Fundamentals_of_Quantum_Computing_with_Qiskit.ipynb

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    {
      "cell_type": "markdown",
      "source": [
        "# Fundamentals Quantum Computation using Qiskit"
      ],
      "metadata": {
        "id": "k_u9cfWBGWQq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Day 1: Introduction to Quantum Circuits with Qiskit"
      ],
      "metadata": {
        "id": "cDFLjU0yGgmb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Introduction"
      ],
      "metadata": {
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    },
    {
      "cell_type": "markdown",
      "source": [
        "Hey everyone, and welcome to this tutorial on quantum circuits with Qiskit! In this tutorial, you will learn how to construct multi-qubit quantum registers, measure quantum circuits in classical registers, use single-qubit and multi-qubit gates, use barrier operations, return the circuit depth, extend quantum circuits, and return the OpenQASM string for a circuit.\n",
        "\n",
        "Qiskit is an open-source software development kit for quantum computing. It provides a high-level Python interface for constructing and running quantum circuits on a variety of backends, including real quantum devices.\n",
        "\n",
        "Quantum circuits are a way of representing quantum programs. They are made up of a series of gates that operate on quantum registers. Quantum registers are collections of qubits, which are the basic units of information in quantum computing.\n",
        "\n",
        "In this tutorial, you will learn how to use Qiskit to construct and run simple quantum circuits. You will also learn about some of the key concepts in quantum computing, such as superposition, entanglement, and measurement.\n",
        "\n",
        "If you are interested in learning more about quantum computing, I encourage you to watch this tutorial!"
      ],
      "metadata": {
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    },
    {
      "cell_type": "markdown",
      "source": [
        "Keywords:\n",
        "\n",
        "quantum computing,\n",
        "Qiskit,\n",
        "quantum circuits,\n",
        "multi-qubit registers,\n",
        "classical registers,\n",
        "single-qubit gates,\n",
        "multi-qubit gates,\n",
        "barrier operations,\n",
        "circuit depth,\n",
        "OpenQASM,"
      ],
      "metadata": {
        "id": "q37lco0FIBoX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "rqhoBcJoGXmx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Topics to be covered:\n"
      ],
      "metadata": {
        "id": "OEETDHuHHRnp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "- Construct multi-qubit quantum registers\n",
        "- Measure quantum circuits in classical registers\n",
        "- Use single-qubit gates\n",
        "- Use multi-qubit gates\n",
        "- Use barrier operations\n",
        "- Return the circuit depth\n",
        "- Extend quantum circuits\n",
        "- Return the OpenQASM string for a circuit\n",
        "with qiskit examples"
      ],
      "metadata": {
        "id": "k0A-UP_NHicY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 1. Construct multi-qubit quantum registers"
      ],
      "metadata": {
        "id": "mYRGg0h7IkZ2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Import all necessary modules from qiskit"
      ],
      "metadata": {
        "id": "C1Z3VR_eIypw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Install qiskit framework, if you are not installed yet\n",
        "# !pip install qiskit"
      ],
      "metadata": {
        "id": "PorR2qsXJGHj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister"
      ],
      "metadata": {
        "id": "1Nry4d6HLV1R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "To construct a multi-qubit quantum register, you can use the QuantumRegister class. For example, to create a quantum register with 2 qubits, you would do the following:"
      ],
      "metadata": {
        "id": "uMfw7w0OQdrP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "qr = QuantumRegister(2, 'qr')"
      ],
      "metadata": {
        "id": "V0YrmRyCLuiJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:\n",
        "\n"
      ],
      "metadata": {
        "id": "Pgrcp0HJXIuX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "`QuantumRegister(3, 'qr')` creates a quantum register named 'qr' with three qubits. This register serves as a container for the qubits in a quantum circuit, enabling the implementation of quantum operations and computations on the qubits within the circuit."
      ],
      "metadata": {
        "id": "LoyRSjkGXMhm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 2. Measure quantum circuits in classical registers"
      ],
      "metadata": {
        "id": "paGOztBvMYgb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cr = ClassicalRegister(2, 'c')"
      ],
      "metadata": {
        "id": "-sNk5jrCV4f7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "iC-7xSHaV2_0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In the code`cr = ClassicalRegister(2, 'c')`, a classical register with two bits is being created. This classical register is used to store and hold the measurement results obtained from the quantum circuit's qubits. In this case, the classical register has two bits, which means it can store the measurement results of two qubits.\n",
        "\n",
        "\n",
        "`2:` This parameter specifies the number of bits in the classical register. In this case, it's set to 2, meaning the classical register can hold the measurement results of two qubits.\n",
        "\n",
        "`'c':` This parameter represents the name of the classical register, which can be used to identify the register within the context of the quantum circuit. In this case, the name is set to 'c'.\n",
        "\n",
        "Once the classical register is created, it can be associated with the quantum circuit for measuring the qubits. The measure method is used to associate specific qubits with specific bits in the classical register, allowing the measurement results of the qubits to be stored in the classical bits for further analysis and processing."
      ],
      "metadata": {
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    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Step 3: Create a Quantum Circuit"
      ],
      "metadata": {
        "id": "8SBzJt9NYD_w"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "circuit = QuantumCircuit(qr, cr)"
      ],
      "metadata": {
        "id": "URNHNQASYIL2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "DgsfSVGVgel3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this code, `circuit = QuantumCircuit(qr, cr)`, a quantum circuit is being created. The `QuantumCircuit` function is used to create a new quantum circuit and is provided with a quantum register `(qr)` and a classical register `(cr)` as arguments. This quantum circuit will operate on the qubits from the quantum register and store the measurement results in the classical register. It serves as the canvas for applying quantum gates and executing quantum algorithms."
      ],
      "metadata": {
        "id": "nlMZYdjIZXmk"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 4: Use Single Qubits"
      ],
      "metadata": {
        "id": "sJjCz0pZXq1W"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "circuit.h(qr[0]) # Hamadard Gate(H-gate)\n",
        "circuit.x(qr[1]) # Pauli-X Gate(X-gate) - superposition"
      ],
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<qiskit.circuit.instructionset.InstructionSet at 0x7880973ef940>"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Code explanation:"
      ],
      "metadata": {
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    },
    {
      "cell_type": "markdown",
      "source": [
        "`circuit.h(qr[0])` applies a Hadamard gate (H-gate) to the qubit stored in the first index of the quantum register qr. The Hadamard gate is commonly used in quantum computing to create superposition, an essential concept in quantum algorithms.\n",
        "\n",
        "`circuit.x(qr[1])` applies a Pauli-X gate (X-gate) to the qubit stored in the second index of the quantum register `qr`. The Pauli-X gate is a fundamental single-qubit gate that corresponds to a classical bit-flip operation and is often used for simple quantum manipulations and demonstrations."
      ],
      "metadata": {
        "id": "g4YYlgfke8AW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 5: Use multi-qubit gates"
      ],
      "metadata": {
        "id": "T12uLkCaZtlR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "circuit.cx(qr[0], qr[1]) # CNOT Gate -entalgement"
      ],
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<qiskit.circuit.instructionset.InstructionSet at 0x7880973eee00>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
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      "cell_type": "markdown",
      "source": [
        "`circuit.cx(qr[0], qr[1])` applies a `controlled-NOT (CNOT)` gate to the qubits stored in the quantum register qr. The CNOT gate is a fundamental two-qubit gate in quantum computing that performs an operation on a target qubit based on the state of a control qubit. In this case, the qubit at index 0 is used as the control qubit, while the qubit at index 1 is the target qubit. The application of the CNOT gate can create entanglement between the qubits and is essential in building various quantum circuits and algorithms, including quantum error correction and quantum teleportation."
      ],
      "metadata": {
        "id": "tA2lTbtieXtW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 6: Use barrier operations"
      ],
      "metadata": {
        "id": "tk6c3OBVZ-ya"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "circuit.barrier()"
      ],
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          "base_uri": "https://localhost:8080/"
        },
        "id": "4eSaZ-1qaFnE",
        "outputId": "41152bbe-5bf0-4f5f-c719-c0da05b765c1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<qiskit.circuit.instructionset.InstructionSet at 0x78805d462da0>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "oLZg4OtGdQfW"
      }
    },
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      "cell_type": "markdown",
      "source": [
        "`circuit.barrier()` is a command that inserts a barrier in the quantum circuit. It's a visual aid and does not affect the quantum computation itself. The barrier separates the operations before and after it, helping to organize and visualize different stages of the quantum algorithm or circui"
      ],
      "metadata": {
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    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 7:Measure the qubits"
      ],
      "metadata": {
        "id": "G53H0DSDgJjJ"
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    {
      "cell_type": "code",
      "source": [
        "circuit.measure(qr, cr)"
      ],
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<qiskit.circuit.instructionset.InstructionSet at 0x7880973eec80>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "oS7YVt8wiNzX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The `circuit.measure(qr, cr)` method in **Qiskit** associates the qubits in the quantum register **qr** with the classical bits in the classical register **cr** for measurement. This operation measures the qubits and stores the measurement results in the classical bits.\n",
        "\n",
        "The measurement results represent the state of the qubits after the quantum computation, and they are crucial for retrieving classical information from the quantum computation."
      ],
      "metadata": {
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      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 8: Return the circuit depth"
      ],
      "metadata": {
        "id": "LUXnl9mcataZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(f'Circuit depth:{circuit.depth()}')"
      ],
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        },
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        "outputId": "3a746bcb-3985-48d0-d9ce-836ec96af60b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Circuit depth:4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
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    {
      "cell_type": "markdown",
      "source": [
        "`circuit.depth()` in **Qiskit** returns an integer representing the depth of the quantum circuit, indicating the length of the critical path, or the longest sequence of quantum operations in the circuit."
      ],
      "metadata": {
        "id": "rYWRe40ufZhC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 9: Extend quantum circuits"
      ],
      "metadata": {
        "id": "KjNcdcDqa6j0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "qr2 = QuantumRegister(1, 'q2')"
      ],
      "metadata": {
        "id": "nV84Dq5YbD6j"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "circuit.add_register(qr2)"
      ],
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        "id": "bF7BCZgrGido"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "circuit.h(qr2[0])"
      ],
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<qiskit.circuit.instructionset.InstructionSet at 0x78805d460d90>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "NQRKnzo7doVD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "`qr2 = QuantumRegister(1, 'q2')` creates a new quantum register named `'q2'` that contains one qubit.\n",
        "\n",
        "`circuit.add_register(qr2)` adds the newly created quantum register `'qr2'` to the existing quantum circuit, enabling the use of the qubit in the quantum operations of the circuit.\n",
        "\n",
        "`circuit.h(qr2[0])` applies the Hadamard gate (**H-gate**) to the qubit stored in the quantum register 'qr2'. The Hadamard gate is a single-qubit quantum gate that creates superposition, a key concept in quantum computing, and is often used as the initial step in various quantum algorithms."
      ],
      "metadata": {
        "id": "sdD8gwiNdqUn"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 10: Return the OpenQASM string for a circuit"
      ],
      "metadata": {
        "id": "ijJpPipcbKVU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(circuit.qasm())"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rkyxyRWybQB9",
        "outputId": "595a4cb4-09d4-4c3e-ce62-cd1bfdc560c5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "OPENQASM 2.0;\n",
            "include \"qelib1.inc\";\n",
            "qreg qr[2];\n",
            "qreg q2[1];\n",
            "creg c[2];\n",
            "h qr[0];\n",
            "x qr[1];\n",
            "cx qr[0],qr[1];\n",
            "cx qr[0],qr[1];\n",
            "barrier qr[0],qr[1];\n",
            "measure qr[0] -> c[0];\n",
            "measure qr[1] -> c[1];\n",
            "h q2[0];\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "b1aSQfjDftQP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "the` circuit.qasm()` method returns the **OpenQASM** (Open Quantum Assembly Language) representation of the constructed quantum circuit. This **OpenQASM** representation provides a human-readable form of the quantum circuit's operations, allowing users to inspect the underlying quantum operations and structure of the circuit."
      ],
      "metadata": {
        "id": "GHMUY6B8fvUG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Conclusion"
      ],
      "metadata": {
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      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "Your feedback matters! If you found this tutorial helpful, please like, share, and subscribe. Leave your questions in the comments below. Stay tuned for more quantum computing and AI tutorials by subscribing to my channel. Thank you for watching!"
      ],
      "metadata": {
        "id": "VhU42O2GIiFt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "lqoX5d4AHrds"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "NNw6_SsF3Cn2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Day 2: Executing Quantum Circuits with Qiskit"
      ],
      "metadata": {
        "id": "u45IYF_nJk5f"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Introduction"
      ],
      "metadata": {
        "id": "1Dtnz5e4JtU_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Hey everyone, and welcome to this tutorial on Fundamentals of Quantum Computing with Qiskit. In this tutorial, you will learn how to execute quantum circuit with Qiskit in Python.\n",
        "\n",
        "`Quantum computing` represents a revolutionary paradigm with the potential to solve complex problems that are intractable for classical computers. One of the primary platforms for quantum computing development and simulation is Qiskit, an open-source quantum computing software development framework from IBM. With its powerful features, Qiskit enables users to create, manipulate, and execute quantum circuits on simulators or real quantum devices.\n",
        "\n",
        "Your feedback matters! If you found this tutorial helpful, please like, share, and subscribe for more Quantum Computing and AI topics. Leave your questions in the comments below."
      ],
      "metadata": {
        "id": "WAnw7mYWJxyf"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## By the end of this tutorial, you will be able to:"
      ],
      "metadata": {
        "id": "aluRwlv0K04z"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "- Understand Quantum Circuit Execution\n",
        "\n",
        "- Build a Simple Quantum Circuit\n",
        "\n",
        "- Choose the Right Backend simulator\n",
        "\n",
        "\n",
        "- Execute the Quantum Circuit\n",
        "\n",
        "- Analyze the Results\n"
      ],
      "metadata": {
        "id": "gtB3LIbRK32g"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Example:"
      ],
      "metadata": {
        "id": "8nnWI4UJRHmA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Install qiskit-aer, if you are not already installed"
      ],
      "metadata": {
        "id": "dn3jDUF5RUDm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#!pip install qiskit-aer"
      ],
      "metadata": {
        "id": "qkY4oL5RRbnC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Import the module classes"
      ],
      "metadata": {
        "id": "T-7D0fvVRhdh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit import Aer, execute, QuantumCircuit"
      ],
      "metadata": {
        "id": "9qERWr4LRkRH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Create and execute simple quantum circuit"
      ],
      "metadata": {
        "id": "4EsbADcPUBcJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# create a simple quantum circuit\n",
        "qc = QuantumCircuit(2, 2)\n",
        "qc.h(0) # hadamard gate (H-GATE)\n",
        "qc.cx(0, 1) # controlled NOT (CNOT-gate)\n",
        "qc.measure([0, 1], [0, 1])\n",
        "\n",
        "# Choose the Aer simulator backend\n",
        "simulator = Aer.get_backend('qasm_simulator')\n",
        "\n",
        "# Execute the circuit on the simulator\n",
        "job = execute(qc, simulator, shots=1024)\n",
        "# Get the result counts\n",
        "result =  job.result().get_counts(qc)\n",
        "print(result)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t-j7ooG1RssV",
        "outputId": "2ef28026-ce49-476f-eb25-06f78492bd02"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'00': 506, '11': 518}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "S3oK-b0VR7Cc"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this example:\n",
        "\n",
        "I created a simple quantum circuit that includes a **Hadamard gate (h)**, a **controlled-NOT gate (cx)**, and a measurement operation (**measure**).\n",
        "\n",
        "I choose the **QASM** simulator as the backend for simulation using `Aer.get_backend('qasm_simulator')`.\n",
        "\n",
        "I then execute the quantum circuit on the chosen simulator using the `execute` function.\n",
        "\n",
        "The `shots` parameter specifies the number of times the circuit is executed to collect statistics.\n",
        "\n",
        "I retrieved the result **counts** using the `get_counts` method and print the results."
      ],
      "metadata": {
        "id": "ykCWAEuRR9g5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Output:**\n",
        "\n",
        "The keys, `'00'` and `'11'`, represent the possible measurement outcomes. In quantum computing,` '00'` can signify that both qubits were measured as the state `|0>`, and `'11'` can represent that both qubits were measured as the state `|1>`.\n",
        "\n",
        "The values, `503` and `521`, indicate the frequency or count of each measurement outcome. Therefore, `'00'` was observed `503` times, and `'11'` was observed `521` times during the execution of the quantum circuit"
      ],
      "metadata": {
        "id": "IOLR1dYrTqlK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Conclusion:"
      ],
      "metadata": {
        "id": "btHp7AheLLmP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "By leveraging the capabilities of **Qiskit**, you can gain valuable insights into the principles of quantum computing through the execution of quantum circuits. This practical engagement serves as an essential starting point for comprehending the potential of quantum computing and its applications in various fields such as optimization, cryptography, machine learning, and AI.\n",
        "\n",
        "\n",
        "Your feedback is invaluable! If you found this tutorial helpful, please like, share, and subscribe. Leave your questions in the comments below. Stay tuned for more quantum computing and AI tutorials by subscribing to my channel. Thank you for watching!"
      ],
      "metadata": {
        "id": "AS5pDT3MLNaJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "-OFjdkJxB3Vm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Construct Visualizations"
      ],
      "metadata": {
        "id": "BPLFQEcCKBcM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Introduction"
      ],
      "metadata": {
        "id": "EVWyMVD5aTnZ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Hello everyone, welcome to this tutorial on Fundamentals of Quantum Computing with Qiskit.\n",
        "\n",
        "This tutorial provides a practical guide to implementing visualizations of various quantum concepts using the Qiskit framework. The tutorial covers the creation of quantum circuits, drawing a qauntum circuit, plotting histograms of quantum data, visualizing states on the Bloch sphere, and representing density matrices using Qiskit's visualization tools.\n",
        "\n",
        "If you are interested learning about Quantum Computing Programming, I encourage to watch this tutorial!"
      ],
      "metadata": {
        "id": "u-RGcVmbaVmv"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Drawing a quantum circuit"
      ],
      "metadata": {
        "id": "wmhrU47qeEDV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Install the qiskit framework"
      ],
      "metadata": {
        "id": "3gX-EJ9rbKIt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#!pip install qiskit-aer"
      ],
      "metadata": {
        "id": "sEZfHIH6bOL-"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Import the classess from qiskit module"
      ],
      "metadata": {
        "id": "knRumkyvbhV0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit import QuantumCircuit\n",
        "from qiskit.visualization import circuit_visualization"
      ],
      "metadata": {
        "id": "ZhzQYreublb6"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Create a quantum circuit"
      ],
      "metadata": {
