full_validation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f2d21901",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b21935ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "442e1ad8",
   "metadata": {},
   "source": [
    "## Step 1 prepare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ddc1e544",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, Y_train = datasets.make_circles(n_samples=500, noise=0.09, factor=0.4)\n",
    "X_test, Y_test = datasets.make_circles(n_samples=200, noise=0.09, factor=0.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f26e6993",
   "metadata": {},
   "source": [
    "### - 1.1 Plot origin data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1d1ec9a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Data:\n",
      "[[-1.0479456  -0.15193589]\n",
      " [ 0.00202277 -0.4745155 ]\n",
      " [-0.66518526 -0.88125556]\n",
      " [-0.15540387  0.83000145]\n",
      " [ 0.34690634 -0.14012244]\n",
      " [ 0.03964596 -0.38300768]\n",
      " [-0.13846332 -0.28026514]\n",
      " [-0.02008824  0.42452154]\n",
      " [-0.44235503 -0.8037406 ]\n",
      " [-0.14298356  0.49525987]]\n",
      "\n",
      "Training Label:\n",
      "[0 1 0 0 1 1 1 1 0 1]\n"
     ]
    }
   ],
   "source": [
    "print('Training Data:')\n",
    "print(X_train[:10])\n",
    "print('\\nTraining Label:')\n",
    "print(Y_train[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9d51433f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_train[:, 0], X_train[:, 1], c=Y_train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "880cb2a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total datas: 500\n",
      "labels: [0, 1]\n",
      " - label 0 datas: 250\n",
      " - label 1 datas: 250\n"
     ]
    }
   ],
   "source": [
    "print(f'Total datas: {len(X_train)}')\n",
    "print(f'labels: {list(set(Y_train))}')\n",
    "print(f' - label 0 datas: {len(list(filter(lambda x: x==0, Y_train)))}')\n",
    "print(f' - label 1 datas: {len(list(filter(lambda x: x==1, Y_train)))}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de312c1d",
   "metadata": {},
   "source": [
    "### - 1.2 Add new dimention datas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "68d72dbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solved Training Data:\n",
      "[[-1.0479456  -0.15193589  1.05890249]\n",
      " [ 0.00202277 -0.4745155   0.47451981]\n",
      " [-0.66518526 -0.88125556  1.10412082]\n",
      " [-0.15540387  0.83000145  0.84442452]\n",
      " [ 0.34690634 -0.14012244  0.37413675]\n",
      " [ 0.03964596 -0.38300768  0.38505413]\n",
      " [-0.13846332 -0.28026514  0.31260301]\n",
      " [-0.02008824  0.42452154  0.42499656]\n",
      " [-0.44235503 -0.8037406   0.91742952]\n",
      " [-0.14298356  0.49525987  0.51548679]]\n"
     ]
    }
   ],
   "source": [
    "Z_train = (X_train[:, 0] ** 2 + X_train[:, 1] ** 2) ** 0.5\n",
    "temp = np.zeros((X_train.shape[0], len(X_train[0]) + 1))\n",
    "temp[:, :-1] = X_train\n",
    "temp[:, -1] = Z_train\n",
    "X_train2 = temp\n",
    "\n",
    "Z_test = (X_test[:, 0] ** 2 + X_test[:, 1] ** 2) ** 0.5\n",
    "temp = np.zeros((X_test.shape[0], len(X_test[0]) + 1))\n",
    "temp[:, :-1] = X_test\n",
    "temp[:, -1] = Z_test\n",
    "X_test2 = temp\n",
    "\n",
    "print('Solved Training Data:')\n",
    "print(X_train2[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d5b6251",
   "metadata": {},
   "source": [
    "### - 1.3 plot in 3D coordinate system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f225e43e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot3D(X, Y):\n",
    "    fig = plt.figure(figsize=(10, 10))\n",
    "    ax = fig.add_subplot(111, projection='3d')\n",
    "    ax.scatter(\n",
    "        X[:, 0], X[:, 1], X[:, 2], \n",
    "        zdir='z', s=30, c=Y, depthshade=True\n",
    "    )\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6c9ce8cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot3D(X_train2, Y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a988d261",
   "metadata": {},
   "source": [
    "### - 1.4 load iris data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "18386b66",
   "metadata": {},
   "outputs": [],
   "source": [
    "X, Y = datasets.load_iris(return_X_y=True)\n",
    "\n",
    "X_train_0 = X[0:30]\n",
    "X_train_1 = X[50:80]\n",
    "X_train_iris = np.vstack((X_train_0, X_train_1))\n",
    "\n",
    "Y_train_0 = Y[0:30]\n",
    "Y_train_1 = Y[50:80]\n",
    "Y_train_iris = np.vstack((Y_train_0, Y_train_1)).flatten()\n",
    "\n",
    "X, Y = datasets.load_iris(return_X_y=True)\n",
    "\n",
    "X_test_0 = X[30:50]\n",
    "X_test_1 = X[80:100]\n",
    "X_test_iris = np.vstack((X_test_0, X_test_1))\n",
    "\n",
    "Y_test_0 = Y[30:50]\n",
    "Y_test_1 = Y[80:100]\n",
    "Y_test_iris = np.vstack((Y_test_0, Y_test_1)).flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "56cdecef",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_iris = (X_train_iris - X_train_iris.min(axis=0)) / (X_train_iris.max(axis=0) - X_train_iris.min(axis=0))\n",
    "X_test_iris = (X_test_iris - X_test_iris.min(axis=0)) / (X_test_iris.max(axis=0) - X_test_iris.min(axis=0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fc32cf7",
   "metadata": {},
   "source": [
    "## Step 2 Initialize Quantum Circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2b1fe9c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import qiskit\n",
    "from qiskit import QuantumCircuit\n",
    "from qiskit import Aer, execute\n",
    "\n",
    "qasm_backend = Aer.get_backend('qasm_simulator')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e338495f",
   "metadata": {},
   "outputs": [],
   "source": [
    "params = [\n",
    "    [[-1.18991246e-01, -8.69694713e-01,  1.43722811e-03],\n",
    "      [ 3.47641545e+00, -4.73632073e-02,  1.97135609e+00],\n",
    "      [ 1.95775707e+00, -1.12139160e-02, -6.21796144e-03]],\n",
    "\n",
    "     [[ 2.02460380e-02, -2.25797547e+00,  5.14234265e-03],\n",
    "      [-1.71552299e-02,  2.46283604e-03, -1.03805722e-02],\n",
    "      [-2.37244982e-03, -3.35799404e-03,  6.10191152e-03]]\n",
    "]\n",
    "\n",
    "params_iris = [\n",
    "    [[-3.42142600e-02, -5.45047534e-03,  8.11905347e-01],\n",
    "     [-1.52484152e+00,  1.49884676e+00, -1.25408626e-02],\n",
    "     [-1.89515860e-03,  1.35760410e-02,  8.22999582e-03],\n",
    "     [ 1.39102114e+00,  4.19729865e-01,  1.60000380e-04]],\n",
    "\n",
    "    [[ 7.88431068e-01, -8.86177264e-01,  1.33830291e-02],\n",
    "     [-3.71228143e-03, -1.12994101e-02, -1.27897783e-02],\n",
    "     [ 9.45954683e-03, -3.34659883e-03,  1.17217829e-02],\n",
    "     [ 1.98256181e-02, -1.07358054e-02,  7.53621360e-03]]\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc600d32",
   "metadata": {},
   "source": [
    "### - 2.1 create quantum circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c449a4e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def createInputCircuit(data):\n",
    "    qubits_num = len(data)\n",
    "    qcircuit = QuantumCircuit(qubits_num, qubits_num)\n",
    "    qubits = qcircuit.qubits\n",
    "\n",
    "    for i, d in enumerate(data):\n",
    "        qcircuit.rx(d * np.pi, qubits[i])\n",
    "        \n",
    "    return qcircuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d92c3a39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 203.885x367.889 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test 1: create input circuit\n",
    "\n",
    "test1_circuit = createInputCircuit(X_train2[0])\n",
    "test1_circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e58a3278",
   "metadata": {},
   "outputs": [],
   "source": [
    "def createModelCircuit(params):\n",
    "    qubits_num = len(params[0])\n",
    "    qcircuit = QuantumCircuit(qubits_num, qubits_num)\n",
    "    qubits = qcircuit.qubits\n",
    "\n",
    "    for i in range(qubits_num):\n",
    "        qcircuit.u3(*params[0][i], qubits[i])\n",
    "\n",
    "    for i in range(qubits_num - 1):\n",
    "        qcircuit.cz(qubits[i], qubits[i + 1])\n",
    "    qcircuit.cz(qubits[0], qubits[qubits_num - 1])\n",
    "\n",
    "    for i in range(qubits_num):\n",
    "        qcircuit.u3(*params[1][i], qubits[i])\n",
    "        \n",
    "    return qcircuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "26bbace8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 872.774x367.889 with 1 Axes>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test 2: create model circuit\n",
    "\n",
    "test2_circuit = createModelCircuit(params)\n",
    "test2_circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "abd6125f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def createCircuit(params, data):\n",
    "    input_circuit = createInputCircuit(data)\n",
    "    model_circuit = createModelCircuit(params)\n",
    "    full_circuit = input_circuit.compose(model_circuit)\n",
    "    \n",
    "    return full_circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2067c49f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 956.385x367.889 with 1 Axes>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test 3-1: create full quantum circuit - circle\n",
    "\n",
    "test3_circuit = createCircuit(params, X_train2[0])\n",
    "test3_circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "63090819",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1207.22x451.5 with 1 Axes>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test 3-2: create full quantum circuit - iris\n",
    "\n",
    "test3_circuit = createCircuit(params_iris, X_train_iris[1])\n",
    "test3_circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0dd182cd",
   "metadata": {},
   "source": [
    "### - 2.2 evaluate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c4c2d66e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(model, data):\n",
    "    qubits_num = len(data)\n",
    "    input_circuit = createInputCircuit(data)\n",
    "    qcircuit = input_circuit.compose(model)\n",
    "    \n",
    "    # the measurement\n",
    "    qcircuit.measure(list(range(qubits_num)), list(range(qubits_num)))\n",
    "\n",
    "    # job execution\n",
    "    shots = 1000\n",
    "    job_sim = execute(qcircuit, qasm_backend, shots=shots)\n",
    "    result_sim = job_sim.result()\n",
    "    counts = result_sim.get_counts(qcircuit)\n",
    "\n",
    "    p1 = 0\n",
    "    for i in range(2 ** (qubits_num - 1)):\n",
    "        comb = str(bin(i + 2 ** (qubits_num - 1))[2:])\n",
    "        p1 += counts.get(comb, 0)\n",
    "        \n",
    "    p1 /= shots\n",
    "    \n",
    "    if p1 > 0.5:\n",
    "        return 1\n",
    "    else:\n",
    "        return 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3411e210",
   "metadata": {},
   "outputs": [],
   "source": [
    "def accuracy(model, datas, labels):\n",
    "    predictions = [ predict(model, data) for data in datas ]\n",
    "    \n",
    "    acc = 0\n",
    "    for i, p in enumerate(predictions):\n",
    "        if p == labels[i]:\n",
    "            acc += 1\n",
    "    \n",
    "    return acc / len(predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "14da4ec5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate(model, X_test, Y_test):\n",
    "    acc = accuracy(model, X_test, Y_test)\n",
    "\n",
    "    print(\"FINAL ACCURACY: {:0.2f}%\".format(acc * 100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a2a47a1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FINAL ACCURACY: 98.33%\n",
      "FINAL ACCURACY: 100.00%\n"
     ]
    }
   ],
   "source": [
    "# Test 4: evaluate noiseless model\n",
    "\n",
    "test4_circuit = createModelCircuit(params_iris)\n",
    "\n",
    "evaluate(test4_circuit, X_train_iris, Y_train_iris)\n",
    "evaluate(test4_circuit, X_test_iris, Y_test_iris)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cb94ce7",
   "metadata": {},
   "source": [
    "## Step 3 Create Noisy Circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fa58a3e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.providers.aer.noise import NoiseModel\n",
    "from qiskit.providers.aer.utils import insert_noise\n",
    "from qiskit.providers.aer.noise import pauli_error, depolarizing_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8ab6d8f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def createNoiseModel(p, errorType):\n",
    "    # QuantumError objects\n",
    "    if errorType == 'bit_flip':\n",
    "        error = pauli_error([('X', p), ('I', 1 - p)])\n",
    "    elif errorType == 'phase_flip':\n",
    "        error = pauli_error([('Z', p), ('I', 1 - p)])\n",
    "    elif errorType == 'depolarizing':\n",
    "        error = depolarizing_error(p, num_qubits=1)\n",
    "        \n",
    "    ## two-qubits quantumError objects \n",
    "    if errorType == 'depolarizing':\n",
    "        error_2qubits = depolarizing_error(p, num_qubits=2)\n",
    "    else:\n",
    "        error_2qubits = error.tensor(error)\n",
    "        \n",
    "    # Add errors to noise model\n",
    "    noise_model = NoiseModel()\n",
    "    \n",
    "    noise_model.add_all_qubit_quantum_error(error, ['u3'])\n",
    "    noise_model.add_all_qubit_quantum_error(error_2qubits, ['cz'])\n",
    "    \n",
    "    return noise_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4d56c42d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def createNoisyModelCircuit(params, p, errorType):\n",
    "    noise_model = createNoiseModel(p, errorType)\n",
    "    model_circuit = createModelCircuit(params)\n",
    "    \n",
