From ce8fd2391a92f07320454fefcbde8b62a8f4802c Mon Sep 17 00:00:00 2001 From: Craig Gidney Date: Sun, 19 Nov 2023 17:23:15 -0800 Subject: [PATCH] Test vs qiskit --- src/stim/circuit/circuit.pybind.cc | 10 +- src/stim/circuit/circuit.test.cc | 13 + src/stim/circuit/circuit_pybind_test.py | 60 -- src/stim/circuit/export_qasm.cc | 791 ++++++++++-------- src/stim/circuit/export_qasm.test.cc | 163 ++-- src/stim/circuit/export_qasm_pybind_test.py | 95 +++ .../timeline/timeline_ascii_drawer.test.cc | 49 +- testdata/circuit_all_ops_3d.gltf | 2 +- testdata/circuit_all_ops_detslice.svg | 67 +- testdata/circuit_all_ops_timeline.svg | 68 +- testdata/circuit_all_ops_timeslice.svg | 67 +- 11 files changed, 854 insertions(+), 531 deletions(-) create mode 100644 src/stim/circuit/export_qasm_pybind_test.py diff --git a/src/stim/circuit/circuit.pybind.cc b/src/stim/circuit/circuit.pybind.cc index b2e2d8ff0..499477bb5 100644 --- a/src/stim/circuit/circuit.pybind.cc +++ b/src/stim/circuit/circuit.pybind.cc @@ -1386,14 +1386,14 @@ void stim_pybind::pybind_circuit_methods(pybind11::module &, pybind11::class_ str: Creates an equivalent OpenQASM implementation of the circuit. Args: - open_qasm_version: Defaults to 3. The version of OpenQASM to target. + open_qasm_version: The version of OpenQASM to target. This should be set to 2 or to 3. Differences between the versions are: @@ -1422,12 +1422,13 @@ void stim_pybind::pybind_circuit_methods(pybind11::module &, pybind11::class_>> import stim >>> circuit = stim.Circuit(""" ... R 0 1 + ... X 0 ... H 0 ... CX 0 1 ... M 0 1 ... DETECTOR rec[-1] rec[-2] ... """); - >>> qasm = circuit.to_qasm(); + >>> qasm = circuit.to_qasm(open_qasm_version=3); >>> print(qasm.strip().replace('\n\n', '\n')) OPENQASM 3.0; include "stdgates.inc"; @@ -1436,11 +1437,12 @@ void stim_pybind::pybind_circuit_methods(pybind11::module &, pybind11::class_ rec[0]; measure q[1] -> rec[1]; - dets[0] = rec[1] ^ rec[0] ^ 0; + dets[0] = rec[1] ^ rec[0] ^ 1; )DOC") .data()); diff --git a/src/stim/circuit/circuit.test.cc b/src/stim/circuit/circuit.test.cc index c5a3f7575..6615ae520 100644 --- a/src/stim/circuit/circuit.test.cc +++ b/src/stim/circuit/circuit.test.cc @@ -1687,6 +1687,19 @@ Circuit stim::generate_test_circuit_with_all_operations() { OBSERVABLE_INCLUDE(0) rec[-1] MPAD 0 1 0 TICK + + # Inverted measurements. + MRX !0 + MY !1 + MZZ !2 3 + MYY !4 !5 + MPP X6*!Y7*Z8 + TICK + + # Feedback + CX rec[-1] 0 + CY sweep[0] 1 + CZ 2 rec[-1] )CIRCUIT"); } diff --git a/src/stim/circuit/circuit_pybind_test.py b/src/stim/circuit/circuit_pybind_test.py index 8d369b5ac..70772b4cc 100644 --- a/src/stim/circuit/circuit_pybind_test.py +++ b/src/stim/circuit/circuit_pybind_test.py @@ -1573,63 +1573,3 @@ def test_detslice_filter_coords_flexibility(): assert str(d1) == str(d3) assert str(d1) == str(d4) assert str(d1) == str(d5) - - -def test_to_qasm(): - c = stim.Circuit(""" - RX 0 1 - TICK - H 1 - CX 0 1 - TICK - M 0 1 - DETECTOR rec[-1] rec[-2] - C_XYZ 0 - """) - - assert c.to_qasm().strip() == """ -OPENQASM 3.0; - -include "stdgates.inc"; -gate cxyz q0 { U(pi/2, 0, pi/2) q0; } -def rx(qubit q0) { reset q0; h q0; } - -qubit q[2]; -bit m[2]; -bit dets[1]; - -rx(q[0]); -rx(q[1]); -barrier q; - -h q[1]; -cx q[0], q[1]; -barrier q; - -measure q[0] -> m[0]; -measure q[1] -> m[1]; -dets[0] = rec[1] ^ rec[0] ^ 0; -cxyz q[0]; - """.strip() - - assert c.to_qasm(open_qasm_version=2, skip_dets_and_obs=True).strip() == """ -OPENQASM 2.0; - -include "qelib1.inc"; -gate cxyz q0 { U(pi/2, 0, pi/2) q0; } - -qreg q[2]; -creg m[2]; - -reset q[0]; h q[0]; // decomposed RX -reset q[1]; h q[1]; // decomposed RX -barrier q; - -h q[1]; -cx q[0], q[1]; -barrier q; - -measure q[0] -> m[0]; -measure q[1] -> m[1]; -cxyz q[0]; - """.strip() diff --git a/src/stim/circuit/export_qasm.cc b/src/stim/circuit/export_qasm.cc index 2a7d6dce6..1381e436c 100644 --- a/src/stim/circuit/export_qasm.cc +++ b/src/stim/circuit/export_qasm.cc @@ -20,412 +20,443 @@ using namespace stim; -static void do_decomposed( - GateType g, const char *q0_name, const char *q1_name, const char *m_name, std::ostream &out) { - auto q2n = [&](GateTarget t) { - return t.qubit_value() == 0 ? q0_name : q1_name; - }; - bool first = true; - for (const auto &inst : Circuit(GATE_DATA[g].h_s_cx_m_r_decomposition).operations) { - switch (inst.gate_type) { - case GateType::S: - for (const auto &t : inst.targets) { - if (!first) { - out << " "; - } - first = false; - out << "s " << q2n(t) << ";"; - } - break; - case GateType::H: - for (const auto &t : inst.targets) { - if (!first) { - out << " "; - } - first = false; - out << "h " << q2n(t) << ";"; - } - break; - case GateType::R: - for (const auto &t : inst.targets) { - if (!first) { - out << " "; - } - first = false; - out << "reset " << q2n(t) << ";"; - } - break; - case GateType::CX: - for (size_t k = 0; k < inst.targets.size(); k += 2) { - if (!first) { - out << " "; - } - first = false; - auto t1 = inst.targets[k]; - auto t2 = inst.targets[k + 1]; - out << "cx " << q2n(t1) << ", " << q2n(t2) << ";"; - } - break; - case GateType::M: - for (const auto &t : inst.targets) { - if (!first) { - out << " "; - } - first = false; - out << "measure " << q2n(t) << " -> " << m_name << ";"; - } - break; - default: - throw std::invalid_argument("Unhandled: " + inst.str()); +struct QasmExporter { + std::ostream &out; + CircuitStats stats; + int open_qasm_version; + bool skip_dets_and_obs; + simd_bits<64> reference_sample; + uint64_t measurement_offset; + uint64_t detector_offset; + std::array qasm_names{}; + std::bitset used_gates{}; + std::stringstream buf_q1; + std::stringstream buf_q2; + std::stringstream buf_m; + + QasmExporter() = delete; + QasmExporter(const QasmExporter &) = delete; + QasmExporter(QasmExporter &&) = delete; + QasmExporter(std::ostream &out, const Circuit &circuit, int open_qasm_version, bool skip_dets_and_obs) + : out(out), + stats(circuit.compute_stats()), + open_qasm_version(open_qasm_version), + skip_dets_and_obs(skip_dets_and_obs), + reference_sample(stats.num_measurements), + measurement_offset(0), + detector_offset(0) { + + // Init used_gates. + collect_used_gates(circuit); + + // Init reference_sample. + if (stats.num_detectors > 0 || stats.num_observables > 0) { + reference_sample = TableauSimulator<64>::reference_sample_circuit(circuit); } } -} - -static void do_qasm_decompose_mpp( - const CircuitInstruction &inst, size_t num_qubits, uint64_t &measurement_offset, std::ostream &out) { - decompose_mpp_operation( - inst, - num_qubits, - [&](const CircuitInstruction &h_xz, - const CircuitInstruction &h_yz, - const CircuitInstruction &cnot, - const CircuitInstruction &meas) { - for (const auto t : h_xz.targets) { - out << "h q[" << t.qubit_value() << "];"; - } - for (const auto t : h_yz.targets) { - out << "sx q[" << t.qubit_value() << "];"; - } - for (size_t k = 0; k < cnot.targets.size(); k += 2) { - auto t1 = cnot.targets[k]; - auto t2 = cnot.targets[k + 1]; - out << "cx q[" << t1.qubit_value() << "],q[" << t2.qubit_value() << "];"; - } - for (auto t : meas.targets) { - out << "measure q[" << t.qubit_value() << "] -> rec[" << measurement_offset << "];"; - measurement_offset++; - } - for (size_t k = 0; k < cnot.targets.size(); k += 2) { - auto t1 = cnot.targets[k]; - auto t2 = cnot.targets[k + 1]; - out << "cx q[" << t1.qubit_value() << "],q[" << t2.qubit_value() << "];"; - } - for (const auto t : h_yz.targets) { - out << "sxdg q[" << t.qubit_value() << "];"; - } - for (const auto t : h_xz.targets) { - out << "h q[" << t.qubit_value() << "];"; - } - out << " // decomposed MPP\n"; - }); -} -static void qasm_output_decomposed_inline( - const CircuitInstruction &instruction, - const std::array &qasm_names, - uint64_t &measurement_offset, - std::ostream &out, - bool decompose_inline) { - auto f = GATE_DATA[instruction.gate_type].flags; - std::stringstream q0; - std::stringstream q1; - std::stringstream m; - auto step = (f & GATE_TARGETS_PAIRS) ? 2 : 1; - for (size_t k = 0; k < instruction.targets.size(); k += step) { - auto t0 = instruction.targets[k]; - auto t1 = instruction.targets[k + step - 1]; - if (decompose_inline) { - q0.str(""); - q1.str(""); - q0 << "q[" << t0.qubit_value() << "]"; - q1 << "q[" << t1.qubit_value() << "]"; - if (f & GATE_PRODUCES_RESULTS) { - m.str(""); - m << "rec[" << measurement_offset << "]"; - measurement_offset++; + void output_measurement(bool invert_measurement_result, const char *q_name, const char *m_name) { + if (invert_measurement_result) { + if (open_qasm_version == 3) { + out << "measure " << q_name << " -> " << m_name << ";"; + out << m_name << " = " << m_name << " ^ 1;"; + } else { + out << "x " << q_name << ";"; + out << "measure " << q_name << " -> " << m_name << ";"; + out << "x " << q_name << ";"; } - do_decomposed( - instruction.gate_type, q0.str().data(), q1.str().data(), m.str().data(), out); - out << " // decomposed " << GATE_DATA[instruction.gate_type].name << "\n"; } else { - if (f & GATE_PRODUCES_RESULTS) { - out << "rec[" << measurement_offset << "] = "; - measurement_offset++; - } - out << qasm_names[(int)instruction.gate_type] << "("; - out << "q[" << t0.qubit_value() << "]"; - if (step == 2) { - out << ", q[" << t1.qubit_value() << "]"; - } - out << ");\n"; + out << "measure " << q_name << " -> " << m_name << ";"; } } -} -static void qasm_output_two_qubit_unitary( - const CircuitInstruction &instruction, - const std::array &qasm_names, - uint64_t &measurement_offset, - int open_qasm_version, - std::ostream &out) { - for (size_t k = 0; k < instruction.targets.size(); k += 2) { - auto t1 = instruction.targets[k]; - auto t2 = instruction.targets[k + 1]; - if (t1.is_qubit_target() && t2.is_qubit_target()) { - out << qasm_names[(int)instruction.gate_type] << " q[" << t1.qubit_value() << "], q[" << t2.qubit_value() - << "];\n"; - } else if (t1.is_qubit_target() || t2.is_qubit_target()) { - if (open_qasm_version == 2) { - throw std::invalid_argument( - "The circuit contains feedback, but OPENQASM 2 doesn't support feedback.\n" - "You can use `stim.Circuit.with_inlined_feedback` to drop feedback operations.\n" - "Alternatively, pass the argument `open_qasm_version=3`."); - } - GateTarget control; - GateTarget target; - char basis; - switch (instruction.gate_type) { - case GateType::CX: - basis = 'X'; - control = t1; - target = t2; + void output_decomposed_operation( + bool invert_measurement_result, + GateType g, + const char *q0_name, + const char *q1_name, + const char *m_name) { + auto q2n = [&](GateTarget t) { + return t.qubit_value() == 0 ? q0_name : q1_name; + }; + bool first = true; + for (const auto &inst : Circuit(GATE_DATA[g].h_s_cx_m_r_decomposition).operations) { + switch (inst.gate_type) { + case GateType::S: + for (const auto &t : inst.targets) { + if (!first) { + out << " "; + } + first = false; + out << "s " << q2n(t) << ";"; + } break; - case GateType::CY: - basis = 'Y'; - control = t1; - target = t2; + case GateType::H: + for (const auto &t : inst.targets) { + if (!first) { + out << " "; + } + first = false; + out << "h " << q2n(t) << ";"; + } break; - case GateType::CZ: - basis = 'Z'; - control = t1; - target = t2; - if (control.is_qubit_target()) { - std::swap(control, target); + case GateType::R: + for (const auto &t : inst.targets) { + if (!first) { + out << " "; + } + first = false; + out << "reset " << q2n(t) << ";"; } break; - case GateType::XCZ: - basis = 'X'; - control = t2; - target = t1; + case GateType::CX: + for (size_t k = 0; k < inst.targets.size(); k += 2) { + if (!first) { + out << " "; + } + first = false; + auto t1 = inst.targets[k]; + auto t2 = inst.targets[k + 1]; + out << "cx " << q2n(t1) << ", " << q2n(t2) << ";"; + } break; - case GateType::YCZ: - basis = 'Y'; - control = t2; - target = t1; + case GateType::M: + for (const auto &t : inst.targets) { + if (!first) { + out << " "; + } + first = false; + output_measurement(invert_measurement_result, q2n(t), m_name); + } break; default: - throw std::invalid_argument("Not implemented: " + instruction.str()); - } - out << "if ("; - if (t1.is_measurement_record_target()) { - out << "ms[" << (measurement_offset + t1.rec_offset()) << "]"; - } else if (t1.is_sweep_bit_target()) { - out << "sweep[" << t1.value() << "]"; - } else { - throw std::invalid_argument("Not implemented: " + instruction.str()); + throw std::invalid_argument("Unhandled: " + inst.str()); } - out << ") {\n"; - out << " " << basis << " q[" << target.qubit_value() << "];\n"; - out << "}\n"; } } -} -static void define_custom_single_qubit_gate( - GateType g, - const char *name, - std::array &qasm_names, - const std::bitset &used, - std::ostream &out) { - const auto &gate = GATE_DATA[g]; - qasm_names[(int)g] = name; - if (!used[(int)g]) { - return; + void output_decomposed_mpp_operation(const CircuitInstruction &inst) { + decompose_mpp_operation( + inst, + stats.num_qubits, + [&](const CircuitInstruction &h_xz, + const CircuitInstruction &h_yz, + const CircuitInstruction &cnot, + const CircuitInstruction &meas) { + for (const auto t : h_xz.targets) { + out << "h q[" << t.qubit_value() << "];"; + } + for (const auto t : h_yz.targets) { + out << "sx q[" << t.qubit_value() << "];"; + } + for (size_t k = 0; k < cnot.targets.size(); k += 2) { + auto t1 = cnot.targets[k]; + auto t2 = cnot.targets[k + 1]; + out << "cx q[" << t1.qubit_value() << "],q[" << t2.qubit_value() << "];"; + } + for (auto t : meas.targets) { + buf_q1.str(""); + buf_m.str(""); + buf_q1 << "q[" << t.qubit_value() << "]"; + buf_m << "rec[" << measurement_offset << "]"; + output_measurement( + t.is_inverted_result_target(), + buf_q1.str().c_str(), + buf_m.str().c_str()); + measurement_offset++; + } + for (size_t k = 0; k < cnot.targets.size(); k += 2) { + auto t1 = cnot.targets[k]; + auto t2 = cnot.targets[k + 1]; + out << "cx q[" << t1.qubit_value() << "],q[" << t2.qubit_value() << "];"; + } + for (const auto t : h_yz.targets) { + out << "sxdg q[" << t.qubit_value() << "];"; + } + for (const auto t : h_xz.targets) { + out << "h q[" << t.qubit_value() << "];"; + } + out << " // decomposed MPP\n"; + }); } - out << "gate " << name << " q0 { U("; - auto xyz = gate.to_euler_angles(); - std::array angles{"0", "pi/2", "pi", "-pi/2"}; - out << angles[round(xyz[0] / 3.14159265359f)]; - out << ", " << angles[round(xyz[1] / 3.14159265359f)]; - out << ", " << angles[round(xyz[2] / 3.14159265359f)]; - out << ") q0; }\n"; -} + void output_decomposable_instruction( + const CircuitInstruction &instruction, + bool decompose_inline) { -static void define_custom_decomposed_gate( - GateType g, - const char *name, - std::array &qasm_names, - const std::bitset &used, - std::ostream &out, - int open_qasm_version) { - const auto &gate = GATE_DATA[g]; - qasm_names[(int)g] = name; - if (!used[(int)g]) { - return; + auto f = GATE_DATA[instruction.gate_type].flags; + auto step = (f & GATE_TARGETS_PAIRS) ? 2 : 1; + for (size_t k = 0; k < instruction.targets.size(); k += step) { + auto t0 = instruction.targets[k]; + auto t1 = instruction.targets[k + step - 1]; + bool invert_measurement_result = t0.is_inverted_result_target(); + if (step == 2) { + invert_measurement_result ^= t1.is_inverted_result_target(); + } + if (decompose_inline) { + buf_q1.str(""); + buf_q2.str(""); + buf_q1 << "q[" << t0.qubit_value() << "]"; + buf_q2 << "q[" << t1.qubit_value() << "]"; + if (f & GATE_PRODUCES_RESULTS) { + buf_m.str(""); + buf_m << "rec[" << measurement_offset << "]"; + measurement_offset++; + } + output_decomposed_operation( + invert_measurement_result, + instruction.gate_type, + buf_q1.str().c_str(), + buf_q2.str().c_str(), + buf_m.str().c_str()); + out << " // decomposed " << GATE_DATA[instruction.gate_type].name << "\n"; + } else { + if (f & GATE_PRODUCES_RESULTS) { + out << "rec[" << measurement_offset << "] = "; + measurement_offset++; + } + out << qasm_names[(int)instruction.gate_type] << "("; + out << "q[" << t0.qubit_value() << "]"; + if (step == 2) { + out << ", q[" << t1.qubit_value() << "]"; + } + out << ")"; + if ((f & GATE_PRODUCES_RESULTS) && invert_measurement_result) { + out << " ^ 1"; + } + out << ";\n"; + } + } } - Circuit c(gate.h_s_cx_m_r_decomposition); - bool is_unitary = true; - for (const auto &inst : c.operations) { - is_unitary &= (GATE_DATA[inst.gate_type].flags & GATE_IS_UNITARY) != 0; - } - auto num_measurements = c.count_measurements(); - if (is_unitary) { - out << "gate " << name; - out << " q0"; - if (gate.flags & GateFlags::GATE_TARGETS_PAIRS) { - out << ", q1"; + void output_two_qubit_unitary_instruction_with_possible_feedback(const CircuitInstruction &instruction) { + for (size_t k = 0; k < instruction.targets.size(); k += 2) { + auto t1 = instruction.targets[k]; + auto t2 = instruction.targets[k + 1]; + if (t1.is_qubit_target() && t2.is_qubit_target()) { + out << qasm_names[(int)instruction.gate_type] << " q[" << t1.qubit_value() << "], q[" << t2.qubit_value() + << "];\n"; + } else if (t1.is_qubit_target() || t2.is_qubit_target()) { + GateTarget control; + GateTarget target; + char basis; + switch (instruction.gate_type) { + case GateType::CX: + basis = 'X'; + control = t1; + target = t2; + break; + case GateType::CY: + basis = 'Y'; + control = t1; + target = t2; + break; + case GateType::CZ: + basis = 'Z'; + control = t1; + target = t2; + if (control.is_qubit_target()) { + std::swap(control, target); + } + break; + case GateType::XCZ: + basis = 'X'; + control = t2; + target = t1; + break; + case GateType::YCZ: + basis = 'Y'; + control = t2; + target = t1; + break; + default: + throw std::invalid_argument("Not implemented: " + instruction.str()); + } + + out << "if ("; + if (control.is_measurement_record_target()) { + if (open_qasm_version == 2) { + throw std::invalid_argument( + "The circuit contains feedback, but OPENQASM 2 doesn't support feedback.