{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "77220448",
   "metadata": {
    "id": "77220448"
   },
   "source": "# Quantum Chemistry in a Nutshell\n## Tam Ders Çalışma Ortamı (Part I + Part II) + Qiskit & PennyLane Lab\n\n**Orijinal Makaleler:**\n- [Part I – Basic Concepts](https://www.quantum-computing-info.com/quantum-chemistry-in-a-nutshell/)\n- [Part II – Post-Hartree-Fock Methods](https://www.quantum-computing-info.com/post-hartree-fock/)\n\nBu notebook, yukarıdaki iki makalenin **yapısını ve tüm temel içeriğini** takip eden interaktif bir ders ortamıdır.  \nKamu malı görseller, formüller, diyagramlar ve **çalıştırılabilir Qiskit + PennyLane laboratuvarları** içerir.\n\n> **Not:** Orijinal makalelerin tam metni yazarın sitesinde bulunmalıdır. Bu notebook eğitim amaçlı yapılandırılmış bir çalışma ortamıdır.\n"
  },
  {
   "cell_type": "markdown",
   "id": "e427dc87",
   "metadata": {
    "id": "e427dc87"
   },
   "source": "## 0. Kurulum"
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "70122ef2",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "70122ef2",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1787416910462,
     "user_tz": -180,
     "elapsed": 52644,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    },
    "outputId": "f2f965d0-f86e-4966-8165-7ad87d7f726b"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.8/9.8 MB\u001b[0m \u001b[31m54.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.2/2.2 MB\u001b[0m \u001b[31m80.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.4/12.4 MB\u001b[0m \u001b[31m76.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m327.8/327.8 kB\u001b[0m \u001b[31m22.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m52.8/52.8 MB\u001b[0m \u001b[31m16.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.4/2.4 MB\u001b[0m \u001b[31m80.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.9/54.9 kB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m368.2/368.2 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
      "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
      "  \u001b[1;31merror\u001b[0m: \u001b[1msubprocess-exited-with-error\u001b[0m\n",
      "  \n",
      "  \u001b[31m×\u001b[0m \u001b[32mpip subprocess to install backend dependencies\u001b[0m did not run successfully.\n",
      "  \u001b[31m│\u001b[0m exit code: \u001b[1;36m2\u001b[0m\n",
      "  \u001b[31m╰─>\u001b[0m See above for output.\n",
      "  \n",
      "  \u001b[1;35mnote\u001b[0m: This error originates from a subprocess, and is likely not a problem with pip.\n",
      "  Installing backend dependencies ... \u001b[?25l\u001b[?25herror\n",
      "\u001b[1;31merror\u001b[0m: \u001b[1msubprocess-exited-with-error\u001b[0m\n",
      "\n",
      "\u001b[31m×\u001b[0m \u001b[32mpip subprocess to install backend dependencies\u001b[0m did not run successfully.\n",
      "\u001b[31m│\u001b[0m exit code: \u001b[1;36m2\u001b[0m\n",
      "\u001b[31m╰─>\u001b[0m See above for output.\n",
      "\n",
      "\u001b[1;35mnote\u001b[0m: This error originates from a subprocess, and is likely not a problem with pip.\n",
      "Kurulum tamam!\n"
     ]
    }
   ],
   "source": "!pip install -q qiskit qiskit-nature qiskit-aer qiskit-algorithms pyscf\n!pip install -q pennylane pennylane-qchem\n!pip install -q matplotlib scipy numpy\nprint(\"Kurulum tamam!\")"
  },
  {
   "cell_type": "markdown",
   "id": "ba267a81",
   "metadata": {
    "id": "ba267a81"
   },
   "source": "# PART I – Temel Kavramlar\n## 1. Giriş\n\n### 1.1 Quantum chemistry as an “early-alerting indicator”\n\nKuantum kimyası, kuantum hesaplamanın **en umut verici erken uygulama alanlarından** biridir. Sebepleri:\n\n- Moleküler spin-orbitallerden qubitlere **süper verimli eşleme** vardır.\n- Klasik exact yöntemler (Full CI) elektron/orbital sayısıyla **üstel** ölçeklenir.\n- Kimya endüstrisi yeni yöntemlere her zaman açıktır.\n\n> “If we can’t make it there, we can’t make it anywhere.”\n\n### 1.2 Learning quantum chemistry\n\nKuantum hesaplama makaleleri geleneksel kuantum kimyasının teknik terimleriyle doludur. Bu boşlukları doldurmak için yüzyıllık bir disiplini baştan öğrenmek gerekir.\n\n### 1.3 Bu iki makalede neler var?\n\n**Part I:**\n- H atomu Hamiltonian’ı\n- Spin, açısal momentum, kuantum sayıları\n- Atomik ve spin-orbitaller\n- Multi-elektron atomlar\n- Atomik bağlar ve moleküler orbitaller\n- Ab initio, chemical accuracy, 1.36 kuralı\n- Born-Oppenheimer ve potansiyel enerji yüzeyi\n- Slater determinantları, Hartree-Fock, Roothaan-Hall\n- Gaussian baz setleri\n- Korelasyon ve Post-HF’ye giriş\n- Single- / Multi-reference\n- Full CI, CSF, size consistency\n\n**Part II:**\n- Second Quantization\n- Jordan-Wigner, Aspuru-Guzik / Whitfield, VQE engeli\n- MCSCF / CASSCF\n- Coupled Cluster, MP2, CCSD(T)\n- DMRG\n- Ölçeklemeler ve sınırlar\n"
  },
  {
   "cell_type": "markdown",
   "id": "cbbc0456",
   "metadata": {
    "id": "cbbc0456"
   },
   "source": "## 2. Atoms, Spin and Atomic Orbitals\n\n### 2.1 Başlangıç\n\nAtomlar: Negatif yüklü hafif **elektronlar** + pozitif yüklü ağır **çekirdek** ($Z$ proton).\n\n### 2.2 Hidrojen atomu Schrödinger denklemi\n\n$$\nE |\\psi_e\\rangle = H |\\psi_e\\rangle\n$$\n\nTek elektron için:\n\n$$\nH = \\frac{P^2}{2m_e} - \\frac{Ze^2}{r}\n$$\n\nAçısal momentum ile:\n\n$$\nH = \\frac{P_r^2}{2m_e} + \\frac{L^2}{2m_e r^2} - \\frac{Ze^2}{r}\n$$\n\nÖzdurumlar:\n\n$$\nL^2 |l,m\\rangle = \\hbar^2 l(l+1) |l,m\\rangle, \\quad L_z |l,m\\rangle = \\hbar m |l,m\\rangle\n$$\n\n$$\n(-l \\le m \\le +l)\n$$\n\n### 2.3 Kuantum sayıları\n\n- $n = 1,2,3,\\ldots$ (principal)\n- $0 \\le l < n$ (azimuthal)\n- $-l \\le m \\le +l$ (magnetic)\n- $m_s = \\pm 1/2$ (spin)\n\n### 2.4 Atomik orbitaller\n\n$$\n\\psi_{n,l,m}(r,\\theta,\\varphi) = u_n(r) \\cdot Y_{l,m}(\\theta,\\varphi)\n$$\n\n**Alt kabuklar:**\n- s ($l=0$)\n- p ($l=1$)\n- d ($l=2$)\n- f ($l=3$)\n"
  },
  {
   "cell_type": "markdown",
   "id": "d39aab94",
   "metadata": {
    "id": "d39aab94"
   },
   "source": "\n### Atomik Orbitaller – 3D Görünüm\n\n![Atomic orbital clouds](https://upload.wikimedia.org/wikipedia/commons/thumb/e/e7/Atomic-orbital-clouds_spd_m0.png/700px-Atomic-orbital-clouds_spd_m0.png)\n\n*Wikimedia Commons – Atomic-orbital-clouds spd m0*\n"
  },
  {
   "cell_type": "markdown",
   "id": "dbd1d992",
   "metadata": {
    "id": "dbd1d992"
   },
   "source": "\n### Gerçek ve Kompleks Orbitaller\n\n![Atomic orbitals spdf](https://upload.wikimedia.org/wikipedia/commons/thumb/8/8c/Atomic_orbitals_spdf_m-eigenstates_and_superpositions.png/800px-Atomic_orbitals_spdf_m-eigenstates_and_superpositions.png)\n\n*Geek3 – Wikimedia Commons*\n"
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c4c862bb",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 451
    },
    "id": "c4c862bb",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1787416911793,
     "user_tz": -180,
     "elapsed": 1324,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    },
    "outputId": "e78cc103-bd1d-4aec-9c03-93350b901df0"
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ],
      "image/png": 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xQy1btnQnPqvVtWPtiBEj1LJlS7333nuSXIvmDz74QBdeeKHX4nPnzp2aOHGiUlJS3H1Ihw4dKkleY/tKcXGxJO8F8Pr163XRRRcpMTFRCQkJSktLc2/4dbQYqt+Pw78+36lTp1rXHjx4ULfddpuaN2+u6OhopaWlqX379sccw1Pnzp01fPhwr3/Vi7UdO3bUOQ/du3d3/9xT27ZtvR5X3ycvL8/r/LZt2/SXv/xFF198sV544YVabRwuu+wyDR48WNddd52aN2+uyy+/XB999NExF/v1+f2ojrmu19WtW7dar8lmsyktLa3W6zr8NR2urKxMDzzwgNq0aSOr1apmzZopLS1N+fn5dc5N9bwBAICmdSKta6vv61loUJeioqJjJnZnz56t008/XTabTSkpKUpLS9Mrr7ziFVNj13QNMX78eGVnZ2v+/PnulhL1FRERoT59+ig6Olo9evSQJOXk5Ki0tPSIa2Cn06ldu3ZJcs13XWv0us41VH3X1Y1Rvd49PE6LxaJ27dod9/0B+BZJWwANMmDAAA0fPlwXX3yxvvjiC/Xs2VNXXnmlO3kpSe+++64mTpyojh076q233tI333yjuXPn6qyzzmr0Qi0iIkJXXnmlPvnkE9ntdv3444/au3evOxkquXqQjhgxQl999ZX+/ve/a9asWZo7d657cwN//JV/3bp1kmoWPvn5+Ro6dKhWr16tRx55RF9++aXmzp2rp556yqcxXHrppXrjjTd044036tNPP9WcOXP0zTff+HSMhjhSpahhGF6PW7ZsqUGDBunrr7/WsmXLal0fHR2tBQsW6LvvvtP48eO1Zs0aXXbZZRoxYsRRNwCrz++Hr17TsUyePFmPP/64Lr30Un300Ufunsepqal1zo1ntQoAAGg6J9K6tvoP72vWrDniNTt27FBhYaFOOumkI16zcOFCXXDBBbLZbHr55Zf19ddfa+7cubryyiu91n2NXdM1xJ///Gfl5+e7NxALNUd6H+q7rvZ0pP0sjue99sc9ATQMSVsAjRYREaGpU6dq7969evHFF93nZ86cqQ4dOujTTz/V+PHjNXLkSA0fPlx2u93r+ZmZmdq3b5/XwljSEXd8vfrqq1VYWKgvv/xS7733ntLS0jRy5Ej3z9euXas//vhDzzzzjP7+97/rwgsv1PDhw9WqVSsfvmpv77zzjkwmk0aMGCHJtZtqbm6uZsyYodtuu03nn3++VwXr0VS/H6WlpV7nN2/e7PU4Ly9P33//ve699149/PDDuuiiizRixAivr3Edr8zMzDrnobq9Q0O+fubJZrNp9uzZ6ty5s0aNGqX169fXusZsNuvss8/Ws88+qw0bNujxxx/XDz/8UOcuzZ6O9ftRHXNdr2vjxo2Nfk2HmzlzpiZMmKBnnnlGl1xyiUaMGKEzzjij1u7RAAAgeIT7urZLly7q0qWLZs2adcRq27fffluSdP755x/xPp988olsNpu+/fZbXXvttTr33HM1fPjwOq9t7JquviZPnqxHHnlETz75pJ588snjvl9aWppiYmKOuAY2m81q06aNJNd8H75Gl2qv2yVXpezh68CKigrt27fvuGP2HENSrXEO/yZZ9Xr38DgdDod7I76G3hOA/5C0BXBchg0bpgEDBmjatGnuxWv1X4c9/xr8yy+/aPHixV7PPe+881RVVaVXXnnFfc7hcOiFF16oc6xevXqpV69eevPNN/XJJ5/o8ssv9+rFVNe4hmH47a/vTz75pObMmaPLLrtMnTt3PmIMFRUVevnll495v5EjR6qyslJvvPGG+5zT6dRLL73kdV1dY0jStGnTGvU66nLeeefp119/9ZqzkpISvf7662rXrt1RKzCOJTExUd9++63S09M1YsQIbdmyxf2zgwcP1rq+uldYeXn5Ue97rN+PU089Venp6Xr11Ve97vXf//5Xv/32m3u34+MVERFRa25eeOEFqhIAAAhy4b6ufeCBB5SXl6cbb7yx1rpk+fLleuqpp9SzZ0+vvrqHi4iIcPd/rbZ9+3bNmjXL67rjWdM1xP3336+7775bU6ZM8XrvGyMiIkLnnHOOPv/8c68E5v79+/X+++/rjDPOUEJCgiTXun3x4sVelcv5+fl6//33a923Y8eOWrBggde5119/3adrw44dO0qS1zgOh0Ovv/6613WnnnqqUlNT9eabb6qqqsp9/v3336/VfqG+9wTgP5ZjXwIAR/e3v/1N48aN04wZM3TjjTfq/PPP16effqqLLrpIo0eP1rZt2/Tqq6/qpJNO8qo+GDNmjAYPHqx7771X27dv10knnaRPP/30qD26rr76at19992SVOur7926dVPHjh119913a8+ePUpISNAnn3xy3P2fqqqq9O6770pybfq1Y8cOffHFF1qzZo3OPPNMr4XLoEGDlJycrAkTJujWW2+VyWTSO++8c9SvM1UbO3asBgwYoLvuukubN29Wt27d9MUXX7gXvdVfUUpISNCf/vQn/eMf/1BlZaVat26tOXPmaNu2bcf1Oj3de++9+uCDD3Tuuefq1ltvVUpKiv79739r27Zt+uSTT7w2D2uMZs2aae7cuTrjjDM0fPhwLVq0SK1bt9YjjzyiBQsWaPTo0crMzFR2drZefvllZWRkeG2KdiRH+/2IjIzUU089pWuuuUZDhw7VFVdcof379+v5559Xu3btdMcddxzXa6p2/vnn65133lFiYqJOOukkLV68WN99951SU1N9cn8AAOA/4byuveqqq7R06VI9//zz2rBhg3vzqRUrVuhf//qXUlNTNXPmTEVGRh7xHqNHj9azzz6rUaNG6corr1R2drZeeuklderUySuBebxruob45z//qYKCAk2aNEnx8fHH1R7rsccec69Rb775ZlksFr322msqLy/XP/7xD/d199xzj959910NHz5ct99+u2JjY/X666+rdevWys3N9WotcN111+nGG2/UxRdfrBEjRmj16tX69ttv1axZs+N63Z569Oih008/XVOmTNHBgweVkpKiDz/80CsxK0lRUVF66KGHNHnyZI0YMUKXXXaZtm/frjfffFMdOnTwiru+9wTgRwYA1MP06dMNScbSpUtr/czhcBgdO3Y0OnbsaFRVVRlOp9N44oknjMzMTMNqtRp9+vQxZs+ebUyYMMHIzMz0em5ubq4xfvx4IyEhwUhMTDTGjx9vrFy50pBkTJ8+vdZY+/btMyIiIowuXbrUGeeGDRuM4cOHG3FxcUazZs2M66+/3li9enWt+z344INGff4ncMKECYYk97+YmBijXbt2xsUXX2zMnDnTcDgctZ7z008/GaeffroRHR1ttGrVyrjnnnuMb7/91pBk/Pjjj173Pvz9yMnJMa688kojPj7eSExMNCZOnGj89NNPhiTjww8/dF+3e/du46KLLjKSkpKMxMREY9y4ccbevXsNScaDDz541Ne0bds2Q5Lxz3/+86jXbdmyxbjkkkuMpKQkw2azGQMGDDBmz57tdc2PP/5oSDI+/vjjOsfwfM+HDh1q9OjRw+u6zZs3Gy1btjS6d+9u5OTkGN9//71x4YUXGq1atTKioqKMVq1aGVdccYXxxx9/HPXe1Y71+2EYhvGf//zH6NOnj2G1Wo2UlBTjqquuMnbv3u11zYQJE4zY2Nhaz63r9+bw9zwvL8+45pprjGbNmhlxcXHGyJEjjd9//93IzMw0JkyY4L7uaP+dqv7Ztm3bjvg6AABA45yo69pqs2bNMkaMGGEkJycbVqvV6NSpk3HXXXcZOTk5ta6t63W+9dZbRufOnQ2r1Wp069bNmD59eq0YGrumq+u11GcN5XA4jCuuuMKwWCzGrFmz6vU+HGm9t2LFCmPkyJFGXFycERMTY5x55pnGzz//XOu6lStXGkOGDDGsVqvRunVr49FHHzX+7//+z5BkZGVlecX297//3WjWrJkRExNjjBw50ti8eXO914bV623PzxFDhw41hg4d6nXdli1bjOHDhxtWq9Vo3ry5cd999xlz586t9VzDMIz/+7//c/9On3rqqcaCBQuMU0891Rg1alSj7wnA90yGUY/yLwAIEgcOHFDLli31wAMP6P777w90OE1i1qxZuuiii7Ro0SINHjw40OEEtRPx9wMAAIQm1i3h54477tCrr76q4uLiRm9qGwhOp1Pp6em66KKLvFq1AQgsetoCCCkzZsyQw+HQ+PHjAx2KX5SVlXk9ru6FlpCQoL59+wYoqtAR7r8fAAAgfLBuCW2Hr9tzc3P1zjvv6IwzzgjqhK3dbq/Vuu3tt99Wbm6uhg0bFpigANSJnrYAQsIPP/zg3nV27NixateuXaBD8ovJkyerrKxMAwcOVHl5uT799FP9/PPPeuKJJxQdHR3o8ILWifL7AQAAQh/rlvAwcOBADRs2TN27d9f+/fv11ltvqaCgIOirppcsWaI77rhD48aNU2pqqlasWKG33npLPXv21Lhx4wIdHgAPtEcAEBKGDRumn3/+WYMHD9a7776r1q1bBzokv3j//ff1zDPPaPPmzbLb7erUqZNuuukm3XLLLYEOLaidKL8fAAAg9LFuCQ/33XefZs6cqd27d8tkMqlv37568MEHNXz48ECHdlTbt2/Xrbfeql9//dW9wdh5552nJ598Uunp6YEOD4AHkrYAAAAAAAAAEEToaQsAAAAAAAAAQYSkLQAAAAAAAAAEkRN+IzKn06m9e/cqPj5eJpMp0OEAAACgAQzDUFFRkVq1aiWz+cSoR2D9CgAAELrqu3494ZO2e/fuVZs2bQIdBgAAAI7Drl27lJGREegwmgTrVwAAgNB3rPXrCZ+0jY+Pl+R6oxISEvw+ntPpVE5OjtLS0k6YapBwxDyGB+YxPDCP4YF5DA+BmMfCwkK1adPGvaY7EbB+RWMwj+GBeQwPzGN4YB7DQzCvX0/4pG31V8oSEhKabNFrt9uVkJDAf6lDGPMYHpjH8MA8hgfmMTwEch5PpDYBrF/RGMxjeGAewwPzGB6Yx/AQzOtXfqsAAACAJtKuXTuZTKZa/yZNmhTo0AAAABBETvhKWwAAAKCpLF26VA6Hw/143bp1GjFihMaNGxfAqAAAABBsSNoCAAAATSQtLc3r8ZNPPqmOHTtq6NChAYoIAAAAwYikLQAAQBBzOByqrKwMdBj14nQ6VVlZKbvd7rOeYJGRkYqIiPDJvYJNRUWF3n33Xd15550nVE9eAAAQ3li/+mb9StIWAAAgCBmGoaysLOXn5wc6lHozDENOp1NFRUU+TUImJSWpRYsWYZfYnDVrlvLz8zVx4sSjXldeXq7y8nL348LCQkmuDxlOp9OfIbrHqZ5bhC7mMTwwj+GBeQwPzGNthmFo//79IbV+leRev/pSUlKSmjdvXuf6tb6/MyRtAQAAglB1wjY9PV0xMTEhkbA0DENVVVWyWCw+idcwDJWWlio7O1uS1LJly+O+ZzB56623dO6556pVq1ZHvW7q1Kl6+OGHa53PycmR3W73V3huTqdTBQUFMgyD3bFDGPMYHpjH8MA8hgfmsbaioiKVl5crPT1dNpstZNavTqdTZrPZZ+tXu92u7OxslZSUKD4+vtY19U0Qk7QFAAAIMg6Hw52wTU1NDXQ49ebrpK0kRUdHS5Kys7OVnp4eNq0SduzYoe+++06ffvrpMa+dMmWK7rzzTvfjwsJCtWnTRmlpaUpISPBnmJJcH0pNJpPS0tL4UBrCmMfwwDyGB+YxPDCP3hwOhw4ePKgWLVqE1PpVkiorKxUZGemz+8XHx8tsNis7O1upqam11q82m61e9yFpCwAAEGSqe4DFxMQEOJLgUP0+VFZWhk3Sdvr06UpPT9fo0aOPea3VapXVaq113mw2N9mHRJPJ1KTjwT+Yx/DAPIYH5jE8MI81KioqZDKZFBsbGxIVttUMw3DH68u4q98Hh8NRKyFc39+XoPmtmjp1qvr376/4+Hilp6dr7Nix2rhx4zGf9/HHH6tbt26y2Ww6+eST9fXXXzdBtAAAAP4XSgtefwq398HpdGr69OmaMGGCLBZqKAAAQPgIt3VbY/nifQiapO38+fM1adIkLVmyRHPnzlVlZaXOOecclZSUHPE5P//8s6644gr99a9/1cqVKzV27FiNHTtW69ata8LIAQAAgPr77rvvtHPnTl177bWBDgUAAABBKmj+tP/NN994PZ4xY4bS09O1fPly/elPf6rzOc8//7xGjRqlv/3tb5KkRx99VHPnztWLL76oV1991e8xAwAAAA11zjnnyDCMQIcBAACAIBY0SdvDFRQUSJJSUlKOeM3ixYu9NmWQpJEjR2rWrFlHfE55ebnKy8vdjwsLCyW5vqbmdDqPI+L6cTqd7p3pELqYx/DAPIYH5jE8MI/eqt+P6n+hZMGCBZo2bZqWL1+uffv26dNPP9XYsWOP657V70Nd6zV+ZwAAAHA8Fi5cqOeee869fv3ss8+Oe/3qC0GZtHU6nbr99ts1ePBg9ezZ84jXZWVlqXnz5l7nmjdvrqysrCM+Z+rUqXr44Ydrnc/JyZHdbm980PXkdDpVUFAgwzBoVB3CmMfwwDyGB+YxPDCP3iorK+V0OlVVVaWqqqpAh1NvhmGoqKhIPXv21NVXX61LL71UDofjuF9DVVWVnE6ncnNza23kUFRUdFz3BgAAwImtpKREvXr10rXXXqs///nPgQ7HLSiTtpMmTdK6deu0aNEin997ypQpXtW5hYWFatOmjdLS0pSQkODz8Q7ndDplMpmUlpbGh9IQxjyGB+YxPDCP4YF59Ga321VUVCSLxRJyG1Wdd955uvDCC92PIyIivF7Dyy+/rGnTpmnXrl1KTEzUkCFD9PHHHx/1nhaLRWazWampqbLZbF4/O/wxAAAA0BCjRo3S+eeff8TNw15++WU999xzXuvXmTNn+j2uoPsUcMstt2j27NlasGCBMjIyjnptixYttH//fq9z+/fvV4sWLY74HKvVKqvVWuu82Wz2+4fEDXsL9cTXG5RbVKZx/ct07Rkd/Doe/MtkMjXJ7w38i3kMD8xjeGAea5jNZplMJve/UGEYhjtez/+sPl62bJluu+02vfPOOxo0aJAOHjyohQsXHvM1Vt+jrt8Pfl9C1/q9BXp3yQ5VOQzde243pcbVXqMDAAAE0rJly3TrrbfWWr82haBJ2hqGocmTJ+uzzz7TvHnz1L59+2M+Z+DAgfr+++91++23u8/NnTtXAwcO9GOkjVfhcGrR5lxJ0vYDpQGOBgAAhJoxLyxSTlH5sS/0sbR4q76cfMZx32fnzp2KjY3V+eefr/j4eGVmZqpPnz4+iBChZsnWXI1/6xdVOlw9mzfuL9IH15+uWGvQfDwBAAA+wPq18YJmVTRp0iS9//77+vzzzxUfH+/uS5uYmKjo6GhJ0tVXX63WrVtr6tSpkqTbbrtNQ4cO1TPPPKPRo0frww8/1LJly/T6668H7HUcTWJ0TQ+2AntlACMBAAChKKeoXFmF/u/B7y8jRoxQZmamOnTooFGjRmnUqFG