From f29ed279132a91b6f99309eaa45ad66d83b2da5d Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Mon, 13 Nov 2017 20:13:40 +0800 Subject: [PATCH 01/30] Add files via upload --- chapter4/numpy_basic_tutorial.ipynb | 3875 +++++++++++++++++++++++++++ 1 file changed, 3875 insertions(+) create mode 100644 chapter4/numpy_basic_tutorial.ipynb diff --git a/chapter4/numpy_basic_tutorial.ipynb b/chapter4/numpy_basic_tutorial.ipynb new file mode 100644 index 000000000..86b260b9d --- /dev/null +++ b/chapter4/numpy_basic_tutorial.ipynb @@ -0,0 +1,3875 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## numpy 速成教程\n", + "### by liupengyuan[at]pku.edu.cn\n", + "参考资料：\n", + "- https://docs.scipy.org/doc/numpy-dev/user/quickstart.html \n", + "- http://github.com/jrjohansson/scientific-python-lectures" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# 引入所有必要的模块\n", + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "from IPython.core.display import Image, display\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "# numpy 简介\n", + "NumPy is the fundamental package for scientific computing with Python. It contains among other things:\n", + "\n", + "- a powerful N-dimensional array object\n", + "- sophisticated (broadcasting) functions\n", + "- tools for integrating C/C++ and Fortran code\n", + "- useful linear algebra, Fourier transform, and random number capabilities\n", + "\n", + "（from Wikipedia）\n", + "\n", + "- Tensor is a numpy.array object in tensorflow(python version).\n", + "- TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is a symbolic math library, and also used for machine learning applications such as neural networks.[3] It is used for both research and production at Google." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "** 1. Array and the axis in numpy **\n", + "- In the numpy package the terminology used for vectors, matrices and higher-dimensional data sets is array.\n", + "- Understanding the idea of an axis is crucial in working with data.\n", + "- Axis of an array allows you to index and access values in a particular dimension.\n", + "- In Numpy dimensions are called axes.\n", + "- For example, in deep learning, you will often work with 4-dimensional and 5-dimensional arrays (also called tensors).\n", + "Below are 1D, 2D and 3D arrays." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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vfuPsnewVv36VE0NhjvS09INbVm1fMyc97VPxctX6jAmr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7ExaxdMilg+9XhcVOCw6a3du4ollE6rR1Dn4X8MyRpuX7kcsXzKpVOHSTHl3WeE74BxRe2LatWs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\n6HX6/HIgNM0ghDV1dm7Q5OyBnREbF0/fv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pmZ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5dYClgERYUSccbjtHUTe67x6Xr/dvRnioz7ty+lxp4jdMaIAyo4/s6pUwMUxc9L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3+QtWbzYw6VJXy2axWB1zAH9E4CCRSBJSUvV1tVF3L9w7ub2mrHDQIKddu4L69OkjItfl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\nJkxo7OG3WVRXV+N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PT88rV67gM5mbN2+uW7euWXlM/xpQd47k5GRv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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "width": 720 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "display(Image(filename='figures/axes.png', width=720))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "可以这样想象及可视化更高维度的数组：\n", + "- 4维数组可以想象成一个向量，其中每一个元素是一个3维数组。\n", + "- 5维数组可以想象成一个矩阵，其中每一个元素是一个3维数组。\n", + "- 6维数组可以想象成一个3维数组，其中每一个元素是一个3维数组。\n", + "\n", + "更高维度的，可以依次类推进行想象及可视化。" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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KSDVHZViCUszBOftaqq7ea9pnaqn6vRdsDl8bpOX7Wro9Yl9LGNl5iPZx8oQv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\nBSRmplOwgmnM/F6Woo27e3pzYBnVKSTvkNLph13fgbObMcrMoDDhmD4K5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MeQA0EG6qYG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JYVaXgGnIauFX47qpzbBY1f4vcsrd95jkUVUD8+pHrCPSKvblhay5qwTdDqTFw/+5ehhygT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P+GNBGYewbM/48vcPyydX906u/za6/GZ4YWMUrsW3Y8tvxhb/dWtto67vjqCc1nvb952Q\nUokpIqrZxggo2tSM0MaWfxteejsy9/uFhd8vLP02svDr2OLGzYebBfWDOwTEPti+S9ncPaK0U0DG\n3MgrqfP+87GV3wfm4fp1bOVfYws/oAjTK79OLP/iHl/+yWHpf+4QisisCs1r+uCgfGRp1/jKr6PL\nrwcWfh1YgFpBfX4bW/jx6upP1GtLahaB2w+KfXZINLWqR8U54QMBpZq+u+PLrwcX3kD3Hlr8fWju\n9fji6/GFn68+eF3SekXglOYX+04cElXLqO49qWwhru/Sc+/pxbXfh5Z/G1r8dXTx99Gl14NL/7q4\n/MvtB794xeR/ckCMsO2ImV9mw+0f2mZ59ZNLnx1RzGy5kUG9n91JT2+alNWyF1W1IV1/MrD0e//C\nT82XV4/KWYpquaY2XsjvYSQ3TJxQMTf1SR2YY19Yx4ILO8R0XK39E97fvr+qAe3sQM2N1nwjQQmf\n0Zj4M2396/9++kuhGkwv2Fo2nw8UE64/oRWxTebcvIisirC6uW9WnXPSea/0Kr/Ucu+kCp+UKte4\nMo/48sCUChuvcAKBcODAgccP0GllyM3A38Rn7jloa8//uZfyLv1fStAjkNMFoBpvS/iB5vrQEkKc\nqG4NA2jouKT0bfsE86vbLs3/NMD6tYv2Qzfrx96ZH7oZP/Sy/jW+9Ftx66XDEnpyeq65jSP5zWMC\nsroCUlrkYdbk7K8DjJ966N8Nz/7Qw/iOyvy5i/mvS0sbUfkt/9wvqesSXdJxIyyv/vPD0haeCUNT\njy/OfT/IeNXL+KaP9XMP89de1m+Ds/8anfnawC3q/UOy3mmN5Z23zXxSPtknHpNde5H11ejcT/2z\nP/Yyvx+g/dhP+2mA/tPo/I/tt9alz7gdlDJKONdb1HJFWMXs8+My1T3XJua/HWFC+T/0MX/oon/b\nw/yuj/Xj8PxvuU0XD4ppq4J0ahlPr6R8LigjrWPfd/PBBNg4xo+DzJ/6ad/30X7oYcL1/cj8D3ZR\nRf88Iu8cW1rSfsMr8ewnB0Xdw9MnmV9dnP2pn/5jH+vXXuYvPYxfhmZ/G5r5YYD+AtTKh8dUIsp7\niijX9Gx8dgqKFzUNXZj9vpf5XQ/r58HZ3/pnfu5lfA+1Gpn7qW6EeVDKUFTfK414paSbGVvYfkpK\nc3LiMjQEQDXu9N7aioE3Hmq1d+mPxOHgW2j5WxvOcf8DmtvBllaX1A3MZA2dKfeejD7iDq1ujKy+\nubiyObaMdttPPMQmV15HFJIB6pxCkm19IoEF7jmlZRVcOL7MBlp5YZUH/HJwhTewwhld511+hA0z\nvnUOyNxzUsUttULJypPw+eFPhVSiq4YvP8WGVzn9a5yBB3ygm71LnMEV7vUnWOMwYz9yPju4xuaI\nqRjvPCF/TN2iapw18Zg3/JA3/IA3vMQZXQZiB+Vzrj3HMhrHPtp7yswlxNov7sAp1d3H5E290nvp\nPwMRHF1hj6zyxle5oysbYyvsi+vYxbVNr6SzhL3SHkm12kbuR46J7xNWjSigXFx6M4k7kIbWNi48\n5I6ucYeWOZcecztvr6ua+IrImoeklIgo6Pxjv+iOU7oV/VOTj3ija7yhNX7f+mb/OgdR8HXsylN+\nMfXSodPq6lZ+DhH5xxQM3t99UsHSv+P+iwmo9jqKUdvzAOtbBtbLG3/Eu/aE7Z1cSdh92iPp7Glt\nBwPPpMapX1sWsfPjy9sE1TJb7+Z2sxIarsga+b/3hfBRRStRHfcTOs5iZ1z/sU9CRMkirW4st5OW\n1UVPJV0SUrXQd4nquvVy8N7XYRk1hH/u/Wz3kcpa/NxQHNf+Q0b/R0J/wv+I5/nfTX+xAxx4xyaH\n+5YD0hpHa5yLY1M0xu6jotp2AReXfh57wBl9wB1bY4+vvJ18yL+wyr2wvnnrBdZ2dWWHsOqe46eP\nnBBZf/gAlcUDJb2J5quRg/Tdrur/AQn6A1h/JJz5yOwj4w8J7XDAu/4WFJytqv9o+25hRT19jzht\n90xtr3x1zww1rwx1r2x1rywNzwxVh5jdwuqnNR3TG0arB+6d1ncmfCggb+pj5Jet7Zml5pmp4ZOl\n7ZGm4Z6h6pOr658vbRL8wQEZbYewwo6bKU2T+05rf7jvtJZjDOTR9krX8UrXck/R9spSc89W88jW\n9805rmi+7YiMe3JVSS/NPbn604Oye8T0znikanumabola3ika3nlaHoUaLjnantkGnqlHDilsfuU\nVnRZR0XPlJJ1+HufnTyl66DnkajvlarrmabtkaHumaXpla3pla7pkarmmPDZESVlE+/s5st51JvA\nMD7YdljTMVrPJ1fDNQOeV8s1TdczS8cjS9MzS8sn45Shx4cHJaxDcgo7byVW9X98QPaTQ1KGXrGG\nHsm6LinaHllqrhkaHtmanjkaHlm6nol7pfQ+OqoUmtdS0HnfKqLkH18cOyajY+CTqumVoeGdreqV\nqeaRCTm1PLK13dL03JM/PaJwUsM2of5CThejoIsVntd2Slpz7AI6tgygmo9t4Ej0Dqr/fyTothzc\nVAPTxGfx0etZXl3WNTRV0LfruvNk4jF/6AHWv7I5vLo5vsYbXuEPr2IjS9zQ3OZ/7pOxDs0633VJ\nz9abQNhuH5YJ+A1YNbbMH19BUIrQd507/pDbdf8rc5+MnUc1wotaUhsHTqgYf3rwdHr9yI1n2Ogq\nHxBuYI3Tu8btxU/yAdw918/aIax1XNGiqOOaJ2Dq9qMS2takS6yrj7ERyL8KIIeqMbjCH1nbmHiy\nmdh4gbBXQssmoHHghr5TCIGw2943dWj6+ytAEVawgRXuCADqKuAuG0gGoLVrYg1hx2nn6Iq6kTk5\nbTsCYVtyWcu1BxxgGGOrnOHlzaEVNpCA4RXOxYdY2+2n8sY+R8QNcuqGkoqJu4XkPj8uX9V/9+pT\n7iDIbqjMCq9nbbP3AXfkAXbhIZZLvbZLWF3ZwPl813WLoBzCbhFlU4+e+19ehMqv8/uX+V1rCKoH\n1pEzaeLRhmPCecIX4ubhZeeGZ0+o2hp6JDbc+4k8x6+aWN0moJLbfie56ZqYXsBeEaOAws7s1hvp\nxMvp5MsFlKsHT2l5xRSXdNNSKfdT2u+nNV85pmiy+6SSgXO0oU2InLLhhx99UVyBziNDDY1WJYCC\nQFgGP0FbI7P1Z9r6+/9++ouhGp5nk897y+O+BU28pZ3uM2YOnZTUcwi8svyvi2vsIWge6L74QVHo\nbKkl9pXnWNWFVYKAgvgZ55ji+oOn5daePUFFcd4ipxJi9TAacGvxLv2NE3QGUB8cgOX/gGpEwPg8\nNujqLazGO31McqaklrlHWo17LsUpneKY3uaW3eKQ0Wyf0eaYSfHKbTcNzj2uaeeU0pDTTS/pmxJR\nMFWxifDKpbpnklwzWhwy2+zS25wyOlwyqI4ZZK8csrpLvIi+d+S5/oJ+pk9J104JA/OAjKD8Ntf0\nNpesdscMinNGq0t6m3sm1SWN7F/QIaxip2UTVNRHy+1mGAdkHlEyt4uv8szvdMmkuGa1umQ0O2ZQ\nHTK6nTJ7XDMoHkmVgjL6VkF55QOz+ZQ7wno+kuZh7tnNHtktbhnNzikk90yKUwbFIYPqlNHqlUsx\n9Ms5oWYfnEsq6JtNJt/ZJaRu7ZfsAcVmdzqnU90y2jzSW93T2lzS2pwzqF753RLG3kpWfslNl3K7\n6H5ZxC+EtZyS6zxzqB4Zze5pZPc0ikd2h1Naq3MmFR7HL4d0UM7YIrigpJue23JT1THuuIqNd1q9\nVz7FHr0ZqktOB3yAzB6Znd5Qq+izO4Q0wvPJBX3MROr97K6Z8ALKKTnNC3+oah4fewvsCtprC6f/\nz9ik/ykJzPQmCBPENdFxMfCXlbUH+sbWcprmw1NPrgI2L/EGF/iAzaCn+xe5aJJi8W1QfvuH+6Rt\nQ/NKe+85xZd+cFDUMixtfA1pmOFlzuj82wvzb0eX3g4u/j62+qZ7+oWNf8oOQZWgwt7i9ttnXMI/\nEZBJrui/85B/aZk9usAZQ4fcvR1e2hha5F1Y5lUN3N8tpn1SySq/9XIG8YKUvpuoknnL+Mz1R5tj\nKDN/bJEzOP9maJk3CJL34eukpkHCHhEF+5DSnlvheXWC4mrGrtHjzJ+urWPDc2Cl+QPr/IHFNyCR\nh5d5/bO/usZVgIR1jq+s7Ltn6pX08UHJ6Pymq+uvR1fRggnA3YGlzaHlTbDt48uclstr8oY+B6TO\nJNcNllBviOvaf3pMpqLr1o0n2PAy0ujj82/HFzf7V9l9K9zxNX5e8809wqqyhh7wpGnne45I6Mie\ncR+Y/vLyIyAZ3IHFjWF45DV278Jr4BDjS689Es8RvhAzCS7O62UVDc2fULc39Ehouv0tZZ5TOzb/\nuaBiWk3faR03ATn70uGV7gVe2xy7dfZN28zG+CNMTMnOObwwpxNwmpHRO5PYcPGkoomxnXff+PXB\n4cukhtar+EkJ0O03MT5OyBAqbzU6PlWHhsJ/mKz/I+mvhWqoN9hhzgaPw0afQU9Psw4JyeraBl5b\n+fXC6ubAEqd3kdezhPUs8/tW+ENLbLSId3iGcEzrqJZzWdeN+PK2/cJyyyiyFhhzNloWj9YewQvC\nTcW79LdO0IqozwPpggtGARg4BNGgqreOvNkaDBmFZa6RWZT731CX0HEK7XOcrvk3XUub1Hl+5wIw\na15JP1PFMcYusSGrd664Z+qkrHHM2cHhB1jn3GbHPHsrJnrHHDpTonPh7fgDdmzlsKR5eFjFAAjH\ngPIhQR338t7pkRX4V177PDoUonOR3znP6Zxjd81tXniKWQbmqlkF5XfTMjvuW4Tma7vF1t943rOK\ntS9yKbNvuhY22+e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j/Y0uMI5MdhMKQQiEgAPD2MgnT93cv7iPDtrUMqJI3Snm/OUv8bD/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jVNjWBXJnGo8SQlSayxlXlUzRqPEMtFlUJmQeKw8pFKN0WpyIvCmTyU5GKtYyBBye6ftadJqG2U\nfA6olr3ZRhlATgABHZKeYl3Ma0YyqwLJ9EyauS9oeUMtbGm4OBD2bOWRkVCbpH3Hx4UPFC+UwKqh\nBX/JtQhiUM42fGTRfcSD1HXU1eAKpm4wUMRlbCwwEOAbGlYWR9nQ+zXsgAHKGJVYBaXyAsFyTKfy\nA2pYeNckvCV6Usk0YIxFiEOodowqqeRmjYiGkSzFQa9QIDt7y4ET07sOCNIV174N9FYEr5SlsimA\nGGoz5zqSzrwZIKa3Iahu/GMb7dB+oGge3QWt8KMe4mHWDpgnjClRlGQikN3LimUqX1Iv3QyIqZ2g\nRJ+C2ZhGxwyvY50CKmJUZhPUMHMAraFoNnlwM2gk3Q8bm08PH1pV01ynIcbQ1EK6MWGCK7pGJ+LM\nPJIa9nVvDAgAmoYGenWWyGoxKATG4TQwxNOMm2jkJNWI+DSBwcQ0wpkBoykRWvyCH5IUzFn+l3iA\nOIWrFMYLzKsmyYE45iwyLUNSAVOb8Qwu2QGACkKBBAcrlJdLE5tkAeWi8umS3nxmUx6XEEbkfJIA\nZlmkeZEBkWgALFI0HddMr3NhAQLEQn4waQE6EDC+ZX4DL4AVJFGHUlHOEtiJhBlkEHknuOCloPFU\nCy8P4hHyCIk8CjIOkciJW2Edi//kkKAA1E2dhjSyBXgPNIe4KqZJyt0VykyELFqqqlljm8EbiENy\nLYIGiHoVYMNOI8FkFP5C86FjGT+AjIaFOAHyjUYT14yK9TxnKbIl2cggFaCOphONOE+k0qguVMkK\nZfXywaC/LAflpyHGwfmfkWIsEc/ygTHI7UZj6QKEVDyyIp5edUQ2NvbMz2WZqT2MZ/jdoQ5qM1kP\ntVCMb+lxMmVir14SiIbIKDdrHisB15LsrHloTHOMlJ4Rs5kIA4B1Bg7JTaEQVgpR0MFiaCaQVkcJ\nrL10Rb9iYAzP6D49fPDXytBbxJXExwCGmzEPepoPH7oVfPwOnQyWJApizoa6Ono+Tb1Oix2MfyQD\ngwNBCXtJqhHxCYILKMgCBNhJqhhoWHkSzu8DUSSauIRic5xcaqhruibBQdFUHtnm4Ckm67jAk4Ki\nUdQfIhIFMesekMgBcluZMgQJ/jHtBWJ+psw8QBzKnuoRMTnpRMyUczMx058SXccIqOWS+2AHay7+\nQrjwe2KFSwgwN+pryWOAJcGmAKYLlY3/TP+TLGXalxbWUTHmBWqjPqTW8VJIclGdEL4okIkxoqAu\nYOKbiuCEKIZ+6kXijlWDUpFSy5rHqahKafN4LhFS8AHkPYVe4/0jYR3qW3ZNLEJBdDT4gQlFdt18\nRsdLsyMnZw6WD+UjmRdFpUjGDvSM3ZqZnYAAXdK1hIwTwDt+y4w71IK6SQuSAYcSYWByqcp4hbn1\njFVouQUMQ/wEvmA1U6UskoqleCoHDArv/h1RUfXvkzWfcbDuYGd2TVOCpbY8JJTUluYeYTNDksqT\ncbB4YtU/MrJJQwqedy2KR+IniQ/9rBr9RL1FTIc/ks7jo0XXdOLGHTFDc6eSCCZGo1Fnfxgpz8ND\nLALFiPiEgYHknMDQzBRsWP85qQUoAYNPTEQ8QNOUOEFizHGpRjmJcZio4gEK4sTkF7wH/KVaKJmB\nTEI2t+tZgJbjSOf9qzbg+o8ofkFWIw+hScTr0mw4s4Y1p+LgV/S/RfnsL+dodg1wYiYeqXxKYXn+\nKb90XjFB2qIIimkmY9F04gSSTqLU5oDkkjqTF8Nz8aJATrWwMM4S8AvKJaIZ6A3p0bKT6S96tbm/\ncOJBySG9ZmceybSO5PiDmP8n7UXXPJItMDLdzECjzJmc/aXqJDzeRJ8AZAubZDvWEaOzsZbyj6TN\njH2htSmNx9AZf3gUDmkkiOkCUaiRaXQeyc784DH84PHvQZrKj5Yl/BFiZ/yVHNJQc4nSCOplCQ9L\n7oulf5L40Kr6fwI6W3qIEPG/BGMcCQNJ/rBoJrzoTNqXPVfBtGXi7I9LyAUu2pjylp5ZPgIV9D9D\nUmtzzf8CEorm478Hoye/iN3if8L/UHhzmpSMXUnwxyWF3qvtj0QR/w14f0mP/4D/QPMfkt5L44wK\nnuWsixjO3riUxuBcV1fHyGjnLwAjjDDPy4uSltryShrDD/6nZQwOKfl7kS0vpce/w3tkOP4d/gNB\ni/j3ePhTxcemqkWI+P8/uCSSCiyca2truWxqmYQAiTam1nHJxRzkGs6ApCwRIj5WSNlYyrEIcyAe\nMZztEeAx4HCWQzIpeDwvSsTHBlFVi/jrg2RVs7QCuPZlMuoPuUb+BXkYBFxKA5wYYUlZIkR8rOBM\nC64G00p5W6qPeSqAyPcuAWlAUpaIjwyiqhbx1wcXQ38WT1w3Mzkm0eKc5r14HpaUJULERwlwKQdn\n2j8DXI0zTyXObtblAM8IICwpTsRHBlFVi/jrAzJIKpv4WZLwz0ASl1yMViLIEJAkixDxEYPzKuPf\n99UtY2cCksDVgDTMCVgmCXiMiI8NoqoW8dcHl0EQT1w21dbW3rp1q6qq6gYDAtevX3/1iraIZnKM\nNDR3QRBTU1Nz9erV9HTJ/kUiRHyc4KwLJkcYHA6WzsjIyMnJ+ekn2pAQkE4BDk4JspSUFDA/j8GZ\nE4v42PBvVTXGFcOGMw+8F8MvWwakoMwtwLPwMAL/uQRp+L1cPMwDAFI5n/FLHnivZH6JMy6laBmP\nMyCN5+CXIv5KwFjzx3UYX842ZWVlY8eOnThxojKDAsPJkyc5MYdUbD19+nQaA5XVDM4tgOS6+VVb\nZOGRLPGPVOklzpyGnzk4Dcd7MS2JeQxLf79kDullS3oRfxPwcUfg5cuX9vb2Y8aMkZOTA5/Pnj07\nLi6urq6O03DG5gHEODo69uzZMzc3F2HE82mCcEu8fftWEmIAAQfoeVEtz4CU5s/0klCLKlpeIgAa\naSQgjedhHmhZ0d8H/1pVoy8wZkDLAO8dhHkf8UgEcCklYySS7uY0HFJKyfWfCuQl8ID0zAM8nod5\nPOX/57bhzGlaBjh4Ft4eHs/P0ic3VCgroSWliL8SMKx8rPn4xsTEdOjQwcHBwdvb29PT093d/fjx\n43AvOCVnBs4PiHnx4sWiRYsWL15MBTUXJQVi4JGcOHGitLSUZ+FnJLEy/jAoAYQRI7UbEAAlz8IJ\nKEMzQ+KSJwE8FUAMz84JpODxPCClp+aK+NuAj/i7d+/Mzc2hfffv35+Xl3f+/PmlS5eCgZ89e4ZU\nxk0Ezj+IcXZ2Hjp0aFFREcJS5uFnxNTU1CQnJwcGSrbQRqQUnJiDl4YAZ+l/R8kvkYqwNAsHTwJa\nsnHLeIBn5JE4cxoe/3fAv1bVvC+oe5qlAM6I52cpqNtadBkCHLDg7t+/z1cUpQQ8iVMCvExAGkAk\nUgHk4jSI5PTS1JZhysOAMArhMThLA1IynouDx7RkCN4ABHgSuzMRfylgZDkz8LCbm9vo0aP/PNZS\nhpFcM/z666+QdAsXLuSXoOHMI6WsrKzs3r37xYsXOQGvi4dbAsTvlSwF4nmuPxP8u3gA8f8yCTEc\nyCuJEvE3AEYc5wsXLvTt29fV1ZVHAmDgGzduQIUj/GeWcHFxkapqzk6cczjlP/7xj7lz5y5fvpzR\nEv5cAoCM/zKeA0koEzSS62bwXH+O5/iXWQBE8gmIMC+Zx//l8W9VNYBe4CoQYWmnIMbf33/jxo0l\nJSWcEkk8lQORsOCWLFkSFhaGMI/8l2QcSOLKkoMPgxS45DFI4iVwSMkQ5gGenadKw4jnlNL49yhx\nCctRGgYkzRLxFwIfXww6whjuHTt2vLegDXAaHobksra2Xrly5Z49e3Jzc3V1defPn8+TpOzEWQVC\n0NjY+KuvvtLR0bGxsUlNTeW13Lp1C5eQcUhNSkpCpSy3UFVV5evrC+kJyl27dtna2p49e1ZaL+Rp\nQkLCunXrkPHgwYN37tzhpQE//fQTLIzvvvtuw4YNwcHBKAGRvA2nGJ48eQLnHr4UxKuUvVlWEX8j\ngGNHjhwJzpFcNwMswXnp+fPnhw4dWrt2raGhYX5+PsIjRozgwpzzDJiKU/72229gp379+sGutbKy\nCggI+PnnnxH/+vVrT09PAwODNWvWHD9+HJeIBJAaERFRWFiI2sHYmGUhISHSV0BwRnWmpqaYKSYm\nJlevXpXGv337FhmhU8DeqPH777/nScDNmze9vLx++eUXTKLdu3e/t/SFAAci//L4t8+qpX0hPQOI\nT0tLk5GRadOmTXR0NC4RybpUIhoQQOSPP/747bff2tvbI8zzchqEOQFEEiTU77//zgkg/jiNVAED\nPIkDqTizMqgiHngvicdLI1EUj+SFcxpOIA0APImfeRbUK+KvBwwxH1xMe2g7yIuYmBgoRQQgHR4+\nfIgkTgC/ZOzYsePHj9/EAKXev39/mJ6cgHENgRPDpd68eTNUNTxvqN7k5GREQlopMSBGT09v+PDh\nR48era2tRVJkZGTXrl0hKKH7Fy9ePGnSJBQeHh6OJAACC/WuX7/e3Nwcbdi2bRuXdDAIZsyYAREM\ncQYtjgJRAmYZzwWhCWMChgVkLhoMCYtItJCnivj74OXLl1paWpqamuBA8N7s2bP19fVjY2Mlyexp\nDji5e/fuK1asgBEJzhk8eDA4DfRIBUtL5SEuYfNB8YM/hw0btnPnTh8fH0jsx48fr1q1CsobbI8S\nkATGw5wC/d27dxUUFNTV1cHbmA4aGho9evSwtLREOUiF/lZRUUHtMILnzJkjLy/PVTKatHXrVjQD\nTQX3ojEopLi4mLcHlitaCythwIAB8+bNKysr4/F1DGwiEhD5l8e/fVaNM7oAY9Zy8OArKCsro5dx\njouL4zQg5qCcDI8ePcIg7du3D2HqyBbakRPEx8dDJMG+4wRI4rXw1JaQqk/eAA5W2B+L2JJYBlwi\nkpcGSGIZEMlT38vCgUhOILkW8deClJGg/KZOndqpUydoREgN6DyIG8Rwgx16btasWRMnTiwoKMAl\npAyMehim0mfVf0ZWVpasrCyUNGfRZ8+eQVxCT8PN5QQQc4MGDcrOzkYYnN++fXvMoMuXL0PAQUSi\nLqnLDqk3d+5cXk5paSmyQMG/efNm6dKlcG5ycnIQjxsJDAzs1avX3r17WSbKhQbgnJ6eDhcHtykF\nJxDxNwEsTmjBIUOGwJ6DGrawsJg+fTpEsYeHB5eWBw4c+OabbyC6OY/BKh01ahQsPK4a/4yffvpJ\nugDOxSn3s/k7mACc4w4dOsC3RviHH36AxoUleuLECShgAFNs4MCBvHB/f/9u3brx19ExR86cOcN9\ndMwvNMnFxYWXD6sUliiazdU/ptXnn38OxY+JgwnFmw3Gxu0AnMkBRP7l8W9VNR9aAL3DOxEiA10G\nJyM1NRXeQFRUFKfkqcD9+/fz8/NBD+OuZ8+eXFVzAgDxAKd0cnKCrLx37x4kESDt6+rqanAPyuGX\nyIUkEEjXD5GFK3iAF4sAqoPgKyoqkpYvDYB3Ie+qqqr4pbQxkMic5vbt2yiTR3JwShF/JWDcMdyc\nzaB9wZlWVlbcqAefnzp1CgIFLiwuoe3Aulz0cECgwBsA5yMMR9bMzAx2KlwHTAHwKiLz8vKgKVEI\nIxdKSkrA25BukGLnz5/PzMyEGILbDccaqXBx4CXwZ0MAajc1NYUbwcUWnBjktbW1lS4qAvAkOnfu\nDKtCcs0WpeCCoBkPHjzAJTwkqH9UxFP5zYrM/DcElCU0q4yMjLOzM1+zhL4Ee8CwA7cjZsKECbBK\nOTEHmA36FXYhwmBUNTU1VVVV0Njb24ORkB0Fwo3mxLiEawvHF4rzypUr4P+LFy/CDMUEAbNB2MrJ\nyWlra3NiAHwOvX7u3DmEIYeh1HV1dcvLy3kqAJ09c+ZMVMcfpXNgpmC+YFohnJKS8sUXXzg4OPAk\ngDM2l+RSJSVJ+0vj36pq3D8mPJ/zPAbD36VLl4qKitzcXAwJX1dBPM7QhbNnz4YMgswaPXr04cOH\n+/btC/sLSawnCaDkxG5ubjD0wE+Qj2PGjIE4QyQspmXLliEXvG2cN27cKFXJjo6Oq1evjo6OhgEI\nkYRaIN2gv3nq6dOnxzHANhw5ciTMCNSFeBhlyAWxi8jevXujeZwdeRL8GLQfJcPQg3dSx37JgObx\nvCL+YsCwck7GECMAbS01/jg2b94MzQdNDK6AQOE6GJQ4wxCES81VNSSLq6srZB+El56eHpcmME/7\n9+/Pl74BiDDwNhQ5ZNaSZkAZBwcHIxUGLniSu+zA27dvLS0t4WQ/fvwYl1DY8HsGDBgA2bply5an\nT58iEiyN+cIXsfgMAiBJUSlvANqD8rnaxj1KbxZgtCL+Lnj06BEkG/Qx3A9JFGNIyO2kpCTYfxC5\nkIqIlMo6/loZd3yDgoKQCt5es2aNt7c3YsDwcNNXrlyJMAA5D06DkOfL7GBsBKBoQYACYShAi5ub\nm4OSFx4TEwNhzq1Y8CT07uTJkzt27Aj1zy3LW7duoXZUh7C0SXC44Wdz/YJphfmYkZHBS+Dzlzi7\nWVtLc/3l8W9VNe8XHkAMFCq62MvLC2FYUtCLXHYAMNbgavfp0wfWE+QFdOfEiRNhCkHocIL3AI6B\nTwPuwQDcuXMH0urXX3/FkA8bNgw+DQw3mGwobdeuXVwfGxoaQkNjRMFJlZWVEG1ffvklwkiCLNPQ\n0DAyMgJLgVGg4FE74mFtgZMg4DDSkL9gC0VFRXAJvHakQvjC1Fi4cCG48MiRI1K25vfLwyL+MuA8\nzGf1e+MrneT82TA8D+hF+LUJCQmI5Jz/6tUreBILFixghPRWGjgWePPmDc8OfQmtiYycAM50u3bt\nwPzICAP0p59+ApeC5bjfAIsTbClV1YgEP0P8ca0MoIX8DTJodNgHmA6YJpgsvr6+nIAD1irmC7c+\noarhmkgft7cEoxXxdwEEprGxMcxE/h4DZ4CSkhLwEhxcGIKQ25C0jFaSCgdsyJAhXFUjO+dtgMte\nsCXUKhiMMrCn0ZCi+vr6ELYQubAMYGKCt/lLjhCkcL127NiBMJ87ULfwqrlM5gAxVxAwGjALwOrw\nzbgjjvbwCQUFD68aeh1hWBhgful84bMYZw4e+TfBv1XVHNB5uMTAo2fXrVvHU2GmQUxwqweAu/D5\n559Ln14AUI1wLLhXDf64du0askANI8AHFXIH3MNfmQGg+zE2LYXR7t27YY7xnxBs374dpUnLx+iC\nIdavX48wmAMmJF+6BMAfnEXOnj0Lcenh4cHjgcuXL8MdhxuNMLxq+DGQyPCHeCpuExlxxi3zGBF/\nJWBY+fgiDA6Ea8u/+cAB9lZTU4MAgoQCRw0fPnz58uX8URkAJoGlCAeCX/4ZOTk5UtcB4I6Crq4u\nv+S4fv06f3QdEREBVc29YQCq2sLCAtwIqccvOQMDcGs6d+5cUVEB0xZ+DExPvvYDoJHKysqQufyF\nHUjS6dOnS1U1RBi/37+bLPubg8uu8PBwiFapcAYOHToEJxUcCP4BW0J3clYBoIlhDkp/rPVngGmh\nqqVeNQC3G7qA+zwcEMhQ4Qjcv38f9i7ENY8HIiMjMTXS0tIQhu6XrnLfvn17wIAB+/btA5du2rQJ\ntgL4nCcBUDRoMC8TYh+zgKvqv7lw/tequqXeQhfDpYA5Bs3K5z8U4ejRozEMnMDMzOzbb7/lPw/g\n0gEDDHnk5OSEMHyC3r17t2nTpnXr1hhj/qohfFnwExdPyHL8+HEoY1VV1fnz58ODgb8LZYwY/lvV\nrVu3Yiyleh1+hrq6utQ29PHxgSRVUlKCx48kHmlra4smcdOSyz7UhfJhvoFfIYXRfoT54xx+U/z8\nN+eGvyQwphhZgF8+f/4cig0S5MSJExAZcILB3jDjuBUP7Nq1CxxlbW0N0XPu3DlFRcWOHTtKveo/\nA4VAlSJXZWXlzZs3MXHAz23btjUyMoJOhTSEhw0GTkxMBDF/A1xqKMA42LlzJ8xNeBu//fYbDFCw\nJcoBi5qYmIBLUTjIDh8+3KFDB1QBli4vL4faRvvhcPBCkGXKlClSVS3lZIATiPg7gHM4XCOYbtDH\n4DSwRGhoKCQtWBGchlQ4UWCkadOmgYuqqqo2bNgAyaygoNDyd9UtmQdSV0dHB570jRs3OA2cLmhZ\nyFIUBS7luoAvekO5ysnJmZqaIsyzwz/u1asXfzbk7u6uoqIClxp8DuWNeP5ICOVAWcyaNQvlQ3HY\n29vDy4Lu4I+oEhIScCmqauA/PasGEC4tLcVwYgyWLl26ePFiyAXoxS+//BIGFMwfcAPGBpKOvwvG\nDX+IJ8TwN1TBIt9//z1kFnQ5AtywgqrG8PBFP2TZs2cPzCjIo5CQEIxfUFAQAjAPuSMCM23UqFFS\nNcxFLRrDLwEYjOA5sKD06R3EHy65Y8RVNbLPnj0bJuSbN2/AKyNHjoQ3wxd5IFv5zaIlf3Nu+EsC\nY/qe9nr8+PGWLVugMqFQIQgmTpzIDX+eCjaAngYDf/XVV3A4wJbgTwg7KutPQBYUDmsV6hzyEeof\nkeCowMDAQYMGoXwA3Ct95xbONwQWf9scgDxyc3OD3clZPT09HWYoWBe5IBChjKVN8vX1HTx48Ndf\nf40kWA/8VR2OHTt2rFq1ij/t5u0BOD9zAhF/B2DoMegIwJ7j8hDcAo/F2NgY+psT4AyTFMIcXASO\nhQyEqwOnmb/qRUKw+V0tnBEDgGOh7FEU3F++JpqVlQUuJc5u2xZJKAQSFfHQBfCy+HNPzu1nzpwB\n5eXLlxGG871mzZpOnTrBDoajDO2O9vAmwVyGrckLhAyX/rIROH/+vLy8vPQ3Wjzy74l/raoBCBEM\nGHoHA+Dg4AA/1crKytLSEuHly5ejr6H2XF1doTghnj777DPpmh6AgYcP3fJZ9Xu9fOzYMYyxVPtC\nK4MVYKDxSw64vFzWbNu2bfjw4XA7eDxqnDFjxrJly/ilFA8ePBg3btzcuXPBT9D0kLMwACVp7N1y\nyL7NmzcjDMaFqsa9cMMNbePSDYH32inirwFwMsaX8zPOPBJGG8xHaDg+6DhzHuCp4A1YltwX+c/g\nBf7jH//g7IoSeCEoAT4xpo9U6kkLB/4Dvz179gymLZdWIJA2GOXAa+evj3G0bDDAypP8duO9JBF/\nB3Am52GIwVu3bkl/SoB4KT+AjD9s5pcAkjjP8BI4MQdS4V9xJc0peQCqF+wtnSDSeADZMRdaxkjD\nkOrIJTUdeHU8CYwN9uYyGUAqB7/kTeLhvyf+taqmsWoeLUlUC8AIgl0mfeW1qqqqT58+CxYsuHv3\nLuQLlCK0eKtWraSqGuMB8YGieLGIgXaHKq2oqIACRir4RlZWFs46XHMIUAx/bGwsPBW++mdoaAh/\nQvpCOHxx+CX8d66vXr1KTEzMzMzkAwwbAkngAxgBsM6mTZuGksFnqAWuP6xI3mYQwFuCqkZreatw\n5i2kCkT85QDBwZkQZ4zynwcaPIAkgHHoPwkFXEpC/wqcWArESAvhBBxSMn7Jwy0BAmTkqRyShH+G\nJK05ldfFY1reHUAt+I8tF/EXA4YbDMBZ4r2h5/yApD8vtCC+JedwMn7JA4hBGJQ8hodbgufiGaVh\nxEvzcuCS03NwMk4DSGKb4wGeBWdpJCf42+J/UNX8zGMQ4GGo6smTJ/NnbzzG09OzS5cuampq8ICh\ns5cuXQo16eLiIs2IMxhCWhr/fQvU7aZNm/gLBefPn4fXO2LEiC1btkA3w+vdvXs3N+V27twJBdzy\nWfWSJUv4S4mVlZUaG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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "width": 720 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "display(Image(filename='figures/tensors.png', width=720))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2. 创建array及array基本特性**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "主要创建方式：\n", + "- 由python的list或tuple创建\n", + "- 由numpy中函数如arange及linspace创建\n", + "- 在文件读入时直接创建" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2.1 由list/tuple创建**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4])" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v = np.array([1,2,3,4])\n", + "v" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "一维list对应一维array" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4]])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M = np.array([[1, 2], [3, 4]])\n", + "M" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Matrix(矩阵)，也即2维数组，对应二维list" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(numpy.ndarray, numpy.ndarray)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(v), type(M)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用type()函数，可知v,M是numpy中的ndarray类型(n dimension array)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(4,)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v.size" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(2, 2)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.size" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用shape属性可查看数组形状(各维度)\n", + "- 利用size属性可查看数组大小(元素个数)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.itemsize" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "每个元素字节数" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "16" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.nbytes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "总字节数(number of bytes)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "2" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.ndim" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "数组维数" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int32')" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.dtype" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用dtype(data type)属性，可查看数组内元素类型\n", + "- 与python内置的list，tuple等对象不同，ndarray数组内元素必须是同一个类型(如：M[0,0] = 'h'，则将会出现错误)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.+0.j, 2.+0.j],\n", + " [ 3.+0.j, 4.+0.j]])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M = np.array([[1, 2], [3, 4]], dtype=complex)\n", + "M" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- array中元素的数据类型，在定义该数组时确定\n", + "- 可在定义时，使用dtype参数，显式指定元素类型\n", + "- 常用数据类型: int, float, complex, bool, object\n", + "- 也可以直接指定数据类型的位(精度): int64, int16, float64, complex32\n", + "- python内置的list，tuple中的数据类型是动态绑定的\n", + "- list及tuple不支持矩阵运算函数\n", + "- 利用numpy的array矩阵运算函数进行计算，要比python内置的list, tuple等类型做相同的计算性能有质的提高" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "D:\\Anaconda\\lib\\site-packages\\ipykernel\\__main__.py:1: ComplexWarning: Casting complex values to real discards the imaginary part\n", + " if __name__ == '__main__':\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[ 1., 2.],\n", + " [ 3., 4.]])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.astype(float)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "元素类型可以由astype()函数改变" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2.2 由numpy内置函数创建**" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.arange(0, 10, 1) #:start, stop, step\n", + "x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "依旧是左闭右开[)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ -1.00000000e+00, -8.00000000e-01, -6.00000000e-01,\n", + " -4.00000000e-01, -2.00000000e-01, -2.22044605e-16,\n", + " 2.00000000e-01, 4.00000000e-01, 6.00000000e-01,\n", + " 8.00000000e-01])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.arange(-1, 1, 0.2)\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. , 0.41666667, 0.83333333, 1.25 ,\n", + " 1.66666667, 2.08333333, 2.5 , 2.91666667,\n", + " 3.33333333, 3.75 , 4.16666667, 4.58333333,\n", + " 5. , 5.41666667, 5.83333333, 6.25 ,\n", + " 6.66666667, 7.08333333, 7.5 , 7.91666667,\n", + " 8.33333333, 8.75 , 9.16666667, 9.58333333, 10. ])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.linspace(0, 10, 25)#:start, end, number\n", + "x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- linspace()是包含两侧端点的\n", + "- 包含两侧端点，在其中均匀取number个点(当number=1时，取左侧端点)，缺省为number = 50" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1.00000000e+00, 1.51689680e+00, 2.30097589e+00,\n", + " 3.49034296e+00, 5.29449005e+00, 8.03119500e+00,\n", + " 1.21824940e+01, 1.84795861e+01, 2.80316249e+01,\n", + " 4.25210820e+01, 6.45000931e+01, 9.78399845e+01,\n", + " 1.48413159e+02, 2.25127446e+02, 3.41495101e+02,\n", + " 5.18012825e+02, 7.85771994e+02, 1.19193502e+03,\n", + " 1.80804241e+03, 2.74261375e+03, 4.16026201e+03,\n", + " 6.31068811e+03, 9.57266257e+03, 1.45207412e+04,\n", + " 2.20264658e+04])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "xe = np.logspace(0, 10, 25, base=np.e)\n", + "xe" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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/bkz72+QVFlwAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(np.exp(x));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 可以直观的解释logspace()函数，其中base参数可以指定任意合法的底" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.18337257, 0.63380606, 0.38995696, 0.16164304, 0.6468163 ,\n", + " 0.01388857, 0.2620011 , 0.58901649, 0.69054286, 0.03078337,\n", + " 0.7048618 , 0.64473979, 0.36315537, 0.00539391, 0.37432821,\n", + " 0.15796796, 0.80564939, 0.80824261, 0.89574276, 0.65957744,\n", + " 0.88529726, 0.45066723, 0.59449983, 0.18279727, 0.82879779])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.random.rand(25)\n", + "x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用numpy的random下的rand()函数，得到在[0,1]之间的随机数1维数组(随机数以均匀分布的方式生成，分布的均值为0.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.33933233, -0.469771 , -2.31839629, 0.05676264, 0.11127693],\n", + " [ 0.54489201, 0.46651208, 1.84016187, -1.46393508, 1.01564912],\n", + " [ 0.48424374, -0.58979811, 0.4431372 , 0.50543707, -1.02986282],\n", + " [ 0.93775131, 1.02304841, 0.52626138, -0.63327381, 1.04351029],\n", + " [-0.29030852, -1.6233196 , -0.9275113 , 1.86146038, 0.77076014]])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x= np.random.randn(5,5)\n", + "x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用numpy的random下的randn()函数，得到随机数2维数组(随机数以标准正态分布的方式生成，分布的期望/均值为0，方差为1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 在深度学习中多用于随机初始化权重/向量" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0.],\n", + " [ 0., 0., 1., 0., 0.],\n", + " [ 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1.]])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.eye(5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "单位阵" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2, 0, 0, 0],\n", + " [0, 3, 0, 0],\n", + " [0, 0, 4, 0],\n", + " [0, 0, 0, 5]])" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.diag([2,3,4,5])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "对角阵" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 0, 0, 0],\n", + " [0, 0, 2, 0, 0],\n", + " [0, 0, 0, 3, 0],\n", + " [0, 0, 0, 0, 4],\n", + " [0, 0, 0, 0, 0]])" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.diag([1,2,3,4], k=1) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "带偏移量的特殊对角阵" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.zeros([5,5])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "零矩阵" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1., 1., 1., 1., 1.],\n", + " [ 1., 1., 1., 1., 1.],\n", + " [ 1., 1., 1., 1., 1.],\n", + " [ 1., 1., 1., 1., 1.],\n", + " [ 1., 1., 1., 1., 1.]])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.ones([5,5])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "全一矩阵" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2.3 读入文件时创建**" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.80000000e+03, 1.00000000e+00, 1.00000000e+00,\n", + " -6.10000000e+00, -6.10000000e+00, -6.10000000e+00,\n", + " 1.00000000e+00],\n", + " [ 1.80000000e+03, 1.00000000e+00, 2.00000000e+00,\n", + " -1.54000000e+01, -1.54000000e+01, -1.54000000e+01,\n", + " 1.00000000e+00],\n", + " [ 1.80000000e+03, 1.00000000e+00, 3.00000000e+00,\n", + " -1.50000000e+01, -1.50000000e+01, -1.50000000e+01,\n", + " 1.00000000e+00],\n", + " [ 1.80000000e+03, 1.00000000e+00, 4.00000000e+00,\n", + " -1.93000000e+01, -1.93000000e+01, -1.93000000e+01,\n", + " 1.00000000e+00],\n", + " [ 1.80000000e+03, 1.00000000e+00, 5.00000000e+00,\n", + " -1.68000000e+01, -1.68000000e+01, -1.68000000e+01,\n", + " 1.00000000e+00]])" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = np.genfromtxt('stockholm_td_adj.dat')\n", + "data[:5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- CSV (comma-separated values) \n", + "- TSV (tab-separated values)\n", + "\n", + "这两种形式存放的文件可以直接利用genfromtxt()函数读入并自动成为array类型。" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(77431, 7)" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 可视为有77431个样本的数据集(stockholm的温度)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.19719779, 0.50034802, 0.04292904],\n", + " [ 0.37833544, 0.53431877, 0.17319566],\n", + " [ 0.69307307, 0.38253128, 0.8481774 ]])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M = np.random.rand(3,3)\n", + "M" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.971977931284261132e-01 5.003480170396453763e-01 4.292904207508307923e-02\n", + "3.783354385509419826e-01 5.343187731139253938e-01 1.731956591680439139e-01\n", + "6.930730680553011114e-01 3.825312826210788275e-01 8.481774049123789183e-01\n" + ] + } + ], + "source": [ + "np.savetxt(\"random-matrix.csv\", M)\n", + "!type random-matrix.csv" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用savetxt()函数，将array存入csv格式文件\n", + "- windows下，!type 文件名来查看文件" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.19720 0.50035 0.04293\n", + "0.37834 0.53432 0.17320\n", + "0.69307 0.38253 0.84818\n" + ] + } + ], + "source": [ + "np.savetxt(\"random-matrix.csv\", M, fmt='%.5f')\n", + "!type random-matrix.csv" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用savetxt()函数的fmt参数，控制保存精度" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "np.save(\"random-matrix.npy\", M)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.19719779, 0.50034802, 0.04292904],\n", + " [ 0.37833544, 0.53431877, 0.17319566],\n", + " [ 0.69307307, 0.38253128, 0.8481774 ]])" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.load(\"random-matrix.npy\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "如果不需要利用编辑器来查看保存文件的内容，也可以利用save()及load()函数存取array为npy格式。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3. 数组基本操作**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.1 索引及切片**" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4])" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.19719779, 0.50034802, 0.04292904],\n", + " [ 0.37833544, 0.53431877, 0.17319566],\n", + " [ 0.69307307, 0.38253128, 0.8481774 ]])" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0.53431877311392539" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M[1,1]" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.37833544, 0.53431877, 0.17319566])" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M[1]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "取第0轴的第1行" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.37833544, 0.53431877, 0.17319566])" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M[1,:]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "M[1,:]与M[1]是一样的功能。完整格式为M[a,b]，当只有M[a]时，即在0轴a行上，其他维度所有值均被选择" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.50034802, 0.53431877, 0.38253128])" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M[:,1]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "第1列，即0轴方向元素均选取，1轴方向取第1列" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.19719779, 0.50034802, 0.04292904],\n", + " [ 1. , 0.53431877, 0.17319566],\n", + " [ 0.69307307, 0.38253128, 0.8481774 ]])" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M[1,0] = 1\n", + "M" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.19719779, 0.50034802, 10. ],\n", + " [ 2. , 2. , 10. ],\n", + " [ 0.69307307, 0.38253128, 10. ]])" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M[1,:] = 2\n", + "M[:,2] = 10\n", + "M" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4])" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v[-1]" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 3, 4])" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v[-3:]" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 3])" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v[1:3]" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 5, 7, 4])" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v[1:3] = [5,7]\n", + "v" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 切片与python序列切片类似，但是切片赋值时，需要赋值相同个数的元素" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 1, 2, 3, 4],\n", + " [10, 11, 12, 13, 14],\n", + " [20, 21, 22, 23, 24],\n", + " [30, 31, 32, 33, 34],\n", + " [40, 41, 42, 43, 44]])" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.array([[n + m * 10 for n in range(5)] for m in range(5)]) \n", + "A" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "一样可以使用类似列表解析的方法" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[11, 12, 13],\n", + " [21, 22, 23],\n", + " [31, 32, 33]])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A[1:4, 1:4]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "取矩阵中的一个区域" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.2 花式索引(Fancy indexing)**" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.16244096, 0.34255333, -0.14172284, -0.37557189, -0.69059278],\n", + " [ 0.73186471, -1.78577639, 1.49461548, -1.11373539, -0.83390612],\n", + " [ 1.05907617, -0.53160463, 0.45099669, 0.62496865, 1.27006929],\n", + " [-0.60160429, -0.17286343, 0.06719654, 0.58424981, -1.29432354],\n", + " [ 0.05082751, -1.25291248, 1.43629003, 1.44186539, -0.07157329]])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.random.randn(5,5)\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.73186471, -1.78577639, 1.49461548, -1.11373539, -0.83390612],\n", + " [ 1.05907617, -0.53160463, 0.45099669, 0.62496865, 1.27006929],\n", + " [-0.60160429, -0.17286343, 0.06719654, 0.58424981, -1.29432354]])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "row_indices = [1, 2, 3]\n", + "A[row_indices] " + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.78577639, 0.45099669, -1.29432354])" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "col_indices = [1, 2, -1] \n", + "A[row_indices, col_indices] " + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ,\n", + " 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. , 9.5])" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.arange(0,10,0.5)\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1. , 1.5],\n", + " [ 3.5, 4. ]])" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "indices = np.array([[2,3],[7,8]])\n", + "A[indices]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "还可以利用array对象作为索引进行数据选择，当索引是二维array时，选择结果的array的维度与索引array维度相同" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5])" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B = np.array([n for n in range(6)])\n", + "B" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False, False, True, True, True], dtype=bool)" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mask = B >= 3\n", + "mask" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "array类型可以直接与数字进行逻辑比较，返回一个元素都是布尔值的array" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 4, 5])" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B[mask]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "布尔值array可以作为同样维度大小的array的蒙版/掩码，以屏蔽一些元素(对象False位置)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ,\n", + " 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. , 9.5])" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.arange(0,10,0.5)\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False, False, False, False, False, False, False, False,\n", + " False, False, True, True, True, True, True, True, True,\n", + " True, True], dtype=bool)" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mask = np.logical_and(A>5, A<10)\n", + "mask" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "logical_and()来进行array的逻辑与运算" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. , 9.5])" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A[mask]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用mask进行数据选择" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. , 9. , 9. , 9. , 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ,\n", + " 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. , 9.5])" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A[[1,2,3]] = 9,9,9\n", + "A" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "可以直接对选择的数据进行赋值" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**where**" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False, False, False, False, False, False, False, False,\n", + " False, False, True, True, True, True, True, True, True,\n", + " True, True], dtype=bool)" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mask" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([11, 12, 13, 14, 15, 16, 17, 18, 19], dtype=int64),)" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "indices = np.where(mask)\n", + "indices" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用where()函数，取得mask数组选取值的索引" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. , 9. , 9. , 9. , 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ,\n", + " 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. , 9.5])" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. , 9.5])" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A[indices]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "与直接使用mask进行数据选择的效果相同" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**diag**" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.14083334, 1.35983178, -1.0715684 , -0.7408125 , -0.81333176],\n", + " [-1.96594885, 0.8182639 , 0.24237043, 1.34791836, -0.21743733],\n", + " [-2.01708277, -0.39736534, 0.82187546, 0.10467931, -0.40930368],\n", + " [ 0.21928891, 1.91806957, -1.61350818, 0.59275986, 0.52594918],\n", + " [-1.28033566, -0.44402051, 1.85905357, 0.60691264, 1.42749162]])" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A=np.random.randn(5,5)\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-0.14083334, 0.8182639 , 0.82187546, 0.59275986, 1.42749162])" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.diag(A)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用diag()函数，取A的对角(默认为左上开始)" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1.35983178, 0.24237043, 0.10467931, 0.52594918])" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.diag(A, 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "可以进行偏移后再选取对角元素" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4. 线性代数**\n", + "\n", + "在数值计算以及深度学习中，向量化是非常关键的步骤，要尽量以向量进行表示与运算。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4.1 一般操作**" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4])" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v1 = np.arange(0, 5)\n", + "v1" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 10, 20, 30, 40])" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v1*10" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "向量乘以标量，结果是每个元素都乘以标量" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 8, 27, 64], dtype=int32)" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v1**3" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "向量进行指数运算，结果是每个元素指数运算" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 4, 9, 16])" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v1*v1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "向量*向量，结果是两个向量中对应的元素相乘" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 1, 4, 27, 256], dtype=int32)" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v1**v1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "向量**向量，结果是对应元素进行指数运算" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 1, 2, 3, 4],\n", + " [ 5, 6, 7, 8, 9],\n", + " [10, 11, 12, 13, 14],\n", + " [15, 16, 17, 18, 19],\n", + " [20, 21, 22, 23, 24]])" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.arange(25).reshape(5,5)\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 10, 20, 30, 40],\n", + " [ 50, 60, 70, 80, 90],\n", + " [100, 110, 120, 130, 140],\n", + " [150, 160, 170, 180, 190],\n", + " [200, 210, 220, 230, 240]])" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A*10" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "矩阵乘以标量，结果是每个元素乘以标量" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "((5, 5), (5,))" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.shape, v1.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 150, 160, 170, 180, 190],\n", + " [ 400, 435, 470, 505, 540],\n", + " [ 650, 710, 770, 830, 890],\n", + " [ 900, 985, 1070, 1155, 1240],\n", + " [1150, 1260, 1370, 1480, 1590]])" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A @ A" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "矩阵点乘，与线性代数中矩阵点乘相同(python3.6或更高可用@)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 30, 80, 130, 180, 230])" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A @ v1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "矩阵与向量点乘" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([150, 160, 170, 180, 190])" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v1 @ A" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "点乘时，一维向量既可以作为行向量又可以作为列向量" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "30" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v1 @ v1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "向量点乘" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 150, 160, 170, 180, 190],\n", + " [ 400, 435, 470, 505, 540],\n", + " [ 650, 710, 770, 830, 890],\n", + " [ 900, 985, 1070, 1155, 1240],\n", + " [1150, 1260, 1370, 1480, 1590]])" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.dot(A)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "对低版本的python，也可以利用点乘函数dot()" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 5, 10, 15, 20],\n", + " [ 1, 6, 11, 16, 21],\n", + " [ 2, 7, 12, 17, 22],\n", + " [ 3, 8, 13, 18, 23],\n", + " [ 4, 9, 14, 19, 24]])" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "二维数组转置" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4.2 广播(Broadcasting)**" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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qatDa2hpzk2TkmxBWq3XMyxtPX8mktiSEaEj0KYJkItcfI9cps53X6x3xNHmi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\nMc9LSkripmnp/fffj3k+ZcqUuGmpGuvALSKz9Ux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LZg1Ay40bNywsLMLDw5l+KBKJIiIiLC0t79y5w3IlFRUVI0eOpHKGIZFIRo8e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7v7VyeTkpIE94KamZmBBQVaE0OH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PBg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\n6rd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mzZoFqdAcsCjL/2zcuPH777/38fHx9va+cOECLTHs2bMnPj4+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\nmZubOzg4tLgPQRB5eXkcDsfGxgYyBgAA1MjNza2srEQ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75EP5M/rckyZC7tVUQr0AG1ef8eCSvW3nIrJypqFJ129O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\nvRan31BB9sXVd/FqZuVhLqvEddWCkMsHhJxLEXK7gfP6swo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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "width": 720 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "display(Image(filename='figures/calories.png', width=720))" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 2.7, 10. , 14. ],\n", + " [ 26.1, 110. , 0. ],\n", + " [ 3.6, 5.2, 95.6],\n", + " [ 129.6, 24. , 9.2]])" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 基于非广播的方式进行计算\n", + "macros = np.array([\n", + " [0.3, 2.5, 3.5],\n", + " [2.9, 27.5, 0],\n", + " [0.4, 1.3, 23.9],\n", + " [14.4, 6, 2.3]])\n", + "\n", + "# 创建一个形状与macros相同的全零矩阵\n", + "result = np.zeros_like(macros)\n", + "\n", + "cal_per_macro = np.array([9, 4, 4])\n", + "\n", + "#对0轴循环，每行向量进行向量相乘\n", + "for i in range(macros.shape[0]):\n", + " result[i, :] = macros[i, :] * cal_per_macro\n", + " \n", + "result" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 2.7, 10. , 14. ],\n", + " [ 26.1, 110. , 0. ],\n", + " [ 3.6, 5.2, 95.6],\n", + " [ 129.6, 24. , 9.2]])" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "macros*cal_per_macro" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "矩阵与向量相乘可以直接利用广播方式，方法简洁快速" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4.3 Matrix类型**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "以上运算的规律无论是向量和矩阵均为array类型，numpy也提供了基于一般线性代数运算规则的Matrix" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[ 0, 1, 2, 3, 4],\n", + " [ 5, 6, 7, 8, 9],\n", + " [10, 11, 12, 13, 14],\n", + " [15, 16, 17, 18, 19],\n", + " [20, 21, 22, 23, 24]])" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M = np.matrix(A)\n", + "M" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用matrix()函数可将array对象或list，tuple对象转换为matirx对象。" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[0],\n", + " [1],\n", + " [2],\n", + " [3],\n", + " [4]])" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v = np.matrix(v1).T \n", + "v" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(5, 1)" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "转置后，v为一个列向量" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[ 30],\n", + " [ 80],\n", + " [130],\n", + " [180],\n", + " [230]])" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M * v" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "矩阵乘以向量" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[30]])" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v.T * v" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "向量内积" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[ 150, 160, 170, 180, 190],\n", + " [ 400, 435, 470, 505, 540],\n", + " [ 650, 710, 770, 830, 890],\n", + " [ 900, 985, 1070, 1155, 1240],\n", + " [1150, 1260, 1370, 1480, 1590]])" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M * M" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "矩阵相乘" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[-1. , 0.6],\n", + " [ 1. , -0.4]])" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M = np.matrix([[2,3],[5,5]])\n", + "np.linalg.inv(M)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "linalg下的inv()函数，可以求矩阵的拟" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[-1. , 0.6],\n", + " [ 1. , -0.4]])" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "M.I" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "更方便的是使用matrix对象的I属性来求逆" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "-4.9999999999999982" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(M)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "可用linalg.det()来求matrix对象的行列式" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5. 数据处理**" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(77431, 7)" + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "6.1971096847515854" + ] + }, + "execution_count": 105, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data[:,3].mean() # np.mean(data[:,3])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用mean()函数计算第三列的均值" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "28.300000000000001" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data[:,3].max()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "计算最大值" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "-25.800000000000001" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data[:,3].min()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "最小值" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "479848.40000000002" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data[:,3].sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "求和" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 1, 2, 3, 4],\n", + " [ 5, 6, 7, 8, 9],\n", + " [10, 11, 12, 13, 14],\n", + " [15, 16, 17, 18, 19],\n", + " [20, 21, 22, 23, 24]])" + ] + }, + "execution_count": 109, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "15120" + ] + }, + "execution_count": 110, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A[1].prod()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "求积" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 66, 78,\n", + " 91, 105, 120, 136, 153, 171, 190, 210, 231, 253, 276, 300], dtype=int32)" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.cumsum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "累加求和" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "24" + ] + }, + "execution_count": 112, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.max()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "全局最大值" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([20, 21, 22, 23, 24])" + ] + }, + "execution_count": 113, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.max(axis=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "求0轴方向的向量的最大值" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 4, 9, 14, 19, 24])" + ] + }, + "execution_count": 114, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.max(axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "求1轴方向的向量的最大值" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**6. 维度变化**" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.37743668, 0.53359374, 0.1454808 , -0.58890887, 0.15780288],\n", + " [-0.20734565, 1.92773188, -0.15751806, 1.48274896, 1.14229955],\n", + " [ 0.34678178, 1.21245727, 0.523016 , -0.54786618, 2.06034313],\n", + " [ 0.01897576, 0.90174686, -1.27448633, -0.20114583, 0.02900983],\n", + " [-1.67857605, 1.11384125, 1.1096132 , -1.09811486, -0.08093909]])" + ] + }, + "execution_count": 115, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.random.randn(25)\n", + "B = A.reshape(5,5)\n", + "B" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用reshape()函数将矩阵变形" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(25,)" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(5, 5)" + ] + }, + "execution_count": 117, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-0.37743668, 5. , 5. , 5. , 0.15780288,\n", + " -0.20734565, 1.92773188, -0.15751806, 1.48274896, 1.14229955,\n", + " 0.34678178, 1.21245727, 0.523016 , -0.54786618, 2.06034313,\n", + " 0.01897576, 0.90174686, -1.27448633, -0.20114583, 0.02900983,\n", + " -1.67857605, 1.11384125, 1.1096132 , -1.09811486, -0.08093909])" + ] + }, + "execution_count": 118, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A[1:4] = 5\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.37743668, 5. , 5. , 5. , 0.15780288],\n", + " [-0.20734565, 1.92773188, -0.15751806, 1.48274896, 1.14229955],\n", + " [ 0.34678178, 1.21245727, 0.523016 , -0.54786618, 2.06034313],\n", + " [ 0.01897576, 0.90174686, -1.27448633, -0.20114583, 0.02900983],\n", + " [-1.67857605, 1.11384125, 1.1096132 , -1.09811486, -0.08093909]])" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "B只是A的一个视图(view)应用，A与B指向同一个array，因此改变A，则B也会改变，反之亦然" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.37743668, 5. , 5. , 5. , 0.15780288],\n", + " [-0.20734565, 1.92773188, -0.15751806, 1.48274896, 1.14229955],\n", + " [ 0.34678178, 1.21245727, 0.523016 , -0.54786618, 2.06034313],\n", + " [ 0.01897576, 0.90174686, -1.27448633, -0.20114583, 0.02900983],\n", + " [-1.67857605, 1.11384125, 1.1096132 , -1.09811486, -0.08093909]])" + ] + }, + "execution_count": 120, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = B.copy()\n", + "B[0,:] = 10\n", + "A" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "一般可利用copy()函数，制作一个副本，由于是复制了一个副本，因此B改变一般不会影响A" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-0.37743668, 5. , 5. , 5. , 0.15780288,\n", + " -0.20734565, 1.92773188, -0.15751806, 1.48274896, 1.14229955,\n", + " 0.34678178, 1.21245727, 0.523016 , -0.54786618, 2.06034313,\n", + " 0.01897576, 0.90174686, -1.27448633, -0.20114583, 0.02900983,\n", + " -1.67857605, 1.11384125, 1.1096132 , -1.09811486, -0.08093909])" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B = A.flatten()\n", + "B" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "利用flattern()函数，将高维数组降维成1维向量" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.37743668, 5. , 5. , 5. , 0.15780288],\n", + " [-0.20734565, 1.92773188, -0.15751806, 1.48274896, 1.14229955],\n", + " [ 0.34678178, 1.21245727, 0.523016 , -0.54786618, 2.06034313],\n", + " [ 0.01897576, 0.90174686, -1.27448633, -0.20114583, 0.02900983],\n", + " [-1.67857605, 1.11384125, 1.1096132 , -1.09811486, -0.08093909]])" + ] + }, + "execution_count": 122, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B[:5] = 10\n", + "A" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "注意降维是新生成1维向量" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5,\n", + " 5])" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([\n", + " [[1,2],[3,4]],\n", + " [[2,3],[4,5]]\n", + "])\n", + "a.repeat(3) #np.repeat(a,3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "重复每个数字三次形成一维数组" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[1, 2, 1, 2, 1, 2],\n", + " [3, 4, 3, 4, 3, 4]],\n", + "\n", + " [[2, 3, 2, 3, 2, 3],\n", + " [4, 5, 4, 5, 4, 5]]])" + ] + }, + "execution_count": 124, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.tile(a, 3) #注意，暂时不能a.tile(3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "每个向量内重复三次，形成的数组维度保持不变" + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4],\n", + " [5, 6]])" + ] + }, + "execution_count": 125, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([[1,2],[3,4]])\n", + "b = np.array([[5,6]])\n", + "np.concatenate((a, b), axis=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "按照0轴方向链接向量，1轴方向维度不变" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 5],\n", + " [3, 4, 6]])" + ] + }, + "execution_count": 126, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.concatenate((a, b.T), axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "按照1轴方向链接向量，0轴方向维度不变" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4],\n", + " [5, 6]])" + ] + }, + "execution_count": 127, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.vstack([a,b])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "竖向堆叠" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 5],\n", + " [3, 4, 6]])" + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.hstack([a,b.T])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "横向堆叠" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.0" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From c08faaa31f421ef7b8c230c42a2f7c3e888f1b85 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Mon, 13 Nov 2017 20:20:30 +0800 Subject: [PATCH 02/30] Create readme.md --- chapter4/figures/readme.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 chapter4/figures/readme.md diff --git a/chapter4/figures/readme.md b/chapter4/figures/readme.md new file mode 100644 index 000000000..92a080678 --- /dev/null +++ b/chapter4/figures/readme.md @@ -0,0 +1 @@ +for figures used in the tutorial. 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8.1 8.1 1 +2011 11 7 7.3 6.9 6.9 1 +2011 11 8 6.0 5.6 5.6 1 +2011 11 9 6.4 6.0 6.0 1 +2011 11 10 6.1 5.7 5.7 1 +2011 11 11 3.4 3.0 3.0 1 +2011 11 12 1.4 1.0 1.0 1 +2011 11 13 2.9 2.4 2.4 1 +2011 11 14 5.2 4.7 4.7 1 +2011 11 15 4.6 4.1 4.1 1 +2011 11 16 3.1 2.6 2.6 1 +2011 11 17 3.7 3.2 3.2 1 +2011 11 18 3.7 3.2 3.2 1 +2011 11 19 6.2 5.7 5.7 1 +2011 11 20 5.0 4.5 4.5 1 +2011 11 21 6.2 5.7 5.7 1 +2011 11 22 3.0 2.5 2.5 1 +2011 11 23 5.7 5.2 5.2 1 +2011 11 24 7.0 6.5 6.5 1 +2011 11 25 8.2 7.7 7.7 1 +2011 11 26 5.2 4.7 4.7 1 +2011 11 27 9.4 8.9 8.9 1 +2011 11 28 4.5 4.0 4.0 1 +2011 11 29 6.1 5.6 5.6 1 +2011 11 30 6.6 6.1 6.1 1 +2011 12 1 5.3 4.8 4.8 1 +2011 12 2 3.1 2.6 2.6 1 +2011 12 3 2.0 1.5 1.5 1 +2011 12 4 4.4 3.9 3.9 1 +2011 12 5 1.5 0.9 0.9 1 +2011 12 6 0.5 -0.1 -0.1 1 +2011 12 7 1.8 1.2 1.2 1 +2011 12 8 -0.4 -1.0 -1.0 1 +2011 12 9 2.9 2.3 2.3 1 +2011 12 10 2.3 1.7 1.7 1 +2011 12 11 0.3 -0.3 -0.3 1 +2011 12 12 2.9 2.3 2.3 1 +2011 12 13 3.7 3.1 3.1 1 +2011 12 14 4.1 3.5 3.5 1 +2011 12 15 3.1 2.5 2.5 1 +2011 12 16 2.9 2.3 2.3 1 +2011 12 17 2.1 1.5 1.5 1 +2011 12 18 0.9 0.3 0.3 1 +2011 12 19 0.3 -0.3 -0.3 1 +2011 12 20 0.9 0.3 0.3 1 +2011 12 21 0.4 -0.2 -0.2 1 +2011 12 22 -0.4 -1.0 -1.0 1 +2011 12 23 3.7 3.1 3.1 1 +2011 12 24 3.2 2.6 2.6 1 +2011 12 25 4.2 3.5 3.5 1 +2011 12 26 8.2 7.5 7.5 1 +2011 12 27 8.3 7.6 7.6 1 +2011 12 28 2.6 1.9 1.9 1 +2011 12 29 4.9 4.2 4.2 1 +2011 12 30 0.6 -0.1 -0.1 1 +2011 12 31 -2.6 -3.3 -3.3 1 \ No newline at end of file From 2301feee9e775feaf138ccd272e4c5e7997e068d Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Tue, 14 Nov 2017 08:57:39 +0800 Subject: [PATCH 05/30] Update 8.md --- chapter2/8.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/chapter2/8.md b/chapter2/8.md index e031a84a6..726212b7b 100644 --- a/chapter2/8.md +++ b/chapter2/8.md @@ -240,7 +240,7 @@ def get_ch_table(line): # 主程序 fh = open(r'd:\temp\idioms_correct.txt') text = fh.read() -chs = get_ch_table(text.replace(r'\n', '')) +chs = get_ch_table(text.replace('\n', '')) print(len(chs), chs) ``` From d7df6268f0ff0d426588e7c9630d289272e6e3ef Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Tue, 14 Nov 2017 09:35:03 +0800 Subject: [PATCH 06/30] Update 8.md --- chapter2/8.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/chapter2/8.md b/chapter2/8.md index 726212b7b..258d32214 100644 --- a/chapter2/8.md +++ b/chapter2/8.md @@ -278,7 +278,7 @@ idiom = '千钧一发' #假设抽取到了这个'成语' fh = open(r'd:\temp\idioms_correct.txt') text = fh.read() -chs = get_ch_table(text.replace(r'\n', '')) +chs = get_ch_table(text.replace('\n', '')) guess_ch_table = [ch for ch in idiom] while len(guess_ch_table) < 6: @@ -319,7 +319,7 @@ poems = fh.read().split() fh.close() for guess in guesses: - if guess in poems: + if ''.join(guess) in poems: print('答案是：' guess) ``` @@ -445,7 +445,7 @@ def idiom_robot(file_name): text = fh.read() idioms = text.split() idiom = random.choice(idioms) - chs = get_ch_table(text.replace(r'\n', '')) + chs = get_ch_table(text.replace('\n', '')) guess_ch_table = [ch for ch in idiom] while len(guess_ch_table) < 6: From 57d9a7e899da09ce670d96ab4580f199cbc3c295 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Tue, 14 Nov 2017 20:52:19 +0800 Subject: [PATCH 07/30] Update 6.md --- chapter2/6.md | 30 +++++++++--------------------- 1 file changed, 9 insertions(+), 21 deletions(-) diff --git a/chapter2/6.md b/chapter2/6.md index 3ba79e69a..761a9576e 100644 --- a/chapter2/6.md +++ b/chapter2/6.md @@ -18,26 +18,14 @@ while i < n: ```python # 正序输出单词示例2，假设确定会输入5个单词 -word1 = None -word2 = None -word3 = None -word4 = None -word5 = None -i = 0 -while i < 5: - word = input('请输入一个单词，回车结束') - if word1 == None: - word1 = word - elif word2 == None: - word2 = word - elif word3 == None: - word3 = word - elif word4 == None: - word4 = word - else: - word5 = word - i += 1 + +word1 = input('请输入一个单词，回车结束') +word2 = input('请输入一个单词，回车结束') +word3 = input('请输入一个单词，回车结束') +word4 = input('请输入一个单词，回车结束') +word5 = input('请输入一个单词，回车结束') + print(word5) print(word4) @@ -410,8 +398,8 @@ for i in range(500): outside_xs.append(x) outside_ys.append(y) # 画点 -p.circle(inside_x, inside_y, size=3, color = 'red') # circle为画圆函数，x，y为坐标，size为大小，color为颜色 -p.circle(outside_x, outside_y, size=3, color = 'blue') +p.circle(inside_xs, inside_ys, size=3, color = 'red') # circle为画圆函数，x，y为坐标，size为大小，color为颜色 +p.circle(outside_xs, outside_ys, size=3, color = 'blue') # 显示结果 show(p) From bc274b83bcee57a872d51448f583307bd0f7b05b Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Tue, 14 Nov 2017 21:01:02 +0800 Subject: [PATCH 08/30] Update 6.md --- chapter2/6.md | 1 + 1 file changed, 1 insertion(+) diff --git a/chapter2/6.md b/chapter2/6.md index 761a9576e..79ca59a2e 100644 --- a/chapter2/6.md +++ b/chapter2/6.md @@ -671,5 +671,6 @@ for i in range(10): - 写函数，返回一个list中所有数字的和 - 写函数，返回一个list中的最小值 - 写函数，返回某个元素/对象在一个list中的位置，如果不在，则返回-1. +- 写函数，可将两个相同长度的list，间隔插入，生成新的list。