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g2c_curves • Show schema
{'Lhash': '331095882514331657', 'abs_disc': 16464, 'analytic_rank': 0, 'analytic_rank_proved': True, 'analytic_sha': 1, 'aut_grp_id': '[2,1]', 'aut_grp_label': '2.1', 'aut_grp_tex': 'C_2', 'bad_lfactors': '[[2,[1,1]],[3,[1,1,1,-3]],[7,[1,-2,1]]]', 'bad_primes': [2, 3, 7], 'class': '1176.b', 'cond': 1176, 'disc_sign': 1, 'end_alg': 'Q x Q', 'eqn': '[[0,0,1,0,0,-2],[1,1]]', 'g2_inv': "['-204800000/1029','16640000/1029','-1688000/1029']", 'geom_aut_grp_id': '[2,1]', 'geom_aut_grp_label': '2.1', 'geom_aut_grp_tex': 'C_2', 'geom_end_alg': 'Q x Q', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['160','4720','130020','-65856']", 'igusa_inv': "['80','-520','4220','16800','-16464']", 'is_gl2_type': True, 'is_simple_base': False, 'is_simple_geom': False, 'label': '1176.b.16464.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.3616472654567443315540810925091610974681841422719899797', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.180.3', '3.640.2'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 4, 'num_rat_wpts': 2, 'real_geom_end_alg': 'R x R', 'real_period': {'__RealLiteral__': 0, 'data': '13.019301556442795935946919330', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, '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': 4, 'torsion_order': 12, 'torsion_subgroup': '[2,6]', 'two_selmer_rank': 2, 'two_torsion_field': ['4.0.441.1', [4, -2, -1, -1, 1], [4, 2], True]} -
g2c_endomorphisms • Show schema
{'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], ['1.1.1.1', [0, 1], -1]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['RR', 'RR'], 'fod_coeffs': [0, 1], 'fod_label': '1.1.1.1', 'is_simple_base': False, 'is_simple_geom': False, 'label': '1176.b.16464.1', 'lattice': [[['1.1.1.1', [0, 1], [0]], [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], ['RR', 'RR'], [3, -1], 'G_{3,3}']], 'ring_base': [3, -1], 'ring_geom': [3, -1], 'spl_facs_coeffs': [[['2025/16'], ['-184437/64']], [[-1620], ['44469/2']]], 'spl_facs_condnorms': [14, 84], 'spl_facs_labels': ['14.a5', '84.b4'], '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}'} -
g2c_ratpts • Show schema
{'label': '1176.b.16464.1', 'mw_gens': [[[[-1, 1], [1, 1]], [[-1, 1], [0, 1], [0, 1], [0, 1]]], [[[0, 1], [-1, 1], [1, 1]], [[0, 1], [-1, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [2, 6], 'num_rat_pts': 4, 'rat_pts': [[0, -1, 1], [0, 0, 1], [1, -1, 1], [1, 0, 0]], 'rat_pts_v': True} - g2c_galrep • Show schema
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g2c_tamagawa • Show schema
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id: 7772
{'label': '1176.b.16464.1', 'local_root_number': -1, 'p': 2, 'tamagawa_number': 2} -
id: 7773
{'cluster_label': 'c3c2_1~2_0', 'label': '1176.b.16464.1', 'local_root_number': -1, 'p': 3, 'tamagawa_number': 1} -
id: 7774
{'cluster_label': 'c1c2_1~2c2_1_0', 'label': '1176.b.16464.1', 'local_root_number': 1, 'p': 7, 'tamagawa_number': 2}
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id: 7772
