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g2c_curves • Show schema
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{'Lhash': '1936178672590621224', 'abs_disc': 10609, 'analytic_rank': 2, 'analytic_rank_proved': False, 'analytic_sha': 1, 'aut_grp_id': '[2,1]', 'aut_grp_label': '2.1', 'aut_grp_tex': 'C_2', 'bad_lfactors': '[[103,[1,2,1]]]', 'bad_primes': [103], 'class': '10609.a', 'cond': 10609, 'disc_sign': 1, 'end_alg': 'RM', 'eqn': '[[0,1,1],[1,1,0,1]]', 'g2_inv': "['-229345007/10609','6540849/10609','-77315/10609']", 'geom_aut_grp_id': '[2,1]', 'geom_aut_grp_label': '2.1', 'geom_aut_grp_tex': 'C_2', 'geom_end_alg': 'RM', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['188','3721','160523','-1357952']", 'igusa_inv': "['47','-63','35','-581','-10609']", 'is_gl2_type': True, 'is_simple_base': True, 'is_simple_geom': True, 'label': '10609.a.10609.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.37585005339749065717302311725113749886116604957', 'prec': 163}, 'locally_solvable': True, 'modell_images': ['2.12.2', '3.2160.18'], 'mw_rank': 2, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 8, 'num_rat_wpts': 0, 'real_geom_end_alg': 'R x R', 'real_period': {'__RealLiteral__': 0, 'data': '16.854923612107439290354693142', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '0.0222991252911', 'prec': 50}, 'root_number': 1, 'st_group': 'SU(2)xSU(2)', 'st_label': '1.4.B.1.1a', 'st_label_components': [1, 4, 1, 1, 1, 0], 'tamagawa_product': 1, 'torsion_order': 1, 'torsion_subgroup': '[]', 'two_selmer_rank': 2, 'two_torsion_field': ['5.1.678976.1', [-14, 5, -8, 6, -2, 1], [5, 4], False]}
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g2c_endomorphisms • Show schema
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{'factorsQQ_base': [['2.2.5.1', [-1, -1, 1], -1]], 'factorsQQ_geom': [['2.2.5.1', [-1, -1, 1], -1]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['RR', 'RR'], 'fod_coeffs': [0, 1], 'fod_label': '1.1.1.1', 'is_simple_base': True, 'is_simple_geom': True, 'label': '10609.a.10609.1', 'lattice': [[['1.1.1.1', [0, 1], [0]], [['2.2.5.1', [-1, -1, 1], -1]], ['RR', 'RR'], [1, -1], 'G_{3,3}']], 'ring_base': [1, -1], 'ring_geom': [1, -1], 'spl_fod_coeffs': [0, 1], 'spl_fod_gen': [0], 'spl_fod_label': '1.1.1.1', 'st_group_base': 'G_{3,3}', 'st_group_geom': 'G_{3,3}'}
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g2c_ratpts • Show schema