        "id": "IrQKENqgbyoc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a quantum circuit\n",
        "qc = QuantumCircuit(2, 2)\n",
        "qc.h(0)\n",
        "qc.cx(0, 1)\n",
        "qc.measure([0, 1], [0, 1])"
      ],
      "metadata": {
        "id": "hgZIG9PLb2xI"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Now draw the circuit"
      ],
      "metadata": {
        "id": "8_sDxyVyB4te"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Draw the quantum circuit\n",
        "print(qc.draw())\n",
        "\n",
        "# You can also use qiskit's visualization tools for more advanced drawings\n",
        "circuit_visualization.circuit_drawer(qc)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "id": "v9r_6tVrB7N6",
        "outputId": "90d7efc6-c2a1-4b6c-bd09-a0aaee2c10d2"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "     ┌───┐     ┌─┐   \n",
            "q_0: ┤ H ├──■──┤M├───\n",
            "     └───┘┌─┴─┐└╥┘┌─┐\n",
            "q_1: ─────┤ X ├─╫─┤M├\n",
            "          └───┘ ║ └╥┘\n",
            "c: 2/═══════════╩══╩═\n",
            "                0  1 \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     ┌───┐     ┌─┐   \n",
              "q_0: ┤ H ├──■──┤M├───\n",
              "     └───┘┌─┴─┐└╥┘┌─┐\n",
              "q_1: ─────┤ X ├─╫─┤M├\n",
              "          └───┘ ║ └╥┘\n",
              "c: 2/═══════════╩══╩═\n",
              "                0  1 "
            ],
            "text/html": [
              "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">     ┌───┐     ┌─┐   \n",
              "q_0: ┤ H ├──■──┤M├───\n",
              "     └───┘┌─┴─┐└╥┘┌─┐\n",
              "q_1: ─────┤ X ├─╫─┤M├\n",
              "          └───┘ ║ └╥┘\n",
              "c: 2/═══════════╩══╩═\n",
              "                0  1 </pre>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Code explanation:"
      ],
      "metadata": {
        "id": "rnJYh5HTgFYd"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "This code demonstrates how to create and draw a simple quantum circuit using Qiskit. It includes a **Hadamard gate (H gate)** and **a controlled-NOT gate (CX gate)** on two qubits, followed by measurement operations.\n",
        "\n",
        "**Output:**\n",
        "\n",
        "The symbol **\"┤ H ├──■──┤M├───\"** indicates the sequence of operations performed in the quantum circuit:\n",
        "\n",
        "- **\"┤ H ─\"** represents the Hadamard gate (H gate) operation applied to the qubit labeled q_0.\n",
        "\n",
        "- **\"─■──\"** indicates that there is a controlled gate operation, specifically a controlled-NOT gate (CX gate), where q_0 is the control qubit and q_1 is the target qubit.\n",
        "\n",
        "- **\"┤M├\"** denotes the measurement operation performed on both qubits in the circuit.\n",
        "\n",
        "The lines and symbols beneath the operation sequence represent the circuit layout and the qubit connections:\n",
        "\n",
        "- **\"└───┘\"** represents the connection between the qubits q_0 and q_1 in the circuit.\n",
        "- **\"┌─┴─┐\" and \"└╥┘┌─┐\"** represent the structure of the controlled-NOT gate and the measurement operation.\n",
        "\n",
        "The qubit labels are represented as \"q_1\" for the first qubit.\n",
        "The classical bit labels are represented as **\"c: 2\"** for the two classical bits used for measurement outcomes.\n",
        "The lines beneath the classical bits represent the classical bits' connection and the measurement output sequence.\n",
        "\n",
        "\n",
        "In summary, the output visually represents a quantum circuit with specific gate operations, qubit connections, and classical bit labels, providing a clear depiction of the operations performed within the circuit."
      ],
      "metadata": {
        "id": "1N0fpdaQfMFP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Plotting a Histogram of Data"
      ],
      "metadata": {
        "id": "Xc1B-NOicVTN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit import Aer, execute\n",
        "\n",
        "# Simulate the circuit\n",
        "simulator = Aer.get_backend('aer_simulator')\n",
        "result = execute(qc, simulator).result()\n",
        "\n",
        "# Plot the histogram\n",
        "from qiskit.visualization import plot_histogram\n",
        "counts = result.get_counts(qc)\n",
        "plot_histogram(counts)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "SMCMMuIICoPH",
        "outputId": "2dcbb8f8-093c-40fc-df1f-80cd811060fe"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Code explanation:"
      ],
      "metadata": {
        "id": "aBiApAnHGbro"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this code, the quantum circuit is simulated using` Qiskit's Aer simulator`. Then extracts the measurement results and plots the histogram of the outcomes, showing the probability distribution of the measurements.\n",
        "\n",
        "**Output:**\n",
        "\n",
        "The keys, `'00'` and `'11'`, represent the possible measurement outcomes. In quantum computing,` '00'` can signify that both qubits were measured as the state `|0>`, and `'11'` can represent that both qubits were measured as the state `|1>`.\n",
        "\n",
        "The values, `503` and `521`, indicate the frequency or count of each measurement outcome. Therefore, `'00'` was observed `503` times, and `'11'` was observed `521` times during the execution of the quantum circuit"
      ],
      "metadata": {
        "id": "MDuLgWpvGeqf"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ---"
      ],
      "metadata": {
        "id": "2R6mWs5niK66"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "H4LZ7oqkiPGT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Plotting a Bloch Sphere"
      ],
      "metadata": {
        "id": "_o7aH_zUGtwu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit.visualization import plot_bloch_multivector\n",
        "\n",
        "# Simulate the circuit\n",
        "backend = Aer.get_backend('statevector_simulator')\n",
        "result = execute(qc, backend).result()\n",
        "statevector = result.get_statevector(qc)\n",
        "\n",
        "# Plot the Bloch multivector\n",
        "plot_bloch_multivector(statevector)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "id": "3MFVkGTaDqm5",
        "outputId": "194540bc-f83b-49f4-c3f6-28eca0111064"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 960x480 with 2 Axes>"
            ],
            "image/png": 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2NjY2sLi4iK2tLdi2jZMnT2J+fh6u40A3DGRsn5z3mbNM0jAUbDFxa3ER260WmpOTePOrX8Urr78OU/I0JSQkJATiOEZrcxPt7W1EYYgkjkV2ngfnKkvwlKFqGu2xUlVoLPjPCQFhCaU0TZFxO00IdE0TyaRdyZc9KsekKBBFEbwggKqqmGg0xHZ8C0IItlot0RO2tLSExcVFdD0P9VoNp06dwvTUFNxSpZn7UO5TihF+Jc8ybGxs4OatW/A9D/PHj+OrX/saXjh/Hpqm7f/GSzzRkMG+xL5QFAU6W1tYX11Fu91GmiTI8pxKjbFGI27sNF2nAX35HzPUZY7+IIOWZRmiOEacJCI7Q4oClmXBYcfhKFN7+kGKAp1uF0mawrYsVCuVnYpACWsbG7h+/TpWV1eR5znmZ2dx6vRpzM/P9ywwuCHOsow6jyxDVhS0v4DzP3kZmS0EwM8PQLvbxcryMjrtNmzHwZmzZ/HKK69g/vhx2I5zqM9GQkJC4nFElqbY3tjAxtoavG6XJlOKAoZhwLasHZU0RRE+pd+38Cw/r9YOarpN05RmyeNY7E8By6yXj4PRfoUncPKiQMV1qcxm33sIgDt37uAWy+JrioLjx4/j1OnTmJ6e7n0vO+c0y5Axv5KXqhO8YiHoSqXrIwC2trexvLSEIAjQqNVw7vx5nH/5ZczOz0tBCQkAMtiXGAOEEHTbbXS2t7G1sYFutysMoaHrsB0HpmHA0HUYug7dMKBr2k6QXDKW3GgpbL8FU0Lg1J1Bx46TBFEUIc0y0XiraxoqjiMy44IqVOZjEoIsyyhFBzSrr2vaDscewNLyMq5cuYLNzU1ohoGFhQWcP3cO9XpdGNWM9RWUDbCiKHQ/vFEYlFvacw3sXMV+StzSwPextLyM7e1t6IaBs2fPYm5+HlPT05idm4NbqcAwjIGVDAkJCYnHHVmWodtuo7u1hY2NDYRhCIDabdOyYJsmTNOkPoX7Ftbo2h+Ac0ooSnQeALsC8PL74zhGGMc0cGZ+Q9d1VBl9hlN6egJ+1vjLKTqqqqJRr0Njjbb8/G/dvIlr16+j3W7Ddl08c/w4zr/4IizLoqIVJZ/Cf+f77xGYwI4EqAD7W172K6x60Wm3sby0hI7noeI4OPvCC5iZnaVNvjMzcBxnp29B4qmCDPYlBoLzJb2tLRrc5zlCxkUHAMdxUK9W4dg2dMOg1J0RKCseiNdKgXJPFoYZszJ44B6zbD9hPH/bNFFhCgj9IAB81vxk6DrqtZow2mEU4bNPPsG95WXMTE3h1OnTsB0HSZLAchxaBuZOgP8jRHA5dZZZ4qVjpXQNxaivFFNzSJIEcRxju9XCpStX4HseTp0+jcmJCaiqCsd1UZ+YwOTUFCqVCqpM0UFCQkLicUWapvA6HXS2txH4PghrUk3SFAohcKtV1CsVkWXfK9lRsEqrAKPuDETJPnMuPiEESZIgYvaY23nHtuEOGbZYsB6wJElgWxYqlYr4W6fTwUcffYStrS0cP34cJ0+eBFQVWZahWqlQv5XnlNffB43JPfNEmaDi8KB/L7+S5zQxFsfY3NjAxStXkGcZzp49i0qlAlVVUa3V0JicRHNiAtVqlfYFSMrPUwEZ7EsIpGkK3/fRbbcReh6KJBGBdxRFVGVA01Cv11GrVnu25RKbKdfLZxmH8sNVlh0TKgn89dK/MggzzIT9U9ixwihCGEVUtgxAxXV3SV7y8mae57TUalkgioJbN2/i888/h6ZpePW11zA9NYUkSdDudpFmGWxW0gV2eKBcP5mXjsvnVx7cxV/j1YtxkOc53nv/fdy9dw+nTp/GzOysoAVpmga3VkO92USz2cTk5KSczCghIfFYgAfTvu+j22oh8n0UWQaFJT3CKAIAGLqOiUYDTh+VUfiSPEeeZUgYvYfTdRRVhcbnoigKCpaY0ZmPGeRXSClTrzD7DVC/4gUB4iSh2yoKqpUK9BI1FaDiEptbWwCAer0OQ9OQFwWuXLmCS5cuoVqr4Y3XX0e1UkGUJGh3OsiLAq7jwGQJG5X5FL3kX3adI0NZlU4koMZAFEX4fz/4AVqtFl48dw7VRkM0FmuGgWq9TtV9JicxMTEh+8eecMhg/ylHnucIwxC+58HvdJCGoTA0BsvYe76PhElnWrYNTVWF8eWGWJQaS6oGBTPIZa17cK4+IEqWZelKAEKDWFUUGIYBy7JgmSalCpmmMNBZlqHr+4JaYxoGKqVMRZrn2N7eBgBMNJsIwxAfffQR1tbWcOLZZ/H888/T47Hjx0mClDXpTrBG3l2Zpb4KBEpKQuWyL8/EkNL+wV5TB9GVAFz44gtcvHQJp06dwvnz55Ewfmkcx8jyHJbjoFqrCePcaDQkzUdCQuKRQ8bml3jdLkLPQxpFojJqsobYTreLJM9RpCkc14WqKEj5TBY+UDHLoKjqzrRa0GBb8OlLlBfs4VfKim6mYVCfYlmwDAO6YYht+OKkYP+3TZMOXGT7CuMY3W4XiqpistHA1vY2PvroI3Q6HZw5cwYnnnuOav4zXxBGEQoAVddFrVod6VeED+F6/jzZxQQlCkBM+O2Xph7kV/Iswwc/+hHu3buHL73yCk48+6zwKbwfznFdVOt1NCcmMDk5iVqtJpNJTyBksP8UghCCOI6pNKTnIQkCZHFMOfiGIQxeEATYbLUE/7HiOIJKUpYhU7n8Gcug6LpOX2PvEwNLGN+RMM5i+TV+XoMoPOVBJxrT4DcZn9M0DGR5jiiORQWg6jiwbRt+GML3feiGgdWVFXzx4x/Dsm288MILmJicFNQbjRl+VVHgeR4UVcXUxMT49xPYdc7i3Amhmsl9xrN8/8p/uXHzJj7+6CPMzczgra99DZqmievzul3EcQzNMFCpVlFtNDA5OYmpqSmZlZGQkHioKJhCDfcrKfMrCguuizxHnKbwfB/b7TYdRMX06VWWoClLYALUNiqM0qJrmkgm8eORohAqbmBNrgP9CvpU23jgDBo865oGi1GHLNuGqWlIs4xSRsGy/K4L0zTR6naRxDEMw8DijRu4du0a6o0GXjh3DrWSAIRumrBMEwWjwBqGgUatNv79ZOc57F4PUoAr+xV+/wiAH3/2GS5fvYozzz+PV155BVAUuiBjPjJOEli2DadaRZ35lcnJSUkdfYIgg/2nCJyH7/s+1cEPAjHoijcNRVEksvFxFNFBV6qKCmsY1UpcdV3brYgAADkvNw5BefQ4h5iSix0N47wokCYJkjQVA0oKpmPMjTyKAoRxHfM0haIoIsOf5Tm2221cv3IF7W4XJ06cwOnTp6GzRYlpmrBtWzgRUhTY2t4GAURmf1yM4unzfoORA8BK1Ka1lRW89957qFSreOedd2DbtrhfSZrC8zyaeQLgVqtwq1U0Gg1MTU2hwSXgJCQkJB4AeGLI931kUYSYDxtkiZ4sTRHHsbDtcZLQKeSaRv1KH0VS0zTKXWc0Fx68ctWzYRik6laevs5/Znku/EqaJEhLdNOC+RNSFKLCnOe5OKeq4yBJU2xsbODqtWtI4xinnn8ez544AQWApmmwmJwn72PLsgytTgeKouwriQSM9iu7+hX60edXFq9dw6effYa5+Xl89atfFdUFQghNJrHYQNU06lcqFTQnJjA9Pd3TlyDxeEIG+08BUhYgBkGANAgQeB7CMNzRhy8ZNlWhE2yzLIOu63AdRzSNjgNCCJ1UO4Sqwjn3/ShTYHjjlHiN7lg0tvLgn/+e57nQvI+SBCFTWVhbXYUXBKjYNs48/zyajQatCrCyLVcEKp9rx/MEx98syXuKUeeMI6ryJipuMLHT+NW/T2AMw9yHVruNH/y//4dqrYZvfvObO0PE+P7YVN82GxZm2zaqzSYajQYWFhZo2VmWYiUkJO4TYkZnicMQcRDA73aRRBHykq1TWaaZ+5U0y2DoOmoskBy7r2lAAqmsiqawxtz+/fHMNoChfiXPcyRpijhNaRIsTZHEcc+ArjBJEEYR/DDE6vIykizDRL2OM2fOwLVtGKYJyzB2VHxKPoAQgnanAwKgzmg8KJ0Tb8YVvoXLU4Pa+VF2fC8t/n6sLC3h3fffx6lTp/DG66/3/pEQZGxAZtfzkKQp3GoV1XodU1NTmJ2dhW3bYx9L4tGCrNE8wUiSBJ7nIYoitNtttNbXkSSJoOvoqgpDVaGwbITrOHBsG1maIkoSAFSucs+gsfT3PM93KDx9fxel2SH7Kwe0wlCWaD+8B0BTVVimCcMw4LLG4Jhn/glBmiRobWzQUquuY3pqSlCTNJbF51ke4QA4zx7UgMZJMvYCR1UUKJomhr7whjFV06CxnyoAUpovMEy/maPZaOCtr34Vf/W97+HihQs49+KLorkZjDJVrVZRrVYRJQm8bhcby8tI2ATfCca/lM28EhISR4koinb8yvY2ttfXkRcFVNA+L1VRYLDqr2NZsBmtMmGBtKZplBc+zsFYlp1z4Mt+pUyDJIoCdUjQWz5O2a9wSWROBzJUFZplwTQM5JYlBCeSJEFBCJIowvbaGgiAZq2GmdlZJElCJacZ/XWoX2EVgjhNMS7hsjzdt7wgKPsYjfmDkQpwJcwfO4bXXn0Vn3z8MWZmZnBsfl70RHCVuWa9jma9jiCK0O50sL6ygpTFElNTU2g2m7vEMCQefchg/wlEkiTodrsIwxDdbhfrq6vI4hi2ZcG1LEp1MU04tk3/OY4IbLkMGQFQq1YHThYEBusXCw5hiXPZj0Fl2PIglDxNRWaIlKU6hy0QFAW6YdCsUZpCVVXcu3cPSlHg1IkTWF5bw0S9Dtu2oWkaYjZQxXUcurhxXaHcANDhKn4YwjQMev3Y4eSLYVl8cm65FyHLaOl3wHnywF9ljkvXdWiGARU7C5xBC4Dp6Wm8eP48Ll68SHWSJycBnjErLURs04Q9NYVqtYqNzU0kUYQ0TRGGIWq1Gmq1GpwhMnISEhIS4yCKInS7XURRhO3tbWyurQFFAduyYLOZIKZlwbZtMQOF26kwDJGkKQghqFQqg/3DEL+RozewH4Rh9B6uEpex6i+33WIeS8kmlrPxnE7EVdhACBYXF2ExX3P6ueegMQELVVEQBAHCKILrunC5bGfJr+iahihJdiQ9UfJ75YRWH+2oX66653bxoB/UR/XPISgr2ZVx+tQprK6u4qMPP0Tzp38aDsvWi0Zgtr1jWXBmZxEGATa2txEzv+L7Pur1OqrVqsz0P0aQNJ4nCGmaotPpUHpHu43W1haKNIXNDFalWhVBrsZX8yUUeY5Wp4OCGXDHdQEMN7BliKmFe7yHU114j4CYFjjEWHP1GpVP32VZdF1VobBMeRxFSFm/waeffoo8y/DKq69CURS8//77ePPLX4bOKha8F4AUBdVjJgSO46Diuqi4Lp0Q7HnQyiPQB50Xv2cs65SVjDUvrfLegzIyRpsCqEPhBlovDTopLwCKosD3/uqvEIUh/vpP/zSMAQ1ToqGNbdP1PARRJPj8tVoNpmmiXq/vkraTkJCQGIU4joVf2draQrvdhpbnsE0TuqahWq3CYVXhQdXQLE3R6nRACEG1UqFiAnsE7xxcdW3ke0p+JWc9AlmWIc+ykZr7CqNjaqVkDM+e58yfFISg1Wrh888+g+04OH36ND795BO888470A0DSRxTiWlGIyryHAWoTXZsG9VKBVXXRRjHCFgSqd4nW91/vcBOA25eFGKacHmSbn/jbnlisD5oCBnQswCIkwR//ud/jmq1iq9//etDk1T8X57naHc6iLMM1XqdCkRUq8KvyEz/ow+Z2X8CQAhBt9vF1tYWtre30e12YagqbE2DYZqoVSqo79FwSgiB5/s0uNY0mgk+5Hn18CmZ0UoZ3WaQEdYURWS9NWZ4lX7tfZaN4ZKhCWvK9TwPn3/6KUzTxNd/8ifpPfF9qIoCt1KBpusgpgmVqfkEUYQwCJBlGZI4RhhF2NjchGEYgrPPM03lyYhllQgA0Fh2xWDvy0ulW4AuoPhAsaIoELN+A55lyvMcYKPbRfBvGELRSFVVfPWtt/Dnf/7n+Pijj/DWW28N/Oy4FJ2iKKjXarANA23fBwhBmqao1WrI85yOU280pMqChITESBRFgXa7je3tbWxvb8P3fZiahpphwHRd1KtVVGu1kXTHoijQ9X0quWlZ+w4KB+Uiue0loLTRNE2RsgB/EJ1FU1UYrGGW+xROg0FpXyogKqJplkEBsL6xgQtffIHpqSm88cYb2G61AACObcN2HAQs4cTnsURhiDCKqNhFGCIIQ6wBYnJ7o1rtTbKRXnnmfr8CUKlSLkTBtyn7FU47TZKEVgjYrJuI7as/+IeiwDJNvPnmm/irv/orXLl6FedeeGHgvS/LejbrdYRRBK/TAQhBEseoNxpI0xSu66Jer0sp6EcY0uM/5ojjGMvLy9jc3ITneTAUBVVdh2UYqNXrdELesC8gC5wV0ImyPIMykL6zB0QgzKgqecnocBWdfolKMVDEMKgiw4BqQxkKaDAdBQEipuigKAo6nQ4+/eQTNJtNvP3225QbGccioNUNA9VqFZ7nochzJISgWa9jamICcRQhYEY5Zc2+Hd+nWYwkQa1aRYM7tD7noAxzRKVytKbr0MiOpKhpmshtG0VRiAFkaZaNDP4Nw8Abb7yBDz74ALdv38Zzzz0n7mX/3eIGWjdNTBgGOt0uojBE7Ptw63VMTEwgSRLUajVaTpfUHgkJiT4EQYClpSVsbW0hDENYmoaKrsO1LNSZXxkFbgfDMBTKNpU9thkEQY1kQXFe8ikpy6j3S1TqfGAVs539cpT07Tu69mD79aNIJI8UAKurq7hw4QKee/ZZ/MRP/AR83+/Zh81oStyvKAAmJicxraoIwhAh+8ftvMcEFcI4Rq1aRXXA5PdBNl0FUJQpTgpVn9NK77dMU1CVyn5lVPA/0WzixXPncPHCBcxOT2OS9bYNkvvkiyjHtqHrOrq+j8jzEPo+6o0G+ODNxoDBaBKPBmSw/5iiKArcvXsXy8vLiKIIap6jYpqoui4ajQZcxxmY5eC8REEZUeggkzAMUYBq6Q9dHJRR5jyyTEMUx8LQDMrIcHk1bmy4oRsYcPYp2oipuUxPn0tsrq6t4dNPPsGxY8fw1ptvQtM0dLpdcTyAGnRd11Gv1eD5Ph3G1emgWq3SgV22jWaziSxNEQQBzcDHMZIkweb2NrZbLTTqdTRqtZ05A9hRdOCB/9CwuXSv+T9V02BpGiymj98T/LOybTn4r1armF9YwMcff4xavY5msymc4CBeJkCzMfVaDUEQ0EEqa2tobW5ibn4ehBCEYYhGoyE1+iUkJADQnq3bt29jbW0NWZJAIwRVy0K9UhF0jYHMX8JkHnkQrShieFNBCOr7SSDxiiohSIsCaRQJ27j7rQoMNttF+BVlZ8bL8EPQY+R5jqBUIVYUBZZl4dq1a7h+/TrOv/giXnr5ZQDYTVNVFJi6jlqtBs/zkBcFPM9DtVIRvH0+QdhjKm9ZliGOIoRhiE1dR5P5FRH092X9975VO+9XFQUq7zFgFZR8j+B/7vhxLK+s4L0PPsC3fuqnYNn2jlAGGTAUEtSXNmo1dNmwtFVG75o/dkyoxMnq8aMH+Wk8hlhaWsKtW7eQxjFQFHA0DRNTU6g3GnCYMd4V6JeC/H4OH89YmGxa7SiUjUvOFAq4Ek5ZWlJhlBzBSdc0ymVkx90TpUA6Ytl3fu6mrsN2HDGe/PnTp/Ha66+Lqb38PIw+2pKqqqhVq/B9X+jVu5WKCLgN00TdMKCoKmKWXY+TBGmaYrvTwXarhVqthol6nU6B5KfK7yV2pEX3cmzlLA0BRPDP91uujPDg/+yZM9hutfDhhx/iJ37iJ2BZFkzLonMCyI4MXdlJqIpCqzu6Dt/3QbIM9+7cgeu6aE5NIUkSVKtV1Ot1meWXkHhKURQF7ty5g9u3b4NkGRRC4BoGJiYn0azVYBiGUEMT4JXhvl4jgAaZnu+DAHBLwxj7QRh3XintL2MKOHGSiGw1h1oK7HkDLR/G2KO6M+BY5dcKluwoJ48sNgTro48+wt179/DG66/j9OnTO3NSgF7/ya6XJ5K6LKDvdjqo1mq0v4otHnizcpKm0DUNfhAgz/OhySS+bxFs76O1snx+uq5TCivzSf3Bv1YUOP/SS3j/gw/w8Sef4PxLL4nJwhpbvPHEVrnqoKoqarUaQuab8zjG7evXUW800GDV43q9LvX5HyHIYP8xQpZluHz5MjY2NqBkGQxVxcz0NCYnJnr0fbnaQI/xG5Kt54E6gF1lVs5j7FcsEIa4lGlRVRWqrsPgCgaca1/aVtlDD7jfQOdM8zdjsmu6ptHmYk3DRx9/jFu3buGVV17B2bNnxbb8nFRVRTFo30yykk8N9H2fjgwvqQpwbqfrOJiyLNrw3OkgYUoE3W4XFdfFRKPRo0aggI0s5/e6xN3nGDZjYOc/O2oQKpMY5fciyzJ86UtfwgcffICtzU1MTE0hYnQlyzRhsCnA5f3wBmcxIdj3QRjNaWttDdsbG5iYnkaWZZjYxzwFCQmJJwNhGOLSpUvotlpQWePt7PQ0Gs2msCc80BeVYaAn0O9P4ERsIrumaQMVW3hVkg994tXUOEl6bKSmqtA1jUpFM7+iKApVjWHvGaYzX6aWls8uzTIEvk/7q1iF2HEcFHmO77/7Llrb23j77bdxbGFBnCvP6g9btKiaJirHaZrC63Z7Ekn8PQYhqFWrmJiYQLfbpdnxIckkAD3BNVdsExTOcuKtKIZWlsuflTYg8++6Ls6eOYNLly/j5MmToopusMnyBptJU17Mcb9is0VB1/OgqioCz0McRdAMA9Ozs5hkgx5lIunhQwb7jwm2t7dx5coVxJ4HDcDUxAQW5uags4ZSEeiXjMA4X7Aookw+q6zHXs7UYGcCbBTHSNO0Z3tD12FZFm1s5RrDpX2gtI9+DDPGAO1F8IJAOBa3UoFtmiAA3n/vPSwtLeGtt97CiWee6dmOn59hGCI7L47Hf1EUVKpVqCVepQIITXquxZ8XBR2TXqmgWqkgCEPKgWdlWN/3YTMKUHUQH1VRaFlb2VHW2Uv8qmeBVqpuaKoKzTTx3DPPYPHaNdy9exdzCwtIWGNalmVQwhAmy06V6UZ8EaLrOqqVCrqeR/sq8hy2rmN9aQl+p4P4+HHMzs7K8quExFOCpaUlLC4uIo8iaADm5+YwOzMDhSnSAKwPiGWGy3KSw1AUBaI4prTQ/kCfB/mgdi1hdMm0j6JjGAZsy4Ku68iKQtjRcp8ZMFzKmQ/y6nkddGETRpGYdltxXRiGgTTL8P99//sIgwA/9c1vYoJNuuV0IO5X9EEiF5zuwirHnu/TqcK+LxYTXBM/Z9l1wzDQqNdRq9UQ+D7a3e7IZJKgarJrF9fPKiF7fSY9MwmwI56hahpsTcP5c+eweOMGlpeWcPaFF5CyinKaplBY0skyzR5qLED9EmF+xfN9FIRAB03sLd++jcDzkCwsYHp6WiaSHjKkV3/EkWUZbt++jaWlJRRRBNMw8MzCAprNJp3+V1rRF2y1PS4SPoiqKGAx/f3+Y/MsfjlI1RjdxOI6yswAa6oqGnH7Ud5+mDEGqKPwg4ByKEEXE5VKhRoVQvDpZ5/h7r17ePtrX8PCsWN0f2xb3n/AeYVRGIrz4XJoZW1lrj3vhyH8MASYUVOYQSsIobx85ui4bGmcJGi32wiY7vDK6ioMw0Cz0UCtUqGZfX695b6DIVSbvdCzeFIUnDt3Du/+8IeIwxATk5PiM+KNyXEc07HtbEAMN7KaqoIwqTxeco6TBK7rwvc83Lx2DYHv48Szz0opNQmJJxhRFGFxcREb6+tAksC1LDx34oSQW865lKOiUL+yj0AtimOQohAqOD2cb5Y44uoxZfAKpWmavVQUVe2Z4VJG2YqW+9F2VYnzHF4QIGfT3S3TFFPG86LAez/8IbxuFz/1zW+iOTHRQ1kpy0qruk6V1cpV29ICBopCqSuKQhNWnodavQ6dVWo51ZRvqyqKGI7Yk0yKIpFMmmg2aUN0yXeJn5xa1UezGYVy4M9/NwwDZ8+exaVLl/Dyyy/DdV3xGRVFgYgNaxz0GWmaRucnuC485rstRYHjONje3ITveYjCEMeOH5eJpIcIeecfYXQ6Hdy6dQutjQ0oeY5mrYbjx46JQIxzw/m0vv0E+oQQBGEIAD2KPcPKqbxxyWTl1B6UKgmqpiHPsqGZ/bIx7g93kySBHwTivQ6bvAhQA3n16lVcu3YNb7zxxq5AnwBC0QagBqg8rlyUP+lFir9ZliU0lX3Pg8I1kDkdihnSnG+j0IFkMzMzgvffZc1Z65ub2NzeRr2/6YrdV+4Qyhz/cQ20uNUAjh07hnq9jsuXL+Odd96BbduwbZtOe2RTKrnMZsAyS7wcq6oqNEJQYxl+XrHhlYul27fhdTo4feYM6iPmDEhISDyeWF9fx+1bt+B3OtAIweTkJI7Nz0PTdYAFtnxy634TSDwwJKBiD3zLPM/pwMY47kn8cKoi54j301MA7GTFh9F1wOimLMnC/SFHGEUIfR9gc1rcSgWmYdBtiwIfffghVtfX8ZPf+AYazabYlve9ZWxeCg/Wy4uAnvMo/d91HCq6kKbodruo12rivPh+CSCqxwDErII4TdFpt6lCXJZhmSWTGs0mKqUBmPy+it6xUiV42IDHUXj++edx+coVXLt+HS+/9BIdOmnbSNNU9K7xKnLQV0Xm1fCKosD3PMRJAiiKqHTcun4dXqeDU2fOSLWehwQZ7D+CyLIMS0tL2FhbQ9DpQFcUzMzNYWZqShhkniUuZ/XHATemfKogAdXxjYeUU8tf6H4jOggKAM0waMDPj1ky0qTvJ/97EAQ008O4+ZVKpWcuwJ07d/D555/jxXPncPr06d5rYsfl2RfRLzDk/EifEXRdF4QQweHn2a1+p1ReNAC06jDRbKJeq6HjefC6XWRFga2tLWxtb6NRq6FRr0NhFQ9+/PK5KAcI+hVFwYvnzuH9Dz5Au9NBkzkogzVEO6yvIoljZMzJJklCm4ANQzS2VatV+IwzqigKKq6LMIrQabXw408/xemzZzHPeKsSEhKPN5IkwZ07d7C1uYmo04FtGJidmcHU5CQdUMgy1uWprOPaJW6D4yQRlQBd1xExAYeyeANAkyxlumG5OjsIPODn/VsgVHKT+8Gy/KYI1vMcPpulAlWFYRio9MldfnHhAm7dvo23vvpVzMzMDDwu92W6pu054Ku8XbVSQbfbpepvnid4+KTkC/gCp3zepmFgenoaKVON81jf2uraGjRVRbPRQL1aRVHaZldzcqlvbFxYpokzzz+PG9ev49wLL8BgCyKTZfILpucfx/FOUjCOobNKv6qqsAwDxHWpAlwUQWUBvx8EWF9bQ7fbxbkXX0RzcnLs85I4Gshg/xFDp9PB3bt3qYat56HiOJiZmhJBI8CaY0rbjG57peDGmGenoygSg57anU7Pe4eVU1Hanp3Irv0DgMKMvcgQqaqYGtuPLE3FMC8oCmzbhlPuHwCwtr6OH334IZ577jm8zGTQes6J74sb5T1KhYPcicum56ZZRtWJeGa/79oHOUBN0zDRaKBZr8PzPHQ6HcRpinang612Gw02xVZIjdKd9VzjftuXnnnmGXxx8SKuXL6Mt956a4eLCYjGKduyekrmRZ4j5OVoVYVj26iwDH/COKncGUZRhCsXLiD0fTx38iRUWX6VkHhssbm5iaWlJSRBgNTz0Gw0MDM1hWql0kMr1Eo2aZxAX/gV9v+YTZTVVBWtdrvnvQZTezPKU12Bnd6mMsrUGPESbTDNs4z2DvDAfwDiOEYQBOL/FdfdRU28fuMGLl++jFdffXVX71cZIomk6yOD/X6ZSoX1hnndLvKiQBgEghbVj0GJNEPXMTk5iUajgY7niYXD+uYmNra3MVGvo1qexsv5/OXPkP9/zKD/zJkzuHbtGhZv3MAL587t+Hvm0x3mn3m2P0lTZHmOLAxFwsm2bcB1EQYB7Y9gC58gCBCHIT7/9FOcOXsWCyPuucTRQ3rwRwRFUWBpaQmbGxsgSYIsDDE1MYFqpSICfT6Ztd+8DWpS6keZ953EMVqloVHATjnVsqzerPggQzHIWJX/DGpgDCa3OVAtgVDpsyiKKN9f0+C6LpUrK6HdbuOH776LuZkZfPnLXx5JDyob5T1R5j+y7SslaosfBKi47q4ydjkbP8gZ1Wo1VKpVdLtdbLfbKOIY2+02ur6PqclJOLYtth04HbLEpywADGPKqqqKc2fP4qOPP6baztXqbinQohAyda7j9Kgopawsa1kWXNel04jjmC4UbBuEZXHusiark6dPo1Kv731fJSQkHhlkWYY7d+6g02ohjyIUaYqZmRlUXBdVNlRPAaN99G1bjBHslwNL3/fRYZXCGrNHuq6L6nAPrZJuTG3ooEB0kKADWDacSUkO8nqE9XylvErMmkf7K7337t3Dpx9/jBdeeAFnz54dcPgdOlFWyuzHu95ZuhfYHfBrTP2t63lIWeKlX45yl6JR37XzZFK9VkO73Uar1UKS51jf2qJ+ZWKCVg1KSj3DroX/fxg1y7FtnDp5EteuXcPzZ87Q6npf9YCALtwMw0BRFL09Y2wBYLP5NXEcC9ls13VRsDk3169ehdft4sTJk7AlreeBQLZHPwJIkgRXrlzB5uoqEMfQAUxPT8N1HNSqVSprOSTAJEOCxp7mIfavyHP4vo/V9XUkaQrDMGCaJmrVKpps8h2nqwijsY8yILBDkeFBscYz2KX9ZFmGTqcjAn3LslDjusQlBEGA//f976NWreKrX/vacGoOO2a53LonBhg7lRlmXdPocBA2/XHwhQ4fZgVCYFoW5ufmMDkxAZM1da2srWFtY2N0doh9ngWnDLHfeb9B+bN+9uRJOLaNq1evDj6/0kh43nNRr9VQL0m7xXGMKIrE9OIwjpHmORwmcUoIwfb2Nq5dvozlO3eGytxJSEg8WvA8D5cvX0Z7cxMkjmExeohj27TS2B98lzBsOrdAqcKbZxm63S7WmF/htI9GvY56rQabiT+InqkhQe0wEPT6FRUQ/PnyOaVJgnanQ5VzFIVeJ/OfZWxubOCDDz7As889h1deeWXwQfm15bmwedoYfmVQCK1pmlhwZFnWU3EYuO0A38Sv0nFdzC8soFGvw1BVpGmKeysr2NzeHmmbuV8p+5eyXynjzNmzSNIUN2/eHHyepc9PVVXYtk2VhapV4TNCJl7Be/R4Lx6vHBdFgfW1NVy9eBEba2tDz1vi6CCD/YeMJElw/do1xN0utKJAvVZDrVaDpqqos2EmosQ3yDiW6CBlw1em25CiQOD7aLXblBufplAVBdOTk/QYbDBJ2Rj3lwP3At924CRZQvWWVQBRGKLb6dDGJBZcV1x3V6YhSRJ8//vfh65peOfrX9+TmpPnuSiPjmOU6Wntvp88E6PpOoo8h+d5wzPwfVScgjW3lZuuarUaFubnUatUYKgqojDEveVltDudsQJn0ePAjHTOjTTj1p45exa3bt1CyJqt+y5QLErKd1fXNNRYCZgb55w1k+VZRsvNgDDeXCFpfXUV1y9d2iVpKiEh8WjB8zwsXr+OLAhgqSoa9TqqrA+qzvzLqKCbDPhd+JRSkO95HlrtNp1Xwmgcs1NTNMhmtoX7FgC7bNFeENsN8CuKqkJngXzgecJW82vkamtldDod/ODddzE1NTWwUkxvx46vzcfoA+s/30H+gvdIKaDy0MEge42d+1Nuts2ZX+GCHKqqYqLZxMLCAhzLgqGq8DwP95aX4Q9ZSPQcoy/LXzD7z/1KpVLBiRMncOXKlcE9etyn8J5B9h6uSFcO6AkhiOIYOUueqaqKKlMryhhldvnOHdy8erWnz0/i6CGD/YeIKIpw7coVpL4PXVEwPzsLlQWQtVptp6EHgw0I2OvDjDFvfN1utRBGkfhiu46DiWYTFqOUkNI2BzHG/bzNXWCZ/SCK6LAVhSrE1BsNoYpQRp7n+MG77yKJY3zjG98YOJSFXfxOqXWACs9eGPY+jTUIA7ThLGSzCIadgwjymWqDuGa+P13H1NQUZmdnKU1KUbDdamFlbU3MORgXqrKj6FAUBZ47eRIKIbh9+zY9nVHXi1JfBSgntF6rwWXG2TAMxEmCruehyzSiK64LhWWkojhGFIa4fukSAjZ1WUJC4tFCp9PBjWvXUCQJbMPAzNSU8CvlKa1iAOMQ9DR/Dgjy252OsOcElBc/OTEBzTB6Kss8KDxQkD9kuzKlJPB9JHlOe75Y9XJQcigMQ3z/Bz+A67p4++23hyeFSkmcvYZpDTyvIX7FsizYTKEoDIKRSROCnWnwBZdB7YNhGJibm8PU5CRMlrBb29jAytoakn0EzoKaWvIrp59/HmEQYHWMrDvP3vNFgGmadLHFeu8Mw0AYBOh0uwijiFY6XBdQFCEe0e10cOPKFZlIuo+Qwf5DQhRFuHHtGvIwhK6qOM4GJKmMbmGXmolISbaxjJ5m0b4gPwwCbLVaCKKIKixoGmq1mlBAMEyztxKA/TeJlkurI99HCLq+j5iNJq+yhlWeXerX4P/ggw/QabXw9a9/vbcBacjxgX1SePj2GL6IMnUdjuOAAIiZ7nH/NRVFQRWNGN91r4Zb27YxNzuLiWYTpq4jS1Msr65ifXMT2T7oMcK4KgrNpC0s4N7SEs2kjDm4q3yuFjPOLpM6LYoCrVZLNG67bLEVxzHyPEeeZbhx6RK2NzfHPmcJCYn7j06ng1s3bgBJAscwMD87i5CporhsgBSwUykcZKeIQtVtFJ79Z7aCVzrbrN+LECICO9M0oamqSFABB/QpZPfU8UHgQWm320WaplAB1Gs1VAbw8wGaTf/+978PBcA3vvENcR8GHb/sa/MxRR/KGHXNnMsOQkSVvf+68jxHlmU7FNI9/EqlWsXCwgKt0qsqkjjG0vIy7Rnbr19h967ZbKJSqWDp7l0h5DFISU+AJ97Ywk9hvV/cr5hMLGJjcxN+ENDJypYFAgg51igMcePyZfjd7tjnLDE+ZLD/EBAEAQ30gwC6pmFhbg5QdiS+3FLDyiD6DiF02JP4cvZn8ttt+Kw7XmclzWazKRRyAIipfgcyyKAOYSBlpw9ZntPmpCQRgT7ncPLBWlzTWQHw6WefYXl5GV/92tcwMUKeq78Rar8ZGPDth2RheEbCsSzKZQ8COhWyKJBlmeByKn3720ueVFVV1Ot1LMzPo1KpwNA0BEGAe/fuobNPI8ePd2x+HttbW6JKwBcie03sLWfHuHGempgQz1/X89DudoWqEpcn5dvcuXkTK0tL+zpnCQmJ+4N2u43bPNC3LMzPz1MpZda/45QqpAP7v9hPhfSpveU5fM+jog5xLOg6ddY0yukfiqLsmrC6H/AK8zg+KcsydLhtYoksrh7HqS68Z4kQgnd/+EOEYYhvfP3rwyvF/PpLPqFcMT4K8IFeBlsUeZ6HJMsojZJl8cuLMN6jsKuJtw+qqmJyYgJzc3NwbBu6oqDdbmNpZWUoZWggyM7Ay2PHjmFpeVk8J4T5lIJJdvPz67k+7PhVPpvAdRxMT07CYgnGTqeDTrcrGoXzPBeLnixNsXjlCra3tsY/Z4mxIIP9B4wgCHDz+nUa6Os6js3PwzRNwZO2bFsYlkHNtwToHVnO3hOGIbbZII6iKCgvu1ZDs9EQ2ZbyyG9V3XvseT/KzTy7pNIGIMtzIRemqmoPNakMbqDvLS1h8fp1vP7665ifnx/YPCS2KZ8Xy4YA+wv2+/fTd1KC/2mYJvKiQKfT2TWHYND+xuF2arqOmelpzMzOiknEm60WllZWREA9LhaOH4eqKFhZXt71t/7Av/9+DjLOU5OToqEsZbrKaZpS1QWW3efbri0t4daNG7JxV0LiIaLVauHujRsgSQLbtjE/NwdVUURFkk+LBSCGLpXBk0c8k0/Aps56HqWBskSHYRhoNBqo1+tCUCFNEqrQYlkHTh4BQ/q9BiBhQ6eKPKe9bdXqQLvPkyGXLl7ExsYG3nnnHdRqNeEz9wKnZZYXMfu9pt0npaAoCjrZXNNQ5Dk6nQ4djrVHYmYceqplWZibm8Pk5CQsppazur6O1fX1sWcEcBw7fhxxkmBre7vvEhQR+Od9CSW+UFHIzjRjgPrl6akpVFwXeZ5T6U42ADLNMioFToh49u4uLmLl7t19na/EaMhg/wEiCALcvHKFUnc0Dcfn56HrOlImhwhFEZQJAb6qBnY1hIIH+a0W/CDYCfKrVTSbTVilwJoQIlbPgwLucTGuMU+Z4g7XXB7Go+QIfB8fffghTjz7LE6fOtVzrHL5kFNvyopBPJDdr1Hm+81LhivjJVTWtJQXBWzLEo3Svu/vWWYWAf8YAbDDHHOzVoOhacjSFEsrK9jc2hqb2mOZJmZmZ2kWZtT1EjI0O6Ow7B/YuVcrFbiOA5X1QGiahizP4fk+up5XulgF7e1tLF65IgN+CYmHgO3tbdxbXESepjSjPzsLTdNopa8o6DC9si8oVSTLggwcBSHwgwCtdptSLED54Y16vSfIB6iscpKmACE9xxgH41J2yojiGF63i4IQ6IZBVYVG2Pz19XVcunwZX3r5ZUxPT4vFTL98MufI898JISI43k8fWPma8qJAzv1InotJvAUTWqi4Lm1iZhX5vcD9yjgLlWq1ivm5OdSqVRiqijiKcHef1J6pqSk4loXl5eWRn1M5oVSQ3mZsQe8hREhAV5lCkqLQAZpxHKPrefQe8M+AEKyvrODurVtjnavE3pDB/gOC53m4cfUq8iSBoes4fuwYdBZAhqwpxbEsYbjKQSynWZSRZhm2O53eTD4P8st8f7Z9QQjSNKXZmX0Y5Z5s/pjbRHGMbqdDewV0fU+DXBQF3nv/fRimiddff31XqbJc0uz5CzMMSZqKrDTnrHNpsbxkhIpSUJ8zfjs3fLwUTQ+k9GTBeKOqqmnI83yw8k0fFIAa8j3fSQ14o9nEwtwcKq5L1RV8H0tLS2OpKwDAwsICNjY2aNadGde9UL4XwE5mTVEUmLy3g+n0V1yXzgggBJ1uF92SSpECqrF9Z4hUm4SExP3B1tYW7t28iTxN4ToO5ufmRMKD+xW3pErTMwW8L8gHgDhN0Wq1EDFBBx7kN+r1Hp4730+WZUIlZj9V1R7VtzG3CcJQqP5YljVQVrOMJI7x/vvvY3Z2FudeeGHX38s0zp7MObNrKUv6CDlq9k/4lAF+hSdUeJ8dKXorqj1+RVVRYbMOEjakai/0UHr2gKbrmJqcxNzcHGzL6qH2jCMMoSgKFhYWsLKy0jtfZgR43JKXfCtYxl4B7VtTmbKRaZpwHQeWZaEoih4hEV5l2t7YwNoeSSyJ8SCD/QcAz/Nw49o1kDiGYRg4trDQo4jAMwhWmVPJAymulV4y1n4Yos1Kf1wqstFo7JoQiFIwlnEKj67TxtgxsN8gHygZZNCM814GGQAuXriA7VYLb7311tDGqVEoyrzKvqbhMt0Jpdd2XVNfcCwyX+x1VdNQYU4ziqKx