPVsIM6YJtzXlzt/Ws/2wE6/fgNfnJ8Rm5rsbzr4+VxAEQRDKGiJaywMFXBAdznTgrD+Uakq0Jm886SU20zFnhyy3qmkN3O4o/evUukj4ufIvB6MG2GgQVYAhlKqPrdSEreYGbN9n5mLHvxye9jaGBoOJCg7shaggCCVUkuDzkblzBevG/cBl/mUYl+ZzoanVDSqcOaV16N96bapSo+Mvt530uIqkzku0MXGL7hKs6FzdFnDBquhZ3cQVDYP4c5NDS0PekOzir5QcBlhhxZ4jjHhrNjc2MnGPdSKGiKrQ8FL9O56uNr8QZkzBOBk5rKYe3VVux0LRMFlxDvyYcSv20z+yLiG2ku3ReqGixq1/67r8kvYMQ1rHYlPGjIIgCCWAiNbyQAEXRNFWF47wavqNLL1BfX6ua2TkuXkGDH4/ryzy8HEAL/4WXmfnmkku1h10aTVnfcd46Frdxpd9LITmi7qq6Mq9M1ysOugigiEstc2gQtZ2+r3yLbuD6vPb7e1pUS23Dk4QhCKR1/M0OsRCTNjJgrDIJQkq1LngE1jwEbUzD/Kg0mzKQNxvwBjXQk/7rd3jjG/31lI3+zPc2tu90DmImOCCsz4G1zdrojWPaxqVnAj5sKeVe1ua+Gatl//2eIjOydDuT/GH403dR6/lb2Aw7tGfPPU5CK8K9XrrtbsFpUKfpRlTYQWucBpMFmxtb2R4Wxh+gQ1UXhucc9EOJ9hq5v1hKsovkX5BEEoWEa3lgQIuiCpGRUGtBvoN1ZrG5z2u/Y2qV20fa2FJoou/tjgYWMdIv1qB+bmodOBJVwbx20Yzz81zaH0G5+9x0vQHF40rWkhz+Mlw+chwqhRl7TqXLFMY8wyt6c0SrjTP5/8cNRj61WLWPNerRBvCC8KFjhKsTo9PWx8nWgub4pof9bq/7oN1v2s3faYgprmaMsvXkpneVizqU/2sauKVg/lnK/S04PrRFm5rduqUjy6xx0cye1Uv2X6lKjvk7e7q3GOF1U5YBXHhFsZlv0Yt/z6S/JHs8FehtXELlvR9sOIn2DIdrhkJVdsU/YMLI3CFckVcRBB+XCf1dK0VLRMcgiCUfUS0llfURU/leD3FTKUOH9kDUbWOe8qjbS0M+8ulXTA+NtsZMNGaP6VvSINgHvnPwwSV1uf3a6l2eWiC1WDk+ngrL3YyY97TG/5bwi22mfzt7UCCqw7P/L2R9wbHB3S/BKE8oSKseZHWotZZnoRyJ9/8DxhMpDW/jQHrerDPfUxU1v0mS5ugujnezJD6BZu6zdrj5bYpyrDNr50Hxl52+iiw1Xz8exxXK1/SOI9oq/isRfrNoIrc732BRekVsRuctDdu4quokQRl7NVbjj24BsIqn/w+xZkoEAqH14Nr0zQmrDnAjqhOPNCzfpmfAI237Gfy0Fh25NjJCY7T7lOC9Tin4QDjcHn5aNYWaqcuZFDzKlgb9gWTXFoKghB45MxSlgj0BY2KrNbpCVunwZKvtH6DLq+fj1d5+Wm9m7RsvR+rSsvrVq1kfirKeVPVnT3TwcyDs1wcyPJT0W4gNtRAwygjdzQzEZR3MVqtvdbP0Za6gzG217jd9Sj7Ugu48BME4axR0dUC04KLmoa6dbouWI1m/q7zIvcvrqfFe9R5JO98om6vT3bxxH8uHv/PQK1IM5fWMWttW/Zl+tiT7tfKApTMVYZtH/QKIirozCK0aSUr65JctKxyjuvqIvNN+IXFYrv4dUaHVmLKTg93TzUwx9ec9qmvsKzCC1gz9+qtfpoNOfl9ijNRIBQOrxPrmGtQNmCNHd9xS+faZVe0KqdtSzCMvwM1hRuvtu9dclK/15Igw+nh+1kJbAh6CJQ9xjOJIloFQSgRRLSWJfJf0OTdLq6AvfRt+LQjHFhD1oaptFrYBZfHpz2kLjBV9OKJ9jZuP01aXiBQvRVHDww6/ZOUMVP/t+C/1wnZv5ofLG/xUbbar4L7zAqCwDlJQz1aF2s3EjP1ee2+n7z9eGFdXT1B0WDQ6lFVem9ipo8PV3qYusPD4RzVVsuv9YP+fMXx7WKUYLVZTIwZGESLSmcnJn4bYOWPrWaGNzqHUVZF3V6wR0VZDXrrLrse2epfy8zIAcFaS550XxBjjjThetNeSFxZsGiVelWhKChxqkRqdgoc2qyJV237HIhWQRCEc8U5/pddKBbqgkal8+Zd2OQXsEWN3FrDoMcT2k3v0u+I8KRoNTB1Klj4rG8wm28LLXHBWijUd+/9Ev8ZO2AzeHjk8Cuw/IfzvVeCUK7Jq4tdM+kzrb9ymj+Ed52DtKhq1XALC64LOVqPGhdq5K1uVlbeGMyqm0K5q5Vde45KATabjITaTMSGmelZy8bqG+1nLVgVysjthibmIveQLjJqQq33i9D7haOCNX9Lns/72rWI8WqfHpH17VtZ8PuoSQLlCCxRVqGwKIEa1xIq5npVCIIgXGBIpLUsRz6K6yCZJ3xbDid95R+Ep65juGkGlrY3cG/LUiRUT8Rk4VXrw+zP/JJrzbPg7wdh1wK45O2TLhgFQSh5ooPNeJd9T+NNb2rBxk89gzAFR/LDRTatRcypUCm/T7dXSyk+3wQAlfr8zkV2ls7Vb6fu30Z0ZnIh+rhKrasgCIJQvpFIa1klEDPyeZHboHCmWHppdzUx7y3dgjWXi+vYeNpzO++6h+I3GGHNaPi8C+yYc753TRAuDJRQUsJKrc/wvJjpD1BlzlNYDR7+9bbhJ+/FpOZ45R+YfAyrepiXrCO17ZGOzjhcrrPPlAlEZo1w/kjbQ2RaAvGGHYRnbpe/hCAIQhEQ0VqeySd856ZW0O5qbEqkLPBgKxN+jHzsvZIfqr+umZ+Qvhd+vAymPANux/neRUEo25yNUErbDd/00SeN1ORRm1twdH8OBzb8fj83Ts7iu3XH16qWS1RLsbn/I8SfzXJffT52X8Hz0w+efaZM/tIQoWyRtgc+bU/fOUOYZHuWDiuewGOyk+oPO997JgiCUKYQ0VqeUBGTw7sgdddJ0ZNlmRW1dZz/gH6hWspRjsINK+rZ7a9vq824hu+xq8rF+oOLPoUvu8OuRWeOEgmCUDShtPlfXbAmrQd7Bej3BjQdzKB6FiYPDtZqOJWZ0isLHHh8urlbuSXhd32cLHbej3wWD2bGrUrCY7Sf3eul1rXsogyR3Nksbv02A5yvM637OKb0nEgi+r+5giAIwtkhorU8oSImrgxwZhwXPfH5fFj8en9Uo9+n9a8rCzzaxqIZvXi8Ph6b56fHzpu51fUYSf4IOLSJ7O+vYObfI7XvJwhCITmVUFKTXr9eA78Og8yDen/nAe9B5abawweyfDw+x625Aiv8Pj+5huTlF+UWDOxqeh9De3VADYff5+XrBXvO956VX0xWXBe/xciKD9EtvhYhtpJtd5MeWocEf23SIuOP9lC9EFDjpsZPjaMaTzWugiAIJYEYMZUnNNOPML2XRL7oiXLaHBy0VNtOsDajqeUMrWdKCf1qmbmnjZ2vVjnxqAaPwAxfay5x/h+fWT+kg3EjvdY+wXcbV3Lzkx9jNJf+Wl1BOKcU1uBn0z/w+2366wwmaDIIWlyrRRAVry9289Uqx1HBGmQx8X/dbcd6LZdXLPrYeq3hVAqzER0WQmpGFr8u3cOI7jUL915iyhQYTBasne/m+s5wfYDesjwSbDXz1Q1tALUIgiCUHCJaA0ROTg52u12r4zKoBqelEXVRWqGAC1O/nyGWBeCGUc7OvE7Z4cl2Fm3Jz+qkEL5f+wrb937HtUzhVvco1r29nqb3/QbhF84MtyAEtG71dKJVZV/Meg3mva/frtgQujx0XB/Iabs8fLUyR+vvrP5ze3Mbz7Q/D+1nSiNB4drK7EjV1j0bxjB+WRa7k9PJdnm0C/+A/82EUs+SnWnHrQOK6teaR3C09GwVBKHMI6I1ABw4cIB7772Xd955hzp16pRO4Xq62fmUrVR178LpNzPB0YabUr00iCrZVKmSRPV1/KC3iiTfx9d/NuC6tC9p6lqN44M2BPV+CtrfBWUkmiwIJUpez+fTGfw4M2HMjbBthn670WXQ9la9N2kuydk+RkxzaII12Gpi8XA7YdbzIFZdmbBmDGybCeFVoc5FUKsr2M6z6Y1NF63W7P3a+vJmlRi3bBdG/Lw1dRsvD2xYtL+ZRF2Ljs+Le/t8JicksT+yNbd2qYX1HGUE1IpWNd8wdskOxi7R7/Pn3l9slEC1BMP4O47dp27fqz4o8P+uuzw+vpu/k9i0FVwaXwlLnS5gLLvXD4IglF5EtAaAKlWq4HK5uOqqq5gwYQI1a9YslHB1Op3akkd6ejoB53Sz8xbdNMVm8FDBmMEVf4axZLid0HNx0alcNXfOhQNr9X9sw2MhLE6fFVb/0BaTO664mJtG1+XR7A9ozg6Y9gIs/Rb6vwkNL9UiQsKFwTk5jsoqpxI3J/Z+LijCOvYmXbCabdD5Aajd47inZLt99ByTo9WWqwvvkQOCzr1g9bph4yRY+RN49fp8HGmQlACLP4canaHjCAiK4LwQ00hbVdnxJ3taPgJB0cRGhXIwNYPv522lYqiV+y+qfXbvlf9vploSSdS1aHgcWEZexiDlmu/4jsGtqxITZuNc0K5mJONGdGFnyjFvCSVY1f3FRv3bqQSqMoDKi7gqAavdrkSgOZLj5sN/VrIh6DZQpdvPJEoGgCAIJYLkbRUTJU4VL774Ip06deKKK65gx44dhYq0vvnmm0RERBxdqlc/lnJ3TpxAI6piqNdb27zWOJNsl5f2v+RohiolhscBGyfCH3dqrSDY8i+s/hXmvguTH4XfroNNk7XU5eLy6ZW1ucrzOo+57+IgUZC2S39/1R5n9+Kz60UplHrOyXFUVilKn0+/H8/fD8HW6bgMVvZ2fPUkwapcgS8a4yDT6dUO1Ve6BtO60jmOsiiRqs4Zy77Rt4MrQpMroE5PCKmkHI9g1zx9wup8HefV20OFuuDJoeq6z7W7nuxbD5PZov0j/L9/1vPI7wln3xv3bM7rhX0vIeAs3ZXGtI3J2nZCYuZxjymBOrR13NElIII1v3CNa6kvFRsE7n0FQRDOIyJai0meM210dDSff/451113HYMHD2b/fj0NLDVVr2E6HU8//TRHjhw5uuzZUwKOkmdqmaDS/YCbgmZjwa0J1y6jslmf4g3sfijn4hU/62Yui7/Q3UdVRLVqO6jSHCKq6/uoLrAXfQbTnofMpGJ9pIoYv9kjmLGeHvR0vMvn3kH4DGY9wvv9JbD+z8JdzAulknNyHJVVCtHn0+PxMWLUWj565R7Mq37G6zdwj/N+ukyvxsW/57A22YvD4+O1RS4afJtNUqZHE6z3trFzU/x5SN7ZOQ8ObwdzEDS4RD+Xqchm9Q76dqub9Cjx4W0w4xXwHIvGnzNUD9vWN2qbcZt+xpqVSGyEjc+vbUFosF1L+Bi/dCeXfbWycJMLpzuvF2WiQgioYB3y+Xw+mLZJuz0tYV/gUoAFQRDKISJai4C6IJ49e7a2bTLpUQWHw8HUqVN5/PHHGTRoEJdddhkvv/wyiYmJZ3w/m81GeHj4cUuJc+IsfP1+EBZLsDedv2r/oaULe70+Lv09mxVJARCu6qpWXVz+OQLWjgbHET1Vr97F0GEEqEivStdtORw63oenTm98yp10/yr44y69Rq0YDG2gOw1nEcRb7qvp6XibOb7m4Pfin/IUbP+v+N9ROK+cl+OorFCIPp+XfziDngnP8oD/V+32S56bmO5vq5mObz7kZuDvWTT8NpNvVju0STt1IT68aRBPnGCIdk5wO2DNb/p2tfYQ20IXiPlRJQfNrwWjRU8XVmnE54O41npbIJ+bypv1sQ0LMvP5tc2oVlFPW1679whfLj18bHKhONHSQkxUCIFHpf6qY6ZvfFXt9kN9G2opwQGNqAqCIJQjRLQWkvXr1zNv3jxGjBjB6tWrj97fuHFjvF7v0VThGjVq8NZbb2l1ddOnT8ftdlOqOHEW3uuEbo9pm433/8n05v/p9Z7KWXhCDnszipEqrD5nztsw+//0OjNVu6rS95QhUtXWmqHLtiwbHWY3ofa/zak5tQV1E26jt+NtVvjqaRd5zHuPv398m+smpPLWUrcmpFVqYmFQLsPjBoVoRjE7fVW42fUE/3jbYfB58I6/k4Ozviz6dxSE0kYRBM8XP/7IV+l3M8w8Gx8G1tS4kedvvortt4cworUdq9mknRbUxbgSq41jrPx3TShvdA1Ab0YVAT2yFw7v0MzhSNoA2YdP/xqVEpyeqBstVW2NOiWsSAvmq50xPLy2Blcsrq8tz+1tw7qYS/XXqAyL84EauLq9tM3wJL3FmMJsNHJFiypH5/ZqxVY6NrlQnGhpISYqhACTtofItATiDTvoFK5nCvVtFCOCVRAEoRiIEVMhSElJYfHixdxyyy1a/WqFChWOe1yJVmXINHnyZC3KWrlyZbp06cLKlSuxWCyl2zVUbTcaoF80zn+f+lu+ZlrHaPosbKZFU/qOy2FpUc2ZdszNvVA0QI1OULOzHgHIZdTeaJ5KqKpdCCu0tQF2+GMZ6nqRe0wTeMj8O5cZ5hB/eDP3HXyAz1fU0i7wDEYDdouRzlXNfHiR5Yz7166KifW3hGj1um8t8XD/1od4zf8115j/o/LsJziQc5gqlzwlBk1CmTdb2nUwlZen76VFbAjXdm5ApfDTmMw4M9j+2+PcvWOUduwdMFSiysUP07xKs6NPebKdUZv4mb7LS6rTz6A6xsK5raraUiVIsw6B16GJVJ8zi6zknfgPbSU0e7fmpltghLJeH6jREUzHxLF752Ism6do269wB+PmtOaI23j0PJKfVWl2ptCfJba/MKZs0UsOQgNvSnNGKjXWVqEpazB4Xfhzv8+Pi3Zr6wphQfSrF1w4d2ehdJG2Bz5tT193Nn3VIbci171XTdYKgiAIRUZEayE4fPgwS5cu1USrEqgq9VcJ0rS0NIYPH05oaCgTJ07UTJiaNWum1bbeeuuttGjRglLHia6heRdH3R+DnBRY8RP117zLd+1f59YlceS4vPQe52DhNUGF77u4bbq+rtlFbz+Rj7tX1eKfA+FHTXzvqZNM8/BsagU7ibG52ZNtY2dOW35PjaX3oZHUMR7gD+sL/ODpx+++7mz2V9f2bcYOL013uhjS0Mb/dTNr0YvTUSXEyPs9rbzTw8xbSx7gs4Rw7jH/RZUl/0e2Yz/BA9+UCIVQtsgXldubZaTXlwl4PR5mbkrhvVm7tYmzZtWj+Oq65sdcUtVrlv+Ad+571MnWDWNG+S9m8LDbwF5whK5PzUIYLan92bcCdi+Avcv0TIt8qKM0fzOaDL8dB1atNMBihAq+w5C4Qlvc5hD2mWuS6LKR7jZzkXEVFgN87bmU7xxttddrEWA1mWUAu8lPBatHixgfcppI9kaw1N+QDoaNjJ00mcFDbzz3PWTDq2lRYaMzg5DUDWRWbIFx3nvM8PzMcksDHD3eOd7h/UzuzmeDtMU5tyiXXnc2i1u/zSsL3VpacN/WjaRPqiAIQjER0VoIVP3qwYMHtW2Px6O5BCujpZtuuolp06bxzDPPULVqVerXr689p1u3blqdXZkg/8XRgPch4wBsmUrvPZ9wb6v3+HSFg4MZHmbv89OzsKasKs0vX9sHhccHAxc1ZGOGTbvAjLD4+LvjJmoEH59GHW3NpmVkNsSGgPtG2DQJW8pW7rJM4i4mccheh39N3XnnUCfS/GGM2+jgzy1GJg+2n1WvWSVun+1oZV7123j1n3Cet4wkeM2PsGc2XPYR1DneLVUQSi35onKPjV6vCVYl2NQkmgEfHo+blTuSaPv6DIY1j+DNakswLfoUQ3ay1r1xl68ST3vu4PVhHbDaAyDm1Dnkvzd0k6RccrCxwVedHL9NE6fq9jZ/HGt9tVjnq80BVPbKsVhpDcNBhphmM9g0l6qeFGp51lNLPZB7aK/31eB/nmFEWb00CXPQN+YIV8YeJsJ6cumASh3+bnFbOrg2MtQxjp9+cXPZ4JuJCj6HWTDqZKfOg3uXEpKyWhOt9Xb8RLQhnUtMSyFGpZJWC6wgPV27s/KM0YKz50uMW5lIm7Cq2C2Bdb1OD61Dgt9FWmQ8RMZxoaLGrU39qvyScSdDWsVhU7XjgiAIJYCI1jOgROmCBQsYMGAAderU0QyXevXqxSOPPMLAgQO19N8ePXrQrl07rFYrX3311dFWOGVGsJ6IyQxXfgnvNYLUndzRegefrojVHqoYVIT3UxdMCuXuqSaiPQYumt+YJIf+82sTlc3Ytls5Y9DDYof4waDS+1Rf18PbqJizneFs5zr7TyywdOLjzItY5G3Cpb/nMO/aYC2iejZ0rWpiScvB3LSyKm+Yv6Fq6k746XJodQP0fkFPJZSIhVBGJp5iI/RjzWI2M/KWNmw4kMmUhCQ8O+cz3DSdAZsWYd6sTxDt9sXwufdyzV370U5h1I4IgGBV0dVZr+ktaExWXJWaM2JvX+a4G+PGrEVBL49NY1BsKt1Cs3NF5j4S0lP4ZW9F5qaEkew0s8dbmXfdw/jAM4TmbKOGOYUqlmzahadRP9RJvRp12WTdeFa7pM4vt3eM45+FfbjEPZ0bfRNYNHoLYX2eJL76OUzdjKqlidbg1E18u3AvL/stx3R6bNPCvdfZCFJJMS4YsxVbj4cZ3gOGF27UhXyEBpkZeVtHQC2CIAglh4jW07Bu3TotBfiFF17Q+j527dqV77//nhtvvFEzW1JCVkUxVD9IVes6dOhQre5V1boWpk9rqSS4AjQaCOt+Z+/a2RgM12iOws1iCjkbrerY1KIwGDWh2nN+I7I8Ri2N74qqR/iw2a6zfz81rqrvnFrc2XoU98BaDJkH6OKaTxfrfLb64njecws9xzRnyXA7YWdZh/tIWwtN1ramn+stXrSPYah/Kqz8GdaOg26PQvOrNdMoiVgIpZ1L4yvxx7KdeNxuHG4vbS07GOZ4llDruqPPWe+rybeeS/jT14UaUUG81crC4PrF/CdBHdTrxmnlBZpVU1gsjoZX0mlJJ1LdpqPH/PvxuwqcpIoPd/BGk70nRUgPucxaqq/ZqGo71VKxaPtnMHJJ57b8s64q3Q6NpqNxPQdnPMjWBoOp17C5LiiNJdxnNlKLFWM5tJGp+/dhMN7E19b3oM3Nes1uYepXz0aQBiLFWBAEQRDOMyJaTxNhXbhwIXfccYcmVoOD9YuCSpUqcd9993HXXXfRu3dvZs7UW7HExcXRuXNnrc1GmReseTQdrInWqofmYWQYYfYiOITmCVYVYfUa6DqvMS6fQbt4va9uEo/XP1D0/dP6u7bRF5WKuH81HFxLPRIZZX2d6d5WPPrb5XwxvDXG3NZEZ+LVrjYenenl8ZybsTfvwcCUH/TIrooaLf0aejwJLa4p+j4LwjmgZ/1ozdJInYqSVk6k5+ZH9WPRZIPa3UiM68cn22pTL9JEQksTQYUxVDoVXjcs/PRoDbu/Sgs+NF7Pt4tjyXDrk1QP1kvikXqFO+aVuK0UlJutESAuaRrLysS7CNk0jgbGfVTe8i1sUQIvVD+ftLsD7CXUmiSqprYKPpxAV+NaptOBrNsXEFKlnt5PtjCIIC06Pi/uvSu1mu/UiCZc1bpq4YzFyhqHNhOZlqw5GtuzK6urloC8rcvjY/yKfUQdWU+vhtFYqrUq+YkfQRDKJSJaT0FmZqZmuqREq2pbo0yYVDRVidnbb7+dSZMm8eijj2qpwiNHjuTvv//m3nvvLX0uwcVBOXbaK1Ah5zB9jMtZaexU+PdQvVZt4eBMZ/RWjgrWN+P3cV31lMDta1gVfalzkdZz1b9/JX1MK+njX8n23+pSp/Ng3QjqDP+YqkjT/5aa2Z/h4b61dehywztEHZivR44yD8KkR/Q2HMqwymAgOcNJSpab6BDLMXMbQTjPmM1GwoKDsGfvp9+mF9QVOlTvCJ3u08SYulz9rHYAP1A5Av/3JhzapNWkHqh+CRfvvI50ty4C1DF/R+1DhRasJUmrODsbgm/kzeW76GhIoJ1xE6GuTNgxG47sgX5v6CI20ERUJyW4DtHZ2/nV+gaba1xNSMy7xwtWKUUoeTwOLN/1pp9q3eT4jt6NB16Y53DlWqwmeMffQV/VescGnll2aLo0IOZQR3LcvDx+CRuCboX5wDOJEtkXBKFEuICnFYuHEp8qNVihalWVAZPZbOaxxx6jX79+xMTEMGPGDC3aumzZMq22Nc+A6YJBXUS1uUnbvMk0laRMD1tT9V60Z40K9cTq7snuFD0NuF6YK7CC9cR9btAPQ7s7mWnpQY7fSh3PNr1P7B93wcZJej/I0zD2siAtFVpdaV/3jwdq94ArvoCmQ/QnqKjrP09oeYtKsDo9+loQShM3dqzBu5YviCQDd2RtPUugJKKHKkV/0sO6YDVZ+SVqBB22XK8JViVWqwe7eblxIs811M+npYnGkX5aNG3GLe4nae74ml31b9bPIco8avrL4HYE7LNU67B7Zjh5dK4X66Vv8rOnj3Z/g92jOfBWa17+/g9mbjqkPznzkD5JptZCmSJhf4a+TsykVKCE6b1L4M7ZTOs+jgdd92D25ugux4IgCGUIEa2noEqVKkRHR9OmTRumTp2qrQcNGsS+ffs01+A777xTe96zzz7L5ZdfTtOmhTTQKCu0vQ2/wUgXUwINjHt5el4RxFlsS23V2rdeWw+vdg4uxIIrcFHHTlxtfJf33YM57A+FzAOw+HOYcA8krjzlS6uFGbmzpW5ksz7Jxe9bPHotq6o5a3+X7m665CsYeyPRQX5sZqMWaRWEc4qKxmUm6+sT8ft51DaB7qa1OPwWXjY/pP+GA43qkzrlSchJxRccwzW+13h2f1fNV8hogI9a7GZutw3cXOOlctwAAQAASURBVLP0iq9LKx9BZYWqNjvP7u8MLYbrY5W8AWa9rqc9B4B3V3iZvNXJ7xsdtP7NzzvmO7nW9Sx7/RWp4kui0/aPueW7xYxcsveYMZMhAL8F4ZyxdFcaT4xbrW1PS9inpejXig4uHcI1rqXmZLzVX1W7a9rGZG1/BUEQygoiWk8xI674+OOPqV27Ni+99JLWi1UREhLCihUrtJTh/fv3ay7BFzSR1TE0GqBtjjD/xZJENz8mFLK+LDfS2sK4jQgyuLH6ubmAVbVw47ru4yfTFXR2fswLrps4bIjSIxjTnof5H4Cz4NnwZztYqBBs1gLFT8x2kOnKrc1tfJmeGmw0w4a/iZnzLI2qhF6YaWVC6Sa/c2x+Du+An6/ENOtV7eZrnuv5ZZ+qYQswCX/Awk+0WtnUiHg6pL/JopxqWnS1UZiT1T3XMSi2bFwU96qoR8fmHgplh6EaNLtGP8b3r4Qt/wbkM75d4zq67fb4SHd42Bbcgp8r3K/d18K4HZPBx7N/rOWgNwRCK0NIxeL9FoRzys6UY+Ov+rOOG9GFdjVLqDa6COQX0B9M28SQz+eLcBUEocwgojUfXq+e+prXcD4sLEyLqKr+rCoNWNW5KlQrm1atWhEZGXnhmC6djq6PaKurTPNoadjCi/Oy6fpbDruOnNwLsUDCqrDLUgeLwct11rlaVONcoYyD53TdgMFk5SdfP7rl/I8fPBfj8xtg63RSx4wge3fBUdefL7FpM+Ver4+LxjhIysr9vipd+KKn9TDIih9h6Tfn7gsJQh7KMVYJqzznWBURnPM/+LQ9bJ+lPTY2dDgjvX3w+X2aYUqgyFk7EZZ9q21PsAyg5YFnSPYEa4L1llqHmNJ5E2GWwH1eSfNa4z26cZWKiG6LhYiqeg28Qhm8FROPz0eOS//35elOdswm/SRoMhh4ekAzrXa2siFVM2Yy+H1sOGyA0Jizrw088bcgnHf6NoopVYJVofbn7SH6JHLf+Kra7z2/0BYEQSjNlHvRunXrVlatWkVSUpImTvOjBGmfPn34/fffqVmzptaPVT3/yy+/5MEHH8Rut1MuqNoaWlyrbb4Z9CNGfOw94qb7b5nU/zaT5j9m02VUDp+vPnUa3YZoZQEBVzFLd2U5h6iL50XdE2gXlY3PFMSLnpsZ5nqebb5YonypmGe+xG//zDgaYc8jvqKJO1oEabt7KMtD+1+y+HZt7nes3gFa6/W+TH4Cdsw9p99JEDRBkydsjuyF7y+Fma/qvVFjW7Cp60c8dkhlSRjoV8cWEGdUNXHz9PeTsK/4Qrv9iWcQD2Zcp50rLUb4pMVuXmpU+mpXz4RyJ24VmaNtz0/JNV+KqKGvDyZoTrPFYU+GXt6vGN7IhN2i32hQwai3uanTU7t9tWkWBpOZ+NjQov8WhPND2h4i0xKoZ9hXqv8C8bFh+jquBEzGBEEQSpByLVqVG7CqSX388cdp3Lgxc+fqwiNPvKjUXxV1bdSoEePHj9dcg1U9q3IMrlu3LuWK3i9qDoRN/NsYXXsyBoNRm6XNS3Pbl+7m/xblkJhZcHTFX6sH2X4b9Y37IP34Poznggirj7Htt7Khz1p29VvDR938fFrhKf72dsRq8HJN0vu8/9NosnOjIXk819HKkx3tR42ZXpmfQ4/ROXy4wk1irSv1qKvfC79dB6k7z/n3Eso5qoZx6bfwWUfYuwQsIdD1UTy9X2Hw7GjtGFVRvU96WgISLXxp3CJeNXyp3f7GcwnveIZp0cLelTJI6L2Gy8pIOnBBDIk7rK0PO004VAWEciNXLYKc6Xp9azHYlqZP1Kn/hlqNpDv082SParn/BNe/WFv1NS6naxxSblDWSNujZTj0nTOED62f4THZdddeQRAEIWCUW9G6fv16tm3bxujRo7VI6tChQxk8eLAWcc1LD85L/c0TsSNGjKBv3740adKEckOewUdQuN4CQqUY7f+VzfE/8GpnC7c0D6J/XZsWRlCj9ficgqOtLaqG8pdXb5mTsXMV55s4u5v3WuynY+deTDTpLp6PGn7hv9/exXOCY+g9LS3Mvy6EKmF6jeuuNDfvL82h869ZNNx4K4lB9fQL21+vAUf6efpGQrlDTZJ80l5vw+TMgOj6cNmHHKnag26jXWQ6vVqWwPs9gwISZX35n2285X8fs8HH5pC23HpRc3b1W8u2i9fwbasdWip+WWZY1ZSjvW3H7Y/W22NFVDtWJ1wMFu33Hv03ZX2KF4P2SVAr3MjE7R46TanCOl8tbQLt7qoy+XVOMFpwdXmCUSE30KRmFeyWYvQWVU687mwWt36bAc7XmdJzYkDayZQF1Lip8VPjqMZTjasgCEJJUC77tKoI6pEjR2jQoMHR2tVXXnlFS/3dtGkTlSpVOvpcj8ejtbRxu91069aNckd+gw/lnqv6Mc56HcvWKdwQsxN6Pgv2KIb97WdJoostp2iJExdq5Cf/JVzDfwSnrQdHNwg6//U+MUE+BnZpw78rI+id/geXMocNo/bR8KrnMKp0u3yOwouuC+adZW7GbnKTlOXVIq9Ov4UrUh9idvjz2FU0ZvLjcNWXRe+zKP0ZyyzntGdvVgqMHKxnLYTEQJMroOGlLDho5IbJ2VodthKsVzUM4rK6xT/N+7LTuCP5TcIMOWww1qdx6566PfAFRIbHpIdCDRBmzj2PqckocqOuRWR1kpevVzu1Sb1q4WZi7Eqyqkk+P7f8k3XUIHiVuS5NjTvpHLI/AN9GOCNmK9a+z3JtX9CLX4pPemgdEvwucoJVJ+TyQWiQmd9HqPrv3BpwQRCEEqKMz40XDTXbrWpUr7rqKv744w/tdsWKFYmKitIEqiLPdCkjI0NzEa5QoQLlkvwGHyoE0eNxuG6MnoaYvFEXaen7iQ3Vf0qZrlPXq/Zr3YA53maY8LNl0zpKDQYD/VrX5+uI+0n1h9LYv4208Q/jO6i36MnP420tLBkezM47w5gxLJQQm4kkQwWGZz2EXx1Oa37TXIWL7OYpLqBllnPWs1f9RkZdAylbdcF66f+gySC+2wDX/p2lC1YMPNTOzvs9rcX/PK+b5ClvUsOQxC5fJaJaXK5HIS8wvthR+Wjd6WWV0zRXZLL1lGEiihY1y3D5GPJXjiZQVQbP+MtsxAQbGXO5fj5VH6cmF6LsZurV0UtODOq8KgglTHjmduINO7Bnl70adEEQyiflUrQq4uLi+Oqrr4iJidFcg9UFhTJXatiwofa4ShNWglUJ2S+++IL4+HjKJfkNPvJShWt1gbvnQlQtvffplCepb9dbRjg8pxatD7a2MMp0mbYdm7qMI9klfHFfSEa0svNu+JNs8FWngj8N75SnYfVvpzRhqRtlZPKVdu3ic4WvPl/5L9cf+PMe8DiK5uYpLqBlFhVhLfGevUrhTLhXr1+1hkKfV7TaudcXu3l5Xs7RGtbfBwXzcJsA7IfjCMx4mcoZCWT47TxpfIgq4Rdm+t/Eg3rmR50Ql9YuS4uyqnp1dRyryYEiMGiCE7c2iQA/XmKnUoj+T26HWBMzhoZwSV0bv10ewsobg+nYuLb+oqSEwH0p4dT4fHj2JzBnwXwmrzuAJ4Du2qUaVWtrCabDiieYZHuW/rMG6jW5RUSNmxo/NY5qPNW4CoIglATlVrQq+vfvT9euXY+6BgcHB5OToztIqoireszpdGrpw8IJUcDounDrv3odXc5hLk7/XRsir+/0zsAPX9aerb44Qg0OflqVG8UoRbzWOot3wx5nkrc9FrywaiRMeQoykwp8fs0II5/0UUZN8D/nVWzyV9cvdhd8VDQ3T3EBLbOolOCA9ezNmyBS6xN7oyaMB4MJej2HJ7wqV05w8NXKHC1KGBZkYvHwYNpWCUAkNHkTTHwI9q/STNRGuB+ie40gLlQSc/Q06ur23H6qefXpSrAWIbLs8PjYlqJPzN3aPIhu1UwnTXp93sdGp7jc+/PKJaQu/tzgycH8ZWe6T72UR0fOJzWndE2ilhiq1vbeJUzrPo4HXfdg9uboNblFRI2bGj81jmo81bgKgiCUBOVatJ6Iql9VkdXU1FQeeughXn/9da0nq3CKKKCq87rk/7TNegcnU5VkLRKU6Tr1TGuDCma2VuihbbdxLCbZWfrSDL9pm8jXwXfykOse0v123Tn0z7tg57wCnz+wjpl7WttxYeYl943afZ4l37Bx7ZJzvOfCBUNBaeJKwKrov+qNGnwVrf6tQ92vs1h5wKUJ1uoRFpYOtxNtP/NpPSXHxwMzXdzyr5P7Z7p4Zp6Ld5e5mbbLw5EcD771f+FVqf9ZyVprqCtcr7DU0JQ7ayYV72uV4iBM3RBdrP6XHMpXO2N0cytFEaOsmvdVbr7xwkTfSS21TsLr1NfStkYoaSKrkxYZz1Z/VRlrQRDKDCJa89GyZUvNjEm1v1GpwwMHDjx/f5nSSEFRwLq9oXZ3jD4PD5vHaddoaw6dPtp60UV98PkNdDat5601pbPX7fj2W1ls68gA1xus8NXT6vqY/X+w6PMC04WfbGdh3KAQttpbMMXbDjM+Do15iFcnFa9VhlBOKSBN3Dn7fS0dX9WVPp4ykNQcj1YrqY62KxsEMfcaO0Fn4RL82So3bX7O4q8tDmbtdPL3Fge/Jjj4ZHkW3/y7nB2/PYJx6VeY8DHZ257Lna+SbInjjw5bdCFWRLHaZU5j6k9tziULG5DqKn2TVZM7biTc4tPOYa9vjGX9Ic+xdMoiYDYa6V9HryneeMhFl9+cWvQ1j5/Xexj2t4PNeeZ1qqRAYSmd50RBEARBOJ+IaM1Heno6Tz31FN98840I1rNFXeH1eUnbvMo0jzqGRNYeOn1EISiiMhuCWmjb9dIXkeEufT9DVdM2o/MGUkwxDHO9wCeey/UmFZsmwZKvCnxNuyomll4fjLP1bbj8ZrqaErhh8SBmjPw/cEvKlFD0CaJlO1NxzPtM237Lcw0maxDt4qy81DWYhFtCz8pwSZkCdRmVw9uLc7SMCGXWVCHYTIzNzSPW8Syy3c9o26u0NG7X6ldfdN3EG+Z7+KTNQVb2TKBJ2PGtoM4WFWDsMqcJ+3Is2uliQ3oQrWbF8+ue0tXHMsgMs7tuwGr0a/s590DuecldSDO1fHzZ18aAejatFHl/hpvWP+cwfLKTet9k8vzcbM1xfeB4hy5mPblpyao3rCAIgiAIx1H61MJ5RDkIq5Y3EmEtJFXbQK1uGA1+uhnXsunw6SOtitod9Cj2daYZfLD5/Le+KYhgs5/pnTdhMJr4n+ca7nU9oD+ghOvGyad83aCW1TB2uocjhFDLeJDeW9/E824TmPUmZBw8d19AuGC457c1ZKGLmY51Y9hwSwhjLwvi5ngzodazSwfuNcbBvnS9bk+lEs+/JogV7Wez1P4gDxjHUdmQit9kIy26NTNqPcbwjrWY130jPWNy02SLyG/7okl2mjXh1jzCkduhFJ5eX5VVaYU0Kithoqxe/lXHvAH+87XU7vPvWXLKmvaz4dPeNu5sZde+f7bLy/w9TjzeYxN7Lo+XwX+71GyefkdW8VKwhXPL0l1pTNuYrG0nJOpdBwRBEITAI6L1BJSbsFBE4Qq0Mm5hZ/qZC9eCa7Vnl7Ea4YYcog4tL7EhL24NXZzdzdxuG7Xoy2RfR95yX60/sPhz2L/6lK8zN7wY09Dvedl7M3t8MZgdh/X04vebwPi7IHFl8XZMKDc4XF4OpmWxxqe3RLmx8s5CvV7Vqqp04OQsPd31luZBzL14P9Vm3Q+LPgVHmm4C1PhyDJ3vJ7LpxVxRy02DsNway2Ky7EjI0UmgvzpuZn73DZgMWjtUrllW93izUa8L3A49M0HV86q2M+eY2iEu/u20iaXEs8DbREvBPrT6n2K957MdLPzfRcGaUZZqk9WpmpUpQ0K4vqlubJWQ5OLTrbmR56wCDLiEUitYh3w+nw+mbdJuT0vYp03K1IouXZMxgiAIFwIiWoXAUKODtmpl2Mr+zDNHWjEYWVPpSm1zqP9f3XQmQChzp0fW1aDR9GY0m9aIhv82otOcJtp9CemFdz+tEuRmZteNWj3f597LGe/tquIvWisQ0k/d4y40OJgOva6gh/M97nPdz1ZLQ/17ql6uX10Ev99+ynY6gpDHL8v2acJpta+OfsehLWc1OFtTvbT5OZuPlx9LB76rlZ0Xa2+GSY/Akb16/WS9PtDuDqjURK+jDTDbMvUIcQWrfoxXs7v5ptUOLfLo8Br4fbcN9i6FZd/CvPdgwQew4ENY+BEs+w48gRHPhUEJ9okdNzPS20e77d8ylZTM4u3HtY3MrL0phISbQxg1IIhG0SZe62KlZqTeQujtVSY85ly/gLTdxf8SQomzMyVbm3zpG68bGj3UtyHjRnShXc3SmT0kCIJQlgn8FYpQPqnZRV8Zk/DlpAFnNhOp3bIHif/8QpzhMNmb/yO4kX6BWByuWVqXhSkhWnpfE8NOvre9TQgOxrgv4rvE/vy+twFxwR6ujE3lntoHCTWfXSRHXWirGtde8xvztPt2ahkO0JqtpE95hfBB74Ct4LZI/WuZ6V4rmIm7OvF3eidGdd5H5yOTYMccWDsWYltA5/uL/b2FC5dxK/SJkb22uqB+rhmnnijJL1j7js3Gr8SqH+pHWxh5qY0qdtXn9SN98iSyBjS5Ciwl2MZm/yredv6K1eokHCfMd2jtenpa7PxhjybHa6b9zo1gOMXkTfYh/lu2mhfcNxFq9tI4zEGHqAx6x6QTbS3ZCZ9GYQ4GN48hbUMIMYYjDB+/hV9ubBrwz/lrkI3WI714vT6S3EHEGbIgfT9UahzwzxLyYbTgan8fE9bsp3ZUDHZL0c3B4uNCYSv0bRQDceVLsKpxqx0bw9icwQxqHovVeGH2cRYE4fwjkVYhMARFkBVaS9ts6NvKkL/PbNrStHIQz3ju0LaDDy6DlG3F2gWVZpgnWNsZNjLW+jKVDWlaT9hbzVOYbX2Yz6wfUNWxlc+2VyR+elO6zW3Mb3srnFU/9Johbhb1SKCC3cgI10Ps91cgPGcvy0a9zIdLsk7Z0uKbiy3YLCZtv65dWI2xlR+CjvfoD05/GZI3F+t7Cxc2u1P0VNHakblzjOYzi8wbp7h0wYqBd3oGM32onSohRtg5R88OMNuh6ZCSFaz7VsDmKTRkN7WNB4n2p+kOue4sTYy2ZhNdTAlYDF5W+erwgutGOuZ8QHzOVzTK+YYbnE9qb9PNMYvQnH2sTw/i932RPLGuOq1nxvPhtsqUNL0rZ4FFT/V0O7JYmxx4oRwRZOTK+lZiSCPOkKL9zYjSz6VCCWK2Yr30dYY+9R2TH+xOqHLiEgqNGjc1fmoc1XiqcRUEQSgJRLQKASOkll7X2tSwg2WJLq6ddOZ0uqzK7fjO01+/sXthsT7/gFN3J+1pXMkY6yuEGI7/fJPBzwDTEsbZXmGa9QluM/9DRraDpxKqUW96c55OqHbGz4ixeVnYfT3X13fzoP8xrY9rW8NG6q97l0bfZWr1gwW1vph0ZRBmk1FL83xsVjbfOHrpdcA+N/x5N3gDlx4tlH2SM5xsPJCprb0+Pd0+0nh2LVF+2+hh3xH9d/hilyCGNcy9GFep6GtG69vV2oGpBC8uD66DrVO1za89l3Kd8yk8Pr1naX4WeBoxzPEMg5yv8ZOvPwcMlcgyhOIwBDPX34KJng7acftO0LfUsDuxmfQWP+o4f29LZcYnRlHSRAbp+203uBizOfCiVTkHj9/sorVRn7wyVGwAYSUvyAVBEAShLCGiVQjIhbVGXCtt1SNYN4pZuNfJLf+eXri+3tXC5+7LcPrNkL4XUncVeX8SMuy0NmzmK8t72kXt6ahv3McLlp9ZbLuX7yxvc41xBjP3Qve5jcn0nPmwuL/OQcb0TCep3tW4MHOpaQnPG77j4+XZWpT5xKhrvSgTc64J1iOuwKsLHLxvuwssIbBvOfz7jNS3CkdJyXLj9Pi0tRKtBnzUc+X2/M2N/BWE+t09P9+h/f5jQszc2jRfqp6aFFJ1rCbLUeO0EiF5E2ycqG1+7+nHa+7hPGgej9l4cq17Z/NGxgS9wVzbA9xinMhww7/cYPyHm4z/8KRxJF2M67Tnxfu3Mafq52zqtYqE3uuwm/S2NA+vrc7iw/n6RpcEBj1tNAgXCxIDL1ofme3W/m7djWv0O2p2Pr4XtlAy+Hx4Du1kxdo1LNyegidfD13h7FHjpsZPjaMaz7NKWxIEQSgCIlqFgFxYa1Rrr606GNbTIka/0Ju108mgP3P7EBZAgygTxvAYRnt76nds/qfIxiubM+1UNyRp6YZni83goZdpFW9YvmVx0H185HmZx2c7yHCdQfXmUq9aFayNB2jRnxvM03nePJJliU66jXbiOuE7x4UaWXSdXXMQVRfcHySE8qX9dv3BJV/ChHvlH3xBIzrEgs1s1Nax/iR+tbxB9/S/9Qcrn7qu8uVFHtwen/Z7/PriE/p9qtRg7YfYBswl1As0aT3+hD+0zTGe7rziuYGLjCvoYDp9CnwN4yFetP7K67YfedX6My9bf2aEdTJRxnwuunuXwJpRhPrSmdZlI8ZcB+Jrl9UtuV7PqTshY7+2udtfiV1HAitaN6d6mbTVRR/jcoabZ+p3Nrw0oJ8hnAJPDuZPWtD6927c+tV/pOacnCVzWtL2EJmWQLxhB+GZ28v0MKuWPWNXJGpuyIVFjZsaPzWOajzVuAqCIJQEIlqFgFxYa1RrC/YocGXyR6ftNKqopx+uPuiizcgcrVdkQTzZzsrbnqvZ66+ot9/YnnvxVkiiLB7m+5rh85+d4DwRZVjT0ridz83vsXnhH/iO6BerZ6RSYwwNLtE2Vcrxc+aR7Et30WmUg8wTeu5EBRlZOtyu9clUwvXNpA68YXsAv8EIq0fBP0/oOyKUa2LCbDSqEkr4gcVMND1KJ9N6PMYg6HQ/NMhNpy+AvEhgrUgLLSvlM5ZRtaR5bZYqNgz8Dqvf7J7FsOEv7XetHLaf8tyJ0e/lc8vHgfscFSle/gPVXDsZ026rJs5V9vSNK/R2QAFFjdkmvR9zcvX+bPDX1CYEdp9FS68zsn8VnhUjWTXhI761vM2Hlk/0+5WLc4OLi//+QsmStgc+bU/fOUOYZHuWDiue0DMggnPbFpUB8rflUS17Hh+zUmvfUxThKgiCcC4Q0SoUHtVDMDOZGJtHu7BWF9j6r8kE9frqm4nLmDI4iGGNg7Tr2Synl86jckjMPPmC76r6ZkLCwnnMfbcuOFX/05Sthd6tq2JTSCaC1f6iXcCqi+0l3gY4/BbasBHjqh/1NEfvWczAKxfg+rqYuN38D8+afiEl20330Y6TIq5BZiOzh9noUFUX9V8d6chLxvt0A5alX8OMV4q0/8IFRtIGDL9drfUyXuGrh2/gB9Cgn/5DPQXpTn3CIzbkhOes+13vfRoUAWFVAruffh++rdNh+yzt5reeS3jEdTdtWc8y2z0EG12B/TxXJqz6mbY587mu2mHtrhWpdr7cGcAe2+qkpY59ZzqEViam260YDEZt6L9L8BTvfVf9ClOfw7z2N4YZZtDHtFKvv6/eAXo9F7jvIJQc2SngzmZx67cZ4Hydad3Hwb1LILJ6mRl11Zbn7SEttO0XOll4qKlL86M4uKfw//YKgiCcC0S0CoXHla23zFDrE1EX1YqtM7SoyNvdrbzY1a5FRJxuL91/y2bHkZOF61d9bCz0NeFbrx6xZOPfoLXOOXuU+WMFq5cZXr22tii0N23mGdfN/K71Ys01lFERUHWhfCbiWkJ9/fvfYZmsRVwPZ7u5aKzzpBpXo9HI6IFBDM0V9T9mdeS70Dv1B1WvyvkfFvk7CBcIf47A6s1mqa8B95hewhp1ZqOwLLcuWisG5xOt6jecZ8BUp+dpRW+h8fs5vH4mxsTl2s1X3dfzmXsAk61Pa7Wqx6X3Bpot//J61UVE27zaV3pjUywLA1XfmjdxpjIgLnpai6LVitQj1zN2FTFFWBlhLfwYVv+q3fzb25F33UP4s8YzcNW3cNU3ZzdBJpQa0kPrkOCvTVpkfJkSrHnE162l/bZVpPihrTdrUeP+swbqkWRBEIRShohWofBYg8Fo1tcnouqxKsXrab6THoElX3NrjWT+1zNYiyR6vD4uHZ9zkohrUcnEFQ2C+J9nGOt8tbS6Vv+a385OLOajS3Qmf/k64y1iirDif5avec11Hde6nuWIP1jvi7niR8g4cOYXKzOqXOGqIq5Pmn4jMd1Fl98cZLtPFuvvdLfSq7YeqX4luQdjwm7QH5j2gh4dE8onqi1N4kot8+Ae10O0q3Zq86U8Uh0+Mpz6byxWtbdRpO2Gac9r0VCUK20gU4P9flavXEiFQ8u0/XzAdS9JvjCW2u6jiencXPQaMxKZ2nkjptz61ntW1wpMWvDO2fp2m1shup622bWqLlr3ZRRBtLodMOs12DIVL0aec9/Cfa4HcHR9iitufRIaXaK7Qhd0ThWEkkIJbRUhvnO2Fi1+0HUPZm+OHkkWBEEoZYhoFQqPcrYMjSnY4VJddN30ly7e3NmwYQL8cSdDd7/KqLZbtahijsvLH9tOFnDv9zBTKSKEW1yPs8tXCYMjDeeqsfpF5FlyV80kdvkq84+vQ5H/skYj/G17ngXeJgxyvco+XwVwZsCKHyB5Y6GE6wjL39xv+oP9GR7a/5KjCYsT+bavhdpReo3rE8mXMNY8UH/gjxF6xEcof2zTU21X++uQTCS3NM1Xn3oKbvnXpbVUUpNDNzQ2QdYhmP6iHr0LrwqNLgtYlFX1S/3lvxW0yNDNnZ5z30x/42