-
g2c_curves • Show schema
{'Lhash': '934349038178523264', 'abs_disc': 12427, 'analytic_rank': 0, 'analytic_rank_proved': False, 'analytic_sha': 1, 'aut_grp_id': '[2,1]', 'aut_grp_label': '2.1', 'aut_grp_tex': 'C_2', 'bad_lfactors': '[[17,[1,-2,14,17]],[43,[1,-3,39,43]]]', 'bad_primes': [17, 43], 'class': '731.a', 'cond': 731, 'disc_sign': -1, 'end_alg': 'Q', 'eqn': '[[-3,-1,0,0,2,1],[0,0,1,1]]', 'g2_inv': "['-796262400000/12427','-82861056000/12427','-9634464000/12427']", 'geom_aut_grp_id': '[2,1]', 'geom_aut_grp_label': '2.1', 'geom_aut_grp_tex': 'C_2', 'geom_end_alg': 'Q', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': False, 'igusa_clebsch_inv': "['480','-21564','-3373785','-49708']", 'igusa_inv': "['240','5994','167265','1053891','-12427']", 'is_gl2_type': False, 'is_simple_base': True, 'is_simple_geom': True, 'label': '731.a.12427.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.2985355886872414062863189873478987786819489163265650277', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.30.3'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_maximal_primes': [2, 5], 'non_solvable_places': [], 'num_rat_pts': 4, 'num_rat_wpts': 2, 'real_geom_end_alg': 'R', 'real_period': {'__RealLiteral__': 0, 'data': '14.926779434362070314315949367', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, 'root_number': 1, 'st_group': 'USp(4)', 'st_label': '1.4.A.1.1a', 'st_label_components': [1, 4, 0, 1, 1, 0], 'tamagawa_product': 2, 'torsion_order': 10, 'torsion_subgroup': '[10]', 'two_selmer_rank': 1, 'two_torsion_field': ['4.2.688.1', [-1, -2, 0, 0, 1], [4, 5], False]} -
g2c_endomorphisms • Show schema
{'factorsQQ_base': [['1.1.1.1', [0, 1], -1]], 'factorsQQ_geom': [['1.1.1.1', [0, 1], -1]], 'factorsRR_base': ['RR'], 'factorsRR_geom': ['RR'], 'fod_coeffs': [0, 1], 'fod_label': '1.1.1.1', 'is_simple_base': True, 'is_simple_geom': True, 'label': '731.a.12427.1', 'lattice': [[['1.1.1.1', [0, 1], [0]], [['1.1.1.1', [0, 1], -1]], ['RR'], [1, -1], 'USp(4)']], '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': 'USp(4)', 'st_group_geom': 'USp(4)'} -
g2c_ratpts • Show schema
{'label': '731.a.12427.1', 'mw_gens': [[[[7, 2], [4, 1], [1, 1]], [[-11, 2], [-4, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [10], 'num_rat_pts': 4, 'rat_pts': [[-3, 9, 1], [1, -1, 0], [1, -1, 1], [1, 0, 0]], 'rat_pts_v': True} -
g2c_galrep • Show schema
{'conductor': 731, 'lmfdb_label': '731.a.12427.1', 'modell_image': '2.30.3', 'prime': 2} - g2c_tamagawa • Show schema
-
g2c_plots • Show schema
{'label': '731.a.12427.1', 'plot': 