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g2c_curves • Show schema
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{'Lhash': '639284731750073843', 'abs_disc': 448, 'analytic_rank': 0, 'analytic_rank_proved': True, 'analytic_sha': 1, 'aut_grp_id': '[4,2]', 'aut_grp_label': '4.2', 'aut_grp_tex': 'C_2^2', 'bad_lfactors': '[[2,[1,1]],[7,[1,-1,7,-7]]]', 'bad_primes': [2, 7], 'class': '448.a', 'cond': 448, 'disc_sign': -1, 'end_alg': 'Q x Q', 'eqn': '[[7,0,0,0,-2],[0,1,0,1]]', 'g2_inv': "['6080953884912/7','155007628668/7','-1306723104']", 'geom_aut_grp_id': '[4,2]', 'geom_aut_grp_label': '4.2', 'geom_aut_grp_tex': 'C_2^2', 'geom_end_alg': 'CM x Q', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['828','16635','5308452','56']", 'igusa_inv': "['828','17476','-853888','-253107460','448']", 'is_gl2_type': True, 'is_simple_base': False, 'is_simple_geom': False, 'label': '448.a.448.2', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.2164663601475456895859403663284466809402159513646999589', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.90.3', '3.2160.5'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 4, 'num_rat_wpts': 2, 'real_geom_end_alg': 'C x R', 'real_period': {'__RealLiteral__': 0, 'data': '31.171155861246579300375412751', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, 'root_number': 1, 'st_group': 'N(U(1)xSU(2))', 'st_label': '1.4.C.2.1a', 'st_label_components': [1, 4, 2, 2, 1, 0], 'tamagawa_product': 1, 'torsion_order': 12, 'torsion_subgroup': '[12]', 'two_selmer_rank': 1, 'two_torsion_field': ['4.0.1568.1', [2, 0, -1, 0, 1], [4, 3], False]}
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g2c_endomorphisms • Show schema
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{'factorsQQ_base': [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], 'factorsQQ_geom': [['1.1.1.1', [0, 1], -1], ['2.0.4.1', [1, 0, 1], -1]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['RR', 'CC'], 'fod_coeffs': [1, 0, 1], 'fod_label': '2.0.4.1', 'is_simple_base': False, 'is_simple_geom': False, 'label': '448.a.448.2', 'lattice': [[['1.1.1.1', [0, 1], [0, 0]], [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], ['RR', 'RR'], [2, -1], 'N(G_{1,3})'], [['2.0.4.1', [1, 0, 1], [0, 1]], [['1.1.1.1', [0, 1], -1], ['2.0.4.1', [1, 0, 1], -1]], ['RR', 'CC'], [8, -1], 'G_{1,3}']], 'ring_base': [2, -1], 'ring_geom': [8, -1], 'spl_facs_coeffs': [[[505], [-11341]], [[33], [-189]]], 'spl_facs_condnorms': [14, 32], 'spl_facs_labels': ['14.a4', '32.a2'], 'spl_fod_coeffs': [0, 1], 'spl_fod_gen': [0, 0], 'spl_fod_label': '1.1.1.1', 'st_group_base': 'N(G_{1,3})', 'st_group_geom': 'G_{1,3}'}