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g2c_plots • Show schema
{'label': '1176.b.16464.1', 'plot': 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UtMnXSS7VfeqpXUurVNMGMICbyAAIiQtWOH9PbbtsD0woWFj1erJvXvLw0aZDOKq1d3r8ZgQQAMXnv3Sr/9Jq1bZ8f69XZ//Xo7Nm0qHD5Rkqgoa1GLi7OjXj076tSR6ta1nXtq1y7sio2NtcDnr5a2nBxrfdy%2B3Von//jDWi03bbJgm3/tGzYUf81VqlggbN9e6tBB6tRJatfOAiMQSgiA8IQVK2zLubfeKtxyTrLw16%2BfTRzp21ci2xSVkpKilJQU5ebmauXKlQTAAJSTY4Fm9WqbKb9mjZ3zj61bS/4e4eFFu0kbNbL7%2BUeDBhb8YmIKW%2BaCWU6OhcG0NPvd8Ouv0rJl0s8/W3j8s4gIqWNHm2jWo4ed6UVAsCMAwlMcR1q8WJoyRfrPf6w1IF9EhHTWWdZF3L%2B//UcIQwugu3bvtoD352PNGvs7XFILXkyMjXtLTCw8jj%2B%2B8Khf31q%2BvM5xrLUwNVX64Qc7Fiw4PESHh0tnnGHDSs47zyabMZ4QwYYACM9yHPsFP3WqHYcuKSPZBJLzzrOWwdNPtxmIXkUArHw7d1rrdP6xenXhOT396K%2BNjJSaNrWjWbPC202bWvCrVcsvlxCSHMfeg6%2B/lubOlb780rrSD9WggTRggHThhdKZZ9qHSSDQEQAB2S/55cttOZmPP5a%2B/dYeyxcdba2DZ58t9eplA8dDoSustAiAx85xbLbsoSHv0GPHjqO/vnZtqXlz6YQT7GjWrPDMjFb/WrPGdiX6/HObdLZnT%2BHXatWyIHjZZVLPnrSsInARAIEj2LpVmjHD9iOeOfPwcUENG9ov9549pe7dpRYtQjsQEgBLJy/PZsz%2BuQUvP%2BRlZh799fHxFvJOPNHCXX7ga97cJlUg8GRn25aVH3xgx5YthV9r1Ei68krp2mvtPQUCCQEQKEFenrRokTRrln3anz/ffukfql49qUsXqXNnGxvUoYPNNg4VBMBC2dnWBbhmzZHH5O3ff/TXN25sYeDQcJd/1Kjhl0tAJcnNlebNs9UH/vMf69bP17OnbVl54YXeHk6CwEEABMpo3z7rIv7qK2nOHBsk/udAGB4utW0rJSfb7MEOHWyv4mAdG%2BSlAJiXZxMB1q0rnEmbP7N2zRpbH%2B9ovzWrVLFJFvmh7tCWvGbNQuuDAYqXnS198omtSTpjRuHuJg0bSrfcIt10ky2fA7iFAAgco%2BxsayH85htrHfzuuyMP2q9a1RaZPeUUC4dt2lgobNgw8LuPM7dsUWz9%2BsrYuVMxQd4XeeBA4Zpw%2BevCHbpO3oYNhQuIF6dGjaJj8PLH5Z1wgoU/WnhwqPXrpZdfll56ydYmlGwJquuvl%2B68U0pIcLc%2BeBMBEKhgjmO/8BcuLFxKYsmSot1Bh4qNtYVnW7a0ySUnnlg4Bsz1tcbS0qT771fm%2B%2B8r9uBBZTRqpJjhw6W77grI0e1791rrXf5OFhs3Fu5usWGDHX/8cfQWPMku7fjjbQbtobNq82/HxQV%2BaEfgOXBAeucdadw4W2pGsg8LV18tjR5tHx4AfyEAAn7gONbK9OOPdixdaseqVUdfw61ePQsdTZoUrtmWkGCDyxs1siBSaTksLc0GNW7bpkxJsZIyJMVI0iWX2P9kfrBvn03K2bq1cA/a/B0e8o/Nm%2B3IyCjd94yMtD/HQ9fFy18nr0kT%2B7MND6/Mq4KXOY6NJx471paVkSwIDh0q3Xcf%2B5bDPwiAgIuys239wV9/tWPlSstdaWklLwsi2dIfcXH2H0b9%2BkW35srfkqtWLWtljI215Wyio60Ls8RuyksvtRWzpcMDoGT/c/XsedRvkZtrrXJ79thixrt3F927Nf/YtctaSHfsKNzKa/t2WzZl796S/xwOVb26davnh%2BT83S0SEuw4/njbtowWPASCr7%2BWxoyRZs%2B2%2BzVqWAP7nXcyKQiViwB4DBzHUVZ5d0gHSrBrV%2BH4tA0brFv599%2Bti3PTptJ1ZR5NeLiFpagoaxGLjLRQGBEhRfn26pPU4xWhg5IsACZI2qDCADi97lV6KvFZHTxoXVv55/37Ldju22ePVYTwcAtt%2BQG3Xr3C4BsXZ8un5B%2Bhsl0ZvGXuXAuCixbZ/QYNpIceki6%2BmL/PlSk6Olo%2Bj/4BEwCPQf7MSAAAEHy8sLJBcQiAx6CkFsDk5GR9//33ZfqemZmZSkhI0IYNG8r8l7I8P6%2B8rwvlayvv64Ll%2Bjp06KxZs%2BZr3z7rXt23z1rusrPtyM2V9u7OVu/bTlWNnZskHbkFcMXF/9Cai/%2Bu8PDClsOICGtJjIqyo3p1qU%2Bfbvrhh3llbsXgvauY1wTLtZX3dcFyfWV5zb590jPPSOPGOdq/36fwcEd33unTHXeUfikp3rvSvc7LLYAMcz4GPp/vqH9pq1SpUu5PFjExMWV%2BbXl/XnleF8rXdiyvkwL/%2BqpWzVOTJqV4zeZbpVGjijwU879DUVFKfma4khuU/H2qVj2o2Fjeu4p4XShf27G8Tgr86yvLa2JipEcekQYPzlLbtnOUk9Nfjz1m6wpOnGjrilZGjW68Tgr89y5UsXtkJRo2bFhQ/LzyvC6Ur%2B1YXldeAfne3XWXNGjQ4Y9HRdkM4AYNKvbnufy68grI966C8N5V3OvK85rEREfS%2BXr11b2qV0/6%2BWfp9NNtbGBOTsX/PDdeV17BUmcgows4wITyjguhfG1SCF/fnDna9uKLqvf22/rjzjsVd/vtpQ5/wSJk3zuF9rVJoX19h17bgQMxuuUW22JOshWa3noruNcODOX3LhhUGTNmzBi3i0BRVapUUc%2BePRUegguRhfK1SSF6fU2aaE/37nryySd194cfqkaILlIWku/d/4TytUmhfX351xYTE66LL7ZtBWfPtjVEJ04sXEQ%2BWIXyexfoaAEEUCI%2BqQOBY%2B1aW6ZzwQK7f9dd0qOPsng5yoYxgAAABJGmTW3dwNtus/tPPimde64tng6UFgEQAIAgExFhewq/%2B67tGDJ7tnTaadLy5W5XhmBBAAQAIEj99a/St99aq%2BCaNdIZZxRuKwccDQEQAIAg1qaNjQfs0sX21j73XOmNN9yuCoGOAOgCx3E0ZswYNWzYUNWqVVPPnj31yy%2B/lPi6jRs36oorrlCdOnVUvXp1nXrqqVqUv3FkACnv9eUbO3asfD6fRo4cWYlVlk95rm3s2LFKTk5WdHS04uLidMEFF2jFihV%2Bqhj5nn/%2BeTVt2lRRUVHq0KGD5s2bV%2BxzJ0yYoG7duqlWrVqqVauWevfurYULF/qx2rIpy7UdasqUKfL5fLrgggsqucJjU9br27Vrl4YNG6YGDRooKipKrVq10vTp0/1UbdmU9dqefvppnXTSSapWrZoSEhJ02223af/%2B/apXz1r%2BBg%2B2NQKvusq6iAPR3Llzdf7556thw4by%2BXz68MMP3S7Jmxz43WOPPeZER0c777//vrN06VJn0KBBToMGDZzMzMxiX7Njxw4nMTHRufrqq50FCxY4a9eudb744gtn1apVfqy8dMpzffkWLlzoNGnSxGnbtq0zYsQIP1RbNuW5tnPOOcd57bXXnJ9//tlJTU11%2BvXr5xx//PHO7t27/Vh5%2BTz33HNOq1atnBYtWjiSnIyMDLdLKpcpU6Y4VatWdSZMmOAsW7bMGTFihFOjRg3nt99%2BO%2BLzL7vsMiclJcVZsmSJs3z5cueaa65xYmNjnd9//93PlZesrNeWb926dU6jRo2cbt26OX/5y1/8VG3ZlfX6srOznY4dOzrnnXee8/XXXzvr1q1z5s2b56Smpvq58pKV9drefPNNJzIy0pk8ebKzdu1aZ8aMGU6DBg2ckSNHFjwnN9dxbr/dcSQ77r3XcfLy/HVFpTN9%2BnRn9OjRzvvvv%2B9Icj744AO3S/IkAqCf5eXlOfHx8c5jjz1W8Nj%2B/fud2NhY54UXXij2dX//%2B9%2Bdrl27%2BqPEY1Le63Mcx8nKynJOPPFEZ9asWU6PHj0CLgAey7UdasuWLY4kZ86cOZVRZqXIyMgI6gB42mmnOTfddFORx1q2bOncc889pXp9Tk6OEx0d7UyaNKkyyjsm5bm2nJwcp0uXLs7LL7/sDBkyJKADYFmvb/z48U6zZs2cAwcO%2BKO8Y1LWaxs2bJhz1llnFXns9ttvP%2Bz/hrw8xxk7tjAE3nZb4IXAfARA99AF7Gdr165Venq6%2BvTpU/BYZGSkevToofnz5xf7umnTpqljx47661//qri4OLVr104TJkzwR8llUt7rk2yLnn79%2Bql3796VXWa5HMu1HSojI0OSVLt27QqvEYc7cOCAFi1aVOR9k6Q%2BffqU%2Bn3bu3evDh48GHDvWXmv7Z///Kfq1aun6667rrJLPCblub5p06bpjDPO0LBhw1S/fn21bt1ajz76qHJzc/1RcqmV59q6du2qRYsWFQxHWLNmjaZPn65%2B/foVeZ7PJ91zj/Tss3b/X/%2ByJWNY9ReHYtlIP0tPT5ck1f/Tbgr169fXb7/9Vuzr1qxZo/Hjx%2Bv222/XP/7xDy1cuFB/%2B9vfFBkZqauuuqpSay6L8l7flClTtHjxYn3//feVWt%2BxKO%2B1HcpxHN1%2B%2B%2B3q2rWrWrduXeE14nDbtm1Tbm7uEd%2B3/Pe0JPfcc48aNWoUcB9OynNt33zzjV555RWlpqb6o8RjUp7rW7Nmjf773//q8ssv1/Tp05WWlqZhw4YpJydH999/vz/KLpXyXNvgwYO1detWde3aVY7jKCcnRzfffLPuueeeIz5/%2BHApMlIaOlT697%2BlqlWlJ56wgAjQAljJJk%2BerJo1axYcBw8elCT5/vQv0HGcwx47VF5entq3b69HH31U7dq104033qgbbrhB48ePr9T6S1IR17dhwwaNGDFCb775pqKioiq95tKqqPfuUMOHD9dPP/2kt99%2Bu8LrxdGV93174okn9Pbbb2vq1KkB9ffzUKW9tqysLF1xxRWaMGGC6tat66/yjllZ3ru8vDzFxcXppZdeUocOHTR48GCNHj3a9d%2BVxSnLtX311Vd65JFH9Pzzz2vx4sWaOnWqPvnkEz300EPFfv8bbpBefNFuP/WU9OCDFVY6ghwtgJVswIAB6tSpU8H97OxsSdaa1KBBg4LHt2zZctgnwUM1aNBASUlJRR5r1aqV3n///QquuGwq4voWLVqkLVu2qEOHDgWP5ebmau7cuXruueeUnZ2tKlWqVNIVFK%2Bi3rt8t956q6ZNm6a5c%2BeqcePGFV8wjqhu3bqqUqXKYa0qpXnfnnrqKT366KP64osv1LZt28oss1zKem2rV6/WunXrdP755xc8lpeXJ0kKDw/XihUrdMIJJ1Ru0WVQnveuQYMGqlq1apHfGa1atVJ6eroOHDigiIiISq25tMpzbffdd5%2BuvPJKXX/99ZKkNm3aaM%2BePRo6dKhGjx6tsLAjt%2BkMHSrt3y%2BNGGEBsHZt6W9/q9jrQfChBbCSRUdHq3nz5gVHUlKS4uPjNWvWrILnHDhwQHPmzFHnzp2L/T5dunQ5bOmQlStXKjExsdJqL42KuL5evXpp6dKlSk1NLTg6duyoyy%2B/XKmpqa6EP6ni3jvHcTR8%2BHBNnTpV//3vf9W0aVN/lI//iYiIUIcOHYq8b5I0a9aso75vTz75pB566CF9/vnn6tixY2WXWS5lvbaWLVse9m9twIABOvPMM5WamqqEhAR/lV4q5XnvunTpolWrVhUEW8l%2BVzZo0CBgwp9Uvmvbu3fvYSGvSpUqcmxC51