例如：给两个list，a=[1,2,3,4], b=[5,6,7,8]。则可以生成：[1,5,2,6,3,7,4,8]。 - 写函数，可求两个向量的夹角余弦值，向量可放在list中。主程序调用该函数。 - 挑战性习题：python语言老师为了激励学生学python，自费买了100个完全相同的Macbook Pro，分给三个班级，每个班级至少分5个，用穷举法计算共有多少种分法？ From cfd3ba8b145d2006b7c34eedcf82236b25077ec5 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Tue, 14 Nov 2017 21:03:45 +0800 Subject: [PATCH 09/30] Update 6.md --- chapter2/6.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/chapter2/6.md b/chapter2/6.md index 79ca59a2e..3d335cde7 100644 --- a/chapter2/6.md +++ b/chapter2/6.md @@ -668,8 +668,7 @@ for i in range(10): 6.8 习题 - 将前面几章用while循环的习题，用for循环实现，并尽量写成函数。 -- 写函数，返回一个list中所有数字的和 -- 写函数，返回一个list中的最小值 +- 写函数，返回一个list中的最大值，最小值，平均值。（不用内置的求和求函数） - 写函数，返回某个元素/对象在一个list中的位置，如果不在，则返回-1. - 写函数，可将两个相同长度的list，间隔插入，生成新的list。例如：给两个list，a=[1,2,3,4], b=[5,6,7,8]。则可以生成：[1,5,2,6,3,7,4,8]。 - 写函数，可求两个向量的夹角余弦值，向量可放在list中。主程序调用该函数。 From 43723be206ebee5165ea9ea981ba53fd933ea0f1 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Tue, 14 Nov 2017 21:13:13 +0800 Subject: [PATCH 10/30] Update 6.md --- chapter2/6.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/chapter2/6.md b/chapter2/6.md index 3d335cde7..3035ccd95 100644 --- a/chapter2/6.md +++ b/chapter2/6.md @@ -668,7 +668,7 @@ for i in range(10): 6.8 习题 - 将前面几章用while循环的习题，用for循环实现，并尽量写成函数。 -- 写函数，返回一个list中的最大值，最小值，平均值。（不用内置的求和求函数） +- 写函数，返回一个list中的最大值，最小值，平均值。（不用内置的求和求函数），以[1,2,-1,55,100,899,-10,3,12.5,5.8]为例。 - 写函数，返回某个元素/对象在一个list中的位置，如果不在，则返回-1. - 写函数，可将两个相同长度的list，间隔插入，生成新的list。例如：给两个list，a=[1,2,3,4], b=[5,6,7,8]。则可以生成：[1,5,2,6,3,7,4,8]。 - 写函数，可求两个向量的夹角余弦值，向量可放在list中。主程序调用该函数。 From 4cc7666658f4edc65f3a86ad84ccdf6648d86b74 Mon Sep 17 00:00:00 2001 From: zhushucheng <30313525+zhushucheng@users.noreply.github.com> Date: Wed, 15 Nov 2017 17:10:04 +0800 Subject: [PATCH 11/30] Create 1 --- chapter4/project_list/2017_map_for_travelling_abroad/1 | 1 + 1 file changed, 1 insertion(+) create mode 100644 chapter4/project_list/2017_map_for_travelling_abroad/1 diff --git a/chapter4/project_list/2017_map_for_travelling_abroad/1 b/chapter4/project_list/2017_map_for_travelling_abroad/1 new file mode 100644 index 000000000..8b1378917 --- /dev/null +++ b/chapter4/project_list/2017_map_for_travelling_abroad/1 @@ -0,0 +1 @@ + From 2a0160a54fbd1aed8f335173c1b56170f7dcf726 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Thu, 16 Nov 2017 11:06:36 +0800 Subject: [PATCH 12/30] Add files via upload --- .../pandas_Tutorial_4(visualization).ipynb | 2082 +++++++++++++++++ 1 file changed, 2082 insertions(+) create mode 100644 chapter4/pandas_Tutorial_4(visualization).ipynb diff --git a/chapter4/pandas_Tutorial_4(visualization).ipynb b/chapter4/pandas_Tutorial_4(visualization).ipynb new file mode 100644 index 000000000..6c8d56d98 --- /dev/null +++ b/chapter4/pandas_Tutorial_4(visualization).ipynb @@ -0,0 +1,2082 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Pandas统计分析入门（4）\n", + "- 转载注明转自：https://github.com/liupengyuan/\n", + "- ## Visualization基础" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "from pandas import Series, DataFrame\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "#import seaborn as sns #即使不适用seaborn内的功能，也可以使绘图自动带有seaborn风格" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " 美国 日本 德国\n", + "2007 1000 500 300\n", + "2008 1500 900 400\n", + "2009 1200 800 350\n", + "2010 1700 1000 500\n", + "2011 1400 800 400\n", + "2012 1800 1200 450\n", + "2013 1000 300 350\n", + "2014 1200 350 300\n", + "2015 1300 500 400\n", + "2016 2000 700 800" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# df = pd.read_excel('https://github.com/liupengyuan/python_tutorial/blob/master/chapter4/countrys_freq.xlsx?raw=true')\n", + "df = pd.read_excel('countrys_freq.xlsx')\n", + "df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用read_excel()函数读入一个表格" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1. pandas定制绘图初步" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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AErTWGUqpTKXUAIwweyLwtv3lV+6N3+re9NDiZcpv/3gDd8zcwAd39GF4p+ak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\n0bph65LpwbXlkqaYcxpe7QB97oJrXrF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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df.plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 直接利用plot()绘图。该图的左上角图例处，显示中文有些问题" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from pylab import mpl\n", + "mpl.rcParams['font.sans-serif'] = ['FangSong'] # 指定默认字体 plt.rcParams['font.sans-serif'] = ['FangSong'] 前者为全局影响，后者影响当前\n", + "# mpl.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题 plt.rcParams['axes.unicode_minus'] = False" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 为正确显示中文，在程序头部加入以上代码(windows平台)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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f7kln2oCOFlvVuypuHwhe/FErn3x1WqwuyicHR9uvjfWfZwp4p44V1hTujTKN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\nRlh6q+PSIZXm8LDGrTlsb2J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HKCgp4/WpUbjZcJcvxb5UaOxYmw5nkJhZwJwrOrtEV2uTKgRlRhNPrTpg8+GT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\nH8GYsDFc3v5yArzUHZ7DRM+A/90PKXs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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df.index.name = '时间'\n", + "df.columns.name = '国家'\n", + "df.plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 为df的index及columns设置name后的效果。index的name显示为x坐标轴的名称。由于是多列，columns的name显示为图例名称" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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V0PZUWWvmrlVb6RPky98Wnn442ekopViYGMmGgyUUlNfaMUIh7G/tzgJKq80s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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df.plot(title = '十年来美国日本德国出现频次对比',figsize=(8,6))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用title参数，为图加上标题\n", + "- 利用figsize参数，调整图大小" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- pandas内置的plot()函数还有很多参数，详细使用可参考http://pandas.pydata.org/pandas-docs/stable/visualization.html\n", + "- 一般的图形可视化，用pandas内置的plot函数已经足够，如果需要进一步定义，则可以利用matplotlib" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['bmh',\n", + " 'classic',\n", + " 'dark_background',\n", + " 'fivethirtyeight',\n", + " 'ggplot',\n", + " 'grayscale',\n", + " 'seaborn-bright',\n", + " 'seaborn-colorblind',\n", + " 'seaborn-dark-palette',\n", + " 'seaborn-dark',\n", + " 'seaborn-darkgrid',\n", + " 'seaborn-deep',\n", + " 'seaborn-muted',\n", + " 'seaborn-notebook',\n", + " 'seaborn-paper',\n", + " 'seaborn-pastel',\n", + " 'seaborn-poster',\n", + " 'seaborn-talk',\n", + " 'seaborn-ticks',\n", + " 'seaborn-white',\n", + " 'seaborn-whitegrid',\n", + " 'seaborn']" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt.style.available" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用plt.style.available，查看目前可用的风格类型" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# plt.style.use(\"ggplot\") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "使用ggplot风格" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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V0PZUWWvmrlVb6RPky98Wnn442ekopViYGMmGgyUUlNfaMUIh7G/tzgJKq80s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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df.plot(title = '十年来美国日本德国出现频次对比',figsize=(8,6))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2. matplotlib绘图基础\n", + "将pandas绘图与matplotlib绘图结合可以很方便的定制可视化实例。这里先介绍matplotlib基础\n", + "\n", + "Matplotlib is an excellent 2D and 3D graphics library for generating scientific figures.\n", + "\n", + "仅介绍matplotblib最基础的使用，matplotlib绘图的进一步详细使用，可参考官方网站文档，特别是http://matplotlib.org/users/pyplot_tutorial.html" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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y9cUXX+DixYsYOXIkXFxcYGRkJPQjGT9+PFJSUtRO0lgRfLMlgOtfYWNjIzSj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\nwcHBgZKSEo4cOcLQoUOb7XgHBgayefNm/Pz8zMFGYGAghw4dIjY2ttnjcnJ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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "width": 800 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.core.display import Image, display\n", + "display(Image(filename='figures/anatomy1.png', width=800))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**1. 概念与布局**" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "x = np.linspace(0, 5, 10)\n", + "y = x ** 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "数据" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 创建一个图形画布\n", + "fig = plt.figure(figsize = (6,4), dpi=100) \n", + "# 创建一个坐标轴(axes)并设置图形大小比例\n", + "axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # 坐标轴图形大小：左，下，右（宽），上（高） (0到1，表示比例位置)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用figure()函数，创建了一个画布对象，并赋值给fig，接下来的绘图将基于这个画布对象fig\n", + "- 利用figure()函数中的figsize参数，设置了画布大小，如果不设置大小，默认为(6,4)inch\n", + "- 利用figure()函数中的dpi参数，设置分辨率为100，即dot per inch，除非需要很高分辨率，一般情况可以不用设置这个参数\n", + "- 图形不能直接绘制在画布对象fig上，而是先要建立一个坐标系axes\n", + "- 由于仅仅建立了一个画布对象fig以及坐标系axes，因此是空的图" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure() \n", + "axes = fig.add_axes([0.1, 0.1, 0.8, 0.8])\n", + "\n", + "axes.plot(x, y, 'r')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 在axes内利用plot()函数画线，其中x,y均为序列或者array类型，一一对应。\n", + "- 在axes内利用set()函数及set函数的变形，加x,y轴标签及抬头" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure()\n", + "\n", + "axes1 = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # 第一个坐标轴 \n", + "axes2 = fig.add_axes([0.2, 0.5, 0.4, 0.3]) # 第二个坐标轴\n", + "\n", + "# 第一个坐标轴下作图\n", + "axes1.plot(x, y, 'r')\n", + "\n", + "# 第二个坐标轴下作图\n", + "axes2.plot(y, x, 'g')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 可以利用add_axed()函数，在同一个figure中，加入多个坐标轴，多个坐标轴可以独立绘图" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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MICLih8ayiD+aJCsiIuKJirCIiIgnxoa4ldEYkwD8ks7LigC7Qhrk7ClTYJQp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\nzMwsiTdhMzOzJH8ARMb7U9J0UEQAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8,6)) \n", + "ax1 = fig.add_subplot(2,2,1)\n", + "ax1.plot(x,y,'r')\n", + "ax2 = fig.add_subplot(2,2,2)\n", + "ax2.plot(y,x,'b')\n", + "ax3 = fig.add_subplot(2,2,3)\n", + "ax3.plot(x,y,'k')\n", + "ax4 = fig.add_subplot(2,2,4)\n", + "ax4.plot(y,x,'g')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 建立一个画布对象，大小为(8,6)\n", + "- 利用add_subplot()方法，对画布fig进行分区，并加入子图，每个子图单独一个坐标系，画布的分区类似于一个2维数组\n", + "- 三个数字依次为：2行，2列，从左上角开始数，第几个图形\n", + "- 可以在子图中分别进行绘图" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "axes type is, shape is (2, 2).\n" + ] + }, + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(nrows=2, ncols=2) # axes 是ndarray类型 里面是2*2个axes对象\n", + "print('axes type is{}, shape is {}.'.format(type(axes), axes.shape))\n", + "\n", + "for ax in axes.flatten()[:3]:\n", + " ax.plot(x, y, 'r')\n", + "\n", + "axes[1][1].plot(x, y, 'g')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用plt.subplots()函数，定义1个figure，以及1或者多个子图\n", + "- 1或者多个子图返回在一个ndarray.array中，本例存入axes变量中\n", + "- 可以利用循环依次取出各个子图，并分别绘图，也可以利用下标取出进行绘图" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2) # axes 是ndarray类型 里面是2*2个axes对象\n", + "\n", + "ax1.plot(x, y, 'r')\n", + "ax2.plot(x, y, 'g')\n", + "ax3.plot(x, y, 'b')\n", + "ax4.plot(x, y, 'y')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "也可以按照数组元素的顺序，依次取出" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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Jh6nfT+XKN6/kxGInsuD2BVEZTqARlBSVFSvguutg40Y3emrVyndFIqE05PMh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\npjbQOpZfg/yK9V5SHx0STX3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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(nrows=2, ncols=2) \n", + "\n", + "for ax in axes.flatten()[:3]:\n", + " ax.plot(x, y, 'r')\n", + "\n", + "axes[1][1].plot(x, y, 'g')\n", + "\n", + "fig.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "用figure对象的tight_layout()方法可解决轴有重叠的问题，这个方法会自动地调节图形的位置" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure()\n", + "\n", + "ax1 = fig.add_subplot(221)\n", + "ax2 = fig.add_subplot(223)\n", + "ax3 = fig.add_subplot(1,2,2)\n", + "\n", + "ax1.plot(x, x**2, 'r')\n", + "ax2.plot(x, x**2, 'g')\n", + "ax3.plot(x, x**2, 'b')\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 加入三个子图，前两个是2行2列的第1，第3个位置；以及一个1行2列，第二个位置的子图\n", + "- add_subplot()方法内的参数可以用逗号分隔，也可以省略" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2. 图例、标签及标题(Legends, labels and titles)**" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(x,x**2)\n", + "ax.set_xlabel('x')\n", + "ax.set_ylabel('y')\n", + "ax.set_title('title')\n", + "# ax.set(xlabel='xx', ylabel='yy', title='title'); #与上面三个等价" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用set_xlabel(), ax.set_ylabel(), ax.set_title()这三个函数来设置x轴标签，y轴标签，图表抬头(标题)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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t9ayuqO8+4ycxwRhfmMmMsUOYVJzNpKJsDi3KJm9QSsDJByYVgsje1GyAl2+B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\nIiKACkFERMJUCCIiAqgQREQk7P8DWt/wqovf3wQAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(x, x**2)\n", + "ax.plot(x, x**3)\n", + "ax.legend(('curve1', 'curve2'))\n", + "ax.set(xlabel='xx', ylabel='yy', title='title');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "利用legend()函数，由一个列表或元组，将图例文字传入" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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LM5g5fhhHFGdxRFEWhxdlkZueFHDyoUmFIHIgNRvh5Vvh7T8CBsd8CU6+BnLH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\ngoiIRPx/n6Hr9m6fB4cAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(x, x**2, label=\"curve1\")\n", + "ax.plot(x, x**3, label=\"curve2\")\n", + "ax.legend(loc=5)\n", + "ax.set(xlabel='xx', ylabel='yy', title='title');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 也可以利用plot()的label参数，设置对应图例信息\n", + "- 用legend()函数，将图例信息显示，同时还可以利用loc参数，设定图例显示位置，默认为loc=0\n", + "- ax.legend(loc=0) # let matplotlib decide the optimal location\n", + "- ax.legend(loc=1) # upper right corner\n", + "- ax.legend(loc=2) # upper left corner\n", + "- ax.legend(loc=3) # lower left corner\n", + "- ax.legend(loc=4) # lower right corner\n", + "- 有关legend位置，可参见：http://matplotlib.org/users/legend_guide.html#legend-location" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3. 字体**" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from pylab import mpl\n", + "mpl.rcParams['font.sans-serif'] = ['FangSong']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "如果要显示汉字，则与前一样需要设置全局参数中的字体" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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JCoJB5u5s3t7Jcxt2HfxXvb2drt4oAOWF2Rw1rpiza8YyY1wxR44tpiBbh7n+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\nEUCBICIiMf8f/pMoaw+OwsIAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(x, x**2, label=\"线1\")\n", + "ax.plot(x, x**3, label=\"线2\")\n", + "ax.legend(loc=5)\n", + "ax.set(xlabel='x轴', ylabel='y轴', title='标题');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "显示中文与之前的设置一样（windows平台）" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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E9tVYDa/Ph1fvgcYqGH46TPsmlE7ynSxhVdQ1B8Wwx1dtU3DkUm5GCscNyg+X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\nGCIiEhEVhoiIRESFISIiEVFhiIhIRP4/jkeX/DGTrlEAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "ax.plot(x, x**2, label=r\"$y = \\alpha^2$\")\n", + "ax.plot(x, x**3, label=r\"$y = \\alpha^3$\")\n", + "ax.legend()\n", + "ax.set_xlabel(r'$\\alpha$', fontsize=18)\n", + "ax.set_ylabel(r'$y$', fontsize=18)\n", + "ax.set_title(r\"$\\alpha^2$\");" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "- 利用fontsize参数，可设置字体大小\n", + "- 可以利用latex公式生成各类标题／标签\n", + "- latex公式的一个简易基础教程可参见：https://github.com/liupengyuan/python_tutorial/tree/master/chapter5" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Update the matplotlib configuration parameters:\n", + "plt.rcParams.update({'font.size': 16, 'font.family': 'serif'})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "更新字体设置" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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NDfUw/WpY9Hc44z44+uqwK5J2pLARkfA11MNfr4WFz8CEe+CYa8OuSNqZwkZE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\nVlVLaUUt6z8uZUP5F0GvZNu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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "ax.plot(x, x**2, label=r\"$y = \\alpha^2$\")\n", + "ax.plot(x, x**3, label=r\"$y = \\alpha^3$\")\n", + "ax.legend(loc=2) # upper left corner\n", + "ax.set_xlabel(r'$\\alpha$')\n", + "ax.set_ylabel(r'$y$')\n", + "ax.set_title('title', fontsize = 20);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "全局设置下，仍然可以对各个标签等字体进行单独设置" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4. 颜色，线型(linetypes)，线宽(linewidths)**" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(x, x**2, color = 'blue') # blue line\n", + "ax.plot(x, x**3, 'g') # green line" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 可以在plot()函数中，设置color参数\n", + "- color参数关键字也可以省略，值也可以简写，如green简写为g，blue可以简写为b" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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FW/OKrNHj55WNbhaXOjl2vplu2RE8+WAGs8clWHsg1adHn9XWQk4O3Hwz9Osn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\nz9vTuPf6RJLjLdom6PXChx+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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "ax.plot(x, x+1, color=\"red\", alpha=0.5) # 红色，半透明\n", + "ax.plot(x, x+2, color=\"#1155dd\") # RGB值，对应红绿蓝，dd最大，因此颜色偏蓝\n", + "line = ax.plot(x, x+3, color=\"#15cc55\") # 偏绿" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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YPj3YsmvoUI0A9gu5ucGiODub7jGh9Ojh1I7borh3b5XJCAASykKItoo97axn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\ntZAvo6PRp7hr3FurhoboSf3Rj2ZXFwAAqF3lvJnvQUk/lvQ1SbdaetP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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(12,6))\n", + "\n", + "# 线宽\n", + "ax.plot(x, x+1, color=\"blue\", linewidth=0.25)\n", + "ax.plot(x, x+2, color=\"blue\", linewidth=0.50)\n", + "ax.plot(x, x+3, color=\"blue\", linewidth=1.00)\n", + "ax.plot(x, x+4, color=\"blue\", linewidth=2.00)\n", + "\n", + "# 线型 ‘-‘, ‘--’, ‘-.’, ‘:’, ‘steps’\n", + "ax.plot(x, x+5, color=\"red\", lw=2, linestyle='-')\n", + "ax.plot(x, x+6, color=\"red\", lw=2, ls='-.')\n", + "ax.plot(x, x+7, color=\"red\", lw=2, ls=':')\n", + "ax.plot(x, x+8, \"r\", lw=2, ls='steps')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "参数：linewidth, linestyle，可以简写为：lw, ls。用于设置线宽及线型" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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ZYjLByqtXhqadKWnamVwFvAHYWqS9421H2qAuVUMwCCiqKULNlhpoKjRISafSh8SO/t9C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9jEscSExwTVjmenZAOBoR7/mvuvQc/X2t3ieF0vpHtVH65mVdkqfKU+rsi7grSBaTyx9glu/OuN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\n+hqSYpI43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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(12,6))\n", + "# 标记符号: marker = '+', 'o', '*', 's', ',', '.', '1', '2', '3', '4', ...\n", + "ax.plot(x, x+ 9, color=\"green\", lw=2, ls='--', marker='+')\n", + "ax.plot(x, x+10, color=\"green\", lw=2, ls='--', marker='o')\n", + "ax.plot(x, x+11, color=\"green\", lw=2, ls='--', marker='s')\n", + "ax.plot(x, x+12, color=\"green\", lw=2, ls='--', marker='*')\n", + "\n", + "# 标记符号\n", + "ax.plot(x, x+13, color=\"purple\", lw=1, ls='-', marker='o', markersize=2)\n", + "ax.plot(x, x+14, color=\"purple\", lw=1, ls='-', marker='o', markersize=4)\n", + "ax.plot(x, x+15, color=\"purple\", lw=1, ls='-', marker='o', markersize=8, markerfacecolor=\"red\")\n", + "ax.plot(x, x+16, color=\"purple\", lw=1, ls='-', marker='s', markersize=8, \n", + " markerfacecolor=\"yellow\", markeredgewidth=2, markeredgecolor=\"blue\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 参数marker可设置标记的符号\n", + "- 还可以设置marker自身的颜色，框线宽，框线颜色" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 1\n" + ] + }, + { + "data": { + "image/png": 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AAAA+hQEMAAAAn8IABgAAgE9hAAMAAMCnMIABAMgBtm/frmeffVa7du1yOgXwegxgAAAc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\nRERo1qxZkqQuXbooODhY1ap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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(12,6))\n", + "\n", + "line = ax.plot(x, x+1, color=\"black\", lw=1.50)\n", + "print(type(line), len(line))\n", + "line[0].set_dashes([5, 10, 100, 10]) # 格式: 线长度，空白长度，线长度，空白长度..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "还可以利用set_dashes()函数，设置dashes线的具体形式" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5. 控制坐标轴(axis)**" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "plt.rcParams.update({'font.size': 16, 'font.family': 'FangSong'})" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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OOceEYdCsA/Q9I+xIMk5VL0XKYh6vA4Zj41BG5GO9gZ1ziZjzLnzyIGzbnOw9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\ni9X2ab6GhhMWn0JkQhqh8WlYIh3YrTbs/nsthBBCiM8YjOK5Azi1OWT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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 3, figsize=(12, 4))\n", + "\n", + "axes[0].plot(x, x**2, x, x**3)\n", + "axes[0].set_title(\"缺省坐标轴（axes）范围\")\n", + "\n", + "axes[1].plot(x, x**2, x, x**3)\n", + "axes[1].axis('tight')\n", + "axes[1].set_title(\"紧致坐标轴范围\")\n", + "\n", + "axes[2].plot(x, x**2, x, x**3)\n", + "axes[2].set_ylim([0, 60])\n", + "axes[2].set_xlim([2, 5])\n", + "axes[2].set_title(\"定制坐标轴范围\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用axis('tight')，可讲坐标轴范围设置为紧致(tight)，这也正是缺省时的设置\n", + "- 还可以利用set_xlim()，set_ylim()函数，设定坐标的起点终点" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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boRhjEjly9gg9wnsQHhFOg7IN+KzVZ5QqUMrtsNyTMDF+3jxnNWLCxPhGjeCl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\nReQ9EVkvIudFREWkTDLXlhKRr0XktIi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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(10,4))\n", + " \n", + "axes[0].plot(x, x**2,'r', x, np.exp(x), 'g')\n", + "axes[0].set_title(\"正常比例\")\n", + "\n", + "axes[1].plot(x, x**2, 'r', x, np.exp(x), 'g')\n", + "axes[1].set_yscale(\"log\")\n", + "axes[1].set_title(\"对数比例 (y)\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用set_yscale('log')可以将y轴设为对数比例绘图，即画出x, log(y)的图形\n", + "- set_xscale('log')设x轴" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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Oml4Kxtwth3WPQqq19zGNhxQth3IC1EwNp1YZU7m8Y0dHendQ21YIcO2pINj5\nULe9PU33YPftKjKlJhb0wvU34UHj5GR4FPZERAbSsq73Wne7tvXe3zAPDiha627SrFDKlNHRncuz\noyPje936BLjtu4NciqZdGXJDDHEN1TFmTEqwT32SfeoT7DOp8JxgRuF1fVLj5KSkFPZERAratwZr\n3T3kw13rht7762b03KVi/kl+YWMZd7K5PE270j6s7UyxrT3N9iDM9YS6NDt2pRlihmNqbZx96hNM\nry8ObcHrINxNr0+QjCnEydhT2BORiauz2V+OLfTcNb3Ye3+yIVjr7mQf7qYfqrXuyli6O8f29vQb\nx8IVBbjXd6Zo7szscXID+G91Y12c6fXJoDfOh7YZkxI9bZOSTK9LTPh7r0p5U9gTkYmjYwdsWtkz\nY3braqDop36stmitu5Ng5hEQUU9MmHJ5R2tnhuaODE27/PP2dt8b93phokPwPJSlRsAvAtxYn+j3\ncuqMosuqjXUJjYuTiqCwJyKVJZ+D1vXQ9LKfUNH0kn+9/UXoau59bDQOc4/rCXezj4aqeDh1TxD5\nvKOtK8uOjjQ7dmXY0RE8dqVp7vt6V4aWzsyQL6VGI8b0ukRw2bRoPNzunjn/PLU2TpVCnEwgCnsi\nMj6ld/lbjPUNdTte6b2+XbF4HexzGMwPbkM29ziIVY9t3RUmn3fsTGWDkJahuSO9uwdux640Ozoy\nu4Pbjg4f3oY6maGgoTrGtLo402rjTK2NM71PgCuMiZtaG9f9VUX6obAnIuXLOT9pojjMFZ53vjbw\n+ybN8feSbTwkeASv62dpzN0eOOfYmere3bvWN7j58NbTK9fSkRnyciIFk5JVTKtL7A5vhdfT6oLt\n2sTucDelNq5LqSJ7SWFPRMLXnYHmNf2Hukx7/++JxmHqgT1Bbvqh/vW0g7R4cRHnHO3pbpp3ZXpd\nOvVBLt2r1625w2/v6cb3fdUnqnqCWq/g1jvENdYlmFIT12QGkTGmsCciY6er5Y2XXZtegua1ve8b\nW6x6CjQe+saeusn7QXRi/ReW6c7T1pWlrStDW1eW1s5sr2f/OlN0SdU/9nQ3hr7qElVBcPO9a9Nq\nE0wtvO4nxCWqNIlFpJxNrP8pRWT05fPQtrEo0BWFuo7tA7zJ/Jp1fS+7Nh4CtY1jWf2oy+d9T9vO\n4rDWJ7y1dfZu29mVpbUrS2dmgEC8BzXx6O6Q1hhcOp1aF6exNlEU6hK7w5vWghOpLAp7IjIymU4/\nGaLvZddlfe9BAAAPQ0lEQVQdL0N3qv/3xGr6H0s39UCIJce2/r2Uyub69K5ldveu9WrvytIW7Gvt\n8sFtmEPcdotGjIbqGJOrY0yqjjG5JrZ7u6E6RkNN3E9m6DP+TXdjEJnYFPZEZGDO+d64ppf80iXF\noa5tw8Dvq5vZf6ibNAci5TNeK5d37OwqCmXFoa2zuK3Qu9bT25buHt6l0WJ1iSofzoLH5Br/mFQd\nY3J1fHdb32PqElWYJpiIyDAp7IlMZPmcH0fX0QSdO3ywa1nbe1xdqq3/90aqYOoBRYGu8DjI33li\nFDnn6Mzk6Eh3057uZlequ/frTDftqW52pX37rpTf15HuZmeqJ8C1p7pHXEMsajRUx/vpXSsEtiom\nBz1tDUXHTKqOaXapiIwphT2RSpLt6glunU3+jhGF1507ivYFr7ta6HUHif4kGmB6P2PppuwP0diQ\nS3POke7O7w5gvcJYsN3f692PVM/rjnT3iC+FFjPzM0kLoayndy3Wp3etKNQFz9WxqHrZRGRcUNgT\nKVf5PKRae4ezAUNc8DrbOfzPqZ4CNdOgptE/T57nQ930Q6HxELLJaXRkcj6AZYJesh3ddGze3iuA\n9Xrdz3ZHunvYS3oMWnYsSm2iivpkFXWJKmoTUeoSMeqTfV7Ho9Ql/SXQuuD4QmirT8a0CK+IVLyy\nCHtmFgG+AHwK2B/YDtwOXOmc6xirc4iMqu50P8FtsBDXPPByJANwkTjdySlkk1PJxKeSik+mKzaF\nzqoGdkUn0x5poM0m0WoNtFBPi6ulI2t0ZXOksnm6dubo2N5NxzPd7Ep30Z5auVdj0/qKRyPU7Q5n\nVdQnqqhL+teFIFYb9231wTH+eB/e6pJV1MV9mNPtrkREhqYswh5wNfB54C7g+8DCYHuxmZ3mnBvK\nT5tSnENkaJyD9M7evWpFwc11NJHvaMIF+yKdO4hkdw37YzojtbsDWguTaHb17HCTaMrX8Xqujq25\nOprz9eygnhZXzy6qoXMoPVUO2Bk8BheNGLXxKPVB71htwveU1Rf1pr0hkBVeByGuLuht03psIiJj\nL/SwZ2aHA5cBy5xz5xa1rwWuAT4E3Dra55Dxy+W6yWZSZNNddKe7yGa7yGVSwaOLXCZNPpsin+0i\nl03jsmlcd8o/smnf49adglwG605jucIjQySfJpLLEM3711W5FLXdbdTm2qhi4MH9BvSNNVkXpYV6\nml3woJ5mNyl4Ln49iR2unlbqyQ7hn2i8KkKyKkJtPEpjLEoyeFTHolTH/XMiFvHbQVvvYyIkq6Ik\n41GSVdFe4aw+ESMZi2hsmojIOBZ62APOx/9s/GGf9huAbwMXsOegVopzlC3nHHkHeefIO4fb/do/\nu3ywnc8H2/mi7Twu7/yzc+TzDufyuHxhO797nz/OH4vLk8/7/a7wnmCf3/ZteVc4H+Dy5HLduGwX\n+W4fsOj2wYruDC6bwnI+XO0OU7k0kVway2eI5tJE8hmq8hki+SxVLk1VPkOVyxJzPc9xssTIEncZ\n4nQTsxxxID7G35ddLtkrtLXge91anO9pa4800FU1mY6qyaTjU+iOTaI6UUUyCF6FsJUMAtgBsSiH\nx6JUxyK723odUwhmfd6rMWciIjKYcgh7xwB54PHiRudcysxWBfvH4hyj6plHf8XM+y8DwHAYDnAY\nYK6wDRHy+B/dLjiu5/hCewRHNGiP4IhY6Qa9jytBxsk7I02MDDEyFiNDnG7zr7vNR8PuSIKcxeiO\nxMlF4uQjcXKRBPlonHwkgYvGyVclcNEERBO4qoS/92pVEqtKYlVxiCWJxKqhdhrR2kYSyRqq4xES\nVVH2i0dZUBTAElURIgphIiJSBsoh7M0Gmpxz6X72bQKON7O4cy5T6nOY2SXAJQDz5s0bWfVDlM+m\naaS1/50lzgT5ojjZN1q+MUIGx1h/EROcRXYfCwTH9Wz3vNe35S1KLhInZ3Fy0SBQRWLkownykTiu\nKomLxnFBoLJoAqoSQahKYDH/HIklicSTRGIJorFqorEk0bh/VMWricWrqUokiCVqqKqKUR2JUF3a\nP0YREZGKUA5hrwboL6QBpIqOGSzsjegczrnrgesBlixZMqrdY4e85Qy2H/oXzAyLGBGLEDHDIsGz\nRYhEosG+omMifh+YXxSs73PxviCwaY6iiIiIFJRD2OsE9hlgX7LomNE+x6hKVteSrK4NswQRERGZ\ngMqhE2gz0GhmiX72zcFfnh2sV69U5xARERGpOOUQ9p7A13FscaOZJYFFwIoxOoeIiIhIxSmHsHcb\nfoXXy/u0X4wfZ3dLocHMYma2wMz6zqYY8jlEREREJpLQx+w551ab2XXApWa2DLiPnrtfLKf3+nhz\ngOeD9lNGeA4RERGRCSP0sBe4HFiHXwbl3UATcC3+vrZDvc1ZKc4hIiIiUlHMuQm6IG8fS5YscStW\naGifiIiIlD8zW+mcWzKkYxX2PDPbDqwPuw4JRSO+J1hkNFTS369K+loqib4v5Wcsvif7OeemD+VA\nhT2Z8MxsxVB/OxIZrkr6+1VJX0sl0fel/JTb96QcZuOKiIiIyChR2BMRERGpYAp7IsH9kUVGSSX9\n/aqkr6WS6PtSfsrqe6IxeyIiIiIVTD17IiIiIv0wswPNLNGn7Swzm7wX57x47ysbHoU9ERERkf4d\nB/x9n7bFwPl7cc5jzWzRXrx/2BT2RERERPp3FvDffdqOBG4sbJjZvsM8ZwewcS/rGpZyuV2aiIiI\nDJGZTQKuAM7E3zc+DmwFfu2cuzTM2iqFmR0CbHLOPV/UdjAQBS40s/nAEcBs4Nhhnn6+mS3Af+/m\nA4cDDzvnbhz8bSOjnj2ZkMxssZndZWYtZtZqZnea2VQzm2NmKTP7cNg1yvhnZieZ2f+a2c7g79Uq\nMzsn7LqGwsy+bmYdZnbtAPuvMbOsmR021rUJAPfj7wX/S+CLwOeA/8QHDymNi4CrAMzstKDtEuDH\nQBtwK5AO2obrfcBCfC/fA8CVwJ17We+A1LMnE46ZnQ/8DHga+Ab+t6rPAxvw/yZe5o3d9iLDYman\nA/cCL+L/nmWBLwC3m9mhzrk1YdY3BL8DTgIuNbNrnXMvFXaY2eHAZ4DrnHPPhVXgRGVmRwDHAP/q\nnPtK2PVUIjN7E/CSc64t6OH7jpmdDSwAtjrnvh+0dzjnVg3hfBHnXL6o6QfOuTG7xZ2WXpEJxcwO\nAJ4FVgMnOedSQfsfgKnA/sBHnHPLQitSxj0ziwCv4n/rX+yc6wra34PvibnAOXdLiCUOiZn9FfAo\n8AHn3B1F7fcDRwEHO+daw6pvojKzOvwvq/Px358HgF8DK5x+qO+14M/3cWAzsAb4a/wvPhcBPwRO\nBGYCpwGXOue2DuGcf++c+5aZRYFrgNvwl95nAu8H/s4598IofDmALuPKxPMFIAlcVgh6gTX439ie\nA+4KozCpKH+F/8XhmkLQC2SD5643vKM8FXrtFhQagsvQpwJXKOiFpgb/C+uV+OAwHR/6/sfMpoZZ\nWCVwzu0CPooPeSvwV37iwCPOuR3OubuB44H0UIJe4CwzexD/8yUOvBN/GTcL7AO8NMh795ou48pE\n8x7gFefcnwfY/zX9ZiwlcHz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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 4))\n", + "\n", + "ax.plot(x, x**2, x, x**3, lw=2)\n", + "\n", + "#设置x轴记号(tick)位置\n", + "ax.set_xticks([1, 2.5, 3, 4, 5])\n", + "\n", + "#每个记号标签\n", + "ax.set_xticklabels([r'$\\alpha$', r'$\\beta$', r'$\\gamma$', r'$\\delta$', '终点'], fontsize=18)\n", + "\n", + "#设置y轴记号(tick)位置\n", + "yticks = [0, 50, 100, 150] \n", + "ax.set_yticks(yticks)\n", + "\n", + "ax.set_yticklabels([\"${:.1f}$\".format(y) for y in yticks], fontsize=18); " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用set_xticks(...)设置x轴记号位置，参数是一个序列，代表各个记号的坐标\n", + "- 利用set_xticklabels(...)设置x轴记号标签，参数是一个序列，与上面的序列对应\n", + "- 类似的有set_yticks(), set_yticklabels()，进行y轴设置" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1, 1) \n", + "ax.plot(x, x**2, x, np.exp(x))\n", + "\n", + "# 标签与坐标数字之间的距离\n", + "ax.xaxis.labelpad = 30\n", + "ax.yaxis.labelpad = 30\n", + "\n", + "ax.set_xlabel(\"x\")\n", + "ax.set_ylabel(\"y\")\n", + "\n", + "# 坐标轴与坐标数字之间的距离设置，并不常用，缺省为3\n", + "# plt.rcParams['xtick.major.pad'] = 15\n", + "# plt.rcParams['ytick.major.pad'] = 15" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "ax.plot(x, x**2, lw=2, color=\"blue\")\n", + "ax.set_ylabel(r\"area $(m^2)$\", fontsize=18, color=\"blue\")\n", + "for label in ax.get_yticklabels():\n", + " label.set_color(\"blue\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 可以利用子图的get_yticklabels()方法，取得所有y轴的标签的表，其中每一个标签是一个matplotlib的Text对象\n", + "- 利用Text对象的set_color()方法，可以设置y轴标签的颜色（含数字）" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(10,3))\n", + "\n", + "#设置网格\n", + "axes[0].plot(x, x**2, x, x**3, lw=2)\n", + "axes[0].grid() #grid(True)\n", + "\n", + "#对网格进行定制\n", + "axes[1].plot(x, x**2, x, x**3, lw=2)\n", + "axes[1].grid(color='b', alpha=0.5, linestyle='--', linewidth=0.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用grid()打开网格\n", + "- 也可以直接利用grid()函数，对网格线进行设置，参数与之前对线的设置类似，grid()函数进一步设置，请参考官方文档" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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FfgMOxrbF+hNoi+oPoecOwlauto7rR1YkOYpQduGlBf488KQqFS68jDdPjs65suTl2WrU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\nozlhrMlxWWiHjs0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BRxdm6VK44AKYO9eCvO02uPXWFKohcemiQo3HRboAR6J6bymv6QQM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\nCqXTdYDcIzwAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax1 = plt.subplots()\n", + "\n", + "ax1.plot(x, x**2, lw=2, color=\"blue\")\n", + "ax1.set_ylabel(r\"area $(m^2)$\", fontsize=18, color=\"blue\")\n", + "for label in ax1.get_yticklabels():\n", + " label.set_color(\"blue\")\n", + " \n", + "ax2 = ax1.twinx()\n", + "\n", + "ax2.plot(x, x**3, lw=2, color=\"red\")\n", + "ax2.set_ylabel(r\"volume $(m^3)$\", fontsize=18, color=\"red\")\n", + "for label in ax2.get_yticklabels():\n", + " label.set_color(\"red\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用子图的twinx()函数，可以得到相同x轴，而y轴在另一侧的子图，子图其他设置相同\n", + "- twinxy()函数用法类似" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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9uqx/9rrAeNrJtJ9tq2KZijSr0+xMkbeIbkGdSnU8+KlEJEwEp9ydc9cAqUAF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\nAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "ax.spines['right'].set_color('none')\n", + "ax.spines['top'].set_color('none')\n", + "ax.spines['bottom'].set_color('b')\n", + "ax.spines['left'].set_linewidth(2)\n", + "ax.plot(x,x**2,'g')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 子图坐标系的脊线，上下左右分别为spines['top']，spines['bottom']，spines['left']，spines['right']\n", + "- 应用脊线的set_color()方法，可以进行线的颜色设置，当颜色设置为'none'时，则该脊线不显示\n", + "- 应用脊线的set_linewidth()方法，可以进行线宽设置，当线宽为0时，该脊线不显示" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "mpl.rcParams['axes.unicode_minus'] = False" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "解决图像中负号'-'有时显示或保存为方块的问题" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "ax.spines['right'].set_color('none')\n", + "ax.spines['top'].set_color('none')\n", + "\n", + "ax.xaxis.set_ticks_position('top')\n", + "ax.spines['bottom'].set_position(('data',0)) # set position of x spine to x=0\n", + "\n", + "ax.yaxis.set_ticks_position('right')\n", + "ax.spines['left'].set_position(('data',0)) # set position of y spine to y=0\n", + "\n", + "xx = np.linspace(-0.75, 1., 100)\n", + "ax.plot(xx, xx**3);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用子图的xaxis.set_ticks_position()方法，可以设定x轴的标签及数字在top或bottom\n", + "- 利用子图的yaxis.set_ticks_position()方法，可以设定y轴的标签及数字在left或right\n", + "- 利用脊线的set_position()方法，可以将脊线放置在特定的点，参数为一个元组，内有两个参数\n", + "- 第一个参数'data'即数据，第二个参数是坐标。('data',0)就是酱该脊线放在数据为0处" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**6. 其他**" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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I7T8aK4//tWSqUoqRq0ei/Udj8ua/lkx1c3Yj2CeYttXb8mGPD2kV0Ippe6ZZ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\nqavftQshSq1Ck79SyqBp2lT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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "ax.plot(xx, xx**2, xx, xx**3)\n", + "\n", + "ax.text(x=0.15, y=0.2, s=r\"$y=x^2$\", fontsize=20, color=\"blue\")\n", + "ax.text(0.65, 0.1, r\"$y=x^3$\", fontsize=20, color=\"green\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 用子图的text()方法，可以在子图中写入文字，x,y参数为文字坐标，s参数为字符串内容。" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "n = np.array([0,1,2,3,4,5])\n", + "t = np.linspace(0, 2 * np.pi, 100)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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cf9e6bKcDh11wedoXTMhNswY31jS6CBRLAKWUUkolwis7XyEjOaOnm3FayMrK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\nmrti5uCoK6/5Ks3tXjw/aHDjLzAjpdXe+i4RGSQ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dz7j/r59RVGtG0zXq5JiGJ4QQQviz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\n8eGHHxIXF8fEiROdnre4uJgrr7yyrKKi4hta6yanB40iozIYGigpQX9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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize = (12,3))\n", + "\n", + "ax0 = fig.add_subplot(1,4,1)\n", + "ax0.scatter(xx, xx + 0.25*np.random.randn(len(xx)))\n", + "ax0.set_title(\"scatter\")\n", + "\n", + "ax1 = fig.add_subplot(1,4,2)\n", + "ax1.step(n, n**2, lw=2)\n", + "ax1.set_title(\"step\")\n", + "\n", + "# axes[2].bar(n, n**2, align=\"center\", width=0.5, alpha=0.5)\n", + "# axes[2].set_title(\"bar\")\n", + "\n", + "ax2 = fig.add_subplot(1,4,3)\n", + "ax2.fill_between(x, x**2, x**3, color=\"green\", alpha=0.5)\n", + "ax2.set_title(\"fill_between\")\n", + "\n", + "ax3 = fig.add_subplot(1,4,4, polar = True)\n", + "ax3.plot(t, t, color='blue', lw=3)\n", + "ax3.set_title(\"polar\", loc='left')\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "还可以绘制各种图形" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "fig.savefig(\"test.png\")\n", + "fig.savefig('test.pdf')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用figure对象的savefig()方法保存文件在当前目录下\n", + "- 可保存成多种格式的文件如：png,pdf,jpg等" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "fig.savefig(\"test.png\", dpi = 300)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用参数dpi设置图像分辨率" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3. matplotlib与pandas联合绘图基础" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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国家美国日本德国
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" + ], + "text/plain": [ + "国家 美国 日本 德国\n", + "时间 \n", + "2007 1000 500 300\n", + "2008 1500 900 400\n", + "2009 1200 800 350\n", + "2010 1700 1000 500\n", + "2011 1400 800 400\n", + "2012 1800 1200 450\n", + "2013 1000 300 350\n", + "2014 1200 350 300\n", + "2015 1300 500 400\n", + "2016 2000 700 800" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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3Pnm0bb24fH8nGvs48fHwNpy6UMjcLQnM25rIkj9SeaprI57u2sis/65nFuh4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R955+F3eCj8Ib3LKTUk7JYicWk5dJ6yiaV7zwPaGqCl1UMRfvz2dEte7RyJm6N9QTuD1Vo222KK\n2sELqYydv5ucPAuezkbCfW+ckRRCCCGKyt5Le3nmj2d4NOJRXnjoBb3LKVXkBLVS4lJqDtHTY4hP\nyykz69o62BsY2apywfXTSZkMnbWDFzvWoGOtCjZ7EtaB86kMmLENVwc7kjJNhJSR/08hhBBlU3pu\nOn1/7Iuviy+ze87GoMhc5rXkq1EKXBt0Zw9rzIOVyuZaeBm5ZhzsDIyet4shM3dwMiFD75JKXH7Q\ndXO05/unmknQFUIIUaxUVeWpX57iRPIJFvRegL/r/e+uWt5I2NVZSpaJJ6ZtJSE9lznDGxNVRoMu\nQK1gT375Twsmda3JntPJdJy8kQ9XHKGsrvhxt/46l0r/6TG4OdqzcFRTwnykdUEIIUTxmrF7BgsO\nLODNNm/SqmIrvcsplaSNQWeezkY61gqkQ61AGlX01ruc+2ZvZ2BYiwfoWi+ID34/Slxars20M+RZ\nrQR7OTN9cJQEXSGEEMVuf9x+nl7xNO0rt2dCywl6l1NqSdjVyfmUbPLMVir5uTKhc/lZNzVfgLsT\nn/Sth+XKCWsHL6Ty/u9H+G+3mkQEFG4nq7IiMSMXPzdHGoZ789vTLTEYbCPcCyGE0E+GKYO+P/bF\ny8mLub3mSp/ubchXRgfnU7J5YtpWRs3dWe5XL7C7EvzOJWez72wKnSZv4t3fDpORa9a5sqKx92wK\nbT9ez4LtZwAk6AohhCh2qqoy5tcx/H35b+Y/Np8KbhX0LqlUk7Bbws4lZ/HEtK2kZOXxYZ96NhOO\nOtYKZN3zbejdMJRpG0/y8MfrWbbvgt5l3Zc9Z5IZNGMb3i4OtK4mJwTcr+zs7NuO5+bmFupx5s+f\nj+z+JYQoz2buncm8/fOY1GoSbR9oq3c5pZ60MZSgs5eziJ4eQ2p2HvOGN6FemJfeJZUoXzdHPuhT\nl+gm4UxaeoC9Z1LoXi9Y77Luye4zyQz5djs+bg4sGNm0zCwXV5otXryYxx9/HJPJRHx8PPHx8cTF\nxREfH8+ePXuwWCxMmzbtjo/j6+vLiRMniIoq1zv6CiFs1MH4g4z9bSwPP/Awr7V6Te9yygQJuyXo\njeWHSMvO47sRTagbaltB91r1w7xY8q+HyLNou8XFnEzij4OXeKZ9NTxK8UYa+eLSchj87XZ83RxY\nOKopQZ4SdIuC0Wikb9++VKpUicDAQIKCgggMDKRx48aEhYWRnJxcqMdxdHTEycmpmKsVQoiSl2nK\n5PEfH8fD0YPvHvsOO4Od3iWVCRJ2S9CHfepyMTWbWsGeepeiOzuDUvBDuudMCrO2xLJ83wVefjSS\nxxqElOr2jgoeTrzUqTqP1KwgQbcIOTk5MWnSJBo1anTDWGpqaqHbGIB/LHeXkpLCwYMHqV27Np6e\n8rMnhCi7xv4+liOJR1g1aBWBboF6l1NmSNgtZmeSspi68QT/7VYLH1cHfFwd9C6p1BnTpgotIvyY\nuPQAz/+4jwXbz/BG91rUDildwWRn7GUc7e2oE+rJoGaV9C6n3FEUBbP55icuZmVl4eJy43JucXFx\n7Nq1i6SkJOLi4rh06RIHDhwgJyeHZcuW4ejoiKurK4GBgaiqSosWLYr7aQghRLGYs28Os/bOYmKr\nibSr3E7vcsoUCbvF6HRSJtHTYsjKszC8xQNU9nfTu6RSq06oJz+Nac6i3ef44PcjrD0SX6rC7o7Y\nyzz5f9upFujOT2Oal761g2d2ufFYtY7w0NMlM14EDAbDLcNuZmYmQUFBNxz39fUlNTWV8PDwgiDb\ntWtXJk6cSGZmJsOHDy+y+oQQQi+HEw4z5tcxtK7Ymv+2/q/e5ZQ5EnaLyemkTJ6YFkN2noXvRjSR\noFsIBoNC36gwOtYMxNGoLRSy9kgcCem5PN4oTLfWhu2nLvPkzO0EejrxzcBGpS/olhMGg4FVq1ax\nb98+Ll68SHJyMhkZGbRq1Qo7OztcXV1vuI+9vT3R0dEF10eOHMnEiRNxcnLCarVy8eLFm4ZkIYQo\nK7Lysui7qC+uRlfm954vfbr3QMJuMYhN1IJurtnC/BFNqRnsoXdJZYqny9WT1JbuvcDSvRdYsP0s\nb/aoVeIn9m07mcTQWTsI8nRiwcimBHiU0hOfhv6q73gRMBgMuLm50bJlS0JDQ/H2vrqj4JdffnnT\nsHutadOm0a1bNzw8PEhJSaFv37689957TJw4sbhLF0KIYjPu93EciD/AigErCHYvmysY6U3W2S0G\ncWk52BkU5o+UoHu/Jverz6d963EuOZseX/3JhJ/+IjnTVGKff9rGk1rQHVWKg245YTAYaNCgAXXq\n1PlH0AXIyMjAze3W747ExMSQlZVF9+7dC47Z29sTGRnJ2rVri61mIYQoTt/t/44Ze2YwocUEOkZ0\n1LucMktmdotQRq4ZN0d7mlT2Zd3zbXCwl78l7peiKDzWMJT2NSswefXfzNoSS81gDwY1rVisn1dV\nVRRF4Yv+DcjMteDv7lisn09oYddisdx0LC0t7ZZhd//+/axZs4ZXX3214FhKSgr79u0jJCSETz/9\nlIYNG+LlZbvL/Qkhyp6jiUd56penaBHegjfbvql3OWWahN0icjIhg/7Tt/Fsh2r0jQqToFvE3J2M\nTOxak+jG4Tzgp72dvepQHL5uDjQM977Dve/OlhOJ/G/9Cf43sBFujva4OMiPSUkwGAyYTDeftb9V\n2N27dy9bt25l7NixjB07FrPZzNmzZ3F1dSU3N5eKFSsyevRoevfuzZw5cwgJCSnupyGEEPctOy+b\nvov64mTvxILeC7A3yO+h+yFfvSJwIiGD6GkxWFWV+ja2K1pJiwjQAo+qqny66hiHL6bRNyqUlzrV\nwNft/mdftxxPZNjsHYT7uJCTZ8HNUX5ESoqiKAUzu1arleTkZOLj47FYLOTm5t5wYuC6deswmUyM\nGTMG0Pp6AdavX09KSgo9e/YsuO3x48dZtGgRYWFhPPbYYyX0jIQQ4t4888cz7I/bz6/9fyXUI1Tv\ncso8+U1+n47HZxA9PQZVVVkwsilVK7jrXZJNUBSFH0c344s1f/Pt5lOsOHCJ5zpUZ0CTcOzt7m1W\nffPfiQyfvYNKvq58N7IJfkUQnkXhXbp0iVdffZXXX38dOzs7PDw88Pb2JjAwkEuXLt1w+0aNGuHh\ncWNP/M2WL3vqqaeKpWYhhChq3x/4nqm7pvJi8xfpXLWz3uWUCxJ270NiRu6VoIsEXR24OdozoXMk\nj0eF8fqyg/x32UGCvZxpX7PCXT9WftB9wM+V70Y0KZJZYnF33Nzc+Oyzz+jRo8cNYx999NENx24W\ndAGOHTsm7QpCiDLp+OXjjFw+kuZhzXn74bf1LqfckLB7H3xdHXiyeSU61qpARIAEXb1EBLgxd3hj\n/jyexEMRvgCsOxJPrRAPAtwLt4KCj6sDjSp680V0Awm6OunWrRtZWVk3HRs3blyhH6d///5cuHCh\nqMoSQogSkWPOoe+PfbE32LOg9wKMdsY730kUioTde3AsLh1VheqB7vy7bYTe5Qi0toYWVf0AyDZZ\neOaHvVgsKuPbV2NIs4q3bG2ITcykkp8rNYM9mD+yaUmWLG7iZlsCAzg4FH6bbS8vL1l5QQhR5jy/\n8nn2XNrDsieWEe4Zrnc55YosGXCXjsWlEz0thvHf78VqVfUuR9yEs4MdS/71EA0revPWL4foMmUz\nMSeTbrjd+qPxdJi8kXkxp3WoUgghhNAsOrSIr3Z8xbNNn6Vb9W56l1PuSNi9C0cvaUHX3k7hq/4N\ndNu+VtzZA36uzBr6INMGNSLTZOaJaTEcupBWML7uaDyj5uyiaoAbXerIdrJCCCH0cTL5JMOXDadx\nSGPee+Q9vcspl6SNoZCOXEqj//RtGO0UFo5qVrDWqyi9FEWhQ61AWlXz54+Dlwp2s/t05VH+t+EE\n1Sq4892IJni5FP4tciFKI0VRQoE+qqpOvuaYArwJeANGYIOqqvN1KlEIcRO55lz6/tgXg2Lg+z7f\n42Anv4+Kg4TdQvpoxVEc7AwsGNVUgm4Z42S0o0d97ez8i6nZfL3+BDWC3Jk3XIKuKNsURQkEegAv\nAPOuGx4DRKiqGn0l+G5VFOW4qqrbS7pOIcTNvbjqRXZd3MWSfkuo5FVJ73LKLQm7hfTZE/VJycwj\n3PfmJ9CIsiHI05nFY5pTJcBNNowQZZ6qqpeAqYqi3GyttfHA2Cu3UxVFWQq8BPQuwRKFELew5PAS\npmyfwtONn6ZnjZ53voO4Z9KzexsHL6Ty7+92k22y4OFklKBbTtQL85KgK8ob67VXFEWpCVQFNl1z\neDvQriSLEkLcXGxKLMOWDaNRUCM+bP+h3uWUe/Ib/xYOnE9l4LfbcDHakZSZS6iDBF0hSpqqqjds\nEywKJQxIU1U1+5pjSYCnoig+qqpe1qkuIWyeyWKi36J+WFUrPzz+A472srZ7cZOZ3Zs4cD6VATO2\n4epgz8JRzQj1lqArRHGzWq188MEH/zj23nvvcfTo0VveJz09nUOHDt3xsc+cOcP8+TZ1bpYfkHrd\nsfQr/970BU1RlFGKouxUFGVnQkJCsRYnhC2bsHoC289v5/+6/x+VvSvrXY5NkJnd6+QHXTdHexaO\nakqYjwRdIUrC7NmzbwiumZmZeHt7A5CdnU1OTk7BddC2GH7qqado3LgxKSkpBZfMzEwURUFRFOzs\n7LBarbRs2ZL+/fuX6HPSUTZw/XRR/vXMm91BVdVpwDSAqKgoWURciGKw/OhyPo35lH8/+G9615T2\n+ZIiYfc6ZqtKsJcz0wY1kqArRAm5dOkSK1euZO7cuSxZsoQdO3aQnZ3Npk2byMjIwGKxoKoqderU\nYfTo0QX3UxQFZ2dnunTpgo+PD97e3vj4+ODu/s/tu7dt28bJkydL+mnp6STgpyiKg6qqpivHAoFk\nVVWTdaxLCJt1JvUMQ34eQoPABnzc4WO9y7EpEnavSEjPxd/dkfphXvz6nxayYYQQJcRsNvP+++/z\nzTffkJmZSfPmzWndujU+Pj48++yzfPrppwDs27ePKlWq3HD/4OBgHn74YVasWMGiRYswGo04ODhg\nMpmwWCy8/PLL5OTk3NWWw+XAX0AiEAVsuXKsAbBat4qEsGF5ljyeWPQEZquZHx7/ASd7J71LsikS\ndoF9Z1MY+O02Xn60BgOaVJSgK8qcoSuG3nCsdWhrnqz9ZImM348pU6YwYcIEnJ2d6dGjB2PHjmX5\n8uXk5OSQlJRE+/btCQoK4sCBAyxYsIDq1avf9HFat27NQw89xLZt2zCZTHTu3LlgLCcnB0fHcn0S\niAEoeOFSVdWiKMr7wGhgi6IoBiD6ynUhRAl7be1rbD23lYW9FxLhE6F3OTbH5k9Q23sl6Hq7ONCm\neoDe5QhhU0wmE08++SQVKlTgm2++YdCgQQQEBPDII49Qv359vvjiC+rVq8fMmTN5+OGHbxp081dr\ncHZ2xt3dvWAWNy4ujvPnzwNav295DLuKogQqivIU8AQwQFGUMYqihF8ZngycVhTlC7Re3E9UVd2p\nV61C2Krf/v6ND7d8yFONnqJf7X56l2OTbHpmd8+ZZAZ/ux1vVwcWjmpKsJez3iUJcU9mdpqp6/i9\ncnBwwMfHh9jYWJYuXcqaNWuIiYkhPT2d9PR0du3axd9//838+fPZvXs3WVlZuLjcvJd++vTpzJkz\nh1OnThEXF4enpyeNGzcumCX28fEpluegp/xNJa5crh9TgYklXpQQosC5tHMMXjKYuhXq8lnHz/Qu\nx2bZbNiNT8th8Lfb8XFzYMFICbpC6CUrK4vPP/+cGjVqAODi4sKyZcto0qQJqampjBgxgoCAAGbM\nmIHRaLzh/lqmg379+lGvXj127NhBZGQkmZmZdOvWreBzlMeZXSFE6WW2moleHE2OOYcf+vyAs1Fy\nhl5sto0hwMOJlx6tITO6QujIYrHw8ccfM2nSpIKTyi5evEi/fv1wc3Pj9OnTbN26lZ9//pkvv/yS\nV155hdzc3H88Rn4bg4eHB40bN8bPzw8XFxfs7Ox47rnnAC3sOjnJCSFCiJIzaWY/jtEAACAASURB\nVN0kNp/ZzNSuU6nud/NzDUTJsLmZ3V2nL2NvMFAvzIuBTSvqXY4QNm3t2rWMGzcOT09PrFYrDg4O\nODo6EhISQkREBH5+flSqVAnQlicLDAy842Pm5eXh4OBAu3btcHV1JTU1VcKuEKJE/XH8D97b/B4j\nGoxgQN0Bepdj82wq7O6MvcyQ/9tORAV3fv5Xc9mGVAidtW/fvuDj/HaElJQUIiMjCQsL4/XXX6dl\ny5Z069aN06dPM3XqVP7zn//c0H977tw5Zs2aRWJiIrt37+bUqVO4uLjg4eFBr169yM7OxtlZ3sER\nQhS/C+kXGLRkELUDavP5o5/rXY7AhsLujitBN9DDiWmDGknQFaKUsVqtZGVlsW7dOrp06cKcOXN4\n77332LlzJ2lpaYSEhNCrVy++/PJLJk2a9I/7hoaG0q9fP/z8/PDy8rrh5/vpp5/G1dW1JJ+OEMIG\nma1m+i/uT2ZeJj/0+QEXo2xOVRrYRNjdfuoyT87cTqCnEwtHNiXAQ97OFKK0ycvL46WXXuLxxx/H\naDRSsWJFvvjiC/71r3/h4ODA119/zcsvv0zt2rUL7mM2m4mJiaF///5kZWWRlZWFyWTCarVisViw\nWCwYjUZMJtMNu6oJIURRslgtjFo+ig2nNzC752wi/SP1LklcYRNhd9rGkwR5OrFAgq4QpVJysraD\n7dtvv42npycAjzzyCK6urgwdqm1osWvXLiIjI+nRo0fB/RRFoXnz5rz99ts4Ozvj4uJy053SJkyY\nYGs7qAkhSlCeJY/BPw9m4YGFTGw1kcH1ButdkriGkt8nV9ZERUWpO3fefn10VVVRFIUsk5nMXAv+\n7rL0kCjbDh8+TGRk+ZwtOH36NBUr3vqk0czMTJycnLCzs7vh+J1aFNLS0vDw8ChUHXf6GiuKsktV\n1ahCPVgZVZjXVyGEJtecS79F/Vh6dCnvt3ufl1q8pHdJZVZxvb6W26XHtp5IYuC320jPycPFwV6C\nrhCl3O2CLoCrq+sNQTf/+J0UNugKIcTdyMrLovvC7iw9upQvHv1Cgm4pVS7bGLYcT2TY7B2EebuQ\nk2fFXToXRDmS/46FKHpl9Z0uIUTJS89Np+uCrmw6vYlvu3/LsAbD9C5J3EK5C7t/Hk9k+OwdhPu4\nMH9kU/zcZEZXlB9Go5Hs7Oxbbpkr7k92dvZNd2kTQohrJWcn0+m7Tuy6sIvvHvuO6DrRepckbqNc\ntTH8eTyRYbN2UNHHVYKuKJcCAgI4f/48WVlZMgtZhFRVJSsri/PnzxMQEKB3OUKIUiw+M562s9uy\n99JeFvddLEG3DChXM7u+bg40qujNF9EN8JWgK8qh/N7TCxcukJeXp3M15YvRaKRChQrS3yuEuKUL\n6RdoN6cdsSmxLHtiGR0jOupdkiiEuwq7iqKEAn1UVZ18zTEFeBPwBozABlVV5xfVeGGcSsykkq8L\nNQI9mD+y6d3cVYgyx8PDQwKZEEKUsNiUWNrNaUd8ZjwrBqygdaXWepckCqlQYVdRlECgB/ACMO+6\n4TFAhKqq0VeC61ZFUY6rqrq9iMZva8OxBEbO2cnELpEMalapMHcRQgghhCi0v5P+pt2cdqSb0lk9\naDVNQpvoXZK4C4Xq2VVV9ZKqqlOBm824jgdmXrmdCiwFXirC8VtafzSekXN2EuHvRte6wYW5ixBC\nCCFEoR2IP0DLmS3JNmezbsg6Cbpl0N2eoGa99oqiKDWBqsCmaw5vB9oVxfjtpOeYGTVnF1UD3Phu\nRBO8XWV3JCGEEEIUnd0Xd9NmVhsMioGNT26kfmB9vUsS9+B+V2MIA9JUVc2+5lgS4Kkoik8RjN/S\n6aRMqlaQoCtEkbGY4chv8OvzcPgXsMgJcEII27Xl7Bbazm6Lm4Mbm4ZuItK/fO5eaQvudzUGPyD1\numPpV/51KYLxy9cOKIoyChgFEBBaie9GNMHLRYKuEEVi1USI+RoM9rBjOrgFQsPB0PYVkE0shBA2\nZO2ptXRf0J1g92BWD15NuGe43iWJ+3C/M7vZwPVrfOVfzyyC8X9QVXWaqqpRqqpGhVXwlaArxL2y\n5MHh5TCvN5zfpR1rOBj6fQcTzsMTCyC4Plz662rQPb1FZnuFEOXeb3//Rpf5XajkVYmNQzdK0C0H\n7ndm9yTgpyiKg6qqpivHAoFkVVWTFUW5r/H7rE0Icb3kWNg9B/bMg4w4cA+G9DhtLCBSuwDU6Kxd\nLGbtesoZmNkZXP2hwQAtGPtU1uUpCCFEcVl8aDHRi6OpU6EOfwz8Az8XP71LEkXgfmd2/wISgahr\njjUAVhfRuBCiqJgy4etmsPkzCG4A0Qth/F9aqL0Vuyt/D3uEQP/vITQK/vwcpjSAOT3g0oGSqV0I\nIYrZvP3z6LeoH1HBUawZvEaCbjlytzO7BqCgeU9VVYuiKO8Do4EtiqIYgOgr1+97XAhxH5JOaLO4\n8YdhwA/g4AqPTdeCrmfI3T2WwQ6qddQuaRe0meE9c8HRTRuPPwwGI/hFFP3zEEKIYjZt1zRG/zKa\nNpXasCx6GW4ObnqXJIqQoi1te4cbXd1U4jm0gPwR8Kuqqmeu2QHNC3AG1qiquuCa+97X+K1ERUWp\nO3fuLOzzFMI2mHPhyC+wazac2gCKHVTrBL1ngINL0X4uVb3az7ugPxz9FSq1hEZPQmQ3sC+fW3Yr\nirJLVdWoO9+y7JLXV2FLJsdM5pk/nqFz1c4senwRzkZnvUuyWcX1+lqosFsayYuxENfID54x38CK\nl8AzHBoNhvoDwSOo+D9/+iVttnf3HEg5Dc4+0Oxf0OqF4v/cJUzCrhDlxzsb3+G1da/RO7I383vP\nx8FOTnzXU3G9vt7vCWpCCL3k5VyZxZ0F9aK1E8fq9tVaCSo/DIb7bcm/C+6B0Op5aPEsnFqvzSzn\n5WhjVisc+hmqdwajU8nVJIQQt6CqKq+ufZX3Nr/HwLoDmdljJvYGiUTllfzPClHWJBzVwuS+BZB9\nGbwrgZ1RG3PxgYhH9KvNYIAqD2uXfLEbYdFQcPLSQnmjIVdXfRBCiBKmqirjV4xnyvYpjGo4iv91\n/R8GpQQnB0SJk7ArRFlgtWpBUlVhQbS2FFhkV2g4BB5oXbKzuHerUisYvAx2z4YdM2Db/yCsCTw2\nTQvqQghRQixWC6N/Gc2MPTMY32Q8n3b8FEU2zSn3JOwKUZrFHdJC4rE/4F8xWhvAY9PBKxzc/PWu\nrnAMBqjcWrtkJmoz0oeWaTu0AZxYC64BEFhb3zqFEOWa2WpmyM9DmP/XfF5t+SpvtX1Lgq6NkLAr\nRGljyoKDS7Re3HPbwc4BIrtDTqoWdkMb6V3hvXP1g+b/0S75VrwCCYchJEpbyaH2Y9oyaUIIUURy\nzblEL45myZElvPvwu0xoOUHvkkQJKsXvfQphY/J3KzuzBZb+C3JSoMM78OwR6PMtuFfQt77iMvQ3\n6Pge5KbDsrHwSQ3Y+rXeVQkhyonsvGx6ft+TJUeWMLnjZAm6Nkhmdsuj+COQehaC6oFbgN7ViNvJ\nzYCDP2mzuBWbQ4e3tZUUhv2h9bXawltsLleWKWs6Bs7EaF+L/O/bzCQ4shxq9wZHd13LFEKUPem5\n6XRf2J0NsRuY3m06IxqO0LskoQMJu+WJqmonAK14Gaxm8AyDZ65s53rgJ+2t4aD65XeGsCy5uE8L\ndft/BFM6+NfQLqD1uIY31bU8XSgKVGymXfId/RWWj4M/XoU6fbQ2h+AGupUohCg7UnJSePS7R9lx\nfgdze81lQN0BepckdCJht7zIy4Ffn4W932k7ZjUdo/V+5lv9urbYP4B7kBZ6q7aHB4frUq5Nysu5\nus7s+ve1E7NqPaYFuLDGtjGLe7caDNL+CNg1C/Z9r/0bVA+GLAcnT72rE0KUUolZiXSY24ED8Qf4\n8fEf6RXZS++ShI4k7JYX6RfhyK/Q+mVo/dKNS1GN+RMu/QUX9sLFvdq/53ZoYVdV4X/NwTNUC8HB\n9bV/PYIlgN0vVYULe7SQduAnGL0JfB6ATu9pYc3ZW+8KSzdF0f4QCGsMHd+Fv36E87uuBt3dcyGg\nJoQ0lO9VIQQAF9Mv8sjcRziZfJJl0cvoFNFJ75KEziTslnVxB7Vf9j4PwNN7tP7Hm3F013pCKza/\nesxq1f4152izZRf2wvHVoF453vTf0OldsFrg2ArtNh4hEioKIzcd9n+vbf5waT8YXbRVBvK/drK+\n7N1z9oLGI4GR2nVzLqz+L2QlQYU62mYVdfvKjK8QNuxM6hnazWnHxfSL/D7gd9pUaqN3SaIUkLBb\nVqkqbP0KVk2Crp9qb4XfKujeSv7sr9EZen2jfWzKhEsHtNnfgJrasaTjsLC/9rGL39WZ31q9ZG3U\na6mqFnKdPCA7GX59HirUhi6fQJ3HJYQVNXtHeHovHFgEO2fCb8/Dyona17uB9OYJYWuOXz5Ouznt\nSM1JZfXg1TQNtcFzH8RNSdgti0xZsOw/2i/5Gl21vs+i4uAK4U20Sz7vSjB81dUWiIv74MRn4F9d\nC7uXDsCqif9sgfAKt50Z4OwU2P+D1qrgGQIDftSe/9gd4BthO18HPTh5QNQw7XJhjzaTXqGWNnZx\nP5zZqs32SruIEOXaoYRDPDLnEfKseawbso4GQXIiq7hKwm5Zc/kUfD9Qa194eCK0eLb4t4q1d7za\nN5kvL/vqxzkpkJEAW6Zoq0AAOPtA9AJtVYHMRDBlgFfF8hX8zu+C7TO0DSDM2VrIr9H16rhfVf1q\ns0XBDf65UsPR32D9e9q7HzV7au9+hDctX9+DQgj2XNxDh3kdsDfYs+HJDdT0r6l3SaKUkbBb1sQd\ngNRz2uxh1fb61WF0vvpxpRYwZrO22kD8waszwF4VtfH938Mfr2iza0H1rlzqQ7WOZW+nrKzLWjuC\nwQ4OL4fDy6DeE1q/qCyJVbq0eRmqP6rN9u7/AfYv1L7vRq4r/j8QhRAlIuZcDJ3mdcLTyZM1g9cQ\n4ROhd0miFFJUVdW7hnsSFRWl7ty5U+8ySoaqaic5BdXTrmenaCfrlBVJJ+DUhqshOO4QWPPgxVNa\nn/H+H7Xnl98C4VO5dM2+qar2dviuWXDwZ+g3D6p10PpyDUZwdNO7QnEnpkxtBj4jHlo+qx1b8yZU\neRgqPnRX32+KouxSVTWqmCotFWzq9VWUWetj19NtQTcquFZgzeA1VMyfYBFlVnG9vsrMbmmXm6Ft\nHXvkVxj9JwTUKFtBF8C3inbJZ86FxGNXT6i7uBe2TwOLSbvu6AkhDWDgEm0GLjtZO1bSs3GmLNg1\nUwu5icfA0QMaDtLCOEgfaFni4AoNBl69nnZRa0HZ9InWV91wCNTvD65++tUohCi0FcdX0Ov7XlT2\nrszqQasJcg/SuyRRiknYLc2STsDCAZB4FNq/qZ0QVh7YO0JgnavXO74D7f4LCYevzv7mpF4Ntz8O\n1fpjA+tenf0NafjPAF1UVBXSLmgnmhnstDDkUwV6fA21epa9tgtxcx5B8NwROLRU+2Nm1URtpveJ\n77T2GiFEqbXk8BL6LepHrYBarBy4En9Xf71LEqWchN3S6tgfsHikFrgG/gRV2updUfGyd7jaz8uQ\nf441GKjNpl7cC9ungyUXghvCqHXaeMw32ixrcH1tls5gd/efPyMB9s3X+jutZm1JK3tH+PcOcPW9\n76cnSiEHF6gfrV3iD8PuORD6oDZ2eLm25F79AeAWoG+dQogC8/+az+Alg3kw5EF+H/A7Xk5l7J1O\noQsJu6XViXXgXVHrD/W28T6kOn20C4AlDxKOaj2YoM3EbvxQ21gAwOgKQXWhdu8rGxCgbZ5xqxaI\n87tgyxdw+Betjzi8mXbWvmoFDBJ0bUVApLarXb6TG2DHdFj7NtToon1PPNBGTmwTQkff7v6WkctH\n0rpSa5Y9sQx3R3e9SxJlhITd0iQnTdv21786dHhLC3YOLnpXVbrYGf+5kYWiwHPHtFaPa9cBzojT\nxvNy4ONqWq9z/jrAvlW1ZcGcvSDxOJxcD41HQcPB2u2E6PKx9j2xezbsna+1O1RpB4N+0rsyIWzS\nlG1TGLdiHJ0iOrG472JcjPK7URSerMZQWiQc03Yps+bB2J1aqBP3L+sybPhAC8KX9kNelna8/Zvw\n0Dgwm7RZXKOTvnWK0isvB478AgZ7qNVTVmMQooS9v/l9JqyZQK8avVjQewGO9o56lySKiazGUJ4d\n/gWWjNYC1+OzJOgWJRcfePQD7WOrRevDjDuonewGWq+wELdjdLraRiOEKDGqqjJp3STe3vQ2/ev0\nZ1aPWRjl96O4BxJ29WS1aDs8bfxIO+Gq3zxtFQBRPAx2WotIeVnVQgghyilVVXlu5XN8FvMZIxqM\n4Juu32B3LycfC4GEXX1ZzXBirbbaQOdP5K10IYQQNs+qWhnzyxim7Z7G042fZnKnySilaaMhUeZI\n2NVD/GFwD9SWyxq8TFu7VX6QhRBC2Diz1czQpUOZt38eE1pM4J2H35GgK+6brKNT0g4ugentYMUE\n7bqjmwRdIUSxUBTldUVREq+7fKZ3XULcjMli4olFTzBv/zzebvs277Z7V4KuKBIys1tSrBZY8wb8\n+TmENtZ2DBNCiGKmqqrsgSxKvey8bPr82Iff/v6Nzzp+xvim4/UuSZQjEnZLQtZlWDQMTq6DqGHQ\n6QNZBUAIIYQAMkwZ9FjYg3Wn1jG161RGNRqld0minJGwWxJy0yHhCHT/Qtu4QAghhBCk5qTSeX5n\nYs7FMKfXHAbWHah3SaIckrBbnE5tgkottO1+n94DRme9KxJC2BhFUXoCrYFgIBUYq6qqSd+qhIDE\nrEQ6zuvIX3F/8UOfH+hds7feJYlySk5QKw6WPO0EtNldYd8C7ZgEXSFEyUsFLKqqPqOqaj/ABIy7\n2Q0VRRmlKMpORVF2JiQklGiRwvZcyrhEm1ltOBh/kJ+f+FmCrihWEnaLWkYCzO0FMV9DkzFQ53G9\nKxJC2ChVVT9TVXX5NYcWAD1ucdtpqqpGqaoa5e/vXzIFCpt0NvUsrWa2IjYllt8G/Ebnqp31LkmU\nc9LGUJTO74bvB0FWIvSaBvX66V2REMKGKYoSBlxUVdV85VAC4KNjScLGnbh8gnZz2pGck8zKQStp\nHtZc75KEDZCZ3aKUfknbknbYHxJ0hRC6UhTFFTgGdLrmcAXgtD4VCVt3OOEwrWa1It2UztrBayXo\nihIjM7v3y2yCszHwQCuo0RmqPCzb/gohSoNsIB7Yec2xvsBsfcoRtmzfpX20n9seg2Jgw5MbqB1Q\nW++ShA2RsHs/0uPgh8Fwfif8Zxd4V5KgK4QoFVRVtSqK0gkYrSjKZcAdiFVVdaHOpQkbs+3cNjp9\n1wk3BzfWDF5DNd9qepckbIyE3Xt1drvWn5ubBr2makFXCCFKEVVVDwOv612HsF0bT2+ky/wuBLgG\nsGbwGip5VdK7JGGDpGf3XuycCTM7a7O4w1dBnT56VySEEEKUKitPrKTTvE6EeYSxaegmCbpCNzKz\ney8un4DKreGx6eAiJzYLIYQQ11p6ZCl9F/Ul0i+SVYNW4e8qy9kJ/UjYLazU89qSYkH1oN3roCja\nygtCCCGEKLDwwEIG/jSQqOAofh/wO97O3nqXJGyctDEURuyfMK01LBoOVgvY2UvQFUIIIa4zc89M\n+i/uz0PhD7Fq0CoJuqJUkLB7O6oK26bCnO7g6AH95knIFUIIIa6TY87hjfVvMGzZMNpXac/vA37H\n3dFd77KEAKSN4dbycuCX8bBvAVR7FB6bCk6eelclhBBClBqqqrL48GJeWPUCsSmxRNeOZmaPmTja\nO+pdmhAFJOzeimKA5FhoMwFavQgGmQQXQggh8u29tJfxK8az4bS2ScTqQatpV7md3mUJcQMJu9eL\n3QwBNbVVFoYsBzuj3hUJIYQQpUZcRhyvrX2Nb/d8i4+zD//r8j9GNByBvUEihSid5Dszn6rC1q9g\n1URo9CR0/UyCrhBCCHGFyWJiyrYpvLnhTbLN2YxvOp5JrSfh5eSld2lC3JaEXQBTJiz7DxxYDJHd\nof2belckhBBClAqqqrL82HKeW/kcxy8fp0vVLnzS4ROq+1XXuzQhCkXCbnIsLBwAcQeh3SRo8ay2\nhq4QQghh4w7EH+CZP55h9cnVRPpFsmLACjpGdNS7LCHuioRdxQ7MOTBgEVR9RO9qhBBCCN0lZiUy\nad0kpu6aiqejJ1M6TWF01GiM0t4nyiDbDLuqCod+hsge4BUG/94u6+cKIYSweXmWPL7a8RVvbHiD\n9Nx0/hX1L15v8zq+Lr56lybEPbO9sJubDkv/DYeWwuOzoVZPCbpCCCFs3m9//8azfzzL0aSjdKjS\ngU87fEqtgFp6lyXEfbOtsJt0Ahb2h8Rj0OEdqNlD74qEEEIIXR1OOMyzK59lxfEVVPWpyvLo5XSp\n2gVFzl8R5YTthN1jK2HxCG0Wd9DPULm13hUJIYQQurmcfZk31r/BVzu+ws3BjU86fMLYxmNxsHPQ\nuzQhipTthF0A38rQdw54hetdiRBCCKELs9XM1J1TmbR+Eik5KYxsOJK32r6Fv6u/3qUJUSzKd9jN\nSYVTmyCyK1TrABGPyLa/QgghbNaqE6t45o9nOJhwkLaV2jK502TqVqird1lCFKvyG3YTjmr9uSln\nYdw+8AiSoCuEEMIm/Z30N8+tfI7lx5ZT2bsyP/X9iZ41ekpfrrAJ5TPsHl4OS0aD0RkG/aQFXSGE\nEMLGpOak8tbGt5iybQqO9o683+59xjcdj6O9o96lCVFiylfYVVVY9y5s/BBCGkHfueAZondVQggh\nRImyWC18u+dbXlv7GolZiQytP5R32r1DoFug3qUJUeLKV9hVFFAt0GAQdP4YjE56VySEEEKUqPWx\n6xm/Yjz74vbRIrwFKzqtoGFQQ73LEkI3RRJ2FUV5HRh73eG5qqo+o2gNQW8C3oAR2KCq6vxr7nvb\n8UKJOwimLAh7ENq+poVe6UMSQghhQ04mn+SFVS/w0+GfqOhZkR/6/ECfmn2kL1fYvCKb2VVV1e8W\nQ2OACFVVo68E262KohxXVXV7Icdv78BP2o5oflVh1AY5CU0IIYRNSc9N591N7/JpzKcYDUbebvs2\nzzZ7Fmejs96lCVEqlEQbw3iuzPqqqqoqirIUeAnoXcjxW1Bh5UTYMgXCmmjr58pfr0IIIWyEVbUy\ne+9sXln7CpcyLjGo7iDea/ceIR5yrooQ1yrWsKsoSk2gKrDpmsPb0cLsHcdvK+mEFnQfHAEd3wN7\n2fFFiPuVYcrg8OXDhLmHUcGlgrz9KUQptfnMZsatGMfui7tpGtqUn/v9TJPQJnqXJUSpVGRhV1GU\nnkBrIBhIRZutDQPSVFXNvuamSYCnoig+dxpXVfXydZ9jFDAKoE6IC/SYCg0GFtVTEMImnc84z/qz\n61l/dj0743ZitprxcPBg8xObAVh9ejUANX1rEuQaJAFYCB2dTjnNi6tf5IeDPxDiHsK8XvPoX6e/\n/FwKcRtFFXZTAYuqqs8AKIryJTAOuHBl7FrpV/51AfzuMP6PsKuq6jRgGkBUVJQqQVeIu2e2mtmX\nsI96/vWwN9gz79A85h2exwOeDzAwciBRFaIwW80Fvzyn7p/KkctHAPB29CbSN5JmQc14svaTOj4L\nIWxLpimTD/78gI+2fATApFaTePGhF3F1cNW5MiFKvyIJu6qqfnbdoQXAB8CnwPUrV+dfzwSy7zAu\nhCgCqbmpbLmwhfVn17P5/GbSTGnM6jSLRhUaMajmIKJrRBPuEX7T+859dC7Hko9xKOlQwWVfwr6C\n8f6/9sfV6EpN35oFl1C3UJlpEqIIWFUr8/+az8urX+Z8+nmia0fz/iPvE+55859XIcSNimrpsTDg\noqqq5iuHEgAf4CTgpyiKg6qqpitjgUCyqqrJiqLcdrwoahPCVpmtZuwN9uyK28XwP4ZjUS14O3rT\nJqwNrUNbU8OnBgDBbsG3fRwneyfq+telrn/dgmOqqgLawvXVvKtxKOkQcw7NwWzVXgJ6RvTkrYfe\nQlVV1p5ZSzXvaoS6SwAW4m5sO7eNcSvGse38NqKCo/jh8R9oHtZc77KEKHPuO+wqiuIKHAMeB365\ncrgCcBr4C0gEooAtV8YaAKuvfHyncSFEIeVZ89gTt4f159az8dxGulXuxlP1niLSJ5JhtYfRKrQV\ndfzqYGewu+/PlR9a7Qx2vN78dQBMFhN/p/zNoaRDhLhqZ4PHZ8Uzfv14ANwd3Knpo838tq/Ynjr+\nde67DiHKo/Np53l5zcvM2z+PILcgZvWYxaB6gzAosrSmEPeiKGZ2s4F4YOc1x/oCs1VVtSiK8j4w\nGtiiKIoBiL5ynTuNCyHuzKpaeXnTy2w6t4mMvAyMBiONgxpTxasKAC5GF55u+HSx1+Fg50At31rU\n8q1VcMzX2Zfvu37/jxaIeYfnEeIWQh3/OpxNO8t/t/63IATX9K1JuEe4/FIXNikrL4uPt3zMB39+\ngMVq4ZUWrzCh5QTcHNz0Lk2IMu2+w66qqlZFUToBoxVFuQy4A7Gqqi68cpPJwJuKonwBOAOfqKp6\nbTC+07gQ4gpVVTmRcoIN5zaQlJPEiw++iEExYLaa6VCpA61CW9EsqBkuRhe9SwXA3mBfEGLz5Vny\nMF/peEozpZGdl82CIwswWbVOJlejKx+1+oiWoS1JyUnhcu5lKnlUkgAsyi1VVfn+4Pe8uOpFzqad\npU/NPnz4yIc84P2A3qUJUS4U1Qlqh4HXbzGmAhNvc9/bjgshYG/8Xn4/9Tsbzm3gfMZ5AOr61cVi\ntWBnsOPTNp/qXGHhGe2MGDECUMuvFgu6LiDPmsfJlJMcSjrEwaSDVPSoCMDas2v575b/4mLvQg2f\nGgXBuU1YG9wd3PV8GkIUiZ0XdjJ+xXj+PPsn9QPrM7fXXFpXaq13WUKUKyWxg5oQ4i4lZiey6dwm\nOlfujKOdIxvPbWTx34tpGtSU4XWG0yqkFRVcK+hdZpExGoxU96lOdZ/q9fTa0gAAFx1JREFU9Kra\nq+B4s6BmvNn8Ta0F4vIhfjz2I7mWXH5/7HfcHdxZfXo1u+J2UdO3JpE+kTzg+UCR9CQLUdwupl/k\nlbWvMHvvbPxd/ZnebTpD6w+V718hioGEXSFKAVVVOZp8lA1nN7Dx3Eb+SvwLFZUKrhVoHtycIbWG\nMLLuSJztbWuv+yC3IHpV7VUQgM1WMydTTxLipp0AdzzlOIv/Xsy8w/MAcLZ3prp3daZ3mI6TvROp\nuam4Gl2xN8hLnSgdcsw5fLb1M97d/C655lyeb/48r7V6DQ9HD71LE6Lckt8AQugkx5xDriUXT0dP\ndsbtZNgfwwCo41eHf9f/N63DWlPduzoAno6eepZaatgb7KnmXa3g+uh6oxlZZySnUk9x6LJ2AtzF\njIs42TsB8MbWN9h0bhPVfaoXtEDU8q1FVe+qej0FYaNUVeWnwz/xwqoXOJVyih7Ve/Bxh4+J8InQ\nuzQhyj0Ju0KUoPiseDae28iGcxvYdnEb0TWieabRM9T3r8+bzd+kZWhL/Jz99C6zTLEz2BHhHUGE\ndwTdq3T/x1i3yt2o4FKBQ0mHWHp8KQuOLKCSRyWW91oOwMIjC3G0c6Smb00qe1XGaDDq8RREObf3\n0l7GrxjPhtMbqB1Qm9WDVtOucju9yxLCZkjYFaIEWFUrQ34fwt6EvQAEuwbTM6InbcLaANpJW9f2\nqoqi0Ta8LW3D2wLa/0FsWiypuVd3KJ97aC5n0s8A4GBwoLpPddqFt2N4neEF95FVIMS9is+M57W1\nrzFj9wx8nH34uvPXjGw0UtpqhChh8hNXDuXvbiW7VekjKy+LmIsxbDy3keScZD5/+HMMioH6AfVp\nHdaa1qGtifCKkP+fEmZQDFT2rPyPY8t7LedM2pmr6wBfPkRSThKgBd22P7QlyDXoH1shC3EnJouJ\nKdum8NbGt8jKy2Jck3FMaj0Jb2dvvUsTwiZJ2C3jrKqV02mncTW6EuASwIHEA4xcOZJcSy5+zn74\nu/jj7+xPdI1omgQ1Ic2Uxv6E/fg7++Pv4o+Xo5fMXBWRtWfW8uOxH9l+cTsmqwk3oxstQ1oWLA/2\nXNRzepcormNQDFTyrEQlz0p0rtz5H2M55hy6V+nOoaRDrDi1gh+P/ahTlaKsUFWV5ceW89zK5zh+\n+Tidq3bmkw6fUMOvht6lCWHTJOyWMdnmbNacWVMwE3Xk8hEy8zJ5usHTjKw7klC3ULpU7oKL0YXE\nrEQSshM4nXaajLwMAI5ePsqY1WMKHs/eYI+fsx+vNnmVNmFtOJd+jl9P/loQkv1d/PFz9sPHyUdC\n8TUsVgt/Jf7FxnMbGVZ7GG4ObpxMPcnptNP0rd6XNmFtaBjQEKOd9ICWVS5Gl4I/UKyqlXPp5ziU\ndIhHeVTnykRpY7KY2HVhF5PWT2L1ydXU8KvB7wN+p1NEJ71LE0IgYbfUslgtxKbFFoTaCK8Ielfr\njaqqvLLpFRzstP7CbpW7UdO3JlGBUQB4OXnxWtPXbvm4NX1rMvfRucRnxZOQnUBCVgIJ2QkFJ0Wd\nSDnBl3u/vOF+k9tMpl3FduxP2M/0v6YT4ByAn4sfAc4B+Lv4U9evLl5OXsXzxSglsvKy2Hx+MxvO\nbWDz+c1czrmMnWJH06CmNA5qzJBaQxhee7i0J5RDBsVAuEc44R7hepcidJaem86+uH3subiHPZe0\ny8H4g+RZ8/B28ubzTp8zJmqM/KErRCkiYbcUMFvNpOam4uvsi6qqjFg5gr8S/yLbnA1oa4f2qdYH\n0GablvZcSph72D2d5OBqdKV+QP1bjrcOa83OgTtJzE4sCMIJWQlE+kYCkJGXwYWMC+yL30dybnLB\n/WZ0mEGToCasOb2Gd7e9+4+ZYX9nf3pG9CTILYgMUwZZ5ix8nHzKxEkaZ9PPYlAMhLiFcCz5GM9t\neA4PBw9ahLSgTVgbmgc3L1gWTM7kF6J8ic+M/0eo3XNxD8cvH0dFOy/C38WfBkEN6NisIw0CG9C+\nSnt8nH10rloIcb3SnzbKoZMpJ9mfuL9g1vbo5aPU9K3J7EdnoygKoe6hVPWuqp0Q41Pzhl2hHvAs\n3v3SHe0cCXELKVi4/1rNg5vTvHtzAPIseVoozk4oOPHH19mXh0IeIj47nouZ/9/enQfXVZ53HP8+\nkmwtSEjWZsnIC8ZLJOFFwQkOS00NZRlCgBrXMRRwgIEASSZtQwmdNCXJpNk7JHSYAC3FZIAAMyXO\nNGlI0hAlNKyT2LgY4w3M6k2WjLzI1vL0j3N1uZKtzbrnnrv8PjMa33vec46e8+ge69F73vOe93h5\nz8vs7drLkqlLqC+t56k3nuLOZ+8kz/KoLKqMF8S3f+R2pp04jTfff5OtHVupLamluriaquKqlBbF\nPX09rNu9jta3W/ndW79j676tXPmhK7nj9DuYVz2PBy98kAU1CzKiUBeR0XF33uh4I17Q9he373a+\nG19nRsUMWupauHr+1bTUt9BS18KUsim6kiOSAfQbO0Tdfd1s69jGhrbgDu8b5t0AwNee+xov7XyJ\n4oJiGisbuWLOFSyoXRDf7itnfCWqkMdkQv4E6kvrqS+tjy9bWLvwqJ7j7t7u+HjflsktfOn0L7Hr\n0K547/Gug7vixfzTbz3Nd1/6bnxbw6gsqmT1RauZfuJ0XtzxIs+/93y8GO7/t6a45rgfs9nT10NB\nXgF93sfF/3kx7x54lwIr4LS601g2Z1l8erD8vHxOm3zacX0PEUkPPX09bNyzcUBRu3bHWjq6OoBg\nyEpjdSNLT15KS11Q1C6sW6iZFEQymIrdJOkvmAAe2/gYa7auYVP7Jg73HgagorCCVc2rKMgr4LaP\n3EZRQRHTy6bnxHPQE8euzSyfedT0T4kum3UZiyYv+mBMcWwYxaSi4BfNut3ruH/9/fR534Dtfrns\nl9SX1vPk5id5avtTwZjiWDFcU1zDWQ1nUZhfiLtjZryx7w1a326l9e1W9h/Zz+OXPE6e5XFN8zVU\nF1dzxpQzKJtYFk5CRCQlDnUf4uWdLw/osV2/az1dPV0AFBUUMX/yfFY0rwgK2/oW5tXOo3hCbj2W\nWyTbqdg9Dt293Wzp2PLB3JxtG9jSsYWn/+ppSieWsr97P4X5hayYuyI+N+f0E6fHezc1V+fQygvL\nKS8sp5nmY7bfMO8GVjWvYm/X3mPeYNfjPXR0dbB572bautro9V4A/rDyDxTmF/KDP/2AxzY+Rmd3\nJwCzJ81mScOS+PRgVzVelZoDFZGkaj/UftQwhI17Nsb/MK4oqqClroVbFt0SH4Ywt3quhiSJ5ACd\n5SM40nuEzR2b2dC2gfOnn095YTmrN6zm+3/8PgBlE8porGpkxdwVdPd1A3D9vOvjT2CS5CvIK6C2\npJbaklqoGti2fM5yls9ZDgQzWrQfbmf3wd2UTigFYF71PDpndnJKxSksaVjClNIpqQ5fRMbB3Xmn\n852jbhzbvm97fJ2Tyk6ipb6FZY3L4j2208una3ytSI5SsXsMm9s38/CrD7OhbQObOzbT09cDQF1J\nHWc3nM25086lobSBpqomGsoaNP9smsrPy6e6uDre6wuwdNpSlk5bGmFUIjJafd7H5rbNR/XY7jm4\nBwjG9M+ums3ihsXcvOjmeI9tzQk1EUcuIukkZ4vdw72H2bR3U/wRoa+2vcpNC27i3GnncqD7AL/a\n/isaqxq5uulqmqqaaK5spqGsAQhmQwh7RgQRkfGyoCvzq8AkYALQ6u6PRBvVsR3uOcwru18ZUNSu\n27GOA90HgGBqv1NrT+UTcz4RL2rnT55PWaHG1ovI8HKi2O3q6WJT+yZKJ5Yys3wm2/ZtY9maZfR4\n0GNbXlhOU2UTRflFAMyvmc8zn3xGl7xEJNPdDMxy95WxwvdZM9vi7i9EGVTn4U7W7lg7YBjCht0b\n4kPBSieWsrBuIde1XBcfhtBU08TE/IlRhi0iGSori93u3m6e2PREvNd2W8c2er2Xqxqv4osf/SJT\ny6byqVM/Fb95rP6E+gGFrYYliEiW+DzwGQB3dzNbA9wOLEtVADv37zxqGMKWvVvi7bUn1NJS18JF\nsy6K99ieUnmK/h8WkaTJ6GL3YPdBNrVv4pW2V9jQtoGGsgZuXnAz+Xn53P2nu5mYP5HGqkbOaTiH\n5qpm5tXMA4LLYZ/78Ocijl5EJDxm1gTMBn6fsPgFgmI36dyd1zteP+rGsff2vxdf5+SKk2mpb+Ha\nBdfGe2zrS+t1FU1EQpWxxe7297fzsUc/Fp9WpqqoigtPvhAIemZ//pc/p6KwQv+Jikiumgq87+6H\nEpa1AeVmVunue5PxTbbu3cr1P72etTvWsu/wPgDyLZ/GmkbOm3levKhdWLeQiqKKZHxLEZExydhi\nt2RCCTfOv5GmymAoQm1J7YDCtv8hBCIiOaoa2DdoWWfs3xJgQLFrZjcCNwJMmzZt1N+ksriSrp4u\nVp66Mj4M4dTaU/VgBhFJGxlb7NYU13DrwlujDkNEJF0dAgoHLet/f2Dwyu5+H3AfwKJFi3y032RS\n8SSeu+G5441RRCR0ugNARCQ7bQOqzSxxCoM6oN3d2yOKSUQk5VTsiohkp/XAHmBRwrIW4NfRhCMi\nEg0VuyIiWcjde4FvAp8GMLM8YCXw7SjjEhFJNRW7IiLZ6y5gu5ndTTAe93vu/lLEMYmIpFTG3qAm\nIiLDc3cH/jHqOEREoqSeXRERERHJWip2RURERCRrqdgVERERkaxlwZCuzGNmncBrUceRxqoJph2S\nY1N+hqf8DG2uu5dFHUSYzGw3sH2Mm+kzoxyAcgDKQb/jycN0d69JdiCZfIPaa+6+aOTVcpOZvaT8\nDE35GZ7yMzQzy/rZDI7nl40+M8oBKAegHPRLpzxoGIOIiIiIZC0VuyIiIiKStTK52L0v6gDSnPIz\nPOVneMrP0JSbY1NelANQDkA56Jc2ecjYG9REREREREaSyT27IiIiIiLDUrErIiIiIlkr8qnHzGwK\nsAp4H5gMlAB3uPsRMzPgq8AkYALQ6u6PJGw7UvvPgPOBfQnfstvd60M9qCQKOT8nA7cA7xB8FqqA\nr7n7wRQc2riFnJtpwN8AbwJTgHfc/a5UHFeyjCc/CftoAK4YfOyj3T6dhZmf0bZnumz4HCRTtv+8\nhzPc+RRlXKlkZqcAVwDdQDPwkLu3RhtVdMzsUuByd18VdSy4e6RfwK+B0oT33wJui72+BXg09tqA\n54CPJqw7UvtPgEkJ7xcCN0V9zGmUn1agMuH9xcBdUR9z1LkhuOLxIlCXsP4DwJVRH3MK81MH3ARs\nAe48xr6H3T4TvkLOz7Dt2fKVDZ+DJOUhJ37eI+RgyPMpV76A54GS2Otiggdf1UYdV0S5OAH4I/Bg\n1LG4e7TDGMxsEnAOkPg0ot8BS2KvPw/8B4AH2VsD3J6w7pDtZpYP/NDd2xPWXwX8e5IPIzQh56cK\nKHf3vQnrPw2cm+zjCEOYuQEWA+3uviNh/UeAv03qQYRovPlx9x3ufi/BcR/LSPlNa2HnZxT5yxYZ\n/TlIlhz6eR/TKM6nXNEIzARw90PAeuDsSCOKzmeBh6MOol/UY3Y7gR8CRQnLqoHdZtYEzAZ+n9D2\nArFibKR2d+9191/0N5jZYoKnrvWEcBxhCS0/QAdQHbvM0G82sC6ZBxCiMHMzlaMfcfgOsNDMCpN1\nACE77vwM0jd4wRi3T1eh5WeM7RkrSz4HyZa1P+8RDHk+RRNOZJqAVxLenwjsiiiWyJjZfOAtoC3q\nWPpFWuy6e4+7f8bdX09YfC1B7+tU4P3YX0f92oByM6scRftgnwUeSu4RhCvM/Lh7L0FP9wNm9q9m\ndhZwK8E41bQX8mdnZ2ydRAuAfIJxzWlvnPkZyXi3j1zI+ckVypMAI55POcPd345d4ejvYAN4JsKQ\nUi42jv+T7p42vboQfc/uAGb2KeBX7v4MwV+F+wat0hn7t2QU7Yn7/RCAux9IasApFkJ+1hJcdjsR\n+C3wqrtn5F/iSc7Ns0CDmZ0R2/cpwIWx9t4kh54SY8zPSMa7fdpJcn5yhfIkxzTofMopZjbRzL4B\n/AD4bH/xm0OuBVZHHcRgaVPsmtm5QL27fyO26BAw+JJx//sDo2hPdAPwCzJYsvNjZnnAo8A33P0a\n4Ezg783slqQHH7Jk58bdDxNciv1rM/sucAnwI4I7bPeSYY4jPyMZ7/ZpJYT85ArlSY5yjPMpp7j7\nEXe/g2C88t1mdmbUMaWKmdUCFe7+WtSxDJYWxW6su3+xu/9zwuJtBGNKJyYsqyO4cah9FO2JPk5w\nV2RGCik/fwa87e7vArj78wTDGjLq5pKwPjvuvs3db3H3L3gwjVA9sM7du0M9oCQ7zvyMZLzbp42Q\n8pMrlCcZYIjzKSfFhvf8G/CVqGNJoT8HDpnZKjNbBZwFzIq9nxZlYJEXu7FLxJe6+9cTll1AcBfj\nHmBRwuotBNObMIr2/n1VA3PJ0EHiIeangqMHjz/DwLtp01qYnx0zqzKzCQntZ5Jhd1qPIz8jGe/2\naSHE/OQK5UnihjmfcoKZlZnZb2JzLffrIpiDOie4+2Pufq+7P+juDxLUFFti79+MMraopx6bSHBD\n1JcTllUDl8VuoPom8OnY8jxgJfBtCGZbGK49wYxQDyJEIeenFVgwqFfmHOCJ8I4oeVLw2fkFcHOs\nfQrwYeDeUA8qicaTn0HyCG7Mixvj9mkpzPyMsT1jZcPnIARZ+/MeznDnU2RBpd4E4AwG3tfxF2RY\nJ0m2sijHTpvZx4EfE/z10+9E4H53vzXh6TwVBBM0/4+7P5qw/bDtsXVmEcz315xpl9bCzo+ZzSUY\nTL6T4EQtJxjDm/ZPUEtBbq4BlhHcuDcD+I67vx3mMSVTEvJTB1wK/B3B0/W+A/ys/6/z0Zx76SwF\n+Rm2PVtk+ucgWXLl5z2Ukc6naKJKPTM7D1hKcMWjkmCKz39x95ybki52k+KVwByCB4w85O77I4sn\n924UFBEREZFcEfmYXRERERGRsKjYFREREZGspWJXRERERLKWil0RERERyVoqdiWrmVlB1DGIiIhI\ndFTsSrZrjD2n/JjM7AIzWzDcDmKPQBQREZEMpF4vyWruvt7MZgzT/pSZ/djM7iF4pPQsoBZoAE4C\nSoALzGxxps3TLCIiIip2JcOZ2XJ3f8LMKgiew13l7qsHrbZziG0XAduBLxAUuB1ADcGjpf8IvOPu\nPWZ2lwpdERGRzKRiVzLdRWZ2ObAfOAH4rzFs+z7wT+7+GaD/6Wg/SXJ8IiIiEiEVu5LpDrj7dQBm\ndhkw5GMZY72/E919V2zRbmBvrO0iYCtBD+8s4BLgW+7+Qoixi4iISMhU7Eqm6x30foaZXQpMJhhz\nOwk428zuBgx4AXgotq7zQXF8BPgH4NcERe8hYGO4oYuIiEjYVOxKxjOzVcACgtlFngXmEBS1a9x9\nZ2zM7edH2E0vsAZYT1AUdwEHQwtaREREUkLFrmSD14HfAKcDncDzwGJ3bx3jfpYT9AT/H1Dg7j1J\njVJERERSTvPsSsZz91Z3fzP2tsfdXwcuN7OpY9zV4+7+AEGxW5LUIEVERCQS6tmVbFJEMPwA4B5g\nLNOF1QDXmNl5sX28aGY17r47yTGKiIhICqnYlUyXb2ZfBk4muMnsZQB3/+0Y99MKvOXuzyU3PBER\nEYmSil3JdDOA7xHMk3st8Nbx7CQ2HVn/lGSYmQGz3X0TwawNIiIikoFU7Eqmu8fd3wAwsx+5+5HY\n60bgo8CjDD3+tnConbq7m1mzmTUDE5IbsoiIiKSKblCTjObu/53w+kjC61eB/wV+CuwbYvNahum1\ndfcngbkEQyREREQkA5m7rtBK9jKzOmCqu784RPu0hJkchtrHYo3lFRERyUwqdkVEREQka2kYg4iI\niIhkLRW7IiIiIpK1VOyKiIiISNZSsSsiIiIiWUvFroiIiIhkrf8HJuPE+AdYPMYAAAAASUVORK5C\nYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.arange(5)\n", + "fig = plt.figure(figsize = (10,8))\n", + "\n", + "ax1 = fig.add_subplot(211)\n", + "ax2 = fig.add_subplot(223)\n", + "ax3 = fig.add_subplot(224)\n", + "\n", + "\n", + "df.plot(ax = ax1)\n", + "df.iloc[:5].plot(ax = ax2, ls='--')\n", + "ax3.plot(x, x**2, 'g')\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "参考资料：\n", + "* http://www.matplotlib.org\n", + "* http://github.com/jrjohansson/scientific-python-lectures" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.0" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 950acab7179697fcccbddcd07d3b07ac4afc3a11 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Mon, 20 Nov 2017 20:07:40 +0800 Subject: [PATCH 13/30] Update 9.md --- chapter2/9.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/chapter2/9.md b/chapter2/9.md index a72801614..67250b814 100644 --- a/chapter2/9.md +++ b/chapter2/9.md @@ -10,7 +10,7 @@ 9.1 抽取指定行文本作为实验语料 -请读者下载文本文件：`http://pan.baidu.com/s/1c1RukqW 密码: 3c32`，并将文件解压，保存到目录:`d:\temp\`下，文件名为：`语料.txt`。解压时间较长，请耐心等待（好在只解压一次）。   +请读者下载文本文件：`http://pan.baidu.com/s/1c1RukqW 密码: 3c32`，并将文件解压，保存到目录:`d:\temp\`下，文件名为：`语料.txt`。解压时间较长，请耐心等待（好在只解压一次）。   (下载慢的话，可以临时下载：http://yunpan.blcu.edu.cn:80/link/FC61CB2B791A1999439CEC52C1A30CE2) 可用文本编辑器打开`语料.txt`来查看文件内数据格式，但是打开这个10G文本文件比较慢。我们可以进入到powershell下，键入：`Get-Content d:\temp\语料.txt -totalcount 10`，来查看文件的前10行。 对单个文本文件，如果比较大(如10G bytes)，则可以考虑先取这个文件的前n(如n=5000)行另存为一个小文件，对这个小文件来进行统计，如果没有问题了，再对这个较大的文件进行处理。 当然，在大多数时候，我们面临的统计任务可能会是很多文件，可能会是较大规模的语料(几十G或者更多)，则也最好不要直接对其进行编程操作，而是拷贝几个相同格式的语料到一个临时目录，对这个目录进行统计实验，这样不但执行起来快捷，而且如果程序有错误，也容易查找。 From 0975f96473cc169d831f82c69e19c7987c267942 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Mon, 20 Nov 2017 20:08:26 +0800 Subject: [PATCH 14/30] Update 9.md --- chapter2/9.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/chapter2/9.md b/chapter2/9.md index 67250b814..a61170efe 100644 --- a/chapter2/9.md +++ b/chapter2/9.md @@ -10,7 +10,7 @@ 9.1 抽取指定行文本作为实验语料 -请读者下载文本文件：`http://pan.baidu.com/s/1c1RukqW 密码: 3c32`，并将文件解压，保存到目录:`d:\temp\`下，文件名为：`语料.txt`。解压时间较长，请耐心等待（好在只解压一次）。   (下载慢的话，可以临时下载：http://yunpan.blcu.edu.cn:80/link/FC61CB2B791A1999439CEC52C1A30CE2) +请读者下载文本文件：`http://pan.baidu.com/s/1c1RukqW 密码: 3c32`，并将文件解压，保存到目录:`d:\temp\`下，文件名为：`语料.txt`。解压时间较长，请耐心等待（好在只解压一次）。   (下载慢的话，可以临时下载：http://yunpan.blcu.edu.cn:80/link/FC61CB2B791A1999439CEC52C1A30CE2，作为小的试验文件，只有100多k)。 可用文本编辑器打开`语料.txt`来查看文件内数据格式，但是打开这个10G文本文件比较慢。我们可以进入到powershell下，键入：`Get-Content d:\temp\语料.txt -totalcount 10`，来查看文件的前10行。 对单个文本文件，如果比较大(如10G bytes)，则可以考虑先取这个文件的前n(如n=5000)行另存为一个小文件，对这个小文件来进行统计，如果没有问题了，再对这个较大的文件进行处理。 当然，在大多数时候，我们面临的统计任务可能会是很多文件，可能会是较大规模的语料(几十G或者更多)，则也最好不要直接对其进行编程操作，而是拷贝几个相同格式的语料到一个临时目录，对这个目录进行统计实验，这样不但执行起来快捷，而且如果程序有错误，也容易查找。 From bb1d38c323c703a411f8cbb653cea46e86f9fa59 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Mon, 20 Nov 2017 20:14:39 +0800 Subject: [PATCH 15/30] Update 7.md --- chapter2/7.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/chapter2/7.md b/chapter2/7.md index 7039e091c..5f520828d 100644 --- a/chapter2/7.md +++ b/chapter2/7.md @@ -174,7 +174,7 @@ for i in range(x-1, -1, -1): # 示例代码 9 line = '北京语言大学信息科学学院' x = 4 -print(line[0:x] + line[x-1:0:-1] + line[0]) +print(line[0:x] + line[x-1::-1])   # print(line[0:x] + line[x-1:0:-1] + line[0]) ``` 本段代码中形如`序列[m:n:i]`的操作称为**序列切片**，就是从序列中取出索引在[m,n)之间，以i为间隔的所有对象，默认i为1。 From 60271067ba40bc725ee538196d5d81852014dcc9 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Mon, 20 Nov 2017 20:17:49 +0800 Subject: [PATCH 16/30] Update 6.md --- chapter2/6.md | 1 + 1 file changed, 1 insertion(+) diff --git a/chapter2/6.md b/chapter2/6.md index 3035ccd95..d51640c26 100644 --- a/chapter2/6.md +++ b/chapter2/6.md @@ -145,6 +145,7 @@ while i < n: words.append(word) i += 1 +i = len(words) #事实上，这句话也可以省略，读者可自行分析原因，但不建议省略，影响程序可读性 while i > 0: i -= 1 print(words[i]) From 8cf1d30995af000c2d9814eedc73c579ef72077c Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Thu, 23 Nov 2017 11:36:50 +0800 Subject: [PATCH 17/30] Add files via upload --- ...350\231\253\345\205\245\351\227\250.ipynb" | 463 ++++++++++++++++++ 1 file changed, 463 insertions(+) create mode 100644 "chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" diff --git "a/chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" "b/chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" new file mode 100644 index 000000000..b81da833c --- /dev/null +++ "b/chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" @@ -0,0 +1,463 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### By liupengyuan[at]pku.edu.cn\n", + "### Project: https://github.com/liupengyuan/" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1. 什么是爬虫\n", + "简而言之，爬虫就是一段能够获取互联网信息（数据）的程序/工具。\n", + "\n", + "一般需要通过抓取网页来获取互联网的信息与数据。\n", + "\n", + "网页本身就是一个本文文件，只不过这个文本文件是由特定规则和符号标记的(HTML,超文本标记语言)，称为超文本文件，也可称为网页源代码。\n", + "\n", + "这段文本经过浏览器的解析（各类图片视频等在此过程中从网页外部加载），就成为我们日常浏览的网页展示给我们的样子了。\n", + "\n", + "因此，爬虫首先就是要获得网页这个文本文件，并进行解析。\n", + "\n", + "如果所需数据就直接在网页文本文件中，则可直接得到；如果所需数据在网页外部，则通过解析的结果得到数据所在地址，将该数据下载。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2. 最简爬虫**\n", + "\n", + "这里我们以优秀的python第三方库requests为例，该库是“唯一一个非转基因的Python HTTP库，人类可以安全享用”。\n", + "\n", + "其中HTTP(HyperText Transfer Protocol)是互联网上应用最为广泛的一种网络协议，超文本文件传输时，必须遵守这个协议。\n", + "\n", + "非转基因是作者幽默的说法，表明该库是原汁原味符合python设计理念，易用易于理解。\n", + "\n", + "输入以下代码，并观察执行结果。" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import requests\n", + "from bs4 import BeautifulSoup\n", + "import re" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "导入必要的模块" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "r = requests.get('https://github.com/liupengyuan/python_tutorial/blob/master/chapter1/0.md')\n", + "print(r.text[:1000])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- import requests，首先导入requests库\n", + "- r = requests.get('https://github.com/liupengyuan/python_tutorial/blob/master/chapter1/0.md')，调用requests的get方法，向网址https://github.com/liupengyuan/python_tutorial/blob/master/chapter1/0.md 发送获取(get)请求，该方法返回一个应答(Response)对象r，其中包含该网页的所有信息。\n", + "- print(r.text[:1000])，利用对象r的text属性字符串，打印网页内容，因为内容较多，暂取前1000个字符。\n", + "- 打开https://github.com/liupengyuan/python_tutorial/blob/master/chapter1/0.md网页，在网页正文区域点击右键，选择查看源代码，会发现代码示例D-1确实已经获取/抓取这个网页的文本文件。\n", + "- 至此，一个最简爬虫已经完成。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3. 静态定向爬虫基础**\n", + "\n", + "- 本小节中的爬虫是开始就指定了要抓取网页的地址（定向），要抓取的内容直接存在在网页源代码中（静态），因此称为静态定向爬虫。\n", + "\n", + "- 由于需要用到Chrome浏览器中的**检查**功能，因此需要读者下载安装Chrome浏览器。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.1 抓取网易首页(www.163.com)上的全部新闻**\n", + "\n", + "- 我们打开网易首页，然后用鼠标右键点击页面，用chrome浏览器可选择检查，进入开发者模式。\n", + "- 发者模式中，右侧为开发者工具面板，右上部的Elements标签页面中显示一片代码，是该网页html标记的文本（经过整理对齐的）。\n", + "- 推荐教程：http://www.w3school.com.cn/html/index.asp ，快速浏览，可了解一些html基础知识。" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "r = requests.get('http://www.163.com/')\n", + "print(r.text[:1000])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 用鼠标右键在新闻标题上点击，并选择`检查`，可在Elements标签页面找到该新闻标题以及对应的链接在html代码中的位置。\n", + "- 代码大致如下形式：\n", + "```\n", + "\n", + "```\n", + "- 其中xxxxx及yyyyyyy随新闻标题不同而不同。前者是新闻链接，后者新闻是标题，因此这两项是我们感兴趣并希望抓取的内容\n", + "- 在Elements标签页面中继续查看各个新闻标题，可以发现各个新闻其实都在标签对`
  • `及`
    • `之间，且没有其间没有换行符。" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "p = r'
  • (.+)?
    • '\n", + "contents = re.findall(p, r.text)\n", + "print('\\n'.join(contents[:5]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `p = r'
  • (.+)?
    • '` 构造了正则表达式，可提取`
  • ...
    • `之间的内容(不包括之间的换行符)\n", + "- `re.findall(p, r.text)` 将r.text中所有的符合上正则的提取出来放入列表\n", + "- 最终打印前50行，可以发现后面有一些并非新闻标题与对应链接，并非所有在`
  • ...
    • `之间的内容都是目标内容\n", + "\n", + "- 有关正则表达式，可参考教程：https://github.com/liupengyuan/python_tutorial/blob/master/chapter3 中的正则表达式快速教程。可以通过构造一些正则表达式来完成网页解析将目标内容提取。\n", + "- 这里我们将介绍一个优秀的第三方网页解析包：Beautifulsoap。该包已经随Anaconda安装，名称为bs4。可以用这个包(必要时联合正则表达式)来进行网页解析。\n", + "- 该包已经通过`from bs4 import BeautifulSoup`在开始导入" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "soup = BeautifulSoup(r.text, 'html.parser')\n", + "contents = soup.find_all('ul', attrs='cm_ul_round')\n", + "print('type is:', type(contents))\n", + "contents[:1]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 函数BeautifulSoup(r.text, 'html.parser')，返回一个BeautifulSoup对象。第一个参数为要解析的网页文本，第二个参数是解析器的选择，暂选择python内置的'html.parser'作为解析器\n", + "- soup.find_all('ul', attrs='cm_ul_round')，BeautifulSoup对象的方法，可返回指定标签之间的所有内容的ResultSet对象。其中第一个参数为标签，第二个参数为标签的属性。根据新闻标题，在Elements标签页面稍加分析可知：新闻标题及链接均在标签对`
      `及`
    `之间，且其他非新闻标题的内容，均不在这种规定了class的`
      `标签之间" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "for line in contents:\n", + " url_titles = line.find_all('a')\n", + " for url_title in url_titles:\n", + " url = url_title.get('href')\n", + " title = url_title.string\n", + " print(type(url_title), url, title)\n", + " if input()=='b':\n", + " break" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 可对ResultSet进行遍历，利用`line.find_all('a')`取得其中在``及``标签对(该标签对表示超链接)中间的内容，link_texts的内容仍然是一个ResultSet对象，含有所有的link及text\n", + "- 对link_texts进行遍历，每一个对象均为`Tag`对象，利用`Tag`对象的`link_text.get('href')`方法，该方法可以取得标签的属性值，本例中参数为属性`href`，其值为超链接的URL\n", + "- 利用标签的`string`属性，取得该超链接的文本" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "url_title_dict = {}\n", + "for line in contents:\n", + " url_titles = line.find_all('a')\n", + " for url_title in url_titles:\n", + " url = url_title.get('href')\n", + " title = url_title.string\n", + " if url and url.endswith(r'.html'):\n", + " try:\n", + " url_title_dict[url] = title\n", + " except KeyError:\n", + " continue" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 这里暂只需要得到首页的标题及对应的新闻页面链接，因此只抽取链接结尾为`.html`的条目\n", + "- 所有结果存入到词典url_title_dict中\n", + "\n", + "我们还要获取各链接下的新闻文本" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "title_text_dict = {}\n", + "for url, title in url_title_dict.items():\n", + " r = requests.get(url)\n", + " soup = BeautifulSoup(r.text, 'html.parser')\n", + " html = soup.find('div', attrs = 'post_text')\n", + " if html:\n", + " passages = html.find_all('p')\n", + " text = ''\n", + " for passage in passages:\n", + " if passage.string:\n", + " text += passage.string\n", + "\n", + " title_text_dict[url] = title, text" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 通过点击新闻页面，可以发现，所有正文在`
      ...
    `标签对之间。\n", + "- 每个例句均在`

    ...

    `标签对之间" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import requests\n", + "from bs4 import BeautifulSoup\n", + "\n", + "def get_word_sents(word):\n", + " url = r'http://dict.youdao.com/example/blng/eng/{}/#keyfrom=dict.main.moreblng'.format(word)\n", + " try:\n", + " r = requests.get(url)\n", + " except:\n", + " print('Can not get the page.\\n')\n", + " return False\n", + " \n", + " word_sents = []\n", + " soup = BeautifulSoup(r.text, 'html.parser')\n", + " contents = soup.find('ul', attrs = 'ol')\n", + " sents = contents.find_all('p')\n", + " for sent in sents:\n", + " word_sents.append(sent.text.replace('\\n','')+'\\n')\n", + " \n", + " return word_sents" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 整个过程与网易新闻抓取的方法类似\n", + "- `word_sents.append(sent.text.replace('\\n','')+'\\n')`，是为了写入文件时候较为整齐" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import os\n", + "test_word = '爬虫'\n", + "sents = get_word_sents(test_word)\n", + "with open(test_word+'.txt', 'w', encoding = 'utf-8') as f:\n", + " f.writelines(sents)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4. 动态页面的抓取(以后)**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5. Scrapy爬虫框架(以后)**" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.0" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 3c9def6bc94473e9e3e9768304845bb3febdce5f Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Thu, 23 Nov 2017 11:43:24 +0800 Subject: [PATCH 18/30] =?UTF-8?q?Update=20python=E7=88=AC=E8=99=AB?= =?UTF-8?q?=E5=85=A5=E9=97=A8.ipynb?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...thon\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git "a/chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" "b/chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" index b81da833c..349452acc 100644 --- "a/chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" +++ "b/chapter4/python\347\210\254\350\231\253\345\205\245\351\227\250.ipynb" @@ -37,8 +37,7 @@ "其中HTTP(HyperText Transfer Protocol)是互联网上应用最为广泛的一种网络协议，超文本文件传输时，必须遵守这个协议。\n", "\n", "非转基因是作者幽默的说法，表明该库是原汁原味符合python设计理念，易用易于理解。\n", - "\n", - "输入以下代码，并观察执行结果。" + "\n" ] }, { From 1fb421dee070e3ab4ea2b44b91ad633a1337c492 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Thu, 23 Nov 2017 21:34:33 +0800 Subject: [PATCH 19/30] Update 7.md --- chapter2/7.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/chapter2/7.md b/chapter2/7.md index 5f520828d..73d215810 100644 --- a/chapter2/7.md +++ b/chapter2/7.md @@ -260,7 +260,7 @@ print(numbers) numbers = tuple() print(numbers) -numbers = (1) +numbers = (1)   #数字而非元组 print(numbers) numbers = (1,) From 9fccec35b5cb1d17a65052416fa29fea30d9cb7c Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Sat, 25 Nov 2017 12:54:00 +0800 Subject: [PATCH 20/30] Add files via upload --- chapter4/jieba_wordcloud.ipynb | 630 +++++++++++++++++++++++++++++++++ 1 file changed, 630 insertions(+) create mode 100644 chapter4/jieba_wordcloud.ipynb diff --git a/chapter4/jieba_wordcloud.ipynb b/chapter4/jieba_wordcloud.ipynb new file mode 100644 index 000000000..7e0054875 --- /dev/null +++ b/chapter4/jieba_wordcloud.ipynb @@ -0,0 +1,630 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 结巴分词及文本内容词云展示\n", + "### by liupengyuan[at]pku.edu.cn\n", + "### https://github.com/liupengyuan" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**1. 简介**\n", + "\n", + "**1.1 分词**\n", + "\n", + "中文句子中词汇之间没有显式的分割，在进行词频处理以及内容分析前，一般需要自动分词。可以完成自动分词(含词性标注)等的工具很多，最常用的：\n", + "- LTP（哈工大开发，除分词外，还有很多语言信息处理的功能模块）\n", + "- NLPIR（北理工开发，前身为中科院ICTCLAS分词系统，除分词外，还有很多语言信息处理的功能模块）\n", + "- jieba分词（以分词词性标注为基本常用功能）\n", + "\n", + "其中jieba分词是纯python开发，这里将以jieba分词的使用为例。\n", + "\n", + "**1.2 词云**\n", + "\n", + "文本内容一个最常用的可视化展示即词云展示，文本中词频越高的词汇，在词云中相对字体越大越明显。有很多在线词云工具(可自行百度)。\n", + "\n", + "这里介绍python的第三方工具包wordcloud，功能齐全，与在线词云工具相比优势是：可以自动批量生成词云。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2. 分词工具包(结巴)**\n", + "- 项目地址：https://github.com/fxsjy/jieba\n", + "结巴分词是国人开发的优秀python分词工具包，便于使用。\n", + "\n", + "windows下安装：\n", + "- 进入powershell\n", + "- pip install jieba\n", + "\n", + "进入jupyter notebook，执行import jieba，如果没有出错，则表明该工具包已经被正确安装" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2.1 基本使用**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2.1.1 分词**" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Full Mode: 我/ 来到/ 北京/ 清华/ 清华大学/ 华大/ 大学\n", + "Default Mode: 我/ 来到/ 北京/ 清华大学\n", + "他, 来到, 了, 网易, 杭研, 大厦\n", + "小明, 硕士, 毕业, 于, 中国, 科学, 学院, 科学院, 中国科学院, 计算, 计算所, ，, 后, 在, 日本, 京都, 大学, 日本京都大学, 深造\n" + ] + } + ], + "source": [ + "# encoding=utf-8\n", + "import jieba\n", + "\n", + "seg_list = jieba.cut(\"我来到北京清华大学\", cut_all=True)\n", + "print(\"Full Mode: \" + \"/ \".join(seg_list)) # 全模式\n", + "\n", + "seg_list = jieba.cut(\"我来到北京清华大学\", cut_all=False)\n", + "print(\"Default Mode: \" + \"/ \".join(seg_list)) # 精确模式\n", + "\n", + "seg_list = jieba.cut(\"他来到了网易杭研大厦\") # 默认是精确模式\n", + "print(\", \".join(seg_list))\n", + "\n", + "seg_list = jieba.cut_for_search(\"小明硕士毕业于中国科学院计算所，后在日本京都大学深造\") # 搜索引擎模式\n", + "print(\", \".join(seg_list))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 以上实例来自其官网\n", + "- 我们一般使用其缺省模式，即第二种模式" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2.1.2 词性标注**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Building prefix dict from the default dictionary ...\n", + "Loading model from cache C:\\Users\\user\\AppData\\Local\\Temp\\jieba.cache\n", + "Loading model cost 1.254 seconds.\n", + "Prefix dict has been built succesfully.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "北京 ns\n", + "语言 n\n", + "大学 n\n", + "汉 j\n", + "研 vn\n", + "中心 n\n" + ] + } + ], + "source": [ + "import jieba.posseg as pseg\n", + "words = pseg.cut(\"北京语言大学汉研中心\")\n", + "for word, flag in words:\n", + " print('{} {}'.format(word, flag))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 其中的词性标记，采用和ictclas兼容的标记法（词性标记集）\n", + "- 其中'汉研'没有被正确切分" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "北京 ns\n", + "语言 n\n", + "大学 n\n", + "汉研 x\n", + "中心 n\n" + ] + } + ], + "source": [ + "jieba.suggest_freq('汉研', tune=True)\n", + "words = pseg.cut(\"北京语言大学汉研中心\")\n", + "for word, flag in words:\n", + " print('{} {}'.format(word, flag))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用suggest_freq，调整'汉研'，使之能够被正确切分\n", + "- 更好的办法是使用自定义词典，具体方法请参见其官网介绍：https://github.com/fxsjy/jieba " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3. 词云工具包(wordcloud)**\n", + "\n", + "该项目地址：https://github.com/amueller/word_cloud\n", + "\n", + "windows下安装：\n", + "- 下载 http://yunpan.blcu.edu.cn:80/link/294855A5A760AC53797C1683E2934F59 并安装(针对python3.4以上)\n", + "- 进入powershell\n", + "- pip install wordcloud\n", + "\n", + "进入jupyter notebook，执行import wordcloud，如果没有出错，则表明该工具包已经被正确安装" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.1 极简词云**" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from wordcloud import WordCloud\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "导入必要的包" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "text = 'The quick brown fox jumps over the lazy dog'" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "image/png": 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f9TL2J03nLQLoIXBEl0Sy2rYQD95VXpYueJOcKvfugNuq3WUAZOrC70ERDSGV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\nwDEteQ1NY9GSNiQ+VT4DRbbE0mkqmQj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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wc = WordCloud()\n", + "wc.generate(text)\n", + "plt.imshow(wc)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `wc = WordCloud()`，声明一个WordCloud对象\n", + "- `wc.generate(text)`，调用WordCloud对象的generate(str)方法，参数是一个字符串，可以生成该字符串的词云\n", + "- `plt.imshow(wc)`，调用plt的imshow()函数，将wc词云载入(imshow即image show简写)\n", + "- `plt.show()`，显示当前被载入的图片\n", + "\n", + "至此，一个极简词云已经完成。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.2 词云基本设置与使用**" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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gLAbDp7Hthna23dC+RC3K8QI4i2micBvZiOJra2RRjOz5KjBlDC+zlXmXpH0p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\n0Ofhnnq5fu/NJMvrwuXSrvj35U/0GRmX2jZOp4aqJW+DsZi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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wc = WordCloud(background_color='white', width = 1000, height = 500)\n", + "wc.generate(text)\n", + "plt.imshow(wc,interpolation='bilinear')\n", + "plt.axis('off')\n", + "wc.to_file('first.png')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `background_color='white'`，将背景色设为白色\n", + "- `width = 1000, height = 500`，设置图片宽与高\n", + "- `plt.axis('off')`，关闭坐标轴\n", + "- `wc.to_file('first.png')`，WordCloud对象的`to_file()`方法，将图片保存" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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n50QFZOD215aZSTSRIKEb/PD0aaIJnS9u2sCm4iJsC6g5Y5pTYy4Ft/AWmCzV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\n0clZt6ZpEkvo9I0GefH4Rfa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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "text = '北京 语言 大学 汉研 汉研 汉研 汉研 汉研 中心'\n", + "local_font_path = r'C:\\Windows\\Fonts\\simsun.ttc'\n", + "wc = WordCloud(font_path=local_font_path, background_color='white')\n", + "wc.generate(text)\n", + "plt.imshow(wc,interpolation='bilinear')\n", + "plt.axis('off')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `font_path=local_font_path`，给出中文字体\n", + "- `interpolation='bilinear'`，利用线性插值是字体缩放平滑" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4 实例**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "任务：利用抓取的www.163.com 首页新闻文本，制作词云" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import jieba\n", + "import re\n", + "import numpy as np\n", + "# from collections import Counter\n", + "from wordcloud import WordCloud\n", + "import matplotlib.pyplot as plt\n", + "from PIL import Image" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "引入需要用的各种包" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "with open(r'news_163_home.txt', encoding = 'utf-8') as f:\n", + " txt = f.read()\n", + "seg_list = jieba.cut(txt)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "读取文本文件，切词" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "with open(r'stopwords.dat', encoding = 'utf-8') as f:\n", + " stopwords = set(f.read())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "读取停用词文件，并形成停用词词表" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "323182" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "clean_seg_list = []\n", + "for seg in seg_list:\n", + " if re.search(r'[\\u4e00-\\u9fa5]+', seg) and seg not in stopwords:\n", + " clean_seg_list.append(seg)\n", + "text = ' '.join(clean_seg_list)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 过滤掉非中文词和停用词\n", + "- 用空格链接成一个字符串" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "font_path = r'C:\\Windows\\Fonts\\simsun.ttc'\n", + "wc = WordCloud(font_path=font_path,background_color=\"white\")\n", + "wc.generate(text);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "生成词云" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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ylg0psA0dQ9MIooiFSh3bMFBQcPyAUAiWa00Stsmh0X5Ssc0tmFMXZinX2gz0\npnn04CjJ+EalHwQRb7x7hUqtzcHdAzz3xC5eemov2VXhq2wU6puh3nT5+Nw0PfkkB3YNrIvhBzKk\nFToYio6macQ1e3Nv0Q85dX6GWsPh8L4hnnxkx4ZrHDfgrQ+u8YM3znH88BivPX+A44dHGRvKc+zg\nCIVsgvHh/GeO7erqrS1sqiaHMgc5lLkVQ5dSsjRXZeFmBVBIpmxUJ0aUkKyUavh+iPRtnJbHolch\nnYmTzt5/64V7QUFDVzveZju4RtzYjaX1k7I2estr31GUDcbZ7dAVE0tLYahxIuljqQkiGaAqGnlr\nBCGj25T91hCyQ7F1IwepSFphi6pfYSg2zERyFxljozFyN4wkNl6/SgEeia//zNR0XhjYXA6E3byQ\nEJJSq00hEe8YjF0W3edNCn8olICUkmrLYbnWJIwElq7z3pWbeN2ijZ19+Q3f8SMPTdVQ0Vh0ZzhV\n+Tn7Usd4sffrJLT0p9pcS+4sN1tX1uL5y94c52ofsSOxn6SefiBOfiDaeFGTQDhIBM2wiKUmH7je\nAbqtBUTAWLyfZujQb+cYsHOU/Tq2ZpE2kozEIa4/mMcipWS6fY03lv+Ka81zPJJ9imcKX6TfHrlr\n99TVzpei26ag5fsUYnF2D/SQjlsoKJSbbYbzaWZLNTJxm1rbxQ+jtYKyVURC8POPriOFZO/OPg7v\nHdz03WlahwdSbzosrNSJx0ys2/q53I8nIITk+s0i/+ZPfk7MNvnyCwf5+hcOE4914rIpPUHOTJPo\nNgz0hI+2iTV5c67MlcllhJS8+ux+UsmNNFZV7eQ7Flbq/PDN8wwNZDl+eJTeQop/9M0nSMQt4vYv\nr0OtiASuG2CaOr4fUF5p4LkBgyN5EimbSqnJylKNKIxoNz36h3OUluogWacETi0sMN+s84UdEw/c\nlqGTcDew9I7lamkDaEqCjh+29bMr3F14q4pOQs9hKCaRjLrvXsVQbTTFWKtXuNt+jaSg6C50CroU\nlUB2wmJ5M08zbNIKW+SMXpaceid1pkDOjBFEgslKlbFspmMI/RIQiAgJZGI2Bwb6mK/VGc1lqDnu\nmtH1eeKhUAK6phG3TLywjaGpeGFE3XEZ68ltSZ38uPoWRW+Ro9mn+Kj8JsOxnbzU+w1omlyZnsZt\n+2QLSUZ393P17Ax9wznq5Ra9QzkMU8ew7hBGMuR09V0qwQrQ4cE/WXiZE/kvkDN7H0gBuGGNFecq\nraiEkBFU9ayzAAAgAElEQVS2lqbs30SIkP7YgQeeH01RGbQLBCKk1XJJ6h0hpaBgqwYpI0Zct7Yc\noxu1KXpLpIxMx6NBXauAfnPl+zhRm68P/SMOZ54goaXuKUxVRSFuGGiKQn8ySdKy1lko71+d4fL8\nMpm4Td3xSNkW+VSc/myKO+Xl+SsLXJ1aJpW0efzI+IYiq7U56Majbcvg5af28uKTe7Bu7+54x5Cl\nlPhBiB9EuG7AzEKF05fmePfkDeaWOsnVtuNzeN8QB3cPAKArGgk9RkpP0I5cyn6NHmu9BRdFgk8u\nzHBjuohl6Az0pHC9AMtcz/zS1A6XH+DYoVFefXZf5zc0lZHBzj0Xyw1sQ18jQmjdrqqGod13N8zZ\nyRVq5Ra7Dw4RRYJY3AKl8/cP37rM068cWst52PFOEVOr4ZJI2QR+CBJWFuv0DWZp1h1yPbf2m5CS\n/+/Cef72xnW+P3iZf3jkKMcGBkmY5gO1MwiiMmXnbdxgFl2bQVUs3GCGSDaRCDQlRso8itb13u9k\n0N3ZpkFBQ0NDSNZyEFKCsZrrUW6N/3byg7wtB6MreidHoqhIVRLIgJyRQ1d1skaOm+0pUnqBoudi\nKBqGquKEPhYmf3j6FDXX5bsHDzGcznxulvlis0EkBJGQhEJgahrZmE3cNKg7Hj2JOAL5uXNIHwol\n4AUhi9UGXhDiRx1XricZp9Z2WKw22DWwMZbsCZcPyz/jo8pb9FvD/ObwPyVlZCl7dYoLVQoDGVRN\npV5p4bZ9Lp6colltE/gRA2P5dUpAIplp3+BS4xN84aErBsdyz/By7zc7HsAmC361rYWqqBsobraW\nYTjxKHPtT4hpGZJGH0m9F1XRsLQHqwJcpYfpqrYJi0Cw4tW43pxnxa2iqzrP9BzacA9PuLxT+jG1\noMSzPV9iwB7jfO1D3iv/lCF7By/0fpWh2I777q0ku+NywpDFZpNRTUNX1E7/eyF5fNcwE/05hvNp\nFqtNRgoZztxcwAvWF9kFYcQb73VCPIahce3mMhevLTI+UiARW8+a0DV1Lfkbs431CuAOtNo+Zy7N\nMbdY48ZskbnFKmEYMdiXYe/OPuYWq1TqDt/9yqPsHu+99b2wTcWvU/ZqSCS7kqMYd7zbuaUqH565\nSavbqO5//j/+hm++epSvvXyYwb5ba0VRbxWvjQ3lyKZiG+b2+z8/R6XeRtc1bFMnbpukEzYjvVkO\n7ujfNCx2+ztoN12uX1ogFjM5+9EU89MlXv3mYwgheO9nl2g3PWJJizDoep9Somoq8aTFymIdw9Dx\n/ZBEyiYMIxR1vQ2+2Gzy/twsK+0Wf3v9Gh/MzfLaxC5+69Bh9vf0kjDvz5ORMiQSLSLZgkhFVTwi\n2SKM6oBEKG1gvYe8yiSaqdf50fVr9/U798JUtbbGvCn7JXRVZVdiN07kcK52hifyJ/CET8kvsi+1\nnwVnCVPNsuTWsVWDQ9lBaq5HK/B5ffIGV8slBpOpB2pffTcsNho4YYitG7SDgJiu0/R8DE2j1G5T\nakFvKoH9OXc0fSiUQMzUOTzaTxgJkjGLdy/f5MBIPy3PQ9uCK653N2crrDMvQj4s/4wXe79OZcVB\nCEmr7pJIxXDaHp4bUOjP4DQ9KsUG/aPrw0te5HKxfrJbW6AwkTjAS71fJ3VbteWdkEgu1E8iEexJ\nHlnXS8gXLZrhEpH0WXGv4okmblTH1lJkjBFsLY2UEk8E1INbbCMn8mhHHstuBYBG6FDxGxzJ7MTS\nOr12bucMq4pKv53jQHqcA+lbNLo7odDhJV9unGbBmWZHYh8r3jxP5l/msexzpIwsQgpqQYOseauK\nuDNGn0AESCSWamHelsheFQJOEJI0TGptl9lSjVTMQkrJ1YUi1bZLXyZJ2wtw/GDduKbnypy7PI8f\ndCqHv/fj03x8boZ//K0nefmpvesqajVtY2M26ISTytU2N+fKzC912BzT8xX+4kef0JtPMT6c5+UT\ne5kY66E3n+DyjWXePTkJOPT3pNcpE4nshhcUNEWjEbQwLQOta21GkeDyjSXOXVlA11QiIag3HD48\ne5Mj+4cY6EuviVBFUbpCtStWN9GtJw6Oc3hikCCKuD5XZL5YR1MVfvzBJSqNNl86sXVrEikkk5cX\nmb66xFNfOMDY7n7aTZer5+eYv1nEc3xe+Y1jZPMJyiuNNRKAaekgYe+hYVCgWXfw3ZBCX4prF+eJ\n39Ye4u2bU5ScbgsNoOq6/NmF83w4P8c/OHiYVyd2sTOX2/KsAyklXrSMqfeSth6h6V/B1ApoSpym\nf4mM/eim31udKiEl8406b05NrrtnrdRhARmmjmnpmJZBEEQ0qu2uJ6Os/rcOs/VbSiBr5CgHS1xu\nXCKUIa2wxeXGJQDmnBkeyT7GgD1AMxT0WEl0tdPVtbM2OgbP1/fu458//iTJ+1SG98Jq2whVAScM\naPs6l5eLCCGpOg4x00DXVGKGcd8K+H7wUCgBXdMopBIEYUQ2YXNizxi96TheENuyY5/KLWaPqVok\n9DRSQqvhkszEqCw3MEwNO24RS5jEkzbJTIxUNrbeC5CSeWeKC/WTBNKn1xri5b5v0nOPArV21OTN\nle9TDyo8mn2Wx/Mv0msNoSoqEkEoPNyo1nV3DXTFxFDjd5y8FNIMXUxVZ1VcPJnfT9Btfe1GPk7o\ndVzALgxVX2M9rNL87gVVUdeUZj2scKb2PsOxcYbsHdhagpJXQSJZcleQCHwRdPvMVLFUi3rYQFd0\ncmaGgpbD1DR23VHWHkaCfDJGGEXETB1T11iqNbFNAyE7zfPc2zyBMBJ8eHaamYUqIwNZ2q5Pudom\nZhnE7I0H69zeSdTzQ6ZmS0zNlZiaLTO3WMX1AqbmOq2Fh/oz/N5vP8eusZ4NHoO4Lbyw2np59b4p\nI8kwEO+2FWmEbQIRonVjsLWmwy8+voHrheyd6GdmoYIUktee3c/jR8bXhUhuETHvjWrD4dSVOfrz\nKY7vG8XxAlRNYb7cKURTFJVCamOyNt+b4uVvHOscjtL2SaZjXDx1k/6RHF/8zuP0D+U6lfZJm72H\nhzuHpmgqlm2sGVfJdAyZlOiGRu9glly+Ew6quS7vzsxs2pJhqlrlf//gPd6fm+XLu/fw8o6d9CUS\nmyhpQdV9DylDEuZ+pPSouR92PAPpbqkEVqGpKk+NjPIvv/Dq2t9q5SZXz86ClBQGMpiWTrYnRb3c\n4sbFefYcGsEwdZKZOMYd7/5fvvkzbtaq3Tnt/DNUA03qmFqnBYuhGvTbg5yunuSV/i9jaxDTDOK6\nial1Qnfa51iodTtius6jA4McHxoibVpru/5muUrSMmn5AfO1Ovv6e+96nwfFQ6EEABw/4Oz0YqeY\noyeLG4ScublINmFzML5J4k251Qys1x7k6cJrGJHN2B6TarFBvi+NHbcwLR1FUWk3HMb2DFBertNu\nuNhdpooTtThf/4hlbxZbTfBS7zfYmbh7czjoUEmX3Dk84fBO6cfMOVM83/sV9qaOYmspeuzda10S\nTS3RDQfpWFpnkymKQly3GdVMdOVWqGc8cYv+Ncz6l91nZ0kZceJ6x1obifeSt+599KHKnSEryaI7\n26mpQCGu5Vl0lzEUnXrQxNYsVEVlwV1mwO6l7FXQFI2MkdpSsOmayq6BwlroTki59v+KovD4rhFS\ntyVCF5ZrnDw3jeP6/JNvP8l/fOMc5Wqbg3sHOX54bJ3wFkJSa7iEYYTrh/zkF5c4f2WeZMKmr5Dk\nscOjFLIJfvrOZSZnSmRSNiMD2U1DRlJIwkiuTgNBJDqN/hRoBQFlx2UkZWPpOmkjyWoAVgjJ1EyZ\n9z+Z4vDeQZ58ZAff+/FpPD8gl4nfd3Vzy/WRUpLozkUYRUwvVcin4xzfO4Jt6uwYyNNXSFFtd4ob\nDU2j2lpf6BhFglPvXqO4WKNSbBKGEVEoMAwNISQrCzVUVWH3oSGGjvQR2gJbU0gaBrWgTVqJoava\nulOzevpuraWzy0tcKC6v0RXvhBuGvH1zisvFIjXX5XeOHCVt3Rm+Uklbj9IKrlJ13sPUCqiKRUR0\ndwV5l49MyyDfl2ZucoUwiLC7YcPZGyuEYcSVszOM7x4gdQ+GU1xLkjGTJPUUIBkNR0loCTRVJ5IR\nF+pG57Q/t4WQgvl2tdveYevakc+KZ0bHONo/wFgmg63rndCT59PwPEIp2FnoeF333yrj/vBQKAEv\nCCk12gxkkhi6xqW5Zf70FwscGRvgkR2bW+SdxGgHumJga3EUVSHXmyKZjqHpKkrXTVUUSKRtVE0l\n15tC78bUhBTMOjf4uPI2umLwQu9XOZo9cc/eRI2wxqnq2/jC7YxfuNxsX8Eq2wza48T1GIFw6I8d\nRIG1fupxfX2SsVOMtFF4lOotHC9gqCeD4wZUWw7FWov+XIpUPMZSqdnh6lsGvfEslaaDF3SKk9Jx\ne61X/yo6BT63nklTdA6nn+DpntcYtMepBy1M1SCQIVkjTVzvNLPTFR1bs3EiD9H1R263nFdx+5GS\nt55NWdcneqRwK7QWRoIzl+Y4e3meZ45P8OQjO/jhm51Dagytc8RfsdLkwtVFLt9YYnKmRLHSZGGl\nhqYqHNwzyLe/+Ai5TJxE3CIRM/GDkI/Pzdz1vUHXEwhvxZ+vVUq0An/tyM+YYTCQTGPRScivwvMD\nfvjWeWK2wVdfPkQqYd8XJfVOXJ8t8oP3LhKGEY4fcnzfCCO9WZ48MEY62WkzvXukh7rrsVJvEUaC\nTNwmc4chpGkqhx4bp1pq0qy79A1lUVWVRq3NjcsLPPr0bhamS7z3+kVODOu0rIBQRAzEMpiqTsrY\nmknmBAG/mJlmulbb8hoF6InH+drevXxh5wTxTZhDiqKQMPYS08dwwmmEdEhbxwCVVnCZSLhryeD7\nhWHqRFFE/0gep+3TM5jFcwMMS6c3k6M4X0EztDXvbSvEtTi2rnXWqFRI6R0FKGWnBuFA6hCBEN2D\nqQKElFiagS/EHUpA0gpdplvLa3+JpCCSEaZqEMqIq405HsvtZjzRj6IozLVLLLplrC69t+I3kcDz\nvYfX7aGEabCzkGNHIUe17aKo0JOI36U9yqfDQ6EEHD/g/MwiQRSRTcSwDJ1vPXmIuuMRbdFLpRMS\nWT8Zq5WVpr1xQQotJEJg33b8XD2o8LPlvyIQHicKr/BU4dV1bR02QyQjTlffZa49tcY2yJt9vNz3\nGxxJP0lcT9EIFqn5c4wln8AXDtcbbzGaOH7f8xGEEcVai1TcJmYaFGstqk2HfLpjcQZhRKAIGo6H\nriqU622qTacTStmkM6WCsq5wJq4l+c7IP8PW4gQyxFQDLNVisb1C1kijBRpZI4Oh6h12BhExzcZU\nDQRiLUa+Oh9Vv0hCT99XUZ2UkqVinZ+9f5VUwuZbX3yEntz6cizfD/nrn57lZ+9fZbAvw+OHx9iz\ns4//5f/6CYsrdXYM5zmw+45WxAH3BSHluv48lqZTdhwqrkvWttmdzxPTN87hxWuLfHRmmlee2cdL\nJ/bwSbfP0YPi4M5+dg0XaLkB528soKgKH1+e4dSVWY7vH+HAjgHiloGmqiQsEwUYLmQ2HMGpqgpj\nu/tJZeK0Gh0lcPr968RTNgPDHWNjx94BxvcOUE/4LLkNMkacdugjta3pJVJKLhZXeHdmGj/anM6s\nKgpH+wf4/SdO8MzoKLaub7lnOgZIjISxh0g6nbWomCSN/RtOIlv7zl3mz3V8NE0jiAKa1Rae41Po\ny9A7lMX3QoSQiEjc8/h1RVFwhbt2mpqiqEQixIna6KrRPY1Qw4tUErqFF4U0AxeTO9s8KFiqzmi8\nF1vrPM+HpcssuGV+Y/hpAPamhtfVc8y0l1lyK+xKdgxcTwS40cYFbGgaA+kUqqqQtixipoEXhsT+\nPiaGDV2jkIoTCYmla1iGTtP1qLVd2n7Hur0TCncvKFmFH7ksefNcbZwlaxZ4LPcc0EkGv1f6CdPt\naxzNnOC5ni+TNu5dIbjsznKm+h6tqAF0qKSP517ksezzay2qbS0NZmdDNYMldiafIabd+96rFrWq\nquRS8TWBHnZL9j2/s8hVTaXecskkbCIh1+iQPZmtetArG1ohr7bN0NGJaTYx3WY0PkQ7csgZWQIZ\n0GvlMVSdfruXtJ6k7FewVHOtHiEUIZOti/x48c85mH6Mp3tew9bu7oaHkeD0hVkuXl3gO195lEN7\nBteKY1ZhmTr/8Def5PGj4+wYLpBMWLhegKGra/UAn7bISgi5ZlgoikLdc2n6HkJKbF3Hjzq1Kbdb\ney3H5z/85Aw7hvN89yuPEvsM/H5d01hsNLg4tUQybnHi4DgvPLKLqcUy75ydpFx3ePbITixdozed\nwAsilqqNtfMlbofS7SskgUtnZrh8ZpYTLx9gaLyHC6du8vQrB8n3pih6TZrCI4giQuXuArIdBLwz\nM82FlZWtn0FV+dqevXxh5877fg+KoqIRo+S8QcZ6Al29GxX5LoVihkbfUBZN1xiZ6KOy0kAIwfCO\nXpy2R09/5p6hoFXMObPMtWcRUiAQ9Fp9rHjLnR5SfokD6UMczRzDFyF9dgpD1Sg5zoZwkK5qJNXO\nnmiGDm+tnOWVgUe7ldw6+h39kSSStBFnMNYJl/oiZMEpbzofq+891z13/PNmBsFDogSgE5s9N7PI\n7oEeHM9HyA7XOrVFy4h7Lb5QBCy4M1yqn+Ja8xwpI8dYYjcArbDBJ9V3+LDyM3Yk9vFC79fJm1u3\nh16FF7mcr59kzumwFVRUdiUPcjz3/IYzCmrBPMvu5W6yKbGmtDLmMClj699yvM6B54au0nZ9YpZB\nfy5FreWQiluYhobrBeRTcdqeTzbZWRypuEXL9Ylv0lfkrklKKQllRM7IMBobwok6bSmSRgIhBc2g\nzeH0PmpBA0/4axZNKEKuty7w48U/Y6Z9jWVvDk3VeSL3EjF96wNRag2HH7x5gX0T/bz01F4ScYta\nY2NjP0PXOLx3aMv7fFpIIQnCqKtIoBCPYxsGrcDHVLVOOGodTx0+OD3F3FKN//w7TzHQe+8czN0Q\nRYJirUUmGUNROuwmQ9eYGCow3JPhnXNTnLk+z97xXryg02xPU9UtaYiKoiAiQSaf4Nv/9DmSmRhO\n2+fiqZuceucaz3/5ML4IMVWNlG7TH0sTimjT1SC7xzb++No1wrscoRhEEX995TLPj4+zt7Dx/ISt\n4IazlNqvkzB2oatdFs9m47gLEd6OmXBb5XnitnYdsbgFD1DsPGQPUzB7CEXIkrfI3tR+jqrHALje\nvMbOROfo1Ntbu9ytkC2Sgo/LV4mkoOw1WHQrGIpGv73+PJGEbhNJgdP1QjRFpbBFbm++0aDl+4xn\nsw98fOb94qFRAqqiMJLPYOoaUhoMZlPELJOW568l0dZja2uw5C3xceUtLjdOE8qQo5kTPJJ9moLZ\nz5I7xy+KP+Jc7QMCGTCROEA7anK9eWHTe92Osr/C2ep7eN1cQNrI83zPVzc9X0BXLBxZoerPMhQ/\nitG1FDrNt7aGpilrno+qKOi6xlAhRW82gWXoSAnj/Tl0TUN0N2o2Get4HY7fObbxAeZKUzXS6q0C\nodurjjVFI2N2qK+F24qmIhkx2bq0pgAEglbU4M3lv0ZKeLLwMrEtPIKPzkxTLDf5r37nOcYGH6ws\n/7NCSkkQRQghMXQNVVXIx2IUYnFagY+UHaF8uyewVKzzxrtXeOnEHo4fGfvsg1Bg71gvpq5xY75M\nGEVrrSssU+eZIzu4OLXE9bkSmXQM1w/xgpDB3OahmWS60zU2nrTXGD+xuMnB4ztw2z6qqjJoZUl0\nyQRpwyYUYtNclB9FvDM7zaVSccvhx3QDPwq5XCryb8+e4b976hky9r3j+kL6VNx3yFiPUnU/QlXO\n0BN/FU29u9T2woiy8+m6/94JNwrXaseEFNh6jLiewBc+jaix1kzu3ti8buhaY55G0OZodidpI46p\n6JytTVLxm+xNDxMKwZxTRMqOJ+CLTgjI0gw8EfLG0iccSI+tUxpXS0WmqlX6Eom/30ogZug8tnO4\n45YJiRdG5BKd4pqtKKJ3WrZCiv+fu/cMkiy9zvSe62/e9JVZ3nd1V1fb6Wk3tsfBE44AFgCNRCfQ\nLSXuShG74i8pdmN3Q6EIBTe0oYhdURLEFQNLcgmCMCQGwGAGM5jp8W2nva/qsmkqfea1n37c7Kyq\nrqru6plhxCzfP2Uy8+a13/m+c97zvjS8KmfLb/Hu8iuU3SLj0SkezXycocg4umy2Vf18luxZKt4y\nsqTwRvEF3iy+uHbbkrQq3SR1pH5bQYOqGxbLZBQez36C8djODWfZMTVLt7mDuleg7NymP7J3Qxew\nZSfP+cq7lJ3C+zx7d6G0/l++8LjVWGm4sYMmzy/8xZrc/oPAFQ7X6heYb04jWLk+Za/Iy7nvA3A0\n88y6+kq52uT5V87z9CM7ePTh8U17QGDjYvMHhRBg2yFNVVXD2XW5ZZNr1EPZ31aLwcQK199xPV59\n5xqZdJRPPDl1zwa1rUKR5c5qbaQ3tc5/QFcVdo70cHU+T6nWxGzTbTfyGRCE1E6jXQMTQhAEAqfl\nMjIRTkwkWWKhWSZvV/FFQK5VZX96mF5z/cwz32jwl++9t+kqIKJqfOPQIV6dvsWp+Xl+dPUqe7p7\n+NKu3ffsFRD4lO2TyKh0RZ6mYp/CCfLMVv6UbPSTRNQx2KBR0Q8CXrl1M6R1trWAwoZZ0e69kO58\nSed3CTrvu4Mw3knMlMt4QRhMr9evcbl2FgjHjopX4ZT2buczLb/FiDVK03fxgwBLXVEdvvuOFG09\nr/lmgYNdO7hVX0SWZLJmklGvl5cWT2OpBgORDHE1Qs1rEoigkwY6mN5Bt+Fj+y5Jbe0quuV55BsN\n/Pfhs75VfCSCgCzLpNo2gncYKA9Cw2p4Nd4o/IQTyz+n6ORI6918tv9XmEo8jCFH1sx6uo1+JmK7\nudW4ghvYFJ0cmqSjywa6bGAoEbr0bjJ6H0mti4SWJq4lqTolvj//ZwT4yMjsSx7laPrZdd3CIcLg\noUgaSa0fXY5SdRdI6APrAkZcTRJRLN6o/pSqt4wm6ahyqLN+RxrigyL0KVhheniBx+Xqmfe9bUFo\nM9ht9G3wqsSZ8huk9Sx7Eoc658f1fL7/07MkYia//PlD66Si797+7cYyad0ipn14+iyBEJ1OX0NX\nURSZpudSsW0kKcx1x/SVwt+t2SIt2+Xzz+2jO3N/OY0HhamvPwdCCGoNm6FMEtsPm+gSEXONHekd\nlAt1Lpy6xaEnJ2k2HBCCZt3m9Z+e5yu/9RR2y2VxdplbkRKO5CEIUw81zyYrBOoa+WLBX184z7Xl\n4ob7KksSz42P8+Wp3ezp7uGPXvgxS/Ua3zp7mpFkksMDg+tSVkIIHD9Hy7sNwiMdOYYXVFDlBOnI\nk9TdK+TqPyaqbafLegqJduq3PYArssyxkVH+xyePYbdcysUa9UqLUqGGbmpkehLIiszS3DLpTAxV\nDymvnhdQr7YQQYAkywyNd6NqCv/2jeP81fnQcXDUGmM8Fq7s3MBlrjXLqDXW2fdbjRvYvs9co0yA\noO7a9FtJ9HUS2oKy2yBnlzmQniChRTtMIUWS2RbrZ6lVQpfVjizJXLNAQosSVy0WmkVmzTxLdpku\nPUZvZK1ooxcE5Bqbmw19GPhIBAFYmfGtifCbIBA+jrA7utszzWvMNm+Q1DI8lHqMp9s5/o0eWlXW\n2Bl/iPPld6l6JXrNIQYjYwxGtoXWkXovqrSW7dDwanyn8P9Q9UKnrmFrgo/1fomounY21fBqAJhK\nBEVSkdqzm4iSQFulx++5Pq7rUavZxOImU+YR3JhEycvTbfbTa/WTMBPostnRN1kNIQSu66/heK9+\n7Y5j1x0VUSdo8dLS9/jJ4rcBiKpx/nDHv76nSNyHjas3c9yaLfJff+noOtnlu5FvVckFVXRZxRNB\nJ5XxQeH7AbliWNC3TD2sr3geFdtGV2RMVWOhViNlhH0CmaTFxx+bpLcnpLfe0dq5W3fqw8RsvsLz\nb1zguUM7mBi8d75dEM78b1yc5+KZGVpNl31HxhnZ3hs6kZ2aJrdQpu/xHi63FrEUg0ErRdaIrZtk\nXV8u8p2L5zddBYwmU3xp125GUil6olE+Nj7Bty+c4/TiIt88dZK+WJyR5N1KuwFL9XBl2BP9LC1v\nFttfRJOTIBkY6i764+NU7DcIhI0sGe3jWoGpqXRHo3i6j+lJXLxWRKp7SA5EexRUSeHadBmv0GLv\n4TGadQc5ALclkGQ5TPmZEQxTI6KuNCFqsoYs3xGaA13WsFSr/beEIZs0fYer1Rx9kQRJPYIhq4hg\nvVqtpeg8lNrW2Xa4ZgmPQpFknugOpVwCIVhsFXEDn6hicruZJ6nHmEoMs1saDT8n1tKwHd/nZqmM\n7d/b1/yD4CMTBLaCQAQsOzmu1y9ythRKPgMYsslEbA+H0sfYGX/ovgyVfnOURzLPYcgm22N7id+D\nFSSE4L3K25yvnAAgo/fyVPfn6DHWasEHIuBU6TjLTo6jmWfpNlaKmpIko60yNfH9gBvXczSbDr29\nSVRVIVoYIa1PINsScTN5Tx53EAhOX7jN1PY+bs0UsJ12ikORSaeiFJZrDPal6ck+mE7R3yckCX7x\nEw8xNpS574y67DZBhqrXwg00zC16LqyGEIJqvUXL9tDbpuz55RpnL84BEIsaGLrGUDLVUYNsuA4J\nw0SVZXzPx660aDUdioSuZU7Lw246jExutAL6YKg3ba7PF7k+W2CoJ8Vg9+aSJXdgGOFsWFEVdh8c\npbhUpW8ozaXTM1w6PUMxV2Fy3xCZdJKUG2WxWcYO3HXFzabr8lfnz7FQq234PRFV5blt2zg6OIQE\nGKrK1/fu5Y3bM8xWK7x08waTmQy/f/joXUqjMlnrYxSbr5JvvEBU305X5Bh15wqBEG1P3ia+2E+1\nbpPS66SNMB1yd2nY9wMWposEfkAsYaJoClbMpLBYxrU9IpZBtRzWDrq6E9hNB98PGBjN4jpeJ2W2\nGq/8nJgAACAASURBVEutRZbsBbzAoxW00GWdXGsJWVIoODkOpLJMJnrQFSVkjd1JQ62BtEZK5c7/\n7u41EkLQ8FtU3AYPpbYRVU1K5RpN3+H1/AWcwEORJCbjQ/SYqc4qvel5zFTK5BsNhhMP5ra3VfwX\nEQQEgoK9yIXKCS5VzzDbvNGelYfoMYf4bP+vdGQb7gdN1jicfhpZUu77/unGFY7nf4wdtIgqcR7p\nepbJ+H5Uee2Fz9lznCi9ymzjBgVniSezn2YsOrlhHcAPQuev3t4EzaZDxNKxWx6GoVGtNoknIiSS\n954t27ZHq+VSrdtE27owsiRRqjRpNN01ujtbge03ud28xlh0apMU14PB9rwO06bpuoyOZDBVbUsN\nVuOxLA3JIa6ZWGp4bC1vi40AbfhBwLVbBV44fol6w0GSQi+BMxdDfn82HSNq6Viahqmq+EIgSdFQ\nEFCWcRyXaqlBo9bCbdcRlmaXSXZtznzaKhYKFYrVBq4Xmryrioznh/WwPeN9jPV34QcBy+2aQKHa\noD+9cUAvLFVYuF1EURQatRaTewcBuHl1EVWVSaQsLE3HVDWyRhRFkkMzpVUX4t35OV66cYOWt362\nKQETXV38o117Oho5siQxlc3yi7t28X++8zau7/OX595jX08fn5hYccOTJImINkaf0kPVOUvTncZU\nh4AACRdZkqh7DhW3SbcZp+E7pImG9aC7OpUNU6PVtLFiJo2aTSobp15uEviCvuEu1LZiq25oZPuS\n2K2w0N/Vszmby1KjxP0kvvBIS5l2D0O4ukiqKaKqTlyNsuw0yRpxLFWn0Gjc9/pui/WhbvDcK5LM\nQCRL1giFBp/I7mGuWSBnlzqvhw2KK9ematuUWy3emr3N/t6+NSm8DwsfuSCwWiDNFQ5zzZu8V36H\nG/WL5Ow5Gn44W5GQOlQyS4mSNfo3HNDvpE5u3i4w0JeiXrfpzsTCdM09TqgQgqKzxCv5v2O+NY0q\nqexLHeVI1zPrmC9u4HC69DrzzWlc4XCu8g7Lbo6nuz/HnsThdWkXTVOwLB1BmBrKZFflmwUdCeLN\nIEkS8ZjJhasLWKbO7bllSpUmUctgeCDNgT1DWJGtp1Du2G8sNGcQArJGHxU3FLFzghZNv872+D4i\nSpRA+FytncOUI5TcsEnMkE084YKAorNExujlzC3BaCqF4/sUGw2Gkkl29mR5Z3qOIyOD96z5VNwW\nCctkqVmhN5JAwAO3yiuyzNhQhuce28nJczP88OXzLOYrQEg/nZroJZOKIsthG93dD4KqK/QMpikX\n6ywvVRgY7ybwBar+wRkai8s13rs+T7PlUmm0qDcdTF3lif3j7NnWhyJLtFyf60sFpnMlepIx4ptc\nz0TSIhozUTWFUqEGkkRXT4LRHb1cfu82vheAaA8wytr7UAhBrtHg+5cucbO0vOH2TVXll/bsY3vX\nWtHFqKbz6YkdvDM7GyqN1uv8XyfeYWc2y3BirfKuIlskjEPoSpaqfYaIOkrFbXB2eQlNDhVo46q5\nzmHrbmzfPYisyBQWK/SNdFEvN0l3x0mkwy7aeCqKCNpjQsy876y5S++iS+/qnAuBYDAyjISELzwC\nJOYaYS1tsVmhNxJHRe2sUupOWDS+u4u+11zPegvTwgYRZeU6qrLCSLSHkejGlHHH98k36jRdl+9d\nusRnd+xkKPH+vFLuhY9cEPCEy636FS7XznC19h4FexE7aIWDDGFz1vbYHlJ6ltOl19esCFZDCIEQ\nIcPjvQuzpFNRlkt1iqU6lmVg6Cr6JoOtEIKKt8wrub/lfPldhAiYShzkU71fI6auXaYHwudS9TQn\nS69hB+FyVG67ttp+C094aKwPAsOjWVRVpl63Q8aIZRAEQdv96/6XRVVlLFPH83we2jNMEAS0Wh63\nZgtcurbI/l1DqOrWJW6LziJ7kocRSJiKhS6bqLLGsrPEzfoldiUOtY834EbtPMe6P0vBWcAJbLr0\nHm7UL9KldzMR34shm2zrqlJsNDFUNWxoQ3Bidg7jPgEO4HajSK5SJaqF+vddRnRDQ/J7QZIkulJR\n0kmLvZP9PHFoG//y3/2QcrXJsSPb+czTu+9ZnJYkCc1QMSMaw9t70U0NVQ8blD4odo32MDGYaWvl\nh3n9luPy7sUZvv/qe3zi6E6c9sogE7dIRsMaxUaolhsszC6jqgqVUoPrF+dJZ2IcfmqSZDpKq+kg\nAoGkrB843CDgpRvXeeH6VdxNagHPjm/jczun1hV9JUliZzbLV/fs5Va5xEKtxqmFef749df4508c\noy8Wu0tGRCWijiOhhuJxapLdKZVLlQUQAWWn0RZqM0Kzog16BVLZeKi7FDdRVAWjTR1PdkVBCn2J\n73wuXLFtfbC8281MlTRaXpg6a/nhz4iiQyAR08OB/PjMNL+wY5IdmcyHLionCOmhZxcX278X+Jcv\nv8T//MyzDCXunyp8EHzkgoATtHgl/7dcqJxcQz+UkOg3R3g083EOpp/kYvUUZ8tvdl4PggDHDTor\nCd8PcBwPWZHJFWvML1VwXI+oZeC6AWPDGbJd6w1rhBDUvQqv5n7IW8Wf4bV7Cb4w8GvragdCCHL2\nPK8XfkLOngfCm+do17N8su+ra+Sl74amSPiOR0RTaFQaBH5AvdxkYKJnjS3kZrBMnd5sgpPvzfDa\nW1fRNJVSucFjh7dh6Cr5YpW+nq3dLBISL+e+x+f6f42AoDOrr7r1zuB7J60lEFS8Ijfrl8jb8wxb\n27lRu4ArXNzA5XrtPMPWdkxV42ZxmahhgBDkag1Ozc3zKwf33/fR1OVwlWb7LgW7TlKPoL1POusd\nI5rdO/r52mcPYpk6Tx3djtXup9iMiup7AaVclcpyA7vphIV4U0V5gMC6GXRNRdfUdd/tTIRicm+d\nm+bAzqGQwtoIDctbXRunw2LJCGOWHq4EinV27B7kxe+f5O2fX+bwsUkKuSrZ3gTGXf0jgRBczOf4\n8/fOstxqbbjtkWSS3z10hPgmssWqLPOJbROcXVzkz8+dxfY8fnztKulIhD848ggZ624NKxlTHcEL\nKm0WIIxHu/GET1Q1Okyw1dkgPwg2TFO5d/9PrDJbWR3QVv36oDRLQRgo45qJFzSoezbdRpypbJao\npnGlWOAPf/gDDg0MtOtKH14gcAOPC7k853Mh00iSIK7rpM3363e+OT5yQSCqJjiW/QxzzZuU3JA7\nr8smO2J7OZb9DBPxPRtSG30/nAn77eVgIMIijipJ+H6AaahELR1dV0knrU1XAXbQ4s3iTzle+DGe\ncBixdvDp/q+T1tcqegoEdtDi3eLPuVY71/n/9thenu354poAIISg1XAo56uAoJSr0qjZxNMWxcUy\nvheQ6UuxMJ2nd2TFI3jmygIA2qoURHGxQro3Sb1hE4+ZbB/vxrbTbBvJ8vqJGxiGSia1sRvbvWAq\nFq2gwY36RfrNEUDiUvVkZwVwBxIS3cYgKT2LKxxiapLbjevsShyk4ddQJZVAeIBGdyxKKhLhUi7P\nYCrJjmyGpWqd7ui98+p3ejSyRpzeSCLMk34Ibkpf+uRD4fZXDfi3F0oUSnUO7Bpa9/5Ud5zugTRB\nENCo2ciyhOf66ySKHxSeH3D66iyO67N/YoCFYqVjyHNjvkDT9ohGDfq7E6RjkXCGu4maZ8QyMC2d\n+ekitXKTarnJwSd2kO1NYkS0sFi6wSy14bp858IFziwtbrjduK7zq/seYqLr3j7IccPgq7v3cHJh\njrOLizQ9jx9cvsRwIsnX9uxdp3svSRKakqTu2uTsKg3PwQ18TCWUU8+acYJ2T0DQ1jH6k3ff2eqp\nvSfOLi22+47EpudzNSKqxkQ8ixv4dJuxMM8vwZGBQb6wc4oXrl8j12jwd1eufCj7dzdkSSKiaSQN\nkwN9ffzOoSMfqo/AHXzkggDAWHQnh9LHeHHpuyS0dMfsPav3bspt1zQVM7U+b1pv2PT2JBjsTWE7\nHsVSnf7e5Ib0Siewebv4Ej/P/xAnsBmxdvDJvn/EcGT7+nqDEFyunuGt5RfxRDgr6TWGeK7nF0lq\n6z2Rfc+nlKuSmwuLeL0jGRrVFtXlBqoqEwQBQxO9qKv26+0X3mPb3iF6hla2d+JnFzjw1BRyV5Rr\nN3Ok0xYLuQrxmMnkeA83ZvIk4xFSiQczC5eQ8ISHG9hkjD4kZC5WT6x7X8VbbruQSVhKnIZfww6a\nLDs5Cs5iW34jvEZ+IKjZDq7ns1StMZRKUHMc7mcAPhrLMKJ2YcgqpqqFtNd7yBhs+Rg3GMwuXV/k\n3JX5dUHAdTwqxTr9o1luXpwnEILRyb57NrhtFcVKg8VijZilU220OHNtrtMzELdMKvUynu9Tbzlk\nE1EsQ2OxtJ65I8kSiiITjZtYMYNuOYksSwSBRKYngaopLOeqGx7327O3+d6lixsOhook8dToGJ/e\nvmNDddC7MdXdzdf27OVqsUjDdck3Gvx/Z04xEI/z3Pi2jT1xpXDFFyihUqe1ql4RiJVBWpXlLe3D\nVqDKbXOgQOAGAVuZU0uShK6sHStGkkl+7/BRHh0aptBo4AtB03c5UZjGUnX2pgbQ5A9eO7pey5G3\nazw3OMljgyMfehroDj6SQUCVNA6ln6LqlRm1JtmbPIKlxN5XQSTSTptYlk6s3ZBmbSCt0PDqvFF8\ngdfyz9Pwaoxak3yq72uMR3euUQC8g6KT42e571PzwmJjQk3zXM8XGbEm1u2nJElYcZPuoTSLMwW2\n7elHNzXOHr/MI5/aj6Iq3L66QGG+xOjOfmgPNI1ai3R3goHxlTy0EdGw4iYj23qYmVtGkiX27Rxg\nbqnMjvEehMhQqbboSj0Yi+XOUNDwatxuXENCxgnWG4q4gY0QgiV7jriaJKn1cF06T0CApcba2dxw\nwO5PJijU6/TEY4ymU4x1pZivbExDXA1DVtdqIEngsfUgkEnFOtaO94Pr+R2K7WpIEsiKTKvhoJsa\nyUzsQ5PwjUV0nj4wQcTUWK42GMgm21Ig4XUXgJDg5tIyc8UKA10bM1wMQ6N/JEPE0sn2rvQylAq1\nzj0YUkjXBq6y3eKbp06w3NpYjmF7V4av7dnLQHxrFGNZkvj09klevnWTn1y7BqwYzwwlEuzp6d3w\ncyWnQa5VRZXldsAPr3kgRNsAXmIq282vH3iY+WYFPwhIGxFm62UGrCSGoiJLEoai0vJdiq0GA9HN\nB8r5apVTC/P4IsD2PDAM5htlXlq4tKGK5/0PHGgvumutKjkth6lofGVwF8d6t3eCDsB0rciJwjTH\nereTMbe2Uv/ezGn+w6VXCMwRuqPW35uPwUcyCEiSRNbo43P9/xWarH+gpiZZlhjoTXYe4EhkpXJ/\nhxFQcBZ5NfdDTpRexRceuxIH+Uz/L9FtDGzI9616JZ5f+Atmm9cBiKlJnun5AnuTRzalV8qyjKoq\na1bmvh8gAkFxsYxuatgtd80U2XM8rp2doVZasaBcnC4Q+AGqqjAy2BWqa2oKo5qCpir0ZOM4ro/f\nVh7dOkL/gKzRT785CpJEK2isK8jWvSrldpqu7BbwCRixJsnb83Sb/USUGDE1RTxhMiCB53fR8jw0\nRcbSdXrjsQ8xc7oKkkRfd4Lf/eUn+eSxqS0rfdq2R61ub+CTIDF3I8fx588QiRokuqJomsrYVD/d\nA+vZH54fIEu0pU7unWqwVu1bLGIwOdxNMhpZE2QWSlUEguFMsu2znWXh9loShNxeBayGqilkehId\na8t40lpzT9mex/978iQn5uc33LdMxOLre/fyyNDwA3nnpkyT3zt0lIu5HDOVcGJ0IZfjX//8Zf6X\nj39yHcfdDXzKToOG72AIlZpnk2tVicWMUNsIiaimE9U0btYK5Ft1oqpOyWkyGksTUTWuVnJISAQI\nesw416r5ewYBWZKwNI2YrnfqAxkjylSyj4RuElONNZLrW8E/f/fbHM6M8kvjB/js0A6iapy0YSHw\nqXo14m0iSc1r8SdXfs7FygL/7dSzxDSDXCtMh/VHkutWG+E5Cig5LboMFZkytmejyhkkSUZCW9dE\n+n7xkQkCQrgI4SBJSvtnDEuNEQQNAuG3W8p9pPsIsG2E1YXW1fe1J1yu1y7w4tJ3uVm/SFRN8GjX\nx3im5wsbrjxC+YUKP138G85V3gnVNpUET2V/gaNdz3T0ibZ2wOGPhek8pVyV/rHsusFR1VR6hzMM\nbl+ZSSUz8c4DrigyVkQP2+QbDvlijb7e5D1ZL5vujghXM/tTj3VSbhPR3eSceQJWVCdz9hyKpOAG\nDhOxPWT0PvLOAgKffnOUS9XT6LJBvzlKvt6gywr9ITRZ5maxRH9ys9nlB0v6G7rK554LTTkUeetS\n08uVBsVyHcf112gDSRIMbuuhf6yb3GyRoYkeEulox7NiNeq2w41ckYgeFrSDThBYqU9tdni6qqDH\n1icmumIWScvE1NTOMW0FkiStYQJJqz7n+j4/uX6Nv75wjoa7fuarKwqf3r6dr+7Z1xEr84MqsrT6\nWQhTNYGoo8gr11ICdnd383uHj/K/vvZzyraNAN6Zm+Pf/PwV/ujJY4wkU53ZbFKL8GTvjtBfolWh\n10x0XMxUWeLJkVG+sHOKY6OjFN0616sFdFmlz4pzpZJnLJYmEIKoquMKH0/4m+oX3cGunm7+KHOM\nZ8bG6bai7WNWOdA13Lm/HzTb4IsAXVbpMgzq/gwpI44TlGj6UW43rrE7eTg8Jim0w324a5hoe8Vj\nKTr//tIrbIt388mBXWSNu8ccgSbLmLJL0z2HKieo2e+gK/1E9ClU6cNJD31kgkAQFPH9PIrSg+td\nxdAfJgg8XO8yEiqKMgAIFOXD8desuiXeK7/Nz3Lfo+qVGY/t4kjXM+xNHFknC30HTa/Om8UXOVV6\nDSewMeQIj2Q+HprR3KdLOexX8CgXaixOF0h1J9ot4uGDKslyaIaxarAI/IBSroJhrcwc65UmIhAE\nQlCttWjZLrbtcf7KPI2Gwy7HQ9dVUgmLTHprKaFQ91xr0+xWHqSqV+J67TwSMkgStt8k0u7JuFQ9\nRc6eZ6E5Q9UrkTH6uN28jizJ+MJDIDi3sMSBwT5KzRZjXWnmKhWyMQtzA7rjB035y5KEvAVW1d0o\nVZrU6jbzS2XGhlZ8kyVZQtMVUtk48WSEWrnJavN4sSpvfafRq1BrUmo0OTDST7FR77x+r2PbbNAJ\ndeTD48km2l20gi0VNDeCEILLhQLfOnuG2+2Z+t3Y19PLbx86THRVDr7lnMYyHkEIGYGP7xeQJAnH\nm0NXhxHCQ1HSyFJIY31ufBvvLS3y7QvncXwfry0CF9N1/uDoI4wlUx0/iEi7DjAeW/tMZ60ov33o\ncGe/S5UGMc3AFwGDVpKbtSI9kTiz9TK5VpXtiW5u10uk9Xs/g1+a2r3h/+8EpqbnECCwlLuNYyDX\nCmVMEtr6iV6Ajysc0no3fuBR96o0/ToRJbbmO0KDnRWhPEvV+fzwfv6nk9/jRjXHb2x/nKHo2lWm\nKskIGvhBrd3MZnbkNT4sfGSCgBA2ghagtH8X+EEO319AUXpxvUvo2p4P/D1+4HG7eYN3l1/hTPkN\nDNniqexn2Z96lF5zaFNrSSdocbL0Gm8UXqDuV5GQOJB6jCezn8ZS753jE4Fg/laed186RyRqYFg6\nuqnSP97dKRj3j3XTO5JBWpXCUTWF4cl+RnauWGyefPkCsiIjAsFSvsrZC7dRFIWjD4/RnYmzmKtw\n4swt+nqSWwoCy0tlWg2beGEIshINu0VxsYSmqxixBCORSUzVpGy3WGoViSsjyCLGVOxx3i28R92r\n0mWYNNVwxaZICrpsAoLBZAI/EB2Hqv5EfFM53GCLUUDApsqyDwohBHOLJfLLdU6ev83IQLoz01dV\nhWginKFHExFUXV0zq74z2xdtn+K67eAFAXHToOG4CLHyniAIPjC5SQiB7bg4brt+8YA5tUKzwbcv\nnOPUwvyG+5K1LL5x6DBDiSRCuARBA4GH482gq9sAgSQZBEEFL8gBCq43gyTpKHKqsz890Shf3bOX\nS4U8J+fD72p5Hj+6egVNUfiDI48wGN+6GJ8bBCiSzN50P/lWjZi2MgAKBE7gk7frLNsNUoZFxWmR\n0NdO4rzA52p1jt5ICksxuV6bZyTaQ1Rd+76r1RyvLl6lJxLvBKg7OFWcQZFkfm3iUfqttTNwIQS+\n8DuMQSF8an6V8eiuzns2Ol5JkphM9PJU3yT/+eY77Ez28RXrYCcoCSFQJBldjiNRIxDtPiQ5hrRO\nyO794yMTBCQpCmKOIFhCkcMWboSPhIoQHkFQAN5/BBQIml6dk6XXeHf55+TteXbGH+JI1zMMW9s3\n1b+HsCHsXPkdXlr6HiU31FrfEdvH092fI65tYUkmhQXd0cl+xnYPEk9H8VwfWVF47/Ur9I9luXzy\nFpMPj66Xqd1k+JAkyHbF2LdriEKxxvF3rrNrex9T2/vofgDNoFqpQathk6z1QQD1coP5GzlMyyCR\niTK6YydCElwu5VloNImoGrpSBQG1VhdRrY8+I82uVM+aQtiVXJ6fXL5GNhql5blcXMqTq9X4yv49\n6xqfhGBTG9E7CB8MCdf1yRVqeH6wZXP3zTA9t8z03DLlapMfvHiWqKXz+MPbiEUNZEVGX7X9u7Vn\ngkC0ueyi06WqKUqYojB0GsLu1Ab8YPN00N1489RNANLJCMl4hHjUxDQ0lssNTrw3g+OGAfVBioSO\n7/PSzRt8/9LFDTn3hqLw9b37eGJ4pH3/yWHaVQiCoAJIyLIFKMhyDOHP4/rT6No2DGUEWV5JZ0mS\nxO7uHn5130PMVasdPaK66/KDSxdRJIl/9viTJAxjS4EgICCqhrIXcc0gphpk2vpCw9E0VbeFLqvs\n7epfxyATQuAKn0AEXK3NYigaiqFwuXqb/kgXi61lWr7LYCSDKisU7Do/njvPl0cfZuKu1cnzzXMs\nNMv8xvbH1u2jIqlYcpRFt4ilJAgI0GVjjd3qZkdqKhpPdE/w0vylNe8RQuCJ0FDIVHuIGQMIwrS4\nqiSRNrHmfD/4SASBsEDrIkkxFGUI234VVR1FlhMoSh+y0o3ntt4XOyg8mS63Gpd5Jfd3LLZu02MM\n8szQ5xmLThJXk/cssHjC42LlJM8v/CUlN4+MjCwpLLs5Zps3SelZNOneRRpJkujqTZLuSSDLIR3U\nczxuXZylqzfJvsd3cOPcbX78reOMTg0QiYbBznU8rp+bpVFZaebJzy3juz43pgu8ffoWnzg2xchg\nF9tGm1y8tsDxd66jqhLyFgZI13ZpNWxKSxUS2TilfLjCsWImvh8QS4aMBDsIqLg2rgipnrvSPdR8\nB1NViWn6hgVESZLY19/LcCpJpWWTjVrMlisbFsBA4Hr3DgKaptCVsrhyI+D4ievEYwaTY1trrNsI\njuvxk1cvspivEgSCa7fyvHnqJvt3DhKL3n+y4ftBOzce5tIHuxLoqspCqRqyW8SKjaXreFtO47Rs\nl1ffucb1mTyu64fyz7KE5wUs5kMFVF1TiVrGlnSY7ngG/x9vvUlhA3MWVZb5/M4pvr5nH1Htjsqm\nApi4/iyWcRTPn8dQ9rZpxIsIfDx/CU0ZREJBiGDN/a8rCp/avoNrxSLfPHWCZjvw1F2X71w4jybL\n/A+PPbFGtnsz6LJK1gzJBJIUUpl3JkO2XMaMktDNtubOHQXPFbjC50zpOn4Q0PQd3ivfRJMUAhEw\n2ywwU19i2OqGts2jTNh1PB7LciAzvGY/srdjqJJMchNhx4gaJUt/Wz6+K1wV+K37ZglkSWJ3qp9/\n9fAXGI52dYK73/YbMGQViRqQBuGD5OP6OVQ5uaYm80HwkQgCECBLURQtBRgYxmNIUgQkrc22kVCU\nPniArlEhApp+gyV7jrPlN7lWO0/G6OWLg7/BeHQnhmx2pJ43/rygFTQ4XXqdny79Dctt34GpxAEm\nors5WTrOd2a/yeXqGR7NfJw+cxhd3nx2s9oXt1qsM31lgfHdQ2QH0qiawuTDY9hNB1ULc+qKpDKy\ns5+pg2N0D670CVSWa8RSFoWWy+c/sY+W7bGUr6KpCqODGW7M5Dl9fo6jB8buf9YDgaaruK6HYepE\nYibNmo1mqAjbDbtMpXA10m1GMRUFU9GIaQbZSAzb91AkudPcsxrjXWmEgO5YFENRyUQjtDyv0/i0\n+jwJEVI17wVJkvj8c/uYXSixmK/yn773zgekbEoEQYCqynSlLHZv7+fLnzpAT2Zr9D2v7UUsgtDf\nudpyUGWPWMSg5YbuZXe8k21360Hg8UPbOLxvhJmFEi8ev8TxE9e5MVPsbEuS4OHdQ2S2SAHONxv8\n8evHmS6X172myjJPjY7xWw8fZGBVikaIgCAoE4gWurYd17tNvfUaln4AWbKQ5RgR4zCyZGB7VzG1\nXUjS2vNmaRrfOHSYS4U8L9643rk/mp7Hfz5/DscP+MdHjtIfj99zVSO35SDuIBBB2M+yqrC9usTt\nCZ+W75DSQ7nsUG5eYKkGO+NDpPU4z8+/jSJJPN27n1v1pbCojLJOOuJuKLK86ZRelhQsJU7dqxBV\nE6gPQGBJaCYPrSpOQ+gjUHcdLFVHkWya7rU2YUYHPCLazn9YQUCSFCRpFdOgXfWW0KAtwazID2ZF\nWPUqvF18iRv1S8S1JJ/q+xo74vtQt6CQGWoHFXmz8CKvF35C1SujyyYPp57g2Z4vkDX6GIiM8t25\n/8jbyz/jRv0iR7ueZV/qETJ6732VSZPZOPvuStnIisxDx6aw/QYle5GsMcazXzmKEAF1r4Qqa5hK\nnEc+uR+AfsJBfGZ+mXOX5kKRMEVGliRSCWtLLliKqjC0o4/+8R4Wp/M4LZdUNk6iK1Ry1I1wZqjJ\nMgPRBJDADQLcwMdSNfZ19RHXDEpOc93DI0sSCdNAkWXSlokiy+iKsml6y/N8VFXGNNfm3lfjycMT\nxKIGb5y6SWG5dt8U0t1wg4DFWo2+WBw38NEMlWTC5In929g50UsksqI333RdSq0W/Ztw5b2287Uu\n2QAAIABJREFUAqhpaiBDvlpHQqLluRweH6IYhCmrRMykvye5ZbqupoZU36ltvUyO9fDcY5N886/e\n4PiJkI48PpThy58+QLbr/n0zVdvmmydP8Nbs7XWvScCu7m6+cfAQU9m7u+FDn2tDm0SWDGRtB6qS\nRRCgyGlMOYrtXiGiH7znCjhpGPzTRx/ndqXCpVWWlQ3X5TsXz9NwHX7/yFEm0l1bpqO6gc90fWnT\nY6+4DeaaBR7JTJHR422hybahkNfCUHQMWafqNpmp5zieP0eXHsOQtXUB50EQFm1lPOESiGDTe3jD\nz0rrQ48TeFTcJnHNxJRV3CCHhIaMh6ZkP7QAAB+RIPD3gUD4xNQEz/Z8nqHINnTFvGeUX/lcwEJr\nhtfyz3O2/BYNv4alxDja9SxPZj9DSg+XjuPRKT7R+2W+P/dn5J0FXlj6a241rvB49lPsiO3dkqT1\nht+PR9XN4QZNWkGNtD5I2Zkna4yvWwjJssTYUIZ41CRfrDG/VGbf1CDctyc3xB35XVWDkZ2bm7qr\nstLJ969eDEfUcLbTp66f9UiSRG987ewwG7U2pvFJMNSfZt/kAI8f3NZmxqyHosgc2jvCob0P7vXr\nBQEzlTIv3rjOc+PbyNXrRDSNxXqNvf0D+CJgvlolqulIEizV65xaXOC5sfG2v+vaR0WWJfZPDfLQ\n1CBHD4wTqOEZr7bssIFJVziwa5Ch/jRPHNz2vmi7siwxNdHHb331MZYKVUYHu/jUsV08vGf4vvUQ\n2/N4/uoV/ubihQ3rAL2xGL998DBHBgfXf6+kg7Ky+pQkFXUNKy+CZRy+7/5LksSOTIbfPXyE/+34\nq8xWq53XWp7H89eu0nQ9fufQYfb39d2X4glhemgi3o+2BRXgglPlbOkGcc3CUgz89op1MjFIoW23\n2WOkOs+qzIOr1a6GIqlo8v1TXHfD9lcN+G1vgqbvkrfrZIwoUS2CpvQgEVJ2VTmN9CEyhP7BBoGk\n1sWRrmcfaDAWIuBy9TQv537A9fpFfOGR1ft4svvTHEg9QWyVk5gkyeyMH6DaXeYni9+m4i23JaTz\nPJn9NAdSj6PLD36hFEnDUKyw71aEaYSMMUZMy2z8fkUmZhn4foBte6hq+PdWsVCtMb1cQpY3mAUJ\nqDsOtu/z3PZt6153fZ/Xbk4zkkoy1pXecBZVazlUWzZ9yVgoNV1v0h0PUxmOH9YY4prOH/76M/T1\nJblSKnCrVGK8K73pw2R7HheX8qStCCOpJA3X5cz8AkPJBEPJjQv1Dddlrlqh2GywUKtSarUY1pIs\nN0OlU6U9Cyw2m1iajqYo6IqMrqgbTh72Tw2yc6KXwd6QGdN0wqREV8xCVxX6u5P86heP0pWKbqpT\ntVVMjGT5p7/5LL3ZBD2Z+H3TYH4Q8Obt2/zpqZMsbmAUoysKv3ngIJ/YNtHWr98cVdveUu5+M+iK\nwrNj49yulPm/T5ygbK/Ut2zP48Wb1yk0G/z3jz3Oo0PD952JS5KEvsVUiyYpDFvd+CIgohiokkzT\nszHbA7UnAp7rfRhLXXE0u1fS7kOQr1q7PSGoeTYvL1yhNxLnofSKdEnds5ltlHgkO0ZUESB8AnxA\nJhAthHDgffRMbYR/sEHgfvm9O7jTNVx2i7y7/EqbObSA1rahfCL7KcajU2gbVONVSeNA+nHqfoWf\n5X5Ay28w17zFjxb+kpJT4PHsJ4kqq3Ot9zZP9wKXG7W3MZU4XfowUTXFbOMCnnBIaD2Mx9bPvjRV\nIZmIkIhHGN6gkzX83s1v4EK9waVcnifHR0mYBqdn5ym1Wjw9MR5aFC7luZzL87Ht2zrHELSP49Zy\niRevXOdL+3Z39F4EYXDQFAWlnZMtN1vU7TAYjGVX9lGVZRzf53w5x/ahDDeKyxy/Mc1YJs1irUYg\nBPl6g/GuNPv6ejvH4vg+1wsFBtwEA4k4tudxLV8kYRh4MR9ZltuFxJXzbCgKScNkLJUmaZgs1Grk\nGnWuFgu4gU/Btqm0bFKmyenFeXZne0ibEXo2Ebvrv0uhVYusHeitiL6hPMnG10dQc0KK6Z0B1w8C\nVFlmsVYjaZpkBhOkoxaFZoNIu+t1s21dLOT5D+++zaVCft11V2WZX9m7ny/v2r0pXXc1/vy9szi+\nz5d27aI3Guvw3R8ECcPga3v2sVSr8+0L5zqFYghXaCfm5/hXL/+Mf/LoYzy3bQL1fXzHRohrFk90\n76Xph/InqwNeTIuACAuwgQg6aSNByMpxAp+VFbUgEAHiQzJ7Dymlgpu1PN+dPs2h7Cg7E72d1WYg\nAmYbJfKtGqOxDHF9BEFPW1pVIEkqsvTheW//FxsE3m/TzGr4wqfqlrhcPc3rhRdYaM0AEgORER7P\nfIo9ycNYSnRDdzBoyxTLFo9mPk7FXeat4st4wqHsFnkl97coksIT2U93qGLVSpPycgNNV1BkGUUN\npSR0Q0U3VBRJZdDaQ8VZxA1aOEGdnsgEvnDvG9DCZ2bj9/jCx/HX6wCFCHn8ajtn7wYBTdcL8/ci\nLIatfvBtz+Pk7Dxu4PP2zCy+CLi1XKJm20iSRNW2ObewxCd3bmdHNsOp6XlqtkPM0Ino2ppUjyxJ\njKRTKLLM9eIytudxZGQI1/fJWFEimsrVfBFNltvSw4JLuTwL1RrXCsucmlug6jj0xWLk6w2u5gu8\ncWuGY+OjbM+uXTnpisLx29OYqkqp1UJXFEYSSZbSdQxFQZNliq0mqYhJVySCLzbm9oeuVy1oDyhC\n3N156xFSKpOrPtNCCG/V9QlAOEhyCklS8IUg32hwu1IhEAFRTccLAvb29nBteZnRVIqT83NkLYuU\naZKxohsGASEEtysV/vc3X+et2dudDtw7iKgqX5razX9z8BBdkciWBtqlep2/OHeWv7tyma/s3sOz\n4+MMxhNo8uakirshSRLdlsU/PnqUqmPzd1eu4AYrRAABXCrk+Rcvv8SFfI6v7dlLbzT2QLIVG8EO\nHK7V5tpnfb038Ewjx43aIl8deYqMHnoV2L7H87PnOF9aK6txvjRPt3n/PLwumxt6X9y5Em7gc7ux\nzM8WLvNO/ha/vO0IhzKjawTnap7Dj+bOE9dMskaMADX0Zf57wkc6CDhBi7K7zB3jZ102OzpCDb+G\nF7wP0SfCekHZLXKzfpm3iz/jau0cqqzSbfQzGX+IxzIfJ2NsLHp1NyRJIqYmeTL7GZbsea7VziEI\nmUUnSq8yEdvDqLUDSZK4fbPAz396DkWRUTUlNJAxNayozrbJPsZ39KIrFpIkU3YXqLo5kno/vnAY\nsvat+243cMjZ8zT9GppsoEsGmqyjyhpqh1kF861bTDcur+zzmmAhUW3ZXMkXiBsGM6UypWaLi0t5\nBIKZ0lq9GkNV2d/fx3Kzydn5Jb64d4ylap2d3Vl62jWAz0xNhuc5CBjPprlZKHUap+q2g9VWzGy5\nLheWctwslnhkZIjZSgVT1Xj+0mXqjsvR4UE+tXMHfe3tCmA0nSJhGsyUSuzu7eGh/j6u5AtIwN6+\nXn569Rq2768boFqehxBgqhp7e3o5uTBPxXGIaBqyJKPJSnuAh/09fZxZWsDYcKYc4LqnARlZzhCI\nMkK0CIIcspRsc7lVDPPplevknsX3biBJYbes75cI/NtY0V9HUrqoOTZVx6Y3FqVq28zXagzE4rh+\nQLnVYrFWxQtEJ6e92QSo2GzyJyfe6Yi4rYalaXxx5y5+/8hRBhObWy7eDUNVaHkeF/I5/s3PX+a7\nFy/w9b37eHIkVLXcaiFVkiT6YnH+2eNPUmq1ePnWzTWvC2ChVuPfv/M253M5fv2hAxweGERXlPe1\nKpAkCUPW2B4bwNygAxhgT3Jszd+BEKiyzOeG9vFk7/Y1r9U8m5rbum9uIaJsvHJ0Ag/b93hl8Qp/\nPX0SU9H4nclj7Emtd0Q8UbjF60vXOZwZ5UTxFnbg8mh2G5b6/tNy98JHOgjUvApvF39Gzp4jokSJ\nKgkiahSE4GL1FM220bwqaVtK/fjCp+gscaN+kUvV01yqnMYXHsPWBNtje9iVOMhQZHydf/BW0GMO\n8kjXc8w2b9D0Q8G3pdYc861phiLbQnG2njif/+pR+ofSVMpNTr9zA01TWJwr8aPvnuSXfusY6e4I\nMTVLr7kDWQoHppZfww1a6PJajrIdtHiv/DZny28B4Q0YUSxMJYIhRzoBc7Z5k+nG1c7n9FWyGAJB\ndyzKwwP9pK0IDdchX2twZHiQQAh0WeGN6ZnO+yVJQlVkzi4skooY7O3t5V+ceZGd3Rl64rHOYC+3\n9XtS0Qjplk2l2aI3ESNlrXx3y/P41okz/NLD+0hbESq2zbu353hmIuxQPT2/wHhXmoRpEFFV/CDg\n+M1plhtNZstVdEWl7jgdJk8yYnYeqDurjzuYr1XZ19tLrl7nciGP7XlUEKiSRLHZoGLb4SrBbrFY\nr3GzVEKRZS7mc4yn0p0GN0lSkOUsQVBCVrIo0iiedw3fvYJqHkZR1xdag6CMEB6aNtb+j4IQ5c5q\nwlQ1/CDsDi00GizVauzoyqApClFdJ26YKFJ13XZXo9xq8a2zZ/j2hfPrXgs1gXbwjYOHHigAABht\nnX8IB8mzS4tcfaXA02PjfHbHJEcHh8ha1pYHp/54nH/y6GMst5qcWVzvZeD4Pi9cv8Zspcyv7HuI\nX9gxSTry4EYqJbdCTLGQJKh5DeLayuDc8m0aXpO4FnoEdPZdgpRudQgPq/F07w4iiramIfJBMF0r\nUnYa/HT+Ip8Y2MVvbn+cbfHudUH0YnmB/3j1DZ7omeD3dz7NxfIC/+nG29yoFfjKyEHSxoNJxG8F\nH+kgEFXiTMb3I0TAmfKbFJwlVufpIAwAWaPvvgXgpdYs5yrvcrX2HrPNmziBzVh0kl3xhxmL7qTH\nGFynGeQGHoEQaLK6pRnP7sRB3l1+hYvVUwAIAqpuqV3QWS1OJnH53Cy3b+b5+Gcforc/FaaE9DAl\nFFHiYf5RUghFdX3coAmszfmbssX+1KNkjV5mGte5Uj3D9fr6QeBu9BgDoR4Qoe7NnUacrSAQggtL\nOX5y+RrHxke5ks9TaraYKZWpOS7XC2Fu/slto5iqiirLTHR34fghd15ZlUawNI2dPdlwm4s5zswv\nENV19vR2oyoKb8/c5rUb05yaW+Bj27eRjkTQZIX+RJyW77E920V/Is7fXrhMVNN47cYtmq6L7flc\nXMpxeHhlQE6ZEYYTSaqOw2K9hqGquL5PTNdRJJm4YdAdjdJ0PZZbTSYzGVw/zMuv1HQ8gmCJIMgT\n3n8K4OI6byNwkZV7WU+G1xFo/1xJh3hBQNN1cX2frohF1XGoOQ6LtRq6IlNsNBhIxGm661k+EBbv\n//rCef7szCmaGwjDPTM2zu8fOcp4+sFo1sCGTK2m5/Gjq1c5s7jAY0MjfGbHDh4bGiayBd1/SZLY\n093Df3f0Uf749eOcz+c2fN+FfJ5/+8brXCrk+aW9+5jKrh8wN4PtO1yp3qDP7A5rUm6VIaufuBpD\nk1XqXoOFVo6G3ySpxYmp0ZDJFO/mG5NPsi22Xp/ske7xLX33ZhiwUgxG00wlevndyacYjq4lPriB\nz8niNH969Q26zTi/ueNx+q0kacNiul7kW9ffouW5fGPyyQ6D6MPCRzoIGEqEiehuBswxdiUe5me5\nH3C+8i6ry5yWEmNf8pE1n+tYTAqP2eZN3iu/zbX6OfL2AoZssidxiMn4QwxERklr2U1n/ufL0+Tt\nMo9kpoiq91cI1WWTQ+mnOkEAIKrGKOUbZDNaZ69rlSYLc8sc+/gesr2hvs7hx3cQT4YzqmV7joZf\nYth6CF+4lJw5Su4CKX0tjVOVVfrMIXqNQabiD/Nw+gnOV05wovgKRXfjh0tCYn/ykU7QbHou89Uq\nb8/MEtV1Li7mKLVaHL85jUBwa7l81+chHYnw1LZRHh0ZRpZD96OeWIzuWJSorqG3c+yeHzBdLOF6\nPoEIC14pK8JoJoUXBNxcLpGJWsxXqtQchzPzi4ymU5ycm0cilGT2RcCbt2bYlkmTiVrsG+jl59dv\nsVit0x+P8+9efZ2HBvrZ1dNN3XFJRSL88OJlxrvSa4JAV3s22RWJdH7fCEkD+mKbNYxJgIEQTURQ\nBc3D93N47kVUbRe+dx0kC0UZQJLkjkWiLCWQ1SiK3N3ehoQkRZDQESJUihxMxFFlhZRpoikKw8kk\n8v/P3nsGWZaf532/k8PNsXOe7sk57M7mBRYLLKJIEDQAiqFkskzZkklZlC2Xq2x/cJVdZZeLtkSR\nYpUokipKpEmQBEAEIhC74OY0u5NDz3TO3Tenk/3h3L7TPd0z2wssyZWtp2pqau7ccO655/zf9/++\nz/s8hE1V2/NI6jp1x6HlOp3FNqxhe3zj1k1+58LbrDUaO474iaEhfvXh83QZEdarDaKaQs2ySUVC\nxzLP95nbKJMwdeqWTU8yti1Qq6LEbr2mgIDFapWv3bjGG4vz/MKJk3zpyLEdzWZB2O6KFjqLSTw6\nOITj+fxfr72ybYZgKzaaDf74ymWur6/zhUOH+fi+8Y7V5YPuxc0GcFQ2aXgtZEHCkHQs36LklLlT\nm2XV2mB/bBRZlDBlEwmBbjNBt5m4b1VhU4YiVAQNaZxuu4H/XjiY6OafH/k43UaCwehd+m0oTW/x\nrfnLfGvhMocSPXxh+DTDkbCnpUsKnxs8zkurt/nu4jWe6BrnWHqnC96Pgw91EIC2IYscYSRykJSa\nIyYneLP4Al7gYUgRns5/lgFzDAgpni2/ScUpcqN6kVvVixTsVUCgzxjmyeynGIyMY0iRcLr3ARPD\nAEk1wrpVpuo2MWV9Twzi0ehB+o1R5pt3yKhd9OhD/OBPLjM3tY7reiTTUYb35Tl4bIBMLmQO5bsT\n4Ui8AJZXR5eiNL0yRXueiJxCk6JIroLrePi+H1IEA5BVGd/38b0AFYMeaYju/ACH4qd5YfXrXK28\nhRPYnWNTBJWTqUfYHzvRudALjSZDqRSn+3vRZYW6bbNeb3Cit4eAAFmUuLCw2D6/AZbrkjENnhob\n7WjrKKKIqSrENJWYpuL6ASu1Ogldo9ayCYKwF5COGJ3xflkUyUUjPBkZRhJEnr8zzf5cli8cP4zl\nuvzGS6/x5VPH+fLJY9ieh9m++WuWzXK1SrXVYrFS5Z3FZcZzWaaKRQjgncUlkrpOynz/JQTLdWm6\nDlE1HHLb+XuLiGIKUUzjBRa+X8WxL6DpH8X3C0jyEK3GV3FFE934NL6/gufOEQRVQMZ1b7anPg0E\nRJrNP0EU0mjGp+hv6+0LhJLMm25cm0wsgXDn5LenrTcZRX92/Sq/+cbrrNbr245Uk2SeHRvjH517\nmLFUimK9xXq1huPqzBXKGIpCLh6h3GhRaVpENJXptSJJM/Q1iLRLaWFNfvfzJQC6LHOmt48nhkZw\nPZ/r82skIzpr5Tpj3RnipkalYVGoNuhKRVFlGUUS0WWZj4yOoisyv/7qy1xeXe18122/iefx1uIC\n19fX+NbkLX7x1GmOdnURVe5fH294TVZbG6TVJI7vUHFrrLbW6Td7cX2PslPFlHQMySCtpjqzAe9V\nUnYDnxdXJvn2whXKdpOi3WChUaLXTD7wdRAGpjPZIQRCxlzLc2m4NldKi3xz4TIxWeO/3P8kh5K9\nRO6p/SdVky+NnOW3b/71fYctfxx86IPAJgRBIKXmeDT7CUrOBg23xvnss5xMPtJR/mz5LV7Z+B43\nKu+giBo9xiDnsx9jyBzHlPauXLgJWZA4lhyh5dmstAo7HMYkQSQum506oSAIRKTQI/n7q3/WViYd\n4Kd//gC25TI3vU6l1KBYqPGDb12kpz/NsdPD9A6kkSQJr00R9QI3ZBnZS0iC0nbtSrEwuUyr3iKW\njtKoNNl3Yhi76VCvNiEIaDUseke6GDTH+GxfaBp/pfwGAeHcxInkIzyee64jeud6HqVmi5F0ilSb\nLaJIUmjpp4YLztbmqOv7XF1Zo+W62xaGQrPJ1ZW1Did9tVrn+uoaXzxxFM/3Q7lsgY6mTuf3bGfk\nVctiplDkeG83U4US3705SV8iwWAyua2uHwQBvfEYf//UCSKqwu2NAqVmk4+MjRLTQ673xaVlzg8N\ncrLvrvLqeyEIAiqWxbcmb/L89BQ/f+IUD/X177hewn9vloZsPPcOmv4xXPcm+BsIgo5ufh7HfpOQ\nIZRCVJO0ml9Hlg8BHo7zCobxeQI8RDGPJI8SSgzf/aytdoz3lkA2n1e1LP7oyiV+/dVXdngDJHW9\nzQI6RW8sjuf7lBpNPD/A0BRczyeTNklHTWbXS9xaWWdqrYDj+WiKTMLQ2d8blkR2b46HxzWUSPIL\nJ07yuQMHiakqxVqTubUilbpBpdkiEwu1p9YqNVZKtc5Ee0861p7DkHhqeIS4qvG/vvgCby/trnAa\nADXb5vnpKd5cXOALhw/zmYkDjKXSu84wKKJCl56jR8+z3FprzwkY+IFHxakyGhmk6JQp2mUkQaRb\nz+2pp6iIEh/pOcDpzBB/MX+RP5x6k2Opfs5lh9/ztRAOhS23KjQcm5n6BtfKy2S0KL888QTD0cwD\n16fz+VFkUeRQcu/X9V7xH00Q2ERazfFU7jOYcpRufXCb9LOIyKC5j/2x4+S0ns6w1vx8gbpaJZfb\nGQjqdYvZ2Q36+lLE47tnj11Gmh+uXtwRhStOg+FIN6fT453HZFHmYPw0CSVDWssRkaPYlsuF12/T\nbDjsP9zHqYfHeOyjh7jw2h3eemWSRn2Asf09SLLYLvlsn/gNCJA9k6WNKrFkhFbdQtEVfM8Pec22\ni9WwiWeiWE0bPaJ1Fv0Na4W83suRxDn2x45vU0tdqdWJaRoDybuuT34QlmCajsN8ucLtjUJn4VEk\niYP5HJosbTNX+erl65zq66E3cbfp+DkO4vk+hqzQclyatoMkCmjKzksuqqr87JkTvHB7im9cu4kf\nBGQjJl+/ep39uSyHuvPostwJUookUbdtXpmZ42hPN3r7PT3fDxfU90FfDIKAtUaDP7p8if9w+SLL\ntRqFZov/4YknOd7VveP5vl/FDyqAiyjlEAQdAp8gCGv8giCjag8BPqH0chnPW0RWDkMQEARNPH8N\nAgvPW0SSh+B9ulnVbIuvXLvCv3rj9R0BIGua/Nzxk3zxyBGybeMUSRSJ6hpN26HcaLFUqhI3dXKx\nSMfGMRM1O7u1Tb9jCH/z3c6kLst8amKCLx45iiKFBAbH9bAcN5TUNsLPi+gqScdgtVQjZmikozup\nqad6e/lnjz7O//Hyi7y1uPTAbLdm2/zeO+/w4uwsn9w3weNDQxzK5dG2sIgUQQYCml4LHx9dVLF8\ni6bXIq0lsbxwd5zRUjTcJn4QsBeVh/nGGrqkktUSfH7oFN1Ggqxu0vKbLDXvDsEFBKxbZfrNHGn1\n7j3R8BxuV9cggMFIhie7J3b1LtgNuqTweNf4ez7vR8F/dEFAl0zGY3fpkq2Ww5XL8/T0JuntTbEv\nutNz4Hvfu4zn+nz5y49gmNszy6WlIr/zOy/w6U+d4JFHJ1B2me6UBYkjiWGc4K7Dlh8EXCpNUXHq\nO55vyhH2xe4eh2WF+vJdPYmwfOP7aJrCucfGWZwrcPPqIpGYTs9AEh8fx2/iBx66FMELPFpelZgf\nyhtXCjWMmE7/RA+25eC5Pquz66wtFDj62AHULfIEo5ED6L1fplsbIK6mtmU7nu9TtSxG0il64nf5\nzxFVIa7pYQnHtrm6sspTY3ebYoa6s3/iBf4OTjrQWVwkUcR2PURR2FY/LTSabDQa1C2bhuMQ13V+\n8ughRtIpNhoN3p5f5KXpGUxV4UA+1/nNis0Wr8/OYyoKx3u6EQWB6UKRqyur1Cwbc5dAcz+s1Gv8\n1htv8NUb1zvTrBeWFvkXr73Krz3y6DZdnSDw8NwZCBwU9TS+v0ar9R1c+yKeN0PglwmwkKQ+dP3j\nIOi4zlVU9WEEwcC234JARJZHEQQVheOEAd9nr4Gg0Gzwp9eu8m/efotSq7Xt/7oiUX7p9Bm+cOgw\nMe3u1LjjeaxVapQaLVzf5+hAN6uVKg3bIaZrHB3opisR4+LsEl2J2LZm8K4m8YS74ISmb/v/hu1Q\ntxzipo/jBqSiBhDQsG0ysQjLxQqO65FP7PRrPtXTy6898hi/+cbrvDQ3u0MWeiv8IODWxgb/uvQG\nz09P8ejgEB8bG+NILt+eLRDoM7pRRIV+o4c+vZu610CXdFRRQREUVFElpkRIqVvnOQIKdrV9TwdY\nvossSoxFexEQuFGZpctIkdUS6JLCR3sOULKrVJwGkihxozKLIWkMmPlwzmTLLSEIAhktwjM9B3d8\nn79rfKiCQLFY5+rVRSqV3Q2wd8PGepXvf/8yJ08O88UvnSef306Ba7Ucbk+uMtHOtLfC83yuX1/C\ndTx6epP3HccXBYFuI73tsaCdMef1964HGobKqYfGaNQtWk0b3w8QxdB3uG8wg6arzE2vkc5E6Y0e\noOlVcH2bmJLB9R3mGhfJx4ZoJha4dWGaA2fHqBbqFFfLxNNRoskI9WoTSRJZndtg+FDYOIopSfYr\nux+fIAj0JxJI9yzMB/M5HM/HUGQOdeWJKAp9iQfTCqOqumu2uLXMsRvLRJdlkoaOqSgEBCR0vbO9\nz0cjjGXSLFVqxNulHtf3ubCwRKXVIh+NMJLuJ2nobbllkblShbFMip490iAXq1X+z5df5NuTkzTc\nuxm1FwS8NDuDqcj81w+dZ196c/BMQJL7kII+RCmF72cQhBiSmCMIWgiCShC4iGIcBAnfm0cQDCR5\nH4KgoCjHcIVJmo0/wveLBEEDRTmGpn803FG8B1ZqNX7/3Qv88dUrrN/TBJ7IZPjl02f52Ng+IvcM\nkomCQHcyTjYW9gA2ag0sx8PzfbriUVqOSzKi05WIEtGUbbu8vTQ9N5GMGJzfP4TluCiyRMt2qTZt\norpGTypOudGi0bLxA3/HQJUsipzq6eWfPfoYibfe5Du3J3fVPNqKlufy7soyNzbW+eF2bs3NAAAg\nAElEQVTMNA/19/Ps2D6O5vP0GNuZWsYWAxlNUtGk3SeuRUHoyEhcL96kZNfx2oNti60NCnaVDavC\nw5nDaJJCXIkQUyJIgsjl0h0iskG/maPf/GAcEP828KEKApGIxkB/GlkRMQyVubkCX/3qWzzyyDin\nTw93nnfx4hzPP3+dz33uFGfPjvDkUwfQNYVkaieHdmmpRLXW4tzZURRFwveDdhNWoNm0uXRpjmc/\nfpSxsS48z8fzfBQl3FqKgoDje3iBv6vGyoCZ2xNvWFakzp9YwtimKCkIAtl8DEWVULUwy1ZEA1lQ\nCQglahNKF4iQyMY5eG4Mx/GoFKoksjEkSaRnJE88E2VjqUSqa2+ThaIgbKu3byKu371ZVEliPJd9\nz/f6R48+3Fmo3w9MVekMjt0LQRDQZJnh9N0gJgkCB/M5AgIMWemIqAlAbzzGl04eRRbFB1IVA8Je\nyMWVZf7l66/xyvxcx/lsKyzP4zu3b+P5Af/4oYeZyGQRBRFBuEuzFIQIojjeSeI3JbI3k4mAPKLY\n1RH7kpWjSPI4QdAAHAh8BNEEHiwv4QcBU8Ui//drr/D9qTvbSkCmovDE0DC/eOo0R/JdKLss2qIg\nkomaQEA6atLvhi5Ym7u6cDJcYKInt6M0Ib+P0loyopMwdTzfD5lHQdBR5hRFgVw8ghs17jsJLIsi\nB7I5/vvHn6A/HuePLl9mo7mT8XQvWq7L5dUVbm2s8/Ub1xlPZ/j4vnEeHxoirRsdqvJ7fQ9BEPCD\nAMf3iMoGRbvGydQ4WS2JIWncri3SpacYj/WjiBKu7+ET7li8wMMNfFzfxfbDnb/ju6EpzI8gKve3\niQ9VEFAUiYHBuxl3oVDDc300TSa5RT9d1xVc18M0VbK7uGh5nk+xWMdxPK5cnkdTFVzPY26uQLnc\noKsrQTYb4/r1JTRN4amnDiFJIteuLTI/X+DYsQF6epKdet5uPBFBEJDvIydxL3zfp1JqPpCLL4li\nZ/GQkKE97SsgklLDzD6Zi5HMxTrbzK3vp5kqqa7E38nFlol88AMsu0G4T+CC8PxtDWC7IQgCGo7D\n96fu8Ftvvs6N9Z3aOlthex7fnryF6/v800ceZV86s61Ra1kutWoT23JDKWxFQlVlEgmTSqVFrdok\nCCCd8VEUGd1Q2g5dez9ftudxaXWF//2lF3ljYb5zvAIwmEjw+UOH+eKRo2SM+w9s3X1YCI3t76PS\nutvje90JbH62IIDYTozufbfNns692Gg00GSZiBLKOefNCL/y0HlGkil+6803mCoVd2UO3QvL81it\n11mr13l1fp6krnF+YJBHBgaZyGRIGwYp3QhnQ+7zvdJqjMvldeabYUM5o8aZaSwzGulFFWUMWSOu\nRPB8j7nGKjW32fnuK60CdbdJojqP4zvcri0xYOY4mz4AQYDnLSBJXfhBo20QI0LgA17bO3377xcE\nHp6/higYCEL8b+ze/lAFgQ/qS7quz61by1SrLS68M4OuyywsFKlWl/jhD6/ziU8c49y5Md544w6f\n+tQJDCPMiA4d6mPy1gq//3sv8vd+4gwTE92IotDmYzv3VZTchGW74S6ifQyu56GpMlbL5ZUXru+w\nKOy8ruUQieqceWQfZuQeY5o2q8Zy3A/MW/f/r2i4Dl+7cYPffedtFqsPnsDdRAB8985tDFnmv3nk\nUQYTd3cmsizieQG249Fq2iRTEaJRnVbL4eUXb5DLx7Etl+WlIsOjeXTj/em/lFstfjgzzW/eE7AU\nUeRkTw+/sKkE+mNq7DwI0h7uyYplUW61woBxz9Mdz8f1PUZTadbqdSzPw/U94premdd4fnqKg7kc\nB9v9l81g8bkDB+mKRvntt97krcVFmu7eZGICwj7VRrPJX9y8wV/cvEFaNxjPZjiSyzOaSpM1Tfal\nMwwkEtsCnSAIHIwP8RuTf87h+DBJNcqrG1fbzeYt50WU6DWyyILU0dZaaKyRVGMcSYQ9tJOpibvn\nwZ2l0fwmUfPzWPYFBEFDlLIEfg3buUQ8+g/YRgYJPBz3BvXG19DUU6jKQYLAAkFCkYfZcaJ/DHyo\ngsAHBVWVOHFiiHrd4sqVBQ4e7OUjHznEnTtrvPXWFJGIxnf+8hKRiI5pqMzOruO6Pp7r092d4Bvf\nuMBX/uR1/otf/gjZbAw/8Hl5/Sotzwrrz4JEVNbpNTIMR7o6i3ap3CAIoFZvEYvqyNKm+BpEYjp9\nA2lm7qwRjetksjFsx6O0UcN1PeJJ875WiZ7v887yMt+7cxvbe3Cd9D/h/qg7Ni9MT1O8p6G6F3xr\n8hZRTeMfn3uYrvYwmSAIzEytMbovTyJhcOf2KsqmJpQqo2sKdjvAR2N7V30MgnAQ6yvXrvDHV66w\nUK10/i9rmnxsdB9fPHKUQ7lcJwBU7WlUKY4qpvADm7o7jyyYGHIXDzJ+eS/sJcAs16rcXF/nYC6/\nw+dgqVplplRiNJXm7aVFErrOeqOBLsuMpcJd/2K1SkLXqVgWZ3r7OouyLIqc7x8gZ0b4f65c5i9u\n3mCtsZOIsRcUWk1em5/ntfl5pDY9+eePn+Dnjp/c1kQH2LArZNUEK60CfhBwJDFCVDZZaRW2PU/b\n4+RuENjY9gV07TFAJAgsZHkQVTmA563Tsl5lKzEgCFxs5zIt60UkqQdZ6sfzNmi0vo2qHkeWh/ZE\nad0r/j8RBIrFOlcuzzM8kqO/P40gCBiGytJSCd/36etLIYoilUoTSRRRFInXXpvEcXxKxTq9fSnS\n6QjxuEEsrvPcc8d54YXrlEoNstlYh7DZ0/YidQOPhmvxyvpVCnZ1G0W00bRYXa9i2x7JhIFpqkii\nQL4rwdj+HirlJtl8jO6+FK88f4OlhQJj+3voH8qgarv/HJIokjVNNhoNvn371q417P+Ev1k4vs/X\nrl8noqj80unTZM3Qfc2xXRzbw5MCvLZPsuf5pDNRdEOhsOET+AGapuxpp+sHAdfX1/ntN9/ghZnp\nDmNJEgSOd3Xz5WPHeWxwiKxpbitNOX6Vsn2LHvMJfGyq9jSyaFCwLtNtPoos3i1B1Z0FLK/YUcf1\n/BZNb50u8zyKuH1aeq9SDV4Q4Po+VjtJsT2f+UqZwcTdEmW51WIgEUp3BIQ9J0WSQq9qVQ1LWve8\nrySKTGQy/MOzZzmYy/Hbb73J7cLGjzwytTnx3huLEdvF7N7ybK5VZjiVHudS6Q63a4scig/9iJ8W\nSsc47hSyPITnL+L7BfygjuOEg4Mh3fgufL+C7U4iECBLw22tqgSN1ndRlYPo6hk+yF0AfIiCwNpa\nhXfemaXRsDs1zPW1KktLJd54Y4pC4W4GMDO9zvJSiR/+8AZXry4wO7PBhQsznDgxxJe+9DC5fDzM\nphZLREyNfD6O63rMzKyTTkc4enSQUqlBImEyOJjBMFRUVUKWwz9d+QS5fJzetj6/IAh06SkOxAeY\na6zxxsYNzmQm0CWFO7WlThCo1S1qtRae5+M4Hu4W31zP82nULQxDRRBFZm6v0WhYPP2Jo1QrD85M\nRUFgLJXiV8+fRxJFvjV5s8OcEAhZRlKbibPZ0BbYUqf9gH6jv2u4ng9CmCF6/tbBs7u16yAId06S\nJIaLdFsbSWw3/WRJ2hMnfHcIfHvyFkld58tHjxGVw/5EsxXOQPjtcl2t1mJ8fw+rKxUKGzV6+9Pt\nYwvuGwiCIOi4bf32m29wp1jAaTdYk5rOTx0+zBePHKM3FutIMwQE2F6Jmj2N49ewvRLLjRfxgiai\noCIJBnZQxfVbSMJdfn7NmaVq3yGmDgMCLW+dlrvRlru+9xvv5axsXm9wc32DXCTCaq1G2tjuJGd5\nHrcKGxSbLQbicQrNBsPJFDFNIx+JMJLc3UhIEASyZoTPTOznYDbXVkoN2UN7CQaqJNEbjfHo4CBP\nDY8ylEygSTJxTcPcQiLwfI/p+jKDZp5+Ixwgqzh1Sk6NpeYGs41V+s3trKMgCGh6FrONVVatEgnl\nXskRAVnqJwgsGs1vEDW/hOdvIEldyFI/vl9kq8i7IBgo8hgCEpLYRct6iXrza+jaoyjyOKL4/ifh\n3wsfmiCQSJicODEYNtB0BUGAyVsrTE+vc/bMCGfPjXae++abU6ysVjh/fh9jY3l8P8Dzwhtfa2fT\ntu2xuFgknY6STkexbZe5uQ2GhnNEIipnzozQaNhomozvB7RaLhA2+ObnChw/PghqQMGqIgoCtu9g\n+Q7zzXVGoz30Ghm8wGc8dlfHIxEz0DWZat1ioD/VXozDi3p9tcJbr96msFFF1xUUVeahxyaIRHVa\njfeudYqiyFAiyX/76GMokshLc7MYskzOjDCQSNAfT9Afj5M2DBKaTkzT0GQJRQx1fH5U79QPCpsL\nttte2CBcuN3Ax9k0USdkqSj3YVy9emsWRZI4OdLL5bkVyvVw0CdmaJwaCXWCKk2LizNLHOzLU21a\nXJheJGHqpKMmd1Y2+MjRMZI/gqTEJgQhnBzVZBkCGNnXRb4rlP0wIxpmREOWJWzbJZE0eOa5o0xN\nrrG6Uqa3b3cBN8t1uVMs8geX3uUbN29StlqIgkDaMDjR3cN/fvIUJ7p7OgNzWyEi4/h1fDxi6hAl\n6yYJdR8l6xpNd5mYOsZS/XkGY59CarOUgsBHl3MktUNAuDNw/Sa7LfmbCcVeTowqSZRbLT49McEP\npqaJa+q2noImy4wm0yzJVaKqymK1uo3q6gU+vh+0S64CkiDiE2B7Lj6hyuq+TJr/6amnOd8/wL+/\ndJHJwsY2k5qtkASB4WSST08c4HMHDtAdjaGI4o4Sl+d6lAt1tKRKr5ElIusQCPQLWdBzmIpGya4h\nCSK9xk62nCYpBEGAIWk7qKECgKBSb34DWR5BFBMEQRPHnSQ0qwkTwCDwEASJ0GvCwXav4rgzOM5N\nJCmPJGYIsPC8BqIYQ9jF5OpHxYcmCKiqTC63nd/tBwGSJBCLG2jalilGRUIUhU79dTeUSnVKpTrH\njg6iKBLFQp3FhSLPfPQwgiCwtFjiD/7gZZ56+uC2AbH19Rp/+e2L/Oo/+QTqMFyvzKFLCkW7Rtmp\no4kKE/F+ZEGi38yibhGfM3SFZMIgn43jtummgihAEJDrTvDoRw6yMFtAUSVsy+X6pXmaTZtoTMeM\nvjfFUhAEuqJR/rtHH+fa+hrDyRRdkcjfaGNwE74fMF0okotG0BWZjXqDmK7t4KRDmB3dWtugPxnv\n0DWrtk3TDSWfFVEirqmYisJcpUzNsSlbLUxZIaHpW3j5ITzfp9q0sCyPQA4oVppYLZf+ZALb93Ac\nj0SbGZTQde4sbTC9UiCqaRzqyeP4PiP5VDjzkEy8L+77AyGwbWHPtWdUjHscxU6e2V1j3g8CVmo1\nXpie4j9cvsSVtVA/J6qqnOju4dMT+3l2bIykvnvQEhAQBAnbr6CIUUy5j+X6iwxGP4nrN1htvk7e\nOE+3+ei214mijO/aNN0lQMD2isiCgbCLGcqejWMId2F1x6HQbFKxWmTuCbae71OxWtQdh4xhcKa3\njwBYuXObAKg6LYp2vWPz2G0kcDyP6fo6ZbtBVNEZMNPk9BhfOHyEUz29/MnVK3z3ziQzpdK2XYEA\nnO7t41ceephzff1Iosj6cpkgCHAdD0WVyLTZdLVKk6//u5f44n/1DFr7OnI9j+lry1TLDY6eGyXe\nMvmUeR674LDqFvF9n2Qmhm6qSEgcTAxxMLGzbBQEPq43j++Xkdq+zaIYA0QkMYuIjycuEAR1BCGO\n71fw/BKyNIzv13GFKWSpG89bwbWXcL1pIsbnkOUPTkTuQxME7kUQBNRqoVtVIvH+M7dGw6ZUamBZ\nDs2mza3JZURRZHgkjNSSJGJZLk8+eRBzyxTx7OwGL/71DXp7k2imjClplN06dbdF1W1RCuoUVi9x\nPDVKt759gGyjVO/4/FqWi2mo5LIxJCHMqGRZ6swoDI5k6e1PMX17ldWlMpktAdALfAqtJrokY8pK\np8Tj+j6FVoO4qvPIwHaz9SAIKK6USXeH7JVqscbC5DKD+/tYmV3HiGh0j2zfyjZrLeZuLJLtT5Pu\nevDQW6HR4MU7Mzw1PkISg4uLyxzqzu8aBJYqVX44Oc3njh3EUBTKVovlWo2qY+P5Pq7v4wfRsInu\n2FQsi/lKhe5obNftvR8ENB0X23VxPYHFYhlBgFTUpNxocm1+FVNTGOvK0HRcSo0WY11pepIxrsyv\nMrVSQJMljg3tzcz80ovX2XdimFbDggCS+Q+enud4Hq/Oz/On167ywswUpVaY/R/v6ubj+8b52OgY\nI6ndfZu3Q0STkthehaJ1BUPuDmUXhLZhfBsBAY5Xw/aLCIhElH5kMQxOupxDFiMUrEsoYpS0foTN\nXcH7aUCGMwFhIJBEcceOzvX9MGsPAjRJJmNup8o6gce6VevM5yRVE8fzKNsNZuob5PQY/WaqU+oc\nz2T4lYfPc6a3lz+9fo2XZmeo2aEkxOFcnn96/hHO9t1dLF/73mXGjw1SWK3QrFs89dmT4bnxAzzH\n28beW57dQJJFBFGgUbNo1K1wvkeA4lqVlbkNjj28D93cvgbshAdIaOoxPH+186gs9WA5V5DEOKp6\nqJPZS1IWP2jiuFN43iKaehpdf5zAr2E57yJLg4ji+5cEfxA+tEHAtj0WFgqk0pEdO4S9IJuN8cQT\nB5ib2+D3fvevmZnd4MDBHqLRMNKHpie7vzbcZcjEFZPVVok7tWVGoz2cSI1RsGtM1ZZ4beM6j+WO\nkNPu0v4kUaRSbYblHjnUUwmCgEAQaNQtpm6tUK+F279mPQxwvhfQbNisLBZJpiNYeCzWKyw2KgxE\nE8iiRFzREASYq5YpWA0GokkCAnojccx2XToI4NbbU6iGwsmnj1At1Ln+2iTZ3jRTl2bJ9qe3BYEg\nCJi+Os/NN2/zaPdZVuc2KK2W2+5aAbcvznLo4XEGD/YhiiKT6wW6YlEyERPP99t6KztPYMtxeXtu\nkYPdOZJGKL+tiBKOH0puVG2LIAhVLmVRZLlWI2kYDMYTHTrspkfxJmRRoisRJR8Pdd9dL6BYb1Jt\ntrBcj5btYmoKkihSqDZYKlZ4aGyAW8sbeL7PYweGmV4r8pXXLnNquI/xnuyO6fDVuQ3WF4oMH+7j\ntW+/y8jRQRqVFm//4AqHz48zcrifwA8orlUoLJcI/ICFyWWGDvVjNW3k9m5yfnKZU08fJpHZ3Yow\nAObKZb524xrfvHmzI6M8lEjy3Pg4z4yOMZJMUWw0cTwPTQ6VYldqdQRCKY9sJELCaF/HgkxH1A4P\nQ87jBg2CwEOV7j0GHxDwfAtBlLG8IjVnlrxxDk1K0vIKnZLR+8Gmv3RS1/nk+H4GEwmiqorteSxV\nq50ezKme3o5nsybLtFyXQrPJar3WkZuWhLB0mTViRCWNVbdKxWmSUs1QgK1ZJqfH2FQ0MhWFj46O\nMZHN8sL0AF+9fo3lWo1fOn2WE93bxdbWl8s88olk2B+8uczUtcVQnK7coLhe4dXvXSbbnWTsUB93\nri6S7oozsr+H9eUSkiTiOh6aoZLJx1lbKOyx2Sa3a//3SLILJpKYxHVniUbOb5kYDxCQUOQBJCmN\n7VzDst7C9WZR5Al07Uxn+PCDwocyCARBQLncYGZmg1OnhrZl6ntFLKZz9uwo+/Z18dJLN/nhD69D\nEHDlygIHDvS8d2bXng1o+TYH4wM4fmhPmNXipNQIPc0Ml0pTPJo93KGKKYoUKsH4PrW6A+hh5o+A\n43jcvLawa2Zl2y5L80WG93UhmzJ1125nQz6XCyt8pG8fkiBg+x5xVWe5UWU8mUUVtxrVwPDhfu5c\nmmX2+gJ3Ls6yNLXK9dcnWZhcZmFymfWFAiefPkIyH6e4UmZ1Zg1RFJm7scjggT7S3UkUXYEAoskI\niVyYATdsh4sLyxiKwlyxTN2yWSxViagqFxeWGU6nGM9nQj2ltjHMib4eri+vIQgCR3q7iKoaouPw\ndmmRg9k8uUgk1IcRICLLNICGY1O1bJque89QUUC50eL64hoRTePMWB8JU8fUVFQ59GvenHZNRnT6\nUgleujFN3NQxVYVGWzhNkSQCYaeBThAEzFxboLBSZvBAD6IkIUkimd4kZkxnbaFA72geVQ/tQNcX\niwjA6NFB1hYKuLbL2LEhZEXitW+9y8mnDu14fz8IKLZafPfOJF+7fp2ra6s0XZeeWIzPTBzgY2Nj\n7EtniKlq6Je8tkHKMNBkmZrtsF6rc3NtnYSh4wcBuiKjShKWV8D1G6hSHNuv4PhViq1LCIKEKoa7\nu7qzSETpRRFjyGKEueo36Yk8DfjUnTmayjBu0KRmzzEU+yzvl0rgBwGmqqLLcqcslzFMJgsb/NXU\nHT41HvLl92eznQliCHcGNduibFmYioLlORTtOgnFpOk53Kgu02+myOtxaq5FSo0wEEnvGN4UBYHB\neIKfPnyE8/0DFJpNDuZCY6JtEMKsnyBA0WRiqQiarqAbKtGEydjhfjRDASEkckiySGm9yvpymcNn\nRpi6vkSl1GBwXxeCKOxpd3iXnhv2vQI8HHcOx5nCNJ7FD6oUy/8bpvEcmnoSkJGkLsDHd+7gexuA\nh6aeQ5GHEYQPfsn+UAYB1/V4550ZDEPh7NnRHSc72CwavgfCRrHC3FyB5547TqNh829/5wV+9uce\nQ1Xv/9U3314VZQ7EBhAEgcXGOm7gISEiCRJ9RgZDUpltrDIeC5uSluW0h8UEau1M3/N8dFPh5EOj\n+G12y64fKAioqsRSs8pUpcDDXYPcqRQ4nulBEgVmKkXWmnXGEhlmayWidY1022rOc31sy8aI6uw/\nM4ZmqLi2R2G5xNiJYWzLIZlLcPChfaiGGjbC1irkB7MsT68hqzJ6JMwuNs91IhenWWuhRTSWK1Uc\nz+Ngd47eRBzb81iu1hhMJclHI0hSyNa5vV7A9wMeHh4I9XemZvnpk0cIgoB8JMLV9TXykSgTqQyr\n9RqqJJFQNfKRKGuNOlFVxfP9HSbqdcvhlRszKJLEWFeafd0Z7qwUKDdaXJpd4uxYH5snNp+I0peO\nU2laHOrPs1is0JeO8870Is8emyAT2zlZWys3WJ3bIAgCLjx/Fc/1mHx3BkmRyPamaNUtvvFvfsBz\nv/AkkYSJEdWxmzb5gQwbS0Vsy+HtH1yhZySPrIjbZEFc36fYbPLK/Cy/+84Fbm1shGwXw+ST4xP8\n5KHD9ESjaHLoXhcEQZv149FwHJKB3iYmeHTForh+QM122lPjAa7fwpC78AMHgSpZ/TRlexJT7sL1\nb2L7ZUr2dQw5j4BEzZklpowgALZfQxHjJNQJQCClHUEU5AeymHbDeCbNaCqFIolYnoMsSoiCyEgq\nxT88c67DwLm3FCeJIqOpNP/k4fMYsoKHT1INqbclp0mXEseUVAYjGXRJoWQ3MCV113tIEAR0WWZf\nOt2hdN/7NM/xmLw8R2mjjqrJFFYrxJImZlRD01VyPckt79f+/VyfwmqFxel11haLpH6EqgSAgIok\n9iAKUXT1HKIYQ5HHUORhVHk/CBIg43kreP4Svl9DFGNEzJ9AECMIqD/WvMeD8KELAr7vc/XqAndu\nr/L5z5/tlG+2IggCXM/bptK3G2q1Fn/1V1cwTZXP/b3TOI7HX3z9ArVai1Qq0qGN6ltrgUslfM9v\nawzdlYYYiGyvp4f+BtGQSdBGb0+S7q4EBOC4HuaWBuGDgs4mvCDkWfdHk9Rdm6pjUXdsCq0GPgF5\nI0JaN0ioGr2ROLbvIYsirXpY25+9tgCiwLM/+wRm3EBWJBRNRlZkVEPB2DyXkkjXcI5v/9vnESWR\ndHeSmauhJEFptYxjOcQzMSbfmeGZn38CTZaZyGcxFYWIqoAdhCweScRQQ2ZEqdlClSXODvXTclxe\nn5nj8bEhZEnEC3wajsNoMsVwIslMuUREUcgYSQbiCeKqRkRRmKtU6IntNC+P6iqfPHWAH169gyKH\n7I6eVIzfff4tlotVfuLckc5NK4kisiSiSCLlRotrC6sMZpOhXIIi7RhmAjAiOk/85Dk0U+W1b73D\n+MkhekbyiJKI3bJRVIUzHzva/rdDvdSg1bBYmFwO9aZcH1mR0HfZsd5YX+dfvfEa35+6Q0xVOZLv\n4pGBQT49sZ+hZHLHd/WDgJplk49FKTWaqJLUCYzL5SpDmRQRRW1/3wBDziH7OvO1b5PUDuLjoEoJ\nkvohHL9KxZ7E9qo4fhUQabmrZIwTSIJOsX6FAI+yfav92S6alCSi9COwt0Eoy3Ooey38wMdxXNas\nMgNmjpQaC5lp2v2lVQTCwBBVwwREQuzsbuPq3T7gpmlLWtu9wb7tPR/AZpIVmYljgyzNFZi7tYzv\n+1y/MMOhLbpkW96o81euN8mBk0MgQKN6fzp3EATMN9ZRJZmclui494VBdQLXdgg8EVk5iSgK1Go2\nhqHgumFDWZFFZLkHmQ/eM+BB+FAFAdt2uXlziduTq3zq0yfouo8Ymu8HOI4Xbu3ug3rd4u23p3Fd\nn08+d5xYe2LzM589ie8HLC+XcV2flZVym2EU5g9r69WQcuq+t0SDKIjoW9QIJVFkc43ZTZL6vSAJ\nIj1mHMf3ias6Kc2gLxInpZuojRorzSqO75PVo1ieGzp6yQpGTGfoUD/1cpPiSonl6VWWp9corpZZ\nurNKYamIYzl4jkffvm6S+TjTV+YproSCc7F0lFxfGkVXePM771Ir1Tn10aOc+uhRgiAgBcwUivc9\nbkEQSJkGKdOg6TjcXt8gbZr0JeJcWVplKJ3c5jWQM+/ezFsby/sz9xerqzQtqi2LqKHRsh1uL2+g\nKTL5RJSLM0scGewmboTDP6mogSJJTK8Vieoa5UYLSRSpNi2S5k6bUFmRiKUi+J7Pwu0VMt1JSmsV\nFFXm8ss3iWeinPvEcVRJxGrYVAo1XMdlfbEIooDdchAlAc1QdyQmK/Uay7UaHxkZ5fGhIc73DzKQ\nSNxXjqHhuAiCwKn+XmYKJVaqNfqTCRzP50BXfnPT2J5El5AFA1k0GEt8CRCoO2z6bGcAACAASURB\nVAtk9OMICOTNh8nzMNB23fM2iKvjaG2WSo/5HLa/zGL9BlBHElw0qR9T7ttzRajmNlhohrtkTVRI\nKJFt98SPCtf3kIS9i9ft6T1dj5WFIsW1CgGw73A/PYPZcIe+A+EPGQRQLTZYmt2guFpFVu9/Xzc9\nm6/M/zVVp8nT+eOcSI0RVQyaTZtioUGp1EDTJHRdIZ2JMjuzTr4rTr1mkUpFdrDK/rbwoQkCjYbF\n1NQatZrFY4/v31UYbhO6rjA2mica271B4jgek5MrKIrEk08eIJOJdi6mdDoc5lhbq3L8+CDnz+/b\nRjNdW6tQq7WI7IGy+SDMNVZZbK6xPzZEQons+WJWRYm+SLhgDsdSmEp4YSQ1naiiYsoKPeb2cyOK\nInpEQ5QEEMB1PBzLQTM0ZEVCkERESURWZURJxLFczJjBofMT1Ip1NENFvc8FuPW4OwvcfWJvudni\n5alZNuoNhtJJZotllis1bqys85mjB34soTnLcVmt1OlNJbi2sIrtejx7bJxSvcmluWWqLYsnDo1i\nOy71lh0apEQNupMxfD9gIJPgxevTfPz4OJnY7hnl6twGZkxn5MgAru2SysUJ/IBsbwpFDTn6kYRJ\nfiCD63gce2w/V1+bpFFp4Dgey7Pr1NrSIZs41tXFM8NjPDY8hOv5DCfvlhz8IGC2VGauWGIonYQA\nUqbBUCrcIQynk52hwIShEdd1Wo5L3bbvPXREIbyGY+ru062CIGLIdznslucyVa5yIDOMXI+T0HSm\ny0VSuo4k7n0x0iUVXVRpeBayIKGKcmf33HAtvr9ygWPJUQbNnQqlD8IPVt8hrcY4kdz3nhRo23O5\nUplmPNpHVLk/kzDwA0RRRFFlVC2c1UlmopQ2ars8OfxLUWWMaHgfGVENw7z/urDY3GCyusjl8jTX\nK7M8lDnIU13HGVa6cByXwkaVfD6ObXt4Xtj3FEUB3VBxXY9m0/47CQQfmiCgKDI9PSlGR5X2sNj2\nC8b2W1wuv87J5ONMTHTT358mlTKxvCazjVsklCw+LjmtF1EUGRhIYxjqfU/q0FCGz//UWZR7DEhS\nqQif/vTJXZvR9xpmPwhLzXX+cPa7GJLOM11neCR7DK09U/BAk2xRJNp2RIsqdy84TZJ5wM66A1VX\n6RnJs3R7hbHjQwzs72VtfoN0d4rD58MGnef69E/0UFotUy3sTYtFkSQkqX3cbcaPtGW7CyHt0XZd\neuIxBlNJIqpCTFd5d2GZQqPZCQJBEHCjOkvRrnIyNRGeF+HBdMRUROdjR8dJmDq262JqKoaqMJhN\n0pdOYDkuqiQiCgr5RJRMLCBh6h1lzHwiSlciinkfFVLfD7hzaZbBiV7693Vz4fmrXH75Jl2DWUaP\nDnY09kVJQFZlPNejUW2hmSqSLFFYKdMoNznz0SOomtI5JxnDpCcSJaXrvDm3yJF2Nq+IIpbrcnl5\nha5ohNVaHdf3yceinRKRJIo7KLi6Inec1H4cvDQ3w63iBndKBdYbDU509YBAx41sr6g6Teaba8zU\nVxgw8ySUBqook9ESSILIlfI0f7n0JuezB3mm+xR5LQyC73X/XCxNcaU8wyPZQ5xNT3RKK7vhjY0b\n/PXaZc5l9vOFgSfIaLtTes88dYCBsTx9I1msVjiguTy3QWG1gm1tH9gM/IDAD+gfz9EzlCEaNzoB\nY2lmnVbTuSdBCpiqLbHU3ABgpVViqr7MQ+4BJF0kCELV2eXlEoePDGAYCqoik0pFqFZbmKb2I1UP\nPgh8iIKARDq9+wXo+g43qxeJygkWW9PkzT4ikTAbLjoFGl4NQRCpOAWCwKfuVhlI7LuvcQSAaWqY\nu0R1WZZ2tZn0A58Nq8xUfYl+M0ePnn3ghSwIAiWnxrXKDDeqM3x98SWe7TrHydQEKTWGKu5NS2Yv\nCIKAZq1FeaOK33Yas5o2+04OhwuW53foqhAuZIIgduigEE5N2i0Hu+ns2ms51teNgNDxIXh0dLBt\nKxhK4TrOTZLGIM8eGEYUFWShietNEVVV8vtTqPLd3Uvda/Li+rt8Z/l1Hs0e5Sf7n6JHzz7Qm0GW\nJPozm+XBu7+bIAhk45Etz2PXRVJTZIbzu3O6fd9n7uYSkiIzcnQAz/XwPJ/Zm0v0jnXRqluhK5oi\nU680WJvboLBcIpGNE0uFjczDD49jWw6DB3qZub7A+MlhFqvhtPndDVTA2wuLWK7HI0ODrNTqTGSz\nzJVLrNXqnBvoRxHF992Y/VFwIJMjoqoMxpOs1GvENY2MYRJV3l8mmtUSnEiNcyw5RsmpkVJixNrZ\nuCrKfH7gcf6Xy/+efzf1ff5q5R0+23eep7uOE5PvL30NYUIwW19luVng5fWrKA+QbV9uFSg7DZZb\nBZqezc8OP0NO31lKPnx2FEkKS0xmuz8WT0V44wfXdvQF4qkI0bjReR6AEdHwXJ+3ptfRTZV46u51\nV3WbXCnPULDDXcVItJtfO/BT5PQEnhUgySKZbJRGw6ZQqKHpCqoqU6k0cRyPS5fmOHCgh3iiTfYI\nfBquFU6nf4BrxW740ASB3RAEPpbfYqE5hS6a5PVe5pt3WGstMhgZJyonuF27QlSOIyGhCBqiINOl\n96OKe1dtfC/YvsPN6hx/Ov88bxSu8kzXOX5m6ONk1PsPEcmChCLIBATU3CZXK1Ncq0wzYOZ5Kn+K\nM6kDDJhdmPKPf5yu4/HSn79B90hIY/yrP3yZ7pE8G0slFidXmLo0R3G5jCSJdI/kO8NPoiQiKeEA\nW73c5NKL17n66i32nRze8RmavIWOCujKpiGJheeXQZBxnHeR5SEkMYXt3MIPygiCgUQZUTDYNE8p\nWBUulW5Tdmp8c+kVrlVm+JmhZzmeHCemmO9rQCkIAhpei5rbJKMm9mTys+P1lSb1cpPesTyO5XLz\nzSmicYN/8D//FC9+7S3+/De/y9ixQY4/eZAbb05htWye+ZnH8D2fa69PcuZjx5BliQsvXGX+1jI3\n35piYKIH1/eZ2ihSbvvPVloWPbEY+7LpkBqrKJSaTWaLZRzP48LiElXbZiKbeaAxzgeBK+urLFQr\nrDXq7Wltla5IlGP57h3srAdBEAQUQSIQRLJqnKVmATdw6dJDIcfhSDd/f+Sj/MubX+V2bYlfv/Fn\nrLZK/OLYc3t6/6wW558f/M+YiPd32HfiPeWh//Hi7/Hi2mVyWpJzmf0k1d2Tyd1Ues2ozmd+7rEd\nj59+8sCu3zWWNHc8PwgCpuvLvFu6Q0CAKip8pu9h+sywx2UJDj09SSQxFLZMZ8KSdN9AGl1XMM3t\nvSQv8LlWnuHP519hf7yf53rOEpF39rI+KHyog4CPT9OrExAgCTIlex0RCdu3KNsFJCR00UBAIKlm\naXg1Wl4d17eJyu9t+/ienx/4rLQKvFm8zjeXXuFObQGAH6y+RU5L8pP9T923CaaI0o4FKSBgtrHC\n709/ixfX3uXR7HEeyhxiNNq3q3PZXuE5Hv37exk7NoisyMRSUS6/dIPLL17Hbjl4jkthucTVV28R\nS0dJtmlu3cM5Etl4+Jq0wv7ToT7TxOnRB33cNgiChigm2mPx3ShyPwF+SHULSohCEkUeQmpz1v3A\nZ9UqMtNY6rzHVH2R35j8Cs92PcTTXacZMPJ7Xsx9Al5YvcDbxRs8ljvOyeQE8ffRgwEQJege1bGs\nCqvLkwydjBNNSmiywif+X/Le8zmuLD3z/J1r86Z3QMITJEFXZFWRZVm2q6urvVO3WtKMpBlpIyYU\nGzPzQX/AftuvGxsxu7Mba7ShGWk0UitaGkmtVqu7qr2p6vKOFiRIeJ/eXnPOfriJBJIASJBFRdRq\nHwYjgMzEtXnPe877Pu/z/OtnuXHxKjMXb9DupDnzfJpz+nHq9VVKC1Uee+kMTtyh3eyQzidYmd3A\nckzaTZfRfJKVWj0UOlOhA1Y+FmUkmezl9jcaTbLdOsCbC0tcXltnLJX8yEEgUC6lzg1iZoGIntoV\nWHNOlKhpcjiVoep2MDWNzVaL2UqJ0wOFA++n5Xe4Wlug6jXI2UkMYWDvqCmYms4jmSmeGzjDd5ff\nIFCSn6y9z+9MvnjbCZDsUmUV281o1WqLVCqKZe39rByJD/FM/vQ/+SrqVrjS51Jljvlm2BE8lRjh\n6fx2r8hWJ/LoWP9KNJfbFpvbecjXaov88cz3eas0zXvl6wB8ceQJHH236un9wMc6CAg0UmaWortK\nRI8SMxJonk5Ed5iMncQN2uTtITqyTVSPh+kKQmtISRA6dN0DpJJsdCq8WbrEG5uXeL9yjbq/7Xvc\nCjp8e+nnjDkDPD94bs9t6EK/rfPYjcYSCsXxxPie7zf9Nm3pkjRidxwQIzGbU09M9X6PjiR54jce\nJ2ZZ6ELDk2Hn6WYjdHCqdDoESlI41C92lR/Lkh+7Uxt8P4JgAy9YACWxzGMEsooQFpqWRCnZXQFs\nT3M86XO5Oksr6C9ultwaf7v4U67VF/jc0JM8kTt9YJaJrwJ+tXmBK7U5zufO8LnhJ5mMjRwosAoh\nsGMa2FW0YA09vYyhpWl5bUw9j2FkmDwzxMDxVQytBsLEV+soa5qRY+NEuumTSNTm/Be2vwteEFBu\ntRmMxcLO6FqdoGtdeGV9nfFUmvF0CjcIKLVanCkMMleq8PTkRJ+cgiubVNyb5OzjaMJAKp/NzjRx\nY4iInt53UKi489yo/YiJ+DPYkURXnGwbpqZRk5JXl+ZJWjYJy0bXtNsavO997X1SZiz02zWiOIZN\n2upX0sxYCZ4beJD3yzeYa67hSh9f3X4/gQop4AJBu+VxY2OdzWKdWNTCjlgMDiZ7jL+duJdBsuI2\n2HSrd/7gPii5dX6+fgFfSQSCs+kjFDuhAf3douY1+ebsT3i7dA2A9U6Fb879BEsz+OLIkwd2M7wb\nfGyCQCdoUvHWCbpytoawyNhDGMKk7lcRCAxNpxXUCVQo0WxqNju5bJrQsXSbiB5DcG8z65X2Jj9f\nf483ipeYbaxQ9urd+Ug/im6Vv5z/ISPOAFOJ3WJOxh2CwIOpKf7loU9zKjm5a7CSSvJ68SKvrL7B\n8cQELxUeY8Q5uHH1ZqNJxw+ouy7ZqEO51ebsyDDXN4sYmka13WEwHqPpeqQikZ4Ewb1ACBtDCy3z\nOu57CC2OZRzB0IcR0kbXMii2i24d6fFO+eqe22pLl7dLV1hsrTHTWOLrYy+QNG9fqNQQPJ1/kHfL\n0/xi433+ceU1putz/Mb4izydf+iOqSWlJL4sEcgmrr+IEAamlkOqDm1vBsecQqo2AhuBiRssI4SF\nF2xiG4e4HZfSMnSyepQXp44Qty1yUYeEbYcrW00wX6kQKMWhTJpfzs6HTJFb6hk6BouNt9CFTdY+\nikCj4a/jygbDzlm2TBx3nqcrm6y3L5GyDtHyi3SCGs4tK+MzAwUanstCrYoutC4rSMO4yxWpJjQK\nkQxRI4LG3l20mhA8kDrEmfQkC60NJuOFXn+NLwN+vvEhj2bCVOAWPOWjUN0aVISUGcUPgh7Rw7oN\nVfNu0Qpc/uzmD1jsFnXvFq70WWiuA+Fq/2frH/YG8btFJ/CYb673jTkbnQp/MftjIrrFZ4Yeve+r\ngY9NEFAoJBJN6GiEufSKu07OHiGmJ0lbAySMNCBo+tuULl3o3WAAEc0hqidImAdLBQUqCJtd/BbX\n6gu8uvkhFyozFN0qzaBzx7+/Xl/kP9/8B/7g6FcZcwb7bs5+QSCiWXx2+El+bfR5hiK5PVkPAoEu\ndBab63xQuc5P197h2YGzvDB4jqFI7raFIi8ImC2VqXVcIobOWCrJYrkKIgwOjmmERh6mQbXtognt\nIwaBOLoeR8fH0AuAHgYGw0FnrKtMuT3rW2kXma4t7Ls9UzPQ0IjqEUztzl9PIQRZK8lXRp5lvrnK\nXHOVS9VZ/vfpv2a6tsCXRp4hYyVvsyoQGFoaqbcQvsDQsoQuT4qodQpNRGh1pnGDeTy5iqGlUKre\nd057wdA0kl3HqnT3+g7umCArpRhOJLoNUzpR00ITok/fXikFQjAcPYepRSl1btAJqmiYBNJlrv5L\nmsEmCXOYsdiToEDis966gEIxEDmOIezuiuApHCOHRkh1DZTE1HQyEQdB2K+hCcFyvbbLaet22Lpf\nd1p1xY0Ij2aOcaU6z9fGnu1JP1yvL3OlusDD6e0UpC8D2oGHQmEIHd3X8YIA35NsNurUau170hPb\nDzk7yZdGzvNG8QrDTo6hSIaEGcXRrTtOIlpBh//r2j8wI5exNZPfPvQizw+eQb8PM/YtIocQYXBN\nGv80Xt4fmyAg0DCFRd0vU/fLHI49hKOHT82R+ANd2VxB3hoGaztKDtijbDV6TcSO3/amKaVwpUfN\nb1LxGsw3V3m7dIX3ytfY6JQJlNxz1r8fJJK3S1f45twr/P7hL5Kzt3Ovxh41AQjdyV4YePT27CIB\n53OnqXh1/uvs95lvrfHNuZf54eqbvDB4jmfyD3EoNrxnukQg8KVitVZnKBHH1MP0WCAlHd9ns9Gk\nkEjQ9nzcwEe/B4cVpRSBagIKQ4t3PZg3MfXMDgGyWxVeQrxZvIQnd/sn6EJj1BnkE4NneXHwMQbt\nTJjKcn2kCp25lAqbBKXcZjWFxwOnkpN8bug8fzb7fRpBiw23wrfmf8RMfYlvjL/IyeREn+x3PyRt\nbwZfVrD0cRQBbe86Kec5lJJYxhi+rBCoehgwlIvP7WeNd5qtCSH6iu3JyO6BN1AuFW+OijtPKygy\nEn2UqJHD0BxafpHLlW/zSO732VqN+KpN2Z2j4W9wOP4Cl8r/jSHnYYajZ/mw9JfkIicYds4RM/JM\nFzdZqFVp+z7HszkW6zWGYnF+OneTyQcPrlIZOWBPgRCCZwZOM5UY6Tn0BUryfnmGoUiGqL59/g2/\nTbubLowZEcZyeYSkV0S9HwjlOcJ+CU2EvsIPZQ7jS4kvw2rEFhvOMfavz7y6cZErtXk0BE/mTvKp\noXOMOrn7MlsvrpYJ/ID8SPb/H+wghcRTbtdQwqAjW1haBEOYfbPl8GKIHT+z/fsew45UkprfYq1d\nZKW9yUJrnZn6ItO1hdBD9A4zup0whE7McIh3/yeMKHEjSsZKdgtjOxRFhb7nbGDri3UnepypGXxm\n6AmKbpW/mv8Rbemy2inyzfkf8Ormh3xu6DxP5k4z7OT7ZmGdwMcxDJ48NEYgw+V0y/NYrYVqnY+M\njbBcrVFstvBlwEQm1b1OPnV3GlPfPgelJG6wSdw61mdPCIqmN0vLXyDnPA1oLNf/jpHEr6P3AtPu\n8/Okz7ulq8g9Am3WSvLfHf4C53MPoglBu+XS8lw2N2p4rk9hOB12cQuB5/rUay3siIlhGqAUheE0\nT+Uf5IPKDL/a/BCJwlM+vypeYNOtdNNDD2Jqxi3fE0UgGxhaCseYwtRzCGHRFmZ4J4SOpRfw9FWE\n1LCNQ/iyjC/376DeC1JJ2oFLRLcPbPCjaxYpc4K2XyZQHgJBzV9HKUmxc5Uh5+GuimgYMBr+GlK5\nTCU/jSYMNGGiazZp6xCn0r/GXP2XVNxZHCODJyWGppOOGLR8n6brshBU7tprYet7LJViubVJ2ooR\nM/Zu2IroFodi20XnUqfKUmuTZwdO9wXoklujGXTCDnonh98JWFmp0G65xOIRlFJEo9ZHWg2UO21c\nGbDWrJO0bAKlOJLKMt+oUvc6lDttkpaNoek8kB3ccxsVr8HfLrxK0+9QiGR4aeiR+xYAABrlJpvL\nJcqr1TBT4kt0Uyc7lCY3fP/kpD82QWDLpM7R48T0JIHy8JWHcUANk51oBx2WWhsstjZYaq2z2Fpn\nvrnGQmuNqnew5ihbM8laSbJWkpyVIh9Jk7OSJM04KTNG2oyTMhO9NvldUgT7pIPuxhvV0ky+PPIM\nq61NXll7s/f6FsPog8p1Xhh8hEczJ3v5VMc0GU4lqHdcRlNJbMNA1zSkgqFEKFT2yNgI8+UKy5Va\nT7dFqjYrjb9nNPGN3n4C1WG18Q/ErX8fHrsKaPsrSNXBC0q0vDmqWhpf1jG0BG6wQbXzARG9QNw6\nsUvwar65xmJ7Y9d5amicSk5yNn28N0BKqXBdn3otlHxwOz5KKSKOxc3rRYQGdsfHdQNOPjACwFAk\nx/MDD3O1Nsemuy3de62+wJ/c/C5SSV4YfOSWeyUw9TwKj5ZbRQgDgdGT6w1kk5Z3CV9WMbo67qaW\noy7rbK1A7wSlFMvtTb63/BpnM8d5MHX0YKkuBIZmI4SGUBqmFiWq51hovMZ84zWeHPh3fftw9Cwp\nc3zXdRdCI2VNcCYz1vvdl5KVRg1b12l6HrKrdHo6v/eAdydIJfnZ+ocU3SpP5k5xKjlB1Lh9Wmmm\nvoKGYDDSbyu53C5SdRuYwuBkYoxWy6VWa+H7knK5Sbvj8dRTx26z5dvDkwHTlQ06vk/dc8lGHNqB\nTybiUO608GTAcqOKrWd7nsm3IlCSn659wKXqHKZm8OzAGR7JTN3XGXsiG6e0VmHuyhKpXJxaqUEs\nFcUw9H+uQUDh6AkiWowNd4GsOYx5gKWmUoqO9FhpbzLXWOVmc5nZxgobnTIlr0bZrdHZI/2wF6bi\nY5xITDAaHaBgZ0mY0e6sP0rCiN4VRUsX2p7poC3im+cHrBfrRCMWfhCQz8Rptl3K1RYCSMQjNJou\nyUSEr4+/wHJ7kwvVG73ttKXLrzYvcL2+yIe5Gb488izj0QKaEIx2lT63+N7nRoeJWVY3D6xhaBq5\naJSEbfcKkUpJpOwQMw/39uHLBmHOfKvRS6AIqLoX0ISDpjkEqo1jjpKwTuDLbgFf31vz6Z3yVRo7\nWFZbcHSLTxee6KMMRmN2T9LXcSyWFkocnhrE8wKWFooMDqVotzxKm3WOnwwFtzQheCx7il9svM8v\nNz7sW+Utttb5i7lXSFsJHsmc6L0e3k8dQ8viWKfQhA1oJCPnu++H71nGGKaWRwgdKVvErIew9MIu\nWeq90Aza/Pnsy/xk/R3eKl3h62Of4On8Qzj63UuTKAIkPoPOg1yrvczJ1FeJ6EkMzcbg9tvbGRxG\n4glK7RZRw0Si6AQB85Uyjw/fm2OVJgTHE6P8x6tv8vrmFR7LHudLo+eZiA7sWfdqBy7XaoskrRh5\ne3tGL5XkZn2VTbdG1LA4m5nCwiAWs+m0fQYGEnTaPp2O3yf8GF4b9vW56LsOCGzdQBD6Hm95Nlua\nzng8zfsbyxxN5egEPoXorZ7BIWbqy/xg5R1qXouTyTG+MvrUbSUr9kOgJBWvgaNZODuCZmm1wts/\n+IBENs7I0QITJ0fYXCoxdHjwtppp94KPURAIZ4RVfxNTszE1G22H3Z0nfTzp46uAildnqbXBXHOV\n6/UF5ptr3Txih1bQwZV+L+WiIXB0G11oxHSHgUgaqRQ3G8s0g35FwM8OneeFwXPYmhnK4e7BMJJK\nopCEWxaorlEH3WqCRtiRaGj7rAS2ij3d32eXivh+gB9IYo7F0lqFTNKh0XIplhucmhpiMjbMv5j4\nNP/PzN9xs7myfSwo1jolvrfyKy5Vb/B7k1/kkcwJHNPEMU2UrIKskrUD2MrVaxmUP03C8EFXqGAA\noQ0CCleWKLXf3nGubXxZ6/0uhIatD9DyFxlL/BbF1qthykFEcIMNFD6urJAzhnel5hp+i/fL13q5\n3p14OH2MM6n+3gSlFG7HD529sjHqXTOesHNX7xXLjK7V6BYSZpTPDp/n/cr1Xau+ueYq35x7hUE7\nu8sLVtei6H0pr64VoLCJ7AiM4TE4RK3dzUS3QqmwUfDP517m5xvv4UqP6/VF/mjm2yy3NvnyyLO3\n7WlQSuLJJjVvGU2YVL1FSp2bDEROETMGuVn/Kdeq/8jp9G8Ae9Uh9tdcX6xVKbfbBHao8Jq0bQZi\nMW5WSz3jl7uBEIIz6cP8xsTz/J/X/4FvL77GO6Vr/P7hz/BU/oG+CZFSivV2mYXmBk/mT/bqCkop\nVttlLlZnaQcdnhl4gGEnS6vmYhg6m/WwKOwHQZ+t51Y6dKNT4VptkfHoQO8BUwpqfpOq12DQTpM0\nQ8pu1DAxhEa506bth6sAU9MoBR4Vt82xTI4PNldJWhE2W01yzrbkSc1v8vLKW1yszhIzbP7loU9S\ncDJ4cu9Vw+2w1CryH67+NZPRIb4+/gzDTi4csxIRMoMpZj6YI11I4cRsKhs1ookIsdTd35/b4WMT\nBALlU/JWCZSPrTmU3FWSZhZLhNH1J+vv8KPVt8IBP2h1GTQamtC6DCGdpBljMJIhZ6UYiKTJ2+nw\nZzvNgB1W/DUE75an+aOZv6PZ2g4CAkHMsHF0g7pfotreYChyGCE0AuWjodEKGgTKp+GXydrDRLQo\nJXcVXTNxgxa+chmKHMEQZpgO2nMlEP4v1VrML5co5BI0Wi7phEOt0aHR6OB5AZapE8gttyWdc5nj\n/Pr4J/mTm99lvVPu26YrPa7VF/kPV7/J7x3+As8NnA1nmaqFCuZRqgmEjCKhT4LcBBFDySJCz7MV\nlkwtQcyc3L4nsoUubmEOCQ0vKNLwbtAOVjC0BF5QphOsY+v5vsC9E1drcyy21nYV3iOaxRdGnt5V\n5Pa8gHKpwfBYhvXVKtGoTSRiUq+3w7b/mI3vB1TKzVu8ZQXn0sd5IDnJa5sXbrn2oWbRT9ff4bcm\nXtqT0eJKj41OpUdD/ijwVcAPV9/keyuv0eqyzRSKolvlL+ZeZrVT4rcnPkMhktlztuzJJler32XQ\neQApfW7Wfko+Euo/Nfw1kuYozWCdZrCBo2cQux7nvVT1Q2ScKC3fZyge59LGOo5hMhJPMlct7/n5\nO0EQdg4/O3CGheYm35r/Kdfry/yvV/8WgGcHzvSClEJxs7FGPWhxJL5t8OQryTula7xfvkHKjPOV\n0aexNAMzaZBMOmSzMSwzFEE0jO3rNRENmwsvV+f5Hy/8GYeig710WztwmW2uUXbrnM0c5Q9PfI3B\nSKZnbvNAdhBL10NHOylJ2xFGYkkc3SJtOZzIDPStLHwV8MuNi7yy8g6uDNgcoAAAIABJREFU9JmI\nDrLQ3GBt8dUd11zt+HkLao/34bXNy7xTvM77pRvcaKzwb45+nlPJcWzH4vCD4wwfLXDjgzkuvHqV\n/GiW2UuLjE4Nb8vC3wd8bIKALgwEGu2ggS5MnG5hbgslt4YCjsRHiRkRUmactBXv5ezTZpyMlSBh\nRu9Iz9pdHAzhK4+Su8pi62qv8zhp5qn6mxjCZK09S9oqMOJMoYmwZwEh8KVHyVvtdjO30IWxb7OY\nItTxMTSt910QQrBZbhBzLCIRE0PXSCejFCvbM1lTM3g2/zAr7SL/beEnu1YxABtuhf9887soBS8M\nPoIpyyhZBNUCLQuqezzKBTSEiKP8OYQVznoD1aLlL/W2J1UbSf/MXQCacHCMEVre7I4Uw7aVx63X\n1pcBF6s3WW/vHmCeyD3AsfjYrkEw8CWF4XQoAV1pkUpHQyVHx+KhcxM9jZWBwWTfgABhPealwhO8\nvnlpV+G/FXS4UV+i7jVJWbuX+lWvyV8t/Ii3S1eQd2houhN8Jal6Ddw90pGeCvjB6huU3Cr/evLz\nHImO0XRdXD/oSpILTN3mROpLtDoK0zCIJQZZar7NYvMtXFknkC6m5uDoORxnd454MHKKqL53899k\nKk0hFsMxTOKWTdQwiVsWk6l7zzULIUiYUT41dJZL1TneKU2z3inz8srbPD1wumcJ2Qpc3i5NM+Lk\nGO76dMuu9MI/Lr+JJ31+c+ITTHUDRDgGCxKJvdMtLw6d5WJ1jsvVORabG8x3Ofs7YQidC5VZrlQX\nGIxkyEai1NwOhhYaIgVK4smAQCnO5ApYusGRVLavUC6V4lptib+a+zlFt8agnWbIyTDdVRK4F5Td\nsA9JKknJrbHc2uRYYjRUY7UMIgjOf+kRFq4sMziR75k/3U98bIKAJnTy9iiDkQmafpWEmUXfYaX2\nycFH+cTAWeJmlIh2cIbF3SBcXRhkrWGq3gatoE7SzKOhYWtRdGHiyjZld42YkUKqADdoAoKGX0Eh\n6chDOHoi5DfvEQRk1xbN8wMK+QReIBECOq6PrmlkklES8bB70/ODPpeqqBHhs0NPMlNf5FebF/dk\nNm10ynxn+ReMxwqcdDqAD1osHPBVDaElwpSQaiBEDKGlCf1NXUwtRco+09uWLxusiVd27UPh48sG\ngerQbeu8LbV2060wXVugLfsDSsqM89zA2b4moS04O6iAR48P9X6OOBZDO5Rho/s8FCcSE4xFB5hr\nru56L0Di7zPTz9spPlN4gvnmGu+Vp/c9p/sBqRQbnQqbnSoTkYBrq5sUGy1itsVAIkY+EcUybG6s\nrzKYjDGYLHAi9cUDb38oenbf9zQhiHW7nYdi28EwYnz0IeFQrMBT+VNM1xap+c0+NphSirJb51pt\nia+PP9NbLVe9Bn+78Euu1RZ5fvBBPjv8WF+O/HYYjw7yb499mffKM5TdsJl0S3aCbsZgq6P5SDwk\nEWRsh4x9+xz+rfWAmtfgbxZ+0Rv0T6cO8e+Pf5WcfW8sJaUUf73wc6Zri6TMGL829jTPDZzB0gyU\nVKHEeyQclwYncqHcdL19X1cB8DEKAoYwUcIIZ9GmsavjN2/vXWy8n/CVi0KioeMpj7Q5gK88AhUQ\nKB9J0KOsRvUEraBOzS+TtQqYmoWtRbs1gm5heJ8gIJUin4mj0opao0Oz7RKxTSxTJ5uOYZk6zVb4\nWuQWR7JCJMvXxl5gujbPhlvZtX2AmfoSH5SvcSQyiW2cQqkKiCSC8BoKkUBoSdRW6qY7IB6sR0Jg\niBhx62h3JaCjCG7bnzHbWOFGY2nX6w+npziRmLgvjTV9RygEccPh0czJXUFAQyNrJfcMPFuYSozz\nu4c+iy8DLlRnMDWDgp1lKJJjIBLmleO6Q0S3MDSj22W79/lfry/wo7W3qOzBSnsgOclvH/oMD6aO\noqPjBxIpJa7v41gmjmWyUqmTdGyWSjUGk9uDklKKtdUq1XKTqRPDCAHttsvFDxZ46OyhnvH9Tvhe\nwMUPFxgaSZNKRbl8YZEjxwok9lDN/SjQhcZT+VP8YOUdbjY8jsSH+lJvFyqzSBQnkxNAWO/7m4Vf\n8urGJZ4ffDDMsUcyd2zU2oImBIfjQ0zGCtT8FrrQcPSuKJtg307mu0GgJP+w/AY/W//wI21nP0SN\nCEORbE/5uF5pUl6rMH5ihM3lEsWVMumBJLOXFnns0w/d131/bIKAtmMg0Agt9YSmejdScG+6IHcD\nS3NImQPowqQl64w5ofeqpUXQhUHKHCBlDhKocEYbpkIUSTNP3S+TNHM94bota8qweLxjJkTYkBYW\nMwXppEN6j4cwehtziVPJST4//BT/ZfZ7ew7cnvJZaq3TVOewzSRCtQEdtlJsRgQwEQSEna/heXhB\niXL7vd52pGrjqzpKyVtohwovqNLyl4ma48Ss4wSqRcObQdf6i1btoMN0fZ71Tj+vPmsleTJ7+sDB\nfWf35EEQ0S1Opw7z7aWf983601ack4lDt2kcCwexU8lJ/s2RL7PQXGMgkiFtJnCM0EBla+DXhR4S\nELr3WGz923GMr21EeW3zwq4g8HT+QX5n4rMciY+gCY2259P2fdqeTzxiI4Dlco101KHaapN0bMrN\nNtmY09t+EEjeen2GdDZGLh9qZ60slcnmEowfyiG7ZukgcF0PKWFpvkQ0amPbJrM315k4nGdxfpN2\n22NiMr/LX+NeMezkeGn4Ed4tXefzw0/0XlcofrFxgaPxYQbsFDWvyd8svMoPV9/liyNP8MWRJ8nZ\nSRSK4E7+sTuglOJ6fYm/mP0xJ5PjfHHkyfumvBnSXz/g7xZfxZM+lmbg3kMR+K73G0h816dRaZIZ\nTNFudqis37vG0X742AQBgHbHI5ASTdP4y++9wzc+fZbFtQp+EHB0LI/VZYXs/OxeM7C265FJOLsk\nZ+8EDR2j69AUNzJYejg4Z7QCrmwz6oTmFp500TUTRyQYcaawtSgZq0BEj2MKu3dIpmagC61vENpe\npnZ1a5SHJnSkCrrpqG1JiHbQwNQsBBq+crG08HhMofPS0OO8Xb7KhcrMnufiygCJjhBmd/DfCYNA\nStoemLqJZQgarsTWHyBpn9pxrB3afih01/F8fBkQMQURYwyJi6EnsI1BLC2DrQ9Q6bzPsPOV3t+H\nbI8S75SuEuzIr2sIHkwd5Vzm+IFXAc2gQzNokzSit/WJ2IJAMGBnGHbyzHdXAxqC44lxHsvemdlT\n8apsumt8svBoGMx3DCZlt8qGVyGUCW8Q06MstVYZcQocjk0c6NheHHyMI/HRvr6IwWSccqMVis81\n24xkEsxulCg1WmTjDpeW1njs8CgR00RKheNYPPzIIQJfcv3qKu22R34wyepymZnpVTbWqzz9/AkK\nwyk+eGeOTsen0/G4fGGBmWsmvi9ZnC+xslxmdCzDgT0lDwBdaHx55DyfG36MmL6dvpipLzPXWOP3\nD3+GxdYGf7/4KxZbm/zB1BcwhcGbpat95k0HRTPo9Hj7rxevgIAvjZzv8wC/F3jS5/XNK/zpjVfo\nBB5fHXuay9V5Pqzc/EjbvRM0XbB8c42Lr03j+wFOLEJptUy7uZtd91HxsQkCSsFblxZwXY+HT4xS\nqbeIORbpRIRvvfwuSilOHRnqfU3fujgPAlLx3bPol1+9zH//G8/gRO6+xVwIjYxVIMN2Z6MmdCL6\n9gx362ddhI1DABlriFthdN23dgaBQG0ZvEhqfpH1zk3iRpamX0YInYw5TNIcQCG5VvsVI84JbD3G\ncusqU4knuscoyFtpvjLyLHONFWp+v1qhQJC3Uzj63g9Ard1ho97g3cUVxjMpJrNpXrkyz0jqRUwa\nZKMOKSeCJixGEl8D4PLqMsvVGs8eOcRI4qsAjMS3B/y4dZy4dbxvP5KQinulNtf3etZK8Wz+IbKW\ng5INwAURKmKGv0NYaHYRIgVCZ6G5yp/O/iMPp4/xePYUw5E8tr7/bF4IwYCd5mRiohcEhp08Xxt9\ngbS1t3WpLwOaQQuFpOLVqPsNmkEL2VWHTJpxNKER73aKKxTfXnqFr499niPxvW0d94OpGX11LU2D\no4NZDuXSNF2PXDxMV8VH7R4F1vMDjG6NqN1ymb2xzuJ8kSNTMDaRQ9MElm3yzhszBFLym7/7dPh3\nnh/aKpo6TtRi6vgQg0MpvvM3bxGJGHzy06e5enkJz/Pvq7uVrZvYO5o9pVL8ZO19dKFxIjnGhcos\nh2IFfmfyRRJmlHdL1/n+8lu0gg7tICymj0Xz+wiQ9KMtPWYbawRK0vDbfGvuZ5xIjHE2M3XHv90P\nnvR5szjNf7rxfYpujd8+9CLn86e4dvlb97zNu8HEyVGOPnSIuctLDE0OYEdt5i7tr7t1r/jYBIFG\nq8PNxU0ySYeF1QoCWFgN2STHJgYpVpu8dXGeR0+No2mChbUyY4Np0nswBgIpsa17OzWlFPVGh4Wl\nEiePDRFIxfWZNY5MDvQ9IJ4XsLBU5HBXjvnm3AbxWIRcdpv3bQpjF+tFIrsJIUknqNMOavjSpRVU\niRkZmkElZCR56+jCoBGEkgGtoMZ6ZxZHTxI3MmE7e/Iwj2VP8uO1d/rSQuHgd6hPj2Unau0O5Vab\neic0b6+2O9Q7Li3XY6VaI2IYpJwIm40mjY6LJgQr1RqlRovlSig50fI8Cok4mej++eR20OGt0uU+\ndoyG4FhijLOZY6DqECyjghWE+RBoaQiuE1aaJdAE83EAbM1iubXJu6Wr/GrzAk/lHuSx7ElGnYF9\npbZTVpxHsyd5tzxNoCRfH3uBh9JH9z3eRtDkev0mWStNK2jhSpem36TolmkHHR5Kn6IddGgGYcOb\nrwJaQYuNThGFYqNTZCgyQNpM3XUaYsukx9R1HGt74DR2EAPsHamaaNTm0OE81XITw9BRSrEwVwwt\nDJfKnO1zytpi2IQppM2NGrqhYZoGC/NF6rU2b7x2nWQyiuPs7n6/X9joVHi/fIPD8SEKkUzYKcx2\niu+h9GH+8MTXcGXAzcYKFyuz/LvjX8W6Q3e1UoqZxgr/w3t/TM1vMh4d4KWhR4iLKOVSI2wqE2GF\nwbSMvr6S/eDLgPdKM/yXm69Q91r81sQLfGHkib7ek1bQYaVVvEUWfWcXeT95ea/3y+7eCga6EaYa\nDdNgdGqIheklUrnkLvn3+4GPTRAIpGRqIk8yFmFuucTYUKZnMH1maoiOF1Cpb3ebCsLGoY7r896V\nRR55YJwrN1cZyMQ5OpbnXpe2SsHiconLV1c4eWwIKSUfXFpkfDTTCwL1epu19Ro/e22aIJBk0jEu\nXlnm6OQAuR0WmXs1nG0ZZAh0EmaesreG7Mpnx4w0hchRFFD11mkFNZpBhYSZBxRVb41AesSNkMaX\ns1M8P3COq7V5FlshLc7RbZ4fOMvp1JF9H+aBRIyIaTBXKoeF6q7G0GQuw4lCvve5a+ubBIFkMh+K\nuWmaQNMEnh9waWUNS9f3DQJKKcpenbeKl/tej+g2nxg8R9KwUP4SqCrIIgTLIOywp0G2QhqrEKAq\nCJHD6s6cPRXwQeU6M/VFXi9e4HzuDJ8YOEt2j9qCIXQeyZxAHAlz9U9kH7htsTGQPu2gQ87KENUd\nNjpFhp0CrvRoBe2wI7UbwnWho6kwHal1rToNsZvQcCcopaiXmyilSGb72Sjtlku93MAwDVLZOGLH\n4CU0gWUZYb1MEyRTUVotj+///bs0Gh0+/cWHe9uvlJu8/uo1kimHXD6BEw2pyA8/cohyuYlh6jzw\n4BjR2D+tyfl75RmWWpt8fjgM7Lcy/EzN4HA87P7OWHG+t/wWa+3Srsa+WxEoybul66y0ixhC51OF\nc3xj7Dk2FmpseDWyuTgbGzViMZuh4VCJ+E64VJ3jj298j7rX5ncmP8UnBh8iZkT6gsDV2iJ/NPNd\nTHHvw+hKe28NqsALaFRbNGotWvU2tmNT2ayRHf7oZlm34mMTBOJRm3MnxzF0wZsX5hnMxdns8uQ3\nyw0Gs3FOHx3uRXGpoFIPH8xr8+scnchzY7FIu+PTdv1ubeHul7Z+EHBlehXT1Hj7vVkG8onul7Xb\n6KIUhhn6EJuGxvpGnZmbG7TbHpulOq++UefMyVGSSQejWzjciUDJHmVOoGFqNlE9j+lHuiY4Cl+6\n2HqMqJHClS2iekhBs7QoO3UKdKFxNn2MLw4/zV/O/4Bm0OHFwUf56uhzpPax2INwtql1u5rTToRc\nPErMsnY9Gm0/FKMbTiZYqdaRKIaScQKpMFZ3n9uteL98rU/DB2AyNsRjmVNdZpIfMpP0IRARlKyB\nbCO0FCpYBq3QXRGApfcLCTaCNu+Wp5lpLPFm8RKfG36Kx7Lb3afTtTWGIkk6geSZ/EPMN0qU3Bau\nrGNpOgkzQsK8tRFO0PAbLLSWaQcdNt0Ss40FlturbPU/RHWHqO50a0Mejh4ha4UPZs6+O459eb1G\nu9lhc6WMDBS5oRSBH5AbydBputTKDdYWitRKDR565gS5oZ3ifv15c6UUrZZLNGbjxCx+9P0PeeHT\np3Eci2jU4txjh2m3XTRNw/cCNtbDTvDNjdAH+annjhON/dM4VwHU/Rbvla7TkR6nUneum+TtJGkr\nxuubVxh1bu/n3ZYeP1p9FwUcig1yLjNFcbnBpYuLaEJj9sY6rutz7rHDt10FKBSoMAD80fXv0g48\n/mDqCzySndpT4mM8OsCXR58isY9g3kHw8/ULzHUdyXbCciwGJ/K4bZdkNo4Tj9BudGjVd/cHfVR8\nbIJA2CADjZZLrdnm9NEhBnMJbFPnrYvzJOMRdt4/XdMoZBNkUlHSySiTw1mu3lxjrJBmZCBJx/Ux\ndP1A2i470W771GotPvvSGV57YwYQeF5Ao9kJm5IErK5VKZYarKxV2SjWSSUcjk8NkU5H2dioE+ty\n17cKwzsROiYp2rJG2V1lszNPx8giCXBlk7K3yqhzkoSRo+4XUUhM4dAJVjCERdzI9hmRR40IXxx5\nhtOpI9T9JqeSk0T1yIHodR3fZ7law9A0Ss0makdSSRAOLHOlCrZhcG19k3KzTSoSqjiWmq3bPpi+\nCvjR6lt9C2JdaHx++OmwWKdqoMIeC6GPovxZhDGG0LOETCYboaWhO7O2NHNPGY+q1+Ct0hXmmquU\n3Bf53PB5yp0W05U1VlpVEkaEqtdmrlEkb8cpey1Go2kie9QTBBA1ogxFBmgGbYpuiRGngK98St1g\ndmt676MMmYlMFNM2KK1XSaQdnEQEJ2ojRFgYjERDltCpx4/0mZpD2Ey3ulxhbbVKLB7h0oVFKqUm\nL33+IVzX54ff+4CL7y/w6JNHiDgmZx4ep9P2EJro6z0ZGknjewH1egfLNjEMre++3o20+n5QSnGl\nusCHlVlOpyZD57E7XDhNaJzLTPHjtff4ZOEsmT0a+7a2/fP1D5ipL2NpBudzpzieHEOPaTTqHdZW\nKwgBwyMZOm2PIJB7eg1vycy/unmJb839jIwV5w9PfJ3xaH+6UbEdgLNWgofTRz5Sn8BeAQDCtJVp\nGUgZBhghBNGkgwzur24QfIyCAIQX5Z3LC5w9McbESJaL15eRCgrZBFPj+R7bRymFlJKVYpXF9bBu\ncPnmKlLB3EqJ6/MbFHIJnn/07otCV6+tkMvFuXBxkahjMTmR4+LlJV59/Tq5XJwnHjlMIhFhY7PG\n6HCadDpKYSCFpgkWl0pMTuR7s41wJbDbNUwiMYSFqVlE9Dh5e4KokWKzM0/MyBA3s7SCKgINDQNX\ntchYw0T1JK2gRlRPYevbPPeIbnEy2V+YDJTs5Vt3BgQ/CKh3XMpdyYyhZJzxTJpLq+tU2x1ubpYw\nNI2RVILhZILjg3lGUkkCpVivNTgzMoihhUY0qT008LfwQeU6NxrLfa8dT0zwaOZE95rEwTyHkhsQ\nzIGwQMRBxEBEEdoQaClEd6l9ayF1Jxzd4rmBh3l+4By+VLSlj6nrNPwOY9E0VS881023wYAdxxDh\ne1m7f2BVbBkNubiBi9dND3Wku2swdKVLK2jv23R2EOiGju/6tJsdogmHD385zcPPnUA3dOanV3Db\nHu1mBydmo93SFV0q1nnjteu89PkHuXxhkZWlkOEzd3ODIJDkB5O02x7lYoNI1OLmzHrf4L8TS4sl\nZmfW+fLXHyU30F80vweizi40gw5vF6eZb67xldHzRHX7QJOUx7PH+fbiq/xs7QO+NPrkntIaJbfO\ndxZ/RStwOZWa4LnBB3F0i0YrlOmIxW0y2TgykNiRvc2YlFJUvAavrLzDT9be5+H0EX7r0AskDOef\nbGV0UOxkOAohuEvC44HwsQoCm+UG1Uabx09PEHMs6s0O71xe5MufOEM8uj3g1Fsu8ZjN6SPDvHt5\ngU+fP4EfSKIRi2q9zchgismR7F2vAnw/IJV0GBlO8/0fXuDUiWGSSYd43ObJx49wc3aDjuuF3Xy2\nyeBAkljUpjCYpFZvs7JW5bFzk73tGXusBHwle3UBEEzFn+gN6AlzgNn6DSJajmYgSZsF2oHLzcYc\n47EBav5m6KF8hwfIkz4XKjN0pMfZ9DEs3ez9jRdI1usNmm7oMdD2fJLd2X3T9ZnZKBIxDAqJOCcK\n27lYpbbFyCKmyQPD+0sOe9LnF+vv75K2OBQt9PLnW563Qi+AXrjjkGAKY0+WiCkMXiw8xm+Ov0Ta\niuPJIBQGc1s8mB7B1HRGnDS+DEKJDyWRSu65vA/NciT1IExDZu00Vb9O02/tEsPoBC5XazN39H++\nHWQgqVebJDNx7IjJwFgGK2KGwnkInFgE0zJYvrFBtuAxOL4tAZEfTPKVbzyG41icf+Y412+sMH1p\nmRvLayhXgQ+FgTRHjhUgpjh6rLDvIHjy9Oj+x6j2cn84OFRXDuJXm5dJmlGOxIcP7JObMmMcT47x\n6uZFHs+dYNjpl8DwZcBP1t9ntrmGo1s8lTvFVCLsCG42wyAgA0mz0SHwAwYLyT3TQeudCt9Z+hWL\nzQ2+Nv4MT+ZOfmRq6f+X8LEJAs22y9xKianxPHHH4srNNXRd56HjI1ycWaFSa3F6aohsKsbKeoV8\nOk4uHSOQimKliWOb3Fwq0my5DOWTNFou0Yh1ICZAD0JwZHKAcqXJxFiOY0e2B6dEzOaJRw8TBJJL\nV1dwXZ/LV5f56hfPkUxEWFwKCzw7l9PmPisBpRSW7pDX+3OjQiWoeXkWmxU6gc/R5CDFThlLHKbc\nMZiIZUhZt88/+jLg/fI1/nT2H6l6DX730Gf7NPQjpsFYOsXl1XUc0+T0yCBT+RwRw+C9xRXG0kke\nGh3qFeW3EBZFD+aHMNdc4VLt5q5Z8jvlaSJzL/OpwuNMxUf3nNntB11oew5gR+Ij/PrYCz1zc6UU\nWTtG1oriyYCG75JyHA7Fc+hCY6NdJ2U5xM3dQSBqOJxOHidjpTB3NJMljTgd6fYdb9yIMWjnGYrc\nm/4+QKvZQTd08sNpblxcJFNIYpgG1WKDeMrBidlEYjbXPpjHc/2+ICCE6Pnt6oZGbNTi8fGjpGoW\naStGVHcYjw5iCI2VdpGabDEh7v5YP4pqsVKKqtfku0tvcKOxwrnMFDk7eeDZtaWbnM+e4n+b/jte\n37zMF0ae6PNhuNFY4cer71H3WkwlRvnU0LlegMkPJIjFbUqbEeKJCK7n91zpdL1//zW/ha1Z/M7k\ni0zECne0yvznho9FEJBS0WyHSppKwdXZdWKOxaMPjBONmNxYLHLx+gpzKyU+/9wDgGBiKI1jm+i6\noFxrcWxigIFsnLnlEm9dnGdiOMOjD4zfVXHY0EO9numZNY5PFcikY/hB0F0Sh52guq5xaCxLq+0x\nO7dBPpegWKyjgFjUYubmBg8+MNqTk741j73lpbwzr7+FqtditVVlxElh6TrtrqFF1DCR3Vnq7RAo\nycXqDf7k5neZrs8TKMmfz72Mo0d4Kn+m+xnF9Y0iTc/jxeNHGEmFs6PhVIKVao0Pl1YpJOOMpPrz\nnIamETXNOz4gUineKl1hZQ/T7tV2ke8s/5LL1VmeyT/Ei4VHydsHYzsIIfbc94CdJmVu54st3UAp\nxbncBIGSWJpORDe7g74gqluhlvweA5GjR/bsrUiYceJKUvM3sLVo2NgndCZio/jSpeQukrFGqXkb\n2Hqs19R3J1i2SX44gxBw6OQITsxGNzQyg0nyI5neBObUo0fw3P07VFtBh5rfJGMlCJREE6FnxFb6\nzBA6rxYvhJz7uxzgDloTkEpxo7HMu6XroayGEUEXGq9tXuaHq+8SKMlUfISsFcf3A4orFaKJSJju\nEBCJ2viuT2m9GsolJxw0TTCVGOFQbJAfrr7LmdQkR7sz/brf4ier73OluoAudL4w/HhPjA5CKuzG\neg1d11hZKZPNxfF9uWcj2qiT4ytj54kfsMB7/7PyB4OUYRp8r5rGR8HHIggIAelElHTcQSqFH0hs\n0+jlME8dKXBoOIPr+SSjNgnHRtND7vOLT4RuVE7EJCkiZBIOU+N5DEPr41gfBK7ns7Rc5sTUEKmk\nEzIUpSKVdHoPpBCCgXyCq9dWMUydYqmO6wWcPjHMyWNDvP7WDJvFNPlcHFMY6HsMNp4MejIDO5G1\nY4xF0wgRGsabmoYb+MRMm0DJ264CpJJcqtzgP05/i7nmau/hnW+u8cc3/h5XejydfxBD6BzJZ9GE\n6BnKQMgYemR8lBOFARxzd9H01NAAUqo+rvpeWGit8W7pKo09VE7Dc/e5XJtltrnCLzbe53PDT/GJ\nrvT1nWaIxgGpeEIIcvbe7KhI1y9WKQl0CCuU++9bKQ/lvkFLjFB0izh6gqq/RqB8xpwzSHxWWldp\nBVXaQQ1Pthl2TpA0C3tubyfMHb0smcHknq8DRBO3T01YwkShqHoNGn4bx7MIpCRnpXB0i8XWBofj\nw9xorHAkNnxXee79pRv6vQoEEDecLiHgPeabazT9MDi50sfRLSZig0T1CLVSgxuXFskPp0mko7Qa\nHVK5ONfeX0BKief6jE8VGD1aIG+n+GThLP/Htb/n20uv8XuHP0NSA2CLAAAgAElEQVTCcHhj8yrf\nX3mLtnR5Jn+aFwoP953X+lqV6cvLlIoNqtUWhw4PcGgyTy7fX2Bu+p1e/azu9RseKUIa65a/yPZp\nh+e91inz6sbFAwePvTBd69fUUkrxix9d4ulPnKRWayMDSSYXHvPqUokL787x0pf2Fwa8F3xMgoDA\n2LFEs24ZgzQhujWB3Uv4nbUCAMPQSe0jOXsnWKbB5EgeIbYbWExT54VnT/SllYQQHDtaYOrI4K50\n0wvPntwuDGu700EAvvL3nE1EdIPDiTxxwyLU9w9TIIGSODvy+ru3F3ClOsv/Mv0tZneYzkA4k5tt\nrvCfbn6HjnR5fuAsUWvvgq6hhwXfvWAfQF1yKxV1uTp3x8+2gg7XG4t8d/mXTMVHmYrf2dHqbmex\n+0JJlH8d2f42aEPo0d9ESReQCK1/kFDeJfza/4wX/bc0gi19IB1Ls6j6awgEnmzT8IogwBQRLO2j\nm350Ag+FJHIg97FQlNDUDUajOZJmjFhX4K7k1nF0i5yd4np9CUe3GLQzB65lSLn/6vPWVNGgneYb\n48/zpZHzvFO6xp/eeIWiG1JR02asx/Bp1Nq4bZ/FmXVyQykyA0k8N0DTBUs3Nxk5PIBSYT7fMHUe\nTh/hkcwU31t+k1Enz/HEGP919oesdcoMRTL8i0MvkDT7r3nEsTAtncJwipGxsD7oecGuQvfrm9Ms\nNos9uer+8wvVZh/PTXF6B611axNLzU2+t/wmxgGsQvfDXvLqxY0wszB/Y51Ox+PR3FTvnAb/OfcJ\n7MSWe8+V2tx9Mfe4FdO1Bdpdk4/ePlFcqy/c0Rf1bjDXWN3TSWu6tkDccA4+qHUvwexuZ0Yg1MD/\n9tLPmbslAOzEUmuDP599GaUULww+elvJhS3crWjbWqfEm8VLNIL+A71VRA8gbkR5PHuKr40+z5H4\n6IH2IcStlhz3BiXXCRr/N9J9EyP2e6CayPb3QSTQnc/271PPI4xDmFqCQG4QaB62HsWTHTLmKAEe\n8433urLnAscwaPplIvrelMaDoBO4vF68iKWZPJk7vednZNerwNJMAiW7A36NhBEN5ZQNia2bNIM2\nR+Oj6EKjZjdZbZVIm4kDBwF/nyAQrgN2rAS6909HEDMiPDtwBk/6/E+XvxWuToxIrxjfqDTxPZ9E\nOko0HsFzPVL5OPFUlHjKCesh8VAuQwhBIZLhU4VzXKku8F9uvsLh+DDTtUWSRpSvjT/LVHxkN3NM\nQSYTo1ZrUxhK0Wq5DAwmdjGkXiicwQ08rtaW+1btQmiMOVmu1Vf6UrpqxwrobObofZGS3jLe2bqO\nR08M4XZ88oNJ/EASBOE9EJogEr3/DX0fyyAA0JEur21+yOubF+97IHClT9Pfna743spr/Hjtrfu2\nH08Fe3rq/mD1TX6+8d59k+vqSI+m375j/napvcGfz72CpZt8YuDcvkGoVGmyXqpjGTqtjoemCQq5\n5J5qp1vwZcDV2hwf7hC004XGUCRH3W9R8eq9101hcD53mn81+TkKdvbAQeYgGjLbUKhgDRUsIMwH\nEF2HOqUCpPs6yr+OHvt9NOcboBpI902EMblrK0IfQTPPIUQMW29haBF86WIKm45sYOtRYkYWU3OI\n6in+X+7eLMiuKzvT+/aZz7nzkPMAIDERBAiS4ADOZA0qUjWrpepWSba61dEKy2G/OPxgR9jhB7/Y\nbw5H2BH2S4cthbpLQ5fUrapSqSYOxbFIggNAAgQxI+fMm3nne8a9/XBuJjKRmUCCRDsY/VdUBJGZ\n99xzzz1nr73W+tf/RyrA0bfXJtrhLNP32TCMOO+v8O+mf8XJyrFtg0AoI95YPs27q+coW3merN7P\n3swIkYyZ91dxdTul1KIx6lbXeyl7MsNMZtQdXcdEqW1pokqx7ny3E44V9mFpJh18HM3E7jfb3azD\n3ntG6XV85q/VcDyLfDlLJu9y+MReZJKWhDZuQh4o7efx6hH+w8ybvL96EVMzeHLgKM8NHt/ed0CA\nl0lVRJVKVXtN09iWMRgryVLQuNF0VqnWr1QSWzMZcDYv8rfbhDRX2wjPxJcRsZI4uoGjm7SjsM+2\nUpRsD2uHQNxu+vzix+8TBDFSSor9GRG/F5LJOhw6MnqbM7gzfCGDgBCCslXgheHHqAUNfrPy8W2b\noncD7bhHmx2223cRnaS3Zbf8/xfm/DQjcDR7vVl8M0xTJ5dx6HQDsp5NFCfEya0DcSfp8crSe5vE\n7Ipmjm+OPMHfz722KQhYmsG+zAjDTiq+l6hk3ZsZIJIRzai5bh2aN9cewrXJ7dvnAkr5JL2/Rfq/\nRM/8EZrz1TQQyBoy+gDNeQ7d/Q5C81DKRLOfhG1MelJoaMIgY1RAKWyjiJ+0CGSbnFFlInM/vaSJ\nKWxMzb2jILAatpj3a9yb37f+s5zpcTA3sb5obkQkY3618DZ/ff1XtOMuXxs+Sc70MDUjlV3IDNPx\nQ8IwwbGtTc30myffFTekG4I4Xp8k34i0HLTd9d4NUSFZf+3a+QEMjqeBv1XvUB4sYDkmmbxLoZwl\nipLUN3ot7eujl0S046BvypRuCEpWdpNC6UaUShnyeZduJ8CyUtXcnRqqjm5yKDdKLWxRNDMpkcBw\nme+t8l79MkNhkacGbgSCjZutJE44d/oSe4+MEccJ2YLHpTPXse8p4ToWmhAESUyoJzRCn4Vui4qb\noWxv9bOYnV5hultD1zX2HhiivtJBJpLKYHo/ddvBZ1JYvR2+kEEA0l3kVHaMf773G+hC5/36eRzN\nZk9miBG3ypBdpmTlKJhZvP7ORxe7mxD+qHGZv7n+IgvByqaf//G+b/BI+cgOr/ps+PMrP+Wt2keb\n3JUOZMf5F/u+cYPVohSJVCiZSlIoueEBTUd32dUH2yU0BOUdUthm2+fS9WW6vZB6s0cu6+C5JpXi\nznVupRTnW9d5Z4NOkIbg+eGTHM7v4e/nXtv8gv5ipJQiVjGvLb/GI+VHaMdtimYRQzOIVMRrS69x\nMHuQ48XPYqJhIfT9KPVDkvb/iYovo3t/kE4mI9Dd30No+f7pmAhtKBW02+lomsOQM5nuKoVOrEJ0\nYaAJg5xRxdNTFVSN7ZlH26GXBPzd9EskSq4HASEEJTPH45X7tmSRkYx5aekUfzvzMoNOif9q4nsc\nzI6TNTaYoHcDlusdao0OhazL1FgFQ9fS+raU6xlHIwj4+aULfP/YcaRS/PtPzvH4+ATj+c0UzmiH\nRUeqnUtFa7jSWSCS6ebB0FLPbSHEeuO7NLD1HrQ3lGuUSnfj091l/uray7yy+CEAedOjG/v8w9zb\nBDLidyeeZsgpbWGP6bp2W8McheLXSx8j+kElkDEvLX7EUwP3YOkGsUwomdktr9kITRM0ai26zV5a\n0iplqMchPT+mG0eMZwrkLYfZbgND12mFAZ04omhtDkrNepdfvfkB8zOrfOf3H2Pq4BBxLBmbLGMY\nOs1Gl4WZOkqqTTpSnxdf2CAAaSDYkxnmv9j/XVbCJkNOGUe30NDWjaLX/reG3TyAK2FrE98Y+hZu\ndpn9/QZlL4xSpyelcEwDy9isKZ9ISS+MMHWdME6tIUWfcbPx74acMrrQkBtKWkIIJr0hqmY6st9o\ndFleahFFCYfuG2V1tUO3E5LPu1hW6jJWHdj97vLzIJuxObR3kJ4fUW91ybg2SSJvOTkayIifzL5O\nsEEt9HB+D18feZxauLMJRi/p8V79PSSSbtLl1eVXsTSLI/kjRDLCT3z2ZvZ+ps8h0BDGKLr3nyG0\nMkn3L1HxBYR5DM15HrRhbm4EKllDRlstJZVcRENhajd2nQYba7MCQ9x5rVYpRSC39oyEEJjCRBc3\nrmcsE06tnuPFhXd4sno/Xx95grKV31TSUwpmlxosrbYxDJ2FlRalnEu1mGGu1ebNmes4Rjp53QwC\nVvw0yMw0m3ywOMfDo1vLDLHcPgNUqNsGgTONK+sKsobQ+w5su0coYz5qXOHPr/yCM/UrZA2Xb4yd\n5LnB4/zbqy/y9sp5/v30G3zcuMrvT36J46V95M3MHfH8W1EPqWDULdKMepStLCdKU/xo5l0c3eR4\ncS/3FG4M020gBwHQrLXpdQJM2yQMIpZnV+m1fHLDBUqZDO0o6EsOKlaCHiNujgSFuc3o78Ejozx0\n8iDvv32Zi5/MEUcJh4+N01jtommCTtun1ezRbvt31Q3uCx0EIN0ND/ZlZ7eDUoowStB1gaHfiKxS\nKpYabTQhGCjeeZPu4nyNpUaHThBybHKYPQM3uvIdP2Sl3eWjawtU8h7XluoM5DNkHZtKzmOsUlin\np643gDcEgW7sI5UkCGIW5utcubREdSDH+ESaJjdWuywvt5idXmFwqMDc7CoDg7c3QtktwiTG3KEe\nqQlB1w+Zma9j2ybXZlfwXIv8LWiKZ5uXOd24uP7vqlXgn058hbKdv2UQWAlXGLAHiFWMp3s8M/AM\n51vn+cXCL/ATn++OfXdDKegO0c82hMiiu99EM+8nbv9fyOBXaNbDpKWfzddA+j9Fdf9yy6GUXEZz\nnr+LlispXMPm+eHH+bBx4ZZ/J5XiWneed1fP8bXhkzxWuQ9nG2MdIWCglMU0dKI4wXVM4iQdkIJ0\n1qMZBORtm0bgM57L0wx8Xp++xrN79jGW2zrIFSfbTwwrpYiSnYNAoiQXW7PrmYAmtDtid9WCJq8t\nf8QPrr5ELWhyT36Sb46d5JnB4zi6yX958FtUr73Crxbe52zzOv/r2R/w1MAxnqwe5VB+nEG7uKvm\n97nmDK2ox/t+g3bc40pnEQHsywyigMP5sZuCilovSQFc/PAarUtNvJyXNrtLSzRqLZ47+jimYZA1\nLTQElq7z1PA+pJLpQJu4cR3XoOsajmuRL3qcODnFuTMzvPnKJ3gZm2ze6f+NzuBq9z/9ILCW1jpW\nOiuw0uzSC9IdhQJWW10qeY/xgSJKwfxKi/nVFvdNDePZ6cORSMnZqwsYmn5HQWCx0SaME5abHWIp\nCaOYWiuVEYiThH1DZT6+voBrmwwWs9iGwXAxRzHjYFsG716cYaiYXQ8CmW1YQL3EJ1GSJE7QdR1d\n14nChPm5eirBXO9y8dMFRsdKFEsey8utu3BVb+Cl+fO0Ih9D03F1k4xpU7Q8JrwSecuhWspSLWWp\nN3vsHSunmjo7PPDd2Ofn82+vS0TYmsmXhh7iWGHqtq5hkYpY8BeohTUaUWM9q3ug+AACQa9v6HI3\nqKHCmMDI/Tck3T8n6f4APeMizHvYmA0I6yE0fas5jAxeBXH3WGPr74fA0Ay8Heraa+glPmdbV3is\ncoz7CwfRb7G4rd13uq5h6Pr65Ldl6ByupDLhFc/j05UasZR8vLTEcDbHA0PD29KA4x3q/lKp9QV+\nO4QyohX31ksnepqb3fJzpp814GzjOi8uvs/LCx/iGjbfGX+Crw4/yFRmZH1hH3Ur/OHerzDklPi7\n6deZ91f4+fwp3lk5z9HCXu4r7OVQfpy9mSEKZmbHe+hgbmR9wW9GXSp2npKVQSrFnL/KXG+Foumt\nB8eUG3TjmjieTenwKIcfnsLvBAyMl5m9tEjWddZ9ntcmp13Dwt0QvJVSLAZbfcKFSDexh4+OYRg6\n01eXOXhkFNezUEqRvcue0F/IIABQa3Y4c3mB5x85lJZegoiVVpe85+AH8frNIITAtU2UVMzXWkSx\n7GvkS6aXmoBi9fUujx/dSyXv3bZclEo66Jh6avwN6SCVbRoYukYiJZahM1LK0+immjKebdIJQkoZ\nj4f2j2FuaEBlDXdLetpLUpaA0ATFokc2a5PNOQwM5kgSRRJLhocLeH01UlS6CN9Mb+vGPovBKmUr\nv4UnfSv4MqZkZ1LvriRmsdfiYmuJl+Y+4ZnyQYyWTrsbpBlA1sEwdDrdgAPbGFp8UL/Amcal9Sbh\nkfxevjz4EDljZyP3NXi6R9EqEsqQnJFj3p8nb+apWBXKVpmVcIVaWGPA/rxGGqlOk9Aq6N4fkfT+\nCun/BKGVU+2iPjTjIJr9Fbh5wZANBLso96gY0La+/nPCEDr35vayJzNyy4AohKCQdTF0DT+MyWWc\ndWYMwAcL85xdXsQzLWq9Ln4cowuNwUyG9+ZnGc7m+L0jRzE2lCriHYK/VIrwFmQBXeibshVxm0wg\nUZILrRleXPiA39TOMe+vcqJ8kN8eeYRjhb3bSqNX7TzfHnuMEbfMv73yIuda11kN27y6dIZ3Vz5l\nxC0z4pQZcAoMOyVKVo6SleOe/AR5M70/12YXpJL9Cf/0WmlCMGDlsEXqJ7xGqU77FDd2707WJpgN\nuHzmOqNTQ6xtKtKGeroOxCrh76ZfY7pXo2hmyJsejm7Riru81jeuN/s9E4DR8TK6rmFaBkeOj1Md\nzGHaBsVSZtf9pjvBFzYIlHMeo5U8jY7PtYU6UireOXedkUqeajHDtcVVchmbjGNRyrkc3z9CECV0\negFe31by6sIqmhAc3TdM9hbG7RuhFKx0ujR7/nrJpN5Ja6dCCEZLee4ZTzVYfvLuWQ6ODKBQXJqv\n4ZgG+4crm46XM7wtN7+fhEQqwfMskkRhmjqeZ1EoZkgSSbHkYTsG+byHZRn0eiEz11eY3HvD8CWV\noV3g/73yE44XDvCN0SfIGbcPcgCTmRL3lcZSiYflq8x0Ax6r7uNXc5/w6/kLPJc5hGnq9PyQ2cUG\npqGzf7K65TirYYtfL73PcpgOvAw7FX575AkmveFdnceQM8SQM8Ql/RJVu0qkonQIK2ryZu1Nvj7y\n9U0aPp8NEUpFiH7NXmhldPf3SLp/hgzfQnNeWP+dUh0UAYKddloKFU+DaiLMo6hkHrSBdTE8GfwM\nYRxFGHdmNbkTVJ+BY2gGk5nhvsrp1kW5X/hK/1uIdNBKKqyb2DCThQJ526bouFxr1LnebNAIfJ6e\n3EPJcXFNcws76FZzArcKAqbQeWHkYS6351kN26kp0UaJ6r7XdiwlV7sL/Gz+Xd6pnacZdZjKjvL9\nvV/mntwEmrTohpLLq3MMeBkGvAyfrtSoeh7tMO2nPFQ8zMg9Zf5+5k1eXvyAVuzTSwIutee41J5D\nFxoZw6FkZnmwdIAJb2A9CNz4nAkaguwGjwlTMyjb2S3lsI0Fsv3HJ3EOGXRbPlZ/jckWvE2EKl3o\nPDN4nFMrn/Lq8hkut+dJlCJS8foc0aBTZMguEUcJ+aK3Tm0FGBgukMQSKRVJkqRmQncRX8ggkIo8\naewfq7BUb1NrdrlncjCVlB6vgoKF1TZxIqm3fc5eXWCl2eXY1DCzy03yGYfDEwNk+gJyE4O7m7JT\nSuFYBkNmlmbXp+0HIAQDhSwjpVzK4CGVTnj70+t4tkWz67PYaDNeLfDh1XmGizkyG7yN82Z2Syag\nULSiLkIIOp0eQhdkcw6aJlAIchUP6oLqcA7XsRgeKd7ICvrwk3SO4v3V85xtXiFSEd8Ze2aTjs5G\nJEqCukEJVAo+bS7yTu0aTw7uZyJT4khxhBG9QH22R73VpVTwyGZsijmX4ZuYHIlKeGflHO/Vz/cn\nmm2+OvQwT1SP3bGyZqximlETS7MYdUbRhIZEkjWyu5aK2B4aSoWgOiAslErLakKrorv/lKT3V5A8\niNLHQbiA0zexUf2UX61LWYPs1wLqKLmM4CjK/0eE+7upBDaAKN3VstH51lVWwq3lgpthayYT3jD7\nMiPYWnrPGzdJTysFjmFQdl3Krkcz8BnMZDA0jYVOh3sqA5TdrdLJsdxeb0cqRRgn22pgQRqMnh08\nzoQ3yMuLHzLslsgaLomSdGOf1bDNueZ13lj+mKvdRXShcaJ0gGcG72NfdgRPt9GFRpgkLHY75G2b\niutxtVHnw6V58pZNwXbwTJPhTJaDuTH+9OA3eWbwPv5+5k0+bl6jHraJVULWcPnK0IN8Y/RRhpzS\ntnMFi0GTy+0Fnh68d9NnuHlKfy0wm0InYzgIJWg3utiuBUrRbfXIV7KbrokmBHszQ4x7VZ4bup+3\nVz7hb679mkvteQSCca/KV4ceZNSr8Ksff8ijTx2iUPRoNXpIqSiWM+iGxsz1Gmfeu8YL3zlx23vi\nTvCFDAKdIOTc1UXmak0GS1la3YC5WpN622ep3kFKSRClu5B8xmasmqfW7CCl4ti+Yf6PH77Gf/vP\nnr3j942StBeQSMVqu4eupdG41uqQSEnXDzkyMUTOtTk7vch3Tx5lsdFG0wRP3rOXv3rtw5SGt+EG\nKJiZbWvjzbiDQlEsZij26ZeKlLp3KWgwMpCjLgMMpXP4yGa9F6UUM/4Sv1p4B4milwT84NovEGj8\nzviz22qZzHTqXGwt4xomV9s1HN2kGfo8P3YvB/ODJEpyuDBESfdQrRqFvENttUM2Y1Nv9mi1fcrr\n56mY763w66X3Wek3fu8vHuR3xp/F+gw790hGnGqdSmuk/uJ6Sagdt8kZuc8cCIQ2iGY9jhB5lOyS\ntP9v0Iro3vcQxgSa/TQy/ghNH0UYe1JTGy2TrpiyhpIr/b4B/QCiQBtEYKXZhXkfCGO96S+0HOym\nbLRLXOnM8dGG4bvtEKuERX+FWCX8y33f5itDqXXjzYuXEHC1UWem1cLRDRqBz6CX4fvHjvPu3Cxn\na0s8MjK2pS9wKwZQKBMiKbH07YO+qRkczo9zOJ8y7pb8Bpc7c3zSnOZ8a4ZIRox7Azw7eJz7S/sp\nmlvLHRJFNwopuR6OYdAMAmKZlnzrfo+8bWPpKXMvYzg8UjnM/aX9nK5f4qWFD7nSmefRyj387sRT\neNvIQydKoiHIGQ5jXmXL72+GQDBgFzhW2Ms3x07SvNpk7uIileEivU5AeahAtrCVZZUyvgwqdp7n\nRx4ma7j8P5d+Rs50+SfjT/HkwFE0oeF6N5SPL19YIPAjHn3qUMo8dCzK1c8+ib4TvpBBIOtYTAwW\nWVhtowkNy9TJeTaubZJ1LRKpSPqNSF3TcG0Lva+amM84PHho7DNJC1iGwWSlhKlrBFHMYqONACar\nRSYHNrOTcq6NtpZ6K8XcaqvPId98E+9EWWuGHdphuH6eUipiJan7Pt0oQhOCxU4HXWg4WXPTI50o\nycuL77EQrG762d/NvIyjWzw/fHJLjyBRkrleg1DGzHUb+ElaDw5VQsXOUrJcht08nW5AGMVIBd1e\niGOb5LPOptpwJGPeq59fZwQNOxW+N/Gldb76neJg7iD7s/v755kQqYhW1KIZN9NhMe2zMYSEXu47\nlQEqQMlFZPAiqBaa+zto5on030hUMguqh7D637PqoqL3wTgEwgEV0LedQcXnIP4EkhlIZlBrj1Ey\njXCeB8pbT+Yz4Mnq/Rwv3NoYKZAhP5p9lZ/Mvcap1XM8PfAAmthqpl6wHR4bmySREiGgF0dcrdeJ\npeTEyCin5mapBz6D+uaF+FbN31hKwiTZMQjcjEbUYd5fZcyr8mjlMKNuhewtjFtUf34mUWr9/rd0\njZxlkbPT3Xyits7JtxbbHMlOMlGq4k/EOJpFWI/wkyD9276fs2kZnKlfYyVs0Y1D2rHPtc7Sjffv\nizweyI0w3g8QRSvLH+79MgeyY+RMl9NnPsGyTQbHK1w8cx03uzXQrHZ76+cYxjHD+Rxj5jDfG3+O\nglbg4eq+9ZJxZSC/PtQ2NFIkjm88d7ZjUql+RrbcLfCFDAKapuFYxtpsIwLQNYEm0kUfJW9pT/f0\n8X18Or3E7HKTyaE7E1xaq6PqmsDQNTzH2taR6ZGDE+k5ir7Msm1y8vAk7k3qdxnD2Xbysxl3UpNw\ntVbLBU2lyqi2oa833rxt6rTTvUVeXfpgyzHbcY8fTr8EwAvDj5HbUPfcl6sykSlzrbPCTLfOqFdg\ntttgrtvgQnORr4wcZjJTJuPZ3LN/GE0IepNVDL2vxrpeRlIsBw1+Nv8W3cTH1W2+Pfo0h3K3943d\nCWt1/42714JRoJt0P0dPQKFkE2QbYYwhtCJG9r8mCV5DBr9Cxdch888R1kOADqqNSpZQKuz3CHSU\n7KSlH+shhMhAfJ608ZsBYYKsgfDSbABAOnw+w8nNyBoew24lbUaiduS/DzlljuT38dzgCQwM2n6Y\nDohJRb3do5BxsHSd4eyNXWQiJQXb6XtNaxwZGNiW8hnLnU1l0kV695P8B3Kj66Yvu0WQxPhxTKav\nbFtyXY7og0gUjm7gGsamRjbAzKVFTMtkeXaVqWPjeBWLmeuLxGGClBJNu2HY4+qpnEWsSUxNx9ow\nP6RIzU03Xve86fFg6UZgdj2HTqOHbmgkUcIn71ziwgdXsSyTh76aTuRfrzfohlFfHViSdx2CQFFJ\nhmh1Az4Ry9w7PLh+5ywtNjFNndpSC5lI9H5pr9v26XY2a57dDXwhg4Dq65XEiVx3DBss5ShmXSoF\nDz+IafXt41K+ckKz4xMlaY0y9RlIdcrHBgq3ebftsXewzGi5gEKRsbem+OOV9Lij5TzlnEc561HN\nb2Uw6ELflinTjDq4hrFpaG2NyVH3fSxdZ9BLqWpyQ4YhleRnc2+xFGxVHwRYCZv8cPolNAQvjDxG\nxnDXj32qdo2LrSXGM0X2ZitMZas0I5/LrWV+MXuOb0zcx5CTW2c33azQCmlG8erSB1xoT6MheHbg\nQZ4dfBDzM5ZsLrQvECQBR/JHaMUtYhWjC52rnatc6V7h26Pf/kzHVcon6f41Kv4EI/MnYBwAfRLd\nG0YYo8juD4lb/xtG9k8R1sl0MZc1kMugj4KWBaEho4/Q7OeACBX8Iyr6KC0dub8HIg/GFEJL7wWl\nfZwe5y5PeAcy5JcLb/PVoUextM3uYIlKsDSTrww9wkOle7l0fYW5pQaeY5HL2DQ6PicOj6Pr2qba\nviYEFffGpHHWtJDG1uV+u3KQJgQPj47xR/c/gLeN7PjdRM6y2V8q4/YlwIcyWZSXBrG17H/jJqnb\n6hEFMc2Vfgm35ZPJuyip0sU03jxteyg/xiGgEXaoBS32ZYc2NWVvR3Dw8i7ZXtrc9bIO3mgJw9S5\ncnYGAD+K6YQhK90enpmK/V1dqbPc7lB0HWrdJO09brhnPincMB4AACAASURBVHznMkkiiaIElOLy\nhQUAAj+iVMly391tCXwxg0CrG/CrU59SyrlcnlvBtU3avYBKPkOzE/DKB5coZB2iOKHe9nnpvYtk\nHItPp5eJEslQKUs1n+Gp+/ZhGjrLjQ75jIOpb+9OtR0yjsVuSJeeba3PJuyEil3YonhTC5tbdlhC\nCBzDoGinKaVjGJt2Wkop3l09xxsrZ4jUVpMRR7PImxkO5iYYcSubWEmxkox6Bfblqkx3Vgllgqub\nFCyX4+VxBt08by9f5dnhg+TNnXnr13sL/GjuNZSCh8tH+M7YM5St3btF3QxNaDi6Qzfpshws0026\nHMkfYW9mL3P+3O0PsBNUBHIeFZ0mavx3aO7voDtfB62C0Peg2U+BsEl6f4umOmjGQWSygIqvgDYC\nIocQGVT0HliPgXAQzncQ5glU/DGy90OEPolQoyjZv87KB1VDUURwZ83xnRqsAK/XTvPX13/JudZV\nvjv2LJPeMIZI6+CRjJnwhqhYhVQ6RRMITWBbBgPFbDpf07/RPlpa5JVrV5A3vVeYJAjgD4/dT9Xb\nvGGJNjCAbF1nNJfj+/cd59uH76Hselt24XcKpRIU0eYxXEARo1CYWg7L3sjY6V/XHUpQlmuRLXpY\njsHi9CqZvINlp0ZDcZgQBhH6BtZUoiRBEqXPihAEMh2kPFO/xpBToGrnb0l0WF1ssDy7wvCeCrql\nUxrMUxzIM7wnZdMZmpYSWLo+g4NZEinJ2Ra1TpdYSvK2TawkC602w/lUFeCJ5+7Bsow0LmwIWJ2W\nz+rKztImnxVfmCCgUMRJDSFM/KjG/QeGOTg+RLPj8+75aX70xm9o9xL8QNDxV6k1A+ZXdCr5fQwV\ns5y8ZwI/jHnj9BVeP32Fbi+g3Q0J4xhDaPzhCw+zd2T7qeO7gUjGNKI2OcPbslurWkVuFj5bCRvb\nsi5cw+RAefsGVS1s8NO5N5nbxrVr0hvit4Ye4cmB+xl1q1sag6amM55JP3/cN9FYgyYEI26exwf2\nca29wrHS9il7Nw74d9dfZCVocjA3zvcmvsxU9vMpGurolOwS55rn2J/dj53YBElAohLk5xANFFoe\nI/8/oJIFpP9zEv+XqXKo932E8JDJEprzDIb1KEnnz5ByBSWXkOFb6Ob9aYNYG0QFL6OSC2jmMRBZ\nlCojzAfQtEFk74fI6C8RWrnfII5BLyP0SW6eRr4VYhUTq2THbGpfZpTHq/fx3uon/O/nf8C3Rp/m\niepxPN3B1iyOFw+sj2LlMy5hlNALIi5OL1MuZNaZQjnL5oX9BxnPb86OP12pUXQcKp63JYMJpUQX\nGuPFPF/eN8X3jx1nX6m0Vbr5M0ApSZjM4EefolSMJEDKLoZeJkqWUNKn4D2PbYwjpU+iOuwoZieb\n6FoO0xjEdizypQz15XbKwGv5DE9WEZpgdbFJt+2vl1hmujWudpY5VpykFrToxgECgZ+E/ODqq3xr\n7BH254Z3/AyHTuxDN3SmP51ndGoIvS8vY/ez6E4YYuoaecdGKkkkE2zDYLSQo+g4NPwAQ9PWAwCA\n69nEccKVi4vYzo1Ma80r+W7jixMEpE8reB1DlFDaWSaHXiCIr+E6Dl968ABPHDNJVBdTH8SPPiFK\nFjH1Lp7pQjDAmfevUxnIMWjYfPVLh1J7ucUmYRjTaPTI3eW0dc2UfMFfYaa3xLXuAhfbMzxRPcZT\n1fs3/W3Zzm/JBFbD1m2lnzcilBFv1M5wpnFpy+tKZo4/mPwaTw88sCt65rCzWYcolgmBjMkYFhOZ\n7QOlVJJ3Vj7mvdXz5M0M3x17hmOFqV2f/3YIkoDFIGUD5cz0nJaCJRb8hX6Z4/MybQRCH0bP/Odo\nzldJej9G9v4aYd6HSq6g4j0I5wh65l8g/R+j4suo6AM05xsgDiK0Cko2UeF7KOMQQqQWlZCAcBHO\n1yF8HYSHMNbqxIo7eawEqUaOnwRb9KzWsC8zyr/c923OV6/x8tIpfjr/Bo2ozQvDj5M1PXRuTKbq\nuqCUc0kSiW0ZVApeauHYf7M1IsNGrJUc+wfZFAiypslvHzzItw7dw2Pj49u6zn1WxHIFPzqPJjwM\nvUQQX8OPL5CxHsDWJwmTWbrhB1jGKIlqEyWLgCRKFlHIdZ8KUx8kimcw9TFMfZDKcIEwjHn0t+5j\neXYVw9DJlTKAwrQN2vU+pRMIZMzx0h7CJKYWtPCMNcKH4pHKQVzj1vegaRkcOrGPOIxBKUS/DL2G\nnGNzcs8EjZ4PQqCRbsImS0UMLTVx6kXRpmOGQUwiJTPXa4T+jd8FfkSxnLll1vhZ8IUJApFcRhce\nljFGL/qYNV62QhLLJggdVEKcLBPLOrpWwNRHiGWNKLRYXe1g2QZ+EBFFCUEQUVvpkMQJ7Xawo+zB\nnSKRCUthnQutaT5pXedyZ4bp7iK9JORAbmxbOuN2mUAn7tFLgm01YG6GUoprnQVeXDhFPdqcDpqa\nwXODJ3iwdHhTAEgSSbcbrN8s2Q2shdcWL/JodW8qjmeYKFIK6QerM+zLVnm4urXJO91b4mcLv6EV\nd/nexFd4snr8c8s5LAaLLPgLTGWm1hd8T/ewNAshBAeyt2bGrCGUITIOiWVEohJszcHVPZpxA0uz\nCJKArFHCyvwRKnwXGfwaFX2ABDT7KYQ+iOZ8DRldBFVf5/oLvYLQisjgRTTnt0AfSXsFyuj/vgrO\n1yCZRejD/VmDO0PO8DiYndiBWqvWH3hTMzhamGLCG+KD+qe8snQKgG+OPr3pHqrkM0glqRazKad9\ng+a/Uooziwt8uDCfrvP9XzWCVELkyYlJ9hQ2EyleOHCIiucynL1zAcPUHKrF6cZpprJTDNgDm54P\nqboYWhVdywMKUx/C0KbRtCxKBdjGHrT+NTW0IomsI1WPOFlCEiIwUEpiahUMrUrGTtVmc6Ubhdyx\nqcFN52SYBpkNzoP7s0OpRIkIub+0lwG7cMclLk0TWM72wXEtYyp6298buqaRtW/03qqDOUxLJ++5\nW+YBWs0ec9dXiKNkiwXp58EXIggoFaFUgK6VSQWaAmJZRxHjGAfQhEU7+hhTq2Iaw+hyGYGBrhVJ\nYo1Go4XnWakZeyzR+laV7ZZPuZLB70V4n8ORRynFUrDKh42LfNS4zLXuPEtBnZWgiWc4PFo+wqPl\ne5nKjq1r5G9E1SlseuggrUXWwgYl6/YPVzfxeXnpPc63tto2Hs1P8VvDj1K4iRIqhKDTDpmZWeHI\nvTdKNucaC3zaXGTELfB31z7g5MA+HqpM4hk2by1d5mhxZMt79JKAV5c+4KPGZZ6sHue3Rx7H3kXw\nuh1KVol9mX2bdvzz/jzdpMu+zD7G3dtbTioFraiBqQlqwWIqxWyli82iP0vVHmQ1XMbQDGy9BNaj\naCILiHQGQKSMHqGNYmT/ND2ons5lKK2C5nwdiNImMCCElzZ/+xDCAX0P6Zcr+1PEgxuGzG6N1JTd\n2zaDC+XWMlHezPBE9Tij7gAvL77Lz+bf5IWRx9dLkEKAhs520vlav+dUclxytr2+Yf2ktkyt18XZ\nRjvo6ODglp8B/dJGhKVbO9qeAviJz0/nf4qjO0x4EzxefpypbKorZerDGFoVPzpPIpsIYSBVlzhZ\nJJEtMvYJNJFNjy802sG7uNYRNC2PUAFCGH2vaJ1e9D5Z55FbXuvtsLaRcXQTU8tt6wn+WTHvz3Ol\nc4Uj+SMUzN0RVCoDuf73uPU8HMdkaLSIdofe6bfDFyIIgI5ljGOqGBAYWhHbmEQIC004gIZt7EPK\nTroLkB2E0Aniy7jGMQYGUtcd0zSwbJOlhSZJInFdExQUS96WFHgnKKUIZUwgQ2phg48blzm1ep6L\n7WnacY9AhuhCp2IV+N7El3l64H4G7CKe4ewomDZgFTGEvmnkP1GSRX/1tt66Ukk+alziH+be2NIM\nnvSG+O7Y0+zN3JBpaDZ7fHp+HqkU3W7I2FgJt5/6ftpc5FTtKgNOjhGvwPNj9/La4kV+s3yFIIl4\nfHCKg/nND71SirONK/xy4R2OFab4Z5NfpWLdHa5y1siSMTLIviBXrGL2eHvwDI9r3Wu8s/IOD5cf\nvo0QnSJSAX4cEquYnJFP7QBFGghbcZNUWFrr76p1MI+gG/tAWAj6OzihIYyJTUcWWGjOlwGtv+BE\nIFe3mQrWQTVR0VmU/49o+f8exO5mBVJ1za0/14WGnwQEMtxSJtKFxlRmlMJYhrdqH/HuylkerRzd\n8TqtSTS0goDpZoOzy0u0w5Ci4zCSzXFxdYVnJvcy4O1em6YZNfnJ/E8omSVOlk9SsAqbjIEgvf6W\nZuHpHpc7lxlyhiiYhXW7RqUC/PgKiWqlGX9Sw9CrJKqTCkV2f4RrHiZjpztiqbqE8TRxskSiOugi\nCyjCxOrvr1KNqLXPnKjkjl0Jw7vkYthLery4+CKv117nSO4I3xj5BuPe+G1FFRXw3tIMQ14OzzCp\n+V2W/Q73VUbImOa6pMTdxBckCGxEOrKfju0nJLKFEAaN7s8oei/QDT8k734ZgHr3J9j6QXRDY3ik\nSLGcwXUtpJSYpsHYRMj8bJ36aodOKyB/C/U9hWI5rPNh4wJn6hc5tXqey51ZfBkiVcrRrlgFjuT3\n8njlGCcrxyhamS03/nawdYuqXWSmd2MQJVEJc73l216NpaDOX1z92SbHLkjLCN8YfbL/8N/YGbiu\nychIEQW0+7ziOE4wTYOMbvFQZQ8Xmotc66Tm2gfzg7y6cIFQJjw2sG+LxHSsEmphgz2ZYX5/8quM\nOEUC2UMTOkpJdGGgCwOFJJQ+lpZe4+1G7rdDohKuda4x5AyhoeHpHlWrSsksMe/PM9ubZcKbuMUR\nBLow+zMkBpGMkHpCLFN7wpVgCUMz6SYdMkYWgZ7u0sUuJi+FQKi1LEWkrmTdP9+UCaAihJZHOM8j\nzOMQfQR8/p3amDfAoFMio29/zwohqFgFnh18kHm/RivqUtwhqwyShNOL87TDkGODQxwqV3FNk2uN\nOn9x5gMavo8mRHqf7+LclFJ0kg6nVk9Rj+qcbpzma8Nf41D2EN5NdGhLs5jwJliNVnm49HAqBti/\nLTThYumjoA8jVUCz9zKedQzLGO+/zwEMfRClJFL1cIwpLGOCUGTpRWcpei+QmhMFBHGeIL6OpY8j\n+s/D9d51Tq2eIpB3n1t/O3STLu+svEMgA95ZfYd5f54/mfoTBu2RTYwrSDM0WzdAwLV2nY9XF1ny\nu4xl8oxl8pxdXSRIYrLm3fcXhi9MEJAksoVUPUBg6cMksoVSIYoI25jCMkYQwkaphCS5wZHXNI3B\noZtv/vRW9jybqQND7BZ/P/Mq/ybu0ttgQm8Kg8nMAPfm9/FY5Sj3Fqa2lWW4FQyhMeyUbwoCkjl/\nK8tnI4Ik4sezr3GxPbPp5wLBY5VjPD98ctsBokzWptn08TyL8fEyvX6WNNtr8MHKDNPdVa53V0HB\nRKbMvzr0JKFMOFefp2x5m5phpmbwaOVe7iseYMguMd37lF7SJmOk6a2nZymag7TjOrO9S1TtUQxh\nUjBvPOy3wrAzzJXOFWzdxtZsYpVSAw3NoGpXaUS31s4RAspWFV1A3igQyhBTM9GFjmekC72ju5+h\nyaxQsouKzoCWRxgHQXho9tdAK6bzBMIFBCr6CKL+8J6wuRNm0E7YSQNqI4QQZA2PA9lbT2pHScKZ\nxQUWOh0KjkMjCCjYDu0wYE+hyNEDg6z4PebaLSbyhdsr7aKY9+dZCVdQKM62zrIQLPD7E7/Pw+WH\nNwV/S7MYd8d5ZekVZnoz3Ju/F2tNzE8Y9MKzKCJ0LUssaySqRSc4haUP0wpep5r9I4SAOFlC10tE\nyQJN/xUy9gnCZI5eeA7LGEPKNt3wNJY7wloQLltlOnGH8+3zuLpL1shiaRa6MAiSmETdaC5Lpcia\nNobQaUU+tm7QiQNK26iX7gaxTD0yAhlgCIMRdwSBRisMaEfhJhKWpemUHW+9aV+wHDzDpBH46US2\npqMLsSHPubv4ggQBjUiZdON0h+naTyHQiGSPWIVoSuJZD2FoRTL2CWwzVWmUhH3Gxu6QKMlq2ORK\nZ27TQr+GxQ0yDK5ucyA7zv3FA9xXOMDh/CSu/tnEwXShb+kVrDGLdur0K6U4tXqOlxbf21IG2p8d\n43fGn932fKRUtNsBUkqiMKG23KJYSheJqVyVYTfPpdYyhwtDaRlIRry9fJWsYTPqFVgOOkzcxIgo\nmFkK/apJK16h05dzcLQMsYpQKHpJ6rlwrXuOSW/3BjgZI8PRwlYzdUgXkLJ1+7KKJnRszcDRXTpx\nC0uz0YXOkD0K9trfaIjb7NCV7KLis6mEhFxFxldR4ZsIYwoj/z/2F30FchkVX+zTQkNUch3UEMJ8\nAOE+mk4U3yWESZRKHO/QhE+UpB62sDRz04T4RuRsmz9+4CEur64w125jGzrNICRMEg6UKjwwNEI7\nCrlSX2Usn0e/zVITq5jTjdPrLLWiWeRE8QQlayuzLL33h8mZOS60L/Bo+dFN0uBRModt7sEx9tPm\nLXSRQdLBMffT8H+BEGkpzjLGsJigG32EY06RsR4kTKZRKsQxD2HqA1scBvNGnm+NfotZf5asnqVg\nFnB0B6kE870mppYu+EXLoxa0mcoN4OoWp1enmcyUudJe5nh5AoG4Y0psPazzry//a1ajVXJmjq8O\nfpUxdxSpFGVnq8cIpAFgsdehaKWbzASFoWk8OjRBotRdH0JcwxciCMQqpB4tESSdfiko1exYDq8j\nZUzVmaRkjaWlB+3GDsk1D+7q+K2oy8fNy3xYv8ClziyzvSXq0fZGLbZm8lDpHp6o3sf+7DijbhVb\nN3dV2tgJhqYz4m6WYlYo6mGLVtzd1gvganeeH82+vmUyuGhm+d3xL7HH2567vMYK6rQDfD9ieKRA\nqxWQz3uU7QxlO8NykDKMDKEznEkH2X69cIERr0DJuvWuMpYRsQwJki6hDCiICqo/d6ALI1V49a8R\nyoAh5/NJKu/WjUoARp9dkzfvTCZk84EM0MrpNy1shPJRWgUZvpWKyemjaeNXGP2FPgIShFYCEpRc\nQhj718sRu8VO06l+EvLzhbd4rHyMgR2c9fwk4N3Vs4y6Axwr7L/l+wxkMpTctCmsi9QbQyqV+mUY\nBlGS7Oo+b8dtzjbPAqCh8XjlcV4YfoGckdtGuE5QtspMepNcaF9grjdHxarc8ntNC8LJBiq0QIj0\n+7X0YTTboRt+QCI7aFqGZu9XeNa9eNZmL+qUJFDaEpxSnaAAU9O42qkRyphOHPZZeOncAMC838Co\n60zlBshsozy6W5jCXGe83arxrAnBp/VlRjI5yo6HH0dcbNSY77bIWTYnByfuauN6DV+IIKALE0tz\n6cXN/pSgRSduoKFj6hamsNebSbfCGnc/UjHNqMPHjct8UL/AhfY0K2GDVtxb9zzdDk9Wj/PN0SfZ\n4w1TMLMYmk4cJSQqNXTZbseeanzL9QCdBmy1SfPbEDpj7sB66rmGTuIz21veFASUUtSjNv8w9wYf\nNi6sN00hzU6+PfYMJyv3goTVWisdJhH9uqKb3miWZdDTQ3w/xLZNSqXNQSaWklDGDLo57ikMoSFS\n7nKmTNbc+WaPZUTWKJH0Szb0ewKRCgCNWEa4RhaBhqfnduUk9R8TSgVI/5d9YbgHuVGrl+n/VQIo\nhLEfMFCYoO0FbQ9CKHQ7RDOPETf/FyAGdOj3PBAWqBC0EmAgtGqaESRzKDG1q0Cwdr+eblxAIHig\ndKjfxE0XwleW3uNvrv+So/kpqirt89y8I21FXd5dPceH9QuMOFWsrs6Hvz7Hw187ju1YJHGSDuMq\nhSN0dNtiaXqFbrPH6P4hpj+dw7AMvJzD2dc+ofD1B3E8+5aibu+tvkc9SjcnezN7eaj0UBoAdnhN\n0SoylZnidP00b6++zYHsAVw9FY7TtTya8BDCxrWOYepDCGHT9t9EE9m+blLUp4bXiGULXVh41oNo\nWir9Hcs63fB9LH0cQ99dQ94QGhnDJlYJlmYQ6+lz1olTkbl0s9Rib7a6rfbXfwz04oixbJ7LjRWq\njseR0iB7ciWUUmRM664M6G2HL0QQEGi4eo6e1iBWMYawsDQX3dTpJW3kenawGWush24S0Il7rIYt\nLrSvc2rlPB+3LtONfWKVbGvEsR0e79v3BX5EEMcExJx+/xoykRy9fwJN0/B7IZ5n4WXSB2V5qcmF\n8wuUyxkQglazx+JCk29858ENn09QtvIUzSyrGzKQbuxzvbvAPfl0x6xQBDLipcVT/GLh7U0By9IM\nvjR4gueHH8XTHdr1Lj/7wRv0OgHNepfJA0O88AePE8WSWq1NHCW4rsX8XB3bMnA28JgX/Rb/4fqH\nALxsuQw4OQ7kBvrSwMmO/sOdpEHeLNGJ6xgira2GMkATOp6Rw0/y2LpLomKyxtpsxO2R0vzETZot\na9+vRPuMukQqvp4azCeXENs0gpVqI7RBZOZ/phXsQROCjh+iCUE57+E5LkofAS2X0jZUG5LFdEgM\nUP6PEfaX08wgWUSYRyBZJM0QdrdznO0t8RdXf8rj1ft4oHSIQIbM9JaZyoyyPzvGqDuAVJLr3QUs\nzWTYvVFWVEqxFK5yuTPLwWw62+F3AuavLBH2IsJuyJWPp3EyNu16FwQ88My9VEaLXD07jeWaLF6v\n0VrtEIcxldES7/z8NI987TjONrpRAO2kzVsrbxHKEEdzOFE6waQ3ecs+gilM9nh7qNpV3ll5h+cG\nnmMqkw4a5t0v98t0GjnnSWIZgGYhdBdTG2c1vELWHEXXCggsenFE3poEYaGLDELT0LUiljGGuMPl\nbKHX5GhhjNP1acbcEolSBElaehUCMkZKo/WTkKx2awvQu4FmGPBAdZQTA2O8szjNudUl/CTBTyK+\nPL6fou3+p9wTUOhCZ9DZ1/+XJG9WkSqmak8SyWDTDjqSMfWoTS1oMNer8Wn7Gp+0rnG5PUunLzG9\nE4y+7Z2fhMQb6GACkdK3FMzN1EkSid8LsSyDxYUGFz6ZJwoT2m2fPfuqHDiUlmMa9R7tVo+TTxxA\n0wTzs3VmZ1Y3veea1vmoW90UBDqJz7XuwrqPrlSK040L/HD6Jdpxb/3vdKHxQPEg3xl7hqqdljsM\ny+ChLx3hwLEJrp6fozSQx/FsZDeg0je16HVDDEPbYkr99fFjfH382IbrmTDXa3CptcSebJkBZ3uW\niaNlcLUssR3jGlmyepFIBWlfA8GoO0UtnMPVc+vlmd2gEV4hb+1BKfDjGrpmY2k5OvECifIpWPt2\nfayNEMYedPe7KLmIZj2w5fdJ7ydo9lN0gyzXF+t4tkWj3cMwNLKu1Xeo2/DYCQ+0Iip6BwClmhC9\nnyqKJjOgT/b9B3b3WAkhKFhZjuT3Yvcb12/WPuKVpVP8T0f/Ffuz4zxaPoovQ/7s6k94uHSEr488\nuT5TEMqI881rhDLi8ep9FIwsn85eRjd03nvxI8rDRc69fZHf/uPnqM3VufbJLHGc0Gv1GDswTGmw\ngJNx+PCVs4xODVIdLVMaymM52zfRpZKcWj3FnD+HQDCVneLB4oO3VXoVQrAns4ep7BRv1d7i5aWX\nmfQmMYWJJm68VirBSniRblyjYI6jEARJk7J9gJXgIvXwMhljiJXgIgrFiHcCvc/O25X95/r5pBsu\n17DImQ4PliepBR38JKKXhAzYOXQ0JGl5KGu6mxzH1tCNu1i6hS70z1UuXsOQd2Oj8lsTuyt13w18\nIYKAEBqOvh0bIt2NWLpLK+ox15tlprfITG+Z6d4i091FrncXCG5R4lmDIXT2ZUa5rzAFQvDK0vss\nb6PEqWmCiT0VNCH4+Mw0mYzNl792jFNvX6Y6mOOxpzZ/OQLodELmZlbRNMHyUgslt84kZAyXUXeA\nj5qX138WyojZ3hLtuEfezDDfq/HX11/c1KAGGHWq/JPx59iTSQOPkorrn85z/sPrHDi2mT7puhaD\ng3miKKFQ8JBSouu3vkFNTWcyU2bMLRLeQj/e7tMVh90btX6dtIdg9y0Zd9sHiFWXTjSPpRdoRpdx\n9CLdZJlYdrD1EgKN+e5vqDhHdnW87SCEidCrCH0AzTq55fcyPINmHsfRylQLbbp+GvTlLeST14bC\nwOovPAngglaF6DToYwj99uYkayiYWU6U7lm3GezEvU2Zqy40DKGzxxvhvfp5jham2J8dRynFrL/M\nG7XTPFY+xrH81P9H3ps+yXGd6X6/c3LP2qurqncAjZ0gwR0kKJEiJZIiKWk0oxnNlZfrsX0d4W83\nwv+B/S84/MV2OOKGru/1yHekkSWNdlHiJpLiKi4gQAINYum9q7v2JdfjD1ld6BULRcVg4j4IEo3q\nzKysrMzznvO+z/s8RH7EwsUVypMF1lealKeKhJu0ZqQQhH5It9Xj7ec/5NG/fJBzb84S+CGtWoez\nb8zyzN99ac8gsOav8W7tXTphh5Se4uHiw4zZW2tTSkUo1UMIgyhaRtPGEcIga2Q5njnOmcYZ3m+8\nz/n2eU5kT2x7hxiUIoo9elENTRj4cRs/7mJpGSQ6mjCIVUDO3IcmPluaxhQ6U24hEfgQEkvTSekW\njmZwX3E/jmYQo5BColC71snW/XV+X/09JavEqcIp9D0kP/4l4LY8c6UUjaDNbHuepf4a871Vlvs1\nVr0aq16dRtC+6RSPITQOp6f4Yvlu7sodYp87ykfNS7yx9tGe+7RbfZYX6ywt1pNHXikuf7qK65q8\n/LuzTE4XmTlUSdr5TY1s1sa0DKSEVNqmPLqzmSqlOUy5Ow3TV7w6C70qutT44fyLO5ykbGnyranH\nByJh1xphVhdqOKmdS3YhBI5j4ty6gkFi0HOTLfPLK00WlxocOzKKbRtcmVsnm7Ep5G+OGdMNV1no\nvopSMb2oyoh1J0HcxNaKhHGXZtyiaB0lZ16/2Pl5QCkGvgkaftBnrdFlZnyXgVxYiYewVgFhoIxj\nINJJ17CKiGX2M0lHCCGGhdIvlE6yvI06XDCz/M3UiSjE6gAAIABJREFUl/nl0uu8UztHxSpiSJ1f\nLb0+MBE6Tc5ME3oh+++YoLXeoVnr4GZs9G1dwJZrUp4aIY5ioiAi8AIO3b2PXCnD5bPzWHt01kcq\n4oPGB1zsJPfn4dRh7i/cv0uBV6DiBmG8mvg5EAIWuj7JiewJXrFf4WLnIi+uvsi0O01G37rq1AYr\nIj9qkTP340dtdGFiaCUM6WJIl37UIK2PJoSEzyBdoklJ7gYECA3BqLN7U2Tdr/P88vO8uPoiKT2F\nQPDwyMM3XA0oFRPH60CMpu3eif3PgdsyCABUvTr/18Ufs+Y36IbertLJe0EgcDWLu3IHebxyP0cz\n01Sswg51z92glGJ1pcnc1XUefDgZgHRdY6SUxrZNeoOagFLwyblF+j0fTddYX2vjOAbtVh/T1Hnn\nzYtMTY9QGUv49KbUGbdLZPVUYigzwFJvjfPtq3zYuMiLK+/uSFE9M3aaL5Xv3dJpKKTg+P0zrC03\nCIOQMIyTAvZAMuNWOwo9L+TSlSp+sMs1VuD7IVfnaxzYN8LJO6cIgoiLn64iJPS9ACEE5z5e5PjR\nMS5dXsOydI4fHbsmXLYLJBp58xC2VmTd+xgpdFr+HHP+yzh6iXH3YXLmQeQNOix3nO5N6sBvhqlr\n5NMOmpRkXItDEyNkUzuX/wpjoBEkqXs9XD2PuVE/ERrCGBjU/AkFPFMapHbxn8gZab46dpqXV9/l\n49ZlLrbnudxd4l/vf459qXEEAt3U2Xd8ko9eP0+v1cfNOLhZmzhWxAMmkJQSJRLfCgQEXkB9tUkc\nxfQ6/V2Lj0opFnuLvFt7l1bYIqNneHrsaVKaSRStkqyGkkK8wAKhoVSXKF5GYx9SJuycolnkgcID\nXO1e5VzzHG+svcETlSeG97bEwJQZTJkCIXH0Iv2ohiYs/LiFredx9CLtYJFetE6kAjLG+PAc1/11\nZjuzhLcwVtwqIhVxoXWBt2pv0Y26dKIOP174MZrQhkFxr2AQx+vUG/8zUbyOJm9N0ViRSOuYxr1k\n0v8GKf8EFtw23LZBoGIXuSt/iJ8u/P7mZ/1SJ6enuK9wlGfGTnMwPYElTTRx8z4CSoHvBRiGRnHk\nWooqm3O2/B1FMbPnl7j/1EziQ1xtoesSIQWHj4zx4XtXabV6wyAghGDMLjLhlGi2rgWBZtjhH+de\nwIv8LcFBE5LTI3fxrakv7bBtFELgpCwunVvg3Zc/ptPskc45jO0vMXN8gkI5g5uxrzsIb4ZpaoxW\ncrBRfBeCIIhwHZPqepvX/jDLXzx399D27uzHi4RRxMnjU3xwZi5xsGp0+fj8MuVShnzOJQgiLGvv\n9xdCw9KypI0JOuESq/0/YutFsuZ+BJJmcAVFTN48csNAEMeKbjupBdVXWzhpi1TWwbRuLl0gZVIQ\nnluto0uJYyf1AH2TPlKkYi7UVxlzMxQsl98tzPJAeZJ96WsPs/iM6YmbRUp3OJSe4meLv6cb9vnv\nD3yD/amJLQ2D3WaPxmqT46cO8e7vPmJ1bp2rHy9QrzYJvIAojGitt1EKvK6PUgxWBOEO4xlIcuf9\nuM9btbc41zqHLnSeHH1yYAdqIGVx69aqSxheRtMmAEEcd9C0JKBKIXms9Bjv1N7hk/YnvFh9kYpd\n4c5s4q8rhCBjTGBKFyl0dOmSMSZQRMQqImfsR5cWjl6iE66SNbZKrmhC41LnEm/X3k5YcsLcSTNW\niYpnFKthrDakTGwqB+ZN2g2emzAOyRm5oR6QQPDa2mtkjSxHM0evs2eMlGUs64vDlBlc/55RqjnY\nRuD772Iadw2IFJ8fbssgkNwMLk+PnuLj5mU+3kU4bTMsaTDpVLg7f4gnKvdzJD19U5LKu0EpRavl\nMVK6sbBbHCs0TSI1OaSQCgS6riHlzhn5mDPCtDvKudblLa8vbJOPkAhOZGf4L/Y9xZg9sruYlGvy\nhefuQZBcr37Pp7pY58wbszhpm2P37qc0kR8O3NeDEALXMXjltfMUCikc2+CdP17hS48eRdMkcRzj\nDtgiQRhx9uMFTFMnCC4TxQpvEDQzGZts1ubM2XnuOD7B5PjesxVdumjSJVI+urSJVYAft5GYZIwp\nitZx6v6n9KMarl7a8zgAoR9y+cMVuu0+vheQLaQY3VdidOrm6IJ+kDjTjWRTmIZG3w9ZXGtyaPLa\n+4Yq5vdLlziaL/PI6H7uLIwOm3o+K/w42O6lsisiFbPQr3K+dZUzzVkmnQrPjp/G0WyudpeYdCrY\nmknoR1Tn15k4NMbhe/cjNYnf95m5a5rGWouVK2t0mj3ee/kc9zx+BwsXV8gUUmRG0mi6xuThca5+\nssT0sfGhSqVSitn2LC9VXyJSEXfn7+ax0mMJ7z3pDtl2tiZSOMRxC10/TBRdIY7raAPqpqM5fHX0\nq1zuXuZq9yq/Xf4tJbPEmD02SItpOPq1VFzWTAZ6R78WbEv2sR3XSAhB3szz9OjTHEwdxNVdRq1R\n0noaQxrDQBArxXqvx1K7hVKQsUxKbopar0cYRziGQclN/clmObtDwzCO4Tp/Qaf7D5jmKUzjDkAR\nRVVAoWmVQSD2iVWHdue7WOZpTOMkQug4zlc/97O6LYMAJNF1vzvGE5X7WehVd2jnbOBAapzTxTt5\neOROZtITBHFILWgSxAFFM0cYR/QG2iElM3/DFUEcKRr1DneevLGCZRTFrC43Wa+20DSJZRs06l1W\nlht0Ot6OBzyjp9ifGsPVLLq7dCxvYMqt8NdTT3AoPbnn+UpNkt7E+nEzNsVKliMnp6ku1Wmsd8iN\npG8qCEBi17e23uGOY+OMj+V5693LqFgNFVk3oEnBXScmaTR7TE8VefPtS9x/7346HY/FpYRVFUXq\nhg+RKdM4Wom6d55OsIwuHUyZJojb1PyP6Udr5K3DeFHzhucuNUmhksV0TEI/ZN/RMVLX0Ynajlgp\nGp0+zU4fy9AZybpMj25drutCcn9pElPTWOy2CD+H2diHjVkutudpBl1CFdIKOnhxwGz7Kr9ZegOA\nj1uX8eMAXSbuWE9VHmImPYkpdXqRx3xvlVbQ5Z78EaIows06TBxMpFKOnzrE9NFxbNfCtA0KlRyG\nZXD6a/dhmDqZfIpPz1xlfbGeaNiHIatza0wcrAyDQDNo8pvl31Dza0w5UzxVeYqckdsz5SGEhaZP\nIlWIEC5SZonjTY2ZAo5nj3NP/h7eWH+DM80zvLj6It+c+Oawd+Bmca2V7BoKZoEHiw/uuY8UAlNL\nmHiRUhhSI4pjav3e0MLyZsUmPyuU6hIEH2IYSTCL4w7d3g+RcoSU+9f0vRcI/PeQ2ihB8BGmvntH\n/eeF2zYIQCK8dnrkLt6rn+cPax9toYkWjAyPlO7iS+X7uCN7AFszqfst2mGHNb+RSPBKg1bQoRl2\n8KOAYjF3w5b4er3Dvv0lcvnrF44gSSMYhoZp6khNousSN2UiZfKz3CYPKYXgSHqKslXgcndp12Nm\njRTfnHiM+wvHbqg4uBuEFJQnCuSK6aF70k3uibbpfOVAlng7lIJOx6NabTM5XqDbTSQqqmstTj90\niGarRxTGlMt7Nw8B1P2LXGg2sGQWXTroIkkZaJqFQiGFiSZMnJtg2oRBxOpCjXajR7PWIY5ixmfK\njIzevL+0oWlkXBtT1+h6wa6ub7ZusC+d57Xly7y3tsCok8HWDGISk/JT5Wmm0zefq/2gMcv79fP4\ncdJ8d7mzSKRiVv06nQFFeNWrc6ZxkX994DkeL9+/RVHUliZFM8v7jQtMuhXKbp6xmRLtIJlVgiRw\nethyDF3T0A0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dLjDCDYKAJnFzyeBrmDr5Upp4IOIntue9hUCIFLc+UQjx4pC612O+08CP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\nvNAAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(wc, interpolation='bilinear')\n", + "plt.axis(\"off\")\n", + "wc.to_file('first.png')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "显示词云" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pic = np.array(Image.open('miao.png'))\n", + "wc = WordCloud(font_path=font_path,background_color=\"white\", mask=pic)\n", + "wc.generate(text);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `np.array(Image.open('miao.png'))`，将图片文件读入，存入到numpy的ndarry对象pic\n", + "- `mask=pic`，将pic设为模板，生成一个wc词云画布\n", + "- 生成词云" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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Y4jRnaaZGZxBRLfmcurhDliuqVR/PdWhUQrqDmL5McB2bsu8W9VVv4RjIRDwm/EehjUKZ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sH9ahKK7bUyaBA2AxzLQPoRShc0ojrNqEE1qPKZhw8xnhnouvd95r4T6KakFBWQoSRjZrGFThBe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\njI/ghyGhlKy4NWrSo7ayjkSytydPOutw+PjotiGB+ESfOjjI5YvzBEGIf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Create readme.md --- chapter4/data/readme.