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzt3Xt8zvX/x/HnNbblsF3OW2NFJ7WIYoS%2BUkIncwzJoRIl9PV1qKS%2BnZNUUl06ir5RQpZDOigSX1HRCinfyjHNobhmi8226/fH%2B2drNYwd3tfn%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%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%2B%2B1/p%2B%2B9tVwMg1L3wwgu64IILFB0drejoaLVo0ULvv/9%2B3v2ZmZkaNmyYatSooUqVKikpKUk7duywWDGA0kIAtCguTrr6anP86qt2awEQ%2BurUqaPHH39cX331lb766itdfvnl6tSpkzZs2CBJGj58uJKTkzVz5kytWLFC6enpuvbaa5WTk2O5cgAljUbQls2fL3XqJNWsKe3YIUVE2K4IgJtUq1ZNEyZMUPfu3VWzZk298cYb6tmzpyRp586dio%2BP16JFi9ShQ4civR6NoAFnYATQsquvlk49VdqzR5o3z3Y1ANwiJydHM2fOVEZGhlq0aKE1a9bo8OHDat%2B%2Bfd5j4uLi1KBBA61cufKor5OZmam0tLQCNwDBjwBoWfny%2BfsDcxkYQGlbt26dKleurMjISN12221KTk5WQkKCUlNTFRERoapVqxZ4fExMjFJTU4/6euPGjZPX6827xcfHl/Z/AoASQAAMAkd6Ai5eLG3ebLcWAKGtfv36SklJ0apVqzR48GD1799f33333VEfHwgE5PF4jnr/mDFj5Pf7827bt28vjbIBlDACYBA44wypXTuzLzCjgABKU0REhM466yw1bdpU48aNU6NGjTRp0iTFxsYqKytL%2B/btK/D43bt3KyYm5qivFxkZmbeq%2BMgNQPAjAAaJQYPM16lTpcOH7dYCwD0CgYAyMzPVpEkThYeHa/HixXn3/frrr1q/fr1atmxpsUIApaG87QJgJCVJtWpJv/4qLVwodeliuyIAoeaee%2B7RVVddpfj4eB04cEAzZ87Up59%2Bqg8%2B%2BEBer1cDBgzQyJEjVb16dVWrVk2jRo1Sw4YNdcUVV9guHUAJYwQwSERE5C8Geeklu7UACE27du1S3759Vb9%2BfbVt21arV6/WBx98oHbt2kmSJk6cqM6dO6tHjx5q1aqVKlasqAULFqhcuXKWKwdQ0ugDGER%2B%2BsnsD%2BzxmON69WxXBAAnhj6AgDMwAhhEzjwzfzHIK6/YrgYAAIQqAmCQufVW83XKFCkry24tAAAgNBEAg0xSktkZZPdu6d13bVcDAABCEQEwyISH5zeGfvFFu7UAAIDQRAAMQoMGSWFh0tKl0vff264GAACEGgJgEIqPl6691hwzCggAAEoaATBIDR5svk6bJmVkWC0FAI7L5/MpISFBiYmJtksBUAT0AQxSubnS2WdLP/9sWsLccovtigDg%2BOgDCDgDI4BBKixMuu02czx5sukNCAAAUBIIgEHs5pulyEjp66%2Bl1attVwMAAEIFATCIVa8u9epljn0%2Bu7UAAIDQQQAMckOGmK%2BzZpnm0AAAAMVFAAxyiYlSs2ZmW7hXX7VdDQAACAUEQAc4Mgr4wgtSdrbdWgAAgPMRAB2gZ0%2BpZk1pxw5p3jzb1QAAAKcjADpAZKQ0cKA5fu45u7UAAADnIwA6xODBUrly0rJl0rp1tqsBAABORgB0iDp1pK5dzfGzz9qtBQAAOBsB0EGGDTNfp0%2BXfvvNbi0AAMC5CIAOcskl0oUXSocOmf2BASBY%2BHw%2BJSQkKDEx0XYpAIrAEwiwy6yTTJsm3XSTuSS8ebNUvrztigAgX1pamrxer/x%2Bv6Kjo22XA%2BAoGAF0mF698lvCzJ1ruxoAAOBEBECHOeUUsyJYkiZNslsLAABwJgKgAw0eLIWHSytXSl98YbsaAADgNARAB4qNla6/3hw/84zdWgAAgPMQAB1q%2BHDzddYsMx8QAACgqAiADnXhhdKll0o5OWwPBwAATgwB0MFGjDBfX35ZSk%2B3WwsAAHAOAqCDXXutdPbZ0v790tSptqsBAABOQQB0sLCw/LmAzzxjLgcDAAAcDwHQ4W68UapWTfr5Z%2Bndd21XAwAAnIAA6HAVK%2BY3hn7ySbu1AAAAZyAAhoBhw6SICGnVKum//7VdDQA38vl8SkhIUGJiou1SABSBJxAIBGwXgeIbOFB69VWpUycuBQOwJy0tTV6vV36/X9HR0bbLAXAUjACGiJEjzdf586UffrBbCwAACG4EwBBx7rlSx45SICA99ZTtagAAQDAjAIaQO%2B80X19/XUpNtVsLAAAIXgTAENKqldSihZSVJU2aZLsaAAAQrAiAIcTjke66yxxPniylpdmtBwAABCcCYIjp2FE67zwT/l580XY1AAAgGBEAQ0xYWP5cwIkTpUOH7NYDAACCDwEwBPXuLdWpYxaC/Oc/tqsBAADBhgAYgiIipFGjzPETT0jZ2XbrAQAAwYUAGKJuuUWqXl366Sdp9mzb1QAAgGBCAAxRlSpJ//ynOR43TsrNtVsPAAAIHgTAEDZ0qBQVJa1bJy1caLsaAKHM5/MpISFBiYmJtksBUASeQCAQsF0ESs/dd0vjx0vNmkmrVplegQBQWtLS0uT1euX3%2BxUdHW27HABHwQhgiPvXv6QKFaQvvpA%2B/th2NQAAIBgQAENcTIw0cKA5fuQRu7UAAIDgQAB0gdGjTWuYzz4zNwAA4G4EQBeoU0e6%2BWZz/PDDdmsBAAD2EQBd4u67pfLlzTzAlSttVwMAAGwiALrE6adL/fub44ceslsLAACwiwDoIvfcI5UrJ334oWkJAwAA3IkA6CJnnCH162eOH3zQbi0Ayt64ceOUmJioqKgo1apVS507d9YPP/xQ4DGZmZkaNmyYatSooUqVKikpKUk7duywVDGA0kIAdJmxY80o4AcfSKtX264GQFlatmyZhgwZolWrVmnx4sXKzs5W%2B/btlZGRkfeY4cOHKzk5WTNnztSKFSuUnp6ua6%2B9Vjk5ORYrB1DS2AnEhW6%2BWZo6VerQwQRBAO60Z88e1apVS8uWLVPr1q3l9/tVs2ZNvfHGG%2BrZs6ckaefOnYqPj9eiRYvUoUOH474mO4EAzsAIoAvde2/%2BXEBWBAPu5ff7JUnVqlWTJK1Zs0aHDx9W%2B/bt8x4TFxenBg0aaOVRfllkZmYqLS2twA1A8CMAutAZZ0g33miO//1vq6UAsCQQCGjEiBG65JJL1KBBA0lSamqqIiIiVLVq1QKPjYmJUWpqaqGvM27cOHm93rxbfHx8qdcOoPgIgC51771SeLj0ySfSsmW2qwFQ1oYOHapvv/1Wb7311nEfGwgE5PF4Cr1vzJgx8vv9ebft27eXdKkASgEB0KXq1pUGDDDH990nMRMUcI9hw4Zp/vz5Wrp0qerUqZN3PjY2VllZWdq3b1%2BBx%2B/evVsxMTGFvlZkZKSio6ML3AAEPwKgi40dK0VGSsuXS4sX264GQGkLBAIaOnSo5s6dqyVLlqhevXoF7m/SpInCw8O1%2BE%2B/EH799VetX79eLVu2LOtyAZQiAqCL1akjDR5sju%2B9l1FAINQNGTJE06dP15tvvqmoqCilpqYqNTVVBw8elCR5vV4NGDBAI0eO1CeffKKvv/5affr0UcOGDXXFFVdYrh5ASaINjMvt3m0WhWRkSMnJUufOtisCUFqONo9v6tSpuvH/V4YdOnRIo0eP1ptvvqmDBw%2Bqbdu2mjx5cpEXd9AGBnAGAiA0dqz02GPS%2BedL33xjWsQAwMkgAALOwCVgaNQoqUoVacMGqQgLAgEAgMMRAKGqVaU77zTH//63lJVltx4AAFC6CICQJN1xhxQbK23eLL38su1qAABAaSIAQpJUqVL%2BriAPPyylp9utBwAAlB4CIPLccot05plmZfDTT9uuBgAAlBYCIPKEh0uPPmqOJ0wwQRAAAIQeAiAKuO46qWlTcwn44YdtVwPAKXw%2BnxISEpSYmGi7FABFQB9A/M2SJVLbtlL58tLGjdJZZ9muCIBT0AcQcAZGAPE3l18uXXWVlJ0tjRljuxoAAFDSCIAo1PjxUliYNGeO9PnntqsBAAAliQCIQjVsKP3/1qAaOVJiogAAAKGDAIijevhhqWJFMwI4Z47tagAAQEkhAOKo4uKk0aPN8V13SZmZdusBAAAlgwCIYxo92gTBzZulZ5%2B1XQ0AACgJBEAcU6VK%2Bc2hH3lE2rPHbj0AAKD4CIBlJCvLdgUnr18/6aKLpLQ06b77bFcDAACKiwBYBpKTpfPPl1assF3JyQkLkyZONMevvCJ9%2B63degAAQPEQAEtZIGAunf74o9S6tTRihPTHH7arOnGtW0vdu0u5udLw4bSFAQDAyQiApczjkT75RLrpJhOaJk6UGjd25mjghAlSZKS0dKkZ1QQAAM5EACwDVapIr70mvfeeVLu29L//mRG14cOljAzb1RVd3br5bWFGjpQOHrRaDoAg4vP5lJCQoMTERNulACgCTyDAxbyytH%2B/uQw8dar5/owzpClTpDZtrJZVZBkZ0rnnSjt2SA8%2BKP3737YrAhBM0tLS5PV65ff7FR0dbbscAEfBCGAZOzIa%2BMEHUny89PPP0mWXSbfdZlbZBrtKlaQnnzTHjz8ubd1qtx4AAHDiCICWdOggrV8v3Xqr%2Bf6ll8xK4UWL7NZVFD16SJdeai4BjxhhuxoAAHCiCIAWRUdLL74oLVkinXmmuax6zTVSnz7S3r22qzs6j0d67jmpXDlp7lzpo49sVwQAAE4EATAIXHaZ6a03YoTpuTdjhnTeedJbbwVvu5WGDaVhw8zxsGHsEwwAgJMQAINExYrSU09Jn38uNWhgRgB795Y6dpS2bbNdXeEeeECKjZU2bTK1AwAAZyAABplmzaQ1a8wK24gI0zrm/PPNJdecHNvVFeT1mt6Akml2vWWL1XIAAEAREQCDUESEaa%2BSkiK1aiWlp0t33GGO162zXV1BN9xgWtgcPGguBQfrJWsAAJCPABjEzjtP%2BuwzyeeToqKk1auliy6S7rkneJowezzS5MlSeLi0cKH07ru2KwIAAMdDAAxyYWHS7bdLGzdKXbpI2dnSuHFmEcbHH9uuzjjvvPwdQu64QzpwwG49AADg2AiADlG7tmm5kpxsjn/6SWrXTurbV9q923Z10tixZleTHTvYHQQAgGBHAHSYzp2l774z8%2B08Hmn6dLM12yuvSLm59uqqWNFcCpakZ581C1kAAEBwIgA6UHS0CVmrV0uNG0v79kmDBkn/%2BIfdRSIdOkjXX2%2BC6MCB5nI1AHfw%2BXxKSEhQYmKi7VIAFIEnEGDdppNlZ5sWMffdJ2VkSOXLS//6l7kMW7ly2deza5eZE7hvn/TEE/lzAwG4Q1pamrxer/x%2Bv6Kjo22XA%2BAoGAF0uCOB78%2BLRCZMkBISzHzBso73MTHSk0%2Ba4/vvN3MVAQBAcCEAhoj4eLNIZOFCqW5daft2qWtX6dprpZ9/LttabrpJuvxy06pm0CB6AwIAEGwIgCHmmmukDRtMr8DwcGnRIrOTyEMPSYcOlU0NHo/08stShQrSkiXSlCll874AAKBoCIAhqGJF6dFHpW%2B/ldq2NcHv/vvNHsOLFpVNDWeeabaHk6SRI017GAAAEBwIgCHs3HOlxYulmTOluDgzH%2B%2Baa6ROnaTNm0v//f/5T7O3cVqadNttXAoGACBYEABDnMcj9ewpff%2B9NGqUWTQyf75ZJPLAA6W7pVy5ctLUqWZv4/fek954o/TeCwAAFB0B0CWioszq4G%2B%2BMQs0Dh2SHnyw9FcLHwmakhkR/OWX0nkfAABQdARAl0lIMHsIz5ol1akjbdliVgt36GB2GCkNo0dLTZtK%2B/ezKhgAgGBAAHQhj0e67jpzWXjsWCky0swVbNTI9BTcv79k3698een11837LFokvfZayb4%2BAAA4MQRAF6tUyazU3bBBSkoyTaSfeUY6%2B2yzt3BOTsm9V0JC/qrg4cPNyCMAALCDAAideaY0b5704Ydm5fDeveZSbdOm0mefldz7/OtfUqtWUnq6dOONZs9gAABQ9giAyNO%2BvekdOHGi5PVKKSnSpZeay8Ul0TamXDlzKbhSJWnZMunpp4v/mgCCg8/nU0JCghITE22XAqAIPIEAU/Lxd3v2SP/%2Bt9nRIzfXtHIZMUIaM0Yq7v7ur7xiRhgjIqQvv5QuuKBkagZgX1pamrxer/x%2Bv6KL%2B8sCQKlhBBCFqllTeuEFMwrYtq2UlSU9/rh0zjnFnx94yy1Sx47mNW%2B4oey2qAMAAAYBEMfUsKFZITxvnlkcsmuXGb278ELpo49O7jU9HunVV6VataT166W77y7ZmgEAwLERAHFcHo9ZJbx%2BvZkfWLWqtG6d6R149dVmFfGJqlXL7BIiSZMmSR98ULI1AwCAoyMAosgiIkwLlx9/NLt6hIdL779v5vANGiSlpp7Y6119tTR0qDnu39%2BMLgIAgNJHAMQJq1bN9AvcsMHsIpKba%2BYFnnWW2V4uPb3orzVhgtSggbR7twmBtIYBAKD0EQBx0s4%2BW3rnHWn5cql5cykjw%2Bz7e9ZZ0osvmsbSx3PKKdLMmebrhx/SGgYAgLJAAESxXXKJ9Pnn0ttvm6bSu3ZJgwebkb25c4%2B/9%2B/555t5gJJpM/PFF6VfM%2BBGn332mTp27Ki4uDh5PB69%2B%2B67Be4PBAJ64IEHFBcXpwoVKqhNmzbacDKTfAEEPQIgSoTHI/XoIX33nQlzNWpIP/wgdesmtWx5/B1FBg40Daezs6WePUt%2BP2IAUkZGhho1aqTnn3%2B%2B0PufeOIJPf3003r%2B%2Bef15ZdfKjY2Vu3atdOBAwfKuFIApY1G0CgVaWnSE0%2BYVcN//GHOXX219NhjUqNGhT/H7zftZTZvlrp0MZeXPZ6yqxlwE4/Ho%2BTkZHXu3FmSGf2Li4vT8OHDddddd0mSMjMzFRMTo/Hjx%2BvWW28t0uvSCBpwBkYAUSqio6VHHjErhm%2B7zWwDt2iRCXg33CD99NPfn%2BP1SrNmmdXFycnSc8%2BVfd2AW23evFmpqalq37593rnIyEhdeumlWrlypcXKAJQGAiBK1amnmh1FNm40l4gDAenNN6VzzzXzBH/5peDjmzaVnnzSHI8axXxAoKyk/n8fp5iYmALnY2Ji8u4rTGZmptLS0grcAAQ/AiDKxNlnm0Uia9aYBtLZ2Wal8FlnmaC3Z0/%2BY4cNM3MHDx828wJ/%2B81e3YDbeP4y7yIQCPzt3J%2BNGzdOXq837xYfH1/aJQIoAQRAlKmLLjK7fixbJrVqZfYBfuop6YwzpHvvlfbtM/P%2Bpkwx4XDbNun666XsnbvNUuMff7T9nwCEpNjYWEn622jf7t27/zYq%2BGdjxoyR3%2B/Pu23fvr1U6wRQMgiAsKJ1a9M/cNEiEwrT06VHH5Xq1TO9BAMBafZsKbb8Xt28uJcCdeqY5cRnn22S41df2f5PAEJKvXr1FBsbq8WLF%2Bedy8rK0rJly9SyZcujPi8yMlLR0dEFbgCCHwEQ1ng80lVXmSw3d67UsKFZCfzgg1LdutLCOYf0eaW26qW3FR44nP/ElSulyy83PWcAFFl6erpSUlKUkpIiySz8SElJ0bZt2%2BTxeDR8%2BHA99thjSk5O1vr163XjjTeqYsWK6t27t%2BXKAZQ02sAgaOTmSnPmSA89ZLaZu1FTNVU3H/0JffpIb7xRdgUCDvfpp5/qsssu%2B9v5/v37a9q0aQoEAnrwwQf10ksvad%2B%2BfWrevLl8Pp8aNGhQ5PegDQzgDARABJ3cXNMDMGbAtWp94L2jP7BChfwmgwCCAgEQcAYuASPohIWZ1b//aHbo2A/MzDz%2BPnMAAOBvCIAIWp5LLjn2A1q2ZKsQAABOAgEQwWvQICkq6qh3f5Y4UpMmSVu3lmFNAACEAAIggldcnLRggVSjRsHzERFKHf2kLp3YWcOHmxXDnTubtjJcEQYA4PhYBILgd%2BiQWR68caNUs6Z0/fXaFxGjunWlv%2B46dfHF0t13Sx07mrmEAMoWi0AAZyAAwrGmT5f69jXHMTHS/v1mXYgknXeedNddUu/eUni4vRoBtyEAAs7AGAkcq08facgQc5yeLs2bZ0b/oqPNYOGNN0pnnilNmiRlZFgtFQCAoMIIIBzt8GGzm8gnn0i1a0urV0uVK0svvihNnCjt2mUeV726NGyYNHSoOQZQsnw%2Bn3w%2Bn3JycrRp0yZGAIEgRwCE4%2B3bZ7YH3rhRuuACsxgkOtpMHZw2TXrySemnn8xjK1aUbrlFGjFCOv10q2UDIYlLwIAzcAkYjle1qrRokZkH%2BO23UpcuZi7gKadIt90mff%2B9NHOmdOGFZuOQZ581l4b79JG%2B%2BcZ29QAAlD0CIEJC3bomBFauLC1ZIvXrJ%2BXkmPvKl5d69pTWrJE%2B/FBq29bcN2OG1Lix1KGD9PHHtJABALgHARAh46KLpLlzzarfWbPMnL8/hzqPR2rf3oS9r74yoTAsTProI6ldOzNCOH26mVcIAEAoIwAipLRrJ73xhgl7L7wg3Xdf4Y9r0sRcFv7xRxMUK1Y0l4P79pXq1ZOeeMK0lQEAIBSxCAQh6cUXpcGDzfH48dKddx778b//bp7z3HNSaqo5V6mSdPPN0j//aeYMAjg%2BFoEAzkAARMgaP970BZRMsBs69PjPycyU3nxTevppaf16c87jkTp1koYPl1q3Nt8DKBwBEHAGLgEjZN11lzR2rDkeNkx65ZXjPycyUrrpJrOa%2BMMPpSuvNPMI331XatPGXDp%2B/fX8HUcAAHAiRgAR0gIBafRo6amnzMjdq6%2Bay7onYuNG6ZlnzNzCgwfNuVq1TIuZ226TTj215OsGnIoRQMAZCIAIeYGAmcf33HMmBE6ZYkb5TtRvv5lRRJ9P2rHDnCtfXrruOjPCePHFXB4GCICAMxAA4QqBgAlpPp8JaS%2B/bHYEORmHD0vJyaah9H//m3%2B%2BSRMzz7BnT6lChZKpG3AaAiDgDARAuMafRwIlEwZvv714r7l2rXm9t97KnxdYvbo0YIC5PFyvXvFeH3AaAiDgDARAuEogII0aZVb5StKECeb74tq718wvfOEFads2c87jka6%2B2oTMDh2kcuWK/z5AsPL5fPL5fMrJydGmTZsIgECQIwDCdQIB6d57pcceM9/fe6/00EMlM38vJ0dauNCMLi5enH%2B%2Bbl1p0CCzACUmpvjvAwQrRgABZyAAwrXGjZPuucccDxli5vSFlWBjpP/9z4wITpsm7dtnzoWHS126mMvDbdqwaAShhwAIOAMBEK42ebJZuBEISL16mR5/EREl%2Bx4HD0pvv212Glm9Ov/82WebUcH%2B/aWaNUv2PQFbCICAMxAA4XozZ0r9%2BpnVvVdcIb3zjlRa/26lpJggOGOGlJ5uzh0ZFRw4ULr88pIdhQTKGgEQcAYCICDpo4%2Bkrl2ljAypUSNp0SIpLq703u/AARM8X35Z%2Buqr/PP16pl5gjfdJNWuXXrvD5QWAiDgDARA4P%2BtWSNdc420a5dUp44JgQ0blv77fv21WUE8fbqUlmbOhYWZbegGDJCuvbbkL0sDpYUACDgDARD4k82bTeuW77%2BXoqKkWbNMECsLf/whzZljwuDy5fnna9SQ%2BvY1o4JlEUiB4iAAAs5AAAT%2BYt8%2Bczn400/NSNzEiWYXkbJcsbtpk/Taa9J//iPwdgrHAAAgAElEQVT9%2Bmv%2B%2BSZNpBtvlK6/3jScBoINARBwBgIgUIisLNOqZepU8/3AgdLzz5f9pdjsbOmDD0wdCxaYhSqSWTjSsaMJg1deab4HggEBEHAGAiBwFIGA9NRT0p13muNWrcwl2thYO/Xs3WtWD0%2BbZlYTH1GzptS7t7lMfNFF9BaEXQRAwBkIgMBxLFpkApbfb1YGz5kjtWhht6ZvvzU9C2fMMItWjjjvPBMEb7hBOu00e/XBvQiAsGn3bqliRalyZduVBD86jgHHcfXV0hdfmHC1c6d06aVmqzebfzpdcIEZndyxQ3rvPalnT%2BmUU6SNG83uJqefbup85ZX8XUiA0uTz%2BZSQkKDExETbpcBl0tPNH8NXX23%2BSJ8503ZFzsAIIFBEBw6YHn1z5pjve/UyffyiouzWdYTfb2qbPt0sYDkiIsL8Yuzd27SUqVDBWolwAUYAURaysqQPP5TeekuaN890UThi8GCzyxOOjQAInIBAQHrmGTMvMDvbbOf29tvShRfarqyg7dulN980YXD9%2BvzzUVFm15Hrr5fatmXxCEoeARClJSfH/HE7c6bZsenPVzfOOsv8kdu7t1S/vrUSHYUACJyElSvNCOD27WaE7YknpDvuCM4FGOvWmcsjb70lbduWf75GDal7dxMGL7mELehQMgiAKEm5ueb37dtvS7NnF5zzHBtrpr/07i0lJgbn799gRgAETtJvv5mdOubNM99feaVp12JrlfDxHPlF%2BtZb5hfpnj3598XFST16mF%2BmzZvzixQnjwCI4srNlVavNo34Z8%2BWfvkl/75q1aRu3cwf4JdeKpUrZ69OpyMAAsUQCJi5JqNGSYcOmebML79sGkkHs%2BxsackSEwaTk838wSNOO82EwR49pKZNCYM4MQRAnIwjoW/2bDOXefv2/Puio6VOnUzou%2BIKtsYsKQRAoAR8951pvXKkP98NN0jPPmv%2BWg12mZlmMvXbb0vz55sVdUfUrStdd525EQZRFARAFFVOjrkqMWeOmdP355G%2BypWlpCRzVaJ9e9PlACWLAAiUkKws6YEHpPHjzV%2BzsbFmdLBLF9uVFd3Bg9L775tLLwsWFFxZd/rpZs5g9%2B5cJsbREQBxLIcPS8uWmcCXnFxwTl9UlNnh6LrrzJQaQl/pIgACJWz1arNF2/ffm%2B%2B7dzejgaeearWsE/bHH6YJ9uzZptdgRkb%2BfXXqmHk43btLLVuygAT5CID4q4MHpcWLpblzzVWGP6/erVLFjPR17y61a0foK0sEQKAUHDokPfSQWR2ckyN5vdK4cdKgQc6ctPzHH2ZP4tmzpYULC14mjo01o5zduplJ2eXL26sT9hEAIUn795s/HJOTze%2BOP/8BWbOm1LmzmSt9%2BeXM6bOFAAiUopQUE/q%2B/NJ837SpuSzs5M0SDh2SPvrIzNuZP7/gApJq1cxk7W7dzGTtyEh7dcIOAqB77dhhfickJ5t%2BfdnZ%2BffFx5s/FLt2NW2nnPiHcKghAAKlLCdHeuEFaexYKS3NzJ27%2BWbp0UelmBjb1RVPVpb0ySdmPs%2B8edLevfn3RUWZnUe6dpWuukqqVMlenSg7BED3CARMo/l588ztq68K3p%2BQYEJfly7SRRcxbzjYEACBMpKaanYQeeMN831UlAmF//xnaMx7yc6Wli/Pn9y9c2f%2BfaecYiZ1d%2B1qQmHVqvbqROkiAIa2w4elFStM4Js/X9q8Of8%2Bj0dq0cJc3u3c2eyUhOBFAATK2MqVJvQd%2BWv5tNOkRx4x3exD5bJIbq70xRcmDM6dK/38c/595cubbei6dTOXi2vVslcnSo7P55PP51NOTo42bdpEAAwhfr9pFTV/vpnXt39//n2nnGKme3TqZFbwOv2qhpsQAAELcnPNPr1jx5p5M5LUsKEJgh07htalkkBA%2Bvbb/DC4YUP%2BfWFhUuvWZgVg167OWymNv2MEMDRs3WpaQc2fb%2BbzHT6cf1%2BNGmYkPynJ9OhjeoczEQABi/74w7SIefzx/MUUiYnSgw%2BaS6ahFASP%2BOEHEwTfeUdasyb/vMcjtWpldiDp1s1sTwfnIQA6U26u%2Bf9x/nxz%2B/bbgvfXr28CX1KSucwbKlcr3IwACASB33%2BXJkwwYfBI8%2BWmTc0IYVJS6PbZ27LFBME5c6RVq/LPezzSP/5htn7q3t20jYAzEACd49AhaelSM59vwYKC83bDwswfZEdC3znn2KsTpYMACASR3btN78AXXsgPggkJZq/h3r1Du63K9u0mDM6aJX3%2Bef75cuWkDh2kPn3MPKOKFe3ViOMjAAa33383Dd7ffdfM6/tzT8/Klc3/a0lJ0tVXm0u9CF0EQCAI7dkjTZwo%2BXymdYxkGi4PGSLdemvoj4ht22aC4FtvSWvX5p%2BPijJ7gw4YwHZ0wYoAGHx%2B%2BcWszH/3XTOfLycn/77atc28406dpMsuC%2B0/MlEQARAIYn6/9NJL5tLwkY3SIyJMCLr9dneEoB9%2BkGbMMO1ztmzJP3/BBSYQ9%2BnDqGAwIQAGh82bzdSKd94x21P%2BWYMGJvB17iw1aRL6v0NQOAIg4ABZWWYbtkmT8ncVkUwIuuUWc3m4enV79ZWF3FzTZ3DKFPNZHDpkzteoYdrq3HGHRN6wjwBoz9at0ttvm9Hzvy6watHCNGTu3Fk66yx7NSJ4EAABh1m92swRfPvt/BAUEWHm7fTpY3bdCPW9NX//XZo2TXruufxRwerVTRudQYNCd9GMExAAy9Zvv5nAN3266TF6RFiY1KaNWVHfpQstlvB3BEDAofbtM7/0X3vN7Dl8RNWqpqdejx5mTk94uL0aS1t2thkNfPBBc6lYMn3J3n5bqlLFbm1uRQAsfTk5ZgHHlClm9e6RHn0ej3TppWaKSNeuNFnHsREAgRDwzTfSf/5jFk38%2Bmv%2B%2BapVTcPWTp1MMIqKsldjacrONgtm7rnHrJ5u2VJatszsOoKyRQAsPXv3Si%2B/bOYFb9uWf75xY6lvX9M2if6ZKCoCIBBCcnKkzz4zI2DJyaatzBHh4WbXjSuvNGGwQYPQu1T6zTdmBMTvNyseO3WyXZH7EABL3pYtpj3U1Kn50z6qVTOh7%2BabzVxg4EQRAIshEAjowIEDtssACpWTY5orL1wovf9%2BwU3bJTNn7h//MM1eW7aUzjvP%2Bd399%2B834faHH8zK6f79bVcU%2BjIzM5WZmZn3/YEDB5SQkKDt27cTAItp715p3DgT/I60bmncWLrtNjOv75RT7NYXCqKiouRx6TJoAmAxHPlLFwAAOI%2BbR6oJgMVwMiOAaWlpio%2BPL9Zfx4mJifryz71AyvD5Nt%2B7uJ%2BdzdqL%2B/yS/tyysqSvvjJtVVauNK1lMjL%2B/lyvV8rMXKsbbrhI55wjnX22aSFRp07RRwtL43PbvdssfFm92jS2/eqr/PvOOMOsEG7UyO7P29FqL4vnluXz/zoC%2BOuvv6pZs2b67rvvVLt27VJ975J%2Brs3nH/l527Rpu%2B66K1rJyeZ8w4ZmFPAf/yi99y6J5zv13wY3jwAyRboYPB7PSf/DEB0dfdLPLVeuXLH%2BYinO822%2B9xEn%2B9nZrt3m5y79/XO78kpzk8zlpfXrzSXjL780gWrDBjOXTmqjKVMKvlZ4uHTaadLpp0vx8WY3gVNPlWJizMrDatXMAhSvVwoLK1/k2nNzpQMHzKXc334zQe/Agev0zDPR2rJF%2BvFH6fvvzU4pf9W8uWkB06dPfhscmz9vxX1/J/%2B8SuYfVj63ItqwQZEvv6zXVE6L203X8q0DFB5eU488Io0YUfTFTE7%2BHWX7/1U3IgA60JAhQ6w93%2BZ7F5ft2m1%2B7sdTrpwZMWvUyGw1J5lRwo0bpaefXqy4uHbauNHMrfv5Z3PfTz%2BZ2/FtUMWKZr5SZKQJj0cWnwQCpoVFZqaZ3H5k/%2BOCHtH99xc84/GYzembNzcLWzp0MKOSf2Xz56247%2B/kn9fictXnNmqU9NRTipR0kyRtHaOb9KA23/%2BmEu7sUrrvXYLPt/2548RxCbiMsULu5PHZnZyS/txycsy2dJs3m1YU27dLO3ea9jO7dpmJ67/9ZkbxsrNP7j0iIswilVq1zB7IdeqY0cYzz5Tq15fOPVeqVKnY/ynHxM/bydmxY0fe5bg6haVy5Hv9denGGwu/LyLC/AV2xhllWpIT8f/qyWEEsIxFRkbq/vvvVyQ7bp8wPruTU9KfW7ly5vLvaacd%2B3GBgHTwoJSebuYXHjxoRg6zs/NXNIaFmRHBiAipQgUT6qKjg2N1Iz9vJ%2BfI58XnVgSTJh39vqws6cUXTf8XHBP/r54cRgABACWG0Zgiys01k/uO9U/w5ZdLn3xSdjXBVUKsDSwAAA4QFiZVrnzsxxCgUYoIgAAA2NCr17Hvv/76sqkDrkQABADAhnvuMSudCtO6tdS1a9nWA1chAAIAYEPdutJ//yt1757X7G%2BfqujV6BE6MOv9ojcABE4CAdCiW2%2B9VR6PR88884ztUoLeAw88oHPPPVeVKlVS1apVdcUVV2j16tW2ywp6hw8f1l133aWGDRuqUqVKiouLU79%2B/bRz507bpQW9uXPnqkOHDqpRo4Y8Ho9SUlJsl4QQ9NnOnep46JDqV6%2BuuqqkhjV%2B1sC0pzRoeMVjrg9xu3HjxikxMVFRUVGqVauWOnfurB9%2B%2BMF2WY5CALTk3Xff1erVqxUXF2e7FEc455xz9Pzzz2vdunVasWKF6tatq/bt22tPYVtCIM8ff/yhtWvX6r777tPatWs1d%2B5cbdq0SUlJSbZLC3oZGRlq1aqVHn/8cdulIIRlZGSoUaNGGjd5srYqQ0NGrFP58tLMmdIjj9iuLngtW7ZMQ4YM0apVq7R48WJlZ2erffv2yihsT0sUijYwFvzyyy9q3ry5PvzwQ11zzTUaPny4hg8fbrssRznSauLjjz9W27ZtbZfjKF9%2B%2BaWaNWumrVu36rTjNfODtmzZonr16unrr79W48aNbZcTtHw%2Bn3w%2Bn3JycrRp0ybawJwEj8ej5ORkpaZ21uDB5twrr0i33GK3LifYs2ePatWqpWXLlql169a2y3EERgDLWG5urvr27avRo0fr/PPPt12OI2VlZenll1%2BW1%2BtVo0aNbJfjOH6/Xx6PR1WqVLFdCkLIkCFD9N133%2BnLL7%2B0XYrj3XabdPfd5njQIGnGDLv1OIHfbFyuatWqWa7EOQiAZWz8%2BPEqX7687rjjDtulOM7ChQtVuXJlnXLKKZo