Integer_Optimizer_3Dtruss.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e30a631d",
   "metadata": {},
   "source": [
    "# Loads packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3dcb71eb-b0a7-46b0-b843-dabb47086fd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "import torch\n",
    "import torch.optim as optim\n",
    "from scipy.spatial import ConvexHull\n",
    "from matplotlib.patches import Polygon\n",
    "import sys,os\n",
    "sys.path.append(os.path.realpath('./src/'))\n",
    "import pandas as pd\n",
    "from materialEncoder import MaterialEncoder\n",
    "import time\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "facd1d4f",
   "metadata": {},
   "source": [
    "## Loads the Database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6443eef2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocessData():\n",
    "  df = pd.read_excel('./data/MaterialDatabase_FULL.xlsx')# # \n",
    "  dataIdentifier = {'name': df[df.columns[0]], 'className':df[df.columns[1]], 'classID':df[df.columns[2]]} # name of the material and type\n",
    "  trainInfo = torch.tensor((df[df.columns[3:]].to_numpy())).float()\n",
    "\n",
    "  return dataIdentifier, trainInfo, df\n",
    "dataIdentifier, trainInfo, df = preprocessData()\n",
    "\n",
    "props = df.columns[3:].tolist()\n",
    "nmat, nprop = trainInfo.size()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02018f95",
   "metadata": {},
   "source": [
    "## Loads the truss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "59649404-c5ec-4dc5-8de0-1061ddab8047",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from examples import getExample\n",
    "from truss3DFE import Truss3DFE\n",
    "\n",
    "#Loads the example truss\n",
    "exampleName, nodeXY, connectivity, bc = getExample(19)\n",
    "#Changes the force\n",
    "bc['forces'] = {'nodes':np.array([8]), 'fx':1.E3*torch.tensor([0.]), 'fy':1E2*torch.tensor([200.]), 'fz':1E0*torch.tensor([0.])}\n",
    "\n",
    "\n",
    "n_bars=len(connectivity)\n",
    "\n",
    "\n",
    "\n",
    "#Loads the truss in truss\n",
    "truss = Truss3DFE(nodeXY, connectivity, bc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4219c821",
   "metadata": {},
   "source": [
    "## SELECT CONSTRAINTS AND OBJECTIVES HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ef40e2f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Defines constraints and objectives\n",
    "constraints = {'massCons': {'isOn':False, 'maxMass':5}, \\\n",
    "               'costCons': {'isOn':False, 'maxCost':5},\\\n",
    "               'tensionCons': {'isOn':True, 'FOS':4.},\\\n",
    "               'complianceCons': {'isOn':False, 'maxJ':35},\\\n",
    "               'compressionCons': {'isOn':True, 'FOS':4.},\\\n",
    "               'co2Cons': {'isOn':False, 'maxco2':30},\\\n",
    "               'energyCons': {'isOn':False, 'maxenergy' : 1e10},\\\n",
    "               'waterCons': {'isOn':False, 'maxwater':4e3}}\n",
    "\n",
    "\n",
    "objectives = {'cost': {'isOn':False},\\\n",
    "              'mass': {'isOn':True}, \\\n",
    "              'co2': {'isOn':False},\\\n",
    "              'water': {'isOn':False},\\\n",
    "              'energy': {'isOn':False},\\\n",
    "              'compliance': {'isOn': True}}\n",
    "               \n",
    "# count the number of entries with 'isOn' set to True\n",
    "no = sum(1 for v in objectives.values() if v['isOn'])\n",
    "nc = sum(1 for v in constraints.values() if v['isOn'])\n",
    "\n",
    "# print an error message in red if there are 3 or more entries with 'isOn' set to True\n",
    "if no >= 3:\n",
    "    print('Error: Three or more entries have isOn=True')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b63a6d91",
   "metadata": {},
   "source": [
    "## ---------------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "154d475d",
   "metadata": {},
   "source": [
    "## Defines problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ac0f696e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from pymoo.core.problem import ElementwiseProblem\n",
    "from pymoo.core.variable import Real, Integer, Choice, Binary\n",
    "from pymoo.termination.default import DefaultMultiObjectiveTermination\n",
    "\n",
    "class MixedVarsZDT1(ElementwiseProblem):\n",
    "\n",
    "    def __init__(self, truss, trainInfo , constraints, objectives, nc, no, nmat, n_bars, **kwargs):\n",
    "\n",
    "        variables = dict()\n",
    "\n",
    "        variables[f\"x01\"] = Integer(bounds=(0, nmat-1))\n",
    "\n",
    "        for k in range(2, n_bars+2):\n",
    "            variables[f\"x{k:02}\"] = Real(bounds=(1e-7, 1e-3))\n",
    "\n",
    "        super().__init__(vars=variables, n_obj=no, n_ieq_constr=nc, **kwargs)\n",
    "        \n",
    "        self.truss=truss\n",
    "        self.trainInfo=trainInfo\n",
    "        self.constraints=constraints\n",
    "        self.objectives=objectives\n",
    "        \n",
    "    def _evaluate(self, x, out, *args, **kwargs):\n",
    "        x = np.array([x[f\"x{k:02}\"] for k in range(1, n_bars+2)])\n",
    "        \n",
    "        matprop=trainInfo[int(x[0]),:]  \n",
    "        \n",
    "        x_tensor = torch.from_numpy(x[1:])\n",
    "        area = x_tensor * torch.ones((connectivity.shape[0]))   \n",
    "        u, _, _, _, _, internalForce = truss.solveFE(E = torch.tensor([matprop[0]]).float(), A=area)\n",
    "        compliance = truss.computeCompliance(u)\n",
    "        volume = truss.getVolume(area)\n",
    "        mass = matprop[2]*volume\n",
    "        cost = mass*matprop[1]\n",
    "        co2 = mass*matprop[4]\n",
    "        energy = mass*matprop[5]        \n",
    "        water = mass*matprop[6] \n",
    "        \n",
    "        \n",
    "        \n",
    "        con_values = []\n",
    "        \n",
    "        if(constraints['massCons']['isOn']):\n",
    "            constraints['massCons']['value'] = (mass/constraints['massCons']['maxMass']) - 1.\n",
    "            con_values.append(constraints['massCons']['value'])\n",
    "\n",
    "        if(constraints['costCons']['isOn']):\n",
    "            constraints['costCons']['value'] = (cost/constraints['costCons']['maxCost']) - 1.\n",
    "            con_values.append(constraints['costCons']['value'])\n",
    "\n",
    "        if(constraints['tensionCons']['isOn']):\n",
    "            tensileForce = 0.001+torch.relu(internalForce)\n",
    "            tensileStress = tensileForce/area\n",
    "            maxTensileStressExperienced = torch.pow(torch.sum(tensileStress**6), 1./6)*constraints['tensionCons']['FOS']\n",
    "            constraints['tensionCons']['value'] = (maxTensileStressExperienced/matprop[3]) - 1.\n",
    "            con_values.append(constraints['tensionCons']['value'])\n",
    "\n",
    "        if(constraints['complianceCons']['isOn']):\n",
    "            constraints['complianceCons']['value'] = (compliance/constraints['complianceCons']['maxJ']) - 1.\n",
    "            con_values.append(constraints['complianceCons']['value'])\n",
    "\n",
    "        if(constraints['compressionCons']['isOn']):\n",
    "            compressiveForce = 0.001+torch.relu(-internalForce)\n",
    "            k = 4. # used in geom factor... see buckling theory\n",
    "            geomFactor = k*(self.truss.barLength/(np.pi*area))**2\n",
    "            compressiveStress = compressiveForce*geomFactor\n",
    "            maxCompressiveStressExperienced = torch.pow(torch.sum(compressiveStress**6), 1./6)*constraints['compressionCons']['FOS']\n",
    "            constraints['compressionCons']['value'] = (maxCompressiveStressExperienced/matprop[0]) - 1.\n",
    "            con_values.append(constraints['compressionCons']['value'])\n",
    "\n",
    "        if(constraints['co2Cons']['isOn']):\n",
    "            constraints['co2Cons']['value'] = (co2/constraints['co2Cons']['maxco2']) - 1.\n",
    "            con_values.append(constraints['co2Cons']['value'])\n",
    "\n",
    "        if(constraints['energyCons']['isOn']):\n",
    "            constraints['energyCons']['value'] = (energy/constraints['energyCons']['maxenergy']) - 1.\n",
    "            con_values.append(constraints['energyCons']['value'])\n",
    "\n",
    "        if(constraints['waterCons']['isOn']):\n",
    "            constraints['waterCons']['value'] = (water/constraints['waterCons']['maxwater']) - 1.\n",
    "            con_values.append(constraints['waterCons']['value'])\n",
    "            \n",
    "        \n",
    "        \n",
    "        obj_values = []\n",
    "        \n",
    "        if(objectives['cost']['isOn']):\n",
    "            obj_values.append(cost)\n",
    "            \n",
    "        if(objectives['mass']['isOn']):\n",
    "            obj_values.append(mass)\n",
    "            \n",
    "        if(objectives['co2']['isOn']):\n",
    "            obj_values.append(co2)\n",
    "            \n",
    "        if(objectives['water']['isOn']):\n",
    "            obj_values.append(water)\n",
    "            \n",
    "        if(objectives['energy']['isOn']):\n",
    "            obj_values.append(energy)\n",
    "            \n",
    "        if(objectives['compliance']['isOn']):\n",
    "            obj_values.append(compliance)\n",
    "            \n",
    "  \n",
    "\n",
    "        out[\"F\"] = np.array(obj_values)\n",
    "        out[\"G\"] = np.array(con_values)\n",
    "        \n",
    "  \n",
    "problem = MixedVarsZDT1(truss,trainInfo , constraints, objectives, nc, no, nmat, n_bars)\n",
    "\n",
    "    \n",
    "from pymoo.visualization.scatter import Scatter\n",
    "from pymoo.algorithms.moo.nsga2 import NSGA2, RankAndCrowdingSurvival\n",
    "from pymoo.core.mixed import MixedVariableMating, MixedVariableGA, MixedVariableSampling, MixedVariableDuplicateElimination\n",
    "from pymoo.optimize import minimize\n",
    "\n",
    "algorithm = NSGA2(pop_size=50,\n",
    "                  sampling=MixedVariableSampling(),\n",
    "                  mating=MixedVariableMating(eliminate_duplicates=MixedVariableDuplicateElimination()),\n",
    "                  eliminate_duplicates=MixedVariableDuplicateElimination(),\n",
    "                  )\n",
    "\n",
    "termination=('n_gen', 750)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c05ba216",
   "metadata": {},
   "source": [
    "## Runs the solver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a8c922d3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\luisy\\Desktop\\SMSUDL-paper\\src\\utilFuncs.py:20: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  return torch.tensor(x).float()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================================================================\n",
      "n_gen  |  n_eval  | n_nds  |     cv_min    |     cv_avg    |      eps      |   indicator  \n",
      "==========================================================================================\n",
      "     1 |       50 |      1 |  1.8274259865 |  1.071869E+03 |             - |             -\n",
      "     2 |      100 |      1 |  1.0547608132 |  1.945178E+01 |             - |             -\n",
      "     3 |      150 |      1 |  0.6306587710 |  8.2197427231 |             - |             -\n",
      "     4 |      200 |      1 |  0.0927658250 |  4.0077631046 |             - |             -\n",
      "     5 |      250 |      1 |  0.0927658250 |  2.3123907897 |             - |             -\n",
      "     6 |      300 |      2 |  0.000000E+00 |  1.1701098778 |             - |             -\n",
      "     7 |      350 |      4 |  0.000000E+00 |  0.6119315782 |  0.1299879382 |         ideal\n",
      "     8 |      400 |      7 |  0.000000E+00 |  0.1883987693 |  0.0909947158 |         ideal\n",
      "     9 |      450 |     13 |  0.000000E+00 |  0.0061949871 |  0.0759724935 |         ideal\n",
      "    10 |      500 |     20 |  0.000000E+00 |  0.000000E+00 |  0.4368655489 |         ideal\n",
      "    11 |      550 |     19 |  0.000000E+00 |  0.000000E+00 |  0.0285196817 |         ideal\n",
      "    12 |      600 |     26 |  0.000000E+00 |  0.000000E+00 |  0.0502829283 |         ideal\n",
      "    13 |      650 |     32 |  0.000000E+00 |  0.000000E+00 |  0.0316033022 |         ideal\n",
      "    14 |      700 |     39 |  0.000000E+00 |  0.000000E+00 |  0.0222826852 |         ideal\n",
      "    15 |      750 |     48 |  0.000000E+00 |  0.000000E+00 |  0.0045628010 |             f\n",
      "    16 |      800 |     47 |  0.000000E+00 |  0.000000E+00 |  0.0401064243 |         nadir\n",
      "    17 |      850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0041580594 |             f\n",
      "    18 |      900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0095438736 |         ideal\n",
      "    19 |      950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0189342909 |         ideal\n",
      "    20 |     1000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030078534 |             f\n",
      "    21 |     1050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0193809380 |         ideal\n",
      "    22 |     1100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0151373221 |         ideal\n",
      "    23 |     1150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022371783 |             f\n",
      "    24 |     1200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038761101 |             f\n",
      "    25 |     1250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015893393 |             f\n",
      "    26 |     1300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0036457535 |             f\n",
      "    27 |     1350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0046075526 |         ideal\n",
      "    28 |     1400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0359819358 |         nadir\n",
      "    29 |     1450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023442309 |             f\n",
      "    30 |     1500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0044541322 |             f\n",
      "    31 |     1550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031261349 |             f\n",
      "    32 |     1600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012979073 |             f\n",
      "    33 |     1650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026351356 |             f\n",
      "    34 |     1700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014266274 |             f\n",
      "    35 |     1750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030034711 |             f\n",
      "    36 |     1800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011089291 |             f\n",
      "    37 |     1850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0043824151 |         ideal\n",
      "    38 |     1900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012663296 |             f\n",
      "    39 |     1950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023850768 |             f\n",
      "    40 |     2000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0041106274 |             f\n",
      "    41 |     2050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011639575 |             f\n",
      "    42 |     2100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0135653890 |         nadir\n",
      "    43 |     2150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0282342952 |         nadir\n",
      "    44 |     2200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011423306 |             f\n",
      "    45 |     2250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029405821 |         ideal\n",
      "    46 |     2300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017074155 |             f\n",
      "    47 |     2350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035446596 |             f\n",
      "    48 |     2400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011959628 |             f\n",
      "    49 |     2450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025559514 |             f\n",
      "    50 |     2500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0067743167 |         nadir\n",
      "    51 |     2550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017397928 |             f\n",
      "    52 |     2600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030814598 |             f\n",
      "    53 |     2650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020852553 |             f\n",
      "    54 |     2700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0036822835 |             f\n",
      "    55 |     2750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022282242 |             f\n",
      "    56 |     2800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035298075 |             f\n",
      "    57 |     2850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014347281 |             f\n",
      "    58 |     2900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022228354 |             f\n",
      "    59 |     2950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0283723771 |         nadir\n",
      "    60 |     3000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027057621 |             f\n",
      "    61 |     3050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0067457966 |         nadir\n",
      "    62 |     3100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016857456 |             f\n",
      "    63 |     3150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024537970 |             f\n",
      "    64 |     3200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037342550 |             f\n",
      "    65 |     3250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011255673 |             f\n",
      "    66 |     3300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031881174 |             f\n",
      "    67 |     3350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016031885 |             f\n",
      "    68 |     3400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024858333 |             f\n",
      "    69 |     3450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033694911 |             f\n",
      "    70 |     3500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023886720 |             f\n",
      "    71 |     3550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0147804039 |         nadir\n",
      "    72 |     3600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010571979 |             f\n",
      "    73 |     3650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034910135 |             f\n",
      "    74 |     3700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012291293 |             f\n",
      "    75 |     3750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0048366318 |         ideal\n",
      "    76 |     3800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011650138 |             f\n",
      "    77 |     3850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0061011487 |         nadir\n",
      "    78 |     3900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019918247 |             f\n",
      "    79 |     3950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035148825 |             f\n",
      "    80 |     4000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025901388 |             f\n",
      "    81 |     4050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025931972 |             f\n",
      "    82 |     4100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009887393 |             f\n",
      "    83 |     4150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017748829 |             f\n",
      "    84 |     4200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030154709 |             f\n",
      "    85 |     4250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007045006 |             f\n",
      "    86 |     4300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027203900 |             f\n",
      "    87 |     4350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013656924 |             f\n",
      "    88 |     4400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027974547 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    89 |     4450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017381957 |             f\n",
      "    90 |     4500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033597579 |             f\n",
      "    91 |     4550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014891537 |             f\n",
      "    92 |     4600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024040029 |             f\n",
      "    93 |     4650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034764096 |             f\n",
      "    94 |     4700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018318239 |             f\n",
      "    95 |     4750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030509874 |             f\n",
      "    96 |     4800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013765566 |             f\n",
      "    97 |     4850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023043409 |             f\n",
      "    98 |     4900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035057145 |         nadir\n",
      "    99 |     4950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011979917 |             f\n",
      "   100 |     5000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023017927 |             f\n",
      "   101 |     5050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035245988 |             f\n",
      "   102 |     5100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016278574 |             f\n",
      "   103 |     5150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023070469 |             f\n",
      "   104 |     5200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038541991 |             f\n",
      "   105 |     5250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013002485 |             f\n",
      "   106 |     5300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028071347 |             f\n",
      "   107 |     5350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013088268 |             f\n",
      "   108 |     5400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025511513 |             f\n",
      "   109 |     5450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012439015 |             f\n",
      "   110 |     5500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030621608 |             f\n",
      "   111 |     5550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017049059 |             f\n",
      "   112 |     5600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032556535 |             f\n",
      "   113 |     5650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025881454 |             f\n",
      "   114 |     5700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014695541 |             f\n",
      "   115 |     5750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026516713 |             f\n",
      "   116 |     5800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0051465533 |         ideal\n",
      "   117 |     5850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022304310 |             f\n",
      "   118 |     5900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030705526 |             f\n",
      "   119 |     5950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009076130 |             f\n",
      "   120 |     6000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016934312 |             f\n",
      "   121 |     6050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024962244 |             f\n",
      "   122 |     6100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035176464 |             f\n",
      "   123 |     6150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0236134783 |         nadir\n",
      "   124 |     6200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019205721 |             f\n",
      "   125 |     6250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031473748 |             f\n",
      "   126 |     6300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010233117 |             f\n",
      "   127 |     6350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022409368 |             f\n",
      "   128 |     6400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030768625 |             f\n",
      "   129 |     6450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009785733 |             f\n",
      "   130 |     6500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022660226 |             f\n",
      "   131 |     6550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0036160304 |             f\n",
      "   132 |     6600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009660253 |             f\n",
      "   133 |     6650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027471637 |             f\n",
      "   134 |     6700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011037681 |             f\n",
      "   135 |     6750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021198813 |             f\n",
      "   136 |     6800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025346028 |             f\n",
      "   137 |     6850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019804083 |             f\n",
      "   138 |     6900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030390126 |             f\n",
      "   139 |     6950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0256843923 |         nadir\n",
      "   140 |     7000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017531985 |             f\n",
      "   141 |     7050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023409563 |             f\n",
      "   142 |     7100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024700719 |             f\n",
      "   143 |     7150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032173468 |             f\n",
      "   144 |     7200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006228992 |             f\n",
      "   145 |     7250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012516061 |             f\n",
      "   146 |     7300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038506071 |         nadir\n",
      "   147 |     7350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0044433914 |         nadir\n",
      "   148 |     7400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011886468 |             f\n",
      "   149 |     7450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022615702 |             f\n",
      "   150 |     7500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038645719 |             f\n",
      "   151 |     7550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011176631 |             f\n",
      "   152 |     7600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032522259 |             f\n",
      "   153 |     7650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016762492 |             f\n",
      "   154 |     7700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0196513312 |         nadir\n",
      "   155 |     7750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021501693 |             f\n",
      "   156 |     7800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037287343 |             f\n",
      "   157 |     7850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020911226 |             f\n",
      "   158 |     7900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034837049 |             f\n",
      "   159 |     7950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023600088 |             f\n",
      "   160 |     8000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038946776 |             f\n",
      "   161 |     8050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025078559 |             f\n",
      "   162 |     8100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016858773 |             f\n",
      "   163 |     8150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037343908 |             f\n",
      "   164 |     8200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011925350 |             f\n",
      "   165 |     8250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026489513 |             f\n",
      "   166 |     8300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012326510 |             f\n",
      "   167 |     8350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024202544 |             f\n",
      "   168 |     8400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032784695 |             f\n",
      "   169 |     8450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008202150 |             f\n",
      "   170 |     8500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026378527 |             f\n",
      "   171 |     8550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010547618 |             f\n",
      "   172 |     8600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0048429863 |         nadir\n",
      "   173 |     8650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016437840 |             f\n",
      "   174 |     8700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021469453 |             f\n",
      "   175 |     8750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034409778 |             f\n",
      "   176 |     8800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009484900 |             f\n",
      "   177 |     8850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0074736723 |         nadir\n",
      "   178 |     8900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007330520 |             f\n",
      "   179 |     8950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015952835 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   180 |     9000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028381472 |             f\n",
      "   181 |     9050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017861010 |             f\n",
      "   182 |     9100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032528740 |             f\n",
      "   183 |     9150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008768910 |             f\n",
      "   184 |     9200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021762037 |             f\n",
      "   185 |     9250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029058769 |             f\n",
      "   186 |     9300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017087902 |             f\n",
      "   187 |     9350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0043892810 |             f\n",
      "   188 |     9400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018219655 |             f\n",
      "   189 |     9450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024126035 |             f\n",
      "   190 |     9500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0041011275 |             f\n",
      "   191 |     9550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0152237512 |         nadir\n",
      "   192 |     9600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025841576 |         nadir\n",
      "   193 |     9650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016576481 |             f\n",
      "   194 |     9700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035115183 |             f\n",
      "   195 |     9750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020257594 |             f\n",
      "   196 |     9800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0040984853 |             f\n",
      "   197 |     9850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016293616 |             f\n",
      "   198 |     9900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037032631 |             f\n",
      "   199 |     9950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018910232 |             f\n",
      "   200 |    10000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026132317 |             f\n",
      "   201 |    10050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0138183306 |         nadir\n",
      "   202 |    10100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014498286 |             f\n",
      "   203 |    10150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029143879 |         nadir\n",
      "   204 |    10200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017643762 |             f\n",
      "   205 |    10250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030404776 |             f\n",
      "   206 |    10300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008824810 |             f\n",
      "   207 |    10350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031063580 |             f\n",
      "   208 |    10400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014443450 |             f\n",
      "   209 |    10450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023012212 |             f\n",
      "   210 |    10500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0036764153 |             f\n",
      "   211 |    10550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018104813 |             f\n",
      "   212 |    10600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025201930 |             f\n",
      "   213 |    10650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008881797 |             f\n",