66KKLFBMTE+jQ0MSembPRnbCVpDW7C/T895t033ndAxgVAADwNdavjRc0SdtXXnlFkjRs2DCv89OnT9fEiRMlubLbnl+BGzRokN5//3397//+r+677z517txZs2bNOurmZYGU5JG0zS8laQsAABomLT4wXx/31bjx8fFasWKF5s2bpzlz5uiBBx7QQw89pKVLlyopKcknYyD4Ld9xUEu359U6/9GyXbpzRBfZIiMCEBUAAPAH1q+NFzRJW8MwjnnNvHnzap0bN26cxo0b54eIfC/BI2lbWEbSFgAANIwvvuIVaBaLRcOHD9fw4cP14IMPKikpST/88ENQ7dQL//p42W738T8u6aWfNx/QrFV7lV9aqW/XZ+nCU1oHMDoAAOBLrF+PY1y/3h1eIswmxdssKrJXKZ+kLQAACEPFxcXavn27e3Oxbdu2adWqVUpJSdGaNWu0detW/elPf1JycrK+/vprOZ1Ode3aNcBRoykt2era4yEywqQxvVqpbUqMZq3aK0n6dMUekrYAAKBJBev6laRtE0uKjlSRvUoFpRWBDgUAAMDnli9frhEjRrgf33nnnZKkCRMm6LrrrtOnn36qhx56SHa7XZ07d9YHH3ygHj16BCpcNLH9hXZtz3VtyNs7I0nRURE6rX2KWibatK/Arl+25aq8yiGrhRYJAACgaQTr+pWkbRNLjI7UrrwyFdirZBiGO4sPAAAQDoYOHSqn03nENU5d7a5w4qiuspWk0zukSpJMJpMGd2qmmct3y17p1Iod+RrYMTVQIQIAgBNMsK5fzce+BL6UGOPqa+twGiourwpwNAAAAEDT+WXbQffxaR1S3MeDO9UkaX/afKBJYwIAAAhGJG2bWKKtZjOyAvraAgAA4ASydneBJMlskvq2TXafH9yxmft4EUlbAAAAkrZNrbrSVpLyS0naAgAA4MTgdBranF0sSWqbEqNYa02ntvQEmzqmxUqS1u8tkL3SEZAYAQAAggVJ2yaWFE2lLQAAAE48e/LLVHYoGdspPb7Wz3u3SZIkVToM/Z5V1JShAQAABB2Stk0skaQtAAAATkDVVbaS1Ll5XK2f985Ich+v3Z3fBBEBAAAEL5K2TYz2CAAAADgRbcquqZ7tnF47aXtyRqL7eM2h3rcAAAAnKpK2TcxzI7L8sooARgIAAAA0nU37PSpt62iPcFLLBEWYTZKktXtI2gIAgBMbSdsmlhRDewQAAACceDZ5tEfomB5b6+e2yAh1ae5K5v6xv0hlFWxGBgAATlwkbZuYV09b2iMAAADgBLE9t0SS1DopWjFRljqvOallgiTJaUhbcorrvAYAAOBEQNK2ibERGQAAAE40JeVV7v0cWidHH/G6ri1qet1uzCo64nUAAADhjqRtE0tiIzIAABDGnnrqKQ0YMEDx8fFKT0/X2LFjtXHjxkCHhQDbk1/mPs5IOnLStro9giT9kU3SFgAA+F+wrl9J2jax6MgIWQ5tsJBPpS0AAAgzCxcu1M0336wlS5Zo7ty5qqys1DnnnKOSkpJAh4YA2pNXk7Q9eqWtR9KWSlsAANAEgnX9StK2iZlMJiXYIiRJhSRtAQBAmJk9e7YmTpyoHj16qHfv3poxY4Z27typ5cuXS5IMw9BDDz2ktm3bymq1qlWrVrr11lsDHDX8bbdHpW2ro1TatkiwKd7m6nf7x3562gIAAP8L1vVr3TsAwK/irRYdLK1SfmlFoEMBAADwq4KCAklSSkqKJOmTTz7Rc889pw8//FA9evRQVlaWVq9eHcgQ0QS8Km2PkrQ1mUzq0jxey3fkaU9+mYrslYq3RR7xegAAAF8LlvUrSdsAqK60LalwqNLhVGQEBc8AAKAeXhsqFWc3/bhx6dL/zG/w05xOp26//XYNHjxYPXv2lCTt3LlTLVq00PDhwxUZGam2bdtqwIABvo4YQcazp+3R2iNIUpfmcVq+I0+StDm7WH3aJvs1NgAA4EesXxuNpG0AJNhq3vaCsko1i7MGMBoAABAyirOlor2BjqLeJk2apHXr1mnRokXuc+PGjdO0adPUoUMHjRo1Suedd57GjBkji4VlaTjbk1fqPj5apa0kdUyLcx9vzSkhaQsAQChj/dporI4DoLrSVpLyS0naAgCAeopLD5lxb7nlFs2ePVsLFixQRkaG+3ybNm20ceNGfffdd5o7d65uvvlm/fOf/9T8+fMVGcnX4MNVdaVts7go2SIjjnpth7RY9/G2A2xgBwBASGP92mgkbQMgwepdaQsAAFAvjfiKV1MzDEO33HKLZs2apXnz5ql9+/a1romOjtaYMWM0ZswYTZo0Sd26ddPatWvVt2/fAEQMf6t0OJVdVC7p2FW2ktS+WU2lLUlbAABCHOvXRiNpGwDxHpW2BWVsRgYAAMLHrbfeqg8//FCff/654uPjlZWVJUlKTExUdHS0ZsyYIYfDodNOO00xMTF69913FR0drczMzABHDn/JLa6QYbiOmyfYjnl9RnK0LGaTqpyGtuQU+zk6AABwogvW9Ss7YAXA4T1tAQAAwsVrr72mgoICDRs2TC1btnT/+89//iNJSkpK0htvvKHBgwerV69e+u677/Tll18qNTU1wJHDX7KL7O7jtPhjtwWLjDCrbWqMJGl7bomcTsNvsQEAAATr+pVK2wCIt3r3tAUAAAgXFRUVslgsMplMdf587NixGjt2bNMGhYDKOdQaQapf0laSOjSL1dacEtkrndpXaK9XWwUAAIDGCNb1K5W2AZDoUWlL0hYAAADhzDNpmx5/7PYIktQhraav7VZaJAAAgBMQSdsASPDqaUvSFgAAAOGrMZW27VJj3cc7D5b6PCYAAIBgR9I2AOKt9LQFAADAiSG7EUnbNik17RBI2gIAgBMRSdsA8Ky0zS+tCGAkAAAAgH95t0eoX9K2bUqM+3j3wTKfxwQAABDsSNoGAJW2AAAAOFHkFNckbVPjour1nFZJ0TIf2guESlsAAHAiImkbAJYIk+KsrmrbfJK2AAAACGPVlbZJMZGyWiKOcbVLZIRZLRNdLRJ25ZG0BQAAJx6StgGSGO2qMsgvJWkLAACA8GQYhjtpmxZXv9YI1ar72uaXVqrQzpoZAACcWEjaBkhybKQkV09bp9MIcDQAAACA7xWXV6ms0iFJSk9oWNLWs6/tLlokAACAEwxJ2wBJjnFV2joNUTkAAACAsOS5CVmzhlbaJpO0BQAAJy6StgGSHBPpPs6jRQIAAADCUF5phfs4NbaBlbapnknbMp/FBAAAEApI2gZIdaWt5L2YBQAACGVPPfWUBgwYoPj4eKWnp2vs2LHauHFjoMNCgBwsqSlOSImNPMqVtWV4VNrupNIWAAD4SbCuX0naBohXpW0JSVsAABAeFi5cqJtvvllLlizR3LlzVVlZqXPOOUclJSWBDi1o7NmzR3/5y1+Umpqq6OhonXzyyVq2bFmgw/ILz3VucmzUUa6srXojMknalUfSFgAA+Eewrl9J2gZIklelLe0RAABAeJg9e7YmTpyoHj16qHfv3poxY4Z27typ5cuXu68xmUx65ZVXdO655yo6OlodOnTQzJkzAxh108nLy9PgwYMVGRmp//73v9qwYYOeeeYZJScnBzo0v/D8RllKTMOStmlxVtkiXR9XqLQFAAD+EqzrV5K2AZLiUWlApS0AAAhXBQUFkqSUlBSv8/fff78uvvhirV69WldddZUuv/xy/fbbb4EIsUk99dRTatOmjaZPn64BAwaoffv2Ouecc9SxY8dAh+YXBz2StkkNTNqaTCb3ZmS788rkdBo+jQ0AAKAuwbJ+tfjtzjiqJK+NyEjaAgCAY7ts9mU6UHagycdtFt1M/zn/Pw1+ntPp1O23367BgwerZ8+eXj8bN26crrvuOknSo48+qrlz5+qFF17Qyy+/7JOYg9UXX3yhkSNHaty4cZo/f75at26tm2++Wddff32gQ/MLz+KElAa2R5Cktikx2pRdrIoqp7KLytUi0ebL8AAAgJ+xfm08krYBkkJ7BAAA0EAHyg4ouzQ70GHU26RJk7Ru3TotWrSo1s8GDhxY6/GqVauaKLLA2bp1q1555RXdeeeduu+++7R06VLdeuutioqK0oQJE+p8Tnl5ucrLy92PCwsLJbk+VDidTr/H7HQ6ZRhGo8Y66JG0TYq2NPgeGck1fW135BYrPb7hiV+4HM88Ingwj+GBeQwPzKO36vej+l+1QK5fPeOoz3WGYejmm2/WunXrtHDhwlrPP/30073OnX766Vq9enWd41S/D3Wt1+r7O0PSNkCS2IgMAAA0ULPoZiEz7i233KLZs2drwYIFysjI8ENUocnpdOrUU0/VE088IUnq06eP1q1bp1dfffWISdupU6fq4YcfrnU+JydHdrvdr/FKrpgLCgpkGIbM5oZ1V9ufX7OBR2VxvrLLTA16fnKkw328fvt+ZcZUNej5qHE884jgwTyGB+YxPDCP3iorK+V0OlVVVaWqqpr/v061pUoB6HCUakv1iuNIDMOQw+Fab9x+++366quv9P3336tFixa1nu9wOLzOVSdm6xqnqqpKTqdTubm5ioyM9PpZUVFRvV4DSdsASfaqtCVpCwAAjq0xX/FqaoZh6JZbbtGsWbM0b948tW/fvs7rlixZoquvvtrrcZ8+fZoqzIBp2bKlTjrpJK9z3bt31yeffHLE50yZMkV33nmn+3FhYaHatGmjtLQ0JSQk+C3Wak6nUyaTSWlpaQ3+UFpS+bskKc5qUauWzRs8dve2hqTdkqQCh0Xp6ekNvgdcjmceETyYx/DAPIYH5tGb3W5XUVGRLBaLLJaadGOorF/vuOMOff755/rxxx/VuXPnOq9bunSprrnmGvfjX3/9VaeccorX661msVhkNpuVmpoqm827vdPhj4+EpG2AREdFyBZplr3SSdIWAACEjVtvvVUffvihPv/8c8XHxysrK0uSlJiYqOjomq+6f/zxxzr11FN1xhln6L333tOvv/6qt956K1BhN5nBgwdr48aNXuf++OMPZWZmHvE5VqtVVqu11nmz2dxkHxJNJlOjxqte56bERjUq1rapse7j3Xl2PhQfp8bOI4IL8xgemMfwwDzWMJvNMplM7n+hwjAM3Xbbbe71a0JCgvbv3y+p9vp15syZ6t+/f631a12vt/p9qOv3o76/L/xWBVB1tS09bQEAQLh47bXXVFBQoGHDhqlly5buf//5j3eVxcMPP6wPP/xQvXr10ttvv60PPvigVgVqOLrjjju0ZMkSPfHEE9q8ebPef/99vf7665o0aVKgQ/M5h9NQfplrnZvciE3IJKm1R0/bvfllPokLAADAU7CuX6m0DaDkmCjtK7Arr6RChmGE1F8iAAAA6lJRUSGLxXLMdU2rVq00Z86cJooqePTv31+fffaZpkyZokceeUTt27fXtGnTdNVVVwU6NJ8rKKtU9b4cKTGRR7/4CBJskYq3WlRUXqV9BSRtAQCA7wXr+pWkbQAlx7oWr1VOQ8XlVYq3NW4xCwAAgNBx/vnn6/zzzw90GH530GOzXc/9HBqqVVK0Nu4v0t4Cu5xOQ2YzhQ4AACD80R4hgDwXr/m0SAAAAEAYyffYt6Gx7REkqVWSa7OOiiqnckvYCwIAAJwYqLQNIM+k7cGSCrVJiQlgNAAAAE3DqP7OPMKad6Vt479R1irJu69tWnztTdkAAAD8KRDrVyptA8iz4iCvlKoBAAAAhI+CsppvkiUeZ3uEamxGBgAAThQkbQPIs+KApC0AAADCSaG9yn2cYGv8F/yq2yNI0t4C+3HFBAAAECpI2gZQimelbQk9bQEAABA+vCpto4+jPUIilbYAAODEQ9I2gJK8NiKj0hYAAADho9BXSVvaIwAAgBMQSdsASvHciIykLQAAAMKIZ9I24TiSti0SbTKZXMckbQEAwImCpG0AJXn1tKU9AgAAAMKHr9ojREaY1Tze1deWnrYAAOBEQdI2gLx72lJpCwAAgPDhmbRNsDU+aSvVbEaWU1Su8irHcd0LAAAgFJC0DaCYqAhFRbimgEpbAAAQDl577TX17t1bCQkJSkhI0MCBA/Xf//430GEhAArtrvVtdGSEoizH97GjpUdf2yyqbQEAgA8F6/qVpG0AmUwmJce6qg6otAUAAOGgdevWmjp1qpYvX65ly5bprLPO0oUXXqj169cHOjQ0sepK2+NpjVCttUfSdg99bQEAgA8F6/qVpG2AJR/ajCyPjcgAAEAYOP/883Xeeeepc+fO6tKlix5//HHFxcVpyZIlMgxDDz30kNq2bSur1apWrVrp1ltvDXTI8BNfJm1bJdrcx3vzqbQFAAC+E6zrV0uTjIIjqk7allc5VVbhUHRURIAjAgAA8A2Hw6GPP/5YJSUlGjhwoD755BM999xz+vDDD9WjRw9lZWVp9erVgQ4TflBe5ZC90ilJSog+/o8crTwqbfdRaQsAAPwkmNavJG0DrLo9giQdLK1Q66joo1wNAABOZNsuvkRVBw40+biWZs3U/pOZ9b5+7dq1GjRokOx2u+Li4vTZZ5/ppJNO0jfffKMWLVpo+PDhioyMVNu2bTVgwAA/Ro5AKSyrch/7pNLWI2m7t4CkLQAAoYL1a+ORtA2w6kpbSTpYXOHVrwsAAMBT1YEDqtq/P9BhHFPXrl21atUqFRQUaObMmZowYYLmz5+vcePGadq0aerQoYNGjRql8847T2PGjJHFwpI03FS3RpCkBJuve9rSHgEAgFDB+rXxWCEHWGqc1X2cW1IewEgAAECwszRrFhLjRkVFqVOnTpKkfv36aenSpXr++ef12muvaePGjfruu+80d+5c3XzzzfrnP/+p+fPnKzLy+BN7CB6Fdo+krQ8qbZNiImWLNMte6dSevNLjvh8AAGgarF8bj6RtgKXG1lTa5hazGRkAADiyhnzFK5g4nU6Vl7v+OB0dHa0xY8ZozJgxmjRpkrp166a1a9eqb9++AY4SvuRZaeuL9ggmk0mtkqK1NadEWQVU2gIAECpYvzYeSdsAS43zaI9QQtIWAACEtv/3//6fRo8erczMTBUVFen999/XvHnz9O2332rGjBlyOBw67bTTFBMTo3fffVfR0dHKzMwMdNjwscIy31baSlKLBJu25pSopMKhInul4n3QdgEAACBY169mv4+Ao0rxqLQ9QHsEAAAQ4nJycjRhwgR17dpVZ599tpYuXapvv/1WI0aMUFJSkt544w0NHjxYvXr10nfffacvv/xSqampgQ4bPlbo40pbSWqRaHMfU20LAAB8JVjXr1TaBlgzj562B2mPAAAAQtzrr78ui8Uik8lU62djx47V2LFjmz4oNLlCe5X7ON7mm48cLT2StvsK7OrcPN4n9wUAACe2YF2/UmkbYJ6Vtrm0RwAAAEAYKPJD0rZFgkelbSGVtgAAILyRtA2w5JgoVSfySdoCAAAgHBTZPXra+qj3bIvEaPcx7REAAEC4I2kbYBFmk5JjXNW2ucX0tAUAAEDoKy6vqbSNs/qnPQIAAEA4I2kbBFIPtUg4SKUtAAAAwkCxR3uEOB+1R2ju0R5hP+0RAABAmCNpGwSq+9qWVjhUVuEIcDQAACBYGIYR6BCCAu9D6PFHT9vU2ChFRrj6ilFpCwBAcGLd5uKL94GkbRBoFmd1H+eW0CIBAIATXWSkqwdoaWlpgCMJDtXvQ/X7guBXdKg9QlSEWVZLhE/uaTab3NW2WQVlPrknAADwDdav3nyxfvXNn71xXKorbSUpt7hCGckxAYwGAAAEWkREhJKSkpSdnS1JiomJkal659IgZhiGqqqqZLFYfBKvYRgqLS1Vdna2kpKSFBHhm+Qf/K96IzJftUao1iLBpt15ZcorrZS90iFbJL8TAAAEA9avNffz1fqVpG0QSI2rSdrS1xYAAEhSixYtJMm98A0FhmHI6XTKbDb7dJGelJTkfj8QGqo3IvNVa4RqLRK9+9pmpsb69P4AAKDxWL/W8MX6laRtEEj1qLQ9UEx7BAAAIJlMJrVs2VLp6emqrKwMdDj14nQ6lZubq9TUVJnNvunCFRkZSYVtiDEMw70RWZzVtx83WnokbfcVkLQFACCYsH518dX6laRtEEj16GlLpS0AAPAUERERMklLp9OpyMhI2Ww2ny16EXrslU5VOV2bb/i60ra6p63kqrQFAADBh/WrbwRXNCcor562JG0BAAAQworKaypr4qy+3TyuZWK0+3hfAUlbAAAQvoIqabtgwQKNGTNGrVq1kslk0qxZs456/bx582QymWr9y8rKapqAfaRZnPdGZAAAAECoqm6NIPm3p20WSVsAABDGgippW1JSot69e+ull15q0PM2btyoffv2uf+lp6f7KUL/SImtaY+QW0JPWwAAAISuIpK2AAAAxy2oetqee+65Ovfccxv8vPT0dCUlJfk+oCaSFB0ps0lyGvS0BQAAQGgrLq9J2vp6I7L0eKtMJskwpH30tAUAAGEsqJK2jXXKKaeovLxcPXv21EMPPaTBgwcf8dry8nKVl9dUsxYWFkpyNR52Op1+j9XpdMowjFpjJcdEKbekQgeKy5skDhyfI80jQgvzGB6Yx/DAPIaHQMwjvzPBp8ju0dPWx5W2kRFmNYuzKqeoXFkFZT69NwAAQDAJ6aRty5Yt9eqrr+rUU09VeXm53nzzTQ0bNky//PKL+vbtW+dzpk6dqocffrjW+ZycHNnt/v9rvdPpVEFBgQzD8NqVLtFmVm6JlFtcrv3798tkMvk9FjTekeYRoYV5DA/MY3hgHsNDIOaxqKioScZB/Xm3R/DtRmSS1DLRppyicuUUlavK4ZQlgv/NAAAA4Sekk7Zdu3ZV165d3Y8HDRqkLVu26LnnntM777xT53OmTJmiO++80/24sLBQbdq0UVpamhISEvwes9PplMlkUlpamteHmeaJ27Q1167yKkNxSamK9fFXyeBbR5pHhBbmMTwwj+GBeQwPgZhHm8127IvQpDzbI8T7YU3bIsGmNSqQ05ByisvVMjHa52MAAAAEWthlBgcMGKBFixYd8edWq1VWq7XWebPZ3GQfLkwmU63xUuJqYsovq1J8dFSTxILGq2seEXqYx/DAPIYH5jE8NPU88vsSfDwrbX3d01by3oxsX4GdpC0AAAhLYbfKXbVqlVq2bBnoMBqsWWxNkvZAcflRrgQAAACCl1elrY972kreSdv9BWxGBgAAwlNQVdoWFxdr8+bN7sfbtm3TqlWrlJKSorZt22rKlCnas2eP3n77bUnStGnT1L59e/Xo0UN2u11vvvmmfvjhB82ZMydQL6HRUmJrKm0PllQEMBIAAACg8Twrbf3R8qvlYZW2AAAA4SiokrbLli3TmWee6X5c3Xt2woQJmjFjhvbt26edO3e6f15RUaG77rpLe/bsUUxMjHr16qXvvvvO6x6hIjWuptI2t5ikLQAAAEJTiZ8rbZsn1CRtswpJ2gIAgPAUVEnbYcOGyTCMI/58xowZXo/vuece3XPPPX6Oqmk080ja5tAeAQAAACHKM2kbE+WPStuaHrZZVNoCAIAwFXY9bUNVWnxNewR62gIAACBUlVT4eSMyz0pbkrYAACBMkbQNEs3iPJO2tEcAAAAIRw899JBMJpPXv27dugU6LJ8qKXdIkswmyRbp+48b0VERSoyOlCTtKyzz+f0BAACCQVC1RziReSZtc4qoGAAAAAhXPXr00Hfffed+bLGE15K8uj1CrNUik8nklzFaJtpUUFap/QXlMgzDb+MAAAAESnitEENYrNWi2KgIlVQ4lFNEewQAAIBwZbFY1KJFi0CH4TfV7RFi/dDPtlqLRJt+zypShcOpgyUVSvUogAAAAAgHtEcIItV9bUnaAgAAhK9NmzapVatW6tChg6666irt3Lkz0CH5VHV7hFhrhN/G8Oxru4++tgAAIAxRaRtEmsVZtT23VIX2KtkrHbJF+m+hCwAAgKZ32mmnacaMGeratav27dunhx9+WEOGDNG6desUHx9f53PKy8tVXl7zR/3CwkJJktPplNPp9HvMTqdThmHUayzDMGoqba0Wv8XXPKGmsnZfQZlOaln3e4caDZlHBC/mMTwwj+GBeQwPgZjH+o5F0jaIVFfaSlJuSYVaJ0UHMBoAAAD42rnnnus+7tWrl0477TRlZmbqo48+0l//+tc6nzN16lQ9/PDDtc7n5OTIbvd/lanT6VRBQYEMw5DZfPQv6pVVOmQYruNIOZWdne2XmGJNle7jTbtzdHKKX4YJKw2ZRwQv5jE8MI/hgXkMD4GYx6KionpdR9I2iHgmbXOKyknaAgAAhLmkpCR16dJFmzdvPuI1U6ZM0Z133ul+XFhYqDZt2igtLU0JCQl+j9HpdMpkMiktLe2YH2Y823wlx0crPT3dLzF1zjBJ2iFJKnFG+m2ccNKQeUTwYh7DA/MYHpjH8BCIebTZbMe+SCRtg0panHfSFgAAAOGtuLhYW7Zs0fjx4494jdVqldVae6Mts9ncZB8uTCZTvcYrraz5ul+c1eK3+FolxbiP9xeV82G5nuo7jwhuzGN4YB7DA/MYHpp6Hus7Dr9VQaRZPElbAACAcHb33Xdr/vz52r59u37++WdddNFFioiI0BVXXBHo0HyipLzKfRxr9V99SIvEmgqVLDYiAwAAYYhK2yDiWWl7oJikLQAAQLjZvXu3rrjiCuXm5iotLU1nnHGGlixZorS0tECH5hNNlbRNsFkUHRmhskqH9hWU+W0cAACAQCFpG0QO72kLAACA8PLhhx8GOgS/KqnwSNpG+e+jhslkUstEm7YeKNH+QtbNAAAg/NAeIYiQtAUAAEAoKyl3uI9jrRF+Hau6RUJxeZWK7JV+HQsAAKCpkbQNIqlxUe7jHNojAAAAIMQ0VXsESWqRQF9bAAAQvkjaBhGrJUKJ0ZGS6GkLAACA0FPclElbz83ICknaAgCA8ELSNshUt0igPQIAAABCTWlFTXuEOD+3R2jpkbTdR6UtAAAIMyRtg0xanCtpW1rh8Pp6GQAAABDsvNoj+HEjMklqTnsEAAAQxkjaBplmbEYGAACAENWU7RFaJka7j2mPAAAAwg1J2yBTXWkrsRkZAAAAQotnewR/J22bJ9asm6m0BQAA4YakbZBJ86i0PUClLQAAAEKId6Wtf3vaNou1ymI2SaKnLQAACD8kbYNMs7go9zGVtgAAAAglpRVN19PWbDa5+9rupz0CAAAIMyRtg0waPW0BAAAQokrKa9ojREf6t9JWklokupK2B0sqZK90HONqAACA0EHSNsiQtAUAAECoKjvU09YWaZb5UOsCf6pO2kpSdiFrZwAAED5I2gYZkrYAAAAIVaWVrvYIMX5ujVCtRUJN0nZfQVmTjAkAANAUSNoGmdRYq6qLErJJ2gIAACCEVFfaNkVrBElq6VFpm0VfWwAAEEZI2gaZCLPJXW3LhgoAAAAIJdVJ25iopknaerZHyCpg7QwAAMIHSdsgVL0L7oHiclU5nAGOBgAAADg2wzBUWtnESVuv9ggkbQEAQPggaRuEqpO2TkM6UFwR4GgAAACAYyuvcsowXMfRAai05VtqAAAgnJC0DULNE2o2I2PxCQAAgFBQeqg1gtR0G5Glx1NpCwAAwhNJ2yDUPJ4NFQAAABBaSiuq3MdNVWkbZTGrWZyr4IGetgAAIJyQtA1CzT2+5pVN0hYAAAAhoMyz0jayaZK2ktTy0No5h/0gAABAGCFpG4SaJ3j25ioPYCQAAABA/Xi3R2i6pG312tnhNNgPAgAAhA2StkGInrYAAAAINZ5J2+gm6mkr1VTaStK+grImGxcAAMCfSNoGIXraAgAAINSUVdb0tG3KStsWiZ7fUmPtDAAAwgNJ2yCUFBOpKItrarJpjwAAAIAQEKj2CC0SPCttSdoCAIDwQNI2CJlMJneLhP1FLDwBAAAQ/LzbIzT9RmQS31IDAADhg6RtkKpukZBfWil7peMYVwMAAACBVRaojcg8k7ZU2gIAgDBB0jZIeS4+aZEAAACAYOdVaRvZdBuR0R4BAACEI5K2QcpzMzJaJAAAACDYlVUEZiOyWKtF8TZXkpiNyAAAQLggaRukqnvaSiw+AQAAEPwC1dNWqulru6/ALsMwmnRsAAAAfyBpG6SaJ9CbCwAAAKGjtNKzPULTJm1bJEZLkiqqnMovrWzSsQEAAPyBpG2Q8kzaZhfR0xYAAADBLVAbkUlSC49vqdHXFgAAhAOStkGK9ggAAAAIJaVePW2bbiMyqabSVpKyCsuadGwAAAB/IGkbpDwrbUnaAgAAINgFsqdtC6/WYnxLDQAAhD6StkEq1mpRvLV6F1wWngAAAAhugWyPUL0RmSRlFVBpCwAAQh9J2yCWfqhFQha74AIAACDIlR3aiCwywqTIiKb9mNHCI2lLT1sAABAOSNoGserFZ1mlQ4X2qmNcDQAAAAROdaVtdGTTVtlKh7VHoLUYAAAIAyRtg1iLhJoNFfbxNS8AAAAEseqetk29CZkkJcVEympxfbTJotIWAACEAZK2QaxVksfXvPJZfAIAACB4lVa4vhnW1P1sJclkMrn72lJpCwAAwgFJ2yDWMrGm0nYvlbYAAAAIYtU9baMDkLSVpOaHWiQU2atUXE5rMQAAENpI2gaxllTaAgAAIARUOpyqdLg2zg1Epa0kd6WtRIsEAAAQ+kjaBrFWVNoCAAAgBFT3s5Wk6AD0tJWk5h5J2/20SAAAACGOpG0Qo9IWAAAAoaDMI2kbExmgStsEj7UzlbYAACDEkbQNYgm2SMVZXZUKVNoCAAAgWFVvQiYFrj1CC49vqVFpCwAAQh1J2yBX3ZtrX4FdhmEEOBoAAACgNu/2CIFK2npW2lLwAAAAQhtJ2yDXMslVMVBR5VRuSUWAowEAAIAvPfnkkzKZTLr99tsDHcpxKav0aI/ARmQAAADHjaRtkGuVSF9bAACAcLR06VK99tpr6tWrV6BDOW7BsBFZszirIswmSVIW7REAAECII2kb5Fp69Oairy0AAEB4KC4u1lVXXaU33nhDycnJgQ7nuJUFQU/bCLNJ6fFWSVTaAgCA0BeYP4Oj3lomeVbakrQFAAAIB5MmTdLo0aM1fPhwPfbYY0e9try8XOXl5e7HhYWFkiSn0ymn0+nXOKvHMQzjqGOVlNckbW0Wc5PEVZcWCTbtK7DrQHGFyioqZbUEJoEcjOozjwh+zGN4YB7DA/MYHgIxj/Udi6RtkGvlUWm7j4oBAACAkPfhhx9qxYoVWrp0ab2unzp1qh5++OFa53NycmS3+3996HQ6VVBQIMMwZDbX/UW9/bn57uMqe4mys7P9HlddkmvqHbRh2161TrQGJI5gVJ95RPBjHsMD8xgemMfwEIh5LCoqqtd1JG2DnGel7V6StgAAACFt165duu222zR37lzZbLZjP0HSlClTdOedd7ofFxYWqk2bNkpLS1NCQoK/QnVzOp0ymUxKS0s74ocZi7XEfdw8NVnp6el+j6su7dJzpU35kqSKiBilp6cGJI5gVJ95RPBjHsMD8xgemMfwEIh5rO8akKRtkPOqtKU9AgAAQEhbvny5srOz1bdvX/c5h8OhBQsW6MUXX1R5ebkiIry/0m+1WmW11q4YNZvNTfbhwmQyHXW8ssqar/nF2iwB+/DaOjnGfZxVVM6H6MMcax4RGpjH8MA8hgfmMTw09TzWdxyStkEuOipCSTGRyi+tpD0CAABAiDv77LO1du1ar3PXXHONunXrpr///e+1ErahorSypqdtdGTgPmK0SvT4llo+a2cAABC6SNqGgJaJ0covrVRWoV0Op6EIsynQIQEAAKAR4uPj1bNnT69zsbGxSk1NrXU+lJRVONzHMVGBSzy3TKr5ltpevqUGAABCGPXbIaC6YsDhNJRTVH6MqwEAAICmFSxJ21Ye+0HwLTUAABDKqLQNAd6bkZWpRWL9GhYDAACgfsrKynTw4EG1bt3a6/z69evVo0cPv449b948v96/KZRW1iRtowOYtG0Wa1VkhEmVDoNKWwAAENKotA0BrTy+5rUnj8UnAACAL82cOVOdO3fW6NGj1atXL/3yyy/un40fPz6AkYUO70rbwNWFmM0md4EDSVsAABDKSNqGgAyPXXD3sPgEAADwqccee0zLly/XqlWrNH36dP31r3/V+++/L0kyDCPA0YWG0oqajcgC2R5BklolugoeCu1VKi6vOsbVAAAAwYn2CCEgI7mm0nZ3XmkAIwEAAAg/lZWVat68uSSpX79+WrBggS666CJt3rxZJhMbwNZHdaWtySRZLYGtC/H8ltq+/DJ1bh4fwGgAAAAah0rbENDGo9J2N+0RAAAAfCo9PV1r1qxxP05JSdHcuXP122+/eZ3HkZUeStrGREYEPNHdyms/CDYjAwAAoYmkbQhoFhflrlggaQsAAOBb77zzjtLT073ORUVF6YMPPtD8+fMDFFVoqU7aRgewn221lonelbYAAAChKPCrKhyTyWRSRnK0tuSUaHdeqQzDCHgFAwAAQLjIyMg44s8GDx7chJGErrLKQ5W2Ae5nKx1WaUvSFgAAhCgqbUNE9WZk9kqncksqAhwNAAAAUKN6I7LgSNrWVNrSHgEAAIQqKm1DhPdmZGVqFmcNYDQAAADhp3379o36NtPtt9+uW2+91Q8RhQan05C90ilJig6CpK1Xe4QCKm0BAEBoImkbIjK8NiMr1SltkgIXDAAAQBiaMWNGo57Xrl07n8YRauxVDvdxdGTgk7YJNotioyJUUuHQ3nwqbQEAQGhqdNK2srJSWVlZKi0tVVpamlJSUnwZFw5zeKUtAAAAfGvo0KGBDiEkVVfZSsGRtDWZTGqVFK1N2cXam1/GfhAAACAkNainbVFRkV555RUNHTpUCQkJateunbp37660tDRlZmbq+uuv19KlS/0V6wnNO2lbGsBIAAAAgBrVm5BJki0IkraS1PJQX9vyKqfySisDHA0AAEDD1Ttp++yzz6pdu3aaPn26hg8frlmzZmnVqlX6448/tHjxYj344IOqqqrSOeeco1GjRmnTpk0NDmbBggUaM2aMWrVqJZPJpFmzZh3zOfPmzVPfvn1ltVrVqVOnRn+tLdh5tkfYdZBKWwAAAH/ZsWOH5syZo6ysrDp/vnfv3iaOKLiVVQRf0rZVos19vDeftTMAAAg99U7aLl26VAsWLNCvv/6q+++/XyNHjtTJJ5+sTp06acCAAbr22ms1ffp0ZWVlaezYsVq4cGGDgykpKVHv3r310ksv1ev6bdu2afTo0TrzzDO1atUq3X777bruuuv07bffNnjsYNcsLkq2SNd0UWkLAADgHx988IE6deqkUaNGqUOHDnrnnXckSTt37tSTTz6p0047TW3btg1wlMHF7lFpGx3VoC/y+U2rpJpvqZG0BQAAoajePW0/+OADSZLD4dCXX36ps88+W/Hx8bWus1qtuvHGGxsVzLnnnqtzzz233te/+uqrat++vZ555hlJUvfu3bVo0SI999xzGjlyZKNiCFYmk0kZyTHanF2s3Xn05gIAAPCHRx99VJMnT9Zf//pX3Xfffbrpppv0xx9/6Mknn1THjh119tln69577w10mEHFM2lrswRHpW1LKm0BAECIa/BGZBEREbriiiu0fv36OpO2TWnx4sUaPny417mRI0fq9ttvP+JzysvLVV5e7n5cWFgoSXI6nXI6nUd6ms84nU4ZhtGosVonRWtzdrHKq5zKLrQrLd7qhwhRH8czjwgezGN4YB7DA/MYHgIxj74ea8uWLbrtttuUmZmpl156SW3bttVPP/2kNWvWqHv37j4dK1x4bUQWFRxJW89K230F9gBGAgAA0DgNTtpKUv/+/bVt2zZ16NDB1/E0SFZWlpo3b+51rnnz5iosLFRZWZmio6NrPWfq1Kl6+OGHa53PycmR3e7/BZ3T6VRBQYEMw5DZ3LCvj6XWFAxo7da96tky1sfRob6OZx4RPJjH8MA8hgfmMTwEYh6Liop8er/Kykr3GjIjI0M2m01PP/00CdujCMaNyLzaI5C0BQAAIahRSdvJkyfrvvvu08yZM9WmTRtfx+RXU6ZM0Z133ul+XFhYqDZt2igtLU0JCQl+H9/pdMpkMiktLa3BH2Y6tyqW1uRIkkpNNqWnp/sjRNTD8cwjggfzGB6Yx/DAPIaHQMyjzWY79kUN9P7772vUqFHq1q2bIiIilJyc7PMxwkkwJm1pjwAAAEJdo5K2l112mSSpR48euuCCCzRs2DD16dNHJ598sqKionwa4NG0aNFC+/fv9zq3f/9+JSQk1FllK7l67lqttdsKmM3mJvtwYTKZGjVem5QY9/GefDsfagOssfOI4MI8hgfmMTwwj+GhqefR1+MMGTJEDz74oO666y4lJyfLbrfr+eef16BBg9SzZ0916dJFFkujltBhy6unbWRw/PfXFhmh1Ngo5ZZUaB9JWwAAEIIateLctm2bVq9erVWrVmn16tWaOnWqtm/fLovFoq5du2rNmjW+jrNOAwcO1Ndff+11bu7cuRo4cGCTjN/UMpJrkra78koDGAkAAEB4mj9/viRp06ZNWr58uVasWKEVK1bo7bffVn5+vqKiotSlS5cmW++GAs+kbXSQVNpKUsskm3JLKrS/qFxVDqcsEcGRUAYAAKiPRiVtMzMzlZmZqQsuuMB9rqioSKtWrTquBWxxcbE2b97sfrxt2zatWrVKKSkpatu2raZMmaI9e/bo7bffliTdeOONevHFF3XPPffo2muv1Q8//KCPPvpIX331VaNjCGaZHpW2O3NJ2gIAAPhL586d1blzZ11++eXuc1u3btXy5cu1cuXKAEYWfII2aZsYrXV7CuVwGsouKvfqcwsAABDsfPbdrvj4eA0ZMkRDhgxp9D2WLVumM8880/24uvfshAkTNGPGDO3bt087d+50/7x9+/b66quvdMcdd+j5559XRkaG3nzzTY0cObLxLySIJcVEKt5mUZG9SttzSwIdDgAAwAmlQ4cO6tChg8aNGxfoUIJKWYXTfRwsPW0lqbVHknZfQRlJWwAAEFLqnbTduXOn2rZtW+8b79mzR61bt25QMMOGDZNhGEf8+YwZM+p8zolS7WAymdQuNVZr9xRob36ZKqqcirLwNS8AAABfaN++vUwmU4Ofd/vtt+vWW2/1Q0ShwV4VfBuRSYdvRmZXv8wABgMAANBA9U7a9u/fX2PHjtV1112n/v3713lNQUGBPvroIz3//PO64YYbTujFq7+0TY3R2j0FchrS7rxSdUiLC3RIAAAAYaGuAoH6aNeunU/jCDVlFcG3EZkktfSorN3LZmQAACDE1Dtpu2HDBj3++OMaMWKEbDab+vXrp1atWslmsykvL08bNmzQ+vXr1bdvX/3jH//Qeeed58+4T1jtUmv62u44SNIWAADAV4YOHRroEEKSV0/bqOCptM1Irkna7iFpCwAAQky9/xSempqqZ599Vvv27dOLL76ozp0768CBA9q0aZMk6aqrrtLy5cu1ePFiErZ+lJkS6z7ecYC+tgAAAAgsz6StzRKcSdvdeSRtAQBAaGnwRmTR0dG65JJLdMkll/gjHhxD5mGVtgAAADh+ZWVlOnjwYK09GdavX68ePXoEKKrQUBaklbZpcVZZLWaVVzm1O491MwAACC3H1XTqjjvu0PTp07V8+XKVl5f7KiYcRWaqR6VtLotPAACA4zVz5kx17txZo0ePVq9evfTLL7+4fzZ+/PgARhYa7JVO93EwbURmMpnU+lC17e68sqNueAwAABBsGlxp6+nMM8/UmjVr9N///lfr16+XyWRSjx491KtXL/Xq1UtjxozxVZw4JD3eKlukWfZKp3bk0h4BAADgeD322GNavny5mjdvruXLl2vChAm67777dOWVV5LoqwfPSttg2ohMklonRWtrTolKKxzKK61USmxUoEMCAACol+NK2l5wwQW64IIL3I/tdrvWrVunNWvW6Pvvvydp6wdms0ltU2L0x/5i7TpYJofTUITZFOiwAAAAQlZlZaWaN28uSerXr58WLFigiy66SJs3b5bJxDrrWMoPJW3NJikqIriSthnJNa3FdueVkrQFAAAhwyerqg0bNmjq1KmaPn26SktLddFFF2natGm+uDXqUN0iocLhVFahPcDRAAAAhLb09HStWbPG/TglJUVz587Vb7/95nUedauutLVFRgRdkpvNyAAAQKjySdL2ggsuUExMjEpKSvTWW2/p7LPPVseOHX1xa9QhM8VjM7IDtEgAAAA4Hu+8847S09Pdjx0Oh77++mu99tprmj9/fgAjCw3VSdvoIOpnW807act+EAAAIHQcV3uEai1atNBtt93mdc7hcBzhahyvzGYem5EdLNWgAMYCAAAQ6jIyMrweR0RE6IorrtD69es1ePDgAEUVOqo3IgumTciqebdHoNIWAACEDp9U2p599tmaPn2617mIiOBbtIULz0rb7WxGBgAA4HP9+/fXtm3bAh1GSLBXVLdHCK5+tpLUhvYIAAAgRPlkZbVs2TI99NBDat++vS699FI9/vjj+vLLL31xa9ShXWpNpe3OXL7mBQAA4GuTJ0/Wfffdp127dgU6lKBnrzrUHiEq+Io2msVZFWVxfeShPQIAAAglPmmP8NVXX0mSioqKtG7dOq1bt07ff/+9xowZ44vb4zCtkmyymE2qchraRk9bAAAAn7vsssskST169NAFF1ygYcOGqU+fPjr55JMVFRUV4OiCR6XDqUqHIUmyWYIvaWs2m5SRFK2tB0q0O69MhmEE3WZpAAAAdWlw0nbHjh3auHGjevXqpRYtWnj9LD4+XpmZmRo4cKDPAkRtlgiz2qTEaNuBEu3ILZXTachsZvEJAADgK9u2bdPq1au1atUqrV69WlOnTtX27dtlsVjUtWtXrVmzJtAhBgV7Zc0+FsFYaStJrZNdSdvSCofySiuVEkvSHQAABL8GJW0/+OADXX311XI4HLLZbHrttdc0fvx47dy5U++//74+/fRTrVixQlVVVf6KF4d0aBarbQdKVFbpUFahXa2Soo/9JAAAANRLZmamMjMzdcEFF7jPFRUVadWqVSRsPVRvQiZJ1iCstJUO34yslKQtAAAICQ3qafvoo49q8uTJWrt2rUaMGKGbbrpJ999/vzp27KgZM2aof//++vjjj/0VKzx0SKvpa7slpziAkQAAAISfl19+WZWVlV7n4uPjNWTIEE2aNClAUQWfUKi0zWAzMgAAEIIaVGm7ZcsW3XbbbcrMzNRLL72ktm3b6qefftKaNWvUvXt3f8WIOnRIi3Mfb80p0ZDOaQGMBgAAILxMnjxZLVu21BlnnKG0NO911uLFi2kHdohX0jbSJ3sc+5x30pbNyAAAQGhoUNK2srJS0dGuRU9GRoZsNpuefvppErYB0NEraUulLQAAgC8ZhqFx48bJMAylp6fr5JNPVq9evdSuXTs9+OCDys3NDXSIQaHMI2lriwzWSlvP9ghU2gIAgNDQ4I3I3n//fY0aNUrdunVTRESEkpOT/REXjsGzPcLWAyUBjAQAACA8bd26VTk5OVqzZo1Wr16t5cuX66OPPtLpp58e6NCChmdP2+ggTdq2oT0CAAAIQQ1K2g4ZMkQPPvig7rrrLiUnJ8tut+v555/XoEGD1LNnT3Xp0kUWS4PzwGiE1NgoJdgsKrRXaWsOSVsAAABfs9ls6tevn/r16xfoUIKWZ6WtNUiTts3irIqymFVR5aQ9AgAACBkNyrDOnz9fkrRp0yYtX75cK1as0IoVK/T2228rPz9fUVFR6tKlCzvqNgGTyaQOaXFatStfe/LLVFpRpZgoEuYAAAC+8ttvvyk5OVmRkZGBDiVolVV49rQNzqSt2WxSRlK0th4o0e68MhmGIZPJFOiwAAAAjqpRWb7OnTurc+fOuvzyy93ntm3bpmXLlmnlypU+Cw5H1yEtVqt25UuSth0oUY9WiYENCAAAIIycddZZslgs6tKli7unbfW/jIyMRt3zlVde0SuvvKLt27dLknr06KEHHnhA5557rg8jbzrlVZ49bYNzIzJJap3sStqWVjiUV1qplNioQIcEAABwVD4rzWzfvr3at2+vcePG+eqWOAbvzchI2gIAAPhKt27d9MknnygrK0vr1q3TmjVr9Nlnn+mxxx5TWVmZHA7HsW9Sh4yMDD355JPq3LmzDMPQv//9b1144YVauXKlevTo4eNX4X+hUGkrHb4ZWSlJWwAAEPT4Pn0I6+i5GRl9bQEAAHxmw4YNkqTu3bvrzDPPdH+l3jAMbdmypdH3HTNmjNfjxx9/XK+88oqWLFkSkklbu0dP2+ioYE7aem9G1isjKXDBAAAA1ANJ2xDWwbPS9kBxACMBAAAIb1arVatXr1b37t3VqVMnn9zT4XDo448/VklJiQYOHHjE68rLy1VeXu5+XFhYKElyOp1yOp0+ieVonE6nDMOoc6zSiir3cVSEqUniaYzWSTb38a6DJUEbpz8dbR4ROpjH8MA8hgfmMTwEYh7rOxZJ2xCWmRojs0lyGlTaAgAA+MKdd95Z53mHw6Enn3xSqampkqRnn3220WOsXbtWAwcOlN1uV1xcnD777DOddNJJR7x+6tSpevjhh2udz8nJkd1ub3Qc9eV0OlVQUCDDMGQ2e/etzc0vch+XlxQpOzs4+9rGGjXv06a9B5WdHXeUq8PT0eYRoYN5DA/MY3hgHsNDIOaxqKjo2BeJpG1Is1oilJEco50HS7U1p5idcAEAAI7TtGnT1Lt3byUlJXmdNwxDv/32m2JjY497vdW1a1etWrVKBQUFmjlzpiZMmKD58+cfMXE7ZcoUr2RyYWGh2rRpo7S0NCUkJBxXLPXhdDplMpmUlpZW68NMRNRB93GLtFSlp6f4PZ7GONmWIGmjJCnXLqWnpwc2oAA42jwidDCP4YF5DA/MY3gIxDzabLZjXySStiGvY1qsdh4sVUmFQ/sLy9UisX4TDwAAgNqeeOIJvf7663rmmWd01llnuc9HRkZqxowZR62Ira+oqCh3i4V+/fpp6dKlev755/Xaa6/Veb3VapXVaq113mw2N9mHC5PJVOd49qqar/fFWC1B+6E1PSFaURazKqqc2p1XFrRx+tuR5hGhhXkMD8xjeGAew0NTz2N9x+G3KsR19Ohruym7fuXVAAAAqNu9996r//znP7rpppt09913q7Ky0u9jOp1Or561ocRzIzJbZPBuRGY2m5SR5NqMbHdemQzDCHBEAAAAR0fSNsR1aRHvPt6YRdIWAADgePXv31/Lly9XTk6OTj31VK1bt85nLaimTJmiBQsWaPv27Vq7dq2mTJmiefPm6aqrrvLJ/ZtaWWVNpW10ECdtJaltaowkqazSoZyi0EySAwCAEwftEUJcl+Y1SdtN+4sDGAkAAED4iIuL07///W99+OGHGj58uBwOx7GfVA/Z2dm6+uqrtW/fPiUmJqpXr1769ttvNWLECJ/cv6mFSqWtJGWmxLiPdxwsVXoCbcUAAEDwImkb4jqn17RH+IP2CAAAAD51+eWX64wzztDy5cuVmZl53Pd76623fBBV8PBO2gb3l/japsa6j3fklqp/u+DcNA0AAEAiaRvyYq0WZSRHa3demTbtL5ZhGD77+h4AAACkjIwMZWRkBDqMoFRWEZqVtjtzSwIYCQAAwLEF95/DUS/VLRKKy6u0t8Ae4GgAAABworBXuZK2FrNJkRHB/dEiM9W7PQIAAEAwC+6VFeqlc3OPFgn7aZEAAACAplFdaRvsm5BJUhvPnra5JG0BAEBwI2kbBrp6bEb2RxZJWwAAADQNe6VTkmQNgaStLTJCLQ5tPraTSlsAABDkSNqGgS6eSdv9xQGMBAAAACeS6o3IoqNC42NF20MtEg6WVKjIXhngaAAAAI4sNFZXOKqOaXGq3ntsUzaVtgAAAGgaZZWh0x5B8t6MjBYJAAAgmJG0DQPRURHuBeim/cVyOo0ARwQAAIBwZxiGu9LWFipJW4/NyGiRAAAAghlJ2zDR+VCLhLJKh3bnlQU4GgAAAIS7CodT1bUCoZK0bZsa6z4maQsAAIIZSdsw0aV5nPv4j/20SAAAAIB/VW9CJoVO0pb2CAAAIFSQtA0TnpuR/Z5VGMBIAAAAcCKobo0gSdGRofGxom2KZ3uEkgBGAgAAcHShsbrCMZ3UMsF9/Ns+Km0BAADgX55J21CptE2KiVS8zSKJSlsAABDcSNqGifbNYmW1uKZzwz4qbQEAAOBfZV6VtqGRtDWZTO7NyPbml6miynmMZwAAAAQGSdumVpKjqF0LpYPbfHpbS4RZ3Vq4WiRszy1RSXmVT+8PAAAAeCqrCL1KW0nKTHFtRuY0pD35bOALAACCE0nbprTuU5mf6aKUr66TNszy+e1PauVqkWAY0u9ZtEgAAACA/4TiRmSS1K5ZTV/b7QfoawsAAIITSdumlN7dfWjKWuvz23v2taVFAgAAAPzJHoLtESSpfbM49/FWkrYAACBIkbRtSqmdZVhsruOs1T6/fXWlrSRt2EvSFgAAAP7jvRFZ6HysaN8s1n287UBxACMBAAA4stBZXYWDCIuU3kOSZDq4VbL7NrHatUWCTCbXMZW2AAAA8CevjciiQqfStoNX0pZKWwAAEJxI2ja1lifXHO9f59Nbx1ktykxx9ej6fV+hqhzshgsAAAD/8Eza2iyhk7RNjo1SUkykJGlbDklbAAAQnEjaNjGjRa+aB/vW+Pz+1S0Syquc2p7LIhQAAAD+4bURWQhV2kpSu1RXte3eArtXmwcAAIBgQdK2qXkmbbP8kLT12IxsPX1tAQAA4CehuhGZ5N0igUIHAAAQjEjaNrX0k2SYDi1q/VhpK9HXFgAAAP4TqhuRSYdtRkaLBAAAEIQsgQ7ghBMZraqkDorM2yTl/CZVlUsWq89uf1LLRPfx+j0kbQEAAOAfZRWhW2nbPq0mabs1QJuRVTortXjvYi3fv1wbcjdoe+F2lVSUqMxRpoSoBKVGp6ptfFudknaK+jXvpx7NeshsCq3kOAAAaDyStgFQ1ay7K2nrrJKyf5NaneKzezdPsKpZnFUHisu1dk+BDMOQyWTy2f0BAAAASbJXeVbahljS1rPStomTtruKdunt9W/rm+3fKL88v85rDtoP6qD9oDblbdL3O7+XJLWKbaXRHUbr4i4Xq3Vc6yaMGAAABAJ/qg2AymYn1TzwcV9bk8mkXhmuatuCskrtyC316f0BAAAASSqr8NiILMSSttUbkUlNl7Q9UHZAjy5+VBd8doE+3PhhrYRtkjVJ7RLaqVtKN7WKbaUoc5TXz/eW7NUba9/Q6E9H6/8t+n/aVrDt+IMyDNc/AAAQdKi0DYCqZt1rHvihr22vjET98Hu2JGn17ny186gkAAAAAHwhlHvaxlotapFgU1ahvUmStt9u/1aPLnlUBeUF7nO2CJvObHOmzml3jnql9VJ6TLrXc5yGU1vzt2pF9gr9sOsHLd67WE7DKYfh0BdbvtDXW7/WFd2v0E29b1J8VPyxg3A6FJm1Qvp9rbTjJyl/h1SU5WrXFhUr2RKltG5Sy15S+z9J7YZIEZG+fisAAEA9kbQNgEqvpO1qn9+/d0aS+3jN7gJdeApfnwIAAIBveSZtQ62nreRqkZBVaNfBkgrll1YoKSbq2E9qIHuVXY8sfkRfbv3SfS7GEqOre1yt8SeNV0JUwhGfazaZ1Sm5kzold9KlXS/VgbID+njjx3r3t3dVWFGoKqNK72x4R19v/VoPDHxAZ7U96whBFEgr35Xp19eVmre97msqil3/CvdIW76XFj0nRSdL3S+QTrtRan5S3c8DAAB+E1p/Eg8ThjVRRlKm60HWWslR5dP7V7dHkKQ1u/N9em8AAABAkso8k7ZRIZi0TfNvi4Tcslz9dc5fvRK2IzJH6Os/f61Jp0w6asK2Ls2im+mmU27SnEvm6ObeN8sa4drMONeeq9t+vE0P/PSASio9XofTIS2bLj3fW/r2PpkOT9jaEqW07lKrvq4K2+hk75+X5Ukr/i29MlB658/SnhUNihcAABwfKm0DpVUf11eSqsqknN+lFj19duvUOKtaJ0VrT36Z1u0pVJXDKUsE+XkAAAD4jld7BEsIJm0P62vbp23yUa5umF1Fu3T9nOu1p3iPJCnaEq0HBj6g0e1HH/cmwbGRsbrplJt0QacLNPWXqZq/e74k6bPNn2lVzipNO3OaOlQZ0ifXSXu9E63lGYMV2ecymTsMk5IzvW9sGK5K212/Sr/Plv741lV9K7mqb7d8L/W+Qjr7QSmh5XG9BgAAcGxk8gLEaNWn5sFe3//VuncbV7VtWaVDm3OKfX5/AAAAnNjKKl0bkUVZzDKbjy8RGQjtPfZ92OLD9fLe4r3667d/dSds06PT9fa5b+v8Ducfd8LWU+u41nrhrBf0yKBHFGOJkSRtK9imK74Yp+/fHuH9GePkcXLetER55/9L6jO+dsJWkkwmKTFD6vln6ZJ/SXf9Lo16UkpqW3PN6g+kl0+TVn3ABmYAAPgZSdtAadW35njvSp/fvpdnX9tdBUe+EAAAAGiE6kpbmyU0P1J0So9zH2/O9k3Sdn/Jfl035zrtK9knSeqY2FHvj35f3VK6+eT+hzOZTLqo80X6eMzH6pzcWZJU6qzQHckxei8hTkrtJE38Srr4TSmta8Nubo2XTr9JumW5K3lrS3KdtxdIs26UPrxKKj3o2xcEAADcQnOFFQ5a9pZ06C/tfugP5dnXdjV9bQEAAOBj1UnbUOxnK0ltUmIUdSjh7IukbWllqSZ9P0m7inZJktoltNObI99U89jmx33vY2kb30bvRvfUucWunraGyaQnU1P07IBxcmYOOr6bW6JcydtbV0onX1pzfuNX0utD6XULAICfkLQNFGu81KyL63j/eqmq3Ke3P7l1oqq/fbVmN5W2AAAA8K3qjchskaGZtI0wm9ThUIuEHbmlqqhyNvpeTsOp/7fo/2lj3kZJrtYFb5zzhppFN/NJrEdlGNLc+xXz0/N6KidXN+TVrP2n//6epiycokpH5fGPE5MiXfyGdNl7UnSK61z+TulfI6U1Hx///QEAgBeStoFU3dfWWSllrfPpreNtke5F6O9ZhV4bRQAAAADHy11pG6JJW6mmRUKV09CO3JJG3+flVS/ru53fSZLiIuP08tkvq0VsC5/EeEyLX5J+fkGS63t8kwfdr/tPv19mk+uj3tfbvtbfFvzNN4lbSep+vnTjQimjv+uxo0L69Dpp4bP0uQUAwIdI2gZSa8++tr7/WlHfQzvgVjoMrd1DtS0AAAB8wzAM2Q9tRBaqlbaS1Dk93n3c2BYJP+/5Wa+teU2SZDaZ9Y8//UMdkjr4JL5j2vC5NOd/ax6PeV4acL0u7Xqpnhv2nKwRVknS9zu/1z0L71GVs8o34yZmSBO/lvpNrDn3/cPS7Dskh4/GAADgBEfSNpA8NyPzQy+ofpnJ7uPlO/J8fn8AAACcmMo9WgnYIkP3I8XxbkaWW5ar+xbd5358e9/bNSRjiE9iO6Z9q6VPb5B0qLp16L1eSdSz2p6l/zvr/9yJ2x92/aDHVj+mSqePKm4tUdL506SzH6g5t3y69NHVPm/9BgDAiSh0V1jhoMXJktniOvZDpe2p7WqStsu2k7QFAACAb5RV1LTeCof2CJK0qYFJW6fh1P/+9L/KtedKkga3HqwJPSb4NL4jshdKH02Qquyux72vlIbdW+uyQa0GeSVuf8r+SVMWTpHD6aPWaSaTNOQu6c9vSOZI17mNX0n/GU/iFgCA40TSNpAibVL6Sa7jnI1SeZFPb9+hWZwSo12LpxU782TQYwoAAAA+UOaxX0Iot0do1yxGEWbX7r0NrbT9ZNMnWrRnkSQp1ZaqxwY/5u4j61eGIX0xWcrb5nrcqq+rLUL1LsSHOTxxO3fnXD3+y+O+/WzQ61LpLzMlS7Tr8aZvpQ+vkirtvhsDAIATDEnbQGvd79CBIe1d6dNbm80md4uEgyUV2p5b6tP7AwAA4MTkucltKFfaWi0RykyJkSRtySmWw1m/ROb+kv16dtmz7sePnfGYmkU380uMtSyfIW2Y5Tq2JkrjprtaFRzFoFaD9NzQ5xRhcs3Vx398rJdWveTbuDoMcyVuI13vpzbPlT68ksQtAACNRNI20Kp3XZWkXb/6/PaefW2XbT/o8/sDAADgxONZaWsN4aStVNMiobzKqT15Zce83jAMPfbLYyqudFXmXtjxQp3R+gy/xuiWv8t747GxL0nJ7er11MGtB+uek+9xP35tzWt677f3fBtfuzOkv3wiRca6Hm/5Xvrkr2xOBgBAI5C0DbQ2A2qOdy/1+e09k7YrdtLXFgAAAMfPXlmzEVkoV9pKh21GlnPsdmVzd8zVvF3zJLnaIvyt/9/8FNlhDEP68jap4lAbhz7jpe5jGnSLs1qepXtOrUncPvnrk5q7Y64vo5QyB3knbn+fLc2+zRU/AACoN5K2gZbaSYo+lFjd9avPFzO9M5JkOdSni83IAAAA4Ate7RGiQvsjhVfS9hh9bcuqyvTPZf90P77vtPuUaE30W2xeVr3vqlyVpPhW0sjHG3Wbq7pfpRt63eB+fN/C+7T+wHpfRFgjc6B0+bs1m5OtfFeaez+JWwAAGiC0V1jhwGSSMg5V25YdlHK3+PT20VER6tEqQZJrR9yC0kqf3h8AAAAnnrIKj43ILKFdads5Pd59vGn/0ZO2/1r3L2WVZEmSzmh9hkZkjvBrbG6lB6U5/6/m8Zhpkq3xyeJbTrlFYzq4qnTtDrtu+eEW9+vymY5nSRe/IenQBmk/vyD9/H++HQMAgDBG0jYYtPHoa7vb931t+3r2td1BX1sAAIBAmTp1qvr376/4+Hilp6dr7Nix2rhxY6DDajB7lWelbWgnbTumx7qPNx2l0nZP8R5NXzddkmQxWXRP/3tkMpn8Hp8k6cfHpbJD35rreYnUZeRx3c5kMumhQQ+pb3pfSdKBsgO65ftbVFJZcryReutxkSvBXG3uA9L6Wb4dAwCAMEXSNhhkePS19cNmZKe1T3EfL9ma6/P7AwAAoH7mz5+vSZMmacmSJZo7d64qKyt1zjnnqKTEx8kyP/OstA31jchioixqmxIjSfpjf5Gczrq/wv/ssmdV7iiX5Gox0D6xfdMEmLVWWvYv13FkrHTOYz65bVRElKadOU1t4ttIkjbmbdQ9C+6Rw+k4xjMbqN9E6UyPKuHP/kfavcy3YwAAEIZI2gaD1v0k06Gp8MNmZKe1T3UfL9lKpS0AAECgfPPNN5o4caJ69Oih3r17a8aMGdq5c6eWL18e6NAaxF4VPhuRSVLXFq4WCaUVDu3KK63187U5azVnxxxJUootRf/T+3+aJjDDkP77d8k49H4P/ZuU0NJnt0+2JevFs19UfJTr9S/YvUDPLH/GZ/d3+9PfpN5Xuo6r7NIHl0t5O3w/DgAAYSTokrYvvfSS2rVrJ5vNptNOO02//nrkytMZM2bIZDJ5/bPZbE0YrY9Y46T0Hq7j7A1S+bF3rW2I5NgodTu0EF2/t0AFZfS1BQAACAYFBQWSpJSUlGNcGVzsnj1tI4PuI0WDVa+VJen3LO+1uGEYmrZimvvxzb1vdic5/W7jf6UdP7mOUzpIp9/s8yE6JHbQs8OelcVkkSS9s+EdfbnlS98OYjJJY56X2g1xPS7Jkd6/VCrL9+04AACEEUugA/D0n//8R3feeadeffVVnXbaaZo2bZpGjhypjRs3Kj09vc7nJCQkePUBa7K+Ur7Wpr+0f63rr+h7lksdhvn09gM7pur3rCI5DenXbQc14qTmPr0/AAAAGsbpdOr222/X4MGD1bNnzyNeV15ervLycvfjwsJC9/OdTueRnubTOA3D8BqrtKLKfWyzmJskDn/q2jzOffzb3gKN6F7z2WPx3sX6NctVSNImvo3GdhrbNK/X6ZDp+4ert/GSc/gjkjlSauTYdc1jtQHNB+jeAffqsV9crRceXvywOiR2UPeU7o2NvjazRRr3b5n+dY5MuZulnN9lfDRBxpUfSRGRvhsnzB1tHhE6mMfwwDyGh0DMY33HCqqk7bPPPqvrr79e11xzjSTp1Vdf1VdffaV//etfuvfee+t8jslkUosWLZoyTP9oc1pNr6qdv/g+adshVdN/2i7J1deWpC0AAEBgTZo0SevWrdOiRYuOet3UqVP18MMP1zqfk5Mju93ur/DcnE6nCgoKZBiGzGZXVW1ufk01anlJkbKz/R6GXzWLrPkm2pqdB5SdnShJchpOPbO0pl3A+PbjlXcgr0lism2cpaSc3yVJFc1P0cHkU3U8b3Rd8+jpT4l/0rmtz9V/9/xX5Y5y3fb9bXpp4EtKjEps9Jh1iTjnFaV+dqnM9jyZts1T6ed3qeiM//XpGOHsWPOI0MA8hgfmMTwEYh6Liur3DfugSdpWVFRo+fLlmjJlivuc2WzW8OHDtXjx4iM+r7i4WJmZmXI6nerbt6+eeOIJ9ejR44jXB2OlgiQp4zR3rwpjx88yfBxL/3bJMplcbbEWbznAX4KOE39RCw/MY3hgHsMD8xgegrlSIdjccsstmj17thYsWKCMjIyjXjtlyhTdeeed7seFhYVq06aN0tLSlJCQ4O9Q5XQ6ZTKZlJaW5v4wY4484P55y/RUpacn+T0Of0pJdcpq+U3lVU5tz6t0f8vvh50/aFPhJklSt5RuGtdrnMymJvhAV1Uu04oX3Q8tIx9TevPjK7qoax4P90izR7R7zm6tPbBW++379c/f/qmXz35ZFrMPPzamp0uXvy/j7QtkclYqdt07iu44UOp9he/GCGP1mUcEP+YxPDCP4SEQ81jf1q5Bk7Q9cOCAHA6Hmh+2GGnevLl+//33Op/TtWtX/etf/1KvXr1UUFCgp59+WoMGDdL69euPuPgNxkoFSZJhU1psC0WUZMnY9Yuy9+3x+deEOjeL1h85ZfptX5E27dyrRFvQTH/I4S9q4YF5DA/MY3hgHsNDMFcqBAvDMDR58mR99tlnmjdvntq3b3/M51itVlmt1lrnzWZzk73PJpPJazzPjchirJaQ/+9tlNmszs3jtG5PobbnlqjCYchqMev1ta+7r7nllFtkiWii9fOqd6WCXa7jTsNl7jDEJ7c9fB4PZzPb9Nyw53TZ7MuUa8/VL1m/6IVVL+iuU+/yyfhu7QZJo5+RvrxVkmSefYeU3s21QTOO6VjziNDAPIYH5jE8NPU81neckM7aDRw4UAMHDnQ/HjRokLp3767XXntNjz76aJ3PCcZKhWqm9mdI62bKXFWmdMc+qeWpPh17SNdc/ZGzXYakrUVmjWxbd59gHBt/UQsPzGN4YB7DA/MYHoK5UiFYTJo0Se+//74+//xzxcfHKysrS5KUmJio6OjoAEdXf2WVNRuRRUdGBDAS3+nWIkHr9hTKaUib9hfroLFKvx38TZLUPaW7/pTxp6YJpKpCWjSt5vFZ9zfNuIc0j22uZ4Y9o+u+vU5VRpVmrJ+hHqk9NKr9KN8O1G+CtG+1tOwtyVEuffgX6X/mS3F8RgEAQAqipG2zZs0UERGh/fv3e53fv39/vXvWRkZGqk+fPtq8efMRrwnGSgW3zEHSupmueHYtkdoO8Om4Azs001uLtkuSlmw9qHNPbuXT+59o+ItaeGAewwPzGB6Yx/AQrJUKweKVV16RJA0bNszr/PTp0zVx4sSmD6iRyirCMWkb7z7esK9As/a/6n58Y+8bm27D49UfSIW7XcddRkmtTmmacT30a95P9wy4R0/88oQk6YGfH1D7xPbqmtLVtwONelLK3iDtXCwV7ZU+ulq6+gvJEuXbcQAACEFBs8qNiopSv3799P3337vPOZ1Off/9917VtEfjcDi0du1atWzZ0l9h+lfm4JrjHT/7/PandUiRxexabC7YdOAYVwMAAMDXDMOo818oJWwl70pbW1R4JG27eiRtF+xapHW561znk7vqzDZnNk0Qjipp0bM1j//0t6YZtw6Xd71cF3a8UJJUVlWmu+bfpeKKYt8OYomSxv1bij9UTLJzsfRN3RtQAwBwogmapK0k3XnnnXrjjTf073//W7/99ptuuukmlZSU6JprrpEkXX311V4blT3yyCOaM2eOtm7dqhUrVugvf/mLduzYoeuuuy5QL+H4pHWVolNcxzsXSz7eWCPeFqm+bZMlSdsOlGhnbqlP7w8AAIATgz1M2yNUW1Hwmfv4hl43NF2V7bqZUt5213GHM6UM37ZLawiTyaT7B96v7indJUk7CnfogZ8fkGEYvh0ovrl0+btSxKFvQy57S1o+w7djAAAQgoIqaXvZZZfp6aef1gMPPKBTTjlFq1at0jfffOPenGznzp3at2+f+/q8vDxdf/316t69u8477zwVFhbq559/1kknnRSol3B8TCZXiwRJsudLOb/5fIihXdPcx/M35fj8/gAAAAh/1ZW2FrNJkRFB9ZGi0dLirUqNjZLZtkfFZtdGyJkJmTq77dlNE4BhePeyDWCVbTVrhFXPDntW8VGuKuS5O+bqvd/e8/1ArftJ5z9X8/jrv0l7Vvh+HAAAQkjQrbBuueUW7dixQ+Xl5frll1902mmnuX82b948zZgxw/34ueeec1+blZWlr776Sn369AlA1D5UnbSV/NIi4U+da5K2C/4gaQsAAICGq+5pGy5VttW6tYxXVMoC9+OrT7paEeYmeo2bv68p2mhzmtRu8NGvbyIZ8Rl6fPDj7sfPLHtGq3NW+36gPldJA25wHTsqpI8mSKUHfT8OAAAhIuiStie8th79e3f85PPb92iVoNRYV2P/nzcfUEWVb1swAAAAIPzZK11ryHDpZ1utffMKWRLWSpJiLYm6oOMFTTf44hdqjgfe0nTj1sOZbc/UNT1cLeuqjCrdPf9u5dnzfD/QOY9LGYc2Yy7YKX16g89bxgEAECpI2gabFr0k66F+WtsW+nyRYjabNKRzM0lSSYVDK3b6YbEFAACAsFbdHiHcKm0PRHwvk8m1/u4aM0o2i61pBs5aK22d5zpObi91G9004zbA5L6T1Te9ryQpqyRLUxZOkdPwcULVEiWNmyHFpLoeb54rLXzGt2MAABAiSNoGmwiLlHnoq1ClB6TsDT4fwquvLS0SAAAA0EDh2B6hsKJQyw9+I0kynBaZCwcd4xk+tPilmuOBk6SmasnQAJHmSP1z6D+VYnNtnPzT3p/0xpo3fD9QYmvp4rckHdr87cfHpS0/+H4cAACCHEnbYNT+TzXH2xYc+bpGGuLR13beRpK2AAAAqD/DMNyVtuHUHmHmHzNld5RKkioL+umPfcd4gq8UZ0trZ7qObUnSKVc20cANlx6Trqf+9JRMhxKqL616SUv2LfH9QB3PlM78f4ceGNIn10kFu30/DgAAQYykbTDqMLTmeNt8n9++WZxVvTISJUm/7SvU7rxSn48BAACA8FTusSdCdGR4fJyoclbpvd/ecz0wTKo4eIb25JfpYEmF/wdf8W/JWek67jdRior1/5jH4fSWp2vSKZMkSYYM/X3B35Vdmu37gYbcJXU+x3Vcmit9PFGqaoL5AAAgSITHKivcpJ8kxR6qht3+k+So8vkQw7s3dx9/t2G/z+8PAACA8FTdGkEKn/YIP+760Z14bBnVV0aFay2+bk+Bfwd2VEnLZhx6YJJOvda/4/nI9b2u1+DWrpZuB+0H9bf5f1NldeLZV8xm6aLXpMS2rse7l0pz7/ftGAAABDGStsHIZKppkVBRJO1d4fMhRpxUk7Sd+xtJWwAAANRPdWsESYoOk/YIH/z+gft4ROs/u4/X7fVz0nbTt1Lhoa/9dxkpJWf6dzwfMZvMmnrGVDWPcX2mWJG9Qi+seMH3A8WkSJf+W4qIcj3+5VVp3Se+HwcAgCBE0jZYefa13er7FgndWsQrIzlakvTL1oMqKPPxX8YBAAAQljyTtrYwqLTdnLdZS7OWSpLaJbTTmK41rcrW7yn07+BL36w57n+9f8fysWRbsp4Z9owsJoskafr66fphpx82DGvdVxr1ZM3jL26Vcv7w/TgAAAQZkrbBqr1/+9qaTCZ3tW2V09C8jX7oQwUAAICwE27tET7c+KH7+LKul6lTWrxsh3r1+rXS9sBmacuhJGdyO6njWf4by096p/XWXafe5X78v4v+V7uKdvl+oFOvlXpd7jquKJY+Gi+VF/t+HAAAgghJ22CV0l5KOtS/adcvUkWJz4fwbJEwh762AAAAqAd7ZfgkbYsrivXlli8lSdGWaF3Q6QJZIszq3jJBkrQjt9R/30hb9q+a41P/6urhGoKu6n6VRmSOkCQVVRbprnl3qdxR7ttBTCbp/Odce39IUs7v0pe3SYbh23EAAAgiobkyOFF0ONP1n44K14ZkPjagXYoSoyMlSfM35qi8ynGMZwAAAOBEF049bb/Y8oVKq0olSed3OF8JUa5kbc9Wie5r1vtjM7KKUmnVu67jCKvU5y++H6OJmEwmPTLoEWUmuPrx/nbwNz3565PHeFYjRMVIl74jRcW7Hq+b6d1eAgCAMEPSNph1Gl5zvPk7n9/eEmHW2d3SJUnF5VVatOmAz8cAAABAePFsjxDKPW0Nw/BqjXB5t8vdxydn1CRtV+/2Q9J2/aeS/dB9e17s2nArhMVFxenZYc/KFmGTJM38Y6a+2PKF7wdq1kka+1LN42+mSLuW+n4cAACCAEnbAHBs2yZnWdmxL+wwVDK7Gvv7I2krSeed3NJ9PHvNPr+MAQAAgPBRFibtEZZmLdW2gm2SpH7N+6lLchf3z/q2TXIfr9yZ5/vBV7xTc9z/r76/fwB0Se6i/z39f92PH138qP7I88OGYSddKA28xXXsrJQ+niCVUHwCAAg/JG2bUPHChdp+0UUqvOZaFc+bd+wn2BKlNqe5jg9ukQ5u9XlMQ7o0U7zNlRiesz7Lq0cZAAAAcDh7mLRH+GzzZ+7jy7pe5vWzDs3i3GvklbvyZfiyd+qBTdKuJa7jtO5S636+u3eAXdjpQl3c+WJJkt1h113z7lJJpe/35tDwh6S2g1zHhXukmddKTj7HAADCC0nbJmSKsqp8o+uvzUWzv6rfkzqdXXO8+Xufx2S1RGhUjxaSpJIKh+ZtzPb5GAAAAAgfnu0RQrXStqiiSHN3zJUkJVoTdXbbs71+bjabdEqbJElSTlG59hbYfTf4yndrjvuOd22yFUbuHXCvuqV0kyRtL9yuB39+0LdJb0mKiJTGTZfiDm2svG2+9OMTvh0DAIAAI2nbhGJO7SdL+qEesgsXypGff+wnefW19X3SVpLO793KffwlLRIAAABwFGWVTvdxqPa0/e+2/6rcUS5JOq/9eYqKiKp1TZ9DSVvJhy0SHFXS6g9cx2aL1Ouyo18fgmwWm54d+qziI10bhn27/Vu9//v7vh8ovoV0yXTJdOh3cOHT0sZvfD8OAAABQtK2CZkiIhR/7rmuB1VVKpwz59hPan6yFOtK9GrbAqmq3OdxDeqYquSYSEnSD79lq7SiyudjAAAAIDyUhUF7hFmbZ7mPL+p0UZ3X9Gmb7D5euTPfNwNvnisV73cddz1Xim3mm/sGmTYJbfToGY+6Hz+97Gmtzlnt+4HaDZZGPFzz+LMbpIPbfD8OAAABQNK2iSWcP9p9XFifFglmc02LhMoSacfPPo8pMsKscw9tSFZW6dDcDft9PgYAAADCgz3ENyLbnLdZaw+slSR1S+mm7qnd67yutz8qbT1bI/QZ75t7Bqmz256tiT0mSpKqnFW6e/7dyrP7YVO3gbdI3S9wHdsLpI/GS5X12PQZAIAgR9K2iVlPOknmNm0kSaVLl6pyfz0SpJ1H1Bz/4Z+v/Fzg0SLhkxV7/DIGAAAAQl+o97T1rLId22nsEa9LiY1Su9QYSdK6vYWqqHIe8dp6Kc6uWcvHt5Q6nn3068PArX1vVd/0vpKkrJIsTVk4RU7jON/Hw5lM0oUvSamdXI+z1kpf3+3bMQAACACStk3MZDIp6uxDCzTDUOHX/z32kzoNl8yu9gXa+LXk60b+kga0S1FGcrQkadGmHGX5crMFAAAAhA3v9gih9XGi0lmpL7d+KUmKNEdqdPvRR72+ukVCRZVTv+0rPL7B1/xHch5qQ9b7CinCcnz3CwGR5kj9c+g/lWJLkST9tPcnvb7mdd8PZEuQLn1HinQl2bXyXWnF274fBwCAJhRaq6wwEXX2We7jwi+/PPYTbIlSuzNcx/k7pewNPo/JbDbpkn4ZkiSnIX2yYrfPxwAAAEDo80zahtpGZAt2L9BB+0FJ0pltzlSSLemo1/dpW/Pz42qRYBjSyvc8bvyXxt8rxKTHpOupPz0ls8n10fPlVS9r8d7Fvh+o+UnSmP+refzV3dLelb4fBwCAJkLSNgAi2rSRrWcPSZJ9wwbZN/5x7Cd1Pa/meOPXfonr4r4Z7uNPlu+W4YeKXgAAAIQ2ewi3R/DagKxz3RuQeerTpmYzsmU7jiNpu3+dlPOb67jN6VJqx8bfKwSd3vJ0TTplkiTJkKG/L/i79hXv8/1AvcZJA25wHTvKpY+ulkoP+n4cAACaAEnbAPn/7d13fBTV2sDx38zW9F5ICL1L70hRAQsIdsUK1mtv2H3t5XIVu+L12q8dUBG7VxGRKk167xBI72XrzPvHhE1CEkhCymZ5vp/PuGfqOevJLGefPXNO+Hnn+dL5c+Yc+4SuZ5Wnt9ZiSIV6SIkOZliHGAB2ZRWzuqEmXBBCCCGEEAGj8vAILSdom1WaxcIDCwGj9+ewVsOOeU73VmEEl73HFXty6t+pYd2s8nTvi+t3jRbu+l7XMyLZeHow15nLnfPvxOFphCHZzngWWg8y0nn7YM6NoDXwOLpCCCFEE5CgbTMJHz8exWKMU5v/3XfobvfRT4hsAwm9jHTqKihohF+mwTdEAsCsFTJEghBCCCGEqKzS8AjmlhO0/W7nd3h1o+zndjwXk3rssptNKgPaGr1t0wuc7MspqXvGmgYbvjLSqhl6HLuHbyBSFZV/jfwXrUON7xubczbz1NKnGv7pPrMVLv4vBBudUdj+P1jwr4bNQwghhGgCErRtJqbISELLJiTzZmdTtHDhsU/qOq48va1xetuO65VIqM2YFOHbtQfJLz1GMFkIIYQQQpxQSsuGR7CZVVRVaebS1I6u68zZUf5023mdzqv1uUPaR/vSf+2ux6P2+5ZAQaqR7jgGQmLqfo0AEWGL4NXRrxJkNiZA/m7Xd3y6+dNjnFWfjJLhovehbBxdFjwHm75t+HyEEEKIRiRB22YUeUH5r+x5X3997BO6VRjXdvP3jVAiCLaaubB/MmD0ovhylfS2FUIIIYQQ5RxlPW1b0tAIazPXsjt/NwADEgbQJrxNrc8d3L48yPrXrnoEbdfPLk/3vqTu5weYLlFdeHr40771F1a+wIq0FQ2fUYdT4fSnytfn3ATpGxs+HyGEEKKRSNC2GYWcfDLmuDgAiv5YgCc7++gntOoLEWUNzN0LGm1Q/auGtfWlP1m2F02TCcmEEEIIIYTh8PAILWkSskoTkHWq2/AEvVtHYDUbX5uW7zlGe/1IHhdsLMvbElL5ybkT2JntzuS6ntcB4NW93PPHPY0zMdmw26D3JCPtLobPL5OJyYQQQrQYErRtRorZTMThCck8nmP3tlUU6HGOkdY8sOWHRilXp/gw34Rku7OKWbQjq1HyEUIIIYQQLc/h4RFaStC2xF3Cz3t+BiDYHMzpbU+v0/l2i4l+KZEA7M8p5WBeae1P3vEbOPKMdLezwRpSp7wD2e39bmd40nCgEScmUxSY+KrR+QUgby/MngJeT8PmI4QQQjQCc3MX4EQXefFFZL/zDgB5M2cRc911KOpRYuknnQ9L3zDSm+ZC/6sapVyTh7Vl6S6jJ8FHS/cyqktco+QjhBBCCCFaFodbA4xgZkvw277fKHYXAzCu/TiCLcF1vsaQ9tG+8WxX7Mnh3L7JtTtx/azydK+L65xvIDOpJp4b9RyXfn8pB4oO+CYme3bEsyhKA46VbAmCSz+Dt0+F4gzY/Sf8+iicNa3h8hCNSnO58KSn483NxZubiyc3F29eHnppKbrbbSwuN7rHg2I2o1itKBYLitWKGhyEKTKy0mKOj0e125v7bQkhxDFJ0LaZWdu0IWT4cIoXL8Z94ADFi5cQOnJEzSckD4CIFMjfD7v+gNJcCIpq8HKd3iOBhHAb6QVO5m1JZ09WMe1ipWeAEEIIIcSJzOPVcHmNoG1LGdN2zvb6TUBWkTGu7Q7AmIysVkFbZyFsLZs8ODgGOp5Wr7wD2eGJya788UpKPaV8t+s7esT04MoeVzZwRskw6WP4cAJoblj2JiT0hH5XNGw+ot50XceTkYFj0yacW7fi2rsP9/79uA4cwJOeDnrDDtlnionB0qqVsSQnY+3QHluHDlg7dsQc1fDfr4UQoj4kaOsHIi+dRPHixQDkzZp59KCtokCPc43etpobtvzYKI0Ns0ll8rB2TP9lK7oO7yzcxbPn92rwfIQQQgghRMvh8Gi+dEsYHmF/wX5Wpq8EoF14O/rE9anXdfq3jcSsKng0nWW7ajmu7ebv4fDj/iedDyZLvfIOdIcnJrt3wb0ATF85nXYR7RiRfJTvRPXRZiic/QJ8d6ex/v1dENcVWg9s2HxErWilpZT+/TfFK1bgWLsOx+bNeHNzmyx/b3Y23uxsHBs2VNlniorC1qUL9p4nEXTSSdh79sSSktKwPcCFEKIWJGjrB8JOPRVzXByezEwKf5+POz0dS0JCzSccDtoCbPqm0X4hvnJIW96cv4Nil5fZqw5w19guxIXZGiUvIYQQQgjh/w6PZwstY3iEb3Z+40uf3/n8egddgq1mereOYPW+PHZlFnMwr5SkyKCjn7R+dnm61yX1yvdEcWa7M9mas5V31r+Dpmvcu+BePh73MZ2jOjdsRgOuhrT1sOJd8LrgiyvgH/MhPKlh8xFV6JpG6dq1FC1YQMnyFZSuXw9u9zHPM0VFYUlJwZKchDk6xhjiICoKU2Qkakhw+VAIFguK2Yzu9qC7XOhuF7rLhVZSgjc3D2/e4SUXd1o67oMH8WRkgKZVydObm0vJX39R8tdfvm1qeDj2k3oQ3K8/wYMGEtSnD2pw3YdaEUKIupCgrR9QLBYiL76IrDf/DV4veTNnEnfHHTWfkDwQwltDwQHY+TsUZ0NITIOXKyLYwmWD2/Duot24PBofLd3DPWd0bfB8hBBCCCFEy+Bwlwdt/X14BK/mZe6OuQCYFBMTO0w8ruuN7BzH6n15ACzansUlg1JqPrgoA3bNN9KRbSBl8HHlfSK4rd9t7M7f7RuD+Pbfb+fT8Z8SE9TA33PO+hdkbIa9i6EoDT67BK75GWyhDZuPQHM6KV6yhKLff6dw/h94s2qe4NoUHY29e3fs3bth694dW4cOWFJSMIU2Xr3objeejAxc+/bh3LUL185dOHftwrlzB97MymXVCgooWbqMkqXLjA1mM0EnnUTwoIEEDxpE8KBBEsQVQjQ4Cdr6ichLLiHrP2+D10vuFzOJufFGVFsNvVpVFXpdCItfBc0DG7+GwTc0SrmuHdGeD5fswaPpfLR0Lzed0pEQm/zZCCGEEEKciEorBm0tR5k81w8sO7SM9JJ0AEYmjyQu+Pgm1h3VJZZX520HYOGOYwRtN84BvawHX6+LjSHOxFGpisqzI57l4C8H2ZS9idSiVO6afxfvnvkuNlMDPu1nssAlH8E7oyFvr9Hz9qvrjMnKVP/+IaIl0DWN0lWryJs7l8KffkYrLq72OGu7dkawc/BgggcOwJyY2OTDDygWC5bkZCzJyYQMG1ZpnzsjA8fGjTg2bjJeN2zAk5lZfoDHQ+natZSuXUv2u++hWCwEDRxA6IiRhIwYga1LZxlOQQhx3CT65icsiYmEn3kGBT/+hDcnh4IffiTygvNrPqH3JCNoC7BuVqMFbZMigzinbxJfr04lv9TNx8uMwK0QQgghhDjxVBwewd/HtJ2z4/gnIKuoT+tIwmxmCp0eFm3PRNN0VLWGoMy6WeXpXhcfd94nimBLMK+Pfp3LfriMjJIM1mSu4fEljzNtxLSGDYCFxMIVs+Hd08GZD9t+hl8ehnHPNVweJxh3aip5X31N/rff4j5woMp+xW4nZPhwwkaPJmTECCwJ8c1QytqzxMdjiY8n7LTyCQTdhw5RsnIVJStWULJyJa5du3z7dLe7vCfu9OmY4+MJGTWSsDFjCDn55Jo7ZAkhxFFI0NaPRE+eTMGPxgyzOR99RMT559XcOEk4yZjxNH0DHFgOObsgukOjlOuWUzvxzd+paDr8Z8FOrhzallDpbSuEEEIIccKp2NPW7sfDI+Q78/l93+8ARNujGdV61HFf02xSGdYxhv9tSie3xM3GgwX0ah1R9cCcXZBqTH5GQi+I737ceZ9I4oPjeX3061z989WUekr5YdcPtA9vz419bmzYjOK6wqSP4ZMLjKcX/3oLotrD0JsaNp8Apus6JctXkPvJJxTOm1dlfFg1JISwM84g7PTTCTl5GKrd3kwlbRiWVq2ImDiBiIkTAPBkZ1OyYiXFy5ZSvHAR7tRU37GejAzyv/yK/C+/QgkOJnTkSMLGjiF01ChMEdV8bgghRDX8+5mmE0xQ377Ye/cGwLllCyXLVxz9hN4VJjRYN7vm445Tp/hQzu2bDEBuiZsPFu1utLyEEEIIIYT/qjw8gv8GbX/Y9QNuzZjkaEKHCVhMlga57sgu5UMsLNyRWf1B678sT/e6qEHyPdH0iOnBtJHTUDA6sLyx5g1+3PVjw2fU4RSY+Gr5+i8PwdafGz6fAKO5XOR9+SW7zz2PfVOmUPjrr+UBW1UlZORIkl54gc6LFpI07Z+EjT6txQdsq2OOiSH8rDNp9cQTdPztVzr8+CMJDz9MyKiRKBXer15SQuEvv3DwvvvZNnwE+669ltwvvkDLy2u+wgshWgQJ2vqZ6MmTfemcDz88+sE9L4KyhgzrZoKuN1q57hjTGVPZ41/vLNxFfumxZ/oUQgghhBCBxdFChkf4Zsc3vnRDDI1w2KjOsb70wm3VTKqk60cMjSBB2/oa02YMdw24y7f+f4v/j78O/dXwGfW7EkbeY6R1Db68Fg6tbfh8AoDmcJDz8SfsPONMDj3yKM5t23z7zHFxxN15B53mz6fNO28TMeFs1KCgZixt01IUBVuH9kRPvoo2b79Nl2VLaf3mm0RceAGmqKjyAz0eipcsJeOpp8m/4EL2/+Mf5M35Bm9hYfMVXgjhtyRo62fCzzwDc2IiAEXz5+Pcvr3mgyOSod0II52zE/Yvb7RytY8N4YJ+Rm/bAoeHd/7cdYwzhBBCCCFEoKnU09ZPh0fYkrOFzTmbAegV24vOUZ0b7NptY0JIiTYCUSv35lDi8lQ+4NBayC5rv7cdDhGtGyzvE9E1J13DhZ0vBMCjebhz/p1sydnS8Bmd9gicdIGRdhfDp5dA7t6Gz6eF0kpKyH7/A3aMPZ30Z5/Fk5bm2xfUrx9JL75Ap9/nEXvzzX4/Vm1TUe12wkafRtKzz9J50ULafvwR0VOmYGld4TNB0yhZtJhDDz3E9uEjOHD77RT89BNaaWnzFVwI4VckaOtnFIuF6Kun+Naz33336Cf0vaI8/fdHjVQqwx1jOmMxlfe2PZgn/5gIIYQQQpxIKo1p66c9bRurl+1hIzsbQyS4vTqLd2RX3rm+wpBlMgHZcVMUhUeGPsKprU8FoNhdzM2/3UxqUerRT6wrVYXz3oTWg431ojRjrNvi7KOfF+B0t5vcL75gxxlnkvH883izynuXh44eTbtZM2n3+WdEnH02iqVhhiAJRIrJRPCgQSQ89CAdf/0f7ed8TfT116EmJPiO0V0uCn/9jdS7p7Jt+AhS77+f4iVL0I8YJ1gIcWKRoK0firr4Yt/g5Pnf/1BpQPMqepwLtnAjvWEOOBvvsYqU6GCmDGsHgNOjMf2XrY2WlxBCCCFEoPrzzz+ZOHEiSUlJKIrCN99809xFqrVSPx8eweV18f2u7wGwmWyc1f6sBs9jbPfynoS/birvcYjmhQ1fGWnVYrTTxXEzq2aeP+V5escZc39klWZx0683kevIbdiMLEFw2RcQU9YzO3sHfHYxuIobNp8WQNd1Cn79lV3nnEvaE0+WB2sVhbAzz6T9N3NIeXMGQWXzsYjaUxQFe/fuxE2dSvgXn9Pms0+JuuoqTLHlQ6/oJSUUfPsd+669jh1jxpLxyiu49uxpvkILIZqNBG39kBoSQtSVVxorXi/ZH3xY88HW4PKxstzFsOHrRi3b7aM7Exls/Io65+9U1u7Pa9T8hBBCCCECTXFxMX369GHGjBnNXZQ6c/j5RGTz988n35kPwNi2Ywm3hjd4Hid3jPW993mbM/BqZfNK7F0MhYeMdOfTITi6wfM+UQWZg5gxegbtwtsBsKdgD7f9fhulngZ+8i8kBq76GkKN4epIXQWzJoP3xJnPo3T9BvZecSWpt9+Ba3f5BNRhZ5xBh+++pfWrr2Dv1q0ZSxg4FEUhqG9fEv/vYTov+IM2H35A5MUXoYaXf255Dh0i+63/sPOscey57HJyZ87CW1DQjKUWQjQlCdr6qagrr0ApG7g9b/Zs3BkZNR/cv3zyMlY37hAJEcEW7hpTPi7Yk99tRNMabwI0IYQQQohAM27cOJ555hnOP//85i5Knfn7mLZzdszxpc/v1Dj/f+0WE6O6GL3isotdrNlf1uNTJiBrVJH2SN46/S1ig4z/9+sy13Hfgvtwaw0cUI1sA1d+BTbjyUd2/AZzb4MAf0zdk5vLocefYM8ll1C6erVve9CAAbT9/DNav/Yqtk6dmrGEgU0xmQgZOpRWTz9N50ULSX7lFUJPOQVM5Z+zpX//Tdrjj7N95ChSp95D0aLFMnyCEAFOgrZ+yhwVRdSkSQDoTufRx7Zt1RcSexnp1JWQvrFRy3bF0LZ0iAsBYPW+PGau3N+o+QkhhBBCCP9Q6ioPEPjbmLZpxWksSV0CQHJoMoMSBzVaXmO7l49F+eumDPA4YdO3xgZrKHQZ12h5n8iSQ5N5a+xbhFpCAVhwYAGPLHoEr+Y9xpl1lNgTLvscTDZjfd0X8MvDoAdeZxVd08idPZtd48aTN3Om7z1a27en9Yw3aPvJxwT369fMpTyxqFYr4WedScp/3qLzH/OJv/9+bJ3LO07pTicFP/7I/uuvZ+fY08l8803cFSaHE0IEDnNzF0DULOb668j94gt0h4O8L2YSc911WCoMVu6jKNB/Cvx4r7G+8n04+8VGK5fFpPL0uT254t2/AJj242bGdk8gLszWaHkKIYQQQpyonE4nTqfTt15Q9mispmloTdDLStM0dF1H0zRKXR7fdrtZaZL8a+vbHd+iYwSczulwDuig6Y1TvlO7xKIqoOnw26Y07m+7DbVsWAa929noZrvf9cysWI8tWefIzrx86svcMu8W3JqbH3f/SJApiEeHPoqiKA2XUZthcOF7KLMno+ga/PVvdEsQ+uhHGy6PemjIenRu307ao4/hWLfOt00JDib21luNJz8tFnRdRw/AYHVzq209qjExRF09hcgpk3Fu3kz+nG8o/OEHvHl5ALgPHiTrtdfJemMGIaNGEnnRRYSMGoVillBPUwiUz9UTXXPUY23zkjvZj5ljY4m64nJy3nsf3eUi++13SHz0keoP7n0J/Pq4Ma7tms9hzGNgj2i0sg3vFMsF/ZL5+u9UChwenv1hE69cKr/ACiGEEEI0tGnTpvHkk09W2Z6ZmYnD4Wj0/DVNIz8/H13XyS0sn5SpuCCPDFPj518buq7z1VZjEjAFheGRw8k42vBiDaBXq1DWHixiR2YxeUs+4vAItrkpp+Nq5Lzro2I9qmrLfuCyndqOR/o8wlNrnsKre/lqx1fobp2but7UsIHb6EEEnfIMEX88DICy6CWKnBrFA25uuDzqqCHqUXe7cXz6GY5PPgFP+Q8xljGjCb7pJjxxcWTmNvBEb6KSetVjbCzKDdcTdvUU3EuX4vzhRzzLlxu9ozWN4j8WUPzHApTYWGxnnYX17PGYWrVq3Ddyggukz9UTWXPUY2FhYa2Ok6Ctn4u57jpyP/8CvaSEvFmziLnuWixJSVUPtEdAn0th5XvlgduhNzVq2R4+uzvztmSQX+rmmzUHmdA7ibE9qukJLIQQQggh6u2hhx5i6tSpvvWCggJSUlKIi4sjPLzhJ9o6kqZpKIpCXFwcuumgb3vrxHjiI+yNnn9trEpfxcFSo2xDEofQq22vRs9zXO8i1h7cShglhKcuAEAPjiWy37mg+t/XrIr1GAjBhfPiz8MeaufBhQ+io/P13q+JCY/htr63NWxG8TejBZlRf7ofgLAVrxASFQ9Dmydwe7z1WLp+PWmPPoZr2zbfNmv79iQ8/hjBgwc3ZFHFURz3/XjRRXDRRbgPHiT/6znkf/01nrIhEvSsLByffILjk08IHjaMiIsuImzMaBSrtYHfhQi0z9UTVXPUo91eu/aT/7UmRCXm6Giir7yS7LffRne7yXztdZL+Na36gwffYARtAVa8A4P/AY34BxcbauP/zu7O/V8aj9M8+PU6fmkziphQGSZBCCGEEKKh2Gw2bLaq7StVVZvsy4WiKKiqisNd/jhfiM3iN19Sv9n5jS99fufzm6Rc43q14l8/b+VM0wrMugsApecFKGb/DYwcrkd/qbfjNb7DeJxeJ48teQyAd9a/Q7AlmOt7Xd+wGQ25ETwO+NXIR/3fw2ANgoHXNmw+tVSfetRdLjLfmGHMlXL4sVyTiZjrryf2lptRq/mMEY2rIe5HW+vWxN9xO3G33kLxokXkzp5N0fw/wGuM81yydCklS5eSERVFxHnnEXnxxdg6tG+gdyAg8D5XT1RNXY+1zUf+qlqAmOuuRY0whjrInzsXx5Yt1R8Y3x3ajzLS2Ttg1++NXraLB7RmTLd4ALKKXDw8Z72MeSSEEEIIcRRFRUWsWbOGNWvWALB7927WrFnDvn37mrdgtVDqKp/wyW71j68SRa4ift37KwBhljBGtxndJPm2jQmhd+sIzlUXl2/sdUmT5C3Knd/5fB4c/KBv/dXVr/L2urcbPqPhd8KpD5Wvf383rPyg4fNpBM6dO9lz6WVkv/22L2Br696d9rNnEX/3XRKwDQCKyUToKaeQ8sYbdJr/O3F3340lJcW335ubS84HH7Br/Hj2XjWZ/O++Q6swVroQwj/5R0tLHJUpIoLYm8qGOtB1Mqa/UPPBg/9Rnl72VuMWDOPXiGkX9iIq2ALALxvTmbVyf6PnK4QQQgjRUq1cuZJ+/frRr2xG9qlTp9KvXz8ee+yxZi7ZsRWXTURmMSnYzKZmLo3hpz0/UeopBYyel3Zz0w3ZMKmbhZPVjQDk2ZOh9cAmy1uUu6L7Fdw94G7f+ut/v86/1/y74TM65QE4+Y7y9e/vguXvNHw+DUTXdXI+/ZTdF1yIY9MmY6PFQtxdd9F+1kzsPXo0bwFFo7DExxN74z/o+MvPtPnwA8LHj0exWHz7S1as4OB997Nj1CmkT5uGc8eOZiytEOJoJGjbQkRdcTmW5GQAihcvpmjR4uoP7DIOItsY6R2/QvrGRi9bfJidf55fPm7YY3M3sulgQaPnK4QQQgjREp166qm+GdkrLh9++GFzF+2YSsp62gZb/WeUta+2feVLX9j5wibNe4JpGSbFeMrsO2048rxZ87m257XcM+Ae3/qba9/kjb/faNinABUFTn+qcuD2x3thWSMEiI+TJzOT/f+4kfSnn0Ev61Fp7diRdl98TuxNN1YK4onApKgqIUOHkvzSi3T6cwHxDz6AtUMH335vfj45//2IXRMmsueKK8mfOxetCSa3FELUngRtWwjVaiXurrt86+nTpqG73VUPNJlhWIXB9xe/1viFwxjT64ohRrDY6dG49bPVFDqqKZ8QQgghhGixip1GT9tQm38EbbfkbGFjttFJoXt0d7rHdG/S/CO2f+NLf1g4iM2HajcbtGgcV/e8mvsH3e9b/8+6//Dq6lcbJ3A7sjxAzM8PNtn3rtooWrCAXeecS/HChb5tUVdeSfuvviTopJOasWSiuZijooi5+mo6/PA9bT/5mPBzJlaamKx01SoOPvAg20edQtqz/8RRYaI6IUTzkaBtCxJ+9niC+vQBwLVzJzmffFr9gf2uhKAoI73hS8hrmuEKHp3Qg57JxgzGu7OKmTprLZom/Q2EEEIIIQJFeU9b/xga4evtX/vSTd3LluydcHA1ABu0duzUk/l27cGmLYOo4qoeV/HQ4PKxZ9/b8B7Tlk9D07WjnFVHigKjH4VTysfS5ddHYcF0aMb5PXS3m4wXX2T/jTfhzc0FwBQXS8o7b5P4yP+h1nK2chG4FEUheOBAkp9/ns5/LiDh4Yewduro268VFJD78cfsPudc9lx6GXlfz0ErLW3GEgtxYpOgbQuiqCoJjzxiNBKArDfewJOZWfVAa0j52Laap06P67g1NxklGWzP3c7GrI2syVjD8kPLWZS6iCWpS1iZtpL1mevZmrOVvQV7yXPk+RpAdouJNy8fQLjd6Hnx66Z0nv9l6/G9aSGEEEII4Rd0XfeNaRvsBz1tHR4H3+/6HgC7yc74DuObtgDrZvqS32nDAfjm71Q83gYMDop6ubz75Twy5BHf+udbPufBhQ/i9jbgk4CKAqc9BKPL82H+M0avW63p/wbchw6xd8rVZL/zrm9b6OjRdPj2W0JHjmzy8gj/Z4qMJHryZDp89x1tP/uMiPPOQ6kwKV3pmjUcevhho/ftU0/XPCG6EKLRNH9rS9RJUK+eRF50EXmzZ6MVF5PxwgskPfdc1QMH/wMWvwoeB6z6EEZOhZBYADyah515O9mUvYk9BXvYV7CPvYV7ySjJIN+ZX+cyqYpKhDWCSHskMfYYBg2KYvEWL153JO+s3EZEeA7XDh2AzSSzkgohhBBCtFSlbq+vE2GIH/S0/XXvrxS6jOEIzmh3BmHWsKbLXNcrBG0VsttPhO0aaQUO/tyeyehuCU1XFlGtSd0mEWQJ4rHFj+HVvfy0+ycKXAW8dMpLBFuCGy6jUfeB2Q7/Kwve/vUWlOTAeW+CqWnGjS1asICDDzyINy/P2GA2E3/vPURPmYJS1uFHiJooikJw/34E9+9HwkMPkv/d9+TNnIlz+3YAtMJCcj/7jNzPPsPepzdRl1xC+LhxqMENeB8JIaolQdsWKO7uuyj45Re0ggLy535L+DnnEDp8eOWDQmKh/2RY/jZedzHr/3ichUndWJ2+mo3ZG30z7DYETdfIdeaS68xld/5uACyxcLiJ8uaO9/n3DpXWYcm0j2hP+/D2xmvZEmWParCyCCGEEEKIxlHs9PrS/jARWbMOjXBgBeTuMdIdTuGsgf35cvtKAL5Yvl+Ctn7inI7nEG4N594F9+L0Olmcuph//PoPZoyZQYQtouEyOvl2Y3i6b+8A3QvrZ0FpLlzyX+MpyEaie71kvvIq2e+849tmSUoi+eWXfMPqCVEXpogIoq+8gqgrLsexdi25s2ZT8OOP6GUTlDnWruPQ2nWk/3Ma4RMnEHXJJdh79GjmUgsRuJq/tSXqzBwdTfy995D22OMApD3+BB2+nVvply6v5mVZ55H8uHsOC4Os5Gb9CVl/1nxN1UxCcAIxQTFE26OJtEViM9mwqBasJitWkxVd13F5XTi9TpxeJw6vg3xnPnmOPHKdueQ58yh2F1d7fR2N/YX72V+4nz+pXI7YoFi6RnelW1Q3ukZ3pWt0V9qGtcWkNn8PDiGEEEIIYSgpGxoBIMTWvO20Pfl7WJluBEnbhbejX3y/pi3A2i/K070ncWrXOBLCbaQXOJm3JYOMQgfxYTJ+qD84NeVU3hr7Frf/fjtF7iLWZq5lyk9TmDF2BsmhyQ2XUb8rISgavrzGeNpxx6/w0blw2Re+Jx4bkjc/n0P33kfx4sW+baGjR5P0z2cxRUY2eH7ixKIoCkF9+xLUty8JDz1IwfffkztzFs6yIRK04mLyvphJ3hczsffsSeQlFxM+/mxMoY33I4UQJyIJ2rZQkRddRMF331OyYgXuAwfIfP0NEh64n4NFB/l6+9fM3TmXtOI0CA2qcm5SSBK94nrRK7YXnSI70Sa8Da1CWmFWj//PodhdTFpxGgeLDpJadJCPVqxhV+5+VGsWJlsmqK4q52SVZpGVmsXi1PIGh91kp3NUZ7pGd6VHTA96xvSkU1QnLGrTPGIkhBBCCCEqOzwJGTR/T9s5O+b40hd2vrBpHwH3uGBjWS9fcxB0n4jZpHLxgBTemL8Dr6bz1apUbj6149GvI5rMwMSBfHDWB9z4643kOHLYmb+TK364gtdHv06vuF4Nl1G38XDl1/D5peAsMHpkvzsGLp8NcV0aLBvv7t3sfexx3PvLJpw2m4m/5x6ir5bhEETDM4WFEXXZZUReeimODRvImzWL/B9+RC8pAcCxYQNpGzaQ8a/nCJ8wgchLLiGo50nNXGohAoMEbVsoRVVJfOpJdp97HrrLRc5//8vnCbv5UF2KV/dWOjZY0zi51MEop5fhV/5IfFzjPb4QYgmhY2RHOkYajdQLOl3MPz5eyR9bMwGdkKAi7psYjTUoi935u9mVv4utuVurjKXr8DpYn7We9VnrfdtsJhtdo7vSM6YnPWN7clLsSbQLb4eqyHx6QgghhBCNrbhC0LY5x7R1a27m7pgLGE+LTew4sWkLsOM349F3gG5ng80YS/eSgUbQFmDmin3cOKoDqioBNH/RLbobn4z7hJvn3czegr1kO7K59pdr+efIf3J629MbLqN2w+GaH+GTi6AozRhG472xcMnH0OGU47584W/zKHjgASg1hrszRUWR/OorhAwefNzXFuJoFEUhqFcvgnr1Iv6BByj4/gdyZ83EuWkzAFpJCXmzZpE3axa2Ht2NsW8nTMAUGtrMJRei5ZKgbQtma98eyw1X4ZrxHmgafd76A/N1JrxWBVVRGZE8gvM7nc+ojT9jXV42ztHy9+DsF5usjFazyr+vGMANH61k0Y4sikvDeG6OxltXnc7lQ+MAYybi9JJ0tuZsZUvOFrbmGq/7C/dXupbT62Rd5jrWZa7zbQu1hBo9cWONQG7PmJ4khiTKL8xCCCGEEA2sxFlxeITm+xrx5/4/yXZkA3BaymnEBMU0bQHWVR4a4bA2McEM7xTD4h3Z7MkuYcG2TE7rFt+0ZRNHlRKewifjPuGuP+5iVfoqHF4HU/+YytQBU7n6pKsb7jtEYi+44Xf4bBKkrwdHPnxyAUx42Zh3pB50TSPrzX+T9cYbvm22Ht1Jef11LMkNOMyDELVgCg0l6tJJRF06idING8mbNYuC779HK+t969y0mbQnniT9uecJP3s8URdfjL13b/meLkQdSdC2hSpxl/Dehvf4KPwzHk6GbqmQmAfXzzfhue8GLu5yMQkhZRMgxPSGNZ+DqwhWfgBDboLYzk1W1iCriXenDOTGj1exYFsmpW4v1364gqfOPYkrhrRFURQSQxJJDEnklJTyX5+LXEVszd3KxqyNbMjewMasjewr3Ffp2kXuIpanLWd52nLftmh7dKUgbs/YnjLZmRBCCCHEcarU07YZx7SdtW2WL31B5wuaNvPSPNj6s5EOjoWOoyvtvvrk9izeYQSU3120S4K2fijSHsnbp7/NE0ue4Ltd3wHw0qqX2JG3g0eHPord3EBjEUckw7U/wZfXwfZfQPPAt7dD5lYY+ySYav9V3FtUzMEHH6Dot3m+bWHjx5H07LOoQVWHwxOiKQX1PImgnk8Sf//9FPz4A3mzv8Sx3nhiVi8tJf/Lr8j/8iusnToSef75hE+ciCVePhuFqA0J2rZAK9JW8NjixzhQdACAGRNNTH/Pi90Np6x20Tq7G2EhFWasDY2H4XfC/GeN2Ux/ewIu/bRJy2y3mHh78gDu/HwNP29Mw6vp/N+cDezNLuHBs7pV++hYqDWUAQkDGJAwwLct35nPxuyNbMzayPqs9WzM2khGaUal83IcOfx54E/+PFA+4VlyaDI9Y3vSK7YXJ8WcRI+YHgRbghFCCCGEELVTXKGnbb3GtPV66hSoqs7u/N0sObgEgNahrRnWathxXa/ONn8LXqeR7nVRlfczpls87WKC2ZNdwuId2Ww6WECPpPCmLaM4JqvJyrMjnqVNeBtmrJkBwLc7v2V77nZeOe0VkkKTGiYjWxhc9jn88jD89ZaxbekbkLYOLvqgVhOUufbu5cBtt+Hcbgy9gaIQ9I8baHXHHagmmbhZ+A9TaAhRl1xC1CWX4Ni0idzZsyn49ju0YmOycteOnWRMf4GMF18iZMRwIs87j9AxY1BttmYuuRD+S4K2LYjL6+LlVS/zyeZPfNvMqpnxI66iVUI8uU8+C8DBhx6mfbduWFu3Lj952K2w4l0oSoct38PepdC2aRu5NrOJN6/oz79+3sLbf+4C4O0/d7Ers5gXLu5NZLD1mNeIsEVwctLJnJx0sm9bRkkGG7I2sCFrAxuzN7IhawMFroJK56UWpZJalMove34BQFVUOkR0oFdsL9/4uF0iu2AxyURnQgghhBDVKalPT9viLPhjGmz+3hjfMyIFel4AJ99Rq4DVkWZunelLX9rtUkxqEwet1pbnT+9LquxWVYVrR7TnsbkbAXhv0W5evKRPU5VO1IGiKNzU5ybaRbTjscWPUeopZXPOZiZ9P4npp0xnaKuhDZORaoJxz0FMJ/j5QaPH7e4/4T+nwKSPIbl/jacWLVpM6tSpaAXGdxs1LIykF6ZT3LWrPGYu/Jq9Rw9aPf44CffdR8FPP5H31deUrl5t7NQ0iv9cSPGfC1HDwwkfN46I884lqG9f+bsW4giKrut6cxeiORUUFBAREUF+fj7h4Y3/K7imaWRkZBAfH4+q1n4Crf2F+7l3wb1syt7k29Y/vj9PnPwE7SPao+s6qXdPpfBn43Ete8+etP3sU1RrhUDoqg/huzuNdKs+cMN8oxHRDD5ZtpfHv92IVzP+/JIjg3jtsn4MaHv8wxjous6BwgOsz1rvG1ZhU/YmHF7HUc+zqla6RXfjpNiTjB65R5norL71KPyL1GNgkHoMDFKPgaE56rGp23L+oLnar19tLmT6L9sA+M9VAzjzpMSjn3hoLXx8PpRkV90XEg+XfFSnTgTF7mLGzh5LkbsIu8nObxf/RoQtoi5v5fjk7YdXehrpmM5w2wqoJsBQ4vIwbNrv5Je6sZgUFj0wmoTwBnrk/jjI52zNtuVu4675d/nm1FAVlTv738nVJ13dsJMe710Ks6cYHWkATDZjvpH+V1U6TNd1ct7/gIwXXwRNA8DasSMpM97A3KaN1GMAOBHvR9eePeTNnUv+3Ll4Dh6qst/arh0R551HxLnnYGnVqhlKWHcnYj0GIn9uv8pfVQuwJHUJk76b5AvYWlUr9w+6nw/O+oD2Ee0B45fiVs88jaVtGwAcGzaQ/uw/qRST73slJJQ1NA+thVUfNOn7qOjKoW15/+pBRAYbPVtT80q55D9LefOPHb5Abn0pikJKeArjO4zn/kH3899x/2Xp5Uv5cuKXPDHsCS7qchHdo7tjUioHrF2ai3VZ6/h8y+c8vOhhzv3mXIZ/Ppzrf7mel1e9zG97f+NQ0SFO8N85hBBCCHGCKnFW6Gl7rOERMrfBf88pD9ia7ZDQC9Syp5qKM+Cjc2HXglrn//3O7ylyFwFwdoezmzZgC7B+dnm696RqA7ZgDB1x+RCjTe726vxnwa6mKJ04Dl2iuvD52Z8zMnkkAJqu8fKql7l13q1kl1bzo0N9tR0G/1gAKUOMda8Tvr0N5twEzkIjb4eDg/c/QMb06b6Abejo0bSb+QXWdu0arixCNDFru3bE33knnX77jTYffkjEueeiVBiT2bVnD5mvvMKO0WPYe/U15H35Jd6CgqNcUYjAJz1t/byn7ZfbvuSZZc/g1Y1GcpuwNrx06kt0je5a7fGOzZvZM+lSdJcLgISHHyZ6coVfbvcuhQ/OMtL2CLh9db0eTWsoh/JLufPzNSzfk+Pb1iclkucu7EW3xMatD4fHwZacLcbQCmU9cvcU7DnmeRG2CLpGdaWNvQ39kvvRPaY77SPaY1ZltJGWRn4ZDQxSj4FB6jEw+HNPhUDSXO3Xt5Zn8eGSvQB8fcvJ9G9TwxNSHie8OwbSjIloSBlq9KoNS4CCg0aAandZsNYSAtf/Bgk9jloGXdc5f+757MzfCcCXE7+ssT3cKHQdZgyBrK3G+p1rIapdjYdnFDoY9fx8HG4Nm1ll4f2nEd/MvW3lc/bYNF3jzTVv8p91//Ftiw2KZdrIaQ03XAKAxwW/PGQMX3dYdEfcI5/jwNNv4dhU/nRl7C23EHvbrShldSb1GBikHg3eomIK//c/8r/5hpLly6vsVywWQk4ZRcSECYSeeiqqvfmfWqhI6jEw+HP7VYK2fhq01XWdN9a8wdvr3vZtOy3lNP454p+EWkOPmkf+3LkcfOBBY0VVSXnr34SOGlV+wNc3wrovjHTfK+G8GfV+Pw3B49V4dd523pi/g8N/jWZV4R+jOnDHmM7YLU03hEOBq4CNWRvZmL2R9ZnG8AoZJRnHPM+qWukc1Zlu0d18S5eoLjLZmZ+Tf2QDg9RjYJB6DAz+3OgNJM3Vfn1pUTqzVhoT4f5y1yi6JoZVf8If/zLGsQWI7Qo3zDMmZDrM64ZZk2Hrj8Z6TCdj2C57ze9l+aHlXPe/6wBjiLD/jvvvcb+vOtm/HN473Ui3ORmu/emYpzz7wybeWbgbgKtPbscT55zUmCU8Jvmcrb3FqYt5eNHD5DiMjiUKCtf3up6b+96MRW3AOTDWzYbv7wZXISUZVg4sicbrMOpGCQ4m6V/TCD/jjEqnSD0GBqnHqlwHUsmf+w35c7/FvW9flf1qcDBhp48lfMIEQoYNQzE3f6cpqcfA4M/t1+b/KxdV6LrO9JXT+XjTx75tU3pM4e4Bd9dqsoWIc8/FuXMX2W+/DZpG6t1TaffF59g6dzYOOP0po5HsLIA1n0CvC6Hj6MZ6O8dkNqncc0ZXRnWJ48Gv1rEzsxiPpvPmHzv55u9U7jmjK+f3S0ZVG39Q8nBrOMOShjEsqXx8tYoTnW3O2czWnK1klmZWOs+ludiYbQR7D1NQaBvels5RnekU2YmOkR3pHNmZlPCUhm3sCSGEEEI0gUrDI9Q0EVlhGix+1UirZrjw3coBWwCTBS56H947A9LWQfYO+O0JmPBSjXl/vuVzX/qy7pfV9y3U3+oKQeL+k2t1yo2ndOSTZfsodXv5bPk+bjqlI4kR/tVLTFRvePJwvjrnKx5e+DBLDy1FR+ed9e+w5OASnh3xLB0jOzZMRr0vhtYDyH30MtLm54NufN+xRFpoPeMV7ANGNkw+QrQA1tbJxN16K7G33IJj/XoKfviB/B9/xJuZBYBWUkL+3G/Jn/stpuhows86i/CzxxPUr5+vJ7oQgUZ62vpZT1td13n2r2crzYz74OAHuaL7FXXKR9c0Uu+8i8JffwXAkpxM288+xZKQYByw4j34YaqRjmgDtywF29F78DYFp8fLm/N38uYfO3B7y/80u7cK54GzunJKlzi/mFEysziTZbuXkaalsS13G1tytrC3YC86x76dzKqZ9hHt6RTRiU5R5cHc5NDkpp8B+QQnv4wGBqnHwCD1GBj8uadCIGmu9uuDP+3jj63GD9d/P3o6USHWqgd/PxVWvmekh9wE456r+cI5u+DfI8BdbKxf+wu0qfoI+oHCA5w952w0XSMuKI5fLvqlaX8AdxTAi13BXQK2cLhnK1hr9zTVtJ82+8a0vWxwG6Zd0KsxS3pU8jlbd5qu8eHGD3l99et4dA8AFtXCbf1uY0qPKcfddtddLtKeeZa8WbN820ISnCSfnIMpPAzOfBb6XVVp/GSpx8Ag9Vg7utdLyfLl5H//PYX/+xWtsLDKMeb4eMJOP52wM88geMAAFFPTfaeWegwM/tx+lZ62fubV1a/6ArYKCk+e/CTndz6/ztdRVJWk5/7F3tRUHJs24U5NZd8119L2448wx8TAgGtg4xzYsxDy98G8J2H89IZ+O3VmM5u4+/QuTOzTimd/2Mz8si8Gmw8VcPUHK+iVHMHNp3bkzJMSMTVBz9uaxATFMCh2UKWbusRd4gvgHl62527HpbkqnevRPGzP3c723O2wp3y7zWSjfUR72oW3o214W9pFtKNduLEca0gMIYQQQojGVuL0+NLB1fW0LcqEvz8x0tYwGHXf0S8Y3QHGPAo/lw3r9d2dcONCMFcOBn+06SM03ZiQaVLXSU3/xNLGr42ALUCvi2sdsAW4cVRHPl22jyKnh5kr9nHV0Lb0SDoxflwIBKqicm3PaxmUMIj/W/x/7M7fjVtz8/Kql5m3bx7PDH/GNzF0XXkyMzlw512Url7t2xZ93mjiY+ahFOvGU5Hf3g6b5sLE1yAiuaHelhAthmIyETJsGCHDhqE9/jjFf/5J/vc/UDR/PrrTCYAnI4PcTz8l99NPMcXEEDZ2LGFnnE7I4MEoFnnCVbRs0tPWj3rafrjhQ15c9SJgBGyfHfEsEztOPK783OkZ7L3yStz79wNg69qVtv/9EFNkpNG74c2TwVNqHHzVnGYdJqE6S3Zk8c+fNrMhtfKskR1iQ5g8rC3n929NRFDTfxDX9pcYj+bhQOEBduTt8C0783ayJ3+P79f62ogNijUCuWVB3MNB3eTQZKymanq5iFqRX0YDg9RjYJB6DAz+3FMhkDRX+/X6WdvZcLAAs6qw/dlxVZ9+mj8NFvzLSA+7zegleMyLe41Jyw7+bayPfqRSsDfPkccZX51BqaeUIHMQ/7vwf0TaIxvmjdXWO6MhdZWR/scCSOpbp9P/s2An037aAsDQDtF8fsPQWj05prtcaA4HutcYlsIUFnZcYzjK5+zxcXgczFgzg/9u/K/v6TqrauX63tdzXc/r6tQmL12/gQO33YYnPR0AxWql1dNPEXHuuVCaCz8/DGs/Kz/BFgFjH4MB16ChSD0GALkfj4+3qJiieb9R8Mv/KF60yDcRe0WmiAhCx44h/IwzjDFwrQ3/vVnqMTD4c/tVgrZ+ErT9afdP3P/n/b71R4Y8wqRukxokT9eBVPZeeSWetDQA7L160eaD9zGFhsKyf5f3bghNgJuXQEhsg+TbUDRN56cNabz5xw42HqwcvLVbVM7pk8SkQSn0bxPVZEMnHO9N7fa62Vuwt1Igd0feDvYX7sere499gTIKCvHB8SSHJtM6rDWtQ1vTOqy1bz02KBZVkX88aiL/yAYGqcfAIPUYGPy50RtImqv9etknW9idVUy43cy6J86sfJDXDS91h+JMYyzbO9dCROvaZXBoHbx9KuhesITAHX9DmDGk11tr32LGGmPS3Mu7Xc5DQx5qwHdWC2kb4K3hRjqxN9y0sM6XcHq8nPHyn+zNNnrr/vuK/ozr1cq3X9c0HBs3Ubp6FY5Nm3Fs34YnLR1vTk6Va6lhYVhat8bari32rl0J6tMHe6/emEJDjlkO+ZxtGGsy1vDI4kfYW7DXt61deDv+b+j/MbRV1eE9jpQ/dy6HHn3MF2QyJybS+vXXCerVs/KB236Bb++AorTybUn90c5+iQxTK6nHFk7ux4bjLSqi6I8FFP7vfxT9+Se6w1HlGDUsjNCRIwkdPZrQkSMwRUQ0SN5Sj4HBn9uvErT1g6Dt+sz1XPPLNTi9Rvf+2/rexo19bmzQfJ27d7P3qsl4s4xBvG09utPm7bcxR0fDpxfBznnGgZ3PhMtnVho3yV/ous7C7Vm8+ccOlu2q2ohtHRXEOX2SmNgniW6JYY0awG2sm9rtdXOg6AB78vewt2Avewr2GEv+HrId2XW+nlW1khyWTHKosSQEJ5AYkmgswYkkhCSc0D115R/ZwCD1GBikHgODPzd6A0lztV8nvLuerCIXSRF2ljw0pvJBm7+DmVca6R7nwiUf1S2TH++D5W8b6QHXwMRXcHgcnPnVmeQ4clAVlR/O/4HWYbUMBDeUnx6Av94y0uNfgME31Osyv25K54aPVgKQFGHn59tPRv17JfnffUfxnwvx5uXVv4wWCyGDBhE6dgxho0djSUys9jD5nG04pZ5S3lzzJh9v+rhSh4vx7cdz78B7iQuOq3KO7vGQMf0Fcv5bPqldUP/+tH71FcxxVY83Mqra61ZXVEpOupyg8c+gBkc13JsSTUrux8ahlZRQ9OdCI4D7xx9oJSVVDzKZCB44kNDTTiVs9GisbdrUPz+px4Dgz+1XCdo2c9A2vTidy364jMxSY+zW8zudz5MnP9koAUfHtm3smzzF1yi0tG1Dm/fewxphgX+fDCVGQJfTn4bhdzR4/g1pa1ohn/21l69Xp1LorDrMQHJkEKO7xTO6WzzDOsZgtzTsYOTNcVMXugrLA7llQd3UolRSi1LJcVQNYtdWtD26UjC3YjouKI7YoFiCLbUfu60lkX9kA4PUY2CQegwM/tzoDSTN1X4d9cbfuDwa3RLD+PmuUZUP+vRi2P4/I33lV9BpbN0yKc6CV/uCqxAUE9yylM+yVjFt+TQAzmx3Ji+c8sLxv5m6cDuMCcgceWC2GxOQBUXW61K6rjP5/eWs27Cbs3cv5aLU5QQV5lV/sMmEOSEeS1w8atmQCLrXi1ZQgCcnB/fBg+Ct+cms4EGDiJw0ibAzTket8DiwfM42vG2523hm2TP8nfG3b1uQOYjre13P5B6TsZvtAHhycki9eyolf/3lOy7ykktIfOT/avfI9p5F8MM9kLnFt0kPiUM57WHoNxlMMlVNSyP3Y+PTHA6KFy+m4JdfKPpjAVpBQbXHWTt1JOy00wg9bTRBfXrXaSIzqcfA4M/tVwnaNmPQ1ouX6365zvePfP/4/rx7xrtYTI03Rqtz5072XXe9b6gEU1wsbd59F7uyFz672DhIUeGqb6DDKY1WjoZS4vLw4/o05q5JZfGOLLRq/prtFpVB7aIZ3C6aQe2j6ZsSedxBXH/7cC52F5NalMqBwgPVvjq8VR8RqYsgcxCxQbG+JcYeU2k9NjiWWHss0fboRv37bWj+Vo+ifqQeA4PUY2Dw50ZvIGmO9uu+g2mc+obRZh3cPppZNw4rP6AwHV7qBroGESnG0AhqPdpaf74Avz8NgKvzmYyzZpNRkgHAzAkz6RHT47jfS52s/QLmlD391vtSuOA/9b6UJzubPS+/TvHXX2HVKnc4UENDCRk2lJCTT8beqze2zp1QbbYar6W73bj27aN0/XpK16yh+M+FRiD3CKbISCIuuIDoKVOwJMTL52wj0XSNb3Z8w0urXiLfme/bnhiSyB397mBMaXtS77gDz8FDxg6LhcT/e5ioSy+tW0YeFyybgb7geRR3hd6Dcd3gjGeMH0r88GlJUT25H5uW7nZTsmo1RfPnUzh/Pu59+6o9To2IIOTkYYSOGEnIiBFYEuKPel2px8Dgz+1XCdo2Y9D2tb9f470N7wGQFJLE5xM+J9oe3ehlcB86xL7rb8C1cycASnAwSf/8J+GW5bCwrAdDcIwx0UJkSqOXp6FkFjr5cf0hftuczrJd2bi91f9pW00qvVpH0Cs5gh5J4fRMiqBzQigWU+1vzpb04azrOtmObA4VHSKtJI204jTSi9N96bTiNDJLM32zMh+vUEsokbZIouxR1b/aooi0l7+GW8Mxq83TO8Dr9ZJxKI24yAgUrxfd5UJ3u43lcNrrBa8XXdOMV68GWoVXTQNNM4478tWroWu1H6O4NhRFMb4Iq4rxK7CiopjUI7Ydbd/RtqnGusmMYjYZk52YTCgWC4rJZOyzWJps7Ojaakn3o6iZ1GNg8OdGbyBpjvbrpt2pTHhnHQCn90jgnckDyw9Y9hb8/ICRHnkPjHmsfhm5SuD1AVB4kJlhoTwTa7SLT219Kq+Pef143kLd6Tq8c1r5BGnX/Axthx39nGp4i4rJ+fBDct5/v9Jjul4U1rXpzdi7riZ27OhKPWLrXlQd55YtFM77nYIffsC1e3el/YrFQsT55xN17TXk2e3yOdtIch25vLnmTWZvm+0bMmHkeo2bftaxeIzvJaa4WFq/+irB/fvXOx8tZw+u7+/HvuuXyjs6nAZjn6jzRHmieUi7p/nouo5r1y4Kf/+dot/nU7pmjfGZXw1bly6EjBhB6MgRBA0YUOWzWuoxMPhz+1WCts0UtN3u3s4tv98CgFkx899x/6V3XO9Gz/8wT24u+2+6Ccfadb5tMddfR1zcYpTdvxsbEnrBtT+BLazJytVQipweFm3PYv6WDP7YlkF6gfOox1tNKl0SQ+mWGE6HuBA6xIbQPjaUtjHB1fbKDbQPZ4/mIas0ywjolqT7XrNKs8guzSarNIus0iwKXNU/UnK8wixhhFkrLJZQItQQor12Ij1Wwt1mQt0mQtwmQrwm7B4Vu0fB6tYxO73gdKKXOowZlh2laKUONEdp+Tans3IgtkK6pn+gxVEcDu4eDuaazWA2oZjMKGazsc9cIW0xG/tMJhSL2QgKV0z7zjGhmC2V02YjgGxc78h147q6yURhSTERMTGolsPHmMuPObxuMqNYjrJ++NgAuKdbokD7XD1R+XOjN5A0R/v1r817uezjTQBcNKA1L1zcp/yAd8fCgRVG+pZlEN+9/pmt+i+u7+7g7JQk0szGj7pfTPiCk2JOqv8162P/CnivbIiHxN5w45916sWo6zqFv/yPtGefwZuZ5duuBAWxuPtI/hM7kIzgaM7u1Yo3Lu/XYD+I6rpO6cqV5M6cReEvvxhtncNUFetZZ9L6vvuwtWpV80XEcdmVt4uXl0+n7UcLOHtleTsztW0IkS/+k4E9zziu6/s+Z527UX99tPzeO6zbBDj1QUjsdVz5iMYl7R7/4cnOpmjBnxT98QfFS5eiFRZWe5wSFETI4MGEDD+Z4CFDsHXujA5SjwHAn9uvfhe0nTFjBtOnTyctLY0+ffrw+uuvM3jw4BqPnz17No8++ih79uyhc+fOPPfcc4wfP77W+TVHo3f7ge38Y+k/fOOQ3jvwXqacNKXR865SltJSDj32OAXffefbFjJkIEnd1mJ2ls2G2mksXPYFtKBH3o+k6zr7ckpYvjuHFXtyWL47hz3Z1QxIXg1FMcbHbR0VRFJEEEmRQbSKtJMYbsPmLaVn+yQigq1+1/OwsTi9zkpB3IpB3czSTHIdueQ588h15lJUkkdYKYSVQmgphJbqhDqM9RCHTrADgl0Q5IRgp06QL20s5obp+CtE3VUMSh8ZfD4cOK64Xha4Vixlgd/DgeiKQeka12sTnLYYwWVTxf2mCoHm8nVj25HrFd6DH5MvL4HBnxu9gaQ52q+/rdnFP2ZtBeDa4e15bGLZUAV5++CVsuBQ/Elwy5Ljy8zrYdY7A3k6yOipOCqqBzPOmXl816yPr66H9bON9LlvQr8ran2qOy2NtKeepuj338s3ms1EXnwRcbfcwiFTCONfW0ihwxgm4alzT2LysHYNWHiDJyuLnP9+RO5nn6EVF/u2K3Y70ZMnE3PD9ZjCWl7nDH/nyc42xq9dvty37de+Ch+cruIxKwxJHMJNfW5iQMKAen2HqPQ5qyiw8Wv47QnjXqyo+zlG8DahiX/wELUi7R7/pHs8lK5bT/GihRQtWoxj/foaO/mYoqIIHjwYb48eJIwdg61DhxMmLhBo/Ln96ldB25kzZzJ58mTeeusthgwZwiuvvMLs2bPZunUr8fFVxxJZsmQJo0aNYtq0aUyYMIHPPvuM5557jtWrV9OzZ89a5dkcjd47fr2DBWkLABjVehRvjH6j2W5uXdfJ/fgT0p97zjehgSk8jMR+WYS3yjYO6ncVnPN6QI2RlFPsYtPBAjYezGdj2euurOJ6dbq0mlSiQ6xEh1iJCbWWp0OsRIfYCA8yE2ozE2Y3E2a3+NIhVjOq2nL+n2olJXiys/FkZeEte/VkZePNycaTm4s3Lw9vfr7xmpePXt1Mnc3AZTYWjwoeU+XF7UsruE3gPWK7ZlLBbEIt6xmqmsyYzBZU1WS8miyYzJaytBmTyYxqMqNW2mbBpJoxqyZMqgmzYsakmjCVvZqVsn1K+WJWzb5XVVErfz5oOuiHh2HQy4ZoOPyqgVcr26/VsE0rH9JBq3ANb4VhHrwedI8X3etF97jhyLTHYxzn8VSb1j0eY71CWvgBRanSA7lyj+bDgeIagtWHe0eba17HpKKoR7yazFW3m01VjkNRKSguIiIqqjxvVS3rpW0M6aGYVCPQraplPbYrrpcN4VFx/Vjb5UtSg/PnRm8gaY7265y/tnPP3B0A3D22C3eO7WzsXPom/PKQkR79CIy677jyKnGXcPbsMWS5iwD4zBFKrxsWQ1Per4Vp8PJJoHmMIcPu3gQWe61OzfvmG9KffqZSkDT0tNNIeOB+rO3a+bb9sjGNGz9eBYDFpDDzxmH0bxPVoG/jMG9BAbmffkr2+x9U6kFmiowk9pabibrsMhRLy+2g4U9KVqwgdeo9eDKNSaaxmMm++XymJ61lV/6uSsf2juvNtT2v5bSU01CV4xymzeOE1R/Bwheh8FDlEzqfCcPvhLYnB9T3uZZOgrYtgyc3l+IlSyheuIiixYsqPTlxJHN8PMFDhxAyZAjBgwdjad1agrgthD+3X/0qaDtkyBAGDRrEG2+8ARj/41JSUrj99tt58MEHqxw/adIkiouL+f77733bhg4dSt++fXnrrbdqlWdTN3p/2vUT9y+8H4AIWwTfnPsNsUGxjZ7vsZSsWMGBu6fizSr/EApv6yShfw5mmw5Db4Ez/xnQ/9CXuDzsyixmd1