Genus 2 curve data - 256.a.512.1

Formats: - HTML - YAML - JSON - 2025-04-26T07:51:14.088418

• g2c_curves •

  Column	Type
  Lhash	text
  abs_disc	bigint
  analytic_rank	smallint
  analytic_rank_proved	boolean
  analytic_sha	smallint
  aut_grp_id	text
  aut_grp_label	text
  aut_grp_tex	text
  bad_lfactors	text
  bad_primes	integer[]
  class	text
  cond	bigint
  disc_sign	smallint
  end_alg	text
  eqn	text
  g2_inv	text
  geom_aut_grp_id	text
  geom_aut_grp_label	text
  geom_aut_grp_tex	text
  geom_end_alg	text
  globally_solvable	smallint
  has_square_sha	boolean
  hasse_weil_proved	boolean
  igusa_clebsch_inv	text
  igusa_inv	text
  is_gl2_type	boolean
  is_simple_base	boolean
  is_simple_geom	boolean
  label	text
  leading_coeff	numeric
  locally_solvable	boolean
  modell_images	text[]
  mw_rank	smallint
  mw_rank_proved	boolean
  non_maximal_primes	integer[]
  non_solvable_places	jsonb
  num_rat_pts	smallint
  num_rat_wpts	smallint
  real_geom_end_alg	text
  real_period	numeric
  regulator	numeric
  root_number	smallint
  st_group	text
  st_label	text
  st_label_components	integer[]
  tamagawa_product	smallint
  torsion_order	smallint
  torsion_subgroup	text
  two_selmer_rank	smallint
  two_torsion_field	jsonb

  
  {'Lhash': '2023392088972236524', 'abs_disc': 512, 'analytic_rank': 0, 'analytic_rank_proved': True, 'analytic_sha': 1, 'aut_grp_id': '[4,1]', 'aut_grp_label': '4.1', 'aut_grp_tex': 'C_4', 'bad_lfactors': '[[2,[1,2,2]]]', 'bad_primes': [2], 'class': '256.a', 'cond': 256, 'disc_sign': -1, 'end_alg': 'CM', 'eqn': '[[0,-1,1,1,-3,2],[1]]', 'g2_inv': "['742586','129623/4','-1521/8']", 'geom_aut_grp_id': '[8,3]', 'geom_aut_grp_label': '8.3', 'geom_aut_grp_tex': 'D_4', 'geom_end_alg': 'M_2(Q)', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['26','-2','40','2']", 'igusa_inv': "['52','118','-36','-3949','512']", 'is_gl2_type': True, 'is_simple_base': True, 'is_simple_geom': False, 'label': '256.a.512.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.1342091471846320562122093249902145220212570013682479272', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.180.3', '3.540.6'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 6, 'num_rat_wpts': 2, 'real_geom_end_alg': 'M_2(R)', 'real_period': {'__RealLiteral__': 0, 'data': '26.841829436926411242441864998', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, 'root_number': 1, 'st_group': 'E_4', 'st_label': '1.4.E.4.1a', 'st_label_components': [1, 4, 4, 4, 1, 0], 'tamagawa_product': 2, 'torsion_order': 20, 'torsion_subgroup': '[2,10]', 'two_selmer_rank': 2, 'two_torsion_field': ['4.0.256.1', [1, 0, 0, 0, 1], [4, 2], True]}
• g2c_endomorphisms •

  Column	Type
  factorsQQ_base	jsonb
  factorsQQ_geom	jsonb
  factorsRR_base	jsonb
  factorsRR_geom	jsonb
  fod_coeffs	jsonb
  fod_label	text
  is_simple_base	boolean
  is_simple_geom	boolean
  label	text
  lattice	jsonb
  ring_base	jsonb
  ring_geom	jsonb
  spl_facs_coeffs	jsonb
  spl_facs_condnorms	jsonb
  spl_facs_labels	jsonb
  spl_fod_coeffs	jsonb
  spl_fod_gen	jsonb
  spl_fod_label	text
  st_group_base	text
  st_group_geom	text

  
  {'factorsQQ_base': [['2.0.4.1', [1, 0, 1], -1]], 'factorsQQ_geom': [['1.1.1.1', [0, 1], 1]], 'factorsRR_base': ['CC'], 'factorsRR_geom': ['M_2(RR)'], 'fod_coeffs': [2, 0, -4, 0, 1], 'fod_label': '4.4.2048.1', 'is_simple_base': True, 'is_simple_geom': False, 'label': '256.a.512.1', 'lattice': [[['1.1.1.1', [0, 1], [0, 0, 0, 0]], [['2.0.4.1', [1, 0, 1], -1]], ['CC'], [1, -1], 'E_4'], [['2.2.8.1', [-2, 0, 1], [-2, 0, 1, 0]], [['2.0.4.1', [1, 0, 1], -1]], ['CC'], [1, -1], 'E_2'], [['4.4.2048.1', [2, 0, -4, 0, 1], [0, 1, 0, 0]], [['1.1.1.1', [0, 1], 1]], ['M_2(RR)'], [4, 0], 'E_1']], 'ring_base': [1, -1], 'ring_geom': [4, 0], 'spl_facs_coeffs': [[[-488, -256, 864, 464], [35520, 19232, -60608, -32800]]], 'spl_facs_condnorms': [1], 'spl_facs_labels': ['4.4.2048.1-1.1-a5'], 'spl_fod_coeffs': [2, 0, -4, 0, 1], 'spl_fod_gen': [0, 1, 0, 0], 'spl_fod_label': '4.4.2048.1', 'st_group_base': 'E_4', 'st_group_geom': 'E_1'}
• g2c_ratpts •

  Column	Type
  label	text
  mw_gens	jsonb
  mw_gens_v	boolean
  mw_heights	numeric[]
  mw_invs	smallint[]
  num_rat_pts	smallint
  rat_pts	jsonb
  rat_pts_v	boolean

  
  {'label': '256.a.512.1', 'mw_gens': [[[[-1, 2], [1, 1]], [[-1, 2], [0, 1], [0, 1], [0, 1]]], [[[-1, 1], [1, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [2, 10], 'num_rat_pts': 6, 'rat_pts': [[0, -1, 1], [0, 0, 1], [1, -4, 2], [1, -1, 1], [1, 0, 0], [1, 0, 1]], 'rat_pts_v': True}
• g2c_galrep •

  Column	Type
  conductor	integer
  lmfdb_label	text
  modell_image	text
  prime	smallint

  
  
  • id: 6
    {'conductor': 256, 'lmfdb_label': '256.a.512.1', 'modell_image': '2.180.3', 'prime': 2}
  • id: 7
    {'conductor': 256, 'lmfdb_label': '256.a.512.1', 'modell_image': '3.540.6', 'prime': 3}
• g2c_tamagawa •

  Column	Type
  cluster_label	text
  label	text
  p	bigint
  tamagawa_number	smallint

