diff --git a/research/new/stabilizer/stabilizer copy.ipynb b/research/new/stabilizer/stabilizer copy.ipynb
deleted file mode 100644
index 4e7982e..0000000
--- a/research/new/stabilizer/stabilizer copy.ipynb	
+++ /dev/null
@@ -1,325 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from quantumreservoirpy import util\n",
-    "from quantumreservoirpy.reservoirs import Static, Incremental\n",
-    "\n",
-    "from qiskit.quantum_info import Clifford, random_clifford\n",
-    "from qiskit.extensions import HamiltonianGate\n",
-    "from qiskit.circuit.library import PauliGate\n",
-    "from qiskit.circuit.library import RYGate, RZGate, RZZGate"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "\n",
-    "class Stabilizer(Static):\n",
-    "    def __init__(self, n_qubits, encoder, *args, **kwargs) -> None:\n",
-    "        super().__init__(n_qubits , *args, **kwargs)\n",
-    "        self.n_logical = n_qubits\n",
-    "        self.encoder = encoder\n",
-    "\n",
-    "        OP = random_clifford(n_qubits)\n",
-    "\n",
-    "        \n",
-    "        H = util.random_ising_H(num_qubits=self.n_logical, num_terms=40)\n",
-    "        T = 10 #s\n",
-    "        self.reservoir = HamiltonianGate(H, T, label=\"UT\")\n",
-    "\n",
-    "        cliff = Clifford(OP)\n",
-    "        ops = [elem[-self.n_logical:] for elem in cliff.stabilizer.to_labels()]\n",
-    "        self.ops = [PauliGate(elem).control(1) for elem in ops]\n",
-    "\n",
-    "    def before(self, circuit):\n",
-    "        circuit.reset(circuit.qubits)\n",
-    "        \n",
-    "    def during(self, circuit, timestep):\n",
-    "        circuit.barrier()\n",
-    "\n",
-    "        circuit.measure([0, 1])\n",
-    "        circuit.initialize('+', 0)\n",
-    "        circuit.initialize('+',1)\n",
-    "        circuit.append(self.encoder[timestep], [0, 1])\n",
-    "        \n",
-    "        circuit.append(self.reservoir, range(self.n_logical))\n",
-    "\n",
-    "    \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "encoder = {}\n",
-    "timestep = [i for i in range(10)]\n",
-    "timeseries = timestep * 10\n",
-    "SHOTS = 50000\n",
-    "n_qubits = 4\n",
-    "N = np.unique(timestep).size\n",
-    "epsilon = np.random.random() \n",
-    "for idx, elem in enumerate(np.unique(timestep)):\n",
-    "    theta = idx * 2 * np.pi / N + epsilon\n",
-    "    encoder[elem] = RZZGate(theta, str(elem))\n",
-    "    # encoder[elem] = ('0'*N + bin(idx)[2:])[-2:]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1959.72x451.5 with 1 Axes>"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n",
-    "qres = Stabilizer(\n",
-    "    n_qubits=n_qubits,\n",
-    "    encoder=encoder\n",
-    ")\n",
-    "\n",
-    "qres.circuit([0, 1, 2], merge_registers=True, transpile=False).draw('mpl')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "states = qres.run(\n",
-    "    timeseries=timeseries, \n",
-    "    shots=SHOTS,\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "WARMUP = 0.2 # 10%\n",
-    "warmup_idx = int(len(states) * WARMUP)\n",
-    "\n",
-    "xstates = states[:-1][warmup_idx:]\n",
-    "target = timeseries[1:][warmup_idx:]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2000x1000 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from quantumreservoirpy.plot import state_plotter\n",
-    "fig, ax = state_plotter(xstates, target)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from quantumreservoirpy.plot import feature_plotter\n",
-    "fig, ax = feature_plotter(xstates, target)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.svm import SVC\n",
-    "from sklearn.linear_model import RidgeClassifier\n",
-    "from sklearn.neighbors import KNeighborsClassifier\n",
-    "models = np.array([\n",
-    "    SVC(kernel=ker, max_iter=1000) for ker in ['linear', 'poly', 'rbf', 'sigmoid']\n",
-    "] \n",
-    "# + [\n",
-    "#     RidgeClassifier(alpha=alph, max_iter=1000) for alph in np.linspace(0, 1e-3, 9)\n",
-    "# ] \n",
-    "+ [\n",
-    "    KNeighborsClassifier(n_neighbors=n) for n in range(1, 10)\n",
-    "]\n",
-    ", dtype=object)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Score of KNeighborsClassifier(n_neighbors=2): 0.9759259259259255\n",
-      "Score of KNeighborsClassifier(n_neighbors=1): 0.9744444444444439\n",
-      "Score of KNeighborsClassifier(n_neighbors=3): 0.9699999999999995\n",
-      "Score of SVC(kernel='poly', max_iter=1000): 0.9644444444444438\n",
-      "Score of KNeighborsClassifier(n_neighbors=4): 0.9529629629629623\n",
-      "Score of KNeighborsClassifier(): 0.9344444444444437\n",
-      "Score of KNeighborsClassifier(n_neighbors=6): 0.8870370370370366\n",
-      "Score of KNeighborsClassifier(n_neighbors=7): 0.827407407407407\n",
-      "Score of KNeighborsClassifier(n_neighbors=8): 0.727407407407407\n",
-      "Score of SVC(max_iter=1000): 0.6825925925925924\n",
-      "Score of KNeighborsClassifier(n_neighbors=9): 0.6281481481481479\n",
-      "Score of SVC(kernel='linear', max_iter=1000): 0.06888888888888893\n",
-      "Score of SVC(kernel='sigmoid', max_iter=1000): 0.03296296296296299\n"
-     ]
-    }
-   ],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings('ignore')\n",
-    "\n",
-    "results = util.stress_test_models(xstates, target, models, test_to_train_ratio=1/3)\n",
-    "sorting = np.flip(np.argsort(results))\n",
-    "for model, res in zip(models[sorting], results[sorting]):\n",
-    "    print(f'Score of {model}: {res}')\n",
-    "    \n",
-    "\n",
-    "model = models[sorting][0]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "AssertionError",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[26], line 4\u001b[0m\n\u001b[0;32m      1\u001b[0m num_preds \u001b[39m=\u001b[39m \u001b[39m40\u001b[39m\n\u001b[0;32m      2\u001b[0m predict_from \u001b[39m=\u001b[39m timeseries[\u001b[39m-\u001b[39mnum_preds:]\n\u001b[1;32m----> 4\u001b[0m \u001b[39massert\u001b[39;00m(\u001b[39m0\u001b[39m \u001b[39m==\u001b[39m \u001b[39m1\u001b[39m)\n\u001b[0;32m      6\u001b[0m preds \u001b[39m=\u001b[39m qres\u001b[39m.\u001b[39mpredict(\n\u001b[0;32m      7\u001b[0m     num_pred\u001b[39m=\u001b[39mnum_preds,\n\u001b[0;32m      8\u001b[0m     model\u001b[39m=\u001b[39mmodel,\n\u001b[0;32m      9\u001b[0m     shots\u001b[39m=\u001b[39mSHOTS,\n\u001b[0;32m     10\u001b[0m     from_series\u001b[39m=\u001b[39mpredict_from\n\u001b[0;32m     11\u001b[0m )\n",
-      "\u001b[1;31mAssertionError\u001b[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "num_preds = 40\n",
-    "predict_from = timeseries[-num_preds:]\n",
-    "\n",
-    "assert(0 == 1)\n",
-    "\n",
-    "preds = qres.predict(\n",
-    "    num_pred=num_preds,\n",
-    "    model=model,\n",
-    "    shots=SHOTS,\n",
-    "    from_series=predict_from\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x2cdce87ea90>"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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pJdPGJjwnaMmYgjD354iZDWF/jhiC28OWzKi4xRALE8+mI8Dtnh308U21y5p+G8A5kCNhS4bliKkB35ABMSodhhceNSYEsnhLpslyxNQ+0lrYR0yKMaqMC76wmPOAaFwMwNxtlOB2WkfRco3IJHv94MYzrRyGF7ZCTCAWZMvdsVvw7UK4OP3PZs5yOXw2pg4NZrkcrsOBGcTCD9t208phuFbwbEwgBcPd4NDo2i34IdxuYh0BA2IY/MXwPrKxsI+YQiz8sG032zjMWqom9pG9sG3Xc3iOmEAs9gY9VK1wVo3tI3kr5ECGyIAoNs0+bGJAFFuXsY95BgoLasl41SPs0DABYZLl8qCwBbDCwkRLJliH51soNI8DMHdo1EIolXLEVPFpk+BQ/TgKW5cAAApOQfs6SHBoUNyC74SIhYHik+D2qe+gsEktVbMMCMoRU8UntWRQPcr3EQOIBbVkBsUtdkExUXy2QznvsV+EUw2JAnlhcTCDtNs7qMEpVQGY433T5HL18CXsY9OpfjYGCQ7ZtSNGh66mAtzOEAsDBQ4xIDpWHXahAsCceBkxIMQcMUEFJg8Ie/MIR7UMtMsIbh+XtoAwV024E7N9xKrDKgRtO1MXlNbCPmKq+CSWjL3J9xETrRA31CmalMR9RP97hsTt2lYDViEogo06zyqMC76wEBkQVnjjMrEhiJbLjaMPET6u/41I0+2FxjF2aJiQwKXp9mnlED80DNw0BixHmrBZjpiB24kBIeaICTXDjXDgudg4Bs8yB3NTS2ZWOWz0NioyIEzuI6O9ATZDBsTcPmLg2VSnwT5SFPcRE7MNlCMbR4zuI3vtANXqOS1YNhUWOWJxIIMsl/vOFuyCuYdNDAjPt3DoIt4KmRmYtCe4vdI8Do9BmPrXQXC7Vz3KYW4Tm3WHt2Rsx1yOkOWy61vYOiYgFgYKi82wbWdvbKF98hsAgPFeP+pLlIQT2nJ71SNAuFmbODQmXd6SsQ3eRkUGROPwRezjJorPTTdATja2jgstVf2viRMisH71CHwa3jSQI+NOUOAMi4eMnjU64oIvLIgBMSptsZuGiWEnJkplbaJcqbKPuwZaIQS31w5dxG6jJm4aHG4/ymYsTMDcJDg0Kh2CFRYWJloh3bCw2LWaKJYqfH0G5NYboeT7RusYxuMgR00Un8VxWOBsHoNvmxvMYy2Z8mHYtjnEQmRAFIslvj4DrqLEgKgfvlhAtQzsI+NgHynUj/F9xECOeCxHDgmoVt4KOZDhCdPtTiF4I5rYEMhyuWu3YDsOXN8K1qd5sxYtlxuHL+aIhYE3ImvJ1I+x26gJxILD7cJNw0DxSQyInt1EIVwHoF/NcDwaMgZE/dBxTMOXwoToUHXC4XbLIGLhh0wqMUdMFJ/Ukuk5LRSEwkK3wJ3IgBD3ESM5IrTtfIND4Ahbu27lkFHkU0dc8IUFCQ551SNGEQuabu8XWgDA6FkzzRU+WS67voWmgFiYGHYiwaFK6yJYBm8aHG4/Csdg/5yxZIpbsGwbM580RvS+JiIDot48zHUsDNy+iAFRbV3EDw0Dz4ZyBNWjDNUyUXxOBJaMI7B0dBefIgNis94yinzSPrJheh8hF97aUTarZdLBWmVc8IUFY0BsHoXDYG79SUcMiHEpoCHNSEpbM8xNlsttqwGnUDAKYZLl8uah44BtbuiqKLRkePFpEG4Pc4QVn5oPDdEDwnYcXlgY6OMTA6J2+GLh0DABt4f7SJ0Xnyb2Ec6AODRXfOqew+kJbTvLto3tI77noRXuI/XDlwjFp/5nU2Y5ckwoPvNWyIEMDrcfhR22QkwgFpwBEcgSz9gbUe+hQQyInt0Mfj5TM9T7BhAtl5tHLgHCN6IJCdyNaRsAUGoegxPCyyZuGiQ4xHLEkI/LkHxCnFawHi/QgdE9EDca9lGzRgAoR6iw0P9siAFRalwEO8wRI86zIgMCYo7oPdBFBgQAY62Q4aCLDSvYQ1tHLxZyxBxLpty8CI7BdpmOuOALC4JSK83jcAp0GzUhSiVMt4PfRnXD3GS5PChsAYAxNUPRcrmxJQxvGngjEgOi3LyI9UZNFJ8Et/vVoLBwDRWfzAMibNsRYqG7by0yIOqNLSFHTLRk2gCASuuYUZjbCZlULEcMFZ/U2t0rGt5HzgQ5sueXUN1sCqiW/mdDPiEbrYuMzmrpiAu+sCBb7s1Dx/mGYACe4mIygWofh7n13jQYA6Ic2gsb6o0uwu2WwZsGsWQ2Dx3nMLeBDYHnyDEA4qGh99m4AgPCsiwgFA3TLV4mMiAs2zY68U8tmfrhi40WnyVx4BkQhKn0ssu8cB8Zh/sIm7HQnKv9szxHABgrPoOWTGAdUT/Mz5pCzgo5eDHHgDhyCZxQMc+EaU9FmG4HBMRCd09ywAWHABibombT7XYLAFhPUjdiMR4NmeVy88ilDOY2cWiQT0ipGegTmGqFiDlSrVZx4nueDgBwHL3bCROlcoJbsakcGfY7jAHRPHIJh7kN5AhjQCzkiHb9CGJAhC0ZU/vIXjjw3Css5IjmdfR7bZStYC9vCTliG5JbVx0XdGEhWi43Dx0z2gphDIhwQzAlpe0stGR8y4wELtf3bwUfYNoA5hgQjdZhNuBrovjcFKBUwFzx6eyFgkM1yhEz+hEkSjUs0qFhpl3WDveRkV9EbbPJ6aYGCot6uI9UtwJPG1OtECcceEZtfh/R3QqZhPsItWRMtVQ7ZwKWzMCvYKNWN4pq6YgLu7BYgNupijRhRU2Wy7VDgRGaZ+jQKC60ZEh0SLek9yIDgklpa96YxJaMZduww+LThKU9Y0AcCg4Nj8HcemcsyqHgkMNyxMxgHrVkJqX5Q8PWnKsi3G7ZtrHiM4Db2wCAzYXCQrePS3lxH2G0dc1tO2LJhC0ZU8JUlCOdcCieis+8FXIAg023h3A7gzAtH56rb1MQLZdbR4LCwjUkpU2Wy8VGcCsmCVzdjpGLDAjLkKDM8CzB7S0AYKJDum8ae4PePAMC/NDQfaCTT0ipcRH29vZw9+fuCNYz2dO6DjBb7uBWbEp0aK/NRakAwCnSBUVzrg66qBDcfpT2kbD41HygU0umHCKwHpPS1vuaWMOgCJ5tzO8julshrCVDOcIYiHkr5MAFMSBoup0eNqDXtEdkQNRbwSbpGeqNEktmoxXMesAQzE0tGYLbTcHcnAER3IqZ1onm4pMEhyZ+IWBAQGyX6X029ZAlU9m6CJ7nodsO/q67XcZYMrXgVmzK/IsYENSSMTVjQQyIoV9GdTOkixsqPokBQS0ZMLl1vQVOIcwRi3LEkNw66RTthQisYxD51BEXdGFBcDsxIOhhA3q19clymVoygDkqYUtgyQAwZjNMDAgnZEDQhqBbdIigVJputwUpbZ2MnUXBIUAsPjXnCAkOHQqQk1moY6FbmIrgdqe+WFjobskEg4qTcnArNlV89s6G+0gItwMiK0Rfjviehy2fs2QAsRWi99nwHAn3EVM5stCS4W33vLA4cCFaLgOY09bXeWiIlssUXAJX3xtgznL5yKXBBw2pGYqWy8EyzIgOUUuGcqRYFD069L0mi1AqACOOkcN+hwkONY8ExeeU6VjofTa8JRPmiGPG68diDIiwsDC0j4zC1m5/SY7o3Ed63V2UrODnUWuXt1T1HuhV0qBh+4iZdpkV7iOUIwXazzQXn7rigi4sHGbLHcDtc8ZOGhEL0XKZgivV6VvHnOVyM9SxMEQTY5bLIQPCNnTTKJDgUNiScYQcmWrMEdaSmcsR/doABLcTAwIQBbL0Fp+LcLup2+giA6Iwh3zq04+gfWRPzBHoZ5eRLcDAr6BS3Qw+yPYR3TkS7CPVEIElozrt+0hoHUEtGXtuH9HvYK06LujCYpEBIZr26LxpLDIgAAja+hpvGouCQ+AtCN2zDS0mShXceCxDaoYlxoAIbjwFYQ5H52YtWi6zj1n6GTu9HWrbtViOUGGhM0dEuJ1yhBWfmlGtRbjdmWuX6Xv/8rbdYfYxE8gnY8kILRmfef2YyRFqyZiaw6lMBOt2zBefugXudMQFXVhwy+XgVmzZNqa+/gOdWS5vmN0QRMtltjZHP4Q5Jzh0NOjjm2qF0HQ7iVI5hQK80NJeqyoqs1wWc0R/K4QLDrXYx8g2XWeOzAsOhbdRQ/4LizlSLJbZv+ksPjncfoT/fKYfob9t13c4cgIDrZBuewdFK8gFasmYktKuhX5D5RCBLQg5orP41BUXdGEhWi5TuOFLonN4U7RcpuCtEH0bwqTDbblZGHAVJcGhiV/AZr0VLsPM8Ca3bj/GPjYDOUZqzJERiVKJOaK/FULT7UOhsLBLgaS3Tpnk7s5+BoRtyJ24sbCP2I4jFJ/6cqQQtmSs2v4Lis4Ch4lSlcR9RP+sVmf72wCAnr+BcqUa/HxD+0g9RGApR0y13XXFBV1YNL1Au70WwmQAMAPpR+h7A4iWyxQm3ADdcJh1IrRkLAOuov2z+xkQ/NDQx/ues1wOGRCAGTXDRQYEYEbNkNp2xICo1Wr4oRfcEKzNsrStg7XtBLjdRCtk3gNC3Ef025UvtmQAM8inNyCWDN9H2AVFI5o0CIdZO8JQPN9H9K3Dc12WI41Qg0YsPnVrjOiIC7awGA37nAEhbAiuFW4IGt+IjAExd2gYcANklsv8xgMDboCLlssABG19fevYZ7kcxszAQBy3XBYODQOKl9ZwfrodMFN87oVtu/5cjpClvb7icxkDAuAXFJ3FZ3U2L0oFiK0QjTmypCWDkLGjkzk0CoXL+gWOnJhohXR3z6BgBTnZPHycfdyUpb2OuGALi2UMCECUwNU3qcs8ILZ40tGwk04JXG65zDcELiijbx1ccIg/F9uA3Pqc5XKtwT5uQhuAWy7zw8uE8ywJDmGTF8FcSlvfs2EtGTFHDLgTd0INmr6/wRkQ4C1VnTnSWBSlgii3ri9HitSSEXLECvcznXLrk85+loxjALGgHOmghlK5wj7OCotpXlgcmFjGgADM3DREy2UKzyIJXH3rIAZEQYBSwSRw9b0RXWa5LNw0DJj2MH3/hRzRbf4lwu0kXAaYMf8qhZLv5BOyt7eHD//VnwT/qJEa7YUDzyLcbsL8a7BDHhCNuY/rNhFctOVmHzfQCimTdfuS4lNnK8QLEdhpZVnxqXMfCXWKrObcx1nxmbdCDk4MlwgOAfqltEUGhNiSYYiFxkOjGg4qkigVYIZuai1hQBSK+mcsljEgAP0zFssYEIDov6AvR2oLDAjP83D/N+4LF6SxbTect+UGzEhp74W34jkGBIRZLU2HxjIGBMBbITqfzSIDAjDTLrOH+1syjgGvH9KgEVsyADCz9M/z6YoLtrBYyoAAn7HQ5QZIDIixX2QMCEAYzNNYzZLl8sbchqBfdIgLDvEbD900dLZCJktEqQD9iAVZLosMCMCMY+Q+DwhwHQudOULCZdbm/sJCp6soyxFh4BkAPM3Dm8SA6KLKGBCAmVYIY0Bs8QKHz2ppzJElLRm+j+jLkUWfEAo3n7E4eMEtlxcetmZtAILbdxfgdq54qecNIFou1w9zBgR3FdXPgLCFlgzxvnW6AXJ9/8PzH9d80+CCQ625j7NDQ9NmPceSEdC1KSss9G3Wi4JDgOgYqRNuD3JkWp7fR2ba95HggtKxWnMf9zUjFp7rMlGqppAjlgEp7Qq1ZBpijoT7iJGWzMI+ovmCojMu2MJi0XKZwtP8sJeJUgEQJHD1bAiDfmef5TJgxlWUWy7vv2kULRe+p6e4IMtlt7JYfOptl3HBofkere7is9s5i9ISuJ1MyHQeGtUQbi/NHRrUCtFXfNpLWDKAfiltYkAMFtp21FLVVXx2zp6GYwX50BTadiZaqjVy4Z3LEf0zFnbYtvM3Fi8oZhysdcQFW1hwBsSKh61pQ1im7w/oh7k7YUtmzy/Nwe22ASntZQyIOUEZTW/EpQwIiIeGnnbZMgYEAGZpb+nq44dwe9/fQGWjxj5uohXSYHA7P7xMFJ/MA2IhRzhzSM+zmXaDw2vfPqLZnZiEyzqooVji6pImWqqNcCi+Jgw8m3AVJeuIxRxh+0gukHVwYikDAvolcDkDYuHQ0NyTZJbLC5PLFnOM1Ae3c31/YUMw4BhZXrBup9DdLlu0XKbwNQ9vEtwuilIBXNJbF2KxTHAImJdJ1lV8MgbE4j4CvbMNBLdPFuB2WHr3EdaSWWjb2Y7eVog7m6Hl9wDMt3ZZYWF52orPSsikElsyAN9HdGom6YoLtrAguL0oiMkA4m1Uz8PmlsvzLRlmM6zpjUiWy72FyWXdpj3zgkPCoSEiFpoKi2WCQ4B+8y8mOFSdzxHdxScTHFpgQNhFKj71bNSi4JDYknFEV1FNOVJjbbvjcx/XDXMT3O5VF/cRvXM4o2U+IRBntfTsI+2dU4EluW+hdZi/fx3BRFDXgc5aMgs5QmeNzsFaXXHBFhbMTndr4WFrFh1atFxmYeuFuVe1ZHS3QshyeeiXsVGrs4/POUZqEpShHNnYMlt8csvlxUNDLyV5QnC74AFRq9Xw6v/2xwAAx9JTWHR2Ql0AVOcEhwpzOaIHXq57tI8sLz51zWqtyhHdxSdJvo9Kqy4ouhBYGmbdREFAO+eKT005wlsy8zmiu+2uMy7IwkJkQGzuKyxCmFvTG7G8YN3OwtGLWKyC221Hr6voKgbEPGKhfkNYZrlM4Wmm8C1jQACAZZN4maaJf5puX8wRza6iAyZc1pr7uHiA6NAYWcWAAPR7/SxjQADigK/mHFloyehuhdA+0l3cRzS3VGfTCbYQtGQa+3IkLCx06r9oiguysFjFgAD4w9Y17MQZEPPVrG5XUYuxZBY2hILeVsjeCuEyy7Yx80ljRP1rskpwCNC/ITDBoYUcYYeGpmdjU9tuAW5nMLem4pN7QLTmPu44/Daqo/hcxYAA9COfHG6fzxFLM2KxqiWjG/kcU0tmIUfmLyjqX5N2iK65voXmoUVUS7/Xj664IAsL0m5fFBwC9EOYzHJ5ATmB5tsot1yeR04szf4L3HL50L5/I963Ditq0XJZZEAA+u3K60sYEIB4aOiC2/fnyGg0wu++8XUAAEfTOoglM1rIEbH41DGH0w33kTY25xgQgP59pMng9vkimBefet6/xdFyBJYXn3rWQTkyXsgRsficTdX7QVFrt2015towgBlLe12RqbB4wxveAMuy8LKXvUzScvQE77819v0bySTrQCzmPSAWbhpMP0JvS8ZZ2BC4Y6SmiX+yXF7o0QKiG6D614RbLjf3/ZtOu3KRAbHYkgHliCYdCzbdLrjwuq6LOz/3WQD6EAtvsN8nhEKnY2Q/zJHukhzReRt1ZzM0iQFxaOGC4uhFLCrT/TkSLEOz+VeYI4stGcu2MfX1DdYynaKlOaJ3CFxnpC4sPve5z+H3fu/3cOWVV8pcj5ZYxYAA9NqVr2JAANBu2rOKAaHb/GslAwLipL16xGIVAwLQ2y5bxYAAIOSI3un2RQYE6VjoyhESpVqE2wG9Pi6rGBCA3n1kFQMCEFEtPc9mFQNCt125tReVI/pQrRFZRyw5a/JWyEL0+3284AUvwP/8n/8TW1v7X7BzPSbdEG4vRmwIGiBMaskM/MocAwLQ3xtllssLNx7dSnXFFS0ZQK+2PrNcXoKc6PRxoRzpLlguA9A+8U+iVLVDKwoLTUVwcRQcGktzhAlTqYe5Z71gH1lsyQB622VMlMqqzw0nAtBefDbDHNlcyBHm0aFpHaVwH9k3FA9xH1F/QZlR224JumbC60dXpCosbrjhBjznOc/BNddcs/Zzx+Mxut3u3H+mwwtFqZZBqTqnqLnl8n6YjLsBqt+sV9lyA/odI7ng0P4NQWcrZBUDAtCrDcA9IMzmiCg41FjIkalmxIILDq3OER0w9zJbbgqt+whjQETkiIZ1zKYTtNAHMC9uB/B9xNYkt04smeKyfUSjKqoftnZnS/YRT7PQns5IXFi8+93vxhe+8AXcfPPNsT7/5ptvRrPZZP+dOHEi8SKlx3A5AwIQb6PqHzZZLu/zCQFYb9TW0H8TGRBbR+dbMkQ31eUYuYoBAQimPRpuGswDYgmUqvOmwS2XW/v+Tac2QOfsg7BXMCAIsdAlk1wLXXgXGRCAcBvVoFEQ1ZLRiWqNybp9SY4QYqEjR0QGROvwImJBUtp6DtFNypHW8X3/phP5JOsIbwm6xnVoLnDE4v7778dLX/pSvOtd70KlUln/BQBuuukmdDod9t/999+faqEyYxUDAhBvGjrg9tUMCJ28b5EBIVouA4BT1Kutv4oBAXB42dWwWcfJEV9D33oVAwKA1lYIwe3LGBBkQqYLseAtmYv3/ZurEbFYxYAAhOJTw7NZxYAA9JoIigwI23Hm/k231knTX86SAcQLivp9pBjRktF5idUdhfWfwuPOO+/E6dOn8YQnPIF9zHVd3HHHHfjd3/1djMdjOAsJVS6XUS6XF7+V0SiHPiHOguAQoNcx0lshSgWAIxYa3oiivn994d8KGoc3meCQNe8BQeEyCVz1b8RVgkOA3uJzpQcE9BafJDjUsVtoLfwbeYUUNMDcUYJDQDhj4espPlmO1PcjJx7zcdHQyhwsF6UC9LZCBuE+0rVbWFwJt7RXnyOT8QgNDAAsGXgG4EJfC2IjbNsVG8tyRK94mc5IVFj823/7b/FP//RPcx970YtehEc96lH4lV/5lX1FxbkatVWiVABzjNQBc3PL5f1Qqq0RwuSCQ/sHFUkgy7F8eK677yYiMzpnT2OL4PbDSyBMOjQ0tEJWCQ4BYitE/bPhlsv7c0RnK4QEhxan22u1Gu766n3A2x+nBdVq75zCESBkQCxBtTTeRjdDDZpKa8k+QjC3BgYTb8nsvxVbGveRcSe0bl8yFE9D4DpaIe3tkzgGYOo7qLeWsctsbfsI5Uh1SY7obJfpjkSFRb1ex2Mf+9i5j9VqNRw+fHjfx8/lWKXvDwA+SWlruGms1PeHXtMebrnc2vdvjuAYOZtNUVJYWHR3TmILAQOisciAgGjao35zanjLvWQAsBaEjpsGWS7v85KBXoO4WTjwPFp2aFCuaig+ezsncQQBA2KrsH/7ouJThzAV5cjmsn2EtULUP5sSswU4N3JkvIRJxe3K1SMWvZ2gsOhYdRxZkouexnZZ0wsQ2EWfEAC8+DyAiMUFp7wZKTgEMMRCh5rhKstlQJDS1tGCWKHvDwAFYfNWPewUxYAA9NmVzzEglkCpzHlWw6FRYVDqkhxhlvYa4PYIBoROS/sBa9tF54jq4nM6GTMGxLK2Hc8RfW27pTlS0HdBYQyIpftImKth8akySJRq0SeEgu8janN1tDdA3doDADSOXLrv33XuI7ojEWKxLG6//XYJy9AXvfY2mis8IAC9NDHWklkCk5HBlA4Ik+D2ZS0Z0VV0Op1gQ+E6mODQkpYMoE8boL1zCofDlswyuN239RWfTJRqWY5obIVwwaF5uH00GuE//h//B/48BCxn0/F+vQ2JESU4BOhrhXS2g5ZM4AGx/0CHxjmcKAaEzn3EiWDJ2HP7yBhlp7rvc2QFMamWtWQArnWifB/ZPonjACa+g0YzQsfiQmeFHIRoh5PLXVT3MSAAMFdRHVPUDcaA2F/g6JyiZqJUSyaXi0IrRPVmTYJDy1gygD4JXGJA7GKJ4BCgtRXCBYeW5IijD9VaJTjkui7++n3vY3+fKdYYmUWxZCCaf6ldR4dyxGoubf3w4lP9s2mSU/OinDf0tkKKrCWzv9DSiXySdfu4vB85AfS1QnrEpLKasOwlR+0BHt684AqLAcFkK+B2XQ9bbMk0ltyKbY2OkeUlHhBsHcIbQjXM7fVJ33/VoaGnFcJyZAXczgziFG/Wc4JDyw4NjcUn9wnZf2hMhR+vuvj0yYV3TY6oLj6HZAuwJkdU7yMBA2IIYL91O6BXSnsjom1XmJvVUvuaxM4RxfvIHuXIMp0i8FaILrl1nXHBFRZRDAgA2uzK5yyXlxYWZDOsoSUTwYAQTXtUT1FHMSAAfa2QVQwIFppaISQ4tIoBwXxcNOTI5mw1A8IH4PlBLqt2nnVWtGQodDlGRjEgAAgaI+rhdmA1A8LSuI9EMSDm7MoVi5dRSwbrckQxY2ddS0bXPmIiLrjCgsRklvmEAKJMsto3Ilkud5Z5QACwmauo+ilqbrm8hAEBfVLaJDi0rCUDiLdRxYN5DG5fsSGEQ5Oqh6644FB9n+UyoPc2SoJDy+B2gKMWqmHuKMEhQN9tlMHtK1oy0CRMxazbl4hSBcvQ507con1kGXLiOHB9C4B6jRHGklmCwAL6csQlnaKVOaJvwFd3XHCFRZTgEADhpqH2jSiKUi1dhqb++Zzl8uH90+2APqW6SoRPCCAoXireEJjg0DLhMgAW3TQUF59ccGg53O4wxEJt8SkKDi0TpQK4rLfq4pPD7dG3UdXFJ7FkVsHt0DTxH2XLDQgzFor3kdHeAJvEgFiRI7qktKvT1T4hgL45HFCOLLGOAMARC11W8hrjgissmJjMiofNBWUUU5FCff/Biv6bLkEZslwGsM9ymcK1yGZYLXRYCx1WlzEgAH3Oszbp+6+AUpn/guLDa9yNbsmwdpniHOkIHhBLGRAQCwu1ObIZ5sgyBgQgFp9qc4R5QCxhQAC8+FTt9TMJ0bVVcDsvPtUeXtSSWcWAAATkc6r2Ndl0A+RkY5kGDcRWiOIcCRFYf0WOsFmtHLE4/yOKAQGAs0IU3zTWMSDsQjDspFpKey0DAsCMSeCqfSNGMSAADmGqhg6jLJcBfe2ydQwI0o9QniMh3L6KAQEA09AvRDWqtcqWm0IXzB3FgACgjV22jgHBWqqKc2QtAwKCq6jifaQV5shSnSJwuXXl+0hoHbFs4BkQfFzywuL8j3KEBwTAEQvVG0KUKBUAOGzoSi3MzS2XWys/x9UwYzEnOLRiQ9BlVx4lOARAW7ssSnAIEBELXXB7a9+/VatV9Pt9YCO4MassPkXBoeYSwSFAn/lXNcyR0jJbAIj7iOqWDDEgVuwjBb050nVWzCVBT0t12O+gao0BAM0lwmWAiHwqzpFQp6i4Ikeg6awxERdcYbEZYbkM6BMdirJcBvhgnupWyCjClpuC877VbQidbc6AaC6Tv4U+u3LKkaVeMhDmXxTnSJTgECDIJCvemPh0e2vfv1mWhVqtxp1nFR4aIgOi0Vp+kOpqhRADYqO5rvhUnCN7xIBYsY841FJVmyPk1DxckiMUOmYs2uE+MvaLqG0unzvR1VKth/vIqhyxNLoT644LrrAgff/aEn1/QPTo0MOAsJd4QABgbQnVboCz7mp9f/Y5Gih83XBQcRUDAtCHWKxjQOiCuTncvrwl42iCubkHxIpBRQAzDRojfZYjjZVwu6+pXRbFgAC4xohqYSpyal7FgHCopap4HW5vDQMCoqW9un2EXHh3I1oyOtSVfc9DKxQuWzUUr6ulaiIuqMJiNp2sZUBYmmhiUbbcAL9pFC0XvqeuuOCWyysGjCAOO6l7A4iWy6tCh6W9yIBYBaXqQrWIAVFaceMhxEJ18Rllyz0ej3H99ddj1A/E3pTC3JQjKwaeAa54qbL4HA37qFkjABE5ognm3gjh9tISW25AXysEJEq1QoMG4FLaKveRvVCnaJUoFaCn+BwOuqhYwXuhdXR58QmNqqi644IqLNo7DwYmOL61kgFhOXp438xyubn8VlwUBildhW/EdS0ZAHBpeFPhxD8THFolSgVwgziFNx6C22e+jcbWiuFNW89tlNtyL88RXcUntWT8JejabDbDH//xH2M8DIoxlTA3tWSGETnCik+F7xnOgCig3lilh6On+GQsmRUILHcVVZurxJLxayuG4iG0VBUKZI1Dtt1wlSgVePGpNEfOBDky9MuormjJ6JrDMREXVGHR2wlFqazVDAhd/fN10+2iaY9KKe11DAhAD2JB0+0rRanAJXBV3kbXCQ4B+hwjW2vadqJMssrikwkORRwa07CuUdm3JsGh8Qp9EQCApb5vzRkQq1syTJJfU44sk3wHhMLC8pQWn4wBscS6nYJcRVXmqhu27SYROaJjH+mdpbOmsfJzdLXLTMQFVVgMQu32lR4Q0GPaM52M0Qzh9voSqWZgQQJXYWFRocnlFT1aQI/5F9f3XyEmA2gZiNtrkwdEa+Xn6LiNioJDqxgQ4iyKyuKTwe2rptvBdSxUFp9xckTHHE4cBoSlobCIw4CgORxA7YG+lgEBjlioLD6twWqnZv5J6m0bRuQTEoGu2XbeCjkQEYcBYWtohRADwo1gQIiIykyhoEyU5TIFb4WoeyMyBkTErZhBmAo3hCgGBIWODSEOA0IsPmcK4eV6CLdvrBAuA8TCQl2uFhjcHnFoaCg+SZQqCm7XUXwSA2IUwYCYKz6V5kiAnFRXiFIBwoyFwiLYCRFYROQILz7VrWOyxjoCEIrPnBVyfgcJDkVNt+uQ0u4IUOoqBgTpWABq1QzJcrm2QpQKECVw1b0R1zEgAD7boPLQ4C2Z1bdiHZb2vZ310+1i8alSY6S1RrgMAKZuIJClUhuA4HZnlSgV9Ez8u731LRkdrRBiQLStVqwcUYVqiQyIqBxhLVWFz6Yc7iPOClEqAFp0aHjbLmof0SO3biIuqMKCoNRVolQAf9gq3QCHrCXTWr0O0bRH0YYgWi63jqzeEHwNEriMAbHCAwIQDg2Fz2ad5TIg3DQUaoxwy+XVbTux+JxNx2rWMegxuL0RkSMMsVDakmkDAEqrhMsgagMo1CgIc8SN2kc0uIoy4bKIHNHhKjrodzgD4shqxIJUUVXmSJWxZOIUnypbMmGObETsI7Y+d2LdcUEVFpwBsfrwYjcNhVXkWsvlMEhKW1Vhsc5ymcLVYP61jgEB6BGUiWJAsM9hh4bKHFnPgLBsGzM/eAurmm1oh8OsUQwIgBcWKuHlOlm3rxhmBcTiU92zIVGqKAaEpWEfmTJRqtXPZa74VLSPdMIciWJAAHrMvxpk3R7RktGxjxTIOiIiR+ycbnowgjMgVh8aOmBubrkcXVi4IPMvNW8AZt1u1VcyIABBqU7hG5Gm21eKUgHcilohhEkMiCi43Q7hZZWHRiwGBERLezWHRi80IFvVkqlWqzh9+jQOf+cTAag7NAK4nRgQywcVAQg5op4l40QMPDs69pFQznsSAbdbto2pr5bV1SPhsoiheED9EHiQI4GeyiqfEADwya5c4bOJ05IhH5e8FXKeB023r/SAAEcsVArKcMvlCAYEBNOemRqYm023R7RkAMHYSdHhNWe5vIIBAUDQ1lc53b7GJwSCTLJKCJNZLkcMKkKUSVYDc++1A1RrleCQZVk4evQorGIlXJCaHBkOutiwgt9xpeAQ9NxGCW4vr5LzhnhBUbcOzoCI3kfogqKqXUYMiH6EKBWgfh/pdXdRsoLXO6q1y+zKFbZ2qzPKkdXomo52mam4oAqLWgwGRKGgvrBYZ7lMwdgYim4a6yyXKVQr1cWxXAagZeKfWS5HMCB4u0yhKBWzXF5zaCj26Bh3gsMrCm4H1GuddAQGRLW2WhtAh7ETZ8ms3kd0GMQVyCckiiUDUUpb1T4SOjWv3UfUsrqoJTPwK6hUN1d+ng5V1EaYI9WItp0OdNxUXFCFRZNNLkdsCBokcNdaLoehuhWyznKZQrVMchzLZUDU1lf3bOIwIBwNxWccBgTAWyGqDg1vDQNiPB7jhhtuwOlv/mv4BapyhITLVjMgACFHFK3D9zxsMS+Z9TmisvgsTWIwICAin2qKT4+8ZNbsI55iP5kB7SNrWjKqvX7itmR0oOOm4oIpLMajIWNANCMfdtD3UukYWV1nyx0GtxlWA3Nzy+XoPr5qV1E+3d6K/DzV2gBzgkNHV/fxmfOs0pbMelEqQGiFqNIoILh9RdtuNpvhf/yP/4GzJ78FQB0lmQmXRWjQAGCIhaocGfQ7KMdgQNChodKduEosmbg5ooqNMSQGRDRywnVoFOVIKOfdjxAuAzhiYStaR7e9g6IVnB9RLRltPi4G4oIpLOIyIJyiem19YkBUI+B2QJTAVfMG4JbLq4fQAFECV81rMmGiVNEbgupWiGi5vFlvrfw8h9001N1GmeXyuhxRjFhwwaHoHJl5gY6FKsRiEoMBAag3EYzLgNABc8dhQADiBUXNPsIYEBFD8QBvqaoa8GU5EqFTBEB5u6yz/W0AQBdVlCvV1cvIEYvzP2i6PcoDAgAKGh520wtgslWWyxQu1NKzmAdExHQ7IPZG1WxMbjioOFnDklEtOhTHlhtQX3z6nidYt6/JEYK5FRWf5XFweK3LEeYVoqj45DkSfWioboX0YsLt3NJeTfE5z5JZV1iobUGUWdsuOkc8xeJlXsikmpbXFZ9qWyG0j3StmDmSz1icv8H1/VuRn8dmLCwfniv/gY+GfcEDIoI2Bz4Qp2rinxgQqyyXKZQ7RsZkQKhuhaxjQFCodoyMy4AABMdIRbdRypEoBgTAdSzgqslVi8Ht0X18S3ErZC/cR9YxIAjmVtUK6XbOohQDbgcA16JZLTXPpjZdz4AARMRCTa7aMVsybB9RVOCMQuv2fpRTM4SWao5YnL/BBYdakZ/nCI6RKgRlRAZElOAQoB6xYJbLrehDA4pvGsxyeQ1LRrWrKLdcjr4VF4h/rqj4JMvlPb8UzYAAb5epUkXlDIjow4sQCyhCLBgDYs2tWLVj5LRHLJnoHKHbaEERYtENkZO+vxHJgADEHFHz/q17631CAPVy64WQSWWtyxGGWKhZx7Qb5Mg6lgzJreetkPM43JgMiILg3aFi2CkuAwJQT+FjlstrWjJ8Q1DzBmCWy2um20kCV9Wh4bLp9uhDQ7WlPVkux8kRV6GaociAWOXCS6F6xqIcQ7gMUK9m6MWw5QY4bV1V8RmbAQEB1VJQfHquyxgQjTUILBTvI+VwKH7tPqI6R6htt0aniOnhKJzVMhUXTGHhD4LDa50olSMcGlMFk/bDcLo9ynKZginVKTi84lgus2A2w4rg9nBQcR1LRnUrhAkOrWHJFOYcI+WLDo3a4XT7OgYE1LZC+r22IDgUnSOsFaI4R0prWjK8+FTUthvGsOXGfPE5VZAjtI8M1rRkAKH4VFEEt7cZA6J5eF0rRO2sVi2GcBkgFp9qcsQOc8Rb07YTi0+VJoIm4oIpLLi+f/SGUBRaISo267jT7QCHMFVI4MaxXKZgEriKbqNxGRCsFaIIOozLgCjMtcvkvyZJcsRTOGnfOcMZEBu1+tLP2djYwL333osnPPOnAaiTW68zwaFo5ER1K4Ss29cxIIpzzrPy37/TbkwGBNTqR1Brdx0DAoDylmoj1KCpbkUjsFYoKaAqR4qMJRO9jzhzzrPqHKxNxAVTWMSdXLYF6FkFzE0tmXUMCEBtK4RbLq+H21XSs0TL5frh6Fuxpdj8q8xYMtE3HtExUkXxST4hUR4Q7Ocr9F9gORLlwmvbuPzyy1Eheq6CQ2O+JRN9aLDbqKLiMy7c7sy1y+S/JgS3T9e0ZACOaqkoPgfhMGvHaq39XKKtqyg+xZZMlE4RoL4VUg6dmgtrENg551mFjq8m4oIpLDaYnW70rdiybUx8hWwMsuVeA6UCarX144pSARD0I+SvY85yeQ0DgvG+FUGY1ZjT7bbjwAst7VXcNCyWI/ELCxUFDhOlMpwjcQWHALH4VJMjcRkQqu3KGQNizcAzIF5Q5K+DMyBa6z/ZVtdS7Zw9DccK5nyaEcJlwTIU5wi58K7Jkfm2e15YnJfBGBAR2u0UXKlOfuIxBsQauB0Q6FkKboHkExIHblc5dEUeEHt+KVJwKFiG2lYIZ0CszxGVrqLccjlB8angNjoNcyRqun0ymeCXf/mX8ZU7PwVADarVDeW8+/4GKhu1yM9VrQ1AcPvatp3jwA2LTxUaI+dajozi7CMKW6rMqRk1FEvlyM8ldWVV+0gzHIqvrTlrVCOfJuOCKSwYAyLKcjkMlUp1zANijeAQIMDcCjYEl023r78VczVD+esQGRDrgile+vKnqJMwIACxsJD/msRlQABiK0RBjrCWzGq4fTqd4k1vehPu/n8/Hy5I/mbdj2nLDQgwt4JDIxEDAmqltCvjeC0ZQO0+EpcBAYAjFgqKPsqRzhqnZkDQKlKwDnc2Q9PvAVjf2lVdfJqMC6KwmGdAxDg0FApTMQ+INf03gNM8VQjKxLVcBgDQpL2Cw4ssl3trxGQA0TFSQYEzZ7kc59BQJzoUx3KZQm2OxIfbiRWiwn+Bwe0xmFS8+JR/aPTa2yhYwS+6riUDCMWnApibWDLl5vr9jLdC5K+DWjLrnJqDT1anijqK6RMCCO0yBcVne+dUQDH2LbTWsGQAXnzOVHn9GIoLorAgwaE4DAhA9F+Q/0aMO90OqLUZjmu5DKhFLLjlcmvt5zoKBWVED4hVDAgxZjRpr+A2SpbLGzHadiph7mICuH0aPhIVt9FJeGjsxRh4tgvqckRkQJTKlbWfP1Mot84ZEDFyxFbXgkiSI2wfUbCOWS/YR0YxcoTaZSqGN0m4rGNtMgGsqGDuxDnd9PyL/i55QERbLlOomrEQ9f3XeUAAwqGh4I1YCieX11kuAxAG8xRAh/34LRlb4U1jwOD2VqzPV1V8xrVcZp+vsPiMy4AAuECWiuLTC5GTOAwIlY6Rg7N0aLRifb6qlqo7m8VmQAA8R1QUnyxHYiCwKtlljCUToyWj0vyLcqQbcx9RWXyajAuisGAMiDiTy1B3aMwxIGK0ZLhHhwIoNaYtNyCaf8nfmJIwIJhHh4KNKREDAoDHWiFyn00SBgSgthVSC22547RkqBWi4jZqU9suBtzO1QwV+PwkYUBA3YxF5+yDsRkQgFhYyM+RzbAls44BAXAfFyU5kqAlw31cFORIqEGTNEe8vBVy/sU0pk8IhauIwhfXcpnCVziY14hp3Q5A6U2DT7evH2Z1FMLcJEq1F0NwCBBaIZJvgWS53IvBgAA4c0gFYlFncPv6w4u8QlTAy8lyJGAEqJixIJ+QUcwcUXVBYU7N2FzLgADUenQ0iAERA4FV6dFRDH1C7DU6RQC/oKjYR2ahT8g4YY64qgweDcUFUVjMevEFhwDRVVT2hhBf3x9Q5yo6Z7kcA0pVKaUdV7gMUOsqSpbLcYTLAEFKW/JNg0+3x82RsBUiOUdEBkScHGGIhYIcqbCWTJwcUXcbZQyIGC0ZQLC0V5Qj3bg5YqlBPmfTCWdArLFuBwAo3EeS5AjRTQsK1uEP4rdkABHVyhGL8y6sYXB4xWJAAHChBl5mHhAx4XYogg4DBkR8uF2lBC6fbo/TkgkPDcuD78mlnLIciTPdDuHQkHygkwtvnOl2QGiFSM6R7u6ZWAyIjY0NfOlLX8ILfunXAajJkVoCBoTK22giBgTUKV6OOvFZMoBQfEqekWrvPJiIAWEpRD43XRKlipMjNIcjn7aeNEdUoeOm44IoLOJaLlOoktImBsQ6y2UKVYcGtWTiWC4DaiVwiQFRjXHjET06ZB/oxQRwOwB4iorPJAwIAIClpvikHOmiFsmAsG0bV1xxBY5d8pDg7ypyJGzJ1GLkCEO1FBSfxVGwj8TNEfL6kZ2rMxKligm3k5S27H2kFwqXdax6LAaESh+XZpgjm3H2EYUt1VK4j8RpyQDiJTZvhZx3UZqQ4FDSwkLuoRHXcpkFcxWVm3RkudyxG7E+X5UbYFIGhDPnKioXOkzCgADU3TSSTLcDYvEpdx2sJRNDuAzg/XPZWicBAyKA2xsx0DWawwHke/2QB8Q6F14KVc6zjCWzxoWXhSJX0UGoQRO3bWeHuSo7R6aTMZoYAIgnXEYCWSqKz8o0YY4oarubjsL6Tzn/oxpOt8dhQAAKq0jS94/hEwKocxXdSyAmA4isELkVfre9g2aClkxhzthJ7huRMyCSbQie5GfDPCBitu1UUYHHMafbJ5MJfvM3fxONzpfxPU35ipedsw/iEDEgDq1//4rFpzubxhpujBubrCWTrPiUjWolhdtVDW8SA2IQcyjeUrSPdLZP4QgA17fQPLT+2SwWnypyJA5LBhCKzxyxOP+CMSBiTLcDogSu3A2BTbevsVxmoWjGgtlyx4RSLUVqhiIDYq3lMjAHt8rWGEnCgADUCVMlYUAA6g6NaUy4fTqd4jWveQ1u+5v3AlBQfNLAc0wGRKGoDrHgLZn1RTCgrvgsJoTbVRWf1JKJy4AgpEB68Uk5YjVgO87azy8U1bmKNkOn5rg5oqr4NB0HvrBIyoAAOM1TdiuEGBBx4XZm/iW5BUEMiDiCQ4BoRS13HUn0/QHAccRWyFjaOjzXZT4hcaBUQJ2raCWJ4BBEbQA1LZlYHhDgrBDZjpFk3R43R1S5is6mE2whbMnE3Ec8ReqsG6xtF+9WzItPyWJuCdt2lq3GnXi4m0yUat5VVF6OjEdDNDAEEA+BBdTKrZuMA19YdDtnEzEgAMC11dxGawl8QgD+RpSNWCSF29mkveTbKBcciteSsWwbMz9IWZnQ4ZzlcgwDMkA0/5LckolpuUzBDg3Jz8YeBoeGH7Ntx7xCJN9Gx22C2+PlyFzxKfFAb4faEQEDIinyKff9u0k5EkeDBuqEqZw9asnEQ05sRUPgLEfiOKxCnasoSb5PfQf1VkzmkCI9HNNx8AuLECaLY7lMoUqYqh6KycSF25kboGQIsxCKyVgxoVRVjpHTUEwmjk8IhQq7csqRdQwIMVS1QhpJc0SR/0IxdM+M4yUDcK8Q2cXnjESpYh4alm1j6svvW/eYB0R9bo4jKlQVnw2yBYjhEwIIs1qSnw0XpYqXI+TjInsfmfVJlMps8UnCZR2rHqslA4itkLywOK9ikFCUChAODYlJl9RyGQCgSKkuKQOCzL9kC8okZUAAagRlkjIgAMGjQyKEmZQBAai7jVYSMiDIK0Q2zM3h9pgMCHDnWZntskFC4TJAzT4yGY8SMSAA8AuKZLh9IyEDgnn9KMqRWeyWDC8+ZV5QyDoibksGEOXWc4Gs8yqG7WSCQ4AameReezuRBwQAZcOb1JKJIzgECKwQyYIyBLfHZckAoqW9vA1hRDkSE24H1ECYZLkMIDbczotPubdAasmUY8LtJOktWxvASgi3A8AM8p8NZ0AkzxGZ+0gnvBXHZUAAopS23GfDWzIx9xHSj5C8Dt6SSbCPKLigEJMqbksGADwr1BjJEYvzK6Zkyx1XcAhcqU5mKySp5TIg2pXLfSMmsVwGOHQo+9BgolRxp9sh+i/IezZkuRzXJwQQ1QzlrYNaMruIJzgEqEMsuOBQvCKYz1jILT6TCg4BgGvJN4hLKkoFiEPgEnMkFC7btZqx4XZVXj9JRKkAde7EpTG1ZGIOxUPNPuKG1hHjmNYRAG+XqfBxMRkHXseCwe1xRamgRlt/sEtwewvxZKlE3re8pGMtGSue5TIA2IpaISQ4FEffn4K1QiROc3v9hIJD4DkikyY22OUeELHLYBIdkvhsZtMJWugDWO8BUalU8NnPfhbtb/0L8MWXoCCZOVRhOZL80JBZWPjkwpskR1jxKRFuJxdeu4m493OLCVPJW8d4NETd2gMQfx9RZWm/kbBtB/DiczaVmSNBEZwoR3JWyPkZjAGRACbjaoby3gBJLZcBKGmFzDEgYlguA4BDOhaSb6NJGRAAFy+TedNIyoAAAE+BfkRSBgSgBuZOwoBwHAdPfvKT8ejHfU/wd2Vwe/wcYa0QiYVFUgYEoAbmTsqAAKCkXZaGAWGT86zkwmIziVNzGLxdJj9HkCBHVDrPmowDX1gkFRwChME8iRV+XMEhMVTQswhKjSs4BAgSuJI3hCazXI45TwAB5pa4IRQTsmQAAbGQWHzyHElSWMgvPrvbJDgUnwFhF9QUn01iQCTIERVqholFqaCmXUZOzXFFqQA15l+9hKJUgNBSlVx8tmgfiYmcAEIrRGLxSTpFdgIEVhW7zHQc+FZIZRzfTpdChV15UstlQE0rRLRcbsX8Gur3yyws3NkssFy2gPrhmNPtUOO/kFSUCgCbtIfEaW5uuRwfObEUtEIGZ/l0+7psnUwmeMtb3gLs7eCXAamtkMl4hEbIgGjGZUAgLD59uYN5BLeXYsp5A2raZUltuQGBLi6xwBlSjjgtxN1ZqfiUuY+Mhn3UrBGAZDniKWiXbTCdovjIiYp22bkQBx6xqCawXGahAJ5Kqu8PqHEVHSX0CQF4K8S2fHiunLXMMyAStEIs+RBmLXRYjesBAXDHSJlW1PZecOPx4vqEQI1j5Lgb3wNiOp3iFa94Bd70xjcCAAoSEQtiQMx8G42tJMOb8ttlmyxHkhwa8vcRJ8wRv5qksJBPWx+H6NowQWuXLigyWyHUkpn4DuqN+HvaTMFsA+VIpZWm+DxYiEWiwuJtb3sbrrzySjQaDTQaDVx11VX44Ac/qGptUiKJ5TIF3xDkvQGS2nID4m1U3jqIAZGoJaPA/CsNAwJQIyiTlAEBiO0yeetIw4BQ0S5Lw4BgrBCJxSdr2yWA2wGxFSLv0EjKgAAgXFDkPZs0DAgVF5Q0DAjKVZnFJ2/JNGHZ8Y8zTwFjh1oyca0jgHzGAgBw2WWX4Q1veAPuvPNOfP7zn8cP/uAP4nnPex6+/OUvq1pfpggEh0iUKvnDlum/QKJUSSaXmVKdTFZICsGhomDaI0t0aHA2mb4/hexWyHQyZgyIuB4QAIRDQ35LJkmOkOy7zBwhuD2u4BDABbIAYCopR0hwqJcwR1jxKSlHRnsDzoA4cmnsr1Mxq0U+IXGdmgGx+DSbIySlbVu+NBNBJkqVAIEFxH1ETrts2O+gagV5n6QlowIdPxciUWHx3Oc+F89+9rPxyEc+Et/5nd+J17/+9djc3MSnP/1pVevLFJ2zDzIGRGzBIUDJw2aWywkml20FUtq8JRP/VuzMIRZyXpNRTFvuxZA97NTZFgWHksDc5OMi79kwy+WYgkOAmlaIQzmSAF2bCj9eVt+aCw61En2dbPEykQHRaMU/SFXsI/UQbt9IsI9YDl1Q5OVIgVoyMSXfAa7gCwAzSQc65cgwCUsGvF0max9pnwlyZOQXUdtMoOCrIEe+9sVP4Ntf/wpmEin5SSP1jIXrunj3u9+NwWCAq666auXnjcdjdLvduf90BWm3t7GZCG5XIShDHhC1uB4Q4BCmzCnqpPr+AFAo8NdOFlIw6ybT92c/X7L/QpfJecdnQADgw5sSNwRiQNRiCpcFy5BffJJPiJ3g0JgJ6Las4pN8QpIwIAB+G5V1aNDAc9tqJILbVRSfaZhUKloh1JJxErTt5pxnJe0jbCg+5T4iq/js71KOJGvJQHJL1fc8XPbX1+LSP3kqTn/r61K+Z5pIXFj80z/9EzY3N1Eul/ELv/ALeO9734vHPOYxKz//5ptvRrPZZP+dOHEi04KTRFJbbhaSWyGz6SRgQCAZ3M4lcOUdXpWElstAIGzj+RYAeTeNNAwIQL5duciASBSScyQtA8JS4L+QhgEhFhayxMvSMCAA8dCQBHMLDIhEwUwE5eTI3qCXigGhwqMjDQNi3q5cUnuIhMsSaNAACloh1LZLmCO+ZAfrQb+DihW8tq2jCVq7kiNxYfFd3/VduOuuu/CZz3wG/+k//Sdcd911+Od//ueVn3/TTTeh0+mw/+6///5MC04So07wsJMIDgGQPnTV3nkwGGpLYLkMqLmNkphMEsEhAJhBrkxyGpYMIL8VMk6bI5Ll1gluT8qAcBT4L/AcSTDwjKCdBMjTGKGWTBK4HVCRIyHcnjhHiDkkqyUTDLNO/EIiBoRNrRCJ+0idhMsSoGsq7MpJlMpP0LYDhFaIpGczTdmSke1OTK3dPb+EaoKWjOxIrGNRKpXwHd/xHQCAJz7xifjc5z6Ht7zlLfi93/u9pZ9fLpdRLscTYpIdbLo94cPmvG85yd/beQBHEMDtWwngdjL/knlosOn2BBsCQIIyLlxJN400DAhAvI1KQpPC6fZRAn0RAIDkm0Z3+wEcQwC3H0nAgLAU+C+0vA5gxWNAVCoVfPSjHwUAuB/993Awk9bbZQyIhIcGa5dJyhG3TwyIpDlCiIWcHOntnMLFCHLkWAK4nQTuZO4jLT/IkXWS73PrcBy4vgXH8qWhWmXSKUrQ2gXkS2nTPpJEpwiA9Dmc3lliUjWxIeU7povMAlme52E8lmdPLDO8QXIPCAD80JD0RhzsBtVsJ4kHBDh0KOvQmE7GyS2Xw2BugJLeiBWyXE4gXAbIH3ZiHhAJNwRL8qGxxzwgWrE9IABBY0RSro72BtgMGRCNGMJljuPg6quvBgAMP+qghBk8STMWDG5PwIAA5PfPuU9IspaM7H2EcqTrbCGBlJv04jNgQASFQSIGBIILioMZZpL2EWbdnjJHZIkgWsPgopTEqRmA9OJzFJ41vcIWzDVCEhYWN910E571rGfhIQ95CHq9Hv7sz/4Mt99+O2677TZV68sUaRgQgOgqKpcBkRRutyUXFp3tUziCZJbLFK7k2YY0DAhAPsydhgERfKHcQyMtA4LN4UjKkfb2SRxHCgYEBEt7SYdGGgYEAHi23BZEGgYEIF9uPS0DwinIZYW0z5xEFckZEEBwQZFZfFKOVBMMxQPc60dW8Vkgn5CkOSK5+JyQm3fSlozkSFRYnD59Gi984Qtx8uRJNJtNXHnllbjtttvwQz/0Q6rWlynS6PsHXyB3Q0gjOATwVogsCdzOzkkcQWC5nARuB+Q7Rjb9NgCglkCUCuAQpiyYmzEgEuaIbLty1pIpJTvMHck+Lr2doLDYtZqx4PbpdIrf//3fBwD8B98GLMCTBHO3vHbYkjGbI6XQA8JJIEoFQGCXyckRr5euJcP3EVktGYLbWziehAEBoficZUe5fc/Dlt9JlSOeZAfrUjgU7yRw4Q2+QO4QuJvCOkJFJCos/vAP/1DVOpTEBmNAJHvYtmR42e+TmEyyh10oyp2xGO4GA4JJLJcpXIlqhuPREA0MAQCtBMJlgPxWSJWJUiW7Fcs+NPw+TbcnKyxs2TC3MN0e510zmUzwkpe8BADwU78RML5cCbfAvUGPCQ4lEbcDxMJCUo4wBkSyfYQXn5JmG0KWjJuwJcPtyuUoXrK2ndNEMpxANP/K/mz6vTbqxICI6dRMwXJE0j5SS5kjsqUNrEG6fUR2HGivkBrTbk97aMh52MwDImFLRvahMQ59QhJZLofhSnSM7OwEG9PMt2NbLlOQtr6swqLG4PaEh4ZkYSo23Z7AAwIAHLKilgWldpJ7QFC4Egfi0jIgAPnFJ2vbJRx4lu3R4YQaNEkZENJntcgnJMM+IqP4JFuAoV9OzICgHJFVfKZtybAckVR8pnHzVhEHurBIpe8P8dCQk3RpGRCFYnBoyIK501guUzBjJwkwd1oPCEBwA5S0IZC+f+IckYxYcMGhZAWO7FZIagYEhENDQo6QuN1uUsEhCMWnhALH97yAAQGgfijZoCIkS2kTA8JJOPBMdNOCpHVwBkTyWzFvqcrIkdAnxE5Oq5Qptz6XI0lsASB/HyHr9sQtGclxYG3TJ+MRY0AknVzm/gtyNms+3Z60JRMeGpYH3/MSb7CL4ffTCQ4B4W3Ul3PTYPr+CRkQABeUkQFhzjEgEnhAAPIRi+o0uU8IwFVRpdFNqW2XdLod/NCQcQvca4dtO6eFhHijVBPB4aCLWsiASCo4ZEse8KUcSeLCCwAOtVQltUKscODZ3TgMz/MwmcQvEsabD8EIVcxmLkajUaZ1DDtnMdo8gY5zOQ4l/F5+7SKMvBOAU8m8jl5nF/X6JRgB2KgfSvb9yg2MNk/AKm9lXgcAlMsVjIonUGpdmur7FYtFOAkve8viwBYWnZ1TOIrkgkOAfAncGrNuT7ZFzkngujMU7ASy5EsijeUyBZdJzl7hT7rpWzIkgStjaJIYEBPfQaOZcCBOsvPsphvceDYSQqmkUSCr+GRwe0LhMkBu8TnuBAVOGridwdwScqSzfQo1BAyIaq2R7Isl7yMsRxIyqQqO3FYIsWTQvAz33HMPPC9+wTL7vldigBmmhQbuvffeTOuwtx6Ke7/vtzGxyom/V/G7fwb3es9DpVDPvI7ZdILt7/tteLBgnzqd6GtLl1yJe4/8NqwUv8OycK/6r7gXHqzqsdTfr9Vq4fjx47AsK/U6Dmxh0Q0Li6SCQwCnecqCMIkBkRRunzPtmU6S+Z0siWIKy2UK1gqRwArJ0pLhh0b2dRADoh2TASEG9UZtSX18xoBIWFg4go/LbDZFsZRNjI4zIJL3aGU6z6ZlQAAQ/Bdk5Eh6BgQrPiXkSBYGhOziszQ5Cx8Wipd+DxzHwYkTJ2DH/J6T0zOUMMWodhkqSQu1hRjsnkJtWsTQrqN6JJlVxGC7iJrXxaC4hdpWNsWH0aCHysDFBAWUjj0s0dcOu2dRHRUwQgWVhF+7GL7vwz+9B9sCpq2HJ94LfN/HcDjE6dPBe+/ii9O/Lge2sOAMiORwu8zbqMiASGK5DMwjFjMJm3U1heUyBRMdkrFJpmRAABCowBJg7oQMiPllyJNbn7NcPpqsbVcQLO1dCYVFNaUoFcARCyk0z5QMCADwJUppMwZEoZWYAWFJZJdlYUA4RZ4TMorP2nQXs1ITzuYRHD16FNVqNfbXWgUbZVjwSiVUKpVM65g5QMW3MCuWE3+vWamAyszCrFDIvA53PEClYAEoJv5e7riEysyCb9nZX4/ZFIVigDKUNjdh28lbGhsbgV7n6dOncezYsdRtkQM7vDlupxMcAviGIGPSPrXlMuZNe1wJ9CzygEgqOATIdYwkBgQSsmQAuRP/EyZKlRxulzmH0w71/cd+EZv1VqKvdSQXn/WwbRc3R8rlMm699Vbceuut8KxgLTKKTycceEaa6XbWLsv+bCZpPSAgt/jsnAmQkzQMiIJgIyBDh6butuEWN2E7BZRKyVBUHyG87mef92DtUDvN/Zhgfj/zOqiQ9lIc5BZ7PbKvg56t69upigoKKhSzGMUd2MIiC9zOWiESBGWYdXtCy2VgAbGYZheUaXqBZX0Sy2UKplQnYWNiHhAJp9sBURsg+zqYmEyaHJHoGEkuvGkYEHNzOBnZGL7nMev2egw57+DnF/Cc5zwHz3nOc1jRJyNHyuOgCE6TI7z4NJsjVHxKyRGy5U7BgJh3Fc2eI4FPiAXbdjL04bMfpDQUSzNx6ZaRfR10yWFspCQRvn6WhNeD3ndE+04bWWYrKA5sYeEzn5DkUKrDDg15cHtiy2UAlm1j5gePKKt+xGjYZwyIpCwZQDB2krBZMwZEmkODYG4ZA3GMAZE8R0hKW8ZtlBgQfSfFoSFsqlkRi+Ggiw3mAZG8+HQlClOlZUAA4HLrEpATkQGRNGyJzKG9cB/pp9hHikIrJGvR1+2cRckKfp80t2I/PLRknOdUsBHCnCgseYgFKyzSICcSDnG2DFdOYSEjDmxhwe10k0+3WxLtylNbLochS0qbWjJpBIcA0TFSRkumDSA5AwKAVNMezpJJniO2xOKThMuGxTS3YhtTX454WftMkCN7fik2A2I6neKWW27BLbfcAi/cTmQUn9wnJMUAGW3wEp4N84BIMczKFHwl7CNclCoFuiagYFmLz+72twEAA7+ScghU3oFOr6udprCQuI5lLZnrr78e1157Lfv71VdfjZe97GVLVhEfsVj1PShob06FnEgO8ytQFGktlwHOxpAhKONmmW5HYNpTxjSzoIzoAXFRig1BpugQ2XInFZMB5Hp0EAMiqeQ7IBjEScmRADlJmyMubBThZm6XiZbLF8ed8p9M8KIXvQgAcNfrnw4A8DMeXiIDon44Q/EpIVfLKYXLgmXIa5eRcFkaDwgqPouWm/mCQm27nlXP9H2yQha+76Pgu4A13+pZF9dffz3++I//GABQLBZw4tJLcN2Lfh6/9mu/NjeLkiTsGMjJX//1X6NYXPLvS5CT22+/Hc94xjOwu7uLVqu1/ntQsJaMecTiwBYWGxkYEPymkX3AyB8Eh1diy+UwXEsOYjFk+v7JBYcAeVbUcwyIFC0Zma6i1XBQManlMsBzRIY2gEUMiBSiVAAwQwHANHu7rB0cXmktlz1JcusBAyL4Hq0UOWIpyJGk4naA4DwrYR2pbbnDmMFBEW7mC8pemCN7TrrCwpc0rOi6MxTCb+UkLAh++Id/GL/7pt9EYfAA3vvRL+DGm16FYrGIm266ae7zJpNJrOFUO8asx6FDKwpCNmOxPlZ+D4oQKUzVkpEcB7YVspnSchkQZiwkHBpZWjKAPI+OLNPtgDyPDpEBkdRyGZCLWDAGRIpDw2ET/9mLT8aASCFcBgCuFbyNsxaflCN7KZhUgLziU2RAbNRSHGASvX7SekAAcr1+SJTK2jS7j0yZLXfy924QcloQjAGB5AyIcrmMi44fw0MvuwQvvv4/4JprrsH73/9+1r54/etfj0suuQTf9V3fBQC4//778ZM/+ZNotVo4dOgQnve85+G+++4TFjPBja/+bVxy4mE4fPgwXvGKV8BfKJwW2xjj8Ri/8iu/gkd+12NQfthT8Ojvezb+8A//EPfddx+e8YxnAAC2trZgWRauv/76pd9jd3cXL3zhC7G1tYVqtYrn//R1uOfr3wTCoeFbbrkFrVYLt912Gx796Edjc3MTP/zDP4yTJ08mer3SxIEtLLgHRPK7ly2xFVJOa7kcxkyS/0LWlgw37ckKpQZJnYYBAYAdGlnFy4Lp9jaA+AyIuWVItKIuM5ZMuhyRNYfD4fZ0BY4s/wXKkbbdSvX1FhOmktSSQbq2HXcVzV5YVCbp23YALz5nGSiEAODRwHNpvrDwfR/DyWz9fzMfw6mHwTjG50b81x+OMJx66E2tfYd4vODIycbGBpMl/8hHPoK7774bH/7wh3HrrbdiOp3imc98Jur1Oj7+8Y/jk5/8JDugJ5MJfN/H77z9Ftzyl3+D3//938MnPvEJnD17Fu9973sjf/oLX/hC/Pmf/zl++01vxFdu/1/4H294JTY3N3HixAn8r//1vwAAd999N06ePIm3vOUtS7/H9ddfj89//vN4//vfj0996lPwfR/P/v/9Z8w8/noMh0O86U1vwp/+6Z/ijjvuwDe/+U28/OUvT/F6JQvzmImC2Bv0ULMCnfSklssA4DCYO/ttdCOD4BAg0VU0ZMmkERwCxEMjYytEEKVK0T2XBnMP+h1skuBQQg8IgCteyoC5SZQqqeQ7xQxyaJ5ZLZf9UMci64DvntC2SxWScqTb3kEzZEC0UuwjNjnPSigsatM2AAk5kvFiYDPhsnnkc2/q4jG/cVuC73Qq0zrE+OfXPgbVUsKjzAoKko/e8Qncdttt+M//+T/jzJkzqNVq+IM/+APWAnnnO98Jz/PwB3/wB4yG+Y53vAOtVgu33347fvAZV+Mtf/hnuOklL8KP//hPwLZtvP3tb8dtt61+Lb761a/iPe95Dz784Q/jB77vKpR3v4qHPPShKFxyJQDe8jh27NjcjIUY99xzD97//vfjk5/8JJ72tKcBAP74v78B3/Hka/CBD/4/eMELrwcQDFe//e1vxyMe8QgAwEte8hK89rWvTfZapYgDiVhksVwGBAlcCRvCJrNuT3fTIHjZzbghMAZESjtdLqWd7TWZZLBcBngfM2srpBO2ZNIIDgHC8KaE4jML3A4IUtoZD/SslsvMeTbjsyEGxF7aHJHUCumGct59fwOVjVrir5dJW6+HTs1pWruAcEHJWHwWQnTNqqZ7NudC3HrrrTj+kO9A5eFPxY+94MX4qZ/6Kbz61a8GADzucY+bm6v44he/iK997Wuo1+vY3NzE5uYmDh0KjMb+9V//FWd3tnHywW086XuuZOybQqGAJz3pSSt//l133QXHcfD0pz89Ne31K1/5CgqFAp7ylKewjx07VMd3PeKhuPuer7GPVatVVlQAgUw3SXarjAOJWPTPBjeetAwI8uSQUVgwBkRSy+UwZG0IzAMihXYEIAwEuVlbMqHgUMqWjCWpFUIMiI7VQHxBYh7crjx7S4Z7QKQ8NCw7MP/KOJjHGRDpcoRTkmW1ZFLmCNHFsw6RnuWiVJspvp6Kz6z7iOe6aPldwAIaaQaewYvPrO2ySpgjhdo8qrVRdPDPr33m2q8fnL4XNbeLfukoNlO0ICn629/G5nQbfaeJjWKyGYtnPOMZ+O03vA4t7yxaxy9H48Rj2L/VavMFZL/fxxOf+ES8613v2vd9jh49ir1+G0Aw6xE3SDYbEOimGVmvvuexAtYSZk4WWSSWlbZ1lCwOZGEhwu1ptmpqhdiWD891YafUSxcZEGngdoD7L2SFMDncng454a2QbJtkVgaELLvy0S55QKRjQFArpJARseh1d9HIwIAAQoM4PztiUZ0lb8mUy2W85z3vAQBYD/zv4IMZD3Rqybgp9EUAsV2WlSVDolTpbud0QcnaCununkHLCvIsTUsGAGaS9pFamCOlhSFSy7JitSP8ooOqbcMrOsnbF0J4BQ9V2PCK5cRKkbVaDY94+MNR2ytjuIaa+YQnPAF/8Rd/gWPHjqHR2K/tUsAEF190BJ/9xy/jmucHH5vNZrjzzjvxhCc8Yen3fNzjHgfP8/Cxj30M/+YHvh/AvI4FISauuzpvHv3oR2M2m+Ezn/kMnva0p2HmztDdbePuf/0GHnvFFZG/k444kK2QcUYGhOgqOs2gDZBGcGgxyFU0qzZAJsEhAL5Nxk4ZoVQSHErJkrEdOYjFhE23pzw0Crz4zOLj0gnbdgO/ko4BAdFVNBti0aCWTALJ90KhgJ/4iZ/AT/zET7DZhqyFRTFjS8aSlSOhcNleKV2OUK6WLBd+AmvxxaAc6aKGUjmdURVj7GTcRxrUkmmme//6S/6UJrL5hCC2lPYLXvACHDlyBM973vPw8Y9/HPfeey9uv/12/NIv/RK+9a1vwXdneOnP/wf89lv/AO973/vwL//yL/jFX/xFtNvtld/z8ssvx3XXXYef+7mfw/vf/ze495vfxu3/8DlWoD/0oQ+FZVm49dZbcebMGfT7/X3f45GPfCSe97zn4cUvfjE+8YlP4K4vfAE/+0v/Jy49fhTX/tiPpXtNJMaBLCwyWS5DnmkP6ft30jIgIKd/zvT9kdy6nYUk86/SJLjxOCmn22WZf5EHxDglA8KeM/9Kf6APzqb3gKCQIaUd5EjgJZOGAQHIG/Athxo0hZRtO158ZmxBkC1A6n2E54iXobAYhOhax0qfI3wfSb+fubMZmn4PALDZSldYsJmCjHB8HO2I6HXE+7RqtYo77rgDD3nIQ/D85z8fj370o/HzP//zGI1GAYLhzvBf/+PP4qd//Fpcd911uOqqq1Cv1/Fjaw73t73tbfjxH/9x/NJLX4pHPf35+I+veB0rIC699FK85jWvwa/+6q/ioosuwkte8pKl3+Md73gHnvjEJ+JHfuRH8PRn/CB838f7/vTt0SJamuJAtkJAYjIpGRDzjpHpN0nWkklhuUwhQ0p7jgGRwgMC4IN5WR0jmS13I2VhIakVwuD2jXSHRlFAtbIUn8SASOMBQUHCVFmKz7QMiNlsxqh1l0kqLLIyICwn9HHJmCOMAZGyJSMin7PZJLGQEwVryRRaqb4eEJDPDDnSOfsgDoXDAJuto2gPvp3iu8jRsaBnm1TO+5ZbbgEADDo7+9ZB/7YYx48fZ2qdi9F/cAeFQgH/1+tfi7f+/jtW/tzbb7997u+VSgVvfvOb8cY3/l8onP5SsJKLv5v9+ytf+Uq88pWvjPweW1tb+JM/+ZPg92mfQW34LexZfH7j+uuvZxoYFNdee62WGYsDiVgwW+6UUKpo2pNFP2KasSUDiIdG+nUQlJqWAQGAia5kdRVthNbtaRkQsmSSszIg5h0j078mTJQqhXsmhYxWSCf0gOj5GyhX4o+zjsdj/ORP/iR+8id/Ep4fwssZCwtiQKTNEescyZF5d+IM+0jIkhllyREmXpZ+Hd2dUF8EmygmtEvnIQexcMKhaTuBnPfcKsJlWBnXweZ4UiInlgCd+Bms5Klg9M4BOW/ggBYW5Qy23ABgOw7bJLPQPMm6Pa3gECAHsejtZBMcAiClFSK2ZNLC7bIM4phwWcqWzBzMnQGx8DIyIADReTb9syEGRCdTjmQ3iGMMCKRnQMhqhVSoJZMSXZOFfJIo1SQlAguIxWeWHAn2kUw5IsHN0/c8NjSdxCdkYSGZ1wHE8wmJXIUlFhYZipwsDqsK4kAWFpksl8OYIbtMMtP3r0g4NDIUFuQBkcaWmwUdGhk26153l1kup51ulyVMRR4QaeF223HgSig+s3pAABzVypIjNPDcT+nCC4gDvhlaMrtnUAgZEM00BmQAbGqFZCw+a5QjjXQ5Iqv4tEMNGi+lcBkgtEIyPBty4R1kaNvJaIXMyMXTz1BYhEqkcVxFo4K3ZLINkQJZC4swv/LCQl1susGtOC0DAuBKdW4GmDuL5TIFb4VkgNu71JJJX+Ag3Kyz3EZFBkSlmkYZQIC5Mx4ajAGxle7QALjGSBaYmzMgshQW2fUjGAMipU8IACmIhQwGBAncZS0+iQFRSznwPFd8ZsqRYB9J25IB+GBtln1kJqElw+uK9Icotfxcy0lMNWXLkANYsH0onXX7PGKR5TVh6JxtfnATOICFhajvn5oBAS54kuU2Wpqkt1ym8CW0ILyMolQAF13JcmgMWEsmPXJCiEUWmFuE29O2ZADu45IFXuYMiPQ54tnZhzcJbp9mgNtlSGmzlkwGBoQM51l3NkMrZECksQWgoAvKLMM+UgmZVMWULRkAcJnAXYZWJsuRDIUF4tE8o4Leb1TYG1uHhJZMIFgV/DkLYmGxlkyOWCiJfq+NckYGBMApfFkgzBrzCclQWEhohWCYTZQKgBTHyCFjQKSH22UcGr32NooZWzJAKDqEbMUn5Ug5pVQzIMeu3JaZIxnWMaIcycCAsCUwh9o7p2CHDIhmSkVUgF9QshSfNSZcln0fyVJ8WiEC66VkyYTfhVaU+jsQ6pJlUNFKKaUtBrXJM7VkIFjJZ1iLk5IloyoOXGFBk8uZGBAQWiEZCousHhCA2D/P0JIZhfr+KS2XAUHNMMOhQdPtwwxQqiPBx6UT5kgX1UQMiMVgcusZYO566MJb3Upf4PgSWiE8R9LD7XwOJ32O0MBzFrhdhvNsj/RFsIliqbzms1cHKz5n6YX2GmGO1FI4NVOw4jNDjhTDHLGz5IgEHQspDAgmkJU+mHV7hpYMwMuJLIgFa8lkKHBkxrmBm0gMkQGR/sgAPLpppHwjMgaElQ1ul9EKIQZEFridIxZZ4Pbg0JiW0yMWTiE7YkFwe9dqIp0eahDMrjzlLdBzXeYT0kg5qAiIlvbpn00lpShVqVTCO94R8PftUvDey6J1IoMBUZBgECcyIFqpvwvgMufZdM9mNp1gC2FLJss+ImF4c4PlSHoERwobIxxUzMKAkIFY0Nngwsl2kFpWsI6UhYXnuSzXsyAnMuPAFRZ7u6Tvn4EBgex25d3O2UyWyxQy1AxrGW25ATkUPntIolTpkROa+M8ymMcFh7I5NLoZ1Qw7Z09ji+D2LIWFjBwJ4fZKwhwpFotMhOezf/VmANmKT2rJ+FlypJB9wHcctmQGmXOEZrXSvSbtnVM4AsDzLbQyFZ/ZW6qblCMZ2nZp3TznvgWT885yiGZHLHwJLRmAt0LSIhbubAobYUsmn7FQEwxuz8KAAKdnpYW5u6HgUFrLZQpfwtBVI6PlMgBhMC/9OpjgUAYoVUYrJKstNwXN4aSd+O+GDIhOBgYEwG+jWWDuJoPb0x9ekODRQXB7Wi8ZgBefhQzrYKJUWXOEuYqmzZEQObHqqZU7AbH4zJAjNBSfgUllsf9nH1TMQq20YnqFRAVvyWQ7zLO2QsiraJaxJSMzDlxh4fWDW3EWBgQgHBopD/RBaN2ehQEBCDB3ytuo57pM3z+t4BAgGjulP9DL4XR7lpZMoZDdMZLlSBYGBDjMnfYW2CcPiCyCQxDbZeleE9EDop7Qyno2m+EDH/gAPvCBD4C2kywDvpVpdgaEU8zeCgH5hGRiQAgXlJSzWmQL0Mm8j4S3+5S5OhmP0MAAQLZ9hM9YZPgWKX1CLMti/5U3arAufQIKl343+9irX/3qZAuRJkqVDcVhw6yZWDJy49zATWQGTbdnmlzmDyntQJwMBgQAwMpG8+y1t6W0ZGSYf/GWTPpbMcHcBcuD73mpzN0Ibs823R5CoH764nMkKUeyFp/tnVM4bPkh3J7sNjoej/EjP/IjAIB/+OvfBZAxR4gBkQFdK0hgDnEGRIZBRXDEIm3xOerIaclwxCLda9LZOYWjAFzfQvPQMUzS6vtIaIWkZUCcPHmS/fnP3vVOvOY1r8FXPvZe2Bc/FgCwucm1dXzfh+u6c4aUi5HZYZV+Fv+h6b6eZj0yIicy48AhFoW97IJDQPabxpRsuVNaLlPQTcNPCWG2t4kBkQ1uZxS+DH38BvOASH9okI4FAMxSPhsZolSAKJOcbh2zXpAjo4w5gowwNzGpOtYmCsW0HhCAFb5nsuRIM8yRzQwMiMXiM02UwhzJxIAA77+nZZdJEaWCWHymzJGwbbdrNWE7ZvUjWGGRcFDx+PHj7L9mswnLAi4+dhjHjx/Hv/zLv6Ber+ODH/wgnvjEJ6JcLuMTn/gErr/+elx77bVz3+dlL3sZrr76ataS8WDj5ptvxsMe9jBsbGzg8Y9/PP7qr/4qwcqyzVhQ0eqfIz4hwAFELCoTCQwICKY9aVsQJCaTsSXDtQHS3TQGgnV7FgZEVo8OJkplAc0M0+0FwRLYnU1TUQFZSyYD3A6IduXpNmtqyWQSpQLg080tZa5SjnTtFrKUOFkHfGfTCVoIrKPrGWY9HMFEcJYyRyoS2nZA9iFwP2zJzDK2ZLJ6/RAC27ObWFqO+z4wHa7/RrM9YLoXnKWTQeJ1eJ4LZxZ8neNNgIkPFKvJpTRpxsKaP9B/9Vd/FW9605vw8Ic/HFtb0e8GO9yTf/stb8V7/uqv8fa3vx2PfOQjcccdd+Bnf/ZncfToUTz96U9fu5TMOhbnmE8IcAALi2pGy2UKLyOEyRgQGeF2muZOuyHIsFwGANvOdmjMMSAyCJfNGzulO9DTMiAWI2vxKaslw9tl6Z7NWIIoFQBYhWzFpywGhAhfpy0+pTAgkF1u3ZHUkslKW2csmVXDrNMh8JvrZy9ojH0j8rNWhwixs6f8aw8ApaQD8ss9Ol772tfih37oh2KuZYbxeII3vfl38Hd/93e46qqrAAAPf/jD8YlPfAK/93u/F6uw4OuI/alzIaslIzPOnZVIikZGy2UKJpOc8vDKarlMYWW0K5dhuQxw2DGtFXV3+wFsIRAcamUQHBKNndKyMZoSBIcAwccldUtGguAQxEMjW46MM+aIZWezK+9un8QRAG2rjkMZGBDzlvYTpGkANiXYAgCiXXm2tl3WHGHFZ8p1kHBZ1hw5V2IO4BBO9Cc96Umxv4fju/iX++7HcDjcV4xMJhN8z/d8T6zvwxCLlLbpVFikdVhVEQeqsBDh9iyiVIBoRZ3ujVgZZ7NcpmCHRkqkQIbgEMCTNu1tlIlS2c1MgkMiTzsNYsEYEFY2uB0QWyHpDtK0olT7IqMqqj+Q4BMCPkyXFtUanOUtmSzHV1FohaQp+kQGRDMLAwLCrFbKHNmYZLcFAIR2WcpnszZHitUAOVgTw34b1d43MEIZlYsflXgdw94uqv1vYoQSKhc/mv/sxLEcsajV5pEP27b3zT5Mp1PA9+FYPvqDoP3zgQ98AJdeeunc55XLcS9Q2VohzLo9RyzURHf3DFqh5XIWBgQgSGmnvI1WM1ouswgP0rQ3DWrJZLFcDpaRDbEYdci6PdugomXbmPoOipabaiAuCwNiMbiUdjrkpBZKvlcysGQAZO6fM1vujC0Z7jybEm7vEgOilWkdtsAUmqZAtYgBMfNtNLbkDG+mzZHNMEeytnaz+rg4YY741RX7iGXFakdYxSlQ3ICFUor2BeA7A6C4Ac+qpvp6to6YduVHjx7Fl770pbmP3XXXXSiEA6yPeuTDUS6X8c1vfjNR20MMPxTeTNsLocuedY6obgIHrLDo7JxCCwEDopGBAQFkVzPMarlMYWU0/ypKasnwVkjKwTzGgMgOpbqwUYSbSnSou3MShxEIDm1lYEAAoo9LuhzhDIishUU2SnIWBkSpVMLv/m5AMy1Vgs556uFNSW07sfhMgxR0tx/AUQBtq4EjmRgQ2U0Em14bsGTkSLbiszSmtl025CQr3VQFA8KPWMsP/uAP4rd+67fwJ3/yJ7jqqqvwzne+E1/60pfw+MdfCQCo1ht4+ctfjv/yX/4LPM/D93//96PT6eCTn/wkGo0GrrvuuhgrsNauIyoc3wWsc0fOGzhghcWA9P0zMiAAsTea/I0YWC4HLZkslssAMruKki13FsEhgE/8p9UG8KRYLgcRGMRNUz0bliN2MxMDAsjmKjqdjBkDIpPgEASDuJQ5UsmQI8ViETfccAMA4Ktf+BiA9MUnwe2zjC0ZILC0T1t8kihVz24tZ0AkCM8K6eIpcnW0N0Dd2gMANI9cuuaz10RGxIJ8QkpZkZOs5l8SfEKCZQgriEAKnvnMZ+KVr3wlXvGKV2A0GuHnfu7n8MIXvhBfvOsfAQQiea973etw9OhR3Hzzzfj617+OVquFJzzhCfi1X/u1WGvhMxbJfw/XncEJh+LzwkJRyGJAANkG4jpnH8Sh8GFnmW4HhNmGlLMem9SSyTjdntX8i7VksjIgALhWAHXPUoj0cMGhVuZ1+BkG8zrbAQOCBIcyRcZDg3IkK0sma/HpUI5kRNcAQUo7RY6MKUeKrczryMIKaW+fxHEAU99Bo5V1RiqbiSA5NWeyBQBgZdSxkMWAuP766/HCH/puAD5838fVV1+9siXymte8Bq95zWvmPjbYfRDYewBeKKP90pe+FC996UszrSlNK8SdTeEgYFLZtjwUJ2scqMJCFgMCENwAU9w0ejuncAghAyIj3J4VsWCWyxlZMnZGNUNZDAggm/nXrBvcimVMt2ehAnfPngoZEA0czgi3W4wKnBJu99OzZFzXxcc//nEAwGWHg2G11DlCcHtG4TKAF59pVFFnPYk5wobAk6+DBp7bVgNHUyjMzkVGPZymF7jwZm3tZm2F0PplMCACpCCdqyg9T1+K2mX614Rcc13LQfEc8QkBDpjypjeQ4wEBZJuxoA0hqwcEIN40km8Is+mE+4RkZMlknbGoSLFcDmLGrKiTFxayGBBANphbZEBkjgytEJEBkWbgeTQa4RnPeAae8YxnwHVDSDZlYSGLAQEIOZKi+JSZI1n0I4aUI04r8zoY8pmi+Nwb9FCzRgCys2SsjK0QxoCQ4OLpsw5Emh6ERFEqK73ypmjdfi7FgSosZDEgAMAjKe0UG9OoE2wIWfX9AbEVknxDaO88CJsxILLdNEhKO62r6KYrR3AI4OJlaVghvCWTHTnhiEUauD3MkYzumYAw4JsmR0LJ96nvoN7KhhQQqlVIWXzyHMl4K4bYCkk+Y0EtGV8CcsIHfNO3ZIYS9pEs7bJ2KOc98QuoN7LKz2ekVkIeYoEM+hEyHFYp/CV/iv21kqzbZceBKiyKo2BDyMqAAMAm7dPcNPh0u8RDI8VNo7cTbAjtjJbLALcrT3sbZQyIDD4hFARzp7mNcgZE9kMjS7uMCw7JKD7Tq6Iy63arntEDIvuMRcuTI0oFCD4uKZ4NMSCcrAwIZGuXuf0wR7LaAiAbu6y3ExTBu1Yzlenf3DpoxiKlyiQVrTIGFbldefKv5aJUElshaVoyMpETiXGgCgvS98/KgACyuQFSSyazTwiyHRqD0Ja7m9FyGeBv5EIKK+rpZIymDMvlMLKIDsmw5abIAnNzD4js6BpnhaSAuduUI63M6yADszSFxWhvgM2QAdFIaN2+LGYZBms3ZOZIhuJTRY6k2UcoR3oSWjKcFZJiUNGdwZbIgPAzHOi2LxE5yYLiSJ31kBcHqrCoSWJAANxVNA3MLRNuZ66iKQ4NWZbLAFAIWyG25cOdJVtLZzu48UhhQEB0FU0OczMGhAS4PYs2gCORJcOLz+Tr4AwIechJyXITu4qKLZmsDAhAoIunaJfJYkAA2YpPcmqW0ZLhOZKhJbMkR5LOBVgZDlFqfcpjQKTXj6DiOal1e9Q60hQ4rLUlBTmhZaR3nqU4UIUFE6XKyIAAkOnQkKbvD+4VkuamIUtwCJi3KJ4lPNA7oS13dsvlINwMt8Cm3wYgB27PcmgUZQkOAbCcsOhLkyPUkilnP8xFy3UvYWHRE3IkK9wOBPoCQDrEoiXBup1FhhwpjYN9REZLhnIkTSvE6+1vyTjh+3gySbYXUGFhW8kPMCoS3ZDimTXYT0+4Dt/3U1u3L19H+t/FYnLe8jQshsNAprxYTP89zy38JEPMphNsQQ4DAuC90TT0rA1JolRAtlaI35cnOLToGJkkhrvBobHScjlhpBUvG4+GaCB402SxbmeRgTlUlZgjWezK/b4kW25gbo5nNpskmutholROC9lfEVE/Itmz2Rv0ULXGAIDm0ewtmSzFZ3VKLJnsyEmWfQQhS8YV9pFCoYBqtYozZ86gWCzOyahHxWw2RWEWHOT+aJSoQNjbGwAzH2NYKI9GCX6B5TGZ+fDhYzwewyrE/37ubAbH9difPT/bWsYzFwXXxxhTFBL+XtPpFCP4mLgenIyvie/7GA6HOH36NFqtFise08SBKSxkWS6zyOAqWpOl749srqKyPCAAoCAYO00Tig6NQ58QGXA7kL4V0tl5EMcghwEB8HZZmkl7ypGqBLideXSkyBGy5UbKtl2xWMQb3/hGAEClws2gZtMJypX45lCTMEeGEoTLALH4TJYj7e0HsIGAAbFZl7CWDK6ivG0nr/hMlSOhBo0vDMVbloWLL74Y9957L77xjW/E/l6e58EOtWT8fhmWFR+dGg+7KE/amFhllAbZkc9p+wyKmGJS8VFKkKuz2RSF/hl4sGAP0hrA8xj3dlB2Bxg7eyh3khUHbvsUHLiYVi0US7uZ1wIArVYLx49nO0MPTGHR2wkslztWHVsZGRAAMkGY0jwgINw0UgzEZfGAWAzRrjxp31q25TJrhSR8Nt3tB3AMoeCQhJYMM4hLkSMtEhySgJzYGVohzAMipcNqqVTCL//yLwMIhnQpZgnncGQyIAChFZJwHb2dU7gYQUvmIgktmbSuor7noeV3Qhfe7MhJFufZMrFkFnKkVCrhkY98ZKJ2yHhvgPIHfwoAMHzR36Nai2++8I/v/b/xqG+/C/+0+QP4ruv/79hftyrufdsv42HuffiXJ70GD3v0c2J/3df/6R/wsE/+V5zGYRx7yW2Z13HXu/8Ej9r+G9x15Ll41E+/KvbX+Z6H6a0/jZLl4szz/wpHL7k881qKxWImpILiwBQWAyZKld0DAgA3dkr4RpyMR4wBkVVMJlhGemGqDQalyrjxOMHQlOXDTXj78vvyBIeA9MZOBLd3nRYkEJJTF5+jYZ8xIOTkSPriszoNPSCyuvBi3tI+8dAkte02ZDTLhFZIwmez1w7bdk4L2V8RpNaPGA66qFnBgd06mr34zMIKoRwpL9lHbNtGpRLf8NGxLRT79wMAxgm/1mrfh0r/fribVqKvW/n9BtuozO6HP9lL9P3Guw+g0r8fo8KGlHX4kz4q/fuB2tlE36+zu43m4D4AwNHjl0lZi6w4MMObMhkQAAAadkq4IXRCzrcMy2VAaIWkODQ2Z0FhIaMlAwTGTkAAcycJgttXWi4njLT+C1xwqCVlHWldRYkBMfGd7IJDAGzSGElxaJAtd1q43XVdfO5zn8PnPvc5+AiYP0ByYaq1ttwJI62PC7XtljEgUkXK4rN9JsiRkV9MdKtfuYwMGiOcJZMdgRWRT3c6jvjMJV9LbTsJLBkg/T5C1hF7knMkabusu/1tAMDAr6BS3ZSzFklxYBALmQwIALBSHhrdnVPSLJcBwMlw02j48gSHgKCwKGGWGF4ujoMCRwYDAgA8O52OhRveimUwIAA+iZ0U1eqdPYXjANpWE8ckwO1ZfFyoJVNP2ZIZjUb43u/9XgBAv99HAQU4mGKWcJMsTeSJUgGASwd6whzxyCdEUkvGSjmH0w9deNtWC8cl5IhTSLePBC2ZbmjdLgE5sW3MfBsFy0u8j5RCnSKnLnkfSfhsvHDgWdY+QvN8Sdtlg7PBRaltN1GTsxJpcWAQCy4mI2dDSOu/wBkQLSnLsAvpRIfmGBBZLZfDINGhpK2QqizL5TDS2pVzBoSkDSHljAVvyci58dgpD41hv8MZEBJaMgDghltK0kNDJgMCEBGLhPMvSxgQmSJlS5WJUklC16yUiEW/10bZCt7vrSNyLigkt560+KxJzhEmg500R4Zhjkhq26WV5B+GOdKXtI/IjESFxc0334wnP/nJqNfrOHbsGK699lrcfffdqtaWKAhulyFKBaR/2OO2PMtlgFP4knp0yBYcAgRX0YQwN3lAyBAcAsQZi2QbE2vJSIJSkVJufRIhOJRqGeTRgaQtmaDAGflF1Dazq7MCQvE5SwZz10MGhKwcYcVn0hwJB54hwxYAEIrPZOuQniMp2WWdM4Hk+9AvoyopR6j4TGppTy2ZqgydIqRvl5FwmSXBFgBA6pbqtBvmiCSUXmYkKiw+9rGP4YYbbsCnP/1pfPjDH8Z0OsW/+3f/DoPBQNX6YodMUargG6U7NGQzINL2RklwqG01pAgOAYKxU8IKnzwgMlsuh0HaAEmHN8tMcEhS8UmoVkKtEzfMkYkEnxCA962dhHLrHG6XI0oFpGNjBHB7G4AkUSoIUtoJN+tyRpbMvkjZLiOWzETSPuKkRD5ZjkiwBaCYMUn++BcUxpIBUJe0j/DiM1mOVCZy9xGklOT3aCi+fO4hFolmLD70oQ/N/f2WW27BsWPHcOedd+Lf/Jt/I3VhSUOm5TIAWGl7kuQTIglKdQqBfkTSwbwh+YTIYkBAQCwSVPijYV+a5TJFWkt7xpKRwIAAMhjEUdtOEpRqpzSI22tzUSo5W7VwG02wWQcMiBBul8CAALjAXdLik1oyyxgQacJiiEWyZ2MNg8PLleDUDHDGTtLic4/B7S0p6wCEfSRB8dntnEXTCl7D1hGzxWd12gYgbygeKQ3iyDpCVktGZmQa3ux0ggry0KHVVfV4PMZ4zGHRbreb5UeujE2JolRA+kNDNtyethUi1XI5DNdyAD/ZxH97+ySOQ5Llchh+SpibMSAkOKwCYDB3Uo8OxoCQBLeTjkUh4TqkMyAgoFoJxMvaZ06iBmDPL0lhQABi8ZkObt9oyTm80u4jjAEh6VbMi8+kcDvliDy4nYrPWQJKcnf722gC6Psb2JTEgODFZ7IcIesIWS0ZK+WsVmFELRlZV0d5kRr/9DwPL3vZy/B93/d9eOxjH7vy826++WY0m03234kTJ9L+yMiQKUoFpJfAZYJDkg4NJyXd1F2i7581SPEyyS1QRUuGyyQne02oJSMLSrVTDviSB0RBUo/WKaZrhbghA2IiMUeY82yCQ6N3lqzb5bVkmIlgglz1PQ9bkplUYKyudC0ZWXA7IZ+FtC0ZiTkyS+Hj0mc6RXIKT0C4oCQ40D3XDVgyAOoyFJ4huhMnezaVMEcK52BhkRqxuOGGG/ClL30Jn/jEJyI/76abbsKNN97I/t7tdpUUF94vfRHf3DmJ4w99lJTvx5TqksLtE7mTy8yu3PLge17sjdcfBIeXNAYEwkPDT+YVQpPLXWdLigcEIMxYJLiNqmBAEGLhJIVSw0HFoqQcKaQc3rQG2afbi8UiXvWqV7E/p2qXtYPDq1eQ15JhA74JcqTfa6NuBa/hlgSfEEAQL0uZI7L2ETsl8slbMvLgdo+QzwSo1l6YIzIZEGlmtXrtbTStoICX1ZKhVoidEF2rSnTzlh2pCouXvOQluPXWW3HHHXfgsssui/zccrmMcrkc+Tkyonn4IjQPy3uB0yrVyWZA0NAVEECHxVK811I6AwKCR0eCN6Ls6XYAqcy/2tunUIVcBoSdsjdKDAhZUCqDuS0fnuvGdpDlDIj0OVIqlfDqV7+a/Z0OjST9cxU5kgbV6px5AHWEDIhaXc5CUiKfshkQhZRaJ9IZEODtsiQHugoGRJp2WXv7JJoAuqiikcBfJCrSmgjyloykAkdiJMIdfd/HS17yErz3ve/F3//93+NhD3uYqnUZj7QeHQS3y5pud1K6ipYlWi6zn5+C5qmiJcP8FxIUFqLgkCy4PU3xqYIB4QgGcUmGJrkHhMQcSVF8crhdHrqWRvGSMyBa8paRAuYWWzJphcsWwwkt7an4jBvEgCjIzBEr+fAmZ0BI3EdSFJ+DMEc6VkvaOtLsI+5sxloyUpyaJUeiHfaGG27AO9/5TvzZn/0Z6vU6Tp06hVOnTmFvb0/V+owF9+iIn/xzDAhJUGqhyBGLaYKhyQ3JYjKA6BiZALILGRDSBIeAVI6RzJZblpw30g3EDfodVCQLDomW9knk1mWIUnmehy9/+cv48pe/DM/zUrmKWowlIy9H/BTKm0yUSiIDgoY3k+wj3fYOipIZELYgpZ1kaLImmwEBEfmMnyM2te0kODXzb5p8CHwUMqn6EvcRK8UQeOfsg3CswH6+KWkfkRmJCou3ve1t6HQ6uPrqq3HxxRez//7iL/5C1fqMRRp4intASLJcRnpX0aweEMvCY/zz+G8A2QwIQDg0EjybCU23y9wQ7OQ3jU4oSiVTcMhJeWjUJVi37+3t4bGPfSwe+9jHYm9vT/BfiJ8jbLpdYtuOFZ8JYG7pHhDgxWcS5LO7Ewyz9v0NVDbkiDUXUiKf9RBul9XaBcQLSoIcCdE1mTmSBrGYhgPPI4k5QsVnkn2kF3pSdVCL3R7XGYlmLHzfV7WOcy4YPJVgQ+jtBNRKWZbLwLxjZJJDg3lASLBcpkhzaBADYtFyOVMwYaoEcDtjQMi7FaeR0iYGRNtuQk6HFigKrZC4xSeD2zP4hCwLN0XxyRkQ8orgNHblKhgQaSztiQHRtpuQZS0lIp9x9xHGgLCAhqyBZ/AcSbKPMAaExJaMz9SV4++r1JKZSERgybYhyVnDWTItyJMukxcHxitEdjgpJHAZ3C4VSrUx9UkbIN4bQGRAyBIcAsTCIjncLktwCECq/jlnQEjcENhAXIJ22a58wSFbKGLjtst63V2UQgaEtOl2pMwRyS68AFLZlVNLRibczjw6krRUCW6XyIAoCEPgcXVourtnUJDNgEC6HKmxHJEI+6fYR0iUypOYI3aKVsioIz9HZEZeWKwIrq0fv4pkolQSxWQAQc0wJj2LLJdlCg4BvBWS5KYhW3AIQCptfdmCQ8EykkOYk678HBGLz7hIQWdbgNslWi77KVCtBrVkZGlHAKkOjSJrycjMkeTI5yQULtuTJPkOzBefcRELypEuaiiVK9LWkqYVQgwIWbYAAFIpXhZHwT4iM0d48Rl/HbLdvGVHXlisiDQeHR6z5ZZbRSadtO+HyIlMwSEguZS2qO8vTXAI6QRlmOWyzMKC/BcSwe3yRamAwNIeiF98DhQIDgGAZwXPJm5hwWy5ITdH0iAW5QnB7TJzJHm7zCNbAIk5Ytk2JgmLz0GIrnUsuWB70guKO5uh6fcAAA3DxWc53EcKDfn7SJLik+WILDdvyZEXFisileKlCgYEuGPkLKYboAoGBCAOb8ZbhwoGBIBUh4ZsW24gXfHJ4HbJ+v5MSjtmjuwpslz2ElKSVTAgAEEmOQG8rIIBwZxnExQWShgQEOzKY7ZCVDAgAMGjI2aOKGNApNhHNkMNmoqKfSRBrqpoyciMvLBYEXYKQRkSpZJmuRxGUjXDqQpRKnBt/bgVPkGpMhkQgMj7TgK3B4WFLMEhQNAGSJAjXN9f7obA7Mpj3gKZKJVkKJWrosbNkW8DAHoSGRAAuKtogon/umQPCIBfUJLcRgsKWjIAR7XiDvhOFcHtXkLFyy7ZAmBTKgPCSuEqylsy8opg5jzrx5fkl+7mLTkymZAd5EgzY8EtlyUOKkJ0A4y3IZB1u1TBIYg3jXhvROYTYrekMSAAJO6NspaMZAZEmuKThMtkTrcDyYtPL2RAZIXbi8UiXv7yl7M/J22XidPtkrQuASTXBlDFgLBTIJ8Vask0JOdIwuJTBQMCEOXW4+ZIKEplt9CSuRCGWMR7NrPpBFsIWzJS95HklOQN1rY79+S8gbywWBlURSbR1t9gDAjZiEXwmOKyQpi+v+T+m8d6kvHWMWL6/nJ7tFZCCLPX3UVDAdxOVOAkMDfzgJB9aLBWSDyYW5Ytd6lUwm/91m+xv3sJYW4aeJbJkgGQGObu7p5BK2RANCWZSwFCKyQBc6hGHhANuYcGv6CM13xmEHaoQeNJZFIBwqxW7BwJ9pGB5BzhxWe8dbR3HsQRAJ5voSUzRwopcoR0imSy7SRG3gpZEU4hef9cCQMCgGsFjynubVQFAwJIjlioYEAAySVw5xgQEuF27ioaP0cakj0gKJIO+BYVWS77CQfiVDAggORS2qoYEAXKkQQwtxIGBERL+7g5Ip8BAQBe2KaKi1goY0AkbJf1dsiFtz5ntZA10szzyXbzlh15YbEiOGIRb0OY1/eXvCEkFB0qTeQLDgHJDw1PgS03kHwwb8BaMnKRE9YbjbkhiJbLMuF2QPBfiFl8cgZEthzxPA/33Xcf7rvvPniel5huyjwgJMPtSKhmyFoykhkQSQd8Aw+IEG6XiK4ByYvPSsiAKEpG1xKzy1iOyN1HbCdZS5UzqWTvI8mKz8l4hCYGAOTvI7Iib4WsCJLSti0f7my2tkINLJeJASH3YTNt/ZhUwtpUgeAQkJyeNVQz3Z60fz5UxICgjalkubEs7QPLZfktGUB0FY1XWPAcyVYE7+3tMTPCfr+fuPi0KUcks2SSwtwjypGC3BxJ2lJt75zC4ZABIRNuB8Li00+wj5AolWRbbj8hc8jaIwaE5EFFO9k+MgrbdgPJOUL7SNxWSGfnFI4CcH0LzUN5K+S8innTnvVvRJpcHvplbMiyXA7DTXgLZC2ZLTUbQtxDozCSr+8PAFZCmWTmASEZbi8KMsmet/620QlzpIuqVLgd4HM4cRGLeujCW5WcI0mLT5YjklsylCNxb6M08LwnGW6n22gxLD7XRS+8Fe+iPifDLSOSIp8NyU7NFNydON6zKYY5YktmUlmFZOyyWYjAjiXvI4VQkt+JiY53Q5+QttWA7ThS1yIr8sJiRYiHRpyhSZEBITuSmH+JolQyGRAAEh8aqhgQSRUvZTEg9q0jYfHJ4faW1HUAyXxcPNdlbTvZlstJEYuKAlEqQEQs4uaIGrh9zkQwRmFBDIiuZLgdEF1F1+9nIgOiLruPn/CCoooBQSaCsdllitp2tJ/FLT6Hu5QjLanrkBl5YbEiRMfIaQzRoT0FPiEUSVoh3c5ZlBTB7T4bdoq3IahqyST1XyAxGdktGfHQiCM6pEpwCEAiu/LO2dPqLJcTWtoT3C5TcAhILjpELRlfckvGnttH1rMxxm01cDsg5EiMi1I7vBXLZkAAoqV9vBzZpByR3JJJKqXtKGrJiPtIHCowyxHJOkUyIy8sVkRSu3IVlsvs5yfgfXdDwSHZDAgAiT06Ggosl4NlJGuFKLHlxqJj5PrXhAkOKcgR1gqJsY5uyIBQYbmc1FW0GcLtshkQdkLmUFFRSyYp8slFqRTkCLG6YtDFu9shAiuZAQFAYGPE20eaZAsguW1nJ2yFcFEqufuIk9B5ltp2slsyMiMvLFaE7ThwfQsA4MaorL1+UM3KZkAAybT1B2eDalY2AwIAsyuPA2F6rsv1/SUPsyYVlGH6/pJbMqKlfZzik+WIbAYEkhWfffKAUAGlJtCPED0g6ofl5khSSnJlSh4QknNkrl0W4wBjHhDypZo58rl+HWQLoAJuZwq+MZ7NZDxCQxEDwk7IHNoIJd9ls2TmEIsY+4gf5shMwT4iK/LCIiISaesrYkAAyfwXVDEgACRCLHrtbSUeEABgF5JBmLIYEPvWIRafMXKE4HYV+v5+ArrpSGmOxJ+xaO+cgs0YEIpaITGLT27LrfDQiNEKYQwIyaJUQLJ9hDMgWtLXwYrPGOvohC0ZFQwIKj7j7iO8JSN3H5krPmO03XlL5tz0CQFyumlkzOCghFmsCr+wp0bfH0hmMzwNRalkMyAAcAgzxhuxvX0STQSCQw3JDIikUtqqBIcAYIYCHEwxi7FJqrDlpnBZ33p9jsx6QY7IEBwqFAr4xV/8RfZnKwHM3d05icMIGBBbkhkQTkJXUS44JLcItmwbM99GwfJi7SMlhR4QpJzrxXg2Sm257fjtsu72AzgKYNdq4ohkBoSd0Mel6bUBS74o1Txisf6CUiLrCMk6RTIjLywighk7xZDArUyIAaFiQwgTL1ZLJpxcVtCSYcJUMXq0A9L3t5qQa8wt+rjEa8kwDwgFhYUbgn5xXEWZKJVEy2WKJIiFTAZEuVzGW9/6Vv6BBKjW4CyfbpddBrPBvBjaANPJGC30Acj1gKBw4aAALxZziFgysuF2QEAsYsHtQY6ogNu5JH8MBJaG4u0mZN/PnQQDvuPREHVrD4B8JpVYfMZphWwozBFZkbdCIsJN0JOsKrBcpkhi2qOKARF88/hKdQSlqmBAJEEslDIgwIvPOGyMmgLLZQqaw4mDWCi1XE6gikoeEEpyJIGJYCecSwrgdvnPhhWfMfYRZsstGW4Hku0jDvmEKEDXePG5/tkwnxAFA89WglmtdjjMOvUd1Fvy3zdcbn19YbFJtgCSh+JlRl5YRAR72DE264YCy2WKJDLJqiyXAfGmsf6NqMpyGeDQYRxBGWJAyLZcpkjCxuAMCPm3YubjEuPQ4IJD2XPE932cOXMGZ86cge/7idpllCMqptuTyK0TA0K2BwTFjOnQrC8+iQFRky1chmTFJ2NASGZSAWBD4HGKT86AkL+PEBsjTvHJdIoUiVLNEvi4tGgfUYCuyYq8FRIRvIqM3hBUWS5T+AlcRStjNZbLAB92irMhqLJcBoThzRgwt2jL3ZK+En4bXUcTYwwISw3cTpP2cQbzKhIFh4bDIY4dC3Kt3+8L7bIYYm4DasnIP7ycBMOb5AHRtVtQMFEQ+zYqMiCaKvaRBM6zGyGTqqTCPTMBc4jniIJ9JAHyOaQccVpQgOFwS/s1bffRsI+aNQKgJkdkRY5YRIQbU1Cm195GQYHlMoWf4KZRVWS5DIDB3HF43wxuVzDdTjoWcezKR4oslyncmGqGxIBQITgEJJNbV2m5bCVolzFbbgUtGTuBO/G4q06UCojfCiEGxMy30dhSMIdjx2+FENyuoiVjJTD/opaMX5W/jyQpPschujZUwZJBfIM4aslMfAf1Rq5jcV4G8b7XtSDoYcu2XKZgvO8YLQiVDIgkh4ZKBgS3K1/fCpHJgFgWzH9hTfFJXjKq4HafDfjGacm0ASiyXGb6EWYZEE4haHvFKT4ZA0LBwDMQMIeA9cUna9spgtvZBSVGYaEyR6wElvYqGRB2MX67zKWWTFmNdkTcVghvyTTXmh6ajHN3ZedA0KGxDsIUGRAqgg6NdYp5geUy2XLLh9vJtMeJsTGVFU4uF8KNKY4boCoPCIq4iAXLERXCZRAH86LXMceAUAClMvGyGDnCGBAKmFSEWMRxFWUMCEWFhWfFa6lyBkRLyTqopbruojTaGzAGREOycBkA7ioao7VLDIiSgoFnh/aRGAWOSpYMIBIF4uVIV4UGjcTIC4uI8GLCU9wDQtHDjglzd84+yBgQKuB2OwFiQdPtsi2XAQHmtnx4bvRaOANCRWdU9F9YkyOKLJcp+BxO9OvR2VYnOARAaJfFzxEVcHshQf/coRxRwYAAPzTWHehjypFiS8k6eLtsTdtOYEA0WipamfFzhDk1K9xH4hSfpFPkqxhmhVB8rrmgUI4Mz2GfECAvLCLDjalUNw3tdFXo+wOizfA6mCy008WmdMtlIJlMMlku1xSwZJwiZ3esY+yoslxmPz9m8TnrqrFcZhFT8bJ7Vq3lsp0A5mYMCAUsGTbxH6P4LI7lsWSWhRuz+JyxfUTNrThu8UkDz7uK4PYk+4gqLxmAe/3EKT6pJeOoypGYxScbij+HfUKAvLCIDC+m6JBKBgSA2I6RIgNCRcRlY8ymE+4TooABURBmFNbJrctkQCyLuK6iKqfbAdExMvrZiAwIFUFzOOtEh0QGhGzJd2DR0j76fUMMiKKKgWeIyGe8HJkpGHgGwIvPNfsIMSBUODUDoqV9dI7sDXpKGRDUColTfG6EtgAlRTnixmyXkZfMTLILr+zI6aYR4TH+efQbgOB22ZbLFOzQWFPhjzrBhqAKbie55nU3jfbOgziikAFRSOAGuOmqsVymcGMaxKluyfgx1QzHlCOSoNRCoYDrrruO/dkO9SPWiQ61t0/iGAIGhArBoWJxwdgpYqiacmSjpUbJ0I25j1BLRgUDAhAGfNcgFgxuV8SAiOtO3N5+ABsAJn5BCQNi0VW0FIHg1cknRIG+CBB/HyGfEF9R205W5IVFRLgxhamKo+Bhy7ZcZkHw8hqYe6bQchkQbYajN4TezgM4gsBy+ZACBkShwDeEdWwMpQwIxPdxUcmACL5xvOJTtuBQuVzGLbfcwpcRs3/e3X4AxxC0ZGR7QACLrqLROdLyOko8ICi8mPsIh9vVFDg+U7xcMwTeJwaEmmHWuIqXvZ1TuBhBS+YiBS0ZEflcV3y2/CBH6ofUaEfEnecrU44oGHiWGXkrJCK44mU0PMVtuRUfGmsKC48slxVtCFxQZg3cHtpydxUxIGxhk5lGtEKmkzGaZLmsSKXOi5kjZMtdVOATAiC26BC3XFZ7aKxrhey1KUdaStYhFp9RzrOjvQE2iQFx5FIla4mbIxssRxR5QMTcR3zFcLsdtxUS5oiqloxYfEbtI8N+BxtW8O8qbAGA+D4uvCVz7vqEAHlhERleTHhKJQMCQGxjJ9Vwe9zbqGoGhGXbmPjrK3zlDAgkzxEVDAgAsQ8NR7JPiO/7GAwGGAwG8H0/diuEMyDU5IhTKMALLe2jEAtRcKjRVEU3jdcKYQwIBQPPAGLLrTMGhCJbbiumj4tqBkRRGAKPQj7bZ4IcGflF1DbVXJbYPrIGTaIcUWEdITPywiIivJiCMg1FlssUcQVliorhdjo01m0ISi2Xw4gjt94JxWR2raYSBgQgyiRH50jTbwNQB7fHRSyKkgWHhsMhNjc3sbm5ieFwGLv4VOkBwX5GuL1FHeg6BIfitkJatI8oKyzi0dZL42AfUcWAIORzXfHp9dS2ZGzHiVV89nZIuKylPEeictX3PGyFTCpVZ42syAuLiIhjRT2bTrAFdQwIALEPDdV2unZMCVy/r1ZMBhAKiwi78uFucGioEhwCxENj9TrGoyEaGAIAmorgdiumq2hVoeAQwA+NdaJDfp/gdvU5EsUcYqJUiuB2IJ5Hx96gh6oV+EQ0jyrygIi5j1QJbleWIzHtykOWjKtwH5kxufXVOcJaMoqGWYF4rZB+r42yFfx7S1FLRlbkhUVE+DEq/PZOkHSeIstlgFP41vUkyQNChXU7ACZFva6wUOkBQTFjgjKrXxNuudxStg6mZhiRI50wR1QJDgHgMPeaiX/KkQ0V5lLgfet1t1Gaboeith3AZZKjYO6JQltuCi+G4mU7lPMe+0Vs1ltK1hHXRJDadipEqQDBedaPluR3Qg0alQwIkluPktKeKvYJAcRWyOp1kC3A0C+jqqglIyvywiIiPCuU0o6EUgkmU+MBAUCwGY7erFUzIOzQf2FdYaGcAYF4Uto64PY45l+iB4QqKDWuNoBqy2WbWdqvyRFqySicbndjFJ/EgJhoyJGoQ4PE7VSJUgEQEIvVz8b3vIABAaCuQs4bwqzWmhzRwYAgg7io4pP2kYkinxAgntw6a9spGoqXGXlhEREcsViddKoFhwDB/CtiY5qMR4wBocpOl9wA18HcbHJZ0a0YEFshqyFMv69WlAoQhzejWjLccllZxMiR0bDPGBCqcsSO6eNSnarzCaHg/gsRVtR9xaJUEIrPqFZIOzg0+o66Q4MXnxG5OugqZ0BQ8Rk3R8oq95EYwlRWOPDsasiRyHZZuI/0Ve4jkiIvLCIizmAeZ0C0lK3DijEQp9pyGYh/G90MxWRUtWSAeFLaTExGkeAQIMokR7Vk1AoOAfGktHVYLhfIeXYNzL2pmgEBccA3KkfUMiAAwGMmguvbdsOiOuQkTruMGBB7fgnVWkPJMpyY+wj3CVGXI3GcZwvUtlPkEwLEIwpQS2bvHPcJAfLCIjLiHBpc31/dhhCnN9rdUesBAcTX1m+wyWWFh0aMwdriOChwVFguU/gxJv7d8FasynIZAHeMjCgseswnRB3cHnfAl1oydVUDz4hXfJaY5Lv6HInaR7we5Yi6fcRmA76rn03/rHqWDCssIorPoCUTODWrZEB4bHgzKkeCfcRRmSMxZrW8cOBZ6T4iKXLlzaiIUVjoYEDE6Z+LDAhVdTVtTCXLhe95SzceHQwIIJyi9qN7o6oZEEC84pMxILTkSJyWzBZkbZGO4+DHf/zH2Z9pMC/KMXLY73AGhKKWDBAWn360FTUxIIoqcySOmSExIFR6QMQYAucMiC2oOs5pH4lqhfR7bdQ1MCDizGrVFLNkgHjtMgw15IikyAuLiIhz0yC4XZXlMhBPmGrcVmu5DAAFQanO8zw4SwqL9vZJXATFDAgAbgwIk3tAqNsQ4hSfXN9f3YZghf4LUbfRiQLBoUqlgr/8y79kfx+EOVKMKD7b26dQRcCAUCU4BIT+C340YlEnBoTCPj53J179bJxw4BkK23YWk+SPmNUKc2RP5T5SpCHw1YhF58wDqEM9A4LlSMQFRYcoVRzEgoTLLEVOzTIjb4VEBQ3ERcHtxIDQcGhE8b51MCBE057pdPlAHBccUseAAARBmYgNoaXQcpnCj+EYWVYsOASIUtqrDy+XptsVWi6LxecqNgbB7UoZEBD8F1YgFgHc3gagjgEBIJY7cZmxZNQVOHFMBBlLRiHcThclKj6XBWvJKGZA8OHN5c9mjiWjZR9ZvcdXJur3EVmRFxYRwdwAI96IG9M2ALUMiDjDm6Tvr5IBMXdorHgjDsknRPHkMhOUWcHYGQ37Si2XWdChEXHTUG25DMT0X9BguRzHrnyvrV6UClivZjgcdFEhuP2ouj5+nNsotWRUDjzH2UesYXB4qWTJxCk+qSWjmgFBxeeqNlW3cxYlK3i9WkcUql3G2Eeq4VmjMkdkRV5YREUMjw5iQCjzgEC8VogOuH3eMXL5a8IZEGonl1krZMU6OANCjeUyBYO5I54NMSBUWS4DgkxyZI6EDAiJbbvBYADLsmBZFgaDAYoCqrWq+OQMCMU5ssZ/gRgQygWHGBsjoiWjAW63Y7RCiAFhKWztLtqVLwsmSqWSJYP1lvbd7W8DAPr+BirVTWXr8GMwh8g64lz3CQHywiI6WG909cNWLUoFALazno2h2nIZWLhprGiFuIr1/SnWSWn3dvTA7XHaZYwBochyGeDMoahWCPOAUKgdMVd8rpBbd0MGxER1jrBWyPL3b+9sIFzWsdTQKinWKfjOe0AoLD5jMIeYKJVCuL0wlyPL21S8JaNnH1k1q9UnJpVqUao1OjSe6zKWTEMlAisp8sIiKtYgFuPREHWyXFbYo7UL6zeEjYliy2UEpj1uaNqzarP2ByGUqrAlAwg+LiuezVCx5TIL6o2ueDbzDAgNqFZE8VkNBxVVWi7Pt8uWHxqWDgYE1hefo3ZwePUUo2vrDo1+r42SFfxbS+GhEaf4pBxRCbc7czmy/DWhlozyHGGtkFUtmVDyXfE+sq747LW3UbCCeZTm4bwVcl6HtcZmmOB21QwIgrmjEAstDAhwQZnZis1aR0sGANw1w04qGBDLwloDc7dD63aVlsuA4NERcWgQA0IllGrZNmY+ySQvf00YA0JxjpBHx6rikzMgVBcW0e2yzpkAORn4FWzU6uqWEcPHhbVkFCKwcYpPXQwI7uOyqiUT7iMKh+KBOPtIcNZ0UUW5UlW6FhmRFxZRQYIyK3q0uuB2pngZ0RsluF21nS5p669yFeUMCHW3YmC986yulsw6VIsLDqmzXAYEVsgKbQCRAaE+R0JX0RWHBveAUJsj6xwjCW5XLTjEJflXwe16GBDOGldRsSWjUrhMLD5XzeEQA0KlcBmwvhXikS2A4n2EsUJWPJtBmCMdq6V0HbIiLyyigjaEVTD3WT3T7esQizkGhCrL5TBm7I24/NDY0CAmAwgSuKvoWSEDQqXlMgBefK7YEJgtt0I5b0AsPpfnyKDf4QwIxZbL7ho1Q2bLrbAlA6w3/7IoRzZ0FZ/Ln40uBoS1pl3Wbe+gqIMBAVFuffmBXtPEgPDWKOfa1LZTKPkOrPeDGoVMqr7ifURW5IVFRDAp7RUbwliDnS7AocNVgjIiA0KV5TLFOjYGY0C0VB8a0RQ+FQyIpbGmXTbRlCPMinrFodEJWzI6LJdnbNJ+efGpgwEBrC8+C2FLRiUDAoDgTrx8HcwDQjHcTmyMVcVnN3Rq7vkbyuH22Rofl3o4FK+6tbtuHymE6JqluG3H0fHlz2ZK1hHngU8IkCtvRgarIldsCLrgdhreXAVz93ZO4jiClsxFKhkQ4LfRVTSxltcBLLUMCIAPO63qjepgQAD8FrjqpsEZEGqRE2eNRwcxINp2EzKPDMdx8OxnP5v9GYi+jTK43VILtwOiieCqtp2elsy64U1dDIh1yCcxIDp2C+omPYLgwlT72WWMAWGpZ0Csa5dVxuq9ZAAI6PgKVkjYkpmoRmAlRV5YRMUa0SF/QJbLaqtZopuusitncLvTgup54ShtfZEBoVJwCOCHxqopai44pHZDsNa4inIGhNoNwV5jEDfaVQO3VyoVfOADH5j7WNRttNfdRYMxIBTnyBphqqoGF14gTo5QS0btPrLOVZTD7epvxbMIg7ju7hm0QgaErhxZtY/UWI6oRdc4Or6iJRNat3uKWzKyIm+FRMQ6K+qCBstlAHCK0a0QJkqlWEwGEARlllT4OiyXKdZJ4HLLZbUb0zpjJ2a5rFiG1wlzdVXxOelqzJGI4rOzzRkQKgWHgPVePw3WklFdWETPahVZS0bxBWVNYTHpkC13S+k6gGhLe8qRLmoolStK17GuFUKiVCptAQCsnecrjtQLl8mMvLCICoKXVyRdSYOYDAAU6NBY0QrxmC23+ptG1KHRD5GTjmpRKoiDecvh9pYG63ZA0I9YlSNkuaw4R6hdtspVlKzbVcPtAIeXl1EJB7oEhyAgFkuKT9GWW3VLhhWfK1ghZQ3W7cD64tPTYAtA4Ub4uAxCdK1jaciRCFdRdzZD0+8BABqK95F1DtblcB8pNPLC4rwPe00VqYsBwWYsLB+eu2QtuhgQEM2/9r8BdDEgABHC3P966GRAWGuktKuacqSwphWiCm4fDAao1Wqo1WoYDAbBz4gQHeIMCPVFMM+R/YeGTgbEOrl1xoBQPKhIyOeq4tPWJFwGCDMWSw50nQwIj0lp739NOmcfhGP5ANSK2wHrWyGboQZN5TzwCQHywiIy1h0a9ZkeUSontBkGlpv2kCgVNMBkbkRvdKpJlApApF05Qak6GBDrYO5GKFymmgFBt9FVxSdjQCgQHBoOhxgOh+zvbkTxyYTLFDMgALEVsuTQCD0gdAgOrTP/qjMPCLUFzroZC54j6veRKMVLYsmMNOQImOLlkuKTnJqxiWKpvO/fZYa1Rm6dt2QUo2uSIi8sImIdG4PZ6aq0XAZQKPAZ22Xa+joslym8CB0Lsm5XzYAAomcsmHW73VK+DtoQlokOzVkuK4bb17mKknCZ8ul2CB4dS3LECxkQUw1tO0RY2hMDoqsBbo+Cuec8IA6bLT4rrCWj4YIS0S7TyYDgrZD9z4aEyzo69pGIHJlNJ9hC2JJR3baTFIkLizvuuAPPfe5zcckll8CyLLzvfe9TsKxzI0hmdVkVOex3sGEFbwrVMJmz5tDYYAwIDTeNCEEZpu9f0XAbjVAzJA+IvqP+0LBD/YhlokO97q4ey2UAxWK0pb0OnxD28yMcI3V5QADcMXIZYkEDzzoYEMTqWraPdHfPCB4QiveRNa6iNY1wO3OeXZIjdjgU7ylmUgFijuxfB7nwqvYJAUTn2f050t4JctXzLbQU54isSFxYDAYDPP7xj8db3/pWFes5pyLyYWtkQBSFVsgyNoY2BgSiDw1dDAgAkeZfOhkQUZb21JLp+xuobNSUrmNd8dnQJEoFRBefRY1wu88UL/e/HpwBob6wiFK8pBzpaGBAiMjnsuJTGwMCIqq1LEc0MiAiZrVmGlsyUZfY3g658NbhCM/wXI7Eq3zWs56FZz3rWSrWcs4FF5RZBreHgkNWExcrZkDYwvefLrRC5gWHdB4a+yHM0kS9dTuLCNEhT5MtNyB4dCyBMAc73ANCLbESKBT4bdRdyBGdgkNAdI7oYkAAiJzD0Qm32xEwtyhKpRpfE4vP6XSCDeHf3NkMLb8X7iMac2RJgVPR4NRMEVV8+uQTogGBjWqFDFiONHF+6G5qEMgaj8cYj7m6WrfbVf0jpUXUbZSm23uFLajGCSzbxtR3ULTcfRV+v9dGnTEg1G8IfsRttDbVIzgEIPLQwFCPvn+wjNWtkKFGBoRTKMDzLdiWvw+x6LW30dTUkgG4lPay2yjPEQ2QboTcuh3miA7BISvCx2WkMUeikM/2zikctvwQblf//vWYfsSylkyYI4qH4gFw59kl+4i1R6JU6pGTKOfZUdi2G2ho28kK5cObN998M5rNJvvvxIkTqn+ktKBDY9mGwPT9NYjJAKKa4fwtkCaXh35ZqeUyhWeF9KwlhwZrySgWHAIQiVgURpr0/RFdfHIPCD0bwix8Oy8e6J0dbrksG263bRtPf/rT8fSnP50ha1GtkHrowqtalCpY3GqBLL05svrQoIHnkYYcsR0Hnm8FP3ex+KRbsbXJqMsqgw+B7382jTBHahradlHCVMUwR2zF1u2AiHwuy5FQp0jTPiIjlBcWN910EzqdDvvv/vvvV/0jpYUd4b+gkwEBCEp1C3blOhkQgHhozK9DJwMCEGme+zcmnQwIO0J0iDMgNNDmINiVL7RCGNyuwHJ5Y2MDt99+O26//XZsbATg+iqPDs91mS13U8d0e0TxyRgQGuB2O6Jdxmy5NXlAzJjz7GKOhMWn7n1kocDRzoCIaIVssLad+iKYtd2Xscs054iMUN4KKZfLKJfVcoBVhRMhOmSF2u0zDZPLALcrX9Sx2BN8QnTEKv+FbuesVridwdxLhq50tmScCAiT9P11tGQAwX9hYbPWbbnsrVC87Jw9jS1NgkOA6NGxpCUTwu06GBDMedbfL8mvsyUDADMUUIK7T0p7TC0ZXTmyQkq7vXMKR6CRAREydpYNb25SjmhoyUS1QhyNLRlZketYRIQdIaVNDAgdUCogSuDOuwHylowemGyVBG43FBzSwYAAxGGn1dPtqoXLAL4hLM0RTR4QFKu0AZjgkOYcWUQsugIDQrXgEABBSnv/s2kyuF3HbXS1Hg6D27XtI8sRC8oRXXA7l1tfzJEQgdXEgLBCxGKZ3HpTky0AIGiMLG3JBPuIrYNtJykSP7l+v4+vfe1r7O/33nsv7rrrLhw6dAgPechDpC7OdDAr6iU3De4BoWG6HatNe7x+UODoYEAAq28ag7PBjUcHAwKAAHPPvxE91w30/TUxIKKsqJm+vw4GBFb7uLAcUQClDgYDXH755QCA++67D7VabaX5V588IDQwIIDV7TLmAaGJARFl/lWZkgeEphyxlqNaYD4hegqcVUPgZAvQtZvQsqOtmLGYjEdoIJCo19GSiWq7b4SS78XzxCcESFFYfP7zn8cznvEM9vcbb7wRAHDdddfhlltukbawcyG4q6hZuB2IkNLWyIAAVtsM62RAAKudZ3UzIAqUI0uKT60MCKwuPlXD7dvb23N/5/4L8+vQyYAAsLJdppsBESWlzVsyenJkBmLszBcWnAGhZx+hC8riPqKbAbGqXdbZOYWjAFzfQvOQ+qIvqu3OWzLnhzgWkKKwuPrqq+H7voq1nHNBvdFlpj3EgKhqgMmA8Kbh73cDJOt2XXa6q2DuaShKpYsBscquvL19Ek0ElssNxYJDAL9pLGuF6BQcAlYjFtyWW2+OLLbLZr0gR7R4QGC1fkR35yQOIxAc2tLAgKDCYtmAbzPMER1wOwB4rBUy/2xKmuH2Va0QnaJUAFYO+Ha3H8BRALtWE0ccR/0y2D6yIkcsfTkiI/IZi4igh120XPgev5HqtOWmWEXPqkyIAaF3Q1gcdmLT7ZpaMqsEZQak76/BAwIQBvMwj1jMeUDoLD6xH+ZmolSaoFRuab/YttMnOARgJcw9YAwIPTmyCuaeTsZooQ9Aj7gdsBr5JJZMUdc+sqJd5ocOqzNNDIhVdHHm1KyJJeOs0DoZj4aoW3sAgOaRS7WsRUbkhUVEFIXbjCcUFt3OWW0eEBTuCgizSpbLuux0V7RCdDMgrHCae/HQGHX0TrfThrBYfHbOntZmuUyxSm5dpwcEAPjOco8OyhFdcLvFJPkXGBChnLeuHCmEwlSLxWcnnEsK4HZNLVXKkYXik9lya4LbV7HLHPIJ0ZQjWNFSZT4hmnSK+AVloW0XDrNOfQeN1vlDN80Li4iw5yRwBfXQkAHR08SAAATEYmFDaDDLZb0bwiLMXdAMt68SlNFquQygIOSISAUmBoQOy2UK5r+w0C5jDAhdlsthrlr7WjIkOKQpR1b4L3AGhN6WzGLxyRkQDW0eEJw5NP9siAGhK0dWuRPrZkCsQj5Jp0hXjrB22UJhwXSKrAYsxdYRMuP8WamBmDs0hDeiqO+vK5igjECLmoPbNTAgAPBDY+GmURnrExwCRIO45XC7Dg8IYLVjpIkcWYZYzKaTgAEBfZbL/orhzYpGwSFgtYkgwe26BIcKgpS2WHySB4QuUSoA8LB/tkFkQOhCYGEtn23YCJlUpaamfcQ5N3KEFRaWN1d8DilHNOkUyYrzwyrNUBTmDg3+BmCCQxofNmuFCOvo7p5BS5PlMgWDuRfeiEzfv6Hp0LCX90YZ3K5JuGxV8TnqBDmiw3KZYlnx2d55EEcYA0J+jti2jSc96Unsz8Eflh8amy4xIPQcGqtuo7pbMiIaMZtN2b4yDnNkqKklAwhzOEKB094+iWMAZr6Neksvu2yx+GQ5oqklY60oLJwwR3xN+iKOaCLozlCwKUdCp+bzyCcEyAuLyCAdCwBwhVbIpBtUs9oYEFgupd3ZOYUW9DEgAPBDYwHmrjO4Xe+GsNgK0c2AmLMrF+TWSd9f23Q7xFYI36x7ZwMlw45Vx5YCuH1jYwOf+9zn5j7mr/DoIA8IXQPPq4rP0lhvS6YwlyMTIGyfshzRNPAMiEPgPFd7O0Fh0bYaWhgQAFYWn00vcGrWIVwGrC4+SafI1raPCMXndMKKTzdEYMcac0RG5K2QiLAdB25o2iNu1rr1/QE+Re15IpSqlwEBgA9vCpt1YLlMLRk9UOoqCVxiQOiwXAYWEQs+26CdAQFRSpsfGixHNDEgAD7bIB4aIgNCV9vOXjFpX9GdIwLyKWqM6GZAAILAnYBYcFGqlrZ1LNPDGe0NtDMgVrVCyCekpGngubCipWoiR2REXlisCRKUmQmbtR0+bHdD0+QyAHfJsBP3gNCHnCw7NDpnH2QMCC36/uBo0uKGQNPtWiyXEVjaz/zQ1VM4NDjcrk8tz1tSfJqwXPaXFJ+d7SBXdQkOAQLMjeU5ogtun0M+heLT0dySAZYjnwS3DzRJvgOAtQSxMMGAsFcMgTOnZk37yPwFhb8mpFOkqyUjK/LCYk0wbX0B5tbtAQEIiIWwIXAGhMb+m71/eJOs29vQY7kMCKwQLMLtbQCaLJfDYK6iwqHBp9sNHBrCjWem2ANiOBzi8ssvx+WXX47hcAhAPDTEth2fbrc1we3OClfRpt8GoC9HxOJTnMMpam7JAMtbIboZEIBYfAptuzBHdq2mNgYELz7nc6TFhMv0ILBi8TkT2u6l0KlZl3WErMhnLNbEjL0R+aFRmejV9wcECVwBsfAG6jwgVsYS/wXyCenYLbR0LYMkcIWbRsCA6Ac+IZoYEEDgKlrGdO6mwXJEEwMCEOzKPRFuJw8INTni+z6+8Y1vsD8D4Dki6FgMQ5+Qrt2Crmy1wxwREYuAAREUQNoYEAhypABvrrAgBkRR08AzsLwVQjmiy6kZgJAjfB17YY70nCZ07azLhKn2Bj1UreBw19XatWwbU99B0XLnBmvJJ6Sk8ayRETlisSaWsTF0Wi5TLDs0CG73NbZkmP+C8EZkDAiNcPsy86/2zoOwFTIgVoW7pPjk0+06Dw2S0jbbkuGKl3wdxIDQCbcvg7lFuF0XAwJY7uNCOVLVmCPLVFGpJQONOWItMRE0wYBYNqvVDjVoJn4B9Ya+tbhL5NbrdNZoGmaVFXlhsSboYYsDNbo9IAA+aS/2Rouj0LpdI5RqLblpzAy0ZJwlMsm9nVCUSpPlMgU/NPiz0e0BAQjFp5Ajuj0ggh+2JEcMwO3Lik8mXKaxJQOIwlQc5m4Rk0ojurasXcZYMprkvIMftr/4dPthjmhkQDCPjrmWTFAE62zJAOI+ElxQROuI+iFNOkWSIi8s1sSisVPAgAgEh+oaN4Rl2vocbjdw0xBugb5mnxCAw9ziocEFhzSyZBDA3AC/jU4nYzQ1Wi5TLNMG2JgS3K6z+NyPalGOzDSyZJa5inIPCDM5QjD3aG+AzZABYSJHxH2kOtXrEwIIOSLSTSlHNCKwDkMsuCjVXjtAtXqaRalmC6qow0EXG1ZQZLSO6ssRGZEXFmtiUVu/czaA2wF9DAiAqxmKMHdNMwMCANPWF3nfFtP317cxOc5+x8hRiJzobMkA+4tPEwwIYHnxWdPMgAAEVEt4Nto9ICDQTcUZC8oRjS0ZYH8rhFoyE99Bo6lxaHJJS3XTDW7FGxoHnpcZxDmh5Ltf1TfrsQzVGneCAmdoKEeo+KR9ZOQXUa01tK4la+SFxZpYPDSIAbGLujYGBCD2Rve3ZHRNLgOCG6CwMenW9wcAu7DfZli75XIYnjUPYXaE6XadcDu3oubPhhgQWi2XSZjKW8aA0FdoLSs+WUumrFcXwF3wceEeEHrh9mWW9sSA0InALhOmMsGAsJmlvTAU39PfkgGE4nNKOUJtu9Z55RMC5KyQteFaDuDz4c0+s1xuQWc9u2hXPptOsAW9HhDAcgncDc2CQwAXlBFvGhxuN3No0IE+3A2hVLsFnexzniPBoTEeDRkDQpXgkGVZeMxjHsP+DCwXHapqFhwCAKe439jJ74cMCN05Eu4jbnigM1EqZ0sbAwIAPObjErwmw36HMSCauvyGsLwVUp2ST4jGHGGuooLzLOkUad9H5r1+9tohS6bQgsZrgZTIC4s14S3AU+M2CQ619C5koTfa3gmkmj2NlsvAcph7k3xCdG4IBGFaPjzXhe04cPb0Cw4B+4tPliOaLJcpeCskeDbt7ZO4CGoFh6rVKr785S/PfcxaIl5GDIgNTT4hwPIZC8oRaM4Rb6H4nBADQnOOgMmtBwVOe/sUqgDGfhG1TZ3qrPtzpB627XSJUgFcSlssPp0QgYUmOW8K17Lnik+eI+eXTwiQt0LWhrdAJeQeEHof9qLNMIdS9TIgaEMQRYcavl4PCGDe0p4YO7ptuSl48RnmCOn7a27JYMHSnqbbdVsuL4O5m14g+a6TAbFYfAKGGBAQWSFBjpAHxERzjvgLlGRy4dXNgFjMEd/zmHW7ztbuMrvy8jj0CdGcI9zrJyQKGMoRGZEXFmvCXRCUYQyIit4bj7+gZmjCchkA7MK86NBkPGIMCJ1QarG431V0Y6rXcpn9/AW7ct+AlwwgDPgSzM3g9pbWddhOmCPhbXQ07DMGhM4cWWZpTwyIkkZRKmD/PmKCAQGIOUJwuxkGxKKlvSkGRIH2M6H4pBwpG9tHgly1Qn0RV6dwmaTIC4s1wbX1g6S3DMHti60QEx4QgDC8Gd40OuGteObbaGxpZIUIiMU0HHailoxOBgSwXxuA4Hbd+v4+k1sPZyw0CA4Nh0NcccUVuOKKK7ik90KOcAaEXsGhwpxjZDBHsBl6QOgWHFq8jTrMA0LvrRiLczidYFBRN9xOnkMsR84EObLnl7QyIOy5fSTIEe4Topfi6S7sIwVq22lGYGVEPmOxJngrJHgDMMEh3aYwC/QsE6JUgODREa6ju/0AjkKz5TL4TQPgm3XTa2u1XGY/f4Gxw+B2Y4dGkKuuhul23/fxz//8z+zPgFB8hqhWb+ckjiPIkWMa4fY5S/tw/qUV2nLXdbJkIF5Qwn0kZEAUNHrJAGLxGTwbN2ztTjQzIBbncHpniQHRxMUac0QsPt3ZFL7nYcsPc0SjnACwf56vHO4j55tPCJAjFmtjUVu/wvT9NT/shUOD6ftrhtsXWyFDmlzW3JJxCgV4oaX9bDbFeDTUbrlM4S20QsgDQud0O4B9cuv+IDi8dOeIteC/QDnSdfQWwcVimf3Zm02NMSAAYR8Ji89qOKhYNJQjtI9YBpyagf1S2qN2UAT3NQ/FF4Qcmc1m6PfaKFlhEWoqR8J9hHJEd2tXRuSFxZpYlEk2BbcvyiQzBoTmW7G94BhpigEBADOmrT8xYrlMsdgKYQwIncJlgOA8a7Ylw0SH/EUGhO62nSMUnxO0BcEhnQwIQEA+wxwhBkRVpygVIOwjYY4wBoTeHLEW9hFTOTJnVz6doHMmQE6GfhkbtbrWtSwSBagloz1HJEReWKyJRQiTJpd1w+3Wgqto0VBLhh8aAe/bhAcEhahm2BNsuXWLySyqGTIPCM1wOxa0TspMcMhM8Um3UWrJTDS37QCx+JwyDRrdolTA/D4SeEC0AQCb2guLsPj0KUfMMKn4PhLmSOgTMtEsXCYWn64r5IhmBBbYnyNb5BOikUklK/LCYk2I/guB5bJ+BgQADnOHhwaH2/XCZM4ChOkPzDAgAMF/YTbF8KwZBgQAeILi5WjYR80aAdCfI9yjI2zJEEtGMwOCiQ6FxSeYLbfmuSQAs3CMzJ3NuE+IiRwRis9Bv4OKFSAG2j0gQsYOFZ8kSqVTgwbY3wqxTFi3hzETTASZKJXJHHFn6LZ3ULSC16alybpdZuSFxZoQJXBNMSAAcdiJ4PY2AP0tGSaBC2rJ0HS7/kND1AYYh8OsOi2XKZjcujs1xoAAIEhpB8/GFAOCtcv25Yj+6XZXaJeRT4gJwSEutz5lHhBDv4yq5paMFSIWJLduCm53FhCLQojAWgb2EVZYTKeYhjmyZyBHeCtkim4o5933N1DZqGlfS9bIC4s1Id40TFkuAxB6o8Eb0YQtN7DftKdkcHJ5xiRwp1oYEKuCcgQeb8noFhwC9iMW1JJRablsWRYe+tCH4qEPfSiT9HYW5NaZB4RmwSEAmAkmgpwBof9WLN5GGQNCs8MqAGYiaPmuUbjdLszniEkGBHMVdadCS8bAPiIM1pJwmZEckRA53XRNiDbD3HJZrwcEwA90y3cx2hswBkTjsF64vVCcn7Ew4RNC4bHb6Iy1ZHQzIID5dpkIt2se3ZwrPucZEOqKz2q1ivvuu29+GQyxmIfbSwZyRDQR5AwIAzkiOM+OdgO4vW8AbrdsPqvV6+6iwRgQegsLUgtmOWLAFoDCFVqq1JJxdesUQUQ+Zxi1g32kr5lJJStyxGJNiDA3CQ6ZYEAwmNufGWVA0KFBrRAuJmNwQ3CnKBhsyYjtsrFBfX9RvIwEh0wwIJhMcghzm5xu94ThTSY4ZCJHhFbIpBvkiAm4XWSXdUIEduBXUKlu6l0G20eCHGlQjugeeIY4BD5lQ/GWgbadeNZMQuGyPQMDzzIiLyzWhOgqyn1C9N94RDVDU/r+wH43wKanX9+fwhVgbpMtGRGx8MgnxACUKsLc/V3yCdFvuewIMHfAgDCXIzNBY6QUDjw7dQM5IrTLXJYjBvYRQUp7YBBudwqBfoTjU44EXjK6W7vA/AWlHCKwBQNtOxEd90LkZGpiH5EQeWGxLoSHzeB2A1CqFU5zW77LGBAmJpfpNlq0XOwNepwBcVQzSwZ8eNNzZ4JPiH7kZM7SnqBUAy0ZsfhkLRnFgkN7e3t48pOfjCc/+cnY2wvac9xV1JtnQChsyawKUUrbhC03BSle+t6Mw+0GWDKWoOBLDAgTcLvYCjHNgBD3kdq0DcBMS0YsPm1q2xloyciIfMZiTfiCY6QTmsL4VXOHhuO7GDIPiJb2dYiCMmcf/CYuRcCA2KzrXws/NCaoM+EyAyp14cZkuVNBlEr/jYf7L7iYasoRz/Pw+c9/nv0Z4DB30XLx4OlvYxNmGBAAt7R3Z1McCoXLqgbadqI7MWdAmC0+98IcMQG3i66ip7e/jSaAnr+BugEGBNtHphPUw6F4E207Kj7nc+T88wkBcsRifTD9iJlRuJ27Ac7Y5LIJuF10jOycvh+AmZYMMO8qSnC7SgbEqiDHSN+b8el2A1Cq6BhJwmUmGBCiTHJ3+1sAzE23e+DtspZJwSGLzzYw4TIDLRkaArd9F55BBgQrLCyPtXY7BkSpAL6PzGZj1pJp6NYpwvw+UqGWjIGBZxmRFxZrglWRvsvgdhMMCJsNb7rcJ8QAlCoiFntnvw3ATEsG4Lzv6bBtxHKZhTAQt8EEh/TniHgbtYbB4WWCAeEIxk6UIyYYEACHuSf9bZQMwu3iHA55QJiA2y2hsOA5on8fcQQTQZYjBjRoAI5YjDunUbDC2THNBmQAOPLpzVALc6RiIEdkRF5YrAs6NNwpZ0AYgMksQVCGMSAM9N/m7Mp3gw1hWDQzYEQbAq1Dt+UyBSs+vZkxy2Vgvvg0ablcOJdyxJrPkb6/oZ0BAWCu+GwYZMmIxSdjQBjIEbH4ZO9fE2w78OKT1tFFDaVyRfs6ePE5RcNgS0ZG5IXFuiDREt9Fi0SpDDxsUQK3ZMgDApg/NNALIMxx2dBNg/rW4To6hloyFmuXTZngkInpdltwFS1NqG1nIEeEdhk9GxNwOyCIl1GO2PoLT0CcsZgwuF23LTcw3wphDIhzJEdM2AIAvPgU9xEjwS6xE7T8HgCgcR7KeQN5YbE2aIramfa54JABBoTj8Nuoyel2y7Yx84O0KQyD4S8TDAiAbwi0DtUMiFVBh4Yz6aJskAHBYG64qBnMEcpVQMgRA3A7sD9HTAkO0T5SGO8aZUDYwhA45UjZwDCreEExnyOFuXWYasnQPlLY24Zt+QCAlomWjITIWSHrIoS5N0bhwKRfNMKAsAT/hc2w/2ZClAoIeN8FeOw1gaHJZTo0aB0mRKkAfmiwdRhiQDiCFfWGF5jl6YBSjxyZPxCo+CxYPEesTbOFBXs2Blx4AX5o0Dq6qKJRqWpfBy8+Z6h5fQBAdUt/gSMWnzxHzo19ZM9QjizuI7uoY0tEds6jyAuLdRG+ERvToGe9azVx3ADcTmyMgj9D3e8DFlDXLOdNMYODMqbsNbENTLcDnPdN6zDBgAAAOPPraNst6D8yAJs8OvyQJWOpZ0DUajWcOXNm38dnYfFJr0nBUI54CzliTHBoIUc6VgsmmjJcFTVs21lA0wBLxrJtTH0HRcsVcsRsYcFypGKo+Fw4a7p2E+en7mbeClkfYRV5yAv6kX3HTP+NeqM1f8gYECo9IKKChp3oNSk3zW4ItA7X0IZw7uRIeHj5PaMMCICrGdJrYsInBOAyySxHDLBkAH4bpXUMDLXtaA6n5XXghHC7sX0kPH7oNTHFgKDik9bhG2rJEDrOc+R8LSvywmJtUAuCFCZNTbc7C+swxYAA+KFBazHBgAA4YkHrMMGAAMAKC9M5worPcB0mLZep+KS1mJpu9xbWYQpuX8wRIz4h4MUnraODGoqlctSXKIvFfaRmYOAZ4MWn6RyxFnJkdJ76hAB5YbE2qCdJYcQDAhzmpmgbYkAAAcwthonpdkCYtA/DhHAZsD9HTDEgRCowoEeUam9vD1dffTWuvvpqJukN7M8RE4JDwP4cMdWS2ZcjhgaeF3PElCgVwO3KKUy1dhlzKAxjolQLOTKtnJ9y3kA+Y7E+FjYmU5PLzkLS9QpbMEVEchcOjZapQ2NhYzIhOARwVIvClL6/vXBo6GBAeJ6Hj33sY+zPFPtzxCyqRVFuGpqyX9hHPFM54ujPkVWxL0cOm3n/Mh2aMEyI2wEcsaDwDLXtZESOWKwJe+HQgAGfEACwC/PrMCUmAwi8bwQMiI1a3cg6Fm+jG1uGVOoW1mEZsOUG9hefJi2XxUOji6oRwSFgf/FZNZQji8WnqRxZLD5Nwu1ijuyiPq9toTEWi08TLrwA9u0jtqm2nYTIC4s1sQhhmmJALL7pjDEgML8htA1CqYuFhREPCOy/BZqC253iApRq0HLZFQ70jtUytg7Pnn9NTDAggP37iCm4XZTSBsyJUgGAKwDmXYP7iLewjzTOkRwxYR0hK/LCYk0s3jRMwe2Lt1ET1u0U4qFhyicE2H8bNQW3nzM5snAbNWm57AnFZ98QAwIAm7SnMMWAWIS5TTEgnMK50ZIBANfix4/JHBERC9e30Dx0bqBaldb5KY4F5IXF2ljcEExNty9CmCbtdMVDw5SYDIA56LBnkAGxuCGYypHF4tNkjojF58hgjojFZxubxhgQizlSMwS3LxafJuF2cR8Zm2RA2CK6Vt9XfOmKxbOmZqq1KyHywmJN2AvQ4aahara4AHOb8ICgcIUKf2JwQ/AFmLtjyJYbAGxnPkdMtWSchXaZKcEhYCFHDLZkxBzpmsyRhQO9bohaWSicmzlikgExnyMtY+uwFnKkaWgoXkbkrJA1sTi8aYoBsXjTMAW3A/PDmybhdnGa2+R0++Jt1FRLplBYbMnoObyq1f06o+Jt1CTcLqJaRnNEOLw83zLGgFgscCqmWDKYR7VM5oiIapkUpRLPmplvo7F1/g5v5oXFmhAPjYFfQc0QA2LxplE1dOMB5gsLk3A7hM3aJANC3Ky7qKFhiAFRKM7D/DoEh2q1GgaDwb6Pi9oAJnNEvI2abMmIt9GOZc4DolhcRGBN7iM8R4wyIITic2QQXbME5LNtNXDEcSI++9yOvBWyJsRWiA7BoVXhFArwfIv93RTcDsxvCKYYEADmNgST0+1i8WnMchkLlvYwa7ksFp9Gp9sFVMuUB0SwDCFHjO4jizliDm4XUa2iwZaMWHzOjBYWwsyYwZaMjMgLizUhbgh9gwwIAJgJj8sU3A7MHxqmxGQAzB0apjwggmXwjcnkdLvtOHPFp6npduBcyhH+/jUJt88hnwZzRCw+AwaEuWcj5ohRBoSwj3gG0TXxrBkY1CmSEXlhsSZE3rdRBgSAWdi56vkbKBuwXKYQEQtTDAgAgAAdmoTbxVaISbgd4FLauhgQo9EIz3nOc/Cc5zwHo9GIfVzMEVMMCADMVRQwC7eL+8jYYI7YjgM3LD7bVgO2Qbj93MkR/v41mSPiEPiodP6qbgL5jMXaEKtIk9PtAHcD7NgtmJn0CEIUpjIJpVrCTcOYvj/maZ6mPCAoZnBQwgwdu4WWhp/nui7+9m//lv2ZQryNmhIcAjA3h1Oom0NwRMTCZNsOCATuHMzQtVswuRIxR0wisCJiUWyYyxFRXdmkTpGMyBGLNSHeRk3C7QCfojbdkhGnqJuGDMgAzMHcZZMbgnBomNb3p+JzYDpHwmcTMCDM5YhYfFYMtmTE4tMoSwYc1RqaFC4DLyxmvo16yyRziD+bjZa5HBGLT9+QdYSsyAuLNSEOOxllQIC3QkwyIAAOYXZRM+YBAcxL4JqyXAbm9SOM50j4bEy3ZChHTAoOAZiDuU0yIMQhcNMeEOQqapIBAXC5ddMtGfFAN5kjYrvMlFOzrEhVWLz1rW/F5Zdfjkqlgqc85Sn47Gc/K3td50yIhYVRBgQAL3xcpqFUuo2aZEAAmEMsTDIgRMTCtL4/+biYZEAAHNUyyYAA5tUMTbbtxOLqXMmRmel9JMwRk6JUABb2kUvNLUMogk3nSNZIXFj8xV/8BW688Ua86lWvwhe+8AU8/vGPxzOf+UycPn1axfqMh3holFtmJVZpQzBl3U5BG0LfoJgMMP9sTMLtYvFpOkeo+PSqZm/FVHyaFBwCwA4N0wwIMVdNe0DQPmK6JUP7yKBoNkeo+Jz4DhpNcwW5WHxumByKlxCJC4s3v/nNePGLX4wXvehFeMxjHoO3v/3tqFar+KM/+iMV6zMeouhQ1XRhEcLLpiyXKejQMGm5DIDB3G1sGrNcBuYhzJrhDYFaIfam6UMjWIdRDwhwYSrTcLtT4PuI6RyhwsJ0S4b2EZMsGYC3VNtWE5ZtbjpAvKBsXkiFxWQywZ133olrrrmGfwPbxjXXXINPfepTS79mPB6j2+3O/Xc+hXjTMAmlAnx40yQDAuAbgmkGBPVGO4ahVHFDMMqAABcdMsmAALjcuum2Hd1GTcPt4m3UKAMCfB8xyYAAePFpnAER7iMmnZqBebpp8+j56xMCJCwstre34bouLrpoPiEvuuginDp1aunX3HzzzWg2m+y/EydOpF+tgdio1THxHez5JbMMCAB7dkAy3Tz2MKPr8MpB39xrXGZ0HaVacNPplMw+l0qtgZlvY+iXjbZkAGDoBDlSP64nR2q1Gnzfh+/7qNW4u6xXbgEA/KbZ93txM8iRbtnsc9nYbMH1LfT9DbMMCADDcB9paMqRVeGG+whM50jt3MiRar0Fz7fQRQ2b9ZbRtWQN5ePaN910E2688Ub29263e14VF9XNJu76gbfCKVXwOIMMCAAoXfsWfPbuT+HJT/q3Rtfxnc/7FXzmo5fgMc98sdF1PPr7novPbL8SFz/+mvWfrDDqzUP4x+/77yhu1PFYkwwIAM6PvgWf+9rn8KTv/jdG1/Ed196Ez9x+Ao/54f+/0XVc8QM/hs+c/RYu+Z5nGl1H89BRfOFp/x2lzRYea9oD4kf/Oz779S/gyY97mtFlfMfz/0985vaH4Ypn/Uej67ji6T+Oz7RP4tInPMvoOraOXox/fNpbUKofxRUGWzIywvJ934/7yZPJBNVqFX/1V3+Fa6+9ln38uuuuQ7vdxv/+3/977ffodrtoNpvodDpoNBqpFp1HHnnkkUceeeiNuOd3orKoVCrhiU98Ij7ykY+wj3meh4985CO46qqr0q82jzzyyCOPPPI4EJEYt73xxhtx3XXX4UlPehK+93u/F7/zO7+DwWCAF73oRSrWl0ceeeSRRx55nEeRuLD4qZ/6KZw5cwa/8Ru/gVOnTuG7v/u78aEPfWjfQGceeeSRRx555HHhRaIZCxmRz1jkkUceeeSRx/kXSmYs8sgjjzzyyCOPPKIiLyzyyCOPPPLIIw9pkRcWeeSRRx555JGHtMgLizzyyCOPPPLIQ1rkhUUeeeSRRx555CEt8sIijzzyyCOPPPKQFnlhkUceeeSRRx55SIu8sMgjjzzyyCOPPKRFXljkkUceeeSRRx7SQrvHMwl9drtd3T86jzzyyCOPPPJIGXRurxPs1l5Y9Ho9AMCJEyd0/+g88sgjjzzyyCNj9Ho9NJvNlf+u3SvE8zw88MADqNfrsCxL2vftdrs4ceIE7r///gPrQZL/jgcj8t/x4MSF8Hvmv+PBCBm/o+/76PV6uOSSS2DbqycptCMWtm3jsssuU/b9G43GgU0Mivx3PBiR/44HJy6E3zP/HQ9GZP0do5AKinx4M4888sgjjzzykBZ5YZFHHnnkkUceeUiLA1NYlMtlvOpVr0K5XDa9FGWR/44HI/Lf8eDEhfB75r/jwQidv6P24c088sgjjzzyyOPgxoFBLPLII4888sgjD/ORFxZ55JFHHnnkkYe0yAuLPPLII4888shDWuSFRR555JFHHnnkIS0OTGHx1re+FZdffjkqlQqe8pSn4LOf/azpJaWOO+64A8997nNxySWXwLIsvO9975v7d9/38Ru/8Ru4+OKLsbGxgWuuuQb33HOPmcWmjJtvvhlPfvKTUa/XcezYMVx77bW4++675z5nNBrhhhtuwOHDh7G5uYl//+//PR588EFDK04eb3vb23DllVcyQZqrrroKH/zgB9m/n++/32K84Q1vgGVZeNnLXsY+dhB+x1e/+tWwLGvuv0c96lHs3w/C7wgA3/72t/GzP/uzOHz4MDY2NvC4xz0On//859m/n+/7zuWXX77vOVqWhRtuuAHAwXiOruvila98JR72sIdhY2MDj3jEI/C6171uzttDy3P0D0C8+93v9kulkv9Hf/RH/pe//GX/xS9+sd9qtfwHH3zQ9NJSxd/+7d/6v/7rv+7/9V//tQ/Af+973zv37294wxv8ZrPpv+997/O/+MUv+j/6oz/qP+xhD/P39vbMLDhFPPOZz/Tf8Y53+F/60pf8u+66y3/2s5/tP+QhD/H7/T77nF/4hV/wT5w44X/kIx/xP//5z/tPfepT/ac97WkGV50s3v/+9/sf+MAH/K9+9av+3Xff7f/ar/2aXywW/S996Uu+75//v58Yn/3sZ/3LL7/cv/LKK/2XvvSl7OMH4Xd81ate5V9xxRX+yZMn2X9nzpxh/34QfsezZ8/6D33oQ/3rr7/e/8xnPuN//etf92+77Tb/a1/7Gvuc833fOX369Nwz/PCHP+wD8D/60Y/6vn8wnuPrX/96//Dhw/6tt97q33vvvf5f/uVf+pubm/5b3vIW9jk6nuOBKCy+93u/17/hhhvY313X9S+55BL/5ptvNrgqObFYWHie5x8/ftz/rd/6Lfaxdrvtl8tl/8///M8NrFBOnD592gfgf+xjH/N9P/idisWi/5d/+Zfsc77yla/4APxPfepTppaZOba2tvw/+IM/OFC/X6/X8x/5yEf6H/7wh/2nP/3prLA4KL/jq171Kv/xj3/80n87KL/jr/zKr/jf//3fv/LfD+K+89KXvtR/xCMe4Xued2Ce43Oe8xz/537u5+Y+9vznP99/wQte4Pu+vud43rdCJpMJ7rzzTlxzzTXsY7Zt45prrsGnPvUpgytTE/feey9O/X/t3V9IU30YB/Cv79aZSeCK5f4YZyiRy6ywjcZJulo34kV0EQYjTkhEpaQV1Si66MK8C6qLogi90BgS2b+b/kwdGFRmWzoitRLtwiVd6CpLY+d5L6LDu/SmOG3vOTwfGMj5/S6eL4+cPbLzc8lkRt7CwkL4/X5d552ZmQEArFixAgAwMDCA79+/Z+T0eDwQRVGXOdPpNMLhML58+QJJkgyVr76+HjU1NRlZAGP1cHR0FC6XC6WlpQgGg5iYmABgnIx37tyBz+fDzp07UVRUhMrKSly9elVdN9p9Z35+Hu3t7airq0NeXp5h+rhlyxZEIhGMjIwAAF6+fIm+vj5UV1cDyF4fs/4lZFr7+PEj0uk07HZ7xnW73Y7Xr1/nqKq/J5lMAsCieX+u6Y2iKGhqakJVVRUqKioA/MgpCAKsVmvGXr3lHBoagiRJ+PbtG5YtW4auri6Ul5cjHo8bIl84HMaLFy/Q39+/YM0oPfT7/Whra0NZWRkmJydx5swZbN26FYlEwjAZ3717h0uXLuHIkSM4efIk+vv7cejQIQiCAFmWDXffuXXrFqanp7Fnzx4AxvldDYVCSKVS8Hg8MJlMSKfTaG5uRjAYBJC99w/dDxZM/+rr65FIJNDX15frUjRXVlaGeDyOmZkZ3LhxA7IsIxqN5rosTbx//x6NjY14+PAh8vPzc13OX/Pzrz0A2LBhA/x+P9xuNzo7O7F06dIcVqYdRVHg8/lw9uxZAEBlZSUSiQQuX74MWZZzXJ32rl27hurqarhcrlyXoqnOzk50dHTg+vXrWLduHeLxOJqamuByubLaR91/FGKz2WAymRY8vfvhwwc4HI4cVfX3/MxklLwNDQ24d+8eenp6sGrVKvW6w+HA/Pw8pqenM/brLacgCFi9ejW8Xi9aWlqwceNGnD9/3hD5BgYGMDU1hU2bNsFsNsNsNiMajeLChQswm82w2+26z7gYq9WKNWvW4M2bN4boIwA4nU6Ul5dnXFu7dq36kY+R7jvj4+N49OgR9u7dq14zSh+PHTuGUCiEXbt2Yf369di9ezcOHz6MlpYWANnro+4HC0EQ4PV6EYlE1GuKoiASiUCSpBxW9neUlJTA4XBk5E2lUnj69Kmu8hIRGhoa0NXVhe7ubpSUlGSse71eLFmyJCPn8PAwJiYmdJXzV4qiYG5uzhD5AoEAhoaGEI/H1ZfP50MwGFR/1nvGxXz+/Blv376F0+k0RB8BoKqqasFx75GREbjdbgDGue8AQGtrK4qKilBTU6NeM0ofZ2dn8c8/mW/rJpMJiqIAyGIfNXsMNIfC4TBZLBZqa2ujV69e0b59+8hqtVIymcx1aX/k06dPFIvFKBaLEQA6d+4cxWIxGh8fJ6Ifx4WsVivdvn2bBgcHafv27bo69kVEdODAASosLKTe3t6MI2Czs7Pqnv3795MoitTd3U3Pnz8nSZJIkqQcVv17QqEQRaNRGhsbo8HBQQqFQpSXl0cPHjwgIv3nW8x/T4UQGSPj0aNHqbe3l8bGxujx48e0bds2stlsNDU1RUTGyPjs2TMym83U3NxMo6Oj1NHRQQUFBdTe3q7uMcJ9J51OkyiKdOLEiQVrRuijLMtUXFysHje9efMm2Ww2On78uLonG300xGBBRHTx4kUSRZEEQaDNmzfTkydPcl3SH+vp6SEAC16yLBPRjyNDp0+fJrvdThaLhQKBAA0PD+e26N+0WD4A1Nraqu75+vUrHTx4kJYvX04FBQW0Y8cOmpyczF3Rv6muro7cbjcJgkArV66kQCCgDhVE+s+3mF8HCyNkrK2tJafTSYIgUHFxMdXW1mb8fwcjZCQiunv3LlVUVJDFYiGPx0NXrlzJWDfCfef+/fsEYNG6jdDHVCpFjY2NJIoi5efnU2lpKZ06dYrm5ubUPdnoI39tOmOMMcY0o/tnLBhjjDH2/8GDBWOMMcY0w4MFY4wxxjTDgwVjjDHGNMODBWOMMcY0w4MFY4wxxjTDgwVjjDHGNMODBWOMMcY0w4MFY4wxxjTDgwVjjDHGNMODBWOMMcY0w4MFY4wxxjTzL5NWVFVdmtHDAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "pred_plot = np.append(predict_from, preds)\n",