b5siurmN2ZRRQ4GifodDiAG2QxYbeYsFtU7BaTb91mUSvvMxtps0nBbFKxqGWvJgWLScWslr2aFMyqitVsvJrL9ptUBZOioCoKqgoKoBTkQ1YGemYGZGSgZWWh5WSjZ2ej5WTjzTYWvbS0Uf4f+FgsmEJDUUJDICQIb7Adb5AVt92MM8iMw6ZQatEpMWsUmzwUq24KVRdFqpsik4t81UmB4iRfcVBochnBWgvoAfA3qyqqL4hrBHnLAr5lwV2LaikP9qpHHKeYqm7zBYsrH6OioqpGXgpK+TZFxaSWbVNMqIpaZaluu28bCqquoGo6qqZj9oKi6Zg0UL0aqgYmDZSycYAVj4bqNcYQVsrWFa8GHo+xfnifxzgej4fi/AJCbHZUXQeP13fs4TQeY6xhX9pjjFXsW68YYC4LUnM4+Hx42+G0t0K64mOnouVRlKpBXLO5bOzosnGeD6dNKoqilm1XKqdVU/Xby9KKqpZfT1WMCT+POLfi9srpiseqZdvL0ofHplZqOsZUdbuilF1fqXHduGaFdYWy82s+5/C6DuQXFBCVnEzYiBFNUo0StG2aoO1/F2zmyV/2APD4xB5cM7y9sfOD8bB3sZG+5S+I73Zcef17zb95c+2bAIwtLuHljCy46APoecFxXbdOfn8W/nzeSNdyjF7N6ST9mWfJmz3bt80UG0viI48QduYZ1X5xf/r7Tby3yBh/NibEypxbhtMmJrhh3kM13Dk57H/5ZVzfzK00bIKtcycSHnmUkCE1P90ojk7XNLLffY/MV14x2huAOS6O5NdeJbhfP7yalx93/8hba99iX2HlHrHtwttxTc9rGN9+PHbzsX8cOGpwwe2AVR8awdvijMr7kgcawdtuZ9dvokDRoCRo2/Louo5z2zZK/vqL4mV/UbJ8OVpRUY3Hm+PiCBowgOD+/Qka0B97165GpwnhdyRoWwsul4vg4GC+/PJLzjvvPN/2KVOmkJeXx9y5c6uc06ZNG6ZOncpdd93l2/b444/zzTffsHbt2lrl25SN3qzSLM6fez55zjwAnh/1POPaj2vUPOvCk5tL2hNPUvhL+aD2JqtGXK8CIjuWoJxyD4x+NKADtzUpdLg5lO/gYF6p8Zpbwq70PPJckFPsJqfYSU6xq8bJz5qDqmtEOQqJceQTW5pPbGkesb50vm/7kTMYHw+PolJkDabIFkKhNYQiWzBF1hCKbEa62BZCoTWYElsIpdYgSi12HFY7JZYgPCbL4diA709MQamQptIXHkWp+TgUDV1xguJEV53oigNdcR6xONBxouEE1QOKG11xoeNGL0ujuMvWXeiKG3CVbfefehbNS9F0FN0YzsPkLXstW8xeMOlKpe2qpmPxlh/jO84LqlZ+nFnTjfXqjtUqH2vy6pWOMZWVpfptRz9WrbBNvj6I45EdpTBi6aYmyUuCtk0TtJ3xvw28+Md+AF66pA8X9G8NRZnwQmdAh5hOcNvK42onZpVmMf7r8ZR6SjErKnP2HaCdx2Nc+5a/wNQEX3adhfByT3DkgWqGO9dCROujnuLav58Dd96Jc9Nm37aI884j4aEHMUVE1HyeR2Py+3+xbJcxZFqHuBC+vvlkIoPrPynZ0Rz+UhrldpP12uuVhkgDCB8/nvj778OSmNgo+QcqT24uBx98kOIFf/q2BQ8bSvL06ZhjK3fO8Wgeftr9Ex9s/IDtudsr7Yu0RXJ+5/OZ1HUSyaHJNeZXq+CCq8QI3i6dAQUHKu+LbAMDr4V+kyEkpk7vVTQcCdq2fLrHQ8nGjWT+/jvKxo2Urlp91I5OanAwQX37ENR/AMED+hPUuzdqSEgTlljUxJ+Dtn4T5s/KysLr9ZKQkFBpe0JCAlu2bKn2nLS0tGqPT0tLqzEfp9OJ01k+KVVBgTGxkqZpaFrjDqI5a8ssX8B2bJuxnNHmjEbPsy7UiAhavfQioT+MJv2ZZ9EKCvC6VNJWRZK7M4SEzNcJ9rrRxzxxwgVuQ6wmOsWF0CnO+FDVNI3MzEzi4uJ8N7Wu6xQ6PGQXu8g5vJS4KHR4KHJ4KHSWvTrcFDk9xvay11K3F4fbW6egr6p5iS3NJ6Ekh4SS3CqvsY58TPrx/30VWoLItYWRZwsl1x5GXlk6xxZGnt1I51uNIG2J2Vb3vw0P4NGAo08WVz/WsqUhx2vTAS+oHhTVCOwqqhsUDyheFMVzRLr8FcWDolbc7y1Leyofo3hQFTeq6kbFOE5RvCh4QdHKztMADV3R0BXdeKXs9cS6PZuVrho9C10moFZPlta2cpq/EpUKAV6zF1S9QhDZCya9PFB9OIisaqDqetkrR301VbPdVO3x1V/Pd2wtt/vSFa5XbX5a2Y9Eevl1FL18/cj0ka8VzzuRuRW9ydo4/tSWCmSFTq8vHRFU9oG39UeMfxeB7hOPu304Y80MSj3GF96LulxCO+8S2LsIsnfAmk9hQBPMAbHyAyNgC9B70jEDtoW//87BBx9CK/tOodjtJD7+OJHnn3fMrKxmlf9cOZAL31rCjowidmUWM+WDFXx07eDy/8eNwJKcTPL054mefBVpTz+DY50xMXHBjz9S+McfxN1yM9GTJ6NYGyd4HEhK/v7bGA7hUNmQBIpC7C23EHvLzdWOJW9WzUzsOJEJHSawKHUR7294n5XpKwHIc+bxwYYP+HDDh4xqPYpLul7CyUknY1br8ZXdGgzDboHBN8CGr2Hxq5Cx0diXt88YA3f+NDjpfBh0PbQeeMJ9vxPieClmM0G9emFPSCA+Ph7F46F0wwaKly2jdNVqStesqTRUjlZSQvGSpRQvWWpsUFVsHTti792LoF69CerdC1vnzjJcjajEb4K2TWXatGk8+eSTVbZfeOGFmBu5q7qu6yilCgdLDrImag3j/1X7CdOamh4SjDczA/3wmC0HgA1gmvUS5oT30Fr3PKH/Ydd1HY/Hg/nwY7T1ZAaiypbD19V00HQdr6ajO51oDic4HeB0gtOJ6nKhuJyobheKDsXArrKlLryqCY/ZUr6YLLjLXj0ms7GoZnQUcHrQHXno+XmAjq77vqJVOw6wXuG/lbdV2Vx1f4UN1R+qV96uV5usPZ1ax8dUNFQ0TGiY9MNpr7FecR8aKl5MyhHr6GXX0H3XMtLl60rZ+vHSKrzqivE2dZSyV2ObRuXtlG3Ht71CPVNxe+Xjqz/GOK66a1ZNK5UCzUde78h01X1KDdupVLfHum5NeVS9TvX5Hak2tVjXmq7VNY/y91x+fs0H1aVMx/v+G1OT5K9Qq8+Pw53zFfAVrEq6bF051jlH2X94e3XXq3hOba5b3XFHPfeIdeUQtB3XNE8TeWTc7CZR6Cz//xx+OKC4pXyIMrpNPK7rr89cz1fbvgIgxBLCzX1vhuTT4b3TjQMWPGcEUWs5tmy9eJxGz0QAFBh+V42H6h4Pma++SvY77/q2Wdu2Jfm1V7F37VrrLCOCLXxw9SDOf3MJWUVO1u7PY/L7yxs9cAsQ1KsX7b74nLyvviLzxZfw5uWhl5SQ8cKL5H31NYmPPUrIsGGNWoaWSvd4yH7nHTLfmFE+L0h0NEnTnyd0+PBjnq8oCiNbj2Rk65Gsz1zPZ1s+45c9v+DW3OjoLDiwgAUHFhAXFMeEDhM4p+M5dIrqVPeCmizQZxL0vgR2zIO//g07fjP2eZ2w7gtjie0CfS6F3pdCRM29fIUQNVOsVoL79ye4f38AdK/XGE5h1WpKV6+iZOUqPBkVhi3RNJzbt+Pcvp38r742rmGzYe/evVIg19KmjYyNewLzm6BtbGwsJpOJ9PT0StvT09NJrOERncTExDodD/DQQw8xdepU33pBQQEpKSl89dVXTfZ42cH0gyQlJLWIxyBKVq0i45/TcG4uf9wLDYKUXKKnPknI6NP9fkbyxlBdT9t6XaekBPeBA7j27cd9YD/u/ftx7d+Pe99+3GkHK0/gZFIhOMhYjkGNiMCSlIQlMRFzYgLmhLLX+HhjW3w8anDjjZnmV7xu41FHZyE4C8rTrkL00nyKc9IINWso7qIKxx2xuIrBXYKie4+dX53452eArprBZDUeC/UtJmNRTNWvK6bybTWum8vG1zzKuqKWX1cxxuDUfeNqKr5tFRcdhaLiYkLDwo0xPCvup+I51Z9f7T6qO/bwmBxHvlLNtsPjdRxxXI3H1/YaR1znuK9xtLIdqZptx3Vc5WM1TSMzK6uGz9XjyLtByilqq6H+fayLgoICoqKijn2gOC6FjiN62joKYNcfxoawJEjqV+9rezQPTy17yvez7M19bibaHg0pg6HLONj2ExSkwop34eTbjudtHN2az6Co7Im97hMgrkv15c3MJHXqPZSsWOHbFnbGGbT657OYQkPrnG1KdDCfXj+Ey95ZRk6xi7X787jy3b947+qBxIc1YpAaUFSVqIsvJvz008l87TVyv5gJmoZr9272XXMtYePOIuHBB7Ec8XTjicy1fz8H73+A0r//9m0LHjiQpBdfxJJQdfLsY+kV14tpcdO4d+C9fL39a2Ztm0VasfF3mFmayQcbP+CDjR/QM6Yn53Q6h9PbnF73QisKdB5rLNk7YeX78Pcn5b3Ks7bBvKdg3tPQ4RToc7lxD1jl0W0h6ksxmYwAbPfucOUV6LqOO/WgEcBdtZrS9etwbt3m++EHQHc6KV2zhtI1a8gt26ZGRGDv1g17t27YunfD3r07tvbt5WmIE4TfjGkLxkRkgwcP5vXXXweMhn+bNm247bbbapyIrKSkhO8qjMd08skn07t3b7+diKwljl2je73kf/sdWa9Mx52eU2mfpVUCkZddQeSFF2COOXHGRKptPeq6jjc72wjE7t9vBGf378O1/wCu/fuOOvvk0ZgiIrAkJ9ewJNXrC4Nf0zRw5kNpLpTmGQ3Mw+nS3LL1w+kjjnPVPDh8s1JUMAeB2QZm+1FerUesV0ibrEbaZAHVYqybLEesHw7Alm2vzTEtLHDVEj9XRVVSj4HBn8cECyTN0X695r2lLNiZB8Cyh8aQuP8H+PJa44BBN8DZL9T7+h9t/IjpK6cD0DWqK19M+KL8kfD0jfDv4YAOQdHGGLP2RnjPHie8MdB4dBzghvmQ3L/KYcXLl5N6zz3lbTizmYT77iVq8uTj7gm1Na3QF7gFaB0VxIfXDKJTfMMM81Sb+9OxaRNpTz1N6Zo1vm1KcDBxt95K9OSrTujHdnVdJ3/ON6Q/8wxaSYmxUVWJvekmYziEBnpq06N5WHhgIXN3zmXBgQV4jph/QlVUekf1Znyn8YxtO5a44Lj6ZeQuNYZOWPNp+WSCFZmDjCBv93Ohy5mNc9+dwKTdExiOtx610lIcm7fgWL+O0nXrKV2/Hve+fcc8T7FYsHbuhL1bd+zdumIrC+qaTpB2UEPz5/arXwVtZ86cyZQpU/jPf/7D4MGDeeWVV5g1axZbtmwhISGByZMnk5yczLRp0wBYsmQJp5xyCv/61784++yz+eKLL/jnP//J6tWr6dmzZ63ylKBt7ekeDwXvP0/Wu//FVXBE2VWVkKFDCT97PGFjxx510oVAULEeFa8X96FDlQKy7v37ytb3lzfq6kAJDsaakoK1TQqW5NaBF5TVvEZgtTgLijOhJMtIl2Qb67502f7SHGiA8XnrRgFbONhCjV4GluAKr8FgCQFLUHnaGlz5GN9xFbcFlQdem2IylRNES/5cFeWkHgODPzd6A0lztF8venMhqw8YP4RufuosguZeBxvnGAdMngsdTq3XtfcX7OfC7y6k1FOKgsIn4z+hd1zvygd9dQOsn2WkR90Po/+vnu/kKJa+Cb88ZKQ7joGrvq60W9d1st99l8yXXzF+TAbMCQkkv/wywf3r38v4SFvTCrn6g+UcyncAEGY38+LFfTjjpOOfHKzWnQ40jfw535Dxwgt4c3N9262dOpL4yKOEDB1y3GVpadzp6aQ9+RRFv//u22ZJSSHp+ecI7tdw9X+kXEcuP+7+kbk75rI5Z3OV/QoK/eL7MbbtWEa1HkXb8Lb1zGgPrP0C1n5upI9kshr3ePdzjABuaN17FIvKpN0TGBqjHj25uTg2bKB0/Xoca9fh2LQJT2Zmrc41JyZi69gRW6dOWDt1xNaxE7ZOHSWYewz+3H71q6AtwBtvvMH06dNJS0ujb9++vPbaawwZYjQMTj31VNq1a8eHH37oO3727Nk88sgj7Nmzh86dO/P8888zfnztx4qVoG3d6QfXU/T8peSuLaH4kI0qj5iazQT37UvIiBGEjByBvXt3lBb6XsFouHoys3AfTMV98CDugwdx7T9A8c6dKOnpuA8dqvRIQ22Z4mKxprTBmpKC5XCANiUFa5s2mKKjW+a4Nc5CKEyHwkNQlA6FaZXTxZllQdjcxg3Cmqxgj4SgKAiKBHsE2MIqLOFgC0OzhpLv0IiIa40aFFn5GEuw8ei+8HuB8LkqpB4DhT83egNJc7Rfz3zpD7ZnlWI1qWx94lSU5zuCu9j4t/be7caTGnXk1txM+WkK67PWA3BJl0t4dNijVQ/M2QVvDALNY/zweetfENXuON9VBY58eLWv8SMxwI1/Qqs+vt3eggIOPvhQpYBd8LChJL/wQqM8aZZe4OCaD1aw6VCBb9t1I9rzwFndsJqPY1iuOt6f3rw8Ml59lbwvZlaaxCD87LOJf+B+LPGBH7jTNY28WbPJeOEFtKLyp7ciLrqQhAcfwhTadMMHbMvdxg+7fuC3vb+xr7D6nngpYSmMSB7ByOSRDEochN1cx+E1dB32LTPGud38vdGxojqt+kLn06HTWEgeKJ0R6kHaPYGhqerRk5WFY8tWnFu3GD1zt2zGtWu370fEYzHHx2Pr1BFrx05GQLd9O6xt22GOj2uZcYcG5s/tV78L2jY1CdrWU3EWzLkR19/zydsVTMG+INzF1f9jrYaGEtS7N0F9+2Dv2Qtb505YkpP9IpCr6zpacTGejAw8GZm40w4ZgdnU8gCt5+AhdLe77he3WLAmJVUIyLYpD8y2bt2yxpT1OI2x5PJToeCgMd5bleBsmvHlrSGZ7RAcCyExEBxTORAbFFXzuiWoVo/4B8z9eIKTegwMUo+BwZ8bvYGkOdqvJ0+bR1qhi9hQKysv9sDnlxo7+14J582oco47I4OCH36keOkSnNt34M3JAVXFHBtLUK+eBA8axMyoHcxIN3rQtg1vy6wJswi21NA++uX/YOkbRrrr2XDZZw33Bn97Eha9ZKR7XQIXvuPbVbpxI6l33oX7wAHftthbbib21lsbdV6HIqeH+2av5acNab5tXRJCef6iPvRNiazXNet7f5Zu2EjaU0/hWLfOt00NCSH29tuIvvLKBhsWwN84d+8m7bHHK41dbIqJIfGJxwk/vR7jyjYQr9fLsp3LWF20ml/3/cru/N3VHmcz2egf35/BrQYzMGEgJ8WchKUuP65oXti3FDZ9C5u/g8KD1R9njzB64bYbCW2HQ1w36fhQC9LuCQzNWY+aw4Fz+3Ycmzfj3LLFCOru3ImWn1/rayjBwVjbtMHatm2FxVg3xcaeMAFdf26/StBWgrb1p2mw5DWY9xS65sWRY6FgfyiFOfG4MwqPeqpit2Nt3x5bhw5YkpMxJ8Qbk2QlJGCOiUENC0MNCalzY1j3etFKSvDmF+DNz0PLz8ebn1+2no83Jxt3RgaezExjychELy2t9/8CNTQUS5sUo8fs4YBsihGgtbRKbBmTtGleKMqA/ANQcMB4zU+tnC7OOPZ1asMSXBaELVt8AdnD2+Iqb7OGNOr4qgF1P57ApB4Dg9RjYPDnRm8gaY72a68nfqHYpdEhLoTfO84yxsEEuGwmdD3Ld6w7PZ3M118nf843x3wSSQPWdlCYN8DM1Ns/5aT4XjUf7CgwxpwtKpuE+IovjZ5+xyt3D8wYCp5S40md21ZCVFt0XSdv9mzSn3kW3WWMMWuKiCBp+vOEjhp1/PnWgq7rfLR0L8/+sBmX1+hNpSpw5dC23DW2C9EhdZuE5njuT13TyPvySzJffAlvhYCArXMn4u+9l5BRowLmy71WUkLW22+T8/4HvroHiLjgAhLuvw9TZGTzFY6q9bgzbycLDixg4YGFrMlYg0f3VHtekDmIvnF9GZg4kH7x/egR04MQSy17CmsapK6CrT/Ajt8gbX3NxwZFQ9uTod0IaDMUEnrWqyd+oJN2T2Dwt3rUdR1vVhbOHTtw7tiJc+cOnDt24Nq+o9Jnd22oISFY2rbB2qYt1tbJmJOSsB4esjEpqWV1QjsGf26/StBWgrbHb99f8PUNkLfXt8ll6Uxx2NkUb8uhZO2aek+4pQQFoYaGoFgsKIpaNtO8YqQVBd3pRHM6fa/Up0fsUaghIViSknwfTJZkI21KTCQ/KIiETp0w+Xtg1us2gq95eyF3r/Gat88IxuYfMH4116pv3NWaLRzCEiE0wXgNS4TQxCPSCcawA34kIO/HE5DUY2CQegwM/tzoDSRN/Z5dbg9dHv0FgAGtQ/mqaLIx2ac1FO7bCRbjEey8r74i/Z/T0IorP3mjRkRgSUhA17y4Dx5Cr2a8f1u3bsTdcTuhp51Wc/Bv7UyY8w8jHdUebl58fLPb6zp8fB7s+sNYH3ornPVPvEVFpD3+BAU//OA71N6rF61feRlLcnL986unTQcLuP+rtWxILR8uIcxu5pZTO3Hl0DaE2WsXEGuI+9OTm0vmSy+T9+WXlYZMCB48mPj77iWo11EC735O13UKvv+BjBdewJOe7ttuad2aVk89ScjJJzdj6codrR6LXEUsO7SMRamLWJS6iPSS9BquYoyH2zGyI71ie9Eztie9YnvRKaoTFrUWf0+FabBjnhHA3fm78XlQE5MNWvWG5AHlS3SHFjfxbUOTdk9gaCn1qOs63pwcnNt34Ny5A9eevbj27sG9dx+u1FTw1D0eYIqKqjz3zuF4SWIi5oQETFFRLebHPH9uv0rQVoK2DcNVAgv+BUveAL1Cr4p2I9FHP4bHlEzJmjU4t27DuWsnrh07ce3fX6+xYBuKGhaGOS4Oc3x82WscloQE48OmLFCrhodX+0HjV/Wo60ZP2by9Rm+R3L2Qt6c8QJufWrlO6kJRjYBrRDJEtIbwZGMJOyIga22Zv7L5VT2KepN6DAxSj4HBnxu9gaSp3/OerCJOfWEBAHe1T+WuQ/cZO066AC7+AM3pJO3pp8n/8ivfOWpYGFGXXUbEuedg7dDB155Ky0/lofcvpc3mHEav1Yg/ouNPUN++xD9wf/WTO+k6fDAe9i0x1gdcDRNfrf8bW/0xfHubkQ5vDbcspXT7PlLvuafS7N1Rl19O/IMPoFrr1rO1IXm8Gu8s3M1r87ZT6i5v14XZzVw1tC3XDG9PXJjtqNdoyPuzdO1a0p55Fsf6yj0uw8adRdwdd2Br3/64rt+UdF2neMkSMl99rdIQEFgsRE++irhbb/WrHmW1nlBO19lfuJ+V6StZkbaC5WnLySg5+tNzdpOdTpGd6BzVmS5RXegS1YXOUZ2JskcdpUBeSFsHexbD3rLFcYweffZISOwFCSdBfA+jN258t+P7EaaFkXZPYAiEetTdbmPenr17y4K55Ys7NbXW4+YeSbFYjFhLQgLmhHgs8Qnl6YSydHw8qu3o/3Y1BX9uv0rQVoK2DevQOvj+LuPxmYo6nQ7DbjXGOyprtGsuF+59+3Cnp+NJz8CTkW6MLZudg1ZcjFZUhFZchLeoGDwedF03PjA0zZdWbDZUmw3FZkOx21BtdtQgO2pEBKaICEwRkZjCwzFFlq1HRRkB2rg41KCger/NJq9HR4ERkK3YW9YXoN1nPNJXH0HRZQHZFCMYe2Q6rFVAP84U8PfjCULqMTBIPQYGf270BpKmfs8LtmYw5QNjXM+v28ymf8YcY8fFH+JpdQr7b7ypUvAu4sILSLiv6mPkB4sOcsP/bvBNotQ7uhevB11N/lvv4NiwodKxYWedRfzUu7G2aVO5MFk74D8jwV3WW/fSz6Db2XV/UwWHYMYQcBrBJX3STLIX7ifz9dd9T26poaG0evopwseNq/v1G0l6gYMX/7eV2asOVOzoitWkcvpJCVzUvzUjO8diNlW9/xr6/tR1ncKffybj5VcqBblRVcLHjSP2phuxde583Pk0ppLVq8l85VVKli+vtD30lFOIf/ABvww+17cedV3nQOEBVqavZEPWBtZnrWdb7ja8tejcERcUR+eozrQLb0fb8La+pVVIK0zqEU8dahpkbDSCuKkrje+FObtqUULFmGAw4SSI7QzRHSGmo/EaGh9wPXOl3RMYAr0edZfLN9eP++BBXKmpxvw/qcY8QJ709EpPXdSHKSICU0wM5pgYTLExmKNjMMfGYPK9RmOOjcUcHY0a0jg/7Phz+1WCthK0bXiaBpvmwO/PQs7OyvviusPQm4yeGfaW+8WqwetR8xoTfOXugdzdZa97IKcsfXg247qyR0JUW4hsazSCotpCZDuIbGP0nG2hPWQbyglxP54ApB4Dg9RjYPDnRm8gaer3/PHSPTw6dyM2XKwLuwObuwDMdtxXLWbfTXfg2m1MhKTY7bR66kkizjmnyjV25e3ihl9v8PX0Sw5N5tPxnxITFIOu6xTNm0fGSy/j2lUhuGOxEH355cTefFPlAPCqD+G7O410cAzcuND4sbm2vG7470RjkiXAETuBg7+X4ty02XeIvU9vkl98EWvr1rW/bhPamVnE2wt28fXfB3B7K3+diwuzMb5nIqO7JzC0QzQ2sxFUa6z7U3e5yJ01m6wZM/Dm5lbaFzp2DNFXTSZ48CC/eUxW1zSKfv+d7Pc/oHT16kr7bF26EH/vPU02bnF9NGQ9OjwOtuRsYX3WetZnrmdj9kb2F+5Hp3YhAotqISUspVIQNyk0iVYhrWgV2oowS5hR7yU5cPBvSF1tBHEPri4fn7o2rGEQ06E8kBvZ1vguE5Fi3PuW+nfGaS7S7gkMJ3o96i4X7vT0skBuWTA3Pa2sU14GnvT0Oo+lezRKUJAR3I2KMoK9kZHlr5GRRme9w+my7WpoKMox6saf268StJWgbePxuo1JKv58AfL3V95ntkPXcdB7EnQcDebm7xJfF/WqR2eh0TO2usBs3j7Q6jEer9luBGCj2pUFZo8I0Noj6n7NE8gJdT8GMKnHwCD1GBj8udEbSJr6PT/7wybeWbibCepS3rC+DoAzaSL7Pj+I59AhAMzx8aT85y3s3btXOf/7Xd/zzLJnKHYbY922C2/HO2e8Q2JIYqXjdI/HmOzqtdfx5pT/YK2GhxN7881EXXG5MUSBrsMXVxiTIoHxmPU1P9Vu7Hxdh+/vhlUf4HUpZO9sRfYGU/mQXapKzHXXEnfHHSgW/3/aKC3fwQeLdzN71QFyil1V9gdbTZzcMYbB7aMZ2DaKOLOD5FaJjXJ/eouKyP30M3I+/LBK8NbWpQtRV1xB+NnjMYWGNnjeteHJzib/2+/ImzkT1549lfZZ27Yl9o7bCR837phf7ptbY3/OlrhL2Jm3k22529iWu43tedvZlruNfGfdAy8hlhAjgBvSisSQROKC4ogJiiEuKI5YxUxsYRYxuQewZm2B9E2QuaW8F31dBMeWBXHLArlhCcZcG6HxEBJvpENi4chewc1I2j2BQerx2DSHwxfAdacbr56MCunMTDw5OdWOd98gTKayp68jUcPDMIWGGa9h4ahhoZjCwlHCQinSNKLbtCHslFMapxxHkKBtLUnQtgl4PbDlO1j2b9j/V9X9lhBj2ITOY6HjGCMI6Se/xNek2np0lUBBqhGgzttvvFYMzJbUZzI2xRiqILp9eVC2YoA2JN6YnE3Uywl5PwYgqcfAIPUYGCRoW3szZsxg+vTppKWl0adPH15//XUGDx5cq3Ob+j3/46OV/G9TOp9anmW4aSOlORb2/9UBb34hAJY2bWjz/vtYW1fu7Xqo6BAvr36Zn3b/5NvWPbo7b53+FtH26Brz8xYVkf3uu+R88CG60+nbbmndmvh7phJ21lkoJTnw7mijnQXQ5mS4YjbYjhIQ1HWY9yTaH6+QtzOYrE1heJ3lf6e2Ll1o9czTBPXuXYf/O/7B5dH4Y2sGX60+wO9bMqr0vj3MZlbolhhO91bhdEsMo1urcLokhBEVbGmwnrBaSQm5M2eR8/77eDIzK+1TbDZCR59GxMRzCB0xHKWRxwnWSkooWryYgm+/pXD+H1Um27F26kjMtdcRMXFCiwjSQ/N8zuq6TrYjm70Fe6ss+wr24dKq/mBQF+HWcGKDYomxRxOpWonQNCLcLiKdxUSU5BJelElkQToRXi8RmpcIr0ad/3IU1QjuhsYbS3AMBEUdsURXXrdHgMl8XO+tJtLuCQxSjw1HKynBk5ODNysLT04OnqwsvDk5eLKy8eZk48nKxpOdjTcrC29BwXEPy1AdU0wMXRYvavDrVkeCtrUkQdsmlroK1nwOG76q+ZH/0ERIGWwsCT2NwembexwjtwOKM6AwHQoPouXtp/TQNoLd2Sj5ByD/QD2DshhB66h2RmA2ql3ZUpaOTGlxvZBbkhP+fgwQUo+BQeoxMEjQtnZmzpzJ5MmTeeuttxgyZAivvPIKs2fPZuvWrcTHxx/z/KZ+z+Ne/ZPQtBXMtj1F/l47h5ZH++Y4tXXtSpt338EcFwcYwZ1tudv4avtXfLntS9wVniQ6p+M5PDzkYUIstRuTzp2WRuYrr5I/d26lL2fWjh2JuvRSIoZ3xzTrgvKZ6xN7waRPjDbUkVwluD6+hbwffiNvRzBeV3mPO8ViIebmm4i9/vpGDyI2hUKHm0Xbs5i3JYP5WzLIrqYH7pFCbWZSooNJiQqiTXQwiRF2YkNtxIXZfK+RQRZUtfbtcd3louB/v5L7ySeUrllTZb8aEkLwsKGEjhhByPDhWFq3Pu7Asa5puHbtomTlKormz6d46VJ0VzU9kIcMIea6awkZOdJvhm2oLX/799KreUkvSWdf4T4OFR0irTiNg8UHOVRspA8VHTruoG51bKiEoBKs64R6PQR7XIRqGiGHF10vS+sE6xo2TSdI17HpOnZdx66Vp41XDbuuY9Wh0l+ENdRYbIdfw45YDzWGb6i4bgk2noi0BBnf5cxBYLEbr2YbWILQFDMZmZl+U4+ifvztfjxR6JqGVlCANz8fb16esfjS+Uesl6e1oqKjXtfSrh2dfv7pqMc0FAna1pIEbZuJ1w075sHGObDjt2MHPIOiIKZT2QRZZY++hCeV/wJqCzderSGgmqs++qJpxvADHqeRt6fUmNzLkV95ceYbYy4VpUNRRtlr+rFnQD2WsKQjgrLtygOzIbF+37M4UMn9GBikHgOD1GNgkKBt7QwZMoRBgwbxxhtvAMb/t5SUFG6//XYefPDBY57flO9Z13UGPT6Xd0ufIHFLNrnby3uy2vr3xfbik2SaSthTsIcNWRtYkbaCXfmVJx0Ks4bxf0P+j7M71GPCMMCxaRPpz0+nZNmyyjvMZkL6dCNEWYU9rBBbuAdTiB1lxG1o3S/A6w3DsXENjgXfULRwCY7Mql97widMIO7OO7CmpNSrbP5O03R2ZBaxYk8Oy3fnsGp3Ngfyncc+sRqqAmF2C2F2s+81vCwdajNjt6jYzCbsFhW7xYTNrGKzmLBbTITu3U7EH79gX/Q7akEN7eqICNSu3TF16465TVvMrVphbpWIOToG1W5HtVhQVAU8bvSiIiguxpuWhmffXjz79+Pevh3n2rVohQXVXt4UG0vk+ecRcf4F2Dr43wRjtdXS/r3UdI0cRw7pxelkO7LJKs2qtGSXlm8r8TTS49F1oFQI5Fp1HYsOFl3HTHnaoutYjlg3U2GfTtl+HZMOJoxXlcppVTVjUi2YVQuqyYLJZEVVVGNdMWEymVBVCybFjEktS6sWVJMJs2JBMVlQVAuqakIxWUE1o6gmVJMFRTGDYkJVVRRFRVFMKKrZeFVUVNVsDAWimIzzFRPK4VdFLT/WZPadr5ZdH8WEqphQVAUF4/qglH2nVcqua/xtKmXbfPsqHKtUOsfkSxuvqu87csVrKJRdu2JelfZVPMdXqzVUdnXb63CsorS4+/FEp3u9aMXFeAsK0YoK8RYUoBUW4snPJ//QIcJjY4meNKlJyiJB21qSoK0f0DQ49Dds/w32LYEDq8BVeJwXVcqDt5rHWBqLohpB2ciUymMpRaSU9ZZtY/yyKvyO3I+BQeoxMEg9BgYJ2h6by+UiODiYL7/8kvPOO8+3fcqUKeTl5TF37twq5zidTpwVhgkoKCggJSWF3NzcRn/Pf895n+yXXyTliN/X5/dWeOdMFY+55h+eg8xBXNHtCqb0mEK47fjKqes6xX8uJOfddyldteroBys66Ef5QdykEjZuPNHXXF3tGLyBStM0MjMzCQqPYmdmMVvSCtmSVsjurGL255SSmleKR2vcr4YmzUv/jK2ccmANAzO2EuEqrvW5GgpeRcVyuJt3LWTZw/kr8SSWterB6rguaGUdOxTFCM0oilL2WmOopmE1VEcNXT/qtZrivTRKnxPFBaYSUEtQTCUoaqmxbipBUUsq7UN1gOosWxwoSu3/LsSJTakQAjtaaLemP/Eqx+kV9zXEZ6h06GoucV744dp1TZJXQUEBUVFRx2y/Ns4ALULUhapC8gBjAdC8kLHZmFU0YwtkbjbWCw/V4aK60bO2PpN7VWQNLRv3KKHCawJaRGtytVCi2vZEjWjdaGMdCSGEECKwZGVl4fV6SUhIqLQ9ISGBLVu2VHvOtGnTePLJJ6tsz8zMxOFwNEo5DyvZu6hSwNZphs9PUflxkFJj1KZnZE9Oa3UapySeQoQ1Ake+AwcNUM7u3bC/+AKWXbtw/vgT7sWL0Q5V0z6sIWBrjbdiPmMClnMuRY2PowAoyMg4/nK1EJqmkZ+fj67rJNtVktvZGdPODhhDW3g0ncwiFwfzXeSUuMkudpNT4iG7xE1OiZvcEg9FLi/FTi9FLm+N4+YejVc1sSKxBysSe6DoGh3zDzIwfQs9snfTOe8AkUcJ4qroqMcI2ObaQtkc3Y5N0W1ZH9uR7ZGt0ZWqPyDpOkZopcn7LzVkfoHY98oMhJctdaR4UMqCuIrqQFFdRjBXdZal3SiKG1Q3KG6UWr16QfGiKJ4Kaa2h37RoYnqFf7sa5C5SalwRLYzba3Q+aAqFhbXrqCiRJuF/VBMk9jSWijxOKDhojB9bkGqkHfngLBvmoDQPPI7ynrWaxwgAq2YwWcsWi/FqthrDKdgjy14rLpHGjKMh8TVPZqFpuDMyIFImAhNCCCFE43rooYeYOnWqb/1wT9u4uLhG72l74IIHKfj0AvLDdLZ0jmTTqa0piQ5ioGLCrJoJtYQSHxxPYnAi3aK70SOmB2HWsEYtE/HxMHQouq7j2rETx7p1OLZuxb1vH1p+NlpOGqpSitnqxRJtx96tM/YzLsPS78wTekgqTdNQFIW4uLgae8InAX1qeT2n20uBw0Ohw02R04vT48Xh1nB6vDjdGo4Kr8Z2DU3T8Wg6Xk3Hq+t4ve3xaMPYqOms9WoE5WcTmbqH0LxMQvKzCM3PxlZahMnrwexxo3o9uC12HLYgnFY7RcER5EQmkBMVT1ZEAnnhMegYgZhwHfoD6LqxTQcd3RewPbyO3jThz4Z6wFUHPB4PZrO52vBQ07yXJsij8bMwHI7B1rKjro4GeNExgrg6nrJ05deK+0EDRS8711h0vHg1DyZVQVd0owCHj9E1FMWDirEoeMtePShoqHgAb9l2DaVsKU97y3p86qDoZT1LtbIuoTqKcSeUH3PUBd95VDhPL/u/UV5PR9aYjnLk1rIuqYrvCL1C+vDuw3lS4ajKoVBjvWp+1ZWi6hH12KfU/C5re40jHf+/RI1zhxyrXIH4U1FF4ZqtVnMLNAS7vXZPY0vQVrQcZpsxLmx0yx2DSgghhBAnttjYWEwmE+np6ZW2p6enk5iYWO05NpsNm63qxKSqqjb6MBQD23XDs2AZOWk7Gduhj98NXxLUtQtBXbs0dzFaDEVRGuzvJsimEmSzkBAR1AAlE7UlwwkFBqnHwCD1GBiaox5rm4/8VQkhhBBCCNFErFYrAwYMYN68eb5tmqYxb948hg0b1owlq5kaHIoW2qq5iyGEEEIIcUKRnrZCCCGEEEI0oalTpzJlyhQGDhzI4MGDeeWVVyguLuaaa65p7qIJIYQQQgg/IUFbIYQQQgghmtCkSZPIzMzkscceIy0tjb59+/Lzzz9XmZxMCCGEEEKcuCRoK4QQQgghRBO77bbbuO2225q7GEIIIYQQwk/JmLZCCCGEEEIIIYQQQgjhRyRoK4QQQgghhBBCCCGEEH5EgrZCCCGEEEIIIYQQQgjhRyRoK4QQQgghhBBCCCGEEH5EgrZCCCGEEEIIIYQQQgjhRyRoK4QQQgghhBBCCCGEEH5EgrZCCCGEEEIIIYQQQgjhRyRoK4QQQgghhBBCCCGEEH5EgrZCCCGEEEIIIYFGbwwAAA6BSURBVIQQQgjhRyRoK4QQQgghhBBCCCGEEH5EgrZCCCGEEEIIIYQQQgjhR8zNXYDmpus6AAUFBU2Sn6ZpFBYWYrfbUVWJmbdUUo+BQeoxMEg9Bgapx8DQHPV4uA13uE13IpD2q6gPqcfAIPUYGKQeA4PUY2Dw5/brCR+0LSwsBCAlJaWZSyKEEEIIIeqrsLCQiIiI5i5Gk5D2qxBCCCFEy3es9quin0jdEqqhaRoHDx4kLCwMRVEaPb+CggJSUlLYv38/4eHhjZ6faBxSj4FB6jEwSD0GBqnHwNAc9ajrOoWFhSQlJZ0wvVyk/SrqQ+oxMEg9Bgapx8Ag9RgY/Ln9esL3tFVVldatWzd5vuHh4XJTBwCpx8Ag9RgYpB4Dg9RjYGjqejxRetgeJu1XcTykHgOD1GNgkHoMDFKPgcEf268nRncEIYQQQgghhBBCCCGEaCEkaCuEEEIIIYQQQgghhBB+RIK2Tcxms/H4449js9mauyjiOEg9Bgapx8Ag9RgYpB4Dg9RjYJJ6DQxSj4FB6jEwSD0GBqnHwODP9XjCT0QmhBBCCCGEEEIIIYQQ/kR62gohhBBCCCGEEEIIIYQfkaCtEEIIIYQQQgghhBBC+BEJ2gohhBBCCCGEEEIIIYQfkaBtE5oxYwbt2rXDbrczZMgQli9f3txFEnX0xBNPoChKpaVbt27NXSxxDH/++ScTJ04kKSkJRVH45ptvKu3XdZ3HHnuMVq1aERQUxNixY9m+fXvzFFbU6Fj1ePXVV1e5P88666zmKayo0bRp0xg0aBBhYWHEx8dz3nnnsXXr1krHOBwObr31VmJiYggNDeXCCy8kPT29mUosqlObejz11FOr3JM33XRTM5VYHA9pw7Zs0n5tmaT9Ghik/RoYpP0aGFpi+1WCtk1k5syZTJ06lccff5zVq1fTp08fzjzzTDIyMpq7aKKOTjrpJA4dOuRbFi1a1NxFEsdQXFxMnz59mDFjRrX7n3/+eV577TXeeust/vrrL0JCQjjzzDNxOBxNXFJxNMeqR4Czzjqr0v35+eefN2EJRW0sWLCAW2+9lWXLlvHrr7/idrs544wzKC4u9h1z991389133zF79mwWLFjAwYMHueCCC5qx1OJItalHgBtuuKHSPfn88883U4lFfUkbNjBI+7XlkfZrYJD2a2CQ9mtgaJHtV100icGDB+u33nqrb93r9epJSUn6tGnTmrFUoq4ef/xxvU+fPs1dDHEcAH3OnDm+dU3T9MTERH369Om+bXl5ebrNZtM///zzZiihqI0j61HXdX3KlCn6ueee2yzlEfWXkZGhA/qCBQt0XTfuP4vFos+ePdt3zObNm3VAX7p0aXMVUxzDkfWo67p+yimn6HfeeWfzFUo0CGnDtnzSfm35pP0aGKT9Gjik/RoYWkL7VXraNgGXy8WqVasYO3asb5uqqowdO5alS5c2Y8lEfWzfvp2kpCQ6dOjAFVdcwb59+5q7SOI47N69m7S0tEr3Z0REBEOGDJH7swX6448/iI+Pp2vXrtx8881kZ2c3d5HEMeTn5wMQHR0NwKpVq3C73ZXuyW7dutGmTRu5J/3YkfV42KeffkpsbCw9e/bkoYceoqSkpDmKJ+pJ2rCBQ9qvgUXar4FF2q8tj7RfA0NLaL+amy3nE0hWVhZer5eEhIRK2xMSEtiyZUszlUrUx5AhQ/jwww/p2rUrhw4d4sknn2TkyJFs2LCBsLCw5i6eqIe0tDSAau/Pw/tEy3DWWWdxwQUX0L59e3bu3MnDDz/MuHHjWLp0KSaTqbmLJ6qhaRp33XUXw4cPp2fPnoBxT1qtViIjIysdK/ek/6quHgEuv/xy2rZtS1JSEuvWreOBBx5g69atfP31181YWlEX0oYNDNJ+DTzSfg0c0n5teaT9GhhaSvtVgrZC1MG4ceN86d69ezNkyBDatm3LrFmzuO6665qxZEKISy+91Jfu1asXvXv3pmPHjvzxxx+MGTOmGUsmanLrrbeyYcMGGVuxhaupHv/xj3/40r169aJVq1aMGTOGnTt30rFjx6YuphAnLGm/CuG/pP3a8kj7NTC0lParDI/QBGJjYzGZTFVmDkxPTycxMbGZSiUaQmRkJF26dGHHjh3NXRRRT4fvQbk/A0+HDh2IjY2V+9NP3XbbbXz//ffMnz+f1q1b+7YnJibicrnIy8urdLzck/6ppnqszpAhQwDknmxBpA0bmKT92vJJ+zVwSfvVv0n7NTC0pParBG2bgNVqZcCAAcybN8+3TdM05s2bx7Bhw5qxZOJ4FRUVsXPnTlq1atXcRRH11L59exITEyvdnwUFBfz1119yf7ZwBw4cIDs7W+5PP6PrOrfddhtz5szh999/p3379pX2DxgwAIvFUume3Lp1K/v27ZN70o8cqx6rs2bNGgC5J1sQacMGJmm/tnzSfg1c0n71T9J+DQwtsf0qwyM0kalTpzJlyhQGDhzI4MGDeeWVVyguLuaaa65p7qKJOrj33nuZOHEibdu25eDBgzz++OOYTCYuu+yy5i6aOIqioqJKv4zt3r2bNWvWEB0dTZs2bbjrrrt45pln6Ny5M+3bt+fRRx8lKSmJ8847r/kKLao4Wj1GR0fz5JNPcuGFF5KYmMjOnTu5//776dSpE2eeeWYzlloc6dZbb+Wzzz5j7ty5hIWF+cb5ioiIICgoiIiICK677jqmTp1KdHQ04eHh3H777QwbNoyhQ4c2c+nFYceqx507d/LZZ58xfvx4YmJiWLduHXfffTejRo2id+/ezVx6URfShm35pP3aMkn7NTBI+zUwSPs1MLTI9qsumszrr7+ut2nTRrdarfrgwYP1ZcuWNXeRRB1NmjRJb9WqlW61WvXk5GR90qRJ+o4dO5q7WOIY5s+frwNVlilTpui6ruuapumPPvqonpCQoNtsNn3MmDH61q1bm7fQooqj1WNJSYl+xhln6HFxcbrFYtHbtm2r33DDDXpaWlpzF1scobo6BPQPPvjAd0xpaal+yy236FFRUXpwcLB+/vnn64cOHWq+QosqjlWP+/bt00eNGqVHR0frNptN79Spk37ffffp+fn5zVtwUS/Shm3ZpP3aMkn7NTBI+zUwSPs1MLTE9qtSVnAhhBBCCCGEEEIIIYQQfkDGtBVCCCGEEEIIIYQQQgg/IkFbIYQQQgghhBBCCCGE8CMStBVCCCGEEEIIIYQQQgg/IkFbIYQQQgghhBBCCCGE8CMStBVCCCGEEEIIIYQQQgg/IkFbIYQQQgghhBBCCCGE8CMStBVCCCGEEEIIIYQQQgg/IkFbIYQQQgghhBBCCCGE8CMStBVCCCGEEEIIIYQQQgg/IkFbIYQQQgghhBBCCCGE8CMStBVCiBYoOzub+Ph49uzZ06T5Xnrppbz44otNmqcQQgghhGj5pP0qhBB1o+i6rjd3IYQQQtTN1KlTKSws5J133mnSfDds2MCoUaPYvXs3ERERTZq3EEIIIYRouaT9KoQQdSM9bYUQwo95PJ4q20pKSnjvvfe47rrrmrw8PXv2pGPHjnzyySdNnrcQQgghhPB/0n4VQoiGIUFbIYTwE3v27EFRFGbNmsXIkSOx2Wx8++23VY778ccfsdlsDB061Lft559/ZsSIEURGRhITE8OECRPYuXPnUfNr164dr7zySqVtffv25YknnjjqeRMnTuSLL76o9fsSQgghhBCBSdqvQgjReCRoK4QQfmLt2rUATJ8+nccee4yNGzcyZsyYKsctXLiQAQMGVNpWXFzM1KlTWblyJfPmzUNVVc4//3w0TWvwcg4ePJjly5fjdDob/NpCCCGEEKLlkParEEI0HnNzF0AIIYRhzZo1hISEMHv2bNq1a1fjcXv37iUpKanStgsvvLDS+vvvv09cXBybNm2iZ8+eDVrOpKQkXC4XaWlptG3btkGvLYQQQgghWg5pvwohROORnrZCCOEn1q5dyznnnHPUBi9AaWkpdru90rbt27dz2WWX0aFDB8LDw33X2LdvX4OXMygoCDDGJhNCCCGEECcuab8KIUTjkaCtEEL4iTVr1nDqqace87jY2Fhyc3MrbZs4cSI5OTm88847/PXXX/z1118AuFyuGq+jqiq6rlfa5na7j5l/Tk4OAHFxccc8VgghhBBCBC5pvwohROORoK0QQviBgoIC9uzZQ79+/Y55bL9+/di0aZNvPTs7m61bt/LII48wZswYunfvXqVRXJ24uDgOHTpUqQy7d+8+5nkbNmygdevWxMbGHvNYIYQQQggRmKT9KoQQjUuCtkII4QfWrl2LyWSiV69exzz2zDPPZOPGjb6GbVRUFDExMbz99tvs2LGD33//nalTp1Y574033qg0McTo0aP5+OOPWbhwIevXr2fKlCmYTKajngPGRBJnnHFGfd6mEEIIIYQIENJ+FUKIxiVBWyGE8ANr166la9euVcb6qk6vXr3o378/s2bNAozHxL744gtWrVpFz549ufvuu5k+fXqV87Kysti5c6dv/aGHHuKUU05hwoQJnH322Zx33nl07NjxqOc4HA6++eYbbrjhhvq+VSGEEEIIEQCk/SqEEI1L0Y8cEEYIIYTf++GHH7jvvvvYsGEDqtp0v7/9+9//Zs6cOfzvf/9rsjyFEEIIIUTLJ+1XIYSoG3NzF0AIIUTdnX322Wzfvp3U1FRSUlKaLF+LxcLrr7/eZPkJIYQQQojAIO1XIYSoG+lpK4QQQgghhBBCCCGEEH5ExrQVQgghhBBCCCGEEEIIPyJBWyGEEEIIIYQQQgghhPAjErQVQgghhBBCCCGEEEIIPyJBWyGEEEIIIYQQQgghhPAjErQVQgghhBBCCCGEEEIIPyJBWyGEEEIIIYQQQgghhPAjErQVQgghhBBCCCGEEEIIPyJBWyGEEEIIIYQQQgghhPAjErQVQgghhBBCCCGEEEIIPyJBWyGEEEIIIYQQQgghhPAj/w8AprYa03zIxgAAAABJRU5ErkJggg==\n"
     },
     "metadata": {}
    }
   ],
   "source": "# Radyal dalga fonksiyonları\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom scipy.special import genlaguerre, factorial\n\ndef radial_wavefunction(n, l, r, Z=1):\n    rho = 2 * Z * r / n\n    norm = np.sqrt((2*Z/n)**3 * factorial(n-l-1) / (2*n * factorial(n+l)))\n    L = genlaguerre(n-l-1, 2*l+1)(rho)\n    return norm * np.exp(-rho/2) * rho**l * L\n\nr = np.linspace(0.01, 25, 500)\nfig, axes = plt.subplots(1, 2, figsize=(14, 5))\n\nfor n, l, label, color in [(1,0,\"1s\",\"C0\"), (2,0,\"2s\",\"C1\"), (2,1,\"2p\",\"C2\"), (3,0,\"3s\",\"C3\")]:\n    R = radial_wavefunction(n, l, r)\n    axes[0].plot(r, R, label=label, color=color, lw=2)\n    P = 4 * np.pi * r**2 * R**2\n    axes[1].plot(r, P, label=label, color=color, lw=2)\n\naxes[0].set_xlabel(r\"$r$ (a.u.)\"); axes[0].set_ylabel(r\"$R_{nl}(r)$\")\naxes[0].set_title(\"Radyal Dalga Fonksiyonları\"); axes[0].legend(); axes[0].grid(True, alpha=0.3)\naxes[0].axhline(0, color=\"k\", lw=0.5)\n\naxes[1].set_xlabel(r\"$r$ (a.u.)\"); axes[1].set_ylabel(r\"$4\\pi r^2 |R|^2$\")\naxes[1].set_title(\"Radyal Olasılık Yoğunluğu\"); axes[1].legend(); axes[1].grid(True, alpha=0.3)\nplt.tight_layout(); plt.show()\n"
  },
  {
   "cell_type": "markdown",
   "id": "aeb47084",
   "metadata": {
    "id": "aeb47084"
   },
   "source": "\n### 2.5 Elektron Spini\n\nStern-Gerlach deneyi → ek bir açısal momentum (spin).  \nPauli matrisleri:\n\n$$\nS_i = \\frac{\\hbar}{2} \\sigma_i\n$$\n\nSpin-orbitaller: $\\psi \\cdot \\alpha$ (spin up) ve $\\psi \\cdot \\beta$ (spin down).\n"
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1818c63d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 612
    },
    "id": "1818c63d",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1787416912684,
     "user_tz": -180,
     "elapsed": 888,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    },
    "outputId": "4f6c036a-2c93-43e2-9063-fdc6e80dd253"
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 700x600 with 1 Axes>"
      ],
      "image/png": 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\n"
     },
     "metadata": {}
    }
   ],
   "source": "# Bloch küresi\nfrom mpl_toolkits.mplot3d import Axes3D\nfig = plt.figure(figsize=(7, 6))\nax = fig.add_subplot(111, projection=\"3d\")\nu, v = np.linspace(0, 2*np.pi, 80), np.linspace(0, np.pi, 80)\nx = np.outer(np.cos(u), np.sin(v)); y = np.outer(np.sin(u), np.sin(v)); z = np.outer(np.ones_like(u), np.cos(v))\nax.plot_surface(x, y, z, color=\"cyan\", alpha=0.15)\nax.quiver(0,0,0, 1.2,0,0, color=\"r\", lw=2); ax.quiver(0,0,0, 0,1.2,0, color=\"g\", lw=2); ax.quiver(0,0,0, 0,0,1.2, color=\"b\", lw=2)\nax.text(1.3,0,0, r\"$x$\"); ax.text(0,1.3,0, r\"$y$\"); ax.text(0,0,1.3, r\"$|0\\rangle$\"); ax.text(0,0,-1.4, r\"$|1\\rangle$\")\ntheta, phi = np.pi/3, np.pi/4\nsx, sy, sz = np.sin(theta)*np.cos(phi), np.sin(theta)*np.sin(phi), np.cos(theta)\nax.quiver(0,0,0, sx, sy, sz, color=\"purple\", lw=3)\nax.set_xlim([-1.4,1.4]); ax.set_ylim([-1.4,1.4]); ax.set_zlim([-1.4,1.4])\nax.set_title(\"Bloch Küresi – Spin\"); ax.set_box_aspect([1,1,1])\nplt.tight_layout(); plt.show()\n"
  },
  {
   "cell_type": "markdown",
   "id": "8f1b06ba",
   "metadata": {
    "id": "8f1b06ba"
   },
   "source": "\n### 2.6 Multi-elektron atomlar\n\n- **Pauli dışlama ilkesi**\n- **Aufbau prensibi**\n- **Hund kuralları**\n\nÖrnek: Neon → $1s^2\\, 2s^2\\, 2p^6$\n"
  },
  {
   "cell_type": "markdown",
   "id": "f76c7f23",
   "metadata": {
    "id": "f76c7f23"
   },
   "source": "## 3. Atomic Bonds and Molecules\n\n### 3.1–3.3 Bağ teorileri\n- Valence Bond Theory (sigma / pi bağları, hybridizasyon)\n- Molecular Orbital Theory (daha sıkı kuantum mekanik yaklaşım)\n\n### 3.4 Ab initio ve Chemical Accuracy\n\n**Chemical accuracy** ≈ $1\\,\\text{kcal/mol}$ ≈ $1.6\\,\\text{mHa}$\n\n**1.36 kuralı:** Aktivasyon enerjisinde $1.36\\,\\text{kcal/mol}$ hata → denge sabitinde **10 kat** hata.\n\n### 3.5 Born-Oppenheimer yaklaşımı\n\nToplam Hamiltonian:\n\n$$\nH_{\\rm tot} = T_e + T_N + V_{eN} + V_{ee} + V_{NN}\n$$\n\nBorn-Oppenheimer: Çekirdekler sabit → elektronik problem çözülür → potansiyel enerji yüzeyi (PES) elde edilir.\n"
  },
  {
   "cell_type": "markdown",
   "id": "f2924c75",
   "metadata": {
    "id": "f2924c75"
   },
   "source": "\n![H+H2 PES](https://upload.wikimedia.org/wikipedia/commons/thumb/5/5a/H%2BH2_Potential_energy_surface.jpg/700px-H%2BH2_Potential_energy_surface.jpg)\n\n*H + H₂ potansiyel enerji yüzeyi (Wikimedia)*\n"
  },
  {
   "cell_type": "markdown",
   "id": "3ba57d38",
   "metadata": {
    "id": "3ba57d38"
   },
   "source": "\n### 3.6–3.10 Hartree-Fock, Slater Determinant, Roothaan-Hall, Baz setleri\n\n**Slater Determinantı** (antisimetrik çok-elektron dalga fonksiyonu):\n\n$$\n\\Psi = \\frac{1}{\\sqrt{N!}}\n\\begin{vmatrix}\n\\chi_1(x_1) & \\cdots & \\chi_N(x_1) \\\\\n\\vdots & \\ddots & \\vdots \\\\\n\\chi_1(x_N) & \\cdots & \\chi_N(x_N)\n\\end{vmatrix}\n$$\n\nHartree-Fock: Tek determinant + ortalama alan.  \nRoothaan-Hall: LCAO ile matris denklemi.  \nGaussian Type Orbitals (GTO) + correlation-consistent baz setleri (cc-pVXZ).\n\n### 3.11–3.13 Korelasyon, Single/Multi-reference, Full CI\n\n- **Dinamik korelasyon** vs **statik (non-dinamik) korelasyon**\n- Single-reference → HF + Post-HF (MP2, CCSD…) yeterli\n- Multi-reference → MCSCF / CASSCF gerekir\n- **Full CI**: Tüm olası uyarmaları içerir → exact (verilen baz setinde) ama üstel maliyet\n"
  },
  {
   "cell_type": "markdown",
   "id": "370b8179",
   "metadata": {
    "id": "370b8179"
   },
   "source": "# PART II – Post-Hartree-Fock Methods\n\n## 2. Second Quantization and Quantum Computing\n\n### 2.1 Second Quantization\n\n**Occupation number representation:**\n\n$$\n|\\mathbf{n}\\rangle = |n_1, n_2, n_3, \\ldots\\rangle \\quad (n_i = 0 \\text{ or } 1 \\text{ for fermions})\n$$\n\n**Creation / Annihilation:**\n\n$$\n\\{a_i, a_j\\} = 0, \\quad \\{a_i^\\dagger, a_j^\\dagger\\} = 0, \\quad \\{a_i^\\dagger, a_j\\} = \\delta_{ij}\n$$\n\n### 2.2 Electronic Hamiltonian in 2nd Quantization\n\n$$\nH = \\sum_{r,s} h_{rs}\\, a_r^\\dagger a_s + \\frac12 \\sum_{p,q,r,s} g_{pqrs}\\, a_p^\\dagger a_r^\\dagger a_q a_s\n$$\n\n### 2.3 Quantum Computing mapping\n\n**Jordan-Wigner:**\n\n$$\na_p^\\dagger = \\Bigl(\\prod_{k<p} Z_k\\Bigr) \\frac{X_p - i Y_p}{2}\n$$\n\nAspuru-Guzik / Whitfield algoritması: Integraller → Pauli string’leri → QPE veya VQE.\n"
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "89322be0",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 357
    },
    "id": "89322be0",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1787416912841,
     "user_tz": -180,
     "elapsed": 154,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    },
    "outputId": "32ec42bd-fd9d-43dd-97cc-66d0ce4a3bdc"
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 1100x350 with 1 Axes>"
      ],
      "image/png": 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\n"
     },
     "metadata": {}
    }
   ],
   "source": "# Jordan-Wigner şematik\nimport matplotlib.pyplot as plt\nfig, ax = plt.subplots(figsize=(11, 3.5))\nax.set_xlim(0, 10); ax.set_ylim(0, 3); ax.axis(\"off\")\nax.set_title(\"Jordan-Wigner Mapping – 4 Qubit Örneği\", fontsize=13)\nfor i, lab in enumerate([\"q0\",\"q1\",\"q2\",\"q3\"]):\n    ax.add_patch(plt.Circle((1.5+i*2, 1.5), 0.38, color=\"skyblue\", ec=\"navy\", lw=2))\n    ax.text(1.5+i*2, 1.5, lab, ha=\"center\", va=\"center\", fontweight=\"bold\")\nax.annotate(\"\", xy=(1.5,2.15), xytext=(1.5,2.55), arrowprops=dict(arrowstyle=\"->\", color=\"red\", lw=2))\nax.text(1.5, 2.7, \"Z\", color=\"red\", ha=\"center\", fontweight=\"bold\")\nax.annotate(\"\", xy=(3.5,2.15), xytext=(3.5,2.55), arrowprops=dict(arrowstyle=\"->\", color=\"red\", lw=2))\nax.text(3.5, 2.7, \"Z\", color=\"red\", ha=\"center\", fontweight=\"bold\")\nax.annotate(\"\", xy=(5.5,2.15), xytext=(5.5,2.55), arrowprops=dict(arrowstyle=\"->\", color=\"purple\", lw=2))\nax.text(5.5, 2.7, \"X/Y\", color=\"purple\", ha=\"center\", fontweight=\"bold\")\nax.text(5, 0.45, r\"$a_2^\\dagger \\;\\longleftrightarrow\\; Z_0 Z_1 \\frac{X_2-iY_2}{2}$\",\n        ha=\"center\", fontsize=12, bbox=dict(boxstyle=\"round\", facecolor=\"wheat\"))\nplt.tight_layout(); plt.show()\n"
