{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2e8a7f97-24b4-455e-b768-57cdee820012",
   "metadata": {},
   "source": [
    "# Create perturbed FY files (only variance, all energies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "06dad8ae-478b-44fe-a0cc-8cd37bd4acc3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:04:58.401513Z",
     "iopub.status.busy": "2026-01-19T15:04:58.401330Z",
     "iopub.status.idle": "2026-01-19T15:04:59.497790Z",
     "shell.execute_reply": "2026-01-19T15:04:59.496805Z"
    }
   },
   "outputs": [],
   "source": [
    "import sandy\n",
    "import pandas as pd\n",
    "from os.path import join\n",
    "import numpy as np\n",
    "import random, sys\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db66e7a6-e7a9-46a2-abea-6cfc699122b3",
   "metadata": {},
   "source": [
    "## Extract FYs and covariance data for U235 fission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3096afe7-8921-4dfe-94b4-1e3443954424",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:04:59.499678Z",
     "iopub.status.busy": "2026-01-19T15:04:59.499430Z",
     "iopub.status.idle": "2026-01-19T15:05:00.519645Z",
     "shell.execute_reply": "2026-01-19T15:05:00.518877Z"
    }
   },
   "outputs": [],
   "source": [
    "za = 92235\n",
    "tape = sandy.get_endf6_file(\"jeff_33\", \"nfpy\", za * 10)\n",
    "nfpy = sandy.Fy.from_endf6(tape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "891967d7-eb66-424f-a8a4-14f625f133cf",
   "metadata": {},
   "source": [
    "## Generate perturbation coefficients for all energies and write them to file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9aa1f7c4-9897-4557-bf2b-626504924a8c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:00.521645Z",
     "iopub.status.busy": "2026-01-19T15:05:00.521482Z",
     "iopub.status.idle": "2026-01-19T15:05:00.524424Z",
     "shell.execute_reply": "2026-01-19T15:05:00.523772Z"
    }
   },
   "outputs": [],
   "source": [
    "energies = nfpy.data.E.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7b45981f-8bf9-4c4b-bbb5-5f3e8ed4098a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:00.525897Z",
     "iopub.status.busy": "2026-01-19T15:05:00.525742Z",
     "iopub.status.idle": "2026-01-19T15:05:01.053019Z",
     "shell.execute_reply": "2026-01-19T15:05:01.052270Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sampling IFY for energy 2.530e-02 eV...\n",
      "sampling IFY for energy 4.000e+05 eV...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sampling IFY for energy 1.400e+07 eV...\n"
     ]
    }
   ],
   "source": [
    "nsmp = 100 # sample size\n",
    "smp = {}\n",
    "rcovs = {}\n",
    "acovs = {}\n",
    "for e in energies:\n",
    "    idx = nfpy.data.query(f\"E=={e} & MT==454\").index\n",
    "    ify = nfpy.data.loc[idx]\n",
    "    relative_dfy = (ify.DFY/ify.FY).fillna(0).values\n",
    "    cov = rcovs[e] = sandy.CategoryCov(np.diag(relative_dfy**2), index=ify.ZAP, columns=ify.ZAP)  # Diagonal covariance matrix\n",
    "    acovs[e] = sandy.CategoryCov(np.diag(ify.DFY**2), index=ify.ZAP, columns=ify.ZAP)  # Diagonal covariance matrix\n",
    "    seed = random.randrange(2**32 - 1)    # create a seed\n",
    "    print(f\"sampling IFY for energy {e:.3e} eV...\")\n",
    "    smp[e] = cov.sampling(nsmp, seed=seed)   # need to change the seed for the different energies    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1d6bb1ef-e27b-4e2f-91b5-29156a293860",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:01.055078Z",
     "iopub.status.busy": "2026-01-19T15:05:01.054703Z",
     "iopub.status.idle": "2026-01-19T15:05:05.638783Z",
     "shell.execute_reply": "2026-01-19T15:05:05.637812Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.ExcelWriter(f'PERT_{za}_MF8_MT454.xlsx') as writer:\n",
    "    for e, s in smp.items():\n",
    "        s.data.to_excel(writer, sheet_name=f'{e:.3e}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9d980cd-c181-465a-a499-acfaf0777027",
   "metadata": {},
   "source": [
    "## Read coefficients from perturbation file and generate random FY ENDF-6 files"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57c30635-895e-4ded-8b0d-ae9933f6cbf6",
   "metadata": {},
   "source": [
    "Skip the part above if you already have the file of perturbations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e2eec6f2-8129-4395-a921-fdb13ca043ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:05.640749Z",
     "iopub.status.busy": "2026-01-19T15:05:05.640569Z",
     "iopub.status.idle": "2026-01-19T15:05:07.964761Z",
     "shell.execute_reply": "2026-01-19T15:05:07.963891Z"
    }
   },
   "outputs": [],
   "source": [
    "smp = pd.read_excel(f'PERT_{za}_MF8_MT454.xlsx', sheet_name=None, index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1e104351-9068-4d8b-adbb-9fefa18407b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:07.966544Z",
     "iopub.status.busy": "2026-01-19T15:05:07.966363Z",
     "iopub.status.idle": "2026-01-19T15:05:08.489877Z",
     "shell.execute_reply": "2026-01-19T15:05:08.489037Z"
    }
   },
   "outputs": [],
   "source": [
    "za = 92235\n",
    "tape = sandy.get_endf6_file(\"jeff_33\", \"nfpy\", za * 10)\n",
    "nfpy = sandy.Fy.from_endf6(tape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ca0cd0b6-e679-48e9-87e9-dddf139a8a08",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:08.491516Z",
     "iopub.status.busy": "2026-01-19T15:05:08.491348Z",
     "iopub.status.idle": "2026-01-19T15:05:08.493744Z",
     "shell.execute_reply": "2026-01-19T15:05:08.493079Z"
    }
   },
   "outputs": [],
   "source": [
    "### run only if you want consistent CFYs\n",
    "# tape_rdd = sandy.get_endf6_file(\"jeff_33\", \"decay\", \"all\")\n",
    "# rdd = sandy.DecayData.from_endf6(tape_rdd)  # this can take a while"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "181943ff-d4b9-4ba1-9fa3-94c67092f68c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:08.495393Z",
     "iopub.status.busy": "2026-01-19T15:05:08.495065Z",
     "iopub.status.idle": "2026-01-19T15:05:48.554044Z",
     "shell.execute_reply": "2026-01-19T15:05:48.553250Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_0.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_1.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_2.jeff33'...\n"
     ]
    },
    {
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      "writing file 'u235_fy_3.jeff33'...\n"
     ]
    },
    {
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      "writing file 'u235_fy_4.jeff33'...\n"
     ]
    },
    {
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      "writing file 'u235_fy_5.jeff33'...\n"
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      "writing file 'u235_fy_6.jeff33'...\n"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_81.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_82.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_83.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_84.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_85.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_86.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_87.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_88.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_89.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_90.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_91.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_92.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_93.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_94.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_95.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_96.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_97.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_98.jeff33'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'u235_fy_99.jeff33'...\n"
     ]
    }
   ],
   "source": [
    "smp_min = 0   # write ENDF-6 file only in the sample range [smp_min, smp_max]\n",
    "smp_max = 99\n",
    "file_template = \"u235_fy_{}.jeff33\"\n",
    "for ismp in range(smp_min, smp_max+1):\n",
    "    file = file_template.format(ismp)\n",
    "    f = sandy.Fy(nfpy.data.copy())\n",
    "    for e, s in smp.items():\n",
    "        idx_ify = nfpy.data.query(f\"E=={float(e)} & MT==454\").index\n",
    "        idx_cfy = nfpy.data.query(f\"E=={float(e)} & MT==459\").index\n",
    "        f.data.loc[idx_ify, \"DFY\"] = f.data.loc[idx_ify, \"FY\"]            # just for me, i copy the original IFYs where uncertainties should be, so i can compare them to the perturbed ones (anyways I don't use uncertainties)\n",
    "        f.data.loc[idx_cfy, \"DFY\"] = f.data.loc[idx_cfy, \"FY\"]            # same but for CFYs\n",
    "        f.data.loc[idx_ify, \"FY\"] *= s[ismp].values                # IMPORTANT, this does not update the CFYs, which in random ENDF-6 file are inconsistent with the perturbed IFYs\n",
    "        #f = f.apply_qmatrix(922350, e, rdd, keep_fy_index=True)      # Run this if you want to update the CFYs (slower), or else comment it out\n",
    "    print(f\"writing file '{file}'...\")\n",
    "    f.to_endf6(tape).to_file(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b6073c28-8097-4104-ae0b-83d814f44c3b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:05:48.555796Z",
     "iopub.status.busy": "2026-01-19T15:05:48.555622Z",