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{'label': '10609.a.10609.1', 'mw_gens': [[[[0, 1], [1, 1], [0, 1]], [[-1, 1], [0, 1], [0, 1], [-1, 1]]], [[[1, 1], [0, 1], [0, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [{'__RealLiteral__': 0, 'data': '0.15468942240591446142412253533183', 'prec': 113}, {'__RealLiteral__': 0, 'data': '0.14478795051589897447104669124810', 'prec': 113}], 'mw_invs': [0, 0], 'num_rat_pts': 8, 'rat_pts': [[-1, 0, 1], [-1, 1, 1], [0, -1, 1], [0, 0, 1], [1, -16, 2], [1, -1, 0], [1, 0, 0], [1, 3, 2]], 'rat_pts_v': True}
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g2c_galrep • Show schema
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id: 3937
{'conductor': 10609, 'lmfdb_label': '10609.a.10609.1', 'modell_image': '2.12.2', 'prime': 2}
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id: 3938
{'conductor': 10609, 'lmfdb_label': '10609.a.10609.1', 'modell_image': '3.2160.18', 'prime': 3}
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g2c_tamagawa • Show schema
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{'cluster_label': 'c2c2_1~2c2_1~2_0', 'label': '10609.a.10609.1', 'p': 103, 'tamagawa_number': 1}
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g2c_plots • Show schema
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{'label': '10609.a.10609.1', 'plot': 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GBaUpKUmGjOExOLt/LlD28JCcVbuXKHt/zQF8Wd%2BQgSAiBC0r//Ld1zj9lGeM0as6UwUBper1der1e5ublau3YtAbC01q41azUtW1b4XFqa9Oyz0llnndSP9vtNj9u2bdL27YXHv7aige9E/6Zyucx9xUdqHk/x5nYXb0lJplWoYHrTgEhCAERIOnRIOuccadUqaehQ6ZlnbFeEcEUP4AnYtk0680wpI%2BPw1ypVkr78Uqpf/7CXcnLMpb/9Jm3dWtgyMoq3bdvM8GxpeTzSKacUtipVClvlyoe3SpVMkKNXDTgcARAha9kyMxQcEyNt2CClpNiuCOGIAHgCxo2T7r%2B/xJe/u%2BAmvd5%2BorZsMWEvv23fXrqeOrfb9O5Xr26ORVvVqoXH/LAXG3vyvxoAgwCIkNaxo7R0qfm76L77bFeDcEQAPLasLGnzZtN%2B%2BUW6ZGxLJWesKvH9m1RH9bTpiK/FxEg1akg1axa2/Mc1apiwl39MSAjUbwTgWLirASFt4EATAN9%2BmwAInAi/3/TMbdokbdxojps2mbCXf9y9u/g13yhHyUf5mRXiczS4n1lrrVYtKTm5sFWtypArEA4IgAhpbdqY4//9n906gFDl95tZrxs2mMm6GzeaY/75pk1mvbljqVhRqlPH3Gqxc1PHo/6Prkrv8zV1aln9BgBsIAAipCUmmuOBA%2BYvOtYEhBMdPGiC3E8/maCXf/z5Z3PMyjr69S6X6Z2rV0%2BqW9e0OnUKj3Xq/GXR9bU3SWc%2Bd%2BR1VGJjpVGjyvLXA2ABARAh7auvzLFePcIfItu%2BfSbYrV9fvP30k7kvLy/v6NfXrGkm5ua3evUKW0qKWTj4uDVqJM2bJ11zjRk/zlepkjRtmlmtHUBYIwAiZB06ZNYDlKQePezWApSF7GwT6NauldatK962bDn6teXLS6eealqDBuZYv7451qsXgAkVF15okudbbxUuBN2zJzM3gAjBLGCEpIMHpUGDzFZwSUnSDz%2BwuTdOTLBnAfv9JsytWSP9%2BKMJe/nHTZuO3pNXsaJ02mlSw4Ym5DVoYB43aGBmztILDqCs0AOIkLN6tdmA4MsvzT6VM2cS/hB6srNNz92aNeYfKGvWFIa%2BvXtLvi4pyYywNmxojvmBr2FD9jAFEDwEQATOsmXmPqKcHLOgX/fuJtGVYPVq6bHHpFdeMb0olSqZHsCuXYNXMiLM4sXSnDnm/N13pcsvL/UaJfv2mWD3/ffSd9%2BZsPfDD%2Bb%2BvJJ682JizNBs48Ym5DVpYo6NGpn17%2BjJA2AbQ8Aoe3v3Sr16SQsXFn8%2BNVX63//MlMM/bd0qvfGG9PLL0mefFb61Tx9p/HgzcxEoNZ9PuvRSackS%2BSR5JGVKcp9xhgmCNWsedsnBg2aY9ttvzQoo%2Be3nn0ve3cLtNuGuaVPTGjc2jxs0YNcKAKGNAIiyN2iQ9OKLR3wp78yztPzJr/TBB%2Bbv4c8/L3wtJkbq3Vu64w6pZcvglIoI1aeP9OqrklQ8AEryt2mjjNeWa/Vq6ZtvCtuaNWbi0ZFUqWL%2B/dKsmTk2bWqONWvSmwcgPBEAUba2bzdrThw8WOJb2muplql9weNWrczf11dfbYbHgJPyyy9memxurqTDA6AkpelzfaG0wy51u6XTTy9szZqZY7VqwSoeAIKDewBPgt/vV9axVmB1gPxFatevlw6887F6HiX8SVLbxKWq2uVMnX%2B%2BdNFFxUfjfL4AF4uIlZdnFkXeMmWxOvwZ/iQTAIseJamllsjXqHGxkNesmVnp5Eg9enwvgciUlJQkl0O78ekBPAn5y0sAAIDwE6zloUIRAfAkHG8PYFpamlauXHnCf04grs/Nlf74Q9q5U9qxw7Tt203btk3KyDBt61bp99%2BP/WckJJgb3xuflqsnPmguT1YJq9pGR5vplDVqnFT9pRHu1/t8PqWkpOiXX3454f%2Bjsv07lMX1b7%2B9UsuWSZ9%2BKn38sZmJ%2B1dxcdKZzQ5ozg/N5D6wU5Lp%2BUuR9Iv%2BHAKOjzc3/FWuHNT6w/l6voMndz2fn/3Pr6QanNwDyBDwSXC5XMf1ZYyOjj6pL21J1/v90p49Znhq927TMjNNsNu92xx37ZK2bXtY117r1u%2B/mzC3c6d5vjTRPz7e3NqXklK4l2j%2BLgQNGvzlZviZj0j9%2Bh35D7j1VrMWRhn8/k65Pp/b7T7hn2P7dziR6/fsMau4LFokbdz4jho1Ovz6U0%2BV2rSRWrc295KecYYUG%2BuWpqVLQ4YUe6/7z6a77jJbZwS4/ki6Pp/TvoNleb3E52fz8yurGiIJATAIhg0brgMHzL7q%2B/YVb3v3mrZvn/kLb%2B9ecyza4uLmq0sXs%2BG7z1fYsrKOvT%2Bo0VPz5x/5lUqVpKpVzeSL/Fajhgl0ycmmvfvuc7rjjuuPf7bjNdeYxDhunFk4TVJecrKibr31hDaRHz58eKmviaTry4Lt3%2BF4r9%2ByRXrzTWn%2BfGnJkqJziRrI5ZJatJDatzetTZujdCQPHiwlJkoPPGB6%2ByTl1aoljR4tjRgRsPoj9fqyYPt3sH39ybJdv%2B3ry0Io1BBKGAIOggcflO69N3A/PzrabCHl8ZhjxYom2OW3ypVNq1LFtFNOMa1KlcCvVZa1apXOadlSn/3%2Bu9ylGHJDoWBvZRZsf/xhFv%2BeNcsM7RZVv77UpYuZLNSxY6lGbQv8tmyZarVvr182blTtunXLpGanifTvYKDx%2BZ0cPr/AoAcwCIrunR4dbTZ1L1/edFDkH4u2ChUKj0lJplWoYJaoSEoqPHo85rx8%2BdBdiywuNVV9xo5VfGKi7VLCVnx8vMaOHav4%2BHjbpZSpr76SJkwwy/VlZ5vnXC7p3HOlnj2lSy4xCyuf7Hc7tkkTSVJ8%2BfInWbFzRep3MFj4/E4On19g0AMYBPv3m6Gs8uXZHQD4%2BmtzG97//lf43BlnSAMGmPUgy3rfZ3oPAOBw9AAGQUJC8V5AwImys6V77jFb/OXlmd7wPn2km2%2BW0tJCtxcbACIRARBAwGVmmiHd5cvN4yuukNLTzQxyAEDwEQABBJTfb3r6li83961Ony716GG7KgBwNgIggICaP1967z1zG8SHH0otW9quCAAQZbsARLY33nhDXbp00SmnnCKXy6XVq1fbLikk%2Bf1%2BjRs3TsnJyUpISFDHjh313Z9rKJZk3LhxcrlcxVqNUuywEizz5pnjjTcS/kLV008/rfr166tcuXI6%2B%2ByztWzZshLf%2B%2BKLLx72vXO5XDpw4EAQKw4PH330kbp3767k5GS5XC7NnTvXdkkhqbSf05IlS474HVzz55qfOD4EQATU3r171aZNGz388MO2Swlpjz76qMaPH69JkyZp5cqVqlGjhi666KJjbjXYrFkzbd26taB9%2B%2B23Qar4%2BPl85piSYrcOHNns2bM1cuRIjRkzRqtWrVK7du3UrVs3bd68ucRr3G53se/d1q1bVa5cuSBWHR727t2rFi1aaNKkSbZLCWkn%2Bjn9%2BOOPxb6DDRs2DFCFkYkhYARUv379JEkbN260W0gI8/v9mjBhgsaMGaNevXpJkl566SVVr15ds2bN0tChQ0u8NiYmJiR7/Yo64wzptdfMDh8jRzLbN9SMHz9e119/vQYPHixJmjBhgt577z1NnjxZ6enpR7wmVHubQ023bt3UrVs322WEvBP9nKpVq6aKFSsGoCJnoAcQsOznn39WRkaGOnfuXPBcfHy8OnTooE8%2B%2BeSo165bt07JycmqX7%2B%2B%2Bvbtqw0bNgS63FIbMMDsDLhsmfTss7arQVEHDx7Ul19%2BWey7J0mdO3c%2B6ndvz549qlu3rmrXrq1LLrlEq1atCnSpwGHOOuss1axZU506ddLixYttlxN2CICAZRkZGZKk6tWrF3u%2BevXqBa8dSatWrTR9%2BnS99957mjp1qjIyMnTeeefp999/D2i9pZWSIv3rX%2BZ8xAiz80cweL1epaamKi0tLTh/YBjauXOncnNzS/Xda9KkiV588UXNmzdPr7zyisqVK6c2bdpo3bp1wSgZUM2aNTVlyhTNmTNHb7zxhho3bqxOnTrpo48%2Bsl1aWCEAoszMnDlTFSpUKGhHu5Hcyf76OeXk5Egyw2pF%2Bf3%2Bw54rqlu3burdu7eaN2%2BuCy%2B8UAsWLJBkho9DzW23SQMHSrm5Ut%2B%2B0qOPmuVhAmn48OH6/vvvtXLlysD%2BQRGgNN%2B91q1b69prr1WLFi3Url07vfrqq2rUqJGeeuqpYJQKqHHjxhoyZIhatmypc889V08//bQuvvhi/ec//7FdWljhHkCUmR49eqhVq1YFj2uV9Z5eEeKvn1P2nxvhZmRkqGbNmgXPb9%2B%2B/bCemaNJTExU8%2BbNQ7InxuWSpk0zS8FMnizdeadZF3DaNKlaNdvVOdcpp5yi6Ojow3r7SvPdi4qKUlpaWkh%2B7%2BAcrVu31owZM2yXEVboAUSZSUpK0mmnnVbQEtj/7oj%2B%2BjmlpqaqRo0aWrRoUcF7Dh48qKVLl%2Bq888477p%2BbnZ2tH374oViIDCXR0ZLXawJgXJxZH7BZM2nmzMD3BuLI4uLidPbZZxf77knSokWLjvu75/f7tXr16pD93sEZVq1axXewlOgBREDt2rVLmzdv1m%2B//SbJTNuXpBo1ajCL8E8ul0sjR47UQw89pIYNG6phw4Z66KGHVL58eV199dUF7%2BvUqZN69uypESNGSJJuu%2B02de/eXXXq1NH27dv14IMPyufzacCAAbZ%2BlWNyucx6gOeeK/XvL33zjXTttaYn8MknzYxhBNeoUaPUr18//e1vf9O5556rKVOmaPPmzbrxxhslSf3791etWrUKZgTff//9at26tRo2bCifz6eJEydq9erV8nq9Nn%2BNkLRnzx6tX7%2B%2B4PHPP/%2Bs1atXq3LlyqpTp47FykLLsT6nu%2B66S1u2bNH06dMlmZnq9erVU7NmzXTw4EHNmDFDc%2BbM0Zw5c2z9CuHJDwTQCy%2B84Jd0WBs7dqzt0kJKXl6ef%2BzYsf4aNWr44%2BPj/e3bt/d/%2B%2B23xd5Tt27dYp9bnz59/DVr1vTHxsb6k5OT/b169fJ/9913Qa78xGVn%2B/3//rffX66c3y/5/VFRfv/11/v9v/xStn9OZmamX5I/MzOzbH9wBPF6vf66dev64%2BLi/C1btvQvXbq04LUOHTr4BwwYUPB45MiR/jp16vjj4uL8VatW9Xfu3Nn/ySefWKg69C1evPiI//9X9PPEsT%2BnAQMG%2BDt06FDw/kceecTfoEEDf7ly5fyVKlXyt23b1r9gwQI7xYcxl9/P4AsAezZulO64w6wVKJklY4YNM/cJluIWyBL5fD55PB5lZmbK7Xaf/A8EgAjAPYAArKpXzywN88knUrt2Una29MQTUv360i23SFu22K4QACIPARBASDj3XGnpUundd6VWraT9%2B6UJE0wQHDxYYptPACg7BEAAIcPlkrp0kT79VHrvPal9eyknR3ruOalpU6l7d2nxYmYNA8DJIgACCDkul9S5s%2BkR/Phj6dJLzfNvvy1dcIF01lnSCy%2BYXkIAQOkRAAGEtPPOk%2BbOlX780Swhk5Agff21dN11Uu3aZrLIxo0lXLx7tzRvnjnfsSNYJQNAyGMWMICwsmuXWTfw6aelTZvMcy6X9Pe/m4DYrZsUHeWX7rlHmjBBvn375JGUGRsr93XXSRMnmpWoAcDBCIAAwlJurhkS9nqlohtZpKRIM%2Brfq/YfPShJ8kkmAEpyS2ZT4hdeCHq9ABBKCIAAwt7atdKzz0ovvijl7PJpi2opSXskHSEARkVJGzZIdetaqxcAbOMeQABhr1Ej6fHHzZqB8279qCD8HVFenllrBgAcjAAIIGKUKyd1bJ93zPd9vCxPWVlBKAgAQhQBEEBkadvWTBUuQZ5cGjjzQtWoIQ0YIC1ZYjoFAcBJCIAAIkvlymY6cAl%2BbH6Foho11L590vTp0vnnSw0aSGPHSj/9FMQ6AcAiJoEAiDyHDkkjR0pTpsiXk2MmgbhccvfpIz33nPwJ5bVihZkMPHu25PMVXtq2rdS/v3TllZLHY%2B03AICAIgACiFxbt8o3d648w4Yp8%2Buv5T7jjMPesm%2Bf9NZb0ksvmeVk8oeD4%2BOlyy4zYbBzZykmJsi1A0AAEQABRDSfzyePx6PMzEy53e6jvnfLFmnmTBMGv/%2B%2B8Plq1aRrrpH69ZPOPNMsPA0A4YwACCCilSYA5vP7pS%2B/lF5%2BWZo1S9q5s/C10083vYJXXy3VqhWgogEgwAiAACLaiQTAonJyzLKB06dL8%2BdL2dnmeZdLuvBC0yvYq5eUmFjGhQNAABEAAUS0kw2ARf3xh/RqsatXAAAbn0lEQVTaa6ZncPnywucTE00I7NdPuuACKTr6JIsGgAAjAAKIaGUZAIvasEGaMcOEwfXrC5%2BvVcsMD/fvb4aLASAUEQABRLRABcB8fr/06acmCM6ebXoJ8511lgmCV10lVa9e5n80AJwwAiCAiBboAFhUdra0YIEJgwsWmPsHJTMk3LWr2Xmke3ezZR0A2EQABBDRghkAi9q50/QITp8uff554fMej9S3rwmDrVuzpAwAOwiAACKarQBY1Jo1Jgi%2B/LL066%2BFzzdqZIaI%2B/eXUlKslAbAoQiAACJaKATAfLm50pIlZqHpOXPMLiSS6QXs1EkaOFDq2VMqX95mlQCcgAAIIKKFUgAsKivLhMCXXjKhMF9SkhkiHjSIIWIAgUMABBCRvF6vvF6vcnNztXbt2pALgEX9/LMZIn7pJXOer3FjEwT795dq1rRXH4DIQwAEENFCtQfwSPLypI8%2Bkl54QXr99cIh4uhoqVs36frrpYsvlmJj7dYJIPwRAAFEtHAKgEVlZUmvvio9/7z0ySeFz1evbnoEr7/e9BACwIkgAAKIaOEaAItas8YEwenTpW3bCp9v104aPFi64gopIcFefQDCDwEQQESLhACYLyfHLDD93HPSO%2B%2BYIWNJqlhRuvZa6YYbpObN7dYIIDwQAAFEtEgKgEVt2WLuFXzuOWnjxsLnW7eWhg6VrryS5WQAlIwACCCiRWoAzJeXJ73/vjRlivTWW9KhQ%2Bb5ihXNvYJDh0qpqXZrBBB6CIAAIlqkB8CiMjJMr%2BDUqcWXk2nfXho2zCwyHRdnrz4AoYMACCCiOSkA5svLkxYulJ55Rpo/v/BewerVpSFDTK9g7dp2awRgFwEQQERzYgAs6tdfTY/glCmmh1Ay6wpeeqk0YoTUsSO7jQBORAAEENGcHgDz5eRIc%2BdKXq%2B0dGnh882aSTfdZGYRJyYe4cL9%2B6WdO6UqVZhVAkSQKNsFAMCR5OTk6M4771Tz5s2VmJio5ORk9e/fX7/99pvt0sJSbKxZL3DJEunbb80wcPny0nffSTfeaIaEb79d2rTpzwv%2B%2BMPcOFitmlSnjnTKKdJ11xV2IwIIa/QAAghJmZmZuvzyyzVkyBC1aNFCf/zxh0aOHKlDhw7piy%2B%2BOO6fQw9gyXbvNpNGvF7pp5/Mc1FR0lXd9%2BiZ79qqwvqvD7/otNOkFStMjyCAsEUABBA2Vq5cqXPOOUebNm1SnTp1jusaAuCx5eaahaWffFL64APpJk3URN1c8gVjx0rjxgWtPgBljyFgAGEjMzNTLpdLFStWLPE92dnZ8vl8xRqOLjpa6t7drCf47bfSzdVeOfoFrxzjdQAhjwAIICwcOHBAo0eP1tVXX33Unrz09HR5PJ6ClpKSEsQqw9/pp0sNqmQe9T25uwnVQLgjAAIICTNnzlSFChUK2rJlywpey8nJUd%2B%2BfZWXl6enn376qD/nrrvuUmZmZkH75ZdfAl165GnZ8qgvL9xxlgYONBNIAIQn7gEEEBKysrK0bdu2gse1atVSQkKCcnJydOWVV2rDhg368MMPVaWUkw%2B4B/AErFghnXeeVMJfD131P72nrpLM0PHo0ebtAMIHPYAAQkJSUpJOO%2B20glY0/K1bt07vv/9%2BqcMfTlDr1tLTT5ubA4tyuaSHHtIDn3VVr17m4fz5Ups2UocO0nvvlZgZAYQYegABhKRDhw6pd%2B/e%2Buqrr/T222%2BrevXqBa9VrlxZcce5qS09gCdh0ybp%2BefNxsK1a5t1AE87reDlH3%2BUHn1Uevlls9C0