  },
  {
   "cell_type": "markdown",
   "id": "d878cde3",
   "metadata": {
    "id": "d878cde3"
   },
   "source": "\n### 2.4–2.8 Diğer Post-HF yöntemler\n\n| Yöntem | Özellik | Ölçekleme (tipik) |\n|--------|---------|-------------------|\n| MP2 | 2. mertebe perturbasyon | $O(N^5)$ |\n| CCSD | Coupled Cluster Singles+Doubles | $O(N^6)$ |\n| **CCSD(T)** | + perturbatif triples → “altın standart” | $O(N^7)$ |\n| MCSCF / CASSCF | Multi-reference, orbital optimizasyonu | aktif uzaya üstel |\n| DMRG | Quasi-1D sistemler için güçlü | bond dimension’a bağlı |\n"
  },
  {
   "cell_type": "markdown",
   "id": "f718faf8",
   "metadata": {
    "id": "f718faf8"
   },
   "source": "# PRACTICAL LAB – H₂ Molekülü ile VQE\n\nAşağıdaki laboratuvar hem **Qiskit** hem **PennyLane** ile aynı fiziksel sistemi (H₂, STO-3G) çözer.\n"
  },
  {
   "cell_type": "markdown",
   "id": "a5c05a4d",
   "metadata": {
    "id": "a5c05a4d"
   },
   "source": "## Lab 1 – Qiskit Nature"
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "aa96a00d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "aa96a00d",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1787416917701,
     "user_tz": -180,
     "elapsed": 4857,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    },
    "outputId": "fe9d693a-58c1-460e-eed3-436fa0d9a3f1"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Qiskit import OK\n"
     ]
    }
   ],
   "source": "import numpy as np\nfrom qiskit_nature.second_q.drivers import PySCFDriver\nfrom qiskit_nature.second_q.mappers import JordanWignerMapper\nfrom qiskit_nature.second_q.circuit.library import HartreeFock, UCCSD\nfrom qiskit_nature.second_q.algorithms import GroundStateEigensolver\nfrom qiskit_algorithms import VQE, NumPyMinimumEigensolver\nfrom qiskit_algorithms.optimizers import SLSQP\n\n# Primitive – sürüm uyumlu\ntry:\n    from qiskit.primitives import Estimator\nexcept ImportError:\n    from qiskit.primitives import StatevectorEstimator as Estimator\n\ntry:\n    from qiskit_aer.primitives import Estimator as AerEstimator\nexcept ImportError:\n    from qiskit.primitives import StatevectorEstimator as AerEstimator\n\nprint(\"Qiskit import OK\")\n"
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0544a86d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0544a86d",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1787416918135,
     "user_tz": -180,
     "elapsed": 428,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    },
    "outputId": "31f7ad92-65cc-43a6-93dc-c1584dd9dd48"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Elektron: (1, 1), Spatial orbital: 2\n",
      "Qubit Hamiltonian terim sayısı: 15\n"
     ]
    }
   ],
   "source": "# Molekül\ndriver = PySCFDriver(atom=\"H 0 0 0; H 0 0 0.735\", basis=\"sto3g\", charge=0, spin=0)\nproblem = driver.run()\nprint(f\"Elektron: {problem.num_particles}, Spatial orbital: {problem.num_spatial_orbitals}\")\n\nmapper = JordanWignerMapper()\nqubit_op = mapper.map(problem.hamiltonian.second_q_op())\nprint(f\"Qubit Hamiltonian terim sayısı: {len(list(qubit_op))}\")\n"
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ad1e0df6",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 333
    },
    "id": "ad1e0df6",
    "executionInfo": {
     "status": "error",
     "timestamp": 1787416918181,
     "user_tz": -180,
     "elapsed": 45,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    },
    "outputId": "c6817aa4-ab58-4ed1-c3bf-ad0db163607f"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Yeni API kullanıldı\n"
     ]
    },
    {
     "output_type": "error",
     "ename": "ValueError",
     "evalue": "The qubit_mapper cannot be `None`.",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_2172/3170371630.py\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     14\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Eski API kullanıldı\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Parametre: {ansatz.num_parameters}, Qubit: {ansatz.num_qubits}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.13/dist-packages/qiskit/circuit/library/blueprintcircuit.py\u001b[0m in \u001b[0;36mnum_parameters\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    135\u001b[0m         \u001b[0;34m\"\"\"The number of parameter objects in the circuit.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    136\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_is_built\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 137\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_build\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    138\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnum_parameters\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    139\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.13/dist-packages/qiskit/circuit/library/n_local/evolved_operator_ansatz.py\u001b[0m in \u001b[0;36m_build\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    455\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    456\u001b[0m         \u001b[0;31m# need to check configuration here to ensure the operators are not None\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 457\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_configuration\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    458\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    459\u001b[0m         \u001b[0mcoeff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mParameter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"c\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.13/dist-packages/qiskit_nature/second_q/circuit/library/ansatzes/ucc.py\u001b[0m in \u001b[0;36m_check_configuration\u001b[0;34m(self, raise_on_failure)\u001b[0m\n\u001b[1;32m    350\u001b[0m         \u001b[0;31m# operators by getting them, and if we detect they are still None they\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    351\u001b[0m         \u001b[0;31m# will be built so that its valid check will end up passing in that regard.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 352\u001b[0;31m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_ucc_configuration\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mraise_on_failure\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    353\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    354\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.13/dist-packages/qiskit_nature/second_q/circuit/library/ansatzes/ucc.py\u001b[0m in \u001b[0;36m_check_ucc_configuration\u001b[0;34m(self, raise_on_failure)\u001b[0m\n\u001b[1;32m    410\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mqubit_mapper\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    411\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mraise_on_failure\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 412\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"The qubit_mapper cannot be `None`.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    413\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    414\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: The qubit_mapper cannot be `None`."
     ]
    }
   ],
   "source": "# Ansatz (API uyumlu)\nnum_particles = problem.num_particles\nnum_spatial_orbitals = problem.num_spatial_orbitals\n\ntry:\n    hf_state = HartreeFock(num_spatial_orbitals=num_spatial_orbitals, num_particles=num_particles)\n    ansatz = UCCSD(num_spatial_orbitals=num_spatial_orbitals, num_particles=num_particles, initial_state=hf_state)\n    if getattr(ansatz, \"num_qubits\", None) is None:\n        ansatz = mapper.map(ansatz)\n    print(\"Yeni API kullanıldı\")\nexcept TypeError:\n    hf_state = HartreeFock(num_spatial_orbitals=num_spatial_orbitals, num_particles=num_particles, mapper=mapper)\n    ansatz = UCCSD(num_spatial_orbitals=num_spatial_orbitals, num_particles=num_particles, mapper=mapper, initial_state=hf_state)\n    print(\"Eski API kullanıldı\")\n\nprint(f\"Parametre: {ansatz.num_parameters}, Qubit: {ansatz.num_qubits}\")\n"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f8bcd74b",
   "metadata": {
    "id": "f8bcd74b",
    "executionInfo": {
     "status": "aborted",
     "timestamp": 1787416918348,
     "user_tz": -180,
     "elapsed": 60710,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    }
   },
   "outputs": [],
   "source": "# VQE\ntry:\n    estimator = AerEstimator()\nexcept Exception:\n    estimator = Estimator()\n\nvqe = VQE(estimator=estimator, ansatz=ansatz, optimizer=SLSQP(maxiter=80))\nsolver = GroundStateEigensolver(mapper, vqe)\nresult = solver.solve(problem)\n\nprint(\"===== Qiskit VQE =====\")\nprint(f\"Toplam enerji : {result.total_energies[0]:.8f} Ha\")\nprint(f\"Nükleer itme  : {problem.nuclear_repulsion_energy:.8f} Ha\")\n"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2cf65b6",
   "metadata": {
    "id": "c2cf65b6",
    "executionInfo": {
     "status": "aborted",
     "timestamp": 1787416918351,
     "user_tz": -180,
     "elapsed": 60713,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    }
   },
   "outputs": [],
   "source": "# Exact\nnumpy_solver = NumPyMinimumEigensolver()\nexact_result = GroundStateEigensolver(mapper, numpy_solver).solve(problem)\nprint(\"===== Exact =====\")\nprint(f\"Exact enerji  : {exact_result.total_energies[0]:.10f} Ha\")\nprint(f\"VQE hatası    : {abs(result.total_energies[0]-exact_result.total_energies[0]):.2e} Ha\")\n"
  },
  {
   "cell_type": "markdown",
   "id": "1fb607f8",
   "metadata": {
    "id": "1fb607f8"
   },
   "source": "## Lab 2 – PennyLane"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e72651f0",
   "metadata": {
    "id": "e72651f0",
    "executionInfo": {
     "status": "aborted",
     "timestamp": 1787416918354,
     "user_tz": -180,
     "elapsed": 60715,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    }
   },
   "outputs": [],
   "source": "import pennylane as qml\nfrom pennylane import numpy as pnp\nfrom pennylane import qchem\n\nsymbols = [\"H\", \"H\"]\ncoordinates = pnp.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.735])\nH, qubits = qchem.molecular_hamiltonian(symbols, coordinates, charge=0, mult=1,\n                                        basis=\"sto-3g\", method=\"pyscf\",\n                                        active_electrons=2, active_orbitals=2)\nprint(f\"Qubit: {qubits}, Terim: {len(H.ops)}\")\n"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7167ae65",
   "metadata": {
    "id": "7167ae65",
    "executionInfo": {
     "status": "aborted",
     "timestamp": 1787416918356,
     "user_tz": -180,
     "elapsed": 60716,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    }
   },
   "outputs": [],
   "source": "electrons = 2\nhf_state = qchem.hf_state(electrons, qubits)\nsingles, doubles = qchem.excitations(electrons, qubits)\ndev = qml.device(\"default.qubit\", wires=qubits)\n\n@qml.qnode(dev)\ndef circuit(params, wires):\n    qml.BasisState(hf_state, wires=wires)\n    qml.AllSinglesDoubles(params, wires, hf_state, singles, doubles)\n    return qml.expval(H)\n\nparams = pnp.random.normal(0, np.pi, len(singles)+len(doubles), requires_grad=True)\nopt = qml.GradientDescentOptimizer(stepsize=0.4)\nenergy_history = []\n\nfor n in range(80):\n    params, energy = opt.step_and_cost(circuit, params, wires=range(qubits))\n    energy_history.append(energy)\n    if n % 20 == 0:\n        print(f\"Iter {n:3d}: {energy:.8f} Ha\")\n\nprint(f\"\\nSon enerji: {energy:.10f} Ha\")\nexact_e = np.linalg.eigvalsh(qml.matrix(H))[0]\nprint(f\"Exact    : {exact_e:.10f} Ha\")\nprint(f\"Hata     : {abs(energy-exact_e):.2e} Ha\")\n"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03c7bfa3",
   "metadata": {
    "id": "03c7bfa3",
    "executionInfo": {
     "status": "aborted",
     "timestamp": 1787416918358,
     "user_tz": -180,
     "elapsed": 60718,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    }
   },
   "outputs": [],
   "source": "plt.figure(figsize=(9,4))\nplt.plot(energy_history, \"b-\", lw=2, label=\"PennyLane VQE\")\nplt.axhline(exact_e, color=\"r\", ls=\"--\", label=f\"Exact ({exact_e:.6f})\")\nplt.xlabel(\"Iteration\"); plt.ylabel(\"Energy (Ha)\")\nplt.title(\"H₂ VQE Convergence (STO-3G)\"); plt.legend(); plt.grid(True, alpha=0.3)\nplt.tight_layout(); plt.show()\n"
  },
  {
   "cell_type": "markdown",
   "id": "4922d02f",
   "metadata": {
    "id": "4922d02f"
   },
   "source": "## Lab 3 – Potansiyel Enerji Yüzeyi (PES)"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "345459a6",
   "metadata": {
    "id": "345459a6",
    "executionInfo": {
     "status": "aborted",
     "timestamp": 1787416918361,
     "user_tz": -180,
     "elapsed": 60720,
     "user": {
      "displayName": "Joseph Volkan ÖZCAN",
      "userId": "11389530967736397480"
     }
    }
   },
   "outputs": [],
   "source": "bond_lengths = pnp.linspace(0.5, 1.5, 11)\nenergies_pes = []\nfor r in bond_lengths:\n    coords = pnp.array([0.,0.,0., 0.,0., float(r)])\n    H_r, _ = qchem.molecular_hamiltonian(symbols, coords, charge=0, mult=1,\n                                         basis=\"sto-3g\", method=\"pyscf\",\n                                         active_electrons=2, active_orbitals=2)\n    e = np.linalg.eigvalsh(qml.matrix(H_r))[0]\n    energies_pes.append(e)\n    print(f\"R = {r:.2f} Å → E = {e:.6f} Ha\")\n\nplt.figure(figsize=(8,4.5))\nplt.plot(bond_lengths, energies_pes, \"o-\", lw=2, ms=8)\nplt.xlabel(\"Bond Length (Å)\"); plt.ylabel(\"Energy (Ha)\")\nplt.title(\"H₂ Potential Energy Surface (STO-3G, Exact)\")\nplt.grid(True, alpha=0.3); plt.tight_layout(); plt.show()\n"
  },
  {
   "cell_type": "markdown",
   "id": "6ecc3cc4",
   "metadata": {
    "id": "6ecc3cc4"
   },
   "source": "## Kaynaklar ve İleri Okuma\n\n- Orijinal Part I: https://www.quantum-computing-info.com/quantum-chemistry-in-a-nutshell/\n- Orijinal Part II: https://www.quantum-computing-info.com/post-hartree-fock/\n- Qiskit Nature docs\n- PennyLane Quantum Chemistry demos\n- McArdle et al., Rev. Mod. Phys. 92, 015003 (2020) – Quantum computational chemistry\n\n---\n**Bu notebook**, makalenin yapısını takip eden, görseller + formüller + çalışan laboratuvarlar içeren bir **ders çalışma ortamıdır**.  \nTam orijinal metin için her zaman yazarın sitesine bakınız.\n"
  }
 ],
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