     "iopub.status.idle": "2026-01-19T15:06:04.363720Z",
     "shell.execute_reply": "2026-01-19T15:06:04.362869Z"
    }
   },
   "outputs": [],
   "source": [
    "mfy_th = {}\n",
    "mfy_fast = {}\n",
    "mfy_he = {}\n",
    "for ismp in range(smp_min, smp_max+1):\n",
    "    fysmp = sandy.Fy.from_endf6(sandy.Endf6.from_file(f\"u235_fy_{ismp}.jeff33\"))\n",
    "    mfy_th[ismp] = fysmp.get_mass_yield(zam=922350, e=energies[0])\n",
    "    mfy_fast[ismp] = fysmp.get_mass_yield(zam=922350, e=energies[1])\n",
    "    mfy_he[ismp] = fysmp.get_mass_yield(zam=922350, e=energies[2])\n",
    "mfy_th = pd.DataFrame(mfy_th).rename_axis(\"SMP\", axis=1)\n",
    "mfy_fast = pd.DataFrame(mfy_fast).rename_axis(\"SMP\", axis=1)\n",
    "mfy_he = pd.DataFrame(mfy_he).rename_axis(\"SMP\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6a71263f-d86f-4152-8fd7-133661babc6e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:06:04.365948Z",
     "iopub.status.busy": "2026-01-19T15:06:04.365748Z",
     "iopub.status.idle": "2026-01-19T15:06:04.763577Z",
     "shell.execute_reply": "2026-01-19T15:06:04.762844Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e = energies[0]\n",
    "\n",
    "mask = f\"MT==454 and E=={e}\"\n",
    "ify = nfpy.data.query(mask)\n",
    "S = sandy.Fy(ify).get_mass_yield_sensitivity()\n",
    "C = pd.DataFrame(acovs[e].data.values, index=ify.ZAP.values, columns=ify.ZAP.values)\n",
    "cov_mfy = sandy.CategoryCov(S @ C @ S.T)\n",
    "\n",
    "mu = nfpy.get_mass_yield(zam=922350, e=e)\n",
    "sigma = cov_mfy.get_std()\n",
    "\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 5), sharex=True)\n",
    "\n",
    "ax = axs[0]\n",
    "ax.errorbar(x=mfy_th.index, y=mfy_th.T.mean(), yerr=mfy_th.T.std(), marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"blue\", color=\"dodgerblue\", label=\"sample estimate\")\n",
    "ax.errorbar(x=mu.index, y=mu.values, yerr=sigma.values, marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"k\", color=\"k\", alpha=.4, label=\"original data\")\n",
    "ax.set(ylabel=\"mass yields\", xlabel=\"A\")\n",
    "\n",
    "ax = axs[1]\n",
    "diff_mean = (mfy_th.T.mean() / mu  - 1) * 100\n",
    "diff_std = (mfy_th.T.std() / sigma - 1) * 100\n",
    "ax.errorbar(x=diff_mean.index, y=diff_mean.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"dodgerblue\", label=\"$\\\\frac{m- \\\\mu}{\\\\mu} \\\\times 100$\")\n",
    "ax.errorbar(x=diff_std.index, y=diff_std.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"tomato\", label=\"$\\\\frac{s- \\\\sigma}{\\\\sigma} \\\\times 100$\")\n",
    "ax.set(ylim=[-100, 100], ylabel=\"relative difference / $\\\\%$\", xlabel=\"A\")\n",
    "ax.legend()\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d4898b17-7338-43cd-9a08-ffc097c092ec",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:06:04.765382Z",
     "iopub.status.busy": "2026-01-19T15:06:04.765215Z",
     "iopub.status.idle": "2026-01-19T15:06:05.098219Z",
     "shell.execute_reply": "2026-01-19T15:06:05.097294Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RQSPdIiIdmiHWijGudkTbC/iqjkUuIBERERGpRyPdIiIiIiIiIiGipFtEREREREQkRJR0i4h0YL4KJ163o+biq3BGOiQRCZFnn32Ws846iyFDhnDllVe2+fabN29m5MiRnHrqqRgMBgwGA3/9619DEKmIiNSlOd0iIh1Qmt1CrC2ZCkdRozncsbZk0uyWCEUmIqHw3Xff8dRTT7FlyxZMJhMlJSVtur3T6eS6667j1VdfZejQofz0pz9lxIgRXHHFFaEJWEREamikW0SkAzqlt42NT2bz4kM34tz5PZw7v8eLD93Ia0/cquXCRDohs9nMd999x+23385///tfkpKSavYNHz6cIUOGNLrk5ubWHPPWW28xZswYhg4dCsDpp59OSUkJBoMhqHF+8MEHTJ48md69e2MwGFi7dm3A45566in69++PxWJhxIgRbN68uV3HiIh0BEq6RUQ6qFN62xg1KIWqvEqq8ioZNSiFsZkpSrglavXv37+mrLnu5YYbbgBg/Pjxjfb94he/iHDU0aFbt27s3LmT4cOH85Of/KReMrt9+3Z27tzZ6NK7d++aY7788kuGDBlS7zZnnXVWs4+5ceNGKisrG23/8ssvOXz4cMDblJeXM2zYMJ566qkm7/ell15i3rx53HfffWzdupVhw4YxadIkCgoK2nSMiEhHoaRbREREwuKzzz4jLy+v5vL2228D1Ctxnj17dr1jHnnkkUiF27SiAvjm68aXotAlhF9//TXdunVj2rRpjBs3Drfb3abbd+/enR07dgD+9yEnJ4fzzz+/yeO9Xi833HAD11xzDR6Pp2b7rl27OP/88/njH/8Y8HYXX3wxixcvZurUqU3e92OPPcbs2bOZOXMmgwcPZtmyZVitVlatWtWmY0REOgrN6RYREZGw6NmzZ73rv/71rxk4cCDjxo2r2Wa1WklLSwt3aK1XVAD3zIKqxiPAmGPgwZWQnBr0h128eDGffPIJVquVUaNGtXku9rXXXsu6desYOnQoGRkZvPzyy8TExDR5vNFo5M0332Ts2LFMnz6d559/nn379nH++eczZcoUbr/99nY9j4qKCrZs2cJdd91V77EmTpzIpk2bWn2MiEhHoqRbREREwq6iooIXXniBefPm1ZtX/Oc//5kXXniBtLQ0Jk+ezMKFC7FarU3ej9vtrjfqW1ZWFtK4cZQGTrjBv91RGpKku6mR5day2+2sX7++Tbfp3bs3//73vxkzZgzXXHMNmzZtYuLEiTzzzDPtjqOwsBCPx0OvXr3qbe/VqxdfffVVq48REelIlHSLiIhI2K1du5aSkhJ++tOf1my75ppr6NevH71792bHjh3ccccd7Nq1i7/97W9N3s+SJUtYtGhRGCLumvr27cvzzz/PuHHjOPnkk1m5cmXQm6+JiHR2SrpFREQk7FauXMnFF19cr9lXdnZ2zb+HDh1Keno6F1xwAXv37mXgwIEB7+euu+5i3rx5NdfLysro06dP6AKPkHAkuj6fr9G2w4cPk52dzeTJk/nss8+49dZb+f3vf9/ux0hJScFkMjVqxHb48OGaaQWtOUZEOriiAn9lUEM2e0iqhSJNSbeIiIiE1TfffMM777zT7Ag2wIgRIwDYs2dPk0l3XFwccXFxQY8x2gRKiBvavHkzN998M8XFxezevRvwdwH/yU9+0q7HLCws5IILLiAzM5OXX36Z3bt3M378eOLi4vjNb37TrvuMjY0lKyuLDRs2MGXKFMDftG3Dhg3MnTu31ceISAcWod4YkaSkW0RERMJq9erVpKamcumllzZ73Pbt2wFIT08PQ1Qdm9Pp5LrrruPVV19l6NCh/PSnP2XEiBFtbrhWzev1cvHFF9OvXz9eeuklzGYzgwcP5u233+b8888nIyODW2+9tdHtHA4He/bsqbm+b98+tm/fTo8ePejbty8A8+bNY8aMGZx99tmce+65PP7445SXlzNz5sya27XmGBHpoCLUGyOSlHSLiIhI2Hi9XlavXs2MGTMwm2u/huzdu5c1a9ZwySWXkJyczI4dO7j11lsZO3YsZ5xxRgQjbsBm94/ENDVCY7OHPybgrbfeYsyYMQwdOhSA008/nZKSknaXpRuNRh566CHGjBlDbGxszfZhw4bxzjvvNOpEX+3zzz9nwoQJNderS/9nzJjBc889B8CVV17JkSNHuPfee8nPz2f48OGsX7++XuO01hwjItJRKOkWERGRsHnnnXc4cOAAP/vZz+ptj42N5Z133qkZ0ezTpw+XX345v/zlLyMUaROSU/2lj1E2F/HLL79kyJAhNde3b9/O9OnTT+g+L7zwwoDbzzzzzCZvM378+FaVws+dO7fFUvHWHCMi0hEo6RYREZGw+cEPfhAwKevTpw/vv/9+BCJqh+TUqCt97N69O5999hkAn332GTk5OZx//vkRjkpEREBJt4hIh+N0OnE6nQCUlVUBjprtdntiBCMTkUi59tprWbduHUOHDiUjI4OXX36ZmJiYSIclIiIo6RYR6XBycnLYvHkzGzdupKKiesTQwO7dOaSnj4hobCISGXa7nfXr10c6DBGRlkVpb4xQUtItItLBZGZmkpGRwbFjx3A6Pbz8MoCJU07JjHRoIiIiIs2L0t4YoaSkW0Skg7FarcTGxmKz2TAaPce3mrBarRGNS0RERKRVorA3Rigp6RaRsMrL818aSk/3X0REREREOhMl3SISVsuXw6JFjbffdx/cf3/Yw+mQ8vLg4EE4cABcrtrt+flg73zToEREREQ6NCXdIhJW06Y5OeccJz/8of/666+DxQL9+1sBlUe3RlMnLlavhl//OvzxiIiIiEjTlHSLSFiVlOSwZ89mYCMAe/aMJj7eRFJSFpAV0dg6ijlzYMIEGD++/vZzz4WtW1WqL9KSQOuES+ej91lEooWSbhEJq8zMTLp3z+CWW44BMHnyVBITzWoC1gbp6eB/uSqAY8e3mrj88kLAzN13W3nwQb2eIg1Vr1vtdDqJj4+PcDQSak6nE0DrlYtIxCnpFpGwslqtJCfHAjYAkpNTsNv1p6h98oBvuOmmczCZPMAaAIYNG0Zh4TCsVqtOZojUYTKZSEpKoqCgAPD/PTIYDBGOSoLN5/PhdDopKCggKSkJk8kU6ZBEpIvTN10RkQ4rHUjm/PNPY/fuHWzevBmAfv1M/O1ve8nKyiIrSyX7InWlpaUB1CTe0nklJSXVvN8iIpGkpFtEpMOKBWLp128k8fHDyMvzj+ZkZl6JyWQmLg4KCwsb3Uoj4NKVGQwG0tPTSU1NpbKyMtLhSIjExMRohFtEooaSbhGJqO3boVu32utqAtZ2L75o5eGHrVSX7P/2tymAmWuv3UKfPpv5z3/8TeuGDRuNyWRizJgsJk3SCLh0bSaTSUmZiIiEhZJuEYmohh24667X7XQ6axrh1KWR2vpmzoSLL659Ld97z38i47nnMvn1rzOobrb2z39OpbrR2qRJEQpWREREpItR0i0iUeGjjyA+vv4od05ODps3b2bjRv9I7ejR/pFazVWuLy3Nf6k2fDjY7ZCebuXyy2MZP94/Av7eeyl062ZWJYGIiIhIGCnpFpGwqDtqXVZWBRTjX/LqINCNk06ChASOj2D7R7GTkjIZODCDr7/2j9QOHDgVk8lMUpJGuVuj/tJiFfTpU0hiov/PfmGhKgZEREREwkFJt4iERd1R64oKH/6kuxjYBCSzdu1o4uPrj2I//7yVRYtqlxernqtctwRdWiMP2M9dd20hJsagigERERGRMFLSLSJhkZmZSUZGBseOHcPp9PDyyxVAJRADxDN58lQSE831Rl7nzIEJExrPVVZ5dFulA0kkJ4PFYlLFgIiIiEgYKekWkbCwWq3ExsZis9kwGj0N9ppITk7Bbq//J6m2PNqveq6ytFUsYOKZZwBMqhgQERERCSMl3SIiXYwqBkRERETCR0m3iEQFp9NJZWVFo+2VlbERiKZzU8WAiIiISPgo6RaRsMjLg4MH4cABcLka79+9O4cvv9zaaHmwU08dFuZIRURERESCR0m3iITF8uWwaFHT+085JZNTT+3HsWP+5cGmTp2K2Ww+PtL9n/AEKSIiIiISZMZIByAiXcOcOf65xE2xWq2kpKRgs9mw2WykpKSQkpKidaRFREREpEPTSLeIhEXDTuQiIiIiIl2Bkm4RiQr5+VBa6p/zDbB1K5jNkJAQ2bg6lgqggqKiQior/X/ey8qqjm831Ry1fbu/e3ld6enqZi4iIiISCkq6RSSk8vL8F4CjR5s+bvVqePjh2usPPuj//x13hC62zicP2M/cuZ9SUeHh9NNHUFkJkAv0pnq97vHjC2n45//uu608+KBKEURERESCTUm3iIRUSw3Uqs2cCRdfDOPH+69XryWdkFA/GRdwOBwUFTkABwBFRYXH9/QAkjhy5Fs+//xbNmz45Ph2M1AA9AWMzJ37Kk8+uQmA+fNHY7GYGDMmC8gK59MQERER6RKUdItISM2ZAxdeCOed1/xxaWn+S7XqtaRLS0MaXofjcDhYsWIFublHqO7q/vTTR47v3QOM4owzTqZ//5N45ZWGt/aPdM+a9SOefNINwPXXTyUx0ayGdSIiIiIhoqRbRELKbndy0knO49eq8I/OevAngLERi6ujcrlcFBUVYbFYAH+i3L17D44dcwLlQBWrVtlo+rU10aNHCmADIDk5BbtdHwUiIiIioaJvWiISUjk5OXz00WZgI+Crs6fv8UsF4KlTIu0vmXY6ndjtieEMtUOJj7cCFgBsNls77qFx0zXwL92mUW8RERGR4FHSLSIhlZmZSffuGdxyyzH8I9zVqkdi84ED3HXXFnw1ObmB3btzSE8fEc5Quxh/07W77tpCTIyB0aNHYzKZyMrKIitLc7tFREREgkVJt4iEhNPpxOl0NtpuSkrGaKu7XpUdOI2Thx0jwXuUl18G8JCcnEphYeHxJa80+h186UASZ5wB8fEmpk6ditmsud0iIiIiwaakW0RCIicnh82bN7Nx40YqKvxD2KakZHrfcwuGmJhGx79EFT/1/QV/gv0t//rXm2zduqnmthr9rnXUDUeOOTEm+tfe3nPYgdvlxBAXg8/d2nvxN1Wz2fxJd0pKCmazPhJEREREgk3fsEQkJDIzM8nIyODYsWM4nR5efhmMtlR8XjdeR+OW5N4YC8diLfiT7nR++MMfAe6a24KJU07JDO+TiELFFRb+8r9kKhxF2EacBMCfPi8BwH7heZR9mIS3tKrV93fwIFgssHUrmM2Qnu6/iIiIiEhwKOkWkZCwWq3ExsZis9kwGv1zuX1eI46PV+B1FjU63mhN5tDAnsevxVJZmVLvtmBS6TPgNtuwfD+buEpXo32GGAvl2/+Jt7QwwC0DW7rU//8HH/T//7774P77gxCoiIiIiABKukUknHwVeJ1FGMzxGGKtdTY78TqL+Mtf7DXbHn4Y+vYFV53cMj/fv3Z3V2eMs0FcazqWu/Av01aXifJyR6Mj33sPunXTKLeIiIhIsCnpFpGQyMvzly4fOFA/cQYwxFr9ieNxXsBXdazeMc8/D0a7CaPVhDkdwMiDywv5+WwzaXYLp/RuzzJZXYkL+Aho2MzOwJo1lUA8UDu3fvhwndAQERERCQUl3SISEsuXw6JF7b/9s39xcNufi/G6S2q2/WPn7/nHzRBrS2bjk9lKvJtVhSGuEkOsHQxxtZt9FXx7pBjoRd2kW0RERERCQ0m3iITEnDkwYQKMH1+7zVvuxufxBjze5/HiLXcDBgCS0t143SUBS9ErHEXkl7qUdDfDmJhAwtmnY+rWs35VgdvB2v8VYky04i3zNXMPIiIiIhIMSrpFJCTS06Fh3zNvWTmOjf/1J9H1Rl/d+Cqc+Nw9gPqJdGtK0buSHhaIM4Hb03ifr7IKr8Nfy29MiMNgMga8Dy8GjAlxeMtcQAXg4b33CrHZaj8S+ve3MnCgGteJiIiInCgl3SISRmZ87hh87sZLhoEV/UlqWUYivDsdDhRWMW7cPwB49Z8/4mgFzLruXxhtFow2C6YehlbeYz5wgClTtuCvMhgNmJg9O4sVK7JC8ySky7r//vtZ1GDeyamnnspXX30FgMvlYv78+bz44ou43W4mTZrE008/Ta9evSIRroiISFDoG66IhEl1J+0zqd9R2wRY8P85skQgro4nIxFsPqj8tghTUgK3vHUMt8tN8rXn1hzjKS+i/JNP8VU48VS58XkqAfBVHsNX5cLnPQp4gDSgx/FbmVi7dio2m5n+/TXKLaFx+umn884779RcN5trv4rceuutvPHGG7z88svY7Xbmzp3Lj3/8YzZu3BiJUEVERIJCSbeIhEGgTtpV+IvF44ER+BNuB/4/Swk1R/kqnNSdBe6raNiNu2szWH0Uf/hso7XPfVUVVBbswtxjAJX5/61Xkm8wx4PvEAaLGZ/rHGpL+k2MH5+C3a6PBgkds9lMWlpao+2lpaWsXLmSNWvWcP755wOwevVqMjMz+eSTT/j+978f7lBFRESCQt+sRCQMqvAn3DHHL1VgzgejG/BgiPVhOD7H21dpwef6Pj1tcRjjkvC6SxrN4Y61JZNm16g4AL7KJtc+j0k9lfgzLse5/SX//pjjr5nJjMXrxesup/zzOLxlEYpduqSvv/6a3r17Y7FYGDlyJEuWLKFv375s2bKFyspKJk6cWHPsaaedRt++fdm0aZOSbhER6bCUdItIGMUAFrD4iOuX5p9C7KkkbuAIjHE2/6i2u5zyz2MZ0NNG2Yc9MFqrS5+NrFt3MQkJWqc7kEAN5wxVxzBau2OMtWK0JjfqYm6oOna8oVpFBCKWrmjEiBE899xznHrqqeTl5bFo0SLGjBnDzp07yc/PJzY2lqSkpHq36dWrF/n5+U3ep9vtxu1211wvK9NZJBERiS5KukUk7IyxMRgMBjCZwWDAGGfDGGerTRQT/KPe3lIP3tLqNt0mRg1S6XNblb23HbPOT0iUuPjii2v+fcYZZzBixAj69evHX//6V+Lj49t1n0uWLGnUnE1ERCSaBF5PRkREOgVPaXmkQxBpUlJSEqeccgp79uwhLS2NiooKSkpK6h1z+PDhgHPAq911112UlpbWXA4ePBjiqEVERNpGSbeIhIUhLgZjtxiMiWYMVvB5KqBKZc0nylvuxmjwHS/Nd9RcfBVOfB4vPtfxruUB9otEmsPhYO/evaSnp5OVlUVMTAwbNmyo2b9r1y4OHDjAyJEjm7yPuLg4EhMT611ERESiieo0RSTkjPYkEseMwesuAcBb4aTiwB58RjNGix1vlQtQZ/L28JZVkD2iO/mFxbzwwjbAV7PPV2nBmHQyRmsyXmdRo4Z0RmsyGGIBnfyQ8FiwYAGTJ0+mX79+5Obmct9992Eymbj66qux2+3MmjWLefPm0aNHDxITE7nxxhsZOXKkmqiJiEiHpqRbRIIqL89/ATh61P9/U7ckbGOuxlfpT669bgflnz2P91gxBqMZKsrxVvjLoP2JYEwkQu+gLNw0Zzput4s/PbMG/9rb1czgspBwzhXUXxu9dv/R918LT5giwLfffsvVV19NUVERPXv25LzzzuOTTz6hZ8+eAPz2t7/FaDRy+eWX43a7mTRpEk8//XSEoxYRETkxSrpFJKiWL4dAPY2McTY43j3bZEshccKtNUk4+BNxX5UbMFP27tsUFxfiX7fbgH8Nb2mKzWbDZrPhX2/bU2+fp8RB/m9ew2irfg2NvPHGD7n00tfxOpx4ShzhDle6sBdffLHZ/RaLhaeeeoqnnnoqTBGJiIiEnpJuEQmqOXPgwgvhvPOaP65uEl6weh0V+18BrwNfRRU+dxUrV+4DvgDigfOAhBBH3nl5Shx1kmsTpyb5qPy2iPoJegXgoaiokMrK2o8Gq9WK1WpFRERERNpHSbeIBFV6OrS1j1FVwRF8rhIMsVYMcd0wxEFFXA+M3ez4KsrxuQOVRktw5QMHuOuuLcTEGBg9ejQmk4msrCyysrIiHZyIiIhIh6WkW0QizmizEJ95OqZuPf0j4MArByHx/HPwHD1C+ecJeMsiHGQnYUpKYFeJgZiTkgFvzXavIw5PSQ/OOAPi401MnToVs9msUW4RERGRE6SkW0RCzutw4auswhDT+E+Or7IKAwYMpsArGBpMRowJcXjLPAH3Sy1TUgJGW2yj7V6HC0+JA1OSjbQFlzLztaOk/mJcg6PM5P/mNWw2B/HxJlJSUjCb9REhIiIicqL0jUpEgsrpdFJYWL30VxWmJANGm5eCVa9jjK+dl+07VoHnqBOvw4UhXktWnag8B6QtuJSmupTn/+Y1DFYo/2wVXmdRoyOM1mQM1p4hj1NERESkq4l40v3UU0/x6KOPkp+fz7Bhw/j973/Pueee2+TxL7/8MgsXLmT//v0MGjSIhx9+mEsuuaTeMTk5Odxxxx28//77VFVVMXjwYF599VX69u0b6qcj0uXl5OTw0UebgY2YknrQ+57fYIhpPPrqq6wi98G/4ClxYI737/dVOOsUPGvd7rY4VOxoOaH2VeB1FmEwx2OIrS0b91U4/bfz2cMZsoiIiEiXELieM0xeeukl5s2bx3333cfWrVsZNmwYkyZNoqCgIODxH3/8MVdffTWzZs1i27ZtTJkyhSlTprBz586aY/bu3ct5553HaaedxnvvvceOHTtYuHAhFouWHBIJh8zMTCZPngqchdGWFTDhBjDEmI8vY+XC53WByYLHWURVyUGqSg7iKcvDV3Xs+Lrdge9DalW4XXUSahuY4sAUh8/rparkIKakSoxWAwCGWCvGOFvNpW4CLiIiIiLBFdGR7scee4zZs2czc+ZMAJYtW8Ybb7zBqlWruPPOOxsd/8QTT3DRRRdx2223AfDAAw/w9ttv8+STT7Js2TIA7rnnHi655BIeeeSRmtsNHDgwDM9GRMC/xFRyciz+NaObT+Z8XhfwET6nD5+7/u+pIa4bCedOx5SQQvmWfwLHQhVy52I0UfHtVnzucgB8ngp8VceI7QvGODu+yuZL+Q8eBIsFtm4Fs9nfjT49PRyBi4iIiHROERvprqioYMuWLUycOLE2GKORiRMnsmnTpoC32bRpU73jASZNmlRzvNfr5Y033uCUU05h0qRJpKamMmLECNauXRuy5yEiJ8BXgSGuEkOcFaOtF+akPpiT+mCyJoPHjTHWhsFowetwRTrSDsPnqfQn3KYYDHFW/zJs5ngM5ni87lJ83uaXX1u6FB58EEaMgKwsWL48TIGLiIiIdFIRG+kuLCzE4/HQq1evett79erFV199FfA2+fn5AY/Pz88HoKCgAIfDwa9//WsWL17Mww8/zPr16/nxj3/Mu+++y7hxDbv1+rndbtxud831sjKtTSQSLF63A19l46TZEGMJuFQYgKfKDRXlHFn1KlWFHrxl5YCJjz920KtXUs1xXXUU1ul0UlRUBjgAKCoqpKy0tN4xBnMMBrMFMIC3CkOMBV/VMfD6As6d93m8eMvd/uOB996Dbt265usrIiIiEkwRb6QWTF6v/2vkj370I2699VYAhg8fzscff8yyZcuaTLqXLFnCokWLwhanSFfh87pwfLyi6eZesamNlgrzVbpw79+E11lE5ZE9+BzVS4UZuOQSD/B/+EvX4b774P77Q/oUolJOTg4ff7yF6tfhjTfWcaisCp/HC95j+DwVUGUGDFBVW05uMJpx/jePK6bE8dKLn4GvdtTbV2UBt/X4fSYwfDjY1VdNRERE5IRFLOlOSUnBZDJx+PDhetsPHz5MWlpawNukpaU1e3z1urKDBw+ud0xmZiYfffRRk7HcddddzJs3r+Z6WVkZffr0adPzEZHGvI6jeI4ewRiX0KhbtufoEXzHEhrdxuet8nctN5rBkEDtElhVQDHg4qOPbMTHd91R2MzMTFJS+nHTTf7rl10GZWWlPLL4HoyJFZgSjs9/P15KbohNAJMZgzkWTKO5ceb5vPiH24C6FQhu4GP88/ADn6AUERERkbaLWNIdGxtLVlYWGzZsYMqUKYB/pHrDhg3MnTs34G1GjhzJhg0buOWWW2q2vf3224wcObLmPs855xx27dpV73a7d++mX79+TcYSFxdHXFzciT0hEanHaDdhsDgp3/YlhrgkDKbjKwhUgfeYC5/7O4xJ/ukidcudvW4HeCoxmGIwGC34apLu2ikgw4dDQuN8vcuwWq2kpNSexEhJgaSkJHyuUWD3Etv3G/887pjjr7nJjMHrxQcYjBas1uqTGQlATJ17rgScBF7rW0REpIsqKgBHaePtNjskp4Y/HulwIlpePm/ePGbMmMHZZ5/Nueeey+OPP055eXlNN/Pp06eTkZHBkiVLALj55psZN24cS5cu5dJLL+XFF1/k888/Z8WKFTX3edttt3HllVcyduxYJkyYwPr163nttdd47733IvEURbqkPYcdJI4ppupoLhUHCjGYy/2jrIDBHM+xr43grgRiMFqT8TqL/PONAW+FE5+vCmOsHTARKAHMzwctShCIBZ/LgLlbb7zuEvAcP1HhceMDjHFJeJ11Z3PHAA2XU6wMS6QiIiIdQlEB3DMLqgJ8Pppj4MGVSrylRRFNuq+88kqOHDnCvffeS35+PsOHD2f9+vU1zdIOHDiA0Vg733PUqFGsWbOGX/7yl9x9990MGjSItWvXMmTIkJpjpk6dyrJly1iyZAk33XQTp556Kq+++irnnXde2J+fSFdVUObC6y7BYLYcXzfaisEcB1X+5asMMTZ8Lv+oq23UjHqN1jzlRTgAo60nlYcOUHeEu9rKlfDQQ+F7PtEmLw/+97/a69u3Q9XxcxPe0irKPkzCaO3R6HZepxdvqX+OvCEuBkOcvzt8NZ/XjM9dia/xSy4iItI1OUoDJ9zg3+4oVdItLYp4I7W5c+c2WU4eaHT6iiuu4Iorrmj2Pn/2s5/xs5/9LBjhicgJMMTEYzDF4u+I7fP/V1UBPn9zL2+5G4PRgtFmq3c7Y6wVs8+Dx1UCOBgxwkNFRQXbthUBe7j4YieFhVasVv+lq1m+HOr2fmx4TtFbWoU3QBWcn4kjx8A2enCjrvFetwPP0SOUf971XlMRERGRUIl40i0inZfBFIMhLgGfu9y/frSn4ngZuQmIwVtWTO6Df8Boi8df6hyDz+vCV3WYyZcksy7mO4hxcMyYgNPjwmDZiM+1lX/840JycgaQlZVFVlZWZJ9kBMyZ42+eVtfRozB+fMMjK45f6jJRcLQCg8kYcOkwg8mIMUE9LkRERESCRUm3iISMwRyH5eQx+I530fa6HXiPfYfH6eL6macQG2th6dKP8JT4gL5AX0xJNtIW/IbPqCL9Dv/9VC841hsT+b/5Iz/96Y9IS+vWJUe5IfD65KUBR7bzgYPA6OPXNwJQUDCy0Vz6akZrMubUnuQ5tGSYiIiISDAo6RaRoMjL818A9u7x/99X4YQ6S4UZDEaMsVYMxlO45ZapACxdegzwAP5Ga0abBZMtqcnHMdr60KdPH+x2/flqWRrQE5h6/Lo/wU7uORjbqKH15tJXM8RYSJxgY/Lffbw3HTISwxasiIiISKekb60iEhR15xkb7RYSxyThdZc0HkmNS8LrjCU5OeX4Fhv+pFuCLxZ/KX/d1xr+/W8Lxt5xEGfD63bUS759lS48lS5cMRaKXTYl3SIi0rXZ7P4u5U11L7epLExapqRbRIJizhy48EJ/Uy9vqY2yD3u02EFbwqO6J2X1nO+LL4J3d/jL/R0fr8DrLGp0G6M1GecV2VQn6iIiIl1Scqp/WTCt0y0nQEm3iASF3e7kpJOcx69V4S0tPZ5cx1JdOl7LFN7gurjhw+tfPzndh29LFb5KF15nUc2ybtV8FU68ziLcLhdKukVEpMtLTlVyLSdESbeIBEVOTg4ffbQZf7MuX509fY9fJFr0skLugy8R0zeO2F5giLXWXzoMGk0LEBGRBooKNPopIq2ipFtEgiIzM5Pu3TO45ZbqxmjVGo5yN8/rcOGrrMIQ0/jPk6+yCq+jcfMvaV5+vv9SbedO8JSUY4h3EdsrcnGJiHRYRQVwz6ym5/k+uFKJt4jUUNItIkFhtVpJTo6l6cZoddeMNlFUVFhne225uafEQe6DL/HP9/8fl176OgDvv/8jAMZkvYSnpDw0T6ATW7HCyWOPOQEHAJdeWgg48Jab8Hm8AW9jNPjobglfjBIahYWFfPrpp3g8Hs455xzSG641JyLt4ygNnHCDf7ujVEm3iNRQ0i0iYVJ3zWgTf//7K7hcx4BcoHed42LxlJRzapKPym/9Db4GJ/v3KOFun1GjcoiP/w/V87NdrtdYunQr3rJkHBv3+edzG+Jqb+CrYPZP+5PeLTLxSnC8+uqrzJo1i1NOOYXKykp27drFU089xcyZMyMdmoiISJeipFtEwqTumtFmTj31P3zxxX+AgfhHuqvngvcFBkQsyo4oLw927256/6hRmYwbN7DmellZ1fH10avwub/F5y4FqvDP5gYw0MN2Kg6HA4vFgs2mZmodgcPhqPdeLVq0iM2bN3PKKacA8MYbbzB79mwl3SIiImFmjHQAItJVVJeepwApjBgxkmuumQ5chT8RPwsYjj85l7ZYvrx2ObBArFYrKSkpNRf/Guk2oBtwHv7qg7h6t3E4jvLss8+yYsUKHA5HyGKX4MnKyuIf//hHzXWz2UxBQUHN9cOHDxMb27YeCyIiInLiNNItIkFlSkrAaGv8xd7rcOEpqe2IbbVasVqrl6mqoum54NKSOXPgkktg3TpwuWDp0rbc2oL/9fcACUAMYKBXrzR8PjdFRUW4XC6NdncAb731FjfccAPPPfccTz31FE888QRXXnklHo+HqqoqjEYjzz33XKTDFBER6XKUdItI0OQ5oPc9VzbZeTz3wZfwlPivb98e1tA6tfR06NnT/5o6nS0e3owY/Em4AZvNhsdj4tgxLR3WUfTv35833niDv/zlL4wbN46bbrqJPXv2sGfPHjweD6eddhoWi7rjiQSFze7vUt5U93KbPfwxiUjUUtItIkHznZuACTf4txttlpqk+7zzwhdXZ+d0OikrK8PhcOB0NlyuLb5V92GIi8EQZ8NgjAG87D1yDE9VORWOYxQVFTWoTJBodvXVV3PxxRezYMECxo8fz4oVKxg+fHikwxLpXJJT/cuCaZ1uEWkFJd0iElRetwNfZeO1tA0x/hG2996Dbt3885BXrAhzcJ1UTk4OW7ZswWazYTJ5aGtTOmNiAglnn46pW0+Mcf4y8j9/DV43+MqdmJ59l6kXnsOkSVmhfBoSBG+++SY5OTkMGzaMP/zhD7z//vtce+21XHzxxfzqV78iPr51J2FEpBWSU5Vci0irKOkWkaBxljtwfLwKr7Oo0T6jNRmfN5Xhw8Fuh/vv989FBjh6tPlGYNK8zMxM+vXrB/g7k99yyzH8c7Rb1zTLmBCHwWTEV+Gk7qrdvgonPoORlWsmkhzXm0mTgh66BNH8+fN54YUXmDBhAk8//TQ//elPWbhwIVu3buWBBx7gzDPP5Le//S0XX3xxpEMVERHpUpR0i0jQVLhdeJ1FGMzx/rWfj/NVOP2JuK97zbb0dP8FoDRAdZ60Xt3S75iYdjSlM8RitCbjdRbhq6o/h9toTWbVqjQmDlNpebR77rnn+Ne//kVWVhbFxcV8//vfZ+HChcTGxvLAAw9w9dVXM2fOHCXdIiIiYaakW0SCzhBrrSlTBv/qzw2TOYkeBqMF26jsJqcFDD/LRroqKKNeQkIC+/btIysri4MHDzZqmjZ48GA+/PDDCEUnIs0qKtD8cJFOTEm3iARNUhz4PN6A+3weL95yd5gjktYyxtkgTsuCdWRLlixh+vTp3HTTTTidTv74xz9GOiQRaY2iArhnVtOd0B9cqcRbpINT0i0iQdMrARwbv8QQl4TBWDvK5vO68Lm/w+fu2er72rkzFBF2bnl5sHt34+35+f559M0dIx3ftddey0UXXcT//vc/Bg0aRFJSUqRDEpHWcJQGTrjBv91RqqRbpINT0i0iQXGoDHYVgyHWDD43vuMD3t6KSnA5gCa+UNSoAKpL0E1cemkh4KC1zcDE3xF+0aLG21evhl//uuljvA4XvsqqgMu9xZp89LAYQhCthEJycjLJycmRDqPjU6mviIgEkZJuETlhh8pgwp/gmNNG4vmj63Uv93m8ODb+F5/bSvN/cvKAb5g/fzQWiwmX6zWWLt0K9Atx9J3HnDlwySWwbh24XLB0qX/7zJm1x0yb5mTUqDLWr3fgcnl45hnwlDjIffBPGG3dGtyjkR2f/IiMRH1USBeiUl8REQkyfZMSkRNW7IJjTv/63PFn/BhfVe3cbUNMHMdyNlCVVwZYmr4T0oFkrr9+KomJZsrKqli69BgQS54DvnNDzEn+Ebwvi8Dmhh4WyEgM5TOLLnl5/ktD1Z3g09OhZ0/Yvh2cztr9aWm1/y4pyWH//i2cdpqNY8dq1/T2lPTFU9K3wT2bSNc0b+lqVOorIiJBpqRbRE6Yf33uFU2uz42hJ00l3Hv3Otm5swx/eTl88QXYbJCcbAVsmJISmPx3ExUeA+kLLgfgqtf8t40zwbvTu07i3VT5+H33+dc9b40TXdNbRKTL0rQDEWknJd0icsLcrpbW57bXbNu+Hbp1qx2ZffjhHJ59dgv+taVhypR1AMyYMQwAo82Cy1kecDmrYzEWil22LpN0z5kDF14I553nv/7RRxAfX7veudPppKysDIfDgdNZvU63CafTid3uf5FOeE1viVr33nsvP/rRj8jKyop0KCKdTyinHdjs/vto6r5t9sbbRaRDUdItIkHTmvW5x4/3/796dPaOOzK58srG87aTk2P54x//g897rNlRdOcV2VQn7J1dejok1jnBMHw4JCTUXs/JyWHLli3YbDZMpurScdi9O4f09BFhjVXC79tvv+Xiiy8mNjaWyZMnc9lll3HBBRcQGxs9VQxLlizhb3/7G1999RXx8fGMGjWKhx9+mFNPPbXmmPHjx/P+++/Xu92cOXNYtmxZuMMVqRXKaQfJqf6kXaPoIp2Wkm4RCYv588FigcsuA7O5dnR24EArAwdaGx1fWlrl/4evstlRdLfLRVdJup1OJ4WFtZO1Cwvh2LHa0evApeNwyimZEYlXwmvVqlV4vV42btzIa6+9xi233EJeXh4XXnghP/rRj/jhD39Ijx49Ihrj+++/zw033MA555xDVVUVd999Nz/4wQ/48ssvSahzBmn27Nn86le/qrleXZ0h0mklpyq5FunElHSLyAnrbgGTAXwB9vk8Xrzlbvr0MRAfD2ed5U+626o1o+idXU5ODh99tJnqEey1a0cTH28iKyuLrKysmuS7dp683+bNTmy2Cvr3D3yCQzoPo9HImDFjGDNmDI888gg5OTm89tprLF++nOzsbM4991wuu+wyrr76ajIyMsIe3/r16+tdf+6550hNTWXLli2MHTu2ZrvVaiWtbgfAcFKpr4iIBJmSbhE5Yend4Lqh4PIeZeXK/9Tu8LnxVTjxuXtw8KANi8XffbtPn+bvz+l0UlRUhn+d7vhQht6hZGZm0r17Rs0I9uTJ/k7vDUcBm5onP3t2FitWND/f15Rkw2irbnpn7LKd4juLzMxMMjMzuf322zly5Ajr1q1j3Tr/z8OCBQsiHB2UlvrLaRuOwP/5z3/mhRdeIC0tjcmTJ7Nw4cImR7vdbjdud+2KCWVlZQGPazWV+oqISJAp6RaRE2axWOjfO5nc3CN4y45Qf8w7DnAfXzPahMtVyJ13mus19GooJyeHjz/2J43eci8GvAGPMxn8o+xdhdVqJTk5lupkOjk5Bbu98Z/xpubJ9+/f/Ci3KclG2oLJQFXNtiv+UgL43+P3Z3edpnWdUc+ePZk1axazZs2KdCgAeL1ebrnlFkaPHs2QIUNqtl9zzTX069eP3r17s2PHDu644w527drF3/72t4D3s2TJEhYFaut/IlTqKyIiQaSkW0ROmM1mIzs7m4ICB0uXrqFuN+wrr8ynrOwrhg0bjclkwm5fx9/+Rk1JdCCZmZmkpPTjppvAW1bE1AHL8ZgK+fOftwFGrr9hCHjdGKr8o+xSX1Pz5FtisEL5Z6sCNq0rtybz7Y+zyUjsGvPnJfRuuOEGdu7cyUcffVRve3Z2ds2/hw4dSnp6OhdccAF79+5l4MCBje7nrrvuYt68eTXXy8rK6NNSOY1IW2nagYicACXdIhIUNpsNj8dCwyWosrL6YjJlcM01UzHXmczdXGMkq9VKSkr1fgun9D+JoqIjeMv8yWBcRTFxcUaSU5OxWLrQUHcQ1S/hP/5++TxqWidhMXfuXF5//XU++OADTjrppGaPHTHC33l/z549AZPuuLg44uLiQhKnSA1NOxCRE6CkW0RCKjY2lvh4EykpKfWS7taz8bOfZVNeXj2KDtdffw2JiWYsFgs2m5LA9qhbwu9PujcCPQGrmtZJyPh8Pm688Ub+/ve/89577zFgwIAWb7N9+3YA0quXPBCJFE07EJF2UtItIlHPZrMdH9Fufi6ztF7dEn7/HO5jQCyQF9G4pHO74YYbWLNmDf/4xz/o1q0b+fn5ANjtduLj49m7dy9r1qzhkksuITk5mR07dnDrrbcyduxYzjjjjAhHLyIi0j7GSAcgIp1VBeDA4fBfCgsLKSwsxOl0tnhLCT1/CX8KUH2xoU7xnceHH37Iddddx8iRIzl06BAAzz//fKP50+H2zDPPUFpayvjx40lPT6+5vPTSS4C/Muadd97hBz/4Aaeddhrz58/n8ssv57XXXoto3CIiIidCQ0UiEiL5wEFsNv9a0tXLFDXXQE0iy1vuxufx+udw19nuq3B2uU7xHdmrr77KtGnTuPbaa9m2bVvNclqlpaU89NBDvPnmmxGLzefzNbu/T58+vP/++2GKRkREJDyUdItIiKQBPWvWkq7WXAO1anl58L//1V7fvh2qqpo8XNqh4WsM4C1z4/j4GwwxruNbDFx33SnExhpJT01mQE9l3R3B4sWLWbZsGdOnT+fFF1+s2T569GgWL14cwchERES6JiXdIhIisYCpXfOvly+Husvunnde/f3bt0O3OkuFpaf7L9J6DV9jPws+1zn4XNVnOEzct0BN6zqaXbt2MXbs2Ebb7XY7JSUl4Q9IRESki1PSLSLt5nQ6683RLiurwr8ElQl/0t0+c+bAZZfV33b0KIwf7/939f+r3Xcf3H9/ux+uS6p+jY8cgcOH4f33oaICXnih7mh2+06aSGSlpaWxZ88e+vfvX2/7Rx99xMknnxyZoERERLowfZMSkXbLyclh8+bNbNy4EYCzzhoJbAX6AH3bfb+BRq5LAyyN+tFHEB+vUe72qH6NnU4nZWVlFBY6cDo9dY6IRY3VOqbZs2dz8803s2rVKgwGA7m5uWzatIkFCxawcOHCSIcnIiLS5SjpFpF2y8zMJCMjg2PH/Gs4//CHP2L+fDf+ke5QqDh+KQTMnHQSJCRUzxNvea64NJaTk8OWLVuw2WyYTNXrdfvwnzRpeQ1liT533nknXq+XCy64AKfTydixY4mLi2PBggXceOONkQ5PRESky1HSLSLtZrVaiY2NrZnrm5xcvfSUp9nbtV8esB/YAhhYu9bfGV0d0dsvMzOTfv36kZ8Pe/dWr9ftoXp6QH4+2O2RjFDaymAwcM8993DbbbexZ88eHA4HgwcP1px8ERGRCFHSLSIdSDqQdPzfpprO6K3piC6BWa1WrFYrv/2tk4ceKquzpwLwsGKFk6VLEyMVnrTDkiVL6NWrFz/72c8YPHhwzfZVq1Zx5MgR7rjjjghGJyIi0vW0Oek+ePAgBoOBk046CYDNmzezZs0aBg8eTHZ2dtADFJHolZcHBw/CgQP+69u3h/oR/R3R/dTkK5jGjs3BYNgC2HC5PCxd6p+nP2pUDjAiorFJ2yxfvpw1a9Y02n766adz1VVXKekWkehXVACOAM1cbHZITg1/PF2JXvuQaPO31WuuuYbs7GymTZtGfn4+F154Iaeffjp//vOfyc/P59577w1FnCIShRouO/Xgg5GLRU7MmDGZZGX1A/xd6Jcu9c/THzUqM5JhSTvk5+eTHqC7YM+ePcnLy4tARCIibVBUAPfMgqrKxvvMMfDgSiV/oRLJ176TJ/ttTrp37tzJueeeC8Bf//pXhgwZwsaNG/nXv/7FL37xCyXdIl3InDkwYULtEl5vvAGXXhrRkKSdqsvMAWJiqvDPzUel+x1Qnz592LhxIwMG1G+Et3HjRnr37h2hqETkhHTyhKQeR2ngpA/82x2lne85R4tIvfZd4ERLm5PuyspK4uLiAHjnnXe47PhiuqeddprOoIt0MenpUJuTVVBaWoh/ne7qRmom9u1zMny45gSLhMvs2bO55ZZbqKys5Pzzzwdgw4YN3H777cyfPz/C0YlIm3WBhES6uC5woqXNSffpp5/OsmXLuPTSS3n77bd54IEHAMjNzSU5OTnoAYpIR5HHNde8Rm33cv+c4IULc1i0aETAtbelbQ6VwYEiiDnJ/7f2yyKwuaGHBTJ0XkOOu+222ygqKuL666+noqICAIvFwh133MFdd90V4ehEpM26QEIi0tm1Oel++OGHmTp1Ko8++igzZsxg2LBhAKxbt66m7FxEuqJ01q6dyl//WsGaNUeBIwC8/noqr79eyN13W3nwQZUqt9ehMhj3rAOXy0XqL8YBcMVfSgB/QvX+bFtQEu+8PNi9u/b69u3QrRs6adKBGAwGHn74YRYuXEhOTg7x8fEMGjSopkpNREREwqvNSff48eMpLCykrKyM7t2712zPzs7W3D+RLi2W8eNTsFj+w4ABW4C049vfBmDMmCxAa2m317dFDoo+XIHXWdRoX7k1mW9/nE1G4omvw9ywOV71fP377oP77z/hu5cwstlsnHPOOZEOQ0Q6o640x1yi3qEyKHY13h5NlYDtWmvHZDLVS7gB+vfvH4x4RKSDq9sFuy6dlDsxbpcLr7MIgzkeQ2zta+mrcOJ1FuF2uahufnYi5syBSy6Bdev81y+7DMxmjXJ3NBs2bGDDhg0UFBTg9Xrr7Vu1alWEohKRTiHUc8xtdv/9NHX/Nnv77zuSOsKJig742h8qgwl/Aren8b4YI6y4FE5NiXzy3aqk+8wzz8RgMLTqDrdu3XpCAYlIx1a3C7YEnyHWijGuNrn2Ar6qY0G7f7vdicFQRo8eDgD69i3EbDYff0/1vnYEixYt4le/+hVnn3026enprf78FhFplVDPMU9O9Sfu0Z6gtkVHaYYXqdf+BJL9YlfghBug0gszX4M4E7w7PbKJd6uS7ilTptT82+Vy8fTTTzN48GBGjhwJwCeffMJ///tfrr/++pAEKSIi4ZGTk8OWLVuw2fyJ/brjQ95ZWVlkZWl6QEewbNkynnvuOaZNmxbpUEQkGDrg6OMJS06NjiQ0WDpSM7xIvPYhTvbdHn9yHvVJ93333Vfz75///OfcdNNNNV3L6x5z8ODB4EYnIiJhlZmZSb9+mh7QkVVUVDBq1KhIhyEiwdLWhKQjlDGLNNTZTrQ00OY53S+//DKff/55o+3XXXcdZ599tuaKiYiEQHcLmAzgrXBSd4aur8KJyeDfHwyaHtDx/fznP2fNmjUsXLgw0qGICAQnCW5tQtJRyphFQqB3RQE9PI1/14pNdiCyP/dtTrrj4+PZuHEjgwYNqrd948aNWCxB+tYnIiL1DOhpYe64ZL759ggvvLANgOuuO4XYWCPpqckM6Km/v+LncrlYsWIF77zzDmeccQYxMTH19j/22GMRikyki6ibZJcWw1MPgKeq8XF1kuCgdV/uSGXM0vmFseqid0UB7+6ehcXX+OffZYhhf8lKSI3cz36bk+5bbrmF//u//2Pr1q0163J/+umnrFq1SmfVRboYh8NBUZED8DfdKioqpLLSjMViqZkTLMFhs9m4/aZsCgoc/OmZNQDct+AaEhP1ekt9O3bsYPjw4QDs3Lmz3j41VRMJseZGmhs6ngQfikltsvtyNDSAaqStc8w7crl7R469KeF6TmGquuhh8f+e9PCUBky4ASy+SkzlpURytLvNSfedd97JySefzBNPPMELL7wA+OcArl69mp/85CdBD1BEopPD4WDFihXk5h4B/gPA008fIS7OSHJyMtnZ2UFLBJ1OJ0VFZfiT++pvJSacTid2ezR9Ewktm82Gx2Ohemmw5OQU7PZ2rfwondi7774b6RBEuq7mRpqb0Fz35WhoANVIW+aYd+Ry92DGHi3N8ML5foSp6iIj0X9i6tBOYE/Tx9njTvihTki7vq395Cc/UYIt0sW5XC6KioqOTyvxzwHu3r0HPp+boqIiXC5X0JLuDz/MYcOGLfiTTQ+wEYCPP87h8stHBOUxRERETsShMnAWw6CWD61RUA7EhyqiEGrtHPOOXO4ezNijZRm0jvx+NCMjETIymj8mNSE8sTRFQyQickLi462Afz6xfyTWxLFjwVs3GuCDDzJ59NF+mJKMGG1eoBsAb3x2OqeMacecN5FO7sMPP2T58uXs3buXV155hYyMDJ5//nkGDBjAeeedF+nwRDqdQ2Uw4U8wyAFvtOF2pe6QhSTRppN3526rgnI4XNB4e7u+0xUVQF50r6LVqqS7e/furZ4HVlxcfEIBiUjHcdQNZT4wJflHtHMd4K0Cd5C/RMyda2XspVZu+BwqfQDXAbAB2PCXKJ3zJhIhr776KtOmTePaa69l27ZtuI//QpaWlvLQQw/x5ptvRjhCkc6nuRLxsIqWMmaRFmS/DtsClHy3+TtdW/ooRFCrku7HH388xGGISEeTdxRe+AJ88SbsPzgLgD/sAK8bDMdg9lFISQnOY6WnQ6EJ3B858FU2bu96LMZCscumpFsEWLx4McuWLWP69Om8+OKLNdtHjx7N4sWLIxiZiNTlMsTgSQhyEnyiZcydsXGYRKVKb+Dtbe5j0Jo+ClFwwqlVSfeMGTNCHYeIdDDfucDjA0OAdaO9Pv/+YHKWO3B8vAKvs6jRPqM1GecV2VQ3GBPpynbt2sXYsWMbbbfb7ZSUlIQ/IJEupNhkx2WICdhF2Y2Z7H73UhjTvebYFUmpNd2Xm+pe3qOtK0K2t4y5Izc9ixY6aVGrmaoLrznm+NrZYfDz22HQkIi//u2a0713715Wr17N3r17eeKJJ0hNTeWf//wnffv25fTTTw92jCISheIsFozWZLzOInxV9edwG63JxFmCu2602+XC6yzCYI7HEGut2e6rcOJ1FuF2uVDSLQJpaWns2bOH/v3719v+0UcfcfLJJ0cmKJEuIjc2lQmnrKSHp3HiVWyykxvb+It/dffloKzTfSKC1WSr4TrlJnPT65RHc7l7e5ZGi7aTFg1PAoTz/Wim6mK3207uP8P0WqT3iXjCDe1Iut9//30uvvhiRo8ezQcffMCDDz5Iamoq//nPf1i5ciWvvPJKKOIUkShjTbBhG5UdsNzbEGPBmhCaBNgQa8UYV3vfXmiU9It0ZbNnz+bmm29m1apVGAwGcnNz2bRpEwsWLGDhwoWRDk+k08uNTSW3FesB1x3FzkjsJH1Jmks8TWa44V6w+0f6Qzb6G6zR5rYujfb1zujqDN6W9wJC8340UXVRGaCBWmfXrnW6Fy9ezLx58+jWrVvN9vPPP58nn3wyqMGJSHQzxtkgTqPLItHkzjvvxOv1csEFF+B0Ohk7dixxcXEsWLCAG2+8MdLhiXRKzZWIxxph+aXQ09b4Np0i0a6rudFyT5U/yevXlkXV2qioAN89szAEiMFnjsHQ1tHm1pTqR2sjr0i/F4EcPyFiKYYhdcZLmqoC6UzanHR/8cUXrFmzptH21NRUCgsLgxKUiEhD3S1gMoAvwD6Twb9fpKurrKzkoosuYtmyZdx2223s2bMHh8PB4MGDsdl0gkwkVKKmRLy9OsCSS61RcLiU1CYSTUNVpX9/sEdzW9PIq7NpTzVBnZMTg6i/tJ7LEMOEU1aSG5va9j4GHaRjf5uT7qSkJPLy8hgwYEC97du2bSOjpVXJRaTTCHrjlxakd4PrhoLLe5SVK/8DwPU3DAGvG0OVf79IVxcTE8OOHTsAiI2NZfDgwRGOqGM6VNaBkyeJmOoS8YY/P8Uu/yXgz08wG2+1976idaS2HUrdNFvY39J+aYX2zl1v5uSExVfJnyaW4spIbfR70uLf4xPt2B8mbU66r7rqKu644w5efvllDAYDXq+XjRs3smDBAqZPnx6KGEUkClWf1T9QWMW4cf8A4P33f4TNZg7JF1OLxUL/3snk5h7BW3YEgLiKYuLijCSnJmMJcuM2kY7quuuuY+XKlfz617+OdCgd0qEymPCnpk8otmn9WOly2vTzE8zGWydyXx1hyaUgnZyIO3IQvjl+pbQYnOVgtbV/bnMnqRBok2A13GvAHgcuak9SARSUwy/egIqWfp/a27E/jNqcdD/00EPccMMN9OnTB4/Hw+DBg/F4PFxzzTX88pe/DEWMIhKlMhLB5oPKb/3LeA1OBnuIPpNtNhvZ2dkUFDhYutQ/xeX6668hMdGMxWJR6azIcVVVVaxatYp33nmHrKwsEhIS6u1/7LHHIhRZx1DsCpwwQTvWj5Uup00/P8FMXkKUCAGRX3IpiCcn+v71kZYPau19tqVCINwnLTrgyYDs12FbXOuP72h/j9ucdMfGxvLss8+ycOFCdu7cicPh4Mwzz2TQoDBPxBeRLsdms+HxWKheGiw5OQW7vV0rH4p0Wjt37uSss84CYPfu3fX2GQyGSIQkIu1RN2mKZJls3SWXWhpxDsX82lCeUDiR+2ztXO5wn7RozcmASFcuBFDpjXQEodXub6t9+/alb9++wYxFRERETtC7774b6RBEuoRAc033FDd9fO+KAiyHSqG6a3NLI5F/qDMqG6l1nutq7YhzBOfXehLsuAwxWHzBnZ8e6L22FEOLQ47mmPBXCbR0MiDSlQuRFMweCm3UqqR73rx5PPDAAyQkJDBv3rxmj1XZmoiIiIh0Zs3N3Q6kd0UB7+6ehWVXO5PBSKzz3FBrR5zDPL/262KwdveXGXdLS2VS5kpsFfUTq4Gug/zu21aUlgfQ1Hs95Fj9DtyNnGhyG6oEsW7lQjge77h87CQ1cULEZYih2BTikfdg9lBoh1Yl3du2baOysrLm301R2ZqIiEjkffjhhyxfvpy9e/fyyiuvkJGRwfPPP8+AAQM477zzIh2eSNRrrmMywObc1ifcAD08pUEffQ2acC251FRSV1kJMTGAv3FWqdu/2ZNgpzIptcUR5Vvegq9ttU211vw8lWJX/eTJcgh4qvWhFpTXdjlvbp5+s5pKblsj3AliWx6vnT8vR+JTmXrKSnp4Gv8MhGWd7nBPU2igVUl33VI1la2JiIhEr1dffZVp06Zx7bXXsm3bNtxu/zfY0tJSHnroId58880IRxjdwr0cokSf5kaxzQboXVlAYmUpQxrsC0vi0JQTSZzDURLeyqZjqdQmu9VrN/fwtDCiTP2mWtWXugoK2xbuziPQs8D/7+amDDTn62Jwxfv/3eZVXcKdILbweAe27CTf1gdHJdhioOc1vwQMVHXrjj0OUqv7dbbw85Ibm0pukBZtizHCEQd8cfx6tC/p2OY53atXr+aqq64iPj4+FPGIiEgTnE4nRUVlgAOAoqJCKivNWK1WrFZrUB8rL89/aSg93X+R6LV48WKWLVvG9OnTefHFF2u2jx49msWLF0cwso6hejlErdPddTU3spnqLuDt3bOaLJGdcMpKcmNTeXwSfK9H7T7LIWBPMw/689v9//9D+0qgW5M4N7ve8fGS8IbHFJRB2RGwx0Kf0lbMYW5Ka5uO1WHxVdLDU0qxqel52q0tSy4220ls5VxvlyGGezbbyd3ewn22ENf0d+zkxvqvB325wdJi+ObrxttbUZVQ92QAHH//W7hN378+QsNOXtU/70XxqTXP7VAZFBc0vn1rTlbGGAM3UzMb4J7zoH8S+Aww53X/cZVemPla7XHRvqRjm5PuO++8k5tvvpkrrriCWbNmMWrUqFDEJSIiDeTk5PDxx1uo7t7+xhvriIuDrKwssrKygvpYTz7p5KGHnI223323lQcfDG6CL8G1a9cuxo4d22i73W6npKQk/AF1QIFGykSg+TLx6iQxl1S+1wOG1h3QOxbwJrXS+5xwbIdiUimObzyK2CMGaMX64dD8PPUW5zA3FVcZOFvTdKwJubGpx0e821+WXJnU+D56VhaT6Cmn1GSjMKZ2ne7m7rN3RUG9+/hF319y1cnlJHa38Q3deWFH4Ptwe/xTEr5X54TGCZ3Ee+oB8FQ13m6OgQUPN1n10PBkAPjf/4/Op83jzzU/755UNudCYlHza2ovu6T5+1v+Q///q5PqalU+WPRh7X001eU82pcQa3PSfejQIV577TWee+45xo8fz8knn8zMmTOZMWMGaWlpoYhRRESAzMxMUlL6cdNN/uuXXQYJCQR9lBtg7Ngc3O7NLF26EYD580djsZgYMyYLCG6CL8GVlpbGnj176N+/f73tH330ESeffHJkguokmh0pjNIvetI+DZOraimV37Xr/urOEW5yfy87PnMMhgDJktccw263ncqC+rcx+KCnzf/vhslKtRgj3D26+fXD39oL+Jqfu9zcyK7PHIMhwChrdan+IEf7EvZqwShLbnQfbSzarWmG1/D5f+NPZuefspLcACc9qt3yVu399PCUEmOEFccTzVI3HDbYOWLx395+GM5vLphACTdAVSX/PhSDc/pKrJWlHHWDswqcbvjbrsAnFNwe2LAfrm7u8VpQ/dya4vZAaUXzx1SXqDeXVLd0H9GszUm32Wxm6tSpTJ06lcOHD/PCCy/wxz/+kYULF3LRRRcxa9YsJk+ejNFoDEW8IiJdVmmplW+/rU2wv/0W4uP95d7BzrvHjMlk0KAMli71D89cf/1UEhPNIUnwJbhmz57NzTffzKpVqzAYDOTm5rJp0yYWLFjAwoULIx1eqz311FM8+uij5OfnM2zYMH7/+99z7rnnRiye5ub5RntZo7RNTEkTyRXgbsVX50Bz/5srb3YZYig226mMSeWaUxp33objydI/25d0Vnr9I4XNWfRBy/fT3IizI9bOmpjUemXKh8ra3nAumrW2yqE5jRL344s+pQJ96kxPGHKshaS7GUs3wc74urPjjz+2yZ/s9zhW//0rNtl5YceJJd2t8d2xpkvIq39nAp3UDJaWuqeXYCeUw8ftXqcboFevXpx33nns3r2b3bt388UXXzBjxgy6d+/O6tWrGT9+fJDCFBGR5cth0aLa69VNqO+7D+6/P7iPZbVaSU6OpbqUPTk5Bbv9hD4yJEzuvPNOvF4vF1xwAU6nk7FjxxIXF8eCBQu48cYbIx1eq7z00kvMmzePZcuWMWLECB5//HEmTZrErl27SE2NTKOq5ub5RntZo7SNqbzp5CqOJkYYj5s/Ek49s/HPQqDy5mrFJjsrklIpdsF+Uyo0M1oaKU2N/NcdOd2cC+dSO7e3LUuqNaVnZTFDaDx3ueGIbUdpqtXaxL25qgI35hZ/DhtqcpQef8J51YCHQ7K+eV11T+zEGGHFpf4qDah9v4KVdAeqStpzLJVHmvsdjE+NvqT78OHDPP/886xevZr//e9/TJkyhddff52JEydSXl7Or371K2bMmME333wT7HhFRLqsOXP8JeUNqbGZ7NixgyFDhmA0GjEYDNxzzz3cdttt7NmzB4fDweDBg7HZbJEOs9Uee+wxZs+ezcyZMwFYtmwZb7zxBqtWreLOO+8MezyHytrfwVg6lkNl/hG59hrSE1KbSPaC2bk5nFpK2KpHZ295q7bpFdRPuJstTQcCLTrsxsSKbx4gNkCC6TLEsOLHK3liTypVLTTVOlTmL79vapS1WnUZfktVAeHQVFVBz8pi+rrz+FX+sjbdX0vJft+KfH7R95ckesprtpeabNg9jnavb96cSq+/VPzUEJwcafaETwR/B9ucdE+ePJm33nqLU045hdmzZzN9+nR69Khtz5iQkMD8+fN59NFHgxqoiESPvXud7N/vxOVyUlx8FMgHYNu2AwwZkhiSbtqizuHStDPPPJO8vDxSU1M5+eST+eyzz0hOTmbw4MGRDq3NKioq2LJlC3fddVfNNqPRyMSJE9m0aVOj491ud82yaABlZWVBjSdYI3YS/Vo7/7jCYCbW1zgR9JljSO3VujWtG44cWw5Vb4/gsmNNaEtZdXXTq4aaK02P8VZSaYyhZ2UxKw48UPPaxtH0L53FV8lb/ymlqomqgOrqE2j8+9vcqD2G1BaT81BrKr4YbyXLDiwOyWh0oMS6pRHw1naOb8otb/lPjvzlxxB7PCNt6eRmYlzLSzq2e131EGtz0p2amsr777/PyJEjmzymZ8+e7Nu3r9X32dZ5Wy+//DILFy5k//79DBo0iIcffphLLgncEu8Xv/gFy5cv57e//S233HJLq2MSkaY9/HAOzz67GXgNKAK+Bxi4+eaVTJ7cjzFjspg0Sc22RMIlKSmJffv2kZqayv79+/F6I/iN8QQVFhbi8Xjo1atXve29evXiq6++anT8kiVLWFR33kWQResXOAm+1r7X2X0XciSmB/NHQp9EatYpNrRyTeuAI8fHlxN7t87IcWfT0kj/EL4OeDLjRDR8T1sctWcllcdfe7PBfxIhnHpWFvPq3nntLis/0US4LovPfzLkRDvHN8ftgStfbd1JjjgTnJbc8pKOoZwXfiLanHSvXLmyxWMMBgP9+vVr1f21dd7Wxx9/zNVXX82SJUv44Q9/yJo1a5gyZQpbt25lyJAh9Y79+9//zieffELv3r1b9+REpFXuuCOTSy/NYMqUUqACuBwws2NHPDt2WLn7biuTJkU4SJEu5PLLL2fcuHGkp6djMBg4++yzMZlMAY/93//+F+boQuuuu+5i3rx5NdfLysro0+fEl18SacqRmB7sjB9Ez0wY1Mqco4eldoQuGA25wqV3RQEDXQcjHUa77Cn2ry9eV1tH7euOegdjvfCWDD62t939BG466XY+SxgS9BM2bZkWEWuE5cfnau8pbrmrOTSfcNdd777uPP1onK/fkoh3xWnrvK0nnniCiy66iNtuuw2ABx54gLfffpsnn3ySZctq5zccOnSIG2+8kbfeeotLL700PE9GpIsYONBKSkos4P9L+N57p9KtW+2fE5VAi4TXihUr+PGPf8yePXu46aabmD17Nt26dYt0WO2SkpKCyWTi8OHD9bYfPnw44NKkcXFxxMXFhSu8gAJ1q5aOKxTJVUZi7Qid5RA1I9vh1JpmaA2Pb2pUuCN45LUCenpKqTsk19YTCMt/WLuU1Z7iVCa8dmKjvs39bAHcXvCnNsXXUHV38mCMQrekbjO0gnIoc/tPcvQMYvuQRuvdh0g4/oZHNOlu67wtgE2bNtU7ow0wadIk1q5dW3Pd6/Uybdo0brvtNk4//fQW4wj1fDCRzm74cLAHp5pJRNphx44d/OAHP+Ciiy5iy5Yt3HzzzR026Y6NjSUrK4sNGzYwZcoUwP+5vmHDBubOnRvZ4AJ4fBKc27tjjrx0ZQG7Gx+fT9rc/OMTSWYyEo//nJxAo7a62pJEt7YZWl3NjQpHu2CdMEhNqE36eligKD6VXE/j9z/WCKsvbXnN9OqfrXPKdwa9QVnd+6v7nl43FM4w2fHsi8Hkad/rUXfEuVr1yPOhMrj8rx1nGk5zzyWUIpp0t3XeFkB+fn7A4/Pz82uuP/zww5jNZm666aZWxRHq+WAiIiKhVLeR2vvvv09FRUWkQzoh8+bNY8aMGZx99tmce+65PP7445SXl9dUxUWT7/VQwt3RtKY5Xig7jReUN1xBue36VhXw3p5ZAZOoQEl0e0ra54+kxRH5to78zx/pX0f6RLX0uME6YbCnuDYhq1ut0OjxGiRt789ofFxBOXzzHSz6MJW9ntBOgan7nl41BIampsKQleBosEb3/w7S488tJ/9NjTi3Zi32YL3ngQQ6eVZQDrEmqAgQU4yx/pSDcC4tF/Hy8mDbsmULTzzxBFu3bsVgCLQAQWOaDybSMeTlwe7dtde3b4du3dTVW6QzNVIDuPLKKzly5Aj33nsv+fn5DB8+nPXr1zc66R5qLS01pLLyjikYzfFO5L0vdZ940p1YWdrkqGWw5oX3aSEZac8c4tN7Nt19utllxUxm9l97L1XduvPdMZi/yU6uOfR1x9UdtquXH6upVmhBU8d9kRD8GFstObVRo78eNju+l2IwVDU9laKpn/XWruzQ3Ht+Ip3im3v8WCOsnty48qC5peVCrc1J99atW4mJiWHo0KEA/OMf/2D16tUMHjyY+++/n9jY2BbuoVZb520BpKWlNXv8hx9+SEFBAX379q3Z7/F4mD9/Po8//jj79+9vdJ/RMB9MRFq2fDnULUoZP97///vug/vvj0REItGhMzZSmzt3bkTLyZv7Qlc9l/HUFI1yd2aPT/IvURRoruqJjJB5Elo3ZzwYI4T3jYWHPmr77eJM/q7szdlr6UNubGpNuW5BOfz3SPMxpybUHy2umxA1LOuPMcKKH/qPu2K9nf3b6iSMxzOYYK6t3dToefXyYx3xd73Fk0PJqRge9I+AF5T7TwhV8yTYWZGUWvuzXlRQb6TcWexfXq+lKRcN3/O6Kqrg6r81vwRYU5o7eVbh9f++9rD4qxWaSuzD+d62OemeM2cOd955J0OHDuV///sfV111FVOnTuXll1/G6XTy+OOPt/q+2jNva+TIkWzYsKHe8l9vv/12zRJm06ZNY+LEifVuM2nSJKZNmxaVZWki0nrTpjkZNaqM9esdAFx0USEmk5n+/a2A1gWXrqszNVKLFoG+0NWdQ9unFDJMwHdAK5eKko6lzU2cGiQlNRr8fFQmtW7OeEsjzS2JM8Gkgf6Lcy/Nloo/PglcGbXXe1gg9bvWPUbdngapCS2fKGg4Cly/FDuV6jqAHhZITYQvCmB/g3OIdX8X+x+FIcfnybd2zv2Bn9xO31P9Va0F5bDzCNyzOfTNx6q72Lfo57dD+vGq27yD8Ie2z/9+fBJYB7YioTw+Al77ygdQVAD3zII6I+KD8K9n31RPgLqaqxBobcl+WxWUR9dc8zYn3bt372b48OGAf73ssWPHsmbNGjZu3MhVV13VpqQbWp63NX36dDIyMliyZAkAN998M+PGjWPp0qVceumlvPjii3z++eesWLECgOTkZJKTk+s9RkxMDGlpaZx66qltfboiEkVKSnLYv38Lp53mH27Yv38dAElJWYDWBZeu7aKLLgLo8I3UolWjxkx1ExhzDDy4Uol3VxYgKakR4OejpTnjcabGy121xTNnHST2VDtpidVdwJo/flAPGmdclXZ/7AGek9ccw9If2+mWVj8xqrs0WkNNjVy2tmS7WqDfxfOP73NjJrvfvS3eh7tnH+g3CPA/7Z4FkLu99TG0V/W88KP5dryPxWBs6udl0JAT/nsyqAcQrBFcR2ngn21OfDpDW9//1ipzR0/CDe1Iun0+X81csXfeeYcf/tBf99GnTx8KCwvbHEBL87YOHDiA0WisOX7UqFGsWbOGX/7yl9x9990MGjSItWvXNlqjW0Q6n8zMTPr169dou9WqUW6RaqtXr450CJ1Ss42Zqir9X0qVdHcqdZtoNedQGTgPlDKoiaSkrT8f1R3xA43+tVbfvz5SP9m3NZ1AYzJD6Xf+Ewd1Y0xO9d8+wOi90WbntADPpy3Nxtqrud/FOKr44zf34jGacRtiiAtwnBsz3d0Bnm+YZCQCiU2/tkGpnDHH+O8nwtT3olabk+6zzz6bxYsXM3HiRN5//32eeeYZAPbt29fuBifNzdt67733Gm274ooruOKKK1p9/4HmcYtIx2O1WpVgh8mhMjhQBDEn+SuHviwCmzu8nT6l9ebNm8cDDzxAQkJCo2U1G3rsscfCFJVIdGpuNLauhk20Aqme+z/I4S+1PdHHb1iu3dRxjlg7PnPgBlg1qpN98P//+l9CQR68/Cx46typpwp+d2/gio0Azbda0uqRy1aW47eHyVvF0Sm/4LDRykn/+B1GT1XNvjiqiPtDE883FJp7nsdH209I3VL0uvcd4ZOAWk6xvjYn3Y8//jjXXnsta9eu5Z577uF73/seAK+88gqjRo0KeoAiIhJeh8pg3LMOXC4Xqb8YB8AVfykBwGKx8P5smz5Eo8y2bduorKys+beINK16NParoqbXU67WUqOl9nRCb+1ocPPHpWKoXAlf72x+vm9pMSyZ12RpcD3hrNhoYzl+eyStXUaSyew/qRBInefbnrL4VgnG82yuSiFIpejB1vDkUVAdP4nRqxzOdNf+/tadz9/a6RnhHIlvc9J9xhln8MUXXzTa/uijjzbZKVVERDqOb4scFH24Aq+zqNG+cmsy3/44m4xEW4BbSqS8++67Af8t7dfa0VDpmKpHY9+f4V9n+Ja3IvP4LR5XWUDGsQCjpKbjI5mOFpa4dZa3LuEOt2bmCDdM/k/od7GphLuBkJXFt+F5NqmZMv9oGNGGwI34TjjhDlQhUFoMTy+GqkpSgbV1dnnNMeyet5LK4x3Xi131G+7VVWyyc/vk1LCOxLc56T548CAGg4GTTjoJgM2bN7NmzRoGDx5MdnZ20AMUEZHwcrtceJ1FGMzxGGJry/l9FU68ziLcLhegpDuatFRSXs1gMLB06dIQR9M5NPwSbjlEs92fpWPKSITvNTN3undFAZZDpXCswY5QJztFBXBoHzz1QODEsXqUNJo0TJJKi/1Jv9UG9u6129s41zhcv4uhaujVotaU2bejzD+oWhhtH9TXDsmNd7VbUQG+e2Y1P32iAWNVJafFlUKq/3Uyfdeg4V4dLkMMJfEraxsNhkGbk+5rrrmG7Oxspk2bRn5+PhdeeCGnn346f/7zn8nPz+fee1vuGCgiIq2zd6+T/fudjbb3729l4MDQzm83xFoxxtUm117AV9Xwm6dEg4Yl5Vu3bqWqqqpm1Y7du3djMpnIylKX/7ao9yXc1EKJZxQ0LZLgqumSvauZ0uDjHZuLTU2vvd3mn4/mSpKr1Z2vHUnVCWNpcdMnCBoyx8D1C9v0MK3+Xexomiv/j6ZVEVo72h6kefoFh0tJPcH3N41SaKLhnsVX6d/fzo7r7dHmpHvnzp2ce+65APz1r39lyJAhbNy4kX/961/84he/UNItIhJEDz+cw7PPbgY2Ht8yGjAxe3YWK1YogRK/uiXljz32GN26deOPf/wj3bv7R5e+++47Zs6cyZgxYyIVYsfU8Avk9b9seuQuGr4YS1C1qmN9vP99z40NvPb2/JHQO91OpScVCo7fb0ult82VJDfU0nxfawirklpzciCQqkpwOtr/uNUJYHOVAG0RwoZuLWqu/D/aVkVoabQ9iPP0S93hTIfDo81Jd2VlJXFxcYB/ybDLLrsMgNNOO428vLzgRiciUUmdrcPnjjsyufTSDKZM8Y8wr107FZvNTP/+6uIugS1dupR//etfNQk3QPfu3Vm8eDE/+MEPmD9/fgSj60DC0OhJosOJzBmue9tAa2/P3A5sr3+bljqit1reQUjHfzIIQ/0TQQCVlVCY3/r7a+uIfFtODgRbdQL40KqWm8k11UzNHON/jTrT73kkTyAEY/56J9bmpPv0009n2bJlXHrppbz99ts88MADAOTm5pKcHMxifhGJRupsHV4DB1pJSYmleg71+PEp2O1t/tPdJt0tYDKAt8JJ3aa+vgonJoN/v0SvsrIyjhw50mj7kSNHOHr0aAQi6qD0BbLLaKqJVmvmDjd12z3FTTdna6kjeqvVTTQbJoitGYU2meGGe2uT9XBWbFgTgjNdIzkVGNL8fS14GGJiGu+z2UP/ex7OSgSdKIxqbf7m9vDDDzN16lQeffRRZsyYwbBhwwBYt25dTdm5iHRe0dDZ2ul04nQ2nuesdbyDY0BPC3PHJfPNt0d44QX/XOHrrjuF2Fgj6anJDOiprDuaTZ06lZkzZ7J06dKaz+VPP/2U2267jR//+McRjk4kOgVsotXKFhYRa8BVV8MEsaVR6J/fHtmlpuw9gteR+0S6e7c0Lz7vYPvjak1swZyX39VPFEZ5b402J93jx4+nsLCQsrKyeqVr2dnZ+rIr0gVEQ2frnJwcNm/ezMaN/nnOo0ePrmkSpUZRJ85ms3H7TdkUFDj40zNrALhvwTUkJpqxWCzYbOpcHs2WLVvGggULuOaaa2rW7jabzcyaNYtHH300wtGJSFRI7+NPwCJZjhzMjtyh6u7dXDVBazUXWzQ0w2tKBH82PAnNNCas48BPbsdyUh9SEwLE1VKVQZgT9HbVKJpMpnoJN0D//v2DEY+IdBCR7GydmZlJRkYGx475H2/q1KmYzWad+Asim82Gx2Oh+gRKcnLoy9olOKxWK08//TSPPvooe/fuBWDgwIEkJCREODKRDiZSX9qbe9xgilQ5sskMpd/BN1/X3x7tDQlDMVocycSwuaQawvezESCOHlUw7XsPk34sn9992/R8/f/b2oevdw8K3CMhytY3b9c3qFdeeYW//vWvHDhwgIqKinr7tm7dGpTARESaYrVaiY2NrRlxTUlJwWxWQihSV0JCAmeccUakwxDpuCL1pb2px8072HzDsLY60XLk5hJGkxmm3+T/f91u/6XF8PRi+F2A1Y664rzjuu919brm1ay22p+BYL8mLZ1wuX5h23822nMCoYk4UoG/mmPYf81C+FPzT6XZHgmRXt+8jjZ/S/3d737HPffcw09/+lP+8Y9/MHPmTPbu3ctnn33GDTfcEIoYRUTqycuDgwfhwAH/9a1bwWyG9HT/RUTkhEVZaaJESDu/tDfXET3O5N8fiscNq/aclPjm6+iadxyuqoLmVD/fcK7X3dIJl/Ys6daen4dm4jBUVTIg9gSWlosybU66n376aVasWMHVV1/Nc889x+23387JJ5/MvffeS3FxcShiFJEoEg2drZcvh0WLaq8/+KD///fdB/ffH/rHF5EuIMpKE6VjaaqrOZzA8pptORHUmmODMZ+4I5wcaE7D3/NgVRO0dT70iVYdFBX4R8qbWx4tHCcKj/88HCpr8LPvAQra8bPfliXvmhPJ3gXHtTnpPnDgAKNGjQIgPj6+ZvmRadOm8f3vf58nn3wyuBGKSFSJhs7Wc+bAhAkwfrz/+nvvQbduGuUWkSCrTigafmFzlPovSr6lGUHvat6WE0GtOTaam3iFU3tOHETLfOjqWJp6vOpl4TL6h+1v1aEymPCnpqs82rRG/dqma8tdhhiKTa04kRAlS6m1OelOS0ujuLiYfv360bdvXz755BOGDRvGvn378Pl8oYhRRKJINHS2Tk+Huj3Thg8Huyo9RSQUouQLmwjQtgSxo49CBxLqEcvWVAiEYj70iWhulNxT5Z9PH8afg2JX4IQbTnyN+ptOup29lj7+xzHZyY1txfOKkqXU2px0n3/++axbt44zzzyTmTNncuutt/LKK6/w+eefa/1PkS5Cna1FotuHH37I8uXL2bt3L6+88goZGRk8//zzDBgwgPPOOy/S4XUsUfKFTTqgKChpbVZH61sQjhNgrakQaGleenvmQ0cba0JU/mzstfRhZ/ygetta1SMhCrT5W/KKFSvwev0zOW+44QaSk5P5+OOPueyyy5gzZ07QAxQR6coOlcGBIog5KRmAL4vA5j6BOYHS6b366qtMmzaNa6+9lm3btuF2uwEoLS3loYce4s0334xwhCJdQEeokGguwaysrJ1GUdeJnjA4kUQ/XCfAOmOFQEMtvQ8ZA8LT06KNjewenwSujPrbOsr3oTYn3UajEaPRWHP9qquu4qqrrgpqUCIiUndelJn0BZcDcNVr/n1tnhclXcbixYtZtmwZ06dP58UXX6zZPnr0aBYvXhzByES6kI5SIREowQzlCQM1KAws3FUHrX0fQv1+tLGR3aAe+NcT64DaVQ/qcrnYsWMHBQUFNaPe1S677LKgBCYi0tUVu+CY04GvsnH722MxFopdNiXd0siuXbsYO3Zso+12u52SkpLwByQiHUuoTxh0hZHktorEyYhoeR9OJI5on8JRR5uT7vXr1zN9+nQKCwsb7TMYDHg8TcycFxGRNnGWO3B8vAKvs6jRPqM1GecV2VTPqxeplpaWxp49e+jfv3+97R999BEnn3xyZIISEekq2jsfur3JZ5TNzT+hNerb8lxaW5ERJa9Pm5PuG2+8kSuuuIJ7772XXr16hSImEREB3C4XXmcRBnM8htjadu2+CideZxFulwsl3dLQ7Nmzufnmm1m1ahUGg4Hc3Fw2bdrEggULWLhwYaTD63ii5AubiESJaJkPXS3KSvZPaI36tjyX1lZkRMnr0+ak+/Dhw8ybN08Jt4hImBhirRjjapNrL+CrOha5gCSq3XnnnXi9Xi644AKcTidjx44lLi6OBQsWcOONN0Y6vI4nSr6wSZB1oLJUOS7UJ8Ba+zMRLfOh64p0qXiD1y7j+KVdv0+heC6Rfn1oR9L9//7f/+O9995j4MCBoYhHREREToDBYOCee+7htttuY8+ePTgcDgYPHozNpqqIdouCL2wSROHoLK4KieAL5Qmwtv5M6G9CrY7QqT