1A4493FcGIaBmZkZTE9Pi+rL2sbGnhrKAA32i6LA6uoqvb7StOVByPv2l5ecFVdV4Nx9Tv+aaDYF3zWKInQ9T9x7BUB7awurksMvIfFAsLGxgXu3bqFIElQrFczPzIikSp7ntLLIFu5AqSpaouvQP9DESJdNaS1YFrZeq+0K8vl++PbcNhiGMZafGEu9bcA2nu+LJIvrOCJIHr4RwY8+/BCkKPCVr3xlKNe9d5NeWymoof2Jqr7quni5f4cDjileYfZX13Wq0MOqxrxHYBS4stK4VRGL9W9M8JkveY7ltbWxesQWjh1Dt9ulU+WBnlhkEMrTgQnQk0wC2OR25ldiFg9NTUzAMAwQ1rTs+35Pv9nK0hJaksN/aMhg/z6Dy6AhTWFaFp45dqwnA5JxWS1VFRmZnAfpfUYlzTK0Oh1h9CzTRHNiQjS87ry1lLlhrycsazAOhedIDLJtiwmNo7C2toZLly/jpfPnMTmiIbfn3MY1ymNiEB+yP8sDAEZpwnDg++JzGmv/+zgf13WxUCrBdrtdrKytjeRcVioVNJtNLJWC7aGLDTJccq+suayxpj6lxP2tui4cxxGqEV3PExkpRVGwurQkm6skJO4z1tfXce/OHeRJglqtRmWbS/YvLanI9M9h4bQ9nnGNswytVgtxkkBRFDiOg4lGY3CQj157lqQppfmM6Vf49uOiYJVELslYqVT2bLAFgGvXrmF5eRlf+cpXxnr/IGWi4pDNuQPtPk/ClF6yLQsG+5yCINg7iGef534SScDOzBfHdaGrKja3t7G2sTEykTQ7Owtd04Rf4dc0yK8PnQWEnSoyKQpYhgGLxSxl7X2uBJdmGZ1kX0ok3b11S8o9HxIy2L+PSJIEtxYXQdIUjmHg+Pz8riw3z7gbpUw/BjS99GTzFarDX6tWxSpfbMvQ38CapClIUeyaUtuPgxrkbrcrgr5KpQLHdffcLoljfPDBB0PLrMPQb2h45uCoFBPYQQDsXliIybLA+ManxBMdF7xRdmpyEjqT6dxLWeHYsWNYWVnpNd7lxjuGgpCxzqVgZXyVNZWFUQRN16Ez2TQ+jC0IAjEhEQDu3rwp5dMkJO4TOp0Olu7eBZIEzVoNczMzu96TlvwKp5ugzy70Z/M1TUOjVhMVTLUUmParnwEQs0UADJyXMgj78SsZF0Vg11Kr1XZXrwegtb2Nz378Y5w9cwZz8/P7OOIOeMIDOFq/0l8xBhhNtFIZmyaqDPl9HGi6jrmZGTTZBN4wDLG0siKSgbver2mYnZ/H8gAqjfAr7FqKMZJfPNvP+zuyLEOcJFQIQ9dhM4GSoijged7OfKCiwK3r16UO/yEgg/37hKIocOvmTZAkgaPrWFhYGKz/yzIwhq4Lfni5i31QNr/RbMIqGVeVGW5BYekL5DinXVHVkbzKgwT6eVGgw7SOQQhq1epYBhmE4Ec/+hFIUeDNMcusfLsyOF8SOJxRHpbZ7w/2uWHm1KhR3MdBAfVe0pz9qFSrmGOKPQCwuraG7XZ74HsXFhaQ5Tk2NjZ2H7d0/P1qL1slPWRVVUUPSDnLlrBhXAXjqt6+cQPxPgeGSUhIjEaWZbh7+zaQZahVKpgdEOjz9xHQzL5QXivZI87N5wkax3HQrNd3+4cSra8fPEA0dH2oz+ifnjsusixDt9NBxqiqjQGVhoHbpSnef/99NOt1vPylL411rEGNwuWs/n6SNMP2zzHMr6iqSgcYjkET7TkfZWdo2X7QaDYxMzu7Q+tZXYVXFl4o4fjCAra2tgYG2pwySvbpVzhnn4A+Rzz+ISyG4AyEKIqoKEZRIEtT3L5xQywwJfYHGezfJ6wuLyP1PKgAZmdmhvLWMxaI68xg8i8Mz+Z3ul3keQ61L5vPwbMumqYN/cKne6jwDCrPjoOMK+7kORSmH18u544Kaa9du4bllRV85c03e3oVRmFQkJwfoVEuo9xI1Q9N04SUXRBF+5Y0G1dRgcMyTczNzaHqujA0De12eyCtp9lsouI4A7MwAIRk2n6dA8/uA3TIjIKdXhPHtoW6QpnWk2UZFq9e3feEYAkJieG4c+sWSBTB1LShgX7BMu4KIFTEuNTmwGx+vS6y+Rwi8cR7xgZASG4OG1AFDGwC3gtxmlK/xyrR9Xp97ETOJ59+iiAM8eZbb40lgYwh5yj8yrj7GLrr3oruoMw+h2EYgpI7iiY68FV2DfvxK1wJzmFNs+tbW9jY3NwVtM+zROXyqH6sotg3rcgyTdrkzYRDAAjFoorrCh/LaT1pliEKAixeubJvnyshg/37gnarhfbaGvIsw/TkJMwBmW6eHeUGVS0Nxypn8wmhkmbNvmw+3weA3YM3+pCyBcUgXuV+pc84sjxHx/OQMyWgxrCs0ACIMuvZs5ibmzvgGVAICs8hjTKAsY0yQJueTMuCCsALgrFKmGWoYyrmiPerKqanpzExMQGdTUlcXl3dFUzPzc8PzOwDEEoSAPZFK+KDYADsKEaU1Cm4ElQ/rSeJY1y/eBHRfoa6SEhIDMT66ipiJp04NyCBtCuDzL7jvOobpynaA7L5/dTOnuTPEBtBWA8ZYdr7u/5e2sd+kKQpfLYQMbm05pi2/c7t27h16xbeeOONkZPXxwEP9kepyI2LHr/Cr2WI7bcdBzrLcg+jiQ69p4x6tZ+AX9N1zMzMoM76wzzfx8raWk9lwWTxx8aQielckQhgzcNjHltVVfrsqKqQby0rGJmGgVq1uovWE/g+rl+8KAP+fUIG+0eMJEmwfvcusjxHxXVRr9d7/s5LVQrYF4N9+QtC6KTCMbL5fD9AH39vgGEumMYvD8oGYb8GOSvomPKCZ17GUNwR27Iya6PRwMsvv7zPI+/GkRrl8u+lBt1hxpPr0I+rk9x7sP0pKnDUajXMzc3BME0UhGB5bQ3tTkf8vdlsUtnTASXV8ms9jVZjOAfTNKGAZvZF45SioGD7VYCBtJ44jnH1wgVE+70/EhISAr7nYXtlBVmWYXJysqfptNx4C5QCSuzYf57Nz0dl8xmdpVzhVcBmhvTZCB5oqarak2gR092xf7+SZhnV0GfUwWq1OrgRdMC2nufho48/xnPPPotnn3127GNyqcx+HPXkXPEZDaHxcOyHJjoM+w34VVXFxMQEVYHTdWRZhuXl5R6fNjExgfYA+ihhcUv/Nahj0lU55Tdm3Hx2QoKnr2kaqpXKLlqPH4a4euGCDPj3ARnsHyGKosDKrVvI4xiqovSUWQdlS8olviRNsd1uj5XNH6aUw/lzZYhgWFXFgoHvg2+zH+RFgW6nQzP6uo5atbrrmP3XXAYvs351P2XWUedTGnxyFBg4lnyYYe7TSY76mpyUEdvyY4xrFMuwLAvzMzOoOg4MVcVWq4W19XUURYFmowGiKOj0GeZiyKJFOPM9svw8C6OoquDqKooihnHxoN+2LNpsxmg9fhAgCkNcuXhx/wsiCQkJZFmG9Vu3kKcpbNvGRKMBoDfIJyx7Lxpr2fc5iuPxs/lDsrIKAKXPvg6aWC72sU97xq+x2+2iAG32rZQm/vaj344VRYH333sPlm3jtdde2/ex+4/DA03g4ApvPftHaar6CHooh6Zp4voH0UTH8dn7DfgBqgI3NzcHyzSpslpJ9rnZbNLFYl9gP6qirfFekREwmBQ4UaiMaw/FVFF6aD0OW5ymWYbA9+F5Hq5cuCBoyhKjIYP9I0JRFNi6dw+x7yMtCiqFVirZlfl0/Ty+KAzRarcPlM3vRz+dJ+szygcN8oEd1Z2crbhHBfqDjnH71i3cunULX37jDVQqlX0du99wcQoJLyUroA4oyzJkWYY0TUWTGp9emOe50P3lQ7d2NeDynyUFm1FGU9d1OI4DlfEsd+kkj0GVOUjAz8uvjUaDqipEEZZWVmCzc2m1WuK9PLs3CqNK9hyWaaJgjVJ8kA6AneebHUtjUmo6p/XEMbrdLq5euIBgSBOYhITEbhR5jrVbtxAzfvzc7Oyu95SFHXZeJAjCEJ1OZ2Q2n28PjOFXSv/vz3wfxq9krPJQEAJT10dLNg+w2V/8+Mdotdv46ptvQj/AnJbe3e8MCuPH4X4lZb6FAMLPDPIrZEhiBdgJuPaifZojaKLjeoqDJNMMw8Dc7CxqlYqQfV5dX0e1WgUBVYLiKPjwsFEYgy5q8UZdFuyLTQFR/c7zHIauo1qi9QRBgHarhasXLgxVE5LYwfgj7ySGoigKBJubaG1uIskyTNTrojzFp8ENMshFUdDMZ5LANE1YrkuzogMyDftpdFIZvYIQ0tPAehSBPldHqI/BpSwbvDAM8fEnn+C5557DiWefFQaRq+nwQJHz9XI+gZAfn10HKe23KAp4nNdYosXwjLrHNIu9IBAqMhw8OC1nEXhWoWDBK+dMaqpKpx2z6ginX/Gftm0jTVOkaYogDFEv8UX5cUaC7bMngB4TfJja5uYm0izD6sYGbNdFi2X2uW7+XnsVf2dTiAeBK3tAVZFm2a5zVZXeEfSu4yBJEkRxjDRN0W63ceXiRbxw/jzcQ3JqJSSedBR5js7KCvxuF0mW9QzNEn6F932Vvot5lsHzfWRZRrPEjgOXzcsoY99+RVVFMJuz6bKH9SucEsqbcau12p42sPz3jfV1XL16Fa+88gqaExO7/QrZmUQvuOXMr5TFMMo/0zSlMsMDmpP9IACYeIZaEsUYeg/4Z0MI9clsHwpoBUNVFID7FXY87ldcx0GWZUKOs8LkrEXFeAxfMZb/6YOqqpiamoJlWdhqtZAmCRJ2b9qtFiYmJnpU8PY6Pr8PwxZApmkCnicWUf3blxXsFADVSgVBGNJqehiiyHNcvXgRZ8+fH2uO0NMKGewfEkVRIOt0sLG2hizPKf2mNBxKUHaAXQa543niITbZtNl+HFTRgAf8Oct8j1Lr2QsEoEMusgyqqu7ZNFUUBXKWCSkYJ/Kjjz+Goqo4eeoUWq2WyFSIgLvEHScAlFKgP8xI8IFk3CjzYJ3fZ43tk++f77NMYyrzVIVeMAuOizxHDqoOkY0KmNnxuAZ+nuc9g84UzmsdgypzkIDfZqoKG5ubiOIYpm1jfXMTeZ6Lhcu4ULgTIbvl6AD0TOgUY83L2wMgqio0vU3ThKZp8IMAeZ6j3engysWLOHP+/KGb6CQknlQUeY5oexsbGxtIswyNapVWQ0t0HWB3AilJU3S7XRE42o6DCptYWsah/Aohgl6hjZDd3AsDKaEjqDtFUaDIc+pXWCb9Rx9+iFqjgZnZWWy3Wju+YkAw3LNAwoDsOtsmZ36F+zhBLeEUKUKgYndyo+xXULKj4u/MF2YsURIxuu8wKKoq+vj8IBALIoWfg6bR7Uf5i5Lf2y+q1SoMw8Dm1haSNIVp21hZW8Ozzz23L5lNYCf+GVTRUBSF+mrsnuxeehP9yRZzjm3D0HUqBJGmaG1t4cqFC3jhpZdkwD8EMtg/BIqiQNbtYnNjAwkrs85OT9MAsz8IKv0/ZdJihBDYpgmdGeacUSA4DpMx4ccs8lzoLR8EBLT5iQ//4t3xvGrAA3texuSGkoAZU0KwtbmJ5aUlvMQacvkXmnMZRUaDZ8tLWQ52IeKell+LogiGrsOyLJH1KINXNarVKhqM59pzbez8uMEuZ3j4IJo8y2BbFrRSVqs8pKY8oErTdURRhE63i4LJkRYlY6+qKlRNg8amJfPmtjIV6iBcS37smZkZtDsdNKpVLN66haXVVcxNT4+kWg2CWByBflb99AAFgM6y+4OG6SiEiCYrsOyfW6nQxuE8R6fTwbULF3DmxRdR7Wtgl5B42lFkGdJuFxvr68iyDLquY4InkIZk8wHa5Nhl1UjHtmEaBsiABsbD+hVu0xRFgX7AvqthlFBS8iNFniNjAT635TxzT0Bpod1uF2++9RZNPpSuS2V2tcevcF/Tdy79fsX3faRpCtdxdk3f5VXPSrWK+jCfQn/p8Su8Il0WzHBY9b/fr/DqNre1mkKnHLfbbSFHySsUfAGiMb+iDvIrpUB5v7AsC3MzM9hqtdCo1bC5vY31zU1MTUzse1/0VHZTY3mFiV9vnue7evBEBaW0WNPZEK4gCJBkGdrb27jyxRc4c/78WFOTnzbIYP+A4IF+0O3C8zwkeY752VnBGRzHIOu6jlqlgla3iyzLkCQJHNved3l1GLIsAxSFGgJN2/eXnQDodLu0abgo4LguwjAUQf7Abdh1q6oKFdQ4Xr5yBVPT0zh96pQI7nuC+VHnUM6890EM0zqgwxHydEP2beg6VIXKTg7TkhYczaKAWxToMhmxgk0J5AshQghyZtCzctYHO5l/bqi5c1L3OTtAVVU0Gw3MzsxgcXERXqcDBXQBetBmaL7I4fckZ1J7umEgiePhkzN59gwQiwPHcRBGEZVt7XZx9eJFPP/iiwOdpoTE04giy5B5Hlrb24jjGDkhVGazFCQN8it+EPQMXnRdF1vb28gJQZqmMAzjSP1KvwrPfpAXBdqdDpI4BhQFpq7DYzLOgyiE5SCe04aSOMaNxUWcOnUK8/PzuxJHe2JEtvswQxrLi4ZhfoUn3kzbFhntXe/j9KOigOM4dJIwS6TphrGjisboNEWeI+1PyvAFAPct3C+Pe48YNF3H9NQUmo0G1tfW4Ps+iqLA1MTEvv0KP6rCqtgAfZ4UJgCh6TriJIE7oBolti8F/KZpIstzxHGMJEkEh//s+fOwh+zjaYUM9g8AHuiTLMP29jYts9ZqqLgufYA5paTvCxUEgaB6WKaJarWKglDlHT422rbtIzHIBEypRlGgl4LGUVnjnJUYeeOR53liCmqlUqFfytI+FLbvnmw1+53v7+LFi4iCAN/4+tfHm6w7AMPuhdD2PcJx5uKYpc9u1BJJlFFVFToArdFAh02StS0LquuC8CoBr4QUBQjLWpE8p/+KAuBNtCVHpKgqdE2j/3R95AKA9zrMzs5CIQRRFMF2HKysrWF2evrA1Z2yYhRAs4a8HD0oC9N/f3iGy2CNWEEQUPUNz8O1S5fw/LlzaDSbBzo3CYknBTzQT+MY3U4HcZZhZmoKtmUNFXcghMDzfTHd1LFtuMwPGaaJOI4RJwn97h+RX8myDIQF6UqpgjcMWVk4gclrpmkKhanO8Cny/Bp5ppovKDSm2KKW/Mp7X3wB0zDwyiuvjDVZdxdKyZae6yOkZ3ruUaO/SjqMgsOTPdA0GABQryNgSn08EOb2ngf7efknIVDY51SmZYpkHPMpGvMro66VV/Hn5uZw+fJlpEkCKAo2trYwPTl5sEQS2ell5H6l4rrI8xxJmsIZ0GMi7iF2ePwKIGbARFGEOEnQabcph//FF2EPqPg/rZDB/j7BA33kOW1YTVPa0MLKrGUuJUe/QbZtG1XOvyQEpmnCDwJkaYo8zw8t98VNWMYaX3VdF1ls8DIhIHj1gl/PsyqKgjAMEccx1U+vVuFYVk8wP87EWs/zcOniRZx94QXUarWDXcwQowyU5N/uh1HGwcrcuq7DYk42CALBS1cVBeqAYJsAuw116XelKJDkORL+XIFmWnRdF8aac/3552eaJhzXpVkgTUOW51jb2DhwwM8XeCkbfGLbNlL2zKSsCXDP7VUVKstqua6LIAio4/c8XL98WQb8Ek81iiyjfoUQtNlUcsey0KjXe+djlGxuURTosKowQBsXbdsW9t8qBfsuU+k6DPiiPWcZZe4DeOBF8hxEUXYSRuyfaIQFXeinaUpV5yoVmCyby4P5vewTAbCysoK7d+/irTffPFigj+FJLy4WISRM7wPKDafjwjJNJGwyeRiGwr5rvMLSd984HUhQovjvrLE6Z36fQ1UU4Vc05luAHeoRADQbDdFArDIa7frmJmampg50rxSweIqdh+s48JnyUJZle3+27HlWFaVHh58H/FwMQgb8FDLY3ydy3wcY567b7SIplbP4l6LfIHc9T2jBVkuDh/jXXVNVWIZBpwf6Pur1+qGaaUWjEVdMYI0+PGPPlWN4WbfMM9Q1jQZwTD6xVqvBPkBGngD49NNPYTsOXnzxxQNeDYYG+lxhob/x+cigKLTRtMQFHReO4yBNU+RFgSRNd2la9xwG2KFZ9Rm3ghAh95bnOXLe8MxkRQHGIWUVFp6h0TSN6iJ7Hs6/9BLW19eRFQVW19cxNzNzoIA/jmMUeb4z9RB0CE6WpsAYz4fCeyIIoQG/bcNnAb/veVi8ehUvvfaabK6SeOpQFAUy3wdYkBP4PjJCMMd5+oTsnp/CBB7yPIeiKKhVq+K7w6kwXMO8KAoEYUgTTAdEj18p9YHleY4sTalfyTJkSYKCNYXybLKiKNBUFXGawjQMuohpNA5kh/Isw6effILZmRkcf+aZA1/LIHEBoDSR/T4kkAD0VMb3E/ArigLXddHpdqlPYT56GFRFAQb4FQL6vKUssViWDi1YXABFoc+QqsLQNBH8G6aJCqPyLhw7hq3NTcRJIhJJBwn4oygScYeu6zB0nQpijBHsC0qQpgFZRp9/QhBGEZ150+ngxrVrOPfyy/ft83ycIIP9fSAPQ5A0BVEUdDsdKm2mqmJKrqAs8PePMMgAehRpKpUKUrbPKIrgHKDBpGyQuYFP4ljo0APoaYThXD6eJdZ1HXEcI2Oatq7rHijQB4ClpSUsr6zg7bffPjB9ZFRpuDw5974E+6CfZ77HeQzbznYcStsKAqpedIBzVBUFpmGIxQLPsmTMwabMyfKmJj44R1UUOK6L9Vu3oAKYnZnBxsYGkizD6vo6Zqam9hVU53mOiFWlXMeBzhq0FUCocozzGfBsWVEU0E0TVZWOZ0+yDJ1OB9cvX8a5l1++bxk1CYlHEXkQiKRCu91GXhRwLEv4gP5AP01TquRWFFCZDHLPcCu+sFYUVKtVdDodxHEMy7JGJh6GQVg/RUGSJAjDUASFYMkG0VCqKNBLWWKegAiCgNoqVUW173z3gytXrsD3fbz9zjuHsvvDtuUUnvtmg1ij8J769AOgaxosy0IcRaJqvN87oIAmF1XL6mkgzlnQn7IZNQWr3uRZBjDbr6oq3GoVm1tbOP/SS5iensbG5ibSNBV+ZT+fa5qmQh+fz3/QdB1KmiLNMozNuCc7KksmU8ELmKT59tYW7ty6hZOnT+/nNj2RkMH+mCjSlAb7oJmTLmvK5Vl9BbRTnAeGaZZRxZ0hBhnATuYD1KDzbGcQhrS8uY/VKAFEABhzzXffR8FoFwToMcA6y/qI6ysKxHEMnzUPu6574I72LM/xySef4Nj8PBbm5w+0DwAjKTyHbc4d6/Clxdh+YZsmkjhGSkiPRvK+zwHo4XVyCU+N6ftzdYeMZf4zVrLlGveb29uUNlat0sFtRYHVjQ3MTU+PHfBzriinKAGMGgYaWPDF4d4XQxfDPODXVBUV1xUZ/vW1NVTrdZx47rl93ycJiccReRyjYBzoPMvod6EoMMMobQp67U8cx+iywXS6pqFWq/X4Ca6CxuUiDV2HbVmI4hie56HZbO4rQCwIQZamSJiARJQkCKOIqoaxJJbOePXcr5SHSRaE0FkycQwQgkq1eqAFB7BDCz334osHp4Wy8xqG/EH4FZQSc/uEY9tIk4Q2pUbRgX00p6kSYKevj9GoHNsWwT/3K5xeWqlUcPfuXSrvyhKYrU4HWZruiypKCNnpX7SsnaZlw0Dg+6ICsZ9FFw/4DcOA7TiIoghRHOPurVuo1WqYmpnZ9316kiCD/TFQFAVSFgQriiK4+jyrL4wn+/LGcUwVd1h5qt8g8332q8zYtk1LWGkKLwjQ2MOg8eaWJI6RJgnKuQKurW8ZBmq1mvgyD0Ne0Il0BJSGchjpqksXLyKOY7z6jW8cKvuyVzMxcH+aczl4A9FBjDJAF0ytTgcJG5p2UCfHjXLOeJhl6hJXVzBKKlA5W7gR0GfRME0UrAzcarWQE4I79+5hYW4O7h6LkDiOhS50ecHClRAixiMd59pI6Sdv7DNKAX+SZbh57RqqtdqO1KCExBOKIsuQ+b7wAW02Rd2xLCqx2Pf+IAwRBAGAnbksgwZlCV14Bsd1hUJYEAR7Jh4KQpAmifBFPdrobGFvWhbq9Trldg+z8YqCJI4RsaCu0lfZ3i8+/ewzWLaNc+fOHXgfo9TdANzX5lwOpTSHZL9QFQWO48ALAoRRBMM0D7UwIYoCwvvDykklRgHinxbP/teqVaoSlecgTNXHtW202m0USYJ7y8s4Nj+/JwUnCEMRzJdZDHyAJe/32O/zwn02ZyRwDv+VCxfwxptvPtX8fVkvHwO570NhXwZS0Il/aZ6j2WjsWnmGYUgzL4TANAw0Go1dhmOQQeaoui6gKMjSFAFTwimjKAqq5e552NraQrfbRcwCfQV0ZVypVFCr12ljrW3DYNNfh6EoCngsW+Q4DuV2HqCJCAC63S6uXr2KF8+do0NgDgjOqxwGMRn4flI+Bigq7Qe6psFhZcWQVYX2C56pyxldR9njM+EKSXwRqjHFC9MwoGsafR5VFUWW4eadO1jb2BBymP3IsgwhewYd2971rOu6DhW7px4OPbcB50pY026FNZzFaYoLn38umtklJJ5EFEWBjNlcsKZW3/eRFgUm+rPvhMDzPBHo27Y9NNDnFM0yVEURtjiKIsSsf6yMPM8RRhHa3S62t7fR8X0kSYKCECE/XK1WUa/X4bouHMcRCj/DkGUZwiCAoqpC5GHU+0dhaWkJKysreO311w8ViA/zuxwiiXQf/YqKHb34g8AyTRiMvsoXUvsB961C6nRMCqau65Q6RAhstiDVdR2GYaDRbEJVFIRRhBu3bmG71ULEFgX9SJJkh77D5gaUwXtN0gHbjgOe4bdMk7IaCEEQRfjx558PPJ+nBTKzvweyIADh/ESwSbJMgaec1ScAPN8XwZFt2wMfZDHFb8jKno8394OAGkrQhz/hHO1SYEUInaJnGIbgdvPj8fPYc6ASIfCZVKSm63SxgZ0GH8H/HBMff/IJ3EoFZ194YexthmFUoH0/ZTfF8dm/g2b2AVatYUZv3LIrryaUM2riXqjjTdnldJskjmGwxiew8qzjOFhfX0fO1BTyPIdt21CZQTcNA1DocBlB3xnQu8Gz+XlRoMDBMgcKm//AA37+3H/+ySf48ptvSv6+xBOJPAholY59jzssq2/3DQgsCEHb86jcIXoFHsromRw7AKZhUL43o/OgUoGqqiLwKiv+EFaRNk2TJglKVbuUDY/cqweJFAU8RiM1TVNkb/m3ea9kThlZluGTTz/FsYUFzB+GForRlEyubQ/cX7/CJVAP7lVo1ThJUzrZdj+V1T6/wqFq2lh9BLZtgyh0+u+E48DQdRDHocMnTRPrGxuIGId/cmKCBu6sH9A0DBRFAZ8tWsv0nTIM1jt4mMCcf6/Kspyt7W1cvnABL73yyoH3+zhDBvsjUKQp8jje0ahnWf0kzzE9MdGTVfZ9XzQxViqVgQ225UbGQV84Dtu2xeCRrufBME3YvJxF6IhygxviIUaJB+l7BUtBGCJh+vk8o1+G0HUmBAW/hiH7unPnDtbX1/GNr3+9ZxjTUYOXFIH7n9kHRn9We0Flw6R8thAcVnYVzVIY7QR5k+tejlLVNJiWRdUOStA0DY6m4cQzz2BjcxOe79OJv6y3o0gSRFGEIAwFf3OYigfXwyaM1zlIWrT3IoecM3u9HPC3Wi1cvXwZ586fH71PCYnHDFkUgSSJ8AVZlsFjWf3Z0mRSAgjKKBg/2hpAaxATSDE6gKxUKsjzHJ7vo9vtwrasHvqfYRg0cTSCGsIDwpFJJEKlpvM8h6ppu+0HC3Z5nxsfSjgsgXHx4kUkSYJXX3vt0EHyqMRNuTn3sDKle+Gwe9dUFbZlIWS2ul6rDdxnuQm3PO190PmUew6HwbYsKICYv8O35Vl/x3GwtraGMI6x3W6jXq3CsiwU7LmLkwQGs/PDBmfpui56I4uioJOQx7gnvRfEtmAZfoAG/MtLS2g0mzh+4sR+9/jYQ6bNhoDLoZUfMp7V1zStZ+qnX9KkrzHqTD/KQfKoQC1lw4aiKBJBbcT4bRXXxcTEBC2l2vZIfXmRoRhhtLiyAghBtVodXR5l2roa+9lvNLIsw2effYYTzzyD2bk5ajgOiL2qCWWJ0/uZ+eXNsYdS+yF0mJRuGLvKrjyw5xmlYo/rFue1Rymaw7HtXcF+eR/TU1OoV6uimZdXioIoEtN+C+a4Y/b3fvBGXc7rH1USHrpoYqpQfH+ObQOE4O7t21hdWRnjSiUkHg8UWYYiDHu+Jzyr79r2zsAkMH+TZVAVBc16fXCgD+wMyxry/SIA4iSh9FMmuZjnOYIwpOo41Sommk3UajU4tj0ygZIzqtCwya8ArSonaSr84VD7yc5bVeiUd4WJD5Svotvt4tq1a3jxxRfhuu59C/SBks+839VEZicPSuPhsG2bJlsYtZeDYIf+KfwK9paoHmeBY5a48IOgaRpmZ2dpMM8awxVVRcEoPnweTJKmVImNS4CXoCgKZSkA4vkfhWJYRYJR0ACa4TdNE4QQXL18GX63u+e1PmmQmf0hyFmDLQfP6mdFgYmJCfEQRVEkArhqpSK+DGWIh7m02iyjKArELKNafnArjiM641VV7TXse2Avw5XnOXzGGbUdZ/zhJOwayk2ihBB88cUXyLIMr/AS2SEN2Ti8yvuuncs/r8NKvBV05HmWZYjTFDrT3j+MsR9Hvs1iFKJR5zY5OQml1YLv+2i3WjAtC47jCPoYn36ZZxlChQ4vMU1TLDR1XUfEmniB4Rkirq4w9F7ynhhW9ufzIC5/8QUazeahGsYlJB4FCD39EjhXPy8KzJaGyvm+L6g7Nd4I24fyVF32Qs/fuWRunCQ7GXlFQb1Woz06LKPOdfzHsXLl9w9CmiQImdDDngmkPpR9CgAUAD7++GNUKhWcPXNm7P0MP8DozLWoFt9nvyKu8DBJJLZgcGybVo3DEIZhQFWUkRn8vaAqCvIR1XtVVWHZtmAxDIKmaZidmcH65iZIFGFzcxOu46BSqYiZCznT+k9ZMG/yilLJr/C5QBboc1Fgd88ab7geiL4FlW1ZVLEuy/D5p5/iK1/72sFlwR9DyMz+AORBgKKviUlkWVQVDaarHyeJ4J/ZTMGm/0vCS6w9E3Wxo6TT9Txst1oIgkAEQxZTOmg0m5iYmBCKKb7vww+CsYLEgmVgBq6KeZmVlW7dQwZSYRhi8eZNvHj+PJ3sV772g2APQ/VAKDxlHCIoJ4SAsAqEyRZU4Zif4V5Q9qDzOHsYZYAF/BMTsC0LaZ7ToS1JgmajQRvyajXK11dV5IQgThJ43S463S7iOKYqT4CQZgN2y4WWDjb0PPhYd/688obgJE3x448/Hp69kZB4TJAHwS4Vlk6rhbwoYJey+gGrFAM0YDZZlrOMXYE+IDK4cRyj3e2i1W7TCjGjQti2jUa9jkajgcmJCZHp7LBK8jjgxxiURMqLAh4L9G3bPrjyDrMF62tr2NjcxGuvvUYz/zgchWcvm/vAMvsMe4ktjAKn5+i6LuiTXATiUJXokg0eBtu292wMVhQF05OT0FUVeZpiq9UCCEGzXke9VkO9pMyUFQWiOEan26WS5kkiFrflHsVBn8qed5D5Xr6Q5PGJ53m4cvHiXls/UXh6ljVjIk9TZFHUG5zzrH6ei6x+mmVCwcayLFQ4/4xlckU5si8Tz8uncRz3BDBcw5wPhSiDly+jKKJSiGmKarU6ksYzKgPj+T5dUasqVWk4JD/x0qVLMA0DZ55/XnyphEMgO1r1oyTPek/+ETPKY76v7EyEZCd/HsAy7UmCPM+FHOdhz2tUY5Vt21jf2Bh9zqBOwjBNVByHZgLjGFEci4Dbtm3Yto2UaW2naQrC1DvCMKQle1VFmmWCasADfn5PxgnWlb5ys+s48HwfrXYb165cwQuHmcQsIfEQkUcRihJPH2BZ/TBElueYZhrgURxTaiWo3R9K3UFvUJemKcIwRJymPfZANwzBzS+/X1F2FHqSNEXABmVVKpWhSRSeQAIGUD5KQg+6Yez4w0PgiwsXMDU1hbn5eWGDVXry1E6Uepz2CnDHed8DqxhzMPs4zrnTX3ay2OXeLseykKWpGJx22PMvV+wHgTd6jzxnQnX0HddFkmXQ8lwMAuMzhLjEt/ArWSYmxkNRECcJNE1Dluci1umXwx7Hr5RjD4310IVhiKW7d9GcnMSx48fHvDOPN2RmvwTB0+/78iVJIpp3GvU6MjYwCwANkkoNSD1BTqkclue5yOKHjIMPRYHNsvj1eh2WbQ/84hNCUHEc1KpVWmZjzbvhiC9cUcool8EXDCoon/KwAbPnebh58yZeOHeud4oj/4VlaZQS118pvdbzXnqxex7zQZVbh4EbWsG3J4Ry3Lnz4W/s+yxVVrVRFKpmcCTZfQzP5FgDGnTLyPMcHsukAMDM1BQm6nVoqor1jQ3xOgdvrKrXapRWo9AJw4TQwWGtdptO1iyfHzPOYxllzvln3xtN0wR95/biItZWV/fch4TEo4Y8TZEFwa7vacSquRZbaMdJIoYa2rbd0/vVYytLAWKapuh0OjSLz6elqypsx0Gz0UC9VoNpmgNtBJ/qzivHKZtknQyQ5gRKvVKMW18GH4ynKMpAoYf9Ynl5GdtbW3j5pZd6ky0lGmmPX0FJTIKh37ruFVQ/8Iox0HOfBNceEH6F93H101XKvoPLX6qq+kAkix3HGXmcNMtocpQlFOfn5lBjMdLG5mZPtl5hFJ5qpYIGryIzKlJeFAjCEO1Op3cbtt1ICk8fRMwBqkzFFecuX7gA7ynh78tgv4QiDHtLayzoCMMQeVHQDDsre/ISWm3EyGpFUXqC/DiOUbDtqpUKJppNuJXKSN4YXzQA9CGt1+tCZisIAnQ9b1fjo8jA9NF40izrGZx1FHy1i5cuwbIsnD51qv/iR26niLf1LgLKwXKPcSv9fj8z+/x+k77fgZ2GJ9If1GN00F2+F5Zl0QmyjJN+ZBhwbJv1ewzSwecSfHmeQ1NVIek3NTUF27KgqSo2trYGbquqKqWa1WqoVSqwLAuEEKRsGFyHNQKKUxtyfntdiwLaWMX1vK9cuDC2pr+ExKOCfECgrwC0EZ5NJU2ZIg/AKsVDhv9wO8MDcx6cE9DEE2+2dR1npHxkWTDCsSw02CK/IARdz4PPpmb3bMMGQfbb3TiOaVKBENSYpOdhceHCBUxPT2NmnKmnPEkg/tuXXAJ6qh09mfJShpj/fl/9Cr+n/PcBQf04Ca/+58lmiUJeOT4s+hdOPccakkQioM3ZPpNc1TQNtWoVtmVhemoKhq6jyHNsbG0NTP7wAVv1Wg1VNhuGgCZbu74Pz/d75sEcNFWmgN4vVVWR5zkuffHFAff0eEEG+wx5mtKx5SXw1WAQBMhYk2Wn0wFhk99qQ+SuVEVBURQ9QT5Ag/Umy+IPouv0Y1C5VlNV1Gs1we9M0hTtdrtnUMqgDAwfnEUIgWVZR9Lw2O12cfvWLbz44otHlmUvK82U7w7na/JufmCwFnI5q064AS8Z2h6D2vcaN8QieyZ2yl7ntJxDQGXVHEVRhOLSYVGWRy3DtiwohPRkYfKiEDKgBIBhGJQSxhZ+iqJganISuqaNNMwcfOFaqVSgM0oR5+52PY+qfxykYawU8DvMkUVxjGtXr+5vPxISDxF5HPfy9Nl3oSgKJIzKaVkWrRSzHqphwwgV7GTyO+02nYoLujiYaDRQG3NC7SD5ZF3T0KjXxTyNiA3YKi+u8wEUnizLEPg+TSC5LvRxhR5G4N69e9hut/HSSy8del8AaEa3FMCXG2R5gqk8TKuH+tpXfRZJnoP6FfT6qEPx60vQNQ2GaUJlfuUoMEzm2WYqb+VXM0Zr5r7GsixUS8wBTdMwNTlJh2UlCba2t0ce1zAM1KpVVFyXPm9FIZQKedA/SgZ8wE53aLXsvvMYqtVqYenevXH39NhCBvsMRd8XhGcjEz7cgRAUeS50X+v1+sBGljzP0WU843KQ36jXUavVRvLsyxg2DZHDsW00ajXRfe95njDORX8GhgwenHVYXLx4EY7r4rnnntv1t4M2H43UmMcO73KYFnI5QOeNOf1ZeAx5bSQOY5j7rsm0LKiahoIpEhwFFOxu2LUdB0Rh03sJQRhF8LpdWm4HfYYGDX7TNA3T09PUMKcpNkcYZoDpUrMG5FqlAkvXgaIQDoCXdMe9e+J8Shk6bpiX79xBu90ec08SEg8PhBDk/X6FPdtckIGrWYlK8ZAEEg90eCa/HORX95FN32uGR9V1Ua1UaNN9nqPNmiazPN+lsT9scNahQAguXriAudlZTE9PH35/bJ+jsuU8868oVAK0573s93ICqlyBPgq/ciBPOeB6eBIpYfKqR4X+pBqfA5RlGU0eBcHOXAVFEXOG+p9j0zQxyQJ+TvsceVzmVyzTRK1ahcGSSWmWod1uw2ffobFjjb7qj6Zp4pm9fvXqLtrqkwYZ7INl9YcEXUEYIs/zHunARq22i9fHg/xtFuQroA+3CPJZ5nScx5L0GZhh0HUdjUZDPLBZlqHd7aLjeSDsi8evYdTgrIOg0+ng9t27R5rVHwcPujkXGFxhOQxURYFdysIcRXYf2MnEcPABKF3PE+o5IpvP+ZFDYOg6zcQodDbAdqs1+ril7JnjOJQrbBjI2MCtwPOonOA+aTi8YVfXdSqdVhRYvHbtaClQEhL3Af1Z/TKdLQxDZJwSOKJSnHG6TrtNgxFmO3iQz23vOIP/xvUrlmmi0WjsTOFOU7Q7HVoZLgrqV8geg7MOiDt376LV6eDlo8rqYzyfmz8Ev8JxVAO8+NRjVVWPLLsP7KZhWqxi3G61aPKIzVSwLAu1Wm3kNF/HttFoNKCpKjrdrqCuDQIX+ODDQSuui3q1KuhmKZsdEUSR6KkceR0DqHSmacIwDMRRhMXr159o1TcZ7APIw3DnQeCUA26UgwBBFNEHWKEaxeXgNmfZja0SXcfQddRZc1Q/L37cwG7crz/PejZLxjmNYyGnFjHFFBBClRaOKDC/cPEiKq6L5559duDfDxK+jnNvhFE+IgO5Hxw42B+wnWVZUI44u08PpYgKSM7KlhHL7GvMKVdcd6wmNNu20Ww2oSkKup6HLlOfGgSVUcbKA89Mxus3TRMENHCJfB++74/k3g96Drgz0TUNmxsbWF1dPbJFkoTEUSPP811ZfQ4+BMnzfZiGMbBSzEUgWu020izbyeQ3m6gOSDbtSQkdM9Dn4H08jVKPWBTH6Ha7iJOEJpDGGZy1H7Cs/sLCAiZKk4QfBB5GEmkcbv5+YbEET5KmR9rfxJ9N0XvAsvPl5JEzRGCkH7VqVag+bW1vD12YqKoq9lem7jqWhVqlQmfVgFLbfN9HEAQjKxq77jbzlVx1bmVpCVtbW3ue/+OKpz7Yz5MEKD0gPXJmTEc/SRLYjoMqe8CAnWaUVquFkEl1GrpONWSZgRzY5DKGUT6I2SwbZ61knFfX1hDFMQw2DOkosN1q4d69e3jp/PmjNY7jZKcetDxaz8HHm3A7DhTG3edZmKPaLyFEzG+IwpAaaUVBxXVRK3Hzx0W1UkGtVoOmKFRJaoRhBnYyjHywFm+64nxigp2BbmK2RD/6vzecZ0kIHE7nuXtX0nkkHlmQJNmhF3CbXqq08gSMZdsiWwlQv+IHAVosk88bbyeaTTGkSunjoO95LvsM9MvQNY024rNjE1Dp5rWNDcRxDNtxjswW375zBx3Pw/nz549kfxzjWFZuhx6oEg/DQT6XYUE1z+5rrMfpqFAUBZIkQafT2ekPVJR9JY/KaDYaokl2Y2trqAKUqqqAqorPh7MrNE2D67qosV6xghBBGw1H+dMB8Rjn76dpiqW7d4Ui1pOGpzrYJ4QgLw2H6C9X8aEkhmlSWSg+BIJxxoIgQEFIb5Df16BUbjgd53wOmx/RWQd8pVJBmiTIWcNkmqbwPA/ZEWSRL164gGq1ihMnThx6Xxzjymjxlft+nN2BMcQw7BtDDI/FSq58fPhhUBQFwjBEp9ulGRfWtwG2CB17QvIANBoNqu6hKAMlOYEdJ8lVLfozLD1BP6uS8WdybK4k43C6joPO9jY2NzePtFwtIXEU6M/qlyvFANDa3kbMEkhlimeSpthutcQzbbIgvzZgEm2PXxlHveVwl7TTj8M01os8R0EIojCEv0dGdRwQQnDhwgUcP34cE6VJwv3vOcCOx7o/PaIWDxpHXKXmssjZEWT3c6aP3+l2EUURFNAYA4TAtu0DK/rxoVuWYQCE7JLk5FBLfqUYkGzTNI0msljQD0KQMKW5QfsbdKc5f9+2bWysrWFra+uJpIk+3cF+mu6aaMiRZRk67TZyQjDRbMK2LJp1CUO0Oh1kzNhVKxU0Go2RwRQfRT7KWI0ruTUWWDOxwYZ91apVANSZdDwP7U5HNIXtF1tbW1haXsb58+ePjMMOjE+R4Znjh5GBAQ5I5RmyjaIosFh2Iz5gdp+XMDudDuXkM/6vw6hd6kEbwPowOTkpJDnXBxhm3gydFwWyohg5bt1xHCrRp1Ct5DAMqVxbn2rJoOeT8/dNy0JrY4OqY0k6j8SjhCQZqA0PAFEY0kAkzzEzNQVT14XcZbfbRZHn4Pr3tT7K6C6UKHvDcBQJpPLxSFHAtW1UWEaXgE3s7XTQZdO3D+JXbt66BT8I8NKorP4BbO9YPXJ4uJl94GCLsWGfu6aqVATigMo8hBAqd8meSf6ZapoGt1Kh8cQRxCuKouwpyck/jzzPBYV3EHjQ7zoOFNDP0/d9IU4hrm3wBQuZZ1VV0d7eRvcJ1N5/qifoiuxLH0+fFAW6TPVAZQ9kmmXwWUMSl0irViojtYx7UOoJ6MdRN4BmjBOq6jrq9brQW4/iWKgLBUGAMAxhmea+pu5dvHgRjXodzzzzzJGcK8e4ZoNnkB5GIxXAlBiOMLi0DAOxpiFnUwRHNc1ycJ7/rinMbFgIn5bJG5uOYhHJJTnX1teRZhk2trYwOz0tPgcu0Zam6ViqHLx/IE4SRGGIDFTK1XYcWKZJaUAjYFkWWq0Wpthz7B6RwpSExGFQFEWvXynZqSLP0e50UBQFbNtGvV6ng7SCQMgEc439cTLMYpoolxXsw5EG+qAJsDhJYFoWJptN6IaBLE0RxTHSNBUTUDlFkc8U2QtFUeDSpUt45plnUK/Xj/CMx0NZg/9BZPYHfiZDPsOR+xlhI23LQhLHyNhnMqpplqMoCsRJgjRJdvyKQodemXzeCSA+46NoZuWSnOsbG0KSc3pqSvydPz9JnmMcErJpmtANA2EQIElTMZnXse3hCVleJSsK2JaFjbU1NCcn6bTfI6I+Pwp4aoP9PI5BOCWkr8wahiGCIAAIQbVaRZIklKvMjHfNdWGySW/jQlGUgVWEw/AphyHk9CJNg82Cx/LKN45jRCxQjNjvmqaJL/WwwH9jcxPLKyv42te+dqTnC/Qa3KHvKRnDYYsswvaVM8MFsKZerrF76BMlQv7zKMAdY5BliOJ46LTLgkmOpbw0y58bRYFhmrAGfG6KogiJz6MAl+RcW1sTkpwzzDCriiJUq8a9P6qqwrYs6LoupkpHYUgXDI4DfYDGM78usMBo9d49OI4Dx3GOtNIkIXEQFKxCt6tfixD4QUCb5UGpcb7vC16+yvyKsc/gYtgzf9TVLkIIAtZnYLOACqAJhqph0ECR+RIu8xsyYQud+5UhgfTNmzcR+D6+/s47I8/hKLPfZfRo7A/bDwBSGlDIZSe1vtjhwDhAsD8KGht8GDORDoNV9/vBE0dJ3zAuVVVhsj6//gWbxp7to3rGuCTn5uamkORsNhr0PBQFOZvEOy5URYFbqcBgcRspCgRBAMMwRJ9A/70moAs9jSnLba6twbbto5N/fQTwVAb7hJAdowz0fFnTJEGcJIijCFBV0YgLQmCyrMtBs8oKdrTiUfqyHGWIEiWJ4H9XHGeXIVIUBbZtw7ZtpCwrkzFd3jDPEUbRzhfdMHo4eRcuXMBEo4Fjx44d3QkTgjhJEAaBWHhEUYQ4ipBlGQijhfCJs2mailkHRZ4jZ7MP8tLvHHzwxvf+8i/ptWsadFWFqmlQ+37X2O8a+13jQTIhgltr2zZsy4JhWSOd135hGgYiXUeeZbTpjWXGhSFOU+T9tBlNg2VZVM1jhLM5atUiLsm5sbkpJDknGg0hkQlCp0FqYx5XURQYmgbVdZGkKaIoQp5l8LpdOJZFqxQD7jPX9e96HjzPQ6VSQXWIQ5OQeBAoigJFHO/w6cv0HZZlTZIEhAUwcZKAEALXccZWMhkGhVFs7pdfCZg9VlR14EBGTs9zbBsJqzryTH+aZQjDkA5+6kso5XmOi5cu4dlnn0WtVjuy8yWEUDW6MNzxKcy/5GwWDfcZvCrBtfb534b5lQLAX33vezvXruvUZ3AfoqrQdF38rjB/IvxKnlPRhEoFFTZh1rJtkWwbO77YI4Fl2zZidr1pmorMdp7nSLgv7eu10HVdyFEOex4VppJzlAtKLsnZbrfR6Xah67qgiQHYd8JKAVUJUjUNcRzTDD9LlA3L8nMfZlkWNtbXMTkzgziOx6q2Pw54KoP9IknoFxu9ZTtSFAhYhjFOEoRJQiXRmMbrYUs6pNRUJag7h9pjLwpCxDRD27aFKs8wGIzywRVckiRBxoJpLtupKApM00Sn3cbq2hq+/vbbe54zAWh5N4p6DS0L4ssBfRRFYly4wrY1dB0WMzgqD8hZc6bBHIVt28J49gTr7H2qpiEIAnz88cd46aWXBJVJGHC2gOCvFawaUDAnnBcFsjxHmmXIVld3mkh5+ZLQQTJ84WTbNixmtG02oZgvDvaaKlnO7vPnjzuZMjTmLA3DGJt2xQdt8Xt7FOCSnK3tbXQ9T3w/VFWlvSxFsb+FEKtAmIyPH4Yh8qJAyAIG27Z3XS/PhtqmiZWlJVQqFbiHWIhLSBwWZAg/Os9zYQOTJEGSZTDZcKHqARSyeo7JfipAj2rJUdN3eEXCse3R1FXmL0zTFAouPJjO8hxZKaFkmSbu3LmDMAjw4osv7nkehGmrc//B/8VRRP11GO74mTgWGXvhVwyD2mPuT0p+xWLVCl4hVcv+pBSoR1GETz77DOe/9CXYtk19CPMlRZ6LxFTPgoH9zgUzeOPs8vLyTiMoq4wqigLLNGE7Tq8fsW1YzMfwxYE2ohIB7ExrD6IIvu/DsiyRLCt/XjoTcDB0fSz7eb8qqLVqlSrq+L6YsMtFUXhfxX7se3lwlmEYQrgiCEPojG66a3+M+qrrOtZWVmDbNmZmZo7qEh8qnrpgvygKMS23/6ENwhB5lqHb7SLng04qFTg8iOAr2YM+7CXqRTGiifGg8Bl9R1NV6Jq2r4mlFqOCgBCkLOBN0xSEEMRxjB9/8QXqtRrcSgVBEEDXdWiahjAMaXa120WHNWl1u11aPsOOoeWGhxuuZrNJDZdtw2R9A9ygDZsyzGcGGKY51hCXbWYw5ufn0Ryi8DAKEStFcwObsMxQyKTzojgWCxbf97G5tUUzWiUDzj/zWrWKer2Oaq2Geq2Gaq0mriHLc2RpiiCKkLIFF19YCkPMFj77BW/QVVR1LKrUuKhWKsjSFK1OB9utFh3VrqpQ+rJg40IBhPOqViqCOpeBSv1VXHd3UMR6Zzqeh26nA9d1HwrnV0KiyHMUrJGxhxbKEjBcbrYgBLZl7UwZPUqRg76fRwFCCLwgAAFgMkrOuPtXWRXAtu2BCSXP93Hx0iUsHDsmKui6rkNVFPhBgG7Jn3SZf0nStMev6KzCyQPgyclJkXjhyRiL9Q8MS5B4vo+UqSPt1W/UYsMF52ZnD+RTAFD6VprCdRzouk77lqIIEZvpwxNicRSh2+1ifWMDMRvCBkDIEEOhAz6rbHBnjfkW13VREEIz+lkmnr8sz6lvLSm06WMG+GWUn1m1tMA8Ckw0m/ScgwDb29uYm50Vx9hvsA/sKCzqpR6xmLEZ/DyHy/T+dzZQRLPu9uYmpmdnEYahkHx+nPHUBfskTQcG7SnLCIRhKIxZs9FAhVMDDhvo94HrnxNCKJf/kPtN0hQJU9hxHGffk0oFFEUElzzwX1ldRavVwrPPPotr164h8H14rNOdZ591TaPGpl7H3NwcLNuG4zgiiNfZ3IFBGNdYPOjBJ+VMuKqqNNviOGg2m/S6h1xPnuc028SMNlc16HQ6WF1dFcNoCOi0Wdd1UalUqO4+k6XkCk+HvVZebuUc4iPT8wdQqVYRRhGiJEFrexsVtng5jPHnixLeEBawLL/v+3Acp7e6xjI3lmlibXUV1VrtSAfHSUiMC8K46igH+kBPUoD/rTkxAZcHD0fVS4Sdapf4jh/Bdz3i9B1Fge04B5ZyLCeUeCP/tWvXECcJHMfBpYsX4QcBgiBAwDKwnIpRr9dRbzRw/Pjxnew2W0SMqorkYybUeBLkgQ9qZPbLdRz6PExMDFWcIUxHvrwQ6PCFUKeDe0tLyLOMshUUBXalgqrjwK1UKB2X/avXaiMpOuOgLIcJ4EirxoQQNOp1QQNrtduiSnSoRQUL4m3LgsH8SkEIfM+DOyCRpGsadE3DxtoaHMeBfcQL84eBpy/YTxKAcfPEa3mOjuch8H0Ypokiz2HZNipc4eMIDLL4MhBClUbY/hRFATmkYgohBD6j71gsM3FQnVjf97G1uYlWu02z9Z4H3/OgEILbt26JvoVmo4GFhQXa9Mv0lxVFESUwgBoFXgYd1Ug2bkPnA59yOOIzUdTBzaMABM3IME24RYFqvY7ZLBMLo4xlW/wwRMAm/22sr4uJhEVRwDBNOsyGLaAmJyfRbDYPlIXhzkyodxwyCCCMdqWqKiYmJrC6toYky6AGAXTmzA+xc1ERUVUVFVZJ4uV/rmQi3g46dIjrKnuehwZr7pKQeFAQWf3S9zNjvSdRFMF2XaG2VSkH+odFeR/su8Nt6WG/61mei6Zc13WF4MG+gx5C0O50sLW1Rau/LGMfhCEUQnDt2jUa8LouJicn8YzrigQID0xVVq3mlD9O1xx+yPGViHiA/aCSBCM/kSGxBpcc1lwXlmUhr1ZRbzQobZL5lYRPkmU+JQgCrKysCPnNvCjgMBUo7lempqZQq9X29ZmK54v7bZZ5P0yExIU1CGg1e6LZxObmJl34gVZ9D+pXeC8Z35orwXlsqKPv+3BcF2aZbqtQWexuu42M9Zw87opvT1WwXxQFVeDpy75st1oIPA+KpqHiOLQZMst2sohHpOICYKCk4GGDMJ9lP1WFTkr1g2Cs7YqiQKvVwubmJjY3N7G1tSUMA9fTnZ2exo1uF8+fOYMXz58XHDoAojSYZRlVJ2AUjoRxE8vVEJVlMcr8R25cxzU0wig/ArxsBbRHouDc/9LPnMnocZDS/1VVpXSTWg0ao0JxcK3h7e1tBEGAOI6xvb2NW7dugRQFNE3DxOQkpqamMDU5icmpqT37SMqZPkVRoGJnVsF+Udaj5jAMA81GA61WC13fR01Vx5J5G4ayIwHofXYdh8rGsub5oih61Hc0purT3t6mjV2VyqF40BIS+0HBEis9CaSiwDZTF9GZCkgYBMjTtFdx54iSSGRAkHhov8LoO4ZpwrassWezZHmO7a2tHb+yuUmTAYqCarWKWrWK6elp3Lx9G2+88QaeffbZnu9rXvIpKWumLYoCMbOxpQsUCSWtr0l23CsmhOwkQx6RJBK/3p4eAOZbyknDsi3WNA1V00Sz0aA9CSW/kmUZ1tfX0WIT0MMgwOrKCq5fv06pkEwNh/uVicnJkfZzl41mn8NBaaI8eVSG4zioVCrw2AyZxiHpmZxaV058VVxXULfDIEDBeuw4VNaIHPg+5f4/5opvT5VH7KHwMLRZBhuKgibLpLbabdqAyagsRyqtNazD/YC0Hl7aAyGoVKt0dT2EcpQkiQjq+c+iKKBqGiYnJvDcc89hkgWRFlvlXrh4EYqq4vxLL/WufAERsIsmGlZqzFi3v2gyZV/moiiAvooDYQsB/sVSFToKvue1vu7/+22U+TRfvpBRVRWRotAJfkUhriXLsqFORQGrbDCjyzNTo5rbVE2jQ0aYlJ0YUU9Iz6Ls5s2buHT5MsBKnpNTU5iemsLk1BQqlUqPQVLYeZf/fxA6DwGEikQ/qtUqwjBEkmVodzo9C8KDgPMsxTky7q+qqjTTCKAIAjrVlz0LhmHA8zxMTk+j2+1iYmLiUOcgITEuCu5XSjz9za0tSglVVTSbTSqEwN4vAqkjpO+M8ivlAHFchLz3iKkFjXxvGPYE9q12G4TQyfKTU1M4+8ILmJqawsTEhOjHeveHP0S9XsepU6d2BVDCr7DAi9vaPM+FeAIXSeCBcE8lW9mZMdLvQ3peU0pa8Ypy35NIPKjlfiVhQiFlv8ITaMOgsPPkdo/fq1FVDl3XMTMzA8dxUBQF6vU6FIU2BG+zSeSbm5u4cvkyUubvms0m9StsEWCXngHuQ3r8Clgic79+hRBKtxrw/DYaDdqMnSTodLuH5s33+xUFQMV1EbJeuZhVjnkvjUIILNOk/WCVCnzff6wV356uYD9Jegxy1/PQbrWE7nGtXkeWZeIh1hl/+khQXpWPwH5oPYQQdBl9x2QyjMBOtsf3PKytrmJrcxMbm5vodrtCUWFqchIvv/wypqam0Gg2B0olZkWBGzdu4ORzz+0K9IedO+f7myU6R78KTs4MNCEEJM+RA9hr2DoBpRhBUaAx/n9PUIudBRP/nZeduVJDTxaM/iJ04cu/cwcQRxESJk82iC9IWNmeG18ur8ZVHvj5FUx/fhyoqgrLMBCxLLbLsgkTExOYmJjAmTNnAABBEAgjvbm5icXFRUChTdA8QzM1PU2NcN+5K6oqZkzshXJ5ddR3YXJiglYj8hxdzxurgXoUlD6jTED1mBVVpRlS0OfBrVToGHBCkJWao6vV6sip1hISR4GiKHb8CqMktlotSn0EMDU1Bdd1EQSBCIDVPRI/+8Ye+9ovrScvCoRszozruj2CCQQ0QdbpdLDJ/ErIKsmVahVTk5M4efIkpqanKT1kwP4938fS0hJef/31sTKlXAoagKiKcDvNK6pcBazHrxTFnn4lK+hsDy5qgX6/ouzIqCqg04IJmE9hSbYev8Ir+Px17ldYMA/sCIGAEGR9NkpUgHnVolwNZzKenJYyaqJsP7igBq+884bl6enpHi35DqNbbW5uYnlpCdeuXgUUKhM6xbP/U1M99FB+n/ZTNS5XiYc9A6qqYrLZRBCGSJIEQRD0ZN4PC07F5ao8URQJtaKK64rPPGLPt8f4/Y+r4ttTE+xzCg9XwuHqMSAEtVpNDHHg2YyDdKmPRB91aPRbS1n+EV+eMIqEXFfFdZFlGVZXV3Hr9m3aCMqcUKPRwPT0NM6dOyeczzhncu/uXYRRhOeff37MiyyhdN48+9AffHEdeZ7x4Aac/+S/c8NWsAxAv+b8MMSMkhTHMaIDZJsVLrvG9Y95hohVHnhD3F7YbxHdtCyhGjBMscNlvNYTJ04AoBUebqQ3NjZw4eJFqicNSlNrsB4L/tmPo84zqLw6DJqu00zM2hodHhRFA/W49wNe0laxcw8NXYdaqfQ0WHE5QMMwEAUBjEYD3W4Xk5OThzq+hMSeYLaIZ0q73S4834eqsEZcxvPlOu4m/04cFTV0H4uGniz/iOpx4PtUPlfXhVb78soKbt26hbWNDRRZBlXT0Gw28cyxY5iansbExMRYk7MBYPHGDWi6LmzXQcBlFTVNA/r8SsYklIty1rzsV5ivEZUB5lfGaT6O41j85JTXfZ03mEKaptFhY5ZF/Uqpoj2OXzkIf90yTVp1HzGpvV6vo16v4+TJkwBog/bW1hY2t7awubGBu3fuiIXMhQsXoBsG5ufmRM/eXn6lnFAbZ6Fn2TZqroutNEW720W9VjsURVNUJfqothZTk+OJJM/3qWAG+xy4P/N9/0jnQTxIPDXBPmFfUkIIPM9DEAQo8hxutdojoZWwld1+J+SOPvjBG0tENqbPqGd5LnSF/W4Xly5exOrqKoqigFupYP7YMczNzGB+YQHmAb4cBMC169cxNzt7sId7jJIerwTshaIoEKcpwChHlUplJ3MCDMzQgxChb28aBjVG2MkiCENTyuRw6o3CJCBDptfsMOWHXefFncYRQ2cSd4QNpxknaNZ1HbOzs5idnQVAM//f//734XkeFFXFp599hk8//RQNpmoxPz8/9HMdxM0fB67rUonSNMV2u425/QyIGQD+efQ/R3waNJ9J4AUBKq5LdbDDEPVmE1EUIUmSJ2rcucSjh4JVDwtW0QpYFrBaq6FWKvmnaYoCdLF6ZH4F2HdTpMjy8+9lX9Afs6GMYRTB63bx6SefYHNzE4QQGgQ++yzmFxYwMzMD/QDf7SzLcOPmTZw6deq+9dWoikJVzfZAwTTXVYVOIXcdZ0+/YrAAn/sUALv9Sp+P6aenat0usjxHhSnl7DqvcfzKASgzhmlCjSIxP2ac3irbtnHs2DExSHNzcxM/+MEPxMLoRz/6ERRFwcz0NBYWFjC/sDBw0cfPdK9s/iBUq1XRTLvVamH2CKbaKsyvlO9zTyIpzxEEgcjkJ2EI27ZFdv9xVHx7eoJ9Jh/mex4dbJKmcCoV1Gu1noCEG+W9BiGNf+Cdst5B0JPlB4CiQMfzcGNxESsrK+h0OtAUBVPT03j55ZexsLAARVEQhiHVGj6gQd3a3sb21hbe2WOE+WEw7j3hY8x1XYfBBraMAz4Iy7btPXmnA89vj78f9RTBMizTpLzONN13hrzdbuMHP/iB0Ll+5sQJvPDCC1hdXcXS0hIuX7mCLy5cgOu6mJ+dxcLx45hmlJ9iTLrZMNRqNbRaLRR5ju12G1OH5c4PqW7xQV5BGFJ1oyBApVJBFATQVDrcq9vtYmpq6nDHl5AYgqIoQFjQ4/k+EjbIqVqpoFav9yZnGD30sP0sPSgHpvtET9DPvmObW1u4sbiItfV1+L4PXVUxOz+PN954Awvz87TamCR05sUBF/G379xBmiQ4ferUwc4bY1RK9+NXFKpyY43pV9IkoRKOB/QpZQwLd8e5xoMsFxVFgWlZKFiScL9CCsvLy/jRj36EWq2Gre1tvPraa5iZmcHK8jKWlpbw+eef47PPPkO1VsMxFvg3m03Rs3dQKEzWu9vpIEkSdLvdI8muDzojnkjyg4D6lTCkfqbbxdTsLNI0fWwV356KYL/IcxCufZ4kiNkqbZduN0pG+YhHJB9KlqoosL29jaXlZdy7dw/tdhuKqmJychI/8eUv49ixYz3ny7NLhwlEr1+7Brdaxdzc3CHOfA/sIztBDpARODT2Orf7FOgDtOFUU1WqSFEadb4XVldX8f7776NWq+Htt9/Gn//5n4sBKs888wyeeeYZFEWBjfV1LK+s4N69e7h6/Tp0Xcf8/DwWFhYwNzd34Kybqqqo1+sIwhBBGMKxrENJlonFLqOr9f/NdRx0u106PToMUXEcRGEI3TTpFM08fyyzMBKPPgjrDwl8nwolMM1423F2DQZMkwSEkKOpNHG7c4DsbhlFnmN9fV34lSAIoLIK4auvvLLLDiRMx/0wal7Xr13DwrFjYibHw8YDV+LB/mmdR7kPyzDE7IT92Mbr16/js88+w/Hjx/Hyyy/jz/7sz+hEYtvGyVOncPLUKWRpirW1NSwvL+PqtWv44uJFWhlgfmV6ZuZAlV4F1B9Wq1VEcYx2tyuGph0UCoYvqrhiXqfTQc4knxVFQcEW9mEYiibnxwlPRbBPkgQpa9LMkgSGacLQ9YErc97gd+TNffs0zKQosL62hntLS1heXkbEJrnOzc/j1KlTqDFu3aCGFUVVgb5u+f0gjCLcuXsXr3zpS/f1gT6QFvLDaI4ZoXSxp3LSISo6pmkiLwqahRnjebx58yY++eQTzM/P480334SmaUjTdFfgrqoqZufmMDM7i1e+9CVsbG5ieXkZS8vLuHX7NjRVxezsLBYWFvDMM8+M/11g98E0TaiaBs/z0Op0xICsw0DT9V7ZPXFIBY7jwA8CapjjGO1WC8dOnEDMph0/zgoKEo8uSJoiYs2DSRzDZpVUp88m8wSSgiOqGB8iyM/zHEtLS1i+dw8rq6tIswyVSgXHn3mGTvauVsVAv12H5b8c8Nhr6+tot9t49bXXDrT9ONjP3BbgIcxuGQfjfL4H9MuqpsE0DErXYovTvfD555/j2rVrOHv2LL70pS/B8zxAUXZVBnTDwLHjx7Fw7Bhee/11rK6uYnl5GfeWl3Ht+nWYpom5uTkcP3YMCwsLI5XpdoEQ2jRLCKIkEXSew9JEh91lTVXhOA6CIECapohUFd1OB9VGo6fJ+XHCUxHsZ2zABNci1g0D9gDN1CzLhD78OOozI9H3ZR03yx5FEW7dvInFmzcRMKmnE88+i2PHjmGCcZGDMKQUDfawcY46vx7x+B/QKC8uLkJTVTz33HMH2n4ciObjMY1WWdP3QWPUEXua3gbgMFkc0zQRMo5llmUjA+Yf//jHuHr1Kp5//nm8+uqrACCa0fq34w6RK+xMTk2hOTGB8y+9hMD3sby8jOXlZXz88cf47LPPcOLECZw8dQoTzebI+1/+S6NWQ8y08VvtNqYPSafhihi7vlegjtqxbQRBgCRJsLWxgWOs+U8G+xL3A0WeI2GN6IT1Emm6Dstxdtk0ntU/EtGHAc//OOh2u7i5uIibt24hTRI0JyZw9oUXcOzYMdRrNXQ9DzHrceFKav1+hV/XQW3a9evXUWNiEfcT+/ERPCH2UIL9YUmkcbY9xDRZy7KQlvrBht2vPM/xwQcfYGVlBa+//jpOMepVxpSEygvXfvUhRVUxNz+PmdlZvPrqq2h3Olhmicv33n8flmniuZMncerkSVT2YZ8nJiexuroqmuEPQ6fZJb9aAgHl8Du2TeU/owjrq6uYnJlBFEWCJv044YkP9tMwhOd59EvNAv1yoFxGkqY0+7KHbu2e2G+QTQjW1tawuLiIpeVlKIqCZ555BqfffJPqhXMJx6KgzoUQOK7b01gq5L+AQxnlrChw/fp1PPvss4eqbozDZ9+XUWZZ3QdqlMf4HO8nb19VVVimSQdKDcjQA9Qgf/jhh7h37x5effXVHuWkslHmhnhQtYfLyxHQYWrPnzmD58+c2Vl4Li5i8eZNNBsNnD59Gs+cODGQ7ylk6kCN/USzifX1dURxDM/3Dy3HqY6oVum6DttxEEURoiTBvTt3MDM3hzRN91woSUjsFylPIAGAqkJnk8NN09xlN5I0pUo8hw0O9mlnijzH0vIyFm/cwMb6OgzLwsmTJ3Hy5MmeBXCWpkjZBGCX9QeVbQI99E7QfxB7x+U23xhTbvOg2M+ZlQdqqQ8wicTPcWQSCaOvRRmQ+BgXg2Q4+xHHMd599110u128/fbbPXTeNE1FZp8/C8WACrf4H1MEbDQaePH8eXidDhYXF3FjcRFXrlzB7OwsTp06RbP9A/w73w8B5dQ3mk1sb2+j6/uw+gZh7ReqooAM8OH8/6Zp0vuUpuh6HrY2N+FWKiIOe5yoPE+0BySEoLu5ibwooLPhRHlR0IbHAV+WjCnxGA9IwSOJY9y8eRM3Fxfh+T5q9TpefeUVnDhxYuA5RFEkMrX9jV7lwP8wRvne3buI4vhgcpslHHUALAzko1RuBfYsuR7WFJiMez5IhjNJErz77rtot9v42te+hoWFhZ5tMya9qWna0IFYHKqq7tJttm0b5158EedeeAEra2tYvHGDZvs//xzPnjiBU6dO9ShZAQBR6DASfu71Wg3tbhetdhu2ZR066O5fXJVl3kzDoBnXNMXK0hLqjQZMy0IYho+tXJrEo4c0SdDd2hK2OGfa7o7j7LYFhNApsLgP1FAMDgp938fi4iJu3byJOI4xPT2Nr7z5Jo4dPz4wmArYDBLbsqD1fT/L9kbjgdEBsso3btyArut49tln971t3wmNDnL34XfKA7UeKRoP9k4iHda7chnOeECw73kevv/976MoCvzkT/7kLhufZRmKPIfKFgxDZcXZfe3PnFfrdbzy2mt46UtfwtLdu1i8eRPvvfcebMsS2X63PzFU2n/FdUV2vdVuH4rOQ7CzcConTMvPuGVZdLBbnuPOzZs4e/48ABqPHXbQ14PEEx3stzY2kKUpNFWFYZoIGf1lmCJCmmUghBzeKI+ipxCC9Y0N3LxxA3eXlgBFwTPHj+PLX/kKpiYnh25XsOEfhJA9Gx5VJvG131IfAXDt2jXMz80dOjja01jt0yiTR5CzzzFqhX/YRc8wGU7P8/CDH/wAeZ7jm9/85u6gmxDEbEIjHxbz/7P3H91tZNuWKDx3OFiCHiBFUqIo75VSSikp/bm39VX367y/UK2qZt12/ZF69QtqvMb3jXuPybznJKWU944ylEiJAD18+P0asXcwEIwAAoailIdzjBxikgDCIPZaa68111xN4cvkNUAQMDY2hrGxMdRrNczPz+Pdu3d48/YthgcHcfDgQUxMTvIDO5MUGdLpNOqaBs3Ds+wEDffR4/D99zcWizlTKk0TC+/fY3pmZi/Y30PPYNs2yqursNm6klgTvSRJWxtZ/kwyP8A5+10lkVrYEWrbWPr4EW/n51EoFCDLMvbv3+/2d4XBMAx31kmzwIVrqAvO/7TVN+CV2+y6Wb7VfUD0BMuuUUOj3Lcum69bQVYUiKoKwyfDubq6iuvXryOZTOLatWsNzwQFQJhf4UmkVn6lWSOsKIqYOnAAUwcOoFQs4u38PF69fo0XL15gLJfD9MGDGGPqgn4M9PfD0DR3avugz/9FhXtubD4AP9+G13j6wnTDwMfFRUxMTe0F+58LapUKzGoVBA41gU/5c7P6AeCyg/7sRmR4VRJ80HTdzeKXy2Wk02mcPn0aB/bvj+QEePZFVpSWm5EgrV9O42iGtfV1bGxs7KjcJkc7RplTN9zpgZ8IUQJ1AriDUAIhCEDEabVh8Mtwrq2t4caNG4jFYvj+++/djCIfV86bAU3WbB61KTAou+9HIpnEiZMnceL4cSzl83j79i1u372Lh48eYXJyEtnR0QaKAGFTEAsrK9CZbFlHHHoWOHF6QZgWNSEEiXgc1VoNtUoFa6uryDI6z95E3T10i0qpBFvTIDLFjnKlAgDBTp/TL9n69yv0REYTO1StVFyanaZpGBoexsWLFzExORkpsK7V6wCAeCLRsmHSrRoz++Ld1Dc7x3cLCzC7kNtsPInwILgdwQdg95tzW/mynaSJEEIgx2KwPDKc79+/x927d5HNZnH58mV38+rn4xuG4cwyiPI8k9aDtgAg09+Pc+fO4fSpU1j88AFv3rzBjevXEU8mMcX8iujxG6IoYmBwEKtra6hUq44KVgd0Hi+lSmDnGfR0ceW3aq2GzfV19A8OulWLz60qFIY/ZLBPKUW1VALgBCd8nHZgVt+bhefNOj08F1XT8OLFC7x69Qo2pZjYtw/nz593mpQiLmTTsqAzjlgUbV/iCfrc3zl/ABAexL5+/Xrn5TbRvlF25dF25nTCj8v+bWVwd5K3DzTKcM7Pz+PBgwcYGhrCN1euuLxJm1KXPsPP1mgz2AdvWIpyLYKA8X37ML5vH2rVKuZZU/mbt28xNDSEs2fOOP0m7PiZdBrFchmlTkeOB8huhp2nN+BfXV7G4NAQ6vX6XrC/h65gWRbUctlx/MkkdE/jbQM9zReQ7oRlKJfLePbsGd6+ewdZkjB14AAOTk+31bCo67qTEGDrpSXYmrV9dsb5H0/Cw3ftr+fmsO9TyG2229OwW8F+xCQSH/y0U/DKcD59+hQvXrzA9PQ0zrG+irDBiqZptmVL2/HboiThwIEDOHDgADY3NzHPuP1zc3MYGx/HmTNnHFUebM06qNbrKJVKiI+OtnEkBu/9ZZsrKyQ5x3s966qKpQ8fnLkuqtqVtPSnxB8y2K9Wq4BpQmTyhWUW+G/L6vsCCIouDHNAU9bLuTm8fvUKAHD0+HEcnJ7uqINbrddhA1Aicp69wWlQBt3/d8DR5l9YWMDZM2d6kk1o9gnt3mPXKH9qvfSIhpY2yTaRHhhrLsP55s0bvHr9GpOTk7jw1VcNm4yg+22apqsq0M6x2nUwyVQKJ0+dwpEjR/D27VvMz8/jl7/9DePj4zh56hQymQzS6TSq1SoM20a5UkF/E2pB4Hmh8bkhxNHeD9swi6IIWZJQV1VsrK8jHo8j0+Yx97AHL8rFIgTbhijLkETR8TMIyOqHKI11HFR6Pqtar+P5s2eYn59HPB7Hha++wuTUVPu9MJS61eJEPB7p3IQWySJvQybPBBeWl1EqlXDu/Pn2zi8ETRMrbdou1698YhqPe4YRKDA7F+o7/lSWJDx4+BAfP37EyRMncOzYMVetLQxmiFhEKEK4+60wMDCA8199haNHj+Lt/Dzm5+fx7//+7zg4PY3jx44hnkgg09eHuqpCNwzU6vX2B515nhnC+1GaXLssy9B1HbVqFVVWUdgL9ncJtm2jUipBohTxeByGrsOybYhhXH3ObWc7WUppV02ghmni1atXmJubg2XbOHzoEI4cPQpZltt+2AEnYNM1rUEpoRXcQUT8epoYFf6XxcVFCIS4cptdlxCbvbfdDMwucSujqCYATkAfdkVdG2uWtX/8+DHevX+PA/v348zZs5HuBR9p3hZPtp3s/ra3EuTGxjA2Po7NjQ08e/YMf/nznzE5OYkTJ0+ir7/fUVGoVJwpnG0GKN5n0qYURBSblocVRYGm6yhubqJ/YAA6kxbcwx7ahWEYUKtVyJQ6cnys0rotq8/hTag0oXe2BAv066qK58+fY/7tW0iKgrNnz2L64MGOq4qarsMyTQiERKY/uDYnYmYahGDh/Xv0ZTIYYVnXduib7aLd++DKbn7iJFLUXoGdDPYppTAMA7fv3MHa6ipOnjyJI4cPR7qHnVAi/epO7UAQRUxNTmL/1BSWlpbw4uVLzL97h0MzMzh67BjSqRTKlQpK5TLisVhbm2r/OVFGFW12H2KKAt0wsLa6imQyiUFG6fnc8YcL9iuVCohpOs1TsoxyuQygOVc/iCLQFlhD4Nu3b/H85UuYuo6DMzM4dvSo21DZqSpuncm7xQKUEsJAOLeZP7StuIEA3r97h30TE+4i9t+DdpuZeklrsXepOTdyBsazYez6mN4SOKUwDQO/37yJlZUVnDl1CkMjIzB0HWKEjZ9hGE5Wv93z6vB6bNbgJAgCpqamMDE5iffz83j24gUW//xn7J+awmg2CyIIKFcqbTdV8bOhnmPZCA8eRFFEPJFAvVZDtVpFrVbbC/b30BFKpRIE1mQrEAJN1wE05+r7m8jbziCzZsiXL17g1evXEAUBx0+exOGZGXeDYaMDW0sp6h6xh6iBirv+Ih7PME18WFzEsePHtyR5t51K73jp7W4kdiOz38531Y28ZrPjUkpRq9UwOzsLTdPw9ddfI5VOwzDNSPOFLMvqSFUtSk9YIFgyTZYkHDlyBAcPHsSrV6/wam4Ob9+8wcyhQ+jv74fFrqudnjDbd1+obbcM9kWmhlitVFCtVlGv1z+bidDN8IcK9i3LQrVc3srqG4ab1d/m5JtkW9pZ/LZtO0H+8+dQVRXT09M4fvx4++WkABiG4Wg0R+Tqe9GOYS4WiyiWSjhx6lT45wVQntDMUDe5h+0aeHejsVuNVJFe1JnD8BthL+r1OmZnZ1Gr1fDdt9+if2AAFaYIEI8S7HeoL0942bVNR+PvcRAIwfTBg5g6cADzb97g+dwcFhYWkM3lkM3lkEqnoXRwft6eD6FF81dMUVCv1VApl7GxsYH+/v5Pr76xhy8amqZBq9UQZ36FZ/VlWd6+vrzJFb5pZrSedp47wzDw8uVLvHr1ChTAkaNHceTIke3rpYNgUNU0WEw6sR1aaYPYQwR8/PgRpmVhig24a/aZHK2SSmF3kCuptIPd4Ow3UBF36hi8gRpbftqLzY0NXL9+HaIk4ccff4TE6I6GYUQK9oOmskdCh9l9LsbAnwlJknD8+HHMHDqEuZcv8fr1awiiiNzYmDMrps0NLD+fBj8iCKFqhoQQxOJxFItFVKtVlEqlvWD/U6NcLgOWBYXJFXJOZWBWP4C7345+MKUUC+/f48nTp6hWqziwfz+OnzgROjiok4XtKiXE422XGtvR2l9YWIAsy2015nobfl146CzNpCjbDbZ2ZaAW0MDla4W2pEab0H44Njc3cX12FqIk4eeffkK6rw+gFAKcwWdRBkV1M0yqk2oFVzLw3y9REHDo8GFMT0/j1evXmJubw/LyMtbW1nD29OnIAYerCOFbp80yegRAMpHA2uoqUun0FyeXtofdR6lUgsiHYnmy+lE23GiTZmNaFt68eoXnL17AsizMzMzg2LFjoXLR7fLUKZNw5rTQdmwxEQT3eFGy6AsLCxgeHm6L09xSwjjs7x1kwXdzKnvU44b6FS+v3mOr+e/C7sTS0hJu3bqFgYEBXLlyBYqiOI3nbNp5IpFomew0DKPjAXGdZPf55sWf7FNkGadOncLhw4fx7NkzvH//HvmlJWxMT+Pk8eOR6KtuoO/zyQKaszFEtlFeW11FIpFANpvtXlZ2h/GHCfYNw0CtUoHCOJW6qrad1Y/KDV9ZWcH9+/dRKpWwb3wcV69ebbvhsBVcpQSElIpbIGqwTwG8f/8ek5OT3ZczCWmgWiDA8HRC79m1keZtllz5gBEvh9+27bZ7NfL5PG7dvIm+TAZXr17dCoYJgawosJtM1PXC0PXwIKEVCNkamhIR3CiHPUeiJOHYsWOY3L8fjx89wsePH7H08SOOHzuGw0eOtHz+hAClBE4basXdL1erKBWLWF9fx8TERORr2sM/N+r1OgxNQ4wQxBMJZ2pulKy+53fcFjSzXxTAwvv3ePToEVRdx8EDB3D8+PGWKjntWmyV+UVBFNsO2Lx+0Wa+tdlxCvl8TxtzAR/twv2Bth3oW55GzE+a2W8iqBAEArhSyt7rtVg/Hv//hn9D8Pr1azx8+BATExP4+uuv3esW2bwISxBgGEZLn6HpOlKdyCcDHfWE8UA87J7FYjGcP38eU1NTeM4ob+/fv8e5M2cwMTkZaVJxoJ9rtoFkcebq2hqq1So2NjYchcXPGH+YYL9SqUCwbSiyDFGSUGH6x6Fc/YDfubzCkMVvWhYeP3qE169fY3h4GD/99BOGmLxgT0HbV0rwQxBFEDYRuBlWVldRr9cx1e1kQx+8mX/vnbY5J46/zruj9nBdvZuV3RhpDjRy9rmxCVz6LMtCKd3erNvmOb99+xYPHjzA+Pg4vv76623ZAkWSoOm6MwinRWauWqsh0YVSQNtlcX7tLa45lUjg8JEjyGazWCoU8OjxY3z8+BEXL15sOvzK9t9bz3k24+4TQpBi2f3+gYHQsex72IMflUoFkmkinkiAUgpN0wAgmlQlGp/LsLWqqiru3buHjx8/YmpqCidPnnTlBXsJ27ZdClIimewooy0yVZVWwf7i4iIoIVvD9noE7zl7z95iVU+/9r9rs1ng5k+CferZLRxh/XTu+bLzs9lGxm/32traUIoHDx/izZs3OHr0KE4F0HVlRXEGbEVIENVrNSS7+F7b7UWgEelWw8PDOHz4MHJjY/jw4QN+v3kTkx8+4Pz586HV49BAH2i5KREEAYlYDGsrKxgYGNgL9j8VNE2DYNuIx2LQNA1mq6x+CMI04FdXV3H79m2oqoqz587h0MxMW8EQ4ceOYFgalBIiOhU/eGDcKthfWFhAMpFwpvf2GkHGzL8B8FQDPC9yjbH3/AWmO0w9mwL+em7YvbJvbknTSy/yvz/sZ++xQwxu0HUF3oOIePToEV69eoXDhw/jzOnTgc+KJEkQCYFBaUu941qttm2yblsg7UmmtdOImEmnodbrmJyYwNTkJJ48eoS//PWvOHXyJA4dPrztMygYnSvks1tl9+PxODbLZdRqtS9KG3kPuwfLsmBoGmRKEYvHHbEE23amj7ZQ4Gn8tWPP/MEKz+Y/ePAAgiDg6tWrGB8b24ErcaCqKmzqKAh1WvHj19DKJrxfWMDY2FgkDng7CLzD3If4fUmAr+G+gVNDvYFnJL8CuCp33mA9kl/xvNe9ez7/4PcWAiHoZiSjZVm4efMmCoUCvvrqK0xPTwe+TpZlkHodhmm6jIgg8OGOXVEh28zu297vowX6MxkYhoGDMzOOX3nyBP/x5z/jq/Pngyu6tLnMaCuaXDyRwMr6Omq1GizL+qypPH+IYN8wDNimCZkQiJLkcN1ZM1XUrD4Al2/sDdxMy8LTx48x9+oVhoeH8e13323x8tulpETJINAtpYREJ8OHGARR3KKWhMC0bSwuLGBmZqajY7Q+ie1DQaJy9oMyMOwPDcYbAT97qwoNpV7+/z7+fNDPnWTnO1VPsCwLd+7cwcePH3H27FkcOnSo2UEgyzIs24beRAKNUupkYLoMagmaVDQCjhn1+5Vl2ZVMI6KIn37+Gc+fPcNDRu+5ePGiq6rgfq4ghBrmpufInhlZklCvVlFhg732sIdm0DTNeW5kGQRsSF2bCRh3Iie3DWxtaJqGu/fu4eOHD5iamsK5c+ecxFQH9iMKbMbV5wo8nUIQBKeS1sSvlCsVrK+t4dI333R8nHbQTh8Y9w08gBR5HwL/G/s7An4OrNC06Vc42qlSB1JYIjwnqqri+vXrqFQquHbtGrLZbOhrBUGAJMuwqSPJKYZkwnkfYdd9T54+g6bwXGeU7zgejyMej6Ouqkj39eFf/+VfcO/+fdz4/XdMTkw0ZvkpdZ7jJknYVpsSSZJACEG9VkOtVmtamd5t/CGCfZ7VlyQJtm3DZBnAbYFQq6w+6+jnD9Xq2hru3LqFuqq6QVgv5bCC4FVK6GT8M0eUzH5+aQm6YfScwsPhD8CCmjdbweXr70KplSOyIyHbm6laPSm6rmN2dhblUglXvvkGY+PjLY8jy7JTvTIM2JQG3htN02CzDWNXINHGnQNb5daoqknpdBq1Wg2GaULTdZw5exb7JiZw984d/Pkvf8GpU6ecjQ+nSbU61VbcfVlGjRnlPeyhFXRdB7EsSPE4DNOETSlEQWir6d1b7eJTnxcWF/Hg/n0QQnD1yhWM79vHX9z2OUatGHNaqKwoXU2SjpLZX1hYgCjLO1ql6Ba71ZzbycyFTmKOcrmM2dlZ2LaNH374IdJkZUWWYRgGDF0PjT3qzHZ2nUQi0RTfGir7Ee9ZX18fVE2DqqpIpdP45vJlLH74gAcPHrhZ/n379kXvRwu7/yyJpEgSqpXKXrD/KaBpmqOBzB5WgGVj/EFHxIeFUoqHDx9i7uVLDI+M4Oq336LP25DSYcDfcgAKpS6nMtWmUoIfvJzUyigP9Pc3XttOooN7tlsjzTtpJA7MLjf5nEq5jNnr12GZJr7/4YfIlBtJkiCKopuFCSrJ8wxMLyRgI2X3aWslJj9EUUQ6nUaxXEa5XHboZMPD+NO//AuePnmChw8fYmFhARcvXEA6nW65fry9IEFQZBmb5TLq9Tps297j7e+hKTRNgwCnIqTpOiilHauQ8M+7e+8ePnz4gKnJSZw7f/6TzH2wbRs68yvd2gORcdzD/AoF8O7dO0xMTOwcpcG/uenAVrebmOgVOkkTBiXNmmFlZQU3btxAKpXCtatXEY/4nfMKlmXboZQUniiJ2rPSDFEU39yqRhuxUExRkGTN9KVSCfGREUxOTmJ0dBT37t3D9Rs3MLFvH86dP4+YorRUlgrN7rPfKUzemas/fq744r0dpdTJwMAJgnRulIOy+hH4+uVyGb/87W94++YNzp49ix++/74xGI7wOZ1CNwwnqy8IXTkVwJPZD8mIaoaBpXy+qQZyz9GJUd6lDAwHD3QjvTbgHMOC09XVVfzy668QGYWlXW69LMsghLibWz/4MLae0FV81LYgUM+6aOebSqXTkEQRFE75H3A2AWfOnsV3332Her2OP//lL3j1+nXr54dShzoW9Hs49gGUolQqQWfyiXvYQxAMw4BlGBDhqEiZug4KBPuVJuAa4RsbG/j3//gPrK6u4ptvvsGlS5d6F+i3WJuaqoICkIIUhNo9lCgClIbKJ65vbKBSrWL/DlWLAWxb4514490YqNWAdjP7XjR55t69e4fffvsNI8PD+OGHHyIH+vw4sqKAEBJqH+tcurgXmyRWNW4GV4mnze+pjyWHDF13NyixWAxXvvkGF7/+GvlCAX/+85/xYWmptW9rcv6AYxN0TUOd8fY/V3zxwb6u66CmCZEFJBan8PgNKSHNd5C2jQcPHuDZ8+egAL7/4QccOXrU0bffQdqOF5qqAgCUWKzr4FYQRbcCEZSF+bi4CLvFwJOuEdBk2S52KwPT0KQV9S2Ido2LCwv4xz/+gYGBAfz4ww8d8R8VZpQNRuXxo1arOVOku3TuHK1KyW6zWoSNgRcCIejLZEAoRblSgWmazucBGBoawr/86U+Ynp7Gg4cP8evf/+6qoTT7vKBzo5RCFEWIgoBqpYI6q3zsYQ9B0HUdhFFDTcMABSCynrAGtHjWdV3H3bt38erVK2T6+vCnn3/G5ORkWwFcKzQ9A0rdqkQ3tFAOka3xMLrcwvv3iMfjGBke7vpYYfBfbzdyzrtF42nnqNvOMeScnz17hrt372J6ehpXr17tyPYrsgyBEOimGXhf67VaT+eUtNpscWp1u5sy3hMmEIJSpeLGQDaAyYkJ/Ou//isGBgdx48YN3Ll9u2mQThASf/C+D1GEIIooFost/dNu4g8R7AuUQpJldzcqseZUFxF4Ybdu3YKm624w8Ouvv+LXX37Bi+fPUSyVHOPWZdDfzLCYluXIKVKKRA+MMrDVfBQU7L9fWMBoNtux2k8UtG2UA/7u5+w3lDM9VQvK/p9XMijb5PDX+APxoDPxf7b/GlpyxtHaebx48QK3bt/G/v378e2330LqkD8rCAIkUYQgCDACsjC1et0xyr1yZoxjGQauBd2JQUklEpCZkymXy/CqZYiShLNnz+L7775DqVTCL7/+iiqrAAQigL/Mm+4JIc60yGr1sy+57mF3oWkaREYN1Tk1NEjZrYlN0zUNt27edHuw1tbW8B//8R+Y/e03vH7zZusZ7DaZ1GSNa7xaLIo9qSTw4Y42s7VeWNQZNDkVtJnZIbQ9jZ3/G0APDfIP3Jdw32Iz29Twd7T2DWF/j/reZq+xbRu3b9/G8+fPcfr0aZw/f75juy9Lktv7FBQAdyvnvA0kQI3PA9fHd5DsS6fTEAUBlmk6PSt0S8Y7Ho/j6pUruHjhAt4vLuK3334LrZIDwVQifxKp8pknkb54zr7L15ckd1cV8wdQzYJsw8CNGzewurqKI4cPI5lKYWBoCJvr6ygUCnj58iWePn0KJR5HdnQU4+PjyGazkHuUMfVeB4WT1W93Wm4YwpqpavU6lldWcPHixZ4cJwq2BfqUNk495EGa73U2V7PwfEbDK3w0JbdhDcHZk6gBf+DwFvZ7EmKgCBwJNq6t7d883Lt3D+/evcPJkydx7NixgE9oD7IswzBN6Lq+TUe4F0o8fjTN7rPvodOyeH8m4wwoUVUkdX1bVmpkZAQ//fgj/vGPf+CXX3/F1WvXQmdcEEEA9Tsqdu6KoqBYKqFarX72Uml72B1wPX0JTuJIZQ58W7Dc5FmvVqv47bffoGkaTp08CVGWMTo8jMLyMvKFAh4+egQ8eIBkKoVcNoux8XEMj4xA6nEFk1N44j2oFgNs4ywIjp1jw7k4VgoFaJq2Y4IPDWD+wmtnAy1TgL2i2KK3+vuAmvkHTukkAYmn0OP7/u6tiPiPRTz/eo/p/OA5T8/5Gix+WV9fx+XLl7sfGEgIFFmGZVmBgxu7lnMOOmQTYYVukkjenrBSuYyYomxLWO3fvx/JZBLXb9zAL7/8gm+/+y60r8X/rHjXkyRJUBlvf3gHq1rd4IsP9k3ThMQCMMuyHO6+N9hvolRQr9Xw22+/oV6v47vvvoNuGKjV61AkCQcPHsTBgwdhWRbW1taQX1rCx3we79+9AxEEDA8PIzc2hrFcDplMpu0BRF5Q24auaT0rtXKEyaQtLCxAFARMcBWIHQLnqzZkx73G1/tzyHe0aw267F+/gwwz9O7vWFDJHQoIgWkYuH7jBtbX1vD111/3jDqlKArq9TpM296mjVyv15Hp8VRnv3P1wuqSbhWPx6EoCmqqimq1GqgekUyl8NNPP+H69ev4+3/+Jy5fvozxAPUiV/M64Fnj1ZBKubwX7O8hELZtg5omBGwFhYIgND4rTWh+mxsb+G12FpIk4eeff8bG+jpUXUcimcSRI0dw5MgRGIaB1ZUVLC0tYfHjR7x+/RqiJCE7Our4lbGx6M20IZtw0zSdKeyUIt7DRmBREGBZlmObPfdkYWEBfZkMBiIov3QKN9MOllihLXTSgz7D857dovEE0g19/3p/5nbX7Y0iBDW2odR1Hd9//z2GejQrR5ZlqAGDG3sl5+xH08x+l34lxeSdddNEXVUDh9UNj4zgxx9/xG+//YZff/kF165dC/Q/BNuHN/LKkizLqNXrn7X4wxcf7IM9DC6FR5YjlXxKpRJ++8c/QAjBjz/9hExfHwrLywDg8oYBZ3eYzWYxOjqKM2fPolqpIF8oIF8o4NnTp3jy+DGSiQRyuRxyY2PIjo6GcuXCHmpN12Ezfmg3smh+hAX779+/x/i+fT3jc4eZWgFwh4d0wqv0vu+TL54OOPt+CADK1SpmZ2dRV1V8e+0aRkZHt7JSns+m3mNGBDcytq7D0HWIHkpWtVZDbgek7wRCYAXRrTjtpoPviTuxRDIJVVVRU1X09fUFltiVWAzfffcdbt2+jRs3buDc+fOYOXhw22duy+6zgIh/5h6NZw/NILBnnPuVQLscYBvy+Tx+//139GcyuHrtGmKKgs3NTRA4VE3+ObIsY3zfPoyNj+M8pSiWSsjn8yjk83hw/z7uA8hkMsjlchgbG8PQ8LDDlw9A2AZc1TTYcBoTe1UtBpy15fcrpmli8cOHnlQsgS2bEBSMNwzC6uCztw1q/IRwz7dNv8KzyoQQ2ADWV1dx/fp1yLKMH3/80ZlJwu+X16904HclSYIoCDBtG4Zpuk3pPZNz9oOED9mybNuRl+7ke2J+NpFIwCiXUa3VQidT9/X14eeffsLs7Cx+/fVXXLlyJXAugX94I38+ud+rlMu7JibSCl98sM8fgQbJTe8LAm78yvIybty4gSSTpuINJyJrat2mNOB5CFPpNA6lUjg0MwPTsrC6uuoE//k83s7PQxAEjIyMYIwF/14lH5di4jsnlWX1w0Y6d4ogzv5mqYTNYhEnTp5s67OaGd9Q+IPZNvE5ZGDaPq7HEW1sbuK3f/wDgiji5x9/RJpr8HoyJb6DNmwCohhqRVGgs6mGvP/CsixomtYT2c1tIMTJnPt+bbH+iHaDCrcCwqpagijCtKxtWRhvQCNKEr755hs8fPAA9+/fR71ex8kTJ7b16fhL4sCWJG2tVut4A7qHPza81TuT+ZUoFJ75t29x99497Bsfx9eXLkFiz5rE/YonieQcYMvGDPT3YyCTwfFjx6AbBpZZQun9+/eYm5uDJEnIZrMYGxtDLpdrKX1ImdwmKO15X5YYQA/9uLQE0zTbrlq6SY6woD4ADRK7Haxh/o7dUOLppEGXvdH98eOHD7h58yYGBwdx5cqVrWeTkPCkkYd6GsmvMCqPYRhusO8O1NqJPr+Q6hTvG2i3Auv6FWxl901GeQ3rXYnF4/j+hx/w+40b+O2333Dx66+x3/c8h22s+Wak0qyfbJfxxQf7hDfzEeKoj/gpPECDIVl4/x537tzByOgovrl8uSFjI4mik7n0G+VtByXu68dyOYzlcqBnz6JSqaCQzyNfKODxkyd4+OgRkqkUxhjdZ2RkZJtRM3QdlmmCCELPg33CFoh387Lw/j0UWUYulwt9X1hg31XA3YFR3s0MTKdNczwDk8/n8fuNG+jLZHD16tVo322zIJ8bQ59RlCUJApxpyKZpOg2o3CjvxJRYEjxkq5PMPsX27ziVTKIUkIUJ4kueO3cOyWQST548Qb1Ww4ULF9znxFVQ4J/vqxBpqgrTNHu+5vbwx4DAhjPKkgRBFN25FgC2B6eU4unTp3j+/DlmZmZw9ty5hkCSP3P+hsdtq5z3lcgyJicmMDkxAQpgc3PTyfoXCrh79y4AoL+/3wn8x8YwODi47Zx4D5gkST2r4Hqvx6+1v7CwgOHh4ZYUDzvAr7RdPfVx7Nv1Svy8dyUDy8+9XX9GHAWkV3NzePDwISYnJ3Hh4sXo9tafoOHPC6dm+nyOLMtQNQ26riORSEAgpLdyzj6QgOy+bVlNaU9hoHDWmpt1F0Uk4nHU6nVUa7WGYN8fvEuShGvXruHu3bu4desW6rUajh492vJZ4ZuROmsE/hyz+3+IYN+wLMeoMUWPhnIQv+mU4uXLl3j8+DH2HziAr776attCEUQRhFJnAq8HoWGfJ/AicLRd+w4fxuHDh2GaJpZXVpzg/+NHvHn92s36Z1lDVjKZhMqbinvUQOUFL/t6A7MPHz5gYmKiYfEEBfc9aeby/NyJUf4sMjAdHPvNmzd4+PAhxsbHcfHChd7wwr2BBqUuh5FyKg+lMFiw38uBWkHwV6i86hRRN2X+QJ8jahbGORGCI0ePIp5I4M6dO1BVFd988427gffSyLxrVRAEmLoOXdeRSqUine8e/rlA4GT1ZUnarq3vtZ22jbv37mF+fh6nT5/G0SNHttkMUZJACGmgh7pKPmGBL3teCYDBgQEMDgzgxPHj0HQdhUIBhXweb9+8wYsXL6DIMkZGR5HL5ZDN5RBTFLda3MseMA6/8INhmlgqFHD2zJmG1wX5zZ74OE/lpZNP2zU5ZzRy8Nt7I8WDBw/w5s0bHDt+HCePH++KYuqNi2jDr1mAzKg8tiDAZFQeLufcS6rxtnPyBvu27fh+Ek3O2e3nCAi2k6kUaqoKVVUbOPWBz6gg4OLFi0imUnj85AlqtRrOnT/vxiFByS5/EulTDMtrF198sC94gpxmpVYe6B8/fhwn/CV/BpFJdjZkYFpleEMyrpIkYd/4OPaNj4PC6RHIFwpYWlrCw0eP8ODBA6TTaWQGBjA4OIgDBw50cvlN4ZVJsyhFrVpFqVzGqVOntisN7EBA7W046uTTdzMD4xrldjIKto1Hjx7h5cuXOHzkCE6eOtVxhaApfFluiU34NE0T8GRg2hmo0u7xiSC452AzWVohglH2GuQgNMvChGFqagrxeBy/37iB2d9+w3fff+9usAKpPITAAFAqFp2s6B724AG1bSfpY5qgcLKcgU8rpbhz5w4WFhdx+dKlUAoLnzq7jR7ayrYEUBtiioL9U1PYPzUFm1JssKz/x48fsbCwAADoHxhAJpPByPDwjjzfAqOHWmyTX1hehm1ZyGazHdE1O0a3fWBfCI3HNE3cvHkTHz58wIULFxy1ox2iIPr9imnbMA3DEU/gGvs7dN/8voOvlyjJMi8dNAjxWAyyJEE3DFRrtS16dQh9CITgxIkTSCQSuH//PmzbxoULF8AlnAOpPKIIQ9ehadpesN9r2LYN27K2aDwhFJ780hIeP37s7IibcNVFQQBhSgPux0Q5kZCA3/0zHGnB/kwGR48cgaqqWF5ZwcLiIvL5PBbev8ezp08blBi6HVzhLlrWqGhZFvL5PAghGA1oPNkJuIuiU6O8mxmYNo2yZZq4desWlvJ5fHX+PKZnZjpSiugEvE/FNE1YloVyuYx4LAaRTabdCXgbdS3bdsqwLegCYdl8P3gWpq6q6I+obDA6Oopvv/0W//n3v+P+/fuuYRZ8GyNg63kql8stP3cP/4RgjYlcQ5tPePbzy1++fIn379/j8uXLmJycDP04XjFu26+0gEAIhgcHMTw4iOMnTqBeq6FQKGBhYQHv37/H/Pw8Hj9+7PL8s7lc90EI29Tbtu38RynyS0voS6edJtFPAJd73uH77c/Br0QMmNV6HbOzs6hUq/juu++QzWY/2ZRWV5XHNEFtG+VqFclEouv73wxeZgavGLey/1H9SiqZhFEsou4N9lv45+npaQiE4M7duxgYGMChQ4dCYz2BEJgAipub6OP9eZ8RvuhgH7btNuZKjLvccPsJQaVUws2bNzE+Po6TJ040/TjObXQzMGGl1iB4y6/8vSGQFQUT+/YhmUy6D8/a6iry+Tzu378PSin6uRLD+DiGhoai0SPoluQgNyoSK8VZloWlfB6jIyM953A2A4GHStEmdjMD044aj6qquH79OsqlEq5euYLc2Jgj3xfBAPUCfFiUxbKRpXIZmUxmS6aNqWf01DiTLRnOVnx9HiQFqS0Ewc3CmGZjFqYFBoeG8NX5842GOcgos/Os7Sny7CEIluX2bW2jLDB7kM/n3QRSs0AfYBVjNtwHQHvJjwj+BHAoa/F4HBOTk+hLp3H02DHYto2VQgGFQgHv3r8HIQRDQ0NOn9nYGDL9/ZHpEdwXUkYhFIijCmOaJpby+Zb3oJdw5618gZl9jij3vbS5idnr1wEAP/3wA9L9/VvDPT/BufMeRpNtVEvFIiYmJ7fuOyGNVMkegBDi9FmxShhFc7/SrErsRyKRQKlUgmnbUFU1cuP6/gMHUCwW8eDhQ/T19SGbzW7rIQO2No+fq9Lblx3sW5arIxzEqzR0HbPXryOZSODrr79uucBcJRE2PY6r2XSEJll+UAqVy22KIgYGBjAyMoJjx49D13VHiSGfx7t37/Bybg6yLCOby2Esm0VubKzhIaVs4VNK3UXihSiKgGFA03WsLC/j1KlTnV1PpyDho9VbYVczMOzfVs9MuVTC7OwsLNvGDz/+6Awc+QTZfD8kSYJhmjBNE8ViEfv4DAW++eMvJKRnmRl30mKIPBr//ChZFz/8WZio5+o1zJlMxpE69YEb6Vqt1vZ57eGPD2pZLr9e8SdGKEWlXMbN33+PlEACtmg8vBeso3UXRjfwgTfmxuNx9KXTyGWzOH3mDOr1uivt+fzFCzx5+hTxeNyV9sxmsw0bm1C/4ml6tGwbGxsbqNfrGGsi+NBrNBvCFAU86bAr9NCISaTlQgE3fv8d6VQKV69dQyKRAJ/i+ykCfX6OsiTBsixXQ77fO7uFOgMkvQkloEu/QpxJ7Taf4Eu3K7zxKpvtacKNAlEUkUgkUK3XUa3XEY/HI5/r6TNnUGKJ459//hmpVKpxrg6lIOy7bTrhfRfxRQf7lBlk96a7f3Bu+u83b0LXdfz000+RmkoEQrYMs2lC6AXvKshICwJUPtnQt7tUFAWTU1OYnJoCpRQbGxtuQ9YdpsQwMDiIXDaLXC6HgYGBrSArpA8BAFZXVmBZFsZ2QHu9KbowTJ87t3JleRm///47EokEfrh2bUv9hn/nn9Awy7KMOmtAqtZq4QO1QhqyOjHQ/MqC5NFacShbodMsDLBlmH///Xf8/PPPDapEfCIzBaCz5vg97MELyzSDq2GUwjCMthJIwFbF2F0PndqFJll+AufZDhvOmEgk3EGRtmVhdW3NVfh59+4dBEIwxAdFZrMODcFfrfZAlCQQ00S+UIAoSZ9+amhII2YU7NagRgCRKsbz8/O4d+8ecrkcLl265MYuBJ31vnUDSZJAdB3FzU1QINiv+BNK8FB4OwARBNieZna/mEg3vXypVAq1eh0qa6QVI7IcCCG4fPky/va3v2F2dhY//vSTU7Fjf+fqPwIhUFW17fP6FPiig31T1yHJMizbbpTLJASPHj7EcqGAb7/7ri0uocA0kY1edFR7jaXHQFum6chtEtL0GLzsOjQ0hOPHj0PXNCwtLaGwvIxXr1/j+bNnkBXFzc7kAjiZ/IFcWVlBKpVC6hPxKt1rADo3yp9BBibs2O/fvcPdu3cxOjKCy998AzmoOfwTnrfI5AHXNzYAIHACYBCCxn9HNtIs8+fdlLVbWg2DPwsTayPY54b5l19+wfXr1/HDjz+6muc8Y8ungKr1+s41Mu/hi4Nt27AMw+HpM+6+zAICivYTSEBjxdjsxdTmkKBfjzicUWCDIrPZLCilqFarWFpawnKhgKdPnuDxw4dIJJOutGcQ9ZNfw3KhgFw229OhXZEQQQwgDLs2qBHNk0iUUjx98gQvXr7EwYMHcf7cucaqNiEOTfcTgveDlYpFR3EwIhfdW8HohEJq2zYItmRee+VXFEVxB1HW6vW2uPWyouDq1av45ZdfcOf2bVy5csW9LpMH+6KI+mdaMf5ig31ulEVRhMD4kDxj9+7dO8zNzeHsuXPItdmMKvqCgp7BE/Cr9bqT1VeUSAbHZqVUWVGw/8AB7D9wANS2sb6x4ZZmFxcWAEIw6OFkDvT3QxQEUDjB/r7x8U8eOFN0HqzvagaGw3fulFI8f/4cz549w/SBA/jq/Hl3nkHD2z7V+XkgS5LLQ4/Kc/eiEy4mZfJo3Al1QtkJQ0MWxjAaG/BbQFYUXLlyxTXM33zzDQBPsM++s2qlshfs72ELtg2bqbtZvCeMbTQfPXqE5UIB37WbQPJVjHsixQtsE4bQdB1RhjO6k1hZlYH3jh06dAgWHxTJ/MrbN29ARBGjIyNuUimdTkMUBBiGgc3NzcAJ1p8rGgLG3UgisX/9R7Yty1V2OnP6NA4HSLgGvW+nQYgzv6haryOVTrfviz0Z/4ZhkS3uvc3eJwhCz4Uu0qkUDBbsp1Kptq6pL5PBpcuXceP6dTx9+tQdTmqaJmzbhiiKME3zs0wifbHBPpgSjyAIDTrjpWIRd+/cwYHpaRyamWn7Y/kUXXsnOt7Z5+qGAdh2uAYye9AbHnDf4iCCgOHhYQwPD+PUqVOo1+sO3adQwNzLl3j29ClisRhyY2OQZRm1eh0jn0iFx4uulijPgnwmqgnUsnD33j28e/8ep06exNFjx8I3MoIAfCLVBA6usZ9KJrvLtHm4mK6ef8hLbTY5lzCj3EvwLAw1DNRUFZk29Z29hvnZs2c4fvy4w5tmPFBKKcrlMoYDeP17+CeFL/tumyYsSvHu3Tu8YgmkbAd2VGCKPqZloafK98z+GIYB0zBACAkN9nmjbSvp21wu5wxdPHsWlWoVec+gyEcPHyKVTiOby8FglYRO7ke36DarD3w+81t0TcONGzewubGBby5fxsQnbHaOAkmWUatWu1ZbCpsYHwSb9YJJzE73EvF43EkQ2zbUDibNj42N4eSJE3jy9Cn6MhmMj425GxjeTPw5JpG+6GCfNzwpsRiobaNer2P2+nUMDg3h/PnzHRkEkXE1e57ZZ9AMw2184QFHA32iw11sIpHA9PQ0pqenYds21tbWUGCNvsViEYQQvHzxAtVKBWO5XGQlhm7RTbe+S+PBVkbGVYaAz3l5fubQmFKToevQNc25XnbNxNOoyrVz2f84P/uyP4au48bvv2N9bQ2Xmmhqu9ilJt1auYx0Ou1shHtAF/A6J/fee+6PwSpq0g5tyNKpFDY2N1Gr15FuMwsDbBnmx0+eINPfj76+PhBBAL8ze026e2gAkykmhEBWFFDbxsbaGu50kUACPBVjZpN6Dc0wQATBEapg63abXwkQcGgKQpBOp3HYMyhyZWUF+XweSx8/umvn3r17GB8fR25s7JMNqetWicfVS2/Tr2i6DmDLp7iCB8y3eHn1fr/iBf99tVLBb7OzMHQd333/PYZa9D7sRsVYEkVUqlVMcPGJXsQNPjoT9fyewom/BGBH6GGCICCZTKJSraJWq3U0fPLosWMolkq4feuWQxOVpK3ZLp9pEunLDfaZUQacnVq9WsWbV6+gaxr+9PPP0cdI+yArCgi2FnWvYeg6QCnkeNwxNrYNSjpXrAmCIAgYHR3F6OgoTp8+jT//9a9Q63XIsoznz5/jyZMnSCQSDUoMOyXHGWaUKaVuVtj7L//ZsixUyuXA6b5RobEGTFXTILOpslFRYR31lDpylvfu3oWu67h8+TJGRkYcY0Sc4VKfy2hsAue8xycmYJgmYj00lO73yIw934hxjf2dugfxeNyRf7MsqKra0aj2o8eOIb+8jKdPn+LS5cuQRNFNFFT3tPb34IFlGK69iSkKVFXFs+fPkUwkOk4gAYAiyxAEAZqqAhH7aaKCUgpD10EohcL8V0MQy9HlGpUkCePj4xgfH4dt2/g//8//g6FMBoZp4uHDh7AfPEBfXx/GxsYwlstheHh457j8IdcS5FcsJoNsU+oMVapUGoYCtoNufAqlFJVKBYRlgEulEu7duwdFlnHt2jWk0+mWfmU3fI1umrBNE+lUCqZl9TRW8PeMcblNPjupZ5Q3H5LJJMrVqjuMsu1rIgQXLlzAyuoqXr58iRMnTjhDyFiS+HNMIn2xwb7XKCuyjJJpYn5+HocPHepqIFWM8eh1XXcmKfYwY0k9cwFi3oZO1owShcvWLgzDQHFzEzOHDmH/1BRSyWSDEsP8/DwEQjAyMuIO9Eqn010bFV6GMzQNOhvKYXsMcCtDa9u2WxHwnwvPpLi/5RkVb3aFEHcBS5IESZIaszeMr7qNLsXAX1ssFvH48WOIooiLFy8ikUyiGrCQBTaQTWAd+Xw4G+8p+RRQVRWGabpOoxV3t11wB0r49+fZpMo7tFnkWZhypYJavd5RsA9CcObMGfzyyy/I5/M4sH+/G+xzVYZPOXtiD58vLGafRUYPzTNq5MWLFztOIAEOJU0gxK029hKmacJiw+ckUXTtGpd5buD29wibm5swdB0zp05hdHQUiiyjsLyMQj6PhYUFzM3NQZIkZEdHXfGIRCdr1wfLsmDbthukte1X+KCmgL9F8St+nwJgm18JmwPg/f3S0hKePnuGTCaDM2fPggjCNr/iNqgyv+JuUCh11JA+UeBfKhZhA0j39fXeVgZtSlkFil//TkCWZcQVBaqmoVqtRha08EKUJBw/dgwPHz3CxOQkRoaHnWCfUtQ+Q/nNL9bDmR6jLAgC3r17B0opDh461NXn8nIMMQyomtb1JFsvNMOATZ2pjIRsz+ZvU0PpgYFeYaPMR4aGYNk2REna4mTCyQTzwP/J48d49OgRksmk0+Q7Po7RkZGm8lQ8qLdNE6ZlOT9b1lbm1zSbcrm5EeNd9wIf2MKMgCAIrrZvuxlkjUlgJRKJSHxDb/aa2jZWVlfx9OlT9Pf34+KFC25viM3+7m1GtW3bmc/g+SyD8cMJ2HMqSY5DFgQIO7AJKJZKAKVusN8rB+91YPz+c91wyjaqvKFxJ5BIJFCuVDrPwgAY7O/HyMgIXr9+jZnpaff3vHKzF+zvAfA0cDM/8PbNGyRTqa25FR0ixiq5uq67SYBeQdd12JQipiguNcVLJWE/9NSvFPJ5yLKM/oEBWEw8YnJyEpNs6FKxWER+aQn5QgH3vIMiWUKp1aBIHtRblgXTsmAz38JtkdfH+MEDdMHnV3iDNGE0Wq7E0o5f4c9HVJ8CbCWWeL/QwsICXr95g4l9+3DmzBmnWZptWvjmBXDiAIv5Fe994covvELAE0qiIOzIJqBULjvqaPF4b+jNXnpUwJ8NNjtJZP6yl6IPXiSTSaiahpqqoq+vryN/PLV/P16+eoU3b964YjAU+GRTjtvBF+vhXG1vSUKtVsPC+/c4MDPjLpaOmm/YIlMUBaquQ1XVngX7FHA1kGVZdnbpIQ+Ey2PrwaLNFwro6+tDIpl0JEp9jsbLybQ8nMx8oYA3b9+6lKBcNouR0VFnwQcE9WHXIcsy+Nj5IAMcBsOjtPSpMuPezdbihw+Ym5vDxL59+Prrr0M3PDzotz0/U2bYOfeQAjBtG/BRw3q9CSiVShBE0Sm3sgFb7SjYbF2UJ0vV5GWWJzDi2cNOy+Php+KsF0WWoRoG6qrakdKQZhg4dOgQrt+4gXfv32N0dLSroV97+GPCOzNieXkZGxsbOH3mDHTD6HhDSOGscz74TtU0pHqQ5eafrWmao9bG+Pph/ULb/EoXQf9SPo+xXA4E2wMbQggGBgYwMDCA4ydOQNc0LC8vI5/PY35+Hi9fvoQiy6785/DICGRZ3hbUh0EQRUiCAMqrqG34Fe6LJGZzPwXcXjHTxNzcHD58/Ijjx47hxMmToYF5qF8xTVDDcCoUzM+YAfe/l5uAUrGIPlbtN02z834w9p22EnLgvpP3gQVNq+0FXIoopdB1va1ZLhyGYWDm4EE8evQIa2trblPuXrDfQ7iBhiji8ePHkGMxHJiagmlZzhfXAYWBP06KokAkpCe8ff6QWqz0SOHwNwnLEDdbgMT7GZ0YaFYunJychCiKsBkXPiyrJEoSxsbHMTY+DtM0sbm5iXw+j5WVFTx89Ag2dWTahoeGMDw87Az0YiO1RUlyDQz/D+waLT7iuw3s1kAtatt4+OABXr99iwP79+PCxYvNvyNuTP2fY1mwYjEnO8UyUTxbZVsWTMZNDNwEMK6iJEmQRNEpzUe4D6VSCZlMxpk9YVkw2g32eXDP+khagWd5JElysmksCyP0MODnmZ14PA7NMKBpWtvBPh82lEwmsW9sDM+ePXMyi0whpZf9Mnv4cuFO7YTz3D15/BhDzNZpqgq5hX59KDxJpLqmQetBsM8zo7phOPaV0Y6iYFtTJD/HiLZWVVVsrK/jILONdkASyQslFsPk1BQmJidhmibW1taQX1rCyuoq3i8uAnCGNQ0NDWFkaAjpTMYN3iVRhMD8CU+GUDD72sG63a3ZLYZh4Pfff8fq6ipOnTyJY8ePN319kF/hFY14PL41uZzde558szzJJv8mQGDUVu5bREGI9J0XSyX0DwxAkiTYtg3TNKFEDfY9VYqoPoHLqEuS5ATj7JpEUXSb57sFr4zE4nFY9Tq0DoJ9nlAbzeXQNz+PZ8+e4fxXXwH4PH3Klxvs8wa7ahXz8/M4f/48Uuk06rUaVFV1OZJtgWVFYrEYiCC4zTidoIESAqcxl+9WeZY4alDUIP/YeJCmi7VYKqFeryM3NubqvwYZSN4Qyx9ek1FvBFHEvokJ7JuYgGmaKG5uYm19HasrK1hcXHRk2rJZtzTr51O78o3+844AlzbyCWU3TdPE7Vu3sJTP49ixY5icmOhc4g1wFRpElmlpcMaUhm8CWAbHWzKVvME/z6T7sFksIpPJQJYk6IQ4VLcolSm2KXMR4Zr5OdrYUhrxK1z0MuiPxeMg5TIMw3A3FFGhapqz9kQRp0+fxr//x39gYXERBw4ccL6HzzALs4dPD8rWIADk83lsbG7ihx9+cDaamgZVVTsL9plfURQFItATv8L/1b0JJHacqCuuwa9413wLv1IoFEDhKF2pmhaaRHKDTtOEaRhOxpZSKLEY9k9PY//0NHRNw+bGBtbW1/Hxwwe8m59HTFFcn5LNZrf1HrWtKuQ7J/+17zTq9Tquz86iUq3i7PnzyHao0sLpSQTO98WTatv8SsgmgDcog1GguYa+2CSpRClFuVTC/qkpSLIMg/klpVkylfdzReih8MO2LFic+sqeJ4EQ2GAVWN670GUwzc8rHouhXq+3vSYppe57YpKEkydP4sb161hfW8PwyIjbR7KrM4J8+CKDfa7aAgAvXrxAMpXC9IEDIKIITdNgmia0Tig4ngwMgbPDNAyjbQMftIvljVmyd5E0KbmGoZ3AP5/PQ5IkjAwPuw+mZZqNRpj95z9fb3ZZZtmA7OgojrBrKxWLyDNpzwcPHuD+/fvIZDIYy+WQGxvD8NCQozXfIbyym58CqqpidnYWlUoFly9fRiqV6jzQj3LuzTYBLHvCN2B2QKaGG2fR0yhWLpUwNTXlZNoJcTYRQSXXiOXUZnAzoOxc/NfbEPSzHoxO7qdbbZNlCKIIyzSh6ToSEbMwpmXBNAxQ20aczR84ePAg3s3PuzzsPRrPHoCtShUhBE+fPsX42BhGRkZgM6EBwzShG4YjbxkVnjUWUxQIzEe1i7CmT52pu7mT0zsMhrwrs1VVr1AoYGhwELFYzA3+vAGm4fEr247DssuuXxkYwNjYGABnHa6vr7s9ZAsLCyCEYJC9Zmx8vKGRsiN6B68Yf6IgrLi5idnr10EAXLt2za2CdgL+vbT0KyGbAO5DLNZfR6kzm8jgzz2wFfizfyuVCizbRqa/H7IkQYUjt7wt3vBn8Dv0LYZpOo25jPbrXNJWnETANnucMtrhxo8/N3wjaRhGW71bBq+oseTw2NgYhoaH8fr1a1c+dS/Y7wF482G5VMLHjx9x6dIlN6BJJhIol8vQVBVKLBZZQcH7aPIAzDBNaJoWOdh3KRC+39uUwmDqQW05ihZoFfgv5fPI5nLuA6eqqjt8LCi450aYL/Sw4IwQgv6BAfQPDODYsWMOJ3NlBYV8Hu/ev8fLuTnIkoShkRGM53IYDcjOtAJ3Vp8is18qFjE7OwsK4McffkAylUK1Wu342K4mfWdv3qJBMVi27RpoPqnPDf4ZBUhVVVi27epcuxNAuQRnDwJ8L1xepcc4ejP73t9R78/tGmfPZ8UVBTXLgqZpkYN93qQty7I7MO/YsWN4v7CA9+/fo//06c+y5LqHTw8u+rCUz6NSqbhTlwVBQDyRQLVWQ61Wg5zJRN64Uk+gosRizsbXtqHr+laA3uozaKMOvHu+zBYA6KziEIKGwJ8fl/cz2Tby+TwOMSEMattQVdWppgfYeMEX3AtN/IogCBgZGcHIyAhOnz6Neq3mzIopFPBybg5Pnz1DPB7HyMgIxthGrN0+il4P/muGQj6P32/eRDqdxrWrVwFCoKpq51UFfu6dvN/zPSAWa0gq8Q2A7a0osw3p6soKACCVTLo9ANz/SJLUNvWzFTg9u+X3yv1MgM9pB6IoQpFlaEyQJR3heaLUM62aMUgogFOnTuEfv/2GZdYn+bklkb7IYJ/LVy4uLiKTyWDSM3FOlmXIigJd11Fng3giwfewKIqCuqpC1XW0Ygi7neUhDxwP9HmTFgcfWd4rDpr3fAxdx2qhgFNnzqBYLDobF884dX4u/D+xiRFuBSUWa1Bi2NzcRCGfx4ePH3Hn7l1QStHHsv5jY2MYHBxsueP9VJz9leVl3Pj9d6SSSVy9dg2JRMKZhQB0rljR41KxKAgQFQU8NHBVKjxZtWKp5KrilEsl2GCVKUJ6GghwmCFGOazxnHRonL2vi8fjqLVRcjUMw6luMKMMOGsjpiiYmprC4sICTp08+dkZ5T3sDrhfef/uHSYnJxuyyLF4HKqmwWKbzcj8Xs/zK7C1yHtPWgX7YckjDs0wQMFmw3hsTVfJBh+4HCU/n9W1Naiqikx/PzY2N6HrOjRdByHE3czwwF6SpKZKbq2QSCYxffAgpg8ehG1ZWFtfd/zKhw+u+t7Q0JA7LyYTYRPG1/pOZ1zfvn2L+/fvI5fL4fLly5AkCXWmy9+xX+ilL/QklfgWzU0qsQ2AbdsolctQYjEYhoFSqeTQsdhmVSRkK8Dv0blxaqg/TmqmytN2oO9jVMTiceiG4VTJIsSLGpNlFwA3eUsIwdDgIEaGh7GwsIBDhw+7lMDPBV90sL+2vo6DMzPbFk8iHoeu69B1HWYs1pGKQiwWg0gIdJYZDINXrz0MOgseg4w7EYSOS15BME0TmmFg6eNHUEKQSqcdqS42XZEIAlLJZEed51FACMHg4CAGBwdx5OhR6LqOJTZx8e3bt3jx4gUURUE2l3MoP7lcYNb/U3Ar38/P4+69exgdHcXlb75xg+JINJwm8H6bO6EkwJvXvOf79s0bxONxyIricDUtC/V6HdVq1eH0KopL7+kWlFKXDrYt2I/wfreJt0WW33/v+PrhFY5m65pS6vKJ+ewMACDs80ZHRjA/P4+NjY0dkwzdw5cFkyVEKpUKTp482fA3AsevVKpVqJrmBrbtQlYUCKoKVdNc6ccgROE78wGNsR3YzPvPxTBN6LqOjx8/QpQkxJn4gJuxFwRk+vp2TMJWEEWMjo5iZGQEJ06eRK1Ww9LSEpaWlrYGRSaTyGWzzQdF7nAvGKUUT588wYuXL3FoZgZnmYa+99gd01u9VJYeJQm9cJNKzM7ato1SsYj+/n4nKcmeA1XTnD6oTMatmPbiXCxWLeYqde0icp+Y7+/xWMxhg+h6S+oNF3uwKUUykWhQ8KOUYmR0FC+eP4fFZNY/J3yRwb7JDLKu64HNLpIkIaYo0Fh2v5lRBRAYbCuK4jTphgzXCuNQbvtoADqn8AQF+10Gg7xRku9M+QO2ubkJSZaRyWQQZxuemCxDY82K/NywA0aDnxfg3McDU1OYnJiAbdvYYFn/fD6P2wsLAOBmZ3K5HAYHB92KB7AzwT6lFM+ePcPz588xPT2Nr86dA/HQZvixe1FV6KQ5uROsrq5ieHgYfamUw5tl2UOLGSeeieeKIpIkdezweO8Al3XzgqD1Nbta4J5sfxR4S66tJDh1xtMnYLxMzxqj1JlFIEsS1lZX92g8ewDgJJE21tcBAKNMM9uLWCzmDGHj05xb9IQFrYGYokBAeJNulOQR4KxB3jcTVLnrhV/hAT5vAgaAjc1NZPr7EYvHociyY0tE0a2iSUwth5/DTiGZTGJmZgbT09OwLAurq6uNgyIZJYhn/fmgyG4TOc1gWxZu37mDxcVFnDlzBocPH26suPfw2Jw6slPgm831jQ2cOHECGTZQS2AxkcUozjqr6siSBIn7lQ6/9wZ1N99nRPnEbX4l/OIa/peLuZjUaWBupuTI160oCM4gSf6dUkfkYmhwEACwvLKyl9nvBSil2Fhfh0CI2wzR8Hc4JX9d152dqKo2zWQHPRayLDsLilLoptkw8badLnOdUWcEH4WHo9OSq2EY0AwDhifAB5xFoSgKKpUKRkdHkfFsdCRJcgcT8dfyHWmDIdwhIy0IgiPbOTSEkydPQlVVZ0JlPo9Xr17h2bNnUBTFLckORKD7tAvbsnD37l28X1jA6VOncOTo0W3X21Nn1UETdivw54+fn2EYKJZKmD54sKH3wrZt1FQVoiCAAG6/huExqrIsQ24z8Hd5lSHya4IgRMqWU/afEGKcg37HJTh5tSzw/CwLGutPicdi2xwF/9SBgQGsrq7uqfHswQHzK/0DA40Tzvmf4VBLeE+YJEnNe7CCkkhM6c3djHrWndvcGAE8AOczW7ahA7tDWbBjsPXlfTenIJVLJUxPTzfQYyVJ2tp8EOJmnvlwr17aU+rzdYCTBNg2KJL5lSdPnuDRo0dIpVLI5XJI9/VhYGCg5z5O1zTcuH4dm5ubuPLNN9g3MbHtNV0nkbw29RP4lY2NDViWhZHhYSegZ5s7i/VpiKLovkc3DOiG4VBJ+SawzcCfz6QJknAN6gdrdR1BG6Kw97sSnJoWGuwbbG1Yto10Muk+3+5n2zZisRjiiQRWVlY+O3roFxvsr29uYmh4OLDcQwAQUUQimUStVkOtXofAsoKBCFg4AiGQFcVp3FBVxBTFzUK2kzHh/O9mpVZeumoFmzpyTzxj654+nABfURTIkgQKJ7N/9OjRhvfzzYZXJWEb19Oz4P2Nlu2g4Q6FvDcej2P6wAFMHzgAy7axwZQY8qzRl/PgxsbGMD4+HomT2QyGruP6jRvYWF/H5cuXG3o9GsDvbbeNVD2At4Lk/6441tfXnRKib+PLtalFSUIymXQz/ly+knP+63CeH64W0grcKIeW7Nu4bw3ZfV/2PQixeBykVHKqWAElV9u2UWPcWDf74gf77KHhYTx//hxqC6reHv744Bn19c1NTIXYBd4Tw6vGtUoFQiYTuukN8iuKLDubb0qhMlUpt9LaRnBgsCRSmE9rp6Jo2bbrV7yJI4EQx6+wwK1aq0HTNAz77Iwky4CmNaiFNdgqoGd+xYuw60un0zicTuPwoUOwLMsVj1haWkLtzRuIbFDkGJP3TEXt6wtBpVLB7OwsDF3H999/j8GABKT3fLuSc+boQbDvD+7957a2tgZRENA/MNDwPlmSYMmyG3Nwv2Iy6gr3MQIhkGMxxMI2pL5zMUOooRwCIbAiXjNPovqVqcI2DK0kOE3LQl1VnZ5HLvbgvwZ274aHhrCyvLwX7PcClmVhc2MDx3zBrBe8fG9bFlRNQ7VSgRDGKQwLLGIxtyHQDbra+AIpAJ09wM10acMymxwmuwbdQ8HxB/jeRVosFmEYxjajzLl1NmvECWqeClv4bnMlEM1Y+66n1a5c9CkxLOXzWFtbQ7lUwosXL/D06VMkEgmX65/NZttqPK0yg6xrGr777jsMj4yEvrbbCkdbzsy3gQw7drPPWVtfh6IoSPvoanxqoncqqCiKiMfjrkSewYJmXq6XJKkpv58yJQZKaWjzndvU144zYtQFkVG4whqyFFmGIEmwGMXAW7GjlKJWr8Nm9B2XU+k7D/65I8PDoLaNDx8+YObw4ejnuoc/HCilbsY+TAedZ94TyaQb1FQqFfT19W1POjV59mVFgcrUP+LxeNMm3CBYTImL+4BARLBdnOqns0ZfgAX4LEDz+8q1tTUADu3SC77Z4cFakN0I8iuuyhAcGoS/1ykKWnHXRVHE+NgYxsfGcPr0aeQLBaytr6NcLOLRo0d48OAB0n19rnjE8PBw6HCwIKytruLG9etQYjH89NNPSDUb+MefiQ78yjb1PETfzLkVo4B71dSvrK051XXfa3gcYZkmCKMIS5IEJBIwmVw5D/w1VXUG0rHNQVggb7E1IBDSfPPcJlxVP07xQQi9rokEp23bqNdqjs8TRfe1286GHWt4eBgL79+juLmJAUbr+RzwRQb7KysrTnkpwnCKeCLhSBAaBirVarBhDgHncmlsR9cuvAOAmjYuBQQknD6kqapLuwCchRaPxRDzKTB4sb62BkEQMOh70DjFw2YPdDtKCe0a627AJ6ZOTExggKmlrK2tuZzMd4yTOTw87AxfyeXQ19cXej9Km5t49PgxZEXBjz//jHSLCazdBPv8ngS90/09e43rqLrMdK2trTm9Dr7fc6NpWdY2yoAb+DOtbK4jzrP93OkrvqwMDzKC+PpecG39dsCpRv4NpR9cglP1qKLwQN+yLIA6k569zVPee8O3EOlUCol4HIusd2QP/7yglKKQz4MAoX6Fb2IJHCnCSqUC07JQrVaRTqcbgiIaYNM5YoqCKhv+aPf1tc3h5sG51CJjGqS3z2UDubIQhyxJiPH13sSv9PX1bdtgcElGyjYhgdW0oPPzHofdV36OXn479fzdn0hpx15SSpFKpdDX14f+TAaGYWBlZQV5pvDz6tUrZ55MLuc2+voHRXqxuLiIO7dvY3BoCFevXIHcSl3JE3i2Cz/d1/0Ef7KI/S6Q897mvVpdW8P09PS2v4mi6MwhCqA/8sCfxuMwGdWYzysyDAOCKCKmKA79zHM+JtPXbxaTcL/TSca81WR3tx+MrQ0uwWnbNqq1mpOAgtOkH/b9cX83OjICCmD+/XscOHiw7XPdKXyRwf7Hjx8hSRIGfOWlBjBjSwhBKpVCpVyGaVluJkbwBKxh4Ds4jXH/oxoxDleFp40MtLsb1nWXqkPYZ8RisUjZ7PX1dfRnMoEZCkmSnIVnmmhP+X47mhlri1IIlIL6fh/6fg+8wTYhjkRYNptFljXNVatVN/B/+vQpHj96hGQyibGxMeTGxjDq01++d/8+BgcGcOXq1eaT//jxW5yf/1zdV3mdvfNHAI7B8AaeWy/vnjdq2zbWVldx7NixbX/j986izkAVOSQwkJmihm1ZTh8IK+e7+tmy7MysEEW3VN9qo9jNlXHnHhYsBUlwqqrqKATZNlLJZAO9Zxtnn10DYeX8xcXFLs52D38ULC8vIzMw0DQxw58lIghIpVIoVyowTRO1arVxEF8Tv6KwPpJ6vd4yMx0EvQWFZ+tkPcEUp+qoamN1OBZzBBwiZLPX1te3ZfU5eI+Q1YGf3H7aAYEqHFvrtaX+zXyrJA3/O/f9sixj37592LdvHyilKJVKLo20YVDk2BhyuVxDf+C7+Xm8fvMG+6emcOHChUj0x3YadP1+hbLJ6vx6G+6FdwPEXt8tKtUq9ADKFsCCfUFwFGeChjbC+Q5kRXHV4XRWQbKZSpyqqi5FjA9LBFrr63fqM12KcpPXKIrSIMFJKXXWqG2DsIpew7MXUjGOxWLoz2Sw8O5dR+e6U/gig/1CPo/9o6NNmze95Roe8JcrFViWhWql4nbnh4HC2UXGFAWmaaJSqWCw2eYiAM1UePznyiWtvI1RAiGIxWKuLn5UrK6vh5aig3j7vQYhWyO9AU/w5gPP4sLjIHl2dxu/07O4UqkUDh06hEOMk7nClRjyebx58waCICCbGUb8Yx1JA+g7MIyr1641NcjUcy42n9DHj8n5f35j4fkb/39eLvXfj51CqVSCaVmBRhlgzXNsGm+rjaIgikjwbL+uQ2PGmTdfiZLk9KA0K7UyuM9Ah9flL7964Zfg5JxR27aRTCQaNrlBRpk/WwIhGM1m8fDxY1RZsLaHf05YloWV5WXsP3PG+QVb2354n0dBFJFOp1EulZzmxHodqSaZYACuDK4oijBY4NPqPQ3nyXptCBDYROyHbhjQVBW6tzosCK5fidosahgGNjc3cTAkUylJkiN1vYN+BcC2hmYe5HtXuE23J2AInGBsW9+dxz709/ejv7/fGRSp61heWUF+aQnv3r3Dy5cvIcsyRpU+jK4Ai+obHD93HCdOnGgeR3jOJSjrHiZMQPx+xXsPPNe1U1hbXQWlW+oyXhDiTH63GEW01UZHZP2Tcdt2fAlLJvE+EUmSoGkaSCsGBEMnG2R24oA38ea794lEAtVq1ZXg5NUvm1KkEonIs4GIICCbzbqzIHbS/7eDLy7Y53JQp7i+fohR5q/lN1oQRfSl0yiXyzBME9VaDekQI0uxVZJJJJOoqyqqtVpbwb5LnUDz3appmqjV6w18fEkUEYvHncaWNh8UVdNQLpdxPCDTyz8b2BrM1A4/sS34vpegq2goRfIfEZKh8b6GGz9CIHjKrvTMGVQqFVT+z0Nk/n8FUMPGISJg/fk6HsUfIjs1juzICERBcN/vPRY3xl7n4c3QbzPLEb+bbmXwmmF1dRUCIdsoWxycX2kGlFzDQDiFJxZzZF0ZxccwDFRqNRBCIs1p6MV1BzX1eSU4S5UKJFba5RKzvpMIDPZBCIggYGhwENS2USgUMDMz09W57uHLBR88mMlknF9EXNuiKDqV42oVmqZBIATxEElO7lcIm8irm6azyWwj2PcqljSj8Oi6jnqtBo1tDACnghdnkpntYmNz0wn+QjL78idIIgUiYH03fHO+bLj37zyBs/XSLbsvKwomJiawb3wcALC5sQn9f91B3/N1WBYBBUF+4Q2eWDbGxscwxLjtnL5F0Vh58FKTvOcSfEmtnz3iv84eY21tDf39/aEJIv78mZaFqE8TYZtMhSVQ+eZQU1XUVdXZPKdSTecQcCpPJ36FJ5/CAnBOLaKUolKpAEBgAglAsE9hfkUgBINDQ3i3uIharfbZJJG+uGAfAEDp1i4rZGEQbF80gigimUqhyjT6a4KAhC9o8S/EZDKJzY0NaCzgiVqi9MobBj1YtmU5QT6j+hBBgMKGlXQzmGRjfR2gNDTTy/sHDMOAuUPBvquuEvZ39m9D9iXEKDdd0v6gnBDEnm9A+scyAAJbFECojeE1CuP/v4DZk0yJIZtFLpfDeC6HBFuI3u/c9pZMPRl/r5FoyNa0QhNKSrdY5U1UIQaSP0t8CFa7m0eXg2nbqFQqEAkBCIGqaTANA/F4vLkqTw+uO4hvGY/HUWeN95xHHFhBCzDKtm1DYEZZEMUdz5Lt4fMHf7ai2EP/OpIVBUlKUavVUFdVJ6jxPYveBBLg+JVapeI0lFMaOcPeSgmLJ49MNnhSJI6iTiwiVScM62trkGU5dGaN27RpWaHiD90iMMDzUSeJ51/4f/YE4Q1+o9mx2OfHf1lA/EUZIDyuoBh/a+LlX17j16kXUGS5YVCkEos1+hQmagCyJSHZyhZ7XxN4nj0eyOnF6traNnU3LyRJAvEpMEWFV8bTtiwUSyX3e6nUam7/SNjz2mkSyWbSsEBjQtH7cyweh1apoFyrIZVIBPo37zPlfjav9gmCUzVm/35O+OKC/ba+5IBgQ5ZlNxNTr9UAOIEDNxL+pkJRkpwMJ+P7R83uhxllatsOZ83DN5YVxWn8QPeUj7X1dcTjcSSaDHyRGbXD9M0P2BHw+xnAl6P+1zC4DTjtVjVUFSv/8RBBBKaxNYJ//elPWFopoFAo4OHDh3hAKfr6+tzBKyPDww3ZfsFraD3Bf8O5e0D463ybl50yyJRSrK+tYSJA05mDT9u12PjzTjd3RBCczXIy6X4vpm03Nc6dPsteXi7/HL+SgihJ0Op12IRggJDwQShBGRj2ez/3dw//vPAHd2EIs9ExNlFWVVXUKhXQVMp9JoP8SjwWgyCKoBEHdHGYpglQui3p5E8e8WP0alI65+uHrRXeH8QlFHci2AewtZ491E/XxoYE8fxnTu9pd70XNzdhXH+DIFmHo2o/xn845dBIl5dxm/X/DDLJ6Fwuh8GBgS1qbsOltPYL20QceOXAZw97CVVVUSmXm6odiixJwjcxHXPpBcGpjiWTEFjfB58Fw/sUgwY3dnaw7e/0V44JAF1VIUgShjKZwCqYEFQtZjFLw6b9M/MrX2awH9FJhy0GWVGQsG3UqlXU63VYpulmeIOQTCSgtknl4UaZB/uUUqiahnq97j4oEtM/976m22mea2trGGJDMMLQS95+Q+YbTlnUtm3YlrX9HFpk/L2f6Xxk9MVSLBYxOzuLr4sh16RZSFsSjh49iqNHjzpKDMvLyOfzWFhYwKtXryCJIkazWWQyGacy0uZipfy/gLLyto1OD7h8tVoN9Xo9tIrDITKpStM0Ow72KTPCFEBfOg0CZ5qgxpq9DdOEIkmIxeOuce7k6popbPDsj6qqTlBDCERCIIVsWMP4+v7jfF4meQ+7gXaSSGGZxUQiAcoD/lrNVRWzA9a6n8oTJdinaJwyCgQnjxSWPOIBt8UUtDoFV2Y5dOhQ09fxJFIvxB+2cd3RWHHdlkCJYksjbui8yOfzuHXzJv61HPJ8LJUxNDyMoeFhnDx1CqqqosAGes3NzeHZs2eIKQpGs1n0ZzKRFAS3nzbdft2Mf+57YQN9qFPwuS3N5Km5GpvNhql1ykYwGSdeEAT0pVKuMIRhmu6Atxir2rZic3QKnlyqsyobhbMpa0fa25vZB9pMSn8ifJnBfpuvD3r44/E4BELchgzDNB35tIBgKJlKYXNzMzKVx6Z0a5Q5az6psa5uwGmQSiST22kHXT7EFqVYW1vDiZMnm77OG+wHDSYKg5tN8PASqU8RwKXoBF1L1OtrM9hfLhTw+82bjqxaWgaK5ZbvkWUZ+yYmnEmHlGKzWEShUEB+aQkvl5ZAAfT7lBginY9tb79OJkvXAL458vwqqDzYDGtra6BA62BfFAGW3e8UfDqiKIpuMJ9IJKDEYlvG2TRhVCoNxrntkmuT13J1BIM1vnO1LNuygCDDHBDs86qR95n//MzyHnYDvajwJFjlS63XUa/XoRuGw0MO+OxkMolqpYJqrYbhCFQeXi0WBAFEEFBX1abJIw4hQIKzHVQqFRi6HsrX53D9Srt2xl/15b4l0lu3uNKtYLfpV96+eYP7Dx5gbGwMhOQjnVA8HseBAwdw4MABUNvG+vo68oUClpaWsLi4CAJnmN9YLofc2Bj6M5nO/b7/e/VQVPxNwO0822vr64gnEk3ZAYDjCwwmkNBxsM8qUZwvLxKCVDLpzBZSVedfNgMmxvpNCKOStlMxp0F+2YNqtbo1u4INzWonNrJ9mX0uUPE54Q8d7Dcr2VFKISsK0oKAcqkEy7JQLpeRSqWciYAeeKk81WoVA/39TY/LjbJl2yiVy26QRViPQCwWCzwvQilsdJ5pLG1uwmqizMIhsNIZZZuSKA80te2tDJXnOwi6jrBvKKr2up9G0wzv5udx7949ZLNZXL58Gdbs39sP3gjBwMAABgYGcOjQIWxsbmJjYwPlYhHz8/N4wZQYstmsa6RjQbSRAKoS/30Yusn4r62tIZ1Ot1R7cnWRu6jkGIwD7NeSFgUh1Dhznf6o3welNDALyv9WrVZh2TZs20aCDQar1+vhFaqA+75tZL0ng7iHf160W01stk4TrKGvUi7DNAxUymUk0+ltVbU4k7M1IlJ5eB+YbVnYLBZbJ48Y/Brt7WJtfR3UtgOVWbzgAZ/NKINN/Qp1ZJnbHVLphxv4tYGWfoVSPH78GHNzc5g5dAhnz5yB9n//n7aOATj+fnhkBMMjIzh8+DA2NjdRZL7l+YsXePL0KeLxuNs/NprLddWvt3Vg3/ftu95WSaXVlRUMDw+3tIuiKDpTbU0TiCBp7QelzmA6iu1ZdIk16xqG4cgqU4q6qkLXNKd6LEntU7oDYFkWarWaM9SLUqT7+pwBk6wSHsjXDziuV4kH+DyrxV9csM8ReafabAfIy0eZDKq1GixmmBPJJGI+rqOXytMq2Dd0HTXWDyAKAkAIEvG40xvQ7LwJaTlNtxnW1tdBBCES1UiSJGcSo2luLTTPcYOC8nYcYTeIxJ+lFE+fPsWLFy8wffAgzp8752j/dnVktgmUJIyPjeHokSOglGJzc9OV9rxz9y4AYHBgANlcDuNjYxgYHNxyOt1UNNhr/Xcv7N2rq6stN3aAZ7iWbW8brhUFNhuWQ4HQqlaQceZSsjEW1LRC2MAUr0EGnIFGkiRB0TTUEUxHc/snfHCDC3Y+e3z9PQC9SyKxD4MoSY5fYRnDcqmEVCrVsFlul8qjaxoqlQpkWUaMOGpSyXjc0e3fwed4bW0NmYGB1tK9TPxBZ0Mb3c1HmF9p10+EvL7dJFIze2yZJu7cuYMPHz7gzNmzONyjydqUUsRjMWSmpnDs2DHYlrU1KHJ5Ge/evQMhBMPDwxjzDIpEk3igne88qF/OpUl5Nq6mZWFzcxOnJydbfqbYaSWHwa1UIbwxXmaTnLmErEWd4YlcPjZS5j0kBjQMA7VazaU+pdmcDEmWnSq1acLf8RLE1we2MvvtSKR/anxxwX67gWSzJhY3gywI6EunUavVoGka6rUabMtyS7KAh8rDKAthQY9hmljf3IRhGG4WP5lIRA6wupErXF9fx8DAQKQFIEkSVEZLisNTDu0FmhmnCMdwy61hf7cs3Ll7F4sLCzh9+jSOHDnSMx6fq+/Od+jEkbUcHBzEiRMnoGkalgsFLDFN/xcvXiCmKMjlcshmsxjJZrc1PXd7Zt47RljJWtd1FItFHIrgjAghEFnzk2maLSc9+mHw6YZsUmYz+I2zbdsoVypIxONQmkx9BhBukOt1p7lYEJD0DMwSmvWeCMJ2Tiu2HBM3ynQv2N8DPJm5iK9vZqd5I6goiujr63MCfsNAtVLZlkiKSuXRNA2bxSJM00SCUSxaJo+859sFlWd9bQ3DLSg8HJIkwWRca1lRuu5B86LbPqdWE2w1VcWNGzewWSziypUrGN+3r+NjbTu2r3IksP6w0WwWZwDU2KDIfKGAZ0+f4vHjx0gmEsgxGunI8PD2puduk2r8B+6XCcHmxgZMy2pJ2QIcG0oEAdQ0Q4drNYNbLW4hMU4IcaihbMKtxvTvK5UK4olEaynZgGdQZYNLbTiJqkQi4a49URBAEH0TwxkSQDQ2wm7hiw3229rVBhgJ/yAOwDG8oig6+sSaBtO2kU4mQURxi8pj24FUHgqnYVJVVWfoCSEYHBjYViFoiS4eltXVVYwzXeBQsOuWGI1H1/XgZtou0C73PAxBGyRd03Djxg2sb2zg0uXLmIyQgWgH/JkIC2ljsRim9u/H1P79jhrO+joKzEi/YxPzBpgSw9jYmPOcdMAxDD0/9j0tLy8DhCA7OrpVpm/y+ZIowiQEpm1H1kXm0ENKrWHgxlmWJNRV1Wm60jQ3UAnaMPgpPJRuDV2xWbUl7jHIgEfbOyigCKHw+DMwn69p3sOXhiCBBUII0um0M/GZNe5aluWqWrmqPKYZSOWxGX2tXq/Dsm1IkoShgYG21W6aJb2aQTcMJ6lw5EjL11I4GxwKJ5D7VIF+1CRSsw1dpVLB7G+/wTRN/PD99xiMuLmJilYbjWQqhZlDhzDDBkWuegdFvn4NEILR0VHkxsYwnsshxYaC9mpoE/crhUIBMUVB/8AACKu0hn26d7iWaVlQ2gj2Gyg8EZNPhK0XWZadGI01p3MJ6CC/QgB4n0Le96WzfsU4k6X1S+mSWi2ygInl+W4FxvX/HPHFBfuAk4nnu8JWCCq5NnS3+8ApB9VqFZZhoFypIJVKQZSkUCqPZVmosHItb1ZJxOPtB/r8nDvI7teZIxkKonV4NjbeaoYkCDApbaTydIlmDVPtcLeB7d9bpVLB9evXoWsafvj+++Br7RLtNHHxsuswU2Ko1WqOgS4UMPfyJZ49fYoY42RmR0cxMjradlY9DPl8Hpm+PiSSyYYMjbc064UoSQDnV7YBrrbQjMITBoHx+UVBcLS/eTaGZfn9r+VGkrJSrWEYsClFXFECJQRFNsOCy/15+ZVeNQ8Ofu1cScKybceOENIbruwevliIogjKKl9REZhECnltMpGAKAio12rQWWYylUo5U6sTCWfQo4/KY7DJ7TalsNjQuFQi0ZmsZYcB4fr6uiMCEBL8+n2pzOyMyXprojY4doPIfoX96//OVldXcePGDcRiMfz4449IpYNENruDm0SK8D2Ioogc0+vH2bMolctO1j+fx+NHj/DowQOk0mkn4z86Gpz17xD5pSXkcrltGwl3sxjgVwTWpNsO+BwIQlpPY/dDFASkUikQpkJlmCZMtna2cew9G0HbtlGr1WDaNijbcAdVBSTWDxAYtAfEZa5Clmdmi8ESvjs2tLQDfHEeThAEDAwNYX1jI/qbPF946JfogSRJSPf1oVqpOI27pRJisZiTWfRReVRVRbVeZ4dxhjIIothd8CAIQJuLZ4PJZXmbqCia03NkRYGlaU7JtUfBPki4dGJUdxOUBVlfW8P169ehKAp+/OknpHfAIAPYKvl14KQSiQSmp6cxPT0N27a3OJmFAt6+fQvAUc7huv6ZTpUYKEU+n8fU1NT2P/EffIG/JIoQ4JQm28kG6YzCI0lSx447xrKXnHdfZ9WvhmwMCxoMw4CqaaCsvyDMIAOO4xRFcZv8W9iV8bKs17msrKwgFou1rojt4Q+N/v5+QJKwvrYWaZKyP4kURTaZz6KoVKuwTBOlUgnxeBzJeBzVctkdsEUIcarETE5TZNx8w7K2iUe0g06oPBsbG1DYbBqOZskyQghktnEyDCNYyKDHiGTJQkQlFhYWcOfOHQwPD+PKN9/0LBnjR7tKQC5YZejw4cM4fPgwLNPE8soKCvk8lj5+xMu5OWdQ5Oio61eSHU5sVet1bIRUcfwb1Bk2BwAA2I1JREFUJR74S6IIDe3z9nlWP9bh80wIcRvhuWRmtVZDzJ+pZ423mqZB03X3uU0HNMxzeBvNLUYf5ccMiqX4RkeUJPfvKysrGNu3r2dzLnqBLy7YF0UR+/btw8fXr6EbRqTR395dadRhFKIgoK+vzyn5aBpUTYNgmgBTsilXKu4kWoAN60om3cbcdrOggefbBvj5xBMJx7BEqAzIHt5+r9ALfVl/ufXD4iJu37mDwYEBXLlyBcoOOpBtai3twHPtAjPAo6OjOHPmDKqVCj4uLSGfz+P58+d48uQJEomEk8EZG0Mum42cndnc3ISqqhgbG2t+OvwH1szHeezUtkEiZhwMXe8oq98A4kwUTKVSLufSm43hEm6qqjpZF2ZgmxlkDom91zBNxGMx55pD+Ppeo8zvzcrKCg4eOtS7ze4evkiIoojs2BiWV1cjv4dnP3kCKYrFECUJfX19qNVqzsa2Xgdh1Bebqb3ZluVS0+KxGJLJJIrFohNcdbkO20W5XEY6kwGAyPQEWZZhWNYnC/ajyG96G3gJmzz74sULPH36FPv378dXFy7sbBWi0yRSQCZ9fHzcSU4w8YiPS0tbgyIfPHAGRbIm3+Hh4chc+kKhAABORSHsdHz/7w2MI1+SbUNnE9272ryy46dSKVf+WdN1mKbpULIFARoTjOAUziA6qB8CqzbolgVd15GMx5v2fVqeJBL/1LW1NXz7448dX9tO4IsL9gVBwOTkJF48fozVlRXsi9hEs02PNkJQSghBMplETFEcGoJpQoDTTFOt1dxFwccqA9uHaXWKdrIwFECpWHTKj20E27Isu40olmX1pOREAnohGv4egaLk/evc3BweP3qEyakpXLxwoe0moHbhZjDafmPz606m0zg4M4ODMzOwTBOra2sO1z+fx/z8PAghGBkddaU9+9LpUOeVz+chyXIkJR4OPsIbhDjyrhGy+3zqLu3yeSbOCYDACV5kSXKGDlGKSrXqPLOUurzRRDzesmmLwx3bbpqwwXotQtQSeLDCM/s2pdjY2MCV777r+Nr28MeAKIqYmJjA8wcPUK/XW2qMc/BgP0rfDIfANrK6YbhiEDalLg2Qz/RIp1JQZHnb3JZOwddhO5Nbi8Ui+vv720riyLIMwoKvnnHKmxw/ivym15fato379+/j3fw8jp84gRPHj/dM4CEMHSeRmsUqhCAzMIB0JoOjx47B0HUsewdFzs1BkiSMZrPOvJhs1hEdCcFSPo+hwcGWUs4N5wa2eWJ+Isp3zZOLoiC0TeHxH59SR1ExmUxCZ5tny7ZRKpXce8erZclEInJSR5QkCB4Ka9h18YoGn1QPOHRj3TBw8ODBzq9tB/DFBfuAQ4Ww4DQpRgn2/ZnydnPPPBujqarzn6ZBNQz0pdPIjY1B4ZMKvQFFt8E+aa6NzI0ff02xVHJoIW1CkiTYjD7Ri2CftthItaxaePh1Dx89wvzbtzh69ChOnTq14wYZ2K7GExmtNpCev4mS5HIyz547h0q57ExdLBTw+PFjPHr0CMlUytFfHhvDyMhIQ9Y/n88jm822fY6iKIKYJizThBSPh/IwObxVq26zXt5NniiKSKVSqDAVEj6Yra+vr2XWxQ+JZen5QBQgmK/vqvCIomu419lQsii0jT38sSEIAvbt24c716+jsLyM6QMHWr+JZ/Q7tEuKLEPOZFBXVZBSCbphoFKrIdPfj5GhIdce88nVfJhWV2hhp/iEehsAbBvlUqltEQTvGutlP1gztEoi8b9YloXZ2Vmsrqzg4sWL2B/le+4BOk4itQFZUTAxOYmJyUkn618sugml+/fugVKKDBsUOTY2hqGhIfd5si0Ly4WCo2zXBrxJJJNRKYUWG1+DDWjsljJFsFWlAdgwLEFAsVhETVUB1tDe19cXOtsoDHwYKu/zsikNFO3gf+drlRKC5dVVyLEYDnyiZysqvshgX5IkjOZyyLOyUyvwnVnoqO02oMRiSDCqjKrrqFYqoCz7z3VjvcauY4Sco0tHangpRblc7oh3LMsyDCaV1hN+WZc0HkopDNPE0ydPsL6+jq8uXMD09HT359XG8YEOuJWt0OTz0n19SPf14RDjZK6srCDPpvm+ffPGpQTlWFl2bX0dF776qu1TEJikmNsIC+d6w4yzS+HpgbMWAHcGgs1UFGw4a1nTNIeC08GzwysA3OhS3qvg+yy/UQaAldVVJNPpPb7+HkAIQSqVgpJKYblQiBbsE7K1doCObB/nAfelUiiVSo5aiKqiwoQhJElyGwC7otJ5jhc0uI6vfy4bSuBMFTUsy9F7bxOyLLsN8L2wH61sQ5QkUl1V8ejhQ2iahm+/+w6jo6Ndn1cUUNt2n422N2ud+lOyNSjy2PHjjmT08jIKhQLm5+fx0jsocmzMoSSbJnItqKFBEEURAlO34UnKhnkunmugtu1WfHrlV3jNxjRN1Ot1CJLkxjUiS2a2fU280dwvqen7rG19YJRidXkZ0wcPfhIKWzv4IoN9XnKde/wYKgsUmqEhyO8wiKuzrL4gCBgfH8f6xgYq1Sp0w4BdqUBju1SK7rP6ANxG14YMPg2eMFpXVRiGgb4OMvuyLLsPdScDl/xoGbC1yCzVajXcv3cPtVoN3167hmwT/uBOoCvOfhMQBKt3+CFKEsbGxzE2Pg6cO4cyU2IoFAp49OiRe3/X19eRTCbb4mSKguAExp6S9rYKEnvmLEYtAHoTZPDP1Vj/C+AY/r50GhnWG2Oy4VnJZDLy/RdFEaAUFsuyioIQmEVzjbLnWlZXV3H4yJFPohiyh88foigiNzaGD/l8y7VKwTbNESmhYahWKjBME6IkYWJ8HBubm6hVq+hLpVAslRCPxdzgqFeKUTwbyrP4XpvtveZyuQwAHQX7XBO9l/1g3WCjWMSd27chiiJ++vHHjnxlp/AO82o3idSyUh7x82KxGKampjA1NQVq21uDIgsF3LlzB4Dj8z5+/Ahq2xhg0ptRIDC/4u3paHgvS8BwBgGBs9Z6MoCKENhsAjWXiCaUor+vDxRAnam6AQ49NOr94oo8XpUhf8XYSw3llXdKKdY2NnDxypXur63H+KKD/fu3bmFlZQVTTcqMDV3kgtBR9rBWq0HXdQBwJTXr9bpj8E0TEEXouo5qtepQFCLyPaOAYmtIi3sdPlTKZYDSjhRqRCZDaLMdd2S+XocIGjXNUSwWMTs7C5tSXPz6608e6HuVi9o2yhFe0/b2gRD0ZTLoy2Rw5OhRmIaB3377DaVSyeX6i6KIbDbrNmQ142TyTUFoM5Xnmk2ugczkLbsBr9ZUqtWGHoB4KuWqmgiC4EyxZk2KqVQqskydIAhOU6NpQmDPr1c5wWIKRMCWvr5pWdgslXo2IXMPXz5cv/L77yiXyy1pke66oOHqNGGg1NHP51l7LsNZV1VQOJUoUZJQ1zRUymXIigKxRwEqD7x4704YypUKJMaHbhcSUybh1NZuN9QtEyVNguKlfB43b9xAMpXChQsXPmmgD2z5ho7uwA5othNBwODQEAaHhnDi5Eloqoq//uUvgCDgzevXePH8OWKxGLKMaprL5ZrGBTzB0qxJl7MrdNZbFUVYpRUopTB0HVXW/2VTipgsb6PsqDzgpxSJRCKSP5Mlye1nbKDw+PwKwPj67DM3i0XYtv1ZUkO/2GA/mUxCisexXCg0D/b9BqBNo1ytVrd2hoyuAzjZDl3XoRsGRkZG3AZe3TAcbWTLcqQFO+TBu0O/AvjHfpTLZRBRRLpDyS1ZlmGxYKnbYJ+iRVAbYpQL+Txu3ryJRCqF06dPtxwdvyPwnle7AW6U56rLoFkURZTLZRycmcGJEydQLpVcus/9+/cBSpHp70eOlWaHh4cbMixuBobS5lUc6gxbo3Boa51WxCil0A3D0RW3bccZ+BqlvDz+dCrlbggqlQrSqVTkadC2bTuDXTzH5gF/EF9/dXUVoih+lkZ5D7sDSZIwNjaGqqZhZWUlNNjnWX03aAgp8YeBUooKk3Xm9CGetU+lUjBNE4ZlYXBwEMVyGaZtw1RVlCsVxGMxxGOxjiuwboUYrZMP5XIZqQ4DY0IIZFmGbRjQDaNl9b0ZmjVIuscLufdv3rzBgwcPkMtmcez48V2RQuTZ306+s1ZPVNSKcTNYloW6quLy5csua4Fz/RfevwcIwfDQkKsc19/f33A8gdlVq8XGxGL9YqC0q2Dftm3Xr9iUwrRtSHymC9O65713iixDII6UrWGaoLUaEhEqx6IoQmC9K5ZpQvD5K74RABqrxcvLy0ikUpiYmOj4+nYKX2ywDwDj+/bh/cICzp07F1ji9C8U3rUfNQtTqVTczEuSKSNwpFIpFItFqLqOer2OVCqFWq2GuqoChKCuaVBV1eH4x+NtDb1wm0Sdk255vuVSCelUqqtGMVXToBsG2s/h+BAhMPTzK9++fYv79+9jLJfD+a++gqZpvefMR4BXC7nt40d4pjoZlubF+vo6NF3HGBt6kunvR6a/H0ePHt1SYigU8P79e8zNzUGSZcdAZ7PI5XJO8yvLQljMQAZBZ1kQiXgGnrRBV2gwxoDbgBv3qOzwzaz3LguCgHQq5cgPUkepxzXgTSBJEnTDcAa1eDeJ7JytAKO8sLCAwaGhSGPh9/DPAVEUIcsyBoaGsLCwgJlDh5pOD/Ui6rrmG1m+WfDLy2b6+lCuVKCpKkzLQjqVgs5ss2VZqNXrqKuqO2iunWSSKw9KCIQI51wulZDpYp6JzKSpjS6D/ciJFO/rKMWjx4/xam4Ohw4dwpEjR6Dp+u5MzN6pPjCGbj+XS26Ojo6CCELDoMh6rYYC4/q/ePkST9mgyDGm6T86OurIZzIaZbMkEmdHKF7Bhzb8imXbzlrQdYenTykIm0Hh9Sv+z5MkCclk0h3sWKtWkYxQOZYkCRZ7fr39BW4SyTtMC05M8+HDBxw+evSzGqbF8UUH+6dOncL1v/0Nr+bmcPzEiW2v6zSwoizQ4E196XR622aCG2pzYwPFctkNZJRYDKlk0hkcZBiurrisKK6kYLPjbnvwIyyGcqXSEa+SQ2IlK4tlRzuVw4qaYfAuysdPnmDu5UscPHgQ586dczmeuxLss01WJyXn7tqSo6FQKECRZQx6BqdxeJUYKHX0lwuMk3n37l0AwMDAAIaGh5Hp73cG/IRsQHlWv6HBKMJasm0bmq47xph9v0QQ3Im53lKvd2KuF4IgIJVOo1atwrJtVGu1lgE/7ynwD3ahjDLkN8qbpRIWFhbw//2//q9dec728HmCP2Pnzp/Hs7t3kV9a2ta87adVAlvJgVb+xrJtVMpl106m+/q28Zb5pHbTslAqFpHp74eiKM5wOUVxZlFYlptMisViiLdIJjUkj/g5o7XNKpZKmOmiiVWWZYD1k3WTfW7Xtlqmidu3b+Pj0hLOnj2LQ4cPo84HX+5Cf85O9YG56LJvZInJvQap4ySSSXdQJLVtrK6uIs+U4969ewciCBgaGsLg4CD6+/uRSqUgB9xjattb1WLvcSKct2lZ7oaXi0qIgoAYi6e8g1LD1qEkSUglkw5V1LZRZQ3wzXw9nw4cNDDMZL4F2LIbi4uLKJZK+P7771te027giw32uVTfocOH8WJuDgdnZhqCk9BHiD0MzZYdD/S51nGYIU339aFYKsEwDFSqVac5VxAgyzJkWXa7ww3DgK7rMHQdsiy7wY97rpxWEWAMCBwj0ayjvFgsdi3z5JXg7Er7NgIIIbBNE3fu3MHi4iJOnzmDI4cPN5TfdgWfIAPTTWY/n887o8xbOCxCCAYHBzE4OIjjJ044SgzMQC8uLEB99QqSKCLLsjPZbBYxVt42DMMNyMNKrX5Nccu2obEGKcBxbl5jHHQ3m90HgRAkUynUazWYHg5/WMDPDXbQZ3qrNfz9Tx4/RqqvD5cuXQo9hz3888GtGI+PY3l4GI8eP8bY2Ng2exD0PLcKnm1PoM919sMCjb5MBrVaDbVaDTE20EeUJMRiMcRiMRiG4SaTVF2HqmlQFAWJRKJhA99sejohpOlMFE1Voes6Ml0kkURRhEgIKCFdSXBG2ZgAjt2o1+u4fv06SqUSrly54m7W/IMaPyW6ofFEQdT7EwTLNLGyvIzjx4+3Po4gYDSbxWg2izNnzqBWq7l0n7dv3kBnQ9TGxscxlsthNJt1n0edVVUEQQhvNPfR4Uw2JMtg1B+bOhN7Y2xWCwe/9la+tYEqyhK66XQ6dBMmehvZPaCUuj6Sx6KmbePJkyeYmprC/v37m57HbuGLDPYB5yabpokzZ8/izx8+4Pnz5zh37pz799AvnpcwQz63Vq9vBfotJniKjHZQKpVQLJWcB8fzeq7xarFucU3T3LKmKIpONUCSXC51M4RlRnQ2Ia7bpiNFlp1JpIaBRIe8xqgGR9M0/DY7i83NTVy+fNnRBfZ9xm7TeD43qPU6NjY3cejQobbfG4vFMLV/P6b274emqljK57G2tob19XXcvn0bADA4NISxXA79/f1bvSkh94GvLZMF+dwYU9uGKElI+IyxH7xBsBkE4gy0q7GAv1arIRVmmNnvgta8aRiAJ9BfXl1FPp/H9z/++FmWWvewe/A+D1999RV++etf8e7dO1f6Nyir76JF8Fyt1SIF+gAQUxTEYjEnu18qIcHodxxuMokF/QarIOs8mcSqdi157k0GN5YrFVB0psTjhSzLsFgSaaf19suVCv7x97/Dsiz88MMPGPBWQLlt2AXbTj1Z57betxMn48Pq2hpMy2o5jT0IyWTSHRRZrVSwVChgY30dK8vLmH/7FgJxBkVms1mkMxnE43GkmvUEeoL8uqo6PQAsyJdlGUlFCUxE8vsaJZnmp4rW63WkQhrQ+SYq0K8wmXW+cZl/+xbVahX/n//yX5oefzfxxQf7sqLg2LFjePbsGQ4fOuRMkW0GzikP+AI5zxhwHuQowUBfXx8qlYqrmBA0eZEPEUokElA1zc2CGqYJkdEcYooS6gAI8ek5e1Dh8mhdcCsBVnJlgVWnEpxRMgyVSgW//fYbNE3D999/H8qZ3s0MTLs0nqhGuZtrckeZd2CUvRAlCQMDA+jv78e58+eh1uvuQK+5V6+cNcWGfvGsv7/