F/3t/%2BVtj6N3Kk7SACj3Nn7om3PfbYY05sbKwzdepUZ%2BnSpc6ll1562FIiZ511lvPss88W3F%2B4cKETHh7uPPLII05aWpozefJkp3r16s6bb77pxiUcVXmu788CcRaw45Tv2m6%2B%2BWYnNjbW%2Beqrr5zNmzcXHHv37nXjEsol2GcB5y%2B38corrzjLli1zRo4c6dSoUcNZt26d4ziOc%2BWVVxaZefn44487ERERznvvvVfkPcvKynLrEopV1mv7s0CfBVzW61u/fr1Ts2ZNZ/jw4c6KFSucTz75xImLi3Mefvhhty6hWGW9tgceeMCJjo523n77bWfNmjXOzJkznRNOOMG55JJLSvXz8vIcZ/hwmxkcEeE4bi1EkJWV5SxZssRZsmSJI8kZN26cs2TJkhKXLkLFIgC6IC8vz3nggQec%2BPh4JzIy0unevbuzdOnSIs9JTEx0HnjggSKPffzxx07r1q2dyMhIp2XLls5LL73kx6pLr7zXd6hADYDluTZJRzxee%2B01/xZ/DII9ADqO46SkpDiJiYlORESE0759%2ByLL8PTo0cMZMmRIwf3ExMQjvmdH%2BzvrprL5St5ZAAAgAElEQVRc258FegB0nLJf3/z5851OnTo5kZGRTrNmzZxHHnnEycnJ8XPVpVOWazt48KAzZswY54QTTnCioqKchIQE55ZbbnF27txZ6p%2BXk%2BM4F11kIbB2bcdZubIir6Z0vvzyyyP%2B%2Bzra31NUPJ/jMDEcwNFlZmYqNjZWGRkZiomJcbscAMdg3z6pZ09p4UKpRQvbRu6449yuCv7GGEAAADykWjXpo4%2BkhARp5Urp0kulAFsmEX5AAAQAwGPi4y0EVqsmff65FEBLJMJPCIAAAHhQu3bSK6/Y7UcflaZNc7ce%2BBcBEECxUlJSlJSUpOTkZLdLAVAJLr20cE3AIUOkdetcLQd%2BxCQQACViEggQug4ckHr0kL77TurUSZo3z7aNQ2ijBRAAAA%2BLiJCmTLGZwAsWMB7QKwiAAAB4XGKiNGGC3X78cWnuXHfrQeUjAAIAAF18sXTttZLjSFddJWVmul0RKhMBEAAASJKeflpq0kT67TfpzjvdrgaViQAIAAAkSdHR0sSJdnvCBGnWLFfLQSUiAAIAgAI9ekjDh9vtoUOlPXvcrQeVgwAIAACKGDtWOv54WxdwzBi3q0FlIAACAIAiataUxo%2B32//6l/Tjj%2B7Wg4pHAAQAAIc57zybGZybK91yi80ORuggAAIAgCP617%2BkGjWk%2BfOlN95wuxpUJAIggGKxFzDgbY0bS/fdZ7f//ncpK8vdelBx2AsYQInYCxjwruxs6eSTpdWrpX/8Q3rkEbcrQkWgBRAAABQrMlJ66im7PW6ctGGDu/WgYhAAAQDAUf3lL1L37tL%2B/dL997tdDSoCARAAAByVzyc98YTdfv116Zdf3K0Hx44ACAAAStSpk3TRRVJeXuHEEAQvAiAAACiVhx6y1sAPPpAWLXK7GhwLAiAAACiVpCTp8svt9oMPulsLjg0BEAAAlNp990lhYdLHH0tLlrhdDcqLAAgAAEqtRQtp0CC7zZqAwYsACAAAyuQf/7Dz1KnSihXu1oLyIQACAIAyad1aOv98yXEKF4lGcCEAAigWewEDKM7f/27n11%2BX0tPdrQVlx17AAErEXsAA/sxxpM6dpe%2B%2Bs91BmBUcXGgBBAAAZebzSbfdZrfHj5eys92tB2VDAAQAAOVy0UVS48bS1q3SO%2B%2B4XQ3KggAIAADKJTxcuvlmu52S4m4tKBsCIAAAKLfrrpOqVpUWLpQWL3a7GpQWARAAAJRb/frWFSxJL73kbi0oPQIgAAA4JjfeaOe33pL27HG3FpQOARAIIo7jaMyYMWrYsKGqVaumnj176pdffjnqa8aMGSOfz1fkiI%2BP91PFALygRw/phBOkrCzpvffcrgalQQAEgsgTTzyhcePG6bnnntP333%2Bv%2BPh4nX322crKyjrq604%2B%2BWRt3ry54Fi6dKmfKgbgBWFh0tVX2%2B2JE92sBKVFAASChOM4evrppzV69GhddNFFat26tSZNmqS9e/fqrbfeOuprw8PDFR8fX3DUq1fPT1UD8IohQ2xtwK%2B%2Bkn77ze1qUBICIBAk1q5dq/T0dPXp06fgscjISPXo0UPz588/6mvT0tLUsGFDNW3aVIMHD9aaNWuO%2Bvzs7GxlZmYWOQDgaBISpJ497fbkya6WglIgAAJBIv1/m23Wr1%2B/yOP169cv%2BNqRdOrUSa%2B//rpmzJihCRMmKD09XZ07d9b27duLfc3YsWMVGxtbcCQkJFTMRQAIaVdcYefJk22rOAQuAiAQoCZPnqyaNWsWHAcPHpQk%2BXy%2BIs9zHOewxw7Vt29fDRw4UG3atFHv3r316aefSpImTZpU7GtGjRqljIyMgmPDhg0VcEUAQt3AgVJEhLRsmfTzz25Xg6MJd7sAAEc2YMAAderUqeB%2B9v822kxPT1eDBg0KHt%2ByZcthrYJHU6NGDbVp00ZpaWnFPicyMlKRkZHlqBqAl8XGSn37Sh99ZFvDtWnjdkUoDi2AQICKjo5W8%2BbNC46kpCTFx8dr1qxZBc85cOCA5syZo86dO5f6%2B2ZnZ2v58uVFQiQAVJRBg%2Bz8n//QDRzICIBAkPD5fBo5cqQeffRRffDBB/r555919dVXq3r16rrssssKnterVy8999xzBffvvPNOzZkzR2vXrtWCBQt08cUXKzMzU0OGDHHjMgCEuP79pchIaeVKqYRlSuEiuoCBIHL33Xdr3759uuWWW7Rz50516tRJM2fOVHR0dMFzVq9erW3bthXc//3333XppZdq27Ztqlevnk4//XR99913SkxMdOMSAIS46Gjp7LOlTz6RPvhAat3a7YpwJD7HoYEWwNFlZmYqNjZWGRkZiomJcbscAAHu1Vel666T2reXFi1yuxocCV3AAACgQvXvb4tCL14