-    "true_plot = np.append(predict_from, timeseries[:len(pred_plot) - len(predict_from)])\n",
-    "plt.plot(pred_plot, label=\"Prediction\")\n",
-    "plt.vlines(len(predict_from)-1, ymin=np.min(target), ymax=np.max(target), colors='k', linestyles='dashed')\n",
-    "\n",
-    "plt.plot(true_plot, label=\"True\")\n",
-    "# plt.xlim([60, 80])\n",
-    "plt.legend()\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "quantum",
-   "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"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/research/new/stabilizer/stabilizer.ipynb b/research/new/stabilizer/stabilizer.ipynb
deleted file mode 100644
index 8c120fc..0000000
--- a/research/new/stabilizer/stabilizer.ipynb
+++ /dev/null
@@ -1,342 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from quantumreservoirpy import util\n",
-    "from quantumreservoirpy.reservoirs import Static, Incremental\n",
-    "\n",
-    "from qiskit.quantum_info import Clifford, random_clifford\n",
-    "from qiskit.extensions import HamiltonianGate\n",
-    "from qiskit.circuit.library import PauliGate\n",
-    "from qiskit.circuit.library import RYGate, RZGate, RZZGate"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "\n",
-    "class Stabilizer(Static):\n",
-    "    def __init__(self, n_qubits, n_ancilla, encoder, *args, **kwargs) -> None:\n",
-    "        super().__init__(n_qubits + 1, *args, **kwargs)\n",
-    "        self.n_logical = n_qubits\n",
-    "        self.n_ancilla = n_ancilla\n",
-    "        self.encoder = encoder\n",
-    "\n",
-    "        OP = random_clifford(n_qubits)\n",
-    "\n",
-    "        \n",
-    "        H = util.random_ising_H(num_qubits=self.n_logical, num_terms=40)\n",
-    "        T = 10 #s\n",
-    "        self.reservoir = HamiltonianGate(H, T, label=\"UT\")\n",
-    "\n",
-    "        cliff = Clifford(OP)\n",
-    "        ops = [elem[-self.n_logical:] for elem in cliff.stabilizer.to_labels()]\n",
-    "        self.ops = [PauliGate(elem).control(1) for elem in ops]\n",
-    "\n",
-    "    def before(self, circuit):\n",
-    "        circuit.reset(circuit.qubits)\n",
-    "        \n",
-    "    def during(self, circuit, timestep):\n",
-    "        circuit.barrier()\n",
-    "\n",
-    "        for i in range(self.n_ancilla):\n",
-    "            anc = self.n_logical\n",
-    "            circuit.initialize('0', anc)\n",
-    "            circuit.cx(i, anc)\n",
-    "            circuit.measure(anc)\n",
-    "        circuit.initialize('+', 0)\n",
-    "        circuit.initialize('+',1)\n",
-    "        circuit.append(self.encoder[timestep], [0, 1])\n",
-    "        \n",
-    "        circuit.append(self.reservoir, range(self.n_logical))\n",
-    "\n",
-    "    \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "encoder = {}\n",
-    "timestep = [i for i in range(10)]\n",
-    "timeseries = timestep * 10\n",
-    "SHOTS = 50000\n",
-    "n_qubits = 4\n",
-    "n_ancilla = 2\n",
-    "N = np.unique(timestep).size\n",
-    "epsilon = np.random.random() \n",
-    "for idx, elem in enumerate(np.unique(timestep)):\n",
-    "    theta = idx * 2 * np.pi / N + epsilon\n",
-    "    encoder[elem] = RZZGate(theta, str(elem))\n",
-    "    # encoder[elem] = ('0'*N + bin(idx)[2:])[-2:]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\users\\otkul\\sintef\\repo\\reservoircomputingexamples\\qreservoirpy\\qreservoirpy\\reservoirbase.py:38: UserWarning: Argument 'backend' must inherit from qiskits abstract 'Backend'. Using 'aer_simulator' instead\n",
-      "  warnings.warn(\"Argument 'backend' must inherit from qiskits abstract 'Backend'. Using 'aer_simulator' instead\")\n",
-      "C:\\Users\\otkul\\AppData\\Local\\Temp\\ipykernel_10720\\3584639998.py:19: DeprecationWarning: The property ``qiskit.quantum_info.operators.symplectic.clifford.Clifford.stabilizer`` is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. Use Clifford.stab properties instead.\n",
-      "  ops = [elem[-self.n_logical:] for elem in cliff.stabilizer.to_labels()]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2210.55x1120.39 with 1 Axes>"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n",
-    "qres = Stabilizer(\n",
-    "    n_qubits=n_qubits,\n",
-    "    n_ancilla=n_ancilla,\n",
-    "    encoder=encoder\n",
-    ")\n",
-    "\n",
-    "qres.circuit([0, 1, 2], merge_registers=True, transpile=False).draw('mpl')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "states = qres.run(\n",
-    "    timeseries=timeseries, \n",
-    "    shots=SHOTS,\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "WARMUP = 0.2 # 10%\n",
-    "warmup_idx = int(len(states) * WARMUP)\n",
-    "\n",
-    "xstates = states[:-1][warmup_idx:]\n",
-    "target = timeseries[1:][warmup_idx:]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2000x1000 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from quantumreservoirpy.plot import state_plotter\n",
-    "fig, ax = state_plotter(xstates, target)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from quantumreservoirpy.plot import feature_plotter\n",
-    "fig, ax = feature_plotter(xstates, target)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.svm import SVC\n",
-    "from sklearn.linear_model import RidgeClassifier\n",
-    "from sklearn.neighbors import KNeighborsClassifier\n",
-    "models = np.array([\n",
-    "    SVC(kernel=ker, max_iter=1000) for ker in ['linear', 'poly', 'rbf', 'sigmoid']\n",
-    "] \n",
-    "# + [\n",
-    "#     RidgeClassifier(alpha=alph, max_iter=1000) for alph in np.linspace(0, 1e-3, 9)\n",
-    "# ] \n",
-    "+ [\n",
-    "    KNeighborsClassifier(n_neighbors=n) for n in range(1, 10)\n",
-    "]\n",
-    ", dtype=object)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Score of KNeighborsClassifier(n_neighbors=1): 0.997037037037037\n",
-      "Score of SVC(kernel='poly', max_iter=1000): 0.997037037037037\n",
-      "Score of KNeighborsClassifier(n_neighbors=2): 0.9944444444444446\n",
-      "Score of KNeighborsClassifier(n_neighbors=3): 0.9918518518518519\n",
-      "Score of KNeighborsClassifier(n_neighbors=4): 0.9725925925925927\n",
-      "Score of KNeighborsClassifier(): 0.9529629629629628\n",
-      "Score of KNeighborsClassifier(n_neighbors=6): 0.8914814814814814\n",
-      "Score of KNeighborsClassifier(n_neighbors=7): 0.8151851851851853\n",
-      "Score of KNeighborsClassifier(n_neighbors=8): 0.7229629629629631\n",
-      "Score of KNeighborsClassifier(n_neighbors=9): 0.6133333333333332\n",
-      "Score of SVC(max_iter=1000): 0.48814814814814816\n",
-      "Score of SVC(kernel='linear', max_iter=1000): 0.07481481481481488\n",
-      "Score of SVC(kernel='sigmoid', max_iter=1000): 0.02962962962962965\n"
-     ]
-    }
-   ],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings('ignore')\n",
-    "\n",
-    "results = util.stress_test_models(xstates, target, models, test_to_train_ratio=1/3)\n",
-    "sorting = np.flip(np.argsort(results))\n",
-    "for model, res in zip(models[sorting], results[sorting]):\n",
-    "    print(f'Score of {model}: {res}')\n",
-    "    \n",
-    "\n",
-    "model = models[sorting][0]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "AssertionError",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[11], line 4\u001b[0m\n\u001b[0;32m      1\u001b[0m num_preds \u001b[39m=\u001b[39m \u001b[39m40\u001b[39m\n\u001b[0;32m      2\u001b[0m predict_from \u001b[39m=\u001b[39m timeseries[\u001b[39m-\u001b[39mnum_preds:]\n\u001b[1;32m----> 4\u001b[0m \u001b[39massert\u001b[39;00m(\u001b[39m0\u001b[39m \u001b[39m==\u001b[39m \u001b[39m1\u001b[39m)\n\u001b[0;32m      6\u001b[0m preds \u001b[39m=\u001b[39m qres\u001b[39m.\u001b[39mpredict(\n\u001b[0;32m      7\u001b[0m     num_pred\u001b[39m=\u001b[39mnum_preds,\n\u001b[0;32m      8\u001b[0m     model\u001b[39m=\u001b[39mmodel,\n\u001b[0;32m      9\u001b[0m     shots\u001b[39m=\u001b[39mSHOTS,\n\u001b[0;32m     10\u001b[0m     from_series\u001b[39m=\u001b[39mpredict_from\n\u001b[0;32m     11\u001b[0m )\n",
-      "\u001b[1;31mAssertionError\u001b[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "num_preds = 40\n",
-    "predict_from = timeseries[-num_preds:]\n",
-    "\n",
-    "assert(0 == 1)\n",
-    "\n",
-    "preds = qres.predict(\n",
-    "    num_pred=num_preds,\n",
-    "    model=model,\n",
-    "    shots=SHOTS,\n",
-    "    from_series=predict_from\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x2cdce87ea90>"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "pred_plot = np.append(predict_from, preds)\n",
-    "true_plot = np.append(predict_from, timeseries[:len(pred_plot) - len(predict_from)])\n",
-    "plt.plot(pred_plot, label=\"Prediction\")\n",
-    "plt.vlines(len(predict_from)-1, ymin=np.min(target), ymax=np.max(target), colors='k', linestyles='dashed')\n",
-    "\n",
-    "plt.plot(true_plot, label=\"True\")\n",
-    "# plt.xlim([60, 80])\n",
-    "plt.legend()\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "quantum",
-   "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"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/research/new/stabilizer/stabilizercx.ipynb b/research/new/stabilizer/stabilizercx.ipynb
deleted file mode 100644
index 2c7bcbf..0000000
--- a/research/new/stabilizer/stabilizercx.ipynb
+++ /dev/null
@@ -1,333 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from quantumreservoirpy import util\n",
-    "from quantumreservoirpy.reservoirs import Static\n",
-    "\n",
-    "from qiskit.quantum_info import Clifford, random_clifford\n",
-    "from qiskit.extensions import HamiltonianGate\n",
-    "from qiskit.circuit.library import PauliGate\n",
-    "from qiskit.circuit.library import U1Gate"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "\n",
-    "class Stabilizer(Static):\n",
-    "    def __init__(self, n_qubits, n_ancilla, encoder, memory=np.inf, backend=None) -> None:\n",
-    "        super().__init__(n_qubits + 1, memory, backend)\n",
-    "        self.n_logical = n_qubits\n",
-    "        self.n_ancilla = n_ancilla\n",
-    "        self.encoder = encoder\n",
-    "\n",
-    "        OP = random_clifford(n_qubits)\n",
-    "        self.reservoir = OP\n",
-    "        # H = util.random_ising_H(num_qubits=n_qubits, num_terms=40)\n",
-    "        # T = 1 #s\n",
-    "        # self.reservoir = HamiltonianGate(H, T, label=\"UT\")\n",
-    "            \n",
-    "        cliff = Clifford(OP)\n",
-    "        ops = [elem[-self.n_logical:] for elem in cliff.stabilizer.to_labels()]\n",
-    "        self.ops = [PauliGate(elem).control(1) for elem in ops]\n",
-    "\n",
-    "    def before(self, circuit):\n",
-    "        return super().before(circuit)\n",
-    "    def during(self, circuit, timestep):\n",
-    "        circuit.barrier()\n",
-    "\n",
-    "        for i in range(self.n_ancilla):\n",
-    "            anc = self.n_logical\n",
-    "            circuit.initialize('0', anc)\n",
-    "            circuit.cx(i, anc)\n",
-    "            # circuit.append(self.ops[i], [anc] + list(np.arange(self.n_logical)))\n",
-    "            # circuit.h(anc)\n",
-    "            circuit.measure(anc)\n",
-    "        \n",
-    "            circuit.append(self.encoder[timestep], [i])\n",
-    "        circuit.append(self.reservoir, range(self.n_logical))\n",
-    "    def after(self, circuit):\n",
-    "        return super().after(circuit)\n",
-    "    \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "encoder = {}\n",
-    "timestep = [0, 1, 2, 3]\n",
-    "timeseries = timestep * 10\n",
-    "SHOTS = 10000\n",
-    "n_qubits = 4\n",
-    "n_ancilla = 3\n",
-    "N = np.unique(timestep).size\n",
-    "epsilon = np.random.random()\n",
-    "for idx, elem in enumerate(np.unique(timestep)):\n",
-    "    theta = idx * 2 * np.pi / N + epsilon\n",
-    "    encoder[elem] = U1Gate(theta, str(elem))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2210.55x1120.39 with 1 Axes>"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n",
-    "qres = Stabilizer(\n",
-    "    n_qubits=n_qubits,\n",
-    "    n_ancilla=n_ancilla,\n",
-    "    encoder=encoder\n",
-    ")\n",
-    "\n",
-    "qres.circuit([0, 1, 2], merge_registers=True, transpile=False).draw('mpl')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "states = qres.run(\n",
-    "    timeseries=timeseries, \n",
-    "    shots=SHOTS,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "WARMUP = 0.1 # 10%\n",
-    "warmup_idx = int(len(states) * WARMUP)\n",
-    "\n",
-    "xstates = states[:-1][warmup_idx:]\n",
-    "target = timeseries[1:][warmup_idx:]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2000x2000 with 4 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from quantumreservoirpy.plot import state_plotter\n",
-    "fig, ax = state_plotter(xstates, target)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 53,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from quantumreservoirpy.plot import feature_plotter\n",
-    "fig, ax = feature_plotter(xstates, target)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.svm import SVC\n",
-    "from sklearn.linear_model import RidgeClassifier\n",
-    "from sklearn.neighbors import KNeighborsClassifier\n",
-    "models = np.array([\n",
-    "    SVC(kernel=ker, max_iter=1000) for ker in ['linear', 'poly', 'rbf', 'sigmoid']\n",
-    "] \n",
-    "+ [\n",
-    "    RidgeClassifier(alpha=alph, max_iter=1000) for alph in np.linspace(0, 1e-3, 9)\n",
-    "] \n",
-    "+ [\n",
-    "    KNeighborsClassifier(n_neighbors=n) for n in range(1, 10)\n",
-    "]\n",
-    ", dtype=object)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Score of KNeighborsClassifier(n_neighbors=2): 0.21916666666666668\n",
-      "Score of SVC(kernel='poly', max_iter=1000): 0.21750000000000003\n",
-      "Score of KNeighborsClassifier(n_neighbors=3): 0.21249999999999997\n",
-      "Score of KNeighborsClassifier(n_neighbors=4): 0.19833333333333325\n",
-      "Score of KNeighborsClassifier(n_neighbors=6): 0.19333333333333325\n",
-      "Score of KNeighborsClassifier(): 0.18999999999999992\n",
-      "Score of KNeighborsClassifier(n_neighbors=7): 0.18833333333333332\n",
-      "Score of SVC(max_iter=1000): 0.1825\n",
-      "Score of KNeighborsClassifier(n_neighbors=8): 0.1725\n",
-      "Score of KNeighborsClassifier(n_neighbors=1): 0.16833333333333336\n",
-      "Score of KNeighborsClassifier(n_neighbors=9): 0.16749999999999995\n",
-      "Score of SVC(kernel='sigmoid', max_iter=1000): 0.1483333333333333\n",
-      "Score of SVC(kernel='linear', max_iter=1000): 0.13249999999999998\n",
-      "Score of RidgeClassifier(alpha=0.0, max_iter=1000): 0.13083333333333338\n",
-      "Score of RidgeClassifier(alpha=0.000125, max_iter=1000): 0.12416666666666668\n",
-      "Score of RidgeClassifier(alpha=0.000375, max_iter=1000): 0.12166666666666665\n",
-      "Score of RidgeClassifier(alpha=0.001, max_iter=1000): 0.12166666666666663\n",
-      "Score of RidgeClassifier(alpha=0.0005, max_iter=1000): 0.12083333333333336\n",
-      "Score of RidgeClassifier(alpha=0.000625, max_iter=1000): 0.12\n",
-      "Score of RidgeClassifier(alpha=0.00025, max_iter=1000): 0.11916666666666668\n",
-      "Score of RidgeClassifier(alpha=0.000875, max_iter=1000): 0.11833333333333335\n",
-      "Score of RidgeClassifier(alpha=0.00075, max_iter=1000): 0.11666666666666668\n"
-     ]
-    }
-   ],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings('ignore')\n",
-    "\n",
-    "results = util.stress_test_models(xstates, target, models, test_to_train_ratio=1/3)\n",
-    "sorting = np.flip(np.argsort(results))\n",
-    "for model, res in zip(models[sorting], results[sorting]):\n",
-    "    print(f'Score of {model}: {res}')\n",
-    "    \n",
-    "\n",
-    "model = models[sorting][0]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Predicting...: 100%|██████████| 10/10 [00:03<00:00,  2.87it/s]\n"
-     ]
-    }
-   ],
-   "source": [
-    "predict_from = timestep\n",
-    "num_preds = 10\n",
-    "\n",
-    "\n",
-    "preds = qres.predict(\n",
-    "    num_pred=num_preds,\n",
-    "    model=model,\n",
-    "    shots=SHOTS,\n",
-    "    from_series=predict_from\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x13478d91e50>"
-      ]
-     },
-     "execution_count": 57,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "pred_plot = np.append(predict_from, preds)\n",
-    "true_plot = np.append(predict_from, timeseries[:len(pred_plot) - len(predict_from)])\n",
-    "plt.plot(pred_plot, label=\"Prediction\")\n",
-    "plt.vlines(len(predict_from)-1, ymin=np.min(target), ymax=np.max(target), colors='k', linestyles='dashed')\n",
-    "\n",
-    "plt.plot(true_plot, label=\"True\")\n",
-    "plt.legend()\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "quantum",
-   "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"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/research/old/stabilizer.ipynb b/research/old/stabilizer.ipynb
deleted file mode 100644
index cd9405e..0000000
--- a/research/old/stabilizer.ipynb
+++ /dev/null
@@ -1,701 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 219,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "from qreservoirpy import QReservoir, Layers, utilities\n",
-    "\n",
-    "\n",
-    "from qiskit.quantum_info import random_unitary\n",
-    "from qiskit_aer import AerSimulator\n",
-    "backend = AerSimulator(method=\"statevector\")\n",
-    "\n",
-    "from qiskit.quantum_info import Clifford, random_clifford\n",
-    "from qiskit.circuit.library import PauliGate\n",
-    "from qiskit.extensions import HamiltonianGate\n",
-    "\n",
-    "import warnings\n",
-    "warnings.filterwarnings('ignore')\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Initialization"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 220,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['-IXY', '-XYZ', '+ZXI']\n",
-      "['IXY', 'XYZ', 'ZXI']\n",
-      "[Instruction(name='cpauli', num_qubits=4, num_clbits=0, params=['IXY']), Instruction(name='cpauli', num_qubits=4, num_clbits=0, params=['XYZ']), Instruction(name='cpauli', num_qubits=4, num_clbits=0, params=['ZXI'])]\n"
-     ]
-    }
-   ],
-   "source": [
-    "n_qubits = 3\n",
-    "n_ancilla = 3\n",
-    "SHOTS = 10000\n",
-    "timeseries = [0, 1, 2, 3, 0, 1, 2, 2, 3] * 10\n",
-    "encoder = {\n",
-    "    0: '00',\n",
-    "    1: '01',\n",
-    "    2: '10',\n",
-    "    3: '11'\n",
-    "} \n",
-    "\n",
-    "\n",
-    "OP = random_clifford(n_qubits)\n",
-    "\n",
-    "H = utilities.random_ising_H(num_qubits=n_qubits, num_terms=40)\n",
-    "T = 1 #s\n",
-    "UT = HamiltonianGate(H, T, label=\"UT\")\n",
-    "\n",
-    "cliff = Clifford(OP)\n",
-    "\n",
-    "print(cliff.stabilizer.to_labels())\n",
-    "ops = [elem[-n_ancilla:] for elem in cliff.stabilizer.to_labels()]\n",
-    "print(ops)\n",
-    "ops = [PauliGate(elem).control(1) for elem in ops]\n",
-    "\n",
-    "print(ops)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 221,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn.svm import SVC\n",
-    "from sklearn.linear_model import RidgeClassifier\n",
-    "from sklearn.neighbors import KNeighborsClassifier\n",
-    "models = np.array([\n",
-    "    SVC(kernel=ker, max_iter=1000) for ker in ['linear', 'poly', 'rbf', 'sigmoid']\n",
-    "] \n",
-    "+ [\n",
-    "    RidgeClassifier(alpha=alph, max_iter=1000) for alph in np.linspace(0, 1e-3, 9)\n",
-    "] \n",
-    "+ [\n",
-    "    KNeighborsClassifier(n_neighbors=n) for n in range(1, 10)\n",
-    "]\n",
-    ", dtype=object)\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 222,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2210.55x1287.61 with 1 Axes>"
-      ]
-     },
-     "execution_count": 222,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n",
-    "def build_method(circuit, timestep, encoding, reservoir):\n",
-    "    # circuit.measure(range(2))\n",
-    "    # circuit.initialize(encoding[timestep], range(2))\n",
-    "    circuit.barrier()\n",
-    "    circuit.initialize(encoding[timestep], [2, 3])\n",
-    "    circuit.append(reservoir, range(n_qubits))\n",
-    "    circuit.append(UT, range(n_qubits))\n",
-    "    for i in range(n_ancilla):\n",
-    "        anc = i + n_qubits\n",
-    "        circuit.initialize('+', anc)\n",
-    "        circuit.append(ops[i], [anc] + list(range(n_qubits)))\n",
-    "        circuit.h(anc)\n",
-    "        circuit.measure(anc)\n",
-    "    \n",
-    "\n",
-    "\n",
-    "qres = QReservoir(qubits=n_qubits + n_ancilla, layers=[\n",
-    "    Layers.H(),\n",
-    "    Layers.Timeseries(build_method=build_method, \n",
-    "                      encoding = encoder,\n",
-    "                      reservoir=OP)\n",
-    "])\n",
-    "qres.circuit.draw('mpl')\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Running"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 223,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Simulating:   0%|          | 0/1 [00:00<?, ?it/s]"
-     ]
-    }
-   ],
-   "source": [
-    "states = qres.run(\n",
-    "    timeseries=timeseries, \n",
-    "    shots=SHOTS,\n",
-    "    transpile=True\n",