8KtDnpfvLJJ7niiiv48MMPGTp0KDExMfX233TTTUELTkQkEIfDQVGRA/CvhVlUVEhlpRmLxdKpEovuFjAZwBdgn8ng3x8qe/c62bmzjOrX+L33CrHZzPTvb2XgQGvzN5aoEBsby+DBgyMdhkj0CUdn8Y5cIRHNJwxClex2lG7z0UivXau0Oen+y1/+wr/+9S8sFgvvvfceBoOhZp/BYFDSLSIh5XA4WLFiBbm5R4D/APD000eIizOSnJxMdnZ2p0m807vBdUPB5T3KypX+53r9DUPA68ZQ5d8fKg8/nMOzz26hes74lCnrAJg9O4sVK7JC98Bywn7+859z3XXXMX78+EiHIhJ1DpWBsxgGNXdQ3sHG26KlTDYcOvIJA5Eo1eak+5577mHRokXceeed9dbrFhEJB5fLxf7cIlxeC8bEngC4Y3vg9rg5mluEy+XqNEm3xWKhf+9kcnOP4C07AkBcRbH/BENqMhZL6Ia677gjkyuv7Ndoe//+GuWOdkeOHOGiiy6iZ8+eXHXVVVx33XUMGzYs0mGJRNyhMpjwJxjkgDeaOzDQOsFdrUy2o54wkK4jmisyAmhz0l1RUcGVV16phFtEIiLvKLzwBfjiu5F00WgA1uwFr9uB4dgxZh+FlJQIBxkkNpuN7OxsCgocLF26BoDrr7+GxMTQl9IPHKgy8o7qH//4B9999x0vv/wya9as4bHHHuO0007j2muv5Zprrmm0lJhIV1HsCryMUauoTFYkunSwiow2J90zZszgpZde4u677w5FPCLSAeTlwe7dtde3b4du3SA93X8Jpe9c4PFBoNN+Hp9/f2dis9nweCxUl3knJ6dgt7f5T3e75eX5Lw2F472W9uvevTvZ2dlkZ2fz7bff8pe//IVVq1Zx7733UlVVFenwRDoXdUIXiYymKjKKCuCbrxtvj+DvZJu/uXk8Hh555BHeeustzjjjjEaN1B577LGgBSci0Wn5cli0qPZ69dTR++6D+++PREQSKk8+6eShh5yNtt99t5UHH9RIeLSrrKzk888/59NPP2X//v1a7lMEKDbZcRlisPiaaP7UFurc3Dl0sFLlqBJtr12U/k62Oen+4osvOPPMMwHYuXNnvX11m6qJSOc1bZqTUaPKWL/e39n6oosKMZnMx+f7hicR81U48Ta4LsE3dmwObvdmli7dCMD8+aOxWEyMGZMFqKFatHr33XdZs2YNr776Kl6vlx//+Me8/vrrnH/++ZEOTSTicmNTmXDKSnp46o9OP3PWQfr+NcB87uaoc3Pn0MFKlaNKa167cFaDROnvZJuT7nfffTcUcYhIB1JSksP+/Vs47TR/yfP+/f7O1klJoU/E4iwWjNZkvM4ifFXH6u0zWpOJC2Fzsa5ozJhMBg3KYOlS/2t9/fVTSUw0Y7VqlDtaZWRkUFRUxMUXX8yKFSuYPHkycXFxkQ5LJKrkxqaSS/0v3u6eEQpGooOax7Vfc69dlI48h1v4JgaKSKeRmZlJv36NO1uHIxGzJtiwjcrGV9l48rYhxoI1oXN0Lo8WVquV5ORYIjWnXNru/vvv54orriApKSnSoYhElR4WiDMFbqYWZ4JuPaKsTFakM4jSkedw0zcnEWkzq9UasZHOHhaIt9pwexon13Em/36RrmbevHk88MADJCQkkJOTw69+9asmj1XvFemqMhLh3en+LuYN9bBAWqJKjEUkNJR0i0iHUv2l6UBhFePG/QOA99//ETabmR4W/36Rrmbbtm1UVlbW/Lsp6r0iXV1GYoPPieq5pseA7+psV5ItIkGkpFtEOpyMRLD5oPLbIgAGJ4NdVX/ShdXtt6LeKyKtFIy5ptHWuVmkq4vS30kl3SIiIp3IgQMH6NOnT8BR7QMHDtC3b98IRCUShYIx11Rdr0WiS5T+TirpFhGJYnl5sHt37fXt26FbN0hP919EGhowYAB5eXmkptb/YlFUVMSAAQPweAJ0kRKR9lPXa5GmRWLkOQp/J5V0i4hEseXLYdGi2uvjx/v/f999cP/9kYhIop3P5ws4yu1wOLBEcEm9/fv388ADD/Dvf/+b/Px8evfuzXXXXcc999xDbGxszTEDBgxodNtNmzbx/e9/P9whi4jIiYrSkedwU9ItIhLFpk1zMmpUGevXOwC46KJCTCYz/ftbAa2VLbXmzZsH+JulLVy4sN4KAx6Ph08//ZThw4dHKDr46quv8Hq9LF++nO9973vs3LmT2bNnU15ezm9+85t6x77zzjucfvrpNdeTk5PDHa6IiARLFI48h5uSbhGRKFZSksP+/Vs47TT/Emn7968DICkpC8iKYGQSbaq7lvt8Pr744oua0WOA2NhYhg0bxoIFCyIVHhdddBEXXXRRzfWTTz6ZXbt28cwzzzRKupOTk0lLSwt3iCIiIiGhpFtEJIplZmbSr1+/RtsjtU66RK/qruUzZ87kiSeeIDEx+tfPKy0tpUePHo22X3bZZbhcLk455RRuv/12LrvssghEJ51elHY5FpHOR0m3iLRaXp7/0pCaeoWO1WqNaIK9O9fB3lwH5vQYAD7+upCEBDNpdgun9LZFLC5p2urVqwH48ssvOXDgABUVFfX2R0sCu2fPHn7/+9/XG+W22WwsXbqU0aNHYzQaefXVV5kyZQpr165tMm63243b7a65XlZWFvLYpZPQXFMRCRODz+fzRTqIaFNWVobdbqe0tLRDjBSIhMv999dv6lUtEk29SkurSEpaBUBJyc+w23UOMdh25zoYPXcFFY6iRvtibclsfDJbiXcQBPszZ9++fUyZMoUvvvgCg8FA9cd8dXO1YHcvv/POO3n44YebPSYnJ4fTTjut5vqhQ4cYN24c48eP5w9/+EOzt50+fTr79u3jww8/DLj//vvvZ1GAP0z6DBcRkVBr7We4vqWKSKtNm+bknHOc/PCH/uuvvw4WC2rq1Unll7qocBRhMMdjiK19f30VTiocReSXupR0R6GbbrqJAQMGsGHDBgYMGMDmzZspKipi/vz5jeZOB8P8+fP56U9/2uwxJ598cs2/c3NzmTBhAqNGjWLFihUt3v+IESN4++23m9x/11131TSRA/8XoD59+rQcuIiISJgo6RaRVispyWHPns3ARgD27BlNfLxJTb06OUOsFWNcbXLtBXxVxyIXkDRr06ZN/Pvf/yYlJQWj0YjRaOS8885jyZIl3HTTTTUN14KlZ8+e9OzZs1XHHjp0iAkTJpCVlcXq1asxGo0t3mb79u2kNzN/JS4ujri4uFbHKyIiEm5KukWk1TIzM+nePYNbbvEnXJMnTyUx0Rz2Ocd79zrZubMM8C+j9d57hdhs/mW0Bg7UiLt0bR6Ph27dugGQkpJCbm4up556Kv369WPXrl0Ri+vQoUOMHz+efv368Zvf/IYjR47U7KvuVP7HP/6R2NhYzjzzTAD+9re/sWrVqhZL0EVERKKZkm4RaTWr1UpycizgH/VMTk6JyFzqhx/O4dlnt9TEMWWKfxmt2bOzWLFCI+7StQ0ZMoT//Oc/DBgwgBEjRvDII48QGxvLihUr6pV5h9vbb7/Nnj172LNnDyeddFK9fXXbyzzwwAN88803mM1mTjvtNF566SX+3//7f+EOV0REJGiUdItIh3PHHZlceWXjZbT8c8sl2HwVTrwNrkv0+uUvf0l5eTkAv/rVr/jhD3/ImDFjSE5O5qWXXopYXD/96U9bnPs9Y8YMZsyYEZ6ARESk4ygq6NArDSjpFpEOZ+BAlZGHQ5rdQqwtmQpHUaM53LG2ZNLslghFJs2ZNGlSzb+/973v8dVXX1FcXEz37t1rOpiLiIh0GEUFcM8sqKpsvM8c41/6L8oTbyXdIiIS0Cm9bWx8Mpu9uQ4uu+yfAKxbd7HW6e6AevToEekQRKJbBx9FE+nUHKWBE27wb3eURv3vqZJuERFp0im9bfRKsFCV5/+wGzUoMvP4pXl1l8xqyWOPPRbCSEQ6oE4wiiYSETpZ1Wr65iQiItLBtXYZMJWXS5cXKEnIO9jhR9FEwk4nq9pESbeIiEgH9+6770Y6BJHo11ySICJt0wlKvsNJSbeItNqhMjhQBDEnJQPwZRHY3NDDAhmJEQ5ORESkOc0lCSISXHkHG2/rwmXnSrpFpFUOlcGEP4HbYyZ9weUAXPWaf1+cCd6drsRbJFp8+OGHLF++nL179/LKK6+QkZHB888/z4ABAzjvvPMiHZ6IiHR2f3ik8bb2lp3b7P7bNlXKbrO3L8YwUtItIq1S7IJjTge+SlejfcdiLBS7bEq6RaLAq6++yrRp07j22mvZtm0bbrcbgNLSUh566CHefPPNCEcoIiJdUnvLzpNT/cl6B27apqRbRFrFWe7A8fEKvM6iRvuM1mScV2QDWkJKJNIWL17MsmXLmD59Oi+++GLN9tGjR7N48eIIRibSAXWQUTSRTi85tUMk101R0i0ireJ2ufA6izCY4zHEWmu2+yqceJ1FuF0ulHSLRN6uXbsYO3Zso+12u52SkpLwByTSUfz8dkjvU39bBxlFEwm75kq+pREl3SLSJoZYK8a42uTaC/iqjkUuIBGpJy0tjT179tC/f/962z/66CNOPvnkyAQlEg1amhc6aIgSbJHWaqrkO+9g4PncXZySbhERkU5k9uzZ3HzzzaxatQqDwUBubi6bNm1iwYIFLFy4MNLhiUROJ5gXKhJVOnjJdzgp6RaRVuluAZMBfAH2mQz+/dL5OJ1OiorKAAcARUWFVFaasVqtWK3W5m8sEXHnnXfi9Xq54IILcDqdjB07lri4OBYsWMCNN94Y6fBEIktJgkhodYJO46GgpFtEWiW9G1w3FFzeo6xc+R8Arr9hCHjdGKr8+6Xz+fDDHDZs2EL1fP1ly9YRGwtjxmQxaVJWZIOTRiorK7noootYtmwZt912G3v27MHhcDB48GBsNvVcEBGREFNFSUBKukWkVSwWC/17J5ObewRv2REA4iqKiYszkpyajMWioe7O6IMPMnn00X411x991P//u++2MmlShIKSJsXExLBjxw4AYmNjGTx4cIQjEhGRLkcVJY0YfD5foGrRLq2srAy73U5paSmJiVp4WKSaw+GgoMDBwIFrANi79xoSE81YLBaNonVSeXn+y5EjUFhYuz0lBXr2hPR0/0XaL9ifObfeeitxcXH8+te/DkJ0HY8+w0VEJFxa+5mjkW4RaTWbzYbHY6G61Dg5OQW7XX9GOrPqpPqee5w89JCz0f6777by4IOa2x1NqqqqWLVqFe+88w5ZWVkkJCTU2//YY49FKDIREZGuSd+WRUSkRWPH5uB2b2bp0o0AzJ8/GovFxJgxWYDmdkeTnTt3ctZZZwGwe/fuevsMBkMkQhIREenSlHSLiEiLxozJZNCgDJYu9a/Jfv31U0lMNKuDeRR69913Ix2CiIiI1KGkW0Q6rL17nezf37jkuX9/KwMHduxk0Ol04nQ2fm6RWqrLarWSnByLphaIiIiItI2+MYlIh/Xwwzk8++xmYOPxLaMBE7NnZ7FiRccuec7JyWHz5s1s3Oh/bqNHj8ZkMpGVlUVWVsd+biIiIiJdiZJuEemw7rgjk0svzWDKFH/J89q1U7HZzPTv37FHuQGSkjIZODCDr7/2P7eBA6diMplJSur4z01ERESkK1HSLSId1sCBVlJSakuex4/vPCXPzz9vZdGi2uf229+mAGbuuw/uvz+SkYmIiIhIW3SOb6ciIp3MnDkwYQKMH++//t570K2b1sQWERER6WiUdItIq+XlQd0ViLZvr00ElQwGV3o61O2XNnw42O0RC0dERERE2skY6QBEpONYvrx25BX8/87K8m+Xzu1QGXxZBDEnJRNzUjJfFsEXBf7tIiIiItI0jXSLSKtNm+Zk1Kgy1q93AHDRRYWYTNWNy9Tgq7M6VAbjnnXgcrlI/cU4AK74SwkAFouF92fbyEiMYIAiIiIiUUxJt4i0WklJDvv3b+G00/zNvfbvXwdAUlIWEP5lrA6VwYHjo6/gH4m1uaGHBSWBQfRtkYOiD1fgdRY12lduTebbH2eTkWiLQGQiIiIi0U9Jt4i0yOl04nQ66dmzJ+PGjavZHh8fj9VqxWoN/yj3oTKY8Cdwe8ykL7gcgKte8++LM8G70zt24r0718HeXAfm9BgAPv66kIQEM2l2C6f0Dm+C63a58DqLMJjjMcTWvte+CideZxFul4vqLusiIiIiUp+SbhFpUU5ODps3b2bjxo0AjB49GpPJRFZWFllZ4R/hBih2wTGnA1+lq9G+YzEWil0dt+R5d66D0XNXUOEowjrEv+2qu38PQKwtmY1PZoc98QYwxFoxxtU+rhfwVR0LexwiIiIiHYmSbhFpUVJSJgMHZvD11/4Ea+DAqZhMZpKSIjeP21nuwPFx4JJnozUZ5xXZdNTR1/xSFxWOwCPLFY4i8ktdEUm6RURERKTtlHSLSIuef97KokWxVCexv/1tCmDmvvvg/vsjE1NXKHnWyLKIiIhIx6ekW0RaNGcOTJhQu1zYe+/Vrs8daUpMQ6+7BUwG8FY48dbZ7qtwYjL494uIiIhIYEq6RaRF6elQt1fa8OFgt0csHAmzAT0tzB2XzDffHuGFF7YBcN11pxAbayQ9NZkBPZV1i4iIiDTFGOkAAJ566in69++PxWJhxIgRbN68udnjX375ZU477TQsFgtDhw7lzTffrNlXWVnJHXfcwdChQ0lISKB3795Mnz6d3NzcUD8NEQmj6tHXQDrL6KuvwonX7ai5+CqcEYnDZrNx+03Z3LfgZrxHR+M9Opr7FtzMkl/eyu03ZWOzdewyfhEREZFQinjS/dJLLzFv3jzuu+8+tm7dyrBhw5g0aRIFBQUBj//444+5+uqrmTVrFtu2bWPKlClMmTKFnTt3Av6ljbZu3crChQvZunUrf/vb39i1axeXXXZZOJ+WiIRYeje4bihccfJRStZvpGT9Rq4ZWMp1pzm5bqh/f0eVZrcQa0vGV3UMr7Oo5uKrOkasLZk0e/jPKNhsNpKTU/DPk/f/OyUlRQm3iIiISAsMPp/PF8kARowYwTnnnMOTTz4JgNfrpU+fPtx4443ceeedjY6/8sorKS8v5/XXX6/Z9v3vf5/hw4ezbNmygI/x2Wefce655/LNN9/Qt2/fFmMqKyvDbrdTWlpKYmIHXXNIJIgcDgcFBQ4GDlwDwN6915CYaMZisUQs6XI4HKxYsYLc3CMsXfofAObPH0ZcnJHk5GSyszv2CGz1Ot2XXfZPANatuzhi63RXKy2tIilpFQAlJT/DbtcMpWDQZ05w6fUUEZFwae1nTkS/MVVUVLBlyxbuuuuumm1Go5GJEyeyadOmgLfZtGkT8+bNq7dt0qRJrF27tsnHKS0txWAwkJSUFIywRboUh8PBI79bwTffHsHYbTcAi35zpGY+b6TKi202G9nZ2RQUOFi61H8y4PrrI38yIFhO6W2jV4KFqrxKAEYNSlGSKyIiItIBRfQbXGFhIR6Ph169etXb3qtXL7766quAt8nPzw94fH5+fsDjXS4Xd9xxB1dffXWTZx/cbjdut7vmellZWVuehkintu+IiyffL8JrSiDx/NEArMv1zzc25hRxxdUuhkYowbXZbHg8FqqXBktOVmIqIiIiItEl4nO6Q6myspKf/OQn+Hw+nnnmmSaPW7JkCXa7vebSp0+fMEb5/9u78/Cmqvx/4O+bvWloS9OWtqwF2ZRFqEO/hUEZ7UPxiwoz6iCKLCOgDLgAowgjIDpOUX7gMjjiAoLjis/XAQZGmFIWFwrIUhxGQGWAsjQFCl3SNM12fn+EBELSUkrTmxver+fJE3LuzeVzepKefu4591yiyHbeDrjFxVtz+R6Szgi38G4nIiIiIqLQZE26k5KSoFarUVpaGlBeWlqK1NTUkO9JTU1t0P6+hPvYsWPIz8+vd479zJkzUVFR4X8cP368kTUiIiIiIiIiukjWpFun0yEzMxMFBQX+Mo/Hg4KCAmRnZ4d8T3Z2dsD+AJCfnx+wvy/h/umnn7Bx40aYzeZ649Dr9YiLiwt4EBHJqaQEKCq6+LqoCNizx1seCfGsXAl89BGwYYO8cRERERFFOtmnl0+bNg3vvvsuVqxYgQMHDmDSpEmorq7GuHHjAACjR48OWGjtySefxPr167Fw4UIcPHgQzz//PHbt2oUpU6YA8Cbc9913H3bt2oWPPvoIbrcbFosFFosFDodDljoSRYNIuWf0pSItMW1KixfbMGjQWQBWAFYMGnQWmZlnsXixPD/3y+OZOPEsRo06iyFDbMjMBN5+W5awSGE6dOgASZICHvPnzw/Y5/vvv8fAgQNhMBjQtm1bvPLKKzJFS0RE1DRkX3FoxIgROHPmDObMmQOLxYKbb74Z69ev9y+WVlxcDJXq4rmB/v374+OPP8Zzzz2HWbNmoXPnzli1ahV69OgBADh58iTWrFkDALj55psD/q/Nmzdj0KBBzVIvomihNxigMpr994m+lMpoht7Q/PeM9nn7bWDevIuvfV/vuXOB55+XI6Kmc+utByBJu+FbJA7w/l4bODATQKZs8Zw7p0NZmQMrV3pXjJ83rzcGDOiNDh2MAIzNHhcpzwsvvIAJEyb4X7do0cL/78rKSgwePBg5OTlYsmQJ/v3vf+N3v/sdEhISMHHiRDnCJSIiumayJ90AMGXKFP9I9eW2bNkSVHb//ffj/vvvD7l/hw4dIPOtx4miShuzCeaBE2G3B6+YZjAY0MYs3625Hn7Yhv79K7F+vRUAMGTIWajVmqhIAAcO7I7MzPZB5UajPPXyxbNv3z5s374HK1fuBADExKhx+PBhJCTIczKAlKdFixZ1rtvy0UcfweFwYNmyZdDpdLjppptQVFSERYsWMekmIiLFkgQz1CANvck50fXiZCVQfNaF225bDQDYunUYTCYNEg1Aaxm/Irt378bu3buDyjMzM5GZyQQwHGw2GyyWSnTq5B3pPnzYe290o9Eo2wkBpbue+pwOHTrAbrfD6XSiXbt2ePDBBzF16lRoNN4xgNGjR6OyshKrVq3yv2fz5s24/fbbce7cObRs2TLomKFu+9m2bdvr4udJRETyamgfHhEj3UQU2VrHASYBOE+UAQBuNAPx8TIHBaB79+5o3z5yRoOvB0ajEWazDrw3OjXGE088gb59+yIxMRHbtm3DzJkzUVJSgkWLFgEALBYLMjIyAt7ju9zMYrGETLrz8vIw79LrTIiIiCIM/1IiIsXi6CqR/J599lm8/PLL9e5z4MABdOvWDdOmTfOX9erVCzqdDo8++ijy8vKg1+sb9f/PnDkz4Li+kW4iIqJIwaSbiIiIGm369OkYO3Zsvft07NgxZHlWVhZcLheOHj2Krl27IjU1FaWlpQH7+F7XdR24Xq9vdMJORETUHJh0ExFRg/14yorDp6zQpGkBANt+OovYWA1S4w3oki