I+tn2uHT/nDEca0VYvA2KP6Dd9AfjwXQv0VOqI6tA491gEZu7WxWqotQifseBD2LtUazN0r/cxRnr70r9FdZ69pP6Zz6mCUNLCNa6lFi3e6q8qYy0IQqlFRKsQeEIqwu0zYfg4qJ9rKrJvOZ3XPc/39veJJIOfCqgLUymzqtazVZ0qXO96mmR/BLacg+xc8jd4z64urllEjtbL8XPPZcX6CtWMKQwx/sdOfyz9nW+R4Q/SH1j/JxzIbU1xJuFat5e2+ahlHHeYJpLp9NLx1xwOZJ2cKjxjiI32cXqN65OZ1/CfrwV4nTDqOq1+WChnbJuhreb6mmm/j9b5TZVOYcC0cr9+jNzQ1EYNuwNmvAxZybo5TNMhequbYqBSb+9eVYtWMxvh3DiV4cZpWoT1bfcQzYDsUvMyzjk5qdpqX47+3SItxXT3zT4M+3K/R7vb9YwSYG2yl725vW8fbF3IcTy8A3bOVVXzrOv9E/94Wmt3t64RUbx9FQRBEIRyRMBFa3p6OqtWrdLWQjlGhVvq94XhY+H+FdD2Nq0+rBdL+cL6ARuTC46eqgv0r/rauLdHbW5yP026304t9zbWzp3A9tSzM0DpWCFLqzOa5zt1a5Cz4S3Lt1j8LjIMITR3fMXfHr2lj3/jZEjZduY3UC2AanXTNp+1/MoT5lG43G66jspm1wl1vep7j7ksiJuaBeHFxAOu+9juq6L1rnX+dhN4i2H+IpQt0vcf7XM6x9ucRtG6cDodI6Y7tSCq3WrilfZ+mPU6pO7Q+wA3G6qnnhaBFJeJoUvqUfvf5ly7tC6rD7r5zvAa15lnaoJ1qz+WJyzjqGs8i9T5kkBFRFXZrlMXkpWsxawJTd6gp1LHtjyul+0Tc93a+FrNRm5rVgjRqlJLlLkacKjmpRyJaXu0rVWTKqHF21eheBjNuFrfyh+WAVSNqUCQRebwi4IaNzV+ahzVeOZN9AiCIASagJ6lR4wYQVRUFG3atNHWJpOJdu3a8fTTTzNzZtHamAgXANF1YeB7cMtkfGY7HY0beNH4HTN3nVqIXdPIzKgbmvBSyPOk+kNpZtiGYdXPLNp35ojr/XX0C+gf3MVrHWE2+njD8o123ek3mLnf8yBjPd21i1f32t/Prsa1RuejwvUe8998bvkQizebi3/PIeOEdjiKlztbmTksBHtYBHe4HyXTH4Rt73xmfn6/1sRdKDvu2tq6KMx8TavpVgZMy/wNuar+6aOsV090cCTHo/1O37/IjHH+e3paubp4bDYEgiKLtBuf7ahEm1nxLE1V9ejQ2bCOSbanaWXcistvwmjw08CYyHmlQh1tleTQL5SrB7sCIoLz6lgVW1O9rE/W3/fGeD0bolARc5WZYbKxu9UTpDk8RzO0a+drOSKcB8w2rJe/z5XP/sr0R3sSFlS8TITyiho3NX5qHNV4llgPaEEQyj0BFa2jR4/G7/dry+DBgxkzZgxfffUVffr00baVgB0/fny5H/RyS41OGIf9qEVoVKRmzeJpp316RJCR94Y2Z3Gr/2OPP4baxoPU3/I1/245vRhoF5VNkMnPLH8rDlO8FLyh5nkstt3LLcaJxJHEU+7bmOttisXgI2f17+DQa+lOibpCrdkFGg3UIs39TUsZZ32ZCu4kLhrtwHOCIZWibpSRxdcFM6hdPR733K3d1+vQr3z+yh08Mm4d949ex60/r+L6H1by4Nh1vDV1K78u3ceRbHEeLfXu2mdiwcewaqS2+br7egwGEzfHn1q03j/TxeLciZxu1a30P/A17Jqvu96qlOCw2ELvghKAXec25u3NemscVSX7cdQYfrG+QQWDboxmNRQzDTdQxDRi7qEwXD6DJtqV6VuxUCn5ilxDJGUYd9VfTs3kSWVDPNW+EFEk5X6+7Fttc2eLR3CGVScyyEzeEb9yr2QjCYIgCMJ5Ea1KmCqBOnbsWG1bCddWrVrRu3dvvvjiC5YuXcq2bdvo168fu3btCuRHC2WFWl2ZWel6bbNr1rSTXIQLon+LWmT3fYd1/tpEGzLovu9LfluXcdrXDIpN09Jsx3lyW9cUgyrGVF60/sqCoIdZaHuAB10j2OCrjt2bQcaKsWcWrorKTaHFddosdLxxFxNsz1MlZwv9fj+5HU4eD7Sy8M6NvRgVPFy7fb9xHDVWvcvfK3cxM2Ef8zYmMmH5Lj6fuYlnfl9F81enM2rpeY58Cad31z4VKv17yjNa/07FJ55BrPLX44r6VsyncDb6d6eHvzbrafbNY4yMtL0Jm6foDza+HKIK76Q7ck807Wc3YW+2HnWqZ89iQ9U3uSznz4B2ygkI1jAIieHtrbowD7X4aB1ZhImC/HhyRatKqwbum+Um3aFHsf93UdAp/xYFogSrM4OsqCbsb3yLdpcSvmazLnwXbtd7zArnCb8fX8b/s3cW4FFcXRh+1+NCBAiQ4O5OcZdCW7RGDQotdYVS15+6u9KWlrYU6hQKxYs7BIegISHuyer/3DtJCBBPIAm57/PMs7OzmdnZuzuT+eac850zHD56jANRKcX6X1RdWLIvhk3HitdyToybGD8xjmI85cGiUCgUlV20CsH6zz//SLFaEI8++igfffQRU6ZMYflyzSFTUY2wptNp6M0y2tpZf4Cft5ws1mrN6gQSNPplVrva466z0jPmJz44HFDg3z/e5JRMaZzv0FJzy4tgfRILLU8yNesBTroC8bbFkrH5O0g9U/TKvnW1FhqeQQTrEmXkSp8QwU2LCo6QCqfS68dfT2RLrYfr3YbfaG6JxdPDHW9Pd8xmCzqDiN7o0LmcPPbzNp5beKA8P7KipJTUCTYtDuaMhvUfyKffe0zkdfu10gX4pV75R/Yy7U7uXpophaSH2cCvYT9LszMZYW06XEYgS4K4Xhe1q0+Ea+6h4th5oeEelno+iUfcbiolNRqQ7tCzM0kzSbumdsn6OudLTnTczYflJxz8dVATsT3rWRjTxFgy86Uj2v+3w91fOqfOz89DS5/cHVn4jTfFRcaWjv6NJjSa3Zar3/6HuLTiZaoIMSdEnSA8smQt2Soz9fOkq7+9ZD/jPvqvWMJVjJsYPzGOYjxl1wCFQqG4CFSI80DDhg2luJ01a5YSrtUNswf+tRqwztBBPk0L/7vYq9b09aTDhMc5gz/19DHER2zncFr+9TO+ZidNvbPY7wplq/NsfVp5ICKvP1pe5Pqsmex31sXdkUzW5m8gsRjZA26+0H4ieIfgp0vjW/Msjp44ydx9hRsthXS5Cup2waRzMLfuL3x+Yzs+vaEdX9/Sge8ndea969pL8SpEzE+bVGP4KlPrGrUbPusHEavA6EZ46xnMjBshX7qqiQWPAsxhnllnlz2Phbj8vfsB9Lt/Phthrd2uxLs2bH0zWbsqfj+BFgcb2y3kpsgXITWayorTtz5D1jWXqbtiHKY3jiw3N2Kbe03u+Ccj19zqm+ElrHfc94d8iA27krTAc78PQ3a0NimjjPW3ikuOEHFCzAlRJ1gSrt0czSv4qipdwvx4dZz2Wx3cqo48ro7GKQGqUCiqoGgdMmQI1157LZ9//jlHjx4tlzfPEa4qVbj6RaGy2mvpcleznCl/p8jIUXHw8vDAo7OWXnyf8RcmbayVY8Z5AV91OIJeBz84+svnNlfRvS6LS4g+ge/Ms5iYNYMNzuZYdHbs23+EM3uLXlkYVQhHV49AaukSmGP+H2+uiiIpnx6u59BZa8Hhf2o5fqdWXPCyI9theGS7kFJ/LsUlrHU9uQVmj4DE4+BVE/vw1xmzo2OuUHqnn7HAdLz5+zXB069mJo13vaW9IMRqCSOsguPpJvYnazd/hgQls7nRl9Tcr9XVVmbuOtFXpjGLbMQ7GsTIG1WlZekZHzosFVEi7YZCx199sNq1mwLfDC9hWrC4KRGxUs5GNb/5nJdsdifRiVp0bmhLrWZYUXUQIk6XLeoEDwxuxs/TekrBdznQqra39hiinK0VCkXlQ18SgSlMlYQr8Msvv0znzp3LRcSK2tepU7XUR0X1oU3fcUTrgqSxS4tT82n+ZRqPrLTKHqbrIh18v8/Or4fs+dYZebUYRKJHGL66dG52/s4je0LzfY+67jZ+6nKIPxw9SHG5yyhlhrP8HCJD9bEsszzKA1l3stDRFaPOCXt/w3liY9ErixYkba/FZvaTBlOfm15l4p9FuM361oHmWv/ZBhuewpR+NiX5nRVH5cGsMxh4YWSzMn82xUWudc1KgW+u0uqhhVPtiNe5d2ttsmwOKcI+G+Im6x/z47PdDi3K6oJ3asyHjHitF2ujgaXaref219XSjHVZfOL2Tm5aa2Um2libv+O0WtZ+Qak83vR0qbf19fFAJm+rT3eX1n9ZuJWnoEXORja20KVWCW92HV8va2PTfRuTIlrc5OH33WfQS2srHff1K3nNsaJykCPqBjcPumwEq0KhUFxW6cG+vr6yXlWYKm3evLlcRKyfn580axK9XRXVhyBfD2qMeErOP2T6mat0a/h5Xybd56Ry/R9pPL4ynQf+TWfUb/mk0OkN+F0xSc7eZPiHTaeyWBOX/53hzv7pvNz2DF/Zh8rnmTozBx0ld1QtCG99JqstD/Gu7arc99AfWYbz8IqiDSks3pjaX0u6zp12+iNMTPqEH/YWUVfV7jrpCOuWdooWy27FYE1m+8lkDp/W0hpv6FZf9pKMScliX1SqfFRUwlrXg/+ANVVGWBk6i7UJPiw8rH1XfcMs9KpTsFD6YJv2Gwn1M+GXtE9bKNoqGUrYjiWbFTHe1CGGv92fRif6lFYB5mV00Yy5Pawyo6K0vLQ/hKf3hNBSd4zXTR/LZWdq9+e1/h58NcKTDwaWon1Hepx8SA3soLmHZyNuwP29W2uTVTfQGy831c9SoVAoFIpLUtNaXiJW9HEVacKK6oWpyy3Q4x45/4b5E4brN8h52Rc1+292R1tZdjyf9hp1OuGs3UG23njMNJdbtzYk1a4v0ElYV78nu5318delcYogbsx6lFRn+fSTE/1cF7k9yTJHG16xXSeX6U+ux75vIbiKSFl098ej9SgcLh3XGldwatOvhf+9EDyDX5DreSbso+GSyby1aKe8NjaZTDw3ommuOUaW3VlscxHFJWbPb/JhnaUnvefD9X9oaYcmg57PBxecDRCR5JQ9WQVPddWdraP2Kn2qqb8zkR/MLxLmrPy10MLATfCLszeeRieLe+yjJJm7eblvVxifRgQSrEvgK/NreOqyZIp1s8GTGd/USP96hjK1zXEY3XMXxadbmTp3F2kZmtvz1F4NSrdthUKhUCiqKeVqxHS+iBXiVfRsnT59uuzRWpCIFeslJGiRIkU1Qwiwltdgws5H5nfY3f4XIqZ4cuwOH7wtBinGHlief7RQ32WyTLO70rCRtq4DjN7QpMC3ubdxHAfrjifTZaKfYScN9LG0zvqcH2x9yu2jfGt5nSinL49ap0oRajyzi6w9fxUdca3RkF1BV8rZB5zfELl/U+F/710LBj2Hy+RBYPwW3je+I1OTF0zrjtGoHdIBniYsRr18VFS86ZKoj7zj+530eHUVI5+djTX8T7n8pciOnEiyoRO3aXQ65l3lLiPlBfHqJps8JkTq8BDvY1qNrKiRFgZfpcFhZbblVWlsluw6K7IqIz/Ze6PXudjubEQEdfil60FKG6x8aHcov53yxUOXyddur1NLFw8+daHvzHOcfsvSNsdp0FyNd55K4e65O0hLz5Cngivbh3JL97plew+FQqFQKKoZF9U9uEGDBrK1jahbFT1aCxOxukrXBFBxSRBhkrFfENfuDvnUa9889OHz5fzr/SzyIk/0SfxkZz4RQ//66JoMlrNvmT4kNjWLVw8WnPo7uokBYyNNpD5r/Jqhhq3MsN/Js1bN2Kk8eMvyCYEkMM36gDR+ssSGkxmxrsj12rdsxTxHPww6F54b3tZqHgvB6Vefu5zTyXKZGGLYwsaQN2njdbYmNsjbQvNaXvJRUbGmSyItdMbr7zFwz5PMS7uNP7lfZggcdwaxy9WQMD8Td3V0Z8fNnrQPLjy6t/Sodhz0CXHCpk+1hf4NzklDLRFRO2mtP0qsy4fvbJphWWUj02mkb+ZrdNIfks8X0ZMNfcOlO3hpeHxPXeaf9EOnc/G+28e0JEJLrR74DFjKwYAm+9gVkdbZG07y0sI94HTIG2zPXNOWD65rU/b3UJQdvRFb6+v40zCAAD8/3Apw6lYUjhg3MX5iHMV4lvmmj0KhUBTAJT1LFyZily5dWu7uxIoqgugzOugFonq9qD3f9o103xxa30iYvxYpfGVDFinWfFJtO94i6wLD9Gf42Pw2nx7xl607CsJYtzPUbCUjk++b3mWgYSuznSN40zq63D7ODPM8uut3M9M2WT43H19Nypnjha+k07G6xlgOOuvg60oi6b/PC/3zp9fZ+TutKbdbHyJT70GNuK3waV84trbcPoeifEyXvp79EW9lPs0E40rq6mJxYCDSoznxnR4kYooXK691Z3oXE75uhZ+ORZq8zeGU/XjfNb4HMfvBYNLqWUuL2Abwkf0q1rhaUxm5zfoIbfXHaKQ/TQqeTO8ZQJAln5KBYrAjyYPvjtfQMjjcFjIQYZqmg8HPg0851brHHpQPL+90Z/HOk9J4SaTu/3ZPTyb1qFc+76EoO0YLpnGfMPKpX1jz2EC83VRWSmkQ4ybGT4yjGE+Z+aFQKBQXgQq9tZhXxIr5giKxycnJFbmbikuAiAjWGnQvdL9bW7DmbYjezedDzDJCIaJVY//IJ7Ii0iIHPI1Lb6Kbfh8vGb/k+s2NSLIW8NMWV6vNroSgFtJN+GPTW/TTb+M9xxjSnaUzssmPSaYlNNGd5Ad7P5nSaNvzOwkphbsDP9k8mhm2KbJuz/fEv5wML1iA1vHSImurXe34NPRV8AvTemrOvhLWfVh0SrLi0pguJUcy4fgLctFyfXeZ1m244QdCxr9O+7ZtC3QIzo8NUdpNmyfN3+MTtQ50emgtWicFlD4anKTVsS5ydGGNsz1rHS2oTJxx+rLW1Zo7jVrfU+/6HdGbS39RHJ7sLk8BnXX7uJ/vtYVdboea5SPYnZkpOLPHdGNmmDwMW9QNYOsT/Wlft5Qp3AqFQqFQKMpftAqBuWDBAjkVV2wK5+CGDRsWGImdMWOG+qqqC0NegOYjwWmDZS/Q1BjD1PZabdj+GBubo/KJsPiHoev/hBS3wsxosu5Phq5rXmD/VnmxL94jsKlM0/zM9CbDDZuYZru3XD/KHaaFpLlMhDvDZGufiM2LSLcVLCaD3ezc08HEl45h8rnPprc4ePxkvn87rZ2JpoFaZOCNfTVY2e5VaNBXM35aPBO+GwdpMefUVSouMaJv7o8T8SRD9vJ9w+MBaSAm2x2Vgqg0F1MMfzLZsFBbIH7Dfvm3eyoWcVpE0OmCWJe3FHNTrQ8WfNxUAA/a7qCPYTet9Me0+zAhHcu0vXa+afiRwofmd7U64vp9oMVV5ba/Hy3ZISOrIvU7yRTIBxM78/c93VUUrzLicsmbDDHx8cQkZ+bbXq264pN6hFa6CNzTI4v8WzFuYvzEOIrxVDdMFQpFlRCt27Ztk+7B48ePl5OYv+6661i2bFmh6wmhOmTIkAuW54jYjz76qDx3U1GZ0Rtg7OfSxVOKrU2f80Q3ExaTZso0fXU+LXAEdTujExET4UZtmksn62YmbW9Y+Pu0uBqCW8mI69umD7BjkvVz5clk0xL2OepIk5uO+oN8sa7wNOEBQSk0btODjc5m+OgySPz3LcJj8v/Mv15lwWw0SNfZ25a4ONT6QRxdpoLBAoeWwrzbtGiamBSXntPbIWYfqbhzj/U+XGWs9eoa9xtPmLKjg+IGRXDLsu2fLUM+6HXwgfldea2ZqvPiafvNVAYSnJ6sd7biSeMc+VwnUvtLKfhzaOaVyT3GXwnWJZLuWReuuLf09cDnsfXQSSbEfSjnd3t0JXxmD0Y20KubRpUVWzr6l+sS9G4D+vzvL+W0LhBZGyYPum2dzl+WJxi2fCQkFu4qLhzqxfiJcRTjKcZVoVAoKr1oFQJTuAeLSTgCiyipiJoOHjyYgIAAKWBFBFbUrIpJiFmRBrx161amTp1anruiqMpuq+LCdOQ7WkT0xHp58X9nOy1193Ccja/DtZYfF9DyaulELHjN9AmnY+J5ZHdo4cK1+ZXYA1rIiOun5rd41T6+3D/aWNNa1jhayfnJzgX8fKjwi+R+wek4mo4ixeVOF/1+fv99PmfSLowCeJj0zBvllps+PWheOo1W92Ns+mOkuyxwdDX8/SgYyy/tWVECjmsGXDv0rYjBj0x7GVK2wxdwY9rXcvZr3dVQr3vZv4o8UdpBhu201x2Q8986hhLn9KaimW6bwq3Gf2imP6kFb8J6lnmbRmsyNxmWyPlVtSeVWQTnkBm1n6A1TxGkS2aPqz5D7v0QszMz14xLoagS+NWDuzeypM/P3G+9C6MjI7fvsEKhUFxWorVGjRpSpIopPj6eJUuWSAErxKtoaSOWiwhso0aN5CTE7JYtW2SLHB8fn/LcFUUVdluV1OkAXaZo8xs/4/524ONmlEGRp9dksOZUAUYsnW7DVbs9HrosPjO/wT8njTyxp5D2Ejo9xpZXstvQQvZpvMf0B3/ZOpf7xxth3MxmRxO5Xw0ify8yhapHHSORdbQ04YcMP3LHzwdl25TzaRds4JmemnDNYYurGVNtD5HlMsLBxfDXwyplqyI4vl4+JPpqEdHDCfbSpSCGL4DNX8rZd+xjWO8zrHyig6J1klFLvRd8Y34Vl8spndzvspZvqnxJsToN7HQ25EGj5iSuaza8fATm8XVYdHbWO1uQVbND2bfndMCunzAunk49XYxMC04Z9yNGT79zzLgUiiqDXz0S/VpxyFWnovdEoVAoLm5Na0rK2VYdAwcOZN68efJCTTyOGzcuNwIrpg4dOsjlIkKrqObkd4HX7zGweEPiMfRbvmDpWAsGg17Wot30VwYRSfkIAL0BXZ/puLxqEqqP4T3z+3x/3I+F0YWYoOiNtOw6jN2uBrL2tLnhFMedgeX+EVc42sg+sZ1c4RC1o8i/b9a4KSfcW8iL7NedrzN5Qf6pxZNamzg8xZONE734Z4In34/yZIO+Hffa7sXu0sOuebBldrl/HkURnBDOtNCjXSvtHoXLxY8HnCXfRrZgfds2hrfsYxlWM6l8hl5kMoh2Odn46tMZp18p59e7WnPIUU5uuqVgln0Cz5u/wUuXic2rDtRqW/aN2jJwZR93b9rG0Tqg8PZCRZIcCYumw9ZvMOLgT0c3fujwLd0aBGgZIzlmXOJRoVAoFApF5RGtwjhJCNO8wjUHEXHNicCKqKsQsps3b5bLFYp8L/A8asCVb2otKfb9SfDRX5h/lbuMKoqIkEiHPZafcHXz0YyZdAb6GnZyv2kBd28PIyqz4JYGwpHUr8NoTrtqyNYa650tZbSnPBlvXM0b2enHjv2Li0670umo124giXo/uU9vp8/k9YX5i12jXk+wp56m/gauCDGwdJwHS+nGLPv18nXbslm5NYyKS4RDc7uu4edDkJdWz/r5rnz6DReEULo75srZo349eNshslZ0DK+ZWH776HtuC5ZXTF+gd9llIPcO2/1UFBm4M9SwWfY6NjUbUj6R5cxE2S4oyuXPBmcLGpTFzNchjOKely2DRBr/I7Y7eDfwWaYPbqxSghUKhUKhqOyitWPHjtI0qX///rz++usFugeLaKtCUSzaToDBz2nzW2bTPn0tHw3WhKvD4aT/T+nsisknVbhGQ3Q975Oz9xl+4Qr9Lq7e0KTQt6rra2Z/He0mygTjKh603SlbbpQXYfoYvrUPYLWjNQadC/b8pl3gFobFC7+uN3JYF0aALoV7zzzD3o1Li34vXz2/XePOt86hnHQFYkqPhg0fKzfhS4kl+7djTWdME+2GyeH4Ir7vvETt1Bx+dQbetYvfpQ53owtzeZ61vWqe89SodxKmi5LzRyooPVAYMD1h0sR6VO3+F+xjaXFkaaUHcS4f9AZ9idoNXcC+PyHpJPH4MiTrVRYwkF+ndVUpwZcpm44lMm9rJAcO7JOuusJdV6FQKBRVPD1YtK4REVTh/DtgwABmzpxZ3m+hqG70vB+63anNr36TEZ77+CBbuIqI/ahf0ll8NB8x0GggNBkq+6S+ZfoQZ2YqT+4t/EK8X5MA1noMkPPPmb9lVNbzbHecTaEsK2P1q3nINo04lzeknYEjK4peyeJNgx5j+cfZRaYKt9j7Ntat3xW5WpsgA/d08eZd+2j53L76XchMUsYwlwq37Dp9axqTWhuyy5hd+d9kyY9dP2uPIe35J7GWnG3vW86mPiK7IQ+bHY054tJqwLvrwqkIfHTpeOsy2OJsgrVOj3LZ5tp4L2buCMgVrXd1KH2vVzISciPgL9smcJoAnhnVCg+zKG9QKcGXo2Ad99F/vPXTEh7ce5101RXuusJlt9Q9khUKhUJR8aI1B5H2K8TrrFmzLtZbKKoTQ/8HTYZo/Vv/eZKRjmV8N9JDSxt0uZi6KJ0uc9JZdL547ToF/MII1iXxpflVfjnuLi9gC+OKTh2JN9UmUJfMbMvrTLE+zNe2geXyMZ4xzSHW5cMjtmwRfmoznNlb5Hp6k5ka7a7kffvV8rl511w49l+R693TzsDv9OOIsxbGrHjtYlsZw1wc1+vzMWYLI0cWtTz1sh5b8MvhYojWhGNwepuMrsYF9yDFpq17c2hsOe589vtkIzyibrY+Jg8pkyuLr82vURGILAThfv2wyHSwls35WnymO7fX5/qNDfF3abXAPr7+PNq54FKBQhEp9stelG09djgbMs/RlzqBPtzSvRCzN0XlRGfA1uwqluiuwMfLC3P28Xk+R+PSpc3dhNY+0kjvcJ+3YepK6bIr3XarOWLcxPiJcRTjKcZVoVAoqpRoVSjKFdGeZvjrWvRUpNSufZdekbP54xoL3m5aD9eYNDt3LEpn4Lw8tZvCHbX/47gMFtroj/KF+Q1u31yXBGsh/1j1Rmq0H4XV6E0L/QnmW57jS+eVdM54j5POst1ZN+sdPGGcwzJHBz62j9IW7v0NUs8UuW7nGpmcrj04d72slW9BWkyh64gUyCntPXjXPkY+t274QjkJX0zX6/wEoacWzaztpf3m1kUWw4zp0D/aY2ATPj7dNLekc1hQOZkwCaLDIVxz53W6YLT1GdJ1HjIi/In5LflbrSg+c4zgqKs2cdZSikuRip1modXyNiyK9pHjJ4zZBO0b1Cx9HevylyB2v+xnK248OTAw57ZOpd5HRQVicsN0/bcMfuZvNjw5FF+Pwn9rrUK0m52NmneQ2Q9KsGqIcRPjJ8ZRjKcYV4VCobgYKNGqqDp4BcI1H0Pvh7Xne36hza6X2XWDnjcGeODnrrXEORxvO7cljk8ddMNfxaEz012/l/eM7zByXUMZhSkQjxqYO96AzeIvL3bnm5+lpj6ZXllv86e9S5k+xu2mxfTQ7eJV+7WscrTRFgrxUAyjpJdanuQbw2gZ5bG4MmHNm1rbjUJ4sKOBxfqeMtpqtiaw6eeKiaBdlhTU1kSkkKZnR0V9tJT0jOw+rUX2axXi6PByOeus2Zb5kf5yvqGnlbKUYeYiVOmJDbj2/iGfLnJ0onHmN+ygmXw+QL+ZAYadVCRf2rV2T1Zn6QyY9qS4Mfi/ZmTYhWkb9AlM5frA7DrE0tTIio2se0/2jHYY3LghYzoHXXW5pmMoDQJUSxvF5cuSfTGynlekSSsUCkVFokSrouog6sW8g2Hg0zD2C5EzCyc3wt/TGVs3le03e2DIvqpfdPQ8IRfQCMPQ57FhZKBhG886PmDqtiJSu9z9MXWcCF7BMlX4R/MLdNMf4G7bg2VOF/7ePItgV5xsSyN6O8paUyEiiujfKni4aQz32+4mzWWBqF2w59cio63zr/HiQ6cWbW104HOe/3ltmfZfkU1BNYwnN8sHl0cAsw+Y6PRtOnFpWur6/R2LiB6e2ABZyThNXlyx+0ris7MCJoUVHlUvFuL3JXr3Hlkub/DMtg9hmu1BnDqjbEM2SreaL0zCsbsCqduVRLzlrKhHLynbEz24cm1TGT0Wa7/f7jjfdDyEPiNe+wMvrT64xL1yDy+TbYIeNT3BThpjMpl4c4zWg1ehuJyon+dGzNtL9vPoT9tkXa8SrgqFoiJRolVRNWkzDiYtAs9gSIiALVovy1rZKZjbzuQTRq3ZGtOQZ7FiYrBhK2OTZvPJkSLSfYUYaXcj+IXKnpGiLraj/iBP2yez0N651LsvtPUyy6M4XDDV9jBZLiMkHIGU00WuO7pWAseozQv2m85eUIvoXCG0DDAw87rBHKW27EU7dued3PLJcmlkpShnxM2HebfI2b9TG/PsmnTi0rU2MmF+Jq5prLW/KZBswft5Rj+isixSZ/YLSmVivSJaJBWDjONbZLRQ9O992nYLz9huoZYrlrv0C9htmcx7lo/KJ5pbFup1zZ0taXWcqFe/ZkNjKVbF9E2nCEbViod9f8mWN1pv2vol2+jRNbDlKzl7pNOTzE/SXMgndAnFaKzowVKUGlGH/qyvnFo8Np+YFK1FlQK6hPnx6rh2cigeGNyM8V0byLpeUd97PmLcxPjljGW+9f0KhUJRDqj/uIqqS93OcL3m4inTKROO0qyG9pM+nlxAymzt9hgHPoHVZWS4YRO1ji5gQ5x74e8jDHXaTJAXu566LL4yv0pz/XEZoTrgCCn17nvorSy3PMwBZwh/OrNdUiO3FrmeEBX9AlOkCYzoOSmjtMeLjpwGeJoIGfkUCfjSSn+MB089zPj3tTRURTkg0rv/ehh+nCgv3LY7G/K09VYpOkN8TLw90IOV1xbxWwOSTu2Rj2udLaTweqxZFLM7lkOLjcRjmCKWydkX7RNZ52guheo69weYbv4Zb30mFYrFBzreytb0YHmBLChJe9Zn94Vw/aaGuc9/6nyQvmyF7d/BGeGErIO+j4G7X/E3KkzSRAo+cLrZzcx2jpC9XsV3em/fEopfRdUj8QR+ieHVss1Nq9patsPg5kF0rV+CY0ahUCguEkq0Kqq+cG1xlRZX2TaHqDQtndCsL/hqV1+3M9Y+M7G6DFxtWMfhHatILzxQqdUtthoD3iH46dL41jyL+vpoxlqfKbw2tgiC9CnMMc/iW9sg+dwRFV6s2tbP2kfgZtTxg6O/fJ6+eW6R0VaBOSAU/6tekkYy7fWHmRE7k1f/rNj6xcuCM/vg80Gw6XP59GP7SMZbn8U/IJB/r/Vk7fXuRUdYRfAnNQHfzEg5v93VhJ+7HmJag6JNuorEnimdo406JwscvYh1erLEbWbFC9UcfEOlYJ0d35rRGxrLReJI7uhbdNTmUKqFTitaMftYoBS74jOuavwD3Q6/o9WKJ5/SIqz9ZkLYFcXfp4SjsOwFcFiJrzuQLS1n8PW6o/KlYH8vavkqw5nLmsQT8EFXBq8ap9rcKBQKRSVAiVZF1WfAk9pF6Yn1BMRtkYuGNihcIHg17MaRdo/idOm4wfAv320oxl10g1mLuHoGyRY635n+R6A+lbts95Zp968w7OWQqxbhzjDZ7oPo3UWuI7ISl1yxn9mOYcS4fPBIP0niWi2FsUj86+N15Yuk4kFX/X66bLiH1fvLQRhVV0Rd8ad95fcmotg3W2fwsv0G+jTwZMk4dxr7Fz/J9YsVWpT1gLMO83ueoot/OfVlPaUdF4ectXncNplGuigqDXU642x9Lffua8Eze0Ok8BT3nOZ2OUKIe+E3Yg6kWBj4XzPisrQ+uK18Mglv9DGhJ38HUcMq6t5bj4NxX5VMsLqcmmDNSiY1oA37r3iTmb8f0KKsOj0/TSmbGZuiCpAeJ1sbbej4KldmvcSSPj+rNjcKhUJRgSjRqqj6BDWDzpPk7Num96lJHA90KDqq1bxDL5YE3Sznpzh+YuGO40W/l7Dzb3stuNegrj6WP8xP4C169zlL2UYjmyH6LSxw9JbzrrjipaGJC/qvu0XxpE377H5HfidqU+GmTLkENEY3+FkyXGb6G3ZwYO7Dqr61NL1Z0+LghxtkJHOfqQVDMmexytmOoQ0tfDEku09rMYlKc/Jfdkmzt8FOI89yrLGL2ScfPrOPIBOL7BVc0cRZ6vKcx0w6nrifBv924I/TvjId2M/sYH2fPVxRI7XIbUzZrtXaCV5ufYq/2m/Ecio7Vb7NtXDdd9DpVvAoYasqkXKfGo0LHXsHfs3ba2NJScuQwvi5q1orx+BqRLJXQ8JdDUj0a6Xa3CgUCkUFokSr4vJgyIvscTUgQJfCVx7vEexWvB6TQ0eM40fDSG0TCT/wz95iOLSavaD9DTh96klzptfMn3LYVYdop2+pd/8h03xWO1rLeWfSSa33ZzFo55vO6LY1edl2nXweHP4FtiOri7WuZ0hL9ra4T85P5ncWzX2v1PtfLXuzZibDz7dC4nGiDbUYn/wgMfjRN8zCJ4NLJlgFdy61st+pOVrXckUX+zdQJBmJuf18/3NobrfhrjAuJXannt9s3XKfz7X3p0fSS3wV30a6IwvhKQRhB78MNvcNJ9it6M++Id6To2lmOT+9aRTX142DI8u0KGmtttBhIpg8Sj9mokzZ4s+s1fGsPxgtn3dvUpNbexThOq5QXE7EHsit6z1wYJ9sf6Na4CgUiopAiVbF5YHJnRe8nyTZ5UFL5wFcW78u3no6HcPG3s6vzt6yFq539Lf8vLcY7odmL/Ttr2drjRGyNnaIYavc1glHCSM62dTVxxHl8pWpvgaXDZK1usbiMKxmEl3btuYb+2CtRcjqN+DExmKt27FbPz5Ha4Uz+ODzcGJTqfa/WvZmFeMcsYp0LExMf4gUnZc0XPpqSBEtbQqIsm6LshKDL1adRYseClFcHsQdyp0VzteCba7mrHa04mJzyFGb67Nm0Nv6Fn2NWtr7p/YrmWm/nSxMeBmdMgV6ZrPTbB0Qzi/dDsrU9+Lw5L66MjLrbnBxl6j7FTWosQc0w6WuU0vm4nQ+wmkYOJblxdaIM3JTAT6efHdrx9JvU6GoSojsBHHTZ8GU3LreB/dex1s/LVEtcBQKRYWgRKvisuHJG4byiPUOOa8TvUsPLCrWer7uRnpPeJCVrg6466xcGf0J83cWo8ZTp6djm7Ysr3c3h5wh1NQlEqxP5jtb/1KZM/XX72CtU4u2El8yp8oBwams8BvDIkcXTNhxLn8RYjWBUhQ/ul/LP45Ocj3+uL9YvWKrM6lOC1+sOQKbPpPPH7RO44CzLr3qWVhzrUX2xS0pD66wSqGq0xkwiV7EgqxyEq2pZ+tX3zZ9jJsrQ4qwKdaHymQiVhjHnYEMz3yRgdY3WOdqyyumz6WB2T4aEBUySNarRgzeye6Bu5nX9RB31I8hwFy87AhBVKaJA8laNPu2sFjNaOrA39qLzUeWvK1NNgmZThYctDNne4J8Hu/0kIdDj6a12PRYH9Xi5nJCZ8DWcBCr6IS7uydmg7ocOge/eloN79SVcjrc5208dFk8NyTknBY4YtzE+IlxFOMpxlWhUCguBuosrbhsaBXizS7/Abxnv0ZbsO4DrcdiMQjwNNNxwuOsQhOuo+O/YuGW/cUScEMbeXCy5RQWOzpj0dmYYFzFg7ZpJe7jep/pV7kNQUZU8d47Lx+2O8b99ntZ4uiEXqRIrpgFWSlFrhfoaeQR2x0yYihbgxxRbXAK4q4fdtHq2cUsWqn9ro47g1jk7MbD3dyZM6J0gjUy1cnak5rh0FVNzOgM2Rd95XXzII+AE7v3mflNuelMnTv32u6mPDnpDNAiq1nvspeGUhxP0C+jj2GXfM/mXQbxdItoetRIK1M/2Bnh9eS2xfRQw1Ow/2+tDtWrJnS4scTbe2atlYafpdJ+dioPLUtn+SktSmvBxmNXtmbupE6l+m4VlRiTG6ab59Pn2WVsfWYYvh6ms67Bkduzo/bVHCFcQ9rLqVHzDvm2wBHjJsZPjKMYT+n7oFAoFBcB9V9YcVlxU/dQ3rCPZ459oNY0Y/XrcKro3qcCbw93Ol/3ND/phsg02xGpv7Bi/XpwFh0B6lcziw7dB7NS3w2TzsGb5o/5x9mFZ6w3FXvfG+mjWOtoQbrLgrstAVKyXXmKiZsRHm9+hodtd3JUGEOlndFSWIWALYT6PjqS8eIne19twR8P5Nb0Kc7y0t8HWbj9uIww1NLFy2VOz2A23+TJfR1KnhKcw8w1NnTit6rTMauX8axYLUt6a16CW55jRNTbEE43nZaqu9hZPi64kU5/xmY+Sc+s91jnaqcJSpeDh/Q/8IrpC/k3ukb9S26IlA8iOrwqzkvOjwqKwbh3AcTu19KC+0zXas6LSabdycB5GXy9K1MakYn9FqOfYdCMqpr7OZnW59LW/yoqvs2NdANfMEWmx2aZ/dVXolAoFJUAJVoVlxV39grFw82Np+238aejh2Zm8+9zsP27YolPD4uJa66/m/cMN8t2OP2sK9n53x84rUU7uQZ7uOjbqy8x/h1l65q3zR8Rpj/DM1kTi73/Dgz869TuaJfmTv8tobHYjB7cZbtf1gxyajPsnl/oOg91Msoo0pv28Rx3BkPiMbZ/MJHF4aoNTg7rIhL4ZKX2fQT5efFgF3c5X792MEEeZTuNbo7STIeuqGPGw6Qvf9Eq2kGF9Tpn0XTTT1ypX88A/fYybTrdaea6zJn0yHqfLbTMFavX6f7hoOVm7jP/rn0M79pQt3wE8u/RfnKIglwJvO54RavZFZ+x7wzNSbyYHE5w0uHbDA7Ha1HuFkFm/hjjScQUL76/RhMqbvaiMxUUl1+bG8Z8pqXF3r2RDI+Qit4rhUKhUCjRqrjcEOJr7u1dsWOQKbr/GnuDywE75sKy5yGr6DYaZpOBu28YxyzPR0l1udHWuY+d6xaSmVV4z0iJTk9Qm8E46nSVTycZF3O3+Q++t/Ur1v4LoRntyr6zby3dBfOgoGT2uOrzjO1WbYEQ7NaCP7cQXT+NcicJL+6y3UeWy0j71NWs+n4WA95ei91+kQofqwipmXZu+nKTvMOnNxh55erm0rRLYsso07aTMp2kZmo3U65vbji3llWvOeOWC0HNoU6n3KedDYf4wPwun1reLtNmr7S+yHpaU1cXyyDdJj4xvs5ht5t42TIboz5PenOzEZqwLAc+P+zLSP06/nJ7AnNapNY/edjLUP9cYV4Y++IcDJqXTqbVRg2SuK2Nmb/HuNEmyIDeng7rP9D+0DOwXPZZUQmxpuF6sTbpzwTT/LH5xKTkuTEZ2FRLixXpsYpCEeMmxk+MoxhP2QpMoVAoLgJFN7NUKKoY7er6cHufxny56iCTUqbxYqN+3BT9KpzaAn8+AP0ek31KixK/T4zvw0t/BXBvzLO01+1n7ToTzbpfSYBbEREwnQ5D4wE4/BtwavdKQnVR3GBaQYQzmAb6M4Ua/Aw1bOE2Q7aBVECTUn3+RxpF8nukLz84+vG45+/4WKPh4FJolV3rmw+daxlkmus3e1rx7eGJ3J45m6eM3zIyujl933Lw36NaD9nqyJhPN2G32XCi48kRzXA3G0mo04/Q7W/A6W1aBF9fOvORb/Y6slNSdVzZQA+pZ7Kda3XlK5jEmzQeDPV7S5Ov9REJuKVHylTntv42dAZjic2/PrBeyXDDZm40vkIdXdyFf+AZBMGtoFbrEqXs5sexFD3bDxwiOGUPC9iLOce0yTcUBjwJPsWMhtnSOb7pT47v38Ni02lCdWdw09ngqCekt4CareDYf1r0VuzzNR+Vab8VlRudPR0PkR1Q0TtS5VrgxBBCbO4iMX7CpEl4+SkUCsXFQolWxWXJ04PqsHh3JKfi03jycAuON/+Ih2Ofxi31pCZcxcV7+xvBt26h23niylZ8sewprjv+HFfodrN8nZFGXUYQ6lV09NEQ0ICQnqF8vPYYNzl/yxWsNpdB1r3m5Q97V5Y4O/O26QOZWixSjIMCi5/qmJcwTxs+ZicpNj3fO4dwJ9/C/r+g5VWFRrtExPXhznroNAb+3YXbqS28Z3qPsXHPsfxAHP2blr0esSqy/3SivCjr17wWrWp5y2Xp/i2wm7ww2lIh6USp3Wo3Rmm/oxruBs3oRwgmgfhdGkpfJ1sgRjdZ47o6qRYfJGouxT7xTn7qcojmzePhyAqI2lmsTU0xLcasy75KFb8rUa/qGQxewVCjoSZay8CyGG++OBbM9kQzb+jf42rD5lx1cUofQkiLHujaXVu8XqwOG879f5O+5QdCncmEnn8Y2NK0VHoxCSw+MHE+1FEtbhSKC1rgAD0tFpalLxR3V9UAKRSKS4KqaVVcnljTWXhrI3w9LTLI9Ok+N+73e5+Y+ldprx9dDb/dBZu+AFtmoZuaPKAtK5o+SYbLTH/9dg5u/JvDycU7dIxGA1N7NWSaZRYf2UbJdOO8gjXVZeGgM4TaukTeNn0kBesWt+4yxbgsNY29A7R04A/T+4PRopk6HV9fvJWFAOn5ALj50kJ/gh/ML/Ddih1UV/TZ30Nt3zyumDo96f4ttfn4w6Xedk75qiknUJvjdi3SeS8iDzeKkg6+4v2TbXqGrm3K80caa2m87ScWS3AKwbrd2ZCDdcdCr4eg82RoMQrqdSuTYLU6od3y1kza2oB1ce78T/8JwwybyXKZ+MJ8A4s7fECdmz5F1/m2YglWu9NJ+G+vod/0KV7OZI44a/Gi8zbCB34N922HJ8/A1BUwdJa2/2E9YfI/UE9L8VcoFOe2wNnQ8VUZWbVYtdZQCoVCcSlQolVxeWL2wNfDjQ0PdaOmv7fUf4sPpzPqzFRm1v6cvT69NFfdPb/AH/fCmT2Fbu7KKzqwrfVMMl0mBhq2EbvlF06lFq/WUwTQvulxBlPjflyR9S5v2cYS59Iidl66LJroI+lsOCAdi+MDO9Opa98ym/BMDdOiukkON+ICsg1wts6WEadi4e4PA58hWedDW30Ej5x6AFJjqI4Ys1vQxKedO3au3O+onE6jIjVYuuCKmrrSRdmLi/hNzu1ymHfbHUefnR755dFAbtzcSIvydroNGg3If2WTO+vNPbg663nG2F6kSaMmoC+/pJ0bNzcmyapH53LypvkTrjasxYkey8DHmHz9DQxtWzw3X+EGPH2VlSafp5OYmCSXzbP34ZHaX/HIk2/Qqvc1UKOBdlMnpAP0uAuunQO3LYTgFuX2eRRVj/DTKczbGimnjUeVk/r5LXCSvRpW5NejUCiqKSo9WHF5YvaUk4iN/fdwL4a8v54jUQlExSczN96DudxFP30PXjJ+SZ2U0zj/nkFio6up0f0m7SI2H67o3IXNpmdotu0luun3sntTJgHdR+HmXoz0ROD2+jEMCU5k/KareTtjDP66VEINcYTpY+jlE8v4lp7U8Djb/64stPdLx6ATbsTwinUMr5q2QXIk7PsTWo0u3kYCm7Kny0s03PAUzXXHsH91JcZbfwfvWlQn3EwGbDY4k9eoRWTLJR7SZsrBrEVGXI9lR1l964GlbDWgxeXq2okMCExm9MYmHEq18F+cJ3dur8/H7Y9C3a5Quz2c2atFk91raLXgPiFMWd6WFJee9n5lM6I6n19P+7Ex3gOTzs53vh/RzbpOVszp+83QIrjFJCHTSb+fMknK0NKXVznb0NMQzrCGJsZPuqJc91lx+TH95x2Eu7IN0bTmadQPKN55XqFQKBQXBxVpVVz2GI16lt7XnTFd6suoq5vFItM7lzs6MMz6iuxPqsdFjcO/cvKH+0lLiCpwW53btWdz+xdkpLS1PoLETd9rEbJiEuphY0PfPRwbtovtQyP4fVAy7w2wcG3nOujLSbDmFa6Cn6NqYa/fR1u49RvI1KJOxSHVI5RrrU9x2lUDY9x++GoEJB6nOtEgSBOQ247Fsv2U5ujslnQEU1a2+ZBP4XXRhVHPW4vWxqQ7cEVcmtTg8/E2OVnacz9tfbU0+b+jfFgY7au9KJx5a7eDVmOgYT8ZhV14xp9kq/av48765dsW6cX9dQjSJfGj5aVcwUqfR7WU3WISleakx/cZUrCKmwEda5uZPLyH9lkj1xRZDqBQCMZ3bcBrEzrI6edpPekSVr7nZ4VCoVCUDCVay4mkpCS2bNlSXptTlBfCfj81Br09gzfHtmLDjD7se24QR2cN5+BLw3nr1v782vBZbrfP4IzLj7qOk2z45X1e2WST6YX50b99c76q9xLHnUHUcsVi3ToHEo5Vuu/srdbHZITA6YIn40eAV01w2mDHD8XexptbbES4ajOJZzWTHRFxWzid6sS3t3TAaDLJGxuvLdqD586v6bAo24lZuOOa8tS6lpBHOhvld9Seg+jisvvylqDXaHnya9cDeBmdMjP9nh1h0sjrfMQhMXNPPfk3/mYHw2oW/wZIUWxP9ECfmcSP5ufppNuvpRz3fwIaZN9wKQbHkpz0nptOps0hx/Wpnu4suMqN4JCGWv2rPQvOhBfZwmNfVOq5LVAUlx86PbZ6V7DB1RKTxYJRpKbkoWt9P8Z3DJGTEqwFI8ZNjJ8YRzGe5dXaSqFQKM5HnV3Kgb1797Js2TKuv/569u/PrklTVA6s6eC0a4/nYTbqGdQ8kO8ndeTjZx/jk8YfYXfpGWDYztptu2j8RTpTl2RxJu1C8frIwIbcanyF9c4WmF1WnDt/gph9VCZEVLeLv/a5fzgVQFLoQO0FkSJcjH212p2Ex2h1nJ2b1NUEhODQEmJjzlSbi35fDxPz7+hOO91h/jLOoO2O57S+t36hcMU9Zdp2gLueRr56XjJ9oS2oWfb2MGWpc/2xy6HcGx1Xrm9G3ha96XYdvde0kPWmIoL5fPNT5fr+b+9x50fLCzTSn9aMnK56H0K7F3t98XsdtiADm8MpP8PLfT24vU22A3NKlGx3g84ANRoVup24NBtZdqd8VFzGmNwxTf6bbs+tY+dzI/H3KMe+yNUIMW5i/MQ4ivEU46pQKBQXAyVay8iZM2fYtGkTo0ePZsWKFTRrVvIoSVZWFsnJyedMinLC7KFFbMRjESnET900AmurCfL5/cYFMtL6z5Esun6XxuqT57aoEcwZHchtjpksdHRFjwPXnl/h2NqzlrCVgI/aRcgLeMHEQwMhSBjMuGDVa5rwKoTv94vOpNrabkYdBDTShJrTTsrOP3Kj2Oc3k6+oi/6LeRy1S1/HfLcXaKE/TqLLkx/9bodR72n1p2Xk3VoLaaU/Jrf7t2fBvXQvBa18MrmzgWa4dTzdRKMlbem4vBVD1zajxb9tOJVhkj/vYbWSGVW7nAxq7FmkH1rDh9YnaaCPJsFUE4a9XGQ7qvN5ZJWdDKtD7t9bAzy4vnkey4aTG7XHsCvAvfA0zwBPExajXj4qFAqFQqGoHCjRWkaio6Nz04Ld3Nzk86VLl7Jo0aJib2PWrFn4+vrmTvXqlf1CWJHHkMkrSHssBh4Dp8v0JhFtvS3kOC5RU+dycduijAvShUO89Mwf7cu99gf42j5YayF5dBXs/hkc1krxFQRZHNwWpjWB35nkzoagseDmB6nRsO7DQtdtHyQkq5Yy99n2DMI+SeGtmM7y+eEV3zLl+3CcdusFUeyKuui/aMfR/kUw93qMLivr9R3pl/Um72UMBX1On5oysGMurY99I2dftV/HvftaypYvFcnMpqcZGJwixZ/49uOtBvanWOS8uIVxR8MYPhFGTWVF3OwQN3k2foLHqTWyhcYWZxPcr/yflspeQk5mu3mH+BgZ0ySPYBUpwQcXa/OipU8RBHlbaF7LSz4qFAqFQqGoHCjRWkbc3d2Ji9MMWURkZ/fu3Rw6dIgRI0Zwzz33kJ5+YVrq+cycOVPWxOZMJ06cKOtuKUqLiCa2u17OPuMxn19Ge8iLd7vDyQc7Loy2tgww8NdYT553TuZR21TZEkfWfYq6UVv5OquWlqebRuJucMk6xDt3N4MWOb1qV4G9YFOa9sEG1t3oSeMaWnRNSNilzk7ytc76AyzZF0PvTw6S4jRXiov+i3Ychf8CLodM3Z0b8hiJeEt32jIjUrS3fydno4N78519gEzHvX1bxbeT+KJDBHsH7eLp5pF08Msg2GJnfJ0EdvbfzeNNT5d+w+KHJOq/RVbC+g+036AtncPO2txhfYDvG7yMm2/JBavA16LdYMnKe5gKx+yFD2vmYSLjovmVBWYIKKoZ1jScrzQk7pm6NH9swWVTznCpEeMmxk+MoxhPdVwpFIqLhRKtpSAmJkZeFAsaN27MwYMHGT9+PBEREQwcOJA777yTzZs38/XXX/PCCy8UuT2LxYKPj885k6IC6fWQZiZxchMdDUdp4K9FDD/cnn/0tHmAgZXXefCHfiDXWZ8iweUFKZHYt30PWRWf6i1qFV9rfULTC1YDH8a2A312FDQ9vtB1RTR56Xh3fh/jydsDPXhmaH253E+XJmt5TyWk0fG1jYRHaq66FclFO44aZ9cCZ8TT2F+L4KVby5gC7nTA+uxId8021GzRkytra2O4MsaLtfEVU9eaFw+ji0lhsfzS7SAb++2RvyFfcxnEetIJ2PIl7JyrCXaXk0OmpjxkvZMh1ldJqNWLN/qV/kZHDTdNtGbas7+bk5vgzwch4ahmInb9j+AfVmiduxK01Qt9RhwBupTcMghF6RDjJ8ZRjKdCoVBcLJRoLQUi/Tcnuir44YcfZFrw888/n7usY8eOLF++nMWLF6sa1apGYGOtxYdg10/M6m2Wgk/Uy325O/86zbreenbe7A41WzIh6ymiXX4YM2KI3zCXBQdtRGVWbH3cyFqJ1PfURPdbh2uf7QNahGjNoV2wgWsaG+ka6gMGTVhMbOOOkDA2m5Xxn27gsqXZcK31S3Ikvdw1l2iRKv7B9jLU7O5fCPFHwGDSWsmI2tY2R7FkR8Sf3VeHqo5wH35odyjj/qvDghXrtahyWgypLje+cwxihPVlBqU8ywJnH1oEu/PTqNK7MAt8sgP+Toddpl3z7/NgS9P6zd6xCpoMKrrOvTBBq1AoimTB9tNsOlZO9e4KhUKRByVaS4DL5eKrr77i7rvvJiXlbGQpJCSEqVOnsm3bNiZM0Ix8BG3btqV///54eVV81ERRQvo8oj0e+48emauo66uJzlkbsgpshSPciH+92o3xPZoyOut5DjlDqOFKYNCpD5m5KpOG/7Sl/5rmPL8/hGNpl17EftT+qBTfNidEOv21heklvDMuFJVHDTk7pqGLewZoxmNpGVnsOV3x0daLgsUbmg6Tsx0OvUdjt1Q5DK9uyGDOHnvJtyf6hG7+Uptv2D+33tqoh1D3ylELXRbE4fHU3jq0Wdaa/045edf2DGN0K+RrP9j70SvrHZ6wTWKPM1T+HjuHmPn96rI7t0YkiWiZi09Nr2enXbugy+1w61/gU7t4de7FNG5TKBQQE7GbXxctpoXubMu3JxbsYNxH/ynhqlAoyh0lWkvgTPr+++9z++238+GHH9KuXTsSEhI4cuQIu3btYuLEifz5558cOHBACtf4+Hi+/fZb7rjjDvQiP1NRsZS0ji24BbSfqM2vfoNf6nyH3uXAZnfy/IbChcrUtiY+HB3GM74vsYXm+Ogy+ML8OtP0v3I0zciXRwPps7qFnERvyktFS+9MQj216OCBjOzUWUcp6rh8QuSDZ/weejfyR2cwShH33opyMOeppL+XhLa3a2Im/gj/uD9GN/MRaUz0xOp0fjtcQuEqVhQDJjgvKzHRppk7BZpLIYYrAXNPBtD83zZ8ezxAfrjXTR8Toosn2lCLL+u+QFrX+7nnimAe7ebOfZ3cmX+NJz+PciuXc2REkpOOuoP0YZu24OoP4co3wGi+aMZtCkV1JLhmCOkuCzeceJYp4TexwPJc7mujO9eXp7ijcSpbQaFQlC9KTZWgXq5mzZq8+OKLXHfdddjtdubMmcOvv/7K0KFDZR1rr169WLduHQ0bNmTJkiV07dqVpk2blvNXpigVpUn7u+pd6HqHnA2O+JUF3q/hRwqzd2URk154bZ8wMfpuTBCdJs6CpsPR61w8avqJOW6v44sWqRMtRa5e35hha5uReYk0yseiBY4LDK7sNxTpqSUluKV88I7RXLOb1NIE8MoDBfdureq/l2j/Tuwb/Q9Z/k3QZ8Tzg/FZbjCtkBdn9y3N4M3NJUgVNrpB50nafMQKrX9oNqkOTbSGuFWtHqHCQOrKdU15bHcdrE6d/I1N8VpPb8NuWR9e86rnmDSwA5PbmGTv1Lvbm3ios4nOtYrnwFxQdkNeotKcTDL+rT3pcBN0uLGsH0uhUORDu1atODhhOUv6/Mxv3X/gUeuU3Nc6h/qqMVMoFBeFPH0BFPkhoqn//fcfI0eOlBHUf//9V4pVb29vhg8fLo2YBg8eTI8ePQgKCpLGSy+//LIazMqGSPcTAqQkaX+ipcmgZ6BmK/h7Ou3tO1lqeZR37GPo9f1gfhntJd2DC0WIwh53Q2ATWPc+PV3b2eE3nZ/8JvPkiY5YHTr2pVjo919L1vbeI02TLnYfzg7+GZjSNYtVJ4aS37kSUegc0epy0bthAAdOxcsU4cqKED0Lw2NISD8rBrvV96NpTa9i/V5E+544mpEycTGWJfeh2/cn/zN8SgMiecl2A+9uyWDeATs/jrQQ6lOMEW06HA4shoQIiFipPRcmQg4tAhvmUXnHMj/B2ndNC9nDVdyMCbQ4+KLtQdodmgPi3kjrseBT+hrdpcccTF6kCXtfNwNN/PV0rW2gVYCO9kF6LAYY+WsmAbZohlk2aSt1n1ZeH09RDRDprcbonZAeUdG7UqWEK61aSffgr1furejdUSgU1QAVaS0E0b5m06ZNPPPMM6xdu1YuE+7AokbVz89PClZBmzZtWLhwIcePHy92VEBxiSlt2p/4+063wJTlENiUQF0yL5hm86PhKe5fsJ9lxy9sg5MvTYbAlW9q/SczE5kQ/Tb7mn3JTSGnZVQqKtPI2E1NuBQIwx/5psCq0kRHA5uCzoAlPQqPhL2czm4VYTSWQ9/Si8TdP4Zzz3ebeeqXHbnT4DdX8vl/2jFb1O8lp41PYEAATPgWetwjl08x/ElLf7scztMpNnrPTeOTnbbi3RDpdqc2f3qH7FeaatPJelBBzxopVU6wijEYHZLI5n7htEtZDhkJWk/gNuPL9B7vbLVJd1IxJWfa2XLaykdbM7hnSTq9vk+l8zepRKfYGWdYiVHnhAZ9tRtNCkVh6PTYg1ricOlkeqv/nEGwYAp2gzsJLm81dsXEaNBhyM7YcQQ0xSWc9xUKheIioM4uhURYRarvkCFDWL16NVdccYU0YhJcc801MhVYtLrJWVanTh05yUFVNayXHzVbwrS1RPV6CZvRk/b6I/xlmsneJV8wf3cxnRIDGsPItyGko+z7qT/yLy8kPsaXvp8TqotmW6I7j+wOvdifhFAPG5tNWr/VTlE/ltyMSaS3hl0hZ+tvfpHIGG19P49L25e1uFjtTv7eeVLOO4X00enlo4gKHlz4LpnvdIUPup2d/p6RK+rzRRzfwpxJ4FWLheN8ebqnu6xTFcLqf2sz+Dq8GPneQli1uVabP7qK9B2/EKhLkm/d3qfy14NZndBrdctcwTq+biJvtTkOqdHSwEwijJBMZavb3hunjWXLIDO9Qy0EehrlOTbnGxLfo5C0N/iFawvajCvT+ymqCSZ3jKM/wqBzwZjPYOpKOS3q/yeRBFb03lUZ/D3MzLurt5w3jP0Mp6FsLuAKhUJREEq0FkBqaqqMsgqSk5M5efKkrF8VZkwCg8HArFmzuOGGG8jMzGT9+vVMnjy5wIFWXAYYTBi6TeHY9auIrzsQs87B3cbfGbj5DhI2zwN7MVI6hdgZ+Ax0m6alTDptDLQuY4XlIeaYXsJ+ehefHr74NUFdWjZlm7MR3roMTv/7fuEiLT/a3SDbwPhGr+fF+EcIJIl6NSqnec0HKyNkT1AhVD+5sSM/3N5VPpr1TmYav8ctYb/WNzRn2vAxbJld8AaTT8OaN7X5TrfKqKmo1dxykyeeFoMUUU+vSWfrmWJE4TveBN3uklGf4LR9LLLMYLBx20VPEy8rq2O96bi8tcwQED+dCXUTeL31ca3/7L6/5HgT2kOLepaBwwlOaX4mmNXLxLfDLWye6MGRKV4cu8OHTTd58dUIT3ZP1FEr/cBZR2aFoqTZIyHt5ZThoRnNKRQKhaJyUckvjSoOk8lEZGSknDebzbIPq7i7//TTT8sU4VOnTknRevPNN8u+rd27d6dRo0YVvduKi4xIE23cqDE1Js8ndtQ37HfWxU+Xhn/41zgXTD0bYSoqNbT5lXDNRzDoOajTGRE36mUI523zR9x44ll2bFoJtoyL9jlWxvsx3TqVLJeR2vGb4NCSkm3Arx4MeREsPrR2HWSB+Wl80s+2PahMnEjIzL3R5OehpbGJx2u89sjvLsrlj3PwizDkf9Amu2XVohlaH9X8WPaidoMiqAWE9cxdHOCu55rG2vZFZermqGKWCTQfAaPe5bQplCBdMp+bXoNDS0t+I+EiIUzCFkX78uy+ECZsakTnFa2YuLkBqXa93MXb6sfyWusTmnHVgb8h7YzW17b7XWddkkvJhmhnbiRV9Ao+nyAPPf3rGfCOC9eEco1GxBiC2ReVKmvtFAqFQqFQXB4oI6YCqFWrFgEBAXTq1IlHH31UOgaL+RMnTtChQwemTZvG77//Ls2YHA6HvCBWVCN0OgI7Xc1/xs588uO7PGT6mboZsbBiFrS9DtrfIKNnhW9DD3U6aVNqNJn7/yV617+E6aJpl76O6HUHCWo/Cr1PzXLd9T9O+/HB4SApBr7UjWYa8+DAIq3utqQuwsNfI+Gvpwm1RfNq0iNYTzXFXKctlYk7e4exZH88OOy8/u8RAr3MRCdn0TUtAkyQ7lEXvYiyCNx8YPfPmig9vgFqNDx3Y9Hh2T1ARbh68jmi7NdDduaEZ0rBWs/XxO2tS3BO8K/P3u5v8NfyL7ldOOCe2gz2TGg2oujfUSkQfYKXx/riaXLQyCOLpl6ZMvK8M8mDrUmehKd4sCvZnZPpJrIcWir1Be16jU5eaXmSUbUTIS0W9v6uCVYxAn1ngHt2L+AyYNJDEIncZFwCv27WasLrdISQTuBdCxKPQ+x+LboraDSAuDQbWXanfBQ3mRSKfLGm4/xugrxzP+b9FXz2eEsCvMreL7i6EZdqZcr7K1hgRo6noW+2g7dCoVCUM0q05oMwUhJR1ffee49Jkybx7LPPMmzYMGm+5OnpydatW+Xz06dPU7t2bSVYqzFXt6tDZNJd9P+rB9NNPzLFuBB2/gAJR6H3w7Juqlh41cSt0w0EtL6We+dv49GsDwjVx5C59Tt21BpN7dCmsha1rOxJcePenaFSdLgZXNzS3he2AymnS7dB3zqYr3yVAwsep6n+FLHf3UbgQ2vBWHnEgnAIDvT1JC45jS1HzhpPJeo68xg/0DBjF3xztbZQROtEtWS97tBq9IUb+/d57XURYQ1qnrt4V4yD+//NkILV3Wxg8VhLiWvb+9W3cJv9ZrY7G/Ou+X300bu1aKuIypdBuEZmmPjhVAArY705km4h2aaX+3k+4q3yC4zKSKcLTAbwN9mp525lcHAy0xqc0cT9iR2aA7LLAQaLJljrdaXMJByl2+H5/GdZJVPxSQKSTmiCXiD65orobg7iN9fzPgIMJilYheOzQlEwLvRp0dmzTpyVJLOhqiHHTZ43yR5PNY4KheLioERrHnIipjkXm6KtzdSpU3nwwQdlSvDKlSulc7Do2dqxY0cpYhWKaX3CiIyN58UNE9nnDOV/ps+xnFgPfz8Kg18oUcTJy2LgvRs68+Di17jq1Fv0N+ygW/SPfH1qMK+5bqCNn51hwUmMqR2Pt8lJik3Pr1H+rI71oat/KrfXj8l3uzFZBmaEh7Is5qwr5t899uMhIouCrBRtyjEYKgGevgE86vYMX2Y9TGD6IVj2gpY6XIl4ZUxr7vthOzbH2QuqVI8mWBuNx23PT5rgymuQdP1cMJ1nKHL0Py0iLQRkh5vPMXoa+7sQrC50Oh2LxrjjIUKEJUScd3zc9PyZ2QOTy8RrurcxnglneYwn75kmM7VhPMNqCuVWfDYneDB2Y+NzRGrOfO5IZIvVHHEqHt2NLmpZbHT0S2dYcCL9A5Mx5v1IwmzpwHaI3nVWOAqDsV4Plj3CKmqGt8+RQljakulgs7Mpncc+AqlRsP9vOLlJe1/h7lynM9TtorkU+4USlJ3Gr1AoFAqF4vKh2ovWQ4cOSdOlkJAQgoODzxkccQE6aNAg5s+fz+OPP07fvn358ccfWbRoEffffz/u7sWMoikue14Y2RR/dyMfrBnAEWttPjG/RXDCUdIXPonHyFfAUkA/0AJ4a2ggn+98mvAt33OPfj63GJfQ1bmfu+Pv45m4EJ7eE4JBDw7n2ejYP2e8+fxYED92PkiYpxaVXRvvxf/2h7Ar2e0csfJVxwgaeFrBZdIiVCJiJqKtpRCtggHNgpixZSqfm9/AtfZ9dK3GaGmclYRBzQPZ8+ygC19w9YHUF3MjBRKRgnp+lFSoucWPa/Mijdr3bN/RWxbbpHCV4zrcgzDf0kdFr2tu5tNtGfyS1ZlU/QN8YHqH/mzEkJHBI9vv5B59GH0DU3ipxUlquRUdeU+2G3K/d1+zk06+afQMSGFocBJ13bX1hc/R0TQzmRmpNPXOwmw0alFM+bkdmrlSlhWST2npuCLaKdrZ5CAMxURUWoxLWVOZI7fDv8/mCuFdvgN46kw/ttOUo+2Gn3UkTo2BrGTtBoNIoy5pD2aFQqFQKBRVimotWjds2MCbb75JfHy8TPkV7sC9e/fOTQ8W7WzEY/PmzVmwYAEfffQRERERDBgwQJkuKc7F7MlDw9tw18CWjP/cj7HHffjZ8hw1U4+x6ftneC/oae7s6MUVIcWvc7y9rQXa3gYnW2Nb/TYtrMf50/wEM22T+c3ZC2d2VEyIJZHqm2nXSTfXPmta0KNGGtuTPMh0aJIlR7gMCU5hVqvjBJizI4tHVmiCVYgNTxGjKh0TWxjouLETyx3tZHSYExsrlWgtEDGA3sWoGU49A6e3ZzsnX5+7ePFRO2tPZMnNXNXETZoClYUnuplo4Kvj7S1Wtru685TezPO2N+hj2MU/+uk8aZvEn2d6sCymBUt77qeRZ+FmQwOCUtDrRAofUuy+2+ZCsyyjI5PGh7/TxGhxEb8XkSLddDjUalNmw6XcGwNbvpKCNalmN452fpJZOz3ZHh2Fh1ueVF8RXc3rVC0EqxC5UrhWTgdrhUKhUCgUZaPaitY9e/Zw+PBhGTkVLW2mT5/O2LFj2b17d27EVURaBTkiVpgvKRSF4WY28Mdd3fhgZU2mLHPwretpuuj3c+OZt7jpj/vRG030rmvi+StM1PUuZlSqbhdMV78Hq1/HI2on75g/5GnPJWwytMe/Vn261BQp7fDlsUBe2Ke1a1gf75mrAzxNTsbXSeCJpqcw57yliJgJp+PEbBHT66EypXUK51zx2Y+7srMVkiO1aJiIfl0OQkK0whF41waPADlrdzq5Z2mm1GsirfudfuVzOr2huVFOGr0gMVS22PGLO8T75vcY4djAT46+XLO2BUt6RxQZcRUpviJNeOmZfKLoIiV810+QJtLKdZqzdd460Rz0JmkWJQWqmIQJV3l/r6JWNf6w7AN8oO+H2C3+RCbtlS8FeBfS+1H8xlSkVaFQKBSKy5pqKVpFBDUpKYmmTZvm1q4+//zzMlV4//7956QJ2+12Nm/ejM1mk1FYhaI43N23Pnf3nULE5jA8/ryeoYbNfMC7fGEfzrKjzfj3qJW+oWbe6GuSbTuKxKOGVh8rTJ52zCUg7SDDOAjJ4mI/CHzrMcm7NmN6NeX6nW04mOpGO990HmsSSRf/9Jwffh6xevxsxKzjrdCwX5m/2OY1DMTF+p6tebycol8x+7VHP1llKZkd7sDmcMphnTPCrcTGS8VGvOeI12Hnj7DjB0YYNspJtCvasb4pwWE10PuGgG9drdXMedzfMJqbtjQgzaaXrWty62LT42HXj5CZBO7i9/W8JkxFOrDDqv2NSBMWU3lEUotCuA+LDOGmE6VgTcm0cyI2TS6r619IKYb4fV0OvzHFpSPxBHv276NlnkV/7IrC283ExqOJ6ptQKBSKSki1FK0ighoWFiZ7q77zzjuMHj2awMBA/P39pUAV4lTUuQrTpZSUFOkiLGpaFYqS0qDzEHD/AubdyjDDJjntdDbgM/uVLDzejc7fGulc28Q7/c1FR15FFKz9jVC/D5xYByc2aRFAESWTkTLw0y3ib1Hn16QR+IZq7sWiXlOIrpMbz7oEC7HaZKhmXuN1bi13acl0uEgkWzyIekMhdrLrDBPSrczfFsXR+LO9Zz1MBh4YUB8PcxU4DQnDIYFvvdxFIuVWoNPraJ9PD9FyRYyl+O7rdZNmUKlHt+BljaEreyD7/oP8ToVw9auviU/REkanp3dgCj4mp3QNFs7Re/tvxxi7Bw4v1VLDRfRYGGeJWl75XgbQX+J6fVsmRO2Ws2caT8Bmd/LAvN24nHac6Hig/3mthxSK0pJ4Asf7XWhp185FTpeOBJc3z/+u/f4E4tCuH6BqpIuDXqdDl33DzuEblqcYRaFQKMqXKnC1eHEQxkuffvqpFKY5rsHCXEmkCgvOnDkjI7JCyH788ccyGqtQlIpW14DXQjLXfoLbob9pSwTvmd/nNudi7rA+yJbTfvT83sZzvdy5tVUxDkm/etrUZgJkJkPUDog5oNVcJkRA1E5tEog6VRE1E9E0gc4ATYdC63HlJlZziEx1EqjLfh+vmmyNNzPjlx1ExKZis9ryDdYtCo9i1cO9qNSIUOrh5dq8uCGQTZtA7ULN5XTJVGHjxYq05iWgMfS4B6/uLu75NYIacVtorz/MCM8DuGWe0SLoYjq6Sms/I34nnsH81uAwdx7oRC/dbtLX/YmPMzuaVKMRDHq20NTwPXEOHl9jIzrNRarNSYbNhadZz/0dTUxqXU5tZSK3gNNGplcoZ8xhPDY/nPTMTDn0T1/Vmm4Nyt7zVaGQpMdhsGdwv/UuGrTsSuP69bjLQyuryEEI1i5hqjtAcRC9beff3Q8+BcO13+CIUgaVCoXi4lBtRatA9FrNi4eHB9HRWt82EXF96aWX2LhxoxKsirITdgXH9I2h+VQCjywgYN9cOtoOssTzaa7LeES2ynlmdTqLIsx8P8Jc/FRT0bKmfm9tElf4Z/ZAxCqI2gVJx3MjsFh8tH6fzUeCW3YKbzmTkuWkgTFKzs8/7s6D/60h51MIwSoiZmaTdsoRu+qw2zgek8S7yyO4r38DKpqYlKzc/p7ntEwR0WxhUiRSb0U9ZzbtgnS5LWL2x7toFXgJd1an4/VR9WnzdTDf2JxMT9GxbmQSQYnb4fQOOL0TbGkQd0hOYnQXu83T1hVGyW5+0PJq7fdQSC/hpEwnIxdkyLr+c5ZnOHn+PzuvbLTyal8LVzcq47+SY2vlw3bvPkz9fruWogzceEVDbu95NiW7TN+jQpGHQ6469GrZjZEdzxWsCoVCoaicVGvRej6iflVEVhMSEnjggQdkJFb0ZFUoyoMafr7EmdrhbNwZ+k6DuddKc52F7s9yj+sRFqa3ZP0pK0MXuFg8xlLyGkmhnkQkMCcaKNqSRIdrAiC0mzS4uVgIcSMijvV1mmhddMpNCla90UjvJsH0buxPi2DPcz7TffN2E5OYykcrD1cK0SqETpbdKR/PETsH/9EehWDNM4ayF2t29Dgy7RKLVqE7jXrmjHBnwu/p2B0uuvzuywu9hnFT/5Hady4EqxDcwmwr8RiZcSc4Yffnc/twnpowDC/3on8PX+91SMEq0iW7hJgJ9tBR00PHkmMOTiTayLI5eHx1VtlEq8OK6+QmOZSvHm0s2+y40DG1bxOeGN6k/L5HhUKhUCgUVZZLkM9WdWjfvr00Y2rRooUUrCNHjqzoXVJcRogL6Oa1vLQL6cDGcPtSaNAHvSOTDzw+p3+oduF/MM7G9QuzjXDKgkj5rN8LGva9qIJVsDHaKTWzvy5VPk/BQ9Z8fn1LR+7sFUqrWt4XiPDrOmm9TtMzs2Sf04pGROYsRr18zMVhhy1fa/N1u1y4UnZdq7uxYuq4utU2MKuvuxR5Iuz75Kp0BszLYPZeF1b/JjKaujr0bvqmvEiztM8ZbH2NNV5DiyVYBXW9zn6un6408+FAC8/0MLPmOneubaltw5bdPalUiFD1+g/R2dI57arBNldjfDzdWfZw31IJ1gK/R4XiPCxYGfTvSA4804oWT/xGXGo5nHOrIWLcxn6wQs47vr+OGnFbCSG2ondLoVBchijRmgdRz/rYY4/x+eefK8GquPgIUXn9jzJdV5caxVetd9EvTIsMbThlZcbqqnMRtT1GU2+7XZphTkfdARn5LazOs0uor8xUFbLon73ZacyXGlHre3gZHFpKUPRqmqeuJyjzmCamBDu+19qwiPTqRgPOWTXVqgl1QZ084u5SI9rjrL7ek0BPo9yfI/E2nl2TTpMv0mjxVRoT/0zjWKJWU2wxGfjlquJHHweHiX7V2ne0MzZ7TLLxtWifWdT+l5rdP8uxd7h0zLTdTrcmIWx/oh+NgjzL5+aQQlEI/mmHaao7KW9OOcvyO67GiHFLcGimVYbU0wz870aWWh7FPT2yondNoVBcZijRmgfhICxa3qgIq+KSIdx1O9ykzR9ZwexhFhrX0CJEP4Rn8uH2wntwVhYOxGuR0q361vKxu35vkenNJqMes0n7rIv2nOGSIy5Sv5sA346GOWPPTh90gbfbwO/3wvL/aX8rTK9M57qJRiS5cjdTr4J92kJ99Gye6MG0ju5SvIo90+Eiw+rI7SM7o7s7e291J9iz+Kd9b7M+93t8acO5v0WrI/vzl2aHHTbY+i1s1aLYz9pvIa7uIH6Y3OnitQ5SKBQXhdNovasFm9q9iIcuC4s1QY22QqEoV1RN63kEBQWV7wgrFEXR4ipY9z6c2iov5heOttDlexdJGXZeWZ9BkhVmdq3cqY7Z+oXVthZggs76A3jqipYzfh4WYpNsHIvL7iV7KTn0L5xYD3rT2f6roj1Q0knNeGnrN2f/tsmgC1ZfE5md0lxERPlSMqOLSU4iCvxVuIN1kU6ubW4oU81pqK+BY4lONkVaafO1g3cHuLE20snsXZkyAutlLuFnTz0Dy56HhKPy6af2K/nbazQb78wn/VqhKA8ST0jXYEnsATWmF5Fkr/pqfBUKxUVBiVaFoqKp2xm8akFqFESsxNx4EKsmuHHFDxmkZTn4ZFsGfx62M2+UhRCvyiGOzufxrkb+jchin6M2SUYPfHXpTAhNKXK9LLtWEOnrYeaSk3PxKmpV++fpw2wXPUN3wb/PnV02fzI07A9Nh2k9UIGFR7R9D/K8yD1aS4EQkvd2EFPZt/XjSAs3LITDcTZSMh3c+leajN7qsqPlXw4rfhquM/YQGYufw9OeQIzLh6dsk1jn0Y//HuylIqyKiydYP+gKtrM3xuwGdxJdXmrEFQqFogpROa+AFYrLHNGWY19UqnxEbzibIhy+QOab+rrpWXudO42yU4VPJdvo8V1apU0XbuxvoHGACRd6djs1J+Draxddp5pl06KVFWKa45lt9ytaw+RFmFaJaKuct4BvPbCmwb4/4Y/74Oga+dK+OLt8vCLk8r73V8tTz7Lx7nw+3EOmGefU8Yrf5rabPOgYXLRoPxRv5effFpD55wwpWPc56zEy8yXCAwazbnpvvNwu7zFUVCAiwioE65jPYOpKOS3q/+c5Ka0KhUKhqPwo0apQVAB523JIukwCozskHodTm+UiIVz/He/OzB7uMgVV1CiKdOGHV1ZOg6bX+pplfeculyZafRL3FLmOzaFFK2t6X1x340JFqzBjykt8RG6tJcNehvt3wMQF0Hiwlj7831tEnzyc63h8c8vKF2m9GAwOM7L7Vk8e7+EuJ/HbjEpzMXBeBv/bYLugl6tg5QkH4749ROKvjzEu8UtZ67bS0YaHfF7njakjWf1wLzzMSrAqLgGBTSGkvZwyPFRvVoVCoahqqKsFhaICEJFFIVhzI4w+IdBlslbbumU21GwNJnf50h1tTYxuZGDkr5mcSbXz874sHu5krHSpwiLidmUTC6dONwYH+ESv10SeruD9zHGedS9pXWR54Jldvy5qK1e+ou2n0wYnt4DTrqUCd7pN63/beCA06AvfjYMjy/Fb+RS9DHezxtmWzrWqh2jNYWrbs1HxZ9bZORxvk9PX4QaevcLC2MZ63tuSyf592+ll38R3hhVYDDZSXO5853cHfa59iIUhvhX6GRQK0SYqxS2EpAwrLp0BfU4KgaJEiHET43fSFUhtX/E/S42jQqG4OCjRqlBUAKIdxwUtOa64D7bNgcRjsOo16H5XbjRQOL6umOBGy6/S0LlcTFli5a/RFRCdLALRx5OsbjDfHY+kQ7T/bSCxDa4itv5VZPo2yveCR8Tn0rPK0uyzlAQ11+pThWg9uvrc1+p2have1wRrDgYjjPsSvr0Gy+kdfGt6me+dA+FYFwhqAR41qG4cTz4bXTXbUli3ehXeazczVb8Tb11G7n+YqKBe1LrxY+70q1dxO6tQ5CETC4uG/Mv4jiHsUyNTagK8zOybdQ0gJnAuW6JGU6FQXBSUaFUoKgveNWHCN1rblZMb4eeN4BcGdTqBb108spL5vlYCp2ISSIzz4tiWhoTVCwMhBMyVyFTE4g3d7oT1H+Kecox6O9+TU0pgB452epzU4E65f6rX63A6IM2q1YdeUgwmuOkXOLAYMpPPRoVDu0ODPucK1hyEMJ30D3u+nEbL0wuYaFgKK5Zqr3nVhNAroOlQ+X1d9tjSqZexlwGGI1ztvoM29l2YRIg9mzhdDTIaDKZuj/HUajwo//FUKBQKhUKhKAZKtCoUlYngljDyTdjwCUSHa1FXMWVzRd6jdnf2lLOeMHOq1YZKQaOBmoA7sUE6Iot2Pt6x22izeDxnGo0losuzOE2eGPR6hFzNyDZkuuTUaAjdp2lGS9Z0rW+u2bPwdUxu/N3oSV491oiBhu2MDjyJV+J+SI2GPb9ok0jv7nI7BDTmskCkcYs2QKd3wJk9EH8Ykk/zvd6lOSNk33NI9W7ELt++tOp/HQENuoi7EhW95wqFojK1HPII0G60KhQKRQlRolWhqEwI0dR0OLQeC/YsOLxM6yeaFqP9s/cMZFeCkQ2799NUd5LmxkiCXXGakFjyFPR+BOr3olIganIb9tOmjASt7+mhJQQfno9Hwn72DfgCu0MTq56WCj4VCaFalFgVZIvb4U29eWdJB1Y4O/CXVy0eGhKAT9Q6gg/9hP+pFeiid7Psj2+YbJ3O4AYm3u1vws1YBQWciD6LSPSOuZARf8HLp1012OMMo3GnQYT1nIBXUFN6VMiOKhQlw4KV/ivGsfO3TK53PMeax4fiXxGtt6o4CelWev1vMXMNz9Cytjf6Ro/K5TERu1myDCzWBHpuvg+DPUNbweQBd4ssIiVcFQpFyVCiVaGoTOQVT+KxzThtyoOIpb4yexsv7osEG9TUJ/FN7fk0i1sqDYVsGcls9x/KwUQXEUkuIlOd1PHS07+enm61dBXTD9PdH3rerxkaLf8fXvG7af33GBo4H+IQtanjW/nqc/NFRGOddlrWMNKrWW3WHjjNugNRjD94BpMpALPxHvpZW/Oh+V1quBJxuZz8cySLFkdt3NPBwsOd82/tY3c6ZcCyQr6bgog/Aus/gJj98qnTYCE5qDPJtbqTGtCW025NmDz/qHxt44BB4FP8fq0KRUWjx0lgcjiBOnFIW7E7NFM4RckQ4ybGr63xMERBcI9apLss3HDiWTih/Y14fmLoNzTzyoIFU7SoqxKtCoWihCjRqlBUQebc2oGX/vbik5UHiXb6Muzkrbxo0XGjfgmmjR+S6FjP9/Yx7HY1zF3n0+0gLsvcTQb61DNelOjfmTQnG6OdtA/SU9c7n22LtNkRr8O/z+KWfIr5pqeYZnuAsIAuVJlIeHYa8ecT29J5VgLpGZlC0mG3iclGtM5f/mlNYzr9altYfswKTifvbcng3S2ZmAw63Iw6LEYdqVaXbH3kcrrQ6XVMbGXhxZ7Fj/YsPGLn54MOannqaOSro0WAns7BOsxl+V4dVtj6Lez9TYu0mtyJaPcI0U1vwGU4K0wPR6bkZg4HelVAn12F4jw2HUvkaFy6nK8f4EGXMD81RpeYNi1asGPCcs5ER8rn4ZGp/LQ7mQfdutAs8Iz6PhQKRalRolWhqKI8MbwJo9vX4trPN5GSlsET1luJNXpxj+FXBhu2ymmesx8v6qaSYtPjcDilF06mzcE/Rxz0jHLw3/Vu5SZco9KcXPF9em6/TiGQjQY9A8NMfDjQhDEniija+wx/neTFL+KbuIevTa9wOqsDMISqFAn3ECXFT/VnV2Qq204ksScqlZMJGUwIyIRtUNuYwuxhFo4nm5j8TxYHYm3odC4ZmUh1QGrW2c1KjyKXizm7M7mtpZFG/voixeqT/1mJS7Nf4G8kWnmMaGTmtT4mvApoJSR6zP4R4aRFDR0tA/K07Ek4Bqtfh4QI+TQ2bATHOj+J1aPWBdtYsD1Km9HrK1eEWFFtBeu4j/7Lbbgizj8/T+tJF3U/5ZLTrlUrEJMoZ90aSeTubZd+JxQKxWWHEq0KRRVG1BDteKIfby8/yumkTHxrv8ABnwdotu9D9LvnMV6/gvHBZ8A7BLvLRWQabE324e/EMHalN+SK72uy9gb3MgtXIVSHzc+UjyLyJoSUuHgUQlmmxx638U5/N0Y0zD7luPkwNPlx3nT8jx6GPYSeWgh1QsEzALyy+6dWAYRYa1fXR06SvX/Agnu0efcA+RDqo2fJOHcOJ1jYEO3kaJKLU6lOkrKgjreOZv46hA/VrHUZcuxqF2IELVK9r/o1k5hUTayKyWLSRGduxFbn4u/DWSw/ksLNoXF0aBxGA38TDX11LDvp5J2tdvbE2NDJy3rtMzT20zHD5x8GnPkGnehVa/Fh7xVvkFh3YL778c3GU+w9GSfff0CTGlqtb3FqghWKi4SIsIpzzviuDeTzeRsj5LIuF95vUSgUCkUVRIlWhaKKI0THQwMb5jEKcoMmb0Hr0fDjRM2k6cweebCHZk/XZGd5xjp9+PTbYQwadT0tA88NSQgBWtwI2vULrSRm2KXoeqmPB0Pr69lyxsncfQ5WHMvCZncy7Z90gryMWAw6KaCj0/UcMobQgz1gt4EjE9LiKq9oLcxh2GGDf5+Hte+edXPu+9g5fyKipwVFUGdttMlHg0GPhyn/v0nIdNL/pwyybA4pFv3djTzb08zVjc6expMyndy/wsbyY1l8Znyd3tG7SYuysMnZnAXOlhxw1cPN5UljnQdZGOmoO0RPfTg903ZTNz1WbmOFqwMfuT9K46SG9PC3EuB5brry8oNx/LX9BHod1Avw5IsxdbPHRYlWRcXTtb6WEjxvI2w8mohfYgyDgSX7YkiM0lJWxXKFQqFQVC2UaFUoLieyjYLkY7PhMHUlHP5Xq00UiMeEoxC5DUfUHgJ1ydyn+4llvx8gvOsj9G7gw7V/ZnEsyS6jdm5mA9c0MfFCD2OBdZJvbbGx/qRVCqkRjS1MbKmdVobV1zOsvpGtZ4zc+ncWyZl2YtPO7cfqbXJpeXwWLzC4aZHWyj62qbFgziNeYw/B/ElaOxhBy2ug062gL/7pdVu01t+0hnvBNwn6/5QpBasYrud6eXBrqwu37+umlynJyYe347NG64fkqcuin2GHnApDmKX8z34DcxyDpKHKhqgjzPlPS/+1mIzS6dnucKDHJQWru5uFxdM6oidLGwuFopIg6llrE8ueTRFYdacYbIa3l+wn3GXN/ZsqYv2mUCgUimyUaFUoLifyGAVJarWGGg3yjRAaEk6wa/lcmux4lQGG7aza9CrDtz5JQoYmLIUIFSLpxz0O5u3TM7KRmfs7nK23PJDgYOZqG5tPa4K1jo+JjwZd6CDbMdjA9pvceGurg/WnNXEm8DQ4GOE4BaKTihCrNZtTJcZWZz17Y0CM5zdXQ/JJ7W/aT4R215V40xFJ2k2Fhr75i9ZdMQ4ZyRY83sM9X8GaF5+IhdpM97uh/Q3Y9i8h4+BK3DLPYLanQmaiFjkWEeGGfaFBP9zqdWPgcSunN55k89F4EtMy0eGUNzqsVu1iP2fvLBYzi+/viYeXe4k/q0Jxsenim8Iarxm5bVbsBnemXdmdDI+Q3L9p6APO+QGyZYuoA1eUHjF+cS5v2TKooNtueaPeCoVCURqUaFUoLify6zeaN/qa9zXPGrQZchsxzbph+Gk0ffQ7Cck8RLyrPte1cpMtcj7daWfLaatMFf79YCa/HQB3swFvs44zOXWVQsSYDCwaW3DLE5Fm/HBncTljOhvxXf0GROwD4Ujb4iqqzNjmTRMWCNG3/TttfvscOLEeGvaH0B5aqx9D0U4wIvVX0Cow/0s+D+PZi+pbWuYxTioIS3aNbVaSvHFh8qqJqcN1WvS3gPRr8c79m4rpbLR7X1QqC8PPsD86lTp+brJ2t1uYH7WqSosiRfUkPU4TrGM+g8CmGD0CGJlfi5UZRxC/9n0VsY+XCUHeFva9PAYQU/5Rb1d2jfEeXQSDLbBw5RpMNWPk68E1QzTjJoVCoSgCJVoViuoWfT1PhAW16suuwEG0iVvMZONC5tV8kFd6a3WMIr33eLKZh1da2RJll+JVuA9n2rRIrHAHvqaJmWd7GAt0qr0AUfi64ROIWAk6A1w7B4IreZS1sBsD13wIHW8ma8UbWCKWQtwhbdr0mfa60QImT6jbBbrdeYGIFWNqE87OIkJUM/8xrON9dv5UiqiPLWIfm42AI8th508w+IWCfwNF0LyWl5xKXOOrUFQGAptCSPuK3otqjWg7JFychSlW4mk/0jdaGLH/Cdh/tixBtMhRwlWhUBSFEq0KRXWMvp5HmzGPwWeLucqwjqv6TBL3v3NfE+6380ZpkbW1kQ4+3mGX7rc3tTRxc4vsdieZSXB8L9RoCF5n170AYVi0/gM4tFQkIMOYT6HpkMophkqyH6Hdsdw8D9JiYfcC2PkjnNqsvWbP0qaDi8GaAn1mgP5stPRAgpacKLR8z5D8RatwdxbRCvF3J1NdRYvWoObadxF/BLbMht4Plf9YFhTBVygUivOEq9YzN4Qd9c/2cI2J2M0NJ57Vnqtoq0KhKAIlWhWK6ki2IIuxGoizmgnwaUVQ6BUYj6+F5c/DwGfBM/CC1a4IMchJYsuEo+vgyApp7JRr9hTUAhr0gfq9tPTYHISgW/kyxOwDnR5GvQttxlVeMVSa/RBj1m2qNjkdkJWsCfpTW2HBFDi2Fla9Cn0ezTVqyjpb5ovwqfItYNMGvV5GZT/eaadvvSJShEUYvPkoWPsOhP+iidbyppTRW4WiUmDLwPbNGLYeT2QKT7ByxhBZk6koGaImuO8r//AZL9Ex1A/TzQvA5F6sHq5LlgEn1IgrFIrioUSrQlEdyRZkiUlpZJlqEJdmI+jKN+DbazR34b8f1YSrf9jZdZIjIToc4g5C7EFIiNBEXQ7+DbR1Y/Zq08ZPwCNQ24ZvXTiyUjMAEgJw3OyzEdbzI5qVRQyVdT9ENFWIdjH51weTB/x4Ixz7D1Y6oc90mSrcLtggRabom/r5bjtPd8//wnlUYzO/Hchk7UkrCZkm/N2KSMcWYy4QwrmCIvgKxaXCPT2SVroI/BLNYEwoegWXE9OJtXTTiftvWdgdWt9iRckQ42bLyqKb2x5NgObcvFQoFIpyRolWhaI6ki3I/HwtOKx6AjxN4N0SJi/B/u1YjPEHYdF06DoVEk/AiQ2QlM8tcb9QaHc9tBkPgU2Yv2oLiRt/onfmcpra94Po/SmmU1u0v6/ZGq79VktdLSiiWVnEUHnvR7NhcP0PMPd6OL5Oi4L2elgK1gZ+RiISbPxz1MHT3fNZNy2WV0O20TdiCw11kZz+xRP/Wt7a/vnUgbqdwS9Mi7DmIGppBWJcs4lJyZI3KMT3LQxUFIoqizgvpcdp8+mxDFs+kZGWDFiV/bq4SeRRiVtoKXLxST0Ckdu1J+I7y880S6FQVHuUaFUoqiM5Jkwimzfvcv8wjlz1C3X+vg3P6E2w5q2zrwnTpNDuUKcjBLfSTE5862lCyewh08QeXBiFnj5AH3xIo7HuFK3NkTzfMUP72yvuuVAIFhTRrCy1reVJk8Fwww/w3XgtrVoIzrbXMbyBkQ8TbJxIsrPwiJ0RDbNPzTH7Yd37MqotJOaYnKxg0YHmeJ7tbp0NXjWh5dUQ2Ewze0rKbsNjS8v9MyFYs+xOLbKuRKuiKgvWD7qC7ewNGQzu3GydwU2DujC4eZASP1WALLO/NGLqtnU6bM1zs+HujUq4KhSKC1CiVaGobhQhBv0Dgjk5ai5ha6bjdmw5afX68Pap5sTW7s9bE3uc+8epMblR0pQsD3SiVjU7PSwZT7a6mnLM3I7nh3fLfu/si8y871tQRLMy1LZeDOHceBAM/R8sekxrlZMcyR0d7+ajbdrYTVuSzt0d3ZloXknwjg8wumw4XDp2uRqyxtmaXc6GuBscvDkqFL1Itz6xURPAqdGw8dML38+rVu6siLDmRFoViiqLiLAKwZrd0kaw6IidVX9GM8qvFYSc7ceqqLyIvrmDsl7juSEh2o2G2ANa7b/4flW0VaFQnIcSrQpFdaMgMZgt0IIsHgTVDYLrvuLPXdHcM3ebZioUF0/QooM8PqxJvlHS9FQXs2/twsI9MQR5mTHowNvNyKTu9cCoP0fgFksAVoba1lIKZ5GG+8qSw6w7EkevxoHc1r3eua1juk/TjJj+ni5b0/gmnWBj50Hcsr0J+23B+Oz8ghDjn/JPlzg6Md02hXiXD+5uFvq3qsnjVzZF75MnvVfs3465sPVryEjQTLLsmVq0achL2ncrIuveFhVhVVw2hNtqsydKcyvfeCaxondHUQoiCeSfxDokRvnhlxjDYDWKCoWiAJRoVSiqGwWm454r0J78Yz/frDmEXqe1YxFZwJ+sPMSkHvWo5au1wMkVctZ0AswG8HVj+qCG+QujkorQylDbWkrh/OxfB/hz23E5Zj/GJvPj+iMYjEZGtKnDe9e21v6o6xRZB8wPN8q+rkFxh1hogHSDBQ+y5J+8Zx/NbPebadekBg8MaED7ugV4C4v96zJZm/JSnBsFeaPJ8vlllpKtuGyZ/vMOwl1njcaElVL9AOVmXVUQ35X4zuZtjGDeRqSR1mALhJ9OoZUKlisUivNQolWhqG4UJAbzCLTwyBS+zRasJrOZGUOa8MJfe9G5nNw/bzc/3t75ArEbZIagGl4lf9/KTCn2WdT2/rH9uBw7o8mMw+HA5XTgsNv5Y9sxavlYeGJ4drS6YT+4a70WJT26Wqb6etgzcerNJA97l3u7Xs+9F1t0571ZIajolGyFIg+bjiVyNC79HKHTJU92+/iuDeha3+/sa7IfaPFwGT3IsDmkcFKUHjF+ojbV3WSQvaSLi/iufp7WM/f7PbXHCocgMikTrSmOQqFQnEWJVoVCcYFAsxjTco1o35vQBl93E+1DA9hxLIbwyKTySeOtgkZLUUmZfPLfce7oGXo22nweh2LSEc1oRHT6y4ntMRn1HI3L4NWlh0hITuPTlQe5qXtdQv2zexmK2q2+07XJniV73uq9gvHL67B8MUX3+d9fRadkKxR5BOu4j/47RwgJgfRSD5iY/VwI1vEdSxGWM3uie/I04pe+T414qRFZNfteHguIqeQI4Zpzo2FJopcUree4CedFOQsrFNUaJVoVCsUFNAx0z00JPpmYKUWruLAQojUlPQu73YlR1KkWJIyKI0grg9FSCVh+II5JszfJqOlXa47w5oT2jGl/1uQoBxElELh0OilYBfUD3Hnl6hZMmbNVRquv/WwT66YLl+XzEONRo9GlFY3nf39V4LtQVA9EBE6XJ5qaeDqCX9dsY9OGU0zMbmes0oEvczfhvChnYYWiWlNEd3qFQlGV2XEymQ4vLeeeH3eVaD29Xo9Or50eIuIz5GPPhn6akMXF8oPZ/RGLm3Iql6VpNZbiUSCEmTAjqgJRvdnrTnDLlxukYJU4HTw4dwszft17wd/GpIh+NELwn5soJ0ypbu7RQI7h6fgU3lkWUbxxKy7nj69CcZkgo6kNHUzZPo6/LE/wjvlD7AZ3/jexf4nSgRWVm5r1GjMw6zWuzHopdwof9SdMXak5RQvHaNHjWkRhRdsjhUJRrVCiVaG4jHns1z0kpKRLU6BMa7bgKiZmk5aIEZWsmQK5mQzSTEiwaM+ZIlbOR5CeL8hERM8rqEpE9l5ZvB89LvQGI/cNbobFYpFR6B/WXyg849NtucL/fEa0CiLIT6v7nb3u6IVvVBYhXxbBq1BUpTY3U1divHcT7VqVofLRlontm7GsenYAHZ9bRFL2casoGWLcxPiJcRTjKZ3LS4m4AfHutKu5dfwYWnYZQLirAXt0jSCkPYT20CKtoiXOp321Pr1KuCoU1QqVHqxQXMYkZZy9EBOOjKE13Ivd8kSfHSkUkcEcDHq97H6TmuUoPBU4v5Thkta+VqKaV7tD6z07tHVtetT3x8/NxPN/7D53cLJxZS8ryJCkcZAXsUmp2B2uktegFjYmlaFFkEJxsRF9WYWIKSsuB6YjSxFJ+hkZaVizj3FFyRDjJsavj9sWOKKNa1nIW+MqHIVzEbX/d2/Ubl6ofq4KRbVEiVbFZcuRI0do2LAhiYla/z4/v+qdRpZldxKXZiuXPp0i6lri2tSSOvFWsZrXS0JhY1IV3ZkVikJwT4+UbVD8Es1gTFBjVQ3ZePRs/936Ad50CatXofujUCgqDiVaFZctd9xxB/Hx8QwaNIiZM2dS3bEY9QR45ukVUUyOxKZhszuJTbNhc2h30T3M+osf4auEkcPDMWnYnU7WRpy9kCoIh9NJSqZd1rLm4HQ6iUrJvKzGRKEoEyLFU0TPzic9lmHLJzLSkgGrspeJ9FDhIKuodj1cBeL5/YNb0EYXw2CxQERcc1DOwgrFZY8SrZcJW7dqVnsdO3aUEUYRXRTzBf3t0qVL5fymTZv47LPP8o1CzpgxQ4q9nNcKW0+8p3itRo0acn7cuHEyylmen2/KlCls2bLlnOXivX7++Wf5XmJ+6tSpufskRKtYLqbqGmWt5+9OZFyy/Gffpo4P5hzH32Lg5WYkMyuLo9GJ3DR7My6XM7cIPtTf4+JH+CpR5NDDYiLJZuNAZDw3frExdxxyzKryEhagjY1wCb792y14e7jJ9jghvm6sOxyL3aalbHu7m6r0mCgUpe212tSSQDt/mxSm/HiTVquaD06dGzdbZ3DToC4Mbh6khEk14vwericSMnlnyV7eXbKXEGLpabHgIepbsxHGXIv6/0mGR0ipevYqFIrKjxKtlwmffPIJn376qZwXkcV58+YV+LdCXE6fPl3Ov/rqqwwcOPACMShEongtb4SysPWEcMx5LUcwin0qD3JEaY4wz8v48eNz90GIViFscz67eC7GQoyLEPBivrrx9c0deHHxIQY2CyyRYBX8Pq07d/2wi21HY6QAEzWawohocq+GTOsTRnXi92nd5FjsOhErBavTBY1q+fHqmAuNYK7rFMKB6FS+WH0YvctJWnoGh8V0WntdlLy2Cg1g9k0dLv0HUSgukTDNEQ1i+X0f/UYNXYpcHqBL5mPT26DLyo2e7h/yDcczPYhOsTI3j7lZgsubUwRyb6MuEKIESHUjb32roHfjGvI3JgTswCWv5f6mGutOSUfpJQvnc8hVJ/d3I6Ky9fzdlIBVKC4TdK4c1xBFpSE5ORlfX1+SkpLw8fHJXS6EYl5hmBchzCZMmCDnC4sqCuEnxGZCQkKusGvUqBGHDx8+JzIqhKKItApBKLZX1HqdOnU6R/iWp2jNQbQQyftzFfuQV7QK/P39c/exsL9TFJ+opExm/XOIYC8LMwY3OtuftZIdH6X9u5JwLC6dBTuiGNOuVm5EtSDiUq3MXn+CzccTOXwmlfi0LIJ93Hl3Qhs6qwiAooIpz+PofGGaw/XdG5CRGM2NRx7DI0ekisxfl4XvGr5M/Xr1OJrhwYurE3ONy3JSQIXYuKgRM2Fq9j8tKtci80tWPTGyXOr9qxsxKVn0eelP9rpN0hY8HnlJskHy3iQRtc/Dlo/E6NDas9n0bkzKvJ94V57rp3HtaFXb+8JofeIJwg8flf21RZ/YnEhtDkX9/i7G/xmFQpE/KtJaCckRZuJkmJfIyMgLluWQkZGR22KjoL8RNG7cmHfeeSf3b06ePCkfjUZj7rJff/2Va665hkcffVQuE9staj1xsm7fvj1ff/01R48epWfPnvnux9NPP81DDz10jrDevn0727Zt47bbbitybPJu848//pDvm3eZ2O6qVaukcBX7IbYp9tHhcBQ6LoqC8dDBC0ND5Xx6emqFD1XO91jU/baCjqOy4G+CyZ0DRTJakdsVyb9TugbJ6XzUb1FxOR1HEfu28wsP44HWoziX9dnv5TKzd+DHNAmtx96oVO759SjR271hu6gNT5RCdVr/ptTxc5MO551C/S7+8SJEa5b22RxZ6aQkJ2NxKdFaUlJSsuT4Jeuyf0fiuzKXzUG4ODTz19PMX2sfBk1JD10GGfFaffSCqXzgevncFX4G8Suy693Y0PFVssx+WKyJdN3yKPVcWQgZm+4yc1XWi0Rxtm5afKpvJne74DdZ0uNIoVCUHRVprYQIQVivnnLIUygK48SJE9StW1cdRwpFGVDHkUJx8Y8jhUJRdpRorYQIh1ERVfX29pYpsXmjlM8//3y+6wjjpZzopYhc3nLLLezYsaPQ9xHr9O3bl5UrV+au+9VXX+VGPNu1a5f7mribKIS0ODGL/Tt/PRGdFSkyIrr5wAMPcOutt8rIbEHve99998mIq3i/gv7ufHJScHJ4++23Wb58Ob/99lvuMrHPzz33nIwUXyzyjkV1TweqiLEQd7RTUlIICQnJzS4oyXFU3VG/XzWGAnUcqWNGnX8u3XGkUCjKjkoProSIE5+Xlxf/+9//zlm+evVqXnrppdznAQEBuTWuhw4dIjRUS+Fs27atFI+xsbGFOviK9N9///03dz1htCTEbo74EPsh5vOKETF//nqiZjQ8PJxXXnlFPh81apSscX3qqafyfX+xjXvuuYerr776gvrTosi7L7Vq1cpNTc4riMU/j0shoM4fm+rMpR4LcQOjKMTvV935Lhj1+y07VX0M1XFUvb7vysTlNJbFOY4UCkXZUaK1kiIimDkiMAdhjHT+MsH5Jkk5iPYzBSFMncT2hKgUQi+Hn376KXdeiNFZs2Zx7bXXyprWnOjm+euJ9+/SpUvueuI14Tqcd7t5EcuFSZMQvmUxbBJuwPmt27lz51JtT6FQKBQKhUKhUFQ+VC7DZYAQiXnFrIiYij6pefurCgGa1xlYtIDJEZ5CqIq/FSJQ9DnNmQRCVObt9yrSb89fT7wu+rbmJS4uLt8+sWK9nLY04nWxfTEVl7xC+PworviMQrBW156sCoVCoVAoFArF5YiKtF4GCJEmxJqInop50YYmb59WES0VkVCRSpzT/uX89XNEao4wzOn5KsSwEJXu7u7yed5a0Zz1hHgcPHhw7vsLChKiYl8+++yz3Oc5wlW8X959yIsQ4UuWLDnnswhRLhCfU0R+xTIhnAvrT1teWCwWnnnmGflY3VFjUfVQ35kaQ4U6ZtT5R6FQVDWUEVMVoqD0YIVCoVAoFAqFQqG4XFGitQqR1yFYoVAoFAqFQqFQKKoDSrQqFAqFQqFQKBQKhaLSompaKyGqv6RCUTCqv6RCUXbUcaRQqONIoahK/4+UaK2EREZGUq9evYreDYWiUnPixIlC+7Cq40ihUMeRQnEpUP+PFIqLfxwp0VoJ8fb2zv3yLpfm2wpFeZGcnCxv6uQcJwWhjqPKy6pD8by19BAmg57HhjamY6iq1b/UqONIoSiafVEpfPHfCawOZ+6yxkEe3N23vowIqeMoG6cDjm/A5nDxzekQXDoDN3eri9moOmvmh9Xu5JsNJ9G5HNxcOxKTQQeh3UBvqJaHZXIxr+uUaK2E6HQ6+SgEqxKtCkXhx4k6jqoOyw/E8cBPO0lMSSfn67vl213U9Pfi04ntaV/Xt6J3sdqhjiOFIv8yrRu+2sbag1GcL7uWH0pg6ZE0lj/YUx1HefEbJh8e7KB+UcXhoeE5N2vbqQEr5v8jdQtEoVAoFJeEe3/YQVKqJlhFv1ijySTnzySmcvfcnepbUCgUlYLvNkWyPluw6vQGPNzc5ORmseByQUR0IgvDz1T0bioU1QoVab0MiEnJIi7NRoCniSBvS0XvjkKhUOSLzeGQj10aBfPQgIZy/ok/9nMkKoEsu/aaQqFQVDSJGTb56NLp+fa2ThjzmMNc9/lGcDk5nZQJ9dwqcC8rEQ4bbJmN1e7gnsNdcOiMvDehFR5mJTPyI91q596fwjG47LzfaBNmowE63QoG0yX/6qoS6td0GSAEa5bdKR+VaFUoFJUdb7ez/5g9zdWzhkehUFSNdMW8glVRAA4rLHwEM7A680sycCPt6uZKtBZAWpaDf3efxJ1MzIdnaAvb36BEaxGoI/EyQERYLUa9fFQoFIrKTlRyZu58XKq1QvdFoVAoCmvFkWlTWSAKRWVARVovA0R0VUVYFQpFZSe0hicHT1vZcyKO6b/YSbPaiU9Ok681q6Wc0hUKReWgd+MavO4CHU7unLuTdnU105yY1Cx0Lqesa21XR52zFIpLiYq0KhQKheKS8MsdXWlQU7v4OxGbJAWruPjr0CCYr25qr74FhUJRKRBO5ncPai7PT1lZWWw8HC0nYcAkaFE3gM5hqlWXQnEpUZFWhUKhUFwSvNyMsk3E47/tZc66I6JijAeHNufBbFMmhUKhqCxMH9yImt4W3ll2CFuePq3+Hma+u61jhe6bouTsCA/nTHSknA+uGUK7Vq3UMFYxlGhVKBQKxSXlf1e34K4+9XE3GQjwEtYdCoVCUfm4pXtdOSmqvmBt8lN/2umy5PN0l4UdE5Yr4VrFUOnBCoVCobjk1PV3V4JVoVAoFBcdEWH10GXxfb1n5STmc6KuiqqDirQqFAqFQqFQKBSK0mGwwA0/YbU7ue1EA1w6I96WSy8xNh1L5GhcupyvH+BBl/PqjoMatNZmTlChiLGZNqAZOpcda70fMBv12hgqCkWJ1qqINQ2s6WD2ALNnRe+NQqFQVA/UuVehuHxRx3fpMRih6VDZp3V6SyoEIVjHffQfuuznLuDnaT0vEK6VATezgRlDGmc/a17Be1N1UOnBVREhWJ127VGhUCgU6tyrUCjUtVU1RkRYhWAd37WBnMR8TtRVcXmgIq1VERFhzYm0KhQKhUKdexUKhbq2qigcNtj5E1kOB48daYtTZ2TW1c3xMF96mdG1vhZZnbcRNh7VWhSdikxlMJWHdKudmb/tQ++y83LDnVgMBmg7AQymit61So0SrVURkRKs0oIVCoVCnXsVCoW6tqpoHFb47S5EVeaizC/JwI0nhzWpENGaU88q0oPnbYyQ4rWV7hQPWCDE143IpEwqmrQsB79tOYY7mby1515tYatrlGgtAiVaqyqq9kKhUFRW1PlJoVCoc4mighB1rL/fVD/XIdgn1QRboVVt70ohWhWlQ4nWy6GuVUVdFQpFZUKdnxQKhTqXKCqKxBO0+3UQ2PLUtJo8wCMAiFHfSxVFidaqiqprVSgUlRV1flIoFOpcoqgo0uM0wTrmMwhsqi0TgtWvHrBPfS9VFCVaL/e61rxpevK5apWjUCgqUd29OEelxiKtHj0DVeaIQqEo+bnk/JIEVaKgEAjBGtJejcVlghKt1a09jkopVigUlQlxbrKmnE3fUuUOCoWiNOeRvNc3qkShWhJCLH6J4WBMqOhdUVwElGitbml62fMxKVnEpdkI8DQR5C383hQKheLiUOj5RkZGvLVIq2rjpVAoSnNOOf9aR5UoVDvc0yNZankUj1VZ59WwKi4XlGitbqk12fNx8alk2Z3ypK9Eq0KhuJiI80yB5xtxTqpRzFRihUKhyO+ckt+1jsrauHQYLDB+Nla7k/HHmss+rd6WSysxLNYEPHRZbOj4Kt06d8tTw1r5EGMzsWdj2afVGvYlZqNeG0NFoSjRWk0Rdydz7lIqFArFZXu+ObMPjv0HbcaBm++lf3+FQlHuqGuYSobBCK1GYwaeb1exu5Ls1bDkdayJJzTzJsElELtuZgMvjmqW/azVRX2vywklWi93CjAjEHcm5d1JaYKSfMHrCoVCUV7knm9Keb4qNdvnwh/3aY3vl70APR+E7tPAKC6tFArFZXdOyTmH5KCubRTFEawfdD3bHkekFd+9sdJGaaszSrRe7hRlRqDMChQKRWWhPM9HO3+CX+/U5k2ekJEAS5+G7d/B6I+hTsdy2WWFQlEJzyEZSeDuq3rZXyocdtj3h0wPfjE7PfjJoY1lRLFKtccRLJiiLbuIojXT6uDFxYdkevCTYfu09ODmo7SItaJA1OiUAxERETidTmrUqIG/vz+VCnGXUbaTsGp3IM+/EFRmBQqForJQXucjcQG1/H/afItR0GkSHP4Xts2B2P3w+UDofhf0mwkWr5JtW7XSUCgq/znEM9uAp7BziTqWyw9HFsy7VaYHz8v8kgzcuL9f/aohWnPI6ed6CUjJsjPnv0O4k8nzWydpCx+PVKK1CJRoLSM7d+7kjz/+wN3dnffee4+ff/6ZTp06UWmQZgSFRC/ymhWonq4KhaIiKS/zlPBfICECLD7Q4RYwmKDpMAi9AjZ8DEdXwbr3Yc9vcOUb0HRo+UeD1QWxQlE+uFyw7y84tBSSTmjpnCmnoVYb6Hk/NBkCOl3R55ALerkWciyr47fyconrTxWVByVay8DevXtZv349TzzxhHweFxdHr169+Pjjj7npppvQ6/XF2k5WVpacckhOTs7/D0t7Es0vepHftrJP4LEJCSQmpVDDFU8NswssnpCZpK0T0gF8Qor/3grFJaLYx5Gi3ClRC63inMfERaoQnqe2QFaKNtkzoXZ7CO0GdTqBxTv/dVPPwIpZ2nyLq8DkdvY1Nx/oOx0aDYD1H2oXwN9PgOCW0KAvNBkEYb3OXae00eDze2SXZ63uRUQdR4rKRGzUCdz+uhevE8svfFEYrIlJHL99HoX6vQs/xs4XqYUdy6p0qnKi6k+rNUq0llG02my23OcvvfQSMTEx3HvvvYSEhDB48OBibWfWrFk899xzRf9heZ5E825L2GxH74KIVXB6Jx4xR/FNisCUmX0nKy86g+bCKVLrSurOplBcRIp9HCkubUubkp7HHDZY+AhsmX3ha/sXao86PQQ2gxoNwC8M/MMg6SQcWQHRu7W/MblDi5H570PdznD1h1p9697f4MwebdrwkbZPYz+HOl3yvwAubjQ47wVxFboAVseRotJweBl+P0/FmBGjXXs0G6Ed855BWhZFxEo48Ld27P58Gwx+EdpdV/AxdkEv1wKO5Zwba7rsG12Ky7L+1Cf1CERuh9gD5b+fiouCEq1loFGjRtx9993UrFmTcePGyWUPPvggZ86cYezYsezevZvQ0NAitzNz5kweeuihcyJE9erVK796r4IumI5vgE2fagetLS138TlbN7rlObHrIPEY7PxRm8RdTZFaF5Rj261QVBzFPo4UZSOfSGmJ2k8Udh4TGR3zbpUXq1KYiuinyOwQ7+N0avWoMfsgLQZi9mpTftRoCB1uAnMh9aoimtplsnYTLmonRG7TIrviAuinW2D0J9mRm1KKzPMviMujVvcSoI4jxSU7d4ja88xEcPcHfXbtY1os7PsT9vwu69DlRaq4MdX7EU2w5iWgEbSdAFu+1sSrMFoLbAzNhuf//sW94ST2UTiM642V/iZTtaUM9adZZn/SXRa6bZ0OWznrGCxSjXPSjhWVEiVay0C7du245557uP/++0lISGDUqFHSiOnXX3/lscce44MPPuDll19Gl1NrUQAWi0VOF63eK7+LRJFut2gGpEadddcMbq6dCHzqZE+1L7zoizsEe36FiNVwdDV8PggmLSLGo3Hx0wMViotAsY8jRelTewu4CXZO+4mi0n8LOo8lHIO512lRE6MF+kyHet3y3wdxYREfAanR2VOUdq6q3Q5qtQN3v+J/y6J3qxCnYhJRXpFafHIj/HInXPttyepdL3at7iVAHUeKi0bOuSMrVasnX/IMpJ3RoqgieiqOWxH1cjnPrtN0OHS5XTsn5Ic47kXmlz1Dy7T4eTJMWaZdz5RnSZWi0rJkXwyJUZGcikylOPmNGR4hDMp6jeeGhDC4edC5tbFKtFZqlGgtIyKyWrduXebMmYPD4aBbt264ubkxbNgwli1bVqRgvSTkd8G09h3tQs+7NvR/AvxCtchGUQQ01u54drwFlr8kRaz986HM0D9NSmAnnruyiRKtCsXlmtpbnAu680Wt3aqZIomLUTGJ6Ipw9vQI1Jx7o3bB8fVweLnmQOleAwY+rZ1rCkJcYIipDKw+6WBbjJNxTQyEeGWf+4Rhk3AUXvE/OLkJfrwJbl8KtduW6b0UCkX2uUPcbPrrITix4eyQuBza9UjOTXRx7AvTtLArwLdu0UMnrrOuuF+rZxc3vb4fD7ctAoM5/yyz0t5YU1Qqwk+n0Ap4e8l+wl1WWulO8YAFQnwL8STIJpJAEv1aQYjyaKlKKNFaRjw8PLjlllu49tprpVjNoXPnzhw8eFAKWYOhElh+n3+STo7UlgtDE//6Jd+euCs6+EWifnuSWhmH+ND1OA9G3MXE2QNY/kBPfD2KkSaoUCgqnAJTewu6sMvvgk5kbsQIUbofosO1qKmIgKZEQfIp7aK0OAS10IySxPnlIrD8hIPv99pZc8pOhlXbpzc2gMVkoEWAgQ419bSsoadTu8do6HgB3entsOxFuPGni7I/CkW1QqT2f3+dFl01ukO7a6H5SO1cI/ooi/IAIVK9apZ82wYT+9vPJHjFdPwTj3Pi7UEsaPQ8k4b1wtvnPBPKhBNgzD7fKXFaPogbBFd/SJbDwbAjjWSfVk/Lxb32jUzKlKJ1cKs63NqyA36JZlgFrWoXYNJXiRBjc3WnMNmnNavhe1iEThBjqCgUJVrLiRzBKkwsXC4XHTp0kNHWSiFY80Y/RM9W0QKn9Xg4+A8cWQ4dby3cLTMfIlOdjP/DQELy47xneo+Bhm18ZH6Hj9KP0OPlDP64tw+NgtSdSoWiUlBIZOGc1N5z1imGeZCoAf3zIRDirjDEBaq4GPWto/1jzkyGLDGlasuF+2fNllqEpYiMjzl77Hy3z46vGWp66gn11tGsho6uNfUEe164borVyQvr7fx60IbV7jjHoFhEaHQ6l1y+I1pMZ9cL093EMssODAcX4zy4FL1wFq4EJCQmcsPXuziZZM1t82Ex6vn0xg50DPWt6N1TKPInLQ5+uFETrOJGeb/Hz3YiEN4ZhWROxKQ7mfyPlf3xDrzNOnnch/nosDngQIKT6DQnGTYnOgzU4TF+ML9IPX0kdx+cysf7RvFP8CRmjmpHjwb+2vnMZYfkeAhSJkvlhshS6XAj4j/JW50v7UHQKsSLwR1DIPKMFK1VAQ+zkXfGt85+pkxNi4sSreXM0KFDmTdvnoy0BgVdnGhBqRAXq0KwJp/ULhrrdgH/BlranqhNbXJhJcD2Mw6WHHcyupGexv5nxfeL6618tiMLHeKqz41ZnjPoGfo9bgd+Z5rxD7o493PLW/fy6b2jaVkF7ngpFJc9pXGvLSwNWKT8rnwZ1rx1tv5MmKn41tMm75patFSkAHsFaym/ZSyVcDqd3LzIxurjWQVuyoUOo0GHUS8m5GNihiP7XKUJVXezgbZBBh7ubKJbbQNrIx18u8fOlmgHCRlOrA6xFRfHXLX52j6UScZFnJhzF5+1+5EXx3SgIhFjMOzjbUQnZrfRySYFmDZ3Oxtm9K2wfVMoCkQceL/drfVW9akLw1/VjG+K8Xt/ep2db3fnXG9Alg1i0yD8zLl/q8t+m0h9TW4xzOIJ3ZcMdK7lHuNvDIvdxAOf3EXn3kN5dnAd0BnBpxTRXEWlRLkAVx+UaC1nOnbsSPv27Yvdo/WSIVP6RHsbM9gyQexfu+u12i3R6iZbtP55xM5bW2wcSXTgEm6dwPubwdvNwIBQEytP2knKsMt/EOLKcUY3N6a1E2k2U6F2S2xr3qUzB1hmeoB5H/9F40c/xuzlX7GfXaGo7pTGWKSwuq7FM2HT59p8/T6aUYpHDS4WZ9KcDF+QSVy6XQpWb4sBd5OOVKuLTLsLh1NEWcSFqwuHQ0yQlfdiFh2dapt4roeJNkHnZr9cEWKQU16SMp18t8/B7F3XM9yxkTBdNJO3X8sbp+7i4XvuL7MALy13zt0lBau4OG9ZLwAfNyPJmXb2nowjKj6VTccS6RJWAhMqheJSsOo1zd1XuPGK9P8iBKvd6WTBQSfPrM2Safw51xtDGphJtcKpVCdxGU55GNbxMtCihp6utfUMCtUT5CGuvYSB5ONYI/7DseZdGhPJh+Z36L2qIe3r+nBNi3qFng9LbE6n0LwKDv+L1e7k7RMNcOmM3N+vAW7mi5dtWKgLcCUn0+rgnRUR6Fx2HqgXgVncZW00EAxKlhWGGp2LQKUTrDmIE7RnsHYV5xmoWcWLaMnpbbLW5JCxCXcvSdf+QWTftdTpdfJCMDXLwe8HHbnLWwWb+W6EGX+3PJ+1fi9MAY2JW/YOAYm7uJFFxL7REd+xb2NqfXXFfGaFQlG+xiLCMClHsApTtob9irXa5igHvx524NQCJvI8MyTMQN96hV/UpFqd9Jybjs3hlOeegQ0sfD7YdMF59niyk83RTvYnuEixusiwQbrdRZiPnoc6GXATFwXFxNdNz13txRTAqYMPk7DuVRroo3k47hmOvTaPsHEvFf65izJ6ES7FwjG1BP8rNkQksHjnSXmh3qJuAE8Pb5L72s2zU7DZrDz3137+vKsAx2WF4lKScwzs/0szbRT3umrezrfr65Bmy5THZoboeGMXN56QGQ42pwu7wyUvMnLuC4ljvn0tM7OHnXe9UQzMDXqC2Q2WPoNRp23zgR+2cdVLQ9EXcj4ssTmdQjPR+34Coirzq8wvycCNST3qXVTRWqgLcCUnJcvOR8v2404m090maQsfj1SitQiUaK1OiJN0jTwnatHzrN0NsH0O7JjLHM8nsqMScFNrNya3NtLAV8/SYw7e22ZjV4wdN6OOV/pYGNWogJ+Ody0Crp7Fp/9sYeCpj2mkPw0/34xtx5WYhr2gNQQvqf28QqG49OQnvM7shZ9u0uabXVmkYN0T5+D1zXbWnLSfU0+aw5zdcEU9C98ON2EsQMDdsNCqCVbgmV7uTGqdv8lbqI9eTuVNnSbt/s/eWYBXWbZx/Hd63YMxYnSN7u6S7hIQRVQsLFREVBAREfTDIkxCaVA6pbu7GwYDxjpOf9fzvGMjtsFggyHv77rOdd7T57znjef/3Pf9v6Hgz/w5eyYdLQsJSTgIU9opLXIaDYUC1TOXjn39JExtD9YEqNwXynYDn3z3PCa6GFIHf0l3rEuHLNAFnTYHuNWrqAjM8dzYMhmvzaPkQHO8tQ1fnaknHshw/ShRVUWsBnro+baBibr5HkL4JJcvJBh85Ucnz5lleLzLVN9plceK6gL8dKGK1qedeu/Cvr+koUqM2xGgEPm8DIyonepi1iREJy+Z4aVmlflk/bcEHJ8h61wNJxZjv7gVXbsflHpaVbSqqDwS7pnqFnUBdv2h9DhMilIcPMVF1KQKYVa4PhRtokRYV36iOAUHlIDKz2f4ue+stTD3aNJtERODXivrTAUiqmK3O9hy0Uy5yTZmtna5K3V3+lEb+65Y5Hs8G+qSrmDNdgxu1G39HPX+asSrhgX0MaxGJ7wAfmsGTYZBnbfuLx1btOSY3AZik93bN4yFzT9AzdegyacZfoXy+bzoXK0Qc3ec4Wx4FB/8fQQPFz1xSTbsNqtcvyPalszqX66ikjnEhnh2I+a1Y/E7t0beNd9em9H2blKN+rvrcNNrcDWAq06Dh1GDtwm8jRp8XDQpxmrFfcRjWTAJJQzfhGec2VVe1ysRlHY23C0TTYGegWqEVUUlB6KK1qcdv8JQoSfsmcbL8RNZxOeUC8yadJjh9Tz40es5Wm2vwTjDj5RKvIBjZi+0jYdC7bceW12YisrTRJqpbmJgKUSqSPM9tiTVTOlWRKua/TOUy60I588mn6XrOC7MU1r9beHINUVs6nRaauU18HZlPZVy6W573htrrCw6YSbBYqf1vATqFTDStoiONoW1HL7h5KP1iuj1d9Mzss7jbQcgorguPrkYFv0cM/XtWFZkHpxaBauHQWj721uHpZeOfXFnqmAVLslivYu0up2/Q7337jmZN7ZTaXaei+Tc1SjOX4u+7bF8gV6UDVbdUFUeMaLVlTiWiHY2144p1wnXpYus2alnlK0HZ/K25efSRhrl1zza8ilxnBOTbSIi5/SXte0/dL3p2JoFdf8q/wmEF8DZCMXczifqGsLhZeXRa0RdCaOgv5vqE5CDUEWrCjT+DI4spETSed7Sz+WUoW+WrZXXKhjI51mSTquGMdowida6rbDqM2znd6Dv8BO4qqYhKioPjUhti7kCh+ZCYEklOuqitD+5K9VNtJtZOBAOzUt9fVA5xQRC9EcUwsngCtEXlJY24iJcPz2CoGhjKNkGTMLoJG0GrLZKwSook8vI3+2Maab+isHrj41NUqQOWJkkRaxwBt5wHt4T40xRUy/SBNEwq3XmWnJlF+9XNfDGKitHEn1IqP4mbgkRiifAxv9Bm//d+w2KNYNy3ZWJACFYhTFNseZQtd99OzsvfrU6L0zby1lhoXpL6vCkZ9W2CSqP6Fhz7QScXC7HDVw5cNdT4pwuLLDX4jdbC3rXKc6noY9nqGk/sQLd5b0kOQ1MsLehdvGg9HvIZ2Xdv8oTJVg7j9+U4uUSqjlDUxP8b+UxDjktMp18zoDaqnDNIaiiVQU8AqHVNzC3Hy/rFtL8eF1ia5bAMytSc4B2RfTkdfen77K32GpdzlD9VEzHF2P5pQXG5+aDVx71X1BReRhEiu+sPnD9WGoUL38N6QoeWK4bgUF5lfsv74fZfeHGKcUIqHgLKNma3y4GMXOfjRizYl4kzFH02tL4mMqQy60vofnjGVjdm0D3jE8Zwn182SmlJU3NfCamt7p31kbzgnr29HbjtX+t7Llqk6ZvN+vaTAYdI+uaKOKbM8ztGhdQvof4feEJUKh8N0W07pmqpPgGpJojpYlwhmw/HoLKQFKskuUijr+ZiPCIlOBZLz7iRogqKgKHHdaOgi0/pGRnODU6zriVY2VsAY7agjnpzMsJZ14celcGVjfx3GMSrMcvXSVo8694aWCsrQsJXkWY2LOs+j+q3IaIsIrzTZdqhahW0AefKKPs9fpW0xKsiMrL7O1n5HNUV/acgSpaVRTKdiZi2wz8L67kbd1sXlv1PlNaZl10o0qQjoN9PRi6qQ2dDhbhV9MYckccwfpjTQy1XoVq/ZU+jyoqKplD9Eyd208RrCK6avRU+jGf36xcxCBzwGbQG+HXJmAzK/Wq9d5nH8V5cZGZa/GJd72tsEuJN9u5FAN7rhiYeiKR3mVMDK+pTzPF72SknTdWJUpB52HSSXOlzLj1TmspBK5JtrtYcdaBTqsI2pyEm0GruKpr4GqCk0J5ykDuMhB+ELZPgpZf3/tNxLqr9cbt991vhOdersQqKtnda3XfdOV27jL8q6/Le2cqcSPRPeUpQV56RlY10rHY49t3fzlgJXjHBIrrEtjnKMy1ci+zrUu5nNvZQSXDlF1BdqfpCsHapVIwhF2VorVpQKS8/7DmDMePuzL7EX0PlYzJWSMClceKtv4g7H+uppVuOzvC/uFMdBfpHpyVfF7byKyAMnRaN4zfDaMpZr6k2OFv+Abafqe04VFRUclcD0QhmoQzd4uvwDsfhB+CZR8k79g60JuU2lUhWH0LktR4BM+tcWHrpXjFMdwJuT31FPTS4ueqwd9FQ6wFLsY5CI93cilG9GZ2Mu1gEnOP6/iukYmmIamnj3PRDlrMTcTpdMp03jltXNJ1A74X4nUtC+fgwaWsxXdK0SrJV01Z/7FXsv+zM3IlVlHJTkR0VQhWjZathV6n/+naxCYlt8EDSgUYGVXXQIVb6tYfBz/utbJj+2b+MG3H5tQS03wc/6utps5nOzojtBwjXeLrniqIXaPH3aTLkpRdQUqabnZ78YmWOaLX67z+srZVpAonHDHRZO/X0qk4q9KFxbppXCYfOqcNS5GvMOp1yjpUyRBVtKqk4FusOrZmX8CKwXys/5N3lhThux5Zn4bWtYRopVOQlgtH8wxbeEW/gNK28/IgQdgeaDocdKrVvIrKPQnbCxvGKMs1XlUEa/x12DxOuc87P3T/U+lbd3ajvMseUof6fxsJj7PIQYFep2VEHRe6l0z/dBCZ5OD55Rb2XLaQaLHz4tIEfNz0sma9drCWNvMTZU2qOKFPbO5KSf/HO3DNTgw6jewlueq8gzZFxApV6ndlHXB2o5rFqDwOji3BueITebz43N6HXw/XEBu+nOwq7GdgcgtTtrSbyizXEhx8vT2RFYa/5G1LlZepW1u02VHJdsSYrVp/2ad1Uq2sTdndfjYqNU03iOxFnCtf2w7Cr0C0JT+6hyLr35K9YLMyXdjNqOfXXuWTb1XOgi/+dPD4jzIqOQp9zQEcz90SvcbBJ+ZvWHrwcrZ8TtUgHWu6e7JEU4fWlpF8b2uvPLD1J5jSXmkNoaKiknFa8N+vKrVlIXWgYB1IjIQVQyAmDHwKwPNLIE95pRYtWbS+dbgE4XE2OeBsVdTE0RfcMhSsAl8XLX+3c+HPNu54uehlsDE60cbILYm0nBOfLFg1/NjUjRY5LKU3qwkNUH7f0tMW+bul+6/A5Jn9Hy6iq6IGVo2yqjwiJvzzL1F/9UeDg1m2+vxqaaqkAXvq+b2lO2u6uuYIwSrotdRMES5RXHsJp1aPW9PBj/srqWRByq64fqQI4RpcQV6KlKwo72paMvDRfw+Vu8gZRxqVnINGQ/F+v3JUU4gATQxBO0fjsNuy5aPyeWpZ3slNOmiOtXXlZcs72HUucG4jTKwHV49my+eqqPxn0oKvHlLSgmsMUO4TLWxEqxrvAvDcIkW4Cvb+CYk3SMCVZTEh8q7OpVyke29m0njr5NWx/zk3JjR3I5+3IaW+U7gmTWnpRuvC/23BKhheS/ndFpuDb3fblckDgTF9R2UVlSeNfecj+frzd+m1uwc+mjhZG/qZsx8187kwp707W3u60ahAzsmomHHUxtFrVmpqD8vbGtFjOtlBXeURICZGz2zAenI9E9adZvz6c/IYmV2IljQiAvukItaNWEdiXYl1JtadXIcqGfLfH2GoZB6jG7bO04id1YSKmhP8vGwr/VvVyZY1KVxBF3ZwpdW8BJY7qtAsYQSzvP6Hf+xF+K0ZPL8McpfOls9WUXliES7AG8Yqy0KwisGZiK6e3aDc120q+CrilIQbsHyIXPzG2hErehoVNDG2/oPXz4hoqricjDQyfr+d/mV0/+mU4Fspn0tH8QADJyKs/Lzfwrtlb1ZeJde4qqg8AVyLNae0wrrZvzkywcKmU5Gs27CWZ6+MYpD2tHTxPqgtgbXuIA4X9iOnEWtxMGCVlQ0XFNfy3MYkZVf0TnZMV3k02JJgcmtEYde4pN9IxIXOFYNSe4NnEYcuxxLK7S1phDnSg/A4RW90opWvlhzElSRecXlBufOjMDWL5h6oolUlTcqEluEf7/a0i5lO1auzuRpXk1we2TMoDQ3QMaetG10WJnLKEUzj6KHMdh1FsaQz8FtzJcUxSLWqV1GR2K3JacF2CKkNIqIgOLNOSRUW/VZFatNNVg8DcwzHHPn4w95c1qD91jxrBhJFfXWMrf90iNVbGVHbSLcFVlnfG56oJbe4U50lV3mCEILVbHMwedtFJm8+R0yiGa3TRj/dUkboZ2LS2ohxunGyyHNUqvOM0kYrByFS84dutvHnYbN0khNTRwadlp7F7HBc3LhFyKiu2/8JhMi8lHBditamoXnpW7riA7n5itcIsSvqUwUPI3xVHi2qaFVJlybPfULSd3OooD3F50u3MLRL9kRbb7bE2dnLjY4LzJyL8qRT4mCmGUdRznwafn8G+vwDedVidZUnK3KRLWz5EcIPKGnB1ZPTggVX9ivXJZ5Jve/8Npy7JssB3VDr8zi1Rua2ycbv9pRQPY9Ouj0Kp8yt4dBO3Clcfe8gyWJn94Vo/NyN2b9dqKhkAhFVfWPmAa5Hx8nbJTXnGW78g+papSzngGtVSrV8jUoeATluvUYnOagxPVFOGgmEZG1bzMTYenqMe9IwRlNdt59obhWZoZpLvGWCpqUCCBUtah4AIXKFA/DNljpqG5snB1W0qqSLu38wm3J3ofbVv3gz/jtWHcxPkzLJKYfZgL+rlnXdXPlqh56fdmvoZRnMH8avqGQ+ifO3Z9B0+hlKy+GhikqOjVyI62wVJ5HK7LB0Cr5Zs3VqNVw5oERDCjdQ7osNxzGrD1qczLXXZTulWdzBVZoqqTw8DQroWXHaztEYE+3EmfRW8zink7jw09T+YT/RNqNsbTCoSRFVtKrkCIYvOc4v608km5o4ecNtJW87pqDFgVNnQlOtP2WLNb9ZsJ7jaP23WQpWUVteMY+Rn5saCXTTKr27Lu9NdU6/ieq6/URzq8j0iTLKPqqheTwf+j3VfqtPHqpoVcmQmi+OZc8XO6moOU7hHZ/zh+Vr+lbyzfxaE3V1N04pvQzF4M4cC4Xqphk9/aCqgdaFtLSdr6G3ZTA/GcZRn/0wqw/U/xDqfwBqk3CVHIaIpN2MtGYrdd6BvX/B1cNwbhP4hCiu2wKxfwQUk4KVPzuhjbvCCUdehlr78tszbjIVP9uJC4fEKKUnrHTW1YB/EXB9gONGDub9KnqWnzJz2iGTgyHipHIt1v3id/A4uojdOg2HtAXZd6Y8Qdd6QO57C4FHFrFXefqwxLNk/2V+XXcCrQZMWiczgv6i4o3FyuMFaqKp+iJ4JG/TD7r/R19SyhdEyrwoWRDHKK/gLBHB+67aOR9llW/1TjVXBlYy3J5tEnkW9C5Qtkvq/UZ3rpn1RNwQ+5VZ3a+eQFJEZthVKVpVnk5U0aqSIVqjGwEvzuHSL40orL3Cxb2jqX1kCD81dZWGJPfF9eOw9P270+dOrYJC9aFqf3C9vSZBDK539nbj+eV6nr88iCGGv+inXwrrRhF5bh++PX4Bk+rWqZJzEALjkYgMYbBU83XY+I0iVkXtlhCIYl+q9x5cPwHTOkLUea45vXjJ+g7PVvDLfqdP0a90+yQ4viztx90Dwb8Y5CoFQeXAtyBon9x6WFHPW6eAidMXlRS12Msn+eHrLxiY+BNuDpFyqUGncVJOc4Zy9jMw92840R3ajAODy4NH7NX6PJUHxJEUx3sLz0jBl9eUwJLAH/G+vkfJ0BDn4ZKtH0xYinP7he1wbClc3pP2czyClEnqkJqQ55aa+0zy2RZFsIr0/NsEq+DwP8p1pT53jSkeWSaMSpYQzHV8og4pItXNX2lDo/LUo4pWlXuSP38IUX3nkDi5OfV0B+ibNIW283pRKY+Rqc8Y8TDeI91w/6xUwSoGrS4+4LDC5X2Kecy5zVDhWSX1VzSovqM35OYwAwNWPc9RS36+0P+K79mlXP2qAhG1P6FUo945NoVJReVBuWe0TYjWzd9LgyV5Ebj5we4pilOwNZ4zjtw8Z/0Qh1c+hlTP5ujv1SOweRxEX1Rui7RlrUHZn4WYFY3a468pl/OblefoXZWosIiKyKiMaI/gAI1OEbPi9V55oEAtCCieI/fzX5sZqDYlD3anBk9NAoPjR8v7DzgKMsX3dT5t4I9rxEF0IgIkUrj3z4CkaOj+V7rZIveM2Kv1eSoPyJfrr1PWso+u+jW0121Hd92iuJWKDI1gpR9lphCR1KOL4OAcpUf0TdwCZCs7xbzJqURf467AscXKpdZAKNY00x+XZHOw+4pV1ui3K3bH/iH2sYs7lOXqrzy+TBiVh8Y1IYxVpkG4rTcrUVUxMSsc8cV2JYIgKk8tqmhVuS98ClWEzhNgzvP01y/hnDM30640peZ0O5t7uOKZoXBNbgVRpBHkq5Z6d57ySlRGnNB2/6EM6sRgPLfwhkulVrCOfX3cmHyoJX235WW09nvyOa6Ra8MbbF43gT9836Bf+xZUL/TfSj9UeXq5ERWNPSmOG1YPAj1z3f6gED0zeioTP7dyaL5yAXbZi8kIa5LJj60dszGqIATprslwJDnCIQbAJVqDX6HbnyciwWI/F215os5DzEWwJaaaR2XEwbnKYCWkluKUHFgyxwhYF72WnX28Obv6GYpcWSLv+97WgXG2DtjC9fwzV8ff7etRukhD5bv/OxyOL4U1X0DjoQ8WsVfr81QegMRdf9FzxzCGmK4od4g5Iv+iUHfQg7WHEenwYuJMlP2Is7zBDWfucjjyVEDv5nP3cSLynGIgJ0TH/pnKeCCTmRbzTjrQ4JQjik9q3DJ8FZNh675SxhoVeinlCI8rE+ZpRUwyNh0uo9mVT+bFrjHganiwTBqTJRI3jZltlUZTvXQRmNkbpnVKfYIQsSL6+gQj1k3N4kHonFbMRT/DpNcq61AlQ1TRqnL/lOmonKD+HcEww2TOO3KxPqk8taYnZixchWHMhW1KndstHKYQkwyf0MJ3E01i/0EffQGWfQDFW0DlvmC8Pf33uVA9vUtV5NsdP2A6PIcXNf9QS3uIalGv8vkvvbnWfQityz5ELY6KSg7B32ghyuLAx5jshHlrbbg4eYftVgRik+EyWplwcT9nd60gb/Qu5tnqMNL2LC4uJtZ3vdeE0kMQcwnWjU4ZtJK7rNJux+BCtEXLO4dCWHNNMcsIMNko7pFEZZ8ESuVOpETheEKcYRwKi2b9dQ/OJrpgderkYFSPA73GjgkLtQ3HaKrdjTbhOhxZoFxEvV2hBpC/mnKMkFFZvVI/mxQDSVFgjgPPIPArooi8bMSo11Kk2QA4WUz+9gEFanNmvY25x5Kku/AzcxJY1NGNsnkrQa03YOO3sGEMBJaAcl0f4APd1V5+KplrkbV8CK7bJ1JIA3FOFzSF6uFeuhkElMj0BFBSQixnN/xJ8SuLpclbtNONr2w9mJ1UH2usHucJEOPv4p5JtAmKone+63gajEpWhSht2Dpeibqe3wIFM9eRoFKgRnotia+844qTRgXEF4qBlZ8qk3miNV7Lr9Wt43GgN0LtgYhpgWn1s+YtYzwKQ9Em8Np2JVvnJv+BdGEPFz3TX7jp6VLjMX+bJwdVtKpkjrrvQcRpdPv+4hfX72iZMIyTSfkyFq5eeVMH3MDmGx58eCg/5+IN8uTzN63xpgEf6qfTQ79Gib4KkVuxNxRueFvKsFar5d3qHlC9L5cuNyd608+Ujt8uRfT3M6P52z6K9hXyqP+qyhNNgK8vAe4JtwsuIcRm9lIEq8mLfRWG8euBEDZdSuJ6QmE0KClxYlBXM5+RaS2N6LPDsEykBJ5cCdsmKGn/OhOUaiujG5EWHW/tCmHtdQ+ZwneTq0l6riZ5sPF66kSU01n6tvGy+N7iRTqNODE5Mds1TLE3l+L154JrqOfYCdePKRHbAzOVy/3glU8ZzFZ+PvsErPghyemO4qT6TQMjLQvpeHF5Ahqnk8+3WpnVRqeIehFpFtHjvweAyfP2FkUqKlmJMAWb2w/ObpA3RQZAeOHOjKyf7DqeCU5cT2D9v0tpnzCHkppYed/f9lqMsPbmOt637Qp2JxyJceFITBBfHQuia75Ivi5zAXRGEJM3wkBO7AOiz3QmRHNJfx2eLjrizHbG7bbSKK8DVn0K0efBMw90+zPbJ6lUHgNCoD7hIlUla1BFq0rmECcYYSQSfQHj2Q1MyDWPxuFvEptkp8HMJHb1TuOE4ZucKhh9gX5b/FkVnVe+jbgIB0MxWI1yejDY1p/59jp8afiFIomXYfN3JO78E9fyHUHY799hXpI3Tx7ydhrKjR0z8TsyjTf0fzNujoa/NaNoXz5I/WdVnlzSiqYdXiAHexb0tI39iKPrRFZBknxIk9yrMMRHz4DyBnqUzKZDu3D9Fqmt4QdT20qUaovN4MnQQ/mYftHvlu8DzXLFUtDNzK4oN84kmIiy6nCISEnyoUTs+15GB00CY3ir8GVC3FNTnn89F8Dwo8GYMdL7THPyuDamY1A4r3puxuPGASXV+KY7qaiJFdFW0ZtRpI4JIZ14Q6n3FanIMh05Ceq+y6OiSYiOpgWNrDxjZu9VpZ+kpGIfxUFdCIlFbytCVkQpVFSykgs7YEYPmTob73ThbesA1mprcLT+Lf1L78HhCDuTd0UQdPlfnnUuop8mSu68Jx3BjHH2It67KB/kiaSil5JyLPZpMXE185I/6yM8uZKkl/fNvuTLFbOBqZVPQ3BlRbRGnFD2z5ttu+6TloUNzDpiZ99VK45L+9CK9xEZF6KXu4jkqjwexLH48l6sdidzr+TGqdHRqWKQzES5X3aci5JtbS6FxZH5iucnC4vNwdw9V9A47XQKCscgZmuFQdkTbE74KFBFq8oDbDVGJQXnpxoUjd3OJxXiGb7XnYgEGxsv2amT946dTtTN5C4jB7rPJC5gtWYALjonA4uE83LIVelHcs2sY8EVXyaeLUaLxFH00a/gJf1iclsiYMfPXNv1N9HVB1G0eOnb31ujwa9adyKNbvjum8RA/Xy+nmVgr/8YKuTL/GyyikqOxJqIY81I2Vdxkq0VRx0FpOAzGrQU99PTo4Se7iW12RNZTcYWHUbc0mH4mC/JFMO/9O05pKmD4YSWeWE+UowKxFXLoBi+Dj2Ph14Uzt1NrFXL0TgX8rtaCXK5ozY3mX4h12kSEE377cXlQFgMgH86m5cfnV3wM3WkdVAU7xS5gq8xVRDG2bRsivDghtVAjE2LLSmBEkn7aBQ9F+3pNUTnro538cylJD4ML5UTvVzNMk14/D6rnFCQg5I6b0P4IWE5DAdmQcVemRrY9fxlBxbrLanjGi0j2peld/V82fNDVJ4szm/FOaU9GlsiRx35ed36Bicc+fimgUlmK2WEOIf/sCsJ72s76aBZwwjtHgwauxSrl5wBbPVoQvNyIUwwiqmn03e/gTtU8U2QizYHtNlWXEZd11/zkOf5QJObMsEksjRErXsmGVRFz8zD4us4OX/hLAXFnSJbQaTbqzw+xKTgz40QeXHDkn4jERealGxy33XE4rjWefwmOaEZqrnEWyYI9k7fZf1JJzrRyuC5e3Alie4uLyh3fhSmln7cA1W0qjwYom2FMBY5u4F+xlWMMXWUzb5Fys5dolVMtVbpB4vfpqN2I79rWtChqAsvFryW8pRAk10OUsVlb5QbP5+rS6uIJjSxb+R1wz/SeMln82Cm7O1Juzad8Ha9fdP1rdCWSJsF30N/MMgwi1GTjIR8+C2+bmoEQ+XJx7Hxf2hjLhDm9OMHazs6l3LhvSp6gtyzT6TeZM0FO/O2HOKThFEEamK45PTnBcsgjpkLQHzq84SIruybwE/lz6UrRG/iaXBQNXlgmxEi8rqr/iF+Ph/IjIv+nI43pkRzpp73Z8o5f3K72DDpnFxOMmC1p5VtWIT39FZe1/+DffMPdNtXhOmdct9z8J4VVA3SUdDXwLkoK19vN9MvVKdEHkSaZOm2sOsP2DQOyve8r97TsUlWevyyHZtVcVBNwelg5NKjqmhVgXNbsE5uj8GRxGZ7afpZ38Oqc+Orei50Kpb2kO9MtINR262sOW+hiWMLI/WzKKxPNmwCjmsKExlQmarFC9JJf/+RILGpL65+nMIry8n9cuTxvHxb9nyqaBUGTZkk0E2LXq/FbncQHX4++c6S6j//hCMirOKY1qVaIZr5GKVrcGgexRNBReUm2X/WVvnvUu0l5fr4UjrkE30JYdeVO3qx3kSYMBRugFbjZLjhD6ItyWGZNKjgk8CP5c+ys9ExBtQK5lufISyy15CzvX0Sp7J1+gi+3Bx91+t8q3TmXOGecvlD7TT+/OZdHLKNhorKE8yN01jXfSMXR1h70aeiL2PqG7NdsE4+ZKPB5CvsXT6ZrxM+lYL1kCOElzWf4OfnTwE3K+56h0zxL+WVxNq6R5lX/eQ9BWtmEVru5YLXWFPnKGea7md0mQvy8wRiIHzVrOdCgkFGdW6mHN98TBoyauB/tk7yu/tp4ugR+ztdF2d+sPyg/NbMJKPP4lj05tpb1k2B2sq1cFM9s/a+3qvVj9ukYBUeqs/XLcqgFqXoW6eI/M2JSWZm7ArLpl+h8iTgOLUW8x+KYN1gL8Pz1kHUK+zN4b5udE+jZECkKPZZaqbB9FisZ7cwVzuYn4zfyZ7scRp3rgbWkhPOxet1lS6u2kwI1lv332p+yuzW4nBvJSJ3cyd9ANEqCHLXocOOf/wJefuioZBsE6by5FOtoA9NSwY+7q+hkkNRI60qD07h+krqb8RJPk38ijnOj7A4jEzcb+XlcmlYd1fsQ+ypbVTWnsB8Yz4469zThEFEWsZWCMdhr8/cPQVpHTeH5rqdBB0bSsOTQ5jYJoDivqkn0pC6PdkRb6dq+Exet01hzhgLnQdNyDEtMlRUMoXDQeSMV/DFwkZ7KNYC9fgoG3uurrtgZ+J+G1cvn+MFzSKW6TbgYlCE1gljKfJVaMki18s8LsQAuGveSHkR81FTLgTw5yV/OftaxSeeZ3JHUcs3Lu2gZUw92DOVptpdDApLYNphPb1KZ/8psIivloYhJtaeM7P0lJm95fRUsO5VXITlj9IrPWvjrikmMnfWMiez6EA4568pk3VNywTTrGRAymOzd4cRn5DILxvP0r1ycLb/JpWcx56F4ym9cygmjZX19rK8rX2fhV29bjs/3sqvB6yM3GbG3R7DT8ZfaKXbLu8XrUp0Barhka8aHvqsaREzpPhl2m4pitGeSNyeOXgIp29Rd+71YNuqn4uGrgnzyOcIk3XsMT6l0MZb1ZY2Kir/cVTRqvLg2CzQ9gf4qwumyOOMd5/IiwmvMWqrmWdL6vC400nYIxdfu73NpwlfUsu8CS573HdDc61OQ6cqBblxrRdJh+dQXnua8fbP6DnrI9qUy82nNVPTgKu26M28+UY6xkylc8IMVv/PTOOBv91X+p2KSo5i8zh8r24jwWniY8dLrG1+fzU+IoLy7R47f5+wEmNxYrY5pUHGrShmSBp0WqQJhHiOzmHhNf3fvKb/R6ljE7U3LnnxLlSZYrI/as7Zh8Tu3DfkurzcF57B0qTJ3ZpARc0Jxu8r90hEq+CnxgbKTbZiszv436Lt/K7/Eo0wkBKTfp1/V5xPRbqkJSFd0Vopv7c02xK1fFtORfBC9bwyxdlqcxCXaJb/Z35f1Tn1aSMuPpHVP7xCu8S/5U691F6V3/zeZltbjzRr3K/EO2j7dxJX42xU1hxjnOlH8mmuK9tWvmroClRXzMyykPLeCeTXXOVn4zd4JFxU0uOFL4Y+8zWLGy7aKXZ9FW8Y/pa342q8h8HFDR93tcelisp/nZwzAlF58hBRATno+kNGCxo7ttBNtxan08Fzy9JO+2lRpzqjbD3ksu3kGrDcUhR3H/gFBuFdpTuJOk9Kai8wyziMFfsvUHdGIkkiPzCZjh26McHtJRxODY2j57N7wguKu52KypPCofmw6jO5ONLWkwjDvR2xz0U7eHaJmeK/xTN+dyKXY23Em+1SLAmxc+tFWCaJfVU8JurRSzjPsMA4hLf086RgjfUsKmstvav1glylc5RgfSBEtoWvtG2hju4AF2OsRCY9mvIBN4OWn5u7EqK5zDjtt1KwOoq3hBeWQ55yyrFURFwzaNcR7OPCiA7lZGZlQmISfafu5cU/99Hvz73y/cS/OrpDqUfye1RyBmt2H+XAV40VwQqMpwseTT9idnuvNAXrynM2av6ZQEScmTd085hlHC4FKy4+aISrdZGGWS5YBdYb51lg+phS2vPYTD7wzGjwK5zp9xGTcWtWzOcb4wRZamQv2w2Pil0oljdQjbKqqDwFqJFWlYdvy1GsCTQdDss/YrhxCmfNQWwJK82S03paFr59E6sVrONlfRvaOLZQTntGaTAumkdnBvcAXCv3xLFvBoXNV1hkGsJbsa9R7c/KrOjsklLr91Kn1nwx3cgQ649UujqfKz9eJuiFP+XrVVRyNDdOw3yl7+oSU0umJTUlj1vGKe5LTtsYsFIxsxAIWVrUz0Cov448Hhrye2jwcwGrEyx2sDog2uwkygyuMad5+dIw6WQo0/aKt8BTRlb/Y2n1QrRePUwP3b9MtzXmy+0ujK73aMzaGubXEZBnOd43EtjtKMpnEQNYcPNYlFaLozQQ7sAbjoax4sg1rBYLtxoIVyyoDtyfJr78Yw7Pn3mPIG2kdPNeGDyQAc3qpvv8r3ZY+Wl3IqGas4wy/qycfwW5Q6FoM8iiVOC7MMehOzQHP42FfY7CFGnxMR4+uTL9Ng67nelzZvCJbrq8fbnU8+Tp8I2aQaWi8hShilaVrKHay3BmPcbjy/jV8DW9nYMZsLIEk5q70rzg7ZtZt5ImxhzoyhTjV9jC9qEvWCfzaUKuvmgrPAuH5+Mbe5nfDaMZbe1GzT/b8WMTVymWRercoG7NeG+anhHO8QRFbMU2vi767lMhXxX1n1fJHkT2gEzzTL8+MUNERsDfr0nDEmfuMrwb1ltK0Nz3MF6aesSeIlhbFzMxrKYBf9f7iI7arbBAGD0lgVc+CO2YYcTviUYI8QvbCUy4zm/G0bxw5nOo9+gmscp6JcIN+Ntem30XY9lyJpKahXwz9R4TupVi/Ho3dl02p/T083Y18HlrteXH04Aw9Bo5bhzvRH2Jm8bMKWderHU/pEeR5H7oafDOWguLjsYwyDCfV3QL0WscoDMo/c9FO7rs5NQqtA5FsHaxfMJxn4AH+s1TZ0zjOdtseXt5QF+ad/32vzep9iSjNUD9D2U0vPTJIGwaA66G/2bP0e1no+R1QX83qob4PNB7iHVTvmAgeqcVS9H3FVd5sQ5VMkQVrSpZg04PXSbD9O64n17DZONX9LQM4aXlRRjX2JX2RVM3tY+q6SlzpKLsHydSfG2X9qIPqZH5z3Txggq94ORKtJf38qFhBqXt53h75Utcq+PLc6F6XPRa3unUiHYzgpmg/5YicWE4f38GTdepUKKF+u+rZD1CsN6jPjFDtv4E5zdLc55PNa+SaBVpvPBB1YxPaBVzadlyUYzjtPzQKBNRk+NLIeaSkhZYtvMD1Zk9MYhaurJdSNo5jVJcYJR9LNfihhHo8YhaY4k6Vlmjr0eUDA/55zD/vlU7U5MdWhdPXmuWzUJDJUdis9r5eewgPkr8TabH7tGXp3ynD+U2kR59l5k5cu4y80xjKKM9q9wZUAKKNQWjR/Z+4ajzcO0odrQMtr6Izuj6QG/z2vwz/GCdI2t2//LuT8++H6iCNaehN0LDwYgj6dym/CcRIlVkMM3efobZ25VspjkDaj+QcPVw0fPPK9WSbyWfA1TuyRNepKSSozC4QPe/IKQOnppEphq/pIzmDANXJzDjaGorHBEBnfyMK5NsreTt2HN7lGjPgyAiDcVbyBljUdPVVreFv42fMm3TMf4+qXxmPk8tL9UvThvzCFbbK6KxW3DO6AHbJqZa76uoZBX3UZ+YLof/gZWfyMVTxV5g8lnlZFingImawRnPWrcqpE2JSlxLuM9aTXOs0itUULDef1uw3sTFG2PZTtLcqr7uAHuXTHqEH64cb8rmVf7XU5ejOHUtua5fCFZzDKwbA2tHwbXjqS8Tgla4C2fSA0Dlv0NSXAzLRnVmQNKvUrCucWtOxR7D0xWs4jjQ4Z8kws8f5x/TUClYnSL1P7SDcsluwSq4ekReLdbU47CzYLpOxhnx3NIkWkVPR6dxss+1Oj2fe+O/mwmikqMR4lSI1K+7VpT9ZDXJ/WVVHh2qaFXJWsTJpOcMyFcNH008fxq/kML1g3WJ0gTiJlWDdCSGNOCS0x9fZzRhx3c83OcGV0RTvicOnYs0e1hkHMLhtTP556TSu61LcT3PVvTjJcvbzLHXU5w7l76Pc0ZPSLjxsL9aRSUVESXzCFSuMyM2bGZY+qGMxtlD6tLyYF15UjTqdfze7N5pQ6EBOsUBVAMLTt2n6ZgQrKJXonugYgj0lKD1DmKyRz+53DhhOV8vP/ZoejqLbQEoUygvGq1e/lcfLziaeuy0WSH8AMSGQ2RyzeGd0XuVpwtLPIsWLyDs6+q0tv+L3anhb78XaNj59ZT08LR4foUVl6t7mGkcTpAmEqdbAJrKzytR1keB2F6vKdv2HLOSSdUgf+ZE6/PLzRS99DetdVtlb+LyHQc9eNmFSvYijp9Xj2C7fIglB6+w5NBVbLeYY/6XhGuXSsGyn+zDINaNWEdiXYl1Jid4HsU56AlHFa0qWY/JE3rNTRGufxlHUlZziheXJbLtcupgemxDN0bYnpPLgeGbiLjxkOLRJz/aai+S6F0Mk8bGR4bpBG8YzJJ9F+TDQ6obeKWKJ+9aX+ZT63OYnXo0x5bg+LWZksakopLV3Ets3Cpq9/4JsWHg6kfXyAGYrcIRFn5u5qLUu9wHfq7KoHD52fsQrVcPw4nlyrIwYnnS3YEzSb9KXixx1JBRqxqXfqfan4nSfTnbsMTBjVNyMS6oOuXyK7Ws+y8q9VFyIO6bH1p9AzVegeLNsyZ6r/LEsurIVUaN+oSm21+gsCaMy04/phUYTvs2HTNMj511zIbp/EYmG0bhpUkE7/xoKvYC14cbaGeKiJNgS8Th6s8Gu5LO3rzg/R1jbA4HreYnoT2/mSH6P5U7G34MeSqo+0BOxZYIP9VAP7EW707bxKtTdxCZ+IAZdDmZqAsQthefqEMEc5/t1tJArBuxjsS6EutMrDu5DlUy5Okapag8OkS9qRCu+avjnSxcy2tO0m1hAocj7CltIF5oXZ9l9iqyxcbR/Vt46Ik5oweu5TsSUbCNdFSsqj1O3T3vsHj9FvnwoCoGNvTwZJtvGzqahxHm9EMbcQLbpCZw5UAW/HAVFe5fbNwUtYnRsPFbedccUzt2hisPdy/tQv1MRCcq5Faee/D6PUSr+MwtPyrLQeXkhM/Thmgj3aR6Bazoqas7SJmkndSbHkfFKQl8vMlCRGIWC9grh2QUPdGzIBb3PFQvpAgI0WM1JSIhhWsBCCyRfvRe5T+PxWpn8LcTCZrelA8dv2DSWNmoqUR4o3E81yjj3ubHI+2sXr+eH43fYdTYcfqXgHLdHn3q/+X98up0QEOcGq2cgCvpe2/jpOgkB9X/SsJx7QTfGX6Qk0rOSs+hrfeuug+oPD6uH4eTq+DHajCpPk3Xd2aVaRCuCWHqv/IIUUWryiMQrjXw0iTws3EsXs44Ws9LTBkQyjThCv2wOHXU1hzgu83Jo/WHQaPBPySU+Ar92ekoIetrnzk9kk1/T5COrAW8tCzr5EKDyqWlcD3myIc+IRzbpEaw+Xs1RUMl60hHbIhUVOGymCJqD82V0f4IvPn4Sj0ZRMnvbeCrupkzCCrqoxzS4y12EkRPm7Qwx8GaLyDqnGJMVLghTytGNx8M+SrJ5eGGyfhpYohMtDHtYBKVpsTx5fYsjBRcPSSvYoJqyuuaBX1kSb3ombvmRETWfY7KE03s4ZUc/aI6X0a/L+tQY3HlYJH+1Ok9jAoFMnaavhrvYOLfq/jBME5OBMf7haIJbaccYx4lSdEQeVouLtUrxxeDTiv9LDLifIyDqn8m4ptwVpo5umvMUKg+mlZjVeMllceDm79iUjivP0zrpNzXay7bKo2W7t0mS6T6zzxCVNGq8ghSheeAXxFya6L4UD9dDtj7r0xtMNihUn7W+SoHgzdtk5m4KzZLPjq3jzvFarZnpqOxnK2tHb2I83+9QdyloylR18+a56eL9TPW28uid1hgxccws5diUKOikkVciU6i1tcbKDxkOSEfLqHQ4KUUG7KU0C+3MnLRPhyrR8jn/c/agUSniWrBRlZ3vn8H4GVnbVSdlsCkPUp6kYhnXI5LZ7Z40UC4uENJBy7ZCgwP5uj5nyGkljRnKqC5yopc31EuQMhIjVyHE/YkcuheUev7JTn92iHMcMScnkGH3qDUKq869uBpZir/IY4uxm1WV8pxgiSngS1eLfDs9gtl6rS7p2hbddbGT9PnMVb7vRSsYV4VcC/T6vGk/V/apVznKc+Cq0pPVr97tN8SE9lNZidQ2H6GGcYR5NJEQa5Q6DpZac+jovI4EFlIr22Hl9YpF7FctAkxHoXV/+MxoIpWlUcjXNt+Lxd76v+lpvYQu8Is7L2aOhhs2rYX/xrqyf5xvWJ/4Z/jWZPb7+2ioV3dqgzVv8UVpy8FnJcxrvyQ07tXy8dbFNQzv0suXtd9zGBrP8xOAxxbjPPXphCZ3B5AReUhEJM0z/ywhbCIGBx2m4ysifGnuNgSY2h++EO09iS2OUoy1daEd6q5MqvN/dWxrrtgl+msryxP4Fq8Tb6nq1HHa5VdKeKrTe37euM07JsBS96DuHBw8YGKfR6dKYtIW4w18e7BAow8noe/Lviz7Yb7w5cDZAUibbJMZxmNCow5zILcv3DkeTd0Oq0Urr2WKGZuWTJjL6K7CZdT7zIpg/HzD+pAqboK/3c4sQr7zD7ocLDQXoOfik6kZofX5YTKvY4v76+OJubfMXxmUJzAj3jVJrhC88cjWIWhXNgeuWgt0ZbjEYoBY9siGUd7ey21UMx+iunGEQRoYqTgpe8i2ZNdReWxC9fgCsrlKSylyUmofVpVHg0Fa0OVfrDzV0YZfuEZx5e8vFLPtmeTa/00Wup1GciWv6KoqdlPrbDf2e3Vj0pBmeg3mQ4uevi8tgs/nRhE4QvzaKHbSeED37LjynmqtuhDEV8dO591pfm8FnSLCmGS8RtyXT2Cc0IdNN2nQ6G6D//7VZ5aek/eS2RsgkwFrVsyD6WCPMjtZSQh0Ur5rQOpbDtBjNONQZaXeKOKOwMr3V9UYd4JG2//myhFsMDHVc+QGkbplC05txmOLYXrR8F6yyRQQHEo0fKR1ridTzDQfEuJuzpM6TSwps4RCrg9ZsMO4Z4c2hEOzIZTq3ELKM7X9Zvz9uoEmS782RYLn9U0ZpFoTS2B8HE1EBsPV2KSHk9PYJWcwZn1sg2bzmljkb06n+kGsqtO+r1XbyImfscu2ctw508U0oVLZ+HreRtTqmjlx5dOK9yvHVbwyssP1yqgwSwzF96qlP5wU3QW0F47xnTTF7KUiLyVode8R2scpaKikuNRI60qj44mn8kTWYgmnPGG/xERl8R3e1IHq3qDiWLtP+KQsyCBmhj8jv7FkeupbXIelleLxeBdvg0T7G3l7arX5rL7r09IiIuSUS2RjumeL5S25s/Z7yiERqQIT2kHB+dm2XdQebrYfOoGG48qkbUKhQJ5rV4IjYr7E5rLjR5hX1DftgmnVs+u0oMZ2qIw71a5P8Eqar9uClYREfypqRt7+7gpgtWaBJu/g7Uj4fIeRbCKlFTfQlD8GSjd4ZEK1lirlmabS0rBKjSrCCCLa3Hb7oT224qTI/ArnFrfu30S7QMu4eumDLT/OJAF0VaP3PLKNfqk7BUt8HZT/u8b8anlEplCdRV+8hGGRX91ldvESnslBlpf49dnMnaJjrU46Dw/mqMLv2Wq5lMKacO5rvHDVq4nuYtVebz1n8mGhlGFW/PjXuX8XtBHj4dwPkuH/609z2TTV4pgzV8Dev+tClYVFZW7UEWryqM1Zuo6BfQm6uv287n+d8ZuT2TNhdQ04QBvDxyNPuG8IxcFNeE4D8xmz/WsOwHX9E+kR50yfMYrJDqNVLLv48qcQWw6ekmaRPzZ0kTtknnpavmEBfaa4LTDnH6we2qWfQeVpwcfNwPO5M03Ii5ZmDgdFNn6IYGn58sMA02992lYrSJNQ+4/8eXzrdbkNGMN67q50bJw8mtFGvDit+DECuV2vmogejPWHqg4iIqUu0c1oHXYsV/ay/JNW6nv3IHRaeHbshc42XQ/55rv56syF6VwvWHR8d0pRdA9dvJVVcS9086xBWOIT1QioK4G7cP3cfUrJFMd9dY4vK9ske93+JLS7ibY5wHrilVX4Scb0e5qeg85sbTFUZrXrW9SLZ8bFXKl7xi+JcxO+ymn+TxqMN31a3E4NVzwqUZAzd6Y/B5z6qItSSk/AJptr4jNrrTtGlw9/cm4uOgIfnIoKcFR3qXh2dnKWEHlyUJrgFpvYKn2OoXyBFI82A9XQ+b68j5NiHUj1pFYV2KdiXUn16FKhqjpwSqPlnxVoOs0nH91pYd+DXudRXl+aSNWdHGjuK9ygCtbIBc76wzHZdOHlNaeY8eBuWwu051agQ8YjbgDb6ODz+r78MOBd2kf8TOFNZfx3DqIMWeG8N4zoYytb+RMtCcDL78m0zZ76VfDgteV+jHRP1FF5T4pnceTPrWLMm3TSS5ej2bSwrV8YvuOXHF7ZRsIIVilEVAm+fe8EsGoV8BIPk9tqvnJ6mFSFIvWT5RsDb4FH/1/JZSo6AF7dgO6pCg6a6Cz8V/MGhdMscUhpgJ4BdM93w0mnc3F6Xgj357KzQsh1/DQP+YiV42G312fo92NMZTSnOEt3RxW5+rDlBbGezqfpodo8XU62smlOCeVjNWomric4+um877NS9Y4i9X1TuMiPD9lL25GHd93DX3gz1J5grBbYXZfiLlIpDEPL8e8TRJGvq6Xfhr6yG1WTu3fyHzDeBmVjNO441a2Lfn9QsgRxCuGYqKV3FWHl0wL/rqBq/SOSBNrAknLhxGivco5Ry7y95uvCtYnFb0Rmo1AbL1LHvd3eQLwcNGz4k3FSR7qPeZv8+SgnhlVHj3Fm6Fp9LFcHK7/g1qaA7Scm8iV+NQBa5Vi+bhWexjRTjfZazXxwEJWhXtk/rOsCUq9Vxq8XtZJVGhfjjhDZDryq+Gf8N1CpZ/rnNZG/NyNfGx7gUm2VsoLln0A68c80E9Wecq4xSBnRJsSlAh04S39HH6KfIVCcXtlD+FXk94gZHk5QibGEDIxlgpTEpQ2OPdRy2oXEQwnDK2uT41wiDY2QrD6FYEqLzwewWqJg73T4OhCSIrimtObv2wNiXS6Y3ImwZX9sGcKnFwNdgt/VDqVkir8wp5CPG667yjCZ6eKM9jaX95+1bCAebUvZZjamB7ivyw/JYGWc+J5fWUCX25J5NtrleVjdWxbcJjjlSdqNPSbvIM1hy+xeO95+v+ViX7RqhHTk8uywXBuI+hdec78HjG4U8jHkDoJdQft5ificuBPfhWt4zQJxLoVwKN6X7SZEKxrrnnSeXtRCi4vyzMrvKi/Mg+11pdmeXjWRDZXn1UyE4478qPRaJnexo2uJTKIjWwYS0Diaa47vXjT+Blar6As+R4qKir/TVTRqvJ4qPOOjASJpum/Gb6mjnMXtacnyKjETUKLFeF6rU9kGm9j3R72HdjLqfj7N2b6c380cZsmkbR5PJv3H8Zhv1sQlAnUU6xWR3ZqQmXPrQERo5i6aKWMdKzq7IJep2OkrSffWJP7c/37OawbnTXrQOW/y60GOddPsFQ7kLf083DVWNjkCKW5+SuWOqtLd1rl4iQq0cauq3c4FaXBsrPKPuJi1FE0OTuB+GtSBMr0otAOSl+5R40QUPumQ8wlYp0ufG3tSn3zt8yz1cZXkyzQbnJphzRlK5B0jHbB0fKu7TfcKbWqLC/tDuHM2TOwe0rK+z0KvjgWzNYb7jJ7er+pIhafIvK/4cq+B3q/iQfsRCcqNfmyhY5Gyx5tKNfwxV8Ty6C8B3mtXn7532uTzbQEqw+FPdh2dh8TKCo5hG2TYMfPcnGs6xvsN+eREzefpGP2NXJLPL0jv+cdwxx525KnCp6VuynO/BkQadHx4+nctN5SnMIryjFwdyChMRtYZvyQpaaPWGz4gKCk0ww6VOChf9KIY8H43tgrl3dTklVd3KgVnEF66NUjcGGb7NH+gmUQuQuVeejvoPIYEeUTkeewXT/LltMRbDkTiS1H2MPnTMS6EetIrCuxzsS6k+tQJUPU9GCVx4NIf+v8m0yPcjm2hEmGb2R045k59XmnqkuKg2qR4mW4kjgA173jeFs/lxe3FWVCA7hX4CP+4kG63VgiW+gIakUuYNf6o2zP1YWXS9nlx99EbzRRqVZLVm72oilb6B0xjiVL4mnZsj3/tHelzfxEvrN3woyBwYYZqRGtBh9m6ypSeYIRBjlCSESdkw3JtUlR4J5LRkBrh9RmudXJkRtO4qww/4SdBSeSpGypmOve9aZNCuhYcRqSrHYikxz4umhvr4XRPobDuiUe577paBIiCHP40cP6MWcdQdTQHGS6cWTar0mKhgOzGOf2L01dy7DKXBqd08GA6IUUir1FqO6ZykpnNZa6t6VliJZGATG37b9ZwcVEA5POBkiRWszDzMrax+BsHog6BVEXHug9k5Ln38QE2On+t2SJ7G8jo80vmScD0Vx2cWeHOT9OjRFPZwze2iQ4ZYLAUkqqZEauwDe3M3GdHqrDcM5CGPuJrB1grmcvvr9WQS7XzGekUYG7Rd7pq9HUPzKS2rpD2NGiK9YUY3DFDI3PPj6aX0ZPE20atBoHNbRHGKNfR0vtNlw0qeaHHpok/jB+RS/L4If6SZ8dDWbnuRg+djmJ1anjxQ4t8brZcisdInbNRfhp/22vw2FdSX5vV+qhvoPKY8aWCOPKSVHxQtJvJOLCjiFNCPR8+A4Q/0UiE630mLgZV5I44vKCcudHYaoL/D1QRavK40NvUoyZ5vXHeGg+Y40TKGM7wxc7nmXWMVdmtjbJVKmg8k05G3aIgldX8ZX2J17e9gm/11RqZ9Lk3Cbcz26QIaz5ttqccgbxsn4JlbXHCb02mmFXniVv4TK8VCj1PbR6HQ1r12PmRk+6sYKW135hy9I4arZ4VrblaTYniYmJwnVYw2DDdFj7pdL/suFHj9epUSVnIoTG9eMwtT0IF2rhTNv085Seix5GDVWTM+F+SnbYFC1rXO6jN2vnYloGrdXICN34fXY+qi5Ea/KhXBiHPWLiEhOJ2TWPYPt1LjsVwXreEcg3hh/ppN90z9drEq7ThrW0Ma5NuU+UBfxhb04QkXTRraOpZjv143fx7r4BvOioRQlPM1MrnSKXS9a4i399MliJqorSgKonbmtRQ/T5B3pP9/TOrsVbwKG5imHN9ol8I+67c1w3NdltuEwXaDQkfVEqtrN7tbq5H2Gr8mjYPxvmvyQnPf81NeHda8/Iu0sHGpnROg1H7/jrOJYOpbbugiwp0JRqh3vutNPoz8UbeP9wASVbQHg3EMdL+hVy/8mvvZbmayxOPV6aRKYZR3EmvBeFcvtl+icNPZKXKef8+cY4W97WFqqDl2/yvpMO83edo134NnmOnuRowz+v18Tf4yFbSqmoqPznUdODVR4vOgN0+g3qK1HL5/XLZbpwTEw0dabHs/uqMggv2HQAYQal9nRg0k+MOhqQ9vslxUgDGMEUW1M22kvxnmEulx0+7LIXlbPMw/R/4HdmAVX/LcbeqNSBnF6noUOdiox3dJS3a16dwckFXxFotLKrlwtVgo1MtLfhC2tP5QXrRxO7+GOlIE9F5VZEm5kZvRTBGlACmo1MEay38schGzsuK6K1StD9OS2KyF1hX0URLTyVnBq6W0TtkotDH9H26LCYWb3nGDHbphJsv0S404fu5iF4O2PZbXrlvgRrelx0+KN32DjqCGa0tbO8z6ix00P3r1w+Fmui1dasa5Wz4boSCS3sbpFGbRL35GNM5HklBTeTuBsUGey48/8Q0dN2PyklEiVa4fQrKqNTSU4DV50+nCFYSfsUonbrD7Lu76FSe1WH4cdPYhT8/SrMe1EK1kXahvSL7isnQYv6GVjUPg3BdvUI0fPeoigXuOL0ZXOBl9MVrOPP5KLehlJsu+GODgfddavZYBoo04nTE6wCo8bGHkcRWSOrPbMu0z9rWbi3FKz1dPtpp1X2d11ppaVcery3zoJm759oNU5WOyox9tVuhAbfuyetioqKihppVXn8iFy/hoMhqCzMfYF6HGC2Zhg9LUN4fpmOfX3cZFQ2uPVHRM9/hwra05y9NI9/vNvSLo/SMiIFkwd2j2B0cWGU054m1qEMBorrlF6ZQrzm0kTTWbee0o5zvLz9LQaUcqVn/gj5uFGnoXfdkgxb/zwfaadQNGojl/+OIE+bT5nTxoPRO3T8uLsNdnR8YpiK584fWHfmKvVfn6RGXFVS2fyDdAXFPRCafX5XjenmMDtvrDYTkZBa8/hmhfs/HDcsoONMpJV8iUdg4Y/JbSY0UKhetm+HcbExbDl8kmqJG2ks+ipq4IIjkP/Z2jHdOIJgbeRDf0ao7oK83EmZQsGEXkniUIwL18xZd/py1ztk650zCUaZKpzP1apEWsX/Jszcwg8p7YIyQWByF5s05xDEexdpJC/i32o5O4ETN5RtIbennm1dDLD0fYg4oQhYGSm9R0RVJWcitp3p3SHqvNzPf3W24YuErjicWuqHmPijueFut+gTK7Bu/hFv7Bx15Od/rq8zoXDa+9WiKz6MOhYkd/tK2uOMc/2N/Pb7yw6IdqS2Wop0yU9mPYiFWBYO/6LvuizFEX2OA0uk+/yOC5LQXDnAGNNmHGio2Psr/PKp7W1UVFTuDzXSqpJzKNUaXlgBHkGU1F7gV+PXWBI+sReMAADPFElEQVTj+GZncg2OV15MTT7G5tTSXr+ZVQcvcib+jhlqjRZdaFtina5U0J7CS9SH3UIebRQ6jROzUy9PtouNQ1h15ArvH0rtbyfabrxZJ5j+jg9ky5s88UeImD9Imt28X9XAzt7uXAppzxBrP/n8+hGzWPNtH7WIXkXBZoFt45XlSs/dJliF0ViDmYn0WBAvBasQNHm9DCzt7Eb5DHoz3rWr+Gp4QbeU6brPFMEqorgVekKBmxb6WUtifCxr9xzh0LpZeOz+iaZJK/DWJHDaEcQ4a3sSnAbGGn/JEsGaLsGV8CpYme75lAmmrOT7sudSXIwbbSzJNbNOHkvwL6o84bziKp4ZivoqkwcijTvBmrHBhl6XeirW3MxASUj+nblKq6m9TypHl8DPjaVgjTTkprPlU0aYu+NAy0sVXZnyjOl2weqw49w6HjZ/hwE7S+zVeFs/hJ+qpb1fiUyh1/YVoIg2jInGb5ln/Oy+Batgnr02FbWnZJS/TMnM15Qa4i7yl/ELWRsrJ51rvZnuc3desbMnLInhhj+UOyr2wa9YtUx/poqKytOLKlpVchbBFeC5BTK6IE6mPxnGMX53HHEWZdDnkrcssSW7yuURht94aasvyQ+l4uLDmQKK229v/Wr22e9OqTJpbNK1UKRF/WYaS5ErS+iyJdVB0ddoZ1wdeM4+VKZm+ZsvEDn/XYg8S6CblolNTQx7oR1jjK/K5u4NYxawZmwPVbiqwLEliuBw9YOCdeUaibU4aPt3Es/MjudslFVGRURPzm8bu7Gphyul/TPRhN0ST4vzY2WkX0Q3rAGlofLz4J068ZIVJNg0fLTbk0VrN2Da8RMNYv4hlNPYnRo22kMZY+2IHisDDX9TQpcJx9sHQZgSFW0qo8jZEUeu4JPAN2UvSOFqcWiot6G0dF4lIDkF+fzWTKddF/TUpLzkVFTGr9Xf+aOEG3TiDWVZ9PFVo6xPDA6Hg8j4JCKWfolzRk9pULPVWYaGscPZ5Sguo63fNHJjSPVbzNMEiVFYVnyK5thieXOstTM/ubzEwtpn0zQeu5Jk4O3tHnytn8gK4/s01+7I9HctrL0ir1fp6qB3yVwk/8yFS0zRj8RXE0eCT3FoMESZbEmHjzdZ6aVfRaj2HBjc0Tb5JNPfV0Ulp+EVdxrC9iqXBzTtU7l/VNGqkvMQ6UW95uHQGWmo28co/USazU6UgwGBb7XuRHoUk5GeCdrRdNyY7y6n8HKF8zHZ0VIuF9WGYXbcLQpEjZwYgAte1i/mm6RP+WprausIUds2pV4s/fiE4468+NpvEPvP+yRcPiYf12u1vNOtBd+6vSmjvw3jl7FxbFewZ405jMoTyomVynXhBqDVse6CXfZg3R9ukWJVRNUGVXfl8PPudCyWyRTXiJOw8E08wzbKOshPrc9xrkBn0Kdh4vIQ/HXGnanrDvBpzGe01myS9Wfb7SX41tqBKdZGVNMc5T3DPAposz7qeRci4lmsWUras1Gr7OxZXbnbKTiSEaUvSaGZaNdQbV1pjulLgM4ICdfh2tFMvZ9RmGolf+cT9xCtnsZU1RqkjYaVnyo3REqy6QH6U6s8UsKiknh7ziFKD1tN4cGLWfVlF/y3jZJR9qm2JvQyv0+k05PiAQY29XSn0537/aXdJM1/HWP4XhKcJl4yv83pwCYsqnWSNL3ZHHYWbT/MMuMHdNWvS3HJzwzXHe7U0R6Sy4b8Sv/g+yUx/AR5T02XbeLWO8rj1nJkhtvp3qt2TBGH+Vg/TblDOO+LHU1tw6TyhGI2+sp9tfru92FSfeXyYzVVuP5XRevZs2f55ZdfiImJueuxvXuVXl8qTzH5q6HtNk2mUXXSbaRP0jS6LrYoj2n1+LYYQpQ+gCLay4ywf0v3bXf3mctXuibb7CVx15g5JcxN0kCkCgtEc3NhWPGB+Ts2b90EdiUl2dPgYGG9cD53fZ+d9uJ4ahKwLR/KhdOHla+i1fJu16aM8xgoRUSd+JXsHtsOrLenJas8RVzapVznCuWDDRb6LInHbnfICEuvMi4cf8GN1yqkH5FIl7irsPQDmQ4saki7WYayQNeEop7J+0UW8c1OM03OjeFl/SLZR/mgPYSF1mpU0JzkbcN8njeuxqh9hC7For3Uha0pN+v4xclrIfMy07f5fuidP4JPSoVJQWx1aGi2NZSTLmWVBx/AqEanVcTo2eiMRetntfRyMsNDOLkavlAciz2DofPvD/ZDVB4JR6/EUXnkWmp+uZr5O8+SkJjI54Y/6KJfLycyP7C8yMe2fuT2cuWPVu6s6OQqHfFTEA70oh/xqk9wsUZxzJGPdpbhlClSgB/Ln037Q2PCuLF1Gi8658r9Uzh1PwjbHaXl+W+fozBNC9z/5Jk5/ASGI/OlidNiezVOVhoChownzQYtvSLTl0WGk6NEKyjX7d79hVWeLISDfdUXsVR6gbyBfoTk8sbFcP8SwzUhjFDNGXyiDinO+zmcRLdgmpi/ZmW9OfDSOuj4s+J/cLOs4x6IdSPWkVhXYp2JdfdY2tU9YTwW0Tpv3jwmTJjASy+9RJUqVe56fMeOHfz7r+ISqfIUU7w52vY/ycVX9Avh8n4Gb0geoLsH4NP6c+Jwk7Wr/RN/5bMjeW57eePc8WzI1UPWpZbWXmCtLXnwmQZ+zhjm2mrL5VrmDVzf+pdsNyAQqVlTa1xmY95+bHOUlCnFPus/4fixgymvf7tjQ750G4TZaaBSwkYOfdNKnUV+GhHu1ckRuU5b8jPzcJIUVyaDjvkd3BhR23i36cr9YDMr/YHtZo44C9LKMpLdzuL8Uz3rTu4Ou5PfN55kYNz/pFnZGUduwuy+lNGdo41h+6MVqndyYRskKOmywcIkKZkl4T5Z/lH9Qq7zS8WzMkgq/rvPbzSW9zuFK7kQGZnALdlB+GBExpGw4r46jvc1sr/g93jEncXhFgB9F4F/kYf4JSrZybmIBFp+v4mImHgloK7RMtp7Hr31q+QEFXXe5qv+7Tn3sqcsAWiY/45sH3McztXDZa/im2733R3D+aV2HG8WEcZqdyAik+c24dw9BT/rZW44PfjY8hwFMnAHzohAjWJiuFVX5b77HtuiLuE8slBGdufZ6nCi3Pu8UD7jVkr/257AV46vCdJEEuNZFG3HiUpUVgzQ1TZM/60Whq3GYmz7Lavebci6d+rg6XKfk7NRF2ixpjWLTUNour6zbIMovSButh3LoYQRwIqovMy+kotD1tvHn/dCrBuxjsS6EutMrDu5DlVynmgVonTUqFHMmjWL/v373/W4uG/FihWP46up5DQq9IBKfeTiWMMEVhwKZ/y+5EGrd348nhmGBT1NdbsICVvCjAu+t738vTKJ/KDrJZfr6A6x3V4szY8RJ+122i28Zn6Na04vAmyXse34Da7sT3nOWyUiiSvVnS320nhqkgje8hmHj6ZGXD/uXItP3IbIfnqhiTs5OrYFjsTo7FozKjmRy/tk4upVTQC7ojzkOLNcbiP7+rhSKRNGS3ex42e4cYoYPOhnfodopzufl75EAbdUAfdQiL6RWzbxvH2OjL78ay9PCOEE67LRWCmznFyRUlcqas4FW25kT+ps01wxbKt3GH+TnU3OMkQ4PdEkRStOsJmguJ/yn+9Lbt2VEdrjS9Fe3itTvbW95mROsIo0y7hr6kTZI6TF95tx2G3SBff5ukX5t/Zhuprnysc0td5AX7Rh+i+OvoRz8TtownaR6DTypuU1fjM9y5b6xwlxT2OftiUpvX3PbpACeb69Nk2TvuJ1/YIH+u4Wh1Z6RgiMudM+J95JfFw0sXvn46Kx8K+9AsdC3+KtKhlHWI9cjqb8wZFU0p4kFne8+s5S3LDVNkwqt5IQgd6eyEDLq6mRy9e2g0/W+jRkJQX93WRGzuztZxg0aw/vzxHnfpX/dE1r586dGTRoUJqPDR48WKYPq6jQZBhOnxBCtFeZahrFT1uvM+1wct1orlJQ+62UHq+Xju2QLQBu5a2a/ixw1JKzw6LP6wVH2rN3eq2Drwy/0CHpU9bbyyp1QsJUR0R5kmkclIS2XCc220tLx8R8Wz/lWHLEVQjXLztX4iO3T2R0t6R5P8fGNseRkIMG/irZy3Wl3nm/TTnZti3uwoL2LrikWZh2n1zcAceXycVXLG/K2d0GgXEylTXLOLGCJvaNssZ7iOV5ympO3Xf05ZEReRaEqBNi0ENJvz8Sm7W1vLeSy8XGjnqHqBuYyG6HYsh07uL9O7MKWhVSROv1BBvRSfeoO4xKfu9ab0Bwxcx9WZFmqaZbPjKWHbpKYpJZzqG80ag4XbyOUHj3SOVBYYomarDT48p+nAveQBMbxkVnAJ3Mn5EYUI61dY7iklZ2oDDlEn2YI05iceoZZH2JtyyvMcY4gaAHdOs+5Cwoz2/iPNalyL2rw09GOriy8x9punTAUZB/Cw9icI2M971f1p/Addk7NNTtlcLc2vF3NXPgv4zYGeKv44i9yvErsRwPj0vxIblfTjrzEuUTqhhy5mDBKqga4sOcAbX5umtFulRLu39yRoh1I9aRWFdincnMvkfUY/1J5rEMS06fPn3P53h7exMZqQ72VUSOnR+a3vNxuCs94X41juHzDZEsOq0IV2PRBsRUeEkuv2uYw/aDR1hzLbVZuZveSckKdbnk9KeQNpwtjlBsjrQ3fQ+tmVmmETxveZcfbclN0k+vuU24Vg+w4la+A1sdpfDSJJJvy6ecOLo/Rbj+r3MZvvL5hCinO6VsRzg9trFyUFL57xOhRC/OOPPgatTxfaM7WjJllqQYnJu/k4u/2J5hs6MM1fzimVz53sfQ++bKASkGxfnydcsb/OloShvzF+RITiyX9eKNAxUvBNFbNZPjokwhhPvvlc5wFSWDY+/ZzKViPheqk6miInt03N57GLSJeiiBSA3OLCLN8s50SzX6mm1M3HhOXru6mGjldojSa/srkwbCLTy0Y/ovPL0G5/KP0Tgs7HIUo13S51Qu4MnPFc+k/fwbp2Hnr5AYSZjDT7bMmWVrwBjDTzTUHXjg719Oq3zeXJcOssVbRiwI8+TKnsUU0YQR5vRjQ4mhjGjgne7zr8Q7GDZtOc+e/oCC2nAuOgM53HIOfuWapz5J3Tb/e4jj19dF0I4tRrv/raDZt+uIiM+iTKAcLFy7VAqmWsHMl6mIdSPWkVhXYp2JdZdyDlDJWaJV1LGKSOq90CQ7L6qoiFQ5rRCuBneqaY/xg+EH3lwZJ3u/CbzKtyWqZA+5/Jl+ClP2RrIzMnUAV9xXw4l8Shucrvr1fGpTUo7TQvSanG38nNHWbnxr7ZQqXEXbi2Qq+NsxlOvEBnsZafSUb+tnnDq8K0W4ftG+DN8GDpepxkXtp7jwbSMckZmL0qg8eVw/dzhFtH5U/eHrU25smIQmMZITjrx8betGvYA4ZlVVhHGWIGZ3k1tsiMNtBe1JKV6vaAJ5x6xMBOU4zm+iS/AN+T3FGWJrVPa765pclc+wixTcTCAcxov7K+Gzv0/cS7QmJn/YA/yetNIt1ehrtrHvvFJf3TfXSUqveRHsFshXDeq8k+IYfRtiY90/CzaMRYODRfbq9DAP4dmiZj4vdSntDwk/mFLvusVeitaWkdI0SQjWLvqND/zdRa26KAEQPWD7hmY8qTbtgj9nDu+UpTXxThNnqwzl1Vq5040cfbDezKIZE/jU/j2uGgs79JXwGrCKytXr3/5kddtUUVF5UkSrSAleuXIlLVq0IDY2Nt3nRUQ8gnYKKk8OQWXQ9p6HQ2uQNazfGX6gx4JYzkQrM8U+1XoSWaC5bM/xveEHhu/Qcjw2VTg0KOrHZlMdufy2YR6jzZ3T/ahKulOMM3zP/2yd+Maa/Lwza+H8lpTnVPa3YSjXkTX28vIEnX/7cHZsS3UYHdaqBN/l/kLOToc4LhA1rg6Oc6nCV+UJJb0owdbxBFxeKxePOPJTLuDBJ93EAHD84s34ha2VfYAHWV+mfi4zU7Iywnoz9fgW2um2pIy55zruGGjmFC7uwFebkJK+/O81r2z/yLq+StaPizOJ8zGZC+32L6uYkUTE2+5R25qcGhar9M58aNKKvqo8NHP3XMZpt/CCdgkfXB+cKlgbDE67T6lwv942HvZMkTcn2lrJjIYPSl3nnaLp/NfhB3EeWSQX/7bXoo91MFFON/40fvFQgvWaw0tmGwln4xmGDpT1Tp4oSYMl4d5sOnqRgYb58nZ81depVSbt+lexT1SalkTEsc28qF8i79tZ8GWqfrQKr6CCd79A3TZVVFQegMdWtbRq1Sq2bdtGwYIFefXVV+9qcyNa4pw6lYURBZX/BgVqoO06BYdGT2vdVsbpv6PlnBgiEh1yhtu33ivE+JWT9aa/GUczYKsXFxNTBxK1qlbjBAUI0MTQybCJny23pCzdQXv9Vj7Q/ck4W0fZ6D2l7cWZ9Sm1BzUCLLiWa89ie3XZ97XSkTGsW7M05T0+f6YQ44O/4JAjBD+isf3eWplxV3lyuTNKYI6Df16DZR/Km3/YmrHHWYy28xNYeCrzPXuPR9qpPjmC9tcmyNu/O56hTQk3JqWXQvgwiNYqyQj37Brm71NuN9TuJqdy7dKplLTg+v7pT3xmCQ4buW8o4n6JvTo3kjJXd9S5mBajXicnA95ck0F7IpFaKtjxK9iyoI2RanaTLZNV05esZLZxOJ8Yp6ERgrRww/QFq3Cb3vit9EYQk0+fWJ9jpPVZRpe9JF2q0+TqYSlYxfYyzdaYt62vEuC8wTbTa9TRKZkcD0K8w0SgVkmr/8z2HJ9WSr8tm8hSGr/PxrcGxb0/oWhrcoWmbSwl/CXqzYgnLjGJwfq/5H2xlV+nSt/Rsk91mqjbpoqKypMkWn18fKQwbdSokWx/U7lyZfz9/WnevLm8FClShI8++uhxfT2VnEzJlmi7/4ldo6elbjvfasbReGYsCVaHHDh4Nf+YGI8iUpj+rh/Fs5tzY7sZHNEZCanWhjCnv+zxWkF3hi8s3dL9qFeNi5loGMv3tvZ8Ze2u3Hl+M5xadYtwNVOmWhNm2BvJtKv6539kzbI5Ke/xebP8TMr7BSvslTFiVezcV38uwmnZu55UsodbogQzFyzi6tgasGea0jm0Uh+KNn8VjUaHBievr0yg/JQEXv/XfF8OsiLC2uGfJN52TCGP5gZXNLl4tnap9Ae4D4MQ24lKBPFLSzfesb4m23Y4nU4+0/3GH6ax5FSiLx6Rg3rRBrVuQDaLVuEYbE3goiOApY5qmDPZ+UeUC7xXVUnDPBtpZeOldN6gUH1w9YXYMDg0Lwu+uEqmuFedZUIkB+eN4i/LW1TRHsemc4HqA5SU4DQFqw3n+tGytERENt+yvsZUR3N+qXSWrnnT8eu4vA/H4QVy2/7L1pCh1uf4UPcXW1zfIlD74Nu5zaHBXWuWy19bu9KofFGKuCu37+RcvIE3d/jyq3EsLhorCbkr41bz7i4Ps4/bqDglgSHrE+S5sKfuX3lOFTXZnk0/eODvqqKiopIej9UfUpgtzZ49W7a3EeJVDJZE2rC43rlzJxUqVHicX08lJ1OiBboe07FpDLTQ7eAzx480mpmguNUZ3fBq+RmxpiDZw26CdjQvbk+twzG6euJdsSOxTleq6o5TVnuOd813n5Rv0kK/izWmd/jD1oSh1r7KnZd24Ty6SIm4ASEedprXrsFvjlbydsPwP1j19x8pwnZcMx9+DviA8bY2yus3jIH5L2e676NKDiA5SvD3zN/ouKsPuSwXZAr44SqfQ9mu1MmnZ203N2nEJAaf0Yk2Fp0w025+PHVnpJ+OJ3hrrY2y1gP01K+Rt4PKNcHFdJ+97h4iyjrR3kZ+V1dnAmtNb9PXsIqcTFHbCYK5TinP9KNFWYLdChe3y8XJ9mbY0SHmxjLLS+UMuJuU7aH34kSGbLRwNOKOfV8In1LJx4etSoRL5RGSUZ2lNRHzzOcoc/oXmVGznkroO4yHkq3SrmG1JRG17As05zZhcep4zTqQLYZqbK9/SLZTSouEM9tBtD3SwJ+2xoyydmWt6V1eNijptg8TYb35FSdZW+FXtCqNAtMXwM9uz8/PhjHk0kSR4BGCW6MPbouYisnhKtMSGLQmgchEm3zvwm5JfOqutPuh4WBwyf6UfRUVlaePHNHUoEmTJlKs3rhxQ4oOIWIrVsyk5b/K00fxZuh7/IUDLe11m3nHPJ5nFycPYl198Ww1gmitD6W05xmcOJYxh1INTty9/TGVaS9nwNvqtxKqO8+b5pfT/ahC2qvsMb3CRntp3rG8Il+nuXoI895Z0s1U4Gty0LVOOX5wdpG3m0TPYdWs71OE6czWLszx6sO7llewOnWKycbCgWrE9Ukk/BBtTn2CQWNnqb0qz5hHscEemvJwiLeWQ8+5Mqq+G+Vzp5qdXIrNeJJiwwULQ/VTlRui7YlPgez7DREn5VWkw11GWAUrTR/IbT0nY3Uq37WBbh+9srLtz52ICSfR8iohAovWlZn2hvKuPG4PVqv8aU2TfL3T6eDPQ0m0mBNP4Z/jGLvzFofNkNrK9fUTWfQjVO6b9OosHQ5ss1/EdHkn0U43XrO8Sd42n4J7YJpvk2SxsH/25/hc20GS00B/y7toAkvIvr+BpjT2f6cTy4k1uJ3/V978ydqG+bYa7Da9Rog2c8Zfd7LMVpEYjZvMAJptq8fZPC3oVzD9febzI7kY7fwfodpzJGndcGv+6V3ro/lcM9fjbXJbzuWh5/smbvxbZCY6Syz4F4VKyRO7KipPISuPXmP27jB2nIt63F/lP0mOEK0qKg9M8WZoO/8qhWtX/TpaX53Al9uS0548g/BuO4rr+FJCe5EOV39k4fnUTd4YEIKmZGu5/IJ+Ofm0kXxj6ZDuR7lobaxxeZ8kp46+lveJcbpiij1P3M4/ISlaPsfD4OSlekUYp+0ja5iaJK1g28xRMmIj0gSXdzLxr6kRA62vyZ6Y7Jmq1EKq/bmeHMR/tWQQOhystFfmVetAkgze9C9ze/2W+L+7l9Rjc6a+bHjtjHsbNnFsVAaMmFJrHLMDEVFKFq3/2ssnf0EH+bQ53/xuc/LkQC3tQboFR2Rvz91rR2Ta92DTh8TgjperjiK+D3ba7FpCz4h6bhT2NchtQyAmab/bmUivJWYlS0RzcxtSnfMfOenUWTpXfIz++CLMTj39LO9Rv14jivilXau57IyVxX/+j3KWfSQ4TfS1DaZbeV8mVDibdt9jpwP7sSUYw5SWal9Ye2Jzapjj8oXsG/6giE3pBfPbxOBFHk2kdAy+mK81I0PTcSoWacFxOipfnkEt3WESMOHSciR45LrtOesu2LkQbZXHspcrurL9WTfaeJ5QWlEJmgwHXVrNZlX+84gJn/I9sZbpjr+PD7l9PXExZHysFMJOCDwh9J5kCvqnTuz8b+UxBs3aQ+fxmzIUrmLdiHUk1pVYZ2LdyXWo8mhE6y+//JJVb6WikjnKdETbcRJ2NDyr/5e8Byew43KyAY53PjzbjiLMGSDrbcqd+oV94akmJ7qg0jgKN5HL7xtmcRU/ltiqZPhxP5l+pIV2G13Mn3DZ6YeH5RrxQrjGhcvHjVoYWDeYrw0vy9Sw6pYtHJz5qUwxEy0w1nd3YZ2htnSElWyfCKuHqf/6k8KBOXBuE06dkU9tfeWEyfgmLilC5CZChLy22syhq8r21qWUC71KZ3BSslsYqJkhF/d4NwGDW/b2kxWup8AiRw157UUcOR3RX3mSvaVcrqs7JJ3Cswox0J90NpC+uwvTemMI4YcUJ/Bxtg7MuaG4pnYv+XB9d3uX1vNvV1dO9/dgVVd3gr0MMr1y4wUztWYkEZ+Se+zMuL5S5ZHg2DoBzdYf5fJ71leoWaminHxIi/H7rBz7dwqdtOtlJs4fHi8yrZGFlrmj03lzO87DC9GFH5DPFxk8rs5E3jQueLjv7IB6lm+waYxyIldMnoo05rdLKG160sTpZPeuzdIjQohzR4OPlajpHXy1Q8kK8HDR8VF1AyTcAFG3KyjdXjr8q9vsU4reBB3GY+g8kY0fNmbbB/XwdEm/tEUIOiHshMATQi8tAfgk9Wsd3VmZ/H2raQm6VCskpx3PRqTfd1WsG7GOxLoS60ysO7kOVR6NaH355fRTK2/lww8/ZMyYMfyXOH36NFu2bJHpzSqPiXJdsLb6QZ6g++hXcmjZRKITlVQsk29eNM+M4pwzFyHaq/gfmcL+8FQTCm3+Kljy1ZLLIw2/sdJRhVOOoAw/rpdhjXRW7Jo0hKOO/LjbY0gUwvWWdhWDavrwufEt2d+ujHU/h2Z/BjYznkYt67u5sljXkI+tzytPFg6T+2dnz7pRyTLORSRwccFwuTzO2oFLzgAZFftqh4Xv91iJTHIw9bCN5nMTKfxLPItPKttZyQAjY+pnLHjiz+wkn+Y64U4fonNXy95/TZiJJXPYESKvQzTKpEtOZrytFducoXKf8hYiOyFrIq0WB1RcW4aRx/Kw9poHdZLWkVsTyXlHID/Z2iqmT1ot71ZOxw31ASjqq2NjNxP1Q5S04SuxNn5cm9zSSMy4p1dfqZL9mGNxLPkgxRF8tLUrFGnEu1XSHoQLo7Wd2zYyUK+0h7ka0opXq3iiT2+EJUpGjvyD5voRObH5uuVN3EjgHaPy+odhgPVNzLjwpV4JJGjyVqZQntsjpneyfvd+OrBGnj83Fn4bj5C0y7MOX1dEa+fiBriwHRa+CfHXwK8INPxYGh2q26zK/SAEnRB2QuAJoScQwk8IwCeR0Dye8rppyUCqFXwyf8NTJVqFedL9MGrUKAoVKkTVqlVZs0YxG3mSOX78OFu3biU8PJz333+f6Oh0ZlVVsh2Xqr04Um2kXO6rXco/s37GZleEa57cQUQ1GMUpRx4pDIRw3X05VbgaC9clOrCKjNyMNUxkoq01SY6MUzVK6y6wwPQJ/c0D2eEoLnu1xu6aCfGK06sIvA2rYeBT43vS9CnUeoi9s0bIVGF/Vy3rurkyW9uCH2zt5PPt8wfAuVQxoZKzSLDY6DpuCflsioHRb5bG0iFYXI5dtzJ2eyIV/ohj6IYEeVsoEXFYFOmgC9rdO0I37ZiyrQoh3CAwY8Omh0IMMpOzAkRU5gpCeEMj7e1tx3IisbhhQ881p7dyhy1rjJh+PBNEtFU4J4O30U4Pw3p5/56gznxQ25uprdw52NcNl3RVyIMhhPDkFiYaFVJEeJ+YicoDZTqpPVYfF0cX4/yhGtrtE9Di5FdbC04W6Mr3je7ehy02B41nJ7LrRBijjZPkfeY81QgulFrfnp5g5fpxGdV82foOUU5XRhiVPq4Pw3JbJdY4KjHJ+A15Raq/qx+aQkpv8vQ4eeo49eKUNm3fGV+kcb30+zM7HU5cMPNqwgT4dzgkRUFgKeg1B7yD1W32aUYcPC3xOJJiuRaTxLXY5JKHeyAEnhB6twq/pwGxbsQ6EutKrDOZoaCWid2TTJ2Bu3XrRrFixRgwYADz5s0jJibVBU+TloNeOnTq1IkdO3Ywc+ZM+T5PKqKP7JEjR+jZsyft27encePGHD16NNPvYzab5bq89aLyYIS2epW1JYbK5T4sYs7M31IOBOUL5iKu0UhOOoLJq4kg6Nhk9lxOHvRqNHiXasw57+pSuH5p+JUxtuTerBngq41ntekDhlr6sM9RGE9NItd3zsESH5UiXMfUsvOlaaCscapg3cOOWaNkFCXIXcvWnq5M0HZnub0KOqcV85QucDXz25BK9u9HnSbtpIxN6ZN4QZuPJiUCGFTdlR6lXcjtqZfyVRwGxdYW4K6nVxkXdvT2kOmgxnuIHXECW35ZqaXLp4vCJTtLW8IPpiwuc1SRx26xi/TVryCnU1QbJq8TRc2vINm9+2HZH+0qr32MDvZVWU0IYbK+tF3jBrxQxkDdfDrc7lGf9TB8UFnHF/pfCdJEkuRdGJqPTLO+8lHw1J6PRG/cOS/AjJ5oYsM458hFL/OHHCn6EpOa3V2LLlx0a05P4saNCKYav8RfE4vTPRemovXS/wyHjdh9NwWrQQrWdfay/GZ8+PZSsQ4XXrW+yRjjRCpqTyqnvTKdQZ9+Hb094iwhF/6RyxPs7Xixc7J7dRok2Rzk115lnvEzcl8SxwoN1HwdXloLfoXV3qtPO9YEGBmMdlQ+6o1cTNUvVhERf4vJ3E2iLkDYXnyiDkkH+KcVsW7EOhLrSqwzse7kOlTJkEydhUUbGiHUJk2aRJcuXfD19aV48eJSxArOnTuXmbeT/VmFU/C//yqueU8a4mReoECqu2eePHmwWCwcOHBARl7vly+//FK2/7l5yZ8/fzZ946eDBj3eY17we3K5u/Uf/p59i3ANCSSpyUiOO/ISrLlBnmOTORaeXDem0RBSvgG7XGtJt8XBhplMsCr1cxlh1NpZYvyYbyztOebIRwBRXNsxl4jY1APQyJowyvi6HKhUtWxj8+yx0oTD10XLuu7uDGIguxzFMNnjSPy9PcRczq7V858lO/ejcf+e4cjFCDkYFOQvXJJvGhh5rYKBL+sa2dbTjTP93Znexp2Dz3uws5cbI2obyeV+f4fYb3fbiXAo7tYBmmzM1nA6IFwR3oKp9sby2p14OQGT0ymUnMKchDG1JU0WcDZBEcFBLla4sl+5M6SWHIjHWRyyVZFI+b6fyEGmcTopeXUxrfXbpKv4TwFD7nawfYQ8lecjcX7451U4OBcrOn60taWpeTRFylRLM61fRFhrTU/CmhDN78bRymSKyRPNzQh5GljsDvZtXopnzHHFVdj6DkfseVli/Ag3barPwoPSwfIp7xnm0la3Rf4cTYUe4OaX/gviwkk6+I90QP/HXpPQpn3xEIYM6RB2Yi8LjB9TWnsOh8kb+vwDzb8AQ8bmcioqtwnWH6vBpPo0Xd+ZVaZBuCYoE5EqKlkuWnfv3s1XX30lI4oiHVhcTp48KUWsWC5cuHC6kdiMhKt4zyeRoKAgBg8eTN++fenYsaMU8s2aNaN+/fpUrlw5pefsvRDvIdKKb14uXLjwSL7/f5mOLw3lN5/X5XL7xPks/vNbLBZlgFsmfwDWJiOlwBSRDe8j0wi7kdy3TqOhctW6rNTVlcK1v34pX1m6yDTKjBAR1cku3zDbWkc6NebVXOPSzkUciUrdxYbXMvCVYYCsYaqVtIGN//wsB0siVXhFN29esb8v05ddEy8T+3tnMOd8Y5ycRHbuR+PXnZLXpY3J7WBEDVcaqZ41g3WyZjkzRCc5+HGPmXCnLza0aB3WLKvVvAvxvqI1hSijtpdis0Mxj6ipPURO55wjkF4WUWPoJJBkYZ9FbosRFuV96phOQtge5c6iikFby/lm6ZgqUr5nHc9C0SrqVY8uhgWvwY6f5V3jbB3ZbinE4+SpPB8dnAsHZstJgxct7zHa2p1+lb0ZVivttP7W/5jRJ0Yw3TiCCtrTSi1n2W7gkpy2fgeHY12YtO4k5e2HZD12P8u7NNbsZJvrQErqLj701x9gfo33DPMYoF8ob2tKPAM+Sq16msSEEbdrJu4kss1RkpX5B1I3fzqmOU4nYdvmErLtU/w0cex1FEH76mYonH4asYpKuucfEU3s+DPbKo3GTWPGZIlUV5bKfZOp0ZWYdR00aJCMjooZ5127dqWIWIEQaHdGYjMrYp8kRGR17NixuLu7SwHboUMHli1bRlhYGD///DP79u0jLu7ewsNkMuHl5XXbReXh6fvm5/zs945sLdPK/i9bpw9PiX6G5vcnsoEScRXC1bl/BpGxyf+VRkPjmrVYqa0jhet7hjkMsT2v9LO8Bx+bZrDbXoRIpwfltKcJ372YU7GpA+uPa7oxRttPLteJXsjW5X/JZZEqPKtLbp63fkiE0xPPyINcn9hGGoKo3B/ZtR9tOxNJktksoxclfZJFiym15+/D0mmhUvuTiAuWXBWUO6+luilmKclGYZFOd56zfCjTmY1OM98bfiInI/aphuaxmDUulOIc+bTJaWXe+bLk/RPt4lTopK/5T8W5t0BNCK7Em/9aOB+VGs39YW8WRHZFTeOu32H2c7BtPESdx6kz8ZW1Gz/a29GohFJj/Lh46s5H8RE4Fr0tF7+3dWCtvTxvVXXlg6ppi7i311iIu36Zmcbhsj2VTL+t0Avc0/7ffjkbyMdbYIBWMVmaZavH74avec6wOku+/nBLDylYW+h2KP2/iz8DeZLbWKVF1HkS98zEgwSZ3TPWezDfNU4nsu90cH71BIKP/i7PhbNs9TnVZm6W7XcqTykBxYnxKPy4v4XKE8hDFelUrFgxRcQKhIgVRku3RmLvFLH+/v6yNla0yBFCVjgJP8muu6Ghofz4448MHTpURltFlNXFxYVnnnmGUqVKZTplWiXrEJGv/m9+yl9FRpPoNFKPPVycM5jDF5UoVo1CfpyuMUJGN0WNa+yuWcTFKSmSWp2GpnVqs8VYU56sPzdM5lPbc+y13zsK0smwmVOO3PIzG+j2cXDHGi4m6FMisu/X8WOM41nlO4RPZ986ZTBTyFvLhE4F6Wf7UDaxD7ixmys/toKk/9Zkz5PGVyuVlGCj0YiXJtkgyZA1tYbf7rJy8oYihF6p6IJb0WTTlGtZX9csoj1LTinmY/PtdbFrDPIYPcM4IkvSE7OLnfaidLAMx6HRy+8rXLsl/sVAl35LhcwgOs3U1B4mv/Ws0iu1+gCmH7Pzz3Gl5t3FoLgGi4jr1fiHiLaKNkNrRyqRPVsiCV5FOFP1U76rvJzx9nayfVKPKsFZ8ptU7o+khYPQmmOkC/xP9rZ8WNOVtyunvV2N221lz/EzzDYNky3UMHlBxT539TO9Sb89hRh31Itxhh/leeSSw4/nDStlSUlW8Ju1Ke8Y5svvcg1fdBWezViwRpzCsm8WrpjZZA/la99PmNHe9652XRK7leiVX1Hg0mJ583NbH4L7/k6nqo83E0Dlv4VX3GlZ462icj9kmbOEMPMQIlY46KYViRVRWjHgiIyMZPbs2bJFjhCyH3zwwX23y8nprF27ljNnzshlUdsaERFBcLA6AHnc9O7zEqtq/MYNpwfltacwrfyQkxeVNM8WpQLZUX64bG1RQHOVaztncyMuuRZVo6FmjXocca+KXuPgG8ME/rC3YJat7j0/s4ruFIccBeTMdzvdJtZs247NrqSKC0+el+uE8J29k7xd/uyvhO1RmrOX9tfxQ7eyPO8YSpTTnaCYfVz6qa3s8aqSzQj3vjt6Y4rj2O6zyiRHtcL+aG3J20YW/R/f71ZEZIiPgcHVDJBf6ZlK/NUs73f4zlYXyluV1NcDjoJ4OOMYYxhPJZ2S+pwTEX1Ze8uIsAaN085849DUdMo0+kg+CBsjPDA6LXykF1FWoMQzOFx8+Gh9koxEe7ro2N/HVR4PhN3gT/ttDx5hXfslXNgGWgPH637PvrYrCCvem993K8Ztnq6mDHsbqmTtPu44thyXo3NlNs771v58VNuTAeXTXv87rtiZtfM8M02fy0lOp6ufEmFNp2506gV/Nl01Mt74P/Jrr2F3asmrzboJ+vHWVvTRr8ZDk8QeSuBfvRdan3TGGyJN5OIO7AfnYsTGSnslRnsPSV+w2pIIXzQM78ubZDnLG7Y36fbGl9Qp6p9l31/l6cZs9JXmlNV3vw/z+it9yd3U7UslY7LPDvGOSKyIpgoRO3HiRDp37izb3ggxO2vWLF588UWedER6cPny5Vm+fDkbNmzgjz/+oEGDBvj5ZWCEoPLIaPNMG062/ZuLzgA5K61f9RFXrirCtXulPKwuPYKLjgAKaa4QtXM2l6JSXYVLVW5IuE8lKVz/ZxzPCWd+vrLc21m4iu4kex1KCkxv7Qr+3ppqgONpcNCxRil+trWSt4P2/UDsUaUFVD5PLb/3DOUlzSfEON3IG7OH87/0AnvWOKWqZFBjeEdvzBVHrkuxIcZ8PSrnISaopvLA9okQl1zf+hDcrHnvWkKfmnas0aaaJmUR8fGxzDIMk4NtkX7+pn4eB11foot+IzmZ563vkqhxk+t/qnEklXTJfUxFhCtQ6e33MFxJMvDcroJ8Y5xAWe1ZnKI2sUxnphxx4HQ6pBP04g6uXE1U2n0Iing/wGlT/IBtE6RwEPWPhxpPJqJgK3l8GbzgGFFxCfIpL9RRU+Ye2T4eG07MrFfk3b/ZnqFrnXLSKTo93l1+nSmGUeTWRGF3C0Qjopou6adOTzjly6+GMdTRHZL/rU6TNfvzeUcAA82v0E+/TJ6TllGLsnXaoXVxTz+6f3QhnFqNDgfz7bX52PAeczukXeLgSIji1OyPyR21V4qK560f0LHPWxTPnXUlESoqiW7BNDF/zcp6c+CldfDadvB5CkzfVJ6cPq1CxPbv318KVWHgJMSsaH/zX0BEAlq2bEmlSpW4fv26XL7VWVjl8VOtclXOt50ro6oFNVewLBlMTITiRvp89bxsLjeCC84ACmsuY94zk53hySlcGi25yzUlNnd1eXOI4S8CtbG8YVYGPBlRVXeCWVYlMtvZtpDdBw6kPJbPzUaB0FpMszWWbXbctn6D+eQ6+Zi3i5bfepTiTd6TvfwKhK8i7Ldns8wtVSUNhGOrMPa5xbn1h3VK5oSrqwl/dyPnKg0mzq8MmGNgzRcP3SfUw6Qcgg9cTx7Qyl5tycsGpQ1LVmA5/q9MbRaTKL7OWAppH15wZzcLbdVY76gol7tqV1NHd0R5wOQJ5Xtm2MrjfrA5oNnmErypm0tr3VaZmqtpMkzWJv52UNnPcnvoKeCl5fOtVhl11Wi1PFvyAU6bh/+B46IXpoZjdcYRE6RE1L9YfpLz1xRTqTol8/BOY1W0PpJ9XG/i6uTe+NhvyLTgvfl70at0+qZe326N5jvHSDnhmaj3Rleua4btiIQB39eOb6itOySzbTLRETBDxltaMtj6IqONv2LU2Nmkq0qzOnXQ69LZJhNuwJ6pcPWw/B7Drb35WPsGq7t5oE8jwjpjx3nOzxpEEctROWH6svYThr/9Og2LqxEwlXsgyipKt8Naoi1eHh74erphTG+7TCZM9FrwCYXgCk+dYBXrRqwjsa7EOhPrTq5DlUcjWkXa79OOSIGuVq2aNGTKl081KsiJ1Kpcgb1NZ8gefAU04cQu+hBbcnuZrpXzcaTqF4pw1V7G9/A0vjucLGA0GjxLNsRSUDEde0G/nBb63XRNGnxPZ+HOug38YG0rlyvdWEzU2b0pjzUPiiWpcAtm2hrImifdxrHYz6yXj4n2A193rcKbjrdlilbwpWWE/9ZD6SeokvWIQegtvTFFavDBC0o6X41CyqDNoXfhWIPxikvojVOw5YeH+sjcbsoh+ERk8kYUnZz6Kr5DFjnjEnES35gjctA6yNJf1lXndBIcRgZaX5eD/VzOa3KQLjEmC1ZXn4f+jA7bitHLsYCBeqWmXFvrDQgqS6zFwblk86UeJZXI2+pzyu06+Qxpp1NmxNXDivGSaK1T+SNuFGgulz9edIyD5xVDqdD8Afyvc+hD/yaV+9vHE9b+j1zXt0kn3/e17/B90/SjiJFxidQ+MpwK2lPE4I5rhc7KxEl6WBLQ7Z9BLd1h4pwusqXMwyLOMW2ThrHDWYpfjN9g0lg57xZK7VoN0KYnDCJOKdtd/DWuOn3oaRnCVFqxtqvbXa1tNofZ6fb7Xpodep+Cmssy62hY0Pf8PuRVigQ++l7BKk8govVR1ykYekxl28fN2TOkId5uT2Gpw/Xjd/Wg3XEuitm7w1Iu4rZYN2IdiXUl1plYd2r7qHujzUrBpqLyJNC2bhVW15qqtKbhGpfnD8UWr9QtNgvNy/V6I1PSiNuF/8A7O1K3bWNIVRwl2koB0Eq3nTcNC+hsGZqhcBVj3La6zXxvbSdv+5xbBldSI64vForgbL520plRpHvZ13+D47LyeKCblg871eUVm4i4Gsh9aSXnfu6hRlwfAZEJNpzJf+yu85EsOHAVq82BxT0vR2r9T3nS6bUP9V+UC1RmVoUZ05rzNjiyQHnAKy9ZxlUlQjnd3ojjzgL3nGTJCUywtUoxXlpu+ig1UlW+B7j6PvT7TzwbSP34ZbxvmKXcIdqVFGsqF+eecMjaVScaXiuvY+xOKza7SBeGT2tkciLh3GZYORScdq6HtOZyqRfk3UsOXePUZWWit2geXxYOqEqgp9IrViWbCduLy9Zv5eJga3++bVsk/YkIp4NTi8ZQTXtMmuPZynQH98D039sSj23vdIo7T0tPgt+tyjb1sHXdTSyjaKXfzm+msbhqLJh9ilKg8jPCMTDtF10/AYfmgsPKDkcJWpm/YAelWNbJTZ5TbuXvkza+WHSQ8ZpRsqXNEW0xrvdYytgBndELAwYVFZV7I+pxRV3uvP639aAVArXz+E0MmrUn5SJui/tVMo96RFJ5KnmhRQ1mlfuFC45A8nOFM3M/wZbs0luxcDD+7b7kErkJ0V7l3fgxPLvBl6TkklJtUGkM5bvIBvGiXmmYcSrdLB9lKAYKaK/jRiK/2J6Rt+1Hl9zmmPdBiXC25+rCEns1aZQRt2IERF9IcRX+sFMtXnEoqcIh4as4NaG7GnHNZvw9jLStpPQ6jI1PZPrW0/T6fQevzzzI1jPJhiruuR4qIjqith6jXidF0t8rV8HZDTKFVLZcySqMShTJmVzGMN7WhpzOMkdVed1TuwpfbbIhVfln0zW9yWwda9jJ/bxnmK3cUaUfVOqd8viucGVHdjNqibcJsywlBbyov4GivveZviUU7oE5ilOwzUxUcD1O1RwpMzZEBH/6jvPyaQHe7qx4o0bmo7cqD26GteANtDhYYK/J1TwNKOKb/rqP2vIHVczb5HH3F88B+PlnIFhFX+19f6FPvEa404dO5k/op1cM9h5GsHaxfMzXxl95Wa+4+JK3Mqay7dM/7ogI6+H5UnAvctSkh2UIV/Hj92fc7vqtB8OTOLduCv8Yh0rBGucXSqkP11GhVPGH+t4qKk8dIr1Z1OW+tO62HrRnIxLk+b1LtUJ83bWivBa3xf0qmUc9U6o8tXzQuR4zy/zEVac3xZznODhzGKevKQcSV9885Ok0iku6YGle8439S7qu8+ViYnK6i29BXCr3JMbpKg1cxKCil/WDDIVrP8MKWac321ZPpgI7Ds6HqNSWSGPKXmSOV29Zd+hFPJELPpJN4AXFfXWM7l6TN53vyVThItdWcerHDmB9uJpKlYz5vlsZ3m8ZSoC3ByL+psVJREwcnFDafC2xlOfXgzZWnbMTFueQgsTmcHA+xiFT7g5dzzg10M2gZW5bF3Jzg+G63+R9sXnrgWeerPtrRMqz0HxaxSV4rL0LFkfOrp055cwr18nHRqWPsRTxWVTzNGlbOMMMk+VyXKnuENrhtsdvpmqL1O3eSy1SgIqo658t7yMSKl1ad8Kit2D3H/KuyyX6cKThLzgMyuTBnL3h2KxW+dQJPSuogvVRIurQr+yX9ZrDLb0Vx+70ODgPnxPz5OIHtpd4qVwG/7+oRd/3FyREEObwo5tlKOU1px6qlZTFoWWErSe/mb6hsvaEbKFG6Q5QtGn6gvXGaSXC6nSwzFmdgZZXsWLgx6auNMx/+z4fc/kEuqXvMFA/T2b4JBRsikf33zOs1VVRSX+DjYfPvOWl1IdzKfjhYq7FKu74Tw3iHBVcIc0etNUK+tClUrC8FsQmWeU6Euvq5nrL6o4B/0VU0aryVPNe12b8WfIHmfpVgWNcXPg5sw8l92r1CCRvp6+4YgyRjpG/6b7gpY3unIk3Ki/2zINXtd5c1wZQUBvOOOMEXrYOlLPj6THd+CVDrc+x3F5Fmi859s6QNUc3+a3KJf7n9oY0B/F1RHL9n49wiBYNyanCo3vUYqDmAxnlLRK5kTM/tpORHJWMEWJy6raLfLfmTMpl532m57xaryA7B9fn6PBmDGxWijx+ntTVKunb/8SH8vnmRF5cFk+tP+MoNCmOIpPiqDc9jp4L42k5J55qfyaw7XL64rVsoI4FwX/grUlgr6MI7cL6ZO3f6RYgr8ppzlCESzLt9jNramQxpzHJ2kL2kP3S8AvuGjN4BEFIcv/ah2TycSMfOpX62AOBrfCoqvRLvkl0koMTkUpKRYCbhgPhiuh4vpyJIPf7OF1u+R5Wf6bUO+tdOV1tGGerfZYiMo5fjWfebiWDomiwL1VCHr42V+U+2TsdNoyVi59Y+4JHAOVzpTN5I6Lku5RJpDHWLlQsXlg6vqeJME47OAcSb3DZ4Us361DpmTDSoLz+QRCTn7ucxfnMOA1fTRwX9QVwrf5Cxo7ZUeeV/r9OByscVXnd/Bo2dHzdwJXWhe8QuceX4bbiPUppzks38UM1v8Gt83jwUb04VFRUci6qaFV56nm7R1s2Vp8o7f3r6Q6Qb9tnDFuvOHqK+rmgDl9yw60wAZoYphlG8OZml9SIq5sfAdW7c1GXj0BNtBSuH1hfJNqR6kB7K2LmfaZxBG9YXmOLvbQUrvZDfyttCZL5o3o4I13e4ZQjDwGO6xyf9zmWpIQUV+GxPWvwhnaINBEpFLWVC7/2VtLeVNLl+an7GTp/H98sP5xy6fTTJsb9q7gD3w9uRj1vNyrMlvfrUchfcfb1NjplyudN73TpMJtcfykiaWL5apyNrv/E02xuIuei0xj4xlwm942dMpL7rvUVrlizuLZR1OC5+MhtbaXpfX41fI02i9pvZDWH7fn5wtabSprjNNIlG5aVapN+7V4m3YK3no+VrqtnNPko+8zLqX8WkGRzUHdmEnZRvwp0LKZPefiNCveRAi6yImQEXkNY6RfZ0WE9e4O6MmNXGEMWHqPvlD0M/ecAGtlKR8v47uUe+jep3CfntuD453W5+KOtLX876zKzVTru0wfnpUTJx1o7s9b9GZ4rkGqqchfCnyD2soze9rB+zHlHbl7SLcRF++AtyswaIzV1R+Xk5Er3NuSr2S1j8zGx7R2YJWunV9kr8ZrlDazo+bS2a2o7rZscmi8N5PTYZTnK/Nr/ENq8320mdCoqKio5EVW0qqgArVq2JaHbHGKdrtTUHaHdqU9oNeMakUkO2YvPr+1IojyKybofIVzf3mwgzpa8+xg9yFejM8cMpWQdw1jTJCbZW3LSHpTmui2vO8NYw3hetbzJZacfusQIHMeWKSonmSk1wxnv8bqcBS/pPM36mWOIiLempJSO61EpJVU4/+XlXP3rFWV6XuUuRBrO2iNKmrVT9EDV6qRoEIJk7IojbDmThvO5SNMREe500nV0ZZSU0tH5NnP2JU/OvezFjt4eTGvtzsKO7ux7zoNzr3gxqr4bLgal5cXx61YazEzgSvwd/9Ppf+XVMX1JmRary6L2GCkIwSd6SvoVkcK1sW4PI4xTyGmIlOVOls9k3e27+mSDpKDyWdZwfsiR/PihTEYF5g5O7YcrBa2D+rOSiEmyyd3wwxqu9Cypl2nBgtXn72PfSk4Z3+tSjVYn29Bl2mnembWHf3af5/SVSMxms3LC1er4uU9lte/lo+LGGWzTuqJ12qRIG2Pvxpy2d9d3SsQEYnKEVQjWRS6tWVA91XvgLuxWbGeUXsff2TpwxpGH/rqFDDYmb78PiDBb2uEozuceH9O0SmjGkzaiX/T+GbL/7CZ7KK9Z38SqMfBrC/fb+86KDXvvX7BTyTT4ydaWT1w/4sVmlR/qu6qoqKg8KlTRqqKSTEDperi8uIQYPGR7g68TP6PplMusPGcDkwc+bUZw3aOETOP8VfclAzfpUnWi3oUSNdtwwKO2vDnIMIfdzuJsspdMc/220W/nRd1iXre8gc2pRXvtMITtvu05Y6rGMtf3RWkC0oTtbJw1JqUVhxCun3epztu2N7A7NeQ6OYv4Oa+qwjUNhi0+joiFikjm730qMb1fVX7uXQmNTi9rVHv9up24my5bN7EkyEGgvE6Lsp2V67A9KVFukb5dJ69OpvuKiLige0k9h/u68molVymAnE4HbeYn3T6QFA7EIrPUqPTuzGrNKhEtOsp24aeAj6UZmHA2zUlEODxpaPmaRI0r1TWHqa07rDwQUitL3j/SomPGRV/8UczWPDx9b0sdrzU9ifBYRbD2r+DCgPLKYN/FoPyPWy/fQ7Q6bEQdWikXx8fUIjJG9NtNzn7Q6sjl40HD0nkZ2akChz9rQrPSue57gkTlIUiMxDy1K3prDAccBXnXNoBZbT2oEpSGCBStxnb+Ihf/Z+vIAlNrVtc6mmGLqPDTe9FbY6Xb/BRbU4bqJ/OxcfpD/WUOp4bR1m58anqfL6okZvzkhBtYRImJ3cIuRzH6W99FZ3RlXTd3moTc8hvFhr1nilJ3KybbrF35ytqdCc8qfZDvG3VbVVFReYyoolVF5RYM+SvhNWAl8QZ/SmvPMcvwKUOWXWLHFbtMnQpo+zkX3ErjpUnkO+dohm69RexotJStXJfDudpIIdlVvx4DTjbaS6W5jl8zLqQQlxhl6yFv206sloOsW3mpvIkNuXrJFjvttJtY8/cvMiokCPbQ0q9tQ9nPUnye++HpsHzwbRFbFdh/SYmu+Xu64WpUUuU8XfQ0D1XMjuw2G6uP35H+Z3RT6hDFdVoECHdNjSJskzKujRXOsH1LCyGrDCJFurBIRU2pQ4u9LJuKL7RWk3eZtNkXMS8e6MYIW2+qJf3IRh+lBdPjZrK1MZXNP3GJIIpoLjHBqLQjIbiS0g83C5h0NpecDAjUJP9Xt6Ra/nHYLv8Tsdv0DHXh4xpKzbrYz2wOZV+KSMp4n7pw4QI+TmU7W+8sL9vYdKpakOkv1eTsyBZs/7A+v/epQM+qeWWaeboTJKooyDocDpxz+mGKPM4Vpy/9LIP4o40fVdMSrNdPyFZjAjGpM13fjtW1MxasVxK0mC5tTal7/dowgRcND+YWLCYuBcJb4QXre8zWt2JBjZMZvibu+iWid/yF0Z7AIUcIz1veJ8jPk929XQnxvuWLiw1b9Gs9oLhlD7P25id7e/IGeKXWVN/vdnevyTwVFRWVbEQVrSoqd5K7NO6vrMTqmY/C2ivMNA5n4MJLxFocsg9X/vbDOWoqJ01iPrV8yx87wm97eelSoZwv8qx0Fq6mO0aI5jqbbWlHXMeYfuGQPR/r7WWlg+P+vdvuek6T0kHsztNNLvfVLGb8PCWiI6iUS0f+Co142/qqcse2CbBpnPqf3kKzUrnldURsPJejzVKMnI1IZMn+i/J+L3dX2pS5JfIlELVdGdV4SVdnUbSqBZNXuutbRPE+3mSh6rT4lNTTtsVdcLnZ/zBBEctON3/2xCoCrWkuJRqYHTTJFUOQiw2LxsizV7pxOHRQsgB/9MQ6XHgmaQSf2PpJ0V5Nc5iFxo/x1cSDqx+EKFkLWcHBWKUGOUSXPDlxS6/NWceUiGguDz1f1k02WQM+3GBLqW99v0rGNa1xrrllmxPBgXZXWTWwFmM7hVKz8H206Ll1gkQVBVnHlu/RnFot60L7mt/nw0Z5qZ4nDcGaGIl19Qh02Fhlr8j/6MG62kfIqEWpKA35YCv4aOK57vSinW4D7fSKgM0MYv5RCFVx7Bd9wztYhnPSpQxr6hzN8PN3HT2F4eB0vImTgrW/cwjDGwfybxfX1GOL/AC7Yg52SHFB/szah9/tz6DV6vijzy1R1vvd7u41maeioqKSjaiiVUUlLfyLYOi3FLNHPgppw5mmH86L85W6SAwulOwyjA2GWtLUpW/C72zee+C2CGeh/Pm4XvoFzjlzkV97jbK6s+ywF03zo/40fsUUW2M5217Ospe/Dtw92129RAGWu7SQy/3jJjB365GUxwZV1rHNrT6fW5OdUFd9CrsUIxEVeKthITQ6nTzYiRrD3r9uZ/C8fTI1WKPVseyNWplvO3JsqXItBJ8u7bYZ6y7YKTM5kWkHk2R6sihsfaeaK983ShVGmBWBetmuCF+xCQ0qejlb/7bFNY+hFYZRQKd9FXCUbA8BGbiSZgNXHd5UME/kCIXx18TwvX4cs0wjZE24bPdTsVeWmsKcT1DWeT7t3aL1WISSLdGsYKowvZbgYPZRxZW7Rl4joQEZG0EZDS58b1PqnHXCodZ6j7TO9CZIVFGQNVzciWPVMLk4zNaHXAWKS2OtNGtS/x2JISlCGt+9Y32NxTVO4JLBHIVIkmiwsRS1nfvkbeGD0FB3MNNfcZe9COH4ynIT4Rbf2TKMdkV0bKx7BA99+k7Fa7fvpHL4bEwaG0vt1ZhZ+Es29g2ifdE7vrTdCuu/krXWoob/PetL/GFvIY95SwZUur2m+n63u3tN5qk8vWh0UKwZ1sJNcHV1x8PNFaPu6ZYYh8Li2H427UwsnVYr15FYV2KdiXUn16FKhjzdW5SKSkb4FMD04lKiTMEy4vplwmeMWpssXHUGand7n6ma1vJmrejFnN+/Vml/kEzhXJ7YKzzHNkdJPDVJVNWdlAOVOxF6aYLhO/62K/V7Za4vYtuNuwcFzauVZwMVcNFYqXt0BJcvX0p+vZYVnVyYQhsm2lopT144UBWuyej1WvrWLnxX1rSocR3/bCWCfVwylyInBMm+5Lq1NKKBIpLbf4WZPkviSbDY5eeWz21kTx93Bla6Q+CaY+XV0SQlIhfsZsPXmL1O0P5GO5MqnJXfK9Gmof7mUCILtckwYpyViOhSa/MI7Bo9HbXr2GR6kzb65AyDoHJQvofMaMhKrlvEgN5JkDPiNtG6JUz8P8o+W9hbw6lIB/1WmKn+Z0LKRMOkJrdMMqSDQQcz7Q1lbaMmPhx2PmC7E1UUPDyx4Thm9UHrtLPIXoMF+qb81jztiSXn9knorx+RWTEvWt9lXKVwQtwV34D06LunMNfNOhppFQ8CMamZWSZbGpFLE0MebSQnHHkZ4/4WaxudZ2CR9N/LkRTHvg0LaJC4St6e4OxIyY4fMby+192TbmKb3vQ/OLdZ7mcvWwYyx95ACtbFb9SmZP5MZpaoqNwLgws8OxtDn7ns/rQFBz9phLebst/tOBfF7N1hrDya2t7vv0ywtzKmWHnoErO3n5HZOgX9bz+nuRl1ch2JdSXWmVh3ch2qZMh9+PirqDzF+BTA55VlXP6+KYW5wrNnPmKa6VN61SyEVqenbdeXGPGXPx9pp1Agahsx+6LwKtsKdMpAt7CPDk2VTkzdsZ3eupVU1p3iosOf3ERiuKV2Ua910Apl4F5Oe4buJwKYUf0O8aTRUKpKY45sv0Ep7XnOrxwG3b6RJlHC+GdeO1daz3tWRhD765fgXPg2GvdcULIlTzuftizOq3VDZIruTfJ4m26vL7w1RS69wdvVIzDnBbh6WIlM3CFa11yw88rKJMxWu4xkmgw6fmnmQt186c2gKrZLvo4b8rpV7vvrHZsVacLPBMWwLNyLCwkGKm+sxJ9Fu1Hzws/Z/tltLcOl4dIP+u9ofVOsChFZrDl4Z0+fSJPWST3tDtxIVGazPZRBey5XIU01UqAO35TI8OS2RQIh6l+p6JJiqpURwR5gwcAmexm66dfCtaPZ8jtU7o1j+y9oYy7JCYQPrS8yq5Mr+rQyKSJOojmuZEwMtLxO9+IaGgYqk0gZsTlCRCidhGgfbAC+ylaBDoYt0hfhjDOIqNK9+CV3xu/luHGOqAOLKU+MbM32g9sA3urYCGNaOcRiw936E5xZhwMtz5nfY6OjnDxfLXytFqXzeD7Q91ZReRCEYO08fpM804VqztDUBIcux4LmjomT/xChyfvYW01LEOUTKgVr1Tt6ct+MwKb1mEr6qJFWFZV74RuC/2srOUcw+bXXaXVsMNv2KelgYkDbvUNHXre9idlpwCv6GObd08ESl/LyQp522tetyiDNO9IQJJ82QrYeue64ffDgqlVm+MVga1u0d5odbALcDawL7keY048CzjAiln2hpIEJQ9tAHVNaujPC1ovptoZocGCf9Rxc3KX+x8KEx9NEkUD3lMtdhjj3SpET7SIm1lMEq4sPNPokRfwIhm6y0HdxvBSsYma1UUETh/q6ZiBYxRmrjhxYVtSepLLmGG2CHo1oFUyocJY3i1yV31X4DXU/3pDteXpm62e+bH4TrUbDIuNHqYK1UH2o/Hy2CVZBHZ8IPjFMVW6U6yrdvgWi7cnSzm54uSg9WcVFp9NSP8TE8i7uDK6WdoTuToQoKuWZSBvdFuWO0I7Z9ltU0ic+/CwJG76Xy+NsHWla3C/d1O7orZPltchwifEpwcsF7y1CJ58PkPuK06khyb90pv4K4QIvnIGb6PdKwbrPWYzAql2pmjsDv3ARMT23GQ7MwI8Yjjny8WWu0bzftUn6gnX7RDi+TKYEv2l5VQpWnV7P6nfqEhqsClaVR8vZCJG1Al2qFaJpaF55X1j0LQ76/2GalgykS6Xg20SpEKninCsisINm7ZGCXgh7lftDFa0qKveB0T8E/zf/ZZ+zKL6aOMrvGUrUic3ysaK+Onq0aERPyxBuOD0wJVzGtmsqxKcOgjwNDr6uZ2S8/0fMs9VBp3ESoI2VfVZtztsHLQcdheTY4+8rqW05buWVEom84Xj3/+2dBXRUVxeF93hcCBoIIcEluLtbcW8LNayU0lKjBepGoQK0BQqUtmh/3KG4u3uwICEhQojL+L/OfZmQhDgJmUzOt9YwPnnceW/e3fecsw/izHbwiLqExMNzU+pp23kp8E9PR3xqeAP7jfWgMOmgW9wfCE1uIcJk8SVnkSJ3fB6wYZxoLYHyjYA+vwHlG6Y8PXaXFksuJQnRY69W4H+9HfFXN03GEZ7U2Ltjm6K9uPmD+k/Ucy44E6aMeL9KCHa0vAGNwiy2/bXAnjA1eC3PqcIXjD6Yp+uJvca6iDRJ43jfVBKzdX3RL+lzEZ1ao/4S3vIwyRm4wStAxRZpeqYWBB+o1qKc7DHum0ohskpaQVnLQ4HzI+wwqZk9fu/igNujnLC4uwY1PHJXX/Sp205Rk3vZVAmGim3z+X/AZMeVoGhcnPsynJCIs6YqCC7bCT+3yziZzBR8Hq6PzglX9l+Ng7G8YdZOvUSCQYav/D3F7XL2Bjj7SG7f2UFGUATVoNJiJZnufa18B35tBsDJMYs0+PhHwLllwN2DIntmjbEtfi47A9/0fLrERPpPGaWWPf5bRPbAB7ox2GJqKQTr3vfawCddeiLD5CtUVvNdOZi/LYcan6yF9ydbER4r+QIQTSu5oTalpBRzSMCuGdcKn/epI6ZtDkhC/cXVxdhx27PsYdHKMDnEqUQ5qEduwx5jA1FX6nxkGhIvbxPPUTRtRMf66Kf7Whh6KHXRknCNvJvmM77yi4BjnZ4YoZss+uqRkZNSlrbYktwgie2hmaeMfN7IiAl6qUer/d1dMFxck/JcBy8FVvZ1wduGiaI3oVofjaSFXUVbByYP3NoN/PeJdLtWf6DTF0JsWtyBB2xKwo4ArRB9Xq4qXBhhjxaeORc8n8YPQ7jZBVVlQcCtXc+9ZVEN5yT83fCO+LMJBjleut4KaDIaqNJF6u+aDQaTHDN1/VEv8Q/00X2H6abheEP/CRroFqBp4u/4yTAMVRQPsUIzHVNU/4p93uxRXYquukgioECJC0XFiMPi5heG13Du8dM1qlQT+FZ9FXr55rFiJuQiWj6SjsH5hl64FZELIybmmTAYTJiy4Sr2z3sbLWSXRfrs6WrvY3kvx4wN1sxmhB1ZIm7+a+yIyfUSszResrA1zE1EWYlR3uE4ofXGA8fa4j4dvwv0PfC17kX8pe+Cfca6YlGRoHMFmTUtNnRBR+1P2F9+ND5v5QC5IosIK/1WU5ua2GBRb/uhfiwWuE7Agh6ZLCbFBAHbPwKubhR3v1O8hXWmtqJHMAlWbxaszPNAnwCZQYqsyvJoUFRchGtvv7IppSgqU5IYOyZ7uKaVYXJBzYplcL7XYvy7+R28qNwP+zNzoYu9D3Wz0cK90WT2Rf+9X2Oh+mc0k/vDdHEV5NV7AGX9Uj6jW5kYtOogx+tnJsE+5hbeV65GfXlASmrwNlMz0Hzm02pSS5aMqOeagI41SuNr/1fwlXoxlOcXAy5lAB8pwtO4rAJrBpbAS+s/xd/4HvUMAYhb1AdO4/YCLlJ/UiaHXForXVfpDDR+I6XoMUFvQo91WtyLktKz65ZRY0Mfde6diO3d8Il2NBaqf4H84QVArgIqd3pSXPkcaFkiDp1Kx2JvuDOOP3bEJH9fzKitAsrVB0IvA4HHn+ohTJwz+uAPQ2+xv5KZkgdiRC/UKrIg1JAHipYgqQmXl4R75SZQlqtb8P+/xCgg6DQQfE7UrO40NsJBWSMsrJCPfzcpBjjzl1jYoG/9mskLu5VtMLs0R7WeB3MO3MXMXdcxEcsxXrlJPHanxmiMaV4x8zfdP4qyCTeEuF2j7IVNpXPm1t27dCSmyitAZ5Lh2+vSb2gV2atYpf4apWQxGKNKdhRPBZksLTZ0xVZZKzT0MGJjnXsi6yZLQi/D7L9V7LMUlZ2kHwO5S1kc7K95+rW00nRzB3BqIWDQiiyRm02+wZoTvvQLhSY+JVmwMlZpUHTFrM7QoMimeHTjyW0HD8DNqzC3xiZg0cowueTFZt6Yr5uNn/77Fh+qVkN9YwuMMQ+gaP8JBlR1Qnmn0nhl81T8qJyLPlTjdn0r4uNj4ehLaZDShJlaGqxudhsROiW+v/4B5sVF467OHUFGZ7jaGbG7kX+2LpYjvCLwaVxj/BUcijeU/0F/8GeoHEoAZeqI5ym9ccdLpdHnf5OxwvQpfBKDEb2oH1zH7ZRSM5nsocJiirQSvh1Svr9L4UYM3JQEnUFyB+7koxHpwHmhp68SK640wsf6MfhRNV8SWmTklbwA8bz4q+EddDlaHTdjNVgZ6A5vex3G+4YC5epJrr50Ar5/DIgLSXlPA8UdzFf8mulnUmRKb18amtKVRVudUk5lCl6skrszTeTDr0u9dAFcNVXE5/rXMKlFDlK2cwJ96Xf2AycXprQtWmrohB8Nw/DZC5UgNySyE2sBQdkN8w7dx9z9t5GYmIDPlEvxunKHeC6hwWjUrts9izcbYDyzBJQHsdDYE32rZP0bmxqKxi5uFIBhpyqLKJLQi6iAjrpf8LZyI0bIdyAJGlySVcUdZWVEO1SCq0cZjPSIw7eO2acfCx6cAm7vEZ+/1thGCFaa6O8bksF+S+nDx+dI76Ea3TItcKvVj9A5ekJ5WvJc0Bufb9YGw6THPiFYGDC5RVHrsMhsDYpsAhKo5IC/bvSTx+j++JMsXJ8RFq0MkwfGtqmEX3RTMHZ3ecxUz4NDyHmYtn4Aeecv0KycJ3YNc8Wwze/iQVIpvKXcBMcHBxEUE4vydTum6etJ7Ud+9gtMvpf7esZvawbhxdj+8IyLQHfFKcT99zWc+v2SYmpTykGO9UPL4KV/p2Cl7DOUivZH7D9D4Pz6WuE6zGRDyEUgPkwy7iktGa+cDzOi73qpJQpNCUfXt8OnzbNvi5IZExsosfwysNrYDq/WAOrcni+iQSjhA7g+35XZ7c2vo+mB2nisU2DGjTK4Fa/BTL/7ktAsVV3qSxt5F+bHd7A+UAMXc5yo8a7tkgQ7O3vpxEwXWjxxLAW5gwc0ZG5VQGx86IapVyuImtxxlcLwRsVwyMkRNnmFO8K9Pj4M74F9hjpwtVdhbN2cGStlCZmsHfxJWlwAEOlYBaOiX8UZQ2WUdLHHS/Vcs3agZvJMaHQiOs8+htiERDgiEb+p5uMFxUnpyaZj4VCzd9YfcHUTFLFBeGR2wULDC7jolUMxmUyLEvG40umySKMvqTaIdmUSfoC5NjSQobVMhtYp75BcwbOFFPDdQ9JxTwtIhu74Wj8cLbzssLxHBtkbt/cBJ+ZJKYVyJe7W/wgPa41MqQ3XG6VobpK+YNtnMUxWyGMeoPu+XuilSQQOJj+ockCXhjUAt+dQGlJYUESVBGpCcos1Oh+RgKX7HG19Jli0Mkweeb+TL77Xj8DA/aXxp+ZnlI8NgmHHZ1D2+gkVXdxx9GUn/Hz6dUw5XxLfKP9G+ZhzuH30Mco37AU7x/xzcVze+A76HRuJ0rpINJTfQuDW6fCiVjjJ4risoxx/D/bBG6snY4XyaziHHIf+35ehGr4KUOYtOlhsIKdggmovFSroDCYM3ZIkBKtMJsdf3e3RseKzNQQv7SiHi50CsVojpjzqgk2VbwK39wIhl567aCVD0n2trqHtkVqI1smxPtgNdxM0WNvkpjRBJ/Fawgefh7bGUp2HmGv/3egO7HLQKiQ/CdcqMOJMFVyL0YhNijNApGz+exPYo74Bg1mBYfpPcfphdfF6Wlz4tUM+7eskGIJOwyRXYqFiGH581BUGmRIkE34bVCNLB2oyJomI18PDUSXcrJnc8fvB+0KwtpJdwk+aP1EO4dJ4t35PcqHOisi7MJxZLCY9MwxD0btCUirRmXMoS4YuT/EMZmJJd0/ALlmwztAPwRxjP3zb1gEjamUwRQs+Bxz+RezVsR71cLvldCS6VUt5esnJIETFJojjoloZXphkCg954mMojYl4V/cWenXuKNx0i02aLP0fi8P/8znDRkwM8wxM6V4FvXq8gD7ab3DHVAbKhFAEbvgSSYlSLd8HjVV4bWBfjDZPRaTZCZVN9xB9ajkOBeTfJJ8mXhta3MUP6reFe7GX/g6ObFyQ5jXernJM6l4LI3SfIN6sgerufiT+73XJcZLJnEptpMno4wAx6R20RZfS0uavHs8uWC30qiwtMFwM08NMvXUJ6idaCLiqTTjT7jJqukhtCc5F2aPV4Vq4FSeJrDiDHEvve4jb9d0S0fE5C9bZt8ugyf7a8I+VBKub2ojy9nohoOtDMhs7a66C06bq4jFHjUKY8pCzdn6kph6LKyVu3zGUwrTYnkKwqtVqLB3ZHC2qeWbuQE2R33g9tAaTuGZyP/b/O3kX4xUbsFwzTRKslG7e9bvsBatRj+g9P0EJozDSO6VpiWm1M/cMeF7oTMDKU/dhd3+/uP+N/mX8rRiIvUOcMhasCY+BQz8LwRpWeSAud1+TRrBuuhSGbecDxXFRroQzZg3KXVsehikIbpnLi3RgeNZnIcc8ExxpZZhnZHy7SijrosErq7TYoP4cXrrb2PvvNGyuNBU/t9egmrsCf77aFF/vnoEXg75HdfkDuN5fgI/vjoS5jB++rxkoIlzPKlz/1yIEUw+PxDTzbLSK3Y7/tpdH9x79Ul5DDsfXmtfF2BPv4S/Vj7C/tRVRa96FvvtPiEgwcPQnI2illFIOr27EuQMbcTH0dfHwkJp2wqU5v/iwsRIrrgIysxlXH8ZCeJIm9xItDGh/3N7iBsac88GOUGc8TFSi0+HqUCnILVh6DQn3hfXvPLdtitXL0fdENQTEq1P+/lifcEypJhnp3ItX4cYFf0APBGqqYYKfPV6uqRCZBs9KnM6El7fpxKKCq9kL5+2AyvKHKKXW4qXWtfFuczfI7bL/vijCaom0Mrnjj73+mIlf0Et1XHqgWneg8UhAZZ/teyOPL4N7/F2xqPelaRR2taB658Itlf/oakWoQs7hB9UK8dg8Q2+E+w7EhbbKp3qwkmB/a68eA4Pmogui4G+uiIE3BgABl1DS2Q5VSjlCJpNh5+UHkMsAF0d77JvYKvemcAyTV2hx17s19CYTVPc1MEENBe9+maJUyEQ7