s/f6729XgSAiAAACgQsXFSaefbrf/t/IUAgwBEAAAVLh%2B/ew8fbq7deDICIAAAKDC9e1r59mzpQMH3K0FhyMAAgCACnfqqdYVvGePVMJ25XABARBAsVJSUpSUlKTk5GS3SwEQZMLCbDkYSZo5091acDiWgQFQIpaBAVAekyZJV18tJSdLCxe6XQ0ORQsgAACoFL162XnRIikjw91aUBQBEAAAVIrGjaXmzaW8PGnePLerwaEIgAAAoNL06GHnOXPcrQNFEQABAEClyQ%2BAc%2Be6WweKIgACAIBK07WrnRcvlvbtc7cWFCIAAgCAStOkidSggZSTI33/vdvVIB8BEAAAVBqfT%2Brc2W5/%2B627taAQARAAAFSqTp3s/N137taBQgRAAABQqfIDIF3AgYMACAAAKlX79tYVvHGjlJ7udjWQCIAAAKCS1awptWxptxcvdrcWGAIggGKlpKQoKSlJycnJbpcCIMi1b2/nJUvcrQOGAAigWMOGDdOyZcv0PQN3AByjU0%2B1MwEwMBAAAQBApTvlFDv/9JO7dcAQAAEAQKVr29bOq1ezI0ggIAACAIBKFxcn1akj5eVJy5e7XQ0IgAAAoNL5fNLJJ9vtX35xtxYQAAEAgJ%2B0amVnWgDdRwAEAAB%2BkR8AV6xwtw4QAAEAgJ%2B0aGHntDR36wABEAAA%2BEnz5nZetUpyHHdr8ToCIAAA8IsmTaQqVWwZmM2b3a7G2wiAAADAL6pWlRIS7PaaNe7W4nXhbhcAb9q7V9q6Vdq2TdqxQ9q5U8rIkLKypN277ev79kn790sHDkg5OVJubmGXgc9nnyLDw6WICCkqyo4aNeyIibHjuOOk2rVt7am6daXoaHstSiclJUUpKSnKzc11uxQAIaJpU2ndOju6dnW7Gu8iAKLC7d8vrV1rn%2B7WrZPWr5c2bJA2bpQ2bZLS0y3kuSEyUoqPlxo0kBo2lBo1kho3lhITrWuiaVOpXj1CYr5hw4Zp2LBhyszMVGxsrNvlAAgBiYl2/u03d%2BvwOgIgym3HDunnn21Bz2XLbFr/ihUW9kozuDciwlrlateWatWSYmOt1a5mTal6dTsiI%2B15Vatai1/Y/wYt5OVZi%2BDBg9ZCmJ1tLYZ79li4zMqyFsVdu6zO7dvt69nZ9kvnaL94ataUmjWz2WotWkgtW9rSBa1aWesiAKD8jj/ezgRAdxEAUSqbNknffy8tWiQtWSKlpkq//17886OjLUQ1aWKf9hISrKWtYUNrfatf3//dsXv2SFu2SH/8YYOPN22ya1i/3o5166yVcvdu26z8SBuWN2smtWlje1qeeqrUrp1dIy2GAFA6%2BWMAN250tw6vIwDiMAcOSIsXS998I82fLy1YUPw/1MRE29onKclayE46STrxxMDsRq1Rw7p4mzYt/jnZ2RYEV62SVq60Y/lyO7ZssW7tNWukjz4qfE2tWlKHDlLHjlKnTnY0aFDplwMAQalRIzsTAN3lcxxW4vG6gwelhQul//5XmjPHQt%2B%2BfUWfExZmQa9jR2v1atfOWsFiYtyp2Q3btklLlxa2DqamWhf4gQOHPzcxUercWerSxQY5t2lT2H0djPLHAGZkZCjGS286gAr344/Wg1Kvnn2whjsIgB61apX02WfSzJnSl19a9%2Bih6tSx8NK5s3T66Rb8GP92uAMHLAT%2B8IOF6IULbUxkXl7R5x13nNStm9Szp3TWWRaegykQEgABVJQ//rDJeD6f/Q4Npy/SFQRAjzh4UJo3T/r4Y%2BmTTywAHqpOHQsmPXtKPXpYd24wBZRAkpVl3ebz5xd2o/951nP%2Bn3fv3lKfPjaOMJARAAFUlNxcm9yXl2fdwA0bul2RNxEAQ9jevdKMGdLUqRb6du0q/FrVqtY1ec45FkBOOYXAV1lycmzizJw51to6d%2B7hgfCkk6Rzz5X69rUAHhXlTq3FIQACqEhxcbYWbGqq/f8D/yMAhpj9%2B61rd8oU6dNPi3bt1qsn9e9vR%2B/e3hq/F0gOHrQZ1bNm2fHdd/aJOF/16tLZZ0vnn2/vVf367tWajwAIoCKdfLItH/bFF1KvXm5X400EwBCQm2utS2%2B%2BKb3/vpSZWfi1xERp4EDpwgulM86wtfQQWDIy7JfgZ5/ZsWlT4dd8PhuDecEF0kUXFW6k7m8EQAAVqUcP6w155x3pkkvcrsabGHoZxNLSpIkTpTfesMWX8zVuLA0aZEfHjoG3HAuKio21kD5woC2gvWSJddl//LFNLvn2Wzv%2B/nebTXzxxXYkJbldOQCUT61adt650906vIwAGGT27ZPee0%2BaMMEmdeQ77jjpr3%2BVrrjCxvYxni84%2BXxS%2B/Z23H%2B/DZD%2B6CPpww9t/ODSpXY88IB1oVxyiTR4sO1YUhnYCxhAZSAAuo8u4CCxYoX0wgvSpEmF/2DCwmwSx9VXSwMGBN7EAVSsHTukadPsA8DMmTaWMF/79tJll1kYzF9ktSLRBQygIo0cKf3739I990hjx7pdjTfRThTAcnOtG7BPH9uP9umnLfwlJkr//Kftozh9urUCEf5CX%2B3aFvY/%2BcQWT5040WYOV6liO7fceadtsdSrl30tK8vlggGgGNHRdj50zDr8iwAYgLKypGeesW69AQNspqjPZzNCP/1UWr1auu8%2BG%2BsHbzruOGnIEJs0kp4uPf%2B8df07ju3ocs01ttDqlVfaBJM/L0wNAG7KD4B/XhIL/kMADCCbN1tzeEKCNGKE7Tlbq5Z01112%2B%2BOPpfPOYyYviqpbV7r5ZhsTunat9PDD9uFh716bGX722bb/8QMP2NcBwG35O0v9eRcq%2BA8BMACkpUk33GC7QTz%2BuC0L0qKFteps2CA98UTg7xSBwNCkiTR6tPTrr7a%2B4E03WWvh%2BvU2bOCEEywQvvOOlJ3tdrUAvKp6dTv/ed95%2BA8B0EVLl0qXXmrj%2B15%2B2fZE7NrVZn0uX26tOuy/i/Lw%2BaROnaTx