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g2c_ratpts • Show schema
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{'label': '448.a.448.2', 'mw_gens': [[[[-2, 1], [1, 1], [0, 1]], [[3, 1], [0, 1], [0, 1], [-1, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [12], 'num_rat_pts': 4, 'rat_pts': [[-2, 5, 1], [1, -1, 0], [1, 0, 0], [2, -5, 1]], 'rat_pts_v': True}
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g2c_galrep • Show schema
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id: 39
{'conductor': 448, 'lmfdb_label': '448.a.448.2', 'modell_image': '2.90.3', 'prime': 2}
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id: 40
{'conductor': 448, 'lmfdb_label': '448.a.448.2', 'modell_image': '3.2160.5', 'prime': 3}
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g2c_tamagawa • Show schema
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id: 96769
{'label': '448.a.448.2', 'p': 2, 'tamagawa_number': 1}
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id: 96770
{'cluster_label': 'c4c2_1~2_0', 'label': '448.a.448.2', 'p': 7, 'tamagawa_number': 1}
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g2c_plots • Show schema
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{'label': '448.a.448.2', 'plot': 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evXpJMqN/6enpGjRokAYPHixJysvLU2pqqp555hnddttt5XpdNoIGEM0YAcRRGT5c6txZ2rVLuvZaqaDAdkVAaatWrVJWVpa6d%2B9e/FhcXJzOPvts/fDDDxYrA4DwQQDEUaleXXr/fSkxUZozR/r7321XBJSWlZUlSUpNTS31eGpqavHHypKXl6fs7OxSDQCiFQEQR61lS2nsWNMfMcKcFQyEG5fLVeq%2B3%2B8/6LGSRo4cKbfbXdyaNGkS6hIBwBoCICrkmmuk/v0lv1/q21favNl2RYCRlpYmSQeN9m3ZsuWgUcGShgwZIp/PV9zWrVsX0joBwCYCICrs5ZelE04w4e/aa80%2BgYBtLVq0UFpamr766qvix/bv369Zs2bpjDPOOOTz4uLilJSUVKoBQLQiAKLCateWPvjA3H79NdcDours3r1bixcv1uLFiyWZhR%2BLFy/W2rVr5XK5NGjQID311FOaMmWKlixZon79%2Bql27drq27ev5coBIDywDQyO2fjx0vXXmz0Cp02TLrzQdkWIdt9%2B%2B63OPffcgx6/8cYbNW7cOPn9fg0fPlxjx47Vzp07ddppp8nr9ap9%2B/blfg%2B2gQEQzQiAqBS3324WhtSrJy1cyP6AiHwEQADRjClgVIqXXpI6dpS2b5euvFLat892RQAA4FAIgKgUNWua4%2BGSk6X586W777ZdEQAAOBQCICpN8%2BbSxInmWsA33zQNAACEHwIgKtWFF5rNoSVpwADpxx/t1gMAAA5GAESlGzJEuvxyKT9fuuIKacMG2xUBAICSCICodC6X9M9/Su3bS5s2mTDIohAAAMIHARAhkZAgTZ1qFoX89FPw2DgAAGAfARAh06qVOSkkNlaaMEF65hnbFQFH5vV6lZGRIY/HY7sUAAgZNoJGyL32mnTnnaY/ebL0t7/ZrQcoDzaCBhDNGAFEyN1xh3TXXaZ/7bXSggV26wEAwOkIgKgSL75otojZu1e69FJp3TrbFQEA4FwEQFSJatWk//wnuDL44osln892VQAAOBMBEFUmKUn6/HMpLU1assScGbx/v%2B2qAABwHgIgqlTTpiYExsdLM2ZI3bpJRUW2qwIAwFkIgFVg3Tpp9mxp82b2wpOkU08108GSNG%2Be1LWr3XoAAHAaAmAV%2BOgj6eyzzdRncrJ0%2BulSv37SyJFmW5Q//pDy8mxXWbUuvli66SbTnzvXHBkHAACqRjXbBThBbKzUvLm0Zo20a5cZ9Zo3r/TnxMRILVpI7dpJbduWbqmp5ni1aPPOO2Z0dMYME4QHDpRefdV2VQAARD82gq5Ce/dKy5dLy5aZtnRpsJ%2BTc%2BjnJSUdHArbtJGOO06qXbvq6g%2BFoiLplFOkX3819//xD2noULs1ARIbQQOIbgTAMOD3S1lZpQNhoK1effhFEk2bBgNhyXDYtKkZVYwEBQVS69ZmhFSSvN7gySGALQRAANGMABjm8vKkFSsODobLlkk7dx76eTVrmlAVCISBgNimjVSvXtXVX167d0stW0pbt5r748ebU0MAWwiAAKIZATBC%2Bf3Stm1SZmYwEAb6K1ZI%2BfmHfm5yculgGGitW9udUt62TWrVSsrONtc8Tp0q9exprx44k9frldfrVWFhoTIzMwmAAKISATAKFRSY6dRAKAwEw8xMaf36wz%2B3SRNzbWHJYHjccWaBSvXqoa99/XoTTvfsMVPYX34pnX9%2B6N8XOBAjgACiGQHQYXJzg1PKgXAYaIebUo6NNSEwEAgDt8cdZ0JjbGzl1bh8uXTiiWb6OzZWmjVL6toqy3wgJcUkRCDECIAAohkBEMUCU8rLl5cOhitWmBG5Q6lRw0zdBgJhydaoUcUWoyxZInXsKCXt36rXXHfq8pipiiksMB/s3NnsF9O5c8W%2BUKAcCIAAohkBEEfk90sbNgSD4fLlwf7KlYc/z7dmTRMOW7cOtuOOM48daeRwwZy9ijurs9prycEfTEiQfvxRat/%2B2L9AoAwEQADRjACIY1JYKK1dGwyFJduqVeZ6xEOpVs2MDrrdUnq6WQXcvr3UqZN0xhlS/Y/flvr3P/QL9O0rTZhQ%2BV8UIAIggOhGAETIBBajrFhhAuGKFcG2atXhRw4l6TNdokv0xaE/oWZNs7s2EAIEQADRjKPgEDLVqpmp3latpAsvLP2xwkJznd9//yv98osJiBs2mIUogUwXp8MfkFyUt18fTPKrXn2XGjUym1/Hx4foiwEAIIoQAGFFbKx00kmmHcjvNyOEuQ%2BdJX309SFfY46/q/pcU/qQ5Hr1zLnLLVqUbi1bSs2aSXFxlfyFAAAQgZgCRvjatElq187sDF2GnvpYn6qn2rQxR%2Bkd4tOKuVxmVXLLlqWDYeB%2BWlrkHJ%2BH0GMKGEA0YwQQ4athQ%2Bnzz6Urr5Q2bw4%2BHhen7y99WtM/7inlSx06SL/9ZqaO16wxo4erV5sVyqtWBVturtloev16afbsg98uLu7gkcNAa95cqlvXhEgAACIdI4AIf/v3Sx99JP35p9kIuk8fqX59ffqpyYb795trDD/80OwOUxa/35wzvGqVCYaBcBi4XbfOXJd4OElJwenl5s0PbnXqVOYXDdsYAQQQzQiAiGhffin97W9mo%2BrOnaVPPzUZ8Wjl55sQGBgtXLkyOIq4enXpAchDcbvNdYaBQNisWelWvz4jiJGEAAggmhEAEfHmzpUuuUTascOsOJ42zWw2XZn27AlOL69aVXqqefVqc4rKkdSqZVYqN2tmbgP9Jk1Mv3FjFqmEEwIggGhGAERUWLZMuugiE8qSk6WpU6Wzzqq698/NNaFw9erSt4G2aVP5XictzQTCkq1x42BAbNjQbK%2BD0PF6vfJ6vSosLFRmZiYBEEBUIgAiamzeLF16qTR/vjmf%2BI03pBtvtF2VkZdnppjXrDEnpwTamjXm8bVrpX37jvw6MTEmJDZubFqjRqaV7Kensx9iZWAEEEA0IwAiquzZI91wg1kzIkkPPiiNHHn4M4fDgd9vppEDYXDdutJt/XqzUfbhjtYrKXC8XqNGZtQwPd20hg2D99PSpNq1Q/t1RTICIIBoRgBE1Ckqkh5/XHrySXP/oovMkcF169qt61gVFZlRzsBWNhs2BG9Lttzc8r9mUpIJgge21NTSLSXFedcnEgABRDMCIKLWpEnSzTeb/QFbt5amTJHat7ddVehlZwfD4MaNpm3aFOxnZZnb8kw5l5SUZMJggwYmEDZoULrVr1%2B61a4d2aueCYAAohkBEFFt0SKzTcyaNSaQvP222UbQ6fx%2BExQ3bTKBMNA2bw72t2wxt1u3mm1yjlbNmuZovpItOTnY6tYN3gZanTomaIZDcCQAAohmBEBEvW3bpGuukWbMMPcHDJBGjXLelGZF%2Bf3Srl0mEG7ebG63bj24bdsWvK1IYAyIiTEhsE4d09zu4K3bbT52YEtMNC3QT0g49hFIAiCAaEYAhCMUFprrAp96ytzv1En697/NOcCoXH6/tHu3CYLbt5u2Y0fp2507TT9wu2uX6eflVV4dMTEmCCYkmFAYHx%2B8n5AQvB8fX7oFHvP7s/W3v7k1Z45PqalJxR%2BvXZuteABEPgIgHOWLL6TrrzehIylJGjuWKeFwsnevCYOB5vMFb30%2BM21d8jYnx/Szs00/J8eEz8qRLcktySep9AhgXFwwDJYMkSWD5YEtMEoZaCVHMxMTTWAFgKpCAITjrFtnpoS//97c79dPeuUV80cYka%2BoyKyE3r07GAhL9nNzgx8vef/Alp2drT/%2BcKtBA5/27k3Snj3mtUMlMTE47V2nTulrI5OTg9dRBhbZBBbe1KgRupoARC8CIBypoEAaPtxMCRcVmang8eOlLl1sV4ZwceA1gH6/maI%2BMCgeGCIDwbJkC4TPwIhlyZHLY7leUjJhMbBdT8OGZhufwL6PgU3CGzc2RxECQAABEI42e7aZEl671kzBPfyw9MQTjKqg6haB7NtngmDJKe/ANZGBayQD104G2tat5rawsPzvU7%2B%2BOVKweXPTWrQw/%2BPTqpXp8zMPOAsBEI63a5c0cKAZAZSkDh2kceOkU06xWhYsC/dVwEVFJhgGVmcHtvApuedjYNPwPXsO/1oxMSYUtmkjtW0rtWsnZWSYVr9%2BlXw5AKoYARD4/z76SLr9drN6tVo1afBgaehQs58dnMPr9crr9aqwsFCZmZlhGwDLK7CNT%2BDs6dWrTVu1Svrf/6SVKw9/ekxqqtlAvUMH6eSTTTv%2BeKl69ar6CgCEAgEQKGHLFrNP4Icfmvvt2klvvCGddZbdulD1wn0EsLL4/WbkMDPTtGXLpD//lP74wwTFssTFSSedZLZT6txZOu00M3rISmYgchAAgTJ89JEJgps3m/v9%2B0tPP21WYcIZnBIAD2f3bhMEf/tN%2BuUX0xYvNtcsHqhuXbOIqmtX8z9MHg%2Bj50A4IwACh7Bzp/TQQ9Jbb5n79eubEHjTTYx0OAEBsGxFRWbqeMECaf586aefpJ9/Pvhs6bg4EwjPPVc67zwzSsi0MRA%2BCIDAEcyZY64N/P13c79zZ%2BnVV80tohcBsPzy883o4A8/mN%2BX2bODo%2BcBCQkmDP71r9JFF5mVxwDsIQAC5ZCfbzaLHj7c7OEmSTfcYPYRbNTIbm0IDQJgxfn95nrCmTNN%2B/prs21NSccfL/XoIV12mXT66VJsrJ1aAaciAAJHYdMms1fgv/5l7teuLT3wgGmcJBJdCICVp6jIXDv43/9K06aZkcKSeximpJggeOWVZpSQqWIg9AiAQAX89JN0773mD5lk/oA99ph0661sqBstCIChs2uXCYOffGLO5961K/ixevWkyy83xzV268bIIBAqBECggvx%2Bs1p4yBBpxQrzWPPm5iSR664zewkichEAq0Z%2BvvTtt%2BZ3afJkc8pJQKNGUt%2B%2B0o03SiecYK1EICoRAIFjlJ9vVgr//e9mPzVJOu44MyJ4zTUEwUhFAKx6BQXSrFnSpElmL86SI4Mej3TzzeZ3yu22VyMQLQiAQCXZs0fyeqVnngle8N6qlblm8PrrzbYYiBwEQLvy8qTPPzfX237%2BuQmHkrnutk8fszLf47FbIxDJCIBAJcvJMUFw1ChzrJwkpaebawZvvVUiS0QGAmD42LLFnNX99ttmY%2BoAj8ec4927N/%2BDBRwtAuAx8Pv9ygnsCQIcIDdXevdds2dgYGo4MdFcz3TbbVLTpnbrQ2l5eXnKy8srvp%2BTk6OMjAytW7eOABgm/H5p7lzpnXekKVPM5ReS1KCBOa2nf3%2BzYTtQXomJiXK5XLbLsIIAeAwCIwQAACDyOHmEnwB4DCoyApidna0mTZoc06iCx%2BPR/PnzK/TcY32%2Bzfc%2B1u%2BdzdolqVOnznrqqZ/k9ZpVjwFt2piL26%2B%2BWkpOrvz3jvTvW1X9vB44Arhp0yZ17txZf/zxhxpVcLfvSP1dO5bnV/W/cfn50tSp0ujRZq9BSXK5zJ6C999vNpwO1XtX5vP522Dn3zgnjwCyPvEYuFyuCv%2BiJiUlVfi5sbGxx/R/LMfyfJvvHVDR753t2qtVi9GVVybpyivNsXJer7nAPTPTLBR54gnpiivMWcPnnVf6vGEnf99s/rxK5g%2BEjfeP5O%2B7VLX/xt1yi/mfqFmzpB49vlNu7ln64APpgw/M79QTT0gnnhia967s5/O3oeKO5XvnRBxpH4EGDBhg7fk23/tY2a695PNPOEEaM0bauNEEwZNOMqseJ06U/vIXs5/go49Kf/5ZOe99LMLp%2B1bV732sIvl3LdJ%2B5lwu6ZxzpGee%2BVULF5rgJ5n9BTt0MCuHly0LzXtX5vNtvnck/7zi6DEFXMVYWVhx0fy98/uln382F7e//77k8wU/dvLJ5o9X795SixZH/9rR/H0LpfXr1xdPKzVu3Nh2OREjnH7eliwx%2B3N%2B8IG5HxNjRtiHDZPC7T9pOH3fIg3fu4qJHTZs2DDbRThNbGyszjnnHFVjh%2BCjFq3fO5fLnHrQo4c0aJAZsdi3T1q50owSzpghvfyy9NlnZo/BlJSjW%2B0Yrd%2B3UMrLy9Nzzz2nIUOGKD4%2B3nY5ESVcft5SUqSrrjJHy23cKC1dKi1aJL32mlml7/FINWtaLbGUcPm%2BRSK%2Bd0ePEUAgjG3fbqawJk0y1zcVFQU/1qaN1LOnCY1nnCFVr26vzmjEqEL0%2BfFHafBg6bvvzP0GDcwIYf/%2BnNgD5yEAAhFiyxaz2nHyZOmbb4J7oElmc%2BkLLpAuvNBcQ1iRqWKURgCMTn6/9Omn0kMPBa8J7NBBeuUV6eyz7dYGVCUCIBCBsrOl6dPNH7Lp04MnjgSJM75MAAAfoUlEQVS0bGlWEp9zjmkV3MXE0QiA0S0/X3r9dbNCeOdO89g110jPP29O7gGiHQEQiHCFhWYByX//K335pTkpobCw9Oe0aCGdeaaZKu7SRWrfXoqNtVNvpCAAOsP27dLQodLYsWZ0MDFRGjFCGjCA3xFENwIgEGVycqTZs6WZM82G04sWlb52UJLi46WOHc1F8J06SaeeKrVuXXrvQacjADrLwoXSnXdK8%2BaZ%2B506SW%2B%2BaVbhA9GIf%2B6r2LBhw9SuXTvFx8erbt26uuCCCzQv8C8OypSfn6/BgwfrxBNPVHx8vNLT03XDDTdo48aNtksLS4mJ0iWXmKmsn3%2BW/vnPT3TqqY%2BoVq3nJc1QfHyhcnNNSBw1ykx7tW0rud1S167mj%2BBrr5kL5XfssP3VIFLMnj1bl156qdLT0%2BVyuTR16lTbJR2VU0%2BVfvjB/Oy73eZ3p1Mn6ZFHzIr8UBk5cqQ8Ho8SExOVkpKiXr16aVl5Nix0uNdee00dOnQo3vy5S5cumjZtmu2yIgoBsIq1adNGo0eP1m%2B//aY5c%2BaoefPm6t69u7Zu3Wq7tLC1Z88eLVy4UI899pgWLlyoyZMnKzMzUz179rRdWkTw%2B3267LKaeuWVOpL%2BolmzftOSJWbPwTvukE47zWyFsXt38A/gnXdK3bpJ9epJqanmOsLbb5deeMFcd7h0aWj/KCLy5Obm6qSTTtLo0aNtl1JhMTHm5/zPP81RcoWF0siR0imnBEcGK9usWbM0YMAAzZ07V1999ZUKCgrUvXt35ebmhuYNo0Tjxo319NNP6%2Beff9bPP/%2Bs8847T5dddpl%2B//1326VFDKaALQtMM82YMUPnn3%2B%2B7XIixvz589W5c2etWbNGTZs2tV1ORFi9erVatGihRYsW6eQD5rUKCsyKyF9%2BMW3JEtPWrj306wX2LmzZ0pxc0ry51LSpaU2amI12ExJC%2BiWFFFPAFedyuTRlyhT16tXLdinHZOpU8z9JWVkmHA4ebBaNxMWF7j23bt2qlJQUzZo1S926dQvdG0Wh5ORkPffcc7rllltslxIR2PnIov379%2BuNN96Q2%2B3WSSedZLuciOLz%2BeRyuVSnTh3bpUSFatXM8XQnnCD17Rt8fPduM9r3558mIGZmSsuXSytWmI%2BtX2/a7Nllv25SkgmJDRualpZmWmqq2aS3QQNzW6%2BeVKtW1XytR%2BL1euX1elV44EoaOE6vXmYk/O67pQkTzGjgF19I48ebhVSh4Pv/xwAlJyeH5g2iUGFhoT744APl5uaqS5cutsuJGIwAWvDZZ5%2BpT58%2B2rNnjxo2bKipU6fK4/HYLiti7Nu3T2eeeabatWun8ePH2y4nYhxuBPBo%2Bf3S1q3mpJJVq6TVq01bu9a0devMYpSjER9vgmBysrmtW9f069Qxfbfb9JOSTN/tNv2kJHPdY2Vv5MsIYMVFywhgSZMnS7fdZrZciouTnn1WGjjQjIRXFr/fr8suu0w7d%2B7Ud4HdqnFIv/32m7p06aJ9%2B/YpISFBEydO1MUXX2y7rIjBCGAITZgwQbfddlvx/WnTpumss87Sueeeq8WLF2vbtm1688031bt3b82bN08pKSkWqw0fh/q%2BSWZBSJ8%2BfVRUVKQxY8bYKjFsHe57V5lcLjNyl5IinX562Z%2BTnW2O39qwQdq0ybSsLGnzZtO2bDFt2zYzBZ2ba9rhpp0Pp2ZNEwYTEkwgTEgo3eLjg%2B3A%2B2W1goKKf38QfS6/3CySuvlmMwp4zz1m66Vx48xIdmW466679Ouvv2rOnDmV84JRrm3btlq8eLF27dqljz76SDfeeKNmzZqljIwM26VFBEYAQygnJ0ebN28uvt%2BoUSPVKmOe67jjjtPNN9%2BsIUOGVGV5YetQ37f8/Hz17t1bK1eu1DfffKN69epZrDI8He5nrjJHACuT3y/5fCYIbt9uVh4H2s6d0q5dwVufL9iys03LywtVZdmS3IqN9SkhIanM8Hhgv2QLhNDExNL9pCTz%2BZU5chRuonEEMMDvl8aMke6/3/zsNWwoTZxoFkodi4EDB2rq1KmaPXu2WnCUT4VccMEFatWqlcaOHWu7lIjACGAIJSYmKjEx8Yif5/f7lRe6v2IRp6zvWyD8LV%2B%2BXDNnziT8HUJ5f%2BbCictlpnbr1DF7ER6t/ftNENy920w75%2BSYfuD%2B7t1mZDHw2J49wcfKaoGPBy4BLCwMhs7K/JoDYTDQAtPaJVudOua2bt3g96huXdNq1YruEBmuXC6zSXS3btLVV5vrY88/Xxo%2B3GwZc7R7afr9fg0cOFBTpkzRt99%2BS/g7BvwtPToEwCqUm5urJ598Uj179lTDhg21fft2jRkzRuvXr9dVV11lu7ywVVBQoCuvvFILFy7UZ599psLCQmVlZUkyF0rXqFHDcoXhbceOHVq7dm3xvomBPcbS0tKUlpZms7RKUaOGVL%2B%2BaZVp2zYztffHH%2BaPeiAgHhgeA8GyZL9k%2BAyE0kDz%2B00LjGBWVI0a5hrJwLWSgVav3sEt8P2pV888LxR2796tFStWFN9ftWqVFi9erOTk5KhcqX/iidL8%2BdJdd5lp4MceM9sojR9v/juU14ABAzRx4kR9/PHHSkxMLP63ze12lzljBOORRx7RRRddpCZNmignJ0eTJk3St99%2Bq%2BnTp9suLWIwBVyF9u3bp759%2B2revHnatm2b6tWrJ4/Ho6FDh7II5DACU5dlmTlzps451rmXKDdu3DjddNNNBz3%2BxBNPaNiwYVVfUIQIxSIQv9%2BMMGZnmzAYCIGBKe2SU9w%2Bn5n2LtkCU%2BHHskDZ7TZhsEGD4CrskrepqcFV2vXrl39xzbfffqtzzz33oMdvvPFGjRs3ruIFR4B33zV7Z%2B7bZ7ZDmjzZ7B1YHq5DDOO%2B%2B%2B676tevX6XVGG1uueUWff3119q0aZPcbrc6dOigwYMH6y9/%2BYvt0iIGARAAyhCuq4D9fhMed%2B0qfb1kyRa4njLQtm0zjx94JOCRuFwmBKamBrfwCWzjE9jWJ7DFT506zp6S/uUXs1Bk5UqzIOmtt6Rrr7VdFXBoBEAAKEO4BsCKKioyI4jbtpktfAItsBo70A%2Bs0N6%2B/egCY82aJhCmp5fdGjUyLcIuUT0qO3ea0Bc4kezBB83egbGxdusCykIABIAyRFsAPFqFhSYslty6JyvLbOezeXNwW59Nm8xoZHklJppTYgKBsHHj0q1JE3MNXaSOJhYWSo8/Lj31lLl/8cXS%2B%2B%2BbhT5AOCEAAkAZnB4Aj8bevSYMbtxoAuHGjaXbhg2mlXdz8Jo1TRA8sJU8ajDcRxL//W%2BpXz9zXWD79tJnn0nNmtmuCggiAAJAGQiAlS8nJxgGN2wwxwhu2GBOjgkcK7h1a/leq06dYCBs1qx0v1kzMx19tFuyVLb586XLLjOhODXVhMBOnezWBAQQAAGgDARAO/btKx0K160LHi8YuC3PlHONGmaksHnzYChs3jx4v3Hjqrk2b906qUcP6ddfpdq1pf/8R7rkktC/L3AkBEAAKMHr9crr9aqwsFCZmZkEwDCUkxM8d3rtWmnNmtK369cfeQFLtWrBgNi8udSiRenb9PTKG0HMzpauukr68ksTOt96y0wPAzYRAAGgDIwARq6CAhMC16wxbfXq0rdr10r5%2BYd/jRo1zJRyy5YmFJZsLVse/UKV/Hypf3/pX/8y90eNku67r6JfIXDsCIAAUAYCYPQqLDTX5a1eLa1aZW5L9teuPfJm24mJwXDYsmXpfvPmZiHLgfx%2BafBg6bnnzP0nnzTHx2nmTOmf/zQXQB5/vHTrrVKbNpX5JQMHIQACQBkIgM4VGEFcvdps7LxqVem2adORXyM9vfSoYWCquWlTc3LIU09JLhXp%2B9b91GXFe6WfHBsrvf66GTIEQoQACABlIADiUPbuDY4YrlwZbIGAWN7tbu7QGI3RgLI/GBMj/fablJFRaXUDJREAAaAMBEBUhN9vTlEpGQgDYXHNGjOymJtrPneJTtAJ%2BuOQr/Vl24Fa2O8VeTzSaadJCQlV8zXAGQiAAFAGAiBCwe%2BXfD5p25YitW57%2BH1ovtG5Ol/fFN%2BPjTUniqSmmunkiy%2BWunWTWrUiHOLoVbNdAAAATuFymU2s69SJkerWNQcIH0JOXH3V8Ev795v7hYXm03fulJYulaZPD35uWprUunWwHXecaa1bh/%2BpKbCDEUAAKAMjgAi5e%2B6RXnnl0B//5BPp0ktVVGQ2kv7xR2nRIhP%2B1q2T3G4zpbx9%2B%2BHfJjW1dCBs0ybYj4%2Bv3C8JkYMACABlIAAi5DZvlrp0MRcIHmCqLtP2Nybrlv878m7Uu3ZJK1aYtnx56dsjHa2Xnm7CYCAUBm5btZLi4ir6hSESEAABoAwEQFSJrCzpH/%2BQ3ntPyslRYZNm%2Bse2OzRi7/0qclXThAnSNddU/OV9PhMGA23FCikz0/R37Dj082JizJF5gVBYsjVtWjXH6CG0CIAAUAYCIKpUUZE5CLl2bWVlmaCVk2OuGZwyRbrsssp/yx07TBAMBMKS/cNtZVOjRnAquWRr21Zq0ODoTkiBPQRAACgDARA2rV9vAtWePWY07ssvpfPPr5r39vvN7HRmZjAQBvorVgQXpZTF7Q6GwZLB8LjjuN4w3BAAAaAEr9crr9erwsJCZWZmEgBhzf/%2BJ7VvbwYGY2PNIhCPx25NhYXmqLxAIAy0ZcvM44dLFI0bmzAYCIeBPlPKdhAAAaAMjAAiHPz6q9Spk5Sfb6Zef/3VhKZwtG%2BfGSFctqx0MFy27PDXG8bFBa81bNeudDisW7fq6ncaAiAAlIEAiHDx/ffS2Web0bfatc2UbHq67aqOzvbtwWAYCIWB6eXDTSmnpATDYMnWsqVUjZ2MjwkBEADKQABEOPniC6lHDzPFmpxsdo6Jhh/LwkJzRF4gFJZsGzce%2BnnVq5utatq2NaOGJW%2BTk6uu/khGAASAMhAAEW7%2B%2BU%2BpXz/Tb9rUXCMYzaNgOTmlRwyXLg2OHO7de%2BjnDRkiPfVU1dUZqaL4RwcAgOhx441mVOyRR8yCi86dpYULbVcVOomJUseOppVUVGRWSZcMhYHb9evN/oU4MkYAAaAMjAAiXA0YII0ZY/qjRkn33We3nnCye7e5TUiwW0ckOPIZMwAAIGx4vdLdd5v%2BAw9IH35ot55wkpBA%2BCsvAiAAABHmpZeku%