sapomVDaWnGf4RVFEPJmMVBVqJSfHQQhBIpl0OM6UQq3XA5VBhCafx2lhfPjW48ePMTA4iMNtDo/Zwx8fXBXKtm0MDg9jcnIST1m2jvuCZms4LNioq6qbQEq1CPQ5+jIZaJqGYrkMJRYLlCmUZBl9TFyhXq9D0zSHNqrrjtpVLIaYooQGmc2upVwugwCt/WkLyKwfrBsJzijV0NXVVVyfnYUSi+H7779H0idWsZuZfVeNZydEH9BdZr+QzyMRjyPd7aZOUTAyNITR0VF8deHC1qDIfB5PnzyBDUfJMJfLYWx8HKMjIw3xFdffd8Uc2MZZURTEFKWpTKcbkEcUkuATd7kalqZpwZr4vGLs+7VNHXU5wnradNPEs+fPcWB6GrnPeGbLFx3sA86NP3LkCN68eoWnz57h0qVLrTvYA4yyxRo3ALj8+yiQZRnJZBKVahWVSgXDTRr+BEKQZIE91xvnWctarQaFcf4V1mzS6pwBxyhToCPZzYZzEwSIoug+yB2p8rQwTmtra7h+4wZiioIff/op+Jx3Mbve8UCtLqg5UdH2KPMQcKNpsWaqeCKBA9PTODA9jVqlgpXVVaxvbGBtdRULCwsAnInVo6OjGBoeRiIed5trbdt2qAWK4lS0WtwHflfboWoJhDhcy2oVRjPDjO3VAtMz6EWWJHz48AEbGxv44fvvu2sY3MMfFqIowrZtWJTi1MmT+Pc//xmvXr/GsaNHIwWd/qZzwzCgqSoAh/8cVVs8mUi4jY+1Wg1DAX067jkLAlKpFOLxuJNM0jSYhoGKaaJWq0FWFMRYNcBv28J6Z8qlEpKpVNda6PyYpmXBsqwdqaa9f/8ed+/exfDwMC5dvhzou3e1YtwhjacbymfEA2Apn0cugKrWLvgUXX6t3kGRxc1NrK6uYmNjA/lCAW/fvnUHRY6MjmJoaAiKLLtNt8BWdWvbHJgAEDSvUgVBFEXEEwnU63WomgZRFLdT4Lb+p+G9XJ1RFEWIoojnz57BNAycPHnysxuk5cUXH+xblCIuijhx6hTu3r2Lw0eOYGBgoOX7GwZWUUfzGHAygO3Kc/Wl01hdXXUpQAjaKNCtISaCICCRSCAej7tBv2Wa0AwDmmFAIGSbgSYh2ctyuew4hh4MXFFYlkg3jI6CymaLcvHDB9y+fRtDg4O4cuVKaB/Ejk2wjQB+7HYzMJQP12mFDq/JMk0U8nkcPXaso/c3nIIgOLQxy3KHUAFbmZX+gQHs27cPkiShUi5jaWkJhZUVvHz1CuaLF4gpiiPDls1i38TEFq+ff28tjG4nfQuc8lZnVDivYebqIkHgPQQycyRPnjxBLpvFyOio26Owhz14ITEFGUqduSWHDh7E8+fPMT093ZoaQwgED5XHsm3UajUAQCweb1tuMJVMYpMNb2w64Iv5FVEUkUomkWBBv65psCzLyfhrGkRBaPArzVCuVFrOGYgK3g+m63pg5bsVwqwFpdRRiHnyBAcOHMBXX30VKdH3qdGRT2vHRnbYoFssFlGtVHD2zJm23+sH9yM2m2nCr5WLIwyNjOAgo8MVi0V8XFrC8uqqk/WnFIlkEiPDwxgbG0POw/UHolVjOun1U1hfpWEYqNXrDVLPxEOt9vorru0POMIQdVXFy7k5HD5yBIlEArHdkAyPiC822OfGStd1pOJxHNi/H3MvX+Lxo0e49u23rfmKgKs1XKvV3AxgqgOtet6IKOg6KtVqoEELmnzL5Qjj8bgT7DPepddAC4RslbLYVDcvyuVy17xKDkVRUGeNWTSR6ElDEaUUL+fm8OTxY+zfvx9fXbjgDOFgXLyg1wPYFW6l3SG3cqfP9ePSEkzLajpPoh1wCpxl2+B5Ni6LBjjqB2q9DtO2McoarWzbRrlSwfraGpZXVvDxwwfcv38fIyMj7kCvvr4+x+gKQuAwGM557gSKosC0rC3DzPn7Xoqb57Nt23YdjSLLeDc/j0qlgsvffANK6WedgdnD7sFtKDRNKKKIY8eOYX5+Hs+fP8eZKEGRJ/CqVauOcogkddQH5VJJTRPVWm07VZNvLAKy9clEwlH1YdUwLt1pqSpUVXUa6BUFSiwGIWDYZKlYxHiPtMJjiuKIVBhGR8F+EGzbxr179/Du3TucPHkSx44dA5/iGmRhdtWvdJJE6lJhJwoWFxchyzKy2WzXn8WTSHyeiuhpzAUAiRCn2VbXQQQB+yYmML5vH2zbdjL/a2tYXl7G+3fvIEoSsqOjTuCfy209MyHiKm7Cp4P7lYjHYVuWszFn/H2eWHWl2j2v50O2CCEQJQmPHj+GKAg4cuQIQOlnXTH+YoN9hXERTT6hTxRx+vRpXL9+HcuFQmtuM8vCqKzBCUDHWvWWZbl8/GqthhFPYB91Vy9KEpJMD9ZroG3Lgsqy/wJxBpUoiuI6pWKphFwPFiuwVZaiQE+m6VJKcf/+fbx9+xbHjx/HiRMnGpppghanW27t6sidwf2udkGerRkWFhYwNDi4jYfaKfzjzW3LQqVSgc64vrwpilIKRVGgyDIkxvXnG45qrYZ8Po/lQgFPnz7F40ePkEgmXf3lkdFR97M4oihLNUMiHofFKhJ1NhyFsKwmQWMGhmf1JUbLePr0Kfbv34/+gQEQSvcy+3sIRCwWQ7lchqbrSCcSiMXjOHr0KJ49f45DMzMt1yCvXNXYNGjCaGidgAKIMxnOYqnUEOxHrY5JkuTojDN6JpcwNFngX1dVVyElFou5iYBqrdazzL5L5elU2jmARvH7779jdXUVX3/9dYP6SVjlcLc4+5Q1mQI7q8bTNijFwsIC9k1M9Oy8BEFwkqgsiWSaJqqVijtUzeT3gsUxMns2BwcG3Cb4zWLRkYxeXsa9e/cAAJlMxk0oDQ0PB6sWdqh0R5gQRKVadYVU+ObC9Smez3Wz+rKMarWKd+/e4dSpU4jHYk4S6TP2K19ssC8wiUudNQoqsozx8XEMDg/j7r17+Pnnn1vScUw2OQ4AEolEW4OvvLBtu4HnXyqV0N/fH53e4YPXQDcE/raNOs/MiCJERrU43IFCSxhiigKrXoem620H+w07YNPE77//jpWVFVy4eBHTEaVBv7gMTBvgxqOdDaWuaSgUCjh9+nTPzoMrRqmscZA/UwCgsAxNnG0ow841lUzi0MwMDs3MwLIsrDCVm2XGySSMk8nLskm2ke6mjM4Dp0ql4mgv67ozTZT93SvBxjfwsqLg3r17MAzD2Wyy13zORnkPuweZDfyxbRuWZUGQJBw+cgRzr17h1u3b+O6771ryznUmtQygpZZ3M9iWhVQq5SheseGNiXg8sErcCoQQpyeM6ZLz6e+c6mOaJlRVhSRJUOt1UNvuWcXYnaar69A1DVKbmx9vH0S1VsP12VmoqorvvvsOIyMj244VmETaJb/iPW4739lO8/XX1tZQrdVwoUfVYsCh8lDA4cHrOuq1GnRNc7P+kiS5iaMwDPT3Y6C/H8eOHYNuGFheXkYhn8f7d+8w9/IlJFaJ4OIRcdZD1k2TsiAISMTjqNXr0A0DkiQ5G1S2efHS8txp7IKA2Vu3EE8kMDMz48rj9oJOvVP4fM8sAuLxuGO0LMvlQ35z+TL+8pe/4Pr16/jhhx/CDTPLvlA4Zf5uyvo2C+r70mnU6/UtGc4ud8zcSPLBEdw4a8xAbxaLsJhyTrVWgyzLkESxq+PKiuIOQrFtu73PYgaqXq9jdnYWtVoN165d66hM+Km5ld4d/E4a5Xav6uPSEqhtY7LLkjqltMGpc+mxZDLpTCyGMyW6L51u+96Louhk9HM5AI7iUj6fR75QwKNHj/DQtpFMJpEbG0NubAxDg4MdP6OCILiNVbqmNeots+/CME1H5pAQvJ6bw8LCAi5dvuxUAuCoAbXbl7OHfw4QQhCLxZz5KKaJOOsPuXLlCv7+n/+J+/fu4cLFi9vXCMtY8qoTpbTrXirbtt2ZE6qmYXNzE/EeNFPya4zFYrCTSehMwcdgqjmr6+ugjL5Qq9fdDGw3x40piqtA1zbYvd3Y2MD169chiCJ+/PHHwM1IqD3epcz+jg/UAjrawCwsLiIej2PYt1lqF5QFwFwus1atAoKAeCwGTdchCAL6+vqQTCTafn4UWcbkxITr+zY3Nx2/ks/j7p07AIBMf78zJT6XQ6a/v+P7LMsyYow+XVfVxsQv9ytsAy9KEu7evYtysehIODNf9rlTQ7/oYJ/fXJ0bEObEr127hl9//RV3797F119/HapPz4PZTnj6XnA92HRfH3Rdh2oYKJZKGIzQKBwVhBCnQ51NU9R0HZubmwCcB1VjzYsETubWWyZrZ5GJggBJFJ2Jd22OOadwuJ6zs7MggoAff/yx7VLwrpZbAScD08EGJzLYoI6oWFxYwMjISNuZaG9wz//l99Zi1DeuExyPxdzNai82Wel0GocPH8bhw4dhmiZWVlextLSEpaUlvHr1CoQQjI6OuqXZIDnNZlBkGZZpQjeMQHUebpTX1tbw9NkzHD9xAhPMYVBKoewF+ntoAjfYtyzECQEsCyPDw7j49de4desW+vr6tjfLs3XDlXdkWe66esRpdplMBvrKCmqq6k6U7hUEJv0cj8ddmo+h6xBEEQRO9U+FY49FSYLMsp7tbmL4cD1ui6K+n1dCl5aWcPPWLfRnMrh69WpoYBVmvXZLjacTjX0+ZDNqEN9uxZjaNj4sLmJicrJ97X/GNuDfo8kkKCm2+OwiAEGSkEokILCm8V5gYGAAAwMDOH78uDMocnkZS0tLePv2LZ49fw5ZkpDNZl2/0i4zIRaLwfZIgPKNA2WUVr5RffvmDT58+IDL33yD/v5+t1/gc68Wf9HBPi+5UvbQiZIEAmBocBCXvv4aN2/dQjqdxokTJxrfyLj6AFwaQDdFM2pZoHAMZ6a/H+b6OjY3N5FJpzumBjWDwJqruEEeGhpyGxItthAty2ow0rw01WzYEQfvUuc0iago5PO4efMm+vr6cPXq1ZbZ08D7vktqPJ1mYLgSRlS086yp9ToKy8v46quvIp0HfwZMNuLbW63gA31ESUKMbTjca2bZy52455IkYXx8HONjY85msFTC4ocPyOfzeHD/Pu4DyPT1ubr+wyMjLb8Dzo3kmUJv4GAYBizbRrlUwr0HDzAxMYFjLDAT2HV/7hmYPewuvEkkN+iiFPunplAul/Ho0SOk+/qwb9++hvfZtg2NbTR70YhqM71xRZbdae0bGxtIxONdV42DIIkiBGazU/E4UskkDNOEyRJjBrMtdVV1NMZZ8C9FpC8osgyVUYja2Sy8ev0ajx4+xPi+fbj09dfNaVStGjV3icbTzvfFq4/toB3bvbyyAlXTMDU11fK13qQRD/J5YzjXt5c8FB2RSXCCUhBBaFuBKircQZFTU7ApxfraGj58/Ih8oYAFNihyaHDQbfIdGBhoLdrCmBQGi30kdu4UcBW6CsvLePniBU6eOuWu/y+FGvpFB/sAy8LwAVVscA4BMDk5iXK5jKdPnqCvrw+THm4aVyYghLgqCd1w5HgHukCcqbvlchmWbWNtYwPZ0dEur3A7OPdZU1VnkJfnIXONMrsntmehqtxIiyIkT+bfD0VRUFNVV6c8iqF6++YN7ty9i7GxMVy6dCmSMQ9qqtltbuXnpMTz4cMHCIRgwhdUcFiW5TTase+XepQoKOA6ZP6fd7qzyrS4NVV1jHKXzdjNwDmVBE6W8mgyiaNHjsDgnMxCAQuLi5h79QqSJCGXzbql2aCgiauHyLLsqHx4lIQ4JeHBw4fI9PXhYkBlT9kL9vfQBCKrjPJ15bVlJ0+eRLlcxs2bN/HTTz81yDxrquoEPyyxwjOCnYJX4ARRRH9/P2q1GjRdR6lcxkB/fzeX2BSapiEWj7tUH8CxNV6/wiu/vDcmSvCvMGqHbhhIRMhEU0rx8OFDvHz5EocPH8aZM2ci2edtCRWfSMCnREdT2TtQlmknibS4sIBUMhkoUU4phWXb7rPPh2x6/y4IQsP3zCvhXExEZ/QdADvqV/g9EgjB8PAw+gcGcPLkSaiqujUocm4OT589QzwWcxNKo9ls8CaEBfsiG+zlDo2EEzMWSyVnyN7+/Y76jg+fexLpiw/24/E46tUqDMNAPJFoWMzHT5xAuVLB7Vu3kEomMTg01JjVj8e3grUOjTIvXwFbjY9Dg4NYXl5GpVJBpq9vR/jBRBCgqeq2zDvP+sfYIuO7coPpyVLbhs5KUnXADf5FUXQyvOxn2aON3Oz8KaV48uQJXrx4gYMzMzh39mxkwxbUTLXDY0RCwQ3aTmTMvGjHKC8sLCCby0Fi8w+4RBg3xvyc+TASLgcmSZLzPTbZcAmEwDQMR7OeUbd2Av7vmHh+L8syJiYmMDExAUopisWi0+TLlBgonIYtbqQHh4Ya1nc8FoNhGO6mlBKCuqbh4cOHIACuXrkS+H1+7kZ5D7uPWCyGWr0OwzDc4VaA8/xe+vpr/Pqf/4nrs7P46eefkUgkYFuWm9Xn9rKbijFf4zyxQwhBJpPBxvo6isUi+lKpnleN+XFUTUPct8nmSm1ga8e0LJhs7TUL/vn7OD2UEOImoJpp/VuWhdu3b2NxcRHnzp/HoZmZtq7Dr43u/dunxCebGxNxg2CZJj5++IAZJuphcr/CVM4sRsUBADCbKnC/wirAQoiv4NeoGwbiTNb1U91v9ziMyn3gwAEcOHAANqVYW111g/9379+DwBkUyf1KJpNp8Cvetc9pS9VaDQ8fPkQmk8FXX33lHk9ga+ZzV+IB/gDBvjfzQFm23sv7vnjhAv6zWsXs7Cz+9Kc/QRBFN6vvDZQ7lQS0TROUB/vsAYjF40gkErBqNaxvbGDfDoxQJnCys60CF25sY82MNKUghuFufAh7ncr5m2y6Lpds5LAsC3du38bihw84c+YMZmZmul7cLTn7LTL/Ub5BrywqrwTZrY77icCNbqVcxvrGBk6fOoVSqbSlqc3A6UOSKEKRJNcYt1Np0A0DsR1uVg3KbHK1E28wRAhp4GTquu4a6Pn5ebx4+RKKLCPLGoFzuRxisZib3TcMAxAEvHn1CtVKBT/88EOD8eWycBTYa87dQ0vEYjFUBMGd1eD1K6Io4urVq/jrX/+K69ev48cff4SmaQ1ZffambZKwUWEahtN/5dms9qXTqFQqUDUNG5ub25RoegGBENTr9ZafLbHEkHu+LBNseKqMumE4foWBEEdr3TQM2JS6NFf/hlzTNMzOzqJcLuPq1avIscb/qPAnGBruf5h95HTMNmmZ7vHQyJu3GYWykyRSRxKSCPd9nOJpWRaWPn6EbpoYGBpCqVRy/J/Ht/BrkCQJUizWNLjfdg5cxco0Ycmym3D8VHBjOM/3L7D+sNHRUZw+fRq1et2R9iwU8OLFCzx5+hSJeNzl+WdHR93svkGpcy22jVdzcxAEAVevXm38Lj3PyuessQ/8AYJ9QRAgx2Iub1+W5QapLlEUcfXKFfztl18wOzvr8J95gONd1IQ0PPRRYLGx6gDL6ns+b3BwEPV6HZqmoVKpIO0fiNID6Lq+LQPTCkFGmnP83dIVGzDGuWuEONMZCSEQWeBvWhbu3rmDUqmEK1euYHx8PHDselNwTnmAcW3YNPgWsPu7DtGQ6fH9jvg2NN5j+4/YUYmefZbNSvRWSFZlnmUgBlg/BiEEgidLxqswndKIdMMAYYo1n1oujAiCs9aYYwm6j4qiYGpqyuVkciWGQj6PO4uLAJyGrRwb5mVZFgpLS1hbW8NXFy40NoZ7jgU4o9z3sIdm4HNcLC7ByZoQ+WpLxOP49to1/PLrr7h965ZT1g/YOLv2JeJxKba4+rwPbOvDnA3x6soKSmyYYs+rVIRAD6gYtwKndMThEwfw2DjXr7ABW26Vj/kUSRRRq9Vw+/Zt2JaFH374AZlMpm076391aBKP9zOBfU/8de0eL2BjQQBHnYl/j2zjF2avuY3vFPwMXD9iWc4MIvYz59i/X1xEKpl0BnmyCercrwjMt3RTMTJ0HQSAErCJ22kQQQCx7aZSnMlEAgcPHsTBgwdh2zZW19Zcv/Jufh6EEIyMjGB0dBSJVAq6ruP94iLq9Tq+/fbbBlqS67uII+qR6NEcnJ3CFx/sA56yCwv2/UsmHo/j6tWr+PXXX/Hg4UOcPXs20JgRtjijLDmLBbacJ+1/rEVJQl8mg2KxiPWNDSSTyZ4//JqqOtSkLhDEr7QZVQQA6ixjReA0Ihu2jVK5jAcPHsCyLJw/fx7JZBKlUsktAwuejQERhIZSl9egUUIagvhtHNceBfdRYHsyMNucS0BfgeC9HrbgeTMfrxhQFtDbLMNjMyfIm0gbPtM5Cef+CQIK+TxGs1lk+vogMIPcs2tl1R0QsnOcyghlZW/ptdlrBUIwNDiI4eFhnDxxApqqorC8jHyhgDdv3jh0JNavc3BmZptMKeeUUjjSsn09Gha0hz8uCCGIJRIOR52rkvme0YGBAVy6dAk3btwAEQQcP3ZsOzWljew+hbM2/ZlJLxKJBOKJBKxqFRsbGxhrNTyyTXBufjeUBG+vkP+zLRaMGboOm/G/eeJjZXkZjx4/RjwWw1cXLgCEoFwuuwkYkf0r+PyKF9zu+ivE3GYH2ZmdrObyCiZhGvRhds69DpYAc8+Jbk1J5lPnqc+nuH6F3VP434uta1xdXsbhI0eQSqVc/9wrmIwmDOwgV7+Jr/BSppolkjgEQUB2dBS5bBb0zBlUq1UUCgXk83m8ePHC7ZehAM6cPbutx8E9DoC+TOaz1tgH/kDBfpVlDMD0XP1B+0B/P86cOYN79+/j3r17+Pbbb7eX84kzVbeVWQ7MYAfsygf6+1GrVh0pzmIRg4ODbV9bM6iatiOUBIENwehLpx1nRQj6MxnHIK+s4O7du1AUBRcvXoSiKC6PHEBjpp7veil1DTYRhG1GmwBu8MzxuarxcANrssyJm6X3GWG+43cVcTwKOBZTyvFm6d2fBQHlUgmVSgWnT51yFQF6CU3THA4ty6jtCJoYWRKwmYoyAdFm9LtYPI79+/dj//79sG0bt2/fRn5pCUSWcWBqatuz4zXKmR7K4e7hj41YLAadU3lYcsib3QeA8fFxHD1yBC9evoRlWbh06dL2NRWRT83ntQAeimGAPRocGIBar++IFKeu66CU9kRNyA9OKc2k066WeTqZhGXbeP/uHR48eICh4WGcPn0aArY2BwC23z+PXxGYX+FJJk7ZI4xv3or6uZNo16/YjDri/r9tOz8DW74E26sV3qqwwPojeJKI90osLi7CtG0cOHBgRwJTVdMAQXBm9ewUmvkVNNJC/b8LfI/H76RSKczMzGBmZgaapuHvf/87arUa4vG4O0Nm6zQaE5MDPY7tdgJ/iGBfURQQUQRlY8AlJknphWXbGBwcxNcXL+LRw4f45W9/w9Vr1xydVA9aBR28LBcJhGxJcRaLSKfTTZuS2oFt29A0bUeMMoeiKBDY2HfTNLG0tIS7d+9iaGgIV65cca6FOt37umG4DaQ2Mzy8s98dGU4IiGnC9Bk+22PEqtUqeNMwz4p5ewkIqwaQgL+BEJiiDSpuLXKL/QsCUNMENK2Bn8izLfV63VFUEgTojGfqXdDerAqBU5Xw/s1rVHhWQQBcgysAIJ4GNUGSQh3A4uKio0rTJlc1CixGzaJw1DHapl5FQYvgxi8rFyXQ56/zwjRN3Lp1C0tLS8iNj6Ovv3/b5si/iez1hnsPf1zEYjEUBcHJWHqreB6YponJqSnE4nE8efIE//nrr7h67dq2JEyrnjDL9zf/psILiUlxlkolrK+v91SKU9M0gJAdbWJXFAV1NhXYTiTw8uVLPH/2DNPT0zjPmx+p0xhpeGmOfD4ID4IpBSwLFtBIkaF0yz6z5IqqaU4AzP2H5/VeXxLkVwghMCQANu/vAmzC7L1EAbZB8vsValmOGAilrt/n/ibUr2CrHyuMTy8Q4vbQCYQ4foVXBJiPCcLCwgKGBweR3AG6iaHrTkM5HEn0TvofuwUNWJ+EkLYpUvV6HdevX0e1WsX4vn1IZzLb3u9fb0PDw52f+CfCHyLYJ4RAicdh6LqjnsAyK16DyRutBgcH8fOf/oTrs7P49ZdfcPmbbxpLoSScu+8uRO/vWjzU6XQa1UoFlqpiY3OzZ1KcvCEsFou5pdBegxBnxHrdtvHs+XO8evkSU/v348KFCw2BqsD0dO2QbIGb9WYG2vIYbNu2QZnEFVcFAHH6BdpqlmIL3ZAs0AQAsM8HdaNwqV4DiW9tLLzGQWNG2WDKN9vgy7TxxS6wTBJvXublZu44gj7H5IaCHb9Bq59SLCwsYGLfPpAdyLrzwWuyoriOptfgm58wBP2NO3ibBkvy+Slg3CCXy2WcPnMGJtuobXtefA5gsAOjPDk5iX/7t3/Df/2v/9X93ezsLP71X/8Vz549w4EDB9r+zD18/pAkCZIsg+o6DNOEwiii3hXD/cq+ffswMjKC2d9+C04kNfEr3mTHNoTYvwYpzlIpUEaxE/DgNBGPR96Etwuu0sOrch8WF3Hy1CkcO3q04XpFSQKYhnsQbK8PodThpnsqrRbzK5Qlq0Bpx35Fj1OAOt++ZdqgAhgvEJBYgsrvVyzLgsE2T155YBf89dhKYgmeSjfx+BXBU8EIvRfMd7rPKFPTAeAKHpw5fTradbcDSp2sPhxxEje510tEqI4FZfEp4D5r2z9y+/PNpzQDwOkzZ6DpOhRFaRpfyYqCVAc9mZ/ar/whgn3AycJoxJETBDNU3oeDG2VRFJFMJvHjTz/h5s2bmP3tN5w9fx6HmRQVEJ5pdPmUAWi2cxwYGIDeYynObRmYiKXidiFJEl48eIAPHz/ixPHj7oAyP/8waFfNIRACcOk2P5hxBpzvyIazaNOpVGNmHZ6NFfu993f8fCxKQG3qZPJt3njl/CuKopP5ABqyOlyzHQCSyeRWCdCb+WH/eRWJOtlgNdwhz/3im6fV9XVUKpVIg7TahcnlV1mZvlav996Zs6CmGUL/yrJW/nPyr62NjQ1cv3EDhFJcvXYNtmWhWC5DkqSGjZp/HSdTqY64pN988w1u3bq1df6U4r/9t/+G//7f//teoP8HRywed6bpGoajze2hhAFwnzdJkpBKpZomkoLopUEJJOcPzdeQIAiuFOdmsYi+Hg1wbJCl3kEQQnD/3j1sFov4+tIlTE1NNdBUOJrdBYE4/WEI8yvs81RNAxidhVOeXP/BXst/hxC/Ylrs/wiTOrbZ/9qOApP7nXoqzybbZIii6MzC8fkT78/cr3SatNvG8cdWspMQgg8fPsC2bUx45g31CrquO7ERgLiioK5pvU8+RvBTYa8Iath1nzWPb/n48aM7Ifv8+fOo1evunA2vX+HN+hz9HW60P7Vf+cME+/F4HCVRhKlpLpUH2HrgebDPswSSJOHKlSt4/PgxHty7h0q57GjE86wsGo2wl0/pRZRQySvFubaxgYkeSHHyDIyr6dxBuaoVdF3H7zdvYnllBcePH8ehw4fDX9xp0EiIy2cnHi3mTrnqsiaCVp2fbYsZZv63RBIkvb2EabEgmJDoMpQdG+WA78cblM7PzyOZTGIkm4UAbEmJ9QAac+SKZ9x9L4P9yHSc1h+09Tz5PtNrkK988w10w0DNMJwgnr2Wq0z4z6e/QwrPlStX8L/+1/9y//9//+//jYWFBfyP//E/Ovq8PXw5iMfjqLHMbCKR2FJVAaMJcr/iSRaEJpLI9p6wpnakxVriUpxWD6U4NU1zJ9NvnUbvbASlFNVaDddnZ1Gr13Hu3DmM79sXfoxuj80SCFwjvlM+uVSD6+wb/IpCoIRkdXVdh82CxUgNz7RRNaxbeCVB5+fnMTY2hkQ83kAV6hqUOolHOHEOT1r1smLcDs0zNOD3v5bFHIBzL+bm5vD48WPs27cP586fh6qqsG0bSjwOURBcNkLQd9MpX/9T+5VPq420gxBFEYl0GpQQNzvB+Xe83AegoSQoCALOnj2Lry5cwOvXrzF7/ToMVm5ryL6ElF+9aLVABwcHIRICnUlxdgt/Bsbls3cJCud+VSoV/PLrr9jY2MDlS5ewb98+d1H3Gq7zZIuvd9uVaHA19j+xVJgfumFgYWHBmVeArfKuG2B0kS3hOth8+AcBOtYAD0PPPotuV5GglOLly5e4ceMGcrkcvv/hh63MHCGQJQky2+DzBmj/+XRjlJ89e4ZKpYJqtYp/+7d/w//8n/9zR+R09/B5IRaLQWRKPNz+8aCCT9h0qXsMPJF06PBhPLh3D/fv33dVSrw2ullA5FUWCQVxpDglQUCpXO6JfdZ8s1t64lPYerYpxdr6Ov7217+CUopvrlzB4OBg8/Pu9PhBNMoeJsKiIOg7bwYSdM5R0eR96xsb2NjYwMzMTEMDq+tXurDbGsviE0IQk2U32N8Vv9LkdTwW9LIDAOeZvHfvHh4/foyjR4/i0qVL7mA4gYlYCKLo0sP8GwpCSMd8/U/tV/4wmX3A6aZWNzZcaUNugPmXx5ta/Dh48CCSySRu3LiBX379Fd9++60jlQmncarpLvX/Ze/PYuRI1+xA8Ni++Bb7xojgviSZZCaZGzNv5t2kqpqeKelF05gXQRgBkoABJKAwEKZfpoVpYJ6qqqVp1FsX1A/daECQpiSoegTNlOrWvZU3K/ckM0kmk1tyT8Ye4avtZv88/EuYe5hvEZHMJGkHIEhGuJubmbt///ef73znGzBB3W8rziAIdjAwu2X3eamSX2e1WsWHH34IWZbxs5/9DMViEdVqVfgmKxnnvZev9g6t3VMOysJ28ym9Lq82deLhgwcgzC2h7fGpzQh/3rCMP98cGrq+/f6l5Eh7bvAbQkbWL3hLqUWI9xV8efky7t+/jxMnTuD06dOI4lg0UquKAj9JBGsXRxFMw2h7HVVVd11ufe211yDLMi5duoS//Mu/xOTkJP7hP/yHuzpWjmcPxXIZdceB7/sw2VTQrGpxGpxIKpVKuHz5MlqtFt58801qDU0I4ozN6G6QtuLc3NrC7B6tOP0Mh7fdaPfF45l0CYTgyZMn+Pyzz1AZGcHFixchSxIarZaommRGs324R53EwdOCmMEzYGzd05X2uE/37t2DbVk7DB/SG0rRHDzMSyaJmBpt8O8Ftzn+HiTFe0aqJyJhpiIff/wxNjc28NqFC1g4eBCB74u5GnwAq86qdlEc0zlOqWsrFou7ViE87XXluWH2AdoFrloWbahJsTDpoNyNzZyensYvfvELRFGEX/3VX2FldRUAhBatG4b5UI9UKtBUFXGSYHNra+DnZcHzvB2OCekvWz9wtoU7HPBEf3l5Ge//9V/Dsiz84uc/R7lcpoPLdB0S8L2x+z8kBmLR0o/f4+t1a0C9e/cuZufmepZ8eUCWGTMzCKIwpM1qhLR9Zrgzxb6UXIc4xsCbUUmC47r44Le/xcOHD/HahQs4feYMgPbNCwfvu+Al1zT453g3sG0bZ8+exZ/92Z/hj//4j/Gv/tW/euoDY3L8cLAsC5KmiamwHCFbV7grWRYOHz6Mn/zkJ1hbW8NvfvMb1Gq17jr9DAzyTRkdGYEiy/A8D41GY6DjdoPbZV0ZGCkWP11Rv3PnDq3Kzczg3XffhWEYUDWNEg+EZDewYu+x9ocEecokUhZ4tfjw4cM938f0hkgGBornfhCAJAlkSRIJ8fdRMR4Yg9xn9pmsVqv4za9/jVq1ip+8+y4WDh4ESZLtRmPDEJV0vpnnFeM0KnuYc/S015XnbsWy2cAcz/dFEsObK0SDaJcPRblcxi9+8QuUSyV88Nvf4tNPPxVVgX4YKCBKEkZHR6HJMur1OhzHGejYWchiYAY5D54spgMxx927d/HRRx9hanoa7733XlvSaTJNNLdt3Hng/UsYn7rHPg/Kg7rf7PVaM56/vr6ORrOJI0eODHYIbDceyeiRFBCyLflizk0c+1HGBYZ/vwZ5tYQQ3Ll9G//lL/4CjWYT7/zkJ1hgFY8gCBBzz33DoMk9sO2WwjawaYzscfjcxYsX8Sd/8if4vd/7Pfz85z/f07FyPFuQJAk2K62nyY6Ek0h9JllzIilJEvzqV7/C19eu0c9nHxkPlwj1g6ppKJXLUGQZ6xsbA69ZWfBdN5NsGGRdSQihU1tT3z2SJLjy1Ve4cuUKTpw4gTfffFOsw5IkiV6brGS/n6tXPwjNOv//Ho61GwwrD90L6dLt/eHV4kOHDg18LCEf7fWYJIHveSCgWv20S91eDCz2hD73jxBq53rt6lX81V/9FSRZxs9/8QuMMxkOdzhUWH8HJ404oUQyrmevVs5Pc115rmQ8AN0ttVQVSRRRH3rTFOw8b9rt7MJOwzAMvPfee3hw/z6+/OorLC0t4ezZs1hYXOzdoDtgwmPZNuxCAUmzifWNDRzQ9V25KGQxMACEB3zWB58n+J2BgRCCa9eu4fbt2zh29CjOnj27I0BxFiaOYwRB0Mao0hceXMax86Tbn/u0g/LQDMw+NI11HuPbu3dRLpV21WTHj8Td4EiS0KZnUGaHb3Z3ONGwx+wlKO+mxN/vLtdqNXxx6RK2Njdx+MgRnDl9WpRKCZsvAdDNi8Q+kxIhUBWFznBgcjY5VVLejeVmGq+88go0TcMf/dEf7ek4OZ5NWKUSnM1N0cwvs4moErZJpG62sQAlkv7WL3+JG7du4cb163j0+DHOnz+PiX2yYh6pVOB7Hlzfx+r6Omanp3fFEnpMqtSJrO+58INnm23+OI4oivD5559jaWkJr776aiaRYRgGPM+jEtE4bnds2yvp06HP/sHkoYO+D3tcVzobSEW1+MAB6LuYm8A/3/y9T58ddwNUU6w+B7cRTQj5UbHJq6uruHT5MnzXxZmXX8axo0dFnhPHsZAkmaYpJh+nrV95/sTfT0VRUO6Y0zQsnua68mN6L/YNVoqFaes6H6JRZvHgQfzO7/4uJqen8dkXX+CDDz5Aq9Xal/MbHxujvvRJgrWNjV0dI/C8rnKPdFMjAcRAkqxu8jiO8emnn+L27dt45ZVXcO6VVzKZiH4szH6ww+SHCsrDVBQGaNbuh85X8TwPT548waHDh/d0XLHgMk9msMSYAGIeQxp83PxeGKX9LNfGcYxrV6/iV7/6FaIows9+9jO8+uqrbZpIn1XsFEWh05vjmG5wmB5TkeUd52TZ9p6Hz/2bf/Nv8E//6T/FsV6OVDmeW6iqCp3ZNgoDCKA9VvWJH4qq4tTJk/hbf/tvwzBN/PaDD3Dpiy+yWe0Bj5l+7fHxcSiyjMD3UavVBnteCnxQY7eBWiLp47007DlZEcD3PLz//vtYXVnBO2+/3bVimZaIel2kPLtGR8PrD0UiPbVKdcfrrLFq8dG9riupvkQJAInj7Tk/GTnIflSMd/PMbvfZ8zx8+umn+OCDD1Cwbfytv/23ceLEibY8h3+nNeZUFzGb9fScg06MjI7u+b19muvKc8fsA4BZLMKp10GSRJQ0029J35Ik28GZhoE333gDi4uLuHz5Mv7LX/wFXjp9GieOH9/+oOzmAy1JGBsbw+rqKlzXRb1eR5nJjwZF2l6013X0SsZ838fHH3+MWrWKixcvYm5urufxerEw3ZpOB0Uv26zvG+kx432xlwpGl2Pcv38fsixjcXFxb8dNgTAdLGHNRjsqMUi9X/tUkdkLVlZXcenSJXieh5deeol+x9jni08f5VUlgLlQSZKwPuRTJbPOZrcuPEmSYG1tDf/6X/9r3L59G//xP/7HXR0nx/MBu1RC4Dgi/g0LHmdKpRJ++t57uP/gAa5euYInS0t49dw5zC8siIRtN5toVdMwOjqKrc1NbFWrtHl3CL/8LMe6NHjVOEvOkEa9XseHH34IQgh++rOf9R34Zeg6giBA6PtIUvaN+xFb9kOmuBukq6VPq7+nc7bQXVYtHt8HS9Y0PN8XCbCW9VnpdL7ZBXaTS3S+GiEEDx48wJWrVwEAr7/+OuYXFrbzP3a/wjBExKb/8qoWJ5FUNpcn61p2Kw39odaV5zLZlzWNJqauKxouAAzMynaWY2emp/E7bKrZtWvX8PjRI1y4cAGjY2PIGgQyCAzTRKlcRr1Ww8bmJkzL2lEO6wXSxXVHTEXlFY0u59ZoNPDhhx8ijiK89957GB3gg8tZmCAI4AUBCowt3au2MnXy9O+nzOw/dQYmhYSVWhfm50WD6b4cN9VsZJomJDZluU2qtF9l8j3A931cuXIFDx89wsTEBH7yk5/ssB4j7LU8phHVVHW7tMreOyU1V6MTu5XwvP/++/jlL3+JU6dO4c/+7M+G3pDneL6gmSY0XUcYBDuMCvhntNd3Kp0kS5KEw4cOYXZmBl9duYJPP/0UDx4+xPnz52EXCm2PGwbFYhGe6yJ2Xaytr+PA3NzAyWbSJQ6mBxhy15ZuWF1dxSeffALbtvHO22/DYtWQXtA0DYqiUIlUEIjKAtmneJwlMfq+kV5TBnndfamQpo7heR6WnjzB2XPn9n7cFMLUYMaCZVEpaMbmb9dXswcCKX2XG40GLl2+jPW1NSwuLuLs2bM7pEx8jo0wezBN0beXxDHth5Plrj0Xg+RMWfih1pXnM9mXZZilEjzPQ5yyi+RfvF5fLEJIZiKtqirOnj2L+fl5XPriC/z617/G0WPHcISVyHYTSLjOMvE8rA2ps+y0S0yz+OnycpZGf319HR9//DFM08R7770He4CAzGHoOgLfR8D6Ibijy55BdnqrPw0My8DsN0e0vLwM1/NweMDG3EHhui4AKh3gQU40IPOFaF9fcTgQQvDw4UNcuXoVJElw4fx5LB482PV7xKdRSmif7hmxoNytymUYBsZ2GZR//vOfP/0msxw/WsiqCtO2EQaBcOXhUrh+CUo3qZxpmnjrzTexuLAgqsenz5wRk3d38x0dGx9HsLQEPwyxvrGBqQH7AtIWv+Jn6Z+zn8mMOOjEw4cPcenSJUxNTuLNN98cypLQMAw4UQQvlezvCyOffm+eYrI/9OyWfb7W+/fvQ5JlLCws7P24DASAx9YVwzC2ew35gKq93uc9Vor5QMVbN2/i5o0bMCwL7777LianprIfD+ooxHOpdPU7jmMQic5vacsX2bWNjI3tesr0D7WuPJfJPgColgWdJ6ZBQMdVA32ZiX4T7EZGRvDzX/4Sd+/cwbXr1/H40SMcO358d18qScLExASeLC0h8H1UazWMDSg54NUHXllIsHNh4DvT9If14cOHuHz5MsbHx/HWW28NzSZrmgZFVXewMHuGJP0gyecPwcCkP4N3797F6Oho31L3MAjDEFEYIgFQzNKq/4A6VgBoNhr4/IsvsLq2hvn5eZw9e7Zn4CRJIjYvumG0uSbxcmu3jdpsumybI8ceoRcKUJpNxEGAMAzbPre9pIz94sbszAzGf+d3cP36dVy9dg33793D8RMndjVgR5ZljI6NYX1tDc1WC7ZlDXQcThjJKW1+FtJNm/x533zzDW7cuIFDhw7h/KuvDj2g0NA0OJIEwjb13aREQ2Mfeqx2g6Fmt+zTOfJ1RVSLFxb2tVrseZ7IO3bEa06k8sZWDL9W7lUhsLGxgc+/+ALNRgPHjh3DqVOn2hu+O5DEsbBo57JQjihJIPEhWp3mIYTgwPz8Hs70h8Fzm+wrqgqzWKRDEhi7n/7odUvqBxn4owA4evw4Zufm8MUXX+CrK1fw8OFDnD59mg41GSK5UFQVY2Nj2NzYQLVahT2gzpI3HifsC9LtFbnejAC4dfMmvr5+HQcPHsSF8+d3PTF2BwuzT5rIHyIox0/ZMSGNVquF1ZUVXLhwYd+OSQihibEkUavNrGDHGBSJOYoMhT2wL7V6Hbdu3cKDBw+gGwZ+8s47mOoY9JIF13WFJVqnU0gURbQhufM6JQmqpgmGNEeO/YBqmjAtS2yoCfs8Sj3Iim7V4jYwFvHcuXNYXFjA5599hs8//xzT09N46fTpoatTlmWhWCqhXq9jY3MThmH0TfzEmphaV7qfLnW8IoTg0qVLePjwIV4+cwbHT5zY1eZakmUYhgHf9+H5Por7lez/UCTSMMz+fvU+seOIavEeG3PTiOMYgecBkkSlWVm5EzsH/hkaFrvV6a+vr+PGjRtYXl5GuVLBz3/+c5QrlZ6fQ0IIWo6DhBCoqrrjuxFHEXXiyVg/i+XyriU8PySe22QfoCyMyoaMpB0PZElCVnvVwDtRSYJECOxCAa+9/jqePHmCBw8e4KMPP0S5XMbJU6ewMD8/8Ae+UCjAdRzEjkPZzgMHeiafhBCETNLQ7xX4B/7ypUu4/+ABTp8+jZMnT+6J7exkYeR9Csz8nJ5mcCbDJvv7iLt370LVtH1lCTzPo+ycLGda6Ans5l7vclHaqlZx48YNPPnuO5imiXOvvIKF+XkofMhdj+f6nieGF9mWteM7FYYhSJLstBUFMDMzs38MYY4cDEaphFajgYQ193FIoFNTs9jcQeItlwONjI7irYsX8ejxYzx68AC//vWvMTU1hVOnTmFyYmLgdWV0ZASe58H3faxvbPSdrhvHsWg87ruusMd/+OGH2Nrawptvvon5PcYxQ9fh+z7CMESyj4w81/4/zQofJ5Gyps1/3/g+qsWcQFJVtbc8i93joeS9u1hXCICV5WXcuHEDGxsbqJTLePPNNzEzMyMmzfc6oue6SJi82+6ofvPvQYIMu2pCMPcMsvrAc57sK5oGy7ZR3dyksoYkAfhAD/SX7PQCD8yKLGN8dBQz09NwPQ83btzAZ59+iuvXr+PkyZM42EOHnMbY+DiCIOirs+ROQX2ZIoYgDPHJJ59gdXUVr7/++r44vggWxvPg+T7sQYdR9cGwk2z3A0M58ewj4iTBgwcPcPDgwZ6lxmEQRRECZrVpZiTGmeDBuYsOt+1xQwZkzrisrKygWCjgwoULWFhchCRJYjHsdcQoikSTsWWaUDr0k0EQiO+wcIVgv1cUBXP7qFfNkYNDMQxqOdhoIGBWsFy7LzP5S6ff+dCvoSiYmZnBoUOHsLmxgRs3buD999/H2Pg4Tp08OVgFWZIwOTGBpaUleJ6HarWamQByyU48hPSk2Wziww8/hOv7ePfdd8Vgor1AVVU6K4PFMS1jA78bSD+AG88wpg/7Zl9MCFqtFlZWVvDaPlaL+RBDQshgFsYpRylJlnu7Nw25rhAA3333HW7evInq1hbGRkdx8e23MTMzI2zG+eO6Xo/vi54by7ahKEpbT43HNja6ouyQQZuW1bUH4MeO5zrZBwC9WISqaQiCAM1mU2jis76Ew/qNc+0if+74+Dh+8pOfoMqYzEuff44b33yD4ydO4NChQz2Tun46yzaXHfZ6/UqErVYLH374ITzPw3vvvruvFlyGrlPWlXXm7xuesr56GG3lvl2nJOHxd9/BD4J9K7US0EFrkOiQk0EZbc6AELTrcHe+wGDXTgCsrKxQxmV9HeVyGW+88QYOHDgwlGyMJAlcNmFa17TMoTB8Y6PpugjK/Ds8MTmZyfbnyLFXyLIMq1KBvL6OhCVYJRarM6WhQxxbyIFSBgtzBw5gbm4OK6uruHnjBj768ENURkZw8uRJzB840DNmqpqGkZERbFWr2NzagmVZbX1W6XVl0AR1Y3MTH334ITRdxy9/8YuhDB76wTAMRGzA0X4l+2knoaeFYaay95NMDQpJknD37l1o+1gtFrJQQmBa1kAxnOvaRaW+V8I/4LqSEIJHjx7h5s2bqNfrmJyYwLvvvouJyUnxOqTLLKE04iii6ySozWbWOskryRq34UwZWszOzz+zPWDPfbKvGgYKpRLCjQ14nocgCGgSwJuLkCpZDpvMSdTbG5IkpvQCtIn34sWLaNTruHnrFr786it88803OHHiBI4cPty1DGZZFkqlEmqNRpvOsjPR5+faK0Hd2trChx99BEWW8bOf/QzlcrktGdorVGZ/GEURfM/b1YS+Togze5rMPv8iDxDEspyNdgVCcPv2bUxNTe2qAS8LvufRz2BW81Q3dF5LKtFoC84DsC8EwJMnT3Djxg1Ut7YwOjqKixcvYmZ2dsc96/cZTOspZUWhVYqdDxITD7llbcS+g4qi4OA+6lVz5OiEZtsoFItoNBpwHAeWZVF9L/uu8KRjIL1+BhRZpox0yuFkenoa09PT2GAVs08/+QTXSyWcPHkSi6xiloVSuQzP95E4DtbW1zE3O0sreakEHxjMQea7777DZ599hpHRUbx98SIMw9jXdUXXdTiuK2bk7IcMj2AIV5x9wjAk0n6tdmEY4t79+zjYh1gcBtwYQVbVzFktXdFx3RJz7NnhbNPncxPHMR48fIhbN2+i2WphZnoaFy5c6NrDIkvd5/WQJIHDrkdTVTEQrK0BV5JEI7LB1hU+y8UwTczMzvY83x8znvtkHwDschmtRgNRGMJxHKiaJhwHuJwH2J2sR5Jlmhxl/K5ULuP111/H6Zdews1bt/D111/j5s2bOHb0KI4eO5bJPI6MjMBN6Sxnpqd3yCvE6Oou5/pkaQmfffopyuUy3n777bbkr5/16DCwTBONZhNeEEDV9cGcBwbAD8HADKKt3K8d/fLKCmrVKt577719OV6SJMIr2B6QfQGwcwJo6v9pNqYXK5YQgsePH+PmzZuo1WqYyGBcOkHITqlDGp7vI45jSJKEgmW1PS6txeQyHr4IxVEEEILxsbF9ZRtz5OiELMuwSiW4rosoiuA4jmD3gfZYsZu4IUikjFg9PjGBn7z7LqpbW7hx8yY+/+wzfHP9Ok4w2WhWojc2OipkopubmxgbH9/BtpIeCSohBHfu3MHVq1dxYH4er7322nbz4n41mILeK9Mw4LouXM9ru6e7Bo9fT4lEGsbOeT8FRt/evYs4jnF8n6axhlEkeh2tDreankjJeNLgmy6SJH0/M1EU4d79+7h96xYc18X8gQN46623UOnTh9DrfjqOI2w22+RIrAeTgG6YOKnH8zNOIs0dOPBM94A9u2c+BIxiEZquIwpDRHEMx3FQLBS2ExjuPrCboCzLkMFKPSR7qIpdKOD8+fM4deoUbt++jVs3b+LW7ds4fPgwFhcWqI6SPy+ls3RdF+sbGzvsODnLnxWU73z7La5euYKZmRm88cYbbR9OITnaJ4Za03UoqookDBH4/q59Z9N4qs25KabhaTE/hBDcuHED42NjmNgnWZXjutQlSlGGL333WqTZwJSs98T1PDx+/Bh3v/0WjWYTMzMzOP/qqxjro90lhEDq8V0L2WcJoJWuzjI475XxgoB+B2S5PShLEhZyVj/HU4BZqUCvVuGxhN9js0cIIJKH3RIrvAcg6TGpd4RVz+q1Gm7duoXLX36J69ev4+jRo1hcXEQhNZyLu76tra2h2mhA1bQdiTQnkTpjYZIk+OrKFdy7exfHT5zAy2fO7NiA9+35GQKmYcBllcogDIcaNvljwFB2zvu0SYrjGLdv38bBgwf3ZR3mnvo86VWGSHK7XfEgsp5Gs4mHDx/i3t27CMIQiwsLOH7iBEqlUt/XTPgmIgOe54mZLFmEGJfP+b4vpLBcGhrHMRRZxuKhQz3P4ceOFyLZVxQFmm0jYV3WYRAg0HVqt8S/bLv80kmSBMgypCQRjVrdYFkWzp07h1MnT+L2nTu4f+8ebt++jUqphIWDB7G4sADLtqGqKkZGRrC+sYFaowFNVds+7NzLNs0aJEmCa9eu4c6dOzh27BhefvnlTFZBYvdjvwKzZZpioTMMY182EU+rneqHGGm+vrGBjY0NvPXWW/tyvCAMEUcRCDBY81QanIHJ+BV39CGpwBxFEZ4sLeHhgwdYWV2FLEmYnZ3FG2++OZDzA/fwjruwOkkct/npZ1kF8t4C3/NAJEmw+gn7/tm2jckBhwjlyLEXGIYBRdehRhHiOIbneTRJSG1QdxvLeMV4kHWpXKng9TfewEunT9OBQjdv4vr165gYH8fi4iLmmd+6ZVmwbRtxo4H1zU2oqirmzwDb2vH0GhZFET797DOsLC/j/PnzXXuMeP/avswhkWVYhoGW44h7uh94WkTSMHbO+1Vlv3fvHsIgwInjx/fleJ7nCVJwV5uHLtfFK7qStG3v6vk+Hj9+jIcPH2JrcxOqpokkf6AKLSEgTF2R9R6HUSQmXluWlblx4Wfrswo5J5C4O9Xo+PgzXy1+IZJ9gLL7YaslvlyO46BUKm03RGH37jyyJCEZopSpGwbOnDmD0y+9hNW1NTx6+BDfXL+Or69dw8TEBOYXFjA3N4dKpYJarYb1rS0amFkyJxgYdq5RFOGzzz7D8vIyzr3yCo4dPTr0NewWGtsBx3GMYJ+GbD0tln0YJ564C8M9LG7euIGRkZF98X8nhIiJhl099XtAlLYzPrcyS/IJIVhdW8PDBw/w+LvvEEURJsbH8eqrr2L+wIGBKwliWA+yNfuEEKrVJdl++uK8ACSgmxyJkLagTJIEB+bnfxAb1RwvJrRCAUkQ0GSBEFo15s26aJedDQOZafYTDJ5EFwoFnL9wAedeeQVPnjyhE22//BJffvklZmdncWB+HjMzM1R25LpYW1vD7MyM2FQLRpp9f1zPw4cffohWs4m3meNJL+ynRNQwTbRcF0kUIQzD/RkO9ZRkPE/bzpkkCW7duoX5+XnYqWrObsE99QlAE9zd3LeMz4LIrxhb/mRpCQ8ePMDKygoAYGpqCm++9RZmZ2YGXsu44w+65G5JHMPjRg+6nrle8bUpSRIEzHDESFWLCSFYOHhwqMv/MeKFSfYty0JTVSFHEfikN9/3afNfare5W90+Yc/lH5pBviCSLIumq1dffRXfPXmC+w8e4PPPP4ciy5g9cACjlQoM08QqC8y6roMP1JJlGZ7n4aOPPkK9XsfFt9/u66UM7G/Zle/8oyiiLIyu75ndf1oMDC+RDxKU9+Octra2qAXqa6/tw9GYpz7o+e/bJGPQ97S6tYWHDx/i0aNHcD0PhUIBJ06cwMLCQps8YFB0Wph1wvM8xHEMWZJQsO3MzxD/Scy0pATYDspRBNM0Mf0MN1DlePZgFQrw63UoLOZHUYSAJad7iRm8Ygy2iRXxeoDYqigKFhYWsLCwAN/z8OjxY9y/dw8fffQRdF3HgQMHUCyVYOg6VtbWMDs9DUVRtkkkANVaDR99+CEIgPd++lOMDlC541WB/WjWlWUZpq7DZfbO+5HsPy0Xladt5/zg4UN4nodTp07t+VgEVBYKidoZ9/TU74Yu91mSJKwxcvO7775DEIYYHRnBuXPnMD8/P7R7Wnrz0O33jusi4QRSlwqFwtYmodeXZSF/jsIQIyMj+zqz4IfCC5Psq6oK2TCQRJGw4vQ9D5qmtTUa7SYcyOx5aTeDYRkOVVVpgJ6fh+N5ePToEWVTHz2CpmkYGRuD47o4duSISNJdz8NvfvMbxEmCn/70pxjt0Pb3wn4GZkPX0ZJlobEcqmv/B8TT1uvfuHEDxUIBcwcO7Pm+h2lP/WJx96wV2R5e47ouHj96hPsPHqBRr0PTdSzMz2NhcVF8tnbL3PV6XhgE241gtp35fojqGyA8khXmCAXQZH9udnZfNz05cvSDYRiApoEEAXRNQxgEcB0HSqlEm/7593IX3xtZkpAAoqmQO+gMdX6miSOHD+PI4cOoNxpiA3//3j0YponR0VH4vo8jhw7RRAeUlLj85ZewbRvvvPPOjqFDPZFqdtwrTMuC5/u01y6K9t4c+ZQbdPsZVuxHFYQQgls3b2J2dhbFUmnPBF7g+0h2KwtNIX3ljXodD1k+47guCraNI0eOYHFxkVbBOEE6BITMlJurZDyGE0iSJFGdfhcCiR+jU68fJwmSJMHk9PRzsa68MMm+JEkwLAuu74MQAk3TqDtPq4VSuZx+4NCBmScnogzKjkMGZGIAtFlr2qaJk8eP4+Tx46jWanjw4AHuP3iA5aUl3P32W+qtTAiuXrmCQqGAn/70p7vTk0kSMMQ59jqOaRhwXJfacGraM+FFO+iUw/1YuOr1OpaWlnDhwgW6aPdovOsHQghcxxGa9d0ugpIkIY4irK6tYXllBaurq5AVBbPT0zhz5gympqZ23hv2/Rj0nvQr7cdRJHT6Rhff407wQVuc7YvCEKqm5d76OZ46FEWBapqIwpBKbxQFJI7hpuQ8Al0MHLohXTEWPxtSKpOOM+VSCS+fOYMzZ85gfX0d9+/dw+