7fonokn+TkZCQnJzfqvUVFRVCpVEhJSQEAZGdn449//COcTie0Wu9nLD8/H127dg05tZyIiEgJmHQT0RXZbDaUlVXCe49moKzsLJxOLp51vfnxlBUDprwDh7UMRu9dGvHArL8AAHQmM75dPJGJN9WpsLAQO3bswK9+9Su0aNEChYWFmDp1KkaNGuVPqB988EHMmzcPjzzyCGbMmIH9+/fj9ddfx6uvvipz9ERERI3HpJuIrujrrw+goODiPaOXLFkDnc57z+jcXK4Sfr2wVNjhsJZB0sRA0l082SIcNjisZbBU2Jl0U530ej0+/fRTPP/886itrUVGRgamTp0acD12fHw8/vWvf2Hy5MnIzMxEUlIS5syZw9uFERGRojHpJqIr+uqr7liw4OIq4QsWeJ9nzTIiN1emoEg2ks4Ilf5icu0BIFw18gVEitC3b19s3779ivv16tULX3/9dTNERERE1DyYdBPRFU2ZYsS99wZPI09LkyEYIiIiIiIFYdJNRFeUlsYEm4iIiIioMZh0ExHRVREOGzyXvSYiIiKi0Jh0ExFRg6TGG6AzmeGwlgVdw60zmZEab5ApMiIiIqLIxaSbiIgapEu6Cd8unojDp6y4554vAQBr1tzJ+3QTERER1YNJNxERNViXdBNaxRrgKnECAPp3TkJ8PLsSIiIiorqo5A6AiIiIiIiIKFox6SYiIiIiIiIKEybdRERERERERGHCC/GIiKjBbDYbysoqAVgBAGVlZ+F0amA0GmE0GuUNjoiIiCgCMekmojrZbDbYbMH3YGaCdf36+usDKCjYDcC7UvmSJWug0wEDB2YiNzdT3uCIiIiIIhCTbiKq09dfH8CWLTuxb9+3AIDevQdArVZHXILFkwPN56uvumPBgvb+1wsWeJ9nzTIiN1emoIiIiIgiGJNuIqrTV191x/z5rQHUAAC+/PLXADQRl2Ap5eRANJgyxYh77w0+kZGWJkMwRERERArApJuI6jRunAf9+gHDh3tfr1oFmExA+/YeOcMKopSTA9EgLY0JNhEREdHVYNJNRCFZrVZ8sPIdHDtxBqoWPwIAvthwBjqdCmkpZjzzxESYTCaZo/SaMsWIwYN1GDTIG8+WLUlo0ULD5JCIiIiIZMekm4hCOnLGjsVby+BRxyLu9gEAgDWnAOGwQXWgDPePtKNnhCTdLVpY0batFb4Vtdu2PYu4OA0MBgN8C34REREREcmBSTcRhXTeDrgFoNIZodJfTFw9ANy2Gpy3yxfbpaxWK155I3BEft7/i8wR+YYoKfE+Lsdp3URERETKxKSbiBRNSSPyDbF4sQ1//nPwSuyzZhnx0ktciZ2IiIhIaZh0E5GiKWVEvqFuvfUAamt3YuFC70rs06cPgMHgXYkd4ErsRERERErDpJuI6iUcNngue03hM3Bgd3Tu3BoLF3pXYv/973+NuDgN7zdOREREpFBMuokoJL3BAJXRDI+tDMJVE7BNZTRDbzDIFFl0O+8yohQ6aNu0BwCUIgnVHg0SXQDTbiIiIiLlYdJNRCG1MZtgHjgRdnvw/GyDwYA25si6TjoaRuRPVgK3vWuF3W5HymO3AQDu/6QcgPdnvnWCCa3jZAyQiIiIiK4ak24iCql1HPBBrhp7fgCmTV8PAFi0cAiMRjW6dVBHTPIXTSPyJ8qsKPv6HXhsZUHbqo1mnPjNRLSOi6yTHURERERUPybdRFSn5W/8gHff3e1//fiILwAAEyZkov87kbGol9JG5OtTa7fDYyuDpImBpLs4mVw4bPDYylBrtyOS7jt++LANR48Gzyjo0MGITp04GZ6IiIgIYNJNRPWYMaM7RoxoH1TeoUPkJFSt44CtE0woPmvAbbetBgBs3ToMJpMGiQZEzIj81ZBCrMR++Sh+JHj55QN4992dAL69UDIAgBoTJmTinQg5KUNEREQkNybdRBSkpMT7AIxo2fJigp2W5n1EmtZxgEkAzhPeadk3moH4eJmDug78dnw7dOxnwuw53tcvvnA7YmLUuKkzf/hEREREPky6iSjIy3+twV+XB0/X/v1YA157MUaGiOp3+LAN+/dXArACALZsOQuTScNpzmH04ykrRs7/GxzWMhh7eMvyVn4AANCZzPh28UR0SY+cqfBEREREcmHSTUQBTlYCq+OcSHnMHbRttc6JpytjIm7Ktnea8274rncePnwNAChumnNLA6CWAE+IldjVknd7pLBU2OGwhr7+3GEtg6XCzqSbiIiICEy6iegyJ8qsKP/2vZAraKuMZpy4L/JW0FbCtecNkZFswJTbzDh24gw+/HAvAGDUqC7Q6VRISzEjIzmCsu4LlHL9OREREZFcmHQTUQClraANAJ06Rcc0cpPJhGeemIjTp6344K2PAQBz//Ag4uI0MBgMMJki6+dORERERFfGpJuIQuIIpjyqqkw4ftwA34mN48eT0KKFBmlpAHNuIiIiIuVRyR0AERFdtHixDYMGnYV3UTgrBg06i8zMs1i8OPh+2JFAOGzw1Fr9D+GIzDiJiIiI5MKRbiKiCHLrrQcgSRcXhQO8i8INHJgJIHIWhUuNN0Aba4azuixoBoQ21ozU+Mi7/pyIiIhIDky6iShASwOgkoR3BPOScuGwQSWJiFpBOxoNHNgdmZnBi8IZjZF1zXqXdBN+2+VhvPu3cwA2XSi9HYAaEx6O58rlRERERBcw6SaiABnJBgxt48D+g4fw7397y3r2BFQq4MYuGRG5gnY0MRqNEZdg12XY7cVI1O4GoL5QshWAb1Q+Wa6wiIiIiCIKk24iCmAymZCW+Aw+2nbeX7Zvm/f5jv9pyRW0yU8po/JEREREcmLSTURBpk1LwciRKUHlaWkyBEMRS0mj8kRERERyYdJNREHS0phgExERERE1Bd4yjIiIiIiIiChMmHQTERERERERhQmTbiIiIiIiIqIwYdJNREREREREFCZMuomIiCjstmzZAkmSQj6+++47AMDRo0dDbt++fbvM0RMRETUeVy8nIqJr8v33p/Hzz+eDym+4oSV69Qq+9Rxdn/r374+SkpKAstmzZ6OgoAC33HJLQPnGjRtx0003+V+bzeZmiZGIiCgcmHQTEVGjWa1WjJv0Cor+/V8ApRdKWwGQcHPPDGzd8DxMJpOMEVKk0Ol0SE1N9b92Op1YvXo1Hn/8cUiSFLCv2WwO2JeIiEjJmHQTEVGjHTljx39jdWjxy76QdEZ/uXDY8F+XDUfO2NGTSTeFsGbNGpSVlWHcuHFB2+655x7Y7XZ06dIFzzzzDO655546j1NbW4va2lr/68rKyrDES0RE1Fi8ppuIiBrtvB3wQIKkM0KlN/kfks4IDySct8sdIUWqpUuXIjc3F23atPGXmUwmLFy4EJ9//jnWrVuHX/7ylxg+fDjWrFlT53Hy8vIQHx/vf7Rt27Y5wiciImowJt1ERETUaM8++2ydC6T5HgcPHgx4z4kTJ7BhwwY88sgjAeVJSUmYNm0asrKy8Itf/ALz58/HqFGjsGDBgjr//5kzZ6KiosL/OH78eFjqSURE1FicXk5Efht3nsF/fqoIKr+pczxy+iXLEBERRbrp06dj7Nix9e7TsWPHgNfvv/8+zGZzvdPGfbKyspCfn1/ndr1eD71e36BYiYiI5MCkm4gAAD+esuK3L62AuyZ4FWp1TEtsf+sxdEnntbkUmnDY4LnsNV0fkpOTkZzc8JNyQgi8//77GD16NLRa7RX3LyoqQlpa2rWESEREJCsm3UQEALBU2OGuOQ9JExO0IJa75jwsFXYm3RREbzBAZTTDYyuDcNUEbFMZzdAbDDJFRpFq06ZNOHLkCMaPHx+0bcWKFdDpdOjTpw8A4IsvvsCyZcvw3nvvNXeYRERETYZJNxEF8C2I5eMBgpIpanpKndrfxmxC3P+Mh9vtCNqmVuvQxswTNRRo6dKl6N+/P7p16xZy+4svvohjx45Bo9GgW7du+Oyzz3Dfffc1c5RERERNh0k3EZHMlDy1v3Uc8MldWhw86g7a1q2DFq3jZAiKItrHH39c57YxY8ZgzJgxzRgNERFR+DHpJqKocbISOBfiFlWJBkR08qf0qf39e8Sgf48YucMgIiIiikhMuokogFIXxDpZCdz6ThVqa2uDtun1enw1sUVEJ94Ap/YTERERRSMm3UQEAEiNN0Abmwhn9bmgRE8bm4jU+MheEOtEmRXnvnkXHltZ0LZqoxkn7p2I1nGRO1ocDZR6XToRERFRODHpJiIAQJd0E3KSB+D/dhwI2nbvXd0jenozANTa7fDYykJO0fbYylBrtwOI7DoomZKvSyciIiIKJybdROT30oxemDDihqDyDh2MIfaOTEqeoq3Uqf2A8q9LJyIiIgoXJt1E5NepkxGdOiknwY4WSp/afykln/QgIiIiCgcm3UREMlP61H4iIiIiqhuTbiKKCi0NgOQRIadoSx6BlhE+WBwNU/uJiIiIKBiTbiKKChnJBjzcJw5Hjp0BcMliXjogo30yMpIjM+v+8ZQVlgrvzcW16RfLU+MNihzhFg4b3K5aCLfT+9pZA+Gy45/flEHtMGBAb+XViYiIiOhaMOkmIlitVtjt9qByg8EAk0kZSZLJZELe3CmKqsePp6zoP/ltOKvPBW3TxiZi25uPKibxTo03QB3TEq6qUjhO7A24jlvSxOCvn7yHd9amYvtbyqkTERERUVNg0k10nbNarXhp4WKcLDkTtK11WjL+OH1KRCasoZhMJsXECnhX/HZWnwu54rez+pyiVvzukm7Cyj+OwdrtxVj6hctbJ+2F2QVqDSSPB+4aZdWJiIiIqCkw6Sa6zh05Y8eSbyshNC2DEj/pv5V4cLQdPRWUyCpRtKz4ndMvGboWEt5fa4TKaA6sU61VkXUiIiIiulZMuomuc+ftgAcSVCESP4+rBueDZ2sTEREREVEDMekmoqh06QJll1LqAmVEREREpExMuoko6ihtgbJQtzlTumisExEREVFjMOluZhx9o0jh+yx+f7QMHocNwiPgqbUCag1UGoOikySlLFCWGm+ANjYRzupzQdc7a2MTkRofmbc5q8+ldfLYKyA8Lv82jbElTpyx4kf+viMiIqLrCJPuZvTjKSsGTHkHDmtZ0DadyYxvF0/kH6LULC79LAqXA85T//YnfZImBro2fSBpdFAZzdAblJf4+UT6AmVd0k3Y9uajUXUizlen7w6fxeN5f4PTdnG2gdtehUl/epe/74iIiOi6wqS7GVkq7HBYy0KOvjmsZREz+kbR79LPospohqFLIoTbCeGsgXDZEfs/46GONUOv16ONmZ/JcOqSboq6732XdBMsFXa4XXaojWZApYZwOwEAwlkD+7nj+Ne+kwBaR13diYiIiC7HpFsGkT76RtHtx1NW/5RylVoPCYCk0UPSxwJuEzy2Msy/24y+nZKQaABax8kd8bURTrt/irOn1gqPw4bvj5bJPpJ83VxqolLDcWIPRG01AEC4HRCuGsx8GZiX2JYj3kRERBT1mHQTXUd808rt547DUbzTO+tCowMASLpYaNv0AQBkJAA9U2QMtIl4bOfhOLXv4vXpbieEcMma8P14yhpy6rWk0kDS6KJu6rVwO70Jt1oLSaMFXN5uR9LEcIYPERERXReYdBNdJ348ZcW/9p2E/dxxCI8AJDWgUgMaHSSPgHBUA27XlQ+kAKnxBqhjWsJZcRIeWxmg0kBSaQG1FipdPCS9SZaE7/KTHv644J0Bo23dO2oTUUmjhaQxAJAAjwuS1gC4a+UOi4iIiCjsmHTLgLfSoeZ06ciqo+IkHCf2AJIanqpSQKWGpDVCnZAOuJwQTjsklSR3yNesS7oJK/84Bmu3F2PpF4AqpiUktdY76ircEE473NVn8ebqXfh8iwkanQYuhyvgOc6gg5AASSDguarGEbTvlZ59xzpuOY8ay4+ApAIkNSSNAZIuxnvSw+P0JuBRlogKZw2E2wG4NBBuN+CsgfC44HFUA25HREz1JyIiIgqniEi633zzTSxYsAAWiwW9e/fGX/7yF/Tr16/O/T///HPMnj0bR48eRefOnfHyyy/jf//3f/3bhRCYO3cu3n33XZSXl2PAgAF466230Llz5+aoDoCL12seP2vFeWstTp+vxvHT5YCzBi5rGSS1GlDrAqaUKvH2QCS/UJ81X2JorXXgi9Vr4bKWwWnZD0AFt/U0oNZAOO1Q6YwQDqt3+q9wQ7hqoE9sGxWfxZx+ydC1kPD+WiMktRaOE3vgqamA+/xxeJzV8Ngr8PkP6wBXLaAxAC67/1nSGr0nJCBBQAQ8ezxOwFkT9J66ngOOJTyA8AAa77X00Oig0sVC3bItAs7ERYHUeAN0JrN3ZoXrQqJdVepNwCUNPK4awO3EjHmV+KMpCaPvvRuJccY6T2zEGXRIToxFYqwebZJNTNSJiIhIMWRPuj/77DNMmzYNS5YsQVZWFl577TXk5ubi0KFDSEkJvqh027ZtGDlyJPLy8nDXXXfh448/xvDhw7Fnzx706NEDAPDKK6/gjTfewIoVK5CRkYHZs2cjNzcXP/zwAwzNcPsj3xTS2vISOE7shcdhhaeyFMLjBCQV1KZk7/WzaT2hjWuJxc+Oxi03JPEPSIWoL8m9mlHPphhBdTlc+Nv//QMu23k4Sw9COGvgsZ6Fx13rTQzVeu+zLhZw1QCGeMBVA5XeDEmtg6ZlO8DjhrZtJuB2IG/GYxjcO/pWlPZfVyypvD9wtQ6SpPL+fFy1gFrnTZR9zxq9930eDwAJAgAgASoVJEkN4awJfk9dz5ceS1J7H4A3EZfUEK5awBNlGTe8sw2+XTwR/9p3EjNfBoRHwHlyDwQkeKyl8FSUeBPxytOo8Tjw190fA5BCntjwnbhQm5IBjQHalK5QGeJx37C70K5Vy2v+PjXmO8mTAERERNRQsifdixYtwoQJEzBu3DgAwJIlS7Bu3TosW7YMzz77bND+r7/+OoYMGYKnn34aAPDiiy8iPz8fixcvxpIlSyCEwGuvvYbnnnsOw4YNAwB88MEHaNWqFVatWoUHHngg7HXy3Y4JqgsLBmljAbUGkkoDSIBkSIAkSVAZ4uF21aJNcvTdMiha1XVCxZ/kXs2oZ1OMoEoq78ipSgtAeBerUqkgweBNDDV673RljR5wOyCpNRAOAXgEcMkscklSQ9IZ0auDOSo/i/4pzio1AAmSSg2h0kDSGiCcthDPMYBwAx53YDuptICkgnBU1fPehh7L+/tAeFwXEm931Ezv9/F+llpjXmJb2M8dB4QbkqQG3M4LlzbEeD/L0F18U4gTG0KtBWqtcFWdARxVcJUdgXBW44Oiz7zXxV/D96kx30lJ6509oY5LhaQzQdemD/QJaVG1AB4RERE1HZWc/7nD4cDu3buRk5PjL1OpVMjJyUFhYWHI9xQWFgbsDwC5ubn+/Y8cOQKLxRKwT3x8PLKysuo8ZrhI2hhIah1UeqP3lkw677NKHwtJo/MuJESKUucJFfWFtlTr6n/W6AGVBgISAJX/GSp1w49x6bHUWm/CrVJBUl84qaPWQdLFeJMRrcH7rNEBkgRIWu9Iq3B7V/J21nin/rpqovISh9R4A7SxiRAuu7eeF5JvIdwXkl6ZElwhvMm7ywE47RD2qqhtB9+Id96Mx6Br1w+6DtnQJGZA26o7tCldIKl1gEbjXdlco7nwu/Lyz68ekKQLn2OV91p4SeVNgq/1+9SY76Tvu6eN9b5Waf0L4BERERFdTtaR7rNnz8LtdqNVq1YB5a1atcLBgwdDvsdisYTc32Kx+Lf7yura53K1tbWorb24eFFlZeXVVYSuO74TKpJaDY9GD6hFA0c/wzeC6h26FvXHDQEY4qCObw0IN7St+0JSSVE7rbxLugnb3nzUP8UZah2cx3cDKjXc5cch/FPHm4sKkloLuOxQmZIB4YFw2aFt3Qu6+PSovdSkS7oJlgozVDojoNZ7vzsa3ZXfeDmV2ju7Q6O9kJQ3xfepMceI8c5W0sdyJXYiIiK6Itmnl0eCvLw8zJs3T+4wiMJHXEjK3Q5IwuO9jlklQVJJMCS2jcqE2+fShE9cuHZauF3e67zdbsDjgnDaL3uu8b7Zt/+FYwmVx/ujDPmeup4vHktSqSHFpUEFAV37LEiSCsJlj9qTHqFcupo5AMDjljcgIiIiojCTdXp5UlIS1Go1SktLA8pLS0uRmpoa8j2pqan17u97vppjzpw5ExUVFf7H8ePHG1Wfy/n+uPTU2iBctRAO77OnthrC5fD+UU7UFDweb/Licl34rNV4Ez5XrTfhdjkgaQ1QGc1QtUiBtnUvxHbLxdsvPHldXIfqW0kbHu99yIXTe09y4b7wHXQ7Ap9dtd4RTAgAHv8zPO6631PX86XHEm5I7lrvSK/wQFKpov6kh4+vDXxT/T32Cnhqyr0JuPBe2x70+b38BIbL4f08CybqREREpByyjnTrdDpkZmaioKAAw4cPBwB4PB4UFBRgypQpId+TnZ2NgoICPPXUU/6y/Px8ZGdnAwAyMjKQmpqKgoIC3HzzzQC808V37NiBSZMmhTymXq+HXq9vsnr5/risLS8BcMkf+B6n9zpSZzWgMwEeJ3RxaVF1/eb1wn9tsEt4k4Q6R0zDPIIqSZCgupBMqiA8DgBqiAujh5LbCeiMUJvM/hXzdXGtonYac1181xVfzarz4bhPtyQQsOI1gOtm1WtfG/juGe+0nfMm3IB/1X0BD3DhnuUALjtxcWGGhnD7TyZ5T1yKa/w+NeY7WQOo1PDUVkOSpKhbAI+IiIialuzTy6dNm4YxY8bglltuQb9+/fDaa6+hurrav5r56NGj0bp1a+Tl5QEAnnzySdx2221YuHAhhg4dik8//RS7du3CO++8AwCQJAlPPfUU/vSnP6Fz587+W4alp6f7E/twq+8PfN5mRtnqPKHiu56zIaOeIVZKDploNOBYkloLlSkRkjYGmpRu0MS2xOh77+atjULoku67S0CS3KFct3xt8ItOU/2Ljl36O7KuExv++83bKuA6fRAelx3Cetb7vZNU1/Z9asx30lXrXUiNJ1CJiIioAWRPukeMGIEzZ85gzpw5sFgsuPnmm7F+/Xr/QmjFxcVQqS7Ogu/fvz8+/vhjPPfcc5g1axY6d+6MVatW+e/RDQDPPPMMqqurMXHiRJSXl+OXv/wl1q9f3yz36PbhH/jRqTEjpuEeQWVCTUpz8fcj0NDfkTN/26/OE5m8TzcRERFFMkkI0byL9ypAZWUl4uPjUVFRgbi4OLnDISKiKMY+p2nx50lERM2loX2OrAupEREREREREUUzJt1EREREREREYcKkm4iIiIiIiChMmHQTERERERERhQmTbiIiIiIiIqIwYdJNREREREREFCZMuomIiIiIiIjChEk3ERERERERUZgw6SYiIqJr9tJLL6F///4wGo1ISEgIuU9xcTGGDh