      "   214 |    10700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021478156 |             f\n",
      "   215 |    10750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034075970 |             f\n",
      "   216 |    10800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017557340 |             f\n",
      "   217 |    10850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033549880 |             f\n",
      "   218 |    10900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0056104329 |         nadir\n",
      "   219 |    10950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011662221 |             f\n",
      "   220 |    11000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0188919279 |         nadir\n",
      "   221 |    11050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025046834 |             f\n",
      "   222 |    11100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006840528 |             f\n",
      "   223 |    11150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024242620 |             f\n",
      "   224 |    11200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027385478 |             f\n",
      "   225 |    11250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016153877 |             f\n",
      "   226 |    11300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032393511 |         nadir\n",
      "   227 |    11350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017284206 |             f\n",
      "   228 |    11400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027747804 |             f\n",
      "   229 |    11450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015941741 |             f\n",
      "   230 |    11500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022119024 |             f\n",
      "   231 |    11550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032823454 |             f\n",
      "   232 |    11600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0005415160 |             f\n",
      "   233 |    11650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018488588 |             f\n",
      "   234 |    11700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026105515 |             f\n",
      "   235 |    11750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022962754 |             f\n",
      "   236 |    11800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034319331 |             f\n",
      "   237 |    11850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0004789873 |             f\n",
      "   238 |    11900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016091997 |             f\n",
      "   239 |    11950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031498006 |             f\n",
      "   240 |    12000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013125976 |             f\n",
      "   241 |    12050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0081650217 |         nadir\n",
      "   242 |    12100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017716153 |             f\n",
      "   243 |    12150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029015460 |             f\n",
      "   244 |    12200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0184942654 |         nadir\n",
      "   245 |    12250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020489396 |             f\n",
      "   246 |    12300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0055160412 |             f\n",
      "   247 |    12350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006597973 |             f\n",
      "   248 |    12400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027395614 |         nadir\n",
      "   249 |    12450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029697247 |             f\n",
      "   250 |    12500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020468590 |             f\n",
      "   251 |    12550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030483833 |             f\n",
      "   252 |    12600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011739480 |             f\n",
      "   253 |    12650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030560532 |             f\n",
      "   254 |    12700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027726314 |             f\n",
      "   255 |    12750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015200482 |             f\n",
      "   256 |    12800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026607153 |             f\n",
      "   257 |    12850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007957927 |             f\n",
      "   258 |    12900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017452384 |             f\n",
      "   259 |    12950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025754857 |             f\n",
      "   260 |    13000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015376278 |             f\n",
      "   261 |    13050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027744519 |             f\n",
      "   262 |    13100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018354460 |             f\n",
      "   263 |    13150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029870447 |             f\n",
      "   264 |    13200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010782325 |             f\n",
      "   265 |    13250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020808006 |             f\n",
      "   266 |    13300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0041659061 |             f\n",
      "   267 |    13350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014054167 |             f\n",
      "   268 |    13400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027012696 |             f\n",
      "   269 |    13450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014079658 |             f\n",
      "   270 |    13500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021297470 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   271 |    13550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030236693 |             f\n",
      "   272 |    13600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019522782 |             f\n",
      "   273 |    13650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0042018903 |             f\n",
      "   274 |    13700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017911510 |             f\n",
      "   275 |    13750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032737882 |             f\n",
      "   276 |    13800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017462349 |             f\n",
      "   277 |    13850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025736810 |             f\n",
      "   278 |    13900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015425771 |             f\n",
      "   279 |    13950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025594019 |             f\n",
      "   280 |    14000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019892150 |             f\n",
      "   281 |    14050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024048733 |             f\n",
      "   282 |    14100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032547158 |             f\n",
      "   283 |    14150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0039325807 |         nadir\n",
      "   284 |    14200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007643279 |             f\n",
      "   285 |    14250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011259841 |             f\n",
      "   286 |    14300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024253732 |             f\n",
      "   287 |    14350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0042168354 |             f\n",
      "   288 |    14400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018073079 |             f\n",
      "   289 |    14450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027011130 |             f\n",
      "   290 |    14500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018494068 |             f\n",
      "   291 |    14550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027920545 |             f\n",
      "   292 |    14600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013917312 |             f\n",
      "   293 |    14650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022730796 |             f\n",
      "   294 |    14700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031462319 |             f\n",
      "   295 |    14750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010341651 |             f\n",
      "   296 |    14800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0054215069 |         nadir\n",
      "   297 |    14850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016558994 |             f\n",
      "   298 |    14900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034337588 |             f\n",
      "   299 |    14950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023090846 |             f\n",
      "   300 |    15000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032887948 |             f\n",
      "   301 |    15050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013663807 |             f\n",
      "   302 |    15100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020570112 |             f\n",
      "   303 |    15150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031513333 |             f\n",
      "   304 |    15200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014223683 |             f\n",
      "   305 |    15250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023835916 |             f\n",
      "   306 |    15300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030336663 |             f\n",
      "   307 |    15350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014142791 |             f\n",
      "   308 |    15400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024544682 |             f\n",
      "   309 |    15450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032527205 |             f\n",
      "   310 |    15500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014094523 |             f\n",
      "   311 |    15550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014440840 |             f\n",
      "   312 |    15600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026733387 |             f\n",
      "   313 |    15650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0160463902 |         nadir\n",
      "   314 |    15700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013647616 |             f\n",
      "   315 |    15750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012704998 |             f\n",
      "   316 |    15800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027713965 |             f\n",
      "   317 |    15850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019093120 |             f\n",
      "   318 |    15900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032203932 |             f\n",
      "   319 |    15950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018145042 |             f\n",
      "   320 |    16000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035164335 |             f\n",
      "   321 |    16050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031620311 |             f\n",
      "   322 |    16100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023299058 |             f\n",
      "   323 |    16150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0044848488 |             f\n",
      "   324 |    16200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009780760 |             f\n",
      "   325 |    16250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0088741664 |         nadir\n",
      "   326 |    16300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017102779 |             f\n",
      "   327 |    16350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031158057 |             f\n",
      "   328 |    16400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012320535 |             f\n",
      "   329 |    16450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026086542 |             f\n",
      "   330 |    16500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015046142 |             f\n",
      "   331 |    16550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015553006 |             f\n",
      "   332 |    16600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027887881 |             f\n",
      "   333 |    16650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008110323 |             f\n",
      "   334 |    16700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021847599 |             f\n",
      "   335 |    16750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025857421 |             f\n",
      "   336 |    16800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019233569 |             f\n",
      "   337 |    16850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027983051 |             f\n",
      "   338 |    16900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024362686 |             f\n",
      "   339 |    16950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038242928 |             f\n",
      "   340 |    17000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013083010 |             f\n",
      "   341 |    17050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022593567 |             f\n",
      "   342 |    17100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030797354 |             f\n",
      "   343 |    17150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018698821 |             f\n",
      "   344 |    17200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031804990 |             f\n",
      "   345 |    17250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010169236 |             f\n",
      "   346 |    17300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023652703 |             f\n",
      "   347 |    17350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034025762 |             f\n",
      "   348 |    17400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034741363 |             f\n",
      "   349 |    17450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017281397 |             f\n",
      "   350 |    17500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015112767 |             f\n",
      "   351 |    17550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020168669 |             f\n",
      "   352 |    17600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033824832 |             f\n",
      "   353 |    17650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015420009 |             f\n",
      "   354 |    17700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026919353 |             f\n",
      "   355 |    17750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009671312 |             f\n",
      "   356 |    17800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030133044 |         nadir\n",
      "   357 |    17850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013012610 |             f\n",
      "   358 |    17900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021751880 |             f\n",
      "   359 |    17950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028892021 |             f\n",
      "   360 |    18000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015182272 |             f\n",
      "   361 |    18050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0041643483 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   362 |    18100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021155393 |             f\n",
      "   363 |    18150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029711217 |             f\n",
      "   364 |    18200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020473749 |             f\n",
      "   365 |    18250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028601335 |             f\n",
      "   366 |    18300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011946365 |             f\n",
      "   367 |    18350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021935598 |             f\n",
      "   368 |    18400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025063345 |             f\n",
      "   369 |    18450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010098135 |             f\n",
      "   370 |    18500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0102871647 |         nadir\n",
      "   371 |    18550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009639098 |             f\n",
      "   372 |    18600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021672820 |             f\n",
      "   373 |    18650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031195697 |             f\n",
      "   374 |    18700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013284870 |             f\n",
      "   375 |    18750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018556779 |             f\n",
      "   376 |    18800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024913502 |             f\n",
      "   377 |    18850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031471272 |             f\n",
      "   378 |    18900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009173118 |             f\n",
      "   379 |    18950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019612166 |             f\n",
      "   380 |    19000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032747839 |             f\n",
      "   381 |    19050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019692791 |             f\n",
      "   382 |    19100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028124677 |             f\n",
      "   383 |    19150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013108225 |             f\n",
      "   384 |    19200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0040455222 |             f\n",
      "   385 |    19250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014960776 |             f\n",
      "   386 |    19300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024602667 |             f\n",
      "   387 |    19350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0039833506 |             f\n",
      "   388 |    19400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007425506 |             f\n",
      "   389 |    19450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027677926 |             f\n",
      "   390 |    19500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031931454 |             f\n",
      "   391 |    19550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011390205 |             f\n",
      "   392 |    19600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018736440 |             f\n",
      "   393 |    19650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028479890 |             f\n",
      "   394 |    19700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011313261 |             f\n",
      "   395 |    19750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024113500 |             f\n",
      "   396 |    19800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034519499 |             f\n",
      "   397 |    19850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010580127 |             f\n",
      "   398 |    19900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019399657 |             f\n",
      "   399 |    19950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0071238175 |         nadir\n",
      "   400 |    20000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014512523 |             f\n",
      "   401 |    20050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0039535173 |             f\n",
      "   402 |    20100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018479621 |             f\n",
      "   403 |    20150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037409794 |             f\n",
      "   404 |    20200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0004000533 |             f\n",
      "   405 |    20250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012096328 |             f\n",
      "   406 |    20300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019018884 |             f\n",
      "   407 |    20350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033182585 |             f\n",
      "   408 |    20400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014382724 |             f\n",
      "   409 |    20450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028690917 |             f\n",
      "   410 |    20500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012501197 |             f\n",
      "   411 |    20550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021655337 |             f\n",
      "   412 |    20600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038938555 |             f\n",
      "   413 |    20650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012460509 |             f\n",
      "   414 |    20700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022869762 |             f\n",
      "   415 |    20750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027313579 |             f\n",
      "   416 |    20800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009043909 |             f\n",
      "   417 |    20850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019502387 |             f\n",
      "   418 |    20900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031690095 |             f\n",
      "   419 |    20950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022805202 |             f\n",
      "   420 |    21000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032808493 |             f\n",
      "   421 |    21050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010293884 |             f\n",
      "   422 |    21100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0047276995 |         nadir\n",
      "   423 |    21150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006475646 |             f\n",
      "   424 |    21200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021434632 |             f\n",
      "   425 |    21250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025692448 |             f\n",
      "   426 |    21300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018110515 |             f\n",
      "   427 |    21350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019906054 |             f\n",
      "   428 |    21400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0036622990 |             f\n",
      "   429 |    21450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012110801 |             f\n",
      "   430 |    21500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021464732 |             f\n",
      "   431 |    21550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031044294 |             f\n",
      "   432 |    21600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017747345 |             f\n",
      "   433 |    21650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030430522 |             f\n",
      "   434 |    21700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014933016 |             f\n",
      "   435 |    21750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015044262 |             f\n",
      "   436 |    21800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022276385 |             f\n",
      "   437 |    21850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031911207 |             f\n",
      "   438 |    21900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023544358 |             f\n",
      "   439 |    21950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0042443841 |             f\n",
      "   440 |    22000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012927579 |             f\n",
      "   441 |    22050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016764752 |             f\n",
      "   442 |    22100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023817772 |             f\n",
      "   443 |    22150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032962081 |             f\n",
      "   444 |    22200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009545548 |             f\n",
      "   445 |    22250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029921354 |             f\n",
      "   446 |    22300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016445510 |             f\n",
      "   447 |    22350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035312053 |             f\n",
      "   448 |    22400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019492974 |             f\n",
      "   449 |    22450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034956702 |             f\n",
      "   450 |    22500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008799115 |             f\n",
      "   451 |    22550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016890076 |             f\n",
      "   452 |    22600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027973163 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   453 |    22650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013689183 |             f\n",
      "   454 |    22700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020019218 |             f\n",
      "   455 |    22750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035271932 |             f\n",
      "   456 |    22800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024077037 |             f\n",
      "   457 |    22850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0036998463 |             f\n",
      "   458 |    22900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014061633 |             f\n",
      "   459 |    22950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034920927 |             f\n",
      "   460 |    23000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009723554 |             f\n",
      "   461 |    23050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015838868 |             f\n",
      "   462 |    23100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022182199 |             f\n",
      "   463 |    23150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026761539 |             f\n",
      "   464 |    23200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011156102 |             f\n",
      "   465 |    23250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022558468 |             f\n",
      "   466 |    23300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031094199 |             f\n",
      "   467 |    23350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015648017 |             f\n",
      "   468 |    23400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029074584 |             f\n",
      "   469 |    23450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016902037 |             f\n",
      "   470 |    23500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025183941 |             f\n",
      "   471 |    23550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022508482 |             f\n",
      "   472 |    23600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0057003876 |         nadir\n",
      "   473 |    23650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015267652 |             f\n",
      "   474 |    23700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0246616161 |         nadir\n",
      "   475 |    23750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0005081180 |             f\n",
      "   476 |    23800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017481257 |             f\n",
      "   477 |    23850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019334030 |             f\n",
      "   478 |    23900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033193856 |             f\n",
      "   479 |    23950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015936239 |             f\n",
      "   480 |    24000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025554679 |             f\n",
      "   481 |    24050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011264506 |             f\n",
      "   482 |    24100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021215421 |             f\n",
      "   483 |    24150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030751086 |             f\n",
      "   484 |    24200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014753029 |             f\n",
      "   485 |    24250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031126553 |             f\n",
      "   486 |    24300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020602781 |             f\n",
      "   487 |    24350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027734390 |             f\n",
      "   488 |    24400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023743985 |             f\n",
      "   489 |    24450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032947248 |             f\n",
      "   490 |    24500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019715446 |             f\n",
      "   491 |    24550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024929196 |             f\n",
      "   492 |    24600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038053062 |             f\n",
      "   493 |    24650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020010859 |             f\n",
      "   494 |    24700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031008028 |             f\n",
      "   495 |    24750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010613914 |             f\n",
      "   496 |    24800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026956918 |             f\n",
      "   497 |    24850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0315955823 |         nadir\n",
      "   498 |    24900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0003932448 |             f\n",
      "   499 |    24950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008714241 |             f\n",
      "   500 |    25000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023317430 |             f\n",
      "   501 |    25050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028150410 |             f\n",
      "   502 |    25100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016410104 |             f\n",
      "   503 |    25150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030885030 |             f\n",
      "   504 |    25200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017086814 |             f\n",
      "   505 |    25250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026852924 |             f\n",
      "   506 |    25300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018587300 |             f\n",
      "   507 |    25350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027308629 |             f\n",
      "   508 |    25400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007084200 |             f\n",
      "   509 |    25450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016627927 |             f\n",
      "   510 |    25500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021946941 |             f\n",
      "   511 |    25550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030013753 |             f\n",
      "   512 |    25600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016160352 |             f\n",
      "   513 |    25650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023564275 |             f\n",
      "   514 |    25700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027673680 |             f\n",
      "   515 |    25750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006716797 |             f\n",
      "   516 |    25800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020536328 |             f\n",
      "   517 |    25850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025041343 |             f\n",
      "   518 |    25900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025516141 |             f\n",
      "   519 |    25950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015989127 |             f\n",
      "   520 |    26000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030330989 |             f\n",
      "   521 |    26050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009950646 |             f\n",
      "   522 |    26100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019687783 |             f\n",
      "   523 |    26150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031723561 |             f\n",
      "   524 |    26200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008802917 |             f\n",
      "   525 |    26250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023531357 |             f\n",
      "   526 |    26300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026995269 |             f\n",
      "   527 |    26350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015603193 |             f\n",
      "   528 |    26400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019451531 |             f\n",