    "    return insert_noise(model_circuit, noise_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c22efea4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABroAAAJxCAYAAAAdC2LsAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAADGg0lEQVR4nOzdd3yN5//H8ffJ3iqCELH3rk1R1BYtWn66jNLSb5W2iqLVoWh9O3XZ2ira+tao2rNFqa2xYwQJQYjsfc7vj1TqyI4kJyd5PR+PPCr3dd33/bnuU7f7XJ/7ui6DyWQyCQAAAAAAAAAAALAyNpYOAAAAAAAAAAAAAMgNEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAAAAAAAAAACAVSLRBQAAAAAAAAAAAKtEogsAAAAAAAAAAABWiUQXAAAAAAAAAAAArBKJLgAAAAAAAAAAAFglEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAAAAAAAAAACAVSLRBQAAAAAAAAAAAKtEogsAAAAAAAAAAABWiUQXAAAAAAAAAAAArBKJLgAAAAAAAAAAAFglEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAAAAAAAAAACAVSLRBQAAAAAAAAAAAKtEogsAAAAAAAAAAABWiUQXAAAAAAAAAAAArBKJLgAAAAAAAAAAAFglEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAAAAAAAAAACAVSLRBQAAAAAAAAAAAKtEogsAAAAAAAAAAABWiUQXAAAAAAAAAAAArBKJLgAAAAAAAAAAAFglEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAAAAAAAAAACAVbKzdADIGyaTSUpMtnQYKCrsbWUwGAr8tCaTZEws8NMCec7GXrLAXyFkE/caFHfcowAAAIo3vhOhuOM7UdFDoquoSExW0uTllo4CRYTdtP6SQ8HfHoyJ0vZZBX5aIM91HC3ZOlg6CmSEew2KO+5RAAAAxRvfiVDc8Z2o6GHqQgAAAAAAAAAAAFglEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAAAAAAAAAACAVSLRBQAAAAAAAAAAAKtEogsAAAAAAAAAAABWiUQXipTvj/0uh4+e0vfHfk+3PDD8hhw+ekrD1s8u4MgAAAAAAAAAAEBeI9EFAAAAAAAAAAAAq0SiCwAAAAAAAAAAAFaJRBcAAAAAAAAAAACsEokuAAAAAAAAAAAAWCUSXQAAAAAAAAAAALBKxSLRFRoaqvHjx6t69epycnKSr6+vxowZo+joaA0bNkwGg0FffvmlpcMEAKv2/aZ31GWcQSG3Ai0dSr7pMs6gmT8OsXQYAAAAAAAAAP5hZ+kA8tuRI0fUo0cPhYSEyNXVVXXr1tWVK1c0a9YsnTt3Trdu3ZIkNW7c2LKBokAZ7vrzy5sXau35QwqPj5W7g5Mer9lSMx5+Sg62Rf6vh1WLjovQyp2fa/fxlQoODZDRmKyyJSurVR0/PdHhdZV0K2PpENN1NviI/jy+Sl2bDZG3Z2VLh4Ni4lq4tDtAOnpJioqX7GyksiWkNtWlJpUlB253ZoxGo1bu+lxr985RSFigHnAtrfaNBmhwt/fk7OBq6fAAAAByxGSSLtxIeR48dVWKTUh5/qvsJbWtKdUtL9kUi9egAWQX34kAWJsi3bUVGhqq3r17KyQkRGPHjtXbb78td3d3SdLMmTM1YcIE2dnZyWAwqGHDhhaOFnnByc5BkhSTmJBueXRivCTJ+Z96kvTig131wcNPydXBSaExEXpyzSx9sHeVpjz0RP4HjFwJunFGE+d107XbF9W2fj91bz5Mdrb2Onlpr1bs+kwbDyzS1Od+U52KLS0dahrnrhzR4s3vqlG1DiS6kO+SkqWf90n7zptvTzZKl26m/Px6WBrUVqpdzjIxFkbfrHlVq3bN0kP1++qJh8fq0rWTWrVrls4FH9aHL2yRDT1BAADASkTFSYt2Sueum2+PS0xJep26KpV2l4Y/nPIiFABIfCcCYH2KdKJr9OjRCgoK0qhRo/TRRx+ZlY0fP15Lly7V0aNHVaVKFXl4eFgoSuSlKiVKS5JO3QpOt/zUzZTtlf+pJ0l1vSqk/tkkycZg0NnbIfkXJO5LXEKM3lrUW6ERwZo6dI1a1umVWtar1Qvq3fo/mjC3s6YselRzx/oX2pFdQH4zGqVvd0nHgjKvF5Mgzd2e0rlR16dgYivMAkOOa/XuL9S2fj+9PfiX1O3enlX01erR2nH0R3V68CkLRggAAJA9MfHSl1ukkPDM692IlGZtlsZ0lcrQNQIUe3wnAmCNimz6/eTJk/rpp5/k5eWlGTNmpFunadOmkqRGjRqZbb9w4YIeffRRubu7q2TJkho0aJBu3ryZ7zHj/j1Ytop83Uvp51N7dCUqzKwsITlJ3xzeJIMM8qve1Kxs5l+/quTnQ+Xz9Uj9feOiRjfpUZBhIwc27FugoBtn1K/tK2ZJrjtq+TbTcz2m63bUdS3f8d/U7Rv3f6su4ww6em5Hmn3GftNBz0yvbLbtwOlNev+H/9OzM6qq10Rn9XnrAU2Y21VHz/2e4f6h4Vc0bcmT6julpPwmueiNed0UdONMar3vN72jj34eKkl6fXZHdRlnMFvzKbM1rp6ZXlljv+lgtu3OvofPbtPoL1rLb5KLnny/gn7c/qEkKTImTB//PEz93ykjv0kuenOhn0LDr6R3WbOUmJSgn7bP1IhPGstvkosee6uE/vN5M63anXZ9w8SkeC1YP0lPvl9BPd9w1IhPGumvk+vS1Pv1z681YW5XDZzqox5vOOj/3iunD5Y+k27777T1ROAevfbNw+o9yVX93i6lj5cPV2x8lFndmT8OUZdxBkXHhuvzX15U/3fKqOdEJ4358iGdvPRXmmObTCat+fMb/eezpvKb5KLek930+uyOOnJ2e66uVWGx41TWSa47jCbpu11SdHz+xmQNth9ZJpPJpH7tXjHb3rPl83Kyd9GWQz9YJjAAAIAc+uVA1kmuO6LjU0Z+mUz5GxOAwo/vRACsUZFNdC1btkxGo1FPP/203Nzc0q3j7OwsyTzRFRkZqY4dOyooKEjLli3T3LlztXPnTvn5+cloNBZI7Mg9OxtbfdH5OYXHx6jpdxM08fdlmn90q6btWaEW30/SH0EnNb7lo6rlWd5sv/EtH1XYmEU6OvS/er5RZ3m7PWCZBiBLf/j/T5LUs9ULGdbp2myI7GzttdP/lwzrZGXTgW8VGXNLXZoO0kt9vtDj7V7V5esnNX7uI/I/vzNN/biEaI39pr1sDbZ6rvt0PdZmlP4+t0NTvn1MycZkSVLb+v3Uq2VK3E92mqQJAxdrwsDF8ms1ItdxnrtyWFMX91ejah00wu9j+XjV0IJ1b2jFzs81fu4jiowN07Nd35Ffq5Haf3qDZv44KMfnSExK0MT53TR/3QSVdC+rwV3f09Du01TTp6l2+69IU3/mT4N17MJO9X/4dQ3uNlW3o2/one/6pElgLf/9I5Vw9VKftqP1ct+v1L7RAO0+tlJjvmqjiOi0Lxecu3JEby7yU60KzTWi9ydqWrOrNuxboNlrXks37jfmd1NoeJCe7jJFT3acqMBrx/Tmgl6KiYs0q/fhsmf15apRKu9VXcN7zdSgru8qOi5cE+Z10Z/Hf83x9SoMjEZp55ms690tPintFIfF0enL+2VjsFGtii3MtjvYO6lq+cY6c3m/hSIDAADIvvBY6fDFnO1z9bZ09lq+hAPAivCdCIA1KrJTF27btk2S1LFjxwzrBAWlvOp+d6Jr7ty5Cg4O1h9//KGKFStKkipUqKA2bdro119/VZ8+ffIvaOSJntUe1O9PvqOP9q/RD8f/0M24KLnaO6pxmcpa0nq0+tduleG+dUr5qGHpihq67htt/r83CzBqZFdgyDG5OLrLx6t6hnWcHFzkW7q2LoT4KzY+Ss6O6Se7M/Nq/3lpFlj1az1Swz+qp2XbZ6hB1XZmZeHRoer/8Dj9X8fxqdtKuJXWvLXjdShgi5rX6qaq5RuqTqXWWvvXXDWt2UWNqnXIcVz3uhDir89H7Uldj6x7i2F6ZnolzV7zqh5rM0ov9ZllVv+XnZ/q8vXT8i1TK9vnWLHzMx09t0MDO03UsB7TzcrSewGghKuXpg5dI4PBIElqXL2jRs1qobV752hYz39H2M4d65/mGreu+6gmzO2s9fsWmF3LlLb+bdZWv9YjFBMXoY37F2lk70/SfM41fJpodL+vU3+vWLau3v9hgLYdXiq/1inJxV3+K7X18BK98vgc9boredqv7Ri9/GUrfbN6jFrX7Z3aFmtx8qoUFp3z/XafkTrUlqysuXnqZsQVebh6ycHOMU2ZVwkfnbj4pxKTEmR/11qPAAAAhc3esymj9nNqV4BUwzvv4wFgPfhOBKAgmUwmxcTESJJcXFxy3QdXZBNdFy+mvLpUqVKldMuTkpK0e/duSeaJrt9++01t27ZNTXJJUuvWrVW1alWtWbMmV4muZs2aKSQkf9d8cra114kB07OuWEw0K1dNPz76Sq72TTQmKyDsat4GZGVq1qih2OTEAj+vg52z5o4KyLROTFyEPN2z/ubl4pQyuXxMfGSuEl13J2Bi46OUmBQvGxtb1a7YUicv7U1T38Zgo75tR5tta1y9kyQpODRAzWt1y3EM2VGnYuvUxI8k2ds5qJZvC+058av63BNP/Srt9MvOTxUcGpCjRNe2w0vk7lxSz3aekqYsvQVo+7YdY/aPUi3f5nJ2dFNwqPlne+caG41GxcZHKsmYqGrlG8nVqYROpTPF4L1tlVKu8b5T6xQSFqgq3vXNyvq1e9Xs9wfv+jzu2HroB7k4uqtN/T4Kjw41q9+6Tm99v/kdBYcGqELpmmniyUyNmjWUkBSbo33yUu1Oo1W/2/isK94jNEqqUq2WkhJykSWzIpnda+ITYmSfzhe6lP2cUuokxvClDlbN0vcoAED+a/3sPPnUz/mU/LsOXdBbT7bLuiIAq8Z3IhR3fCcqPIxGo65eTemLb9y4sQ4fPpyr4xTZRFd0dEonXWxs+v/D/vTTTwoNDZW7u7uqVKmSuv3EiRPq379/mvr16tXTiRMnchVLSEiIgoODc7VvdrnYp/8PEDIXHh+j1QH79Wj1Zirh6CL/0MuasWeVulRuaOnQLOrK1auKSSz4xXqc7F2yrOPi5KHo+Igs68XERcjGYKMSrl65iuVK6Dkt2jBZB85sVFTsbbOy9N4sKOVRXg72TmbbPFxKSZIi05mGL6+UK1U1zTY355KSUhaKvZu7S8r2iJicxRMcGqBq5RunaV+GMXmmjcnDpVSa8x4+u00/bH5Ppy79pYSkOLOyqFjzNfak9Nt65xqnN9XhvfU9XP+pe1ccl66fVEx8pAa8Wzaj5igs8lqOE11Xr1xRXGJMjvbJS5Xik3K97/WbYYqNuJGH0RQ+md1rHB1cFBt1Pd2yO/+fOmbjXgUUZpa+RwEA8l9ici53tLHP9/4LAJbHdyIUd3wnKpyuXcv9HMpFNtHl7e2tsLAwHTp0SK1btzYru3r1qsaNGydJatiwoVmndVhYmB544IE0x/P09NTp06dzHUt+c7a1z/dzFEUGSUtP7NK4HT8oITlJZVw81KdGC01p87ilQ7Oo8uXKWWxEV1Yqe9eX//k/FBx6NsPpC+MSYnT5ximVKVlJdv/83chs2Guy0TwpEBsfpde+aa+4hGj1a/eKqng3kLOju2wMNlq2fYaOnN2W5hg2NrYZHt+k7M0ZYlD2Y0w9ryHj89pmEJMpn1eYzuha3H3e05f36415XeVTqrqG9fxA3p5V5GjvLIMMmrZkoIymtFMiZtZWpXONs9N+k0x6wLW0Jj61NMMjV75npFh2lCtf3qJvBjna5n5NSa8H3GR0L9pv5mV2rynlUV6Xrp1QQlJ8mqk6QsODVcLVizcXYfUsfY8CAOQ/G2PuXlw0JkTJx8cnj6MBUNjwnQjFHd+JCo+7R3SVLZvxi+hZKbKJrs6dO+vkyZP68MMP1aVLF9WsmfI2/v79+/Xss88qNDRliqrGjRvneywHDhzI93OYEpKUNHl5vp+nqPFwdNGGAZMtHUahcyYgQAaHgr89JCdI22dlXqd9gyfkf/4Prd83X8N7fpBunc0Hv1dScqIeafJM6jZ3F09JUkTMrTT1Q25dSE2ISdLhgK26GXFFYwcsVPfmQ83qLtp4f2u3ZZZwuxNjZMwteXtWTt2ekBinWxFXVb5UxuuS5Scfr5q6fP1Uug+5ubXt8FIZjcmaNny9yt018iw2ITrd0Vz5xcerhvbdOKM6lVrlaorLjAScCZCtBZ/7r4VLM37L+X61y0mXLp7P+4AKmczuNbV8m+vgmU06fWmf2Vp8CYlxOn/liBpUbV9AUQL5x9L3KABA/jsYKC3enfP9Hn+kthaNDcrzeAAULnwnQnHHd6LCIzo6Wm5uKX1yu3btyvVx0i6uUkSMHz9epUqV0uXLl1WvXj01aNBANWrUUIsWLVS1alV16pSyVsvd63NJUsmSJXX79u00x7t165Y8PT0LInQAmejeYpgqlK6pX/74RPtPbUhTHhB0SAvXT5SnRzk91ual1O0VvFKS3YcDtpjV33Z4mW5GXDHbljoi6Z6RTwdOb0p37aiccHZIuXGnl3Dz+Wd6vEP3xPjLzk/THeFUUB5p8rQiY8O0dMv7acpyOzosdXTWPfsv2zq9QNvapekgGU1GLVg/Md3ysMjcD5m2pLIlpBq5eAmmbc5maCySOjT6PxkMBq3Y+ZnZ9nV/zVNcYow6Pfi0ZQIDAADIgUa+klv2Zh5PZZDUxjLv1gEoRPhOBMAaFdkRXRUqVNDOnTs1btw4/f777woMDFTdunU1Z84cPf/886pWrZqktImuOnXqpLsW14kTJ9S+PW8sAJbm5OCi94b8qknzu+vNhb3UtsHjalStg2xt7HTq8j5tPbhYbs4l9d6QX1XS/d+eft8ytdSkRmet3TtHJpNJ1co31rkrR7T72EqV96qu5Lumaqxfpa083b0157exCgkLVOkSFXTuyhFtObRYVbwb6EKIf67jr+XbPGUKxK3TFBUbJicHV3l7VlGdii3VpEZn+Zaupe82TVFEzE15e1bR8Qu7dPLS3lyvNZYX+rYdo70n1mjJ1vd1+vJ+Na3ZVQ72TgoMOa6gG6c1c8SWrA9yj4fq99WKnZ9q8oKe6tnyBdnZOejQmc26cPXvAm1r+4ZPqFvzoVq9+0sFBB1Sq7p+KuHqpRu3g3Ti4h5duXlWiyda5winrvWlc9clYzZzkb6eUt3y+RuTNahSroEebfOSVu/+Uu98108tavfUpesntWrXLDWs+rA6PfiUpUMEAADIkp2t1KWetPJg9vdpWU3yzLtJDgBYKb4TAbBGRTbRJaUkrX77Le3cTVFRUQoMDJSNjY3q1zdfe8XPz0+TJk1SUFCQKlSoIEn666+/dO7cOf33v/8tkLgBZM63TC3Nfu2oVu78XLuOrdC+U+sUlxAtSapctp4+fWmX3JwfSLPfhIGL9eXql7Xt8BJtObRYDaq0039HbtesFS/qWlhgaj035wc0Y/hGzVs7Xqt3f6FkY5Jq+DTVtOfWaf2+BfeV6CpTsqLGDlion7Z/qFkrXlRScqK6NB2sOhVbytbGVu8N/VVfrRqt1bu/kJ2tg5rW7KqPX/xdr3z1UK7Peb/s7Rz0wfObtPyPj7X98FIt3DBJDnZO8vGqoW73TO2YXfWrPKQpg37Rki1T9d3Gt+Rg76wmNTrr4xd/12vfFOxLBa8PWKhG1Tpq3V9z9eO2GUpMTpCnu7eq+zTRsB4zCjSWvFTDW/q/ltKPe9NbwcxcGQ/p+Q6STZEd550zLz76mcqWrKx1f83VvpNr5eHqpT4PvazB3d6TDRcJAABYifa1pFvR0u+nsq5bp7z0RPP8jwmAdeA7EQBrYzDldt4pK/bXX3+pVatWqlWrlk6dMn/ii4iIUIMGDeTl5aV3331XcXFxGj9+vEqXLq09e/YU2ps5a3QhL9lN619o1+jKcN/kJE1d3F+7j6/SyN6f6PH2r+ZtcEAOdBytQjPX84lgad1RKSidpc/sbKUmlaQ+TSSXvFl+zSrcz70GKAoK0z0KAJC/TCbpzwBpywkpLDptuYtDyvTV3RpItoWzuwNAPuA7EYo7vhMVHnev0RUVFSVXV9dcHadIj+jKiL9/ymiMe6ctlCQPDw9t27ZNY8aM0cCBA2VnZyc/Pz99+umnhTbJBUCytbXT5Gd+0jvf9dXsNa/Jwc5Jvdu8aOmwAIur65Pyhu7Fm9LRS9L2k/+WvdtXci1GCS4AAIDixmCQHqopta4unbwinbwq7Trzb/k7fSULvOMIAACQp4rl40xmiS5JqlatWrpTHgIo3OztHDRt2FpLh2EVEpMSFBlzK8t6JdxKy9bGtgAiQn4yGKTKXik/O06mTGVoEEkuAACA4sLGRqpXIeVn95l/nwdJcgEAgKKgWD7SZJXoKs4Cwq5q2PrZCo2NVAkHF83vMVL1vCqkqffq1u/027mDuhgRqn2DpqtxmcrZLt944aje3vWzEpKT5GLvqK+6DFOjMpUKNP715w/r7V3LZTSZlGRM1mvN/TSofsq6QDdjI9Xt5+mpdWOS4nXh9nUF/2e2PJ0zX5k3u+fPrF5mZVld9zu+89+h5zfO1fLHXtVjNZpnuwzFx4mLf+r12R2zrLd44gV5e1bO/4AAAAAAAAAAIBeKZaJr27Ztlg6h0Hpp0wINb9hJg+o/rF9O/6Xh62drz7Pvp6nXr2YLjW3hp47L3k33OBmVh8VFafDar7R14BTV86qgXUGnNHjtVzoydGaBxW8ymTRk3dfa/H9vqWHpigoMv6EGC19X35rN5e7grFLO7joweEZq/U/2/6Y/Lp/MMsmV3fNnVS+zsqyuuyQFht/QAv/talmueo7KULxULddIHz6/Oct6nu7eBRANAAAAAAAAAOQOi04h1fXocB28dkFP1W0rKSWpEhR5U2fDQtLUbedbRxXcS2V4rIzKz9++Lk9nt9QRSm0r1NblyJs6fO1CgcZvkEHhcSkr8UYkxKqUs5scbe3TPe4i/x0a2qBDnp0/s3pZHSOr6240GTVy41x91mlwmvZkVobix92lpJrU7Jzlj4O9k6VDBQAAAAAAAIAMkehCqqDIm/J2fUB2/6zHYzAY5OtRSpcjb+bZOaqX9Nat2CjtCU5Z/XbN2YOKTIhVYPiN+z52duM3GAxa0vtlDfj1U1WfM1odl72rBT1GysE27QDHPcFndDsuWr2qNcmz82dW734/g88OrFNrn1pq4l01R2UAAAAAAAAAAFijYjl1YXHVbskUnb2ddnSTJO17dka62/NaCUcX/fjoGL2580dFJcapVbkaqlPKJzWxk5m8ij/JmKwZe1bp50dfVTvfOjpw9Zz6rfpYhwZ/IC8XD7O6i/x36Ol67bIVn6Udu3FZK8/s07aBU3JUBgAAAAAAAACAtSLRVYzsfPq9TMsdbe0UEn1bScZk2dnYymQy6XLETflmMlVebnSoWE8dKtaTJMUnJcr3mxdVp5RPlvvlVfxHr1/UlegwtfOtI0lqVq6afNw8deT6RXWu3CC1XlRCnP53eq/+fGZqttpVwb1Uts6fWT0PB+dcfwa7g0/pYkSo6i54TZIUEh2uk5sWKCT6tiRlWDaicZdstQ8AAAAAAAAAgMKGqQuRqoxrCT1YprKWntglSVpxZp983D1VvaR3np7nalRY6p+n7V2pDhXrpZ5j6LqvtSpgf66Om934K7iXUkjUbZ28GSxJOhsWovPh11TTs5xZveWn96hhmYqqfU8SLqMYs3v+zOrdz2cwonEXXXrxawW8MEsBL8xSy3LV9XXXYRrRuEumZQAAAAAAAAAAWCtGdMHMV12Hafj62frgr9XycHDWvO4jUstGbJwrv2pN1bt6U/1n03ytP39EIdG35fe/D+Tu4KyTwz9NrZtZ+bu7/6ddwaeUbDSqZfkamtvthdT9DoZc0Kgm3fM9/q+7DtdTa2bJxmCQ0WTSZ48MUUUPL7NjLfLfoWENOqY5R2YxZvf8mdXLrCyr6w4AAAAAAAAAQHFiMJlMJksHgftnSkhS0uTllg7jvtyIidCgtV9qff9Jlg4lQ9YQY16wm9ZfBoeCz4MnJ0jbZxX4aYE813G0ZOtg6SjS9+oSySTJIOnTpy0djWVwr0FxV5jvUQCA/MfzIAC+E6G44ztR4REdHS03NzdJUlRUlFxdXXN1HKYuRKFR2sWj0CeQrCFGAAAAAAAAAACKCxJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKtlZOgDkEXtb2U3rb+koUFTY21rktDb2KYtBAtbOxt7SEQAAAAAAAADFA4muIsJgMEgOfJywbgaDZOtg6SgAAAAAAAAAANaCqQsBAABQ5H2/6R11GWdQyK1AS4eSb7qMM2jmj0MsHQYAAAAAAAWKIUAAAAB5LDouQit3fq7dx1cqODRARmOyypasrFZ1/PREh9dV0q2MpUNM19ngI/rz+Cp1bTZE3p6VLR0OAAAAAABAlkh0AQAA5KGgG2c0cV43Xbt9UW3r91P35sNkZ2uvk5f2asWuz7TxwCJNfe431anY0tKhpnHuyhEt3vyuGlXrQKILAAAAAABYBRJdAAAAeSQuIUZvLeqt0IhgTR26Ri3r9Eot69XqBfVu/R9NmNtZUxY9qrlj/QvtyC4AAAAAAABrQaILAAAgj2zYt0BBN85owMPjzJJcd9TybabnekzXFytf0vId/9ULfv+VJG3c/60++nmoPhq5XY2qdTDbZ+w3HXQtLFA/TApM3Xbg9CZt2L9Apy/v162Iq7K3c1Qt3xZ66pHJalTt4XT3/+ylPzXnt7E6cHqDEpPiVb9KO43q84UqlK4pKWUNq8Wb35UkvT67Y+r+XZoO1viB36aWL554Ic1or2emV1bZkpX18Ys7/t1vnEFdmg5Wl2aDtGj9ZJ2/elTuLp567KGXNbDjBEXGhGnub69r74k1ik2IUuPqnfTK43PlVaJ8Ti+7EpMStGLnZ9p2eKmCQ8/I1tZePl411LXZEPV5aNQ9deO1YP0kbTn4vcKjbsi3TG0912OGWtbpaVbv1z+/1u5jq3Tx2nGFR9+Qh0spPVj9EQ3p/n6a9t9pq1+rEZq//g0FXD4ge3snPVS/r/7z6GdydnRLrTvzxyHafPA7rXrvtuave0O7/H9RdHyEavg01chHP0kz0s9kMum3PbO1ft98Xbp+UgaDjWr5NtcznaeocfWOAgAAAACguLOxdAAAAABFxR/+/5Mk9Wz1QoZ1ujYbIjtbe+30/yXX59l04FtFxtxSl6aD9FKfL/R4u1d1+fpJjZ/7iPzP70xTPy4hWmO/aS9bg62e6z5dj7UZpb/P7dCUbx9TsjFZktS2fj/1apkS95OdJmnCwMWaMHCx/FqNyHWc564c1tTF/dWoWgeN8PtYPl41tGDdG1qx83ONn/uIImPD9GzXd+TXaqT2n96gmT8OyvE5EpMSNHF+N81fN0El3ctqcNf3NLT7NNX0aard/ivS1J/502Adu7BT/R9+XYO7TdXt6Bt657s+CrkVaFZv+e8fqYSrl/q0Ha2X+36l9o0GaPexlRrzVRtFRN9Mp61H9OYiP9Wq0Fwjen+ipjW7asO+BZq95rV0435jfjeFhgfp6S5T9GTHiQq8dkxvLuilmLhIs3ofLntWX64apfJe1TW810wN6vquouPCNWFeF/15/NccXy8AAAAAAIoaRnQBAADkkcCQY3JxdJePV/UM6zg5uMi3dG1dCPFXbHyU2Wif7Hq1/zw5O7iabfNrPVLDP6qnZdtnqEHVdmZl4dGh6v/wOP1fx/Gp20q4lda8teN1KGCLmtfqpqrlG6pOpdZa+9dcNa3ZJc3Isty4EOKvz0ftSR2l1L3FMD0zvZJmr3lVj7UZpZf6zDKr/8vOT3X5+mn5lqmV7XOs2PmZjp7boYGdJmpYj+lmZUajMU39Eq5emjp0jQwGgySpcfWOGjWrhdbunaNhPWek1ps71j/NNW5d91FNmNtZ6/ctMLuWKW3926ytfq1HKCYuQhv3L9LI3p+k+Zxr+DTR6H5fp/5esWxdvf/DAG07vFR+rVOSi7v8V2rr4SV65fE56nVX8rRf2zF6+ctW+mb1GLWu2zu1LQAAAAAAFEeM6AIAAMgjMXERcnUqkWU9FyePlPrxkVnUTN/dCZjY+ChFRN+UjY2taldsqVOX/kpT38Zgo75tR5tta1y9kyQpODQgVzFkR52Krc2m4rO3c1At3xYymUzqc0889au0y1U82w4vkbtzST3beUqaMhubtI+6fduOMUsM1fJtLmdHtzTnvXONjUajomPDFR4dqmrlG8nVqUS61/jetkop1zjZmKSQsMA09fu1e9Xs9wfT+Ty2HvpBLo7ualO/j8KjQ1N/ouJuq3Wd3goJC8zXzw8AAAAAAGvAiC4AAIA84uLkoej4iCzrxcRFyMZgoxKuXrk6z5XQc1q0YbIOnNmoqNjbZmXpje4p5VFeDvZOZts8XEpJkiLTmYYvr5QrVTXNNjfnkpIkb88qZtvdXVK2R8TkLJ7g0ABVK984TfsyjMkzbUweLqXSnPfw2W36YfN7OnXpLyUkxZmVRcWGpT1uOm29c43Tm+rw3voerv/UvSuOS9dPKiY+UgPeLZtRcxQWeS11nTUAAAAAAIojEl0AAAB5pLJ3ffmf/0PBoWcznL4wLiFGl2+cUpmSlWRnay8p/eTUHcnGJLPfY+Oj9No37RWXEK1+7V5RFe8GcnZ0l43BRsu2z9CRs9vSHMPGxjbD45tkyk7TZFD2Y0w9ryHj89pmEJPJlL14ciuja3H3eU9f3q835nWVT6nqGtbzA3l7VpGjvbMMMmjakoEymtJOiZhZW5XONc5O+00y6QHX0pr41NIMj1zZu34m5wUAAAAAoOgj0QUAAJBH2jd4Qv7n/9D6ffM1vOcH6dbZfPB7JSUn6pEmz6Ruc3fxlCRFxNxKUz/k1oXUhJgkHQ7YqpsRVzR2wEJ1bz7UrO6ijW/eV/yZJdzuxBgZc0venpVTtyckxulWxFWVL5XxumT5ycerpi5fP6WEpHg52DnmyTG3HV4qozFZ04avV7m7Rp7FJkSnO5orv/h41dC+G2dUp1KrXK3lBgAAAABAccAaXQAAAHmke4thqlC6pn754xPtP7UhTXlA0CEtXD9Rnh7l9Fibl1K3V/BKmXrucMAWs/rbDi/TzYgrZttSRyTdM/LpwOlN6a4dlRPODinJlPQSbj7/TI936J4Yf9n5abojnArKI02eVmRsmJZueT9NWW5Hh6WOzrpn/2VbpxdoW7s0HSSjyagF6yemWx4Wea3AYgEAAAAAoLBiRBcAAEAecXJw0XtDftWk+d315sJeatvgcTWq1kG2NnY6dXmfth5cLDfnknpvyK8q6f7vuku+ZWqpSY3OWrt3jkwmk6qVb6xzV45o97GVKu9VXcnJial161dpK093b835baxCwgJVukQFnbtyRFsOLVYV7wa6EOKf6/hr+TZPmQJx6zRFxYbJycFV3p5VVKdiSzWp0Vm+pWvpu01TFBFzU96eVXT8wi6dvLQ312uN5YW+bcdo74k1WrL1fZ2+vF9Na3aVg72TAkOOK+jGac0csSXrg9zjofp9tWLnp5q8oKd6tnxBdnYOOnRmsy5c/btA29q+4RPq1nyoVu/+UgFBh9Sqrp9KuHrpxu0gnbi4R1duntXiiecLLB4AAAAAAAojRnQBAADkId8ytTT7taN6tss7Cg4N0Ly14/XZLyO0Yd8C+XjV0MLxp1TLt1ma/SYMXKyHGvTTtsNLNOe3sboWFqj/jtwuLw8fs3puzg9oxvCNqu3bUqt3f6E5v43VxWsnNO25daru0+S+Yi9TsqLGDlio+MRYzVrxoqYveVJr/vxGUsqaUu8N/VWNqnbQ6t1faMG6N5SYnKCPX/xdTg6u93Xe+2Fv56APnt+kId3f143wy1q4YZIWrp+k05f3qW2Dfrk6Zv0qD2nKoF/k5OCq7za+pcWb3pGjvbNF2vr6gIUaP/B72djY6MdtM/Tlqpe1+eB3cnZ007AeMwo0FgAAAAAACiODKb9X/AYAAIXGq0skkySDpE+ftnQ0lpGcIG2fVcDnTE7S1MX9tfv4Ko3s/Ykeb/9qwQYA3KXjaMnWwdJRAAAshedBAJb4TgQUJnwnKjyio6Pl5payjEJUVJRcXXP3cikjugAAAPKZra2dJj/zk1rU7qnZa15LHSUFAAAAAACA+8MaXQAAAAXA3s5B04attXQYViExKUGRMbeyrFfCrbRsbWwLICIAAAAAAFBYkegCAABAoXLi4p96fXbHLOstnnhB3p6V8z8gAAAAAABQaJHoKsZMJpOUmGzpMFAQ7G1lMBgsHUWWTCbJmGjpKID7Z2MvWcFfOaDQqlqukT58fnOW9TzdvQsgGqDo4ZkLxR3PataFvgtYBSvpdwGAoopEV3GWmKykycstHQUKgN20/pJD4f/rbkxkMVQUDSxqCtwfd5eSalKzs6XDAIosnrlQ3PGsZmXou4AVsJZ+FwAoqmwsHQAAAAAAAAAAAACQGyS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAAAAAAAAAACAVSLRBQAAAAAAAAAAAKtEogsAAAAAAAAAAABWiUQXAAAAAAAAAAAArBKJLhQp3x/7XQ4fPaXvj/2ebnlg+A05fPSUhq2fXcCRAQAAAAAA5C/6RQAAxRGJLgAAAAAAAAAAAFglEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqFYtEV2hoqMaPH6/q1avLyclJvr6+GjNmjKKjozVs2DAZDAZ9+eWXlg4TAKza95veUZdxBoXcCrR0KPmmyziDZv44xNJhAAAAAAAA5Aj9NijK7CwdQH47cuSIevTooZCQELm6uqpu3bq6cuWKZs2apXPnzunWrVuSpMaNG1s2UAA5Eh0XoZU7P9fu4ysVHBogozFZZUtWVqs6fnqiw+sq6VbG0iGm62zwEf15fJW6Nhsib8/Klg4HxUjQLenoJcn0z+8mSXGJkpO9JaMqnJZtm6GA4EMKCDqokFsXVLZkJf0wKdDSYQG4DyaTFBgqHQuSYhIke1vJp6T0YCXJoch/I8o5o9Golbs+19q9cxQSFqgHXEurfaMBGtztPTk7uFo6PAAAYAXotwFQkIr017rQ0FD17t1bISEhGjt2rN5++225u7tLkmbOnKkJEybIzs5OBoNBDRs2tHC0KEiGu/788uaFWnv+kMLjY+Xu4KTHa7bUjIefkoNtkf7rYdWCbpzRxHnddO32RbWt30/dmw+Tna29Tl7aqxW7PtPGA4s09bnfVKdiS0uHmsa5K0e0ePO7alStAw9MKBABIdK6o9KF0LRlU1ZIzatIvR8k4XW3hesnyd3FUzV8mig69ralwwFwn/6+LG30l4LD0patPiS1qi71aJiS/EKKb9a8qlW7Zumh+n31xMNjdenaSa3aNUvngg/rwxe2yMamWEwMAgBFGv0iyE/02wAoaEX6X6zRo0crKChIo0aN0kcffWRWNn78eC1dulRHjx5VlSpV5OHhYaEokZec7BwkSTGJCemWRyfGS5Kc/6knSS8+2FUfPPyUXB2cFBoToSfXzNIHe1dpykNP5H/AyLG4hBi9tai3QiOCNXXoGrWs0yu1rFerF9S79X80YW5nTVn0qOaO9S+0bwgBBeHgBWnJHsloSr88IUnaHSCdvyG99Ijk5lSw8RVW379xTuVKVZUkPf9RfcUmRFk4IgC59fspaeXBjMtjEqRtJ6TAG9KITpJjkf52lD2BIce1evcXalu/n94e/Evqdm/PKvpq9WjtOPqjOj34lAUjBABkhn4RWBr9NgAsoci+infy5En99NNP8vLy0owZM9Kt07RpU0lSo0aNUrfdSYy1aNFCjo6OMhgM6e6LwqlKidKSpFO3gtMtP3UzZXvlf+pJUl2vCnJ1SOndNUmyMRh09nZI/gaKXNuwb4GCbpxRv7avmD0s3VHLt5me6zFdt6Oua/mO/6Zu37j/W3UZZ9DRczvS7DP2mw56Znpls20HTm/S+z/8n56dUVW9Jjqrz1sPaMLcrjp67vcM9w8Nv6JpS55U3ykl5TfJRW/M66agG2dS632/6R199PNQSdLrszuqyziD2dzBmc2V/Mz0yhr7TQezbXf2PXx2m0Z/0Vp+k1z05PsV9OP2DyVJkTFh+vjnYer/Thn5TXLRmwv9FBp+Jb3LmqXEpAT9tH2mRnzSWH6TXPTYWyX0n8+badXutOsbJibFa8H6SXry/Qrq+YajRnzSSH+dXJem3q9/fq0Jc7tq4FQf9XjDQf/3Xjl9sPSZdNt/p60nAvfotW8eVu9Jrur3dil9vHy4YuPNkxAzfxyiLuMMio4N1+e/vKj+75RRz4lOGvPlQzp56a80xzaZTFrz5zf6z2dN5TfJRb0nu+n12R115Oz2XF2rwuLc9cyTXHe7elua/7tkNOZ7WFbhTpILgHU7einzJNfdzt+Qftidv/FYi+1HlslkMqlfu1fMtvds+byc7F205dAPlgkMAJAt9IvA0ui3+Rf9NvTboOAU2UTXsmXLZDQa9fTTT8vNzS3dOs7OzpLME11nz57VL7/8Im9vbzVv3rxAYkXeebBsFfm6l9LPp/boSpT5/DQJyUn65vAmGWSQX/WmZmUz//pVJT8fKp+vR+rvGxc1ukmPggwbOfCH//8kST1bvZBhna7NhsjO1l47/X/JsE5WNh34VpExt9Sl6SC91OcLPd7uVV2+flLj5z4i//M709SPS4jW2G/ay9Zgq+e6T9djbUbp73M7NOXbx5RsTJYkta3fT71apsT9ZKdJmjBwsSYMXCy/ViNyHee5K4c1dXF/NarWQSP8PpaPVw0tWPeGVuz8XOPnPqLI2DA92/Ud+bUaqf2nN2jmj4NyfI7EpARNnN9N89dNUEn3shrc9T0N7T5NNX2aarf/ijT1Z/40WMcu7FT/h1/X4G5TdTv6ht75rk+aB6Hlv3+kEq5e6tN2tF7u+5XaNxqg3cdWasxXbRQRfTOdth7Rm4v8VKtCc43o/Yma1uyqDfsWaPaa19KN+4353RQaHqSnu0zRkx0nKvDaMb25oJdi4iLN6n247Fl9uWqUyntV1/BeMzWo67uKjgvXhHld9OfxX3N8vQqLTf7ZS3LdERgqnbqaf/EAQEEymaQNf+dsH/8g6fKt/InHmpy+vF82BhvVqtjCbLuDvZOqlm+sM5f3WygyAEB20C8CS6Pfxhz9NvTboGAU2ck5tm3bJknq2LFjhnWCgoIkmSe62rdvr6tXU3r63nnnHe3ezaud1sTOxlZfdH5O/Vd/oqbfTdCQ+h1V7YEyuhYTruWn9urEzSBNaPmYanmWN9tvfMtHNb7lozp5M1jLTu6Wt9sDlmkAshQYckwuju7y8aqeYR0nBxf5lq6tCyH+io2PkrNj+snuzLzaf16axdb9Wo/U8I/qadn2GWpQtZ1ZWXh0qPo/PE7/13F86rYSbqU1b+14HQrYoua1uqlq+YaqU6m11v41V01rdlGjah1yHNe9LoT46/NRe1Lnte7eYpiemV5Js9e8qsfajNJLfWaZ1f9l56e6fP20fMvUyvY5Vuz8TEfP7dDAThM1rMd0szJjOkOASrh6aerQNakjYhtX76hRs1po7d45Gtbz3xG2c8f6p7nGres+qglzO2v9vgVm1zKlrX+btdWv9QjFxEVo4/5FGtn7kzSfcw2fJhrd7+vU3yuWrav3fxigbYeXyq91ykPqLv+V2np4iV55fI563fUQ3q/tGL38ZSt9s3qMWtftbXWje69HSKdz8QLmrjNSXZ+8jwcACtr5G9LV8Jzvt/uMNLBV3sdjTW5GXJGHq5cc7BzTlHmV8NGJi38qMSlB9ndNeQUAKDzoF4Gl0W9jjn4b+m1QMIrsiK6LFy9KkipVqpRueVJSUmoS6+5EFwsrW7+e1R7U70++o4d96+qH439o9NZv9dmBdSrt4qElfqM1td3/ZbhvnVI+ali6ooau+6YAI0ZOxMRFyNWpRJb1XJxS1t2LiY/Momb67v6HPDY+ShHRN2VjY6vaFVvqVDrDqG0MNurbdrTZtsbVO0mSgkMDchVDdtSp2Nps8VZ7OwfV8m0hk8mkPvfEU79Ku1zFs+3wErk7l9SznaekKUvvntm37RizB4xavs3l7OiW5rx3rrHRaFR0bLjCo0NVrXwjuTqVSPca39tWKeUaJxuTFBIWmKZ+v3avmv3+YDqfx9ZDP8jF0V1t6vdReHRo6k9U3G21rtNbIWGB+fr55Zfj6c9SkqWTV6Sk5LyNBQAs4VhQ7vbzz+V+RUl8Qozs00lySZKDXcq0VvGJMQUZEgAgh+gXgSXRb2OOfhv6bVAwiuyIrujoaElSbGxsuuU//fSTQkND5e7uripVquRrLM2aNVNISOGb29jZ1l4nBkzPuqIValaumn589JVc7ZtoTFZAWNGav6tmjRqKTU60dBhZcrBz1txRmf/j5OLkoej4iCyPFRMXIRuDjUq4euUqliuh57Row2QdOLNRUbG3zcrSe0uklEd5Odg7mW3zcCklSYpMZzh3XklvLSE355KSUhaNv5u7S8r2iJicxRMcGqBq5RunaV+GMXmmjcnDpVSa8x4+u00/bH5Ppy79pYSkOLOyqFjzKTak9Nt65xqnN2T+3voerv/UvSuOS9dPKiY+UgPeLZtRcxQWeU0VStfMsDw9NWrWUEJS+v/+FIT63SaodqeXc7yfSVKteo0VHxWa90EVItm51wBFmaXvUQWh6RMfqUrzgTneLyo2WRUqpP+iXFGS2X3Q0cFFsVHX0y278++1o71LvsUGFITicB/MTL8ZF2VjY6tko3Xc84py30V+ol+kYFlLv8sd+fmdiH4bc/Tb0G+DzN096rBt27Y6fPhwro5TZBNd3t7eCgsL06FDh9S6dWuzsqtXr2rcuHGSpIYNG+b70MaQkBAFB+fy9fp85GKf/puaxUl4fIxWB+zXo9WbqYSji/xDL2vGnlXqUrmhpUPLU1euXlVMYrylw8iSUzY6TSp715f/+T8UHHo2w2HwcQkxunzjlMqUrCQ7W3tJ6T/k3JFsTDL7PTY+Sq99015xCdHq1+4VVfFuIGdHd9kYbLRs+wwdObstzTFsbGwzPL5J2VsoyaDsx5h6XkPG57XNICaTKQcLN+VCRtfi7vOevrxfb8zrKp9S1TWs5wfy9qwiR3tnGWTQtCUDZTSlHVqfWVuVzjXOTvtNMukB19Ka+NTSDI9c2bt+JudN39UrVxRnwbfdfW6l30GZHUGXzishNndv1FmL7NxrgKLM0veoglAzPHeLbSUlxBXK5/a8ltl9sJRHeV26dkIJSfFppi8MDQ9WCVcvpi2E1SsO98HMmVL/aw33PPou8ldx6RfJb9bS73JHfn4not/mnvPSb3Pn6Gm2FOd+G6Tv2rVrud63yCa6OnfurJMnT+rDDz9Uly5dVLNmSlZ3//79evbZZxUamvK2euPGjfM9Fm9v73w/R244//MPSXFmkLT0xC6N2/GDEpKTVMbFQ31qtNCUNo9bOrQ8Vb5cOat4s8jBzjnLOu0bPCH/839o/b75Gt7zg3TrbD74vZKSE/VIk2dSt7m7eEqSImLSdnyF3LqQ+mAlSYcDtupmxBWNHbBQ3ZsPNau7aOOb2WpLRjJ7cLsTY2TMLXl7Vk7dnpAYp1sRV1W+VMbzW+cnH6+aunz9VLodXrm17fBSGY3JmjZ8vcrd9QZTbEJ0um8F5Rcfrxrad+OM6lRqlas5wTNSrnx5i74ZZIzK3dxb0bcuqbSnhySPvA2okMnOvQYoyix9jyoIiREXc7VfxLWT8vEp+osVZnYfrOXbXAfPbNLpS/vM1rZISIzT+StH1KBq+4IIEchXxeE+mDlD6n+t4Z5H30X+Ki79IvnNWvpd7sjP70T02xQ8+m1yjmeBwsNoNOrq1ZRRxGXLZjxyLytFNtE1fvx4LV26VJcvX1a9evVUu3ZtxcXF6ezZs+rRo4cqV66sjRs3mq3PlV8OHDiQ7+fIDVNCkpImL7d0GBbl4eiiDQMmWzqMfHcmIEAGh8L/1z05Qdo+K/M63VsM0+o/v9Qvf3yiRlU7qHnt7mblAUGHtHD9RHl6lNNjbV5K3V7BKyXZfThgi9o16Je6fdvhZboZcUVlS/47ZUfqmy33vEFz4PSmdOcgzglnh5R/lNN7cPP5Z5j1oYAtqlGhSer2X3Z+mu6bMgXlkSZPa97a8Vq65X0N6T7VrMxkMuVqVGzqWz73XONlW6cXaFu7NB2kvSfWaMH6iRrV54s05WGR11TSPef/yAacCZCtBV92TzZKU1dLt3P4ctLAThU17+Wiv0BNdu41QFFm6XtUQYhLlN5eIcWn/2JthkYPbKbFk4r3fbBDo//Tsm3TtWLnZ2aJrnV/zVNcYow6Pfh0AUUJ5J/icB/MzKtLUt6rt7WxVVBQ4b/n0XeRv4pLv0h+s5Z+lzvy8zsR/TYFj34b6+u3wb+io6Pl5pby927Xrl25Po713IFzqEKFCtq5c6fGjRun33//XYGBgapbt67mzJmj559/XtWqVZOkAkl0Acg7Tg4uem/Ir5o0v7veXNhLbRs8rkbVOsjWxk6nLu/T1oOL5eZcUu8N+dXsHzrfMrXUpEZnrd07RyaTSdXKN9a5K0e0+9hKlfeqruS73ryqX6WtPN29Nee3sQoJC1TpEhV07soRbTm0WFW8G+hCiH+u46/l2zxlKP3WaYqKDZOTg6u8PauoTsWWalKjs3xL19J3m6YoIuamvD2r6PiFXTp5aW+u56zOC33bjtHeE2u0ZOv7On15v5rW7CoHeycFhhxX0I3TmjliS46P+VD9vlqx81NNXtBTPVu+IDs7Bx06s1kXrv5doG1t3/AJdWs+VKt3f6mAoENqVddPJVy9dON2kE5c3KMrN89q8cTzBRZPXrG1kR6qIa09mv197G2lltXyLyZrsvngYl0PSxkNcjv6hpKSE7Rky/uSpDIlK6lL02ctGR6AbHCyl1pUk3aezv4+bk5S48K/VE2+q1KugR5t85JW7/5S73zXTy1q99Sl6ye1atcsNaz6sDo9+JSlQwQAAIUY/TYFj34b6+u3Qd4rsokuSapTp45+++23NNujoqIUGBgoGxsb1a+f8zk8AViWb5lamv3aUa3c+bl2HVuhfafWKS4hWpJUuWw9ffrSLrk5P5BmvwkDF+vL1S9r2+El2nJosRpUaaf/jtyuWSte1LWwwNR6bs4PaMbwjZq3drxW7/5CycYk1fBpqmnPrdP6fQvu64GpTMmKGjtgoX7a/qFmrXhRScmJ6tJ0sOpUbClbG1u9N/RXfbVqtFbv/kJ2tg5qWrOrPn7xd73y1UO5Puf9srdz0AfPb9LyPz7W9sNLtXDDJDnYOcnHq4a63TNFQHbVr/KQpgz6RUu2TNV3G9+Sg72zmtTorI9f/F2vfVOwUyK9PmChGlXrqHV/zdWP22YoMTlBnu7equ7TRMN6zCjQWPJSp7rSuevSqWysIW2QNOihlE5eSBv2LdDf53832/btxrckSQ2rPkyiC7ASfo2li6HSpWys5W1nIz3XLiXpD+nFRz9T2ZKVte6vudp3cq08XL3U56GXNbjbe7KxsbF0eAAAoJCj36Zg0W8DSAZTfq9uVwj99ddfatWqlWrVqqVTp06lKf/f//4nSfr555+1fPlyLV+eMkS+cuXKatasWYHGmp8Y/l982E3rbxVD6O9n6HxycpKmLu6v3cdXaWTvT/R4+1fzNjggBzqOVqEYAp+YLC3dIx3OZKkaRzvp2Yek+hUKLi5LY+pCFHeF5R5VEGITpG93SaczSfq7OUrPtZeqlim4uCyN+yCKu+J0H0zPnakLDZI+tYLZSOm7gDWwln6XOyzxLEC/DQqT4v4sUJjcPXVhVFSUXF1dc3Uc67kD5yF//5SsfkbTFvbv3z/d3wcPHqxvv/02X2MDkDu2tnaa/MxPeue7vpq95jU52Dmpd5sXLR0WYFH2ttLgttIjdaXdAdLRS1JMgmRjkMqWkNpUl5pXTZniCwCKImcHaWRHKTBU2n1GOhacsn7XHU+2kh6sJFlRvxQAAIBVot8GQH4qll/pskp0FcNBbkCRYG/noGnD1lo6DKuQmJSgyHQWVr1XCbfSsrVhHidrV8FT+r+WKT9Go2QwpPwAQHFgMEhVSqf8SNIrS/7ZLtYmBAAAKEj022Qf/TZAzpDoQrp6Lp+hkOjbsjHYyN3BSZ90GqwHy1bOsP53/jv0/Ma5Wv7Yq3qsRnNJ0vrzh/X2ruUymkxKMibrteZ+GlQ/7+ZwDQi7qmHrZys0NlIlHFw0v8dI1fNKO/dWdurdG//N2Eh1+3l6anlMUrwu3L6u4P/MlqezW5Ztz8yrW7/Tb+cO6mJEqPYNmq7GZSqnW2/jhaN6e9fPSkhOkou9o77qMkyNylTKUWxARk5c/FOvz+6YZb3FEy/I27Ny/geEAsPSKgCKO4NSpuwCABQfedV/kNH3+cy+p7vYO+jp377QyZvBcrZzUBkXD33R+TlVL+ldYHFnVB6XlJCt2NLr94hPStT4HT9oc+DfcrRzUMPSFfVdr5eybFN2ZLfdWdXNrP8lN31FQEGi3wbImWKZ6Nq2bZulQyj0lvYerQecUubDXBWwX8M3zNbBwR+kWzcw/IYW+G9Xy3LVU7eZTCYNWfe1Nv/fW2pYuqICw2+owcLX1bdmc7k7OOdJjC9tWqDhDTtpUP2H9cvpvzR8/Wztefb9HNdLL/5Szu46MPjfxQw/2f+b/rh8Mk0iKb19s9KvZguNbeGnjsvezbBOWFyUBq/9SlsHTlE9rwraFXRKg9d+pSNDZ2Y7NiAzVcs10ofPb86ynqd71l++AAAAAKAwy6v+g4y+z2f2PT0uKUHDG3ZS9yqNZTAY9PWhjRq5cZ62DHyrwOLOrDyr2DLq95i880cZDAYdH/aJDAaDQqJvZ9me7Mpuu7Oqm1n/S276ioCCRL8NkDO814103UlySVJEfIwMSn+OK6PJqJEb5+qzToPlaGu+yItBBoXHRaccIyFWpZzd0tTJrevR4Tp47YKeqttWUsrDS1DkTZ0NC8lRvcziv9si/x0a2qCD2bbs7nuvdr51VMG9VKZ1zt++Lk9nt9S3idpWqK3LkTd1+NqFbMUGZMXdpaSa1Oyc5Y+DvZOlQwUAAACAXMur/gMpe9/nJfPv6U52DupR9UEZ/pk7vGX5GroYcaPA4s6sPKvYMur3iE6I0yL/HXqv7YDUfb1dH8iyTdmR3XZnp25Gn1de9RUB+Yl+GyBnSHQhQ0PXfa2qc0bpnd3Ltahn+otDfnZgnVr71FIT76pm2w0Gg5b0flkDfv1U1eeMVsdl72pBj5FysM2bQYRBkTfl7fqA7P6Zg9ZgMMjXo5QuR97MUb2M4r/bnuAzuh0XrV7Vmphtz86+uVW9pLduxUZpT/AZSdKaswcVmRCrwHDzh+GMYgMAAAAAAHnXf5BdWX1P/+LQBvWu3rTA4s5Ju+6NLaN+j3Ph1+Xp5KoP/lqtVosnq+Oyd7Xt4rEs25QdOYk3t59ZXvQVAQAKl2I5dSGyZ1HP/0iSvj/2hyb/sUy/Pj7BrPzYjctaeWaftg2ckmbfJGOyZuxZpZ8ffVXtfOvowNVz6rfqYx0a/IG8XDwyPW+7JVN09nbaN3Ukad+zM+TrkfXbU9mRWfx3W+S/Q0/Xa5f6AJSTfXOrhKOLfnx0jN7c+aOiEuPUqlwN1SnlYxZDRrEBAAAAAFBcZNWHUNAy+57+wd5VOhcWoq8HTC7wuLJyb2yZ9XskG5N1MSJUdUr5aHr7J3X4WqB6/m+6jgz5r8q6lsj0PIXt87pXfvf3AADyB4kuZGlQ/fYatWWBbsZGqpSze+r23cGndDEiVHUXvCZJCokO18lNCxQSfVvNvKvpSnSY2vnWkSQ1K1dNPm6eOnL9ojpXbpDp+XY+/V6WMVVwL6WQ6NtKMibLzsZWJpNJlyNuyveeIemZ1dt60T/D+Ec07iJJikqI0/9O79Wfz0w1O25mbb+z7/3qULGeOlSsJyllkVffb15UnVI+qeUZxQYAAAAAQHGRVR+Co63dffcfZFdm39M/2f+bVgXs14b+k+Ri75jlsfKi3yO7x0kvtsz6PR6v2VI2BoOeqpMy9d+DZSurskcZHQu9pLKu99fnk93PKyfXKCf7ZaevCABQ+DB1IdK4HRetK1Fhqb+vDtivUk7u8nRyM6s3onEXXXrxawW8MEsBL8xSy3LV9XXXYRrRuEvKQ0PUbZ28GSxJOhsWovPh11TTs5yklGkRVwXsz3WMZVxL6MEylbX0xC5J0ooz++Tj7qnqJb2zXS+z+O9YfnqPGpapqNp3JZiyantetE+Srt71GUzbu1IdKtYza19GsQEAAAAAgBR50X+QXRl9T//swFr9dOpPre8/0WxNdCnj/oO8ijur8oxiy6zfw8vFQ50q1temwKOSpAu3rysw4rpqe/pk2qbsyMnnkNvP7H77igAAhQ8jupBGeHyMnlzzuWKTEmVjMKi0s7tW9ns9dYHRERvnyq9a00znlC7rWkJfdx2up9bMko3BIKPJpM8eGaKKHl6SpIMhFzSqSff7ivOrrsM0fP1sffDXank4OGte9xGpZXfHmFm9rCzy36FhDTrmOLbM2vefTfO1/vwRhUTflt//PpC7g7NODv80Tdzv7v6fdgWfUrLRqJbla2hutxfyJDYAAAAAAIqTvOo/yOz7vJT+9/SgyJsav2OJqpYooy4/TZOUMmpp9z+jvjLrP8iruDMqzyq2zHzZ5TmN2DhPk/74UTYGg77qMlw+7p5Ztik7stvurOpm9nndT18RAKDwMZhMJpOlg4BlmBKSlDR5eYGf90ZMhAat/VLr+08q8HMXhMLYPrtp/WVwKPx57eQEafssS0cB3L+OoyVbB0tHgYxwr0FxV9zvUa8ukUySDJI+fdrS0VgG90EUd9wHres+aKm+i4JQGPsP7ldRbFN2WEu/yx08C6C4K+7PAoVJdHS03NxSZpKLioqSq6trFnukj6kLUeBKu3gU6Qeeot4+AAAAAABw/4pi/0FRbBMAoPAj0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJTtLBwALsreV3bT+lo4CBcHe1tIRZIuNvdRxtKWjAO6fjb2lI0BmuNeguOMeBQCwKvRdwBpYSb8LABRVJLqKMYPBIDnwvwAKD4NBsnWwdBQAijruNQCA4uj7Te9o8eZ3tXjiBXl7VrZ0OPmiyziDujQdrPEDv7V0KMhD9F0AAICs8KQAAAAAAMhT0XERWrnzc+0+vlLBoQEyGpNVtmRltarjpyc6vK6SbmUsHWK6zgYf0Z/HV6lrsyFFNhkEAAAAFDUkugAAAAAAeSboxhlNnNdN125fVNv6/dS9+TDZ2drr5KW9WrHrM208sEhTn/tNdSq2tHSoaZy7ckSLN7+rRtU6kOgCAAAArASJLgAAAABAnohLiNFbi3orNCJYU4euUcs6vVLLerV6Qb1b/0cT5nbWlEWPau5Y/0I7sgsAAACA9SDRBQAAAADIExv2LVDQjTMa8PA4syTXHbV8m+m5HtP1xcqXtHzHf/WC338lSRv3f6uPfh6qj0ZuV6NqHcz2GftNB10LC9QPkwJTtx04vUkb9i/Q6cv7dSviquztHFXLt4WeemSyGlV7ON39P3vpT835bawOnN6gxKR41a/STqP6fKEKpWtK+ncNK0l6fXbH1P3vrPmU2RpXz0yvrLIlK+vjF3f8u98/60V1aTZIi9ZP1vmrR+Xu4qnHHnpZAztOUGRMmOb+9rr2nlij2IQoNa7eSa88PldeJcrn9LIrMSlBK3Z+pm2Hlyo49Ixsbe3l41VDXZsNUZ+HRt1TN14L1k/SloPfKzzqhnzL1NZzPWaoZZ2eZvV+/fNr7T62ShevHVd49A15uJTSg9Uf0ZDu76dp/522+rUaofnr31DA5QOyt3fSQ/X76j+PfiZnR7fUujN/HKLNB7/Tqvdua/66N7TL/xdFx0eohk9TjXz0kzQj/Uwmk37bM1vr983XpesnZTDYqJZvcz3TeYoaV+8oAAAAwMbSAQAAAAAAioY//P8nSerZ6oUM63RtNkR2tvba6f9Lrs+z6cC3ioy5pS5NB+mlPl/o8Xav6vL1kxo/9xH5n9+Zpn5cQrTGftNetgZbPdd9uh5rM0p/n9uhKd8+pmRjsiSpbf1+6tUyJe4nO03ShIGLNWHgYvm1GpHrOM9dOaypi/urUbUOGuH3sXy8amjBuje0YufnGj/3EUXGhunZru/Ir9VI7T+9QTN/HJTjcyQmJWji/G6av26CSrqX1eCu72lo92mq6dNUu/1XpKk/86fBOnZhp/o//LoGd5uq29E39M53fRRyK9Cs3vLfP1IJVy/1aTtaL/f9Su0bDdDuYys15qs2ioi+mU5bj+jNRX6qVaG5RvT+RE1rdtWGfQs0e81r6cb9xvxuCg0P0tNdpujJjhMVeO2Y3lzQSzFxkWb1Plz2rL5cNUrlvapreK+ZGtT1XUXHhWvCvC768/ivOb5eAAAAKHoY0QUAAAAAyBOBIcfk4uguH6/qGdZxcnCRb+nauhDir9j4KLPRPtn1av95cnZwNdvm13qkhn9UT8u2z1CDqu3MysKjQ9X/4XH6v47jU7eVcCuteWvH61DAFjWv1U1VyzdUnUqttfavuWpas0uakWW5cSHEX5+P2pM6Sql7i2F6ZnolzV7zqh5rM0ov9ZllVv+XnZ/q8vXT8i1TK9vnWLHzMx09t0MDO03UsB7TzcqMRmOa+iVcvTR16BoZDAZJUuPqHTVqVgut3TtHw3rOSK03d6x/mmvcuu6jmjC3s9bvW2B2LVPa+rdZW/1aj1BMXIQ27l+kkb0/SfM51/BpotH9vk79vWLZunr/hwHadnip/FqnJBd3+a/U1sNL9Mrjc9TrruRpv7Zj9PKXrfTN6jFqXbd3alsAAABQPDGiCwAAAACQJ2LiIuTqVCLLei5OHin14yOzqJm+uxMwsfFRioi+KRsbW9Wu2FKnLv2Vpr6NwUZ9244229a4eidJUnBoQK5iyI46FVubTcVnb+egWr4tZDKZ1OeeeOpXaZereLYdXiJ355J6tvOUNGU2Nmm/8vdtO8YsMVTLt7mcHd3SnPfONTYajYqODVd4dKiqlW8kV6cS6V7je9sqpVzjZGOSQsIC09Tv1+5Vs98fTOfz2HroB7k4uqtN/T4Kjw5N/YmKu63WdXorJCwwXz8/AAAAWAdGdAEAAAAA8oSLk4ei4yOyrBcTFyEbg41KuHrl6jxXQs9p0YbJOnBmo6Jib5uVpTe6p5RHeTnYO5lt83ApJUmKTGcavrxSrlTVNNvcnEtKkrw9q5htd3dJ2R4Rk7N4gkMDVK184zTtyzAmz7QxebiUSnPew2e36YfN7+nUpb+UkBRnVhYVG5b2uOm09c41Tm+qw3vre7j+U/euOC5dP6mY+EgNeLdsRs1RWOS11HXWAAAAUDyR6AIAAAAA5InK3vXlf/4PBYeezXD6wriEGF2+cUplSlaSna29pPSTU3ckG5PMfo+Nj9Jr37RXXEK0+rV7RVW8G8jZ0V02Bhst2z5DR85uS3MMGxvbDI9vkik7TZNB2Y8x9byGjM9rm0FMJlP24smtjK7F3ec9fXm/3pjXVT6lqmtYzw/k7VlFjvbOMsigaUsGymhKOyViZm1VOtc4O+03yaQHXEtr4lNLMzxyZe/6mZwXAAAAxQGJLgAAAABAnmjf4An5n/9D6/fN1/CeH6RbZ/PB75WUnKhHmjyTus3dxVOSFBFzK039kFsXUhNiknQ4YKtuRlzR2AEL1b35ULO6iza+eV/xZ5ZwuxNjZMwteXtWTt2ekBinWxFXVb5UxuuS5Scfr5q6fP2UEpLi5WDnmCfH3HZ4qYzGZE0bvl7l7hp5FpsQne5orvzi41VD+26cUZ1KrXK1lhsAAACKB9boAgAAAADkie4thqlC6Zr65Y9PtP/UhjTlAUGHtHD9RHl6lNNjbV5K3V7BK2XqucMBW8zqbzu8TDcjrphtSx2RdM/IpwOnN6W7dlROODukJFPSS7j5/DM93qF7Yvxl56fpjnAqKI80eVqRsWFauuX9NGW5HR2WOjrrnv2XbZ1eoG3t0nSQjCajFqyfmG55WOS1AosFAAAAhRcjugAAAAAAecLJwUXvDflVk+Z315sLe6ltg8fVqFoH2drY6dTlfdp6cLHcnEvqvSG/qqT7v+su+ZappSY1Omvt3jkymUyqVr6xzl05ot3HVqq8V3UlJyem1q1fpa083b0157exCgkLVOkSFXTuyhFtObRYVbwb6EKIf67jr+XbPGUKxK3TFBUbJicHV3l7VlGdii3VpEZn+Zaupe82TVFEzE15e1bR8Qu7dPLS3lyvNZYX+rYdo70n1mjJ1vd1+vJ+Na3ZVQ72TgoMOa6gG6c1c8SWrA9yj4fq99WKnZ9q8oKe6tnyBdnZOejQmc26cPXvAm1r+4ZPqFvzoVq9+0sFBB1Sq7p+KuHqpRu3g3Ti4h5duXlWiyeeL7B4AAAAUDgxogsAAAAAkGd8y9TS7NeO6tku7yg4NEDz1o7XZ7+M0IZ9C+TjVUMLx59SLd9mafabMHCxHmrQT9sOL9Gc38bqWlig/jtyu7w8fMzquTk/oBnDN6q2b0ut3v2F5vw2VhevndC059apuk+T+4q9TMmKGjtgoeITYzVrxYuavuRJrfnzG0kpa0q9N/RXNaraQat3f6EF695QYnKCPn7xdzk5uN7Xee+HvZ2DPnh+k4Z0f183wi9r4YZJWrh+kk5f3qe2Dfrl6pj1qzykKYN+kZODq77b+JYWb3pHjvbOFmnr6wMWavzA72VjY6Mft83Ql6te1uaD38nZ0U3Deswo0FgAAABQOBlM+b3SLQAAAAAUEq8ukUySDJI+fdrS0VhGcoK0fVYBnzM5SVMX99fu46s0svcnerz9qwUbAHCXjqMlWwdLR2E53AcBWOJZAChMivuzQGESHR0tN7eU6cOjoqLk6pq7l6oY0QUAAAAAyFe2tnaa/MxPalG7p2aveS11lBQAAAAA3C/W6AIAAAAA5Dt7OwdNG7bW0mFYhcSkBEXG3MqyXgm30rK1sS2AiAAAAIDCi0QXAAAAAACFyImLf+r12R2zrLd44gV5e1bO/4AAAACAQoxElxUzmUxSYrKlw0BxYG8rg8GQ76cxmSRjYr6fBsh3NvZSAfyVAQAARVTVco304fObs6zn6e5dANEAAAAAhRuJLmuWmKykycstHQWKAbtp/SWH/L9dGBNZDBVFA4uaAgCA++HuUlJNana2dBgAAACAVbCxdAAAAAAAAAAAAABAbpDoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokulCkfH/sdzl89JS+P/Z7uuWB4Tfk8NFTGrZ+dgFHBgAAAAAAAAAA8hqJLgAAAAAAAAAAAFglEl0AAAAAAAAAAACwSiS6AAAAAAAAAAAAYJVIdAEAAAAAAAAAAMAqkegCAOSJ7ze9oy7jDAq5FWjpUPJNl3EGzfxxiKXDAAAAAAAAAPAPO0sHUBBCQ0M1c+ZMrVixQkFBQSpdurT69eun6dOna/To0Vq4cKG++OILjRo1ytKhAsim6LgIrdz5uXYfX6ng0AAZjckqW7KyWtXx0xMdXldJtzKWDjFdZ4OP6M/jq9S12RB5e1a2dDgAABQbJpN0I1Iy3fndotEUbsu2zVBA8CEFBB1UyK0LKluykn6YFGjpsADcJ6NRus59EEA28CwAwNoU+UTXkSNH1KNHD4WEhMjV1VV169bVlStXNGvWLJ07d063bt2SJDVu3NiygaJAGe7688ubF2rt+UMKj4+Vu4OTHq/ZUjMefkoOtkX+r4fVCrpxRhPnddO12xfVtn4/dW8+THa29jp5aa9W7PpMGw8s0tTnflOdii0tHWoa564c0eLN76pRtQ4kugAAKACxCdK+89LuAOl6hHnZ//ZJD9WUyj1gkdAKrYXrJ8ndxVM1fJooOva2pcMBcJ+i4qQ9Z6U/z0ph0eZlqw9JD9WQvNwtExuAwolnAQDWpkj35IeGhqp3794KCQnR2LFj9fbbb8vdPeXpbebMmZowYYLs7OxkMBjUsGFDC0eLvOBk5yBJiklMSLc8OjFekuT8Tz1JevHBrvrg4afk6uCk0JgIPblmlj7Yu0pTHnoi/wNGjsUlxOitRb0VGhGsqUPXqGWdXqllvVq9oN6t/6MJcztryqJHNXesf6Ed2QUAAPLftXBpznbpVnT65bsCpN1npcebSW1rFmxshdn3b5xTuVJVJUnPf1RfsQlRFo4IQG5dDJXm7ZCi4tMv335S2nlaeqaN1LhSgYYGoBDjWQCAtSnSia7Ro0crKChIo0aN0kcffWRWNn78eC1dulRHjx5VlSpV5OHhYaEokZeqlCgtSTp1Kzjd8lM3U7ZX/qeeJNX1qpD6Z5MkG4NBZ2+H5F+QuC8b9i1Q0I0zGvDwOLMk1x21fJvpuR7T9cXKl7R8x3/1gt9/JUkb93+rj34eqo9Gblejah3M9hn7TQddCws0G4Z/4PQmbdi/QKcv79etiKuyt3NULd8WeuqRyWpU7eF09//spT8157exOnB6gxKT4lW/SjuN6vOFKpRO6Tn7ftM7Wrz5XUnS67M7pu7fpelgjR/4bWr54okX0oz2emZ6ZZUtWVkfv7jj3/3GGdSl6WB1aTZIi9ZP1vmrR+Xu4qnHHnpZAztOUGRMmOb+9rr2nlij2IQoNa7eSa88PldeJcrn9LIrMSlBK3Z+pm2Hlyo49Ixsbe3l41VDXZsNUZ+HRt1TN14L1k/SloPfKzzqhnzL1NZzPWaoZZ2eZvV+/fNr7T62ShevHVd49A15uJTSg9Uf0ZDu76dp/522+rUaofnr31DA5QOyt3fSQ/X76j+PfiZnR7fUujN/HKLNB7/Tqvdua/66N7TL/xdFx0eohk9TjXz0kzQj/Uwmk37bM1vr983XpesnZTDYqJZvcz3TeYoaV+8oAIB1CouWvtoqRcRmXs9kkv63X7KzlVpVK5jYCrs7HVsArNvV29I326S4xMzrJRml73ZJ9rZSvQqZ1wVQPPAsAMDa2Fg6gPxy8uRJ/fTTT/Ly8tKMGTPSrdO0aVNJUqNGjVK3/e9//9Pjjz+uSpUqycXFRbVr19bkyZMVFcWbC9bgwbJV5OteSj+f2qMrUWFmZQnJSfrm8CYZZJBf9aZmZTP/+lUlPx8qn69H6u8bFzW6SY+CDBs58If//yRJPVu9kGGdrs2GyM7WXjv9f8n1eTYd+FaRMbfUpekgvdTnCz3e7lVdvn5S4+c+Iv/zO9PUj0uI1thv2svWYKvnuk/XY21G6e9zOzTl28eUbEyWJLWt30+9WqbE/WSnSZowcLEmDFwsv1Yjch3nuSuHNXVxfzWq1kEj/D6Wj1cNLVj3hlbs/Fzj5z6iyNgwPdv1Hfm1Gqn9pzdo5o+DcnyOxKQETZzfTfPXTVBJ97Ia3PU9De0+TTV9mmq3/4o09Wf+NFjHLuxU/4df1+BuU3U7+obe+a6PQm4FmtVb/vtHKuHqpT5tR+vlvl+pfaMB2n1spcZ81UYR0TfTaesRvbnIT7UqNNeI3p+oac2u2rBvgWaveS3duN+Y302h4UF6ussUPdlxogKvHdObC3opJi7SrN6Hy57Vl6tGqbxXdQ3vNVODur6r6LhwTZjXRX8e/zXH1wsAUDisOpR1kutu/9svRWcw4gEArNHyfVknue4wSVq2V0pKzteQAAAA8kWRHdG1bNkyGY1GPf3003Jzc0u3jrOzsyTzRNdHH32kihUravr06apQoYKOHDmid999V7///rv++OMP2dgU2dxgkWBnY6svOj+n/qs/UdPvJmhI/Y6q9kAZXYsJ1/JTe3XiZpAmtHxMtTzNR7SMb/moxrd8VCdvBmvZyd3ydnvAMg1AlgJDjsnF0V0+XtUzrOPk4CLf0rV1IcRfsfFRZqN9suvV/vPk7OBqts2v9UgN/6ielm2foQZV25mVhUeHqv/D4/R/HcenbivhVlrz1o7XoYAtal6rm6qWb6g6lVpr7V9z1bRmlzQjy3LjQoi/Ph+1J3WUUvcWw/TM9EqaveZVPdZmlF7qM8us/i87P9Xl66flW6ZWts+xYudnOnpuhwZ2mqhhPaablRmNxjT1S7h6aerQNTIYUlbDa1y9o0bNaqG1e+doWM9/XzyYO9Y/zTVuXfdRTZjbWev3LTC7lilt/dusrX6tRygmLkIb9y/SyN6fpPmca/g00eh+X6f+XrFsXb3/wwBtO7xUfq1Tkou7/Fdq6+EleuXxOep1V/K0X9sxevnLVvpm9Ri1rts7tS0AAOsQHiP5X87ZPknJKWt5dayTPzEBQEG6Eiadv5GzfaLipaOXpKZV8icmAACA/FJkszbbtm2TJHXsmPG0U0FBQZLME11r1qzRzz//rKeffloPP/ywxowZoy+//FK7d+/Wrl278jdo5Ime1R7U70++o4d96+qH439o9NZv9dmBdSrt4qElfqM1td3/ZbhvnVI+ali6ooau+6YAI0ZOxMRFyNWpRJb1XJxSpiONiY/Momb67k7AxMZHKSL6pmxsbFW7YkuduvRXmvo2Bhv1bTvabFvj6p0kScGhAbmKITvqVGxtNhWfvZ2Davm2kMlkUp974qlfpV2u4tl2eIncnUvq2c5T0pSll/zv23aMWWKolm9zOTu6pTnvnWtsNBoVHRuu8OhQVSvfSK5OJdK9xve2VUq5xsnGJIWEBaap36/dq2a/P5jO57H10A9ycXRXm/p9FB4dmvoTFXdbrev0VkhYYL5+fgCA/LH/gmQ05Xy/PWfzPhYAsIS95wp2PwAAAEsqsiO6Ll68KEmqVCn91VSTkpK0e/duSeaJrtKlS6ep26xZM0lScHD66z5lpVmzZgoJyfs1n5xt7XViwPSsKxZDzcpV04+PvpKrfRONyQoIu5q3AVm5mjVqKDY5m3Ne3AcHO2fNHZV5UsHFyUPR8RFZHismLkI2BhuVcPXKVSxXQs9p0YbJOnBmo6Jib5uVpTe6p5RHeTnYO5lt83ApJUmKTGcavryS3rzZbs4lJUnenuavYrq7pGyPiMlZPMGhAapWvnGa9mUYk2famDxcSqU57+Gz2/TD5vd06tJfSkiKMyuLijWfelRKv613rnF6Ux3eW9/D9Z+6d8Vx6fpJxcRHasC7ZTNqjsIir6Wus5ZdNWrWUEJSDubLAgDkqSb9PlDVls/keL+rN+NUoULGo8aLiuw8cwFFWXF4VmszeKHK1+2a4/2OnLykCkPa5ENEAAoTngVQ3BWHZwFrcfdsUW3bttXhw4dzdZwim+iKjo6WJMXGpv8/7E8//aTQ0FC5u7urSpXMx+Vv375dklSnTu7mMQkJCcl1kiwzLvaOeX7M4iY8PkarA/br0erNVMLRRf6hlzVjzyp1qdzQ0qEVKleuXlVMYv4vWuFk75Jlncre9eV//g8Fh57NcPrCuIQYXb5xSmVKVpKdrb2k9JNTdyQbk8x+j42P0mvftFdcQrT6tXtFVbwbyNnRXTYGGy3bPkNHzm5LcwwbG9sMj29S9l4pNyj7Maae15DxeW0ziMlkysUr7jmQ0bW4+7ynL+/XG/O6yqdUdQ3r+YG8PavI0d5ZBhk0bclAGU1pp0TMrK1K5xpnp/0mmfSAa2lNfGpphkeu7F0/k/Om7+qVK4pLjMnxfgCAvFE7Ni7rSukx2ObLc3thk51nLqAoKw7PavEJuXtR0WjM/Uu+AKwHzwIo7orDs4A1unbtWq73LbKJLm9vb4WFhenQoUNq3bq1WdnVq1c1btw4SVLDhg0z7QAPDg7WW2+9pe7du6tx48a5jiU/OP/TgY/cM0haemKXxu34QQnJSSrj4qE+NVpoSpvHLR1aoVK+XLkCG9GVlfYNnpD/+T+0ft98De/5Qbp1Nh/8XknJiXqkyb9vcru7eEqSImJupakfcutCakJMkg4HbNXNiCsaO2ChujcfalZ30cY3s9WWjGR2v7kTY2TMLXl7Vk7dnpAYp1sRV1W+lGXeMPfxqqnL108pISleDnZ5k2DfdnipjMZkTRu+XuXuGnkWmxCd7miu/OLjVUP7bpxRnUqtcrWWW0bKlS/Pm0EAYEG2yVG52i8+6rp8fHzyOJrCJzvPXEBRViye1RKyngUjPYkxN4vFfRAo7ngWQHFXLJ4FrITRaNTVqymzq5Utm/GMS1kpsomuzp076+TJk/rwww/VpUsX1ayZMu3U/v379eyzzyo0NFSSMk1eRUVF6bHHHpODg4MWLlyY61gOHDiQ630zY0pIUtLk5fly7OLCw9FFGwZMtnQYhd6ZgAAZHPL/dpGcIG2flXmd7i2GafWfX+qXPz5Ro6od1Lx2d7PygKBDWrh+ojw9yumxNi+lbq/glXIPOBywRe0a9Evdvu3wMt2MuKKyJf+d5jR1RNI9I58OnN6U7tpROeHskJJMSS/h5vPP9HiHAraoRoUmqdt/2flpuiOcCsojTZ7WvLXjtXTL+xrSfapZmclkyjR5l5HU0Vn3XONlW6cXaFu7NB2kvSfWaMH6iRrV54s05WGR11TSPef/yAacCZCtQ15ECADIjWvh0ozfcr7fow/5aO4/6/gWZdl55gKKsuLwrBZwTfpqS873G97vQX0/sejfB4HijmcBFHfF4VnAWkRHR8vNLaW/dNeuXbk+TpFNdI0fP15Lly7V5cuXVa9ePdWuXVtxcXE6e/asevToocqVK2vjxo1m63PdLTY2Vr1799aFCxe0c+dOlStXroBbACA9Tg4uem/Ir5o0v7veXNhLbRs8rkbVOsjWxk6nLu/T1oOL5eZcUu8N+dUsQeFbppaa1OistXvnyGQyqVr5xjp35Yh2H1up8l7VlXzXiLX6VdrK091bc34bq5CwQJUuUUHnrhzRlkOLVcW7gS6E+Oc6/lq+zVOmQNw6TVGxYXJycJW3ZxXVqdhSTWp0lm/pWvpu0xRFxNyUt2cVHb+wSycv7c31WmN5oW/bMdp7Yo2WbH1fpy/vV9OaXeVg76TAkOMKunFaM0fk/Bv0Q/X7asXOTzV5QU/1bPmC7OwcdOjMZl24+neBtrV9wyfUrflQrd79pQKCDqlVXT+VcPXSjdtBOnFxj67cPKvFE88XWDwAgLxRtoRUo2xKR292GQxSm6K/PFe2bD64WNfDUtY8vh19Q0nJCVqy5X1JUpmSldSl6bOWDA9ANlQvI3mXkELCs7+Pg53UPPOVHQAUEzwLALA2RTbRVaFCBe3cuVPjxo3T77//rsDAQNWtW1dz5szR888/r2rVqklSuomuxMREPfHEEzpw4IC2bt2qunXrFnT4ADLhW6aWZr92VCt3fq5dx1Zo36l1iktIWZevctl6+vSlXXJzfiDNfhMGLtaXq1/WtsNLtOXQYjWo0k7/Hblds1a8qGthgan13Jwf0IzhGzVv7Xit3v2Fko1JquHTVNOeW6f1+xbcV6KrTMmKGjtgoX7a/qFmrXhRScmJ6tJ0sOpUbClbG1u9N/RXfbVqtFbv/kJ2tg5qWrOrPn7xd73y1UO5Puf9srdz0AfPb9LyPz7W9sNLtXDDJDnYOcnHq4a63TO1Y3bVr/KQpgz6RUu2TNV3G9+Sg72zmtTorI9f/F2vfdM+j1uQudcHLFSjah217q+5+nHbDCUmJ8jT3VvVfZpoWI8ZBRoLACDvPPqgNGuzlJicvfqd6kieeTeLrVXbsG+B/j7/u9m2bze+JUlqWPVhOrcAK2AwSH2bSnO2S8ZsLtHbq5HkzNvtAMSzAADrYzCZTNl85Ck6oqKi5OHhIYPBoMjISLm4/LsAo9Fo1MCBA/Xrr79q3bp16tSpkwUjzRxTF6Kg2E3rX2imLsxw3+QkTV3cX7uPr9LI3p/o8fav5m1wQA50HC2GwANAIXD6qrTwDyk+KfN6bWtI/ZpLNjmfjdcqMV0Rirvi9Kx2KFBaskdKzmJ28B4NpW4NCiQkAIUAzwIo7orTs0Bhd/fUhVFRUXJ1dc3VcYrsiK7MHD9+XCaTSTVr1jRLcknSSy+9pOXLl+uNN96Qi4uL9u7dm1pWrVo1lS5duqDDBZANtrZ2mvzMT3rnu76aveY1Odg5qXebFy0dFgAAsKBa5aTXuks7TkkHL0gJ94zuqlpaal9LalQxZfQDABQ1TSpLpT2kHSelI5fSJrxql5Meri3VKW+R8AAAAPJEsUx0+funTDuW3rSF69evlyR98MEH+uCDD8zKFi1apCFDhuR7fAByx97OQdOGrbV0GFYhMSlBkTG3sqxXwq20bG1sCyAiAADyR9kS0v+1lHo/KAWESDEJkr2t5FNSKveApaMDgPzn6yk9+5DUp2nKfTA+SXKwlSp6SaXdLR0dAADA/SPRdY/AwMACjib/vLr1O/127qAuRoRq36Dpalymcrr1Nl44qrd3/ayE5CS52Dvqqy7D1KhMJUlSfFKixu/4QZsD/5ajnYMalq6o73q9lGcxBoRd1bD1sxUaG6kSDi6a32Ok6nlVyFG9zNqZWVlcUoKe/u0LnbwZLGc7B5Vx8dAXnZ9T9ZLeBdq2rOpmVpbR55NZ2/K73bAOJy7+qddnd8yy3uKJF+TtWTn/AwIAIJ+5OKSM3AKA4srdKWWEFwAAQFFDoqsI61ezhca28FPHZe9mWCcsLkqD136lrQOnqJ5XBe0KOqXBa7/SkaEzJUmTd/4og8Gg48M+kcFgUEj07TyN8aVNCzS8YScNqv+wfjn9l4avn609z76fo3qZtTOrazC8YSd1r9JYBoNBXx/aqJEb52nLwLcKtG1Z1c2sLLPPJ7O25We7YR2qlmukD5/fnGU9T3cSoAAAAAAAAAAKLxtLB2AJ27Ztk8lkUq9evSwdSr5q51tHFdxLZVrn/O3r8nR2Sx0h1LZCbV2OvKnD1y4oOiFOi/x36L22A2T4Z9ECb9cH8iy+69HhOnjtgp6q21ZSSlIqKPKmzoaF5KheZu3MrMzJzkE9qj6Y2raW5WvoYsSNAm1bVnUzK8vs88msbfnZblgPd5eSalKzc5Y/DvZOlg4VAAAAAAAAADJULEd04V/VS3rrVmyU9gSfUWufmlpz9qAiE2IVGH5Dtja28nRy1Qd/rda2i8fkbOegt9o8rk6V6ufJuYMib8rb9QHZ/bP+j8FgkK9HKV2OvGk2jV52692vLw5tUO/qTfPkWDmJObO6JRycMyyLSUrI9ueTWdvyst0AAAAAAAAAABQkEl3FXAlHF/346Bi9ufNHRSXGqVW5GqpTykd2NrZKNibrYkSo6pTy0fT2T+rwtUD1/N90HRnyX5V1LZHpcdstmaKzt9OOXpKkfc/OkK9H5iPNCtoHe1fpXFiIvh4wOVv1s2pfQcju55NZ23LabgAAAAAAAAAAChMSXVCHivXUoWI9SVJ8UqJ8v3lRdUr56AFHF9kYDHqqTsq0eQ+WrazKHmV0LPSSyro2yPSYO59+L8vzVnAvpZDo20oyJsvOxlYmk0mXI27K956pBrNbL7c+2f+bVgXs14b+k+Ri75itfbJqn6OtXbZjzqx9Hg7OGZZl5/PJrG25aTcAAAAAAAAAAIVJsVyjC+auRoWl/nna3pXqULGeqpf0lpeLhzpVrK9NgUclSRduX1dgxHXV9vSRJA1d97VWBezP9XnLuJbQg2Uqa+mJXZKkFWf2ycfdM83UftmtlxufHVirn079qfX9J+oBJ1ezsvtpX05izqxuZmVZfT6ZtS2zMgAAAAAAAAAArIXBZDKZLB0EcseUkKSkycszLP/Ppvlaf/6IQqJvq5Szm9wdnHVy+KeSpBEb58qvWlP1rt5UIzfO067gU0o2GtWyfA191mlwavLj/O1rGrFxnkJjI2VjMGhy637qV7OFJKnhwnFa1PNFNfWumus2nL51RcPXz9bNuCh5ODhrXvcRalC6YpoYM6uXWTszKwuKvKmqc15W1RJl5ObgLCllJNbuZ6bmSfuy27as6mZWltHnk1nbsmp3euym9ZfBIf8HgCYnSNtn5ftpgHzXcbRk62DpKAAASB/PXCjueFYDUNzxLIDijmeBwiM6Olpubm6SpKioKLm65m5QBokuK5ZVois/3YiJ0KC1X2p9/0kWOX9+K+rtyykSXUDO8MAEACjMeOZCccezGoDijmcBFHc8CxQeeZXoYupC5EppF48inQQq6u0DAAAAAAAAAKAoINEFAAAAAAAAAAAAq0SiCwAAAAAAAAAAAFaJRBcAAAAAAAAAAACsEokuAAAAAAAAAAAAWCWDyWQyWToI5I7JZJISky0dBooDe1sZDIZ8P43JJBkT8/00QL6zsZcK4K8MAAC5wjMXijue1QAUdzwLoLjjWaDwiI6OlpubmyQpKipKrq6uuTqOXV4GhYJlMBgkBz5CFB0Gg2TrYOkoAAAAijaeuQAAKN54FgBQ1DB1IQAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoKgQWL16spk2bqmTJknJ2dladOnX0ySefyGQyWTo0AAAAAAAAAACAQsvO0gFAKlOmjN566y3VqlVLjo6O2rlzp/7zn//I1tZWY8aMsXR4AAAAAAAAAAAAhZLBxLChQqlv376SpJUrV1o4EgAAAAAAAAAAgLwVHR0tNzc3SVJUVJRcXV1zdRymLixkTCaT9u3bp927d6tjx46WDgcAAAAAAAAAAKDQYurCQiI8PFw+Pj5KSEiQ0WjU22+/rdGjR1s6LAAAAAAAAAAAgEKLRFch4e7uriNHjigmJkZ//vmnJk6cqPLly2vYsGGWDg0AAAAAAAAAAKBQYo2uQmrGjBn6/PPPFRISYulQAAAAAAAAAAAA8hRrdBVxRqNRcXFxlg4DAAAAAAAAAACg0GLqwkLg7bffVrt27VS1alUlJibqjz/+0IcffqihQ4daOjQAAAAAAAAAAIBCi0RXIRAREaGRI0cqODhYTk5Oqlq1qmbMmKGRI0daOjQAAAAAAAAAAIBCizW6AAAAAAAAAAAAUKBYo6uYCr0VrqSkZEuHAQAAAAAAAAAAYHFMXWhFjEajvvtlgxISkzSoXzf5eHtZOiQAAAAAAAAAAACLYUTXPZKTk7V48WJ17dpVpUuXlqOjoypWrKju3btr/vz5Sk623Giqv0+d141b4UpMTFKpkh4WiwMAAAAAAAAAAKAwYI2uu0RERKhPnz7avn27JKl8+fLy8fHRlStXdOXKFZlMJoWFhemBBx4o8NiMRqM+XbBcN26Fq1v75urY+sECjwEAAAAAAAAAACAv5NUaXUxdeJdhw4Zp+/btqlChgr7//nt17NgxtezatWtasGCB7O3tLRLbndFcLk6Oat2knkViAAAAAAAAAAAAKEwY0fWPgwcPqlmzZrKzs9Phw4dVv379PDv2F9+tUGRUbK73N5lMio6JldFkkqODvRwdHPIsNgAAAAAAAAAAgIKWEB+nd8cOlyT9d84Svf7CU7k6DiO6/rFq1SpJUq9evfI0ySVJkVGxioiKzpNjxSckKj4hMU+OBQAAAAAAAAAAYAkJCfGpf466j8FCJLr+ceLECUlS69at8/zY7m7Oud6X0VwAAAAAAAAAAKCoSYi3Tf2z233kUUh0/SMiIkKSVKJEiTw/9suD++V63yMnzurHNdvk4uSo8SOflJMjiS4AAAAAAAAAAGDdoqOjU6cufPHpx3J9HBJd//Dw8JAkhYeHWziSfxmNRm3dfVCS1K5FQ5JcAAAAAAAAAACgSHBxcVFUVFTqn3OLRNc/6tWrpxUrVmjPnj15fuwvvluhyFzML5mYmKTY+HgZJP158Lj2HDqR57EBAAAAAAAAAABYkrubc65nxyPR9Y++fftq6tSpWrdunU6cOKG6devm2bEjo2IVERWd6/1NkiKjY/IsHgAAAAAAAAAAgKKARNc/HnzwQQ0YMEA///yzevTooe+//14PP/xwavm1a9e0cOFCjR49Wq6urjk6tnsuFlG7ezSXm6uLDAZDjo8BAAAAAAAAAABQ2OUmj3KHwWQymfIwFqsWERGhxx57TDt27JAk+fj4qHz58rp69aqCg4NlMpkUFhamBx54IF/jMBqN+nTBct24Fa5u7ZurY+sH8/V8AAAAAAAAAAAA1sjG0gEUJh4eHtqyZYsWLFigDh06KCYmRkePHpWNjY26deumBQsWyN3dPd/j+PvUed24FS4XJ0e1blIv388HAAAAAAAAAABgjRjRVQjtOXRcG37fpw6tGjOaCwAAAAAAAAAAIAMkugqp6Ng42dnaytHB3tKhAAAAAAAAAAAAFEokugAAAAAAAAAAAGCVWKMLAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAAAAAAAAAAAAVolEFwAAAAAAAAAAAKwSiS4AAAAAAAAAAABYJRJdAAAAAAAAAAAAsEokugAAAAAAAAAAAGCVSHQBAAAAAAAAAADAKpHoAgAAAAAAAAAAgFUi0QUAAAAAAAAAAACrRKILAPD/7d17fM71/8fx57XDZWfMMGbM+ZBT5hyKkGOk+OokouibqGRC6aBQ+UryK2eVIinJ+dQUKadQk9PIZGYYY9u1zU7X74/Vctl5tl0+87jfbt1u7fN+fT6f1/uzL3/0/L7fbwAAAAAAAAAwJIIuAAAAAAAAAAAAGBJBFwAAAAAAAAAAAAyJoAsAAAAAAAAAAACGRNAFAAAAAAAAAAAAQyLoAgAAAAAAAAAAgCERdAEAAAAAAAAAAMCQCLoAAAAAAAAAAABgSARdAAAAAAAAAAAAMCSCLgAAAAAAAAAAABgSQRcAAAAAAAAAAAAMiaALAAAAAAAAAAAAhkTQBQAAAAAAAAAAAEMi6AIAAAAAAAAAAIAhEXQBAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImgCwAAAAAAAAAAAIZE0AUAAAAAAAAAAABDIugCAAAAAAAAAACAIRF0AQAAAAAAAAAAwJAIugAAAAAAAAAAAGBITvZuAIXLarVKyan2bgNG5uwok8lkl1dbrVJasl1eDRQqB2fJTn+MAAAAAAAAgNsKQVdJk5yqlIkr7N0FDMzp7f6S2T5/NaQlS9tm2eXVQKHqOEpyNNu7CwAAAAAAAKDkY+tCAAAAAAAAAAAAGBJBFwAAAAAAAAAAAAyJoAsAAAAAAAAAAACGRNAFAAAAAAAAAAAAQyLoAgAAAAAAAAAAgCERdAEAAAAAAAAAAMCQCLoAAAAAAAAAAABgSARdKFE+O/SjzNMf0WeHfsxyPOzqRZmnP6KhG+YUc2cAAAAAAAAAAKCwEXQBAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADOm2CLqioqIUFBSkWrVqycXFRf7+/ho9erQsFouGDh0qk8mk2bNn27tNADC0zza/ri5jTYq8HGbvVopMl7EmvfvlYHu3AQAAAAAAAOBvTvZuoKgdPHhQ3bt3V2RkpNzd3dWgQQNFRERo1qxZOnnypC5fvixJatq0qX0bRbEyXffvz21ZpHV/7tfVawnyNLvowTqtNPXuR2R2LPF/PAzNkhijb3d8oJ1/fKuzUaFKS0tVxbIBal2/lx665yWV9ahg7xazdOLsQf38xyp1bT5Yvt4B9m4HAAAAAAAAAAytRK/oioqKUu/evRUZGakxY8bo3Llz2r9/vyIjI/XOO+9o3bp12rt3r0wmkxo3bmzvdlEIXJzMkqT45KQsxy3J1yRJrn/XSdIzd3ZVyJDpujRqofYNmqrfL/6labtWFXmvKLjwi8c1YkYTfbblNVXyrqGh3afpmftnqn611lr500w9Nf0OHflrt73bzNLJiINasuUNnY8Os3crAAAAAAAAAGB4JTroGjVqlMLDwzVy5EhNnz5dnp6eGWNBQUFq0qSJUlJSFBAQIC8vLzt2isJSvXR5SdLRy2ezHD96Kf16wN91ktTAp4rczS6SJKskB5NJJ65EFm2jKLDEpHi9uri3omLOavKQNZo06Gv1uetZ9Wz9tF4asEgzn/1ZKanJmrT4fkXHXbB3uwAAAAAAAACAIlRig64jR45o+fLl8vHx0dSpU7OsCQwMlCQ1adLE5vqpU6d0//33y9PTU2XLltWgQYN06dKlIu8ZN+/OitXl71lOXx39RRFx0TZjSakp+vjAZplkUq9agTZj7+5erbIfDJHfRyP0+8XTGtWse3G2jXzYuGehwi8eV792z6tV/Z6Zxuv6N9eT3afoStwFrfjhvYzrm/Z+oi5jTfrt5A+Z7hnz8T16bEqAzbV9xzbrrc//o8en1lDP8a7q+2oZjZvXVb+d/DHb+6OuRujtLx7WA5PKqtcEN708/z6FXzyeUffZ5tc1/ashkqSX5nRUl7EmmzOfcjrj6rEpARrz8T021/6598CJYI36sI16TXDTw29V0Zfb3pEkxcZH639fDVX/1yuo1wQ3vbKol6KuRmT1WXOVnJKk5dve1fAZTdVrgpv6vFpa//2guVbtzHy+YXLKNS3cMEEPv1VFPV4upeEzmmj3kfWZ6lb//JHGzeuqgZP91P1ls/7zZiVNW/pYlvP/Z66Hw37Rix/frd4T3NXvtXL634phSrgWZ1P77peD1WWsSZaEq/rgm2fU//UK6jHeRaNn35XlSj+r1ao1P3+s/84MVK8Jbuo90UMvzemogye2FehbAQAAAAAAACg+JfYQomXLliktLU2PPvqoPDw8sqxxdXWVZBt0xcbGqmPHjvL29tayZcuUkJCgoKAg9erVSzt37pSDQ4nNBksEJwdHfdj5SfX/boYCPx2nwQ07qmaZCjoff1Urju7S4UvhGteqj+p6V7a5L6jV/Qpqdb+OXDqrZUd2ytejjH0mgFxtD/laktSj9dPZ1nRtPlgfr35eO0K+0dO93su2Lieb932i2PjL6hI4SD6lq+jS1bPasGeBgubdq+nDt6lRjfY29YlJFo35uIPqV22tJ7tNUeTlU/r2pw806ZM+mj/mkBwdHNWuYT9djjmndbvn6eFOE1S1Qn1JUuVyNQvUoySdjDigXUvWqGerp9UlcJB+/P0rLVz/ssxOLtry66eqWDZAj3d9XRFRJ/Ttzll698tBenf41ny9IzklSeMX3KffTv6gwDpd1bnZY3J2dlHYuRDtDFmpvneNtKl/d/kTcnJ0Vv+7X1JySpJW/jRTr3/aV4uDjtucS7bix+mqX7W1+rYbJS83b52KPKSNuxfowMlgzX8xRF7u5W6Y60G9sriX7ms+RJ2aPqLf/vxBG/cslIPJQS88NC9T3y8vuE9l3Mvr0S6TFGu5pK93zNArC3tqyfhTcnP5d4XvO8se17aDy9S+8UPq2mKIklOuKfjAFxo3v4teG7RSbe+4P1/fCwAAAAAAAEDxKbFBV3BwsCSpY8eO2daEh4dLsg265s2bp7Nnz2r79u2qWrWqJKlKlSpq27atVq9erb59++a5B6vVqvj4eEmSm5ubTCZTfqeBAuhR8079+PDrmr53jT7/Y7suJcbJ3bmUmlYI0BdtRql/vdbZ3lu/nJ8al6+qIes/1pb/vFKMXSOvwiIPya2Up/x8amVb42J2k3/5ejoVGaKEa3FyLZV12J2TF/rPl6vZ3eZarzYjNGz6HVq2bWqmoOuqJUr97x6r/3QMyrhW2qO85q8L0v7QrWpR9z7VqNxY9au10brd8xRYp4ua1Lwn333d6FRkiD4Y+YvqV20lSerWcqgem1JNc9a8oD5tR+rZvrNs6r/Z8b7OXDgm/wp18/yOlTtm6reTP2hgp/Ea2n2KzVhaWlqm+tLuPpo8ZE3G33lNa3XUyFkttW7XXA3t8e8K23ljQjJ94zYN7te4eZ21Yc9Cm2+ZPtffbebaq81wxSfGaNPexRrRe0am33Ntv2Ya1e+jjJ+rVmygtz4foOADS9WrzXBJ0k8h3+r7A1/o+Qfnqud14Wm/dqP13OzW+vi70WrToDd/fwMAAAAAAAC3qBIbdJ0+fVqSVK1atSzHU1JStHPnTkm2QdfatWvVrl27jJBLktq0aaMaNWpozZo1+Qq64uPjM1aTVapUqVhWg7k6OuvwgCm5F5ZwzSvV1Jf3P1+ge5PTUhUafa5wGzKQOrVrKyE12S7vNju5at7I0Bxr4hNj5O3pm+uz3FzSz92LvxZboKDr+gAm4VqcklOuycHBUfWqttKRv3ZlqncwOeiBdqNsrjWt1UmSdDYqVC3q3pfvHvKiftU2GcGPJDk7mVXXv6V+ObxafW/op2H19vpmx/s6GxWar6Ar+MAX8nQtq8c7T8o0ltXfaw+0G20TDNX1byHXUh46G2X7u/3nG6elpSnhWqxS0pJVs3ITubuU1tEsthi8ca5S+jfec3S9IqPDVN23oc1Yv/Yv2Px853W/j398v/9zuZXyVNuGfXXVEmVT36Z+b3225XWdjQpVlfJ1MvWTk9p1aispJSFf9wAAAAAAAAC3K19fX+3bt69A95bYoMtisUiSEhKy/g+Ny5cvV1RUlDw9PVW9evWM64cPH1b//v0z1d9xxx06fPhwgfs5d654ghM351LF8p6S4uq1eH0Xulf312qu0qXcFBJ1RlN/WaUuAY3t3ZrdRJw7p/jka3Z5t4uzW641bi5eslyLybUuPjFGDiYHlXb3KVAvEVEntXjjRO07vklxCVdsxrJa3VPOq7LMzi4217zc0rfei7UU3Rl/lcrVyHTNw7WsJMnXu7rNdU+39Osx8fnr52xUqGpWbpppftn25J25Jy+3cpnee+BEsD7f8qaO/rVbSSmJNmNxCbZn7ElZz/WfbxyTxTe+sf6frRCv7+OvC0cUfy1WA96omN10FB17Pt9B17mICCUmx+frHgAAAAAAAAD5V2KDLl9fX0VHR2v//v1q06aNzdi5c+c0duxYSVLjxo1t/qN1dHS0ypQpk+l53t7eOnbsWIH7Kc4VXcg7k6Slh3/S2B8+V1Jqiiq4ealv7Zaa1PZBe7dmN5UrVbLriq7cBPg2VMif23U26kS22xcmJsXrzMWjqlC2mpz+/jOR09ZzqWkpNj8nXIvTix93UGKSRf3aP6/qvo3kWspTDiYHLds2VQdPBGd6hoODY7bPt8qa67wkyaS895jxXlP273XMpierNW/9FFR23+L69x47s1cvz+8qv3K1NLTHNPl6V1cpZ1eZZNLbXwxUmjXzlog5zVVZfOO8zN8qq8q4l9f4R5Zm++SAG1aK5UWlypVZ0QUAAAAAAADkka9v7rt4ZafEBl2dO3fWkSNH9M4776hLly6qUyf9/42/d+9ePf7444qKSt+iqmnTpsXST2hoqNzd3XMvvEnWpBSlTFxR5O8pKbxKuWnjgIn2buOWcjw0VCazff5qSE2Sts3KuaZDo4cU8ud2bdizQMN6TMuyZsuvnyklNVn3Nnss45qnm7ckKSb+cqb6yMunMgIxSToQ+r0uxURozIBF6tZiiE3t4k03d3ZbToHbPz3Gxl+Wr3dAxvWk5ERdjjmnyuWyP5esKPn51NGZC0eVlHJNZqfCWTUafGCp0tJS9fawDap03cqzhCRLlqu5ioqfT23tuXhc9au1LtAWl9kJPR4qR3OhPQ4AAAAAAABANop+iZGdBAUFqVy5cjpz5ozuuOMONWrUSLVr11bLli1Vo0YNdeqUflbL9edzSVLZsmV15cqVTM+7fPmyvL29i6N1ADno1nKoqpSvo2+2z9DeoxszjYeG79eiDePl7VVJfdo+m3G9ik962H0gdKtNffCBZboUE2FzLWNF0g0rn/Yd25zl2VH54WpOD1OyCtz8/t4eb/8NPX6z4/0sVzgVl3ubParYhGgt3fpWprGCrg7LWJ11w/3Lvp9SrHPtEjhIadY0LdwwPsvx6NjzxdYLAAAAAAAAgPwrsSu6qlSpoh07dmjs2LH68ccfFRYWpgYNGmju3Ll66qmnVLNmTUmZg6769etneRbX4cOH1aFDh2LpHUD2XMxuenPwak1Y0E2vLOqpdo0eVJOa98jRwUlHz+zR978ukYdrWb05eLXKev577pJ/hbpqVruz1u2aK6vVqpqVm+pkxEHtPPStKvvUUup12zU2rN5O3p6+mrt2jCKjw1S+dBWdjDiorfuXqLpvI52KDClw/3X9W6Rvgfj924pLiJaL2V2+3tVVv2orNavdWf7l6+rTzZMUE39Jvt7V9cepn3Tkr10FPmusMDzQbrR2HV6jL75/S8fO7FVgna4yO7soLPIPhV88pneHb839ITe4q+EDWrnjfU1c2EM9Wj0tJyez9h/folPnfi/WuXZo/JDuazFE3+2crdDw/WrdoJdKu/vo4pVwHT79iyIundCS8X8WWz8AAAAAAAAA8qfEruiS0kOrtWvXKjY2VrGxsdq9e7eefvppWSwWhYWFycHBQQ0b2p690qtXL/30008KDw/PuLZ7926dPHlSvXv3Lu4pAMiCf4W6mvPib3q8y+s6GxWq+euCNPOb4dq4Z6H8fGprUdBR1fVvnum+cQOX6K5G/RR84AvNXTtG56PD9N6IbfLx8rOp83Ato6nDNqmefyt9t/NDzV07RqfPH9bbT65XLb9mN9V7hbJVNWbAIl1LTtCslc9oyhcPa83PH0tKP1PqzSGr1aTGPfpu54dauP5lJacm6X/P/CgXc9FvfZodZyezpj21WYO7vaWLV89o0cYJWrRhgo6d2aN2jfoV6JkNq9+lSYO+kYvZXZ9uelVLNr+uUs6udpnrSwMWKWjgZ3JwcNCXwVM1e9Vz2vLrp3It5aGh3acWay8AAAAAAAAA8sdkLei+Uwa2e/dutW7dWnXr1tXRo0dtxmJiYtSoUSP5+PjojTfeUGJiooKCglS+fHn98ssvcnDIezZosVjk4ZG+TVlcXBxndMEQnN7uf0uf0ZXtvakpmrykv3b+sUojes/Qgx1eKNzmgHzoOEqc0QUAAAAAAAAUgxK9ois7ISHp247duG2hJHl5eSk4OFiVKlXSwIEDNWzYMLVt21Zr167NV8gFoHg5Ojpp4mPL1bJeD81Z82LGKikAAAAAAAAAQMlVYs/oyklOQZck1axZU2vXri3OlopNaPQ5Dd0wR1EJsSptdtOC7iN0h0+VPNclpiTp0bUf6sils3J1MquCm5c+7PykapX1van7blZen59b3bWUZAX98Lm2hP2uUk5mNS5fVZ/2fDbX9+f1u+ZWm9NY7XmjZHZ0lqtT+jKRoFb3a0C9NpKkF77/VGtP/qrTMVHaM2iKmlYIyPTeT0N+0FOb5mlFnxfUp3aLPH1Xo3F2Muvtoevs3YYhJKckKTb+cq51pT3Ky9HBsRg6AgAAAAAAAID8I+i6zTy7eaGGNe6kQQ3v1jfHdmvYhjn65fG38lU3rHEndaveVCaTSR/t36QRm+Zr68BXb+q+wpDX5+dUN3HHlzKZTPpj6AyZTCZFWq7k6d15/a651eb2nC96P5dliNWvTkuNadlLHZe9keU7w65e1MKQbWpVqVae5oOS7/Dpn/XSnI651i0Zf0q+3gFF3xAAAAAAAAAAFMBtuRdfcHCwrFarevbsae9WitUFy1X9ev6UHmnQTlJ6OBIee0knoiPzXOfiZFb3GnfKZDJJklpVrq3TMRdv6r7CkNfn51RnSUrU4pAf9Ga7ARnjvu5lcn13Xr9rbrX5ec6N2vvXVxXPclmOpVnTNGLTPM3s9IRKOTrn+izcHmpUaqJ3ntqS6z/enoWz6hIAAAAAAAAAisJtuaLrdhUee0m+7mXk9Pc2ZCaTSf5e5XQm9pLNFn95rZOkD/dvVO9agTd1X1HI6/Ovrzt59YK8Xdw1bfd3Cj59SK5OZr3a9kF1qtYwx2fkZ9451ZY2u+b6nCfXfyyrpBa+NfV2h4Eq7+aV6xxn7luvNn511cy3Rq61uH14upVVszqd7d0GAAAAAAAAANwUgi4U2LRdq3QyOlIfDZhYpPe1/2KSTlzJelXTnsenyt/LdiVTXp9/Y11qWqpOx0Spfjk/TenwsA6cD1OPr6fo4OD3VNG9dJ56LUrfD5ykql4+Sk5N0aSfVmjoho+1+sFxOd5z6OIZfXt8j4IHTiqmLgEAAAAAAAAAKD4EXbeRKp7lFGm5opS0VDk5OMpqtepMzCX537DlXV7qZuxdq1Whe7Wx/wS5OZe6qftys+PRN/M8x7w+P6s6f89ycjCZ9Ej99K0D76wYoACvCjoU9ZcqujfK9ll5/a651XqZXXN8TlUvH0mSs6OTRgV20x0Lx+T6PXaeParTMVFqsPBFSVKk5aqObF6oSMsVDW/aJdf7AQAAAAAAAAC4ld2WZ3Tdriq4l9adFQK09PBPkqSVx/fIz9M70/Z6udXN3LdOy4/+rA39x6uMi/tN3ydJQ9Z/pFWhe29qfjk9Py91Pm5e6lS1oTaH/SZJOnXlgsJiLqiet1+OPeb1u+ZWm9OYJSlRVxItGc9ZfvRnNa0YkOs3Gd60i/565iOFPj1LoU/PUqtKtfRR16GEXAAAAAAAAACAEsFktVqt9m6ipLJYLPLw8JAkxcXFyd09+/ClsFiTUpQycUW248cuR2jYhjm6lBgnL7Or5ncbrkblq0qShm+ap141A9W7VmC2deGxl1Rj7nOqUbqCPMyukqRSjk7a+djkHJ+f232NF43V4h7PKLCA50jl9vx/5nZnxYAc6/68cl7DN81XVEKsHEwmTWzTT/3qtMy1x7x+19xqsxv788p5/Wf1TKWmpckqqXrpCprRaZACSpeXJP138wJt+POgIi1XVM7VQ55mVx0Z9n6mPjt/OVnPBXZTn9otsv2WTm/3l8lsn8WeqUnStll2eTVQqDqOkhzN9u4CAAAAAAAAKPkIuorQrRh03Youxsdo0LrZ2tB/gr1byZYReiwsBF3AzSPoAgAAAAAAAIoHWxfC7sq7ed3yAZIRegQAAAAAAAAA4HZD0AUAAAAAAAAAAABDIugCAAAAAAAAAACAIRF0AQAAAAAAAAAAwJAIugAAAAAAAAAAAGBIJqvVarV3EyWVxWKRh4eHJCkuLk7u7u5F/k6r1Solpxb5e1CCOTvKZDLZ5dVWq5SWbJdXA4XKwVmy0x8jAAAAAAAA4LbiZO8GULhMJpNk5tcKYzKZJEezvbsAAAAAAAAAABgFWxcCAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImgCwAAAAAAAAAAAIZE0AUAAAAAAAAAAABDIugCAAAAAAAAAACAIRF0AQAAAAAAAAAAwJAIugAAAAAAAAAAAGBIBF0AAAAAAAAAAAAwJIIuAAAAAAAAAAAAGBJBFwAAAAAAAAAAAAyJoAsAAAAAAAAAAACGRNAFAAAAAAAAAAAAQyLoAgAAAAAAAAAAgCERdAEAAAAAAAAAAMCQCLoAAAAAAAAAAABgSE72bgD/slqltGR7dwHcPAdnyWSydxcAAAAAAAAAgJKOoOsWkpYsbZtl7y6Am9dxlORotncXAAAAAAAAAICSjq0LAQAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImgCwAAAAAAAAAAAIZE0AUAAAAAAAAAAABDIugCAAAAAAAAAACAIRF0AQAAAAAAAAAAwJAIugAAAAAAAAAAAGBIBF0AAAAAAAAAAAAwJIIuAAAAAAAAAAAAGBJBFwAAAAAAAAAAAAzptgi6oqKiFBQUpFq1asnFxUX+/v4aPXq0LBaLhg4dKpPJpNmzZ9u7TRjcZ5tfV5exJkVeDrN3K0Wmy1iT3v1ysL3bAAAAAAAAAABAkuRk7waK2sGDB9W9e3dFRkbK3d1dDRo0UEREhGbNmqWTJ0/q8uXLkqSmTZvat9F8siTG6NsdH2jnH9/qbFSo0tJSVbFsgFrX76WH7nlJZT0q2LvFLJ04e1A//7FKXZsPlq93gL3bAQAAAAAAAAAABlaiV3RFRUWpd+/eioyM1JgxY3Tu3Dnt379fkZGReuedd7Ru3Trt3btXJpNJjRs3tne7eRZ+8bhGzGiiz7a8pkreNTS0+zQ9c/9M1a/WWit/mqmnpt+hI3/ttnebWToZcVBLtryh89Fh9m4FAAAAAAAAAAAYXIkOukaNGqXw8HCNHDlS06dPl6enZ8ZYUFCQmjRpopSUFAUEBMjLy8uOneZdYlK8Xl3cW1ExZzV5yBpNGvS1+tz1rHq2flovDVikmc/+rJTUZE1afL+i4y7Yu10AAAAAAAAAAIAiU2K3Ljxy5IiWL18uHx8fTZ06NcuawMBA/fbbb2rSpEnGtfDwcE2bNk179uzRb7/9pqSkJFmt1uJqO1cb9yxU+MXjGnD3WLWq3zPTeF3/5nqy+xR9+O2zWvHDe3q613uSpE17P9H0r4Zo+ohtalLzHpt7xnx8j85Hh+nzCWEZ1/Yd26yNexfq2Jm9uhxzTs5OpVTXv6UeuXeimtS8O8v7Zz77s+auHaN9xzYqOeWaGlZvr5F9P1SV8nUkpZ9htWTLG5Kkl+Z0zLi/S+ATChr4Scb4kvGnMm1r+NiUAFUsG6D/PfPDv/eNNalL4BPq0nyQFm+YqD/P/SZPN2/1ues5Dew4TrHx0Zq39iXtOrxGCUlxalqrk55/cJ58SlfO72dXckqSVu6YqeADS3U26rgcHZ3l51NbXZsPVt+7Rt5Qe00LN0zQ1l8/09W4i/KvUE9Pdp+qVvV72NSt/vkj7Ty0SqfP/6GrlovyciunO2vdq8Hd3so0/3/m2qv1cC3Y8LJCz+yTs7OL7mr4gP57/0y5lvLIqH33y8Ha8uunWvXmFS1Y/7J+CvlGlmsxqu0XqBH3z1D9qq1snm21WrX2lznasGeB/rpwRCaTg+r6t9BjnSepaa2OAgAAAAAAAADgVlViV3QtW7ZMaWlpevTRR+Xh4ZFljaurqyTZBF0nTpzQN998I19fX7Vo0aJYes2P7SFfS5J6tH4625quzQfLydFZO0K+KfB7Nu/7RLHxl9UlcJCe7fuhHmz/gs5cOKKgefcq5M8dmeoTkywa83EHOZoc9WS3KerTdqR+P/mDJn3SR6lpqZKkdg37qWer9L4f7jRB4wYu0biBS9Sr9fAC93ky4oAmL+mvJjXv0fBe/5OfT20tXP+yVu74QEHz7lVsQrQe7/q6erUeob3HNurdLwfl+x3JKUkav+A+LVg/TmU9K+qJrm9qSLe3VccvUDtDVmaqf3f5Ezp0aof63/2Snrhvsq5YLur1T/sq8nKYTd2KH6ertLuP+rYbpece+D91aDJAOw99q9H/11YxlktZzPWgXlncS3WrtNDw3jMUWKerNu5ZqDlrXsyy75cX3Keoq+F6tMskPdxxvMLOH9IrC3sqPjHWpu6dZY9r9qqRquxTS8N6vqtBXd+QJfGqxs3vop//WJ3v7wUAAAAAAAAAQHEpsSu6goODJUkdO2a/IiU8PFySbdDVoUMHnTt3TpL0+uuva+fOnUXYZf6FRR6SWylP+fnUyrbGxewm//L1dCoyRAnX4mxW++TVC/3ny9XsbnOtV5sRGjb9Di3bNlWNarS3GbtqiVL/u8fqPx2DMq6V9iiv+euCtD90q1rUvU81KjdW/WpttG73PAXW6ZJpZVlBnIoM0Qcjf8lYpdSt5VA9NqWa5qx5QX3ajtSzfWfZ1H+z432duXBM/hXq5vkdK3fM1G8nf9DATuM1tPsUm7G0tLRM9aXdfTR5yBqZTCZJUtNaHTVyVkut2zVXQ3v8u7pw3piQTN+4TYP7NW5eZ23Ys9DmW6bP9XebufZqM1zxiTHatHexRvSeken3XNuvmUb1+yjj56oVG+itzwco+MBS9WqTHi7+FPKtvj/whZ5/cK56Xhee9ms3Ws/Nbq2PvxutNg16Z8wFAAAAAAAAAIBbSYld0XX69GlJUrVq1bIcT0lJyQixrg+6HBxu7U8Snxgjd5fSuda5uaSfORZ/LTaXyqxdH8AkXItTjOWSHBwcVa9qKx39a3emegeTgx5oN8rmWtNanSRJZ6NCC9RDXtSv2sZmKz5nJ7Pq+reU1WpV3xv6aVi9fYH6CT7whTxdy+rxzpMyjWX1v5cH2o22CYbq+reQaymPTO/95xunpaXJknBVVy1Rqlm5idxdSmf5jW+cq5T+jVPTUhQZHZapvl/7F2x+vjOL38f3+z+XWylPtW3YV1ctURn/xCVeUZv6vRUZHVakvz8AAAAAAAAAAG5GiV3RZbFYJEkJCQlZji9fvlxRUVHy9PRU9erVi7yf2rVr5xqimZ1cNW9kzqGCm4uXLNdicn1ffGKMHEwOKu3uk68+/xERdVKLN07UvuObFJdwxWYsq9U95bwqy+zsYnPNy62cJCk2i234CkulcjUyXfNwLStJ8vW2/b16uqVfj4nPXz9no0JVs3LTTPPLtifvzD15uZXL9N4DJ4L1+ZY3dfSv3UpKSbQZi0uIzvzcLOb6zzfOaqvDG+u93P+uva6Pvy4cUfy1WA14o2J201F07PmMc9byqnad2kpKyfrPHgAAAAAAAAAA1/P19dW+ffsKdG+JDbp8fX0VHR2t/fv3q02bNjZj586d09ixYyVJjRs3LpZt2f7ZDjEnLs5uudYE+DZUyJ/bdTbqRLbbFyYmxevMxaOqULaanBydJWUdTv0jNS3F5ueEa3F68eMOSkyyqF/751Xdt5FcS3nKweSgZdum6uCJ4EzPcHBwzPb5VllznZckmZT3HjPea8r+vY7Z9GS15q2fgsruW1z/3mNn9url+V3lV66WhvaYJl/v6irl7CqTTHr7i4FKs2beEjGnuSqLb5yX+VtlVRn38hr/yNJsnxzg2zCH92btXESEEpPj830fAAAAAAAAAAD5UWKDrs6dO+vIkSN655131KVLF9Wpk74iZe/evXr88ccVFRUlSWratGmx9FOpUqU8rejKTYdGDynkz+3asGeBhvWYlmXNll8/U0pqsu5t9ljGNU83b0lSTPzlTPWRl09lBGKSdCD0e12KidCYAYvUrcUQm9rFm17Jtcec5BS4/dNjbPxl+XoHZFxPSk7U5Zhzqlwu+3PJipKfTx2duXBUSSnXZHYqVSjPDD6wVGlpqXp72AZVum7lWUKSJcvVXEXFz6e29lw8rvrVWhfoLLfsVKpcmRVdAAAAAAAAAIA88fX1LfC9JTboCgoK0tKlS3XmzBndcccdqlevnhITE3XixAl1795dAQEB2rRpk835XEUpNDRU7u7uOdakJknbZuX8nG4th+q7n2frm+0z1KTGPWpRr5vte8L3a9GG8fL2qqQ+bZ/NuF7FJz3oOxC6Ve0b9cu4HnxgmS7FRKhi2X/PMstYkXTDyqd9xzZneXZUfria08OUrAI3v7+3x9sfulW1qzTLuP7NjvezXOFUXO5t9qjmrwvS0q1vaXC3yTZjVqu1QCsCM1Zn3fCNl30/pVjn2iVwkHYdXqOFG8ZrZN8PM41Hx55XWc/stzXMTujxUDmaC6NDAAAAAAAAAACyV2KDripVqmjHjh0aO3asfvzxR4WFhalBgwaaO3eunnrqKdWsWVOSii3oKiwuZje9OXi1JizoplcW9VS7Rg+qSc175OjgpKNn9uj7X5fIw7Ws3hy82iag8K9QV81qd9a6XXNltVpVs3JTnYw4qJ2HvlVln1pKTU3OqG1YvZ28PX01d+0YRUaHqXzpKjoZcVBb9y9Rdd9GOhUZUuD+6/q3SN8C8fu3FZcQLRezu3y9q6t+1VZqVruz/MvX1aebJykm/pJ8vavrj1M/6chfuwp81lhheKDdaO06vEZffP+Wjp3Zq8A6XWV2dlFY5B8Kv3hM7w7fmu9n3tXwAa3c8b4mLuyhHq2elpOTWfuPb9Gpc78X61w7NH5I97UYou92zlZo+H61btBLpd19dPFKuA6f/kURl05oyfg/i60fAAAAAAAAAADyo8QGXZJUv359rV27NtP1uLg4hYWFycHBQQ0b5v/8IXvzr1BXc178Td/u+EA/HVqpPUfXKzHJIkkKqHiH3n/2J3m4lsl037iBSzT7u+cUfOALbd2/RI2qt9d7I7Zp1spndD46LKPOw7WMpg7bpPnrgvTdzg+Vmpai2n6BevvJ9dqwZ+FNBV0VylbVmAGLtHzbO5q18hmlpCarS+ATql+1lRwdHPXmkNX6v1Wj9N3OD+XkaFZgna763zM/6vn/u6vA77xZzk5mTXtqs1Zs/5+2HViqRRsnyOzkIj+f2rrvhq0d86ph9bs0adA3+mLrZH266VWZnV3VrHZn/e+ZH/Xixx0KeQY5e2nAIjWp2VHrd8/Tl8FTlZyaJG9PX9Xya6ah3acWay8AAAAAAAAAAOSHyWq9Ye+028Du3bvVunVr1a1bV0ePHs00/vXXX0uSvvrqK61YsUIrVqyQJAUEBKh58+Z5fo/FYpGHR/pWfXFxcYWydWG296amaPKS/tr5xyqN6D1DD3Z4oWAPAgpBx1Fi60IAAAAAAAAAQJEr0Su6shMSkr4iKbttC/v375/lz0888YQ++eSTIu2toBwdnTTxseV6/dMHNGfNizI7uah322fs3RYAAAAAAAAAAECRIejKglEXuTk7mfX20HX2bsMQklOSFBt/Ode60h7l5ejgWAwdAQAAAAAAAACA/CLowm3p8Omf9dKcjrnWLRl/Sr7eAUXfEAAAAAAAAAAAyLfbMugKDg62dwuwsxqVmuidp7bkWuft6VsM3QAAAAAAAAAAgIK4LYMuwNOtrJrV6WzvNgAAAAAAAAAAwE1wsHcDAAAAAAAAAAAAQEEQdAEAAAAAAAAAAMCQCLoAAAAAAAAAAABgSARdAAAAAAAAAAAAMCSCLgAAAAAAAAAAABgSQRcAAAAAAAAAAAAMiaALAAAAAAAAAAAAhkTQBQAAAAAAAAAAAEMi6AIAAAAAAAAAAIAhEXQBAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgmq9VqtXcTJZXFYpGHh4ckKS4uTu7u7jnWW61SWnJxdAYULQdnyWSydxcAAAAAAAAAgJLOyd4N4F8mk+RotncXAAAAAAAAAAAAxsDWhQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImgCwAAAAAAAAAAAIZE0AUAAAAAAAAAAABDIugCAAAAAAAAAACAIRF0AQAAAAAAAAAAwJAIugAAAAAAAAAAAGBIBF0AAAAAAAAAAAAwJIIuAAAAAAAAAAAAGBJBFwAAAAAAAAAAAAyJoAsAAAAAAAAAAACGRNAFAAAAAAAAAAAAQyLoAgAAAAAAAAAAgCERdAEAAAAAAAAAAMCQCLoAAAAAAAAAAABgSARdAAAAAAAAAAAAMCQnezeAf1mtVik51d5tADfH2VEmk6lAt1qtUlpyIfcD2IGDs1TAPwYAAAAAAAAA8oGg61aSnKqUiSvs3QVwU5ze7i+ZC/ZXS1qytG1