  
  {'label': '256.a.512.1', 'p': 2, 'tamagawa_number': 2}
• g2c_plots •

  Column	Type
  label	text
  plot	text

  
  {'label': '256.a.512.1', 'plot': 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zTwvffsrGHtFBYRL0hLs8GLtDTrfHDNNa4r8iYFQJ8JBKB/f7v9n/9A6dJu6xE3gqOBs2fbDvA//rCdwt262W46EZFQNXIkzJ0LMTEZGxnl9CkA%2Bsz48ZCUZMPlffq4rkZcq1/fvh969bKdwm%2B8ATVq2BpREZFQs24d9Otnt4cMgTJl3NbjZQqAPhIIwFNP2e1774VixdzWI6GhYEF4/nmYOhXOPdcWVV92GfTuDfv3Z//jJSYmEhcXR0JCQvb/5SIStgIBO91o71649FL1/MuqiEAgEHBdhOSOb7%2B1di%2BFCtmrqOLFXVckoWb3bgt%2Bb7xh9%2BPiYPRoiI/P/sdKTU0lNjaWlJQUYmJisv8BRCSsvPeebVrLnx8WLIALLnBdkbdpBNBHnn3Wrt26KfzJiUVH2ykiX31lZwovWWLTxP/3f9YzUkTEhS1bbN062Dp2hb%2Bs0wigT/zyC9SpA3nzwqpVcM45riuSULdtm023fPKJ3a9Xz04Tya7zojUCKCKZ1aGDnfhRs6ZtAMmXz3VF3qcRQJ8YNsyu7dsr/EnmFC9uT7jvvguxsfDTT9Zp/9VXbS2OiEhu%2BPxzey7KkwfeekvhL7soAPrAH3/YDw/Y%2Bi6RzIqIgE6d7Ezhyy6zo5e6d7e%2BW8nJrqsTkXC3Y4fNRIAdX3rxxW7rCScKgD7w6qu2fqthw5xZzC/hr3x5%2BO4767wfFQUTJkD16jpKTkRyVq9e9mKzalUdXJDdFADD3KFD8Nprdvvee93WIt4WGWkjyPPm2TqcbdvsKLlu3WDPHtfViUi4%2BfJLW4ISGQlvv20N7CX7KACGuS%2B%2BsFdPpUrBdde5rkbCQbVqth7wwQczmkfXqmXHC4qIZIcdO%2BCuu%2Bx2797WjUCylwJgmHv1Vbvefrv1ThLJDlFR1oX/%2B%2B9tenjVKmvMOmCA2sWISNbddx9s3mztXgYOdF1NeFIbmDC2Zg2cd56N0qxebac8iGS3XbugRw/44AO7X7%2B%2BTdtUqnTqz1MbGBE5kc8/txmryEiYM8daUEn20whgGHvrLbu2aKHwJzmnaFEYM8beYmNtKrhWLfv%2B08tLETkdW7fCnXfa7b59Ff5ykgJgmEpPtyO8AG67zW0t4g8dO9rxTE2a2Fmdt98ON9wA27e7rkxEvCAQsDZTW7faWuMBA1xXFN4UAMPUtGmwfr2NyLRt67oa8YtzzoEpU2DwYGvWOm4c1KhhLWRERE7l/fftOSNvXhvAiIpyXVF4UwAMU%2B%2B9Z9f27bV1XnJXnjzw0EM2FXzBBdaIvGVLeOABOHgQOHwYPvrI5ncAfv3Vab0i4shvv8Gjj8J997H9hXfp3fMgYGf91q7tuDYf0CaQMHTgAJQsCampMH06NG7suiLxq337LPi98ordv6bKcj7Z25r8m9aQCsQCKUBMu3a2iFBb1UXCX1qarU0KrlP6n02U4aFqXzNqfk3y5nVUm48oAIahceOgXTtrz7F2re2kEnHpq6/gjq5pzNp2AZVYBXBsAARLiv/9r7siRSR3DBxow3wncKREafKuX62pq1ygaBCGPvrIrh06KPxJaLj6alg2ZPzR8HdCr7%2BuI0VEwt2hQ5CYeNI/zrt1c8YvMclRGmTNgkAgwO7du12XcYx9%2B%2Bz4HICrrrJpYJFQkD5/Kn/9dkz925XUVDtnTqe9i4Sv33%2BHLVtO/TEzZ%2Bba0VXR0dFERETkymOFGk0BZ0Gwka2IiIh4j58b0SsAZkFwBDAhIYG5c%2Bfm%2BONl5nHuuAPGjoV77oGnn865x8mq1NRUypcvz4YNG3L0hy%2BU/m/8/jiHFi8mf4MGR%2B%2BnAuWBDdgawJX54tj73Q/UqpWtDwt4%2B9/NxWPk1uPk1vMAhNe/W249To49RsuW8PPPJ//z77%2BH%2BPhsf9gTfT1%2BHgHUFHAWREREEBMTQ548eXLlFcQ/Pc6hQ/Dtt3a7Y0c405Jy6%2BsBiImJydHHCpX/Gz0OcMkl9grljTeOeXcMUIg8PH74Ob5rEcNTT0GfPtZOJrt4%2Bt/NwWPk5uNAzj8PQPj9u3n5e23Xo0Mo1LYl%2BTl8/B%2B2bw%2BXXZbtjwm5%2Bz3tBXkGDFCv7exQt25d54/z/ff2u7VkSXj%2BeTsDOCceJzscPHiQwYMH88gjjxCVw90%2BQ%2BH/Ro/zP1dfbV1eFy/m4N69DAb6VqtG2ohRTEhvzeLF1jR6%2BnRo3twamWcXT/%2B7OXiM3Hic3HwegPD5d8vNx8nuxwgEoP2D5/LmikbUKricUkc2ApB%2B1llE9O4NL76Yva/%2B/ia3/m%2B8QFPAYeTee2HkSBtkef1119WcWnD9pJ/XX/jaoUP8MWsWZZs3Z8OGDZQrV45AAN5%2BG%2B67z46Si42FV1%2B13ewSnvQ84D8jRtjPeFSUzQJXjFxE/erV%2BeHPP4n5179cl%2BcrahISJgIB67UGcM01bmvJjKioKPr3758rr/olBOXPT77q1QGOfg9ERFhv2KQkOwA%2BJQVuugk6d7bbEn70POAvSUm2vAPguefsmMj8lStzY//%2BRGlDZa7TCGCYWLIELrrIXlVt3w6FC7uuSOTUTjX6c/gwPPWUbWRKT4cKFex4w0svdVSsiGTJ3r22r2P5chuk%2BOKLrC1TkqzTCGCY%2BPpruzZtqvAn3pcvnx0WMHMmVKwI69ZBkybQr5%2BFQxHxlp49LfyVKQNvvaXwFwoUAMPEN9/Y9Yor3NYhkp0aNLBpoy5dbCTwmWfsfcuXu65MRDLr3XfhnXfsZKoxY6B4cdcVCSgAhoV9%2B2ykBBQAJfzExMCoUfDxx3DWWXZYSO3a8PLLtvZVRELXsmVw9912u39/G8mX0KAAGAZmzLAegOecAxdc4LoakZxx442wcKG1h9m/H3r0sLVEf/7pujIROZF9%2B%2Bzndu9eaNbMlnBI6FAADANTpti1RYvQWlcRCAQYMGAAZcqUoWDBgjRt2pTFixef8nMGDBhARETEMW%2BlSpXKpYol1JUtC5MmwbBhtuFpwgSoXh3Gj3ddmZzMSy%2B9RMWKFSlQoADx8fHMDE5XnMCoUaOO%2B/mPiIjgwIEDuVixZJd774VFi6w37fvvH9veb8aMGVxzzTWUKVOGiIgIPv/8c3eF%2BpQCYBgIBsDmzd3W8XdDhgxh2LBhjBw5krlz51KqVClatmzJ7t27T/l5F110EZs3bz76tnDhwlyqWLwgMhLuv9%2BmgmvUgK1b4dproVs32LPHdXXyVx999BG9evWiX79%2BzJ8/n0aNGtG6dWvWr19/0s%2BJiYk55ud/8%2BbNFChQIBerluwwapRt9giu%2B/v76/i9e/dSs2ZNRo4c6aQ%2BAQLiadu3BwIREYEABAKbN7uuJkN6enqgVKlSgcGDBx9934EDBwKxsbGBV1555aSf179//0DNmjVzo0RxLCUlJQAEUlJSzvjvOHAgEOjTJ%2BNn4PzzA4E5c7KxSMmSunXrBrp3737M%2B6pWrRp4%2BOGHT/jxb7/9diA2NjY3SpMctGBBIFCwoP1MDhz4zx8PBD777LOcL0yOoRFAj5sxwxbCV616/Cssl9asWUNycjKtWrU6%2Br6oqCiaNGnCnDlzTvm5K1eupEyZMlSsWJGbbrqJ1atX53S54lFRUdZQ9vvvbQ3sqlXWK/Cxx9QuxrVDhw7xyy%2B/HPMcANCqVatTPgfs2bOHChUqUK5cOa6%2B%2Bmrmz5%2Bf06VKNkpNhXbtbJ3u5Zdr3V8oUwD0uOnT7dq0qdMyjpOcnAxAyZIlj3l/yZIlj/7ZidSrV4/Ro0fz7bff8vrrr5OcnEyDBg3Yvn17jtYr3ta0KSxYAJ06WbuYp5%2BG%2BvVh6VLXlfnXtm3bSEtLO63ngKpVqzJq1CjGjx/PBx98QIECBWjYsCErV67MjZIliwIB6NoVVq6E8uWteXukUkbI0n%2BNxwXXUzdu7LaO999/nyJFihx9O/y/4ZeIv%2B1KCQQCx73vr1q3bk27du2oXr06LVq0YMKECQC88847OVe8hIXYWOs39vHHcPbZ8OuvcPHFMHy4hUJx43SeA%2BrXr0%2BnTp2oWbMmjRo14uOPP6ZKlSqMGDEiN0qVLBo6FMaNs0buY8eq31%2BoUwD0sN27ITg70qiR21ratGlDUlLS0bfi//vJ//sr/S1bthw3InAqhQsXpnr16hoBkEwLtou5/HI4cAB69YKWLeEU%2Bw4kBxQvXpw8efJk6TkgMjKShIQE/fx7wNSp8PDDdnv4cDvPW0KbAqCH/fSTjWycey6UK%2Be2lujoaCpVqnT0LS4ujlKlSjF58uSjH3Po0CGmT59OgwYNMv33Hjx4kKVLl1K6dOmcKFscSExMJC4ujoSEhBx7jDJlYOJEeOklKFjQ1ghWr24jhGoenTvy589PfHz8Mc8BAJMnT870c0AgECApKUk//yFuwwbo0AHS0qBzZ%2Bje3XVFkimON6FIFgwYYLusbr7ZdSUnNnjw4EBsbGxg3LhxgYULFwY6duwYKF26dCA1NfXoxzRr1iwwYsSIo/cfeOCBwLRp0wKrV68O/Pjjj4Grr746EB0dHVi7dq2LL0FyUHbsAs6MFSsCgfr17WcFAoHrrw8EtmzJ0YeU//nwww8D%2BfLlC7z55puBJUuWBHr16hUoXLjw0Z/nzp07H7MjeMCAAYFvvvkmsGrVqsD8%2BfMDXbt2DeTNmzfw008/ufoS5B/s3x8IJCTYz1atWoHA3r2Z%2B7zdu3cH5s%2BfH5g/f34ACAwbNiwwf/78wLp163K2YDkqr%2BsAKmfuhx/sehoDarmqb9%2B%2B7N%2B/nx49erBz507q1avHpEmTiI6OPvoxq1atYtu2bUfvb9y4kY4dO7Jt2zZKlChB/fr1%2BfHHH6lQoYKLL0HCQOXKtlb22WdhwABbozRzJrz%2BuvUPlJzToUMHtm/fzsCBA9m8eTPVqlXj66%2B/PvrzvH79eiL/sktg165d3HnnnSQnJxMbG0vt2rWZMWMGdevWdfUlyCkEAtCzJ8yda8c0jhsHhQpl7nPnzZvHZZdddvR%2B7969AejSpQujRo3KgWrl7yICAU2IeFF6OhQrBrt2WUPc%2BHjXFYmcntTUVGJjY0lJSSEmJiZXHjMpyaaoFi2y%2B126wAsvQNGiufLwImHlpZcsAEZG2pKLv3X8kRCnNYAetXKlhb8CBew0BBH5Z7Vq2Qumvn3t2MR33rG1gX9bpiYi/2DGDPjPf%2Bz2oEEKf16kAOhRP/9s14svti33IpI5UVE2HTxzJpx/PmzcaL%2B87r5bR8mJZMa6dXDDDXDkCNx0Ezz4oOuK5EwoAHrU3Ll21dIYkTPTsCH89hvcc4/df%2BUVG00PNlcXkePt3Qtt29oZ3LVrw5tv2mi6eI8CoEfNm2fXOnXc1iHiZYULw4gR8N13dpTcmjV2qkivXrBvn%2BvqREJLejrcequtpS1RAj77LPObPiT0KAB6UFqajVyANn%2BIZIfmza159B132P3hw6FmTZg9221dIqFk4ED45BNbdjRuHKg5g7cpAHrQsmU2OlG4sLW4EJGsi4mx1jATJ0LZsvD773bCTu/eGg0U%2BfhjePJJu/3KK3DppW7rkaxTAPSgpCS71qoFefK4rUUk3FxxhbWJ6drV%2Bpw9/7z9rM2a5boyETfmzrWWSWAviG67zW09kj0UAD0oGABr1nRbh0i4KloU3noLJkyw0cCVK6FxY1sbuHev6%2BpEcs%2BGDdCmjZ2rfdVVMGSI64okuygAelBw/V%2BtWm7rEAl3V1557GhgcG2gdgqLH%2BzeDVdfDcnJUK0ajBmjWadwogDoQQsW2FUNoEVyXnA0cOJEKFcOVq2yncI9etgvSJFwFOzxt2ABlCwJX31l62QlfCgAeszWrfDnn3b7oovc1iLiJ1dcAYsXw5132v2XX7ZRkW%2B/dVuXSHYLBGy5w9dfQ8GCMH68dvyGIwVAj1m82K4VK0KRIm5rEfGbmBh49VXrG1ixIqxfb8Gwa1fYscN1dSLZ4/nnITHRGjy/954OHAhXCoAeEzzEvlo1t3WI%2BFmwb%2BB999kvyVGjbET%2B009dVyaSNZ98An362O3nnoPrr3dbj%2BQcBUCPWbLErpr%2BFXGrcGHbFDJ7Nlx4oS2Uv%2BEG%2B4X5xx%2BuqxM5fbNnQ6dONgXcs6e1fJHwpQDoMUuX2vXCC93WIXKmEhMTiYuLIyEhwXUp2eKSS%2BDXX6FfP8ib147HiouDN96wX6QiXrBsmbV7OXjQrsOH64zfcBcRCOgpyktKl7aRhp9%2B0roM8bbU1FRiY2NJSUkhJky2Fy5YALffnnFWd9Om8NprOrFHQtvmzfZCZt06qFcPvv9eZ/z6gUYAPSQlxcIfQNWqbmsRkePVqAE//ABDh9ov0GnToHp1GDQIDh92XZ3I8VJTrd/lunVQqRJ8%2BaXCn18oAHrIihV2LVVK/Zj/XTdwAAAgAElEQVREQlXevLZ2atEiaNnSptQefRTi423kXiRUHDwI111np0v961/wzTdQooTrqiS3KAB6SDAAVqnitg4R%2BWcVK1qPwNGjoVgx2zV8ySW2czg11XV14ndpadC5s033Filijc7PP991VZKbFAA9ZOVKu2o9kYg3RETYL9lly%2BwaCMCIEbZJ5LPPXFcnfhUIwL33wtixkC%2BffS9efLHrqiS3KQB6yO%2B/27VSJbd1iMjpKV7cRgInT7ZRlk2brF1M27awYYPr6sRvBgywk2yCjZ5btHBdkbigAOghq1bZVQFQxJtatLCp4EcftbWCX3xho4EvvGBnr4rktBdfhIED7fbIkdC%2Bvdt6xB0FQA9Zvdqu553ntg4ROXMFC8LTT8P8%2BdCgAezZA/ffb22d5s51XZ2Es9Gj4T//sdsDB0KPHm7rEbcUAD1izx7YssVuKwCKeF%2B1ajBzpvUJPOssC4T16sE998CuXa6rk3Dz%2Bedw2212u1cveOwxt/WIewqAHrFunV2LFrU3EfG%2ByEjo1s02iQSP4EpMtJN%2BPvhAJ4lI9pg8GTp0sJ2/t95qfSp1yocoAHrE2rV2Pfdcl1WISE7417/g3XdhyhRr85ScDDffDK1aZbR/EjkTs2bZZqNDh6BdO3j9dXvhIaJvA48IjgBWqOC2DhHJOc2a2XFyAwdCVBR8952dJPLEE7B/v%2BvqxGvmzYOrroJ9%2B%2BCKK2DMGNt8JAIKgJ4RDIDnnOO2DhHJWVFR8PjjsHix/dI%2BdAieegouugi%2B/tp1deIVCxbYCHJqKjRpAp9%2BCvnzu65KQokCoEcEe4VpBFDEH84/3wLf2LFQtiysWWOjOdddl/GCUOREli61lkM7d0L9%2BjrfV05MAdAjNm60a7lybusQkdwTEQE33GCbRPr0sem7zz%2B3TSKDBtnooMhfrVwJzZvD1q12usfEiRAd7boqCUUKgB6hACjiX0WKwHPPWauYxo1tPeCjj0KNGrZOUASsV2yzZrB5s60dnTRJXSPk5BQAPSAQsKOjwKaCRMSfqlWDadOsoW/JkrB8ObRsaS0%2Bgi8SxZ/WroXLLrPvgwsvtBcGxYq5rkpCmQKgB2zfnjHVU7q021pExK2ICOjc2cLfvfdaS4%2BPP4aqVWHIEE0L%2B9G6dRb%2B1q%2B3NkLff2%2BthURORQHQA/74w67Fi9sOQREvS0xMJC4ujoSEBNeleFpsrJ3r%2BssvdqTc3r3w0ENQq5YFAPGH9est/K1da%2BfET50KpUq5rkq8ICIQUK/5UDdpElx%2Bua3pWLDAdTUi2SM1NZXY2FhSUlKIiYlxXY6npafbtHDfvrb4H6B9ezvxQeuGw9eGDdC0qa39O/98Wx6g/2/JLI0AekBysl31qk5ETiQy0o74WrHCzhLWtHD4W78%2BI/ydd56N/Cn8yelQAPQABUARyYyiRWHEiOOnhWvW1G7hcPL38DdtGpQv77oq8RoFQA/YssWuWtQrIplRqxbMnAmjRtnzxrJltlu4fXvtFva6dess/K1ZkzHtq/AnZ0IB0AMUAEXkdEVGQpcux%2B4WHjtW08JetmaNHeu2Zo1t%2BFD4k6xQAPSA4KLuEiXc1iEi3lO0qO0W/vVXaNjw2Glh7Rb2jtWrbeRv3TqoXFkbPiTrFAA9QAFQRLKqZs3jp4WbN4ebbspoNSWh6fffbeRv/Xq44AILfzoUQLJKAdADtm%2B3a/HibusQEW%2BLiMiYFg7uFv7oIwsVw4bB4cOuK5S/W77cwl/whI%2BpU6FMGddVSThQAPSAYADUsT4ikh2Cu4XnzYN69WDPHnjgAYiPh9mzXVcnQUuX2rTvH3/ARRdZ%2BNNpUJJdFABD3KFDsHu33T77bLe1iEh4qV0b5syB11%2B355eFC%2BHSS%2BGOOzJeeIobixdb%2BEtOhho1LPyVLOm6KgknCoAhbteujNtFi7qrQ0TCU2SkBb7ly%2BG22%2Bx9b75pu4VHjQKdFZX7Fi604922bMk42k9rwCW7KQCGuJ077RoTA3nyuK1FRMJX8eIW/GbNgmrVYNs26NoVmjWzcCi547ff7N9861a4%2BGKYMkXLfyRnKACGuJQUu2r0T0RyQ8OG1jLm2WehYEHbcVqjBgwcqN6BOe2332xn9rZtkJBgp7do6Y/kFAXAEBecAlYAFJHcki8f9O0LS5ZA69YW/Pr3tzWDP/zgurrwFBz5274d6taFSZPgrLNcVyXhTAEwxAVHAGNi3NYhIv5z7rkwYQKMGWNr0JYssRHCXr2sobRkjwULbORvx46M8KcX/ZLTFABDXHAHsAKgiLgQEQEdO1pLki5dbFPI8OE2LTxtmuvqvG/xYgt/27fbtO%2BkSRAb67oq8QMFwBCXmmpXBUARcalYMdsV/M03dv7s6tW2U/W%2B%2B2DfPtfVedPy5Rlr/uLjFf4kdykAhrjgCGCRIm7rEMkuiYmJxMXFkZCQ4LoUOQOXXw6LFsGdd9r9ESNsbeDcuW7r8pq1ay38/fmnHdOnaV/JbQqAIW7PHrsqAEq46NmzJ0uWLGGuEoNnxcTAq6/aaGCZMrBiBTRoAE8/DWlprqsLfZs3Q4sWsGmTHe82ebJ2%2B0ruUwAMccGF1gqAIhJqLr/cmha3bw9HjsBjj1mw%2BeMP15WFrl274IorYNUqqFjRWr2oybO4oAAY4oJrawoVcluHiMiJnH02fPihrQ8sXNg2htSqZQ2M5VgHD8J119mu35IlbeSvTBnXVYlfKQCGOAVAEQl1ERG2Q/jXX20929at0KqVNZPWUXImEIDbb7eAHB1t0%2Bfnn%2B%2B6KvEzBcAQt3%2B/XQsWdFuHiMg/qVLFGkV37Qrp6fDww9CpExw44Loy955%2BGt5/H/LmhU8/tVFSEZcUAEOcAqCIeEnBgnam8EsvWdgZM8bWBe7Y4boyd776Ch5/3G4nJkLLlm7rEQEFwJB38KBdo6Lc1iEiklkREXD33fDtt9bXbvZsaNTIn5tD1q2Dzp3tdo8eGe1zRFxTAAxxCoAi4lXNmsGsWVC2rB0j17SptUDxi7Q0mwLftcuOeHv%2BedcViWRQAAxxhw7ZVQFQRLyoWjWYORMqVICVK236c%2BdO11XljuHDLQBHR9tO6fz5XVckkkEBMMQFA2C%2BfG7rEBE5UxUrwtSp1vJk8WK48UbrGxjONm2CJ56w20OH2r%2BBSChRAAxxhw/bVa8cRcTLKlaEr7%2B2XoFTpsCAAa4rylmPP26N/Bs0sPYvIqFGATDEBV8l583rtg4RkayqWdN2CAMMGgTz5rmtJ6esXQujR9vtoUMhUr9pJQTp2zLEBQNgnjxu6xARyQ4dOkDHjtYnsFev8GwU/cortgGkRQuoX991NSInpgAY4oIHq2sEUHJKIBBgwIABlClThoIFC9K0aVMWL158ys8ZMGAAERERx7yVKlUqlyoWrxve5VfGRnZg4uxo0gsVhrZtrYN0GAgE4IMP7Hb37m5rETkVBcAQl55u14gIt3VI%2BBoyZAjDhg1j5MiRzJ07l1KlStGyZUt27959ys%2B76KKL2Lx589G3hQsX5lLF4mmTJlHi2gbckP4x0ewhz4F98MUX0LgxfPaZ6%2BqybMUKWL/eOjdceaXrakROTgEwxAUDoKaAJScEAgFeeOEF%2BvXrx/XXX0%2B1atV455132LdvH2PGjDnl5%2BbNm5dSpUodfStRokQuVS2elZ5uw2LBBqd/deSIdY8Otj7wqF9/tWt8vE5wktCmAOgRGgGUnLBmzRqSk5Np1arV0fdFRUXRpEkT5syZc8rPXblyJWXKlKFixYrcdNNNrF69%2BpQff/DgQVJTU495E5%2BZPh3WrDn5n//5J0ycmHv15IANG%2Bx6/vlu6xD5JwqAIj6WnJwMQMmSJY95f8mSJY/%2B2YnUq1eP0aNH8%2B233/L666%2BTnJxMgwYN2L59%2B0k/Z9CgQcTGxh59K1%2B%2BfPZ8EeIdf/75zx9ziu87Lwie3164sNs6RP6JAqCIj7z//vsUKVLk6Nvh/zWajPjbEHMgEDjufX/VunVr2rVrR/Xq1WnRogUTJkwA4J133jnp5zzyyCOkpKQcfdsQHCoR/6hSJXs%2BJoRFR9t11y63dYj8E%2B0tDXHB38HBtYAiWdGmTRvq1at39P7B/63FSk5OpnTp0kffv2XLluNGBU%2BlcOHCVK9enZUrV570Y6KioojSmYb%2BdvHFkJAAc%2Bee%2BM%2BrVrUDgz0seOLHsmVu6xD5JxoBDHEKgJKdoqOjqVSp0tG3uLg4SpUqxeTJk49%2BzKFDh5g%2BfToNGjTI9N978OBBli5dekyIFDmhd9%2B1M%2BH%2BrkQJOzDX4wue69a164IFcIoVESLOKQCGuODuXwVAyQkRERH06tWLZ555hs8%2B%2B4xFixZx6623UqhQIW6%2B%2BeajH9e8eXNGjhx59H6fPn2YPn06a9as4aeffuKGG24gNTWVLl26uPgyxEsuuIBFHyykL0OYRhP2xTeCp56CRYvsqBCPK1sWatSw5%2BxPP3VdjcjJaQo4xAUDYLAhtEh269u3L/v376dHjx7s3LmTevXqMWnSJKKDi5mAVatWsW3btqP3N27cSMeOHdm2bRslSpSgfv36/Pjjj1SoUMHFlyAekpYGdz1yNnN4kHXtH6TpR64ryn6dO8ODD8LIkdCtm%2BcHNSVMRQQC4XgQT/ioVAlWrYLZs%2B1QcZFwkZqaSmxsLCkpKcTExLguR3LJU0/BE09AkSKweDGcc47rirLfzp32de3ZA598Au3aua5I5HiaAg5xwSPggmcCi4h41eefQ//%2BdnvkyPAMfwBnnWXnHAP07QsHDritR%2BREFABDXL58dvV4c3wR8blp06BjRzsr9%2B67IdyXi/bta3tdVq%2BGJ590XY3I8RQAQ1z%2B/HZVABQRr5o6Fa66ykbCrrkGXnzRdUU5LzoaEhPt9pAhtoxHJJQoAIa4YNs0BUAR8aLPPoPWrWHfPmjVCj7%2BOGNpS7hr29Y2hKSn2%2Bin2sJIKFEADHHBEcATnZ0uIhKqAgF44QXbAHHwIFx7LXzxBRQo4Lqy3DVyJFSubGcEd%2Byo9dwSOhQAQ1zwyVKLiEXEKw4csPYn999vQfCuu2w3rN/CH0BMjPUDLFQIJk%2BGBx5wXZGIUQAMcQUL2lUBUES8YN06aNwY3nwTIiPhv/%2BFl1/2z7TviVSvDqNH2%2B0XX7RRQRHXFABDXDAA7tvntg4RkX8yfjzUrm1H/Z59Nnz9tY14qRGyTYU/84zdvu8%2BGDfObT0iCoAhrlAhuyoAikio2r/fQs2111oT5IQE%2BOUXuPxy15WFlocftunwQABuvtl2R4u4ogAY4hQARSSUJSVZ4Bsxwu7ffz/MmgXnnuu0rJAUEWHTv9ddZxtj2rSBn392XZX4lQJgiCtSxK579ritQ0Tkr44csSnNunXtSLeSJW3Kd9iwjO4Fcry8eWHMGGjWzJ7Xr7gCFixwXZX4kQJgiFMAFJFQs2QJNGwI/frB4cPW727hQuv3J/%2BsQAFriVO/vk2Zt2hh/6YiuUkBMMRFR9t19263dYhkl8TEROLi4khISHBdipymw4dt1K92bZu6jI2Fd96xDQ0lSriuzluKFIGJE%2BHii2HrVmjeHJYvd12V%2BIkCYIhTAJRw07NnT5YsWcLcuXNdlyKn4ZdfbLq3Xz87meiqq2DRIrjlFu3yPVNFi8KkSVCzJiQnw2WXwYoVrqsSv1AADHExMXZNSXFbh4j409690KePhb%2BkJGvvMno0fPkllCvnujrvK1bMGkRXqwabN0PTpgqBkjsUAENcbKxdU1Pd1iEi/jNxogWToUPtPNubboKlS%2B18W436ZZ8SJeD7748NgZoOlpymABjiiha1665dbusQEf/44w9o3x6uvBLWroVzzoGvvoIPPoB//ct1deHpRCFw2TLXVUk4UwAMccERQAVAEclpaWnWp%2B7CC2HsWMiTB3r3tjYvV13lurrwFwyBNWrYmsCmTbU7WHKOAmCIO%2Bssu%2B7dawuvRURyws8/2zq/e%2B%2B1JSd168K8eTb9G2xHJTmvRAmYMsU2hvz5p4XARYtcVyXhSAEwxAWngMH6RYmIZKcdO6B7d%2BtJ9%2Buv9pzz8sswZw7UquW6On8qXtxGAoMtYpo2hd9%2Bc12VhBsFwBCXJ0/GKOCOHW5rEZHwkZ4Ob78NF1wAr75q59N27mzrzrp3t%2Bcecefss%2BG776BOHdi%2B3U4OmT/fdVUSThQAPeDss%2B26fbvbOkQkPCQlQaNGcNttsG0bxMXBtGnW3qVkSdfVSdBZZ1mLmHr1bACgWTOblhfJDgqAHlC8uF23bnVbh4h4265dcN99EB9vU7yFC8Nzz1kgbNLEdXVyIsFm0ZdcYv9/LVrYek2RrFIA9IDgEUvbtrmtQ0S8KT3djmy74AIYMcLut29v0719%2BkC%2BfK4rlFOJiYFvv4VLL7VDAVq2hB9/dF2VeJ0CoAcEA6BGAEXkdCUlQePGcOutsGULVK1q04offaSTPLwkOtoaczdubLu0W7WyUVyRM6UA6AHBNTl//um2DhHxjl27rKVLfDzMnm3TvYMH227SFi1cVydnokgR%2BPpr2xW8ezdcfrlCoJw5BUAPCHbe37LFbR0iEvrS02HUKKhSxZo6/3W696GHIH9%2B1xVKVhQubKeyXHYZ7NmjEChnTgHQA0qVsmtysts6RCS0JSXZOrGuXW3JSNWq1kpE073hJRgCmzVTCJQzpwDoAcEpYAVAETmRnTszpnt/%2BMECwpAhNt3bvLnr6iQnFCoEX36ZEQKvuEIbQ%2BT0KAB6QOnSdt282W0dIhJa/rq7Nzjd26EDLF8ODz6o6d