JJ19tjRmjNlpJIouBiBkEQABhKSNGzeqfv36R3xt8eLF6tix43H9HAJg4P36q/T442a7uX37zHOnn26C4BVXHN6RCMA%2BAiCAiEYADJ4dO6QJE6RJk6T81XeaNJHuuUfq25cgCIQSOugBAGWialXp3/82I8f33y9VqiStWWP2GU5NlWbONItOA7CPAAgAKFMVK0r33Sdt3GgCYeXK0tq1Jgiefro0e7aUl2e7SsDZCIAAgIBwu6W77zZB8MEHC3sE%2B/aVzjxTmjuXWcOALQRAAEBAJSWZCSEbN5qhYY/HbDnXs6fUqpW0aBFBEAg2AiAAICjcbjM0/PPPpmcwMVFauVLq3Fm64ALps89sVwg4BwEQABBUlSqZewM3bJBGjpTi4qQlS8z60716mWFiAIFFAAQAWFGtmvTEE9K6ddKgQWbh6DffNBNFhg6Vtm61XSEQuQiAAACr6tQxG458%2B63Uo4dZKmbKFLPpyLhx0p49tisEIg8BEAAQElJTpbfekj76yAwH79tnJo00bChNm8YagkBZIgACiEher1epqalKS0uzXQpKqV076ZNPpNdekxo0kDIypCFDpJYtpQ8%2BsF0dEBnYCg5ARGMruPB28KDk9UoPPCDt3m2eu/RS6T//MUPEAE4MPYAAgJAVFyfdcou0fr10001mP%2BG33jLDxXfeKWVl2a4QCE8EQABAyKtSRZo40UwU6dJFysmRHn1UatRImj6dhaSB0iIAAgDCRtOm0v/%2BJ82fb4aAMzKkAQPMfYOrV9uuDggfBEAAQFhxuaRLLpH%2B7/%2Bk9HSzo8jHH0tnn22GifPvFQRQMgIgACAsxcdLo0ebnUOuvFLKy5MmTZKaNJFmzmRYGDgaAiAAIKzVri3Nni29/77UuLG0bZt07bVSp07Sjz/arg4ITQRAAEBE6NRJ%2BuYbs89wuXLS4sXSGWeYxaSzs21XB4QWAiAAIGLExUl33y19953UrZtZR3DcOKlFC2nZMtvVAaGDAAgAiDinniotWCD9979S9epmKLh9e%2BnGG6XMTNvVAfYRAAEAEcnlkvr0kX74wWwlJ0nPPmsWkZ4/325tgG0EQABARKtUSZoyRVqyRGrYUPrtN6lHD%2Bmaa6SdO21XB9hBAAQAOEKHDtLXX0u33y5FRUmzZpnewDlzbFcGBB8BEADgGAkJZgu5FSukZs2kHTukyy%2BX%2BvalNxDOQgAEEJG8Xq9SU1OVlpZmuxSEoLQ06csvpTFjpOhos47g6adzbyCcw%2BX3s1Y6gMjl8/nk8XiUmZkpt9ttuxyEoC%2B%2BMPsJf/%2B9eTxokDRhgsTXBZGMHkAAgKP97W%2BmN/C228zM4RdeMAtIf/SR7cqAwCEAAgAcr1w56bHHpKVLpfr1pU2bpI4dpbvuMotJA5GGAAgAwJ/atTMzha%2B7TvL7pYcfls49lz2FEXkIgAAAFJGUJD33nFkepnJl6auvpJYtpWnTTCgEIgEBEACAI%2BjVS/rmG6lTJ2nfPrObyJVXSrt3264MOHkEQAAASlCrlrRwoVk7MCZGev11qUUL6dNPbVcGnBwCIAAARxEVZXYP%2BeQT6dRTpc2bzb2Cjzwi5eXZrg44MQRAAACOQ1qatGqV2TUkN1caPVq65BJ2EEF4IgACAHCc3G6zh/CUKWbpmP/9TzrrLNM7CIQTAiAAAKXgcpkJIZ9/LjVqJP36q9Shg/TEE8wSRvggAAIAcAKaNzfbyPXtKx06JI0aZWYJZ2XZrgw4NgIgAAAnKCnJDAk/9ZQUG2tmCaelFe4rDIQqAiAAACfB5ZJGjDB7B9eubXYNOeccEwaBUEUABACgDLRubXYNOf98ae9e6YorzEzh3FzblQGHIwACiEher1epqalKS0uzXQocpGpVs3D0bbeZx488Il18sfTHH3brAv7K5fczZwlA5PL5fPJ4PMrMzJTb7bZdDhzkv/%2BVrrtO2r9fOu006a23pNRU21UBBj2AAAAEQN%2B%2BZn3AunWl9evNEPHbb9uuCjAIgAAABMiZZ0orV5p1ArOypB49zL7CjL3BNgIgAAABVLWqtGiRdOONJvjdeac0cKCUnW27MjgZARAAgACLjZUmT5YmTZKio6Xp06ULL5R27LBdGZyKAAgAQJAMH272D/Z4pOXLzX2BP/xguyo4EQEQAIAguugi6dNPpVNPlTZskM47T1q82HZVcBoCIAAAQda0qbRihQl/u3dLXbqYYWEgWAiAAABYULWq9MEHUp8%2BUk6ONGCA9K9/MUMYwUEABADAknLlpFmzzMxgSbrvPmnIEBMIgUAiAAIIC0OHDpXL5dKECRNslwKUqago6eGHzSzhqCjpueekSy81%2BwkDgUIABBDy5s6dq88%2B%2B0zJycm2SwEC5sYbpblzpYQEM1P4/PNZJgaBQwAEENK2bNmiESNGaObMmYqNjbVdDhBQ3btLH34oVa5sdhBp00bauNF2VYhEBEAAISsvL0/9%2BvXT7bffrmbNmtkuBwiK1q0L9xBet87MFP72W9tVIdIQAAGErEceeUQxMTH65z//edzXZGdny%2BfzFWtAuGncWPr4Y%2Bn006WtW6X27U0oBMoKARBASJg5c6YqVKhQ0JYuXaonn3xSL774olwu13H/nPT0dHk8noKWkpISwKqBwKlVS/roo8K1Ai%2B8UHr3XdtVIVK4/H5WHAJgX1ZWlrZt21bw%2BLXXXtOYMWMUFVX479Tc3FxFRUUpJSVFG0u4MSo7O1vZ2dkFj30%2Bn1JSUpSZmSm32x2w%2BoFA2bdPuvxyMzEkNlaaOVO64grbVSHcEQABhKTff/9dW7duLfZcly5d1K9fPw0aNEiNGzc%2Brp/j8/nk8XgIgAhrBw9K/ftLs2ebpWKmTZMGDbJdFcJZjO0CAOBIqlSpoipVqhR7LjY2VjVq1Dju8AdEirg40/PndktTp0rXXSft2SPddJPtyhCuuAcQAIAwEB0tPfusdMst5vE//yk98ojdmhC%2B6AEEEDZKuu8PcAqXS3r8calCBbNv8OjR0v790tix5jXgeNEDCABAGHG5pAcekNLTzeP775fGjJG4ox%2BlQQAEACAMjR4tPfGEOU9Pl%2B64gxCI40cABAAgTI0cKU2aZM7/8x/p1lsJgTg%2BBEAAAMLY8OHS5Mnm/IknpFGjCIE4NgIgAABh7sYbzQxhSZowgZ5AHBsBEACACHDDDYUh8IknpDvvJASiZARAAAAixA03FA4HP/YYs4NRMgIgAAAR5MYbpaeeMufp6WbJGOCvCIAAAESYESOk8ePN%2Bbhx0qOPWi0HIYgACCAieb1epaamKi0tzXYpgBW33CI99JA5v/POwuViAEly%2Bf3cHQAgcvl8Pnk8HmVmZsrtdtsuBwi6%2B%2B4z28ZJ0vPPS4MG2a0HoYEeQAAAItj995veQEkaPFh6/XW79SA0EAABAIhgLpf0%2BOMm/OXlSVdfLb33nu2qYBsBEACACOdySc88I/XpI%2BXkSD17Sh9/bLsq2EQABADAAaKjpenTpW7dpP37pUsukb75xnZVsIUACACAQ8TFmXsA27SRdu%2BWunSRfv7ZdlWwgQAIAICDlC8vvf221Ly5lJEhde4sbd9uuyoEGwEQAACHqVhRevddqV49af166e9/l7KybFeFYCIAAgDgQMnJ0sKFUtWq0pdfSr17SwcP2q4KwUIABADAoRo2lBYskBITpUWLpOuvl9gewhkIgAAAOFhampkYEhMjzZgh3X237YoQDARAAAAcrmtXaepUc/7ww9LkyXbrQeARAAEAgAYOlB54wJyPGCHNn2%2B1HAQYARAAAEiS7rnH3AeYlyf17WsmhyAyEQABAIAks2Xc5MlmbcB9%2B8xuIZs22a4KgUAABBCRvF6vUlNTlZaWZrsUIKzExkqvvVa4UPQll0g%2Bn%2B2qUNZcfj8TvgFELp/PJ4/Ho8zMTLndbtvlAGHjl1%2BkVq2krVvNlnFvv21mCiMy0AMIAAAOk5JiJoKULy%2B99540cqTtilCWCIAAAOCIzj7brA3ocklerzRpku2KUFYIgAAAoEQ9e5q1ASXp5ptNbyDCHwEQAAAc1e23m3UC8/KkK6%2BU1qyxXRFOFgEQAAAclcslPfOM1KaNmRHcvbv0xx%2B2q8LJIAACAIBjio%2BX3nhDqltXWr9e6tNHOnTIdlU4UQRAAABwXKpVk956y8wMXrTIDA0jPBEAAQDAcWvRQpo%2B3ZxPmCC99JLdenBiCIAAAKBUeveW7rvPnA8dKn3%2Bud16UHoEQAAAUGpjx0o9ekjZ2VKvXtK2bbYrQmkQAAEAQKlFRUkvvyw1aSJt2SJdcYWUk2O7KhwvAiAAADghbrc0d645Llsm3Xqr7YpwvAiAAADghDVubHoCJempp8zWcQh9BEAAAHBSevSQ7r3XnN9wg/T113brwbERAAFEJK/Xq9TUVKWlpdkuBXCEsWOlrl2l/fvNpBB2CgltLr/f77ddBAAEis/nk8fjUWZmptxut%2B1ygIi2a5d09tnSxo1mu7i5c81kEYQe/rMAAIAyUbmy9PrrZtu4%2BfOlRx%2B1XRFKQgAEAABl5uyzzWQQSRozRlqyxGo5KAEBEAAAlKnBg6UBA6S8PKlvXykjw3ZF%2BCsCIAAAKFMul/T009Lpp5sdQq66SsrNtV0ViiIAAgCAMle%2BvLkfsEIFMww8bpztilAUARAAAARE48bSlCnm/N//lhYtslsPChEAAQBAwFx1lVkc2u%2BXrr1W2rrVdkWQCIAAACDAJkyQmjeXtm83IZD7Ae0jAAIAgIBKSJBefdXcF/jhh1J6uu2KQAAEENJ%2B%2BOEH9ejRQx6PR0lJSWrdurU2b95suywApdSkiZkZLJlt45Yvt1uP0xEAAYSsn376SW3btlWTJk20ZMkSff3117r33ntVrlw526UBOAH9%2B5sh4Lw86eqr2S/YJvYCBhCy%2Bvbtq9jYWL388ssn/DPYCxgILVlZUsuW0vr1Uu/e0muvmXUDEVz0AAIISXl5eVqwYIEaNWqkLl26qFq1amrVqpXmzp171Ouys7Pl8/mKNQChIylJeuUVKTZWmjNHmjbNdkXORAAEEJK2b9%2BuPXv26OGHH1bXrl21cOFC9ezZU7169dLSpUtLvC49PV0ej6egpaSkBLFqAMfjb38z6wJK0s03S2vW2K3HiRgCBhASZs6cqaFDhxY8XrBggTp27KirrrpKs2bNKni%2BR48eSkxM1CuvvHLEn5Odna3s7OyCxz6fTykpKQwBAyEmL0/q0kV6/33prLOkFSukuDjbVTlHjO0CAEAywa5Vq1YFj6tWraqYmBilpqYWe1/Tpk21/CjTB%2BPj4xUfHx%2BwOgGUjago6aWXpDPOkFatku65R3r0UdtVOQcBEEBISEpKUlJSUrHn0tLS9OOPPxZ7bu3atapbt24wSwMQIMnJ5h7Anj2l//xH6tZNOv9821U5A/cAAghZt99%2Bu2bPnq2pU6dq/fr1mjRpkubPn69hw4bZLg1AGbnsMmnIELNVXP/%2BLA0TLNwDCCCkPf/880pPT9evv/6qxo0b6/7779ell1563NezDAwQ%2BvbuNfcBrlsn9e1rZgkjsAiAACIaARAID59/Lp13ntkneNYs6aqrbFcU2RgCBgAA1p1zjnTvveZ82DDp11/t1hPpCIAAACAk3H23CYK7d0uDBpmlYhAYBEAAABASYmOl6dOlhASzPuDTT9uuKHIRAAEAQMho3LhwPcA77jATQ1D2CIAAACCkDBsmdeok7d8vDRhgJoagbBEAAQBASImKkp5/XnK7pU8/lR5/3HZFkYcACAAAQk6dOtKECeb83nul77%2B3W0%2BkIQACAICQNHCgdPHF0sGDZij40CHbFUUOAiAAAAhJLpc0ZYpUsaL0xRfSY4/ZrihyEAABRCSv16vU1FSlpaXZLgXASUhOlp580pyPGyd9953VciIGW8EBiGhsBQeEP79f6t5dWrBASkuTPvlEiomxXVV4owcQAACEtPyhYI9HWrlSeuIJ2xWFPwIgAAAIecnJ0vjx5vy%2B%2B6S1a%2B3WE%2B4IgAAAICwMGiR17iwdOCBdfz17BZ8MAiAAAAgLLpf07LNSYqK0fLn0zDO2KwpfBEAAABA26tWTHn7YnN95p7R5s9VywhYBEAAAhJVhw6TzzpP27JH%2B8Q8zSxilQwAEAABhJSpKmjZNiouT3nlHmj3bdkXhhwAIAADCTtOm0pgx5vyf/5R27bJbT7ghAAIAgLA0erSUmirt2CHddpvtasILARAAAISluDgzFOxySS%2B8IC1ebLui8EEABAAAYevcc6UbbzTnQ4eaNQJxbARAAAAQ1tLTpZo1pXXrpIcesl1NeCAAAgCAsObxSBMnmvOHH5Y2bLBbTziIsV0AAASC1%2BuV1%2BtVbm6u7VIABEHv3lL//tIFF0j169uuJvS5/H6WTwQQuXw%2BnzwejzIzM%2BV2u22XAwAhgSFgAAAAhyEAAgAAOAwBEAAAwGEIgAAAAA5DAAQAAHAYAiAAAIDDEAABAAAchgAIAADgMARAAAAAhyEAAgAAOAwBEAAAwGEIgAAAAA5DAAQAAHAYAiAAAIDDEAABRCSv16vU1FSlpaXZLgUAQo7L7/f7bRcBAIHi8/nk8XiUmZkpt9ttuxwACAn0AAIAADgMARAAAMBhCIAAAAAOQwAEAABwGAIgAACAwxAAAQAAHIYACAAA4DAEQAAAAIchAAIAADgMARBAyNqzZ49GjBih2rVrKyEhQU2bNtXkyZNtlwUAYS/GdgEAUJJbbrlFixcv1owZM1SvXj0tXLhQw4YNU3Jysi699FLb5QFA2KIHEEDI%2BvTTTzVgwAB17NhR9erV0w033KAWLVroiy%2B%2BsF0aAIQ1AiCAkNW2bVvNmzdPW7Zskd/v1%2BLFi7V27Vp16dLFdmkAENYYAgYQsiZOnKghQ4aodu3aiomJUVRUlKZNm6a2bduWeE12drays7MLHvt8vmCUCgBhhR5AACFh5syZqlChQkFbtmyZJk6cqBUrVmjevHn68ssv9fjjj2vYsGF6//33S/w56enp8ng8BS0lJUWjR49WUlJSEH8bAAhtLr/f77ddBABkZWVp27ZtBY9r1aolj8ejN998UxdffHHB84MHD9avv/6qd99994g/5689gJIUHx%2Bv%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'}