WITcE2EHHUZKj2d5dAAAAAAAAACUfWxcCAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImgCwAAAAAAAAAAAIZE0AUAAAAAAAAAAABDIuhCifLZoR9lnv6IPjv0Y5bjYVcvyjz9EQ3dMKeYOwMAAAAAAAAAAIWNoAsAAAAAAAAAAACGRNAFAAAAAAAAAAAAQyLoAgAAAAAAAAAAgCERdAEAAAAAAAAAAMCQCLoAAIXis82vq8tYkyIvh9m7lSLTZaxJ73452N5tAAAAAAAAAPjbbRF0RUVFKSgoSLVq1ZKLi4v8/f01evRoWSwWDR06VCaTSbNnz7Z3mwDywZIYo8+3TNYzM5vp/lc81WuCm4a+10Dz1wYpOu6CvdvL1omzB/XZ5tdLdBgEAAAAAAAAAMXFyd4NFLWDBw+qe/fuioyMlLu7uxo0aKCIiAjNmjVLJ0+e1OXLlyVJTZs2tW+jKFam6/79uS2LtO7P/bp6LUGeZhc9WKeVpt79iMyOJf6Ph2GFXzyu8fPv0/krp9WuYT91azFUTo7OOvLXLq38aaY27VusyU+uVf2qrezdaiYnIw5qyZY31KTmPfL1DrB3OwAAAAAAAABgaCX6v+RHRUWpd+/eioyM1JgxY/Taa6/J09NTkvTuu+9q3LhxcnJykslkUuPGje3cLQqDi5NZkhSfnJTluCX5miTJ9e86SXrmzq6advcjcje7KCo+Rg+vmaVpu1Zp0l0PFX3DyLfEpHi9uri3omLOavKQNWpVv2fGWM/WT6t3m/9q3LzOmrT4fs0bE6KyHhXs2C0AAAAAAAAAoCiV6KBr1KhRCg8P18iRIzV9+nSbsaCgIC1dulS//fabqlevLi8vLzt1icJUvXR5SdLRy2ezHD96Kf16wN91ktTAp0rGv1slOZhMOnElsuiaxE3ZuGehwi8e14C7x9qEXP+o699cT3afog+/fVYrfnhPT/d6T5K0ae8nmv7VEE0fsU1Nat5jc8+Yj+/R+egwfT4hLOPavmObtXHvQh07s1eXY87J2amU6vq31CP3TlSTmndnef/MZ3/W3LVjtO/YRiWnXFPD6u01su+HqlK+jqT0M6yWbHlDkvTSnI4Z93cJfEJBAz/JGF8y/lSm1V6PTQlQxbIB+t8zP/x731iTugQ+oS7NB2nxhon689xv8nTzVp+7ntPAjuMUGx+teWtf0q7Da5SQFKemtTrp+Qfnyad05fx+diWnJGnljpkKPrBUZ6OOy9HRWX4+tdW1+WD1vWvkDbXXtHDDBG399TNdjbso/wr19GT3qWpVv4dN3eqfP9LOQ6t0+vwfumq5KC+3crqz1r0a3O2tTPP/Z669Wg/Xgg0vK/TMPjk7u+iuhg/ov/fPlGspj4zad78crC2/fqpVb17RgvUv66eQb2S5FqPafoEacf+MTCv9rFar1v4yRxv2LNBfF47IZHJQXf8WeqzzJDWt1VEAAAAAAAAAbl0l9oyuI0eOaPny5fLx8dHUqVOzrAkMDJQkNWnSJOPa119/rQcffFDVqlWTm5ub6tWrp4kTJyouLq5Y+sbNubNidfl7ltNXR39RRFy0zVhSaoo+PrBZJpnUq1agzdi7u1er7AdD5PfRCP1+8bRGNetenG0jH7aHfC1J6tH66WxrujYfLCdHZ+0I+abA79m87xPFxl9Wl8BBerbvh3qw/Qs6c+GIgubdq5A/d2SqT0yyaMzHHeRoctST3aaoT9uR+v3kD5r0SR+lpqVKkto17KeerdL7frjTBI0buETjBi5Rr9bDC9znyYgDmrykv5rUvEfDe/1Pfj61tXD9y1q54wMFzbtXsQnRerzr6+rVeoT2Htuod78clO93JKckafyC+7Rg/TiV9ayoJ7q+qSHd3lYdv0DtDFmZqf7d5U/o0Kkd6n/3S3rivsm6Yrmo1z/tm+lcshU/Tldpdx/1bTdKzz3wf+rQZIB2HvpWo/+vrWIsl7KY60G9sriX6lZpoeG9ZyiwTldt3LNQc9a8mGXfLy+4T1FXw/Vol0l6uON4hZ0/pFcW9lR8YqxN3TvLHtfsVSNV2aeWhvV8V4O6viFL4lWNm99FP/+xOt/fCwAAAAAAAEDxKbErupYtW6a0tDQ9+uij8vDwyLLG1dVVkm3QNX36dFWtWlVTpkxRlSpVdPDgQb3xxhv68ccftX37djk4lNhssERwcnDUh52fVP/vZijw03Ea3LCjapapoPPxV7Xi6C4dvhSuca36qK637YqWoFb3K6jV/Tpy6ayWHdkpX48y9pkAchUWeUhupTzl51Mr2xoXs5v8y9fTqcgQJVyLs1ntk1cv9J8vV7O7zbVebUZo2PQ7tGzbVDWq0d5m7KolSv3vHqv/dAzKuFbao7zmrwvS/tCtalH3PtWo3Fj1q7XRut3zFFinS6aVZQVxKjJEH4z8JWOVUreWQ/XYlGqas+YF9Wk7Us/2nWVT/82O93XmwjH5V6ib53es3DFTv538QQM7jdfQ7lNsxtLS0jLVl3b30eQha2QypZ+G17RWR42c1VLrds3V0B7//h8P5o0JyfSN2zS4X+PmddaGPQttvmX6XH+3mWuvNsMVnxijTXsXa0TvGZl+z7X9mmlUv48yfq5asYHe+nyAgg8sVa826eHiTyHf6vsDX+j5B+eq53Xhab92o/Xc7Nb6+LvRatOgd8ZcAAAAAAAAANxaSmxqExwcLEnq2DH7bafCw8Ml2QZda9as0VdffaVHH31Ud999t0aPHq3Zs2dr586d+umnn4q2aRSKHjXv1I8Pv667/Rvo8z+2a9T3n2jmvvUq7+alL3qN0uT2/8n23vrl/NS4fFUNWf9xMXaM/IhPjJG7S+lc69xc0rcjjb8Wm0tl1q4PYBKuxSnGckkODo6qV7WVjv61O1O9g8lBD7QbZXOtaa1OkqSzUaEF6iEv6ldtY7MVn7OTWXX9W8pqtarvDf00rN6+QP0EH/hCnq5l9XjnSZnGsgr/H2g32iYYquvfQq6lPDK9959vnJaWJkvCVV21RKlm5SZydymd5Te+ca5S+jdOTUtRZHRYpvp+7V+w+fnOLH4f3+//XG6lPNW2YV9dtURl/BOXeEVt6vdWZHRYkf7+AAAAAAAAANycErui6/Tp05KkatWqZTmekpKinTt3SrINusqXL5+ptnnz5pKks2ezPvcpL2rXrp3rajBXR2cdHjAlxxrkTfNKNfXl/c8X6N7ktFSFRp8r3IZuI3Vq11ZCanKB7jU7uWreyJxDBTcXL1muxeT6rPjEGDmYHFTa3adAvUREndTijRO17/gmxSVcsRnLanVPOa/KMju72FzzcisnSYrNYhu+wlKpXI1M1zxcy0qSfL2r21z3dEu/HhOfv37ORoWqZuWmmeaXbU/emXvyciuX6b0HTgTr8y1v6uhfu5WUkmgzFpdgu/WolPVc//nGWW11eGO9l/vftdf18deFI4q/FqsBb1TMbjqKjj2fcc5aXtWuU1tJKQn5ugcAAAAAAAC4Xfn6+mrfvn0FurfEBl0Wi0WSlJCQ9X9oXL58uaKiouTp6anq1atnWfOPbdu2SZLq169f4H7Oncs9OHFzLlXg56Ngrl6L13ehe3V/reYqXcpNIVFnNPWXVeoS0NjerRlWxLlzik++VqB7XZzdcq0J8G2okD+362zUiWy3L0xMiteZi0dVoWw1OTk6S8o6nPpHalqKzc8J1+L04scdlJhkUb/2z6u6byO5lvKUg8lBy7ZN1cETwZme4eDgmO3zrbLmOi9JMinvPWa815T9ex2z6clqzVs/BZXdt7j+vcfO7NXL87vKr1wtDe0xTb7e1VXK2VUmmfT2FwOVZs28JWJOc1UW3zgv87fKqjLu5TX+kaXZPjnAt2EO783auYgIJSbH5/s+AAAAAAAAAPlTYoMuX19fRUdHa//+/WrTpo3N2Llz5zR27FhJUuPGjXP8D+Bnz57Vq6++qm7duqlp06YF7qdSpUp5WtGF4mWStPTwTxr7w+dKSk1RBTcv9a3dUpPaPmjv1gyrcqVKN7WiKzcdGj2kkD+3a8OeBRrWY1qWNVt+/Uwpqcm6t9ljGdc83bwlSTHxlzPVR14+lRGISdKB0O91KSZCYwYsUrcWQ2xqF296JU9zyU5Of9/802Ns/GX5egdkXE9KTtTlmHOqXC77c8mKkp9PHZ25cFRJKddkdiqcQD74wFKlpaXq7WEbVOm6lWcJSZYsV3MVFT+f2tpz8bjqV2tdoLPcslOpcmVWdAEAAAAAAAB55OvrW+B7S2zQ1blzZx05ckTvvPOOunTpojp10red2rt3rx5//HFFRUVJUo7hVVxcnPr06SOz2axFixbdVD+hoaFyd3fPscaalKKUiStu6j3IH69Sbto4YKK92yhRjoeGymQu2F8tqUnStlk513RrOVTf/Txb32yfoSY17lGLet1sxkPD92vRhvHy9qqkPm2fzbhexSf974ADoVvVvlG/jOvBB5bpUkyEKpb9d5vTjBVJN6x82ndsc5ZnR+WHqzk9TMkqcPP7e3u8/aFbVbtKs4zr3+x4P8sVTsXl3maPav66IC3d+pYGd5tsM2a1WnMM77KTsTrrhm+87PspxTrXLoGDtOvwGi3cMF4j+36YaTw69rzKema/rWF2Qo+HytFcGB0CAAAAAAAAyEmJDbqCgoK0dOlSnTlzRnfccYfq1aunxMREnThxQt27d1dAQIA2bdpkcz7X9RISEtS7d2+dOnVKO3bsUKVKlYp5BgCy4mJ205uDV2vCgm56ZVFPtWv0oJrUvEeODk46emaPvv91iTxcy+rNwattAgr/CnXVrHZnrds1V1arVTUrN9XJiIPaeehbVfappdTrVqE1rN5O3p6+mrt2jCKjw1S+dBWdjDiorfuXqLpvI52KDClw/3X9W6Rvgfj924pLiJaL2V2+3tVVv2orNavdWf7l6+rTzZMUE39Jvt7V9cepn3Tkr10FPmusMDzQbrR2HV6jL75/S8fO7FVgna4yO7soLPIPhV88pneHb833M+9q+IBW7nhfExf2UI9WT8vJyaz9x7fo1Lnfi3WuHRo/pPtaDNF3O2crNHy/WjfopdLuPrp4JVyHT/+iiEsntGT8n8XWDwAAAAAAAID8yXkvPQOrUqWKduzYoZ49e8rFxUVhYWHy9vbW3LlztW7dOh0/flySsgy6kpOT9dBDD2nfvn3asGGDGjRoUNztA8iBf4W6mvPib3q8y+s6GxWq+euCNPOb4dq4Z6H8fGprUdBR1fVvnum+cQOX6K5G/RR84AvNXTtG56PD9N6IbfLx8rOp83Ato6nDNqmefyt9t/NDzV07RqfPH9bbT65XLb9mmZ6bHxXKVtWYAYt0LTlBs1Y+oylfPKw1P38sKf1MqTeHrFaTGvfou50fauH6l5WcmqT/PfOjXMw5rwgtSs5OZk17arMGd3tLF6+e0aKNE7RowwQdO7NH7a5bHZcfDavfpUmDvpGL2V2fbnpVSza/rlLOrnaZ60sDFilo4GdycHDQl8FTNXvVc9ry66dyLeWhod2nFmsvAAAAAAAAAPLHZLXesG/UbSAuLk5eXl4ymUyKjY2Vm5tbxlhaWpoGDhyo1atXa/369erUqVOB32OxWOTh4ZHxTrYuxO3A6e3+Rbp1Ybb3pqZo8pL+2vnHKo3oPUMPdnihYA8CCkHHUWLrQgAAAAAAAKAYlNitC3Pyxx9/yGq1qk6dOjYhlyQ9++yzWrFihV5++WW5ublp165dGWM1a9ZU+fLli7tdAHng6OikiY8t1+ufPqA5a16U2clFvds+Y++2AAAAAAAAAABF6LYMukJC0s/XyWrbwg0bNkiSpk2bpmnTptmMLV68WIMHDy7y/gAUjLOTWW8PXWfvNgwhOSVJsfGXc60r7VFejg6OxdARAAAAAAAAAOQfQdcNwsLCirmbohEafU5DN8xRVEKsSpvdtKD7CN3hUyXfddmNJ6Yk6dG1H+rIpbNydTKrgpuXPuz8pGqV9ZUk9VgxVZGWK3IwOcjT7KIZnZ7QnRUDdCkhVvd9NSXj+fEp13TqygWd/e8cebt6FNu8c6vNaSy7ueU2di0lWUE/fK4tYb+rlJNZjctX1ac9n70l5pRTby98/6nWnvxVp2OitGfQFDWtEJCn3wVubYdP/6yX5nTMtW7J+FPy9Q4o+oYAAAAAAAAAoAAIukqoZzcv1LDGnTSo4d365thuDdswR788/la+63IaH9a4k7pVbyqTyaSP9m/SiE3ztXXgq5Kkpb1HqYxL+plkq0L3atjGOfr1iWkq5+qpfU9MzXj+jL1rtf3MkUIJufIz79xqcxrLbm65jU3c8aVMJpP+GDpDJpNJkZYrt8yccuqtX52WGtOylzoueyNP/cIYalRqonee2pJrnbenbzF0AwAAAAAAAAAF42DvBuwhODhYVqtVPXv2tHcrReKC5ap+PX9KjzRoJyk9qAiPvaQT0ZH5qstp3MXJrO417pTJZJIktapcW6djLmY8+5+wR5JirsXLJFOWvS4O+UFDGt1TrPPOrTa35+Q0t+zGLEmJWhzyg95sNyDjm/m6l7kl5pRbb+3966uKZ7lce4WxeLqVVbM6nXP9x+zsYu9WAQAAAAAAACBbt+WKrpIuPPaSfN3LyOnvc3VMJpP8vcrpTOyljK0F81KX1+dI0of7N6p3rUCba0PWf6QfzxyWJH3XLyhTn7+cPa4riRb1rNmsWOedW21ps2uuz8lpblmNnbx6Qd4u7pq2+zsFnz4kVyezXm37oDpVa2j3OcWnJBWoNwAAAAAAAAAA7I2gy4DafzFJJ65kXtEjSXsen5rl9aI0bdcqnYyO1EcDJtpcX9zjv5Kkzw5t18Tty7T6wXG24yE/6NE72meEL7m5lead09yyGktNS9XpmCjVL+enKR0e1oHzYerx9RQdHPyeKrqXLtbeb3Qr9wYAAAAAAAAAQE4Iugxox6Nv5jheytFJkZYrSklLlZODo6xWq87EXJL/DdvPVfEsl2NdbuNS+hlbq0L3amP/CXJzLpVlP4MadtDIrQt1KSFW5Vw9JUlxSYn6+tgu/fzY5GKfd25z8zK75vk5Wc0tqzF/z3JyMJn0SP30rQPvrBigAK8KOhT1lyq6N8p2Tnn5HdzsnMqUcitQbwAAAAAAAAAA2NtteUZXSVfBvbTurBCgpYd/kiStPL5Hfp7emba6y60ut/GZ+9Zp+dGftaH/eJuzqa4kWhQRF53x83ehe1XOxVPeLh4Z11Yc+0WNK1RVvXJ+Nj0NWf+RVoXuLdJ551ab01hOc8tpzMfNS52qNtTmsN8kSaeuXFBYzAXV8/bLcd7FMafcegMAAAAAAAAA4FZlslqtVns3UVJZLBZ5eKSHO3FxcXJ3d8+x3pqUopSJKwrl3ccuR2jYhjm6lBgnL7Or5ncbrkblq0qShm+ap141A9W7VmCOdTk9Jzz2kmrMfU41SleQh9lVUvqKqp2PTdbpqxf18JoPlJCSLAeTSeVdPTXtnkfVtEJAxnM7LH1NQxt11BON7rHpu/GisVrc4xkF+tYo0nnnVpvdWE5zy23ef145r+Gb5isqIVYOJpMmtumnfnVa5jrvop5Tbr39d/MCbfjzoCItV1TO1UOeZlcdGfZ+tr8Dp7f7y2Qu2GLR1CRp26wC3QrcUjqOkhzN9u4CAAAAAAAAKPkIuoqQPYMuI7oYH6NB62ZrQ/8J9m6lWJW0eRN0AQRdAAAAAAAAQHFh60LcMsq7eZWYsCc/btd5AwAAAAAAAABwswi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADMlktVqt9m6ipLJYLPLw8JAkxcXFyd3dPcd6q9UqJacWR2tA0XF2lMlkKtCtVquUllzI/QB24OAsFfCPAQAAAAAAAIB8cLJ3A/iXyWSSzPxKcPsymSRHs727AAAAAAAAAAAYBVsXAgAAAAAAAAAAwJAIugAAAAAAAAAAAGBIBF0AAAAAAAAAAAAwJIIuAAAAAAAAAAAAGBJBFwAAAAAAAAAAAAyJoAsAAAAAAAAAAACGRNAFAAAAAAAAAAAAQyLoAgAAAAAAAAAAgCERdAEAAAAAAAAAAMCQCLoAAAAAAAAAAABgSARdAAAAAAAAAAAAMCSCLgAAAAAAAAAAABgSQRcAAAAAAAAAAAAMiaALAAAAAAAAAAAAhkTQBQAAAAAAAAAAAEMi6AIAAAAAAAAAAIAhEXQBAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImg6xawZMkSBQYGqmzZsnJ1dVX9+vU1Y8YMWa1We7cGAAAAAAAAAABwy3KydwOQKlSooFdffVV169ZVqVKltGPHDv33v/+Vo6OjRo8ebe/2AAAAAAAAAAAAbkkmK8uGiozFYpGHh4ckKS4uTu7u7nm+94EHHpAkffvtt0XSGwAAAAAAAAAAgNGxdeEtxmq1as+ePdq5c6c6duxo73YAAAAAAAAAAABuWWxdeIu4evWq/Pz8lJSUpLS0NL322msaNWqUvdsCAAAAAAAAAAC4ZRF03SI8PT118OBBxcfH6+eff9b48eNVuXJlDR061N6tAQAAAAAAAAAA3JI4o6sI3cwZXVOnTtUHH3ygyMjIomoPAAAAAAAAAADA0Dij6xaVlpamxMREe7cBAAAAAAAAAABwy2LrwlvAa6+9pvbt26tGjRpKTk7W9u3b9c4772jIkCH2bg0AAAAAAAAAAOCWRdB1C4iJidGIESN09uxZubi4qEaNGpo6dapGjBhh79YAAAAAAAAAAABuWZzRVYRu5owuAAAAAAAAAAAA5IwzugzmzLkLik+8Zu82AAAAAAAAAAAA7I6tCw0kJTVVn3+7RYnXkjR0QA9V9ato75YAAAAAAAAAAADshhVdN0hNTdWSJUvUtWtXlS9fXqVKlVLVqlXVrVs3LViwQKmpqXbr7deQY7oaa5HZ7KxKFcrZrQ8AAAAAAAAAAIBbAWd0XScmJkZ9+/bVtm3bJEmVK1eWn5+fIiIiFBERIavVqujoaJUpUyZPzyvMM7pSUlP13twvdTXWot73ttVdzRsW+FkAAAAAAAAAAAAlAVsXXmfo0KHatm2bqlSpos8++0wdO3bMGDt//rwWLlwoZ2dnu/T2z2ouTw83tWxSzy49AAAAAAAAAAAA3EpY0fW3X3/9Vc2bN5eTk5MOHDighg1vfsXU9Su6XvvfAplLuRToOVarVXHxCbJarSplNquU2T5hGwAAAAAAAAAAQGHz9HDVc0/0K9C9rOj626pVqyRJPXv2LJSQ60YxlniZk2/+fK9rSUm6lpRUCB0BAAAAAAAAAAAYG0HX3w4fPixJatOmTZE838vdrUAruljNBQAAAAAAAAAASjJPD9cC30vQ9beYmBhJUunSpYvk+WOHD5S7u3u+79t98Ii+3bRDnh5uCnp6oJyd+ZUBAAAAAAAAAABIBF0ZvLy8JElXr14ttGe6ubkpLi5OH3/xnWYu/lYmkylf9/+zmkuSkpJS9N685YXWGwAAAAAAAAAAwK2AM7oKwR133KGVK1fql19+KbRnmkwmubu7KynZqlhL/E09i7O5AAAAAAAAAAAAbBF0/e2BBx7Q5MmTtX79eh0+fFgNGjQotGcXZG9JzuYCAAAAAAAAAAC3g5s5o8tktVqthdiLof3nP//RV199papVq+qzzz7T3XffnTF2/vx5LVq0SKNGjSrQWVv5xdlcAAAAAAAAAAAAOSPouk5MTIz69OmjH374QZLk5+enypUr69y5czp79qysVquio6NVpkyZIu0jJTVV0+ct15WYOPW+t63uat6wSN8HAAAAAAAAAABgRA72buBW4uXlpa1bt2rhwoW65557FB8fr99++00ODg667777tHDhQnl6ehZ5H7+GHNeVmDh5eripZZN6Rf4+AAAAAAAAAAAAI2JF1y3owB+h2vDDHt3dqgmruQAAAAAAAAAAALJB0HWLSk5JkUkmOTk52rsVAAAAAAAAAACAWxJBFwAAAAAAAAAAAAyJM7oAAAAAAAAAAABgSARdAAAAAAAAAAAAMCSCLgAAAAAAAAAAABgSQRcAAAAAAAAAAAAMiaALAAAAAAAAAAAAhkTQBQAAAAAAAAAAAEMi6AIAAAAAAAAAAIAhEXQBAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImgCwAAAAAAAAAAAIZE0AUAAAAAAAAAAABDIugCAAAAAAAAAACAIRF0AQAAAAAAAAAAwJAIugAAAAAAAAAAAGBIBF0AAAAAAAAAAAAwJIIuAAAAAAAAAAAAGBJBFwAAAAAAAAAAAAyJoAsAAAAAAAAAAACGRNAFAAAAAAAAAAAAQyLoAgAAAAAAAAAAgCERdAEAAAAAAAAAAMCQCLoAAAAAAAAAAABgSARdAAAAAAAAAAAAMCSCLgAAAAAAAAAAABgSQRcAAAAAAAAAAAAMiaALAAAAAAAAAAAAhkTQBQAAAAAAAAAAAEMi6AIAAAAAAAAAAIAhEXQBAAAAAAAAAADAkAi6AAAAAAAAAAAAYEgEXQAAAAAAAAAAADAkgi4AAAAAAAAAAAAYEkEXAAAAAAAAAAAADImgCwAAAAAAAAAAAIZE0AUAAAAAAAAAAABDIugCAAAAAAAAAACAIf0/7VMXt7cnddoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 2210.55x785.944 with 1 Axes>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test 5-1: create noisy model circuit - circle\n",
    "\n",
    "test5_p = 0.001\n",
    "test5_circuit = createNoisyModelCircuit(params, test5_p, 'phase_flip')\n",
    "test5_circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fe673741",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2210.55x953.167 with 1 Axes>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test 5-2: create noisy model circuit - iris\n",
    "\n",
    "test5_p = 0.001\n",
    "test5_circuit = createNoisyModelCircuit(params_iris, test5_p, 'bit_flip')\n",
    "test5_circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "052716ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluate <noiseless>: \n",
      "FINAL ACCURACY: 88.50%\n",
      "\n",
      "Evaluate <bit_flip>: \n",
      "FINAL ACCURACY: 89.50%\n",
      "\n",
      "Evaluate <phase_flip>: \n",
      "FINAL ACCURACY: 90.00%\n",
      "\n",
      "Evaluate <depolarizing>: \n",
      "FINAL ACCURACY: 89.50%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Test 6-1: evaluate noisy model - circle\n",
    "\n",
    "test6_p = 0.001\n",
    "models_type = [\n",
    "    'noiseless', 'bit_flip', 'phase_flip', 'depolarizing'\n",
    "]\n",
    "test6_circuits = [\n",
    "    createModelCircuit(params),\n",
    "    createNoisyModelCircuit(params, test6_p, 'bit_flip'),\n",
    "    createNoisyModelCircuit(params, test6_p, 'phase_flip'),\n",
    "    createNoisyModelCircuit(params, test6_p, 'depolarizing')\n",
    "]\n",
    "\n",
    "for i, model_type in enumerate(models_type):\n",
    "    print(f'Evaluate <{model_type}>: ')\n",
    "    evaluate(test6_circuits[i], X_test2, Y_test)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "77a127b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluate <noiseless>: \n",
      "FINAL ACCURACY: 100.00%\n",
      "\n",
      "Evaluate <bit_flip>: \n",
      "FINAL ACCURACY: 62.50%\n",
      "\n",
      "Evaluate <phase_flip>: \n",
      "FINAL ACCURACY: 100.00%\n",
      "\n",
      "Evaluate <depolarizing>: \n",
      "FINAL ACCURACY: 60.00%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Test 6-2: evaluate noisy model - iris\n",
    "\n",
    "test6_p = 0.5\n",
    "models_type = [\n",
    "    'noiseless', 'bit_flip', 'phase_flip', 'depolarizing'\n",
    "]\n",
    "test6_circuits = [\n",
    "    createModelCircuit(params_iris),\n",
    "    createNoisyModelCircuit(params_iris, test6_p, 'bit_flip'),\n",
    "    createNoisyModelCircuit(params_iris, test6_p, 'phase_flip'),\n",
    "    createNoisyModelCircuit(params_iris, test6_p, 'depolarizing')\n",
    "]\n",
    "\n",
    "for i, model_type in enumerate(models_type):\n",
    "    print(f'Evaluate <{model_type}>: ')\n",
    "    evaluate(test6_circuits[i], X_test_iris, Y_test_iris)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "191d7ea2",
   "metadata": {},
   "source": [
    "## Step 4 Algorithm Objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d89e2661",
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import reduce\n",
    "\n",