\n" + "You can use `stim.Circuit.with_inlined_feedback` to drop feedback operations.\n" + "Alternatively, pass the argument `open_qasm_version=3`."); + } + out << "ms[" << (measurement_offset + control.rec_offset()) << "]"; + } else if (control.is_sweep_bit_target()) { + if (open_qasm_version == 2) { + throw std::invalid_argument( + "The circuit contains sweep operation, but OPENQASM 2 doesn't support feedback.\n" + "Remove these operations, or pass the argument `open_qasm_version=3`."); + } + out << "sweep[" << control.value() << "]"; + } else { + throw std::invalid_argument("Not implemented: " + instruction.str()); + } + out << ") {\n"; + out << " " << basis << " q[" << target.qubit_value() << "];\n"; + out << "}\n"; + } } - out << " { "; - } else { - if (open_qasm_version == 2) { - // Have to decompose inline in the circuit. + } + + void define_custom_single_qubit_gate(GateType g, const char *name) { + const auto &gate = GATE_DATA[g]; + qasm_names[(int)g] = name; + if (!used_gates[(int)g]) { return; } - out << "def " << name << "(qubit q0"; - if (gate.flags & GateFlags::GATE_TARGETS_PAIRS) { - out << ", qubit q1"; - } - out << ")"; - if (num_measurements > 1) { - throw std::invalid_argument("Multiple measurement gates not supported."); - } else if (num_measurements == 1) { - out << " -> bit { bit b; "; - } else { - out << " { "; - } - } - do_decomposed(g, "q0", "q1", "b", out); - if (num_measurements > 0) { - out << " return b;"; + out << "gate " << name << " q0 { U("; + auto xyz = gate.to_euler_angles(); + std::array angles{"0", "pi/2", "pi", "-pi/2"}; + out << angles[round(xyz[0] / 3.14159265359f)]; + out << ", " << angles[round(xyz[1] / 3.14159265359f)]; + out << ", " << angles[round(xyz[2] / 3.14159265359f)]; + out << ") q0; }\n"; } - out << " }\n"; -} -static void collect_used_gates(const Circuit &c, std::bitset &used) { - for (const auto &inst : c.operations) { - used[(int)inst.gate_type] = true; - if (inst.gate_type == GateType::REPEAT) { - collect_used_gates(inst.repeat_block_body(c), used); + void define_custom_decomposed_gate(GateType g, const char *name) { + const auto &gate = GATE_DATA[g]; + qasm_names[(int)g] = name; + if (!used_gates[(int)g]) { + return; } - } -} -static std::array define_qasm_gates( - std::ostream &out, const std::bitset &used, int open_qasm_version) { - std::array qasm_names; + Circuit c(gate.h_s_cx_m_r_decomposition); + bool is_unitary = true; + for (const auto &inst : c.operations) { + is_unitary &= (GATE_DATA[inst.gate_type].flags & GATE_IS_UNITARY) != 0; + } + auto num_measurements = c.count_measurements(); + if (is_unitary) { + out << "gate " << name; + out << " q0"; + if (gate.flags & GateFlags::GATE_TARGETS_PAIRS) { + out << ", q1"; + } + out << " { "; + } else { + if (open_qasm_version == 2) { + // Have to decompose inline in the circuit. + return; + } + out << "def " << name << "(qubit q0"; + if (gate.flags & GateFlags::GATE_TARGETS_PAIRS) { + out << ", qubit q1"; + } + out << ")"; + if (num_measurements > 1) { + throw std::invalid_argument("Multiple measurement gates not supported."); + } else if (num_measurements == 1) { + out << " -> bit { bit b; "; + } else { + out << " { "; + } + } - if (open_qasm_version == 2) { - out << "include \"qelib1.inc\";\n"; - } else if (open_qasm_version == 3) { - out << "include \"stdgates.inc\";\n"; - } else { - throw std::invalid_argument("Unrecognized open_qasm_version."); + output_decomposed_operation(false, g, "q0", "q1", "b"); + if (num_measurements > 0) { + out << " return b;"; + } + out << " }\n"; } - qasm_names[(int)GateType::I] = "id"; - qasm_names[(int)GateType::X] = "x"; - qasm_names[(int)GateType::Y] = "y"; - qasm_names[(int)GateType::Z] = "z"; - qasm_names[(int)GateType::SQRT_X] = "sx"; - qasm_names[(int)GateType::SQRT_X_DAG] = "sxdg"; - qasm_names[(int)GateType::S] = "s"; - qasm_names[(int)GateType::S_DAG] = "sdg"; - qasm_names[(int)GateType::CX] = "cx"; - qasm_names[(int)GateType::CY] = "cy"; - qasm_names[(int)GateType::CZ] = "cz"; - qasm_names[(int)GateType::SWAP] = "swap"; - qasm_names[(int)GateType::H] = "h"; - define_custom_single_qubit_gate(GateType::C_XYZ, "cxyz", qasm_names, used, out); - define_custom_single_qubit_gate(GateType::C_ZYX, "czyx", qasm_names, used, out); - define_custom_single_qubit_gate(GateType::SQRT_Y, "sy", qasm_names, used, out); - define_custom_single_qubit_gate(GateType::SQRT_Y_DAG, "sydg", qasm_names, used, out); - define_custom_single_qubit_gate(GateType::H_XY, "hxy", qasm_names, used, out); - define_custom_single_qubit_gate(GateType::H_YZ, "hyz", qasm_names, used, out); - define_custom_decomposed_gate(GateType::XCX, "xcx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::XCY, "xcy", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::XCZ, "xcz", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::YCX, "ycx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::YCY, "ycy", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::YCZ, "ycz", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::SQRT_XX, "sxx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::SQRT_XX_DAG, "sxxdg", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::SQRT_YY, "syy", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::SQRT_YY_DAG, "syydg", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::SQRT_ZZ, "szz", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::SQRT_ZZ_DAG, "szzdg", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::ISWAP, "iswap", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::CXSWAP, "cxswap", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::SWAPCX, "swapcx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::ISWAP_DAG, "iswapdg", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MX, "mx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MY, "my", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MRX, "mrx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MRY, "mry", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MR, "mr", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::RX, "rx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::RY, "ry", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MXX, "mxx", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MYY, "myy", qasm_names, used, out, open_qasm_version); - define_custom_decomposed_gate(GateType::MZZ, "mzz", qasm_names, used, out, open_qasm_version); - out << "\n"; - - return qasm_names; -} -void stim::export_open_qasm(const Circuit &circuit, std::ostream &out, int open_qasm_version, bool skip_dets_and_obs) { - auto stats = circuit.compute_stats(); - std::bitset used; - collect_used_gates(circuit, used); - if (open_qasm_version != 2 && open_qasm_version != 3) { - throw std::invalid_argument("Only open_qasm_version=2 and open_qasm_version=3 are supported."); + void collect_used_gates(const Circuit &c) { + for (const auto &inst : c.operations) { + used_gates[(int)inst.gate_type] = true; + if (inst.gate_type == GateType::REPEAT) { + collect_used_gates(inst.repeat_block_body(c)); + } + } } - // Header. - if (open_qasm_version == 2) { - out << "OPENQASM 2.0;\n"; - } else { - out << "OPENQASM 3.0;\n"; + void output_header() { + if (open_qasm_version == 2) { + out << "OPENQASM 2.0;\n"; + } else { + out << "OPENQASM 3.0;\n"; + } } - out << "\n"; - // Gate definitions. - std::array qasm_names = define_qasm_gates(out, used, open_qasm_version); - - // Storage. - const char *qubit_decl = "qubit"; - const char *bit_decl = "bit"; - if (open_qasm_version == 2) { - qubit_decl = "qreg"; - bit_decl = "creg"; - } - if (stats.num_qubits > 0) { - out << qubit_decl << " q[" << stats.num_qubits << "];\n"; - } - if (stats.num_measurements > 0) { - out << bit_decl << " rec[" << stats.num_measurements << "];\n"; - } - if (stats.num_detectors > 0 && !skip_dets_and_obs) { - out << bit_decl << " dets[" << stats.num_detectors << "];\n"; - } - if (stats.num_observables > 0 && !skip_dets_and_obs) { - out << bit_decl << " obs[" << stats.num_observables << "];\n"; - } - if (stats.num_sweep_bits > 0) { - out << bit_decl << " sweep[" << stats.num_sweep_bits << "];\n"; + void output_storage_declarations() { + if (stats.num_qubits > 0) { + out << "qreg q[" << stats.num_qubits << "];\n"; + } + if (stats.num_measurements > 0) { + out << "creg rec[" << stats.num_measurements << "];\n"; + } + if (stats.num_detectors > 0 && !skip_dets_and_obs) { + out << "creg dets[" << stats.num_detectors << "];\n"; + } + if (stats.num_observables > 0 && !skip_dets_and_obs) { + out << "creg obs[" << stats.num_observables << "];\n"; + } + if (stats.num_sweep_bits > 0) { + out << "creg sweep[" << stats.num_sweep_bits << "];\n"; + } + out << "\n"; } - out << "\n"; - simd_bits<64> reference_sample(stats.num_measurements); - if (stats.num_detectors > 0 || stats.num_observables > 0) { - reference_sample = TableauSimulator<64>::reference_sample_circuit(circuit); + void define_all_gates_and_output_gate_declarations() { + if (open_qasm_version == 2) { + out << "include \"qelib1.inc\";\n"; + } else if (open_qasm_version == 3) { + out << "include \"stdgates.inc\";\n"; + } else { + throw std::invalid_argument("Unrecognized open_qasm_version."); + } + qasm_names[(int)GateType::I] = "id"; + qasm_names[(int)GateType::X] = "x"; + qasm_names[(int)GateType::Y] = "y"; + qasm_names[(int)GateType::Z] = "z"; + qasm_names[(int)GateType::SQRT_X] = "sx"; + qasm_names[(int)GateType::SQRT_X_DAG] = "sxdg"; + qasm_names[(int)GateType::S] = "s"; + qasm_names[(int)GateType::S_DAG] = "sdg"; + qasm_names[(int)GateType::CX] = "cx"; + qasm_names[(int)GateType::CY] = "cy"; + qasm_names[(int)GateType::CZ] = "cz"; + qasm_names[(int)GateType::SWAP] = "swap"; + qasm_names[(int)GateType::H] = "h"; + define_custom_single_qubit_gate(GateType::C_XYZ, "cxyz"); + define_custom_single_qubit_gate(GateType::C_ZYX, "czyx"); + define_custom_single_qubit_gate(GateType::H_XY, "hxy"); + define_custom_single_qubit_gate(GateType::H_YZ, "hyz"); + define_custom_single_qubit_gate(GateType::SQRT_Y, "sy"); + define_custom_single_qubit_gate(GateType::SQRT_Y_DAG, "sydg"); + + define_custom_decomposed_gate(GateType::CXSWAP, "cxswap"); + define_custom_decomposed_gate(GateType::ISWAP, "iswap"); + define_custom_decomposed_gate(GateType::ISWAP_DAG, "iswapdg"); + define_custom_decomposed_gate(GateType::SQRT_XX, "sxx"); + define_custom_decomposed_gate(GateType::SQRT_XX_DAG, "sxxdg"); + define_custom_decomposed_gate(GateType::SQRT_YY, "syy"); + define_custom_decomposed_gate(GateType::SQRT_YY_DAG, "syydg"); + define_custom_decomposed_gate(GateType::SQRT_ZZ, "szz"); + define_custom_decomposed_gate(GateType::SQRT_ZZ_DAG, "szzdg"); + define_custom_decomposed_gate(GateType::SWAPCX, "swapcx"); + define_custom_decomposed_gate(GateType::XCX, "xcx"); + define_custom_decomposed_gate(GateType::XCY, "xcy"); + define_custom_decomposed_gate(GateType::XCZ, "xcz"); + define_custom_decomposed_gate(GateType::YCX, "ycx"); + define_custom_decomposed_gate(GateType::YCY, "ycy"); + define_custom_decomposed_gate(GateType::YCZ, "ycz"); + + define_custom_decomposed_gate(GateType::MR, "mr"); + define_custom_decomposed_gate(GateType::MRX, "mrx"); + define_custom_decomposed_gate(GateType::MRY, "mry"); + define_custom_decomposed_gate(GateType::MX, "mx"); + define_custom_decomposed_gate(GateType::MXX, "mxx"); + define_custom_decomposed_gate(GateType::MY, "my"); + define_custom_decomposed_gate(GateType::MYY, "myy"); + define_custom_decomposed_gate(GateType::MZZ, "mzz"); + define_custom_decomposed_gate(GateType::RX, "rx"); + define_custom_decomposed_gate(GateType::RY, "ry"); + + out << "\n"; } - // Body. - uint64_t measurement_offset = 0; - uint64_t detector_offset = 0; - circuit.for_each_operation([&](const CircuitInstruction &instruction) { + void output_instruction(const CircuitInstruction &instruction) { GateFlags f = GATE_DATA[instruction.gate_type].flags; switch (instruction.gate_type) { @@ -444,7 +475,19 @@ void stim::export_open_qasm(const Circuit &circuit, std::ostream &out, int open_ case GateType::M: for (const auto &t : instruction.targets) { - out << "measure q[" << t.qubit_value() << "] -> rec[" << measurement_offset << "];\n"; + if (t.is_inverted_result_target()) { + if (open_qasm_version == 3) { + out << "measure q[" << t.qubit_value() << "] -> rec[" << measurement_offset << "];"; + out << "rec[" << measurement_offset << "] = rec[" << measurement_offset << "] ^ 1;"; + } else { + out << "x q[" << t.qubit_value() << "];"; + out << "measure q[" << t.qubit_value() << "] -> rec[" << measurement_offset << "];"; + out << "x q[" << t.qubit_value() << "];"; + } + } else { + out << "measure q[" << t.qubit_value() << "] -> rec[" << measurement_offset << "];"; + } + out << "\n"; measurement_offset++; } return; @@ -499,7 +542,7 @@ void stim::export_open_qasm(const Circuit &circuit, std::ostream &out, int open_ "Use `stim.Circuit.without_noise` to get a version of the circuit without noise."); case GateType::MPP: - do_qasm_decompose_mpp(instruction, stats.num_qubits, measurement_offset, out); + output_decomposed_mpp_operation(instruction); return; default: @@ -507,7 +550,7 @@ void stim::export_open_qasm(const Circuit &circuit, std::ostream &out, int open_ } if (f & (stim::GATE_IS_RESET | stim::GATE_PRODUCES_RESULTS)) { - qasm_output_decomposed_inline(instruction, qasm_names, measurement_offset, out, open_qasm_version == 2); + output_decomposable_instruction(instruction, open_qasm_version == 2); return; } @@ -520,11 +563,25 @@ void stim::export_open_qasm(const Circuit &circuit, std::ostream &out, int open_ return; } if (f & stim::GATE_TARGETS_PAIRS) { - qasm_output_two_qubit_unitary(instruction, qasm_names, measurement_offset, skip_dets_and_obs, out); + output_two_qubit_unitary_instruction_with_possible_feedback(instruction); return; } } throw std::invalid_argument("Not implemented: " + instruction.str()); + } +}; + +void stim::export_open_qasm(const Circuit &circuit, std::ostream &out, int open_qasm_version, bool skip_dets_and_obs) { + if (open_qasm_version != 2 && open_qasm_version != 3) { + throw std::invalid_argument("Only open_qasm_version=2 and open_qasm_version=3 are supported."); + } + + QasmExporter exporter(out, circuit, open_qasm_version, skip_dets_and_obs); + exporter.output_header(); + exporter.define_all_gates_and_output_gate_declarations(); + exporter.output_storage_declarations(); + circuit.for_each_operation([&](const CircuitInstruction &instruction) { + exporter.output_instruction(instruction); }); } diff --git a/src/stim/circuit/export_qasm.test.cc b/src/stim/circuit/export_qasm.test.cc index c77d364db..d8f9d86f4 100644 --- a/src/stim/circuit/export_qasm.test.cc +++ b/src/stim/circuit/export_qasm.test.cc @@ -7,7 +7,7 @@ using namespace stim; -TEST(export_circuit, export_open_qasm_feedback) { +TEST(export_qasm, export_open_qasm_feedback) { Circuit c(R"CIRCUIT( H 0 CX 0 1 @@ -21,13 +21,12 @@ TEST(export_circuit, export_open_qasm_feedback) { std::stringstream out; export_open_qasm(c, out, 3, false); ASSERT_EQ(out.str(), R"QASM(OPENQASM 3.0; - include "stdgates.inc"; gate cxyz q0 { U(pi/2, 0, pi/2) q0; } -qubit q[2]; -bit rec[1]; -bit sweep[6]; +qreg q[2]; +creg rec[1]; +creg sweep[6]; h q[0]; cx q[0], q[1]; @@ -45,7 +44,31 @@ h q[0]; )QASM"); } -TEST(export_circuit, export_open_qasm_qec) { +TEST(export_qasm, export_open_qasm_inverted_measurements) { + Circuit c(R"CIRCUIT( + M !0 + MX !0 + MXX !0 1 + MPP !X0*Z1 + )CIRCUIT"); + std::stringstream out; + export_open_qasm(c, out, 3, false); + ASSERT_EQ(out.str(), R"QASM(OPENQASM 3.0; +include "stdgates.inc"; +def mx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; h q0; return b; } +def mxx(qubit q0, qubit q1) -> bit { bit b; cx q0, q1; h q0; measure q0 -> b; h q0; cx q0, q1; return b; } + +qreg q[2]; +creg rec[4]; + +measure q[0] -> rec[0];rec[0] = rec[0] ^ 1; +rec[1] = mx(q[0]) ^ 1; +rec[2] = mxx(q[0], q[1]) ^ 1; +h q[0];cx q[1],q[0];measure q[0] -> rec[3];rec[3] = rec[3] ^ 1;cx q[1],q[0];h q[0]; // decomposed MPP +)QASM"); +} + +TEST(export_qasm, export_open_qasm_qec) { Circuit c(R"CIRCUIT( R 0 1 2 TICK @@ -73,13 +96,12 @@ TEST(export_circuit, export_open_qasm_qec) { std::stringstream out; export_open_qasm(c, out, 3, false); ASSERT_EQ(out.str(), R"QASM(OPENQASM 3.0; - include "stdgates.inc"; -qubit q[3]; -bit rec[4]; -bit dets[3]; -bit obs[1]; +qreg q[3]; +creg rec[4]; +creg dets[3]; +creg obs[1]; reset q[0]; reset q[1]; @@ -119,7 +141,6 @@ obs[0] = obs[0] ^ rec[3] ^ 0; out.str(""); export_open_qasm(c, out, 2, true); ASSERT_EQ(out.str(), R"QASM(OPENQASM 2.0; - include "qelib1.inc"; qreg q[3]; @@ -157,7 +178,7 @@ measure q[2] -> rec[3]; )QASM"); } -TEST(export_circuit, export_qasm_decomposed_operations) { +TEST(export_qasm, export_qasm_decomposed_operations) { Circuit c(R"CIRCUIT( R 3 RX 0 1 @@ -176,17 +197,16 @@ TEST(export_circuit, export_qasm_decomposed_operations) { std::stringstream out; export_open_qasm(c, out, 3, false); ASSERT_EQ(out.str(), R"QASM(OPENQASM 3.0; - include "stdgates.inc"; -def mx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; h q0; return b; } -def mrx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; reset q0; h q0; return b; } def mr(qubit q0) -> bit { bit b; measure q0 -> b; reset q0; return b; } -def rx(qubit q0) { reset q0; h q0; } +def mrx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; reset q0; h q0; return b; } +def mx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; h q0; return b; } def mxx(qubit q0, qubit q1) -> bit { bit b; cx q0, q1; h q0; measure q0 -> b; h q0; cx q0, q1; return b; } +def rx(qubit q0) { reset q0; h q0; } -qubit q[5]; -bit rec[5]; -bit dets[1]; +qreg q[5]; +creg rec[5]; +creg dets[1]; reset q[3]; rx(q[0]); @@ -206,7 +226,6 @@ rec[4] = mrx(q[4]); out.str(""); export_open_qasm(c, out, 