      "   529 |    26450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033187134 |             f\n",
      "   530 |    26500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025645197 |             f\n",
      "   531 |    26550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016541623 |             f\n",
      "   532 |    26600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021847784 |             f\n",
      "   533 |    26650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035385566 |             f\n",
      "   534 |    26700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0004356018 |             f\n",
      "   535 |    26750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021056164 |             f\n",
      "   536 |    26800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0040157889 |             f\n",
      "   537 |    26850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015385912 |             f\n",
      "   538 |    26900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030548555 |             f\n",
      "   539 |    26950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013886114 |             f\n",
      "   540 |    27000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029973071 |             f\n",
      "   541 |    27050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012711503 |             f\n",
      "   542 |    27100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023267915 |             f\n",
      "   543 |    27150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034139683 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   544 |    27200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0110921772 |         nadir\n",
      "   545 |    27250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030622670 |             f\n",
      "   546 |    27300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008745201 |             f\n",
      "   547 |    27350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016681394 |             f\n",
      "   548 |    27400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024267071 |             f\n",
      "   549 |    27450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029609218 |             f\n",
      "   550 |    27500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013053677 |             f\n",
      "   551 |    27550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023783179 |             f\n",
      "   552 |    27600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028087690 |             f\n",
      "   553 |    27650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008775307 |             f\n",
      "   554 |    27700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019060262 |             f\n",
      "   555 |    27750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032617478 |             f\n",
      "   556 |    27800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019096912 |             f\n",
      "   557 |    27850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019131977 |             f\n",
      "   558 |    27900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022855051 |             f\n",
      "   559 |    27950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029458638 |             f\n",
      "   560 |    28000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019254082 |             f\n",
      "   561 |    28050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023344503 |             f\n",
      "   562 |    28100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024150333 |             f\n",
      "   563 |    28150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030389519 |             f\n",
      "   564 |    28200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017134353 |             f\n",
      "   565 |    28250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015154398 |             f\n",
      "   566 |    28300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020100662 |             f\n",
      "   567 |    28350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033802969 |             f\n",
      "   568 |    28400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016600995 |             f\n",
      "   569 |    28450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022595396 |             f\n",
      "   570 |    28500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031952606 |             f\n",
      "   571 |    28550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014058952 |             f\n",
      "   572 |    28600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037339606 |             f\n",
      "   573 |    28650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010355738 |             f\n",
      "   574 |    28700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014870718 |             f\n",
      "   575 |    28750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034957481 |             f\n",
      "   576 |    28800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022072570 |             f\n",
      "   577 |    28850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025077203 |             f\n",
      "   578 |    28900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019998694 |             f\n",
      "   579 |    28950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035037580 |             f\n",
      "   580 |    29000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023251124 |             f\n",
      "   581 |    29050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0038278458 |             f\n",
      "   582 |    29100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0005544447 |             f\n",
      "   583 |    29150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021826544 |             f\n",
      "   584 |    29200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0080821410 |         nadir\n",
      "   585 |    29250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011840802 |             f\n",
      "   586 |    29300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015535743 |             f\n",
      "   587 |    29350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031943606 |             f\n",
      "   588 |    29400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011474618 |             f\n",
      "   589 |    29450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016190535 |             f\n",
      "   590 |    29500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021367943 |             f\n",
      "   591 |    29550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028804916 |             f\n",
      "   592 |    29600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010797221 |             f\n",
      "   593 |    29650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015465209 |             f\n",
      "   594 |    29700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032878286 |             f\n",
      "   595 |    29750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009081259 |             f\n",
      "   596 |    29800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015979792 |             f\n",
      "   597 |    29850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0153338469 |         nadir\n",
      "   598 |    29900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015747479 |             f\n",
      "   599 |    29950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026149126 |             f\n",
      "   600 |    30000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012826770 |             f\n",
      "   601 |    30050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0169920395 |         nadir\n",
      "   602 |    30100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008117088 |             f\n",
      "   603 |    30150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021248788 |             f\n",
      "   604 |    30200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037853010 |             f\n",
      "   605 |    30250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016093972 |             f\n",
      "   606 |    30300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030228044 |             f\n",
      "   607 |    30350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011738883 |             f\n",
      "   608 |    30400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014641147 |             f\n",
      "   609 |    30450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030334706 |             f\n",
      "   610 |    30500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010466017 |             f\n",
      "   611 |    30550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029600315 |             f\n",
      "   612 |    30600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014492661 |             f\n",
      "   613 |    30650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025119368 |             f\n",
      "   614 |    30700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013983023 |             f\n",
      "   615 |    30750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018720427 |             f\n",
      "   616 |    30800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024695906 |             f\n",
      "   617 |    30850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035412545 |             f\n",
      "   618 |    30900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025567673 |             f\n",
      "   619 |    30950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009341774 |             f\n",
      "   620 |    31000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024764500 |             f\n",
      "   621 |    31050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026391946 |             f\n",
      "   622 |    31100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027177593 |             f\n",
      "   623 |    31150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015121862 |             f\n",
      "   624 |    31200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025956132 |             f\n",
      "   625 |    31250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014853807 |             f\n",
      "   626 |    31300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016455625 |             f\n",
      "   627 |    31350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028177055 |             f\n",
      "   628 |    31400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013950504 |             f\n",
      "   629 |    31450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019785579 |             f\n",
      "   630 |    31500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027480000 |             f\n",
      "   631 |    31550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007636490 |             f\n",
      "   632 |    31600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024382443 |             f\n",
      "   633 |    31650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037614653 |             f\n",
      "   634 |    31700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029507287 |             f\n",
      "   635 |    31750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009453757 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   636 |    31800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019443305 |             f\n",
      "   637 |    31850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034291766 |             f\n",
      "   638 |    31900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016308011 |             f\n",
      "   639 |    31950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033027988 |             f\n",
      "   640 |    32000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018233319 |             f\n",
      "   641 |    32050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030299487 |             f\n",
      "   642 |    32100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009596611 |             f\n",
      "   643 |    32150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021339102 |             f\n",
      "   644 |    32200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032465078 |             f\n",
      "   645 |    32250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016111976 |             f\n",
      "   646 |    32300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025047730 |             f\n",
      "   647 |    32350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006994496 |             f\n",
      "   648 |    32400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023343136 |             f\n",
      "   649 |    32450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031547757 |         nadir\n",
      "   650 |    32500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0004437678 |             f\n",
      "   651 |    32550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018276901 |             f\n",
      "   652 |    32600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0041095822 |             f\n",
      "   653 |    32650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006902562 |             f\n",
      "   654 |    32700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025143436 |             f\n",
      "   655 |    32750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019908458 |             f\n",
      "   656 |    32800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021099094 |             f\n",
      "   657 |    32850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0035401595 |             f\n",
      "   658 |    32900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011718691 |             f\n",
      "   659 |    32950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017640349 |             f\n",
      "   660 |    33000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027116450 |             f\n",
      "   661 |    33050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013135306 |             f\n",
      "   662 |    33100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033187772 |             f\n",
      "   663 |    33150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025119713 |             f\n",
      "   664 |    33200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0009519896 |             f\n",
      "   665 |    33250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020432141 |             f\n",
      "   666 |    33300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0041519168 |         nadir\n",
      "   667 |    33350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010370131 |             f\n",
      "   668 |    33400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0026671765 |             f\n",
      "   669 |    33450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020221222 |             f\n",
      "   670 |    33500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030740951 |             f\n",
      "   671 |    33550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0014291796 |             f\n",
      "   672 |    33600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024202380 |             f\n",
      "   673 |    33650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032104055 |             f\n",
      "   674 |    33700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020232061 |             f\n",
      "   675 |    33750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028172191 |             f\n",
      "   676 |    33800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020403602 |             f\n",
      "   677 |    33850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0042630881 |             f\n",
      "   678 |    33900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018806541 |             f\n",
      "   679 |    33950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027881317 |             f\n",
      "   680 |    34000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016785399 |             f\n",
      "   681 |    34050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025430298 |             f\n",
      "   682 |    34100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008388906 |             f\n",
      "   683 |    34150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018595160 |             f\n",
      "   684 |    34200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018165451 |             f\n",
      "   685 |    34250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018775605 |             f\n",
      "   686 |    34300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0023254049 |             f\n",
      "   687 |    34350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030554993 |             f\n",
      "   688 |    34400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008359978 |             f\n",
      "   689 |    34450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028158516 |             f\n",
      "   690 |    34500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0031295857 |             f\n",
      "   691 |    34550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011341393 |             f\n",
      "   692 |    34600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030824614 |             f\n",
      "   693 |    34650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006618001 |             f\n",
      "   694 |    34700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017786387 |             f\n",
      "   695 |    34750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028633081 |             f\n",
      "   696 |    34800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0010425905 |             f\n",
      "   697 |    34850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013555635 |             f\n",
      "   698 |    34900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0021711542 |             f\n",
      "   699 |    34950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032059965 |             f\n",
      "   700 |    35000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0006455613 |             f\n",
      "   701 |    35050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0018186072 |             f\n",
      "   702 |    35100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0030820968 |             f\n",
      "   703 |    35150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0019553773 |             f\n",
      "   704 |    35200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024988049 |             f\n",
      "   705 |    35250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0039992553 |             f\n",
      "   706 |    35300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015967894 |             f\n",
      "   707 |    35350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0022803679 |             f\n",
      "   708 |    35400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027888022 |             f\n",
      "   709 |    35450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027054575 |         nadir\n",
      "   710 |    35500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011661081 |             f\n",
      "   711 |    35550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0028851426 |             f\n",
      "   712 |    35600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008837208 |             f\n",
      "   713 |    35650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020612392 |             f\n",
      "   714 |    35700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0072301163 |         nadir\n",
      "   715 |    35750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011233038 |             f\n",
      "   716 |    35800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032179835 |             f\n",
      "   717 |    35850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0008285258 |             f\n",
      "   718 |    35900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015416144 |             f\n",
      "   719 |    35950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037614412 |             f\n",
      "   720 |    36000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0004071642 |             f\n",
      "   721 |    36050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0032213138 |             f\n",
      "   722 |    36100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0011455521 |             f\n",
      "   723 |    36150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025926833 |             f\n",
      "   724 |    36200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013131177 |             f\n",
      "   725 |    36250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017364409 |             f\n",
      "   726 |    36300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0033934291 |             f\n",
      "   727 |    36350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015480977 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   728 |    36400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029382875 |             f\n",
      "   729 |    36450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0020743466 |             f\n",
      "   730 |    36500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029594443 |             f\n",
      "   731 |    36550 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0012765000 |             f\n",
      "   732 |    36600 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027275203 |             f\n",
      "   733 |    36650 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007125618 |             f\n",
      "   734 |    36700 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0081381046 |         nadir\n",
      "   735 |    36750 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0015287537 |             f\n",
      "   736 |    36800 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0034987296 |             f\n",
      "   737 |    36850 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016146593 |             f\n",
      "   738 |    36900 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025338513 |             f\n",
      "   739 |    36950 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016600048 |             f\n",
      "   740 |    37000 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024515286 |             f\n",
      "   741 |    37050 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0037434715 |             f\n",
      "   742 |    37100 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0024323483 |             f\n",
      "   743 |    37150 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0025048642 |             f\n",
      "   744 |    37200 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016205184 |             f\n",
      "   745 |    37250 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0027035479 |             f\n",
      "   746 |    37300 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0007055728 |             f\n",
      "   747 |    37350 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0017480088 |             f\n",
      "   748 |    37400 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0029996858 |             f\n",
      "   749 |    37450 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0013487076 |             f\n",
      "   750 |    37500 |     50 |  0.000000E+00 |  0.000000E+00 |  0.0016026670 |             f\n",
      "Solver time : 126.05\n"
     ]
    }
   ],
   "source": [
    "start = time.perf_counter()\n",
    "res = minimize(problem,\n",
    "               algorithm,\n",
    "               termination,\n",
    "               seed=1,\n",
    "               save_history=True,\n",
    "               verbose=True)\n",
    "print('Solver time : {:.2F}'.format(time.perf_counter() - start))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdcaefa0",
   "metadata": {},
   "source": [
    "## Plots the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "aaae91ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solution limited by the areas\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAAItCAYAAACpT8sTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOxddZwcVdY9Va3j7h7PJBN3IQkJgQR3C87iy7KwwH4ssAa7CyzuLO4enABxd5fJuLt2T3t31fdHSVdVV3X3SI9k6vx+kJnumn7V3VXv3XfvuecQNE3TUKFChQoVKlSoUDFsQA70CahQoUKFChUqVKjoX6gBoAoVKlSoUKFCxTCDGgCqUKFChQoVKlQMM6gBoAoVKlSoUKFCxTCDGgCqUKFChQoVKlQMM6gBoAoVKlSoUKFCxTCDGgCqUKFChQoVKlQMM6gBoAoVKlSoUKFCxTCDGgCqUKFChQoVKlQMMwzqANDlcuGxxx7DnDlzMHfuXMyZMwebN28GALjdbrz55ptYsmQJTj/9dEyfPh033ngjmpqaAr7u6tWrMWPGDCxcuBCLFi3CsWPHfJ4bPXo0oqKiMHXqVJx99tmora2Vfa2tW7dizpw5WLRoEebMmYMtW7b0aDy559Tx1PGG23jD4T2q46njqeOpc0yo32NQoAcx7r//fjo/P5/u6OigaZqmf/75Zzo8PJwuKSmhq6uraaPRSB86dIimaZq22+30smXL6IULF/p9zV27dtGRkZF0YWEhTdM0/d5779EZGRm0yWTin3vhhRfolJQU+sUXX6QzMjLohx56iJ4yZQrt8XhEr1VRUUFHR0fTGzZsoGmapjdu3EhHR0fTFRUV3RpP7jk5qOOp453K4wXz/FB/j+p46njqeOocE+r3GCwGbQDo8Xjo8PBw+umnnxY9np+fT9999910Y2Mjfccdd4ie++KLL2gAdG1treLrXnTRRfRll10mGocL9rjnpk2bRj/wwAP8c08++SSt1Wrp77//XvRa9957Lz1r1izRYzNnzqTvu+++bo0n95wc1PHU8U7l8YJ5fqi/R3U8dTx1PHWOCfV7DBaDtgTc0tICq9WKlJQU0ePp6enYvHkzkpOT8fLLL4ueMxqNAACn06n4uuvWrcPMmTP530mSxPTp07F27VqsW7cOEyZMwP79+zFz5kz+uW3btmHMmDFYu3at6LXWrl0rei0AmDlzpui4QOMpPScHdTx1vFN5vGCeH+rvUR1PHU8dT51jQv0eg8WgDQCTkpIQERGBqqoq0eM1NTWoqamR/ZsdO3ZgxowZyM3NlX2+tbUVnZ2dSE1NFT2empqKoqIidHZ2giAI/jHu37KyMv5fIbjHpa/FHRfMeP7+Xgp1PHW8U3W8srKygM8P9feojqeOp443cOMNhzlG6TWVMGgDQIIg8Pvf/x6vv/46qqurAQAfffQRSktL4fF4fI5vaWnBm2++iZdeeknxNa1WKwDAYDCIHjcYDPxzNE2LjuGeEx4jfD1/rxXMeP6ekzt/dTx1vFN1vOHwHtXx1PHU8dQ5JtTjBQttt47uZzz22GNITEzEVVddBQCYPXs2br/9dvzwww+i49xuN6644gr84x//wOzZsxVfLzw8HADgcDhEjzscDv45LgPIHcM953A4EBER4fN6/l4rmPH8PSd3/up46nin6njD4T2q46njqeOpc0yoxwsWgzYDCAAajQb33XcftmzZgi1btuC///0vOjs7UVBQwB9DURSuu+46LFq0CLfeeqvf10tISEBMTAwaGhpEjzc0NGDMmDGIiYnhM4DcMQ0NDRgxYgT/rxDc49LX4o4LZjx/fy+FOp463qk63ogRIwI+P9TfozqeOp463sCNNxzmGKXXVMKgDgAPHz6MtrY2/neaprFlyxZccskl/GN33nknMjIy8MgjjwBgCJT+6uCnn3469u7dK3rN/fv3Y9myZTj99NNx/PhxTJ06FXv37uWfW7BgAYqKirBs2TLRay1dulT0WgCwd+9e0XGBxlN6Tg7qeOp4p/J4wTw/1N+jOp46njqeOseE+j0GjW71DPcz7rzzTvqvf/0r//vzzz9Pz5kzh3a73TRN0/SDDz5IL1q0iN6zZw//3+9+9zteP4emaXrJkiX0Qw89xP++a9cuOioqij558iRN0zT9wQcfiPR6oqKi6BdffJFOTU2lX375ZTojI4N++OGH6SlTptDXXXcdvWrVKv61OL2eTZs20TRN05s3b6ajoqJ89HoCjSf3HE3T9PXXX6+Op443bMYL5vmh/h7V8dTx1PHUOSbU7zFYDGoO4OzZs/Gvf/0LP/30EwwGAyZMmICff/4ZGo0Gx44dwxNPPAEAPi3THGcQAGw2m6hWPmvWLLz33nu46qqrEBYWBpIk8csvvyAqKop/7vHHH0dERAQefPBBjBw5Evv378f333+P+++/Hy6Xi3+tnJwc/PDDD7j//vuh1+vhcDjw448/Iicnp1vjyT0HAHa7XR1PHW/YjBfM80P9ParjqeOp46lzTKjfY7AgaJolvalQoUKFChUqVKgYFhjUHEAVKlSoUKFChQoVfQ81AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmCMoJhKZpmM3mUJ+LChUqVKhQoUKFil4iKioKBEH4PSaoANBsNiMmJqZPTkqFChUqVKhQoUJF6NDZ2Yno6Gi/xwRlBTcQGcCXXnoJZrMZUVFRuOuuu9Tx1PEG3ZjqeOp46njqeKfSmOp4Q3s8IfosA0gQRMBIsq9hNBrhcrlgNBr7ZWx1vKE93kCMqY6njqeOp453Ko2pjje0x+su1CYQFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQY1AFShQoUKFSpUqBhmUANAFSpUqFChQoWKYQbtQJ+AEpxOp+hfdbzBPx5F0WgyO7CnohXtVhe0ADq6rLj74wPIjA/DiMQIpMYYEGHQIUyvQZiO+c/I/qzT9G4/0l+f5UCMV9rchS6rDQDQZbXh3W3lCNNrYNRqYNSTMGg10JIkSBLQkiQ0JEASBDSk4D/B7yRBQKthHiNJAlqS+VdDECAJoNPmQkeXFRoANrsDHoqGhiRC+h77+56w2Bz9Ot6peM8P5HjScU/F8fpzrKPVbWgxWWAggDazFQueWAcNSUJLENBqSOg0BLQkCZ2WgE5DQq8hoeXnF7DzCgmNhoBWMK8I5yCthoRGMPd45zQ7PtxZwby+hjkWBEBRAE3ToGnAAxq0B6BAg6JpeCjATdFweyi4KYr9mWZ+9jA/uzwUOu0uNJnsaOtyYnaXFToAFpsdn+6ugstDw+XxCP6W+RsPRcPlpuD0UHC6KfY4yvsff7wHbg9zHszfuOFwU7A4PbA6KZxHMJ+nw+Hot++xOxi0ASBN06J/B+t4dpcHbRYnOqxOtFtd6LS5YLK7YLK5YLa7Yba7YXG4YXG6YXV4YHV5YHd5MNnBBEh2pxuf76nCsvwUxEcYQvDOGPTF5+l0U6jvtKG23YaaDubfihYLjtZ2oq7TBpuL4o+9zOiBlgA8FI3vDtcF9foEAIOWRJhegwi9BhEGHYw6EkadRjZgDGMfN7I/u9weAMyYLg/V64AyEPr62nS4PahstaKsuQvFjV3YV9mOwgYTGk0O0ACuNlLQE4DDTeFv3x/v07HlcLWRhoYArE43Rj70EwDmOyIAEASg0ZAgCSbQJAmAIAjvz+wxAMH+yzzGfWQ0aNA0wf7LTJ7nEy7oCKDL7sKYv/wE7tOl+f8Jfhf+REsflzlW5pirjW7m83R5UFhvgkGngU5DQK8lYdBooNMSzCLXR9fRUJnThsp40nFPxfH6c6xzX96Bq4zecWva7SEf0zunefDwN8dCPt4sIw0QzLr956+PhHw8gv08nW7K/4EDhEEbABLsqsH9G2pYnR5oAVhdHqx4bjPsbibyd7o9TPTP7io8FLP7oHp5X040AloCcFI0HvjqCPDVERAEEKbTICFSj7yECEzJisXE9GjERRoQE6bj/zPqNN0eL5jP0+Jwo7ZDHOAxv1tR22FDo6n7uxga7MIf5LF2NwW7m0K71QWgexPQVUYKBgJo7nJgzMM/IyXKiIy4MGTEhiEjLgzpsWHIZH/OiA1DhKF3l39Prk2aptFocqCsuQulLRaUNXehrNmC8hYLqtusfj8nWvJvqCE3Hg1vQObp40mNYidLCoDTE/p3yY3g8FA46/ktiseRBJiMh5aEQUvyP+s1gp+Fz7GPif+GgNvTv4tAf8+h/T2edNxQw2R3gwDg7odrk0N/fpb8vY2BnWNOxfFcvQ0YQoRBGwDq9Xo4HA7o9fp+Gc9Bk9ASHjgoEicazCEfzw0NDKDghjeYo2kmELW22VDdZsPm4hbZv9WSQFyEOCjk/ouW/B4bzvyr1engcDhAaHRYc7QeNXxwx/7bYUOH1dXj9xNt1GJUciQWjUnC2QVpeOPVQ/z7LP/P2QCAti4nChtMKGnuQkWLBbXtNjSa7WjtcsJkd8PmdMPloXt8c3KfKcB8lg0mOxpMduyrbJc9PiZMxweHGbFh4p/jwpAQofc7AXPXqBwsDjfKWywoZQO8shYLylu6UN5sgcXp6fZ7IwmAJrQAnPw1QwAYmRyBKZmxyEuMAEEQbGmEhoemQbFlCb48ISiPON0emOxutFmcaLc60Wl1weRwQ5hwkLtGQ4nBOh5FM1lXh5tCb2aGy4wEIgig3UHjyjd24tzJ6ThrYiriI/p+jqNpGhTBvK/+mkP7e84Wjhtq/HKsAVanGxEE4CH75/oE/M8xoUAo7kGuGiAXAw3We76vx4uJCOuX8bqLQRsA9ifazd2/wcK0JIx6DSL0WkSGaRCp0yIyTIcIvRbheg0iDFq+lBmu1yLCwPwbzv6++etC2K0uxIfr8cpFU3GywYwD1R2oaLWitcsBm8ujmGV0U0Cz2YHmbpz3ZUYHIgig1eLAbR/uVzxOy/K83H52LBF6DXISIzAjJw4rC9IwKzcOJOktkx2r6xQdf+/nB3HH4lEYlRyJeaMSMW9Uos9reigarV0ONJkdKG/pwpFaE0qbu1DXbkOrxYkuhxsOlwfd3XwTBFNWjjRoEW3QgSCAFosTnTYX/9/xepPs3xq0pCgoTJcEiRwcbgpvbS0XZfMaTP6zl3oN4TfLRQBIjTFidl48Lp6eiQWjEvHssydhNjsRG6bD7LR47CpvQ0mTBSVNFqREG3D5jCxcNjMLmXHhoteiaRoNJjuO1HTiSC3z39HaTrR0Bc8v0mkIRBq0/CZDryHg8NAwWZ1oMNnhcIvfS5hOg5FJERiRFIGchAgkROhQ0mTB3sp2FDd2wcNGmlqSQHZ8OLLjw2Gs0wAeFwxaDU4bkwiHi4Ld5YHV6YHFydApuuzubm8QdBoCCRF6jEuLxtLxyVgyJhELntwU8O+y4sNwwZQMnDUhFTHhOqYi4KHgctNwejxwsNwgJ1ct8HjgctNw8Lwhin/O5aHgOHgMcDGbrB1lrdhR1opHvj2K+aMScc6kNJw5IRUxYbpuvjtfmO0uPLT6KMJsLkQQgKufM4+nGuo7bXjwq8NYzv5ODaOPk8t+ezwUPHTPMmc0gFBXskl2no8L1yMvKQLzRybiwqkZSIsNw/aSFlz15q7QnkAAeNQM4ODFJ3uqfB7TkASumpWNC6amI9Kg44O6cL0GBi3Z69T8Dg0BOwC9lsTKSelYOcn3GJPNhQ0nm7CtpAVHa02oabfCHGAB1GtJhOlIhOm1MGiYjFCXwwM2MQaSIFCQEQ2DlkSXw41WiwsdVidcbDAiDfx0GgJpMWGYlBmD08cl48z8FEQY/S9S0ozb1/trsXp/LcamRmFkYgScHgqtXQ6029ww2VywON2wu0Izq9I0YHdRsLucooAnTKdBcpQBeUnhGJ0SBYIG6k0O1LFZ0UazHQ43hbIWJnsnh8uMdiajY3Xi9R98OXkJEXrkJIQjTKtBg9mO6nYbzwWRC/4SI/WYkROPC6elY+m4FEXumVGnwWe3zkVpcxc+21ONL/fVoNHkwAvrS/DihhLMzovH1KxYkASBY/UmxWBPQxJIjTai0WT3G/ADgMtDo93qYkvz8tCSDDnc6aZgc3lwtM6Eo3VMcC2lAUzMiMZVs3Jw7uQ0RLHX0zPPbIXZbEdcuA7/vHE2AKCly4GjtZ3YX9mOHWWtONlohsnm9nuucufeYHKgwdSMjSebZY8xaEk4BCVtLQlUt9nw4voSvLKxFEvGJuHymdlYMjapx5zAZwp/htkFJEUa8Ocl4/DD4TocrTVhc1EzNhc14+HVR3HamEScMykdy/JTENkDisLR2k7c9fF+VLRacRlbUu/HiuUpBw9F455PD6LD6uL5XFQ/cw4HElz2e6BBANCym9C0GCMmZ8bg3MnpmJUbB61W+T5ptzhx03t7ejSmQUsgKcqIEWyy4/TxyYgy6LDuRD1+OtqE4/UmWIOs5mg1/UuLCBZqAAjgl2P1GCv4fcXEVPx8tAEf7KxES5cDT1wyCdEBgp5QIDpMh/OnZOD8KRn8YxRF43BNB9YXNmN/VTtKmrvQ0uXgeSlcxqFTsEgatCQ0OuYCpGngSK18xosAkBCpx9jUKCxgsxJZ8RH8824PhU6bC/VNXei0OdFucaHd6kSHlfm3zeJEaXMX9la041Kj+LVpAIUNZhT2Q3k9GNhcHlS2WVHZZsXGk0ypXa8hkBhpwOTMGCyfMAYT0mPQbnXxpfK6Dm+5vLbDxr+WliSxYmIqRiRFIC8hAgQBbCtpwZbiVuyv6lA8h2ijFtNz4nD+lAycNSEFRn33bscRiRG4cX4epmTF4ruDtdhV3oZ2qws7y9qws6xNdKyGJDA6ORIFGTEoyIzBuNQo/HCoHu/vrAxqrAeWj8Hk7DjUd9rR0Glj/7Uz/5rsaLM4mU46Sn5ClC6ZJ+pMeH5dEb47VIuCjBhMyYrlM1VdDjeufGMnjteb0GlTDjgJAGkxRhRkxmDJ2GScNiYJaTFGmB1u1HfY+e+rvtOGug47ajuY77Cm3ebzWlFGLTIMWpS1WgEwWfasuDAkRRqwv7oDa080Ye2JJiRHGXDJ9ExcNiMLuYkRPq8TDDQkgdsWjcRti0aivMWCHw7V4YfD9TjZaObHMWhJLBmbjHMmp2HpuBSE6f2XrGiaxgc7K/HYDyfg9FDIiA2D1kkANEAP0uzDUMArG0qwq7wNEXoNoo06uB2uYRUADjSun5uD/zt7PAxa+eufpmk0mx2oZ+ek+g7m37pOO+rarThY0xl09i3KoMFNC0dg8ZgkTMqMBSlRPbA43Phqfw0+3FWjmBQAgIxYIyZlxODnY438Y2Q/82KDhRoAAqhotYoCwFeunob3tlfg8Z9O4OejDTheb8LLV03DxIyYATtHDiRJYEp2HKZkx4kebzbbsb6wCTvL2nCsrhN1HXZ0OZgg0OGm4NEy3U9Shp2OJBCm1yAmTIcooxYkQaDD6sL3h+rx9f5aONhsjsXhDnq30xNwPBGSYLpGhfIkGtIrP6BnSfYGHclIoOg0CDeQTAmSjWX0GhK5CeFot7pgcbgDZrc4OD00M3F02vHL8Ub+vML1GuQlRmBlQSruWjIKWQnhoCgazz57Al1dLsRH6JGSGoVvD9aiotWqWLoP02kwKTMG509Jx9mT0hAT1j3uEve6XQ43bnhnN47UmtDS5UsDIMBcJ8KJb3ZePFbNycGy8Slo7nLgro/344BMcEoSwH8umoQHvjosevz9nZXYefpoxXOzuzw4XmfC53ur8dvxRrRavBnHcL0GBCDiPnpooNHkQKPJwQerlxmdiCCY97ejrNVnjJgwLfLTYrBgVCLmj07E+LQo2YUh2qhDdKoOY1OjZM9z3CNrfB5v6WIyxGkxRtR3MuX76nYbmswOvHL1FByo6sTX+2uZ3zeW4pWNpZg7IgGXz8zCWRNTe9SYBQB5iRH4/dLR+P3S0ShuNOP7w/X44VAdylosWHOsAWuONSBcr8HS8Sk4Z1IaFo1J8hmr0+bCg18exppjDQCA5fkpePKSSXj22T2AW557pSIw9la04bl1xQCAf14wESXrj8HtAIZjRV1LAuvvW4zsBO+mp8vhxveHavHmlnKUNisHRFKkRhuxcHQC5o1KRMm6QlgtLqRGG/HHBWPw8oYSOD0UNAQBD03j3R2V2FjUjBvm54IkSW+A1+HdhDp78YUsHZeEdYVMVcDs8OCXYw24Z9kY0THVbVa8t70Cn+2thtnOrKlhWgJ2ty9fffGYRLx2zQxc8caOHp9Tf0INAAGY7R5AkLEiCALXz8/DlOw43PnRflS2WnHRq9vxt3Mn4MpZWf3e5RYMkqKMuHxmNi6fmc0/5vJQ2FfZjt+ONcK875Ds37koGi67GyZ798pqPUVmrBFpMWHYX9XOl6am58ThriWjsHhsUo8/W6ebwiOPrQXAZE43/mkJ/5zbTaGoyYwjtZ042WBGeYsF9Z12tHQ5YLK5/HLxaDCBC1fOfPKXIgBMkHWZ0Y5wAmgy2/H52mKfv9VpCIxNicJ5U9JxwZQMJEcbfY4JFvur2tFktvMB0ga2lEkSwOjkKBRkxqAgIwYTM2KQnxYNDUlg3YlGfLy7CluKW7C9tBXbS1sRbdTyDQ1SaEkCm+5fjPTYMJ8AsMHEfFbREo6ah6KxuagZn+yuwrrCJj7ojDJqcdHUDFwxKxvj06IBMNdjk9mB2nYb9la0YX9lO042mlHf6VuC1pIERqdEYu6IRMwewZS0e/P5cfhib7Xf5+s77eCuQBrM5umOjw7ijsUjse3B07HhZBM+3VONzcXNPI8v+lstLpyagctnZiM/PbrH5zY6JQr3nhGFPy4bjeP1JvxwuB4/HK5DdZsN3x+qw/eH6hBl0OKM/BScOzkd80cl4ni9CXd9vB817TboNAQeWjke18/L5SV5gOFVsuwrdNpc+MOnB+GhaFwwJR0XTcvEfzewVRQwvE+99tTxUaACEBvdFHDJq9vxy72LsL+yHR/vqsLGomaf7Jqc4oOWJET3d4PJjk1FLSAJEjHs4zanB2EUhSXjkrCjrFVE86hoteKv3ynLXhEEQ6tIiw1DeowRqewmbs3RBsW/4e6NTpsbD5w5hp/XT9SbseSp9Vj/pyXYWdaGd7aVY+2JRn4TlZcYgdgwLQ5Ud/q85nVzc/DXcyeAJAmcqB8cla5AUANA8PQ4HuXNXchLisSUrFj8ePcC3Pf5IawrbMJDq49gd3krHr+woNcSIv0BkiBQ3mLBNwdrsVTmeS3JcCoiDFoYdayshZYEweq4MUKbTEnZ7qLQbnX2KAto1ABumpkEajrsqOmwQ68lkRltQF0H06V7w7t7MCE9GnctGYUzJ6T6pN8DgZPigMdXc0mrJZGfHoP8dOUMbn2HDYdrOnG8vhMlTV0obe5CbTuTRVXSl5M+ThJAdnw4zp2cjkunZ4p2y73F65tKwZ19mE6Dv52Rj4LMWOSnRSuWB1cUpGFFQRqq26z4ZHcV3t1e4TfQ/+bOeciIC0ezWb6B5ZnfivC38yYAAOo6bPh8bzU+31ONuk7v8TNy4nDlrGysLEjzOS+dhuS7rWflxfOPeygax+tM+PbD4/A4XEiMMKDwkbP6TH9PiH/9dEL28a/vmIO7Pj6Iug677Pf9ysZS/Ha8AR/ePAcrCtJQ22HDF3ur8cXeGtR22PDejkq8t6MSBRkxuHxmFs6bkt5j2ghBEJiQHoMJ6TF44MyxOFTTiR8O1eHHI/Wo77Tj6wO1+PpALYxaEg4PBZpmGlZevmoaJmXG+ryeGgB2DzRN46Gvj6C2w4bs+HD884KJAJj7m0O71YmUPtiQDBbsq2gLeExTlxPT/vFbQKmq9Bgj5oxMwJwRCZg7IgFZ8eGo67Bh48lmrC9kOO1NZgc+21vNZ/077S78b31JwHNIjjLgomkZGJ8WjbSYMKTFGJESbRQF4/ur2nDxq/4zcDRNw6AlsbeyHXcsGYnHzs/Hw98yQWZ5qw2jHvpJxJ1dODoRl83IxEOrj6Jcpvz7l5XjcfPCPBAEAbvLw2+wNYMwWSTE4I9iBgBvbyvHPy8oAADEhuvxv2tn4I0tZXjql5P45mAdjtR24tVV0zEmxbfENFiw8WQT/v1TIU42sjsRdq5KiNBj2z2nIy5chzCdxm/Gzely4/XNZfhoVxUaZDQASQLISQjHuZPSMTI5Eia7G1/tq8HB6g7x63iAkn+dhXe2VeCd7RWoYZshKtsYLlaUUQuHy4NjdSbc/tF+jE6OxB1LRuLcSendCgL0Gg0oT89Iy2mxYUiLDcOZE1NlnzfbXNhc1IyfjtZjX2W7qMTJIUKvwaUzsnD7ohGirujeorrNit+ON+ISVic8JkyH6+fnBf33Bi2JfZXtfoP3+SMTEMZyENefkN85f72/BvNHJeLT3VXYcLKJ3xXHhOlw8bRMXDkrC6N7cE9oSAIFmTH4Ta+B2cEQpkMR/P1l9RGRWLkQh6s7sf3PS/H53ir85eujsrpdxU0WzP/POrx45VSsKEjHPcvG4Penj8a2khZ8tqcavx5v4LusH/vxOM4uSMcVs7IwIyeux5ltgiAwJSsWU7Ji8dDK8dhf1Y4v99Xgq/21sAuu8y67G5/vrYbV6cHM3HhoSGYhMmLwdiAOVny+txo/HqmHliTwwpVT+SYlIVq6HKdUAPhxkFxguSspJdqAuSMSMJcN+rLjw32u9/TYMFw1OxtXzc6Gw+3BrrI2bDjZBMeBwwDNzFFXzc5GegxTIUqLNSJcp8Hb2yrw3SHGSIAA0GR24IMdlfjruRMwM9f3vqrrsOGqN3Yqdh1zmT8awHmT0/HFvho8ueYk3rl+JtYXNmM9W1nhgr/LZ2bhdwvzsLu8Fb//5KDP62lJAk9fNlnE099e6pVvM+o0QM/V1UIONQCUwYaTTaLfSZa0PT0nDnd9vB+lzRac99JWPH5BAS6enjlAZymPE/Um/OunE9jCagjGhutwwZQMWPczJWAuC6MEu9ONp38rwtf7a2WDHB1JYFJmDB5cMQ6z8hJ8nn9zS5nPYxQAkiRx08IRuGnhCJQ3d+HfPxdi48lmOD0Uz6vQsETA4qYu/PGzQ3j2t2LcvngkLpqWoUgCFkKvJWF3MhnAvrYuiwrT4ezJ6Th7cjr/2DPPFMJsdvHjmB0ePPXLSby4vhhXz87Bg2eN65My0Yc7K0HRDLfRJ10dANtLW3D7h/tETUEAMCY5EkVNXfzv20pbsfTpTZiVF6+YATTZ3fjd+3v532fnxeOq2dk4c0LPOXD9hWO1nfhol2+3P4c3Nhbh+vkjcNmMbJwzKR33fX4QPx9t9DnOTQG3f3QAF05txOMXFiBcr8VpY5Jw2pgktHY5sPpALT7bU43ipi58tb8GX+2vwYikCFw+I6vXXDwuK76pqJl1umGCw+JGM9qtLny4swof7qxCcpQBKyamMlI7hJoB7A5Kmsz4G1tu/NOZYzElK1b2uNZuSCgNBWwvC5wBFGJ8ahSumZuLuSMTkJvgG/D5AyPzxNwzzxT/ArPZibhwPe69sMDn2Bey43DpjEw8/M1RVLINWhanBw98dRi/Hm/Efy4uQGIkszM22V24+NVtsLuVr/cwQUBG0TTC9RoUNpgx/4n1svfn6v3V2FXWigp2bCEiDVq8cc10H1mzD3d655kIgwYWNQAcWmhScLyYmRuPH+9eiD9+dhBbiltw3xeHsLu8DX8/f8KAL4CNJjue/vUkvthXA5oNFq6bl4O7lozGusJG7FSW/oPZ5sJjP53AmqP1PoECwOzOZuTG4eGV4zHeTxnV7vKgSuZGkSIvKRJvXDsDFEXhkz3VeGNzGSpbrcyui12sSAKoarPi/74+gufXFuPWRSNwxcxsv92QOlZahwaNY3WdsuWwUCAp0oDV18/DX1YfwfF6M+wuRhfw/R0VOG9yOv523gTZLEIwsDrd+GQ3M6FEGLRw2oLTfqQoGi+tL8YzEm5iQqQej549Hvd8xmwIsuPD8Mg5+fhsTzXWFzZhd7n/hUBLErhxQR4un5mFkUmRPXhH/Q+Ph8Kqt/zrgNWZvdnRcL0Wr66agaO1nbjpvT2yDjirD9RhR2kb3rh2On+dJUQacPPCEbhpQR72V3Xgsz1V+P5QPcqaLfj3z4W8bFCnzYVnfitCGstXSosxIi06DNFhWsWFlKJovLqpFM/8VgQPRWNEYgReumoa8tOj4fJQ2F7aih8O1eGXYw1oMjvw3o5KXgZGTQAGB7vLg99/chA2lwcLRiXiloUjFI9ttQxOb9eeormbAe2JBjPGpUUhr4ed8N3BwtFJ+OWe0/DCumK8sbmM5xOuPdGI5c+04T8XT8KSccm45n87Ud/p/3sx6kjY2YDsu0N1vPwZRTNc9JsW5KHD4sRD3xwFwFSv5IK/lGgD3r1hFs9vFoKbQwkM3u5fDmoAKAN/TQGJkcwX/9L6Ejy3rgif7a3GoZoOvHL1NIwYgAXR4nDjjc1leGNzGWwuZhE7e1IaHjxzHLITGEHgSpkLuMlkxz9/PI4NhU2MTqAE4XoNFoxOxCNnjxdJwfjD7vK2bgmFkiSJq2fn4OrZOajtsOI/Pxfit2ONsLsp0aLVYLLj798fx0vrS3DzwhFYNSc7YEC1vbS13wJAAJiaHYef/nAaSpu78H9fH8Ge8ja4PDS+2l+L1Qdqcfq4ZPzrwoJuNzKsPlALk92N7PhwGLQkgpmm2yxOXPvWLl6Dj8Mdi0fi5oV5mPef9aABhOlIfHfXAsSG63FGfirqO234fE8Nnl1bpPjaFEXj/uVjoAsiIztY8PtPD/jVL1TCxIwYbP/zUry5pQxPrin00dNrMNlx/svb8KflY3HbopF8JpggCEzPicP0nDg8ck4+fjhcj8/2VAOsBKHN5cF763ybhsJ0Gp7TJAwOw/VafLirku/avnBqBh67YCLPQ9ZpSCwak4TZefGYMyIeb2+twDGBuHl/e+UOVfzn50KcqDchPkKPZy6b7JeHfKplAHvSR3v1/3Zi3X1M01ioYdRp8MBZ43DelHQ89PURXl6rzerCLR/sQ0qUHo1m73dCwvueuMYUPatRysHlYbzOtRpGA/SCqRlYWZAGAPhgVwVO1HsrJEKMSo7EezfOkq2kOd0Ur74RH9H/0nHdhRoA9gAaksAflo3GjNw4/OHTAyhsMOPcF7fiiUsm4ZxJ6YFfoA/goWh8sbcaT/9WxDuCTM+Jw0Mrx2N6jlgipqrNCu5SbLc6Mf6RNXywKESUQYtl+Sl4+OzxSGDT6t3BL8eUu65omvZbJsiIDceLV04DRVFYfaAWr2wsQ2mz+AZstTjxxJpCvLqxBDfMz8MN83MRGy4vpbK9tBW3LRrZ7ffQW4xMisTnt85Fo8mOv6w+gvWFDFdu7YkmrDuxDjPz4vHviwqCyp7RNI13t1UAAK6bl4vO3QcC/s36E4249cN9/M4WYLTyvr9rPuIjDFj8342wuygQAD68abbo80uLCcMflo32HwACeHNrOW5fPCrguQwG/Ha8ET8dUb4uA0FDErh10UicOzkd939xCNtKxfI0NA089ctJbChswvNXTvVZFKKMOlw5KxtXzsrGk//dCZvFhUiDFldOykZDp40RqO60od3qgs3l8Ss8DjCk8t3lrbj+nd1IjQlDarQBbg+N4iYz9ld1yPI8mcS6//tvuGPdiUa8u70CAPD0pZMDbtTk6DGnIoSySFLYXBQufmU71v1pEcK7qWHaU4xLjcaXt83Dx7ur8J+fC/lgSxj86UhASPWNNGhhdrih0xAwOxg7Pw5/XjkOBq0Gj357DC+sK8aSMYk449nNilzhpCgDPr55tuL1caSmg/95wahEoL7n77U/oAaAvcD8UYn48e6F+P0nB7C7vA13fXwAe8rb8JAf4cq+wKaiZvzrxxN8g0d2fDj+vGIcVkxMlZ3kK1st4JZrTtePQ1y4DudMSseDZ41FZC/Frted8OVMcWg2O4LKfpEkiYunZ+Hi6VloMtnxxJpC/Hy0QbSwmexuPL+uGK9vLsV183Jx84IRSIoSB6x7ytsGVKohJdqIN6+bCbPdhb9+ewzfHaqDm6Kxu7wNS5/ehPy0KDx+YQGmSvQchdhe2oripi6E6zW4dEYm3tytPJ7T7cGtH+zj5WE4/HHZaPyB1bW6/cN9qGpjssEPrhiH6bnxPq8TDD7YWTkkAsAuuwu//9gP90ECf0FSemwYPrx5Nn451oAHvzyETrs40Npb2Y5lT2/Ek5dMxrmT5TeBnM1ipEGLRy8S853sLo9AWJsRsP7tWCMO1TByExpW19FD06jtsKO2ww5A3uMaYBqShLA6PUNCuWAg0Giy4/4vGdmjG+fnYcm45IB/0yqjv3kqQc82YV06PRPv7ahUFGSvN9lx8Svb8OPdp3VbuaGnIEkCq+bkYOm4ZJz30jY0S74L5h5mNsAZsUb2XmG4g4SROUeuNLv2eBM+uGk2/relDNVtNix4cqPfsZvNDtzx8X68tmo6zz0U4rN9NfzPtywagV8+9f96A41TR8ioh3AqdEaWNAWn45MSbcTHN8/GHYuZbNN7Oypx6Ws7UN0WmAvXXRQ2mHDt27tx3du7cbLRjJgwHR4+ezx+u/c0rCxIU1y8qtrEzgdJUQbcsXgkiv95Fg48uhz/vGBir4M/xv9WeVLcUyZvweUPydFGPH3ZFBz/x1l45appGCcR9rW7KLy+qQxz/r0WD39zhCe7kwQBm8uDQ4Ld2EAhyqjDM5cz7+GmBXkw6phb7ni9GRe+sh2Ln9qA9YVNsn/7zrZyAMAl0zP9Sor8erwBk/72qyj4S4nSY8efT+eDv7e3luNnVhdrydgkxeyo0x1Y5qeuwy4rhTDYsOqtXaJO2UAI5K1NEATOmpiGLX9eimvn5vg8b3NR+P0nB3Dv5wdhtnev5GzUaZCbGIG5IxMwb2QithW38sHf5TOycPRvZ+LQo8vx6DnjMSkjBsI7XUMSiI/QISFCx0uVWCTzWocfR5XhDA9F44+fHUSbxYn8tGg8uGKs4nFCGsGpVgKWgktgHKrpxHs3zuI3L3I40dCFS1/f0a9UA5Pdhds+2ucT/AFiCpdw3pycGYPESKbiYWATA0dqO6EhCZhk7o8wnXx4tLeiHee9uBVHa321ANcd9yZBJqTHBvdmBhDDPgDcraB/9M7W0qBfQ6sh8cBZ4/DO9TMRG67D4ZpOnP3CFvzqpyTaHTSa7Hjwy8NY+fwWbC5qhk5D4OYFedh0/2LcvHCE32yjxeEWuUVEG3XY85dleOCscdD1YePKBoUghsP7O/wL8AbCyklpWHPPaTj46Bm4alaWyCfVQzGdV03sAs5l/baX+LpJDBT0WhKPnJOP438/E/efORbRRub8K1qtuPHdPZj9+Fp8tc/7GVW2WrCO/UyvnZsr+5q1HTZc+cZO3PL+PlGgc8vCPOz6yxlIY8uR+yrb8E/Wqzg12oj/XTtD8Tz3VyhnlYR4ck1hUMcNFN7eWo6DrFhrUlRwjivHJZxJJUQbdfjH+RPx9R3zkB3nm9X+en8tTn9qo48ndjDYXNSMlc9vwY6yVoTrNXj2ssm4ZEYm/vbdMcx/Yj3+8cMJHK7tBA1gzoh4/PfSyTj81+XY/8hy7HtkOYofX4ldDy3F7Dxxdrd9mJQsu4vXN5die2krwnQavHjVVMW59D8/n4BDsDlqOcU/TwMb/Owoa8XYlCg8d8UUv8fvq2zHxa9uh12GWtTXqGix4JwXtuCQRIx5ZGK4z7EnWOtRo47EV7fP43m6XMna6vRg5EM/+TQ/Jkbq+TLw/60Yh/uXi12Q6jrtuOS17fielagBmE1CG3td9MTHeyAw7APA7w7VyD6+paR7bfEAsGRcMn68eyGmZsfCZHfjlg/24fEfj/Mep92F1enGc2uLsPipjfhsbzUoGji7IA1r712Eh8/JV+S/CVElyUSGqltZKp0jxcHa7i+GcogN1+NfF03CgUfPwPmT0yG3MTWw5QuhHtNgAUmSuHPJKBz+25n490UFfOm60ezAfV8cxuS//4rXN5Xive0VoGngtDFJGJUs5gvSAJ5fW4TTntwgskyLNmqw5g8L8dDZ+fxjLWY7Vr25GzSYLumvb5/rV2MvWG/g9YVNg7a5oKbdisd/ZASfM2PD0GwObrH+9Xj3NmzTsuOw7k9L8PvTR0F6GTZbnLj41e345/fH4A7i/nd7KDy5phDXvr0brRYnRiVH4vIZWXhuXTEufW0HPttbjS6HG1nxYfjjsjHY8sASfHrLXFwyPVNU2tWQBFKijby0EoeOHjTBnOo4UNWOp39l+K5/P2+CIi/3091V+N+WctFjp3oJWEsSyIgNg9NNYUdZC86ZlI7zJqf5/Zv9VR0476WtATPpvcH2khac99JWn6pWQUYMzpyofH5Ts2JF855OQ/jcs0K0dDmh0xB4/oopuHXRSNx5+hj8camY9mJnM/5Prinkxey5GXFyZs8dgfoTQyNMDSH2VnbIPt6gQHwNhIzYMHx2y1w8saYQb20tx/+2lGN/VQdeumoq0mKC65byUDS+3FeNp38t4rNaU7Nj8fDZ4zE9p3u8LWkAGAqahsXhxs5S/9k2Rx85zTWb7Hj850L8eLhO1OggjGk0GuZNHqjqYCyG/EjHDCS45oBfjzXgsR+Oo6rdhk6bC//+2Ztdu26Ob6mxxezAJxJ5l3MnpeH5K6aIBKhdHgqXvLaD53y+dvV0pMf57pKFOFAVXKDucFP45mAdLpyaEfjgfgRN07j89Z3w0DS0JIHTxiTi493BZZ/XFypzWJWg05C4b/lYnD85A6ve2oUGk3jeeGtbBb4+UIsvbpun+Bp1HTbc/ckB7GUzhqnRBpQ0daGE1WmM0GuwsiANl0zPxMzc+KC4VrUdNkwU/N5hO7UzVt2Fye7C3Z8egIeicc6kNFw6Q17PdXtpC/7CSoII0XaKZwABYMm4JHy4swobCptx+rgU/PfSKdhQ2AizQ3lDU9TYhXNe3IJ3rp/VK1tEOXywsxJ/++6Yj7B5fIQer1w9FYue2ih6XGhLt6u8De/vqOCfazD5Ov5EGzWwuyg4PTR0GgLv3jAL8wUaf384YyxcHhovbRRXB1/ZWIrCBjNGCDKQq+bk9uxN9jOGfQawodMm+7g/KZhA4Mp9r62ajiiDFvsq27Hy+S3YGCBLBjAloLNf2IIHvzqCJrODt3j6+vZ53Q7+AASly9dbbC9tlXVO6EscrG7HJa9tx6x/rcM3B2r54G9CejQ+u2UONty3iD/W4nAjPcYIJ+uFPNixfEIqNj94Or68ba4Pz/HWD/figS8PocXsQLuVWXQ8gsybjiTwyc2z8eJV03zcR/7wyQFew+rmBXlYmp8S8FyC6W7kyhuvbQxs3dTfePTbY6jtYO7pv5+Xj1+OBR/UNZh6vqiPSonE9j8vwcXTfAPidqsLy57ZJMvD++14A5Y/u5kP/pjzYDZ980Ym4JnLJmPPw8vw1KWTMXtEQlDBn9nu8iHt90QG51QFTdN4ePVRVLfZkBkXhscvLJDlT5e3WHDbB/tknVSsTg+szv7xTw817DJ8VRrAkrFMM8yGk0y2X68l8eQlUwK+XqPJgUte247fjnd/QyUHl4fCI98cxSPfHPX5LrQkgc9vnYM/fHpQJB32+IUTce/yMfzvFM3MDU0K2ckxKREw6rT8uk9RNDLjfBM29505Fred5uvCtL6wCe9u91ZPzpwQeK4dDBj2GUCrK3SBy1kTUzE+LQp3fLQfx+pMuOHdPbhrySjcs2yMz7EnG8x4/KcT2FzEEPmjjVrcvXQ0rpmb06uO4sq20JP1A5V/ewq3h8K3h+rw3G9FqG73BuokASwem4y/nzcBWfG+GS2Hm8LcMYn4an8Ntpe2YMHoRJ9jBiNm5Mbjp7sX4rSnNqCGfb9uCvh8bw2+2FuDS40UtIJ1amp2LD67Za5sp/ObW8rwE9v0MSUrFn85e3xQ5xDMxoeLQU42dqHd4kRcRHAcu1BjX0UbPmBL2HNGJCAh0tivch0kSeLpy6ZgeX4K7vrkgChDDTCdvpwERVlzF/70xSFez4xDTkI4LpmWiQunZSAzQLZWCVwALERrCMtyQw1f7a/Fd4fqoCEJPH/FVMSE+TZYdViduPHd3SLvbGmI2NrlRHj80F9C1xX7BmodVhdm58VDryVR025DaXMXRiVH4ayJqZicEY1Dtf75slanB7d8sBcPnjUOt542oscSRB1WJ+74aD+2K1SYnrlsMl5cXyK6j66alYmrZ+fgyjd2AgBiwrRwuinYXBTTKChzKlVtNthdFEYlRyIhQo9d5W145rciPH/FVNFxBEHgwRXj4fTQeJuV6OLACVRrSaJPrUBDiaFxlkMYOQkR+Or2eVg1Jxs0Dby4vgSr3tzFd6xSNI0/f3UYK57fzDd43LQgD5sfWBKwwSMYyIlA9yVomsbGAA0g3UW7xYmnfinElH/8ivs+P8QHfwYtiWvn5uDgo2fg7etn+gR/QtX1OSOYbKnSxDFYsaWkBTXtNkQatFj7x9OweGwSSMLXg/M/FxVg9R3zZYO/nWWtPAcuNkyH926c1acacCa7m59Dn/lNWTOwP+FyU7j+3T0AGBHzd66fgS/2dr/xqC98c8+cmIZ19y6WzSAAjJ/p6U9v4hctnYbAJdMy8cVtc7HxT4vx+6Wjexz8AUAte78I7wdpaXq4oqy5C49+y5R07z1jjI9mKsBknO74aD/KW7xz57SsWJ978FTRAlxz2DcAdLg9eGNzGeaMYOw+OaUCgiDwjwvEEkZKDBuaZsS17//ysKiBJliUNJlxwcvbsL20FTqN7/x14dR0vLShBN8e9DZiaEngXxdNBgAcqe1gHyNldf0i9Bq+09fuojAjJw5f3jYXj5zDcKi/PViHY3W+nb4EQeCRc/Jx7Zxs2fN2UzT+t7ls0HKkhVADQD84WR9cV2AgGHUaPHZBAZ6/YgrC9RrsKGtFCysj0Gx24NM9TIPHyoJU/PbHRXgkyAaPYBAKORohTjaaUddpD4pbaA9QMjlRb8LtH+7DjMd+w8sbSnmHkrhwRu7myN/OxD/On4joMPnPJlwwEzWyC97hmg6YuinJMZB4l5V+uXRGJkalROHdG2Zh1/8tFW1aU6KMuGKW/ORT22HDDe/sAQ0mU/fRzbNlMxy9BTe1fXeots9fuyf43Qd7+caH/107Aya7u0eZ6dp2eUpId5GdEI4195yGpeN9NeW4zZ+WZDZ7h/96Jv572WTMzI3vk0CdywAK78lQEvOHChxuD+7+9ACsTg/mjIiXlUKiaRqPfntMtHGcnBkjclbhcKo0ghyRkTMBgBfWl/CyKRsKvRJTk7NicXaBt8Tp9ABRRvlMKAHgy301WPXmrm59XhtONuHCl7ejotWK+Ai9TzY9PdaIH480oKhRbBbwl5VMpaOy1cKvH3KBupYkcd28XD4w1JDAhzczwvgTM2J4Lc///nJS/n0RBP5+/kRcOVOeO/r4Tydw7+eHuuWMNRBQA0A/eJ9Vhu8rnD8lA9/dtQBjU6L4RYAGU6L78ra5eOXq6cjtQ29Ft4cSlU5DAW5iCMbzcF+lbzbOQ9FYc7QBZ7+wBSue34Kfjzbwllt5ieF49epp2PfwGbh54YiAos7C1vv3d1QgNyEcFM2IQg8FlLdYsOFkMwgCuE4g/VLYYBZNJEoftc3pwVX/28k3ffz9/AmYkKHs3SxFXbu89ZE/dNrc2Fk2sFnW7w7WYSOrgXjJ9EzMH5WIr/fX9sgD92RD32z6AOZ6/N81M3D36b6i2flp0dh4/2I8ck5+nzcpcUGsRlCGalQzgPjvLydxtNaE2HAdnrt8Ki8JIsRbW8t5720AyIoLg1ZDwCGjJ3mqZAAbzcrXBidzsqeiTaRt+X8r80WbUrPdjQi97/zMWU7uqWjH+S9vw8kG//q6NE3jzS1luOndPTA73BifFgWLgxmXm/e0JIG6DjucbkqUGQzTkbhhwQgcr+3E8uc2+x3HoCXxiqCZw0MBzQId23vPGAMNSWDDyWZFf3SCIPD4hZNw6XQx71dLMo49qw/UDvpmITUA9IPNIZARGZUciW/unM9nq2LD9Fh9xzzM6KErgz/Ud9r7pKTlD1yWxR3EOJ/s8pbkOq0uvL6pFLMeX4vbPtyHYwINtpm5cfjytjnY8KclWFGQ1iOF+SazE3NHMuWLoVIGfo/dcCwZmyzaCHy1X16qSAiapnHXx/v5kv/ZBWm4ppudaO9trwp8EAvhN/Lod75dkv2FdosT931xEACQHGXAkxcXgKZpfLGvZ7qTHAe3r0CSBO5dPhYvXzVN9Pj07NhelXn9geOPCsV7T5VgpafYeLKJl3J56pLJSI3x1W9cd6IRj7HUCYDJat21ZCT2sUoROgmv61QRg7Yp8ODHpkSyfrkE3BSNbSXe9TAzLhw3L8gVHW9xUjDIlGodbgppMUbUtNtw0Svb+G57q9Mt4lg63B48+NVhPPbjCbYilobGTjscbqYrl6uouikaeg2JM/KTRZnBv6wcj0te3Y6VL26FQ6bke0Z+ChIiDOy5MuP+ecU46Nj75J3tXqmfvMQIXD4zCwCjeapUziVJAv+5aJJoPnRTTEYxJkzHS8AFsz4OBNQA0A8aeygFEwhheg2vUG7UkSHz6Aw1/6/T5grYZasRvLdtJS0oajTjwa8OY8bjv+HfPxfyCxNJAOdNZjQOv7htHmbkJvT6/HITmAV2KASAZruL56xdPy9X9NzmYmbi1fnR73tpQwkvHJ2bEI6nL5vc7XNQciSRg5bwlhiLGrqwuSg0jUCBcOX/dsLloUESwCe/mw2SJLG/qh1lzYGbn+Tuup3loblWzp6UJnIl+O5wnZ+je4catgSsFSzGXfZTo2O1J2gy2/GnLw4BAK6bm4MzZLrhT9SbcPtHXttALQn88ocFePjbYwAYeS9pmfNUKQErIcKgxdiUKF514DdJR/3vl42BXhLwOTy0T1BB0Uwzx/ScWFicHtz03l68uaUMr2wo4TupKZrGqjd34fO9NSAJ4E/Lx+BEfSfarC4YdaQo0BuVHIkvbpuDTUXegFSnIfDId8dE3fQc5o5IwJe3z8XVs7NFdKBnL5+M2xaNxLg0RnlhnWT+u/v00TBoSeytbPdLJ6lss/qUep0eGjaXm9+EyWWbBwPUANAPeiMFMxgg1AAMxeW3pbgZHopGQqQyX1EYtLTbPVj+7GZ8tqeav6GNWhK/W5iHnf+3FC9cOc1H9Lg34LI5J+pNgz4V/+W+GlicHoxKjsRCQddyXYeNP/cwBRHvdScaeUFbo5bE+zfO7pHgd203NjwuGnjh8in879e9vQe7QxQ8KeGFdcUoZEtK954xBiOTmYn88z2BM6aAPG1BqpvZlxByVDtt7oCc2J6iViYDaOsHh4bBCIqicd/nh9DS5cS41Cj830rfbvhmswOr3twFJ1vmJQBsvH8xbvvoAL+5+Ojm2aKAGjj1s6r7qzrw+IUT+cD3hyP18AhEzaONOr5hQgg5lUCbi0J1mxWXTc8ETQOP/XgCrwpKsC1dTuypaEeUQYvXr5mOzcUtKG+xwqglYRdk866anY3v71qA93dU8t8XALg8NOSSdDcvyMWC0Ym459ODuP6dPXxGLj5cjwunMvy9cyYxfL/qNisoyvuaqTFGXD8/FwDw5JqToBSyeMKqQUaM1x/Y6ab5zN/gDP+GeQDo8Zzak6JQAiYUOxCO/+evyYBWoMHGh+vx0Ipx2PPwMvzl7HwkR/uWZHqL3RXtGJvCBAW7Bpin5g8URfPl3+vm5YoywqsPeJss5ALAkiYz7hBkLl68ahqyE3pWWuyujZPZ6UZuAtPpSgO48n+7sFfBWrGvUdLUhWfXMkHv+LQo3HU6Y9VkcbjxfZDZNTlqgcPdf5u+p36VJ5j3BnaXh7d+FHIA3RStuICdynhzaxm2FLfAqCPx4pVTfTZGdpcH1769SxTMfXHbXGwqasFh1ov5jsWjkJsY4bNhOJUDQD27cd9X2Y7XVk0HwJRyH5KIYl8xKxsx4d7PdFSSMoe9yexEYYMJD589HgQAYX6FomnkJoTjq9vn4ftD9dhd3gYtAd7ikgDw3OWT8a8LC2C2u/DVfuXmsyiD93ze2V6Jp345iZp2G6KMWt4CTsgnv2p2NnsOTJArxO2LRiLKqEVhg1lxXvlGMEc/e/kULBuX5HMMNUg7god1ACjV4DrVIBSB1vaxLhFF0djElv0sfmw+pOTp3IRw/PfSydj50FLcsmgkoox936HKmfy4PDSmZscCGNxl4E1FzahotSLKqMVFEmeNH1gSdkZsmE/zR6fVheve3sN/xr9bOEK2vBUsuhsfrD3ehPuWj+V/91A0Ln9jZ9BuIj0FRVG48n87QdPMQvXp7+bwz/10pB5WJxPIRsqQ0oXQKFAv+sPPFGA8g/saXAdwhF7j05lv7is7niGCwzUdeIrt4nz0nAkYnSIWWadpGvd8egAn6r2NCc9dNhkjEiPxV7b0mxMfjj+dORZyOJVLwFyg/N2hOswflYj8NMbV47M91fj2oPe61WlIPH2JVyuvpNmCVQryKABwuNaErSW+3HoCwDd3zse3hxiNRgAQ7sXeuWEmLmAzdue+tFX2tdNijFg5MRUWp/f+9VA0pmXH4r+XTsbuh5bxHuxCRBl1fLfzF3vF1YPYcD3fLf70r0WirCPAXEPHBR3iU7Lj8fKq6Vg0Rqw9a3EMzmTTsA4AfzoSOFNwtK4j9CcSIggDwEAdtN3F0bpOtHQ5EaHXdEtiYv19i3HJ9Mw+Px8hOG0nwJvlHYy+wBzeZqVfLp+RJfJ1dXkoFLF2YMslgZ2HonHHx/v5BX96ThwePEt+oQoVdrEeoUb28ybY87r0tR04VB26IPD+Lw/z19x/L52EGIFk0ucC7T8qQOFFKSte1tz9buieoN3qgsPVt0EZV/7NkNEg7LCeuhkrKbocbtzNinGvmJiKK2dl+Rzz7G9FWCPgtd2zbDQumJaJq9/aCTfFlH4//N1sxTFOlSYQORh1GmhJAsfqTCht7sIqgSXl/V8eFm3ylo5PRp7ABu1wdQfOnsT48srN8htPNoMGsGBUAp9ppAF8srsKL28o9Tn+oRXjsHhsMnaVt2Lcwz+j0SReb6KNGkxIj0ZLlwM/HW3gN7IjEsOx5p6F+PqO+bhkeqbfbnuuYfBgdYfPczfMz0VipAFVbVZ8JtEWrWm38VSxaKMGei0Jg1aD16+ZgQWjvDz2wWpHOqwDwANV8vpHQny0ozLgMYMRNE2jrMVbAu4JJ8wfuIaByZmxfjNHWski2x+JcGFWcUNxC0gCKG22DEopjJImM7YUt4AggGsF0i+Al2MJAKvmij2B//PzCb4rLz5Cj1dXTROZnXcXzh5kvbqcFGo7bFg6jglOtSQTVLkpGhe/ugNHFfTFeoNtJc18+WfJuCScN8WbMS1vsWBPBbMwGTXgM4FK4AJAaRjIvUaoIMw8PvNbsZ8juw9uQ5ARKxcADh09zN7i0W+PoqLVivQYI9OlKcn2fneoDi+s91oZXjg1HfcsG4O3tpTxGcE/njEGWX46tVstjiEh9tsTkAR4B6XvDtZh8VhvWdPppnDLB/tQx15rBEHgxSu9Xe6Ha0144IzRmDMiXpYPyGHx2GTEC1yEnljjS4lYNDoRV87MxIrnN+Py13fyJWEOYToNTHYPjtWZ4PLQSI/1UoluWzwK41KD8yNeNZuZX812N2o7xDzgcL0Wdy9lpJxeWFcssgDcWuzl/03J8oqKG3UavHndTD7Ala6DgwXDOgCsDsImbVvJ4C0d+kO71SUifvf19beB1V2TyzQIESkp8R6oCj1HjBB0qLaYnbwp+Y5BWAZ+j/WPXDY+xYe79+luZrcZadBgZJK3Ocbu8vCSFiQBvLZqOpKjesehFPJYuoNdZW14cMU4AICLAm5fNIKXjbjwlW04LqOk31PYnG787v19ABirxDdWzRA9/6VA+mVsemD9Q+7+kGYC94SYxyjMBny5L7iGlWDhLwPYPkwygKsP1ODr/bUgCeD5K6ciJlw6B7XjD58c4H+fmROHZy+fiiaTHf/6uRAAMDIpAr9neaVKcHlokYzJUESrSVkn9jxWDPn7Q3VIizHyPuVpMUY0mx24+b29fDA0MSMGc0Z4A6Br3tmDN66d4eNtLsS/fjrBN2XIISFCj/S4MBT8Y62oTC+EzeVBpEGLVXOy8ePdC0TSSjO7Ia02e0QCryn4rsTiDQCumJmNrPgwNJsdeFegD/yNwIXk/Cnpor8x6jSDxiZTCcM6AAzm5m3wI5I5mFHZ6g1upa36vUVLlwOHazoABG4u0UuyUh/v7Jk+W3eRIwimuF38YCsDd9pcvMbfDRLpFwDYxXbVzswTT2QdNm8m588rxmFWXvATnRK+6GEgsqmoCdnx4XzGac2xRnz8u9nQEARcHhrnv7wNhX3kqHP9O3v4rN67N86CTkAj8FA0Phfwdyz2wBlNbvGRkvv7MmiVQ4TeW+ZvtTjh6EPOIZcBlNMY7LSd+hnAylYLHl7NNCrcvXS0TxBQ22HD5a/v5CsRWXFGfHH7PADA1W/ugodidO8+FvBK/WGwqwsEgrTpQYjlE1Jh0JIoa7HgWJ0Ji8cyrjYT06OREKHH8XoT7v3sEN9c9MxlXi5gVZsNte1WvHvDLKTLaC4CDOfY3+dnsrvwyW7l9YLJ7hZg10NL8dgFBciKD+dlyWLDdLwMWLAYw6oIrDvhK/mi15K494wxAIDXNpaik82mc41CADArz1e6bHDm/bwY1gGgjFakD5z92BXYlxDKWfS1FdjmombQNDAhPRrFTf75UiQBhOm8t8GO8r4V2lWCcPfO2eENtkaQL/ZWw+r0YExKJM9B4VDbbkWnjdmgXM2WJ6SdZMvzU/C7hSP65FyKm/wr9CthazEzWV43jznHkqYujE6Jwkc3zwZJMFmS817ahqLGnr0+h092V2EXq8h/3bwcTMsWe7huLm7meYEFGdGoag9ezkVanqkPkf4nB4IAkiO99+SL6/uuDFzDvm+5EnDbKcxZA5jS5N2fHIDF6cGs3HjctUTswNLlcOPcF7bCyQb+UQYNNv5pMQDglY0l/Fz25xVjkRKkKsFQbwTZJBE+F94JkQYtb2X43aE6LGHLwHsr2/HKqmnQa0isOdbA+4Gnx4bhshleSsbV/9uF1Bgj3rtxluIa5G91ldq/CRGu12Drg6fjilnZPG96a3ELT5mZPaL7toorClIBABWtFpEcDIfzJmdgXGoUTHY3XttcikaTna8iaAkoen8PZgzrAPBUhrABJCu+bx0HuPLv4jFJKAzCOis33isN0NjZP4vQBYJ0/Il6E7QkgZp2W8i9kYOFh6Lx3o4KAMD18/J8JqsPdjKlYQ1JYMnYZDjcHrQLOFzZ8eH472WT+0xE3NzDLrU2qwcNnXbcOD+Pzwb/99dCzBmZgPdvnAWSAJweCue+uBWlPWyuaDTZ8QgrP5EZF4a/nzfR55jP93gzBYvHJvl06/mDNIstZxzf11gxybtQfrqn77Li/krAg5ED25d45rciHKrpREyYDs9eMUXEifVQNC5+ZRva2DK4jiSw4/+WQqPRoLbDiqfZbuGxqVH43Wm+HsFKaBniQbXUS1c6n3Bl4B8O1WFqViyijFq0W13QaUj866ICAIwIPdcZ/Oi5E3n6TZvVhc0nmzA6JcqnPNpb3LNsjI+M0waBkHN3yr8crpnDbbSBX443+jyvIQn8iVU9eGdbOdYIsqcjk6NCZugQSqgB4CmKSkGgM12SLekN3B4Km1hV9ILMmKDa2wsyY/mfQ7+0MiBJku8G9tDAGFYCYrCUgdcXNqG6zYaYMB0ulEi/AMCvbHfi6ORIaEgCX++v5UuWBBjeX3QfSuj0xjJwV3krtBoSs9lS9PeHmIlxwegkvHP9TJAEIwe08vktKO9BEHjFG0xXpoYg8OktvqW5NosTv7ITdrhOg9qO3gc6oe6Yve00b+a2pcsJWx+IQrs8FBrYIC9TJgPY1I1u/aGGLcXNeG0T00H6xMUFPhnQOz/ah5NssEMAWP+nRTw/edWbu+ChmUzwRzfP6ta4rZah/Zk2SzKYUkbP4rHJiDJoUddpx6HaTpw2hskCbixswiXTM3HrIuY65jqDIw1a3LtsDP/3t364Dx0WJ75luXLdCZGMWhJXzMzChHRxI0eEQYObFuSJHqMoGhsF2cyeWKvGhOv5ppTPFTZlS8cnY3pOHOwuCq9tLuMfX56f3O3xBgPUADAIHA6hpEWoUCIoza4oSOuz1z1Q3QGT3Y3YcJ0Pd0rp5h7rhwgcSgi5ceGsJtxgKQO/y/pOXjEry0ciwO2hUMFyOM+dzHx3727z+lRGh+n4xpbBgO1so9T9rF6a2e7GthJmMl40NhlvXjcTBBsErnh+i4ifGgj//ukEytlu9ofPGS/Lbfv2YC0fwF4yIxM7uyn6LVdp2hViV5O02DBEGbzT72sby/wcHRwaOu2gWG3ExEiDz/ONQ5TPHAgUDdz7OWP1dvXsbJw1UTzfPb9WLPfy1e3zkMVWJZ797STKW5jN8qPn5CMxsnvNVENdCkYqfC6d0406DZZPYEqj3x2swxKWB8hVgR44cxyWjU+B003hd+8zncG3LR7J++vaXBTu/uwAOm0ujE2Jwt/OmxDwnBIi9HjsgonY8/AyXDkrS+QTDwB3Lh7lk7U/VmfiKSAGLeETNAYLbhOrZHFKEAQeYOc5IVVkzshE2eMHO9QAMAh8vGvoScEIA8BpOX2XAeTS7IvGJPE2XByUek0yQmR6Hwj/EJQKT7Lnur20dcClG4oazdhW0gqS8JYdhPjpSD0vrbNqdg5Kmsx89gJQtoTrKXr7eWxheYBTs+MQx3ZcCuVNTh+XjP9dMx0Eq+x/5nObUR2ET/XR2k68we6yp2bF4ob5eT7H0DSNj3ZV8b9fMj0T9d3MAMplP/eWh37Tt3S8N1D5eHfv55gaQflXzuWkO3qdQwmdNieazQ6MTo7Ew2eLrcl+OVaPZ9d6r8Xnr5jCz4eVrRa8yErBTEyPxrUyjViBMNSbQKSQa+o7jy3f/nSknte2O1LbiSazHRqSwHNXTMG41Ci0dDGdwU4PhWcFXuSbWc/eP68ch+vm5eLOJfIldm7sy2ZkYtWcHEQZdbj9w/2iY8L1Gtxymi/vWejVOzU7zq9vuj9czbqCmOxuRcrE7BEJmCfhbE/KDKw6MBihBoBBYFtp/9hb9RXsLg+6WNX/vmYlcDu/JWOTcVyyM1MyG5GWYzx+Wv/7EjmJEfz7Nzs80GtJNJsdPeai9RXeYWUGluenyma0OE5YUqQBMeF6H/HRvsa+yt5d33WdDjSx2aWLpjFq/Qeq2kXdrcvyU/Ha1dNBALC7KCx/bjOq/TRquN0UVr21CzQAo47EBzfJC/IeqzPxm51JGdE42WDuttakXAB4NMSdwABwyyJvQNvc5ey1A4k/DUAAIg7pqQSHm4JeS+LFq6aKsulFDSbc+oE3gLhn2SicL9CNXPXmLlA0oNMQ+PBmZcFnf2gZ4k0gUsj5Y88fmYCECD1aLU6cbOzig52N7FoQadDizetmIDGS6Qz+42cHsaIgTeS6kRkbhsVs+fhPy8fiYnae4KAhCPzrQmbDzq0xX+ytRp2kIeu200bK6p0KA8Ce8P84LBidxDeFvSeQe5HitNFeXcTYMG1IHK36A8M2AOyOD/BQK50IGx3CA9hhdQf1nTacqDeBIIDTxiT5CP3KNE4BANJixWWVfZX9V4ZNivLqMGWxxPiBLAN3WJ1YfYCVfmGNxqXg1OgXjE6E20Ph8z3M8USIRAXe2loe+KAA2M126N6zbDQIMGW5VzeJVf3PnJiKV1ZNAwFGv+vMZzejvkNeh+yuT/bzwsWvXD0NkTIWTgBjTcXhunl5Iu/kQOAWOw9FI0In/myFIuqhQn5aDATGL3hjs68LQnfAN4AoBID+LBuHItyCwP2Rs8eLRH/bLQ6seN5rGXbB5HTcs8zrlPPEz4WoZj+vf14wEbHhgfXa5LpSh3oJWAq5zLFWQ2IlSyNiRKGZMvBGQdCVGReO16+ZDr2GxC/HGvHM2iI8eq43G1vbYeMtKwmCwH8uLuD5hAAQF67H8vxUkARQ2GBGRUsXHvlW7Dts1JG4XSZ72NrlEDl49IT/J8SoZEZz9VeZRhAOwvF6mm0cDBi6Z95LdGeHP9SkYIQSMCnRfdeazu34pmTFQq8lUSNZvIXxnzBYSZCIYX66p+89UJVw5SyvL6WNXQC3D6C492d7qmF3URifFi2r31fSaOa17m6Yn4vNxc28fpvQ4q4vcaAPPLF3lTEBYJRRh/Es/+aT3VU+x62YmIYXr5wKAoxTx7JnNvmUWhxuiudsnTMpDaePk/c3trs8vI5iuF6DsyeliXS5AoGzI6RBI1Ei+9Ffpb35o7yL4Ec7fT+v7oBzMFASZ+9LvcHBAC6gNWg1Iqsyl4fC/Cc2wMNSG6ZmxeK5K70adaXNXXiNDbanZsXiipnK3rUcdpS0yDZ8DPUmECmU/LG5MvCvxxr4MvCWohaRkPP0nHj852KmM/jlDaV4fZOX10qDcWfhoNOQuEmwAdZqCMRF6DEjh5kTH/zyMOySbvzfLRwhG2xtLmZkyQBGYonzf+8pzprIcB7Lm+XlYACIeMbNXU5+AzzUMGwDwB8PNwz0KYQMlQJ+1bi0vmsW4Ph/p49NxkkZ+RdhJU14nxKEOHe1N8ROC0LctdirBVbHekjuKGvlxUv7E24PhfdZa8Eb5uXKyga8xTZ7GLUkJmXG4tNd3gyXMUR+kn0R7HA8QIAhaQNAo8mBYhn9v3Mmp+PZy6cAACxOD5Y+vRFNgiCQ68CNj9DjhSumKI756/FGPli+dEYmWi0OnvoghJINk3AxSZI0Tbg8dL9QFW4U8BobzQ7YAtjX+QPHAVTSI/PQzDV4qoAr3YfpSP5eomkai5/awF8XqdFGrL5zvujvVr25CzTbLPP+Tf67ft0eCg99fQRXvrlL9vlTLQOoJOw/PTsO6TFGmB1utHQ5kBChh9nh9mmWuGhaJm5fzGTpipu6RAHG53trYLJ7aQgHBFk0TuOU0x3cJbFjNGpJ3HW6WNeRw4ZCb/fvuNToXqsjXDsnFwDgoWm+HC1Ep80lEuMHgCfXFA44t7wnGLYB4H6FLh8ldKdkPNAQSm0sHO2rTt4TONwe3nt2yThf/p902tBKCIExYd5al1LZLxTQ6TR8RxrATCSdNheO95E7RXew9kQjajtsiAvX8TtqKbgs64SMGLRZnFh3ksmEJUTofVxV+gpOBcHV7hScK1ptfCC5siCVb1R5Yk2h7PEXTM3As5dNAQB0OTxY+swmfhGg2bE/vHkWSCViKYCPdnobJ66Zk4MPFHy75cpaAETXhZzw77F+uEYWjE4SNU+9vbXn3cCBOIBAcO5HQwXerI/3A7z89R28DFC4nsT2Py8R/c0/vj/Gd28+cfEkv9ytkqYuLHxyAz6WyWRzaLc6eyWhNJCQC1iUNkskSeAcThPwcD0WseVbIfeOw73LxiCS5TYYdBrkp3lVIO7+2MvJFFYeuPLw0vHy2f4bF+TBoPXdALs9lEjMemZu7xse4yP1iGWb2eSqGLsFCgFakoBeQ2BvZbvsZzHYMWwDwKr27nF8uhswDiQOCspgK/tIAmZPeTssTg+SogzIT4vGcYk3Y6RBfHMKbboAiDwhXf08X44TTECcL+hA+AJzzR9XzsqGUaaT1+pw84vTJdMz8c2BWnAJmwtktAIHG7iJkSAInJHPTOSbi1oUd8YXTsvAfy+ZBICRjhF2qd6+eCTy05Q762o7bLwzyKTMGIxKjsJaGQsnAIqi0FpB5CX3ffTXNSLs0n9/p3wQGwgURfPdz/78uU8lP2Buw8BxOR9afQS72cyRhiCw+6Flog1EYb2Jvwdn5cbhwmny9xRN03hxXTGWP7spoCsMRYdeMzJUKJdxcfKnZcyJQq870YQ5I5hSrVB8mcPqg7XocrhBEgzXV7i/3FjUgiaTHRRF40CVd03l7lGLIEPInYpBS+LupfK+zAerO9Bpc/Gl697y/zjMYl9nr8y6/+NhrwD0xPRo3MBqEj655uSAVJZ6g2EbAJps3dsJf7G/b03bQwmhzlpMWN+YUXO7m8VjkkCSBI5JOJQccZaDNFs1vg9L0d3FX1aO539uZYOM/haEPl5nwq7yNmhIAtfM9ZV+AYBP2W5fAsBFUzNEDQ7c5Nuf6O5UtrPMW9p/8CyGcO/0UKL3IcUlM7Lwb9ZRgBtPSxJ44Kxxfsf6QtAZfdOCPFAUxesFctAJAzyteGWLMmpFHY9Smz0A3eIT9gac1R/AlM2tPRCFbu5ywOmhoCEJpEqymcJ33nEKdQJ7A0BGJ/NjgRzQpvu9Qs8AQFEUrnl7N9NVriXx9vXypd9msx0rnt+Cp38rAkWLPzudQja6dYhKwXxzqK5bx09Ij8aIxAg43BQcbgokwTiJ1Ai6+W1OD575lbGGu2PxKCRG6nGywYyUKC/F4vp3d6OsxSLKRjvcFDweCrd95M0QcnfktXNzZTdogHdd4q6FvsgAAsAVLHe8w+pCS5d4E7C1xLt2zB6ZgNsXjUSUUYvCBjO+P9y9z3SgMWwDQKkAZiBsLxkaJE+KomFmbyydkjBfD8DdaEvGJcND0byuHocFo8RCmNzayq2ro1MGRgwaEIt0cl/77vI2EYE51OAkBc6amIq0GPkMzTdsB2tGXBiKm7pwkuXPZcaFhUxnqrGj76zxdgiI0Rlx4XzX9f+2+C9rXjkrG49f6NVsjI/wv2mhKBofspmycL0GZ01MxdaSVp9SnLBrM0wn7iIelSTesMhxB4ub+ocmcN5kcZb+fYVStj9w/L/UaKOPTIawRDpUs1VS2F0ePkBwUzT+9v1x/rnPb5mNTIH9JAA88u0xPsP8zGVTZLvKv9xbjXn/Wc/rm6ZEG/gxVkxM5ZuGpBiqUjBSwXSF6i8PgiBwLpcFLGzi/bg3Cnhyb28rR4PJjsy4MPx+6Si8fs0M6DUkGgXZ/eN1Zqw5ymTROB4uRdN4aX2JT8ZVpyFw7xljoIT1LP+PBkN9UJpbu4vFYxJ5PuT72733o8XhFtn/Tc2KQ2y4HrctYniPT/9a1C0byoHGsA0Au5vdaBoiUjANJjv/3oS8u96gstWCsmYLtCSBBaMTUd5i4TkbHGaOEKfeuQ49LpuRLuElOd39y6mMEkz4Bi0Ji9ODI7X9k+FpszjxDeuVeYOC2CxN0zjBcs6Wjk8WZbjOn5IeMp/JN3sgARNpkL+uTjaY0SnIMF3PNjiUNlvQEuD+uXp2DlKimMyVnBaZEDvLW/lJ+IqZWTBoNbJcHYAJEAHwHaEcxkucAhplSn31Hf2zsJMkifECmsK7bJmyO+CyMHLlX+HCfqpoAQpL2cKfn7h4ImaNEG9GD9d08GLhC0YlYOUkccBtdbpx1Zs78acvD8PloUEAuGVhHm/PF2XQ4sUrpipuqIeqGHSlRIw9GDkTjru8tbgFc0Yw/HJODqa1y4FXNzLd1fefORYGrQbTc+LwxCUFPq/z8gZGgFtYKXqBfUyI5fmpPk5JHBo67fycCQAz+ij7BzD35MgkZhPxi8BFRqqZynUc3zA/F4mRBlS1WUOu29qXGLYBoBKU2uCViPKDDUIJmNzESD9HBg9uhzcjNw7RRp3opuOQJ9hx6whvSp7LwkgDwN1l/ZtRPUNILqaZ4LW/OF6f7K6Cw01hYkY0piu4suwqa+M/q6tmZWH1Qa9UzrkhLP+uL/TtcgsEvZ/M8h5Bh/d1c3N4UvlTvxQFfN1gY1yhQOs1c3MBQFGGgQv8XRI5ByklQSo4CzBZwf7q7LtEIIzbYLLLZiT9gWsAkfMAFgbUrUM0WyWFXNB10/xcXD5TTK+gKArXv7MHAOOg8+a1M0TPby5uxszH1vLSUImRevzw+wVoNDtgsjOb1FdXTYNWSypmAIdqJ3CbRMImGIehkUmRmJAezWgwEsy9sa2kFXaXBy+uL0GXw42JGdE4d5J3zrpwaibuWCzW77OxEi9CrjiXwY8P95bu/TU0cYEnd4/3Ff+Pwxn5jBxMaXMXLwfz81GvekhihJ5vHgvXa/GHpUyX8gvrintE4xgIqAGgBAaFm3yooEqwq+NS9L3Fepboy/lAygWA7YIJOTHKwItCu9kf0mLEvKSv+5lT+ei5Xh6gg00+9gcP0OWh+HLlDfPyFDN57+2oAMBk10qarDxHdXRypEjgtq9Rr2B35A/SbJoQQg9drYbkyeI/HqlX+pNuwWR3YR3b7FGQEY28xAh02V0+PCwuSOUEiNySDdxYCSWhpcsJqcwiDaCum7ZyPQVnQcWhu/aTtQIbOCmE0h4NAZoahgqkXMaECD08NPC/zWX44XAd9le1o6HTjvu/PMwHiy9eOQVGPRMsuD0U7vn0AK59azcsrGTMxdMysOP/lsLm8uDbgwyX64z8FCxgXR+UMtNDNaiWyOwhOsiKEcdH3l3WhpRoA2wuD74/VMfPcw+tHO/Tef+n5WOxPN+3w1e6mdSSBNoE3+3mYuUNKrcucQ46fcX/43Ady9V2UzS2FDNrhbDcPVOi43r5zGxkxYeh2ezgm40GO4Z2tNOH4C5DJbIpMDSkYI7UdvA/r2QFLXsDm9PDc7uWjGMCQKmEio4ksEVwo87IjeMzgG6Khs3p8ZFb2NsH4sPdQWy4wYfjsreivdf2W4Hw67FG1HfakRipxzmTlTuyuWzktOxYfLGv/5o/eqI75+8zk/KK7j+Taebocrixuaj72UYpvj1QyztAcJ6gn+zxLf9GsF3pXCZNGgCOSfFmx7nLIjbcVxJEGNCGEka9Ftnx3uCtu2VgfxIwwgCw6RTxA5Z2M7danHh3ewUe/+kE7vr4AC56ZTvm/HsdvtrPZNJjwrT4/nA9/vNzIZ78uRBT//kbvmGDvEiDBh/fPBtPXzYFGgK4+f29AJhr6OWrpgFgeKdKWdmWIVoCliIhwhD4IICXg9lT2Y7ZeUwZ+OUNJXBTNJaMTcK8kYk+f0OSBJ69fIpP5l1qshAfwdyDGhK8K0iNjGWkUJbM5aERZdRiTHLf8syTo408jeqT3VWwuzyiDZRUcFqvJXHfGUzz2+ubSkV0mMEKNQBkwU2SUvkSIXYMAbXvPQIBzSl9kAHcUdYCp5tCRmwYRrOdvlINwMRIA7aUehf3cwpSRVkirplB+NE2dvZd80GwyBL47uo0BBxuqk9cMPzh3e0Mx+6qWdmyOlYAUNtu5YVFz5yQik2CXeY5IQ4Ae1Lg5Bqo5PIhR2pNMAukHCZnxfJNHc/+FrgMHAhvs4FRuF6DMycwAbWcqHunlVmsuUVb+D41gMj6i7v35TThpEK3ocS5k72yJHWddtHnGAheEWhfb2mhtpuSwf1Qg7DiQAD4x/kTcOuiEThvcjpm5MQhLUYczHTa3Pj2YB1e21SKVzaV8o1yALM5eOTbo7jmrV04/elNfHbxjsUjUd1uxckGE1Y8v1kxAByqGUApkqOCCwAzYsMwMzeOEdNmu+srWq0gCeDPK8Yr/l0E6xksrLJ12MTBc5OZ+f2yGVm8K8g6GXmnvRWMLBnHR56eE6eo99kbcJSdXeVtOFjdIZpHpmT5rq/nTU7HuNQomOxuHyvMwYhhGQDKZfI44WJ/l9A3Q0AKhlsI+upW4FTWl4xLAkEQaO1y+GQRJmZEo6TJK8ExIVN8YxSyGcOUSO+i6xiAZOrti0fwP3N8ux0hLAMfre3Enop2aEkCV8/JUTzuI7aBgSQYaylukinIiEFeYoTi3w00lDSapdpZl7B6a4dqOnrldFHUaOalXi6dkclzsgplKAkUvNygJMnCliD5nQsApZ3CAPiO0P7A7xbmiX7/dHdwZHKapoMuAQ9VyRIphM0sBEHg2rm5+L8V4/HClVPx5e3zMDPXK4D/yNnj8M/z8hEnyPAS8GaJ7W4Kpc0WbCluQYWAQvPUL0VY+vQmnPncFpxs9NXM4zBUm0CkSI4OLgAEvJWJ43Umfq05a0Iqxqb6z8JlxIZhYoZ/RQMNSeDPZ43nXUHWnvD15OXKv1zWfmYf8/84cDaB7VYXvhPwsgkw87MUJEng/jOZLOC728tl5aUGE4ZlAChnT6VkgSPEjn5uXOgJLCz51F8pO1jQNC3D//P97OaNSuQzLoCv8C7HGRyfGdvrc+oNLpfx/NwewkYQjgdy9qQ0WacJDj8fYTJYeYkRWH3AqyN1rp+ScV/AYu955oIkACUVnV2S++QPS0eDACOa+8pG306/YPHWFm/H8k3zmWC+sN4Eu+R642hFXDk0J16cFZM2JHH3vlamuaWqtXuC8b1BbLgeyYJNEpc9DoR2qws2tiwv5doCgEYQqQ+FslQwEDYwSNfYnaWt+I7VuDszPwVaUoO//XCCDxonZcbgwKNn4Njfz0LhP8/Chj8txoc3zeI7xgkE35AEDN0mECmSopTnKClWFKRBQxI4Xm/mN6yBgj+AWVPKmn2DaWGW+uyCNMSE63hXkF1lbT7ZV06WjMuSz1Borustlo1P5qlDwkpDfnq0Ynfy6eOSMT0nDnYX1e1mrv7GsAwAfzzqWzKSm/ylaB7k/JlOm4ufDKUlkJ6gpKkLtR026LUk5o5kdtTH632lUyZmxPC8LMA3y3CCzaKMD2KCCCUIgoBRwvQ/WN3BS9b0JVq6HPieXYSuV5B+AZgSZQWb1ZqSFSsSMz5nUmjLv6sP9LwxI8aPhZaUNxdh1GECK7vyqR9RaH9weSh+Uc9Pi0J2AhPUvb+zwufYRDbDx2UAUySZDWlAqOF9ZH3HbbM4+9Xjc5mAKF/bYUenLXDAxmX/kqIMshs/4d7WMkS6EwOhTJCRo0Hz35HbTeF3HzAcvkiDBvWdNvz1+2PwUDQ0BIFHzs7Hd3ct4CkAWpJAdZsVD39zlPcPpiG+FkYnR+Kjm2crCkEPVR1AKdJjgw8AEyMNfIMXBznXDCkqWq1ot7qg15KIErhHCZvjOE3ZkUkRyE0Ih9NDYauAY87JkmlIAp02N3QaApOzYoM+9+6AJEm+CtMpoGRM8TMeQRB4kBWyt/ai4tEfGJYB4O4y3wtVeHOH64amFEy1QAJmvB8brWDB7bLmjEhAONs9J5cBzEuMEHEjpJyYE/Um0DSNPIksTVc3OE59BelO0U3RIumSvsInu6rg9FCYnBWLqX64mL8ea+A/O2F5dGZunE+mqq/x9YGeUxoMbCAdLSOoe7Cqw0cGgbNyajY7ZEu2gfDb8UY+y3XnEq8t1JYi3xK+lGsZLtmpj0oRX4dcBtAho03poSESfg01bl8kNrz/XKbBRQpeAzCI66U/xc9DiTJJZpbbdN758X6e3+dwUThcy1xrOQnh2PzAYty0MA80TWNfZRv++u1RzPn3Olz79m6+9GvQkiLbyoumZuD73y/A/FGJijqAJrt7SIn/AkwXtBT+LATlwOt2sr/vKmsLKH/CWaoWZMRg4/2L+MeF1+WB6g4ATCB1+jhmQyS0eeTs53LZTeDEjJg+qXgpYZmMP7G/ABAAZuXFY/HYpBCdUd9hWAaAVW0yKWjBzS0NVIYKSgW74r64+Dj+3+mC15J2AAOMBIMQ0gXTbHejrtPuE9BsK+19V2h38bdzJ/g81td6gE43hQ946Zdcv8d+vpcJwqKNWpGpeSi1/ziUNve8vMlN2NwkLAQN3+aJ5RNS+UDsyTWF3R6PE5gN12mwfAIzIbvdFGrY7lch6lh3ky42EJA2U0yQdCJyAWCHQrZNLusdKmQlhIuCaqHmoRJ4DcAgFnCKVvZGHkpol1QZattt2HSyCb8c9/LFXBQj6nzraSOw4b5FMNndeGJNIRY8sQEXv7oD7+2oREuXk+ew6TUEJqRFobDBDJIAHlo5Dk9fNpkPLqQOK0IMNR7gvgrfOS8nPni+cZfDjY3sfEWBcaBxeihsK/E/lx6oZuaFqVmxSIgMk6VebS3xzoPLWB7ghsImXidwA9skxzVthYr/x0GuguNvU8+B4wICEFXIBhOGZQCoNNFzmCvTxs5hMEvBbBAEECsm+O5augOz3cVnxhaz/D+H24MSiYF4uF7jc3ELOTFcc82JOhPSJTY93x/0LcWHGqNSonwaZPqaB/jz0Xo0mR1IijJgZYEyj89D0djPGqLnJETwemQkAayYGFr+HwB0BejE8UeKsLB/K+ymFULKAwSYIBAAtpS0wNONTFST2c67tlw4LYN3LPjxaL1P2ZYA4KaA2DAdnxlrNIkz0hmSTlluEVKieOytCFza6kssHO2df2o67AF5ezV+GkA4iPyAbUMrWJGDlPdZ2WLBrR/sEz2WEKnHW9fPQJRRizOf24IVz2/BqxtLUdthQ4Reg4umZmDx2CQ+Ax9p1GF/dSeiDFq8df1M3HLaSFFp0h9NqNUytMrAPx7xnXsTI4OnDb2xuQxtFie/qUtguatc1UgJ+ys7AADT2EpMlMFLJcmJD4NOQ6C6zcb72c/Mi0eUUYtWixMHq5nKAidLxkkBhYr/xyEtNkzECY0yajEiiOa8CekxiGArZ9oQdCj3BYZlABjIB1g4AUuxNcAOZyBxqKaD/zkyzL+faiBsLW6Bm6IxIjECuezFXtzY5eO3mhEbhpImb1mYgHgy5DbNhQ0mpEh4iYcF59ufSIgUfzZH6zr7lBz/Lpu1WTU7R9E9AGBshbhsjEOgrTdvZKJP52ooIP0updAqtfnCuwDXddplA8VtJb7Z3QfPYnbELg+NT7rBBRQ2f9yxxFsi/UqmK5/TERubGgUzG6Q2SygJ0u+fJAjoNASUPo4jNf2XAQS8+oYcvtzn/7Py5wLCQXgdSkWUhyKkbJy/fHtEFBQWZEQjI8aIG9/di//+WoTipi7oNSTOnJCCl6+ahr0Pn4GbT8vjJZdIgsni5SVGYPWd8/mmNyH83Q9DrRGEK7MK4W+uEqLJZMf/NjP+3lfNYhrrOH28jYVNipxZq9ONwgamgsSZFNhc3pJxXaedz6xtZTX+dBoSi8YwFaj1hY3YUdoKp5tCWoyRt7JTclfqK3goWrTRnJIVG7TkTJQMRWYwYVgGgIGysf7Su98KWsEHGziNr2A6mgOB28ktFkyEcuXf6Tlx2FnqzfZoNYRoMuSygyfqzT7crKYBIk9fOj1T9DtNM/6yfYGD1R04UNUBnYbAVbN9u46F+JIt/5IEUCTIrIZa/DlY+FnveFS1WpEq03l6sLrTRzA6LSaMb8B4K0gPYpqm8RkbLI5LjRLx3A7KaDhyzSEcoT09xohOm5iXFCeTteRM5KVuIABQ1qIsARIKTM6Kg1GwGL8ToAzsTwKGg1B7TVo+HWqQK2Gb7d5rjQCjR3m41gSSYDb0T14yCXseXobXr5mBsyelwaAlcN1bu/nsH0Uzx31zx3yMSpanAPmbVodaBrCmTUz/6M6K8ezaIthcHkzLjsV9y8cgQq9Bq8UJvYZEXacdRQqSOYeqO0HRTKd6cpQBj357VOQp7/LQiAtjNnBbi73cXk4OZt2JJn5d4jqORyRFIKEbmcueQKp7Oy51aFLE5DAsA8BAiA7z0+FYNngzgBxJXo6Y3x3QNM3zLE4f5w0A5SzgZuTGiXaT4TqNqCuO2zmdYHd+Rq13qrFLvYj6CX9cNtrnsb7iAXKcrXMnpQfM4q1lyczCgESnIXDmhN47uAQCFQQnRcn6ioOWJOD0UFg02pdvSgN8eVuIG+bnAgDKWyxBiRLvKm/lKRt3LvZm/5pMdpjsvoRzrpEmkuUH5SZGwCYgphOQ3yBxgWWY3vfekZaQ+wNCm6madpvfoI0rdcuJQHOIEDTCBKLADHYEKmHTYBx1/nZuPnY+tBQf3DQbl83IQoxgXn/422NoFmxUb16Qh3eun4kYGTeYYDDUMoAmu3hzFmzSoLjRzG/IHlo5HmF6LU/t4ISklcrAHP8vOz4c0x/7De/v8LU73M6ur9tLW/kKxeIxybwryG8sx5MrPc/MCS3/DwA2nBTrELZZh9Z37Q9qAIjufQjNg/RGd7opPtiSylx0F8fqTGg2OxCu12BmnjcbKt0JAcCo5CgUNXofT4jSi2RgOCHMihYLbE4Psnp5bn0BvU7rw8noC1/gJpMdPxxmpV/YQEcJZc1dPHFc2AG3aExSjxeh7mBriX+uDgBF32IOXHljSk6s7PNyHbrXzMnhP/unfjkZ8ByeX8voBobpSKwo8AbGXJONFFxjC1eGykuMgDBhFK6Xv9u57JlcGczhpvqd5C8lnq/eL195MNtdfCDsrws4RrDJGOoZQKUSdk58OO4/cyy2PLAEX98xH9fPz0OyjLbd5qJmfLyL6a4mADx1ySQ8fE6+3yaPQOjPTvG+gLSEbgiy/PvEmkJQNHDmhBTMYJsvuIoFp7PIacdKwVWKdpW3iYS8AS9Hzmx3I1xPotPm4nm/cRF63hWk0eSAXkvyJecZfez/K4efJXzJY7X9Jw4faqgBIIBIo9ZHC07pgxmsUjC1gm7IOSMT/BwZGFyb/fxRiXzZlqZp2QxgXkIEagSSDGOSonxkYOLDdaBoxsmB04Pj0J8aa0KMkUiBFDV29Vrn8aNdVXB5aEzPicOkAKLXwknFZHfz5aX+6P4FgA93BubgBUoKcFkDu4LW1U9H63we02hIzBvFXJ8/H/WvQ2h1unlNwXMmpYsW6F+P+boDRBo0cHloxITp0MYuyFInlUSFrCwXPCllQqTNT6HG0vEpIuvEdxREobn7PjZchwiDcuY/RfC+m8xD2w5OLhjXkgQ2PbAEdy4Z5XeTubOsFde9s5v//YObZuPSGVl9cE5DqwQshb9rh8POslasPdEEDenVuQOABaMTEReu4zUm91W2i/QrPRSNt7eWYbNAyy9cr8FYQSlV2EhIsAVpzusX8JaBAWB2XjyOsvI+oe4ApigaxZJ7v1RGyHqoQg0AAcSF6/iOSC4bExM+uMmbUghL0+f1UkCYS+ELidC1HTafkhtJANFhWnS5vDfvnJHxPru7bFZe4ES9CeNSxQHgQImoPiBo0eewoxflfYfbg4/YrII/4WcO3x5iMjqcthhFA0YdKas5FQocqg7c2RqoBMxxsSparUiM9OXVVbXaZLX1HjiTWTwsDg/Wydg8cXh3ewXP1733jDGi5+QmYU5ofGJGNK/rJpVGyYyVDw64DKDSfuRIbYfieYYKEzNi+Z+r222ynrM8/y+ABqCQHzgQJe2+RIdMCc5N0QFdFz7aVYkr/7eT/47/fl4+Fvhp+OsOhloJWIr4CP9NgxRF418/nQDANH6MSPIGbzoNiRWs2kG0UQsPRfMcvn2VbTjjmU34xw8n+OOXjE3ClgeWoLxF7AefzHL5ODWELYKAcalgXsxLiIDTQyExUo8cGRmqvkRxU5ePyoXLQ2NvCLRjBwJqAAjm4qdZOjD3ZfvTAnQOQnVvYUYkP4DXoj+0WZw8p0+oJSgnAB0TpkOdRIdtvERjDfCKBhc2mJGdIM7ICBXe+xOLx/kGWr3xBf7pSD1auhxIiTbgrIn+OXztFidPlBZ24i4dnxLUTrwv0BZEJ2igAJDbEJS3WHj1fiFoALtl5GAmZsTwAePz64oVX//97UyZd2RSBNIEAc6uslZZXS3O43diegwq2Kx0jITPm62wYHAdtEpCyXINJ6HGlbPEmalvDviWgTkJmEAagNkCjTeufDZUoRTAcsGwFC4PhUe+OYq/rD7KB3/TsmNx3bw82eN7gpYhXlZXyoxz+PFIPQ7XdCJCr+FF3YXgysAcD/3no/X442cHcfGrO1AmcDfKSwjHOzfMQlFjF5xuSjTHWJziOWlfZTsvLJ0U5Q1Q67nyb058QJpKb7FRwmfUs1UIJQrKUMOwCwArZDIHMQLJFG5Bnp2nnFreNEBBiz9w7fW9vR22FDeDppmOS6Fws1z5d2RSJHaVixf4KBmLMBNbDjheb/IRg/7pqHIGKNSINIi7kreW9DwA5Hx/r5mTw+vUKWFjkXdSoWgv/+XcEFu/CeEKgsrgpoJr0qlotcjKZgDAezsqZB/nym5Hajtl3QNONpjQwDaJCKVfAPCZVum1zgUA2fHhsDo9jF+xJKBLUfA75TJkXTKNJQAUOxtDiYunirvV35X5LLkScIZCZpNDXqL3+aZBbmkZCLUy4t/M41afx9osTlzz1i7Rgq3TEHjvxll9ek5y2dmhhBQ/AaDD7cGTvzDi7bctGinb3DYrNx4p0QZ+XvnhcD1WCzYsGWxX/mK2qZDbbHPcQy1JwOKkECnYALs8NL++CAWmj9Yx3MB+4f9JaCrj0pgqQyg95PsTwy4A/OGQLy9JSLrnMgsz/HALfjoy+KRgOF5MsFpOSuAIvEvGiRd0uQaQGTlxPo4P0vIvANSwE3NhvQlpEl/W43X9q7EmxBKJW0p1m01xcfEHl4fC4ZpO6LUkrpzlX/oFAL49IL4G3RSNSIN20FkHBWtkXt1mlc38Aspl9d+fPgoEwZRcX1zvmwXkGkQMWhIXTMkQPbeTfU1hCKsjCZxsYIK0CLY5JTMuHCWSDZ9SpoOTsnEpdEfXyAQXoYZWS4q4qtVtNh+eajASMABEvLj2Id7FWKnAwartEGc2CxtMOO+lrdhZ1iaycfvPRQWyG9XeYKiXgJU2RgDw4c4qVLfZkBxlwE0L5bOmJEnw2n5ChOk0+O+lk/kSM3cMNy9wGTVOMFkn4eBuY0vJwsYSLoMdav4fTdM4XuetfOk1JK6Zy8zvzWaH4mZxKGHYBYA7ZEpSwjIR55Hoz+tvV3n/OgMEA05PKRCXwx88FM3bkUkzOpyMixATM2N8fF3lOH0WuwdakmA8M31cQwZu5/zIOeN9HuuJHAzHWTl/cnpATSqH28NLHQDeLNbyCSkh9bMMFTgBZYKErFeqxeFBl8N3UxCu16KApSp8sddX0Jm7DpdPSBE1ZlidbtkM1tiUKDg9FKKNWljZwDUvMQIHJVxHqW0hB4NWw8tYyMHi8IiI7f2FC6aKg99vJP7NNR3BcQCFEjGmIS4DIw3qOQhLwL8ca8BFr2xHTbsN6TFGPjM1LTsWF0/vfdOHFDaXJ6AP7mBBl4yMToqMlicAdNpc/Abt3jPG8J7wQtR32nDXx/vx81Fxt2xGrBG/3Xsazi5I4ylEU7NjYXW6cYClVHAJC6Neg8RIPdptLtE8sqW4GRRFYyMrS2bUkaABGDQk8tPlN519hfIWC5yCCkJ+ejQunJzJu4J8smfol4GHXQBY3uLLZROWAhnVb9rvQt5sHly7PZqm+WzI+LQov8f6w8HqDnRYXYg2ajEtO5Z/3Gx38arrQuQmRKBawruR2wlTYMrFAFDUYBaV7uwBXFlCieTocJ9O1209KANzgsfXBdH8sausTSRky5WL+1P8uVQSzPdmEghjg9aqVivGpcpfe6+xPr5S/IHlErV0OfmyDgBYnR5+wRZ2GwLywSIATMxkFoOJGTH8tZqXGIGjEskGf/d1oCxaf3cCA8C1c3JFv0u5R7Xt8s0uUgi1TW2uwcdh7g6UJFdqO2ygaRovrivGrR/sg9XpwTyBIoJOQ+Cd62eG7LyGShaQcz8RQun6eWVjCTqsLoxJicQlEgF9h9uDVzeWYunTm/DDYd+O/qQoIzLjwnGkthNuikZylAEZsWHYU9EON0UjI9brBUwAuGE+k10UloFPNnZhS0kzWrociNBr+HUkMcoQkGrTW2wuEn9OU7JiodWSyGI/qx8O+VcxGAoYdgFgu813l0YLuE40Ams6KZWJBgp1bd4gbHkvPIA5wutpY5JEkhsnG+R1j3ITI3wkGZQU8Uez6von6k2IMgyeTJeUk7i5qLlH0jSzcuMxMYjmm18knBKnh0JcuA7zZZooQoV3JAKscjxqoS6Yv2YQ7pMqb7EolmS+VNCwWzo+hRcofupnryYgJyeRkxDuI278PUvhkMr5cV9ZQUYMylnSeW5CuI/YtNQGTgheCkbh7RY3+mbBQ41Io1a0OFe12dDEvie7y8PPVYECQCHcHnrA5Jf6AkqZtqpWC+765ACe/q0IANONPzkzFnVsyfCxCyaK9BD7Gq1DpBHkV5nOeznpnNoOG89t/vOKcaI1YVNRM1Y8twVPrCmEVdAUKVQDOFTTgdYuBw6wgvBTs2NBEARfZZkrkStbNTsH4XoN2q0uUZLgk90M53fB6ER+wyl1GQoFpBnNqWxSZAnbQHhCYV0cShh2AaBDxkaoXJLd4hYQbW87KvoJXx70arqdMzGtx68jJ/8CyFvA6TQEPB7apxtTaRdsZFfsEw1mjEgWdwK7FTov+wO/WyDmtLRanLyESCAI33kg4WeAydSuEXRr69lIY0VBWsh3s0Jsk3Q7y4UCwvPx12jHlVvLWyyK2ocNnXbF7lpO3Fl4Tlwj1i0LR/gcf4zlogpNZAgAhWyTxgRBAJiXFClanAAgMSJwBlBJEPhITf8HgAB8usq5bmCOrxqh1/h0O/sDjYFz4ekLyEzhAJhr48fD9dBpCPz7ogLcND8Pr29mss+TM2Nw+czA/NzeYKg0gsjxuVOifUvAT/96Ek43hTkj4vk1obrNilve34vr3t6NshYLX0EhANy1ZBTeFzTX0DSwubiZdwTi+X/svT5PEgDGhOt4DrXwet5ezASMS8Ym8x3ArRYn74ATKhyWeIBPzWLO//q5OQAYGaxg5LQGM4ZdACiXvCuUSJxUsAtInB8+nW0QScFsKfJyyiLDerbDbTLZeXHNRZJmBLkO4MRIA/bLXPxK2VMraz10ot6ECemxoudqQ3wj+8Oqubk+jwXrCsLtQjUEgeX5gTOvJ+rN4iwB0f/dv4CvDIhcMkgY9BF+esu5ZuLyFgsmZihzcr5X8NC+fzlT4nVTtChY02sIn4aa0uYuvnwpPOWMWCN/jU5Ii0ZlG1sCTojwcTyIDlOW2eGkYJQEsI/J3Af9AWkg/CHbBS1sAAlGDkP4voZyI4hS7tJN0YiP0OOjm+fgylnZWPXWLlB0aLp+5TBUMoANMhaMUvtQN0XzXbwPrRwPh5vC82uLseyZTfj1eCM/I1A0k2n/8vZ5+NOZY5GfHiOigmwobMJ+lu83LScOJrvX4UOaAQSAGxfkQUsSIrtCE7vJnJgRI2rSW3cisJtRT1HdZhVRJeIj9MiKZ+aHvKRI3oruve1Dmwc47AJAOTRJghZOt0jqIiCEVB9oIMFlPIK0c5QFR7KdnBmDRAlP6riMBuCE9GjskjTUaAjlEnBRM/MaFS0WjEgSf65binsuv9JbaEjCxwZp7fHA0jQ0TcPKioeH67VB2UitlZRenG4KyVEGzPIjORQKSLM/cguqJwiag15QK61osSAvMVLRUuqNLfJOFikxRuSy2nxCN57TxiSBlFzQnHeo1MZvwehEON0Uogxa6LQEnG4KOg2B9FhxVkNHEn4DJV4MWuH5CoGeWX8iOdooKq1VtVnR0GkXSMAEV/4VfjdKdmqDHYGuy9euno5ZefF4bm0RvxH423kTEBvC0i+HocIBtDh8kxfS+8Jsd4GmgXMnpaHR5MAZz27Cs2uL4HBTCNNp+Hvk6tnZ+PHuhZie4+0APm+Kd0O74WQzms0OaEkCBRkx2F3WBopm1ta0GN/rNiM2jOdDhwv8q3Piw3huL9estU7Bcq4vIOWCT8mKFX1Gk9lqh7SaMtQw7ANAAr7ZvHK2y2ya4KKWYo2MzdVAwWRnJnPhDdNdcOXfxZLyr4eicVKmA3hKVhyO1YpT5HotiRYFjbGaNhsSIvRMBlYyh//mxw2iPyDt+N5V3gYqwEKzr7IdLpY7Ghbk5/7zES//j9txnzMpPWgj9r6C8J0pjewU1dnkPwvhR1THlnmlVn8cihrNiov3zay0hEeQivy/FeN8juM2XUadeNrKY8XFJ2RE84tEVnw47BIXkkij/++J09JzK2gkdthcPpaR/QUpLeO7g7V8CUzKk1SCsMtczk1jKCBQJ7abplDbYcULrMD4hPRoXD07p0/PQemeGSolYGkFXW76cbgp6EgCzV0O/O79vahusyHSoAVJME1ESVEGvHPDTDx+YYGPeL2womFmpVLy06Nh1Gl4/Ty57B+HWxYxGW9hRaDL4cEe1n2DKx3vLG0NWqqqu/jpiJirLV0jLpzGdOc3mhxDpvtbDsM+ADRoCZ/l7WQDE9gU+CH176kYPLV/rmNSbkcV3N9TfBbudIn+X3mLRZYvNCo5kndb4BBt1CpOgnY3xYtomiWyIEWNA0umffTsfNHvVqcHRU3+z0loUxRM/NZosotIw9xneu7knnM2+wJKGTsht1OpX4AL6DjZhopWZR4gRQNrJKRqDlfOzBZJP2gIAiOTxR3FFEWhms3oSAngNaz+W0FGDJ+lG5EYwUtNcEjww/8DvBlAOZcRDgPlA3rradIycGXQGoAchN2VHUNUCiaQ525tuw2r3tzNC6x/cOPsPj8HpSzyUCkBS6HEP/bQNHaWtUFLEkiOMqDL4QZFA2cXpOHXe05TFH/Pig8XqUgAwFQ2gOL0/+aOUA4Ax6VG+2i0tlqcfAB4+rhk5CSEw+mhQuYktV8yd0yVvJ+LpmTwG4HP9gT2VR+sGPYBYITBlzxd2WYHRdGywpYcBpsUDOB7kQaLPRVt6HK4kRCh9wl65RpAACaF3ywJ9jJijLD6IZePZ32ApVZOcubu/YkJmb6B/voA/JLulq2FfBWSYLp/M+PC/OpNhgLtkgU0Ljxw84BSOMQ9zom5VrRYFDOAAPDudvkysEZDirqg5bTGfjneyGcchcnJSIOG5xRNzIjh/UVzEyKwXyJSLu34liLSoA3YTFE8AI4gADAqJQpRAp5WVZuNp6oEWwIWaoQOlAd3b8FtApSw+kAtT4l55Jx8xPvp+u4plDZ8Q/UzDRNkhoV+7xTNbPQ1JIEmswNRRi2eu3wKXrpqql9+POArazUtJw5tFifP1Z3jJwAEgFsXjfR5jGsAm5kXj6VsJ+7aEPAAG012n8yidGOr1ZL8xut7GXOJoQI1AJSRJKHBEGVTFcQxgcEjBXNY0Ihx6YxMP0cqg+P/LRrry7uSawABgJRog09mcHSqsn8y4JXgKJXoqTkHUAuQQ7wkEPrpqH+Np9Lm7vHBfj3uzX5xC/G5k9ND7mUpxQcSCZhsGfkHDpz8CxVAMoTr8C1rsfiVwjlQ1aFYWheWfOXuyS/2MrvsSEm5af7IBP4aLcjwegDnJkbgEOtpzSEnXpnTyyFQMDWQ2Wpp1oSjqgSbARTOZ0PVD7iyzb9TDycxMj4tKihdzp5ASRZpoDeyPQWnEbm+sJEvZxIgkJ8ejZKmLjjcFOaPSsAv95yGC6ZmBDVnrZwkrmxkxobzDj5jU6Jk7eSEmJ0XLyvMnhFrRFpMGJaNZ7KPGwqbAtJ1ugsp/29kUoTsxnDRGCZLKddVPVQwrALA+nbf3bt0QeFQ3mLp98W5JxCmn2fm+t9VKWFDobz8CyB/cRu1JL/LFoIT6RRCbPbNlO4KG8wiiZ2BD/+AC6aJHRcK682K8jQuDyVyUwgkqWZ1unlLI8DLv+rv7l/AlzjtTz9O2myhBCdLQahosWB0snIjiJuisb5Qnu85NjXarxPH/soOAEC4RABwybhkONyMh2huQgR/XY5IjECxpIyfEuN/0QECB1NHB9C68GaJDZeZJfNnBpkBzBK8N7lO0KGAQIoBNNjS702h6/pV4uwOlSYQKZKimA3pT0eEFA0ax+tMMGhJ/PXcfHxw4+yAGXQhkqOMKBCoAhQ3mRX1/+RAEIRsaTqVlauZmRePKIMWrRYnDtZ0BH1ewUBKVZmqUAm8gd1g2N3UgFqa9gbDKgD8/rAvB0lKYOXALST+vHXlLHX6G3sre8dFrG6zoripCxqSwGmjfb1o5TKAmXFh/G5OiJRo3wlCeBOXNpl5S7iYcPHnPtCyOvewrhQc3BSNg5IMEofKVosoaFXSuOOwtbiFzxjrSAJuiimt9Ma1paeQBu7+7OeEC53SXkhYQq5osUKrITFOwRcYAN5ihWXloJhZ6XLynLVOqZA7+zcT0qNB0TRfIsxNjOAFkzkEyjoAgTOAA1UCBoBZeQkwSuYjvYb06dpXQnaCNwM6VDOAgUrAAJNNToxUrt70Fkod/60Wx6AX2JY7v2T2sxJKrNBgMuo/3r0AN8zP86kMBQNhdWHDySZeXiuYALC+U96XvYitHuk0JE5jeYLr+riJcFe5WN1CiaYzKiWKL5+/u72iT8+hvzCsAsCtJb5BS5RCAMiRyaWlQSHWFYaGgNodcCr3wWZrpOA6K6dnxyFG8l5buhyyvquTM2NwiBXJFI7qkOmeFHYmH6jq4LOEyRLz8arWgVtYASA6TO+zs/9yn7zt2CGJQGigAFAo/8J9xudO6v/yLwAfbkuLH1K9MCBTuk/iBPIaHCdtoh8e4L7K9m4vkh/uqmTPRyzkriUJnKjzln9r2m1wUzQMWhLRRi2kaheBmkCAwI4aTWZHv7gQKEGajQjXk0EvzlmCbmEluabBDrnKgxBCS7FQQSkD6PLQIg7dYITUGQcAUlm5pCpBU1+kQYuv75iHUck936S6BOvBpqJmlDZbQBDAnLzAASBHS8qS3I9mu5t3FuHKwH2pB9ja5fDpNPfH0+aynAMpZdYbDKsAsKzZl7+jJOHB20n50QL89fjAewFyshRSIc9gsYG90RaPCy77BwDj02N8eHyAfAlEmEFt7nLwncCRRnGwualo4IPpkRJ9ws0KHWZ7JDtEl4JsCABQFI1fBCUFjid0zgB1/wrpMiQBXllfDsKFLkwhUygM8Fu6HDDbXX67551uSvFzVQL3+UlLxOPToiQNIF79TjmOZjANARkBxKCBgesEBoBr5oglTbrj6MEJ2QJDVwewyeQ/cGWsPEMb3Pq7Nga7FMzPR3wbFjgXEGHwGmnQ9tqd6IhAJoy7TiekR/skGuSwnqWqXDQtE7ES8fZHvz0GAFg8JhkkwVCK+soVRFrZMupIRY9zALhgKsO7r++0wz4E5WCGVQDYJjPpOd3yu/lCVgpmkp/FbF/VwNf9uQVdWN4JFnaXh0/Ly/H/lALAvMQIWQ6R3OQnnCs9FDCeLQ9KsygbQijqGSz+uExcBq7vsMMhk+3hPhfuvfnLAB6s6UAnO7HqNQQompkE5fiS/Y0wnQatXb73BLfACTOASlkPLp7kpWBarHwjiNI6+aaCKLQSOEmeKMkm5/wpGXyX+kSRB3AETso0a/izgeMQDM+pRGbz0184a2KKKNtvd1OoCtK6ME3QBNI1yDNVSrAEscjWyJQO+xL+vLEHeyPIZplMFXfNy811PUV9pw31nXYf6si8kYE9zx1uD9+IcUZ+CqbliIXyj9R2oqbdirgIPWawz63vo/VDyv+blBHrV+T/kumZ/Dz31QF5t6PBjGEVAMrtlus75SfP2g4H3B4K+enKAWCrguhxf0HIm1s4KvCNJcXOslbYXRTSYoyyuxyl7qbs+HB+ARHmvoLRwRrFBj5Sy7judtWGAssniLNyNIDvD/tmeatZ/TVuh+yhaUVOldBVhOObSiUS+gsuyWYnNcYIs933O+NK06RgdlBqtOMCec4urrzVgtEpkdBpfPU1Oewpbwu6DHygqp3PsNZ1iD/jadlxsLsoROg1GJEYIeoALpIxak8IJgPIlpz8NRYOJA+QJH0zEt8dDm7hEcrryHmiDwX402jkwOkjhgr+AkAlK8zBArnKDVdm7UtlC06Dc2xKFC8TBfjX/+Owp7wdVicjNp2fFi1Lb/rXT4UAgKVsGbiv5GA4oWoOUwJIq+m1JL+x+kYNAAc35K7vKj+yArUdNkzOUg4AB1oK5heBVMlF07ovAcPxLBaPTZblo52QsYADGFkQuXeuVHoRNm5yGVdpwDQYhGk1JOHjpvL1fjEP0O2heB9VYXn7kEIn2ncCD9x2NgN99qSBKf9+d0g8QU3OjJHdFHGyChrBNaGUKee+NyebBS1vtsCg1WBMinLZxO6mZJuI5MDJ1oTrNXwXOcBkFznO4YT0GJAkIeoALpQEgASCc8pJiND7OI1IIeeM05+4bGaW6PfPdwcnRCu8x90UPegbFuQQzJQr1zzQl/BbAh7k3MpmmaQF11nbl5cDp8E5IzcOc0d6M3hpsYGbc9bzqhRJIAjINuOtOVoPk93FB4B94QrSaXPxSQxuag9Gp3UhKwdztHboycEMqwBQDma78k64vMWC3B6UVvsLPwoCwJyE4OygONA0LbrRpLC7PCiR4TpFGbXYx97c0nlQLgDssLqQJiCfH683IT5C7xNA+uPR9SekmVRpYFfVZuUnSuHOVqo5BwBVrVbepYIroU7PiQvauquv8c1BcTbzjPxU2c+de0TYXKA0uZpsLnEnMJuF88cDBIA3NpcFc8o8RUFKBk+JNuCogP8HiHm7JyUBoF5LBtV0QxBEwDLwCZnsYn/iipnZot+r2m0BmyPkECobrf6GUSsO7OtCHAAC/uzgBncG0C6juRoXoYe5jzfgB9j5cGpWHPISvXSXnaWBN35cY+KSscmobrOhyewQOQUBzEbg9Y2lGJkU2WeuIEJuN5cgD8Zc4bp5DC/X5vIMuKtVdzHsA0B/YQenBehv2egcQCkYrgOSALrdpl/WYkFVmxU6DSFyYeBQ0tQl6906KjGSt8kRcrJIAmiRcUdxuD1YPMYbYG4vbZWVP6EhL1HQ33hopdiD1uLwoKrNu7geE5TFtYJJ6bCkMxgQ+0ly2adzByj7B/hyOmfnxSte/9FGrei6dyoE6C4PLdokcYHIBDYoU2oe2VnWJvu4EHanGw0s6T9OIht0+rhknmRekBkNh9vDZ37iI3Q+LjVy4tJKCCQFU9dhg0MhI9ofkCuJ/Xg4ODcC4UI61BpB7C75gFUrCQ5CXQIGfP2oOQz2JhC5u9io06C8te8oOE43xd+b03Li0CGgBn1z0P91WtFiQVmLBVqSwPzRibz9W0FGjA/14e1tFXBTdJ+5gqw5Jt4gp0QbgrJXzU+L4a+Hd7d1j9880BjWAWCgJidOCkZJ2BYAfj3WtxpE3QHHN/GnVagErulidl6CrBaiEv+vIDOG3+UInQW0JIE2q+/kRwO4eKpXZLmo0YxxrCWcdBlrHwQLUk5ipM95vbfd657BTUhakhBxgQ7V+LpcCGVkzHY3SMJXIb8/IZU3iAlX5sRxnYGAf84TAKQLyjrlEikYebIAs1veW+E/G7BasFhIM3rXzMnhr9GCjBhUtTKZ2UiDVjYLE4wEDIdAUjAUzTS7DBTkpJmC9SMVdnZyVIahggqFZhcNSYjKsqEuAQNAXIR8J+tQ8wPmPra+bGw6Xm+C000hLlyHnPgw7BRk1o7UdPqVUdrAZv9m5sYj2qjD3so2/nepELrN5cHqA7V95gqytVjC/+uGTSdngbmpaGjJwQzrAFAfIAIsYbsPlW52AFin4GzQH+CI3MH4uUrB8f+WjJM39FbyAB6ZHMnvsEcJOlmNWg2UmmEnCMqBFoeH7wSWbqLLWwZWC5CD1AJQKDTKBR1CUWECTIAn3EV3Wl0+JfS5IxN89A/7E8Jyr4YkeEcSOQgDQE2AADBeEFx12lxotzgxPi0aGpKQ5Rhyr/b6Jv9l4G9Z/mRKtAHtNvGiQZIEbC4PwvUa5CVGCsq/4bxYrBCZccF/7sF460pdRvoTtR2+gVB1uy2oRVzIgxxqGcByhUYxLUmIMnL9kQFMUbiPB3sJWAqOmtKXjU0c/29qdhwqWq1oMNnBJWk9NO1XM28Dvy4xVaO9FRyXMB7nT8nwmYv++8tJzMiN67UriMXh5pUtDKxN1ZQseQcQOZw3mUly1HXY4BxCDVbDOgA0+HFBALwls9xEZcmOg6xF1UCAW879Ee7l0OVwY1c5s9uR4/8ByhIwOQnhPPF/VIq39BcboaxDKNSDogE+lS+9TTYXDbwUDABcO1estVbZZuU7rivZLMQIgT4kl1UR8gC/3OfNyHAZ5IGwflNCpEHjV7IiOdob1ClJwHCIYIMKrjRZ1mKBUafB6GTmvpH+NXfdSjvupDjCltVHS8Row/UannA9IZ0JNPkO4AT5DuBgfIA5BOOtO5CdwDVsgKOXlD6DKQMLPU3bh1i2qlLBBURLkqKAzOxw+2S7+xqZCtfTYG8CkYKbm3rCIVUCx/+blh2LHWyz1/ScOD5I/2R3lezfWZ1uvjlsydhktFucKGY3NdNz4qDTkD5NmU1mB/ZUtPfaFWRfpTdLyXGFg+H/cbh8BtOESQNYfUDeQGAwYtgEgE0m38lDiZ/Eoc3qhsPt8SsE6c9JIZQQdiIuz0/p1t9uK2mBy0MjJyEceTJC1zRNK2YAY8J0PDcwVZAlSotWzrB8uLtSFATEhOmgYS3RhJBzahkISE3kaRr47XgDPBTNT/CTMr0TkVwA+KmgJOdwU9CSBM6amBq6kw4AKb8yKy4MtQoSSICkBMwGdkq8J04ni7suKgTduYCyBZvF6cGhankrw+pWK9/1mxAmvk+nZcfxnrzSBpARifIagNLuQ5qmFTvPM2IDN+kMpBYgV+KUNhMpOdcIkRDhLfvLlZIHM5SaOwjCN1sT6iygtCmJw1DLAEay9J/6zr77vIQZQG6TN39UEq8BuLOsVZbvvb2kFU43hcy4MIxKjuSbDUclRyKevW7PkdlE//unE712BflFQOWyuyiQROBGNiGMei1S2E3z6iEkBzNsAsBfJAKPgH8fVA7VbVaesyaHgcr2fnfIu9ufE4S3ohDCLiu5zsjaDhvMMkKxBIA6wcQqzCBkxisvmnvL2/mJBmDS+lLXDQAoH0BelRDheq1PduWLfTWobrPyMhTTc7wLDhcAHmQzVnaXh9+5cjhtTBJi/XDuQg0p325WbgKKG5SDGKHrBpcBVKJMONwUDFqSz+xx2biJrE2SHMeUyxa+plAGfm9nBQCmaWFHeYfouStmZnk7gNPFAWBOQoRsJ57UG1Zo6SZtdgomAziQUjBcBnDhGHHzVnW7DcUBuhCFgXBfLvr9gVo/bg9zBFIjQOg7gaWuNBzaLE7Z5rnBADnBei6w4qoBvTWnbDLZUdthA0Ewm2Su63feqATcxHL4rE6PLMd8g2Rd2sNm5WYI5tqFo30bFo/WmZATHxGUK4iS2sRmiRPVmJQo2XnLHxawzZRyDYGDFcMmANx40pd3IG0tB3xvgPIWK6b40QIcKOwS6Kh1V1ZkQyGn/ydf/lVqAEmI1GMv68MYptOIPHGVJkSA0fwbmewN+LYUN/M8QCHM9sHDSZoo2f3trWhHoSArOibFe/7cdXSizgSH24N3tlXwz3Hx9bkDZP3G4YNd4rLL0vwUv2Wf7nAAm0w2jBDwQTl9Pm4HLcc15ILKrSXyfKD17E5+ZFIkmiSdlUvHJ/Pd2AVsJpZryogN18ly26Qi0MJFQiounBJlCFj2rmi1BPSADhW47FZ+WrQP//f7Q/7LwFlx3vtQSbx8sKLSj+PJDIlbRKgbQeIj5ec7GvLX+2BAscymJZGdt7kNf2/9yfcLBKDrOuxotTgRptNgcmYs5o1IgJEtOb+51bdblmtM5Ph/+wT8Pw6jkiP5TJsQb2wuC+gKcqi6g6/gtFtd/CbS7vLwmyqO/yf13A4GXOXI6vQMqF1kdzBsAsBiGR9gj2AC5zodpTdARYtF1Owgh/YBSPuXsYRoAsFlMjm4KRoNJjuMOhJzFFTZlQSgx6dG8dzA5CgDSgQ8KC2pfCnZ3RTOmuAtf+6rbJPNqg4WLUAAuP/MsaLfbS4P1hxjssgkIc4SaUgC8RF6OD0UCuvN+HyvN9iiaYZnc0b+wJV/AV+u6pSsWH7Sk0NKtIEPcLjEn9L3U99px6hk7z3ClYDHp0WDIJjJVtqozjUwme1uWb5pZStXRhZfJxqCWdytTg/CdBqMTIqE1eklcDsVgjJpF7Dwvbsl70urIUX0Bjm4Kf8BSSjBBTcZseE4bYx4E/fV/hq/ckrZAj/gxiFWAvbn8ZuXKN4EhzoAFJbSpRisncA/y1TBOBcLG5sN76aamA8OVAvLv8zmbkZuHK/DOT2XCayk3u9uikZdpx0GLYm5IxJhd3n4TNrMXG8wRhAEFozyTVz8erwBc0cwAaCSHMwL64r5nx1uD855cStufm8vvt5fw1cvuLV0ajc6gDlMyozlOZXvba/o9t8PBIZNAChn0WMScIC48pZ051/WYoFGQ/pNja857msXFmpwxt2BXAuk4Pwe549MVAwcj9fLp7DHpUXzi15uYrhoousM4C0qbICo77TLagECvuW4gcLsPN/geBcrZ5AQ6ZshmsxmonaUtviUspeOTxaVwAcCUr5XhEGLRj8ZIJvTw3+/3Hu1Kcg31HXaRSX98hYLaJpGhEHLN8uMSvb9vrl77pUNJaLHHW4KXEwWpRd/znmJEXxTUT7XACLI/ilxv3wzgIIAkPINGoMpA5cMQCcwTdP8e8yIC8Oti0aInq/tsKPIT4OKsFrQNsg166QQOsFIQUo2oKHmAMb7CQD9BaoDiV0CORYOnM4dt9kLJPkUCAfYjebU7Fie/zdXQFG6cT5TBm6zOEVlegerFjB3ZALC9Bocqe2E00MhKcqAbAm9iCsDC+dgigZqWUqDnCvI0dpOrBNkBsN0GpAEsPZEIx5afZR/3OpgrrFAFnBKGMeuaxsHgbd9MBg2AaBDRo6iU1By5AIpaVn4OLvYGPwEWpsG4MvmylZJ3ZQV4TIvixXkXwDlDGBuYgQfFExMjxEFBC0BsgmNZm+w4fTQsiVgAHwmZ6BBkgRiwsRBWyN7bnKuK5MyYwEAqw/6EoAHQ/ev0PuVu8bb/IiYCzUZSYKQpUtwaDE7RBlAq9PDW05xZWA5ikA8K68kzQZwHdexYTr8dkJcIj5rYhqO1Hj1/wCIO4AVOHDSBVtYApbLbGYGIwUzAJ3AbRYnf9+lxRiRnxbDd2Fz+P6QMgldGNgG2rQNNkgztVJoBZdozUBmAAdpI0iFjMwWlwHk9t1yIuPBwuWhcLi2AwAwJTOWpylxzR8AsHR8Cj+XvLaplH+cE1Y/nV2XOL3VGTlxPlW5eaOYgFKaLPjhcD2y4sNkXUFeWs9sMrmkR0yYDr/+cRHOnyKem10UzVcWeoLz2Lm+ut0G9xCQgxk2AaDc3CHcUHJiynqNeDLltQD9EPgPyNiAhRI2wYkXZCg3qMiBK5Epyb+Y7S5UKcgtpEYbeY2jOSMSRAunMMCTw0e7KkW/x4fpZHfRcmblA4WzC8STAzffTEzz5YRyoqElTWJeXaRBq6i12J8QXv5cYMvtdqWIC9fBJNgcUbSvNqIQdjfFa+dxczUvCM0GaXLaWBRbqjTZ3SgRBG7cNTo5Kxa1kizltXOzFS3gmA5g3+tHjiYhzAB6KApuSek4kB0cAJ9Gn/4AV9pMjjLw72lWnpj/9vWBWsUycJzgnrM6h04ASCv4jwsRJZC4CXUTiL+GLn/ySgMJOW5sRlyYyOdbE8gdwQ8K682wuyhEG7WwuTww2d2IMmh5UXgO3Mbt12PekjR3zy8ew8yVcvw/DslRRl6ZQ9isZ3dRyGAzmsJu4JMNZp6+I6zEjEqOxFOXTIY06WlzeXDnR/sVpdD84XLWppEG8P3h/q8MdhfDJgAMBC71Lc10WFwUbE4P8vx4Avc352ONwAN4ydjuBxdjUiIVG0cK/fic2gQLxuTsWNGE3CxjAyfE3ooO0cV2tN4kK6+zZZBoAQLAH5aNln18mqArjQMnCyPdlS7PT+kWR7M/wHlzKtmZpUQbRVkMD0UjPYAlUoRBC4LwGsqXS6RgqtqsCJNk0ZvMTp4z8/JGbxmYCwzldLgSI404xkrAFEgCwJyEcNkuWDknH2EASMPXZSKYEvBA+H4Ky78cblwgdkio67ArZvGjBAvgUBKsDUbXL09QKmwWdHmHAnotqbh4DlY7OKfM150eYxRxWf1l+gNByP/jdGZn5cXzMlEcrpzFBEkNJgd/rwPAyKQIZCeEg6Jo7GUlYIT8PyG4jttciYzZCbbRZcNJryvISyzFZMXEVJ8M55HaTn7OihcYPqw51oAVz2/B7R/u61YgGGnU8tUOoRbsYIUaAEog1/1X0WoRdbFK0d/z6EZByWxUN0WgAf9Bo9LFTpLeBU+nIRBtFHcftgXQQ2ww2UU8rG0lLbJl4GA8YvsLKdFGWVL0WJnANSHS4FOKA4BzJw98+beqTRwMzGc5OUrXbXK0UbSIeSg6oDtGp82FLMGmgnNFmcBmqOs67bK7eU6HkutM50ASgEsSoCZE6FDWYoHF6YFRR/K8Q67pJDpMB6vT49O1HCXhX1IU7cMRkwZzwbiBlDbL+2WHEt4GEO/5LRyd5CPR88Nh+TKwsJxG0YOHcxsIzUE0rEyX8HbrQ9zlrEQLahmkGUA5xEUYRFWXQB3//uDV/5Pn/3E4d3I6P69aBFUIrvxb0tyFTpsL4XoN8hWoQgtYHmCnzSUKYjptbhi1JFq6GFeQ0uYu/MAKpN91+iif1xEKR3Nr/9/Pm4BzJqWBIJjGmRXPb8EdH+1DYZDST1zJu6euJP0JNQCUgXTRL2+xdNttI5Q4KnDWkBJkg8FiPwGgkgRMRkwYjtYxi6Rc6bZLoZzIweGmMJnlyQHA1uIW2QxgtR8Np4GAdIcJ+DYUAAz/RWp7FhOmxfxRvrpV/Y13t4olYJbnp/rtFE2JMoiapjw0HbAk2mQS8wA5265oow65LGdSTnSc4yB12FyiYCQrLhw/HhGXUGbnJfDZv/y0aD6zwHEAuR1/pFEc8MVLvq/mLodPt7DUaziYDKDLQ6NagS4RKtTIZAAB+DgkrN6vLAcjnN5MIXbM6Cs0BsENln4GoW4EkZsHgMGbAZRDTJgORQLJErIXHEBOAmZSZgx2sw0nQv4fB6NOg5HsXCHM0nKJCY7/NzU71id7yGFWXjz0GhKNJgeWSYwQdGzGf92JRry8oQQ0DSwbn8xXI4QQNoa0sFWslQVpeOmqafjlntNwNhsI/nSkAWc9twV3frTfZ66Q4hrWScri8ATkrQ40hm0A6C/TLRWALG+xYFKAtvAmU/+JqnL6XQSC9wHm+HoECMxQSKsDyhnA/PRovtQmDTqDrRqsnOTVwitsMMlmAKXdWwON208b4fPYDhkLs/WFTfBIgqqVBWk8t3Qgsb1MfL6jU6Ngsil/zsnRBlEno4fyBoBK33WjSSIFI/BF5rygtTJ/XNVm5Uu0wu9+wegEVLSK76lr5+Xy9nBc+ddkd/HBKtcZT0pMBqWuDVwDiDDb0ZMMIND/PEAuAJQ2qVw1S2xfWG+yKy4+OsE1qeSGMtgQjKzLNIl2m5xncl8iS2HzPVibQOSgIQmUCa7hnoZ/LV0OnjuuJUlYnR7EhesUXbQumsp453JzJrMuMRUCzv93eo5vxYBDuF6LaTmxAIDRKeKGDU7T8OcjDfj2ILMR+v3pvnQeD0Xzjj56DQEaQGZcGO9cNCYlCi9fNQ1r/nAazi5g1q4fj9TjrOc3486P98tSQFq6HGg02fkk0kA5hQWLgV+dBghyixEHaYdXcYMJ4wNkANfIaCyFClwTSLheE7RwJ8f3MmhJ3rlCCreHUuQAjkiK5Hfh41OjRRkkrVb5HITPpArEU012N0anRPpkWwcbLekc1uRbiN+O+37Xn+725XsMhu5fAD56fzoN6dezNCXaKOK1MgEgk6lTIok3mR0iKZiKViufkePcOho67D5yOKXNFp4/KcwGTMv2nfxn58XzEjBcUMmVfxMjDXzQ6ZQEPtKube7zENI9pPZxRp0GCRGBN1fF/SwFo2QDd/6UNJ/gXEm2R0icbx+kosVSKDWmCSHNUoc6A5ipYBk4WJtApOAuf65hphf0Pxxgs3+jkyNxmC19zhmRoJhRlFJjDFqS3yzvZR1AlPh/HBaOZhoZixu7ZJsay1os8FA0Fo1JwmSZBM6JehNfdUhis7lTZI4bmxqFl6+ehjX3LMTKglTQNPDj4Xqc+dxm3PTeHry+qRQPrT6CpU9vxIzH1uKOj/ZDyqyg/FRcBhLDIgDssPoudhqBbpT0Es2WGH0frO6AXqfxuzuSWsmEElyMlOanM1MKTgbEn5xNRatFJBciRFZcGKxs4DkjN060yw3XKjc5CFP4XwpMsikaMGg1smXBUJK3u4swvYZXr+ew/v/Z+87AOI7z7Gf3egMOvYMgCPbeSVFdsoplS5bkbkvukSzbikvyJXYcx70lthPHPa6yJVdVq/dCUSLF3isAEr2Xw+H67fdjd+Zm92bLAXcgRPH5IxHt2u7MO+/7lCP9qhSItCThBY14pdjjwEYdo+2ZBqv2JN02o02qMqDPAdTjjPVrOoDxZBrdii8X6dYd6hnHJQuyR0IkVo/8ZQHZVAC3XYQkIZMAwlMAK4cX7TVcGzQvANsHw1nXnZWEnZMzbAVD4tC0I2BRFLNoKnr3EVuEj3GUobMR3aPW+HzsGt1l8XeminKd9KPZ6gOoBWkEDChruWMa04o9SkLUGib/l8f/I6gv8aqsoYj4pHcsio7hCETBPI2DCEFeOTWEj16UPakhuPOKbO4fADxzNMP/87rkwx6vACRYVF2Ez1+7GJ990wLUBz2QJFlt/K3HjuKe7WdwSqG9LKoOYI1GwDZdf8VC4Q1RAD5xMFuOLTAaVpfm6JPFJVFOSEbF0/4ZInyyJs08Uj0PQxMxWrDwFJEEh3T4f4BaHbZhbilOD2dGfEbOAWy3kSi7CEYn41lJD0B2x+psY1Wj+nqYiKfomAIAIol01olvTWPQNE5spsA+N9LdNsrLLPc7VT6AqXSa2sDoFYB949Es7yxi0Ew+49NDk9xrdjKeUokYHDYRjx1Qc9gW1QTQPhTGRCwJl13EfKXYpLSEMi9Nx9GGgWg3ajoCVj4fURCQlkDHQQRWeIAzOQIejybomJs3or5prbpbraUkEBQzdimzNbVCix7OOFfgHMnZ9a3QI+BSHSuY8Why1imseZY/HsWdgCisvRwRm1XsVgrAZXVF2KWs8xeYZNS/haEETcZT6B+P0u7fktoiU/P8ZXXFKPY4EIol4XGI3C5f0OPA2jml6BuP4r+eOEYN8QcnYvi/FzM55Ky9EnmvJElC22AYf9pxBp/5815s+fazuOi7z+H7Tx3X9Zm8Zmk1fvTeNfjdhzcYPvfZgrMbTzBDePZIdneO3cgqNGTei+aX43+fzdhSJNLy4lvideoqy4bCM3OSfoTxFlrBiCqMwOatGp1E9KwjAKBnPKb8vjwiVKs29f8mu7H3jsfgtGX8F19pHcLimmI8tE9doJ/oG1d1k842rllSjVdb1cXr00f6QHqXEc7iauQTdjZBnOq1xQ4L7SFBgny/FHscunYcPWMRBL1OlPudlJPXNjiBC+eXo8TnRF3Qg67RCJezur11WHbeVy4Dl8OGY31qP8XrV9bS8e9iVgCiFIDFHjviqTS8ThvtVBOU+7UFYKYDmETG/PZ4X0iVAW2FB3iiL4R0WpoWed4qyEgz6HVwg+pv2TgH33zkqKlfXlWRm/ol9ozNrsOWHnjdPN5SVuZzoGtMXqs6hsPZP5BHGKWBDIfjht6ZM43d7dnuCkXKQYBQiord1vjkWiRTaRrb5rLbEEvKCR5mZsrXr6rDPbvk/09JEt7/q+2Ux6nNdubBJgq4YF4ZHjvYi60nh3D7xc34+N27VT8zHk3gjj/swpOH+5BMS3inWwIEOUiBFS6SNePOP+0FIDc8JCk7J9wmAAtrAtgyrwIXzCvD2qYSdAxP4ofPnMATh/rw+KFePHG4F9evrEXQ6wBm1zkgC2+IDuBxDk+HLQAXasQIizjihPbBsKHidqbEPq8xnSdeIgUPLxyzNp7WE4A4bQJOKOO1Yo8DgiBgX2fmeYQMiORs5zCeTKOWGau9cGyAGwn30onBrK+dTYxzEhNYHqB2kQCsqRZnAhOatI+L58tKu9ND+hs/r3HUORIxpBz0KQcEdtFnI/HIyHYgFEdQk7ByrC+E96xvoP/mpRG8e33GAHo5U6S1KR5mpBvEoxRkp4CoR8CkmNTyAK0UgNFkuuC5swSkAKzX6Uy6nXbuGsWaegNq6kjv66QA5FEWeDU3u3Z3j8YKanOjVZezmG1j4McOZfOWSeODKOK1ByWrONYXwmQ8hYDLTqkbm5vLTPnpqxqC9DFFQcDxvgk8qCQpGQkVWRA7mK0nBnHV0mrqOECQloBHD/YimZawoakUQY/8mtlilzfYS6Qk7rqekoDD3SH830ut+Oe/7cf7f7kd//vMSdQGPfjwliasqCuGJAEP7u1WGW/rZZSfbczaDmA8Hlf9dzoY4Kiy2A79JQsq0fVi5vG0HneAPGqaW+7j5ilOBVN9fWycjxULmHRawosnBnAVUqaPd1inAJxb4cNJxSqAEK3ZcXHM4NpOJdWbz4amUjoa3Nk+jM+8aUHW7+zWjIqtIh/XCg88P6czwxFEivUX+f2dY3nvDE3lmrl7h9oC5vJFMlm6Z4w/HivzOWhEol25ZuxIoXNkEnVBj65IKBxPIZpIYV6ln94jrBJ4WV0RHj/Ui4PdY7h8URXu26P2qfM47fDbASkFxOPq91UUAK/LTjuApACUJAltynU5qfDdaoOeLCoDa9fBegCmlWtTTMsF/vEsKxhrB6yT/RO6ilAW013TeB6AWly3ogY/eV6O2CKfXyqhvgdZVbRVbp0V5HPN1oInaBEFAZDUj7e8rhjPKNMJCUB/KErzbvMF8nhGcXD5EoLk673c35Gd715VpOb11pV4EB/L/TMkApBVjUG8SuPfjMe/QxMxPHawFxOTEdgAOJCCXRQQUay0/ryjA48f7IVdFGC3iXDYBNhEAXaR/L/83wnlcL7z9DD+++njsIvZ1Vy5z4HbLmnBvEoftt37PAAgGsusMax7l9shYkVdMRZWF6E26IbXacfgRAzdo1F0j0bQMxZB91gU8WQagxMxDE7EaPeTB3IPxmOzk2oxawtAojI18iuziggnRJz9q1cvq8KvXlA/ntMmqNSErQMTWFBl3NLuGolY4g2xj5Pr62NPFVZEIId7xjE4EYfoVj+uFgOhmK7Z6oKqIrykiFwI0bzXosmqJEko8znoiHwJYwvQORpBZcCV9V5PdVPKx7XCg964VC/r0WUXMRFLonVwAi2V+fOPnMo189ThPtW/ibCBdygC5E2BCHxI6SpA7pqZeQEOhGJoUXUAs61gDnSN4c7L52cVgNvbhpTrAEhp2um1xW6k0xIOdcmFHRnTjkxmOHEDSgeylDNiZrlaxANQFIBoPAUbMp2k4xpBh3UrmJCluL/prmmZAlC/2Pzohc20ACSfnzZEjS1sB/LYqcrnms0ilkxlcWwBpYObVj/ecg0PrGskkvcCkDye0QjYSGU/lceaLjpHssfhdUE30unMGja3wofJttw/Q8r/qy3CL7e2AeD7/41OxvH4wV48cqAH204NIZWW8D63BJsgC+nYjttLJ3ObAqUlqGhbLAbDCXzj0SMAgPe5k3AKalWuz2lDOJ7CnVe04JOXzTe17pIkCcPhOHrGSFEYRefIJLa3DeNIz7gqIlXvHpwtmLUFIGkfW7U5MYLZeLayyJP1eH6XHcNMsbXn9Ag+dUV2t4rFE4d6s2KZ9DDV10cKJZ/LpmuSyeIFpXATRRGQ0rqPZxR301TmxSNKV4iopEIWg+QFQcCy+iAdQ7O5ydGE/HzqSzxoZcaF4SlmlObjWtFCkiRd3mc8lYZT85Blfieay314rX0EezvG8loATuWaIcII+fcyRq96XD7WA5DcNhKsFYD9oSg1eAWAjuFJJFJpOGwitYJpG8zYvrDY3jqMi5XXldRsPhfOr8CZ4UmEYkk47SL1/SIFZk2xG6eUTqBWeCMKaiU6EYBUBFxIxuXNh7yfXaMRhKIJBJQJgNXD3AmLSuDprmm8GDgtSv1OVAZc6A/F6OenLZ5qmd/Pp2VJPtdsFoM6hxWR83irtQXgaATr8vpsMo9X5tMfmebLCzBf7+V4NLsJUh30oJtZ25bWFmHnFD7DvUoH0Ou0I5GSHQMaSj3K4ybw5KE+PLy/G1tPDKqKvOV1xXCN2SCl0nA77Lh6XhWeONRHIyWX1Rbh+lW1SKVlnmEyLSGZTiOZkhBPpdE+GMbhnnFKPzHC/EofPA47hGH5dZFnIQpAQnlON66ut+TbKggCyvwulPldWFpbhCcO9eF3r7TTtbYy4MKAcv+Rx3EZOGWcTcxaDqDT6VT9d6Yfr6pI3V073DuuIojzsPWEdSuYqbw+ls/VaHE8RQovs8czKgCDHgfdRDY3y+RcM04D4WQ5nU6sY7JziVs8QTqdxoIqNedyqnzKQlwrveNRxkRbjQSyb+rrltfQIjnfyvCpXDMs/8vDZBJHOV1xAKgKuOmGm1ReXxI2pQA07jhr00CSaYny7SoCLlQXuSFJsvJUKwY53DMOh8OpelyCj17YrBKAEGU5mwFMxs3aNBbtgk6eT6nXSR9HsNlRrdzvbBew2ONQvWd6sKoEnu6aRopXs87kFUo3kv38WFQwXK8Jiwc5KyjUmq03mSBcUfbxSjVFWSH4meTxPAaqWb2idaqPNV3w1tT6oEcVA9dU5s/5MxwJx9Gq3IdEUb6+qQQP7u3GR3/3GtZ97Wn801/34fljA0imJSyuKcI/X70Qz//TpbjnYxsRS8v3p8/jokbwt2yaA7so4GD3ONoGJ3H7Jc341BXz8Zk3LcDtl8xDZZEbzxzpx3PHBtA3HqMd/ICSALSoOpBl3VUVcCMUSyAuyV8n90R9iQfxZBpBryOLP2iGHW3DuOmn23D7H3ahdSCMEq8DX7h2EYJeBy38yOPMVB2TK2ZtAXi20aLJ/h0OJ+B2iIZegAe69bkA+cDjzDhPe9LlYTyawC6lPW9k/wLo8/8AdbeoWRnxmU0IWCoGKRqBbHHE8b4JLK/LFt3MFn8ytrtjZYG4ZdMcakewj+l2ni2wU+qqoszmqFfAVxW5uFFWhANohL7xKGqK3Co7ifZBNQ8QAA50juFNmvgmo+fUUuWnApBljG0Q+dtBrxNpSVbH9ofUG36RJhaOFIBeZ+briZSEBQo1Qevub1b0AjJFoFD0AxYZE2jjz+H2S+cZfp9VqGsL5tkIvQLQpuNczDaBC20G7daxBns9xMHVFLtVh5dyA1GLHvYqa9zcch+eU2LVHt7fg0//eS+ePtKPeCqN+ZV+fObKBXj6s5fgsX+8CJ+4rAVN5T588YGDSCgj6FgyTbmE7980B//97lUQBeCPO87g248dRevABL780CFs+uYz+NrDh3FmeBLFHgduu6QZj9x5EQRkplKfvnIB3rdJnYyz9dSQSpRGUKvQqFY1BC13PY/1hvCR376Gd/78Few5MwqPw4Y7L2/Bi//vMoxGEqpDpDaje7Zh1o6AzzbWNZXh7/szyqm0JHOOXHYRUR3u13CosERPVs0710RiDwDbTg4ilZbQXOEzDfk26gASQ18/M3Y22+7sogCF/4pFNZnOaTwlIeCyI6Sc9raeGOAaJneMTKLYa9xxnQmw2cifuGwe/ulvB3R/tsTrwPyqANxK1+hwzzhiydSsaf+vqAsCkMfaeuLIyiI3DnL8ILtMVMCAnAYiigKaK3w4qPD12gbDuEz5/tLaYjx9pB8Hu8dw1ZIq/GVnp+r3ed5ppIDTCkAAoE3p+pFkiwVVgazECC1Rn3TR2ANKIpXGwio/Xjw+kJXz2VDqpQavepiIJdE7nn+xAYtoIkW7SmYF4JyybCU0C7YoTqRnfwHYH+JTMOyiCF6Z5XPaEFIsPoz8LvOBoMeB3kT2s3g9pIGU+p0qfjPrD2kF0UQKf90pJyCdHgrTNSWZltBc7sNbVtTguhW1WMiJg5MkCU8c6sX1ytI4OhnHZDyFYo8DLRV+LKgKYCKaxL/edwA/f7EVP2c8+1oq/fjQlibcuLqOHuQqi1zoG4+husiNq5ZUwWUT8CuFj0hgFwGf0w4woqjXTo8CMDaAJugajeAHTx3Hvbs7IUky3eQ9Gxpw5+XzUVnkxp4zI/jZC6foz9tEASVeJyZm8WHgfAGog0sWZEfLtA1OoMSn7wVY6PwK1qev0UI3ivD/LllQAZzQ/7loIqW7yfmcNspt0I7FjeCwiZCUN8TvssMmZgx651Z4sb9TLhCePz6I929uyvr9w93mI/eZwJ4OuYPqtot4y8o6wwLw8kVyV6u+xIMynxND4TiO9IQsLS6FQErTUbtMUQBrffJYVBW5uR2XUCwJt8MGmyjop4Eov9dS4VcVgAQ0EaRrHP9+3ZKs348l09CyqpbVF0OSpEwHkC0AleuSJH8srArgYNeo6ve1aR6kA8gStZNpiRpLZxWAFqkWJ/omCloAku6fz2kz3aifPWIcS8lyIiUJlKc5W6HXAdQT2NeVeHC0Vy5s2kyK9+miNuhBL4eDNvg6KABLvM7MgUiwxvuLJVN48fggHtnfjacO9yGsrCVkSSj2OHDPxzZiSU2R4d97YG+X3H1WCkByN66bU4JYMo3793Tht9vUBdyCKj/+/S1LcGFLuepvh6IJjCjvd5nfiZt/to12E1ksqS1CIG5HiBkukbWsdUDu4vOe8+hkHD95/hR+u62dHlKvW16Dz121gE7EookUPvfXfaqD9bo5QQz1xbPWtNmE2XvXzxD0LlGerUPb4KTp6buQYMenZhYwkiTh+WNMAWiAE30Tupv6/Co/3TSbLXQdCbQbChte38x4tR3rG6cdMxavts5ctJ4RSDu/NuiB22EzdKe/7WI5jkgQhFkxBn5Mk4BzsZKdadSdqCpy6W64veNRypXjgVyfrBeg2gpGLt5O9IfgdtiyeIBJTjfqPesacGZ4EuPRJJy2TNyZJEn0b5PFf0F1ANG4+m/MLecXgOFYhvuWliSq6NSOgC0LQQqcCNLJCEDMNup7tmfnUg9OqA+t7N05OkvoFnrgOQ4Y5dYuZr0AxyIFHc83lvKvj9fDCNjrtNFDm9EBIJFK47lj/fjcX/Zh3defxsfu2okH9nYjHE/R/ZNEPL55eQ2W1habXqM/VhS72slUz1gEm7/9DL5w/wEc75uA12nDSkU0drxvAv3jsay/fdcrp6k48lD3OC3+tH6iBzrVCl3WMeChfT24/kdbVdSjaCKFnz5/Chd/9zn84sVWxJNpbGouxQOf2IIfv2+Naj/8zuNHVYI7ANjeNkLXtEL6UU4H53wBOBkzJjnrceNsopB1wjzYOWpaeBXSfZ7dtMyex4n+CfSMReGyi9hkkklrNP5tLvfTgoGoN60sqFo15lrG2Z3lFJK/rY3j22fgrTRTkCSJBqUvqJZv9qs43DVAJiAvYEYdK5WUlrNZAN63W221UqqQ/43ivyoDLt0C0cwMul8pAFkhCLsoVhW5UO6X+XpHesdNDyYA8OYVmQSQRTUBKuoYCMUwGU9BFDLF0fwKf5bxPtsBZD0AtUa9kUQagiC/N+z3rFrBnOSYzecTGRNo847k/q7se+eZw+qsajb3dSwyu7tV3Rwhh1Es5yJGVJZM6yve84FyP/9+6J9FBttpTvEhQD6okuKfdwh/6cQA/uVv+7H+G0/jQ795Dffu7kQomkRVkQsf2tKEH7xzJSTIhSRR4pr5/wFyRN9JZV3Qxs8d7glhdDKBhlIPvnjdYrz6hSvwwCe24ENbmgAA//y3fXj8YKbDfWoghB88dVz1N2yCzCPc/aU3YQvzfCSor/VVSl4vKRQPdI1j07eewYvHB/Dn187g0v98Ht95/CjGo0ksqg7gNx9ajz9+bBOd6ETiKTx5qBcf+PUO/ObldtVzcNqAq5dW0W79bIkF1eKcHwE/edB4HFLk0X8LXHabyoB0R/swrl9Vp/vzgBzVdvul/PDp6YJsbl6njRsFxYLwBTc2l3FvbhZGApDqYjeV7m+aK99MbIFgA3/0rY2c2zyvjHq/sSRZMqWsKnbjzHBm0ewdO/sn6IFQjI4XVykF3e2XzsvysAMy7w0ByZPmmUjPFA73Zj5Xdv0Z1OFUCZA3Aj0xBrWC0THqJp0atgDsHosgmkjB7bDJlkB1xXj+2AAOdY3h+pW1eGBvN/dvATK3zyYKtABkx79EeVgb9NACsLIoe9hSHshs0KwH4MhkAmD27hP9E5hT6kX70CSO94ZQ3iL/rXxbwUwVJNfWSkE6wingXz41iHdtaKT/dttFem2PzPIOIC9Vx+/SH4Mv19gMdY5EChbNqJcGEk/L+bus2OhsYWiC00FVFgTSVAi47egPRTE4IY8se8ejuOVXOzI/Lwjwu23wu2Rl/EsnBvGwEkualiRqEP/9p47hf59V8420mc1s/OBkPAVtCX3x/HL85kMbVEXTv1+3BKFoEn/b1Yk7/7gH33vnCjywpxvPHO2HFp9500J88nJ5D/7UFfPx8qkh+r1kWoJLoxp+y4oaeJw2/HFHByKJFG79deZ11wU9+NxVC3DDqjrYRAGjk3E8c6QfTx7uxQvHB7giqhV1xfjzbZvhcdrw/e+/CJ3ldlbg7F+dBcbTR/sMv2800g16HYiMZcqbM8OTNNheD6+cGipIAXiAKSR4cVdaqPh/JjAqAFnDzKWKipMd67kdIsKcmyCmFM4JpZjYyBRI/ZoR42Q8iWW1xaoCkOf8P9Ngx3okYmp+pR8CskUwH7mwSfVv0gFsHQhjLJLImWCdD4ww+dQ+V+YQ0KGjjCz2OAzHgZ0jk4ZegGPRJOLJNOaU+SAKMi9IkmQ/wPnK6HZZrVwAHuwax41r6g2ff6MiZuBFwBEFcLnfhc6RCKqKXNzFmBWBEL5TuV/2yWMPKYe7x7CgKoD2oUkc6wvhghZ5pFVv2Qxan0OUD1jxACRIcDo+2pQTn9uOMUU1ySsYZxP6OJQEo/tpRYO6AOwajRSMT1xqUFgOTcThLT37W+zLJ4eyvkY66YTTVupz4hcvtCKZTtMCiUVKkjAWSWIskj1RY+87ntLWCClJojwsYsj80olBnOyfUIlHRFHAt29ajpFwHM8c7cen/rhX9XfWNgZxycJKfP+p49h5OpPWtXFuKeZX+bkHNCKqWjOnBEtqivBa+4hKFFPmc+LPt22EIIj4/SvtePJwH7a3DavGueQ5k/XOZRfx59s2GVoEzSac/auzwDAabwLAcmWj5qE26FYJPiZiKawwWUgO9RRmdPnI/gyfi/Cg9DAZT2KHEsdlVgBKkmT4HhE+mMsu0tPsTiZYPOh1IMzp1k3EknAjk6PLFtqJlAQRmY7mjrZhbJhbgkcPqlXX+Y5SyxXs+0K6WsS4mi2iBCBLyVzic2JOmRenhyZxoHOMZlbOJGKMqpYVM7QO8LtVFQGnYYJB10gEF5m8joGJGOqCHjSV+WiXrnUwnCkAiRVM1xj8LjuCHjtGOZsKALxpcZUiAJE/B54CmPj0LagKoG88u7BlY+A6lAOGbBcTo0kSAHCwaxzvWFePJw/3qXiA5X4XXdyNMBZJYGAihsqAdaFULqAcQJOCNKZDedEeukp9Tpq4k880kHxDkiSMc0a4pT4noMO20XYHC2kFY5wGErcUEVhoPMNpghAuM5nu1BS5cbwvhGrl+wG3A3e/fyMdj2ovf0kC/umv+9A1GsGqhiD2dozi6qVV+MAFTcwPZT+X54714/9eksUdX3jzIgy/egQx5fN9z/oG/GHHGUQTaXzwNzvwyuevoL83Hkngiw8cwLOcjl91kQt//IfNODUwge8/dRzbW4ep+4IgCPjslQvw8bt3q37HJgh0XXlkfw++9OAhAHJn3O+yYzAcx1A4jou+83zWy1hUHcBVS6tR4Xfi35XfI+vDv79lMTyzoOtrFa+fZzpF9I8bn24vXahfIC2qLsIuRSZOEE2muR0gguGJwoxTiJ8fYM7/e7V1CPFUGnVBD+ZVGHcLO0cihqkexAKGDQpn7WicHIsTm5A52SWVDqAoCnAxY6cyv5PGkT17pB9vWVmT9Xf6QzFUW4i7KxSIx5VdFFDLKDw/fOFcfOXvh+m/HTaR2/lZUR/E6aFJ7OscPSsFIIu1Ct8FyBQTWtQUewwNbK2kgfSNR1EX9KC5wk8LQNYLcGktIXSHEEumsKG5FE8eyl7UAeDDFzahcySCsUhCJQBh/ybpUC+sCqg6yARsWgPpAJKikSWgyzYu8rXG5h2LooBij8PSmPRk30TBCkCrHoB/0GQ/E0xoCsPqgBsHIW+APQUwS84XxiNJbvFdWeTWLQABwCFmMl4LYQZNUGbgnTdbhCCHObZOpT65SCZv7dwKH54/NkALQJ/Thi0t+mvW2GSCvq+jk/KacdOaem4EHIsv3C+7KBR7HPjYRc34wc6Mlc+meeVY3hDEP/5pL3rGovj2Y0fwj1fMx5cePIT79nTRzpsA+RBH7sl3rW+E0y5iYVUA5X4nBifi2H16FJsV/h8p1tj4S7tNwJiyV29vG4ZNFHD5wgpUFrmx9cQAyJJF3p8ynwO3XTIPVy+txpwyH8ajCVz9gxcBgB4Q55b78P5NTYavf7bh3BeBJI1FIJsYcYIWF7RkE1rbBsOGcTGFctU6PZRprc8xsYAhBdqlCytMR1JG499SrwOdyqY6hyk62d/h/X22KJQAmjfJ5sRWFWc25h1tw9zCQuvpNtMghUB1sVvVibx+Za3q5/Ta/US9tncWGEJfvqSa/n8/h1MFyHw6NsJK+8majYDlv61YwTA8QNYKpr7Eg6DXgWRawvHeCbxv/Zysv0EeuyLgpvy/hdUB1X1H/iZJOllQHUDbYHZnkx0VksKXXLKEY0TVgiQTuDekEjpZPYQUSgmcSKUpD85sBPzogR7u1xOaKIi6ksxr6ppi9vZMYIDDXwMyBr56KPZkCrO2Aiq0tckjLPIVBzdd8FTUVUVuDDPd/kXVRbSQswLCbW4o8aB9aBKCkM2D1uJg1xjalX3snevqIQiCqrhfO6cEN6yqwxrlsPqzF1qx7D+ewF93dSKVliAIsghv5xevpBw/APjLzg50jUYgigItWl9msoRtooA7NTGu7HSkvsSDgNuOp4704+7tZ3B6OAKnTcTaOUFq9D0UTuC329rpWvHVvx9Gz1gUHoeItDLF/tUH8h06WHic8wWgSWIZPG59Lsml87O7g8f7QigxaPsXCqPMGMSsA5gL/89o/NtSGaDjoSXK6C6WTKlGdpFEdoHtd6kLoh3KyFjVBWNu/I7RSa7H4KHuUdPnXyhIkkQ7Ri0a+5syvwsuxjbBrWP0TNRieztGZyQpgoVWfbyhKRPHNxzmd7Oqi92qroVWuTYeTVLitB6IaS/beWYLQEEQaC7wga4xbNRRDZKOc0YAkuHeptMSPRCRzW1hVQDtGv6Rjck+BjIFIFn8yWJOfPGGJ+Jw2ASE4ylV18jsfiM4USAlcO9YFGlJ5m2VGxQcgFpgxUJ79dUFM6+pdxYpVrXo18l5NfNBnVOWKZQL9bkA5iPg2YBJDje2ptiDk32Z+7Klwmc53x0AditCMLJuL60tQrHXmOf8c8Yk+VbF+5VwxO2igBKfE4lkijouAHKEnQDg8oWV2PGFK/CLW9ehyOPAr7e2A5DTS3rGonj/L7djIBTDhUoB+BJTAALAO9bVZ9nCEHSORDA6mUDAZccNq2rx4/euwe4vvQn3fnwL9n7pKtpJ7B6N4pL/fB5f/fsh/G2XbGIfUd7bm9bU5WSTNltwzheA04GPUxy+cnLQNBHhZF/+Fxw2JcFo8WsfDKN9aBJ2UaBEdiMYFYANpR5K8CUijt2akTgvS7Rcsyg+qCg92QJwkElNmYyluD5U29uyycszhaFwnL72Vcz4lODKpZX0/9M6xd3S2mLYRAEDoRh6dbpuhcJdr6hNVH0MLyqkwxOrKnKrLFBYkQRZO8cjCUMvRF4HkBUNARkx0cHuMbgdNm5RuVbJj+YZQPeMRxFLpmEXBToGml/lp0pZAq1VCCnoyUZHClyHEgtypDeE5nL5ebM8QPI1MxRKCczy/8w4sdpRrx5qmE7uwCzpVPGgx0+ca5J2Mp+xguGJSPIFbdQgi9kyAuatTnVBD04OZK7xymK3bsIVD3uUAyZZ+8xGv6OTccrxXlwToNxIsq85bSK++egRLP3yk/jTDnVC0Ccum4dff2g9KhR6xf27u9A1GkG534W/3X4B6oIetA2GccuvtlPx3YHOUZWn36HuccP80oqAE5curMCaxhI0lHqoPZzbYcMfP7YJX37rUoiCzJn8tWL5QixsfC4bvnPTCsPXP1txvgA0gbYLsr9rDI0mY5jHTKxncgXrXeS0iaowdy1ePCF3/9Y1lRhu1ARGI2DWo2m1oqx76YTaoDnMSZUo9qof99VWuZBb05jpQrFO+eS21Fp7HeoqrLeaEdgCYFF1tvL7K9cvo/+vt+l6nDYsVHhrM+0HyHJXtaa5UU7XFpB9+tjPhb32yaimazRqmI9LO4BMAdg3HlN5WGYSQeTibqXGtgMAPnhBEyRJ4kfAKR5iFQH5Pmgs9cLrtGeNtgPM9Z9OS7SrRwQRtABU3qDD3eNUeXisN1PMNZvwaAlOFmjUSApXKxYwVvvMbC70WA6jv5mGnik5e8DgYRGjII2nJEQM0m+mA0EQdPNeZ0sHkIe6Eo86Bs7tsGxWnE5L2KNw0omQaLOJ1+xfXuugf/+DjFCEWE5NJlLUbFn+e6WYp7hd/PSFVgwq10EylcaPn5dNpP/h4rloKvfh7o9uREXAhaO9IfzLffvRXO5DWgK2nZK7gK+1D+PWX21HUsqmtTSVeSAIwEAojr/v78F/PHQI1//oZSz/8hN4589ewbcePYLHD/bizSuq8cznLlH5BpNEpf98+0rYDWhhsxmvz2c9g9AaVQ6EYmipNFbhbm8bNvx+rnj8QKagbCrzGvL6XqDpH5W6P0MwHk1QZSQPbKeE+Km9dELdWuetGVphCFkkfC47vQGTml/sGJpEtSZK62yqE1nbDN5mU+530YU/ZnByXknHwDNrbM2qPv2aLoXe060MqGPgeOalnSOThpFnxBC2yO1AZSBTZKgSQZQR8JHeEBKpNG7hRAFubC6loxmHTVBZQhAFMOkcEnFIOKbe5FmT3v5QTFafC3LXQRQYDqDyObYNhqnFEnsAsGK+DMgbfiG6PlYFILtPG687rEK4hLEv4R3iZgu06mWCSpNYypWa+MVCCkECbj4FRGs2PptQW+yhfDwB0I035aF1cAKhaBIuu4je8ShsooD1c/W59Om0hF+9LE8kHDYBb14uC/5OD4XpCJhgXVMJXvx/l+GP/7AZ93xsE2yCHD35AcWb7+/7u3F6aBIlXgfet1HmDzeV+/D7j2xAsceBPWdGqYXY1pODeLV1CB/49Q6E4ylcMK9Mdd2U+1147p8uw77/uAq//8gGfObKBbhkQQWK3HZEE2nsaB/Gz19sxe1/2IUN33gGN//kFe5azzMqf73gfAFoAm2YfDwlYVGNcQF4JM/ctReZomuOgQdgLJnCNsX00gr/72iPcYdtQOnmkMiuoYkYDnabFzKhqHpDiSXTVA3sYwpq9jT1wol+2i2jv8fhrswUSJqCAH3RDbHFSUsS+nQW0FVK53SmO4BRZlNnfSNjSes5wDzOjJkSmN2w9YQgjaVeBFx2xJNpnOibwOWL1IcVklJAxr8LqgJwMYcKogAmB6GF1X5IkoSk5jBSz8R0kS4aUW2yr0EUQCPuyDXJZgJbiX8kb1UhuoBdFi1gvv7wEcPvv3Qqs46wfK14DqO/mQavA2jFGYocMggKWQDqpYHMFhEID2V+JxUW2W0CjvTqT4K0IDQgcg+tqC82nDa9cHyAHgyvWVaNgEKt+vSf9tKfcdhEPPu5S/C32y+gnNuqYjc+/ab5AIBDPeP4w6vt+JESIffRi5pVYQiLqovwuw9vgM9po8XsU4f78MHf7MBkPIWL5pfj1x9cr+oArm4MQhAEFLkduGh+Bf7xyvn43Yc3YO+XrsLTn70E3337CrxnQyPtJg/rdMq//sgRXPm9F3CmgClghcIbugB0WFhJeJt/FSdxgMXIpHUyrRUcZW7OOQaE9J3tI4gkUqgIuLDYpEgFzD0SScg52QC3nhw0olFQjHBuFDKaXs6Q+Ys9mU39mSP9WVw7CcYFSyFBrBMqAi7dnEw3M7P+2YunuD9DOhEHusZmNA+S3dJZfo5ezJsA+bCj4gDqdADrDEbAfYygQJUJzBSAoihgSW2GB+iwiapOO+nI8ca/QKaYJGO9BVUBrk3LPCYHmPDoipTNRyvsWEZFTvI7d3Jggh5arKiAyUdbCCUwKV6MFMCSJGGfSeoM66HGqqO13fjZBF4BqBffycKh+ZlCegHqHRAGOL6UswVBr5MagLvtNhrZaMV1dU+HPP4l+6dZ/NtvX87wkd+1Tk6jSafTqpSkMp+TK6L41OXz6b36Hw8dxqmBMIrcdty6Ods9YFVDEP/3gXWU0tEfiiGaSOOSBRX4v1vXZSVirdJ0iQlEUUBLpR/vXNeAb920HI/940X0kKrH+Tw5MIGLv/s81n3tSXzint341dY27Gas22YrzukCUM8UlcCKW/cKDj/JzBMs3+fpPkYJZ2QBw6p/rSQS8PyhCGqKXLSbQzpz2vGvHog1B4uH9slCkCsYOxI2Iuhob4g7Wi/kwm2EDsWCZp5FZdcTh/i8z/mVAXidNkzEkroGzIXGm5j8Yr2uhN9tR1qSVEpAbVA7IBcjRh3A4ckEHeuoMoEH1adjLQ9wYVXmZ8lCzYuAAzLFJOlQL6wOUO4hi/rSTOeTdABJJ7FBM9ZdonSMOkcm4XHYEE+m6YjMYRN1eV6AuiNViA6gFRPoIz0hpEzquMNM996loWlEZ0HyDg/cGDgD5wYWbgejAC9gd0bvQDQUTsy4+l8LvQN00Oug3GWf204tt6zsG6QDSPYHIwHI6aEwXlD2jYqAiypqf/L8KUvNBAC468MbIAigB+gPXziXdhG1uGBeOe5gkriCHgd+fssabhzqap0CUIsH9nbh2aP9sIsZ0Uupz4mnP3MR/vPtKzC/MrPODIYTeGR/D7728GHc9JNtVPynJxQ82zinC8Bnj/ENZglKTGTrAJ9Lt7NtxNIpNF+YjGc2ZSNn+eeV12tl/AvAsO3fVO6nCt81TSWQJClLAKKHSQ6naFe7fBpijbdZ1dlgKMYVF+jFlhUSw+E45UXxDgA8dI9GuWR6myjQAmam/AC1th5sAaXXASzxOrJGHNo8Z8CaGTTpIqqUwJoCkDwnUuTdesFc+j2vwwZJkmTlHtQdwGQqTTerSEJWAjeX+1WHJALWvJwUUZIik9Aq6UnE4+GeEBZUZSuBfS79wyLbQMu35Ug6LdHs1HqDe//Pr/ENoFl0aWgKbOFqFAF4NsHjABZbLABZsdyBLusjzlxRpjMCTiOThHS20K3D8XbYROpyUOJ1UB6bWf0XiiZwXLnGRxWDdqLY5+EPr56m//+OtfWUd/t/L7XKj2fhNTSV+3AFQxMxOgg9e7QPP30+M40ZjSTww2dO0n+zhdgKCwVg71iUpoQsryvGhMIz/vF7V6OlqgjvWNeApz57KX7/kQ2qiZDHYVO9ttlKszinC8AnDhnnABuNUwlWN2QXAFtPDSBoku16LAdOhRnYDWaOjv1B92gEx/smIAqgXkhGSKbSqsQDLcr9Tqoo3NhUhhP9E+gbj6mUunbO3SuAf7GTkxDbUWPVs4m0xC0s9p8FE+UTzMa/uMY4+5kFsQfQgowazEZ0+cJvNc+DHWEP6iSTl/tdqu6gXRS4m8HoZALFHmN1OSnG2M+6LasAJAXXOFJpCTeurqNjYEEAuseiGA7HYRfVApDOkQiSaYmOeeaW++C0i+geyTYNL+MUgGTT0x6kSAF4oi9EnzfLAyw3UN6zyLcVDBGv2EQBVQH+c0inJdy7u8v0b41rIvfYriaPtnG2EU+mMcaNgbNWADaVZa6/U4U0g57FaSDPHc9ugpDCP6kY9Fcx4i/eoY/Fvo4xSFKmebK6McjtrgEyReNPr3XQf9+8Vs7+bhucoJnCer/LQpIyhyAA+NKDB2nWPIsnD/Xitt/vQjyVxqbmjCjlJ8+fokUhMUS3i6KpS4YkSfiXe/cjFE1iUXUAezvlw+oF88qwWdP1vGh+BV77tyuxVKFeRRIplSLfZeF1ng2c0wXgIRPBwlqDFBACm82WdUppH+QbF7N4TMeRP1fsZXgEoqB/+nlRGf+ubAhaMqpuGwwbnkrY2J3GUi/9+0sZcjWPQumwCVxlcCIlIZpIQRAyhYXWpDvAuSF3mSgbCwGWx2VmNwFkxBIP7uVvwsSbat8MKYFZE1StkKN9KLtQAoCaYrUHoI/zWdjoxmE8ziB2LFVFLir6GZlMqHy55pb74XXaEE2k6Wi8iOnsHOjMCEDYTYIogINK0sMCpTjUjpgBtYCLjIBJQaHlANYFPSj2yAklJUqBoVYCmwtBALlgG8tjN414G1YXuSk3UouXTgxY8v/T3u8e5n2djR1APRWtmQKYYG4FO5orXCFW6p29ZtBk3WZBriNyG88p89IDAI/2wYLYvxD6lNH496F9XZRSsqohSA9W//SXffRniix0c5871o9D3SG4lY5DJJHG7XfvUv3M4wd7cMfdu5FISbhuRQ1+88H1qgLvO48fxU+fP0mnWpIk4UsPHsR/PXEMv3jxFP604wwePdCDrScGsb9zFO2DYfxqaxteOD4Ap11ELJmCJMn728/fv5b7PEPRpMpvlcXZS7Q3xjmdBcwbC7G4fLG1UanDJiDOEGzGIwnUz/NQpSgP+bKCeZTxFKwp9ujG0OWS/gEY+/8BmQ0h4LZDFAWqRG4q99GTkN1uQ1wz7nU7RMRTfN7Jc0f7cO3yWgR1slX3doxm5SwfL4CpthkOMJ+rFQ84j0O+jU4PTSIaT8KtCQNfqXSRj/SMI5pIWTr1TgcdTISe1mT5tA4Xqk4TA8d2uElXgHwu/eMxVAac6A/xNzcythMEmUy9T7le2obCWOUNApBH40tqirDz9AgOdI1hvkYBfpCTAAJkRskOZTMg/FQev5IoflkPQEJ8b9AUdIIgYFldEV4+mTEfP8Zce/Mr/XjumDEFwi4KSKYlnBwIWTpcWgHl/xkUoP/zzAnu17WbubZsD3jsGFEK4uECFkhThZ4HoJkRP8ESpnsfT0lIptK6RfR0YJgGcpaVwLz10+sQMcHwtBdU+fG3XYw5ugEdlAgbyP6wWUcAIkkSfrctM/4l3b90Oo3dZ0YBEEsz4+cvSRId4d56wVyMhOP4665OPHd0AC+dGMBF8yvwyP4e3PmnPUilJdywqhbfe8dK2G0iNjWX4ekjfdg4txTb24bxnceP4Z3uNJxKVv0fXzlt/OAKUqk02pSUoaqAG//4570octtR5HGgyO1AkceOtsEw7tvTRZ0rREEtMp2tHNtzugM4qWN4S7DE4njPr6nqUxLQZOJEf7QnP90eErkD6AtAEqk0tioFWr4KQOLBV1PsQTSRwnbFzJlVQfEuHr9T/0zx4F65K7qR8YxyM3PkJw/3wudU/9XBiZnvTBBhQonXQa1ejEBGlxKAu7dnc7Hqgh6U+51IpiXT9z0fYE2X52uENT2j/E21qcyn6riwIfekkCAdg86RCOoMvPFYQ+Z5KisYdZFGeIAHOfwsMwUw6WYRD0CezQfpALAegBJkK6JSn5Oa0BKQ7jbp4LUPhunCrS1QeSD8onyOgUkBWK/T+Z+IJWgqgxZmIjd2rD3TSTVWoFcAagU8etCqPAuVCFJmNAI+y4U17/GLPU5Vx3xRdRHlY+vFpQFyMUautcl4Cm6HqKuk3X1mhK51DpuAt66Qvf9+/lIrPYh87W1LTZ//1pOD2NsxCpddxEcvmovv3LycHk7vuHs37tvdQYu/m1bX4fvvXEWL/IuU5KkTnCLY57TjU5e34AOb5+DG1XW4YlEl1jeVYGFVANVFLtV0ixVXdY5G8OzRfjywtxt3vXIaP3ruJL756FH8cUeHyrYsLQEx5hdn6wj4nO4AmvEubTZrH0plkSuLIG82hhiN5KfiZzs2egXg3o5RhGJJlHgdWKGMG81wxMQDkCXy72wfQSyZRlWRS2XOnObkDrgNNh0ignjLylo8rvAz7aIIcuR8pXUINUGvagSr3aRnAmRMOtfAc5GFIACNpR6cGY7gr7s68ZGLmjXfF7CyPohnjvZjf8eoKhGlEGAXrEsXqkc0AxP8jb62xKPqWlcXuwHlR7WG0J0jk6gt9mAPRrl/S98LUD1+pgUgh6rBi4CT/4Z8P5AOBPHo6tdYbsgcRoE+XwAo8TkxNBFHQ6kX4XgKI+E4vEImIYrwAFsHwwh6HRidTODUwASW1hZbOiwWwgrGzAT6+08e11VTep02GE0gq5k1rPssqe2NoGcCPddiMsuCKjV9o2skYilNJVfM5g4gjxlQHnCqOJFlfiel/NhtAvTaJm2DYYxOJmine31Tqe5E6i6mu/amJVUIKmPynz8viz9cdhEXza/EaybP/3+V7t97NjSiUgkj+Pkta/GuX7yKUDSJz/5lPwBZYPLtm1eo1iriRjA8mYBNkN0CoPRTAm47PnvVQu5j/vblNnz574fhcdiwdk4QW5WpwDdvXIYSrxPj0QTGI0kc7R3HE4d6qTAEkPO6gx4HJuMpFS1jto6Az+kOYL7AHwMaFyb5En2PMZ6CjaX8hY+kf1w0v4Kb3sDDYQN+ZGOplxLGVzYEqfr3ovkVaO3PFKQJToXtMhixkKKS7VIm0pm/0Tkc4foX8mxlCoXRyTi9cbVmskZ4y4paAPLIhcetXEmFIDObCHLtshrVv/X4aVVFbhq3BKi7LNkFYMQwDo617tDzAgQYIUj3ONIMrzAtSRgKx2EThSwRDkkUSaYluB0iFXNozcfdzMZEumiEY9pY6sXJ/gl6j5JDBikAj/SEML9SrQQ2KzrYzkleC0CDEXA6LeEvOzuyvg7IAg8eoT/F0DNqmb9ZSKPkqUI3Bs6iNZMoiqoNTpsVnS+UGHEAZ2EaSHWRW3WNsjF5dlF//SajW9JZ1xv/DoRieGR/N/33zWvk8W/7UBijCuXg+pW1ps/z1dYh7GgfhtMm4vZL5tGvb2wuw7LazLpw1ZJKfIcp/oYmYvjE3bvx9UcyxuhfuWEZHvrkhVyeOYu2wTC+/fhRAMBHLmyixd+bl1XjvRvn4NrlNbhpTT3GIgnct7tLVfxdsagSu//9Tdjxb1fi4FeuxslvXIuqgDW6wtnC+QLQAtZx+Dz7Ogo/ygPUHTAtcZ0gV/5ffyiKQYOTaW3QjZTSVtjcXEb//kXzy9HPLGi8oA4jgUAyLWEillB5OCWY+IaJWBKrGrK7YyynrdBgfdyW1FqjCADARy6UbUzSEvDAnmwxCC0AC6xqjsTUBV6TposZ1uGiVAZcqo4L+3taQ2gzL0C9DmCrZgTcUuGHyy5iIpZURcURpd78Sr+KLxlLplS+kPMrA7CJAiRJyroW2fg70gEk5sANSgFIQAr2ueV+eBw2RBIpGndHlPJmVAD2uj+ZR94qNYEOZt/7jxzoVm1ALGp0CnR23F7DdADN+NJnA3rdajMjfhZ+xr7nsAFnezqwiYKueOJsi0B4qC/xqlT5bCScESePCECILZmeAORPO87Q6Vu534mLlX3pnxnxx1euX2L6PP/3WZnb+o519Soz9j/tOIODjIetnHsu33+PHejBVT94EY8c6IFd4RkDsh+h3SZyxW0EqbSEz/1lL6KJNLa0lOGBvXIR63bY8N/vWgVA5hq//afb8KPnTqqaPLdd3Ixf3LpOJTyx20RTjuPZxvkC0AK0UVWAfDM4bcaf7oFp2n6MRdSLB28EPDgRo3ypixaY278A5uNfdtMN+uw42huCIMgdQLPc0AmT7z+h5BqTt47dt9MSv9t6mqPwLBRyVQATlPlddGO6Z0c2D3Cl4ifYOhjOq0pUiz/v7FT9W2vsmuBU7QLkLgbbuVN1AAVeB9AgD5jxm2ss9dLPum0wrDLGtdtELKohiSCZBZ2MbrT8v47hSaQVJR6Q4f/xrELK/awCWC6iSJexUVsAKo8ndxzlv0lGW2wmtMPkfifoHosilIeutSRJtHjldQC/9+RxAHw7pvVNfBHK44dYUVlmUy2kSnaq6OcUpSLkzp5VVDPX6S6lg1UIeJ3853S2R8A81JV40Kvco3ZRwCklBURvnEtAOoDxlAS/y67qwhEkU2kVD/qGVXVw2ESk02nsUgrIOWVeeHXUsgS7To/g5ZNDsIsCPn5ppvv3h1dP41/vOwAA1BtwKBzHv957AHf+cQ8+fvduDIXjWFQdwAOf2ILbLpHpOFsZcZcefvlSK3afGYXfZcfqxiBdN77+tqVw2EXcs/0MrvvhVuzrHKNrosMm4Ls3r8Dn37zY8vRtNuENWwDm8llpuyiAPOYqNvECfFwnHcIqHtVYyWjNawHQ8ezS2iLKkTCDWQQcGQl4HDa81ibftMtqi1Hqc9J4LD1MmBifklNVuQ5xmkdcnykDZUBtHZRLAQgAVyspJwc5sW9BrxNNyue3v2t0ek/SAI8dylwzWkJ3MpXmEhc8DhtEUVBtVpVMl0U71R8Oxw2tLwbDcXqdOGwiza8Ox1JZnWcSDXiI6c7QArBey/+bpM8XkDOAAX73qlGVAiIv5OS61haAiVSaFmxECEJ8xo4zgg6PBSI38dYjm+p0MByOU99C7cj9tfbhjKUPp82gF8+1tyMjKivxZT7j0Fk2LOZhgDM+dTly27LYg8yZAk4SinXuh/7xmZteWEVd0EMLfqddxGml++414G+HY0mVt+3GuaVcRfVTh/tUgiIy/v3l1jbKkf36DebiD9L9u3lNPeqVz/B329rxxQcOApAnLr/8wDpsUa7zv+zqxEP7umETBXzq8hY89MkLsayuGFsUT9wjPeO6lAJApnqQA9X/u3ohfv6CzFVcUOXHZQsr8bG7duEL9x9AJJGC0yYgJUko8Trwh49sxDvXN5i+ntmKN2wBaPU0T6AtGCOJNCpMCq7XpmkF8+LxjJ9b0OvgeiYR/p/V8S9gXgCOKoKXyoCLxr8RRZVZbGhUEz2k7R6RYu7yRZl4MvYnTnDMqWfKQBnIjMj8LhslLlvFRy+Sx8DJtISnDmcX/zMxBmYLm6Am6UYvwtDvtkOSJIwyHefKAFsACtn/b3L7sKOv+WwiyJCGB1irTgQBMiPgbAGI/NrINUg6gLwYuJZKtgCUN2Hy+htKvTilsY3ZpajtCQ+QjLG7RiO0ODQ78AGZYpmnPMwVZPxbGXBlRbf999PH6f/zaBcLdFTLpxkhDnt9zEabCt6GbTTC44FVofM6xflCjY4ocOAsdgD1YujK/S6EFI63z2mjJstG1/e+zlGkpUwOsx7/jxV/LK4pojSanzwnGzG77CIu4qRrsdjfOYrnjw3AJgq44zK5+/errW34j4fkRI7bLm7GF69bjPFIUiXAsYsC7r/jAnzuqoW0m1nud9Ex8LZT/CjTRCqNz/1lH+KpNC5bWIEnD/chkZIgCPKafvV/v4Snj/TBLgqwi7Il3PxKPx78xIXY2Gycgzzbcc4WgCkdLzoCK/YeLHjRb2Z+VMemaQXDJhHwUkvSaYn68+VSABplAAOgiuc5ZR6mADT/+wKApCaQVBvKHlIEFsQXClAX1y9wjEtb89BNsQrCjdET3BihscxHHfJZDywCYgi9t4CG0Ox4eaFGBakXAxf0OhCOp2jhJUC9GYiMeTf5rMYjcTh5s0cF7DhZrQTmR8IdZArAtCRRn0AWpANIbG5IQkjPWHYBSLoGrAdgRClyKgMu2vUgIApo0gE81heiyRukC2hm/g5k4g3zkQmsJwA50jNO/Qr17Kj0FOzDzPXBFoA8QdfZhCRJXBVwkYUinMUSRlSWSEkFy+blTWcAYDyaypoGzBT0zMFLvE56LxR7HBhQ/DyN0m72KONfctjgFYDH+0J4pTUzar15TR0AoGM4N/EH8f27YWUt5pT58IsXT+FrDx8GANxx6Tz867WL8NyxfrzpBy/g7/t76Fk0mZbwJGfqdqHSvNDLsv/p86dwoGsMxR4H3rmuAVsVI/35lX78v78dwOBEDGU+2cYrmZZwyYIK3HvHBbqf+esJ52wB+NJJY9PWCgPvJh54C4+2w6LFWGx6iyrb2WjkLPQHu8cwHI7D77JjjUEeIwsJxgWVTchYbFQXezA4EYPXaTPMeyQQxWz1s5MzJmgfnMCaxiD3bxzuCWVdlDMVUzUeTdAuwdIcBCAsSNbx7jMjKmUrkOkA7u0YLdhGxO7jVyyuUn1Pz5NMjoHLfM/rsmVxB8uVcSEp8LtHo6guNhCCjPOFINoCcEFVAA6bgPFoUrVRagUgQEZFLEG2cSA2JjwTaNKdZz0AAVlA0DMWRVoCBKaNuUMpABdU+2EXBYxOJujomiiBm0wWfJGxlMmHEpiaQGv4lj9/IZN1yuPM+pw23U5ZjLlASJoKIFsHFeqanArGo0mumt6IesCDdl3UOwRNFzUG98LoWYrZ04u/C/oclGZREXDR9dXogEMEIKm0hKDXgcXV2evj75nun00UcMMquQD83F8z4o+v3mAs/jjcPY6nj/RBEIA7LmvBT56XffYA4M7LW3Dbxc34f3/bjw//dif6QzE0V/hw3x0XUI71T54/lWVpRKJRXz6ZXQAe7BrDDxUj9a9cvwRffFAeMYtC5uDXXO6jE40Pb5mLX31gnaUEk9cDztkC8JH9xvy7eTnyu3ik90IHPE8yggpeB5CMf7e0lKnyXo2QTElU4ctDY5mP6QTJG+Tm5jI47aLpBuHkkLN5o/b/fvq4isjNNg0HJ2Io1hTWyfTMbE6sgW8uCmAWH71QJh3HkumskcPS2iLYRQGDEzFu1yrfeMvyatW/9Ta/qiK3ipvHW9xqS+TNgXwKnSMRNBqkU7DdGyMrGKddpJ28BHMhLOVY8LDj44VVAVqknurPPtAQc14y/iWHNZb/Z2euzf2do4jEU3DZbdT0uVhREpNO/GKTa4LlRJ3oz98IuJ7hsXUMT+KhfTKPVhSA4Yls+5YaA4EOexe5NXw6M4HXTEKPr1Whk4esB61pdKHsbgy9AM+SEpjXDQNkOyRy1qov9dJOYUMp/7qRJIl2AAF5P9A6A4SiCdy3OyNAu3RBBf2sdrYr4o9SLzxO48LpR8/Jxdh1y2vw6IEefPfxYwCAz1y5AGubSnHN/7yEv+7qhCAA/3BxMx698yKsbizBbz60HnZRjiG95dfbVX9zw1zZr7BnLKqiS8SSKfzTX/chmZZw7bJqHOkZpzzotCRHSc6r8KF1MAy7KOAbNy7Dl966pCBpMmcL584r0cBMgbs5x9n9Yg6n5syI+WjSbBRtBLaBxLOAydi/GHMqWCTTxkVrCVN8kQ2X8P/MTs88FRnvZiGRWrziMJZMcxWPRgTefOEks2nnKgAhWFJbRPNvf7OtXfU9t8NGi51C8ADTms+2slh9zfTrpD3UlXhUHUDeZqbtQnWORLjWJAR6XoC80SjhASYYgdFyTQRcJJ5SFc0kAxgAOjn+buQ1kC4a6YixFjBEJGMTBCRSEu1ykO4vuf1IB5BXlLJgBVKdIxFqlzFV8GLgfvlSK10XLp5fgf2d2YWmVZ88QRBUG8DZ6lTxwON1Avr2NnoQBEGlkm7No0cjC6M0EL1M40JjRxtf+co2LuaX+2mChR5t4MzwJIbCcdov541/79vdhXA8RTnCb1coPr9irtevv22Z4fM90RfCY0r0abHHge8/JfNc77yiBb3jEXzg1zvQMxbF3HIf/nrbZnzhzYvplKDU58IXr1sMQBZg/d+LrfTvuh02rG8qyXrt//P0CRztDaHM58T7NjTg5y+20e9tbi6Fwybi1EAYxR4H7vrwBrxv4xzD5/96xDlbAHbrRF4RXMmxdjECj+zZOWx+mtwzResBNgIOyOaYjE0maC7jxRbtXwB1l4UH0mizi5nnfpHCL2RVdDz2l4PDCRMAlGjG52ORJIbDcV3i9HJOp6VjpPBquqMM51IboWYVgiDgghb5Wnnl1FBW55KOgQsgbHn2aL/h908P8d/DOaVeVQewktNlqS7SFoCThpsx2wH0ueyUcnF6eDJrNL5U4QGyhxOtApgcRkjRtpA5kA1yDgdlysiadACJwW1jqRcnByZUXyMHl1cpD1C+/sYVOgDpAM4zMYMmL8tlFyFJ0+eu0g6gUnwPTsTwR8ZiaF1TCVfVvaLeeveaTe4ZLaA9Ua6YbgwcC5bPupUzBswHZmMaSBvnfrcJ6nV8QY2fToT0hEPaPUyrMJckCXe90g5AHhEXexy4fLG8v/7oOZnPJ4s/jHnkP3ruJCRJHrkSK5l3r2/Avbu68McdHRAEeQT76J0XYR3H5uiDW+ZSwdl3Hj+KYabwJmpgQoFIpNL4mUKleNvqOtz6m0wmyTvX1WNf5xh6x6NoLvfhgU9swQUt1vfY1xPO2QIwYpIDXJsjyZ8nghiLJE3VxE8eMd6U9fDIgW7Vv7UegFtPDiItyZ2q+hwWRTMbFzJ29rsdiKfSqAt60KycDNkCgmdw6dDx1lnESfd44lAvrltRw/lpoIxTgLQPFubkzoIoUV12MSezWS0+eIGsBp6Mp7IsbFYpQpBCdADZVAjeddmhc2BpLverOoA8uoPWhsTMDHpA08EhHbt4Mo0+zfeI3x97Ol9SoykAldExSbdgNyutX6aAjJ0Q6aKR4rKhJHsETOgTpGNChClnhiMQBHmEJxPBrV0TRDA23TGw1gPwd9vaEVcOcB6HjcuvBTJiIytgbZdmimtrBXoFoFkGOw/sSPyAiQBuqpiNaSA81bPLYVMfTJizmF4BSBoNEuQR/DxNh3nbqSGcGgjT7t/1K2vhstvQPTJJlfdv0VnrCVJpCQ8pFmEkp3htYxB/eq0DXaMRNJZ68aePbcKX3rrEMOP6rg9vgCjIgpAPMEXdRS3y/k3WmLFIAmkJaCjx4FeMRc3qxiD+uqsTk/EULmwpx/13bLEcCfp6xDlbAPJSKqaDUk6LP5mWTMmgu9unZgXDnrqcdjErUuaF43JhmYv6FzDvABK1FtnELl5QTrlW3Sx/hvNn2MYOW35oDX0B4P49nXjfJn5LvYNzct1dQBNXAhJz11DqzRJB5ALCmQSAX29tU32PdAAPdGZ7BU4XbMoDb0PSFl4EzRVe1ZiKZzherVG8D07EqTCEhz7NuJntqLZpOmOLqpVED+XfdlHIWuTJpkBMm0nOqyRJ0FLXWNsaUgCGlcSMuhIPFY2QbiL5rPacGUUsmcLimiIIAtA7HqWj7+O9IYiiYMk/lHyuLKc0V4xHE9Sbry7owUQsid8xlIKrllbpThdaNBu5NhKuYzhTmBYz69fZGlXyoBsDV5U7NaOeoc/0FogDaDQCLpTwxAw8irrfZVcJlEjnX4C+xY6W/6ddG0n3j4A4PHyGSf745o3G49+JWFK1pQQ9Dmrc/YHNc/D4py+yZLlSE/TgzivmA5AP9ORQvLS2CCVeByTlUZJpWRjWwQhGXHYRe86MQpKAWzbNwW8+tD6Lj36u4ZwtAAsBntN3ic/4AjneN7UTJ9umbyjxqEi3kiRR/h9RnVqFZJJSTLopxICW7Xy2MWpLXn3NegCyi8QCjmJsR9uIyliXfWePcbwA92hG4vnGRCxJ7W94CrdcIIoCVU1rbW1aKv3wOm0Ix1NZXnTTxSCz0SzgbJTDOht80OtUmbfyTrys5REpnIwCGbTmzKzoqk1jweJ22FRegTxBEyseKfe7UKZYVpDMau3fIyBdNMJvc9pExJJpOO0ivZ/tooByvxOxZBr7O8fgd9lpp4mMw48pPEArYisippiOEphYwJR4HfC57Pjj9jMYjyZpqsoNK2vxKofjZReFrBG+tgD8+/6MWXiFP7N+dY0UpjiaCvQKwDoT6y0e2GurUEIXoxHw4CyKgyv1OVXrDjnU66WAROIplW+sdvzbNRrBU4f7AMgHn3kVPqrIfU1pfswp9cLl4BeXxFUgovGhHI0kUF/iwT0f24iv3LAsJ9u2T1+5APVK1/yLDxxEKJqAKApZY9y0BMrXBuTxsE0U8NUbluJrb1tmWVj5esa5/wrzCF4SgJF7OgCMT9EKZpxp38/RjD2O9YXQNx6D2yHqRj5NBS67SAu/sUgCoqC+4U+aFCyxRKa4ZGtlXjECAE8c6qP/z5alPRyxQiFd/IGpZQAbCZNv3Sx3N8ejSRxjFlCbKNCOaL4TTtgRqtYCBuD7gtlFAYIg0GgogJ87y9pckAIwZqCCHwjFVB1OVpig7QACatNnbgHIKoCrM3+LJxYocsv3JOsBSExsSTemWVPkbpgr30fEDoZcA6SYJEIQMyNiNn1lOl6ArAdgLJnCL7fKpPaUJG/iTWU+lbE3ecfKfM6sDo1dQwd4+USmcKxhPuvO2VQAcg4rucbAEbCCIqOs8unAZbfp5r6erREwD1VFLnQphyK2A+bTKbAOdI2p3jOtAOSe7aeRlmRbJkDu/gmCgF9tzYg/vqYj/nj6cJ9uBOGGuaX4xo3LTQ/jkiRhMp5E92gEh7vHse3UIB470IN3rpPTOeLJNK743vO4/fe7cJhJeQKAq5dWqZw2Am47fvPB9bh1c5PhY55LyM0N+Q2OUp8jaxONxgtjBRNnRrVaBTCxf9ncXJbllTYd1BS7M/FSAFbUB1VpGN0m1iVxhl9oE0VAubf0FLWPHOiGyy4gllQvyrw4uXCB3mcCNrnBigL4X/62D1IoCp/Oon/FoirYRAGptITfbGvHt29eQb+3qiGI7W3D2NcxSheqfOP6FdmGq9pTNpCxAmHHf5Uc/mNFwAVRkAspQhofCMUQcNu5MWISZN9BEk84j0nm4HU+l9UW4bBs9M/lL7L+gSxXiRcDV+7P9gBMS0B9iQetCpd0XqUfYFwyNjSV4tEDvXi1dQifuKwFS2uL8Mj+HpqQQbrSJV6H4UjPYRORTMu/c3oojGgiNaV7lBSudUEPHtjTRQ980UQab1lRgz2aw4NH6Srz3AK0kYAsB4wt7LsLNB6dCng5wGZZtXpY3aA+JIdjyZwTRazAZROpETiL2ZQHXBv0YHurfMhx2kT6mRd7+e8H4f8B8rXIXl+xZAp/2iGPWEPRJAQBuHG17P33o2cz4o+LOTSlUDSBLz5wEBfrPM8dbcPY0bYDgNxkKfY44HHY6OEwnkwhFEtiPJJU7Ts89IfiNJZ1vdJALvY48GLnKG08NJR48JsPbZiy+8PrFW/IDmCOKXAUDZzFdTRifnPnagUzolkwsgpAav+S2/jXDNqN6uL56pb5uEmUEnu4djJvstdpRwPH2uWVU0Oo5RiopiRAG/kpQW0Tkm+wfC0ri8C9u7sMv++0i9TehIxICGgkXAEj7rRCmnRa0uEEySNAtpvEM9t12EQ6diU80s6RiKFYht3EK/wueJUPlWsFw3QAtdZBoWhCpVJeqCoAs4uWxjKP8vzkwwwxcWc9ALVWKYRftOv0CJKpNP3sSIF5vG8CkiSZpv8QsYnLLiItZRtfWwV57rVBD80lJSLpG1bV4bV29fiXbIILOYIrbRwjK/ZgP7+ZsFqyCl4H0GzaoocKzTXaMVyYZCG/m19E9XCu0bOFhhIvFYd4nDb6PuulgOxhCsDN89T8v0cP9GAoHIffJX8uF7aUo6bYg76xKF1PrlvOF3/81xPHVLQTI0wqFlCtg2Ec6wvhWF8IbUOTGJyI0+teFIAitx1zSr1Y2xjElYsrcdPqOjq1c9gEfO+dKxBU1oJYIo3eMfm1N5V58dAnL3zDFX/AG7QAnOpJcjnHB8ysKAJkvlsueNhAARyOJSm34pKFuVnZmIEohMktrj25GRlfa8cf2vd4YXX2xpSWsuPKCHjh6oXsUOzvGgUgb5a8YpXFcDiuMRTlvy/v2Sh394bCcZWKmRSAR3tCectg1Y43tNDLQQ16HUim0nQU4rILWSavBNlegJOoN/ACZMezgiBgrlJ0dY9Fs9ToqxqCdLHWPnr7YGZkBag9ALXZwkCG80VGmqRwUBWAmsV+YVUAxR4HJuMpHOwep1YwXaMR2EV5fN49FkWzicceKY79SodpqjxA0gGciCbROhiGx2FDPJVGQ6kHaxqD2HpSXQCSx13TmJ3Yo/082Y57OXNQmC0q4Hgyze2yToeQz9aOr7ROL6NdD3pF1KDFQief0HN7qCvx0Hu9yGOnhRovBUSSJJX4TuudS3J/bcpY/uY1svjjH/+8h/7MNznj391nRvA7JjWEhdshorrIjUXVAWycW4orFlXgTYurcNnCCmxqLsWSmiJUKtMIFmlJptucHp7Ewe5xdI1GkUhLuHG1PAlJpCQ8sr+XNjkIX93vsuHJz1yCEgMO57mMc3IEbNZxC7imtpBc0FKOnzEGkwAQTZpzSp4+2ofNOfgIvaxZ3NkC8JVTQ0ikJDSWek2jqVhYCdIgSkkJsls8KVQIjATENgFg3wptF2d+VQBPcyxxhnW8x4rcdlXXB5A7R1o+ZL5ACoPaoNvU6f2rfz+o+ncoyn8N1y2vwefvPQAJwB9ePYMvvkWOQaotdqPc78LgRAyHusctxeyZ4XeMEo8X0Tuss7mX+Zyq7/kNRmM1xW7szTjNoHMkglUNQYCT3wxkj/EWVwdwqHscqbSE7tGoytvSbhNR7HEgxOH0kbEtqblZUv8xjtKW5Dh3Uq6T/IbUl3hw/x65c9tS6ccJ5ndEUcD6plI8faQPO9qGsKphHqqL3Ogdj6Km2IOOkQiO9Y5n5RPrgRyITvZlC5qsgHAAdyiHvaoiF9qHJnHDyjoMh+Mqvp5NyNybbCd1NJKADdkFtVptmdn4JmKzIwlEL7LQyGrFDGV+NzUSf+n4AD60Ze6U/5Ye6oMelZcoQSwlF7VTbTxMBSM662plwE27ZuU+F46E5OfL81fsHImousIs/+9A5xj2nBmFTZQPl36XHVcvlZOHCI+2sdQDt2Y9SaTSeP8v1Ukd8vNy4ei/XWOZLhFLpnB6aBIn+iZwsn8CJ/pDONk/gdbBMGLJNI70jKvEK4Dsk1rhjsHL3BD333HBjH4usw3n5Ct/zcR6pap4ah5vq3Xya81GyjtztII5qlEOsz5/7Pg3F6uShEkCCCBbTxBsnmc9Xg7InAIJtM9MTwiyU0fdyytYzT7XqWIynqTF5iILCuDHD6lHusm0hINd2R24gNtBi5WHGeWlIAhY1SBv1PnyA9zBhLDzfBSNYuBYjlKJgbWL1gqmcyRC1XY8aPl585nRbWsOvo6kAwjIXcgAY13SyREHka4WKZIIdaDY68R4NAlR4CudNypCEMKRIl1AYiR8rHfCsifY5DSVwKQDeHpoEi67QMn6b1tdi12ae4ZV/ZLD4nA4TrvLRtGPbJ55PDk7CsB8xcCxYEfd+chp5qGpXP9APtNWMPs7+etqic9BxVm1QQ+9RnjXNcsznVvuU/l+EusXIhh78/JqeJw2/O7ldl3xx0QsibVfe0olvCDqXlEQcuLKuuw2LKgK4LoVNfjHK+fjR+9dg8c/fTGOfPUaPP9Pl+KXt67Dv167CDevqccKRgTEumDcuLoO86um5/jwesc5WQCyNgc8LLZ4itcioOP5Z0YozlUNyC6A1UVuemNIkoTnp+j/lzTx/wPU2cNmru1asERzXlnKMxkl5HwexjldtdfaClMAslmyZgrg0ck4VUqz+M8njnF/nnhi9Y5HVSNsYtabLx5gD1NsLeS813pE9NqgR/U9vTEWgCy+5uBEzPDntQpdo0xgI6gVwOrXpu0SA2wKiPx+E5EKSWVpKPVyNxuqBG4fRiot0YQSguN9Ie6ojIfpFICReEr1ulY3lsjPp7YILZWBrIMQGWf7XTa47PLrepHpyhp1/9mUjEIpZHMFTwACqAUruaKRMf4vVDZvRUD/2phpj8WnNbxjggCzVzWWeuj6y6PosGlUm5jx70g4TvOoyV5Fxr//86wc3+a0iTSiVJIkPLCnCyu//ATGlXtRAPDIp7agSIc3OVXYRAFN5T5cuaQKt18yD99750o89KmLcM9HN6p+TgDwn29fwf8jbyCckwXg3jP80w/BJfOtj2O14CkUzVrIuSpYI0whxo7J2ocm0TEcgcMmcPMYjWAmoPA4bKrRkFYAoo0004L1GuP5Jc6r8GcVhmTx4RWMPGVpa5598whO5JAB/JuX27hff/H4AB05srhJWRgBdVIHFYLkqQMYY4rSyzgxh3odiDllHtXITdvlY1HN8QI0SsLp13Ry2Pe2NYcCsFVHAQzwDwrElJfEB5JijFxTelm5S5Uc51A0iWO9IdoBHGUi4ax0odzMetA+GDbkzvLQxRwURCHz/N+2SlZYbj2hjjMbUbwQ2bi+545l6BaptATtEkXuZ7YDmJaQFdN3NsATgAAw7DabgT0U5Yt3q4VhHNwMdwD1LKZYr9Yy5vnO56x7bAeQtQP7y84OObM96EEkkUJDqQfrm0rRNx7BcFgRf6yQx8GHusfw9p++jE//eS+lKYgCcPjLV2FpXXCKry53XNBSjjctzqyLxR6nKdXnjYBz8h3oMskBvmj+1MUTPL+kfKpTU6mUqis2h1EAv6As6uubSnOyMegcmTRd9NjFoLHUm8W1MxthsAWii1MQux02NOmMz3hbTpzTsRzjmP7mA8dzsID53TY+eVmCHC6uRUXARTcuwj8DgBWKWWr70CQ1KZ4O2HfrysXZ13fvGF9AM7fcr+o4NxpssqwClhx6jLpGfRrboPoSD1Wk8rhSemC7hawHoCRJ3G5sidep8Awzr7nM56QdQb3P2G4TsVbx1dzeNkQLQMIdOzkwAZdd1PV7Y/8OIN8HybSE0xyhihHYAvCqJVXY3zkGQQDeurIWkXgq670jr5NY7aTSksqAPC1JqsQPIBPrqOV88g5eM418xsARLGPykQtV4xqngcxsB7BTRzDXOZy5J8kaKwiAV3MdSAAOMbQW0gFMpSX8Ybu8BhJx1U2r6yGKAj7z50zyx/+7ehG++MABXPfDrdh1Rk2PeeLTF8NjkqBVCPzovWtofKJbazPxBsU5+S6EY8bK3KJpqMl4HQAr3BmrVjA7NfFOrAXMVO1fvvL3wyb5H+pUh4sXZHdIzTaxJMMxLPLw31/eKbPCYISoRRrmncip4JCSDyqAz4UhGAjFaDeIh/v3dGGMQ74mnZvTQ5N0cwt6nfSx9ncaK3hzBc/IWc9Iu6HEo9pw9Yp0QJ2pSj6H8WiC28EFkGXzYLeJNFPYqj3KSDiuUjCzHcAQx9hagFyc9oei1AMQkOPACBVjnkGRv5ExhK4LelDskTlTLruIeDKN08OTuhm8BOReIN21XMfAbFeYjD03zS1DdbEbeztGVfey0ybQA0TGYHwEo8x1mEpLWbnN9+3qBCDzUdmXMxuUwDxzb8CaPZMeVjeohVaFsJQqNeDPzrQXYDiavd8IAE4NZA4PRPzl4lzPyVSaHu7mV/rovvf8sX50DEcQcNtpMAAZ/25XeMglXgeu/eFL+MOrZ7L+7mffNF/FBZ5JuBw2wy7tGxHnZAGY7xxgFs0V2Ruk1siYB61tgx6eONir+jcZAUcTKbyi3GCX5BD/9vThviwfOh7YMRUb/0bQMWxswcJmDOuNEXk8wFwjd6fqq2YE0gGsLHIZEpEf3Gvsya+ODwAA/JxJREFU/ZdMS/jFS6eyvv6OdZkxMPs3SGTSdMfAAxrOFM/GpVunA1jqd6m+Z2RzUhlw0WKPWN/0jEZ1TWSHwvGskSK5BgZDMUujUXb8KwpqHmE/x16DjKZJt48kFBhZwLDYqEkEIV1AsgEe7w0ZKqWBTIwiKRRzzQR+/KDMYa4LuvHyKXnc+zbFzkIrKGso8dKOFlGTP3dUPiiSbmtaklTWOQCwrS0zRia8QQCGB5yZgl4H0MyeyQjaQ+mh7tEp/y098PwzCXhc1UKCd2fZbYKKjz4Ykp+TtvsHqCcwW1oy+wGxfllUHYAkyQbqjWVe3LWtnY54RyYTGJ3MPhguqPLjjktbpvaCzqMgOCcLwEJilcYaBbA2UnjmaLYFCg+7NR1AMord0TaMaCKN6iI3l+TPQySewpf/LscrmHUtQgw5l8cv7DLx4GMntnrPT7sJAXwOFwGPXrb15GD2F6eBaCJFSecLKo3f158+n13cafGbl9sR03SE55T5UKGMh7g8wGkKQe56NcNL1CtfB0LZG5AA2eCZjYEzMjp22ERaCJFrvnMkotvFTaWlLPuZJYpRsQRr8X7s+Lep3Kcq0HliATLaIXxM8vPVRS7akTQqAFfUB+GyixgKx3FqYILaqhBaw9HekOUuAukysRxTM/SNR+mId1VDEMf7JuC0ibhmmWyoq73+l9dnhCpEwf6sstZ4lBFdKi1lRd+dZpTVfsYkb2SGR5U88ApAAYBtmpwtrzPz+w/v7TX4yamh1GAEPBvi4LxOG+XFCkKG2lDMmdgkmMMZGf+2D4bpFIoo/G9eW4f+8Si+/siRzOM4RIiCmpYiCsB/vWPled7dLMP5TyNHTDV716oVjFZIQEbAU7F/+dFzJ9A5EkFtsVvX3JeAEM1rgm4UcfgZeh0kHrSGoQTECoZ9JtFEGqsbsg22gewQewDYqymQp4uT/RN0oVrMSVEg6B6NWCJyT8ZTqiKP4NplMin6RN8EHdmRAnBvx9i0RttPHc4cLrSpBwQ8niHh8bF2LWUmxU0NxwyaN3Im0BZpLczhwIoSWKUA1hws+jgdQKLU71Q61oJytZECrjLg4l7fBE67SM2UX20dph1AIrI53hfKGqfqgXix5eIC8OutbbS4Jl3WyxdV0lH0Ho3ArcwnvxaHKKDE50TvWBSHe8YhCJnscgnZxursWD3oy7wfvToK3JmEVjwEAE6euWWOKGNGtLs6cjPntwKfQVLJTNvA8FDscdB73SEKVJlczilc2Xi1Tc3ynvf7V+Xu39rGIM4MT8LtENE3FsXF33mG8RZ0IJJMZwn8PrRlLlYozgfnMXtwvgDMEct0bELMlqc2iwpWdmEOuOwoUXhEtAC0OP492R/CLxTT6tsumYeYiQiElB+88S8AtA1YH72ua+IbG88t98EmCll8xFUN/J+XOMxFrbnndMFuzi0GndWH9nZnfU3vM/+fp09kjT7fub4RgPw+P3pAHvEtqSmCXVmIzXKWjdDBdNL0upiTHL4c6RAR3pddFExP6DVF2V6ARobkfQZWMFbG+UYKYF4BSXKMyQiYdGOJDZIVHtnG5swYmBSA/cpmeawvZEmNKiBTwLUOhHWTGViMTSbwh1czIqM9ymGHjH+P9IxniaNOKZ080pV8QbGJWlEfVKnxtWptlrJRydiX8HwVZxKSJHE7gF6O+C5XsNSUjgK8TkEQdFXx3bMgDq7C76IcZbfDRnmiPHudtHIgXVITQNDrxGQ8ib8qB1tymLCLAr7/9AmwdMPBcILaDomQ17u6oAeffdOCwryo85gW3nAF4HRNv91OO3fj1wauaxGxwBME1AtzY5kXgiCgc2QSJ/snYBMFbLGQKCJJEv79gUNIpCRcvrACjx3oMRSBsCfXt62q5f5MB8fihED7yvX8ulx2G7dY0BsD8yhi+V64rVrA/OwF9fjXZRezzK8JBifiePqImne5tLaI8tFIgLrbYaOelNPhAbL+jbwDgiRJiHFU1UVuByRJwqSSAOGxYMRaE1QXgP2hmMqqSAstP5EtAI/2mhfzagWwugA8zumskUSDzlH5OiG+Y0QwQj5jSZJ0Fa/ED3B72xCaynxyDJtyMbYPhk3zgIGMN6jTJiCeSlsad/9h+2mEmc9yKBxHwG3HpUrko3aKIAqZ96demRQQ/t/lmpjItKbDzP6LNUnuGDm7hUooluRGK/LGlLmCVRGPF8hRQO8e6h2d+Tg4LaqLPZiIy6874LZjQrknGkr1DzRkv3lwbzfGo0nUFLmox+RELIVyv1OXxy0pX//625bl5FpxHjOHN1wBmIvbuB4KFR2j5YkQV/8Xj8u8n9UNQUsL4YN7u/FK6xBcdhEbm8vwatuwYYeSfT0b5vLHtyNhfa6etg4yGjfzhCB7O0Ytx9pNxFN59fE60mNeALYPhrPI8e9YW6cq+rUjqu88flT1b0EQcIXiz3ewe4zGx63MQyIIu5mT7hWLCU73D5BHP5PxFE2KsJK1WsPxAvQZRCtqFZ0ep412tc2sYCRJUhWA2mvnzHB2B5AUiaQDKHvgCZTnSD7j7rEowspmmNJ0a1c3lMBhE9A3HkPXaIRSA7xOG9KStTXErnSCSCqJmRI4mkjh11szXE5yaV27rJo+3sun1EKyoNdJx6ULq/2IJ9OUI3jZIvVBIGFwAK0uytx7PTlQPQoBPRPo6cTAEbAHiEKogAH9QpXnDlAosD6yLOpLPIgrVIZSn5N2x42cDy6YVw5JkvC7be0AgL5QjKqDP7SlCbdd3Mw1Gq8LeiBJsnURz5f0PGYHzrkC0MxuJR8nSR6HSHvC5iGuc2MSPLJfPWZsoPw/6+kfY5EEJeR+5MK5tHPlMRihkBO32yFyTZwBY/NUlqtn0gilmzj7OF0jEbx/0xzjX2SQa7KKEUgXKuhx6HLD/rgj285gU3OZylRV0Hz+pwbCWYbk71zXAEAWUBCnfpIIomfcmisaOV5pevyj2mJ1CogZ/w+QuwgENKHGoL+sjYMDMsKmTpNu08BEjHbEHKKQdUgY5AhbGsu8WR6AdSUeOkomJtCHuzPdR62Xocdpo5/L9rZhLK2Vi3SiJJ2Mm3ePyMiZ+IaaXbN/3dmBoXA8i49FLIQkScIrp9QCkMXVAdr9XdNQgp3tw5iIJVHud2JZrZpXy7N3IZ33ikDmMQd1FLgzBT0FcPk0YuAIVjCCmULZXet1h9Owdt3kAwM64+Y5ZV56rVcGXJSnxzuUA7JQZF1TCf732ZP0sEZ+593rG/Dv1y3OOugCwBWLKtE1GkGxx4EvKfnn5zE7cc4VgPtNFJV1FgncRqjmZAlbSFrDS6cGjL+vUfjNKfUhkUrj5ZPW7V++/+QxDE7E0FzhQ/doFCOTCSyqDhgmNhCCu9F7Y2T4y15EZhwystg4mecTTabxZkUkYQX54gFGEyn0KKOZ+TpZxUDG+oBAEID7NZzAWApYpPkb33j0iOrfG+aW0pSIP74mF5VECHKgayyrE2UFMY3nJa+I1ROv1JZ4VKkLRikg9HeYnyF1v9HhgOfpRnh1Y5GEbrcCUPNOW6oCWddWiEMdqPC7szwA64Ie6mNJOoDsNcTrBm1gcoHJ8yVVA09RrUVY6bqST/REn363M5lK4+cKX/ciJYEnLcmj2Y2KoKpjOIKJmPq9uoTh666dU0LTPy5ZUJnVhe8dj0HrfdulFOAlTOE/fpaNoPVSQKyM3c2gFSFEdDrj08Ecg0nGTHkB7tARHFb6XfR6ZBshPH9WAGgu9+G23+/C95+S4908iroXAG7dPAeX/dcLWTSd925oxDalU/1vb148rfzm8yg8zrkC8KG9xjnAeorTXKB3YjLDsyZWMMQvjCzdc8q82H16BBOxJEp92ad6LQ50jlGl1rvXNeCBvV0QBOCbNy03zAImI0AjhbNRacLWLV4DJRyQUQInNM8nF+7RnjwpgdsGwxkFMMeiBpDjvyKaAmdumRcvHMsu5v/wMXXe5GvtIzgzlOF+2W0i5dTsPj2KSDyFeRV++Jw2TMZTU+ps/nV3xldQ72Ye1tl4Gku9KtqBFXUrWyQSXtxAKMa17AFAC2wWS5nruN3AYFytAM7epCIcw89yfybxg/j1FXscSEsy74lsSIe6Runv8ApAUnjtaB+iz5cItIz4sATkuiKFoNEI+JEDPegciaDM51Qpqq9fWUs75dr8XwDwKZxSAfK0gKwvl3NGbr1jkazpx5lBuShlvz5pMqUoNHjejsD0YuAI3A6bigrzxGHjvWIqaCg1KABnSAn87BH+PiMyNylRxQuCejrE3gunBsK0mAOAd69vRFqShZAf+PVrOK3htb5jbR06RyYRSaSwqblU5X96HrMT51wBuPOMsd3KFUuqpv0Yqxv5qlUz7Gw3th4g4w+yeTSWeqn69+L55YbculRawhcfOIC0BFy3vAZ/fE0WGrx/4xy0VPpV40o98DYOK2AVr2YeaU3lPjhsQlZH8a+7OlQZqkY4wEQUTQfspqznTv/Dp49nfe0da+u5HdFSr5MmXRBoRyTvWi+PgZNpCS8c74dNFKiX21R4gPcx8XI8OwfAYAQcdKs2JStRW1VF7iwz6K6RiK5KU5sGAqi5lkZWMG2MV53WQ3IiluQeSkp9TmqlRLit5L/zKvzUQmkvk76iPYwAckfNJgpK6oENdlGgB4ETfROGHXUW5J7WK+4lSaL+kh/a0qQqLm9Qxr8AsPVk9oGDTDv8Lju6R6M4NRCGTRRwISfrvGcsivoydRH1kjJZCDL8ukJx46xCrwOojaacKogQCwCePmx8IJ8Kyv36ncqZ8gI82M1fH1nREwlu0sZ2ag8A85Tgg7VzSrBdMUc/0R/K+pyuWlKFzfPK8eKJQTjtIr5543LLdmXncfZwzhWAnSPGaqvVefAi4plBW4GZ7xnbabKLAmqK3ZbtX+7ZcQb7OscQcNlRXeRC22AYlQEXPnfVAnz2z/ssjRfXNAa5XzfzqGOXjDkGJ2BANhMmpGN2edjRNmL5fW0dmMhLJNxJZizHiweTJAlPcFJUjukkOxzvn8Avbl2r+trjB3sxwhRZFy+ooF2dPylFOvUDnIIhtBUbG60ZM0GJ16nK6+Wl3GjBmkETdI5EVGNEFkPheNZnxRaAxw1Go22DmddmxQMQkIsZ4gFIHlZrAROKJlTcxLQkZY2q/S47tXza2zGmOiB0jUa4meBa2ET5oOOwCYgl09x78PnjAzjaG4LPacMtm5pwUDncVAZcmdEzgOc00wOnTaAq6MoiF55XeMJr55Rwec5941EsrlZPEHafHgUg818JpkJDyCf0OIDzLFybVsDm9R7JIY/aKowOwDM1Au7XKTQHmWt8TKFPsNfx9tYh1R700/evpgKyKxZX4rBCm9AmX7VU+vCVG5biGwr3/M7LWwwThc5j9uCcKwAnDJIlAMDhmL4cfdEUR8A8Kw6CVCqlGqXWl3gwPBmnObV6/nyAvGh+V+k03XrBHNyljIG/fP1S3PXKaTx9pE9XBUy+LgpAeYB/es3FxHSlhQKbjNBZa4DesSj+4eJmS48Rjqe4ZrG5gt0AeArg3aeHswUCDhFPHckuCgHg2SN9WFYbRLEn87pSkoT/ffYE/bfbYcM6JbJr28khxJIprFLes6l0AFmF74U6FkHdo/yRZZnPpeo4GakBWWj5WMRsnIdUWqKGyASlPidN7DDq5rYZKIB5alEBctFFRsCEm0jEDuQzPsbZ+A91Z/NKWTsYUowRyySPCdUByHSbqhTvRF7XmHT/3rdpDoq9DsrLu2xRJe2gDIfjGNXYllQG3PRnm8v9huNfQDal1opoiFAmyKi/JcCSZ2GhoFcANpXmpwBkLarysYZoUWaQBjI4QykrsQR/n2FFV+SeZD97NpHILopIp2UlfLnfhd2nM9MrdhAlALjvji343pPHMRSOY2FVAP9w8bz8vJDzKDjOuQKwkDnABHa7aKp2zRU72tTj4cYyH15S7F+W1xWjXCduCwC+9egRhKJJLK0two7WYdn/b1ElXHYBP1BGmAEdhStZKkoMLEBOD1n33tvMsSHRgmzm7DgmnkrjYs7oSg/5EIIcVf6G1yFy48z+46HDWV+7bFEFwjH+OJ10a7/21qWqr9+z44xKKEG4MfFUGttODtEO4NHeUM4WN2xNoee0r9cVL/E5VJtCpc4BQAutWKQvFDUkv/OEILXKRtyqYzCeTktoV0bAHoeYJVDq5SgdyViWeAASBTHpFlIFMOfaOcwpADcqlkjbGUNol6J81o7OeHAoiwTpyGl5uLtOD2NH2zCcNhEfuXAuekYjiCpj9ZvXZvhTPP7f2qYSquxdWO3HKwpX6zLG/484E5ClymVXH36JN6J2bRg7i3nAegWgPU/WW+whx0iANFUYdQD1uLj5hl6bgfCsBWTG0ey+coqZJrjsIu56pR0AsLQ2gKcVXqFNAKoZ1fiVSypxsHMMf9vVSfnmhbJJO4/84/wnNUW47VPzE9SzgnnskDqbsrHUo4p/08OrrUO4b48s9rh0QQVeOz0Cj8OGj13UjE//eR8kCXj/pkY4TNS5RuRlK6R3gqV15iIbIgTRRr1pVdBGYP37poJ4Mk3zjZsZbhhBOi1xu0IVBhyfU0ox8+aVtSqOWDSRxl2KjxYAXLm4im7Kf93ZgZpiNyoCLqTSEg7p8HesQM/QtU/HFsLvstPiSBCs+1uyXRS7KECSYKj241nBkG5cj04CSs94lMZLLagKZPFf2zmFI7GlYYtav8tGDzA8BTDBfk73dX1TKQRBLlJJAUoSdazQm0jHj9x7ybT6dPrT52Xl701r6lBV5KbKcABYw9AhHj+YnVv77rX1lLvocdgQS6ZRW+ym9xabqEHuM0FQlwakHrWJgkrEo+3YziR4BaAzj7vUIibu0cjZYKowslKaKREID6IA6oVpswnU15Q9zLGdcbtNwHbFP/aF45l1eVG1H93jmdfx7ZuW4/P3HwAA3LJpDtbOmRo//jzODs4XgFNE0IJpLg/PHOMTj/d3yBs/2VgaSrx48YQx/y+eTOOLDxwEANy0uo4qgD95eQv+46GDCEWTWDunBF96y9KszUcLEiTPQ1cOCl2/Qc4qAeFTDWq4Kn/b3aWrJtXCSoqEEdqHwrR7xssAfnBvZ9ZJWgDwJIcTSEDydu02EXdoxiA/ef4UFcsEvU4sUTpKzx0bQCotMX6A1gtALbdOT8U7zDHxdtoECIJA46CsdLQI2BEwGYUa5evylJ0rFeFLJJHiJsGwfFnetclT1RZ57FkegDXFHsSSaTjtIj3k8Lp9uzWejYBsjE0em3TLSFeRl1ahBSHd0zg6puA43heSqRkCKPXhkf2yKrXY41BZ3jzPWTMkpgIlnZ1LmbHxyycH6PVLOoE8JwDScWbNrcciZ6dQSaTS3CLJm8cUCW3sZD64xCyM7oPesbMXs+eyi5TK47KLVJ3OHvxZJ4aEcn2z705t0I1DPZn7ri7owa+2tuP00CSqi9z456sXFvAVnEch8IYqAPMpSpqqLcFzR/kFBOmykdO6JEkYnUwg4LZjtY444ldb23CyfwJlPjnRYVwZAx/oGsXxvglUBlz46fvWwGkXDW1gAGCNwcmNp+QkmMpbOqfUC6dNRCyZVhUee86MWC6seZt4LjjRZ6wA/tZjx7K+1lzu1e1YAeroulu2NKm+NxpJ4GHG6PvmNfKIL5JIYXvbMFZNIRHkGU0xqtfl5W3ohH9J0jCsiBoIqjlpIEZXF49rtYTpFPPEUSr+H8eihxcJWOF3ZXkAEppBs5JDnUyluR3AgYk4N61ho8ID3N8xqhofWhmTkoKPiIBYbh0xaL92WTWaK/xoHZigHWRW8BCJp7I6cgIyY2GHTaDpH2z8278/eIj+P/lsIhwnAFIs+5kiS28MW2joiSSKPNNPASHQ2j0ZiZCmAlEUdOlBZzNn2e/KRL/5nXZ6gGnWuaYnOVSU7tGo6oD+kQubaN78V29YqkszOo/ZizdUAWjPYwW4qEa/Y2aE107zbWpoF0RZrTuVhfmi+eVcc+XOkUn88BlZXHDzmno8drAXouLc/vjBPjhsAn76/jWoLHJjaCJmyi0jGx0PbEdFC/Yd1UsR0cJuE6nqlhDkAXnjWWvRYqd1IDytSDh24dcKQCLxJLdoWWfgk6hFud+Ft6xQm1t/94lMUXkNY3x93+4uygPcl4MS+HfMWFnPAgYAIvHsblWRx4FkKk3HiKU+64s322kkRY5enjPA7wC2MCrBU5xuHlsAahXAAL+obCzz0vEv8aMkRTG53tqHwojrHIYO9WR3XzNCkGHatQWgywPloU/xSSSPmkpLeEgxEr/9ErlT/ABjLN7EbMpbT2Tbv3icNhxUDkABtx2dIxE4bSIuaJE5i5IkqSx0CHjJKYQGUcpcP7l0/PMJvcLTiJ+cK+w2URXh+OiB/HsB6nXTB2dgBKzX0Sz1OxFVCPJFii8mkLm3Eqk0dyReX5JZn22iQLuxdhF4cF8PkmkJ1yytxlVLrRv5n8fswRuqADQzKc4FKyxw3XjoGuYvrmQjJqbM+xWfMj3+31f+fhiRRArr5pTgsYPyInbl4ir8Xkmt+I+3LsXaOaWYjCfx4d++Rv8uDwLkkbMerATZA7mNEQlXqbKI9SCTqE+eGVKSNK1IOLYAnF+pLjC++0R2vBGQ+UyMEGXinj5yoVrV3DkSwfY2maxfG/RQVeaTh3qpyffpoUmVbYwRDjIFy7xyvu1CNJHidufKfU5VZ4ktxM1QzfzspNJV6B6N6naDeR3kuqCHdkr2cd7XUwOZz3ZBdfZrC3FSHBZVB6gHICn8iK9dRgCi3/E51KWvBD7aG6LdklzWEZddhCTJcXQE4XgKybSELS1lWFEfhCRJeHBvxs+xnimw79vdmfU3G0o9tED2KK4GG5tLqRfjb15uy/odQOaAaZ86KfaqGG5rLqbs+QRPLASAK9CaDljx2autxr6xU4FfZ2QdSUh5HzlrMR7Jvi8AoCrgRkKhAQVcmYtgXqV8TfN43ouqA2CZQ1+4djGlNSysCmBfxygCLju+csPSrN89j9cH3lAFYKlBlyRXrJ4i2ZXTjEG/hqRf5nNSP7CLOQXg04f78NThPthFAfMq/egYiaDC78L2tiGkJeCd6+rxvo2NSKTS+MTdu7GvcyxLcMEi4LYbmkwbjYTY5SyQA1eHKIG1YpqoBW4VwXSUwOR3HTYhS2H6xx0dWT/vc9poHqYR9jAj3FUNQSyqURcvX384Ew93kzIGDsWSODkwQQsMq13AMWax39AU5P6Mbgxc0IMhxpaiNqh/ANCiqshN6RSkmdY1EtEVkXRz0kBEUUCZsrHzPseTyoje77JxCwBe93dOmZ96AJJmBok2I11eI+oAL0ay3O+iI1mje0gPJD+YVVtGlEPCxy9pASDnQJ8emsxE1zHF4sutmSQGgksXVFDxTkLJPmftX8hkQIue8ajK9BnIdAArmXjLzhxEX/mE3jpjJaIwF7CfhVESTT7+vhaFjtrr0vns6oIe6otJ+J6iALiVAwRr80Jw1ZIqdCuUlzuvaMFzxzNc1DZFWPUv1y7K6fB4HrML51QBeKR71PD7+fKSAuQ4sHzh4f1qlR9p0S+sCqgUl4DMCfry32V+z42r63DvLrlD4HKIGIsksbK+GF+9YRkA4PP3HcBzxwbgdoiGYxTtY2gRNrBLYAvAqhwWapI/OTgRV3WO7meSLcxgpSDjIZFK0y5HU5lPVfy2DU7QUQmL5XUBSwHyjzMjJUEQ8NEL1WKQA11jaFO6W9cyY+AH9zJjYItCEHZi06Ij4tGznqgNelScq0YdBTEPTruYtcl1jkzq8gj1TJsbFQI6r8PcPSZ/Pi2V2QrtcCwJnoCzMuCiI+BJpciiFjAGCmCCnTr0DBILR0RLucSlESsYVmQhQbZ22qKMbB9Uxr+ks0ji4KKJFLej8+Etcymfi4x1if3LUCia5RlI0DsWyer0H1Qi8SoZFXevAc+1kNArAOvyEAOn+nvMgY/H+5z23zd4voVOA9FzUqhkijSbQuRjD2z7NWuOy27DD589CUC+Tz9z5QK8oiTHuOwiJuMprJ1TgvduaMzr8z+PmcU5VQA+sMeYz7HBgkedVYiiaJnzpsWEhpS/7ZR805K/Rtz4eerfHz13Ap0jEdQUu3G8L4RkWkJNsZtmif70/WvhdtjwX08ew992dcImCvjxe9dweYTk8XgmyCysGsMuMPk7qp9VOoBtg2GVhcj+zjGYONZQTLUDeHooTN/jRRpS+BfuPcD9nbSk/qw9dv5nT+KSCN6yogZFLvUL+vLfZX/Blko/qpTX/sj+Hqyok4u4XHiABI06Nj5DOuazNUE3BpiRm1UTaPr7mmK/dzyqa4I7zEkDATLq68GJmOr7qbREC7zlHKqFnoFvmd9FPQAJpSIUTUIUMq+P5wFI0DMWo4UjCyoE6RxTjb+t3P4J5YVoX/7HL50HQZBFKUQcRIj5RGCmdxhKpiX699KQX1tTuQ+SJOH6H7+s+1wGQjEs1ozTjyoj8RJf5h7US44pNPQ+13zFwBGwIptYAUyv9egYQOGtYLae4LtMuJhFlbxkdlStFcPEGMHQv1yzEPfsOENpRLFkGg6bgG/ftNxwcnQesx/nVAG4vc3YR+6qPOQAs5gqp/CZo2pi9wnl5iM3E+k0aPl/J/tDVHV12cJK7Oscg9MmomcsKhd671uD2qAHv9vWjh8/J6sMv/G2ZbhicRU34ol8ZaVJBJtVu6z1ORTYDaVeuB2yEpgtQIfCcZT6rHF+jvSMT4lTo6cATqbSeLUtuwskANh9ZlT1Nb1H7dIIZtwOG963ea7qay8cH8DQRAyCIOC6lTUAZO81YqGzr2PU9HVpv6/n46iX4lLhd6ueq5YHaYYajRI4LekLUZJpiauaXaMIfhIpdVoIS0ZfyOls6nUU5RzgzGsqU4Qt8rVmw0AoZqpwNeIBHuoew8KqzLVq5dILKeKYUCzz+uyigKsV0vzLp4YwOBFH0OugRWuNkif90N7sAlAUkHWNku7fr7a2oYszbidIS0B1UF1MkYKEjYMLc/iVMwH9GLj8xootZsQ8haDk1Rp2AAtbAB7t5fOiJ+KZ6498vmxk4Gkdnnexx4Erl1ThB0+pM9E/fmmLbn76ebx+cE4VgGdMyMv5zic0Mv00wrMaK5gBZVEg6rTJeAoehw3rmjI8Q0mS8O8PHEIiJeHClnI8tE/eHAix99/evBibmsvw6IEeOiL+7JsW4N1Ki97IBmazMuKaLqwqeAFZUUYKP7b7lEpLKhNcI4xMJqYU58R6yLHF52MHeriFXX2JK0shF03y388Jjjr0fRuzxyTfUaL73rKiln7taE8IDpuAoXBcVcjwsOeMugjQuxb1CsBSnxNtA5lFvzFHSgNLGyCWMkYpCFwrGGYjbmVEHylVAZi9yehZ8ficNpVindhSEAGIlY7xvRzRRU2xB42lXqQl2RsQkC2lrNQOhE7AjlV9TjudHjyodPnIPVgZcMGl8GL38LwJ3Q7sUfhapPdy2aIKvHRigGax8pBJA1F3bOIpCclUWmW/xKNAzAQGdMajuXanzbBG4wU4mueunGEecIHj4EZ1urds55HwEFlurbYwJXzXt66swehkAoPM95srfLjj0vNxb+cCzqkCMGTizaXlEk0XTVNcmHZpFnYSwM0+uwvmldGNAJB5Qq+0DsFlF+GwC5iIpWBTUhjetqoWH9rShFdbh/DpP+2FJMlFx6cub6G/b2QEzVNZEqSttv8AzM1xVLNA6Tp5HepOqlGsmBZTGQOf0LGA+eajfPVvZZH6RG90FfELSG9W9/neXZ2IJuQc4CJFlfjwgW46kjZTHP/8hVb6/36noHttD+ooK0t9TpxRCOMC1Bw1K2CJ+ST1pNiAZ8rL7m1irpf9TCYwSzlYwOlMtg1kdzkEyAUE6wFoF+XlzQr/j+Cxgz3c7isZA8eVwt9pgafAfiSDE3HKkSTm2ZF4Ck8oCUCkGCb8sbaBCe4hY36VH8eUDrYEOQWkqsiFT96zx7AgzZhCZ3+vLxRTFYCJs5QFrKcCzne02NwK9TqlPZBPF4ZpIAXuAOrV7gPM/TeuSQEJRRM0dYeA3AM3r6nHP/91n+p737pxec7rxXnMTpxTBeBMH1y1pqJW0acZ05D9hlXAsvy/sUgCX1dO99ctr8Fzygg5lZawpKYI37ppBY71hfCxu3YinkrjqiVV+OoNy2hREE2kENdR13ocNlWhqcVwDidWm1XyngIyQugZj8LtyPxuLjFvU4mEO6KIR0QhU4R0jUbQozNa1D7GVKZGH7igSfXvlAT85LmTEEWBegL2jcco38mMB7iLGUm3VOp7Uup1y0p9TurPZ7Mav8KAHQGTosLoOuKNbd0OG+UhsSR0wpsrctu5RWUrxzjaYRNp19SjbE5kUyMegFr+H+9Vj0WSNIKRBRkDdykcQ737iQW5r8lr1G6aTx3pQzieQkOph3K06hWRxn06/L/rV9WqVLob55bijrv3WM7v5SWYdI1EUMyYLRcgIc0UbHQdCx2q7bQgCAKczDWfSwSlFRi5TRRaBKIH4kFoEzPm76Trf7wv+0AlQe70rawvxtYTmffnPRsaqCjqPF7/OKcKwJkGyyXJBQlmgdXbSFj+3/eePIbBiRjmlvvwKmMLEfQ68PNb1mJ4Mo4P/HoHQtEk1jeV4IfvWU1HTN2jEbz9Z9uyTnjk+5UGGa6APjdEi6ms08QL8GT/BJoZ4rQRUV+LXCPhkqk0TZ6oC3pod+GXSjKDFh6HkJPqEwAGJ7KLnQvmlanI5wDwfy+dQiot4TpmDEzsTfaaJIKwo10jDqceJ6zE66BFg2cKudbsCJjk4+qNnwB9gj/pQpzozxTZZASs12HnqYbdTpEWRuTaJq9PrwOoZ+vyw2dOZHUBN86VN72jvSEUue05HQII1yql6cITjt8NK+uo3QZRqPLyfwHgptW1qs++dzyKk/0TVG1shgmODUnX6GRWAk+MkxpSSEzEktzRszufQcAMihj+Gy/zezowGgHr5XIXGiPKQd5ps2WlgOh1xm9eU48/vdYB8qkE3Hb86zWLC/5cz2PmcL4AnAbyEXwd5Sy0TWVe2gk60DlGM36X1BTRjUIA8L/vWQ2/y45bf7UdfeMxLKjy45e3rqedhl2nh3H9j17Gwa7xrM2O7BdNFcZjW6upAPYpdJGIErh1IIwNczPv5chkXOXWb4RcR8Bnhicpn4/wy1JpCXfvOMP9+Xodg+witx2CTtn70onsjoIgCLh1c5Pqa5GEhD+/1oHNzWVwK4Uo2YwOdI4Zqq/ZLo0RFUGbtwwANkFORCCFLWuMaxVsB5DYBPH8/gj0hBukKGY7lSS7dnkd/4DFGycXux3UA5B8vmwBGE2kaNQaAVHGaz/F3WdGs9TcDaUe1BS7kUhJhqbpPJB7g+WRjoTjeP6Y3Gl82+pMV6+uxINQNMHNOpb/lk3VxTvaG4LTLtKuqRl4ptxyB1BdABbCHsUIegeEYB5j4FhUFND2psSr/5w7hs6Ox2JI4SZ7HCLtTJOIRb34yZvW1KnSi75103JDmsd5vP7whikAC6FWr8vBPFcLchMmFJ4P+/xI9y+VlvBvDxyAJAGXLqygiR+AbMC5bk4pPvK713BqIIzqIjd++6EN9Ab982tn8O5fvIrBiRgWVQeyeCkpRRSyzKSLaSZGIJiKIrou6IHXaUM8lVbZfaQl69FkpwbCOXUr2I2VFKAvHO/XjQcb1OHsvG11na4NkF681E1r6uDTvE/ff/IonHYRlypKzp6xKLwOGyKJFE5yuG486FnAAHIGsRbksyLdZz37FiPwzF+NrpWeMf73yOfO6x6urA9yfyfEiZ2rYDwAI0zHtjLgQpHbgRN9E1lKeJJcYxOzl8EfP3dS9W9BEOgY2OXIbdkkAiz28R85IMdoLakpQktlgD73+qBHNXJj4bAJNAKOxSaDGEctesejcGkOa12jEThsomrcqs0fLjT0FMBWHQFyBZvlnmuH3wwOm6g7EdGjmRQSdlGg94SHWX+ay/Q7gE6bCKTlPHoAqPA7cd3ymhl4tucxk3jDFICOHPlplv/uFCtL0vkj3krs8yPFwD07zmB/5xj8Lju6RyK063Pd8hp8ZEsTPvXHPdh9ZhRFbjvu+sgG1AY9SKTS+PJDh/Av9x5AIiXh2mXVuPfjF2Q9PukhbDLhc/A6BjwYnXr1IIoCNYTW+hRaiX8SBXlTPcHhsOjhJEcB/JNn+eNfQH8jfPvaet0upd5IKeB24Oa19aqvDYYTeP5YP966MjMGJnYqeidzLYwKwDBn5FfkcSAcS9IxZp2JETgPPDPo3vGoilvFQmuPQ0CU7mkp0/kj0MvbjvBSQEp91ANQQkaYQhNAODm/hCvo5BDNXjoxmDWGJ2NgoqK0eueTnGS2A0ii3962Wv7cyftTV+JRHfRYlPmdePWUOhnkw1ua8HIOHLbesWhWF4cUnyxHMRfubz6gVwAaZVxPBy2MuIiXgTtd6E1E9KLa8gE98Y7HYaPfc7EpIIooqZ3TlfQ6bbjlNzvov+/6yIa8iyjP4+zjDVMA+nKIKcsF/imMzwAgpvBd0poC0CYK2NhcioFQDN9VrEK2tJThuFK4NJd78Z2bl+NLDx3G00f64LSL+OUH1mNBVQAjYZkL+Ntt7QBkG5gfv3cNfC47d9MEgBU6XRaCfosFYC5JEizmM4bQLB/RKLuYgCxHuSSCHNcogHvHotjJsdsAgFIPv6u5sCqA5XXFtMjQwojofevmOVlf++pDh3DJwgraUSQ5t3t1EkG0G5bemDqRSnNHg0GvU6VGbCib2mfHjoFtooBUWqJ5tFrwxrYAsIjx+UtourA8g/LJOD8FRM4BzhSZRHgxj1rAZF8jZD/TilfI7/7oWXUXkHQAz+Q4xiP5qWwn8LX2EQgCcP3KOoxHE/RnaorceO5YtggFAFbVl6jSSlbWF6O22AUDh6cs9I5Hs0bYpwfltSXgyXx2U7FXmg70Hi+XdKFcsFQz+UjlWfns0ZmIJCVwPVnzAb0M8WIlWQoASPOaXPODEzGaKsPCYRNxsl+mTBS57Fhck23Ifh6vf7xhCsDKQGFOkpWBqS1Q2tMaIYgvrg7A67TjW48eQSiaxMLqAJ4+LNsUuOwifv3BDfjl1jb8cccZiALww3evxoa5pTjaO47rf7wV204Nwee04ee3rMWdV8yn5tI8sYnDJmRxf7TQ69xosYyT2GAFRAhyom8CyxjOV++Y+QZENr5ceIBssTivwo+/7Mzk/mrLOUFUL+LEjeLta+shCAIcOvYUMR2PQEDuPJAIMILWoUl0DE9SLzjSddTrALJGvQ5Bf7PR2xBKvE4MMh2eueVTU7OzBSDhEeodtEYm+WkgQa+TFtLsPVHssXOLSb1CsqnCq/IAJMW0Xgawi/nsXJrPkaSBPH2kT3VtzavwodzvRDyVhtMmWhKCsE1iSfkNIvTZNLcM1cVuyrMt8TpwajBMi0Et3rm+Hi+fzHQAf3HLWvzXk/zcXz3Ek2m0VKo5o92jUUiSpKKJnJ5hrpp+DFz+IjdZrNF4lm5v58cAThVBt/5+M1KgpJVTOpQRluIhCvK17nPJa8ZxncPzKDP5+PINS/L1FM9jluGcKQDb+42LAJ6fWD7QbCKi0IO2w0UsYC5eUIFXW4dw354uCAKQSKZpofPj963GtlND+O+n5UX/qzcswzXLqvH4wV7c9JNt6BiOoKHUg/vu2EKTBgjYrhHZk4zUagRWOwEbcuAhsSAdwON9IVy+KOOVN8bheenBqhI4lZaoh1yl3wm3w4Zfb8346Wk3dG1sUzItFxZvW10HAHBwuGNWQMQgbMH5xfv34y0r1BybY30hFZ+NgBUBNBvE7+nFTlUEnBhkPteWKRqkswUgsTEp0umIJ1ISHZ1qQa5DtgDU62rqXY82UUQiJdH3lBx4Wir9kCQp65BQqhmDsirYtARcvKAcgJoLyPIArfImyW3O3msRpftPxr+kc1lX4sGzR/Q96Z4+3E8/+6oiF5471q+yjrKKGg13OSnJ1wp7mO0YzrbaKST0CsA5U5wsmEEbZfiCTtd1qqgq1qew6JmzTxcvHufHwLGHfBIcQMQ1x/r4BSD5OZsA3LSmIZ9P8zxmEc6ZAvDePd2G379wfmG8ixZUTW3z1IJsFFcvrcIXHzgIAFjVEKSeZ7dsmoN0GvjiA3JW7Z2Xt+C9GxrxP0+fwO1/2IXJeAoXzCvDQ5+4kJuewPKrSHfEiDtGYJWzsqwuaOnntFjIjIAvbCmnX5ekTMfNDEd6QpYi4TpHJqnYY0F1AC+eGMBohM/ncmi+QCiKly2sRJnPiR8/d9KwOE4bGG9fsagSdUGPquDcdWYMy+szXVS7MlI91J09BmY/S22WMQu9jaYy4FbZrsw3MAI3Qk0wszmTcaoR1WJAx+iXjCTZ0Zje6+rQsSUiVjTET5J00Voq/egcidCxOsE8TeE8X/Nvwvd75ECPKqWEfN0qyCtiC+NkWu4gXrNMLvi7iAI46MFTh/ULwHsYpfqF88rxzcf0kz8AwK1j72PjcLm6RiKoYIQ9nSMzK1bQM4HOdwwcgSAIqs7vVPK3jWBkZs9T5ucDbHeYBeuxSg6URAV9zIQ+c0We41PPY3bhnCkAt50yJkJfuagwFzIvrH6qsAkCtp0awsn+CQS9DuxVzH6byrx468oafOqPe5CWgHeta8A/XNyMT9yzGz94Ws5o/OAFTbjrwxtQwunq3XH3LtW/SQGxWIdkzyJuUWE71Vi8mmI3Ai47kmkJ0URKtSi7Heb8SkGQCx2zjFcgOwP47lfa6b+1il6PppBxKt9/05JK3PrrHfjPJ47RkR4PJ3VO1oAseHnfJjkejqUR/s/Tx7FSKQJJx9bMD3COQfqKXgewJuhWiWGmIuAB1F0U0pkysgPSG98SNTZbAK5r4neU2zgm0EBGaEHsjiQAAZcdlQEXV5Rzwbxy1b+1hd1AKIorF1dCkoCfPp8RCZEOYK6JDloR2mWLKmhnhtAsSrxOalJuhrqgB+MR43tTrxhPSRwz6NGI6h7WK9YLBb37tznPMXAs2K5vu851NVUYddULlQbCE3NoQRTPxH9TrwNI8M0bl03/iZ3HrMU5UwCaXfylU+TqmWFN49RGnyxI7VHic+CHz8gjJyktlxd2UcC3blqOj921C7FkGlcsqsTtlzbj7T97BY8d7IXDJuC7N6/Al69fmqWkBYAjvWN49IDaVJbss+vmmD93qwTzqSrEBEFAC+EB9k+ocj+tdABJiL0V8+jjTNerMuDC00czYx+tsEI7rowkJQTcdnz38aPYenIQZi/34QN8I1+Cd61rgNMuqt7fJw/3Z0XG7TOJhGsw6OIO63Qa6oNeOnacjj1SNdMxIkTySFy/Y9ynU1SsaQwCUI/gtRwtgvYh/kY9EJI3VdbwfF6lH4IgcDmi2nH7m1eoKRPbTg3hE5fJUYr37+miPn0LqwIo9jiyjNXNoI1ifNuqOvr/pADU4/4RsF2lPzLcVR6ay726IqXJOD8NhC2IxgqoVuVBryvm1hEV5QPsyHs0z7Y3lRybJIJCpYGEOWIOQH1dkQJwTpkXkiTpcgABoLrIhXJ/YfbN85gdOGcKwJk2LiUwiv2xCjLRS0sSIokUynxOjCk37T9fvQCf+8s+jEUSWN0YxC2b5+Cmn2zD0d4Qyv0u/OkfNuGd6/kcjWgihZt+/Iru465vmr6RNTB9j0XCzzzRF8LG5kxRyout0oIYKFtRAp9kOoDsiV9voyTwOjNjxaFwAouqA/jthzYY/s5WE2uOMr+LFiGsdcrxPnWxYmYFY1gA6nIAXbTjMh17pFpmBEwUvEbjLb0O4AaOFdFcnc4PbwQsCqAFGqskbtGJgAOy37clNcWq0WjbQBgr64PY0lKGZFqi2cuiKGC90p3M5bpnN2EBAi5bVEn/TYrxjhH9Q2yp10479zZRv2NGcPNafd4WTxzUNRpRmS5PGhTy+UYyleZ2qwvh3cqikSmoraw1ucCIX63XmZ8u9A7rxBBdFDLc2OZyH7pGI9TEnYd/unph3p/jecwunDMFoIHwsuDQqghzBXnqw+EERCGzQKxuCOK+3d3oHouiucKHq5dU4aO/24mRyQSW1xXjoU9uwVqDLt5n/7KX2r9oeT+ikBkD6MGqXcF0X/98pQN4vG9CJV7hRUNpQTZ8K0pgdtzxzNEMYVqb0erS+MKxHZP3bWzEA5/YouIr8qA3qmTxAUUMkmJW7r/v78VcZmM6MzxpSBo34nHqFWOlPifdFKZi4E1QWZRNdO8b13+uemkg9UGPioMpQKARfVrweJdsDjAA+rt6EXAOm8DtWFcwryeRltAxMolPXjYfAPDnnR3UEmmjMgbWs7zhgR37uR2i6pojKuAjHK9Cgv9+9yp0K7w8C3RXvNnAtLd3PJrFee0ciaj8AXPtcE4HQ+E49zVNd10xwwKG95nv7aPMwMC6f4bj4AiP2y5mlOsLqgIqSywe3m5wiDiPcwPnTAF4NlFkYqWSC8hC6LQJgCAXLZUBF5bWFuPbjx9DMi3hhlW1+Ovtm1UdGC0e3NulGv1qVYvFHofp2NaqXYHfPb3XT0Qrx/tDqtGflUV5IiYXMkc5Pm8s0mmJ8t68Dpsq4UNrlsyzcREF4MfvXYNv3LgcbocNNlHQTQIBgBAngUOLlQ1BrGwIIoXMZpeWkPW5GhHUeYkcBN06Fj6lPicdBZnZABnBZbepjHptomBoqsvL8AXkrhrrp2nUlBznvK8eh01VAJKGakuFH2ORRFZCid5rXlKjFp4c7BrHpuZSrJ1TgngyjV9ubQMA2qW2mkAjCupr2cMUf5F4ih74dKw6AcgRcMQ5wOxc5nOKuh1UQDaD1ppfyx3AzPtSCHNkPZBupvZ2KvYUbvwLZPO32wetG8qbwWgydEaHxlAohJVuLvuZN5X7DKcmWm/M8zg3cb4AzAO0lgJTBbtRzK8KYM+ZUfhcNlQEnPj7vm4IAvCv1y7Cf79rVVbXikXrwAT+6S976b9vXlOXdcI2Kh4JrBreVgX0T7tWQEQAZCxbrvKtMv7dqFKs6XlgEXSNRuiYh10IAy47rPQ6PnnZfFyn4Y3x1JQEVjvSH1CMoT3MgrtD40mmNwauL3YbFqF6KS5eZyYZwEriihFqmBQRonTVW1R6DDJX2WvIbmCvwzM0D7jtqmI3xljAHFW6f+zb1KQjnLlofoXq3/s6RiAIAj6pcAH/8OppjITjWFJTBL/LnmVcrQciTPEpHUO2u0n4f0Y0BFEAnjvKt/jg4YJ5FYbf7x2Lqoo9QFYiBxkxkCTBkrI+H9BTABt10fKBVQr3lOApAwueXGEkijs9PLMCmwgtAOXrThTkqYcR/6/Qxfd5zA68IQpAE4rXtNFcnh+rAnLoLvc7cah7HHZRgNsu4lB3CAGXHb/+wHrcfsk8w85dNJHC7b/fCTI9ddpEfO+dq7JO9Fbsa4w4SSzmVU5PqSfntdqRloDWgTCW1WZO5qIFcUnALauIjboWrO3JKENwtxI15bAJ+OCWJtXXukYjltJKzPDm5TUo8zkxGk3QLmAiJaGIUXDu1DGpba4y9rYcCmd3y1w2QYldk/9dP02fNZZGQAypedFqgDFvje1Y6RlsRxMpbvcr6HUgmc54AKYlebNrKPVS/h/7Ua3X8azUZp0SHuelCyuwtLYIk/EUfvNyG+w2EWvnWOfPkuuSV6yTAtDoUvK77Hj2iPUC8FNXtBh+PxRLolbjBTgeTWYpuPXSg/INcl1o34OKAgn3CEp9LtUofFc7PxFoKjA6oOsZtE8HRsU6+RhJbCnp7h0ziNC0su6ex+sfb4gCUI9PlC8smKKPGg+iAAxOxCFAtjgZCifQXO7D/Z/YoiKO6+GrDx/G8f7MiOF771gBIJvPp6eyZNE1Yo2rYkVNbARBEGgX8ER/CJctynQwrHQhSLC7XhYmAN28YD1eGosrFlWpSN2SJOHz9x0w5UhGLRDp3Q4b3r1B5trMYfh8k8zmu6djlPs+NJQYF2+8MbTHaVON9udP0yCd7X6TTcOls/kZKS2XMkW/S2cGrCciKVU6VyxnrLncB5uYUQCz7951y9WKX4LKIrfqb5wamIAkSaou4G+3tWM8mpiS8TnvgELEK0aHl7qgB6dysCkxi3cEgDmc+D+tilQvBzvfoAWg5utVHI5pvsF65J3sz+9oVq87PxXzbjNMGog5yEGVpID4XXYkU2mc6s/fyPs8Xp94QxSARdPkqJkhn16AZB+QIHeCLllQgfs/sYWbi6rFQ/u6cc/2jFlsfYkHb1XsJrQbzEaO8lKLXoORHYuVDUFLP2cENhHkisUZKxQrUzZSnCUNfvgEZ7GrKnJh0kBoQhoi71hXr/r6c8f68eJx8+SAFyz8DAC8b+MciAJwvH+CKoLZzyscS2Xx2ABjAUgqLXE3moDboRKHWLmujMCOgMn779Qp4OKpNDd3FJC7bAR6XoK9OuT5YsIfZH5tnoEC2CjXtI6hRsSSEvqUovPqpdVoqfRjPJrE7185jU3NuSuBUxxzcCuHLLNCn4V2tKuH6qLsvzk4EVO9ntECRZZpoWeoXqgYOBasB6beKHqq0LsPJPCjOaeDQZ33kHUYIL6lQa8D7UOTMyr0OY/ZiTdEAVhbPL0xlxlW5aEA4uG2i5vx6w+ut0TUbxsM4/P37ld97W+3bwYAHOwao/mjBFYMVq061ufDrHUhowSuC3osp4AAGZNmow4gT/G2uMa4+5WSgHK/C5csyBQn8WQaX3vYOIGB4IlDxl6ABLVBD65aInel1uuMFre3DmWNyIwKwDEdEUqRx4EOhtu5wGSMbAa2A0jI5kZFkV7HdVVjCfwGKSIAcGaIXyzZlI2W3VRbKvxIpNI4run8mol3tIeZg12yMlcUBdxx6TwAwK+3tqGlIgC3QzQVZLDgdYz1srbZZzgRs16IXbLAWJ1OwCuyu0YiKlV4ofzqtNCNgTNI08gX1Ndvfkfefpf+GDjfcXB6LghsTjg5VFYEXKYJIOfxxsA5UQB2meRWLqs3T7yYDgJuh6kxcC5w2AT84F0r8fk3LzbcrAiiiRTuuHu3agG7dlk1qos9ePnkIN79i1dV8WF+l41rGq1Fn8Uc4OmqgIFMIXK8LwRBENCcQwQUeZ56YzRJkrJGwAKA3afNOT83ralTvVe/29aOtsGwpeSTPSYefixuvUAWg+zpHOMKAh492JtlJmzsAahvAXOI2Sxy6S7xwHIAidedkaea3hgXgGkB2Kqj0pxQCs+0lCmcWir9aB0II55Mq8Q6AZ2sYoIrNDSLvR2Za+T6lbVoKPVgKBzHvbs7LdEoWPAKwNM6QiuWR/lau7EZOIv3bpyT9TXeCsL7jDpHI6rDJq/rXAjodQDzxa02QiMjCLJqe2UVRvzifMfBPXOkh/t1Ng2GxCXWFHtME0DO442Bc6IAvH93p+H3r1hozp2bLvRyN3NFZcCJv91+AW5cXW/+wwq+9vBh1QnQLgr40XtW4e/7uvHB3+zARCypGkdUWSRXW+HH5QtkBHxmeBKReCqnzNXO4UmIgjojl0X3WDSL0O5z2TEeNT/xv31t5nMYCMXww2dOAAD+5ZpFpkTpPoNiR4vNzWWYX+nHZDyFa5dmxxbuOTOS5YtoVADqxU2V+ZyU+yMg0z2bKnjddaNEi+mM2fSKJbabQj6Slko/vSdsTEFdb6J+v3Kxeq146UTG0NtuE/HxS2Qu4C9ebM1JCCIIfFsjVpzEgtQiNkH2JLQKnrk77xCpzUYG5A4gy3XVe7/zDb0O4HTFZVawUNMBn7Bg32QVWqENi3ybQe86wz8ksPsSsbdqLPUYKoDP442Dc6IAfNEkdWHzvNwC3KeCEt/0u2Ar6ovx8KcuyolT9/d93bib4f0BwDfetgx3vXoGd/5pDxIpCdctr1Et7Fa7a1Y4QGYpGlZR7neixOuAJMnk+2uW8on6PIzHUoa+Zyc4p109LhqLlfXFqhHp9548hlAsieV1xXj72npDGxggNxWlIAi4VbGEOdgdgl2zaY9MJlRjfJ9DMKQG6I2YKovcdOxopbtshqpiNVHfJgiGvE2jDqAZOkf5BQn7N9OSPIKeW+6j/D+2s7NaY/2hhdtpV3UitSPkm9fWobrIjd7xqCHxXgte4sqZ4UmEY/y/QfiURtnKWrjtIkSOhQ7vc+ZxxrpGI6hk7HhO6/g25hOSJOkWgLkYbU8VK+rVfNDnLfJ2raDFoIDV69BPFT2j/IMV+9ETzt+8Cr+pCfR5vDFwThSAbQPGI2DXDCwkZp0FM1y5uAJ/vX2zYYakFm2DYXz+vgOqr1UFXGgfnsRX/n4YkiT7zP3wPatVP6Nd9PRgJYnDyO4gFwiCoBKCrM0xpo4dRWpHwbzFzmHhyme7fwe7xvBnJX/1P966BA/t60aCQ+pnkatLzI1r6uF32dE6GMZ71md3gFnbmbkm6l29DkN1kZuOn/KhjteaQbNpEjx06nDerECveNT6CzaUeuF22GgHkC0Ar1lmfrCYW57p3EQSKVUx7bLb8LGLmwHIHE+rB6C05pqMJlL42F07dX+e/DTPlFwPrJKahY1TFHaNRrJGw10jEZX3Xs80PiurmIgluQelmdqYVmrWQrMIx1ww12CErdehnyr0aBdkLWQ/68Yyj26m9nm8sXBOFID5DvKeCuZMQwghCsDP378uJ/f1aCKFT9y9Wx7vMhv56oZi/PT5UwCAf756Ib58/VLYREFFVrfaEbXCiQmabPi5YCEtACfgdtgy6k4LYOPUBidieN8vX8XTh/uQTkt4/pj6VF/qdUDiMqMycNpFXL9SVlBLkoSvKgX19StrUVfiwRfvP2D4+1OB32WnRWfPeMxQTGEkAAH0O4D1JR6MKyNanwFJPRewxbfPJFqOl+VrFbwUEFGAygMQkAUgkiThcHc2Md4oOpFgXZP6Zw51q8dr79nQgDKfE50jEWpBZAbtoeQL9x3QJeIHXFNblq/VsbdxcC6kntFIVuRhfyimSjXKt1CBB9L903a8ZyqIwud2qO4zK5GSVlFuYLI+mOcCUO8oSqYGbAM6npRkr0xOV/q8/98bC+dEAZg4iznABIumoaacW+7LmYv19UcO43DPOHxOG1U/lvgcePxwP2yigO/evAKfuKyFmkazCtkltdZEMVbe1ul2PlksoEpgeWNckcMovH0orBpzv3xyCB+9ayc2f/sZbDs1pPrZT17eYhp1ddWSKtrNeuRAD3a0D8PtEPEv1yzE5+87gAnN+E+7gRHk2kV5/yZ5DPzM0X586IIm3Z9rMLHI0C0ASz2IKM896DEXslgBayliJi7qHZt6V4nXKSLvOztinVfpx0AoltUFJQkIZrhW0yXcoxELeZ12fPjCuQCmdvgMx1O4b0+X7vf9rqkdqq5fWcv9uo3TpRyNJLn2WOz+b4UmMV3oFYC+Kb4HUwF7TejFJ04FJUZpIHmMnTNCRJnikC6wKGS4nTzDdjNay3mcWzgnCsDZgOl44c3RiabSw9/3deMPr8q8P9b6YiScgNsh4he3rMU716uDvMnPCbDGrUla9IjSGztNBewIGAAuy0G80zseo6fXCr8LH71oLlx2MUuIYReFrI4OD6QTF4mn8K1HjwIAPn5JC15pHc7qKAL6fLr7dutv9Dy0VPpx0fxySJJcTOktx0YCEAAY0BFbVAXc9DBQnQPdwAi1wczfSXFGTiym2vnQSwEhsXESc1xpqfBTpbOfudZ9Fqkg6zTiDh4v7JbNcxBw26dklhyKyr/j0eEhTMUoWBSgSx/RO5xUcSIs2dt+JpJA+nVMoEvymK9uBvbgOG4gYMoVRk4BJ02iK/MFovwlXFKX3UbXV96EJxfO6Xm8/nHOF4AzdTkvs9hV48FsnMeineH9LawKqBSCxR4H7v7oJpWRMgHZ9K22+K3GFa0xIdXnAiK46ByJIBxL4iqOGtYIZNwhCMChrnEuLyaZlvDgXr5lAkFVkYvmwv7ixVZ0jUZQF/TghlW1+PJDB7m/o1cwbzuZO6n81s1NAIA/7+zALZsauT9jds1065h4B71OWkg15slnjR0BRxLGXoBTpWvoCQVI54/N5Z3HKIDZy91qZrcoiqrNm8chLXI7DDu0Zrh2WTXtzmihTeSwAqNiQ++er+MouOOpTNFnNet4OiCfq1bBzx4qCg12jJ9Pg+ZSAxuYgWmIoXIBWfdJZ8/vtlMLGN7n6ypwatZ5zC6c8592PpSOVuB22nNKBWBh1fA0mkjhE/fIvL+VDUUqL6faYjfu/fhmlTXFcDiOu15px9t+/DJVgFl9P6zmAFsdJ1tBqc9JBQUn+2VD6FzeU1IADk7E8UrrEDwOkcsjNBv/3rSmHjZRQPdoBD994SQA4F+uWYivPnwYE4pqU+vxpbdXnpjCSf/yRZWoC3owOpnAMp1YL/MOYPYGIwKIJTMb/KLq6ZlAE7CF1dikXLzonTPiqfSUChy9FBA7p6nXUumn/D827WCZRfEToDbInoilaNeOxYe2zFUZJ1uFwyZmiQ8IbIKAOHMxWW3IbGkx5vXyNvYKTtTaJKNK1gpXCoEBRZCkfawaAwuVfKOJmcBIANIm4i6rCBj4Wk5YiIm0CqPPSbsulXgd1AKGtw7mwkM/j9c/zvkC0G1F7pknTNW2wGoH8BuPHMGh7nGU+pzoHcts8I0lHtx7xwVoqQwglkzhsQM9+PBvX8O6rz+FLz14CHsZQ2K9nFYtOoatcWFq8sgBBLINoa2S7IHMgpaWJCyuKcLXb1yOMWakYxcFfOTCJtO/Q8a/337sKKKJNNY3lSCRkvDs0X76M9+8cbklvsxURoQ2UcAtiiXM77a146bVNVk/U2fyvo9xLHycdlEV77c0T8U7GwdHCi6jRoqe8a8R9JT+2ru7IuBCscdBO4BsR+dNnM64Hi7QFFQ8QUmJz4n3beR3aLnPVbleSrwOvHiCrzZtKlN3vqzWYNevMvYNreB0o3ij4TGm0JVgLYt7OiDKbm2hUlcycx1A7UFoX4d1420jCIKge4DNZxLcqAXvQvI5lngdutMBQP/gdh7nJs75AnAmuSRGzu9GsNIBfHh/N37/6mkAwAXNZZTb5nfa8NCnLkTn8CTuuHsXVn75SXz87t149mi/avMg97XHYgHYZZGsn+8T4wIND/CilgqjH+fC67Tj/jsuwAsart7GuaV45ki/zm/JKPE6MB5JYGf7MB7a1w1BAD51+XzV6PfG1XW4amm1pTSVqYzRBidiqAt6YBMFHOoex4sn1CIWmyAYWrhIkoQQx1/O4xBxuCezubWYWMlYhXa0ata17Z+CwXirTgGoHdm1VPgRiafQNij/PPvuW8m/JnjrCrWgYs8ZfmrMxy5q1uXYaUF+TICA7a1D3J/RmrRbvXoubjGOgKvliIaGOYcTrXiIZxidTwzoJGI0lhbeBJpAy99+5qjxGpELjK6NyTx1AfvGzKc1ZBTsUZoUvL1qhoZl5zGLUHiDvLOMXPh100Vd0IP2Kbjn15soOtsHw/jXe2Xe38Xzy/HwgQyH7YJ5pbjwO89xFXu1xW5ctbQaly6swK5HjmEilLB8k/canBIJCrFezGcygQHg6uXVuHvHGaNfoXDaRCANFLntmIyn8PhBdRbvtcur8cUHDhn+jZHJBG78yTZaKL99dR3ueqWdFlSVARf+461LAMgm2NI0efL941Ec7B7Dgc5xHOgaw8GuMfRqCiStcMJsjK9HZPe7HTjUlaENmMWiWUWVRnxQ4nUaJh1MpQOoR0nQprm0VPpxrC+EtCTb3BCjZQFqsr8Zmsp9sAmZztSzx/px+6UtWT9XWeTGTWvq8JedxmlEgEK6F2TPNr1zwYHu3A16nTYBdhPuVlOZFzvahlVf4ynUtdSB0XCCqxbOF/S4nfnIF7cKLX97Xw4RjmZwO2yIp/j349BEHN7S6d+De8+Mmv4MNRZX1o5SnzNrXbHaHDiPcweztgCMx+Oq/+phYNy44FpjMa7J6uMZYW65Dy+f4p/stbBD3picQtrQmoLl/dUUu7NGR08eyXS5RAFYVleMG1bV4vJFVap0jFfvz+316S3MLKwYCef6fpIOIEnv2KDxZDOCxybR0cp9uztV/C/AfIFz2gVcs7QGjxzooQrIxw/3qaLNvnXTcgS9ciEhplOwUv+l02kIgoC+8Rgt8g52jeFA1xi3GBKUJIuGEi9eOD4Amwg89ZlL8Puf7wVSgM3kUfUsYAJuB9oGMzFwgsm8x+o94XbYUObLFH1+t92wANQ7XBg9XpeOPYcE+bWQeorl/wVcdloA8u4xs9dXE/TQPNyjPfqF2Z1XzLdUAJLPLRbXv7em0nHT8yBlX98Cjk2V1kAbyP5sRibjlsVCU1lD9dTq8yqt5wBPZ80GAIfdpkRJyv9uN8mWz+Xxij0O3QPZUDhuyuW18lhPHeN3LJ22DJ+U+ImTTiAvmaYi4MrLPpgLzj/e2cWsLQAJZ8GMg3K/gZ8WAFyjY4461cczQi6kerL1mpVQX/37IRzqHocA/oLtdohYN6cU79/UiEsWVMKjQ0rP9fUNWYgq8huQnLWPaxULlLFk91gUoWgCAbcDbrtoyRqDJUPfo+ka+pwi/rbT+Fp587IafO1ty7D1xCCGJ+PwOm2q4q+pzIs6hpMoCOrX5hAFbm7rjT9+GV1jMW4AvCjI0UzL6oqxrK4Yy+uKsaS2iL63N/7kZew5M4qH9/dAUgyPza4ZvZipEq+DXkNW7B5yuWaqi9206OMZzLI4rbPBGj2eUYSc3SbQUXtLpZ92ftmPopIjeDB7fUtri2gBOB5NIppIcQvJ+hIvgh47RiPGxRt5x1M6IgO7ODVu2HXLsjmigPr1La7O5nsOh+Oq4hmQebReh4hJRaGcy7g+1zUmmUrrHhQCOXQd88FT9DrtdIpiZoCdy+NVFbnRMcI/vAzpjL9zfazDXXzzaodNVKm6gYwKP8m5BhdU+SF1TX8fzAX52HfPP97UMWsLQNKdMOtSPMfxZGOxpMaa8s/q4xlhVaP1+DJyOQiacZ4kSWgdDOO5o/34/SunaR6n9vJZ31SCf756IdY3lVp6zrm+Pl5WqBYVAX2ne+3jWkWx14GqIhf6xmM40T+BNY0lWFZXhJ2nR01/l7xH8VQarZqoo4U1Rdjebtydfce6BvzouZMYnoyjqcyL5gq/SvjRPjSJa/77JVwwrwwf2jIXNlEEu+XrJafsUxZoUQDmVwaUQq8Iy5Riz0g89IHNTdhzZi/u3n4aVwOwARBNRsDDYT4pvMwvxwQC1gyRc7lmaordOMQRSvCgJzAyerwxA6J7kpmntlT6aQYwm53MO5yZvb5LF1TiiUN99N9He0NYpeP3uaWlHI8c6OV+j4A8SzmFQa32BawVf+xYmuDGNXXcn2VfH6/TNBlPwWkXsuLmvC47JhNyEZRLZFiua8xwOA5JyW6ejuB4Oms2QZnPSQvAiEnGcy6P11jmxU6NkTiBlTg4K4+lV7DyqCJkP5ngdCXXNZViuHv6+2AuyMe+e/7xpo5ZWwA6nU7EYjE4nca8nZP9xguU1Tfe6uMZIZc0kCRscCENm92BSDyFV1oH8fyxATx9uM9QpQUAK+qK8dfbL8jpueX6+oZ0iggWzRXmPJ2pvJ8LqgLoG4/heG8IaxpLcPWyaksFYEqwQUSCu4CXex2Gm0xd0IPqYjd+vbUNAHDV0mr84sVW+v0vvHkR9nWM4fFDvdh2agjbTg3hPR4JLPtNb/+u9Dvxs1vXYXF1kW6HVg/XLq/G1x9xom88hqhbhE9Imb6neh3AioCL2plY6d7mcs2wSuCoiYFwn05XyejxjP4m+Vj9LjvKfU4cVQrASeY6uJxjKm72+t68vBqfZyL/dp8e1i0Ar1lWY1oAkns+CRuCPqdhV1MPvGtYz0iefX3VHA9ECfKYPJZU3+ssVYKIaawg1zWG0B98Lruq056rFd101myChlIvLY7MitFcHo83eicYtDBlIe+pEbQHCS1IgS1A7gCKAl85/KbFVbh/5/T3wVyQj333/ONNHa97FfAIx+7ibMFuF3P2HYwmUljxlSfw4d/uxF2vnOYWfx6njS7KAoA/37Y5H0/XEBELCjW9zXC6mF+ZyQQGgGuW8kdcWpBOEK9YOKyTu0pw85o6fOvRo0ikJGxqLsNfXsuMkN+1rgH/cPE8/Ph9a/Di/7sMt13SjGKPAymLbf3JRAprGktyLv4AWWX9ng1qqxGza0xvrFZd5EI0LpepuQgirIAtMEImaQpWOh8sYsmUrmiCRUulHx0jEYTjKThsgsrnTJt/nUyl6fPQ+9PFXifcTFzW0wYK8nkV1jlrABA16TLpQftciywKeZx2kespWMLJ8nYwFdgZnfFlPkB4xg5RvQ2dDTNi7WE2X5FwjaX6dk2dg1PPxbYCMpEg9kOEs91U5qPrAIu5OV7D5/H6x+u+AMynn1I+YKWzwiKZllRWIYIAlPsyi3K534kbVtZQUcLHLm6eUiGRK3hcNi2W1+UvBo4FyQQ+0S8XbfUlHkuKY1KQ8Z5554hxV7WxzIunj/RBFGSlHOFz1RS78W9vWUx/ri7oweevXYxXPn85SrzWiqjJKW72BO/d2Kgq+szSXIZ1Cqy6Ei/l/tTkKQaOgLWCMfMlG+OYKhtBT5CkfRdamAQQrU+iVmnfOhhGQnkvjIqxRqa7dsRgxG2FDsEizLHpMQOvgMvlEMa7Xos4edDsuWZgCpY9VjFAY+DUd2whVcd6WFKj5kg+ddi4m2sVZT796+JIrzXKxFRBDkDkunEo/zO/yp91eJ2dA8rzKDRe9wXgbENljhsBwaLqAL7w5kW47aJmDCrj1+oiN/5y22b8WVEY+pw2fOHNi43+TN5gpbk1t0BWDdpMYEEQuJ0KLbRxUlaxvqkEP39BHvdevKACW09mlNbfffsK7obkddotdyqmG6hQU+zB1TnE4ulxghpLvfS5zLUwvs8FZARMxU0GO0o8mTblWbHgiZ94YPl/LMfRZRezeJNsHnQ4ntRNU1jNFFgjkQRVUWqRS0fVYRO53WOz4QHpzLFX3c1r+fw/Hnjmyryikn2NU43us4J+RQGs5c7yBDuFxmpNIb2jnc/byxVG10VnnrqMeqBCD+XAaBPkK6eWEwHoOB8B94bEOf2pnw3eZW2OyRg+px2P3nkRHv/0xQi47fiZwjurDLjw6D9ehM/9ZR8txn5+69p8P10u9HJttSj3F2ahJh3AvvEYxpQN6OKFuRtCW0Vd0IMT/RMo9tixlzH8fc+GRpoJfLZx+yXzLJ/S+3WsNaqZrp9VcZRVaM2gzbqjes+Rh5P9/PG9toRqqch0ANkihpeTe4hRTibT6pQXFm9aonYRONHHj/aziYLl1CE9c2Czg0JUUeayd+fVS6y5HADAnLLsEV+EM0JhO9bT7V4bgXQAtevNTHq3ErRobGdO6nzOucKoADSjSkwX9G1VNhBy6ODZdwXz5Al6Hq8vnNMFoFWH/nxiXo6dlYDbjiW1Rbhn+2l8/j45baLIbcdTn70YXSOT2KOYki6s8uPCKaRiTAVmNggEVpIwpoKA24FapaA4rmz+N5pEXU0VLrtIN/+GEi8d/dYFPfi364y7rbk0HK1YPhhhRX0wy3BZD306HTPWhmZFQ/4ynIEMB5C8JcUmCTy5mEFbFSKwHoCsMbp2cweQpVj+xUutWT8DAJcsUN9zu84Mc38OsD665KnFrQiqtLCJAtw5xE/y3gdeVCGbe8xmR+cbJAVEm5bTVD7zXDSbTc3fzuWAYoSgwUEolgf+kpXPh0xGCDc6wuFIN5XPfNF9Hmcf53QB6D0LzuZaLokV/Pi5k/jC/XLx57AJePhTF6LY48Qtv9oBQB6r/eX2wgs/CDotEL8LVPtRaMfAG5utG0LngvoSD8ajSdQG3TjIFAXfffsKQz7nfbs70adsEmwmsJ693n27zY2C8wWeCEQAcKAzM/asC+Z3wXc7bKpuh1k3LBcFrFEutcjwmwJuOxVRsbYx2oOTJEmqETAA7GgbVmVmEzjsIgKuzDryFGMLo4VVTmiSUwC+e73xAcevPAdWoVuVI91kCSf7mTfiZQsy3nPNF8g1oOUbn40OIAB4GW41L1lpKjASbOUja9nKYZ3Umcm0BKdN5P7OmjnWYxLP49zBOV0AVpwFLkmuytjxaBL/+cQx+u+fvX8NGst8+MnzJyiZ/r0bG1DMIWsXCh3D5uq0QscGUSGIMopxO2yqQitfIBmzIaZguGXTHGwxyFadjCfxxQcy2cDsIq+3nr90cpD/jQJgjLOpO+0CDvdmih4rPoC5gh0xm9kvWbnGCHoMcqlJ7TCnzIdjymGhPuim41IAuHC+enPrHImo0hnItfx/Ol3AFsbKQ1s4srC63mi5qgKAZw7rF5ZAZvwbZDqrVyzOtrYxAo+za5ZHW8D6TzcHON/8VKtg83GnkuGtB6MiUC8lxCq6LRzW2Vcyr9KPM5y40ssWGmdJn8e5iXO6AJzJPEn6mDkuXuwCfNslzbhicTVSqRT+64njAOROyjduXJHX52gGvdgtFmYjvulC2wEEgAYDS4WpwGETIEEuXEjWb32JB/967SLd30mnJdz2+10qbhQbq6Q31DnZZ2xDky9MxpPcoDi3w4Z2xXaiUMyI2mCmANTG8GmRi8GwlXHxwqoAjihxbfWaDlKzxt6CjH+J/YhP6fQ+dqCHW5hunJspIIfDCV3BSC3Ha88KltUVYRfjc8krzUknLpzIFPdaeyAzaJXRgLUCT8/gfLrQU3fPP0t2JFo/xZgFKywrMIrMnC41ZFuOB8uFVX50jWZf42sbCzNhOY/Zjdd1ARgy8QDUen/NBERRpHL7XLB2Tgn+6aqFAIBbfv0aXZj/992r8/n0LKHPAv8lV7FLrlhYpfYCBICbVltXPFr5BBIpCXZRQC9jdfGfb19JCwIe/uvJY3hJk8dsJVYtV++7qULvcfwuB8155eWA5gOsF2DYZIRm5ZBBMG5iKwOo+X/s67OLQla387DSxSOfm10UcPGCCqQl4FeKETiL65ZnfCglAG3/v73zjpOjrP/4Z7Zf2b3L9d4vl14uvXc6SA8gJSCCCoqK2EBBBfUnIgoqoiggoiggHQQChAAJIZ30drn03OV6v9vy/P7YndmZ2al7s7ezd8/79eJFbtuzZcp3vuXzkQle1Xxd5ZhfnQ2+GYc4gE8KBRAumwUdveF7xxXoG+SRy/raVa4IlFxYoqWr3yc7YJKmsZRuNKwNJctag7L2qQqyXUqe2VpQc8ISMzrPLZl1tNEp4BFJQv/qL21X7qvSMyFnJHp1rNKT7Xj06qmwWy042NCJdYeClmVlmclYMX7oP4OW/qyxOnyPo4FtWG/q6ud6Vi6p1T4IojVnwR8UWjW3TPGi4YXNx/HHNYcibpfLCPHpN7CkpIRcT5DbZeNE02NR/gWEbiBqAa+cG4gUvRKitWIqeRqAfBFzKfmgXRKB4i0LKgAA/954DG2iC8uJRWmCC4qN9dKDIGUyjhxqtKkFAaHFK3PCr6914liMlHC02gWr+PswAjb7lzIEmqZaEfdIrt2vL7iSI0NBLWGwGcC6Jn3TytU5qRHl7XgMS1LMQUIHgO8oNGQDQMGo+DQT69UCfOiKyVxG7aq/fMrd/uJX9dm9GYWWxuJYuYCwpDhtKBoV/E7YMjD7t1E4bRb0hTqkSzKS8d1zamQfu7G+BT/47+fc39luJ5jQmdkXIDErq+pF7rdLT7Jzje1a3SP0wpeCUZtw1DppPuALaHJcKc1I5oTD+ZOtpRJtIOEAMPyjzavKxNh8D3q9fjy74WjEc/j9YXLHHa1T2mJe235C8f7eUP9fNS8ArJaY6NWCWK4HUM8Ia/2t9MAGgGKZlHjuR7WlQi93rd7Waii1Bgw2A9gpk2lnv0fx1yl1bko2URBOGVoSOgDcb5BWk9HoCVRSHDYsGxsU+f37usNoCmVOLp5agMwY6eypoeWAPzrPWBkRyTVCZeADPEHopCgzH1KwQQoD4NdXTEayjKTG0eYe3PrMZnj9hAsELp9WxE1C+wJEU09kIDB42Qc15E4oGakO7vPGartiS8DssI6U/h6L1ub3Jg0ZEgZBNwmvn8Dtsgl6y2aVCXubmrv6cbqjDwwjlDFiGAa3LCwHADz5SX2EvMZY3nT/58fbJN+HXjcQIOgT3aUhw8kwwMm28Oe6Ylp0skiSvsESQRd/hue4joEdrbAyK+LgM5r2GaMoFh23jbKDU5IGG+x3K9dqy7oF8X/HFIdV8sJM6qKAMjJI6ACwNQZXpkYgbjpXwh3Kxvj9fvz09T0AAIfVgt+uHPrePxYtAWCsewCBoGURIAz0x0tIWUQDf8O/cV45ZpZLN0F39Hlx09Mb0dI9gJo8Nxegr5xeDFtoiMAfIIIJWDk21DUP+n2r0SJjMJ/tdnFeydEOK6jBloBZa690BfeWAV9A0rNZzNEW9WGRLLcThxqDjxub7xFkRRaKdPzYrE5ZZkpE3HPBpALkp7nQ1NWPV7aeFNy3oDo8JdnSPSAp3xGNC5Camwzbp1iWmYIdJ8ITyHraIfhIeRYPSAQF/O/mkEYdRj2wQbp4IlruImwoYBhGUA5VszTUSk2ufLvMzhNthqwhht0H+QHg6Dw39kl4ok8sio2lJ8X8JHQA6I19QiUqxhdqD1LYCbtb/7GFm/R78PKhnfoVo0UDS4s122CpkZgE/vKCckNem910SjOTcdfZ0qVfnz+A2/+5FQcbu5DncXFBwJyKTJRlpXD2SQFCNAX9r+8wxl9UCbkMYK7byfVFRiM6rAU2k8C2RKqdzOWmQPkcbFQPPiqyUrj+v9LMZIEUz2jRyZcNAKU08exWC26aF9y+/vxRnaC38/xJBdy/A0RaKzPFaVOU/JDihIrNHRu0Lx2Tw5WCGQTF0qNhrIROaZ/EgZTf1qpViFsP7G8v7kfLiNMACAt/AMwIoWYAyFfQ3KyXkGQxgvA+EN4ea3Ld2CdRNVs4Wp+cEGX4kNABoFmZWjJK/UEher1+HG/tweo9QTeKgnQXvqBj2jUWyPmd8lHTeTOC0bwAkM24LKpR98TV+s4YAL+5cjKSZHpgfvb6bqzdfwZJdisev24a3vz8FADgqpnFAITZGy0OMFuPtml8Z9EjlxXnl6iNyqKKcdmtggsDteZyLW4L9Rqa3McXeDgPYP6KFgYYJSpDszp+ct/BVTOL4XbacLCxC2v2h+3hCtKTwE/WbayXzuamhASbtVYytSqssLqYgHJmVY3q3MjtVPwWxG/dqFIoH1baR1xqz4tzOZLf60nI4IWaAeU+RyknFiPg3jbv/Y/OdaPuTOT+tCSGNpsUczNsA8B4NhMX6xg+6fcFcMWf1nN/P39rfAY/+KidlByxtgEJUZmdCoYJHiTZ0qvLblUN8LQesr+8sALTSqVLv8+sr8fT648AAB5eORmtPQM42d6HtCQ7zg5NZvMDHC1m6idajc+kiJEr31uY8LcyJgq3Gq3k8SaB1VwkTqtkvwBtrjQ1eW4uA9jBszGTypKxUjHjZSRU3C47rp4V1Nf781qhMDS/7eGtHdKDIGmhNeUuKqIh1WnFcZ52m1y7ghaKohiMG+ygghRsBrBf1AYQD+1WPuWiHsndCsLfWslMFQaA/JiydxBey0rBKXsPP8Fak+fGEQkJo2izyZTEZ9gGgPFsJgbUe3tYfP4AToVOhGeNy0WhwZOuetGS/UtxDs3UWJLDytlCHeCVgdOSBt8nVJGVgm+vGC1539r9Z3Dfa7sBAN89pwbnTMjHvzceAwBcMrVQUkalUYOsCSs2HUvkNBz5Ysp6LlD0wu8vVHOZYF1YlDilIUgclexAa48XVguDxnbe5xQJh3f3+zgNP6Us6Kq5ZbBZGHxa1yIY+JhclM79e7vMIEhWaMDGSNeauZVZeJcXcH5pXlnUr6XlZC8OK/jewEbBBoC9on1irI72mVgwVrRdsJWZwSDO2PK/38GoQ8lNAMtRk+eOyUQ3JXEZtgFgqjO+VzXpGp0y2P3fZmHw2BfjN/jBomWwZiink6tzIvsAxY39LFrt6SwM8NCVkyUDuYONnbjt2S3wBwgurS3EVxdV4kxnP94NWXWx5V8x+xu6VDOjsbTVYmnqkP79jreGAylbDDO4/BKemn7cEQ0TkHJ2YXwGQmXEyuwUHOeVK2tFrRh7TnWAECDX4+QCNSkK0pNw0eRgz99fPgoLQy8dE24/aJLpX8wNff7BeOiKQ8fzJubhIK8Pb3pZ9BlAAHDZ9AWnfRqmlPXCXpCIQ5iqOLmAsEwoFGaGjWjbcNqUj0vROq3oEZdPT7IjM8XB9ZGyxNrSk2Juhm0AmB+lJpdR6JWE+NnF42G1xn9nPK6h36c8a+j0FWvyQpPAjeHelTuWVkk+VosgMwDcsrBSsk+zpXsANz21CZ39PswoG4VfXDoRDMPgv1uOwxcgmFKcjjEy8jdHWnoG1ZtlFM3d0hkz1v4pFn7KfPhl0uZu5cyRlt4yNReQZIeVa6Qfl+8RZDgWyUwAy5V/+dwcEoZ+k2cPd9b4cAAYgHTWtyj0+bVMOMsh3opH57q5gNJuZWCxDO6wnevRV2VQs/XTiz9AZKfVq3NiKzCvxlSRvqkey0IllPa61iiFtusl+vnkGJ2bKnkxlZES/2MWJX4M2wBwTH58ryRLMrUHSWlJdlw9szSG70Y7Ul6oYiYVpsf+jYTgBkF48gUVMicJr4YAsCo7Fd9cXh1xe7/Pj688sxlHW3pQnJGEx6+bDqfNCkIIV/69aoZ09g8AWroGNOlpNUj4cBpFv88PqZYiuwVo7AyeZOw6sz96YeVw2DhTqVyvpWwuzliIKUhL4jyAq3NSBZm3yAlg5QEQPuMKPFhQnQV/gOBvnwSzgClOG1y81o4NhyMHQUpD+320pb3SDOE2VJ6VgmO8Pkgj5JdKM/W9htFewM3d/QgQ6T5t8dDOUJMjShwM1qmDRaklKVqbyPf3aS9Pj833SPbTRisoThkeJGwA2NurvNMsronvaLueHWtqUXz7Xvho8WiVktCIFfwSMNv0zDCMpNyGWFNMDAPp0i8hBHe/tBOf1bfA7bThbzfM4Cb3Nta3oq6pG8kOKy6YXCDxqkEG/AFNVmBvqbjXDIZWmYyby27lyrFJ9tjqrLFBMDsgk64g66E2Aen1B1SDj8qcFG4CWEyhKFgKZwC1bb9f5tnDtYfeazlvSOHNHaci1+T18EbThtznE37e5WNz8BFvGpnvSxwtenRKAe1DVVphrSbjJXSvBj9Y6zFIa8yl6AccXZC5oU67V3FNngfHJCRn5lfTCeCRTMIGgK9JHHz5LInzhq2lzMSy10SOJlomM0t1ZDcHS0V2CixM0DmCP8igRXhZzG1LqjBZwsLu8bV1eGHzcVgY4PdfrEU1L3P03GdBW7ALJxUg1akcPGkZjvnQIH9RKeROJClOO7pDzfZGDNAokR8KutjATckhRa2J/YwGmZiaXDdXpmvilX9TnFZYeBcJA74A10eqdd9cUJ2FMXlu9Az48exnwYlwfv/dtmNtEc/JTg1vl3pbAhgADSIf7gXV2XiXN4hw4yAGQFjk2hiUkBKLjha2FJktCgBN4qYo0AI0KvuptB9EmwE80aY9cKzJc2N/Y6QI9Irx6rJalOFLwgaAb+1SDgBT4iwoWluarvmx0R4AYoEWcd5oPU+jwWW3cpk1/iDI5dP0aSVmpTjw9WWRvYNv7zqN//vfXgDAvReOF/SNtfd68cYOofafFOyJq0eDpAP/MxiN3ISf22Xj+riUhh+MgA3M2fOmS2EafsAXUAwsjmgQyU1PdoCQoAsHX7C4IE2Y/TvY2AWvn8Djsmm2agzawwWzgKw93NkT8rj7Gzsi95UcT/j7LdSpaTe7QjjcYbMwmFYySrBOtnvw+944DTJA4uxlm0rFRQ/sMUYsJq9XRDtWiANTI8rA4tfkczpKeSg9EjKjc1NxUCLRUJoRX9kdSnxJ2ABw94nB6zPFkqxUl+YrWm+AGCI4agRaZALUMmFGExaEDh/AvrqoUtdr/OX6aRHTeDtPtOObz20DIcD1c0pxw9wywf2vbjuBfl8ANbluTJHIHLKwvptaJEuM6imSQu63S0uycZkMsd+p0SQ5rILMl9pWrTTlq8Xrmx22GJvvEYjcThS1VbD9f+MKPLpEzC+YVIA8jwtnOvvxyraTmMsL0vwEXGmYhS/6K+4nE5PqFB5+ieiIMaNsFBo6+7jvMMUgbcHiDPUMvkMUuIs/52BgA0DxtiFeM16Ui7QI39k9+LaNEoXvfHuUWoNqOVl2a3LaLHC77DikQXaJMrIwxx4XBS3d+jSQ4oGeEfsjTbEbDtCD2kQag6FxAeHDuiDwB0FcOjxDk+wWTBUJPjd09OHmpzeh1+vHguos/PiCcYL7CSH412fB4Y+VM4oVPzObuTjR2qMqQC7u8TISuUwyX/utcgiavvN52Te1IY4GhUEQtQlMq4XBsdbQBHCBR1A+XVgt7AHWMwHMx2GzcGXXv6ytA8MwcPMugNaL+rDsVgtc9pBHtMpP3c/7bpxWBluOtgruXzA6G1uPtnB/j803ZkI2mml1pd9JL5wGoCiD5XHFXwUBACaKpGA+NcDDuyZP+Nvx+wy1XOhEA7v5sRclpzuE/d0mibcpcSRhNwGvORJmiogPtEqxwYtbj8f2zWikXUV2w0iHA62wPXniHha7xq1X7PXbO+DHl/++Cac7+lCVk4rfX1MboY2380QHdp/qgMNmwaW1yuVme+i5zd0DcZWCkcsAJvN+s+rcoQgAw5kvNRmX4wpT52ouIKOS7dgbuigYk5sq8G4dIwqWduscAOFz9awSpDptONDYhTX7z3DSRADw+ueRrShsgNjZp3yRyo+Nr5xRFFEOX1CVjbd5Q0NG9P8BoSEqlQsVnyh6PWxg9ogNALsHRNlTkwyFiPuEDxgQoImHAhne2eBMZ2xbgEoykkEI4fqAWZT6Eikjg4QNABOBXFEPkFLM+q4BZQYj6OhVPmnFwzaILQEfbOgSlMq1aoZdO7uM+3cgQHDn89vw+fF2jEq24683TJc8ED63MTj8cc74PMVJViBcuur1BgTZLzmMbKjnI2fZxe+tqsyKvc4aXwxabZDjkIKWmZpMTEFaEvaGJGDEFyb8iexAgHCTwnozgADgcdk5CaC/rK3DvKos7j4poWBWyqRDwUHDKYrABkSZ4SS7BeMKPFh/KJx9Onvc4CeAWcT2ZGLEQtYHdWjOqcF6QPeIApLi9KEbLlNicrFwGzltQPZT3LvpC4SPAd06HT30Mr7Ag6augYjzT7xdpyjxZ1gGgENkVauKUt+HmKMa9PeGggGfcmNxftrQX6WXZ6XAZmHQ2e8T9NndvlS9DzAj2S7oLXp49X68ueM07FYGj183HaUS0i09Az68uu0kAGXtPxb+62doGD7aVD/4kpIUcuK6fFHiEp0acNHAt4Pr9QYUB0GUBj2aVIajcj0u9Hr9cNktONIczhY6bRaB1M/Rlh509fvgsFlQkR1d0/tN88thszBYd6hZoC/Y0BGZpWRF4JVcdfjlTiuAtQeEpeRZ5ZnwBwhnH2hhAJuBNTup7Z6POFjQ4tqiFS4DKAp8Rg9BdloLaUnCfdgIK7wMkb4hP77Wol8qxqdDnHtmWYakvJfYKYcy8jBJqGQsTpNEgGIhWiV6BvymGARR61uq0fGZjMJhs3CN2fwp2nMnyuvysXxlcThIfHnrCTz6/kEAwM8vmYiZ5dKWWm98fgqd/T6UZiZjdkWm6hoMwj09Wn7Dt3adVn1MNDTJDFR08bK6DhVbKiPIC2VB2e8k1SXfr6k0ONOuMnnKStrU5HmwgzcUxp/EBcL9f2Py3Fy5Xi8F6Um4YFIwA/f2rgaugOcLRAYybBa4s98n22d1htfDfO3s4ojvYcX4XOzj9bxmGiyQXKlTC7BBw4CTVrgAUFQiry01T0Di4GVovYMx7A2hlHGN5rCvpqHJZ1rZKBxvjQzgjdCUpCQ25oiUDMYThzKlFJOK9JWbxBpgQ42W0qTez2QU4Ung8ElRyzDK9XPKAACbj7Tguy98DgD4yqJKXDFdPrPHOn9cOb1YoCWnBHuF364hW7D1SJum19SLXMasLXSijUaYOBrYHkB2OtqtEAA2KsgOqQ2QsL/NuHw3DvC2C7HMiR4HECVYe7g3dpxCOk9PUTwkUJzB2sEFkKxBeHtUSuS08MLqbGw6Eh4A4ZedjaBa54Vcm0ovp1a6+33oDg1/DIgCH7EPbzwRKx14VSojaqgNBOptC2nq0h6QZ6U6JR2ephabJ+CmxIdhGQCyB+B4oyQdIsXHB2InEqyFVg2K9JVx8upkhxfEE3NKxvYelw0uuxXHWnpwy983Y8AfwFnjcvFd0VAIn4ONndh0pBVWC4MrphVpfn9suV+LpqPU1bgRNMn027GZtKGS2WADQLaPLEVhYrtNZurcJ3IBkfqV2cnUcfkegV3afFGwxGYAx0XR/8dnQmEa5lUFS7OpzvBF5mvbTwoex9dWE2cjgcjPsla039utDIozkvHS1hPcbd+Q0LAcDFqCYf77NKpPjc3+JUsMkxmhcWgU2aLfjd+LGQ0MwygOAWqR3+KzT8b9RoyVCa59sDGyh9PIlgJKYjIst4B4ZanEuF12VVkQPq9+flL9QTHkuAYbOC1+t7GAzQAeEAkpT1coG31xVjE6+7y4+elNaO4ewPgCD3571RTFrN5zIemXpWNyVHXc+IwNZZ20COaqTYdGgz9A0D0gnUXoCq2XrEM6ZzCwJVA2gHMolF3Fk4kscuVsFpfdgn2ngye1sfkeQYAitirUawGnxC0Lgy0FDbxge1N9i+Ax/KCvSqKvjZ/4sluALaJBkqKQm8pe3km+ItvYCy8tvZBJvDH7foMGl9iML9snaVYqsoS/2xoDHHyUhK7VtncxWrUJWQs68STzsDzxU3STkNuBmg/w2Sayt9Fz0t1xPL7i1sdb1APAnDhdpbMN4gcauxDgZYa+d+4Y2ed8bXE1vvGvrdjX0IkctxNP3DBd8ffo9/nx31DWRcvwBx+2n7BnIKAY8ADqfZbRIKffaAHQ62Vt4IamNSJCDJqR/8AD/gC8Eg3t4oyF+BXSkuzcdGZWqkNwP7+/rbGjD01d/bAwwNgoLNDELKzOQk2uGwO8H1E8JcrfR0pVBsHSJIaGZpZnoKvfx61hj0HtPitFPQBL5lkbimVhooXNAOaYPACcLEoi7IxSrJmPQ+F3lJvgl2O7xnMFu88fE1UdkhwJeeqnGExCbgVvqzTRm2m6SWx3pISaBl+skZoUExMPHUAgOLXosFrQM+AXvM+JRdK/tdNmwcOrD+CDfWfgslvwxA3TVSVaVu9uREv3AHI9ToElnBbm8oZFslQkNmKBXAnJYWO4JnapcmSs4Hs1q1lWSWU/1LTX0kMnttLMZGw7Fj4Z2iyMQLaHzf5VZKcasu0yDIMvh+zhWHyB4MUDCz+7pXYxkCzRG3bO+Hzs5A21qAWR0aClt5U/nBAwaECNlQUSZwBN4gLHUSsSjj+m4eJYjWQFB6WGdn2vr8WyEwhO5BNCIs4tZiq3U+JHQgaAr+9UDgBttqG1KlNCT8k0QLTv2LFATe9qqIYIpLBbwxIeWvx0a/Lc+NsnhwEAv7lyCiYVpas+h9X+u2JacYQwtBoZqU7YQmcxqf4mMUdUXC70Itd7mOy0c9mx4lFDp7PG3+5bu5UvbE63RW539So+wGwwNy7fg81Hwg4a4mlLowZA+Fw0uQC5omB6w+FwGdjjsnEBTZdKuV9KJ3FCURo+OtDI/X2pTt9rrbidytspPzNrVNKaLQGPEkmt2EwWAU4sFG4vcr2qehBPcvNb8HYcb9P1WgMaM7KV2alo6R6AWGlGLJROGZkkZAC480Sr+oNMQmmWPt0xvQcCI1ELPofaA1hMtYQnMCBdWmHL6d85azTO0yB3cKylBx8fDGqxrdRZ/mVJC2V7teh6fbjP2IEfuQwgf/qwPGsIA8D0cLa1UaW/SUpk+Hib2qBM8Dcfm+/BHl6vnNhxwcj+PxaHzYJVc8sFt73MG9hgGAYpoX3llMpkf29IAJoNBixMMIP8yrZwP/BNorWMoiRD+djUL5rC5utJRgt7jOn3C19Lj23mUJDksAmGNozogcwTJQP4kkw7Tmob6tBLWVaqpKPOirHmaZOixI+EDACbEsAHmEWvuOk7u7Q198YCtUm0UQZrkelldOjkLh4EmVUeWQYmAC6ZWojblmibnnx+0zEQEpwgLY6y5MY27/eolDwB4MP9jaqP0YOcCLSTl2YozRw6od18DysFEywlKmWPDzdFZkMbVQInNiMzLt8jeP7cSukJ4GgcQJS4ZlaJwM1jo0gKhu290uqhyybbMlIcYBgGJ0NZUQb6fK/1UKkyCCLOMqn5hGvhTOhioF2kY5cWRwtFOey8fScKreYIykXJAL5m6EkN7TfRUJWTIhkAnj2eagBSEjQAjJGTVkyYrKH0yOeTQ03qD4oRamWOksz4WjXJeQLf/4XxEY+dVjoKv7h0oiatQH+A4D+bgl7M0Wb/gLDhe5cGLcB9BhvAyzWR84WPK7KH7vdjsx3OUJbDpWDcLOWC06ySNWR1zcYWeAQadeN5WnIdfV7utY3MAALBAO+qWSXc3+JMH1uKburqh5xSEf9mNhSoyklFU1c/F3CkqJRpB8NolaEYccyjV6pECjawbxEda7JN4gPMxy2qeIjt8fQyLl94EcIPsDtioAwABPtHpWSnlMTZKSOHhAwAlTBXJwkwSae4aayuBLWgdhCaYPBJVC9sgHWwsUugEVeaHfm+HFYGm4+0anLm+HB/I0539GFUsh1nDWKCfFpIkkZNwBhQD3D0IndyDvA8R4uGsAewgC0Bh3bIFIX2ASk3EEUfXZsFfhIMwjKSbIJtoYpXAt4dyv4Vpiep+jlHw5cXhIdBfAEisOfKDTXZt/d6BdO0fNh3nc6bzp5YmIbPeW0gWnpXo0VvUGyEfiWbAezoER5rSuN8cSmFeGiqf5Al8DJRCwZ/u42VP3huWpKkCDSFAgzDAFBJaykeuBw2Xe/JT5Q9RGNJh8oU8hgDZDQGQ0lGMpw2C/q8AdWD2vq6FnzxiQ046+EP8dxnRxX7l1jtv0tri7iMVTTMr9bu1qAlSNSDXAaQn2UYyh5ONgPoDZ3YlOR3pKaAlb4fdgBkbL4bm3kaegzCpWeALwAdm+22aFQyUnkDPxt5zh1Fo4IBcFe/T3UQzMV7jYmFaXiF10/4VZ6VodFU62xPOXB6cFlrf4BwFz7iAD9Wv9FgqBCVbLUOXsiRpZDl1JNcVJuq5+Nx2SJ6bJXkaCgji2EXACqVmuJFik75iV0xaghWo08lKIm2N84orBaG03gTTwLLnUAONHbj+//dgWk/exc/fW0XTonkFho7+/De3mA/nl7tPzEFaUnc9OdQH2RbZKaAWXkSq4XRVA43CrEbiJIcirgfDICiCwjb1zguPw2f8aZv05PtAnmTWEwAi1k6Nof797OfHuH+zbZLBIh65pzv4FKRnYoPeaLDC6r1yRHpIU+D0Lmd931KDevoobk7WNpmGKBFNHA2p1zdc3uoEcuJ+QODu2jL1KC9qIVmDY5NQFDIm2EY1J0R9tjGIhtOSUzMFy0NkgwTNhMrGYFLIXYWGCr8KuXSXB3OGLGCLwjN581vLFAUqe4e8ONvn9Rjzi/ex9kPr8W/Nx6FP0Dw4uYT8AcIppWO0u2PKoZhGLhDPtRJGhr3OzX0CmqlWcYbtHcgWGpT06MzmmSHTSA8rZTh6B4QlgPFmnPiuJUt648r8Aj08sRN9rtjNADC54a5Zdy/+ZPdBTzNSTmtSiAoDcKv/pVlJqOtN/h9xLqYISV1JF7SxZvO1aITqgQ7AZyZ4oR4yx9rwgzgrHKhFqCEXrkuPEnKx4SeAW19gA0d2n4HT5IdhJCI6oAZy+2U+DDsAkDxScAMqAkQi3lv79BPAvdrMDs3g31TWAomUguQPWFmpzoj/GD57GvoxPde3IHR97yF367eDwA4b2KeIe+vID0YhGoRzt14eHD+onwaZaZN+0LRRSyHCeTglz57vfInN69f2D/n9SsHgGyrwth8t2CYZibvhN3n9XMXCbHMAE7l+X139vu50ibfRlCpBFzCy6qnOm1o5WVDh2J/ExtCRGRbeZtNkwafayXOKNjAWSzmOxWxPccsZJBqiGoZeC0+4gCw+bC2BEFGigOtPV5BNh0AZldkyDyDMtIw3143SGaUm2/j1huUqrkgxAItfYf2Ic4iSVEjowXIx2ph8I+bZ+HZL81EYbp88O0PEE7f62ev78HZD6/F//1vLz6ta466Kbs6J/j+tDx/7QFjJr4DAYK2PukAng2m0ofIBo4PX/dMbYKUn6UQn7DEsXSfj8BuZVCd4xZoV/IHJvY3dMIfIBiVbI+pf7XFYhFI7fwzVAbmBzm9Cv2nnTwP44J0FzbWhbeJJTU5Uk8xlDzx/iHOtvKCls5BOhUlig8wi91mNXyoUCmrq9UP+H2NGqI5bpfk4M4lU4s0PZ8y/In/GV0nPp9ymvxcE+objc3TV1rs8wUUpyBjwUkJNwY+cXKAi2B0KAA81NglyBpJMa86G2u/uwQ/uXCcoJQlx76GTjy25hCu+vOnmPrTd/Dlv2/CPz49omuKbmpJOoCgx60am4+0aX5dJZS2FTaWyo1hECQHP/OtNvTC/47FchtS5ePK7FTYLMLvmT8BzNf/i3XvI198+vEP6zDgCwjsAKVkboCg4DPf87gqJxX/DA0kAcCdK0bH4N0KGS1qexB/1/wLGaVAVguJ4gPMx2Ez9hRpE2U6+S+v1QVK3P4iR2G6S1IDsCJ76PRAKeYm4QLA1XuVbeAqB9nHFQsm8cpELGqnpF0nhnYQRO4kxeJJMkfjcNGoJCTZrRjwB3BEQ2BmtTC4YV45Nt2zHFdMK5L83q0WBpmixujuAT/e3d2Ae17eiQW/+gBLf70G9726Cx/sa1ScwmNLz1qsU48bJM+gxUheKRMaK/I5LUD1w8w+XklfnAHkw/5+4wo8OChqbuf3Ng3FAAjL2ePD7QOtvV68/vlJOG1WLniQ85GdIjouTCpKx07eAFj2EPTcigNAMf28AFvLRY0SciXgaOel2PfjHWxzngJug/XyxEOK/KrKjmNtml5Dq2d8aWaKIdI9lOFLwgWAL20+qf4gkzEuCvmUnSfajH8jCqjpD2qZGBwKLBaGy/SIHUGUSHXa8OAVk/HBdxZjgsjn0x8gaO4ZQKrTirF5bkGQ6LRZwDBAXVM3nlpXjxuf3IjJP30H1/11A7olAsGqnFTNZSN++W8wyJXv+eWmwlHxCwC1tA4c5gVzAYUAMDwB7MEnB8Pl0lSnTSDhE2sJGD5fmFog+PvPa+tACOGEhE+190oGOVZRNqgyK4Xr2RyqKfJx+crfj9cX/i2UAnMtsAGgeFAv2ixbd2j/ae4ewF9C37nR5CoMlkWDxyX87Px9Y8txbRanWrtTKnNScUKUAaQKMBQ+CRcAboujV2602GwW2EV7ntqh6pNDxg0IaOG0imVVVY55ygasfplSH6AcZVkpeO32+ShMjzywd/X7sed0J3I8TiyuyYbHZUO/LwBCAJfNgtG5qchxOzHgC+CjA02SU7x8H1g1BusswCKXARTYwMVBwkc8/KR0nj/Gy1QoDdCwX9m4fA+2HwtPABfzAlx/gGDvqeDFQSwngFnEnrp7T3fiowNNyAhZJzZ29nPahSwZKQ7sOtkmuI0vYaNm02YUahlS/i8x2M2VDQB7+oUXTslR9pfwy9MPvLkHNz+9yXAN1QqDf4dst7DSwA+qjzQbawJQkpGMo83CDGC03zVleJJwAWBz99D2xhmFXhHerUe0XQ0aRZNK/8m4ITiRaqVGYRJYC58fb8eJtj44rAxunFsmEOpmADR09GPNvjPI9bhw3ewSVGYHMzP7G7rQ2NmPORWZOH+ifK8pK5ejRQA8MEhtMUB+wIIv81GWNfQBPDsEwk6YOxREtht4VmpKASBb9hub7+HKvABQW5rO/ftwUzd6vX4k2a1DpgogPrH+5aM6rtTZ2u2NkFBaWJ2F463hiy6GAfacCn+eq2aWYCgo1OkOM5gsG+sCckokYxKNLl1L90DERfR7exux5Ndr8O5u5TYhPdSWykv4REORKBPfxwti2wwOXnPdLhwQaTfGciCKkngkXACYSD7AfDJ1el229/m4EsdQoCbxUJ5lHu2o0YMMAJ/beBQAcP6kAtx70XhsunsZJ43AnlQsTLDZ+plPjyIj2YF7zh+LRaODorzr65rxxo5T3OuJz4lVoayBlmrL3tPRfQY+cgEgwztFFsRlCCTkBhKaRHYq1J/41nhqIUZ+mgujUhwCXbrJxeETNRsYjs13D5kz0ERRW8FHB5qQFBo86ujzYnKR8AKKtcpjReIzU5x4fvNx7v5rBilKrhW95deuQRyTWKmiRtHFZq5H/1DI5iPSUihtvV58+e+bUfuzd/HD/+7Aa9tPah6ukGKBDncfLYi1RvkZwD4DT24MA7hdVjSIKjsTCtMNW4OS+CRcAKiEyVzgBETThL/n1NANgqgNEujVMowlbAn4cFO37gbw7n4fXt0W7CNdGTrJjkpx4rlb5uDft8zmTOnZ47KFATYeacX9b+yBy27B31bNwLWzS7iTOxDZhM4O/WjpmdpggOi3nH4Yf/VRKUM/xJPitMHDa6K3KrmB6JAYGRvqW+MP41RmR3oAD6W92BemFHL/LhoVDHzZALXfF8DSGqGjR10oM8OKr5dmJAsygnb70Nn2iQ+bSofRNgnXFi109/u4nlnxxWY0U6mvbw9fgPHfL9tq09I9gH9+dhRf/9dWzHhgNZb/5kPc8/IOvPH5Kc1yKwBQYXDmfLxCz6WW44U4Ayu3RyXZrWjv9UVoap47wRi9U8rwYFgFgGbzAeYTTU/PDp7LQazp6FUOAMXG6PGkMD0JKQ4rvH6C+qZu9SfweOPzU+ge8KM8KyVC6X9WRSY+u3sZvr1iNGyhbSlAAGtIRuTtXQ24+emN8PkJnrhhOvc88XTkvMqgrZWWYtknBmgBtshYQ/lD8ZGFiZ+GI//CoV9BCkZOYkRKwWVcvgctXcISYFW2tATMUHHBpPAgCGupuI+X3a3k9dA6bRasr2sRPLY6N5ULADwGT56qMSpZuJ7SUVROcFwNNuhKsltxRlQCnlSo/3dazxNRz0x1cplUr59gRukort/UZmHAADjY2IV/fHoUt/1zC6bfvxorfvMhfvTyTry545Qg+yzGYmEkt8FoUSq5azledPQKM7Byz3G77JISMItrYmctSEk8hlUAqNdzdygZozJtJ8U2jbIARtDVr6zxlWWQj6URMAyDKg2C0FL8K1T+XTmjWFIfjmEYfGNZNTbfs5wr/7BZGpfNggABntt4DDc++Rl3ouwXlW4m6Dih7Ts9+CyvXPbWF+ov1CLDEivyecM2SlPP4kwFi9Q7H5vvwceHwmK4TpsFaaHJUkLIkErAsHiS7Nz20No9gNkVGYKTc7+PcPe77Fa093qRzMsi823z+P2MQ0FFtkgLUOGxh6L0A2bLvjkeZ4RvdW1IO1MP/Ky3zcLg5dvmccNXG4+04oJJBajMTuEGrS6cVIBVc8u47HGwveMIvvbsFky7fzXOevhD/PiVnXhLIiAU2yiK93c9qLUCqfVYNoku9uQenZFix4m2SAkYu0IfLmXkMawCwCyDR/aNpFZCCxAALArX258O4STwgIIVnAXCCUUzUMNNAmvvodt3uhNbj7bBZmFwWa2yGn5asgPPfGkW/n3LbE64lu3R8bhsGPCHjaF8/oDgwG2zWgQlYiUGa68FyPcAskGV1qnkWMD2AWoaiJE4+UkF6eMKPAIRbX5j+6n2PrT2eGG1MKoad0bDasb5CfDlBeWC+850DXBleFbmhp8V3Mtr9/j60qpYv1UBE4t0XLBE2XfLaQCmOtEvip+KM/RVR/q9/ohyaXWuG6/cNo8btnt520nMrcrE5bWFIABe+/wk9jd04umbZmDrj1bgT9dOw6q5ZRiTF76Q/Pv6I/hqKCA8++G1uO/VXfjfzlMRA3yD6YMcpeJV39Gn/NrHm7UF4LmeSBFocx3BKWZgWAWAo3PN5wPMIicnIBYG5dPQ2Y++Qarva0UmAQMAERIWZiCaQZB/bwy6LCwfm6vZjmpWRSbWfX8pvrWimisLd/T5BAdTAkQIrmp9/T4VhwwtNMqYw7M/6agopiyNIs8TLAEnKWznLD6JjVCcEUl2WFGakYzPj4Wn5CfxAhi2/Fudk6rJ/cVIpvMmRrPdTsEE8qn2Xi6TxGaQMlLCwcB2nrzVtNLMGL9TIWNUnIpsvI398Bl9LRcsSj7ATp2/07pD0m0TVTmpePX2eXCHDIyfWX8U6SkO/ObKyUh2WLHuUDPO+91H2HWyA+dMyMN9F43H/765EFt+tAJ/urYWq+aWcQoD+xo68dS6enzlH1siMuxqDkRK2CRaMfjXRkrlaEC7fWRhelJEAOiw0RCQImRYBYALqszb32CxWCJKCQCQrJKdGYpBELUgMx4DBGpU6wwA+31+/HdrcMpy5Ux9E5Y2qwV3LBuNj763RLa/7+1dDYK/tU5ND1YJkBCCli7lxvx4Wm+xJWCxBZYUUrqI4pvG5LlhsTCoawoH3FMkJoCHcgCE5ZrZ4e3quQ3HcOvCCu7vw7zSKTs0xAb/DqsFbaHerngI9U5Q6ZXkhztSfWVaaOwM9g4asS2+sk3eDKAiOxWvfX0Bl4194qPD2Hu6E6/ePh9j8txo6hrAdX/bgF+/vY8L5DJSHDhnQj7uu2g83v7WQmy+Zzke+2Itrp9TitG5kUMgBOrHTCXEPzFfI1Y8IS1mncaqUGlmskBbEwAy4nghSDEnCRUA+v3KO93Z43KH6J1Eh1Rzt02lNMa3hooVrT3KZchinVphQwF7YK5v7uF05pR4e1cD2nq8yE9zYWF1dBcK+WlJePbLs/HXG6YjXVTKeXe3MACcqKMPMNrGeiBoWaf26ePhA8zClmeVtP1YpAJA8S1sDxdfhFvOA3ioWVwdPv68v7cRl9SGJ4M38UrWBEFZnlOhKWG+DEpOHBx31KZw+T+LXLuBGnIZwGji3U/rlIOgsqwUvPH1Bdzx9s9r6/DC5uN4+bZ5uGZWCQgBfv/BQVzzlw041R4Z0GamOnHuxHz89AsT8NYdCzFZYl/eOYgBPfG1ED8xsEckDi5GzlZQTGV2Kg6LBuQqTSTmTzEHCRUAfnSgUfH+DBP3AALS5Q+vP6B4ENTqDzkYTrUpByBqJaJ4kOdxwe20wR8gEQc6Kf4dGv64YnrxoKfFl43Nxb9vmS24TZypnV2hXT9s0yBEv8UN9VLEwweYhQ0AtWicaZHBGFfgwYAvIAhK+AHgbi4AHPoMoM0W7ug909UPp83KBSFi28J5VZk42R7c7zxJ4QvDc8YPvUyHnhaP7oHo+t/kAkANieHI1wpt80p7cUlmMt74RjgI/NOHh/DIewfw80sm4pGrpyLVacNn9S0473cf4YO90ueVYy09OOvhD7FdIthbuyd6sWlxJYhfFt5wWFkWqkdj5rEwPSnCBo71KadQWBIqAPzPphPxfguDQsqPtc8b4HTDpDBCJ06NoyqG4dUSZZB4wzAMRudpmwQ+2tyDTw42g2GAK6crD39opSbPIzgBdfT50MbLpE4vS9f8WhsPRz/s0ywjAcOnJA42cCx5IRkY1rZL6YCj5AHMMjbfgy28gNnChIPM1u4BTnsvHiVgAFxm2E+C5fmiUPa8zxcQWJdNKEznMp6tPG2925dUDuG71Y/ctLYabGkzU9RO4tQ5lTrgCw+AqF3IFWck4807FnAB9h/XHMKDb+/FRZML8PrX52NCoQetPV7c+NRG/OLNPVxpnhCCf288iiUPfYBDMj2PT284put98xEPZfG/04ONyscyrXZ8SXZrxLTy+TypIgoFSLAAcDCZEjNQKVFq6ff5cbbCVf9RjSXOwXBSpa+nyIQlYCBcBt6v4qbx703B7N+C6mxDP4tYW+/FLeELFJfdptllYcvRtqjfg5aSXGlm/H6/VKeN68cCpHX9WLSUicfkufEpL2DO9bi4SeHdoSxsSUYyPC7lactYwc+y7D3diQIZGZys1HAgxHeqyIxTFSPJri0rriVLKwX7GbtEU656LTL5uplahnyKRiXjf3csRFooCPzDB4fw0Dv7UJaVghe/Ohc3zCkFADy+tg4rH1+Pz4+34eanN+F7L+6A0mG3vc8XtS2eeBK4l5dVNUIVgGGAzv7IvmCxDR2FklABYLT9J2ZhfGFkVsIfIFg1r0z2OQTA/tPRaW9phW+pJYXYx9QsVOeoD4L4/AE8vyk4/HGVwfZa4hPQ27uEZaEsjcMzR1qim6wE5DUA+cmR7Di3RhTwxKCVEkhqsUV5ZjKSHTZBBnBsfrg9IR76f2Ju4Q1+PPXJYUH5nc0w2S0WQdAXtsqL3+G4aJQ2BYVoQh5/gHDbaX2zcFsflaIvUH9hS9guT6u+ZUF6Et66YwHSQ1qLj75/EA+/ux9OmxU/+cIEPPbFWrhdNmw52oYv/P4TvCdREpYazqlvVq6cyJHrEQZi/H2ie2DwF/tJdqvAVYZFSlKJMrJJqAAwUX2AWaaWRBqLEwCF6coZmp0no2841oLaZF80Xp1DASsFc0ChbLJm3xk0dvYjM8WB5WONHRISZ/h2nmgXZAVKNGbeuvqiP+jL+wCH4Web4kGexiEUohJejAs14/P9k/n71K449v+xTCxK5/79/r5Gyeyrw2bBnlORFy1VcZSxEnsZG0lL9wD8AQKGAepbhEFTgU6LSX4VSEpSRY6C9GT875vhIPB37x3A71bvBwDMrcrCXInpfv50Ll+omyXa1o0y3jYhDsmkpJD04nHZI2Sp4nhtQTExw2azMJlOsSRy07TbjrVB6WL2c55GWCxQM0uXOviZAbYEfKS5W1aW4bnQ8Mdl04p0G9+rIZ7g7hnwC5wStE6iSk2/aqVVJgBkX5GB/jKb0bA9elrFsVnEu/S40AQwf2o93hZwUrCbRXPXAAokBnCcNgtXrubPX1w/p2wI3p00EwvTNT/Wp/NK/Ayv/++4KACs1jmZ2tQZ/O0dViUJfWny0pLw9jcXcH2aD68+gO88vw3n/HZthIwTAKSG9ASX1GRL/o7PfnZU5zsIwt8+xUk5pSPBgOh7lzuaZaRE2sClOOJ7DKCYk2ETANrjIaAVBVLCz49/eEixUX9TfWx7H9sUZGBsjHlLB9luJ9KT7QgQaYuq0+19eD9UzrlyurHlXzn4ZeCZ5ZEZXznEB3etyJWA2ZjSYbPE/fdj/YCVRM+1wAaA/KZ5dgK4d8CPutA2EM8MIBAedAgQIItn/eUKDTw4bBYcCZVCCS+MuXRqIeLFBB1uIIeb9bUsnAmJG2elOnFKFJjwS/hqdPZ5OVvG4ij72XLTkvDONxdymcAXNp/AqfY+QTCZmeKA22lFa0+wN29CYRqqJAbhPj8WXWWmJj/8WnraCMVyXUkO6f0pR8IFpDDdnG08lPgybAJAd5yzHFqRak7fcLhFcULr0Jkurn8oFnQrWBulDrExvR4YhsFohT7AF7ccR4AAM8syBFIhseStHeEAcI4OKZhtx6IL8tX6YuOd/QP02cEpMTbfExHol2YGy6Z7TndwAVc8tPT4LB+bw/27i6dXyAbAhIQtv9iSH4P4+rTW6JB60utfzepc5nhcaBJVG8qztO+Xa/aFe/MW1eQoPFKZU+19AukdIJx5m1SYhk33LMeN88O9nI++f1ByUI4AaO9RFmGXIo/XA8jP1LPIDdo0iVxCAjLnhML0JBwV9RVLtR9RKMMmAMzT2UsSL6SU8Nt6vFg1t0z2OQGiLg8wGJQ02nJMrq1YzXkCC7+fQIBw1m8rDR7+UGLXqQ4uoPYk2WHTmJneejS6AFAuA8iit8k+FrA9gHpL3fxHW5lgL+onB8NToKOS7VxZ3wz9fyy3LQ1LubywOTy0wH5+/vfA/ssd5wstPVPTuyT6F5VgM4DZqU70izYBPRPqL20NO4AsHK1f087rD+A37+7HpY+tw9GWXridwtNfVXYKXrl9HgIEeCnkGrRodFA0/jOZKsyWKPbbDInhMH6Pnpww/wGR2oGcJGB5VkqEYPS5E/P1vUnKiGDYBIATCs0nViyF1GAAQaTnqZjBKM+roZRdrMgxr78ywBsEEWUA19c142hLD9xOG84bwoMfIUK7Jq0+vNGW+Zs6lQd4MlPjP8DDSqH0DWLCMT8tKPfyGU8ot1ogAB3/CWCWolHh97WurplrT2EzO/5A5P42szxjaN6cAei1p1TyAU7XYU/G74XW2+d5sLETl/5xHR557wD8AYIpRWno7Bf+DgfPdOOxNYewek8DjrX0Ij3Zjj9dOw1P3TgDqa5wdpZ/SffuLnlbOjmk5Gv4klKNHdI92e/tE04ny9Vt8jxO9IqiQ5oBpEgxbALA5WPMbQPHUiVju/TC5hNwKGSLtsfQEUQpMVOTG/8TqhJyGcDnQtm/L0wt0OV0EA12kZ0Bv1SltVdpr4qWoRzNKgM8uXH0AWZhs/Na3EDkqC0JnvD5QYD0BHB8B0BY2PN5W7cX7lB2jQ0ApSY9v7Y4/gLQWk8Gx1r0yZ+wItBS1Q+t/amEEK7dwWqRDialCAQI/vrxYZz3yMfYcaIdaUl2nD0+F9uOhy+o71haxWnz/ertfbj/9d0AgGtmluDD/Wfwzee2CSb1+b/ey9tOaXofavAlbfY3SAfYWs8BUt+pGVpBKOZj2GwVbKre7EyQ8Yh9YctxlGelYJ+Mq8XGGIlg96pkZcriKCKshZpQBvBYaw9IaBMIEODtncFevKtmlMT8PdhF08Vv7TiF+y+eAIZhMCbfo0no+UyXuqOHmD6vH2oKMlLTi0NNqtMGt9MmEELWy+zK4I/Lz46wfZ1ef4ALoM2QAQSCrROn2vsQQLBU3dI9wAldeyUygGbI0OR4HDjdoa612qxTrFgpA6iVk2293IUqu02zw0DtvV785LVdSE9yIC3JhvRkB9KS7fD6AnhszSFsDQVOi2uy4bBaBBO/j1w1BRdNKcSq+eVY9tCHaOkewLFQv99T6+rRo3J87PEG4PUHIkTh1bAwwgtvG+8ict2hJlw8NdKxSC4zKKbPK9y+zDnCRzEDCRMAfnrojOL9dntifJTa0nTJ2480d+Oby6rx4Dv7Je8/1NgFf4AMupFejFy/CUuuRg23eJGZ6kRmigPN3QNcZqXP68eAP4AJhR7ZgNtIxJnblh4vDp3pQlWOGzNKR+GfG9TlIvq9+rNjWoTR42kDxyc/3YVOFcs+JaaWpAMQZhHZAPDQmS4M+AJIddpM83nPn5iHJz6uBwAk2YLbB3vCF2cArSaZtK/OdeN0h7q2nV4/4CaZAFCPcMO7u8NB24zSYLm8q98LG4Berx//+aRe9TXW7jsD/l42u3wUNhxuwb6GTqQnOfD1ZVX42Wu7ud+JDf6sFgZXTisCdn4u+bp7TnVgEk//UQs2C4MB3nYwwGvD2X1COgMotnaTgkGkqoPR8leU4UPCbBnPrKuP91swhKxUl+CKzBI68Hv9RFGqxBcgnMyFkZxqV+4hyzOpCwgftgzsC2VWekInqJVDkP0DIi3hAHAG8/M0GrBHowSoJQAsNEEGEAiXga1RBjpVOe6IE1tlKADcFTphjsv3wGISQdBvLK3i/t0ckhNh+3z9on5fswitTyvV1ofo9RNdNmhsCThbJEju1KEL+TYvAJxfnQVCCJcBTHHY8LXFlbhmVgmWj81BBm/wib85iMOnTw+34tkNR/GHDw7hgTf34Cev7pZsh7FbGXyw74zsPrr+kH5BaPFn7+Jlx0/LtHVo+caTHFacaBO6gGQkx38QjGJOEiYA/CzBfYD58HvS+Ker3SrN1bFwBNmn0nsWb0kNLbCDIGxmxRcgcNkt+MKUoTE/t1qYiJP4K9uCzeE5HpfmneyITn01tQlgAMgyQQ8gAOSHtqNoZYXsVgvWHQyfaJPtFm5yle3/G2eS8i8AeJLD33tLqLwvdwK/UEECaiiZUpyu+bEdvdqygD0DPi646RL50+qZfN59MnxsnFSUjsNN3VxJ3e2y4bvnjMGSmhxsO9aGlm4v7FYG3ztnDNb/YJlAyN5lt+BXl03Ewysn457zajChwKNaIu3zBnC6o0/Wq/o/G/ULQntEn50feIr9kvW9bqQLSE2+efYLirlImADwTJd+vSWzks47IPEPKv/49AicCnWRzTEIgtXkZRKhebiaDQB5vVXnTyzQJW0xWKaVCnu4dp4My8GkabwC31jfov4gHi3d6j1BWSaYAgaCJWBAu3+rFOvrwhIw5QIHkOCFkZkCQCDsFNOvYu9104LyoXg7qkzQMUBzvE3bIAjr3OGyW/C5aIghW+O26fMH0N4bPP4zCMqcbOO9FiHAd1/Yji//fROaugYwJs+NV26bj+Vjc7DwVx9wz81MceDj7y3FZbWFeG9PI37+1j7sPNkREZh/e3k1rptdrLl37lCTfk9g/nS+uEQbrSg8EJSYEQ/pLKlJjP54ytCTMAHgcIKfVeMffD6rb0GFzJQwAGyMgSOI0kSf02aOcpoao7lhgPC3edXModP+A4BaiSb+D/cH+1a1DmJs12n5p6UZX0pzLB6wYtDR9LqxgRR/+2ezVYQQLnNulgEQlgKN/bO5HnOU6TN1eEafUPEPZ2nsDIlAu13YfUp4sam1PWEXr/KRleqA1cIIAsCmrn78Z9NxMAxw66IKvHL7PLR0D+Cc337E9c2VZSbjrTsW4M7/bEfV3f/D65+f4rJuaUl2LB0TDJIYAL9ZfQDPfHpMV1vGiTZt3wdLEe+ziy0lByP5n+dx4qgoAzhfYxsKZeQxLALABHGB4xCLn7KBVnuvD5dMlS8H1Z3pQmAQvrFSNCjIiOjR6IonbAmYzabaLAyml0YGZLGEzQDyj+Xs8IdWl4XtOq2l1HoA7VZG93RirGB7AH0SE7BqsB7CfHsrVgPweGsvOvt8sFsZVOeYSwv00mnq1m6DyYgajZ7gXGvAw58APtwsDAArsrVpjP5vZ9hdhx3q2sqbrPcTguKMJPzn1jn4wblj8eq2k7j2rxu4XssJBW5kpDow8+fv4cP94V4+j8uGORUZ8PsDeH9v8GIt2qPrpsP6+gAFzkQa+im1vq9stwvd/cLJ5SKTDEZRzId5jj6DwEwHUS2wAQsL//1PVejD8foJjujU4FKjVSGIKEgQd5VRKQ7BhGGSwzbkU5XjC9LgsFkEvTwb61tACEFtsbZg9Gizvt82EWzgWNhsWE+/fjHorFBmqoc3fVoVCvbY7NDoXLfpph1vXVCh+pjqIbIoNBqtGUC+C8gJkTtF0ShtgQlfWH1WRSb6vH5O+BsIXiC8dcdCzCjLwG/e2Ye7XghP66Y6rNh5shNbjrRxt7nsFliZoB3f+roWdClIvbBHEbUkwyvbTmj6LCwTeeoE7IWr0tYrvvCXO+eJLe6Cj42fxSDF3JjriBklnqTEmnKaICpVdfPE3NbsbxI/XMAOgx1BuhS02cbkJc7JaTTPrD1Jx3ShUThsFkwSSc70+wLYfKQFCzTaVunVyVMbAkkz0X7B2sGJHQq0UJDugs8XEATXlSGHGjNZwIlJcqp//9fPKR2Cd6KdVLu2CyetPYCsdl2Ox4mGDuF0qlbJngO8PuUZZRnYdbId/LbKtCQ7UhxWfPO5rXjk/YOC50oFd33eAPwESLLLn/5qct1gEMy8LRqdjXXfX8opNkjx8QHl47YYfvaTtQa08qLMfp/wfYsHUOS6c8QuI4lWHaMMLcMiACzJTIxMFUstrzxpYRjwd/U3dpxSdAT5rE6/5IASfQon5Ipsc5XUlBibFw4A4qUEIh4EAYC/rD2s+UQnZwIvh1oG0Cz9fwDgdtnhjjIjWZ6Vii3Hwv1/NktYnshsDiBi7Cpn4AtMMgHMUpKlrSyrNVvNlYBTnRgQVf/LNKzV1e8TiDGPyXMLyr8sKx9fj5e3qduyFaS7uIxyr0h7M8Vhxc3zy3HNrBLsa+gEAbByejGeuGE6ctOSuOdJMRAAN/SlBX4fODvzwW/XYIdnuNcXDRIRmaKweIAk2URVAIr5GBYBoNYSm1lw86ZTWWFn9jRxrLVXkM0Ss+mIvklRNcQHFj5mcJHQyi2LKpDiiO/BrpbrAwyf9D8+1ASGYZCq0Y6us0/7tHuDioZjrskkfPKiFBWfWJgmyLAUZ6RwJf5dJvIAlqJEoczJwHwnaK2OJGKtOTm4ErCEHJGW7eGTg+Hf3eOyIcVpwwciT9zGzn58pjAgN7UkHYtGZ2NUsh0n2/rQJDE8NTo3FZ98fymauvq53t1vLR+NX142kQvMlDKAALB2v7JZAR+p9gwnLwA80CCs9PSLLtT7vNLHbXFFpyiBjuGUoWdYBIDnT8qL91vQDXcwCe3HbEuHP0CwbKz85znc1KNLhFUNpaESswjUaiHH7dKlKxYL2Elgfrmmu9+PHcfbOBkUNfRI/ahlAPNN5uLCnvCTFUpvUkwrS8cnh8KBAFtqb+rqR0NHPxgGGGtSrbOVCtPo8d5epZhVnqnpce29XsXqAQs3BSxxLNEyoMR3AKkMKSSw/XxsOCYujzIAFlVn4tsrqnHp1ELsPtmBD/efQWtP+OLKwgArxuVy7SLfXjEaX3t2C17edhJWC4NfXT4Jdyyv1tVL/KNXd2p+rNTr2nh9fZ8cEl7o+0THaalRKgbhjCvLrApt4t6UkcmwCAAnFCZWBhAAHKGDH7tj86sRo5LlTwz9voBgGnIwECJXSAhitgyS2cl2OyMmvAHgsQ8PaZ5Q1SoF4/UH0KNiH2cWWzQWdqgoVac+Y2F6CurOhEWyR+exAyDB8m95ZgpSTJZJY7l2lnyP35wKbcHWUDJZhxi0lkngcAk4umPJlqM86Z+SdOw+2c71kYqPXZkpDvz2yon4yw3TYbFY8Jt3D+C/W08ILNQyku24fUkVPvn+UsyuyESv14+yzGQ8/O5+rDvUjBSHFX9bNUPRlUkuJGzqHMAmHVqe4tfh9/1tOyq8EJQToeYTdAER/iZLx+Rofj+UkYc5j5oith1RbrA1g4+mXpIdVvT3Bns5yjKTUc/rqXlnd6PCM4HPj7eh2ICTOyuQKsdgzNtHKtNKRuGIqD9qzb4zuGNpFd7kyVnIseO4tiEfNQ9nIPqSa6xg349DpzRNksOKDl5pnM0EmVUAmo9SifemeWVD90Y0UqxxMhcITgJXKuiW+gOEK7eKM4Ba+3T5OqXzKjPxxzWHgs8XPe7ccTlYNj4fj62tk3Q3mlTowap55Th/Uj6cNiv8AYKn1h0GEMykd/T5kO124slVM1T9w112KyBTAb/lmc3Y8qMVmj6bxQLwLIAF7irHNZbY+Xhc9ojezCqTSSNRzEVCBIB/DpmqDyccNgvYZL24FLTtWBucVkbWQeDjA00434Dm8UMK3sIWRE6UUdSpLR2F/24VSkL0DPgFfZ9KqFnzsWjxATaLCwjLYErS/BNlVcQEsDkHQFgcNouku8MMjeXWoUSPl7JaBrC1ZwD+AAHDRA4kaZHuOtnWIxB3H53nxnt7ghfH4nbft3Y34i3RhbPdwuCCyQW4YW5ZhM3d6j0NOBaSpeno86EyOwVP3ThT04V1skI/b0v3AP6ytg5fXqguAeSwWtAb0sVkGKEcoNj3WgvpyXacFk1a0yoORYmECAA/Ozx8fIClEDs69Az4MS7Pjd0ywcAWkaVStBxokA8AkxzDojtgyGEngcUH9A8PaGsQF/fwyNGiwQUk02wBYKghfcCvXQyaYYDDoguV0sxgALjbxBIwfMozk7FPtK9ZGX3BlhlR0wJkt+WMZAcaRQNLWtoA3uUFdE6bBRsPt3Dl3z4fZM9e2akOXD+nDFfNLJGtYjz4v73cv2eUjcJfrp+uWfjebrVwEjFS/PJ/e3DD3FI4VPT3khxWbhI5xWETDHBEYwcn9hcGwkOGFIoUCXGWl5raGk5IuXFMKUmXffyRpm5DBkGUfICz3fTKMRpG57qR6rRFiPt/sO8MtMw+9Gs88KtpAAL6rL2GAjYDqKQ9KcbKMFjLC57zPE7YrRZ09ftwuCnYF2j2APAaiUGQHBNnZrSeFNQygI08F5B1dcLeuFwN7SUf7g8HgIXpSXhyXb2m91WVm4rr55RJBn+EENz36i4cDPWULh2Tg2e+NEu365HSvuUPALc+s1n1NUbx1nSJDg4q9tGSiPtgleTEKBQgQQJAJYbDJu4PEJSLNLG6+uRPkn2+AE616+8REXNUwVVE/H4o2rBamIhyExC8ok/WIAxMAAQ02KWplYAtDKLW3YsVbA9gj4LzghiHzYI1+8IBIFvu3RPy/83zuEyX6RRzaW1kAHjh5Pw4vBNt5Hm0BUNaM4DZbmdEb6uWXkO2xA8A+eku7DwR/FupOGFlgPWHWnDJHz9BnShz7A8Q/PiVXXgqFEhWZqfgieunR9XqsnxsruL9H+w7g8NnlNs5cngBqs0y+FOx2PHDTDqgFHOS8AFgoqe45bSlNhxWnibbenTwZXGxMj8fpeZuijJCoe/w7Vq31L0a+gDVMoApzqG3w1PD47LrtqdLdlix+1Q4EOAmgE+YW/+Pj1vCkeXqGeZyAOEzvihd0+PUMoD8APBAo3CbzlXpB/UHiKAdopM3IKE0Q+Qnwf2srqkbF//hE04/snfAj6/8YzOe+fQI99iHrpwSdRn+utnqv9+Vf96geD9fMYDVYxjM6Uys6TBGowc5ZeSScAGgeP8Qp84TDVYLS9z71dDZr5jCX6vTekiKFoVG45IMKiAaLXxHEL58l9rUNcsWDVqAzV3KvYJmtUdks4BaT3TpyQ5BtjM8AZwY/X8s4qGH8mzzZthnlGnTjjvd0QefQj8npwHoduFIkzAALFDRxdx5ol2w7+zief/2qnQQsE/r6PPhhic/w58+PISr//Ip3t3dwG13tSXpkpl6rYwvTIPa9dWZzn5u0lgKvnYl+z0OJqHRKaoaLR9LJWAoyiR29ARhH0Uiwk6UdfX7IB6MUzpIGpEBFB8w+OSl0QAwWqYUp0ueHLS29Wjxe1ZrAcgw6X7B9gFqFUHO8zgFk6BVOcIAcJzJJ4BZqngZdXPlZSOZV6nNu9ofIBFTp3z4GcCmLuHFT5FKCfh/u4SSSUHvXvlSrVwiwB8g+OVbe7HtWBs8Lhs3jX/T/HLF9bWQp6GP82ev70HfgPRxdiJPbobt/eVLJOlxBQIipaEmFiWePi5laEn4AJCVhEhUnDYLd1WaL7LtqVDowxNrzUWDkpI/lQ+InrQkO0bz9Lf0NmPv4ZU85WhUOPECwv4iM8EGgFpt+wpEFyIV2SkY8AW4kmKiZACv4g2CGNHvFUtqdJQOlfoA+QGg2Ae4VEVu5dNDYc9z9mJK6Xi1uCZb5Z0Ge+Lae70oSHPhnPGDd486Z4L6a/gDBDc+tVHyvrLM8PF9ICQCzc8UH1IY0hPDADgp0g40QiuWMrwx95FIA3Mr1Xd8s8MOXPSJnB2OKhxc+30B1SBADa/CxCkNAAcHvw9Qb9+b0nAOS1On8m+v1XpuqGEzyw4NOnAA4LKHg2ePywaPy479DZ3w+gnSkuwoGpUYmerzJoWHPpKd5tbXtOkQ6lbqA2QDQKmLETWXmoO8AQ5CgKxUh2IGfd2BJthDF1pZMsMPrNj+BZMLdH1GObT0AQLA+roWbDzcHHE7f/KYjW1tvBLwujrtbT4uuyWixWRUsjnbQCjmIeECQPFB4DwNV2FmZ0VooqxV1Nh/uEk5ENikYICuBiFEUWogy2QSIokGvw+wQ6HULkWnBpkUtX5CtRJbvCjQKQbNz2qMyQtm+1j9v3H5HtMNusiRmeLkynvDSWBdawZQTKpCC0B3vy+iPUUt09vR78f00mDvYmuPV7E/75l19Vh3cPA91BXZqZp7WW96elOEth9/AIU9FPfxHrPhUGTQKEeyKKPOMInpkEUZWhIuABRTOAzS3NfPLQMQ9AV22cI7rT9AIvoC+by/T9kyTgmlIMPK6MsCUCLhB4C+ANG1o2nRSe71KXcUmrUEzA6B9GnUO9zPK4ONyWc9gBNnApgPK8sxnE7LchnA3gE/d4yRCgCVgpNPRMGZw8rIqiXwOdUevGD2EwJCgEumFGJSYeQ20usL4JonNuCpT+QHNLRSLJOBThVleTv7fHjgjd2qr8e/WKxTSQDwSRGtp9QvSaGwmP4s79OgiZboFKQncU3xaUnCzFumgpaTlmlRORoUhgikFOUp+ijLTBbocBXqnKpWKu8HNEyTmFUbLz9UAtba4M6fjo+YAJY4uVOMIUVj9VAuAGR/N5fdEqFHqZY1e3d3g+DvCycXCDQBxdhDPZX1zeH3kpFix29WTsarX1+Ary2ulHzefa/txs1Pb1ScZFbjwsnSlpyepMhj6NPrjwimmQHhd2EVBblaxN5ZxFnlQpO2gFDMhekDwK4+7aKxiczUkPNHl2hiTMlD9lhr9IMgxxVKNwUmLR8mEgzDoLYknAXUO5WrVN4PaHCBUbpwiCdsb2J3v7b9mt8XW5WTikCAcEMy4/ITYwI4EanK0RZcy5WAz3QFL2Cy3c6IbJ9dpbqwRaRwcPHUQs5VRAqpYKul28tZbLLbkNSg8Oo9jZj9i/fQ2q3NglHMF2dJ9wGebOvHdbMiBcC/8sxmeHkBJ1/2JU3Us9fv037uEw8WzTahzzTFfJg+ANSzEyQyV04LHizEJ0alJmuvn6g6QshR39wte18ldQExBH4ZuLVHn6SDkhSMlgBQzgM13ridNqQ4tJen+J+0MjsV9c3d6B7ww2mzoNLEWnqJzjSNWoAn2nolbSm5/r9UJ5pEwZvaUNQxXlCZ4rCiQ0b4jy0L8/thLUw4qHrw7b3o7PPiP5uOAQD++MVp+MKUyIxdU9cAan+2Gq9vP6H4vqTIT0+S1e5bNa8CLlEPz7HWXvzhg4Pc3/zMnVgaSV9iUvgbzK+mASBFHdMHgIN3vE0Mzp2Qx5UDknmXqr1e5aPAR/uj6wM8ohAAlmVRFxAjqOX5OR9t6UGuR3tQtuN4m+x9WkrAZtXHZBiG6wO0q8jj8O92WBnkepxcKXBMnpv2qcaQORq1APt9AUmv9kZuAtiF9aJpVqUBs1NtvYJhidrSUdh2TDobzh4vfQHC/TtAgLzQxc/rn5/CfzYeQ1e/D1U5qVg+Lhe/u2oqfnPl5IjeagLg9n9tww1/+0yTFSMfObmutQfO4GcXT4i4/ZH3DmDv6eB2zO8VdNmi79sT2yuW0mM4RQMJdQQVX00NpyEnq9XC6TY5RAcCpZ6Zl7efjGo9JakRNZV+ijYmFaULZB30OA/sbZC3gwuoRIAuu0WzzEo8KAjpXaplAvn7d1WuGwzDJJwAdKIyt0I9A8hu2lJVCv4E8DZRSTdfQWT+HVH/3xXTi7HtWJvkY328/YC/S5wI9Td3D/jxy7f2AggODG052oqOPi8urS3C/765EJVZka0uH+4/g4k/eYebNNfCxVMLJW9/ZdsJXDK1ENmigDdAgG//ext8/gAyU8IXhez1DH/P1ZoAEVeCtHgtUyjmPUtIIB5OsCW4D7CYpWOC1j3iCd1UhRPl9mPqrhFSnO6Q73mhGoDGkOSwCiZV03Vk5cSq/nz8KgGgR6Fv1AywDgpqcij8yiLra5qoE8CJRoqObUiqD5AfAO49LRQ0zk2Tz4SvESkbTClOw+fHlY9x6UkO/HblFJRlRgY93tC+8sq2k7jssfWYdN87mPOL9/Cz1/dg4egczJQodXf3+3HeIx/hvld3Ka7LctWMyF4/ANh5vB02qwV3nT0m4r7dpzrx54/qBHqd7OZu5aW+pcrrUoilplJ0ao9SRiYJFQCKJ5v09BIlAqtCcjDiE7ySXp9SoKCEUtNzjo5SJUUZviB0U2d/hCesHEr9P36Vk0KGSQdAWFg3EHGmWwx/N6jMTgUhhMvM0AAw/rCb4Ym2yGpCI08E+kCDMIDLV7jA5Gf77FYG7T1eziaNj5NX/nfZLbh4aiH+c+sc7rYM3kDFmDw3Fo7O5i48TrX34cP9Z/Dkunp8Vt8i+16eWlePWQ+sxuEmZUeOzFSnZDuDjwDtPV5cPLUQ+RLH1Iff3Y9Mvhh0qN+dn71Xu9iTYpjlRSgxJKECwJo84UE/y6RSF9FSmpnC6Tnxy93dA/KDMIQAJyUOwGoo+gDTDKBh8AdBth9vx+xybc31ACKEY1nUSsBmHQBhYS0PGUb5c/DvrcpJRWNnP5q7B2BhwqLQlPjB/j5qGcC2HuGxRmx5yeIPEMGwVJ7HhW0y2T+vRJ9ejsfF6fK18F5nbL4Hf79pJj794TJsv/csvPCVOfj5JROxam4Z5lRkKvYkNnT2Y8mvP8Syh9agK1SZkdpqa3Kl7fM+O9wMh82Cry6pivwMfoINh8MBaG/IL48f3EaIR0sEd+KLSirjRdGKaQPAgYFgZsuGcPDjcQnf7pgC7Z6VWtdj/x9r5NabXJSu+7X+9nG97vXEtnN8jBwgGKrvc6jX0roePwBs6urHwhptzfUA8MkhYfM8ux4TUHYKydfptiFHrPYJdgjEKxKzZvd1/j7PUpmdypV/K7NTkWRA9t8s+7xZ19N6cmB7APnrKfoAS5RqAeD9vcL+vzF5bmw9Kj0Awr8G4n++e84fG/HYt3aeQm/oIjotyY7pZRm4ZlYJ7rtoPP51y2xsumcFNt+zHE/fOEMwuMXn0JluLgBs7ezBa9tPCsqzl00rknzei1uCk8VXTi+WvDA7zPN07+4PBq02XjZxwCv87aQmqMUBIKuXGQ2Jto3S9QaHaQNAdufiX/B8fkLYmLtsTK7h62ntuYjVepfWBhuKxU4JSln99/Y0KNwbuZ7XHxA0UPNxWhmBRdFgGarvc6jX0rpeflqSwP7M7dQeXK/edVpyPaLSGl6g0GSvh1jtE2yAKu51ZUT/599empmMXSeMLf+aZZ8363oF6doyyaymKH+9pq7wFLCYskzpqdnfv39Q8PfMiswITUA+7HbC/3xnT8iH0ybcgvq8AbyqIvGSmerEopoc/Pdr8/CbKyfDqTChTgjB1/+1FZc9to4LUC+vlQ4APwt5ALvsVtyyoAKAfImWVXzo5VV8iOg47UmK7M0U6youqcmRfe9qJNo2StcbHKYNAFnxUP7XduiMULrkbAMDQHa9ofJPlFvv4imFksGeTeGAdExBK1BqPSXtQKP7x4bSj3KovS+1rsfvAzx0pkuzft12UfmL2ydUjiVZBpWAY7VPhN1AhAEgEf2fpSQjGXarJewAYtAEsFn2ebOuN7l4lPqDEM4AhtdhuAvMTInyarZEUNgz4MNOkfbllMI01CvYoTlDPaTizyduFQKAP6+t03wSvrS2CG/csUC2rAsErda2HG3DJX9ch2/8ayva+7yS/b0tPV5O+PmaWSUYlWyXlXEaCDV7d/K0YMV1mozkyABQrEM4qTj6/SPRtlG63uAwbQDocAQPHD6ESz3tIkHQZImrocGux/4/1sitZ7NaUBjqY+E3FnsVJkF8foLjKq4g/PUaFSaAS2SuzqNlqL7PoV5Lz3r8MvDWY224YJK0fZSYYyKpHnY9L5TLn0o9TXqI1T7hcdmQLFHCZfd1n+jzcR7Ap4ydADbLPm/W9WZpdJPo7POho8/LrWO1B4/LGSkOSdcPKeHk/245IRh2YwB0Dii3OrDbEP/z9fv8ApcjNiY7dKYbm3RYZ1bluPHybfOwcnrkhK8XVrx1x3xcPq0IDAO8uv0klj70IdIlgjMAnHNNitOGL80vBxC0qhNDEKmNKd4XkiTsTMSDIiUZ0R/DE20bpesNDtMGgFIMKI3DDiMW12QD0DcB9r+dp9UfFIK1aZJCTtSUEj38AHDH8XacNV5b5los7aAVs/oAszAMw5WBtVwXV2anor3Xi2MtwRP7ODoBPCQsGp2t+hhPqCeNPwjCDinlSGSipRIhhBD87ZPDgttGpTiw47i8Fp/TJq11+dr2U2jpHuACKX4nzVOf1Mu+nhRJDiv+7/JJeHjlZLhEZeWXt57Ar6+YjNdun4/ZFRkY8AXQIHNh/eq2sFbrdXPK4Hba0NLtlbRrTFNJanRIWKP2eoW3FcgM2VAoYhIqABwp3BCSg9GjAPDyVu02Ro0d8gFgsUyDNiV6xuZ7uL6kXq8/aFeloSRAAHT26bOQA8zrA8yHLQM7NcxyVOWkcvIvhelJuvQUKdFTouFYkBT6AfkBICtTJDX0IKXd+snBZtSJ2nvKs1Lw8YEzsuvOrYzMThJC8LePg4HkSgltvv/tOo3T7fLHPjkumVqE17+xULDPPrX+CABgQmEa/vXl2fjzddNQkiEdeL27O3xxnpZk547vmamOiAsgsaOHmGaJi3fxc8wsAk8xFwmzpQwvxT9lqnPcSFIRyRWz93QnfBrNI4/LGLgDQK5Efw5lcNitFkE/1fZj7SiXcCGQQo8jAYvZM4BAeBI4WYNgLX8CmOr/DR1a+pbCWoD8DGDw/9mpTnSLLmCkprefWnc44rapxenYfqJNdt1rZpVE3LbhcAt2n+qAy27Bd86qiSjJ+gME/9xwRPY1lajKScUo3oVVW4+Xs4xjGAZnjc/D6m8vltQDPNIiPN7eNL8cSXYr9jd0RUwPqwWA7Sqe4sPNHIESWxImAMzzjKyr/omFwROd1t3ZFyARQwNySFk3sVAXkNgg1ANsw4px2srAaw80qT+Ih9XCJIQOGDsZ7bJrCAB5GUCjBkAoxtAfEi8WBIBsBtDjxKeHhULLaSKHkSPN3Xhvb6Sf+Zg8NwZ80iUQm4XBgurI8jSb/bustgjpyQ7cNK884jHPbjjKvWe9iIOr5zYeE/ztsFkwo0x6cObO/2znhu8yUhy4dnYwgD3c1C15jJc77verXOOPkulDpFCkSJgAcGxhuuDv4X6hc/HU4JWhnq7HjxRKJnxOKZRBcqkLSEyYVsIbBDnahqVjtQWA6w/pCwA9LptpJ8745LFSNSpvNTPFjlSnjTcBTDOAZoIVKpYsAac6sVkUAIqngp9edwSERPYGKonfz6zIiLARPNrcg3dDclg3zisDAHxtUWXEeaK5ewBv7dDeL62EWLYGkLeFe3HLcSx68AP8ZW0d+n1+fHlBBRw2CzYfaUWWzEBINLCWiRSKFhImADxngvCE6VCQRRkOXFYrLQejxOrd6nqAANCgEADm0AxgTOBLwexv6NSs1XfojLINlRgjRbxjCTsE4lMZ7Bqbn4Y+rx8HQ9/D+EIaAA4lErGJAFad4Hhb5BBIttuJ7SeEk7eFvO2+q9+H5zcFs2h8hZZkhxVv75IP0q6SmMx9al09CAkOrlTlBIMgm82ChdWRwutPr69X/lAaOSlxHD13Qr7kY5PsVnT2+fDAm3tw1sNrseVoK1ZOD17kizVf9SDOSk6X8DamUORImADwwonCHUtKEX044bRbdTs67DzZodojAgAt3fKPSYTyYSKSkeLgJqwDBDje2qMpwG/v9aFHRQ6Dj1EagLEmP+TrrdbzVJmdgn2nO+EPEGSkOKhN4RAzJl854Gb1/gRTwISdAnbhwOlOweMLRoUDwP9uOY7Ofl/E0FJhehK28zyB+VgYRGTPCQH+Ewokb5ovLPv+6MLxEa+x9WgbPj8u/fp6EbuX2G1WuCXOTYQE8KvLJyHb7cSR5h585R9b8PnxdlgZoe6fXsT6sPxWEwpFjYQJAJ0O4aVonkFuB2ZmvsTVqxrrNJQMu/qlA4pkuyUhyoeJSq2oD1Cr6DarI6YFo2zgYk2+J7j/ym2LLFU5qYLyL90+h5YZGrUAm7r6ubIlO4uW7XaiVewDHDpuBwIET62rBxBZFq7Jc8uWgKeVjoq4+O/1+tHV70NVTmpExq8yOxWF6ZH7xNProhsGASAY0PvlW3sj7p9RHhmE9fkIzp+YjzXfWYxvLK2Cy27B9uPtGKyyGSO6jGSznxSKFhImAPT7hQeEycXDvxS0KiQXoIe1Kn2ABOEeHTE0uxJbBIMgx9pRlaPNs3PnCe0BYKL8hp4km6ZJd/4EMNX/G3rmV6lrAbIOGGzpl7UqzPE44RUdakoygtPvaw+cQd2ZbridNrSJqhYpCtUdKcu17tBFxI3zyiQvEG5bUh1x22ufn0Rzl7wgvhJ8O7b9DZEtGl+cWSr5vM8ONyPFacO3z6rB+3cuxqVTCyMeoySLJJVZFGvFSmkvUihyJEwAKLaBO3eCNjeFRGZcQRpcOjWd1u5vUrQ8CiiIC5ZrDEgo0SF0BGnV3LC9Q2SRpYSU9ZYZYRiGKwMrIcwA0gngoWZKiXpJkQ2I+MGI02aRDFhKQ9qCbPbvsmlFnG8wi9gSjs9yiel5PyFIS7Lj0qnSfrxXzSiK6Bkf8AUipni1wiDsMAIAu0RyNayQv5j/bDzO/bsgPQm/WTkFr94+TzC5q1QNHiVRMRgQSX8Z6eNOGf4kTAD4zq6Tgr9nS6TZhyN6sx4n2npR19Qte79c9g8ASjOoCHQsqcpORWroEv9kW5/mgY1tx7RbWGWmJE4GQK1cnWS3ICPFgb2n6QRwvNDSa81mAPkBYLbbKZmNKxqVhLozXViz7wwYBphTmSEQvLdaGBxs6Ix4HgBMKvLIalxeM6tEUmMQACwWC86bGJkwePbTI5q1U8Wcxxv2uO+13YL7rFaLpBzLZ/XNEbdNKkrHc7fM1rSmnNUci50GfxSdJEwA+ME+YW+bzTYyhhUumqI/07l2v3wZOKBwvMsfAX2V8cRiYTCtNDyl169x+u9QYzf6vNoaxRNlCAQA8kJ9gHLnrZo8Dw43daPPG0CS3Yoyg32qKcbAVhX4F5dypcgkhw1/D7loLK3Jweci7dLsVAf6ZRrjxBk+Hy9yvH6OdNmV5YfnjRH8bbUwONneh9V7tCkniPnVZRO5f2+qj7xAmyPhVNLc7ZWswNTkabuwkcqo8slyJ0b2n2IeTBsA+kWRyuGmnji9k/hypYTkgRqKAaBCBjCHagDGnFpeSY0VhlWDIOj0osUaMBFs4FgKQiVgOUmnYP9fMPs3Nt8NK81wmJLu0JS6OAMohgHQ0eflpF9unFeO9YeCWTF2E5DL4gHAWePzhOuGev9cdqvqxWuOxyVouWDfK1uK1ovLaefeMwFwok14frpOJiDdL5Pd5FOdI32ho+aaU5VNW3go+jBtANjWG54eS7GqW+AMV5IdNuTqzOp8Wtciq3YvbhrmQ11AYg+/D/BIi/aLmp0n2uFTSt+GyEoAGzgW1g6O9UkWE+z/Yy3gaP9fvFA7SbT3agsArRYGL2w6ju4BP6pyUjGvKhMHG4NDFGzSr61H+qKoJjcVBenhIG9/Qyd6Q1nxFIe2atCdK0YL/maY4LFy32n1oEwKvpvPj17eKbhvtsz09H9lPNv5e4DcBDTxK1cBxhfSfYSiD9MGgF5eb8bZ47MRvVJS4jOvSp8cTK/Xj80SZQlAOQOYKBOkiczk4jTuYL/zRDuS7Np2wZ0n2uHXoBmhVVrGDLBi2FaL9Am8MjuFOoCYgIJ0bfZi/AAwx+1Cv0jix25lOBHmVXPL0OcNoKNP+Ji2HmlZoIumCCdmH3pnn+B1tbBifB7Xgxt8XnDfi1YY+teXT+b+vWafsOrCMAyyJAay5MT6+dntU21BgWmX6NjQ0Kk8tTylOF3xfgpFjGkDQD7XzquK91uIK9fPKdP9HDkPWaUMIC0Bxx63y46aUCmqq9+nue9y58l2Qc+TFMkOKxw6p8bjCZsB7JPJVgsDQJrdiBfTy9SlYABhD2C224nNR4UXoXarBUeae+Bx2XBpbSE+ORh5jJLbws+ZEC7/bj/Whrd3Rde7d/m0cEsNa2P30pYTaO/VX2FKTbJzF3MBArR3CwO0RaMjv7ejLdIDek7efst+B8vG5Age09gp7+AEBAdKKBQ9JMTZorZUaG8zzF3gIphSkq7b+k6uD1ApA5issZRCGRzTeYbxyQo9T3z2ne5UnOAGEscGjoWdApZyA7EwgNXKoL3XC5uFweg82t8UL2ZXqNuLidszs1Od+LROOPXK2sZdNbMEyQ4b3tkdtHtjs19ymbzSjGRU8vrbHnw7mP3ToiMp5jtn1Qj+TnXa0Ov144XNx2WeocyCqnCp90ev7RLcd53EhbsvAJyRyORJTVt3iTRh2kQOTuJvK1FE4CnmISECQDGJlOUwijEaJ8VYdp/qkDzQyKkepDpH3ncaL/h9gEoZWT5ePxG0RUghVXIyM2lJdtmTeGV2KvadDvaHVeWkwmnTf7KnGIMWf1nx75jjcWLTkRbBbb1ePywMcN3s4IDElqNtAMIBoJxG6YWTw0oI6w424eODTbBbmajsQFNdNkzn7X9sH+Ez6+sVNVLl+NUV4TLwG9tPCe6TK8mygS8ffusGux+L9RD7Rbu/+N1SlxyKXhLyrJ+WpK0nZThx/mRpk3EpWIPwjw9GZgGJTJGFleSgxJ5pJeETapuO0pNasJiXYBkAhmFksxb8CWBa/o0vRaPU9UHFwUe224n9EsMVy8fmojikN3osNAQVCA03ybW4suVfQggeDPX+XTOzJOqp8B+cN5b7tz9A4LJbUN/cgw9VXJSkyEtL4jJxfgL0iPoepfqq/7slchCEvx+MDbWINGtUCQCoBiAlOhIyACzRcEAablwzo0TzY9lesbX71X2BWcqpxtqQUZyRxJVrGzqU+3r0kONOrAAQkA9aK3NSsJsOgJgCl4ZSq1h1IDPFKVByYFk1rwwA0NDex+lgKslhpifZud//vT2N2Hq0DS67Bbctjb4vfFrpKMG0PNt/93SUkjBTi8MXKD9+dYfgvmVjc8QPx55TkU4nZVnh4280CQ6qAUiJhoQMAGeVq5ckhhvuJLukurwSHx04o7msQW3ghg6GYTCjLB0ANGn7aSVRbOD4yA3BVOWkYjcnAUMDQLPj5aXvLAwDh80Cn2jbzk9zYk5FsGfubYkyqBRfmFIAhmEQCBD8OpT9u3Fe+aAvdm6YG9bpa+/1gUFwkrdewUVJjv/jTQO/vE1YBpYSqO4ZCEQIu08qTOf+3RrFQErxCEyKUAZPQgaA0bhjDAf0yMHYLAyaugawJ2SjpUZBgpUPEx0tfVV6kbPJMjNyJeDsVCdOtgezo3rtECnxxSLTi3bxlEKuVPxhSDZFzev8/EnBY/1rn5/E3tOdcLtsuHVhxaDf41cXVgqGCVndQtalRA/VuWGBaZ+foJU3DVyT54kY1gAibeEmF4e38YaOvoieSrnvlEVvjziFAiRoAFg9Qjf2a2cp2x3xYRuktZaBqQj00MIfBDGqfycrgTQAWdgSsPgb6PMG64Klmclwu0Zez6/ZSNYxbyG3OX9xdvj4xQp82xUCQJsluJ94/QH85t39AIBbF1Yg3YBpd5vNgkU1YZkW1pXn+c3HOIcRPVRlh0u4v3xrr+C+wlGRWe7nNhwT/F2cEX5+c9dAhJC22iFiQuHIPCdSBkdCBIAHNGaxhjuzKjJUDwQsA6GJUSVbOD45NAAcUsYXpMHK7n0G9W8nYgaQtYOz8o5EFobBoTPBCWBa/jUHelwm5IYzWOHvQICgMaRQ4FMQN59flQ2rhcHzm47jSHMPslIduHFeuY53rcw954/j/u0LEGSmONDZ58NLMm4dSvz80gncv8VuH+dOyBM/HJ/VCyekbbwdoGfAz00Cu0LT72oZQOoCQokGUwaA7/A0mRgAr26PTqNpuMEwDArTtU3rstpqm460oGdA/Yo2l4pADykuuxXj8oPBjVeDw4cWEk0GBghPn9ss4UOR3crQCWCTMatC2tpMCrlgxRIKDPec6uB6X3u98h5PX5xdgj6vH4+8dwAAcNuSKqREIf0iR0V2Kkp42Tlf6KL57+vrQVQ0N8XMLA+353j9BEeaw72EUkL+TV0Dsmt4/QEuA8jaP6pJvFRk0R5uin5MGQD+33thmx+304Y1+7RPsw53zp+oXQ4mK9UBr59ECLJKkYgTpInOLBm/0GhJxAxgPucGEh4FtVosXImQ9v+Zg1kV2vuPLRIZQP5Nb+4IDkqoybkuGp2Df3x6BKc7+lCQ5sI1s7QrIWjlq0vC08TtfT44bRbsb+jCeg3HTDF5vIvoR0NBKwAUZyRLVm7qQlluMQES9vRmFR3UKj9JGgXlKRQ+pgwA3/vuMk4/Kdlpw5Em6R1lJHLrokrNj2WvItX6ABmMTHHteMPvAxwsVgsDjyvxnFzSk+0Rnqc2C4O60DQmLQGbgzIdMlFWhkFTZ6/gNhsvgmGDq1SnfG9nvseJfp8ff/jgIADgm8tHx0QMfOX0IoENGyvI/Pd1+odBfnxBuKT88rYTggxfaUbklO6/Nwn7AC0SQylasFEJQEqUJMRZv2vAQK2MBGdUikOz+TnbSL9WReCUb5BOGTpqDQwA05PtCekEEBSDjmxrICR4EqSZaXOgJjLOT0A57Rb89r2Dgvv5wRvb36mkL3jVzGL87eN6tPZ4UZGVgktrC6N41+pYLBacx6uqnApNnr+z+zROtPXKPU2Sc3mv4wsAm46EvZAvmhL5/lfvbhT8zQ+SM0SDLkoVaSOGYigjk4QIAPk6oTaqeK75avxMZz+sFgZ1Z7oVXSToSTY+5Hpcuq70lchOwPIvi9gtgc2c0OyfebBblU8V2e5wEM8AeEnkrZsayk73ef1oDwlED/jk+/8unFyIv3xUBwD49lmjBUMSRnP3+WMEf+d5XAgQ4NlP9WUBGYZBOk/E+clP6rh/f1GifH20Rag5mMTzYneIsuJKx+/8dHr8pkRHQgSAfNR0o0YCl0zVpoPY1e/DhNBJtF9Bbp+aiMcPo0TNE3mKW3wCY/ueaACYOCTxApY+bwDdXuHxhs1ofXww3I7S0ScteGxlgOc2HkNXvw/j8j04b4L2vudoyEp1oZonhM9Kwjy38ViEYLMa31o+mvv3WzsauOfneFwRfXy+ANDeE/4O0pLCAeCA6HjtV0gBVmXTARBKdCRcNDUqAbXOjOYaHXqA5SGLod4B+QNZgcbJYorxzDQoAEzECWAW9gKElbxgpUHoBLC50Fp7kVIdYH/jd3YFHUCS7VZZC7ixeamcLdtd59RIDpUYzffOqeH+PeAPwOOyoaV7AK9/fkrhWZFcx3P+IABW72ng/paa1H1z50nu33x7OvHxOqAQANbk0wslSnQkXABYmU09a9OTtfcBstkUb0A+A1gk0aBMGRpqS4zpA8xK4BIw2wPInuJY6QuaATQXuanyQ0Z8PT9Wg5RPaehCdOvRNgDKtoXZniT0+wKYUTYKi0dnyz7OSJaPyxNkMVmeXqdPEsZiYQQuHs99Fh70uHxaZB/gC7xSeTFPkqazT7sY9dh8t/qDKBQJEi4AXFyjXY5gOFOusQ+w7ky3qrl4RRYNquPFmDw3HBqDeSWGQwaQ9a0mCMo/UX9TczGnUv7Y26fQzwcAZZnB3/JoSw+A4KCIHB8dCJaJ7zp7zJAONl0+rZj7d0efDzYLgx0n2rH1WJuu17mR5zP88cEmnAmJXq+cWRzx2H2nO7l/V+eEA7kznb2cm5MaRXQ/oURJwgWAF00amT7AYs6dGKkuL8XBM12YV6msN1dCM4Bxw2a1YFz+4EudmSmJmwFkJ0z5fU5jCzxDUvqjaGd2ZY7sfUo9xkBQC6+xo497XEtXv+TjGASrFotGZxvWHqGV750jHAZhL5zZcrRWvrmiRvD3q9uDZd5Ryc4I7cOufj+8oYzp1NJ07vajrT2aB8RoDzclWhIuAMxw0341AJhXpa00MuALYGKRcoChJvFAiS3zqgYvCK1UUjM7nEUYLwAcR/uaTEd1nvywQb8vwDmA2C2Rp5WyzBS8Her/YwC09UiXONkt4Dtn1UjeH0tSXTbBMEhzaBjkzR2n0NjZp/l1HDaLIKv//Maj3L+rciLLtRvrg7qI43g9rydb+zRl9RkAyY7E0/+kmIOECwApQfT0R6mVEhLRQWI4Mb1s8JmORO4BTE+2C8R4Adr/Z0YKJPQaWbz+ABwhqZYUCV3R/HQX1uwL6pFmpDiglC88b2Ke6kVrrPj5JRMEf49KtsPrJ/jXhmMyz5DmC1PClaq9DV3YcypobXi1RBn4H+uDr82XkGntGdCUAZT6rikUrdAAMEFJcdpQoDFzt/NEu6J+opx5O2VomFqSPujXSOQAMCgGLdyW6QSw+VAKSPwBAk8ogJESeHbarJy/c0ayfE+yhQG+vWK07P2xZkZ5psCZpr03KNPy7AZ9moB8VxAAeGnrCQDA5dOKIh67sb4FgNDvt88b0LRP5xikI0oZmZg+AFQSwBzpzFHp7WP55GAz3C7pg26ynQZ/8SY92SHwEY2GjASXR+K7gTAAqnOptpnZULpQDBB5v1oGwQEftoza2iOt/wcAl9UWSZZJh5JLpoandQMESLJb0djZzzkracGd5BB8Hy9uPgafP4AUpx120RfVJNEP6QsQTcFdmYS0DIWiFdMHgD0K+nUjnSnF6Zoed7K9N6LExjIqgTNHw4mZ5dH3AaY6bQnv5czPANosFlXnCUriYLEw2HOqA+y1PCu0LMUdy6uH6F3J85MLxgv+ZntTpfQNlVhYHZ6abu724pNDwV6/MSLZFgLgWHPQFYQNDQMEuHhqIaeNKQcVgaYMBtMfZftV5AVGMhOL0jU9LkDCeoBishJ4enQ4Mb8qenmjRB4AYeEPItkMkMWhxAaHhjOG+FhjtzJ4a2dQUNlmYWT7/y6YlG8KSROHw4pSnjJCcMBFWt9Qif+7dJLg7/9uCWr+rZpTFvHYZzYEB0X4ycGiUclIVyiXA0BlDpXwokSP6QNAfgmYtrsKGZvvhtZzpdhaiMUoL1rK4KgtjV4Qejj0AeXz3Gho9s+8TCiSL8+yR2qxfVqS3Yr1dcE+N7dLfiDtnvPHyd431Nx3kfC9JDv0n31y05ME7ilv7zqNzj4vLpwcKWW2enfQMYSfyfdrCDgL0+MfMFMSF9MfafnXkqkKB4+RiNNmFUgHKNEr42mZrzDZRxk6KrJSoh7GSeQBEJZ8npexVpcbytAzr1Jefoq9WO8X9cp5XHYcbOwCAAzI9NFZGXPJUS0Zk8tthwyCen0setrSJxaFp9n7vAG8teM0HHZrhPj7sZZgCTiFp9jQ2CmtlchH7KNNoejB9AEgn2xP4pe6jEarXIJX5mqyaBQNAM2AxcKgMMqD+fArASfUYWlEMbYgXfY+tsrgJ8JjTUaKnZum7Za5EF0xXl5kOl4sH5sLIJyEYEM2Pb2Av7liiuDvF0NlYPGFuzcAdPf7MCo5vC8fDvUFKpHnoQEgJXoS6kg7Npdqg4mZPEi9rDJqA2capkXpC5zILiAsNXluTkeO5v/Mi9IFI+vhLM6QaRlQumVB1aDeVyy4+zyhMwj7sbr6ffj8eJum16jKFZbMNxxuwbGWHtw8vyzisa9uPylQAzjR2qP42lZGmDGkUPSSUAHgeRPy4/0WTMfEwvRBPZ+vfE+JLwtrojO+T2QfYBa71ZLwUjYjAaWWETnJrq6+YNZPqbKvVdFgKCnKSJHdt771720RvY5ylImsNl/eegLnSpzLXtx8XHBBfqJV2X1kOLR+UOJLQgWAy8ZGPyk5XBmdmyoQLtUL9QE2D4tHR1cGoycCylCRqRCkywWATd3BXja51jmnFab1fb5lQWXEbRaGwaEz3fjlW3s1vcavr5gs+Pu/W0/AYmEi+gD3nu7AOJ4DzvFW5RJw4Sha/qUMjoQKAB0OmiEQY7NaBuWaQPutzMOoFAeYKM6D1MqPMlQoBWpEJsJrDen+yQ1PLKo2X/8fy5UzIp072OGQp9bV4+MDTaqvMb1caPV4uKkbW4+1YZJIxqur34+pxeE2kLom5QCQtu9QBgs9+w8DJhZGFwDSH998pEUx6T4chkAoiY9cgDfgVx6bvXp2aQzejTGkJzswuVh4fO33BTA9JNt01wvbuQEXJbJF++iLm4/jK4sis4tnOsNl34Z25Sng0gwaAFIGB40BhgHiA5RW3C6qrGg2KqNQ9qdi3pShJDNZ7rQRnW0n3zHDjEiVgTcfaUWux4lT7X2495Wdqq/xk4smCP5+bftJzKvKiHjcvz47xv27TSWw5GtnUijRQAPAYYC4lKCVtCSaOTIbWt1dWKwWBp4kOglIGTrmybjWRBP+2RjAavI2lGVjcwT+vUl2KwiAjl4fLAzw8raTeP3zk4qvcc6EPMHfHX0+rNnXBKdNWFLfWN/K/VtOvJ8l30S6iZTExNx7HkUT5ZkpcEchB5BBe8dMx9h8eacFKdKT7GCiaRykUKJkaqlxGbvZFdF7YA8VLrsV500STu3OrshAr9ePFEfwuHv3SzvR0CE/tWuxMHA7hRWXF7ecEPT8AUBTV7jsK2ffyUJF/CmDhQaAwwCLhcGEKPoAs900A2g2SnT29WQNAxs4SmJhpHLAJdMihyzMyOW899nr9WNGaQbKs1LQ2e9Dkt2K9l4v7nrhcxC5SRgA314xWvD3mn2NuG6usP+RIKyDqZZRNZNzCiUxoQHgMGFSFH2A+R56BWk29DqzDAcfYEpiYWTm6TxRadSszKnIhIWXaX/0g4M4f2I+0pLs6PX6YWGAtfvP4B8bjsq+xnVzygR/+wIEje3KWn9ySUCnlUEqFYGmDJKECQBT6bauyKQoBKGLqAag6dDb15NNA0DKEFNgkP+sBUCSIzEO7DarBUl2YQn39x8cxNUzi2GzMFyg9vM39uCwjHyLzWqBU+SK8t+tJ6Ek4+oPSPcB0uwfxQgSJgAszqTBihKTorCEK6XfqemwWS3ISLZL32eJ3F2pCDRlqElLkt4+9TKpMLGsPfm2a6z4/uMf1mHlDGF5+Fv/3gafjPf6qrllgr93nGiP8HPnJ/0GfNIpwGIqAUMxgIQJAKeWRo7MU8IUjUrSbaVVRGUETEnhKOnAXCoboOTMQKHEAqOGjs6dVGDI6wwVfA1sh5VBsiM4DfzPz47hnPG53H3bjrXhsTWHJF/jW7w+QPbl5PZ3ABjwS9vN6W0VoVCkSJgA8AuTC+P9FkwNwzC6BaGpg4Q5KcuSPiFI5QLob0iJB0bkAM9NkP4/MTaLBR19fiwbkwuXzQJCgLd3NWBaaXii97fvHcCO4+0Rz3XZrWCrwOz+vPFwa8TjWHwyItp0AphiBAkTAM6qNLdYqBmYrLMMPCrFmFIOxViqdIhBy5nVUyixpDpv8O0jxQnag8zqbr6+4yR+s3IyHFYLCICtR1tRFmqr8QcI7nhuK/q8kRm88yeEJWWcNuB0R5/sidgvM1VMNQApRpAwASBFHVYQWouvOgPAaaNOIGZEz4mR9gBS4sH80bnqD1KgMis5YfUrHVYLLplaCEKAP689jBe/OocbBDne2oP0UA9vXVM3fvnW3ojn//TisCtIIBD8DjJ1XoznGzSIQxnZ0ABwGMEOgqjohwIAnEqjZ5S4UqTQEySG+gBT4kFFln7LQj7Lxg4ugIw3Pzh3DFKdNmw71obdpzrw3C2zYWUAXwDo7vfBFroKf2pdPdYdbBI8Ny3ZwV2ke0MHay1+wnxoBpBiBDQKGEbkeFzI82g7MBg1yUcxHj0N3noHfygUIxisD+3ycYkdAOZ4XPjm8moAwP/9bx+qclLx1E0zYWEAr5/AwivDfPXZLREB3uzy8FBjdqoDA8qubxHk0R5AigHQAHCYIZYUkCOLBg6mJdfj0lTGd9kttIxPiQsFg8xARetfbiZumFuG0bmpaOkewEPv7MeC6mw8dm0tGAR9fFn/4PZeL772j82C5/76isncv7v6fbrWTbZbqAg0xRBoADjMYAdB1AKIbI2ZQsrQY7UwSE9WD9BpFpcSLwaTAcxOscFlT/wLF7vVgp9cFOzne3bDEew80Y6zx+fjN1cGgztvgMAaOsN+cqgZf/u4jntuwahkTgam16sv/VdIJWAoBkEDwGEGe2VtVYkA82kAaGq0lPIzNASJFEosGEwGasEgB0jMxJzKTFw4uQABAvz4lZ0IBAguqS3Czy8JBob+QPgke/8be7D3VAf33NF54T7KcXnaeyrz0xNzeppiPmgAOMxgtQC9MvpRLNQGztyUaHBpoRqAlERkUU12vN+Codx93likOKzYcrQN/916AgBwzaxS/PC8MQAANr8XIMDKP69HnzdY8n34iinca5zu6Ne83mDL7xQKi2kDQL6VTmKKBcSHUSkOlGgI7nKoh6ypqc5RzwjkeuhvSIkf0W5+fMHk4UBemgvfWBYcCPnlW3u4gY9bFlbijtDtLO29Plz15w0ghGAcT7i/pcfL2ctpWY9CMQLTBoD8xtiStMTvFxlKtPgC0+lRc1OZre71WUCt/ChxZHZ5pu7nJFmBwmG43d44rxyV2Slo6hrAw+/u527/1orRuHlBueCx24614f43dgMQZvMWVGn7PqkEDMUoTBsADvAygOdOKlJ4JEUMGwDaFPoAaQBobrSIQdMsLiWeTCjS788+oyIrYQWglXDYwgMhf19fjz28Xr97zh+Hq2cWCx7/14/r8eq2k/i/y8Ki0AcaujStRW3gKEZh2gCQL2a8cmZp/N5IAsI5gigEgJkpNHgwM8UaxKBpDyAlnhToECxnmacxy5WIzK/OwnkT87iBEMKzcfvFpZNw0eR8weO/9Z9tcLvCF+JHWnqRrUHYnWYAKUZh2gCQT3m2O95vIaGYUJgGhglqUcmRQR0kTE1WqlNVyieTZnEpcSSaYYTaUv1Zw0TinvPHIcluxcb6Vry87YTgvkeursXysTnc3/4AwaqnNsLjCk5UEwDnT8xTXYP2AFKMIiECQIo+Up02VGYrDxGkOGhfpZmxWBhVnb8sWgKmxJFotAAnFmoTqk9UCtKTcPvSKgDAz9/ci84+oQPIEzfMELiAtPV44bKHr/R2nOyAEqkOK9wuqv9JMQYaAA5TlAZBkh3WYdmHM9zIVgnwsmgZnxJH9JYix+a5h4UAtBo3LyhHeVYKznT247erD0Tc/69bZmN8friq1dgZDhK3HW1DnkdeY3GwFnwUCh8aAA5TJof6AO3WyEAvk5Z/EwKlPkCGATxJ1A6KEj/0BnOzKoZv/x8fp82K+y4aDwB4al099jd0Cu5nGAavfX0+CtMjA2g/AVbNKY+4nYUGgBQjoQHgMIX1BJb6gbW4TFDiT7mCFEyynWZxKfFHzxZYO8z0/5RYNDobZ4/PhT9AIgZCAMBiseDDu5Yg1RkZRO861RlxGwt1cKIYCQ0Ahynj8j2wWRj0SziC5NKDSEIwNs8je5/bRbN/lPhTmq69mlBbkh67N2JCfnTBODhtFnxa14LXPj8Vcb/NGgwCraILuTd3nJZ9TToAQjESGgAOU1x2K2rypKens6h8SEJQqeAGkpZEy/iU+DNXo69vRrJ9WApAK1E0Khm3LQkOhDzwxm6BuQFLZqoTT944XXCbnwA1OdLZ/wKJsjGFEi00ABzGyA2CUPmQxKBolPwJkwp5U8xAcYa6Yw0AzCzPHJEtC7csrEBpZjIaOvrx6HuRAyEAsHB0Dm6aJ+z7O9DYLfnYPCoCTTEQGgAOY1hBaIdoEIRqACYGmSkOWS3AbDf9DSnxR2tGqrY0PbZvxKS47Fbce+E4AMBfPz6Mg43S/X3fP3cMqrLCwbScgisVgaYYCQ0AhzFyGcCMZBo8JAIMw8hqfuV6aCaAEn+02pLVloycARAxS8fkYvnYHPgCBPe+uitiIAQIWsn94dppqq9FA0CKkZgyAPzH+jru30p+thRlRue64bRZMCAaBKHlw8RBTrJHSkKCQhlqtAQkDILuRCOZH18wHg6bBZ8cbJYd8qjJc6MyS176KdVpoyLQFEMxZQD46cEz3L89dIOPGrvVgnEFkZOkVAcwcSiQybBo8QqmUGKNlqnUScXpI0IAWomSzGR8dVElAOD+N3ajZyByIAQA/nHzbNnXoBPAFKMxZQD4++tmcVp1Dpsp32LCMCl05c3PpGZQB4mEoSwzGOiJ8+A5VMqHYgLsVvXj80iTf5Hjq4srUZyRhFPtffj9+wclH5OfniSrrUjLvxSjodHVMIcdBOEXgdU8ZinmgZXyEXcN0SwuxSw4Vc4iI7n/j4/LbsWPLwg6hPzlozrUnemSfNzEQmn9TxoAUoyGBoDDnMnFwQygPxAMISwMAyvtq0wYxhfISPnQAJBiEqYUyutVAsBUmgHkWD42B4trsuH1E9z32m7JgZBfXzFZ8rlUAoZiNDQAHOaUZ6UixRHuv6GxX2JRIWMH57SN7J4qinkYX5Ite1+O2zniBKCVYBgG9104Hg6rBWv3n8HbuxoiHjNaxgGogGYAKQZDA8BhjtXCCCbwLCNQjDWRSUuyRwTt9BekmAklLcDaklEjUgBaibKsFNyysAIA8LPXd6N3wB/xmNKMyKCZDoFQjIYGgCOAycXp3L9pAJhYMAyDFKct4jYKxSwoaQGOVAFoNW5bUoXC9CScaOvFH9dEDoT83+UTI24roJlUisHQAHAEMJGfAaS/eMIxSiTcTcv4FDOhlJmiAyDSJDms+NEFYwEAj39Yh/omofXbrPKsiOfQDCDFaGg4MAKYHJoEBmgGMBHJ9Qhle2gGkGIm5ErAdisz4gWglTh7fB4WVGdhwB/AT1/fLbiPYRhMKQ5/dwwAt6gSQKEMFhoAjgCKM5K4wI8GgIlHSYZwEIT+hhQzkeOWDgDHFaSNeAFoJRiGwU8uGg+7lcH7exuxerdwIOQfN8+GKzTsZbUw9MKPYjg0ABwBMAwDR0iwlUrAJB5VOcIAUIP2LoUyZMgdU6gAtDoV2am4eUFwIOQnr+9Cnzc8EJLqtMFpp8dtSuygp5IRgick/uykzioJxwSRFqCVZgIoJiMzJfK4Qvv/tHH7kirkp7lwrKUXf/rwkOC+AE+/lUIxGhoNjBDoBWTiMrFIGABa6I9JMRkzSjMjbqstpQGgFlKcNtx9fnAg5LE1h3CspYe7zx8SiqYZQEosoAEghWJy0pMd4CcAbPRkQDEZJVluwd+5HicVLtbB+RPzMbcyE/2+AH7yWnggxB8I/p9m/SmxgAaAFEoCkMRrpqfZAIrZEPvUUgFofTAMg59+YTxsFgar9zTgg72NAHgWnnSfp8QAGgBSKAkA28MJ0H4givkQi0HT/j/9VOW4cdP8cgDAfa8FB0ICtARMiSE0AKRQEoAct1P9QRRKnBBrAVIHkOj4xrJq5HqcONLcg0ffPxAOAOlFHyUG0ACQQkkACqkNFMXEiDOA4wuoAHQ0pDpt+OF54YEQFhr/UWIBDQAplATgrHG58X4LFIosmSkOsDGK3WqhAtCD4KLJBZhVnoFQ+x+FEjNoAEihJACX1BYhK5WWgSnmxGJhuN5UB1UqHxTBgZAJtO+PEnPonkqhJAhU/oViZmzWUABIxeYHTU2eG6vmlsX7bVCGOabdUwcGBgT/p+sl1nridYfbWvFcb7huM3S9xF4vyRqsWTIB35CsxzJc9/sfnDsGHvvQXvQN9210uK+nF9MGgCQ0/cT+n66XWOuJ1x1ua8VzveG6zdD1Ens9NlQZKfthrLFZLUPu+z3ct9Hhvp5eTBsAsiKiQyUmSteL7brDba14rjdctxm6Hl1vMOsOx/XoMYauF0tMGwA6HA7B/+l6ibWeeN3htlY81xuu2wxdj643mHWH43r0GEPXiyWmDQApFAqFQqFQKLGBBoAUCoVCoVAoIwwaAFIoFAqFQqGMMGgASKFQKBQKhTLCoAEghUKhUCgUygiDBoAUCoVCoVAoIwwaAFIoFAqFQqGMMGgASKFQKBQKhTLCoAEghUKhUCgUygiDBoAUCoVCoVAoIwwaAFIoFAqFQqGMMGgASKFQKBQKhTLCoAEghUKhUCgUygiDBoAUCoVCoVAoIwwaAFIoFAqFQqGMMGgASKFQKBQKhTLCoAEghUKhUCgUygjDpuVBhBB0dnbG+r0I6OvrQ19fH+x2Ozo6Ouh6dD3TrUnXo+vR9eh6w2lNul5ir8fH7XaDYRjFxzCEEKL2Qh0dHUhLSzPsjVEoFAqFQqFQYkN7ezs8Ho/iYzQFgPHIAHZ0dKC4uBjHjh1T/RB0PbpePNak69H16Hp0veG0Jl0vsdfjoyUDqKkEzDDMkL95Fo/HM6Rr0/USe714rEnXo+vR9eh6w2lNul5ir6cVOgRCoVAoFAqFMsKgASCFQqFQKBTKCMO0AaDT6cS9994Lp9NJ16PrmXJNuh5dj65H1xtOa9L1Ens9vWgaAqFQKBQKhUKhDB9MmwGkUCgUCoVCocQGGgBSKBQKhUKhjDBoAEihUCgUCoUywjB9APjSSy9h+vTpWLBgARYtWoRdu3YpPv7jjz/G7NmzsWjRIsyePRsfffSRrtek69H16HrxW28kfEa6Hl2PrkePMbH+jJogJmbDhg0kNTWV7N27lxBCyNNPP00KCwtJR0eH5OPr6+uJx+MhH3zwASGEkDVr1hCPx0Pq6+s1vSZdj65H14vfelruT/TPSNej69H16DEm1p9RK6YOAC+99FJy5ZVXcn/7/X6Sm5tLHn30UcnHf/vb3yYzZ84U3DZjxgxy5513anpNuh5dj64Xv/W03J/on5GuR9ej69FjTKw/o1ZMXQJ+7733MGPGDO5vi8WCadOmYfXq1ZKPX716teDxADBjxgzB45Vek65H16PrxW89Lfcn+mek69H16Hr0GBPrz6gV0waAzc3NaG9vR15enuD2vLw81NXVST6nrq5O8fFKr7l//366Hl2Prhen9erq6ug+T9ej69H16DFmkJ9RD6YNAHt6egAgQkHb6XRy90k9R+nxWl6TrkfXo+vFZ72R8BnpenQ9uh49xsR6Pa2YNgBMTk4GAPT39wtu7+/v5+6Teo7S47W8Jl2PrkfXi896I+Ez0vXoenQ9eoyJ9XpaMW0AmJmZibS0NJw+fVpw++nTp1FRUSH5nIqKCsXHK73m6NGj6Xp0PbpenNarqKig+zxdj65H16PHmEF+Rj2YNgAEgKVLl2LTpk3c34QQbNmyBcuXL5d8/LJlywSPB4BNmzYJHq/0mnQ9uh5dL37rabk/0T8jXY+uR9ejx5hYf0bN6JoZHmI2bNhA3G432bdvHyGEkGeeeUagdbNq1Spy7bXXco9n9XM+/PBDQggha9euJW63O0I/R+416Xp0Pbpe/NbTcn+if0a6Hl2PrkePMbH+jFqx6QsXh5aZM2fi6aefxjXXXIOkpCRYLBa8/fbbcLvdAIC+vj54vV7u8aWlpXj99ddx1113weFwoL+/H2+88QZKS0s1vSZdj65H14vfelruT/TPSNej69H16DEm1p9RKwwhhOh6BoVCoVAoFAoloTF1DyCFQqFQKBQKxXhoAEihUCgUCoUywqABIIVCoVAoFMoIgwaAFAqFQqFQKCMMGgBSKBQKhUKhjDBoAEihUCgUCoUywqABIIVCoVAoFMoIgwaAFAqFQqFQKCMMGgBSKBQKhUKhjDBoAEihUCgUCoUywqABIIVCoVAoFMoIgwaAFAqFQqFQKCMMGgBSKBQKhUKhjDBoAEihUCgUCoUywqABIIVCoVAoFMoIgwaAFAqFQqFQKCMMGgBSKBQKhUKhjDBoAEihUCgUCoUywjB9APjb3/4W27Zt4/4+evQoFi9eDJfLhbKyMtx6660AgK997WsoKyuDy+XC4sWLsXDhQkydOhWrVq3Crl27JF974cKFWL58ueR9AwMD+MEPfgCbzYb6+npDPovcev/5z39w1llnYdmyZZgxYwYuu+wy1NXVxWy9V155BRdccAFWrFiB+fPnY9q0afjPf/4Ts/X4PProo2AYBmvWrInZevfddx+mTJmCxYsXc/994QtfiNl6AHDkyBGsXLkSS5cuxaRJkzBt2jR88MEHMVlvzJgxgs+2ePFiVFVVYeHChTFZr7+/H9/61rcwZcoULFq0CLNmzcJLL700qLWU1vN6vbj//vsxe/ZszJkzB7Nnz8batWsNe31A2/79+OOPo7a2FvPmzcP555+PEydOxHS9jo4OfOlLXwLDMIrrDHY9n8+HJ554AkuWLMHSpUsxbdo03HTTTWhsbIzJegDw5JNPYsWKFTj77LMxe/ZszJ07F++9917M1uNz5513gmEYTcfxway5atUqzJ49W7BfsuenWKwHAJ9//jkuuOACLF26FOPGjcO8efOwc+fOmKyXnp4ecdwpKirC9ddfH5P1WlpacOONN6K2thaLFy/G/PnzVY8Dg1mvq6sL3/72tzFnzhzMnDkTS5YsUfwuldbTek7Xe4wxHGJySktLyZNPPil5+7333iu47d577yWlpaXc3z6fj/zxj38kbrebvPTSS4LHHj16lNhsNmKxWMjJkycF9x0+fJjMnj2bXH/99QQAOXz48KA/h9J6drudvP3224QQQvx+P7nhhhtIdXU16e3tjcl6Z599Nnn66ae5v1999VVisVjI559/HpP1WE6cOEFKSkoIAPLBBx9EvZbaevfee++gX1/PemfOnCHl5eVk9erVhBBCAoEAufLKK8mjjz4ak/UWLVoU8fjLLruM/P73v4/Jevfccw8pLy8nHR0dhBBCtmzZQhwOB9m2bVtM1rvrrrvIuHHjSFtbGyGEkLfeeoskJyeTgwcPGvL6WvbvF198keTm5pKGhgZCCCE/+clPyJQpU4jf74/Jelu2bCG1tbXkiiuuIFoOy4NZ79ixY8TlcpHt27cTQgjp6+sjy5cvJwsWLIjJeoQQMmbMGPLhhx9yfz/yyCPE5XKRpqammKzHsnXrVpKVlaXpOD7YNW+44QZd54rBrrdv3z5SUlLCHbcHBgbInDlzyGuvvRaT9aSOO9OmTSOvv/56TNa79tpryZw5c0h/fz8hhJCXX36ZuN1ucurUqZisd8UVV5AlS5aQvr4+Qgghjz32GMnNzSWtra2619NyTtd7jIkFps8ADgar1YqvfvWruPvuu3HdddcJrnD/9a9/4bvf/S4IIXjuuecEz+vq6sIzzzyDG2+80bD3orTeF77wBZx11lkAAIvFgttvvx0HDhzAli1bYrLeAw88gGuuuYb7e/HixQgEAjh48GBM1mP5+te/jh/84AdRr6F3PSNRWu9Xv/oVZs6ciWXLlgEAGIbBgw8+iAsuuCAm6z355JOCv1taWvDuu+8KflMj19u2bRtmzJgBt9sNAJg6dSrS0tLw/vvvG75eIBDAH/7wB3zpS19CWloaAOCcc85BWVkZHnnkEUM+j5b9+4EHHsANN9yAnJwcAMAdd9yBnTt34s0334zJev39/XjjjTdw3nnnxfzzORwO3HTTTZg0aRIAwOl04tZbb8VHH32EkydPxuTzPfXUU4IM9eLFi9HX14ejR4/GZD0guC3ddtttuPfeexUfZ+Saehjsevfccw+uvvpqTJw4EQBgt9vx5JNPYubMmTFZT3zc2bVrF06ePIlzzjknJutt27YNCxYsgMPhAACsWLECnZ2dWL9+veHrNTQ04Pnnn8ftt98Op9MJAPjyl7+Mnp6eiM+tZT0t53S9x5iYYFQk+fzzz5PJkycTAOTVV18lF1xwASkrKyP3338/aWtrIzfddBOZOnUqOeuss0hLSwshJHh1du6555L58+eTefPmkYsvvpgcO3aMe80VK1YQp9NJampqyKJFi8iPf/xj7j4tGUCWjo4OYrfbya9+9SvuthkzZpDm5mYyd+5cMn36dMnP9MEHHxiWAdSyHsuOHTsGnSXTut7AwAD50Y9+RMaNG0c6Oztjtt6rr75KVq5cSQ4fPmxIBlBpvVhkAJXWq6ioIH/84x+HbD0xv//978nKlStjtt6TTz5J8vPzuX3zf//7HwFAnn32WcPXa2hoIADIP/7xD8Hjly9fTqZMmWLI52GR279bWloIAPL8888Lbh83bhy54447DF+Pz5NPPqkpA2j08eu1115TfKyR63V1dZEvfelLZMmSJcTn88Vsvd/97nfke9/7nub3Ndg19WYAB7PewMAAcblc5M033xyS9aT4zne+Q773ve/FbL17772XTJw4kYsXHn/8cQKAfPLJJ4avt2HDBgKAfPzxx4Lbq6qqyMUXXxz1eizic3o0x5hYYFgG8PLLL8dvf/tbAMCBAwfw2muv4e2338aPfvQj3H333Xj00UexadMmdHV1cVfyH3/8McaMGYOPPvoIH3/8MWprawX9BO+88w7y8vLw/e9/H2vWrMFPfvKTqN6b2+3GmDFjsHHjRgDAnj17kJeXh4yMDFx99dXYtGkTDhw4MLgvQAG9661fvx4FBQWYN29eTNe77bbbkJ2djffeew9vv/02UlNTY7Jed3c37r77bjz88MNRvb7e9QDgb3/7GxYvXox58+bhhhtuwKFDh2KyXnd3N+rq6hAIBPDFL34R8+bNw4oVK/DCCy/E9PPxeeqppwaVmVBbb9WqVfjhD3+ICRMmYOzYsTj33HNx2WWX4YorrjB8vezsbKSkpERkho4fP47jx48b8nnUYHt18vLyBLfn5eVJ9vGY/XiihfXr12P69OkoKyuL6XoXX3wxcnJy0NjYiJdeeglWqzUm6504cQJ//etf8eMf/1jT4436jL/4xS+4frXbbrsNDQ0NMVnvwIED6OvrQ2trKy655BKuh0yut9robcbv9+PZZ5/FqlWrYrbefffdhwsvvBBlZWWorq7G1772Ndx+++2YO3eu4eux2z3/uOPz+dDQ0CB53BnsOV3vMSZWxKQEfOWVVwIARo8ejaysLOTl5SE5ORkWiwVz587F1q1bAQBXXXUV7rvvPsHz1qxZg97eXsPfk8fjQVtbGwDg2WefxdVXX82tabPZ8M9//tPwNVn0rNff348HH3wQjzzyCOx2e0zX+8Mf/oDm5mYsW7YM8+bNw6lTp2Ky3o9+9CN85StfQX5+flSvr3e9kpISTJ06FatXr8ZHH32E8vJyTJs2LeoGW6X12G3qnnvuwZ133olPPvkEDzzwAK677jr8+9//jsnn47N7926cPn0aK1asiGotLes9/vjj+NWvfoXNmzdjz5492Lp1K+bPnw+bzWb4egzD4Otf/zoef/xxHDt2jHv8oUOH4Pf7Dfk8avT09AAAVwpicTqd3H1GrqcXo9dramrCE088gd///vcxX+/ll19Gc3MzsrKysGjRoph9n1//+tfxi1/8AsnJyZoeb8Sao0ePxsKFC/H+++/j/fffR39/P2bPno2uri7D12ttbQUA/PCHP8RDDz2ETz75BLfeeiuWLVsmWSI1ept5++23UVZWhjFjxkjeb8R6P/zhD/H666/jwIEDOHDgAN555x1Mnz49Juvl5OTgqquuwkMPPcR9t7/61a/Q19cnedwZ7Dld7zEmZhiZTmTTq/y0fmlpKXniiSe4v++9916yePFiQgghTU1N5Jvf/CaZO3cuWbhwIZk1axYBQOrr6wXPj3YIhM+ECRPIlVdeSQghZOLEiaSrq4u77+yzzyajR4+W/TyDLQFrXY+QYBnhBz/4wZCtR0iwSbW4uJh85zvfMXy9LVu2kLlz53KNrUaUgPV+Pp/PR3Jzc8kPf/hDw9c7efIkAUCuvfZawXOuvvpqMmvWLMPXE3PXXXdF/bm0rBcIBEh6ejq5//77Bc9ZunQpeeCBBwxfj5Dg7/XrX/+azJ8/n8yfP5/ceeed5Bvf+AapqKgw5PVZ5PbvTZs2EQDko48+Ety+dOlScuGFFxq+Hh8tJWAj1/N6vWTZsmXkT3/605Csx9LZ2UmcTqfk4NJg13vllVfIFVdcoet9xeIztre3E4vFQv785z8bvt66desIAHLPPfcIbp8zZ45kO4jRn++KK66Q/FxGrdfY2EisVmtEK0hlZaVk64kRn6+np4fcfffdZM6cOWTBggXk/vvvJ1dccQVZunRp1OsRIn1O13uMiRXRXcKrIE7ri/8mhAAArr/+erS0tOCdd96B2+1GfX09ysvLufuNorOzE/v27cOqVauwfv16NDY24vzzz+fub2howP79+7Fp0ybZK4xo0bPe97//fdhsNjzwwAMxXW9gYIBrrAWCTarV1dXYvXu34eu99dZb6O3txdKlSwEAfX19AIBvfvObSE9PxxNPPIGqqipDP58Yq9WKsrKyqMrAautNmTIFTqcTRUVFgueVlpaqylxEsx7/87FlmA8//FD3OlrXKykpQVtbW0RpsLy8HC+88AJ++MMfGrre9OnTYbVaceedd+LOO+/kHrNq1Squ2X2wr69GRUUFAOD06dOC26UyrWY+nqgRCARwww03YNGiRbJyJUasRwiBz+cTVDRSU1NRWFgYccwxYr033ngD9fX1WLx4MYBwlv6qq66Cy+XC66+/Lmh3idVv6PF4kJ2dHXHcMWK94uJiAJA87ohLiEZ/vtbWVqxevRpPPPGE5P1GrHf48GH4/f6I405ZWRleeOEFwcCbUZ8vKSkJ999/v+C2xYsXY8qUKVF/Prlzup5jTEwxMppko2s+4gzevffey42Tp6SkkJ/+9Kfcffv27YuIzsvLy7nnszIU7OtqzQD+8pe/JG63m5w5c4bcfvvt3Hg2S0dHB0lKSiLf+ta3JD/PYDKAWtf75S9/SVauXMllyjZt2kQ2bdoUk/XGjx8f8byxY8eSm2++OSbr8RlsBlDLet/4xjcinhdthlPLeosXLyY33HCD4DE33nijamNwtOuxvPnmm4rSHUas5/f7idPpJA8++KDgMeeddx6ZO3eu4esRQsj27dtJc3Mzd38gECAVFRXkmWeeMeT1WZT276lTpwoa3Nvb24nNZouQ2DD6eKKWATRyva985Svkrrvu4v5+9913yaFDhwxf7/Dhw+T8888X3Obz+Yjb7Y7ILMfi+Kz2OKPWFB93+vr6iM1mi8hyGrVeeXl5xDlwyZIl5PLLL4/Jeix//OMfyXXXXSd7vxHrHT9+XHZI4pprronJ51u/fr1ApqW7u5ukpKREZOmMOqdrPcbEkrgGgDNnziRLly4lXq+XEELIz3/+84gfZ+bMmeQ3v/kN8Xq9ghKQVh3Axx57jHg8HvLqq68Sn89HJk2aJDl5tnLlSlJQUCDQ4BlsAKh1vccee4yMHz+erFu3jmzcuJFs3LiR3HvvvZKlbyPWYxhGoN30zDPPEIvFErGhG7Uen8EEgFrXKysrI6+88gp331/+8hfidDrJ7t27Y7LeW2+9RdLS0khdXR0hhJD6+nqSnp5O/v73v8dkPZYrr7yS/O1vf9O1RjTr3XLLLaSmpoabxtu8eTOx2+3kt7/9bUzWu+222wT79u9+9zsye/Zs2YlRva/PorR/v/jiiyQvL480NjYSQgj52c9+FqHRFYvjiVIAaOR63/ve98iiRYu4483GjRvJl7/8ZcF+adR6hw8fJi6Xi2zevJm77f777yfJycnkwIEDMfl8fJQeZ+SaDoeDbNy4kfv7nnvuIZmZmZzOm9Hr/elPfyLl5eWcluKmTZuI3W4na9asicl6LDNnziTvv/++5H1GrnfWWWeRhQsXckHZq6++SgCQl19+OSbrnX/++dw5NxAIkG9/+9sRwbSR53Qtx5hYY1gA+NZbb3EyMIsWLSLNzc0CGZdnn32WPPTQQ6S0tJSkpaWRlStXkp07d5L58+eTmpoactFFF5Hvfve7BACZNWsWJ275/PPPk9GjR5NZs2aRRx99lBw5coQsWrSIOJ1OUlpaSm655RZCCCFf/epXSWlpKXE6nWTRokVk4cKFZPLkyWTVqlVk165dpK2tjcycOZNkZmaS22+/XfDen3jiCVJVVcWtvXfvXrJo0SLu88yaNStiQ1BD63q1tbXEYrEQABH/6QkA9Xy+Rx55hMyZM4fMnz+fzJkzh8ydO1dWzNOI9djA6I477uD6PCdPnqxLukTPevfffz9ZsmQJWbx4MZkzZw5ZtGgRWbt2bUw/3zPPPEOmTp1K5s2bR2bNmkX++te/xnS91tZWkpmZGbV0j571du7cSe666y7u802aNIk89NBDJBAIxGS9n/70p2TMmDFkxowZZP78+eTWW2+VFWON5vW17t+PPfYYmTp1KpkzZw4577zzBBJVRq/HHtdqamq4Yyj/dY1cb+fOnZLHG/6FmZHr9fb2kgceeIBMnz6dLFiwgMycOZMsW7ZMIOcRq+PzypUrBY/jS2wYveYjjzxC5s+fTxYvXkxmzpxJzjvvPIG4fiw+40MPPUQmTZpE5s+fT+bOnSvIHsVivT179pDy8nLJfd/o9ZqamsjNN99Mamtrydy5c0ltba3AwMDo9R588EFSWVlJ5syZQ+bNm0e+973vCTKCsTinKx1jhgKGEIMb7igUCoVCoVAopmZYO4FQKBQKhUKhUCKhASCFQqFQKBTKCIMGgBQKhUKhUCgjDBoAUigUCoVCoYwwaABIoVAoFAqFMsKgASCFQqFQKBTKCIMGgBQKhUKhUCgjDBoAUigUCoVCoYwwaABIoVAoFAqFMsKgASCFQqFQKBTKCIMGgBQKhUKhUCgjDBoAUigUCoVCoYww/h9S+0mvlsI0cwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1.70000000e+01 9.92839828e-04 9.95925958e-04 ... 9.96709160e-04\n",
      "  9.98573501e-04 9.99700084e-04]\n",
      " [5.00000000e+00 8.52878488e-04 3.94813672e-04 ... 6.48286451e-04\n",
      "  7.85162903e-04 7.51572683e-04]\n",
      " [1.70000000e+01 8.22843957e-04 3.27331789e-04 ... 6.52008215e-04\n",
      "  7.17786771e-04 7.02978848e-04]\n",
      " ...\n",
      " [1.70000000e+01 9.41781159e-04 4.43039706e-04 ... 9.11515817e-04\n",
      "  9.51379248e-04 9.97891532e-04]\n",
      " [1.70000000e+01 9.37782654e-04 3.92888028e-04 ... 7.43037558e-04\n",
      "  6.39933561e-04 7.49222784e-04]\n",
      " [1.70000000e+01 9.41781159e-04 4.43039706e-04 ... 9.11515817e-04\n",
      "  9.38393925e-04 9.97891532e-04]]\n"
     ]
    }
   ],
   "source": [
    "from pymoo.visualization.pcp import PCP\n",
    "X = res.X\n",
    "F = res.F\n",
    "G = res.G\n",
    "Z_res = [[d['x01']] for d in X]\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "labels = list(res.opt[0].X.keys())\n",
    "labels_x = ['matID', 'A1', 'A2', 'A3', 'A4', 'A5', 'A6', 'A7', 'A8', 'A9', 'A10', 'A11', 'A12', 'A13', 'A14', 'A15', 'A16', 'A17', 'A18', 'A19', 'A20']\n",
    "bounds = np.array([problem.vars[name].bounds for name in labels]).T\n",
    "\n",
    "\n",
    "X = np.array([[sol.X[name] for name in labels] for sol in res.opt])\n",
    "\n",
    "plot1 = PCP(labels=labels_x, bounds=bounds)\n",
    "plot1.set_axis_style(color=\"grey\", alpha=1)\n",
    "plot1.add(X)\n",
    "\n",
    "plot1.show()\n",
    "plt.savefig('./figures_Advanced/PCP.png',bbox_inches='tight', dpi = 200)\n",
    "\n",
    "\n",
    "# Maybe the solution is limited by the limits in areas. Example, you want to minimize the compliance but\n",
    "# you have a maximum area, so you can't reduce the compliance further\n",
    "\n",
    "upper_bounds = bounds[1, 1:]*0.999\n",
    "lower_bounds = bounds[0, 1:]*1.001\n",
    "\n",
    "\n",
    "\n",
    "# Check if each row of X is within the limits\n",
    "is_within_limits = np.logical_and(np.all(X[:,1:] >= lower_bounds, axis=1), np.all(X[:,1:] <= upper_bounds, axis=1))\n",
    "\n",
    "# Print the results\n",
    "if np.all(is_within_limits):\n",
    "    print(\"Solution not limited by the areas\")\n",
    "else:\n",
    "    print(\"Solution limited by the areas\")\n",
    "\n",
    "\n",
    "\n",
    "    \n",
    "\n",
    "names = []\n",
    "types = []\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "legend_dict = {}\n",
    "material_name_dict = {}  # Dictionary to map material types to material names\n",
    "\n",
    "for xData in Z_res:\n",
    "    matname = dataIdentifier['name'][int(xData[0])]\n",
    "    mattype = dataIdentifier['className'][int(xData[0])]\n",
    "    names.append(matname)\n",
    "    types.append(mattype)\n",
    "    material_name_dict[mattype] = matname  # Populate the material name dictionary\n",
    "\n",
    "unique_labels = list(set(types))\n",
    "\n",
    "# Define specific colors for each material type\n",
    "mat_colors = {\n",
    "    'Steel': 'slategrey',\n",
    "    'Aluminium Alloys': 'violet',\n",
    "    'Plastics': 'lawngreen',\n",
    "    'Titanium Alloys': 'indigo',\n",
    "    'Copper Alloys': 'chocolate',\n",
    "    'Composites': 'gold',\n",
    "    # Add more material types and corresponding colors as needed\n",
    "}\n",
    "\n",
    "for i, mattype in enumerate(types):\n",
    "    if mattype not in mat_colors:\n",
    "        mat_colors[mattype] = plt.cm.get_cmap('jet')(i / len(set(types)))\n",
    "\n",
    "# add scatter plot for each unique label\n",
    "for i, (x, y) in enumerate(F):\n",
    "    material = names[i]\n",
    "    mattype = types[i]\n",
    "    color = mat_colors[mattype]\n",
    "    label = material_name_dict[mattype]  # Use material name as the label\n",
    "    ax.scatter(x, y, color=color, label=label)\n",
    "    if mattype not in legend_dict:\n",
    "        legend_dict[mattype] = ax.scatter(x, y, color=color, label=label)\n",
    "\n",
    "# set legend colors and remove duplicates\n",
    "handles, labels = [], []\n",
    "for label in legend_dict:\n",
    "    handles.append(legend_dict[label])\n",
    "    labels.append(material_name_dict[label])  # Use material name as the label\n",
    "    legend_dict[label].set_color(mat_colors[label])\n",
    "\n",
    "ax.legend(handles, labels, loc=\"upper right\")\n",
    "\n",
    "# show plot\n",
    "plt.title(\"Objective Space\")\n",
    "entry_order = ['cost', 'mass', 'co2', 'water', 'energy', 'compliance']\n",
    "enabled_entries = [entry for entry in entry_order if objectives[entry]['isOn']]\n",
    "ax.set_xlabel(enabled_entries[0])\n",
    "ax.set_ylabel(enabled_entries[1])\n",
    "plt.savefig('./figures_Advanced/3Dcompliance_mass.png', bbox_inches='tight', dpi=200)\n",
    "plt.show()\n",
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18e911a8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}