    "Dag = lambda matrix: matrix.conj().T\n",
    "Kron = lambda *matrices: reduce(np.kron, matrices)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f4a68fa",
   "metadata": {},
   "source": [
    "### - 4.1 get density matrix/statevector from circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6a4c33d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.quantum_info import DensityMatrix, Statevector\n",
    "\n",
    "def getDensityMatrix(circuit):\n",
    "    return DensityMatrix(circuit).data\n",
    "\n",
    "def getStatevector(circuit):\n",
    "    return Statevector(circuit).data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff5b48d0",
   "metadata": {},
   "source": [
    "### - 4.2 Measurements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "82267cf7",
   "metadata": {},
   "outputs": [],
   "source": [
    "psi_0 = np.array([1.0, 0.0])\n",
    "psi_1 = np.array([0.0, 1.0])\n",
    "I = np.eye(2)\n",
    "\n",
    "M_0 = psi_0.reshape([2, 1]) @ psi_0.reshape([1, 2]).conj()\n",
    "M_1 = psi_1.reshape([2, 1]) @ psi_1.reshape([1, 2]).conj()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "48894fd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def getMeasurements(qubits_num):\n",
    "    measurement_0 = [M_0]\n",
    "    measurement_1 = [M_1]\n",
    "    \n",
    "    for i in range(qubits_num - 1):\n",
    "        measurement_0.append(I)\n",
    "        measurement_1.append(I)\n",
    "        \n",
    "    return [\n",
    "        Kron(*measurement_0),\n",
    "        Kron(*measurement_1)\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f05aa354",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1+0j)\n",
      "(0.4999999999999999+0j)\n",
      "(0.4999999999999999+0j)\n"
     ]
    }
   ],
   "source": [
    "# Test 7: test measure\n",
    "\n",
    "test7_M_0, test7_M_1 = getMeasurements(qubits_num=3)\n",
    "\n",
    "# 2: |0> - X -\n",
    "test7_1_circuit = QuantumCircuit(3, 3)\n",
    "test7_1_circuit.x(test7_1_circuit.qubits[2])\n",
    "test7_1_circuit.draw(output='mpl')\n",
    "\n",
    "test7_1_density_matrix = getDensityMatrix(test7_1_circuit)\n",
    "\n",
    "test7_1_p1 = np.trace( test7_M_1 @ test7_1_density_matrix @ Dag(test7_M_1) )\n",
    "print(test7_1_p1) # should be 1\n",
    "\n",
    "# 2: |0> - H -\n",
    "test7_2_circuit = QuantumCircuit(3, 3)\n",
    "test7_2_circuit.h(test7_2_circuit.qubits[2])\n",
    "test7_2_circuit.draw(output='mpl')\n",
    "\n",
    "test7_2_density_matrix = getDensityMatrix(test7_2_circuit)\n",
    "test7_2_p1 = np.trace( test7_M_1 @ test7_2_density_matrix @ Dag(test7_M_1) )\n",
    "print(test7_2_p1) # should be 0.5\n",
    "\n",
    "test7_M_0, test7_M_1 = getMeasurements(qubits_num=4)\n",
    "\n",
    "# 3: |0> - H -\n",
    "test7_3_circuit = QuantumCircuit(4, 4)\n",
    "test7_3_circuit.h(test7_3_circuit.qubits[3])\n",
    "test7_3_circuit.draw(output='mpl')\n",
    "\n",
    "test7_3_density_matrix = getDensityMatrix(test7_3_circuit)\n",
    "\n",
    "test7_3_p1 = np.trace( test7_M_1 @ test7_3_density_matrix @ Dag(test7_M_1) )\n",
    "print(test7_3_p1) # should be 0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6b4b482",
   "metadata": {},
   "source": [
    "### - 4.3 power sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e92b8d16",
   "metadata": {},
   "outputs": [],
   "source": [
    "def powerSets(items):\n",
    "    N = len(items)\n",
    "    combs = []\n",
    "    \n",
    "    for i in range(2 ** N):\n",
    "        comb = []\n",
    "        for j in range(N):\n",
    "            if (i >> j) % 2:\n",
    "                comb.append(items[j])\n",
    "        combs.append(comb)\n",
    "    \n",
    "    return combs "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f2a4c71b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[], [0], [1], [0, 1]]\n"
     ]
    }
   ],
   "source": [
    "# Test 8: calculate power sets\n",
    "\n",
    "print(powerSets([0, 1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94569c90",
   "metadata": {},
   "source": [
    "### - 4.4 algorithm class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "d3dc2261",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Algorithm:\n",
    "    def __init__(self, model_circuit, measurements, outputs):\n",
    "        # DensityMatrix of model\n",
    "        self.E = getDensityMatrix(model_circuit)\n",
    "        \n",
    "        # Measurements\n",
    "        self.M = dict()\n",
    "        for index, output in enumerate(outputs):\n",
    "            self.M[output] = measurements[index]\n",
    "        \n",
    "        # Outputs\n",
    "        self.O = outputs\n",
    "        self.O_ = powerSets(outputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "0e5c08ca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 16)\n",
      "[0, 1]\n",
      "[[], [0], [1], [0, 1]]\n"
     ]
    }
   ],
   "source": [
    "# Test 9: algorithm objects\n",
    "\n",
    "test9_circuit = createModelCircuit(params_iris)\n",
    "test9_A = Algorithm(test9_circuit, getMeasurements(qubits_num=4), [0, 1])\n",
    "\n",
    "print(test9_A.E.shape)\n",
    "print(test9_A.O)\n",
    "print(test9_A.O_)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cec5aa3a",
   "metadata": {},
   "source": [
    "## Step 5 Distance Calculation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "553f64a6",
   "metadata": {},
   "source": [
    "### - 5.1 trace distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "84c6caa5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.linalg import sqrtm\n",
    "\n",
    "def D(rou, sigma):\n",
    "    A = rou - sigma\n",
    "    A_ = sqrtm( np.dot( A.conj().T, A ) )\n",
    "\n",
    "    return 0.5 * np.linalg.norm( np.trace(A_) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "03ecaa4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test 10: trace distance example\n",
    "\n",
    "from math import isclose\n",
    "\n",
    "# example from: quantumnanophotonics.org/media/Module2Lecture8.pdf\n",
    "test10_rou = np.array([[2.0, 0.0], [0.0, 1.0]]) / 3\n",
    "test10_sigma = np.array([[3.0, 0.0], [0.0, 1.0]]) / 4\n",
    "\n",
    "assert isclose(D(test10_rou, test10_sigma), 1/12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "07c94015",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n",
      "0.9991324663029832\n"
     ]
    }
   ],
   "source": [
    "# Test 11: calculate input states' distance\n",
    "\n",
    "test11_rou = getDensityMatrix(createInputCircuit(X_train2[0]))\n",
    "test11_sigma = getDensityMatrix(createInputCircuit(X_train2[1]))\n",
    "\n",
    "print(D(test11_rou, test11_rou)) # should be 0\n",
    "print(D(test11_rou, test11_sigma))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "781c7105",
   "metadata": {},
   "source": [
    "### - 5.2 total variation distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "5b4ab407",
   "metadata": {},
   "outputs": [],
   "source": [
    "def d(A, rou, sigma):\n",
    "    distance = 0\n",
    "    \n",
    "    for output in A.O:\n",
    "        trace = np.trace(\n",
    "            Dag(A.M[output]) @ A.M[output] @ \n",
    "            (A.E @ (rou - sigma) @ Dag(A.E))\n",
    "        )\n",
    "        \n",
    "        distance += np.linalg.norm(trace)\n",
    "    \n",
    "    return distance / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "f032e6eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n",
      "0.14724516131436494\n"
     ]
    }
   ],
   "source": [
    "# Test 12: calculate total variation distance\n",
    "\n",
    "test12_circuit = createModelCircuit(params)\n",
    "test12_A = Algorithm(test12_circuit, getMeasurements(qubits_num=3), [0, 1])\n",
    "\n",
    "test12_rou = getDensityMatrix(createInputCircuit(X_train2[0]))\n",
    "test12_sigma = getDensityMatrix(createInputCircuit(X_train2[1]))\n",
    "\n",
    "print(d(test12_A, test12_rou, test12_rou))\n",
    "print(d(test12_A, test12_rou, test12_sigma))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd03c6b6",
   "metadata": {},
   "source": [
    "## Step 6 Calculate Lipschitz constant"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3fc2606",
   "metadata": {},
   "source": [
    "### - 6.1 calculate lipschitz constant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "11838400",
   "metadata": {},
   "outputs": [],
   "source": [
    "def Lipschitz(A):\n",
    "    E, M, O, O_ = A.E, A.M, A.O, A.O_\n",
    "    \n",
    "    # Step 1: Calculate W_i\n",
    "    W = dict()\n",
    "    for i in O:\n",
    "        W[i] = Dag(E) @ Dag(M[i]) @ M[i] @ E\n",
    "    \n",
    "    # Step 2: Calculate K_star\n",
    "    K_star = 0; vectors = [None, None]\n",
    "    M_star = np.zeros(E.shape)\n",
    "    \n",
    "    for S in O_:\n",
    "        if len(S) == 0:\n",
    "            continue\n",
    "            \n",
    "        # calculate M_S = Σ Wi\n",
    "        M_S = np.zeros(E.shape).astype('complex64')\n",
    "        for i in S:\n",
    "            M_S += W[i]\n",
    "        \n",
    "        # calculate eigenvalues and eigenvectors of M_S\n",
    "        eigenvalues, eigenvectors = np.linalg.eigh(M_S)\n",
    "        min_index = np.where(eigenvalues == eigenvalues.min())\n",
    "        max_index = np.where(eigenvalues == eigenvalues.max())\n",
    "        \n",
    "        # calculate K_S\n",
    "        K_S = np.linalg.norm(eigenvalues[max_index][0] - eigenvalues[min_index][0])\n",
    "        \n",
    "        if K_S > K_star:\n",
    "            K_star = K_S\n",
    "            vectors[0] = eigenvectors.T[max_index][0]\n",
    "            vectors[1] = eigenvectors.T[min_index][0]\n",
    "            \n",
    "    return K_star, np.array(vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "64cbc725",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier for centric circle: \n",
      "(1.0, array([[ 0.08830713+0.j        ,  0.0052315 -0.00061151j,\n",
      "        -0.54784316+0.03141748j,  0.03646262+0.00281407j,\n",
      "         0.14485073-0.00194239j, -0.00875763-0.001208j  ,\n",
      "         0.8147165 -0.05454154j,  0.04297415-0.00832087j],\n",
      "       [ 0.5483868 +0.j        ,  0.03865225+0.00100061j,\n",
      "        -0.13613315+0.11122154j,  0.00441891+0.13853304j,\n",
      "        -0.7345542 +0.26197848j, -0.09349396+0.03739827j,\n",
      "        -0.03322783+0.0185454j ,  0.1658317 +0.01931279j]],\n",
      "      dtype=complex64))\n",
      "\n",
      "Classifier for Iris: \n",
      "(1.0, array([[ 5.1224810e-01+0.0000000e+00j,  1.2805447e-01-1.5716428e-01j,\n",
      "        -4.6464182e-02-4.8011953e-01j, -1.7507088e-01-1.1697307e-01j,\n",
      "         1.9302657e-03-2.3970471e-05j,  4.7483321e-04-5.9813249e-04j,\n",
      "        -2.5687154e-04-2.7331561e-03j, -9.9440350e-04-6.6813920e-04j,\n",
      "         3.9289543e-01+1.7302768e-01j,  1.6676332e-01-8.4787413e-02j,\n",
      "         1.3040526e-01-3.9493093e-01j, -8.8753097e-02-1.3898401e-01j,\n",
      "         2.2194656e-03+9.8545512e-04j,  9.4497600e-04-4.7709129e-04j,\n",
      "         4.7669682e-04-1.5082960e-03j, -3.4465280e-04-5.2442454e-04j],\n",
      "       [ 3.1758568e-01+0.0000000e+00j,  2.9468201e-02-1.8393441e-01j,\n",
      "        -2.2971131e-01+6.4443976e-01j,  2.4498379e-01-2.7509290e-01j,\n",
      "        -5.5171194e-04-8.1406842e-04j,  1.2663535e-04-7.7127159e-04j,\n",
      "         2.1664377e-03-9.2658226e-04j,  4.6017810e-04-7.5275602e-04j,\n",
      "        -9.2287837e-03-1.5119736e-01j,  1.0151771e-01-2.3656576e-03j,\n",
      "         4.2002317e-01-1.1694973e-01j, -1.7974521e-01-7.0664361e-02j,\n",
      "        -1.3843905e-03+2.1386005e-03j,  1.0767560e-03+5.4406049e-04j,\n",
      "         7.4833655e-04-1.9062139e-03j,  4.1396494e-04-2.4905446e-04j]],\n",
      "      dtype=complex64))\n"
     ]
    }
   ],
   "source": [
    "# Test 13: calculate lipschitz constant\n",
    "\n",
    "print('Classifier for centric circle: ')\n",
    "test13_1_circuit = createModelCircuit(params)\n",
    "test13_1_A = Algorithm(test13_1_circuit, getMeasurements(qubits_num=3), [0, 1])\n",
    "print(Lipschitz(test13_1_A))\n",
    "\n",
    "print('\\nClassifier for Iris: ')\n",
    "test13_2_circuit = createModelCircuit(params_iris)\n",
    "test13_2_A = Algorithm(test13_2_circuit, getMeasurements(qubits_num=4), [0, 1])\n",
    "print(Lipschitz(test13_2_A))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "07ac06b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier for centric circle: \n",
      "p: 0.0001\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.9982796311378479\n",
      "phase_flip model: 0.9992163777351379\n",
      "depolarizing model: 0.9989377856254578\n",
      "\n",
      "p: 0.001\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.9829362034797668\n",
      "phase_flip model: 0.9922083020210266\n",
      "depolarizing model: 0.9894289970397949\n",
      "\n",
      "p: 0.05\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.43096035718917847\n",
      "phase_flip model: 0.709731936454773\n",
      "depolarizing model: 0.5891456604003906\n",
      "\n",
      "p: 0.1\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.19194786250591278\n",
      "phase_flip model: 0.5588558912277222\n",
      "depolarizing model: 0.35014522075653076\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Test 14-1: calculate lipschitz constant in noisy model\n",
    "\n",
    "test14_p = [0.0001, 0.001, 0.05, 0.1]\n",
    "models_type = [\n",
    "    'noiseless', 'bit_flip', 'phase_flip', 'depolarizing'\n",
    "]\n",
    "\n",
    "print('Classifier for centric circle: ')\n",
    "for p in test14_p:\n",
    "    test14_1_circuits = [\n",
    "        createModelCircuit(params),\n",
    "        createNoisyModelCircuit(params, p, 'bit_flip'),\n",