5wFwyBl12WsSZQLWIksxQAPaBMGbumpNiZwCJelpiYSFxcHAkJCa5L8bTffsvY3Ruc7p0yBT78EMqWdV2d5JZgCGzSJGN3sJpFS2ZEBAKBgOsi5NQCAdv9tW8frFgBlSu7rkgk61JTU4mNjSUlJYWYmBjX5XhGSgr075/Rz69wYXjiCejVSyN%2BfrZnD7RuDbNm2Qki33%2Bvs5zl1DQC6AERERkLuDdudFuLiLgRCMCYMTbSN3y4hb8bb4SlS6FvX4U/vwu2iLnkElsT2qIFLFrkuioJZQqAHqEAKOJfS5faZo5//9s2g1WubCdDfPwxlC/vujoJFcFm0XXq2NnxLVrYelCRE1EA9AgFQBH/2bcPHnkEataEqVOhQAF46ilYuNDWeon8XWysvTioWdMOD2jeHFavdl2VhCIFQI845xy7rl/vtg4RyR1ffglxcXZ6x%2BHDcM01sGQJPPYYREW5rk5C2dln23F/cXGwaZOFQA0eyN8pAHpEhQp2XbfObR0ikrPWrYNrr4U2bez2OefA55/D%2BPFQsaLr6sQrSpSwJuCVKsHatTYdrNOk5K8UAD0iGADXrnVahojkkMOH4bnnbNRm/HjIm9eObluyxAKhyOkqXdpCYPnythawVSs7I1oEFAA949xz7bpune0GFJHwMWeOneLRt6%2Bt%2B2vUyI51GzzY2ryInKkKFaw/ZMmS1jvyqqvUT1aMAqBHnHOOtYPZt0/D%2BCLhYudO6N4dGja0jR3FisFbb8H06XDRRa6rk3BRuTJMmgRFi9qLjXbt4NAh11WJawqAHhEVlbETeM0at7WISNb8taffq6/a%2B267DZYtg65d7cWeSHaqUcP6BBYqZLuEO3WCtDTXVYlLCoAect55dl21ym0dInLmVq%2BGK66wnn5btlgInD4d3nwTihd3XZ2Es0susQ1F%2BfLB2LHQs6eWFPmZAqCHnH%2B%2BXX//3W0dInL6Dh%2BGZ5%2B1qd1Jk2xUf%2BDAjDN9RXJDy5bw/vs2yvzqq3asoPhTXtcFSOZVqmRXBUARb/n5Z%2BjWDRYssPvNmsErr%2Bhcb3HjxhvtpJC777bG4iVL2mig%2BItGAD0k%2BMti5Uq3dYhI5uzZA716Qf36Fv6KFYNRo6w1h8KfuNS9Ozz5pN2%2B916bEhZ/UQD0kCpV7LpihdZtiIS6r7%2B26d7hw%2B3n9d//tjN9u3TRJg8JDY8/Dj162Pdnp04wbZrriiQ3KQB6SOXK9otj507Yts11NSJyIlu3ws03W7%2B19euth%2Be338J779npDCKhIiICXnwRrr/e2sK0bWvtiMQfFAA9pGDBjBNBli51W4uIHCsQgHffhQsvhA8%2BgMhI6N0bFi2yExhEQlGePLYppFEjSEmB1q11brBfKAB6TNWqdl22zG0dImcqMTGRuLg4EhISXJeSbdavtxG/W26xxfU1a8JPP8HQoTrJQ0JfgQLWHubCC2HTJguBKSmuq5KcpgDoMRdeaNclS9zWIXKmevbsyZIlS5g7d67rUrIsPR0SE22t38SJ1trl6adh7lyoU8d1dSKZd/bZ9j1cqpSNWuu0kPCnAOgxweOhFi92W4eI361YAU2awD332G7fhg3t/N5HH7VGuyJeU6ECTJhgo9ZTpsBdd2nDYThTAPSYYABctMhtHSJ%2BdeQIPPecTfPOmmW/LEeMgBkzMpZoiHjVxRdbS5g8eaxl0dNPu65IcooCoMcEA2Bysq01EpHcs3ixjfT17QsHDtipCosW2ShgpJ5NJUy0bg0jR9rtxx%2B3TU0SfvSU5THR0dZWArRdXyS3HD5sIyEXX2ynesTG2tm9336b8fMoEk66d4cHHrDbXbvCnDlu65HspwDoQTVq2PW339zWIeIHCxfaSR6PPWaL4q%2B%2B2kYCb7tNDZ0lvD37rPUGPHjQrmvWuK5IspMCoAfVqmVXBUCRnHP4sJ2TGh8Pv/4KZ51lff7Gj4eyZV1XJ5Lz8uSxBua1a1uD82uugdRU11VJdlEA9KBgAExKcluHSLgKjvo98YQFwWuvtdZLnTpp1E/8pXBhe9FTurSNfHfsCGlprquS7KAA6EHBALhokfo0iWSnI0fgmWcyRv3OPttGQD77zPqjifhRuXIWAgsUsDOu%2B/Z1XZFkBwVADzr3XJuOOnxY7WBEssuSJdCgAfTrZz9bbdrYz9e//61RP5E6deCdd%2Bz2sGEZt8W7FAA9KCLCdiMCzJvnthYRr0tLg//%2B136m5s6FokVh9Gg7Gqt0adfViYSO9u2tLQzAnXfCDz%2B4rUeyRgHQo4LHTCkAipy5lSvtNI8HH7SdjldeaeucOnfWqJ/IiQwYANddZ8uPrr/ezg4Wb1IA9Ki6de36889u6xDxouAZvrVqwezZ1l/zjTfgq6%2BgTBnX1YmErshIGyGvVs0OJLj%2BemuKLt6jAOhRwQC4aBHs2%2Be2FhEv2bABLr/cTu/Ytw%2BaNbNdv7ffrlE/kcwoUgS%2B%2BMI2Sf38M9x9t84M9iIFQI8qW9ZGKtLSNA0skhmBQMbIxXffQcGCdobv5MlQoYLr6kS85bzz4KOPbERw1Ch46SXXFcnpUgD0qIgI61MGWogr8k%2B2boV27aBLF2tkW6%2Be9dHUGb4iZ65FCzstBKBXL5g1y209cnr01OdhDRrYVWc0ipzc%2BPE26vfZZ5Avn53pO2sWVKniujIR73vgAejQwXpo3ngj/PGH64oksxQAPeyvAVDrL0SOlZpq6/quvRa2bIGLLrL1So8%2BCnnzuq5OJDxERMCbb2ZsCrnxRh1Q4BUKgB4WH2%2Bd2bdtg%2BXLXVcjkjmJiYnExcWRkJCQY48xa5bt8H3rLfsF1aePrZUNnqIjItmncGEYNw5iY21A4sEHXVckmRERCGjsyMuaNoXp0%2BG116BbN9fViGReamoqsbGxpKSkEBMTky1/58GD0L8/DBlio%2BIVKtjGj8aNs%2BWvF5FTGD/eRtwBPvgAbrrJbT1yahoB9LjgL7bp093WIeLaokW2uePZZy38de0KCxYo/InkljZtbIkFwB13wNKlbuuRU1MA9LgmTew6bZrWAYo/pafD88/b6Ti//QbFi9uGj7fegmwaWBSRTBo40Hpr7t1rO%2B/37HFdkZyMAqDHXXIJ5M9vx/H8/rvrakRy14YN0LIl9O5t079XXWVNndu2dV2ZiD/lyQNjxtg52kuXQvfuGpwIVQqAHleoUEY/wO%2B/d1uLSG768EOoUcO%2B7wsVgldegS%2B/hFKlXFcm4m8lS1qT6Dx54P337ZhFCT0KgGGgeXO7fved2zpEcsOuXdCpE3TsaLcTEmD%2BfLjrLh3lJhIqGjWCZ56x2/fea8szJLQoAIaBFi3s%2Bv33djScSLiaMQNq1rRRhchIeOIJmD1bTZ1FQlGfPrYs4%2BBBaN8edu92XZH8lQJgGKhb1xa779gBv/ziuhqR7HfoEDz8sLU9Wr/eziGdNQuefNJO9xCR0BMZCe%2B8A%2BXKwYoVcPfdWg8YShQAw0DevBmjgN9847YWkey2bJmtcw22d7ntNjvH95JLXFcmIv%2BkWDFbrxtcDzhqlOuKJEgBMExccYVdJ050W4dIdgkE4KWXoHZtW%2BN39tnw6ad27FR0tOvqRCSzGja09jAA99xjL%2BrEPZ0EEiY2boTy5W0R/JYt1gtNJJSd6iSQP/%2B0c3wnTLD7rVrB229DmTIOChWRLEtPt5/jKVNs9/5PP9lRpuKORgDDRLly9kMVCGgUULztq6/se3nCBIiKsibPEycq/Il4WWQkvPsulChhJ/T07eu6IlEADCPXXGPX8ePd1iHhb9y4cVx%2B%2BeUUL16ciIgIkpKSTu8vWLnSDgsFSE0FYN8%2B6NHDvo%2B3bIHq1WHePOjVy355iIi3lS5tm0IARoyAiZ/stXUdo0fDkiVui/MhPa2GkTZt7PrNN7btXiSn7N27l4YNGzJ48ODT%2B8Rdu%2By0%2BAsusCMCAKpW5Y97BxEfDy%2B/bO%2B6/374%2BWeoVi176xYRt1q3thd19/IiDdqXhRtugC5d4KKLbI5461bXJfqG1gCGkfR0Wwf4xx82fXblla4rknC3du1aKlasyPz586lVq9Y/f0LTpjB9OgCpQCyQAsQA9zCCcaXvYdQo%2Bz0gIuHp8JujyXdHlxP/YXy8vfrTsH%2BO079wGImMzDgDddw4t7WIHGfWrKPh70SeLDCYBb8eUfgTCWeBAPmGPH3yP//lF/UzyyUKgGGmXeM4TsYAABGVSURBVDu7fv45HDnithaRvzry1Ven/PNiBzZRfPPCXKpGRJxYs8a6Qp%2BKdjLmCgXAMNO4se2y2r7djoYTyar333%2BfIkWKHH2bOXPmGf09c%2BbMyebKRETkTCkAhpm8eeH66%2B32xx%2B7rUXCQ5s2bUhKSjr6VqdOnTP6e6JvfPLUH1C2rPV/EZHwVbGibQI7ldatc6cWn1MADEM33WTXTz/VbmDJuujoaCpVqnT0rWDBgqf1%2BUeO2Jm9CfdfxlSanvwDH37YzosSkfAVEQGPPnrSP95dJT7jaCvJUQqAYahRI2uau2uXllJIztixYwdJSUks%2BV/vruXLl5OUlERycvIxH7dqlS1LGDAA0tJgzA2fcbh1G/slEFS4MDzzjJ0RJSLh75ZbYPhwiI095t3f0orGeyeSslvRJDeoDUyY6tMHhg616eBPP3VdjYSbUaNG0bVr1%2BPe379/fwYMGEAgYL1d77kH9uyBmBjr8Xfzzf/7wJUrSZ06ldi77iJl40ZiypbN3S9ARNzbuxe%2B/Rb27GHvhXWocVMcq1fDrbfa0Y%2BSsxQAw9Rvv0GtWpA/v/UFLFbMdUXiFzt2WI/nsWPtfqNGdgRUhQrHftypzgIWEf%2BZNctmDAIB%2BOKLjMMNJGdonDVM1axpb4cOwYcfuq5G/CJ40PvYsbYh6emnYerU48OfiMjfXXqpzV4BdOsG27a5rSfcKQCGseAM3Ztvuq1Dwt%2BBA/DAA9CiBWzaBFWqwA8/2Fpv7esQkcwaONBOhduyxc4Gl5yjABjGOnWyKeD58%2BHXX11XI%2BFq4UKoWxeGDbP7d91l329n2C1GRHysQAF45x174Th2rNqZ5SQFwDBWrFhGT8DXXnNbi4Sf9HR4/nkLegsXWgPy8ePhlVdsY6%2BIyJmIj4d%2B/ex2jx7w559u6wlXCoBh7q677Pree5Ca6rYWCR8bN0KrVtC7t60zveoqC4HXXOO6MhEJB/362Tr27dstBGq7avZTAAxzTZrAhRfabvvRo11XI%2BHgww%2BhenXb8FGokLV3%2BfJLKFnSdWUiEi7y54dRo2wz2bhxmgrOCQqAYS4iImMh7YgRNm0nciZ27YJ//xs6drTbderYWr/u3Y/t6ywikh1q1cqYCr7nHti61W094UYB0Ae6dLFGvCtWWM9NkdM1ZYqN%2Bo0ZY4uzn3gC5sz55yM9RUSy4tFH7bln2za4917X1YQXBUAfiI6G22%2B320OHuq1FvGX/fujVy9q7bNwIlSpZs9Ynn4R8%2BVxXJyLhLn9%2BOxUkTx746CP4/HPXFYUPBUCf%2BM9/7AdoyhRrCyPyT375xXbjDR9u9%2B%2B6C5KSoH59t3WJiL/Ex8ODD9rtHj1sCYpknQKgT1SoAO3b2%2B0hQ9zWIqHtyBF46ikLekuXQunSMGGC2ruIiDv9%2B1uD%2Bc2bM04LkazRWcA%2BEjwfODISli2DypVdVyShZtkyuOUWmDvX7t94o%2B3yzYmzpHUWsIicjpkz7axggO%2B/h8suc1uP12kE0Edq1rR%2Bbenp8MwzrquRUBJs6ly7toW/okWtd%2BRHH2V/%2BEtMTCQuLo6EhITs/YtFJKw1agR33223u3WzNcpy5jQC6DM//WRTe3ny2GhPpUquKxLXVq%2B2c6NnzLD7l19u50eXLZuzj6sRQBE5XampEBdnZ44/9BAMHuy6Iu/SCKDP1KsHrVtDWpodui3%2BFQjYur4aNSz8FS5s9ydOzPnwJyJyJmJi4KWX7PZ//2tLm%2BTMaATQh%2BbNg4QEa967YAFUq%2Ba6Islt69bBHXfAd9/Z/caNrdXCeeflXg0aARSRM3XDDfDpp/a77IcfbFZLTo9GAH2oTh1o185GgB55xHU1kpsCAXj9dWus%2Bt13ULCgrf2bOjV3w5%2BISFaMGAGxsbZmOTHRdTXepBFAn1q%2BHC66yKaCp06Fpk1dVyQ57e%2Bjfg0a2FmbrnaDawRQRLLilVdsU0iRItayqlw51xV5i0YAfeqCC6yxL0Dv3hYEJTylp1srl2rVLPwVKGAnwsyYoVZAIuJdd94Jl1wCe/bYYQdyehQAfWzAABtCnz/fdn1K%2BPn9d2jWzLrn79kDDRvaounevbVmRkS8LTISXn0V8uaFcePgq69cV%2BQtCoA%2BVqKEnekKduD29u1u65Hsc%2BSI7ZCrXh2mT4dChexItxkzrJu%2BiEg4qF7dXtAC3HMP7N3rth4vUQD0uZ49bWpw%2B3brqSTe99tvNi3y4INw4AA0bw6LFsF999krZhGRcPLEE3DOObbO%2BamnXFfjHfp14HN589r6MLBp4OnT3dYjZ27/fhvJrVPHWv0ULQpvvAGTJ0PFiq6rExHJGYUL265gsPXNS5a4rccrFACFSy%2B1xbRgu0T37XNbj5y%2B77%2B3hs6DBtn07/XX25Pg7bdbv0cRkXDWpo29HTlia57V3%2BSfKQAKAEOG2OkPv/8O/fq5rkYya%2BtW6NLFpnl//x3KlIHPPrMGqaVLu65ORCT3DB9uvU0XLLAjLuXUFAAFsN3Ar79ut194wUaUJHSlp9uUfdWqMHq0jfL17Gm9sNq2dV2diEjuO/dcGDvW%2Btyef77rakKfGkHLMbp3t231ZcvaZoJixVxXJH%2B3cKE1P5092%2B7XrGn/Z/Xqua3rdKkRtIiIOxoBlGMMHWpNojdtgq5dtY4ilKSmWruD2rUt/BUubK1e5s3zXvgTERG3FADlGIULw4cfQlQUfPklPPec64okEID337dg/vzzdmpLu3Y23fvAA7aTW0RE5HQoAMpxatWCF1%2B02488knF2rOS%2BpCRo3Bg6dYLkZKhUCSZOhE8%2BgfLlXVcnIiJepQAoJ9StG9x6q202aN/edphK7tm61c5qvvhimDXLTvJ4%2Bmlr6HzFFa6rExERr1MAlBOKiLAG0fXqwc6dcNVVsGOH66rC38GDtg6zcmV47TWb/u3QAZYtsybPUVGuK8y6xMRE4uLiSEhIcF2KiIhvaRewnFJysoXA9euhYUM7VaJgQddVhZ9AwPr39e0Lq1bZ%2B2rXtr5WjRq5rS2naBewiIg7GgGUUypVCiZMsD6Bs2fbdPDhw66rCi8//PD/7d1tqNZ3HcfxzzW3zpH0WOTohLrh2GSKTg%2Bk2Y4yFmu2%2B6JRVlO2YGNERURPx7An%2BmAPxtwBF7HcaI2EpNk2V1sRClGs8HQ/dTfOpu4%2Bz1HTI%2BjVgx%2B6pN2dM8/5q7/XC/7gdR2v63zPszf/m9%2Bv7MbyxS%2BW%2BOvuLmv8Pf30mRt/ADRLAPKeZs8uTwR3diaPPpp87Wtlux0%2BmH/%2Bs2zZdumlye9%2BV86s3nFHsn178vWvJ%2BPGNT0hAGcqAcj7snhxsn59cs45ZaX1r37VmcCRevHFEnizZ5fLvmedVfbs3b49%2Bf73kwkTmp4QgDOdAOR9u%2BqqssfssQj8wheS//yn6alOH7t3J9/8ZjJjRvKjH5UnrG%2B4oezs8cMflt1XAGAsCECG5brrkkceKZcrH3ssueKK5PXXm57q1LZrV/LtbycXXJD09SWHDyef%2BUzy%2B98nP/95MmtW0xMCUBsByLBddVXyq18lH/lIeYDhU59K/vGPpqc69bzwQtmz94ILktWryxIvixYlv/lN8utf274NgOYIQEZk0aLy4ML06cnzz5eY%2BdnPmp7q1PDXvybLlpW1/NasKWf8Fi0qS%2Bhs2pRcfnnTEwJQOwHIiM2cmfzhD8lllyX79yc33lgudR461PRkY6/dLmdFP/e55JJLkh//uOzZ%2B9nPJr/9bbJ5c7lc3mo1PSkACEA%2BoHPPLWe2vve98nr16mT%2B/ORPf2p2rrFy4EBy333lid4lS5Jf/rI81fulLyV//GOJwssua3pKADiRnUA4aR5/PLnlluTVV8sadt/9bnLnncmHP9z0ZCff3/9ewu/BB5OBgfLehAnl7//Od8p9f7w7O4EANEcAclK99lryrW8lP/1peT11arJqVfKVr5QzY6ezwcFk3brk/vvLwy/HXHhh8o1vlLX9Jk1qbr7TjQAEaI4AZFQ8%2BmgJwR07yut585IVK8oyMqfTfXCHD5fLuj/5SVmy5dj9jePGJddfn9x%2Be7m373SP2yYIQIDmCEBGzcGDyd13JytXJvv2lffmzCmXhpcuLVvLnYoOHkyeeqo81fzII8nevW/9bObM5Oabk%2BXLy569jJwABGiOAGTUvfFGctddyb33lqeFk%2BRjHytLpSxblvT0NH9W8LnnysMsjz9e4u/gwbd%2B1t2dfPnLZQ/kT36y%2BVnPFAIQoDkCkDHz738nP/hB2Q3jX/966/0LL0w%2B//nk6quTSy9NOjpGd46jR5Nt28o6hps3l2Vajl2qPmbatDLTjTcmvb3lki8nlwAEaI4AZMwdOZI88UTywAPJL35x4rqBnZ3JggXJwoXlvsHZs0sgjh8//N9z9Gjy8svJs88mW7cmf/tb8uc/J1u2lAc6/tfZZyef/nRZx%2B/qq5O5c53pG20CEKA5ApBG7duXbNxYHhp58skSbG/nE58oR3d38tGPliVXOjrKwxdHj5aHNfbvL/frvfFG%2BZ5du8r7b2f8%2BHI5t7e3rNO3aFH5TkZfX19f%2Bvr6cuTIkWzbtk0AAjRAAHLKaLeTZ54pl2affjr5y1/KHsPH1tkbiXHjkvPOS2bMSGbNKrt09PSUf59zzsmbneFzBhCgOQKQU1q7nbz%2BevLii8mePWWR6b17y9m%2Bw4fL5eRx45IPfagsON3VlUyenHz848mUKeUQeqcmAQjQnLObHgDeTatVtps799ymJwGAM4flawEAKiMAAQAqIwABACojAAEAKiMAAQAqIwABACojAAEAKiMAAQAqIwABACojAAEAKiMAAQAqIwABACojAAEAKiMAAQAqIwCBMdXX15dZs2Zl/vz5TY8CUK1Wu91uNz0EUJ/BwcFMmjQpAwMD6erqanocgKo4AwgAUBkBCABQGQEIAFAZAQgAUBkBCABQGQEIAFAZAQgAUBkBCABQGQEIAFAZAQgAUBkBCABQGQEIAFAZAQiVW79%2BfZYsWZLJkyen1Wqlv7//PT%2Bzdu3atFqt/zsOHTo0BhMD8EEJQKjcgQMH0tvbm1WrVg3rc11dXdmzZ88JR2dn5yhNCcDJdHbTAwDNWrZsWZJkx44dw/pcq9VKd3f3KEwEwGhzBhAYkf379%2Bf888/P1KlTc%2B2112bLli1NjwTA%2ByQAgWG7%2BOKLs3bt2mzYsCEPP/xwOjs709vbm%2B3bt7/jZ4aGhjI4OHjCAUAzBCBU5KGHHsqECROOH5s3bx7R9yxcuDA33XRT5s6dm8WLF2fdunWZMWNGVq9e/Y6fWblyZSZNmnT8mDZt2kj/DAA%2BoFa73W43PQQwNvbt25dXXnnl%2BOspU6Zk/PjxSco9gNOnT8%2BWLVsyb968YX/3rbfempdeeikbN258258PDQ1laGjo%2BOvBwcFMmzYtAwMD6erqGvbvA2DkPAQCFZk4cWImTpx40r%2B33W6nv78/c%2BbMecf/09HRkY6OjhNmGRgYGJV5AHh3AhAq9%2Babb2bnzp3ZvXt3kmTr1q1Jku7u7uNP%2BS5fvjxTpkzJypUrkyQrVqzIwoULc9FFF2VwcDD33HNP%2Bvv709fX975/b6vVcuYPoCHuAYTKbdiwIT09PbnmmmuSJEuXLk1PT0/WrFlz/P/s3Lkze/bsOf567969ue222zJz5sxceeWV2bVrVzZt2pQFCxaM%2BfwADJ97AAEAKuMMIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGUEIABAZQQgAEBlBCAAQGX%2BC8E9pcg6%2Bt9PAAAAAElFTkSuQmCC'}