-    "\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# qres.circuit.draw('mpl')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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mphQInN3w8oMf/EB33HGHZmdndcEFF2j//v164okndPnll6/0+chHPqKTJ0/qAx/4gObm5nTDDTdofHxcO3bskORvPf/KV76ij3/84zp9+rQuvfRSffjDH9bhw4e3+vOjWI6/bGq5vflz/AEAmovrZpVMTimdXlAo1KVwuE/BYFmbaQEAAAAAqLxA6Nx9yumHplJWAfpmRvHNAjxXOtG/wdY0w9+hsvdoU+f4AwA0D8eZVDQ6rpmZzEqbZZmKx4dk2wN1HBnQnDgHRrl4zQAAAGxg5XpqSoXrpnA9tdmUc/7LMs921kY5/gAAjc9xJhWJjOUFUiQplcooEhmT40zWaWQAAAAAAMgPkJjx3J21D/o3ZoxASosimNLO2izHHwCgcbluVtHouArtl821jY6Oy3WztR0YAABoLZ4rnZ6QFo/4t55b7xEBbSnrujo2MaFnjxzRsYkJZV3+FtuN60kTJ6Uj8/6t20y5kzptaU9CCvTktwcsv52SCS2r7JopaCHk+AMANIhkcmrdjpTVPE+ans4omZzS4GB/7QYGAABax6IjZaL5GRoClr/CmAtfQM1MOo7Go1FlZs7+LZqWpaF4XAM2f4vtwMlI0VlpZulsm9Uhxbslu1myjHba0o7h5cw/af/66bYwO1JaHDtTGkG9VsZsC/snjuu2pOUYUqDX7wcAQBWl0wsV7QcAAJBn0ZHmIutTXWdTfvuiU59xAW1m0nE0FonkBVIkKZNKaSwS0aTD32KrczJSZCY/kCJJqSW/3Sm+xq7xGEFp+6DUebN/SyCl5RFMqbdFxy9a9MoBae6Qf3uivzYncuT4AwA0iFCoq6L9AAAAVniuvyOlYKHg5bbMKCm/gCrLuq7Go1FtlNt3fHSUlF8tzPX8HSkbvBtrdLbJUn6hrRBMqadGWBlDjj8AwBqum9XExDEdOfKsJiaO1aROSTjcJ8syZRTZLGkYUm+vqXC4r+pjAQAALeZMcv28O48nZaf9fg2OOhNoZlPJ5LodKXk8T5npaU0lG/9vEZuTPLV+R8pqnqTpJb8f0IiomVIv51wZY/grY3YMV39nCDn+AADLHGdS0eh4Xv0SyzIVjw/JtgeqdtxgMKB4fEiRyJgMI3+xWi7AEosNKRhkHQgAAChTNl3ZfnVCnQk0u4V0aX9jpfZD80lvEEjZTD+g1rgiUS+NtjKGHH9oB/WqTwRUWpVey44zqUhkbF0h+FQqo0hkTI4zWZHjFGPbA0okRtTTk19x0LJMJRIjVQ3mAACAFhYIVbZfHVBnAq2gK1Ta31ip/dB8QiUu6y+1H1BrhucVSlTYejKZjHbv3q35+XmZpnnub6i2xSN+jZRz2fOIH+AAsDWLjr8bbHUQM2D5dYNIZ4dmUqXXsutm1d8fXxdIyTEMP6hx9Gi06rtDXDerZHJK6fSCQqEuhcN97EgBNqnhzoHR8HjNoCV5rl+bNJtS4ewQhn8+tfdoQy4szLqu4v39xdMjGYZMy1L06FEFgo03fiBn5bWcShWum8JrueW5ntT/vF9svsi7sawO6ehlUrBICmig0so5/+XKRL20wMoYoGk0Qn0ioBKq+FpOJqeKBlIkf64zPZ1RMjm16WOUKhgMaHCwXzff/FYNDvYTSAEAAFtjBP2FJ/6dtQ/6N2asIQMpEnUm0DoCwaCG4st/i2uLJS7fH4rFCKS0sKAhxbv9fxd5N1asm0AKGhdXJ+plW9hf+bLurSPHkAK9fj8Am3fO+kTy6xOR8guNrsqv5XR6oaL9AAAAGkqnLe1JSIGe/PaA5bc38G516kyglQzYtkYSCZk9+X+LpmVpJJGg/k8bsE0pYUk9a1J5WR1+u83GWDQwMtDVS25lzFxEfkBl9cWxxl8ZAzSNcuoTbR+s1aiA8lX5tRwKdVW0HwAAQMPptKUdw8vnVWk/E8S2cMPPu6kzgVYzYNvaNzysqWRSC+m0ukIh9YXD7EhpI7YpDXdJyVN+sflQhxTeyY6Uasi6Ln9rFUQwpZ46bUmJIrnvYw29MgZoGtkSV2eV2g+olyq/lsPhPlmWqVQqUyx9sSzLVDjct6nnBwAAaAhGsOkWUfWFwzIt65x1JvrCZLZA8wgEg+ofHKz3MFBHQUMa3FXvUbS2ScfReDSalyrStCwNxePsAtsk0nzVW6ct7T0mXfi4X2z+wsf9oncEUoDKoD4RWkWVX8vBYEDx+JCkoumLFYsNUb8EAFA/niudnpAWj/i3pGlFm6DOBACgXJOOo7FIZF3NrUwqpbFIRJMO9YM3gysijSC3MqbzZv+2wbcYA02F+kRoFTV4Ldv2gBKJEfX05CeptSxTicSIbHtg088NAMCWLDrSiX7plQPS3CH/9kS/3w60AepMAABKlXVdjUejhXczLreNj44q67IwpVyk+QLQ2qhPhFZRo9eybQ9oeHifkskppdMLCoW6FA73sSMFAFA/i87y59+aCwLZ1HJ7YxcPByqFOhPAWa5HvQ2gmKlkct2OlDyep8z0tKaSSdLtlYlgCoDWR30itIoavZaDwYAGB/sr8lwAAGyJ5/qfe2sDKf6DkgwpM+oXFWdxDNoAdSYAyclI0VlpZulsm9Uhxbv9wuZAu1tIl1ZLtdR+OItgCoD20Gn7k+wzSb9AdyDkp0Ni0o1m0wCvZVaBAQBq5kwyfwHBOp6Unfb7NVlRcQBA+ZyMFJlZH2JPLfntCYuACtAVKq2Waqn9cBbBFADtI1efCGh2dXwtswoMAFBT2RJXTJbaDwDQtFzPn4tssFdRo7PScBeLvdDe+sJhmZalTCpVuG6KYci0LPWFqR9cLhKgAwCAkuRWga0OpEhnV4E5mfqMCwDQwgIlrpgstR8AoGklT62fi6zmSZpe8vsB7SwQDGooHvfvGGsii8v3h2Ixam5tAsEUAABwTudaBSb5q8DcQh0AANisbWG/NpiKLTE2pECv3w8A0NLSGwRSNtMPaGUDtq2RREJmT09eu2lZGkkkNGBTP3gzSPMFoGTUSUArcN2skskppdMLCoW6FA73KRhkbcG5lLMKbHBXzYYFAGh1RlAy49JcRH5AZXXUfvlE1IxRBw8A2kCoxKuYpfYDWt2AbWvf8LCmkkktpNPqCoXUFw6zI2ULeHsBUBLqJKAVOM6kotFxzcyczUdlWabi8SHZ9kAdR9b4WAUGAKibTltSQspE84vRByw/kNLJykoAaAfhnf51iNRS4R3zhvzHwztrPTKgcQWCQfUPDtZ7GC2DpbgojedKpyekxSP+refWe0SoIeokoBU4zqQikbG8QIokpVIZRSJjcpzJOo2sObAKDABQV522tPeYdOHj0p5H/Nu9RwmkAEAbCRr+gk5pffLH3P1YNxk0AFQPwRSc26IjneiXXjkgzR3yb0/0++1oedRJQCtw3ayi0XF5BV6nubbR0XG5bra2A2siuVVgG2SsVy+rwAAA1WQEpe2DUufN/i2pvQCg7dimlLCknjWLuKwOv53MGQCqiWAKNrbo+PmJV2+nl6Rsym8noNLyyqmTADSqZHJq3Y6U1TxPmp7OKJmcquGomgurwAAAAAA0AtuUjl0mPf4m6ZEe//boZQRSAFQfwRQU57l+XuKN9iRkRkn51eKok4BWkE4vVLRfu2IVGAAAAIBGEDSkwV3Szbv9WxZ1AagFMpujuDPJ9TtS8nhSdtrvt32wVqNCjVEnAa0gFOqqaL92ZpvScJe/Gy295P/th3cyeQEAAACaRdZ1NZVMaiGdVlcopL5wWIFgm6VO9Nzl615pKRCStoVJHwngnLj8ieKy6cr2Q1PK1UlILRXeo2TIf5w6CWhk4XCfLMtUKpUpWDfFMCTLMhUO99V+cE0otwoMAAAAQHOZdByNR6PKzJxdPGtalobicQ3Ydh1HVkOLjp+JZfUC4oAlmXGps01+BwA2hTRfKC4Qqmw/NCXqJKAVBIMBxeNDkvzAyWq5+7HYkIJBPhYBAAAAtKZJx9FYJJIXSJGkTCqlsUhEk04b1MWlNjCALeCqEYrbFvYj8+suoecYUqDX74eWRp0EtALbHlAiMaKenvwXrGWZSiRGZNsDdRoZAAAAAFRX1nU1Ho2q4Fb95bbx0VFl3Raui0ttYABbRJovFGcE/S2OcxH5AZXVHzbLARYzRk7JNkGdBLQC2x7Q8PA+JZNTSqcXFAp1KRzuY0cKAACQ63GuC6B1TSWT63ak5PE8ZaanNZVMqn9wsGbjqilqAwPYIoIp2FinLSlRJJdkjFySbYY6CWgFwWBAg4P99R4GAABoIE5Gis5KM0tn26wOP90tu7ABtIKFdGn1bkvt15SoDQxgiwim4Nw6bWnH8HIEP+3XSNkWZkcKAABFsLoZAJqHk5EiM+uTvqSW/HbS2gJoBV2h0urdltqvKVEbGMAWEUxBaYwgWxwBACgBq5sBoHm4nv+eXSx7viFpdNZPd0tQHEAz6wuHZVqWMqlU4bophiHTstQXbuG6uLnawNmUCr/zG/7j1AYGUARJ4gEAACokt7p5dSBFOru62cnUZ1wAgMKSp9a/Z6/mSZpe8vsBQDMLBIMaisf9O8aa6PDy/aFYTIFgC2chydUG9u+sfdC/oTYwgA0QTAEAAKiAc61ulvzVzW6hDgCAukhvEEjZTD+gHWRdV8cmJvTskSM6NjGhrOvWe0go0YBtaySRkNnTk9duWpZGEgkN2G1QF7fTlvYkpED+70ABy2+nNjCADZDmCwAAoALKWd08uKtmwwIAbCBU4oy41H5Aq5t0HI1Ho8rMzKy0mZaloXi8PS7Et4AB29a+4WFNJZNaSKfVFQqpLxxu7R0pa1EbGMAmcUoIAABQAaxuBoDmE97p17VKLRXNni+rw++HCvBcLl42sUnH0Vgksq7eRiaV0lgk0j47G1pAIBhU/+BgvYdRX9QGBrAJpPkCAACoAFY3A0DzCRpSvNv/d5Hs+Yp1U3y+IhYd6US/9MoBae6Qf3ui329Hw8u6rsaj0cKFy5fbxkdHSfkFAGhpBFPQHDxXOj0hLR7xbz1O0AAAjSW3urnY9TZDUi+rmwGg4dimlLCknjXBbqvDb7fN+oyrpSw60lxEys7kt2dTfnsFAyquJ02clI7M+7fUKquMqWQyL7XXOp6nzPS0ppLJ2g2qgVFXBgBaE2sj0fgWHSkTzT/xDliSGacwGACgYeRWN0dm/MDJ6ms3rG4GgMZmm9Jwl1/XKr3k7yIM7+Q9uyI815/PFUyk5kkypMyoX79giym/nIwUnc2vYWZ1+J/PBMW2ZiGdrmi/VkZdGQBoXexMqQFWxmxBDVcwAQCwVaxuBoDmFTSkwV3Szbv9WwIpFXImuX4+l8eTstN+vy1wMv6Chpk1tclSS367k9nS07e9rlCoov22pIEzV+TqyqzdxZOrKzPp+NcwXDeriYljOnLkWU1MHJPrZusxXABAmdiZUmWsjNmCGq5gAgCgUljdDADAKtkSdyqU2q8A1/Pn3RvMHDU6638+83m8OX3hsEzLUiaVKlw3xTBkWpb6wuHqDqSBM1ecs66MYWh8dFT/x/1hjR7+umZmzkb4LMtUPD4k2x6o4YgBAOViZ0oVsTJmi2q0ggkAgEpjdTMAAMsCJe5UKLVfAclT6+fdq3mSppf8fticQDCooXjcv2OsObFZvj8UiykQrOJCxwbPXFFqXZn/NPLbeYEUSUqlMopExuQ4k1UeJQBgKwimVMm5VsZI/soYUn5toAYrmAAAAAAAVbQt7O8cULGVBYYU6PX7bVJ6g0DKZvqhsAHb1kgiIbOnJ6/dtCyNJBLVrQdyzswV8jNX1DHlV6n1Ys7Xq+vacptZRkfHSfkFAA2MNF9VUs7KmMFdNRtW1WRdV1PJpBbSaXWFQuoLh7e+IqUGK5gAAAAAAFVkBP0UTHMR+QGV1RfDlwMsZmxLqZtDJV7ZKLUfihuwbe0bHq78/P9cyslcsX2wumMpotR6Ma/q/ILtnidNT2eUTE5pcLC/giMDAFQKpxJV0k4rYyYdR+PRaN52VtOyNBSPb21lSm4FUzalwqtPDP/xLaxgAgAAAABUWactKVGk1kVsy7Uuwjv92qSppaIzR1nLNcywdYFgUP2Dg7U9aBNkrjhnXRkZmleXXtCbNnyedHqhOgMEAGwZab6qpF1Wxkw6jsYikXV5QTOplMYiEU06W8hZmlvB5N9Z+6B/s8UVTAAAAACAGui0pb3HpAsfl/Y84t/uPVqRouFBQ4p3+/8uMnNUrJsaZk2tCTJXlFJXZlxD8s5xKS4U6qrG8GrPc6XTE9LiEf+2jinYNiPrujo2MaFnjxzRsYkJZd3mGj+A6iCYUiW5lTEbZIVVb5OvjMm6rsaj0cIrLpbbxkdHt/aB02lLexJSID8nqwKW316BE28AAAAAQA0YQT8FU+fN/m0FF8bZppSwpJ41CxatDr/dNit2KNRDDWrvVMJGdWUifzqmBeu6dXGWHMOQentNhcN9NRhplS060ol+6ZUD0twh//ZEv9/eBCYdR/H+fn35wAE5hw7pywcOKN7fv7UFwwBaguF5BfcetpxMJqPdu3drfn5eplmbsygnI0WWN2wUyArb9Cd0xyYm9OUDB87Z79bHH9/6FmDPXc6RmvZXmmwLl33i7bpZJZNTSqcXFAp1KRzuUzBIPBEAALSuepwDo7nxmkGzcz2/Nml6yc8EEd7JjpSWsegs196RCl5laaAFl8XqyjrOpCKRMUn561JzAZZEYkS2PVCHEVfQyv/T2suNjff/VEguA8u6hcPL/0kjicTWUtoDaDjlnP82eZKpxpZbGROdzS9Gb3X4W4ybOZAiSQvp0nKRltpvQ7kVTJvkOJOKRsc1M5NZabMsU/H4UPOfqAAAAAAAJPmBk8Fd9R4FqqLKtXcqqVhdGdseUCIxUvD6RCzWAtcnPNf//ylYvciTZEiZUWnHcEOmbD9nBhbD0PjoqPYNDysQbLzxA6g+gilVZpvScFdrrozpCpWWi7TUftWSW/mx9rMwlcooEhlrjZUfqIhiq4cAAAAAAA2g0/YvxG8xc0U92faAhof3tWbmjDPJ/EDXOp6Unfb7bWHBbLVMJZPragLn8Txlpqc1lUxuPQMLgKZEMKUGWnVlTF84LNOylEmlCkftDUOmZakvXL+cpa6bVTQ6vtGiAo2Ojmt4eF9rnLhg0yYdR+PRaN6Jk2lZGorH2cILAAAAAI1ii5krGkEwGNDgYH+9h1F52RIzk5Tar8ZqmoEFQFPi6jE2LRAMaige9++sraC2fH8oFqvryv5kcipv6+xanidNT2eUTE5t/WCeK52ekBaP+Leeu/XnRE3kcqKuXYGSSaU0FolQZA4AAAAAgHMJlJiZpNR+NdYsGVgA1A/BFGzJgG1rJJGQ2dOT125aVkMU5UqnFyrar6hFRzrRL71yQJo75N+e6Pfb0dDOmRNV0vjoqLIuwTEAAAAAAIraFvZr2KhYbntDCvT6/RpQLgPLugXDOYYhs7e3rhlYANQXab6wZQO2rX3Dww1ZayIU6qpov4IWHWkuonUF1rKp5fZEQxXCQz5yogIAAACoFNdrzZqpQEmMoGTGl6+FGMq/TrL8h2DGGrbGTS4Dy1gk4gdUVi+6bJAMLADqi50pqIhAMKj+wUG99eab1T842DAfLOFwnyzL3GhRgXp7TYXDfZs7gOdKmajWBVL8B/2bzCgpvxoYOVEBAAAAVIKTkfqflw68IB1K+bf9z/vtQNvotKU9CSmQn8FEActvb/DFpo2egQVAfbEzBS0tGAwoHh9SJDJWbFGBYrGhzRefP5OUshvsapAnZaf9fk1eIK9VkRMVAAAAwFY5GSkys36ZXWrJb09Ykm3WZWhA7XXa0o7h5Wsmab9GyrZww+5IWauRM7AAlea6WSWTU0qnFxQKdSkc7tv8ddI2QDAFLc+2B5RIjCgaHc8rRm9ZpmKxIdn2wOafPFviboVS+6HmcjlRM6lU4bophiHTssiJCgAAAKAg15Ois8XzFRiSRmel4S5SfqGNGMGmXlSay8ACtDLHmSx4vTQe3+L10hZGMAVtwbYHNDy8r/KR1kCJuxVK7YeaIycqALQmVlgBAGoleUqaWSr+uCdpesnvN7irZsMCAKAox5lUJDK2bl1xKpVRJDKmRGKEgEoBBFPQNoLBgAYH+yv7pNvCft7PbEqF1yEZ/uPb2NXQyHI5Ucej0bxi9KZlaSgWIycqADQZVlgBAGopvUEgZTP9AACoJtfNKhodL5igxfP8tcWjo+MaHt7HgrQ1CKYAW2EEJTMuzUXkb95e/S60vH/bjDVNXtB2Rk7U1pF1Xf4fgTbGCisAQK2FSryyUmo/AACqKZmcylt4tpbnSdPTGSWTU5VfmN7k+CgHtqrTlpSQMtH8YvQByw+kdLKroVmQE7X5TTpO4R1G8Tg7jIA2wAorAEA9hHdKVodfbL5IvgJZHX4/AADqLZ1eqGi/dsIsEqiETlvae0y68HFpzyP+7d6jBFKAGpp0HI1FInmBFEnKpFIai0Q06Th1GhmAWilnhRUAAJUSNKR4t//vtfXlc/dj3RSfBwA0hlCoq6L92gnBFKBSjKC0fVDqvNm/JbUXUDNZ19V4NKqiy9EljY+OKuu6NR4ZgFpihRUAoF5sU0pYUs+a/B9Wh99um/UZFwAAa4XDfbIsU0aRIL9hSL29psLhvtoOrAmQ5gsA0PSmksl1O1LyeJ4y09OaSiZJ5YaW4LpZJZNTSqcXFAp1KRzua720VZ4rnUlK2bQUCEnbwudcqMAKKwBAPdmmNNwlJU/5xeZDy6m92JECoBraYk6AqggGA4rHhxSJjMkw8tel5gIssdgQr6cCCKYAAJreQjpd0X5AI3OcSUWj43nprCzLVDw+1DqF1RedIrXI4hum0MytsEqlMgU3qhmG/7tihRUAoFqChjS4q96jANDq2mJOgKqy7QElEiMFX0exGK+jYgimAABqyvUqv1qvKxSqaD+gUTnOpCKRsXWBglQqo0hkTInESPOf9C460lxE60r4ZlPL7YmiARVWWAEAAKDVtcWcADVh2wMaHt7HDqcyGJ5XaN1e68lkMtq9e7fm5+dlmiQrBYB6cDJSdFaaWTrbZnX4BTu3kkc667qK9/crk0oVrptiGDItS9GjRxUIUs8Izcl1s+rvjxctsJ7bdXH0aLR5T349VzrRn78jJY/h71DZe3TDlF+FVur19rbnCivOgVEuXjMAADSutpgTADVWzvkvf1UAgJpwMlJkJj+QIkmpJb/dKXwuWJJAMKiheNy/s7aC2vL9oViMQAqaWjI5VXTSJPlxxOnpjJLJqRqOqsLOJDcIpEiSJ2Wn/X4bsO0BHTsW1eOP36pHHrH1+OO36ujRaNsFUgAAANBa2mJOADQwgikAgKpzPX9HSqGtkLm20Vm/32YN2LZGEgmZPT157aZlaSSR0IBdvM4C0AzS6YWK9mtI2RLrGpXQLxgMaHCwXzff/FYNDvazMg8AAABNry3mBEADo2YKAKDqkqfW70hZzZM0veT320rBzgHb1r7hYU0lk1pIp9UVCqkvHGZHClpCKNRV0X4NKVBiXaNS+wEAAAAtpC3mBEADI5iChlCNgtQAGkd6g0DKZvptJBAMqn9wcOtP1MKyrkvAqQmFw32yLFOpVKZYaSBZlqlwuK95P1e3hf2aKNmUCu9lW66Zsi1c65EBAAAAdVfOnABA5ZHvAHXnZKT+56UDL0iHUv5t//Nbq58AoLGESgzdl9oPmzfpOIr39+vLBw7IOXRIXz5wQPH+fk06Tr2HhnMIBgOKx4ckFS0NpFhsSF89GWjez1UjKJnx3J21D/o3ZmzD4vMAAABAqyp1TkCKW6A6+MtCXVWzIDWAxhHeKVkd6y+N5hiSepdXz6N6Jh1HY5GIMjP5Bb4zqZTGIhECKk3AtgeUSIyop8fMa7csU4nEiHRwoPk/VzttaU9CCuTXP1LA8ts7qX8EAACA9nWuOYFtD9RpZEDrMzyv0Kaw1pPJZLR7927Nz8/LNM1zfwOqzvX8lbLF6igY8i++Hr2sSVKTANhQLngq5Sfvyf15JyzJ5u25arKuq3h//7pAygrDkGlZih49SsqvJuC6WSWTU0qnFxQKdfnb+AOB1vpc9VzpTNIvNh8I+am92JFSNs6BUS5eMwAANIdCcwJ2pADlK+f8l4QqqJtaFaRuFNQoqL6mrRGwWgtfPLRNP2ASnc3/27c6pFg3gZRqm0omiwdSJMnzlJme1lQySc2ZJhAMBjQ42J/XNnGyxT5XjaC0fbDeowAAAAAaUqE5AYDqIpiCuqllQep6m3QcjUejeRcyTcvSUDyuAZt0JZXgZApfpI8300X6RUfKRKXsqgveAcuvH9AiaW1sUxruaoGgVxNaSKcr2g+Np50+VwEAAAAAqDWCKS2iGbf2tUtB6lyNAq3JqJerUTCSSBBQ2aJc+qi1OQtzNQKaIn3UoiPNRbTup8imlttbp05A0GiSVfEtpisUqmg/NJ52+VwFADSwFt5ljRridQQAaFCNfbUdJXGcSfX3x3XgwJd16JCjAwe+rP7+uBxnst5D21A7FKTOuq7Go9F1gRRJK23jo6PKum6NR9Y6XM/fkVKo+FOubXTW79ewPNffkbLRT5EZ9fsBm9QXDsu0LMko8q5rGDJ7e9UXDtd2YKiYdvhcBQA0sEVHOtEvvXJAmjvk357o99uBUvE6AgA0MIIpTc5xJhWJjGlmJpPXnkplFImMNXRAJWj4KZik9Rd+cvdj3c2d/qecGgXYnHJq7zSsM8n81F7reFJ22u8HbFIgGNRQPO7fWRtQWb4/FItRy6mJtcPnKgCgQeV2Wa89p83tsuZCOErB6wgA0OAIpjQx180qGh3faNODRkfH5brZ2g6sDLmC1D1rUo5YHU2SmukcqFFQfS1RIyBb4v9/qf2AIgZsWyOJhMyenrx207JIOdgiWv1zFQDQgNhljUrgdQQAaAJkzW5iyeTUuh0pq3meND2dUTI5pcHB/toNrEytXJCaGgXV1xI1AgIl/v+X2g/YwIBta9/wsKaSSS2k0+oKhdQXDrMjpYW08ucqAKABlbPLevtgrUaFBuZ6Bc5TeB0BAJpAI19exDmk0wsV7VdPrVqQOlejIJNKFa6bYhgyLYsaBVuQqxGQWiq8hsmQ/3hD1wjYFpYClr99vdhPEbD8fkAFBIJB9Q8O1nsYqKJW/VwFADQgdlmjDE7Gr3m5OlWz1SH9fxel9bZSnoDXEQCgjkjz1cRCoa6K9kPlUaOg+lqiRoARlMx47s7aB/0bM+b32yLXkyZOSkfm/Vu3UOwGAAAAKBW7rFEiJyNFZtbXvEwtSf+/l3kdAQAaH8GUJhYO98myzHXX6HMMQ+rtNRUO99V2YMhDjYLqa4kaAZ22tCchBfJfJwpYfnvn1l8nTkbqf1468IJ0KOXf9j/vtwMAAACbkttlvW5RUI4hBXrZZd3mXM/fkVKsIkpyKawXs5Y8XkcAgAZmeF6h3EOtJ5PJaPfu3Zqfn5dpNsOV1dI4zqQikTFJ+VmkcgGWRGJEtj1Qh5FhrazrUqOgygrm3m3kHSmFeO5y3um0v+pqW7giO1Jyq8DWvuHnfj1NE3QCAJSlVc+BUT28ZrApi440F1m+s/qMc/lss0KLg9C8Jk76i7k28v+c5+j/Oz+y/KrhdQQ0O9fNKpmcUjq9oFCoS+Fwn4JB1vWj8ZRz/kswpQU4zqSi0fG8YvS9vaZisSECKQDkev4OlLXb6XNydWWOXtaEwScAwIZa+RwY1cFrBpu26EiZaH4R8UCvn66WC+Bt78i8vzv+XL55saPwEq8joNkVulZpWabica5VovGUc/5LAfoWYNsDGh7e19DRXqLRQP0kTxUPpEj+mq/pJb/fVgtW87cOAADQpjptacdwVXZZo/mFSrz65O6wpZ28joBmlsuis3b5fiqVUSQyRhYdNDWCKS0iGAxocLC/3sMoiGg0UF/pDQIpm+lXDH/rAAAAbc4IStsH6z0KNKDwTn83fGqpcN2U3G758E7xOgKamOtmFY2OrwukSH55AsOQRkfHNTy8j4WXaEq8alFVuWj06our0tlotONM1mlkQPsodRVYqf0K4W8dAAAAQDFBQ4p3+/9em1k4dz/WTdphoNklk1Prrgus5nnS9HRGyeRUDUcFVM6mgin333+/+vv7tWPHDl177bX69re/XbTvQw89JMMw8r527NiR18fzPN19990KhULq7OzUwYMH9fzzz+f1eeWVV/RzP/dzMk1Te/bs0S/+4i/q1Vdf3czwUSPnikZLfjTadbO1HRjQZnKrwIrNSwxJvblVYJvA3zoAAACAc7FNKWFJPWsWcVkdfrtNmSag6aXTCxXtBzSasoMpjz76qA4fPqx77rlH3/nOd3TllVfqxhtv1IkTJ4p+j2maSqfTK18vvPBC3uOf/exn9cUvflEPPPCAnnrqKe3atUs33nijXnvttZU+P/dzP6fnnntOX//61/VXf/VX+uY3v6kPfOAD5Q4fNUQ0GmgM1V4Fxt86AAAAgFLYpnTsMunxN0mP9Pi3Ry8jkAK0ilCoq6L9gEZTdjDl85//vO644w7ddtttuvzyy/XAAw9o586devDBB4t+j2EY6u7uXvm6+OKLVx7zPE+xWEy/8Ru/oeHhYV1xxRX6oz/6I7344ov68z//c0nS5OSkxsfH9V//63/VtddeqxtuuEG/8zu/o6985St68cUXy/+pURNEo4HGUc1VYPytAwAAAChV0JAGd0k37/ZvSe0FtI5wuE+WZcoo8ndtGFJvr6lwuK+2AwMqpKxgypkzZ/T000/r4MGDZ58gENDBgwf15JNPFv2+V199VW9605vU29ur4eFhPffccyuPHT16VLOzs3nPuXv3bl177bUrz/nkk09qz549uuaaa1b6HDx4UIFAQE899VTBY54+fVqZTCbvC7VFNBpoLJVYBZZ1XR2bmNCzR47o2MSEsq7L3zoAAE2MeVPtFDqPWst1s5qYOKYjR57VxMQx0qQCAJpKMBhQPD4kSesCKrn7sdgQxefRtMoqN/zyyy/Ldd28nSWSdPHFF+uf//mfC37Pvn379OCDD+qKK67Q/Py8fvu3f1tvf/vb9dxzz8myLM3Ozq48x9rnzD02OzurvXv35g+8o0MXXnjhSp+17rvvPn3iE58o58dDheWi0alUpmAtBcOQLItoNFBLuVVgmzHpOBqPRpWZmVlpMy1L7/zCF/hbBwCgSTFvqo1i51FD8bgGbFuS5DiTikbH89KnWpapeHxItj1Q8zEDALAZtj2gRGKk4GdaLMZnGppb1cOA119/vW655RZdddVV+omf+Ak5jqM3vvGN+v3f//2qHveuu+7S/Pz8ytf09HRVj4f1iEYDrWPScTQWieRdAJCkTCqlxMiI7r05KIm/dQAAmg3zpurb6DxqLBLRpOPIcSYViYytq0OXSmUUiYzJcSZrOWQAALbEtgd07FhUjz9+qx55xNbjj9+qo0ejBFLQ9Mq6snXRRRcpGAzq+PHjee3Hjx9Xd3d3Sc9x3nnn6eqrr9b3v/99SVr5vo2es7u7e12B+6WlJb3yyitFj7t9+3aZppn3hdrLRaN7evJ//5ZlKpEY4U0UaAJZ19V4NKqC206W2+a+8tv600ffy986AABNhnlTdZVyHjUeHdXor/73jbpodHSclF8AgKYSDAY0ONivm29+qwYH+1lgiZZQVpqvbdu2af/+/Xrsscf0nve8R5KUzWb12GOP6c477yzpOVzX1bPPPquf/umfliRdeuml6u7u1mOPPaarrrpKkpTJZPTUU0/pV37lVyT5u1vm5ub09NNPa//+/ZKkv/3bv1U2m9W1115bzo+AOrDtAQ0P71MyOaV0ekGhUJfC4T7eRIEmMZVMrltJmcfzlJme1v43vqxjx6L8rQMAACwr6TxqZlpBPSvp0mJdND2dUTI5pcHB/qqMEwAAAOdWVjBFkg4fPqxbb71V11xzjd72trcpFovp5MmTuu222yRJt9xyi3p6enTfffdJku69915dd911evOb36y5uTl97nOf0wsvvKDbb79dkmQYhkZHR/XJT35Sl112mS699FJ97GMf0yWXXLISsBkYGNDQ0JDuuOMOPfDAA3r99dd155136n3ve58uueSSCv0qUE25aDSA5rOQTpfcj791AACAs0o9jzpfr56zTzq9sNXhAAAAYAvKDqbcdNNNeumll3T33XdrdnZWV111lcbHx1cKyE9NTSkQOLsK+Qc/+IHuuOMOzc7O6oILLtD+/fv1xBNP6PLLL1/p85GPfEQnT57UBz7wAc3NzemGG27Q+Pi4duzYsdLnT/7kT3TnnXfqp37qpxQIBPTe975XX/ziF7fyswNYw3WzDb2roNHH16q6QqGK9gPQJDxXOpOUsmkpEJK2hSUjWO9RAUBTKfX86FWdf84+oVDXVoezZa4nJU9J6SUp1CGFd0pB49zfB6D18H5QfVnX1VQyqYV0Wl2hkPrCYQWCnI8D9WR4XqHMrK0nk8lo9+7dmp+fJw8wUIDjTCoaHc8remlZpuLxoYaod9Ho42tlWddVvL9fmVSqcL5vw5BpWYoePcqJHdAqFh0pE5Wyq1LTBCzJjEuddv3GhbJxDoxy8ZqprJLOo3osfcGLaubFV4t1kWWZOno0WteFRE5Gis5KM0tn26wOKd4t2bxUgLbC+0H1TTqOxqPRvFSRpmVpKB7XgM35OFBJ5Zz/sqQbgBxnUpHIWF6gQpJSqYwikTE5zmSdRuZr9PG1ukAwqKF43L9jrFlqtHx/KBYjkAK0ikVHmovkB1IkKZvy2xed+owLAJpQSedR8ZhiX/zpjbooFhuqeyAlMpN/4VSSUkt+u5Mp/H0AWg/vB9U36Tgai0TW1dzKpFIai0Q06XA+DtQLwRSgzbluVtHoeMFVcLm20dFxuW62tgNb1ujjaxcDtq2RREJmT09eu2lZGkkkWBkDtArP9XekqNDG5eW2zKjfDwBQklLOo2x7QInEiHp68ldDWpapRGKkrjuxXc9fgb7BJ4NGZ/1+AFob7wfVl3VdjUejhXczLreNj44q63I+DtRD2TVTALSWZHJq3Y6P1TxPmp7OKJmcqkth8UYfXzsZsG3tGx4mZyvQys4k1+9IyeNJ2Wm/3/bBWo0KAJpeKedRtj2g4eF9DVcjMHlq/Qr01TxJ00t+v8FdNRsWgDrg/aD6ppLJdTtS8nieMtPTmkom1T84WLNxAfARTAHaXDq9UNF+ldbo42s3gWCQEzaglWXTle0HAFhRynlUMBhouAVC6Q0unG6mH4AK8NzlRTBpKRCStoUlo/qL3Hg/qL6FdGnn2aX2A1BZBFOANhcKdVW0X6U1+vgAoKUEQpXtBwBoeqESrxqU2g/AFi06flrW1buJA5ZkxqXO6qZf5v2g+rpCpZ1nl9oPQGVRMwVoc+FwnyzLXFfsMscwpN5eU+FwX20HtqzRxwcALWVb2J+Mq8ibrgwp0Ov3AwC0hfBOyerY8JNBvR1+PwBVtuhIc5H1aVmzKb99sbqFyXk/qL6+cFimZWmjiyBmb6/6wpyPA/VAMAVoc8FgQPH4kKT1n9W5+7HYUN1yNTf6+ACgpRhBf1Wjf2ftg/6NGatJGgkAQGMIGlK82/93kU8Gxbr9fgCqyHP9HSkblX/PjPr9qoT3g+oLBIMaii+fjxe5CDIUi1G7FKgTrj4CkG0PKJEYUU+PmdduWaYSiRHZ9kCdRuZr9PEBQEvptKU9CSnQk98esPz2KqePAIDNyrqujk1M6NkjR3RsYkJZt3oXFBuW50qnJ6TFI/5thS6q2qaUsKSeNal7rA6/3TYLfx+ACjqTXL8jJY8nZaf9flXE+0H1Ddi2RhIJmT355+OmZWkkkdCAzfk4UC+G53mFQtotJ5PJaPfu3Zqfn5dp8s4OFOK6WSWTU0qnFxQKdSkc7muoHR+NPj4AaCl1KmyKyuIcGOVq1tfMpONoPBpVZubshUbTsjQUj7fPRaca1FFwPSl5yi8uHVpO5cMKdKBGFo9Ic4fO3W/PI1LnzVUfDu8H1Zd1XU0lk1pIp9UVCqkvHGZHClAF5Zz/EkwBAAAAWhTnwChXM75mJh1HY5GItHZqu5wOpS1W8ebqKKxL/7N8ZZOdhUDzOz0hvXLg3P0ufFzaPljt0QBAyyjn/Jcl3QAAAACAppR1XY1Ho+sDKdJK2/joaGun/GqAOgoAamBb2N9ttlH590Cv3w8AUBUEUwAAAAAATWkqmcxL7bWO5ykzPa2pZHVrCNRVg9RRAFBlRtBP2+ffWfugf2PGSMsKAFVEMAUAAAAA0JQW0umK9mtK2RJ/tlL7AWhcnbafti+QX5hcAYt0fgBQAx31HgAAAADqgALzAFpAVyhU0X5NKVDiz1ZqvzZHwWc0vE5b2jHMeRyqj/kCsA7BFAAAgHaz6Pj59VenhQlYfuoIVjQCaCJ94bBMy1ImlSpcN8UwZFqW+sItXEMgV0chm1LhuimG/zh1FM5p0nE0Ho3mpY4zLUtD8bgGbD4f0UCMIEXmUV3MF4CCSPMFAADQThYdaS6yPr9+NuW3Lzr1GRcAbEIgGNRQfLmGgLGmhsDy/aFYrLV3FlSwjoLrZjUxcUxHjjyriYljct1sJUfa0CYdR2ORyLoaPJlUSmORiCYdPh8BtAnmC0BRBFMAAADahef6K8wKrlxebsuM+v0AoEkM2LZGEgmZPfk1BEzL0kgi0R47CipQR8FxJtXfH9eBA1/WoUOODhz4svr743KcySoNunFkXVfj0Wjh3U3LbeOjo8q6fD4CaHHMF4ANkeYLAACgXZxJrl9hlseTstN+P1JHAGgiA7atfcPD7V3rYgt1FBxnUpHI2LpYQiqVUSQypkRiRLY9UKWB199UMrluR0oez1NmelpTyaT6BwdrNi4AqDnmC8CGCKYAAAC0i2y6sv0AoIEEgkEudG+ijoLrZhWNjhfdlGEY0ujouIaH9ykYbM3kFgvp0j73Su0HAE2L+QKwIYIpAAAA7SIQqmw/bCjruu29Sh5AU0gmpzQzkyn6uOdJ09MZJZNTGhzsr+pY6vW+2RUq7XOv1H4A0LSYLwAbIpgCAADQLraF/fz52ZQK50E2/Me3hWs9spYz6Tgaj0bz0saYlqWheLw96jcAaBrp9EJF+21WPd83+8JhmZalTCpVuG6KYci0LPWF+XwE0OKYLwAbas09ugAAAFjPCEpmPHdn7YP+jRkrKb8+ipt0HI1FIuvy72dSKY1FIpp0nDqNDADWC4W6KtpvM+r9vhkIBjUUX/58NNZ8Pi7fH4rF2F0IoPUxXwA2RDAFAACgnXTa0p6EFOjJbw9Yfnsnuya2Iuu6Go9GC69sXm4bHx1V1nVrPDIAKCwc7pNlmetiCDmGIfX2mgqH+6py/EZ53xywbY0kEjJ78j8fTcvSSCLBrkIA7YP5AlAUab7QEshJDgBAGTptacewdCbpF48MhPyt+qww27KpZHLdyuo8nqfM9LSmkkkKZQNoCMFgQPH4kCKRMRlGfkwjF2CJxYaqVny+kd43B2xb+4aHmVsCAPMFoCCCKWh65CQHAGATjKC0fbDeo2g5C+l0RfsBQC3Y9oASiRFFo+N5xegty1QsNiTbHqjasRvtfTMQDBLsBgCJ+QJQAMEUNLVcbt21W8JzuXXZjg0AAGqpKxSqaD8AqBXbHtDw8D4lk1NKpxcUCnUpHO6r2o6UHN43AQBAsyCYgqZ1zty6hqHx0VHtGx5mWzYAAKiJvnBYpmUpk0oVPkcxDJmWpb5wuPaDA4BzCAYDGhzsr+kxed8EAADNggL0aFrl5NZFjXiudHpCWjzi33oU1wUAtJdAMKiheNy/s7aa8/L9oViMhR4AsIz3zQbEvA4AgIIIpqBpNVpu3ba36Egn+qVXDkhzh/zbE/1+OwAAbWTAtjWSSMjs6clrNy2LFKQAUADvmw2EeR0AAEWR5gtNi9y6DWTRkeYiktZsy8+mltsTUicTIABA+xiwbe0bHtZUMqmFdFpdoZD6wmFWVgNAEbxvNgDmdQCaTNZ1+dxATRFMQdMit26D8FwpE9W6E27/QUmGlBmVdgxLBh9oAID2EQgG1T84WO9hAEDT4H2zjpjXAWgyk46j8Wg0rwSAaVkaisfZ0YiqIc0Xmha5dRvEmaSU3aB2jTwpO+33AwAAAIAtcN2sJiaO6ciRZzUxcUyum633kFoD8zqg/TRxfaRJx9FYJLKulnImldJYJKJJh9SEqA6CKWhq5NZtANkSa9KU2g8AAAAACnCcSfX3x3XgwJd16JCjAwe+rP7+uBxnst5Da37M64D20sT1kbKuq/FotHCWmuW28dFRZd3mCQ6heZDmC02vZrl1PXd5tU5aCoSkbWG2N0v+76KS/bAlrptVMjmldHpBoVCXwuE+BYPEzQEAANDcHGdSkcjYumtnqVRGkciYEokR2fZAfQbXCpjXAe2jyesjTSWT63ak5PE8ZaanNZVMkjoSFUcwBS2h6rl1Fx0/f+zqbc8BSzLjDf0BUxPbwv7vIptS4fy6hv/4NmrXVJvjTCoaHdfMTGalzbJMxeNDTCwBAADQtFw3q2h0vOgiZMOQRkfHNTy8j4VEm8W8DmgPLVAfaSFd2g65UvsB5eAsAziXXMR+bf7YXMS+CbZAVpUR9INK/p21D/o3ZqxhP4RbRW6l3upAinR2pR6pDwAAANCsksmpdee5q3meND2dUTI5VcNRtRjmdUB7aIH6SF2h0nbIldoPW9TEtXc2g2AKsJFzRuzlR+xb/I3inDptaU9CCuTXrlHA8tvbffdOlZ1rpZ7kr9SjOCcAAACaUTq9UNF+KIJ5HdD6WqA+Ul84LNOy/G2JhRiGzN5e9YXZSVd1TVx7Z7MIpgAbaYGIfc102tLeY9KFj0t7HvFv9x7lhLsGWKkHAACAVhYKdVW0HzbAvA5obS1QHykQDGoovryTbm1AZfn+UCxW+VrKyNemmXwIpgAbaYGIfU0ZQWn7oNR5s3+7dgt4m239qxVW6gFAlfC5BQANIRzuk2WZGy1CVm+vqXC4r7YDa1XnmtcBaF65+kjr0vnlGFKgt+HrIw3YtkYSCZk9+TvpTMvSSCKhAZsAcFW1cSYfCtADG2mBiH3DWHT8N9rVEeuA5eflZZXTlrBSDwCqgM8tAGgYwWBA8fiQIpExGYby0tvmAiyx2BDF5wHgXHL1keYi8gMqqy+GN1d9pAHb1r7hYU0lk1pIp9UVCqkvHGZHSi2Uk8ln+2CtRlUTnGkAG2mgiL3rSRMnpSPz/q1bKPjbqErc+pd1XR2bmNCzR47o2MSEsm7rRbCrgZV6AFBhbbplHQAamW0PKJEYUU+PmdduWaYSiRHZ9kCdRgYATaaF6iMFgkH1Dw7qrTffrP7BQQIptdLGmXzYmQJspEEi9k5Gis5KM0tn26wOKd4t2Wbx72sI59z6Z0iZUU3+96zGRz+szMzZC1emZWkoHmd75jmwUg8AKqjEzy3tGG6KFXsA0Epse0DDw/uUTE4pnV5QKNSlcLiP81wAKFen7Z/Pnkn6F7wDIX+hMOe3KEUbZ/IxPM9rpvXtm5bJZLR7927Nz8/LNBv96jMaTsFUH71+IKXKEXsnI0Vm1l/SyW1CSFgNHlA5PSG9cmDDLpP/XRq7QwV+SP+nJN9laRxnUtHoeF4x+t5eU7HYECv1AKBUJXxuSfIL8jbBlnXOgVEuXjMAAADYkOdKJ/r9nfsFF6EZ/k6nvUebIkBXzvkvO1OAUtQpYu96/o6UDdbGanRWGu6SgsUykdXbObb0ZV1p/GMq8kN6kmFofHRU+4aH2a55DqzUA4AKaOMt6wAAAABwTg2SyaceCKYApTKCNV+BmjyVn9prLU/S9JLfb3BXzYZVnnNs6Zt6SspsdD3K85SZntZUMqn+wcGKDq0VBYMBDQ7213sYANC82njLOgAAleC6WRZ4AagMzyUVWaPqtCUlCmTyscrK5JN1XU0lk1pIp9UVCqkvHG7oxdQEU4AGlt4gkLKZfnWxLey/kRbZ+rdwvLSnWUizAhgAUAPn+Nxa2bK+LVzrkQEA0PAKpR62LFPxOKmHAZSpYMp9y98RUeWU+yjRFjP5TDqOxqPRpqqfzNIAoIGFSgx3ltqvLnJb//w7ax9U18WlPU1XiBXAAIAaOMfnlqSW3bIOAMBWOM6kIpGxvECKJKVSGUUiY3KcyTqNDEDTWXT8FFKrAymSv+BpLuI/jsaQy+TTebN/W0YgZSwSyQukSFImldJYJKJJpzH/jwmmAA0svFOyOtZfyskxJPV2+P0aWqct7UlIgZ789oClvhvHZFrWSrH5dQxDZm+v+sKsAAYA1MgGn1vak2AlHAAAa7huVtHouLwCmzpzbaOj43LdbG0HBqD5eK6/I6VoBWFJmVG/H5pS1nU1Ho1qow+N8dFRZd3G+z8mmAI0sKAhxbv9fxdZG6tYdwMXn1+t05b2HpMufFza84h/u/eoAuf/rIbiyyuA1wZUlu8PxWINnS8RANCCinxuEUgBAGC9ZHJq3Y6U1TxPmp7OKJmcquGo0NY8Vzo9IS0e8W+58N48ziTX70jJ40nZab8fmtJUMrluR0qeVfWTGw3BFKDB2aaUsKSeNam8rA6/3TbrM65NKbL1b8C2NZJIyOzJXwFsWpZGEomGzZMIAGhxm9yyDgBAu0mnFyraD9iSRUc60S+9ckCaO+TfnugnNVSzyJZYM7fUfmg4pdZFbsT6yY1caQHAMtuUhruk5Cm/2HxoObVXU+xIKdGAbWvf8LCmkkktpNPqCoXUFw6zIwUAAAAAGlwo1FXRfsCm5WptrE0Rlau1IVK2NrxAiTVzS+2HhlNqXeRGrJ9MMAVoEkFDGtxV71FUVyAYVP/gYL2HAQAAAAAoQzjcJ8sylUplCqbANwzJskyFw321HxzaxzlrbRh+rY0dw+w4bmTbwn6twmxKhf8vDf/xbdTWbVZ94bBMy1ImlSpcN8UwZFpWQ9ZPJs0XAAAA2o7rSRMnpSPz/q1baJ4GAABKEgwGFI8PSSpaClOx2JCCQS5DoYqotdEajKBkxnN31j7o35gxAmJNLBAMNm39ZD7FAAAA0FacjNT/vHTgBelQyr/tf95vBwAAm2PbA0okRtTTk1/Y07JMJRIjsu2BOo0MbYNaG62j05b2JKRAfm1dBSy/nVRtTa9Z6ycbnldoL03ryWQy2r17t+bn52WazVSxGwAAAGtlXXdTdbacjBSZWZ8wILceKmH5tcpaBefAKBevGQBb5bpZJZNTSqcXFAp1KRzuY0cKauP0hF9s/lwufFzaPljt0aASPHd5x1Har5GyLcyOlBaz2XldJZVz/kvNFAAAADSVScfReDSqzMzZNA6mZWkoHt9wBZPrSdHZDbNoa3RWGu7ya5UBAIDyBYMBDQ7213sYaEfU2mg9RpDAV4trtvrJLA0AAABA05h0HI1FInmBFEnKpFIai0Q06ThFvzd5SppZKv7cnqTpJb8fAAAAmgy1NgBUGcEUAAAANIWs62o8GpUKZaldbhsfHVXWdQt+f3qDQMpm+gEAAKDBUGsDQBWR5gsAAABNYSqZXLcjJY/nKTM9ralksuBW8VCJZ76l9gMAAEAD6rSlHcPU2gBQcUwVAQAA0BQW0ukt9QvvlKwOKbVUNIu2rA6/HwAAAJoYtTYAVAFpvgAAANAUukKhLfULGlK82/93kSzainVTfB4AAAAAsB7BFAAAADSFvnBYpmVJRpFoh2HI7O1VXzhc9DlsU0pYUs+a/dlWh99umxUcMAAAAACgZZDmC2gQrptVMjmldHpBoVCXwuE+BYPEOwEAyAkEgxqKxzUWifgBldWF6JcDLEOxmALBjfNh26Y03CUlT/nF5kPLqb3YkQIAAAAAKIZgCtAAHGdS0ei4ZmYyK22WZSoeH5JtD9RxZAAANJYB29ZIIqHxaDSvGL1pWRqKxTRg2yU9T9CQBndVa5QAAAAAgFZjeJ5XqP5my8lkMtq9e7fm5+dlmuRvQONwnElFImNa+5eYy2CSSIwQUAGAcnmudCYpZdNSICRtC/tFKFExWdfVVDKphXRaXaGQ+sLhc+4IaaXjNwvOgVEuXjMAAABoJ+Wc/7IzBagj180qGh1fF0iR/MwlhiGNjo5reHgfKb8AoFSLjpSJStmzuxYUsCQzLnWWtmsBG5t0nMI7Q+LxkneGbFUgGFT/4GBNjgUAAAAAAFdngTpKJqfyUnut5XnS9HRGyeRUDUcFAE1s0ZHmIvmBFEnKpvz2Rac+42ohk46jsUgkL5AiSZlUSmORiCYdfscAAAAAgNZDMAWoo3R6oaL9AKCtea6/I0WFMpgut2VG/X7YlKzrajwaVdEtlZLGR0eVdfkdAwAAAABaC8GUNuF60sRJ6ci8f+u2RaWcxhcKdVW0HwC0tTPJ9TtS8nhSdtrvh02ZSibX7UjJ43nKTE9rKsnvGAAAAADQWqiZ0gacjBSdlWaWzrZZHVK8W7KpKVlX4XCfLMtUKpUpuMjXMCTLMhUO99V+cADQbLLpyvbDOgvp0n53pfYDAAAAAKBZsDOlxTkZKTKTH0iRpNSS3+4UL9eBGggGA4rHhyT5gZPVcvdjsSGKzwNAKQKhyvbDOl2h0n53pfYDAAAAAKBZcIW2hbmevyNlg8zxGp0l5Ve92faAEokR9fTkbxOyLFOJxIhse6BOIwOAJrMtLAUsSUaRDoYU6PX7YVP6wmGZlrV+BUCOYcjs7VVfmN8xAAAAAKC1kOarhSVPrd+RsponaXrJ7ze4q2bDQgG2PaDh4X1KJqeUTi8oFOpSONzHjhQAKIcRlMy4NBeRH1BZvVpg+eK/GfP7YVMCwaCG4nGNRSJ+QGV1jsrlAMtQLKZAkN8xAAAAAKC1EExpYekNAimb6YfqCgYDGhzsr/cwAKC5ddqSElImml+MPmD5gZROu14jaxkDtq2RRELj0WheMXrTsjQUi2nA5ncMAACA1ua6WRbEAm2IYEoLC5X4v1tqPwAAmkKnLe0Yls4k/WLzgZCf2osdKRUzYNvaNzysqWRSC+m0ukIh9YXD7EgBAABAy3OcSUWj45qZOVuI2LJMxeNDpGoHWhyX0VtYeKdkdfjF5guVRTHkPx7eWeuRAQBQZUZQ2j5Y71G0tEAwqP7BwXoPAwAAAKgZx5lUJDKWl+1WklKpjCKRMWrfAi2O/WctLGhI8W7/32vLxObux7r9fgCA/z97/x8md1nfi//P2Qn5BZkghiRLdmOQoxjFXydo5Nil4TSFaC8M15qC4hGkitWiDeayn5pWodij1PYcmv22CC2XVlsrQvcsrT3WtJaash6xtmguqY2AmpgQNwGrZEOIBGfn+8eQkGV337ub/b37eFzXXsO85555v/ZOmMw9z/d93wAAANC/arUnGzdu7ROkJM9sJXjttVtTrfaMb2HAuBGmTHOtlaS9KVn2rDlITbPqx1srE1MXADCwnmo1u7Zty/23355d27alp1qd6JIAqFWTJ7clh2+v39a8NwPMJJ2du3st7fVstVqyZ093Ojt3j2NVwHiyzNcM0FpJ1i9IOp+obzbf+PTSXmakAMDks6Ojo//N3dvabO4OMFEOdyTdG5OeZ96b09CUVNrqe3UBMO11dR0c1XbA1GNmygxRLiVrTk7evLB+K0gBgMlnR0dH7tywoVeQkiTde/fmzg0bsqOjY4IqA5jBDnckj23oHaQkSc/e+vHD3puB0VWtJdsOJbcfqN9W+9sIl3HX2LhgVNsBU48wBQBgEuipVrN148YULcK89dprLfkFMJ5q1fqMlPT3TebTx7qvteQXMGo6upMVDyUX/CC5fG/9dsVD9eNMrJaW5WlqqqQ0wAXKpVLS3FxJS8vy8S0MGDfCFACASWB3Z2efGSm91Grp3rMnuzs7x68oitk/Aaa/I519Z6T0Ukt69tTbAYxQR3ey4eHk4Z/1Pr73Z/XjApWJVS43pK1tXZL0CVSO3t+yZV3KZV+3wnTl/24AgEngYFfXqLZjjB3uSB5Zkfz4guSxy+u3j6yw3A9MNz1DfM8dajuAAVRrycZ9hfPgcu0+S35NtNbWlWlvvzTLllV6HW9qqqS9/dK0tq6coMqA8WADegCASWBBY+OotmMMHd0/4dlfdxzdPyHtNqSG6aJhiO+5Q20HTAnVWtL5RNL1s6RxVtIyf+z3nu18ou+MlOPVkuz5Wb3dmpPHthaKtbauzPr1Z6ezc3e6ug6msXFBWlqWm5ECM4AwBQBgElje0pJKU1O69+7tf9+UUimVpqYsb2kZ/+J4xqD7J5Tq+yfMXZ+UyuNbGzD6ZrckDU31sLTf/+9L9cdne2+G6aKjuz5D5Phgo2lW0rY0aa0M/LyR6ioIUk6kHWOrXG7ImjUrJroMYJyJTAEAJoGGcjnr2trqdwZYhHndli1pKPuCfkLZPwFmllI5qbQdvfPsB+s3lS3CU5gmJnLPksYhXu481HbA4Kq1ZNuh5PYD9VvL6DEYYQoAwCSxsrU1l7a3p7JsWa/jlaamXNrenpWtlo6acPZPgJlnXmtyanvS0Pu9OQ1N9eOW9YNpYaL3LGmZX58BM9BqYqUkzU8vOQaMXEd3suKh5IIfJJfvrd+ueGhsQ1OmPnk2wCiaiLV1gellZWtrzl6/Prs7O3OwqysLGhuzvKVlys1IqVZ7puc60vZPgJlpXmt9+b4jnfWwtKGxvrSXGSkwbUz0niXlUn0psQ0P14OT4zObo0PKLUuNL2E0HJ2F9uxs9OgstPamsV3Wj6lLmAIwSiZqbV1g+mkol7NizZqJLuOEdXTsyMaNW/Pww89c1tXUVElb27q0tq6cwMpGgf0TYOYqlZM5aya6CmCMTIY9S1or9S9x+xtXbjGuhFEx2Cy0Uuqz0NYvEF7S1zS4PBBg4k3k2roAk0lHx45s2HBnryAlSfbu7c6GDXemo2PHBFU2SuyfAADT0rD2LKlVkye3JYdvr9/WqqNWR2sl2fWC5MvPSz67rH678wWCFBgtw5mFBs8mTAEYoYleWxdgsqhWe7Jx49bU+nm/O3rs2mu3plrtGd/CRpv9EwBg2hnyniUNHckjK5IfX5A8dnn99pEVyeGOUaulXKovJfbmhfVbV8fD6JkMs9CYuoQpACPkqgaAus7O3X1mpByvVkv27OlOZ+fucaxqjMxrTRbvSk77cnLqZ+u3i3cKUgCY9Kq1ZNuh5PYD9VsXfdUd3bMkGXDuae5c1JHyYxuSnod7N+jZmzy2YVQDFWBsDGsW2hirVnuybduu3H77/dm2bdfUv+hsBjihMOXmm2/OihUrMnfu3KxevTpf//rXh/S8z33ucymVSrnkkkt6Hd+/f3/e9ra35Ywzzsj8+fOzbt26PPTQQ73arFmzJqVSqdfPu971rhMpH2BUuaoBoK6r6+Cotpv0ju6fMO/N9VtLewEwyXV0JyseSi74QXL53vrtiocsS3zU0T1Llj3rS9SmWUn7smpe89TGFK5J0H3tqC75BYy+Ic9Cmz+2dXR07MiKFW254IJP5/LLO3LBBZ/OihVtU39Z5Glu2GHKHXfckU2bNuX666/PN77xjbz85S/PRRddlEceeaTwebt27cr73//+tLT03oyzVqvlkksuyfe///38zd/8Tb75zW/mec97XtauXZtDhw71anv11Venq6vr2M/v//7vD7d8gFE3ma5qAJhIjY0LRrUdADB67PM4NAPuWTK3s++MlF5qSc+e5EjnuNUKDN9QZqFtWTq2y+tN+30mp7Fhhyk33XRTrr766lx11VV58YtfnFtvvTXz58/PJz/5yQGfU61W85a3vCU33HBDnv/85/d67KGHHsrXvva13HLLLXnVq16Vs88+O7fccksOHz6c22+/vVfb+fPnZ+nSpcd+KhW7bwETb7Jc1QAw0VpalqepqZLSAG+IpVLS3FxJS8vy8S0MAGY4+zwOT797lvR0De3JQ20HTJjCWWhN9cfHyozZZ3KaGlaYcuTIkdx3331Zu3btMy/Q0JC1a9fm3nvvHfB5H/7wh7N48eK8/e1v7/PYk08+mSSZO3dur9ecM2dOvvKVr/Rq+5d/+ZdZtGhRzjnnnGzevDlPPDHwBgRPPvlkuru7e/0AjIXJcFUDwGRQLjekrW1dkvQJVI7e37JlXcpl2/bBZGHcBDODfR5HQUPj6LYDJtSAs9DG+Nr9GbXP5DQ0rJHsj370o1Sr1SxZsqTX8SVLlmTfvn39PucrX/lKPvGJT+S2227r9/EXvehFWb58eTZv3pyf/OQnOXLkSD72sY/l4YcfTlfXM2n+5Zdfns985jP58pe/nM2bN+cv/uIv8j/+x/8YsNYbb7wxCxcuPPbT3Nw8nF8VYFgm8qoGgMmktXVl2tsvzbJlvd/4mpoqaW+/NK2tKyeoMqA/xk0wM9jncRTMbkkamlK4JkFDc70dMCX0OwttjM24fSanmTFdwf/gwYN561vfmttuuy2LFi3qt81JJ52Ujo6OvP3tb89pp52WcrmctWvX5nWve11qx813euc733nsv1/60pemsbExv/ALv5Dvfe97Oeuss/q87ubNm7Np06Zj97u7uw0MgDHVWknWL6hfzdX1s/oeKS3zzUgBZp7W1pVZv/7sdHbuTlfXwTQ2LkhLy3IzUmASMm6CmcE+j6OgVE4qbcljG1IPVI5fo+fpQV9lS70dwADsMzm1DeufyUWLFqVcLmf//v29ju/fvz9Lly7t0/573/tedu3alYsvvvjYsZ6e+npvs2bNygMPPJCzzjorq1atyvbt23PgwIEcOXIkp59+elavXp1zzz13wFpWr16dJPnud7/bb5gyZ86czJkzZzi/HsCIHb2qAWCmK5cbsmbNiokuAxiEcRPMDEf3edz7s/73TSml/rh9HgcxrzVJe9K9sfdm9A1N9SBlXutEVQZMEUf3mdy7t7vffVNKpfqsfvtMTk7Dujxw9uzZWbVqVe6+++5jx3p6enL33XfnvPPO69P+RS96Ue6///5s37792M8b3vCGXHDBBdm+fXufK54WLlyY008/PQ899FD+7d/+LevXrx+wlu3btydJGhutRQkAADDVVWvJtkPJ7QfqtzbChuGrVnuybduu3H77/dm2bdexDYzt8ziK5rUmi3clp305OfWz9dvFOwUpwJDYZ3JqG/YEzk2bNuXKK6/Mueeem1e/+tXZsmVLDh06lKuuuipJcsUVV2TZsmW58cYbM3fu3Jxzzjm9nn/qqacmSa/jf/VXf5XTTz89y5cvz/3335+NGzfmkksuyYUXXpikPsPls5/9bF7/+tfnuc99br71rW/lfe97X84///y87GUvO9HfHQAAgEmgozvZuK/3BtlNs+pf/tp7Doamo2NHNm7c2mtj46amStra1qW1deWxfR77+39ti//XhqdUTuasmegqgCnq6D6T/b1nb9myzj6Tk9iww5TLLrssjz76aK677rrs27cvr3jFK7J169Zjm9Lv3r07DQ3DS866urqyadOm7N+/P42NjbniiivyoQ996Njjs2fPzj/+4z8eC26am5vzxje+MR/84AeHWz4AAACTSEd3suHhvksP7f1Z/Xh7ky95YTAdHTuyYcOdfZaM2bu3Oxs23Jn29kuPBSr2eQQYolo1OdKZ9HQlDY3J7JZR2xfJPpNTU6lW6291tumnu7s7CxcuzIEDB1Kp+CQOAMD05zMwwzXef2eqtWTFQ72vkj/e0X0cdr7Al70wkGq1JytWtPW6uvl4R9ff37lzoy/pAIbqcMcA+yO1WdZvmhnO51//igIwtdSqyZPbksO3129r1YmuCAA4QZ1PDBykJPXZKnt+Vm8H9K+zc/eAQUqS1GrJnj3d6ezcPY5VAUxhhzuSxzb0DlKSpGdv/fjhjompayqaZt/hDHuZLwCYMK4MAYBppasgSDmRdjATdXUdHNV2ADNarVr/3qHPAqR5+lgp6b42mbt+1Jb8mram4Xc4ZqYAMDW4MgQApp3GIV7eN9R2MBM1Ni4Y1XYAM9qRzr7fO/RSS3r21NsxsGn6HY4wBYDJb9ArQ1K/MmSKTxcFgJmmZX59T5SBtkMpJWl+eoNsoH8tLcvT1FRJaYD/kUqlpLm5kpaW5eNbGMBU1NM1uu1momn8HY4wBYDJz5UhADAtlUtJ29L6fz/7e+Cj97cstfk8FCmXG9LWti5J+gQqR+9v2bLO5vMAQ9HQOLrtZqJp/B2Of0kBmPxcGQIA01ZrJWlvSpY9aymvpln1462ViakLppLW1pVpb780y5b1/h+mqamS9vZL09q6coIqA5hiZrfU9/Uomjfb0FxvR/+m8Xc4Vp4FYPJzZQgATGutlWT9gqTzifpm841PL+1lRgoMXWvryqxff3Y6O3enq+tgGhsXpKVluRkpAMNRKtc3SH9sQ+qByvFLVT39waSyxebzRabxdzjCFIAppKdaze7Ozhzs6sqCxsYsb2lJQ3kG/AN+9MqQnr3pf83NUv1xV4YAwJRVLiVrTh67169We3zJzLRXLjdkzZoVE10GwNQ2rzVJe33fj+OXq2poqgcp81onqrKpYRp/hyNMAZgidnR0ZOvGjel++Jl/yCtNTVnX1paVrdP8H3JXhgAAI9DRsSMbN27Nww93HzvW1FRJW9s6yx8BAH3Na03mrn96/4+u+iyK2S2+dxiKafwdjstwAKaAHR0duXPDhl5BSpJ0792bOzdsyI6OjgmqbBzNa01ObU8alvU+3tBUP+7KEACgHx0dO7Jhw529gpQk2bu3Oxs23JmOjh0TVBkAMKmVysmcNcm8N9dvJ+OX/7Vq8uS25PDt9dtadaIrqpum3+GUarVaf3Ntpp3u7u4sXLgwBw4cSKViB0Ng6uipVtO2YkWfIOWYUimVpqZs3LlzZiz5Vau6MgRgiHwGZrim29+ZarUnK1a09QlSjiqV6jNUdu7caMkvAGBqOdwxwFJkbZMnrJgC3+EM5/OvT4sAk9zuzs6Bg5QkqdXSvWdPdnd2jl9RE2kqXBkCAEwKnZ27BwxSkqRWS/bs6U5n5+5xrAoAYIQOd9SX0ep51vdFPXvrxw9PkhVMptl3OMIUgEnuYFfXqLYDAJgpuroOjmo7AIAJV6vWZ6T0u7n708e6r508S35NIzagBxiiarUnnZ2709V1MI2NC9LSsnxcloNY0Ng4qu0AAGaKxsYFo9oOAGDCHensOyOll1rSs6febs6a8apqRhCmAAxBR8eObNy4tdcyEU1NlbS1rUtr68oxPffylpZUmprSvXdvfS2KZ3t6z5TlLS1jWgcAwFTT0rI8TU2V7N3bPdDHqDQ1VdLSsnz8iwMAOBE9Q1yZZKjtGDLLfAEMoqNjRzZsuLPPett793Znw4Y709GxY0zP31AuZ11bW/1OqdT7wafvr9uyZWZsPg8AMAzlckPa2tYlGfBjVLZsWWfzeQBg6mgY4sokQ23HkPnECFCgWu3Jxo1b+72S8eixa6/dmmq1Z0zrWNnamkvb21NZtqzX8UpTUy5tb8/K1tYxPT8AwFTV2roy7e2XZtmySq/jTU2VtLdfOuazjAEARtXslqShKUlpgAalpKG53o5RZZkvgAKdnbv7zEg5Xq2W7NnTnc7O3VmzZsWY1rKytTVnr1+f3Z2dOdjVlQWNjVne0mJGCgDAIFpbV2b9+rMnZP87AIBRVSonlbbksQ2pByrHXwH8dMBS2VJvx6gSpgAU6Oo6OKrtRqqhXM6KNWvG5VwAANNJudww5he/AACMi3mtSdqT7o29N6NvaKoHKfOsYDIWhCkABRobF4xqO6aBWjU50lnfyK2hsT5t1tUe005PtWoWGAAw/nzWBGCo5rUmc9f7d2McCVMACrS0LE9TUyV793b3u29KqVRfb7ulZfn4F8f4O9wxwFUfba76mEZ2dHRk68aN6X74mT/nSlNT1rW12Z8IABg7PmsCMFylcjJnzURXMWNYIBagQLnckLa2dUnqwcnxjt7fsmWd9bZngsMd9fVIjx/cJknP3vrxwx0TUxejakdHR+7csKFXkJIk3Xv35s4NG7Kjw58zAMxk1WpPtm3bldtvvz/btu1KtdozOi/ssyYATHq+/QMYRGvryrS3X5plyyq9jjc1VdLefmlaW1dOUGWMm1q1fpVg+pmedPRY97X1dkxZPdVqtm7cmH6noT19bOu116an6s8ZAGaijo4dWbGiLRdc8OlcfnlHLrjg01mxoi0dHTtG9sI+awLAlGCZL4AhaG1dmfXrz05n5+50dR1MY+OCtLQsNyNlpjjS2fcqwV5qSc+eertBptdWqz3+Hk1Suzs7+8xI6aVWS/eePdnd2ZkVa9aMW10AwMTr6NiRDRvu7HPNxd693dmw4c6RXWQ1ip81AYCxI0wBGKJyuSFr1qyY6DKYCD1do9Kuo2NHNm7cmocf7j52rKmpkra2dWY4TQIHu4b25zzUdgDA9FCt9mTjxq0DTl4tlZJrr92a9evPPrGLZEbpsyYAMLZcCgsAg2loHHG7o1czHh+kJM9czTji5SEYsQWNQ/tzHmo7AGB66Ozc3ecz3PFqtWTPnu50du4+sROMwmdNAGDsCVMAYDCzW5KGpiSlARqUkobmert+DHY1Y1K/mnHUNjDlhCxvaUmlqal+eWl/SqVUmpuzvKX/P2cAYHrq6jo4qu36GOFnTQBgfAhTAGAwpXJSaTt659kP1m8qW+rt+jHmVzMyKhrK5axre/rP+dmBytP3123ZkoZy/3/OAMD01Ni4YFTb9THCz5oAwPgQpgDAUMxrTU5tTxqW9T7e0FQ/Pq91wKeO+dWMjJqVra25tL09lWW9/5wrTU25tL09K1sH/nMGAKanlpblaWqqFE1eTXNzJS0ty0/8JCP4rAkAjA8b0APAUM1rTeauT4501jcAbWisL7cwyFWCY341I6NqZWtrzl6/Prs7O3OwqysLGhuzvKXFjBQAmKHK5Ya0ta3Lhg13plRKr6VbjwYsW7asO7HN5493gp81oY9a1d8jgDEgTAGA4SiVkzlrhvWUo1cz7t3b3e++KaVS0tQ0wqsZGVUN5XJWrFkz0WUAAJNEa+vKtLdfmo0bt/ZavrWpqZItW9altXXl6JzoBD5rQi+HO5LujUnPw88ca2iqLyVnhhPAiAhTAGCMjdvVjAAAjJnW1pVZv/7sdHbuTlfXwTQ2LkhLy3Kf4Zg8Dnckj21I8qwruHr2Pn3cknEAI+FffAAYB0evZly2rNLreFNTJe3tl47e1YwAAIyZcrkha9asyJvf/NKsWbNCkMLkUavWZ6Q8O0ipP1i/6b623g6AE2JmCgCME1czAgAAY+JIZ++lvfqoJT176u0sJQdwQoQpADCOjl7NCAAAMGp6uka3HQB9uBQWAAAAAKayhsbRbQdAH8IUAAAAAJjKZrckDU1JSgM0KCUNzfV2AJwQYQoAAAAATGWlclJpO3rn2Q/Wbypb6u0AOCHCFAAAAACY6ua1Jqe2Jw3Leh9vaKofn9c6MXUBTBM2oAcAAACA6WBeazJ3fXKks77ZfENjfWkvM1IARkyYAgAAAADTRamczFkz0VUATDuW+QIAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACggTAEAAAAAACgwa6ILAABGWa2aHOlMerqShsZkdktSKk90VQAAAABTljAFAKaTwx1J98ak5+FnjjU0JZW2ZF7rxNUFAAAAMIUJUwBgujjckTy2IUmt9/GevU8fbxeoAAAwo1WrPens3J2uroNpbFyQlpblKZetgg/A4IQpADAd1Kr1GSnPDlLqDyYpJd3XJnPXW/ILAIAZqaNjRzZu3JqHH+4+dqypqZK2tnVpbV05gZUBMBWI3gFgOjjS2Xtprz5qSc+eejsAAJhhOjp2ZMOGO3sFKUmyd293Nmy4Mx0dOyaoMgCmCmEKAEwHPV2j2w4AAKaJarUnGzduTa2fSdxHj1177dZUqz3jWxgAU4owBQCmg4bG0W0HAADTRGfn7j4zUo5XqyV79nSns3P3OFYFwFQjTAGA6WB2S9LQlKQ0QINS0tBcbwcAADNIV9fBUW0HwMwkTAGA6aBUTiptR+88+8H6TWWLzecBAJhxGhsXjGo7AGYmYQoATBfzWpNT25OGZb2PNzTVj89rnZi6AABgArW0LE9TUyWlASZxl0pJc3MlLS3Lx7cwAKYUYQoATCfzWpPFu5LTvpyc+tn67eKdghQAAGascrkhbW3rkqRPoHL0/pYt61Iu+5oMgIH5VwIApptSOZmzJpn35vqtpb0AAJjhWltXpr390ixbVul1vKmpkvb2S9PaunKCKgNgqpg10QUAAAAAwFhrbV2Z9evPTmfn7nR1HUxj44K0tCw3IwWAIRGmAAAAADAjlMsNWbNmxUSXAcAUJHoHAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoMGuiCwAAmHFq1eRIZ9LTlTQ0JrNbklJ5oqsCAAAABiBMAQAYT4c7ku6NSc/DzxxraEoqbcm81omrCwAAABiQZb4AAMbL4Y7ksQ29g5Qk6dlbP364Y2LqAgAAAAoJUwAAxkOtWp+Rklp/D9Zvuq+ttwMAAAAmFWEKAMB4ONLZd0ZKL7WkZ0+9HQAAADCpnFCYcvPNN2fFihWZO3duVq9ena9//etDet7nPve5lEqlXHLJJb2O79+/P29729tyxhlnZP78+Vm3bl0eeuihXm1++tOf5pprrslzn/vcnHLKKXnjG9+Y/fv3n0j5AADjr6drdNsBAAAA42bYYcodd9yRTZs25frrr883vvGNvPzlL89FF12URx55pPB5u3btyvvf//60tLT0Ol6r1XLJJZfk+9//fv7mb/4m3/zmN/O85z0va9euzaFDh461e9/73pe//du/zV/91V/ln//5n/PDH/4wra02aQUApoiGxtFtBwAAAIybUq1W62/h7gGtXr06r3rVq/LHf/zHSZKenp40Nzfnve99bz7wgQ/0+5xqtZrzzz8/v/Irv5LOzs489thj+eu//uskyYMPPpizzz47//7v/56XvOQlx15z6dKl+ehHP5p3vOMdOXDgQE4//fR89rOfzYYNG5Ik3/nOd7Jy5crce++9ec1rXjNo3d3d3Vm4cGEOHDiQSqUynF8ZAGDkatXkkRX1zeb73TellDQ0JYt3JqXyOBfHdOUzMMPl7wwAADPJcD7/DmtmypEjR3Lfffdl7dq1z7xAQ0PWrl2be++9d8DnffjDH87ixYvz9re/vc9jTz75ZJJk7ty5vV5zzpw5+cpXvpIkue+++/LUU0/1Ou+LXvSiLF++fMDzPvnkk+nu7u71AwAwYUrlpNJ29M6zH6zfVLYIUoBxZdwEAABDM6ww5Uc/+lGq1WqWLFnS6/iSJUuyb9++fp/zla98JZ/4xCdy22239fv40VBk8+bN+clPfpIjR47kYx/7WB5++OF0ddXXDN+3b19mz56dU089dcjnvfHGG7Nw4cJjP83NzcP5VQEARt+81uTU9qRhWe/jDU314/MsYQqML+MmAAAYmhPagH6oDh48mLe+9a257bbbsmjRon7bnHTSSeno6MiDDz6Y0047LfPnz8+Xv/zlvO51r0tDw4mXt3nz5hw4cODYz549e074tQAARs281mTxruS0LyenfrZ+u3inIAWYEMZNAAAwNLOG03jRokUpl8vZv39/r+P79+/P0qVL+7T/3ve+l127duXiiy8+dqynp6d+4lmz8sADD+Sss87KqlWrsn379hw4cCBHjhzJ6aefntWrV+fcc89NkixdujRHjhzJY4891mt2ykDnTZI5c+Zkzpw5w/n1AADGR6mczFkz0VUAGDcBAMAQDWvqx+zZs7Nq1arcfffdx4719PTk7rvvznnnnden/Yte9KLcf//92b59+7GfN7zhDbnggguyffv2PlPIFy5cmNNPPz0PPfRQ/u3f/i3r169PkqxatSonnXRSr/M+8MAD2b17d7/nBYCJ0lOtZte2bbn/9tuza9u29FSrE10SAAAAACM0rJkpSbJp06ZceeWVOffcc/PqV786W7ZsyaFDh3LVVVclSa644oosW7YsN954Y+bOnZtzzjmn1/OPziw5/vhf/dVf5fTTT8/y5ctz//33Z+PGjbnkkkty4YUXJqmHLG9/+9uzadOmnHbaaalUKnnve9+b8847L695zWtO9HcHgFG1o6MjWzduTPfDDx87Vmlqyrq2tqxstYQTAAAAwFQ17DDlsssuy6OPPprrrrsu+/btyyte8Yps3br12Kb0u3fvHvZeJ11dXdm0aVP279+fxsbGXHHFFfnQhz7Uq80f/uEfpqGhIW984xvz5JNP5qKLLsrHP/7x4ZYPAGNiR0dH7tywIanVeh3v3rs3d27YkEvb2wUqAAAAAFNUqVZ71rc+01R3d3cWLlyYAwcOpFKpTHQ5AEwjPdVq2las6DUjpZdSKZWmpmzcuTMN5fL4FgfMaD4DM1z+zgAAMJMM5/Pv8KaQAAB97O7sHDhISZJaLd179mR3Z+f4FQUAAADAqBGmAMAIHezqGtV2AAAAAEwuwhQAGKEFjY2j2g4AAACAyUWYAgAjtLylJZWmpqRU6r9BqZRKc3OWt7SMb2EAAAAAjAphCgCMUEO5nHVtbfU7zw5Unr6/bssWm88DAAAATFHCFAAYBStbW3Npe3sqy5b1Ol5pasql7e1Z2do6QZUBAAAAMFKzJroAAJguVra25uz167O7szMHu7qyoLExy1tazEgBAAAAmOKEKQAwihrK5axYs2aiywAAAABgFFnmCwAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoIAwBQAAAAAAoMCsiS4AAAAAAABGU7Xak87O3enqOpjGxgVpaVmectncAk6cMAUAAAAAgGmjo2NHNm7cmocf7j52rKmpkra2dWltXTmBlTGVieIAAAAAAJgWOjp2ZMOGO3sFKUmyd293Nmy4Mx0dOyaoMqY6YQoAAAAAAFNetdqTjRu3plbr+9jRY9deuzXVas/4Fsa0IEwBAAAAAGDK6+zc3WdGyvFqtWTPnu50du4ex6qYLoQpAAAAAABMeV1dB0e1HRxPmAIAAAAAwJTX2LhgVNvB8YQpAAAAAABMeS0ty9PUVEmp1P/jpVLS3FxJS8vy8S2MaUGYAgAAAADAlFcuN6StbV2S9AlUjt7fsmVdymVfizN8/tYAAAAAADAttLauTHv7pVm2rNLreFNTJe3tl6a1deUEVcZUN2uiCwAAAAAAgNHS2roy69efnc7O3enqOpjGxgVpaVluRgojIkwBAAAAAGBaKZcbsmbNiokug2lEFAcAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFBAmAIAAAAAAFDghMKUm2++OStWrMjcuXOzevXqfP3rXx/S8z73uc+lVCrlkksu6XX88ccfz3ve8540NTVl3rx5efGLX5xbb721V5s1a9akVCr1+nnXu951IuUDAAAAAAAM2azhPuGOO+7Ipk2bcuutt2b16tXZsmVLLrroojzwwANZvHjxgM/btWtX3v/+96elpaXPY5s2bco//dM/5TOf+UxWrFiRf/iHf8iv/dqv5Ywzzsgb3vCGY+2uvvrqfPjDHz52f/78+cMtHwAAAAAAYFiGPTPlpptuytVXX52rrrrq2AyS+fPn55Of/OSAz6lWq3nLW96SG264Ic9//vP7PP7Vr341V155ZdasWZMVK1bkne98Z17+8pf3mfEyf/78LF269NhPpVIZbvkAAAAAAADDMqww5ciRI7nvvvuydu3aZ16goSFr167NvffeO+DzPvzhD2fx4sV5+9vf3u/j/+2//bd8/vOfz969e1Or1fLlL385Dz74YC688MJe7f7yL/8yixYtyjnnnJPNmzfniSeeGPCcTz75ZLq7u3v9AAAA8AzjJgAAGJphLfP1ox/9KNVqNUuWLOl1fMmSJfnOd77T73O+8pWv5BOf+ES2b98+4Ov+0R/9Ud75znemqakps2bNSkNDQ2677bacf/75x9pcfvnled7znpczzjgj3/rWt/Kbv/mbeeCBB9LR0dHva95444254YYbhvPrAQAAzCjGTQAAMDTD3jNlOA4ePJi3vvWtue2227Jo0aIB2/3RH/1Rvva1r+Xzn/98nve85+Wee+7JNddckzPOOOPYLJh3vvOdx9q/9KUvTWNjY37hF34h3/ve93LWWWf1ec3Nmzdn06ZNx+53d3enubl5FH87AACAqc24CQAAhmZYYcqiRYtSLpezf//+Xsf379+fpUuX9mn/ve99L7t27crFF1987FhPT0/9xLNm5YEHHsgZZ5yR3/qt38pdd92VX/qlX0qSvOxlL8v27dvzv/7X/+q1pNjxVq9enST57ne/22+YMmfOnMyZM2c4vx4AAMCMYtwEAABDM6w9U2bPnp1Vq1bl7rvvPnasp6cnd999d84777w+7V/0ohfl/vvvz/bt24/9vOENb8gFF1yQ7du3p7m5OU899VSeeuqpNDT0LqVcLh8LXvpzdNmwxsbG4fwKAAAAAAAAwzLsZb42bdqUK6+8Mueee25e/epXZ8uWLTl06FCuuuqqJMkVV1yRZcuW5cYbb8zcuXNzzjnn9Hr+qaeemiTHjs+ePTs///M/n9/4jd/IvHnz8rznPS///M//nD//8z/PTTfdlKQ+w+Wzn/1sXv/61+e5z31uvvWtb+V973tfzj///LzsZS8bye8PAAAAAABQaNhhymWXXZZHH3001113Xfbt25dXvOIV2bp167FN6Xfv3t1nlslgPve5z2Xz5s15y1vekh//+Md53vOel4985CN517velaQeuPzjP/7jseCmubk5b3zjG/PBD35wuOUDADAJVGtJ5xNJ18+SxllJy/ykXJroqgAAAKB/pVqtVpvoIsZDd3d3Fi5cmAMHDqRSqUx0OQAAM1ZHd7JxX/Lwz5451jQraVuatPqYNqp8Bma4/J0BAGAmGc7n3+FNIQEAgBHo6E42PNw7SEmSvT+rH+/onpi6AAAAoIgwBQCAcVGt1Wek9Dct+uixa/fV2wEAAMBkMuw9Uxh/PdVqdnd25mBXVxY0NmZ5S0sayuWJLgsAYFg6n+g7I+V4tSR7flZvt+bkcSsLAAAABiVMmeR2dHRk68aN6X744WPHKk1NWdfWlpWtrRNYGQDA8HQVBCkn0g4AAADGi2W+JrEdHR25c8OGXkFKknTv3Zs7N2zIjo6OCaoMAGD4God4Gc9Q2wEAAMB4EaZMUj3VarZu3JjU+lk0/OljW6+9Nj3V6jhXBgBwYlrmJ02zktIAj5eSNM+qtwMAAIDJRJgySe3u7OwzI6WXWi3de/Zkd2fn+BUFADAC5VLStrT+388OVI7e37K03g4AAAAmE2HKJHWwq2tU2wEATAatlaS9KVn2rKW8mmbVj7dWJqYuAAAAKGJF6klqQWPjqLYDAJgsWivJ+gVJ5xP1zeYbn17ay4wUAAAAJithyiS1vKUllaamdO/d2/++KaVSKk1NWd7SMv7FAQCMULmUrDl5oqsAAACAobHM1yTVUC5nXVtb/U7pWZdpPn1/3ZYtaSiXx7kyAAAAAACYWYQpk9jK1tZc2t6eyrJlvY5XmppyaXt7Vra2TlBlAAAAAAAwc1jma5Jb2dqas9evz+7Ozhzs6sqCxsYsb2kxIwUAAAAAAMaJMGUKaCiXs2LNmokuAwAAAAAAZiTLfAEAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABQQpgAAAAAAABSYNdEFjJdarZYk6e7unuBKAABgfBz97Hv0szAMxrgJAICZZDhjphkTphw8eDBJ0tzcPMGVAADA+Dp48GAWLlw40WUwBRg3AQAwEw1lzFSqzZDL1Hp6evLDH/4wCxYsSKlUGvfzd3d3p7m5OXv27EmlUhn3808H+nDk9OHI6cPRoR9HTh+OnD4cOX04cmPdh7VaLQcPHswZZ5yRhgYr/DI446apTx+OnD4cOX04cvpw5PThyOnDkdOHIzeZxkwzZmZKQ0NDmpqaJrqMVCoV/+OMkD4cOX04cvpwdOjHkdOHI6cPR04fjtxY9qEZKQyHcdP0oQ9HTh+OnD4cOX04cvpw5PThyOnDkZsMYyaXpwEAAAAAABQQpgAAAAAAABQQpoyTOXPm5Prrr8+cOXMmupQpSx+OnD4cOX04OvTjyOnDkdOHI6cPR04fQm/+nxg5fThy+nDk9OHI6cOR04cjpw9HTh+O3GTqwxmzAT0AAAAAAMCJMDMFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFAAAAAACggDAFYBr51Kc+lVKp1O/PBz7wgTE551e/+tX8zu/8Th577LExef2R+Pa3v51f/uVfzvOf//zMnz8/ixYtyvnnn5+//du/nejSAACACWLcVOwjH/lISqVSzjnnnIkuBWBSmTXRBQAw+j784Q/nzDPP7HVsrD4If/WrX80NN9yQt73tbTn11FPH5Bwn6gc/+EEOHjyYK6+8MmeccUaeeOKJ/J//83/yhje8IX/yJ3+Sd77znRNdIgAAMEGMm/p6+OGH89GPfjQnn3zyRJcCMOkIUwCmode97nU599xzJ7qMETl06NCIP8C//vWvz+tf//pex97znvdk1apVuemmm4QpAAAwgxk39fX+978/r3nNa1KtVvOjH/1o1F4XYDqwzBfADPTFL34xLS0tOfnkk7NgwYL80i/9Ur797W/3avOtb30rb3vb2/L85z8/c+fOzdKlS/Mrv/Ir+c///M9jbX7nd34nv/Ebv5EkOfPMM49Njd+1a1d27dqVUqmUT33qU33OXyqV8ju/8zu9XqdUKuU//uM/cvnll+c5z3lOfu7nfu7Y45/5zGeyatWqzJs3L6eddlre9KY3Zc+ePSf0u5fL5TQ3N0+J6fUAAMDEmWnjpnvuuSft7e3ZsmXLkJ8DMJOYmQIwDR04cKDPVUSLFi1KkvzFX/xFrrzyylx00UX52Mc+lieeeCK33HJLfu7nfi7f/OY3s2LFiiTJl770pXz/+9/PVVddlaVLl+bb3/52/vRP/zTf/va387WvfS2lUimtra158MEHc/vtt+cP//APj53j9NNPz6OPPjrsun/5l385L3jBC/LRj340tVotSX293g996EO59NJL8453vCOPPvpo/uiP/ijnn39+vvnNbw5pivyhQ4dy+PDhHDhwIJ///OfzxS9+MZdddtmw6wMAAKYP46ZnVKvVvPe978073vGOvPSlLx12TQAzQg2AaePP/uzPakn6/anVarWDBw/WTj311NrVV1/d63n79u2rLVy4sNfxJ554os/r33777bUktXvuuefYsT/4gz+oJant3LmzV9udO3fWktT+7M/+rM/rJKldf/31x+5ff/31tSS1N7/5zb3a7dq1q1Yul2sf+chHeh2///77a7NmzepzfCC/+qu/eqwfGhoaahs2bKj9+Mc/HtJzAQCA6cW4qa8//uM/ri1cuLD2yCOP1Gq1Wu3nf/7nay95yUsGfR7ATGJmCsA0dPPNN+eFL3xhn+Nf+tKX8thjj+XNb35zryuwyuVyVq9enS9/+cvHjs2bN+/Yf//0pz/N448/nte85jVJkm984xtpaWkZ9brf9a539brf0dGRnp6eXHrppb3qXbp0aV7wghfky1/+cn7rt35r0Ne99tprs2HDhvzwhz/MnXfemWq1miNHjox6/QAAwNRh3FT3n//5n7nuuuvyoQ99KKeffvqo1wswXQhTAKahV7/61f1upPjQQw8lSf77f//v/T6vUqkc++8f//jHueGGG/K5z30ujzzySK92Bw4cGMVqn3HmmWf2uv/QQw+lVqvlBS94Qb/tTzrppCG97ote9KK86EUvSpJcccUVufDCC3PxxRfnX/7lX1IqlUZWNAAAMCUZN9V98IMfzGmnnZb3vve9o1YjwHQkTAGYQXp6epLU1/9dunRpn8dnzXrmn4VLL700X/3qV/Mbv/EbecUrXpFTTjklPT09Wbdu3bHXKTJQSFGtVgd8zvFXdR2tt1Qq5Ytf/GLK5XKf9qeccsqgdfRnw4YN+dVf/dU8+OCDOfvss0/oNQAAgOlpJo2bHnroofzpn/5ptmzZkh/+8IfHjv/0pz/NU089lV27dqVSqeS0004b7FcBmPaEKQAzyFlnnZUkWbx4cdauXTtgu5/85Ce5++67c8MNN+S66647dvzoFVrHG+jD/3Oe85wkyWOPPdbr+A9+8INh1Vur1XLmmWf2O/3+RB0+fDjJ2F0pBgAATF0zady0d+/e9PT05Nd//dfz67/+630eP/PMM7Nx48Zs2bJlWK8LMB01THQBAIyfiy66KJVKJR/96Efz1FNP9Xn80UcfTZJjVzPVarVej/f3Afrkk09O0vfDf6VSyaJFi3LPPff0Ov7xj398yPW2tramXC7nhhtu6FNLrVbLf/7nfxY+/9nT7JPkqaeeyp//+Z9n3rx5efGLXzzkWgAAgJlhJo2bzjnnnNx11119fl7ykpdk+fLlueuuu/L2t799yLUATGdmpgDMIJVKJbfcckve+ta35r/+1/+aN73pTTn99NOze/fufOELX8hrX/va/PEf/3EqlUrOP//8/P7v/36eeuqpLFu2LP/wD/+QnTt39nnNVatWJUl++7d/O29605ty0kkn5eKLL87JJ5+cd7zjHfm93/u9vOMd78i5556be+65Jw8++OCQ6z3rrLPyP//n/8zmzZuza9euXHLJJVmwYEF27tyZu+66K+985zvz/ve/f8Dn/+qv/mq6u7tz/vnnZ9myZdm3b1/+8i//Mt/5znfyv//3/z7hZcIAAIDpayaNmxYtWpRLLrmkz/GjgVB/jwHMVMIUgBnm8ssvzxlnnJHf+73fyx/8wR/kySefzLJly9LS0pKrrrrqWLvPfvazee9735ubb745tVotF154Yb74xS/mjDPO6PV6r3rVq/K7v/u7ufXWW7N169b09PRk586dOfnkk3Pdddfl0UcfTXt7e+6888687nWvyxe/+MUsXrx4yPV+4AMfyAtf+ML84R/+YW644YYkSXNzcy688MK84Q1vKHzuZZddlk984hO55ZZb8p//+Z9ZsGBBVq1alY997GODPhcAAJi5ZtK4CYChKdWePf8PAAAAAACAY+yZAgAAAAAAUECYAgAAAAAAUECYAgAAAAAAUECYAgAAAAAAUECYAgAAAAAAUECYAgAAAAAAUGDWRBcwXnp6evLDH/4wCxYsSKlUmuhyAABgzNVqtRw8eDBnnHFGGhpcR8XgjJsAAJhJhjNmmjFhyg9/+MM0NzdPdBkAADDu9uzZk6ampokugynAuAkAgJloKGOmGROmLFiwIEm9UyqVygRXAwAAY6+7uzvNzc3HPgvDYIybAACYSYYzZpoxYcrRKeqVSsWgAACAGcVyTQyVcRMAADPRUMZMFk4GAAAAAAAoIEwBAAAAAAAoIEwBAAAAAAAoMGP2TAEAYGaqVqt56qmnJrqMMXHSSSelXC5PdBkAAMAUZsw0NMIUAACmpVqtln379uWxxx6b6FLG1KmnnpqlS5faZB4AABgWY6bhEaYAADAtHR0ULF68OPPnz592YUOtVssTTzyRRx55JEnS2Ng4wRUBAABTiTHT8AhTAACYdqrV6rFBwXOf+9yJLmfMzJs3L0nyyCOPZPHixZb8AgAAhsSYafhsQA8AwLRzdL3f+fPnT3AlY+/o7zhd1zgGAABGnzHT8AlTAACYtqbbNPX+zITfEQAAGBszYTwxWr+jMAUAAAAAAKCAMAUAAAAAAKCAMAUAAAZQrfZk27Zduf32+7Nt265Uqz3jct6bb745K1asyNy5c7N69ep8/etfH5fzAgAADNdMGTfNGtNXBwCAKaqjY0c2btyahx/uPnasqamStrZ1aW1dOWbnveOOO7Jp06bceuutWb16dbZs2ZKLLrooDzzwQBYvXjxm5wUAABiumTRuMjMFAACepaNjRzZsuLPXgCBJ9u7tzoYNd6ajY8eYnfumm27K1VdfnauuuiovfvGLc+utt2b+/Pn55Cc/OWbnBAAAGK6ZNm4SpgAAwHGq1Z5s3Lg1tVrfx44eu/barWMydf3IkSO57777snbt2mPHGhoasnbt2tx7772jfj4AAIATMRPHTcIUAAA4Tmfn7j5XVh2vVkv27OlOZ+fuUT/3j370o1Sr1SxZsqTX8SVLlmTfvn2jfj4AAIATMRPHTcIUAAA4TlfXwVFtBwAAMN3MxHGTMAUAAI7T2LhgVNsNx6JFi1Iul7N///5ex/fv35+lS5eO+vkAAABOxEwcNwlTAADgOC0ty9PUVEmp1P/jpVLS3FxJS8vyUT/37Nmzs2rVqtx9993HjvX09OTuu+/OeeedN+rnAwAAOBEzcdwkTAEAgOOUyw1pa1uXJH0GBkfvb9myLuXy2HyU3rRpU2677bZ8+tOfzo4dO/Lud787hw4dylVXXTUm5wMAABiumThumjVmrwwAAFNUa+vKtLdfmo0bt/baVLGpqZItW9altXXlmJ37sssuy6OPPprrrrsu+/btyyte8Yps3bq1z+aKAAAAE2mmjZtKtVqtNmavPol0d3dn4cKFOXDgQCqVykSXAwDAGPrpT3+anTt35swzz8zcuXNP+HWq1Z50du5OV9fBNDYuSEvL8jG7supEFf2uPgMzXP7OAADMDKM1Zkom/7hptMZMZqYAAMAAyuWGrFmzYqLLAAAAmLRmyrhp8sRDAAAAAAAAk5CZKZNBrZoc6Ux6upKGxmR2S1IqD+slRjyVahRqmOz1TYYaJnt9k6GGyVzfqExZ1EdjXsOY16iPxrw+fTQO5x+FGsa8xlHoo5/+9Gf5yU8O55RTSjnllNkpPXtXxEFrqCW1x5McSTI7KZ3Sd2dFYNLoqVazu7MzB7u6sqCxMctbWtJQfuZ9Y8yXnxjkfWuw+sajRn00uKneR+OxzMqE16CPBqePBqePBqePBjcN+qhWq+XQoSM5dKgns2eXT2zcVGSQMVWtVsuRxx9P9ciRlGfPzuxTThnd84+yCQlT7rnnnvzBH/xB7rvvvnR1deWuu+7KJZdcUvicbdu2ZdOmTfn2t7+d5ubmfPCDH8zb3va2cal3TB3uSLo3Jj0PP3OsoSmptCXzWof0Eh0dO/rd5KetbYib/IxCDZO9vslQw2SvbzLUMJnrG/H5R6GGMa9RH415ffpIH41GffpoaH30+7//z/md33l5qtWDSQ5n9uxympsrec5z5g3tl+j5SVLdk9SOPHOsNDspNycNzxnaawDjZkdHR7Zu3Jjuh59536g0NWVdW1tWtraOzntnkUHetwarLxml9/cC+mhwU72Pxry+6KOhmPAa9NHg9NHg9NHgpkEf/cM/fC/z5j2eJ554LEdjgmGPm4oMMqY6/JOfpHvPnlSPPPN4efbsVJqbM+85k3PMNSEb0H/xi1/M//t//y+rVq1Ka2vroGHKzp07c8455+Rd73pX3vGOd+Tuu+/Otddemy984Qu56KKLhnTOSbmR4uGO5LENSZ79R/B0+nZq+6BfGHR07MiGDXfm2X+KRwO89vZLi/8HHIUaJnt9k6GGyV7fZKhhMtc34vOPQg2D0UeD00eD00eD00eDmyx9tHz5ybn11tdm0aJlOf76obPOes7gA4OenyQ/+97Aj886a1IFKjagZzRNxb8zOzo6cueGDRnojWf5+7fk7f/rJyN77ywyyPvWjm3vz51v+V8D1ndpe3t2ZOXI398L6KPBTfU+GvP6oo+GQh8NTh8NTh8NTh8Nbih99OG/OpJbbuk7ZkqGOG4qMsiY6vDBpfnJzn0DPv6cs84a1UBltMZMExKm9CqgVBo0TPnN3/zNfOELX8i///u/Hzv2pje9KY899li2bt06pPNMukFBrZo8sqJ3etlLqZ5mLt454JIW1WpPVqxo65Vg9nqFUj3R3LlzY/9TxEahhiKTob7JUEORyVDfZKihyETXN+Lzj0INg9FHg9NHg9NHg9NHg5tMffS85/UfpsyeXc5LX7p44KnjtVrys/t7Xz3Vp4zZyayXPjPamWDCFEbTVPs701Otpm3Fil5XXPZSKuXxhoX539VfT62fLUOH9N5ZZJD3rZ5q0vbqcrq7qgPWV1nWlD+sbcyevY8P1GRENeqjwU2HPhrT+qKPhkIfDU4fDU4fDU4fDW6ofdTe9Fu55daf6zdMGXTcVGSQMVUtySM7kupTA79EefbsLH7pS0dtya/RGjOd2J/IOLv33nuzdu3aXscuuuii3HvvvQM+58knn0x3d3evn0nlSGfBFwVJUkt69tTbDaCzc/eAX1Yk9b+3e/Z0p7Nz95jVUGQy1DcZaigyGeqbDDUUmej6Rnz+UahhMPpocPpocPpocPpocJO9j5LkyJFqHn+8ICipPV4cpCT1x2v9f6EHU82kHzcNYndn58BfFCRJrZZTqo/lefnBQA8P/t5ZZJD3rd3/koG/THm6gO6H96S89/6iJiOqUR8Nbjr00ZjWF300FPpocPpocPpocPpocEPtozPywwGbDDpuKjLImOrIoeIgJUmqR47kyOOTb8w1JcKUffv2ZcmSJb2OLVmyJN3d3Tl8+HC/z7nxxhuzcOHCYz/Nzc3jUerQ9XSNuF1X18EhvcSA7UahhhM671Db6aPB2+mjwduNsL4Rn38UahjRuYfSTh8N3k4fDd5OHw3eTh8N3m6c+ujIkYLBTYY6YDjBgQVMMpN+3DSIg11De984JcWD8aG+f/QxyPvWwf1De5nB6ktOvEZ9NLiZ0kcnXF/00VDoo8Hpo8Hpo8Hpo8ENtY9OzqHCx4vHTYXPLHx0sCDlWLsjk2/MNSXClBOxefPmHDhw4NjPnj17Jrqk3hoaR9yusXHBkF5iwHajUMMJnXeo7fTR4O300eDtRljfiM8/CjWM6NxDaaePBm+njwZvp48Gb6ePBm83Tn00e3bREmazh1bDkNvB5Dbpx02DWNA4tPeNx3NK4eNDff/oY5D3rQVLCh8+ZrD6khOvUR8Nbqb00QnXF300FPpocPpocPpocPpocEPto0M5ufDx4nFT4TMLHy2fNLRXKc+efGOuKRGmLF26NPv394719u/fn0qlknnz+t8IZ86cOalUKr1+JpXZLfU1vzPQum+lpKG53m4ALS3L09RUGXC57lIpaW6upKVl+ZjVUGQy1DcZaigyGeqbDDUUmej6Rnz+UahhMPpocPpocPpocPpocJO9j5L6gOCUUwo+lJdOqe+JUqQ0u94OpoFJP24axPKWllSamgbew6hUyuPlU7M7zxvo4cHfO4sM8r61fHVSaSwX1ldpak512UtH9v5eQB8Nbjr00ZjWF300FPpocPpocPpocPpocEPto66cMeBrDDpuKjLImGr2yYMHKuXZszP7lMk35poSYcp5552Xu+++u9exL33pSznvvPMmqKJRUConlbajd579YP2msiVFm7+Wyw1pa1tXf8azXuLo/S1b1g28WdEo1FBkMtQ3GWooMhnqmww1FJno+kZ8/lGoYTD6aHD6aHD6aHD6aHCTuY+Oam6uFG9iWCol5WeWOarWkm1PLMjtB0/LticWpFpL/fFR2gixP/fcc08uvvjinHHGGSmVSvnrv/7rMTsXTHUN5XLWtT39vjHAG8+LN92QWqnhxN87iwzyvtVQLmXd/95UWN+6ti3Z8v97fVGTEdWojwY3HfpoTOuLPhoKfTQ4fTQ4fTQ4fTS4offRwGOaQcdNz1KtJdsOJbcfSLY9UUq1YeClY0tJKk1LC1+v0txceP6JGjNNSJjy+OOPZ/v27dm+fXuSZOfOndm+fXt2765vrLN58+ZcccUVx9q/613vyve///38f//f/5fvfOc7+fjHP54777wz73vf+yai/NEzrzU5tT1pWNb7eENT/fi81kFforV1ZdrbL82yZb2vIGtqqqS9/dK0tq4c8xome32ToYbJXt9kqGEy1zfi849CDYPRR4PTR4PTR4PTR4ObLH20ZEnvq5hmzy7nrLOek+c8p/9Zzb3P9Zxk1lnpOLQoK3a9LBf88Oxcvv/5ueCHZ2fFD/5rOh5/zuCvMQKHDh3Ky1/+8tx8881jeh6YLla2tubS9vZUlvV+36g0NeXS9vZc9fu/PvL3ziKDvG+tfPPvF9a3srV1dN7fC+ijwU31Phrz+qKPhkIfDU4fDU4fDU4fDW4ofdTW9ro+oc2wxk1P6+hOVjyUXPCD5PK99dsV33tOOg6/KH1mqJRmJ7POyrznNuU5Z53VZymv8uzZec5ZZ2Xec4rHXBM1ZirVarXauJ4xybZt23LBBRf0OX7llVfmU5/6VN72trdl165d2bZtW6/nvO9978t//Md/pKmpKR/60Ifytre9bcjn7O7uzsKFC3PgwIHJN3W9Vk2OdNY3MGporE8XG+YVodVqTzo7d6er62AaGxekpWX58BLMUahhstc3GWqY7PVNhhomc30jPv8o1DDmNeqjMa9PH43D+UehhjGvUR+NeX2HDj2RBx/8XpYubcopp8zPKafMHtaVVR3dyYaHa6l/UH7meUf/q70paR2Hj5SlUil33XVXLrnkkgHb/PSnP83OnTtz5plnZu7cub0em9SfgZmUpvLfmZ5qNbs7O3OwqysLGhuzvKUlDeVn3jdG5b2zyCDvW4PVNx416qPBTfU+GvP6JkMN+mhw+mhw+mhw+mhwU7yPfvrTn+b73/9+lixpSjLr2NJewx83Jc8OGI6Nm5bV0rrg8dQ3pX96ueTjXr9Wq+XI44+neuTIsaW9hnP+ZHzHTBMSpkyEqTwoAABgeIo+LA+mWqtfWfXwz/p/vJSkaVay8wVJeexW+6qfS5jCOPN3BgBgZhjJmCmZPOOm8RwzTYk9UwAAYLx0PjHwgCCpX3W152f1dgAAADPRTBw3CVMAAOA4XQUDghNpBwAAMN3MxHGTMAUAAI7TOGt02wEAAEw3M3HcJEwBAIDjtMyvr+070LK+pSTNs+rtAAAAZqKZOG6aRrkQAACMXLmUtC1NNjxcHwDUjnvs6EBhy9Kx20Tx8ccfz3e/+91j93fu3Jnt27fntNNOy/Lly8fmpAAAAMMwkeOmiRozmZkCAADP0lpJ2puSZc+69KhpVv14a2Xszv1v//ZveeUrX5lXvvKVSZJNmzblla98Za677rqxOykAAMAwTdS4aaLGTGamAABAP1oryfoFSecT9U0TG5+eoj5WM1KOWrNmTWq12uANAQAAJthEjJsmaswkTAEAgAGUS8makye6CgAAgMlrpoybLPMFAAAAAABQQJgCAAAAAABQQJgCAAAAAABQQJgCAAAAAABQQJgCAAAAAABQQJgCAAAAAABQQJgCAAAAAABQQJgCAAAAAABQQJgCAAAAAABQQJgCAAADqVWTJ7clh2+v39aqY3q6G2+8Ma961auyYMGCLF68OJdcckkeeOCBMT0nAADAiMyQcZMwBQAA+nO4I3lkRfLjC5LHLq/fPrKifnyM/PM//3OuueaafO1rX8uXvvSlPPXUU7nwwgtz6NChMTsnAADACZtB46ZZY/rqAAAwFR3uSB7bkKTW+3jP3qePtyfzWkf9tFu3bu11/1Of+lQWL16c++67L+eff/6onw8AAOC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-      "text/plain": [
-       "<Figure size 2000x2000 with 4 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "WARMUP = 0.1 # 10%\n",
-    "warmup_idx = int(len(states) * WARMUP)\n",
-    "\n",
-    "xstates = states[:-1][warmup_idx:]\n",
-    "target = timeseries[1:][warmup_idx:]\n",
-    "fig, ax = utilities.result_plotter(xstates, target)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'state 2')"
-      ]
-     },
-     "execution_count": 199,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "\n",
-    "\n",
-    "\n",
-    "cmap = plt.get_cmap('jet', len(np.unique(timeseries)))\n",
-    "\n",
-    "plt.scatter(xstates[:, 0], xstates[:, 1], cmap=cmap, c=target)\n",
-    "# for i, x, y in zip(target, xstates[:, 2 * ii], xstates[:, 2 * ii + 1]):\n",
-    "#     ax.scatter(x, y,  color=cmap(i))\n",
-    "\n",
-    "# ax.set_xlabel(f'state {2 * ii + 1}')\n",
-    "# ax.set_ylabel(f'state {2*(ii+1)}')\n",
-    "plt.xlabel(\"state 1\")\n",
-    "plt.ylabel(\"state 2\")\n",
-    "# plt.show()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The biggest question of the life is only how long you can sit on this desk before you get shooed away"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "if xstates.shape[-1] >= 3:\n",
-    "\n",
-    "    fig = plt.figure()\n",
-    "    ax = fig.add_subplot(projection='3d')\n",
-    "\n",
-    "    cmap = plt.get_cmap('jet', len(np.unique(timeseries)))\n",
-    "    for i, x, y, z in zip(target, xstates[:, 0], xstates[:, 1], xstates[:, 2]):\n",
-    "        ax.scatter(x, y, z, color=cmap(i))\n",
-    "    ax.set_xlabel('state 1')\n",
-    "    ax.set_ylabel('state 2')\n",
-    "    ax.set_zlabel('state 3')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Training"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Score of KNeighborsClassifier(n_neighbors=9): 0.45148148148148143\n",
-      "Score of KNeighborsClassifier(n_neighbors=8): 0.4459259259259257\n",
-      "Score of KNeighborsClassifier(): 0.43777777777777793\n",
-      "Score of KNeighborsClassifier(n_neighbors=7): 0.4344444444444443\n",
-      "Score of KNeighborsClassifier(n_neighbors=6): 0.42888888888888876\n",
-      "Score of KNeighborsClassifier(n_neighbors=3): 0.4281481481481482\n",
-      "Score of KNeighborsClassifier(n_neighbors=2): 0.4266666666666666\n",
-      "Score of KNeighborsClassifier(n_neighbors=4): 0.42481481481481476\n",
-      "Score of KNeighborsClassifier(n_neighbors=1): 0.40148148148148155\n",