421dwbfessW/Hce6hAcPtiEEd91lH0AAwJ/yx63v3%2B9uHV5GAHTBTz/Zmm9t29qOHXl5Ur9%2B0tdfWzfegAEs44KKU62afdCYNcu6gO%2B91/be3LZNeuopa23u3du2DDx0ZnERy5bZeft2v9UNIHTVzNmlLvpaCdtT3S7Fs4gZfrRsmc3YPeUU%2B8/W57MFfVNTbWZnly5uV4hQNHXqVJ1zzjmqW7eumjb1aeDAVP32m7U0n3ee/T2cPds%2BlDRpIj30kE0skWSLD556qm0jI9mmxVddZeMUAKCs9u2TbrlF513fUF%2Brmyb%2B2E5q1crWuIJfsQ6gH6xdawPw33zTuuB8Plu0%2Bf77bTFfoDK98cYbWrt2rRo2bKgbbrhBS5Ys0amnnlrw9XXrpJdekl55xZaXkaSqVaVRPb/VA3POVNiBbGVKipWUISlGsv7lb75hRhKAsjnvPFu%2B4M/CwqwlpG9f/9fkUQRAP%2BjVy5bmkGxP3gcftC29AH9at26dmjZtelgAzJedbXtJP/ecbT33mc7VuZohSYcHQMmasS%2B80E/VAwh6X38tdetW/Nc7dLD9L%2BEXdAH7wYMP2szL77%2B3/zMJfwhEkZG2m8j8%2BdJ3s3eqj2Ye/QVTp/qnMAChoaTfGYsW2ZIF8Av2AvaDrl1t6y4gWHw583F10tE7B7K2ZSvaT/UACAGlWXuKacF%2BQwsgEEImT56smjVrFhzz5s0r1/e57cEHlZuUdNTn3Pt5V11wgQ0FBIASHa37V7KNzJs1808tIAACoWTAgAFKTU0tODp27Fiu7xMZGakqd91V7Nd3RdTTRA3RRx9ZC3fnztKHH7LlHICjGDjQtiUqzsiRUjgdk/5CAARCSHR0tJo3b15wVKtWrfzf7OqrbQDrn38hJyTouO9maMHyWF1/vY0d/PZbmw%2BSlCS9%2Bqotag4ARVStKs2YYctJHSoszPY/veMOd%2BryKGYBAyFux44dWr9%2BvTZt2qR%2B/fppypQpOumkkxQfH6/4%2BPiSv8HmzcqcNEmxo0Yp4/XXFXPppUVCYXq69MwztnVh/vKAjRrZ7/KhQ9nNBsCf5OVp/n2fadajC1Xn%2BJoaPuev7HfqAgIgEOImTpyoa6655rDHH3jgAY0ZM6ZU3yMzM1OxsbHKyMhQTExMMc%2Bx9QTHjZM2b7bH6tSxD/a33mp7EgOAZPuRDx4s9exp683D/wiAAEpUmgCYLztbev116fHHpdWr7bGYGGnYMOm226R69fxQMICANmmSjTI55xzp88/drsabGAMIoEJFRko33CD9%2Bqv01ltS69bWOjh2rPXy3HnnIVvNAfCkvXvtXL26u3V4GQEQQKUID5cuvVT68Ufpgw9skf%2B9e6X/%2Bz%2BbCDhyZGFXMQBv2bPHzowRdg8BEEClCguTLrjAdsKZPl06/XRb6/Xf/7YgOGKEtGmT21UC8KesLDvXrOluHV5GAATgFz6f7fM%2Bf77tjNOli40XfOYZW/t1xAhaBAGvyA%2BAJQwpRiUiAALwK5/P9saeN0/64ovDg%2BAdd0hbtrhdJYDKlL9kVGysu3V4GQEQQLFSUlKUlJSk5OTkCv/ePp/Uq5cFwVmzpDPOsK7hceOsa3jUKGnHjgr/sQACwM6ddq5Vy906vIxlYACUqCzLwJSX49gmAfffb%2BMFJeseuv12Wz6GriIgdPToIc2dK02ZIg0a5HY13kQLIICA4PNJ554rLVggffSR1LatLR8zZox1DT/5pLRvn9tVAqgI27fbuW5dd%2BvwMgIggIDi80kDBkhLlthuASedZP9Z3H23dMIJ0gsvSAcPul0lgGORP86XheHdQwAEEJDCwqRLLpF%2B/ll67TUpMdFmCd98s9SqlS0ynZfndpUAyionR9q2zW7Hxblbi5cRAAEEtPBw2zJqxQqbKRwXZ1vMXX651L69rS3ISGYgeGzdav9mw8JoAXQTARBAUIiMlG691cLfww/bpJAff5T69ZPOPFP67ju3KwRQGvnrfdavL1Wp4m4tXkYABBBUataURo%2BW1qyxfYUjI6U5c2wZmYEDraUQQOD6/Xc7N2rkbh1eRwAEEJTq1LGZwWlp0jXXWHfS1KnSySdLN97IriJAoNqwwc6NG7tbh9cRAAEEtYQE6dVXpZ9%2BstnDubnSSy9JzZvbmoL5W04BCAzr19v5%2BOPdrcPrCIAAQsLJJ9v6gXPmSKefLu3dKz30kAXB8eNZOgYIFGvX2rlJE1fL8DwCIICQ0r27NH%2B%2B9N570okn2npjt9witWljAZEZw4C71qyxc9Om7tbhdQRAACHH57MJIb/8Ij37rO02sGKFdMEFUs%2BehVvNAfAvx7GZ/JK1zsM9BEAAxUpJSVFSUpKSk5PdLqVcqlaVhg%2BXVq2SRo2SoqJs/9HTTrN1BH/7ze0KAW/Zvl3atctuN2vmbi1e53McOkQAHF1mZqZiY2OVkZGhmJgYt8sptw0bbAmZN96w%2B5GR0siRFg5jY92tDfCCb76Runa1yVv5k0HgDloAAXhGQoL0%2BuvSokW2eHR2tvT44zZWcPx426IKQOX59Vc7t2zpbh0gAALwoPbtpdmzpWnTpJNOsq2pbrlFOuUU6bPP3K4OCF3Lltm5VSt36wABEIBH%2BXzS%2BedLS5faRJE6dew/p/POk8491yaQAKhYS5fauXVrd%2BsAARCAxx06UeSOO%2Bz%2BjBlS27bWKrh1q9sVAqHjp5/s3KaNu3WAAAgAkqTjjpOeespaAS%2B8UMrLs3GBJ55oj2dnu10hENz%2B%2BMMOn48AGAgIgABwiObNbU/hL7%2BU2rWTMjKku%2B6yLisWkgbKb8kSO7doIdWo4W4tIAACwBHlLxj9yitSfLx1EV9wgdS7d2E3FoDSW7TIzu3bu1sHDAEQAIpRpYp07bXSypW2VmBkpPTf/1rL4E03MT4QKIv8HXiCdF35kEMABIASREdLjz5qa5j99a82PvDFF627eNw46cABtysEApvjSAsW2O3TTnO3FhgCIACUUpMm0rvvSnPmWCtgZqbNHG7TRvr0U8YHAsX57TcpPV0KD6cLOFAQAAEUK9j3Aq4s3btbd9bLL0txcdZF3L%2B/1LevtHy529UBgeebb%2Bzcrp1UrZq7tcAQAAEUa9iwYVq2bJm%2Bzx%2B8gwJVqkjXXSelpdks4fz1A9u0kUaMkHbudLtCIHDMm2fnbt3crQOFCIAAcAxiYqQnnrD1AwcMkHJzpWeeYX9h4FBz5ti5e3d360AhAiAAVIDmzW2dwJkzpZNPlrZvt51E2re3NQUBr9q82SZQ%2BXwEwEBCAASACnT22VJqqu0vXKuW7X161lnSxRdLa9e6XR3gf7Nn27ldO/s3gcBAAASAChYebvsLp6VZK2BYmPT%2B%2B1KrVtK990p79rhdIeA/M2fa%2Beyz3a0DRREAAaCS1KkjpaRYi%2BBZZ9l%2Bwo88Ip10kjR5MsvGIPTl5dnkKEk65xx3a0FRBEAAqGRt2khffGF7DDdpIm3cKF1xhdS1q/TDD25XB1SexYulLVukmjWlLl3crgaHIgACgB/4fNKFF9o6gY88ItWoIc2fb9tiXXut9McfblcIVLxPPrFznz5SRIS7taAoAiAA%2BFFUlPSPf0grVlgroCS99potG/Pkk2wrh9Dy4Yd2Pv98d%2BvA4QiAAOCCRo2kN96wVsCOHaWsLOnuu6XWra3VhPGBCHZr10o//miToPr3d7sa/BkBEABcdMYZ0oIF1goYH28zh88/n23lEPzef9/OPXpIdeu6WwsORwAEUCz2AvaPsDDp6qttT%2BG77y7cVq5tW2nkSLaVQ3B65x07//Wv7taBI/M5Dh0NAI4uMzNTsbGxysjIUExMjNvlhLxVq6Q77pCmTbP7depIDz8s3XCD7UEMBLq0NKlFC/v7ummTFBfndkX4M1oAASDAHLqtXFKSbSt3881sK4fg8eabdu7dm/AXqAiAABCgzj7bBtE/84xtofXTT7ag9MCB0po1blcHHFlenk1wkqSrrnK3FhSPAAgAASw8XLr1VutSGzbMutSmTrVt5UaNstnDQCCZM8dmAEdHSxdc4HY1KA4BEACCQJ060nPP2bZyvXvbeoGPPWbjrF591VpdgEAwYYKdL71Uql7d3VpQPAIgAASR1q1tbOBHH9lYwfR06brrbEeRefPcrg5et3Vr4fIvQ4e6WwuOjgAIAEHG55MGDJB%2B%2BUV66ikpJsb2XO3e3ZbcWLvW7QrhVa%2B8Yq3THTtKHTq4XQ2OhgAIBJGpU6fqnHPOUd26deXz%2BZSamlriayZOnCifz3fYsX//fj9UjMoUEWHLxaSlSTfeaOsJvveejQ%2B85x4pM9PtCuElOTlSSordHjbM3VpQMgIgEET27NmjLl266LHHHivT62JiYrR58%2BYiR1RUVCVVCX%2BLi5NeeEFaskTq1UvKzpYef9z2F54wQcrNdbtCeMF770m//y7VqycNHux2NShJuNsFACi9K6%2B8UpK0bt26Mr3O5/MpPj6%2BEipCIGnbVpo1y/YSzm8ZHDpUevZZadw4mzwCVAbHkZ580m4PGybx%2BTLw0QIIeMDu3buVmJioxo0bq3///lqyZMlRn5%2Bdna3MzMwiB4KDz2d7Cf/8s/T007Z%2B4NKltqZgv37sL4zKMXOmjUOtVo3u32BBAARCXMuWLTVx4kRNmzZNb7/9tqKiotSlSxelpaUV%2B5qxY8cqNja24EhISPBjxagIERHSiBG2rdyIEbae4PTpUps20i23SFu2uF0hQoXjSI88YreHDpXq1nW3HpQOewEDAWry5Mm68cYbC%2B5/9tln6tatmyTrAm7atKmWLFmiU089tUzfNy8vT%2B3bt1f37t31zDPPHPE52dnZys7OLrifmZmphIQE9gIOYitXSnffbcvHSLZI76hR0siR1moDlNfs2Ta8ICLCdqhp1MjtilAatAACAWrAgAFKTU0tODp27Fgh3zcsLEzJyclHbQGMjIxUTExMkQPBrUUL6cMPbS/hDh1sB5F//EM66STbtouFpFEejiPde6/dvvFGwl8wIQACASo6OlrNmzcvOKpVUDON4zhKTU1VgwYNKuT7Ibj07CktXGihLyFB2rDB9mvt2NFacoCy%2BPBD6bvvrBV51Ci3q0FZEACBILJjxw6lpqZq2bJlkqQVK1YoNTVV6enpBc%2B56qqrNOqQ38QPPvigZsyYoTVr1ig1NVXXXXedUlNTddNNN/m9fgSGsDDpiiukFSuksWNtIeklS6wbr29f6aef3K4QweDgQVtvUpJuv13iM2VwIQACQWTatGlq166d%2BvXrJ0kaPHiw2rVrpxdeeKHgOevXr9fmzZsL7u/atUtDhw5Vq1at1KdPH23cuFFz587Vaaed5vf6EViqVbP/wFevlm691SaKfP65dOqp0pAh0vr1bleIQPb88za2NC7OxpciuDAJBECJMjMzFRsbyySQELdqlTR6tPTuu3Y/MlIaPtzGCtau7W5tCCx//GHjRzMypJdekm64we2KUFa0AAIAJEnNm0vvvCMtWCD16GE7ivzf/0nNmllX8d69bleIQHHXXRb%2BOnSQrr3W7WpQHgRAAEARp51ms4U//dR2F8nIsFbA5s2l8eNt7Be8a9Ysm0Tk81k3cJUqbleE8iAAAgAO4/NJ551nk0PeeENq2lTavNkWkW7VSpo8maVjvEWU8F8AAAnVSURBVGj3blvsWbLhAQwlDl4EQABAsfJnDP/6q%2B0pHBdnk0auuEI65RRbWJqR5N5x553SunVSkyaFu38gOBEAAQAlioiwFp/Vq6WHH5ZiY22/4QsukDp1kmbMIAiGuk8%2BkV580W6/8ortJoPgRQAEUKyUlBQlJSUpOTnZ7VIQIGrWtJnCa9fauMAaNaTvv5fOPVfq1k3673/drhCVYeNG6Zpr7PZtt0lnneVuPTh2LAMDoEQsA4PibNkiPfaYTQbI3z66Rw/pwQftjOB38KAFvq%2B