0Ko9GIlJQUPP3003C5XAH7bNmyBX379oVer8cNN9yA5cuXhz94IiKiMGLSTURERNfM4XDg/vvvx6RJk0Jud7vdGDp0KBwOB7Zt24YVK1Zg+fLlmDNnjn+fI0eOYOjQofjVr36FoqIiPPXUUxg/fjw2bNjQXNUgIiJqcpIQQsgdRKSprKxEfHw8KioqEBcXJ3c4REQUxaKtz1m+fDmeeuoplJeXB5R/+eWXuOuuu3Dq1Cm0atUKALBkyRLMmDEDZ86cgU6nw4wZM7Bu3Trs37/f/74HHngA5eXlWL9+fYP+/2j7eRIRUeRqaJ/DkW4iIiIKu8LCQvTs2dOfcANAbm4uKisr8Z///Me/T05OTsD7cnNzUVhY2KyxEhERNSWN3AFEIt/gf2VlpcyREBFRtPP1NdE+8cxisQQk3AD8ry0WS737VFZWoqamBjExMUHHra2tRW1trf91RUUFAPbhREQUfg3tw5l0h1BVVQUAaNu2rcyREBHR9aKqqgrx8fFyhxHg2Wefxcsvv1zvPgcOHEC3bt2aKaJgeXl5mDdvXlA5+3AiImouV+rDmXSHkJ6ejuPHj6NFixaQJKlRx6isrETbtm1x/PjxqLmmjHVSBtZJGVgnZWiOOgkhUFVVhfT09LAc/1pMnz4dY8eOrXefjh07NuhYqamp2LlzZ0BZaWmpf5vv2Vd26T5xcXEhR7kBYObMmZg2bZr/tcfjwblz52A2m9mHX4J1UgbWSRlYJ2WIpD6cSXcIKpUKbdq0aZJjxcXFRc0H14d1UgbWSRlYJ2UId50ibYTbJzk5GcnJyU1yrOzsbLz00ks4ffo0UlJSAAD5+fmIi4vDjTfe6N/nn//8Z8D78vPzkZ2dXedx9Xo99Hp9QFldtyy7WvwsKwPrpAyskzKwTlevIX04F1IjIiKia1ZcXIyioiIUFxfD7XajqKgIRUVFsFqtAIDBgwfjxhtvxMMPP4x9+/Zhw4YNeO655zB58mR/0vzYY4/hv//9L5555hkcPHgQf/3rX7Fy5UpMnTpVzqoRERFdE450ExER0TWbM2cOVqxY4X/dp08fAMDmzZsxaNAgqNVqrF27FpMmTUJ2djZiY2MxZswYvPDCC/73ZGRkYN26dZg6dSpef/11tGnTBu+99x5yc3ObvT5ERERNhUl3mOj1esydOzdoypuSsU7KwDopA+ukDNFYp3BZvnw5li9fXu8+7du3D5o+frlBgwZh7969TRjZ1YvGdmedlIF1UgbWSRkiqU6SiPZ7lBARERERERHJhNd0ExEREREREYUJk24iIiIiIiKiMGHSTURERERERBQmTLrD4M0330SHDh1gMBiQlZWFnTt3yh1Sg+Xl5eEXv/gFWrRogZSUFAwfPhyHDh0K2GfQoEGQJCng8dhjj8kU8ZU9//zzQfF269bNv91ut2Py5Mkwm80wmUy49957UVpaKmPEV9ahQ4egOkmShMmTJwNQRht99dVXuPvuu5Geng5JkrBq1aqA7UIIzJkzB2lpaYiJiUFOTg5++umngH3OnTuHhx56CHFxcUhISMAjjzzivz2RHOqrk9PpxIwZM9CzZ0/ExsYiPT0do0ePxqlTpwKOEapt58+f38w1uehK7TR27NigeIcMGRKwj5LaCUDI75YkSViwYIF/n0hrJ2o67MMjC/vwyGwj9uHsw+Wi1D6cSXcT++yzzzBt2jTMnTsXe/bsQe/evZGbm4vTp0/LHVqDbN26FZMnT8b27duRn58Pp9OJwYMHo7q6OmC/CRMmoKSkxP945ZVXZIq4YW666aaAeL/55hv/tqlTp+If//gHPv/8c2zduhWnTp3Cb37zGxmjvbLvvvsuoD75+fkAgPvvv9+/T6S3UXV1NXr37o0333wz5PZXXnkFb7zxBpYsWYIdO3YgNjYWubm5sNvt/n0eeugh/Oc//0F+fj7Wrl2Lr776ChMnTmyuKgSpr042mw179uzB7NmzsWfPHnzxxRc4dOgQ7rnnnqB9X3jhhYC2e/zxx5sj/JCu1E4AMGTIkIB4P/nkk4DtSmonAAF1KSkpwbJlyyBJEu69996A/SKpnahpsA+PTOzDI6+N2IezD5eLYvtwQU2qX79+YvLkyf7XbrdbpKeni7y8PBmjarzTp08LAGLr1q3+sttuu008+eST8gV1lebOnSt69+4dclt5ebnQarXi888/95cdOHBAABCFhYXNFOG1e/LJJ0WnTp2Ex+MRQiivjQCIv//97/7XHo9HpKamigULFvjLysvLhV6vF5988okQQogffvhBABDfffedf58vv/xSSJIkTp482Wyx1+XyOoWyc+dOAUAcO3bMX9a+fXvx6quvhje4RgpVpzFjxohhw4bV+Z5oaKdhw4aJ22+/PaAsktuJGo99eORhHx752IezD5eLkvpwjnQ3IYfDgd27dyMnJ8dfplKpkJOTg8LCQhkja7yKigoAQGJiYkD5Rx99hKSkJPTo0QMzZ86EzWaTI7wG++mnn5Ceno6OHTvioYceQnFxMQBg9+7dcDqdAW3WrVs3tGvXTjFt5nA48OGHH+J3v/sdJEnylyutjS515MgRWCyWgHaJj49HVlaWv10KCwuRkJCAW265xb9PTk4OVCoVduzY0ewxN0ZFRQUkSUJCQkJA+fz582E2m9GnTx8sWLAALpdLngAbaMuWLUhJSUHXrl0xadIklJWV+bcpvZ1KS0uxbt06PPLII0HblNZOVD/24ZGLfXjkt9Gl2Icrq29gH9487aQJ69GvM2fPnoXb7UarVq0Cylu1aoWDBw/KFFXjeTwePPXUUxgwYAB69OjhL3/wwQfRvn17pKen4/vvv8eMGTNw6NAhfPHFFzJGW7esrCwsX74cXbt2RUlJCebNm4eBAwdi//79sFgs0Ol0Qb8wW7VqBYvFIk/AV2nVqlUoLy/H2LFj/WVKa6PL+X72ob5Lvm0WiwUpKSkB2zUaDRITExXRdna7HTNmzMDIkSMRFxfnL3/iiSfQt29fJCYmYtu2bZg5cyZKSkqwaNEiGaOt25AhQ/Cb3/wGGRkZOHz4MGbNmoU777wThYWFUKvVim+nFStWoEWLFkHTVZXWTnRl7MMjs39gHx75bXQ59uHK6RvYhzdfOzHppjpNnjwZ+/fvD7h2CkDAdRw9e/ZEWloa7rjjDhw+fBidOnVq7jCv6M477/T/u1evXsjKykL79u2xcuVKxMTEyBhZ01i6dCnuvPNOpKen+8uU1kbXG6fTid/+9rcQQuCtt94K2DZt2jT/v3v16gWdTodHH30UeXl50Ov1zR3qFT3wwAP+f/fs2RO9evVCp06dsGXLFtxxxx0yRtY0li1bhoceeggGgyGgXGntRNcf9uHKwD5cediHK0ck9eGcXt6EkpKSoFarg1bNLC0tRWpqqkxRNc6UKVOwdu1abN68GW3atKl336ysLADAzz//3ByhXbOEhAR06dIFP//8M1JTU+FwOFBeXh6wj1La7NixY9i4cSPGjx9f735KayPfz76+71JqamrQ4kYulwvnzp2L6LbzddbHjh1Dfn5+wBnyULKysuByuXD06NHmCfAadezYEUlJSf7PmlLbCQC+/vprHDp06IrfL0B57UTB2Icro39gHx752IdfpLS+gX340bDFw6S7Cel0OmRmZqKgoMBf5vF4UFBQgOzsbBkjazghBKZMmYK///3v2LRpEzIyMq74nqKiIgBAWlpamKNrGlarFYcPH0ZaWhoyMzOh1WoD2uzQoUMoLi5WRJu9//77SElJwdChQ+vdT2ltlJGRgdTU1IB2qaysxI4dO/ztkp2djfLycuzevdu/z6ZNm+DxePx/oEQaX2f9008/YePGjTCbzVd8T1FREVQqVdD0rkh14sQJlJWV+T9rSmwnn6VLlyIzMxO9e/e+4r5KaycKxj5cGf0D+/DIxz78IqX1DezDw9hOzbps23Xg008/FXq9Xixfvlz88MMPYuLEiSIhIUFYLBa5Q2uQSZMmifj4eLFlyxZRUlLif9hsNiGEED///LN44YUXxK5du8SRI0fE6tWrRceOHcWtt94qc+R1mz59utiyZYs4cuSI+Pbbb0VOTo5ISkoSp0+fFkII8dhjj4l27dqJTZs2iV27dons7GyRnZ0tc9RX5na7Rbt27cSMGTMCypXSRlVVVWLv3r1i7969AoBYtGiR2Lt3r38V0Pnz54uEhASxevVq8f3334thw4aJjIwMUVNT4z/GkCFDRJ8+fcSOHTvEN998Izp37ixGjhwpV5XqrZPD4RD33HOPaNOmjSgqKgr4ftXW1gohhNi2bZt49dVXRVFRkTh8+LD48MMPRXJyshg9enRE1qmqqkr84Q9/EIWFheLIkSNi48aNom/fvqJz587Cbrf7j6GkdvKpqKgQRqNRvPXWW0Hvj8R2oqbBPjzysA+PzDZiH84+PBLr5BOJfTiT7jD4y1/+Itq1ayd0Op3o16+f2L59u9whNRiAkI/3339fCCFEcXGxuPXWW0ViYqLQ6/XihhtuEE8//bSoqKiQN/B6jBgxQqSlpQmdTidat24tRowYIX7++Wf/9pqaGvH73/9etGzZUhiNRvHrX/9alJSUyBhxw2zYsEEAEIcOHQooV0obbd68OeRnbcyYMUII7y1HZs+eLVq1aiX0er244447gupaVlYmRo4cKUwmk4iLixPjxo0TVVVVMtTGq746HTlypM7v1+bNm4UQQuzevVtkZWWJ+Ph4YTAYRPfu3cWf//zngM4vkupks9nE4MGDRXJystBqtaJ9+/ZiwoQJQQmKktrJ5+233xYxMTGivLw86P2R2E7UdNiHRxb24ZHZRuzD2YfLRal9uCSEEI0dJSciIiIiIiKiuvGabiIiIiIiIqIwYdJNREREREREFCZMuomIiIiIiIjChEk3ERERERERUZgw6SYiIiIiIiIKEybdRERERERERGHCpJuIiIiIiIgoTJh0ExEREREREYUJk24iIiIiIiKiMGHSTURNorCwEGq1GkOHDpU7FCIiIroK7MOJwksSQgi5gyAi5Rs/fjxMJhOWLl2KQ4cOIT09Xe6QiIiIqAHYhxOFF0e6ieiaWa1WfPbZZ5g0aRKGDh2K5cuXyx0SERERNQD7cKLwY9JNRNds5cqV6NatG7p27YpRo0Zh2bJl4CQaIiKiyMc+nCj8mHQT0TVbunQpRo0aBQAYMmQIKioqsHXrVpmjIiIioithH04Ufrymm4iuyaFDh9CjRw+cPHkSKSkpAIApU6agoqICf/vb32SOjoiIiOrCPpyoeWjkDoCIlG3p0qVwuVwBi64IIaDX67F48WLEx8fLGB0RERHVhX04UfPg9HIiajSXy4UPPvgACxcuRFFRkf+xb98+pKen45NPPpE7RCIiIgqBfThR8+H0ciJqtFWrVmHEiBE4ffp00NnwGTNmYNOmTfjuu+9kio6IiIjqwj6cqPkw6SaiRrv77rvh8Xiwbt26oG07d+5EVlYW9u3bh169eskQHREREdWFfThR82HSTURERERERBQmvKabiIiIiIiIKEyYdBMRERERERGFCZNuIiIiIiIiojBh0k1EREREREQUJky6iYiIiIiIiMKESTcRERERERFRmDDpJiIiIiIiIgoTJt1EREREREREYcKkm4iIiIiIiChMmHQTERERERERhQmTbiIiIiIiIqIwYdJNREREREREFCb/HyKBp15T5Gf9AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e = energies[1]\n",
    "\n",
    "mask = f\"MT==454 and E=={e}\"\n",
    "ify = nfpy.data.query(mask)\n",
    "S = sandy.Fy(ify).get_mass_yield_sensitivity()\n",
    "C = pd.DataFrame(acovs[e].data.values, index=ify.ZAP.values, columns=ify.ZAP.values)\n",
    "cov_mfy = sandy.CategoryCov(S @ C @ S.T)\n",
    "\n",
    "mu = nfpy.get_mass_yield(zam=922350, e=e)\n",
    "sigma = cov_mfy.get_std()\n",
    "\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 5), sharex=True)\n",
    "\n",
    "ax = axs[0]\n",
    "ax.errorbar(x=mfy_fast.index, y=mfy_fast.T.mean(), yerr=mfy_fast.T.std(), marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"blue\", color=\"dodgerblue\", label=\"sample estimate\")\n",
    "ax.errorbar(x=mu.index, y=mu.values, yerr=sigma.values, marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"k\", color=\"k\", alpha=.4, label=\"original data\")\n",
    "ax.set(ylabel=\"mass yields\", xlabel=\"A\")\n",
    "\n",
    "ax = axs[1]\n",
    "diff_mean = (mfy_fast.T.mean() / mu  - 1) * 100\n",
    "diff_std = (mfy_fast.T.std() / sigma - 1) * 100\n",
    "ax.errorbar(x=diff_mean.index, y=diff_mean.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"dodgerblue\", label=\"$\\\\frac{m- \\\\mu}{\\\\mu} \\\\times 100$\")\n",
    "ax.errorbar(x=diff_std.index, y=diff_std.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"tomato\", label=\"$\\\\frac{s- \\\\sigma}{\\\\sigma} \\\\times 100$\")\n",
    "ax.set(ylim=[-100, 100], ylabel=\"relative difference / $\\\\%$\", xlabel=\"A\")\n",
    "ax.legend()\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9e0a5a39-6798-4e81-9ca2-34ac5f0c5ad3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-19T15:06:05.100010Z",
     "iopub.status.busy": "2026-01-19T15:06:05.099734Z",
     "iopub.status.idle": "2026-01-19T15:06:05.452809Z",
     "shell.execute_reply": "2026-01-19T15:06:05.452010Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e = energies[2]\n",
    "\n",
    "mask = f\"MT==454 and E=={e}\"\n",
    "ify = nfpy.data.query(mask)\n",
    "S = sandy.Fy(ify).get_mass_yield_sensitivity()\n",
    "C = pd.DataFrame(acovs[e].data.values, index=ify.ZAP.values, columns=ify.ZAP.values)\n",
    "cov_mfy = sandy.CategoryCov(S @ C @ S.T)\n",
    "\n",
    "mu = nfpy.get_mass_yield(zam=922350, e=e)\n",
    "sigma = cov_mfy.get_std()\n",
    "\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 5), sharex=True)\n",
    "\n",
    "ax = axs[0]\n",
    "ax.errorbar(x=mfy_he.index, y=mfy_he.T.mean(), yerr=mfy_he.T.std(), marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"blue\", color=\"dodgerblue\", label=\"sample estimate\")\n",
    "ax.errorbar(x=mu.index, y=mu.values, yerr=sigma.values, marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"k\", color=\"k\", alpha=.4, label=\"original data\")\n",
    "ax.set(ylabel=\"mass yields\", xlabel=\"A\")\n",
    "\n",
    "ax = axs[1]\n",
    "diff_mean = (mfy_he.T.mean() / mu  - 1) * 100\n",
    "diff_std = (mfy_he.T.std() / sigma - 1) * 100\n",
    "ax.errorbar(x=diff_mean.index, y=diff_mean.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"dodgerblue\", label=\"$\\\\frac{m- \\\\mu}{\\\\mu} \\\\times 100$\")\n",
    "ax.errorbar(x=diff_std.index, y=diff_std.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"tomato\", label=\"$\\\\frac{s- \\\\sigma}{\\\\sigma} \\\\times 100$\")\n",
    "ax.set(ylim=[-100, 100], ylabel=\"relative difference / $\\\\%$\", xlabel=\"A\")\n",
    "ax.legend()\n",
    "fig.tight_layout()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sandy-devel",
   "language": "python",
   "name": "sandy-devel"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}