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 chapter4/data/readme.md diff --git a/chapter4/data/readme.md b/chapter4/data/readme.md new file mode 100644 index 000000000..01b186640 --- /dev/null +++ b/chapter4/data/readme.md @@ -0,0 +1 @@ +## 本章用到的数据 From b3d24b435691b2624d29138993df717e91cbf1cd Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Sat, 25 Nov 2017 13:00:11 +0800 Subject: [PATCH 23/30] Add files via upload --- chapter4/data/stopwords.dat | 1611 +++++++++++++++++++++++++++++++++++ 1 file changed, 1611 insertions(+) create mode 100644 chapter4/data/stopwords.dat diff --git a/chapter4/data/stopwords.dat b/chapter4/data/stopwords.dat new file mode 100644 index 000000000..7ed2a9841 --- /dev/null +++ b/chapter4/data/stopwords.dat @@ -0,0 +1,1611 @@ +、 +《 +》 +% +（ +） +； +！ +。 +， +： +“ +” +啊 +阿 +哎 +哎呀 +哎哟 +唉 +俺 +俺们 +按 +按照 +吧 +吧哒 +把 +罢了 +被 +本 +本着 +比 +比方 +比如 +鄙人 +彼 +彼此 +边 +别 +别的 +别说 +并 +并且 +不比 +不成 +不单 +不但 +不独 +不管 +不光 +不过 +不仅 +不拘 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+认识 +许多 +设或 +诚如 +说明 +说来 +说说 +诸 +诸如 +谁人 +谁料 +贼死 +赖以 +距 +转动 +转变 +转贴 +达到 +迅速 +过去 +过来 +运用 +还要 +这一来 +这次 +这点 +这种 +这般 +这麽 +进入 +进步 +进行 +适应 +适当 +适用 +逐步 +逐渐 +通常 +造成 +遇到 +遭到 +遵循 +避免 +那般 +那麽 +部分 +采取 +里面 +重大 +重新 +重要 +针对 +问题 +防止 +附近 +限制 +随后 +随时 +随著 +难道说 +集中 +需要 +非特 +非独 +高兴 +若果 \ No newline at end of file From 569d28dab685fc2b520be198c54b28ede6420488 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Sat, 25 Nov 2017 13:00:59 +0800 Subject: [PATCH 24/30] Add files via upload From a509377e788b89a6d81686c3a8ca39e317865311 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Sat, 25 Nov 2017 13:02:58 +0800 Subject: [PATCH 25/30] Add files via upload --- chapter4/data/news_163_home.txt | 1135 +++++++++++++++++++++++++++++++ 1 file changed, 1135 insertions(+) create mode 100644 chapter4/data/news_163_home.txt diff --git a/chapter4/data/news_163_home.txt b/chapter4/data/news_163_home.txt new file mode 100644 index 000000000..5cb972529 --- /dev/null +++ b/chapter4/data/news_163_home.txt @@ -0,0 +1,1135 @@ +http://news.163.com/17/1122/19/D3SCU2OH000189FH.html +他们做了啥 习近平给他们回信了 + + （原标题：他们做了啥，习近平给他们回信了） + 【学习进行时】11月21日，习近平给被称为“红色文艺轻骑兵”的人们回了一封信。他们是谁？他们有着怎样的历史和故事？新华社《学习进行时》原创品牌栏目“讲习所”带您探寻究竟。总书记的嘱托：永远做草原上的“红色文艺轻骑兵”近日，苏尼特右旗乌兰牧骑的16名队员给习近平总书记写信，汇报乌兰牧骑60年来的发展情况，表达为繁荣发展社会主义文艺事业作贡献的决心。21日，习近平给他们回信了！习近平在回信中说，从来信中，我很高兴地看到了乌兰牧骑的成长与进步，感受到了你们对事业的那份热爱，对党和人民的那份深情。习近平指出，乌兰牧骑是全国文艺战线的一面旗帜，第一支乌兰牧骑就诞生在你们的家乡。60年来，一代代乌兰牧骑队员迎风雪、冒寒暑，长期在戈壁、草原上辗转跋涉，以天为幕布，以地为舞台，为广大农牧民送去了欢乐和文明，传递了党的声音和关怀。习近平表示，乌兰牧骑的长盛不衰表明，人民需要艺术，艺术也需要人民。在新时代，希望你们以党的十九大精神为指引，大力弘扬乌兰牧骑的优良传统，扎根生活沃土，服务牧民群众，推动文艺创新，努力创作更多接地气、传得开、留得下的优秀作品，永远做草原上的“红色文艺轻骑兵”。乌兰牧骑：“以天为幕布，以地为舞台”乌兰牧骑的蒙古语原意是“红色的嫩芽”，后被引申为“红色文艺轻骑兵”，是适应草原地区生产生活特点而诞生的文化工作队，具有“演出、宣传、辅导、服务”等职能，深受广大农牧民欢迎。1957年，苏尼特右旗建立了内蒙古第一支乌兰牧骑。解放前，苏尼特右旗人民群众的文化生活可以说是空白的，全旗有极少数的民间艺人为王府服务，普通老百姓没有欣赏歌舞的权利。1949年以后，在中国共产党的领导下，苏尼特右旗民间文艺活动开始活跃。同年10月，苏尼特右旗人民政府在温都尔庙成立文化室，组建农牧民业余文艺宣传队。工作重点为宣传党的方针政策和路线，为农牧业生产服务，为普及文化教育服务。由于文化室业余文化宣传队的组织和演出方式不适应牧区地广人稀的特点，1957年，内蒙古自治区文化厅党组决定改造旗县文化室，组织小型、流动、多功能的文艺工作队伍。1957年6月17日，全国第一支乌兰牧骑宣告成立。“过去牧区的路都是勒勒车走出来。”年逾八十的伊兰是乌兰牧骑第一批队员，回忆起当时的情形，她记忆犹新。最初，这支乌兰牧骑只有9名演员，带着马头琴、四胡、三弦等几件简单乐器，他们深入牧区巡回演出，哪怕只有一个农牧民，也会照演不误，受到广大牧民群众的高度赞扬。目前，内蒙古草原上活跃着75支乌兰牧骑，每年演出超过7000场。习近平的回信全文苏尼特右旗乌兰牧骑的队员们：你们好！从来信中，我很高兴地看到了乌兰牧骑的成长与进步，感受到了你们对事业的那份热爱，对党和人民的那份深情。乌兰牧骑是全国文艺战线的一面旗帜，第一支乌兰牧骑就诞生在你们的家乡。60年来，一代代乌兰牧骑队员迎风雪、冒寒暑，长期在戈壁、草原上辗转跋涉，以天为幕布，以地为舞台，为广大农牧民送去了欢乐和文明，传递了党的声音和关怀。乌兰牧骑的长盛不衰表明，人民需要艺术，艺术也需要人民。在新时代，希望你们以党的十九大精神为指引，大力弘扬乌兰牧骑的优良传统，扎根生活沃土，服务牧民群众，推动文艺创新，努力创作更多接地气、传得开、留得下的优秀作品，永远做草原上的“红色文艺轻骑兵”。习近平2017年11月21日 +http://news.163.com/17/1121/19/D3PQJTJR000189FH.html +习近平给兰牧骑队员们的回信|全文 + + （原标题：习近平总书记给内蒙古自治区苏尼特右旗乌兰牧骑队员们的回信） + 苏尼特右旗乌兰牧骑的队员们：你们好！从来信中，我很高兴地看到了乌兰牧骑的成长与进步，感受到了你们对事业的那份热爱，对党和人民的那份深情。乌兰牧骑是全国文艺战线的一面旗帜，第一支乌兰牧骑就诞生在你们的家乡。60年来，一代代乌兰牧骑队员迎风雪、冒寒暑，长期在戈壁、草原上辗转跋涉，以天为幕布，以地为舞台，为广大农牧民送去了欢乐和文明，传递了党的声音和关怀。乌兰牧骑的长盛不衰表明，人民需要艺术，艺术也需要人民。在新时代，希望你们以党的十九大精神为指引，大力弘扬乌兰牧骑的优良传统，扎根生活沃土，服务牧民群众，推动文艺创新，努力创作更多接地气、传得开、留得下的优秀作品，永远做草原上的“红色文艺轻骑兵”。习近平2017年11月21日 +http://news.163.com/17/1121/12/D3P0J48L00018AOQ.html +习近平致首届丝绸之路沿线民间组织合作论坛贺信 +新华社北京11月21日电首届丝绸之路沿线民间组织合作网络论坛21日在北京召开。国家主席习近平向论坛致信祝贺。全文如下：习近平主席致首届丝绸之路沿线民间组织合作网络论坛贺信值此首届丝绸之路沿线民间组织合作网络论坛开幕之际，我谨代表中国政府和中国人民，并以我个人的名义，向论坛召开表示热烈的祝贺！向出席论坛的各国民间组织代表和各界人士表示诚挚的欢迎！“一带一路”倡议提出以来，从愿景转变为现实，取得了众多建设成果。实践证明，加强“一带一路”国际合作，为维护世界和平、促进共同发展提供了新平台、注入新动力。民间组织是推动经济社会发展、参与国际合作和全球治理的重要力量。建设丝绸之路沿线民间组织合作网络是加强沿线各国民间交流合作、促进民心相通的重要举措。希望与会代表以这次论坛为契机，共商推进民心相通大计，为增进各国人民相互理解和友谊、促进各国共同发展、推动构建人类命运共同体作出贡献！祝首届丝绸之路沿线民间组织合作网络论坛取得成功！中华人民共和国主席 习近平2017年11月21日于北京 +http://news.163.com/17/1122/10/D3REH7OO000189FH.html +多地宣传解读十九大精神 + + （原标题：宣讲入脑入心 道理讲活讲新（认真学习宣传贯彻党的十九大精神·聚焦基层宣讲）） + 江西家常话语接地气本报南昌11月21日电（记者魏本貌）11月20日上午，“草根名嘴”杨会军和南昌市青云谱区惠民社区的居民们，边拉家常，边宣讲十九大精神和习近平新时代中国特色社会主义思想。“小区里80%以上是老人家，养老方面有什么说法？”居民郭丽华问。“十九大报告指出，推进医养结合，加快老龄事业和产业发展。”杨会军说，“咱们青云谱区正在建设13个居家养老服务点，老年人在家门口就能享受多样化服务。”“十九大报告，您最关注的一句话。”南昌八一公园内，部分已经征集到的话语正在展出，将基层干部群众的心里话与十九大精神有机对接。请身边人拉家常话，用心里话对接大道理。泰和县“民嘴讲堂”、景德镇珠山区“小巷讲堂”、萍乡市“百姓身边故事宣讲团”……江西各地组建起数百个基层宣讲团，不断创新宣讲方式。结合省委常委理论学习联系点制度，江西省级领导干部赴各地基层带头宣讲十九大精神。邀请十九大代表、省直单位主要负责同志组建省委宣讲团，深入基层一线，在宣讲的同时进行调查研究，倾听广大干部群众心声，让十九大精神播撒在基层干部群众心间，并化为行动、落到实处。四川特色文艺送大餐本报成都11月21日电（记者刘裕国）“十九大报告对实施乡村振兴战略作出了部署，我们不仅要脱贫，更要致富！”11月15日，四川红原县邛溪镇玛萨村党支部副书记依姆青听了宣讲后高兴地说。四川省委高度重视党的十九大精神宣讲工作，迅速组织省、市、县三级党委宣讲团开展声势强大、全域覆盖的集中宣讲，同时组织动员全省各地开展丰富多彩、富有成效的群众性宣讲。阿坝州、凉山州、甘孜州等地组织少数民族语言和汉语“双语”宣讲团，一边双语宣讲十九大精神，一边为群众排忧解难送温暖。凉山州的摩托车“突击队”、德阳的基层“轻骑兵”、达州的“挎包宣讲队”、巴中的“扁担小分队”……部分地区针对山高路远、村落零散的实际，因地制宜组建“马背宣讲团”穿梭于各牧民点进行宣讲。自贡市创作60余幅农民漫画作品诠释十九大精神；泸州的金钱板、广元的车马灯、乐山的“文瀚嘉州·百姓直通车”、南充的数来宝、凉山州的情景剧……四川各地创作、编排、导演一大批群众喜闻乐见的文艺节目，引领群众在演艺中学习、在学习中演艺，既宣传解读了十九大精神，又给群众送去了文化大餐。河南分类定制传政策本报郑州11月21日电（记者朱佩娴）“大学生回农村创业有前途吗？”面对新乡医学院大学生的提问，11月20日上午，党的十九大代表、辉县市张村乡裴寨村党支部书记裴春亮耐心讲解：“党的十九大报告提出了乡村振兴战略。如何振兴？就要有新思维、新技术、新农民。只要大学生有想法、有技术、有魄力，回乡创业一定前途光明。”连日来，裴春亮先后宣讲20多场（次），近万人聆听了报告。针对不同的群体，宣讲内容也会微调：面对机关干部，他会着重讲党员干部干净做人、静心做事；面对院校师生，他会着重讲青年学生奋发有为、大展身手……“例子都是分类定制，力争把党的政策、党的意志、党的温暖传达到老百姓的心头。”裴春亮说。党的十九大代表、郑州圆方集团党委书记薛荣的宣讲也是如此。她还自制宣讲海报，把党的十九大民生看点通过10张卡通图片展现出来；在直播应用中直播十九大宣讲，获得10万多次点播。河南宣讲团共组织省委宣讲团12组24人、十九大代表报告团5组15人到全省各地宣讲，计划宣讲130场，宣讲团成员均认真备课，切实把党的十九大精神讲全、讲透、讲明白。甘肃贴近群众把准脉本报兰州11月21日电（记者银燕、柴秋实）“乡亲们，你们所想的，翻开十九大报告都有体现。”在甘肃省武威市凉州区下双镇日光温室现代农业园一间活动室内，武威市委讲师团副团长张生龙的宣讲吸引了种植大户们。为深入学习宣传贯彻党的十九大精神，甘肃省委、省政府领导干部带头深入分管的部门、行业系统和所联系的县、乡、村进行宣传解读。一批政治素质强、政策理论水平高的领导干部、理论工作者，组成了各级宣讲团深入农村、社区、机关、企业、校园，将十九大精神带到陇原大地的每个角落。各地结合本地区实际开展对象化、分众化的宣讲活动，突出时代性、贴近性，让群众听得懂听得进。近日，在兰州市团结新村街道，十九大代表、甘肃日报社时政部首席记者徐爱龙的宣讲现场，不时会有听众站起来提问。互动式的交流，让大家听得入神，现场响起阵阵掌声。在深入基层宣讲的同时，徐爱龙还积极创新方式，利用微信公众号宣讲十九大精神和习近平新时代中国特色社会主义思想。 +http://news.163.com/17/1122/11/D3RFAL69000189FH.html +十九大后六项民生福利待查收 + + （原标题：十九大后深改组首次@你 六项民生福利待查收） + +http://news.163.com/17/1122/11/D3RFO07F000189FH.html +温州洞头蓝色海湾整治:生态养海 + + （原标题：温州洞头蓝色海湾整治：生态养海 拥海而兴） + 洞头仙叠岩段海洋生态廊道。“全靠修复了这片沙滩！”这是东岙村人给出的答案，言语里满是自豪。2016年，总投入4.76亿元的蓝色海湾整治项目落户洞头。一年多来，随着项目的实施，人们欣喜地发现，赤潮减少、海水变清、沙滩又回到了最初的模样。在沙滩的勾连下，人海相亲相近，小渔村也由此兴盛起来。以海兴国、人海和谐。十九大报告指出，人与自然是生命共同体，人类必须尊重自然、顺应自然、保护自然。人类只有遵循自然规律才能有效防止在开发利用自然上走弯路，人类对大自然的伤害最终会伤及人类自身，这是无法抗拒的规律。对此，洞头人的感触尤为深刻。14年前，习近平总书记在浙江工作期间，曾到洞头列岛调研半岛工程建设。在发展的关键时期，他曾嘱咐洞头人，“要特别重视生态环境保护工作，坚持走可持续发展之路，做好山体、岛礁等生态环境资源的保护”“真正把洞头建设成为名副其实的‘海上花园’”。而今，半岛工程已经建成，洞头也由县变区，但不曾变化的，是洞头人保护海洋的初心。党的十八届五中全会确立绿色发展理念后，洞头更是率全国之先，明确不再围垦滩涂，并积极开展蓝色海湾整治行动，做好保护、修复、提升三篇文章，加快建设“海上花园”，谱写了一首新时代人海和谐的动人恋曲。一片被修复的沙滩“自从东岙沙滩修复后，今年营业额至少翻了一倍。”东海渔家老板洪求强的朋友圈，记录了东岙村的点滴变化：白净沙滩映衬着碧海蓝天，沙滩边环绕着渔家民宿。135米长的沙滩上，孩子们追逐嬉戏。“在家门口吹海风、玩沙子，仿佛回到了从前。”洪求强说。“回到了从前”，是满满的欣喜，也是对现今洞头沙滩整治修复成果的认可。上世纪80年代末，在填海造地、取沙建房、建造码头的影响下，一处处洁白美丽的沙滩，开始消失于视野。挖土车在沙滩上不分日夜地开采，面积达1.84万平方米的东岙沙滩，最后竟只剩下裸露的碎石。人们无度的索取，换来大海无声的抗议。那些年里，洞头海洋生态环境也越来越差：赤潮频频出现，羊栖菜大量减产，养殖户亏损严重。海水受到污染，辛苦捕来的海鲜，不敢吃了；岛礁破坏严重，原本珍贵的贝类，逐渐消失。靠海吃海的日子难以为继，小渔村日渐颓败，不少村民只得进城打工。现实面前，洞头人幡然醒悟，靠破坏海洋生态环境换来的发展，不可能长久。2016年，蓝色海湾整治项目落户洞头，东岙段被纳入项目建设重点，其中包括沙滩修复和海洋生态廊道等建设。2017年1月，投资总概算达850万元的东岙沙滩修复工程启动。当东岙村前的沙滩开始吹沙、施工车进驻后，村民们满心欢喜。7月，洞头区这片最有名的沙滩终于恢复原貌，吸引了天南地北的游客。原本离去的村民，再度回到村里，办起渔家乐和民宿。洪求强的生意越做越红火，曾经的小门面，如今也摆开了阵势。沙滩从有到无、从无到有，村里环境好了，带动的是整个东岙村旅游业的提质增效。眼下，这个陆域面积仅0.35平方公里、常住人口仅1500多人的小渔村，涉旅人员就达600余人。旺季时，东岙村50家民宿，几乎天天客满、一房难求。“十九大提出建设美丽中国，要求我们实施重要生态系统保护和修复重大工程，加大生态系统保护力度。身为海岛区县，要在保护的同时，加快修复海洋生态，还海洋以宁静、和谐、美丽。”区海洋渔业局副局长李昌达说。一块被拯救的礁石或许体会过失去的痛苦，如今，洞头人对海洋资源倍加珍惜。在鹿西乡，工作人员叶明伟带我们看了一块并不“壮观”的礁石：“为了保护这块天然‘老虎礁’，鹿西人迫切想造的综合交通码头，也往后推迟了一年。”鹿西乡位于洞头区东北部的鹿西岛上，乡以岛为名，至今岛民依旧靠船出行。1992年改造的鹿西港码头，是乡里最主要的码头。由于狭小和老旧，许多大型船只难以靠岸，已严重制约了鹿西乡的经济社会发展。2015年，鹿西综合交通码头开始筹备。最初，码头选址在鹿西岛西南方的“老虎礁”，该处水域开阔，水深条件良好，临近老码头，交通便利。工程即将施工时，部分乡民提出意见，认为“老虎礁”是鹿西岛的标志性景观，应当予以保护。面对乡民的诉求，洞头区政府确立保护不可再生的岸礁海岸线旅游资源的政策，并对原设计方案进行调整，“现在码头选址向西北方向横向平移了200米，移至已开发利用的人工岸线区域，并对原方案进行集约化设计，通过提升码头综合利用率及管理的自动化水平，以减少占用宝贵的岸线资源。”洞头区交通局副局长谢铭说，为此工期不惜延误一年，造价增加约200万元。不只是鹿西综合交通码头，小三盘通村公路、中心渔港港区道路二期工程等项目，均为了保护沙滩、海湾、岸礁等优质自然海洋生态资源，而改变了原来的方案和线路。“发展”与“保护”，并非总是并行不悖，更好地“有所为”，坚决地“有所不为”，这是洞头的取与舍，也是他们守护海洋的决心。　一处被叫停的围垦区从码头的重新规划、道路的重新设计，再到滩涂围而不填的创新，折射的是新时代洞头人的“耕海之道”。眼下，“梦幻海湾项目”正在建设中。这是洞头迄今为止，单体投资额最大的项目，不过它的“看点”并不在此，“人造蓝海、围而不填”才是亮点所在。2015年，中国大部分沿海地区还在向海洋寻求更多发展空间之时，洞头就明确，今后对新增的涉海工程，不得进行围填海审批；对早已确权可填的3710亩海域，则通过围而不填的创新之举，尽最大可能保护海洋生态。“梦幻海湾模式”，正是围而不填的一种做法。这一做法，得到了国家海洋局的赞许与支持。围而不填的意义何在？“‘梦幻海湾’整个项目，将以透水构筑物的形式建造，不对海域进行填海，全部打桩，然后再在上面建造相关建筑物，建筑物下面依然是海。”李昌达表示，海洋是洞头的命脉。一个项目要用海，首先考虑对生态环境会否造成破坏，如果会，宁可不要金山银山，也要绿水青山。如今，蓝色海湾整治通过实施岸线资源整治修复、沿海村居改造升级、生态廊道建设等项目，海岸线变靓了、村容村貌变净了、海岛变美了。美丽海岛轮廓逐步呈现，引来大批客商投资，渔民逐步实现转产转业。尝到生态回馈的洞头人更加清醒，选择项目更加挑剔严格。他们坚持经济生态化目标，政绩的“指挥棒”，清晰指向绿色生态、蓝色发展。近年来，洞头投放人工鱼礁9万余立方空体，建成152公顷海洋牧场示范区和1053公顷省级水生生物增殖放流区，助推振兴东海鱼仓。在南、北爿山（鹿西鸟岛）实施筑巢引鸟工程，有效保护51种海洋鸟类繁衍生息。同时，洞头不断创新制度建设。《洞头国家级海洋公园总体规划》在全国首个获批实施；出台海洋生态红线划定方案，在县一级率先实施海洋生态红线制度；编制完成洞头国家级生态保护与建设示范区建设方案、海域利用规划、海岛保护规划、海域海岛整治修复规划等。洞天福地，从此开头。从上世纪的伸手索取、肆意开发，再到如今的生态养海、反哺大海，洞头人坚信，海洋不仅意味着生命，意味着资源，更意味着未来。如今，行走在这座拥海而兴的小岛上，我们随处可以感受到尊重自然、顺应自然、保护自然的海洋生态文明理念。 +http://news.163.com/17/1122/23/D3SPFVUT0001875O.html +津巴布韦执政党证实：姆南加古瓦已经回国 + + （原标题：姆南加古瓦已经回到津巴布韦） + 据美联社消息，津巴布韦执政党证实：被推举为津巴布韦新任总统的姆南加古瓦已经回国。 +http://news.163.com/17/1122/22/D3SN231D0001899O.html +台湾云林县发生5.2级地震 福建网友：震感明显 +中国地震台网正式测定：11月22日22时20分在台湾云林县（北纬23.71度，东经120.60度）发生5.2级地震，震源深度16千米。另据东南早报微博，台湾发生5.2级左右地震，泉州厦门网友反映震感明显。 +http://news.163.com/17/1122/15/D3RVPKUO0001899O.html +一架美运输机在日本冲绳海域坠落 8人获救3人失踪 + + （原标题：一架美军运输机在日本冲绳海域坠落 3人下落不明） + 该架美军C2运输机是位于日本神奈川县横须贺基地的美军核动力航空母舰“里根号”的舰载机。据称，当时美军正同日本海上自卫队参加训练。美军曾通知日方发动机或有故障。没有消息表明运输机上有日本自卫队员。目前，日本防卫省正向美军了解详细情况。日本防卫大臣小野寺对记者表示，“现在美军正同日本海上自卫队进行搜索，自卫队已派出军舰和船只。”他还表示，“将尽力协助搜救下落不明的人员。由于美军飞机事故不断，希望美方今后能够做到安全飞行。”C2运输机提供航空母舰舰队关键的后勤支援，即主要用于海上航空母舰和陆上海军基地之间士兵及物资等的运输。它是一款双发涡桨舰载运输机，内部最多可乘坐26人。为了保证从航空母舰起飞的速度，C2运输机还装有被称作“弹射器”的特殊装置。美军机飞行事故不断2017年10月11日下午，在日本冲绳县东村高江地区美军北部训练场内，一架美军大型运输直升机CH-53着陆后起火，现场燃起滚滚黑烟。2016年12月13日夜间，驻日美军一架MV－22“鱼鹰”倾转旋翼机在冲绳县宇流麻市海域碰撞着陆，5名机组人员负伤后获救。2016年12月7日晚，一架属于驻日美军岩国基地的海军陆战队F/A－18战斗机在高知县附近海域坠落。2016年9月，美国空军嘉手纳基地的一架美军AV-8鹞式战斗机在冲绳本岛北部的边户岬以东约150公里的海域坠落。约40分钟后，驾驶员获救。另据中新网11月22日电，据日媒报道，日本防卫相小野寺五典22日表示，美军核动力航母“罗纳德·里根”号舰载机中的一架C-2运输机坠入冲之鸟礁近海。机上11人中至少2人下落不明。根据美国海军第七舰队官网22日消息，美国海军一架搭载11名机组成员和乘客的飞机在日本冲绳东南部海域坠海。第七舰队方面称，事发时，这架飞机正飞往“罗纳德·里根”号航母，目前该航母正在菲律宾附近海域。消息称，“罗纳德·里根”号正在执行搜救行动，舰上医疗人员将对获救人员的情况进行评估。目前尚不清楚这起事故的原因。 +http://news.163.com/17/1122/16/D3S3GMEF0001875N.html +武警调整部队部署和兵力调动制度:由中央军委规定 + + （原标题：关于<关于中国人民武装警察部队改革期间暂时 调整适用相关法律规定的决定（草案）>的说明——2017年10月31日在第十二届全国人民代表大会常务委员会第三十次会议上） + 关于《关于中国人民武装警察部队改革期间暂时调整适用相关法律规定的决定（草案）》的说明——2017年10月31日在第十二届全国人民代表大会常务委员会第三十次会议上中国人民武装警察部队司令员 王宁全国人民代表大会常务委员会：我受国务院、中央军委委托，现对《关于中国人民武装警察部队改革期间暂时调整适用相关法律规定的决定（草案）》作说明。一、暂时调整适用的必要性为了更好地坚持党对武装力量的绝对领导，贯彻军委主席负责制，建设一支听党指挥、能打胜仗、作风优良的现代化武装警察部队，高效完成新形势下维护国家安全和社会稳定的使命任务，党中央和中央军委对武警部队改革作出了重大决策部署。党的十八届三中全会作出的《中共中央关于全面深化改革若干重大问题的决定》，明确要求“优化武装警察部队力量结构和指挥管理体制”；党中央批准的深化国防和军队改革总体方案明确，按照“军是军、警是警、民是民”的原则，调整武警部队指挥管理体制，优化力量结构和部队编成。《中央军委关于深化国防和军队改革的意见》强调要加强中央军委对武装力量的集中统一领导，并对贯彻中央决策部署作了具体安排。当前，武警部队改革正在按照党中央和中央军委部署全面推进。现行《中华人民共和国国防法》、《中华人民共和国人民武装警察法》对武警部队的领导指挥体制、职能任务、警衔制度、保障体制、部队部署和兵力调动使用等作了规定。为了保证武警部队改革于法有据、稳妥推进，需要对上述法律规定作出修改。考虑到改革任务较为紧迫，而法律修改周期较长，有必要请全国人大常委会作出暂时调整适用相关法律规定的决定。二、暂时调整适用的主要内容一是调整领导指挥体制。强化党中央和中央军委对武警部队集中统一领导，坚定贯彻军委主席负责制，按照“军是军、警是警、民是民”的原则，调整武警部队指挥管理体制，优化力量结构和部队编成，实现领导管理与高效指挥的有机统一。二是调整职能任务。按照党中央和中央军委赋予的新时代使命任务，武警部队将主要担负执勤、处突、反恐怖、海上维权、抢险救援、防卫作战等任务，拓展了维护国家领土主权完整和国家安全职能。三是调整警衔制度。根据武警部队领导指挥体制改革和军官军衔制度改革情况，调整改革武警部队警衔的设置、授予、晋升和批准权限等规定。四是调整保障体制。根据武警部队领导指挥体制改革要求，对武警部队的后勤、装备实行统一规划、统一保障、统一管理、统一审计监督，提高保障效益。五是调整部队部署和兵力调动使用制度。由中央军委对武警部队部署和兵力调动使用作出规定。三、暂时调整适用的组织实施本决定的组织实施，按照党中央的有关决定、国务院和中央军委的有关规定执行。改革措施成熟后，将及时提出修改《中华人民共和国国防法》、《中华人民共和国人民武装警察法》等有关法律的议案，按照立法权限报批。《关于中国人民武装警察部队改革期间暂时调整适用相关法律规定的决定（草案)》和以上说明是否妥当，请审议。 +http://gov.163.com/17/1122/13/D3RO5MKS00239803.html +农民工断指送医遇堵 河南交警逆行护送 + + （原标题：暖闻｜农民工手指被锯断送医遇堵，河南高速交警逆行一路护送） + 11月20日上午10点，一辆警车打着双闪鸣着警笛，从连霍高速河南开封服务区南半幅逆行下站，警车后还跟着一辆轿车。轿车里是一对父子，父亲在工地干活时被电锯锯断两根手指。男子手指不小心被锯断急就医向警方救助。警方供图开着警车为这对父子开道的，是河南省公安厅高速交警总队五支队副支队长马国宝和民警李飞。马国宝11月21日告诉澎湃新闻（www.thepaper.cn），20日早上郑州附近高速路段大面积起雾，他接到任务在连霍高速开封西服务区进行路面分流。当日上午9点半，雾散了一些，但高速公路北半幅由于交通管制，车辆非常拥堵。“我们往西查看路况，绕了一圈后回到开封服务区南半幅。我们看路况有所缓和，便向上级联系报告路况。就在这个时候，一个男子就跑到我们警车旁，说他父亲手指不小心被锯断了，因为车流拥堵，北边过不去。”马国宝说。看男子神情紧张，马国宝赶忙走到车前，伤者（男子父亲）此时坐在副驾驶位上，左手用一条白色毛巾裹着，但还是止不住血，加上天气寒冷，显得很痛苦。“由于雾天原因，连霍高速由开封到郑州方向车辆十分拥堵，因在郑州就实行了交通管制，反方向并不拥堵。”马国宝当机立断，决定带父子二人逆行沿连霍高速南半幅下站，然后送往开封西汽车站。20分钟后，警车将伤者送抵开封西汽车站后因为有任务返回。伤者的儿子冲着马国宝和李飞深深鞠了一躬后，便驱车前往汽车站附近的解放军第一五五医院治疗。马队长表示，自己并没有做什么，希望群众们在遇到此类困难时，要及时向附近民警寻求帮助。 +http://news.163.com/17/1122/20/D3SGINVA0001875O.html +朝鲜谴责美将其列入支恐国家名单:严重挑衅 + + （原标题：朝鲜谴责美国把朝鲜重新列入“支恐国家”名单） + 据朝中社22日报道，就美国宣布把朝鲜重新列入“支恐国家”名单一事，朝鲜外务省发言人表示，继特朗普在联合国舞台上抛出“灭绝”朝鲜的言论之后，21日给朝鲜贴上“支恐国家”标签，是对朝鲜的严重挑衅和粗暴侵害。发言人称，美国列“支恐国家”名单是旨在扼杀不听其指挥的自主国家的手段。此次，美国将朝鲜重新列入“支恐国家”名单，以切断“用于朝鲜非法的核导计划的非法资金”为名，通过涉朝后续制裁，暴露了美国欲动用一切手段和方法来扼杀朝鲜的思想和制度。发言人称，美国以对朝鲜贴上“支恐”标签来发起挑衅，却大谈“和平解决”，这使朝鲜进一步坚定“紧握核宝剑”。 +http://news.163.com/17/1122/16/D3S23VHT000187VE.html +穆加贝辞职是否会对中津关系造成影响?外交部回应 + + （原标题：外交部：中方尊重穆加贝辞职决定，他仍是中国人民好朋友） + 外交部发言人陆慷主持11月22日外交部例行记者会。问：当地时间11月21日下午，津巴布韦总统穆加贝宣布辞职。请问中方对此如何评价?穆加贝的辞职是否会对中津关系造成影响?中方现在如何评价穆加贝?中津关系长期友好，经受了时间和国际风云变幻的考验，近年来中津各领域务实合作不断推进，给双方特别是给津巴布韦人民带来实实在在好处。中方高度重视中津关系，愿同津巴布韦各方一道，推动中津友好和各领域合作不断取得新进展。穆加贝先生为津巴布韦民族独立和解放事业作出过历史性贡献，也是泛非主义运动的积极倡导者和推动者。他长期致力于中津和中非友好，为中津关系和中非关系发展作出过重要贡献。中方尊重穆加贝先生的辞职决定，他仍然是中国人民的好朋友。问：据报道，穆加贝辞职后，英、美均呼吁津巴布韦举行自由、公平大选，请问中方对此有何评价?问：据悉，前副总统姆南加古瓦即将回国接任总统，请问中方对其有何期待? +http://news.163.com/17/1122/15/D3RUBEC00001875P.html +云南一民政局被通报 70%干部职工亲属违规吃低保 + + （原标题：云南德宏一民政局被通报 70%干部职工亲属违规吃低保） + 56名干部职工中，有40名领导、干部职工及亲属违规享受城乡低保。近日，云南省德宏州纪委对外公布了这起“陇川县民政局‘靠山吃山’塌方式违纪违规案”。今年6月初，德宏州纪委发现陇川县民政局存在干部职工及亲属违规享受低保问题，随后德宏州和陇川县纪检部门迅速介入调查。调查发现，陇川县民政局56名干部职工中，有40名领导、干部职工的82名亲属不符合享受城乡低保。而部分领导干部职工的配偶及直系亲属，违规享受低保资金已达到40.5万多元。2017年7月31日，德宏州纪委对陇川县章凤镇党委书记、县民政局原局长杨恩增立案审查。德宏州纪委通报，陇川县民政局长期以来对申请享受低保人员抽查、核实、公示把关不严、监管缺失，70%以上干部职工亲属违规享受低保，把服务群众的权力当作亲属获利的“工具”。同时，陇川县民政局还违规私设“小金库”48万余元，违规审批发放抚恤金和丧葬费199.8万余元。干部职工利用职务便利收受“好处费”，其中，陇川县民政局公墓管理所所长董勒堵在2012年至2017年担任所长期间，利用职务上的影响先后2次收受墓地建造施工人员好处费1.1万余元；办公室副主任张璟利用职务便利，先后3次收受太阳能热水器安装项目人员好处费7.1万余元。多人被处理 违规低保全部收回随着调查工作的不断深入，陇川县民政局“靠山吃山”塌方式违纪违法案件被及时查处，5名班子成员、4名股所级干部受到党政纪处分，40名领导、干部职工及配偶亲属违规享受城乡低保被责令清理、清退。在涉案人员的处理中，纪检部门对陇川县民政局5名领导班子成员作出纪律处分，其中，陇川县章凤镇原党委书记、县民政局原局长杨恩增，受到留党察看二年处分、撤销行政职务、降为副主任科员。党总支副书记蔡万保，受到党内严重警告处分、免职处理。副局长董麻崩，受到党内警告处分。副局长刀保亮和老龄委办公室专职副主任郭庆昌，受到留党察看一年处分。同时，陇川县民政局公墓管理所所长董勒堵、办公室副主任张璟受到开除党籍处分，涉嫌违法问题已移交司法机关处理。社会救助股股长孟秀明、中心敬老院原院长黄国忠，受到党内严重警告处分。此外，纪检部门对陇川县民政局干部职工的亲属违规享受低保作出处理，对陇川县民政局27名干部职工及配偶直系亲属44人违规享受城乡低保资金40.5万余元予以全部收回，上缴财政，82名亲属违规享受低保从2017年8月全部予以停发。当事人：国家政策执行不到位这起案件中，原民政局局长杨恩增受到留党察看二年、撤销行政职务、降为副主任科员处分。日前，央视记者独家采访了案件主要当事人杨恩增。从2011年开始，杨恩增一直担任陇川县民政局局长；2016年7月，调任陇川县政府所在地章凤镇党委书记，但仍然兼任陇川县民政局局长。2017年6月，纪委工作人员找到了杨恩增。但是令杨恩增没有想到的是，在自己担任陇川县民政局局长期间，单位持续发生人员违纪违法案件，涉及的干部职工竟达70%。那么，为什么一个有56名干部职工的单位，违纪违法人员竟然有40多人？为什么会在享受城乡低保上出现“优亲厚友”问题？根据德宏州通报，杨恩增违反工作纪律，对陇川县民政局“靠山吃山”塌方式违纪违法问题负有领导责任。同时，陇川县民政局主要领导、班子成员带头“靠山吃山”，以权谋私、造成全局塌方式违纪违法。边查边改 以案警示案件发生后，德宏州、陇川县采取了边调查边整改的措施，以本案为警示，启动城乡低保对象精准识别专项行动。昨天（21日），记者在陇川县民政局看到，大厅悬挂了“陇川县城乡最低生活保障工作办理规范流程表”，对低保的办理流程、具体要求等方面进行了公示。工作人员介绍说，流程表是纪委对民政局案件展开调查后不久悬挂的。据工作人员介绍，今年6月初发现问题后，德宏州一方面组织力量对具体情况进行调查，一方面迅速展开整改。6月8日，德宏州全面启动城乡低保对象精准识别专项行动，针对低保工作中存在的突出问题和薄弱环节，开展低保对象精准识别，对不符合享受低保的人员全部进行了清退，制定出台了《低保经办人员亲属享受低保备案制度》，严防民政干部优亲厚友。 +http://news.163.com/17/1122/19/D3SCG5T10001875P.html +母亲因给不起儿子彩礼自杀? 官方:不满意儿子对象 +【母亲因给不起儿子彩礼轻生？ 宁陵县：系误传，不满意儿子对象自杀】近日，一则母亲因给不起儿子彩礼而轻生的视频在网络热传。今日，事发地河南省商丘市宁陵县发布通报称，网传为彩礼轻生说法不实，死者林某某是因对儿子相中的对象不满意而跳河自杀。北京青年报记者从网络视频中看到，在一条河边，一男子趴在一女性尸体上哭泣，随后突然转身跳河，后被民警和周围群众救起。负责处理此事的河南省商丘市宁陵县黄冈乡派出所民警杜传峰对媒体表示，轻生者的儿子前不久刚刚订婚，女方彩礼要求一辆车，男方这边付不起因而酿成悲剧。11月22日下午，宁陵县宣传部发通报回应此事，称网传说法不实。通报称，死者林某某因为其儿子谈对象订媒意见不一致，儿子对象与其同乡，林某某因相不中儿子谈的对象，嫌弃其个子低，林某某便以死相逼，一时想不开，骑电动车来到宁陵县黄岗镇张桥村境内废黄河境内跳河自杀。事发后，在不知真相的情况下，误认为林某某是因为高额彩礼致跳河自杀。通报中表示，事发后，临界的黄岗派出所接到报警后，及时出警将死者林某某打捞出来。死者林某某丈夫赶到现场后，见到妻子已经死亡，当时情绪失控跳河，其儿子看到父亲跳河也跳下河救父亲，现场民警随即跳入河中将父子二人救上河岸。 +http://news.163.com/17/1122/22/D3SNNCTI00018AOR.html +女子迷信算命将娃打致瘫痪 出轨被捉奸与情夫私奔 + + （原标题：妻迷信算命之言将亲子打致瘫痪 与情夫私奔6年后丈夫上电视痛诉） + 法制晚报·看法新闻(记者张恩杰)11月12日，央视12--社会与法频道《律师来了》节目以《消失的妈妈》为题，报道了陕西省神木市的货车司机闫彩斌痛诉妻子怀第二胎时，因神官算命称其腹中的孩子与其相克，为此妻子吃打胎药未将胎儿打掉。于是在怀胎四五个月时，向他提出做人流手术，他未同意。最终妻子生下孩子，取名旗旗。满月后，闫彩斌将旗旗送到农村父母家照料。闫彩斌称旗旗长到三岁，被他妻子从父母家接了回来。结果不到一个多月，妻子竟将旗旗痛打的瘫痪在床，医院下发的病危通知书显示：患儿颈髓损伤、闭合性胸部损伤，肺挫伤、肺炎、胸腔积液，身上多处骨折。后经辗转多家医院，终于救回来一条命。事发40多天后，闫彩斌才选择了报警。警方以没有证据证明有所控告的犯罪事实为由，不予立案。再后来，闫彩斌发现妻子出轨他人，被他捉奸在床。最终妻子跟着情夫离家出走，一晃六年到现在，旗旗在爱心妈妈公益慈善组织地不断接力下，于上海复旦大学附属儿科医院做保健康复治疗。目前肩关节、肘关节功能均有所恢复，大小便不再失禁，可以挨着墙角站立一分钟。此时，闫彩斌向央视《律师来了》节目组求助，提出追究妻子虐待抛弃孩子、进而出轨与他人结婚的法律责任。最终，他通过此节目选定了上海海华永泰律师事务所严嫣律师为他代理此案。从发病危通知到康复治疗 旗旗痉挛缓解大小便不再失禁看法新闻记者注意到，在这期节目一开始，就播放了一段央视记者于今年8月1日来到上海市闵行区复旦大学附属儿科医院，探望在此康复治疗的旗旗的视频短片。只见他穿着病号服，坐在轮椅上，微微活动着双手。记者问他感觉怎样，他小声回答，“比以前好些了。”据旗旗的父亲闫彩斌透露，就在2011年旗旗3岁时，其母亲将其打得瘫痪在床上。“当时他左臂骨折，只有头会动，脖子以下均不能动弹，一点知觉都没有。西安交大医院给我们家属下发的病危通知书显示：其多发伤颈髓损伤，闭合性胸部损伤，肺挫伤、肺炎，胸腔积液，伴随多种骨折。”而据复旦大学附属儿科医院儿童保健康复部副主任医师王素娟介绍，旗旗刚入该院治疗时情况比较严重。那时他的颈髓损伤已有两年多，到了后遗症期。手指没有办法打开，双腿肌肉收缩。“经过这几年的治疗，他的身体康复效果蛮不错。这表现在他的手功能有一个很好的进步。整个痉挛的情况，也有明显的缓解。他上肢可以抬得很好，肩关节、肘关节的活动恢复的不错。大小便不再失禁了，有知觉。”王素娟如是说。神官算命说腹中胎儿克她 她堕胎不成生子后常虐待孩子至于妻子为何要下狠手毒打幼子。闫彩斌说出了一个近乎荒唐的秘密。他称，妻子在怀孕时，请神官算过一命，说是腹中胎儿与她相克。她起初吃了打胎药，却未将胎儿打掉。“当她怀孕四五个月的时候，她跟我说她要做人流，我没同意让她做。就这样孩子生下来满月后，送到农村我母亲那里去抚养了。”闫彩斌如此解释说。节目中，闫彩斌提供的旗旗十六个月大时拍摄的照片显示，其留着锅盖头，喜笑颜开，穿着小蓝棉绸褂，撅着屁股在地上爬着，甚是活泼可爱。可惜好景不长，就在旗旗三岁时，其母亲突然提出要将孩子从婆家接回来，由她自己抚养。“我想她能自己主动接回来，这样以后母子相处会好一些。但没想到她将孩子接回来后，我在外开大货车，十天半月回一次家，就会发现旗旗身上有淤青，颈部、背部、腿上到处都是。为此，我问妻子这咋回事，她说是楼梯上摔得。”闫彩斌在节目中如是说。紧接着其表示，“有一次，我在家中看到旗旗将大便拉在地上，我妻子呵斥他去吃。我看到后将孩子抱起来，和妻子吵了一架。妻子带着大儿子出走，一晚上没有回家。第二天一早，我将孩子托付给我的一个姨妈，我妻子中午回来后接孩子，对我姨说，要报复我。”这次争吵过后的第三天，妻子告诉他，她打孩子了，胳膊响了一声。于是他发现旗旗胳膊有些红肿，他以为没什么大碍。休息一晚上，次日天不亮他就开车去干活了。走在半路上，妻子打电话给他说孩子在发高烧。他连忙折回家中将旗旗带去神木县高新医院，给其降温输液。输了一整天液体，其小便却尿不下来。于是他连夜又带着旗旗去了榆林市星元医院，各方面的检查都做了，却未查出什么毛病。孩子受伤40天后他才报警 警方以查无证据为由不予立案“当时孩子躺在病床上，眼睛都睁不开，我叫一声他的名字，他流着眼泪。看得我的心都碎了。后来我买了飞机票，带他到西安儿童医院，也未检查出什么毛病。紧接着又去了西安市中心医院，该院诊断说是颈髓损伤，让我将他转到西京医院;西京医院说病情太重，没有办法接受。就这样，我辗转将旗旗送到西安交大医院，下发了病危通知书，抢救了两天，才渡过危险期。”谈起孩子受重伤后一波三折转院的经历，闫彩斌至今记忆犹新。其还表示，转院过程中，妻子一直跟随在他和孩子身边。妻子称她听见孩子在外边哭，就将孩子带回家。但她对医生却说，旗旗是从3米高的轮胎垛上掉下来的。“我认为孩子是被她打成了那样，否则一个三岁的小孩子，如何爬上三米高的轮胎垛，再说我家附近也没有轮胎垛。”节目中，闫彩斌的大儿子作为事发时在家里唯一的见证人，他接受《律师来了》节目组采访时称，弟弟是被他妈妈拿着扫床的刷子打成了那样。值得一提的是，闫彩斌一直忙着给孩子看病，未就孩子的伤情做司法鉴定。直到事发40多天后，他才选择了报警。据神木市公安机关的不予立案通知书显示，“我局经审查发现，没有证据证明有所控告的犯罪事实。”妻子出轨被他捉奸在床 抛夫弃子离家出走6年未有音讯由于自己的疏忽，证据不足，无法将妻子绳之以法后，闫彩斌却又发现妻子背着他和其他男人偷情。“刚开始我只是怀疑，后来我在招待所将她逮着了。我看到她们躺在一张床上。我妻子脱得只剩下一个胸罩，其他什么都没穿。而那个男人贺某则穿着衣服。他们不肯承认，这事也就一直拖着，直到他们私奔，离家出走。到现在已经有6年杳无音讯了。”闫彩斌如此透露说。他称，妻子找不见后，他去过妻子的娘家，发现丈人丈母娘一家也搬走了。坊间有人传言妻子和那个情夫贺某有了新家庭，还生了一个孩子，在过年时曾带回来过。对此，贺某的妻子则接受《律师来了》节目组采访时称，她去榆林做完剖腹产手术回到家中，发现丈夫贺某和闫彩斌的妻子同在屋内，贺某只说他们是朋友关系。再后来，贺某也跟着闫彩斌的妻子一起消失。“这些年，他(贺某)再也没回来过。我不清楚他们是否生了孩子。我家的户口上，只有我和贺某生的两个孩子，我将户口给闫师傅看过了。”镜头里，贺某在农村老家的妻子如是说。医疗费均靠慈善组织捐款 依靠父母辛苦劳作买菜钱度日看法新闻记者还注意到，节目中，闫彩斌称妻子失踪后，他陪着孩子在上海看病，每月1.3万元的医疗费用均来自爱心妈妈慈善公益组织的接力捐款。他自己没有经济来源，很多时候还要靠农村父母每月少则三五百，多则七八百元的接济勉强度日。对此，闫彩斌的老父亲则站在神木市大柳塘镇的自家菜地里，接受《律师来了》节目组采访时称，他现在一边要照顾正在上学的大孙子(即闫彩斌长子)，一边还要种菜，拿到集市上去买。收成好的话，一年能赚1万元，然后用这些钱给小孙子旗旗看病，以及家里的其他吃穿缝补等生活费用。提起自己含辛茹苦拉扯大的小孙子却有这般遭遇，闫老伯双眼里噙满了泪花，哽咽着说他心里实在憋屈，很难受。在视频短片里看到这一幕，节目现场的闫彩斌突然情绪失控，小声抽泣了起来。他称老父亲都已经60多岁的人了，还要在地里劳苦，太不容易。他母亲身体也也不太好，经常生病。“每当想起我妻子虐待完孩子，抛下一家老小，和情夫跑了，自此杳无音讯。我就恨不得将她千刀万剐。并将家里有关她的照片撕成两半，以此来解恨。”闫彩斌指着镜头里出现的被他撕成两半的妻子的照片如是说。就此，现场有观察员对于闫彩斌的行为点评到，现在不是埋怨的时候，作为一个聪明的男人，在摔跟头时，要学会反思，为何家庭成了这样。要从自己身上找问题。首先作为一个30多岁的年强力壮的汉子，不能再靠60多岁的农村父母接济度日，也不能总依靠公益慈善组织的爱心捐款。而应该自食其力，在上海边打工边给孩子看病。节目最后，闫彩斌提出了自己的诉求，称要给孩子讨个公道，能否告孩子母亲重婚罪，遗弃家庭成员罪，虐待罪?对此，现场四名律师均结合闫彩斌所陈述的事实从法律角度对这几项罪名进行了分析。最终闫彩斌选定了上海海华永泰律师事务所严嫣律师为他代理此案。看法新闻记者将在后续追踪报道里，专访严嫣律师，对于此案中涉及的这几项罪名及一些法律疑点进行解答。 +http://news.163.com/17/1122/18/D3S9E4VL0001875P.html +8岁男孩疑似坠井身亡 家属质疑:井口还没他肩膀宽 + + （原标题：希望学校男童井下死亡之谜：肩比井口宽，校内有施工队） + 这是一口直径约20厘米的井，比一张A4打印纸的短边还少1厘米，一个成年人的脚掌踩在井口会被卡住，起初，没有人把它和一个失踪的8岁男孩联系在一起，直到11月20日，男孩失踪的第6天，遗体从3米多深的井里被发掘出来。孩子课间失踪了?这口井，座落在在安徽阜阳市临泉县医药希望学校内的一片工地旁，失踪男孩巴天宇，是这所学校一年级的学生。医药希望学校是一所规模较大的小学。巴天宇的父亲介绍，学校一年级有9个班，全校32个教学班，学生1998人。学校上午一共有四节课，最后一节课的铃声每天会在十点四十分准时响起。11月15日这天，第四节课一开始，一年级2班的班主任张老师就发现坐在第一排的巴天宇不见了。巴天宇没请过假，此前的三节课也都在座位上正常上课。张老师介绍，天宇之前出现过不按时上课的情况。巴天宇是个不让人省心的孩子，他的母亲徐仅仅没少接到老师的电话。老师说天宇不爱学习，因为爱稿小动作，天宇还被调到第一排靠墙坐，这个位置在老师眼皮底下。发现天宇没在课堂，张老师立刻派班长和几名同学去校园里找他回来上课，厕所、操场都去了，找遍所有能找的地方，还是没找到他。第四节课很快就结束了，天宇还是没出现。上午将近11点，天宇的姥姥做好午饭，出门往学校方向走，准备接外孙回家。学校虽然提供午餐，但天宇的父母觉得在家里吃更放心，况且天宇的家跟学校只有一墙之隔，走路也就五分钟，因此他平时都回家吃午饭。姥姥刚走到学校门口，手机就响了。电话是班主任打来的，问她：天宇是否提前回家？双方一沟通，发现天宇去向不明。姥姥顾不上吃饭，从上午11点找到了下午1点多，也没找到外孙，于是她报了警。天宇的父母巴玉和徐仅仅都在浙江金华，去年，他们开了一家馒头店。天宇上学前，跟在父母身边在浙江“飘着”，去年8月份，才被送回老家阜阳。11月15日凌晨三点多，巴玉夫妇起床开工，准备做馒头。干活时，徐仅仅和丈夫商量，准备招一个工人帮老公打理店铺的活计，她自己回老家照顾儿子。这个念头的热乎劲儿还没过，中午她就接到母亲的电话：天宇失踪了。监控盲区的竖井15日深夜，徐仅仅和老公巴玉连夜赶回阜阳。夫妻俩去了学校。监控记录了天宇的最后行踪。失踪前，他穿着带白花的红色毛衣，下身穿黑色长裤，脚上是一双红色运动鞋。15日上午，第三节课结束之后，天宇和同学一起跑出教室。在走近胡同前，天宇抬头朝教学楼上边望了一眼，身边的小孩与他动作一致。“好像被楼上什么东西吸引了”，巴玉说。此后，天宇自己拐进了教室旁边的一条胡同。胡同是监控盲区，通往教室后面（北面）的一片施工工地，穿过工地就到达学校的操场。拐进胡同之后，天宇的身影就不再出现了。巴玉说，出了胡同，在施工工地旁边安有两处监控，但校方告诉他，这两处监控早就坏了。另外，从学校大门的监控里，也找不到天宇离开学校的身影。施工工地成了寻找天宇的第一现场。官方公布的招标公告显示，临泉医药希望学校工地的在建项目包括一栋五层的教学楼和配套设施。临泉县重点工程建设管理局的负责人韦柏林介绍，这个工程今年3月份开标，4月份动工，目前已基本完工，中标的施工单位是安徽华彩水利工程有限公司。巴玉了解到，出事当天，施工工地上只有七八个工人在作业，整个教学楼的建设已接近尾声。15日白天和16日一整天，警方、救援队以及学校的师生，对施工工地以及周边进行地毯式的排查，找遍工地的每一寸角落，也没有发现天宇——所有人都忽略了两个井口。工地的北侧，有一个略低于地面的缓坑，坑里有少量的积水，坑的外围竖着两口井。井口只有20厘米左右，一个成年人的脚掌踩在井口会被卡住。包括救援队的志愿者、老师、校长和家属在内，所有人都觉得，井口太窄，孩子坠井的可能性不大，用手电筒照看，还能看到井里有水，但没有发现井里有异物。家属们反复查看过两口竖井。他们估算过，天宇一米三的个头，七十多斤的体重，怎么看也和20厘米的井口不匹配，“正常情况下，一个8岁男孩掉下去根本不可能”。徐仅仅一度认为儿子是被拐骗了，她印了一大摞寻人启事，四处发散。她一直处于精神恍惚的状态，每天以泪洗面。而巴玉身为家庭的支柱，硬撑着，面对每一天。井口有新土和线头有很多疑问，巴玉想不通。儿子为什么突然会拐到胡同里？是自己贪玩，还是有什么东西吸引了他？难道是被人给害了？孩子身上应该没什么贵重物品。天宇唯一贵重的物品是一条金链子，但出事那天，天宇也没有戴着它出门。他才8岁，还不太会花钱，平时想要什么，也是直接和姥姥讲，学校和家只有几步路，他身上一分钱都没。出事前几天，天宇看到同学在吃“粘牙糖”，回了家，他通过微信视频跟父亲聊天，希望爸妈从浙江寄糖回来。巴玉有点后悔，他对儿子的这个小小要求没上心，始终没有给天宇买糖。11月19日，孩子失踪的第五天。巴玉越想越不对劲，“监控显示他没出学校，我这孩子不可能凭空就飞了”，于是，他又去了学校里的那片工地。再次来到井边的时候，巴玉发现变化。原来竖井旁边的坑，被填埋了一些。巴玉15日第一次往井里看时，可以看到井水，隔了4天，他趴在地上仔细看，发现井口竟有一层新土，“好像有人动过现场”。更蹊跷的是，巴玉在井口找到几条两厘米左右的红白线头。巧的是，这些线头与天宇失踪时所穿毛衣是一个颜色的。巴玉此时确信，儿子就在井里。井下发现遗体11月20日下午，巴玉找到蓝天救援队，救援人员开始对竖井进行探测。在此之前，一对住在5公里外邻村的老夫妇说，曾有一个和巴天宇年龄相仿，相貌接近的男孩，连续两天向他们讨要食物。巴玉打开手机让他们看照片，这对老人语气笃定，那个讨吃的男孩就是他。这个消息，曾让巴玉夫妇脑中闪现一丝希望，但随着竖井被挖开，希望很快破灭。救援人员用探测设备发现井下3.5米至4米之间有异物。起初并不确定井下是孩子。他们伸下铁钩试探，钩上了孩子的衣服，就是天宇穿的那件毛衣。看来，孩子真的在这口竖井里，且已“出事”。由于井口过于狭窄，直接从井口把天宇拉来上，肯定会破坏孩子的遗体，救援人员和警方决定：利用挖掘机将井口侧方挖开，把孩子从井里挖出来。此时，距离天宇失踪已经过去6天。20日晚，8点左右，挖掘工作正式启动，为防止孩子遗体受到二次伤害，接近孩子被卡住的地方，救援人员用工具手动挖掘。巴玉提供的救援视频显示，井里仍有蓄水，随着井口豁开，井水渗到四周，天宇被救出时身体蜷缩，头朝上。头部上方有些积土。在现场的巴玉夫妇没有亲眼看到孩子被捞出时的样子。他们都晕过去了。法医进行尸检后，天宇的遗体暂存在县殡仪馆。巴玉测量了天宇的遗体。“就算不穿衣服，天宇的肩膀至少也有23厘米宽，加上毛衣有25至28厘米，掉进一个20厘米的洞这不可能，”他说。谜团待解天宇是怎么坠井的，现在还是个谜。根据孩子平时的表现，班主任张老师认为，天宇在智力方面有些反常，跟其他孩子不一样，字也写的不好。“从来不写作业，也不会写（做）”。天宇还会在同桌的书上乱画，影响同学的学习。姥姥给他买的本子，也被他撕得满地都是。张老师评价，天宇在学校算是调皮的孩子，下课的时候会去抓别人一下，拽别人衣服一下什么的，两位任课老师多次跟天宇的家长沟通，说这个孩子在学校不适合大的环境，“他家长说，只要他在教室，学多少是多少，不惹事就行了，只要平平安安。”张老师还说，出事的井是施工用井，并非学校自用的水井，“以前（天宇）也没有发生什么大的问题，没想到会发生这种情况。”巴玉承认，天宇是很调皮，但他否认孩子有智力问题，“就是学习不行，其他事情甚至比大人还聪明”。看到孩子长期不能集中精力学习，巴玉也曾担心他有多动症，去年，他特意带天宇去浙江的大医院做全面检查，结果显示，一切正常。徐仅仅说，唯一能让天宇提起兴趣的只有画画，天宇的作文本上，被他画满了穿裙子的小公主，“没有学过（画画），他就是喜欢”。寻人启事上，注明天宇“口齿有些不清”，巴玉解释，孩子舌根的筋有问题，做过手术。徐仅仅回想，如果孩子留在身边，也许不会发生这种意外。她和丈夫都不相信儿子是自己坠井的。深一度记者联系了临泉医药希望学校的孟校长、施工单位安徽华彩水里工程有限公司的负责人，谈及两口施工竖井的问题时，两人都挂断了电话。目前，此案由临泉县公安局刑警大队进行调查，队长表示，要等尸检结果出来后才能给案件定性。徐仅仅今年29岁，将来还有生小孩的机会。但眼下，夫妻俩只想知道，天宇在落井之前到底遭遇了什么？监控盲区的工地上发生过什么？他们在等尸检报告和调查结论。巴玉把天宇失踪之日当成祭日。21日早上，他走到学校门口烧了一堆纸，这天算是孩子的头七。8岁男孩失踪5天 学校操场直径20余厘米井中现尸体安徽省阜阳市临泉县8岁男孩巴天宇在几天前失踪，家长及警方寻找数日后，在学校操场的一个直径20余厘米的井内发现了孩子的尸体，目前警方正在对此进行调查。 +http://auto.163.com/17/1122/07/D3R3EPTH0008856S.html +3种动力9款车型 最美凯美瑞哪款适合你 +版权声明：本文版权为网易汽车所有，转载请注明出处。此次上市的新一代凯美瑞包含三种动力/九款车型，分别是2.0L（四款）、2.5L（三款）和2.5L混动（两款），售价区间17.98-27.98万元，与上代车型基本保持一致。※ 车型简介新一代国产凯美瑞的2.0L和2.5L都会提供运动版（锋尚版）车型，运动版车型的外观要比普通版更加激进运动，混动版的外观则和普通版保持一致，只是加入了一些专属标识，前不久我的同事刚刚实拍了运动版车型，下面我们就围绕运动版车型做简单介绍。第八代凯美瑞运动版和普通版看上去的差异比较大，运动版设计了专门的前后保险杠、格栅、大灯、排气、尾翼和轮毂，混动版则是在普通版的基础上加入了一些专属标识。其实三种版本的外观在当前市场的中型车中都算运动风格比较浓郁的，第八代凯美瑞的运动版在细节上更进一步，前脸中部为X型大嘴，雾灯区域还有加大尺寸的辅助格栅装饰，这些让它显得更加激进。运动版车型提供了双侧四出的排气，配合全新车机的后保险杠让它平添了一份霸气。并且，运动版尾灯的两个装饰绝对算得上点睛之笔，简单的勾勒就让它比普通版多了不少韵味。车身及内饰颜色选择新一代凯美瑞除了提供六种单色车漆外，还有两种专为运动版车型设计的双色车身，在六种单色车漆中有一款海钻蓝是混动版的专属，所有车型选择铂金珍珠白都要额外支付2000元，运动版车型选择红黑双色也需要加2000元，运动版如果选择铂金珍珠白+黑的双色搭配就要加4000元，这是丰田在车身颜色上的一贯策略。此外内饰也提供了三种颜色，其中红色内饰是2.5L运动版的专属。丰田当前在售的车型内饰基本都是一板一眼的规矩设计，谈不上不好看，但是很难分泌让你兴奋的激素。在第八代凯美瑞上，我们终于看到了丰田在内饰设计上“飘”的一面。除了雷克萨斯以外，在丰田当前的车型上，我们绝少见到一丝发飘的设计，在第八代凯美瑞上，我们对丰田内饰的印象也将被改变。这一次，第八代丰田凯美瑞很不“丰田”。凯美瑞的内饰做工依然保持着较高的水准，无论是包裹的皮质还是覆盖的装饰板，在接缝处理和做工上都很令人满意，现在的年轻人多数时间都接触者优质的东西，凯美瑞的作用和用料这些细节能打动他们的挑剔心。第八代凯美瑞纵向空间上的表现还是比较出色的，当前的中型车后排空间都越做越大，新凯美瑞在这一环节上也表现不错。新一代国产凯美瑞提供三种动力系统，分别是2.0L+6AT、2.5L+8AT和2.5L混动+ECVT，2.0L发动机还提供两种调校，不过差别几乎可以忽略，其中最亮眼的当属2.5L+8AT的组合了，搭载的2.5L发动机拥有40%的全球最高热效率，这要比带T的发动机更加难得。※ 配置分析一、2.0L怎么选？既然提供三种动力系统，那咱们就按照动力来逐一分析，先来看看2.0L的入门版，也就是全系的入门车型怎么样？入门版表现如何？2.0E 精英版  售价：17.98万先来看一下全系的入门车型，2.0E精英版在基础安全性配置上是比较齐备的，特别是标配的10气囊在同级中是比较罕见的，此外LED大灯也是一个亮点，在其它配置方面，入门版基本处于同级的主流水准，但倒车雷达和影像的缺失肯定会给消费者带来不便，带来了事后加装的麻烦，概括起来就是，入门版的配置有亮点，但也有小缺陷，算是个值得考虑的入门版车型。三款普通版怎么选？三款2.0L普通版车型使用一台发动机，但顶配豪华版在调校上要比另外两款高了1kW和2N·m，这是可以忽略的差别，选车时不用去考虑它，主要还是来看配置吧。精英版和领先版的配置差别主要就是座椅材质和调节方式，所以差价也只有1万元，如果不反感皮质座椅的话，领先版的性价比应该是高于精英版的。再来看豪华版，配置确实配得上2.0L顶配的地位，从外观、安全配置、科技配置和舒适配置上都有了显著提升，最关键的是终于有了倒车雷达和倒车影像，这么多配置，价格上也只比领先版贵了1万，所以对于准备购买2.0L的消费者来说，豪华版应该是最值得推荐的车型。2.0L运动版值不值？别忘了2.0L还有一款2.0S锋尚版，也就是我们俗称的运动版，它在整体配置上和2.0G豪华版比较接近，具备更加动感的外观套件和多种驾驶模式，但在座椅材质和调节方式上做出了牺牲，由于只比豪华版贵了6000元，所以里外里两车性价比基本打了个平手，要不要运动版就看您自己的喜好了。二、2.5L怎么选？2.5L值不值得选？2.5L车型的动力系统还是比较值得购买的，首先发动机的动力要更加充沛，而且还有新的8AT变速箱，能够提供更加平顺的驾驶感受，无论是技术含量还是动力水平，都是比较大的卖点，如果对动力多少有些要求的话，2.5L肯定是更合适的选择。但由于2.5L的起步配置比较高，最低也要接近22万元，导致性价比降低，所以可以预期的是，未来新凯美瑞的销售主力还是2.0L车型。2.5L选哪款？2.5L普通版只有两款车型，旗舰版代表了新凯美瑞最高的配置水平，豪华版其实已经很丰富了，旗舰版则是又加了一个更字，又添加了一些科技和舒适配置，几乎已经武装到了牙齿，所以价格也就并不那么亲民了，比豪华版足足贵了4万元，如果选择2.5L的话，豪华版的性价比要更高一些。2.5L也提供了运动版车型，就是2.5S锋尚版，它的配置和2.5G豪华版相近，差别可以参照2.0L对比的内容，锋尚版具备更加动感的外观套件和多种驾驶模式，但在座椅调节方式、全景天窗这些地方做出了牺牲，两车价格差别只有3000元，性价比差不多，如果想将动感进行到底，那运动版显然更如意一些。三、混动版怎么选？混动版值不值得选？这是个比较俗的问题，也很好解释，同配置的混动版要比汽油版2.5L贵了2万，配置上没什么差异，计算下差价和油费的关系就都知道值不值了，车辆使用频率越高肯定就越值得考虑混动版。混动版选哪款？和2.5L一样，混动版也是提供了豪华版和旗舰版两款车型，配置差别也与2.5L车型一致，旗舰版比豪华版贵了4万，所以从性价比的角度来看，豪华版肯定要高一些。推荐车型：毫无疑问是性价比最高的车型，也应该是未来的销售主力2.5L+8AT动力是很大的卖点，只可惜较高的配置拉高了售价如果用车频率很高，这是个很实惠的选择结语：2.0L车型未来一定会是新一代凯美瑞的销售主力，因为它具备最突出的性价比，其实我个人更喜欢2.5L车型，不过它的配置起步较高，影响了性价比，但为技术买单我还是觉得值得。至于混动车型，出于使用成本的考虑，它不会适合所有人，而且随着本田、通用混动技术的兴起，丰田在这个领域也已经不是唯一的选择了。 +http://news.163.com/17/1122/19/D3SCU2OH000189FH.html +他们做了啥 习近平给他们回信了 + + （原标题：他们做了啥，习近平给他们回信了） + 【学习进行时】11月21日，习近平给被称为“红色文艺轻骑兵”的人们回了一封信。他们是谁？他们有着怎样的历史和故事？新华社《学习进行时》原创品牌栏目“讲习所”带您探寻究竟。总书记的嘱托：永远做草原上的“红色文艺轻骑兵”近日，苏尼特右旗乌兰牧骑的16名队员给习近平总书记写信，汇报乌兰牧骑60年来的发展情况，表达为繁荣发展社会主义文艺事业作贡献的决心。21日，习近平给他们回信了！习近平在回信中说，从来信中，我很高兴地看到了乌兰牧骑的成长与进步，感受到了你们对事业的那份热爱，对党和人民的那份深情。习近平指出，乌兰牧骑是全国文艺战线的一面旗帜，第一支乌兰牧骑就诞生在你们的家乡。60年来，一代代乌兰牧骑队员迎风雪、冒寒暑，长期在戈壁、草原上辗转跋涉，以天为幕布，以地为舞台，为广大农牧民送去了欢乐和文明，传递了党的声音和关怀。习近平表示，乌兰牧骑的长盛不衰表明，人民需要艺术，艺术也需要人民。在新时代，希望你们以党的十九大精神为指引，大力弘扬乌兰牧骑的优良传统，扎根生活沃土，服务牧民群众，推动文艺创新，努力创作更多接地气、传得开、留得下的优秀作品，永远做草原上的“红色文艺轻骑兵”。乌兰牧骑：“以天为幕布，以地为舞台”乌兰牧骑的蒙古语原意是“红色的嫩芽”，后被引申为“红色文艺轻骑兵”，是适应草原地区生产生活特点而诞生的文化工作队，具有“演出、宣传、辅导、服务”等职能，深受广大农牧民欢迎。1957年，苏尼特右旗建立了内蒙古第一支乌兰牧骑。解放前，苏尼特右旗人民群众的文化生活可以说是空白的，全旗有极少数的民间艺人为王府服务，普通老百姓没有欣赏歌舞的权利。1949年以后，在中国共产党的领导下，苏尼特右旗民间文艺活动开始活跃。同年10月，苏尼特右旗人民政府在温都尔庙成立文化室，组建农牧民业余文艺宣传队。工作重点为宣传党的方针政策和路线，为农牧业生产服务，为普及文化教育服务。由于文化室业余文化宣传队的组织和演出方式不适应牧区地广人稀的特点，1957年，内蒙古自治区文化厅党组决定改造旗县文化室，组织小型、流动、多功能的文艺工作队伍。1957年6月17日，全国第一支乌兰牧骑宣告成立。“过去牧区的路都是勒勒车走出来。”年逾八十的伊兰是乌兰牧骑第一批队员，回忆起当时的情形，她记忆犹新。最初，这支乌兰牧骑只有9名演员，带着马头琴、四胡、三弦等几件简单乐器，他们深入牧区巡回演出，哪怕只有一个农牧民，也会照演不误，受到广大牧民群众的高度赞扬。目前，内蒙古草原上活跃着75支乌兰牧骑，每年演出超过7000场。习近平的回信全文苏尼特右旗乌兰牧骑的队员们：你们好！从来信中，我很高兴地看到了乌兰牧骑的成长与进步，感受到了你们对事业的那份热爱，对党和人民的那份深情。乌兰牧骑是全国文艺战线的一面旗帜，第一支乌兰牧骑就诞生在你们的家乡。60年来，一代代乌兰牧骑队员迎风雪、冒寒暑，长期在戈壁、草原上辗转跋涉，以天为幕布，以地为舞台，为广大农牧民送去了欢乐和文明，传递了党的声音和关怀。乌兰牧骑的长盛不衰表明，人民需要艺术，艺术也需要人民。在新时代，希望你们以党的十九大精神为指引，大力弘扬乌兰牧骑的优良传统，扎根生活沃土，服务牧民群众，推动文艺创新，努力创作更多接地气、传得开、留得下的优秀作品，永远做草原上的“红色文艺轻骑兵”。习近平2017年11月21日 +http://news.163.com/17/1121/19/D3PQJTJR000189FH.html +习近平给兰牧骑队员们的回信|全文 + + （原标题：习近平总书记给内蒙古自治区苏尼特右旗乌兰牧骑队员们的回信） + 苏尼特右旗乌兰牧骑的队员们：你们好！从来信中，我很高兴地看到了乌兰牧骑的成长与进步，感受到了你们对事业的那份热爱，对党和人民的那份深情。乌兰牧骑是全国文艺战线的一面旗帜，第一支乌兰牧骑就诞生在你们的家乡。60年来，一代代乌兰牧骑队员迎风雪、冒寒暑，长期在戈壁、草原上辗转跋涉，以天为幕布，以地为舞台，为广大农牧民送去了欢乐和文明，传递了党的声音和关怀。乌兰牧骑的长盛不衰表明，人民需要艺术，艺术也需要人民。在新时代，希望你们以党的十九大精神为指引，大力弘扬乌兰牧骑的优良传统，扎根生活沃土，服务牧民群众，推动文艺创新，努力创作更多接地气、传得开、留得下的优秀作品，永远做草原上的“红色文艺轻骑兵”。习近平2017年11月21日 +http://news.163.com/17/1121/12/D3P0J48L00018AOQ.html +习近平致首届丝绸之路沿线民间组织合作论坛贺信 +新华社北京11月21日电首届丝绸之路沿线民间组织合作网络论坛21日在北京召开。国家主席习近平向论坛致信祝贺。全文如下：习近平主席致首届丝绸之路沿线民间组织合作网络论坛贺信值此首届丝绸之路沿线民间组织合作网络论坛开幕之际，我谨代表中国政府和中国人民，并以我个人的名义，向论坛召开表示热烈的祝贺！向出席论坛的各国民间组织代表和各界人士表示诚挚的欢迎！“一带一路”倡议提出以来，从愿景转变为现实，取得了众多建设成果。实践证明，加强“一带一路”国际合作，为维护世界和平、促进共同发展提供了新平台、注入新动力。民间组织是推动经济社会发展、参与国际合作和全球治理的重要力量。建设丝绸之路沿线民间组织合作网络是加强沿线各国民间交流合作、促进民心相通的重要举措。希望与会代表以这次论坛为契机，共商推进民心相通大计，为增进各国人民相互理解和友谊、促进各国共同发展、推动构建人类命运共同体作出贡献！祝首届丝绸之路沿线民间组织合作网络论坛取得成功！中华人民共和国主席 习近平2017年11月21日于北京 +http://news.163.com/17/1122/10/D3REH7OO000189FH.html +多地宣传解读十九大精神 + + （原标题：宣讲入脑入心 道理讲活讲新（认真学习宣传贯彻党的十九大精神·聚焦基层宣讲）） + 江西家常话语接地气本报南昌11月21日电（记者魏本貌）11月20日上午，“草根名嘴”杨会军和南昌市青云谱区惠民社区的居民们，边拉家常，边宣讲十九大精神和习近平新时代中国特色社会主义思想。“小区里80%以上是老人家，养老方面有什么说法？”居民郭丽华问。“十九大报告指出，推进医养结合，加快老龄事业和产业发展。”杨会军说，“咱们青云谱区正在建设13个居家养老服务点，老年人在家门口就能享受多样化服务。”“十九大报告，您最关注的一句话。”南昌八一公园内，部分已经征集到的话语正在展出，将基层干部群众的心里话与十九大精神有机对接。请身边人拉家常话，用心里话对接大道理。泰和县“民嘴讲堂”、景德镇珠山区“小巷讲堂”、萍乡市“百姓身边故事宣讲团”……江西各地组建起数百个基层宣讲团，不断创新宣讲方式。结合省委常委理论学习联系点制度，江西省级领导干部赴各地基层带头宣讲十九大精神。邀请十九大代表、省直单位主要负责同志组建省委宣讲团，深入基层一线，在宣讲的同时进行调查研究，倾听广大干部群众心声，让十九大精神播撒在基层干部群众心间，并化为行动、落到实处。四川特色文艺送大餐本报成都11月21日电（记者刘裕国）“十九大报告对实施乡村振兴战略作出了部署，我们不仅要脱贫，更要致富！”11月15日，四川红原县邛溪镇玛萨村党支部副书记依姆青听了宣讲后高兴地说。四川省委高度重视党的十九大精神宣讲工作，迅速组织省、市、县三级党委宣讲团开展声势强大、全域覆盖的集中宣讲，同时组织动员全省各地开展丰富多彩、富有成效的群众性宣讲。阿坝州、凉山州、甘孜州等地组织少数民族语言和汉语“双语”宣讲团，一边双语宣讲十九大精神，一边为群众排忧解难送温暖。凉山州的摩托车“突击队”、德阳的基层“轻骑兵”、达州的“挎包宣讲队”、巴中的“扁担小分队”……部分地区针对山高路远、村落零散的实际，因地制宜组建“马背宣讲团”穿梭于各牧民点进行宣讲。自贡市创作60余幅农民漫画作品诠释十九大精神；泸州的金钱板、广元的车马灯、乐山的“文瀚嘉州·百姓直通车”、南充的数来宝、凉山州的情景剧……四川各地创作、编排、导演一大批群众喜闻乐见的文艺节目，引领群众在演艺中学习、在学习中演艺，既宣传解读了十九大精神，又给群众送去了文化大餐。河南分类定制传政策本报郑州11月21日电（记者朱佩娴）“大学生回农村创业有前途吗？”面对新乡医学院大学生的提问，11月20日上午，党的十九大代表、辉县市张村乡裴寨村党支部书记裴春亮耐心讲解：“党的十九大报告提出了乡村振兴战略。如何振兴？就要有新思维、新技术、新农民。只要大学生有想法、有技术、有魄力，回乡创业一定前途光明。”连日来，裴春亮先后宣讲20多场（次），近万人聆听了报告。针对不同的群体，宣讲内容也会微调：面对机关干部，他会着重讲党员干部干净做人、静心做事；面对院校师生，他会着重讲青年学生奋发有为、大展身手……“例子都是分类定制，力争把党的政策、党的意志、党的温暖传达到老百姓的心头。”裴春亮说。党的十九大代表、郑州圆方集团党委书记薛荣的宣讲也是如此。她还自制宣讲海报，把党的十九大民生看点通过10张卡通图片展现出来；在直播应用中直播十九大宣讲，获得10万多次点播。河南宣讲团共组织省委宣讲团12组24人、十九大代表报告团5组15人到全省各地宣讲，计划宣讲130场，宣讲团成员均认真备课，切实把党的十九大精神讲全、讲透、讲明白。甘肃贴近群众把准脉本报兰州11月21日电（记者银燕、柴秋实）“乡亲们，你们所想的，翻开十九大报告都有体现。”在甘肃省武威市凉州区下双镇日光温室现代农业园一间活动室内，武威市委讲师团副团长张生龙的宣讲吸引了种植大户们。为深入学习宣传贯彻党的十九大精神，甘肃省委、省政府领导干部带头深入分管的部门、行业系统和所联系的县、乡、村进行宣传解读。一批政治素质强、政策理论水平高的领导干部、理论工作者，组成了各级宣讲团深入农村、社区、机关、企业、校园，将十九大精神带到陇原大地的每个角落。各地结合本地区实际开展对象化、分众化的宣讲活动，突出时代性、贴近性，让群众听得懂听得进。近日，在兰州市团结新村街道，十九大代表、甘肃日报社时政部首席记者徐爱龙的宣讲现场，不时会有听众站起来提问。互动式的交流，让大家听得入神，现场响起阵阵掌声。在深入基层宣讲的同时，徐爱龙还积极创新方式，利用微信公众号宣讲十九大精神和习近平新时代中国特色社会主义思想。 +http://news.163.com/17/1122/11/D3RFAL69000189FH.html +十九大后六项民生福利待查收 + + （原标题：十九大后深改组首次@你 六项民生福利待查收） + +http://news.163.com/17/1122/11/D3RFO07F000189FH.html +温州洞头蓝色海湾整治:生态养海 + + （原标题：温州洞头蓝色海湾整治：生态养海 拥海而兴） + 洞头仙叠岩段海洋生态廊道。“全靠修复了这片沙滩！”这是东岙村人给出的答案，言语里满是自豪。2016年，总投入4.76亿元的蓝色海湾整治项目落户洞头。一年多来，随着项目的实施，人们欣喜地发现，赤潮减少、海水变清、沙滩又回到了最初的模样。在沙滩的勾连下，人海相亲相近，小渔村也由此兴盛起来。以海兴国、人海和谐。十九大报告指出，人与自然是生命共同体，人类必须尊重自然、顺应自然、保护自然。人类只有遵循自然规律才能有效防止在开发利用自然上走弯路，人类对大自然的伤害最终会伤及人类自身，这是无法抗拒的规律。对此，洞头人的感触尤为深刻。14年前，习近平总书记在浙江工作期间，曾到洞头列岛调研半岛工程建设。在发展的关键时期，他曾嘱咐洞头人，“要特别重视生态环境保护工作，坚持走可持续发展之路，做好山体、岛礁等生态环境资源的保护”“真正把洞头建设成为名副其实的‘海上花园’”。而今，半岛工程已经建成，洞头也由县变区，但不曾变化的，是洞头人保护海洋的初心。党的十八届五中全会确立绿色发展理念后，洞头更是率全国之先，明确不再围垦滩涂，并积极开展蓝色海湾整治行动，做好保护、修复、提升三篇文章，加快建设“海上花园”，谱写了一首新时代人海和谐的动人恋曲。一片被修复的沙滩“自从东岙沙滩修复后，今年营业额至少翻了一倍。”东海渔家老板洪求强的朋友圈，记录了东岙村的点滴变化：白净沙滩映衬着碧海蓝天，沙滩边环绕着渔家民宿。135米长的沙滩上，孩子们追逐嬉戏。“在家门口吹海风、玩沙子，仿佛回到了从前。”洪求强说。“回到了从前”，是满满的欣喜，也是对现今洞头沙滩整治修复成果的认可。上世纪80年代末，在填海造地、取沙建房、建造码头的影响下，一处处洁白美丽的沙滩，开始消失于视野。挖土车在沙滩上不分日夜地开采，面积达1.84万平方米的东岙沙滩，最后竟只剩下裸露的碎石。人们无度的索取，换来大海无声的抗议。那些年里，洞头海洋生态环境也越来越差：赤潮频频出现，羊栖菜大量减产，养殖户亏损严重。海水受到污染，辛苦捕来的海鲜，不敢吃了；岛礁破坏严重，原本珍贵的贝类，逐渐消失。靠海吃海的日子难以为继，小渔村日渐颓败，不少村民只得进城打工。现实面前，洞头人幡然醒悟，靠破坏海洋生态环境换来的发展，不可能长久。2016年，蓝色海湾整治项目落户洞头，东岙段被纳入项目建设重点，其中包括沙滩修复和海洋生态廊道等建设。2017年1月，投资总概算达850万元的东岙沙滩修复工程启动。当东岙村前的沙滩开始吹沙、施工车进驻后，村民们满心欢喜。7月，洞头区这片最有名的沙滩终于恢复原貌，吸引了天南地北的游客。原本离去的村民，再度回到村里，办起渔家乐和民宿。洪求强的生意越做越红火，曾经的小门面，如今也摆开了阵势。沙滩从有到无、从无到有，村里环境好了，带动的是整个东岙村旅游业的提质增效。眼下，这个陆域面积仅0.35平方公里、常住人口仅1500多人的小渔村，涉旅人员就达600余人。旺季时，东岙村50家民宿，几乎天天客满、一房难求。“十九大提出建设美丽中国，要求我们实施重要生态系统保护和修复重大工程，加大生态系统保护力度。身为海岛区县，要在保护的同时，加快修复海洋生态，还海洋以宁静、和谐、美丽。”区海洋渔业局副局长李昌达说。一块被拯救的礁石或许体会过失去的痛苦，如今，洞头人对海洋资源倍加珍惜。在鹿西乡，工作人员叶明伟带我们看了一块并不“壮观”的礁石：“为了保护这块天然‘老虎礁’，鹿西人迫切想造的综合交通码头，也往后推迟了一年。”鹿西乡位于洞头区东北部的鹿西岛上，乡以岛为名，至今岛民依旧靠船出行。1992年改造的鹿西港码头，是乡里最主要的码头。由于狭小和老旧，许多大型船只难以靠岸，已严重制约了鹿西乡的经济社会发展。2015年，鹿西综合交通码头开始筹备。最初，码头选址在鹿西岛西南方的“老虎礁”，该处水域开阔，水深条件良好，临近老码头，交通便利。工程即将施工时，部分乡民提出意见，认为“老虎礁”是鹿西岛的标志性景观，应当予以保护。面对乡民的诉求，洞头区政府确立保护不可再生的岸礁海岸线旅游资源的政策，并对原设计方案进行调整，“现在码头选址向西北方向横向平移了200米，移至已开发利用的人工岸线区域，并对原方案进行集约化设计，通过提升码头综合利用率及管理的自动化水平，以减少占用宝贵的岸线资源。”洞头区交通局副局长谢铭说，为此工期不惜延误一年，造价增加约200万元。不只是鹿西综合交通码头，小三盘通村公路、中心渔港港区道路二期工程等项目，均为了保护沙滩、海湾、岸礁等优质自然海洋生态资源，而改变了原来的方案和线路。“发展”与“保护”，并非总是并行不悖，更好地“有所为”，坚决地“有所不为”，这是洞头的取与舍，也是他们守护海洋的决心。　一处被叫停的围垦区从码头的重新规划、道路的重新设计，再到滩涂围而不填的创新，折射的是新时代洞头人的“耕海之道”。眼下，“梦幻海湾项目”正在建设中。这是洞头迄今为止，单体投资额最大的项目，不过它的“看点”并不在此，“人造蓝海、围而不填”才是亮点所在。2015年，中国大部分沿海地区还在向海洋寻求更多发展空间之时，洞头就明确，今后对新增的涉海工程，不得进行围填海审批；对早已确权可填的3710亩海域，则通过围而不填的创新之举，尽最大可能保护海洋生态。“梦幻海湾模式”，正是围而不填的一种做法。这一做法，得到了国家海洋局的赞许与支持。围而不填的意义何在？“‘梦幻海湾’整个项目，将以透水构筑物的形式建造，不对海域进行填海，全部打桩，然后再在上面建造相关建筑物，建筑物下面依然是海。”李昌达表示，海洋是洞头的命脉。一个项目要用海，首先考虑对生态环境会否造成破坏，如果会，宁可不要金山银山，也要绿水青山。如今，蓝色海湾整治通过实施岸线资源整治修复、沿海村居改造升级、生态廊道建设等项目，海岸线变靓了、村容村貌变净了、海岛变美了。美丽海岛轮廓逐步呈现，引来大批客商投资，渔民逐步实现转产转业。尝到生态回馈的洞头人更加清醒，选择项目更加挑剔严格。他们坚持经济生态化目标，政绩的“指挥棒”，清晰指向绿色生态、蓝色发展。近年来，洞头投放人工鱼礁9万余立方空体，建成152公顷海洋牧场示范区和1053公顷省级水生生物增殖放流区，助推振兴东海鱼仓。在南、北爿山（鹿西鸟岛）实施筑巢引鸟工程，有效保护51种海洋鸟类繁衍生息。同时，洞头不断创新制度建设。《洞头国家级海洋公园总体规划》在全国首个获批实施；出台海洋生态红线划定方案，在县一级率先实施海洋生态红线制度；编制完成洞头国家级生态保护与建设示范区建设方案、海域利用规划、海岛保护规划、海域海岛整治修复规划等。洞天福地，从此开头。从上世纪的伸手索取、肆意开发，再到如今的生态养海、反哺大海，洞头人坚信，海洋不仅意味着生命，意味着资源，更意味着未来。如今，行走在这座拥海而兴的小岛上，我们随处可以感受到尊重自然、顺应自然、保护自然的海洋生态文明理念。 +http://news.163.com/17/1122/23/D3SPFVUT0001875O.html +津巴布韦执政党证实：姆南加古瓦已经回国 + + （原标题：姆南加古瓦已经回到津巴布韦） + 据美联社消息，津巴布韦执政党证实：被推举为津巴布韦新任总统的姆南加古瓦已经回国。 +http://news.163.com/17/1122/22/D3SN231D0001899O.html +台湾云林县发生5.2级地震 福建网友：震感明显 +中国地震台网正式测定：11月22日22时20分在台湾云林县（北纬23.71度，东经120.60度）发生5.2级地震，震源深度16千米。另据东南早报微博，台湾发生5.2级左右地震，泉州厦门网友反映震感明显。 +http://news.163.com/17/1122/15/D3RVPKUO0001899O.html +一架美运输机在日本冲绳海域坠落 8人获救3人失踪 + + （原标题：一架美军运输机在日本冲绳海域坠落 3人下落不明） + 该架美军C2运输机是位于日本神奈川县横须贺基地的美军核动力航空母舰“里根号”的舰载机。据称，当时美军正同日本海上自卫队参加训练。美军曾通知日方发动机或有故障。没有消息表明运输机上有日本自卫队员。目前，日本防卫省正向美军了解详细情况。日本防卫大臣小野寺对记者表示，“现在美军正同日本海上自卫队进行搜索，自卫队已派出军舰和船只。”他还表示，“将尽力协助搜救下落不明的人员。由于美军飞机事故不断，希望美方今后能够做到安全飞行。”C2运输机提供航空母舰舰队关键的后勤支援，即主要用于海上航空母舰和陆上海军基地之间士兵及物资等的运输。它是一款双发涡桨舰载运输机，内部最多可乘坐26人。为了保证从航空母舰起飞的速度，C2运输机还装有被称作“弹射器”的特殊装置。美军机飞行事故不断2017年10月11日下午，在日本冲绳县东村高江地区美军北部训练场内，一架美军大型运输直升机CH-53着陆后起火，现场燃起滚滚黑烟。2016年12月13日夜间，驻日美军一架MV－22“鱼鹰”倾转旋翼机在冲绳县宇流麻市海域碰撞着陆，5名机组人员负伤后获救。2016年12月7日晚，一架属于驻日美军岩国基地的海军陆战队F/A－18战斗机在高知县附近海域坠落。2016年9月，美国空军嘉手纳基地的一架美军AV-8鹞式战斗机在冲绳本岛北部的边户岬以东约150公里的海域坠落。约40分钟后，驾驶员获救。另据中新网11月22日电，据日媒报道，日本防卫相小野寺五典22日表示，美军核动力航母“罗纳德·里根”号舰载机中的一架C-2运输机坠入冲之鸟礁近海。机上11人中至少2人下落不明。根据美国海军第七舰队官网22日消息，美国海军一架搭载11名机组成员和乘客的飞机在日本冲绳东南部海域坠海。第七舰队方面称，事发时，这架飞机正飞往“罗纳德·里根”号航母，目前该航母正在菲律宾附近海域。消息称，“罗纳德·里根”号正在执行搜救行动，舰上医疗人员将对获救人员的情况进行评估。目前尚不清楚这起事故的原因。 +http://news.163.com/17/1122/16/D3S3GMEF0001875N.html +武警调整部队部署和兵力调动制度:由中央军委规定 + + （原标题：关于<关于中国人民武装警察部队改革期间暂时 调整适用相关法律规定的决定（草案）>的说明——2017年10月31日在第十二届全国人民代表大会常务委员会第三十次会议上） + 关于《关于中国人民武装警察部队改革期间暂时调整适用相关法律规定的决定（草案）》的说明——2017年10月31日在第十二届全国人民代表大会常务委员会第三十次会议上中国人民武装警察部队司令员 王宁全国人民代表大会常务委员会：我受国务院、中央军委委托，现对《关于中国人民武装警察部队改革期间暂时调整适用相关法律规定的决定（草案）》作说明。一、暂时调整适用的必要性为了更好地坚持党对武装力量的绝对领导，贯彻军委主席负责制，建设一支听党指挥、能打胜仗、作风优良的现代化武装警察部队，高效完成新形势下维护国家安全和社会稳定的使命任务，党中央和中央军委对武警部队改革作出了重大决策部署。党的十八届三中全会作出的《中共中央关于全面深化改革若干重大问题的决定》，明确要求“优化武装警察部队力量结构和指挥管理体制”；党中央批准的深化国防和军队改革总体方案明确，按照“军是军、警是警、民是民”的原则，调整武警部队指挥管理体制，优化力量结构和部队编成。《中央军委关于深化国防和军队改革的意见》强调要加强中央军委对武装力量的集中统一领导，并对贯彻中央决策部署作了具体安排。当前，武警部队改革正在按照党中央和中央军委部署全面推进。现行《中华人民共和国国防法》、《中华人民共和国人民武装警察法》对武警部队的领导指挥体制、职能任务、警衔制度、保障体制、部队部署和兵力调动使用等作了规定。为了保证武警部队改革于法有据、稳妥推进，需要对上述法律规定作出修改。考虑到改革任务较为紧迫，而法律修改周期较长，有必要请全国人大常委会作出暂时调整适用相关法律规定的决定。二、暂时调整适用的主要内容一是调整领导指挥体制。强化党中央和中央军委对武警部队集中统一领导，坚定贯彻军委主席负责制，按照“军是军、警是警、民是民”的原则，调整武警部队指挥管理体制，优化力量结构和部队编成，实现领导管理与高效指挥的有机统一。二是调整职能任务。按照党中央和中央军委赋予的新时代使命任务，武警部队将主要担负执勤、处突、反恐怖、海上维权、抢险救援、防卫作战等任务，拓展了维护国家领土主权完整和国家安全职能。三是调整警衔制度。根据武警部队领导指挥体制改革和军官军衔制度改革情况，调整改革武警部队警衔的设置、授予、晋升和批准权限等规定。四是调整保障体制。根据武警部队领导指挥体制改革要求，对武警部队的后勤、装备实行统一规划、统一保障、统一管理、统一审计监督，提高保障效益。五是调整部队部署和兵力调动使用制度。由中央军委对武警部队部署和兵力调动使用作出规定。三、暂时调整适用的组织实施本决定的组织实施，按照党中央的有关决定、国务院和中央军委的有关规定执行。改革措施成熟后，将及时提出修改《中华人民共和国国防法》、《中华人民共和国人民武装警察法》等有关法律的议案，按照立法权限报批。《关于中国人民武装警察部队改革期间暂时调整适用相关法律规定的决定（草案)》和以上说明是否妥当，请审议。 +http://gov.163.com/17/1122/13/D3RO5MKS00239803.html +农民工断指送医遇堵 河南交警逆行护送 + + （原标题：暖闻｜农民工手指被锯断送医遇堵，河南高速交警逆行一路护送） + 11月20日上午10点，一辆警车打着双闪鸣着警笛，从连霍高速河南开封服务区南半幅逆行下站，警车后还跟着一辆轿车。轿车里是一对父子，父亲在工地干活时被电锯锯断两根手指。男子手指不小心被锯断急就医向警方救助。警方供图开着警车为这对父子开道的，是河南省公安厅高速交警总队五支队副支队长马国宝和民警李飞。马国宝11月21日告诉澎湃新闻（www.thepaper.cn），20日早上郑州附近高速路段大面积起雾，他接到任务在连霍高速开封西服务区进行路面分流。当日上午9点半，雾散了一些，但高速公路北半幅由于交通管制，车辆非常拥堵。“我们往西查看路况，绕了一圈后回到开封服务区南半幅。我们看路况有所缓和，便向上级联系报告路况。就在这个时候，一个男子就跑到我们警车旁，说他父亲手指不小心被锯断了，因为车流拥堵，北边过不去。”马国宝说。看男子神情紧张，马国宝赶忙走到车前，伤者（男子父亲）此时坐在副驾驶位上，左手用一条白色毛巾裹着，但还是止不住血，加上天气寒冷，显得很痛苦。“由于雾天原因，连霍高速由开封到郑州方向车辆十分拥堵，因在郑州就实行了交通管制，反方向并不拥堵。”马国宝当机立断，决定带父子二人逆行沿连霍高速南半幅下站，然后送往开封西汽车站。20分钟后，警车将伤者送抵开封西汽车站后因为有任务返回。伤者的儿子冲着马国宝和李飞深深鞠了一躬后，便驱车前往汽车站附近的解放军第一五五医院治疗。马队长表示，自己并没有做什么，希望群众们在遇到此类困难时，要及时向附近民警寻求帮助。 +http://news.163.com/17/1122/20/D3SGINVA0001875O.html +朝鲜谴责美将其列入支恐国家名单:严重挑衅 + + （原标题：朝鲜谴责美国把朝鲜重新列入“支恐国家”名单） + 据朝中社22日报道，就美国宣布把朝鲜重新列入“支恐国家”名单一事，朝鲜外务省发言人表示，继特朗普在联合国舞台上抛出“灭绝”朝鲜的言论之后，21日给朝鲜贴上“支恐国家”标签，是对朝鲜的严重挑衅和粗暴侵害。发言人称，美国列“支恐国家”名单是旨在扼杀不听其指挥的自主国家的手段。此次，美国将朝鲜重新列入“支恐国家”名单，以切断“用于朝鲜非法的核导计划的非法资金”为名，通过涉朝后续制裁，暴露了美国欲动用一切手段和方法来扼杀朝鲜的思想和制度。发言人称，美国以对朝鲜贴上“支恐”标签来发起挑衅，却大谈“和平解决”，这使朝鲜进一步坚定“紧握核宝剑”。 +http://news.163.com/17/1122/16/D3S23VHT000187VE.html +穆加贝辞职是否会对中津关系造成影响?外交部回应 + + （原标题：外交部：中方尊重穆加贝辞职决定，他仍是中国人民好朋友） + 外交部发言人陆慷主持11月22日外交部例行记者会。问：当地时间11月21日下午，津巴布韦总统穆加贝宣布辞职。请问中方对此如何评价?穆加贝的辞职是否会对中津关系造成影响?中方现在如何评价穆加贝?中津关系长期友好，经受了时间和国际风云变幻的考验，近年来中津各领域务实合作不断推进，给双方特别是给津巴布韦人民带来实实在在好处。中方高度重视中津关系，愿同津巴布韦各方一道，推动中津友好和各领域合作不断取得新进展。穆加贝先生为津巴布韦民族独立和解放事业作出过历史性贡献，也是泛非主义运动的积极倡导者和推动者。他长期致力于中津和中非友好，为中津关系和中非关系发展作出过重要贡献。中方尊重穆加贝先生的辞职决定，他仍然是中国人民的好朋友。问：据报道，穆加贝辞职后，英、美均呼吁津巴布韦举行自由、公平大选，请问中方对此有何评价?问：据悉，前副总统姆南加古瓦即将回国接任总统，请问中方对其有何期待? +http://news.163.com/17/1122/15/D3RUBEC00001875P.html +云南一民政局被通报 70%干部职工亲属违规吃低保 + + （原标题：云南德宏一民政局被通报 70%干部职工亲属违规吃低保） + 56名干部职工中，有40名领导、干部职工及亲属违规享受城乡低保。近日，云南省德宏州纪委对外公布了这起“陇川县民政局‘靠山吃山’塌方式违纪违规案”。今年6月初，德宏州纪委发现陇川县民政局存在干部职工及亲属违规享受低保问题，随后德宏州和陇川县纪检部门迅速介入调查。调查发现，陇川县民政局56名干部职工中，有40名领导、干部职工的82名亲属不符合享受城乡低保。而部分领导干部职工的配偶及直系亲属，违规享受低保资金已达到40.5万多元。2017年7月31日，德宏州纪委对陇川县章凤镇党委书记、县民政局原局长杨恩增立案审查。德宏州纪委通报，陇川县民政局长期以来对申请享受低保人员抽查、核实、公示把关不严、监管缺失，70%以上干部职工亲属违规享受低保，把服务群众的权力当作亲属获利的“工具”。同时，陇川县民政局还违规私设“小金库”48万余元，违规审批发放抚恤金和丧葬费199.8万余元。干部职工利用职务便利收受“好处费”，其中，陇川县民政局公墓管理所所长董勒堵在2012年至2017年担任所长期间，利用职务上的影响先后2次收受墓地建造施工人员好处费1.1万余元；办公室副主任张璟利用职务便利，先后3次收受太阳能热水器安装项目人员好处费7.1万余元。多人被处理 违规低保全部收回随着调查工作的不断深入，陇川县民政局“靠山吃山”塌方式违纪违法案件被及时查处，5名班子成员、4名股所级干部受到党政纪处分，40名领导、干部职工及配偶亲属违规享受城乡低保被责令清理、清退。在涉案人员的处理中，纪检部门对陇川县民政局5名领导班子成员作出纪律处分，其中，陇川县章凤镇原党委书记、县民政局原局长杨恩增，受到留党察看二年处分、撤销行政职务、降为副主任科员。党总支副书记蔡万保，受到党内严重警告处分、免职处理。副局长董麻崩，受到党内警告处分。副局长刀保亮和老龄委办公室专职副主任郭庆昌，受到留党察看一年处分。同时，陇川县民政局公墓管理所所长董勒堵、办公室副主任张璟受到开除党籍处分，涉嫌违法问题已移交司法机关处理。社会救助股股长孟秀明、中心敬老院原院长黄国忠，受到党内严重警告处分。此外，纪检部门对陇川县民政局干部职工的亲属违规享受低保作出处理，对陇川县民政局27名干部职工及配偶直系亲属44人违规享受城乡低保资金40.5万余元予以全部收回，上缴财政，82名亲属违规享受低保从2017年8月全部予以停发。当事人：国家政策执行不到位这起案件中，原民政局局长杨恩增受到留党察看二年、撤销行政职务、降为副主任科员处分。日前，央视记者独家采访了案件主要当事人杨恩增。从2011年开始，杨恩增一直担任陇川县民政局局长；2016年7月，调任陇川县政府所在地章凤镇党委书记，但仍然兼任陇川县民政局局长。2017年6月，纪委工作人员找到了杨恩增。但是令杨恩增没有想到的是，在自己担任陇川县民政局局长期间，单位持续发生人员违纪违法案件，涉及的干部职工竟达70%。那么，为什么一个有56名干部职工的单位，违纪违法人员竟然有40多人？为什么会在享受城乡低保上出现“优亲厚友”问题？根据德宏州通报，杨恩增违反工作纪律，对陇川县民政局“靠山吃山”塌方式违纪违法问题负有领导责任。同时，陇川县民政局主要领导、班子成员带头“靠山吃山”，以权谋私、造成全局塌方式违纪违法。边查边改 以案警示案件发生后，德宏州、陇川县采取了边调查边整改的措施，以本案为警示，启动城乡低保对象精准识别专项行动。昨天（21日），记者在陇川县民政局看到，大厅悬挂了“陇川县城乡最低生活保障工作办理规范流程表”，对低保的办理流程、具体要求等方面进行了公示。工作人员介绍说，流程表是纪委对民政局案件展开调查后不久悬挂的。据工作人员介绍，今年6月初发现问题后，德宏州一方面组织力量对具体情况进行调查，一方面迅速展开整改。6月8日，德宏州全面启动城乡低保对象精准识别专项行动，针对低保工作中存在的突出问题和薄弱环节，开展低保对象精准识别，对不符合享受低保的人员全部进行了清退，制定出台了《低保经办人员亲属享受低保备案制度》，严防民政干部优亲厚友。 +http://news.163.com/17/1122/19/D3SCG5T10001875P.html +母亲因给不起儿子彩礼自杀? 官方:不满意儿子对象 +【母亲因给不起儿子彩礼轻生？ 宁陵县：系误传，不满意儿子对象自杀】近日，一则母亲因给不起儿子彩礼而轻生的视频在网络热传。今日，事发地河南省商丘市宁陵县发布通报称，网传为彩礼轻生说法不实，死者林某某是因对儿子相中的对象不满意而跳河自杀。北京青年报记者从网络视频中看到，在一条河边，一男子趴在一女性尸体上哭泣，随后突然转身跳河，后被民警和周围群众救起。负责处理此事的河南省商丘市宁陵县黄冈乡派出所民警杜传峰对媒体表示，轻生者的儿子前不久刚刚订婚，女方彩礼要求一辆车，男方这边付不起因而酿成悲剧。11月22日下午，宁陵县宣传部发通报回应此事，称网传说法不实。通报称，死者林某某因为其儿子谈对象订媒意见不一致，儿子对象与其同乡，林某某因相不中儿子谈的对象，嫌弃其个子低，林某某便以死相逼，一时想不开，骑电动车来到宁陵县黄岗镇张桥村境内废黄河境内跳河自杀。事发后，在不知真相的情况下，误认为林某某是因为高额彩礼致跳河自杀。通报中表示，事发后，临界的黄岗派出所接到报警后，及时出警将死者林某某打捞出来。死者林某某丈夫赶到现场后，见到妻子已经死亡，当时情绪失控跳河，其儿子看到父亲跳河也跳下河救父亲，现场民警随即跳入河中将父子二人救上河岸。 +http://news.163.com/17/1122/22/D3SNNCTI00018AOR.html +女子迷信算命将娃打致瘫痪 出轨被捉奸与情夫私奔 + + （原标题：妻迷信算命之言将亲子打致瘫痪 与情夫私奔6年后丈夫上电视痛诉） + 法制晚报·看法新闻(记者张恩杰)11月12日，央视12--社会与法频道《律师来了》节目以《消失的妈妈》为题，报道了陕西省神木市的货车司机闫彩斌痛诉妻子怀第二胎时，因神官算命称其腹中的孩子与其相克，为此妻子吃打胎药未将胎儿打掉。于是在怀胎四五个月时，向他提出做人流手术，他未同意。最终妻子生下孩子，取名旗旗。满月后，闫彩斌将旗旗送到农村父母家照料。闫彩斌称旗旗长到三岁，被他妻子从父母家接了回来。结果不到一个多月，妻子竟将旗旗痛打的瘫痪在床，医院下发的病危通知书显示：患儿颈髓损伤、闭合性胸部损伤，肺挫伤、肺炎、胸腔积液，身上多处骨折。后经辗转多家医院，终于救回来一条命。事发40多天后，闫彩斌才选择了报警。警方以没有证据证明有所控告的犯罪事实为由，不予立案。再后来，闫彩斌发现妻子出轨他人，被他捉奸在床。最终妻子跟着情夫离家出走，一晃六年到现在，旗旗在爱心妈妈公益慈善组织地不断接力下，于上海复旦大学附属儿科医院做保健康复治疗。目前肩关节、肘关节功能均有所恢复，大小便不再失禁，可以挨着墙角站立一分钟。此时，闫彩斌向央视《律师来了》节目组求助，提出追究妻子虐待抛弃孩子、进而出轨与他人结婚的法律责任。最终，他通过此节目选定了上海海华永泰律师事务所严嫣律师为他代理此案。从发病危通知到康复治疗 旗旗痉挛缓解大小便不再失禁看法新闻记者注意到，在这期节目一开始，就播放了一段央视记者于今年8月1日来到上海市闵行区复旦大学附属儿科医院，探望在此康复治疗的旗旗的视频短片。只见他穿着病号服，坐在轮椅上，微微活动着双手。记者问他感觉怎样，他小声回答，“比以前好些了。”据旗旗的父亲闫彩斌透露，就在2011年旗旗3岁时，其母亲将其打得瘫痪在床上。“当时他左臂骨折，只有头会动，脖子以下均不能动弹，一点知觉都没有。西安交大医院给我们家属下发的病危通知书显示：其多发伤颈髓损伤，闭合性胸部损伤，肺挫伤、肺炎，胸腔积液，伴随多种骨折。”而据复旦大学附属儿科医院儿童保健康复部副主任医师王素娟介绍，旗旗刚入该院治疗时情况比较严重。那时他的颈髓损伤已有两年多，到了后遗症期。手指没有办法打开，双腿肌肉收缩。“经过这几年的治疗，他的身体康复效果蛮不错。这表现在他的手功能有一个很好的进步。整个痉挛的情况，也有明显的缓解。他上肢可以抬得很好，肩关节、肘关节的活动恢复的不错。大小便不再失禁了，有知觉。”王素娟如是说。神官算命说腹中胎儿克她 她堕胎不成生子后常虐待孩子至于妻子为何要下狠手毒打幼子。闫彩斌说出了一个近乎荒唐的秘密。他称，妻子在怀孕时，请神官算过一命，说是腹中胎儿与她相克。她起初吃了打胎药，却未将胎儿打掉。“当她怀孕四五个月的时候，她跟我说她要做人流，我没同意让她做。就这样孩子生下来满月后，送到农村我母亲那里去抚养了。”闫彩斌如此解释说。节目中，闫彩斌提供的旗旗十六个月大时拍摄的照片显示，其留着锅盖头，喜笑颜开，穿着小蓝棉绸褂，撅着屁股在地上爬着，甚是活泼可爱。可惜好景不长，就在旗旗三岁时，其母亲突然提出要将孩子从婆家接回来，由她自己抚养。“我想她能自己主动接回来，这样以后母子相处会好一些。但没想到她将孩子接回来后，我在外开大货车，十天半月回一次家，就会发现旗旗身上有淤青，颈部、背部、腿上到处都是。为此，我问妻子这咋回事，她说是楼梯上摔得。”闫彩斌在节目中如是说。紧接着其表示，“有一次，我在家中看到旗旗将大便拉在地上，我妻子呵斥他去吃。我看到后将孩子抱起来，和妻子吵了一架。妻子带着大儿子出走，一晚上没有回家。第二天一早，我将孩子托付给我的一个姨妈，我妻子中午回来后接孩子，对我姨说，要报复我。”这次争吵过后的第三天，妻子告诉他，她打孩子了，胳膊响了一声。于是他发现旗旗胳膊有些红肿，他以为没什么大碍。休息一晚上，次日天不亮他就开车去干活了。走在半路上，妻子打电话给他说孩子在发高烧。他连忙折回家中将旗旗带去神木县高新医院，给其降温输液。输了一整天液体，其小便却尿不下来。于是他连夜又带着旗旗去了榆林市星元医院，各方面的检查都做了，却未查出什么毛病。孩子受伤40天后他才报警 警方以查无证据为由不予立案“当时孩子躺在病床上，眼睛都睁不开，我叫一声他的名字，他流着眼泪。看得我的心都碎了。后来我买了飞机票，带他到西安儿童医院，也未检查出什么毛病。紧接着又去了西安市中心医院，该院诊断说是颈髓损伤，让我将他转到西京医院;西京医院说病情太重，没有办法接受。就这样，我辗转将旗旗送到西安交大医院，下发了病危通知书，抢救了两天，才渡过危险期。”谈起孩子受重伤后一波三折转院的经历，闫彩斌至今记忆犹新。其还表示，转院过程中，妻子一直跟随在他和孩子身边。妻子称她听见孩子在外边哭，就将孩子带回家。但她对医生却说，旗旗是从3米高的轮胎垛上掉下来的。“我认为孩子是被她打成了那样，否则一个三岁的小孩子，如何爬上三米高的轮胎垛，再说我家附近也没有轮胎垛。”节目中，闫彩斌的大儿子作为事发时在家里唯一的见证人，他接受《律师来了》节目组采访时称，弟弟是被他妈妈拿着扫床的刷子打成了那样。值得一提的是，闫彩斌一直忙着给孩子看病，未就孩子的伤情做司法鉴定。直到事发40多天后，他才选择了报警。据神木市公安机关的不予立案通知书显示，“我局经审查发现，没有证据证明有所控告的犯罪事实。”妻子出轨被他捉奸在床 抛夫弃子离家出走6年未有音讯由于自己的疏忽，证据不足，无法将妻子绳之以法后，闫彩斌却又发现妻子背着他和其他男人偷情。“刚开始我只是怀疑，后来我在招待所将她逮着了。我看到她们躺在一张床上。我妻子脱得只剩下一个胸罩，其他什么都没穿。而那个男人贺某则穿着衣服。他们不肯承认，这事也就一直拖着，直到他们私奔，离家出走。到现在已经有6年杳无音讯了。”闫彩斌如此透露说。他称，妻子找不见后，他去过妻子的娘家，发现丈人丈母娘一家也搬走了。坊间有人传言妻子和那个情夫贺某有了新家庭，还生了一个孩子，在过年时曾带回来过。对此，贺某的妻子则接受《律师来了》节目组采访时称，她去榆林做完剖腹产手术回到家中，发现丈夫贺某和闫彩斌的妻子同在屋内，贺某只说他们是朋友关系。再后来，贺某也跟着闫彩斌的妻子一起消失。“这些年，他(贺某)再也没回来过。我不清楚他们是否生了孩子。我家的户口上，只有我和贺某生的两个孩子，我将户口给闫师傅看过了。”镜头里，贺某在农村老家的妻子如是说。医疗费均靠慈善组织捐款 依靠父母辛苦劳作买菜钱度日看法新闻记者还注意到，节目中，闫彩斌称妻子失踪后，他陪着孩子在上海看病，每月1.3万元的医疗费用均来自爱心妈妈慈善公益组织的接力捐款。他自己没有经济来源，很多时候还要靠农村父母每月少则三五百，多则七八百元的接济勉强度日。对此，闫彩斌的老父亲则站在神木市大柳塘镇的自家菜地里，接受《律师来了》节目组采访时称，他现在一边要照顾正在上学的大孙子(即闫彩斌长子)，一边还要种菜，拿到集市上去买。收成好的话，一年能赚1万元，然后用这些钱给小孙子旗旗看病，以及家里的其他吃穿缝补等生活费用。提起自己含辛茹苦拉扯大的小孙子却有这般遭遇，闫老伯双眼里噙满了泪花，哽咽着说他心里实在憋屈，很难受。在视频短片里看到这一幕，节目现场的闫彩斌突然情绪失控，小声抽泣了起来。他称老父亲都已经60多岁的人了，还要在地里劳苦，太不容易。他母亲身体也也不太好，经常生病。“每当想起我妻子虐待完孩子，抛下一家老小，和情夫跑了，自此杳无音讯。我就恨不得将她千刀万剐。并将家里有关她的照片撕成两半，以此来解恨。”闫彩斌指着镜头里出现的被他撕成两半的妻子的照片如是说。就此，现场有观察员对于闫彩斌的行为点评到，现在不是埋怨的时候，作为一个聪明的男人，在摔跟头时，要学会反思，为何家庭成了这样。要从自己身上找问题。首先作为一个30多岁的年强力壮的汉子，不能再靠60多岁的农村父母接济度日，也不能总依靠公益慈善组织的爱心捐款。而应该自食其力，在上海边打工边给孩子看病。节目最后，闫彩斌提出了自己的诉求，称要给孩子讨个公道，能否告孩子母亲重婚罪，遗弃家庭成员罪，虐待罪?对此，现场四名律师均结合闫彩斌所陈述的事实从法律角度对这几项罪名进行了分析。最终闫彩斌选定了上海海华永泰律师事务所严嫣律师为他代理此案。看法新闻记者将在后续追踪报道里，专访严嫣律师，对于此案中涉及的这几项罪名及一些法律疑点进行解答。 +http://news.163.com/17/1122/18/D3S9E4VL0001875P.html +8岁男孩疑似坠井身亡 家属质疑:井口还没他肩膀宽 + + （原标题：希望学校男童井下死亡之谜：肩比井口宽，校内有施工队） + 这是一口直径约20厘米的井，比一张A4打印纸的短边还少1厘米，一个成年人的脚掌踩在井口会被卡住，起初，没有人把它和一个失踪的8岁男孩联系在一起，直到11月20日，男孩失踪的第6天，遗体从3米多深的井里被发掘出来。孩子课间失踪了?这口井，座落在在安徽阜阳市临泉县医药希望学校内的一片工地旁，失踪男孩巴天宇，是这所学校一年级的学生。医药希望学校是一所规模较大的小学。巴天宇的父亲介绍，学校一年级有9个班，全校32个教学班，学生1998人。学校上午一共有四节课，最后一节课的铃声每天会在十点四十分准时响起。11月15日这天，第四节课一开始，一年级2班的班主任张老师就发现坐在第一排的巴天宇不见了。巴天宇没请过假，此前的三节课也都在座位上正常上课。张老师介绍，天宇之前出现过不按时上课的情况。巴天宇是个不让人省心的孩子，他的母亲徐仅仅没少接到老师的电话。老师说天宇不爱学习，因为爱稿小动作，天宇还被调到第一排靠墙坐，这个位置在老师眼皮底下。发现天宇没在课堂，张老师立刻派班长和几名同学去校园里找他回来上课，厕所、操场都去了，找遍所有能找的地方，还是没找到他。第四节课很快就结束了，天宇还是没出现。上午将近11点，天宇的姥姥做好午饭，出门往学校方向走，准备接外孙回家。学校虽然提供午餐，但天宇的父母觉得在家里吃更放心，况且天宇的家跟学校只有一墙之隔，走路也就五分钟，因此他平时都回家吃午饭。姥姥刚走到学校门口，手机就响了。电话是班主任打来的，问她：天宇是否提前回家？双方一沟通，发现天宇去向不明。姥姥顾不上吃饭，从上午11点找到了下午1点多，也没找到外孙，于是她报了警。天宇的父母巴玉和徐仅仅都在浙江金华，去年，他们开了一家馒头店。天宇上学前，跟在父母身边在浙江“飘着”，去年8月份，才被送回老家阜阳。11月15日凌晨三点多，巴玉夫妇起床开工，准备做馒头。干活时，徐仅仅和丈夫商量，准备招一个工人帮老公打理店铺的活计，她自己回老家照顾儿子。这个念头的热乎劲儿还没过，中午她就接到母亲的电话：天宇失踪了。监控盲区的竖井15日深夜，徐仅仅和老公巴玉连夜赶回阜阳。夫妻俩去了学校。监控记录了天宇的最后行踪。失踪前，他穿着带白花的红色毛衣，下身穿黑色长裤，脚上是一双红色运动鞋。15日上午，第三节课结束之后，天宇和同学一起跑出教室。在走近胡同前，天宇抬头朝教学楼上边望了一眼，身边的小孩与他动作一致。“好像被楼上什么东西吸引了”，巴玉说。此后，天宇自己拐进了教室旁边的一条胡同。胡同是监控盲区，通往教室后面（北面）的一片施工工地，穿过工地就到达学校的操场。拐进胡同之后，天宇的身影就不再出现了。巴玉说，出了胡同，在施工工地旁边安有两处监控，但校方告诉他，这两处监控早就坏了。另外，从学校大门的监控里，也找不到天宇离开学校的身影。施工工地成了寻找天宇的第一现场。官方公布的招标公告显示，临泉医药希望学校工地的在建项目包括一栋五层的教学楼和配套设施。临泉县重点工程建设管理局的负责人韦柏林介绍，这个工程今年3月份开标，4月份动工，目前已基本完工，中标的施工单位是安徽华彩水利工程有限公司。巴玉了解到，出事当天，施工工地上只有七八个工人在作业，整个教学楼的建设已接近尾声。15日白天和16日一整天，警方、救援队以及学校的师生，对施工工地以及周边进行地毯式的排查，找遍工地的每一寸角落，也没有发现天宇——所有人都忽略了两个井口。工地的北侧，有一个略低于地面的缓坑，坑里有少量的积水，坑的外围竖着两口井。井口只有20厘米左右，一个成年人的脚掌踩在井口会被卡住。包括救援队的志愿者、老师、校长和家属在内，所有人都觉得，井口太窄，孩子坠井的可能性不大，用手电筒照看，还能看到井里有水，但没有发现井里有异物。家属们反复查看过两口竖井。他们估算过，天宇一米三的个头，七十多斤的体重，怎么看也和20厘米的井口不匹配，“正常情况下，一个8岁男孩掉下去根本不可能”。徐仅仅一度认为儿子是被拐骗了，她印了一大摞寻人启事，四处发散。她一直处于精神恍惚的状态，每天以泪洗面。而巴玉身为家庭的支柱，硬撑着，面对每一天。井口有新土和线头有很多疑问，巴玉想不通。儿子为什么突然会拐到胡同里？是自己贪玩，还是有什么东西吸引了他？难道是被人给害了？孩子身上应该没什么贵重物品。天宇唯一贵重的物品是一条金链子，但出事那天，天宇也没有戴着它出门。他才8岁，还不太会花钱，平时想要什么，也是直接和姥姥讲，学校和家只有几步路，他身上一分钱都没。出事前几天，天宇看到同学在吃“粘牙糖”，回了家，他通过微信视频跟父亲聊天，希望爸妈从浙江寄糖回来。巴玉有点后悔，他对儿子的这个小小要求没上心，始终没有给天宇买糖。11月19日，孩子失踪的第五天。巴玉越想越不对劲，“监控显示他没出学校，我这孩子不可能凭空就飞了”，于是，他又去了学校里的那片工地。再次来到井边的时候，巴玉发现变化。原来竖井旁边的坑，被填埋了一些。巴玉15日第一次往井里看时，可以看到井水，隔了4天，他趴在地上仔细看，发现井口竟有一层新土，“好像有人动过现场”。更蹊跷的是，巴玉在井口找到几条两厘米左右的红白线头。巧的是，这些线头与天宇失踪时所穿毛衣是一个颜色的。巴玉此时确信，儿子就在井里。井下发现遗体11月20日下午，巴玉找到蓝天救援队，救援人员开始对竖井进行探测。在此之前，一对住在5公里外邻村的老夫妇说，曾有一个和巴天宇年龄相仿，相貌接近的男孩，连续两天向他们讨要食物。巴玉打开手机让他们看照片，这对老人语气笃定，那个讨吃的男孩就是他。这个消息，曾让巴玉夫妇脑中闪现一丝希望，但随着竖井被挖开，希望很快破灭。救援人员用探测设备发现井下3.5米至4米之间有异物。起初并不确定井下是孩子。他们伸下铁钩试探，钩上了孩子的衣服，就是天宇穿的那件毛衣。看来，孩子真的在这口竖井里，且已“出事”。由于井口过于狭窄，直接从井口把天宇拉来上，肯定会破坏孩子的遗体，救援人员和警方决定：利用挖掘机将井口侧方挖开，把孩子从井里挖出来。此时，距离天宇失踪已经过去6天。20日晚，8点左右，挖掘工作正式启动，为防止孩子遗体受到二次伤害，接近孩子被卡住的地方，救援人员用工具手动挖掘。巴玉提供的救援视频显示，井里仍有蓄水，随着井口豁开，井水渗到四周，天宇被救出时身体蜷缩，头朝上。头部上方有些积土。在现场的巴玉夫妇没有亲眼看到孩子被捞出时的样子。他们都晕过去了。法医进行尸检后，天宇的遗体暂存在县殡仪馆。巴玉测量了天宇的遗体。“就算不穿衣服，天宇的肩膀至少也有23厘米宽，加上毛衣有25至28厘米，掉进一个20厘米的洞这不可能，”他说。谜团待解天宇是怎么坠井的，现在还是个谜。根据孩子平时的表现，班主任张老师认为，天宇在智力方面有些反常，跟其他孩子不一样，字也写的不好。“从来不写作业，也不会写（做）”。天宇还会在同桌的书上乱画，影响同学的学习。姥姥给他买的本子，也被他撕得满地都是。张老师评价，天宇在学校算是调皮的孩子，下课的时候会去抓别人一下，拽别人衣服一下什么的，两位任课老师多次跟天宇的家长沟通，说这个孩子在学校不适合大的环境，“他家长说，只要他在教室，学多少是多少，不惹事就行了，只要平平安安。”张老师还说，出事的井是施工用井，并非学校自用的水井，“以前（天宇）也没有发生什么大的问题，没想到会发生这种情况。”巴玉承认，天宇是很调皮，但他否认孩子有智力问题，“就是学习不行，其他事情甚至比大人还聪明”。看到孩子长期不能集中精力学习，巴玉也曾担心他有多动症，去年，他特意带天宇去浙江的大医院做全面检查，结果显示，一切正常。徐仅仅说，唯一能让天宇提起兴趣的只有画画，天宇的作文本上，被他画满了穿裙子的小公主，“没有学过（画画），他就是喜欢”。寻人启事上，注明天宇“口齿有些不清”，巴玉解释，孩子舌根的筋有问题，做过手术。徐仅仅回想，如果孩子留在身边，也许不会发生这种意外。她和丈夫都不相信儿子是自己坠井的。深一度记者联系了临泉医药希望学校的孟校长、施工单位安徽华彩水里工程有限公司的负责人，谈及两口施工竖井的问题时，两人都挂断了电话。目前，此案由临泉县公安局刑警大队进行调查，队长表示，要等尸检结果出来后才能给案件定性。徐仅仅今年29岁，将来还有生小孩的机会。但眼下，夫妻俩只想知道，天宇在落井之前到底遭遇了什么？监控盲区的工地上发生过什么？他们在等尸检报告和调查结论。巴玉把天宇失踪之日当成祭日。21日早上，他走到学校门口烧了一堆纸，这天算是孩子的头七。8岁男孩失踪5天 学校操场直径20余厘米井中现尸体安徽省阜阳市临泉县8岁男孩巴天宇在几天前失踪，家长及警方寻找数日后，在学校操场的一个直径20余厘米的井内发现了孩子的尸体，目前警方正在对此进行调查。 +http://auto.163.com/17/1122/07/D3R3EPTH0008856S.html +3种动力9款车型 最美凯美瑞哪款适合你 +版权声明：本文版权为网易汽车所有，转载请注明出处。此次上市的新一代凯美瑞包含三种动力/九款车型，分别是2.0L（四款）、2.5L（三款）和2.5L混动（两款），售价区间17.98-27.98万元，与上代车型基本保持一致。※ 车型简介新一代国产凯美瑞的2.0L和2.5L都会提供运动版（锋尚版）车型，运动版车型的外观要比普通版更加激进运动，混动版的外观则和普通版保持一致，只是加入了一些专属标识，前不久我的同事刚刚实拍了运动版车型，下面我们就围绕运动版车型做简单介绍。第八代凯美瑞运动版和普通版看上去的差异比较大，运动版设计了专门的前后保险杠、格栅、大灯、排气、尾翼和轮毂，混动版则是在普通版的基础上加入了一些专属标识。其实三种版本的外观在当前市场的中型车中都算运动风格比较浓郁的，第八代凯美瑞的运动版在细节上更进一步，前脸中部为X型大嘴，雾灯区域还有加大尺寸的辅助格栅装饰，这些让它显得更加激进。运动版车型提供了双侧四出的排气，配合全新车机的后保险杠让它平添了一份霸气。并且，运动版尾灯的两个装饰绝对算得上点睛之笔，简单的勾勒就让它比普通版多了不少韵味。车身及内饰颜色选择新一代凯美瑞除了提供六种单色车漆外，还有两种专为运动版车型设计的双色车身，在六种单色车漆中有一款海钻蓝是混动版的专属，所有车型选择铂金珍珠白都要额外支付2000元，运动版车型选择红黑双色也需要加2000元，运动版如果选择铂金珍珠白+黑的双色搭配就要加4000元，这是丰田在车身颜色上的一贯策略。此外内饰也提供了三种颜色，其中红色内饰是2.5L运动版的专属。丰田当前在售的车型内饰基本都是一板一眼的规矩设计，谈不上不好看，但是很难分泌让你兴奋的激素。在第八代凯美瑞上，我们终于看到了丰田在内饰设计上“飘”的一面。除了雷克萨斯以外，在丰田当前的车型上，我们绝少见到一丝发飘的设计，在第八代凯美瑞上，我们对丰田内饰的印象也将被改变。这一次，第八代丰田凯美瑞很不“丰田”。凯美瑞的内饰做工依然保持着较高的水准，无论是包裹的皮质还是覆盖的装饰板，在接缝处理和做工上都很令人满意，现在的年轻人多数时间都接触者优质的东西，凯美瑞的作用和用料这些细节能打动他们的挑剔心。第八代凯美瑞纵向空间上的表现还是比较出色的，当前的中型车后排空间都越做越大，新凯美瑞在这一环节上也表现不错。新一代国产凯美瑞提供三种动力系统，分别是2.0L+6AT、2.5L+8AT和2.5L混动+ECVT，2.0L发动机还提供两种调校，不过差别几乎可以忽略，其中最亮眼的当属2.5L+8AT的组合了，搭载的2.5L发动机拥有40%的全球最高热效率，这要比带T的发动机更加难得。※ 配置分析一、2.0L怎么选？既然提供三种动力系统，那咱们就按照动力来逐一分析，先来看看2.0L的入门版，也就是全系的入门车型怎么样？入门版表现如何？2.0E 精英版  售价：17.98万先来看一下全系的入门车型，2.0E精英版在基础安全性配置上是比较齐备的，特别是标配的10气囊在同级中是比较罕见的，此外LED大灯也是一个亮点，在其它配置方面，入门版基本处于同级的主流水准，但倒车雷达和影像的缺失肯定会给消费者带来不便，带来了事后加装的麻烦，概括起来就是，入门版的配置有亮点，但也有小缺陷，算是个值得考虑的入门版车型。三款普通版怎么选？三款2.0L普通版车型使用一台发动机，但顶配豪华版在调校上要比另外两款高了1kW和2N·m，这是可以忽略的差别，选车时不用去考虑它，主要还是来看配置吧。精英版和领先版的配置差别主要就是座椅材质和调节方式，所以差价也只有1万元，如果不反感皮质座椅的话，领先版的性价比应该是高于精英版的。再来看豪华版，配置确实配得上2.0L顶配的地位，从外观、安全配置、科技配置和舒适配置上都有了显著提升，最关键的是终于有了倒车雷达和倒车影像，这么多配置，价格上也只比领先版贵了1万，所以对于准备购买2.0L的消费者来说，豪华版应该是最值得推荐的车型。2.0L运动版值不值？别忘了2.0L还有一款2.0S锋尚版，也就是我们俗称的运动版，它在整体配置上和2.0G豪华版比较接近，具备更加动感的外观套件和多种驾驶模式，但在座椅材质和调节方式上做出了牺牲，由于只比豪华版贵了6000元，所以里外里两车性价比基本打了个平手，要不要运动版就看您自己的喜好了。二、2.5L怎么选？2.5L值不值得选？2.5L车型的动力系统还是比较值得购买的，首先发动机的动力要更加充沛，而且还有新的8AT变速箱，能够提供更加平顺的驾驶感受，无论是技术含量还是动力水平，都是比较大的卖点，如果对动力多少有些要求的话，2.5L肯定是更合适的选择。但由于2.5L的起步配置比较高，最低也要接近22万元，导致性价比降低，所以可以预期的是，未来新凯美瑞的销售主力还是2.0L车型。2.5L选哪款？2.5L普通版只有两款车型，旗舰版代表了新凯美瑞最高的配置水平，豪华版其实已经很丰富了，旗舰版则是又加了一个更字，又添加了一些科技和舒适配置，几乎已经武装到了牙齿，所以价格也就并不那么亲民了，比豪华版足足贵了4万元，如果选择2.5L的话，豪华版的性价比要更高一些。2.5L也提供了运动版车型，就是2.5S锋尚版，它的配置和2.5G豪华版相近，差别可以参照2.0L对比的内容，锋尚版具备更加动感的外观套件和多种驾驶模式，但在座椅调节方式、全景天窗这些地方做出了牺牲，两车价格差别只有3000元，性价比差不多，如果想将动感进行到底，那运动版显然更如意一些。三、混动版怎么选？混动版值不值得选？这是个比较俗的问题，也很好解释，同配置的混动版要比汽油版2.5L贵了2万，配置上没什么差异，计算下差价和油费的关系就都知道值不值了，车辆使用频率越高肯定就越值得考虑混动版。混动版选哪款？和2.5L一样，混动版也是提供了豪华版和旗舰版两款车型，配置差别也与2.5L车型一致，旗舰版比豪华版贵了4万，所以从性价比的角度来看，豪华版肯定要高一些。推荐车型：毫无疑问是性价比最高的车型，也应该是未来的销售主力2.5L+8AT动力是很大的卖点，只可惜较高的配置拉高了售价如果用车频率很高，这是个很实惠的选择结语：2.0L车型未来一定会是新一代凯美瑞的销售主力，因为它具备最突出的性价比，其实我个人更喜欢2.5L车型，不过它的配置起步较高，影响了性价比，但为技术买单我还是觉得值得。至于混动车型，出于使用成本的考虑，它不会适合所有人，而且随着本田、通用混动技术的兴起，丰田在这个领域也已经不是唯一的选择了。 +http://news.163.com/17/1121/00/D3NN21FV0001885B.html +嗑红牛就是和魔鬼做交易,你被它蹂躏它让你吃鸡 +没有什么能比一听功能饮料更能安慰熬（拖）夜（延）狗（症）的心了。 当你打开拉环，那股熟悉的浓郁的香精气味就能让你头脑清醒一半。 我也无法描述一般功能饮料的味道，大概说来是一种蔓越莓和蓝莓混合的气息，因为曾经吃到过一款蔓越莓和蓝莓口味的雪糕，就是“红牛味”的。 据说红牛最初也就是想用这种味道掩盖牛磺酸和维生素的气味，但后来消费者开始认为这种莓类气味有“提神”效果，所以后来的功能饮料也一般采用类似的香型。（《南方公园》截图）正如气味难以描述，喝下这罐液体的过程就像和魔鬼做了笔交易：你知道他将让你彻夜保持清醒，但你并不清楚它会对你的身体做了些什么。 +可晚睡的诱惑和拖延的快感逼迫着你一次又一次做着这样的交易。又一个难熬的长夜降临，年轻人，干了这罐功能饮料，我还能再肝一晚。 +阴谋论是功能饮料的浪漫 +人们对于提神的要求古已有之，茶叶和咖啡可能是最早的功能饮料，而在更早的喝热水都是奢侈行为的年代，嚼一口大蒜或者花椒是大众的提神醒脑、恢复体能之选，“炒肝”也能算上是上古功能饮料了，它在北京的兴盛的确与劳动人民的刚需有关，商贩走卒冬天来一碗加蒜的炒肝，和现在白领去星巴克买杯咖啡，一个道理。 +（黑暗料理系炒肝可以说是一种传统中式功能饮品）功能饮料的出现，可谓满足了人们自古以来的熬夜刚需。 软饮界最具代表性的可乐，最初就是以提神药剂的面貌出现的。后来美国政府担心有人用可乐制造毒品，在1916年对可口可乐提起了诉讼，尽管最后可乐赢了美国政府，但在这一年之后可口可乐也主动降低了配方中的咖啡因含量。 +（喝可乐曾经如同飞叶子 插画/Th. Metzger）至今仍然有对咖啡因十分敏感的人喝可乐睡不着觉，可乐却不能算“正儿八经”的功能饮料。 真正第一家获得成功的标杆性功能饮料，算得上是日本的“力保健”。 和平成废物的时代风貌恰恰相反，60年代的日本人民正面临空前的压力，熬夜赶工的需求空前高涨。打着补充营养旗号，但实际就是给加班狗续命的力保健，就在这样的历史进程中火了。 +（施瓦辛格因为业绩不佳被上司训斥，还不是因为没喝力保健）典型的脸谱化的日本企业和日本人总是给人一种发力过猛的感觉，传说中的日企似乎个个都是血汗工厂。力保健作为血汗工厂专用保健品，也采用了非常发力的包装，从一开始它就希望别人把它当药喝，力保健的标志就是棕色瓶。喝力保健总给人一种喝大力的错觉。（喝完力保健的施瓦辛格为所欲为）至于力保健的宣传策略，更是继承了发力过猛的优良传统。比如这款施瓦辛格早期作品，可谓真·脑洞大开，施大爷这狰狞而鬼魅的笑容，很难让熟悉哲学的观众老爷们不想入非非。 围绕着功能饮料的脑洞是从来不会少的，提神的显著功效容易带来某种超自然的联想。 （脑洞大开大概就是脑袋上的瓶盖被打开的意思）最著名的功能饮料阴谋论莫过于红牛成分的猜想。在中国，因为罐头上一句青少年儿童不宜食用，很多人猜测红牛甚至是整个西方饮料界的饮料都添加了“激素”，肥胖率提高，儿童早熟，不是金拱门作祟，就是红牛捣鬼。 +（emmmm）而在美国，关于红牛的猜想就更纯粹一点，红牛之所以叫红牛，是因为里面加了公牛的体液，看来吃什么补什么的朴素自然情感是共通的的。 +与这种望文生义的低级阴谋论不同，有关功能饮料最精彩的都市传说当属“怪物”（Monster）饮料与撒旦崇拜，我觉得精彩到可以据此拍一部丹·布朗风格的悬疑电影了。 怪物饮料说起来也是最近在国内突然走红的饮料了，它的口感并不奇特，可以说就是汽水强化型红牛，但它的包装却相当朋克，因此圈了不少粉。 +这个撒旦崇拜传说就与怪物饮料的包装有关，怪物饮料标志性的怪兽爪印，正好是三个希伯来字母zain的组合，zain是希伯来字母表的第六个字母，这个爪印就是666的象征。 +在阴谋论的世界里，666当然不是很6的意思，这个数字和13一样臭名昭著，因为666是魔鬼的步伐，它是撒旦崇拜的重要符号之一。 +而在爪印下面，怪物饮料的商标，字母o被一道横线贯穿，形成了一个十字架形象，当人们喝饮料的时候，十字架就会倒置，又会形成撒旦崇拜中一个重要的标记：倒十字。（恐怖游戏outlast2的图标中就有一个倒十字 +来源/OutLast游戏截图）都市传说的背后，是人们对功能饮料爱恨交织的情感。 在《绝地求生：大逃杀》里面，那一罐大概叫Hot Bull的功能饮料，无论从名字还是包装看都是在致敬红牛。喝下游戏中的热牛功能饮料，你就可以立刻恢复体能，还有缓慢加血的功效。 +但现实啊，恢复体能跟回血是不可兼得的。一手红牛一手霸王，已然成了当代年轻人生活的一种缩影，还要自嘲一句： +你秃了，也更强了。有关功能饮料的阴谋论，也许来自内心深处对加班的抵触——正如当年美国的家庭主妇不舍得用电，就说微波炉和空调是有害的。辛苦而贫穷的年轻人喝着手边的功能饮料，嘴上说着不愿意喝下一罐可能含有神秘物质的液体，身体却很诚实。 +毕竟，我们幻想着一天能够咸鱼翻身，带着一背包的功能饮料大吉大利，今晚吃鸡。 以上内容纯属胡诌，感谢你每天陪我一起幽默。网易新闻首发，未经授权不得转载。  +http://news.163.com/17/1121/00/D3NN21FV0001885B.html +嗑红牛就是和魔鬼做交易,你被它蹂躏它让你吃鸡 +没有什么能比一听功能饮料更能安慰熬（拖）夜（延）狗（症）的心了。 当你打开拉环，那股熟悉的浓郁的香精气味就能让你头脑清醒一半。 我也无法描述一般功能饮料的味道，大概说来是一种蔓越莓和蓝莓混合的气息，因为曾经吃到过一款蔓越莓和蓝莓口味的雪糕，就是“红牛味”的。 据说红牛最初也就是想用这种味道掩盖牛磺酸和维生素的气味，但后来消费者开始认为这种莓类气味有“提神”效果，所以后来的功能饮料也一般采用类似的香型。（《南方公园》截图）正如气味难以描述，喝下这罐液体的过程就像和魔鬼做了笔交易：你知道他将让你彻夜保持清醒，但你并不清楚它会对你的身体做了些什么。 +可晚睡的诱惑和拖延的快感逼迫着你一次又一次做着这样的交易。又一个难熬的长夜降临，年轻人，干了这罐功能饮料，我还能再肝一晚。 +阴谋论是功能饮料的浪漫 +人们对于提神的要求古已有之，茶叶和咖啡可能是最早的功能饮料，而在更早的喝热水都是奢侈行为的年代，嚼一口大蒜或者花椒是大众的提神醒脑、恢复体能之选，“炒肝”也能算上是上古功能饮料了，它在北京的兴盛的确与劳动人民的刚需有关，商贩走卒冬天来一碗加蒜的炒肝，和现在白领去星巴克买杯咖啡，一个道理。 +（黑暗料理系炒肝可以说是一种传统中式功能饮品）功能饮料的出现，可谓满足了人们自古以来的熬夜刚需。 软饮界最具代表性的可乐，最初就是以提神药剂的面貌出现的。后来美国政府担心有人用可乐制造毒品，在1916年对可口可乐提起了诉讼，尽管最后可乐赢了美国政府，但在这一年之后可口可乐也主动降低了配方中的咖啡因含量。 +（喝可乐曾经如同飞叶子 插画/Th. Metzger）至今仍然有对咖啡因十分敏感的人喝可乐睡不着觉，可乐却不能算“正儿八经”的功能饮料。 真正第一家获得成功的标杆性功能饮料，算得上是日本的“力保健”。 和平成废物的时代风貌恰恰相反，60年代的日本人民正面临空前的压力，熬夜赶工的需求空前高涨。打着补充营养旗号，但实际就是给加班狗续命的力保健，就在这样的历史进程中火了。 +（施瓦辛格因为业绩不佳被上司训斥，还不是因为没喝力保健）典型的脸谱化的日本企业和日本人总是给人一种发力过猛的感觉，传说中的日企似乎个个都是血汗工厂。力保健作为血汗工厂专用保健品，也采用了非常发力的包装，从一开始它就希望别人把它当药喝，力保健的标志就是棕色瓶。喝力保健总给人一种喝大力的错觉。（喝完力保健的施瓦辛格为所欲为）至于力保健的宣传策略，更是继承了发力过猛的优良传统。比如这款施瓦辛格早期作品，可谓真·脑洞大开，施大爷这狰狞而鬼魅的笑容，很难让熟悉哲学的观众老爷们不想入非非。 围绕着功能饮料的脑洞是从来不会少的，提神的显著功效容易带来某种超自然的联想。 （脑洞大开大概就是脑袋上的瓶盖被打开的意思）最著名的功能饮料阴谋论莫过于红牛成分的猜想。在中国，因为罐头上一句青少年儿童不宜食用，很多人猜测红牛甚至是整个西方饮料界的饮料都添加了“激素”，肥胖率提高，儿童早熟，不是金拱门作祟，就是红牛捣鬼。 +（emmmm）而在美国，关于红牛的猜想就更纯粹一点，红牛之所以叫红牛，是因为里面加了公牛的体液，看来吃什么补什么的朴素自然情感是共通的的。 +与这种望文生义的低级阴谋论不同，有关功能饮料最精彩的都市传说当属“怪物”（Monster）饮料与撒旦崇拜，我觉得精彩到可以据此拍一部丹·布朗风格的悬疑电影了。 怪物饮料说起来也是最近在国内突然走红的饮料了，它的口感并不奇特，可以说就是汽水强化型红牛，但它的包装却相当朋克，因此圈了不少粉。 +这个撒旦崇拜传说就与怪物饮料的包装有关，怪物饮料标志性的怪兽爪印，正好是三个希伯来字母zain的组合，zain是希伯来字母表的第六个字母，这个爪印就是666的象征。 +在阴谋论的世界里，666当然不是很6的意思，这个数字和13一样臭名昭著，因为666是魔鬼的步伐，它是撒旦崇拜的重要符号之一。 +而在爪印下面，怪物饮料的商标，字母o被一道横线贯穿，形成了一个十字架形象，当人们喝饮料的时候，十字架就会倒置，又会形成撒旦崇拜中一个重要的标记：倒十字。（恐怖游戏outlast2的图标中就有一个倒十字 +来源/OutLast游戏截图）都市传说的背后，是人们对功能饮料爱恨交织的情感。 在《绝地求生：大逃杀》里面，那一罐大概叫Hot Bull的功能饮料，无论从名字还是包装看都是在致敬红牛。喝下游戏中的热牛功能饮料，你就可以立刻恢复体能，还有缓慢加血的功效。 +但现实啊，恢复体能跟回血是不可兼得的。一手红牛一手霸王，已然成了当代年轻人生活的一种缩影，还要自嘲一句： +你秃了，也更强了。有关功能饮料的阴谋论，也许来自内心深处对加班的抵触——正如当年美国的家庭主妇不舍得用电，就说微波炉和空调是有害的。辛苦而贫穷的年轻人喝着手边的功能饮料，嘴上说着不愿意喝下一罐可能含有神秘物质的液体，身体却很诚实。 +毕竟，我们幻想着一天能够咸鱼翻身，带着一背包的功能饮料大吉大利，今晚吃鸡。 以上内容纯属胡诌，感谢你每天陪我一起幽默。网易新闻首发，未经授权不得转载。  +http://money.163.com/17/1122/09/D3RAKJ2G002581PP.html +中国炒房人提振希腊经济 + + （原标题：外媒称中国人赴希腊“炒房”提振该国经济：推动房价上涨） + 报道称，以财务造假被曝光为开端、陷入债务危机的希腊在2010年以后处于欧元区等的金融支援之下，作为交换，希腊政府被要求采取削减养老金和公务员收入等紧缩措施，这导致国民和企业的存款流向国外，而提振经济所需的资金依赖来自海外的投资。正因为如此，对希腊投资被认为在具有相似制度的欧洲各国之中是门槛最低的。居留许可以连续持有房产为条件，能够进行更新，希腊加入了无需边境审查即可往来的欧洲的《申根协定》，因此也可以自由到欧盟（EU）的大部分国家旅行。据希腊政府统计，利用这一制度，在2017年9月之前购买房地产的外国人达到2014人，投资额和相关收入超过10亿欧元（约合78亿人民币），包括家属在内的居留许可的发放数量也逐渐增加，2016年达到1567人，比2014年增加八成。按国别观察截至2017年9月的情况可以发现，中国投资者为850人，按居留许可计算为2091人，分别都占到整体的四成以上，居于首位。在希腊，最大港口比雷埃夫斯港被中国国有海运企业收购，2017年6月中国国有的国家电网收购了希腊国营电力企业旗下的送配电子公司的24％股权，民营投资公司复星集团也将参与雅典机场旧址的大规模重新开发。以基础设施为中心，两国的联系不断加强，房地产也不例外。据房地产广告网站“Spitogatos”统计，英语版来自中国的访问在过去1年里增加至3倍，近期将推出中文版。在希腊国民之间，与迫使本国采取严格紧缩措施的德国相比，对于一直在创造就业的中国更有好感。排在中国之后的投资者来自俄罗斯、土耳其和埃及等国家，这些国家的富裕阶层为了“保险”起见投资了希腊房地产。雅典房地产中介业人士Alexandros Nikolaidis表示，“由于新建房供给中断、家庭旅馆网站的普及，房产价格呈现上涨态势，外国人的买入也成为进一步推高行情的原动力”。 +http://tech.163.com/17/1122/07/D3R4NJNE00097U81.html +这个人与马斯克小扎竞争破解大脑 能成功吗 + + （原标题：INSIDE THE RACE TO HACK THE HUMAN BRAIN） + 在洛杉矶一间普通的医院病房里，名叫劳伦·迪克森（Lauren Dickerson）的年轻女子在等待创造历史的时刻到来。她刚刚25岁，是一所中学的教师助理，目光温柔，非同寻常的是她的头上插满了裹着绷带的信号电缆，像是未来感十足的辫子。三天前，神经外科医生在她头骨上钻了11个洞，将11根细电缆插入她的大脑中，而另一端则连接在电脑上。现在她被医生固定在冷冰冰的铁床上，塑料管扎住了她的手臂，医疗监视器跟踪着她的生命迹象，一动也不能动。房间里挤满了人。当摄像人员做好准备后，两个独立的专家团队准备工作，其中一支是来自南加州大学精英神经科学中心的医学专家团队，另外一支则由来自科技公司Kernel的科学家组成。医学专家们正在寻找一种方法来治疗迪克森的癫痫。到去年为止，他们为迪克森精心制定的癫痫药物治疗方案效果还不错。但随着时间推移，药效开始降低。医学专家之所以使用信号电缆来检索迪克森的大脑，是为了查明癫痫发作的原因。而来自Kernel公司的科学家则出于完全不同的目的：他们为布莱恩·约翰逊（Bryan Johnson）工作，后者是一位现年40岁的科技企业家，在将自己的企业以8亿美元的价格出售后，开始追求一个雄心勃勃的疯狂梦想——约翰逊想控制人类进化并创造出一个更好的人。他打算通过打造一种“神经假体”来做到这一点，这种设备可以让人类更快地进行学习，记住更多的东西，在人工智能的帮助下“共同进化”，解开心灵感应的秘密，甚至可以将人们的思维相连。他还想找到一种方法来让人类瞬间学会武术等技能，就像《黑客帝国》里的那样。他还希望能够在普罗大众中普及这项发明，而不仅仅面向有钱人。迄今为止，约翰逊所拥有的仅仅是一个存储在硬盘上的算法。当他向记者和观众介绍神经假体时，他经常使用媒体易于接受的一种表达方式——“大脑中的一个芯片”，虽然他知道这种需要在人的头骨上钻孔的东西永远不会成为大众市场消费品。目前世界各地的科学家正在开发各种各样的非侵入性接口，通过可以注入大脑的微小传感器，或者可以与头戴式接收器交换数据的基因工程神经元与大脑相连。未来约翰逊将通过这些新型的脑机接口来实现其算法。当然，这些脑机接口还都没被制造出来，所以约翰逊只能使用连接到迪克森海马体的信号电缆来进行一个大胆的实验：当我们用外部设备与大脑相连时，我们可以对大脑传递何种信息。这正是约翰逊的算法将起到的作用。嵌入迪克森头部的电缆将记录大脑神经元在一系列简单的记忆测试中互相传递的生物电信号。这些信号将被上传到硬盘中，算法会把这些信号转换成数字代码，然后进行分析，对其进行功能增强或重写代码，从而提高记忆力。该算法随后会再将代码翻译成电信号发送回大脑。如果这种方法能够帮助迪克森在大脑中显现出一些关于曾经记忆的图像，那么研究人员就会明确算法正在起作用。然后，他们会尝试用间隔更长一段时间的记忆做同样的事情。这是前所未有的尝试，如果这两项测试能够奏效，他们将会破解人脑创造记忆的模式和过程。虽然其他科学家正在使用类似的技术来解决简单的问题，但约翰逊是唯一一个试图开发出一种增强记忆力产品的企业家。几分钟后，他将进行第一次人体测试。对于商业记忆假体，这将是第一次人体临床测试。 “这是历史性的一天，”约翰逊说。 “我非常兴奋。”这一听起来有些匪夷所思的测试，发生在2017年1月30日。读到这里，你或许会认为约翰逊是一个钱多又不切实际的傻瓜。我第一次见到他的时候也抱着同样的想法。他穿着普通的牛仔裤，运动鞋和T恤，充满了孩子般的热情。他滔滔不绝地向我阐述“对人脑进行重新编程”，想法似乎过于天马心空。但是你很快会意识到这种风格是约翰逊的一种伪装或是自己先入为主的看法。约翰逊和许多成功的人一样，既聪明又现实。他拥有充足的活力，好像浑身长满了像章鱼一样的触手，一面应对笔记本电脑，一面应对手机，还不忘谋划全身而退的路线。当他开始谈论他的神经假体时，各种论断会一起向你扑面而来，直到你屈服于他的观点。约翰逊在29岁创办了在线支付公司Braintree，在他36岁的时候被PayPal以8亿美元的价格收购。随后约翰逊向Kernel投资了1亿美元，开始疯狂研究神经假体项目。数十年的动物实验支持着他的科学野心：研究人员已经学会了如何恢复脑损伤的记忆，植入虚假的记忆，人为控制动物的动作，食欲和好斗行为，诱发愉快的感觉和疼痛，甚至可以将大脑信号从一只动物传送给数千英里以外的另一只动物。约翰逊并不孤单。在他进行实验的几周之前，特斯拉首席执行官伊隆·马斯克（Elon Musk）和Facebook首席执行官马克·扎克伯格（Mark Zuckerberg）都公布了他们的破解大脑计划。而一个名为达尔帕Darpa的军事研究小组也已经进行了数十次研究。毫无疑问，其他国家也都在进行相关研究。当然，和约翰逊不同的是，他们不会邀请记者进入任何实验室。马斯克关于其项目公开的要点如下：（1）他想用一种称之为“神经纽带”（neural lace）的神秘装置将我们的大脑与电脑相连接。（2）他创办的公司名为Neuralink。通过去年春季Facebook举办的F8开发者大会上扎克伯格所做的演讲，我们得以了解他的破解大脑计划：（1）迄今为止，该项目一直处于Darpa前董事Regina Dugan和谷歌先进技术小组的监督之下；（2）项目团队工作地点位于Facebook总部的8号楼，这里也是扎克伯格实验室所在地；（3）他们正在研究一种非侵入性的“脑机语音文本界面”，它使用“光学成像”来读取神经元形成单词的相应信号，找到一种方法将这些信号转化为代码，然后再把代码发送到计算机；（4）如果这种方法起效的话，我们只需要通过思考就能够“一分钟”打出100个单词。至于达尔帕，我们知道它所进行的一些项目是对现有技术的改进，还有一些是让士兵更快地掌握一些技能，这与约翰逊的某些想法不谋而合。但是我们对其所知甚少。这使得约翰逊成为我们唯一的向导，他也认为这是他需要承担的工作，因为他认为整个世界需要为即将到来的未来做好准备。但是，所有这些雄心勃勃的计划都面临同样的障碍：大脑有860亿个神经元，没有人知道它们是如何工作的。在大脑研究方面，无疑科学家已经取得了令人印象深刻的进展，比如揭示甚至操纵简单大脑功能背后的神经回路，但是诸如想像力，创造力和记忆等功能却是如此复杂，世界上所有的神经科学家联合起来可能都无法解决这些问题。这就是为什么在让专家对约翰逊的计划发表意见时，日内瓦生物与神经工程中心Wyss中心主任约翰·多诺霍（John Donoghue）回应说：“我很谨慎，这就好像我要求你把斯瓦希里语的东西翻译成芬兰语，你却试图将一种未知的语言翻译成另一种未知的语言。“为了显现出这个挑战的艰巨程度，他补充说，目前所有用于大脑研究的工具都像”两个纸杯之间的一根连线“一样原始，而我们的目标是创造能通话的电话。约翰逊并不清楚到底是100个还是10万个或者是10亿个神经元在控制复杂的大脑功能。在关于大多数神经元如何工作以及它们使用何种方式进行交流的问题上，约翰逊还是一团浆糊，而要解开这些谜团甚至需要几十年的时间。最重要的是，约翰逊没有相关的学术研究背景。他可能会在一个神经科学笑话上跌倒：“如果大脑足够简单，能够让我们理解，那我们也会愚蠢得无法理解。”图示：Kernel公司创始人布莱恩·约翰逊我和你们一样觉得，没有什么比科技乐观主义者的梦想更令人生厌。他们的永生计划和自由主义是青少年的幻想;他们开创的数字革命所摧毁的似乎要比创造的更多，甚至于他们的科学成果也不完全令人鼓舞。但约翰逊的动机源自内心深处。他出生在犹他州一个虔诚的摩门教社区，对于人生有着一套循规蹈矩的精致规则，这在他的脑海中印象如此深刻，以至于在我们首次会面的第一时间他就向我讲述了这些规则：“如果你在8岁时受洗，得到一分 ；如果你在12岁时进入教堂，得到一分；如果你戒色，得分；排斥手淫，得分；每个星期天去教堂，得分“。而最高分的奖励是天堂，一个虔诚的摩门教徒将在天堂与他的亲人团聚，并拥有无穷的创造力。当约翰逊4岁的时候，他的父亲和母亲离婚，也不再去教堂。虽然约翰逊并未向我提及那些不愉快的过往，但他的父亲告诉我，信仰的丧失导致他长时间的吸毒和酗酒。而他的母亲说，她的生活是如此窘迫以至于约翰逊不得不穿着手工缝制的衣服去学校。他的父亲记得约翰逊11岁时开始给他写信，每个星期都会写：“会用100种不同的方式反复说，'我爱你，我需要你'。他还是个孩子，而他的父亲是个吸毒酗酒的人渣。“约翰逊中毕业后仍然是一位虔诚的信徒，还曾前往厄瓜多尔进行传统的摩门教仪式。他在那里不停地祷告，一天重复数百次关于约瑟夫·史密斯（Joseph Smith）的话语，但他对于那些让生病和饥饿的孩子们在天堂里过上更美好的生活的故事感到越来越羞愧。减轻他们在现实中的痛苦不是更好吗？他的父亲说：“布莱恩回来了，完全变了一个人。”他有了一个新的目标，自我救赎。他的妹妹还记得约翰逊的言之凿凿：“他说，他想在30岁时成为百万富翁，这样他就可以利用手中的资源来改变世界。”他的第一步是在杨百翰大学（Brigham Young University）取得了学位，通过销售手机来支付自己的学费，并阅读会对未来有用的每一本书。其中一本给他留下深刻印象的是《忍耐》（Endurance），这是一本关于英国著名探险家欧克内斯·沙克尔顿（Ernest Shackleton）前往南极点探险的书。如果纯粹的勇气可以让一个人熬过如此多的艰辛，那么他就会信仰纯粹的勇气，约翰逊也是如此。他娶了“一个好摩门教女孩”，生了三个摩门教的孩子，并找了一份上门推销的工作来养家。在工作中，约翰逊还赢得了年度最佳推销员的奖项，手中的业务业越来越多，这让他进入芝加哥大学攻读了商业学位。2008年毕业后，他留在了芝加哥，创办了Braintree，开始向成为世界级的摩门教企业家努力。那时候，约翰逊与生活作着一系列斗争。他无法入睡，脾气暴躁，头痛得厉害。为此他采取了一系列无用的治疗方法：抗抑郁药，生物反馈，能量治疗师的治疗，甚至盲地服从教会规则。2012年，在约翰逊35岁时，他似乎到了人生的最低谷。在生活的痛苦中，他想起了沙克尔顿，并抓住了最后的希望，也许自己可以通过痛苦的磨难来找到答案。他计划攀登乞力马扎罗山，结果行程的第二天就得了胃病，第三天又患上了严重的高原反应。当他终于抵达峰顶时流下了眼泪，然后不得不被担架抬下山。这次经历过后，他是时候做出改变了。约翰逊开始不再掩饰自己的弱点，不再坚持怀疑态度，也放弃了生活斗士的姿态。在接下来的18个月里，他和妻子离了婚，卖掉了Braintree公司 ，并切断和教会的联系。为了缓解生活变故对孩子的影响，他在家附近买了一栋房子，几乎每天都去看望他们。他知道自己是在重复父亲的错误，但却别无选择——他要么在错误中沉沦，要么开始寻找他一直想要的生活。从厄瓜多尔回来时约翰逊曾经许下承诺，他将以此为起点，改变这个世界。他首先在华盛顿倡议善政，失败之后转向创立“人体器官芯片”等未来主义产品的风险投资基金。但他发现，即使这些做法获得成功，也无法改变世界的规则。最后，约翰逊想：如果人类的根本问题源自意识，那就让我们改变意识。此时，神经科学领域正在发生很多神奇的事，其中一些听起来就像圣经中所述的奇迹一样。比如科学家正在将假肢通过微芯片连接到大脑，并通过患者的视觉皮层进行控制。在多伦多大学，一位名叫安德烈斯·M·洛扎诺(Andres M. Lozano)的神经外科医生使用深度脑刺激减缓了老年痴呆症患者的认知衰退，并在某些情况下能够逆转患者的病情。在纽约州北部的一家医院，一位名叫格温史克（GerwinSchalk）的神经科学专家要求工程师记录听众在听摇滚乐队平克·弗洛伊德（Pink Floyd）的乐曲时听觉神经元的放电模式。当工程师们将这些模式转化为声波时，他们制作出一张几乎完全一模一样的单曲。在华盛顿大学，坐在不同楼的两位教授在脑电波帽的帮助下一起合作玩起了视频游戏。当一位教授想到要在游戏中发射子弹时，另一位教授有按下游戏按键的冲动。约翰逊还听说了一位名叫西奥多·伯杰（Theodore Berger）的生物医学工程师。在近20年的研究中，伯杰和南加利福尼亚大学以及维克森林大学的合作者联合开发出一种神经假体来改善老鼠的记忆力。在2002年开始测试时，实验材料只有一块老鼠大脑切片和一块电脑芯片。但是研究的关键之处在于芯片内置的算法，可以将神经元的放电模式转换成与实际记忆相对应的莫尔斯电码。以前从来没有人做过这样的事情，有些人认为这个想法过于激进——把我们最宝贵的意识归结成零和一未免太过狭隘了。著名医学伦理学家指责伯格篡改了自我认同的本质。但其意义是巨大的：如果伯杰能够把大脑的语言变成代码，也许他可以弄清楚如何解决与神经疾病相关的代码问题。与人类一样，大鼠海马体中神经元在放电时会产生相应信号或代码，而大脑会将其认定为长期记忆。伯格训练了一群老鼠来完成一项任务，并研究了所形成的代码。他了解到，当老鼠的神经元发出“强代码”时，大鼠关于相应任务的记忆更加清晰明确，他通过将其与收音机的音量进行类比来解释这个现象：在低音量下，你听不到所有的话语，但是在加大音量时， 就能清楚辨别出每一个单词。然后，他开始研究大鼠记忆或遗忘时产生的代码差异性。?2011年，通过对训练过的老鼠进行相关实验，伯格证实他可以记录大鼠大脑产生的初始记忆代码，并将代码输入算法进行处理，然后再将更强的代码反馈到大鼠的大脑中。当他完成实验时，忘记了如何推杆的老鼠突然想起来该如何去做。五年后，当伯杰仍在寻求人类临床试验所需的支持时，约翰逊出现了。2016年8月，约翰逊宣布投资1亿美元创办Kernel公司，伯格将加入公司担任首席科学官。在得知南加利福尼亚大学将在迪克森脑部植入信号电缆以治疗癫痫时，约翰逊与迪克森实验的首席医生、南加利福尼亚大学医学院神经重建部门负责人查尔斯·刘（Charles Liu）进行了接触。约翰逊要求刘允许其通过迪克森的信号电缆测试算法。事实上，早在刘六岁的时候，就痴迷于电视剧《无敌金刚》中的情节，也梦想着用技术增强人的能力。他协助约翰逊征得了迪克森的同意，并说服了南加利福尼亚大学机构研究委员会批准这个实验。在2016年底，实验的绿灯向约翰逊亮起。他准备着手开始他的第一次人体临床试验。在医院的房间里，迪克森正在等待实验的开始，我问她对于自己成为第一个实验对象有何感想。“如果我一定要做这场手术，”她说，“那正巧可以做一些有用的事情。”有用？关于机械超人的光辉梦想？ “你知道他在试图让人类更聪明，对吗？“这不是很酷吗？”她回答道。在电脑旁边，我向一位科学家询问屏幕上的五彩网格的含义。一位研究人员说：“每一个方格都对应着她大脑中的电极。”他解释说，每当迪克森大脑中的神经元连接到一条信号电缆时，一条粉红色的线就会跳进相应的方块中。首先约翰逊的研究团队将进行简单的记忆测试。这位科学家向迪克森解释说：“我们将向你展示一些单词。随后会提出一些数学问题，以确保你不会在脑海中反复回想之前的单词。你需要做的，是记住尽可能多的单词。“其中一位研究人员把平板电脑举到迪克森面前，在场的每个人都安静下来。迪克森读出屏幕中显示出的一个个单词。几分钟后，在数学问题打乱了一切之后，迪克森开始回想记忆中的单词。 “烟......蛋......泥......珍珠”接下来，他们加大了困难，开始尝试一连串的记忆。正如Kernel公司的一位科学家向我解释的，他们的信号电缆只能连接到30或40个神经元，从而收集到部分数据。收集到的数据重现一张面孔应该不太难，但是要获得足够的数据来再现一场电影中的场景几乎是不可能的。坐在迪克森床边的科学家开始发问，“你能告诉我上次去的餐馆吗？”迪克森说：“大概是五六天前。我去了观澜湖边的一家墨西哥餐馆。我们点了薯条和沙拉。”随后科学家向她抛出了更多问题。当迪克森绞尽脑汁回想时，另一位科学家递给我一个连接到处理电脑的耳机。我一开始听到了嘶嘶的声音。 在20或30秒后，我听到正在播放的流行音乐。他说：“这是一个神经元在放电。”随着迪克森的叙述，我开始听到大脑中那些神秘的语言，流行音乐让我们的腿不由自主的跟着抖动，我们的梦想随之震颤。她记得上次去好市多（Costco）超市时正在下雨，我听到了耳机中有好市多的音乐，还有下雨的声音。当迪克森的眼皮开始下垂的时候，医疗团队说她已经做的够多了，约翰逊的研究团队开始整理收集到的数据。在接下来的几天里，他们的算法会将迪克森的神经元突触活动转化为代码。如果他们把这些代码反馈回迪克森的大脑，她会想到自己用薯片沾了沙拉酱，而约翰逊或许离自己人类意识进行编程又近了一步。现在还剩下另一个挑战——约翰逊的研究团队需要经过两天的疯狂编码后返回医院，将新的代码反馈到迪克森的大脑中。正当他们得到一个消息说实验可以提早开始的时候，忽然又传达来一个消息：实验必须终止。实验被叫停的原因在于约翰逊和伯格之间出现了问题。伯格表示他对于正在进行的实验并不知晓，约翰逊没有得到他的允许就进行了受监管部门管控的实验。约翰逊说，伯格的指责让他感到困惑。 “我不知道他怎么会不知道这件事。我们整个实验室都在和他的团队一起工作。“他们之间的关系在不久之后就破裂了，伯格带着自己的算法离开了公司，他把责任完全归咎于约翰逊。伯格说道， “像大多数投资者一样，他希望尽快获得高回报。他没有意识到他必须等待七八年才能获得FDA的批准?-?我原以为他会认同这一点。”但约翰逊不想放慢速度。他有更大的计划，他太急了。八个月后，我回到了加利福尼亚，去拜访约翰逊，在实验结束之后他看起来似乎更轻松。我造访了Kernel公司位于洛杉矶的新办公地，有人在约翰逊办公桌后面的白板上用大大的字母写下了几首歌曲的播放列表。 “那是我儿子写的，”他说，“今年夏天他在这里实习。”这一年是约翰逊和一位31岁的演员兼电影制片人Taryn Southern合作的蜜月期。自从与伯格决裂以来，约翰逊已经把Kernel人员增加了两倍，现在他已经有36名员工，招募了芯片设计和计算神经科学等领域的专家。他的新科学顾问是麻省理工学院合成神经生物学组主任、神经科学界的超级巨星埃德·博伊登（Ed Boyden）。在新办公大楼的地下室里，有一个弗兰肯斯坦博士实验室，科学家们在那里建立原型，并在玻璃头模型上进行试验。看到约翰逊的工作一切顺利之后，我提到了访问的目的。 “你说你有东西给我看？”约翰逊有些犹豫。我已经答应不透露敏感的细节，但现在我必须再次承诺。然后他指给我两个小型的塑料陈列柜。里面是搁在泡沫橡胶上的两对弯曲的精致电缆。它们看起来很有科技感，也相当怪异，就像未来机器人的触角。我看到的是约翰逊的全新神经调节器的原型机。从一个角度说，这个神经调制器只是目前市场上深层脑刺激器和其他神经调节器的微型版。但不同于发射电脉冲的普通神经刺激器，这个神经调节器的功能是读取神经元发送给其他神经元的信号。它也许能采集超过100个神经元的信号，这比市面上最好的设备还厉害。这个设备本身不仅仅是一个巨大的进步，它也具有更为深远的意义：使用约翰逊的神经调节器，科学家可以从数千名患者那里收集大脑数据，从而可以编写精确的代码来治疗各种神经疾病。在短期内，约翰逊希望他的神经调节器能够帮助他“实现神经科技领域的淘金热”——金融分析师们预测在六年内神经设备市场规模将达到270亿美元，世界各国的科学家都在竞相破解大脑。从长远来看，约翰逊认为他的信号采集型神经调节器将以两种方式拓展他的计划：（1）通过为神经科学家提供一个巨大的新型数据库，从而用来破解大脑的运作模式；（2）在获得超高利润后，Kernel有能力推出一系列具有创新性且有利可图的神经工具，使公司深入涉足神经科学领域。有了这两项成就，约翰逊就可以推动神经科学达到他所需要的复杂程度，再用一种提高思维的神经假体来激发人类进化。痴迷于《无敌金刚》的神经学家查尔斯·刘将约翰逊在神经科学领域的野心比拟于人类最初的飞行梦。 “回到古希腊时代，人类一直有飞行的梦想。我们没有翅膀，所以我们发明了飞机。很多时候，这些人为创造的解决方案比自然创造的能力还要大，因为没有一只鸟能飞到火星。”但现在人类正在学习如何重塑自己的能力，我们真的可以选择我们的进化方向。“我们必须围绕这一点思考。这是世界上最具颠覆性的事情。“关键的因素还在于利润驱动，它总能推动科学的快速创新。这就是为什么刘认为约翰逊可以成为我们的翅膀。他说：“我从来没有遇到任何急于将此技术推向市场的人。”这场革命何时到来？ “比你想象的还要快，”刘说。现在我们回到了开始的问题。约翰逊是个傻瓜吗？他是在疯狂造梦中浪费自己的时间和财富吗？有一件事是肯定的：约翰逊永远不会停止尝试改进世界。在威尼斯海滩租赁的后现代造型的房子中，约翰逊想出一个又一个主意。他甚至把怀疑主义作为有用的信息——当我表示他的神经假体听起来像另一个版本的摩门教天堂时，他很高兴。“好主意！我喜欢它！”每隔一段时间，他都会停下来去探究我的“约束程序”。“首先，你有好奇心这种生物倾向。你想要得到数据。而当你使用这些数据时，你就有了意识的界限。““你想破解我的思维吗？”我问。他说，一点也不。他只是希望分享我们的思维。他说：“这就是生活中的乐趣，这个难题有着无穷解。我想，如果我们能够使数据传输速度快上千倍呢？如果我的意识看到的只是现实的一小部分呢？我们会讲出什么样的故事？”约翰逊在空闲时间写了一本关于控制人类进化的书，并且描绘了我们人类未来的光明一面。每当我和他谈话的时候，他都会提起这件事。很长一段时间，我把这个想法和他关于重新编程人类意识的梦想混为一体：未来正在扑面而来，比任何人想象的都快，光明的未来在呼唤我们，我们将很快为奇点的到来而欢呼。这让我很想用“炸弹客宣言”来打击他滔滔不绝的兴奋劲，我这样对他说：“你如何回应泰德·卡辛斯基（Ted Kaczynski）的恐惧？技术对人类来说会是一种自残吗？”（网易编辑注：卡辛斯基1995年发表论文《论工业社会及其未来》，文中指出工业革命及其带来的后果，对于人类社会来说是一场灾难，在论文的结束部分，作者作出预言：工业技术体系在未来的变革，将最终剥夺人类的自由。）“我想说他可能站在了历史发展的对立面。”“是吗？那气候变化呢？“他回答说：“这就是为什么我感到如此的急切。我们正在与时间赛跑。”他问及我的意见。我告诉他，我认为即便当饥民毁掉他实验室寻找食物时，他还会坚持研究机械大脑——而这也是我第一次揭示出他梦想背后的困境。事实是，他也有同样的恐惧。他说，世界变得太复杂了。金融体系摇摇欲坠，人口老龄化，机器人正在取代我们的工作，人工智能正在迎头赶上赶上，气候变化正在加速。他说：“感觉一切都在失控。”他总是反问，“为什么我们不能自我进化？为什么我们不能尽己所能更快地适应环境变化呢？”我转向一个更加轻松的话题。如果他发明出神经假体来革新我们使用大脑的模式，他会首先给我们带来什么？超人？心灵感应？集体智慧？还是功夫？他毫不犹豫地回答。因为我们的思维总是受到习惯的禁锢，他说，我们无法想象一个新世界。但是我们必须想象一些比现实更好的东西。所以他会试图让我们更有创意，这会给未来带来新的可能性。雄心壮志能让人坚持走过漫长的路途。当众人嘲笑不可能时，沙克尔顿抵达了南极；当约翰逊濒临死亡时，他登上了乞力马扎罗山，还在36岁打造了一个价值8亿美元的公司。而现在，约翰逊的雄心壮志是实现人类最古老的梦想：掌控意识。通过破解我们的大脑，他想让人类拥有一切。（翻译:晗冰 校对：王华春） +http://tech.163.com/17/1122/07/D3R3JP7900097U7R.html +乐视网停牌坑了融资炒股:不仅巨亏 还要交2亿利息 + + （原标题：乐视网停牌之殇：券商下调公允价值 融资客陷亏损黑洞） + 乐视网的“无限期”停牌，已经让越来越多的融资客面临亏损黑洞。在公募基金集体调降乐视网估值的同时，部分券商两融业务也开始下调乐视网的公允价值，最大调整幅度较这家公司的停牌价“腰斩”。第一财经了解到，由于乐视网财务状况严重恶化，国金证券将自11月22日起，调整乐视网的公允价值至11.18元，调整后，融资客将按照11.18元计算持有乐视网的市值，维持担保比例也随之变化。此前不久，中信证券、海通证券等券商也已下调乐视网的公允价值，其中，中信证券下调至7.82元。记者从两融投资者以及券商两融人士处了解到，随着券商下调公允价值，不少融资客面临爆仓，持仓比例高者已资不抵债，违约纠纷恐将产生。尽管10月27日深交所已将乐视网调出两融标的，但33亿两融盘仍将存续。自乐视网停牌以来，融资客所承担的利息已有近2亿元，受访融资客认为，乐视网的“无限期”停牌在两融领域并无先例，对两融交易规则也提出了挑战。除了沉重的利息外，众多的乐视网融资客都处于“准爆仓”状态。但证券法人士则表示，现有的法规下，若无监管认定乐视网违规，两融投资者很难追回损失。在乐视网公布三季报后，券商也加入了下调其股价预期的队伍。11月初，中信证券就发布业务公告称， 乐视网停牌时间较长，且于2017年10月28日发布三季报，根据融资融券业务规则及《融资融券业务合同》的约定，中信证券决定自11月6日起，调整乐视网的公允价格至7.82元，并按照调整后的公允价格计算维持担保比例。有资深的两融投资者对记者分析称，对于乐视网的融资客来说，这一价格将让仓位在三四成以上的，基本都处于一个“准爆仓”状态，损失普遍在50%～60%，很多千万级重仓面临的肯定是爆仓的“致命亏损”。不仅中信证券，部分券商也在适时调整乐视网公允价值。以海通证券为例，海通证券11月20日公告的乐视网最新公允价值13.87元。而国金证券则于日前公告，因乐视网三季报显示财务状况严重恶化，多家基金公司和券商对该证券下调了估值。为防范风险，将于11月22日调整乐视网公允价值至11.18元，并称根据后续市场和乐视网情况，可能还将多次调整。“我们目前还在观望， +没有下调（公允价值），只要能付利息，担保比例是正常的，就还是给客户进行展期。客户有钱还掉是最好了，复牌以后亏多少谁都说不定。”上海一券商两融业务负责人接受第一财经采访时表示，如果按照个别券商给出的低价公允价值，很多乐视网的两融投资者已到了平仓线，将出现诸多爆仓。该人士认为，乐视网的停牌是市场第一例，后期如何处理更多券商也都在观望，不排除更多券商继续下调乐视网公允价值。前述两融投资者则认为，相比公募基金下调估值而言，券商的公允价值下调带给投资者的亏损更为惨烈。“如果公允价格继续下调，很多人爆仓两三次都够了，重仓的、集中度高的，身家性命都可能赔进去。按照之前的情况，很多人就会选择违约，彻底不要了。”该人士称。两融爆仓违约在2015年股市异常波动出现，融资客与券商为此对簿公堂。不止一位券商两融人士认为，由于乐视网的长期停牌以及资金风险带来的两融投资者亏损，券商并没有更多责任，只是履行合同。相反，作为债权人，当融资客明确不还债务后，券商有权进行诉讼。“出了这种‘黑洞’之后，（客户）亏损是非常大的，很多资不抵债了，让券商平仓，这种情况是比较无奈和尴尬的。”北京的两融人士告诉记者，面对乐视网的停牌，融资客似乎没有什么比较好的办法，只能根据合同去支付利息，履行相关义务还债。他给出的建议同样是“能拿钱了结就赶紧了结”。数据显示，乐视网的两融余额高峰时曾达到50亿元，占比流通市值超过11%。到其今年4月18日停牌，两融余额仍有逾44亿，10月27日最后公开余额是32.98亿元，占比流通市值仍有8.47%的比例。停牌7个月以来，乐视网每天均存在百万至千万不等的融资赎回。记者了解到，目前两融的利息在年化8.5%左右，部分大客户最低年化也有至少6个百分点。按此计算，32.98亿元的融资盘，自乐视网停牌以来利息超过1.6亿元。对于高额的利息，此前已有投资者对第一财经表示“不堪重负”。乐视网在长期无先例停牌中，意味着融资客仍要在无法交易的状态中支付利息。对此，有两融投资者颇为不满，认为乐视网应对融资客的亏损负有一定责任，后续或遭到融资客起诉。北京市问天律师事务所主任合伙人张远忠告诉记者，尽管融资客有追偿意愿，但前提必须有监管认定乐视网有相关违规，而融资客又因此遭受亏损。“乐视网目前的停牌是监管所允许的，如果后面证监会认定它停牌违规或者存在其他问题，两融投资者包括一般投资者都可以追究损失。”实际上，令接受第一财经采访的两融投资者感到无奈的是，目前乐视网融资客的亏损“有苦难言”。券商在这之中虽然不存在责任，但相关的交易规则却被认为有更新的空间，比如是否应规定融资融券标的停牌时限，若停牌达到多久将被剔出两融标的等。“在上一次股市异常波动之前，是有对两融标的停牌进行规定的，最长停牌就半年，半年以上要客户还债。之后就放松，只要能正常付利息，担保比例没问题就继续展期。”受访的两融负责人认为，乐视网的两融盘，未来可能出现更多的投资纠纷，这让券商也十分尴尬，券商所能做的也只是跟着合同走。 +http://sports.163.com/17/1122/17/D3S52J2Q00058780.html +球童抱球不放拖时间帮主队 赛后一起举奖杯 +网易体育11月22日报道：北京时间11月21日，澳洲足总杯决赛在悉尼安联球场举行，坐镇主场的悉尼FC历经加时，艰难的以2-1的比分击败了阿德莱德联，在家门口摘得桂冠。然而这场火星四溅的比赛却因为加时赛中和赛后的一幕而显得颇有争议。起因发生在加时赛第115分钟，彼时由前锋波波打入1球的悉尼FC以2-1领先，时间所剩无几，阿德莱德联争分夺秒想提速进攻以求追回比分。然而在悉尼队员将皮球解围出界后，阿德莱德等候发边线球的队员却迟迟没有接到球童掷来的皮球。原来主队的小球童眼看自家球队胜利在望，耍了个心眼，拖着不肯给阿德莱德队员皮球想着耽误些比赛时间。这下可惹火了落后中的阿德莱德队员，边后卫马罗内直接扑上去就把小球童撞倒想要抢走皮球，结果不堪“自己人”被欺负的悉尼队员也一拥而上，场面顿时一片混乱。最终裁判分别罚下了撞人的马罗内和参与斗殴的悉尼前锋西蒙才算了事。比赛结束，2-1艰难夺冠的悉尼FC自然是一片欢天喜地。然而不知道是出自什么考虑，本应只有球队人员参与的夺冠捧杯仪式却出现了一位“既熟悉又陌生”的小面孔，正是刚才因为拖延给球导致大冲突的小球童！特别是颁奖台上的悉尼众将对这位“功臣”还非常看重，特地让他与球队队长一齐举起了冠军奖杯。一时间舆论非议声四起，因为这位用了不太光明的“盘外招”的小球童，如今却被悉尼FC视为“夺冠功臣”，一旦这种行为被传播开来，无疑会降低澳洲足球在世界足坛的公信度，想必夺冠的悉尼FC要好好遭受一番口诛笔伐了。 +http://sports.163.com/17/1122/22/D3SN14U400058782.html +柯洁丢钱包1万元悬赏 自嘲:棋输多了脑子也坏了 +网易体育11月22日报道：接着，他又在评论里说：“还有...包是我妈买给我的礼物...我蛮珍惜的...你喜欢可以留下...但可不可以把身份证还有驾驶证还给我”之后又补充道：“还有...我手机快没电了，飞机也要起飞了。明天还要去韩国，但身份证丢了好像不四森么好玩的四。” +http://ent.163.com/17/1122/06/D3QVDRFE00038FO9.html +肚子抽了一下！熊黛林首曝怀孕心情：很害怕 +熊黛林在微博发文表示，昨天晚上肚子抽了一下，因为事发突然不确定怎么回事，感到很害怕，好一会都不敢动，今天她问了妈妈才知道，原来是“宝宝踢我了”，并附上脸红红红、眨眼睛的表情符号。初次感受到宝宝“胎动”的发文公开后，引来不少网友回覆“妈妈经”说，“幸福的胎动，会越来越感恩生命的神奇”、“越大宝宝胎动越频繁”、“我猜4个月左右了，因为我怀孕时也是，第一次宝宝踢我时，以为出了什么差错了”、“开始有胎动了，你要多跟他互动，说话、读书、听音乐，他会给你他的回应的，很奇妙的感觉，再大点，就可以摸出他的小脚丫、小屁股”、“宝宝踢妈妈了，幸福的感觉”。熊黛林和郭可颂2014年认爱，两人交往两年后就步入礼堂，前男友郭富城9月迎来女儿后，秒变女儿傻瓜，她出席活动时也不免被提问何时要生小孩，先前传出她为了求子到香港荃湾龙母庙拜神，还瞌了100个响头，2月更被拍到求诊有“妇科圣手”之称的中医诊所调养身体，为了夫妻俩的第一胎做足淮备。果然在6日发文公开好消息，熊黛林写到：“第一次，和宝宝一起开工，好奇妙的感觉。”她换上球鞋，穿着蓝色吊带裤、白色上衣T恤，在拍摄现场帮模特儿调整衣服，侧面明显可见小腹隆起，目测约已3个月，但四肢仍纤细，还认真的和模特儿一起比划姿势。 +http://ent.163.com/17/1122/06/D3QUPNKD00038FO9.html +萧敬腾女粉闹自杀住精神病院 曾卷入泼粪案 +萧敬腾因Yuki在网络上漫骂他“台湾败类”、“贱人”等，诋毁萧及经纪人林有慧（Summer）的言论，控对方妨碍名誉。一审判Yuki须赔偿萧100万（约人民币22万）、林50万（约人民币11万），并刊登道歉启事在4大报，双方再上诉。高等法院于7月11日判决荫山友纪赔偿萧、林2人共台币80万元（约人民币18万），并且需登报道歉。11月22日，Yuki依照判决内容，在报纸头版刊登道歉启事；而她的父亲荫山次郎，在同天也用买广告的方式，在同个版面发出千字声明，以“一个疯狂粉丝的父亲”为题，阐述女儿5年来与萧敬腾之间的纠葛。他透露，女儿2007年来台治疗自律神经失调症，并开始在台湾生活，并从2012年起，开始赞助萧敬腾的演唱会。“友纪前后赞助了一千多万台币，但并未有奢求任何回报，只把这些赞助当作是在支持好音乐，同时把赞助回赠的门票送给慈善机构和一些经济不宽裕的年轻人。”至于先前发生的“送汤事件”，荫山次郎则表示，由于女儿在香港出生，有着地域文化差异，加上误以为与萧敬腾是好友关系，才会想藉着送汤，慰问当时受伤的老萧。不料，Yuki却在一夜之间，变成“骚扰萧敬腾半年的疯狂粉丝”。她的父亲透露，女儿为此饱受酸民谩骂，原先有好转的自律神经失调症，因此演变成更严重的忧郁症，“同年11月，友纪更是莫须有地被怀疑为萧敬腾‘泼粪案’的主谋，让我女儿承受了无法想像的精神压力和名誉损害。其后，2014年的“面包虫”也被怀疑是主谋。”他认为，这些毫无证据的指控，都是让女儿忧郁症变得更严重的因素。如今Yuki试图自杀、住进精神病院，作为父亲的荫山次郎，看见女儿毫无生气地躺在病床上，内心相当悲痛，却也只能心疼隐忍着，“希望陪她一起面对，一起熬过这最艰难的日子。”他透露，这段时间以来，虽然女儿心力交瘁，一直没有得到所期望的审判结果，为此深感失望至极，“但她还是会尊重台湾法律，奉公守法，接受台湾高等法院的判决。”据报导，得知Yuki曾意图自杀一事，萧敬腾经纪人Summer表示，“这几年坚持打这官司，要的是一个公道，我不能任凭一个你说你自己生病，你就可以按电铃、诬赖我们。”她希望对方保重身体、展开新人生，认为此事已经告一个段落，无论双方是否满意判决内容，“它（判决）已经是个答案了，我们都必须往前走。” +http://lady.163.com/17/1122/07/D3R37R1600267VA9.html +你和明星之间只差一个P图师！ +昨晚的维密大秀，除了奚梦瑶的一摔，亮点还挺多，比如国内来看秀的嘉宾们...连195cm的高以翔都能拍成这样，摄影师昨晚心情估计不是很好....其中的重灾区，就是我们的pgone同学.....摄影师怕是没被rapper打过....为了给万万挽尊，必须上官方的精修图了，明明是同一件衣服，腿长了一截不说，气场都不一样了...后期必须加鸡腿！港真，明星们真的应该给工作室的修图师们涨工资了，不上个对比图你们都不知道人家有多努力！这双鞋子，被网友diss惨了...然而，拯救这双鞋子的，是修图师！你们说，是不是应该给修图师涨工资？！上个月赵丽颖生日，她的工作室发了一组庆生照↓赵丽颖在下面和工作室开起了玩笑：“你们的图修的，真的惨不忍睹啊....”其实还好，哪有什么惨不忍睹。不过丽颖啊，其实工作室的小伙伴，已经很努力了，真的。你们再看看工作室发的精修图，画风秒变，年轻了10岁，也没那么油了。毛衣都从中黄色变成了柠檬黄。你们看，这程度的话，工作室已经很厉害了吧.....工作室发的照片，明明是同一个动作，瞬间高大上有木有。但是再看工作室发的精修图之后，首先整个皮肤变得都很通透，而且还很紧致，瞬间觉得有精神了。皮皮刚想硕给修图师加个鸡腿的时候，发现下面这张精修图是不是有点太夸张了，连胳肢窝都给磨平了...之前参加某活动的时候，他的现场照是这样的...嗯......比例嘛...有点....为了证明的确是现场照，上个动图↓然而，你们看看人家工作室之后发的图！是不是对修图师肃然起敬了，腿长两米有木有！甚至有些官媒发的图，还把裤腿给拉直了233333333333333....修图师下手好像重了些....对比照太残忍了......对大长腿有执念的，还有我们的晓明哥...结果有网友发现，为了拉腿，修图师把轮胎都给p成椭圆的了....后来豆瓣八组的网友，非常厉害的把轮胎恢复了原来的形状，晓明哥的腿也随之....短了一截....所以你们看看，一个靠谱又合格的修图师是多么重要！修图的时候下手不能太轻，不然跟原图没差，更不能太重，因为容易看出破绽....必须给那些有“起死回生之效”的修图师涨工资！最后一句你和明星只差一个负责的修图师！ +http://lady.163.com/17/1121/15/D3PDOEO500267VQQ.html +43岁的贾静雯生三个娃却依旧美成少女 秘诀是... +上周五，在Booking.com的助攻下，修杰楷更是为贾静雯承包了一座博物馆，在他的精心设计下，玻璃屋的角角落落都充满了爱与旅行的记忆。敞亮的客厅内尽是贾静雯热爱的美食美酒，手冲咖啡浓郁的香气和云朵棉花糖的甜腻四散在空气中；闪烁着暖黄色灯光的帐篷里，陈列着咘咘和BO妞最爱的玩具公仔；横空悬挂着的巨幅照片，诉说着修杰楷和贾静雯一起携手看过的风景。“从未想象过可以实现在博物馆住上一夜的愿望。Booking.com如此创新大胆的想法与我的梦想不期而遇，相信这一独特的‘博物馆之夜’一定会成为我和修难以忘怀的旅行体验。”收到这份特别礼物的贾静雯也深有感触，“有时候旅行就像是人生，我们在探索世界的过程中，会享受顺境，也会经历逆境，还好有修在我身边，无时无刻都能给予彼此最长情的陪伴。”修杰楷：有趣的故事挺多的，因为我是一个非常需要时间去整理很多东西的人，我就会在出发前两三天去打包行李，静雯已经养成一个坏毛病，很多东西都要问我，你准备了吗你准备了吗你准备了吗？我总是在最后一刻说，你的行李不要再给我了，我已经准备打包关箱了。她都会说等一下我还有什么东西没带。在国外买东西的时候，我都会计算我们带回去的空间够不够，往往都是在当地再买一个小箱子，因为静雯看到什么都会想要很兴奋的带回去给小朋友或者家人。我总是在旁边扮演计算的角色，空间带回去到底行不行。（贾静雯：你们可以知道我们家行李箱有多少个）但也是蛮有趣的，回到家里跟家人分享国外带的东西，给他们看的时候，他们表现出来的开心程度，真的像我们从当地希望跟他们分享的喜悦是一样的。修杰楷：我必须重申，我们真的没有想要秀恩爱这件事情。修杰楷：所以旅行其实是很好的方式，旅行是考验，确实是考验，你到另外城市的时候心情会不一样，回到家里你会回忆很多片段那都是有帮助的。贾静雯：《贾如幸福慢点来》谢谢大家支持，对我来说，这个书名就代表我想说的话，到了现在的我很想要用文字和我自己对对谈。我想透过文字，我自己很开心完成这本书，给我自己做一个很好的礼物。修杰楷：男生的话我会觉得是帽子吧，帽子在夏天时候可能是鸭舌帽棒球帽，在冬天的时候是毛帽，懒得整理头发的时候，好的帽子是加分的。 +http://war.163.com/17/1122/10/D3RE6ADC000181KT.html +美最先进攻击型核潜艇下水 验证新静音技术 + + （原标题：美最先进攻击型核潜艇下水 验证新静音技术确保美水下优势） + 美海军有史以来技术最先进的攻击型核潜艇现已下水。下水的美国“南达科他”号（SSN-790）潜艇是一艘弗吉尼亚级Block 3（第3批次）型潜艇，在设计上有诸多前所未见的水下技术创新。一些海军官员称，有关海军“声学优势”新研发工作的很多具体情况，自然不可展开公开讨论，但海军海上系统司令部女发言人科琳·奥罗克对“侦察勇士”网站说，美国“南达科他”号潜艇在验证先进技术方面起到了技术示范作用。海军官员解释称，目前进行的技术创新已经作为原型技术进行过多年测试，随着美国“南达科他”号潜艇入役，其中很多技术创新现已进入实用状态。海军技术研发商也普遍表示，“南达科他”号潜艇的先进水下技术经开发、整合、测试后如今已进入运行状态，这些技术包括旨在加大潜艇探测难度的轮机舱静音技术、新式大型垂直阵列声呐，以及为艇体提升“静音”性能的涂层。海军于10月14日在位于康涅狄格州格罗顿的通用电船公司造船厂，为美国“南达科他”号潜艇举行了下水仪式。奥罗克说：“作为第七艘Block 3型潜艇，‘南达科他’号将是执行巡逻任务中最先进的弗吉尼亚级核潜艇。”近年来，海军在研发新式声学、传感器及静音技术方面不断取得进展，确保了美国在水下技术领域占得技术优势。与此同时，中国和俄罗斯等国也在持续快速推进军事现代化进程和新潜艇建造工作。推动美国海军维护“声学优势”的具体原因是以下一个现实性苗头：俄罗斯和中国不断取得进展，美国的水下技术优势正在迅速缩小。被称为嵌入式技术的有关改进技术经整合后，最终将装配给弗吉尼亚级潜艇，以及目前处于研发阶段的新一代哥伦比亚级弹道导弹核潜艇。海军开发商解释称，这些理念被称为第四代水下技术，注重评估先进的水下电磁及声学技术。奥罗克还说：“从‘南达科他’号潜艇身上汲取的经验教训，将为此后研发的Block 5型及后续的弗吉尼亚级潜艇所用，从而加强美国在水下领域的优势，并确保美国在本世纪中叶乃至更长的时间内保持住优势地位。”“声学优势”理念旨在设计以下一种环境：美国潜艇可在敌方水域内或附近以及海岸线附近执行行动时不被敌方探测到，进而可执行侦察或攻击任务，还可在敌方探测范围以外探测各种动向或敌方活动。声学传感器技术的工作原理是，利用潜艇水下传感器探测声音脉冲信号，以确定敌方舰船、潜艇或来袭武器的轮廓、行进速度和距离。 +http://war.163.com/17/1122/10/D3RCFDGF000181KT.html +俄外长:美国在叙利亚利用恐怖组织来实现自身利益 + + （原标题：俄罗斯外长：美国在叙利亚利用恐怖组织来实现自身利益） + 【环球网报道 记者 李德意】据伊朗塔斯尼姆通讯社报道，俄罗斯外长拉夫罗夫11月21日称，美国在叙利亚利用恐怖组织来实现自身利益。据报道，拉夫罗夫表示，“我们与华盛顿在叙利亚问题上建立了相当稳定的合作关系”，但是，在征用恐怖分子和极端分子上存在很大分歧。“有消息表明，美国利用那些本该被孤立和摧毁的极端主义团体，来促成自身的计划安排，尽管美国声称涉足叙利亚只为消除恐怖组织。”拉夫罗夫强调道。根据报道，拉夫罗夫向媒体表示，他将与美国国务院高层接触，继续讨论叙利亚局势。 +http://war.163.com/17/1122/10/D3RCE89H000181KT.html +美国首次在阿富汗境内使用F22 参与摧毁鸦片运动 + + （原标题：美国首次在阿富汗境内使用F22战机 参与摧毁鸦片运动） + 【环球网综合报道】据美国有线电视新闻网11月21日报道，美国国防部发言人迈克尔?安德鲁斯透露，在本月19日，美国对阿富汗境内的鸦片加工场所发起了空袭。负责执行空袭行动的包括美国F-22“猛禽”战斗机，这也是F-22首次在阿富汗使用。此次空袭是美国和阿富汗联合行动的一部分，目标是北部赫尔曼德省塔利班控制区的毒品设施。安德鲁斯表示，此次空袭是由停放在阿富汗巴格拉姆空军基地的美国F-16和卡塔尔阿尔乌迪德空军基地的美国B-52飞机进行。驻阿富汗美军司令约翰?尼科尔森(John?Nicholson)将军告诉记者，一架美国F-22“猛禽”战斗机和阿富汗空军A-29也参与了这次空袭。美国官员表示，这次空袭标志着美国在阿富汗首次使用F-22。这架先进的隐形战机所处的基地是阿拉伯联合酋长国阿尔扎夫拉空军基地，它需要KC-10和KC-135飞机提供燃料补给才能抵达目标。美国空军中央司令部表示，美国海军陆战队还使用了长程高机动火箭系统，以支持这次行动。尼科尔森表示，在这次行动中有10个设施被击中，其中8个被美国飞机击中，2个被阿富汗战机击中。在其中1次空袭中，美国B-52轰炸机使用2000磅的炸弹摧毁了1个设施和50桶鸦片。他表示，这些鸦片黑市价值大约数百万美元。报道称，21日，阿富汗总统阿什拉夫?加尼通过推特网站宣布了这一行动。他表示，在国际部队的支援下，阿富汗军队在赫尔曼德发起了袭击，以废除鸦片加工实验场所。?分析人士认为，塔利班通过鸦片贸易获得大部分资金，而且越来越多地在其控制的地区加工毒品。(实习编译：李婧妍?审稿：谭利娅) +http://war.163.com/17/1122/10/D3RCACSL000181KT.html +外媒:特朗普称同普京进行了"极好的电话交谈" + + （原标题：外媒：特朗普称同普京进行了“极好的电话交谈”） + 【环球网综合报道】据俄罗斯卫星通讯社11月22日报道，美国总统特朗普同俄罗斯总统普京进行了一个小时的电话交谈。克里姆林宫新闻处发布消息称，通话中交流了必须保持叙利亚主权独立和领土完整的思想，以及反恐合作、乌克兰等议题。特朗普表示，他同普京进行了“极好的电话交谈”。据克里姆林宫消息，普京与特朗普详细讨论了鉴于叙利亚消灭恐怖分子军事行动结束，叙利亚当前面临的问题。普京强调，愿意为长期政治解决叙利亚问题发挥积极作用。另据白宫消息，两位总统还强调执行联合国安理会第2254号决议的重要性，以及支持在联合国领导下日内瓦进程的重要性。白宫方面称，两位总统还重申在整个中东和中亚地区共同打击恐怖主义的重要性，并同意探讨就打击“伊斯兰国”、基地组织、塔利班和其他恐怖组织展开进一步合作的途径。 +http://war.163.com/17/1122/10/D3RC1K3R000181KT.html +外媒：继中国之后 苏丹获得首批苏35战斗机 + + （原标题：外媒：继中国之后 苏丹获得首批苏35战斗机） + 【环球网军事报道】据“防务世界”网站11月21日报道，苏丹成为首个获得苏-35战斗机的阿拉伯国家，同时也是除中国外又一个苏-35海外用户。据报道，在苏丹总统本周首次访问莫斯科之前，首批苏-35战机已经于11月20日交付苏丹空军，目前交付的苏-35数量还未公布。苏丹空军副司令赛义德表示，苏丹和俄罗斯有关苏-35交易的协议于今年3月份签署，这些战机将有助于巩固苏丹的国防，能“应对任何威胁”。据悉，在苏丹总统访俄期间，两国将可能签署有关采矿、石油和防务等多项协议。 +http://war.163.com/17/1122/10/D3RC0SGH000181KT.html +巴沙尔当面感谢普京:多亏俄罗斯拯救了叙利亚 + + （原标题：巴沙尔当面感谢普京：多亏俄罗斯拯救了叙利亚） + 【环球时报驻俄罗斯特约记者 林涵 柳玉鹏】俄罗斯21日发布消息称，叙利亚总统巴沙尔20日访问索契，与俄总统普京举行会谈。巴沙尔上次访俄是在2015年，俄开始在叙军事行动不久后。对于俄叙总统此次会谈，俄总统新闻秘书佩斯科夫21日表示，两国总统讨论了叙政治调解的可能方案。俄罗斯官方是在巴沙尔访问索契后的第二天发布消息的。据俄新社21日报道，普京与巴沙尔20日会谈了大约4小时。普京表示：“我认为，现在最重要的是转向政治进程，很高兴您准备好与希望和平解决问题的各方合作。”巴沙尔对普京说，多亏俄罗斯，叙利亚才能作为一个完整的国家得以拯救。俄罗斯空天军的行动非常成功，推动了叙利亚政治和解进程。在巴沙尔访俄的消息发布后不久，俄新社21日报道称，在俄叙总统会谈后，俄罗斯总参谋长格拉西莫夫表示，在叙利亚军事行动的积极阶段已经结束。叙利亚冲突后期的调解工作开始前，必须巩固所取得的军事胜利，防止恐怖分子卷土重来。俄卫星新闻网称，普京21日表示，叙政府已控制了叙利亚超过98%的领土。他还说，俄制武器的有效性在叙利亚反恐行动实战中获得了证明。巴沙尔上一次访俄是在2015年俄空天军开始在叙军事行动后不久。22日，俄罗斯、伊朗和土耳其三国领导人将举行推进叙利亚和平进程的峰会。伊朗总统鲁哈尼21日也宣布，此前盘踞在伊拉克和叙利亚境内的“伊斯兰国”(IS)极端组织已被战胜。俄罗斯《消息报》21日援引俄总统新闻秘书佩斯科夫的话称，在与巴沙尔会谈后，普京将与美国总统特朗普交流与巴沙尔会谈的情况。俄塔社21日报道称，俄罗斯国家杜马议员热列兹尼科夫认为，俄叙两国总统在叙利亚局势由军事行动阶段转向政治调解时期进行“对表”，将对叙利亚政治对话产生积极影响。俄罗斯联邦委员会国防与安全委员会第一副主席克林采维奇表示，俄叙总统会面表明，叙利亚战争将结束，但反恐战争结束后，俄罗斯在叙利亚的军事基地仍将保留，以保障叙利亚的稳定和防止外部干涉。 +http://war.163.com/17/1122/10/D3RBVOI0000181KT.html +印拟斥巨资租世界最空机场监视中方汉班托塔港 + + （原标题：印拟斥巨资租世界最空机场监视中方汉班托塔港） + 资料图【环球时报驻印度特约记者易简】“斯里兰卡总理来访，印度紧盯在汉班托塔附近租机场”，斯里兰卡总理维克勒马辛哈21日开始对印度进行访问，印度向斯租赁汉班托塔港附近马塔拉机场的计划成为印媒关注的焦点。据《印度教徒报》报道，维克勒马辛哈访问印度期间，将与印度总理莫迪举行双边会谈，并拜访总统科温德，他还将参加在新德里举行的全球网络空间会议。该报称，印度和斯里兰卡正在就一项经济和技术合作协议进行谈判，协议或包含允许印度开发斯里兰卡汉班托塔港附近马塔拉机场的条款。《印度时报》报道称，中国此前宣布投资11亿美元租用汉班托塔港，这将减轻斯政府的债务负担，同时也意味着中国几乎永久拥有该港口所有权。印度希望以2亿多美元的价格租用马塔拉机场40年，问题是该机场位置偏僻，被戏称世界上“最空的”机场。报道称，印度想为国内航线租用该机场，也有一些模糊的计划，比如将其作为训练场或货运中心。从安全和战略角度来看，印度可通过租用该机场监视汉班托塔。印度《自治》周刊网站21日则称，斯里兰卡由于在重要航线上占据的位置，再次成为印中地缘政治战略的交叉点。该国际机场是中国公司承建,在维克勒马辛哈访问印度之前，印度就表示出对租用马塔拉国际机场的兴趣。 +http://war.163.com/17/1122/10/D3RBSED1000181KT.html +专家:琼州海峡铁路轮渡军事运输和南海无关 + + （原标题：专家：琼州海峡铁路轮渡军事运输和南海无关） + 【环球网军事11月22日报道 环球时报记者 郭媛丹】中国军方媒体20日的一则报道引起关注——琼州海峡铁路轮渡首次组织平车跨海军事运输。据报道，近日，“粤海铁4号”渡轮载着装有装备器材的平车军列缓缓驶出粤海铁路南港码头，跨越琼州海峡，所用时间比换乘海上船舶运输缩短近10小时。这是粤海铁路通车以来首次组织平车跨海军事运输，标志着琼州海峡铁路军事运输保障能力实现新跨越。到底这一名称听起来有些陌生甚至拗口的演练有什么用，又是针对什么具体课题设置的呢？据报道，粤海铁路轮渡于2003年开通运营，为国家I级干线，距离22.5公里。过去粤海铁路轮渡只能办理客车、棚车和敞车等车型过海，一直未开办平车军事运输和超限军事运输业务。陆岛衔接主要靠水路运输，进出海南岛的装备需采取铁水联运方式，铁路运输大运量、高效率、全天候的优势未充分发挥。据介绍，平车军事运输和超限运输的开通运营，突破了粤海铁路轮渡的运输限制，打通了部队进出海南岛的铁路通道，提升了粤海铁路战略投送能力和部队快速反应能力，对于完善我国铁路军事交通网络、满足日益增多的运输需求具有十分重要的意义。下一步，军地有关部门将积极协调交通、海事等部门，进一步细化琼州海峡铁路轮渡军事运输组织，规范程序、明确标准，确保各项军事运输任务圆满完成。海军军事学术研究所研究员张军社21日接受《环球时报》记者采访时表示，这次运输进一步完善了我国铁路军事交通网络，提高铁路战略投送能力和部队快速反应能力，标志着琼州海峡铁路军事运输保障能力实现了大跨越。过去进出海岛通过陆地铁路，然后是水路运输，在这个过程中人员需要换乘。现在利用铁路轮渡，实现了人员、物资整列直接跨海运输，进出海岛人员、物资速度大幅提高，节省了装卸过程，运输能力提高。对于这一演练有没有针对特定方向，比如南海，张军社对《环球时报》记者回应称，这种演练并不针对特定的战略方向或者目标。 +http://war.163.com/17/1122/10/D3RBRBPB000181KT.html +解密歼15战机拦阻系统：大大小小试验做了上万次 + + （原标题：解密歼15战机拦阻系统：大大小小试验做了上万次） + 我国首款舰载机歼-15，也叫“飞鲨”。2012年11月25号，当歼-15舰载机在航母辽宁舰上成功降落时，引来世界普遍关注的目光。作为中国航空工业发展中一款具有里程碑式的舰载机，歼-15，是怎么研制、打造出来的？又是什么支撑研发人员们呕心沥血，甚至付出生命的代价去研制歼-15？　　攻克难题仅花两个月 科研人员搏命歼15歼-15舰载战斗机是中国航空工业沈阳飞机工业集团承担研制的。它长22.28米、翼展15米、高5.92米;有12个武器外挂点，可挂载空空导弹、反舰导弹、火箭弹、航空炸弹等多种武器;配装2台大推力发动机，最大起飞重量32.5吨，最大飞行速度2.4马赫，实用升限20000米，航程3500公里。2012年11月25日，歼-15舰载机在我国第一艘航空母舰辽宁舰上首批完美着舰，成功实现双剑合璧，中国航空工业由此实现从陆地到海洋的跨越。在国外看来，至少要花上一两年时间，才可能攻克的舰载机起降问题，却让中国航空工业的英雄团队，仅在辽宁舰服役两个月就做到了。但就在世界见证中国智慧、世界奇迹的时候，歼-15舰载机总指挥长罗阳却因积劳成疾，永远地离开了，去世时，他年仅51岁。是什么让研制人员不惜牺牲生命的代价，也要打造这款世界先进能力的舰载机？孙聪，56岁，先后担任歼15等多种型号战斗机的总设计师。说起歼15研制过程中的自主创新，孙聪仍然觉得这是一个很大的挑战和课题。中国航空工业集团公司科技委副主任歼15总设计师 孙聪：实际上我们是，朦朦胧胧的懂舰载机，但是并不完全懂舰载机，在这样一个前提下，我们接到这个任务，就开始做这项工作。实际上对整个设计生产、设计制造这两大领域来说，都是具有挑战性的。孙聪说，舰载机与陆地上战斗机最大的不同，就是舰载机在航母狭小的跑道上起飞、降落，而一般航母甲板上的飞机跑道长度只有100多米，大约只相当于陆地跑道的十分之一。如何让飞机在这么短的距离里平稳起飞，一直是困扰他们的一道难题。孙聪所在的沈阳飞机制造厂是新中国第一家飞机制造厂，但过去产品主要是传统和民用飞机，十几年前，接到设计生产航母舰载飞机的研发任务时，孙聪和他的同事们清楚地知道舰载机研制是一场必须打赢的硬仗。而这场没有硝烟的战斗刚一打响，就面临设计手段、设计方法的重大改变，当时发达国家早已开始在电脑上用软件设计飞机，而孙聪他们还停留在用笔画图的阶段，他们决定要在歼15上尝试全新的数字化设计方法。既然是全数字化操作系统的高科技产品，无论在什么条件下都必须保持网络畅通，成了舰载机首先必须攻克的技术难题。因此，研制中，设计师们围绕航母周围的复杂电磁环境，开始各种设计和试验。孙聪：电磁环境是非常恶劣的，跟陆上飞机相比，不是一倍两倍的关系，是很多倍。那就要考虑三方设计，我们在整个的试验鉴定过程中，是严格按照鉴定程序，有全机的、体系内的，做电磁防护的设计，进行试验验证，最后才拿得出去的。 就是说它们不能干扰，不能由于前边的环境，激发着火这些东西。取保舰载机通信畅通仅仅是设计的第一步，在航母上比起飞还要难的实际是降落，拦阻钩、拦阻索系统直接决定舰载机着舰的成功与失败。然而，拦阻系统是中国飞机制造的一大空白，更是航空工业沈飞公司面临的一道全新课题。设计方案反反复复，大大小小的试验做了上万次，中国自主研制的国产拦阻钩、拦住索系统终于成功研制，但设计师们还没有来得及品尝成功的喜悦，新的难题又迎面而来。孙聪：确实很难，但是更难的东西还有很多。一个就是舰载机载荷怎么定义的好，当然你这个就是机组载荷怎么算？那是减重最好的办法。第二就是舰载机灵巧的结构，我会用最小的代价设计结构，承载能力很强，这是水平问题。第三个就是舰载机制造材料。【半小时观察】近几年我们看到中国的军事装备呈现井喷式的发展，这首先依赖于综合国力的提高，其次就是我们国家对国防建设的重视，而且不断在军工企业内部进行体制变革，像沈飞就在酝酿公司重组，中航黑豹收购沈飞的重组方案已经获得证监会的通过，有望成为中国战机第一股，而通过这样的军民融合将激发军事装备更新研制的活力。今天上午AC312E直升机在海拔3293米的云南宁蒗机场成功完成高原试飞，这款直升机经过了次高原、高高原和高原试飞三个阶段，在进行高高原试飞时，AC312E飞越自然条件复杂多变的青藏高原，最大飞行高度达到6300米，只有持续创新，我们的航空工业才能砥砺前行，不断超越。 +http://war.163.com/17/1122/10/D3RBQ335000181KT.html +外媒:东风41与美俄导弹没差距 可开发海基型 + + （原标题：外媒：东风41与美俄导弹没差距 可开发海基型） + 资料图【环球网军事11月22日报道】据新加坡《联合早报》网站11月21日报道，有专家指出，属于全新一代战略威慑武器的东风-41型，射程、速度、弹头数量和突防能力等主要技术参数与美国、俄罗斯的新型洲际导弹已经没有代差。接近中国军方的人士对《联合早报》分析说，与东风-5型、东风-31型等中国现有的几款洲际导弹相比，东风-41型属于全新一代战略威慑武器，它的射程、速度、弹头数量和突防能力等主要技术参数与美国、俄罗斯的新型洲际导弹已经没有代差。除陆基机动发射外，东风-41导弹还可开发海基型，列装后将使中国核威慑能力达到与美、俄比肩的程度，是名副其实的“大国重器”。这名人士介绍，长期以来，中国的战略核威慑主要依靠的东风-5系列洲际导弹，进入新世纪后，中国开发出增程型东风-5A、多弹头分导型东风-5B以及东风-31型，射程基本能够覆盖有核国家。但是东风-5型导弹主要依靠地下发射井进行战备值班，一旦爆发核战，这类发射井很容易被对手摧毁。同时，面对新一代导弹防御系统，东风-5和东风-31型导弹的突防能力都显得不足，战略威慑力自然也大打折扣。 +http://war.163.com/17/1122/10/D3RBP0FM000181KT.html +解密中国"战场之眼"：防空反导反隐身样样俱全 + + （原标题：解密中国“战场之眼”：防空反导反隐身样样俱全） + 资料图【环球网军事11月22日报道 环球时报特约记者 张亦驰 环球时报记者 刘 扬】日前央视播出了《走出国门的“中国神器”：极目千里的奥秘》专题片，重点介绍了中国电子科技集团公司(以下简称中国电科)所属第14研究所的多款新型雷达。中国电科第14研究所被业界誉为中国雷达工业的发源地。通过该片以及近期公开的信息，《环球时报》记者发现，该所研制的雷达覆盖海陆空天平台，功能涵盖机载火控雷达、空基预警雷达、防空反导、炮位侦察等众多领域，一些中国军迷耳熟能详的大装备、新型号很多都和这个研究所有着千丝万缕的联系，比如国产航母、中华神盾、反隐身雷达等等，其中一些外销型号还在国外经受了实战考验。先进雷达让“枭龙”战力大增节目首先报道了用于改进“枭龙”战斗机的轻型有源相控阵雷达，该雷达能在100多公里的距离跟踪多批机动目标。尽管央视并未透露该雷达型号，但是根据之前在珠海航展上公开的信息，这型机载雷达型号应为KLJ-7A有源相控阵火控雷达，探测距离大约170公里。它是在KLJ-7基础上使用有源相控阵技术进一步升级设计的型号。一位不愿透露姓名的军事专家对《环球时报》记者表示，“枭龙”采用有源相控阵技术之后，其探测距离已经达到甚至超过歼-11B这种重型战斗机安装的采用平板裂缝天线的脉冲多普勒雷达。而且新雷达抗干扰性能、反侦察性能都大大领先于传统三代机的机械扫描雷达，基本与F-35的雷达相当。简言之，“枭龙”安装这种雷达后，在中距对抗未使用有源相控阵雷达的F-16C/D，甚至基本型的F-15C/D重型战斗机时，都可能具有一定优势。众所周知，歼-20、歼-16和歼-10、歼-11系列的最新改进型都使用了有源相控阵雷达，由于其机头直径更大，可以安装更多收发组件，探测距离更远。这些雷达安装在高端战机上，必然采用更多的新技术，具有更多模式，性能将更为先进。防空反导反隐身样样俱全除了机载雷达以外，反隐身雷达也是当今雷达领域一个重要发展方向。14所在珠海航展、巴黎航展等场合曾多次展出多种系列反隐身雷达。简氏信息集团网站本月6日则报道了该所的多型先进雷达。其中SLC-7雷达的性能要超过以色列的EL/M-2080S“绿松”相控阵多功能雷达。据报道。SLC-7对雷达反射面积为0.01平方米弹道目标的跟踪距离超过300公里，对0.05平方米目标的探测距离超过450公里，最大跟踪高度超过3万米。而且该雷达具有高机动性，能在15分钟内机动到新阵地。据简氏报道，近年来，该所还推出了YLC-8B中高空远程三坐标监视雷达，该雷达可通过公路、海上和铁路机动，6个乘员能够在30分钟内扯收架设完毕。该雷达能够在550公里远的距离上探测跟踪传统多任务作战飞机，对低可探测性目标的跟踪距离大约350公里。该雷达是世界上为数很少的能够远距离连续跟踪西方第五代战机的雷达系统之一。据中国电科相关人员在巴黎航展期间向《环球时报》记者介绍，YLC-8B工作在UHF波段(特高频)，研制时就重点考虑了现代战场中隐形飞机威胁。这种电磁波的波长较长，照射到隐形飞机后会形成绕射现象，故而有利于发现隐身目标。此外，14所的情报雷达大量配属给地空导弹部队。据14所的微信公众号近日报道，前段时间空军“蓝盾-2017S”演习中，地导部队使用了该所研制的多种目标指示雷达，从其配图来看，包括“红旗-9”导弹营配备的一种有源相控阵目标指示雷达和一种双面大型无源相控阵雷达，后者被认为是一种帮助“红旗-9”进行反导作战的大型搜索雷达。海陆空通吃据一位熟悉情况的中国军事专家对《环球时报》记者介绍，近年来，14所在满足解放军需求的同时也积极走向国际军贸市场，如通过向巴基斯坦出口预警机实现了我国在该领域的突破，并且开创了联合研制、联合生产的创新军贸模式。而SLC-2系列炮位侦测雷达在国外的实战中表现神勇。据报道，该雷达不仅可以在敌方炮弹落地前解算出其火炮坐标，方便我方火炮实施压制摧毁，还可以为我方火炮进行校射，让我方火炮打得更准。南亚某国政府军在与恐怖分子作战中，饱受后者火炮袭扰，而恐怖分子躲在森林里面开炮，政府军很难发现。中国的炮位雷达、侦察雷达部署后，很快对恐怖分子的炮位实施定位，政府军后来全面占领了战场上的主动权。上述专家表示，14所还在舰载雷达领域收获颇丰。中国的052C/D系列驱逐舰之所以被称为“中华神盾”，主要是因为装备了有源相控阵雷达，而这种雷达就是14所研制的“海之星”雷达。该雷达是世界上首部实用的集搜索、跟踪、引导等功能于一体的舰载多功能有源相控阵雷达，在体制上要比美国SPY-1先进一代，为中国海军驱逐舰的对空探测设备赶超世界先进水平奠定坚实基础。而辽宁舰和首艘国产航母同样安装了“海之星”系列雷达。据外媒推测，055万吨大驱的大型对空雷达也很可能是“海之星”的发展型号。 +http://news.163.com/air/17/1122/11/D3RG3TDU000181O6.html +济南直飞太原航班全无 或与直达高铁将开有关 + + （原标题：济南到太原航班已“撤”） + 不久前，有一则新闻被广泛热议，那就是西成客专还未开通，成都直飞西安的航班便尽数取消了，无独有偶，这石济客专还未开通，济南直飞太原的航班也提前“撤场”了。高铁何时开通暂时还没准确消息，现在两地交通陷入了“尴尬真空期”。　　济南直飞太原的航班全没了最近有省城去太原的市民惊讶了，济南到太原居然没有一趟航班，而且未来一个月都没有。“我大学同宿舍姐妹在山西临汾，因为她大学时常往返济南太原，她买票时我见到一天有四五个航班可选择。结果，毕了业我要去山西参加她的婚礼，却发现济南到太原居然一趟飞机也没有了。”随后，记者打开数个订票软件查询济南至太原航段，均显示“抱歉，没有可查询的航班”。多个网络售票平台的工作人员告诉记者，在执行冬春航季航班计划后，往返济南与太原之间的直航航班几乎全取消，最优的方案只能是绕回烟台中转，时间需耗费至少五六个小时，而以往，两城之间的航班只需不到2个小时。　航班取消或与直达高铁将开有关根据国际惯例，航班计划被分为夏秋和冬春航季，夏秋航季是指当年3月最后一个星期日至10月最后一个星期日的前一天，冬春航季是指当年10月最后一个星期日至翌年3月最后一个星期日的前一天。各航空公司会按照民航生产需要来调整航班，增加热门航线运力投放，同时停飞或减少市场需求不足的航班班次。济南遥墙国际机场的一位工作人员告诉记者，按照计划，其实今年以来，济南到太原的航班数量就开始骤减了，虽然不是每天都执飞，但起码一周有两三天是有航班的。但进入冬春航季后，确实没有航空公司安排这段航线的运力了。而在以前，无论是冬春航季还是夏秋航季，济南到太原的航班每天都至少三四班，相比以往，两地的直航航班成了真空地带。一位业内人士告诉记者，航空公司之所以取消了全部的济南与太原之间的往返航班，或与即将开通的石济客专存在一定关系。高铁开通后，济南至太原的直达高铁仅需要三小时左右，类似于济南到南京，二等座票价估计在300元以内，这个时间这个票价飞机对于高铁几乎没有竞争力。　高铁暂无开通日期据了解，石济客运专线是国家规划“四横四纵”快速铁路网的最后“一横”——太原至青岛客运专线的组成部分，起自河北省石家庄市，向东沿既有石德铁路经河北省石家庄市、衡水市、沧州市、山东省德州市，至济南市。2014年3月16日，石济客专山东段先行开工，2016年7月15日山东段开始铺轨，2017年5月10日全线铺轨完成，9月8日全线接触网成功带电。按照工程进度，石济客专将于2017年底先行开通到济南西站，而经由济南新东站计划2018年内与济青高铁同步开通。但目前，即便是仅至济南西站，铁路也并没有准确的开通时间。而记者查询发现，目前济南去太原的高铁需要绕行天津，全程5个多小时，每天只有很早从济南西站发车的一趟列车。而济南与太原之间的普通列车，耗时最短的也需6个多小时，慢点的就要近10个小时。 +http://news.163.com/air/17/1122/17/D3S5LRAN000181O6.html +一架载11人美国军机在冲绳海域坠落 3人下落不明 + + （原标题：美军一架载11人军机在冲绳海域坠落 3人下落不明） + 据日本NHK新闻报道，有消息称，22日下午，美军C2运输机在冲之鸟礁西北约150公里的海上坠落。据称，当时运输机上有10至11人，其中已有8人获救，其余人员状况不明。目前尚不得知是否有人员受伤。该架美军C2运输机是位于日本神奈川县横须贺基地的美军核动力航空母舰“里根号”的舰载机。据称，当时美军正同日本海上自卫队参加训练。美军曾通知日方发动机或有故障。没有消息表明运输机上有日本自卫队员。目前，日本防卫省正向美军了解详细情况。日本防卫大臣小野寺对记者表示，“现在美军正同日本海上自卫队进行搜索，自卫队已派出军舰和船只。”他还表示，“将尽力协助搜救下落不明的人员。由于美军飞机事故不断，希望美方今后能够做到安全飞行。” +http://news.163.com/air/17/1122/14/D3RS5MMS000181O6.html +民航法国际公约冲突 马航案能否破解"限制赔偿" + + （原标题：【社论】马航案能否破解民航“限制赔偿”？） + 马航370案件终于在北京进入了诉讼阶段。家属们提出的索赔金额在1000多万到7000多万元之间。公众很同情家属这三年多来的各种身心煎熬，但是就空难索赔诉讼本身来说，可能是另一场漫长的拉锯战。空难案件的特殊性在于，其赔偿标准不适用一般民事法律，而是适用《民航法》以及国际公约的相关规定，国际航班的空难更涉及到复杂的国家管辖，以及国内法与国际法的冲突问题。最关键的是，空难案件绕不开“限制赔偿”这道坎，法定赔偿往往难以满足受害方的要求。我国的国内法《民用航空法》吸收了国际条约中的“限制赔偿”这个原则。《民用航空法》第129条规定，国际航空运输承运人对每名旅客的赔偿责任限额为16600计量单位（“计量单位”即SDR，是指国际货币基金组织的特别提款权）。按目前的汇率，16600计量单位只相当于15.5万人民币。而对于国内航班，2006年确定的法定的限额赔偿是每人40万元。但是，事实上，之前多次国内空难的实际赔偿额都高于这个标准的，比如，2010年伊春空难每人赔付96万元，被称“创下中国民航史空难赔偿的最高额”。至于，屡屡闹出新闻的“航空行李丢失‘按公斤赔’”，也是源于《民用航空法》的“限制赔偿”原则。但是，哪怕前述的“最高赔偿额”恐怕也难以让空难家属满意。为了绕开“限制赔偿”的壁垒，空难受害者家属也会选择其他应对方式：一个就是起诉飞机的制造商、发动机制造商；另一个是，选择到美国等空难赔偿额较高的地区提起诉讼。比如，2004年发生的包头空难，家属认为东航提出的赔偿偏低，到美国法院一并起诉了美国通用公司（发动机制造商）、加拿大庞巴迪公司（飞机制造商）和东航。但是，东航提出管辖异议，美国法院最终以“不方便管辖”终止了审理，之后案子又回到中国起诉，至今还没有做出终审判决。这次马航案在起诉航空公司的同时，还起诉了飞机制造商波音公司、发动机制造商罗尔斯公司，以及保险公司，包括在北京起诉的同时，还在美国诉讼，也是使用了这一套诉讼策略。但是诉讼过程显然也会是很曲折的。对于马航370的家属来说，还有一个令人宽慰的消息是，我国加入的《蒙特利尔公约》引进了“无限制责任”，不超过10万SDR的(约合13.5万美元)，不管有无过错，承运人必须赔偿；超过部分，实行推定的过失责任。但是，中国法院绕开“限制赔偿”，直接适用《蒙特利尔公约》做出空难赔偿判决，之前没有先例；而且对于航空如何推定“过失”，也缺乏相应的审判实践。总之，从“航空行李丢失‘按公斤赔’”，到国内空难“法定”最高赔付40万元，再到这次马航家属提出的上千万元的索赔，其实都是指向民航“限制赔偿”这个症结问题。在国内法、国际公约之间，在法定赔偿畸低和当事人的正当诉求之间，如何寻找到公正的平衡点？如何树立起中国式空难判决的标杆？这是目前公众对于北京铁路运输法院的期待。 +http://news.163.com/air/17/1122/18/D3S8JODP000181O6.html +脸书、空客联手发展高空无人机 可提供互联网服务 + +http://news.163.com/air/17/1122/17/D3S73734000181O6.html +布达佩斯机场成首个采用远程塔台的中型机场 + + （原标题：布达佩斯机场成全球首个采用远程塔台的中型机场） + 据外媒报道，匈牙利空中导航服务商HungaroControl与远程塔台和数字化机场解决方案提供商Searidge Technologies合作开发的远程塔台系统，已获得现场运行认证。布达佩斯机场将成为全球首个采用远程塔台技术的中型容量机场。该系统获得了匈牙利民航局的认证，这意味着在没有容量限制和无需对现有塔台实施影子运营的情况下，能够从远程塔台提供即时管制服务。布达佩斯机场的远程塔台概念建立在，对现有地面监视系统和恰当定位的摄像机网络的双向集成基础上，旨在提高管制员的情境意识和飞行安全。称为A-SMGCS的地面监视系统，使布达佩斯机场的塔台在没有任何目视参考的情况下（特别是在恶劣天气），可以管制达到最大容量70%的航班起降。机场机动区安装的分布式固定相机和PTZ摄像机，配有温度传感器，可以独立控制并覆盖整个机动区。捕捉到的视频图像将传输到一个大型的视屏墙上，为管制员提供通用和特定的图像信息。实时图像可以用图形符号和飞行数据进行标记。管制员还可以根据偏好使用地理边界等条件，来调整图像。去年年底，HungaroControl和Searidge成功完成了将远程塔台整合到布达佩斯机场的相关测试。在测试期间，成功管制了近600个航班起降。共有13名管制员参与了这一测试，所有管制职能交给了由4名管制员和1名管理人员组成的班次承担，并提供了顺畅的空中交通管理服务。这一系统将被用于应急运营、现场培训，以及作为一个后备系统，但HungaroControl的目标是2018年前，在布达佩斯机场实现远程塔台的全时段运营。 +http://sports.163.com/17/1122/22/D3SMBF9400058781.html +欧足联最佳阵容50人大名单:梅罗领衔 皇马11人入围 +网易体育11月22日报道： +http://sports.163.com/17/1122/17/D3S52J2Q00058780.html +球童抱球不放拖时间帮主队夺冠 赛后一起举奖杯 +网易体育11月22日报道：北京时间11月21日，澳洲足总杯决赛在悉尼安联球场举行，坐镇主场的悉尼FC历经加时，艰难的以2-1的比分击败了阿德莱德联，在家门口摘得桂冠。然而这场火星四溅的比赛却因为加时赛中和赛后的一幕而显得颇有争议。起因发生在加时赛第115分钟，彼时由前锋波波打入1球的悉尼FC以2-1领先，时间所剩无几，阿德莱德联争分夺秒想提速进攻以求追回比分。然而在悉尼队员将皮球解围出界后，阿德莱德等候发边线球的队员却迟迟没有接到球童掷来的皮球。原来主队的小球童眼看自家球队胜利在望，耍了个心眼，拖着不肯给阿德莱德队员皮球想着耽误些比赛时间。这下可惹火了落后中的阿德莱德队员，边后卫马罗内直接扑上去就把小球童撞倒想要抢走皮球，结果不堪“自己人”被欺负的悉尼队员也一拥而上，场面顿时一片混乱。最终裁判分别罚下了撞人的马罗内和参与斗殴的悉尼前锋西蒙才算了事。比赛结束，2-1艰难夺冠的悉尼FC自然是一片欢天喜地。然而不知道是出自什么考虑，本应只有球队人员参与的夺冠捧杯仪式却出现了一位“既熟悉又陌生”的小面孔，正是刚才因为拖延给球导致大冲突的小球童！特别是颁奖台上的悉尼众将对这位“功臣”还非常看重，特地让他与球队队长一齐举起了冠军奖杯。一时间舆论非议声四起，因为这位用了不太光明的“盘外招”的小球童，如今却被悉尼FC视为“夺冠功臣”，一旦这种行为被传播开来，无疑会降低澳洲足球在世界足坛的公信度，想必夺冠的悉尼FC要好好遭受一番口诛笔伐了。 +http://sports.163.com/17/1122/18/D3S8PTQ200058780.html +热身-新帅首秀遭惨败 中国女足全场被动0-3澳洲 +网易体育11月22日报道：比赛概况日前中国女足做出重大调整，球队一分为二，分别组建了红队和黄队，其中红队作为主力队伍，将代表国家参加各类国际赛事。原中国女足主帅布鲁诺下课，冰岛籍教练埃约尔松成为红队新帅。按照计划，中国女足红队将在11月底前往澳大利亚进行2场热身赛。根据FIFA官方统计，中国女足与澳大利亚女足国际A级赛交锋38次，中国女足19胜10平9负。【精彩瞬间】比赛开始后，中国女足被澳大利亚压制，场面十分被动，但主队也没有获得很好的射门机会。第23分钟，久攻不下的澳大利亚利用一次定位球机会打破僵局。埃格蒙德左路角球传中，中国女足盯人不紧，克尔后排前插甩开李丹阳的防守，马君门前也没未能阻挡住克尔的前插，后者后点利用身体优势高高跃起头球破门，中国女足0-1落后！此后，布特和福尔德先后在禁区内完成一脚抽射和头球攻门，但都没有打在球门范围之内。上半场45分钟，中国女足射门数是尴尬的0！第49分钟，中国女足险些再次丢分。福尔德中路送出身后球，中国女足防线再次出现漏洞，克尔杀入禁区形成单刀赴会之势，在禁区左侧面对赵丽娜一脚抽射偏出球门。第53分钟，中国女足再丢一球。福尔德禁区左侧倒三角回敲，中国女足禁区前沿保护不力，布特弧顶左侧稍做调整后起脚射门，球打在防守队员身上后变线，赵丽娜措手不及，球直接吊入球门，中国女足0-2落后！第59分钟，澳大利亚在布特进球相似的位置获得任意球机会，肯尼迪主罚，球绕过人墙飞向球门左下角，赵丽娜做出精彩扑救，将球扑出底线。第64分钟，中国女足再次暴露出禁区前沿保护不力的弊端，丢掉第3球。洛佳索发出前场左侧界外球，中国女足禁区线前沿一片空旷地带，克尔极为轻松的调整，在弧顶前沿轰出一记世界波，球直飞球门右上角，赵丽娜无可奈何，中国女足0-3落后！第67分钟，任桂辛前场左路突施冷箭，可惜球没有打在球门范围，这是中国女足唯一一次射门！补时第2分钟，薛嬌左路送出高质量传中，李影门前高高跃起，力压防守队员头球攻门，球在飞入球门的一瞬间被替补门将坎贝尔单掌托出横梁。这是中国女足全场最有威胁的一次射门。1分钟后，韩鹏力压战术角球，在前场右路打出一脚远射，可惜没有打上力量。此役，中国女足全场仅有3次射门，而且都是在下半场完成。【双方阵容】中国女足出场名单(4231)：1-赵丽娜；2-刘杉杉(76’13-薛嬌)、5-吴海燕、32-马君、33-李丹阳；23-任桂辛(82’12-李影)、20-张睿；21-许燕露(76’17-韩鹏)、7-王霜、9-唐佳丽(61’36-宋端)；11-王珊珊；未上场替补：4-高晨、6-李冬娜、8-娄佳惠、10-姚凌薇、16-杨莉娜、18-毕晓琳、22-李雪彦、28-陆菲菲澳大利亚出场名单(4141)：18-阿诺德(82’12-坎贝尔)；14-肯尼迪(46’6-洛佳索)、7-凯特利、4-波尔金霍恩、16-拉索；10-埃格蒙德；9-福尔德、19-戈里、13-布特(67’17-西蒙)、11-德范娜(86’22-克拉默)；20-克尔(86’23-海曼)；未上场替补：1-威廉斯、2-哈里森、5-阿勒维、8-奈特、21-卡彭特 +http://sports.163.com/17/1122/11/D3RG0LDH0005877U.html +18分+4帽!周琦助毒蛇大胜 5犯后单节轰10分收官 +网易体育11月22日报道：本场比赛双方打得很激烈，首节比分就是你来我往，互相纠缠，周琦状态很不错，进攻、防守都有闪光点，开场后，队友进攻不中，就是周琦狂抢篮板，得到二次进攻机会打进，防守端他也是秀存在感，抢断、盖帽不时闪光，之后，周琦还和奥努阿库来个双塔连线，空中接力得分！首节双方打成36-35，毒蛇领先1分。次节周琦依然在防守端发威，比如喧嚣队打出一波快攻反击，周琦从空中直接把对方的突破上篮扇飞，这帽太狠，现场解说也是高呼：“我的老天！”当然，周琦也暴露出一些经验不足的问题，上半场最后阶段，他在防守端犯了错误，一方面是补防慢了，另一方面是扑得太凶，结果被对手生造了一个2+1，这样的失分很打击士气，看得出来周琦也是有一些沮丧。进入下半场，周琦在进攻中吃了一个犯规，但他的情绪没有被影响。不久后，周琦卷土重来，这次他在左侧接球，面对防守人一路的跟随，他强起上篮，打进还制造加罚，周琦也和队友们击掌庆祝。比赛开始倾向毒蛇这边，他们打出更好的防守，迫使抢夺队在3分钟的时间内仅得到2分，而毒蛇自己得了14分，场上分差也就此拉开，之后毒蛇一直保持领先优势。末节，虽然周琦5犯规了，但教练还是把他放在场上，解说员们也是讨论一番，都认为即便周琦被罚下，可能教练也觉得没关系，要让他学会在场上带着犯规打球。果然，周琦仍打得很有侵略性，外线做假动作后直杀篮下，成功制造犯规，罚球建功。片刻之后，他又上罚球线，分差进一步扩大。更精彩的是，此后他还继续暴扣，直接把对手打停。细算一下，周琦此节轰了10分！凭借周琦的发挥，最终毒蛇队锁定了这场胜利。 +http://sports.163.com/17/1122/14/D3RRBHMJ0005877U.html +这才是榜眼?库兹马第7次20+ 超西蒙斯成新秀第1人 +网易体育11月22日报道：在今天与公牛的比赛中，库兹马再次获得了首发出场的机会，他首节便火力全开，两次外线三分飙中，并有直杀禁区的暴扣，仅用了6分钟便4投全中拿下10分。而在第二节，库兹马右侧三分命中后，又有一记极其潇洒的中距离急停跳投，上半场虽然湖人大比分落后，但库兹马独得18分，帮助湖人咬住了比分。不过即便如此，库兹马依然在40分钟里15投7中，其中三分球7投4中，拿下了22分3篮板5助攻，22分是全场最高，5次助攻也是并列最高，甚至比鲍尔还多一次。这场的22分也让他拿下了赛季第7次20+得分，超越了此前并列6次的西蒙斯，成为了目前的本届新秀第一人。作为一名低位秀，湖人能够拿下这样一位场均16.8分的砍分怪物实在是意外之喜，而他的惊艳发挥，也足以在这支冉冉升起的紫金新军里，占据重要的位置。 +http://sports.163.com/17/1122/13/D3RM7Q3F0005877U.html +湖人捡到宝!库兹马破队史近24年新秀得分上双纪录 +网易体育11月22日报道：库兹马是今年第一轮27顺位，这样的表现，湖人算是捡到宝了。 +http://sports.163.com/17/1122/16/D3S2E5OO0005877V.html +CBA最神秘工种有争议才被提及 61岁教授竟干了22年 +再精彩的比赛也无法欣赏“我们技术统计有三个人组成，没特殊原因，人员不会更换，有人负责录入，有人口报。”张大伟说，他们虽然离球场非常近，但是从来无法真正做到欣赏比赛，“我们没有办法把精力真正投入观看比赛中，再精彩的比赛，我们没有感觉，我们只是看过程，谁投篮了，投篮没中的话，篮板谁抢到了，是二次进攻还是快攻，我们都需要做记录，你根本来不及欣赏比赛，所以，再精彩的比赛，我们是没有感觉的。”每场比赛下来，61岁的张大伟总是需要一段时间才能让大脑安静下来，“感觉消耗很大，可能和年龄有关系，我现在每次回来都感觉头轰轰的，很难静下来。”有争议才会被提及的工种当然，这样的个例不能掩埋记录员们的付出。为了杜绝辽疆争议的再度发生，CBA新赛季启用了PTS系统，即篮球无线计时系统或称精确计时系统。在记录台人工计时的同时，裁判员通过随身携带一个无线开表发射器，由裁判员依据规则在场上实现同步开表，两套系统互不排斥。球队越来越重视数据统计在大数据时代，CBA球队对数据的重视度越来越高。这一点，张大伟感触非常深，“以往的时候，真正重视数据的球队并不多，现在越来越多了，我印象中这种重视数据的现象是从2015-2016赛季开始的，特别是一些强队，比如新疆、广东、广厦、辽宁等等，他们每一节都会要数据统计。”众所周知，一个球员的数据往往与其收入挂钩。据张大伟观察，在联赛里，外援对技术统计表的需求很大，“他们经常会看数据统计，因为他们知道数据就是他们收入的保障，这也是有些外援进行刷数据的原因。”做这份工作只因热爱CBA济南赛区记录台工作由12人来完成，他们都来自济南，6人是国家级裁判，6人是国家一级裁判，他们大多数的本职工作是教师，个别供职于企事业单位。分别负责记录、宣告、计时、进攻计时、技术统计等工作。由于规则不断变化，记录员们需要不断学习，考试。只有通过每年的考试才能继续从事记录员的工作。据记者了解，记录员这份工作收入并不高，由于都是兼职，所以报酬都是按场计算，每个人每场球只有几百元的辛苦费。“说实话，我们真不是冲着钱去的，就是热爱篮球，热爱这份工作。”王宇是军人出身，在部队的时候就非常喜欢打篮球，后来因篮球之缘考了裁判，做起了记录员的工作。和王宇说的一样，老记录员张大伟也提到了“热爱”俩字。“说实话，老师们真的很辛苦，他们有很多在长清工作，经常需要上完课来赶场，因为我们要求六点半之前必须到场。”张大伟说，“大家很敬业，有可能会出现瑕疵，但从态度上绝对做到了百分百的精益求精，虽然我们都是业余的，但是是在用职业的精神来做这项工作。这些和名利没有关系，就是因为热爱。”正是凭着这种热爱，CBA济南赛区记录台已经连续三个赛季被评为优秀记录台。这支由老中青三代人搭配起来的团队，一直用他们的努力默默地为山东篮球增光添彩。 +http://sports.163.com/17/1122/22/D3SN14U400058782.html +柯洁丢钱包1万元悬赏 自嘲:棋输多了脑子也坏掉了 +网易体育11月22日报道：接着，他又在评论里说：“还有...包是我妈买给我的礼物...我蛮珍惜的...你喜欢可以留下...但可不可以把身份证还有驾驶证还给我”之后又补充道：“还有...我手机快没电了，飞机也要起飞了。明天还要去韩国，但身份证丢了好像不四森么好玩的四。” +http://sports.163.com/17/1122/14/D3RSMQA000058782.html +高度不超1米15!世界第一跪地发球调侃羽联新规 +世界羽联发球新规明年起施行上周，世界羽联在牙买加召开了理事会，会上讨论并通过了新的发球规定。目前这一新规具体细则还未颁布。据世界羽联秘书长伦德介绍，明年3月14日全英公开赛将成为首次实施新规的大赛。发球新规最大的变化，就是从原来的击球点不得过腰，变为击球点不能超过1米15。据了解，这一新规早在几个月以前就已经通知到各个国家协会，不过当时定的高度是1米10，中国羽毛球队在今年年初陵水冬训的时候就已经特别制作了一个1米10的杆放在网前，让队员适应新的要求。对于新规，国羽双打主教练张军表示：“这个规定绝对是颠覆性的，谁抢在前面，谁就占据优势。”新规则是否公平惹争议世界羽联之所以讨论通过发球新规，其初衷是为了公平。以前的规定是发球不能过腰，但实际上球员身高千差万别，既有安赛龙（1米94）、科尔丁（2米）这样的大个子，也有奥园希望（1米55）、山口茜（1米55）这样的矮个子，同样是腰部，相差却有40-50厘米。这让很多身材高大的选手占尽便宜，矮个子选手则很吃亏。一些身材矮小的选手比赛中从来不敢用反手发球，只能发后场高球。正是在这样的情况下，世界羽联才决定干脆统一发球高度。但是这一新规又引发了很多高个子选手的不满，早在今年4月，当世界羽联决定将发球高度定为1米10时，安赛龙就曾经在自己的社交账号上发布视频，用蹲地发球和跪地发球等搞笑的姿势调侃世界羽联，以表达对新规的不满。但在7个月之后，世界羽联还是决定施行发球新规，只不过将发球高度从1米10提高到了1米15。1米15的发球高度如何判定身高194cm的安赛龙在以前的羽毛球比赛中，每当裁判判罚球员发球违例时，往往会引发球员不满，毕竟过腰不过腰本身就有一点含糊，腰不是一个精确的高度，裁判判罚有时候会和球员的判断产生分歧。如今，世界羽联虽然将发球高度精确地确定为1米15，但毕竟不可能在球员发球时，在球员身边放置一个高度测量仪。这就产生一个问题，1米15的高度如何界定？昨天，记者联系上江苏羽毛球老帅张洪宝，他认为这个只能由发球裁判通过目测来判定，毕竟鹰眼目前可以判定界内界外，但却没法测定高度。不过也有网友认为，这个问题很容易通过仪器来解决，在场边设置一个红外线测量仪就行，当发球高度超过规定高度时，测量仪就会立即报警。据说，世界羽联已经研制出了高度检测器，但目前还未在任何大赛中亮相。 +http://sports.163.com/17/1122/13/D3RNQ6MA00058781.html +巴萨大将:看到布冯哭我也哭了 愿他替我打世界杯 +赢球“每一场比赛都很重要，但欧冠是我们尤其喜爱的。明天必须踢一场精彩的比赛。表现出自己的水平，争取一个不错的结果。”缺少引援？“就现在来看，我们还不算不上差。所以我还会继续这样，我百分百的相信我的队友，一月份会发生什么我们到时再看。我们所有人都会打起精神，保持在自己的最高水准。”尤文“我们尊重尤文，他们在意甲中遭遇失利，但不会而改变他们的本质。这可是欧冠，我们在和最好的球队比拼。”教训“我说过球队必须从失利中学习。每一场比赛都是一次全新的挑战。显然去年我们的那场败局不是偶然。现在必须展示出球队正在沿着一条很积极的道路上前进。”梅西续约一事“我只能说我自己的观点。在我看来，一直都没变。其实我们没聊过这方面的问题。大家都坚信同一点。希望梅西也是。大家都知道梅西在更衣室的作用，高层和球迷们都很爱他。每个人都会有自己的观点，但梅西知道他自己是巴萨的一部分。”厄齐尔“所有来巴萨的人我们都欢迎，球队签的自然都是极好的，我百分之百地相信我的队友们。不论谁来了，都将会受到欢迎，因为我们将为同一个目标而奋斗。我会做好我自己。尽量帮助球队。我们不是一个人在战斗。”没有梅西的巴萨“他的规划都是关于巴萨的。我不能百分百确定他会留下，因为这是他个人的决定。需要去尊重人家。球迷们想要看到最终签署续约合同的合影，我也是这么想的。我相信莱奥。我知道他想和我们在一起，续约总会来的。”布冯 +http://sports.163.com/17/1122/11/D3RGTJFR00058781.html +皇马球迷别看!武僧还俗小组头名出线 卡西也快了 +网易体育11月22日报道：贝西克塔斯的提前出线，最大的依仗就是佩佩领衔的后防线。5轮小组赛中，贝西克塔斯一共只丢掉了4个球，这使得该队以3胜2平的不败成绩出线。 +http://sports.163.com/17/1122/22/D3SLPK2L00058781.html +搁置续约!蓝军门神想去皇马? 英媒:闹加薪的伎俩 +网易体育11月22日报道：今年5月份，切尔西曾向库尔图瓦提供了一份新合同，但双方当时并没有谈妥。此后的半年时间，库尔图瓦一直都拒绝和球队谈续约。“在续约一事上，切尔西必须和我的经纪人来谈。据我所知，谈判并没有任何进展。”库尔图瓦说道。2014年夏天，库尔图瓦从马竞回到切尔西。截止目前，他一共为切尔西出场125次，帮助球队获得两次英超冠军以及一次联赛杯冠军。对于库尔图瓦搁置续约的决定，英媒体的看法并不一致，有人认为他确实是想去皇马，也有人认为库尔图瓦实际上是想借皇马来逼切尔西给他加薪。 +http://sports.163.com/17/1122/22/D3SO8MUO00058782.html +反转!格斗孤儿可回俱乐部练格斗 毕业可获学历 +武警出身的恩波（穿大衣者）与学员在一起（图自中研网）观察者网22日下午就此致电恩波格斗俱乐部，一位不愿透露姓名的工作人员介绍称，恩波目前通过与阿坝州体校的合作，解决了俱乐部孩子异地教学的学籍问题，俱乐部作为一个九年义务教育机制之外的机构，平时供孩子吃住训练，孩子们走读前往体校读书，接受正规九年制义务教育。观察者网又致电阿坝州体育局法宣科询问相关情况，对方表示不回应此事。“格斗迷”也采访到恩波俱乐部创始人恩波先生，对方表示，这是一个趋于完美的结局，孩子们保留了选择权，格斗运动也得到正名。文章还称，相信这群孩子们未来会用成绩与更好的生活，来回报恩波，阿坝州政府与亿万曾为他们努力过的网友们。事件回顾：今年7月，一段讲述恩波俱乐部“格斗孤儿”的视频引发网友热议。视频中介绍了两名失去了双亲，无依无靠的小男孩小龙和小吾的故事。两人都是14岁，是成都一家MMA俱乐部的队员。该俱乐部先后收养了400多名像他们一样失去双亲无所依靠的孩子，他们的梦想都是拿到UFC金腰带。有的网友认为，对于失去双亲的孩子，能够在生存之外学到一技之长是一件好事。也有网友担心，孩子投身格斗而非学习文化知识，将来可能仍会遇到生存的危机。恩波“格斗孤儿”持续成为舆论热点后，大量媒体跟进报道，逐渐拼凑出时间全貌，恩波曾是一名武警，在格斗训练方面较有心得，2001年，恩波退伍后通过从事建筑工程积攒了一些资金，组建了一支武术散打队，开始招收孤儿进行培训。但恩波俱乐部并不具有教育资质，孩子在这里无法接受正规文化教育。同时，俱乐部让孩子打一些商业表演赛也成为一个争议点。许多孩子则表示，在恩波俱乐部不用花钱，伙食也比老家好得多，虽然训练辛苦，但不愿意离开。虽然训练很辛苦，但一些孩子不愿回去随着大量媒体报道、网络热议，事情持续发酵，首先是四川成都警方介入，调查俱乐部对孤儿们收养的合法性，和是否有未成年人参与商业比赛；之后，凉山的教育部门，要求孤儿们回到老家，接受法定的义务教育。同时官方表示，孩子们如果在接受义务教育之余到这里训练，不会干预。最终，虽然有一些孩子明确表示不愿意离开，但还是在8月中旬被要求必须回归凉山老家，事件告一段落。今年8月，一名恩波俱乐部的孩子被强制离开如今，恩波俱乐部恢复招生，尚不清楚有没有原先的孩子回去训练。 +http://sports.163.com/17/1122/22/D3SLKN3H00058782.html +国乒也追星:马龙牵手蔡依林 张继科为1人打call +7月24日，陈梦发微博称“谢谢~超人@任嘉伦Allen炎炎夏日收到这份礼物再好不过啦 期待你的新作品哦，看了大唐荣耀里的广平王、现在的秋蝉，话说儿时怎么不知道你有如此演技呀。”没错，梦梦的“跨界”明星朋友就是任嘉伦，中国内地男演员、歌手。小时候，因为打球，梦梦与任嘉伦相识。但由于伤病原因，16岁的时候，任嘉伦离开了乒乓球台。2009年，他开始参加选秀比赛，一直到后来去韩国学习，任嘉伦也始终保持着对运动的热爱。有这样一位跨界大咖朋友，是不是做梦也会笑出声呢！2015年年底，刘诗雯与队里其他几位主力，一起参加了由邓超和俞白眉联合执导的电影《恶棍天使》的首映，当时，她还发微博称参加首映很开心，并称赞邓超和孙俪夫妇人很好。从这之后，友谊的小种子就慢慢发芽了。去年年底，刘诗雯再次发博文力挺邓超主演的新电影《乘风破浪》，“超哥主演，必须支持，到时候我们组团去吧@丁宁。”刘诗雯表示很喜欢邓超夫妇，会在行动上去支持他们的工作，比如关注他们主演的电影、电视剧等，但是，平时他们交流很少，刘诗雯说：“我本身就不是一个追星的人，而且我们不在一个行业，能交流的话题也不太多，所以我能做的就是默默支持他们，并带动身边的朋友一起喜欢他们。”去年的里约奥运会结束后，张继科曾在直播平台中打趣，退役后要做樊振东的经纪人，东京奥运会的时候，要去现场坐在观众席给小胖加油，见证他拿大满贯。张继科口中的“世界第一可爱”樊振东谦虚地表示，“前辈”定的目标，他会争取去实现，但要说经纪人的话，他对这个“职业”也比较感兴趣，“我可以当身边‘跨界大咖’的经纪人，我带的‘艺人’涉猎很广，音乐、相声、小品、美食界的都有。”至于樊经纪手下这些“跨界大咖”都是何许人也，他笑言全部是自己的队友，朱霖峰、程靖淇，两人体内有艺术细胞，唱歌、捧哏都不在话下。美食界的大咖非国乒队中的“大胖”——梁靖崑莫属。身边这些能带来欢乐的“跨界”朋友，给樊振东每天枯燥的训练生活带来了些许安慰。陈幸同的演艺圈朋友是王博文。王博文从六岁开始接受乒乓球训练，曾代表辽宁队参加全国少年组乒乓球比赛，并多次获得好成绩。但之后，他渐渐走上了演艺道路，让曾经一起打球的队友又惊又喜。陈幸同说，因为两人年龄相仿，以前在辽宁队的时候，他们曾经一起训练过，但平时交流不是很多，当时也没有想过他能进演艺圈。为了支持曾经的同门师兄，陈幸同会帮助王博文打榜新歌，并呼吁身边人一起转发关注。虽然现在大家在不同的领域，但都需要奋斗拼搏的精神，像运动员勇创佳绩一样，这种精神从小就根植于心的王博文在演艺道路上也定会越走越顺。 +http://sports.163.com/17/1122/21/D3SIDNS300058782.html +前拳联主席吴经国再辞IOC执委 体系重建任重道远 +网易体育11月22日报道：随即，吴经国通过国际拳联官网和国际拳联执委会发表辞职声明，这一辞职是在国际拳联宣布和吴经国达成友好协议来解决组织内部管理问题的声明后做出的。友好协议也提出双方都收回及终止所有在瑞士法院及国际拳联纪律委员会相关的悬而未决的程序。双方都同意目前对方并没有不道德的行为。 +http://sports.163.com/17/1122/18/D3S8VBN900058782.html +火箭发飙撵走摄像师 震惊对手轰137:以为最多30分 +网易体育11月22日报道：不得不提的是，这已经不是奥沙利文第一次跟摄像师发生矛盾，在2017年大师赛上，他更是怒骂一位摄像师在自己击球时猛拍，毫不顾忌自己的感受，并在获胜后接受采访时依然将矛头指向了这位摄像记者，“你真是我的噩梦。”奥沙利文因此爆了粗口受到台联的处罚，而这更让奥沙利文气不打一处来，认为台联专门针对自己，并表示自己今后将惜字如金。奥沙利文也是这么做的，他在一次采访时全程都用一个单词打发记者，奉献了历史上最装采访，不知道这次撵走摄像记者，是否还会有炮轰行为。当然，奥沙利文的精力并没有全放在场外，最终还是击败了21岁的德国小将克莱克斯，而对于对手在比分落后时打出单杆137分，“火老师”也在赛后毫不吝啬溢美之词，“这是我第一次与这位选手打，以前都未见过他，觉得他就是单杆超过30分的水准，没想到他竟然完成单杆137分，看来，我真得重视这位对手。”无论是重视对手还是与摄像师“PK”，都说明奥沙利文最近的比赛态度真是敬业，从冠中冠到上海大师赛夺冠再到北爱尔兰首轮获胜，奥沙利文是从英国辗转到上海再回到英国，尽管是不折不扣的“空中飞人”，状态和手感却丝毫不打折扣。而对于冠中冠和上海大师赛背靠背作战，奥沙利文说道：“这样的赛程是我之前就做出的决定，我享受其中，能夺冠很棒，其实即使落败也没什么。而我也计划在中国拿到一个冠军，因为斯诺克运动在中国太受欢迎了，因此上海赛夺冠的重要性不言而喻，这是送给中国粉丝的。” +http://sports.163.com/17/1122/20/D3SGS1TV00058781.html +好消息!曝皇马三大将下周或复出 水爷或戴面具出战 +网易体育11月22日报道: +http://sports.163.com/17/1122/19/D3SB8O9L00058781.html +英甲前锋梅开二度早早离场 赶去医院迎接儿子出生 +维冈的助理教练Leam Richardson解释道：“半场休息时，我们收到信息，他的妻子的羊水破了，他们的第2个孩子即将出生。”“当他打进第2个球时，我们马上就把他换下了，因为他的心思在别处了。我们都是男人，都是独立的个体，有些球员可能不会离开，他们可能现在还在更衣室。”“但是有些人有直接离开球场，去支持自己的伴侣，你必须尊重每个人的做法。”本赛季早些时候，斯温登队的Olly Lancashire也在半场离开球场，因为他的妻子已经临盆了。 +http://sports.163.com/17/1122/17/D3S6T2CN00058781.html +揭开新篇章!小白布冯坦然谈退役:离开足球不可怕 +伊涅斯塔说道：“只要我的身体还能坚持，我会一直踢下去。我并不害怕退役，因为生活中的一切都有极限和终点。”明天凌晨，两位老将将在安联球场展开正面对决。 +http://sports.163.com/17/1122/06/D3R0JSRS0005877U.html +魔术师后,前3顺位PG没水过 现在轮到薛定谔的球… + +http://sports.163.com/17/1122/11/D3RG0LDH0005877U.html +18分+4帽!周琦助毒蛇大胜 5犯后单节轰10分收官 +网易体育11月22日报道：本场比赛双方打得很激烈，首节比分就是你来我往，互相纠缠，周琦状态很不错，进攻、防守都有闪光点，开场后，队友进攻不中，就是周琦狂抢篮板，得到二次进攻机会打进，防守端他也是秀存在感，抢断、盖帽不时闪光，之后，周琦还和奥努阿库来个双塔连线，空中接力得分！首节双方打成36-35，毒蛇领先1分。次节周琦依然在防守端发威，比如喧嚣队打出一波快攻反击，周琦从空中直接把对方的突破上篮扇飞，这帽太狠，现场解说也是高呼：“我的老天！”当然，周琦也暴露出一些经验不足的问题，上半场最后阶段，他在防守端犯了错误，一方面是补防慢了，另一方面是扑得太凶，结果被对手生造了一个2+1，这样的失分很打击士气，看得出来周琦也是有一些沮丧。进入下半场，周琦在进攻中吃了一个犯规，但他的情绪没有被影响。不久后，周琦卷土重来，这次他在左侧接球，面对防守人一路的跟随，他强起上篮，打进还制造加罚，周琦也和队友们击掌庆祝。比赛开始倾向毒蛇这边，他们打出更好的防守，迫使抢夺队在3分钟的时间内仅得到2分，而毒蛇自己得了14分，场上分差也就此拉开，之后毒蛇一直保持领先优势。末节，虽然周琦5犯规了，但教练还是把他放在场上，解说员们也是讨论一番，都认为即便周琦被罚下，可能教练也觉得没关系，要让他学会在场上带着犯规打球。果然，周琦仍打得很有侵略性，外线做假动作后直杀篮下，成功制造犯规，罚球建功。片刻之后，他又上罚球线，分差进一步扩大。更精彩的是，此后他还继续暴扣，直接把对手打停。细算一下，周琦此节轰了10分！凭借周琦的发挥，最终毒蛇队锁定了这场胜利。 +http://sports.163.com/17/1122/16/D3S2E5OO0005877V.html +CBA最神秘工种有争议才被提及 61岁教授竟干了22年 +再精彩的比赛也无法欣赏“我们技术统计有三个人组成，没特殊原因，人员不会更换，有人负责录入，有人口报。”张大伟说，他们虽然离球场非常近，但是从来无法真正做到欣赏比赛，“我们没有办法把精力真正投入观看比赛中，再精彩的比赛，我们没有感觉，我们只是看过程，谁投篮了，投篮没中的话，篮板谁抢到了，是二次进攻还是快攻，我们都需要做记录，你根本来不及欣赏比赛，所以，再精彩的比赛，我们是没有感觉的。”每场比赛下来，61岁的张大伟总是需要一段时间才能让大脑安静下来，“感觉消耗很大，可能和年龄有关系，我现在每次回来都感觉头轰轰的，很难静下来。”有争议才会被提及的工种当然，这样的个例不能掩埋记录员们的付出。为了杜绝辽疆争议的再度发生，CBA新赛季启用了PTS系统，即篮球无线计时系统或称精确计时系统。在记录台人工计时的同时，裁判员通过随身携带一个无线开表发射器，由裁判员依据规则在场上实现同步开表，两套系统互不排斥。球队越来越重视数据统计在大数据时代，CBA球队对数据的重视度越来越高。这一点，张大伟感触非常深，“以往的时候，真正重视数据的球队并不多，现在越来越多了，我印象中这种重视数据的现象是从2015-2016赛季开始的，特别是一些强队，比如新疆、广东、广厦、辽宁等等，他们每一节都会要数据统计。”众所周知，一个球员的数据往往与其收入挂钩。据张大伟观察，在联赛里，外援对技术统计表的需求很大，“他们经常会看数据统计，因为他们知道数据就是他们收入的保障，这也是有些外援进行刷数据的原因。”做这份工作只因热爱CBA济南赛区记录台工作由12人来完成，他们都来自济南，6人是国家级裁判，6人是国家一级裁判，他们大多数的本职工作是教师，个别供职于企事业单位。分别负责记录、宣告、计时、进攻计时、技术统计等工作。由于规则不断变化，记录员们需要不断学习，考试。只有通过每年的考试才能继续从事记录员的工作。据记者了解，记录员这份工作收入并不高，由于都是兼职，所以报酬都是按场计算，每个人每场球只有几百元的辛苦费。“说实话，我们真不是冲着钱去的，就是热爱篮球，热爱这份工作。”王宇是军人出身，在部队的时候就非常喜欢打篮球，后来因篮球之缘考了裁判，做起了记录员的工作。和王宇说的一样，老记录员张大伟也提到了“热爱”俩字。“说实话，老师们真的很辛苦，他们有很多在长清工作，经常需要上完课来赶场，因为我们要求六点半之前必须到场。”张大伟说，“大家很敬业，有可能会出现瑕疵，但从态度上绝对做到了百分百的精益求精，虽然我们都是业余的，但是是在用职业的精神来做这项工作。这些和名利没有关系，就是因为热爱。”正是凭着这种热爱，CBA济南赛区记录台已经连续三个赛季被评为优秀记录台。这支由老中青三代人搭配起来的团队，一直用他们的努力默默地为山东篮球增光添彩。 +http://sports.163.com/17/1122/14/D3RQSG550005877V.html +曝青岛不满琼斯单打独斗 将签深圳大外援兰佩 +目前距离间歇期后第一场比赛大约还有一周的时间，青岛队最快有望在三日内完成大外援的更换，重新步入正轨。 +http://sports.163.com/17/1122/10/D3REFH440005877V.html +西热力江:我是野生男人 不使小动作球队难赢球 +网易体育11月22日报道：西热力江的全名是西热力江-木合塔尔，维语的意思是“自由的雄狮”，西热力江也表示，自己就是个“野生男人”，“小学刚上完就离开家了，到乌鲁木齐上学、打球，包括来广汇，算是野惯了吧。我名字的意思就是野生动物，正儿八经的，但是我是个野生男人，所以干什么都比较暴躁一点。”西热力江说，不过他也认为，由于已经结了婚，也拿了CBA冠军，所以没以前那么野了。西热力江并不避讳自己的小动作，“不说是针对某个人，我也不会说故意把你搞伤，我只是想尽办法尽力防守，或是用一些小动作，如果不惹毛你的话，我们很可能赢不了，因为对方的领袖和队魂一场球拿四五十分是非常简单的事情，所以我的有些动作不太合理，但是确实没办法，因为他们的能力实在是太强了。”他解释道，“外援天生身体素质就很强，他们做一个动作我们有时候会反应两下，所以如果我在场上不拼的话，连他们的节奏都跟不上。我们费了吃奶的劲去跟对方拼，也是对他们的一种尊重。” +http://sports.163.com/17/1122/19/D3SBVN7D0005877V.html +前瞻:世预赛中国首战香港 丁彦雨航领衔红队出击 +网易体育11月22日报道：观战指南：对阵双方：中国男篮VS中国香港队比赛时间：11月23日19时30分比赛场馆：南京青奥体育公园体育馆电视转播：CCTV5男篮近况：中国队首战迎击的对手中国香港队，日前也公布了他们的12人名单，由现效力于CBA浙江队的探花秀惠龙儿领衔球队阵容，而曾在CBA长期效力的后卫罗意庭未能入选。对手的具体12名球员是：郑锦兴、梁民熊、蔡再勤、梁兆华、刘凯涛、方诚义、黄镇炜、惠龙儿、林凯光、林羽、司徒伟杰、陈耀祖。核心看点：丁彦雨航需证明自己的国际赛统治力最近两个赛季的CBA联赛，丁彦雨航的名字高幅度刷屏，因为他在进攻端强悍的表现而被称为“四字外援”。小丁在联赛中强大的火力输出不亚于多数外援，这一点已经无需质疑；但如果想要与胡卫东、李楠、朱芳雨等前辈比肩，还需要在国际大赛中证明自己。小丁目前仍缺少国家队的代表作，本次赛事他毫无疑问是全队的进攻核心，体现自己在国家队价值的机会终于来到了，他的表现令人期待。男篮将有哪些新星闪光？李楠率领的男篮红队，此前先后出战了对阵伊朗的3场系列赛、7月举行的斯坦科维奇杯以及男篮四国赛成都站的赛事，比赛过程中先后有阿不都沙拉木、赵睿、王子瑞等国家队新人涌现。经过国家队赛事锻炼收获了自信，以上球员在之后的全运会以及联赛期间均有不错的表现。此次男篮世预赛李楠再次带队出征，还会有新的球员令球迷们眼前一亮吗？预计男篮首发：丁彦雨航、俞长栋、王哲林、刘志轩、王子瑞 +http://sports.163.com/17/1122/19/D3SAIB0K0005877V.html +山东男篮正式集结备战广东 主帅外援明日陆续归队 +间歇期后首场比赛，山东男篮主场迎战易建联领衔的广东宏远，这场比赛无疑是一场硬仗。闪电体育 徐凯华 孙东昊 实习记者 岳超 +http://sports.163.com/17/1122/22/D3SMBF9400058781.html +欧足联最佳阵容50人大名单:梅罗领衔 皇马11人入围 +网易体育11月22日报道： +http://sports.163.com/17/1122/07/D3R4ACPF00058781.html +欧冠16强6席出炉!英超2强头名晋级 卫冕冠军成雷 +网易体育11月22日报道：新加入16强之列的两队分别是卫冕冠军皇马和土超劲旅贝西克塔斯，皇马本赛季联赛状态低迷，所幸欧冠赛场仍保持着不错的状态，6-0狂胜希腊人竞技之后，皇马积分来到10分，但由于在与热刺的相互战绩中（1平1负）占据下方，皇马只能屈居小组第二，这也意味着在欧冠1/8决赛的抽签中，皇马将成为各个小组第一最不愿碰到的对手。贝西克塔斯本轮1-1主场战平波尔图，5轮比赛过后拿到11分，领先小组第二波尔图4分，提前以小组第一身份出线。 +http://sports.163.com/17/1122/09/D3R8BIO200058781.html +主帅中场告知患癌症，弟子连扳3球，震惊+感动！ +网易体育11月22日报道：贝里佐患上的，是甲状腺癌。在中场休息时，贝里佐将自己的病情通知了球员们，下半场很可能是他执教塞维利亚的最后半场比赛。在得知此事之后，塞维利亚球员们迸发出了超强斗志，并最终在下半场奇迹般的追平了比分。在比赛结束后，塞维利亚方面不愿多谈贝里佐病情。主席卡斯特罗表示“我们更希望在周三在回应这个复杂的私人话题”，中场大将巴内加则这样说道：“我们告诉自己，我们只要敢做，就能做到。我们要永远为了球迷和教练而战。”《阿斯报》指出，塞维利亚官方将在本周三正式宣布贝里佐的病情，并将同时宣布他的治疗方案。如果贝里佐需要接受手术或放疗化疗的话，他不但有可能缺席一段时间比赛，甚至有可能将告别塞维利亚。 +http://sports.163.com/17/1122/05/D3QSJ9CN00058781.html +欧冠-本泽马C罗梅开二度魔笛世界波 皇马6-0出线 +网易体育11月22日报道：@@LinkCard="http://sports.cctv.com/H5/wydwhz10/v/index.shtml?id=VIDEmgPpTnCWLhN0wPErGUyr171122&s=123163" Title="视频集锦" ImgSrc="" Digest=""@@ +http://sports.163.com/17/1122/05/D3QT1R8500058781.html +欧冠-菲尔米诺梅开二度 利物浦3-0到3-3仍未出线 +网易体育11月22日报道：@@LinkCard="http://sports.cctv.com/H5/wydwhz10/v/index.shtml?id=VIDEMneqldBNXR6QSSswO4Im171122&s=123163" Title="视频集锦" ImgSrc="" Digest=""@@ +http://sports.163.com/17/1122/05/D3QSS8S000058781.html +欧冠-凯恩扳平孙兴慜绝杀 热刺2-1多特头名出线 +网易体育11月22日报道：@@LinkCard="http://sports.cctv.com/H5/wydwhz10/v/index.shtml?id=VIDEVF3pFPMDJ1PGbIqXsweq171122&s=123163" Title="视频集锦" ImgSrc="" Digest=""@@第76分钟，阿里在左侧带球突破巴尔特拉和格策的防守，随后传球，孙兴慜在禁区内射门得分，热刺2-1反超！扎加杜还在这次防守时和阿里相撞后受伤，随即被换下。第81分钟，孙兴慜把球分到左侧，罗斯传中，埃里克森头球顶偏。第83分钟，卡斯特罗左路传中被戴尔挡出边线。第83分钟，多特蒙德左路传中，禁区内奥巴梅扬争顶时摔倒。第83分钟，奥巴梅扬右路下底传中，戴尔把球踢出底线。第85分钟，多特蒙德右路传中，奥利耶冒顶，格雷罗射门打偏。第88分钟，奥巴梅扬和队友配合后在禁区内射门，戴尔用腿把球挡出。第89分钟，热刺反击，略伦特单刀面对布尔基，最后一下把球趟大了，布尔基倒地把球扑住，布尔基还在这次扑救时受伤接受治疗，随后他被担架抬出场，老门将魏登费勒替补出场。补时第6分钟，托利安犯规吃到黄牌。全场比赛结束，多特蒙德主场1-2不敌热刺。 +http://sports.163.com/17/1122/12/D3RJGPCN00058780.html +30:0!河南高中联赛比分太离奇 媒评:新"甲B五鼠"? +据报道，吸引外界眼球的并非该项赛事有未来之星或名门之后亮相，而是令人咋舌的30：0的比分。油田一高最终凭借净胜球的优势逆袭夺冠，这不得不让人想起2001年出现的“甲B五鼠”。油田一高末轮狂进球 凭净胜球反超领头羊河南省濮阳市第三届青少年校园足球联赛高中男足比赛共有9支球队参赛，以单循环积分的赛制决出最终名次。在末轮比赛之前，实力高人一等的油田一高与油田二高战绩均为6胜1平，两队间的交锋以0：0互交白卷。油田二高得失球比为41：0，净胜球高达+41；油田一高得失球比为32：1，净胜球为+31，油田二高以10个净胜球的优势力压油田一高领跑。油田一高与油田二高将在末轮中争夺冠军，净胜球成为重要因素。在收官战中，油田二高以8：0的比分战胜市二高，最终战绩为7胜1平积22分，净胜球为+49。在另外一场比赛中，油田一高以30：0的比分战胜油田三高，最终战绩为7胜1平积22分，净胜球为+61。油田一高净胜球反超油田二高12个，最终获得了冠军。难道一高与三高之间的真实差距是30个球？在收官战前，油田三高战绩为5胜2负，与市一高同分，依靠净胜球优势排名第3。在此之前，有望争冠的油田二高与油田三高之间的比分仅为1：0，二高技高一筹。在二高与一高实力相差无几的情况下（此前油田二高与油田一高交手时两队0：0战平，与油田三高交手时，油田二高只是以1：0的比分小胜），三高末轮输给一高0：30，“给”足了对手净胜球，确实令人值得怀疑。赛后，二高某知情人在社交平台上宣称其中有“黑幕”，认为是一高和三高联手导演了一场30：0的悬殊比分，做掉了二高到手的冠军。“真是机关算尽，不知道给了油田三高什么好处……”30：0刷净胜球 让人想起当年的“甲B五鼠”事件由“四川德比”成都五牛国腾与绵阳太极发起。倒数第2轮即第21轮比赛，成都五牛国腾与绵阳太极打出了令人惊愕的11：2的比分，“创造”了中国次级联赛比分和进球数的“纪录”。引起全国媒体和球迷同声叫假，称之为中国足坛假球之最。末轮比赛，舜天对五牛、绿城对亚泰。在中远已经冲A的情况下，亚泰、五牛、舜天都有希望拿到第2个冲A名额。末轮比赛，若亚泰不胜绿城，那么舜天只要赢五牛就能冲A；绿城若赢球，舜天则无望冲A。五牛、亚泰若同时赢球，那么两队将比较净胜球的多少。收官战，五牛客场4：2胜舜天，拿到2粒净胜球，净胜球达到+23；亚泰客场6：0大胜绿城，净胜球达到+24，反超五牛1粒净胜球获得甲B亚军晋级甲A。对于甲B最后两轮不正常现象，中国足协决定：除上海中远外其他队一律取消本年度升入甲A联赛的资格，取消绵阳太极参加2002年甲B联赛的资格，降为乙级。■网友 足球踢出篮球的比分网友“东院故事”：必须取缔这个冠军，并处罚假球两队三年内不得参加任何比赛，追究责任。网友“better”：绝对假球……踢个小学生队，说不定能踢这比分。网友“暗之飞龙”：就是假球。网友“峰哥爱恋”：篮球打得不错！网友“在水一方”：呵呵，从小就学会踢假球了。网友“太空999”：我以为是篮球，假球无疑，30球，3分钟进一球。 +http://sports.163.com/17/1122/18/D3S8PTQ200058780.html +热身-新帅首秀遭惨败 中国女足全场仅1射0-3澳洲 +网易体育11月22日报道：比赛概况日前中国女足做出重大调整，球队一分为二，分别组建了红队和黄队，其中红队作为主力队伍，将代表国家参加各类国际赛事。原中国女足主帅布鲁诺下课，冰岛籍教练埃约尔松成为红队新帅。按照计划，中国女足红队将在11月底前往澳大利亚进行2场热身赛。根据FIFA官方统计，中国女足与澳大利亚女足国际A级赛交锋38次，中国女足19胜10平9负。【精彩瞬间】比赛开始后，中国女足被澳大利亚压制，场面十分被动，但主队也没有获得很好的射门机会。第23分钟，久攻不下的澳大利亚利用一次定位球机会打破僵局。埃格蒙德左路角球传中，中国女足盯人不紧，克尔后排前插甩开李丹阳的防守，马君门前也没未能阻挡住克尔的前插，后者后点利用身体优势高高跃起头球破门，中国女足0-1落后！此后，布特和福尔德先后在禁区内完成一脚抽射和头球攻门，但都没有打在球门范围之内。上半场45分钟，中国女足射门数是尴尬的0！第49分钟，中国女足险些再次丢分。福尔德中路送出身后球，中国女足防线再次出现漏洞，克尔杀入禁区形成单刀赴会之势，在禁区左侧面对赵丽娜一脚抽射偏出球门。第53分钟，中国女足再丢一球。福尔德禁区左侧倒三角回敲，中国女足禁区前沿保护不力，布特弧顶左侧稍做调整后起脚射门，球打在防守队员身上后变线，赵丽娜措手不及，球直接吊入球门，中国女足0-2落后！第59分钟，澳大利亚在布特进球相似的位置获得任意球机会，肯尼迪主罚，球绕过人墙飞向球门左下角，赵丽娜做出精彩扑救，将球扑出底线。第64分钟，中国女足再次暴露出禁区前沿保护不力的弊端，丢掉第3球。洛佳索发出前场左侧界外球，中国女足禁区线前沿一片空旷地带，克尔极为轻松的调整，在弧顶前沿轰出一记世界波，球直飞球门右上角，赵丽娜无可奈何，中国女足0-3落后！第67分钟，任桂辛前场左路突施冷箭，可惜球没有打在球门范围，这是中国女足唯一一次射门！补时第2分钟，薛嬌左路送出高质量传中，李影门前高高跃起，力压防守队员头球攻门，球在飞入球门的一瞬间被替补门将坎贝尔单掌托出横梁。这是中国女足全场最有威胁的一次射门。1分钟后，韩鹏力压战术角球，在前场右路打出一脚远射，可惜没有打上力量。此役，中国女足全场仅有3次射门，而且都是在下半场完成。【双方阵容】中国女足出场名单(4231)：1-赵丽娜；2-刘杉杉(76’13-薛嬌)、5-吴海燕、32-马君、33-李丹阳；23-任桂辛(82’12-李影)、20-张睿；21-许燕露(76’17-韩鹏)、7-王霜、9-唐佳丽(61’36-宋端)；11-王珊珊；未上场替补：4-高晨、6-李冬娜、8-娄佳惠、10-姚凌薇、16-杨莉娜、18-毕晓琳、22-李雪彦、28-陆菲菲澳大利亚出场名单(4141)：18-阿诺德(82’12-坎贝尔)；14-肯尼迪(46’6-洛佳索)、7-凯特利、4-波尔金霍恩、16-拉索；10-埃格蒙德；9-福尔德、19-戈里、13-布特(67’17-西蒙)、11-德范娜(86’22-克拉默)；20-克尔(86’23-海曼)；未上场替补：1-威廉斯、2-哈里森、5-阿勒维、8-奈特、21-卡彭特 +http://sports.163.com/17/1122/17/D3S5BVQ800058780.html +德国球迷扬言继续挂"言论自由"横幅和"藏独"旗 +【环球时报驻德国特约记者 青木】本周六，中国足协U20选拔队(国家青年队)将在法兰克福球场参加德国西南地区联赛的第二场友谊赛。18日，在国青队的首场比赛中，观众席上有人打出“藏独”的标志“雪山狮子旗”，中方队员随即以退出赛场抗议。据德国黑森州电视台21日报道，主队FSV法兰克福的一些球迷扬言将在周六的比赛中悬挂“言论自由”的横幅和“藏独”旗。对此，在法兰克福的华人告诉《环球时报》记者，他们正在组织华人球迷，到球场举起国旗为中国队助威。黑森州电视台报道称，据FSV法兰克福总裁格尔纳透露，该俱乐部的粉丝已经申请了标语横幅，以表明德国的言论自由。他们还想挂一面“藏独”旗。“只要表达在法律的框架内，俱乐部就不会干预。”格尔纳称。在接受《斯图加特新闻报》采访时，这名总裁扬言“不会对我们民主的基本权利让步一厘米”。德国《图片报》则援引在首场比赛中打出“雪山狮子旗”的“藏独”组织发言人的话说，不排除在以后的比赛中继续挂旗。德国足协、足球俱乐部相关人士和德媒的不负责言行，令在德华侨华人非常气愤。《环球时报》记者看到，在华人论坛上，大家都表示这与所谓的“言论自由”无关，完全是“藏独”闹场，有违德国足协和国际足联的规定。在法兰克福工作的华人球迷陈先生21日告诉记者，当地和德国其他地方的华人正准备周六到球场为中国队助威。如果德方不阻止“藏独”挂旗的行为，他们将拿出更大的中国国旗遮挡住“藏独”旗。20日在被问到国青队首场比赛中出现的情况时，中国外交部发言人陆慷说，中方坚决反对任何国家、任何组织、任何个人以任何形式和理由为“藏独”反华分裂活动提供支持。“相互尊重是东道主应有的待客之道。而且，尊重在任何国家之间都是相互的。”目前，德国官方尚未就此事表态。柏林中国问题学者波西尔21日对《环球时报》记者说，足球场是德国的形象窗口。许多德国足球俱乐部在中国开拓市场，赚了许多钱，德甲比赛也深受中国球迷欢迎。中国球员到德国是为了学习，现在一些俱乐部和德国足协的做法是自我抹黑。他认为，如果事件仍不断发酵，损失的将是德国足球的声誉和经济利益。当地时间20日晚，中国国青队迎来一场热身赛，最终以6∶1轻松击败德丙球队埃尔福特的U19队。 +http://sports.163.com/17/1122/12/D3RKVE3A00058780.html +高中联赛"30-0"罚单:仅处罚输方 网友又曝光1事… +网易体育11月22日报道：一名网友在评论中叙述称，甚至赛事的组委会还存在涂改比赛记录表的行为，“阳市30:0假球事件发生后，油田三高和油田一中默契球令人发指，但是以受害者身份出现的油田二高同样难逃了假球默契球事件，根据透露出来的赛程表可以看到最后一轮同时开球的两支队伍面对实力都很不错的对手都打出了不可思议的高比分，市二高在前几轮都没有大比分输球的情况下面对争冠的特殊时刻竟输了一个如此之大的比分，而净胜球又恰恰是油田二高所追求的，这其中难道就真的没有像他们口诛笔伐油田一中的情况发生在自己身上吗，我只能呵呵一笑了，还有赛事组委，在比赛结果记录表上多次涂抹，甚至还出现故意更改比分的情况，比如油田二高与市一高的比赛，竟然硬生生给油田二高多加了一个净胜球，这样的赛事组委会怎么能让人信服？管理不认真，犯低级失误，这样的校园足球令人心痛，两场假球默契球伤害的不仅仅是另外几支球队的心，伤害的是整个校园足球！心痛！心痛！心痛！我希可以彻底查清这件事，还我们校园足球一个干净的环境。”濮阳市校足办第三届“市长杯”青少年校园足球联赛情况通报如下：联赛最后一轮，在濮阳市油田一中与濮阳市油田三高在比赛中，在两队竟技实力水平相当的情况下，出现了惊人的大比分30:0。在比赛过程中，市油田三高的队员、不围抢，不主动触球，消极比赛，在社会上造成相当严重的影响。经当值裁判员报告，录像分析，经校足办纪委检查委员会研究，作出如下决定:1、取消濮阳市油田三高男子足球队比赛成绩，取消教练员郭耀东评选优秀教练员资格。2、禁止郭耀东三年内带队参加省、市级与足球相关的活动。3、责成濮阳市油田三高对队员进行批评教育。濮阳市校足办2017年11月20日 +http://sports.163.com/17/1122/09/D3R9HB8K00058780.html +历史性假球案引泰足坛地震 亚洲又一国深陷假球丑闻 +网易体育11月22日报道：据了解，本次假球丑闻共涉及本赛季4场与中下游保级球队相关的泰超联赛，缘起于诡异的比分存在巨大的假球嫌疑，而涉事人员共计12人，包括泰超联赛海军FC的素提蓬、那龙、素威他亚和沙讪，以及呵叻FC的主力门将。此外，嫌疑者还包括裁判汶马林和提拉集，1名线人和1名四色菊FC的教练组成员，余下四人则是俱乐部的投资人。先前，警方以上述所列人员操控比赛为由将其悉数逮捕，如今上述人员已获保释。同时，根据警方的调查，不排除球队与海外利益集团勾结的可能性。 +http://sports.163.com/17/1122/10/D3RDOM0I00058780.html +足协欧洲青训中心落户捷克 计划再推进至德国西班牙 +捷克是中国“一带一路”战略的重要合作伙伴。在足球领域内深化合作，是两国领导人共同确认的重要合作内容。欧洲青训中心建成后，中国足球青少年国家队将定期前往捷克训练，接受捷克高水平教练员的指导，并与捷克同年龄段优秀球队进行比赛。此举将进一步推动中捷两国足球界的交流，助力中国足球青训工作的发展，加深两国人民的友谊。根据中国足协全新的青训体系构架，中国足协还计划在德国、西班牙等欧洲足球强国建设青训中心，给更多优秀青少年球员更加广阔的成长舞台。期间，中国足协还与捷克足协在裁判合作领域内的深化合作达成一致意见。捷克将继续派出其高水平国际裁判来华执法中超赛事，并协助中国足协开展裁判员培训等工作。 +http://ent.163.com/17/1122/18/D3S8J6NE00038IPD.html +TVB董事方逸华83岁病逝 系邵逸夫遗孀 +方逸华原名李梦兰，邵逸夫的第二任妻子，她于1931年于上海出生，方逸华于1952年登台期间，认识丈夫邵逸夫，1969年入邵氏兄弟电影公司，1988年入无线电视董事局，方逸华在2012年向无线电视董事局辞任副主席兼董事总经理，过半限公司退休生活，今年并没出席无线台庆活动。李宝安回覆香港媒体查询时称"Already on TVB News." +http://ent.163.com/17/1122/19/D3SDKDP300038IPD.html + 63岁嫁九旬邵逸夫 邵氏无线掌门方逸华传奇一生 +她最后一次的公开亮相是在今年9月26日，与香港行政长官林郑月娥一起出席2017年邵逸夫奖颁奖礼。从星马登台歌手到邵氏兄弟电影公司的物资采购；电影制片到终登邵氏兄弟董事位置；初入无线到执掌无线电视台13年；从52年初识邵逸夫到97年终于注册成为夫妻，该如何定义这样一位传奇女性的身份，歌手？演员？制片？掌门？情人？伴侣？还是妻子？1950年，中学辍学的李梦兰远赴新加坡马来西亚开展歌唱事业。她有了个新名字，叫方逸华，偶尔也用自己的英文名字Mona在歌厅唱西洋歌曲。除了在南洋登台，方逸华也曾在美国、菲律宾等地献唱。录制的《花月佳期》颇为畅销。而方逸华认识邵逸夫，则是在1952年的新加坡。1957年，邵逸夫离开定居南洋的家人到香港创业。方逸华也退出舞台，来邵氏公司任职。1969年，她正式入职邵氏。在邵氏公司，她向邵逸夫极力推荐李翰祥担任导演，接连拍了《江山美人》《梁山伯与祝英台》等黄梅调电影，引得香港台湾街头万人空巷。《梁山伯与祝英台》的主演凌波到了台湾更是引发万人围观的狂潮。方逸华并非空降邵氏，而是从管采购、服装的基础部门做起，期间也客串过演员，《曼波女郎》《万花春色》里都能看到她的身影。70年代，方逸华才参与制片。邵逸夫喜欢方逸华的一点，是她深得自己勤俭立业的真传。曾经广为流传的段子，是方逸华招考秘书所出的题目：“这个电器换了，为什么一定要换新的，而不拿去修？”也因为太过勤俭，方逸华在制片部与当时的经理何冠昌以及秘书处的邹文怀大闹不和，引得两人出走邵氏，组成嘉禾对抗。当上制片部经理后，方逸华有了“方总管”的称号，也因为锱铢必较的作风被人称作“悭钱lady”。香港在1969年才推行一夫一妻制，伴随在邵逸夫身边的方逸华一直没能得到名分。但她凭借着自己的能力在邵氏公司的每个环节都经历过一翻，才进入高层，成为邵逸夫最重要的事业伙伴。1987年，为邵逸夫生下4位子女的原配黄美珍病逝。当时有新闻表示，六叔邵逸夫曾当着子女的面向方逸华征求意见该怎么办黄美珍的后事。这虽然让四位子女耿耿于怀，甚至后来无人愿意继承邵氏与TVB产业，但也了解了方逸华在邵逸夫心中的地位。即使邵逸夫与原配分隔两地，方逸华也从不以邵逸夫的身边人自居，碰到记者提问涉及邵逸夫时，也以“邵老师”来称呼。在成为邵太太前，她从未住进过邵氏的豪宅，而是住在自己购置的房子里面，只有周日才会前往邵府，两人共进午餐，聊天、散步，度过短暂的闲适时光，晚饭前又独自回到自己的住处。1988年，方逸华进入无线电视台（TVB）的董事局。到2000年，她参与到无线的日常业务中。但方逸华的行事风格也让TVB内部人员颇有微词。曾有人评价方逸华做事太主观，更有一位TVB新闻部的工作人员透露，如果方逸华看新闻主播不顺眼，就立马炒鱿鱼。虽然率先进入无线施展拳脚，方逸华也终于在1996年成为了邵氏兄弟的董事总经理。一年之后，63岁的她与90岁高龄的邵逸夫在美国拉斯维加斯注册成夫妻。对于这桩婚事，有人问邵逸夫这对方逸华来说是不是一件好事？邵逸夫说：“当然是好事啦！我同方小姐做了多年朋友，又一起工作了45年，结婚不单带来了正式的名分，也确定了方小姐日后的幸福。”2010年，邵逸夫以102岁的高龄正式退休。方逸华全面接管TVB大局。但这却让她面临从业多年来的最大威胁——收入锐减，垄断多年的香港电视界王国随时面临着瓦解，甚至TVB出品的剧集也面临着口碑的逐年下降。2013年，方逸华向TVB董事局递交副主席兼董事总经理的辞呈，并与3月25日离职。随着方逸华的全身而退，无线电视正式告别了邵逸夫时代。邵逸夫于2014年在家中离世，陪他走完人生最后一程的自然还是他永远的“方小姐”。据说在邵逸夫离世后，送走所有亲朋好友，方逸华在房间里哭了两个小时。2000年，香港亚视曾经以邵逸夫的一生为原型，拍摄了一部《影城大亨》。刘嘉玲所扮演的雷梦华所影射的就是方逸华。那部剧里也囊括了众多邵逸夫的“朋友仔”，比如当年的娃娃影后李菁。时隔17年，他们的故事再度被搬上电视。贾青和陈乔恩的身上都有着方逸华的影子。你看，如方逸华这样的人，即便她的敌人和朋友都已老去，也会将她留作传奇。 +http://ent.163.com/17/1122/18/D3S934HJ00038IPD.html +(独家)方逸华离世秦沛哽咽：很震惊很惋惜 +今天也是香港金牌经纪人陈自强设灵仪式。秦沛出席时受访，当媒体告诉他方逸华已离世消息时，秦沛表示不知情，更一度哽咽：“很震惊，很惋惜，会致电方逸华的妹妹慰问。” +http://ent.163.com/17/1122/21/D3SIM14K00038FO9.html +刘亦菲16岁试镜小龙女的视频曝光 青涩稚嫩 +当时16岁的刘亦菲在试镜小龙女之后接受采访，表达了对“金庸4次赞同她出演小龙女”的感激和荣幸，脸上胶原蛋白满满，充满了少女的灵气。 +http://ent.163.com/17/1122/14/D3RSJ7LD00038FO9.html +黄毅清指责黄奕出尔反尔 讽刺其爱炒作博眼球 +随后黄毅清便附上了对方律师发给他的致歉信内容，还带上了《为黄奕女士消除影响，恢复名誉》的话题，发完后黄毅清讽刺道：“发完了，还有什么要求需要满足的吗？希望靠我能让她重回一线的位置吧！”大概是气愤难平，黄毅清之后还在该条微博的评论里透露黄奕为了“博眼球炒作，跟法院申请庭审直播，才让我突然对这种只为自我炒作完全不考虑孩子的行为感到恶心，才毅然决定撤销上诉，为了孩子我忍了！我认了的！” +http://ent.163.com/17/1122/20/D3SGR35200038FO9.html +坑好兄弟！袁弘借胡歌摔倒糗事来安慰奚梦瑶 +对此，网友纷纷调侃袁弘坑好兄弟，拿胡歌的往事开玩笑。 +http://ent.163.com/17/1122/15/D3RUPJ0500038FO9.html +周杰伦紧搂昆凌撒狗粮 两人互换表情超有爱 +照片中，周杰伦紧搂着昆凌，两人都是黑帽配墨镜，十分炫酷。网友纷纷留言表示：“这狗粮撒的我一脸措手不及。”“甜死我吧！” +http://ent.163.com/17/1122/07/D3R357S500038FO9.html +实现对PG ONE的承诺却跌倒 奚梦瑶：我给他丢脸了 +奚梦瑶20日在结束走秀后，出来接受采访，被问及在场上跌倒一事时，她回想表示自己也不清楚是否不小心踩到了纱裙，坦言当下脑袋有几秒钟是空白一片，而且有点站不起来，“不是因为疼还是什么，是因为地板真的有点滑”，因此她也非常感谢身后的模特儿特别停下来扶自己，“我觉得真的很幸运，她就先让我走，那一刻我就真的觉得她有鼓励到我，而且有互相关爱的感觉。”除此之外，奚梦瑶也指出可以得到粉丝以及好友们的鼓励与关心，认为自己非常幸运，“当下我听到大家在下面为我鼓掌，我觉得很感动，就是还好在中国，在自己的家乡，有你们会来关心我。”她也提及有许多好友都纷纷到场支持，却出现这样的意外，让她非常内疚，尤其是对PG ONE，因过去曾在《中国有嘻哈》的节目中向PG ONE许下承诺，如果赢得总冠军，就邀请对方来看维密大秀，“这是我给他许下的承诺，所以我一定要完成我给他的承诺，结果…没想到…我让他们丢脸了。”事实上，PG ONE也在微博上转发了奚梦瑶向大家道歉的发文，并安慰：“今天真的特别美，加油啊，会一直疯狂为你打call滴”，暖心喊话融化了不少人。 +http://ent.163.com/17/1122/17/D3S5VHL100039867.html +王源17岁生日会 粉丝感动落泪：说我们脑残的人才是真脑残 +（文/张志明）王源，这个17岁的少年只用了4年的时间就站在了无人企及的荣耀之巅。入选美国《时代》周刊30位全球最具有影响力的青少年，在联合国上代表中国青年用英语演讲，粉丝拿下北京标志性建筑世贸天阶的LED滚动着王源的名字。这个17岁的少年伴随着千万粉丝成长，粉丝则以他为榜样。除此之外，粉丝还为王源定制了主题飞机，从重庆出发飞往五湖四海长达三个月共耗资300万。与此同时，北京世贸天阶LED屏上，一号线地铁、加拿大多伦多17块LED、德国慕尼黑市101家咖啡馆、伦敦地铁都响彻着这个清秀少年的名字和粉丝的祝福。这个出道4年的少年，在娱乐文化和粉丝经济的风口浪尖，收获了千万粉丝的喜爱。不禁让人想问，17岁的他凭什么？王源以崔健的《一块红布》作为开场，他稚嫩的脸庞和对不喑世事的音色中达不到崔健的情感表达，这首歌在特定时代有着特定的意义，他无声的坚持，在悲悯的时代里“我感觉你不是铁，却象铁一样强和烈。”重庆一家媒体曾拍到还未成名时王源家里的陈设，工薪家庭的本色可见一斑，12岁的他当年懵懵懂懂的决定，那时他还不知道这个决定改变了一生。在王源心里对母亲是有愧疚的，在常人来大多数都是20多岁步入社会参加工作，这个只有12岁的少年比同龄人提早了很多年，在忙碌的奔波中失去了自由，和母亲的相聚只是酒店里的匆匆一面。在生日会的最后，王源送上了献给妈妈的礼物，一首名为《骄傲》的新歌。“我只想有一天你能为我骄傲，你说男人要有理想，我说不会让你失望，看着家乡和你都变了模样，不知何时给你炖那碗，说了很久的汤”王源还是忍不住洒泪舞台，用衣袖挡住眼角，不让镜头抓住他的泪水。台下的粉丝被这个举动触动到，也纷纷跟着自己的爱豆哭起来，捂住面颊，热泪盈眶。在粉丝的价值观里，要为偶像消费尽力的刷流量，互联网将偶像和粉丝之间的联系变得更加紧密不分。“爱他就要为他花钱”成为粉丝心中的共同价值取向。她们的身份是恋人、是姐姐、是母亲，养成类的偶像模式，促使粉丝更加狂热，眼看着从12岁的年纪变成17岁的少年，这种情感依托务必强大，认同感和情感依赖是的来自不同年龄段，不同层次，不同身世的粉丝有了更加强大的凝聚力，彼此都获得了不同愉悦。她们把偶像当做一种道德模范和精神寄托，在采访的过程中，粉丝喜欢王源的年份各不相同，当问到为何喜欢王源时，得到的答案是：“为梦想坚持，认真专注，不忘初心，做公益事业，聪明通透”。这些还不到20岁的粉丝将现实里美好的一面都加于自己的偶像，但凹凸地被遮挡的背光面往往被忽视。当我们设想，假使你们喜欢的爱豆有了负面新闻，还会喜欢他吗？上世纪80年代出生的人群现在已经在社会中具有一定的话语权，他们始终无法理解这代将情感支撑寄托在偶像身上的粉丝做出的狂热的行为，嗤之以鼻称她们是脑残粉、丧失理智。步入中年的80后被生活琐事困扰，愈发油腻，来往于人情世故羁绊在是是非非中，理想和现实的差距让他们有所彷徨更坚信柴米油盐的珍贵。他们至始至终无法懂得粉丝在一起撕心裂肺的喊叫偶像的名字，大概代表着他们还仅有的热情所在。80后也许会忘掉，曾几何时，他们被称作“垮掉的一代”。叛逆和时代格格不入，有着对于这个世界的迷茫与无助，在批判声中，他们老去成为这个社会的中坚力量。也许忘记了，家中墙壁上挂着的“费翔”海报，走在路边摊上买的周杰伦和朴树的卡带。会小心翼翼的把孙燕姿的歌词手抄在笔记本上，在旁边画满五颜六色的图案。还有“超女”、“快男”火爆荧屏时，每个夏日的夜晚会准时准点为李宇春、张靓颖、周笔畅投上一票，那是国人第一次开启全民偶像的年代，也是第一次有了投票器。再过多久，这些都成为回忆，即使淡忘，都是追星的经历。生日会结束，王源站在舞台中央，90度鞠躬随着尖叫声消失在粉丝的视野中，对她们来说这就像一场梦，终究会有醒来的一天。生日会现场，幸运儿可以得到和王源合影比心的机会，当然不会是冲到舞台上亲密接触，而是在大屏幕上，相隔着舞台彼此做出“心”，即便这样也是她们和偶像最近距离的“接触”。散场后，北京一号线五棵松站被粉丝挤满，大多数粉丝都在买地铁卡，可见都是从外地赶来参加王源生日会的，当地铁里广告牌浮现王源的滚动视频的时候，粉丝都会停住脚步发出阵阵欢呼声，围成一团与偶像的照片来合影。当晚，王源的生日会将近有半个娱乐圈的明星来为他送上祝福，阵容可谓是空前强大，作为王源的牵线人，范冰冰也是亲自到场，而头号迷妹甜馨也在场。就当所有人在想组合成员的另两位为何没送上祝福的时候，王俊凯和易烊千玺推着蛋糕上台为好兄弟王源送上祝福，只是三个各自有了自己的工作室，至于以后在同台献唱的机会可能是屈指可数。粉丝采访实录：为王源过生日，你们会用哪种形式？你会喜欢王源多久，假如他有负面新闻了，你们还会喜欢他吗？很多人不理解粉丝对王源这种热爱，大家会觉得粉丝是失去理智的，是脑残粉？你喜欢王源多久了，喜欢王源身上什么？你为她做过最疯狂的事情是什么？我自己一个人来北京来看他，我从安徽过来，四周年的时候也是自己一个人去南京看他。 +http://ent.163.com/17/1122/09/D3R87SSM00038FO9.html +杨幂私下面貌曝光！素颜穿拖鞋坐地板超接地气 +杨幂杨幂工作室微博截图此照片曝光后，网友纷纷围观并留言称：“工作室也跟着杨幂学坏了，发日常都不发全脸”、“给工作室鸡腿”、“文艺幂回归，日常也这么有范”。 +http://ent.163.com/17/1122/07/D3R3EKDE00038FO9.html +谢娜怀孕后首度亮相 挺孕肚踩高跟鞋何炅全程紧牵 +谢娜21日晚间出席品牌活动，这也是她怀孕后第一次出席公开活动，她穿着黑色长外套，里面搭配一件桃红色长裙，宽松设计巧妙遮住孕肚，她的四肢看起来依旧非常纤细，气色看起来也非常好，而引人注目的是，她虽然已经怀孕数月，但是脚上仍踩着高跟长靴，让身旁的何炅也为她感到担心，全程在身边守护，紧紧牵着她，非常暖心。随后，谢娜也在发文中晒出与何炅以及杜海涛的合照，并开心表示：“在一起就很欢乐哈哈哈”，看来玩得非常开心。谢娜自怀孕后，就从未主动晒出自己的孕肚照，因此这次她首度亮相，随即引起近100万人次狂搜，瞬间登上微博榜首。事实上，谢娜过去曾被拍到挺杜与老公、朋友一起吃饭，当时她穿着黑色贴身长裙，外披一条粉色格子长围巾保暖兼遮身形，但是从侧身看上去，她的圆肚已经非常大，看起来约莫已有6、7个月身孕，让不少网友惊叹，“肚子已经这么大啦”、“这已经是快生了吧”，引起不少热议。 +http://ent.163.com/17/1122/11/D3RGN9O400038FO9.html +孙俪每逢佳节必泡脚 获封养生泡脚娘娘 +孙俪一贯都有在节气提醒大家泡脚的习惯，于是，此条微博一出，网友们便纷纷在下面调侃道：“又开始泡脚了，娘娘”“养生泡脚娘娘再次上线”等。 +http://ent.163.com/17/1122/11/D3RGFBG800038FO9.html +罗志祥遭“奇怪人士”尾随 微博求助被吐槽超会玩 +粉丝们纷纷吐槽又被爱豆给耍了，“哈哈哈哈哈哈罗妈妈好可爱！！你现在应该回头给她一个巨大么么哒！！”“你应该回头说：姐姐，我是朱碧石呀，您认识我吗”等。 +http://ent.163.com/17/1122/16/D3S3KIT500038FO9.html +上围丰满+肌肤雪白 萧蔷魔鬼身材维持18年 +萧蔷萧蔷推出2018年年历，主题是“暗夜瑰宝”，萧蔷解释：“‘暗夜瑰宝’是‘心中的深情’，静谧而安宁，显现自在自思的喜悦。正如心灵环保，映画于无污染的皓月星空。”萧蔷表示喜欢在夜深人静的夜里做心灵环保：“保护我们的环境，跟保护我们的心灵一样重要，即便墨夜浓云，心里依然皎洁。”萧蔷在2018年的新年历中，萧蔷也同样的展现出她性感的魔鬼身材，十八年前当红之际，萧蔷就以完美的33C、23、35的傲人身材比例，获媒体封为“台湾第一美女”，经过十八年，她依旧维持33C、23、35的身材，萧大美人是如何保持十八年如一日的好身材？一听到“魔鬼身材”，萧蔷立马谦虚地说：“不敢当！”但是她透露平日多做运动和练瑜伽，是可以维持身型的修长与柔软。 +http://ent.163.com/17/1122/14/D3RSBE3100038FO9.html +周杰伦晒与化妆师杜国璋合影 墨镜黑帽遮面凹造型 +网友们看到这张合影，纷纷留言评论道：“姿势没毛病，很酷！”，“虽然你比较酷，但杜哥腿比你长！”也有网友有不同意见，调侃称：“杜哥腿快不够长了~” +http://ent.163.com/17/1122/10/D3RCSDG900038FO9.html +Ella分享观看维密秀心得 呼吁大家勇敢大方做自己 +配图上的Ella也像个天使一样美丽，一身镂空黑色连衣裙时尚又性感，裙尾的流苏俏皮又可爱，长耳环配上披肩的中长发，被网友点赞：“气场十足完全不输超模啊！” +http://ent.163.com/17/1122/21/D3SI21IN00038FO9.html +新人男星叫刘德华"华仔" 冯德伦变脸：你几岁呀 +在最新一集节目，冯德伦特地邀请沙溢、胡可夫妻档做客，但他事先没向其他人透露嘉宾是谁，引起大家好奇纷纷问是谁，冯德伦则继续卖关子说“你看到就知道啊”，接着潘宥诚开口问：“是华仔吗？”他一猜完，冯德伦就皱眉回说：“你叫华哥做华仔呀，你几岁呀？”潘宥诚听完后，马上就解释这样叫显得刘德华年轻，再接上一句“对不对，冯仔”想化解尴尬。但节目播出后，不少网友认为“华仔”是让粉丝叫的，而潘宥诚作为圈内人不应该这样称呼，直批他不尊重前辈。 +http://ent.163.com/17/1122/11/D3RH1VT0000380CU.html +《机器之血》曝海报 成龙打上悉尼歌剧院 +成龙再战新地标 飞跃悉尼歌剧院挑战动作极限从《我是谁》中的鹿特丹地标马士基大厦的玻璃外墙，到《新警察故事》里香港会展中心的屋顶，成龙征战过的地标性建筑不胜枚举，惊险刺激的危险表演，无不让观众惊叹折服。此次，影片《机器之血》中，成龙再战新地标，在悉尼歌剧院楼顶上演精彩震撼的玩儿命打斗飞跃，再次为观众带来命悬一线的危机感，和大饱眼福的动作特技。这也是悉尼歌剧院首次迎来功夫巨星的登顶演出，之前从未有任何演员上去过。罗志祥迎来“人类”角色 “龙猪组合”打逗贺岁继《美人鱼》中的八爪鱼之后，这次在《机器之血》中小猪终于迎来“人类”角色，饰演一位超级骇客，耍小聪明闯大祸，被成龙大哥多番“修理”，但这位“猪队友”添乱之余，偶尔还能歪打正着帮点儿忙，“龙猪组合”的打逗搭档为影片带来意想不到的惊喜。据了解，两人在拍摄期相处十分融洽。起初在剧组面对成龙还有些“偶像距离”因此颇为收敛的罗志祥，在几场戏之后，就敢“偷袭”大哥，还得意称“我是唯一打的赢成龙的人”。成龙也赞他表现精彩。年关佳节的票房大当家 贺岁大片看成龙已成观影现象从1995年的《红番区》开始，几乎每年年关贺岁，都少不了一部成龙的精彩影片。去年春节的《功夫瑜伽》更是叫好又叫座，拿下了17亿的票房成绩，成为该档期最大赢家。每逢佳节年关，全家老少去影院看一部成龙电影，几乎成了国内观影现象。“成龙”这一标签，也逐渐成为年关佳节的票房当家。《机器之血》中，成龙依旧玩儿命，勇敢突破，动作细节和表演张力均十分到位，过硬的动作喜剧特质展露大片气质，有望延续其历年佳绩。电影《机器之血》由成龙监制，张立嘉执导，成龙、罗志祥领衔主演，欧阳娜娜、夏侯云姗、卡兰·穆尔韦（Callan Mulvey）、泰丝·哈乌布里奇（Tess Haubrich）主演，将于12月22日压轴贺岁，全国上映。一如既往玩命打拼的成龙贡献了近10年来最精彩的打斗场面和精巧的动作设计，更有前所未见的全新的情节和元素，值得期待。 +http://ent.163.com/17/1122/10/D3RDQ6UI000380D0.html +《捉妖记2》曝天师犯傻特辑 白百何井柏然更默契 + +http://ent.163.com/17/1122/17/D3S62IDV00038IPD.html +《蒙面唱将》第二季收官 阿鲁阿卓《消愁》吸睛 +阿鲁阿卓。“我是大魔王”阿鲁阿卓的《消愁》不仅让猜评团大呼：“这么好的声音怎么现在才来”，也让电视机的观众对她留下深刻印象。日前，阿鲁阿卓接受媒体采访时透露，自己早在去年就关注了这档节目，“没想到（《消愁》）引起那么好的反响。”该曲是人气歌手毛不易的原创作品，得知毛不易也有观看自己的演唱后，阿鲁阿卓笑称这是一个隔空交流，“我之前也被他的演唱所感动。这首歌很难唱，后面有点激动，我觉得还可以唱得更好一些。”低调的阿鲁阿卓虽然对部分观众来说名字有些陌生，但其实近年来她唱过不少热播剧的插曲，包括《芈月传》的片尾曲《西风》，《急诊科医生》片头曲《在你身边》。她表示这都是机缘巧合，“《芈月传》是因为我录了小样，出来后导演非常满意。《急诊科医生》是制片人打电话给我，说想听我唱一唱。刚好这两部剧播得也不错。”这次上了《蒙面唱将》，阿鲁阿卓坦承最期待能与大张伟[微博]合作，“我跟他不是很熟。但我能感觉他一定是在音乐方面会很有感觉、很有灵感，他太聪明了，跟他一起合作一定会有火花。” +http://ent.163.com/17/1122/16/D3S2LU3H000380EN.html +《海上牧云记》首播告捷 满屏诚意构建耀目九州 + +http://ent.163.com/17/1122/15/D3RUQ9MO00037VVV.html +《神秘的味道》沈南自曝身高 白菜竟花五小时烹调 + +http://ent.163.com/17/1122/15/D3RTV9H2000380EN.html +秦凯何姿亮相《蔚蓝50米》 冠军夫妇甜蜜发糖 + +http://ent.163.com/17/1122/15/D3RTQ89R000380EN.html +《凡人的品格》温馨收官 多面梁振伦精彩延续 +事业爱情双丰收 《凡人的品格》完美收官 昨晚，电视剧《凡人的品格》终于落下帷幕，完美收官。剧中作为创业小白的展昭一面与父亲爷爷一起“打怪升级”，建立展家包，事业初起步。另一面，虽然同样坎坷不减，但却在不断的误会与相互理解中赢得了温迪芳心。从一开始的玩世不恭公子哥，到后期的稳重而又敢创业的热血青年的转变是展昭这个角色的一大看点，剧中梁振伦凭借纯熟的演技，对人物动作细节，内心世界转变的刻画以及阳光温暖的气质属性成功的塑造了展昭一角，备受好评。新作品接连不断 多面梁振伦精彩延续随着《凡人的品格》大结局的播出，展昭与温迪的相拥不仅为该剧添上了甜蜜的一笔，也代表着梁振伦对角色形象的又一次新鲜尝试也正式谢幕。作为从话剧舞台转战到电视荧屏时间并不长的实力演员，2017年梁振伦再度为观众奉献了不少深入人心的优秀角色，举手投足间一点一滴的渗透中，倾尽所能还原丰富人物形象和剧本。入行至今，踏实演戏，琢磨戏的梁振伦正在一步一个脚印的奋力前行。透过前期的蛰伏岁月，多年的舞台表演经验积累，慢慢蓄力，终于在影视剧中得到爆发。据了解，梁振伦接下来还会有《我的小姨》多部剧集等待播出，精彩延续。 +http://ent.163.com/17/1122/15/D3RSQ6H900037VVV.html +《天籁之战2》华晨宇遭遇无字歌“好绝望” +华晨宇抽中“无字歌” 直言“好绝望”在上期节目中，华晨宇上演“假面的温柔”，深情演绎了《我很丑可是我很温柔》，好评如潮，许多网友都对他大为赞赏。本期节目中，他被选到的是一首游戏背景音乐，只有旋律，没有歌词。此次看到歌单的一瞬，中了“大奖”的华晨宇哭笑不得地说：“这怎么改编啊，我有一种绝望的感觉！”其实在上一季《天籁之战》中，华晨宇就遇到过《齐天大圣》这首难度系数极高的歌曲，但是华晨宇用他天马行空的想象力改编创作之后，这首歌无论是在歌词和曲的衔接上还是rap和唱的衔接上，都毫无违和感，且现场表演极具爆发力和感染力，让观众充分感受到了“华氏”摇滚说唱的魅力。这一次，在24小时之内，他又会如何改编这首“无字歌”呢？所有人都抱以期待！张杰挑战经典民歌 原版MV女主竟是谢娜除了精彩的曲目改编，稳定的唱功、精心的编排、舞美的配合往往也都是制胜关键，在前几期节目中，张杰就以他力求完美的舞台表现广受认同。在本期节目中，张杰又一次被抽中了一首经典之作，这首歌唱遍了大江南北，巧的是这首歌的MV女主角，正是著名主持人谢娜。就是这样一首与张杰“渊源颇深”的歌曲，被张杰赋予了全新的生命，延续了他最擅长的“MIX-POP”，用当下最流行的“牙买加风格”与经典民歌相融合，国际化的改编令费玉清大加赞赏：“从张杰来到《天籁之战》，听了他这么多首歌，真的觉得没有什么可以难倒他，不容易，太棒了！”面对具有超强实力的素人挑战者们，“天籁唱将”们会有怎样的惊艳表现？而对华晨宇撂下“狠话”的挑战者究竟实力有多强？与张杰渊源颇深的歌曲又是哪首？更加精彩的音乐对决，就在本周六20：30东方卫视《天籁之战》第二季。 +http://ent.163.com/17/1122/08/D3R726IK00038FO9.html +防弹少年团破吉尼斯世界纪录 微醺直播呆萌可爱 +防弹少年团受邀在全美音乐奖表演，不但事前上遍通告做宣传，更在现场俨然成为“人形立牌”被许多欧美歌手邀请合照，精彩的演出和现场粉丝们的超大应援声都引以话题，在当地掀起一股BTS效应。演出结束后，防弹少年团也即刻登上了美国Google关键字排行榜第一名。世界弹的威力也获得了认证，吉尼斯世界纪录在20日宣布，防弹少年团成为“全世界在推特被提及次数最多的音乐组合”，甚至光是20日短短一天，就有2000万条防弹少年团参与“2017全美音乐奖”相关推特，人气和讨论度都让人惊奇。事实上，防弹少年团今年五月就在美国“告示牌音乐奖”（Billboard Music Awards）击败六连霸的小贾斯汀，拿下“最佳社群明星奖”（Top Social Artist）。防弹少年团20日（当地时间19日）也开直播分享参加2017全美音乐奖的心得，直播一开始，就可以看到桌上有酒瓶，因此团员们超海的反应除了是卸下重担的轻松心情外，也可能是带点微醺的反应。包括团员V和JIMIN都露出了有点“茫”的软萌可爱模样，队长RM也不小心对团内的“老么”柾国说了“敬语”，连自己都傻眼笑了出来。至于光是现身红毯就在推特被狂搜得“左三男”大哥JIN则是看着镜头傻笑，不但差点说出“还不能说的合作对象”，还脱口：“哇！我这样穿著衬衫，有点透，好性感。”而因为法定年龄未到实岁21岁而不能在美国饮酒的“老么”柾国彷彿成了最清醒的人，还会提醒JIN：“哥，衬衫领口要挡一下。”不过下一秒就被JIMIN再度拉开。逗趣的反应也让粉丝笑说：“微醺状态太可爱了，拜托以后多多这样开直播。” +http://ent.163.com/17/1122/08/D3R70HJB00038FO9.html +萧敬腾活动出灵异事件！灯光诡异失控全场吓傻 +《可可夜总会》首映会刚开始，主持人黄子佼麦克风突然没声音，换了另外一支麦克风又没声音，他只好打圆场说：“刚好符合这部电影亡灵节的主题。”后来萧敬腾讲话一半灯光突然暗掉，全场吓傻，还好马上又亮了起来。没过多久，灯光又突然闪烁不停，萧敬腾傻看活动公司：“故意安排好的吧？”但对方猛摇头否认，令在场观众不禁毛骨悚然。萧敬腾被主持人黄子佼要求模仿角色的口音，他也有求必应说出“一定要来看可可夜总会”，真的跟平常的声音不太一样。其实他配音时，动画根本还没画好，只能透过一些素描，听从导演指示去配音，被黄子佼笑说是“盲配”。被问到灵异体质时，萧敬腾笑回：“不要说这个，有些人相信，有些人不相信，我不想让大家不舒服。” +http://ent.163.com/17/1122/07/D3R357S500038FO9.html +实现对PG ONE的承诺却跌倒 奚梦瑶：我给他丢脸了 +奚梦瑶20日在结束走秀后，出来接受采访，被问及在场上跌倒一事时，她回想表示自己也不清楚是否不小心踩到了纱裙，坦言当下脑袋有几秒钟是空白一片，而且有点站不起来，“不是因为疼还是什么，是因为地板真的有点滑”，因此她也非常感谢身后的模特儿特别停下来扶自己，“我觉得真的很幸运，她就先让我走，那一刻我就真的觉得她有鼓励到我，而且有互相关爱的感觉。”除此之外，奚梦瑶也指出可以得到粉丝以及好友们的鼓励与关心，认为自己非常幸运，“当下我听到大家在下面为我鼓掌，我觉得很感动，就是还好在中国，在自己的家乡，有你们会来关心我。”她也提及有许多好友都纷纷到场支持，却出现这样的意外，让她非常内疚，尤其是对PG ONE，因过去曾在《中国有嘻哈》的节目中向PG ONE许下承诺，如果赢得总冠军，就邀请对方来看维密大秀，“这是我给他许下的承诺，所以我一定要完成我给他的承诺，结果…没想到…我让他们丢脸了。”事实上，PG ONE也在微博上转发了奚梦瑶向大家道歉的发文，并安慰：“今天真的特别美，加油啊，会一直疯狂为你打call滴”，暖心喊话融化了不少人。 +http://ent.163.com/17/1122/06/D3QV0OS900038FO9.html +罗大佑再回京开唱：离家的人要勇敢起来 +1985年3月9日，罗大佑离开家乡开始独自闯荡，在外生活数十年之后，他终于在去年带着妻女回到台北定居。“现在北京也有很多离家在外的年轻人，大家可能会有更多的压力，”罗大佑说，“我非常理解这种心情，所以这次也希望能够通过音乐告诉大家，要勇敢，不要怕。”在今年的10月14日，“当年离家的年轻人”已在台北小巨蛋拉开帷幕，而在大陆首站北京站过后，“当年离家的年轻人”还将于2018年1月27日在深圳继续上演。离家的日子 想家，不要不好意思讲出来“家是我们内心深处最沉重最深层的感情，也是不会轻易跟人分享的主题，”罗大佑在今年刚刚发行了最新个人专辑《家III》，他感慨道，“因为我曾经离家不止一次，所以现在我已经有这个辈分和资历跟大家讲：提到‘家’是很好的一件事，很多人想家却不好意思讲出来，尤其是很多男生，会觉得是在跟竞争对手示弱，但其实不是这样。”回想起自己第一次离开家乡的经历，罗大佑说，是发生在学生时代，“当时我从家乡高雄去台中念书，到现在我还记得爸爸妈妈去月台送我的画面。”后来，已经走上医生岗位的罗大佑，选择离开台湾前往香港，“当时我对音乐不死心，所以就写了10页的信，跟家里讲不要当医生这件事。因为我在做音乐时会全力以赴，经常会有‘做完这首歌，死而无憾’的感觉，像《童年》《未来的主人翁》，但在做医生时没有办法这样，在医院里面看病也好像是一个负担，我也找不到让我快乐的点。”离家在外的日子里，罗大佑坦言，自己也与当下的年轻人一样，经常走入迷惘与困惑，“在香港的时候，有一次我在做杜琪峰一部电影的配乐，那天是星期五的晚上，我突然发现整个录音室只有我一个人在那边写东西了，其他人可能都去玩了。当时我也不会讲广东话，所以就觉得自己怎么那么惨。我有一首闽南语的歌叫《故乡》，就是那段时间写的。”罗 大 佑 有 话 说给孩子的话 让女儿喜欢生命，让别人也喜欢她从2012年开始，我人生扮演的角色不一样了，变成爸爸了，天哪。从2012年到2014年那段时间，家里的事情就比较多，因为小朋友出生前三年是比较重要的，她以后无论是要成为一个开心的人，或是压抑的人，都是这段时间在她潜意识里埋藏的结果，所以我们就很小心。因为我58岁才有了这个小朋友，没有心理准备是不行的，我们就会讨论应该要怎么养她、怎么带她。不过我也不会有“望女成凤”的想法，我就觉得在一起的时间就开心一点，给她的人生导引正确一点，让她有一个快快乐乐的童年，让她喜欢生命，让别人也喜欢她，这样就够了。给年轻人的话不快乐？因为一切“太便利”现在的年轻人比起我们那个时候，可以很轻易地结交世界范围内的朋友，也拥有几千万倍的资讯来源。但是为什么现在的年轻人更加不开心了呢？我相信其中一个原因是，“便利”让现在的年轻人缺少了“不知道怎么办”的过程。比如说，在做音乐时，很多软件很方便，但一些基本的动作是很重要的——像你想做什么音乐，却做不到，你想联系什么人，却联系不到，那么经过挣扎之后克服这些问题，从0到0.1那个找到一束光的过程，才是真功夫，你才知道这个东西有多可贵。给自己的话角色改变后，肩膀上扛的东西多了很多人说我今年新专辑的音乐风格更温暖了，其实写歌的程序都还是一样的，但是如果旁边多了一些支持你的人，你的身份从“一个年轻人”变化成了“这个人的爸爸”“那个人的先生”，这些角色改变以后，肩膀上扛的东西就多了。你会认识到当年父母对自己的栽培，而现在，要换我了。所以像《未来的主人翁》这首歌，可能就是对未来小朋友或者人类的责任，让我们变得更坚强了吧。 +http://money.163.com/17/1122/16/D3S3284V0025816E.html +现金贷遭监管重锤：从野蛮生长到一夜崩塌 + + （原标题：监管靴子落地，现金贷一夜间变“烫手山芋”） + 整治现金贷的政策“靴子”开始落地。这一纸标注“特急”的文件被视为整治现金贷的第一步，据悉，围绕网络小贷还有一系列的规范政策将在不久之后陆续出台。从野蛮生长到一夜崩塌早在2007年前后，网络小贷业务雏形初现。那时阿里小贷与建行、工行等展开合作，前者提供商家信息，银行提供资金，互联网平台与商业银行“联合放款”。进入2014年，伴随中国整个互联网生态的日渐成熟和旺盛的市场需求，网络小贷开始兴起，并逐渐成为新的互联网金融热点，大量资本蜂拥而至。从时间上看，2014年可作为网络小贷野蛮生长的分水岭。在2014年及之前，全国范围内被准许在互联网上开展业务的小贷公司不过10家左右。从2014年开始，网络小贷公司数量开始逐年增加，仅2016年一年，全国就冒出了近60家。在此之后，网络小贷一路高歌猛进，开启“疯长”模式。据不完全统计，截至2017年10月末，全国范围内共有237张网络小贷牌照，另外还有22张牌照尚在发起状态。图片来自网络。网络小贷一路疯长的背后离不开其特殊的审批机制。根据2008年的《管理办法》，“设立小贷公司需向省级政府主管部门提出正式申请”，即省级金融办拥有最终的批复权。审批权被下放到地方金融机构虽然灵活，但缺乏了中央层面的监管，也为小贷行业的发展之路埋下隐患。另一方面，网络小贷打破了小贷公司不得“跨区经营”的要求，公司在一地注册，可在全国放贷。这同时带来了监管上的Bug，极大地放大了风险。近期一些公司借助互联网小贷的牌照而大肆发放现金贷，其中的道德问题和法律合规问题已引发了舆论的诸多诟病。一旦陷入疯狂和失序，监管就来了，只是这次监管出手更快、更彻底。先是2015年8月7月人民银行等十部委联合发布的《关于促进互联网金融健康发展的指导意见》就将网络小额贷款归类于网络借贷，并明确网络借贷业务归属银监会监管。再是今年初，银监会对各地金融办做了“窗口指导”，要求严格准入，并提高了网络小贷的准入门槛，例如，提高实缴资本、（在注册地）建立线下职场、（股东）有互联网背景等。直到21日，随着“特急”文件的下发，网络小贷的新增窗口彻底关闭。图片来自网络。对现金贷砸下重锤“特急”文件中明确显示，部分机构开展的“现金贷”业务存在较大风险隐患，各级小额贷款公司监管部门暂停发放网络小贷牌照。至于现金贷业务存在的风险隐患，官方其实早有指出。2017年4月，官方下发的《关于开展“现金贷”业务活动清理整顿工作的通知》中便提及现金贷，其中明确指出部分现金贷平台存在三大问题，一是利率畸高，二是风控基本为零，坏账率极高，依靠暴利覆盖风险，三是利滚利让借款人陷入负债危机。中国人民大学重阳金融研究院高级研究员董希淼表示，处于快速增长中的“现金贷”，存在着较大风险隐患。如果任由其野蛮生长，可能对金融稳定进而对社会稳定产生较大冲击。一方面，“现金贷”门槛极低，极易将资金放给不合适的申请人，从而产生次级贷款。另一方面，“现金贷”利率畸高且不透明。同样是今年4月，银监会发布《中国银监会关于银行业风险防控工作的指导意见》，现金贷被“点名”。银监会列了一份详尽名单，包括429个APP，72个微信公众号和117个网站，要求各地的相关互金和小贷协会重点排查这些网络现金贷的利率和服务费、放贷对象、催收方式、数据来源及放贷资质。虽然此后有部分违规现金贷公司被关停，但业内仍认为银监会的指导意见并没有带来实质性的措施落地。然而这一情况在今年10月发生了改变，趣店上市事件推动了监管部门的措施落地。10月下旬以来，伴随着趣店上市，现金贷引发强烈关注，社会各界对现金贷背后存在的各种风险隐患表示担忧。与此同时，对现金贷的监管存在诸多难点，包括互联网突破了属地监管限制、各种手段规避36%利率上限、“暴力催收”难以认定等。随后，北京金融局对北京地区的现金贷平台资金来源作出限制，要求各平台只能用自有资金放贷，不再允许与持牌金融机构联合放贷。这意味着，现金贷平台的放贷规模会受到重创。此前一位小贷行业资深业务人士表示，现金贷的归属目前还存在模糊的地方，从本质上看它不属于互联网借贷，也不属于金融机构，应该属于互联网小贷。因此，谁来监管的问题还存在盲区，很多机构也没有相关牌照，这也是地方和银监会未来一定会整顿的重要原因。但可以确定的是，这趟“列车”现在已经被按下了刹车键。 +http://money.163.com/17/1122/15/D3RSS1GC002580S6.html +高利贷公司堵门 煤矿工作人员开装载机冲向讨债者 + + （原标题：因债务纠纷 煤矿工作人员开装载机将卡车和轿车撞下10米高台） + 视频截图视频截图当地警方接警后，当地派出所迅速组织警力赶赴现场处置，及时制止双方行为，组织人员将伤者送医院治疗，开展现场调查取证工作，并将情况向宣威市公安局报告。视频截图经宣威市公安局初步调查，该群体性事件系债务纠纷引起，在要账过程中双方发生口角纠纷，言语升级后发生打斗，造成3人轻伤。目前，宣威市公安局依法刑事拘留双方犯罪嫌疑人6人，并对其他参与人的违法犯罪行为开展调查，各项工作正在有序进行中。（原题《因债务纠纷 煤矿工作人员开装载机将卡车和轿车撞下10米高台》） +http://money.163.com/17/1122/17/D3S56IA300258J1R.html +共享单车死亡名单！数亿元押金打水漂 你被坑了吗 +网易研究局NO.154作者|张梅图2 共享单车死亡名单（制图：网易研究局（微信ID：hccyjj163））不得不说，曾经一个调色盘都装不下的共享单车游戏，热闹过后一地鸡毛。多少用户的押金打了水漂？今年创业圈有一句话非常流行——“失败了就当做公益”。现今，多个共享单车企业跑路，用户押金难退，细细想来，真正在做公益的难道不是广大用户吗？根据《中国互联网络发展状况统计报告》，截至2017年6月，共享单车用户规模已达到1.06亿。按用户平均超过百元押金估算，整个共享单车行业的押金数量或已超100亿元，其中还不包括用户提前充值的各类未消费余额。究竟多少用户的押金打了水漂？黄局长根据公开资料为大家算一下。悟空单车：押金已全部退还图3 悟空单车（来源：网络）2017年6月13日，悟空单车宣布退出共享单车市场。截至退出前，悟空单车有约一万名用户，每辆车每天平均使用频率在三到四次。停止运营后，悟空单车将押金全部退还给了用户，总计约100余万元。町町单车：1万多名用户退不了押金图4 町町单车 （来源：网络）2017年8月2日，运营町町单车的南京铁拜网络科技有限公司因非法集资、资金链断裂，公司与栖霞工商局失去联系，因此被纳入异常企业经营名录。根据北京青年报10月31日的报道，町町单车创始人丁伟表示，对于退不了押金的一万多用户，仍希望退还钱款，或者每人分到一台成本为1800元的单车。小鸣单车：欠用户的押金约5000万元左右图5 小鸣单车 （来源：网络）2017年7月，小鸣单车用户反映押金难退问题，引发用户退押金潮爆发。10月26日，小鸣单车员工对《华夏时报》记者表示，小鸣目前欠用户的押金大概在5000万元左右，以每个用户199元押金粗略计算，涉及的欠款用户大概在25万左右。他同时表示，小鸣单车现在仅剩微博一个退款通道。酷骑单车：仍有7亿元押金未退还用户图6 酷骑单车 （来源：网络）今年8月起，酷骑的退押金困难持续蔓延，它与P2P平台诚信贷之间扑朔迷离的关系也让外界心生警惕。从9月中旬开始，酷骑单车位于沈阳、合肥、郑州、西安等多地的分公司都陆续被曝出“人去楼空”。21世纪经济报道在11月21日的文章中指出，酷骑仍有7亿元押金未退还用户。小蓝单车：欠款高达2亿用户押金难退图7 小蓝单车 （来源：网络）今年9月份，小蓝单车不断被曝出有逾期未退还押金的现象。10月20日，小蓝单车曾发布公告称，用户于2017年10月30日之前申请的退款，将于2017年11月10日前退还完毕。到了11月中旬，小蓝单车承诺的退款期限已过，却有不少网友反映并未收到退款。有媒体报道，目前小蓝单车拖欠供应商款项高达2亿元，涉及70余家供应商，大部分供应商被拖欠款项在100万元左右，部分供应商被拖欠款项高达800万元。虽然目前小蓝单车拖欠的用户押金还没有准确数据，但是小蓝单车官方公布的资料显示，注册用户数量超过1500万，以每人押金99元计算，这个押金池规模着实不小，风险不容小觑。你的押金还能要回来吗？? ?“押金难退”着实让正享受着共享单车便利的用户们揪了一把心，新京报记者分别致电北京市工商局和北京市交通委的热线电话，得到的反馈均是，“由于当前押金池监管权责规定不明，尚未开展相关具体工作”。北京市工商局表示，押金属消费者所有，在用户提出退款申请后，共享单车企业必须在规定期限内归还。但工商部门针对消费者投诉只能开展行政调解，如果企业拒绝配合，依照相关规定只能终止调解，建议消费者走司法途径解决。北京市交通委则回复称，出现押金退款延迟时建议联系软件运营商，市交通委不负责监督押金，也不负责受理消费者要求追讨押金的投诉，建议向其他部门反映。中国人民大学法学院教授刘俊海认为，押金所有权属于用户，退还押金后才能破产清算。而消费者未消费的充值余额，名义上仍属于消费者，同样不是破产财产，消费者享有优先取回的权利，不能用作债务清偿。北京汇佳律师事务所律师、北京市消费者协会法律顾问邱宝昌建议，在相关法律文件并不完善的前提下，一旦共享单车企业出现破产问题时，用户可进行债权申报，并保留相关押金付款证据。网易研究局（微信公号：hccyjj163） 出品网易研究局是网易新闻打造的财经专业智库，整合网易财经原创多媒体矩阵，依托于上百位国内外顶尖经济学家的智慧成果，针对经济学热点话题，进行理性、客观的分析解读，打造有态度的前沿财经智库。特朗普携豪华商贸团访华 重点合作领域提前曝光五大美联储主席候选人对决 胜算最大的竟是TA +http://money.163.com/17/1122/17/D3S3T37S0025816D.html +媒体：安邦被要求减持其所持有的民生、招行股权 +知情人士称，为减少对市场的影响，监管当局建议安邦集团通过非公开方式退出或减持；监管当局正在帮助安邦寻找合适的股权接盘方。据澎湃新闻不完全统计，光在保险公司方面，安邦保险、富德生命人寿、新华人寿、中国人寿等的资管计划，持有沪深股市的上市银行股份就超过了上述规定，更不用提在未上市银行中的持股。财新此前报道称，四大国有银行半年报显示安邦保险集团二季度减仓，截至6月 末安邦已经退出工行、建行、农行的前十大股东之列。据彭博计算，安邦人寿9月原保险保费收入同比下降97.4%。银监会阻击银行业资本大鳄:持股5%以上需事先核准11月16日，中国银监会为规范银行股东行为、弥补监管短板，发布了《商业银行股权管理暂行办法（征求意见稿）》，向社会公开征求意见。本次征求意见稿最为醒目的是，“同一投资人及其关联方、一致行动人作为主要股东入股商业银行的数量不得超过2家，或控制商业银行的数量不得超过1家。”安邦退出三大行前十股东 减持套现66亿元近日，中国四大行相继公布上半年年报，其中工行、建行、农行的半年报显示，安邦保险集团已经退出上述三大银行的前十大股东之列。由此，截至6月末，除了通过安邦财险和安邦人寿持有0.12%中国银行A股股份、仍为该行前十大股东外，安邦保险集团已经退出工行、建行、农行的前十大股东之列。安邦保险集团通过旗下不同产品，集中买入工农中建四大行A股股份，且均跻身前十大股东之列是在2015年下半年。 +http://money.163.com/17/1122/05/D3QSOI3S002580S6.html +蚂蚁金服重击现金贷：芝麻信用停止服务部分机构 + + （原标题：蚂蚁金服重击现金贷平台： 趣店导流缩减 芝麻信用停止服务部分违规机构） + 由于趣店股价近期连日重挫，引起美国证券律师事务所Faruqi & Faruqi的注意，该公司在当地时间11月20日宣布，对趣店发起调查，以查明其是否存在潜在的违规行为。Faruqi & Faruqi还向因投资趣店而亏损的投资者号召，希望他们能够提供调查线索。对此，趣店相关人士21日回复21世纪经济报道记者称，暂时还没有更多的情况可以披露。上市后，趣店的现金贷模式深陷舆论风波。据多地金融办人士向21世纪经济报道记者透露，国家有关部门正在制定针对现金贷的监管细则。继近日宁波鄞州区叫停两家违规现金贷公司后，11月21日，监管下发《关于立即暂停批设网络小额贷款公司的通知》，要求自即日起，各级小贷公司监管部门一律不得新批设网络（互联网）小贷公司，禁止新增批设小额贷款公司跨省（区、市）开展小额贷款业务。可以预见的是，现金贷行业将迎来一波清理整顿的生死大考。蚂蚁金服否认收紧趣店导流蚂蚁金服相关人士11月20日对21世纪经济报道记者表示，趣店是蚂蚁金服开放平台上的合作伙伴之一，双方的合作关系没有变化。趣店在支付宝App中的入口遵从蚂蚁金服开放平台统一的标准和算法，蚂蚁金服开放平台并未针对单一产品进行调整。个别用户反馈的趣店入口不可见的问题，可能是由于算法优化产生的。但不管是怎样的算法优化，客观上确实导致了部分支付宝用户看不到趣店的入口。这将给趣店的业务规模带来多大的影响，尚待其四季度报告披露。事实上，蚂蚁金服旗下自有现金贷产品蚂蚁借呗，且规模不小。21世纪经济报道记者根据Wind数据统计，2017年前10个月，蚂蚁借呗发行的ABS总额达1071.1亿元，蚂蚁花呗ABS发行总额达1061亿元，占企业ABS中以小额贷款为基础资产的发行总额的95%以上。虽然ABS发行规模不能完全代表业务规模，且存在时滞，但结合市场和ABS发行情况估计，蚂蚁借呗今年的业务规模可能已经破千亿。21世纪经济报道记者还在统计中发现，主要提供现金贷款产品的蚂蚁借呗ABS发行量，在2017年7月之后连续快速增长，其中10月份单月发行量达239.7亿元，已超过有消费场景的蚂蚁花呗单月发行量的最大值。消费者对于蚂蚁借呗现金贷产品的需求，显现出超越消费金融产品的趋势。其发行的ABS招募说明书显示，蚂蚁借呗ABS的预期收益率一般在4.5%-5.5%，而蚂蚁借呗贷款利率约在日息0.015%-0.06%之间，相较其募资成本，净收益率可观。存在竞争关系的背景下，蚂蚁金服为什么还要在支付宝开放导流入口给趣店？对此，蚂蚁金服的官方说法是，因为趣店是蚂蚁开放平台的伙伴之一，蚂蚁一直以来就想打造一个开放的金融平台生态，对于平台来说，并不存在竞争对手的问题。且二者间存在利益攸关的股权纽带。据趣店招股书披露，蚂蚁金服旗下投资公司仅持有趣店12.8%的股权，为第五大股东。而趣店的转折点，正是从接入支付宝后，开始扭亏并迎来快速发展的。之前支付宝的导流是免费的，但从今年开始支付宝向趣店收费。趣店今年三季度财报显示，其当季销售费用为1.88亿元人民币，同比增长384.7%，环比增长97.13%。趣店的销售费用主要用于支付宝的通道费用。对此，趣店相关人士对21世纪经济报道记者表示，趣店和蚂蚁金服的合作是基于市场化的合作，蚂蚁金服对趣店的收费方式，与其它的消费金融业务合作伙伴基本保持一致。芝麻信用停止与部分现金贷公司合作尽管监管靴子尚未落地，市场已经悄然谨慎收缩。继银行等金融机构收紧与现金贷公司的合作后，蚂蚁金服也给了现金贷一大打击。蚂蚁金服旗下的芝麻信用为包括趣店在内的多家现金贷公司提供征信数据服务。以趣店为例，他们为芝麻分超过一定标准的用户提供信贷。11月21日有消息称，一现金贷平台收到芝麻信用关于终止服务的通知，理由是“芝麻信用持续收到多起用户对贵公司存在收取法定保护利率以上各类费用、不当催收等方面的投诉”。对此，蚂蚁金服21日对21世纪经济报道记者回应称，近日芝麻信用在排查中发现，个别商户存在超过法定保护利率以上的各类费用、不当催收、没有按照协议履约等问题，所以暂停了合作；芝麻信用对合作伙伴有明确的准入规则，还会持续排查商户的资质、产品和服务情况；后续，如发现类似问题，也会立即停止合作。蚂蚁金服表示：“消费金融行业是芝麻信用对外开放的一个重要领域，包括银行持牌消费金融机构，也包括现金贷公司。芝麻信用的平台业务是很谨慎的，为了整个行业的健康发展，芝麻信用有持续的关注和规范方式。目前芝麻信用对合作伙伴的管理，主要是从资质和产品两个维度，并没有专门针对现金贷公司的政策和服务。”事实上，芝麻信用的排查并非最近启动的。早在今年8月份，芝麻信用就开始排查与现金贷公司的合作。当时芝麻信用要求合作的平台提供对应经营资质的证明，否则芝麻信用将无法继续提供服务。芝麻信用所要求的资质证明，指的是针对有放贷资质的机构，需要提供放贷资质证明文件；如非使用自有资金放贷的机构，需要提供平台与放贷机构间的合作协议。目前多数现金贷平台都将芝麻分作为征信的主要手段之一。芝麻信用一下子收紧了与现金贷对接的通道，被抛弃者只能筹划替代芝麻信用的风控方案和其他可选的数据源。凑巧的是，另一互联网巨头腾讯的信用分于近期上线。11月19日，广州的用户可以凭借腾讯信用分申请摩拜免押金。腾讯信用分的定位与芝麻信用分如出一辙。目前，腾讯信用分尚处于灰度测试阶段，需要拥有公测资格的用户才能查询分数。不过，蚂蚁金服并未透露此次终止合作的现金贷平台数量。 +http://money.163.com/17/1122/17/D3S653PQ002580SM.html +阿里华为等巨头涉足石油生意 马云任正非意欲何为 + + （原标题：阿里、华为等资本巨头涉足石油生意，马云、任正非意欲何为？） + 在各国制定燃油汽车退出时间表的同时，各大互联网巨头纷纷强势进入石油圈，他们意欲何为？2014年，国际油价暴跌，全球能源行业进入“寒冬期”，但这不意味着石油石化行业将一蹶不振。石油石化产品已深入到我们生活中的吃喝住行，其重要地位无法替代。可以确定的是，无利不起早，这些互联网巨头肯定是看好并且相信能源行业未来不会衰落，才积极在能源圈展开布局的。其实，互联网巨头和石油公司合作早已不是什么新鲜事。今天，跟随小编的脚步，让我们看下究竟是哪些互联网巨头插足我们能源圈了。阿里巴巴牵手中国石油今年10月中旬，阿里的第一个无人加油站在杭州开业。这座无人加油站的机械臂将替代加油员加油操作，移动支付替代收银员工作，汽车加油全程没有一个服务员上前服务。事实上，这并非阿里巴巴在能源圈的首次布局。早在2016年3月，中国石油就与阿里巴巴签订了战略合作协议。根据战略框架协议，双方约定将立足互联网平台，深化合作渠道、拓展合作领域、创新合作模式、提升消费体验，共同推动双方业务的转型升级和创新发展。此外，中国石油和阿里巴巴及其关联企业——蚂蚁金服，也将在阿里云、电子地图、互联网汽车、天猫、菜鸟物流以及中国石油掌上营业厅、互联网支付、电子加油卡、互联网金融、会员共享和积分互换、联合营销等领域开展广泛务实合作。华为——能源圈的“老朋友”2011年，华为就开始向石油企业提供一些零散的设备服务。2013年，华为同石油公司的合作逐步升级，不仅为中国石油建成了全亚洲最大的数据中心，还成为了中国石油第一家ICT战略合作伙伴，同时，为中石化、中海油也提供了服务器及网络服务。华为的ICT产品和解决方案当前广泛应用于石油天然气行业的各业务环节，从上游的石油天然气勘探开采、中游的管道运输到下游的配售再到油气企业运营管理，截至目前，华为的ICT产品和解决方案服务于全球TOP20石油企业的60%，业务遍布170多个国家和地区。微软高调进入油服行业2017年8月22日，微软公司高调宣布进入油服行业——与石油界著名油服公司哈里伯顿开展合作，组成战略联盟，拟在油气领域的数字化方面有所作为。以此进入石油行业，推动石油和天然气行业的数字化转型。据境外媒体透露，此次战略联盟名为“数字化石油和天然气工业联盟”。二者具体的合作领域包括：储层描述的深度学习、建模及模拟的应用，为“混合现实(mixedreality)建立特殊领域可视化，建立高度交互应用，促进勘探开发资产的数字化。在当前低油价、市场竞争激烈的形势下，以石化行业下游的加油站为例，以传统加油站销售体系和网络为基础，借助大数据、云计算、车联网、物联网、移动支付等互联网技术手段，打造以“人·车·生活”为内涵的综合服务站；以异业合作、跨界联盟为渠道,建设多方共赢的商业生态圈；实现从油品销售到汽车全生命周期服务转变、从传统加油站经营模式到全渠道资源整合转变、从实体营销到大数据营销转变，能够使营销和管理模式发生革命性变化。从这些合作中不难看出，石油+互联网的时代已经到来。在此形势下，互联网巨头企业进军油气行业且以智能化作为切入点，这对于油气行业的发展无疑是有益的。 +http://money.163.com/17/1122/18/D3S8OVFA00258105.html +刘士余：保持"本领恐慌"意识 加强监管能力建设 + + （原标题：证监会党委举办系统会管干部学习贯彻党的十九大精神第一期专题轮训班） + 刘士余指出，深入学习领会党的十九大精神，首先要明确我们党和国家事业所处的历史方位，即中国特色社会主义进入新时代。要带着感情学、带着使命学、带着责任学、系统全面学、联系实际学，学出一份忠诚，学出一份担当。要强化“四个意识”，坚定“四个自信”，切实增强坚决维护以习近平同志为核心的党中央权威和集中统一领导的政治自觉；深刻认识并自觉运用习近平新时代中国特色社会主义思想武装头脑、指导实践、推进事业；深刻认识中国特色社会主义进入新时代和我国社会主要矛盾的变化对党和国家各项工作的新要求；深刻认识党的十九大描绘的宏伟蓝图，不忘初心，牢记使命，为决胜全面建成小康社会、实现两个一百年奋斗目标不懈奋斗。刘士余要求，全系统各级党委和党组织要切实担负起主体责任，将政治建设放在首位，始终扎实推进全面从严治党。狠抓作风建设，严格落实中央八项规定精神，切实把权力关进制度的笼子。牢牢抓住资本市场的发展机遇，强化改革意识，勇担当、敢作为。各单位党委书记要高度重视干部人才工作，加快推进年轻干部“百人计划”，建设政治过硬、本领高强的监管干部队伍。要保持“本领恐慌”意识，加强监管能力建设，推进监管科技化智能化网络化。要狠抓落实，以钉钉子精神扎实推进证监会系统学习宣传贯彻党的十九大精神不断走向深入。中央党校高度重视证监会系统本期培训班，精心组织安排，科学设计课程，选派权威师资，确保了培训班顺利举办，取得了良好效果。会党委委员、副主席赵争平，会党委委员、主席助理张慎峰参加培训班结业式。 +http://money.163.com/17/1122/21/D3SKG49500258169.html +千亿级混改基金或明年面世 50家混改试点大军来袭 + + （原标题：千亿级混改基金有望明年面世！50家混改试点大军来袭！且看大戏“剧透”） + 临近岁末，央企混改再度迎来新进展——官方透露，有31家国有企业纳入第三批试点范围。加上前两批纳入混改试点的19家企业，50家国企混改试点大军正扑面而来。中国证券报记者获悉，一个规模上千亿元的国家级混改基金目前正在积极筹备中，有望于明年上半年成立。该基金由一两家央企并联合几家其它所有制投资人一起组建。据了解，该基金在LP层面已经形成混合所有制，纯民营资本将作为投资人参与其中，从源头上实现混合所有制，未来将积极参与国企混改。混改基金群加速集结今年以来，各地成立的混改基金如雨后春笋般涌现。11月8日，阳煤集团和梧桐树资本联合出资成立的阳煤产业基金举行签约仪式，标志着山西首只国企发起市场化运作国企混改100亿基金正式成立。近期，深圳市提出，下一步市属国资将积极推进打造以混合型并购基金为牵引，构建天使基金、创投基金、产业基金、并购基金、母基金等涵盖企业发展全生命周期的国资基金群。力争至2020年，市属国资基金群规模超过5000亿元（撬动社会资本比例超过50%）。目前，深圳市属国资基金已超过180只，基金群总规模超过2700亿元，实际投资金额超过1200亿元。今年8月，由国调基金与国富资本共同发起并成立的首只市场化专向国企混改子基金——北京国调混改投资基金在京成立。据了解，国富资本未来还将在深圳、上海、西安打造多个混改子基金，以推动地方混改进程。中国企业研究院执行院长李锦表示，“三批试点企业共计50家，表明混改突破势头已初步形成，下一步将重点推动三批试点任务落地见效，加快形成可复制可推广的制度性经验，推动形成国企混合所有制改革新局面。而各类混改基金的加速集结，将充分利用市场力量，为新一轮国企混改注入活力。”央企混改持续破题作为混改的基本前提，央企公司制改制正进入倒计时。中国铁路总公司据中国铁路总公司11月19日消息，截至11月15日，中国铁路总公司所属18个铁路局均已完成公司制改革工商变更登记，19日正式挂牌，标志着铁路公司制改革取得重要成果。下一步，中国铁路总公司将指导铁路局集团有限公司加快建立适应新体制要求的运行机制，推进资产资本化、股权化、证券化改革。此前，中国铁路总公司党组书记、总经理陆东福主持召开总公司机关月度例会时就表示，指导总公司所属非运输企业加快推进公司制改革工作，条件成熟的要在年底前完成；做好推进国铁企业混合所有制改革、三项制度改革的研究和准备工作，为明年深化改革奠定基础。中国石化管道储运公司根据今年7月国办印发的《中央企业公司制改制工作实施方案》的目标要求，2017年底前国资委监管的中央企业（除金融、文化企业）全部改制为有限责任公司或股份有限公司。李锦表示，“完成公司制改制是混改、资产证券化等一系列改革的前置条件。改制完成后，央企将全面步入公司制时代，将有利于促进企业真正成为市场经济的主体，推进企业建立高效灵活的市场化经营机制。”与此同时，近期，央企混改尤其是石油石化领域混改正进一步发力。中国石油集团电能有限公司中海油中化集团中化集团董事长宁高宁近日表示，正在推进资产上市计划，将在未来3-5年内在所有业务领域引入混合所有制改革和战略投资者。南瑞集团华创证券预计第三批央企试点数目将会从两个维度大幅增加，而油气领域混改或将成为第三批央企混改的重中之重。地方国企入场唱主角北京深圳近期，深圳市属国资全系统混合所有制改革工作方案制定，对系统内法人企业整体混改情况进行摸底梳理，遴选出一般竞争性领域企业，特别是二级以下企业；2018年，全面推进系统混改工作；2019年，基本完成商业类企业的混合所有制改革，做到应改尽改、能混尽混。上海走在改革前列的上海，近期召开的市政府新闻发布会披露的数据显示，上海通过坚持公众公司导向，发展混合所有制经济，截至目前，混合所有制企业占市国资委直接监管企业总户数比重为68.5%。目前，整体上市或核心资产上市企业已占竞争类产业集团总数的三分之二，2014年以来境内外上市16家；员工持股企业累计338家。东北东北证券随着未来几个月包括中央经济工作会议在内的重要会议相继召开，国企改革有望再度被重点提及。目前上海在国企改革领域仍走在全国前列，在政策推进具有充分预期的情形下，可以将上海作为国改主题配置方向上的首选区域。 +http://money.163.com/17/1122/16/D3S2263M00258169.html +证监会主席助理宣昌能：IPO堰塞湖现象基本消除 + + （原标题：证监会主席助理宣昌能在汉表示：IPO堰塞湖现象基本消除） + 宣昌能介绍，2017年以来，IPO企业从发行申请到完成上市，平均审核周期一年3个月左右，较之前需要3年以上的审核周期大幅缩短，直接融资效率显著提升，可预期性增强。据统计，2016年至今年10月底，沪深交易所新增上市公司605家，占沪深交易所全部上市公司3400家的比重为18%，合计融资3400亿元，IPO加速和工资规模均居同期全球前列。IPO常态化发行，为下一步发行股票制度的改革和完善奠定了良好基础。新上市公司的质量充分反映了资本市场服务供给侧结构性改革的成效。新上市公司中，高新技术企业495家，占比达到82%。IPO企业的地区分布亦准确反映了我国经济发展的体量、结构、活力和市场化程度的区域对比。截至10月底，新上市公司的区域分布，前5名为广东、浙江、江苏、上海、北京，存量上市公司和IPO在审企业的地区分布情况基本一致。在上市公司市场化重组方面，2016年到10月底上市公司规模交易4500单，交易金额3.8万亿元，国有上市公司1200单，1.66万亿元，占全市场并购交易总额的44%。高铁等产能过剩行业的上市公司共发生交易重组交易金额2900亿元，通过提高行业集中度，化解行业过剩产能，武钢宝钢合并消减落后产能1600万吨，成为全球第二大钢铁企业。宣昌能指出，资本市场仍然是我国金融体系的一个短板，下一步证监会将紧扣推进供给侧结构性改革主线，着力提高直接融资比重，把好资本市场准入关，进新旧功能转化和转型升级，守住不发生系统性金融危机的底线。一是严把上市公司准入关，严格审核发行人做好信息披露，实现IPO企业线上检查常态化，防止病毒侵入。对信息披露不实甚至有造假嫌疑的企业及时查处，完善发审委员的遴选和管理机制，督促市场各方主体携手提升IPO企业质量。三是以执法协作机制为依托，积极打造协同作战新格局，强化行政与刑事执法衔接配合，建立政监稽查与刑事侦查信息共享、同步推进、分工协作，约束互补的办案模式，及时移送案件线索，积极开展与其他金融监管部门的协作。宣昌能表示，中国证监会将一如既往地支持湖北利用好资本市场促进实体经济发展。第一财经记者注意到，2016年至今年10月底，湖北省共有11家企业完成IPO，融资48亿元，境内外上市公司总数达到119家；20家上市公司实施再融资，融资478亿元；湖北省上市公司完成并购重组124单，交易金额911亿元；交易所债券市场方面，湖北辖区发行债券79支，金额744亿元，发行地方政府债券51期，金额606亿元；新三板挂牌企业达到401家，四板挂牌企业达到3666家，融资额、挂牌数均位居全国前列。截至11月底，湖北全省金融机构存贷款余额分别为5.17万亿元，3.9万亿元，同比增长9.49%和13.75%。截至10月底，长江经济带产业基金已通过基金管理会核准基金28支，总规模1161亿元，已出资基金18支，首期规模492亿元，其中长江引导基金累计出资90.54亿元，储备重点产业项目20多个，总投资3601亿元。 +http://money.163.com/17/1122/06/D3R04ARJ002580S6.html +申万宏源桂浩明：热点风向不定 谨慎操作为上 + + （原标题：热点风向不定 谨慎操作为上） + 在这种情况下，市场出现了无论大盘蓝筹股上涨还是中小市值品种上涨，都存在缺乏后劲的问题。因此，中长线资金只能观望，而短线资金则快速在各个板块中流动。这种谋求短差的操作，不但本身风险很大，也加剧了市场节奏的紊乱，使得行情风向多变。尽管在指标股的努力下，周二上证综指又重返3400点之上，但绝大多数股票下跌，以及大盘蓝筹股也出现较大分化，提示出短线市场缺乏可操作性的特征，指数走高并不能掩盖交易重心下移的现实。由于量能不济、热点风向多变，对大盘而言，现在最需要的是稳定下来，同时在风格上有所协调，而不是急于向上突破。对于普通投资者来说，在一个多方面缺乏确定性的市场，谨慎无疑是最重要的。 +http://money.163.com/17/1122/07/D3R3EPMP0025817I.html +绩优基金“关门谢客” 保排名还是后市堪忧？ + + （原标题：控规模保排名 绩优基金频发“限购令”） + 例如，业绩表现最好的东方红沪港深混合和国泰互联网+股票，今年以来净值涨幅分别为64.95%和64.58%，均暂停了大额申购。基金规模冲刺往往会在四季度上演，那么，上述绩优基金缘何纷纷“关门谢客”？在业内人士看来，“规模恐惧症”、维护业绩稳定以及对于后市预判略显谨慎成为三大主要原因。据了解，基金规模迅速增长成为“限购”的一大原因。上述基金业绩表现抢眼，无论机构还是普通投资者的申购热情均较高，因而导致短期资产规模迅速“膨胀”。统计数据显示，今年以来净值涨幅超过50%的39只偏股型基金，截至三季度末的平均规模为26.7亿元，而“限购”的13只偏股型基金的平均规模则达到了39亿元，所有偏股型基金的平均规模仅为8.66亿元。从上述数据来看，限购的基金确实多数规模偏大，部分基金超过了50亿元，甚至有基金已经超过了100亿元。而“规模往往是业绩的敌人”。据券商测算，偏股型基金中，中等资产规模的基金表现会相对较好。一般而言，资产规模在30亿份至40亿份之间较为合理，基金经理比较容易操作。不过，从“限购”的基金来看，也不全都是大规模的基金。从三季度末的数据来看，也有规模在10亿元以下的基金“限购”，个别基金甚至不足2亿元。业内人士认为，这类基金限购则主要是为了巩固排名的稳定，这类规模较小的基金，一方面底仓配置行业龙头获取稳健的收益，另一方面也能获取一定的打新收益。而由于本来规模较小，一旦出现大额申购，则容易摊薄收益。此外，步入年底，部分白马龙头股高位震荡加剧，虽然基金经理普遍看好中期的“慢牛”行情，但就短期而言，则认为市场不确定性有所增加，且部分白马股或进入过热状态，一些机构开始兑现收益，操作难度将加大。沪上一位基金经理坦言，其掌管的基金不仅进行了“限购”，还进行了分红。在其看来，如果短期规模迅速增加，并不利于基金投资，因为目前来看，“性价比”高的股票较年初已大幅减少。此外，近期市场对于明年的通胀有所担忧，市场波动加大，因此选择分红并兑现部分收益。 +http://money.163.com/17/1122/19/D3SAR6TK002580S6.html +00后CEO回国融资:没钱发工资 否认成另一个贾跃亭 + + （原标题：00后CEO回国融资：没钱发工资， 否认会成另一个贾跃亭） + 河南洛阳少年李昕泽今年17岁，自称中国00后CEO第一人。9月，李昕泽前往俄罗斯读哲学，在此之前要学一年俄语。11月初，李昕泽回国，接受了红星新闻采访。他说，这次回来，是为了拍微电影，故事由他开公司改编。同时，他要见一些投资人和合作伙伴。但在上海见投资人时，他的演示网页被黑客攻陷，会面结束后，他说自己并没有慌张，“说点儿投资人想听的就行了。”李昕泽成立了“崇才科技”，“员工”均为00后。这家公司目前拥有300多人，都分散在一个个崇才的QQ群中，此外还有400多人在编外群随时“待命”。但他没有和任何人签合同，不给任何人开工资，因为“没钱”。李昕泽告诉红星新闻，他们公司有鲜明的高低官职，高层职员现有6人。两年过去，他的公司高层选举已经完成了14次，这些人均是李昕泽提名。李昕泽  红星新闻 图回国见投资人时网站被黑2017年9月，李昕泽卸任崇才科技CEO，并提名了崇才科技新的高层管理者。他要去俄罗斯圣彼得堡国立大学读哲学，最初一年主攻俄语。圣彼得堡的生活单纯、轻松，用李昕泽的话说就是“每天上3小时课，和朋友斗地主，自己做饭吃，上网，睡觉”。他从家里带过去大量冬季衣物，还有俄语教材。李昕泽看俄语网站、读俄语书略费劲，整天泡在国内网站上。虽然卸任了崇才科技CEO，在国内的副总裁张泽昊还是习惯性把公司事务、采访都告诉李昕泽，由他定夺。除了张泽昊，在俄罗斯他很少跟公司其他人接触。回国第一天，可能是时差缘故，李昕泽一时想不起来一些公司重要人物的名字，一边想一边嘀咕：“我怎么连他都给忘了。”一方面，他像一个远程遥控；另一方面，他还是大脑中枢。在圣彼得堡，他坐在月租1000元的小房间，一边喝威士忌，一边想崇才科技的未来。他想联合涉及各个领域的公司组成“崇才生态圈”，自己帮助生态圈的公司揽项目，“大家一起赚钱”。由于有人想邀请李昕泽将自己创办公司的故事拍成微电影，他在11月初回国。期间他告诉认识的媒体人这个消息，还约了一些投资人。11月4日凌晨，李昕泽落地上海，住在预订的酒店。他睡到中午12点，走路时有点儿晃晃悠悠，没有准备电脑和计划书，只身搭乘地铁和投资人见面。那是一个新闻导航项目，他掏出手机打开网页向投资人预演，跳出来的却是两个讽刺他抄袭和负面评论的网站。投资人笑笑点开，说：“还是要做好技术，等修复好还可以谈。”李昕泽并没有觉得羞耻，“事情已经发生，往下接着聊自己公司的理念和文化，说点儿投资人想听的就行了。”李昕泽这样对红星新闻说。那位不愿透露姓名的投资人对红星新闻描述着对李昕泽的印象：“00后算比较有想法的，技术不够硬，但毕竟年纪小，没必要妖魔化年轻人。”对李昕泽的抄袭，他说：“如果他拿的是开放源代码改的也不叫抄袭吧。”最后他总结这个年轻人“把商业环境看得比较简单，缺乏经验，但是如果不放弃未来应该还是可以的”。95后王凯歆发过一条关于李昕泽的微博，说：“比我当年还不靠谱！”王凯歆是1998年生人，高二辍学，创立“神奇百货”。之后，王凯歆融资上千万，却最终失败并招来非议。李昕泽看到后随即转发，配文写道：“毕竟不是谁都是梳个杀马特发型上节目哗众取宠取得融资的，所以说还是大姐牛，炒作这方面我比不了。”再提到两个不足20岁年轻人之间的交锋，李昕泽说：“如果 神奇百货 交给我，我至少能让它活下去。”11月7日，李昕泽和副总裁张泽昊在北京碰面，见了一圈投资者和要建立“崇才生态圈”的合作伙伴。11月12日，李昕泽回到河南洛阳自己的家中。他又想起王凯歆在微博上的言论，凌晨发了微博：“企业嘛，没有什么后悔不后悔的……又回到洛阳了，加油洛阳，加油未来。”李昕泽发的一条微博 微博截图否认会成为另一个贾跃亭李昕泽回顾往事，惊奇地发现“崇才的每次重要节点都是我生日前后”。2014年之前，他在一个叫《巴士模拟》的游戏里做游戏模组供玩家下载。后来，他和另一个玩家Vayk成立“凌海工作室”，对抗高年级玩家的嘲讽。然而，李昕泽不喜欢Vayk的做事风格，“遇到外界说我们东西做得不好就回应，撰文道歉，很软。”他回忆，2014年3月27日，生日前一天，自己“掌权”了工作室。从此，他对于批评“不回应，不道歉”。李昕泽说自己的目标是挣钱，商业化，卖游戏模组，做APP。2014年8月，他将工作室改名“崇才工作室”，意为“崇尚人才”。他开始在经常逛的贴吧发招聘，只找00后，联系上一批对编程感兴趣的同龄人，并将他们加入各个挂有“崇才”字眼的QQ群。2014年10月，李昕泽在母亲的陪同下去北京国家会议中心参加了“COCOS全球开发者大会”。他看到与会者的公司名称都带有“科技”，回来后将公司名改为“崇才科技工作室”。2015年3月27日，他和崇才挣到第一笔钱，也是到目前的唯一一笔。他的大伯将他介绍给当地一家旅游服务公司，为公司开发APP，李昕泽拿到1万左右的奖励。他用这笔钱做了一批奖杯，有三个“2014年最高贡献奖”颁给当时的“公司高层”。2015年4月，他独自一人前往北京参加“全球移动游戏大会”，参加了高端酒会，平生第一次喝酒，并在年级群向暗恋的女生表白。当年全国正掀起创业狂潮。据英国会计及咨询公司UHY International统计，2015年中国每天诞生的新公司多达4000家。李昕泽抓住这个时机，2015年7月，用母亲肖蓓的名字注册了公司“洛阳崇才科技网络有限责任公司”。受母亲做生意的影响，李昕泽从小就知道要赚钱，“做东西不就是要赚钱么？”他学着百度百科公司架构设立了CEO、COO、副总裁以及一系列总监。在总监里面，“国际部总监”、“技术总监”、“学科理事”、“谈判总监”又在所有总监职权之上。能受李昕泽重用的人不多，这些职务多有重合。这些听起来不知所谓的职务，是李昕泽的创新，比如学科理事，类似于总裁助理，谈判总监类似于公关。公司成立后，发布了一系列应用软件，并被人迅速指为抄袭，被李昕泽征用的福厦桌面原作者还因自己作品稚嫩感到羞耻。李昕泽9月在接受红星新闻采访时对此回应：“我们的确借鉴了很多，学习了很多。我们借鉴了他们，发展成自己的产品，这样不好吗？”这次再问这个问题，他依然否认是抄袭，“我还保留着很多他们同意我们可以拿来用的聊天记录”。李昕泽留有的大部分是聊天式的证据，他还没有签过正式的合同。2016年，他甚至找到女子团体Sunshine组合，迅速发了公告说明双方要合作，却因为没有签合同被别人从中间“截胡”。再提及此事，他觉得没人可以否认崇才和Sunshine的合作关系，尽管还没什么实质性的成效。后来，Sunshine女团发生变化，李昕泽说她们没有前途了，“都去好好学习了”。副总裁张泽昊向红星新闻介绍，目前崇才科技有300多人，编外400多人，经常活跃的有100多人，多为技术人员。“除了00后，我们也在招90后，目前正在接触的就是一个90后的人力资源。”他告诉红星新闻。他还向红星新闻透露，目前有一个食品公司还未签约，“但是这次我去北京和他们老总吃饭，问题不大。”离开的员工称他独断专行、盲目自大李昕泽和同龄人有很大不同。Vayk是崇才工作室的创始人，由于受不了他的“独断专行”，六进六出后还是离开。Vayk告诉红星新闻，当年读初三，由于耽误学业便选择退出。对于自己在崇才的那段经历，Vayk不想多提，只说：“现在看来崇才很不成熟。”这家公司刚注册两年多，已经召开了14次选举会议。公司高层一般是上届CEO提名，再经过QQ群投票选出。一开始，一个月一次，李昕泽告诉红星新闻，他为了长期当上CEO，便将选举时间缩短为了一个星期，等过了一段时间，也不提选举的事，这个CEO便悄然做下去了。李昕泽在公司高层讨论组里宣布要做一件事情，大家都在下面回复“同意”。只有一次，谈到选哪首歌做“司（公司）歌”时，出现了分歧。大家觉得《明天会更好》不错，他嫌俗，找了另外一首歌，结果遭到全员反对，于是，“司歌”到现在也没有定下来。李昕泽在网上发了很多关于崇才的帖子，大部分都含有口吻成熟老练的词汇。今年提升为副总裁的张泽昊更熟悉这套术语，但李昕泽嫌他啰嗦，开玩笑说：“去采访张泽昊，你什么都问不出来，他只跟你讲意义。”李一龙也是李昕泽所说的“好好学习去了”中的一人。受李昕泽重用时，李一龙提出要举办一个中国青少年创业大会，Vayk说，“因为大会选址，他俩吵过多次，吵得向我互揭老底。” 为此李一龙离开了崇才，他的微博介绍是“晋城一龙网络技术有限公司总裁”。现在李一龙正备战高考，他说：“我对崇才没有印象，只对李昕泽有印象。”提起李昕泽，李一龙用了“自大、盲目、没真才华、善于利用他人、不愿承担”等词汇来形容。11月4日傍晚，17岁的李昕泽挤进高峰期的上海地铁，衣服后背印着林则徐的两句诗：“苟利国家生死以，岂因祸福避趋之。” +http://money.163.com/17/1122/17/D3S4DQ1O0025816E.html +现金贷整治潮来临 无牌照公司仅剩P2P方式经营 +在中概网贷股方面，美东时间11月21日，趣店(NYSE:QD)收盘报收于19.31美元/股，下跌3.83%。受互联网小贷牌照被紧急叫停、数据疑似遭内鬼外泄以及美国律师事务所Faruqi & Faruqi对其发起调查等消息的影响，趣店21日盘前跌幅超35%。临近盘前时，趣店宣布将在未来12个月内回购不超过1亿美元的A类普通股ADS（美国存托股份），受此消息影响，趣店跌幅大幅收窄。根据股票回购计划，该计划将于2018年11月20终止，“并可由本公司董事会随时修改，暂停或终止。”购回将由趣店现有现金及现金等价物或经营活动所提供的未来现金提供资金。截至2017年9月30日，趣店期内现金及现金等价物约为人民币14.83亿元（约2.23亿美元）。罗敏表示，该次回购计划体现了董事会对未来的信心。互联网小贷牌照在11月21日被紧急叫停被视作整治现金贷的开始，财新消息指出有网络小贷牌照的200多家企业也将重新审核规范，没有牌照的网贷平台要着手取缔。在整治期间，监管或将要求银行暂停与现有现金贷公司合作，“助贷”模式被叫停。此外，《21世纪经济报道》消息指出，央行及银监会将召集多地金融办负责人召开会议，主题包含网络小额贷款整顿。事实上，今年上半年互金的专项整治已经将现金贷纳入。2017年4月10日，银监会发布了《关于银行业风险防控工作的指导意见》。《意见》除了要求重点做好校园网贷的清理整顿工作外，还首次提出做好“现金贷”业务活动的清理整顿工作”。要求“确保出借人资金来源合法，禁止欺诈、虚假宣传。严格执行最高人民法院关于民间借贷利率的有关规定，不得违法高利放贷及暴力催收。”也是在此时，面对监管意见，趣店对所有信用产品的价格进行了调整，以确保所有信贷额度下的年化费率不超过36％。石鹏峰解释说，目前现金贷业务的经营形式主要有网络小贷公司、消费金融公司、银行、P2P和其他。而目前存在严重合规问题的是其他类的相对较多。“简单来说就是既没有放贷资质，又没有以信息中介的方式按照P2P平台的监管要求运营。”他进一步分析说，将现金贷纳入互金的专项整治后，对于现金贷相关工作重点应该会在突破利率上限、不合理收费变相太高利率、暴力催收等，以及非持牌机构是否经营放贷业务。“对当前没有拿到牌照的现金贷主要的合规路径将只有通过P2P的形式，按照P2P的监管要求进行，否则很可能将在短期内被取缔。”（网易财经 马莉bjmali1@corp.netease.com） +http://money.163.com/17/1122/15/D3RU3C9Q002580SK.html +特斯拉通知用户确认Model 3订单 预计4周内交付 + + （原标题：特斯拉通知外部用户确认Model 3订单 预计4周内交付） + 从外部用户提供的邮件来看，特斯拉以邮件的方式通知外部预订者，让他们选择颜色、轮胎和其他配置，支付剩余款项以确定订单。已收到特斯拉确认订单邮件的外部用户预计，确定之后的Model 3将在4个周的时间里交付，这也就意味着部分幸运的外部用户会在圣诞节之前收到期待已久的特斯拉Model 3。Model 3是特斯拉在2016年3月底推出的首款廉价电动汽车，续航里程超过350公里，但售价仅3.5万美元，因而自发布以来就备受关注，已有超过45万人预订，并交付了1000美元的订金。在经过一年多的等待之后，首批30辆特斯拉Model 3在今年7月28日交付用户，但由于其遭遇产能瓶劲，三季度仅生产了260辆，远低于1500辆的预期，实际交付用户的则只有220辆。虽然目前已有数百辆Model 3交付给用户，但已经收到Model 3的用户，不是特斯拉员工就是与特斯拉关系密切的人士，已经预订的外部用户尚未收到。（辣椒客） +http://money.163.com/17/1122/23/D3SP2DQ3002581PP.html +诺奖得主舒尔斯谈中国经济:应让国有企业收缩信用 +舒尔斯指出，若假设容许中国国内的投资人能够投资海外，放松QDII海外投资的规模，让国内的投资人能有投资海外的渠道或者接触海外投资产品的机会的话，可能才会对中国的金融市场产生真正的重大的影响。今天，舒尔斯是在深圳高等金融研究院和资本市场学院举办的名师讲堂上发表上述观点的，除此之外，他还发表了以 “投资管理的演进：约束的成本（The Evolution of Investment Management: The costs of constraints）”为主题的演讲。据了解，迈伦?舒尔斯教授是美国著名经济学家，1997年诺贝尔经济学奖得主，曾提出布莱克-舒尔斯期权定价公式——一种为期权或权证等金融衍生工具定价的数学模型，这一模型扩大了期权定价模型的应用范围，为企业新型债务及交易证券如保险合约进行定价提供了新方法，该计算法已成为金融机构涉及金融新产品定价的指引方法。（网易财经 张艳gzzhangyan@corp.netease.com） +http://money.163.com/17/1122/23/D3SOSK49002581PP.html +习近平等通过各种形式对萧灼基先生逝世表示哀悼 + + （原标题：习近平等通过各种形式对萧灼基先生逝世表示哀悼） + 社会各界人士送别萧灼基先生来源：北京大学经济学院2017年11月20日上午，著名经济学家，第九届全国政协委员，第十届全国政协常委、社会和法制委员会副主任，中国民主建国会会员，第六、七届中国民主建国会常务委员、特别顾问、民建经济委员会主任，北京大学经济学院教授萧灼基先生的遗体告别仪式在北京八宝山革命公墓大礼堂举行。萧灼基先生因病医治无效，于2017年11月14日23点34分在北京逝世，享年84岁。萧灼基先生逝世后，习近平、李克强、张德江、俞正声、张高丽、栗战书、汪洋、王晨、刘延东、李源潮、陈希、胡锦涛、朱镕基、温家宝、李岚清、李长春、吴官正、尤权、杜青林、陈昌智、马培华、王刚、王光英、张榕明等通过各种形式对萧灼基先生逝世表示哀悼并向其亲属表示深切慰问。萧灼基先生病重期间，李克强、赵乐际、李源潮、温家宝、贾庆林等对他的病情十分关心。萧灼基先生生前的同事、学生、好友，社会各界仰慕萧灼基先生的人士，以及家乡代表400余人前来送别。萧灼基先生生平北京大学经济学院教授，全国政协第九届委员会委员、经济委员会委员，全国政协第十届委员会委员、常务委员、社会和法制委员会副主任委员，中国民主建国会会员，第六、七届中国民主建国会常务委员、特别顾问、民建经济委员会主任，北京市场经济研究所所长，我国著名经济学家萧灼基先生因病医治无效，于2017年11月14日23点34分在北京去世，享年84岁。萧灼基先生1933年12月出生于广东省汕头市潮阳区一个文化氛围浓厚的家庭，从小天资聪颖，勤奋好学，成绩优秀。先后就读于汕头聿怀中学、联合中学和第一中学。萧灼基年少时就树立了“追求知识、强国富民”的理想，当解放战争的炮火燃到这个南疆小镇时，他已经能够用通俗的语言向劳苦大众宣讲马列主义常识。在中学读书期间，他担任联合中学和第一中学学生会主席、汕头市学生联合会宣传部长、学联主席。1950年3月，年仅16岁的青年萧灼基当选为汕头市第一届人民代表大会代表。毕业后，萧灼基先生来到北京大学经济系任教。自参加工作到“文化大革命”结束，任助教长达20年。他始终追求真理，坚守信仰，身处逆境也不放弃教书育人的初心。1979年6月晋升为讲师，1980年12月晋升为副教授，1985年9月晋升为教授。1986年被国务院学位委员会批准为全国第一批博士生导师， 1992年起享受国务院有突出贡献特殊津贴。数十年来，萧灼基先生一直躬耕于燕园，著籍立说，教书育人。为北京大学争得了荣光，为中国经济学界赢得了自豪。萧灼基先生为马克思主义经济学的发展做出了特殊贡献。早在1956年，萧灼基先生就立下两个宏愿：一是要通读《马恩全集》，二是要自己写作《马克思传》和《恩格斯传》。2008年，萧灼基先生出版了倾注其毕生心血的学术巨著《马克思传》，并再版了他1985年出版的《恩格斯传》。这是中国学者首次在此领域的成功探索，同时也是中国社会科学研究领域的重大突破。由一人独立完成两大革命导师的单独个人学术传记，这在世界马克思主义研究史上具有里程碑的意义。萧灼基先生对马克思主义的研究既是矢志不渝的，也是与时俱进的。他在《马克思传》再版序言中写道：“很长一段时间以来，人们普遍认为马克思的经济理论已经过时了。但是，随着美国‘次贷危机’的全面爆发，马克思的《资本论》在西方发达国家又骤然热销。实践再次证明，150年前的马克思主义经济理论仍然具有不朽的价值。”在数十年的教学研究工作中，萧灼基先生始终坚持用马克思主义的立场、观点和方法研究发展变革中的经济社会问题。无论学术风气如何变化，从未动摇。萧灼基先生为改革开放做出了前瞻性的理论贡献。他拥护改革开放，积极投身时代洪流、贡献才智和力量，是我国最早研究和主张商品经济、市场经济的专家之一，堪称市场经济理论的主要旗手。1981年，萧灼基先生在《北京大学学报》上发表的《关于改革经济管理体制的若干设想》一文中，首次提出并系统论证了国有企业所有权和使用权（经营权）“两权分离”的改革设想，为推动国企改革提供了重要理论指导，并因此获得1984年颁发的首届孙冶方经济科学奖。他的“价格运行弹性论”、“公有制与市场经济兼容论”、“证券市场与社会主义适应论”等理论在学术界和经济实践中产生了重大影响。他极富学术勇气地提出“重新认识社会主义”，指出“生产资料所有制是经济体制改革的关键”、“在商品经济下要率先强化市场经济作用”等观点，如大海潮音，振聋发聩，为改革开放做出了前瞻性的理论贡献。萧灼基先生为市场经济与资本市场的发展做出了重要理论贡献。他是新中国成立后最早研究股份制经济和证券市场的专家之一，主编了国内首批介绍股份制经济的著作《股份经济学》和迄今为止关于证券市场最全面系统的权威性工具书《中国证券全书》，为资本市场的发展奠定了坚实的基础。他对中国证券市场的研究鞭辟入里，对股市的真知灼见令众多海内外学者叹服，被誉为“萧股市”；他长期研究宏观经济问题，对经济发展形势见解独到，被称为“燕园里的中国经济预测家”。1999年，萧灼基先生在政协九届二次大会《关于金融发展与金融安全的若干建议》发言中明确指出，金融发展要放在首位，不发展是最大的不安全。这次发言为深处困境的中国资本市场指出了方向。萧灼基先生为我国经济领域人才培养和学术繁荣做出了不可磨灭的贡献。从教五十余年来，他始终热爱党和国家的教育事业，在经济金融领域辛勤耕耘，教书育人，桃李遍布天下。他思想开明，坚持“真理无国界，科学无禁区，探索无止境，争鸣无尊卑”，认为创新是研究的灵魂，鼓励学生独立思考并勇于提出新的理论和观点。他一身正气，“从政为官要清廉，下海经商要守法，科学研究要创新，待人做事要真诚”的毕业赠言，成为历届学生铭记遵循的行为规范。他对学生的成长与发展倾注了无限的热情与心血，春风化雨，金针度人，提携后进，深受广大学生爱戴。他所培养和指导的许多学生在政、产、学、研各界都有突出表现，成为改革开放和经济建设各条战线的栋梁之才。萧灼基先生是知名的社会活动家。萧灼基先生担任第九届全国政协委员、经济委员会委员，第十届全国政协常委，全国政协社会和法制委员会副主任委员，第六、七届中国民主建国会常务委员、特别顾问，民建经济委员会主任，第五届北京市海淀区政协副主席，北京、吉林、云南以及武汉、成都、汕头等省市政府顾问或咨询委员，中国国际贸易促进委员会特聘顾问，《经济界》杂志社社长、主编、名誉主编等职务。他身体力行“经济学家必须贴近实践”的诺言，常年带领学生深入农村、工厂、科研单位等生产劳动一线考察，与当地工人、群众、领导干部交流意见。1992年10月，萧灼基作为大陆首位访问台湾的经济学教授，迈出了两岸经济学术交流破冰之旅的第一步，在社会上引起巨大反响。“学之大者，为国为民”。萧灼基先生心系家国天下，是我国优秀知识分子的代表。他秉承“经世济民”的北大经院百年传统，抱有对党、国家和人民的赤子情怀，“先天下之忧而忧，后天下之乐而乐”，心系家国，鞠躬尽瘁。在参与政协工作之后，他的历次提案、大会发言等论述对关键政策的出台和深化改革都起到了有力的推动作用。2003年政协第十届一次会议上，萧灼基先生发表了题为《加大财政支农力度提高农民收入水平》的发言，提出大幅减免农业税，免费供应农村初中和小学生教科书、练习本和其他文化体育用品。三年之后，在中国延续了千年的农业税被废除，得到了亿万人民群众的高度赞誉。即使在病重期间，萧灼基先生仍然关心学科建设和改革发展，针对金融安全、金融体制改革、新兴产业战略等问题继续建言献策。拳拳之心，可昭天地。萧灼基先生自称“三书主义”者：“读书、教书、写书是我的人生经历，我通过一生的努力把每一件事做好！”五十余年的教书育人，萧灼基先生著作等身，成果丰硕。他出版《中国经济建设与经济体制改革》、《重新认识社会主义》、《萧灼基选集》、《纵论股金》、《社会主义宏观经济研究》等数十部著作；在《北京大学学报》、《经济研究》、《经济科学》、《人民日报》、《联合早报》等国内外报刊发表论文数百篇。荣获数十个奖项：包括“国家有突出贡献专家”、“孙冶方经济科学奖”、“陈岱孙经济学著作奖”、“中国企业改革与发展‘金三角’奖”、“全国十大财经英才奖”、“北京市优秀学术报告一等奖”、“北京大学优秀教学奖”、“北京大学优秀社会科学著作奖”、“北京大学优秀博士论文指导奖”、“北京大学改革开放30周年百项精品奖”、“改革开放30周年60位经济人物奖”、“影响新中国60年经济建设的100位经济学家”、“中国证券市场20年最具影响力人物奖”、“中国出版政府奖”、“北京大学终身教书育人奖”等。虽有诸多荣耀接踵而至，但在萧灼基先生看来，最重要的却是：“有是非之辨，坚持真理，理论创新；无名利之争，淡泊人生，爱学生、爱朋友、爱亲人。”无论面对人生中的挫折还是辉煌，他都豁达淡然，胸怀坦荡。他是学术大师，改革的理论先锋，杰出的马克思主义理论大家和教育家；他是妻子眼里的好丈夫，儿女心中的好父亲，学生们永远的好师长。萧灼基先生离开了我们，这是北京大学的重大损失，是中国经济学界的重大损失，也是中国特色社会主义理论领域的沉重损失。先生之风，浩浩汤汤，欲报之德，昊天罔极。萧灼基先生千古！ +http://money.163.com/17/1122/22/D3SMGHPJ002580T4.html +百度"阵亡全家桶"：巨头养的儿子也难活啊 + + （原标题：百度"阵亡全家桶"：巨头养的儿子，也难活啊） + 文/秦予百度正在改变。它的路线变化，正直观映射到了它的产品上。“All in AI”和宣布回到“内容分发”业务一年后，百度在feed流上的广告营收开始逐渐逼近今日头条，日前，百度又推出了“熊掌号”。爱奇艺要用AI打造“大娱乐生态场”的同时，百度新的短视频App“好看视频”亮相。百度也开始涉足智能硬件产品。2017百度世界大会上，百度新推出的渡鸦智能音箱Raven H，因为亮眼的颜值和1699元的售价在朋友圈里刷了屏。而过重的品牌意识和对百度搜索数据与流量的依赖，也许正是它们失败的主因。创业家& i黑马在这些年百度“做死”的产品里挑选了一些有代表性的案例，也许能够通过它们的命运，让我们窥见百度产品路线的发展轨迹。1、百度空间诞生日期：2006年结果：2015年4月关闭失败主因：新浪微博与QQ空间的步步紧逼2006年正值百度产品的巅峰时代，百度空间就诞生于此时，背靠着百度搜索这个爸爸，百度空间的发展势头很猛，3年就成为了国内最大的SNS社区平台之一。然而，在强社交属性的QQ空间和迅速走红的新浪微博的夹击下，腹背受敌的百度空间匆忙走了一步臭棋——强制升级轻博客，然而新产品的体验不尽人意，这也加速了百度空间的衰亡。2015年4月7日，挣扎了6年的百度空间宣布关闭，并从4月21日起停止让用户编撰更新博文，百度空间的内容也于2015年5月7日正式迁移到百度云。2、百度有啊诞生日期：2008年10月结果：2011年3月关闭，商城业务转移给乐酷天失败主因：“打败淘宝的不会是第二个淘宝”2007年10月，百度认为基于搜索引擎的电商才是大趋势，于是成立电商事业部，在2008年10月高调推出对标淘宝的C2C电商平台“百度有啊”，甚至放言“三年内打败淘宝”。3、乐酷天诞生日期：2010年1月结果：2012年4月关闭失败主因：“外来户”水土不服，百度也依然不懂流量转化有啊中后期的惨淡经营让百度决定放弃纯粹模仿的C2C模式，转而拥抱B2C。2010年1月，百度与日本第一大电商乐天合资创立B2C电商平台“乐酷天”，持股比例为49：51，百度负责入口和流量，乐天则主要做运营。4、百度Hi诞生日期：2008年结果：目前仅有百度内部员工办公使用失败主因：体验还不如QQ，就不要打即时通讯的主意5、百度说吧诞生日期：2010年9月结果：2011年8月关闭失败主因：强制实名社交，这么做问过中国网民吗？这实在不符合当时绝大多数网民的习惯，用户增长数据一直很难看。意识到不该“逆用户习惯”的百度在2011年4月推出新版，最重要的改变就是让用户可以选择是否实名认证。可惜，这一改变似乎来得太迟，后续的用户增长并没有突破，加之百度内部对该产品的推广宣传也不上心，最后百度说吧于2011年8月宣布关闭，惨淡的结局也让它成为许多人眼中“微博大战中第一个失败者”。6、百度云OS诞生日期：2012年6月结果：2015年3月宣布停止更新失败主因：选择“队友”的失误根据刷机精灵发布的一份2014年手机刷机行业的数据报告，2014年的百度云OS曾在第三方ROM资源排行榜中超过MIUI、乐蛙等，排名第二。在2013年，百度战略投资深圳百分之百公司。在该交易中，百度以云OS资产加现金的方式投资了百分之百，随后，百度云OS一直由百分之百运营，并支持百分之百的百加手机。2015年3月，上线1000多天后，百度云OS和自己的千万用户道别，宣布停止更新。对此，百分之百创始人徐国祥给出的解释是百分之百在进行新的融资，因此停止了对云OS业务的投入。而百度的心里，想必也是无奈的。7、百度游戏诞生日期：2014年4月结果：2017年1月被第三方收购失败主因：并不想做好游戏内容研发，凭什么打破游戏江湖的垄断？遗憾的是，在持续的高层人事动荡、内部腐败中，原本有过优秀发行作品的的福州团队核心成员（创业家&i黑马注:原91游戏）陆续离职。 2016年3月，百度移动游戏宣布战略升级为“百度游戏”，同时裁撤了福州分公司运营团队。升级后百度游戏依然不重视游戏内容的研发，而是希望借助渠道优势做代运营和游戏分发，而此时游戏行业也已形成腾讯、网易两巨头的格局。自此，百度游戏逐渐边缘化，并于2017年1月仅仅以12亿元人民币的价格被“贱卖”。至于4年前斥巨资收购的91无线，目前已经没有任何实质业务。8、百度mall诞生日期：2015年11月结果：无声地消失失败主因：百度做电商，三而竭百度mall最后消失得无声无息。虽然接连在电商领域折戟，但百度做电商的心依然没死，只是在2015年11月上线百度mall的时候显得低调许多。与前两次不同，此次百度mall定位于中高端品质电商，只和品牌官方直接合作，面向25-40岁的中产阶级，颇有些“消费升级”的意味。9、百度医生（百度医疗）诞生日期：2015年1月结果：2017年4月关停失败主因：“KPI文化”遭遇“慢”医疗百度血友吧被卖、魏则西事件让百度医疗相关业务臭名昭著，但其实这些都与百度医生无关。百度医生是一个医患双选平台，是2015年1月8日百度医疗事业部成立后开始重点打造的一款产品，希望从“预约挂号”切入医疗服务。2017年4月1日，百度医生正式被关停，医疗事业部也在同一时间遭裁撤。10、百度外卖诞生日期：2014年5月结果：2017年8月被饿了么收购失败主因：O2O是场恶战2017年8月24日，昔日的对手饿了么正式宣布收购百度外卖，作价为42亿元（创业家&i黑马注:由百度2017Q3季度财报“其他收入”一栏推算）。合并完成后，百度外卖成为饿了么的全资子公司。日前，饿了么召开双方合并后的战略发布会，公布融合进展，并且表示，合并18个月后，“百度外卖”这个名字将被新的品牌名代替。在不同的领域，百度基于自身的搜索流量，经历了一次次产品变现的尝试和失败。而“错过了移动互联网时代”之后，百度却成为国内最先布局人工智能的互联网巨头，并且，在现在的产品战略中，百度开始了立足AI的产品和商业化的布局。对于百度而言，这是否是一个新的产品时代的开启？还值得我们期待。 +http://money.163.com/17/1122/22/D3SLUOKR00258169.html +三会高层今天集体发言：从直接融资到穿透式监管 + + （原标题：三会高层今天集体发言，从直接融资到穿透式监管…重点关注这些话题） + 图片来源：东方IC1、中央财经领导小组办公室副主任杨伟民：新时代仍要坚定不移地把发展作为党执政兴国的第一要务，但衡量标准将先看质量，再看速度；下一步要通过完善产权制度实现产权的有效激励。2、银监会国有重点金融机构监事会主席于学军：长期以来中国金融管理中的最大问题是管不住货币，这是中国所有金融问题的重要根源；中国金融业改革的目标和愿景是建立严格、有效的货币管理体制，整个金融体系要进一步市场化、国际化，金融的监管职责定位更加准确、清晰，加强监管的有效性，并且分工更加明确，协调更加有力，真正能够覆盖金融业面临的所有风险。以下是根据讨论会内容整理的发言要点：杨伟民：经济体制改革新部署有三个亮点中央财经领导小组办公室副主任杨伟民表示，关于经济发展的新部署，最重要的是两点，即高质量发展阶段和建设现代化经济体系。高质量发展阶段是对我国经济发展实际的准确判断；建设现代化经济体系是我国发展的战略目标。“国家的现代化首先要实现经济的现代化，经济的现代化必须要有现代化的经济体系。”杨伟明进一步指出，关于经济体制改革的新部署有三个亮点值得关注：首先，十九大报告在14条基本方略中将十八届三中全会提出的“使市场在资源配置中起决定性作用和更好发挥”作用，将“和”改为了逗号。他认为，这本身就是一个重大的改革，是一项比改革方案还要重要的重大改革，进一步宣示了我们党坚持社会主义市场经济改革方向的决心和立场，对今后的经济体制改革将带来长远的、深刻的影响。其次，党的十九大提出经济体制改革必须以完善产权制度和要素市场化配置为重点。十八届三中全会以来，经济体制改革取得了不少突破性的进展，但产权制度和要素市场化配置这两个重点还有待攻破，下一步要通过完善产权制度、实现产权有效激励。于学军：中国金融管理的最大问题是管不住货币银监会国有重点金融机构监事会主席于学军表示，长期以来中国金融管理中的最大问题，实际上是管不住货币。这是中国所有金融问题的重要根源。这不仅是中国金融业长期稳健发展和防范风险的重要课题，而且也是金融业改革绕不过去的一道难题。于学军表示，2015年之后，随着地方政府＂债务置换＂、＂重点建设基金＂、棚户区改造、扶贫等刺激性政策的持续出台，全国各地又掀起了新一轮组建政府融资平台的高潮，致使债务总额进一步巨额膨胀。而且，后一轮的债务规模更大，期限大幅拉长，结构也更复杂；又有商业银行等金融机构层层嵌套、相互交叉持有。这对金融机构的流动性管理带来严重挑战，倒逼货币管理不断加大流动性投放。针对 “僵尸企业”，于学军表示，其根本原因在于我国资金供应长期太过松驰，在这些企业缺乏市场核心竞争力的情况下仍然源源不断地过度堆积，背后则与中国现行经济管理体制以及金融管理体制相关联。对于近年来被热议的＂债转股＂，于学军认为，＂僵尸企业＂出现资金链断裂，就去搞＂债转股＂，将银行过去的贷款变成股权。银行将债权变成股权，短期信贷变成了长期持有，企业的流动性问题暂时解决了，却把这个难题转给了银行，企业的流动性问题变成银行的流动性问题。这样的情况发展下去，一定会对银行形成倒逼机制，银行反过来又会倒逼中央银行进行流动性投放。对于中国金融业改革的目标和愿景，于学军提出了三点：第一，建立严格、有效的货币管理体制。第二，整个金融体系或者金融业要进一步市场化、国际化，并以此提高我国金融配置资源的效率。第三，金融的监管职责定位更加准确、清晰，加强监管的有效性，并且分工更加明确，协调更加有力，真正能够覆盖金融业面临的所有风险。保监会副主席黄洪：社会主要矛盾变化是做好保险工作的重要逻辑主线保监会副主席黄洪表示，从我国的保险供给看，不平衡、不充分的问题仍然十分突出，深刻把握我国社会主要矛盾变化对保险业的影响以及在保险业的体现，是做好保险工作的一条重要逻辑主线。黄洪强调，要保障人民群众的美好生活，解决不平衡、不充分的保险供给与人民群众日益迸发、不断升级的保险需求之间的矛盾，保险供给和服务必须有大的飞跃。“保险行业存在很多为人诟病问题的重要原因，就是背离了行业为人民群众提供安全感、获得感和幸福感的要求。‘黄洪说，为此，他提出：首先，保险产品服务要能够给消费者带来安全感。其次，提升消费者的获得感是第一位。再者，给消费者带来幸福感是具体要求。“无保险监管的监管理念、资源配置、保险行业的产品设计、保险服务，保险公司的经营愿景、战略规划、管理流程，都要和这一点紧密结合。”黄洪还特别说到，这几年保险行业规模、实力和影响都上去了，但从业人员工作的自豪感和满足感却有所减退。保险行业在方向理念等方面出现了偏差，一定程度上冲淡了保险业理想主义的色彩，让这个本应是崇高的行业变得不是那么崇高，甚至给经济金融发展带来了一些负面影响。对此，黄洪表示，中国特色社会主义进入了新时代，这是我国发展新的历史方位，更是保险业发展新的历史方位。他呼吁保险人，不忘初心、永存爱心、常怀敬畏之心。他提出三点要求：一是重塑行业理念，把以人民为中心作为保险业的根本追求。把人民群众需不需要、满不满意、获不获益、喜不喜欢作为检验保险业发展成果的根本标准。二是重塑保险监管，守住不发生系统性金融风险的底线。从监管的定位看，要处理好发展和监管的关系，制定科学的游戏规则，营造公平的竞争环境，防止“市场失灵”和重大风险积累；从监管的资源配置看，要把监管资源向发现风险、防范风险、处置风险倾斜；向风险监管、法人机构监管、重大风险处置等领域倾斜；此外，要大力加强保险监管科技建设，应对和把握新技术给金融保险业带来的新变化；从监管的实践看，要敢于作出不同于市场的独立判断，敢于质疑，能够说“不”，拒绝监管上的“父爱主义”，提高依法监管的能力。三是重塑行业形象，建设国家和人民可信赖、可托付的保险业。这几年，金融大鳄在保险业兴风作浪，保险乱象也相当程度地存在，极大地破坏了党和人民对保险业的信任。保险业和保险监管要消除这些负面影响，保险业要围绕保障人民美好生活这个核心、服务实体经济这条主线、让保险业再次崇高这个信念，发挥好保险的经济“减震器”和社会“稳定器”功能。张慎峰：着力推进资本市场更加高质量、高效发展证监会主席助理张慎峰从大力发展直接融资、进一步扎实推进基础制度改革、强化依法全面从严监管、防范风险和健全多层次资本市场体系等方面着力推进资本市场更加高质量、高效发展，他介绍了证监会的下一步工作计划。第一，大力发展直接融资，进一步完备资本市场融资功能，切实提升服务实体经济和国家战略的能力。张慎峰表示，证监会将更加全面的贯彻新发展理念，积极服务供给侧结构性改革，加快建设创新型国家以及乡村振兴、区域协调发展的战略。积极发展多层次股权市场和债券市场，增强资本市场投融资功能的发挥。同时，要引导行业机构更加注重以客户需求为导向，以服务创造价值，专注主业，做精专业，更好的满足居民多样化财富管理的需求，提升对中小投资者的服务能力。第二，推进资本市场四梁八柱的改革，进一步扎实基础制度。第三，强化依法全面从严监管，逐步实现市场监管有效。张慎峰表示，证监会将继续强化依法全面从严监管，健全以监管会员交易为中心的交易行为监管模式，健全穿透式监管机制，防止监管套利，打好专项执法行动与常规执法案件查办的组合拳，强化稽查执法处罚力度，坚决打击各类违法行为，真正使市场的生态好起来，逐步实现市场监管有效的目标。第四，贯彻以人民为中心的发展思想，把防范化解风险放在更加重要的位置，确保投资者合法利益得到很好保护。第五，健全多层次资本市场体系，进一步拓展资本市场服务的覆盖面。张慎峰表示，证监会将积极拓展多层次、多元化、互补型股权融资渠道，继续扩大交易所市场，持续深化新三板改革，持续完善创业投资基金的差异化监管安排，继续推进债券市场品种创新，有序扩大交易所债券市场融资规模，引导期货市场健康发展，深化期货市场价格发现、风险管理、服务宏观决策等功能。交易所将深化“保险+期货”试点期货市场在稳定和促进农民增收方面发挥着重要作用，近年来，我国期货市场在“保险+期货”试点方面进行了有益探索，主要期货交易所均表示要对此加大推进力度，拓宽金融服务实体经济尤其是农产品的路径。大连商品交易所在服务三农方面也进行了积极的探索。大连商品交易所副总经理朱丽红介绍，今年大商所“保险+期货”试点项目亮点频出，参与试点机构开始尝试“收入险”，对农民的保障力度更强；引入大型企业集团，探索打通粮食销售渠道；引入商业银行，依托“保险+期货”向有融资需求的农户发放贷款；另外地方政府支持力度明显加大，为财政资金进入探索了路径。另外，朱丽红透露，接下来大商所将推出一个涵盖“保险+期货”、场外期权、基差贸易等多种形式，期货经纪公司、保险公司、银行等金融机构共同参与的、综合性的农民种粮收入保障计划。中国金融期货交易所副总经理张晓刚表示，当前，我国实体经济与金融市场存在巨大的风险管理需求，金融期货市场的发展相对来说仍不平衡、不充分。下一步中金所将坚持服务实体经济的宗旨，按照“品种丰富、功能齐全、交易适度、运行规范”的原则，基于实体经济和现货市场风险管理需求，进一步研究上市新的金融期货品种；以功能发挥为导向，进一步优化业务规则，提升市场运行效率，促进合理交易规模，增强市场服务能力；进一步提升监管效能，加大违法违规打击力度，建设一个更加规范高效的风险管理市场，助力现代金融体系发展。 +http://money.163.com/17/1122/22/D3SLKLHR00258169.html +乐视网复牌仍无明确时间 逾30亿融资盘严重套牢 + +http://money.163.com/17/1122/21/D3SJRTPE00258169.html +安邦或将减持民生、招行 三季报持股均超10% + + （原标题：安邦或将减持民生、招行 三季报持股均超10%） + 知情人士称，为减少对市场的影响，监管当局建议安邦集团通过非公开方式退出或减持。监管当局正在帮助安邦寻找合适的股权接盘方。11月16日，银监会公布《商业银行股权管理暂行办法(征求意见稿)》(下简称：《办法》)第十三条中明确指出：“同一投资人及其关联方、一致行动人作为主要股东入股商业银行的数量不得超过2家，或控制商业银行的数量不得超过1家”。同时，该《办法》也对主要股东作出定义，即持有商业银行股份总额百分之五以上或持有股份总额不足百分之五但对商业银行经营管理有重大影响的股东。不难看出，上述两条新规条例对“安邦系”入股银行的股份划下了监管红线。经财联社不完全统计，截至2017年9月30日，安邦集团通过旗下多个子公司、保险产品等投资组合形式共计持股民生银行19.20%，持股招商银行13.11%。另外，截至2016年12月31日，安邦财产保险还持有成都农商行35%的股权，为该行第一大股东。而值得注意的是，今年2月份，民生银行第七届董事会换届完成，银监会对相关股东的董事资格给予批复，但安邦副总裁姚大锋的董事资格仍未获批。3月7日，银监会副主席曹宇表示，安邦在民生银行的股东资格尚在审核中，“今年是否能有结果实在不好预测”。此外，公开信息显示，安邦目前在境外除成功收购比利时劳埃德银行100%股权之外，旗下韩国东洋人寿还竞购韩国友利银行4%的股权。（财联社记者 王涵 尹哲） +http://money.163.com/17/1122/21/D3SIT54K00258169.html +中信建投:安邦集团所持民生和招行股权将安全落地 + + （原标题：安邦持民生和招行股权将安全落地） + 事件简评市场对安邦系持招行和民生股权有担忧根据之前银监会发布的《商业银行股权管理暂行办法（征求意见稿）》，同一投资人及其关联方、一致行动人作为主要股东入股商业银行的数量不得超过2家，或控制商业银行的数量不得超过1家。该《办法》也对主要股东作出定义，即持有商业银行股份总额百分之五以上或持有股份总额不足百分之五但对商业银行经营管理有重大影响的股东。上述两条新规条例对“安邦系”入股银行的股份划下了监管红线。事实上，今年上半年，安邦集团已相继退出工行、建行、农行前十大股东之列。但对安邦持民生和招行有担忧，因为持股比例高。股权处理办法落地，利好银行股。监管层意图降低金融系统风险，引导对银行股的长期价值投资从银行股权管理办法的出台来看，监管层的意图一方面是降低金融风险同业传染的可能性，另外一方面是引导资金对银行长期价值的投资。此次安邦以非公开方式退出为主，由监管当局帮忙寻找接盘方，在一定程度上能够减少对二级市场的冲击。我们认为可能的接盘侠是其他未触及监管红线的保险公司，也有可能是更看重长期投资价值的战略投资者，后者可能性更大。总体来看，我们认为如果报道属实，影响更偏正面，中长期有助于银行股价值提升。我们重点推荐：招行、民生、光大，宁波、农行、工行。 +http://money.163.com/17/1122/06/D3R04H3F002580S6.html +万科股价创历史新高 龙头房企资源充足 + + （原标题：万科股价创历史新高 龙头房企资源充足） + 在易居研究院智库中心研究总监严跃进看来，地产股表现不错，充分说明房地产板块的基本面依然获得市场认可，尤其是近期众多房企都在冲刺年度销售业绩，地产股的大涨是对其业绩预期的体现。也有业内人士认为，多重因素助推了房地产股的上涨，龙头房企未来上升空间更大。以万科为例，今年前10个月，万科实现销售金额4328.9亿元，同比增38.8%。而根据兴业证券日前发布的纪要，万科有关负责人在回复投资者关于万科总货值的提问时表示，项目资源方面，加上10月份新获取的500多万平方米，未来总的可结算资源约1.35亿平方米，可售规模在9500万平方米左右。而就推盘而言，四季度可能更集中。今年上半年，市场好，推盘相对多一些，但下半年推盘会更多，最后两个月的推盘量预计比9月份、10月份多。关于转型，万科董事会主席郁亮日前接受采访时表示，万科未来的发展理念，就是以人民的美好生活为中心，成为美好生活场景师、创新探索试验田、实体经济生力军、和谐生态建设者。对于行业冷暖，中型房企也有切身体会。新城控股高级副总裁欧阳捷向记者透露，公司今年的销售情况很不错，主要得益于公司的布局符合市场发展趋势，在进入的45个城市中，一、二线城市和三、四线城市的配比比较均衡。另外，公司的住宅和商业并进的战略在今年也取得了良好的效果。截至10月底，碧桂园、恒大、万科、融创等龙头公布的销售业绩均已超过了2016年全年。中原地产首席分析师张大伟指出，龙头房企转型加速，布局合理。对住房租赁鼓励政策的出台，加快了部分房企的业务转型，受到市场关注。据上证报资讯统计，今年三季度，基金对房地产板块进行了加仓。三季报数据显示，基金配置房地产股的市值占净值比和占股票投资市值比例分别为0.53%和3.12%，而上期数值分别为0.5%和2.79%。与此同时，其他机构则小幅减持房地产股。三季报上市公司前十大股东榜显示，包括保险、QFII、社保、券商、阳光私募在内的机构合计持有69.94亿股，占总股本比例为4.27%，而上期为5.18%。 +http://money.163.com/17/1122/00/D3QBUVPR002580S6.html +易事特拟29亿收购背后：IPO募投项目未达预期 + + （原标题：易事特拟29亿收购背后：应收账款不断上涨 IPO项目未达预期） + 易事特拟29亿收购背后：应收账款不断上涨 IPO项目未达预期 应收账款逐年升高易事特主营UPS电源、EPS应急电源、通信电源、光伏发电系统、新能源汽车智能充电系统、智能微电网系统等产品的研发、制造和销售。2015年、2016年和2017年前三季度，易事特的营业收入分别约为36.82亿元、52.45亿元和54.73亿元；同期，净利润分别为2.79亿元、4.72亿元和5.24亿元。值得注意的是，伴随易事特业绩的上涨，公司应收账款水涨船高：2015年末、2016年末和2017年前三季度末，易事特的应收账款分别约为17.44亿元、29.92亿元和39.77亿元。《每日经济新闻》记者计算发现，易事特的应收账款占营业收入的比重不断上升，2015年度、2016年度，易事特的应收账款占当期营业收入的比重分别为47.37%和57.04%。11月20日，易事特相关高管书面回应，随着国内市场的快速发展，公司数据中心、光伏发电业务的销售量进一步上升，公司未来仍将会加大这一业务的拓展力度。此类业务的客户主要是大型互联网集团公司、发电集团、地方电力投资公司、光伏电站建设商及经销商，由于国内数据中心及光伏行业具有单个项目金额大、付款周期长等特点，将会导致公司应收账款余额较快增加。针对应收账款回收的风险，公司制定了严格的信用管理制度，加强对客户账期的管理，并加大对应收账款的考核力度。记者对比易事特所处行业的其他企业，其规模相当企业的应收账款占营收的比重。据东方财富Choice数据显示，与易事特同为输配电气行业且营收规模相当的企业，在2015年是思源电气（002028，SZ）和太阳电缆（002300，SZ），应收账款占营收比重分别是47.96%、18.29%；在2016年是国电南自（600268，SH）和思源电气，应收账款占营收比重分别是79.51%和52.11%。IPO募投项目未达预期原本被给予厚望的IPO募投项目，其实际效益却不及预期。易事特指出，上述两个项目，均属于易事特发展战略的重要组成部分。其中，高频UPS项目的建设，可增加易事特的高端UPS产品系列、实现UPS产业的技术升级与产能扩充，增强市场竞争力；分布式发电项目的建设，可依托自主知识产权核心技术及易事特经营管理综合资源、发展易事特战略新兴产业。不过，高频UPS项目的建设在一年后被终止。2015年4月，易事特公告，高频UPS项目终止的原因包括：该项目原计划开工时间为2011年4月（建设期36个月），但是募集资金到位时间为2014年1月底，资金到位时间晚于预期。同时，在2014年的项目实施过程中，高频UPS项目所处市场的容量趋于平稳，增长量不大。即使在这之后，易事特对生产工艺进行部分设备的重新选型及技术改进，但效果低于预期。据2015年年报（更新后）显示，高频UPS项目未能达到预计效益，项目可行性发生重大变化；分布式发电项目受市场环境影响，2014年市场环境较好，达到预期效益，但到了2015年，受市场竞争环境影响，分布式发电项目未达预期效益。 +http://money.163.com/17/1122/21/D3SHHLGN002580PL.html +股市早知道：影响股票市场的重磅新闻汇总(11.23) +宏观要闻李克强：进一步清理规范涉企经营服务性收费国务院总理李克强11月22日主持召开国务院常务会议，听取依法保护产权工作汇报，以更有效的制度促进各类市场主体立恒心增信心；决定进一步清理规范涉企经营服务性收费，持续为企业减轻负担。增值税有奖发票在上海试点 最高奖40万元11月22日，在上海市国家税务局召开的新闻通气会上，上海市国家税务局巡视员胡兰芳表示，为规范增值税发票的开具和使用，上海作为国家税务总局指定的首批试点城市，将于2017年12月起，开展全新的有奖发票试点工作。雄安新区市民服务中心招标花落中建 投资额8亿备受瞩目的雄安市民服务中心项目中标单位尘埃落定。11月22日，从中国建筑总公司了解到，经过严格的招投标及公示程序，中国建筑旗下中建三局集团有限公司、中海地产集团有限公司、中国中建设计集团有限公司、中建投资基金管理(北京)有限公司组成的联合体，中标了雄安市民服务中心项目。统计局：10月铁路货运量3.22亿吨 同比增长4.8%据中国国家统计局，10月铁路货运量3.22亿吨，同比增长4.8%；9月同比增长9.2%。1-10月铁路货运量报30.8亿吨，同比增长13.5%；1至9月同比增长14.6%。在岸人民币兑美元收涨178个基点 创近三周新高周三在岸人民币兑美元16:30收盘价报6.6159，创11月2日以来新高，较上一交易日涨178个基点。人民币兑美元中间价报6.6290，调升66个基点，升幅创11月15日以来最大。媒体：安邦被要求减持其所持有的民生、招行股权知情人士称，为减少对市场的影响，监管当局建议安邦集团通过非公开方式退出或减持；监管当局正在帮助安邦寻找合适的股权接盘方。股市关注刘士余：把发展直接融资放在更加突出位置11月14日至20日，证监会党委举办系统会管干部学习贯彻党的十九大精神第一期专题轮训班。刘士余强调，把发展直接融资放在更加突出位置，充分运用资本市场机制，主动服务国家战略，坚决打好防范化解重大风险等三大攻坚战。加快建设多层次资本市场，深化新三板改革，规范发展区域性股权市场，积极探索股权众筹试点，推动经济发展实现质量、效率、动力“三大变革”。要保持“本领恐慌”意识，加强监管能力建设，推进监管科技化智能化网络化。深交所：强化对快递服务业务量和网络节点披露为帮助投资者了解快递服务行业信息披露指引，更好地理解该类行业上市公司业务，深交所投教中心编制了股市三国诸葛锦囊系列之快递服务行业信披指引，供广大投资者参考。证监会主席助理宣昌能：IPO堰塞湖现象基本消除尔康制药：遭证监会立案稽查 明日复牌国泰君安联合网易发布“君易市场指数”今年8月份网易经济学家年会夏季论坛上，国泰君安与网易传媒正式签订了战略合作协议，就营销推广、产品研发、数据挖掘等层面的深度合作达成了共识。大数据是这几年很热的词汇,随着业务应用场景的不断拓展,它与业务的融合越来越深,为了持续探索数据价值,形成长效的探索机制,国泰君安联合网易成立了大数据实验室。国泰君安证券信息技术部总经理俞枫表示，这是双方的一次尝试,希望双方能在大数据资源价值发现、新型合作业务模式方面做一些探索。希望大数据实验室后续能成为双方业务合作的发酵器、排头兵。欢迎大家关注原创微信公众号股市圣经（gssj_gssj）！公司公告中航黑豹：沈飞集团注入完成过户中航黑豹公告，沈飞集团100%股权由航空工业、华融公司转让至中航黑豹的工商变更登记手续已经办理完成，沈飞集团于11月20日取得了沈阳市工商行政管理局换发的《营业执照》，上市公司成为沈飞集团唯一股东，沈飞集团成为上市公司全资子公司，拟购买资产已过户至上市公司名下。中航黑豹本次交易实施的其他相关后续事项主要为：上市公司及其他相关方尚需继续办理拟出售资产交割的相关手续；上市公司及其他相关方尚需办理本次交易所涉及的募集配套资金相关工作等。久联发展：筹划重大资产重组 明起停牌久联发展公告，公司正在筹划重大资产重组事项，公司股票将于11月23日起停牌。高鸿股份：控股股东正筹划重组事项高鸿股份公告，公司于2017年11月22日收到控股股东电信科学技术研究院通知，电信科研院正在筹划重组事宜，重组方案尚未确定，方案确定后尚需获得有关主管部门批准。金种子酒：定增募资不超6.96亿元 明日复牌金种子酒公告，公司拟向不超10名特定对象，发行不超1.11亿股，募资不超6.96亿元，用于优质基酒技术改造及配套工程项目、营销体系建设项目、金种子酒文化中心项目，上述项目投资总额7.61亿元。公司股票11月23日复牌。模塑科技：重组获证监会无条件通过模塑科技公告，公司发行股份及支付现金购买资产暨关联交易事项获得证监会无条件通过。公司股票及可转换公司债券自2017年11月23日开市起复牌。一汽夏利：一汽股份目前尚没有继续转让公司股份的计划 股票明日复牌一汽夏利披露投资者网上说明会召开情况，一汽股份目前尚没有继续转让一汽夏利股份的计划，也没有再次公开征集受让方、非公开与特定对象的打算。针对此前曾有消息称，一汽夏利或在第三批国企混改名单中，因故停牌。一汽股份相关负责人明确表示，一汽夏利并不在第三批国企混改名单内。一汽夏利股票将于明日复牌。鹏欣资源：重大资产重组申请材料获受理鹏欣资源公告，公司于2017年11月22日收到中国证监会出具的《中国证监会行政许可申请受理通知书》（172287号）。中国证监会依法对公司提交的《鹏欣环球资源股份有限公司上市公司发行股份购买资产核准》申请材料进行了审查，认为该申请材料齐全，符合法定形式，决定对该行政许可申请予以受理。 公司本次重大资产重组事项尚需获得中国证监会核准，能否获得核准及最终获得核准的时间均存在不确定性。【增减持】欧浦智网：董事高管拟增持公司股份欧浦智网公告，公司副董事长肖芳，董事、总经理马苏未来3个月内拟合计增持不低于2000万元，不超过1亿元。华锋股份：汇海技术拟减持153万股华锋股份公告，公司持股4.5%的股东汇海技术未来6个月内拟减持153万股，占公司总股本的1.125%。?健帆生物：珠海红杉减持150万股 持股降至5%以下健帆生物公告，公司股东珠海红杉资本股权投资中心（有限合伙）11月15日至21日通过集中竞价交易方式减持公司股份150万股，占总股本的0.36%。减持后，珠海红杉合计持有4.97%公司股份，且不排除在未来12个月内继续减持。华闻传媒：国广资产增持公司5%股份华闻传媒公告称，公司股东国广资产2017年5月15日至2017年11月17日期间，通过自有证券账户、星光5号及永盈1号在二级市场合计增持华闻传媒股票共计100,064,775股，占上市公司目前总股本的5.00%。 本次权益变动完成后，国广资产共持有华闻传媒246,564,905股，占上市公司已发行股份的12.32%。皇氏集团：股价持续下跌 公司董事所持公司股票遭遇平仓被动减持皇氏集团公告称，公司董事徐蕾蕾的证券账户出现卖出公司股票的行为，徐蕾蕾的证券账户于2017年11月21日卖出公司股票64.9万股，成交均价7.70元/股，成交金额499.9万元。本次减持后，徐蕾蕾女士持有公司股份2264万股，占公司总股本的2.70%。近期，因公司股票价格跌破最低保障比例，徐蕾蕾女士接到东方证券通知后，与其协商补充质押物的相关措施，在此过程中，公司股价继续下跌，因徐蕾蕾女士未能及时完成补充质押物的相关手续，致使其部分股票被东方证券强行平仓。TCL集团：两名董事拟减持股份TCL集团公告，公司董事兼总裁薄连明、董事兼财务总监黄旭斌未来6个月内拟通过集中竞价分别减持公司股份不超过101.47万股和84.58万股。腾达建设：金元顺安旗下资管计划减持2939万股腾达建设公告，金元顺安基金公司旗下金元顺安腾达定增资管计划22日通过大宗交易减持公司股份2939.43万股，占公司总股本的1.834%，减持后持股降至5%以下，且不排除未来12个月内继续减持。安洁科技：董监事终止减持计划安洁科技公告，公司董事、总经理吕莉，董事、副总经理贾志江，董事、董秘马玉燕，董事顾奇峰，监事卞绣花决定终止减持计划。据此前计划，吕莉、贾志江等董监高拟自9月4日起6个月内合计减持不超744万股。截至目前，吕莉已减持112万股，其他董监高未进行减持。汇顶科技：国家集成电路大基金受让6.65%股份 控股股东增持1%股份汇顶科技公告，汇发国际、汇信投资与国家集成电路产业投资基金股份有限公司签署了《股份转让协议》，共计转让3020万股(总股本的6.65%)给大基金，每股对价93.69元。在本次协议转让前，汇信投资已于2017年11月22日通过大宗交易减持260万股(总股本的0.57%)，减持价格93.69元/股。控股股东增持张帆11月22日大宗交易增持454万股(总股本的1%)，增持均价93.69/股，持股升至48.41%。乐通股份：控股股东拟增持8%-13%股份乐通股份公告，公司控股股东大晟资产11月16日至22日以集中竞价方式，累计增持公司股份316.19万股，占总股本的1.58%。自11月22日起未来12个月内，大晟资产将继续增持，合计增持比例（含此次增持）不低于公司总股本的8%，不超过总股本的13%。龙净环保大股东之控股股东累计增持5.87%股份 完成增持计划龙净环保公告，公司第一大股东东正投资之控股股东阳光集团通过其委托设立的阳光财富1号信托计划和莱沃18号信托计划，买入公司股份。截至2017年11月22日，累计买入金额已达9.66亿元，累计增持公司股份6280万股，占公司总股本的5.87%，已达其原定增持计划5-10亿元的上限，增持计划已实施完成。雷科防务：多名董事高管拟增持股份雷科防务公告，公司董事长戴斌，董事、总经理刘峰，副董事长、副总经理刘升，董事、财务总监、副总经理高立宁拟15个交易日内各增持10万股。正源股份：控股股东计划增持1%-4.99%股份正源股份公告，公司控股股东正源地产计划6个月内增持公司股份，增持比例不少于公司总股本的1%且不超过4.99%。目前，正源地产持有公司股份3.58亿股，占总股本的23.7%。梦网集团：拟回购3亿元至5亿元公司股份梦网集团本次回购股份的资金总额不低于人民币3亿元、不超过人民币5亿元；回购的股份将予以注销，从而减少公司的注册资本；本次回购股份的价格不超过16.75元/股；回购期限为自公司股东大会审议通过回购股份方案之日起7个月内。 ????中金环境：董事长增持逾40万股中金环境公告，公司控股股东、董事长沈金浩当日以集中竞价交易方式增持公司股份43.87万股，成交均价13.81元/股。未来6个月内，沈金浩不排除继续增持的可能性。云海金属：高管终止减持计划云海金属公告，公司董秘吴剑飞、副总经理刘小稻终止此前披露的减持计划，并承诺2018年3月15日前不再减持。据此前计划，吴剑飞、刘小稻、副总经理孙勇拟在8月10日起的6个月内分别减持64万股、75万股、9万股。目前，孙勇减持计划已完成，吴剑飞、刘小稻已分别减持18万股和2万股。龙韵股份：股东拟减持不超3.3%股份龙韵股份公告，公司股东许龙拟6个月内以集中竞价或大宗交易方式，减持公司股份不超220.08万股，即不超总股本的3.3%，减持股份来源为公司上市前取得的股份。鹏博士：多名董事及高管拟减持不超567万股鹏博士公告，公司董事张光剑，副总经理周柳青，监事杨玉晶、孙莉斯，原董事任春晓，原常务副总经理吴少岩，原副总经理吕卫团、冯劲军、林磊、方锦华、吴祯计划减持公司股份，拟6个月内通过集中竞价或大宗交易合计减持不超567.04万股，即不超总股本的0.4%。 ????誉衡药业：董事拟减持不超858万股誉衡药业公告，持股0.89%的公司董事杨红冰未来6个月内拟减持不超857.72万股，约占公司总股本的0.39%。中牧股份：中牧总公司减持近860万股 占总股本2%中牧股份持股占比49.91%的股东中牧总公司于2017年8月1日至11月20日，以集中竞价方式减持中牧股份股票8,596,000股，占股份减持计划拟减持数量的100%，占公司总股本的2%，该减持计划实施完成。达实智能：董事贾虹减持2880万股达实智能公告，公司持股5%以上股东、董事贾虹于2017年11月21日，通过大宗交易方式减持公司股份28,800,000股，占总股本的1.50%，减持均价5.88元/股。【重大事项】新国都：终止设立小贷公司威华股份：将全资控股致远锂业威华股份公告，公司拟以8000万元收购致远锂业30%的股权。收购后，致远锂业将成为公司全资子公司。致远锂业预计2018年初进入试生产阶段。为保证致远锂业的原料供给，公司将托管控股股东旗下瑞盛锂业，通过瑞盛锂业从海外进口锂矿石选矿产出锂精矿，所产锂精矿全部供给致远锂业。紫金矿业：刚果（金）卡库拉铜矿开发拉开序幕紫金矿业披露公司与加拿大艾芬豪矿业公司等合作的刚果（金）卡莫阿-卡库拉铜矿项目进展情况：卡库拉铜矿段超高品位矿体的并列双斜井施工完成首次爆破，表明该铜矿开发正式拉开序幕；卡莫阿-卡库拉两个采区合计年处理矿石量1200万吨的新版初步经济评估及工程设计即将完成；涵括卡库拉矿段控制范围的最新资源估算有望在2018年1月完成；资源区拓展潜力大。金亚科技：公司股票存在退市风险 明日复牌贵研铂业：前10月获政府补助3746万元贵研铂业公告，2017年截至10月末，公司及下属控股子公司累计收到各类政府补助共计3745.83万元。公司确认与收益相关的政府补助3565.83万元，确认与资产相关的政府补助180万元，上述补助将对公司2017年利润产生一定影响。通光线缆：拟发行不超2.86亿元可转债通光线缆公告，公司拟公开发行不超2.86亿元可转债，用于高端器件装备用电子线缆扩建项目、新建年产7000公里防火电缆项目和年产4000公里铝合金电缆扩建项目。华大基因：核查完毕 股票复牌华大基因公告，公司因近期股票价格涨幅较大停牌核查。截至目前，相关核查工作已经完成，公司目前的经营情况及内外部经营环境未发生重大变化；公司于近日取得由湖北省食品药品监督管理局颁发的医疗器械注册证；公司不存在应披露而未披露信息。公司股票自2017年11月23日起复牌。 ????江丰电子：核查完毕 股票复牌江丰电子公告，因近期股票价格涨幅较大停牌核查。截至目前，相关核查工作已经完成，公司目前的经营情况及内外部经营环境未发生重大变化；公司不存在应披露而未披露信息。公司股票自2017年11月23日起复牌。凯普生物：推高送转方案不存在配合成泉资本减持的情况凯普生物就高送转事项回复深交所问询表示，公司董监高、控股股东、高送转方案参与筹划人与成泉资本不存在关联关系，未参与投资相关产品，公司推出高送转方案不存在配合成泉资本减持的情况。11月17日晚间，凯普生物推出两市首份年报高送转预案，拟10转10派5元，公司股价连续3个交易日一字涨停。中曼石油：不存在未披露重大信息中曼石油发布异常波动公告，公司股票于2017年11月20日、11月21日、11月22日连续3个交易日内收盘价格涨幅偏离值累计超过20%。根据《上海证券交易所交易规则》的有关规定，属于股票交易异常波动情形。经公司自查，并向公司控股股东和实际控制人发函询证，截至本公告披露日，确认不存在应披露而未披露的重大信息。强生控股：拟受让公共交通卡公司12.87%股权强生控股公告，公司拟受让关联方强生集团持有的公共交通卡公司12.87%的股权，交易价6700.64万元。公司主业之一是出租车业务，而交通卡是出租车营收的主要结算方式之一。此次交易有利于促进交通卡业务的代销和ETC等增值项目的推广，同时获得较稳定的投资收益。神州易桥：减持凯莱英约23万股 收益超1200万神州易桥公告，11月20日至21日，公司累计减持22.99万股凯莱英(002821)股票，取得投资收益1240.17万元（未扣除税费）。减持后，公司持有凯莱英225.29万股，占其总股本的0.979%。时代新材：高性能绝缘结构产品产业化项目建成投产时代新材公告，公司配股募资建设的高性能绝缘结构产品产业化项目，即年产500吨聚酰亚胺薄膜产品生产线，顺利产出合格产品，并已开始批量供货。聚酰亚胺薄膜产品技术壁垒高、利润空间大、市场前景广阔，公司项目建成投产，实现了产品的进口替代，同时优化了公司产业结构。人福医药：退出氨基酸原料业务 子公司药品获批在美销售人福医药公告，公司拟3.5亿元将宜昌三峡普诺丁生物制药有限公司100%股权，转让给京山京源科技投资有限公司。公司预计普诺丁氨基酸原料业务短期内仍将亏损，且生物发酵行业环保投入将持续增加，公司遂决定退出氨基酸原料业务。另外，公司控股子公司的度他雄胺软胶囊获美国FDA批文，具备了在美销售的资格。该药品主要适用于良性前列腺增生症的治疗，国内仅葛兰素史克进口的度他雄胺软胶囊在售。步森股份：拟终止参与设立网络小额贷款公司步森股份公告，2017年11月21日，互联网金融风险专项整治工作领导小组办公室下发《关于立即暂停批设网络小额贷款公司的通知》。根据该文件指示，经公司管理层充分谈论，同时考虑到后续实缴出资可能带来的资金成本对公司业绩的压力，公司拟终止参与设立网络小贷公司。*ST华菱：拟转让华菱新加坡100%股权*ST华菱公告，公司拟将下属子公司华菱新加坡100%股权转让给控股股东华菱集团下属全资子公司华菱资源，交易价1475.37万元。华懋科技：控股股东拟协议转让不超10.74%股份华懋科技控股股东金威国际拟12月31日前协议转让不超公司总股本10.74%的股份。目前，金威国际持有公司1.27亿股，占总股本的53.69%。此次转让不会使公司控股股东及实控人发生变化。公司此前曾于9月28日公告，金威国际6个月内拟减持不超总股本6%的股份，该减持计划尚未实施。安迪苏：维生素A产品减产安迪苏法国工厂生产维生素A产品的原材料购自全球主流化工企业。由于其中某大型化工企业宣告相关产品不可抗力声明，安迪苏法国工厂将要被迫显著降低维生素A产品的产量。目前预计恢复时间为2018年4月。凭借以前月份累积以及仍在陆续产出的产品库存，安迪苏将继续执行目前已经与客户签订的全部订单。铁汉生态：联合预中标近20亿元PPP项目铁汉生态公告，公司作为牵头方组成的联合体，成为广东省梅州市大埔县旅游产业道路改扩建PPP项目第一中标候选人，项目总投资约19.68亿元。合众思壮：联合中标逾10亿元PPP项目合众思壮公告，公司作为牵头单位组成的联合体，与新疆和田地区公安局签署了《和田地区“雪亮工程”建设PPP项目合作合同》，项目投资估算10.17亿元。国祯环保：预中标逾6亿元PPP项目国祯环保公告，公司成为内蒙古五原县乌拉特后旗恢复湿地中水循环利用工程PPP项目的预中标人，项目总投资约6.05亿元。龙元建设：预成交潍州大厦PPP项目龙元建设公告，据潍坊市政府采购网《潍州大厦政府和社会资本合作（PPP）项目预成交公示》，公司为该项目的预成交供应商。项目总投资估算约2.57亿元，计划合作期11年，其中建设期暂定1年，运营维护期10年。 +http://money.163.com/17/1122/20/D3SH13BG0025814U.html +公告汇总：皇氏集团董事所持股票遭平仓被动减持 +中航黑豹：沈飞集团注入完成过户久联发展：筹划重大资产重组 明起停牌高鸿股份：控股股东正筹划重组事项金种子酒：定增募资不超6.96亿元 明日复牌模塑科技：重组获证监会无条件通过一汽夏利：一汽股份目前尚没有继续转让公司股份的计划 股票明日复牌鹏欣资源：重大资产重组申请材料获受理【增减持】欧浦智网：董事高管拟增持公司股份欧浦智网公告，公司副董事长肖芳，董事、总经理马苏未来3个月内拟合计增持不低于2000万元，不超过1亿元。华锋股份：汇海技术拟减持153万股健帆生物：珠海红杉减持150万股 持股降至5%以下健帆生物公告，公司股东珠海红杉资本股权投资中心（有限合伙）11月15日至21日通过集中竞价交易方式减持公司股份150万股，占总股本的0.36%。减持后，珠海红杉合计持有4.97%公司股份，且不排除在未来12个月内继续减持。华闻传媒：国广资产增持公司5%股份皇氏集团：股价持续下跌 公司董事所持公司股票遭遇平仓被动减持TCL集团：两名董事拟减持股份腾达建设：金元顺安旗下资管计划减持2939万股安洁科技：董监事终止减持计划汇顶科技：国家集成电路大基金受让6.65%股份 控股股东增持1%股份汇顶科技公告，汇发国际、汇信投资与国家集成电路产业投资基金股份有限公司签署了《股份转让协议》，共计转让3020万股(总股本的6.65%)给大基金，每股对价93.69元。在本次协议转让前，汇信投资已于2017年11月22日通过大宗交易减持260万股(总股本的0.57%)，减持价格93.69元/股。控股股东增持张帆11月22日大宗交易增持454万股(总股本的1%)，增持均价93.69/股，持股升至48.41%。乐通股份：控股股东拟增持8%-13%股份龙净环保大股东之控股股东累计增持5.87%股份 完成增持计划雷科防务：多名董事高管拟增持股份雷科防务公告，公司董事长戴斌，董事、总经理刘峰，副董事长、副总经理刘升，董事、财务总监、副总经理高立宁拟15个交易日内各增持10万股。正源股份：控股股东计划增持1%-4.99%股份正源股份公告，公司控股股东正源地产计划6个月内增持公司股份，增持比例不少于公司总股本的1%且不超过4.99%。目前，正源地产持有公司股份3.58亿股，占总股本的23.7%。梦网集团：拟回购3亿元至5亿元公司股份梦网集团本次回购股份的资金总额不低于人民币3亿元、不超过人民币5亿元；回购的股份将予以注销，从而减少公司的注册资本；本次回购股份的价格不超过16.75元/股；回购期限为自公司股东大会审议通过回购股份方案之日起7个月内。 ????中金环境：董事长增持逾40万股中金环境公告，公司控股股东、董事长沈金浩当日以集中竞价交易方式增持公司股份43.87万股，成交均价13.81元/股。未来6个月内，沈金浩不排除继续增持的可能性。云海金属：高管终止减持计划龙韵股份：股东拟减持不超3.3%股份龙韵股份公告，公司股东许龙拟6个月内以集中竞价或大宗交易方式，减持公司股份不超220.08万股，即不超总股本的3.3%，减持股份来源为公司上市前取得的股份。鹏博士：多名董事及高管拟减持不超567万股誉衡药业：董事拟减持不超858万股中牧股份：中牧总公司减持近860万股 占总股本2%达实智能：董事贾虹减持2880万股【重大事项】新国都：终止设立小贷公司威华股份：将全资控股致远锂业紫金矿业：刚果（金）卡库拉铜矿开发拉开序幕金亚科技：公司股票存在退市风险 明日复牌贵研铂业：前10月获政府补助3746万元通光线缆：拟发行不超2.86亿元可转债华大基因：核查完毕 股票复牌华大基因公告，公司因近期股票价格涨幅较大停牌核查。截至目前，相关核查工作已经完成，公司目前的经营情况及内外部经营环境未发生重大变化；公司于近日取得由湖北省食品药品监督管理局颁发的医疗器械注册证；公司不存在应披露而未披露信息。公司股票自2017年11月23日起复牌。 ????江丰电子：核查完毕 股票复牌江丰电子公告，因近期股票价格涨幅较大停牌核查。截至目前，相关核查工作已经完成，公司目前的经营情况及内外部经营环境未发生重大变化；公司不存在应披露而未披露信息。公司股票自2017年11月23日起复牌。凯普生物：推高送转方案不存在配合成泉资本减持的情况中曼石油：不存在未披露重大信息中曼石油发布异常波动公告，公司股票于2017年11月20日、11月21 日、11月22日连续3个交易日内收盘价格涨幅偏离值累计超过20%。根据《上海证券交易所交易规则》的有关规定，属于股票交易异常波动情形。经公司自查，并向公司控股股东和实际控制人发函询证，截至本公告披露日，确认不存在应披露而未披露的重大信息。强生控股：拟受让公共交通卡公司12.87%股权神州易桥：减持凯莱英约23万股 收益超1200万神州易桥公告，11月20日至21日，公司累计减持22.99万股凯莱英(002821)股票，取得投资收益1240.17万元（未扣除税费）。减持后，公司持有凯莱英225.29万股，占其总股本的0.979%。时代新材：高性能绝缘结构产品产业化项目建成投产人福医药：退出氨基酸原料业务 子公司药品获批在美销售步森股份：拟终止参与设立网络小额贷款公司步森股份公告，2017年11月21日，互联网金融风险专项整治工作领导小组办公室下发《关于立即暂停批设网络小额贷款公司的通知》。根据该文件指示，经公司管理层充分谈论，同时考虑到后续实缴出资可能带来的资金成本对公司业绩的压力，公司拟终止参与设立网络小贷公司。*ST华菱：拟转让华菱新加坡100%股权*ST华菱公告，公司拟将下属子公司华菱新加坡100%股权转让给控股股东华菱集团下属全资子公司华菱资源，交易价1475.37万元。华懋科技：控股股东拟协议转让不超10.74%股份华懋科技控股股东金威国际拟12月31日前协议转让不超公司总股本10.74%的股份。目前，金威国际持有公司1.27亿股，占总股本的53.69%。此次转让不会使公司控股股东及实控人发生变化。公司此前曾于9月28日公告，金威国际6个月内拟减持不超总股本6%的股份，该减持计划尚未实施。安迪苏：维生素A产品减产安迪苏法国工厂生产维生素A产品的原材料购自全球主流化工企业。由于其中某大型化工企业宣告相关产品不可抗力声明，安迪苏法国工厂将要被迫显著降低维生素A产品的产量。目前预计恢复时间为2018年4月。凭借以前月份累积以及仍在陆续产出的产品库存，安迪苏将继续执行目前已经与客户签订的全部订单。铁汉生态：联合预中标近20亿元PPP项目合众思壮：联合中标逾10亿元PPP项目国祯环保：预中标逾6亿元PPP项目国祯环保公告，公司成为内蒙古五原县乌拉特后旗恢复湿地中水循环利用工程PPP项目的预中标人，项目总投资约6.05亿元。龙元建设：预成交潍州大厦PPP项目 +http://money.163.com/17/1122/06/D3R04NCI002580S6.html +西南证券:业绩弹性继续释放 周期股配置价值提升 + + （原标题：业绩弹性继续释放 周期股配置价值提升） + 西南证券当前周期股行情的演绎已经到了一个关键的时点。一方面，依据半年报、三季报的披露，周期板块业绩确实出现了大幅改善，但边际上也有所下滑；另一方面，周期品价格依然维持在相对高位。而9月份以来，周期股已调整近两个月，从全市场比较来看，大蓝筹、消费及制造业的龙头估值已经不低，周期股则处于市场相对的估值洼地。近期，上游材料期货价格有企稳反弹的迹象，周期股资产负债表修复及业绩弹性继续释放的机会值得关注。2017年三季报已经全部披露完毕，其中周期股整体业绩大幅改善已经成为毋庸置疑的事实，但站在当前时点如何判断未来周期板块的盈利走向？我们需要从财报数据中进一步挖掘隐含的投资信息，从而为投资提供指导性意见。利润表：净利率与ROE继续回升资产负债表：有一定修复但还有很大改善空间历史统计数据表明，公司财务费用的比率与资产负债率呈现比较强的正相关关系。财报数据显示，周期行业的财务费用比率从2016年开始已明显出现下降，其背后原因在于这次周期行业盈利驱动的逻辑更多在于供给端。换句话说，企业在没有经历资产扩张，仅通过原材料价格的上涨就实现了经营改善。因而，财务费用比率的下降更多是收入增加导致的，并不意味着资产负债表修复明显。此外，我们进一步参考反映股东利益的指标，周期板块的每股净资产只是有所企稳，但没有明显改善。因此，我们认为周期性行业资产负债表整体有所修复，但还有很大改善空间。现金流表：煤炭行业改善最明显现金流量表是反映公司经营效率最直接的报表，持续的现金流量改善能为后续资产负债表的修复提供有利的条件。根据最新披露的财务数据，周期行业的现金流改善非常明显，其中煤炭开采行业每股经营现金流以及每股现金流净额已经超过2013年的水平，改善最为明显。而普钢、铝、铜、铅锌等行业经营现金流相比于2015年的低点已经有了较大程度的改善，但每股现金流净额改善并不十分明显。从上市公司账面上的现金及其等价物来看，同样也是煤炭开采行业现金增加最多，为后续扩大资本开支、扩张产能提供条件，而普钢、铝、铜、铅锌行业现金增加不明显。从筹资活动现金流来看，2016年开始周期行业筹资现金流转为负值，说明企业开始偿还债务，进而导致资产负债结构修复，但其中铜行业的筹资现金流从2017年开始由负转正，表明企业可能有扩大资本开支的意愿。需求端：下行空间有限根据国家统计局披露的月份经济数据，今年1月至9月，全国房地产开发投资额为8.06万亿元，同比名义增长8.1%，增速与1月至8月相比回升0.2%，依旧保持在今年以来的较低水平。与此同时，我国社会消费总额、民间投资、规模以上工业增加值、固定资产投资等重要宏观经济数据也整体继续呈现疲软态势。具体来看，9月社会消费总额增速为10.3%，环比回升0.2%，处于年内第三低点；9月固定资产投资增速为7.5%，继续回落。对于上游原材料来说，固定资产投资中房地产投资、基建投资、制造业投资是决定其需求走向的最重要三项，我们认为可以从这三方面分析未来需求端的走向。房地产库存创近三年来新低从商品房的库存量角度来看，房地产库存已经处于低位。根据国家统计局的数据，截至9月末，商品房待售面积为61140万平方米，比7月末减少1212万平方米，持续创下2015年以来的新低，房地产去库存效果比较明显。业内人士指出，按当前月均成交面积测算，目前全国楼市去库存周期仅剩5个月，除了东北、西北等少数城市，大部分城市库存已经进入良性周期。从投资额的角度来看，房地产投资完成额增速依旧平稳。今年1月至9月，房地产开发投资额为80644亿元，同比增速8.1%，增速环比小幅回升（8月份数据为7.9%）。其中，住宅投资额为55109亿元，增长10.4%，增速环比提高0.3%，明显有所回升。我们认为，未来随着房地产库存逐步见底，房地产投资底部支撑较强，继续向下的空间并不大。基建投资增速持续下行但有望改善数据显示，今年1月至9月基础设施建设投资同比增长15.88%，已经出现连续8个月的增速回落。在各大类投资中，唯一高于投资整体增速的是基建投资。今年以来，在金融去杠杆背景下，代表基建项目资金来源的国家预算内资金规模增速快速下滑，因而基建项目受到拖累。但我们认为，未来基建投资仍有改善空间：一方面国家预算内资金在5月份重新回到正增长，未来基建项目资金来源改善；另一方面，基建项目作为稳增长重要手段，随着经济增长变数的加大，以及PPP项目的落地加快，基建投资有望回升。制造业投资有所回落但不悲观国家统计局数据显示，今年1月至9月制造业投资同比增长4.2%，环比下降0.3%，连续3个月出现回落。从2016年8月开始，受全球贸易复苏以及补库存周期的影响，制造业投资出现回升，持续时间长达8个月，而此次制造业投资的回落主要原因还是在于去产能政策的影响。从制造业内部结构数据来看，我们认为，对制造业投资增速回落不需要过于悲观，主要原因在于制造业内部结构有所改善。一方面，从制造业投资的分项来看，上游黑色和有色制造业的固定资产投资持续负增长，拖累了整体制造业增速，但其他行业如专用设备制造、通信、计算机设备制造增速尚可；另一方面，从工业增加值数据来看，钢铁、石化、有色金属等传统制造业增加值增速均在0%至4%，而通用和专用设备制造、汽车制造、电气机械、电子通信设备制造等新兴制造业增加值增速均在10%至15%，增长的稳定性较高。这些数据均表明，制造业的结构有所改善。供给端：收缩力度有望超预期我们认为，从长期来看，环保将继续保持高压的态势；而从短期来看，进入寒冬季节，季节性雾霾等将使环保限产力度加大。市场力量：自发退出的产能上游民企中大部分产能或已经实现自发退出。从2012年开始，大部分上游原材料行业的固定资产投资增速快速下行，到2015年时，大部分上游行业投资已经下滑至负增长，到2016年时才有触底迹象，整个过程大概持续了约4年。我们认为，上游原材料行业已经历了4年多时间的市场化去产能周期，在这个过程中，企业盈利下滑，净利率很低甚至为负值，如果没有充足的资金来源很难维持下去，因而一些相对低效的产能会自发退出。2016年以来，在供给侧改革的推动下，大部分周期行业固定资产投资增速有触底迹象。这表明在过去4年时间里，市场化的去产能可能已经接近完全。现货价格未来趋势演绎综合以上分析，我们认为，从中长期来看，一方面经济总需求未来下行空间有限；另一方面，今年以来环保督查力度空前，而且高压态势有望在未来持续数年，供给端难以快速扩张，从而导致周期品长期均衡价格有望维持在高位。而从短期来看，随着四季度煤炭旺季到来，短期需求有望再次扩张，其价格有望再次获得上涨动力。从价格端数据来看，今年下半年以来，上游生产资料PPI有拐头向上的趋势，而且10月份数据验证原材料工业PPI依旧维持强势，我们认为未来上游原材料现货价格将继续维持量缩价升的态势。煤炭开采：业绩弹性和估值修复空间都比较大一个比较完整客观的分析框架是研究股价波动的前提条件，以煤炭板块为例，我们分析过去5年动力煤价格和煤炭板块股价指数的相关性，同时探究其背后的产业结构变迁及演化，进而分析其背后股价波动的逻辑。2010年之后，随着国内总需求的下滑，动力煤价格开始进入长达6年多的下行周期，而2016年开始大力推行供给侧改革，煤炭价格开始重新上行，但期间煤炭板块股价走势的变化并不同步。通过将营收增速、净利润增速和动力煤价格走势比较，我们发现，在动力煤价格下行的阶段，动力煤营收增速呈现同步快速下滑，但净利润增速下滑平缓。这可能表明在产业竞争格局中，一些低效产能已经在市场机制下自发淘汰，而上市公司作为相对优势的产能，在低净利率环境中，通过削减费用开支生存下来，而且进一步扩大了市场份额。在2016年初动力煤价格开始上行的阶段，煤炭板块的业绩增速开始好转，由负转正，在这个过程中，煤炭股股价总体呈现震荡态势，并未出现明显上涨。但从2016年9月开始，随着煤炭板块业绩明显回升，煤炭股股价与动力煤价格呈现同向波动趋势。价格与业绩背后的产业结构变迁从全行业数据来看，煤炭开采和洗选业的固定资产投资完成额的增速从2014年开始快速下滑至负区间，并且在负区间维持了3年左右的时间，说明整个煤炭开采行业大致经历了近3年的产能收缩。从上市公司数据来看，2015年煤炭全行业亏损，上市公司煤炭板块的固定资产增速开始明显下滑，与此同时，在建工程规模的同比增速下滑至负区间。这意味着上市公司的产能从2015年开始收缩，滞后于整个行业约1年的时间。这说明在2014年至2015年的2年时间里，上市公司产能在扩大，而整个产业的产能收缩至负增长。因此，在这个过程中，行业产能在向上市公司这种规模相对较大的龙头企业集中。煤炭行业集中度提升 龙头规模优势显著煤炭开采行业在2014年整个行业开始市场化去产能的低谷期时，代表行业领先地位的大企业上市公司产能却在不断扩张，具体表现为上市公司固定资产的增速超过行业固定资产完成额增速。这说明行业集中度在这个过程中有所提升，但目前总体来说，煤炭行业集中度依旧偏低。根据中煤协数据显示，目前90家大型煤炭企业原煤产量仅占全行业比重不到70%，但龙头公司规模优势显著，以神华集团为例，2016年原煤产量占全行业比重超过12%，远远领先于第二名的中煤集团。煤炭股股价与期货价格相关性已经进入高弹性的阶段。当前煤炭股股价与期货价格属于高度正相关的阶段，并且弹性较大，意味着未来股价的波动或将超过期货价格的波动，其背后有两个因素驱动：一是现货价格已经进入高盈利区间，业绩弹性较大；二是行业集中度在提高，龙头公司将获得估值溢价。我们认为，随着进入四季度煤炭消费旺季，在环保限产力度加大的情况下，煤炭价格有再次上涨动力，由此带来煤炭股股价的高弹性。而且即使未来现货价格仅是维持高位震荡，那么这种高盈利状态也将带来煤企资产负债表进一步修复，从而带来估值的溢价。普钢行业：业绩弹性较大 仍有估值修复空间按照上文的分析方法，我们同样从期货价格、业绩、股价三个角度去分析，得出的结论如下：从业绩弹性来看，当前普钢行业股价与期货价格的相关性同样进入了高弹性区间。我们认为，随着未来财政资金重新到位，基建投资后续仍有可能回暖，由此带来短期钢铁需求的增加，而随着未来冬季北方停产，短期供需错配导致螺纹钢价格有望再次上涨。从行业集中度来看，整个黑色金属采矿业的固定资产投资完成额增速同样经历了近3年的下行期，并且在2016年供给侧改革后，固定资产投资完成额的增速一直处于低位。从中钢协的数据来看，钢铁行业集中度在2014年、2015年后确实开始缓慢回升，到2016年，前十大钢企产量占比也只有35.9%，行业集中度总体来说依然不高。此外，从资产负债表的角度来看，当前钢铁行业上市公司整体资产负债率仍达到63%，财务费用占营收的比重达到1.66%，仍有一定的修复空间。有色行业：供给端的收缩动力依然较强与煤炭和钢铁行业有所不同，2016年以前，有色行业固定资产投资完成额一直处于大幅波动状态，并没有出现明显的供给收缩，而严格意义上的去产能从2016年才开始。2016年以前，有色行业基本是处于供给过剩状态，2016年大力推行供给侧改革后，有色行业产能才开始大幅收缩，至今已经持续约一年半时间，而当前数据也并没有明显改善的迹象。因此我们总体判断，未来有色行业供给端收缩的动力依然比较强。铝行业：资产负债结构修复空间较大当前铝行业同样进入业绩的高弹性区间。铝的下游需求主要是电线电缆以及房屋铝合金装饰，因此铝的需求与房地产以及基建的投资周期密切相关。根据前文分析，一方面，我们从房地产库存数据可以看出，未来房地产投资继续下行的空间已经非常有限；另一方面，四季度基建投资还是有回升动力，因此铝的需求有望在四季度开始改善，铝价依旧有上行的动力。从行业集中度来看，2016年以来，铝行业相关上市公司的固定资产净额增速上升，在全行业去产能过程中，铝行业集中度的提升幅度非常明显，未来铝龙头企业有望获得继续估值溢价。从资产负债表的修复角度来看，2017年三季报显示，铝行业整体资产负债率高达64%，财务费用比率高达3%，虽然环比有一定改善，但未来改善空间依然较大，未来铝价格如果持续高位，估值仍有较大修复空间。铜行业：看点在于产能结构优化升级从行业集中度来看，目前我国的铜行业整体呈现出一种寡头垄断的市场结构，其中铜陵有色、江西铜业、金川集团和云南铜业等四家公司产量约占全国的一半，但同时也有一大批的中小企业存在。2016年，整个行业供给侧改革开始，由于行业集中度已经较高，铜行业上市公司总体产能也呈现收缩态势，其中固定资产净额增速下滑较快。但在建工程规模2016年以来保持在20%以上的较高增速，表明铜行业整个产能结构在不断优化升级，其中原有的落后产能在退出，新增的先进产能在增加。此外，从资产负债表的角度来看，铜行业上市公司目前总体资产负债率在55%左右，财务费用率在0.6%左右，未来进一步修复的空间比较有限。铅锌行业：看点在于行业集中度提升2016年我国大力推行供给侧改革，整个行业产能快速收缩，但作为处于行业领先地位的上市公司来说，固定资产净额增速却在不断增加，这表明铅锌行业集中度提升较为明显，因此我们认为未来铅锌行业业绩弹性可能加大。但另一方面，在建工程增速下滑同样明显，表明优势企业扩张产能的动力不足。此外，从资产负债表来看，铅锌行业资产负债率目前为55%，财务费用比率为1.9%，下降已经较为明显，未来进一步改善空间有限。总体来看，我们认为：1.未来周期股下游需求的下行空间有限：一是房地产库存即将见底；二是与基建投资相关的国家预算内资金下半年重回正增长；三是制造业投资数据有回暖迹象。此外，今年以来环保督查力度前所未有，产能在市场作用下已经自发收缩。因此我们认为，未来上游材料现货价格有望继续保持高位强势状态。2.在上游材料价格维持高位强势状态的条件下，周期股的盈利能力将获得持续，由短期的利润表修复，进入资产负债表以及现金流量表的修复阶段，并由此带来估值的修复。3.在供给侧改革背景下，周期板块中不同行业未来业绩和股价的驱动逻辑有所不同，其中煤炭开采行业的逻辑最为明确，北方进入采暖季，煤炭需求进入旺季之后的现货价格上涨预期较强，以及本身业绩弹性较高，此外，高负债率的修复以及行业集中度的提升有助于进一步提升估值。我们建议未来重点关注煤炭开采、铝、钢铁行业的业绩弹性以及估值修复机会，并且从数据比较来看，需要尤其重视钢铁和铝。同时，从中长期关注铜行业产业结构升级以及铅锌行业集中度提升带来的投资机会。 +http://money.163.com/17/1122/15/D3RSTNAL002580PL.html +收评：沪指震荡涨0.59% 军工航天板块涨幅居前 +对于下阶段的行情，机构人士认为，以龙为首的格局仍将延续。朱雀投资表示，在市场风格方面，龙头企业在行业集中度提升和业绩的支撑下表现优于中小板块。从2017年四季度到2018年上半年，随着中国经济的复苏和经济质量的提高，以消费升级和新经济为代表的制造业升级有望成为投资主线，行业龙头仍将持续受到追捧，以龙为首的风格有望持续。短期市场的变化往往难以准确判断，但中期市场趋势是明确的，看好慢牛行情。国海富兰克林基金研究分析部副总经理王晓宁表示，成长股目前来看没有非常明确的板块性行情，但细分行业存在结构性机会，需要自下而上挖掘个股机会。部分成长股经过近两年的调整，PEG和估值已具有一定优势。近期市场“二八分化”愈发明显，对于市场风格问题，海通证券首席策略分析师荀玉根表示，过去一至两年，A股市场整体是偏价值风格，价值与成长之间的风格变化，每两年到三年会有一次切换，切换的因素既不是资金面，也不是经济增速，最终决定风格的还是盈利，就是看哪一类资产盈利增长速度会显著改善。2018年市场整体偏好龙头的风格不会变，因为A股上市公司还是处在行业集中度提高的过程中，一线龙头公司业绩的优势会比小公司更高。另外，随着外资投资占比的提高，他们也会聚焦行业龙头。华宝兴业基金最新策略认为，近期市场充分反映了盈利对超额收益的正贡献。因此，守住盈利改善的行业仍是上策，并可以关注和布局一些细分领域的龙头品种，这可能是明年的主线。三季报梳理出的盈利向好的细分板块包括机械和电气设备(光伏)；必需消费品中白酒、服装、一般零售；可选消费中地产、旅游、白电，TMT中的通信、光学电子；交运、环保、水务。申万宏源策略研究报告认为，龙头不能简单与价值板块划等号，成长股也有龙头。风格判断的基础是相对业绩趋势，2012年至2015年二季度创业板相对沪深300业绩增速不断向上，构成3年创业板牛市的基础。2015年三季度至2017年三季度沪深300业绩相对占优，也强化了价值股结构牛市。申万宏源对2018年各板块的业绩趋势判断有所不同，认为2018年尽管中小创外生业绩的正贡献将逐渐消失，总体业绩增速回归内生增速，同时商誉减值的压力仍可能边际提升，中小创业绩增速下滑仍是大概率。