PvvsOjx49x+/ZtTDPDgM8++wzT09N48803h2bUJQBg8W3PFV5ZhqbrSHwfnu+j+Iw4oQxq57wfyf7jx4/RbDbxxhtv7PlYURTBc12R6O+FBPN9H6uPHmF5eRlbTIY8v7CAxYUFjI2Pt5OqLHEfJuHf8T3ouJdhGG4TSBlGD8DOaj1fV4Q0NAxRKBYxOjb2XEhDn41vzz7Btm24rRYCz0OpVBJlG891oe+hg53v4NOsCw96g3yhE+7kk4GRSgUj587h1KlTuHXrFlbX1nDrzh3hJDMxMYFqrQZN03YVmGVFEbvfvcA0DOrlHMcIw3BvSVdKUvV9YtAhMj0nAA6IGzduwLIsLOxxqisB0HKcbW37sJ/bJKFyorU1rKysYINNlx4dG8NrFy5gdm6uZ0OcBIAMyN5JjLFpu7+p95T7HhNQ3+Osa+HSuPQxA98HkSSYbF6GHwRYOHQIxWLxmdhk5ni+YNs26r4Pj8ndWq2WsC1U+HcpzfAP+BntrBgDKSKpX2wkpGvyJAGYnJjA5MQETr30Eu58+y1WV1dx59tvqV7ZMFCuVLBVrWJsbGy78j0g9tMEwjRN+L6PKAgQm+a++cd/nxjIznmfWP2bN25ganoaI6OjiPdwTDE8S5ahqerQc3PiKMLm5iZWV1exwhL8GMAM2zTOzMz0fu+4ecMAToHDEkiD5EUJIWJzoBsGnfMQxzh47Ngz35jL8UIl+4ZhwLAs+Eyvb1kWHMehPvGatr2T5ez+gIFZkmWaBHUEt0ECM0kx+j3PXddx/NgxVCoVzDSbuHblCsbGx7G0tIRvv/0WkiRhfGICU5OTmJyawtjY2GDe8aBBac9yHpZ8OUxjuZ8MK2FOKyRJELOm0SSOkQDbw9HY5icwYpASTYpj7obKLk11WpAaiXCOaDWbSEAHhoA1+siyDIn1Q+xX4thqtfDdd9/h7LlzuyrFp+F7nnDfsS2r/+eTEDSbTayurmJtdRWra2sIwxCKomBifBxHjx7F5OQktQEd8Lx4wt9zWFBHE7n4Mf87SdBstbJ9j1PoLIVHUYSIDTlRdR1RFKE0MoLRsbF9G1CWI8cw4Al+zNzedF1H4Pu0WbdUarNVBgY3guisGIufs797fVsHjTGlYhHHjh7F+NgYniwt4f69exgZGcG9u3dx88YNKIqCyclJTE1PY3JyEiOVymDnjv1p2FUUBbphIEhtpoZF+gzEObH1Ik6SnesLINZ/bp/qF7ePFcdsXQEAjUCr1+k9YXlDy3EgSxI0XYfKiDQ5tbZIkgSyCwVBJ5aXllCv1/HK+fN7Og5Adfpcr24NQiAlCaq1GlZXV7G6uor19XUkcQzDMDA+MYHpmRnMzMygnFZNDIB+vV2DJPqcDFMVJVN+00kgARBuPYqiQFcU+L6PqelplEqlPNl/VlEqleD7PnzPE+OSQzYUpVAo7CowZzH7HD0DM2NfBk0pTaaxTJIERJIwOTmJl06dQstxRDJ3+84dXL9+HYqqYmpqClOTk5iamkK5XO55HfsRmA3O7rMmtWEs0wghiKIIYRSBuC4iZim5456mg2TqengATySApIlkbP8/SRLIcSzeCz4WOw5DeOzf/Dn08NtJv6IokGUZqqIMXd68efMmNF3HwT129PMmaK5B7OZY4Hse/Tww9t5lfsljY2M4dvQopqanMTo6ijAM0Wy1qBXZsNI19A/M3dCZ6Be66PRl7PzeeJ5Hm8cUBaokIUgSzLOm4WeB9cvx/EGSJJRKJVTDEJ7vo1QsIgwCJIwttdLJwhB9Yb3WlV7a+EEJJI5SsYgwDFEplZAAOHrsGKanplCr10Uy9/XVq4iZS8nU9LRYW3ol37x5cq8ctmkYCH0fQRBQScYQ8TchBDFz9HEdB54sU7Ikg4zItG5km4KkIxgRif1XpvGM/ypOEVFRECBKPY0fXyT/kgRFVSHLMp2YPMR1EUJw4+ZNjE9MYILNNtktNcUrJwSgQwyzzoMQtFotShixtcUPAiiyjInJSZw5fRpTU1Molct0KKjnDT/zhV9Dj1yk689BE30nVfW2uxg9KBnrFpfwKJqGhBComoapmRnh2Pg84IVL9nVdh2ma8JIEjufREmy1ipBNITU7J6sNcEyZT9HtVrZkx+n8gA2T6HOUikXRrFSv1eB6HoqFAoqsCSshBLVqFatra1hdXcXVq1eRJAl1KpmexiQL0und6n4FZYm5wrie19MfOWGJfRzHYvZBxHyqoygSVQFxPxkbwtkROc28s3vL/x0EMtCibH4SAwnZTvZV04ZUsGjwTtlsmYZBmR1e+k6xO9xnN4oiUUmQJQmyokCRZarZZQE7C67j4MGDBzh95szQ5fA0uLOAJElUspUKpFEYYn19XQTiWr0OEIJSpYK5AwcwPTmJ8YmJHXr4JEmoVGAvm7xuDFWXAJkkCZp8kqFEnXe66SmzzqrlukCSQLcsRFGEWebikLP6OX5IWJaFpq4jYlVju1BAvV5H4PvU1SSd+AzYtMsrxln9PV2ToiEJJI6x0VG0Wi0osoyV1VWMjY1RCWmlghPHjyNOEmxubFD53+oqHj96BEIICqUSZqamMDk5icnJyTYmda/6fR4DVFWFpusIggAeW7OzwNeVKIroupIkSOIYLRZvIEkiBgu/dzCb037rSpOdE9lm9okEIAS0YlFsCkJGUsmSBN0wkDDrxjhJtjdnbF2JAIBVafm6oigK/cMcYbptANbW1rC1tYV33nln6PuaRhzHQqdvdnjQ+56HtfV1rK2sYGVtDU6rBQAYGxvDoSNHMDU5ibEsPXu6d/EpIWHDUrnzTk8CqTMPY5vyhKkTwjDEoWPHoOv6npqUf2x44ZJ9ACiXy/A8DyHrtraLRTSaTTiuu3MK6QCBmXsi8xJg54c8/X9+lL3oGUdHRmAYBgghWFtfx+z0tEiQZUnC6OgoRkdHcfLECcRxjPXNTaytrmJlZQUPHjwAGBM1NTmJkdFRjFQqKJVKUBRlIM3cDqTujWkY8H1fsCmaprWx9lEUIU6x6OKesOCrsImonGEYVlKTJBIIXxv5LeYyHlWBzJs6o4g2Esty5uKRsM9GxBYMXqKP+aaA/R9sw6BIElTmDpMO0rfv3IGiqjiyx+l7juMI2Uwcx3jy+DGqtRo21tawsblJN3SWhenpaRw/cQJTk5MwBijHJoQMJPfKgsT+xOy961cFI0mCVquFhFtsFgoDNU5x+EFA3SIkCZZpwiwUMDI6imKx+Fw0UOV4dsHZ/a0ogs/mjZimCddx0Gi1UGZJnMAAG2zu5tNrrWiryO4y0eeYmpqi1bo4xurqKmZTOmtFlkVCf+b0aQSMYFhl68q3334LABgdHcXU1BRGRkZQLpdRZK5Ee5WJmqaJMAypXbZpCjkkT+6jMBTEDEe6QqsoCkxdp4MfOyQ1gyBOUgdM2NJCACTUopIjIQS6pkFV1R0uRlxqGieJWE8S9m9+eE588TWRJ/2qqrZVlW/cuIGRSgXTU1ND3cfO83EcB2Drru+6WF1ZQbVaxdrqKqq1GkAIiqUSZhlRODkx0deOk0ufdsuIS6Ab3fTnvtfxkiRBs9nsm+jzc+uE4zhI4hiqokDXNJRHR2FZVt+pvc8aXshkX1VV2LZN9fpRhKJpUjcZx0Gz1UJJkobyl5VlmTa6skS2m6NIWi+4V70eHzokAVhZXcXMzExb0OFQFAXTk5OYnpzEy2fOIAgCrDHWf4U1ZXEGo1QqoVypoFwuo1KpoFKpwDTNob60EkvWHddFrVaDYRiIOBXCQFJBTOZMhqLAc134YQjLNEWD0PfVpMsXhm6JrmB7CAFSnwU+PjuJY0QsUHPWP4wi+NwWkll33bt3D8eOH9+VX3EURajVatjY2EB1awuNeh3NVkvcT8MwMD42hrPnzmFqagqFQmGo94onBv0s4vqBX2vfRN9xEPZJ9LtCktBg2ljLMCCrKubm52lw34dBMjly7BWWZaHZbCJMEvhMchKx5L9Rr6NSqQzVF6aq6jaJ1CXZ4bE72YfKbLrPKk4Ssa5kxQdd0zA3O4s5NtfCcV0hJX348CFu3rwJMKKmUi6jVC6jUi6jMjKCSqUyWE9XKvarqgpNVeF6Hqq1GlRVRRxFgv3nj1RTzLiiqnSdURREcQzTsij51HHs/YQYqJVFYqQq1J2SQ04u8U1AxP4mhCAIQ7quJAkUVUWzXsf6+jqdwr6L2B34Pmr1OtbW1lCr19FsNNBoNERuYtk2JiYmcPTYMUxOTg7FbktIuRHtZV0hRAzrlHk/RAZ4oh8nCeQeiX63M5EANJtNSIDIO6ZnZ4UC5HnCC5nsA1S777ouQgBhHMO2bTEQpdFooFwu7xyr3CcwRyzx62UfKAGI9mEaq2GaUFjnfMDsE2e7BOY0+FCVAwcOAKAJZb3RQK1aRa1eR61axZMnTxCGISRJgmEYNPFngZpvBLKY1IRN0Q2CQDS/EkKoLlFiQzrYn0ESve/Tiyc9E6EbsqQkEmPwoargy1WSSvqjKBJT9zjbNTU9Dcd1BeOThVaziVqtJt6DWr2OVpPVjmUZhUIBlXIZ84uL4v0YhLnvdl3c6nU/7jEBxBTDzN+zRD9OEsig7iVZ7z8fHrTzhCVawme6Sts0MTU9DU3TcgeeHD8qlMtlbGxswI9jGISgUCggjiJESYJ6vY5KuUyHZQF9HXokpumOWVzp6SrCNgV7qW9JoEYQuq5DlWUEYYi19XVMT072fa5tWTh08CAOsb6kIAxRq1ZRr9dRrdVQq1bx8MEDEXcty0KlUhEVgEqlglKx2B6P2YYoiiKEQQAvCGjzJYAi02PLigKNbQR6yV46r/P7Wls4idRrHc56bS5RTa8PSZJsrylRhESmU81v3b6NQqGAYrEINz0rqCP+EpYIV2s11Go11KtVbNXr8D2PVtIVBcVCAaMjIzh8+LB4H/YywIz3Qog1YQ/gw0O7vVdJktA8gxDIikI/Ez0Y/ax3pOV5iMIQkGVYto3puTlIkjR0Y/GzgBc22eeMYLPZhBvHKMkyiqUS6vU6oihCo9HYycT0Op6qQvJ94RTSDd0+dMNC1zT4vo/JyUmsrK4iiiKsrKxgenp6KKZWVVWMjY5iLDWQKyEETquFWr2OarWKWq2GJ8vLuHX7tmAnSqWSCNSmYUBm2nW+QVJVlZY6JQnlYnHnxmkQsLLn95HMJX2YfWDwBYEHah4kkyRBo9HA40ePsHjwIHRVRRSGVDoWhojYhrLRbIrEPmJNY6ZhoFwuY3Z2FuVyGaqmwbYs6IYx3HCbHiCEtCX8e7m/BHRhI4QgS2yQTvQl0ES/22eBT/FsAzt2k5WbNVXFyNgYKqOjokKXI8ePBYZhwGBSRi+KYOs6XVcaDURxjHqz2d70x1jLbs5WiqpCGiTZx/b3cC/RUmfM9/jEBNbX1uC5LtbW1zHJPPiHOQ6X/XAkhKBer6NWr6PO4t4DNmhJAo3F5XIZIyMjdMKvYdDBeYoCWVHoY1RV6OzLpdJw1UGGp0Ei9TILGGZd0dnmC6Br1pPlZWxubuLsuXOCBHEch0qcggCtRkOQd/VGQ9h6W7aNSrmMQwcPolgsQtM0mKYJy7L2bWCU+Oyx19zL55CvK9y+uRMJl4Syx3WbC0AY47+DiOLrSqMBKAosXcf4xAQs24Zpms/lvJYXNtkHgGKxCIclIq7vwzIMFAsFNBoNxIyJKaetxngja0aCpKoqIEk9k30CtI8830MpUdM0NBoN6LqOyYkJrK2tIQgCLC0vY2Zqak/OJLIkoVAswi4UMMvKtACrAtTrqNVq2NzcxFa1isePH8MLAnFPFGbdZVoWVE2DruvYKBZRKhZhWRZM24ap64MxMLx89z2UXMWUwx7nscMjvgt4Y5bnunA9D67r4vadO5AAOK0WPvvsM7ieh5A5HvDJfJytPzE7S0dyd7D1LccRn6f9KCnyBF84RPFkf5cMDHezIEBmEzohBC3XFYm+1cUdAdhOVHa8BpNNua0WCC8xT08DwHPllJDj+UG5XMb6+jr8OIYcBNA0jdpzNpsIwxCtZpNacqbQredFZclt1GcIH19XpD3GS43ZXNqWhbGxMWxsblKJztoaJiYm9iT5kyUJlXKZsqbz8+LnQRCgVquhWq2iWq1ifX0d9x48QMDipQQIDbxpmlBUlc4CKJdRKBZhmaaQYAxqC8pZ4/0GJ5G6nccwEiJCqPe767rizzfXr8PQdSw9eYJ7d+9SdUIU0X6NOEbCiLhKuYzFgwcxwmS5vA+REIJGswmSJFC6WFMOi6x1ZU8kHV9L6MF2/Fok+qyp2epmQc2kQG3HSEmpA9+HHwSQJAnFchljExOCyHwe8UIn+7IsY3R0FJubm/ABSL5PA3OxiCZjYpr1OoqlUhvDLwE7Sq8Ka/jhko7MZDtjd5n58wGgs65xgCaCk5OTWFtbQxRFWF5d3XPCn+X2oCgKCsUiVFVFeWQEhwhBQgjCIEAYhgiDAD4LTp7rotlqYWtzEw+CAIQHQdBAaNo2LNOkAdyyxM5cURR4lgWLBXWFseZc179fyV2ckezzBineOMUdg/ifwPdFMu95Hu35cF04LKEV7yNj6mzbhizLGB8fpxsg04Sm6/R9YSVoDrNj+IfPxsQTQmgD6j5cdyfrl2U/Nww6n5cuj/PmrziOIQHC1jYroe/cJLCDi59xOzVZUXBgYUEkT8+TU0KO5weapqFcLqNWq8GNIsigyWqhUECz1YIfBJBbLVqVShFJ/HuQ/l5x95iIubZkfVOTzsSVbcB347JlpNaVYrEISBI2NzbgMmeWyT0m/FkWz5qmoVQqQWPsKndFSxs9cIc3z3VRb7Wwvr6Ou/futTHIsqLAYmuJxTYGlmWBSNSFJwoC6IYh1hJZkiCzNWY/1pU0A51ee7ktZMwcguI4pv9n//bYmsLXFf5vx3W3CRl2nARApVQS94xfp8bMJhRZpjIxRuIYhtHWL+a6Lu0rkKR2S9i9XHfqPUhSa8qu7mnnpleSIKfY/c5Ev1AoZDZ/Z0pCOz57rVZLSOUOLC5CkqQ9y5h+zHihk30AgiGo1WrwwpCWCnnC32wiiCK0Wi0U0trgDK2lxAJKkCSIuiT7mRPu+DGGDMyapomJbwBN+KemprDKE/6VFcxMT++L9zghhJalfZ96/LMApLOSdWfnfOqJqNXr1HpNloEkEcmyy1hwjzXycoaCT2ft3GzwxUtmJV01/TdrxlIVBWdaLXRLAb/44hJcm1pVBmGIhLEh3C2IJ6Zi4EkqcAl7NFa5sGwblmVhZGREVDJ44P30s88QRxF++ctfZga8hBBxDr7vgxBCg7znwWCbAY9NALQsa8/vYSfzsv32EPH7oY7XTUeZqnw5joMolegrikKrFKn7kTXcBGhndAi36iQEI6USRsfGxHc2R44fKwqFAsIwhOM4cMMQFgBV08QgR9fztgcY9Uj4+XwPniB29vyIanEHuM3jsN9tTdepQwtDsVCABGBjYwOu62JtbQ2Tk5P7kvDzhN73fWF9DNYnxhnnrEQuiWPU63XESSIadTvXFNd1sbm1BY+tKzxZlukJiISXrytKej3h0iFmvKEqCl7vsjwnSYIP/uZvRM9WGIZ0jWQDuqIoEk27fBBh230AqOuOorQRX2NjY20bF01V8dfvv4/JyUm88cYbXc+FN4Sn1xWPzRQiAEJGIBVse88EkpiQnv5h6v0aOtln60fm89jnozPRz6pkcQOQtp92JPpxHKPFNlOz09OwbRvFYvG5loW+8Mk+0BGYPQ82a5SxLQstx6HDIzwPhmluf0EyPpCqqiIIQ0RRBKND88W/1B999BH+9E//FP/yX/5LjIyMAJKEP/0f/0d8e/cu/sW/+BcD67J1XRfML/9yGIaBaZbwh1GEpZUVTE9NZbr0DARWRuT+telgbLIkH+gxrVGiFoncNrLMGrK6oc507LzZirMfEWdBUkx7wv7PHXGErzIhSBLaIpTECcS4Ewms4Zh22Se8e58l02lXIL7Apv9WFEXoJ3uFsO+ePMHW5ibeeeed7sEuxboYzD86CAJESYLA99F0HPH527N2sIuOl38ehy638qDZ5TmSJKHFHIOERl9RhNRn+wQyEv0M1s/zPMRhiDhJcPzkSaiqitHR0Vy+k+NHj0qlQk0fkgSO66Jg29QyOUV6KLIMVddFEppVOVZVlcbBON6Z7GetKQD+9E//FPfu38f//b/9b2EPIQHUVRW1FIkEQCRV6+vrcNnAvqmpqd0ni4TAc1202NwQkiSQFIVKcXRdfLe7WY7KigLDNGmjKagVdbrnrP2lCDarVbieJ+SjfB0JGeEj3NXY3/zf3KefMvI8hhLECRFxKpElsTbwc1ZVta0yLdYUVk1oc6GTZRimKeRa3fD19esIggBnzpzpeWslWYZpmnRdYWRSwsiXluNAZ6YGvUxEBgXJMBoRBNIuE/1e0qpmR6Ivdyb0DHInGZWxrjSbTbrJ0jQcOnwYhmE8t/IdjjzZZ+CB2Ytjar9ZKEBnXvaO68JxHEigzEd68AZngMG+xJIk7fCRB7a1fG9fvIj/z//2v+HP//zP8Q/+wT/Av//3/x7Xrl3D/+O/++9gW9bAbAy3EAvDsC0h1HUdU5OTIuFf4Qn/kKWpkLElPNEG08algzFHr3KxbhjwgwBxFMFjC143KCldZnpkN0GGzKMLgr/8NchWHYAEWW7/kp9/9VVIEzbVzbZaUBQl8wu+W2u2OElw7do1TE1NYZrpyjPRUXLXDQO6YSAMAmxVq6LsGzF3I03TdpXcSkDXQW9pCc/Ax+6iK+ZIkgRuitG3bXt7UUndzx2MPvt31nvcbLUQRhEOLCwIxiv31M/xLIBPrV5bW0PI1pVisQjTshAnCYIgoGuNLIMoChT6pO0/7PugqqqIoUhprDmr329NGSaW8eFVnbBtGxOTk1hnk1N3YwYBUJcehw+5YpVSo1AYOsaZbF1J4hh+EAgr6k5IEm3qly0LhUKhbdDjMN7//v/8H9nCwGQl2G7EfevNNwFAsOhdzRQ6mP1B4Xoebt+5g2PHjvVkntPxM00meUGAra0tAJTRDqMIKpuBsxtIPa5DyHiGidE9CFSAnjMnHNOJPtB9fePHy5omzee9BGGIl06cgKZpLwSBlK+aDDwwa7oOIsvU4osQGKYpSoqO6wrvWx6sRGBGyheZPYaDW1GxF8L/8b/+r/Gb3/wGf/7nf46/+Iu/wP/tv/lvMDo6KhqsBglBuq6LZD/rd1OTk9AZI7S8soIg43FZ4Jq4RqOBMIqQsJLfSKVCJTtZX4g+XxKurfZ8v2+jGYDvpSE3DaHX3weJUxr37t5Fq9XC2bNnez+wy/WFYQjDMGCbphgU5Xoe9dbv4/LUCS7dGeQcBmpq65Pox1GEZrOJiE2PbEv00b4QdSbrhEvDOhD4PlqOA0mWcfDQIYyMjOwLI5Ujx9OCLMsYGxuDouuIQTXTAE2eNVUFIQTNZhMkjllVMmmPD4TQYUpSD/OHXmsK+/2g0FKa/U7YloWpqSlqyxkEWF5e3jHIqhviOEa90aAxgj2nWCyizDz3h11XuARKkiR4ntcz1nU7yn4nd8L0octxd7uqXbt2Daqi4NSpU70f2OV1IzbzocA2PAAE07+b4Z69njMMsz9Ik3QYhnRgVno+S7rPLiVF5X96kUcAzeN834ddLGJmdvaFIZCe/yscAiIwmyZ1AEnppnU2CbbVbIoAx4edpHX7iqqCdAbmjg/d+fPnMTc3h//wH/4D/uAP/kB43nMMkvBzOUm3wKzrOqanp6GzBWV5ZSWTsdk+Rarvq9ZqlEVKEmiqSv3cDYM2M+0yOPJx54osCy16FnodfT/Tf9InKO8GfhDgmxs3hF/xsODaUgIIH32bLWaEEDhswvOgbFSWRr/z98AQiX6Px3KGkpfji4XCjqScv54MtJVrd8h7UqjWaoiiCHNzc5iYmHjuhpzkeDGgaRpGRkYg67rQqEsscVFYvxP//gAQU7ohSQDrR+L66M6pohz91hROSvVdVzSNkjxdEjpuBqEqCkJmBtEr4eeV8Vq9Lsgjbi+s63pbg20n+jUYG6zKDlBWvSvSseZ7BCeRuvZY7YLEqlarePToEV566aW+RMeO+0UIdXRj8xdGRkZQYVbZEusDadTr8DxvoMo518f3XDHY7/utKgmr6vSC53lwWi0qt1FVlEqlHYl+pxKCr5e9rmZrawsJIVhcXMTY2NgLQyDlyX4HNE3D6NgYJE2Dz8pykiTBZk2GCWNi4jhuazTi4D7A6WS/84N35coVLD15giSOUalUMs+jX8LPJUO9EnhVVWnCz4Lq8upq5uP5NYlkUpJQLpV27KL5ee0GlmnSHgDWxNQLndc9SPAYBn2D8i5w8+ZNEELwUj/2JQO+7wv70oJlCRtX3TBQKZVgaBogy4gYy9GL5RcMfJ/XFIxIrzkDjMnv9jkUjcWOQxlIVUWRfU86HkhfC9vJfb+A7HkeavU6dMPA8ZMnqTNIjhzPKCzLQnl0FLKqUqlbGEKSZVHBi5nMh+ugCSFtG3JFUXqSSIOsKfxYvb53XBLaK0ZzMwiVNd0vr6xkJvyczfc8T2jZy8xBhq8jEutRyIpXpN9aI207yvieJ+L6joeJA2a4tvR+haHQy855N9JQAuDK1asoFYs4fPhw/8d33C9hywnA5hPLJQmmaaLEdPuSotA+sVarL8s/iARpUNvNHQ20KXB1Ae/J0AwjOxfhr5l+bp97XK/X4bouCqUSjh479kIRSHmynwHLslAaH4ekKNQCi1k0FdNMTKNBJ68xxAlV8SmKAhloC37pj9/9+/fxJ3/yJ/hH//gf48zLL+P//e/+Xdfz6PWF4cmz24MpB2jCPzU1JRL+pZUVMYkU2PbO56yLbVkol0pdd7u7Tbx5U5UsSXC7MAm9jrufJVcxzjsrKKe0soOi2Wzi2zt3cOLEiaGn2oZhKN5D07KEHzKHxCb7FYtFkURz+75OiGa3AV6XcM1sj5Kz1CcgO6mAbJgmXVC4lrJDxsbLq4P0X/BeE0mSMHfgQNushxw5nlWUSiWYLBFvtlrwfZ9O/mTWunyYo1g7uCQUgJbht8+/R8OsKUDvWGqYJiRQnXgvGIaBqclJaGxy/NLKikgsATZBt16n08QBFIrFbCKAnlDP1+oFjU8ll+Xua2E3MwHsX3WXELJdMc5YV3azfi0vL2N9fR0vnz07uCyGwfN9Kt1lMtzO9VxhFdgCs4cmhFDpbrdN3oBrIncc7Mra96kwxXFMDR64rbhlwU5tDrPOSZIk0SvQC57nYX19HbKi4NixYz3NQp5H5Ml+F1QqFRRHRyGBSjRarRYkWUaJJcIJIWi2WghY4swZVZXtnrkkA9jeEa+vr+OP//iP8Xf/7t/F22+/jb/39/4ePvv8c9y/f7/7iXT5kquqCrtQQL3R6HstqqJgampK9B6srK7SZiLfF5MdAaDMphb2CyycjRH/73sGFKZpAozF8nswR99nuTVdiVEzFp7dhP6r167BNE0cO3p04HMA6EbLcRzqEqRpXZvMAPp+l4pF6KoKWZbhp32Y0btpKgtxktDpgxn3oF9lII6i7T4Cxq6ZTHLETkYE+/RnaZBSceD72FhfRxhFsItFvPb6689941SOFwfjExMwi0WAbZY916WJF5MoxJxIYokzX1dkFnO5+QPvA9vVmsKQ9W0sl0qAJKFRr/d9fjrhj+MYK6w3zHFdqrMm1AKxVCq1NcZmoXNNAfrLeDgs24YECCe8bvg+15U0gZQVrwY1mBDHIwRXr17F5MQEZmZmBnoOf9UwCKg0B7TPolcjrsbdeRQFkizDbbXaZD3CGWpAENavmEmk9XluWp8vyTIKxWLb0K+2BmRJQszOb5BKgut52NjYQJIkGJ+YwKmXXhr4mp4X5Ml+D1TGx2Ezf/3A96ldE2hjka7rVMPPBitx8OSJEOqlzj+erVYLf/iHf4jXLlzA3/k7fwcAcPToUZw7dw7/7t/+294nkmoCbju/SgWNAZJ9gCa2k5OTIqG8//AhNjY3kRAiBnQMI2tpS+IGTMb6NlXx42QFl31q2uUNcN1caIYNyuvr61haWsKZl1+GMqj2T5KQxDGcVgsENJEfaEAUk5Nxb24u6+nU8g6CJI4zmX1Jkmig7vKehmFI5QYsIBcLha72oDwQ86pXP3ieh5bjoNVqQVUUvPrqq8+173GOFw+SJGF8ZgYmS1Bdz0Or1YIsy0JawWWVQaoCq6gqEmYXGbEYttc1RcpYV3RNg22aqA+Q7APbZhCaqiKKItx78EBUJwzDoBXJAZsfRcLPY/CA64qiKNQlT5Lg9Kp0f4/GD1lDGsXLYvh15d69e2g0m/3NHjpeJ4oiamkKwNR16ANMyJUZy2/oOsCar/kgw2HPm/cxdhJpWZu5NPwOfX6WPShfs2Vsk3b9zo4QAqfVQrPRgOu6MAwDb7z11nM7OKsXXozOhF1ClmWUx8chA7TRJQzRaDRQKBaphkyS4LGpqjGbmCpJEnRdF8M9LEWhWuxCAX/4h3+44zX++T//54OfUIfEpFwq4eHjxwM/XVUUTE1O4uHjxyBxjI2NDUxNTWF0l+UsnswNA0PX4TMNp+95bUnuIDKeYV+vE/10lYPo3dOPv3r1KkZGRrCwsDDwOXDrLwJAlWVqRzoEe22wKZDcwq7ZbNLhN0M4CvCgzDconI3p5ZDgeZ6Q7aiqCouVgHdcHzvGoBsQwuRoURiiUa9DUVVMzczg8JEjA19PjhzPCmRVRZk5gDitFoIgAEkSFAoFFItF+rMwbHOEkxUFumEgCEO6rjBnlT2vKYDooeHf+nKlMlDFmIMn/A8ePkQUBFhbX8fc7OzAM2PaT0UaKnZwWJaFMAjopPMwbK8k9HL1we6km53g0qtuhNkwtckwivDNN99gcWEBlSHWZl5xlUBlX+Yw91+i1tqqoqDFXAebzabIcwYBd5MiqeZbgpTvfRdyzWG5FUDdoKwesh1JkmgDe5L0ZfNJkqDF1pVmswndMHD46FFMTEwMdD3PG3Jmvw80y4JZKKDIGlzSZVbLtgXzGAQBWs0mSJKI3XTI2FNg70mqQErvViyXxQCjQUAIget5VA7CvIBbjoO19fVdWXBJXK4xzLWxoAJkWHE+BblGr6Dcj33oxN27d7FVreLcMOwLIWg6DmIWuAqFwq6uW2UzArhsbJAGK462oMw+TyJpzziXzoYp3TDa9Pnpa+OTKXlg7ve5J0kCx3Fo74LngUgSTMvC+QsXXgg7tBwvJrRCQfTicFe1Bls/7EKhze651WqBECIqaHyYophmvg9IJ07lcnkgGQ9HkiTwPA8VZqNpWRa2qlVUa7XdnQt6aL67QJZlmCxJHMa1jL/eXtGLRBoW165dQ5IkePnll4d6/RZL9BVF2XVFVNM0lFgPCU/EB72TfJZQeg5Rr4ZwvqFo0+czwjQNTsKlybh+n/uENbwnUQSn1aLmEaUSzr7yyoBX8/whX00HgFGpQDMMlFhJkpdZwyCgpUo2YTBkDVYSIMpEPi/FspLYMEGoG/gXqVQqQQLQHJCFcRxHlIYXFhYwPj4ORZLgOA5WVlf7uuR0gzJkwq/pOlTmrczLhWn0OtJe715PZn+Ia2g5Dq5eu4bDhw9jfECmQLAYTFdaGJKNT4OXNLl9HyQJTTZ4pB/SQVlmHt4DN0zZ9g7mpW1wCU/0gb6fdx6QY9YcHrJBLy+fPYuxsbGB7kOOHM8iZFmm64quU72+oiCOIjSYLM/OIJJUNpE1JgRRFInvYOdcl12DHa9cKtGenAFIJJ5khmEIWZZx8OBBsU7WqlWsrK0N7MXfdioYvqnVNAzRbJpu1u3lxrNf4DE1U7I0xOuurq3h3r17ePnllwd2iuHvAbezHLZS3Abm/FQoFkWFhctNBzkPgG42+hE9EatCJHEMZOjzgVSS30li9WnGjVLOVnwSsqbreOPNN18o951O5Mn+AJBlGebICBSmbVdVFYR5I/u+D03XhQdsnCRoNJuCOQ65awq3GgP9UuxH0j/C/NxrAzAoLXauCZMUqaqKSqWCyclJKIpCh6SsrPT2K+4GaXgPftuyAEmizbopbSqArsFxPyw4uzH7w1ijEQCXLl2CoWlDsS+u59FEn5DuzhQDgp+pxIK7wpJsHvR7gX/++r1+Z8NUsVikus7UOZDUv7POrxv4JiJOEkjMVlRSFByYn8fRY8f6PDtHjmcfiqrCqFRE872iKEiSBA3m9NZJJDUZQykBbTGTJ8VRFLVvvHcDSUK5UgEf9tULhMWbgPWmcZ31xMQERkdHoSgKfNfF8vLy7oikARovO8/dLhRos24Q7HjNbndlP5j9bnbOw7wTURTh0hdfYGJiYiCrTWCbQEqYrKVg27sikLiHPgd365EkCfGACX+UWlcIum/WfM9Dq9kEkgQys2tu0+czYpSwtbrzOL3WtzAM4TSbQkrkBwFUVcWJU6cw1Wuq/QuAPNkfEIqqwiiXqSMPk8EAbBJdswkJaAvYvu8jYTvLzqDDv1h7TfpVTUOhWOzbpOv5Pjx2PrZttzWnWJaFmelpGKzheGVlZaDNww4MmfDLsiwstVzPoyzSAM/fq1VaN2Z/mKM+ePAAa2trOH/hwsADOXzPo9rcLlZog6Bb8JQVRfgQE0Ko730PxGxh6DZBOEkStBxnR8OU0Pcjxbj0kA5lyYoIIfBZs3tCCB1lL8sIwhCVSgXnXn01l+/keGGgGQaMYhEyk+XxqbqNZhOO40BlBBP34g/YwMMoDLcdYFhckFl/mBj2uMu1pVwuQ5blvuuK4zgIWUzrbKgslUp0+Bab4v5kaQmtPnGpE5IkQRqihwqgvUTcUa6VmhsDoOf92Ivjl5h6nGH6MMxRr3/zDVzfx4Xz5wd+jsP09dxiczdT4QUL33HuqqrS6jNL+PsRgSI573IOXLbDj6Ppejvpxd4fMV+iyzqQlTORJKE26ewzpmsa/R4kCaZnZ3FyF/Nvnjfkq+oQ0AwDerEIwuQTXM4QsMbdMIpQKhahsaAXBgGiMOw5+Cqd9O+mFDtSqaDRbIomq05EcQyXSWUsy8p0TtE0DTMzM7BZw+VWrbZ7Hf8Qj9UNA6qm0YR/wIWg3zCmXkjI9sTjHXrzAY/heR6uXrmChYUFTA/IFPieR32rCYFpmju89PtiAP07T/glXi3p8pmTZBkJK/tnJdW+71NmkT1fTw804YxLOsnosUh2ni1n83mw15ndaL3RgGVZOHP2bO6+k+OFg14oQDUMQJKE0xvAvov1OkiSCCIJzBkujKId6wqvfPJNv0j6h4TGHHka9XrXdSUIAlEpznJOAajV8jQjkiRJwtr6Oraq1eFORuo+dKsbLMsS8cr1vMGeuwfSLU5JeLL05oNgY3MTd+7cwctnzlAJTR9wJ0Dev2HZ9uBucNsH6fr+cqiqSmVBoLbIWdamvPk2ZrLNTikTH77YbDSodSzry+L6fE4e8Ryos8rQeaxO8Ap0EATUIMUwaKNxq4XyyAjOnD37wkzJ7YU82R8SBg/MoMGMW1bGrNGw1WrBsm3oug6NjUdv1Os7EmeuuU7rCXfDypSKRdFM1TkEibO8CaHTTXsNfJIkCZMTExgZGRE6/qWVlYHLr/w6ulladgN3bIjieNtqrg8Ds1t2P83qt2nO+7xm+nGXv/wSsizj3LlzA72mx6YwA3RgjWmaQy/AgzS6ArT0arFZBp7rtn3meFmVEELdDDpkPHEco9VsUhtZQmh5tVgU/vmdm6x+70CafRHBnk2e5lWdQqGAeq0GRVFw6OjRgf2kc+R43mCUy1B0HWBEkpisy2ShruehUChAU1VoqgrP89BoNHbGBS4X5c2RnEwaMvEvp2ydO9eVJElEE6xhmj0TKT7FvVgoQJEk1Ot1rKyuDqTjF0kfT/gHjfuSJEgDP5Wg9rr6PTP7yJ5ZMsi6EicJLn3xBUZHRnB0gFktoveLVVU6q/UDgRM1A5yfqml0w6YoO5uf2ecsIUTYOafXlSiK0Gw2t13cmK8/l4Mm3XKdLu9H25qWJHAdh8qY2OsWCgWYhoGtahWmZeHYiRMv3PCsbsiT/V3ALJchswCnKArKpZIILrxJN63D9H0fm5ub2Ykz/9KlNP18lztIgC5XKqLJkR5u+1i+7yNkO/9BGdNyuUzLr4qCKAyxvLLS27s4fR0cQ2gtZUWhQ1EkSYxV3zfnog5E3ZpzBzzX7x4/xtLSEl49f76rt3waLkv0CejG0NpFog8Mp/vUDUOMQRdOCmyxJIAIypzZT7MufEiWYZrCfSrLa1lYqfUAb1iLWOmWa4x1XUeJNWO1Wi14QYC5+XkcPnw4l+/keGEhyzKsSkVIFzRNE0MOCSEIgoDaB+q6qOA5joNqtSr04jvQyTITOpFXVJF7xKJyudwm40nHcy4dkdnclH6QJAnj4+NUxy/L8DwPy8vLO3u1eh9kKIZf1TTozHs/PSSq33nuBl1NHwY83o0bN9BsNnHhtdf620mSbZMHAsBmxOJQGDDJT8OyLNoXxu5n53E6nXgSTn6mer4s26ZVYqbp77S5HuT+841GGARoNJtiSrDJDFQ0VaXkpyxj/uDBoSyxn3fktY1dQJZlmJUK3K0tYTVomiY0TYPDXAwcx4GqqiiXy4iSBJ7vQ2k2YRgGTNNsCwziI86+JJ1OJwlrYuQaxnQQKbMm3Uaz2baDTeIYLmN3u/mhd4NlWZiZmcHa2hqCMMTa6ipGRkZQYaPe+yE99XGQngTDMKjkKYrg+f5ALAUBa3b+dhPJlSUky7SZjKx3lwOF/+EaIlOCYppIjk1Dev0AJHk7Ee4Fz/fx5VdfYW5uDnNzc33Pz3FdUamwTLNnVSULYiLuLhYg2zRRbzYRJwnCIIDGyuhAe1BOmM6R/0xl3sxprWTm4LE+r08Yk+gFwfaEaQBWoQAj5VJVq9UwPTuL+YWFXL6T44WHrCgwKxV4W1s0vskyTeY0DS3WhNlyHLFhrtZq8DwPElt/Oqef87iWrgxytpwAdII2e1xnnCmVSrh16xaSON5mrCUJYRDAZwTGsLbBpVIJmqZhY2MDURRheWUFE+Pj9Dhd0OkUxl9tkFTVsiwxyd5nznm9wO8XAUCuLCO+vgqy5fZ+wTCG/79eRiQTGMUikjMzkM9QeecgG4xqtYqbN2/ipZdeEmt5N/CG6LSb266GQ+2GTJPopPRms0kHu+k6rejwdSXVoBzwCb7sZ5qut1WIO69p0E0WYRp813URsnsgSxLslHTacRw0XRfzi4tYXFzM5Tsp5Hdil1BUVST84mesycpng7a484quqgijSDTuhlHUdYw1Z1vTEAGakO0Azb4gpVIJkkTHm6eTfY/pKVVdH37nD5r4zczMYGNjAy3HwVathiAIMD4+nrlx6EyY+fkNKkGxbBs+u2c9exzYa8kAog8fIvpfLw9Mfcf3N0EUAB4Q/c13kL5agvp/vgCo/TdCV65cASEEr/bx6eW2b7yKY1lW30Wm4wDbOspdMk2yoqBgWWi5LjyW7HPw/pAwDOlcCNCkwjSM7p+TIc8lDENqA8qCva5pdMPJjhGGITY2NzE2NYWpmZmBex9y5Hjeoeo6jHIZbr0uEltV01Aul4UkMAgCEFASIWCNuq7rIggCasWbklH0isO8ikxS/+eJP088m80myimSx/d9EFCCZjeJFNfxr6+vw/d9rG1sIAgCjI6OZj+hk4VmhNcgIZ9vljzPgx8EIkHsBl75jP/sayR/9e1gF5QQRHfWQSQArQ1Ef/0A8u8dh/J3+jeEJoTgi8uXUS6XceLEid6PZUx5FEWQABQ6+iS+n1p4O1RVhWma8Hwfvu+3vT63uIzCUNg0y7IM0zSh9tiQDFxNIQSu79P+Q/YjQZyyY3ieh61qFTPz85iZne3+mXpBkdfN9wBV12F2fqCYDKLMnBW4RId74MqKQv3Fm03B1nSi17RYIfNh7KmiKLAtq328OSv7EkJgdbA9w0CSJGqjxnX8noellZWhyq8SBnPQURSFjpCXJLiui7jfBsGPEP2br4aKcjE7DYXJRcmXSyBXV/o+b2l5GY8fP8Yrr7zSk6HnJVbuUDF0og8A+yFlkSRomkbvOyFti5zn+4IdIqABvFgo9N4QDsG8uI4jBnzJErXCS09hDMMQ6+vrGBkfx8zsbC7fyZGjA5plwSyV2uK/JEmwTFNIQ2VZFj74CnO0iuMYjUajq2ylZz8V2Z4DkxCCYqkEArRN0o2iSMQSa5jprB3gOv5SqUR1/I0GlofoDwPr2xpkXdPSch7X7Uk8SQDwqDZ4og8gkUATfQASW8qT/99tYLXV97m3bt1CrVrFa6+91jMG8ooO73PoTPQBfK8zBIDtTaCuaQChcx74+XApaMtxqEQUzNihWMxM9IeVsibM2IEn+kI6bVliXfF9H5tbW5iem8Ps7Czm5+f3dsHPIfJVdo/QdB0m8yVOQ1YUFJmWXzcMEJbgyywRA2h3e4OVxTrBp9MOouEbGR3F6tqa0GH6vg9CCFRFEb7MezGsLJfLmJqagirLiMMQy8vL2NzaGsqtZ5CE3zAMUTLu5s7DNeTx7Q0gGvz1Ewkg7NMup54Wf7PaM5kNowhfXr6M6enpnvq/LC1lVqLfNdDxc9ht0E6XQxkTr7OGv8D3hRNOg2nzFWarJpx2sk5p0JdmtmyNRgMe++zpuo5Sudw2tj6OIqxvbKA8MoLZuTkcPnw4L7PmyJEB3bahdyT8kCTK8pdKMA0Dmq4jYk5wqqpSf3NWWeTf8yz0NVEg1BLXtm2ssXWFEIKAfbcNXW9bU3ZDJkmShLGxMYyNjUGRZQRBgO+WltpJK/SJQQNKQLjrS9TDPpL3MSTXV4e4CiDhg8cTQE69Vcn1tZ7rSr3RwDfffIPjx4/3bCAVA7NY82upi/NRV+yh8RjAthMc+7esKNCZg54fBIjiGPVmk8qX2VDEtLFD9ikNdk5citxoNEQ1yzQMlJkpCofv+1jf3MTE9DRmZmdx8ODBnEDKQH5H9gGaacIcGcnUpxu6jrGREZiWhSRJhOaNJ7WC5WdsaBb6fTmmp6awublJk7okget5iJNkB1vbdpQhk0rTNDE7OwubJYeNRgNPlpZE8+4gX+B+Cb/M2CsCmmT7bFgLZ5si5iQTEwIyMhxj3i0oS6OMoeLn1tEwfeXKFYRRhFdffbXrsbmWkjdDF/ox5Z3YRcNU1jE6NxK6rgOMFarWamL2g6ZpGGHDfLKuRfy7z0umk3zf84SntW3b1PNZ2nabiqMIaxsbKJZKmDlwAEeOHNmVvCxHjhcFZqEArVDYua4w/fT42BgM00TMp5EmybbXPmP53R5sdr+YPTc7i6XlZVpFjmO4jDRIf28lYE+xq1gsYmZmBoauQwawVa1iacDmXS5v7buuMDkJQCubEWOf+boSp/7GyHC9VTHLOZXOpXs0dZx0Dx7788WlSygUCnjppZe6HjthgzsT1ruVnnWyAxmfkcyfDwNJAjplxYRQ8pIQ1Ot1NOp1BL6PBLTaU6lUug5rHHTbkTC78EajIXq+ZFVFuVjcUVHiktDxycm8UtwH+V3ZJ+imCatcFraGAoyhn5ycpKVR7ojAHFG4hjoIArGDzUIvNmZmZgYgRFia8fHpqqZluvqkG7KGKakpioLJiQlMjI/T4S9JgtW1NaxvbAw8El3ukdhKkgRFlmkwSW2MeFBOP0+aKQ0VmLsFZfmlqfQJtP3uu+++w4MHD3C2h/87Z164lrJYLA7WNNXJxO8GXT4TBNRKMwwC+EGAIIroRgRU59up66WnQAa2t+tM8rmNp8WsaDuT+DiKsLG5Ccu2MbewkCf6OXIMCKtUgmHbmUSQpmmYmJhAoVBAzHrCeLM9X1c8z0O9B8sPdP/Oz8zMwGm10Gw0qOsJk43KzGo6Ydr5tOZ/N+BzXsaYW08YhlhaXka1Vutr8CAGivWIWxIATVWhKgoSQFQ9+LqSXgPlExOAPPiVxCyDUtLLn6ZAPjbOT3D7bxavb9y4ga3NTVy4cKFrYswHUCVs2GSxUOjpoy8+Hby/ahczcjiEox8hQJJsN0UTag0ehiEc1iQbRZHojehnsjCIg5tI8lkepDDTiKzr55LQsYmJPNEfAPmd2Ufotg27XN5pVyhJUBUFBduGxaan6swhhQ//8JkbTavV6sny08O1ByPLsjAyOorl5WWR6Gus1MZfXzAZHT7+u/GstwsFzMzM0KRRluG0WlhaXhbT6/qBX/MOsGCiKopwhGk5TvZjFRnK7x4f+JyzgrJ0chLS4ewmnmajgUuXLmF+fh6HDx2iiXBHIBlIS9kJfi0DNi73RMo/m7C/kyRBwDztHc+DpChQQBdUwzAgy3J7YxfZdukYlMmvdyT5tm2jUCxS158dp5hgs1qFbpqYW1jAoUOHBMuWI0eO/jDLZWhdEn5D1+n8DsuCoqpUtsnWlYQN14uYHbST0SMmGnixc12ZmJiAqqpYXllBHEViXUk/j691e50GDwClchmzs7MwDQOKLKNWq2F5iB6xzLWMnVPMKpoy6DrY1U561IL89uB2jQnL1eXUuiK/dxAoZpMZy8vLuPHNNzhz+jQmJiYoiSfLbXEzjmPK6LM+v2IGObMDqXVlWEMFAWl7NgP4usKrHnHcJtVUFQWKRAdYaapKpV8pkqvTVrMXuiX5hWIRReY41PnJiqIIGxsbKI+OYnp2FkePHs0loX2QJ/v7DN22YZRKO9l0tvtVWFlMURSUy2XaPCTL0DUNYRQJxwXeaNUrOKe/0LOzs1heXqb6f0K6l9JYUsd9bvkQL8K+5IMmoIqiYHx8HJMTE2LE+9rqKtbW1oTnfy9IqYSfJAllplLnyHWW3IUgC/I7iwOz+5lB+b/KdkCIoggfffwxTMuio8tTTAcPzly6M4yWktvd7QosoW9bZDuOzaffOkxSI0sSCpYlpFfcEYqf57BMPk/yQYjQ/BdLJVqJyXhekiTY2NyEoiiYOXAAhw4dyi02c+TYBexKBZppZq4rxWKR2hzHMSzLEtVFVVXpusKsEF3PQ6PZhM8MBNrQsa7wNWp6amqbREKXwVHYmfyn/wwzO4U3746NjUFVFMRhiJUhesREwk8ISBwjimPxPAmUqCKgrHC3TYTye8cHYvcJMirGmgLld45lPt5xHHz++eeYnpnByZMnUwciQgHAE33wRJ9PTu5zHntS5nNdfpo8Yr9KCJ1CLPqxALEBsQsF+v5yJQHLA4DByKOsJF/lST77DKffO46I9X4VymXMMklonuj3R57sfw8wi0WYpRItdaYClCLLVHMmSfB9H5JEpyWWKxUYhgGD2WS6nocmY/i57nJHoJNSQ0YkCTPT0wiCAFvMo7lbUO6ESPaSRGwCYhYgk9Tuvhssy8Ls3BzKpRJkWYbruniyvIxms9n7hVnyysupbYsNtgMzAARhuD1dNw1NGYjdzwrK0slJyMfHM8/r8uXLcF0XFy9ezHQTiMIQjWYTCQuSPbWUKQysb+WPYRUYEXyZN376/UjYDIdGvQ43leTbTFJjMceCOI4Rs5IrD4wDMfmum53kM6cFsXlMkrZrS5IEW9UqJFnG7MICDh8+jOIAY+Bz5MiRDXt0FGpGwq+rKjUDkCQ4rksdtopFIakzDAOapsF1XSrLaTbpd5o13LaBrSsyY5tnZmepTWYQUCvnAdeVzmNydjgh7RuBbigWi6JHTJJlNBsNLC8tdW2w5SCEADzJR7v8lbuP2ax51HXdbHnTeAHSAOx+ksqeuOmD/N4hoLyTgEriGJ98/DE0VcUbb7yRybz7vk8TfTCDjx7mCWlIwGBVlVRFnzP2nOjrzC/4lOQG/5yA5i+2ZdFhb+we8sZZVVUHdkjqleTz6nh6Rk/6cxLHMTY3NmAVCmIYYy4JHQz5duh7glkqgSQJfCbJ4UHHNE0x2db1PBRsGwpL+k3Lgue6kFhy5rLApmkaNNcVVo5tAYAF57GxMRiGgbW1NSwsLu4qKItEm41HbwvIvCzXmZSz6xodHYVuGLRROAiwsbkJp9XC6NjYDg0771sAdk5jTftBa8zX1/U8OJ4HhTlOtJ3z2wvAX9wGqt0XgaygrPzvs1n9u/fu4fGjR3jjjTdQKpV2/N73fbiuCwls4WDVmrhb2ZJtCPjGYEeJlf+fB7b0z+kN2f5/RzIdBIEIxAC9l9ylIx10OWMkATD7WeYRImYdpF2iFFWFaRh088M2FPx94sfmnxlJkrC1tYUEwPziIg4fPtx3YEyOHDn6w6pUKEnCyCL+p1AoIAxDxOy7a5gmFJb0R6xizKt7ruNAkmUEbIChaZqiwtwGScLMzAwIIdjc2MD4xMSuNNG8gkhYTGpLTDPWFR67FEXB1OQkDF1HtVZDHMdYWV1FsVDASKXSRrAIlzamMZdTMbdzSKVhmojjGEEYwmm16KyajutSf+84wo8eAUn3JDotDZUAqtX/naOZj/3qyhXUGw387Kc/3dnTxdhzPwjouqJpsC1re93IOB4fWsljbjfZDnfRaWP/eSWBk0jpdSWO4fk+7dFgUBSFriup8+afAz513bas3uQRobNdAiYr41CZvJQTUHxdEQQSWxv5WrOxuQndsnCA9X7lktDBkSf73yMsZskZOM62zz6T89RZF7vBJ9GBftDTSb+mabTcyKYWep4HXddh2Tasjim8sixjZnoaG2tr+2I91dbEy7506cDA/82beSRQ/ej09DRqtRqazSa8IMDS0hJGRkZQ5r0MXbSdPFnkCXECQAF1AYqZv3Or1UKpWGyf8KqrUH73OOJ/e7XrtXQGZenkJKRjO1n9ra0tXPnqKxw9dgzznTabTOcZhCEkidpaWiwgA6xE1iGtAbuHaYZCBF/eRJXRsEzYZ6UzEAM0yffZZFqR5MsyTF3fkeRzKLKMhAXlbpvAJI4RBAGCMBSTD4GOJB+phTt1bVLHJmSTVZcOLC7i4KFDA09ezpEjR2/Isgx7dBTO1hYiNjhRkWVaNTZNNB0HnudRfTqLk2pH0h+wIY++7wvZqKbrKNj2jqS/YNuoVCpYX1/H1B6H34nI1GUtEf9OT5GX6KwO07KwtbkJx/Oo57rnYWx0FLZtb0tJ0q+BFJGUQa5Yto240UDM+q6KndOAxwuQLy4g+fBh1+vplIbK7x2ClMHqP3z4EPfv3cP5Cxcw0jGXh8tB4ziGRAgMy4KVSmCVDNadr5ViHe1kwDOSf1FVlmU6lKxjrcpK8lVFEVWhTkgSnXUQJwnkOBYTbDsRRRFCRhylGfrOJD99XWDHTT+ea/QNy8IsY/TzRH845Mn+9wx7ZASqrsOt1ag2XaKDKQzDgOf7cBxHTMEVjIYso1AoCPbWCAI6gtr30XIcuK4rgrPNmmQBWnJ9+OhRu+Slx66/H8Sz2PGzSr5p5oD/tlKpwLZtbGxuIvA8bG5uotlqoVws0qFUKf17+nXazjL1WrZtU9kMKy12jleX315A3IPd7wzKyv/h5I7HBEGAjz/+GKNjYzh79mz787nXMQu6bcOy2P3lCbBEqIWbzDSQaba7bTOQ8b7wJD+reZdPX+ZlU4B+Tngw7kzy+bEk0OY0fk5tzbnMWSFgjCCHxHpINE1rY88Ek8SfjxT7AjobYataRaFUwtTMDBYXF/Mphjly7DNkWUZhbAxeowGfxUVIEgzLEpNiedUYgHBn4Ul/nCTUqYtNQg3CEH6zCddxoOs6CoUClf+xuD89PY17d++2xaS96MS5/JSTO1nWop0VTkmSMDY+Dst1sbW1hSiKsLq6SnsUSqW2eR6dsTDduJt2HbNtG/VmUzSfdlY9lf/dCSQfd2f326ShmgIlg9Wv1Wq4fPkyFg8exKGDB9t+F0URnNRE2EKnkxtn5NP9dDz5T60fWYYgnZA61mpxDXEsPgMcKid4uiTw/P5GrF9NYcNCORJWNQnDULhDAVSapGkadE1re/yOtYudJ88TWq0WarUaRsbHMTUzg4MHD+a9X7tAnuw/Bei2DVnT4G5tIY4ixKByijAMaTkxCDIHMHF/YJOVHbmEhI+r9n0ftXodtmWhVCphZnoakiRhfX0dk1NTgnXfK9qOkAowWY/jP9U0DdNTU2g0GqhWq1Qv6rowdR3lSgUm8+pNH5dXE9o0qYyNKNg26o0GwjCE57rtgbkPu58OytLJSUhHx9p+TwjBp598gjhJ8Oabb7YFnzAM0XIcyl6z89A0DcLRKC3BYUm9wmRY25e2rRntBv5edd7XtKSmLck3zbYFTlwLGBuUes2ww6EpYuXUzmFuqqZtV5rSMqBUaTWNhG1mkiRBo1ZDy3UxMT2NyakpLC4u5gE5R47vCZIkwSqXoeo6nGpVuHFZloWI+ZOL7zInJEANAhRZhsLWFS6tcBwHfhDAZY28WqpRcmZ6Grdv30a9XhdyvL2vKttxUeLnNoDu3LIsmKaJarWKer2OZrOJRrMJ27ZRKZe3YzPa4y4/fpsTnaqiYFmUQPM8KIoCLa3/HrchXVwA6cLut1WMf3YQKLWv4WEY4pNPPkGxVKJzWlIx1Q8CKgclBJKi0CZrWabvoyS13V++rvDKOLu47d/3uF9tG4XU8TjjHqRIHo31fvRK8tvY9jCkhg9M2pkl0wEjN7WUgiF9vKwetjiO6SYwilDd2kIQhphdXMTExAQWFxdzjf4ukSf7TwmqpqEwMQGvVkPgusK2ynFdIc/p3OFyNxpJkoTFoWVZghFotVoIowiNZhPNZhMWS/o3Nje32eT08QDBzO4mWKePJ3VJADsfX2ZNYrVaDa1WC34QYG1tDYZhYKRS2f7idugK25qbCYHEmpudVosGSVnetoED1e4n//kWUHXpT6RtyVAEppiJCKT/6ti29IRdwzfffIOV1VW8++67ME1TBDRe4pYkCTK7/4qi7NDT83udvj+Kogw0e0AwW6mgF8exCJzpBTBLO5k6UDtjlvpVxCYdxnGMeqPRLtNhC5yuaTt0q/wYO0rh2GZf4ijC5uYmiCRh/uBBTM/MYH5+Pvc7zpHjKUAzTZQmJuBUq4iCAJqqQtM0+GHYVjUGICqPSDmhaayCZ1kWlUo2m8JDvVqtol6rQTcMKIqC9bU1zM/Pdz2XrDVnEPBnpPu3OufCpNcZSZIwMjJC15V6HZ7rwnVduI4Du1BAuVRqS/rF+YElkjw2ETqLRtc0+EGAZquFIltr+evKv3cM4d88YOw+XVfiKEEiE8QAEAMSJMh/6yhtCGbJOkkSfPbZZ/A8D7/85S9pIs+SbsdxEIYhJAAKq9CnZUsi7nasK/wYO8w6OhJ5buXZmeRz4igKwzZXON4bl+n607HxaCPCoghxHCOKItTr9bbXUpi9uK5p2ZKi1PHbL4VWXnzXxcbWFkzTxOLCAmZmZzE9PZ2vK3tAnuw/RXC9pWoYcGs1WIYBnzkCNJpNqkfvLDlydj7FVmiahkqlglKpRMdJN5vwfZ9KXGwb3z15gq3NTZRKpTYdN/8qppO4vTA0nJHplKqkzz+JY6iqivHxcZTKZTTqdZr0+z6WV1bo1D1mQcqPCaAtIeXQdZ0GLDbUo6QoQsIEVYb8e8eQ/Nur4kqJRP/wBl1lcQzysQl+8gCAlZUV3LhxA2dOn8bUFB2wlSQJXNcVAblTn5++vl7DzmTmnpN+PMF2WZkHY4m9Jk/w49RzJNAFWc9gRsCOlWDn+8iboMMwpJ77vk+rKUnSVaaTfs2e1mmMdfFYQC6Vy5hkSf74eIbDUY4cOb43yKqK4sQEvEYDXqOBQqGAYHMTYRzDcZx22WNnjAaE+46h6zDGxlBJEuHaE4QhXNdFqVDA8vIy6vU6LMvqquNOH3M3SOv6gVTzaSczHccwDANTk5PwfB/1ahUeq1A4rRYKhULbNFeJSZnSLDmHZVmImTOc4zht67A0ZkN+ZxHJ3zyAWEGVbVZfBqC+dwRSxRTnLQG4fecOlpaWcPHiRXH/Y/Z+cOaaV+273osucpzO80/oTaGvzTZy/LfdiCNZkkQld0eSzzYMWe8jrwp4rHciDEMUi0XhAJgl00m/Zr9m4oQNE6vV6xibnMTk9DTm5+dzg4d9QJ7s/wDQbRuyrsNlidJWtYogCNBqtagneueXoUt5U2ba/kKhQJmJRgPlchmPv/sO9x88wNTUlGiwtGwbuqq2JXdtpULsMUCzIBSnWOpO5l/XNJH012o1KkliZWPLslBJsVBich9jSXiAsC1LTAl2Wi0UU4FZeWcRyX+4DoTbjLoIygRQ/077aPJWq0V9j6encYL5HsdxjFarJYJSmz6/87r7sFhCx49tdpwzLvz+8FJqpwUcZ+iy9Pii7I32942zLFEYIooiENBehCCKhFOPaZo7ZDpt58srHl2uJ2GLYqNeR7PVwtTMDCampnDw4MG8YSpHjh8QZqkE1TDQ2txEsVxGncVYiTXvZiaPwI5kWpFllEollEolOl+jXke5UsH65ia+e/KEeqAzNtg0TUoapDXY2MnGD4vOpD+NJDXVFQCNa9PT8HwftWoVPutt44235XKZJsGs0roj4ZckKhNN94UxCSIhBPLvHmPJ/jbapKG/c6Ttd2tra/j6669x8uRJzM3NAaCSHj4vRmLrdmdT66CVEVmW6eTatISUM/CM+Re9WGk5KbYrOXz4Whrp6gJ/PABhkBGl1qmW4yAmROQXWTKdtuPyXCDr+th7EQQBatUqwjDE3OIiJiYncfDgwdxDf5+Q38UfCKqqojA+DqVeR5IktBzJfI8LxWL/gUfsC8IfYeg6jPFxGIaBldVVrK6sYHp6GlEYohmGaLVaUDVNBGld06CmHBv463HZ0LAQpVhA+PbGHUGZQ9c0TE5MIPB91BoNuI5DS7GOI5LcJCXvaWOZJepYVK/XhZMCL4NKugr57UUk798TryWCsq1DOTkhfu55Hj744APhe8w9gx1mqylJdET5XgONoijCg547DAiHApaQpx9rdLwvAp06TrAG2zgWyX2Wa0MYRdQilDWydaJzse/GJnFf5jCKsLG+DsgyFg4dwhRjXvLyao4cPzxUXUdpchJKtUpZUjavBZIEi5EWO77jaVkirzayx/CEXlVVLC0vY3VlBaVikZIIQYBGswlVVWHoOm3q1HWaxKYSxraGyyHBY3HM/+4xoIsn/a7rolavi0nizVYLqqJAN4ztjQJfVxiRJLF+rGaziTAI4DKiR5IkSJNFSAdHQB5UxWvxdUU9OAqlsm07WatW8fFHH2FiYgKnX6LkUqcctMDloOL2964QZ0FRFBqTAapRJUQ0xYZDEEfATu083yzw5L7zfkugzbm6qqJcLsPK6M3a8To9knwQAtd1sbWxAcO2sTA/j7kDBzC9R/enHO3Ik/0fELIsU7ceFoRrtRr8IIDiutCZn37XpJ8n+h1Jv2maOHrkCD797DPIsoyx0VG4rguffXlD1hjEE39d00SATu/20409wwShtN5QTp1fVuVANwxMGgYC30e1VqNBkTUdF3xfSE3SxybsvhWLRTSbTURRhJbromBZ1KP4/3QW4VID5PY6ABqUiSHD+L+8Lc4hCAJ88MEHiKMIP/v5z6GqqihJSpIk/PN3m8CKBJreCBDQZibH9xEFQZteUpYkoW3cUfpM6fATbEtzog6WJQ2VvY+aqiJOEjieR/tFOgLyjpJqjySfv39Oq4XNzU0UKxVMTk9jYWEBY2NjO56XI0eOHw6yoqA4Pg5F1xGvrMBtteC0WpAlCZqqbhM8XZJ+KRW7eFwoFAo4fOgQvvnmG5w/f14MUAzDEFEYIgwCtDhZo6rQmV0vX1d2k+i3XZO0PbwvLRciGeSUZVmwLGs76WcS11qjgXBkBJO8EsHlKizh53HfYTJTLrUBIZD/4B3E/89fAxsuAJbsj1nQ/9Gbws+/2Wjggw8+QLFUwtsXLyIhBE6zSYcZAtB0Xfjn09s7fJKffiyX6Hiel0kc8fWzcx1Ly2/5efD1JIyiNgcdAGKmjKqqUDUNQRBAaTYB1uux4/z6NVrznIXlLdVaDXUu22HmDvkAxv2HRHqNscvx1BCHIVYeP0ar0UCSJCgWi9A1TSS3vZj+dEJOCEGtVsNHH30EVdfx0/feo8ePY/hBAM91BRMcp4IcD8r8j6woUBVFvPagjb188m7UETDScpasAA0Anu9jc30d9UZDlJ4LhQLtPeBJf4qNicJQTBzUdB2FVOBJntTR/OhbfLbxLY787uuYm5uDoiiIoggf/M3foNlo4KfvvQeDDe0SFRImdRm2utHJkHO5S5SyIeNafBmUgdNZOXX7IO1NtkmS0KmTbCJkFssiy3Lbopo+73q9jq1qFYqqYnRkREwm7KWbpKfRrgn12WbM931Mzc6K8mou28mR48eN0Pex9OABfM8DIQQlNqEUQPekPwNJkmBzcxN//f77WFhYwCuvvAKANX36PlzPa1tXZDapW2PSUf63oihQ2LoCYFvW2Occ4iShw8S6rCsAug6gchwHa2trcBwHKqtAlJjTkKIo2/aWbF3hrncAq2yw6cQgBLVL93D3Ly9h9L2TKJ6YRblchizLcBwH77//PhRFwU9/+lMkhNANAzuHtBx0aAItRegJsoet53EUUeksehNH6QQ/jmOxtkRRhLhjowDQzYLKKgKKoojzTZIEtVoNW/U6DE3D+NgYZEUZ7H3sICZbjoNarQZCCKYPHMDk5CQWFxdz2c73hPyu/kigaBpmDh7E6sOH1Maw1YLMAjNJEiTonvR3uuRouo7Dhw/jy6++QrVaxcjICHXzsSyqeY8i+GGIgE3y5T7DBBABmg8A46VHhSX/iixDVtVM1xf++jtba7cfJ84/tTnhMA0D0zMzUFVVJPEtx0Gz1YJpGLALBZrQs/PijHWr1ULo+3ABkYDKc2UEP1/Exq+/xRF2DXEc4+OPP0a9VsNP3nkHsqLQicWgTW62ZQ0VaNKVlXQQjvlGqgO6qgpto6igsGPESYIoCOix2HEy7U3Z5oz/yXRQAEQjcxzHVFfL2LWuukm0M/kATfLr9TqtBKkqFg4exMzcHObm5nLZTo4czwA0w8DcoUN4cv8+PNdFq9VCsVSig/Y4+TBA0i/LMnRdx/yBA3hw/z5eOn1akBWqqsJmE3zDMKQT4hlT7DAiRUuRSJzNVhSFbgBkGaqiQGJJYxYkAFFGTE0/XhgfAG3ssm3bmJ2ZwcbmJlzPQ5IkqNfrqNfrMC0LxUIBpmFAYtIYg9lCe54nJtobuk5j45FR3DlC8PosHe4os83BBx98AAC4+Pbb8NmwM4m5/ViWJWQ3gzD5betKak2JoqityZavpTpzvuFrF0+605sDntzHvdaVFGnULb6HTL6lSHRqLn9cr3Wlk8l3HAf1eh1+GMI0TcwcOID5+XlhkJHj+0Ge7P+IIMsyZg4dAnn4EM1qFY1mE+VSie6sAZH0K5JEE94ux9E1DZNTU7AsCzdv3sRbb73V9ntFVWGz5JYn/mEQiMAQRhESttvnwZgPzhDNsCzxVxQFMnuMCBADlPHa/9te1tR0HWOGAcMwaFDwfVqVCAJUq1WqPy8WoTMbSrtQoD7RvPRqWVQjz1ggPuDqs88/x/r6Ot544w0omkZ/z0q1hmEMxLYI/XocU+uxjCAM0ECs8KRcUYQMJyHUEjRkLBXpEYAB+pngbBhP7vudJ2Gsks+8tk0+yKzPNYkkPwhQr9UoG8jYopfOnsXcgQM5m58jxzMGVddx4OhRPL57F77joNlsolQqieSYJ/0SI1G6RQrDMHDw0CE8ePQId7/9FqdOnWr7PdeF27ZNE382kTtmyaofhiAeHXzI1wzO8ot1hcU4lf1OUhTI0nbz6SBIyyi5UxzYzJpCoQBZUdCo1xEyVxnPdaEoCqxCAUXbhsbYf8Kmlbss4e+ca6KqKoIwxAcffIAgCHDx7bepZIcl9DabSCzOq1cMZucapdaULMKHb5J4pYSTSglzKEqShJJNbF3pBkHgsQpMlitbJ3i1wg8CqLpO/fUHYfJTSX6D9USQJEGhWMSZc+cwwwi+HN8v8jv8I8TMwgKWJQmNzU00m03BxADYHj7C7LuE9CP1peP2V4cPH8b169cpm8Psv3aU61jiD+bfz6ep8gSUN9qGUYTE90UzE0/204FakmUokoSQlXElUGcHHrCz0FmVkGVZ6CgN08S0ZVGrTdZoFscxZfuZPrRg2ygUizBNEx5z9wFjYgRzpSi4dPkylr77DudefZVahTHWRbjT9AHXR3Zj3XkQFjIoSRJDXGLGEmXpIdveCxaAFVmGkqqu9AMBRH8EbwR2XBdBEMC27Ww3ISk1yCad5Nfr8NniBgATk5N49bXXcg1ljhzPMBRFwYHDh7H04AFcNpelWCohHV04mSRJkojX6fjMLYgPzM3h22+/xYnjx0VlsXNdEYk/IBJ/noxysiQmdBBTusLQKfMhhIiknyfSMltP0mtPN/C1UWGPJYSgWCigWCgg8H00Wy1hh9lsNNCo12GwKnLRtoWjmeM4kDomt0sAPvzoIziOgwsXLtDqKSFis9Ct6rp9w4mQZ3aT06QrueIasK2zd30fcYY5Q/ocFVZR4RUUeQDCKP18jigM4XgeEkJgMzvoHY9PbSC5JNV1XToQMwjEpm3h0CG8cuFCnuQ/ReR3+kcISZIwfeAACIAWT/iLxW1PeQbeyZ4l8bFtGwdmZ3Hn229x89YtvHb+PD02fy5/rdS/eVDhx45T5cM4jgV7LUqCUYSA6wWxzRaEcbzDJ5+zHZIsQwYNQBJ7jixJ2wwOZ3FY4iox/2dd01Aul+GzAO2y3oNarYZarQbTsqCyUqnnupBlWTg3PLh/H0+ePMHpM2cwMT4OMNbF6AhWfIND2AaH9x90BmG+YHGWPR3UwyCAHwQ7WCg/CNruRXpRGzYAp48jGrXpmwZg2/2Bl5DbNgy8ryDVNM2TfM91xXtgWhYOHjmCE6dODX1eOXLk+PFBVVXMHjyIJw8fwms00GLrCtAuswSvQKJ9XeENq4cOHcLjR49w78EDHDtyRDxP9GVJEiSybbvME396aCLWkyhFKnFiKUkShCkTA0WSELPYGDADhTTSawonodIbAi616SSVANAp5IaBkdFR6s/fbMLzfQS+L2wgLWb8IMkyWq0WNUWQqNvcF198gWq1ivOMQJJlGbZt70hgBXHG1tCYrY+d/QfpTY/MroFvUHzGhiN1nwG63qSvi68lSurPoCCEdCXlALqu+L4PTVXb5s7w95znI/xcRJLPKu4SgEKxiFNnzuDAwsLA55Vjf5An+z9SyLKM6bk5rEgSnK0tNOp12IXCjlIiACHxEQk8Y4RN28ahxUXc/vZbvHz6dBvDm/WVTif+aUaBP0s09XBdeorhFo25UST6ANqOzZkYdn5SZ+Dmi4uiwHVdkUxzfbso88oyKuUySqUSnGYTTcehjjxM4x/HMRRVhce0o5Ik4cnSEo6dOCEGPqmKgpA1Kyc8CLNpu7zRKK37JKkAltaZ8gEmWeVSvpFp2+SkpE+7Rdv7llHWjtlAnDiK6GwF3lzGH59uvA0CNBoNeI4j2DzTslCpVLB46BBme0zLzJEjx7MHVVUxMz+PpceP4TcaqNdqsJnne2cPVtu6wuKYpmkoFYuYmZnB7Vu3cOTIEVEdEBuGjKpnOoamk38AwtCBJ/9xymUsTbhEYbhTLplaV8Dkphw8hvME1mFxjltQptcVXdOgj45SO+dmkyb23CCBrRGapolzu33nDpqNBl4+e5YOzWLVA9d1RTMx/7vnusKSYL7W8um+fHBYVk+cwjYDCQAzoxoyLNKyp24IowgtxwEhRMxW4PkCvyZ+BM/zUKvXEXElgETtsisjIzhy/DjGJia6vk6O7w95sv8jhqIomJ6dxbqqorG+jmazCdM0BdvQDTxAG4aB+fl5fHv3Lm7euoVzZ89mPn5HgE//nQrUXFayI1CnG1PjmLL7qYDNHXh4Qp2E4faQDbQn05JE/e75WHElVWlI/80TV0PXocoyHNeF7/tUchSGCKIIa2trIADGRkdhmibV9fdItPlGhCfyiqKIIC4zqzb+uM5SMk/s+XPTDEmMdgZmEKSrG/weDsKvO44Dz/chqSoKhYJg/zm4I5PnefScUkx+pVKBYRhYOHQI45OTQ51vjhw5ng3ouo65hQWsLy+jWa2i2WzCMk0YrB8nM9aQbQte0zRx8OBBLH3yCR49eoSDXVjadMWxjUhK/Rtgzb9sqjeHqCqnGkxlWW5r0uXVAN4LlYQhwtQ6QQgRCbAsywiCAJIkodVqCQksZ6M7ZZmWacJjLkN8+mzA7EUJqNPZ/MICrb67LhTfb7tX6eSZEyl8reBrGiey+P3mGxfO7Iu1KPXzNutNJq8dFDve0/TaQLKdjDgazSYC36eyX9tuc95JkgQB623wPA9JFAGyDLAkv1wuwzBNHD5+HKV8Eu4PhjzZ/5FDURRMTU/DME1sra7Cd11EUYRCobDNYnQkdBwSgGKxiIWFBdy+cwdzBw5gYgBf9M6Sbqf0h74k/Sl3aUgLYiLm7iMCMUvyServzuCa3hBIsoyI2YpJHQlv2vcd7PwSUGsz07LgOg6V92xuwmk2qbe0rtPziWPopgmTjQmXONPO+goUzhClpER8AyKCdUciPwg6JU3pe9ztvePXtuPx3V4DdENRZY1nRWZXmm4y8zyPMlPSdhMen1ys6zrschkHjxzJm3Bz5HjOoWkapg8cgG5ZqK2tUVlkFMFmBEE6MU9DAl2TxsbHMT4+jitffonJyUk6obfPa3aSShydr0VAq6+Kooh1hRA60C8IArqucOIotcakq9vpYyesAi1JEu29iiKoKfImc11JEiiKgmKhgNiy4LZaCDwP9WoViGMUmGwnYMktN3ngvva8/0Dm1YaU5AWpNaVbIj8IulWU238w2PrSC47rotFoICIEY4UCFEVBkiRwXRcuk4yS9ABNiTr1VJgL4OjYGBYOH871+T8wcp/9Zwi+72N9dRVurYYkjjN15xxpdqbRbOKDDz5AFMf4xS9+AYNP0ksHoD1CfIhYIumFIZ3sB+xgOvjP0mXOdPDmianBGsLQea4Z5x3HMYIgQBgEuH37NjY2NlCuVFAsFmGYJgxdh6brIvipbPCLYZqwdR1qamIvBy8ZiyoHoa4O6Z/x56QZms574qfvxfcAAnr9q6urCIKADtUpFuH5/s5ADFrxsSwLNpvkKCkK5g4cwNTs7Pd2jjly5PhxwnEcrK+swG80IAFC1sPRVulN/Wx9fR0f/Pa3GBkbw8WLF9sc2faryye9EUhAm2W3f7lzXUkn/ul1hctzwjCEZdswmJNMuoKdJWeJ2AbD8zzcuH4dDcfBSKmE0fFxyIoiEnz+2qqm0Um+hgGTWW7yc22T8KTOv3NNS7PmOyrtqev0fF9ISfcLne9xEARYXV1FmNrQeL4P3/NoryDbJEnM7ci2LJimSR2DdB3zBw9iJB+8+KNAnuw/Y4jjGJubm2htbSFwXcrI2nZvWQ+ApaUlfPjhh5ibm8Nrr70mWAQC5k8sbQ902g9EhCAKw1091/d9uI5DB2V1OCAAEI27AMQEwYhpOq9evYp6o4HTL72EyakpKIoC3/cRhKFg2MW/WaAkLPk3UkFa3YOuPg1e/t0PpGVV6eEkALCyvo5qtYrA92GyplwZ2BGIbdveZpAIQalSwcLhw6KEnyNHjhcPYRhiY2MDTrWK0PNopbQPW58Qgm+//RaXLl/GmdOncfz48R2NsL2sPHeDiMlGdwPXdeF7Hkx2bVng8ZWvK3Ecw3VdfPXll4iTBGfPnkW5XBbris906YTJRzulqbqm0WoyW1v20q+VBper7htScl2+eUgIwZOlJTRaLcRhKJpy+cZD4euKbbcPoiQEo5OTmD94MGfzf0TI34lnDIqiYGJiAqZpYmtjA36ziXq9jiIrr3XD7MwMTp44ga+/+Qbj4+M4dOjQ9heX6xbZY6WUh/9uA7UiSUhSg1uGei67jrbndjAdIWNbuFe+67q4euUKojjGT959FxrTQxYKBWiahpbjAKDlYYvZeXJ3gcD3kcQxdWRwHJDNTajMvlRlDbl82MgwjVDc0Wi34Ml9mhUK2aaGD62JogjVWg2NZhNxHKNUKkFhvQN8bHzWRGBZljG3sIDJmZldn1+OHDmeD2iahunpadRME7XNTfjNpmjy73SB45AlCUcOH8ba2hq++eYbjI6OYmJiYptISmnh0/IV8f9dgGvbd8NR8rjdua6IGEu255Pwx1SrVVy9dg22ZeHt11+nx1EUFGy7TXqj6zoM06RrCltXQh6nWy00m036OE2DyoaRadyqma0zg2Jf1hVsy5ckYPtcw1BMfa9ubcFptUAAlMtlSAA0RYFp23RdybB01ljPV2VkZNfnl+P7Qc7sP8MIggAbGxvwmk1ErguN+cZ3C85xHOP93/4WW1tbuPj22xgdHRWPzWrK4qywJFErtWFkP1xaEiXJ0GVGQghqtRokScJIKmh0Mi6cOWo2m7h0+TJs08Q777wDRVXhOo7w0QdoMGuxwCWzTQBvlOIj330me0kzNOnr4WVXvgEQG4EuQTvmg7MG3PDw5J57Lgds/Hz6T+fX1fM8NFOJ/vj4OGzLoi48XVBibjt6zubnyJGjA47jYJMl/CQIoBsGdF3vuq44rovf/OY3IADeeustlIpFmpBLEqQk2Sm1ATJ9/AdZVxJQDf7Q64okIQwCtFotqKpKG0W5pIb1NfEkn+voV1ZWcO3aNUxPTeHNt94S02P5/ZAkOj03TSQVCgVRdY740C6W/MdRBNLRg0b/wdYVtqa0/c0Jp5QcKCYkcy3IQjqx5/0KYRC0ryu8p0GcDoHTasFhzkLjY2OoVCqwbbvNnKMT41NTmFtYyNn8HynyZP8ZR5IkqFaraDUaCFwXke9DV1UYptmmu+RotVr41a9+hUKxiLNnz6JYLO74chJees1wghFevB3BOitQc5974SfMNYrp4J9iadKvUa1WAQAjlQoSluTz5iyALha6YWB5eRlffvklpiYn8eZbb0HTNDQaDcRRROU4qWtLkoQmxuwYO66dnUccx/B8n7IcqTkDcRy36S6TjnPm9yPtIJSV7AtNJvtb+BOzcjDfyIhbxJ/H/uZeyumNT7lcxmQPBx1CCAqlEmbm5lAZHe36uBw5cuSIoghbW1twWy2EjoM4DKH3GBa1uraG3/72tzgwP4/jx47RBtYUw5+WjUpZMR/buvleGwCetALY4VMP0Kq0SFw7mlPjOEa9XoeiKCiVSkL66QfBdmyVZRimiVu3buHWrVs4evQoXjl3DpBl1Gs1kCSBnbo2gNlSNpuZRBK7AeJ8Pc8T7DkndXiTMSfX0ilZmxMemyPDmf0dJhf8/6lKBb+v6QZmLtdtM9wAdQeSZZk6tnkeCCEYGxtrI9w6QQBURkcxc+BAtuQ2x48GebL/nCAIAjSbTZr0Ow5iZpOV9sTleML0+0ePHcPc7CyKxWLPHXsa3T4sPEinAzUPYgBEgj0otjY34QcBbUBO9RTITCeoaRquf/01bjKv51dfeUUwKtVqlerRy+X2wAkAhKDJh6MAbZZz7ReafaVi4iHfCKSCthiewoKs2OhkBOVOWU1nZUVmY8w1xu5oqgqNlX8TQtBiE4X9IIBpGBgdHc2WF7HFZ+bAAZTz0mqOHDkGBJe1NJtNuM0mfDa/oxuZ9M2NG7j29dd49ZVXMDI62ldamvaZz4q2hBAoGcSScODB9qTWga4nSbCxuUmbdC1r+/UJoWulYUCSZXz++edYWlrCuXPncPToUZoss42CJMtiAnsafYmk7YvKvM5Opj2O2u2sAUaeISXjSUlvMyvz7G9B3Elsyrui0DWFrSvc4z+OYzFROAxD2LaNyshI9v2VJFRGRjCdJ/nPDPJk/zkDHzBVr9UQtFqIfB+KLMMwDOiGIRiJL7/8Et/evYvzFy6gYNu0ackwhrb/6gWh2eRNpZxZSOnQ0/pOnkSHUUTZ+TiGZVnQdZ2652gatdF0XVy6fBkrKyttARlgcp1mE7Iso1QuZ2obCQDXccSkWz4GXupSpiastJv5u9S/eTNuyI4bJzstRjvR+Zoyqwx0K5mHYYiW4whfY0PXUa5UMjdrhWIR0zmTnyNHjj0iYBKYBltXYmZfaXBJC2j8++CDD1Dd2sJrr78Olc360Ls4xu0WSaoSCtAkWAzyYmtN57oSMOlKvV4HCBGOQxrT0Ou6jlq1is8//xzNVgtvvvkmZlPuZGnTCMuyMnvRSJpIInT4lGmaO2RMYnPTZW1IrxmSJCFOEvi+T4mjJOkrYcpax2Rpe5hYFnzfF7NqgiCAYZqosEbktnOTJFQqFcrks+nLOZ4N5Mn+c4okSUTS7zUaiIIACpO+cMbh/fffR61Ww5kzZ6h+X1GEHeN+Ic3o87KiGPvNAzFjydNJte/7QJKgWCqhWCqJx9+7dw/Xvv4amqLgwmuvYSbdYCpJNIn3PJrA2/aOZD/NgHieB9fzxO8sZi22A4x9SgAg5eXcydDHHSy+kP3sAwgh1E2CBWOfBWTTMGDbdttj7UIB03NzueVZjhw59hWcTKptbSFotZBEkZBUaqqKIAzx61//GkmS4Ny5c7AsCwpL+oedT9IL3JgBgFhT0tPc4yhCwKa5C2tktj4oLGG1WNyM4xg3vvkGt27fRqVcxutvvIFKpUKPzZ7bbDYRMbZb1bQdyX5aG58mkmRZps/hLH+HtAgp4ittlJHerCSp5D4tY9qX+5gkcNhsGpfNxuEOf+m1UJIklCsVzMzPw86Z/GcSebL/nIMnibVqFU6thogFIY6vr13DysoKjp04gQNzc0gIoTZhGQ4uu3197nccJwltrmLSlzAMtxNmFhhVXYfGSooeS9oLhQJqtRouX7qEza0tHDl8GGdefnmbzU7p3xu1GpIkocyNpmXLh1LXH8UxXFa2JKCuFHbaHzkDwsmA/Z+PU+/02N+voByGIRzXRRLHcJmWUuN+zsxKUwJgcyY/l+vkyJHje0TCksTq5iZ81iPF+7mCMMTly5fhOA5Onz6NsbExJITAtqxsMmU3r8+qxgnrcepcV4DthFlWFOiqCk3XBVnCJ9GvrKzg8uXL8DwPL506hRMnTmwz4ym3umqtBolQq2Kugd8BQmi/GyEIwhBOqyXOk8826bnhYetYkurf2tHvhf1ZVwirQjuuCz6tXmUzVwq2Tas1bIhkqVzGzNxczuQ/48iT/RcInueh1WrBqdfhNZtC+3j79m08fvgQM3NzWFhYgCxJUDUNpVJphy6z1wZAjC1nzaw8EAtfe66/5CwFm5arMf0gHx8O0AS32WyCEIInT57g1q1bKJdKOP/aaxjvwljHcYxGvQ5IEkYqFUCSBgqMhBA6ZZa5KgB0JLzRw2daJPqpKoVgZYCBJDyDnJfjugh8HwT0/VMVBZIswy4UYOo6FE3D6Pg4xiYn6QCyHDly5HhK4GRSq9mE02jAb7WEycC1a9ewvraGI0ePYmpqCpAkGIy86dSzD72uMOY+bW7AH0vAJrszeU6auPF9H47jICEEd+7cwXePHmFyagoXLlzoOtPFD0O4rRZt7C2XBXm146Fo180TQoQbD4c1wIaHIGUPytdK3vu2D9XiOEngMLlRwpyINE0DAVAqleh9MwyMTUxgdGJi32VYOX4Y5Mn+C4okSdBqNNCq1+E0Grh37x5u3biB0bExHD58WDAIWQFTBOaOxql0KTWd1PPgyB0FuFc9960Ha4DqbO69d+8ebty4gSAMcfrUKRw/caJrEyq4zMXzoBkGCqkSbSZSCwRHnCRwHQcBY4YURYHd4ejTmeRnH5rKk9IOFOI1B0BCCPVqDoLtycJxDFVVESUJtdicmMDo+DjKIyMD+/7nyJEjx/eJOI7RqtfRrNXgNBr45vp1PHz8GAfm5jA7OysSd55QppnugdaV9GsxAkmRJLqusPVFVRTIqkpZ8o5+qzAMcev2bdy5cweKLOPcuXNYWFjoudngEh4+jKtbsg9kmy9EbIZLHEUgoK43WdXjtiS/y7Hj1Cagl+4/C1z777PNR8zXZUWBBOqlPzYxgbHJSSGdzfH8IE/2c9DdvePg5vXr+OTDD2EXCjh16hQS7i6TJNB0Hbqm9dfzs45/PjpdYaVBYYXWC4ylaTkOrl27hsePHmF0dBSvnj+P0W5NpqlNRa1eB4lj2KmmsN2UPIMwpMO1mD5f13UYug5FVQcaEpZwneWOy9uWLIl7kXZUYME4CAJR/k0/RjcMLB48iMmZGWg525IjR44fMZIkgdNo4NKnn+La1auYmpzEoUOHhENZt6Q/E6l1ReG+89z9bcB1pVqt4suvvsLGxgamZ2bw2oUL3SfpAkJHX6vVqLtbpQJFlnsm+91PYbt6zCsAhmlC17Qddpvd0Lda3LGupI0xPD7tF9tVAl5tLxSLWDh0CGMTE7lH/nOMPNnP0YbHjx7hP/7Zn0FTFJw4dgwzMzNI4hgJaJDQmJ2nwjx/gXaLL1mWM4NvkmpszUSSYHl5Gffu3cPy8jJUTcPJkyfpkCg2jrsXYubgk5bwAH2S/c5mqfTpEALPdeH6vgiYiqJANwwYLEB3w7ADX3iS7/v+dpLPgrUsyyiUSnT8+Pz8vjZP58iRI8fTwNfXruEv/vN/xli5jGNHj2J8fFxYFRNCxARaubMaCuok0y3e9rN0jqMI3z1+jHv37mF9cxMF28apU6dQKpWoTLWP5bQfBG0SHgC7SvY5ojiG57rwwpCaPbA1VTeMnm45BGirFg+ChM2LEUl+asCZoqoolkqYnJnB9MxMXh1+AZAn+zl2oF6v49e//jW+uXoVBdvGsUOHqJZfloXzga7rwhKzL7MCUCvKjI+a6zh4cP8+7t2/D9d1MVKp4PCRI1iYn0fEZDWarqPI9JS8LNtZLnUcB4Hvt0l4gAGY/RQDkm68TWskPc+j0p7U+Wu6DsMwdow5H6aBKonjdiY/ScT1qZqG8ugoyqOjKJVKqFQqeUDOkSPHM4ulpSX8+le/wsP792nSf+QIpmdmRDwnhFD/fta/NQi4LKgTjVoNd+/dw8OHDxGGIaampnD48GHMzszA9TzapGsYsGy7J1vOJTxWyp1moGSfrSsJSU2mZc+VQOVEvu9Tm2ZZFk50hq5Dzxhc1ibh6QMxET4I6HNTFQHDNFEZG0NpZERsePbTbjvHjxd5sp+jKxqNBj755BNc/uILqAAOLy5iYWGB+gwz9lmWZZH4y31YZ5Ikwr5SsPgrK1AUBQvz8zh0+HCbXCdibL0ky5St7zgWL+OSJEGt0UASxygWCm0SFz48q1NG1OaPn5os2Ovc/SBA4PsimSeAYPs1VYUky0hSlnDdjhOyqY1hGLaNMpeYhd0I0+IXCoXuw1ly5MiR4xnE2toaPvzwQ9z4+mvYhoEjhw5h/sABQRyJKipbV3pVUfkmgaCdxd/Y3IRhGDh06BAOHTrU1nzLm3Q1TUOROcykq9Qyq/jGSUKn5gKoMBceiSXw6QQ6vbZwEoowcqtfGp3EMfwwROD7bWYPnO3nphVRR09b1nH4BiKJYxB2H2M2dMwqFDA6MYFSpQLbtumU37xK/EIhT/Zz9IXv+7h06RI++fhjRK6LA7OzKBWLME0TumHAtizohiH0l7qmCYmM4zhoNJtoNBpoNBqo12qo1evwfb+NxVczyqmEEKrDTxKUisW2x6Q/tn4QwGm1IMsyyuXy9qRF1tiaxm/++q9x4sQJzKUGppCO4/VDGIYIgmCb7WeLTcICfbpfgTeOhWFIS6qeJzT9SRxDYg1lhWJRBONCobDv8w5y5MiR48eETjJpfm5O2HPyZliDJfwGnw/DkthWq4VGs4lmo4E6X1dqNYRRhOmpKRxiLH4WARXzabiShHKpJB7TuQY4jgPf99s2BQBrbE2tK1lrCrDdcDsIc85NHdJsPxg5ljBzC5UZW8iyDEVVRYXAY2YOIHRie5IkUNj09VKlgpGxMRRKJRSLRdjMqjnHi4c82c8xMOI4xtdff42vLl/G1tYWms0mZIAmt5IE27JgmyZUTYPnusLDF6BsSbFYRKFYRKFQwNzcXPem2xRarRaCIBB++0B7UCaEoM5YfcuycP/+ffyn//SfcO/+faytr+P/+gd/gNdee008/l//T/8TDF3H3//7f7/tdYZN+IFttj8MAjraPGWLlp4IHDEXBh6kNXYtdrEIwzCgGQYMw8iDcY4cOV44+L6Py5cv4/rXX6NWrcJzXTpJnPUs2ZYFy7KgShIcz4PruuK5qqrSdcW2USyVsLCwkG2h2YFGo4EoimDZNkzD2BH7kyRBvV6n1s9LS/j//uf/jHv376NareKf/bN/htcuXBCP7bamcMQDJvziteNYrCtxHLfJd/j/+ZojAZBVFbIsw7AsFGwbVqFAN0ds2m+REXP5uvJiI9cH5BgYiqLg3LlzOHfuHIBthmRrawubm5tYW1vD5uYmvFYLxbExzFoWLNNEoVhEmfn3CnZmwMTaMAwEQYCQTdjtlMiEYYg//dM/xT/+R/8IhmHA930sLi7iZz/7Gf7ov//vdxzvtQsX8D//L//LjsDMS7HDJPySLIuR6GEYij+e5yEMQ6i6Tq072TRf0zRF4FUURViP8n/nyJEjx4sGwzBw8eJFXLx4EQCN6bVaDVtbW9jY2MDa2hqq1Sp8z8Po5CQWLAuWYaBUKqFQLFKXOFUdKnZrui607WaG7/0f/dEf4Z/8k39C7Y7DUKwp/6//4X/Y8dhuawqHLMsDM/wAHQJmsbUzjCJaRWZT0yO2rhRHRihJZJpClsPXlc61JUcOIE/2c+wBiqJgdHQUo6OjOHLkiPg51w7yP4HnIfA8OJ6HqNGApqpU3qKqdEgUt1DDzuEqKtfCJwmCMGwb8EEIgcs8gw3DgCRJeOWVV/DKK690PeczL7+MWrWKR48fY2F+vu13POFP+mktWVNYFMeIwhBBGCIOQ8iqCtO2UZmYgMmSe9M0t3sa8gbbHDly5OgJTdMwMTGBiYkJHD9+HACN9Xxd8TyPyl18H4HrouU4iKJIrCsqW1tkRRGmCp3riqFp8EB7uqI4hpKKzVwGAwCmYexpTQG2Xeq6Jvwpy0wxCTiOEfo+wiiipFGphPFCQawrBnPvydeVHIMiT/Zz7Dv4RNxisUiT9CDYTv49D6Hv0ySZNUrxhizxh7ESPDDqmiYmEXKrNEmS4Lgu1eQz67aBzk1VcfbsWVy6dAnz8/PbTglszDkAyPQFxIRhkiRCpsP/JEkCzTCoa06xSIMw05vyPzmrkiNHjhx7hyRJgjQplUp0NgxbUzzPQ8CS/4gx4EGrRV3NOtYVWZaFKYKsKIijCG6rhWKpRCWYrB+AEAJZUQaaZ5JeU3iyzw0f+LoicftQSQLiWPSTRXH7VGACWnXQDANWsUhdgDrWlTy5z7Eb5Ml+ju8VckrqAjBbMOZEE4YhfNdFfWsLURAg5km16wKMXZdYwuy6LiRJQhCGKBaLCNkGAqCaT25NxgO5xKbyct/69BTbCxcu4L/85V/i93//98XQMP6HEELddtjxuENCejCYquuojI+jVC6LjY2u6z19knPkyJEjx/5AlmUqdbEsANumCUJK6ThobG4iZgl1EIY0lqfWFZIk8FwXviQhjGPYlgXX8xCFIQghsExTuKRxJCwx59Vfvq5cOH8e/+VXv8Lv//7v08clyfb089S6kv4bkrQ9Q0CSoFsWxqamYNn2jnUlR469Ik/2czxVqKrapk8nhGB6drZN8x6yptYkjhFHEZIogmZZqFerdMjJ2poIoIZhQNN11Gq19kRbklAplxEGAXX0SU2kPXT4MDY3N/FkaQnFwv+/vbvXaSONwgB8hh8lYNnSSqtYeBNFq2yBkpYLgBuAS+CaaKno07lAovNNYDcrkfVujCOhLWITYWIzW9gzNkvK1YI/nkeazsVU33nnzPGZSjlStLq6Guuz+c/iWpt9NXhtba08gItLsAd4fMWZXMjzPMaNxoO6MplM4m48jvF4HJPJJFa/fYvh169xPdsaV2zZWcmy6drnhRHTyLKo1Wox/v49BoPBfO1nnsev797F3x8/Rq/Xi0qlMt2aU8zNFzVkfX1aa2b/XSuuxZpSrNqE/5qwz6PKsqw89IouTUSUnfbF0Znr6+vperWi87KxEZubm9H98iVevXkz3f0/66bkd3fxqdeLlZcv4+etrbKLEisr0el04o9+P357/z7WZq92740R/evy2hRgeWRZ9uABICIe1JRiycRgMCi/n1KpVOJTvx/1t2/nTaJZXfm924148SJ+qtfLerKyWFM+fChHUH9UR9QVHouwz5NU7BNefAtQrVajXq9HxPwPV3mex3A4jK1G416nJc/z+KvXi41KJRqvX5cdmizL4vj4OHZ2dqYz+7ooAM9CUVcWHwJqtdr8A1mzejAcDqPxg5ry5+fPsVmpxC9qCkvGoyVL5d5r1ZgfzsWozWg0ina7HZ1OJ0ajUXS73Wi323F5eVmuI2s2m3FwcOBQBuBBXYmIshN/c3MT5+fn0W634/b2NrrdbnQ6nej3++XojZrCU+ejWiy93d3daLVaERHRarVib2/vwW8ODw/j5OQkLi4uYnt7O66urqJarf7PdwrAU6emkBphn2fl6OgoTk9P4+zs7LFvBYAlp6awDIzx8Kw0m83Y399/7NsAIAFqCstAZx8AABKlsw8AAIkS9gEAIFHCPgAAJErYBwCARAn7AACQKGEfAAASJewDAECihH0AAEiUsA8AAIkS9gEAIFHCPgAAJErYBwCARAn7AACQKGEfAAASJewDAECihH0AAEiUsA8AAIkS9gEAIFHCPgAAJErYBwCARAn7AACQKGEfAAASJewDAECihH0AAEiUsA8AAIkS9gEAIFHCPgAAJErYBwCARAn7AACQKGEfAAASJewDAECihH0AAEiUsA8AAIkS9gEAIFHCPgAAJErYBwCARAn7AACQKGEfAAASJewDAECi/gHkeEYo7LDkDAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Code explanation:"
      ],
      "metadata": {
        "id": "UgrlKAQCG_e6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The Bloch sphere is a 3D sphere representing a single qubit's quantum state. The poles denote the classical states **|0⟩ and |1⟩**, while points inside represent superpositions. Rotations on the sphere correspond to quantum gate operations, illustrating how the qubit's state evolves during computations.\n",
        "\n",
        "This code simulates the quantum circuit using the **statevector simulator** in **Qiskit**, obtaining the resulting **statevector**.\n",
        "\n",
        "It then visualizes the state using a **Bloch sphere** representation, which provides insight into the state's quantum properties."
      ],
      "metadata": {
        "id": "V8Ka906LG8gH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Plotting a Density Matrix"
      ],
      "metadata": {
        "id": "4Vy8cRA8HPlA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit import Aer, execute\n",
        "from qiskit.visualization import plot_state_city\n",
        "\n",
        "# Simulate the circuit\n",
        "backend = Aer.get_backend('statevector_simulator')\n",
        "result = execute(qc, backend).result()\n",
        "statevector = result.get_statevector(qc)\n",
        "\n",
        "# Obtain the density matrix\n",
        "#density_matrix = result.get_density_matrix()\n",
        "\n",
        "# Plot the density matrix\n",
        "plot_state_city(statevector)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 442
        },
        "id": "GnSTDnsKDygU",
        "outputId": "8e531359-556a-408e-be38-56d425afcbc5"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 1500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Code explanation:"
      ],
      "metadata": {
        "id": "IXMFhivzdT8k"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "This code simulates the quantum circuit using the **statevecto**r simulator in Qiskit.\n",
        "\n",
        "\n",
        "Then, instead of directly converting the statevector to a density matrix, it obtains the density matrix from the simulation result.\n",
        "\n",
        "Finally, it visualizes the density matrix using a city plot, representing the complex amplitudes of the quantum states."
      ],
      "metadata": {
        "id": "0Lwiw3sqdYL0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---"
      ],
      "metadata": {
        "id": "bZh62XfMJtdG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# How to Programming Quantum Cat Swarm Optimization Algorithm"
      ],
      "metadata": {
        "id": "r3mTLOjITBGa"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "PVWU52GVGOb4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Steps of the algorithm\n"
      ],
      "metadata": {
        "id": "hoQlYxPFTaHF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Define the problem\n",
        "2. Initialize the cat swarm\n",
        "3. Update the cat positions\n",
        "4. Evaluate the objective function for each cat\n",
        "5. Update the global best position\n",
        "6. Repeat steps 3-5 until a termination criterion is met"
      ],
      "metadata": {
        "id": "ynn2rGwBTfKK"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7ma1NZ2lR-7o",
        "outputId": "700590b7-b1bf-4abb-aaa6-d98fc5a90b70"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cat 0: Position: [4.45603283e-171 1.01729661e-172], Fitness: 0.0\n",
            "Cat 1: Position: [3.27653639e-171 6.15878008e-171], Fitness: 0.0\n",
            "Cat 2: Position: [6.63932245e-171 1.82160956e-171], Fitness: 0.0\n",
            "Cat 3: Position: [1.08033876e-170 5.75400370e-171], Fitness: 0.0\n",
            "Cat 4: Position: [2.26455145e-171 4.24351313e-171], Fitness: 0.0\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "\n",
        "# Function to omptimize -\n",
        "def fitness_function(x):\n",
        "  return sum([i**2 for i in x])\n",
        "\n",
        "# Defines parameters\n",
        "n_iterations = 100\n",
        "n_cats = 5\n",
        "n_dimensions = 2\n",
        "h_bar = 1.0545718e-34\n",
        "\n",
        "# Intilizie the position of the cats\n",
        "cats = np.random.random((n_cats, n_dimensions))\n",
        "\n",
        "# Initialize the best known positions and fitness values\n",
        "best_positions = cats.copy()\n",
        "best_fitness = np.array([fitness_function(c) for c in cats])\n",
        "\n",
        "# Main optimization loop\n",
        "for _ in range(n_iterations):\n",
        "  for i in range(n_cats):\n",
        "    # Quntum-inspired update rule\n",
        "    cats[i] = np.sin(h_bar * cats[i])\n",
        "\n",
        "    # Upfate the position if the fitness improves\n",
        "    current_fitness = fitness_function(cats[i])\n",
        "    if current_fitness < best_fitness[i]:\n",
        "      best_positions[i] = cats[i]\n",
        "      best_fitness[i] = current_fitness\n",
        "\n",
        "\n",
        "# print the best positions and fitness values\n",
        "for i in range(n_cats):\n",
        "  print(f\"Cat {i}: Position: {best_positions[i]}, Fitness: {best_fitness[i]}\")\n",
        "\n"
      ]
    }
  ]
}