/ltq1k7791pYIQnCjBRAAUG5xcdK4cdKaNdZFHBEhzZljW86deab01Vd0DQe7u%2B6y8BcTY8sEEf5CAwEQAHDMGja0SSKrVkk33yxVrWrh78wzrSXwiy8IgsHotdekf//bbk%2BaJJ14orv1oOIQAAEAFSYhwbqDV6%2B2JWMiIqR586Szz5Y6d7aJBATB4PDll4VLvjzwgE34QehgDCCAEjEGEOW1caP0xBO2Xdj%2B/fbYKadIo0ZJF1/MIsKB6scfpe7dpcxMadAg6e23bW1IhA4CIIASEQBxrP74w7aVGz/eFhOWpBNOsPFlQ4ZIUVHu1odCaWk2o/uPP%2Bw8cybvTygiAAIoEQEQFWXHDhsr%2BMwzdluS6teX/vY3GztYq5a79Xnd6tU2gef3362l9quvpOOOc7sqVAYCIIASEQBR0Xbvll5%2B2WYQb9hgj9WoIV17rTRypNSsmbv1edGvv0q9e1u3fatWFv7i4tyuCpWFSSAAAL%2BrWdOC3urVttdw27bSnj3WOnjiidLAgbb0CE0U/vHDDzbmb%2BNGKSnJFvQm/IU2AiAAwDVVq9q%2BwqmpNtbsnHOkvDxp6lQbf9axozRxYuEEElS8Tz%2B1bt%2BtW6X27a3lLz7e7apQ2QiAAADX%2BXy2VMznn9sew9dfbxMPFi%2B2LcgSEmzm8Lp1blcaOhxHeuopacAAa33t3duWfqlXz%2B3K4A%2BMAQRQrJSUFKWkpCg3N1crV65kDCD8avt2acIEW1cwf5ygzyf17SvddJOdw8PdrTFYZWZKN9wgvfuu3b/%2BevtzrlrV3brgPwRAACViEgjclJMjffyxBZQvvih8vHFjmzRyzTVSkyaulRd0vv9euuwy27UlPFz617%2BkYcNY589rCIAASkQARKBIS5NefNHGBW7fbo/5fNJZZ1kQvPBCqXp1V0sMWNnZ0qOPSo88IuXmWrf6lCm2Qwu8hwAIoEQEQASa/fulDz%2B0pWRmzy58PDradhi5/HKb2MBOI2buXFtncdkyuz9okC3KzbqL3kUABFAiAiAC2bp11iL4%2BuvS2rWFjzdoYEFn0CCpUydvdnGuW2eTZ6ZMsfv16knPPSddcomrZSEAEAABlIgAiGCQlyd9842tK/jee9LOnYVfS0iwlsGLLpLOOCP0WwY3bZIef1x64QXpwAELv0OHWhdw7dpuV4dAQAAEUCICIILNgQPSjBnW8jVtWuH%2Bw5K1gvXvL51/vi19Eh3tXp0VbcUKm9QxcaKN%2BZOkXr2kJ5%2BU2rVztTQEGAIggBIRABHM9u2zMDh1qs0m3rWr8GtVq0pdu9oC1GefbfvfBlvrYHa29Mkn0ksv2WLa%2Bbp0kcaMsZAL/BkBEECJCIAIFQcPSvPmWRD8%2BGPbiu5QtWpJPXrY0bWrBcJAXBvvwAFpzhzpP/8p2t3t81nr5p132k4qXhz3iNIhAAIoEQEQoSotzVoHZ860LdCysop%2BvXp1qUMH6bTT7Nyune1V7O9Wwrw8aflyC31ffGEznzMzC7/esKE0ZIgt7ty0qX9rQ3AiAAIoEQEQXnDwoLRokQXBefOk%2BfOLdhfni4qSkpKkVq2kFi0sEDZtKiUmSvXrS2HHsMmq49j6hqtW2Xi%2Bn3%2B2fZJ/%2BOHwWurXl/7yF5vRy5I3KCsCIIASEQDhRXl50q%2B/SgsWWABbvFj66Sdp797iXxMeLsXH20STOnWk446zSSbVq0sREYUhLSfH1jLcs0fKyLDQt2WLtHFj8d%2B/WjWbwXzmmVKfPlLHjscWNuFtBEAAJSIAAiY3V1qzRvrlF%2BuSXbnSxhGuXWtLr%2BTlVczPadTIWheTkmwcYocOUps2gTkeEcGJAAigWCkpKUpJSVFubq5WrlxJAASOIidHSk%2BXNm%2BWtm61Vr2MDBtXuG%2BfTdzIzbXnhodLkZFSjRpSTIy1FsbF2Vi%2Bxo2tmxmoTARAAP/f3t2rNJNHARw%2BgcUgOijaKRFtA5ax9gqsRMTC29DG2iuId2BrZW0KSyEXoCDaiJYaEMP4sdWGXXizKfbdDMx5HphiMmE45S//mcxMZAUQoF7cPQAAkIwABABIRgACACQjAAEAkhGAAADJCEAAgGQEIABAMgIQACAZAQgAkIwABABIRgACY3W73Wi329HpdKoeBYDfyLuAgYm8CxigXqwAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEGquLMs4OjqKzc3NmJubi5WVlTg8PIynp6eqRwOgIgIQau79/T36/X6cnJxEv9%2BPi4uLuL29jZ2dnapHA6AingMICd3c3MTW1lY8Pj7G2traxO97DiBAvVgBhIReX1%2Bj0WjE4uJi1aMAUIE/qh4AmK6Pj484Pj6Og4ODsat5w%2BEwhsPhaP/t7W1a4wEwBVYAoWbOz89jfn5%2BtF1fX4%2BOlWUZ%2B/v78f39HWdnZ2PPcXp6GgsLC6Ot1WpNY3QApsQ9gFAzg8EgXl5eRvurq6sxOzsbZVnG3t5e3N/fx9XVVSwvL489x69WAFutlnsAAWrCJWComaIooiiKf3z2V/zd3d1Fr9f71/iLiGg2m9FsNv/PMQGokACEmvv8/Izd3d3o9/txeXkZX19f8fz8HBERS0tLMTMzU/GEAEybS8BQcw8PD7GxsfHLY71eL7a3tyeew2NgAOrFCiDU3Pr6evidB8Df%2BRcwAEAyAhAAIBkBCACQjAAEAEhGAAIAJCMAAQCSEYDAWN1uN9rtdnQ6napHAeA38iBoYKKfn58YDAZRFEU0Go2qxwHgPxKAAADJuAQMAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASEYAAgAkIwABAJIRgAAAyQhAAIBkBCAAQDICEAAgGQEIAJCMAAQASOZPOwIP9wXJHk0AAAAASUVORK5CYII%3D'}
Genus 2 curve data - 1176.b.16464.1