4caIWL16sGjVq2C7LUQ4dOqS7775bvXv3ZnQGCGKPPWaCYCAg9esnTZ9uu6LgFQgENGLECF1yySVq0KCB7XIcgwBYimbMmKHKlSvn3ZYtW6ZJkyZp2rRp8ng8tssLWn/93JYvXy5Juuyyy5SSkqKVK1fqyiuvVI8ePbR7927L1QaXo312klkQ0qtXL%2BXm5mry5MkWqww%2Bx/rcABs8HsnnkwYONJuG9Osnvfqq7aqC09ChQ/Xtt9/qrbfesl2KozAHsBQdOHBAu3btyvt%2B9uzZGjt2rMLC8nN3Tk6OwsLCFB8fry1btlioMvj89XOrXbu2KlSo8LfHnX322br55ps1ZsyYsiwvqB3tszt8%2BLB69Oihn3/%2BWUuWLFH16tUtVhl8jvUzxxzAE8NWcCfvyBzAzp07553LzZWGDpVeeMF8/9RT0ogRlgoMQsOGDdO7776rzz77TPXq1bNdjqPQZKgURUVFKSoqKu/7QYMGqWPHjgUe06FDB/Xt21c33XRTWZcXtP76uR1NIBBQZmZmGVTkHIV9dkfC3//%2B9z8tXbqU8FeIov7MAWUtLMyMBFauLE2YII0cKf3%2Bu/Tww2aU0K0CgYCGDRum5ORkffrpp4S/k0AALEPVq1f/2z%2B%2B4eHhio2NVf369S1VFfwyMjL06KOPKikpSaeeeqp%2B%2B%2B03TZ48WTt27NB1111nu7yglp2dre7du2vt2rVauHChcnJylJqaKslMlo6IiLBcYfD6/ffftW3btryeiUd6jMXGxio2NtZmaQgh6enp%2BvHHH/O%2B37x5s1JSUlStWrW8VfoejzR%2BvFSlijR2rPToo9KePdLkyVK5crYqt2vIkCF68803NW/ePEVFReX9XvN6vYVeMUIhArDq9NNPD0ycONF2GUHt4MGDgS5dugTi4uICERERgVNPPTWQlJQU%2BOKLL2yXFvQ2b94ckFTobenSpbbLC2pTp04t9HO7//77bZcW1Px%2Bf0BSwO/32y7FEZYuXVroz1n//v0LffyLLwYCHk8gIAUCXbsGAgcPlm29weJov9emTp1quzTHYA4gAKDEMAew9L3zjtS7t5SVZbYMnjfPjA4CJ4JVwAAAOEi3btKHH0rR0dJnn0mXXiqxuyNOFAEQAACHadNGWrZMio2Vvv1WatlSYitcnAgCIAAADtS4sbRypXT22dLWrVKrVtIXX9iuCk5BAAQAwKHq1ZP%2B%2B1%2BpaVPpt9%2Bkyy%2BXPvrIdlVwAgIgAKDYfD6fEhISlJiYaLsU16lZU1qyRGrXTsrIkK65Rpo503ZVCHasAgYAlBhWAduTlSX172/Cn8cjPfecNGSI7aoQrBgBBAAgBERESDNmmNAXCJgt5B56yBwDf0UABAAgRISFmZG/%2B%2B83399/v9k7ODfXbl0IPgRAAABCiMcjPfCANGmS%2Bf6ZZ6RbbpFycqyWhSBDAAQAIATdcYc0bZoZFZw6NX/3EEAiAAIAELL695dmz5bCw6VZs8wuIocO2a4KwYAACABACOvaVZo/XzrlFGnhQikpSfrjD9tVwTYCIAAAIe7KK6X335cqVZIWLza9AtPTbVcFmwiAAAC4QJs2ZpeQqCjp00%2Blq66SDhywXRVsIQACAOASLVtKH38seb3SihWEQDcjAAIA4CLNmpkQWKWK2UeYEOhOBEAAAFymadOCIZA5ge5DAAQAFJvP51NCQoISExNtl4IiatLELAjxeqXly6WOHVkd7CaeQIBdAgEAJSMtLU1er1d%2Bv1/R0dG2y0ERrF4ttWtnLgO3b29axkRG2q4KpY0RQAAAXKx5c9MipmJFs0q4Rw/p8GHbVaG0EQABAHC5Vq2kBQtMs%2Bj586V%2B/dg7ONQRAAEAgC6/XHrnHbNt3MyZ0u23S0wSC10EQAAAIEm6%2BmppxgzJ45FeflkaM8Z2RSgtBEAAAJDnuutM%2BJOk8eOlJ5%2B0Ww9KBwEQAAAUcMstJvxJ0ujR0uuv260HJY8ACAAA/ubOO6VRo8zxgAHSokV260HJIgACAIBCjR%2BfvyL4uuukL76wXRFKCgEQAAAUKixMevVVqUMHs0vINddIP/5ouyqUBAIgAAA4qvBwac4c6aKLpL17pauukvbssV0ViosACAAAjqlyZem996S6dc0IYKdO0sGDtqtCcRAAAQDF5vP5lJCQoMTERNuloJTExpqFIFWqSJ9/LvXvL%2BXm2q4KJ8sTCNDnGwBQMtLS0uT1euX3%2BxUdHW27HJSCTz%2BV2rc3%2BwXfc4/06KO2K8LJYAQQAAAUWZs20iuvmOPHHqNHoFMRAAEAwAnp318aO9YcDxworVhhtx6cOAIgAAA4YQ89JHXrZi4Fd%2BkibdliuyKcCAIgAAA4YWFh5vLvhRea9jBJSVJ6uu2qUFQEQAAAcFIqVZLmzZNiYqR161gZ7CQEQAAAcNLi46XkZCkiQpo7l1XBTkEABACXmDt3rjp06KAaNWrI4/EoJSXlb4/JzMzUsGHDVKNGDVWqVElJSUnasWOHhWrhJC1aSC%2B8YI7//W9pwQK79eD4CIAA4BIZGRlq1aqVHn/88aM%2BZvjw4UpOTtbMmTO1YsUKpaen69prr1VOTk4ZVgonuvlm6fbbzXGfPtKmTXbrwbHRCBoAXGbLli2qV6%2Bevv76azVu3DjvvN/vV82aNfXGG2%2BoZ8%2BekqSdO3cqPj5eixYtUocOHY772jSCdresLKltW9MWJiFBWr3abCOH4MMIIABAkrRmzRodPnxY7du3zzsXFxenBg0aaOXKlRYrg1NEREizZ0unnip99500YIDEMFNwIgACACRJqampioiIUNWqVQucj4mJUWpqaqHPyczMVFpaWoEb3C02VpozRypfXpo1S3r2WdsVoTAEQAAIQTNmzFDlypXzbsuXLz/p1woEAvJ4PIXeN27cOHm93rxbfHz8Sb8PQkfLltJTT5njUaMkBpCDDwEQAEJQUlKSUlJS8m5NmzY97nNiY2OVlZWlffv2FTi/e/duxcTEFPqcMWPGyO/35922b99eIvXD%2BYYNk3r2lLKzpR49pD17bFeEPyMAAkAIioqK0llnnZV3q1ChwnGf06RJE4WHh2vx4sV553799VetX79eLVu2LPQ5kZGRio6OLnADJMnjkV55RapfX/rlF6lvX5pEB5PytgsAAJSN33//Xdu2bdPOnTslST/88IMkM/IXGxsrr9erAQMGaOTIkapevbqqVaumUaNGqWHDhrriiitslg6Hiooy8wGbNZM%2B/FB6/HHpnntsVwWJEUAAcI358%2Bfrwgsv1DXXXCNJ6tWrly688EK9%2BOKLeY%2BZOHGiOnfurB49eqhVq1aqWLGiFixYoHLlytkqGw7XoIHk85nj%2B%2B6TijEdFSWIPoAAgBJDH0AUJhCQ%2BvWTpk%2BX6tSRUlKk6tVtV%2BVujAACAIBS5fGYreLOOUfascPsGsLwk10EQAAAUOoqV5befts0i54/P/%2ByMOwgAAIAgDLRuLE0YYI5HjVKWrfObj1uRgAEAABlZtgw6ZprpMxM6frrpYMHbVfkTgRAAABQZjwe6bXXpJgYacMG6c47bVfkTgRAAABQpmrVkqZNM8fPPy%2B9/77VclyJAAgAAMrclVdKd9xhjm%2B6Sdq71249bkMABAAUm8/nU0JCghITE22XAgd5/HEpIUHatUu69VZaw5QlGkEDAEoMjaBxor7%2BWmreXDp8WHr9ddMwGqWPEUAAAGDNhRdKDzxgjocNk7Zts1qOaxAAAQCAVXfeKV18sZSWJg0YwKXgskAABAAAVpUvby7/Vqggffyx9OKLtisKfQRAAABg3TnnmEUhkjR6tPTzz3brCXUEQAAAEBSGDpUuvVTKyDCXgnNzbVcUugiAAAAgKISFmV1CKlaUPv2US8GliQAIAACCxhln5F8KvvNOaetWu/WEKgIgAAAIKkOGSJdcYi4FDxzIquDSQAAEAABBJSxMmjJFOuUUafFis0IYJYsACAAAgs4550gPPmiOR4yQUlPt1hNqCIAAACAojRhhdgrZt0/65z9tVxNaCIAAgGLz%2BXxKSEhQYmKi7VIQQsqXN5eCy5WTZs2SFiywXVHo8AQCTK0EAJSMtLQ0eb1e%2Bf1%2BRUdH2y4HIeLOO6UJE6T4eGnDBikqynZFzscIIAAACGoPPCDVqydt3y7dd5/takIDARAAAAS1ihXzm0I/95y0Zo3dekIBARAAAAS99u2l668328PdequUk2O7ImcjAAIAAEd4%2BmnJ6zUjgJMn267G2QiAAADAEWJjpXHjzPG990q//mq3HicjAAIAAMcYNEhKTJTS0qSRI21X41wEQAAA4BjlykkvvCB5PNJbb0lLltiuyJkIgAAAwFGaNJEGDzbHQ4dKWVl263EiAiAAAHCcRx6RataUNm6UJk2yXY3zEAABAIDjVK0qjR9vjh96SNq50249TkMABAAAjtS/v3TxxVJ6ujR6tO1qnIUACAAoNp/Pp4SEBCUmJtouBS4SFiY9/7xZEPLmm9KKFbYrcg5PIBAI2C4CABAa0tLS5PV65ff7FR0dbbscuMSgQdIrr0iNG0tffWVWCuPYGAEEAACO9uijUpUqUkqKNGWK7WqcgQAIAAAcrWZN6YEHzPHYsdL%2B/VbLcQQCIAAAcLzbb5fOO09q00Y6dMh2NcGvvO0CAAAAiis8XFq1SmLqadEwAggAAEIC4a/oCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAis3n8ykhIUGJiYm2SwFQBJ5AIBCwXQQAIDSkpaXJ6/XK7/crmqZsQNBiBBAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQABwgcOHD%2Buuu%2B5Sw4YNValSJcXFxalfv37auXNngcft27dPffv2ldfrldfrVd%2B%2BfbV//35LVQMoLQRAAHCBP/74Q2vXrtV9992ntWvXau7cudq0aZOSkpIKPK53795KSUnRBx98oA8%2B%2BEApKSnq27evpaoBlBYaQQOAS3355Zdq1qyZtm7dqtNOO00bN25UQkKCVq1apebNm0uSVq1apRYtWuj7779X/fr1j/uaNIIGnIERQABwKb/fL4/HoypVqkiSPv/8c3m93rzwJ0kXX3yxvF6vVq5cWehrZGZmKi0trcANQPAjAAKACx06dEh33323evfunTdSl5qaqlq1av3tsbVq1VJqamqhrzNu3Li8%2BYJer1fx8fGlWjeAkkEABIAQNGPGDFWuXDnvtnz58rz7Dh8%2BrF69eik3N1eTJ08u8DyPx/O31woEAoWel6QxY8bI7/fn3fbv36/du3crKiqqZP%2BDAJSo8rYLAACUvKSkpAKXcmvXri3JhL8ePXpo8%2BbNWrJkSYF5erGxsdq1a9ffXmvPnj2KiYkp9H0iIyMVGRlZwtUDKG0EQAAIQVFRUX8bhTsS/v73v/9p6dKlql69eoH7W7RoIb/fry%2B%2B%2BELNmjWTJK1evVp%2Bv18tW7Yss9oBlD5WAQOAC2RnZ6tbt25au3atFi5cWGBEr1q1aoqIiJAkXXXVVdq5c6deeuklSdKgQYN0%2Bumna8GCBVbqBlA6CIAA4AJbtmxRvXr1Cr1v6dKlatOmjSTp999/1x133KH58%2BdLMpeSn3/%2B%2BbyVwgBCAwEQAADAZVgFDAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAN3qhfcAAADbSURBVAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwmf8DcALoF2TaJ1AAAAAASUVORK5CYII%3D'}
Genus 2 curve data - 731.a.12427.1