2B4yi0Kuu87sEQgcDQIgAAARxuUyIbBnTykvz9yuXGm7KkQSAiAAABEoNlaaOFE69VRp2zbpkkukXbtsV4VIQQAEACBCxcdLn35qjllbulTq3ducGgIcCQEQAIAIlp5uQmB8vPTVV9K999quCJGAAAgAQIQ7%2BWRp/HhzbaDXK73%2Buu2KEO4IgABQgtfrVUZGhjwej%2B1SgKPSq5c0YoTpDxwozZpltx6ENzaCBoAysBE0IpHfL/XtK02aJNWvLy1YYI6NAw7ECCAAAFHC5ZLefls65RSzMrhXr8OfmwvnIgACABBFateWpk41I4CLFkm33WZGBoGSCIAAAESZpk2l//zH7BX43ntmYQhQEgEQAIAodO650rPPmv6990o//GC3HoQXAiAAAFHq3nvN5tAFBdJVV0lbttiuCOGCAAgAQJQKLAo5/nhp40bpmmukwkLbVSEcEAABRJTJkyfrwgsvVP369eVyubR48eKDPicvL08DBw5U/fr1FR8fr549e2r9%2BvUWqgXsS0iQPvzQnBTyzTfS8OG2K0I4IAACiCi5ubnq2rWrnn766UN%2BzqBBgzRlyhRNmjRJc%2BbM0e7du9WjRw8VMvQBh8rIkN54w/RHjJC%2B/NJuPbCPjaABRKTVq1erRYsWWrRokU4%2B%2BeTix30%2Bnxo0aKD33ntPV199tSRp48aNatKkib744gtdeOGF5Xp9NoJGNLr9dmnsWKlBA2nxYnOOMJyJEUAAUWXBggXKz89X9%2B7dix9LT09X%2B/bt9QPLIOFwL70knXSStHWrdO21XA/oZARAAFElKytLNWrUUN26dUs9npqaqqysrEM%2BLy8vT9nZ2aUaEG1q1pT%2B/W9zPeC330pPPmm7IthCAAQQtiZMmKCEhITi9t1331X4tfx%2Bv1wu1yE/PnLkSLnd7uLWpEmTCr8XEM7atpVee830hw%2BXjuHXChGMAAggbPXs2VOLFy8ubp06dTric9LS0rR//37t3Lmz1ONbtmxRamrqIZ83ZMgQ%2BXy%2B4rZu3bpjrh8IV9dfL91wg1RUZKaCD/h1gQMQAAGErcTERLVu3bq41apV64jP6dixo6pXr66vvvqq%2BLFNmzZpyZIlOuOMMw75vLi4OCUlJZVqQDQbPVpq3Vpat47zgp2omu0CAOBo7NixQ2vXrtXGjRslScuWLZNkRv7S0tLkdrt1yy236P7771e9evWUnJysBx54QCeeeKIuuOACm6UDYSUxUZo4UTrjDOmDD6SLLpJuusl2VagqjAACiCiffPKJTjnlFF1yySWSpD59%2BuiUU07R66%2B/Xvw5L774onr16qXevXura9euql27tj799FPFxsbaKhsISx6P9I9/mP7AgdL//me3HlQd9gEEgDKwDyCcorBQOu88afZsqUsXc1uN%2BcGoxwggAAAOFhsr/etfUlKS9OOP0mEO2UEUIQACAOBwzZpJXq/pDx8uLVhgtx6EHgEQAADo2mulK6%2BUCgrMNjH79tmuCKFEAAQAAHK5zAbRqanSn39KQ4fargihRAAEAACSpPr1pTffNP0XXpDmzLFbD0KHAAgAAIpdeqnUr5/ZGPqmm6Q9e2xXhFAgAAIAgFJeeklq1EhasUJ65BHb1SAUCIAAUILX61VGRoY8Ho/tUgBr3G7prbdM/5VXpO%2B/t1sPKh8bQQNAGdgIGpBuvll6912pTRtp8WKpHMdxI0IwAggAAMr0wgtSw4ZSZqY0bJjtalCZCIAAAKBMdepIgWO2n3%2BeDaKjCQEQAAAcUs%2BeUp8%2BUlGRdMstUn6%2B7YpQGQiAAADgsF5%2BWUpOln75RRo1ynY1qAwEQAAAcFgpKdKLL5r%2B8OFmexhENgIgAAA4ouuvly64wJwRfPvtZqNoRC4CIAAAOCKXyywIqVlT%2Bvprafx42xXhWBAAAQBAubRqJT3%2BuOnfd5%2B0fbvdelBxBEAAAFBu998vnXCCtG2bNHiw7WpQUQRAAABQbjVqBPcGfPttjomLVARAAABwVM480%2BwJKEl33MHegJGIAAgAAI7a00%2BbvQF/%2B0169VXb1eBoEQABoASv16uMjAx5PB7bpQBhrX596ZlnTP%2BJJ6SNG%2B3Wg6Pj8vvZyQcADpSdnS232y2fz6ekpCTb5QBhqahI6tpVmjtXuuYaaeJE2xWhvBgBBAAAFRITI3m9Zo/A99%2BXZs2yXRHKiwAIAAAq7NRTzckgknTXXVJBgd16UD4EQAAAcExGjJDq1ZOWLJHGjLFdDcqDAAgAAI5JcrL05JOm//jj0tatduvBkREAAQDAMevfXzrlFMnnk4YOtV0NjoQACAAAjllsrPTKK6b/5pvSokV268HhEQABAEClOPNMqU8fye%2BXBg0ytwhPBEAAAFBpnnlGqlVLmj1b%2Bugj29XgUAiAAACg0jRtKj34oOk/%2BKC0b5/delA2AiAAAKhUDz0kNWokrV4tvfyy7WpQFgIgAACoVPHx0siRpv/kk9KWLXbrwcEIgABQgtfrVUZGhjwej%2B1SgIh27bVSx45STo70xBO2q8GBXH4/a3QA4EDZ2dlyu93y%2BXxKSkqyXQ4QkWbPls4%2B25wZ/NtvUkaG7YoQwAggAAAIiW7dpF69pKIic10gwgcBEAAAhMwzz0jVqkmffy59843tahBAAAQAACHTpo10%2B%2B2m/9BDZjQQ9hEAAQBASD32mJSYKC1YIE2aZLsaSARAAAAQYikp0uDBpj90qJSXZ7ceEAABAEAVGDRIathQWrVKev1129WAAAgAAEIuPl4aNsz0R4yQsrOtluN4BEAAAFAlbr5ZattW2rZNev5529U4GwEQAABUiWrVzNFwkvTCCxwRZxMBEAAAVJnLL5c8Hik3NxgGUfUIgAAAoMq4XNJTT5n%2B669La9bYrcepCIAAUILX61VGRoY8Ho/tUoCodcEF0nnnSfv3S8OH267GmVx%2Bv99vuwgACDfZ2dlyu93y%2BXxKSkqyXQ4QdebNk04/XYqJkX7/XWrXznZFzsIIIAAAqHKnnSb17GmOhnviCdvVOA8BEAAAWPGPf5jb//xH%2BuUXu7U4DQEQAABY0aGDdPXVps8oYNUiAAIAAGuGDTPXAX78sfTzz7arcQ4CIAAAsKZdO%2Bm660z/8cft1uIkBEAAAGDVY49JsbHStGnS3Lm2q3EGAiAAALCqdWvphhtMn2sBqwYBEEBEyc/P1%2BDBg3XiiScqPj5e6enpuuGGG7Rx48ZSn7dz505df/31crvdcrvduv7667Vr1y5LVQM4kqFDzVnBX34p/fij7WqiHwEQQETZs2ePFi5cqMcee0wLFy7U5MmTlZmZqZ49e5b6vL59%2B2rx4sWaPn26pk%2BfrsWLF%2Bv666%2B3VDWAI2nZUrrxRtMfNsxqKY7ASSAAIt78%2BfPVuXNnrVmzRk2bNtWff/6pjIwMzZ07V6eddpokae7cuerSpYuWLl2qtm3bHvE1OQkEqHqrVklt2kgFBdIPP0hdutiuKHoxAggg4vl8PrlcLtWpU0eS9OOPP8rtdheHP0k6/fTT5Xa79cMPP5T5Gnl5ecrOzi7VAFStFi2C1wL%2B/e92a4l2BEAAEW3fvn16%2BOGH1bdv3%2BKRuqysLKWkpBz0uSkpKcrKyirzdUaOHFl8vaDb7VaTJk1CWjeAsj36qFkRPH269NNPtquJXgRAAGFtwoQJSkhIKG7fffdd8cfy8/PVp08fFRUVacyYMaWe53K5Dnotv99f5uOSNGTIEPl8vuK2bt26yv1CAJRLy5bBfQEDR8Wh8lWzXQAAHE7Pnj1LTeU2atRIkgl/vXv31qpVq/TNN9%2BUuk4vLS1NmzdvPui1tm7dqtTU1DLfJy4uTnFxcZVcPYCKeOQR6b33pM8%2BkxYtkk45xXZF0YcRQABhLTExUa1bty5utWrVKg5/y5cv14wZM1SvXr1Sz%2BnSpYt8Pp9%2BKjF/NG/ePPl8Pp1xxhlV/SUAOEpt2kh9%2Bpj%2BiBF2a4lWrAIGEFEKCgp0xRVXaOHChfrss89KjeglJyerRo0akqSLLrpIGzdu1NixYyVJt956q5o1a6ZPP/20XO/DKmDArt9/l9q3N/0lS6QTTrBbT7QhAAKIKKtXr1aLFi3K/NjMmTN1zjnnSJJ27Nihu%2B%2B%2BW5988okkM5U8evTo4pXCR0IABOy74gpp8mTp2mul8eNtVxNdCIAAUAYCIGDfwoVSx45STIyUmSm1amW7oujBNYAAACAsnXqq9Ne/SkVF0rPP2q4muhAAAQBA2Hr0UXM7bpy0YYPVUqIKARAAAIStM880bf9%2B6cUXbVcTPQiAAAAgrD3yiLl9/XVpxw67tUQLAiAAAAhrf/2rdNJJUm6uNHq07WqiAwEQAACENZdLGjzY9F95xQRBHBsCIAAACHtXXWXOCd6%2BXXrnHdvVRD4CIACU4PV6lZGRIY/HY7sUACVUqyY98IDpjxolFRTYrSfSsRE0AJSBjaCB8LN3r9SsmbR1qzRhgtS3r%2B2KIhcjgAAAICLUqiXdfbfpP/usxBBWxREAAQBAxLjzTql2bemXX6QZM2xXE7kIgAAAIGIkJ0v9%2B5v%2Bc8/ZrSWSEQABAEBEufdeKSZG%2BuorMxKIo0cABAAAEaV5c7MtjCQ9/7zVUiIWARAAAEScwJYwkyZJ69fbrSUSEQABAEDE6dRJ6tbN7Af46qu2q4k8BEAAABCR7r/f3I4dK%2B3ebbeWSEMABAAAEalHD%2Bm44ySfj%2BPhjhYBEAAARKSYGLMiWJJeflkqLLRbTyQhAAIAgIh1441mb8CVK6VPPrFdTeQgAAJACV6vVxkZGfJ4PLZLAVAOtWtLt91m%2Bi%2B%2BaLeWSOLy%2BzlJDwAOlJ2dLbfbLZ/Pp6SkJNvlADiMDRvM3oAFBdKCBdKpp9quKPwxAggAACJao0ZS796m/9JLdmuJFARAAAAQ8QYNMreTJklZWXZriQTVbBcAAABwrDweqWtXqU4dKTtbSkuzXVF4IwACAICo8PXXUlyc7SoiA1PAAAAgKhD%2Byo8ACAAA4DAEQAAAAIchAAIAADgMARAAAMBhCIAAAAAOQwAEAABwGAIgAJTg9XqVkZEhj8djuxQACBmX3%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'}