KpNBjhD3xijrYlfgrd9sAR4hhskHBjYoh38nvYifSk9DolmNjorzaHZnDjquSoTBZBKThy+7VoSu6484gIaiDcJ0xR+oGbIJNffUwYaHz25GQPOTb1rbYw6GiPtdQhfh+mXJpMPCmLoq9G/fHBP140Wje7erS4GDMzj6kxXN3hRXNaP2wwPRKOesEj138xMPeznKOUtriNdDkmubVYUnWi0saHAH4yuHi4kwRW8sgpXoUSYGpe0Mz2U7SJA2PlA7RbB6O+hwqt3VFMEqPaZFF5VkQDOwZS2R5ZAfgpUYtlWHC6E6mM1mRJqd8QBSNPzEcGe817IE5JQcTHWs2UApwTXKOnFqcC6JeRSCNgdfRi/FcejJRqnF29IlB4LVEHIFrjfXiduT9aPwT4uwHLW4KShORzqgzr46cAw5gR9UC8Vj2+16YthLo/BrR/VTgjUyyYSmK5KQeOckuuC4aHP2nm4c4vUyxCcm4V5YFPZcCcJuEqzUD1ajxoEPWsNOXTiZGkwxhY7F17dCNXI7Ln7VC9e/6gIXO16cywx3BzV+GOAHLdQ41GapGLuc/J4Vd1i0Mkw+UcHdHtPGj4C+/58wQo5hyv34JOEntF8WhVjKAyO7jvLOaDfiC9zzGQYTZML18mfFHHx4wRPvXcqiTUMOofnOyJY+WGNsB4XMjLKnf4QpKm0a3MCqSnTt0BGf6qWoYanTP6Pk3c0c/cmMii0AT2mh4QPlKsTps2lZkUdmttdQpSzqyKT2R5/fqYlae+qg0o66qLyzLmbeLovCYFLVhwjoehEbmt1CH89oeGiMqOSow6w6aXsQFxTHHjui/ZGa0BplIt13nE84DrTxf1owk5FNwiMprTrZQTs/oCjX5XApnbdBWTXOdbiMCggT9+WOHlL9akZ1rLp4IC6cG8Y/6/jHP0bInO7wkwcgwuyM4BbfSFHWHJCQmIh7O36HXGbGGkMbdKpVDpUdtSgMaMHnnUveGHaiEt7HcnytWiwej/HtjR5DxsHd/mmRSS7lTZYlQBP/EDNVc8RjB936oWbjdhja3BdtaniifEkXKJUqkXlQwsURuya2FhNihmGsDDJkCj4PRFnMN5ncwunBDJPPuNTvC8jnw7BunHD09TZ+in7LJ2H5kIpS5EeugHfb4YBXRZgO/iTa4riq4zEueCLaRdXA1hY3Mjb6yCF2KhncanXC2WtBwpgpZNt3KDtwBqB5Yv5EPWVnnemB+XGhGKvcCs+970LmXQ1wbpJPo2BDUIix2/fA390xTLEfS5O64FhwbbTwzN9IBn3ef82votr5IBjMcmxIqo+E5HVF6lwx+1ZprHxQAv82vgUfRx2eN/XdEvCr273n+jdXBbnjo8teUosRMlOqdx99y2XQlD7cX2rHQ7SeCNi7Z/m55AD97j4dHsaZUM5JLvoav+CjQPsKsqdSKvcEmoS7KwnmRc1CUWLvTOmJ5m8B5RtKtzOqYaXIq8nATsLPQlw4bs3ujWrmOwgzu2JH9W8xoppPjt4amWjEgVW/ox8CEW52wYVSvfFN+Ry6+eYzSwM98LV/eTQ0X8M2zV+oJg+Snmj4ClzqDM6wDdQKfwMmH0iEHbT4Qz0TJWRxgGcDdHj9D3SwgiwMhmHy2ALH0v5GNN9icgNHWhmmIKg7BMo3tiFe4Yqa8vtYKZuCCSvOYsfdVNEhn7aiRY5ZpkA7xUXRpD4pIQ4N99fG/YRnS6vpXDYBCx3GItTshrL6QCRtnwokpW2ps6SHBj8YXsIuYyPITHpg+SBeAcwM7xZA7QEiYvOuaj2mnSwAI52Ex6h5cZq4uVXRET6uChHZnFQtBL6OlJoKhCQp0f5wDewNzz/3aWvl3wce+OiSJFgpPXl9s1sZC9aYYMB/s3S7Vn+pn24WzD6rR9918bgXpRd9dul6rX8S3tgej1b/k8ynUrP2pmRWRvWrJY5Nk/rAkkFXl6+z/g9kFoFlcoZBi4D5w1BNfw3RZgfMLfU5RrTImWBNMpgw839b0A8HRDrtLo8R+Kbu8xesCQaZOF5nXnXGNMUfWKn5RghWs8YVaPcJ4DfkKcFKkf1hW5IweT+11TLhG9U/8JPfBTQuwJAlVlE2wDBPQZklM3xhmu6LGp+sg/cn2xCZwIZzaVrgjDkADFgoWlVFPgrBB6vOwx5J6LW9pRg7MYZMlrBoZZiComIzOE44gscuNVBSFoNlqm+xcddefHci1Q95+UaQ9ZguWs/Ukd/FJs2nqGm6jQ6Ha+JG7LO1xJjZKAKv6ieLKINddACw//s0bsEVXeR4s6ED3tWPxxWTN5AUBawfK/UMZJ5O8Wz7kXiIoueBEbnvqZst17dJkTkAfcs8wsZGF/Gr3z285ROGva398XWtYCHg6DLqnI8wJrJVInQKTLlSXszn7RVmHG5zDQ3d0tWM0n768DxwYbm0X5dvBDR6LdvPPhRkFJ9Lqdi9qmpQpYQqRTgExz5doxsQbYInHol2UYh5ILU/6vETYMwm2k3R1yychJmsubzhJ/jGnhZu559opuLLF6T2RTlh9LYoTJZJ6ben3XvgJb/nv8hzJcYODfbXQYmEu9iu+QSDFAdFtgClNsv6zwcqPenmaiFBb0KblVocD9KJXfID+60YotgvGbQMWAC4PXsJCcMUGAkRkCdGSC3hpL2dSS1cyT2Zep0nI08eI3t95JOerkyW2O6sh2GsATcvlHh7L2J9ekAjM2Cu+leYLq1F3w1JwmBDUKoG0Hcu4OaNMrIorFR/g96yw+h2rDrORuU9SkNmI1XLuOAl3aeIM9sBoZeB85JTpYWPm6igsXfCWP37SDKrgHtHgMtrn/V/bTukTvGMlGo4aREgRq9MqVPONyo2B5zLSbdJjJ2YBwSdAczS33m14iNsan5TnOZMZmDAyaqwVYacqir+n3T5r4U/PO1TLfTQeMSHA1fXAzf+kwRruXpS5EqefbpVq+S0bhIFv3fUYPdge2zol3ycmaVIV2qqaK+JxSRKURXRrj5zAHvXHBkvMXkjJDoJ0Re3ituzzcPw8yC/HL93820DFCGXYC/TIULugWZ1c/7e/GLB3VLoeawa+mE//qf+RvyuU89lWc+fJQMpzdP9U4PjTGi8LBFBMVL7pq9L78cEc/LvdbuPgfKNn/v/g2HyQjlEoLbsDhSPb/AAMvkKi1aGKWjUjnAesRz6xlI9w2eqZegTsQgNFscId+FjwUap32DPHwGvZsLwZ5Z6LmYrf8OYE6WwLdQ1z3/6yxoPcMNcAZ/ok2spLq2UhFAqFnbVINBcCguNL0gPbHwLCDr7DP9hG8KS4kkpecckI5R1xrYwypRYezOfRatHFaD/AqDLN4B7JSmSd2sXcPovIC5UvMTPNRFv+oSL2zfjNIVmzlSQnHjsiFuxkpHM275h8LZPBB7dBG5sB878I/WpPL1IMrWgCFTjN6Qxy6Hz4uBqCimZgNoLRUiZByXtZSlCNj51sPXGf/hV/5XIlLinrgy8eVhkUHDab8Hy0sJjaCSTJryvdmkKB5U8x2nB7+1LQnPFNXG/RKnyGdaLFhS0jvXiqcqY4V8K3ykXYbpqIdQyI1CxJfDCz0CpjKPFD2JNaPe/BCTojGLfnF35NF6JkZyF0fJdqbUPp5kzRYQtmqnYqpkKl21vwaCwF47rDJMfsGhlmOeBXAHVCz+m1MGNVG7HHNWvCIqMx7DN8fjymE4qzu8wFag7VCTXkEHTHs0H2HYxCN2OVkdYUu590zzURtR1TcIWUwv8a+wsPbjve6lJfTJkQtOqggazDQOw31hX1JJhxVAgOtkspJgQHquFf0icuH4qxfP4PODeYUChxmZlV/HU7DM60c4oX6EJtmcDoNdsyehHoZYccS+vEXUwxORqD0XLF2LWrdK4FF1EbfJpdh4bAoRflxwV7x+DOeAgDl24hgGKQ+ipOo2PTIuAo78CV9YCDy8AcSGA2Qgo7aXo6gszRa1xbvrblabhShYy+8lkSYjWJ1nxWwKSv1NauDn2O5QwYrOxOX7znQ+4e3PabwFDx2CpiDNi8S5e6Yby5XOeEjvnvBEGownN5VfFfZn780mnpZ+Br/w9UX23H5yirmGH5mMMV+6Rkv8ajADaT5Z+3zOAMjY6r06E3mgSr1/hdxb9Hs6Wwv5NRgFdvuI0c6ZI4SDT4V3dW4gcvhv/ddiCYJQs7E1ibAQWrQzzvKCJcqt3gQF/wixX4gXFSSzT/ABXxOHvC0mYfEgnTb4bjICs10wkulaGqywBv6t/R7/EdWh5oBomXfFCUi5bY35cNVhcf6EbDq19WcCoBS6vTvOaP7uqoFZr8Lb+HVw1VQTiw2De+j6KExHx+oz71Z5bBuz7Trrd7E30b+glBE5kogF9NxaQiy+luVbvCQxeDLiUB7SxwNWNKanCG5rdlHqnAhh0qgriDEXsp5wG8PYe4Ow/Uprvzf+AOwcgCzyKD+UrMFM9D3MVvwAhl6SIM7kv1ugtTf77LwReWgl0/Q7wqJzrP/3BQYOotyKBQI7BhJ1SjpJO0qLQZ4eToKP+JPePivu7jQ3wtm4CXm2b85pKJu/4lnRAPYXU9ummqkauIqWdK8pFL91asmSXa5cKBR5ZpWyHanvq4tT9GPyr+hYL1b+gsvwhzHaukHX6QixCZvZ/oEWvDquSkKQ3wh0xOFR+Llrd+klamKnZB+j85XONFDNMfnHLXB6GMnWR6ODJg8rkG0VspsMwNkDdwZCN2ACoHNFE5o8Ndl+jvOwRVlxJFq6ERxXY9/kFqDNI3B2n3Iyt6im4FRSOGnvqYsQZXwQn5sxhuLVHnBA4Opka/ygHPzH9SeUmTOl3p4fbw93VFRP146E3KyC78R8SLkt1ZTZL6FVg/w8i+ux1/heUP/cLyl9fDNw5CMQ/Avy3ApsmSK+liF7Vrhjpp8KA6pKD55UwHcbtLsC+j9SmiIQapShH3RPCjnBXG/FngztC+1H/0rp764i2Gs+TSJ0CKwI98P7livj1dhlhPJM+8JxhINoiWINOP6nprtAU90t3xFJDZ2wytsAlVT2gRGXAuzXQfTow6G+g2VjAuxXgUi5XkdXUhCeYsOmm9H219tLA2/XJ5yzpTn1yISJ1o3froVdKBkqB5tKo610Kfp4uefqbTO5QK+Xo6Cz1MdwVW+mpGuOsqFdaAV8nvZSSKz7MMd9F6rpgd7xyxhd+e+ugxs7auB5wF0sU32KL5lM0l1+DifoE+w2BjBZXKmTdQqz3Bh0exevRW34URxwnoWLEYWnfbjpWWpTRP+1mzTAMU1zhPq0MUxj4tAFG7QKWDYJv7ANstPsCr2s/wIorvlArgK9aqqVoG7mhelSG6fgfqK59gDXqr7DU2Bk/PhqKFgdqolPpWPxZ/w7StZZ8itouSbgUbYe50U0x1qWMVCN5fStQ78U0wvXAEA1G7qqCRYE98KZqCx6veQ9q37ZQOthgTYpRD/w7TBKDAGh6m+kUt0oXoNHrKXdndlDjdrQJF0N12H5bi5qBBoz2U2NiQ8VTfT6fGapvbfMBcGA6EHhCMmsqVQMdS8Xi3SphmH27tDBm+vRKeewKc8WSRlKUqqDYFeaCty54Q2eUpQkC/XKrTEqKrXDnNUvX9JLOpWPxS517cFYagdt7nwhWMqWp1h13ok3ouDIBZrMJzhoFLgyzR7Y7dR4YtVMnuVrKZPijc9pFn9olFehRWYP/bmux/54Wf0W7YSyZisgeY/5L9fJ9W5hMMJvRWHZd3DxlrIo1N00YUj3n+8LH9ZKAs0CCWYOrMa5o7P7shlnROjn6nKiGu/FqsU9roMOriq14zW4HPGVSqQWVdMh820NO6cBOpbP9zPf3JsIn4hCmqbeivvw2QDq7TB2g7++SwygZfXEdK1NUoMUWzwYwauOhiLgBpUIJpYKzBDJDIachU8BkkuORS22UdFLneTG2OMEjxDCFRZnaknAtVQOlEIn1mi/wguI4/rmYhLf2aJ9EGCq1gbzfPKByZ9En9FXlLuzSTEIrxWXRr7PV4VrZtj8Z6R0mrqO0Ctxwbys9eG2zJNxSQYLr724aJPq9hGBTCVRAKM7NGgAYc5mTXBTw3yIJVnKErf7Ck4tXM8AplcFRxRaSuEqXprehjxpVPVRCnCXqjPj1TCKqLErAoksF0JuO+oJSpNey3XHS9/l+lRAM8JR6l9LmXYgpmJ6gFGGiaGqT/bUw6mwl6E2SYCWNqlE8aW0gRGryMFmu6dldYc5ovtcXh44eAoJOSU+0eBumKl3x4QEd2v8vXghWmviv72uX/8Jf9Fs14HyIlMnwUi0NnNVP/43fO6qgkMuF0L4YIy1hVLaPg6cb98Z8bkQHQpkQKrI9Lpp9ce1x7urGu5eVeh1Gwgl/3c9ePGYH1Yw3PlAb9xIkwVoHAdip+RhTVP8KwSp6rlJkdeAiaXEpB4L1yLVAvHLvY+EmLwQr1a63nwKM3ifVtHO7JKaoQUZ4Y/ZDMVAyENv4VnO4O0iGeszTuNipMGNQXWihxr72a8TY5dRMsDjDkVaGKUxcKwBv/AdseAuq69vwm/o3OOqTsPpWezQPMWJrfzuUcpADdi5A64lA5fbCxbZc7EOsUH+PPw098GPiUDTcXxvrmt4S7rIZ0a9cFCZf9UKiQYY3H3THXtVWQBsDhF0DytV96vXvNXPBrMiPMDbkCzTRncTx319D83eW2lZ9VcQt6ZpEavNxTz+vT5TEIX1HGbRSIWG1a5A9TjxUY/JhHW4/1ouFhq+PJqK8swzdK+Xzz2vDV4HHAVI7HKoDbfgq3rtWDeuC3MTXYqcwY22Tm/n252jNZH2IOxbeLY1rsRoh5Aj6Wyq5GXPr3UOnkjEpAVHqrdr9aHU80ioxvGIE2nnEwk1lwLy7ZWB6dAvfqRbB0/AYRrMMX5lH4saN9jh3OBFavVHqPyuT4ecO9qjinn3bmtwSFm/Ch/sSxba72ivxbcuMvxulXI4KLgrcizKhr+KIeEzv5pvv28NkQZSUGkyO5knQoKp7Lhcwoh+IqwfmUjgf/WyLOA8SVeh93NJayoS/S61G+7jNkFFtOdVZ1x8uoqtQ5KxUg9ozJV3ehAZnl8FBrkWM2QFObd+GvNkYyWyJYRiGyRSOtDJMYWPvDgxdJlKBFTDjR9UCvCHfhrA4A5otT8C0k5IYEpSrD/T+DajWQ9wdpdyOzeqpqGW+jV7Hq+K3gDKZ/pl3fKW2KbcT7BHmmGwqY0nTzICJ3f0ww+E9ITKaR27G2aWTYVPopIhMpqub9LhL9iYSzcopsHewPfYPc4JGpRAC7M2dibgVmVxXl1+QcG77EeBYCkiMhP7aNqwPdhFCrLy9HmfbX0YVp2evryUPopdPV0blXXXxwSUv+CcLVoqYkmvxtNpBuN7pErqUfiJYLU7Vp9pfxZ1uF/FNzSB0Lh2Dxo5hWGQ3G3+rfxRRqXvm0hiun4Iluo44HqQTgpUi1c3Kq3HxNUcMrFow66h9N2qFQQ9Fctf1zjqSW8VdDj9ZALoqzoh9P67pxALZJiYTEiPFVRScxL7xQqVcTlMe3xZXV0yVEJIHx3UL9JPb53g1cdtPdhsX3KegQ+xGSbB6t5T69VbtknPBSgtO2z6E3blFcJBpcdRYCw9e3Ad5p6ksWBmGYXIAi1aGsQZIkPSaBbR8R9z9XL0MnymXACYD5p9LhN+SRJwPSxZB1DO0xXiAnCnt3FBNHoSNms8xQ7kAC286os2hmiJCkJ6x3mFCeJDI+TWqpfTgg+RUzUyYOqgVpslGidsNA+Yh8lBy70BbgGrGCGqfkhH3jgArhgBL+wJL+0n1r5vflRxtM8DHVY7N/e1SCjon7CuANGE7V8mYSSaH6vENvKXYJCb2O1peh4PySZruszDlmheORDiKfYU+m0yfRlSMwMUOl3GgjT9erBCRfbkpLQhQX9Xjc4Ewaj8iE+nN3sPnYmKvpuhQSQMnjQLlnFVY088RK3vZZZiumx9QO6mHsXohWv+qegyVT34qfY97vpa27/I6KeqeXJDbsBTwoXKVuL3B2Aq16jQskO1ishGtZmkRyNUul/sFtVBKFq1GE/CFf/lcD/WtOA0a7K8DuS4OPynnYbPmM7gm3pd+p6lUoN1kQOOUsw+jEgzqtbxlIhBxU0RXJ+tHYl+zhahVo0aut41hrPZ8OtMPpuVDxN0Xfj+KiLgCcte3AaIS9fhw1XnYQYvuOzuJsUuZkzCZwunBDGMtkNihPq72bmJCPVL5H6qqIzEqfhzitWr0XR+P4bXt8F3r5DoRcqbsOwc49ScQsA9DlfvRWnEJExPHo9XBmnBTm1DJXotazom4FOMA/zi7lBTPGupQgM4n0YGAIQlQ2mWaLjluSG/8tuIRJijXw2XPR4Crm3BALvKYkut09ckRVwtJ0cCFf6Xa0dSv1cUBj+OAHVOA2v2l/ovpoizV3BXwcVPiTqQeRosrUX5DJi3Uw/XY75ikWgWNTI8eh3tiedP7qOjw7EJ540M3cV3O3oD1TW+irF0uP5N6AF9aBSRJtbYoVV1yQ6XtFpFpKTpNdjYFjX+EEX9f1MIOOsxx/gudAg8+FZFLgdI9KzTBm7HhUCguwmCWY0OJ1zHQjk+Tz5ML+9eCbK8emV0xpEYOo5gWqD3SI0m03lRXgywJ+OeuB2L0Csz0u5+j2u0v/SvgxINEjFf8iyGa/XCTJf8+VO4opejTfpKb7dk/LWVxcKuxKb7UvwrXcr7Y3atO7v5vDGPVmIHo+08iYWYTTAV1DrQBhFGhyP0xwzkpGCCjcOpFTuVIbl6FvXlWC5+NGcbahCuZeZTwBdaOQlvTCZwoG4NOjz7AY6MDll9JEi/5tpX6SeSNXl+9B3B4JsrHPsRK9Tc4ZPLDSkN77I5uhAvRJdL8ifGqzRiuWyPdoZY6mQhWCx72cujqjsC/F6PwonIfzOvGQGbSA/VfQpGmalfg9CIh+FPGgHrY3tr7RMhW6Qz0/ElqOUMRoBN/AOeXA1fWAcFngTYfSu6+qQiJl1K5a5ZQFOC2d5McoC+txrvK9XjJvBfzjvaGW8W6eKea5GaaF3aHuYgWOnRCnVf3bu4Fa8xD4OL/pHEkM6vW7wGlaxVKLXSC3oTBW5JQBo+xQP0L6htuS+6M7T4GytYF4kKAmGCp7VHAfiAhArjxH+hbM8tVuFb/cyzulWx+xTwXDqxfgHYx+8SCwRGXHpht+Z3LKdRuJpk1ze+h/YmSCE5UYn2wG8J1SixpEJBhlgCJ1RmXnZEQFoABinX4XnPjyZPuPlJ0lRZfcgMJVurvHHQGiWY1Jurfwg5TU5Qv6YJt45vn7rMYhrFJyiHiyZ2/uwMqB2D8SRaumcCilWGsEYrkUe3i8iFwj76G0x5fYHTiO9gT64Wll5JQy0OOl2qkOnxJGPSeDZxYAPnt3WinuCgu0XDEPmN9aOX2KGUP1Hd4hBKPz0vvoab39YfnaHM+aKJG3atjYDLI8bJyjzCOEmlvjV5FkYXq0dy8JQfhy8ki3kJZP6lPom+7J4/R6me/uUCNF4AN44DIu8B/nwDk7Ex1yckk6Ewiot2sXAFWX5AIpKiPa0XEnVyKUrowfK5ahvBgV2x42AC1Pd1QtZy7tF2UcqSLBbRx0kSaavLoQtCqrmNp8Xn+sXb46Iq0wuuiNqG+Wy5Tlahm78paYTYjeqx2/jLNuDxPDCYTmq9IQmySEQtUcySHVup5O3R52u/UAvXDvHsIuL4diA+HrPFI+JG7dwG4GDMZpJLrEnD9/kPUO/+lyCRfIBuInwfWyv1QUfouOfEadVCbdTjc+iq6Hqsu0n0PP3JC9T1+aF8yDmMrhSLRIMep4AS4RfujofE8PpUHAMmBXSPkMHo2hrp6N6BC4wyN2DKD/Ae23kyE1+nvUd9wQQjWN/Qf4ajZDyPbVsbnPaWMA4axdTZfCsG1kHSZTEwa3GRxT+70+R3Y9La0gMrR1gxh0cow1kql1im9XOUxQfhTNgU/2b2MOUnd8OWRJAyr5pDWUIZW6MhhuO4Q4NZucXFNfIx+yS6oIv3E0queUltJtOaC3zo64JWtb0AHJV5X7gA2vyO1ZvAbhCIJTUSHLJEEa+o0pnL1gDoDM5+okmh9+4xU5xp6GTgxT6pxk8nEhFX0AQVQr+RziC5W7gCnSq0R578HcWdWoizC0Q/7gWBIlxxwxeSNqYaROGeskhIQfb3io9xtR7g/cHWjlCJGLTuo7pb2x3ziUrgRejNQ1U2Wo9rXf64YEZNkQAPZDbRQXJUicKP3AyWrZPwGqhOnRQy6JIso7pH5nKCxNuqRsPF9kYp70eSLQYNeFKUJeYKyJmhxJvoB5GVcsbPFdbx2zhcHwp1Eq6aDYRqUibiDNxTb0UYeIr0n+U/dUFRFmRot4VqrExQOJXL33zCYMG6PDqr7hzFVuRxe8nDRK/Y13SSElWqBEyMboawrt05iig9fb7osrumMWMmjYNqx2RQemZyfmBRYtDKMNUPRnjcPA1vfg+zqRnyEJfBS3sdnhjfw23kN3m2YwcSOHG8bvgLUf1lqj0K1ewYdYNBKkzmKIpIgziXtvBQo4aDCV4mvwFUjwwDjf8COqUC1blIUqyjiWV+6ZEZqAUMC3QK1p+jzG/BnJ+DeUeDcMqDhCLGIIGpVZEDM8/KgUKjgVLs7nGp0wv7jJ3Dr5jXUNN1CXXkAnGWJSDKrEGp2RwhKINZsDwOUMEAOB2jRSn4FteX3sFb1BebLe2O+qS+GeseJ/q85huqir22SpibU/qPluzl3VM0B00/pMfeM1K7GMgGSy+QoYS8X7VCoPvbFGgqUdXxyLCy+YoAr4jBHM0d6gBZyLII1s+/UAj2W0eNM7shunFPG2wFx+2ajgfYUdGYFVpV+F986P0N/R8oeIPMv/81A2BXIvdtgST0tAh48xN0HD1DPcBEeshjxUjo2zirqIqhEU7Rp2gzVSpXM05/8n78Biw/fxKfyf9BKfUU8FooSWOb1BSa07402VXJRB8swNsLnferA2U4lBGsTb8krgcmcqyFxyEN+SbGCRSvDWDuOHsDgxVI95Y4pGKbcjyryYHxw7h1MqF8x8/YdFCks30i65BMjaqnw6xkDPokfhj4e56GkusD9PwDdvoNNQpNuYcKU8PTEu3xDoPevUjrPpZWAU2lJwAt1ZUZE0nM2oVCo0L5Va3GhSfT4E0kwJsUhFvYwm2Ui7ZJ6oTpr5PByVqBOSTmuqGPROWQRakYfxFvKTRin3AWZXVPA0BBQ5sAoifr8Xt8mpRt7NQdavZerVMrsuB1pwtyzUh23ZTFAjK7ZhIgEugDHg4BZp4FapdSY3UGFCk4yBEbr8JdqLjwRLtUcd/8hZ98pk39kN84WURuwDw7HZoiHZhiG4b2OPs/2d9t9ApxfBtzcJaWs0wUy+MIM0XFXBhgdSkFfsz/sqndBy8xaXuWAA4FGfH0kHr3i1mCTciNUMiP0UEHf4l2U6fABPiDBzjDFlN5+ZVHKueAN92yFTzdcwjoerixh0cowRQGarTcfJ9JHjCtfQWPDDWySTcJP697C+wPa5j2VLpe8XV+B2Wdk0EGNkY9fwWLNDJiOzUVSzaFwqFgXNgdNOrNKFW04Aoi6DxycARyfI+rpZLLGIhwYkYhCY1gNJYbVcEJkkgNUcsBBSeWZGe0jFAGaBNxvA5z5GzIyJrpzAAg8KUWgyYTGqczTAlafKBlYhVyU7pepA7T9MF8FKzF+r05yWJTLcW6EA6K0wO0oMy6Gm3AyxIibkSRcjeI118J16L7GgAkNNXhHsR4dFedhpu9jyFLJkTun3ymTP2Q3zroEmO6fhGHdeKhhxmJDFxhrDRDGb88EpfVS6zAymbu4Eri9V4rPu5RPWcRTlKsHBZmr5ZG/Lusx64we5bQB+FU1D7VV98TjMZW6waXvDKjSmbMxjO0jA0rVQExcHFwSHwjTO3khGPAVFcQCrILOl9LvXYTaE3j2Nus2D4tWhilKVO0CxVtHcWPeMFTT+2NS/E+YuSQIPXoNRY2SBX84q5VyvNXQTkS/DpjrY7uxCXooTuHwog/Q4MMttreqmpNU0Q5TJOFKrrmHf8Yvyjb4TP8aEgx5j+DkF+457XFZsQVQoSlw5yBw8V/JVff+MelCkKESTfLJZMlsBLSxT8yc/MjQ60Xp+XwmWpvcO7WMUvxf3O2oHy7Q2ZtO9qoU06Xpp4xYcC4RJpMRhstr8YFyrXhORuZk5dItpnD67/Mhm3E+cPoc6u0fAzfosMvYEH9oRuJI8/xLKxdlEuReTYZl5HZOiy95hOpVV90wYc1NAy6HG2AwmtBUdg1/q2fAUaZFosIZ9v1/hUsddptmiiFRgZJ5UP/5uHb6BJqdnYSJnavCw+kZ0vxtHDd7Fe581x0ILgssAM42/xXaXVK7LiZzWLQyTFGjhA+qTDqAXb+/jS7Rq/Ge7F8s2fgIa2qNxqQmdkJYFiQfN1Hhg0YKLLlqxJbLA9BDewrNcBltZh7CyU86wE5dgK1erHXJtO/vgLs3cPBHDFAcQj3ZLRyP+4g6t6LIQFHSyh0An7bAvSOSYKX034RHUruf9FAUtuloqX1MAWGZ88ToMk+1piyDqc3kWO+fgI8N8zEYB8Wi/zaXwehZ1Nsy2Rgh0Un4evtNxF3Zgd/lP8FFloizpirY4PkBjnRNZyyXX+TSUCk1ZKzWd6MOF8Mo4v+EtrILWKCZKfr/0vFiP+BPwDnvophhirRgndMU0Etu883IQd+sgVZdOM7xRYZHN9JeMzmCRSvDFEHkKjt0ee9PXFlXFTUvTMMryl04fC0YjS5ORJ0K7ljYRQ2nHLis5hUSCm/UkeONWrWgX24HV1MCyibeQs+59tg7sRWKHWQ8RBFX3w54+NfLqCx/CO/bk4ASI4EavQqlT+kziVcSrnQhSLBSJJlSLCmaKldJxlsUySpgyPCLiEtvahUfDsQESQ7FaskEbKX6J1TGdRjNMnxjGIHqrT8p8O1jcs6WS6F4a/kZDFXsw2zlIlH/eQY18bDFp5hTw9Uqh7LbOi1uRuilOmpaL7RX4u0Sx/HG418hMxukXs+Ufk7u0wxTHKEIKwnWAQuBktWwyz8cX+wMxnsOBX9+KJI4eEjnrXWjnzymcmCRn0NYtDJMEab2gI8R7VMd6o1j0FpxBRtln+H1oEmou9gTy1+wRwvPAo56yhVQlakOPLyAJvLrWPbQC/ciEuBdTO3tT5hqYHTS9/hZPR9dFGeBk/PF2KDdx/nqqPtcodTgQuq3qjNK1yaSDEnRkksxRYGjHzz12soUkTU7YLz+HRwy1cWFOqXz5mbLFAj/HAnAFOVyvKncIu5He7ZFo47vWfVxcSNZsDb1VGNJdyXsbm4FTv0pSVhqi9XvDyn1OC6c9yumeONWEVg/Fo0T9HiMT/HR6gvoWK0kpwg/NU5ewPiTiIoIwfC/TkEDHVa5L0abE2PwF4YXyldXlODO6QxTxHFt0A/2b+6ByaUCfOUhWK3+Ci1xAS9tScCNyORZf0FSsrq4qim/LwKKK87ksEGotUMihyajdJ3DVMI3lpxFjMwZb5o/we1Gn0mRycDjwNnFBb65toh/hLT/vux6BVg7SjLWIcEqkwMeVQGXCoBKEqBJ7jXQT/e1EKyEY/o09dRutswzEx6rhX9InLjOCZ+qVqQI1tgaQ+Ha+SOrFqyEi0YhGkS10h6E3faJwKmFkmBt9LoUWVKqeb9iGILs3cP94R5/W+pVbjbBlLr/OfMENy/oS9fFZaM3rhq9oIgMgGvsbR6hHMCRVoaxBcr6QT56L7BsIEqHXsIy9TRsMLbE8LWvYtOL5dL0sMx3HKXehhWUMYAeOHD9ESZ3tYEm2blojULR5YELTiE+MUmcuyd2qoqwio2hd66AGvvHAlc3AJ4NpTY5RRgS5k1XJCHRYMa+wfYoXYD71YNYE7R6IyrIwjEu+hfAkCj1GG41EajSKW3016hHQGgiAn49lPkH5sQ1mKOxOSYiXg+twSSuszVgC7mEeg+WiZsf6ccgLrYb5ll7ynzCY3zutg8tojajQvwjgNaulHZAl6+BpmOepPyzGzXDMMxzgUUrw9gKZATyxnZg73cwn5iPfoqjaC+/gJmrXsT4gd1R2qWA6q7sJaOTCqoYgDqhhMfCJkg/GbUImtTPJ4vZbr8eRZJWKwRrk8qlYTIBo5ZfQGyCC75VdcUrip0I3z0TffArIo1q6IxmsQpNLQHUChk0Shlal1dgTifrdl++9MiMR/EGcbvpsnj0rKLGtFYquObUpTgX/HPFADuZDvPUs6DSx0qGTyN3ZVw/SBE7WVKah5K9jXPnGsw9XLPkfmQius0+giSdQdR4EqTdJnSshvc7iS6oT0MHw9YPIDObcELdAquT2kMWoEdYvKpAFz3yRMxD4N5h4P5x4NF1DKbHZEC42QXyZuPg0WHc06ny7EbNFENO3YvC3YgEuEWFowuAqyFxqFXYG8XYPFZ2xmAY5pkgg5weP0A2eg8eu9SEmyweX8n/hG7dm1iy94yIlOU7yZO4MngsrrU6XcH8necNTUadSj0ROhZBEx/xVJqpRiWlosrkCtwKj8cvO68hPiERcpjxnf4l3DeVQilEYoLhb+j0eml8zGZxnaQ3IjrRgK23tHh/f3rHIevih1P6VPfM2HZLi7qL4/Hxofzf7j33DPhetQh15XcAjQswbHmWhjc1yjhCqZLSTe3sNIhOTL2tOYQWIiilm3u4Zsiv++4gMUkLM7U+Sr6YjUbM2uWPs/ejM37T9a1A4AlAaY/S7UZT112YzSZ0Wp2IJIOV/E7QatOlNcCGsVIq/yOp9QQ5G0/Vv4HW+jm4WWMcwg3Fs1afYdIL1nfmbcQ/q9dhy27qgwx8uuESDxJT4LBoZRhbpHxDlHj3MM7UmoyH5hKoIHuEVwK/wLLF87DiUrzobZlvuFagLtlw1oWhEh4K45KzgTGwOSyCxtHjKWGz7I1GMNH/3GxEVGy8iD65OGjwcc86GN+tPvb7vCde95JyLzZ6zMH7DRX4srUD3mlkj6G17FDeRRJba68nYfe951CHnMdelceCJCHY3luDNhU1QoBQ/dLKq0nosS4p//arxCi8HL8YAxWHYKLT1JDFktFHFlC7lIMftEW/RpUw/6UGIm31mRcqmDRcDpKOa0d7O7zUwhcvNveFTKEUizMvLjop9pGnoJ6/RLm68PEsje/a2AuNGKs1ottabeEvcOmTgIMzgLP/iDq8EI9m+Nw8Fk2T5mCA7mtsd+yL+a+1gr1akbd9imFsjNDAW9ij+QhbNVMxWz0XOpkdosxOhb1ZTDGA04MZxlZRKNFoyCe4du9VnFr+PvrotuEV+XYEnj6ND48PxiF1W3T2VePTZko4P0t7HJrgl6sLBJ9Db+VJ/Gboi5l7AzBrUO3sa92KEmpH/HggBL/v8UetCh7Y/GbTlB9QP08XfNitJn7ecRUOGjWmdPLCiOZeqcTPeOBSGeGu6Bd/DH4RsUCtDwDHUuJZmuzXW2pCos6IMTsTceFVh2f7TgqAmeeMIiJFaaE/t1PBw16OBL0KAzfrcC1cujRYasTcTnawUwJRWjNojt+hgjxn6cNxYcDdg8D9EzCH+2OUQkpAfdTyM5Su3DFHdaiebo6Y2r2KEBcejtZt8lMUeRApmZJVL+uC3snuzBXcNJi+/Rq0Wh0GLTyNDWMbp+23allsoLpQAMNrKXEzyg7/XEzCvSg9xu+VY17ngvudoGNr6FYdguJMqOQiF47qvX3lqOKuAKKDgAM/AJF3YJIpMEvzJmYFtYRcRIOBnvUrYs7Q2rgRmoCAiHj4evBiBsNodJFwkGlxouEMNGvcDDsDDHi45R4PDFPgsGhlGBunpnc51JzyL64f3Qi3Xe/DSx6OWeq58Ddtxrf+w+F3rS4GVtdgWisl1Mo8CiWf9kK0vqnchDWG1rgS7Jgzg5YixtLj94Rz7bUHEVh2Oggv1C6d8n98p4MP3m7nnXbCnhq/QYBTaWDFUCD0MrDmdcl52bsl1D7tsKqXO3qtSxCRp1/OGPBFCzWshdMhRsw9mySi6NU8JMFKOKjk2D7ADh8dlGPV1STEJhkxYmtat2WKxn7czA5v1c9ERIZeAS6vAR6cTu6GKcoIcclUCctNXfFD+7G5qkOl78PW9jtrIUEr1TOXTjW+Db1c0aZ6ORy58RAX74Wj6fRDeL9zFQxpUA5K+j1JEa1hKe/5qqUaVyJMOB2sw7bbOsS2VRXIIg0dS13WaoU4JsLigJPBwIrTUfhIuRIDFIeglJkQZnbFW9p3cTqxhkg/UyiVmDW0Pnr7lZE+SAaUd7OXdkyGYQQxTr6AZ30khgTDjPuIt/eEiYyDkyj/RiY8G5iMEWMjoxwVBYwuXqJMCDkzYi/WsGhlmGJC9ZZ9gcZdoD06Dzj0M2ogULgM/2HohVn+A7H+hj3ea6zBhAZ5iFD5tgdubIdjuD/+Us/A9+6zbDLS9WnPGvhk3SW0rlYWDSq4PiXMMxWsFnzaSmZC2z4C7h+TaufocuZv+LlWxCyH6tibVB0Xg5oA8IA1cC/ahCGbE0UasEwmx59dnhaEP7ZVo2lZOeYfuotO5hPYaWyEAEjN5el9M04kYt1NA1b31sDdEnU16oBTi6Sax2Siy7RAhHd3bNM3xE/HYsXE5wdL7XBmKbvs3vrcKOlsh7CoOJy4+xjuDtLx7WKnwFttvBCZoMOVwAg8io7DlLXnMXntBZR1d8JrDUtgHL1QGwskRqbUwP/dTY06f1MfVDMmHdQXSLT1pW26FMFKKfhJRjOqJ17AbNXvKCWTanD3GBuIutWHZg+4OtmjW+2ymNanhiS4k6HfMo7eM0zmJEGDbV32SLdXncNPQ+pzj9Ys8HBS4+60Hsn3+mHb2WBoV6/jXSwbWLQyTHFC7QBN+w+AZm8Ae74BTi8SvRN7yk/gc8Pr+OlEfTirZXitdi5/GuQKLC7xDrqHTUFNeSDm6D6Di3IbyEjYMtmzhejXkEae4kK9KbObxI5ZfgFHbj3Cpreao3KpVIKrbB3J5Tk2BPDfAlxcLfVyjb6P/riP/updCI7zAJJ+Bexcn/rcS+FGXIowIyjOjLAEKTL5XkMlPJ3k+R6l+vSoAcuvaIWwIAG5uo89vF3T/R3Kowy9hMEPNmKw8qSIlk522AC0nYQw90YYsFmLB9F63HqsR8MlRrzmp8bUJjIoqY6Q/t8UAas8GEF1xiLJRXKgLROZCOCC+LuxCUlwzlK05sAVmMkXmlQqga3n4xAZE49/jwekPP6/0w6YO7QO/rvmhnXnghCbmCTqXEMjYzF9Tyy6u1SDj+4G8OAUULWreA9FVjt4q7H/nhbbA3Qi1Zwi9/nFRwd1OB4kGYS1rajBktaRwPnlQMB+sY8mulbB1XpTEOfohw9UTuhaoxRck4V4ejh6zzAMU/iwaGWY4ghFO3r9AlTtIqJ+FaMD8Y96BrYYm+F/RzuimUc91Cybc2OFqxFGfHHRHUswFas136JE1FVg6QBEdVkMrcrN5lKFs5vE3gyNw85LD8Ttjzdcw5rRjZ9+kXNZoMko6UKOxPeP4c7ZXbC7sQmesgiYDs2EvPMXKf0gg+NMGLJFEoDpWXUNaF5ejbmd1Cmpu8/KiP/0OBJIglXqa/JrJ3s0KSu5JAuMeuDuIeDqRuBxqsborl5AdCCw52uUbvQ6Dg/tjxmnlZhzNkkY3fx9MRGVry3GcMVxQK7CtfZ/IKp8hzR/u6yrRmhh+q9fCNWjdXWprRJTuEzqUhl7/UNFyxsLJqMR0XEJmLD6Cn7oWxM9a5dCos6A//wjsPNqKKJiE7A+vi7eV90AAk+miFYk10Y3XKKDzGzG9ycN+LbVs6fERyeZ8OUxA9ZdTxL7Twv3GCxx3wSs3yGM0gQNX4F9p8/RyAw0StW6imGYvHPybhQPH1OgsGhlmOJM9R5ApTbA/mkwH5+LXooT4mL4Tw5tGT9oGgyV+mNmwf0YE3qtSxQRt9uyCjB0/gY49CkQfBa+qzsiuN2PsKvaDsUGXTwUZ//Cx8qTWGHsiOplKmf/HnIkrtkLbt5dMeybGtik/gya4NPAzZ1AtW6YfVaPX05RTakUWaWop1Ih9XhN1JvEpP9EkA4Nl+gxqIYGP7d79sm/IlU5kl8pFXr7yCWhSimelNp8eS2QKLU5gkID1BsGtJwAuHkD2z6UWoec+UuMx6QmIzCwigLv7tehfsRWDFfshMksw28lpqKmRxspkpqKRUcfCMFB9VG+Xp6AuoB6DDO5wtvDAde+7JzmsbdXXsLms/fxOCYeY1ecx9Qe1VG7nDP61y2DvnVK4dUl57Db0BDvY42oe4dBCyilBR9aYHGxk4ta6Ifxls6vuTNZOhduxvlwE06HmHD8oQExiUax79SVB2CKZhWaJ14Crid/Nhl6dfwUKN+Iv3mGyScqeThADR2Gn39Z3N9o/hwfr72EzjVKwt3BerwZrAkqp2jy/X5ooMWFCj+hU5IBKzBIevLRjScvdPAA3LwKbTutDRatDFPc0TgB3b6DrFYfhOz6Dfp7x+AlewRl2AVgxwWgdC2g7lDAs2FK1M/C+TAjhmxOEqmkJKSW9HBA6fK+QLfvgQPToYgOhNeOUUDix0DL8cUjoqFLgGfMRQx4oTe8Dd7o2cwLiAuXai+z+f+Ta2klWWjK/btBwRhyKgFhcYaUiCeZGo2rp0ozcZ9yxIA117VCvK71T8KNxyZs7KvOvsY2M+JC8Y/vOayNegCnxCB4R4UhasljlJDFpn2dUxmg8RtA0zGAQ6po6As/S1HYxwFAhHQCruwux5b+dojZeByIAn42DMacB9VgWnoaJZwd0cjbDbfC4nE/Ig5moxTJa+RbGp5uLFitmd+H+sG3pKPo1So3GvD1lqui5nt8Gy+x/+kNRpRMrh+VIp1pxWmcVrpft6Q8x5HUjw7psfeuFl6mYNSU30dlWTCqQY6KUCFJqUFj+XX0Vxx58ibv1kCHKcI0Rhh2keN0cfgtYpjnQBNvN/w7qhnqLZNKBhQyE3RGAwzG3C9EFRdobAwGPVTQQRlyHnT2jDa/CoPCHsp1o5+8UOUAjD/JwjUZFq0Mw0i4+6LsoB/x78VozN1yFGOUWzFEsR+asKvA7i8AjypA/eFAhcaiH+eATTpcCNEJHUunptmd7NHOKzl91L0Swjv+jPBdv6BW3HFg/3dYffQyflWPThG+5FT8y8A6qFfBxba+AbUD7DpNhl3iI/Ss0FRq9ZHK3TbLt97ahjmq2cLRdA+aYNz13tDJJAFXyU2FVb00KO2YdnJP4/hTOzW+aKHES1t1uBQmXdqsNGPfYE3uHaEptXfLRMgNWgym+6kyggmdWYlYRy94dHwXqP8yoMxgJX3XF5JgVdlLgjYVLlpJlD8s2w7mYDnkZpPobbvnclrXYScHeyx4KesoP2MdvN/JF6183fHyX6dg0Otx9MZDnLzzCGPa+EJuMmCKZoX0whovAMonixBJBpNY8KKfhJae2e+n43ZrER5wEe8q1+JX1XXYybLpm1p3mCRW3b2l+7R4lMNjkWGYnNOo4tP+C0zueAgPTK+6Ak1LS2UMvniAygcnAgkRLFqTYdHKMEwaF9YXm3ohXN8Bn+4sh98N/TBauRUvK/bAPuIWsOdLPKoyCNvdXsLF0GTBagZeqKpBGQcZwhNMOBRkwqyzetyLMkCOt/Gu0hMTleswWLcRQQkKzDIMelI3+fdpXPwsix6cRRGaDLuUBexcAL3UP9TSRzRLAg7AbsMbkMlMWGtsg0n6MTDKFHC2U2BKMw1erJHu55qiRVc3ANo4wLMBnCs0xub+dnhztwzbb2kRFKNHm1VmHBlmB2VOI670ZR6bI1I4E1wqI6ZcSyQ6V8JdcxksvGTC1Wg1omVOMGvlcN5mj99dY9GuajqX40trgONzpNut3pNqXC0YklJSin8Z9QJmqFzx1/FALD0RiAeP41DC0Q5tq5XC6FYVUatc+qRhxqpI1R+X9vlmPu7iWB659AKO3ggR4nXu3usYptyPGvJAmNXOkNV9Mc1H7L0vCVba7RqUzro9RuDdWxh6/2+011xIecyotIesdC3IS9cQZnDQJyUfc45A49eBElXSHnfsNM0weebUvSjcjUhAUHAcuvA45ju0+L/wfCIWJt+vLYvHVtuxAskXWLQyDPOUCyv1HB3VygvfbL+Jb455YK6hLyYo1+N15Q6UvLUG9sZQ2CnfQpKB2qAA225pxSU1NAU1yxT4RzUMWnlJfGxcIMRrqFt97NDVEzVwMfGJWHbyAYY3rWBb30Lq3qFOpbKP6pDQ2/AWZCYDTqqbYlLMGCiUakxrrcGQ6ul+pqODJNfhW7sBA7nsAvDfDDQeCdTujz86a/CpvQxLLyUhNNaAaosSMKi6Gl+3VMIuu6jrw/NSD1mFBv6d/obWSfpeKDY2oRZwLSQOfxy+h9DHsYhNSMQrfx5HXe+SGNOmEhpUcEEFVzWw9QPps6p1Fz1o0xB6VbrWuAozMPqfjWntjXidEb/vvYnhzSvivY6SgzBj5aTrj0s4qJX4d2QjnLgTiVH/HMcIwzq8o1wvnpNRzTOVIqRi9U0pouCoUWS9sBIdBK/Dk+Cl0EFvVuB/xg7Y5NAff74zCK5OmaSPR94Tae7QOD85/thpmmHyLFgHzTsizuu1ZUGYqAE8Xbl0Iz9ZPqoFAmKemFpdPXUnbY2rA9e3smhlGCZDaAI6rW9NISpeX3wO30WOwkWdL35UzccgxSGoTGZEtJiIGaeNwgyIwiWWqElJRyXe8FNhbF3LZLQPcCJYiK0vTfPQb8AOjF0bIJxFv9vmb3uiNTcRnYM/Anu/lW5XaIKm7T/BjhgFfF1lT9eknl8BXEhOtSTcfQB7N8ngJuyaEK0EubDS97DsilRvvOpaElb5y9DcU4V6pRVoUkaO5uVkcFKn+3xqwwPgcbk2KYI1NeQoPXtQbZy+H43f9t2GTqfDpfuPMGH5o5SV4sUaH7SXnYP53jHIavUHXMtLb354ATgyS7rtNzDlM7ddCcPsndfE7dm7b2B4k/I25TRts2SxjzeTXcU5j8+gfHxT3Dd7NoKses+nXncmRBKtfqXS5aCnh1rVGHWILdUQn8gmYss9JWQxQKtfjuDslA4Zp8BbyunMSNOiivcthskhUYFSaiqtNwZKvgqDm/qgq5saOAhhuMbkb4p1o1QL3EdOOqetcVVxfSuL1nxEr9dDpcq8byPDFEV8nM3YP6ZachpgV9w5VA8Vdo9HX/lhHDkXh5lN3kIPP08hjh4lSiWrpRwymEQ2fA14cBqauIfwPjsDb7f/CN9suoLEJC3mH76Hsa2T685sgZxGdE4teiJY6wwCGowQaY5V3DN4LaVnX/j3SRSz2VjAtwMQsA9Y2h+Iupfm5d+1VmOMnxLvH9Dh9EO9MGmivpXHg4D5yZnADcqpsaFvqtVyXZy4MlAkNAsaV3TF3yPq458TwdhzLQQGo1H05aRJzXjt2/hX/S3qau/AvOszyDp9DlxZD9yWGs/DoyrQ5Wtxk/aZ8cvPPvlgkxG7/R/hxSbJQpcpWvs4tW7aMRm4uFKaXNi5AU1GQubT/ikTNzIQi06SJsL9qmQxFaFJ873D4mZA068xvEQt2J8PweqTdxGXkIRXF58T0d2ncCoJ6Og3ywERj/XQGkw213qLYQpUsM5pKqXbA+iusEdb+TtCsHYpGckD/xwIRkn812ELevkqpWjrutHFvr41f7vRF2O2bt2KqVOnFvZmMEzBpgGSiG3zImaX+hJasxKtcB7tzkzAd3+uQNU/49BmZSIGb9YKg5WnUNlJLVGoD+eNZWgu94ezo724v8c/vPh9c/eOiR65Ar+hQKPXpLq8jCCFeUJITRy064CZZadJ7TtICJC7MxH7UKoZTYW3qxxr+9jh7CuO6OSjgbu9UkRvLT1Qz4fo8P5+Xdo6RRKtquzNsehz3mhRAcvfaIyfB9VFz/oV4ebsiHjY43XdJASYykIWHwZselsIVmpxs9jQBbWDPkGtaSfQefZRLDkRlMZLlraLUkWZIsjDi8Dc5kKwpiys9PtDWlhJJ1iJWL1UQkB08MpiKuK/TfT3jSndGAklpH19YP2ywlmaOHorDKHRyWnyqSFBnZyaTxFWjVIurhmGyQG0WESCdcBCYPha8dAS9XR0OThIEk8U9aN01dQ4eMBk7yGWL6UlTCYrLONEY/bUWCaT6OApuZ6XrMaDyTWt+cOyZcvwyiuv4OWXpR5VDGPraYC9Br2Bpcero/75L9FYdhVTVSvQ2XQWU/QjcTuqPOZdUOK9RhlMREv4StGXpCi4BR1ACccXEJeQiLCYDCadts7ZJVILkIotgAbZ/HZQbV74NejMCnwUNRChO6/h4M0IrB7ZCEpqO+NcThKtR38D2nwAyNKOPfXDXNT1SYSJIpy9NuhwNVwnWuQ0LivHS9UVQOgl8bzeQRIE2XHodiTm7LsJmTntIkWMqiQ+c/sBv0RPRBlZFPxNXpisH4Vz5qrSC5K0uPVQiy82ROLjF2pj+clAPHgUg85+FdCnbtkcDiBjVRyZDdAiBR3fHaYCpWtm+XLXVAHPx0lmlE2fmED71LllwKVV4m5otbTHyOvNK+BMQBhN+bD1yiO80TLzXoYUXeUIK8PkARJLnvVFxG/e1uOY2KU6utQo9XR9JS0STQoQkTB/Huhsod+jez9YSiYG5HzEHhXvHq6cHvyMLF26FK+99hqOHj0Kd3d3REdHw9U1d9bfWq1WXCzExCRXYjOMlaYBUsSidfNW8Oi4D48vLIPL/qloBn/sVE/CelMb7LlPkcN06b5GPbDvOyFYtY6eCKn+Cko8isX9cCAqPlW0L48UuePIlNyuo0ydp0Rmen45HIr3KV3IXFLY4lMq7rk7YWj8wwEceL81XHv/Cvw7DLhzAIh+AFTtCvi0lUxoMomSbuqnRsOlJsQkGTD5QCKaG67CN/y6MGEK983ZSXTFycAnglUmh6O9GrXLuYqeq3P3XEcf2bdo5XAfYV6d0axCCYwo5YBLD+Nw9WEsTt99DKNBj593XselzzsJk6g895Vl8o08H0e0sEKQa282gpVQpor4P07K4LNO/AE8OCXuBtcahUeVeqd5SUknNTQaDXQ6LTZfCslStDIM82xQxO+K2QdRbrUBT08ezufMhUgVanMPVxatecVgMOCjjz7C7NmzsXv3bjRv3hzr16/H3bt30a1bt1x91rRp0/DVV1/leVsY5nmTJnLRZhTg0wDY9y0Ut/dikOIg+sYcAY52klJXXcpLl1MLJWdalQOudVgkonklnSSxmqCTDFmehSJ3HFmEarooZXpuRRpxIzAc0ACP5W6YNaQeVp0NwbGbIYiKS8Cnm6/jt6FdgYELgXVjgce3gRPzpPH2bAhQJNaO3HrdAGdPqd+u2kGIhp2D7NByRQJMJiNMFNUCEFT9VejtS+Xov/A4LlGsrE/qWRtvta2U8niVz3YKMaJz9sLAId3TiNFyrnboWqMk7kSUwSfrLtGPKX4/cA+TulTO2zgy+Uqej6PE5Do3u4wKsjNBpA2bEaU1C6MlkTJ/a6dk2kXIVbjZYjoe+fbL8O21PF1w/m44rodY+QIVwzDMszg3L72L8pgOd1mseKyKLAizMbfY1bhypDWvA6dUYuTIkWKlt2NHqc9k9+7dcfDgwZT0u5xGDSZPnoz336c4ypOVbS+v4rMTMjYA9UnsvwDTV2xFi8A/0VZxCbi5U7qkRibH1bbzkOheXdy1uH6mrmvMK0XuOLKIVuqzmgVBcUA5ueTgWNGrErSudni3QyX4h8YI9+Ww2OQwVZ2BgE874NJq4NxyKdX3wcmM/y6laZeuhbJmE5Y6RsBdG4wqpnuA0h7Btcfk4j8hfXN1y6etgTUYJSHey69spr+DPh4O0KhU0Ot1iEx49kg7kz/k6TiiWugEyUFaGG7RJMox+4WP0ohEe8V5NLh2GTh+AdBLNdVEVNmWuN9wEuI96mb6fg8ntbg2mrJe+GEYpoDRJwLLBkFvMqHR/fHQQoPjH7eDu4N0jDJpoXNe8+kHoIEWZyrOgYrOk8PXACrJ5yM11BuXlvdaNW2CppXcktvh7C2WQ8qi9RmoU6cO3nvvvZT7kZGR+O233+Ds7IyWLVvCLFqAZF+MTsKXLgxTJKEJa3LN6z3Hupinn4y2ituYUe067GICYB9zB5qEh4BciVvNv0e0Z5unP4PyBOlzcuK4ayvHUflGkhvw1fWAdwspApoRZjOGKA6ImwkedVIelmVkdOFYEmg+TrpQtOreUSAuTKo1pOswfyD6vuRETBc6EdI/ybrybt2JMNiVKID/LFNUyNNxRMd/6TpSyyRKUadLicpAxeZSTZy9O2BfAlCqpV691A/44XmcsrsrvT9Z72odyiGsyiCEVx6cYcslhmGsFMoYuncYZHWm146CFjIYjPmxHG2b0NhotTrIoYUq8GimWVckUC00reSGwQ2l1OyrUuUEdvmHw00fhSbebigOsGh9Rjw8JMcvEqienp4YOnQo3nzzTVHrWq9evRwLV4axCXdhheTOeUhXHfurDoB3CWnVUC5s880wqdKK0sSUtGAzEBkIuHs9k3C1dlGf5v/WeCRwazdw4z+p1rf7dMDpaQOkEhGnUVN+H3FmO8yK7Yh+BhOuhcYjOkH7pFY4I8Ffrp50SU9MMHD3CBB0RqzqLjofh/OP1Qgwl8crnn1QMYf/rf03IyCjOUkWP2+bLj5ErNaALjU8UCLVivut8Hjs9H8EnV5qecIUcWjf7vkjcHUjcG0jEHxeSlOnSxaQo/RFsw/8nVuiRut+SCxZL3MH7dTvM5kQGqvHhcDofPxPMAzDWAeVPBxEHtPqk3fEfXPyY0h1TczadR2Xd+qwZlyrYiFcWbQ+6wAqpSG0CNPBgwfj7NmzmDJlCmbNmoWqVZPdMhmmGLgL1yzrhG1iwdCASWsvoFq5Eni5cXlUK23/VJro6fvR2HM1WAT5StgrAKUqpa1OhiLPFkR96v8PjUf/+cCfnaSo59b3n3ZdTYpGzVsLxM1lxs5YdyUaa66cEj1XLWth1Uqqn/7srHDxBOoOli4ArkdfxOZHgeL2pNUX4OLkgD71yqJnzZJPfWdJeiNO3IsWbr+x8YliG2ht2DfVSZRwtlMjNiER0XEJ2HDmHtafvgeFUglHOzViEpJSzJtERaMZ8PPMvsUOY8XQvkemX/WGAXUGALpE4P5h4PY+IPKuFIGl2iuaelF9u287oEpntFhlRqjOHqCnNhvRuuoDeLo96RscHqvDzbA44S6epJN6DRPp14FLOBahDAuGYZhsIAFKQpRSgy1CtUmyKKXrGYPqAZuBLrXL48plKYWYRSuTa+zs7NC7d28sXLiQnTCZYucuPKG9DxRyGX7ZeQMGgx63Hj7GV5sfwwQZHDRquFG0LXnCGfw4TrjgKhRKrBrZENCYnghgEnnxj2xDvGbQMigFMkcasQFYMRQIuwL89zFQo5eUKkwplsHnoDSbYJKrcNBjKMyhMjFmNIaO9nYY36Yi3mrqlvFn55Af+teBRq3Bvyfuie8sNj4By48GYOnRAMjlCmhUSqgUcsQn6WEyGtIIhpKuTpg1xC+N0CAOftgav+y5g13XQhESGS/aktB7Y+OlyCppD6VKiWplXTGhgy961s5Zix2mCOzndi6AuyNQpgZQ78Un+76CnMTuSMcyZWQ4lcLa8ol4e+VlnL0bBrnJiMPXH2b68WL5JJ1YlSuU6FWvPL7vU6PA/3sMwzDPExKhmQnR2uWkzgC1PZ2Ay8XHE4IjrQUAGTM1bNgQbm62H6pnmPSQi+yYlhXx2dbrWH0qEHq9HnKZGUlaLUJStdKgSahcocD2d1rBu4xT2g+hia5Bl3GE0gZaBqWBTGve+E+KtJKJ0rVNaZ8vUwfyTp9jRaXWiIiMxoIzUajnXTLfhB5FU7/pXV1c/ncmGLP33EJwRCzkJBBMRmi1Rli+NRKsFOtycbTHl71qYmCDchl+JplvWD6TOHEnEqvOPsTt8Hg083XHy03Ko6L704YTDGxrP0+dZeDkCLh6plnAqeBujw1vNsG9iARMWHUZlx9EwpzKlo0crsu6OaC2pwvaVvEQEzWVQgalXAaNUg4vdzteHGaYfHaqpaidW1Q4ugC48jAWtbnDDWMlsGjNZyw1rCxYmeKMUinHtL41xSUiTofNl0Kx70YEwuOeNGR01ijxXZ+aqFLa8em6T3W6x2wdik4N/FNKr9z9ldT+o8YLQNXuQNnaKWLAo4wjJvcsuBnEsEae4kLOhifvRuNqSKwQmhHxOiEYOlYrieY+bk+EQmb1uulo5uMuLkwxI32WQSYLON7OZmwa4QOon+zrDMM8Xy5cuYIvl+1LaanSRQ1MWnMBnaLK42F0+mbKDPP8YdGaz7DpEsM83ZbitRZe4pKrus/sIpS2SJXO0qWQoUhpt1qlxCVP9boMk5tjmPcjhinU6Gpo4C103fMCtmqeiFO93A6Pzc74dde1p8yAMkTlIEo/6HXsG5w9lnEyKx2eqtPPKS5xAagt08M+oQwA2w+Js2hlGOb5kFVULqu6T+bZx7eg4O+NyY/9jvcjhik0wTpo3hHUkd1BL00S3tW9hTEDe0qp+A4e+DXaOUMzoKegY3/qQ1F27v98/wtFklLOGtz74YXkewNz/wEOHmKRoNnZSdiqAQz77IGyywCHkk+ep9IjG4NFK8Mwz4esoinFMaqa3xRGtIq/NyY/9jvejxjmudetEjdu+AvB+nIVPRAISbA2etJLvYmbZAjEWBluXsD4k9h11h9Ld5/CX/a/AstSiV+Vg3je1oQri1aGYZ4PHE3h8WVsDz6uGabIRVYpIuqJR9it+QhTNVohWEno1K5cqbA3kckpbl6IclPgoEmH6VVXoGlpIzxd7VBb9RBYNxq4f0xqNWZDUVcWrQzDPB84msLjy9gefFwzTJGBIqwkWAc39UFXNzUcDmpxu+0sVK7R4NnEjT4JWDUCeqMJze6Mhk6mxpEP28DVQZXf/wWbIDpBj1Y/HYLarMMJn4WirRyGLAVUadvHZUclDwdRF7vwfCIWihpZHTaNqI16FGkl4WpjUVcWrQzDMAzDMAxTTGhayQ1dyuqAg5AEq2f9Z/tAsxG4uRMkUROTXkIijNAZTfm1uTYHjU1cQiLskQRVwO4nY5hLmni7Yc24VmIx4uTdKKw+eQc3tO6oRyI1IQK3/c+h8sGJIo3YrbJzkU/1ZtHKMIx1UhjGQtYOjwljLfC+yDBWW6uarXESYzM08XZL+Z5Xn4QQr4AbAiNdsGd3vDBq2rJ7L27tuo4Zg+pJKeBFNOrKopVhGOuE22DwmDDWCx+fDGOVtaoWKG2UonCphat9QjBqy+7ALUoNKCMLZVuZgqFScqowRVtJvBLl4CxaF81Wz5Ue2Fy004VZtDIMY52wwQuPCWO98PHJMFYTXbW4AHepXR61PZ1wJTgOu64EIeq2GlCVwpWHsYgIf4iuJyaI1jaUFiwgAUO1rEyRp0mqVOHUQlbl2lGkB8/adR2ft1CJNjlF1aSJRSvDMNYJG7zwmDDWCx+fDFN4RAXiyu27+HLNBXjIYvCHapbkAnwL4tIFwEQNJHF6EKid/LYEswYj9R/jk4FtRC/WoiZamJynCj/BTbgMXzHrEF6ijLRQkWzSZFDY42iTX+FRqlyRSBtm0cowDMMwDMMw1kZUoBQRS03CI2DlCNTWJ4h6RYv4uN5pCapX8hb3KbI6ac2FNG97sbkP3DzK4B2vKqjNta7FkkQHT5EaTAseP6w9hPmqWWh7XBKwRqU9FMOWAQ4lpRcnL2hQND808BY0ukippQ4tdqQmg4WPgqqvZtFqhZjNlJUOxMTEFPamMIzVYTkuLMdJZvBxxDB8HDFMkTofxYYCcaHSbRKr68YAhsSnX6e0x5H6szHzSDje6lAVHetVQzm3CrB8uldV4MOXvXH/sfTeiiXs0ajiE9GQ7/NLMmbTSv9HozYBJpgQGxMDjTlZVTNpv+ZYLUzaBBiRhBhZ8r5D34k69w7COSEhLlb8vUNXHyAhzhVn7mtwILEqplVZBEdjDM77X8fv6nlQLxqQ8h6D3A5bq3+HLRcCMVs1Fw4ynXg8/Z5Dr9vddhUS7cuJ+0FRSZi378ZT9dVLRjZLsw/m5TiSmbN7BfPcefDgAby8rDtEzzCFTWBgICpUqJDp83wcMQwfRwzzPODzEcMU/HHEotUKMZlMCA4OhrOzM2Sy1GsVhQetgpCQph3KxcUFxRkei8IdC1pni42NhaenJ+RyeZE6jqwB3n95DAk+jvh44d8h2ziO+Dedx6eo7z85PY44PdgKoS8sq5WGwoR26OIuWi3wWBTeWLi6uhbp48ga4P2Xx5CPIz5eChtb+B2yluPIFsayIOHxse7xydFx9Fy2hGEYhmEYhmEYhmHyAItWhmEYhmEYhmEYxmph0crkCI1Ggy+++EJcF3d4LHgsijK8//IYMny8FDb8O8RjyfuadaApQvN7NmJiGIZhGIZhGIZhrBaOtDIMwzAMwzAMwzBWC4tWhmEYhmEYhmEYxmph0cowDMMwDMMwDMNYLSxaGYZhmAybfTMMwzDWi16vL+xNYJjnBotWhskneJLP2NJEKCoqqrA3o0gTGxuLwMDAwt4MpoCIjo7GmTNneHzzmcTERHHN59Ps2bp1K6ZOncr7YAYEBATg2LFjePz4MY9PBty5cwe3b99GZGQkihIsWpk88/DhQ1y7dg1xcXHFfhRpAnP37t1iPw68XxR99u3bhyFDhqBVq1YYPXp0YW9OkeTixYtYs2YNZs2ahcWLFxf25jD5DJ339u7dixdffBHXr1/n8c0nQkJCMHz4cCE4ZDIZC9csWLZsGXr37i3mYUxabty4gePHjyM0NBSTJk0S8zMm7flpxYoV2LhxIxo2bFikFt+Uhb0BTNGETtQHDhxARESE2PnXrVuHKlWqiBNNcWTz5s0wGo3w8fFBcYb3i6LNqVOnEB4ejl9++QU3b97E4MGD4eDggNmzZxf2phWpCQFNvl9//XUx6f7mm29ExLV8+fKQy3mduKgTFhYmjpNXXnkFzZo1g6enZ2Fvks1QtmxZ6HQ6DBgwQEyovb29xTFUXOcVmbF06VK89tprOHr0KNzd3YUoc3V1LezNsgooekiLSi+99FJK5N7f318cqwzE2JCgt0ToaQ7funVr/PHHHxgxYoTVn6Ose+sYq4R+AK5evYoxY8Zg8uTJ6NWrV8pJxmAwoDiRlJQkJvg0QfXy8kJxhveLop8STKv2FGWlxZeuXbtiyZIl2L17t1ix5nS9nIsaGjuCJtv16tUTE8qEhIQC/f6Y5wMdC5bIhJ2dnbhPx8h///3HX8EzYPl9+eKLL9CiRQv069dPpDCyYH0Cza/ee+89vPrqq9i1axeaN28u5mIkQhiJmJgYVKxYMWU4ypUrJxZCLl26JI7V4s61a9fS1EF/9913QqxOmDABe/bsgbXDkVYmTzu9Uvlk15k2bRqcnZ3xySefiFUbEnDWvlqTH1BklWpKpk+fjn///RcdO3bEo0ePxOonRakodaw4rcLTyVOtVqO47xdFFZVKJfbpLl26YPv27eIYr1u3rnhOq9WKySNdazSawt5Uq4ZqgceNG4d27dqJ/X7hwoUYP3487O3txW/EV199JSJKTNGEvkf6Xi0TZIrs3Lp1C2+99Za4zJgxQ2QnMLnDZDJBoVDAw8MD8+bNw48//oiBAweKcywJD6q9o6hicYZ+k0eOHCl+g+m3hOjevTsOHjyYMobF/RxLv60016BrOj4PHTokStjouKXj8u+//0bnzp2L7WJI5cqVxfmoTJkyGDRokHiMFkJosZWOt8uXL6cR/dZG8d67mTyt9Pn6+oo6gdSrMlOmTBHpUpRycP78+WIxsnSC6NChAz766CNx4iD2798v0lFoDOrUqSNW94oLdJKgsaCoQ3HeL4oilpVXShOqUaMGzp49K+5TxHXo0KFiMknQogzzNHTMBwcHi9s0EaDJ0c8//4zffvsNlSpVwjvvvIN//vkHJUqUEL8RTNGCUuYtdXFUBmNJnadIYKdOnfDmm2/i9OnTon6Z0sGZnEFjSmVGhOU3hrKXdu7cKc4lffv2FXWbtNBjOb6KOzSvIJFhgcQ8/c7QYjkJ1uKeEUMLHPTb6+joKOYk/fv3F1kQtP/QAuKFCxeKtQ9LvXr18Pbbb+Pdd98V40GlLLQYtGHDBrHoNmfOHOveh8wMk0M2b95snjBhgrg9a9Ysc+fOnc2HDx9O85pJkyaZa9WqZY6NjbX5sXjnnXfE7cDAQPPcuXPN8+fPN9+8eTPlNaNGjTLXrFnTnJCQYLZV6P976NAhc1BQkLhf3PeLogZ9dxYMBkPKbZPJlHJ7+vTp5jNnzojbP/74o/nnn39+zltp3Vy+fNn8+++/m1977TVxzKfm2LFjZn9//zTj+u2335rDw8MLYUuZvLJixQrz7du3U+4HBASY27RpY27fvn2a1506dcrcoEEDc3R0NA92Nly5csW8ZcsWcY48f/58mue2bduWcrt///5me3t789GjR827du0y63S6Yj+2er0+ze/0kiVLzH5+finjmPr3uzgTHBxs3r59e5rHaJ+7dOmSuTgTHx9v/ueff8Rcbd68eeazZ8+aIyMjzfv27TN/9tlnZmuGI61Mjgv/+/TpkxJpoQgjRVy//PJLHD58OOV1lCpLK9CUlmHrY0Gr70SFChXEanCtWrXEKrwFWrGy5TQUcugjQxJaLadIKqVFUi1fcd0vimJLlg8//FDURVkiHZaIK+2zlElAUK02RQvj4+NFFKl27dqFut3WBNU2kskSpVuRkQVlVlB06MqVK+J5GrMtW7akvJ7GlcaS0uYZ64ciDpROSN8vHS8WqOyDPB3OnTsnasAtUDo9nRudnJwKaYuLBpRefeLECbzwwgviPEHRn9RQmQLVIVL0h6KsVMNJbualSpUSZQzFHUt5lmVuQedWivhTZhNlAdjqnCMvUGYLZUQQtE/RvlecyrYygjKB6JgiA1HKEmnQoAHc3NzQuHFjcb6n489aYdHK5MqpjsQICQ86Ob/xxhsifZBS3ywmFFTzRikqZFBh62NBJ1NLjysSrpRaSZNVqgckSADQCZZ+KG0NaklANaxUt0sTjx49egjn4Jo1a4ofQaqJoP3CMha2vl8URWgSTumMVOtDJyuC9leLmZqlNoos8SmFjxZkyCm8W7duhbrd1gTV/7Rs2VLcpjozmoDTcT9x4kRhjkKTcRIw27ZtE0ZMlCJMvxNcF2z90G/W77//jlGjRmHu3Lniu6Tfe/rto8UJas1CCxK0eEfClfpB0vlh7Nixxb6uMDtorGjBk6AJMqVuUu3q8uXLxWN0zNDY0qKBn5+fqLUjkZte3DISdF6lhXMXFxfe91JB6cG0z+zYsUPUttLvb/v27UWZBoOU+Rj5j3z//fdijKjUzZKqb42waGUyhU4mH3zwQRqnOnKItdSgkIU41VbQSZomaevXr8eiRYtEb0db+1HIaCzIkIrEa/pJLNX70jiRORPVDdCJxNaghQtq4WGBivqpToQmc7RS9+mnn4r6CNo/bHm/KIpY6lVookjfIfVltayyWlbxU7uAWwwaKOJECxTMkzG8d++ecE+nLAPL2G3atEmc9D/++GNxn0Q/mfXQhLxt27aijQdj/dDCAv2uffvttxg2bJg4Jqg3JkX/aOGGFudoAeLYsWMiu4TOC02bNkW1atUKe9OtHjo+LE6uNK4UCaMFAfI/oEVhioSRWKV6RKJNmzZo0qRJIW+1dUPGTGRgRUY7jARFnHv27Cl+gylLkG5bs8lQYdGtWzexiG2JtFozMsoRLuyNYKwXip7R6hStxBAUNSQDJoqspYbSpCgVjn4QbPVHIauxsLj20eFkOQGXLl3a6n8A8oqlDyWJHfqxo4kbmdGQezAZIJBIpRU7Miehx2mibqv7RVGC9ks6TikzID2Uyk7Pp280Tt8fpZxZnISLOzRGtEBjObYpTZQm3mSGQvs+QfdJwNDiFkXpLI+ldl1nrPf7PXLkiFiMIOg3nlpBUUo3pcZTxgEtzlFbFlqUY+OlnI8rLfJaFr7omn5b3n///ZSxplR7EqdUfrNgwQLxGPdpzR4eI+ZZKSrO09a/hcxzh9I+SZxR+k716tVFmmfqEw+lTO3duzdlR6coJOXE06qzrQmTnI6FRbDSyh6tujdq1MjmBKtlLMhZltJuZs+eLSIRVatWFTU1FGmgqBz19rx48aKo+aWVO1olt7X9oihCqauUKUATRIr4WaKD5NZJkOszuQhaIq4EZRNQ+jAL1rRjSKl4tF/TbwC5K1PUmrIqLK6UJE5pIYfuW+q4WbBaP5QpQ7/11CvUkkVDtYKUrkoLdBbPAooCUsr3/fv3xX1L/TeT9bh+/vnnKV4HlLlBi5w01pbYCZ0zKQ2YnOap9pDFWM7gGlbmWSkKgpUoGlvJPDcookLF2VSjSvWKdFK29BSkEwiJFErfIfF28uRJsaMXlZ29oMeCThy2mriQeiyofovSHSkNbtasWaIPK03iySiDJiE0yatfvz63KLAiaKGBhBUtOlDaOtWUWQxkqK7Fkg5MwpX2cWp7Q2mRbCiT9RiSgKX9neoeg4KCRJ2jpc6dhAxlGHAdd9GAvjdaaCAzOartolply+95v379xKIs/Q5aHqPUekuJhK2eAwtiXGkcCcpEotYblLVDx5AFSg2msaeyGhZjDMOkhn9pmRQo558iZVSL9fXXX4uJKxkLWU4cdLKmC6XuUG0ArZqmft6W4LHIeiwoVTo1NBmhCZ3FwIQmIhmloDLPH8qEoKg3pf9STTGZZVE0nL7TW7dupUQBLY6BZIBC9WZUI2Vr2QL5OYZkukOlAA8ePBCOwRRppR6B9PtI4pZqHyl1mBZyGOuHouIWcyCKjtP3St8hZdNY6jCpNOSll14S2QlktDVy5MhC3uqiOa5r167Fn3/+KbI+yICJ5hD0e0PHzV9//SXcmtklmGGY9LBoZVKgdB3LCZqiaFS/Q46XlEZIIoRWk+nkQgYVdLIpWbKkzbpg8lhkPRZUi0T7BU0yKOJM6eEUpaNUaYtDn4eHR6F9f8wTaLJNtZaUzmpJZ6QIIB3P9P0RVOdKr6PJOKV5U4qexRWXyXwMaWJNwp+u6TkyQqGoHAkaWywRsGXoO7QcD7TQQAs3dIzQ4ixFAimSTqKVzILot47qldn0Jm/jSotk1G6LDGCojQ3VDdMYkwcCZexQyQnDMLZNQECAuKa5pKVcKTvYiIlJgSIv5I5Iq5wkRik9kEQrrYyuWbMGM2fOFE7BFmgnozofW4THIudjQf1oKbpEKcNkWEKTdY6yWhckRn/99VchRGlSSItPZJZFZjLUX5hccC2utrQgQXWsTO7GkKKu1AKMKbpQujfVX3700UfCMdiyoEOLcpRhQs7Qlsi7NbeFKErjSgKVoq0MwxQvunTpIspsKINp8uTJOdITLFqZNCdhi/FBdHS0MEIgUyESLX/88Yfo0UouwbbeK43HIudjQc6olDJMxhls1lO0oPRWigRSVJwWHi5cuJDi2MnwGBZH50xKX6X+4ySwKFpumURRiiu5oa9evVqkgDP5N67kvr9q1SpRS2+LpUYMY/FEIKj9DkUYKehDtzN7LWVzEJRav3DhwgwF3ccff5xG7GX1Pvqb9ByVt9DtQYMGiXlcfkF/m9oapu8+QH+Lghv0t+g2lcxYtsnyOF1yHACjljcMkx6DwfDUY8OHDzcfOHCg2A0WjwWPhS1hMpnE9aZNm8zXr183x8bGmkuWLGneunVrYW9akYHH0DZ/2+l73bFjh7lWrVrmhg0bimOD0Ol05gkTJpgTEhIKaUuLFjyuDJOWMWPGkIObuHTu3NkcGRmZ6RBNnz49zW36LUrPmTNnxGel/pys3pf6Ocv25BerV69O2Z70pN6G27dvmwcNGpRmm2j76XrXrl05+ltc01pMyc7l1pL6RIYtlogbuWDaYusSHgsei+K0T1uiGdRHlFZjKT2P6pDJXI3hMbR1qAaZMkMoUyR9ii8dG5SqRkZBlC7frl078fr58+cLoy1Om+dxZZjMmDFjRqbPUdkUOWnThXwjMossUsSSauctUESUHrPUf1qg+6kjpdm9b+XKlSgo6G9lFDVOv820vZZIMDFp0iQxDvR+ihrnBO50Xkyhk3N2ze7379+PCRMmiBM7GSiQIYUtGovwWPBY2AJUbxcbG4uXX345pf1SVul2NGkfMWKEcAtmwcpjWBwgg7FffvlF1FHRhI7cgclAy5LGSscMXVP96rp164SxFtUqk7Mtmy7xuDJMVlDpVFbkJAWWxB+l9VqwGBRRWq8FSqtNL/Syex9dk3CmEgcSk1RPmhHpU44J+q0kkzRK7c0NlnTk1NB9+jz6DbakC6d/TVZwpLWYQS59VJtDkGC19GfMCDIYoQbq9DoyHrE1wcpjwWNhS5AxFjmbWupSM+sbbHnMz88PN27cYMHKY1gsuHr1qjCLo4gDRVIHDx6MgQMHisUbS59VyyIPiVhi3LhxYnJHRlsMjyvD5BUSkSQ26ULCMH0UMjUkSC3Q7xVlf1hEZFQWBqhZvY/EKkGLb3Q79WtTQ4KValMt0HZSpkluBatlWzPCYr5kibxShDi14M4KjrQWM8henvpuUmrgyZMnU4Rr+ogrnbTpBE5i1VbhseCxsBWoJVXr1q2xY8eOFBFKJ5n0EVc61inaRCeTF154AVWqVCnkLbceeAxtFzoGyESOWnYRzs7OwkCOUn+p53Tp0qVTXkvHCEUV9Hq9iMIyPK4M86ykNiAisUaLYbSIlhOhm9rcaNWqVdkKyIzeR+Jw+vTpQoRauoCQGE0PbSMJSFrUIwFLr8nodc+CRcyScE19nRM40lqM0Gq1ol8anZBdXFyEcM0o4kqClVKDf/vtN9HmwRbhseCxsCXc3d3FIgz9+FMGAbUnyijiSsf54sWLbS5rIj/gMbRd6BigGtUBAwZg/fr14j71GafvnM6HFidbglLs6dyXm5S14gqPK1NcIeFFEdPUFxKGqe+nrnFNHVm1OOlmFW0l6DNS17/u3r0bQ4YMyXbb0r+P/g75V9D8gAQviWUSv5n9fXofCVvqnfwsgpU+h6KqqaH7z9QqM5/Mo5giQmr3ww4dOpibNGmScp8cEi0sWLBAuIHZMjwWPBa2hl6vF9cHDx40K5VK8/z581OeMxqN4jopKanQtq8owGNou2zfvt186NChFHdbum1xzSZny5iYGHHbcs3wuDJMTpk0aVKGj9Nc2s3NLeU+Oeamd/5NDznq0m+S5fV02bVrlzinWy70GfQ3U8/VM3ofufvSJf3nZzbHp/eQyy89nxuX4fSSkrYjvfMxjUNW/+9s/0ae38kUWSyT14yEq1arNRcneCx4LGwNy4TcIlwXLVqUMmFPvTDF8BgWd2hStmbNGnF75cqV5rp16/KiDo8rw+SraCWRlnoBmQRk6tYv9DtkEZqW5y0tYNK/N71IzMn76DXpty2rbU2/bTkVrhkJ8fQtb6jdz7MgS/5DTDHD4pZIdOjQQaQBk4vo3r17hVET1fwUF3gseCxsDWpRRa7f586dE46B1Lrjr7/+go+PT2FvWpGBx9D2IV8HSgtu0KABateuLVLqe/XqVdibVeThcWWKI5SWS3WjGUGOuZTeS6mxlJ6b+nVUP9qkSRPRAoZSdtM7ldN7qFVO6tRk+q2iv0fpvpTKS6/J6n30t2kbLKm5FiOk/HAPps+mdGRKh6b/A/1fLEZPFiMneoxSlNN/dm5h0VqMSS3WyHCCdsoLFy6kmFUUJ3gseCxsSWilhlrg0MmGhCvDY8g8QafTiR7F1M7tzz//ZMGaT/C4MsWRrEQrkz+waC3mWJxFZ86ciWbNmqFly5YorvBY8FgUZWhFk3pKkji1uIFTpNXDwwMVK1Ys7M0rEvAYFi/ISZ8WaZcsWcKClceVYZ6JrNrRMPkDi1YGMTExSEhIQNmyZYv9aPBYPIHHouhw8+ZN/PHHH3j99ddRp06dlMdTt7theAyZpwkPDxfO20z+wuPKMEx+w6KVYRimiAtWqlcdOnQo6tevX9ibUyThMWQYhmEY64b7tDIMwxRxsUW921iw8hgyDMMwjK3CkVaGYZgiyI0bN4SJDDkPkvspw2PIMAzDMLYKR1oZhmGKGHfv3sXff//NgpXHkGEYhmGKBRxpZRiGKWKEhobi8ePHqFmzZmFvSpGFx5BhGIZhig4sWhmGYRiGYRiGYRirhdODGYZhGIZhGIZhGKuFRSvDMAzDMAzDMAxjtbBoZRiGYRiGYRiGYawWFq0MwzAMwzAMwzCM1cKilWEYhmEYhmEYhrFaWLQyDMMwDMMwDMMwVguLVoZhGIZhGIZhGMZqYdHKMAzDMAzDMAzDWC0sWhmGYRiGYRiGYRirhUUrwzAMwzAMwzAMY7WwaGUYhmEYhmEYhmGsFhatDMMwDMMwDMMwjNXCopVhGIZhGIZhGIaxWli0MgzDMAzDMAzDMFYLi1aGSceMGTPg7u6OLl26YPfu3Tw+DMMwDMMwDFOIyMxms7kwN4BhrJGAgABUrlxZ3J4/fz7GjBlT2JvEMDbDmjVrsHLlypT7UVFRaNiwISZPngw3N7dC3TaGKYrQIuuuXbsKezMYhmEKDI60MkwG+Pr6YtKkSeL22LFjxaSaYZhng46jwYMH4/Hjx1i9enXKxTLZ9vHxEQtGDMPk7rjixR6Gyfz4oCAEnXuYog2LVobJBBKrFlatWsXjxDDPOHHo1KkTpk+fnmHmAj1eokQJETFiGCbnUBkLHzcMkzELFiwQi6Fnz57lISrisGhlmCyirXSxpAgzDJN3aJV74cKFKcdURnTu3FlMLjjayjA5hzIV6NhhGCbj48NyfmGKNixaGSYH0VZaoeOJNMPkfaWbalbpkhWUNkxwOj7D5JzTp09nuRjEMMUZi6EmZyMUfVi0MkwWpE5jJPMYhmFyBwlQqlul9N/ssKRvZSduGYZ5cnyxYGWYrM8pBEdaiz4sWhkmC8jcwvJDxynCDJO3KGvq+vCsVsMpm2HQoEE8zAyTQ7ielWGyPj4IWthhs7KiD4tWhskGi+Mc19oxTO6h1jY5EaIkbGlSkZOILMMwElzPyjCZw/WstgWLVobJhiFDhqTc5mgrw+QuNatx48bZvs7SBmfPnj2c6sgwuYDrWRnmSaq8TCZLc7FEWinjJ/XjdJ8perBoZZhcpAjzDx3D5C7Kmro3Hhlh0H26NGrUSNyn/nnU6ubOnTtcy8owyYs9dGzQhY6TzFp1ZFbPShN1d3f3HKXlM4wtzdXMZnPK5cyZMynP3b59O81zGbVdY6wfFq0MkwMsJ3+aJHCvL4bJGTR5Tm1+QQZLdAzRhR63pARTtIjrjRhGKkP5+OOPhXkZpTaSKCXhmpGjdmb1rJRiT6+nRVZ24maKK6nrWdmszDZg0cowOSB1TR6nCDNM3qDJNE3E6UK36biiyTktBKWOyDJMcYWOAzom0i/iWCbgOalnTR1h5VZtTHGF61ltDxatDJMDaLXaMolYtWoVjxnD5DLKmhm0Ak7ilVpK8QSbKc7QMTB06NA0gjUjsZpdPSsdT5aFVo4wMcUV7s9qe7BoZZgcCFZKz7IYMtH9rCYSDMNIq9w5bebepEkTcc29kJnizLRp09LU2tF5xpLem34BiBZ4shKkJH4JTrtniiPcn9U2YdHKMDkQrJRuRWnBlgkApwgzTP44BxOWyfepU6d4WJliCwnT1CLTcp6hqGlG6cJZLQrRMUU15AxTHOH+rLYJi1aGyUaw0ol/0qRJ4jFLtJUjQgyTNdTCJqdRHktaMJvGMMWZ9D2KLeeZjFyAs+vPSsdfTtLzGcYW4XpW24RFK8NkIVhp0k2mGBZSTx5YuDJM5lHW3EyYqR0BwfV3DJP2/JK65Vpu0oPpvJXT9HyGsTWo3pvgY8C2YNHKMJkIVlqp3rNnT5rnKOrKKcIMk31qlqVONTcTDOrZyjCM1OOYyItgtRxTHGlliuuiaWa14EzRhkUrw2QgWGlSQI2pM0pvtBhlpDbJYBgm56mLqaFjzWKakbq1FMMUZyw1eRZDpfTPZRVBmjFjBiZPnlyg28cw1oplEZTmbxnN4agPMlM0YdHKMBkIVktT94xInSLM7W8YBhlOqnNaz2oxmyGRy+nBDCOdiywLohmZKWW1KGQ5f/ECEFNcyaqeldLuPTw8snw/LfpQv2QSt3ThUjDrgUUrw6QTrGSGkVWUKLUrI7sIM0xaLFHTnGQh0GtogsDHEsM8IbsFn6zSgy1O9wxT3M9BGWUjUFspi7FmZvPAiIgIURNOc0G6kKs99xC3Dli0MsWe1IKVUn8z+0FLjSVli34c+ceMYdJGWWlCbUnRyorRo0eLa5ogcJSVYZ5gWRhNf37JSrDSJJ0iQ3wsMcUZy/5fokSJpxZ00jt0p54H+vj4iPekfg1FWWlh1ZKuzxQuLFqZYo9FsFJ0Nacr1KkbwPOqNsOkTc0iEZpd3RClX9GEgI4fTmVkmLRYalLTH0cZ1bPShNsiWNl4hinuWEq4Ui/40GN0jGR2fKReQM1okcjS7pApXFi0Mkzyqnb6H6vs0rcsq3GW9EaGYZ4cT5SNQMI0PSRUySXYYnaWegGIYRgJWsihBR3K5qGFVUvKY+p6VhKrJFTpOKPXsmBlmCfHDjlwk1ClCx0jmS2O0kIQnZdImKZPzafMO2rJllOPBqZgkZnNZnMB/w2GYRimGEATa5ooWBZ0aDKQOtWK2kg1btxYrHpnZDDDMExaSJguWLBAiFVa6LFkBRE0kaaILB9LDJN3SNTSuYoWUflYsm5YtDIMwzD5AmUdUCoVp/syTP5DgpUiq7nJCmIYJmvc3d3FdWRkJA+VlcPpwQzDMMxz78/KMEzuyK4/K8MwectmoAwgxvph0cowDMPkC5T+y7U/DFMw8KIQw+Q/2S20Unq+paacKVxYtDIMwzDPDJ3UebWaYQqOrNrdMAyTN8h3gbIY0reXshid0THHta7WgbKwN4BhGIYp+nDqIsMUHCxYGaZgIEFKJkwWgerh4fFUlwjGOmDRyjAMwzwzp06dYgMmhikgeFGIYayn7SFTOHB6MMMwDPPMUCoVpy4yTMFAkSDqI8kwDFNc4ZY3DMMwDMMwDMMwjNXCkVaGYRiGYRiGYRjGamHRyjAMwzAMwzAMw1gtLFoZhmEYhmEYhmEYq4VFK8MwDMMwDMMwDGO1sGhlGIZhGIZhGIZhrBYWrQzDMAzDMAzDMIzVwqKVYRiGYRiGYRiGsVpYtDIMwzAMwzAMwzCwVv4PrcDeQk+/V2EAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 970x970 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fisher_res = bilby.core.result.Result(label='fisher_samples', search_parameter_keys=list(samples_pd.keys()), posterior=samples_pd)\n",
    "# the posterior data can be found in https://doi.org/10.5281/zenodo.18339164\n",
    "pe_res = bilby.core.result.read_in_result(\"intro-pespace/autodiff/pe_resp_params/outdir_extrinsic_params_LISA_noiseless/extrinsic_params_LISA_noiseless_result.json\")\n",
    "\n",
    "latex_labels = dict(\n",
    "    ecliptic_longitude=r\"$\\lambda$\", \n",
    "    ecliptic_latitude=r\"$\\beta$\", \n",
    "    polarization=r\"$\\psi$\", \n",
    "    coalescence_time=r\"$t_c$\", \n",
    "    )\n",
    "\n",
    "fig = bilby.core.result.plot_multiple(\n",
    "    [pe_res, fisher_res],\n",
    "    filename=\"corner_fisher.pdf\",\n",
    "    labels=[\"PE (noise-free)\", \"Fisher\"],\n",
    "    titles=False,\n",
    "    quantiles=[0.05, 0.95],\n",
    "    corner_labels=[latex_labels[key] for key in fisher_res.search_parameter_keys],\n",
    "    label_kwargs={'fontsize': 26}\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9ee42a32",
   "metadata": {},
   "outputs": [],
   "source": [
    "params = {\n",
    "    'axes.labelsize': 18,\n",
    "    'font.family': 'serif',\n",
    "    'font.serif': 'Computer Modern',\n",
    "    'xtick.labelsize': 18,\n",
    "    'ytick.labelsize': 18,\n",
    "    'text.usetex': True,\n",
    "    'text.latex.preamble': r'\\usepackage{amsmath}',\n",
    "    }\n",
    "matplotlib.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a41dca32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "mask = np.tril(np.ones_like(cov_AET, dtype=bool), k=-1)\n",
    "cov_masked = np.ma.array(cov_AET, mask=mask)\n",
    "log10_cov_masked = np.sign(cov_masked) * np.log10(np.abs(cov_masked))\n",
    "\n",
    "im = ax.imshow(log10_cov_masked, cmap=\"RdYlBu\")\n",
    "\n",
    "labels = [r'$\\lambda$', r'$\\beta$', r'$\\psi$', r'$t_c$']\n",
    "ax.set_xticks(range(len(labels)))\n",
    "ax.set_yticks(range(len(labels)))\n",
    "ax.set_xticklabels(labels)\n",
    "ax.set_yticklabels(labels)\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(False)\n",
    "ax.xaxis.set_label_position('top')\n",
    "ax.yaxis.set_label_position('right')\n",
    "ax.xaxis.tick_top()\n",
    "ax.yaxis.tick_right()\n",
    "ax.tick_params(\n",
    "    top=False,\n",
    "    right=False,\n",
    "    bottom=False,\n",
    "    left=False\n",
    ")\n",
    "\n",
    "cbar = plt.colorbar(im, cmap=\"RdYlBu\", pad=0.15)\n",
    "cbar.set_label(r\"$\\pm \\log_{10} \\lvert \\mathrm{Cov} \\rvert$\")\n",
    "\n",
    "for i in range(4):\n",
    "    for j in range(i, 4):\n",
    "        val = cov_AET[i, j]\n",
    "        mantissa, exp = f\"{val:.1e}\".split('e')\n",
    "        exp = int(exp)\n",
    "        text = f\"${mantissa}\\\\times10^{{{exp}}}$\"\n",
    "        ax.text(\n",
    "            j, i,\n",
    "            text,\n",
    "            ha='center',\n",
    "            va='center',\n",
    "            fontsize=12,\n",
    "            color='black'\n",
    "        )\n",
    "plt.tight_layout()\n",
    "\n",
    "fig.savefig(\"cov.pdf\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0400e692",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 3.49566764e-06, -9.50811498e-07, -3.97684000e-06,\n",
       "        -5.93983332e-04],\n",
       "       [-9.50811498e-07,  1.56888845e-06,  1.81335752e-06,\n",
       "         1.34486412e-04],\n",
       "       [-3.97684000e-06,  1.81335752e-06,  5.87109893e-06,\n",
       "         7.20021991e-04],\n",
       "       [-5.93983332e-04,  1.34486412e-04,  7.20021991e-04,\n",
       "         1.05851374e-01]])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cov_AET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb34dd0d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pespace",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}