2, true); ASSERT_EQ(out.str(), R"QASM(OPENQASM 2.0; - include "qelib1.inc"; qreg q[5]; @@ -227,52 +246,52 @@ h q[4]; measure q[4] -> rec[4]; reset q[4]; h q[4]; // decomposed MRX )QASM"); } -TEST(export_circuit, export_qasm_all_operations) { +TEST(export_qasm, export_qasm_all_operations) { Circuit c = generate_test_circuit_with_all_operations(); c = c.without_noise(); std::stringstream out; export_open_qasm(c, out, 3, false); ASSERT_EQ(out.str(), R"QASM(OPENQASM 3.0; - include "stdgates.inc"; gate cxyz q0 { U(pi/2, 0, pi/2) q0; } gate czyx q0 { U(pi/2, pi/2, pi/2) q0; } -gate sy q0 { U(pi/2, 0, 0) q0; } -gate sydg q0 { U(pi/2, pi/2, pi/2) q0; } gate hxy q0 { U(pi/2, 0, pi/2) q0; } gate hyz q0 { U(pi/2, pi/2, pi/2) q0; } -gate xcx q0, q1 { h q0; cx q0, q1; h q0; } -gate xcy q0, q1 { h q0; s q1; s q1; s q1; cx q0, q1; h q0; s q1; } -gate xcz q0, q1 { cx q1, q0; } -gate ycx q0, q1 { s q0; s q0; s q0; h q1; cx q1, q0; s q0; h q1; } -gate ycy q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q0; cx q0, q1; h q0; s q0; s q1; } -gate ycz q0, q1 { s q0; s q0; s q0; cx q1, q0; s q0; } +gate sy q0 { U(pi/2, 0, 0) q0; } +gate sydg q0 { U(pi/2, pi/2, pi/2) q0; } +gate cxswap q0, q1 { cx q1, q0; cx q0, q1; } +gate iswap q0, q1 { h q0; cx q0, q1; cx q1, q0; h q1; s q1; s q0; } +gate iswapdg q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q1; cx q1, q0; cx q0, q1; h q0; } gate sxx q0, q1 { h q0; cx q0, q1; h q1; s q0; s q1; h q0; h q1; } gate sxxdg q0, q1 { h q0; cx q0, q1; h q1; s q0; s q0; s q0; s q1; s q1; s q1; h q0; h q1; } gate syy q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q0; cx q0, q1; h q1; s q0; s q1; h q0; h q1; s q0; s q1; } gate syydg q0, q1 { s q0; s q0; s q0; s q1; h q0; cx q0, q1; h q1; s q0; s q1; h q0; h q1; s q0; s q1; s q1; s q1; } gate szz q0, q1 { h q1; cx q0, q1; h q1; s q0; s q1; } gate szzdg q0, q1 { h q1; cx q0, q1; h q1; s q0; s q0; s q0; s q1; s q1; s q1; } -gate iswap q0, q1 { h q0; cx q0, q1; cx q1, q0; h q1; s q1; s q0; } -gate cxswap q0, q1 { cx q1, q0; cx q0, q1; } gate swapcx q0, q1 { cx q0, q1; cx q1, q0; } -gate iswapdg q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q1; cx q1, q0; cx q0, q1; h q0; } -def mx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; h q0; return b; } -def my(qubit q0) -> bit { bit b; s q0; s q0; s q0; h q0; measure q0 -> b; h q0; s q0; return b; } +gate xcx q0, q1 { h q0; cx q0, q1; h q0; } +gate xcy q0, q1 { h q0; s q1; s q1; s q1; cx q0, q1; h q0; s q1; } +gate xcz q0, q1 { cx q1, q0; } +gate ycx q0, q1 { s q0; s q0; s q0; h q1; cx q1, q0; s q0; h q1; } +gate ycy q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q0; cx q0, q1; h q0; s q0; s q1; } +gate ycz q0, q1 { s q0; s q0; s q0; cx q1, q0; s q0; } +def mr(qubit q0) -> bit { bit b; measure q0 -> b; reset q0; return b; } def mrx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; reset q0; h q0; return b; } def mry(qubit q0) -> bit { bit b; s q0; s q0; s q0; h q0; measure q0 -> b; reset q0; h q0; s q0; return b; } -def mr(qubit q0) -> bit { bit b; measure q0 -> b; reset q0; return b; } -def rx(qubit q0) { reset q0; h q0; } -def ry(qubit q0) { reset q0; h q0; s q0; } +def mx(qubit q0) -> bit { bit b; h q0; measure q0 -> b; h q0; return b; } def mxx(qubit q0, qubit q1) -> bit { bit b; cx q0, q1; h q0; measure q0 -> b; h q0; cx q0, q1; return b; } +def my(qubit q0) -> bit { bit b; s q0; s q0; s q0; h q0; measure q0 -> b; h q0; s q0; return b; } def myy(qubit q0, qubit q1) -> bit { bit b; s q0; s q1; cx q0, q1; h q0; measure q0 -> b; s q1; s q1; h q0; cx q0, q1; s q0; s q1; return b; } def mzz(qubit q0, qubit q1) -> bit { bit b; cx q0, q1; measure q1 -> b; cx q0, q1; return b; } +def rx(qubit q0) { reset q0; h q0; } +def ry(qubit q0) { reset q0; h q0; s q0; } -qubit q[18]; -bit rec[20]; -bit dets[1]; -bit obs[1]; +qreg q[18]; +creg rec[25]; +creg dets[1]; +creg obs[1]; +creg sweep[1]; id q[0]; x q[1]; @@ -360,39 +379,64 @@ dets[0] = rec[16] ^ 0; obs[0] = obs[0] ^ rec[16] ^ 0; barrier q; +rec[20] = mrx(q[0]) ^ 1; +rec[21] = my(q[1]) ^ 1; +rec[22] = mzz(q[2], q[3]) ^ 1; +rec[23] = myy(q[4], q[5]); +h q[6];sx q[7];cx q[7],q[6];cx q[8],q[6];measure q[6] -> rec[24];rec[24] = rec[24] ^ 1;cx q[7],q[6];cx q[8],q[6];sxdg q[7];h q[6]; // decomposed MPP +barrier q; + +if (ms[24]) { + X q[0]; +} +if (sweep[0]) { + Y q[1]; +} +if (ms[24]) { + Z q[2]; +} )QASM"); out.str(""); c = circuit_with_inlined_feedback(c); + for (size_t k = 0; k < c.operations.size(); k++) { + bool drop = false; + for (auto t : c.operations[k].targets) { + drop |= t.is_sweep_bit_target(); + } + if (drop) { + c.operations.erase(c.operations.begin() + k); + k--; + } + } export_open_qasm(c, out, 2, true); ASSERT_EQ(out.str(), R"QASM(OPENQASM 2.0; - include "qelib1.inc"; gate cxyz q0 { U(pi/2, 0, pi/2) q0; } gate czyx q0 { U(pi/2, pi/2, pi/2) q0; } -gate sy q0 { U(pi/2, 0, 0) q0; } -gate sydg q0 { U(pi/2, pi/2, pi/2) q0; } gate hxy q0 { U(pi/2, 0, pi/2) q0; } gate hyz q0 { U(pi/2, pi/2, pi/2) q0; } -gate xcx q0, q1 { h q0; cx q0, q1; h q0; } -gate xcy q0, q1 { h q0; s q1; s q1; s q1; cx q0, q1; h q0; s q1; } -gate xcz q0, q1 { cx q1, q0; } -gate ycx q0, q1 { s q0; s q0; s q0; h q1; cx q1, q0; s q0; h q1; } -gate ycy q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q0; cx q0, q1; h q0; s q0; s q1; } -gate ycz q0, q1 { s q0; s q0; s q0; cx q1, q0; s q0; } +gate sy q0 { U(pi/2, 0, 0) q0; } +gate sydg q0 { U(pi/2, pi/2, pi/2) q0; } +gate cxswap q0, q1 { cx q1, q0; cx q0, q1; } +gate iswap q0, q1 { h q0; cx q0, q1; cx q1, q0; h q1; s q1; s q0; } +gate iswapdg q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q1; cx q1, q0; cx q0, q1; h q0; } gate sxx q0, q1 { h q0; cx q0, q1; h q1; s q0; s q1; h q0; h q1; } gate sxxdg q0, q1 { h q0; cx q0, q1; h q1; s q0; s q0; s q0; s q1; s q1; s q1; h q0; h q1; } gate syy q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q0; cx q0, q1; h q1; s q0; s q1; h q0; h q1; s q0; s q1; } gate syydg q0, q1 { s q0; s q0; s q0; s q1; h q0; cx q0, q1; h q1; s q0; s q1; h q0; h q1; s q0; s q1; s q1; s q1; } gate szz q0, q1 { h q1; cx q0, q1; h q1; s q0; s q1; } gate szzdg q0, q1 { h q1; cx q0, q1; h q1; s q0; s q0; s q0; s q1; s q1; s q1; } -gate iswap q0, q1 { h q0; cx q0, q1; cx q1, q0; h q1; s q1; s q0; } -gate cxswap q0, q1 { cx q1, q0; cx q0, q1; } gate swapcx q0, q1 { cx q0, q1; cx q1, q0; } -gate iswapdg q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q1; cx q1, q0; cx q0, q1; h q0; } +gate xcx q0, q1 { h q0; cx q0, q1; h q0; } +gate xcy q0, q1 { h q0; s q1; s q1; s q1; cx q0, q1; h q0; s q1; } +gate xcz q0, q1 { cx q1, q0; } +gate ycx q0, q1 { s q0; s q0; s q0; h q1; cx q1, q0; s q0; h q1; } +gate ycy q0, q1 { s q0; s q0; s q0; s q1; s q1; s q1; h q0; cx q0, q1; h q0; s q0; s q1; } +gate ycz q0, q1 { s q0; s q0; s q0; cx q1, q0; s q0; } qreg q[18]; -creg rec[20]; +creg rec[25]; id q[0]; x q[1]; @@ -478,5 +522,12 @@ measure q[0] -> rec[15]; reset q[0]; // decomposed MR measure q[0] -> rec[16]; reset q[0]; // decomposed MR barrier q; +h q[0]; x q[0];measure q[0] -> rec[20];x q[0]; reset q[0]; h q[0]; // decomposed MRX +s q[1]; s q[1]; s q[1]; h q[1]; x q[1];measure q[1] -> rec[21];x q[1]; h q[1]; s q[1]; // decomposed MY +cx q[2], q[3]; x q[3];measure q[3] -> rec[22];x q[3]; cx q[2], q[3]; // decomposed MZZ +s q[4]; s q[5]; cx q[4], q[5]; h q[4]; measure q[4] -> rec[23]; s q[5]; s q[5]; h q[4]; cx q[4], q[5]; s q[4]; s q[5]; // decomposed MYY +h q[6];sx q[7];cx q[7],q[6];cx q[8],q[6];x q[6];measure q[6] -> rec[24];x q[6];cx q[7],q[6];cx q[8],q[6];sxdg q[7];h q[6]; // decomposed MPP +barrier q; + )QASM"); } diff --git a/src/stim/circuit/export_qasm_pybind_test.py b/src/stim/circuit/export_qasm_pybind_test.py new file mode 100644 index 000000000..f25308445 --- /dev/null +++ b/src/stim/circuit/export_qasm_pybind_test.py @@ -0,0 +1,95 @@ +import pytest +import stim + + +def test_to_qasm_exact_strings(): + c = stim.Circuit(""" + RX 0 1 + TICK + H 1 + CX 0 1 + TICK + M 0 1 + DETECTOR rec[-1] rec[-2] + C_XYZ 0 + """) + + assert c.to_qasm(open_qasm_version=3).strip() == """ +OPENQASM 3.0; +include "stdgates.inc"; +gate cxyz q0 { U(pi/2, 0, pi/2) q0; } +def rx(qubit q0) { reset q0; h q0; } + +qreg q[2]; +creg rec[2]; +creg dets[1]; + +rx(q[0]); +rx(q[1]); +barrier q; + +h q[1]; +cx q[0], q[1]; +barrier q; + +measure q[0] -> rec[0]; +measure q[1] -> rec[1]; +dets[0] = rec[1] ^ rec[0] ^ 0; +cxyz q[0]; + """.strip() + + assert c.to_qasm(open_qasm_version=2, skip_dets_and_obs=True).strip() == """ +OPENQASM 2.0; +include "qelib1.inc"; +gate cxyz q0 { U(pi/2, 0, pi/2) q0; } + +qreg q[2]; +creg rec[2]; + +reset q[0]; h q[0]; // decomposed RX +reset q[1]; h q[1]; // decomposed RX +barrier q; + +h q[1]; +cx q[0], q[1]; +barrier q; + +measure q[0] -> rec[0]; +measure q[1] -> rec[1]; +cxyz q[0]; + """.strip() + + +def test_to_qasm2_runs_in_qiskit(): + pytest.importorskip("qiskit") + pytest.importorskip("qiskit_aer") + import qiskit + import qiskit_aer + + stim_circuit = stim.Circuit(""" + R 0 1 + MZZ !0 1 + """) + qasm = stim_circuit.to_qasm(open_qasm_version=2) + + qiskit_circuit = qiskit.QuantumCircuit.from_qasm_str(qasm) + counts = qiskit_aer.AerSimulator().run(qiskit_circuit, shots=8).result().get_counts(qiskit_circuit) + assert counts['1'] == 8 + + +def test_to_qasm3_parses_in_qiskit(): + pytest.importorskip("qiskit") + pytest.importorskip("qiskit_qasm3_import") + import qiskit.qasm3 + + # Note: can't really exercise this because currently `qiskit.qasm3.loads` + # fails on subroutines, classical assignments, and all the other non-qasm-2 + # stuff that's actually worth testing. + stim_circuit = stim.Circuit(""" + R 0 1 + SQRT_XX 0 1 + M 0 1 + """) + + qiskit_circuit = qiskit.qasm3.loads(stim_circuit.to_qasm(open_qasm_version=3)) + assert qiskit_circuit is not None diff --git a/src/stim/diagram/timeline/timeline_ascii_drawer.test.cc b/src/stim/diagram/timeline/timeline_ascii_drawer.test.cc index cf5be8140..98a8ec4d2 100644 --- a/src/stim/diagram/timeline/timeline_ascii_drawer.test.cc +++ b/src/stim/diagram/timeline/timeline_ascii_drawer.test.cc @@ -513,43 +513,48 @@ TEST(circuit_diagram_timeline_text, repetition_code_transposed) { TEST(circuit_diagram_timeline_text, test_circuit_all_ops) { auto circuit = generate_test_circuit_with_all_operations(); + std::cerr << "\n" + DiagramTimelineAsciiDrawer::make_diagram(circuit).str() + "\n" << "===============\n"; + std::cerr << "\n" + DiagramTimelineAsciiDrawer::make_diagram(circuit).str() + "\n" << "===============\n"; + std::cerr << "\n" + DiagramTimelineAsciiDrawer::make_diagram(circuit).str() + "\n" << "===============\n"; + std::cerr << "\n" + DiagramTimelineAsciiDrawer::make_diagram(circuit).str() + "\n" << "===============\n"; + std::cerr << "\n" + DiagramTimelineAsciiDrawer::make_diagram(circuit).str() + "\n" << "===============\n"; ASSERT_EQ("\n" + DiagramTimelineAsciiDrawer::make_diagram(circuit).str() + "\n", R"DIAGRAM( /-------------------\ /--------------\ /---------------------\ /-----------------------------------------------------------------------------------------------------------------------------------------------------\ /------------------------------------\ /REP 3 /---\ \ /--------------------------------------------------------------------------------------------------------------------------\ - q0: -QUBIT_COORDS(1,2,3)-I-C_XYZ-SQRT_X-----ZSWAP-----SQRT_XX-----X------------DEPOLARIZE1(0.02)---------------X_ERROR(0.01)------------------------------------------------------------------------------------------------MPP[X]:rec[2]-MPP[Z]:rec[3]-MRX:rec[4]-MXX:rec[11]-|------H-@---|---MR:rec[15]-X_ERROR(0.1)-MR(0.01):rec[16]-DETECTOR(2,4,6):D0=rec[16]-OBSERVABLE_INCLUDE:L0*=rec[16]-MPAD:rec[17]-MPAD:rec[19]- + q0: -QUBIT_COORDS(1,2,3)-I-C_XYZ-SQRT_X-----ZSWAP-----SQRT_XX-----X------------DEPOLARIZE1(0.02)---------------X_ERROR(0.01)------------------------------------------------------------------------------------------------MPP[X]:rec[2]-MPP[Z]:rec[3]-MRX:rec[4]-MXX:rec[11]-|------H-@---|---MR:rec[15]-X_ERROR(0.1)-MR(0.01):rec[16]-DETECTOR(2,4,6):D0=rec[16]-OBSERVABLE_INCLUDE:L0*=rec[16]-MPAD:rec[17]-MPAD:rec[19]-MRX:rec[20]----X^rec[24]-- | | | | | | | | | - q1: ---------------------X-C_ZYX-SQRT_X_DAG-XSWAP-----SQRT_XX-----X-E[X](0.01)-DEPOLARIZE2(0.03)---------------Y_ERROR(0.02)------------------------------------------------------------------------------------------------MPP[Y]:rec[2]-MPP[Z]:rec[3]-MRY:rec[5]-MXX---------|--------X-S-|------------------------------------------------------------------------------------------------------MPAD:rec[18]-------------- + q1: ---------------------X-C_ZYX-SQRT_X_DAG-XSWAP-----SQRT_XX-----X-E[X](0.01)-DEPOLARIZE2(0.03)---------------Y_ERROR(0.02)------------------------------------------------------------------------------------------------MPP[Y]:rec[2]-MPP[Z]:rec[3]-MRY:rec[5]-MXX---------|--------X-S-|------------------------------------------------------------------------------------------------------MPAD:rec[18]--------------MY:rec[21]-----Y^sweep[0]- | | | | | - q2: ---------------------Y-H_XY--SQRT_Y-----ISWAP-----SQRT_XX_DAG-X-E[Y](0.01)-DEPOLARIZE2(0.03)---------------Z_ERROR(0.03)------------------------------------------------------------------------------------------------MPP[Z]:rec[2]---------------MR:rec[6]--MXX:rec[12]-|------------|-------------------------------------------------------------------------------------------------------------------------------- - | | | | | | | - q3: ---------------------Z-H-----SQRT_Y_DAG-ISWAP-----SQRT_XX_DAG-Y-E[Z](0.01)-PAULI_CHANNEL_1(0.01,0.02,0.03)-HERALDED_ERASE(0.04):rec[0]--------------------------------------------------------------------------------------------------------------MX:rec[7]--MXX---------|------------|-------------------------------------------------------------------------------------------------------------------------------- + q2: ---------------------Y-H_XY--SQRT_Y-----ISWAP-----SQRT_XX_DAG-X-E[Y](0.01)-DEPOLARIZE2(0.03)---------------Z_ERROR(0.03)------------------------------------------------------------------------------------------------MPP[Z]:rec[2]---------------MR:rec[6]--MXX:rec[12]-|------------|--------------------------------------------------------------------------------------------------------------------------------MZZ:rec[22]----Z^rec[24]-- + | | | | | | | | + q3: ---------------------Z-H-----SQRT_Y_DAG-ISWAP-----SQRT_XX_DAG-Y-E[Z](0.01)-PAULI_CHANNEL_1(0.01,0.02,0.03)-HERALDED_ERASE(0.04):rec[0]--------------------------------------------------------------------------------------------------------------MX:rec[7]--MXX---------|------------|--------------------------------------------------------------------------------------------------------------------------------MZZ----------------------- | | - q4: -----------------------H_YZ--S----------ISWAP_DAG-SQRT_YY-----X------------ELSE_CORRELATED_ERROR[X](0.02)--PAULI_CHANNEL_2[0](0.001,0.002,0.003,0.004,0.005,0.006,0.007,0.008,0.009,0.01,0.011,0.012,0.013,0.014,0.015)-----------------------------MY:rec[8]--MYY:rec[13]-|------------|-------------------------------------------------------------------------------------------------------------------------------- - | | | | | | | | - q5: -----------------------------S_DAG------ISWAP_DAG-SQRT_YY-----@------------|-------------------------------PAULI_CHANNEL_2[1](0.001,0.002,0.003,0.004,0.005,0.006,0.007,0.008,0.009,0.01,0.011,0.012,0.013,0.014,0.015)-----------------------------M:rec[9]---MYY---------|------------|-------------------------------------------------------------------------------------------------------------------------------- + q4: -----------------------H_YZ--S----------ISWAP_DAG-SQRT_YY-----X------------ELSE_CORRELATED_ERROR[X](0.02)--PAULI_CHANNEL_2[0](0.001,0.002,0.003,0.004,0.005,0.006,0.007,0.008,0.009,0.01,0.011,0.012,0.013,0.014,0.015)-----------------------------MY:rec[8]--MYY:rec[13]-|------------|--------------------------------------------------------------------------------------------------------------------------------MYY:rec[23]--------------- + | | | | | | | | | + q5: -----------------------------S_DAG------ISWAP_DAG-SQRT_YY-----@------------|-------------------------------PAULI_CHANNEL_2[1](0.001,0.002,0.003,0.004,0.005,0.006,0.007,0.008,0.009,0.01,0.011,0.012,0.013,0.014,0.015)-----------------------------M:rec[9]---MYY---------|------------|--------------------------------------------------------------------------------------------------------------------------------MYY----------------------- | | | - q6: ----------------------------------------SWAP------SQRT_YY_DAG-Y------------ELSE_CORRELATED_ERROR[Z](0.02)--HERALDED_PAULI_CHANNEL_1(0.01,0.02,0.03,0.04):rec[1]-------------------------------------------------------------------------------------M:rec[10]--MZZ:rec[14]-|------------|-------------------------------------------------------------------------------------------------------------------------------- - | | | | | | | - q7: ----------------------------------------SWAP------SQRT_YY_DAG-X------------ELSE_CORRELATED_ERROR[Y](0.02)-------------------------------------------------------------------------------------------------------------------------------------------RX---------MZZ---------|------------|-------------------------------------------------------------------------------------------------------------------------------- - | | - q8: ----------------------------------------XSWAP-----SQRT_ZZ-----Y-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------RY---------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- + q6: ----------------------------------------SWAP------SQRT_YY_DAG-Y------------ELSE_CORRELATED_ERROR[Z](0.02)--HERALDED_PAULI_CHANNEL_1(0.01,0.02,0.03,0.04):rec[1]-------------------------------------------------------------------------------------M:rec[10]--MZZ:rec[14]-|------------|--------------------------------------------------------------------------------------------------------------------------------MPP[X]:rec[24]------------ + | | | | | | | | + q7: ----------------------------------------SWAP------SQRT_YY_DAG-X------------ELSE_CORRELATED_ERROR[Y](0.02)-------------------------------------------------------------------------------------------------------------------------------------------RX---------MZZ---------|------------|--------------------------------------------------------------------------------------------------------------------------------MPP[Y]:rec[24]------------ + | | | + q8: ----------------------------------------XSWAP-----SQRT_ZZ-----Y-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------RY---------------------|------------|--------------------------------------------------------------------------------------------------------------------------------MPP[Z]:rec[24]------------ | | | | | - q9: ----------------------------------------ZSWAP-----SQRT_ZZ-----Y-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------R----------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- + q9: ----------------------------------------ZSWAP-----SQRT_ZZ-----Y-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------R----------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | -q10: --------------------------------------------------SQRT_ZZ_DAG-Y------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q10: --------------------------------------------------SQRT_ZZ_DAG-Y------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | | | -q11: --------------------------------------------------SQRT_ZZ_DAG-@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q11: --------------------------------------------------SQRT_ZZ_DAG-@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | -q12: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q12: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | | -q13: --------------------------------------------------------------X------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q13: --------------------------------------------------------------X------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | -q14: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q14: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | | -q15: --------------------------------------------------------------Y------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q15: --------------------------------------------------------------Y------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | -q16: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q16: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- | | | -q17: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|-------------------------------------------------------------------------------------------------------------------------------- +q17: --------------------------------------------------------------@------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------- \-------------------/ \--------------/ \---------------------/ \-----------------------------------------------------------------------------------------------------------------------------------------------------/ \------------------------------------/ \ \---/ / \--------------------------------------------------------------------------------------------------------------------------/ )DIAGRAM"); } diff --git a/testdata/circuit_all_ops_3d.gltf b/testdata/circuit_all_ops_3d.gltf index ac324d752..d20d88a6f 100644 --- a/testdata/circuit_all_ops_3d.gltf +++ b/testdata/circuit_all_ops_3d.gltf @@ -1 +1 @@ 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kIaGBl2/fv27baWkpFC7du2oefPm9OTJE3J1dSUAZGhoSO/evePiJSUlkY6ODr18+bJC10EzMzMCUGQUSlEPQQBka2sruO2IiAj6/fffebdz8uRJ0tLSKvJRU1MjNTW1YsNOnjzJesgKTs+ePbnRqG/lh94JsFatWoI6AJYHYmJi4OLiInPtxo0baNy4saDpMDY2xk8//YSAgADo6uoiKioKLVu2FGwzpPHjx2Po0KFwdnYGANy9exc7duzAgAEDoK6ujvbt28PAwACzZs36LjuvXr1C06ZNkZ6ejoiICNSuXRsrV66ESCRCamoqJk6cyMUNCQnBypUr5bocsjzy9u1bbg5e0Uj9f1JSUgS33b59e3Ts2JF3O126dMHHjx+LfPz9/bFo0aJiw7p06cImyCswHz9+5FajfA8qP3IhfL4UsKIjdQLMy8sDEck4AObm5kIkEnHX+HICLA4vLy94e3ujffv2ePjwIVasWIH58+fzavPw4cNITk7G1q1buWt//PEHAKBOnTrcNWtra0RFRSE7O/ubndWGDBmC58+fY+PGjdxvNG3aFKNHj8bGjRuxe/dudOrUCbVq1UJSUhJWr15d4evi5yszFI2Ghgb3QGRUfPLz89G2bdtiwy5evCjonjCK5Pjx4/Dw8PjuVU8/tAD475twRWbJkiVYsmQJevbsCR8fH/To0YML69y5M6ZMmVJiw5Cn6tTW1i5y3dbWFhs3bkTXrl152Q74c54/f4558+YhKipKZhmk9A3w8xUhWlpaKCgowNu3b79JANy9exfnz58HAG6kQcqKFSsQFRWFe/fuYdSoUbCwsEBERESlqIsGBgZISUlBTk6OwtPy6dMnAEDVqlVZ71gJKCwsLPEZU1hYWGnK4dChQ5gyZcp3/84PPQVgbW0Na2vrStUArl+/XmS9f0xMjCBTAL/88ssXxZh0/T4fFBQUwMfHB2vWrCmy8Y6uri4AQCwWc9fy8vIA/LuBy7cQFxfH/f348eMib56HDh2ClpYWPnz4gKysLBnbUu7du1fh6qB0iiMjI0PhacnKygIA1K5dm/WOlYAqVarg/33XinwUtSOm0Hz48AF3795FixYtKq8AICKsW7cOGzdurDSV/8WLF1BVVZVZ75yYmIgaNWoI8gaUmpqKyMjIYsOuXbsG4N8pAb4ICgpCs2bNit31qlWrVgCApKQkmbKRbtz0LUi3IAaAgIAA5ObmyoQ/ffoUBgYGUFVVRWJiItzc3GTK5+jRo7h06VKFq4fSrZYTExMVnpbnz58DgOA+MJWdly9fYuzYsVi7dm2levP+nDVr1ijkILBjx46hW7duRfZh+daO9Ifk0qVLnAe6PDy9fwQOHTpEffv2lbl24MAB8vX1FcR+u3btyMzMjM6ePUtExB0GdPfuXTIzM6NBgwZRQUEBL7ajo6OpadOmlJ+fX+Iyvf/973/Upk0bKiwspJiYmBKX6n0Nnp6eXD2zt7engIAAWr58ObVv357q169PDx8+pD/++IN0dHS4eGZmZlSnTh2ytbUVdF24UEgPIurfv7/C0zJ48GACQGfOnKl0XuBLliyhVatWKcT2oEGDuPoeEhJS6cr+zz//5PJ/5coVQW136tSJO4zse/lhBcCbN2/I1taW6tWrJ7MUqyIzZcqUIg1+8uTJtHnzZkHs3759myZNmkSNGjUiR0dHMjU1pWbNmpGHhwevS8LevXtH9vb2FB8fX2q8jIwMGjhwILm7u5OzszOtWbPmu22LxWJat24dOTs7k7a2Nunq6lKLFi1o06ZNMhtwJCYm0sCBA6l69eqkp6dHXl5eRfZqqCiIxWKytrYmKysrhafF1taWzM3Nv2szFMbXs2HDBtLW1iZnZ2fq0KFDpct/Wloa2dnZUd26dSktLU0wu+np6VSnTh2ZzdC+BxHR/2+wzmB8JX5+fhg1apQg58AzyhdhYWEYOHAg7t27xx2QJTQJCQmwtbXF1q1bMXz4cHZTFEB0dDQ2b96Mffv2scL4AVFiRcD4Vjw8PL7ZwY7xY9O/f3+0b98e69atU1ga1q1bh1atWsHX15fdEAWxZ8+eUp2DGeUbNgLAYDC+iXfv3sHV1RW7du3iDkoSigcPHqBbt26IjIwU9Dhwxr/k5OQgODgYJiYmTAAwAcBgMCojSUlJGDlyJNauXQtbW1tBbL5+/Rq+vr6C2mTIEh4eDhcXF1hZWbHCYAKAwWBUVrKzs7F27Vp06NCB9+V4N2/exIkTJzBlyhRu7wcGg8EEAIPBUCCFhYXyWZusYBsMBhMADAaDwWAwKixMSjMYDAaDwQQAg8FgMBgMJgAYDAaDwWAwAcBgMBgMBoMJAAaDwWAwGEwAMBgMBoPBYAKAwWAwGAwGEwAMBoPBYDCYAGAwGAwGg/GjCYD3799j3LhxaNiwIRo1aoQBAwbg1atXgiY8NzcX69evh7m5OTIyMgSzm5OTgxkzZsDS0hJqamowNzfH+PHj8e7dO0HsSyQShISEoF69etDQ0ICFhQXmzJkDsVissEo0bNgwiEQi5ObmCmZz5syZEIlERT7//POPoHlPTk7G3Llz0alTJ4wdOxa7du3i1V7Tpk2Lzbf0Y2FhwXued+/ejZYtW6JDhw5wd3dHy5YtsXv3bsHK/OTJk2jTpg2aNWsGS0tLeHl54dGjR+xpzqgUnDhxAr6+vvD19YW9vT0cHR0RHBwMiUTy9T9GX0lqaio5OjqSt7c3icViIiKaM2cOmZiY0NOnT4lvcnNzafXq1VSnTh0CQADo/fv3JAQFBQXUqlUrUlZWJmtra6pRowaXhjp16lBycjKv9gsLC8nb25vq1atHPj4+5Orqytn39fUlRXDw4EEuDZ8+fRLEZnp6OlWtWpWUlZVlPh07dhQ078uWLSMdHR1avHgx5eXl8W7v1q1bBICUlZWpevXqZGhoKPMRiUQ0btw4XtMwbdo0MjExoUePHnHX7t+/T3p6ejRz5kzey2D58uVkYmJCd+/eJSKiDx8+UIcOHahq1ap07do1YjAqMoGBgeTt7U0FBQVERCQWi2nkyJEEgAYMGPDVv/fVAqBbt26ko6NDGRkZ3LW8vDwyNDQkNzc3Kiws5LUAxGIxvXv3jlJTU0lVVVVQAbBmzRpq3749JSYmctcOHDhAmpqaBIC8vb15tb9//34KDg6WuRYaGsp1wHwLkP+SmJhIderUoapVqwoqAObMmUNLly5VWCOUSCTUp08fUlNToz/++EMwu6NGjaIlS5ZQdnZ2sfcCAP3555+82Y+PjyeRSESrV68uEjZjxgwSiUSUlJTEm/2//vqLlJSUaPv27TLX09LSSFNTkywsLIotG4awbSM8PJxiY2MrTJ5u375NR44c4TpdRZGRkUGqqqq0bNkymes5OTmkp6dHAOjvv//mTwBERUURAPLy8ioS5uvrSwDo+PHjghWImZmZoAJg0KBBlJOTU+T6qlWrCABpaWnxar+km2tra0sA6MGDB4KVvVgsJldXVzp58iSZmpoKJgDevXtHVlZWlJWVpbCGKK3r/+2I+C7vjRs3lhgeHBxMZmZmvArw/fv3E4Bi07Fu3ToCwOtbuKenJwGgx48fFwnz8fEhALR27VrWCyuA9PR0Wrp0KVlaWlL37t3p2bNnFSZvCQkJ9L///Y+srKwoJCRE5uVXSJ4+fUoAqHbt2kXauXQ0ODQ09Kt+86t8AA4ePAgAcHFxKXZuEgDvc6Cfo6amJujci5+fHzQ0NIpc79evHwBALBaDeDxc8aeffir2es2aNeHg4IC6desKVhbz5s1DkyZN0KVLF0HvwerVq5GSkoIePXpg2bJlSE5OFtT+7t27sWPHDrRt2xa+vr6C2VVRUcHo0aNLDD906BD69OkDkUjEWxpMTU0BAJs3b0Z+fr5MWGxsLIyNjdGgQQPe7F+8eBEAYGhoWCSsdevWAIDjx4+zSWIBiYuLw8iRI1G/fn28efMGFy9exLFjxwTxRREKa2trREZG4ujRo4iLi4O1tTXGjRuH+Ph4QdNhaWmJzp07Q0VFBYWFhUX88j5vo7z4ANSuXZsA0L59+4qERUREEAAyNDQUTBFJ/QCEGgEobdhLJBJRw4YNFTIsVLNmTYqJiRHMZmRkJDVu3Jib9xZqBCAjI4OqVavGTXkAoCpVqtD8+fMFGZ77+PEjGRsbEwA6f/58uXlDefLkCQGg69ev82qnsLCQHB0dCQB169aNG26/ffs2VatWjX7//XfebOfm5nL3/MWLF0XCz549SwDI2NhYsBGZVq1akZmZmYw/hFB8+PCBnJycqHbt2vTy5UtBbRcUFNCxY8eobdu2ZGdnRxs2bKCPHz/yZu/kyZOkpaX1VZ+jR4/ylp43b95QUFAQmZiYkIeHB507d06h7T85OZlUVFTIwsKCcnNz+ZkCKCwsJGVlZQJAly5dKnZ4WtpAMzMzK5UAiIuLIwC0atUqQe1mZWVRly5daNu2bYLZTEtLo7p161J8fDx3TSgBkJmZSVeuXKHjx4/TjBkzyNLSkqtzvXr14l0E7Nmzh+tkoqOjydvbm2xsbMja2ppGjRpFqampCql/ixcvJktLS0FsxcfHcyLI2dmZzpw5Qy1btqQbN27wbltLS4sAFPtwP336NAEgbW1twR66IpGIANCuXbsEv+exsbFc3T99+rRgLxshISFUp04d6tSpE/3xxx+8+3yVZ/Ly8mj37t3k4uJC9vb2tHnzZoX4oEybNo2UlZW/6aWkzAIgLS2Nq3DFNfZ79+5x4Xw6ApVHATBnzhyysLAo1j+AD168eEELFy7kfCCUlZVp9uzZgtju1q0b7d69W+aakD4A/30rDAoK4h7EK1eu5NVejx49OAEQFBREsbGxdPv2bW5u2tLSUiEiwNnZmWbMmCGYvcTERHJwcODau1DCt3v37gSAfv755yJhUmfYWrVqCVYOe/bsoaCgIEFWgBRHaGgohYSE8C58k5OTacyYMWRsbEx+fn4y4p/xL5cvX6bevXtTzZo1acaMGZSWliaI3ZSUFNLU1CzVP0guAuDly5dcg79z506pilSoh2B5EACpqamkr69PERERgnZ8iYmJtHfvXnJxceHKfcuWLbzaXbt2LQ0aNKjIdUUJACkrV64kAGRmZsarnbp16xIA2rBhg8z1/Px8sre3JwA0ePBgQfMeHx9PAOjWrVuC2bx+/Tr17t2bAgMDSUlJiQDQ6NGjee+I7ty5w624mTJlCn348IEyMzPpwIED3LOgc+fOrDeSM8+ePSNPT08yMjKigIAASklJYYXyH7KysmjdunVkbm5OP//8syBL4omIJk2aRNOmTfvm75dZAHz8+LHUEYCrV68SABKJRCSRSCqNAOjVqxctXLhQYfYlEgkNGjSIAJC9vT1vdmJjY8nJyalY73tFC4DCwkJq2LAhAaDXr1/zZkdXV7fEIej169cTAKpataqgw6ILFiwgW1tbwexFRESQiYkJt+T0t99+oypVqnAigG+uXbvGiV4lJSWqV68erVu3jqysrAgAbdq0ifVGPPH06VOaPHky1axZk3x8fATzOzp16hTp6up+1Ueo1WiPHz+miRMnkqmpKY0ZM4YePnwo6Iugh4fHd/W3X+UEKH3QF+fsc+rUKcGH4BQtAFasWEEjRoxQeMNMS0sjNTU1UlVV5c2GdOlbWT7STVqEJDAwkADw6hAlnfsurv7fv3+fy/+HDx8Ey7ejoyP5+/sLYuvdu3ekp6dH06dPl7n++++/c3tyCLUZT3p6OjfMeuPGDQJAenp6gpZ9ZX/btbW1pZYtW1J4eLhgL33lhfPnz1PXrl3J2tpaYUsDr169SocOHfqu31D5mhUDrVq1wv79+/HkyZMiYc+ePQMAuLu7V4rlL4cPH8bNmzcRFham8LRUr14dLi4uvG6H2rhxY2RnZ5e4NeWnT5/g5eUFJSUlVKtWTfAyMDExQfXq1WFkZMSbDTs7OyQnJ+PNmzdFwszMzAAA6urq0NbWFiTPjx49wt27d7F//35B7O3fvx/v37+Hq6urzPWOHTsiMDAQs2fPxokTJ7glwXyir6/P/e3v7w8AWLhwIapWrcrW5vGMtrY2/Pz8MHbsWJw5cwZr1qzB1KlT4efnh2HDhimk/QtBTk4O9u7di7Vr18LQ0BDjx49H165doaSkmCN1nj59+v1t7WvUgtTTtrh54OHDhxMAOnXqVIUfATh16hT17NmT8vPzix2SVwT169enfv36KcS2oqcAiIh++eUXmjJlCq821q5dSwBo1KhRRcJevHhRooMan6MeDg4Ogtnz9/cvcQokOTmZAJCfn5+g9126FXXv3r0rtUe6orl37x6NHDmSDAwMaOzYsQpbEcMHb9++penTp5OpqSmNGDGC4uLiykW65FHfv3orYFdXV6pevbrMwz4vL48MDAyoadOmgjZC6b4EQgqAkydPUteuXYtdb/nq1Svy8fHhzXZ+fn6xAuPatWukra1N9+7dq9AC4OnTp3ThwoVi8+/g4MB7PcjJySFzc3PS09Mr4gtx6NAhEolExS6R5Qt7e3sKCgoSzF5kZCQBoKlTpxYJe/jwIQGgEydOCJae69evk6amJnl6eipEfG7fvp3mz5+vkFUA79+/p8mTJ1NQUNBXr/3me2pm6dKl9Ndff1UYAfDnn3/S0qVLKT09vdykKT8/nxYvXvzdS8C/WgA8efKEDA0NuYM/CgoKyM/Pj0xMTOjJkyeCFoL0MJ7nz58LYi8sLIxUVVXJxcWF3NzcuI+rqys5OTmRiooKr0uizM3NSVdXl2bPnk0JCQn07t07OnToENnY2NDZs2cVVhmFEgDS7S5btmxJhw8fpujoaJo/fz41a9ZM5nwGPomJiSEdHR0aMGAAJ8ZevnxJNjY2tGjRIkHfuAAIvgnNiBEjqEqVKhQdHc1dy87Opq5du37TYSTfyq+//ko1atSgRYsWKWSP9mfPnnE+H3v37hXcfkBAAGef7wOgGOWP8PBw7v5/zzMA3/KlxMRE6t27N7m6upKbm5vgQz4bNmyg3r17cwXg6upKS5cu5bUDOnLkCLfevKSPiooKr+UQGBhIpqampKqqSlWrViVnZ2eaOXOmwpflCCUAoqOjycXFhTQ0NEhPT49at25NoaGhxU7F8Mndu3epc+fO5OzsTF5eXtSlSxdBz8CQdgDOzs6C3+vCwkLasmULNWnShDp27EgDBgygLl260ObNm3kf/du3bx9NnTqVunXrRtOmTVPofvO5ubnUtGlTMjMzo4SEBMHtHz9+nHR0dMjFxYVsbGxYj1jJePr0KZmbm1Pjxo2/a/MhERGPm9czGAwGgzeSkpLQr18/XL16lRUG46tRYkXAYDAYPyZ79uzBqFGjWEEwvgkVVgQMBoPxYyGRSLBx40aIxWL4+PiwAmF8E2wKgMFgMH4w/vjjD5iamsLR0ZEVBoMJAAaDwWAwGGWH+QAwGAwGg8EEAIPBYDAYDCYAGAwGg8FgMAHAYDAYDAaDCQAGg8FgMBhMADAYDAaDwWACgMFgMBgMBhMADAaDwWAwmABgMBgMBoPBBACDwWAwGAwh+erDgMRiMU6ePIkzZ85ALBZDXV0dRIScnByoqKjgp59+wuDBg6Gjo8NKl8FgMBiM8gp9Bbt37yY3NzfasGEDZWRkFAkvKCig33//nTw9PemPP/4gvhk7dixdvHiRVxsXLlygmTNnkq6uLgEgAKShoUG2trbk4uJClpaWZGtrSwMGDKCzZ8+SEERFRdHgwYOpTp06ZGxsTA0bNqTmzZvTggUL6Pnz53TlyhVauHDhd9t59OgRLVy4kOrVq8flHQCpqamRsbEx6evrk6WlJbVp04ZmzZpF//zzDy/5PXz4ME2YMIE0NDQIAKmrq5OFhYXMx9TUlNTV1QkA+fv7y9X+gwcPaMGCBWRlZcWVgYmJiYx9fX19LmzBggW83fu3b99SSEgItWjRghwcHMjJyYmaNGlCbdq0oVWrVlFSUhKNGTOG8vLy5Hb/69aty+XN2NiYZsyYQTdu3ODiHTt2jCZMmEBqampcvP/973+0fPlyys7Olmv+79y5Q4GBgWRpacnZMjc3p/nz59OdO3cEaX/S+lC7dm2Z+jBv3jyKiYmRmx1p+depU0em/OfNm8e1tYyMDFq4cCFpa2sTABKJRNSlSxc6cOCA3NJx8OBBGjNmDKmqqnLpcHFxoYCAALp9+7bcy/fhw4c0c+ZMMjIy4uxt3769zN8fOGu29kwAACAASURBVHCgTD0MDg7+6nqYm5tLixYtIjc3N+63+vfvX2L8Z8+e0aJFi8jJyYkAkJOTEy1atIhevHgh17KJiYmhX375hezt7cnW1pYsLCzI3t6eJk6cSE+ePPnq3yuTAMjOzqYePXrQsGHDylSQEomEZsyYQaGhobw1woyMDNLW1qYePXoI0uhXr15NAEhLS6tI2OXLl8nR0ZEAkI+PD4nFYl7SkJmZSX369CFlZWWaPn06JSUlcWE5OTm0a9cuMjU1JWVlZZo0aZJcH7rSRhAeHk4SiYQLi42NpfHjx3MPBx8fH/r48SMv+R89ejQBIDc3txIb7eDBg2nixIm82P/777+5cnjw4EGxD+yGDRvSzJkzebF/6NAh0tHRoRYtWlB0dDQVFhZyYampqTRnzhxSUVEhAHJ98MTGxnL5PnHiRInxpk2bRgCoRo0alJ+fz7sIlqYpMjKSFME///zDpeH06dO82YmJieHsnDx5stg4jo6OZGhoSFFRUbylw9fXlwCQoaGhXATmlzh79iyX73r16snU95J4+fIl9yzS1taWSz2cP38+l47g4OAvihcAlJiYKNeyyM7OJl9fX1JTU6MlS5bQu3fvuLCEhATy9vbmwuQqAHJzc6lFixbf9FY1ZMgQunfvHi+VIyQkhACQsrIyPX/+nPfKeOzYsRIFABFReno6p1hDQkJ4ETz16tUjJSUlOnbsWInxkpKSyMzMjAYPHixX29IG8Pmb3+f8+eefpKenx6luPjqAwMDAUgWA9A15xIgRvNSBly9flioApGJpwoQJcre9YMEC7i2koKCgVJEAgG7duiU322lpaVy+S3vDlbZJR0dH3tvj48ePuTR9y5uPPEhJSeHSEBsbqzA7y5YtI0tLS3r69Cmv+ZV2hE2bNhWkfJOSkkhNTY0bWTp+/PgXvzN16lRuNKROnTpyS4t0BFhJSYl+//33UjtqADIvSd9Lbm4utW7dmgDQoUOHSozn5+dHAGj8+PFl/u0vOgGOGTMGpqamCAoK+urphdWrV8Pf31/u0xaFhYVYv349tLW1UVBQgE2bNvE+VaKsrFxquL6+Pvr27QsA2L17t9ztDx8+HA8ePMDw4cPRvXv3EuPVqlULW7Zswfv37wXLOwC4ubkhLCwMAHDp0iUsXbpU7mWgpPRln9UaNWqga9euCqkDAODo6Fjq/fkWIiIiEBAQACsrK+zcubPUcvDy8sKgQYPw5s0bXvJdmm1pWFnuk1BpqghpKM3Or7/+ig0bNiAyMhJWVlaC5FdFRUWQ8lVVVYWGhgYGDBgAAFi2bFmp8bOysrBt2zYMGzaMl3TWq1cPhYWF6N+/PxISEkptA2V5VpSVCRMmICoqCj169ICXl1eJ8YKDg2FoaIi1a9di7969ZXumlhYYGRmJY8eOYePGjd+UcF1dXdSoUQPPnj2T6404fvw4NDQ0EBgYCADYtm0bcnNzFe5PIb3pqampcv3d33//HeHh4QCAadOmfTG+h4cHzM3NBc9/p06d0LFjRwDAihUrkJWVpZD7wJcAKCtt2rSR22/l5ORg8ODBICJMnz4d6urqX/zO9OnTIZFImINTBWfnzp3w9/fH+fPnYWlpWWHzOXXqVIhEIly5cgVXr14tMV5oaChatWoFOzs7XtKxf/9+mJubIyMjA927dxfk+RYXF4etW7cCAEaPHl1qXE1NTQwcOBAAMGvWLOTl5X2fAAgICMD06dOhr69f7Fv41q1b0bdvX0yaNAmBgYE4deoUWrRogWPHjsl0RufPn5droaxZswbjxo2Dr68vNDU1kZaWhgMHDii0kubk5ODIkSMAgCZNmsj1t0NDQwEANjY2sLa2LtN35s2bp5ByGDRoEAAgMzMTp0+fFtT2/v378c8//ygk32KxGLNmzZL774aFhSE5ORkA0KtXrzJ9x8HBAZ07d2Y9ZAVm3bp18Pf3x4ULF8r8TPhRcXBw4F4sShoFkEgkWLt2LaZOncpbOgwNDXH8+HFoaWnhwYMHGDhwIIiI17yHhYWhsLAQKioqaNGixRfjt27dGgDw8uVLREZGfrsAuH//Pm7cuIGRI0cWCcvLy0OvXr0QHR2NvXv3YtWqVXBwcMCECRNw9epVNG/enItrYWFR4nDJtxAbG4vY2Fj4+PigWrVq8Pb25hqEUBQUFMj8ff36dXTq1AnPnj2Dvr4+Fi9eLFd70hvp4OBQ5u/UqFFDIY21WbNm3N83btwQzO7bt2+xYcMGhYm/xYsX49OnT3L/7ZMnTwIATE1NYWBgwHo+BhYsWIClS5fi4sWLsLW1rRR5lo58njhxAo8ePSoSfvDgQRgbG6Nly5a8psPZ2Rl79uyBSCTCiRMnEBAQwKu9y5cvAwDMzc2hoaHxxfj29vZFvlsaJU6SHD9+HG3atIGenl6Rzq9z5854//49rl69ClVVVQCAra0tnj59ip9++gmGhoZcfC0tLbkOz69ZswbDhg2DlpYWAMDPzw9bt27FrVu38Ndff8mIDz7Izs6GkZERDA0NkZ2djZcvX3LDrV26dMGqVavkqsjT0tLw4cMHhXbqX6uSpaSkpPBi49atWzLDfNnZ2Xj16hXvavxzGjRoAJFIBADIz88HEWHChAlyt/PgwQMAQPXq1UuNt2HDBly5cgXv3r2TSeO4ceNgZmYmt/T06NGjxGkIefqdMIpnxowZOHPmDNzc3OR6X8s7bdq0gYuLC2JiYrB8+XJs27ZNJjwkJARz5swRJC09evTAggULMHfuXCxatAjOzs5lHp37WqSjf9WqVStT/M/jSb/7TSMAN2/eLFZNBQcH4+LFi9ixY4fMg0A6z//focfXr1/D2NhYbm95Bw8ehJ+fH3fNycmJS6cQowBaWlp4+/Yt4uLikJiYiHfv3iE8PBz169fHuXPnMHPmTCQlJcnNXn5+Pvd3WRSgovncSUlNTY0XG40aNcLDhw+5z4sXL/DkyRPUr19fsHzGxsYiNzcXubm5yMnJwdy5c3mxI73/mZmZpcYbO3Ysli9fjqioKJw9exYaGhoIDg6Weydx9OhRmbL//MPHFAijqPBUVlbGlStX0KVLF+Tk5FSavEuH9/fu3SvTuV24cAGZmZno0aOHYGmZM2cO+vfvDyLC4MGDcffuXV7tfT7qXBqfP3PL4ohYogB4/vw56tWrJ3PtyZMnCAwMhKenJxo0aCATdvHixWIFQHx8vNwcVDZv3gx3d/civzd27FgAQHh4OG9vnSWho6ODXr164ebNm3B2dsZvv/2GZs2ayc0LW19fn+tU3759W+4b6ef5NjExEcyulZUVRo0apZA8V6lSBYGBgbzsfikdUXn9+jUKCwtLjWtqaso5fzZs2JD1lhWQAQMGYM+ePVBWVkZkZCS6du3Ky9RTecTLywuWlpbIy8vDmjVruOsrVqzA5MmTBV8NsmPHDjRp0gTZ2dno3r070tPT5W7DyMgIQNlH1z53TDQ1Nf12AfDx48ciww4rV65Efn4+Jk2aVESdHDt2DAYGBnBxcZEJO3PmDDp06PDdBSEWi7Fp0ybExMTAzs5O5uPv7w8VFRWIxWJs2bJFIZVTXV2dm/tPTk7G+vXr5da5SN9s79+/X+4b6d9//8397ebmJqhtd3d3rsEoYuRDulxJnkhHt/Lz8/Hnn39+Mb50So6v0RdG8chz2deX6N+/P/bt2wcVFRVcvHgR3bp1qxQiQFlZmet7Nm/ejKysLNy7dw8xMTEYOnSoQoT/sWPHYGpqisTERPTt27fMb+plRfoMffHixRdHAaUv6VKkDoHfJAA0NTVllhIREQ4dOgRjY+Mi3ohhYWF4/vw5fv75Z25eFPh3/loikXxx/rIsHDp0CDVr1kRSUlKRocf4+HjMmDEDALBlyxaIxWKFVNDPvf/l2Vn369cPAHDnzh0kJiaW6TvZ2dmCzol/Xhekb//t27cX1LaNjY3CBACAIiNm8mDYsGFcm5KWLaP8oaurK6i9Pn36cCLg/Pnz6N69e7lYCi3l4cOHvPzusGHDoK+vjw8fPmDLli1YsWIFxowZo7DpUWNjY5w4cQKampq4cOECpkyZIvcRH2n/WxavfukyyTp16pTJIbJEAWBhYSEznJ6YmIi0tDQZ5yfg3+UG0vlPd3d3md9YvHgxNzz/vaxZs6bUwh07dixUVVWRnJyM3377TSGV4fMhegsLC7n9rnQzJgCYPXt2mUZLZsyYIeM/IASXL1/GiRMnAAALFy5U2FtoXl4epk+fXiE6Fnt7e4wZMwbAv0OOsbGxrLctZ+jo6Mg4vwqFl5cXDhw4ABUVFURERMDT07NciID8/Pwyb0TztWhpaXFTfSEhITh69Kjc+phvpVGjRvj1118hEonkPgLt7OzMvQB+acM7iUSCnTt3AgCWL19epo2QShQAP/30E27duiXzUAWAjIwM7lpKSgqCgoLQtm1bAICrqysXdu7cObx+/Zpbv/k9REdHIykpiSuIkpSYp6cnAGDVqlVyv8llGVUICQn5t1CVlLjdqOT1dnHgwAFoamriwIEDCAoKKvHtPi8vDyNHjsSIESPKtGmMvPIeFxeHvn37orCwECNGjOBlSE46vPalkY358+fzMgf++Ry8vIf6SmPFihXw8PCARCJB//798eLFC0EfcGXNtzRMiLJRxL1IT09H3bp10bVrVxQWFnJ2O3fuzOsUwH+XHX9Or169cPDgQaioqODs2bPo3LkzbxvUSJ8DX3oeBAQEoHHjxt9tTyKRFOv3Mn78eKirqyMlJQX9+/cvsjxWOnL9JZ8ZeaTlczHG15LA0NBQODo64uzZs6WOAs6dOxePHj3C7Nmzy+4QWdIewXFxcWRtbS2zH3GNGjUIAP3yyy80d+5c6tatG71//547fenevXuUl5dHK1asIA8PD+5QmOvXr9Ply5e/aR9ksVhMTZs2JS8vry/G3bJlC7dntjxPwyIiWrFiBQEgTU1N+vDhQ5E94qUH1SgrK/N2CFJUVBRZWFhw++Hv3buX4uPjKSMjgx4/fkxbt26lDh060F9//SVXu7du3eLK9b+nL6akpNDixYtJR0eHtLW1v3hYxvcwbNgwAkCWlpbFnjXw6dMnWrRoEWlpafFyING1a9cEOfylOPLz82nq1KmkpqZGRkZGFBoaSjk5OTJ537VrF+np6ZG6urpc6//nh94cPXq0xHjjxo3jDgPi60AsKZcuXeLSFB0dLcg9uHv3Lmdz7969dP78eapZsybve/DfuHGDs3vq1Kli44wcOZKL4+joyMvZBEOGDCEApKurSwkJCTJnUuTk5ND9+/dp9OjRpKmpKZdTIK9cuUIikajI85aIaPjw4aSkpETx8fElHkqlo6Mjlz35379/X+o5KFIKCwvJy8uL8HWH7JY5DV26dCFVVVUKDg6mzMxMLuzp06fk4+NDGhoatGbNGvkdBtS2bVuZB92ZM2fI1NSUzMzMaP78+ZSbm0tERJGRkWRqakomJibk7u5OYWFhXOUoKCggd3f3Ym/il/j999+pWbNm3BG8o0ePLvEmLFmyRObYUnV1dRoxYkSxFeRruHDhAk2fPp07YAKfHctpZ2dH5ubmpKurSw4ODjRs2DC6e/curw+D7OxsWr9+PbVt25aMjY25o3lbtGhBGzZskKkY38ujR49owYIFZGNjI5N3AwMDcnBwIHt7e7KysqLOnTtTSEgIpaWl8ZLnw4cP09ixY0lJSYlLQ/Xq1alOnTrcx8zMjDsFrG/fvnK1/+DBAwoKCiJra2vOvqGhIQUEBMj1+NeykJiYSIsWLaJWrVpR7dq1ycnJierVq0eWlpbk7u5OK1eupOTkZLne/8/blZGREfn7+xc5DtjPz0/muFghjwO2srKiwMBAQY4DXrBgARkYGJChoSF5e3t/9/OlNO7fv09z5syROYbayMiIZsyYIVPvtmzZQrVq1ZJpo8rKyuTh4UGbN2/+7nQcPHiQRo0aRcrKyjI2Svp07979u+tdUFAQdwyym5sbLV26lN68eSPTJnv16iXzvTNnztCkSZOoSpUqXFo6dOhAy5Yt+6Z6+ObNG1qyZAk1adKEO5Fw4cKF9OjRoxK/k5OTQy4uLrzViYiICPL29iYbGxtycHCgevXqUYMGDWjmzJnfdAKoiEoZT7116xYGDx6MmzdvfvNw8oIFC2BsbIzhw4ezyUIGg8FgMMoJSl9ybvD19cWQIUO+aT4lNDQUycnJrPNnMBgMBuNHEgAAMGnSJDg7O8PT07PMm9t8/PgRfn5+SExMlNt6eAaDwWAwGPKj1CmAz4mOjoa/vz9atmyJQYMGFXsIxePHj7F//35ER0dj9uzZcj0WlcFgMBgMhgIEAPDv8qtz584hPDwcz58/h6qqKpSUlCASiVBQUAArKyt4eXmhVatWMnsFMBgMBoPB+IEFAIPBYDAYjIqBEisCBoPBYDCYAGAwGAwGg8EEAIPBYDAYDCYAGAwGg8FgMAHAYDAYDAaDCQAGg8FgMBhMADAYDAaDwWACgMFgMBgMBhMADAaDwWAwmABgMBgMRjnn3bt3sLa2BttAFrhx4waSkpIqvgCIj4/HwoULYWdnB5FIxH00NDSgp6cHOzs7+Pr6IiYmhvcE379/H+PHj4e9vT3MzMxQvXp1ODk5YebMmXj16pXc7V28eBGzZs2Cnp4el29lZWUYGhqiatWqsLCwgIeHBw4fPixIo7h//z769+8PQ0ND6OrqwsbGBuPGjcOVK1ewcuVKXLp0Se42w8LCZO57WT59+/b9brvnzp3DrFmzUK1aNe53GzZsiCVLluDly5cycRMTE7F48WI4OTlBJBKhVq1amD9/Ph4/fvzN9qOjo9GzZ0+ZfNWrVw+LFy8uNv7p06fRokULLm63bt3w5MmTr7a7bNkymJubc79Tu3ZtrFy5EgAQFxcHX19f7gwOkUiEjh07IiwsTOY3Ll++jJEjR0JJSQmqqqoYMWIEkpOTvyodSUlJmDRpEmrVqiVTBoaGhpgzZw6ys7O5uL/99ht69+7Nxalfvz6CgoK+6/5HRkaiXbt2MrYNDAzg7++PFy9eyMR98uQJRo0axZVL1apVMW3aNLx+/VoubSAqKkqm/Wtraxf5KCsrQyQSQUVFBVevXuXtGZCbmwuRSAQ1NTXUqFGD+/y3TPhAX18ftra2uHbtmkI6rBcvXsjkWU1NDSKRCLm5uYKmQywWY9CgQZg0adKPrWLoK7h58yYBIAB06dIlIiJKT0+nBQsWkLKyMolEIlq1ahXxQUFBAU2fPp1UVVVpypQplJSUREREEomEoqKiyM3NjbS0tGjr1q282F+7di0BoKpVq1J2djYREX369Im2b99O2traBIAGDx5MhYWFxBeXLl0iDQ0NGjBgAL18+ZKIiJKSkmjWrFmkoqJCACgyMlLudjdv3kz29vZ08+ZNysvL4/IurQt//fUXdy8ePXpEnp6e5OHhITf7wcHBnK2UlJRS4yYkJBAAun79utzsz5w5k7N/8eLFUuOKxWJSV1ensWPHfpfNR48ekZKSEgEotk1NmTKFS9OjR49K/J369evTwoULvystubm51K9fP87e1KlTi42XlpZGAGjs2LGUn58vt/KfNm0aZzsgIKDUuM2bNycLCwuKj4+Xaxs4fPgw1a1bl/7+++9i2/i9e/eoSpUqBIBmz55NfCJte+3atSNFsHPnTpowYQKVB37++WcCQJ8+fRLU7rJly8jHx4fq169P58+fpx+VrxIAqampXEO8e/euTNicOXMIAIlEIrk+fImICgsLqU+fPgSANmzYUGycvLw86tixIwGg4OBguRfUsWPHCADp6uoWCdu2bRtXLvv37+flRkkkEjI3N6f69euTRCIpEn7kyBESiUS8CIDly5dznfx/H0KfC4DPw7y8vORmPzw8nACQpqbmF+Pm5eURAHr37p3c7L979460tLQIAK1YsaLUuA8fPiRdXV3KyMj4brvu7u4EgPr06VMk7O3bt6SqqkoA6MiRI8V+Pycnh6pVqyaXshCLxdSqVSsCQDVr1qT3798XiePn50d9+/aVe/0Ti8XUsGFDAkB2dnYkFouLjZeenk56enp07do1uadh48aNdOrUqWLD8vPzufQ1atRIruKnPAqA9+/fk5WVFa8vO+VZALx+/ZrMzMwoJSWFLl68SA4ODiXWyQolAN6+fVuiAHj16hUXNnLkSLkmctGiRQSA/ve//5UaLykpiTQ0NEhJSYnOnTsn1zScPHmyRAEgkUhIXV2dAJCnpycvN+r27dsEgHr37l1inE6dOvEiAPbu3VuksZcmAIiIdu3aJTf7R48eLbHsi+ssAFBWVpZcy2DMmDEEgOzt7UuNN2fOHJo4caLcyh0AaWlp0cePH4uEd+3alQDQwIEDi/3+kSNHqGvXrnIrg5cvX5Kenh4BoCFDhsiE7d+/nxwdHbnRMT7qv3SUa+nSpcXGGTt2LE2ePJkX+0uWLCkxb9IRoipVqtC9e/d4f2grWgAQEXXp0oWio6MrpQAYMGCAzKicl5cXrVmzpnILACLi3pJ+/vlnuSUwJSWFNDU1CQCFh4d/MX7Pnj0JADk5OclVoZYmAIiI6tSpQwCoRYsWvNyoW7ducZ1BSQ+ZHTt28CIASnsIlSQA5El5EADx8fEkEokIAJ09e7bEN0FjY+NSh+S/huzsbG56KSwsrEj4+vXrCQBpa2sX2zn17t2b9u3bJ3cxKL3vZ86cISKiu3fvkrGxsdyH3YsTVwBIQ0ODEhISZMKuXbtGVlZWxQolPrl8+TI3VbN69WpB254iBcCePXvIz8+v0gmA6Ohoql+/vswb//Pnz8nExITevn1beQXAhw8fuLChQ4fKLYHLli3jfrcsQ5nbt2/n4l+9elUQAfDp0ydOpIwaNYqXGyUWi8nU1JRLw6+//lokzqtXr+j58+dMAPAgAKRvPQCoY8eOxYbv37+f2rdvL1ebgwYNIgDF+lT07t2buwf/7egzMzOpRo0avLyR9+jRgwCQmZkZPX/+nGxsbEqchpAnubm5VK9ePW40UCrw8/PzydHRscQher7IzMwkKysrrjMWaki8PAiAzMxMsrS0pIKCgkojACQSCTVo0IAuXLhQJCwoKEjuI98/lADYtGkTF1bSG9L33GBTU9OvelMG8N3OT2UVAAsWLCAApKamxutb0Pnz5zlHIwDUvHlzioqKUkjFqYwC4MKFC5yfy/3794uEt2zZUu4dYUREBAEgFRUVevPmjYzgrlatGicC/isQfv31V/L29ublfqSmplKNGjU4p9hp06YJVu+uXr3KvXFLHX4XLVpUrJ8E3wwdOpQAULVq1ejFixeCtz1FCgAiIk9Pzy86xVYkAbB27doSfZs+ffpE1tbWdOvWrcohAG7cuEFE/3rnHz58mHR0dAiA3OY/pdjZ2REAcnR0LFP8Fy9e8OKLUJwASEpKoilTppBIJKLq1avTiRMneL9h169fp7p163J5BECdO3cutkNiAkD+NGjQoNi6FRcXR7Vq1SrWQfN7KCgo4EZ+1q1bx13fuXMn9ezZk6KioooVCO7u7nT69Gne7snhw4e5+3/y5ElB697EiRO5jjc6OpqMjIwoOTlZ0DRI62RJ0zOVQQDs37+ftxHP8iYA3r59S6ampqWOsB47dozc3NwqhwDo0aMHeXp6UqNGjcjBwYG8vLx4GYIzNzcnAOTi4lKm+Dk5OVwa+/fvL3cBoKKiQu7u7uTg4EAASElJiTZv3sxbh1MceXl5FBwcTLq6ulxeVVVVadGiRUwA8CwAdu7cyc1Dp6WlcddHjx5NCxYs4MWmdBlcs2bNuGsdOnSgo0ePUmFhIVlaWhIAWrt2LRH96zdjaGjIq2fy1atXSVlZmZsK+PDhg2B1Lzs7mxt6V1FRoc2bNwv60ExJSeFGQPhY9fCjCICPHz+ShYWF3EVveR0BqIjI1QmQD1xcXAgA2dralin+u3fvuDSOGTOGtxGAjIwMql27NgGgESNGKOTmpaWl0aRJk7jlYGVZJ/0jCoATJ06UWQDk5uYSAMrJyeFNfBkaGhIATnBlZWVR9erVv7hHwbdy584drqwfP35MKSkpZGBgwO3JMHv2bAJATZo0ISKiNWvW0OjRo3ntAC0tLSk8PJwTocOGDRO07u/Zs4cTYkIvR/Pw8OCmJeW53PRHEwBE//qhREREMAHwg1LutwK2srICALx+/RqFhYVfjP/27Vvu7wYNGvCWLl1dXRw+fBjq6urYunUr9u/fz2s55OTk4P79+zLXqlevjpUrVyI2NhZ169YFACxZsgRpaWkVastNDQ0NrgzoC7stZmdnQ1lZGVWqVOElLWpqahgzZgwAYMOGDRCLxdi9ezfat28PQ0NDXmw6OjpydXnfvn04cOAAevXqBTU1NQCAj48PAODvv//G48ePsW/fPgwYMICXtEgkEvTt2xeTJ09Gr169EBISAgDYvn07zp07J1idqFat2r9bmf7/zn9CsWnTJpw5cwYikQg7d+6Enp5epd4Ot2/fvjh48CDbI7kibwWsSLp06QIA+PjxIx49evTF+LGxsQAAZWVleHh48Jq2Ro0acVu0/vLLL0hISODNVmZmJrZu3VpsWL169XDy5EmoqKhALBbj9u3bFaqS1qxZk9t+MzU19YtbhZqYmPDaKYwePRpVqlTB69evcfDgQWzatAljx47ltQyknXxYWBjCwsIwcOBALszOzg4uLi4AgKCgIKSmpsLNzY2XdEyfPh3GxsYYN24cAGDYsGHo0KEDAGDEiBHIysqqsA/LhIQETJ06FQDg5+fH5bukelgZ6Ny5M86dOweJRMJ6UyYA5E+PHj24DiA8PPyL8Y8dOwYA6NevH8zMzHhP35gxY9C3b19kZWWhT58+vO5JfezYsRJHQWxsbGBnZ8eNTlQkbG1toaWlBQBf3IM8IiICzZo14zU9BgYG8Pb2BgBMmTIFANCyZUtebQ4YMADKysp49OgR0tLSinTwUkGw97mGFQAAIABJREFUZ88e9OvXjxcBdOjQIZw9e7aIEN26dSu0tbWRlJTElUdFQyKRYODAgcjJyYGdnR2Cg4NLjCsWi7Fp06ZK0YFoaGjA1dUV58+fZ73pj8jXzBckJydzc5GxsbGCepsCICMjo1K3WE1ISCB1dXUyNDSUu1ew1BFNR0enSFhmZibZ2NgQAPL19eWlDKRlX5Kj35s3b0hDQ4NsbGwEWZublZXF1YUrV67wbi8gIIDbaKkk57bbt2+Trq4uxcTE8J6euLg4Lv8bN24UpB1Itwb29/cvdl5e6pR3584dudu+ceMGGRgYlLjaRLopEQBBVsNI26OGhoYgZT9v3jzO6VC6AqoktmzZQitXrqwUPgBE/+44+d+dIZkPQAV0Avz777+5Ri70phvSDYF69uxZbAfw/v17cnFxoerVq3+xgX4Lq1ev5taAF+fx/M8//3Br9CdPnix3D+zPxdfAgQM5AVZYWEi3bt2iJk2akL6+viCdHxHRgwcPuPQcPHiQd3u5ubnUq1cvAkCtW7emyMhIyszMpKysLLp16xZNmzaNtLW1aceOHYLVyQ4dOpCOjo5gK0Ckjm8l7TTYsWNHql+/vtztnjx5kvT09Ep19MvLy+PW5+vp6fG+Je66deu4+peens6rrevXr3PbEAcFBZUYLyMjg0JDQ0lLS4vXA2LKmwD49OkTmZubc06pTABUMAHw6NEjCgoKImtra67R1apViwIDAwXrcIj+XWdZq1YtatSoEe3du5fu3LlDN2/epDVr1pCZmRm1a9eOnjx5IlebFy5coBkzZnD7HAAgV1dXCg4OLjLKEBoaysUxNzcnPz8/ev36tdwEwPjx4+nGjRu0YMECcnV1JWNjY6patSpZWFjQqFGjBNmM5NmzZ7Rw4UKqX78+l1cTExOaN28eL8LrcwoKCmjnzp3UoUMHMjQ0JBUVFdLV1SV7e3saM2aM4HshnDlzRq4rTb7Ex48fqW3btiWGh4WF0eLFi+Vm7/Tp09SuXTvuPtesWZPmzp1Lubm5MvGio6NldiXE/29ZPWrUqCJb9n4v0dHRNGvWLO5MAgDUtGlTWrJkCaWmpvJS7p/XdU1NTdLS0iry0dDQkMk/X2kpjwKAiGjgwIGC7wfBBMD3IyIS4BB7OSIWi7Fnzx5MnDiRczhSV1fHhQsXeHN8YjAYjPJCbm4uNDQ00K5du0o/996xY0ecPXsWnz594m3lD3MCLEeoqqrC19cXly5dgqmpKQAgLy8PFy9eZHeTwWAwGIyKKgCkNGrUCHfu3EGfPn0AAIGBgTh16hS7owwGg8FgVGQBAAD6+vo4ePAgoqOj4ebmhl69emHVqlXIz89nd5bBYDAYjFL44XwASuP+/fs4dOgQnj59CltbW7Rv3573NeEMBoMhJFIfADU1NZmdCG/cuIFatWpV6Ly/ePECDRs25P6fmZkJsVhcoX0AYmJi0LRp06/6zpUrV8r0nQolABgMBoPBYJQNJVYEDAaDwWAwAcBgMBgMBoMJAAaDwWAwGEwAMBgMBoPBYAKAwWAwGAwGEwAMBoPBYDCYAGAwGAwGg8EEAIPBYDAYDCYAGAwGg8FgMAHwQxAREYEuXbqgZ8+erDA+IyMjAytWrICFhUWlO55ULBZj6dKl6NChA7S1tdGoUSP89ttvFTKvsbGxGDp0KCwtLctFevr37w9DQ0PExcUpxP7AgQNhZGSEe/fuCWLvxo0bGDJkSLnY7vfly5fw9/eHsbEx/vnnH/YQ/FGhb+DatWukoaFBAOjhw4dU0SksLKQJEyaQubk5AaDu3bsT419u3rxJXl5epKSkRAAoIiKi0uRdIpFQ+/btKTQ0lIiIrl69SlWqVCEAdP78+QqV1/Xr15OzszMBIENDw3KRJktLSwJAR44cUYh96fMgPDycd1s7d+6k9u3bEwCqXr26Qsv9ypUr5OPjQyKRiADQ7du32YPwBwXf+sXDhw+TSCSiZcuWVZrCCg8PZwKgBNzc3CqdANiwYQMBoKysLO7a7t27ycjIiP76668Kl9/Hjx+XKwHw5MkTOn36tMLsx8fH04kTJ6iwsFAQe8nJyeVCAEhxcHBgAuAH55unAHr37o0lS5bg+PHjlWa0pHr16mzIqARq1KhR6fK8f/9+qKqqQltbm7vm4+OD5OTkCnkKZXmr/7Vr14aHh4fC7NvY2KBr164QiUSC2Pv85L/yQHlLD0NgH4AZM2bA0dERb968qRSFpaKiwmoMKxuOhw8fQlVVld1jhiAoKyuz9DDk26a/9wc2bdrESpFRKcnIyIC6ujorCAaDUflGABRBYWEhtm7ditatW6NHjx6oW7cufvrpJ4SFhQmajry8PMycORNGRkbQ0dGBl5cXkpKSBLGdm5uLxYsXw9XVFU2aNEHt2rXxyy+/ICUlRRD758+fh7u7O9q0aQM3Nzf4+vri/fv3gpX9hw8fMHPmTLRo0QJmZmYwNjbG8OHDkZqaKkinb2dnBzs7O0gkEuTk5HD/HzFihCD537lzJ9zd3TFq1Cg4OztDJBLJfAICAgRJx9mzZ/HTTz9BU1MTLVq0wOPHjwWrA4mJiZgzZw6MjY1x8+ZNwZ9DSUlJCAgIgKmpKf7880+FPQ/z8vIwYMAAiEQiGBsbY+bMmYiKiqoQnZNEIsGRI0fw888/cyuvjh49ChcXF2hra6NNmzZcnXv69Ck8PT2ho6MDU1NTbNy4Ue7puXz5Mry9vWFnZwcAuHjxIpo3bw5NTU00b94cCQkJgpTLqVOn0LlzZ3Ts2BE2NjZwc3PD3r17v+3HfjSnhfHjxxMAunfvHhERZWdnk729PQGgP//8k1fbly9fJvwfe+cdFtXxNeB3d+lVEBAERIKIVHuPLWrsLbaINRF7N7Ek+tPEFnvvhcReYolRYzQaNVhjb2DBghQLvfed7w+X/QBBjbKL5b7PwxMzd3fP3LlzZ86cOecMiJYtW4rPP/9cfPrpp6JFixZqz+/SpUuL8PBwjdYhPj5eVK9eXfj5+YmMjAwhhBC7du0SgHB2dhYJCQkalb9y5Uphamoqjh8/ri6bMGGCALTiBBgVFSWqVKki9u/fL4QQIjs7WyxZskR9/zExMVrriwqFQhgbG2u1/48ZM0bo6uqKO3fuCCGEyMjIEPXq1ROA6Nmzp0hKShJZWVkakZ2YmKh2Aly1apVo27atmD9/vmjZsqUARK1atbTSBv/884/o06ePus+dP39eq8/g7Nmzon///mov+ICAAK3IzczMLNAJcNSoUeKzzz7Tat8XQogGDRpo1Anw+++/F+7u7mrH68mTJ4uvv/5aLFiwQNSqVUsAomLFiuLChQuibt26YubMmWLixInqCLV//vmnyOqyYcMG0bVrVwEIJycnsWrVKtGsWTMxbdo00bRpUwGIKlWqaLzNJ02aJFxcXMTDhw/VfWLIkCECEH5+ftqLAiguTE1Nha6ubp6yiRMnCkD89NNPWlEASpUqJU6dOpXHG7h06dICEL6+vhqtQ48ePYSDg4NISUlRl6WlpWkl/OzSpUtCR0dHzJ07N095VlaWcHR01IoC4OvrKyZOnPhCuZeXlwDE1KlTP1gFIDAwUMhkMvHZZ5/lKT9w4IAAhIWFhUbl5ygAenp64ueff87z/O3t7QUgwsLCtNYe3t7exaIA5FCjRo1iVwDGjBkj2rZtK9LS0rR+/5pWAIT4/8grJycncenSJXV5cnKyMDMzE4AYPny4ejEkhBCzZ88WgBg6dGiR1iU0NFQAwtDQME//z8zMFDY2NgIQDx480Fhb/PXXXwIQW7dufaFf5Ix/69at004UQHExatQoxo4dm6fM1NQUgJSUFK3UoVatWtSpU0f9/66ursycOROA3377jczMTI3IDQ8PZ8uWLXz++ecYGhqqy/X19Tl27Bj+/v40bNhQY/c9adIksrKy+PLLL/OUKxQKqlatqvF2j4mJYfv27Rw6dIj27dvn+dPT08PNzU0r2wDFxenTpxFCYGNjk6e8UqVKAMTGxpKWlqbxelhYWNCnT588z9/Dw0PdR7VFcUclWFpaFutW6IABAwgLC2PXrl0frC9KiRIl1H28cuXK6nIjIyN1n+vVq1ceZ1xvb28AIiIiirQuOfOMjY1Nnv6vo6NDxYoVAXj8+LHG2mLGjBkANG7cOE+5jo4OgwcPBuCnn376T7/53rn1/vjjjwBkZGSwY8cO9uzZQ2hoqPqlKC46d+5M7969SUlJISwsDGdnZ41MAEqlssBMYLVq1dJo6FlycjKHDh1CX18fe3v7F65rwyP44sWLZGdnM2rUKLp168bHRs6El9/XI2ciMjc3x8DAoFjqlqOQakMB0WafexflCyHo3r07e/bsITg4+IOOznhZGxsbG6vbIzc570B6errW6mJmZqaelzRBUlISx48fL1TxrV+/PgDBwcE8efIEW1vb1/rd9zIVsL+/PzVr1iQ1NZUtW7bQq1evYq+TgYHBazf626yANa1lFsbDhw/JzMxELi++LpNz//fv3+djpFmzZtjb23PlyhUSExPV5SEhIQB06dKl2OqWEwtfnEr4x4JMJsPU1FTtAJiVlSU1yjtCfmWkqAgLC1P/ds44mBsHBwf1v/+LJfy9UwD69u3L+PHj+f333+nXr987ZfpSKpXo6elhZ2enkd83NzdXWwIKQ1N5yXO039TUVCIjI4ulfXMS7uzbt6/Qz5w/f/6DHVwMDQ05ePAgpUqVYuLEieo+N336dDw8PJg1a5Y0An8kLF68mEqVKhEQEMD48eOlBvnAyRn7cyv8ucmZB3V0dAq00H4QCsA///yDv78/rVq1eicOxMhNdHQ0T58+pVmzZhozw1arVg2AGzducODAgReunzhxQmMHozg7O6vNvC+bgDW5AszZAzx37hzbtm174fqNGzf4+++/P+iBwMjICBMTE1JSUvjqq6/w8/PDw8ODs2fPSpnZPiIMDAzYuXMn5ubmzJs3jz179kiN8gFjZ2eHq6srQIHPOmdR1qJFi/+0KH6vFIAcp47r16+rzSHZ2dlcu3YN+P89n6ioKK3Xbd26dejr6zNt2jSNyShXrhyNGjVSW0JOnTqlvvbXX38xYsQI2rRpoxHZ+vr6+Pr6As+dAfNvQyQlJQHPY/Q1RenSpWndujUAffr0YenSpeo953PnztG9e3et+QYIIVAqlWRnZ2utj6WmptK0aVN8fX1Zs2YNP//8M/7+/owfP17toKTpey6Kz2izPh8S+e/XxcUFf39/9ftw+/btYq3Ph/6MX2dxo8n6jhs3DnieByQ5OfmFxZ9cLv/v1qD3KQTw3r17QldXVwCiSZMmYuzYsaJGjRqiS5cuAhAuLi6iR48e6hwBRc2NGzeEgYGBMDIyEqtXr1aHnuzcuVNYWlqKvXv3aqUN7Ozs1DHQjo6OwsrKSujq6ooTJ05oVHZ0dLQoX768AIS9vb1YvHix2LVrl+jZs6dwcnISgPDy8hKTJ0/W2AEpYWFhalmA0NXVFSYmJgIQa9as0WpfzKnDs2fPtCLz5s2bAhAKhUI4OzsLNzc34e7uLry8vEStWrXEgAED1PkBNEFISIgAhLGx8QvP97PPPtPayXg5+Pj4CEAcPny4WMajVq1aaTUMMOcwIH19/Ty5Hvr37y8A4erqKp48eaK1+885DEiTocc5YYANGjQoNAzz77//zlP++++/C0DUrVu3SOty+/ZtAYgSJUq80P9zTmrUZP9XKpWiZ8+e6rwIcXFxQgghrl27JsqUKSNmzZr14ecB2Lx5s3BychJGRkaibdu24uHDh+L+/fvCzs5OeHp6itOnT2tU/sOHD8WIESOEi4uLsLS0FBUrVhS9evUSt2/f1lobPHr0SPTo0UNYWFgIQ0ND0aRJE3H27FmtyI6KihIDBgwQVlZWwtDQUDRu3Fj8+++/olOnTqJRo0Zix44dIjMzU6N1ePr0qRg4cKCwtbUVenp6olKlSmLHjh1aa//Zs2erY9ABUbt2bbFgwQJx48YNjcueOHGiKF26tLCzsxNGRkbqY5hz/iwsLMTjx4+LXO5vv/0m6tevr5bTqVMncfDgQXHt2jXx7bffqpPiuLu7C39/f43nQxg2bJi6Lt7e3uKXX34pNgUgd04QTbFx40bRqFEj9T137dpV/PHHHyI1NVV07Ngxz4JgxowZ6slBE9y9e1cMHTpULdPT01MsXbq0yOWsWrVKuLq6CkDI5XIxevRocfnyZXH+/HkxaNCgPM9/4cKFQggh5s6dq16kyOVyMWLECHHv3r23rsvevXtFw4YN1TK//PJLcejQIXH9+nUxZswYdf+vUKGCWLlypUaVgNWrV4sqVaqIkiVLiipVqojmzZu/sRIsEx+bHU1C4j0lMjKSbt26sXPnTnV8dA5paWk8fPiQAQMG4OfnR8+ePaUG0zCtW7fmwIEDXL16FR8fH6lBJN475FITSEi8H/j6+tK4ceMXJn947hRWoUIFGjVq9FEezVxce8JyuVwjOT8kJCQFQEJCAoALFy5w5MgRAgICCk22c/XqVc6ePcvnn38uNZgGiIuLy5NcJikpiXr16mnFAVNCQhNIB3xLSLwHuLu74+Pjw8GDB3F2dqZ169a4ublhZGREfHw8Fy5cICoqiu3bt0vntGuAtLQ0PvnkE3R1ddm6dSuenp7cuXPnpSGxEhLvOpIPgITEezQJrVq1il9//ZUbN26QnJyMhYUFVapUUYdAfshpYYubfv36sX37dpRKJQ0aNODHH39U5+aQkJAUAAkJCQkJCYn3AskHQEJCQkJCQlIAJCQkJCQkJD4GpA1DCQkJCQmJYkCWc4ymZAGQkJCQkJCQkBQACQkJCQkJCUkBkJCQkJCQkJAUAAkJCQkJCQlJAZCQkJCQkJCQFAAJCQkJCQkJSQGQkJCQ+JC5d+8eixYtIjk5WWsy/fz82LRpk1bvc9++fezbt4/s7GzpoUsKgISEhMTHixCCSZMmsWTJEnr37o2xsfEHfb+tW7dGoVDQokULHj58KHWAt0RKBCTxVgQEBFCvXj2pISQkioGZM2dy6tQpjh49+lHcr0wmo2XLlqSnp9O0aVMuX76MiYmJ1BEkC4CEtrl8+TL+/v5SQ0hIFAMJCQlMnTqVRo0afXT33rBhQ4KDg1m5cqXUESQFQELbpKWlMWDAAKTDJCUkioeLFy+SmppKdHT0R3fvOfccEBAgdQRJAZDQJunp6fTs2ZPz589LjSEhUUzkpJG/cuXKR3fvOfcsl0tTmFYUAKVSyYEDB2jfvj0tWrRACMHMmTNxdHTEyMiI5s2bExgYqJVKX7p0ic6dO1OjRg3Kly9P7dq1Wbt2LTVr1uT48eMal3/69Gl69+6Nq6srQgjGjBmDubk5bdq0QalUalx+QEAALVu2pH379pQvXx6ZTEaJEiW00vZCCPr06cOFCxcA+P3336lUqRKVKlUiIiJCY3Lnzp2Ll5cXMpmMWrVqqctPnTpF3759kclkyGQybt26pRH5y5cvx8bGRi2nb9++hIWFqa/v2rULb29vLCwsWL16dZHI3Lt3L05OTmqZ06ZNA+DgwYM0aNBAXd62bVv1Sig7O5uxY8cil8vx8fHh+vXrRVKXnTt3Uq1aNbVMHx8fbt68SXp6Op06dUImk1GlShUOHz6skfafMmUKhoaGyGQydHR0GD9+PPHx8errBw8exN3dHX19fXU7aWTAlMuxsLDA29tb3e8rVaqEmZkZMpmMMmXKaM0q5ubmBsCNGzc+uonr5s2bAHh4eEiz+FsO6K/F9OnTRcWKFQUgGjduLIYPHy7atm0r+vXrJ2xsbAQgLC0tRUhIiNAka9euFba2tuL48ePqsk2bNgm5XC4AcezYMY3KX7Jkiahdu7YAhL29vfjhhx9Eu3bthEKhEAqFQkRFRWlU/u3bt4Wtra0IDw8XQgihVCrF9OnThbm5udAme/bsEYDo3bu31mSePn1aAKJmzZovXPPw8BCACAoK0pj8y5cvC5lMJgARExPzwnU/Pz/x888/F6nMmzdvCrlcLgwNDUVmZqa6PCkpSVhZWQlA3LlzJ893UlJSRMmSJcWzZ8+KtC6pqamiRo0aAhBffPGFunzRokWiVq1aIjk5WaPPf/ny5QIQtra2BV7v3r27mDBhgsbkZ2ZmCk9PT5Gampqn/Pr168LAwEAoFArxzz//aPU9tLOzE5aWlqI46Nu3r9i4cWOxyP7f//4nALFr1y7xPvPeKABCCPHXX38JQFhbW4vNmzery8PDw0WZMmUEIL788kuNNVZAQIBQKBQFPvS6detqRQEQQoiQkBABCAMDA7Fs2TL1QH3y5EmNy542bZqwtbUVWVlZ6jKlUinq1KnzwSsAQUFBhSoAOc9fkwqAEEK0aNFCAGLTpk0vTLoeHh4iIyNDYzL/+uuvPOWjRo0SgJg7d26e8l27domBAwdq5P7v3bsnTExMBCAOHz4swsLChKurq1oh1SRKpVL4+PgIQAQEBOS5lpaWJmxsbMSjR480Jj8lJUVMnjy5wOcOiClTpmh9AqlSpUoeZexjUQD+/vtvAYgzZ85ICoC2fABywi28vb3x9fVVl5cuXZoff/xRbbbMyMjQSGUnTZqEiYkJ7du3f+Gara2t1hotx9xuYmLCwIED1aaounXralx2RkYGT548oW/fvsTFxan3AseMGSOZs7TAsGHDAFi2bFme8u3bt/PFF1+gq6tb5DK//vprAH755ZcC+/yaNWvylPv7++Pn56eR+//kk0+YM2cOAEOGDKFPnz7Mnz+f0qVLa2XPe/z48cDz8Lf8WxQ1a9bE0dFRY/INDQ2ZMGFCnrIRI0YQGBhIo0aNXrimaZ48eUJkZOQLbfEx0KhRI7p27cqxY8e0Iu/Ro0e0b98ee3t7ateuzZQpU7h9+3aBn/X39+f+/fsf1haAEEKcOXNGvQWQn6ioKAEIQAQHBxe5ppSQkCAUCoWoWrVqgdc7duyoNQtAYmKiegtA2wQHBwtTU1MBCAsLCzFx4sQiN/VKFoCXr0JdXV0FIC5cuKAur1OnjggNDdWIzPT0dGFlZSWMjIxEfHy8EEKIjIwMUbFiRVGtWjUBiBMnTgghhHj8+HGh70hR0rRpUwGIzz//XKv9LisrS7i4uAhAXLlyRV1er149ceDAAa3WZceOHQIQVlZWWrGA5G6DgIAAMWjQIBEYGFhsq9fitADkbMmMHTtWLFmyRERHR2v0nW/QoIHYuHGjCAoKErt37xY9e/YUJiYmokaNGmLx4sXqre8rV66Izz77TGRnZ394FoCXUbJkSUxNTQHIysoq8oqGhoaSnZ2tkd9+n3BxceHff/+lUaNGxMbGMm3aNMqVK8fatWul5bkWkMlkDBkyBIAlS5YAz51SbW1tcXBw0IhMPT09unfvTkpKCjt27ABg8+bNtGvXjqFDhwKoHQ/Xr19Pnz59NN4OI0eOBODvv/9WO4RqA4VCobZ2zZgxA4CgoCBCQ0Np3ry51uoREhJC//79kclk/PLLL1qxgORw8uRJFixYQMeOHXF3d/9o38UcZ9DQ0FCNWkGCg4Np1qwZPXr0oEKFCnTo0IENGzbw+PFjBg8ezN69e3FxccHQ0JAvv/ySefPmvT/RCUVlARBCCGNjYyGXy9WrlKLkxo0bAhBmZmYftQUgN0ePHlU7ZWnbIaY4LAC3bt0qdguAEELEx8cLExMTYWBgICIjI4Wfn584cuSIRmVeu3ZNAOLTTz8VSqVSVKtWTTx79kwkJycLc3NzYWBgIKKjo0WlSpUKdFAs6v5fuXJlMX78eAEIT09PkZaWprV+kJaWJuzs7IRcLhe3b98Ww4cPF9OnT9fqyjPHEXjUqFHF9v7PmjVLjB49WiiVyo/SAnDhwgXRrFkzERkZqVE5qampLzh+5icjI+ON6vFeWgAKCnWLjIwkOTmZ6tWrY2ZmVuQVdXZ2RkdHh4SEBPbt2/fRar2rVq0iPT0dgM8++4wzZ84wYsQIADZs2PBB37uenh7ASw880UYYppmZGb169SItLY25c+dy+fJlGjdurFGZ3t7eVK1alZMnT7Jw4UKqV6+OtbU1RkZGdO/enbS0NAYPHoynpycWFhYarcuQIUMYPnw4P/30E82bN+fmzZtMnjxZa/1AX1+fkSNHolQqmTx5Mtu2baNv375akz958mTOnDlD1apVX1h53r17V2v1GDt2LLt37+bnn3/+6MbBhIQEWrZsydChQ7GystKoLAMDAwwMDF76GV1dXY3X452xAHh4eLxwbfXq1QIQO3fu1Jgm1r59ewEIFxcX8eDBA3X5nTt3hKOjo9YtAHZ2dlrXeseNG/eC1p1TH01GYOTnwIEDAhDt2rUTQjz3htZ0CGhycrKQy+XCyMgoT7jl5s2bhYWFRYHe4ZoiMDBQAEImk4lFixZpReayZcsEIHR1dcXdu3fV5ZcvX1Zbgf7++2+N1mHjxo3C19dX/f+hoaHC1NRUKBQKcfr0aa31v4SEBFGiRAkBiM6dO2vV6iaXy4WpqWmeZ5DDjz/+qNXxwMfHR3h5eX10FoAVK1Zo9X3XFO+lAgCItWvXqsvv3r0r7O3tRb9+/TTaWPfv31fHPhsaGoqWLVuKVq1aCV9fX9GuXTutKQARERECEHp6eiIxMVHrCoC5uXmeeOPDhw8LXV1drb4MOeZ4IyMjsWjRItGpUyfx5MkTjcvNcT5zc3MTw4cPF59++qmYNm2aegugevXqYubMmVppgyZNmghjY2MRFxenFXmxsbHCwMBAdOrU6YVr1apVEy4uLho1B1+5ckXY2dmJ2NjYPOXTpk0TgPjkk09euKZJJkyYIABx9OhRrciLjIwUpUuXFkCeMOgcgoODRcuWLbW6FaGvry+MjY0/OgVg7NixAhArVqyQFABtKwC1atUSgwcPFq1atRKNGzcWNWrUEMuXL9fKXtSdO3dE69athZGRkXBwcBDTp08XWVlZWvMB2LFjh6hXr55aEapVq5b6npCFAAAgAElEQVTYsmWLVhWAHNmVKlUS7du3F61atRLnzp3TeuedNGmSMDExEd7e3lrJgSDE85wTTZs2FQYGBsLd3V3d9g0aNBBt27YVf/75p9b2RPfu3Sv69++v1Tb39fUt8FmvWrVKzJgxQ2Nyd+7cKaysrIRCocgT7379+vU8fiheXl5i27ZtWmmL8+fPi/Lly2u17XMsMDVr1szz5+3tLfT09ESzZs20Vp8cvxBXV9ePTgFYuHChAISfn5+kALwrToDFiTadACUkJIqfb775RsybN++jvf9Dhw5pfQvkXVEATpw4IQCtWlw+RAVARwrskpCQeN9ISkpi27ZtXLt27aNtg1KlSgEfZz78nPBHbSaA+xD5TwpAjsIi3sEjYIV0LK2ExAfNgQMH0NPTo379+owbN46uXbtiaWn50baHj48PPj4+pKSkfHT3npqaCkDPnj2lF0NbCkDO6Vu5T+F6V4iNjX1n6yYhIfF2BAQE0Lp1a+D5iXwVKlTg5MmTH3WbyGQyNm7cSOfOnRkxYgT29vYfzb1Pnz6dcePG0bBhQ+nleAteKw9AWloakydPVsebX7x4kX79+nHixIliv4Hr16/z7bffqusybty4jzI3toTEh4yXlxfVq1fH3NwcX19fjh07pvF8B++LFeDAgQNMnTqVOXPmqHOEfKgcP36cwYMHU7t2bWmcLwolUki2cwkJCYn3nuTkZPT19dHR+XBduxISEjSSaK7YJmCZTCYpABISEhISEh/bCryYFQC59AgkJCQkJCQ+PnRQOc8VG0eOSE+hOFGdIidRTCsAqf8XK6JJk+KtQP/+73T7bDl5Et9PP9WcgOJu/48cyQLwARIeE4Ntv34sPnhQagwJCYk3QikE57R4uJGEpABIFAHP4uN5Gh/P9UePpMaQkJB4Ix4+e0ZZGxupIT5gpEyAHyCVypaljJUVX9SoITXGe46LoSGDHBzoYWdHKdVxyOlKJfMfPWLxo0c8ycgAYJCDA0MdHfEwNiYiPZ2fIyKY9uABaW95PHJxywcob2REf3t7+tvbY6rycF8dHs6shw+5n5qKuY4OA+ztmeriQjawNDSUuSEhPFPVTeLNCAoPx/0dzS1w+do1Zsyfj6uLC9cDA4mKjubM4cPs+O037t67x1/Hj1OzalVm/fADAIG3b7Nx+3ZS09K4HhjIljVrKGVt/dE/Y5mIiSneKABpD1Qj/PDrr/yvY0cU8lcYeSQfgOJ9AV+z/1vo6HCoShWqm5nxIDUVl1OnyP/iznZ1pYaZGW2uXCExO7tI61nc8gG8TEw4Wa0a5jo61Dp/nnO5kn6ZKBQE1q5N26tXuZKY+Nq/KfkAFM7cffvoXKsWJwIDWfLnn1y4dw8dhYLFX33FoM8/B2D3uXMMXLMGSxMTJnbsSJuqVVlz9Cjz9+/ncWwsZa2tWT1gAE19fEhJT2flX3/xzYYNNK9Uie87dKDesGFvVLfUtDQ69e5NbFwcaxcv5uKVK7i5unL0xAm+GzWK2Lg4HDw92bZuHY3q1aNphw6c2L8fPT09qjRsSLsWLZg8blzxv/+WlsUaBSBZAD4gei5ZwqaAAOwsLHC3t6fjvHnsu3ABMyMjDk2YQI1y5aRGek+Jzcqi7ZUrXKlVC2dDQ/rb27MqPFx9vYqpKZ9bWtLw4kWNTL7FLR/gRlISA4KC2Obtzcxy5Wh08aL62tIKFRh5585/mvxzuJOSwk8PH/JLRASzXV0Z4+T0wmcSsrJwCAigpJ4eC8uXx9PYmKVhYSx69Ih6JUpQzsiIa0lJdLSxYXzZssRmZrL72TMG3LpFOUND6pUoQWByMl4mJswqVw4LXd13vs89ioqijJUVvRo0oEudOnz244+cv3ePFpUrqz/T0NMTDwcH9o4di7mREQDftmlDx5o1qTZ+PPq6unzm5QWAkb4+1Vxc6FGvHhvfcOLPwdDAAFsbGyp5e+Ph5oaHmxtDxowBYOGKFQA0a9yYuPh4fjtwABdnZ/RUFqxDO3diaGgoDSpIPgAfFJ9XrMj0bt24s2gRPk5O7Bw9msMTJ/JVw4aUsbKSGug950lGBl/dvPl8dVa+PGVVg5iVri4bvLzoduMGcVlZH6x8gO1Pn7L72TMaWljwdenSAHxVujQJWVnsfvbsjX6zvJER35cti6FczuJHj8gsIDXK2ogIsoSgiaUl7aytKWdkxFAHBwCmuLjg7+HBigoVmBAczIwHD7DU1cXP3h47PT262dqy1sODg5Ur80dUFF2uX3/n+lZodDTpmZl5ypRKJTlh6ga6umwdMQIjPT2GrF373HoiBEPWrWNlv37qyT8HZxsb1g0axO2ICObv3w9AdGIis/fuZfWAAUWzepbJyB1G/ygsjAZ16zJy0CBGDhrE7g0b6Nm1KyGhoXkyJFpbWWFibCwNKJIC8IFZAOrX5/sOHUhJT2fTP/+w6sgRGnt7M793b2xLlJAa6APgYHQ0q8LDMVEo8PfwQFcmY5u3Nz/ev09QcvIHLx9gyK1bxGZmMtfVlcaWlnxdujTfvqW3uq5MRjdbW55kZLDtyZM817KF4J/YWHxMTVHkKtfJl8OlupkZXiYmbM31/dyfMdfR4QsbG47ExBCVb7ItjC0aPu8gOjGR0evX02bmTNb9/fcLE2xunKytmdOzJ39cvsyWkyeZ+dtvtKlalQqF+Am0r16dbnXrMnnHDu4+fszANWuY16sXhqqVeFFjV6oUO/fuzVN27uJFStvacvzUqTxKwKlz56TB5FUKwKOwMEZNmICjlxcyS0v1Xyk3NyZMm0ZyrlOodu3bR6fevdWf8apThymzZ7+XjZKtVLL44EEqjRmDaa9e2Pj50XjKFFb99RdB4eH0W7XqnZZ/IzSUqMRE/g0Ofi/aOyU7mzkhITS7fBnZkSPqP5Njx7A+cYKSJ05Q+dw5vrlzh7APPNf56/DNnTsEp6TQyMKCszVqcDUpiV+fPv1o5D/JyOCbu3ex0NVlX6VKfBUYSEYROBs6GhjQycaGefmiZ/ZERtLhP3jDm74iFa9cJsNYoXjl72gjDE9XR4dv27blt7Fjmbd/PxkqC86TuDjsCjhroX+TJjT29mbIunWERke/MkfAkq+/xtTQkNoTJ9KhRg3cVFabIhsrc203devYkV/37mX4+PEcP3mScT/8gJGhIW2aNyc9PZ3u/ftz9sIF5i5dSnxCgvp7sXFxfDdlCnOWLKF648YkJSfTvFMnGrdvT1x8PD0HDqRS/fqERUQQGh5O/VatePz0KcdPnmT+8uW06NyZ9Vu3ApCens7MhQv5cdYsmnfqRGxcHCv8/fm0RQsWr1qFk48P3fv3R1kE/VXjCkAZBwcWTJ9O8MWLfPnFF+ryXl27Mn3iRIxzmX06tmnDqgULnmvofn5cPnGCSWPHvpeTf4c5c5i6cyc/dulCtL8/4atW8W2bNqw4fBiPUaO4+/jxOy2/srMzAFVU/33XMVIoGOPkxMFKlbBS7Y1Oc3EhqVEjIhs04Fz16ljr6jL/0SMqnj3LxVwv78dIcnY2vW7eJFsIqpiasi7XXvzHIB/g54gIApOTMZTLcctnfn4r5cbJiauJiRyJiVGXbXvyhG6lSr3yu0djYp77KRSyIn6cns6Op0/paWuLofzVxldthOGZGRpS2sKCstbW1Hd355fjx4GXRwDM7tGDuORkYl/D4lPS1JRx7doRnZhIouoI36Lg4pUrnP73X/b9+SeXrl4FoFG9eiybM4fd+/bRvX9/PCtUwNvDA6uSJdm9cSPXAwNp060bQghaNm36/1atI0coZW3NmGHDGDVoECbGxvw0aRKxcXGUMDfnh3HjiImNpbStLXp6evTv3RtzMzPWbdrE6MGDWbVgAUPGjCEhMZHFq1fToG5dJo8bR2k7OxasWEGzzz7jzr17tPr8c66fOkXAmTPs/P33d18ByEFfX5+NK1dSv04dADZs305cAcfu/jBrFl07dGDp7NnovgdOLgUOLMeOse/iRZb5+dGuenX0dHTQVShoUbkyZ2fMoKar6zsv38LYmLLW1q+tAKwND6f+hQvqlff211jNpWRnY3XiBLIjR/jk1CnmhIQQ/parc7lMhoOBAUCeFVI5IyN+r1SJckZGxGRmqiefj5mozEy1s91aDw+t7+UVt/xONjbcSk4mTalkRYUKmLzGivp1qGZmRr0SJZgbEgLAvwkJVDE1Re8lE/ZvkZFMe/CAzU+e8FvFivTJt8o9n5DA/EePmHjvHt+VLctaD4/Xqou2w/C+79CB2Xv3kpWdTVBYWIGyhRDM37+f4S1asO3UKfblcsQsiOjERE7dvk2LypUZu2kTYdHRL455mzdTv1UrtfW4bMWKbNqxQ339WEAAjdu3R2ZpSd3mzdmzfz9VK1Ui8OxZbpw+TZWKFdWfHdy3L2E3bxIeGEivL79Ulzdp0IDb588TefcuY/I5INaqVo2pc+fSd9gwGqosGpV9fEhPT+d2cDAXr17F0sKCE6dO8fvBg7Rr2ZJrN28SGRXFL1u28Pc//9C0USOiY2I4euIEV2/c4JctWyhlbY2hgQF6enqYmZri4uyMmakpndq25fylS++PAgCgo6PDljVrsChRgmeRkYyaMCHP9W27d3Pi1Cn8ly79z5U4dfs23RcvRtalCxZffcWKw4fV2uXxmzdpO2sWsi5dKD1gAGuPHiUpLU1jDbJf9WA8VQ4+uTHQ1WXxV19p9IEUlfwK9va42tm91mf97O05VKUK+qpBbtbDh6/8zrqICKJV+5jTXVwY4+SEvb7+W9+/opCzMQzkcnqr7icwOZkbSUkf7eRvolCw1cuLtleuEJySQm1zc74twHP9Q5VfzsiIYY6O+N64wYwHD3A0MGB6EUa4jHZy4lB0NDeSklgZFsaAAt7F3LS3tmaiszP+Hh60LSC2vLqZGaPLlGGdhwcjypR5wXfgVQrAhhMnqP7dd8i6dEG3WzdWHD6s/szuc+ew8fOjwsiRbAoIID4lhbn79lF6wABkXbrgPGQIf1279lxpT09n/v79yLp0ocWMGQQEBeWR52pnR/Vy5djwzz8EP3mCi63tC3Wa+dtvdKxZk/m9e1PF2ZlBa9YQn2srOL+yMNTfn7k9e7Kqf3+UQjBI5UCYm6+6d+fE/v349ewJgHv58vTo0kV9vVG9ejSsW5fe3boR8McfdGjdukj7k5OjI9dPnSIlNZUqDRqoF7e+nTqxbdcuwh8/ZsSAAWzcsYPEpCRMTUzIysrC2NiYPr6+9PH1Zc/GjZS2tSUrO5u6NWvSx9eXnyZNYvTgwS/Is7SwwMzU9P1SAADs7exYMmsWAL9s2cJBVQzzjaAgRk+YwK716zF6g/CKum5uzOvVC4DOtWox6PPPsVB5aTb09GSOqmN0//RT/Bo3xkS1StQEOYcjzt23r8DrNcqVw0mDCSSKSr6NuTkl/oOnq6FcTkldXT4xNORyYiKHCtDUc8gWgkWPHv2/F7iGnHryUzbXc39dJ6pXEZOZybyQEGRHjtDqypVCP9fg4kV0jx5lXUQE8VlZ7Hn2jLInT1LyxAkGBAXR7fp1qp47p/G9cBmw3tOTZWFhBMTF8VVgIEohmOLigocWPJuLW76BXI6/hwd+QUGkK5XMCgkhKDmZoQ4O1DQ3LxIZba2sKGdkxLd372KsUFCymKyZucPwAqZMoXb58gAFhuGdmzGDHvXqYW5kxLdt2nBq6lQsTUwKDcM7+P331HN3f0HmhC++4Kc9e0jNyEA3n1Xl2M2bRCUm0qFGDRRyOWsHDuRpfDxjNm4ssP7Tdu+mS+3aONvY4FiyJD/5+rL/4sUCHRtlMhnL5syhopcXfx49yrGAAPW1wNu3OfrPP6xesAC5vOhtTTt//x0TY2O2rl1LRS8vHqisP76dOrFs3TqqVqxIx7Zt2fvHH5R3cQHAx9OTE6dO8fPmzTyNjGT5unWkpKbSoE4dBn/7LXfv3eNGUBC/qpwSk5KS1GN70J07tFLlUXivFACA7p07qzWw/iNH8igsjC969WLZnDm4qhrnjV5s1UtmVMAq0lhVpq+FFzHn5frl+HHazJpVoMlqkAYfXlHJtzI1Vbfpfxncc1ZyM19iBfj12TN8TE1xUSkA2spkcV+1hyiDIptsLHV1+cbJCRdDQw5GRRFYwL7mpcREzsfHU9bQkL6lS2Ouo0MHGxsaWljgbmzMKnd3tnp709XWlq7Xr3MqLk5jbTDB2ZlnGRn8HBEBwMm4OBaFhqIvl7PB0/O1V5fvq/wlbm6sDAvjrmrVmaFUMiAoCJlMxlp395ea6l9GlhBkqQZouUzGCEdHDkdHM9TRMY/im5Vr6ynn31kv2Y7KyvedwnhXwvC8HB3xLlOGyHx+NrcjIpiycyc/+fqqyyo7OzOwaVPWHD3KH5cv551Uz54lPCaGDrmykQ5u1gwfJyeG+fsXOK7p6enx89Kl6OjoMGD0aNLS00lOScFv+HB+XrpUHcdf1CQmJdGqa1eWrV1LlYoVqeTt/bwNnZzo2KYN9evUwczUlK4dOtDss88AMDM1ZcOKFfw4ezaV6tWjlI0NFiVK8M3Qodjb2VG1USO+mzKF9q1aAZCekcHcpUtZtnYtdWrUyLNt8V4pAAAr583DqmRJwiIi8K5bl/YtWxa5Waa46Ne4sXoS3n/xIhVGjmTS9u0k5HJgqaVBP4Cikm9tZvZG8nvZ2WGrp8fx2Fj+LcTZbs7Dh4zVoskXIDIjg5UqZ7M+pUtjVwTbDXmsUCVK4GZszDyV9p+b5aGhdLW1Jf8uc/7JrpedHQLYHxWlkTZoZ21NSysrRty5k3dSDg7mdkoKVc3MmPTJJxp7BsUt//uyZSljYMCWfGF6AXFx/B4ZiZeJCXPe4N0MTklhUWgoB6Ki1M5/X5UuTQ87O9yMjEjJzmbT48cEJidzNDaWvZGRBKeksDg0FAD/iIgXEhDFZGayKjycxxkZHIiK4nAhFrV3MQxvYseOuKu2PVLS05mycyfVv/uOp3FxXHrwQP25O48f80CVe6HbwoXM3ruXwLAw+q9aRdcFC3gWH8/DyEj15/8JDCQ1I4OYpCSaTJ1aoCWgso8P3w4dyt1795g6Zw6Dv/2W0UOG4KzB8cavZ08C/viDIX5+/DRpUp52XzFv3v+PA3Pn5vFta9m0KQ+vXuXxrVt0bNPm+QLW0JBt69aR8OgR+7ZuVecbKGlpyZhhwxji58cQP793Zr57IwXAxtpa3TAJiYlq58APAYVczm9jxvBNmzYo5HKS09OZumsXLkOHsvjgQbI0lOWsqOVbmpi8kXx9uZyRZcoUagU4GhODiY4OtYrI3PoqMoXgj6go6l24wOP0dDrY2LDYzU0jpu2RZcqw+ckTnubKIR+Rno5CJlPnwX8ZcaoVnI0GViqdS5Viq7c3A4KCXgh5S1UqmXr//vPJuGxZWmkg6VNxym9sacmxqlWZXq4cbsbGL4TkdbKxoaKqvw93dGSLlxfV/oMCXM7IiCVublyuWZMmlpbPrY4KBRs8PZ8P6goFPezsSG7UiAd166oTAS12c0M0acIWLy8q5dvTtdTVZYC9PdmNG3O5Zk0+L1myQNnvYhheFWdn+jVurLbITurUiYT16wlcsCDP4qO8nR37x49H7NhB/Pr1jG3XDg8HB1YPGED29u3s/vZbyubarmzo6cmdRYsQO3Zwa+HCQus+edw43MqVY+bChegoFHRq2xaJd0gBgOf+AArVHtGgb74h4Q1ScL6r6OnoMLdnTy7OmqXeP4tKTGTEzz9Tbfz4PGF4D54948dff6Xk118j69IFRdeuLDhwgBSVR/yt8HAGrVmDrEsXGk+Zwv5XeM3+V/mF8TZ+EgMdHDDT0eG3Z8+4lc8kPjskRCur/1Xh4TS+dAnL48dpdeUKdvr6XKxZk90+Pi94fKdkZ7MkNBSPM2fUkQwDg4J4oLKaxGRmsujRI+RHjuBy6hTLQkMRhVg/TBUKlqhWdgDLw8IYkssMXBjxWVl8c/cuFYyN1RnqioLPS5bkcJUq7PD2xlAuZ3SZMnjnU+6alSyJn2oVKJfJ2O3jw4oKFV743PsoP0fpbHTxIrIjRyh78iR78mX82/nsGc6nTqmfve+NG1x4T0JF39UwvOLMHGqgr8/UCRNQKpXcCAp6Z2Lm3wSlUsmu33/nydOn72TyoTc6C+BpZCS+/fqx3d+fvsOGERYRwegJE1i7ePFbV+jw1av0WbYs7wBfTKd6VXRy4uikSRy8fJmxmzZxIzSUqyEh1Js0iStz5mBbogTONjZM7tyZLnXqUGfiRBJTU+lcq5bal6GCvT1VPvmE3g0a8PPgwS+Y9d5WfmG8amXwMsx1dBhob8/skBBmh4TgrwpbupaURER6Oi1fMjhsePyYJaGhXEhIQEcmY7GbG4NU5sTdz54x8NYtLHV0mOjsTI+XRCkMsLdnZJkyLA0NZdjt21xISCg01MtIoWCYoyN9Spem8cWLnE9IoKGlJc4qHwVLXV2aW1nx8+PHnKhaFfNCErUYyuUMcnBgWVgY35cti0wm415KCj4mJmwppJ5haWl8e/cua8LD6W1nx3Zv7yILSQM4HB1dqPk4h0PR0S912nyf5X9MfN+hAy1mzODrRo0ICgtTK/+5yR2Gt/jgQXw//ZQ2VasW+pv5w/BaVamCQyHWiDeh7axZWJiYsH7IkCL7zfT0dJavW0frZs3Yf+gQS9esYXgRpQ/W+gpbLmfEwIGMGDjww7AAZGVl0fXrrxk9eDAd27Rh3rRpAKzbtInDx469/YqjYkV+GTIkz998VYSANrhw794LZS0qV+bKnDn8qApNeRofz6x8KSfd7e35ZfBgspVKhvn7q8tvR0Tw65kzrB4w4LUm//8qXxMWCHhuDteXy9n85Ik6+97shw8Z4+T0Uqe/XnZ2BFSrRm3VFkGLXINNQwsLPIyNOVejxksn/9wMdXSkk40NSdnZdLl+/aXHy5oqFPzq40MJHR3G3r1LgsqcmqpUMigoiD0+PoVO/jkMcXQkOTubnyMiWB8RQa9XrOYdDAyY6+pKe2trDkRFvZbDl4REQRRXGN7bkJmdXeQr9FETJjDwq69Yv3w51lZWTJg2jUdhYVIHeRcUgLGTJ2NXqhTDVMdY9u3Rg6YNGwLQb8QIEt/z+Gz/Y8cKNK0p5HImdepE7wYNAApMs9uuenX6NGzIb+fPs/XUKZLS0ui/ahXrBg1CT0dHI/JzLBAnp06lhLExMpmsUAvEkf/9j9YvWS3kxk5fn552dmQolSwICSE0LY3T8fF0K2BQesGEJ5ez1dsbI4WCIbdvPx+MeJ7DfWWFCq+chPOzzsODckZGXE1MZKTq9wrDycCAhW5uhKalMUaVRnVgUBDfOjmpLQIvo5SeHr62tix49IjDMTE0f83V0ooKFTBWKOhz8yb/RQUwVSjoZWfHs/r1iW/YkF88PdV/eypWJLNxY/TkclyNjJjq4oJo0oSwevXY7u3N0SpVuFKzJoPzxanXLVGCXT4+iCZNuFKzJlu9vfm3Rg2OV63KZ6o97oL4xNCQFRUqsKdiRdZ6eLDa3Z3/OTvz4yef4GlsTE1zc37x9EQ0acKJqlXV9dzo6cmtOnWY/hZRQO8Lp+Li6HjtGrIjR7A8cYKjKqfBmMxMxgcHY3rsGLMePlQrn/+V4grDe1MGNG3KV40aFdnvbdu9G6VSSdcOHbC0sGDe1KkkJScz+Ntvpdm6uBWAHb/9xqG//2bNokV5ytcsWoSJsTGPwsL4ZuJEjVf6cWwsXRcsQNalC31XrCBGpXREJybyxdy51PjuO86rVtLlR4xg9Pr1TNy2jYnbtvHZjz+i7+vLjVz7vLlRCsGef/8tVHabatUAXgi7yWFhnz44lCzJMH9/ui9ezP86dcLxP5jc3lR+UVkgcjPGyQm5TMbq8HD+d+8ewxwd0X3N33AyMGCOqyt/REWx5ckTZj58SBtrayq8QfiemY4OO7y9MZDLWRUezrZXxNr3trOjjbU1q8PD6X3zJk4GBi/dtgDyWBZGlynDvdRUmpcsqbZ2ZBcQzpUlhDojoZFCwS4fH47Fxqod4l6HxOxsNjx+zMm4OB5nZNDn5k31X4erVxl15w4mCgV3U1L43717ZAnBtidP6Hr9Oo0vXWLb06csq1AhjxJwKi6O+ap89hPv3aPb9evUPX+exOxsDlWuTMUCkpA0trTkbPXqHI2JocPVq/gFBtI/KIiD0dEMc3TEQleXc/HxzFdFSawIC1PXs+fNm1Q8e5YEDTnIyoF+9vbcrVMHWy3lnCiMHOWqu60tadnZlFe9h5a6usiA3ypWZFzZspjpvNlJ68UZhve6RCYkYNW3L4quXVn8xx8sPngQ3W7dsO7bl6cFZIh9XW7dvcuS1atZ+NNP6rKeXbvSpEEDDhw+zJadO9+JSXPj9u3Yurlh6ujIBVW7/3vpEtaurixauZKMYtqy1qgCcOHyZYaOHcvO9etfOErRydGRmZMnP1cGNmxg359//ueK5OzzZxYwiKSrtOmcOFk7Cws2DhuGp6Mjcrlc7fFe0tQUOwsLDn7/PdVdXMhWKpnSpQvze/dm2pdf8k2bNtyKiGBSp054vcSx64cdO3hSSCz3GVUIVLe6dQu8bm5kxNqBA4lOTORZfDxNVDGl/4U3lf+2Fgih+suhvJER7a2tScrO5veoKPrlc0oS+f6bn/729jS2tGTIrVuEpqXh+xrWg5xJNr9RsbKpKQtV3v/9AgO5+QoHqFUVKmCpq8uOp08Z/RKnxZxwrUPR0Wx98oRUpRIvExN8bW3pqdqmOBQdzR9RUYSkpeGvSgS0+9kzjsXGcjMpia1PnpCcnY2rkRH+Hh5Mvn+frwIDOfMfBsOMQrYO/CMi8qwm0/OZW5eoHBo75ctVn/9zmUKwIiwMHZmMdvkSSdnq6bHd2xv/iAh25nOwu5CQwKBbt7BQ9Z/C6pmuVLLyDc207aytCfn0U+7WqcPC8uVZWL48S93ceFC3LgY4DBsAACAASURBVNXNzFDyPJ1uOdVk+4mhIfPLl0c0acJGT0/1d3718WF/pUpaGThXurtTSl+fQbduAXAgKgpLXV0av8TC8roUZxje62BuZESfhg05M306o1q3ZsIXX3Bs8mT6NGxIiTc8lyEkNJQ23boxd+pUDPKF+M6ZMgWAIWPGcP81spRqmp5du/Lb5s2kZ2Sgr6pramoqs374gREDB2osX4EmeC01df+hQ/QaNIgvWrfGXZWNKj/9evVi+PjxKJVKeg8ezMmDB/F4zXCt07dvs1qVVXDv+fNUcXbmi5o1sTA25p+gINYePfrcPHT6NBXs7elapw4mBgas6t+fBpMn069xY2qUK0dAUBA1y5WjZK4VTs6KGWCYvz+lLSwY167dS+sTGh1NlXHjmNGtG51q1cLEwIDk9HRWHj7MwgMH6NOwIT3q1XvpC2JhbMzZu3fZduoUXxaiLGhC/sI+fThy/TrD/P3ZdurUa1sgsoUgLiuLqIyMPDH248qWZfezZwxycHjBuS1KpbRFvkTjne3qStVz54h9jcx9SiEIU6V5Di8g3fMAe3tOxMay9ckTml+6xB+VKxfqaa4vl1NaX58bSUmMv3uXlQVkPctZuQ2wt3/hAJfNuRywmpUsyc3atfNc/8LGhi8KOKilo40NokkTAOKyslgSGsqYu3cZYG/P3PLlicnMpOO1a/S0s1OnNi6MjjY2XExM5OFLvLfNdXSQAU9e4xyGEqpJPP9nBzg4UFJXF39Vcp/87Hr2DK+XePQrZDKGOTqyUGV1qGluzqgyZYjMyCAqM5PRZcrQPyiI6mZmfFqiBFMfPGC9pyfzQ0KY8fAheyMj6WZri45MxshcOQaWh4WpQyrv5drnvp+ayurwcEaVKcOskJA8aaEHvyJtb1FholCw1t2dJpcuMfPhQ4KSk/lFFTb4tlRxdsZKNYblhOFN6tTphc/lhOHlZ/WAAQUm+8kJw3tbcqKUANrMmkVpCwtW9e/PpxUq/PeFX2oq0+fNY8nq1SQmJbFh2zacHB0prVoshIaHs3r9+ufvU3w89Vu1YviAAYwdPrxYJ85a1aoxoE8fho8fz97Nm9m9fz+LclkuPggF4I+//mL+8uUcPXECgH2HDvG/GTOY+M03as0HIODMGRavWqV2BomNi6NG48b07NqVb4YModwrkoPUcXOjjpsbvxTgSVrf3Z367u5sGDr0RXOcmxtfN2rEwDVrODNtGltPnWJZ377/PzDJ5eosgr9fuMCvZ85wcdYsdF7ipW1qYMDl2bO5+/gx+y5eZMrOnaSkp5OakYGPkxPrhwyh+0sm/2fx8YzfvJkLM2dSZ+JEhvn785mXFzavGTf/tvJzLBDNp09/bQvEpseP2RsZSUp2Nl8FBtLO2pqBDg7IgBpmZjQvWZLhuSwmf0RFcSAqimuqgfeH+/eJzMigc6lSlM7VLwQwPySE4Y6OLA4NxdfWljYFpDFOyc5mWVgYf0ZHq88XWKFaTdazsKB9ru+sdnfnUkICt1NSqHzuHM1LlqRrqVLq1XqOIvFVYCA/e3jwXXAwq8PD6VyqVJGszv4LJXR0GOboiJFCwcJHj1AKwY2kJMY6ORWYM95OT089iVjo6NDSygrX06cL/f2SurqscnfnSUYGU3OtDAvCw9iYqS4unI2PZ2O+MNIWJUuSlJ3NnUKcybKEeCHRzSAHB5pbWSEHapmbczqXtSMxK4uKJiakK5X8+OABW58+JSYrC1t9fZwMDXEyMGBxaCj3cik2WUK8kFgpMDmZhypFUBRiKcrPeg2e1FnQtkk/e3u+Cw4mqHbtIs2IWZxheP+FS/fvE/UWdTUyNGT6xIlML2Tr2NHenuVz57J87tx37t6nTZhA+erV6dCzJ1vWrOF95KUKQMumTfMcm1gY9WrXpl6+FZK2mNWjB+4jR/LZlCms8PMrcJ87JimJAatXv9L0D6jPHahUtiyd/+M9ZWVn02f5chZ99RWflCrF0r596Tx/PkPWrePX0aNf6zfeRv6bWiB62Nm91Cv/YK7c4wAtraxoaWXFsldo/DMfPqSjjQ1tra05GRfHoFu3qG9h8YITYM5xwGNeI7+AiULBrVcknpp0/z6trKyoZmbGGnd3vM6exS8oiOu1ahVpiN7r0rd0aQ5FR9M3MJBa5uZ50svmJscHIIephTjV1bOwYKu3N+2trVmr8nOIKcTC0qd0aUY7OVG/RAn6BQWx6fFjMvNNng4GBoV+vzBWhIWpfTFs9PQYV7Zsnon7bkoKSdnZ7Hn2TB23721sTEMLC1aEhb3SUdJQLqeDjc0LWf9e1c7rIiLQk8sZ6uDAiDJlGHzrFv4eHoy7e5eKpqa4GRlxJj6ewY6OVC+CuGxrPT1s9PSYfP8+299gu+99x6tMmfdGWSlqzM3MGOrnx+oCtsXfF+Tv+0OwMDZm0Oefo5DL8SlkAhnm74+9peUrTf9vy9hNm+hSuzYVVfXoVKsWHWvWZOfZs+w4c0Yr7ZHbAlHK3Jxh/v48ewvHnDflWGwsURkZdLCxQSGTsdbDg6cZGWrPfE2xNzKS8PR0+qtM+mUNDZlZrhwPU1MZq2HZL2N++fJsf/oUz/+QHOdAISmFA2Jj6X3zJndSUqhvYUHSS5zvfomIoF9gIGlKJTXNzV+Y/HMsMKZvoRg9y8jgfL4+poQXnAKVQFJ2dqGTv5eJCTPLlWNWuXIEVKuG5WucZTGyTBlmlivHSnd3pqgUpiylkn8TEihjYICJQsHAW7c4n5jIk4wMKpmaciQmhonBwcS8oad+7r7moK/PKnd3djx9yt5c++0fjQKgclr8GImJjSU9IwMba2um50oZLCkAWkZfVxd5Id7pv50/z86zZ/llyJA8pv/HsbFFWodlhw7xKCqKPqqQyByW9u2LrkLBwNWr1Q47mqIgC0RUYiJD1q3T6vO4nZLClPv3+SnXEa2VTU0Z6ODAmvBw/tBQrvyz8fF8HxzMsny+J0McHaloasqKsLAXsshpAwGsj4hgu7c3fW7eJP41J56z8fGF7v9nKJX0unmTCkZG/PCKLbZ7qal8q/JDKCgl7en4eCx0ddWnO74J24rgFMQbSUmMDw5mXHAwzS9ffmnOhxwWPnrE+OBgBgYFqTM4KoEQ1dbBbpUF4qYqidWD1FTOxMezLiKClLeIWrifmsqf0dEMcnCgvbU1HW1sGHzrFnFvqVS8b5Sztc2T7vdj4qcFCxg3YgRLZ89mwfLl3C0gh4ukAGgBpRAoC1jZRCcmMrAA039MUhJHrl8vEtn/BAXRYsYMhq5bR3hMDOdyrTIzsrLYefYsSiGITU6m4Q8/sOTgwQLr+iFYIFKys5ly/z7Vz53jaUYGl3LtG99JSVGn5u124wazQ0LeagDOPxgPDAqi3oULPMvI4GC+EKf9kZFqE3f3GzeYfP8+j1/Daa6oWBoaSg87O76wsaGVlRUD853D/ip6FrI9czUxkR/u32esk9Mrz2ZYGRbGoeho1nl4qJ0Bc1j06BHZQjCykK2JUnp6NH0N/wkXQ0PqFNEZEVGZmRz/j0p67giGnKNXRT5FrCjevLisLEbduZPn4KGlFSqQkJXFEFVUwMeClalpoSHRHzL+mzfTsmlTTE1MqF29Op3bt2fo2LHv3X3ovO8P4kZoKH9du0ZgWBiHrl6lWa5jFkdv2EBMUhKJqalM3LZNPSnvv3iRZUV0IlOOk2JB6OnoMLR5c4Y2b67xdsixQMzv3fsFC8TvFy4wcPVqqru44FyA53pRYaRQMOmTTwo8Ea68kZHGQrQ+MTRkpbt7oZ7+baytC3Q+1DSP09P56eFDnmVkqHPlN7G0pOO1a9jp6/O9s7P6s7oyWYE5FppaWuaJfdeTyzHIdeTt7JAQ2lpbs9XLixrnz6sjMvRVn8n92b6BgdyoXZv1np58ce2aOofB5cRERt65w6Ly5YnKzGReSAipqtV3eSMjutnaMkWV2yCnjrr5jt3VlcmY4+rKlzduqFcW+vnup6CylxGckoKXiUkeL/9XfT7nqOh4Da3ENz1+zKT79zFWKHiQmqqOQrmZlIS+XM6WJ08wUSgYX7bsayWeet8xMzJ6q3NH3jdSUlOZu2QJ85Yt429VNtbUtDSMDA05fOwYI777jkljxlBSyw7Hb4pMxMQUb+5SVfifxJtbIH7as4c/r1yhlqsrC/v0oaZqZZKRlcXqI0cY+csvZCuVlLGy4ts2bRjSvPn/b5msXi01YnEOoMeO8aWtLbNdXTHX0WHXs2ckqywjJXV1+dzSkornzpEtBH3s7Pje2ZnQtDTGBwfz69OnZAqBq5ERV2rW5GlGBktDQ7mUmMiIMmVob23N3zEx/PTwofqY2+62tmzy8iIgLo5Fjx6xK9equZGFBWOcnPAwMSEkNZXw9HT+TUhg8aNHKHnu7T+6TBk6lyrFnZQUdZ4DXZmMamZmXE5M5Mvr12ltZcXPqmiGwbdu8evTp1QyNWVFhQrUMjdnQnAw8/6PvbMOj+ro4vC7u9nIRjfuQgwSQghaoDililuhxT5cWqRQKFakLVCkaIHiXihOgUJxKQWKRghR4u4um/3+2LCwJEFCIMj+nidPknvnzpk7M3fOmTNHIiNVYhXsqF0bLaGQbnfuKK/pi0R86+jI9NBQ9EUiMlu3xvrCBeIKCnCTSLjXtCl1/v0X30cEhGE2NpxPTyeruJio5s3RPn1aSedLKytG2drS5Nq1h1qBUpfNakNpRNU3ef0xMzCoMHHRU1Hd/V/dDNjYWFCt9NUCwDsOtQBQvQuAev7TtTTFs7ZQyLa4OIrlcjSFQj4xNWVaSAi/JyTwtZ0dS93dmRoSwr6kJEbb2jLKzo5jyckE5OQgEAiw1dLCS0+PuleuMM3JielOTswMC2Pe/fuYiMWscHfnQxMTvvT3V9qCqAWAF8PVkBDMDAwqr1lUCwBqAUANtQCgFgDUqA6oBYAXw43wcCwMDbGprMpbLQBUqwCgkSat3g442UO9CFUr/1f3fzWvAOouqE588Hc18//XvH8u7rjI+32elFrciRexfW+nnoLVCqG6C94+pMakMsRyCMeWHVN3hhpqqFEpyEvkBF8JVneEWgBQ401CRmIGGQkZRPpGqjtDDTXUqBQS7ydi7miu7oi3GBrqLnj74FjXEVN7Uxp1baTujDcc0pZSanxfA2nr0rM6OUSviSZ2XSyZ1zNVy82sgbSVFHmxnOhV0UQujSQvNO+Npg9g9L4Rrj+7YthEEWMg7Wwa9+fdJ+X4w3gP1gOscV3githUTPz2eMLnhpPjn6OeQC+AmLsx2NSyeS3bdufmHRb/tBhnV2cCfANISU7hxOUTHNh9gNDgUM7+fZb6jeszc/5MAO4F3GPX1l3k5+UT4BvA2h1rMbMwe+fHWK0BeAshEAhoPbA13u291Z3xhiPtXBrX214nfociJn5xRjH3Rt9TYb4PyoVMDaGkoIQb7W5w7+t7VcJ8q5s+QPrFdK63uk7WLUVgqfjt8SrMHyB2Uyzpl9IJmRKC35d+auZfRQKAhbMFf8z6gz5afegp6Mmq/60iPuRhfoagy0GM8xhHf8P+HF50mPjQeFb0W0FPQU96CnpyeOFhcjMeJpm6uOMifXX7MrbmWK7sq3wuBreabuTl5nHx7EVmzp/JoJGDuHH1BuGh4Xwz9Ru27t/K2hVr+evwX+Rk5/DVoK+YPGsyPy35ifS0dDas3qAeYLUG4O3C8r7LubDtAlIrKTa1bFjUbRH/Hf4PiYGEqcen4tLIRd1JbyLkEDgiEKPmRmjbaWM73JaolVFliln3syZ0eihp59LeLvpASWEJAf8LoNG1Rjh860DcljhKCh/GEdB20EZsLOb+/PvPXXduUC73594ndlMsrj+74jCxbE6R4sxiLtheQNNEE7clbuh66hK9QqHlMGpuhMRFQvadbMy7meM42ZGitCIS9yUSOCwQHRcdjJobkROQg15tPVzmuyCWil/7aZccmYyliyU9vu+BxFDC5nGbcWvihqWL5UNG3MQNO087hq8bjntTRQju0VtGk5eZx7WD12jQsQESw4eRApv0aMLhRYeZ/vd09Iz1Kt02bR1tzC3N8arrhbuHO+4e7kwcNRGAVUtWAdD2w7ZkpGdw5MARnJyd0CwNqLXn+B503oEgTWoNwDsG7/be9P6xN0uDluJQx4Hxe8Yz7cQ0Wg1sham9qbqD3mAUZxZzd4gihLDzXGe07VSjrxk0MkCvrh6RiyPfSvoAWTeziFoWhcRVgsO3qkzabZEbQeOCFIkAnhMSNwmOUxwR6giJXBaJvKisZ3TsuljkxXKM2xlj1skMiYsE29G2iv6Y7YzHBg9qrqpJyNQQwn8KR2wsxmawDZpWmlj2tsRjnQc+x3xIPpqMb0/f125+pUSlUFSgmhGypKREmV31k68/waWRC7tn7iYv86FmJ+x6GCa2Jkrm/wCDfx2MjoEOW77ZonL9r5V/0W1atxdi/g8gEAhUsr9GR0bTrGUzRowdwYixI9iybwu9+vYiKiKKgkdCf5uamaKrp6teVNQCwNuFFn1b0GVKFwpyCzi/7Twn15zEq60X/Rf3x8jSSN1BbzhSjqcQuzEWDX0Naq55mIpZIBZQa1UtAocFIpfJ31r6AKEzQsmPysdpqhM6zopdnMnHJhQmFpY5lnguZiIWYNnbksL4QuJ/V01BLJfJSTufhn4dfXgkaaJAQ9WH06ChAXq19YjfGV9uGQ1DDcy7mpN6MpWi5GdLv3xxx8WX2p9ZKVlsHr+ZeR3mcXr96TIMVvm3UMCwtcPITMxkx5Qdin4pkbN3zl56zupZpl6ptZQ+c/tw/c/r/LvnXwDSYtMIuRJCoy4vxzbJwsqCg3sOqly7fuU6ltaWXDp7SUUIuHLpinpBeZoAcOHMBTq37YyxwFj542rmyk/TfyImKkalbHhoOOOHj8dEaIKxwBh7A3tmTJxBfGx8pRsXFxTHvh/3MbbmWOWZ0jDrYWyfvJ3Q/x56n147eI1NYzcpz6l6Cnoyq/UsDi88TEHu8yd9KZGVcGzZMSbWnUg//X4MNh/M7Laz+XvN38TcjWHNkDUvdVBelH6UXxRZyVmEXA15IyahLFdGxIIIbn54k5OCk8qfM3pnOGd2jnMm57jic4Wgb4IoiC54pz/YoHFBFMQUYPqxKVb9FEmCHCc7kvxXMlm3s956+rJsGfe+uodQW0jNFTURagupMaMGIVNffK5r22lj3t2cyEWqWoyk/UmYd3l2a3gN/SefrAqEAkS6T0+//Crc8DTEGnSc0JFvD3zLn4v+pLhQkUMhPT4dqZVqkBiHOg58Nv4zTqw6QfCVYE6sPkGz3s3QMShfnd5+eHvcmrix8euN5GXmsWPKDnr/1Ltq58MjCcW69e7GwT8OMvnryQrbgEkz0ZHo8FGHjygoKGDoF0P579//WLFwBZkZD4XF9LR0Zn83m+ULltO2YVtysnPo/lF3OrftTEZ6BsP7DqdF3RbERscSExXDpy0+JSEugYtnL/Lr4l/p8XEPdm7eCUBBQQFL5i1h/qz5dP+ou8LeYNUGPn7/Y9YsW0MdhzoM/WIoJSUlr8V68kQBoHnr5hw4dYCvJn6lvDZo5CCmzJmCjZ2qdaiTsxOLVy+mwXsNsHOw48z1M8xeMBtLa8tKN87KzYquU7sybvc45bWha4byxbwvcG7grLzWsFNDBiwZwCdjPgFA31SfaSem0WFCB7QkWs/NfBd0WcCeOXvoOasnG1I2sCZmDR0mdODEqhOM8xhHXHDcS2X+L0rfyUeRZMapntMbwdREEhEOEx2oe6wuYlPF2ajzD860zm5Ny6SWNLzSELGZmMjFkfzr/e8L7fTedBRnFHN3mEIV7/aLG9KWUiy6WxA+J/ydoA+QdDCJpANJmHxkgs9fPsSsi6E4rWqS/zh840DW7SxST6Yqr8X/Ho9Fb4unPpt6KpVsv2xshpVvOV8QV0DC7gQs+1oi1Hm68vVVuOHpGOggtZZi5mhGrRa1OLvpLFCxB0CPmT0wdzRn1f9WEXAugKa9mj5R0Bn22zAykzP56ZOfsHa3xtypat7n1vVbXP3nKn8d/ovbN24r+dWClQs4vO8wQ78YSk3Pmnh4eWBiasLWfVsJ8A2gd4feyOVyPvjkA2VdJ4+dxMzCjK8mfsWIcSPQ1dNlxtwZpKelY2hkyKSZk0hLTcPS2hJNTU36D+2PgaEB29ZvY+T4kfyy5hcmjppIVmYWvy37jWYtmzHp+0lYWVux6pdVtPmwDaFBobT/tD2XfC9x+cJlDu059PoLAA8w/afp1PGpA8D+3fspriDTVlpqGsGBwWzYtQFnV+cqa6SxjXG5fz+OB2puqZUUkVhUKVpnNp7h+uHrDF45mIadGqKhqYFILMLnYx9++vcnXBu7vtQBqQr6ulJdzBzNnlkAiFkXw38t/lPuvBN2PT23uyxXxjnTc5wUnORSjUtELIigIObFducCoQBtW8XZ8qM7JImLhLqH6iJxkVCUWoR/P/+Xrmp+nZF8JJm4rXGIjcXU+7segaMDKckveWfoAwR+FYi8WI62rTaxG2KrrF6DBgYYNTciYmEEAJlXM9Gvp49Qs+KlMulAEuE/hBO/PR7vA95YD7BWuZ95LZPIxZGETgvF8TtHPNZ5PNt3+Yrd8LpM6cLBnw8iK5YRfTe6XNqaOpr0nN2T6IBo2o9o/9Q67Wrb0ap/K0KuhtBxQseyQlFBAT9O+xFriTXGAmOsdKxY+MNC0lLTVLTLgz4fhLHAmNp2tVm7Yi1169fl34B/+cfvH7zreatsUP2j/QmICeDzfp8rr7ds15Jr964RnBSssqEFaPBeAxbOWchXg77i/VaKqId1fOpQUFBAyL0Qbl+/jdRYyqVzlzh26BifdPoE/zv+JCcls2PTDs6fPk/rD1qTmpLKuVPn8Lvtx45NOzCzMENbRxtNTU30DfRxcnZC30Cfjt07cuPajTdHANDQ0GD5huVoaGgQHBjMykUryy03d8Zc+gzsQ/3G9au2kSKhCpN4EgN5Wpmn4cafioGx9bQtc0+sLWbgsoEvdUCqir5NTRusXK2erexgG+odr4dQS9HPz2JJHbs+lqIUxTmm84/OOEx0QMtG64XfXyAqf+yE2kKs+iveJycgh2y/bN5lPNhxF8QWkH4h/Z2jXxBdQElBCUXpRVDFsqDDeAdSjqeQ7ZdN9OpobIfZPrG8WWcznKY54bHBA7OOZX3LDRoaYD/eHo/1HtiPsS9jO/AkAeBVuuFZuVrh0tCF81vOEx8Sj6Vz+dpbfRN9hTCgrflM76FnoodQKCx3U6alpcXUH6ayarPCct/UzJTxU8YjNZaqaJfHTh6LjZ0NZ66fYcjoIVU63nYOdlzyvURebh4t67UkI12R5bJ7n+7s/X0vcTFxDBszjN1bd5OdlY2evh7FxcXo6urSZ0Af+gzow9b9W7G0tkRWLKNxs8b0GdCHGXNnMHL8yDL0pMZS9A303xwBAMCrrhdjJo0BYP6s+YSFhKncv37lOn8f/Zsps6e80QurvDRH+uGFh8u979LIBTMHs9eevqG5IbpGz27pKtQRIjYRo1NDh6ybWWX8rFXaKJMTuTQSHUfF2Z+mqeYrGRttx4eW589qRPU0FKUWEbEogpOCk9z69FaF5a63vM4p8Sli18dSnFFM4v5ELjpe5JzJOe4Ou4tvb1+u1L9Cwh8Jr2aeFlWvBqS66b9MmHY0ReIiIXhCMCJdEWKT6nHZe9QN74v5XwBU6IY35dgUOnzTAUtnS0ZvGU3DTg0Vu9ty3PCsa1rzwz8/0Lhr4zI0u07tyv65+ynMK6y0FrUy6NSjEx26diAmKkZ5nv4oNq7eyMJfF2JmXvVr76E9h9DV02XdznXU9q5NRHiEUgBYv3I93vW96ditI0cPHsXZTaHZ9qzjyaVzl9i+cTtJCUms/3U9ebl5NG3ZlAkjJxAaHMpdv7sc/ENhlJidna1c24PuBtH+0/avxVx/Li+ACdMn4FbLjfy8fMYOGat8oaKiIsYMGcP85fOR6Ere6I/f52MfAM5uOsv8DvNJiS7LCJ9F9VXd9PVN9RFrP+fCJQCHCQr3qvvzKtYCJP6RiH4dfaUV9qtKaJMXlqekp+tRNW48YmMxDt84oOOsQ/KxZHICygaQybqRRca1DHQcdbAeZK2w5u5ijrSVFN1autRaUwuvnV5Y9rLEt5cv6ZfSUeMNE/yL5ciL5UoNot0YO1JOpGA32k5F8H1Q5sEzj/5+Wr1PwuvihmdX2w57L3sykyq2s3lgKPh4e59UvrioWMkvKsK8ZfPQ09dj1qRZKkcAt2/cJjkxmQ8/+/CljH12Vja9Pu3FupXr8K7njVddL4UmyMmBDt060LRFU/QN9OnSqwttPmyjWF8N9Fm1ZRU/z/qZ5nWbY25hjpHUiNHfjMbKxorW9Vsz+7vZfNr5UwAKCwpZsXAF61auo1HTRirHFm+MAKClpcXy9csRCoVcPHuRbeu3AbB8wXLcarm9NlLNi6DtkLZKJnz9z+uMrTmWXTN2qXx0ru+5vvb0DcwMKkXfqp8VmpaapJ1NI/Nq+YvA/QX3y/hhv2wUJhUSs1rheWI9wBotK60qrd+omRG67rpELIoocy/q1ygse1mquIBBWTcwq35WIIfkP5NffocIeKXC1+tGXyAWINQRomH44rHMckNyiVoaRfKRZKXxn/VAa6y+tELiLkGWKyNuWxw5ATmknUoj6WCS4pllimBIsRtilVEKH9UsxayJoTCukOQjyaScKF+j9jq64XWb1g3bWuUfe/id9uOvFX8BcGTJEQIvBlYs/JTIubjjIlf3X0VeIuf3ab8/0YDZysaKKXOmkJyUzKzJs5Qa0RkTZvDD4h9e2lzqO7gvRy8cZfCowcyYO0Ol3xetWqT8e+GvCxGLH26qPvjkA27fv01gXCAdunUAQEeiw/rf1xOZGcnOwzuV8QaMTYz5auJXDB41mMGjBr82GLfZGQAAIABJREFU/O65v56GTRoy7OthrFqyihkTZ+Di7sJvy3/j/M3zr6TBC7osQKxV/s42J+3Fw38KRUImHpjIzik7ObLkCAU5Beyds5cTq07QfXp32o9sj0jj5anGqop+ZQNtCLWE2I+1J2RyCPfn3afOvjoq91NPpaKhp4Hhe4avZmdWJCfl7xSCxgdREFeAeRdz3Je5vxSGZj/Wnntj7uHykwuaFopjjYLYAgQigdI74UkoSlfsiDTNX/6RyIP2iI3FCESCV24UWZ30jdsYY9nXEoFQgMRFgvMPziTuSyTrRuXcECUuEtyXq84pka4Izy2eir8lIqy+tMLqS1WbGvdl7hXORbGxGJthNhV6BCgX4FI3vE++/oTZbWfTdnBbNDQ1nuiGd2jhIVr0bUHY9bCnuuFd2HaBjV9vxLu99zO74TnVc0LftPwz6tptalO7Te1n+6SEAt7v8/5T0gmrYuhXQ/lj2x9sXbeVLwZ+QaB/IO+3fh97R3u1mqq6NQAPMO3HaTg4OZCRnkGnNp2YPHMy5pavJmvUxP0TWRK4pNyfzt91rhqpSFODvgv7Mv/6fOVkz0rOYuOYjUxuMFlFig25GsLstrOVRjerB68myv9hmNS8zDx2Td9FT0FPRjqM5NTaU1VKvyJo62lX+v1th9uiYaBB4oFEcgJVhaqInyNeye4/Zk0MN9re4KzxWW59egstKy0aX29MnX11EOmpCkAF0QXcHX5X6cXwX4v/SP07VaVM7MZYzhqe5bTkNGGzwyhKLSpX+yHSFxG1/OH4Rf8ajd0ou6erOTOKCf4mGN2aulj/z/ql9YtIT4TdaDtqrqyp/L/2ttpY9rF8Jd9fddMHSD2dSsDAAOV4h04LrTTzr268rm541RU5VCgUsnjNYoRCIWOGjGHr+q18/e3XbyyDLSkp4dDeQyTEJ7yWwYcqJQDoSHT4bvZ3Sgm2/9D+b6V05ODtwIxTM/ju6HfY1VYwgYjbEcxoPoP0eMU5r0sjF6Yen6p0z2vUpRF2nnYqH/gnYz/B2MaYudfm0nZI2yqlXxGeR+ouI4AYamAz3AbkCob/ANl3simILcD0k/IXh5KCEsJmhXFa6zQnBScJ+F8AuSEPLZAzLmdw2eMyZw3PErEoQiWW++OwGWZDvVP1cJmryF+Q+V9mGcb/AFq2WtRaXQv78YpdgmFjQ4w/UHUXtR5ojU4NHXz+8qHGjBqIjcvu6IU6QmxH2BK9KhpZroySvBJyQ3PRq1OxNiU/Op/gCcFctL+IjrMOja41qhK1dEWQZcuIWhHF1UZXlQzQt7evMlnPy0Z103+bUR1ueC+K+R3ns7L/yiqt07ueN30H9yXQP5BBIwehpaX1xo6pUChk+JjhRGdH07hZ47dDAAAwNDJUvuCjZyZvOh6NMPgAPh/7sODWAuVZW0ZCBgfnPww5KdIQMXLTSMRaYrZP3o6sSKby/L4f9zFo5SAMzQ2rnP7L0ECAQh0u1BISvz1eGX3v/s/3FYlSKhhuoZaQGt/XwGW+gmkbNjFE4vLQKNSwiSG6nrr4HPPB4RuHJ/pWKxew0XaYdzdHli3Dt6fvE/3NXX50QeIuIWpl1EODwVIkHUpC2lqKtIX0yfRG2SHLkRG7MZbYzbFY93vybl7bVhvXha6YdTYj+UjyMxl8qaFGeagON7wXFgiLZC8lql0NlxoAGEnVIcxfSwHgbcWZDWfKtSUQioR0n9Gdlv1bKhmvyo61pg3dpncjyi+KA/MOKK+H3wwnNSZV6ZZT1fRflgZCy0oLq75WlBSWEPFLBPlR+WT8k4Fl76ereu2+tsOgkQFhM8MoznwYNCrzeibattoYNn0++wGP9R5IXCRk3c7i3th7FU9mbSEe6zwoyS/h7tC7DxepHEWoYec5Tw9OpWmhiWUfSyJ/iST1RComH5k8UxtrrqqJSFeE/wD/5/JLF+mLsOpnRYvEFrTKaIXnJk/lj/d+b9oWtUWoKUTiKsF5jjPt5O1oHt0cr11e1DtVj8a3GmM7UtVgy6iZEXX21qGdvB2NbzXGa6cXja42ov7Z+hi3qTiQlk4NHWquqon3fm881nlQ67daOE13osasGuh66mLY2BDPTZ60k7ej/rn6D9u61ZOmgU1x/tH5rV8fEnYlcN7yPCcFJwmeGPzQHVUOEQsV7qSBIwMrHbK6utzwKosPhn1A64Gt1YxDLQC8HZCXyLm6/2qF9xt0aACg4lv7AJ0mdcLB24F9P+4jJjAGeYmcbRO3MeCXAS+VflVqIB6Fw0QHBEIBMb/FEDo9FLuv7BCIn67tEQgFeKz1oDCxkNApocr3Cp8TTo1ZNZ57TDQMNPDa7YVQW0jMmhgSfq/Y197ofSNsR9iSeiqV2I2KCHGh00NxnOz4xPjrj2oW7Mfbkxeap2D+pa/7uAsYlLp4lRq/iSQi6uytQ9qZNMLmhD37DipLRtyWONIvplMYV4j/AH/lz+0utwkaF4RIT0RucC6h00ORF8uJ/z0e316+3Gh7g4TfE6i5sqaKEJB+KV2ZlS90Wii+vX251uwasiwZPsd90Pcua+Bl3NaYhv82JPVUKre73CZgcAB3h94l5VgKdl/ZIZaKybiSQcRixZFQ9Kroh23t68+/3v8iy5S9tFXKZogNTYObommpWa3rg0UvC7x+9wIB6DjrPDQOFYC0hRS7r+2o+WtNtGwrp7auTje8Z0VmUiaDTAfRS9SLo8uOcmzZMXqLezPIbBAZCRlvNX/Iz8tnxsQZGAuMGTVglDJoUMi9EOo41OH7b78nK/PNsUeptADwIBzwq0hqIC95OHFLZBXTe3DvSWWeBbtn7q7wjD3ochAAzXo3K7ub0xAxcsNIZMUy1gxZw9GlR2nUtRFSa+lLp18lGgg5KrtXiZsEs85myLJlJB9KxmaITdnyUO6OV6+OHvbj7YleFU3GlQxiVsdg2dsSDYMnn48rmexjQ6jvo4/7EoXFdcCQAHL8K/b4cJ3nira9NsETgkk5lkJBXAGmn5Zvt/DAXSvleArxO+MpyStBr7Yeln0sseqrsPpOOZ5C8tFk8iPyid1QGghoXyJpZ9LI9s8mfmc8shwZElcJHhs8CPs+jICBAWRcfvbFUF5Y/uIcuyFWRYtSUqDaMVHLo0AOFt1VY9U/Xk5eJCd6VTQCDQFmnVSDqWhaauK1y4vYDbEk7klUXez/yyRwRCAaUo0ntrOkoITo1dGV+t7MOpnxfsT7NA1uitsSN9yWuOG+wp1m4c0waGgAJYpwug+Ok3Rq6OC22I128nZ4bvVUPlPnjzrU/bPuS1+PpK2k2AyyIXR6qDIaJnKIXBqJy08uL1x/dbnhPSskhhJaDWjFj5d/5LNxn9F1ale+P/M9rQa0QmJUNXFgHiTreTRpz+sAbR1tZi+YTct2LRFpiJRH4XaOdnzU4SNm/TzrtYny90ybq8o+GBsdq5SI0lLTVEI3VjVSolJU/q5Rv/xdZHKEwv86PT4dWbGs0u56KVEpTKo3id4/9ea97u+hradNQU4BJ1af4MiSI7Qa0IrmXzYv91mnek50mNCBg/MPIi+RM/vC7FdGv9OkTlz+4zL7ftzHez3ew9rNmm0TtzF6y+inMyCZnOL0YgqTC1V87B0nOZK4LxHbEbZljPAKkwsVv5MKy63TeaYziXsSCfhfAHq19fDa5fVUQS8/Ol8xr2Lyy9y3GWZD2rk04nfGc+OjG/gc9UHPq6yBnkhfRK3Vtbj5yU38vvDjPf/3KqRZkbtW7e0PXZ1MPjShiX8TlfvmXc0x71rWotq8mznt5O0U/ZJQiO/nviQdSqLRv43Qq6OHLEuG3xd+6NXVUwZdqgjm3czJup5F3v28ij9gQw0QQEH801XOGkaKz/3xsrbDbBGbiCuMqZ+4NxG92hUbQgpEAuy+siNyiULrYNjYEPtx9hQmFVKUXIT9eHvuDr2LQUMDjN43InxOOJ6bPYlYHMH9n+6TdDAJy96WCDQEBI0NUtYb/Wu00qUyN/ShMWleWB4xv8VgP86eiPkRKmGhHz8OeVlwXeBK0p9JBE8IxmOjB7EbYrHoYfFMWf6ehup0w3smplHqpQQwv8N8pNZShq4ZSs33a75w3Wmpaez7fR/bN24HYOWilRTkF/B5/8/R0NDgdcG8pfNoVa8Vw8cMx8PLgw2rNjDqm1FvnEbjuXv08oXLnDx2ko2rNyqv9fykJ592/pQv/vdFlYZqjAuK45/d/3Bh2wXltbUj1hJ2I4wGHRsoMwJeO3gN35O+/L3mb0DhMvfDBz9Q79N6tB/Z/rkyAmrra/PzzZ+JC47j+uHr7Jm9h4LcAgrzCnGo48CozaNo/kXzJ9bRakArDs4/SM3mNZ87L8GL0H+ggfiu0XesGbKGxl0bP5MGIm5bHEkHk5DlyggYGIBZJzNsh9uCAAwaGWDykQl2Xz+0K0g+mkzykWSy7ygW3rCZYRQmFWLRwwIt64d9LdQR4jzbGb8v/ZRuY+WqwXNlRK+MJuWvFOWOKnqVYjcpbS7FrPPDOVXrt1pk3sgk914uV3yuYPKRCRa9LJS7dSXT/tgETQtNdBx1qjxo0LNC00ITz02eXKl/hZx7OQpvApEiNrzT9LKJmjStFOUBNKQamH5iyj+u/1QsvJiIqbWmFoXxhU/NxqfroYvzHGcy/s0gbmtcmb6SZcvIDcqtUCvzeKAb2xG2mH5kCkIwfM+QjH8eajuKs4rR89ajpKCE8FnhJOxMoDi1GC1LLXQcdNB20CZqWRR5oXkqNB4PrJQTkEP+/fxytUwVGVvGbY57NQunkQbuS93x7eWLaQdT0i+m47HRo8rqry43vOdF2I0wTJOrrq1SYymDRg5i0MhBr/V7u3u4039of6aOn8raHWvJzsrGwcmBNw3PLQA0ad6EJs2bMP2n6S+9cVZuVnSb1o1u07o9sVzDTg1p2Kkh/1v+vxem2XeBQrJ1rOtIkx5NXvmAvCj9ymggygty8ih8jvmoLk6fmGL6iekTmfqjTAoUBnoV4UE6YIeJT/+ARHoimgY2fWM+MKG2EM/NntzueBtpSylxm+JUhCkVjUqpDYBSg1KB0aK0uRSvnV6YdTYjZl0M/v39y41rAIqoiQ7jHTBqYcTdIXeJ2xZXJo6/tq12hc9XhOhV0UpbDE1zTRwnOaow7tzgXGTZMhL3J5K4X3GsoOuli7SVVCHcPeU4WqgjxLyL+XO5F1oPsiZ2fSxCTSG2o22xH2NP4MhAPDZ4EDwpGH1vfSTuEjIuZ2A30o4rDV/ML9uipwVxW+Lw6+NHk8AmvIuwr23/xggrVY3JsybT0K0hQ78YysbdG9/Id1AbAb6FaDWgFUClNBBqVD0MGhhgM8SGW5/eQs9L75njBCQfKT+kcNqFNPz7+5MblIu0hRRZdsXGd7GbYgkYEkBJfgmGjQ3LTeIjy5Uh0q+86rowsZCMa4/ZO5RQ1iiwRBFHoCLmr1dbD5d5LrjMd6HBhQblxmoow4DG2uMyz4Vaq2vhPFshMJUUl5B5NRNte21EeiIChweSdS2LwvhC9Ovqk3oylZBpIRSnFr/4jrWVFJGeSJkY613DA6PFdxFGUiN6D+iNja2N0hbgrdcAqPF0FOQUqPx+l/Eg2M/jRmmvArJcGbIc2WvRD7ajbYlYFIHJxybP/EzGvxlP7Ff/fv40vNqQGjNrEDIlpMKyeaF5BE8IpuaqmiTuSywTlz7jnwys+luh46jzRHuDJ+FJnhnPimy/bEImK95DbCrGvPPTo9ZFLolU2gA43ndUChr5EYqjg8R9iUqhR7+ePnnheWRcznguA001KoaliyXGNsbv7PtraWm90ZsstQaginH7+G32ztkLwJV9Vzi76WyV5Ch4E5F6OpWoFVHKhTr94qvJkpd1K4uQySHIsmTkBOQQsTCC3ODcau2LFwmW9bh9g/I9b2cRNjMMh28dnpqbIXp1NCnHU/BY76E0BlQy0aWRyGVy7MaWfzShaaFZJrJiedBx1nnuGA8VoSi5iLSzac/1zKMeDEqXt0e1DY95uVQFnjXb39sKfVP9cl2i35kNTkmJipeaWgPwjsP7Q2+8P6zeVI+viwbCuI3xEwPPvLRFqa4++nX1cZnn8lrMCXmRnKTDCiPLpMNJmHUoaygrEAvKjbFg/IGxiu+7UFOoYk8R8XMEZh3NqL2zNtcaXVN6ZAi1FGUeLRswKIAmfk3w3OzJna53lDEMsm5mETQ2CLelbhQlFynCNOcpNDYSNwmWvS0Jmx2mbCeAUCws037XBa74fe6n3FoItARlthtlrj0BuSG56NXWU7Hyf1r5B6miizOKX/q4pp1NI3F/IsUZxUQtj8Licws0zTTfqfVOYiB5obwjbzKC7gZx8exFsjKz8L3lq0wjrBYA1KhWDcSJVSeUGoga9WvQsFNDdKW66s6prt2/WID1QGusB5YNKyzSF2H5uSXGbYzRMNSgzh91lMcWYhMxxu2NueJ9BYmrBKsBVgjEAsw6mpHxTwYJfyQgL5Lj38+fxrca0/BKQ6JWRJF1Iwv7MYpzWdsRthSnF5N6MpWCmAICRwdSe1tt6p+pT+TSSBL3KnbNUSuiyPbPxmGiA00HNyUvIo+CmAIyr2YqAhvJFdb+D/ItOE1zwritsfL9DBoYkHUzi5LCEkw/M8WoiSKEq0UPCxL+SEC/rj4WPSzQcdTBcYojkYsiVY+FhJQJMS3SF2HRy0IhAAge06Q8kD8ee8ZmqA3p5x9qmgQigcoOXSCqOnWttJWURlcavdNzW1NH87m8rN4muNVy4/g/x9/stSlVnlqt+ouTnFRziGrEb/ym7oTqnP8C9fw376pI8SzUFiq8FIrlCDWFmH5iSsi0EBJ+T8Duazvcl7oTMjWEpH1J2I62xW6UHcnHkskJyEEgEKBlq4Welx5X6l7BaZoTTtOdCJsZxv159xGbiHFf4Y7Jhyb4f+mv9Ex4ELOhujCUoW/02IVcDcHAzOCZsww+jna0e6fnvrHAuFoNCNQCgFoAUHeCWgB4Z6EWAF4M4TfCMbQwrLQhoFoAqF4BQIM0afX2wMke6lWoWiUAdf9XL9RumtWKD/6uXvpvAP+/cGE7Li4NsbJyK3PPCSD0RSQw9RSsTqi9AN5CpKbGMGSIJceOLVN3hhpqqPFCCAr6B2NjG3VHqAUANd4EZGQkkpGRQGSkr7oz1FBDjRdCfn4OWlpqI+K3EWovgLcQjo51MTW1p1GjrurOeIvg43MME5OPKCpKobhYNaaCUKiNlpZilxYYOILo6NVvHX19/Xo0bnyd/PwoCgvjVNLbSiSuiMXGxMfvxM+vj3qyvMX488/9rF27nNat23Px4lkiIsK5ePEOsbHR7Nq1hfT0NK5du8zcuUtp1EgRNnzTpjWkpqZw585NRCIRy5evRyJRCzVqAeAthEAgoHXrgXh7t1d3xlsEkciAW7c6kpx8uMw9T8/NWFn1Izn5z5fCfF8H+pqapkRG/kJQ0HiV69raDjRp4kdhYQL37n2lnihViJycNPT0FAZ+164d5JdfeuLu3hSJ5GHAp4yMRIKCLmNl5caCBbfQ1NTh2299yMvLxNbWA6HwYZjpgIDz5OSkMWLEelq3rlzuljZt2jNjxgQuXDjDwoW/cvHiGQQCAdOmjWfz5r1oaGjwyy9z6du3K3fu3GfPnh2EhYUwe/YC8vJyqVHDhJYt29Kv3xC1AKCe4m8Pli/vy4UL25BKrbCxqcWiRd3477/DSCQGTJ16HBeXRupOeoORkfFPuczXwqInVlb9KCxMJCBg0FtLXyw24f79nx8Xd/Hw2IBIpIe/f3+KilKeu97c3CDu359LbOwmXF1/xsFhYpkyxcWZXLhgi6amCW5uS9DV9SQ6egWRkUsxMmqOROJCdvYdzM274eg4maKiNBIT9xEYOAwdHReMjJqTkxOAnl5tXFzmIxZL34g5Fx19F1vbWgBkZSXzzTd7qV//M5Uyc+d+gkAgZOTIjWhqKnIiWFu7M3r0FjQ0HgZGCgq6zH//HaZu3Y8qzfwV2h5djI1NadfuI5ycnHFycub06eMkJMSzdu0KALKzs/DyqktiYgKrVy/lxx9/AUBHR8L168GYmJipFxS1APB2wdu7Pba2tfj446/ZtWs6X365gICAc9y4cQRTU3t1B73hSEzcU+aatrYdtWqtKd1dDaSwMPGtpZ+aeprCQtWcA7a2wzE2bkNCwi4SE/dVkqG44eg4hfj4XURGLsPefiwCgWoiotjYdcjlxRgbt8PMrFMp7dFERi7F2Xk2UmkrMjOvcfVqY+TyEpycpmJjM5iwsJlYWvamRo2ZFBdncPmyJ3l54dSr9/cbMediYu5iY1OrVAOkUYb5nz69nps3j9Ghwze4uz/M0unj87EK8y8szGPlygHo6OgzbNjaF26XIiDUQw+aqKgITE3NGDFibJmyERHhFBUVKv+3trZVLyalUBsBvkVo0aIvXbpMoaAgl/Pnt3Hy5Bq8vNrSv/9ijIws1R30xmsArpT5fD09t6KhYURU1EqSk4++1fQfZ/46Oo64uv5MYWEigYGjX5ChiLG07E1hYTzx8b+r3JPLZaSlnUdfvw4geuQZ1f2TgUFD9PRqEx+/s9wyGhqGmJt3JTX1JEVFyc/ctgsXthMXF/RS+/b27RNMndoEP7/TFQoALVv2V7mXkhLN5s3jsbJyo1evOSr3Hi+7c+dU4uKC6N//F0xMqp4BW1pac/HiWRIS4pTXwsJCSEiIw9raluPH/1Qpf/78afWC8jwagEuXztGhQyvFZy8Uoq1dNv1lfn4eJSUliEQijhw5rzTAeJsQHR3A3r1z8PM7TWFhPoaG5tSt+xHNmn1OcPAVnJzq4enZqkpolZTIOH58JadPbyAhIRRNTR3s7b1o0qQnHh4t+PPPxeVK01FRfmRlJRMScpUPPxz13HRzc+8RG7uJ2NhNFBYq8rF7eKzH2vrZ1Hb+/n2Ji9sGgFTaClPTj7G1HY1I9PxJQ1JTT5Oa+jfR0auVhmcCgRCx2BSZLA+xWIqurifW1gOxsOjOu+RX7+g4Cam0JTk5dwkOnviO0RdQq9b6UtX/gOdiqBVBW9sOc/PuREYuwsqqr/J6UtJ+zM27EB296tkWVQ39pwgbQkSiZzdACwr6h0aNOr9E5n+cqCh/2rQZxJ49s6ldu43yXmZmMvr65WewXL16MPn52YwatUmp+i8P9+5d4ujRpaWq/4FV1u6SEtkjm582GBub0LlzO6ZMmY2OjoQjRw7wyy9r6NNnAHPmTMHBwYmmTVuwb98uevT4Qvlsenoay5b9jFRqzIEDuzl06Az9+3enuLiIzZv3MmnSVwQE+PL7738il8sZOvQLNmzYRXDwPe7cucGZM3/Ttevn9O7dn4KCAlat+oWCggKuXbvMunU72bfvd/74YzudO/dk5cpFvPfe+6xevRWhsPr338/cgpSUJFxc3Dl16ipJScVER2er/Jw6dRWxWKHyGTNm0lvJ/AMCzjF5cgMEAiHz599g8+YMvv/+NDo6+syc2YotW76p0sm9YEEX9uyZQ8+es9iwIYU1a2Lo0GECJ06sYtw4D+Ligst91snJp/R3vUrRlkjccXGZi6fn5kfUaAt5llRqBQUxxMfvKlUZ6lGv3gkcHL6tFPMHMDZug4vLXJydZ5curga0apVFixYJtGyZSI0a35OefgFf3574+w+kytO9vaYwMGiAs/MsSkoK8fP7gpKSvHeKvq3tiFLV/24SE/dWWb0ODt+QlXWb1NSHERrj43/HwqL3Mwirp8jO9sPGZlgF30YcCQm7sbTsi1Co88xtetlueN7eH/LZZ+Np0+Z/pKXFcffu+ac+c+rUOm7fPs5nn43Dza3JE7Q2efz668AqU/0DnDlzgpCQe+zfv5s7d26WaoMk7N59FKnUmJEjB7By5WImTJgGwMiR4xk16huWLp3PoEGf06hRU+rU8VHWd/LkMczMLPjqq4mMGDEOXV09ZsyYS3p6GoaGRkyaNJO0tFQsLa3R1NSkf/+hGBgYsm3bekaOHM8vv6xh4sRRZGVl8ttvy2jWrCWTJn2PlZU1q1b9Qps2HxIaGkT79p9y6ZIvly9f4NChPW+WBiA5OYkffliEj0/DMveKiooYNuxLCgry8faux6RJM9+6BbekRMaKFf2wsHBm9OgtSstWExM7evf+CWfnhixa1K3K6J05s5Hr1w8zbtwuGjbspLzu4/MxtWu3ZubMirUMurpSzMwcKy0APKynFkKhQqjLyblLUtJhzMw6PvGZyMglCIVayGRFaGpalDlLrfzuzF6583sgTAiF2qVaCTkBAYOJi9uMqelHWFh8/sz1FhenExe3hYiIheTnR6GvX5fGjW8+8Zm8vDD++ccNuVyGhUUPLCw+R0/Pi+TkPwkP/4GiolQ0NS2QSNyQybIpKkpBX78ejo6TMDR874X7QiTSpXbt7QgEYkJCviUr6+Yr/Raqm76OjhOurvMpLEwiMHBUldZtYNAAI6PmREQsxNi4HZmZV9HXr6f8DspDUtIB0tMvkpcXhrf3gTLfSGbmNSIjF5Od7Y+j43fY2Y16Ldc4gUBIly7fsWfPHKZP/5vCwjy0tCTl8IJItmz5Bmtrdz7//Icn1rljx3fExQUzYsSGJ6r+v/lmBJs3/4azsxsGBoaPrSn3SUpKwNnZjXPnbtC6dXvCw8umiq5Z05OjRy+Uo5HRYObM+cycOb9c2g0avEfbtg0JCPBl6lTFUUadOj4UFBQQEnIPP7/bSKXGXLp0jvDwELp2/Rx//zskJyexY8cmAFq3/oDU1BTOnTuFnp4+wcH3MDOzQFtbB01NTfT1DXBycgagY8fu3Lhxjc6de745AkBmZgbNm7cu997cuTO4c+cmWlrarF69FbH42Rf9+PgQLlzYzp49s5HLS+jSZQqtWg3AysqVmJhATp9ez+HDCxGJNOjRYybNm3+BmZnjK++oyEhfkpMjee+97ipuLQ/QqFEX6tY+ooWmAAAgAElEQVT9qMro3bjxZ+lOx7PMPbFYm4EDl7Ft27cVPm9jUxMrK9cXUw8JxQiFOpibdyE2dhMRET8/UQCQybKIiVmHjc0gIiOXljkjfbHFSVThPSurAQQGjqKkpID4+F3PJQBoaBhhZ/c1GhqG+PsPICvrFikpxzAx+bjCZyIiFiKXK9SPDyzQAeztx5GXF05U1HJcXRdiZfVl6bdzlZs3P+K//47g43MUY+MXi3/q5rYEicSNtLSzREQseuXfQvXSF+DhoVD9BwT8r0pU/2W1AOO5fbsL2dl+REevxtV1wRPLm5l1Ript9QShoiH29uMr1ZZX7YbXvPmX/PHHLIKCLqOpqYO1tXuZMg9U/yNHbkQsrjgVcGDgRY4dW46Pz8dPVf1nZmZw6NAZmjZtoXI9MTGeZs28EIvFrF2746X47tvZOXDpki/Tpn1Dy5b1uHo1EENDI7p378Pevb9jYGDAsGFj2L17K7Vq1UZPT5/i4mJ0dXXp02cAAH36DKCgoACZrJjGjZvh4eFVqvUpICUlSYWeVGqsEsOiOvHMRwBjx05GR6esNPjvvxdZtkzhmvP99/Nwd/d4rgZYWrrQo8f3WFm5YmXlSu/ePyoZl41NTfr2XYCRkSWOjnXp2nVqtTB/QDlgN28eIzo6oNwy773Xo8rpHT68sNz7Li6NMDNzqPB5Q0NzdHWNqmhBnAAISE+/REbGPxWWi47+Dam0BRJJzVe8cxGhpWVbqo2qHEMQi00wMGgAQHj43CeoNBNJTT2FpqY5AoFIyfwf1mNcDgNohKPjd8jlRYSGfv9C72pm1hkbm8EUF6fj798PKHmlfV3d9O3sRiKVtiYh4Q8SEv4oR1PkUOnjpgcwNe2IROJCcPAERCJdxGKTalugy3PD+/77M0yceED5o6trVK4b3i+/3GXSpMPKcp06TSI3N+OJbngikQadO09iz57ZKgaAD9Xlv3Hnzt989tn4clX/eXmZpYwv94mq/wflHsDd3aMM85fL5Qwf3o+UlGSmTJlD3br1X0ofHzq0B11dPdat20nt2t5ERIQD0L17H9avX4m3d306duzG0aMHcXZW5EPw9KzDpUvn2L59I0lJCaxf/yt5ebk0bdqSCRNGEhoazN27fhw8qJij2dnZyjU9KOgu7dt/+mYJAOUhOzuLESP6UVJSQsuWbRk27OtK1yUWa6OpWf6Hq6Wli4ZG9eactrf3wtjYhoKCHKZNa8q5c5vLlKlb90MsLGpUCT0fH8UO9OzZTcyf34GUlOgyZdq3H1Hh8/r6pk+Uzp8HurqemJgotBtl/bAffKzFREUtKxUWXi1KSvIpLFRY/+rp1a50PUZGzTAyakZ6+gXS0y+VWyYqahm2tiOf+2hDR8elVICIr3T7tLSs8fBYB8Ddu8PJz48qt5y5+cuJAFnd9HV0nHBxUaj+790rX41ubd0fmSy/EgJ3MXJ5calAKcTObgwpKSewsxv9SBmZssyDZx79/bR6K4NndcP77LNxVeaG16rVQCIjfTl3botS+ACF6n/r1gmlqv855Xwbfty/fwtQqP7j40Po3/+XcvMInD+/TeX/vn3Lxo/49dfFnD37N++/34qvvnp5RqbZ2Vn06vUp69atxNu7Hl5edUs3Pk506NCNpk1boK9vQJcuvWjT5sPS9dWAVau28PPPs2jevC7m5hYYGUkZPfobrKxsaN26PrNnf8enn3Yu7f8CVqxYyLp1K2nUqCne3vV4HfBCAsB3340hIiIcQ0MjVq7cVOqb+XZCJNJg1KjNiMXa5OZmsHLlAKZNa6piMCOVWleZv33btkOUQsD1638ydmxNdu2aoSI5u7q+9wS1Y9UGunB0VHyASUmHyM29V+Z+QsIutLSsMDJq/srHJiJiITJZLkKhZqVVrQ/fc3KpoFNWCyCTZZOQsAsbm8HPXW9a2pnSOdK6snoOPD03IRabEBe3hYSEXeV/0EIdTE0/eRl6lmqnrzhu0eXevdEUFiaVo/VqglTa9rm1Erm5IURFLSU5+YjS+M/aeiBWVl8ikbgjk+USF7eNnJwA0tJOkZR0sPQZRbKt2NgNZGXdUqmzqCiVmJg1FBbGkZx8hJSUE09sw+vkhicWa9GhwwQCAy9ibGyr3I2vWjWI/PycclX/xcWF7NjxHXZ2tbl79zx//VWx6v/u3QvEx4eoXLOwsFL5/86dm8yZMwUjI+lLt5jv23cwR49eYPDgUcyYMVeFjy1a9NDzY+HCX1WOtz/44BNu375PYGAcHTp0KxVSJaxf/zuRkZns3HkYXV2FhtDY2ISvvprI4MGjGDz49bEBqfQh7ZEjB9i+fSMACxasfCeCK3h5tWXWrHOsWNGP2Nh7BAVd5vvvW1Kv3qf07bugjLrshSQzoYiJEw+wc+cUjhxZQkFBDnv3zuHEiVV07z6d9u1HIhJVPHwPzg2rClJpawwM6pOZeZ379xcod4IPmfAinJymvtLxyM+PIipqKRERixGLTfDw2IhE8mJ2D6amn5Ya9B0hO/sOenp1HlmM12Jp+cVzuXDJZLlERS0nKmoFUmkLXF3nV6pdDg7jMTb+gLy88ArD3WpqmuPuvoK8vPAq7+vqpm9tPQCptBVyuQx7+/FlBD2x2BiJxIW4uK3PXbdE4oK7+/LHBH5dPD23lP4twcrqS6VNxwO4uy/D3X1ZBUzUGBubYRV6BKgy/9fPDa9du6H4+p5UMsPz57fg63sSXV0pBw/OL8P879+/DcjR1TXi11//h1wuJycnnQULVN0XMzOTCAr6lyFDKnapzMvLZciQPhQWFrJmzTZ14J7XTQBISkpg7FhFHOUuXXrRvfu7k3zDxaURCxfe4ciRJezf/xO5uRncuHGE27dP0LPnTLp0mVJ1g6OhSd++C2nRoi+bN4/Hz+80WVnJbNw4htOnNzB+/B8VGvppa+u9BCYwAV/f3sTHb8PZeQ5aWgqpPTX1FMXFmZiZdXnp/S+T5XDz5ofk58eQk+OPQCCkVq1VpYy5Kt5ZgIPDt/j79+X+/XnUrr2jdAdURHT0Gho2vPRMtcTFbSIxcTcpKccRi02pV+8kUmkrBILn38no6Djh7PyjkrG8996dcgRGLTQ1LQABfn5fVmmfVzd9xS57I7GxG9/KNcXb+0O8vT9ELi/h0KEF3L17nlq1WjzxmQdueB06fPNS3PC0tCQMHLhURaPwuFYBYPHiHuTn57BmTYzy2vLlIS/UH999N5bg4EC++GIgnTr1eKPHtqSkhEOH9pKQEM+VK5do3LjZmy8AjB79P1JSkrGyslFRkbwokpMjWblyQJnrmZmJr1UkOw0NTTp1+pY2bQaxb9+P/PXXCmSyInbunEpRUQE9e86qYsbrzYwZp7h58xjbtn1LVJQfERG3mTGjOQsW3Cq3b95/v+qFMnPzHujofEde3n2iopbi4jKvdPe/EAeH8ZVibs8LkUgXH5/jFBdncOVKPfLywsjMvP5MO61nhaXl54SFTSchYTfOznPQ0XEmPn4HJiYfPrNBmJXVAKysvuDGjQ9ITT1FUVFSpfsnLy+c06e1q22+Vzf9dwXV6YZXHiwsnJ9aJjo6gOzs1Crrgz//3M+WLWupUcOFefOWvfFjKhQKGT58DMOHj3k92/e8D2zYsIq//z6KQCBg5cqNGBlVXVILU1N7Ro3aVObHwMC82juqoCC3jPW/vr4J/fsvZuHC20p3mf3755KV9eKuSaGh/5W55uPzMQsW3FIKGBkZCWXUcS93gRJhbz+u9MNfjUyWRU6OP1lZ17G2HvhKx0NDw5A6df5AKNQiJmatSvjVF39PDeztv0Eul5UaPcqJjFyCg8PzBnoS4Om5FbHYlLt3h5GfH6Hmcmo8Ec2bf0l8fAhBQZeJjb33ytzwKosGDTqqxCl5EcTFxTBmzGA0NDT47bftyvNzNV4TDUBoaDDTpyusvIcMGU2rVh9UWDYmJgobG7u3pqPy8jI5dWot/fv/UuaejU0tJk06zPjxHshkRYSH36ROnQ9eiN6ZMxuwtHRGV1f6mEQponv3GSQkhHHu3GZCQq6+0n6wth5EWNgsiopSiY5eQ06OP7a2I58rsllVQV+/Hm5uiwkMHMXdu8MwMGjwwjYAD8d0EOHhs4mL24yBQX309LweCUb07NDSssLTcyO3bnXAz+8L6tc/pxLTQCTSx9y8C66uCxEKtUhK2q8i5JiafsaZM7poaztgZdUPJ6dpFBTEkJ5+CbHYFLHYhJiY34iO/lX5nJFRM+ztx2Nu3pWsrNvk5t5FR8cZmSyX8PDZpKaWHwddR6cGDg4T0dKypKgoBbm8hPz8KAQCDRISdqOhoYet7QisrPqTlnae/PwHZ/0iDA0bkpCwl9DQqW/9oimT5XL+vBmmph3R0Hjgj19CbOxGdHVr0ajRf08MHPRkDddDN7yWLftV6IbXocOECt3wdHQMnskNT0fH4IX7onHjrmRlpbxwPSUlJQwf3pe0tFSmTv2BevUalVsmJOQebm61UOMVawCKi4sZNuxL8vJycXWtWWFUJVBEBtywYdVLa/Tly7sZM8adnj0FHD2qOKfKyUlj7drhfPutD35+pwkPv8nEiXXp2VPAX3+tQC5XWAbHxt5jzBg3Vq7sT3Jy5HPRvXr1gLKex2Fl5Yq1tcL//dEgHZWFXF7C1av7nyB5d6gyWs+3QOliazscUBj+JSbux9a2+qxabW1HYmHRC5ksC1/fnpSU5FfNhyHUwc7ua0pKCggMHIWj46TnHcFHNFufYWc3mvT0S4SFff8YM8kiLm4L6ekXKSyMw99/gPLn9u0uBAWNQyTSIzc3mNDQ6cjlxcTH/46vby9u3GhLQsLv1Ky5Elvbkco609MvERm5uFRon4avb2+uXWuGTJaFj89x9PW9y7TW2LgtDRv+S2rqKW7f7kJAwGDu3h1KSsox7Oy+QiyWkpFxhYiIxaUaoFWPtLUv//7rjUyW+dKWKRubITRtGoymZvUfBRYVJVGr1lq8vHZSq9ZqatVajUTiUqrx2VJp5v8A1eGG9zwIDr5C37569OolYvv2yZw4sYovv5TQu7cm589vrVSdy5cv4MKFMzRp0pxx474rt8zJk8dITU3hdUD37h/x3Xdj+PHHafz44zSaNq1N06a1KSoqejsFgEWLfuDGjatoaGiwevXWcpMBPcCOHRsxNX0+N7TCwlxksqIKhI8CiosLlP83adKTGTMUFqnFxYWljFAR9Ob7709Tu3YbnJx8mDBhL5qaOujqSpXnr2Zmjri5NWXkyE3P7bKXlHSfAwfmlXsvMzOJhIRQrKxccXZuUCWDs3v3TNLTy/cbDwq6DECzZr1f2uRQ+DCXFXjs7L5GKNSisDAeS8veaGqalXnuwa6oKtvyQDB6HB4ea5FIXMnKulXp0LDFxRkUF2c8JlyMQiTSx8TkI3R1PVWYu0yWhVwuQybLfqye9FImoXou6uq6AD09L8LDfyrXUl0uLyy3XbGxGyguznxkF1Tw2KK/HJCXJkKiwnIKI8ZVCAQaynS2D6CpaYmX1y5iYzeUSfmbmfkfgYEj0NCQPrGdJSUFREevrlTfm5l14v33I2jaNBg3tyW4uS3B3X0FzZqFY2DQECghM/NaKZNVaCrc3BbTrp0cT8+tymfq1PmDunX/fPmLplBbxdUxJ8ef0NAZ1KgxA339ui9cf3W44T0PTExsadPmf8ybd42uXafSrt1QFiy4Rfv2I7C393ru+m7e/I+ffpqOgYFhhS5/9++HMXXqeDw967wWjLNfv8HMnbuUqVN/oE+fgdy/H8bixaufKwru64BnOgK4ceMqixYprIAnTpyBj0+DCphgBgcO7Gbq1PFs337wmRoQHx/ClSt7iY8PQSgUsX//XN57r7syFPDVq/tJSYkmPT2BAwfm0azZ55iZOWJiYsf//rec334bRpMmPfjnn920aTNIRWVuYeH8//buO7zG8/8D+Puc7CVTBpkyjVglQsRWam+1FSFRM/YqRY2ipaUpQWvVKkHaUpG2ZhK+SM0gyI6IICI7J+f3x3NykpOchJBI8uv7dV2uNmc89xnPee75+dwYOHAx9u6dixYtekNLqxb++GMTBgxY+M45C/bvX4S4uLvo02cObGwaQyqVIioqHP7+3lBX18KMGQcqbDFcSkos5s1rjmHDVsHdfRA0NXWRnZ2O06d/xO+/b0SHDmPh6Tmy0k6OrKwYSCSvkZf3CqqqtYpUGGawsBiFhISdSuPus7KEkZXs7CeQSiVlpvF9W5mZ0bIec8nXo6KiB1fXw7hyxR0JCTuhqmoAR8e1b5WKOC8vFUlJBxEbuxlZWbHQ1XWFsXEP6Oi4QE3NEJaWExWiG1JSTuHp02PySvnu3YkwNR0kCx0MlFfusbHCngimpv2grm4OsVgTrq4HEBbWArdvj8HTp0dhYTGizNdmajoQaWlXkZkZVfoPWFUfgAjZ2W9OMKSqaiD/XhQbOpOgpmaMhISdSp/39OmRMhMsiUQqsLKaipiYjQAAff1WsLaeiZycZOTmPoO1tS/u3p2IWrVawsCgLR4/XoGGDXchOvobREWtQnLycZibD4NIpIr79wv3c4+L+wHq6sL6n4yMh0XOhUeIj98Ga+uZiI5ei9evbymMCFU2IdqhsGF169Zo6Oo2hq3tggoroyrD8N7EyKguPvtMWKD33Xcj8Pr1cyxceFIhaqA8Jk4cjtzcXOjrq2PcuKFK65XHjyNRp44l9PRqoTooSAgEALNnT8bAgZ/C3b1tjZsCED1//uakxB4errh795as9a2ttPLMz89HVlbhjmD37iWhdu03L947c+b93sCaNb2QkhKHTp3G45NPSsYnSyS5mDu3GRo16oRevXxx/vw+DBhQ/nnKly+fICBgNdq1G4Xw8FMIDz+Jp08fIysrHbq6hmja9BMMGLCowva63rNnDjw9RyAx8QGuXg1ERMQFZGdnICcnEzY2jdG1qzc8PUe8dznbtpW8LSPjPpKSDiIhYRcyMx/CwMADJia9UafOOHlvPz09Ag8fLkbjxr8WqRxPIiUlCHFxfvKheCOjrjA27irrTb/rdsCnERv7AySSNFkF0wampn1hYTFaYUg4Pt4fd+9OBCBsHlS7dh/Y2i6UhytWR2fOCL8lV9cDMDb+RL4GQFXVECYmPXDpkqNCA6Bjx9eIi/sRDx7MhpqaMRo2/Bm1arXA1audkJ5+V/64WrVawM3tCsLDe+PZs9+go9MATZsGIifnKa5e7aSwe1/LlqHQ1W2Iv//We+Pr1dFxQevWd4usARBDX98dqamXcPv2WNljGqBx4yPIz8/G48dfwti4G54+PQILizEwMuqMR49WQF3dBOnp9+QJhRo12guxWBM3biiOZKioaEMiyYCKii46dkzDuXMWyMl5Am1tB7Rp8wChoa4KDQAVFR1IJOnlqGjfLyf7w4dfIDp6HVq1ug4dnfKnwJ44sfT7kpIevtVK/Krk42OF7OwM7Nz5bkPzXbqgRjt69ADmzp2CsLAIGBubvENjqmqz573VCMDFizer7RcwfPhqzJ7duNS5cBUVNUycuBXLlnXA8+cJmDr13eaoDAzM5S1ce/sWGDhwcaW+r1GjhA1IbG2bonXrDxsLq63tBDu7JbCzW1JmRVC08heGBj+BsfEncHL6psJei5FRJ9mWwGve+Ni6db1Qt65Xjb2YFKwBKGBvv0Lp4wwNPeHquh+1a/dDfPx23L49psSUQ4E6dcbCxsYXBgbtcPeuFxIT90IqVZxq09S0LPX5pYmL80NS0gFZj9hUYY1EevodZGQ8gETyGk+fBuDp0wDZOeMKQ8MOiIvzw5u2bS7YhOrJk1/e+jXVqTMeCQk7IBarw9JyCqytpyMiYjIaNNiJBw/mQU+vCbS1nZGaGgIrq8kIC2v5Xt/Xq1f/Q1TUajg6fv1Olf+bVPfKHwCsrRsjNzcL/0Vpaa+waJEvli1b+06Vf3WgWtO/hODg7Rg8eCl2756F5s17QE+v5Bfh7OwBF5e2sLRsUGbGLKLq5Nmz35Xe/uLFeTx8uBBubldgaNiuxDqEohISfkZ6+l24u/8Lff1WSpPpSCQZUFN79wtYTs5TpKZeKT4mqGRRYL7stSqv/HV1G8kaeiIYGXVGYuLPb1EBzUBOzjOoqRnAxKQ3EhJ2ID8/D69eXYampjVUVHQREeGNjIz70NAwg5nZUDx+vALZ2QnIy3v3+PX8/Czcvj0aBgZtYGU1/T97jtraNkFubvZ/8r2vWLEQtrb1MGLEuBr7Hmp0A+CPPzahbdthcHBww7Vrv+Pnn2eW2sNXVdWo1HzSRBUtNTW0jAooB7dvj0bLlpdRr94yREaWnoEyM/MhHjyYDRcXPzx9erREXvrU1EuwsBgDLS3bMtcblKVgNOB9vH59C5GRwl4MamomMDXt98bnxMRslE8B2NpGyRsaBTkXnj49Kh/x0NNrjszMx0hNDUFqash7vdbIyEXIyopF06a/K6z5yct7hezshEoZEaiO6tRxRlZW+n/ut3n9+v+wZ892BAdfkU+JSyQSvHjxvNwL4KtSja0R79w5i/x8CRwd3SESiTFx4jZcvLgf//vfCaWPl0rzkZ+fD6KaxsJilNLb09L+xaNHy2BjMxf6+u5lHiMu7kekpPyJBg12yBcDFlaimyCVSmBlNUPpc9XVzWBk9Oa8Flpa9tDXb1Mh7zk39xlevPinXM8pGsFQuN960dEGKd409fA2Xr48j9jYjXByWg8tLTuF+2JjNxfJDfD/X61atSt835HqTiKRYNYsb0ycOA0NGhRGPZw5cxI5OTVrNKTGNQCyszNw4sQ6rFnTS2GTjLy8bGhoaGPLljElYlFv3gxGdPQN3Lol/JeouhGJ1JRuMWxk1FVhoaNYrA6xuDAELDr6a7x6dQWNGu1XCMcUizVk/9Us0mgeDxUVXTRsuEshMiMt7Tru358BK6upsLNbrJDUSVvbCZaW3vJd8gpeo1isVuL1OzquQ1ra/+SXFpFIo8TlpuRtpcvIiCzX9s4ZGZEARMVCNiuWVJqL27fHQiRSQ2rqFdy5M0H+79q1jxET8021XnRa0bS1DSpl35HqbNeubQgPv4q8vFx5HoAFC6Zj7twpNW7joho3BaChoY0+feagTx/F/aEdHd2xa5fyRCSurp3h7/8ERNWNiooezM0/hZFRJ3l644JV7GpqxjAy+hhhYU2gre0ICwuh4qlduw9SUy8hKemwrEIajVatwtGyZRhiYzcjLe0arK2FeWlLSx/k5b3E8+dnkJ0dj4iIKWjUaC8++uhvxMRswtOnR+Q919evb8PGZg7atJmAzMxoZGfH49Wry3j0aAUAKfT13eVhn3Z2i2Fk1Fle+deq1QJpadeRn58DE5NeMDAQstSZmQ1GUtJh6Ok1hZnZYGhp2cLWdiFiYjYUy1UgBiAq8dmYmQ2VDfGLZGWJivVdFJ9Tt+5EvHx5rkjDRKVIXgq8d0iqSKQGD4+HPHFlNDV1/nOLAMeN88G4cT4lbl+9elONey9vFQZYmd43DJDej7IwQPqQ57/oP/8ZmJoOgLPzdxCLNWVRCnkQi9VhYtIDkZGLkZR0AFZW0+DsvAmRkYuQnHwUlpZTYGX1OZ49O4n09DsQiUTQ0LCErq4rwsKaws5uMezsluDRo2WIiloDNTVjODtvhrFxN9y+PVIemfC+YYDvq6wwwJogIeEeXr9+XuaOhGWp6WGA76uqwwDZAGADgNgA+M9iA+D9JCU9Qnr6C9Sr9xEbADWxASCVVm0DADhcxaVX7X7TQ0T/7Qqgyk+//zjRf/38q+IaqGtQFX8AVfwCunRZW6Xlz58//z99/jMujoiIiA0AoqqxY8cOGBgY4PLly//J8omIPrQamQjoypWH2Lo1CJGRT6CnpwVVVTG0tNTRt29LpKVlwsBAB4MGuVda+Q+vXEHQ1q14EhkJLT09iFVVoa6lhZZ9+yIzLQ06BgZwHzSIZ1c5aGlpwcDAABoaimFiDx48wMKFCxEfH4+MjAzcuXNHvuXmzZs30ahRo/8X5RNRoezsbISEhCAsLAwvXryAiooK5s6dC339snMsxMbGYsuWLQCAevXqoWHDhmjTpk21nOpSVQVWrgRq1QJmzAAGDQImTABGjwa2bwf++AOIiwMaNgS++w4ICBBuc3YGDh5UXD+3ciWwZAkglQrHO3IEOHoU2LoVyM8H9PWF5wcHA8nJgJsbMH9+DRsByMuTYM6cPejU6Ut07NgQwcFfIDBwHgIC5sDPzwtXrz6Cl9dWPH/+ulLKl+TlYc+cOfiyUyc07NgRXwQHY15gIOYEBMDLzw+Prl7FVi8vvH5evhSjHh4eOHLkiGxnwSicOHEChw4dwpUrV3Do0CF4enrKH6unp4fRo0fj6dOnSE1Nxc8//yz/FxAQgNzcXKirq8PJyQkrV66EVCpFfHw8jh8/jqtXr+L06dPw8PCoVuUDwPDhwxEVFYUmTQr3qr99+zY++ugjdO3aFZcuXUJ4eDhiY2PRv3//Cv9uq7r8/4/s7e2xdetWBAQEyG+bOXMmDh069J8on96dhoYGOnTogEGyjpREIsH58+ff+LyzZ8/K/3/YsGHw8PCotutc8vKAW7eAa9eAnBzg8mXg0SOh0o+MBP76S6jEv/0WSE0F7t8Hjh0T/p41q/A4BgZA48ZA+/bC369eAffuAefPC5U/UPj8I0eEhd+//iocp0Y1AObP/wXr1wdi796pGDHCEyoqhS9fX18bX389Er6+vSqtAfDL/PkIXL8eU/fuheeIERCrFMYUa+vrY+TXX6OXr2+5GwAXL17Et99+CwCYMmUK+vTpgyFDhsDT0xMxMTE4e/YsZs6cCQBIS0vD7t27ceHCBSQmJmLs2LHyf/3798fMmTOhq6uL+/fvY8mSJcjPz8eePXvQt29fuLu7Izc3F8HBwQo916ouvzTr16+HqakpJhZZKm1mZoaDBw8qVNSVparL/1Bat26NoGvi0IoAACAASURBVKAgSKVSHDhwAAcOHEBISAj69u37XsdNTEyERCKBllZhYqGTJ0/C39+/WpVP1Ze+vj4MDAwgFotx+fJlZGRklPrYlJQUJCQkyCt8bW3tGv3ePTyAzz4rrNgL2NgAMTGFfzdrJowcDBv29scOCgI6dapBDYDQ0AfYsCEQbdo4o2/f0nfxWrZsMPLyJBVe/oPQUARu2ADnNm3QsowL0+BlyyDJyyv38bOyspTeNnv2bOzfvx/r1q1D8+bN5ffl5OQoPc7OnTvx6pWQEEkqlcqHqwEgNzcXGzduhIaGBkaMGFGtylcmKSkJ8fHxuH//vsLtampq8Pb2rvRzrqrL/1BCQkJw8KCwLe+nn36KTz/9FEeOHMHRo0cVRn/KKyMjA3FxcQq3RUREICgoqFqVT9WXSCSCvr4+GjdujJycHFy6dKnUx547d06hx19TIlyaNgX69SsZEnnxIvDTT0BSUuFtffoAU6cqjgA4OwNt2ggNA923TMoolQJZWTWoAbB58ykAQL9+ZW/hqaenBW/vjyu8/FObNwMAWvYre4MSLT09fFzBlcPy5cuhoqKCqVOnlvm4gQMHwtTUFHllNEAKwu7S0tKqTflxcXFYsWIFbG1tERpauAFO9+7dkZWVBQ8PDxw4oLjZTM+ePWFmZgYA2LBhAzQ0NCASibBx40YAwK5du2Bubg6RSISRI0fiwYMH8srGxcUFrVu3llcOVV1+9RiOzCvRkBOLxRg6dOh7Hfdt99+o6vKpemsv6wZfunRJoVNRID09HREREWjZsmWNe2/h4cLQfmk5cW7dEub1AeDECeDJE2HIHwBcXYXnHjsmrBsYMqTk87W1AWNjxds6dRJGAcrdALh58yaWL18OOzs7iEQiiEQi2NjY4Msvv8TNmzcr7UM6e/YOAKB+/bpvfKyJiV6Fl39HNrdUt379Nz5Wz6Ri94a+d+8enj17Bnd3xYWNFhYW8vn348ePl6ikitPU1MScOXOQmpqKvXv3Vpvyb9++jfPnzyM6Olrh8VOmTMHw4cPx7NkzDBs2DO7u7ggODgYAWFlZoXZtIff9rFmzMGOGsJFN167CpjVjxozBihUrAABDhw6Fo6MjAGG42dzcHCdOnIClpWW1KL86K2ioLVy4EOvWrcO2bdtw7NgxaGlpoV69ejh+/DjCw8MBAC4uLvjnn3/w22+/KT1W/fr1sXPnToU5+epePlUPFhYWcHJyQkZGhtJInYsXL6JFixZQV1evMe9JVVXo/TdoAKirC0P5dnZA3bqAvT3QowcwYACwejWgogK4uADNmwsjAF9+CfTqBcyeDRQMdKSmCosJXVyEUYFhw4QFhRs3CmsBXFyA3r2BwYOBjz8G5s59hwaAq6srvvjiC+zatUt+265du7B06VK4urpWygeVny9FQoIwr25srPfBvyhpfj6eJyQIlXvxptQHkpKSAlNTU4Xbis7B9+3bF2vWrFH6XDc3NyxatAjbt2/H/fv30bx5c8QUnUSq4vK7deuGHj16lHieWCzGvn37sG/fPlhaWiIsLAxdunRBt27dSgzLe3t7QyQSYd++ffLbBg0aBJFIhJ9++kl+W0REBBwdHeWVd3UovzqaMWMGsrKysGvXLri4uGDJkiWYM2cOJk2ahNatW6NLly549OiRQmUaERGBP//8s9RjRkZG4tWrVwpz8tW1fKp+OnToAAA4f/68wshOTk4Orl69ijZt2tSo95OXJ1Tgvr7CIsDDh4HOnYH4eOCTT4CvvxYWAc6cCbx4AXToABw6BKSnA127Ar/9BowZAyQmCscLChJGBiIihPsXLQJ27xayTRY8f906oZy5c4XFgu88BVC3bmFP3NraulI/KLFYBHV1VVmPIPODf1EisRiqspZlZjmGziuSoaEhnj17VuZjfv/9d6W3X758GV999RVGjhyJqVOn4tGjR9Wu/OLhd0UNHz4c9+/fx5o1a2BgYIDTp0+jRYsWCsP1dnZ26NSpE3bv3g2JRFgDcuzYMTg4OCAwMBCJsl/Jjh07FBb1VZfyq4spU6Zg9erVMDU1hZubGyIiIhAZGYlu3bpBLBbjk08+gVQqRa2CMcnijeUyMjvm5uYiqeiEZjUsn6qvevXqwcrKCi9fvpSP+gDAlStX0KBBA+jo6PBDKm/d+q5PVCmyAl4srvylBM2aCftu37uXUCUflF2zZgCAhHv3PnjZDg4OMDU1xblz58p8XGhoKKKiompk+coW7Ny4Ubh1s5aWFubNm4fIyEj07dsXaWlp8PFR3JHLy8sL8fHxOH36NKRSKQ4fPoyDBw8iLy8PO3bsQG5uLm7evKl0nrCqy68uNm/ejAULFsDb21s+pZeXlwdDQ0OsWbMGUVFRePbs2TsvsHpT6ucPXX5Eejo+j4iA6MwZdLl2rdTnJWRnQz04GCZnz+KnhASkSypmoXF6RDoiPo/AGdEZXOtSevnZCdkIVg/GWZOzSPgpAZL0iik/I+MeHjyYjTNnRPjnH33k5b0q9bGvX9/CmTMi/P23LuLi/JCT8+EbUwVrAc6ePQupVIr8/HxcunTpnRaLisX5WLMG+OEHYQh++HAh9M7SEjh1Cpg2TRiCX7JEiKP/6y+hx+7vX3LB3sqVhUPxtWoJvXEfH6Cgaix4/qJFQo98+3ag+EyxWCwMz0skQi99507hdTg4lP9zGjJECCUs7JwByi47NWYR4Jgxwhd/6FDIGx97/35ixZ94Y8YAAELeIoY4sdjw8PtauHAhcnJy5KF6bzJq1Kj/F+X7+/uXWPBjbGyMQ4cOwdbWFuHh4QqLx/r37w9jY2P5PG/Pnj3RrFkzuLu7w9/fH8ePHy9XaFlVl19deHh4YO3atZg3bx7u3LmjcJ9EIlHoDNS08l10dLDR2RmqIhGCnz/Hv6WM8G2Ji0M+gE5GRvisTh3oVNB71nHRgfNGZ4hURXge/Bxp/yovP25LHJAPGHUyQp3P6kBFp2LK19Z2hqPjemhoWCIv7xUSEraX+tiYGGGBq4FBO1ha+kBd3eyDn4sNGzaEiYkJkpKSEBERgZs3b6Ju3bowMjIq97Hy88VVHoev+HqEij8lBdiwARg3DoiNBX75pfyfU2Cg0JApMG2asNiwxjYAxo/vBHd3R1y4EIHt24NLfdyFCxG4fTu2wsvvNH48HN3dEXHhAoK3l/4jibhwAbG3b5f7+MqGoFVVVbF06VKMHDkSEyZMULj4qampQU1NrcRzunbtCnNzc3mvVk1N7a3mPKu6fGXS0tIU5tQLqKurw8rKCra2tlBVVVW4fdSoUThx4gS2bNmCcePGAQAmTpyImJgYLFiw4K3CD6tL+R9Swfso+n4KtGjRAtra2tDT00Pz5s1hYmICbW1t2NnZ4cmTJ7Czs0PdunVRv359tG/fHrVr15afGwULhYuOtCjrvVdl+WoiEToaGsJITQ0blKyNyczPx+XUVNhqakK9EkLLRGoiGHY0hJqRGmI2lCw/PzMfqZdToWmrCZF65YS2aWvbQ1e3EWJivoNUWnJ0ITf3GTIzH0FFRQcqKlUXXy8SieSjAP/88w/OnTsn/7viG56VH4evvGFStD4TFgmWV2axmfKHDwElwRM1pwGgqqqC339fADc3B0ycuA2+vrsQE1M4J/3qVSY2bz6Fa9ceo39/twovX0VVFQt+/x0Obm7YNnEidvn64lmRsyDz1Suc2rwZj69dg1s5M8W1bdsWc+fOBQCsWrUKu3btwvbt2xEUFAQrKys0b94ce/bsASBk4vPy8kKnTp1gZ2eHw4cPy1fiBwYG4rfffkNgYCCcnJywatUqiMVi9OvXD8OHD1daYVeH8oHCPATF8wtMmTJFYV4dAPbv34/Q0FB88803JY4zYcIE5OTkoFOnTvKGx9ChQ6Gvr4927dqVOnf8Icr38PBAmzZt0LFjxxLPS05OxvTp07Fu3Tq4ublh5MiRyM3NxeLFi2Fubo7Y2FiEhoZCX18fGzZskD+nZ8+eCAkJkf0GXsmjEQpERUXB09MTvXr1wvLly9G5c2fcLtZAbd26NYbJrl5z5syBlZWVwv1HjhzB69evcevWLbRo0QJ//fUXxo0bh/T0dAQHByM4OBg3btzA2LFjcfbsWaSmpqJ9+/awsbFBt27d0KRJE3h6esLOzg5du3aFq6urQkRJVZcPANoqKphUty4OPHmChOxshfv2JCZilIVFpV7fVLRVUHdSXTw58ATZCYrlJ+5JhMUoi0q/xlpbz0BWVjSePj1acgQibissLSd98Ou+simjZs2aQU9PD9HR0dDS0lJYj1b0OW+702hVxuG/sePZqTA8cPVqYZV/YCDQtq0w1bB1K1AQUDVrlhAyWNxHHwFhYcJzStSrNWko0shIF5curcRPP/2N/fsvokWL+VBXV4WdnSns7Ezh4/MxWrd2qrTydY2MsPLSJfz900+4uH8/5rdoAVV1dZja2cHUzg4f+/jAqXXrch/3woULuHDhwlv3Sv39/d8qm9mCBQuwYMGCal/+H3/8ge2yUZV169ZBR0cHH30k7C+enp6OMWPGwNfXFw4ODsjIyICpqSlOnz4tXxVcfIjw448/xueff16kd6ONUaNGYeTIkVVa/oABA7Bnzx7ExMRAKpUq9EQ3b96Mtm3bYvDgwZgyZQrWr18PNTU1LFq0CH5+flBXV4e7uztGjRolb4zUrl0bHTp0QGvZObdv3z788ssvWLx4MUxkE4y2trb46KOPYGtrixkzZmDp0qWYPXs2Tp48KS87JCQEnTt3LvX7iYuLQ4Mi3ZBt27Yp3F98WqNoNEjxz6iTkm5PVZcvb+xZWWF9dDS+j43FatnEqxTAwaQknGzaFMvfYfFseVhNsUL0+mjEfh8Lh9WyiV8pkHQwCU1PNsWj5ZVbvrn5CERGLkBMzDcwMxtcpLLKxbNngWjR4gLu3Bn/Qa/5GRkZSE9PLzFa1LZtW5w8ebJE7z8zM1Ne8aenp5fa4C+qIA7fwQFo0aLk/cXj8Bs1Eob8L10qjMN/8kQI6xsyRJi7VxxdAYoPghbE4Zeme3egY0dhpGH9ekBHR4gQcHMDnj8XRibGjxeOUZCa5vhx4fbirl4to2ONGkZFRYwJEzpjwoTOVVK+WEUFnSdMQOcJE0AVo0ePHkrD8ApGFspLWSjY999/Xy3K79atG2xtbUsMQzdt2hTTp0+HtrY2evbsidGjRwMQFh/2798fBw4ckN+/d+9ezJ07F+Hh4WgmW5yan5+PFy9eYPjw4di6dSsWLVqk9LW9fv0aderU4UmnRB0NDQw1N8fW+HgstrODjooK/kxJQUdDQ6h/gIXOGnU0YD7UHPFb42G32A4qOipI+TMFhh0NIVav/PLFYk3UrTsJjx+vRGpqCPT1hYZlUtJh1K7dHyLRh6susrOzcfXqVVy9ehXPnj3D8ePH4eTkhPqyPCzu7u64d++ePL8GAISFhSmMbh0+fBgNGzZEq1atlE47icX5aNpUWHxXWhy+kxPg6QksX64Yh3/sGLBpk7Bob/584XipqcAXXwgNg4I4/Hv3hJ73vHmFcfiursKCPNmgq1KnTgFFgowACK9j6FChEVBG0NJbTQnU2AYAFR0RMYKvry+cnJwwRFkKqMrsrVhZwc/PD+3atUNiYiJWrFhRruRC/yXDhg1DSkoKpk2bJp8O2L17N/z9/eUbnPTv3x8SiQSTJ09GvXr1sHXrVvnzR48ejVmzZsHHxwfm5uaQSCQIDw/H33//jenTp8t6JifQp08faGtro2PHjpg3b57CfPrt27exc+dO1KpVC0uXLuWXUoqZ1tbYm5iInxISMMXKClvj4uD/LpOw78h6pjUS9yYi4acEWE2xQtzWODTwb/ABf9efIzr6a0RHf4PGjQ8DAOLjt6Nx4yMf9HvQ0NBAmzZtSo3t19DQKBFO26pVK7Rq1eqty8jPFytUwocPC/8AIQ6/wNGjBaNJhbfJ8n2haM6pgjj8ovcDQix+8ecXlPO2dHSA/fuFXr9EUtjrf8tZjtIbffzJ10yqqqro3Lkz+vbt+1bDXBVJJBJhx44duHDhAnx8fJCcnIw9e/age/fulVZmSkoKvLy8MGnSJIwYMQIuLi4KvforV67Ay8sLzZo1Q2pqKoYNGwY9PT3Ur1//jRkKlV8c8rFq1SoMHToU3t7eaNCgASZPnoxs2fxwTEwMvvjiC1haWiI2NhZffvklateuDUtLSyxevFghOiAyMhI3b97Er7/+iitXruDOnTsICgrCvSIhpbGxsRg0aBDu3buHtm3bomvXrvJkJ56enkhJScHGjRvRs2dPjBo1Sp6IqyAENygoCP/73/9w7tw5GBkZ4cgRxQt2w4YNMW7cOCxduvSDny81SXM9PbQzNMSm2Fjcev0apurqMClj7UpF02uuB8N2hojdFIvXt15D3VQdaiYfrnx1dXOYmQ1FcnIAMjOjkJoaAh0dZ6ipGf6//c7r1hWGyWfNEirWWbOA1q2FXnpqKjByJLBjBzB2bMnn/vCDkKWvsFMmZOkbMwYICRGG8ps2BV6+FI7drx/w449vGolRPCYgLEisXVvYyrdOHeExurpAWlrhav8mTUpONbyxHuFPvmbKy8vD4cOH0aVLF9jY2HzQsps0aYLVq1fj77//BiAkvLl//z6GDBmCU6dOVUqZo0aNQmZmprzMefPmYdq0aejSpQvMzMwQHR2NI0eOwMDAAHPmzMHHH3+M9u3bY/HixRg2bBg0NTXR7w37OBS1fv16LF++HKmpqdDQ0MDJkyfRo0cPNG7cGN7e3vj3338RFBSE+Ph4fP3117CyssL333+PtWvX4quvvsLr16/l+wJcuXJFftyvvvoKtra2WLhwoUJ5v/76Kz777DMYGBhgxYoV2LNnD7KysqCtrS3fTyAwMBBz587FyJEj4ejoKN8Y5fr16+jZs6d8GsPc3BzLly9/rzz6tra2GD9+PBYvXozjx48jUhZUrKWlheHDh8Pa2rpc+0kAwmLTxYsXw8/PD8ePH/+g5bdv3x7ff/897OzscOnSJXh7e+Px48dKH+trbY1+//6LwTdv4khBl+4Dsva1xr/9/sXNwTfR+EgVlG89E4mJexAb+x2ysxNRr17ljhjdvHkTZ86cQVJSEuzs7KChoYHnz5+jQYMG6NKlS4nIkGvXrkFNTU1p5tmix7KwsICJiQkkEglSU1NhaWmJDh06wNBQsTETHw88fgycPQv873+yhpieULm+eCEssvvnH+Dff4GiM4L16wMWFkD//kJYHyBMG+TkALt2CYv1mjYV1hi8fClMGwBAcHDpFf/AgULe/kGDhLDB5OSC9yzc/uefwqhDkyaAlRVw7pywODA0FNi8WRjq9/AQQhM1NIBu3YT35uAg/P+lS4pRBlXeAHj1KhN79pzDihW/IikpFYMGuWP9+lGwsamNW7diMXnydjx9moqlSwejXbv6WLLkIH766W+YmxvA338SevUSFmslJr7A9Ok/488/w/HVV8Pg5dUZK1cexfHjV9CqlaN86+BHj5IQFHQDCxb0x6pVwsrjm8HB+H7kSDTp1g3qmpoAgJzMTJzdvRvOHh5YEhSEPzZtwsEvvoAkNxfjt2xBx88+g7qWFvJycnB87VocWroUPWfORNdJk3AjKAi/rliB1KQkuA8ahFHr16O2jQ1ib93C9smTkfr0KQYvXQqP8sSNlELZxhiV7c6dOwqr5dPT0xEWFibvHVeGly9fwsPDo7CnJtuZ8PHjx6hfvz4GDRqEb775Bvfu3cPKlSvlaYvr1KmDvn37YtWqVeVqALx8+RKurq7y8MiC8gqyGPbu3RshISEIDQ1Fv3795IvYOnToAHt7e/j5+WHp0qUKF5u4uDisXr0atWrVwqBBgxTylqekpMDd3R3Dhw9HdnY2li9frrCd6ejRo+XhlZaWlpg4cSKaNWuGxMREzJgxAytXrpQ/1sTEBCEhIVi3bh0GDBiA69evIzY2Fp9++qn8GG8SFRWFTZs2YfHixfj5559xrODqBSH8Sk9Pr1wVsKGhIVRUVNCuXTv8+KYuUAWXb2hoiM8//xxeXl7Q1tbGjz/+iICAADRt2hQAIJFKkVEkyqO3iQnstbRgo6mJBkWyy+VIpciWXT1f5OZia3w8ljx8iGZ6ejjSuDGsNDXxQ1wc1kZFYYuLCwxUVTH7wQOEpabCz8UF3paWiM7KwuAbN+Cmr4/FdnYA1CGVSCHJKCzfpLcJtOy1oGmjCZ0GheVLc6TIzxbKz47Lxp0Jd5DyZwqcNjrBerqQjTXlZApuDL4B503OEGmIcNfrLnQa6KDxocbQstdC7vNc3BopLBV32ewCZR1GPb1mMDRsh/h4fxgZdYSOjkupn+3r1zdw69YImJj0lK8RePJkPwAR3N1vIDMzssz7ASG9fFJSEpKSkjB+/Hioqqri8ePH2LZtG16+fIlPP/1UocxLly5BQ0NDaQPA1dUVycnJOH36NHx8fOS/sbS0NBw8eBDffvstxo0bB1tb2xLPbd1aGA1o3bpwXr+AgwMg289L4bbx44U4/YIGwMmTQv6A+vWF9QB//SXcrqIijAaYmAg9d2U/gYI8AMqmB549E9YjFCi6pEm2XhlAYUSAMFJb+P+lbTvyzg2AormYJe+RFatWLS18/nk3dO3aGC1bCp+6jY2QJ93e3gwGBtoICJgt3wNg504fJCe/wsWLEfD0LNyYx8LCEI6O5vDymoWuXYVWs76+Nq5cWQ0NDTVZZSlB69aL0LSpLZYtK1zl+jolBcvPn4d5kZRLP02bBk1dXUzZvRvqWlroN38+VFRVsWfOHFi7ukJdNtaiqq4OBzc3DFi0CENlm79YODmhcdeumC9LvVRb1kM3s7eHtoEBZgcEVNmeAhVB2VbAFhYWZS60e18XL16ESCTCixcvsGfPHvlIQ9HXIhaLYWhoqLBnQZ8+fWBtbY2rV6+WK2nMqlWr8NVXXyE3NxcBAQE4I4vFKV4eADg7O8tvMzc3x6BBg7B7926Eh4crhPwZGxsjJycH6urqJTYtWblypUIlXpyDgwMcipyfmzZtkn/uZ2UbVRVo0aKFQghU8fvLM8qkzPHjx986xKrAixcvcPbsWTx58uSDl+/k5IQJEybIt6mePHkyzpw5AxMTE9zLyMDO+HiEpqZiR0ICBpqawkBVFdOtreEoa4DFZWfjwJMniM3KQoZEgp8TEjDYzAzzbW2hIhLh+9hY1JZ9n68lEvzRrBkayhoOp5o1Q6OQEEhkr1dHRQWeBgbYILuaZ9zLQPzOeKSGpiJhRwJMB5pC1UAV1tOtoe2oLa/snxx4gqzYLEgyJEj4OQFmg83QaH8jhDiHQM24cIpA3UIdDmscUGe8sNAzKzoLibsToWkrdGzUjNSg7aANhzUOUNFWKfKbVkzzbWU1AzduDIClZWE0i1Saj/z8LEgkGUU6IClo1uwUNDTqyhrOFxEVtRbNmwdDRUX7jffLK6JivXw7OztYW1vj33//xcCBA+UhxHFxcdDS0sKDBw+QnJysdE8NZbkk9PT0MGbMGGzatAn79u3D3LlzS4Qlh4QIIwAvXhTepqYmZO4bMkTYfKeAqakQ9qeiIvT43dyEREIpKUIkgY+PkAhowgShUSCRCAv7AKBdu7LPVxsbYM0aIbSwINiqdm0hm6CyaQhl7O2FY2zfLowalDrd8K4X5NjYwmQ7CQnvn57XyckCfn5e+PXXUBw/LgyZzpy5CytXflpiA6Aff/RCfr4UCxYUpkh6/Pgp0tOz5ZU/APTq1Vxe+QPAsmWHcOtWLPbunSrfWwAArBs3Vqj8/z19Gqc2b8bYjRthVq9e4fF8feHg5oadU6ZAIut5S/Ly8M/PP2PgkiWKFaKTE7z8/BD666+4Ihvu3DVzJj5dubJGV/7KuLi4IDExUT48XxmysrIwd+5czJo1C126dClXPn0HBwfk5+eXe7Rkx44dGDhwIIyMjLB27dpylQegxIiIlpYWGjZsWCO3LC3QqFEjuLm5ITc3F82bN8f+/fuxbds2+Pn5IT4+HhMmTMDZs2cxbdo0XLx4sUT66Pfdnvddyg8LC5NX/gWjOKmpqUhNTYWztjbWOjriVceOGF+nDgxklcdUKyt0l/1OLTU0MNvGBtIuXfCsfXuMLZIJ0NfaGsZqalgbFYVraWnQFovllT8AGKiqYpOzM5Y+eoTnublY+fgxvihyTdF21objWkd0fNURdcbXgaqBUL7VVCsYdxfK17DUgM1sG3SRdkH7Z+1RZ6yQCVDNUA32K+3xcNFD5GcJn2vinkRYehd292xm2UCaK0X81ngAQGpYKvRb68sr/4yMB3j8eBXS02/j4cMvkJ5+R1bh9IWJSU8YG38s7+lHRs6FVCrBy5fnER+/DTk5SdDTay6v3PPzM3HnzmewsvochobtZBVv2fe/iaqqqkKjPTw8HCNHjoSJiYnCXhxvQ01NDZ6enkhLS1NI813cuXPCSIDQwBEq4eRkxUV8Hh7CkPuxY0Kq4Jkzhdu7dRP++913QhSAsrXZRY+vTHS00GiIjRVSDK9cCUyfDvzxR3ka74C1teIoQIWMANy8eRMBAQEKO5yNGTMGY8eORf/+/d9rR8Dhw9siIOAyfHy249atWHh4OKNx45Lz23XrGuHrr0fC29sfw4Z5wNOzPpYtO4yNG8cWq5jqFulB3sPatcfx9dcj0bChYqKRui6FQ1yvnz/HD599hua9eqHTeMWYV5FYDJ+dOzGveXMcW7sWAxcvRuD69ej2+efyzYIU5jyHD8flgABs9/FB7K1bcPbwgE0VzClWJpFIhFmzZsHLy6vSysjNzUXHjh3RoEED7JQF2d4vR7plkUgEc3NzaMqmd96Gr68vTp06hWvXrkFTUxMvX74sV3kFvRhlvdGioUs1wahRo+Du7g51dXUMHjxYnrTn1q1bEIlE8PT0xMCBA3H9+nUcPXoUS5cuRYcOHfDZZ5/J8ylUp/Lbtm2LzZs3fflw8wAADm1JREFUV8j0mYpIhC0uLuh67Rpis7KwTcl24QNNTbEtPh6drl3DOkdH6KtW3MxrnQl1EOcXh+j10ajlVgtGnYwgUi286os1xXBc74i7k+7CbJgZkvYnwenbwrFkbW1H2NkthJ3dwmLnsBhNmxYucdfVbQxHx/VwdFxf6muJjFwIqTQf9varilTg+mXeX/qxIhETEwMPDw/5SFt6ejp0dHSgoaGB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