    "        createNoisyModelCircuit(params, p, 'phase_flip'),\n",
    "        createNoisyModelCircuit(params, p, 'depolarizing')\n",
    "    ]\n",
    "    \n",
    "    print(f'p: {p}')\n",
    "    for i, model_type in enumerate(models_type):\n",
    "        test14_1_noisy_A = Algorithm(test14_1_circuits[i], getMeasurements(qubits_num=3), [0, 1])\n",
    "        print(f'{model_type} model: {Lipschitz(test14_1_noisy_A)[0]}')\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "e49cf354",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier for Iris: \n",
      "p: 0.0001\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.9974957704544067\n",
      "phase_flip model: 0.9983262419700623\n",
      "depolarizing model: 0.9986007213592529\n",
      "\n",
      "p: 0.001\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.975249707698822\n",
      "phase_flip model: 0.9834035038948059\n",
      "depolarizing model: 0.9860955476760864\n",
      "\n",
      "p: 0.05\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.29632073640823364\n",
      "phase_flip model: 0.4548749029636383\n",
      "depolarizing model: 0.4973519444465637\n",
      "\n",
      "p: 0.1\n",
      "noiseless model: 1.0\n",
      "bit_flip model: 0.09604907780885696\n",
      "phase_flip model: 0.23411400616168976\n",
      "depolarizing model: 0.249342143535614\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Test 14-2: calculate lipschitz constant in noisy model\n",
    "\n",
    "test14_p = [0.0001, 0.001, 0.05, 0.1]\n",
    "models_type = [\n",
    "    'noiseless', 'bit_flip', 'phase_flip', 'depolarizing'\n",
    "]\n",
    "\n",
    "print('Classifier for Iris: ')\n",
    "for p in test14_p:\n",
    "    test14_2_circuits = [\n",
    "        createModelCircuit(params_iris),\n",
    "        createNoisyModelCircuit(params_iris, p, 'bit_flip'),\n",
    "        createNoisyModelCircuit(params_iris, p, 'phase_flip'),\n",
    "        createNoisyModelCircuit(params_iris, p, 'depolarizing')\n",
    "    ]\n",
    "    \n",
    "    print(f'p: {p}')\n",
    "    for i, model_type in enumerate(models_type):\n",
    "        test14_2_noisy_A = Algorithm(test14_2_circuits[i], getMeasurements(qubits_num=4), [0, 1])\n",
    "        print(f'{model_type} model: {Lipschitz(test14_2_noisy_A)[0]}')\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66dd0fb4",
   "metadata": {},
   "source": [
    "### - 6.2 Fairness verifying"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "f042e7d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def FairVeriQ(A, epsilon, delta):\n",
    "    # epsilon <= 1 and delta > 0\n",
    "    K_star, kernel = Lipschitz(A)\n",
    "    \n",
    "    if delta >= K_star * epsilon:\n",
    "        return True, None\n",
    "    else:\n",
    "        return False, kernel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "8dc632d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "find proper epsilon - centric circle\n",
      "Mean distance: 0.8015871518061924\n",
      "Max distance: 0.9999996127156026\n",
      "Min distance: 0.19951183226870292\n"
     ]
    }
   ],
   "source": [
    "# Test 15-1: find proper epsilon - circle\n",
    "\n",
    "import random\n",
    "\n",
    "# D(rou, sigma) <= epsilon\n",
    "indices = []\n",
    "while len(indices) < 50:\n",
    "    a = random.randint(0, len(X_train2) - 1)\n",
    "    b = random.randint(0, len(X_train2) - 1)\n",
    "    if a != b:\n",
    "        indices.append([a, b])\n",
    "\n",
    "distances = []\n",
    "for pair in indices:\n",
    "    rou = getDensityMatrix(createInputCircuit(X_train2[pair[0]]))\n",
    "    sigma = getDensityMatrix(createInputCircuit(X_train2[pair[1]]))\n",
    "    \n",
    "    distances.append(D(rou, sigma))\n",
    "    \n",
    "print('find proper epsilon - centric circle')\n",
    "print(f'Mean distance: {sum(distances) / len(distances)}')\n",
    "print(f'Max distance: {max(distances)}')\n",
    "print(f'Min distance: {min(distances)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "42e60912",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "find proper epsilon - centric iris\n",
      "Mean distance: 0.7648498873789216\n",
      "Max distance: 0.9999596813114654\n",
      "Min distance: 0.11293627887720475\n"
     ]
    }
   ],
   "source": [
    "# Test 15-2: find proper epsilon - iris\n",
    "\n",
    "# D(rou, sigma) <= epsilon\n",
    "indices = []\n",
    "while len(indices) < 50:\n",
    "    a = random.randint(0, len(X_train_iris) - 1)\n",
    "    b = random.randint(0, len(X_train_iris) - 1)\n",
    "    if a != b:\n",
    "        indices.append([a, b])\n",
    "\n",
    "distances = []\n",
    "for pair in indices:\n",
    "    rou = getDensityMatrix(createInputCircuit(X_train_iris[pair[0]]))\n",
    "    sigma = getDensityMatrix(createInputCircuit(X_train_iris[pair[1]]))\n",
    "    \n",
    "    distances.append(D(rou, sigma))\n",
    "\n",
    "print('find proper epsilon - centric iris')\n",
    "print(f'Mean distance: {sum(distances) / len(distances)}')\n",
    "print(f'Max distance: {max(distances)}')\n",
    "print(f'Min distance: {min(distances)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "7d94ee5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "find proper delta - circle\n",
      "Mean distance: 0.0617588018773251\n",
      "Max distance: 0.2668696054715782\n",
      "Min distance: 4.443084240540264e-05\n"
     ]
    }
   ],
   "source": [
    "# Test 16-1: find proper delta - circle\n",
    "\n",
    "test16_1_circuit = createModelCircuit(params)\n",
    "test16_1_A = Algorithm(test16_1_circuit, getMeasurements(qubits_num=3), [0, 1])\n",
    "\n",
    "# d(A(rou), A(sigma)) <= delta\n",
    "indices = []\n",
    "while len(indices) < 50:\n",
    "    a = random.randint(0, len(X_train2) - 1)\n",
    "    b = random.randint(0, len(X_train2) - 1)\n",
    "    if a != b:\n",
    "        indices.append([a, b])\n",
    "\n",
    "distances = []\n",
    "for pair in indices:\n",
    "    rou = getDensityMatrix(createInputCircuit(X_train2[pair[0]]))\n",
    "    sigma = getDensityMatrix(createInputCircuit(X_train2[pair[1]]))\n",
    "    \n",
    "    distances.append(d(test16_1_A, rou, sigma))\n",
    "\n",
    "print('find proper delta - circle')\n",
    "print(f'Mean distance: {sum(distances) / len(distances)}')\n",
    "print(f'Max distance: {max(distances)}')\n",
    "print(f'Min distance: {min(distances)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "c0b20ecb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "find proper delta - iris\n",
      "Mean distance: 0.09494891366564139\n",
      "Max distance: 0.26286960081164606\n",
      "Min distance: 0.000792585408952696\n"
     ]
    }
   ],
   "source": [
    "# Test 16-2: find proper delta - iris\n",
    "\n",
    "test16_2_circuit = createModelCircuit(params_iris)\n",
    "test16_2_A = Algorithm(test16_2_circuit, getMeasurements(qubits_num=4), [0, 1])\n",
    "\n",
    "# d(A(rou), A(sigma)) <= delta\n",
    "indices = []\n",
    "while len(indices) < 50:\n",
    "    a = random.randint(0, len(X_train_iris) - 1)\n",
    "    b = random.randint(0, len(X_train_iris) - 1)\n",
    "    if a != b:\n",
    "        indices.append([a, b])\n",
    "\n",
    "distances = []\n",
    "for pair in indices:\n",
    "    rou = getDensityMatrix(createInputCircuit(X_train_iris[pair[0]]))\n",
    "    sigma = getDensityMatrix(createInputCircuit(X_train_iris[pair[1]]))\n",
    "    \n",
    "    distances.append(d(test16_2_A, rou, sigma))\n",
    "\n",
    "print('find proper delta - iris')\n",
    "print(f'Mean distance: {sum(distances) / len(distances)}')\n",
    "print(f'Max distance: {max(distances)}')\n",
    "print(f'Min distance: {min(distances)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6904fc21",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lipschitz constant: 0.9829362034797668\n",
      "\n",
      "A is (1,1)-fair: <True>\n",
      "\n",
      "A is (0.9,0.89)-fair: <True>\n",
      "\n",
      "A is (0.6,0.58)-fair: <False>\n",
      " - bias kernel pair is: [[ 8.7966137e-02+0.j          5.2421880e-03-0.00060624j\n",
      "  -5.4890203e-01+0.03147535j  3.6392592e-02+0.00287853j\n",
      "   1.4496601e-01-0.00197145j -8.7222224e-03-0.00120635j\n",
      "   8.1403214e-01-0.05442044j  4.2936157e-02-0.00820159j]\n",
      " [ 5.2705202e-02+0.j          8.3077484e-01+0.12186631j\n",
      "   5.6519429e-04-0.00089926j  1.2709215e-01+0.01143511j\n",
      "  -2.9756736e-02-0.00739511j  5.1050264e-01+0.07122577j\n",
      "  -3.7684434e-04+0.00077956j -9.5929116e-02-0.0083804j ]]\n",
      "\n",
      "A is (0.6,0.59)-fair: <True>\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Test 17-1: fairness verifying - circle\n",
    "\n",
    "test17_1_circuit = createNoisyModelCircuit(params, p=0.001, errorType='bit_flip')\n",
    "test17_1_A = Algorithm(test17_1_circuit, getMeasurements(qubits_num=3), [0, 1])\n",
    "\n",
    "print(f'Lipschitz constant: {Lipschitz(test17_1_A)[0]}\\n')\n",
    "\n",
    "test17_1_fairness_params = [\n",
    "    # epsilon, delta\n",
    "    [1, 1], [0.9, 0.89], [0.6, 0.58], [0.6, 0.59]\n",
    "]\n",
    "\n",
    "for epsilon, delta in test17_1_fairness_params:\n",
    "    flag, kernel = FairVeriQ(test17_1_A, epsilon, delta)\n",
    "    \n",
    "    print(f'A is ({epsilon},{delta})-fair: <{flag}>')\n",
    "    if not flag:\n",
    "        print(f' - bias kernel pair is: {kernel}')\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "82e0123f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lipschitz constant: 0.9834035038948059\n",
      "\n",
      "A is (1,0.99)-fair: <True>\n",
      "\n",
      "A is (0.8,0.79)-fair: <True>\n",
      "\n",
      "A is (0.5,0.3)-fair: <False>\n",
      " - bias kernel pair is: [[ 5.12724161e-01+0.0000000e+00j  1.28032640e-01-1.5713547e-01j\n",
      "  -4.64939214e-02-4.8043025e-01j -1.74887925e-01-1.1684963e-01j\n",
      "   1.93114916e-03-2.3846040e-05j  4.74575209e-04-5.9770868e-04j\n",
      "  -2.56348285e-04-2.7266780e-03j -9.90394386e-04-6.6539587e-04j\n",
      "   3.92745733e-01+1.7295834e-01j  1.66417331e-01-8.4614113e-02j\n",
      "   1.30292282e-01-3.9460191e-01j -8.85802880e-02-1.3871221e-01j\n",
      "   2.21203268e-03+9.8205451e-04j  9.40186088e-04-4.7472160e-04j\n",
      "   4.76128538e-04-1.5061955e-03j -3.43756721e-04-5.2313803e-04j]\n",
      " [ 1.20339826e-01-0.0000000e+00j  2.04094738e-01-1.3560200e-01j\n",
      "   7.11197257e-02-6.2828250e-02j  4.01143461e-01+5.6327677e-01j\n",
      "  -4.79472615e-03-5.2465363e-03j -1.07054040e-03+1.1039445e-03j\n",
      "  -4.30674199e-03+3.5000923e-03j -1.87959417e-03-1.5740625e-03j\n",
      "  -3.30644876e-01-2.8429070e-01j  4.30287540e-01+2.0151950e-02j\n",
      "   1.10182323e-01-1.9434731e-01j -7.73455948e-02-8.0621324e-02j\n",
      "   8.03802907e-03+3.7426520e-03j  1.15413719e-03-8.2395109e-04j\n",
      "  -2.48990348e-03+1.5234994e-03j -7.15605449e-04+6.0832815e-04j]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Test 17-2: fairness verifying - iris\n",
    "\n",
    "test17_2_circuit = createNoisyModelCircuit(params_iris, p=0.001, errorType='phase_flip')\n",
    "test17_2_A = Algorithm(test17_2_circuit, getMeasurements(qubits_num=4), [0, 1])\n",
    "\n",
    "print(f'Lipschitz constant: {Lipschitz(test17_2_A)[0]}\\n')\n",
    "\n",
    "test17_2_fairness_params = [\n",
    "    # epsilon, delta\n",
    "    [1, 0.99], [0.8, 0.79], [0.5, 0.3]\n",
    "]\n",
    "\n",
    "for epsilon, delta in test17_2_fairness_params:\n",
    "    flag, kernel = FairVeriQ(test17_2_A, epsilon, delta)\n",
    "    \n",
    "    print(f'A is ({epsilon},{delta})-fair: <{flag}>')\n",
    "    if not flag:\n",
    "        print(f' - bias kernel pair is: {kernel}')\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3efa186",
   "metadata": {},
   "source": [
    "### - 6.3 Generate Bias pair"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "4534485b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generateBiasPair(sigma, kernel, epsilon):\n",
    "    psi, phi = kernel\n",
    "    size = len(psi)\n",
    "    psi = psi.reshape(size, 1) @ Dag(psi.reshape(size, 1))\n",
    "    phi = phi.reshape(size, 1) @ Dag(phi.reshape(size, 1))\n",
    "    \n",
    "    rou_psi = epsilon * psi + (1 - epsilon) * sigma\n",
    "    rou_phi = epsilon * phi + (1 - epsilon) * sigma\n",
    "    \n",
    "    return np.array([\n",
    "        rou_psi, rou_phi\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "bcdf50c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lipschitz constant: 0.9834035038948059\n",
      "\n",
      "fairness: False\n",
      "epsilon=0.9, delta=0.3\n",
      "D:  0.9000000232731683\n",
      "d:  0.39121552565082224\n"
     ]
    }
   ],
   "source": [
    "# Test 18: generate bias pair\n",
    "\n",
    "test18_circuit = createNoisyModelCircuit(params_iris, p=0.01, errorType='depolarizing')\n",
    "test18_A = Algorithm(test18_circuit, getMeasurements(qubits_num=4), [0, 1])\n",
    "\n",
    "print(f'Lipschitz constant: {Lipschitz(test17_2_A)[0]}\\n')\n",
    "\n",
    "flag, kernel = FairVeriQ(test18_A, epsilon=0.9, delta=0.3)\n",
    "print(f'fairness: {flag}')\n",
    "assert (not flag)\n",
    "\n",
    "test18_sigma = getDensityMatrix(createInputCircuit(X_train_iris[11]))\n",
    "test18_bias_pair = generateBiasPair(test18_sigma, kernel, epsilon=0.9)\n",
    "test18_rou_psi, test18_rou_phi = test18_bias_pair\n",
    "# print(test18_bias_pair)\n",
    "\n",
    "print(f'epsilon=0.9, delta=0.3')\n",
    "print('D: ', D(test18_rou_psi, test18_rou_phi))\n",
    "print('d: ', d(test18_A, test18_rou_psi, test18_rou_phi))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63e502f3",
   "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
}