-      "Score of RidgeClassifier(alpha=0.0, max_iter=1000): 0.3951851851851852\n",
-      "Score of RidgeClassifier(alpha=0.000125, max_iter=1000): 0.3951851851851852\n",
-      "Score of RidgeClassifier(alpha=0.00025, max_iter=1000): 0.39185185185185184\n",
-      "Score of RidgeClassifier(alpha=0.0005, max_iter=1000): 0.39037037037037015\n",
-      "Score of RidgeClassifier(alpha=0.000375, max_iter=1000): 0.3899999999999999\n",
-      "Score of RidgeClassifier(alpha=0.000625, max_iter=1000): 0.38444444444444437\n",
-      "Score of RidgeClassifier(alpha=0.00075, max_iter=1000): 0.38259259259259254\n",
-      "Score of RidgeClassifier(alpha=0.000875, max_iter=1000): 0.3796296296296295\n",
-      "Score of RidgeClassifier(alpha=0.001, max_iter=1000): 0.3781481481481482\n",
-      "Score of SVC(kernel='linear', max_iter=1000): 0.3585185185185186\n",
-      "Score of SVC(max_iter=1000): 0.3562962962962964\n",
-      "Score of SVC(kernel='poly', max_iter=1000): 0.3555555555555556\n",
-      "Score of SVC(kernel='sigmoid', max_iter=1000): 0.3144444444444444\n"
-     ]
-    }
-   ],
-   "source": [
-    "\n",
-    "\n",
-    "results = utilities.stress_test_models(xstates, target, models, test_to_train_ratio=1/3)\n",
-    "sorting = np.flip(np.argsort(results))\n",
-    "for model, res in zip(models[sorting], results[sorting]):\n",
-    "    print(f'Score of {model}: {res}')\n",
-    "    \n",
-    "\n",
-    "model = models[sorting][0]\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Predicting"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Predicting:   0%|          | 0/43 [00:20<?, ?it/s]\n"
-     ]
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[126], line 5\u001b[0m\n\u001b[0;32m      1\u001b[0m predict_from \u001b[39m=\u001b[39m timeseries[\u001b[39m-\u001b[39m\u001b[39m20\u001b[39m:]\n\u001b[0;32m      2\u001b[0m num_preds \u001b[39m=\u001b[39m \u001b[39m2\u001b[39m\n\u001b[1;32m----> 5\u001b[0m pred_states, preds \u001b[39m=\u001b[39m qres\u001b[39m.\u001b[39;49mpredict(\n\u001b[0;32m      6\u001b[0m     num_pred\u001b[39m=\u001b[39;49mnum_preds,\n\u001b[0;32m      7\u001b[0m     model\u001b[39m=\u001b[39;49mmodel,\n\u001b[0;32m      8\u001b[0m     shots\u001b[39m=\u001b[39;49mSHOTS,\n\u001b[0;32m      9\u001b[0m     from_series\u001b[39m=\u001b[39;49mpredict_from,\n\u001b[0;32m     10\u001b[0m     backend\u001b[39m=\u001b[39;49mbackend\n\u001b[0;32m     11\u001b[0m )\n",
-      "File \u001b[1;32mc:\\users\\otkul\\sintef\\repo\\reservoircomputingexamples\\qreservoirpy\\qreservoirpy\\reservoir.py:33\u001b[0m, in \u001b[0;36mQReservoir.predict\u001b[1;34m(self, num_pred, model, from_series, shots, backend)\u001b[0m\n\u001b[0;32m     31\u001b[0m \u001b[39mwith\u001b[39;00m tqdm(total\u001b[39m=\u001b[39mtotal, desc\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mPredicting\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mas\u001b[39;00m pbar:\n\u001b[0;32m     32\u001b[0m     \u001b[39mfor\u001b[39;00m _ \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(num_pred):\n\u001b[1;32m---> 33\u001b[0m         state \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrun(pred_series, incrementally\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m, shots\u001b[39m=\u001b[39;49mshots, disable_status_bar\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m, backend\u001b[39m=\u001b[39;49mbackend, transpile\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\u001b[39m.\u001b[39mreshape((\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_features))\n\u001b[0;32m     34\u001b[0m         state \u001b[39m=\u001b[39m state[\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m]\u001b[39m.\u001b[39mreshape((\u001b[39m1\u001b[39m, \u001b[39m-\u001b[39m\u001b[39m1\u001b[39m))\n\u001b[0;32m     35\u001b[0m         states\u001b[39m.\u001b[39mappend(state)\n",
-      "File \u001b[1;32mc:\\users\\otkul\\sintef\\repo\\reservoircomputingexamples\\qreservoirpy\\qreservoirpy\\reservoir.py:62\u001b[0m, in \u001b[0;36mQReservoir.run\u001b[1;34m(self, timeseries, shots, transpile, incrementally, disable_status_bar, backend)\u001b[0m\n\u001b[0;32m     58\u001b[0m \u001b[39mfor\u001b[39;00m series \u001b[39min\u001b[39;00m tqdm(timeseries, desc\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mSimulating\u001b[39m\u001b[39m\"\u001b[39m, disable\u001b[39m=\u001b[39mdisable_status_bar):\n\u001b[0;32m     60\u001b[0m     circ \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m__build(series)\n\u001b[1;32m---> 62\u001b[0m     mem \u001b[39m=\u001b[39m utilities\u001b[39m.\u001b[39;49msimulate(circ, shots, transpile, backend)\n\u001b[0;32m     64\u001b[0m     result\u001b[39m.\u001b[39mappend(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39manalyze_fcn(utilities\u001b[39m.\u001b[39mmemory_to_mean(mem, \u001b[39m1\u001b[39m)))\n\u001b[0;32m     66\u001b[0m result \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray(result)\n",
-      "File \u001b[1;32mc:\\users\\otkul\\sintef\\repo\\reservoircomputingexamples\\qreservoirpy\\qreservoirpy\\utilities.py:26\u001b[0m, in \u001b[0;36msimulate\u001b[1;34m(circuit, shots, transpile, backend)\u001b[0m\n\u001b[0;32m     25\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39msimulate\u001b[39m(circuit, shots, transpile, backend):\n\u001b[1;32m---> 26\u001b[0m     \u001b[39mreturn\u001b[39;00m _simulate(circuit, shots, transpile, backend)\u001b[39m.\u001b[39mget_memory()\n",
-      "File \u001b[1;32mc:\\users\\otkul\\sintef\\repo\\reservoircomputingexamples\\qreservoirpy\\qreservoirpy\\utilities.py:23\u001b[0m, in \u001b[0;36m_simulate\u001b[1;34m(circuit, shots, transpile, backend)\u001b[0m\n\u001b[0;32m     21\u001b[0m \u001b[39mif\u001b[39;00m transpile:\n\u001b[0;32m     22\u001b[0m     circuit \u001b[39m=\u001b[39m qs\u001b[39m.\u001b[39mtranspile(circuit, backend)\n\u001b[1;32m---> 23\u001b[0m \u001b[39mreturn\u001b[39;00m backend\u001b[39m.\u001b[39;49mrun(circuit, shots\u001b[39m=\u001b[39;49mshots, memory\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\u001b[39m.\u001b[39;49mresult()\n",
-      "File \u001b[1;32mc:\\Users\\otkul\\sintef\\repo\\quantumRC\\quantum\\lib\\site-packages\\qiskit_aer\\jobs\\utils.py:41\u001b[0m, in \u001b[0;36mrequires_submit.<locals>._wrapper\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m     39\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_future \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m     40\u001b[0m     \u001b[39mraise\u001b[39;00m JobError(\u001b[39m\"\u001b[39m\u001b[39mJob not submitted yet!. You have to .submit() first!\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m---> 41\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39mself\u001b[39m, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n",
-      "File \u001b[1;32mc:\\Users\\otkul\\sintef\\repo\\quantumRC\\quantum\\lib\\site-packages\\qiskit_aer\\jobs\\aerjob.py:106\u001b[0m, in \u001b[0;36mAerJob.result\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m     88\u001b[0m \u001b[39m@requires_submit\u001b[39m\n\u001b[0;32m     89\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mresult\u001b[39m(\u001b[39mself\u001b[39m, timeout\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m):\n\u001b[0;32m     90\u001b[0m     \u001b[39m# pylint: disable=arguments-differ\u001b[39;00m\n\u001b[0;32m     91\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Get job result. The behavior is the same as the underlying\u001b[39;00m\n\u001b[0;32m     92\u001b[0m \u001b[39m    concurrent Future objects,\u001b[39;00m\n\u001b[0;32m     93\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    104\u001b[0m \u001b[39m        concurrent.futures.CancelledError: if job cancelled before completed.\u001b[39;00m\n\u001b[0;32m    105\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 106\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_future\u001b[39m.\u001b[39;49mresult(timeout\u001b[39m=\u001b[39;49mtimeout)\n",
-      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.9_3.9.3568.0_x64__qbz5n2kfra8p0\\lib\\concurrent\\futures\\_base.py:441\u001b[0m, in \u001b[0;36mFuture.result\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m    438\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_state \u001b[39m==\u001b[39m FINISHED:\n\u001b[0;32m    439\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m__get_result()\n\u001b[1;32m--> 441\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_condition\u001b[39m.\u001b[39;49mwait(timeout)\n\u001b[0;32m    443\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_state \u001b[39min\u001b[39;00m [CANCELLED, CANCELLED_AND_NOTIFIED]:\n\u001b[0;32m    444\u001b[0m     \u001b[39mraise\u001b[39;00m CancelledError()\n",
-      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.9_3.9.3568.0_x64__qbz5n2kfra8p0\\lib\\threading.py:312\u001b[0m, in \u001b[0;36mCondition.wait\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m    310\u001b[0m \u001b[39mtry\u001b[39;00m:    \u001b[39m# restore state no matter what (e.g., KeyboardInterrupt)\u001b[39;00m\n\u001b[0;32m    311\u001b[0m     \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m--> 312\u001b[0m         waiter\u001b[39m.\u001b[39;49macquire()\n\u001b[0;32m    313\u001b[0m         gotit \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m\n\u001b[0;32m    314\u001b[0m     \u001b[39melse\u001b[39;00m:\n",
-      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "predict_from = timeseries[-20:]\n",
-    "num_preds = 2\n",
-    "\n",
-    "\n",
-    "pred_states, preds = qres.predict(\n",
-    "    num_pred=num_preds,\n",
-    "    model=model,\n",
-    "    shots=SHOTS,\n",
-    "    from_series=predict_from,\n",
-    "    backend=backend\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x1e77f6d87c0>"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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WlQsTWxopLEKYIeNQIm02PY6tUs4+h4H0nbEYRWfe/0ZFRUX4+vri6+tLUVFRtWNK+j0NgN/Z1RQVGG45txCNQVZWVuUyb948nJ2dq9z20ksvVY5VVZWKiop6zWdvb0+rVq3q9TFrQ1lZGXq9Hk9Pzxte/VpLUliEqKGc08exXzkWZwo5bNWdbhGrsLK2MXs7qqqSmZlJZmYm17qUV6+7Hua04okLhexfv+BWowvRKHh6elYuLi4uKIpS+efDhw/j5OTExo0b6du3L7a2tuzYsYPJkycTHh5eZTszZ85k8ODBlX82mUzMnTuX9u3bY29vT0BAAKtXr75mjsGDB5OZmckLL7xQeXQHrv5K6I033iAwMJAlS5bQtm1bmjVrxtNPP43RaOT999/H09OTVq1a8Y9//KPK9i9dusQTTzxBy5YtcXZ25q677iI5Obny/uTkZIYMGYKTkxPOzs707duXxMTEyvt37NjBHXfcgb29PT4+Pjz33HOVF2aEK0eH3n77bSZOnIizszPTp0+v9iuhAwcOMHz4cJo1a4aHhwcTJkyovKQIwOrVq/H398fe3p4WLVoQGhpa5XFqmxQWIWrAcDGPoiWj8eA8mbo2eD4Vjb2jU509nt7KijPdpgDQ+vBSjPX8N0XRBKkqlBVqs9TiNXhfe+013n33XQ4dOkSvXr1qtM7cuXP56quvWLhwIampqbzwwgs89thjbNu2rdrxP/74I23atOGtt96qPLpzLcePH2fjxo1s2rSJ77//nsWLFzNixAhOnz7Ntm3beO+993j99ddJSEioXGfMmDGcO3eOjRs3smfPHvr06cPdd9/NhQsXAHj00Udp06YNu3fvZs+ePbz22muVV3g+fvw4w4YN48EHHyQlJYWVK1eyY8eOq64Y/eGHHxIQEMC+ffv4+9//flXuS5cucdddd9G7d28SExPZtGkTOTk5jB07FrhytGv8+PE8/vjjHDp0iNjYWB544IFr/iWsNljusR8hLERJcSFnFoTjZ8okl+bYTPoRV3fPOn9c/xEzMBz6lDZqNntjvqdP2IQ6f0zRhJUXwT+9tXnsv50FG8da2dRbb73FPffcU+PxpaWl/POf/+SXX34hJCQEgA4dOrBjxw4+//xzBg0adNU6bm5u6PV6nJyc8PS8/nuByWRiyZIlODk54efnx5AhQzhy5AgbNmxAp9PRtWtX3nvvPX777TeCg4PZsWMHu3bt4ty5c9ja2gJXykV0dDSrV69m+vTpnDx5kpdffplu3boB0Llz58rHmzt3Lo8++igzZ86svO/TTz9l0KBBLFiwoPJKyXfddRcvvvhi5XoZGRlVcs+fP5/evXvzz3/+s/K2JUuW4OPjw9GjRykoKKCiooIHHniAdu3aAeDv71+TXX7TpLAIcR3GigoOzn+YPmX7uazak//QCjq261ovj+3QzIU474cIObsc+8QFIIVFiBsKCgoya/yxY8coKiq6quSUlZXRu3fvW87j6+uLk9N/j8Z6eHig1+urzMHk4eHBuXPngCtf9xQUFNCiRYsq2ykuLub48eMAREZG8sQTT/D1118TGhrKmDFj6NixY+X6KSkpfPvtt5XrqqqKyWQiPT2d7t27AzfeT8nJyfz22280a9bsqvuOHz/O0KFDufvuu/H39ycsLIyhQ4fy0EMP0bx5c3N2j1mksAhxDarJROLC6QQXbqdM1ZN5zxf09B9Qrxk6jYyk7PNv6F6eytG9sXTpM7heH180IdYOV450aPXYtcTRseqRGp1Od9XXFOXl5ZX/XlBw5ero69evp3Xr1lXG/XmE41b8+VXNnxRFqfY2k8lUmcfLy4vY2NirtvXn+TFvvPEGjzzyCOvXr2fjxo3MmTOHFStWMHr0aAoKCnjyySd57rnnrlq/bdv/XjLkr/vprwoKCrjvvvt47733rrrPy8sLvV7P1q1b2blzJ1u2bOHf//43/+///T8SEhJo3779dbd9s6SwCHEN8V//nZC8K9f0Sen/HkG331/vGVp6+7LbNZR+hs1c/m0eSGERdUVRau1rGUvSsmVLDhw4UOW2pKSkytLg5+eHra0tJ0+erPbrn2uxsbHBWAcXKe3Tpw/Z2dlYWVnh6+t7zXFdunShS5cuvPDCC4wfP56lS5cyevRo+vTpw8GDB+nUqdMt51izZg2+vr7X/OWQoijcdttt3HbbbcyePZt27dqxdu1aIiMjb+mxr0VOuhWiGrujowhJnw9AfOcXCRoxrda2rSgKfn5++Pn5Vf664HrcQq/8zx+Qv42szCO1lkOIpuCuu+4iMTGRr776irS0NObMmVOlwDg5OfHSSy/xwgsvsHz5co4fP87evXv597//zfLly6+5XV9fX7Zv386ZM2eq/HLmVoWGhhISEkJ4eDhbtmwhIyODnTt38v/+3/8jMTGR4uJinnnmGWJjY8nMzOSPP/5g9+7dlV/1vPrqq+zcuZNnnnmGpKQk0tLS+Omnn6466fZGIiIiuHDhAuPHj2f37t0cP36czZs3M2XKFIxGIwkJCfzzn/8kMTGRkydP8uOPP5Kbm1uZoy5IYRHiL1J+W03gvitnzcd7PsqAR2fX6vYdHBxITU0lNTUVB4cbHwrv6D+AA7aBWCkmMjd8UqtZhGjswsLC+Pvf/84rr7xCv379uHz5MhMnTqwy5u233+bvf/87c+fOpXv37gwbNoz169df96uNt956i4yMDDp27EjLli1rLa+iKGzYsIE777yTKVOm0KVLFx5++GEyMzMrz385f/48EydOpEuXLowdO5bhw4fz5ptvAtCrVy+2bdvG0aNHueOOO+jduzezZ8/G29u8E6q9vb35448/MBqNDB06FH9/f2bOnImrqys6nQ5nZ2e2b9/OvffeS5cuXXj99df56KOPGD58eK3ti79S1Lr8DVI9yc/Px8XFBYPBgLOzs9ZxRAOWtm87raMfwkEpJdE5lD7Pr0Kn12sdi+RfVxGwfRoFqj2mF1Jxdm1x45WEuIaSkhLS09Np37595a9GhKhL13rNmfP5LUdYhPg/Z06k4vbTYzgopey37U2viG8toqwA+A96kEydD82UYg6un691HCGEqHdSWIQAzuecRv36AVpg4Li+A75P/4iNbd38zbOoqIgePXrQo0ePa07N/1c6vZ4cv8cB8E37morysjrJJoQQlkoKi2jyCi9f4sKicNqo2ZxVWuEy7SecXNzq7PFUVeXgwYMcPHjQrFkhe907nQs440kuyVu+qrN8QghhiaSwiCatvKyU41EP0bkijYs4YXxkNe6ebW+8ogbsHJpxxGccAE77Pkf9v3kbhBCiKZDCIpos1WQiKWoivUp2U6zacG7kV/h0DtA61nV1GTmTUtWaLhVHObx7q9ZxhBCi3khhEU1W/OIX6GfYRIWq48id/6Zr0F1aR7qhFh5tSHYLA6Bk2780TiMaukbwI1HRQNTGa00Ki2iSEla+R8iZZQDs7TWbwLsf1jaQGTzCrlywLKBwJ6ePHbjBaCGu9ucsrzU96VuIW/Xna+2vlyUwh0zNL5qcfZuX0+/gXFAgru2ThDz4gtaRzNKuWx+S7fsTULyLM5s+os0zS7WOJBoYvV6Pq6tr5QX3HBwcajTrshDmUlWVoqIizp07h6urK/pbmCpCCotoUg7Gb8Jv54voFJUEt/sZMPndes+gKErl5dhv9kNCP/AZiJmIf+56DOdzcGnhUZsRRRPg6ekJUFlahKhLrq6ula+5m2X2TLfbt2/ngw8+YM+ePWRlZbF27VrCw8OvOX7y5MnVXo/Bz8+P1NRU4MqVJ/+cVvhPXbt25fDhwzXKJDPdiprIOJSI28r7caaQfQ4D8X/hJ6ysbbSOdVNUk4kT/+hDR2M6ce0jCJn0T60jiQbKaDRWuXqxELXN2tr6mkdWzPn8NvsIS2FhIQEBATz++OM88MADNxz/r3/9i3ff/e/fYisqKggICGDMmDFVxvXo0YNffvnlv8GucXVIIW5Gzunj2K8cizOFHLbqTreIVQ22rAAoOh0X/KfRMelvdEr/jrLS2XU20Z1o3PR6/S0dpheivpjdCoYPH27WxY1cXFxwcXGp/HN0dDQXL15kypQpVYNYWd3y4SIhqmO4mEfRktG05zyZujZ4PhWNvaOT1rFuWcDwqeQmfUBLLrJ742L6hUdoHUkIIepMvf9KaPHixYSGhlZ+h/+ntLQ0vL296dChA48++ignT5685jZKS0vJz8+vsghRnZLiQs4sCKe9KZNcmmMz6Udc3bUtxsXFxfTr149+/fpRXFx809uxsbXjWPtHAHDbv0gmkhNCNGr1WljOnj3Lxo0beeKJJ6rcHhwczLJly9i0aRMLFiwgPT2dO+64g8uXL1e7nblz51YeuXFxccHHx6c+4osGxlhRwcGoh/Er289l1Z78B1fg1a6r1rEwmUwkJiaSmJiI6RZLht/I5ylSbeloTCf1j//UUkIhhLA89VpYli9fjqur61Un6Q4fPpwxY8bQq1cvwsLC2LBhA5cuXWLVqlXVbmfWrFkYDIbK5dSpU/WQXjQkqslE4udP0qdgO2Wqnsx7vqCj/wCtY9U6lxYe7G85AgDjTrmKsxCi8aq3wqKqKkuWLGHChAnY2Fz/ZEdXV1e6dOnCsWPHqr3f1tYWZ2fnKosQ/yv+mzkE564GIKX/e/S8/X6NE9Wd1sNexKQqBBTvIvPwXq3jCCFEnai3wrJt2zaOHTvG1KlTbzi2oKCA48eP4+XlVQ/JRGOz+6fPCDnxKQDxnV8kaMQ0jRPVrTadepLsOBCAnC0fa5xGCCHqhtmFpaCggKSkJJKSkgBIT08nKSmp8iTZWbNmMXHixKvWW7x4McHBwfTs2fOq+1566SW2bdtGRkYGO3fuZPTo0ej1esaPH29uPNHEpcSuIXDv6wDEe4xnwKOzNU5UP+wGPQ9AwPlNnM85rXEaIYSofWYXlsTERHr37k3v3r0BiIyMpHfv3syefeWDISsr66pf+BgMBtasWXPNoyunT59m/PjxdO3albFjx9KiRQvi4+Np2bKlufFEE5aW9DudfpuBtWIk0TmU/tOjtI5Ub7r1u4ejVl2wVco5ul4uiiiEaHzMnunWEslMt+LMiVTsvhpOCwwcsA2kS+Rmi51IrbCwEF9fXwAyMjJwdHSsle3uWf8lfXe/yAWccXjlEHYOzWplu0IIUVfM+fyWqzWLBu98zmnUrx+kBQaO6zvQ7um1FltWABwdHcnNzSU3N7fWygpAwNCJZNMSN/JJ2bio1rYrhBCWQAqLaNAKL1/i/KLRtFGzOKu0wmVqNE4ublrH0oSVtQ0ZnScA4JG6GJPRqHEiIYSoPVJYRINVXlbKsaiH6FJxlIs4UTH+B9y92914xUbMb8QzFKj2tDOdYv/2H7WOI4QQtUYKi2iQVJOJpKiJBJTspli1IWfkctp2CdQ6Vo0UFxczePBgBg8efEtT81fH2bUFBzzDAdDHy0RyQojGQwqLaJDiF79AP8MmKlQdR+78N92C7tY6Uo2ZTCa2bdvGtm3bbnlq/uq0u/cFKlQdPUuTOL4/vta3L4QQWpDCIhqchJXvEXJmGQB7e80m8O6HtQ1kYbzadSXZeRAAF36RieSEEI2DFBbRoOzbvJx+B+cCENf2Sfo/+ILGiSyT05CZAARc+oXcsxmaZhFCiNoghUU0GAfjN+G380V0ikqC2/0MmPyu1pEsVpc+gzlk3QMbxcixdXKURQjR8ElhEQ1CxqFE2mx6HFulnH0OA+k7YzGKTl6+11McNAMAv7OrKSowaJxGCCFujbzjC4uXc/o49ivH4kwhh6260y1iFVbW17/it4CAu8dzWvHEhUL2r1+gdRwhhLglUliERTNczKNoyWg8OE+mrg2eT0Vj7+ikdaxb5uDggIODQ50+ht7KijNdJwPQ+vBSjBUVdfp4QghRl6SwCItVUlzImQXhtDdlkktzbCb9iKu7p9axbpmjoyOFhYUUFhbW6tT81fEf+TQGHGmjZpPy64o6fSwhhKhLUliERTJWVHAw6mH8yvZzWbUn/8EVeLXrqnWsBsehmQsHvR8EwG73ZxqnEUKImyeFRVgc1WQi8fMn6VOwnTJVT+Y9X9DRf4DWsRqsTiNfpEzV0708laN7Y7WOI4QQN0UKi7A48d/MITh3NQAp/d+j5+33a5yodpWUlDBixAhGjBhBSUlJnT9eS29fkl2vzAR8+bd5df54QghRF6SwCIuy+6fPCDnxKQDxnV8kaMQ0jRPVPqPRyIYNG9iwYQPGerqistvdVybYC8jfRlbmkXp5TCGEqE1SWITFSIldQ+De1wGI9xjPgEdna5yo8ejYayAHbAOxUkxkbvhE6zhCCGE2KSzCIqQl/U6n32ZgrRhJdA6l//QorSM1OsbgCAB6Zkdz2XBB4zRCCGEeKSxCc2dOpOIW/SgOSikHbAPpFfEtOr1e61iNjv+gB8nU+dBMKSZ13b+1jiOEEGaRwiI0dT7nNOrXD9ICA8f1HWj39FpsbO20jtUo6fR6cvweB8A37Wsqyss0TiSEEDUnhUVopvDyJc4vGk0bNYuzSitcpkbj5OKmdaxGrde907mAM57kkrzlK63jCCFEjUlhEZooLyvlWNRDdKk4ykWcqBj/A+7e7bSO1ejZOTTjiM84AJz2fY5qMmmcSAghakYKi6h3qslE0meTCCjZTbFqQ87I5bTtEqh1rHrj6OiIqqqoqlrnU/NXp8vImZSq1nSpOMrh3Vvr/fGFEOJmSGER9S5+cST9Lm3EqCocueNTugXdrXWkJqWFRxuS3cIAKNn+qcZphBCiZqSwiHqVsOp9Qs4sBWBPrzkEho7XOFHT5DE0EoCAgj84feyAxmmEEOLGpLCIerN389f0S/0nAHFtp9P/wRc0TqSNkpISxowZw5gxY+plav7qtOvel2S7fugUlTObPtYkgxBCmEMKi6gXhxI202PnC+gUlV1u9zFg8ntaR9KM0Whk9erVrF69ut6m5q+O/rZnAfDPXYfhfI5mOYQQoiaksIg6l3loD603TsFWKWefw0D6zFiCopOXntZ63HYfJ3S+OCilHFwn57IIISybfGqIOpVz+ji2K8fiTCGHrbrTLWIVVtY2WscSgKLTcb7XdAA6pn9HWak2X08JIURNSGERdcZwMY+iJaPxJI9MXRs8n4rG3tFJ61jifwQMn0ouzWnFBZI3LdE6jhBCXJMUFlEnSooLOb0gnPamTHJpjs2kH3F199Q6lvgLG1s7jrV/BAC3lC9kIjkhhMUyu7Bs376d++67D29vbxRFITo6+rrjY2NjURTlqiU7O7vKuKioKHx9fbGzsyM4OJhdu3aZG01YCGNFBQejHqZH2X4uq/bkP7gCr3ZdtY4lrsFv5PMUqbZ0NKaTunOd1nGEEKJaZheWwsJCAgICiIqKMmu9I0eOkJWVVbm0atWq8r6VK1cSGRnJnDlz2Lt3LwEBAYSFhXHu3Dlz4wmNqSYTiZ8/SZ+C7ZSpejLv+YKO/gO0jiWuw6WFB/tbjgDA+IdcxVkIYZnMLizDhw/nnXfeYfTo0Wat16pVKzw9PSsX3f/8SuTjjz9m2rRpTJkyBT8/PxYuXIiDgwNLlsh36g1N/DdzCM5dDUBK//foefv9GieyPA4ODhQUFFBQUICDg4PWcQBoPexFTKpCQPEuMg/v1TqOEEJcpd7OYQkMDMTLy4t77rmHP/74o/L2srIy9uzZQ2ho6H9D6XSEhoYSFxdX7bZKS0vJz8+vsgjt7f7pM0JOXPl5bHznFwkaMU3jRJZJURQcHR1xdHREURSt4wDQplNPkh0HApCzRSaSE0JYnjovLF5eXixcuJA1a9awZs0afHx8GDx4MHv3XvlbXF5eHkajEQ8PjyrreXh4XHWey5/mzp2Li4tL5eLj41PXT0PcQErsGgL3vg5AvMd4Bjw6W+NEwly2dz4HQMD5TVw4d0bjNEIIUVWdF5auXbvy5JNP0rdvXwYOHMiSJUsYOHAgn3zyyU1vc9asWRgMhsrl1KlTtZhYmCst6Xc6/TYDa8VIonMo/aebd35TU1NaWsrkyZOZPHkypaWlWsep1L3/UI5adcFWKefIunlaxxFCiCo0+Vlz//79OXbsGADu7u7o9XpycqpODZ6Tk4OnZ/U/g7W1tcXZ2bnKIrRx5kQqbtGP4qCUcsA2kF4R36LT67WOZdEqKipYvnw5y5cvp6KiQus4lRSdjvzeVyaS63pyBSXFhRonEkKI/9KksCQlJeHl5QWAjY0Nffv2JSYmpvJ+k8lETEwMISEhWsQTNXQ+5zTq1w/SAgPH9R1o9/RabGzttI4lbkHg0Elk0xI38knZ8IXWcYQQopKVuSsUFBRUHh0BSE9PJykpCTc3N9q2bcusWbM4c+YMX331FQDz5s2jffv29OjRg5KSEr788kt+/fVXtmzZUrmNyMhIJk2aRFBQEP3792fevHkUFhYyZcqUWniKoi4UXr7E+UWj6aJmcVZphcvUaJxc3LSOJW6RlbUNGZ0ew/PYJ3ikLkYd/bxc90kIYRHMLiyJiYkMGTKk8s+RkZEATJo0iWXLlpGVlcXJkycr7y8rK+PFF1/kzJkzODg40KtXL3755Zcq2xg3bhy5ubnMnj2b7OxsAgMD2bRp01Un4grLUF5WyrGohwioOMpFnKgY/wPe3u20jiVqid/IZyn4ZCHtTKdI3raGgCFjtI4khBAoqqqqWoe4Vfn5+bi4uGAwGOR8ljqmmkwkfvoI/S5tpFi1IfO+FXQLulvrWA1KYWEhzZo1A64csXR0dNQ40dXiFzzJgJwV7Lftjf+sWK3jCCEaKXM+v+VYrzBL/OJI+l3aiFFVOHLHp1JWGql290ZiVBX8S/dxfH+81nGEEEIKi6i5hFXvE3JmKQB7es0hMHS8xolEXfFq15Ukp0EAXPjl5qcgEEKI2iKFRdTI3s1f0y/1nwDEtZ1O/wdf0DhRw+Xg4MC5c+c4d+6cxUzNXx2nu678Nw64tJXcsxnahhFCNHlSWMQNHUrYTI+dL6BTVHa53ceAye9pHalBUxSFli1b0rJlS4uZmr86XfoM5pC1HzaKkWPrZLp+IYS2pLCI68o8tIfWG6dgq5Szz2EgfWYskZ+5NiHFQU8D4Hd2NUUFBo3TCCGaMvnkEdeUc/o4tivH4kwhh6260y1iFVbWNlrHavBKS0uJiIggIiLCoqbmr07A3eM5rXjiQiH71y/QOo4QogmTwiKqZbiYR9GS0XiSx0ldazyfisbe0UnrWI1CRUUFn332GZ999plFTc1fHb2VFWe6Tgag9eFlGC08rxCi8ZLCIq5SUlzI6QXhtDdlkocrVhPX4upe/XWdROPXc8QM8nGkjZpFyq8rtI4jhGiipLCIKkxGIwejxtOjbD8Fqj2GB77H27er1rGEhhydXEn1fhAA293ytZAQQhtSWEQl1WRi18In6VOwjTJVT8Y9X9Cx10CtYwkL0Gnki5SpevzKD3B07zat4wghmiApLKJSwjdzGJD7AwAp/d+j5+33a5xIWIqW3r4ku16Z1fjyb/O0DSOEaJKksAgAdv/0GQNOfApAfOdIgkZM0ziRsDRud//fRHL5sWSfTNM4jRCiqZHCIti/7UcC974OQLzHeAY8OkfjRMISdew1kAO2gVgpJjLWf6R1HCFEEyOFpYk7lryDDr/OwFoxkugcSv/pUVpHavTs7e1JT08nPT0de3t7reOYxRgcAUCP7GguGy5onEYI0ZRIYWnCzpw4RPO1j+ColHDANpBeEd+i0+u1jtXo6XQ6fH198fX1RdfAZg32H/Qgmbo2OCnFpK6br3UcIUQT0rDeLUWtuXDuDOrXo2mBgeP6DrR7ei02tnZaxxIWTqfXk+M3FYB2aV9RUV6mcSIhRFMhhaUJKiowkPdFOG3ULM4qrXCZGo2Ti5vWsZqMsrIyXn75ZV5++WXKyhreB36ve6dzAWe8yCV569daxxFCNBFSWJqY8rJS0qIeokvFUS7iRMX4H3D3bqd1rCalvLycDz/8kA8//JDy8nKt45jNzqEZR3zGAeC0dyGqyaRxIiFEUyCFpQlRTSaSPptEQPEuilUbckYup22XQK1jiQaoy8iZlKrWdKk4ypHdv2gdRwjRBEhhaULiF0fS79JGjKrCkTs+pVvQ3VpHEg1UC482JLuFAVC8/V8apxFCNAVSWJqIhFXvE3JmKQB7es0hMHS8xolEQ+cxNBKAgII/OHMiVeM0QojGTgpLE7B389f0S/0nAHFtp9P/wRc0TiQag3bd+5Js1w+donJ6g0wkJ4SoW1JYGrlDCZvpsfMFdIrKLrf7GDD5Pa0jiUZEN/BZAPxz12G4kKtxGiFEYyaFpRHLPLSH1hunYKuUs89hIH1mLEFpYBOVCcvW8/b7OKHzxUEp5eB/5mkdRwjRiMmnVyOVc/o4tivH4kwhh6260y1iFVbWNlrHElyZmv/AgQMcOHCgwU3N/1eKTsf5XlculNkx/TvKSks0TiSEaKyksDRChot5FC0ZjSd5nNS1xvOpaOwdnbSOJf6PTqejR48e9OjRo8FNzV+dgOFPkEtzWnGB5E1LtI4jhGikGv67paiipLiQ0wvCaW/KJA9XrCauxdXdU+tYohGzsbXjuO8jALilLJKJ5IQQdUIKSyNiMho5GDWeHmX7KVDtMTzwPd6+XbWOJf6irKyMN954gzfeeKNBTs1fne73PU+RaktH4wlSd67TOo4QohGSwtJIqCYTuxY+SZ+CbZSpejLu+YKOvQZqHUtUo7y8nDfffJM333yzQU7NXx2XFh7sbzkCAOMfchVnIUTtk8LSSCR8M4cBuT8AkNL/PXrefr/GiURT4z0sEpOqEFCcQObhvVrHEUI0MlJYGoHdP33GgBOfAhDfOZKgEdM0TiSaIp9O/iQ7hgCQveUTjdMIIRobswvL9u3bue+++/D29kZRFKKjo687/scff+See+6hZcuWODs7ExISwubNm6uMeeONN1AUpcrSrVs3c6M1Sfu3/Ujg3tcBiPcYz4BH52icSDRltnc+D0DA+Y1cOHdG4zRCiMbE7MJSWFhIQEAAUVFRNRq/fft27rnnHjZs2MCePXsYMmQI9913H/v27asyrkePHmRlZVUuO3bsMDdak3MseQcdfp2BtWIk0elu+k+v2X8TIepK9/5DSbPqjJ1SzpF1clFEIUTtsTJ3heHDhzN8+PAaj583b16VP//zn//kp59+4j//+Q+9e/f+bxArKzw95ee3NXXmxCGar30ER6WEA7aB+Ed8g06v1zqWaOIUnQ5D7ydh90t0ObmCkuI52Nk7ah1LCNEI1Ps5LCaTicuXL+Pm5lbl9rS0NLy9venQoQOPPvooJ0+evOY2SktLyc/Pr7I0JRfOnUH9ejQtMHBc3552T6/F1s5B61hCABBwz0SycacFBlI2LNI6jhCikaj3wvLhhx9SUFDA2LFjK28LDg5m2bJlbNq0iQULFpCens4dd9zB5cuXq93G3LlzcXFxqVx8fHzqK77migoM5H0RThs1iyxa4jL1J5xc3G68orAYdnZ27Nq1i127dmFnZ6d1nFpnbWNLRqcJALRK/VImkhNC1ApFVVX1pldWFNauXUt4eHiNxn/33XdMmzaNn376idDQ0GuOu3TpEu3atePjjz9m6tSpV91fWlpKaWlp5Z/z8/Px8fHBYDDg7Oxs9vNoKMrLSjn4yUgCindxiWbkP7Ketl0CtY4lxFXyL51H90kPminFpAxaTK8hD2kdSQhhgfLz83FxcanR53e9HWFZsWIFTzzxBKtWrbpuWQFwdXWlS5cuHDt2rNr7bW1tcXZ2rrI0dqrJxL7PJhNQvIti1YbsEculrAiL5ezaggOeowBQ4mUiOSHErauXwvL9998zZcoUvv/+e0aMGHHD8QUFBRw/fhwvL696SNcwxC95kf6XNmBUFY7c8Snd+l2/9AnLVVZWxgcffMAHH3zQaKbmr07b4ZEYVQX/0n0c3x+vdRwhRANndmEpKCggKSmJpKQkANLT00lKSqo8SXbWrFlMnDixcvx3333HxIkT+eijjwgODiY7O5vs7GwMBkPlmJdeeolt27aRkZHBzp07GT16NHq9nvHjx9/i02scElZ9QMjpK1fB3dNrDoGhsl8asvLycl555RVeeeWVRjM1f3W8fbuS5DQIgAu/yERyQohbY3ZhSUxMpHfv3pU/SY6MjKR3797Mnj0bgKysrCq/8Pniiy+oqKggIiICLy+vyuX555+vHHP69GnGjx9P165dGTt2LC1atCA+Pp6WLVve6vNr8PZt+Yag1H8AENd2Ov0ffEHjRELUXLPB/zeR3KWt5J7N0DaMEKJBu6WTbi2FOSftNCSHE7bgu+ER7JRydrndR79nvkLRydUUGrrCwkKaNWsGXDli6ejYuOcpOfSPELqXHySu9WRCpslkckKI/7LIk26FeTIP7cFr42TslHL2OQykz4wlUlZEg1Qc9DQAfmd+oKjAcIPRQghRPfkEtEDnzqRju3IsLhRy2Ko73SJWYWVto3UsIW5KwN3jOa144kIh+9cv1DqOEKKBksJiYQwX8yhcHI4neZzUtcbzqWjsHZ20jiXETdNbWXGm62QAWh9eirGiQttAQogGSQqLBSktKeL0gtG0N2WQhytWE9fi6i7XVxINX88RM8jHkTZqFim/rtA6jhCiAZLCYiFMRiOp8x+mR1kKBao9hge+x9u3q9axRB2ws7Pjt99+47fffmuUU/NXx9HJlVTvBwGw3b1A4zRCiIZICosFUE0mdi18kj4F2yhT9WTc8wUdew3UOpaoI3q9nsGDBzN48GD0TegK2x1HRFKu6vErP8DRvdu0jiOEaGCksFiAhG/mMCD3BwBS+r9Hz9vv1ziRELWvVev2JLneDcDl3+ZpG0YI0eBIYdHY7p8+Y8CJTwGI7xxJ0IhpGicSda28vJyoqCiioqIa9Uy31XG7+8rEhwH5sWSfTNM4jRCiIZHCoqH9234kcO/rAMR7jGfAo3M0TiTqQ1lZGc888wzPPPNMo76WUHU69hrIAdtArBQTGes/0jqOEKIBkcKikWPJO+jw6wysFSOJTnfTf3qU1pGEqBfG4BkA9MiO5rLhgsZphBANhRQWDZw5cYjmax/BUSnhgG0g/hHfoGtCJ1+Kps1/0BgydW1wUopJXTdf6zhCiAZCCks9u3DuDOrXo2mBgeP69rR7ei22dg5axxKi3uj0erK7Pw5Au7SvqChvWl+LCSFujhSWelRUYCDvi3DaqFlk0RKXqT/h5OKmdSwh6l3AiCe5iDNe5JK89Wut4wghGgApLPWkvKyUtKiH6FJxlEs0o/yR1bh7t9M6lhCasHNoxmGfsQA47V2IajJpnEgIYemksNQD1WRi32eTCSjeRbFqQ/aI5bTtEqh1LCE01XnETEpVa7pUHOXI7l+0jiOEsHBSWOpB/JIX6X9pA0ZV4cjt/6Jbv1CtIwkN2drasm7dOtatW4etra3WcTTj7ulDsttQAIq2f6pxGiGEpZPCUscSVn1AyOklAOzxn03gPY9onEhozcrKihEjRjBixAisrKy0jqOpVkMjAQgs2MGZE6kapxFCWDIpLHVo35ZvCEr9BwBxPtPo/1CkxomEsCy+3YNIseuHTlE5vfFjreMIISyYFJY6cjhhC93/mIleUdnldh8DpryvdSRhIcrLy1m2bBnLli1rclPzV0cZ+CwA/uf+g+FCrsZphBCWSgpLHcg8tAevjZOxU8pJcgihz4wlKDrZ1eKKsrIypkyZwpQpU5rc1PzV6Xn7fZzQ+eKglHJwnZzLIoSonnyK1rJzZ9KxXTkWFwo5YtWNrhE/YGVto3UsISyWotNxvteVi352PPENZaUlGicSQlgiKSy1yHAxj8LF4XiSx0lda1o9GY29o5PWsYSweL2GPU4errTiAimbl2odRwhhgaSw1JLSkiJOLxhNe1MGebhiNXEtzVt6aR1LiAbB1s6BY76PAtA8+QuZSE4IcRUpLLXAZDRyYP54epSlUKDaY3jge7x9u2odS4gGpdvI5yhWbehoPEFq3Hqt4wghLIwUllukmkzs+vwp+hbEUqbqybjnCzr2Gqh1LCEaHFd3T1JajgTAuOPfGqcRQlgaKSy3KOHbNxhwbhUAKf3fo+ft92ucSIiGy3tYJCZVIaA4gcwjSVrHEUJYECkstyDx5wUMOP4vAOI7RxI0YprGiURDYGtry6pVq1i1alWTnpq/Oj6d/El2DAEge/NHGqcRQliSpj0v+C3Yv30tAXv+HygQ7zGeAY/O0TqSaCCsrKwYM2aM1jEslu0dz8HmnQSc38iFc2dwa9Va60hCCAsgR1huwrHkHXSIeQprxUii0930nx6ldSQhGo3uwWGkWXXGTinnyLp/aR1HCGEhpLCY6cyJQ7iufRRHpYQDtoH4R3yDTq/XOpZoQCoqKvjhhx/44YcfqKio0DqOxVF0OgyB0wHocnIFJcWFGicSQlgCKSxmuHDuDKavH8CdSxzXt6fd02uxtXPQOpZoYEpLSxk7dixjx46ltLRU6zgWKWDoJLJxpwUGUjYs0jqOEMICmF1Ytm/fzn333Ye3tzeKohAdHX3DdWJjY+nTpw+2trZ06tSJZcuWXTUmKioKX19f7OzsCA4OZteuXeZGq1NFBQbyvgjHRz1LFi1xmfoTTi5uWscSolGytrElo9MEAFqlfikTyQkhzC8shYWFBAQEEBVVs/M20tPTGTFiBEOGDCEpKYmZM2fyxBNPsHnz5soxK1euJDIykjlz5rB3714CAgIICwvj3Llz5sarExXlZaRFjaFLxVEu0YzyR1bj7t1O61hCNGp+I5+lQLXH13SK/dt+1DqOEEJjiqqq6k2vrCisXbuW8PDwa4559dVXWb9+PQcOHKi87eGHH+bSpUts2rQJgODgYPr168f8+fMBMJlM+Pj48Oyzz/Laa6/dMEd+fj4uLi4YDAacnZ1v9ulUSzWZ2P3po/S/tIFi1YbMkd/TrV9orT6GaFoKCwtp1qwZAAUFBTg6OmqcyHLFL3iSATkr2G/bG/9ZsVrHEULUMnM+v+v8HJa4uDhCQ6t+wIeFhREXFwdAWVkZe/bsqTJGp9MRGhpaOeavSktLyc/Pr7LUlfglL9L/0gaMqsKR2/8lZUWIetR2eCRGVcG/dB8nDiRoHUeIJkk1mUj49yQSVr2vaY46LyzZ2dl4eHhUuc3Dw4P8/HyKi4vJy8vDaDRWOyY7O7vabc6dOxcXF5fKxcfHp06yH90bS8jpJQDs8Z9N4D2P1MnjCCGq5+3blSSnQQCc3/qxxmmEaJril71K8PloglL/SebhvZrlaJC/Epo1axYGg6FyOXXqVJ08Tpc+g0no/jfi2j5J/4ci6+QxhBDX12zw8wAEXNpK3tlMjdMI0bTsWv0xISe/ACCxx99o162PZlnqfKZbT09PcnJyqtyWk5ODs7Mz9vb26PV69Hp9tWM8PT2r3aatrW29TWkePO7Venkc0XTY2NiwdOnSyn8X19c16C4Obfaje/lB0tZ/jPs0mUxOiPqQ9Mv39N3/FigQ13oKIWNf0TRPnR9hCQkJISYmpsptW7duJSTkyvVCbGxs6Nu3b5UxJpOJmJiYyjFCNCbW1tZMnjyZyZMnY21trXWcBqEk6CkAup9ZTVGBQeM0QjR+hxNj6Pr7c+gVlV2u9zJgqvZfyZpdWAoKCkhKSiIpKQm48rPlpKQkTp48CVz5umbixImV45966ilOnDjBK6+8wuHDh/nss89YtWoVL7zwQuWYyMhIFi1axPLlyzl06BAzZsygsLCQKVOm3OLTE0I0Br3ufpQzigeuFLB//UKt4wjRqJ08moTHuknYK2Uk2/Wj99PLUHTan0Fi9ldCiYmJDBkypPLPkZFXzu2YNGkSy5YtIysrq7K8ALRv357169fzwgsv8K9//Ys2bdrw5ZdfEhYWVjlm3Lhx5ObmMnv2bLKzswkMDGTTpk1XnYgrRGNQUVFROQ9RWFgYVlZyDdIb0VtZcarLZFofeY/Wh5diMr4kl8QQog7knc3E+ruHaM5ljlp1ofMza7C2sYyryt/SPCyWoi7nYRGitsk8LDen8PIljB/54Uwh+wZG0XvoY1pHEqJRuWy4wLlP76KjMZ3TihcOM2Lq/GrpFjUPixBC1AZHJ1dSvR4EwDZRvhYSojaVlZaQ+dloOhrTOY8LyoS1dV5WzCWFRQjRYHQcGUm5qsevbD9p+7ZrHUeIRsFkNJIy/xF6liZRqNpxIfxbWnfornWsq0hhEUI0GK1atyfZ5S4ADL/O0zaMEI3Eri8iCLocQ7mq58RdC+gceIfWkaolhUUI0aC43n3lF4aB+b+RfTJN4zRCNGzx377FgJzvAUjq8w7+gx7QONG1SWERQjQonQJuI9UmACvFRMaGT7SOI0SDlbh+EQPSPgIgvsNz9Bv1tMaJrk8KixCiwakYcOWNtUfWj1w2XNA4jRANz4EdP9Nr15WZ3ONbjiH4sTc1TnRjUliEqGc2NjbMnz+f+fPny9T8N8l/0BhO6lrjpBSTuj5K6zhCNCjH98fju3U6NoqRvc0G0f+pzy1iYrgbkRmrhKhn1tbWREREaB2jQdPp9WR1n0rb1Ldod3Q5FeWvYmUt5U+IGzmbcQTnNQ/TTCkm1cYfv4jvG8wkjJZfqYQQohoBI57kIs54kUvy1m+1jiOExbuUl03FV6NpyUXSdb60mRGNnX3DmbhSCosQ9cxoNBIbG0tsbCxGo1HrOA2WnUMzDvuMBaDZ3gWoJpPGiYSwXMWFl8leGE5b0xmyccdxajQuzd21jmUWKSxC1LOSkhKGDBnCkCFDKCkp0TpOg9Z5xExKVWu6VhzhSGLMjVcQogmqKC/jcNRYulUcwoAjpeNW0ap1e61jmU0KixCiwXL39CHZbSgARdv+pXEaISyPajKxZ8FUehftpES15uzwpbTr3lfrWDdFCosQokFrNfTKFeMDC3Zw5kSqxmmEsCzxy14j+MLPGFWFgwM/oXtwmNaRbpoUFiFEg+bbPYgUu37oFJXTGz/WOo4QFmPXmk8IOfk5AIk9/kafsAkaJ7o1UliEEA2eMvDKz8T9z/0Hw4VcjdMIob2kmBX0SXkLgLjWUwge+4rGiW6dFBYhRIPX8/ZRpOt8cVBKObjuU63jCKGpw4kxdN3+LFaKiV2u9zJgauM48iiFRQjR4Ck6Hbn+TwDQ8cQ3lJXKr69E03TyaBIe6yZhr5SRbNeP3k8vaxCz2NZE43gWQjQg1tbWvP/++7z//vtYW1trHafRCBg+lTxcacUFUjYv1TqOEPUu72wm1t89RHMuc9SqC52fWYO1ja3WsWqNTM0vRD2zsbHh5Zdf1jpGo2Nr58Be3/G4ZyzANXkR6sgnG83fLIW4kcuGCxgWj6IjuZxWvHCfHo1DMxetY9Uq+b9ZCNFodB85k2LVhk7G46TGrdc6jhD1oqy0hMzPRtPRmM55XFAmrMWtVWutY9U6KSxC1DOj0cju3bvZvXu3TM1fy1zdPUlxvxeAih3zNU4jRN0zGY2kzH+EnqVJFKp2XAj/ltYdumsdq05IYRGinpWUlNC/f3/69+8vU/PXAe/hL2FSFQKL48k8kqR1HCHq1K4vIgi6HEO5qufEXQvoHHiH1pHqjBQWIUSj4tPJn2THEACytzSOn3MKUZ34b99iQM73ACT1eQf/QQ9onKhuSWERQjQ6tnc8B0BA3gYunDujcRohal/i+kUMSPsIgLgOz9Fv1NMaJ6p7UliEEI1O9+Aw0qw6Y6eUc2SdXBRRNC4HdvxMr12vApDQ8iEGPPamxonqhxQWIUSjo+h0GAKnA9Dl5ApKigs1TiRE7Ti+Px7frdOxUYzsbXYnQU9+3mR+vt80nqUQoskJGDqJbNxpgYGUDYu0jiPELTubcQTnNQ/TTCkm1cYfv4gV6K2aznRqUliEEI2StY0tGZ0eA6BV6peoJpPGiYS4eZfysqn4ajQtuUi6rh1tZkRjZ++odax6JYVFiHpmbW3NnDlzmDNnjkzNX8f8Rj5HoWqHr+kU+7f9qHUcIW5KceFlsheG09Z0hhxa4PD4Wlyau2sdq941nWNJQlgIGxsb3njjDa1jNAnOri2I9xjFgHMrUeKjYMhDWkcSwiwV5WUcjhpL74pD5ONI8bhV+LbpqHUsTcgRFiFEo9b23hcxqgr+pXs5cSBB6zhC1JhqMrFnwVR6F+2kVLXmzPCl+HYP0jqWZm6qsERFReHr64udnR3BwcHs2rXrmmMHDx6MoihXLSNGjKgcM3ny5KvuHzZs2M1EE8LimUwmUlNTSU1NxSTnVdQ5b9+uJDvdCcD5Xz7ROI0QNRe/7DWCL/yMUVVIHfgJ3YPDtI6kKbMLy8qVK4mMjGTOnDns3buXgIAAwsLCOHfuXLXjf/zxR7KysiqXAwcOoNfrGTNmTJVxw4YNqzLu+++/v7lnJISFKy4upmfPnvTs2ZPi4mKt4zQJjoNnAhBwcQt5ZzO1DSNEDexa8wkhJz8HILHH3+gTNkHjRNozu7B8/PHHTJs2jSlTpuDn58fChQtxcHBgyZIl1Y53c3PD09Ozctm6dSsODg5XFRZbW9sq45o3b35zz0gIIf6ia9BdHLb2w0YxkrZejrIIy5YUs4I+KW8BENd6CsFjX9E4kWUwq7CUlZWxZ88eQkND/7sBnY7Q0FDi4uJqtI3Fixfz8MMP4+hY9edYsbGxtGrViq5duzJjxgzOnz9/zW2UlpaSn59fZRFCiOspDnoKgO5nfqCowKBxGiGqdzgxhq7bn8VKMbHL9V4GTJXrYf3JrMKSl5eH0WjEw8Ojyu0eHh5kZ2ffcP1du3Zx4MABnnjiiSq3Dxs2jK+++oqYmBjee+89tm3bxvDhwzEajdVuZ+7cubi4uFQuPj4+5jwNIUQT1OvuRzmjeOBKAfs3fK51HCGucvJoEh7rJmGvlJFs14/eTy9rMrPY1kS97onFixfj7+9P//79q9z+8MMPc//99+Pv7094eDjr1q1j9+7dxMbGVrudWbNmYTAYKpdTp07VQ3ohREOmt7LiVJfJAHgfWorpGn8hEkILeWczsfp+DM25zFGrLnR+Zg3WNrZax7IoZhUWd3d39Ho9OTk5VW7PycnB09PzuusWFhayYsUKpk6desPH6dChA+7u7hw7dqza+21tbXF2dq6yCCHEjfiPfJp8HPFRz5Ly60qt4wgBwGXDBQyLw/FWz3Fa8cJ9ejQOzVy0jmVxzCosNjY29O3bl5iYmMrbTCYTMTExhISEXHfdH374gdLSUh577LEbPs7p06c5f/48Xl5e5sQTQojrcnRyJdXrQQBsdn+mcRohoKy0hMzPRtPReILzuKBMWItbq9Zax7JIZn8lFBkZyaJFi1i+fDmHDh1ixowZFBYWMmXKFAAmTpzIrFmzrlpv8eLFhIeH06JFiyq3FxQU8PLLLxMfH09GRgYxMTGMGjWKTp06ERbWtH9zLhona2trXnrpJV566SWZml8DHUbMpFzV41e2n7R927WOI5owk9FIStSj9CxNolC140L4t7Tu0F3rWBbL7Kn5x40bR25uLrNnzyY7O5vAwEA2bdpUeSLuyZMn0f3lJKEjR46wY8cOtmzZctX29Ho9KSkpLF++nEuXLuHt7c3QoUN5++23sbWV7+9E42NjY8MHH3ygdYwmy6NNRxJd7iIofyuGX+dB7zu1jiSaqF2LnmVA/i+Uq3pO3LUA/8A7tI5k0RRVVVWtQ9yq/Px8XFxcMBgMcj6LEOKGjiX/Qae191Kh6sh7YjeePp20jiSamPjv3mbA0Q8B2N17Lv1GPa1xIm2Y8/ktv5cSop6ZTCYyMjLIyMiQqfk10ingNlJtArBSTGSsl3kuRP3as/7LyrIS1+G5JltWzCWFRYh6VlxcTPv27Wnfvr1Mza+h8uArHxI9sn6kIP+ixmlEU3Hgj//gv+tVABJaPsSAx97UOFHDIYVFCNEk9Ro8hpO61jgpxRxYN1/rOKIJOL4/nnZbpmGjVLC32Z0EPfm5TAxnBtlTQogmSafXk9X9cQDapn1FRXmZxolEY5aVeQTnNQ/jpBSTauOPX8QK9FZm/+6lSZPCIoRosgJGPMVFnPBWz5G89Vut44hG6lJeNuXLR9OSi6Tr2tFmRjR29o43XlFUIYVFCNFk2Tk040ibsQA027tQ4zSiMSouvEz2wnDams6QQwscHl+LS3N3rWM1SFJYhBBNWqeRL1CmWtG14jCHd23VOo5oRCrKyzgcNZZuFYfIx5HicavwaNNR61gNlhQWIUST5u7pQ1LzoQAUbftU4zSisVBNJvYsmErvop2UqtacGb4U3+5BWsdq0OSMHyHqmZWVFU8//XTlvwvttQp7EVZuIKDgd86cOCTTo4tbFr/sNUIu/IxJVTg48CN6B8ulZm6VvFsKUc9sbW2JiorSOob4H77dg0ixC6JXSSKnNn5E64gvtY4kGrBdaz4h5OTnAOz2m0Vw2CSNEzUO8pWQEEIAysBnAOh17mcMF3I1TiMaqqSYFfRJeQuAuNaTCR73qsaJGg8pLELUM1VVyc3NJTc3l0ZwKa9Go+fto0jX+eKglHJonZzLIsx3ODGGrtufxUoxsdt1OAOmfqJ1pEZFCosQ9ayoqIhWrVrRqlUrioqKtI4j/o+i05Hr/wQAHU58Q1lpicaJRENy8mgSHusmYa+UkWzXj8Cnl8sstrVM9qYQQvyfgOFTycOVVlwgZfMyreOIBiLvbCZW34+hOZdJs+pMp4jVWNvYah2r0ZHCIoQQ/8fWzoE03/EAuCZ/gSpX0xY3cNlwAcPicLzVc5xWvHCbFo2jk6vWsRolKSxCCPE/uo+cSbFqQyfjcQ7GbdQ6jrBgZaUlZH42mo7GE5zHBWXCGlp4tNE6VqMlhUUIIf6Hq7snKe73AlC+Q06+FdUzGY2kRD1Kz9IkilRbLoz6htYdemgdq1GTwiKEEH/hPSwSk6oQWBxP5pEkreMIC7Rr0bME5f9Cuarn2JAFdO59p9aRGj0pLEII8Rc+nQNIdgwBIHvLxxqnEZYm/ru3GZB95ereSX3eodfgBzVO1DTITLdC1DMrKysmTZpU+e/CMtne8Rxs3klA3gYunDuDW6vWWkcSFmDP+i8ZcPRDAOI6PEfIqKc1TtR0KGojmLkqPz8fFxcXDAYDzs7OWscRQjQCqsnEsX/0o7PxGHHtniJkyntaRxIaO/DHf+iyZTI2SgUJLR+i/4xFMtfKLTLn81v2tBBCVEPR6TD0fhKALpnfU1JcqHEioaXj++Npt2UaNkoFe5vdSdCTn0tZqWeyt4WoZ6qqUlhYSGFhoUzNb+EChk4ihxa0wMD+jXJBxKYqK/MIzmsexkkpJtXGH7+IFejl69x6J4VFiHpWVFREs2bNaNasmUzNb+GsbWxJ7zQBgJYHvpSJ5JqgS3nZlC1/gJZcJF3XjjYzorGzd9Q6VpMkhUUIIa6j+4hnKVTt8DWdZP/2tVrHEfWopKiA7M9H0850mhxa4PD4Wlyau2sdq8mSwiKEENfh0tyd/R6jAFDi5mucRtSXivIyDs0fQ7fyg+TjSPG4VXi06ah1rCZNCosQQtxA2+GRGFUF/9K9pKcmaB1H1DHVZGLPwifoXbSTUtWaM8OX4ts9SOtYTZ4UFiGEuAHv9t1Idroyk2ne1k80TiPqWvzyWQSf/wmTqnBw4Ed0Dw7TOpJACosQQtSIw+DnAQi4uIW8s5kapxF1ZdeaeYRkLgRgt98seodN0jiR+JMUFiGEqIFuQXdz2NoPG8VI2no5ytIYJf+6gj4pbwIQ13oyweNe1TiR+F9SWISoZ3q9noceeoiHHnoIvV6vdRxhhqK+VyaS637mB4oLL2ucRtSmI4m/0mXbs1gpJna7DmfAVCmlluamCktUVBS+vr7Y2dkRHBzMrl27rjl22bJlKIpSZbGzs6syRlVVZs+ejZeXF/b29oSGhpKWlnYz0YSweHZ2dvzwww/88MMPV/2/ICxbQOhjnFU8cKWAlPULtI4jasmptGRarZuIvVJGsl0/Ap9eLrPYWiCz/4usXLmSyMhI5syZw969ewkICCAsLIxz585dcx1nZ2eysrIql8zMqt//vv/++3z66acsXLiQhIQEHB0dCQsLo6SkxPxnJIQQdURvZcXJLlfOafA+tBST0ahxInGr8rJPov/uIZpzmTSrznSKWI21ja3WsUQ1zC4sH3/8MdOmTWPKlCn4+fmxcOFCHBwcWLJkyTXXURQFT0/PysXDw6PyPlVVmTdvHq+//jqjRo2iV69efPXVV5w9e5bo6OibelJCCFFX/EdGkI8DPupZUn5dqXUccQsuGy5waVE43uo5TiteuE2LxtHJVetY4hrMKixlZWXs2bOH0NDQ/25ApyM0NJS4uLhrrldQUEC7du3w8fFh1KhRpKamVt6Xnp5OdnZ2lW26uLgQHBx8zW2WlpaSn59fZRGioSgsLKz8erSwUC6o19A4OrmS6vUAANa7P9M4jbhZZaUlZH42mk7G45zHBWXCGlp4tNE6lrgOswpLXl4eRqOxyhESAA8PD7Kzs6tdp2vXrixZsoSffvqJb775BpPJxMCBAzl9+jRA5XrmbHPu3Lm4uLhULj4+PuY8DSGEuCUdRkRSrurpUbaftKTftY4jzGQyGkmJepSepUkUqbZcGPUNrTv00DqWuIE6P6soJCSEiRMnEhgYyKBBg/jxxx9p2bIln3/++U1vc9asWRgMhsrl1KlTtZhYCCGuz6NNR5JdhgBg+HWetmGE2XYtepag/F8oV/UcG7KAzr3v1DqSqAGzCou7uzt6vZ6cnJwqt+fk5ODp6VmjbVhbW9O7d2+OHTsGULmeOdu0tbXF2dm5yiKEEPXJ9e4XAAg0/Er2qWMapxE1Ff/d2wzI/haApN5v02vwgxonEjVlVmGxsbGhb9++xMTEVN5mMpmIiYkhJCSkRtswGo3s378fLy8vANq3b4+np2eVbebn55OQkFDjbQohRH3rFHA7qTa9sFJMZKz/WOs4ogb2rP+SAUc/BCCu/TP0C4/QOJEwh9lfCUVGRrJo0SKWL1/OoUOHmDFjBoWFhUyZMgWAiRMnMmvWrMrxb731Flu2bOHEiRPs3buXxx57jMzMTJ544gngyi+IZs6cyTvvvMPPP//M/v37mThxIt7e3oSHh9fOsxRCiDpQHnzlA88vey0F+Rc1TiOu58Af/8F/15WZaxPcH2TAhLc1TiTMZWXuCuPGjSM3N5fZs2eTnZ1NYGAgmzZtqjxp9uTJk+j+Z8KdixcvMm3aNLKzs2nevDl9+/Zl586d+Pn5VY555ZVXKCwsZPr06Vy6dInbb7+dTZs2yaRaQgiL1mvwGE7+8RZtTWeIXxfFgEde1zqSqMbx/fG02zING6WCvc3uJOipL2RiuAZIUVVV1TrErcrPz8fFxQWDwSDnswiLV1JSwoMPXvnefM2aNVLMG7iEHz4kOPVtziqtaPW3VKysbbSOJP5HVuYRrJaG0ZKLHLTxp8MLm7Gzd9Q6lvg/5nx+S8UUop7Z2dmxfv161q9fL2WlEeh175NcxAlv9Rwpv3yrdRzxPy7lZVO2/AFacpEMXVtaP7VWykoDJoVFCCFugb2jE0fajAXAcc9CjdOIP5UUFZD9+WjamU6TQwvsH4/Gxa2l1rHELZDCIoQQt6jTyBcoU63oWnGYw7t/0TpOk1dRXsah+WPoVn6QfBwpHrcKjzYdtY4lbpEUFiHqWWFhIY6Ojjg6OsrU/I2Eu6cPSc2HAlAU+y+N0zRtqsnEnoVP0LtoJ6WqNaeHLcG3e5DWsUQtkMIihAaKioooKirSOoaoRa3CXgQgoOB3zpw4pHGapit++SyCz/+ESVU4OPAj/AYM0zqSqCVSWIQQohb4dg8ixS4IvaJyauNHWsdpknatmUdI5pXziHb7zaJ32CSNE4naJIVFCCFqiTLwGQB6nfsZw8U8jdM0Lcm/rqBPypsAxLWeTPC4VzVOJGqbFBYhhKglPW8fRbrOFwellEP/kXNZ6suRxF/psu1ZrBQTu12HM2DqJ1pHEnVACosQQtQSRacj1//KZUc6nPiG8rJSjRM1fqfSkmm1biL2ShnJdv0IfHq5zGLbSMl/VSGEqEUBw6eShyutuEDypqVax2nU8rJPov/uIZpzmTSrznSKWI21ja3WsUQdkcIiRD3T6XQMGjSIQYMGVbnulmgcbO0cSPMdD4Br8heoJpPGiRqny4YLXFoUjrd6jtOKF27TonF0ctU6lqhD8m4pRD2zt7cnNjaW2NhY7O3ttY4j6kD3kTMpVm3oZDzOwbiNWsdpdMpKS8j47AE6GY9zHheUCWto4dFG61iijklhEUKIWubq7kmK+70AlO/4VOM0jYvJaCQl6lH8S/dRpNpyYdQ3tO7QQ+tYoh5IYRFCiDrgPSwSk6oQWBzPyaNJWsdpNHYtepag/F8oV/UcG7KAzr3v1DqSqCdSWISoZ4WFhbRs2ZKWLVvK1PyNmE/nAJIdQwDI2vyxxmkah/jv3mFA9pUrYif1fptegx/UOJGoT1JYhNBAXl4eeXkysVhjZ3P7swAE5G3gYm6Wxmkatj0bFtP/yIcAxLV/hn7hERonEvVNCosQQtQRvwHDSNN3wk4p5/C6eVrHabAO/PEf/BNeQaeoJLg/yIAJb2sdSWhACosQQtQRRafDEDgdgC6Z31NSLF8BmuvEgQTabZmGjVLB3mZ3EvTUFzIxXBMl/9WFEKIOBYRNJocWtMDA/o1fah2nQck+mUaz1Q/jpBRz0MYfv4gV6K2stI4lNCKFRQgh6pC1jS3pHR8DoOWBL2UiuRoynM+hdNloWnGBDF1bWj+1Fjt7R61jCQ1JYRFCiDrWfeRzFKp2+JpOsn/7Wq3jWLySogKyFobTznSKHFpg/3g0Lm4ttY4lNCaFRYh6ptPpCAoKIigoSKbmbyJcmruz3+P+K3+Ij9I2jIWrKC/j0PwxdCs/SD6OFI9bhUebjlrHEhZA3i2FqGf29vbs3r2b3bt3y9T8TUjb4S9iVBV6lewhPTVB6zgWSTWZ2LPwCXoX7aRUteb0sCX4dg/SOpawEFJYhBCiHni370ay0x0A5G6dp20YCxW/fBbB53/CpCocHPgRfgOGaR1JWBApLEIIUU8cBs8EIPDiFvKyT2obxsLsWjOPkMyFAOz2e43eYZM0TiQsjRQWIepZUVERvr6++Pr6UlRUpHUcUY+6Bd3NYavu2CgVpK37ROs4FiP51xX0SXkTgDjvSQSPe03jRMISSWERop6pqkpmZiaZmZmoqqp1HFHPioKeAqDb6R8oLryscRrtHUn8lS7bnsVKMbHbZRgDnpindSRhoaSwCCFEPQoIfYyzigfNuUzK+oVax9HUqbRkWq2biL1SRopdPwIjvpJZbMU1yStDCCHqkd7KipNdrpyf4X1oCSajUeNE2sjLPon+u4dozmXSrDrTMWI11ja2WscSFkwKixBC1LOeI54mHwd81LOk/LZK6zj17rLhApcWheOtnuO04onbtGgcnVy1jiUsnBQWIYSoZ82cm5Pq9QAA1rua1kRyZaUlZHz2AJ2Mx7mAM8qEH2nh0UbrWKIBuKnCEhUVha+vL3Z2dgQHB7Nr165rjl20aBF33HEHzZs3p3nz5oSGhl41fvLkySiKUmUZNkx+fy+EaLw6jIikXNXTo2w/aUm/ax2nXpiMRlKiHsW/dB9Fqi3nR31L6w49tI4lGgizC8vKlSuJjIxkzpw57N27l4CAAMLCwjh37ly142NjYxk/fjy//fYbcXFx+Pj4MHToUM6cOVNl3LBhw8jKyqpcvv/++5t7RkJYOEVR8PPzw8/PD0VRtI4jNOLRpiPJLkMAMPw6T9sw9WTXomcJyv+FclXPsSEL6Nz7Tq0jiQZEUc38XWVwcDD9+vVj/vz5AJhMJnx8fHj22Wd57bUb/3beaDTSvHlz5s+fz8SJE4ErR1guXbpEdHS0+c8AyM/Px8XFBYPBgLOz801tQwgh6tux5B10WjuCclXP+Sd24enTSetIdSb+u3cYcPQDAHYH/pN+4REaJxKWwJzPb7OOsJSVlbFnzx5CQ0P/uwGdjtDQUOLi4mq0jaKiIsrLy3Fzc6tye2xsLK1ataJr167MmDGD8+fPX3MbpaWl5OfnV1mEEKKh6RRwO6k2vbBWjGSs/1jrOHVmz4bF9D/yIQBx7Z+RsiJuilmFJS8vD6PRiIeHR5XbPTw8yM7OrtE2Xn31Vby9vauUnmHDhvHVV18RExPDe++9x7Zt2xg+fDjGa/zcb+7cubi4uFQuPj4+5jwNIYSwGOXBVz68/bLXUpB/UeM0te/AH//BP+EVdIpKgvuDDJjwttaRRANVr78Sevfdd1mxYgVr167Fzs6u8vaHH36Y+++/H39/f8LDw1m3bh27d+8mNja22u3MmjULg8FQuZw6daqenoEQt66oqIgePXrQo0cPmZpf0GvwGE7qWuNMEQfWNa5fDJ04kEC7LdOwUSrY2+xOgp76QiaGEzfNrFeOu7s7er2enJycKrfn5OTg6el53XU//PBD3n33XbZs2UKvXr2uO7ZDhw64u7tz7Nixau+3tbXF2dm5yiJEQ6GqKgcPHuTgwYMyNb9Ap9eT1f1xANqmLcdYUaFxotqRfTKNZqsfxkkp5qCNP34RK9BbWWkdSzRgZhUWGxsb+vbtS0xMTOVtJpOJmJgYQkJCrrne+++/z9tvv82mTZsICgq64eOcPn2a8+fP4+XlZU48IYRokHrd+yQXccJbPUfy1q+1jnPLDOdzKF02mlZcIEPXltZPrcXO3lHrWKKBM/vYXGRkJIsWLWL58uUcOnSIGTNmUFhYyJQpUwCYOHEis2bNqhz/3nvv8fe//50lS5bg6+tLdnY22dnZFBQUAFBQUMDLL79MfHw8GRkZxMTEMGrUKDp16kRYWFgtPU0hhLBc9o5OHGkzFgCHPZ9rnObWlBQVkLUwnHamU+TQAvvHo3Fxa6l1LNEImF1Yxo0bx4cffsjs2bMJDAwkKSmJTZs2VZ6Ie/LkSbKysirHL1iwgLKyMh566CG8vLwqlw8/vHLGuF6vJyUlhfvvv58uXbowdepU+vbty++//46trVxXQgjRNHQaOZMy1YpuFYc4vPsXrePcFGNFBYfmj6Vb+UHycaR43Co82nTUOpZoJMyeh8USyTwsoiEpLCykWbNmwJUjjI6OcqhcXLFr3nj6X9rA3mZ30uel/2gdxyyqycSuqCkEn4+mVLXm+PBv8BsgM5aL66uzeViEEELUnZZDIwEIuPw7Z9MPa5zGPPHLZxF8PhqTqnBw4EdSVkStk8IiRD1TFIV27drRrl07mZpfVNHerx8pdkHoFZWTGz/SOk6N7f7xX4RkLrzy736v0TtsksaJRGMkhUWIeubg4EBGRgYZGRk4ODhoHUdYGCXkykRy/jk/Y7iYp3GaG0v+dQW9k98AIM57EsHjbnyJFiFuhhQWIYSwID3vCCdd1w5HpYRD6z7VOs51Hd0bS+dtz2GlmNjtMowBT8zTOpJoxKSwCCGEBVF0OnL9nwCg/fFvKC8r1ThR9U6lJdPy5wk4KKWk2PUjMOIrmcVW1Cl5dQlRz4qLi+nXrx/9+vWjuLhY6zjCAgUMf4I8XPHgPMmblmod5yp52SfRfzeG5uSTZtWZjhGrsbaRaShE3ZLCIkQ9M5lMJCYmkpiYiMlk0jqOsEC2dg6ktXsYANfkL1At6HVSkH+RS4vC8VZzOK144jYtGkcnV61jiSZACosQQligbiNnUqza0Ml4nINxG7WOA0BZaQnpUQ/QyXicCzijTPiRFh5ttI4lmggpLEIIYYGat/Qixf1eAMr/+LfGacBkNJIS9Rj+pXspUm05P+pbWnfooXUs0YRIYRFCCAvlPezKRHKBRXGcPJqkaZaEL58jKH8r5aqeY4M/o3PvOzXNI5oeKSxCCGGhfDoHkOQQAkDW5k80yxH/3TuEZH0DQFLvt+g15CHNsoimSwqLEEJYMOvbnwMgIG89F3OzbjC69u3ZsJj+R65crDaufQT9wp+p9wxCgBQWITTh7u6Ou7u71jFEA+A3YBjH9B2xU8o5vG5evT72gT/+g3/CK+gUlQT3Bxgw4Z16fXwh/pcUFiHqmaOjI7m5ueTm5sqVmsUNKTodlwKfBKBz5gpKigvr5XFPHEig3ZZp2CgV7HW8k6CnFsnEcEJT8uoTQggLFxA2mRxa4M4lUjYtrvPHyz6ZRrPVD+OkFHPQuid+z6xAb2VV548rxPVIYRFCCAtnbWNLesfHAGi5/8s6nUjOcD6H0mWjacUFMnRtaT0jGjt7ORIotCeFRYh6VlxczODBgxk8eLBMzS9qrPvI5yhU7WhvyuTA79F18hglRQVkLQynnekU53DDbspaXNxa1sljCWEuKSxC1DOTycS2bdvYtm2bTM0vasyluTv7Pe4HQI2bX+vbN1ZUcGj+WLqVHyQfRwrHrsLTp1OtP44QN0sKixBCNBBth7+IUVXoVbKH9IO7a227qslE4oKp9C76g1LVmtNhi2nv16/Wti9EbZDCIoQQDYR3+24kO90BQO6Wj2ttu/HLZxF8PhqTqnBw4Ef4hQyvtW0LUVuksAghRAPiMOh5AAIvbiEv++Qtb2/3j/8iJHPhlX/3e43eYZNueZtC1AUpLEII0YB06xfKYavu2CgVpK27ten6k39dQe/kNwCI855E8LjXaiGhEHVDCosQQjQwRX2vTCTX7fQPFBdevqltHN0bS+dtz2GlmNjtMowBT8yrxYRC1D4pLEJowMHBAQcHB61jiAYq4J4JnFU8aM5lUtYvNHv9U2nJtPx5Ag5KKSl2/QiM+EpmsRUWT16hQtQzR0dHCgsLKSwslKn5xU3RW1lxsvNEALwPLcFkNNZ43bzsk+i/G0Nz8kmz6kzHiNVY29jWVVQhao0UFiGEaIB6jowgHwd81LOk/LaqRusU5F/k0qJwvNUcTiueuE2LxtHJtW6DClFLpLAIIUQD1My5OaleDwBgveuzG44vKy0hPeoBOhmPcwFnlAk/0sKjTV3HFKLWSGERop6VlJQwYsQIRowYQUlJidZxRAPWYUQk5aqeHmUpHEvecc1xJqORlKjH8C/dS5Fqy/lR39K6Q496TCrErZPCIkQ9MxqNbNiwgQ0bNmA049wDIf7Ko01Hkl2GAHAp5to/cU748jmC8rdSruo5NvgzOve+s74iClFrpLAIIUQD5nr3CwAEGH4j5/Txq+6P//4fhGR9A0BS77foNeShes0nRG2RwiKEEA1Yp4DbSbXphbVi5MT6qtP179mwmP6HPwAgrn0E/cKf0SKiELXipgpLVFQUvr6+2NnZERwczK5du647/ocffqBbt27Y2dnh7+/Phg0bqtyvqiqzZ8/Gy8sLe3t7QkNDSUtLu5loQgjR5JT3fxqAHlk/UpB/EYDUP9bjn/AKOkUlwf0BBkx4R8uIQtwyswvLypUriYyMZM6cOezdu5eAgADCwsI4d+5cteN37tzJ+PHjmTp1Kvv27SM8PJzw8HAOHDhQOeb999/n008/ZeHChSQkJODo6EhYWJickCiEEDXQa8hYTineOFPEgfWfkZ6agM/WJ7BRKtjreCdBTy2SieFEg6eoqqqas0JwcDD9+vVj/vz5AJhMJnx8fHj22Wd57bWrr0Mxbtw4CgsLWbduXeVtAwYMIDAwkIULF6KqKt7e3rz44ou89NJLABgMBjw8PFi2bBkPP/zwDTPl5+fj4uKCwWDA2dnZnKcjRL0rLCykWbNmABQUFMjkcaJWJKz6gOCD75BNS3QYacUFDlr3pEPkFuzs5TUmLJM5n99mVe6ysjL27NlDaGjofzeg0xEaGkpcXFy168TFxVUZDxAWFlY5Pj09nezs7CpjXFxcCA4OvuY2S0tLyc/Pr7IIIURT1mvEU1zECU9yacUFMnRtaT0jWsqKaDTMKix5eXkYjUY8PDyq3O7h4UF2dna162RnZ193/J//NGebc+fOxcXFpXLx8fEx52kIoSlHR0dUVUVVVTm6ImqNvaMTR9qMBeAcbthNWYuLW0uNUwlRexrkl5qzZs3CYDBULqdOndI6khBCaC7w0beJ7/IyFZM24unTSes4QtQqK3MGu7u7o9frycnJqXJ7Tk4Onp6e1a7j6el53fF//jMnJwcvL68qYwIDA6vdpq2tLba2crEuIYT4X3b2jgx45HWtYwhRJ8w6wmJjY0Pfvn2JiYmpvM1kMhETE0NISEi164SEhFQZD7B169bK8e3bt8fT07PKmPz8fBISEq65TSGEEEI0LWYdYQGIjIxk0qRJBAUF0b9/f+bNm0dhYSFTpkwBYOLEibRu3Zq5c+cC8PzzzzNo0CA++ugjRowYwYoVK0hMTOSLL74AQFEUZs6cyTvvvEPnzp1p3749f//73/H29iY8PLz2nqkQQgghGiyzC8u4cePIzc1l9uzZZGdnExgYyKZNmypPmj158iS6//m9/8CBA/nuu+94/fXX+dvf/kbnzp2Jjo6mZ8+elWNeeeUVCgsLmT59OpcuXeL2229n06ZN2NnZ1cJTFEIIIURDZ/Y8LJZI5mERQgghGp46m4dFCCGEEEILUliEEEIIYfGksAghhBDC4klhEUIIIYTFk8IihBBCCIsnhUUIIYQQFk8KixBCCCEsnhQWIYQQQlg8KSxCCCGEsHhmT81vif6crDc/P1/jJEIIIYSoqT8/t2sy6X6jKCyXL18GwMfHR+MkQgghhDDX5cuXcXFxue6YRnEtIZPJxNmzZ3FyckJRlFrddn5+Pj4+Ppw6dUquU3QDsq9qTvZVzcm+Mo/sr5qTfVVzdbWvVFXl8uXLeHt7V7lwcnUaxREWnU5HmzZt6vQxnJ2d5QVdQ7Kvak72Vc3JvjKP7K+ak31Vc3Wxr250ZOVPctKtEEIIISyeFBYhhBBCWDwpLDdga2vLnDlzsLW11TqKxZN9VXOyr2pO9pV5ZH/VnOyrmrOEfdUoTroVQgghROMmR1iEEEIIYfGksAghhBDC4klhEUIIIYTFk8IihBBCCIsnhQWIiorC19cXOzs7goOD2bVr13XH//DDD3Tr1g07Ozv8/f3ZsGFDPSXVnjn7atmyZSiKUmWxs7Orx7Ta2b59O/fddx/e3t4oikJ0dPQN14mNjaVPnz7Y2trSqVMnli1bVuc5LYG5+yo2Nvaq15WiKGRnZ9dPYA3NnTuXfv364eTkRKtWrQgPD+fIkSM3XK8pvmfdzL5qqu9ZCxYsoFevXpWTwoWEhLBx48brrqPFa6rJF5aVK1cSGRnJnDlz2Lt3LwEBAYSFhXHu3Llqx+/cuZPx48czdepU9u3bR3h4OOHh4Rw4cKCek9c/c/cVXJkVMSsrq3LJzMysx8TaKSwsJCAggKioqBqNT09PZ8SIEQwZMoSkpCRmzpzJE088webNm+s4qfbM3Vd/OnLkSJXXVqtWreoooeXYtm0bERERxMfHs3XrVsrLyxk6dCiFhYXXXKepvmfdzL6Cpvme1aZNG95991327NlDYmIid911F6NGjSI1NbXa8Zq9ptQmrn///mpERETln41Go+rt7a3OnTu32vFjx45VR4wYUeW24OBg9cknn6zTnJbA3H21dOlS1cXFpZ7SWS5AXbt27XXHvPLKK2qPHj2q3DZu3Dg1LCysDpNZnprsq99++00F1IsXL9ZLJkt27tw5FVC3bdt2zTFN+T3rf9VkX8l71n81b95c/fLLL6u9T6vXVJM+wlJWVsaePXsIDQ2tvE2n0xEaGkpcXFy168TFxVUZDxAWFnbN8Y3FzewrgIKCAtq1a4ePj891G3tT11RfV7ciMDAQLy8v7rnnHv744w+t42jCYDAA4Obmds0x8tq6oib7CuQ9y2g0smLFCgoLCwkJCal2jFavqSZdWPLy8jAajXh4eFS53cPD45rfh2dnZ5s1vrG4mX3VtWtXlixZwk8//cQ333yDyWRi4MCBnD59uj4iNyjXel3l5+dTXFysUSrL5OXlxcKFC1mzZg1r1qzBx8eHwYMHs3fvXq2j1SuTycTMmTO57bbb6Nmz5zXHNdX3rP9V033VlN+z9u/fT7NmzbC1teWpp55i7dq1+Pn5VTtWq9dUo7has7BMISEhVRr6wIED6d69O59//jlvv/22hslEQ9a1a1e6du1a+eeBAwdy/PhxPvnkE77++msNk9WviIgIDhw4wI4dO7SOYvFquq+a8ntW165dSUpKwmAwsHr1aiZNmsS2bduuWVq00KSPsLi7u6PX68nJyalye05ODp6entWu4+npadb4xuJm9tVfWVtb07t3b44dO1YXERu0a72unJ2dsbe31yhVw9G/f/8m9bp65plnWLduHb/99htt2rS57tim+p71J3P21V81pfcsGxsbOnXqRN++fZk7dy4BAQH861//qnasVq+pJl1YbGxs6Nu3LzExMZW3mUwmYmJirvndXUhISJXxAFu3br3m+MbiZvbVXxmNRvbv34+Xl1ddxWywmurrqrYkJSU1ideVqqo888wzrF27ll9//ZX27dvfcJ2m+tq6mX31V035PctkMlFaWlrtfZq9pur0lN4GYMWKFaqtra26bNky9eDBg+r06dNVV1dXNTs7W1VVVZ0wYYL62muvVY7/448/VCsrK/XDDz9UDx06pM6ZM0e1trZW9+/fr9VTqDfm7qs333xT3bx5s3r8+HF1z5496sMPP6za2dmpqampWj2FenP58mV137596r59+1RA/fjjj9V9+/apmZmZqqqq6muvvaZOmDChcvyJEydUBwcH9eWXX1YPHTqkRkVFqXq9Xt20aZNWT6HemLuvPvnkEzU6OlpNS0tT9+/frz7//POqTqdTf/nlF62eQr2ZMWOG6uLiosbGxqpZWVmVS1FRUeUYec+64mb2VVN9z3rttdfUbdu2qenp6WpKSor62muvqYqiqFu2bFFV1XJeU02+sKiqqv773/9W27Ztq9rY2Kj9+/dX4+PjK+8bNGiQOmnSpCrjV61apXbp0kW1sbFRe/Tooa5fv76eE2vHnH01c+bMyrEeHh7qvffeq+7du1eD1PXvz5/e/nX5c/9MmjRJHTRo0FXrBAYGqjY2NmqHDh3UpUuX1ntuLZi7r9577z21Y8eOqp2dnerm5qYOHjxY/fXXX7UJX8+q209AldeKvGddcTP7qqm+Zz3++ONqu3btVBsbG7Vly5bq3XffXVlWVNVyXlOKqqpq3R7DEUIIIYS4NU36HBYhhBBCNAxSWIQQQghh8aSwCCGEEMLiSWERQgghhMWTwiKEEEIIiyeFRQghhBAWTwqLEEIIISyeFBYhhBBCWDwpLEIIIYSweFJYhBBCCGHxpLAIIYQQwuJJYRFCCCGExfv/v07GJwNkeIUAAAAASUVORK5CYII=",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "true_values = timeseries\n",
-    "\n",
-    "pred_plot = np.append(predict_from[-num_preds:], preds)\n",
-    "true_plot = np.append(predict_from[-num_preds:], true_values)\n",
-    "\n",
-    "minlen = min(len(pred_plot), len(true_plot))\n",
-    "\n",
-    "plt.plot(pred_plot[:minlen], label=\"Predictions\")\n",
-    "plt.vlines(num_preds - 1, ymin=np.min(target), ymax=np.max(target), colors='k', linestyles='dashed')\n",
-    "plt.plot(true_plot[:minlen], label=\"True timeseries\")\n",
-    "plt.legend()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Experiment: 100%|██████████| 1000/1000 [2:08:41<00:00,  7.72s/it] \n"
-     ]
-    }
-   ],
-   "source": [
-    "from tqdm import tqdm\n",
-    "\n",
-    "\n",
-    "NUM_EXP = 1000\n",
-    "exp_res = np.zeros((NUM_EXP, len(models)))\n",
-    "\n",
-    "for i in tqdm(range(NUM_EXP), desc=\"Experiment\"):\n",
-    "\n",
-    "\n",
-    "    OP = random_unitary(2**n_qubits)\n",
-    "    qres = QReservoir(qubits=n_qubits, layers=[\n",
-    "    Layers.Reset(),\n",
-    "    Layers.Timeseries(build_method=build_method, \n",
-    "                      encoding = encoder,\n",
-    "                      reservoir = OP)\n",
-    "    ])\n",
-    "\n",
-    "    states = qres.run(\n",
-    "        timeseries=timeseries, \n",
-    "        shots=SHOTS,\n",
-    "        disable_status_bar=True,\n",
-    "        transpile=True,\n",
-    "        backend=backend\n",
-    "    )\n",
-    "\n",
-    "    xstates = states[:-1][warmup_idx:]\n",
-    "    target = timeseries[1:][warmup_idx:]\n",
-    "    exp_res[i] = utilities.stress_test_models(xstates, target, models, test_to_train_ratio=1/3, N=50)\n",
-    "\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# np(\"data/random_LONGSIM\", exp_res)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 9 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "\n",
-    "fig, axes = plt.subplots(ncols=3, nrows=3, sharex='col', sharey='row')\n",
-    "fig.suptitle(\"KNeighborsClassifier\")\n",
-    "ii = 0\n",
-    "jj = 0\n",
-    "\n",
-    "mod = KNeighborsClassifier(n_neighbors=2)\n",
-    "for idx, model in enumerate(models):\n",
-    "    if type(model) == KNeighborsClassifier:\n",
-    "        axes[ii][jj].hist(exp_res[:, idx], density=True)\n",
-    "        axes[ii][jj].legend([model.n_neighbors])\n",
-    "        ii += 1\n",
-    "        if ii >= len(axes):\n",
-    "            ii = 0\n",
-    "            jj += 1\n",
-    "# temp_res = exp_res[:, 0]\n",
-    "# _ = axes.hist(temp_res)\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "\n",
-    "plt.figure()\n",
-    "plt.title(\"KNeighborsClassifier\")\n",
-    "for idx, model in enumerate(models):\n",
-    "    if type(model) == KNeighborsClassifier and model.n_neighbors in range(1, 4):\n",
-    "        plt.xlim([0.5, 1])\n",
-    "        plt.hist(exp_res[:, idx], density=True, label=model.n_neighbors, alpha=0.7, bins=50)\n",
-    "        ii += 1\n",
-    "        if ii >= len(axes):\n",
-    "            ii = 0\n",
-    "            jj += 1\n",
-    "plt.legend()\n",
-    "plt.xlabel(\"Score\")\n",
-    "plt.ylabel(\"Probability density\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 12 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, axes = plt.subplots(ncols=4, nrows=3)\n",
-    "fig.suptitle(\"RidgeClassifier\")\n",
-    "ii = 0\n",
-    "jj = 0\n",
-    "\n",
-    "for idx, model in enumerate(models):\n",
-    "    if type(model) == RidgeClassifier:\n",
-    "        # axes[ii][jj].set_xlim([0, 1])\n",
-    "        axes[ii][jj].hist(exp_res[:, idx], density=True)\n",
-    "        axes[ii][jj].legend([round(model.alpha * 1e4, 1)])\n",
-    "        ii += 1\n",
-    "        if ii >= len(axes):\n",
-    "            ii = 0\n",
-    "            jj += 1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# fig, axes = plt.subplots(ncols=2, nrows=2)\n",
-    "# fig.suptitle(\"SVC\")\n",
-    "# ii = 0\n",
-    "# jj = 0\n",
-    "plt.figure()\n",
-    "plt.title(\"SVC\")\n",
-    "# plt.xlim([0, 1])\n",
-    "\n",
-    "for idx, model in enumerate(models):\n",
-    "    if type(model) == SVC:\n",
-    "        plt.xlim([0.3, 1])\n",
-    "        plt.hist(exp_res[:, idx], density=True, label=model.kernel, alpha=0.7, bins=70)\n",
-    "        ii += 1\n",
-    "        if ii >= len(axes):\n",
-    "            ii = 0\n",
-    "            jj += 1\n",
-    "plt.legend()\n",
-    "plt.xlabel(\"Score\")\n",
-    "plt.ylabel(\"Probability density\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots(ncols=2, nrows=1, sharey=True)\n",
-    "\n",
-    "BINS = 30\n",
-    "ax[0].set_title(\"KNeighborsClassifier\")\n",
-    "for idx, model in enumerate(models):\n",
-    "    if type(model) == KNeighborsClassifier and model.n_neighbors in [1, 2, 3]:\n",
-    "        ax[0].set_xlim([0.2, 1])\n",
-    "        ax[0].hist(exp_res[:, idx], density=True, label=model.n_neighbors, alpha=0.7, bins=BINS)\n",
-    "        ii += 1\n",
-    "        if ii >= len(axes):\n",
-    "            ii = 0\n",
-    "            jj += 1\n",
-    "\n",
-    "ax[0].legend()\n",
-    "ax[0].set_xlabel(\"Score\")\n",
-    "ax[0].set_ylabel(\"Probability density\")\n",
-    "\n",
-    "ax[1].set_title(\"SVC\")\n",
-    "\n",
-    "for idx, model in enumerate(models):\n",
-    "    if type(model) == SVC:\n",
-    "        ax[1].set_xlim([0.2, 1])\n",
-    "        ax[1].hist(exp_res[:, idx], density=True, label=model.kernel, alpha=0.7, bins=BINS)\n",
-    "        ii += 1\n",
-    "        if ii >= len(axes):\n",
-    "            ii = 0\n",
-    "            jj += 1\n",
-    "ax[1].legend()\n",
-    "ax[1].set_xlabel(\"Score\")\n",
-    "\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "quantum",
-   "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"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}