但与非金融石油石化相比，创业板(剔除温氏乐视)业绩增速的下滑幅度可能更小，相对业绩趋势将重新占优。2018年中小创可能成为重要的超额收益来源。需要注意的是，在沪深300相对业绩趋势连续6个季度占优之后，创业板相对业绩重新占优将是一个逐渐确认的过程，2018年第二季度和第三季度将是成长股强势归来的时间窗口。【关注公众号 网易股票：Stock_163、股市圣经：gssj-gssj】 +http://money.163.com/17/1122/06/D3R04AJN002580S6.html +新能源股股东户数下降 机构年末吸筹动作曝光 + + （原标题：新能源股股东户数下降 机构年末吸筹动作曝光） + 从行业来看，股东户数降幅明显的个股大多和新能源产业沾边。拥有锂电池概念的德赛电池和科恒股份，两者股东户数较10月底降幅环比下降超两成。德赛电池10月底的股东户数为27312户，11月中旬为21179户，环比下降22.46%。而将时间区间拉长，9月底至今，德赛电池的股东户数持续下降。以9月底数据对比最新数据，其股东户数下降幅度达31.39%。为核电和可燃冰试采提供阀门的纽威股份，其股东户数也从10月底的20318户下降至最新的17669户。拉长时间看，可以发现，该股股东户数从9月底以来就持续下降。除此之外，激智科技、盛弘股份等多只新能源个股的股东户数，下降幅度均超5%。业内人士认为，多只新能源个股筹码趋于集中，与现阶段国内经济发展趋势不无关系。随着国内节能环保监管趋严，光伏、风电、动力电池、核电等新能源势必成为不可或缺的代替品。国金证券表示，目前新能源产业的发展环境、竞争格局和技术成熟速度，处于多年来最优状态。在政府持续加大生态文明建设的背景下，未来5年内，新能源产业的市场规模有望进一步扩大。机构或已布局年末行情从三季度持仓情况来看，这些筹码集中的个股多数受到国家队的长期“宠爱”。以科恒股份为例，中央汇金自2015年三季度上榜其十大流通股东后，至今未曾增减持，持股数量一直维持在235.01万股。与其类似的还有纽威股份。中央汇金和证金公司同样在2015年三季度首次上榜纽威股份的十大流通股东，前者持股数量至今未曾变动，后者在2015年四季度小幅减持后，持股数量至今维持不变。通常来说，股东户数下降代表多空博弈现象减少，走势相对较强。不过，这些个股11月以来却表现平平。纽威股份11月以来累计上涨6.05%，德赛电池则累计下跌3.59%。业内人士认为，11月以来大盘指数进入调整期，市场风险偏好维持在相对低位，机构选择在股价持续走高期吸筹的风险较大。因此，机构更偏向在个股出现筑底信号，或下跌趋势已接近尾声时，逢低吸纳筹码。受此影响，11月至今筹码集中的个股表现并不抢眼。上述人士还认为，机构选择此时逢低吸筹相关个股，或是对今年四季度和明年一季度行情提前布局。以德赛电池为例，不少机构对其今年全年盈利能力持乐观态度。安信证券表示，德赛电池四季度的业绩高增速值得期待，预计其今年全年净利润同比增速将达45.2%。 +http://money.163.com/17/1122/07/D3R3F42J0025814T.html +6天94家公司获产业资本增持 逾25亿追捧四大行业 + + （原标题：6天94家公司获产业资本增持 斥资逾25亿元追捧医药生物等行业） + 产业资本6天净增持逾25亿元媒体市场研究中心根据数据统计发现，11月14日以来的6个交易日里，共有163家公司出现产业资本(大股东、高管以及自然人)持股变动(二级市场)，其中获得增持的公司有94家，遭减持的公司有69家，产业资本合计净增持资金达到25.73亿元。雏鹰农牧较为典型，11月14日以来的6个交易日里产业资本净增持6324.26万股，合计增持资金达到28205.05万元。对于该股，民生证券表示，公司目前的战略定位为“生猪养殖、粮食贸易和互联网”三大板块，努力开拓下游销售终端，打造核心竞争力，发展前景相对良好。预计公司2017年至2019年每股收益分别为0.34元、0.38元、0.48元，对应估值分别为13.11倍、11.74倍、9.29倍，未来12个月合理估值区间为5.10元至6.12元，给予“强烈推荐”评级。40家公司年报业绩预喜媒体市场研究中心根据数据统计发现，上述11月14日以来的6个交易日里获产业资本增持的94家公司中，共有68家公司2017年三季报净利润实现同比增长，占比72.34%。摩恩电气年报业绩预增幅度最高，2017年三季报披露显示，公司预计2017年净利润为7600万元至8000万元(上年同期净利润为870.24万元)，同比增长773.32%至819.29%。业绩变动原因：预计公司类金融业务，特别是全资子公司摩安投资开展的银行不良资产处置清收服务业务，将对公司2017年利润增长产生相对显著的贡献。94只增持股扎堆医药生物等四行业 +http://money.163.com/17/1122/07/D3R2MPRU002581P1.html +股价一度暴跌30% 趣店急推1亿美元股票回购计划 + + （原标题：遭监管暴击后紧急宣布回购 趣店跌幅急剧收窄） + 而后现金贷板块跌幅集体收窄，趣店更是明显反弹，跌幅由盘前30%以上收窄到开盘后11%左右，最终收盘跌幅不足4%。周二盘前，趣店美股一度大跌逾30%，距离历史最高点跌逾60%。此前多家媒体称互联网小贷牌照的发放被紧急叫停。临近开盘，趣店宣布，未来12个月内将回购不超过1亿美元的A类普通股ADS。趣店盘前跌幅收窄到20%以下。开盘后跌幅进一步收窄，早盘跌幅一度在6%以下，最终收跌约3.7%。趣店、信而富、拍拍贷、宜人贷、融360跌幅截图 来源：谷歌财经互金整治办：部分“现金贷”业务存在较大风险隐患文件称，近年来，有些地区陆续批设了网络小额贷款公司或允许小额贷款公司开展网络小贷业务，部分机构开展的“现金贷”业务存在较大风险隐患。文件要求，自即日起，各级小贷公司监管部门一律不得新批设网络（互联网）小贷公司，禁止新增批设小额贷款公司跨省（区、市）开展小额贷款业务。《证券时报》还提到，接近监管人士透露，监管部门后续或出台规范网络小贷公司的相关管理办法，可能会涉及提高未来网络小贷公司批设门槛的内容。业内人士：互联网小贷牌照价格已达5000万 料将上行这个新政对现金贷平台影响较大，因为现金贷业务迎来整顿的可能性很大，它们都迫切希望通过持牌去解决放贷业务的合规需求，牌照暂停批设，意味着它们只能通过有限的存量牌照来解决合规问题。 +http://money.163.com/17/1122/07/D3R408F40025817I.html +越涨越卖 10月以来主要A股ETF净流出近百亿 + + （原标题：越涨越卖 10月以来主要A股ETF净流出近百亿） + 沪深交易所上市交易的ETF方面，根据资讯的统计，10月以来，逾百只ETF份额合计缩水42亿份，按照区间均价估算，资金净流出规模达80亿元。其中，资金净流出最大的当属跟踪上证50指数的50ETF，该ETF今年9月底的规模达到133亿份，而到了本周一，规模跌至117.78亿份，累计缩水15.22亿份，缩水比例超过10%。按照该ETF10月以来2.85元的成交均价估算，资金流出规模约43亿元，占据了沪深交易所ETF资金净流出的一半。今年A股市场呈现出典型的二八分化行情，以上证50指数为代表的蓝筹指数表现突出，截至11月21日，上证50指数今年以来涨幅已经超过30%。而伴随着该指数的节节走高，50ETF规模却呈现出了不断缩水势头，资金逢高减磅、落袋为安的心态表现得十分明显。相比而言，华泰柏瑞沪深300ETF规模保持稳定，并获得约7亿元的资金净流入，消费板块的强势表现也使得汇添富中证主要消费ETF10月以来份额大增近50%，资金净流入约4亿元。不过，资金净流入的毕竟是少数，无法改变ETF整体上资金明显净流出的局面。实际上，不仅是沪深交易所挂牌的ETF，港交所上市的跟踪A股指数的主要RQFII ETF也从10月份开始出现了显著的资金净流出。其中，规模最大的南方东英A50ETF表现得尤为明显，截至11月20日，该ETF份额规模为16.9亿基金单位，比9月底减少1.185亿基金单位，而10月以来该ETF成交均价为12.73元，意味着约有15亿元资金从该ETF中流出。规模同样较大的华夏香港旗下沪深300ETF10月以来经历了一个规模先升后跌的过程，截至11月20日，该ETF份额为2.559亿基金单位，比9月底减少720万基金单位，约有3.6亿元资金净流出。这样，10月份以来，在沪深港三地挂牌的主要A股ETF合计资金净流出规模约达100亿元。和A股ETF资金大幅流出形成较大反差的是，现金管理的货币ETF规模在10月以来增长明显，三大龙头品种华宝添益、银华日利和建信添益等货币ETF10月份以来份额分别增加71亿份、73亿份和72亿份，推动货币ETF整体吸金超200亿元。相比波动较大的股票ETF而言，货币ETF收益稳定，资金回流货币ETF也反映出一部分资金年底前求稳的心态。 +http://money.163.com/17/1122/05/D3QSOOBU002580S6.html +分级基金步入“消亡”周期 业内坦言转型路径 + + （原标题：公募分级步入“消亡”周期 业内坦言转型路径） + 本报记者 庞华玮 广州报道资管新规冲击波对于不少人来说是靴子落地，而对于另一些人，则是预期之内。资管新规无疑给资管行业未来发展指明了发展方向，亦意味着变化将会行业的各个细节处发生……（李新江）导读今年以来市场已有2只分级基金清盘，12只分级基金转型。“我们的一只分级基金将转型为LOF指数基金。”11月21日，基金业人士杨远（化名）向21世纪经济报道记者表示，“今年以来分级基金的规模一直在萎缩，证明大家已经开始离开分级基金。当参与方越来越少，不让宣传，不鼓励，未来分级基金迟早会消失。”当11月17日，央行、银监会、证监会、保监会、外汇局联合发布《关于规范金融机构资产管理业务指导意见（意见征求稿）》（以下简称“《意见》”），记者采访的多位人士表示，《意见》对分级基金限制更加严格。11月21日，格上理财研究员杨晓晴受访时指出，“虽然分级基金为永续型产品，但行情不佳时难免会触发清盘条件，届时难逃清算或转型的厄运，而且这种转型或清算是不可逆的。”分化Wind数据显示，目前市场共有149只B类基金。截至11月21日，今年以来，102只基金获得收益，占比68%，收益最高的是白酒B、食品B、保险B、酒B，它们的复权单位净值增长率都超过了100%，分别达到160%、127%、103%、102%。反观另一面，分级B跌得惨的也不在少数。47只B类基金收益为负，占比32%。其中传媒B级、传媒业B、创业股B、体育B4只分级B的复权单位净值增长率跌幅超过60%。对此，杨晓晴表示：“目前市场分化显著，强势板块涨势喜人，相应的分级基金也赚得盆满钵盈；反观投资弱势板块的基金则亏损严重。”那么，分级基金到底还有没有投资价值？杨晓晴认为，分级基金具不具备投资价值，关键取决于所投基金是否适合当下行情。一位业内资深人士告诉记者：“分级基金还有很多套利机会，比如市场大涨时，可以做短线波段。下跌时，可以买分级A锁定收益。即使对于大机构来说分级基金也是很好的配置品种。”一位分级基金经理则表示，看好券商B，“现在券商和去年白酒行情起步时类似。券商有机会，未来边际改善，走势会越来越好，现在是低点。”然而，《意见》是否会给分级基金带来冲击？事实上，今年政策给分级基金带来冲击已不是第一次，今年四五月，分级基金“30万门槛”的政策曾使大量分级B成交量暴跌，甚至出现日内零成交，分级基金被大量赎回，分级基金被迫抛售重仓股。多位人士认为，《意见》对分级基金限制更加严格。《意见》明确规定，公募产品、开放式私募产品等“不得进行份额分级”，同时“分级资产管理产品不得直接或者间接对优先级份额认购者提供保本保收益安排”，前者意味着基金不得再发行公募分级基金，后者则意味着分级基金中的优先级份额不得保本保收益，直指分级基金中的A份额。对此，杨晓晴表示：“本次规定并没有四五月份的 30万门槛 那么直接具体，对市场的短期冲击不会很大，对投资者也是间接影响。”保留、转型，还是清盘？资管新规的缓冲期至2019年6月30日。对于不远的未来，杨远介绍：“分级基金一般有两种出路：一方面规模大的分级基金可以选择转型成标的指数的LOF基金，比如沪深300分级基金可以转成沪深300LOF基金。另一方面，规模小的分级基金可以直接选择清盘，毕竟如果要维持迷你基金运营需要成本，往往不太合算。”不过，记者采访多位业内人士对《意见》过渡期结束后违反规定的分级基金存量产品的处置的解释存在分歧：一种解释是过渡期后存续期结束，大概率将面临转型或强制清盘可能；另一种理解认为分级产品多为永续型，此类产品无需续期，指导意见未给出明确处置方式。那么分级基金最终的出路究竟是保留、转型，还是清盘？对此，杨晓晴也表示：“分级基金一般会选择转型，迫不得已才会清盘，毕竟这比发行新基金成本低很多。”不过，今年以来，市场上已有2只分级基金清盘，其中，中海惠丰纯债分绩优股今年以来母基金和B类的复权单位净值增长率为负，而银华永益分级的规模小于规定的5000万。市场人士普遍认为，分级基金未来清盘的数量不在少数。在严格的监管下，更多的分级基金选择转型，证监会官网显示，目前已有12只分级基金转型，且主要转型为LOF和定开产品。而好买基金研究中心研究员雷昕认为，“监管层去杠杆的态度在对于分级基金起购金额的提升，以及不再受理分级基金申请上已经明确了。”“分级产品在过渡期后面临转型或强制清盘可能更大，考虑到这一点，当前折价分级A或将迎来机会。”雷昕告诉记者，经历了四五月份的出清，当前分级基金子份额的活跃度可以说是在冰点，分级B的杠杆效应很多时候无法有效体现。记者采访中，没人看好分级基金的未来。不过，雷昕表示，“相信在未来中国金融市场越来越丰富，投资者越来越成熟之后，结构化类公募产品还是会以某种新的形式回到我们的视野中来。”（编辑：李新江） +http://money.163.com/17/1122/07/D3R1JQTI002580S6.html +孙宏斌要让新乐视转向文娱 前高管感叹：黄粱一梦 + + （原标题：孙宏斌要让新乐视从电视转向文化娱乐） + “黄粱一梦。”灰飞烟灭的，还有乐视网宏大的智能生态蓝图。乐视网（300104.SZ）停牌已经超过半年，估值从停牌前的15.33元/股被下调至3.91元/股。以电视业务为最大营收来源的乐视网今年前三季巨亏16.5亿元，目前乐视网最大的希望是尽快完成对乐视影业的收购重组并引入新的投资者。随着乐视网的估值越来越低，乐视网在收购乐视影业过程中，将要向乐视影业的股东定向发行更多的股票，才能完成此次收购。今年前三季乐视网的经营活动产生的现金流量净额是-28亿元，定向增发股票是比支付现金更为可行的收购方法。乐视影业董事长兼CEO张昭近日表示，拟把乐视影业改名为新乐视文娱，即从影业扩展到文化娱乐的更大范围，这为整合融创中国旗下的文娱资产留下了空间。不排除在乐视网收购乐视影业、引入新投资者的方案中，包含乐视影业整合融创文娱资产内容的可能性。在乐视网的股权结构中，大股东贾跃亭持股25.67%，第二大股东融创旗下的天津嘉睿持股8.56%，两者的股权占比仍有较大差距。不过，11月20日，乐视网公告称，融创中国向乐视网、乐视致新提供17.9亿元借款，贾跃亭旗下更多的上市和非上市资产质押给了天津嘉睿。这意味着在乐视网重组乐视影业的过程中，孙宏斌有可能将跃升为乐视网的第一大股东。事实上，乐视网正沿着现任董事长孙宏斌的思路，业务重心从彩电硬件转向文化娱乐的“软件”。究其原因，乐视电视去年全年销量近600万台，今年却陷入资金链紧张、商誉受损的困境，供应链和销售渠道变得脆弱，加之整个彩电行业的集中度在提高，乐视电视已经很难恢复往日的辉煌。熟悉硬件的乐视网CEO梁军辞职，张昭被提拔为新乐视管理委员会主席，也就不难理解了。张昭认为，新乐视文娱仍将以电影内容为主，逐步扩大剧集投入，垂直化运营IP，通过电视大屏进入社区场景、家庭场景。上周，融创要求旗下的子公司，办公区及住宅、公寓和旅游地产项目要配电视的，都要用乐视电视。这预示着，未来乐视电视会更多依附于融创和新乐视的文娱产业链。乐视影业更名为新乐视文娱后，将不仅仅局限于乐视网和乐视电视，而是会更加开放，定位于整个家庭大屏娱乐市场。一家全国电器连锁企业的董事长在谈及乐视和贾跃亭时说——“欲速则不达”，如果老贾聚焦在家庭互联网，就不会到今天的地步，他曾经有机会掌握中国最大的家庭互联网入口。 +http://money.163.com/17/1122/07/D3R3EIES00258169.html +一汽夏利暂无接盘者 非公开特定交易股权或将启动 + + （原标题：一汽夏利“卖身”暂无接盘者 非公开特定交易股权或将启动） + 公开征集受让方受挫一汽夏利此后公告称，一汽股份拟协议转让所持有本公司的部分股份，本次股份转让完成后，公司控股股东将发生变更。根据一汽夏利11月7日的公告，国务院国资委同意公司控股股东一汽股份通过公开征集受让方的方式协议转让所持公司24.73%的股份。按照计划，意向受让方递交申请材料的截止日期是于2017年11月20日17:00之前，符合条件的意向受让方应向一汽股份现场报名，同时递交申请材料。不过，截至公开征集期届满，一汽股份仍未征集到符合《公开征集公告》中各项资格条件的受让方。为此，一汽夏利于11月20日晚的公告称，一汽股份决定终止本次公开征集。与此同时，一汽夏利还表示，日前一汽股份已启动对动力总成资源整合工作，并设立了天津乘用车动力总成分公司，并将2015年从一汽夏利收购的动力总成资产拨入天津乘用车动力总成分公司。为保证天津乘用车动力总成分公司正常运转，一汽夏利与天津乘用车动力总成分公司于2017年11月20日签订了《资产转让合同》，将公司下属内燃机制造分公司和变速器分公司动力总成日常生产制造相关部分的资产及负债转让给一汽股份。对此，有分析人士向记者表示，一汽夏利巨亏的业绩使其卖身受挫，成为了一汽股份真正的烫手山芋。巨亏业绩致无人问津事实上，拥有燃油车和新能源车汽车生产资质的一汽夏利，在双积分考核下，理应成为跨国车企追逐的对象。据了解，即使合资，拥有双生产资质的企业开出的“迎娶”条件也相当高。如果能够迎来有新能源技术优势的新控股股东，将会显著提高一汽夏利的竞争力。然而，就在上月底，尚处于停牌期的一汽夏利公布的三季报却让投资者大跌眼镜。报告期内，公司实现营业收入9.97亿元，同比下降32.28%；净利润亏损11.23亿元，同比下降36.14%；每股收益为-0.70元。值得注意的是，相较半年报，一汽夏利的亏损非但没有收窄，反而持续扩大。对此公司解释称，由于产品结构调整尚未完成，产销规模低，盈利能力较弱，因而导致亏损持续增加。目前公司正在紧张进行产品结构调整工作。而9月份产销报告则显示，一汽夏利旗下夏利、威系列以及骏派三大系列中，夏利系列已处于停产状态，当月并未有任何产量。从这些数据可以看出，一汽夏利旗下品牌基本停滞。上述分析师表示，尽管二级市场对一汽夏利重组充满了预期，但由于二级市场的股价和净资产之间差距太大，买壳方付出的代价太大。 +http://money.163.com/17/1122/05/D3QSORO6002580S6.html + 亚洲家族企业传承面临挑战 逾80％家族毫无准备 + + （原标题：摩根大通： 亚洲家族企业传承面临挑战 逾80％的家族毫无准备） + 总部位于美国波士顿的Wise Counsel Research总裁Keith Whitaker在采访中指出：“研究发现只有不到3%的家族企业可以传承至三代以上。有趣的是，我们发现很多这些 百年家族 通常在第二代接班时，会有意识地重点关注如何成为一个伟大的家族，而不单单是针对家族生意的管理、股权架构等。”香港中文大学曾进行的一项对近20年来中国香港和中国台湾以及新加坡的200宗家族企业传承案例的研究显示，家族企业在交接班过程中都要面对巨大的财富损失。其中，香港家族企业损失最严重，这些家族企业在交接班时间段里，股票异常变动率高达-120%。91%的家族倾向保留家族企业李思颖透露，根据摩根大通的一项调查显示，受访的140多个亚洲家族企业中，仅有9%的家族正在考虑出售家族企业，或寻求家族企业上市，“同时，超过90%的家族仍倾向于保留家族企业，这个比例明显高出欧美市场。”据悉，受访的亚洲家族企业管理的资产规模大约在5亿美元以上，而且家族生意至少延续至第三代或以上。同时，Whitaker认为，通常是否出售家族生意是第一代关注所在，相比保留家族生意（business），这些家族应该意识到保留家族企业（enterprise）的重要性，“如果注意力只是放在家族生意上，这样的家族很难长久下去。调查发现事实上大约60%的百年家族曾经在某个时点出售过家族生意，但这些家族找到了可以让家族企业持续下去的方法。”事实上，那些能够成功打破“富不过三代”魔咒的家族存在一些共通点。“这些家族通常设立了家族议会（family council）、家族宪法（family constitution）、独立董事会、退出机制、下一代教育等，这些机制确保了在一些重大决策上家族成员可以有效沟通并适当处理家族矛盾，从而避免一些破坏性的私下沟通。”Whitaker表示。以退出机制为例，这让不少坐拥巨额财富的家族十分烦恼。随着更多的家族成员成为家族企业的所有者，在某些情况下，个别家族成员可能不打算在家族企业内就职，并且希望出售其在家族企业内的股份。不少家族在这些事务上投入巨大的精力，而成功的家族则通过设立退出机制，彻底避免或尽量减少为此耗费的时间和精力。约一半的受访家族为家族成员提供了某种形式的退出机制。其中，大部分的退出机制仅限于家族成员内部，不允许将所有权转让给家族以外的人。随着家族成员数量的增加，会有越来越多的亚洲家族企业着手设立相应的退出机制，仅有11%的受访家族允许成员将股权转让给第三方。同时，家族希望对所有者的数量加以限制，从而将所有权集中在那些真正对家族企业的持续发展怀有热情的成员手中。家族办公室蔚然成风随着亚洲各国经济的蓬勃发展，全球财富的重心“东移”的趋势正在加速。由于这些家族企业进入接班高峰期，家族办公室已成当下亚洲顶级富豪们的热点话题。根据瑞银与普华永道10月26日联合发布的报告显示， 亚洲每隔一日就有一位新亿万富豪诞生。去年，亚洲亿万富豪的总人数增加近四分之一至637位，有163位新晋亿万富豪。中国的内地亿万富豪人数则净增67位至318位，位居亚洲首位，印度则净增16位至100位。李思颖表示，大部分家族办公室设立的初衷在于管理家族投资，很多中国富豪们在选择设立家族办公室的地点时会考虑很多因素，“比如，某个城市对金融牌照的政策，资本是否可以自由出入，当地的税法等。在亚洲来说，中国香港、新加坡是很多家族办公室的首选之地，也有一些家族办公室选择设立在伦敦、纽约等亚洲以外的城市。”据业内人士介绍，家族办公室作为家族财富管理的最高形态，设立一个架构完整的单一家族办公室（Single FO），家族的可投资资产规模至少为5亿美元。对于那些资产规模在1.5亿-5亿美元的家族，则建议加入一些联合家族办公室，从而节省成本。 +http://money.163.com/17/1122/05/D3QSOI3S002580S6.html +蚂蚁金服重击现金贷：芝麻信用停止服务部分机构 + + （原标题：蚂蚁金服重击现金贷平台： 趣店导流缩减 芝麻信用停止服务部分违规机构） + 由于趣店股价近期连日重挫，引起美国证券律师事务所Faruqi & Faruqi的注意，该公司在当地时间11月20日宣布，对趣店发起调查，以查明其是否存在潜在的违规行为。Faruqi & Faruqi还向因投资趣店而亏损的投资者号召，希望他们能够提供调查线索。对此，趣店相关人士21日回复21世纪经济报道记者称，暂时还没有更多的情况可以披露。上市后，趣店的现金贷模式深陷舆论风波。据多地金融办人士向21世纪经济报道记者透露，国家有关部门正在制定针对现金贷的监管细则。继近日宁波鄞州区叫停两家违规现金贷公司后，11月21日，监管下发《关于立即暂停批设网络小额贷款公司的通知》，要求自即日起，各级小贷公司监管部门一律不得新批设网络（互联网）小贷公司，禁止新增批设小额贷款公司跨省（区、市）开展小额贷款业务。可以预见的是，现金贷行业将迎来一波清理整顿的生死大考。蚂蚁金服否认收紧趣店导流蚂蚁金服相关人士11月20日对21世纪经济报道记者表示，趣店是蚂蚁金服开放平台上的合作伙伴之一，双方的合作关系没有变化。趣店在支付宝App中的入口遵从蚂蚁金服开放平台统一的标准和算法，蚂蚁金服开放平台并未针对单一产品进行调整。个别用户反馈的趣店入口不可见的问题，可能是由于算法优化产生的。但不管是怎样的算法优化，客观上确实导致了部分支付宝用户看不到趣店的入口。这将给趣店的业务规模带来多大的影响，尚待其四季度报告披露。事实上，蚂蚁金服旗下自有现金贷产品蚂蚁借呗，且规模不小。21世纪经济报道记者根据Wind数据统计，2017年前10个月，蚂蚁借呗发行的ABS总额达1071.1亿元，蚂蚁花呗ABS发行总额达1061亿元，占企业ABS中以小额贷款为基础资产的发行总额的95%以上。虽然ABS发行规模不能完全代表业务规模，且存在时滞，但结合市场和ABS发行情况估计，蚂蚁借呗今年的业务规模可能已经破千亿。21世纪经济报道记者还在统计中发现，主要提供现金贷款产品的蚂蚁借呗ABS发行量，在2017年7月之后连续快速增长，其中10月份单月发行量达239.7亿元，已超过有消费场景的蚂蚁花呗单月发行量的最大值。消费者对于蚂蚁借呗现金贷产品的需求，显现出超越消费金融产品的趋势。其发行的ABS招募说明书显示，蚂蚁借呗ABS的预期收益率一般在4.5%-5.5%，而蚂蚁借呗贷款利率约在日息0.015%-0.06%之间，相较其募资成本，净收益率可观。存在竞争关系的背景下，蚂蚁金服为什么还要在支付宝开放导流入口给趣店？对此，蚂蚁金服的官方说法是，因为趣店是蚂蚁开放平台的伙伴之一，蚂蚁一直以来就想打造一个开放的金融平台生态，对于平台来说，并不存在竞争对手的问题。且二者间存在利益攸关的股权纽带。据趣店招股书披露，蚂蚁金服旗下投资公司仅持有趣店12.8%的股权，为第五大股东。而趣店的转折点，正是从接入支付宝后，开始扭亏并迎来快速发展的。之前支付宝的导流是免费的，但从今年开始支付宝向趣店收费。趣店今年三季度财报显示，其当季销售费用为1.88亿元人民币，同比增长384.7%，环比增长97.13%。趣店的销售费用主要用于支付宝的通道费用。对此，趣店相关人士对21世纪经济报道记者表示，趣店和蚂蚁金服的合作是基于市场化的合作，蚂蚁金服对趣店的收费方式，与其它的消费金融业务合作伙伴基本保持一致。芝麻信用停止与部分现金贷公司合作尽管监管靴子尚未落地，市场已经悄然谨慎收缩。继银行等金融机构收紧与现金贷公司的合作后，蚂蚁金服也给了现金贷一大打击。蚂蚁金服旗下的芝麻信用为包括趣店在内的多家现金贷公司提供征信数据服务。以趣店为例，他们为芝麻分超过一定标准的用户提供信贷。11月21日有消息称，一现金贷平台收到芝麻信用关于终止服务的通知，理由是“芝麻信用持续收到多起用户对贵公司存在收取法定保护利率以上各类费用、不当催收等方面的投诉”。对此，蚂蚁金服21日对21世纪经济报道记者回应称，近日芝麻信用在排查中发现，个别商户存在超过法定保护利率以上的各类费用、不当催收、没有按照协议履约等问题，所以暂停了合作；芝麻信用对合作伙伴有明确的准入规则，还会持续排查商户的资质、产品和服务情况；后续，如发现类似问题，也会立即停止合作。蚂蚁金服表示：“消费金融行业是芝麻信用对外开放的一个重要领域，包括银行持牌消费金融机构，也包括现金贷公司。芝麻信用的平台业务是很谨慎的，为了整个行业的健康发展，芝麻信用有持续的关注和规范方式。目前芝麻信用对合作伙伴的管理，主要是从资质和产品两个维度，并没有专门针对现金贷公司的政策和服务。”事实上，芝麻信用的排查并非最近启动的。早在今年8月份，芝麻信用就开始排查与现金贷公司的合作。当时芝麻信用要求合作的平台提供对应经营资质的证明，否则芝麻信用将无法继续提供服务。芝麻信用所要求的资质证明，指的是针对有放贷资质的机构，需要提供放贷资质证明文件；如非使用自有资金放贷的机构，需要提供平台与放贷机构间的合作协议。目前多数现金贷平台都将芝麻分作为征信的主要手段之一。芝麻信用一下子收紧了与现金贷对接的通道，被抛弃者只能筹划替代芝麻信用的风控方案和其他可选的数据源。凑巧的是，另一互联网巨头腾讯的信用分于近期上线。11月19日，广州的用户可以凭借腾讯信用分申请摩拜免押金。腾讯信用分的定位与芝麻信用分如出一辙。目前，腾讯信用分尚处于灰度测试阶段，需要拥有公测资格的用户才能查询分数。不过，蚂蚁金服并未透露此次终止合作的现金贷平台数量。 +http://money.163.com/17/1122/00/D3QBUPJM002580S6.html +亿利集团15亿中期票据未足额兑付 信用等级为AA + + （原标题：亿利集团15亿中期票据未足额兑付 刚被大公国际提高评级至AA+） + 亿利集团15亿中期票据未足额兑付 刚被大公国际提高评级至AA+ 值得一提的是，亿利集团是上市公司亿利洁能（600277，SH）的大股东，截至今年三季报，亿利集团持有上市公司亿利洁能49.16%的股份。对此，《每日经济新闻》记者第一时间联系到相关公告中披露的亿利集团的联系人张宝，对方表示，钱已经打出去了，因为大额系统关闭，钱款没有全部划出去，有一部分钱打过去了，有一部分没有打过去，明天系统开了，钱就到了，不影响明天兑付。亿利集团：拟补偿投资者一天的利息《每日经济新闻》记者注意到，该中期票据发行总额15亿元，本次计息期债券利率7.5%。稍早前几日，亿利集团曾发布了一份落款为本月15日的兑付公告，公示了相关兑付事宜。蹊跷的是，为何又在21日被上海清算所直指其未足额划付付息兑付资金呢？记者第一时间联系到相关公告中披露的亿利集团的联系人张宝，对方表示，钱已经打出去了，因为大额系统关闭，钱款没有全部划出去，有一部分钱打过去了，有一部分没有打过去，明天系统开了，钱就到了，不影响明天兑付。记者还注意到，在上海清算所发布公告后，11月21日当晚，亿利集团在其官网上发出了《亿利资源集团有限公司关于上清所11月21日有关公告情况说明》以作回应，称已知悉情况，并表示，11月21日大额资金支付系统关闭前，所兑付中票资金有部分未能及时进入银行间市场清算所股份有限公司账户，亿利集团将于2017年11月22日第一时间完成划转剩余款项，完成“14亿利集MTN002”兑付，并拟补偿投资者一天的利息。亿利集团官网信息显示，该公司创立于1988年，现有员工近万人，总资产1000亿元，旗下有亿利生态股份、亿利洁能股份、亿利金融等板块。《每日经济新闻》记者注意到，亿利集团即为上市公司亿利洁能的控股股东，亿利洁能三季报显示，亿利集团持有其49.16%的股份。亿利集团2017年三季度合并及母公司财务报表显示（下称均为合并口径），期末货币资金余额105.2亿元，期末短期借款余额122.94亿元；期末流动资产合计394.27亿元，期末流动负债合计379.42亿元；资产总计988.19亿元，负债合计593.81亿元，所有者权益合计394.38亿元。当期实现营业收入380亿元，归母净利润4.79亿元，经营活动产生的现金流量净额40.19亿元。丹东港集团未足额兑付被下调至Cwind数据显示，上述中期票据“14亿利集MTN002”最新债项评级为“AA+”，评级机构为大公国际资信评估有限公司，并且该评级是在今年6月15日刚刚调高的，上次评级是AA。如今却被惊爆未足额兑付。《每日经济新闻》记者发现，这是近一个月内第二家被爆出中期票据未足额兑付的案例。与此类似的是，半个多月前的10月30日，上海清算所同样发布公告称，“14丹东港MTN001”未足额划付付息兑付资金，丹东港集团有限公司（以下简称丹东港集团）发行的2014年度第一期中期票据被曝未足额兑付。不过在次日即10月31日，上海清算所即发公告称，已收到丹东港集团2014年度第一期中期票据（代码：101473011，简称：14丹东港MTN001）的付息资金，并按发行人指定的方式于当日完成了该期债券付息支付工作。彼时尚未爆出未足额兑付之前，联合资信评估有限公司（下称联合资信）对丹东港集团主体长期信用等级的评级为“AA”级。2017年6月6日，联合资信出具跟踪评级报告，维持丹东港主体长期信用等级为AA，评级展望由稳定调整为负面，并维持“14丹东港MTN001”、“15丹东港MTN001”和“13丹东港MTN1”的信用等级为AA。而在10月30日当晚，丹东港集团被爆出“14丹东港MTN001”未足额兑付之后，联合资信便出具公告称，确定将丹东港集团主体长期信用等级由AA下调至C，将“14丹东港MTN001”、“15丹东港MTN001”和“13丹东港MTN1”的信用等级由AA下调至C。 +http://money.163.com/17/1122/07/D3R38BPK00258169.html +万科5个月后再涨停股价创新高 宝能浮盈超400亿 + + （原标题：万科5个月后再涨停股价创新高 宝能浮盈超400亿元） + 据悉，31.79元/股（前复权）的股价不但创下历史新高，也使得万科的市值达3417亿元，若以港元计算，则是首次突破4000亿港元。值得注意的是，万科董事会主席郁亮日前在接受新华社采访时指出，“高速扩张期过后，中国房地产行业已经到了危急关头。提出房地产行业属性的回归，不仅是中国经济稳健成长的需要，也是房地产行业自身发展的需要。”他表示，“下一步万科要在恢复住房的居住属性、回归房地产初心上作出努力和贡献。万科计划数年后，成为全球领先的住房租赁企业”。而2016年，万科已经推出了第一个长租公寓品牌——泊寓。不过，眼下商品房销售仍是万科的最核心业务，今年10月份，公司实现销售面积247.8万平方米，销售金额367.9亿元。前10个月，公司累计实现销售面积2912.3万平方米，销售金额4328.9亿元，较上年同期增长39%。有业内人士指出，按照目前的销售节奏，如无意外，万科全年的销售肯定会超过500亿元。 +http://money.163.com/17/1122/07/D3R2PSL7002580T4.html +外教资质调查:无资格证者多 中介称3000元可代办 + + （原标题：外教资质调查：无证者多，外教资格证可以“买”） + 据艾瑞咨询联合励步英语发布的《2016年中国少儿英语学习白皮书》，现阶段，约六成的家长让孩子通过线下培训机构学习英语。师资力量（如老师的知名度）及结构（如是否有中外教）成为众多家长选择培训机构的最主要标准。一位曾在英语培训市场工作多年的业内人士向记者表示，如今绝大部分家长在送孩子学习外语时，都更倾向于有外教进行授课的机构。“在他们看来，外教来自英美等国，口语自然更纯正。”巨大的英语培训消费市场，以及家长们的态度，让越来越多的培训机构大打“外教牌”。记者调查发现，国内多家培训机构的外教，大部分是“无证上岗”，甚至有的还是机构“包装”而成。有的外教则是旅游途中“顺便”兼职当老师。而家长对外教是否有相关资质并不清楚，他们在意的是“外国人”这个身份。记者走访：“看不到”的外教资格证近日，记者以“给家中小孩报名学英语”为由，走访了廊坊周边多家英语培训机构。对于记者要求看外教老师是否有相关资格证书，有机构人员表示“不方便提供”或者“资质不重要”。在一家以“纯外教上课”为卖点的机构里，大厅四周墙上挂满了学员照片，10多位家长坐在大厅椅子上，通过监控电视看着孩子和外教上课的场景。前台工作人员热情地介绍称，机构为纯外教上课，同时配搭1名中教老师辅助教学。“我们这边有2名女外教，4名男外教，都来自美国、英国、加拿大等以英语为母语的国家，在上课前我们也会进行严格的培训。”当记者咨询这个“培训”是能获得教师资格证的培训，还是机构自己开设的培训课程时，该人员表示是“机构自己做的”。记者随后咨询外教老师是否有教师资格证或者TESOL等证件，该人员称，自己手中并没有这些证件，也不清楚外教是否拥有类似资质，需要带孩子来参加试听课时，向外籍老师或者课程顾问进行咨询。记者追问能否立即咨询课程顾问以及外教时，对方表示，“顾问全部在外面，没有人在机构现场。”外教是否会向家长出示资格证？现场一位家长告诉记者，自己孩子已经上了快2个月课程，从没看到类似资格证。此前他也听说过外教需要资质才能上课，但孩子在体验课时特别喜欢外教，自己也觉得老师水平不错，因此对资质并不在意。“只要孩子喜欢，能学到东西就行。”另一位家长则向记者表示，自己曾因为机构给不出资质，而去打听过其他培训机构。但问了一圈后，几乎没有任何一家愿意提供资质证明。无奈之下，只能选择这家看上去环境更好，就读孩子更多的培训机构。“不愿意出示证件的培训机构，很大可能没有资质。”一位业内人士向记者表示，“他们通常会以邀请你上体验课，让孩子感受氛围等各种理由进行推诿。”在另一家少儿英语培训机构里，前台人员向记者介绍称，该机构对于外教选择十分严苛，必须要拿到大学毕业证才能进入机构进行教学，“我们的英国籍外教是硕士学位，是有资格教大学的，而且他在中国做儿童教育已经有4、5年时间了，这方面完全不用担心。”但当记者提出能否看一下外教资质时，对方一再表示“不方便提供”。“资质不重要，重要的是看孩子学得怎么样。”一位外语培训机构负责人在记者咨询旗下所聘请的外教资质时，毫不讳言，“我们机构里面有4位外教，就一位有TEFL资质，其他的都没有，但扎实的授课能力还是吸引了很多学生报名。”记者调查了解到，不少英语培训机构尽管公示了外教简历，但却没有公示外教资质证书等信息。上述业内人士表示，如果要在网上进行资质查询，不仅需要外教姓名，还需要资质证书编号，缺少其中一项都无法查到。“这正是很多培训机构的‘底气’，反正你也查不到。挂出来也无所谓啊。”培训业者：“大部分外教无教学资质”“家长不知道外籍教师同样需要教学资质，他们只要看到金发碧眼的老外上课，就会下意识地觉得没问题。”经营着一家英语培训机构的林琳（化名）说。2015年，当过多年英语老师的林琳辞职后，在老家开了一家针对3~12岁年龄段学生的英语培训机构。为了彰显“专业”，她特意邀请到2位留学国内的外国朋友在她的机构担任老师。“当时确实担心过朋友没有教学资质，无法赢得家长信任的问题。”林琳向新京报记者回忆，但她很快发现，自己的担心是多余的。前来咨询的家长对外籍教师是否持有教学资质并不清楚，通常在得知老师来自英美等以英语为母语的国家后就再无其他问题。而事实上，在国内从事英语培训教学，同样需要相关资质。11月20日，记者致电中国国家外国专家局时获悉，外国人要在国内英语培训机构从事外教工作，必须要持有外国人工作证，同时国籍必须是母语为英语的国家。此外，在国内培训机构工作的外教还必须是本科以上学历，两年相关工作经验的业内人士。“如果外教持有TEFL或者TESOL证件，可以放宽两年工作经验的要求，但据外专法（2017）36号文规定，前提是必须持有外国人工作证。”专家局相关人士向记者解释道。新京报记者了解到，国内外教资格证书主要有两种，一种是被全球普遍承认的TEFL英语教师资格，一种是“对外英语教学”的TESOL资格。而国内培训机构的这些外教老师，很多没有在中国执教的资质。“这几乎就是业内的潜规则。”林琳解释说，“国内很多培训机构心知肚明，不少所谓的外籍老师，都没有TEFL或者TESOL等从事教学资格的相关证件。”“现在市面上的外籍老师很多没有资格证。”此前曾开设过英语培训班的王希（化名）说，学生家长并不了解外教需要持有资质才能从事教学工作，他们往往更在意的是外教“口音纯不纯”，以及“是不是白人”。“2015年我聘请了3位教师，其中2位金发白皮肤的都来自挪威，母语根本不是英语，在留学中国之前也从没当过老师。而真正有着多年教学经验的是一位来自美国的黑人。”但让王希无奈的是，几乎所有的家长都更希望孩子能参加白人所带的培训班，“家长自己不会英语，因此他们很难考量教师的教学水平，都下意识觉得白人老师英语水平更好一些。”新京报记者在调查英语培训机构时同样发现了这一情况，多家机构工作人员都特意提及机构的老师“全部为白人”。根据博思数据发布的《2017-2022年中国英语培训行业市场投资前景分析及投资前景研究咨询报告》，2015年我国英语培训行业市场规模约1042亿元。预计到2020年，中国英语培训市场规模将突破2200亿元。“国内教育培训机构的高酬劳吸引了不少外国人。其中大部分是半路出家，没有任何教学资质的外行。”林琳说。Paul在一家省会城市做外教招聘的工作，每个月会通过各种网络社交渠道招聘五六十名外教，月薪在13000元-15000元之间。“中国这么大，每个城市的外教需求是不均衡的，所以行业标准也有差异，是否要求拥有教学资质，是由需求关系所决定的。”Paul举例，比如北上广深这样的大城市，国际化程度高，外教市场起步早，而且比较成熟，薪资水平高，外国人聚集很多，所以对外教要求比较高。但在中国东北、西北地区的城市，薪资较低一些，外国人愿意主动去的少，对外教资质的要求就会低一些。“过去十年，外教市场发生最大的变化是，外教涨薪的同时，资质合格的教师却并没有随之增加。”Paul表示，“2009年我们花9000元月薪就可以很容易招到外教，但现在13000元-15000元依然很难找到完全符合资质的外教。”对于国内大多数外教没有从事外语教育资质的说法，Paul表示认同。他说，“确实如此，但并不是所有的外教都没有资质，一些急于招聘外教的机构会降低门槛来招更多的外国人，伪装成实力雄厚、资历深的样子。”中介：“办证”价格数千元，“无证”会被压薪水记者走访了北京七八家外教中介机构，以及有外教的教学机构发现，直接向教学机构应聘时，TEFL、TESOL资格和本科以上学历为基本要求，但向外教中介机构咨询时，几种证件都有“价格”。有中介称3000-6000元可搞定。来自希腊的女生Kris想在中国从事外教工作，虽然来自非英语母语国家，但她大学学习英国文学，可以讲不带口音的标准英语，没有教学经验。“有资格证的话最好，大机构喜欢招，很好介绍工作。”她在中关村一家负责外教中介的机构咨询应聘时，一名中介告诉她，“如果来自美国、英国、加拿大和澳大利亚等几个英语母语国家，本科学历以上，有2年以上工作经验，并且有TEFL或TESOL，在北京找外教工作的话可以进入一些大的英语机构，至少在月薪2万元以上。”“Kris这种来自非英语母语国家的外国人应聘外教，用人机构会担心她有口音。而且比起资质，更注重她是否有教学经验。”该名外教中介表示，“工作签证是基本条件，否则就算是打黑工，用人单位现在怕麻烦，都很在意这一点。而TEFL和TESOL可以自己考，我们也可以代办，价格在4000元左右，大概需要一个半月时间。”“有无资格证，收入差别很大。”该外教中介说，“非英语母语国家的外国人收入不会太高，而且没有资格证和经验，只能推荐到一些小的外语机构去，薪水非常低，大概只有几千块，还不到有资质外教薪水的一半。如果是非英语母语国家，但有资质，就可以达到1.5万元左右。”为何有资质和无资质区别如此大？该名中介解释称，“用人单位都想少发工资，如果没有资质或者经验少，就会被狠压薪水。”Kris又联系了位于海淀区的几家外教中介机构，对方都表示，“可以先来面试聊聊，资质可以慢慢补，课程是设计好的，主要教四岁到十几岁年龄段，只要简单培训就可以上岗工作。”新京报记者还以为学校招聘一名外教为名，拨通了回龙观一家外教中介机构的电话，一位负责人为记者介绍了一名拥有“TEFL”和多年外教经验的美国教师，期望月薪2.75万人民币。她表示，工作签证和教师资格证，都可以代办。工作签证代办费用由用人单位支付，约6000元，而如果一定需要教师资格证的话，可以由该名外国教师自己办理，费用由他承担。当记者询问，办理教师资格证是否复杂时，该中介机构负责人说，“如果他在国外办理教师资格证，需要去驻华大使馆进行认证，在中国的话办起来比较简单，在线上课就可以，不到一个月可以拿到。如果着急让他入职，我们可以帮忙代办，但需要收取3000元费用。”“我们办理的话很快就可以办好。”该负责人说，但具体代办渠道不便透露。包装出的外教：“改国籍”变身英国教育专家有的培训机构用“包装”的方式打造“资深教师”。开过英语培训班的王希就曾把挪威朋友宣传成“英国资深教育专家”。据媒体去年报道，中泰证券研报分析，婴儿潮奠定K12市场规模未来5~10年的增长基础。全国K12英语市场规模保守估计为7296亿，未来5年将以10%~30%速度增长。但持有教师资质的外教缺口严重，导致只要是外籍人士，都成为不少中小培训机构心目中的“教师”人选。“不少机构为了彰显‘纯正’，都打着外教来自英美加等以英语为母语的国家，但市场中哪有那么多合适人选？”王希表示，“这时就需要按照家长心中的人选，将外教进行‘包装改造’。”此前王希曾因为缺少“母语为英语”的外教人士，而将自己的挪威朋友，在宣传中以“改名”和“改国籍”的方式，将对方包装成一名“英国资深教育从业者”。“其实非常简单。就是在培训机构所印发的传单，以及海报上修改而已。”王希回忆称，当时在得知自己的想法后，朋友曾一度担心被家长发现而提出反对，但在王希“提高薪酬”的诱惑下最终还是答应了。王希的底气在于，这两位朋友在来中国之前，曾在英国生活过多年时间，无论对城市地理的了解，还是英语口语发音，都和当地人相差无几，不熟悉的人根本听不出差别来。“当时我们打出资深英国教育培训专家招牌后，确实吸引了大批家长前来咨询报名。”那段时间里，两位外教没露出任何破绽，也没有家长提出检查护照、资质等要求。几乎全部学生以及家长都不知道面前这些“教育专家”，其实是没有任何教学资质的外籍普通工种人士。记者在调查时发现，“伪装身份”已成为部分中小培训机构在业内发展的方式。一位曾在中国当外教的外籍人士接受媒体采访时承认，从未从事过教育的他曾先后收到多个机构的邀请，约其担任外教。而身边的朋友也有着被包装成其他国家，甚至连机构老板或许都不清楚其真实国籍的经历。上个月，林琳开设的少儿英语培训机构合作的外教向她递交了辞职信，他们计划着去另一个城市旅行，顺便再以“外教”的身份寻找下一家培训机构。林琳也开始在市场中寻找其他的外籍人士作为外教，“不管此前有没有教学资质或经验，只要是有一张金发碧眼的脸，都能成为外教。”“黑外教”：教学和安全或难保证“外教如果没有工作证的话，就如同是在打‘黑工’。无论是从安全角度还是教学角度都难以得到保证。”11月21日，一位培训机构业内人士向新京报记者表示。“其实很多外教在教学水平上并没有中籍老师教得好，毕竟他们没有经过系统学习。”王希称，“事实上，其中不少外教是来中国旅游的，以兼职形式到培训机构授课。这种情况造成的影响就是流动率高，课程质量不好保证。说不准孩子才适应了，外教就换人了。”记者在调查时了解到，一些没有资质的外教来华所办理的签证并不是工作签，而只是留学或者旅游签。这种签证受时间限制，外籍人士在签证到期回国，很容易造成培训机构人员频繁流动。往往持旅游签的外教本身并不是教育工作者，此前未接触过教学工作，加上流动频繁，学生或许难学到有价值的课程。“孩子最初参加的培训机构在一年内换了2、3位外教老师，每个教法都不一样，孩子也没学到什么东西。”记者在走访一家少儿英语培训机构时，一位家长无奈地表示。去年，哈尔滨开展严厉打击外国人非法从事教学活动的专项行动，对百余家外语培训、幼教机构进行拉网式清查，共查处涉及4个国家的“黑外教”7人。这些“黑外教”大多是在校留学生，有的是刚刚留学毕业的无业人员，没有任何从事教学工作经验和相关部门认定的从业资质证明，普遍存在发音不清、语法不通、拼写不准的问题。另一方面，外教人员的不稳定性也暴露出一定的安全隐患。根据媒体此前报道，国内多地爆出过多起外教事件，如外教在授课时对女学生进行性骚扰，有性侵前科外教在国内任职多年等。“看似‘黑外教’只是缺少一个资质证，但实际上危害很大。如今市场虽然逐渐规范，但还是存在培训机构聘请黑外教的情况。我认为必须要整肃目前培训机构聘请外教资质混乱的局面。”上述业内人士表示。“很多机构都不会和外教签订工作协议，就是单纯的合作，甚至连工资都是私下以现金的方式支付，这样才能避免因外教资质问题拖累机构。”王希说。新京报记者 覃澈 任娇 +http://money.163.com/17/1122/05/D3QSORE0002580S6.html +遭美司法部起诉 AT&T854;亿美元收购时代华纳遇阻 + + （原标题：遭美司法部起诉 AT&T854;亿美元收购时代华纳遇阻） + =导读市场认为，这一行为是美国政府目前为止“最激进”的监管措施。AT＆T是美国两大电信巨头之一，旗下还拥有美国名列前茅的卫星电视服务商，以及海量的家庭宽带用户。时代华纳集团是全球知名的电视媒体巨头，旗下拥有HBO、CNN等知名电视台，以及好莱坞制片商华纳影业公司。2016年10月，美国电信运营商AT&T宣布收购时代华纳，双方董事会均已批准该计划。交易涉及的总权益为854亿美元，总交易规模1087亿美元，其中一半通过现金支付，另外一半将以换股形式完成。在一份长达23页的诉讼中，美国司法部认为，这笔交易可能会让付费电视订户和竞争对手面临涨价的处境，并妨碍网络视频的制作。此外，其竞争对手的消费者，可能被迫转移到AT＆T的服务之下，以便能够继续观赏时代华纳集团的电视节目和内容。针对司法部指控，两家巨头给出的理由是该并购为垂直交易，而此前有很多垂直并购的先例。在11月20日晚间，AT&T和时代华纳召开的联合发布会上，AT&T首席执行官Randall Stephenson称政府的说法“不符合逻辑”。AT&T法律顾问David McAtee在声明中进一步提出，“司法部针对收购提出的诉讼激进且令人费解，背离了此前数十年反垄断事务的惯例。垂直并购通常会被批准，因为它使消费者受益，同时不会消除市场上的竞争者。”垂直并购指合并涉及的公司无直接竞争关系，业务却互有补充。AT&T拥有有线电视、无线和卫星传播业务，时代华纳则生产内容，拥有好莱坞“六大制片厂”之一的华纳兄弟、出品了热门剧集《权力的游戏》的HBO、知名媒体CNN等。类似的大型垂直并购案例曾在奥巴马政府得到批准。2011年，美国最大的有线电视公司康卡斯特收购了NBC Universal，该案在联邦通信委员会（FCC）审理13个月后，最终获通过，同时设立了一系列附加条件。“我们没有找到我们的并购交易被区别对待的理由。”David McAtee表示。他补充称，AT&T相信法官将驳回美国司法部的起诉。新上任的美国司法部反垄断部门负责人Makan Delrahim曾在此前演讲中表露出对待反垄断交易的严苛态度。“应该首先使用反垄断法来阻止交易，而非依赖于 行为纠正方案 。”“行为纠正方案”被设计用于企业兼并之后保证市场公正的竞争以及保护消费者权益。诉讼消息迅速成为美国市场最大的新闻。市场认为，这一行为是美国政府目前为止“最激进”的监管措施。AT&T首席出庭律师丹尼尔·彼得罗切利（Daniel Petrocelli）周一对记者表示，AT&T准备尽快进入审判阶段。他们认为，该诉讼将在4月22日交易截止日期前给出结果。11月20日当日，AT&T收于34.64美元/股，微涨0.38%；时代华纳收于87.71美元/股，下跌1.14%。美国电信行业目前正在经历一次大规模重组，随着竞争加剧，利润率下降，电信公司纷纷涉足了媒体内容行业，希望通过电视广告、网络广告等获取更多收入。最近，媒体传出默多克旗下的美国21世纪福克斯公司计划对外转让部分电影和电视资产，竞购者中除了迪士尼公司之外，还包括了Verizon、康卡斯特等电信服务公司。这不仅仅是特朗普政府上台后的第一个反垄断大案。美国政府前任反垄断事务官员Gene Kimmelman表示，司法部反对AT＆T收购时代华纳集团，将成为当代最重大的一宗反垄断诉讼和事件。司法部的举动将为未来包括其他领域的并购监管定调。 +http://money.163.com/17/1122/07/D3R3HOAD002580T4.html +中国移动宽带用户直逼中国电信 固网市场临洗牌 + + （原标题：中国移动宽带用户直逼中国电信固网市场面临洗牌） + 联通管理层面临挑战中国移动移动用户总数达到8.80935亿户，月增322.7万户，低于上月的398.1万户（上月有校园新增市场），与前9个月新增平均数相当。4G用户达到6.28668亿户，月增691.1万户（上月不足500万户），但仍明显低于前9个月的平均值。有线宽带用户达到1.06996亿户，月增357.1万户，低于上月的449.1万户，但明显高于前9个月的平均增长。可以看出，在经历了9月份混改元月的红火增长后，联通10月份月增移动出帐用户、4G用户、有线宽带用户都低于两个对手，且月增移动用户和有线宽带用户数明显低于电信和移动。独立电信分析师付亮指出，这表明联通要想缩小与竞争对手的差距并不是一个容易的事。而且随着两大竞争对手陆续推出低资费大流量的套餐，模仿联通推出互联网合作套餐和日套餐，联通的资费优势也开始减弱。互联网套餐向老用户放开，还将进一步拉低用户增长数。下一步如何应对，对联通管理层是一个挑战。固网宽带市场面临洗牌尤其在联通以往的优势业务固网宽带市场，在中国移动的强力竞争下，市场也面临重新洗牌。付亮指出，10月份的有线宽带市场，中国移动继续高歌猛进，中国电信稳步增长，而中国联通再次跌回个位数。在中国移动低价、免费的政策下，中国联通应对乏力，这还只是用户数，如果计算宽带业务的收入和利润，在两强夹击下，中国联通相关业务的下滑非常明显。而有线宽带业务，本来应该是联通重要的“粮仓”，现在的收获已很难让人满意。事实上，在原本中国电信和中国联通“双雄争霸”的固网宽带市场，2016年才正式进入市场的中国移动，在进入当年就超过了中国联通，成为了固网宽带市场的第二名。通过移动业务补贴，中国移动在全国推出了极为优惠的固网宽带资费套餐，低价宽带以及捆绑销售对消费者具有巨大的吸引力。如此，中国移动的固网宽带用户以狂飙式速度增长，不断蚕食着电信联通的领地。继2016年10月底，中国移动宽带用户数首次超过中国联通之后，经过近一年的高速发展，终于突破1亿大关。2017年，作为第二大宽带运营商，中国移动逐渐与中国联通拉开距离，并且与中国电信的差距也在逐渐缩小，冠军宝座似乎指日可待。业界专家预计，按照中国移动近几个月每月净增300万左右的增速，中国移动极有可能在两年内挑战中国电信有线宽带市场第一的地位。今年5月份联通股东大会上，中国联通董事长王晓初在提到固网宽带业务竞争时表示，宽带的竞争确实激烈，资费上受到很大冲击。对此，王晓初在会议上提出相关应对措施。“从微观层面，价格有必要做一些调整，但是我们不做主动的价格调整应对，而是更多从内容和服务方面入手。内容方面，增加更多特色、有差异化的内容；服务方面，中移动主要是包干给社会的企业，而在这一块我们是有优势的。另外一块，我们通过融合的方式，加快移动用户和宽带用户的融合，来解决问题”。 +http://money.163.com/17/1122/07/D3R3GN5E002580T4.html +中青旅实际控制人恐生变 中国旅游集团入主概率大 + + （原标题：中青旅实际控制人恐生变 中国旅游集团入主概率大） + 11月21日，中青旅紧急发布关于重大事项停牌的公告显示，中青旅及控股股东中国青旅集团公司涉及重大事项，该事项可能会导致公司实际控制人的变更，公司股票自2017年11月21日起连续停牌。查看中青旅股权结构显示，中国青旅集团公司及其一致行动人共持有中青旅股权20%，是中青旅第一大股东，而中国青旅集团公司同时也是团中央4家直属企业之一。对于上述消息的发布，中青旅公司相关负责人也觉得很突然，但对于由谁来入主，公司方面也并不清楚。实际控制人生变11月21日，中青旅发布公告称，公司及控股股东中国青旅集团公司涉及重大事项，该事项可能会导致公司实际控制人的变更。鉴于该事项尚存在不确定性，为保证公平信息披露，维护投资者利益，避免造成公司股价异常波动，经公司申请，公司股票中青旅，自2017年11 月21 日起连续停牌。查看中青旅股权结构显示，中国青旅集团公司作为国有法人持有中青旅17.17%股权，为第一大股东。前十大股东中还有中青创益投资管理有限公司，持股比例为2.83%，中青旅表示，中青创益投资管理有限公司为中国青旅集团公司控股子公司，其他股东之间是否存在关联关系或是否属于一致行动人尚不清楚。也就是说，中国青旅集团公司合计持有上市公司中青旅的股权比例为20%。而中国青旅集团公司同时是团中央4家直属企业之一，中青旅的现任董事长也是来自团中央。2015年年底，康国明被选举为公司董事长，查看其履历发现，康国明长期在团中央工作。事实上，关于中国青旅集团公司引入新的股东，中青旅实际控制人发生变化的传闻由来已久。中青旅方面相关工作人员也表示，这则消息虽然发布突然，但也不是无迹可寻。《证券日报》记者发现，在发布上述公告之前，公司高管人员就开始发生变动，2017 年 1 月份，公司独立董事陈业进申请辞去公司独立董事职务，为填补空缺，公司第七届董事会提名翟进步为独立董事候选人，并经2016年度股东大会选举为公司第七届董事会独立董事。今年9月1日，中青旅发布公告称，公司董事会于近日收到董事会秘书王蕾递交的书面辞职报告。因个人原因，王蕾申请辞去公司董事会秘书职务并同时辞去在公司下属控股子公司及参股子公司的一切任职，王蕾辞职后，将不在公司担任任何职务。有业内人士表示，在公司实际控制人发生变化的情况下，后续人事方面会否有持续变动还未可知。中国旅游集团入主概率大值得注意的是，2016年，经报国务院批准，中国港中旅集团公司与中国国旅集团有限公司实施战略重组，重组后中国港中旅集团公司更名为中国旅游集团。中国国旅集团将持有的中国国旅的股份全部划转至中国旅游集团，中国旅游集团成为中国国旅控股股东。此前中国国旅有关工作人员在接受《证券日报》记者采访时表示，重组完成后，中国国旅将依托中国旅游集团的资源优势，从客源、渠道、资源三方面来促进国旅股份在旅游产业中的发展布局。而对于中青旅来说，如果中国旅游集团与中国青旅集团公司重组会有哪些好处呢？查看公司2017年半年报发现，从营业收入分行业来看，中青旅排名靠前的业务分别为旅游产品服务、整合营销服务、酒店业以及景区经营业务，其中，旅游产品服务以及整合营销服务营业收入比上年分别减少12.68%和17.08%，收入有所增长的业务为资源型的酒店业和景区经营，同比增长12.81%以及11.38%。换句话说，中青旅的核心优势仍是景区业务。中青旅方面也表示，公司中青旅遨游网在维持营收规模的同时毛利有所提升，整合营销业务受 MICE 整体市场环境及大项目周期变化影响业绩有一定下滑，景区业务在高基数基础上继续保持稳定增长，山水酒店业绩实现高速增长，策略性投资稳中有升，继续贡献利润。2017年上半年公司实现主营业务收入47.61亿元，与上年同期基本持平；实现净利润3.47亿元，较 2016年同期增长9%。而拥有国资背景的中国旅游集团优势更多的还是资源型业务，如果上述三者合并也并不能形成绝对优势，“各个旅游公司业务的重点有所不同，虽然说合并重组确实能增强实力，但其它业务为主的旅游企业也有自己的生存空间。”上述业内人士补充道。 +http://money.163.com/17/1122/09/D3R87IMG002580T4.html +外媒：富士康工厂非法使用学生加班组装iPhone X +金融时报消息，苹果(Apple)在亚洲的主要供应商雇用学生非法加班组装iPhone X。厂家在遭遇生产延迟之后正竭力赶上需求。这些年龄介于17岁至19岁的学生说，他们被告知，在这家工厂工作三个月，是为了获得“工作经验”，使他们能够毕业。 +http://money.163.com/17/1122/07/D3R2MPRU002581P1.html +股价一度暴跌30% 趣店急推1亿美元股票回购计划 + + （原标题：遭监管暴击后紧急宣布回购 趣店跌幅急剧收窄） + 而后现金贷板块跌幅集体收窄，趣店更是明显反弹，跌幅由盘前30%以上收窄到开盘后11%左右，最终收盘跌幅不足4%。周二盘前，趣店美股一度大跌逾30%，距离历史最高点跌逾60%。此前多家媒体称互联网小贷牌照的发放被紧急叫停。临近开盘，趣店宣布，未来12个月内将回购不超过1亿美元的A类普通股ADS。趣店盘前跌幅收窄到20%以下。开盘后跌幅进一步收窄，早盘跌幅一度在6%以下，最终收跌约3.7%。趣店、信而富、拍拍贷、宜人贷、融360跌幅截图 来源：谷歌财经互金整治办：部分“现金贷”业务存在较大风险隐患文件称，近年来，有些地区陆续批设了网络小额贷款公司或允许小额贷款公司开展网络小贷业务，部分机构开展的“现金贷”业务存在较大风险隐患。文件要求，自即日起，各级小贷公司监管部门一律不得新批设网络（互联网）小贷公司，禁止新增批设小额贷款公司跨省（区、市）开展小额贷款业务。《证券时报》还提到，接近监管人士透露，监管部门后续或出台规范网络小贷公司的相关管理办法，可能会涉及提高未来网络小贷公司批设门槛的内容。业内人士：互联网小贷牌照价格已达5000万 料将上行这个新政对现金贷平台影响较大，因为现金贷业务迎来整顿的可能性很大，它们都迫切希望通过持牌去解决放贷业务的合规需求，牌照暂停批设，意味着它们只能通过有限的存量牌照来解决合规问题。 +http://auto.163.com/17/1121/09/D3OOHDF4000884NK.html +电动车闯红灯撞奥迪负全责赔3万 "弱者"别任性 +版权声明：本文版权为网易汽车所有，转载请注明出处。“闯个红灯，几个月的工资没了，以后再也不敢这么任性了。”肖先生后悔地说到。而网友的评论更是“炸”了，纷纷为司机伸冤，称电动车违法导致事故担全责是“活该”。行人或者非机动车闯红灯，在许许多多人身上已经根深蒂固，甚至成为了日常行为习惯，不少司机对此抱怨，“其实我们才是‘弱势群体’啊”。前车斑马线避让行人致追尾 后车承担全部责任今年5月份，在陕西西安一辆私家车因为斑马线前礼让行人突然停车，被后方驶来的车辆追尾，两车碰撞严重，前车的后备箱被撞凹进去，而后车的前引擎盖也变形严重，由于冲击力大，后车的安全气囊弹开，所幸事故并无人员伤亡。交警对此表示“后车都要跟前车保持安全车距，而且保持安全车距这个责任完全在后车。”也就是说，在本案中，后车违反规定与前车距离过近，造成紧急刹车时后车追尾，对此造成的损失，后车应承担全部责任。大妈闯红灯被拦拔刀袭警后“躺尸”9月5日，南通市集中整治非机动车的违法行为，一个闯红灯的女子的被拦下来之后，情绪激动，连说了几声“呸”，面对警察执法，竟然掏出了一把刀。交警：放手！你这个情绪不能开车子！违章女子：呸交警：不要激动行不行！违章女子：呸。交警：不要激动行不行！刀拿出来了！交警王鹏回忆称“她从随身携带的挎包中，拿出一把水果刀，当场使用暴力阻碍民警执行公务。”在执法过程中，民警吴志勇的右手被划伤，为了避免这个女的拿刀再误伤到其他人，民警立即将她制服并夺下她手中的刀。在被夺刀后，该女子立马倒地“躺尸”。vote(v60874)【往期回顾】163个用车姿势(94)无故变道加塞怎么罚?一图看懂常见违章扣分标准163个用车姿势(93)因变道女司机被跟踪3月并拍裸照 女性外出需警惕163个用车姿势(92)"路怒"爆表:50万奥迪堵收费口被后车连撞5次报废163个用车姿势(91)宝马X5只卖39000刚买就被扣 低价购车当心"犯罪"163个用车姿势(90)女司机挂过期临牌上高速被扣12分 号牌动不得手脚163个用车姿势(89)为拒朋友借车百万豪车拒买商业险 车子外借需谨慎163个用车姿势(88)女司机停车2天4个轮胎全被调包 停车当心奇葩小偷163个用车姿势(87)遥控解锁车辆致液化气罐爆炸 私家车不得非法运输163个用车姿势(86)"送学"客车核载44人竟挤76人 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车型简介新一代国产凯美瑞的2.0L和2.5L都会提供运动版（锋尚版）车型，运动版车型的外观要比普通版更加激进运动，混动版的外观则和普通版保持一致，只是加入了一些专属标识，前不久我的同事刚刚实拍了运动版车型，下面我们就围绕运动版车型做简单介绍。第八代凯美瑞运动版和普通版看上去的差异比较大，运动版设计了专门的前后保险杠、格栅、大灯、排气、尾翼和轮毂，混动版则是在普通版的基础上加入了一些专属标识。其实三种版本的外观在当前市场的中型车中都算运动风格比较浓郁的，第八代凯美瑞的运动版在细节上更进一步，前脸中部为X型大嘴，雾灯区域还有加大尺寸的辅助格栅装饰，这些让它显得更加激进。运动版车型提供了双侧四出的排气，配合全新车机的后保险杠让它平添了一份霸气。并且，运动版尾灯的两个装饰绝对算得上点睛之笔，简单的勾勒就让它比普通版多了不少韵味。车身及内饰颜色选择新一代凯美瑞除了提供六种单色车漆外，还有两种专为运动版车型设计的双色车身，在六种单色车漆中有一款海钻蓝是混动版的专属，所有车型选择铂金珍珠白都要额外支付2000元，运动版车型选择红黑双色也需要加2000元，运动版如果选择铂金珍珠白+黑的双色搭配就要加4000元，这是丰田在车身颜色上的一贯策略。此外内饰也提供了三种颜色，其中红色内饰是2.5L运动版的专属。丰田当前在售的车型内饰基本都是一板一眼的规矩设计，谈不上不好看，但是很难分泌让你兴奋的激素。在第八代凯美瑞上，我们终于看到了丰田在内饰设计上“飘”的一面。除了雷克萨斯以外，在丰田当前的车型上，我们绝少见到一丝发飘的设计，在第八代凯美瑞上，我们对丰田内饰的印象也将被改变。这一次，第八代丰田凯美瑞很不“丰田”。凯美瑞的内饰做工依然保持着较高的水准，无论是包裹的皮质还是覆盖的装饰板，在接缝处理和做工上都很令人满意，现在的年轻人多数时间都接触者优质的东西，凯美瑞的作用和用料这些细节能打动他们的挑剔心。第八代凯美瑞纵向空间上的表现还是比较出色的，当前的中型车后排空间都越做越大，新凯美瑞在这一环节上也表现不错。新一代国产凯美瑞提供三种动力系统，分别是2.0L+6AT、2.5L+8AT和2.5L混动+ECVT，2.0L发动机还提供两种调校，不过差别几乎可以忽略，其中最亮眼的当属2.5L+8AT的组合了，搭载的2.5L发动机拥有40%的全球最高热效率，这要比带T的发动机更加难得。※ 配置分析一、2.0L怎么选？既然提供三种动力系统，那咱们就按照动力来逐一分析，先来看看2.0L的入门版，也就是全系的入门车型怎么样？入门版表现如何？2.0E 精英版  售价：17.98万先来看一下全系的入门车型，2.0E精英版在基础安全性配置上是比较齐备的，特别是标配的10气囊在同级中是比较罕见的，此外LED大灯也是一个亮点，在其它配置方面，入门版基本处于同级的主流水准，但倒车雷达和影像的缺失肯定会给消费者带来不便，带来了事后加装的麻烦，概括起来就是，入门版的配置有亮点，但也有小缺陷，算是个值得考虑的入门版车型。三款普通版怎么选？三款2.0L普通版车型使用一台发动机，但顶配豪华版在调校上要比另外两款高了1kW和2N·m，这是可以忽略的差别，选车时不用去考虑它，主要还是来看配置吧。精英版和领先版的配置差别主要就是座椅材质和调节方式，所以差价也只有1万元，如果不反感皮质座椅的话，领先版的性价比应该是高于精英版的。再来看豪华版，配置确实配得上2.0L顶配的地位，从外观、安全配置、科技配置和舒适配置上都有了显著提升，最关键的是终于有了倒车雷达和倒车影像，这么多配置，价格上也只比领先版贵了1万，所以对于准备购买2.0L的消费者来说，豪华版应该是最值得推荐的车型。2.0L运动版值不值？别忘了2.0L还有一款2.0S锋尚版，也就是我们俗称的运动版，它在整体配置上和2.0G豪华版比较接近，具备更加动感的外观套件和多种驾驶模式，但在座椅材质和调节方式上做出了牺牲，由于只比豪华版贵了6000元，所以里外里两车性价比基本打了个平手，要不要运动版就看您自己的喜好了。二、2.5L怎么选？2.5L值不值得选？2.5L车型的动力系统还是比较值得购买的，首先发动机的动力要更加充沛，而且还有新的8AT变速箱，能够提供更加平顺的驾驶感受，无论是技术含量还是动力水平，都是比较大的卖点，如果对动力多少有些要求的话，2.5L肯定是更合适的选择。但由于2.5L的起步配置比较高，最低也要接近22万元，导致性价比降低，所以可以预期的是，未来新凯美瑞的销售主力还是2.0L车型。2.5L选哪款？2.5L普通版只有两款车型，旗舰版代表了新凯美瑞最高的配置水平，豪华版其实已经很丰富了，旗舰版则是又加了一个更字，又添加了一些科技和舒适配置，几乎已经武装到了牙齿，所以价格也就并不那么亲民了，比豪华版足足贵了4万元，如果选择2.5L的话，豪华版的性价比要更高一些。2.5L也提供了运动版车型，就是2.5S锋尚版，它的配置和2.5G豪华版相近，差别可以参照2.0L对比的内容，锋尚版具备更加动感的外观套件和多种驾驶模式，但在座椅调节方式、全景天窗这些地方做出了牺牲，两车价格差别只有3000元，性价比差不多，如果想将动感进行到底，那运动版显然更如意一些。三、混动版怎么选？混动版值不值得选？这是个比较俗的问题，也很好解释，同配置的混动版要比汽油版2.5L贵了2万，配置上没什么差异，计算下差价和油费的关系就都知道值不值了，车辆使用频率越高肯定就越值得考虑混动版。混动版选哪款？和2.5L一样，混动版也是提供了豪华版和旗舰版两款车型，配置差别也与2.5L车型一致，旗舰版比豪华版贵了4万，所以从性价比的角度来看，豪华版肯定要高一些。推荐车型：毫无疑问是性价比最高的车型，也应该是未来的销售主力2.5L+8AT动力是很大的卖点，只可惜较高的配置拉高了售价如果用车频率很高，这是个很实惠的选择结语：2.0L车型未来一定会是新一代凯美瑞的销售主力，因为它具备最突出的性价比，其实我个人更喜欢2.5L车型，不过它的配置起步较高，影响了性价比，但为技术买单我还是觉得值得。至于混动车型，出于使用成本的考虑，它不会适合所有人，而且随着本田、通用混动技术的兴起，丰田在这个领域也已经不是唯一的选择了。 +http://auto.163.com/17/1122/11/D3RHKE6B0008856R.html +化妆后更美 奥迪Q3三十周年版售24.9万起 + + +http://auto.163.com/17/1121/20/D3PUN6KH0008856R.html +售199.8万 阿斯顿·马丁全新Vantage首发 +外观：扁平的车头和贯通式尾灯是全新Vantage的显著标志，整体外观与DB11并不是很相像，更像是整合了DB10和Vulcan的特点打造而成。全新Vantage后包围造型比较繁复，拥有着现役量产车型面积最大的后扩散器，贯通式尾灯则将马丁车型优雅的线条很好的勾勒出来。内饰：华丽的内饰走的标准英式跑车的风格，清晰的功能布局比较简约，一切以突出驾驶为主，用料也十分考究。坐在车内，所有的元素都会引导你握紧方向盘，踩下油门踏板，这种呼之欲出的动感体现在每一个针脚、每一项数据上。全新Vantage标配360度全景摄像头、胎压监测系统与前部和后部泊车传感器以及泊车距离显示。车载娱乐方面，8英寸中控屏提供车载信息娱乐系统包含阿斯顿·马丁音响、蓝牙音频和电话、iPod 和iPhone、以及 USB 设备接口。此外，全新Vantage还内置卫星导航系统。动力：虽然外观跟DB11差别较大，但动力方面则是实打实继承了DB11的总成，全新Vantage采用DB11铝质架构的缩短版本，搭载来自梅赛德斯AMG的4.0T V8双涡轮增压发动机（V8 Vantage），这款性能强大的铝合金发动机被置于前轴之后且位置极低，以优化车辆重心并实现接近50:50的均衡重量分配。最大功率510马力，最大扭矩685牛·米。全新Vantage通过后置的ZF 8速自动变速箱将强劲的动力与扭矩传递至后轮。新车0-100公里/小时加速时间为时3.6秒，最高时速可达314公里/小时。配合采用的Skyhook技术，可提供三种驾驶模式：运动（Sport）、运动+（Sport Plus）和赛道（Track）模式。全新Vantage现已开始接受预定，中国市场的厂商建议零售价是199.8万元人民币。新车预计将于2018年第三季度开始在中国市场交付。全新Vantage依旧是阿斯顿·马丁家中的入门级超跑车型，其对手主要是梅赛德斯-AMG GT R、保时捷911 GT3等车型。 +http://auto.163.com/17/1122/07/D3R1GO97000884MM.html +上海62名新能源车主被4S店诈骗 涉及近300万元 +（原标题：上海62名新能源车买主被4S店诈骗 涉及近300万元）4S店销售员口中的补贴，或许也是陷阱。购车款被4S店销售员骗走2017年1月11日，赵伟接到李磊电话，声称已为他垫付24万多元购车款，让赵伟把钱打给他。当日，赵伟来到4S店与李磊签订了销售合同，却没有收到购车发票。李磊表示发票等提车时一起给他。“当时李磊穿着工作服戴着工作牌，是4S店的员工，我想这么大一家4S店应该不会有骗子。”赵伟说，他于是通过微信、支付宝、银行转账等方式，分五次将24万多元转账给李磊。赵伟开始陆续听到传言，许多车主上了李磊的当。他拿着相关购车材料到4S店了解情况，被工作人员告知购车合同上的公章是假的。赵伟于是报案。“我觉得4S店有不可推卸的责任。”一名被骗取定金的被害人表示，“我每次打电话想确认他们公司关于补贴办理及其他费用时，他们总是告诉我找对接的销售顾问，导致我无法确定自己是否被骗。”一年骗取新能源汽车补贴20万元检察院透露，李磊因为自己的资金链断裂，才诈骗了赵伟的购车款。2015年9月，李磊到上述新能源汽车4S店担任销售。当时新能源汽车享有国家及地方性政策补贴，上海嘉定区和浦东新区还有额外的区域性补贴。另外，据李磊供述，2015年该新能源车品牌厂家有14000元的厂家补贴，但4S店并不知情，销售员会直接向厂家要返利。为了瞒住4S店，销售员会先向客户索要这笔钱，垫付来平账，之后厂家再将该笔钱返给客户。通过这样的操作方式，李磊会从补贴中抽头一部分，2015年，他靠这种方式赚了约20万元。补贴下不来，开始“拆东墙补西墙”李磊交代，2016年嘉定区新能源车补贴政策的红头文件还在，当年第一季度，他通过这种方式下了约50辆汽车订单，收取了约50万元补贴定金。其中三分之二的钱给了“黄牛”和同事作为好处费。然而，他供述：“不知道为什么，过了三个月后，客户还没有拿到该有的补贴款。于是，他们都来找我给要补贴。但是我收的钱很多都给了黄牛和介绍来的销售，自己的部分也已经花完了，实在没有钱给他们。”于是，李磊就铤而走险，继续向后来的客户收取补贴定金，一部分给黄牛和介绍来的销售，另一部分还给之前要求退订的客户。他想只要等补贴下来了，就好办了。此外，厂家的14000元补贴，其实在2016年12月已停止，但因为李磊资金链断裂，他之后继续骗客户有这个返利，要求对方交定金，来偿还债务。2016年至2017年4月，李磊共收取了一百多台车辆的地区补贴款，近两百万元，但由于区域性新能源汽车补贴没有下来。他只能拿新客户的钱还旧债，欠债的雪球越滚越大。闵行检察院表示，李磊以非法占有为目的，采用虚构事实、隐瞒真相的方式，骗取他人财物，数额巨大，其行为已触犯《中华人民共和国刑法》第二百六十六之规定，涉嫌诈骗罪。近日，闵行检察院以涉嫌诈骗罪批准逮捕李磊。 +http://auto.163.com/17/1122/08/D3R6JLPJ000884NK.html +挪威最新研究结果显示:女司机开车更安全 +版权声明：本文版权为网易汽车所有，转载请注明出处。据悉，测试分为两组展开，第一组研究对象是1100名高中生，其中208人有驾照。第二组研究对象是414名普通挪威人。研究人员调查了两组人开车时分心的频率和原因，以及他们对待开车分心这件事的态度。结果显示，在所有人中，受收音机影响是最常见的分心原因，其他明显差异体现在年龄和性别上。年轻男性、经常开车的老司机及性格外向的人是最容易开车分心的群体。另外，那些认为自己驾驶时“一切尽在掌控”的人也容易分心。但是，年纪较大的女性和那些认为自己“能够控制自己不分心”的人的确开车时较不易分心。研究人员还发现，手机拥有率的快速增长是造成司机开车时不注意路况的重要原因。 +http://auto.163.com/17/1122/09/D3RALIKG000884NK.html +高速突发团雾引连环追尾致18死 警惕"移动杀手" +据现场反馈，连环交通事故造成交通堵塞3-4公里，30余辆车连环相撞，有1处着火点，4辆车起火(2辆客车、1辆物流车、1辆水泥槽罐车)。车主刘先生回忆道，现场能见度很低，很多车辆撞在了一起，“当时我紧急踩了刹车，但是后面的车还没来得及反应，直接就撞上来了。”刘先生表示，自己车前方的车也都相撞，“后面的车也都一辆辆追着撞了”。“我的车出事的位置相对靠前，而事故中起火的客车，在我们后面。”突遇“团雾” 50余车相撞2016年4月，沪蓉高速4月1日，沪蓉高速常州段往上海方向过横林枢纽4公里处，因雨天路滑，前方两辆大货车不慎相撞翻车，导致后方数十辆车相继追尾相撞。公安部消防局次日发布通报称，现场共有56辆车追尾，21人被困。据现场多位司机当时介绍称，事故发生前，突然看到一大块团雾，然后就看不清前方，大家就减速，因为团雾来得突然，司机“哎呀”叫了起来，紧跟着发生了追尾。结果就像放鞭炮一样，噼噼啪啪连环追尾，大家都撞在了一起。苏州的王先生也说：“我的车速不快，突然，我发觉前面有一片白雾，刚准备减速时，已经撞上前面的车了，我的车还没停下，后面的车就撞上了我的车。”王先生说，他觉得很奇怪，高速上怎么突然有白雾。“或者是前面的车，车速太快了，甩出来的水雾?”团雾在气象学中称为辐射雾，直接使贴近路面的气层变冷而形成的雾。团雾往往出现在大雾中数十米到上百米的局部范围内，雾气更浓，能见度更低，具有突发性、局地性、尺度小、浓度大的特点，因此，被称为高速公路的“流动杀手”。气象专家表示，普通的辐射雾或平流雾形成后，范围可能达到上百公里，但是“团雾”的范围仅仅有几公里，甚至几百米。受风力影响，“团雾”可以移动。“移到高速上，就会对交通造成很大影响。”vote(v62931)【往期回顾】163个用车姿势(95)电动车闯红灯撞奥迪负全责赔3万 "弱者"别再任性163个用车姿势(94)无故变道加塞怎么罚?一图看懂常见违章扣分标准163个用车姿势(93)因变道女司机被跟踪3月并拍裸照 女性外出需警惕163个用车姿势(92)"路怒"爆表:50万奥迪堵收费口被后车连撞5次报废163个用车姿势(91)宝马X5只卖39000刚买就被扣 低价购车当心"犯罪"163个用车姿势(90)女司机挂过期临牌上高速被扣12分 号牌动不得手脚163个用车姿势(89)为拒朋友借车百万豪车拒买商业险 车子外借需谨慎163个用车姿势(88)女司机停车2天4个轮胎全被调包 停车当心奇葩小偷163个用车姿势(87)遥控解锁车辆致液化气罐爆炸 私家车不得非法运输163个用车姿势(86)"送学"客车核载44人竟挤76人 校车安全不能打折扣163个用车姿势(85)曾因违停被罚不满 车窗内侧贴条:开罚单者死全家163个用车姿势(84)北京10名肇事逃逸司机终生禁驾 逃逸罪如何量刑?163个用车姿势(83)因小事故下车理论致堵7公里 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剐蹭豪车到底该怎么赔163个用车姿势(26)四人组团开二手奥迪入水沟骗保险110万元163个用车姿势(25)可恶的高速倒车 同行美女竟还跳操遮挡车牌163个用车姿势(24)违停民警训交警:你这娃儿不懂事163个用车姿势(23)比女司机还危险的老年代步车163个用车姿势(22):酒驾出事被查 无证驾驶20年163个用车姿势(21):交警在什么情况下能扣车?163个用车姿势(20):豪车美女"借"钱加油日薪上万163个用车姿势(19):别急着交钱 你的罚单有"水分"163个用车姿势(18)划车真不能泄愤 最高可判7年163个用车姿势(17)不收拥堵费 开车走"水"路进京163个用车姿势(16)停着的车被"撞"死人 还得担责163个用车姿势(15)遮挡号牌下跪可免罚你get了吗163个用车姿势(14)两岁女童在车内着火该怎么救?163个用车姿势(13)给新车"开光"就能保平安了?163个用车姿势(12)两车腾空飞起只因司机看手机163个用车姿势(11)故意刹车不让救护车致人死亡163个用车姿势(10)轻微事故对方全责竟然又反悔?163个用车姿势(9)为何大"祸"车总爱出事?163个用车姿势(8)女司机27分钟熄火23次163个用车姿势(7)精神病肇事如何担责?163个用车姿势(6)撞了5万的狗该怎么赔?163个用车姿势(5)按一声喇叭竟被罚17万163个用车姿势(4)不求人!汽车DIY大保健163个用车姿势(3)开车这样加塞才不被骂163个用车姿势(2)学校周边应这样行车163个用车姿势(1)与使牌车剐蹭就吃哑巴亏? +http://auto.163.com/17/1122/07/D3R27HV4000884ML.html +丰田称电动车仍不适合大规模量产 特斯拉并非对手 +Autoblog援引德国《明镜周刊》（Der Spiegel）报道称，丰田汽车董事长内山田竹志（Takeshi Uchiyamada）在接受采访时表示：“长续航里程的电动汽车非常昂贵，而且充电时间还非常长。这种汽车并不符合我们的项目规划。”内山田竹志表示：“特斯拉并不是我们的敌人，也不是我们的行为榜样。我认为，德国的汽车制造同行们才将特斯拉当做竞争对手。”宝马以及梅赛德斯均认为，品牌可以依赖传统车型，并提供相应的全新电动版车型，无视那些怀疑主义者言论。怀疑主义者认为，宝马以及梅赛德斯需要更为激进前卫的设计风格，才可以成功抵御特斯拉以及其他汽车初创公司的竞争威胁。内山田竹志表示，丰田正在攻坚一款全新的固态电池，电池可以储存更多能量，而且充电时间要比现有版本的电池快得多。内山田竹志说：“固体电池技术将是一个重大的研发步骤，但这需要一定的时间。我们预计，固体电池将在4到5年的时间里实现量产。”此外，上周五，丰田与铃木表示，双方同意从2020年左右起，在印度市场上合作销售电动汽车，以实现双方在新兴市场以及零排放技术方面的互帮互助。 +http://auto.163.com/17/1122/08/D3R7AT9B000884NK.html +司机背景调查不力 Uber被罚款达890万美元 +版权声明：本文版权为网易汽车所有，转载请注明出处。科罗拉多州公共事业委员表示，该机构已经对Uber罚款890万美元，原因是Uber违反了该州的司机资格认证法。委员会发现，尽管存在重罪前科、交通违规或驾照吊销等问题，仍有57名司机在过去一年半来从事Uber司机工作。科罗拉多州公共事业委员会称，在被当地警方告知一名Uber司机涉嫌骚扰乘客后，他们在今年早些时候开始对Uber进行调查。委员会称，他们利用法院记录和州犯罪数据库对Uber提供的司机信息进行了交叉审查，发现许多Uber司机存在案底。该机构表示：“调查发现，有12名Uber司机被判重罪，17名司机曾有重大交通违规行为；3名司机曾被吊销驾照，63名司机存在驾照问题。”委员会表示，在科罗拉多州提供运输服务的公司必须对司机进行背景审查。据悉，如果Uber能够在10日内付清罚款，罚款金额就可以减半。针对此事，Uber发布声明表示，该公司发现了不符合科罗拉多州共享乘车监管法的程序错误，并且已经主动通知科罗拉多州公共事业委员会。2017年以来，Uber一直状况不断，除了受到包括行贿、性骚扰、性别歧视等指控，海外监管部门的禁令也对公司业务造成打击。新任CEO Dara Khosrowshahi上任后，不得不从企业文化开始，对Uber进行彻底整顿。 +http://auto.163.com/17/1122/11/D3RFED580008856R.html +将于明年初上市 宝骏730混动车型申报图 + +http://auto.163.com/17/1122/10/D3RCIC7U0008856R.html +推出2年就换代 北宝全新X55将2018年上市 + +·六边形大嘴式格栅激进动感，侧面采用悬浮车顶设计，车尾排气镀铬饰条增添质感，长宽高分别为4480/1809/1680mm，轴距为2665mm；·内饰方面参考绅宝X25，预计还将延续借鉴奔驰式的风格，配备悬浮式中控屏和较有个性的空调出风口，三辐式多功能方向盘将用银色装饰条点缀；·搭载代号为A151E-1的1.5T涡轮增压发动机，由北汽自主生产，最大输出功率为150马力，匹配6速手动和CVT变速箱供选择。编辑点评：X55是北汽绅宝的第二款SUV，基于2012年广州车展亮相的北汽C51X概念车打造，量产版在2015年上海车展首发并在2016年1月正式上市，而在2017年上海车展上，北汽绅宝全新X55亮相，在2018年一季度就要上市，2年的时间就完成更新换代，真的是"北汽速度"。 +http://auto.163.com/17/1122/11/D3RGPM0D0008856R.html +以SUV为主 北汽幻速明年至少推出5款新车 +幻速H5·幻速H5是一款定位高于幻速H3F的MPV车型，这款车采用了全新的X型前脸设计，车身的造型十分硬朗，尾部通过贯穿式的镀铬装饰拓宽了尾部的视觉感。新车的内部采用了棕黑双色搭配，线条简洁稳重，整个车内部给人的感觉比较内敛，符合家用MPV的定位；幻速H5·该车将搭载一台1.3L涡轮增压发动机，最大功率133马力，最大扭矩185牛·米，与之相匹配的将是一台CVT变速箱；幻速S6X·幻速S6X在一些外观细节上有所调整，网格状的前格栅替代了原来的横条式的设计，尾部方LOGO换为了英文样式“HYOSOW AUTO”；幻速S6X·动力依然采用1.5T发动机，最大功率为150马力，峰值扭矩为215牛·米，并提供5速手动、6速手动和CVT三种变速箱可选；·对于幻速S4和幻速S8，目前的具体信息仍不是很多，官方也没有对外公布太多信息。据悉，这两款车都会定位7座SUV车型，此外，幻速S7 2.0T车型也会在2018年上市。 +http://auto.163.com/17/1121/10/D3OQVP100008856R.html +18款车型/两种排量 大通T60汽油版上市 +·此次上市的大通T60汽油版车型，在车身方面新车提供大双和小双车型，以及高底盘和低底盘车型可选；·动力分为2.0T和2.4L两种不同排量的发动机，2.0T发动机的最大功率为224马力，峰值扭矩为360牛·米；2.4L发动机的最大功率为143马力，峰值扭矩为200牛·米，传动系统匹配的是6MT和6AT变速箱。 +http://auto.163.com/17/1121/11/D3OSMVAQ0008856R.html +广汽的新年礼物 传祺GM8或12月31日上市 +新车信息：·外观方面，新车基于2015年广州车展发布的i-lounge朗智原型概念车打造而来，传祺GM8和GS8一样采用了LED大灯的配置，矩阵式的灯头颇具设计感。高配车型LOGO下方集成有全景监控系统的前视摄像头，两侧后视镜下方也多了侧方位摄像头，此外前杠居中位置还有ACC自适应巡航系统雷达模块；·传祺GM8轴距3000m，车身长宽高5066*1923*1822mm，侧面是商务MPV标准的侧滑门结构，滑槽隐藏在第三排车窗的下方。一直延伸到后风档玻璃侧面的车窗，形成了悬浮式车顶的设计风格；·连体式的尾灯组是从i-lounge概念车延续下来的设计，同样是全LED光源的配置，长条形的示廓灯灯带一直贯穿整个尾部。后杠下方除了中置式的LED后雾灯，两侧还内嵌有对称式的排气管；·传祺GM8采用的是2+2+3的座椅布局形式，配备真皮座椅、自动空调、前排电动座椅、一键启动等配置。车身尺寸方面，新车长宽高分别为5066/1923/1822mm，轴距为3000mm。此外，新车配备有自动侧滑门； +http://auto.163.com/17/1121/10/D3ORLD42000884MM.html +一汽夏利停止征集受让方 正式转出动力总成资产 +一汽夏利在关于控股股东终止公开征集的公告中表示，公司于2017年11月 20 日收到一汽股份《关于一汽夏利重大事项情况的通 +知》，截至目前，《公开征集公告》中的公开征集期已届满，一汽股份未征集到符合《公开征集公告》中各项资格条件的受让方，因此，一汽股份决定终止本次公开征集。同时，一汽夏利在公告中表示，公司将于2017 年 11 月 22 日召开投资者网上说明会，并于说明会后复牌。据介绍，“投资者网上说明会”活动具体时间定于2017年 11月22日（星期三）14:00-15:00点，出席本次年度报告网上说明会的人员有：一汽股份有关负责人员、公司董事兼总经理、董事会秘书。另外，一汽夏利同时发布了董事会关于转让动力总成制造相关部分资产及负债的关联交易公告。公告称一汽股份已启动对动力总成资源整合工作，并设立了中国第一汽车股份有限公司天津乘用车动力总成分公司（以下简称“天津乘用车动力总成分公 司”），并将 +2015 年从一汽夏利的收购动力总成资产拨入天津乘用车动力总成分公司。因此一汽夏利与天津乘用车动力总成分公司在 +2017 年 11 月 20 日签订了《资产转让合同》，将一汽夏利公司下属的内燃机制造分公司和变速器分公司动力总成日常生产制造相关部分的资产及负债转让给一汽股份。根据一汽夏利公告，其动力总成制造相关部分资产和负债原文如下，（1）内燃机制造分公司，其前身为天津市内燃机厂，是本公司下属分公司； +变速器分公司，其前身为天津市汽车齿轮厂，我公司于 2003 年 12 月从公司原第 +二大股东天津汽车工业（集团）公司收购。 （2）本次公司向一汽股份转让的动力总成制造相关部分资产主要包括内燃 机制造分公司和变速器分公司的库存（原材料、在库周转材料、库存单品、在产 +品）和设备类资产（机器设备、电子设备）。 本次公司向一汽股份转让的动力总成制造相关部分负债主要为应付经销商账款。 +http://auto.163.com/17/1122/10/D3RDUMIO0008856R.html +终于换代了 英菲尼迪全新QX50预告图曝光 + +http://tech.163.com/17/1122/15/D3RSUVP700097U7R.html +腾讯宣布代理《绝地求生》后，Steam多了一波差评 + + （原标题：腾讯宣布代理《绝地求生》后，Steam上再遭遇一波差评） + IT之家11月22日消息 今天中午，腾讯官方突然宣布了一个重大消息：正式与PUBG公司达成战略合作，获得《Playerunknown's Battlegrounds》（《绝地求生：大逃杀》）在中国的独家代理运营权。腾讯官方表示，将协同PUBG公司为《PUBG》国服提供网络优化、服务器扩容、外挂打击等技术支持，营造积极、正向的游戏氛围，为用户们传递具有教育指导意义的游戏内容，尤其是为未成年人用户传递健康正向的文化理念和价值观导向。腾讯代理《绝地求生》是坐稳了，不过Steam这边又出现了一番新景象。因为腾讯代理《绝地求生》国服，玩家又逐渐开始在《绝地求生》的Steam页面上打差评了。从数据上来看，截止到现在，《绝地求生》Steam页面已经收到了近200个差评（不推荐），而这些差评中，几乎大部分都是关于腾讯代理《绝地求生》的。此前《绝地求生》就因为服务器差、挂多、打广告等遭遇过一大波差评。目前其在Steam页面的好评率为41%。大家感受一下▼ +http://tech.163.com/17/1122/22/D3SMRC0N00097U7R.html +小蓝单车CEO父亲被围堵:要钱没有 谁要钱给谁打工 + + （原标题：小蓝单车CEO父亲被围堵:要钱没有 谁要钱给谁打工） + 11月22日消息，小蓝单车CEO李刚的父亲李文生今日出现在北京，与从深圳等地赶来的供应商见面。除了与李刚的亲属关系之外，创业家&i黑马通过查询工商资料发现，李文生同时还是小蓝背后的天津鹿鼎科技有限公司最大股东，占股95%。供应商和运维人员等待与李文生协商在与原计划约定的供应商见面后，李文生将供应商带至由黑洞资本投资创始人张量创立的某联合办公空间，并声称今日将与小蓝单车的投资方联系，并推出新的解决方案。此前黑洞资本是小蓝单车的A轮投资方。截止到晚上八点，得知李文生出现的消息后，北京、天津等地未收到还款的十几位供应商代表，和此前小蓝单车的30多位运维人员陆续赶来，要求李文生与李刚通话，并拿出还款方案。李文生向供应商回应，目前可以协商，但没有能力还款。参与协商的供应商告诉创业家&i黑马，在与投资方的通话中，黑洞资本表示目前无能为力，而且自己也是“受害者”。李文生与供应商现场沟通自小蓝被爆出用户押金难退，和深圳小蓝单车公司被供应商上门讨债的问题后。11月16日下午，李刚对外发出声明，宣布小蓝单车与拜客出行达成战略合作，将小蓝单车日后的运营交由拜客出行全权代理。并承诺，完成技术对接后，押金用户将免费使用小蓝单车。对于大家的工资，会想尽办法尽快解决。但对于用户如何退押金以及供应商欠款的问题却只字未提。 +http://tech.163.com/17/1122/07/D3R3SCOM00097U7T.html +苹果承认富士康用学生组装iPhoneX 同时非法加班 + + （原标题：Apple admits student interns worked illegal hours on iPhone X production line） + 网易科技讯 11月22日消息，据9to5Mac报道，苹果已经证实了英国《金融时报》的报道，承认其代工厂商富士康公司利用高中实习生在其生产线上组装iPhone X，且存在非法加班现象。然而，该公司否认这些学生“被迫为其工作以允许毕业”的说法。《金融时报》的报道中涉及3000名高中学生，他们参加为期三个月的长期工作实习项目。6名高中生告诉《金融时报》，在中国郑州工厂组装iPhone X时，他们经常每天要工作11个小时。根据中国法律规定，学生加班属于违法行为。这6名学生说，他们是来自郑州城市轨道交通学校，9月份被派往台湾的苹果供应商富士康公司工作。这些学生年龄在17岁到19岁之间，他们被告知，在工厂工作三个月时间是想要毕业而必须完成的“工作体验”。一名18岁的学生声称，他们每天最多要组装1200部iPhone X，并说参与这项计划是强制性的。她说：“我们被学校强迫在这里工作，而这项工作与我们的研究毫无关系。”苹果已经证实，一项审计发现学生实习生的确非法加班，但否认他们被迫参与。苹果表示：“我们已经确认了这些学生是自愿工作的，并且得到了补偿和福利，但他们不应该被允许加班。”学生的法定工作上限是每周40小时。苹果定期对其供应商进行审计，以确保其遵守法律和该公司自己的规则和程序。富士康通常会在iPhone上市或销售旺季雇佣临时工，包括学生。但《金融时报》报道称，富士康通常会招募更多季节性员工，以期及时生产更多iPhone。延迟生产导致富士康第三季度利润下降了40%。（小小） +http://tech.163.com/17/1122/10/D3RD46GA00097U7R.html +狂飙!美国5巨头+BAT今年市值涨1.4万亿美元 + + （原标题：Tech Rally Goes Global, Powering Major Stock Indexes to Fresh Records） + 网易科技讯 11月22日消息，据华尔街日报报道，全球科技公司股票今年明显跑赢其它板块，创下自互联网繁荣时期以来的最大领先记录。少数几家大公司的强劲势头驱动着市场在全球各地的表现。这种态势在美国时间周二继续上演。纳斯达克综合指数上涨1.06%，2017年以来第67次创新高收盘，这一次数比以往任何一年都要多。苹果股价收涨1.9%，IBM上涨1%，微软也上涨1.4%，这三大科技巨头也因而成了道琼斯工业平均指数周二涨幅的最大贡献者。科技股的涨势提振了整个大盘。标准普尔500指数和道琼斯工业平均指数也双双创下新高，在前两周罕有地出现下滑以后迅速反弹。欧洲和亚洲的蓝筹股指数也呈现上涨。腾讯昨天收涨2.4%，日内涨幅一度让该公司的市值达到5300亿美元左右，超过Facebook的5280亿美元。这标志着科技股的涨势正在全球范围上演。腾讯周一首次突破5000亿美元市值关口。2017年，仅仅八家公司的合计市值涨幅就达到1.4万亿美元，相当于西班牙和葡萄牙的合计GDP。它们包括Facebook、苹果、亚马逊、Netflix、Alphabet、百度、阿里巴巴集团和腾讯。科技巨头们拥有极其强大的用户网络、庞大的现金储备和海量的消费者数据，因此很多投资者都认为强者愈强。“你需要一定的体量来支持持续性的创新。”Eaton Vance全球股权总监克里斯托弗·戴尔（Christopher Dyer）说道，“虽然有例外的情况存在，但中国和美国会是科技领域增量投资自然而然的选择。”正当科技公司帮助美国股市和部分亚洲股票市场创下新高，科技股权重相对较低的欧洲、加拿大和澳大利亚股市则没能取得同样的亮眼表现。摩根士丹利认为，对于MSCI（摩根士丹利国际资本）欧洲指数来说，它相对于全球股市的弱势大体上可以归结为科技板块的权重和表现差异。“毫无疑问，拥有高科技板块的市场今年将会是表现最好的市场。”投资管理公司Newton Investment Management全球股权投资组合经理保罗·马卡姆（Paul Markham）表示，“这轮上涨覆盖范围相对狭窄，肯定会引起一些人的担忧……但那些表现强劲的公司都是些现金产生能力很强的公司，都被视作是新经济的基石。”该公司也投资了多家大型科技公司。全球科技股票今年上涨了42%，涨幅约为MSCI全球指数的两倍。今年到目前为止，科技板块的涨幅比表现第二好的材料板块高出21个百分点——根据摩根士丹利的分析，这是自1999年以来任何一个板块的最大领先幅度。部分分析师认为，一旦投资者的热情减退，或者政府监管妨碍科技公司的发展，科技板块的统治性表现可能会让领先的市场不堪一击。不过，大多数分析师都觉得这在短期内不会发生，因为该领域的巨头在持续地取得出色的业绩，这意味着科技股未来几年可能仍然是全球市场表现最突出的一个板块。三星电子、腾讯、阿里巴巴和台积电在MSCI新兴市场指数中的合计权重达到17%，甚至高于Facebook、苹果、Netflix、亚马逊和Alphabet在标准普尔500指数中11%的权重。MSCI欧洲指数的科技股权重不到5%，明显低于MSCI美国指数的25%和MSCI全球指数的17%。科技并不是今年全球股市涨势的唯一驱动因素。全球各地的经济同步复苏，提升了人们的收入水平。人们持续寻求投资回报，除了股票鲜有其它的理想替代选择。今年节节攀升的科技板块也面临着风险，其中包括政府加强监管的预期，或者投资者纷纷跳出已经取得很大涨幅的板块。然而，一些分析师拒绝拿科技股当前的繁荣与互联网繁荣时期进行比较。美国科技股的估值相比互联网繁荣时期可谓不值一提。根据财经信息提供商FactSet的数据，2000年代初期，标准普尔500指数科技板块远期市盈率高达52倍。而现在，这一数字仅为19倍，标准普尔500指数整体的远期市盈率则是18倍。今年第三季度，标准普尔500指数科技公司表现超出预期，盈利增长率达到21%（接近于表现第二好的能源板块的两倍），创下单个板块的最大领先记录。许多的市场参与者认为这轮上涨仍有支撑。根据资金跟踪机构EPFR Global的数据，本月早些时候，它促使科技板块的周流入金额录得新高，其中来自美国和中国的科技基金尤其活跃。“1999年，科技股都极其昂贵，而且这些公司都没什么收入。”AllianceBernstein股权投资主管马克·菲尔普斯（Mark Phelps），“但现在，这类公司不仅持续地取得收入增长，它们还拥有更多的数据，能够给消费者提供非常出色的产品。”（乐邦） +http://tech.163.com/17/1122/21/D3SKDSRF00097U81.html +任晓平：不披露换头图片，因这是科学不是拍恐怖片 + + （原标题：新华访谈：换头术靠谱吗？去中国医生任晓平的实验室看看） + 写在前面：11月21日，承载着诸多公众疑问的哈尔滨医科大学教授任晓平就“全球首例人类头部移植手术模型”举办了简单的媒体见面会。现场，他并未回答澎湃新闻有关脊髓修复的核心问题，只展示了数篇纸质版论文和一段动物实验的视频。11月22日，新华网黑龙江频道刊发了《新华访谈：换头术靠谱吗？去中国医生任晓平的实验室看看》。该专访披露了任晓平实验室内的部分场景，以及实验狗的照片。不过关于两具遗体上进行“换头”的相关照片与视频，任晓平表示不便披露，“要考虑社会的承受度，因为我们研究的这个东西，特别是这个手术，它不是所有常人能接受的，我发表文章没有用实际的图，（尽管）所有的数据、影像、图片都有，我在杂志发表的文章插图是画家画的手术示意图，因为我们这是科学工作不是拍恐怖片。”访谈中，任晓平仍旧强调了他在该领域的诸多“突破”与“进展”。他称大鼠实验“大概存活率90%以上”，“狗的存活率在90%以上，最长的存活时间一年。这个模型今年早些时候也取得非常好的成果，这篇文章发表后引起国外同行的极大关注。”关于脊髓损伤修复问题，任晓平的描述是：“用一个锋利的刀在后背把脊髓完全切断，这个动物就截瘫了，不会动弹了，然后给它用一种化学试剂-聚乙二醇，在短时间内进行创面融合，脊髓神经几周后开始逐渐恢复功能。这份成果是在去年取得的，已经发表在美国著名的医学平台上。”《新华访谈：换头术靠谱吗？去中国医生任晓平的实验室看看》全文如下：换头术、头移植、异体头身重建术，这三个在科幻小说、悬疑故事中偶尔蹦出来的词汇，却因科研人员在人类遗体上完成头移植手术外科模型的消息被再次聚焦，一片惊叹声、质疑声中，新华网一行走进了哈尔滨医科大学骨科主任医师、博士生导师任晓平教授的实验室，面对面听他独家披露活体实验的最新进展，在人类头移植手术外科模型上取得的突破以及他对头移植未来走向的判断。任晓平在他的实验室接受新华网的专访。新华网 才萌 摄狗在脊髓损伤手术后各个时期恢复情况的拼版照片。新华网 资料图做过小鼠实验，我们开始做大鼠实验，共做了几十例，做的不是头（离断），而是头以下的脊髓部分，大概存活率90%以上。做完手术要长期观察它功能的恢复情况，有一部分动物可能因为并发症，在功能恢复之前就死掉了。目前大鼠最长的存活时间是一个月。这项成果今年中旬发表在一个神经科学治疗医学杂志上，现在我们又把这一部分成果往深去做。在实验成功的基础上，我们又开始大动物模式，做了20例左右的狗实验，狗的存活率相对来讲更好，因为狗比较容易护理。狗的存活率在90%以上，最长的存活时间一年。这个模型今年早些时候也取得非常好的成果，这篇文章发表后引起国外同行的极大关注。实验过程中难题不断产生，随着实验的进展找出相应的办法。比如说，我们做的是脊髓神经损伤模型，这是病发率、死亡率、伤残率极高的医学难题，做这样的模型护理起来工作量特别大，实验动物可能会截瘫，还可能由于运动功能没恢复长时间瘫痪，出现尿路感染、关节僵硬、肌肉萎缩等一系列问题，一切都是团队在实践中摸索出来的。现在我们的团队在这方面做得非常好，都不再出现这样的并发症了。任晓平(右上一)与意大利医生卡纳维罗（左上一）在美国的一次学术会议上相见。（翻拍照片） 新华网 才萌 摄我们要求这两具遗体从性别上、形态上、肤色上要尽量接近，这次实验是为了设计一个非常完美的外科手术方法：就是头移植怎么去完成，详细的手术步骤是怎么做的，每个组织如何进行解剖、切取、移植、连接、修复，这样才能保证术后这个功能最大的恢复，也就是说在医学史上还没有过的头移植外科手术方案。我们的团队第一次提出来头移植外科治疗方案，治疗方法这一部分已经总结成文章发表在美国的《神经外科杂志》上，文中详细地记录了我们用两具遗体记录建立头移植模型过程中的手术步骤和手术方法。它的意义非常重大。都说头移植是人类遥远的梦想，开始是科幻小说，在现代实验室里是西方最早开始探查，100多年前在美国芝加哥的一个实验室里进行了实验，后来就是苏联以及很多国家在做，哈尔滨医科大学赵世杰教授在中国做了第一例狗头移植。这些宝贵的经验都对今天我们的团队进一步深入研究这个课题、向临床转换提供了非常有价值的经验和科学指导，所以我们现在继续沿着这条路把这个课题背后的科学问题、技术问题更加有效地去解决。任晓平在指导学生做实验。新华网 才萌 摄找我的志愿者很多，总有电话打进来，有国内的，也有国外的。头移植是适应目前临床上治愈不了的头脑健康而身体已经不行了的患者，这样的患者非常多，等我们有一天在这些科学和技术问题都解决之后，我们会从这些患者中选出一个志愿者，但我认为现在还为时过早。2016年任晓平发表的部分学术论文。新华网 杨昊 摄就以前人类医学史上的各类经典的挑战性的手术来说，比如器官移植这方面，第一个肾脏移植手术，是1953年在美国完成的，当时也是面对着学术界以及社会上各方面的反对和不理解，大家认为不应该做或是觉得为时过早，认为人的死亡是正常的自然过程，人本身是不能干预的，但是莫雷医生还是义无反顾地和他的团队把手术完成了。从现在反观当时的那段历史，莫雷医生的手术对于人类医学发展做出了极大的贡献，没有他的坚持就没有移植学至今为止这么快速的发展。再比如1967年同样在西方完成的人类史上第一例心脏移植手术，同样也面临当时的诸多不理解与不支持。头移植相比之下具有更大的挑战性和复杂性，是人类医学史外科领域中最独特也最具挑战的，对于伦理这方面是肯定逃不过的，要面对伦理学的争论再争论，业界一直存在着相反两方面的意见。我们刚刚在美国的医学杂志上发表一个有关伦理学的公开辩论，我觉得这是一个非常好的形式，有争议拿到台面上来辩论。我们现在处于新的时代，我个人觉得是要与时俱进的，一个时代有一个时代的伦理标准，而且和一个国家对应的民族、文化、历史都有关系，有的时候可能不能完全对接，有一部分能对接，有一部分要相互合作和包容。 +http://tech.163.com/17/1122/18/D3S7I2V700097U81.html +太阳系其他行星环境多恶劣？金星探测器仅坚持2小时 + + （原标题：Extreme Conditions of Alien Worlds Damage Spacecraft Irreparably） + 网易科技讯 11月22日消息，据Futurism报道，“朱诺号”太空探测器是由美国宇航局下属喷气推进实验室控制的木星轨道飞船，它可帮助科学家们研究太阳系内最大的行星——木星。具体来说，“朱诺号”会向科学家展示木星的磁场，这是人类对木星磁场的首次观测。但这次观测是否会让“朱诺号”付出“生命”的代价呢？专家们已经开始权衡探索外星宇宙天体对我们探测器的危害情况。工作人员为“朱诺号”安装辐射拱顶木星的磁层在太阳系中是真正的庞然大物。它宽近500万千米，比太阳大15倍，是整个太阳系中最大的结构之一。但直到“朱诺号”于2016年夏天进入木星磁场，我们才得以直接“看到”这个巨大的结构。但是，探索如此宏伟的宇宙结构，我们需要付出什么代价？事实证明，探索这样的地方会给探索宇宙的飞船带来潜在的灾难性影响。木星的磁层包含来自太阳的带电粒子，它们构成了木星周围的辐射带。它比地球周围的范艾伦辐射带强数百万倍，这种强烈的辐射是对“朱诺号”的主要影响因素。为了在磁层中生存下来，“朱诺号”配备了巨大的钛辐射拱顶，它可以保护飞船最重要部件免受辐射影响。然而，一些关键仪器必须露在这个保护罩的外面，以观察它们的任务目标。为此，研究人员想出了很多方法来保护敏感仪器，同时获得尽可能多的数据。但是，如果仅仅是观测木星就如此困难，“朱诺号”对太空探索的未来是否一片黑暗？宇宙射线、各种严酷的条件，再加上极端的温度，使得宇宙冒险看起来似乎不太可能。曾经有些人认为金星上可能有潜在生命存在。但金星的表面布满了有毒的空气，这些空气时刻冲刷着燃烧的土地。在Glenn Extreme Environments Rig(GEER)，研究人员模拟了类似于金星的条件，化学家、材料科学家古斯塔沃·科斯塔（Gustavo Costa）将其描述为“地球上的地狱”，试图创造出能够承受这一恶劣环境的宇宙飞船。目前为止，这仍是一个没有完成的挑战。科斯塔说：“最新访问金星的探测器是Venera 13(1982年)，它只存活了2小时零7分钟。金星的腐蚀性非常强。”而当我们把目光扩展到太阳系更远的地方，我们的技术必须跟上。目前，除了极端温度和地表条件外，辐射似乎是宇宙飞船面临的最紧迫、最具威胁的因素之一。我们让“朱诺号”探索木星磁层可能需要付出高昂的代价，但随着科学家们向宇宙中进一步推进，相信会有新的方法在抵抗辐射的同时允许进行数据收集和观测。（小小）原文链接 https://futurism.com/extreme-conditions-alien-worlds-damage-spacecraft-irreparably/ +http://tech.163.com/17/1122/17/D3S57LB400097U7T.html +马斯克说他2030年前要实现这些目标，这忙得过来吗？ + + （原标题：Here’s a List of Everything Elon Musk Says He’ll Do by 2030） + 网易科技讯 11月22日消息，据国外媒体Futurism报道，亿万富翁、科技企业家伊隆·马斯克（Elon Musk）旗下的公司涉足各式各样雄心勃勃的项目，要跟踪其中每一个项目的进度并非易事。本文整理了马斯克旗下公司2030年要实现的目标。伊隆·马斯克：疯狂的梦想家马斯克手头上的事情绝对是多到忙不过来。他同时掌舵多家公司，每一家都明确制定了未来的发展目标。在特斯拉，他致力于推动电动汽车和可再生能源解决方案的发展。在SpaceX，他致力于给予人类殖民其它星球的机会。在Boring Company，他致力于改变交通出行方式以及打造更好的隧道。在OpenAI，他参与推动人工智能（AI）的良性发展。最后，为了强化人类大脑的能力，他创建了Neuralink。在如此多不同领域的公司有着如此多样的目标，一般人肯定驾驭不了。下面来看一下马斯克计划在2030年之前完成的事情：项目时间线该项目在9月份正式开始。到9月底，项目建设就已经完成了一半。与此同时，马斯克承诺今年年底以前开始交付特斯拉经过改进的SolarRoofs太阳能屋顶产品。接着说说Boring Company在洛杉矶的隧道项目。尽管马斯克还没有确切透露该项目的具体时间表，但我们可以推断——考虑到当前项目的推进速度以及当地政府的许可——该隧道交通系统可能会在未来几年完工，并开始投入运营。另外，这一年，特斯拉旗下的电动汽车充一次电可行驶的里程可能将达到1000公里。该公司还计划基于自有车辆提供移动出行服务。马斯克还有许多尚未确切时间或者还没有公布的项目。其中包括备受关注的Hyperloop超级高铁项目，马斯克决定让特斯拉或者SpaceX更多地参与该项目。另一个目前处于最早期发展阶段的项目是Neuralink，它意在将人脑与AI融合。很显然，马斯克手头有着各种各样的项目。可以预见的是，在推进这些项目的过程中，他多多少少都会遭遇一些挫折。不过，像马斯克这样习惯批评、嘲讽和质疑的科技领袖很有可能会带给我们惊喜。（翻译：乐邦，审校：王华春）原文链接 https://futurism.com/heres-list-everything-elon-musk-2030/ +http://tech.163.com/17/1122/16/D3S0DNNU00097U7R.html +福布斯：马化腾身家已超谷歌创始人 位列世界第九 + + （原标题：Tencent chief 'richer than Google founders'） + 网易科技讯 11月22日消息，据BBC网站报道，中国最大社交网络公司腾讯市值目前已经超过了Facebook。该公司拥有在中国极受欢迎的消息应用程序微信，并运行着英雄联盟（League of Legends）和王者荣耀（Honor of Kings）等广受欢迎的网络游戏。腾讯也是第一家超过5000亿美元（3770亿英镑）市值的亚洲公司。据《福布斯》报道，腾讯首席执行官马华腾的身价已经超过了谢尔·盖布林（Sergey Brin）以及拉里·佩奇（Larry Page）等谷歌创始人。根据《福布斯》周二发布的报告，马化腾身价约为483亿美元，位列世界第九。在宣布明年将在马来西亚推出微信支付服务后，腾讯股价一路上扬。此外，腾讯还拥有Snapchat背后的Snap公司，打车服务公司Lyft和电动汽车制造商Tesla的股权，公司还有望将其非常受欢迎的多人对战游戏“王者荣耀”引入美国，这款游戏让玩家付费升级他们的游戏角色或服装。现在，腾讯已经与苹果，亚马逊和微软等美国公司并驾齐驱。它旗下的明星应用微信在中国几乎无处不在，每个月有近十亿人使用它。现在，微信不仅是一个消息传递平台，用户还可以通过微信为购物付款，预订出租车，投资，外卖等等。腾讯希望把微信拓展到海外，而马来西亚则是第一个引入微信支付的国家，但是让中国以外的用户去接纳微信也许会遇到困难。（晗冰） +http://tech.163.com/17/1122/15/D3S03TPQ00097U7R.html +走访双十一快递：为何说我们离智慧物流没那么近 + + （原标题：线下走访丨触目惊心的双11快递“消化战”） + 作者：陈霞2017年双十一之后的第五天，上海浦东新区从一大早就乌云密布，后面开始下起了淅沥沥的小雨，吴师傅（化名）作为某快递公司的外包员工，正冒着雨将刚从瑞翔路分拨到附近营业网点的包裹“安排”进自己的小面包车内，整齐有序。吴师傅告诉亿欧，车内的包裹基本上都是按照地域来装车，“先进后出”便于按顺序派送。吴师傅做快递派送员的工作已经有一年多的时间，跟他签约的快递公司给他的价格是：每派出一件包裹就获得4元，今年双十一期间他平均每天可以送出100多件。吴师傅一边从一个个已经扫描装车的包裹上撕下带有收货人信息的面单一边告诉亿欧：“这些在你们看来只是普通的纸，对我们来说可就是钞票啊。”同样的时间，浦东新区东高路附近的一家快递营业网点中，刘师傅（化名）正在扫描准备装进自己面包车内的快递包裹时，发现扫描终端“不奏效”，告知该网点负责人后拿着负责人的手机正在进行扫描，扫描完成后发现淋过雨的快递面单比较难撕下来，网点负责人看到后“教了一招”说：“像这种撕不下来的单子就拿手机拍照记录下来也可以。”对于没有面包车派送，只有两个轮子车派送的临时快递员，个别派送费用只有3.5元/单，有时候工作慢了会受“上面的人”督促。据亿欧了解，很多网点负责人不直接参与包裹的派送，但是需要在凌晨3点就起来接车卸货，双十一期间要忙到多晚，有时候他们自己也不知道，只知道快递公司总部的要求是“当天要清仓”，否则在第二天就很容易出现“爆仓”。双十一刚好过去一周，物流资深人士鬼老二曾在朋友圈预测：接下来的一周是洪峰过后的分流，如果说双11上半场打的是产能战，下半场就是消化战了。为了具体了解这场“消化战”的战况，亿欧作者专程探访了几家快递转运中心及网点，据不完全统计，申通快递今年双11期间在浦东发出的订单就有10万，由20几个9米6高型货车从转运中心发出；百世在浦东新区的一个网点一周内发出的订单在6000单左右。11月16日晚8:30，在上海闵行向阳路附近的顺丰转运中心内，陆续会有中大型的货车驶进，带有顺丰logo标识的厢式货车驶出。仓库内，货物卸货、分拣、包装、打单、装车正在有序进行着。对于家俱类的大包裹要经过较长的流水线作业才能实现从卸货区到装货区的仓内分拣，而小件的包裹则只需要经过较短的流水线作业实现装车运输到下面的网点进行派送。当一整车货物从生产商运到顺丰的转运中心被分拣完成，而后面的整车货物还没运到的间隙，分布在各个流水线上的穿着亮眼颜色马甲的兼职人员则可以停下来休息一段时间。“我们是按照时间算，从早上9点到晚上9点，一天240元基本都待这儿了，男女兼职都一样按照小时计费，女兼职可以做做扫条码等简单点的活，比男的相对要轻松点”其中一位男兼职工张师傅向亿欧聊起，他家基本就住在仓库附近，正待业在家，对于双十一这项差事还算满意，“不过也就这段时间有，后面就不需要这么多人了”张师傅最后带着点失落感笑到。顺丰转运中心除了流水线上的自营和兼职人员外，也会有保安实时巡逻，因为仓库很大，不同的装货、卸货区都有出入口，对于人员的进出不好把控。一旦发现非工作人员未经过允许轻易进入其中，保安便会喊来顺丰仓库运营负责人一起检查“闯入者”的手机拍照记录，如果有拍照记录的会要求其连带回收站的照片一起删除，要做好对外的保密工作。为了完成今年双11定的目标，各大快递公司可谓是日夜兼程。快递公司总部的一个指标“每天要清仓”，但在仓库内还未发出的双11包裹又增添了好多新的“伙伴”，完成指标的压力落到了一个个分布在城乡结合部的营业网点。申通快递双11当天的订单已经由4米2大小的厢式货车从瑞祥路293号，拉到了浦东东陆路营业网点附近的门口，由于这个临时被用来当作临时“仓储”的厢式货车太长，完全挡在隔壁一家店铺门口，店老板劝了几次发现货车依然一动不动的时候开始破口大骂：“我管他是什么公司的车，就是不能挡在我门口！店里不要进人做生意啦？”东陆路附近的韵达网点人员告诉亿欧：今年派件压力跟往年比起来差不了多少，丢失件现象是少数，但发生了也不可避免。亿欧在走访中发现网点包裹“抛物线分拣”、“堆积如山”的现象简直不要太普遍。仔细一想如果让这些众包的快递员们在那么多的包裹中一个一个端着分拣似乎现在还无法全面实现，很多商家肯定也早意识到这点，所以在出库的货物包装上塞满“泡沫袋”“空气枕”、“空气柱”等，防止快递员在再次分拣时不小心带来的损坏。为了让快递订单“消化”的更快，各家快递公司很早就准备了大批量新设备的投入。上海邮政EMS曾表示在今年双十一期间率先使用AGV自动分拣机器人，亿欧在走访中无意发现EMS在一个临时站点的分拣情况，货物按照包裹的大小和区域分成多堆，依然是人工手持终端完成扫描后依靠人力搬到相应的区域。不可否认，我们当中很多人收到的快递仍然需要拣选多遍、靠着一个一个的快递员送到我们的手中，我们离智慧物流的距离其实没那么近。通过随机采访收货人亿欧发现：很多人直观的感受是今年的快递比往年到的快多了，大家普遍对顺丰快递的服务体验较满意。然而顺丰董事长王卫近日在接受央视财经专访时表示：顺丰并没有多快！他表示：之前认为的快可能是交通工具的投入造成了所谓的快，但未来对快的定义可能不一样。11月16日晚间中国电子商务研究中心发布《2017年“双11”电商平台大促评测报告》据星图数据检测显示，2017“双11”期间全网交易额达到了2539.7亿元，同比增长超45%。如果如菜鸟网络所说，今年的双十一是一次重要的“练兵”，我们在看到硕果累累的同时对需要“修补的短板”、流程的优化应该有更深的思考。 +http://tech.163.com/17/1122/15/D3RTVB1R00097U7T.html +中国3年内计划建15家半导体工厂，追赶日本韩国 + + （原标题：强劲追击！韩媒：中国高新企业发力超韩 动摇半导体格局） + 【环球网综合报道】腾讯市值20日首破5000亿美元，市值位列亚洲第一、世界第六。这可担心坏了邻国韩国的媒体，韩国《朝鲜日报》22日的一篇文章称，“不仅是韩国，这是连日本企业也无法企及的市值。而腾讯不过是最近中国技术崛起的一个案例。”文章称，中国企业腾讯、阿里巴巴、百度等在内需市场积累了竞争力，已经发展到了“威胁”美国硅谷的水平。腾讯2012年起跻身游戏和移动聊天工具世界第一和第二名，中国电商阿里巴巴11月11日光棍节的打折活动，仅一天就创下1682亿元的销售额，超过了美国的竞争对手亚马逊。在尖端制造业方面，中国也开始超越韩国。在今年三季度全世界售出的智能手机中，每10部就有5部(47.1%)是华为、OPPO、小米、VIVO等中国企业制造的产品。相当于排名首位的三星电子和排名第八的LG电子等韩国产智能手机的两倍。在韩国最领先的半导体领域，中国也开始了强劲追击。国际半导体设备与材料协会(SEMI)的统计显示，在今年到2019年的3年里，中国计划建设的半导体工厂共达15家，比同期韩国(3家)、日本(4家)加起来还要多。《华尔街日报》推测说：“仅是中国为支持半导体产业而设立的基金，就高达1000亿美元以上。”文章还称，中国半导体企业明年起将正式生产由三星电子和SK海力士主导的存储芯片，预计将撼动世界芯片行业的版图。对此，韩国汉阳大学科学技术政策学系教授金昌经说：“中国半导体至少能在短期内掌控巨大的本国市场”，“韩国半导体产业不能陶醉在史无前例的最佳业绩中，应该具备可能被中国夺走尖端制造业主导权的危机感。” +http://tech.163.com/17/1122/11/D3RHI0PG00097U7R.html +顶级科技大佬高端闭门会议，你也有机会参加！ +那么接下来，福利来了！！！如此顶级科技大佬高端闭门会议，你也有机会参加！你将获得与这些科技大佬零距离的沟通机会！希望你：欢迎邀请各位届时关注本次峰会，与众多顶级科技大咖共同交流智慧见解。 +http://tech.163.com/17/1122/22/D3SKVFSD00097U7R.html +福布斯：深圳硅谷可结合成制造巨头Calichina +图示：深圳华强北电子市场网易科技讯11月22日消息，据国外媒体报道，中国深圳和美国硅谷正在迅速结合起来，一个拥有创新思维，一个拥有中国制造的强大能力。两者的结合大可成为全球制造的巨头，这被称之为Calichina。欧洲知名飞机制造商空中客车（Airbus）公司最近宣布了其设在中国的创新中心位置。这个幸运的城市是深圳，是毗邻香港的年轻城市。深圳是一个蓬勃发展的大都市，人口在1200万到1500万之间，建市迄今还不到40岁。人们都说，在1979年深圳只不过是一个小渔村，但实际上现在的深圳是由当时的300多个村庄组成，曾经是一个30万人的聚集地。但不管你怎么讲，深圳的发展速度都是惊人的。今天，深圳已经成为世界新兴的制造中心，在这里占制造业大部的是电子产品。深圳的华强北市场全球闻名，你可以从中买到任何电子产品东西，从零售到批发应有尽有一百万到一百万。深圳也是苹果承包商富士康，中国智能手机制造商华为以及其他科技公司的所在地。难怪空客想要在这里设置它的创新中心。空客在深圳的创新中心是公司在全球所设置的第二个类似机构。鉴于该公司总部位于法国南部的图卢兹，由法国，德国和意大利政府共同管辖，或许你会认为它的第一个创新中心将设在欧洲，比如说是具有巴黎硅谷之称的“硅桑蒂尔”(Silicon Sentier，或是柏林的科技中心Silicon Allee。但事实并非如此。空客公司的第一个全球创新中心位于加利福尼亚州旧金山的硅谷中心。空客在图卢兹，汉堡和阿拉巴马州的莫比尔等地都有飞机制造厂。空客在中国北方城市天津有一条生产线，与中国航空工业集团公司（AVIC）合资经营。后者是中国第一架民用大客机C919的制造商。为什么空客的全球创新中心不在，也不在天津呢？答案是，喷气式客机的真正价值不在于机身的铝材或机翼的气动结构，而是机载的各类电子产品。从控制燃料消耗的航空电子设备到车载Wi-Fi以及娱乐系统才是飞机创新的关键所在。而且飞机的未来价值将会体现在物联网。空客不在硅谷开发设计新型飞机。它是在那里开发飞机的自动驾驶技术，（代号：Vahana），用于自动驾驶飞机操作的空域管理系统（代号：Altiscope）以及类似于Uber的直升机乘坐共享服务（代号：Voom）。这些都是真正的硅谷型项目，而不是欧洲硅谷所模仿的东西。而且你可以确定，空中客车深圳创新中心将发挥作用，使硅谷的项目成为现实。深圳和硅谷正在迅速融合成为一个跨太平洋的制造中心。我们大可以将其称之为Calichina。创新思维在加州诞生，而在中国制造中成为现实。需要明确的是，我们所讨论的并非飞机生产线（虽然生产线也在中国）。我们正在讨论模型，原型机和概念型飞行产品。这不仅仅是属于空中客车公司的Calichina。从技术巨人苹果公司到农业巨人嘉吉公司，以及全球的每一个行业，都是如此。深圳和硅谷是共生的，因为尽管加州仍然有梦想，但事情只能在中国制造下成为现实。在加利福尼亚州本地生产苹果Apple I个人电脑的日子早已不复存在，但显然有人能够用在深圳收购的备件生产出iPhone 6s。用深圳的材料装配硅谷的想法，你可以用Calichina创造出未来。 +http://tech.163.com/17/1122/16/D3S0IIAT00097U7R.html +百度"阵亡全家桶"：巨头养的儿子，也难活啊 + + （原标题：百度“阵亡全家桶”：巨头养的儿子，也难活啊） + 文/秦予百度正在改变。它的路线变化，正直观映射到了它的产品上。“All in AI”和宣布回到“内容分发”业务一年后，百度在feed流上的广告营收开始逐渐逼近今日头条，日前，百度又推出了“熊掌号”。爱奇艺要用AI打造“大娱乐生态场”的同时，百度新的短视频App“好看视频”亮相。百度也开始涉足智能硬件产品。2017百度世界大会上，百度新推出的渡鸦智能音箱Raven H，因为亮眼的颜值和1699元的售价在朋友圈里刷了屏。而过重的品牌意识和对百度搜索数据与流量的依赖，也许正是它们失败的主因。创业家& i黑马在这些年百度“做死”的产品里挑选了一些有代表性的案例，也许能够通过它们的命运，让我们窥见百度产品路线的发展轨迹。1、百度空间诞生日期：2006年结果：2015年4月关闭失败主因：新浪微博与QQ空间的步步紧逼2006年正值百度产品的巅峰时代，百度空间就诞生于此时，背靠着百度搜索这个爸爸，百度空间的发展势头很猛，3年就成为了国内最大的SNS社区平台之一。然而，在强社交属性的QQ空间和迅速走红的新浪微博的夹击下，腹背受敌的百度空间匆忙走了一步臭棋——强制升级轻博客，然而新产品的体验不尽人意，这也加速了百度空间的衰亡。2015年4月7日，挣扎了6年的百度空间宣布关闭，并从4月21日起停止让用户编撰更新博文，百度空间的内容也于2015年5月7日正式迁移到百度云。2、百度有啊诞生日期：2008年10月结果：2011年3月关闭，商城业务转移给乐酷天失败主因：“打败淘宝的不会是第二个淘宝”2007年10月，百度认为基于搜索引擎的电商才是大趋势，于是成立电商事业部，在2008年10月高调推出对标淘宝的C2C电商平台“百度有啊”，甚至放言“三年内打败淘宝”。3、乐酷天诞生日期：2010年1月结果：2012年4月关闭失败主因：“外来户”水土不服，百度也依然不懂流量转化有啊中后期的惨淡经营让百度决定放弃纯粹模仿的C2C模式，转而拥抱B2C。2010年1月，百度与日本第一大电商乐天合资创立B2C电商平台“乐酷天”，持股比例为49：51，百度负责入口和流量，乐天则主要做运营。4、百度Hi诞生日期：2008年结果：目前仅有百度内部员工办公使用失败主因：体验还不如QQ，就不要打即时通讯的主意5、百度说吧诞生日期：2010年9月结果：2011年8月关闭失败主因：强制实名社交，这么做问过中国网民吗？这实在不符合当时绝大多数网民的习惯，用户增长数据一直很难看。意识到不该“逆用户习惯”的百度在2011年4月推出新版，最重要的改变就是让用户可以选择是否实名认证。可惜，这一改变似乎来得太迟，后续的用户增长并没有突破，加之百度内部对该产品的推广宣传也不上心，最后百度说吧于2011年8月宣布关闭，惨淡的结局也让它成为许多人眼中“微博大战中第一个失败者”。6、百度云OS诞生日期：2012年6月结果：2015年3月宣布停止更新失败主因：选择“队友”的失误根据刷机精灵发布的一份2014年手机刷机行业的数据报告，2014年的百度云OS曾在第三方ROM资源排行榜中超过MIUI、乐蛙等，排名第二。在2013年，百度战略投资深圳百分之百公司。在该交易中，百度以云OS资产加现金的方式投资了百分之百，随后，百度云OS一直由百分之百运营，并支持百分之百的百加手机。2015年3月，上线1000多天后，百度云OS和自己的千万用户道别，宣布停止更新。对此，百分之百创始人徐国祥给出的解释是百分之百在进行新的融资，因此停止了对云OS业务的投入。而百度的心里，想必也是无奈的。7、百度游戏诞生日期：2014年4月结果：2017年1月被第三方收购失败主因：并不想做好游戏内容研发，凭什么打破游戏江湖的垄断？遗憾的是，在持续的高层人事动荡、内部腐败中，原本有过优秀发行作品的的福州团队核心成员（创业家&i黑马注:原91游戏）陆续离职。 2016年3月，百度移动游戏宣布战略升级为“百度游戏”，同时裁撤了福州分公司运营团队。升级后百度游戏依然不重视游戏内容的研发，而是希望借助渠道优势做代运营和游戏分发，而此时游戏行业也已形成腾讯、网易两巨头的格局。自此，百度游戏逐渐边缘化，并于2017年1月仅仅以12亿元人民币的价格被“贱卖”。至于4年前斥巨资收购的91无线，目前已经没有任何实质业务。8、百度mall诞生日期：2015年11月结果：无声地消失失败主因：百度做电商，三而竭百度mall最后消失得无声无息。虽然接连在电商领域折戟，但百度做电商的心依然没死，只是在2015年11月上线百度mall的时候显得低调许多。与前两次不同，此次百度mall定位于中高端品质电商，只和品牌官方直接合作，面向25-40岁的中产阶级，颇有些“消费升级”的意味。9、百度医生（百度医疗）诞生日期：2015年1月结果：2017年4月关停失败主因：“KPI文化”遭遇“慢”医疗百度血友吧被卖、魏则西事件让百度医疗相关业务臭名昭著，但其实这些都与百度医生无关。百度医生是一个医患双选平台，是2015年1月8日百度医疗事业部成立后开始重点打造的一款产品，希望从“预约挂号”切入医疗服务。2017年4月1日，百度医生正式被关停，医疗事业部也在同一时间遭裁撤。10、百度外卖诞生日期：2014年5月结果：2017年8月被饿了么收购失败主因：O2O是场恶战百度外卖的兴衰一直是被众媒体津津乐道的好故事。从2014年5月成立开始，百度外卖就机智地选择建立外卖专送队伍、攻占白领市场——这是当时饿了么和美团外卖在校园市场里厮杀正酣时忽略的阵地，百度外卖也因此得以迅速占领市场份额，最高时达到了33%，一度被美团视为最大的竞争对手。风光无限的百度外卖在2015年下半年正式拆分独立，几乎所有人都知道了李彦宏“要拿200个亿支持O2O”。?2017年8月24日，昔日的对手饿了么正式宣布收购百度外卖，作价为42亿元（创业家&i黑马注:由百度2017Q3季度财报“其他收入”一栏推算）。合并完成后，百度外卖成为饿了么的全资子公司。日前，饿了么召开双方合并后的战略发布会，公布融合进展，并且表示，合并18个月后，“百度外卖”这个名字将被新的品牌名代替。在不同的领域，百度基于自身的搜索流量，经历了一次次产品变现的尝试和失败。而“错过了移动互联网时代”之后，百度却成为国内最先布局人工智能的互联网巨头，并且，在现在的产品战略中，百度开始了立足AI的产品和商业化的布局。对于百度而言，这是否是一个新的产品时代的开启？还值得我们期待。 +http://tech.163.com/17/1122/14/D3RSO8FA00097U7S.html +5G手机高通收多少专利费?3000元全网通手机约百元 + + （原标题：费用不小：高通公开5G手机专利授权许可费率） + 那谈到5G就要说说高通了，高通不光是做手机芯片，通讯技术的专利的授权使用费也是自家盈利能力很强的业务。近日高通就公开了5G专利授权的许可费率：从得到的消息来看，对于单模5G手机的专利使用费费为2.275%；而多模式(3G /4G/ 5G)手机专利使用费率则高达3.25%。并且高通表示将会提供4G的后续版本及第一次5G的发布，不会增加在此类协议下所适用的特许权使用费。高通预计首批5G手机将在2019年商用。这也就意味着如果手机厂商使用高通的5G全网通解决方案，就需要在设备价格的上给高通3.25%的专利使用费，以一台3000元的手机为例，需要支付的专利使用费差不多是97元左右。 +http://tech.163.com/17/1122/14/D3RSFM6300097U81.html +科学家证明环境、生活方式产生的影响也能遗传给后代 + + （原标题：We Can Observe Memories Being Passed Down Through Generations） + 网易科技讯 11月22日消息，据Futurism报道，我们已经非常了解遗传性状是如何代代相传的。这很简单，可以理解。有些特征可以被父母传给孩子，比如头发的颜色或对某些疾病的易感性等等。然而，近年来，科学家们已经发现，我们不仅继承了父母的遗传信息，也可以通过细胞的表观记忆来继承他们的表观遗传信息。（网易编辑注：表观遗传是指DNA序列不发生变化，但基因表达却发生了可遗传的改变；表观遗传信息是在生物发育过程中获得的信息，能影响基因表达，也能对表型产生影响。）生物学家佐伊·米格卡夫斯基（Zoe Migicovsky）和伊戈尔·科瓦尔查克（Igor Kovalchuk）发表在《遗传学前沿》（Frontiers in Genetics）杂志上的一项研究中写道:“哺乳动物将表观遗传信息传递给后代的能力提供了明确的证据，证明遗传并不局限于DNA序列，表观遗传学在繁衍后代的过程中也起着关键作用。”研究人员始终在试图更好地理解表观遗传记忆，他们在这方面取得了显著的进展。2014年，加州大学圣克鲁兹分校的科学家证明，一种表观遗传标记可以代代相传。而在2016年，特拉维夫大学的研究人员称，他们接近于找出允许表观遗传发生的机制。在2017年4月，来自西班牙欧洲分子生物学组织(EMBO)的研究人员在《科学》杂志上发表研究论文，证明了环境变化导致的表观遗传记忆可以遗传给14代萤火虫。虽然环境影响某些基因发育的能力十分显著，但更值得注意的是，我们也许能够利用这些知识来对抗某些基因诱发的或与基因相关的疾病。阿尔茨海默氏症（Alzheimer）被认为是由遗传和环境因素引起的，而癌症也可能有表观遗传原因。神经精神病学、免疫学和智障障碍等，也是表观遗传学家的可行研究领域。了解环境不仅可影响个体健康，也可能影响到他们的后代，这可能会对医疗和疾病预防产生长期的影响。我们生活的时代，基因操作技术比以往任何时候都好，这要归功于新一代测序方法和基因编辑技术，如CRISPR-Cas9。再加上这些新知识，我们可以找到更多方法来编辑那些可能对几代人产生负面影响的表观遗传因素。无论是通过基因操作还是其他形式的治疗，我们对表观遗传记忆如何发挥作用的认识可以改变我们治疗基因疾病的方法。至少，知道我们的环境和生活方式是可以遗传的，可以让许多人在有生之年做出更健康的决定，毕竟要为子孙后代着想。（翻译：小小，审校：王华春）原文链接 https://futurism.com/observe-memories-being-passed-down-through-generations/ +http://tech.163.com/17/1122/14/D3RQG4J500097U7R.html +央行银监会召集多地金融办开会 网络小贷将迎整顿? + + （原标题：独家！央行、银监会召集多地金融办开会，网络小贷将迎整顿？） + 21世纪经济报道 王晓 北京报道央行及银监会将召集多地金融办负责人召开会议，主题包含网络小额贷款整顿。21世纪经济报道独家获悉，央行及银监会将召集多地金融办负责人召开会议，主题包含网络小额贷款整顿。事实上，网络小贷的部分乱象早已被监管警觉。在今年2月22日的中国小额贷款公司协会第一届会员代表大会第二次会议上，银监会普惠金融部主任李均锋就提醒：希望各地在互联网小贷还没有一个全国性的意见和办法之前慎重批设。要确实把握股东的企业是不是互联网企业，有没有大数据和技术，有没有需要服务的客户群体。“对小贷公司的跨区域经营问题一定要慎重。对于有条件在省内跨区域可以给予支持，但按照小贷公司支小、熟人的定位来说，必须立足于某一个区域。”而且，批设跨区经营的网络小贷公司已经超出了地方金融监管机构的职责。（银监会李均锋：慎重批设互联网小贷，慎重对待小贷跨区经营）此外，在P2P备案落地前，网络小贷资质还成为部分P2P公司的马甲，但这已经突破了小贷公司主要以自有资金放贷的要求。一些网络小贷公司更是异化成了线上“高利贷”公司，产生不好的社会影响，“现金贷”即是其中的典型代表。此前，重庆要求辖内网络小贷公司对现金贷业务进行自查，上报期限、利率、放贷对象、资金来源等多方面信息。11月21日晚间，互联网金融风险专项整治工作领导小组办公室下发特急文件，要求各地立即暂停批设网络小额贷款公司，禁止新增批小额贷款公司跨省（区、市）开展小额贷款业务。（现金贷招致强监管规整风暴：网络小贷暂停批设！）亦有小贷业内人士对21世纪经济报道记者表示，管网络小贷的方向没错，不过对于一些开展“现金贷”等业务的公司，还应该管住更多无资质开展业务的公司。 +http://tech.163.com/17/1122/12/D3RKOOET00097U7R.html +腾讯宣布获得"吃鸡"游戏在华独家代理运营权 +网易科技讯11月22日消息，腾讯今日宣布，公司正式与PUBG公司达成战略合作，获得《Playerunknown's Battlegrounds》（玩家戏称“吃鸡”）在中国的独家代理运营权。腾讯称将协同PUBG公司为《PUBG》国服提供网络优化、服务器扩容、外挂打击等技术支持，营造积极、正向的游戏氛围。尤其是为未成年人用户传递健康正向的文化理念和价值观导向。同时腾讯也将和PUBG公司一起与各直播平台、媒体、上网服务场所等行业各界合作伙伴打造公平、健康、可持续的生态体系。腾讯会与国家主管部门保持密切沟通，在本次合作达成后，将与PUBG公司遵循主管部门的相关指导意见，对游戏中不符合相关规定的内容进行调整，并进一步突出游戏的团队协作和公平竞技属性，确保符合社会主义核心价值观，符合中华民族的传统文化习惯与道德规范。随着中国区代理权的确认，腾讯与PUBG公司将于近期公布《PUBG》国服的相关内容和双方合作的更多详情。根据Steam官方的统计数据，《PUBG》本日玩家数峰值突破290万，刷新平台纪录，其中接近50%的玩家来自中国内地。网易科技注意到，腾讯在新闻稿中并未提及这款游戏原来的中文翻译《绝地求生:大逃杀》，而是采用了英文，或许国服会采用其他名称。 +http://tech.163.com/17/1122/10/D3RC9JQL00097U7R.html +酷骑修改退押金方式 用户将只能通过电话退款 +网易科技讯11月22日 在宣布由拜客托管，并公布了线下、电话两种退款方式后不到2天，酷骑单车又修改了退款方式，宣布取消线下现场退款点。按照最新的说明，酷骑用户将只能通过3部专线电话实现远程退款。酷骑通知如下：酷骑表示，取消线下退款点的主要原因是基于公共安全因素考虑。但由于退款点设置在了成都，大部分用户其实很难通过这种渠道退款，电话退款依然是最现实的选择。 +http://tech.163.com/17/1122/09/D3RAQ2KJ00097U7T.html +在诺基亚的老家做到第一后 华为接下来要干什么？ +一、11月的赫尔辛基，下午四点已经天黑。当知道我来参加“Who is HuaWei”活动时，已在当地生活了近十年的华人丙先生有点诧异。他说华为在芬兰已然足够知名，是芬兰智能手机市场上的销量NO.1，所有人都知道华为是个来自中国的手机企业，为什么突然办一个“Who is HuaWei”活动？这也是我的疑问所在，华为在这个已经占据了优势的地区办这个活动，想要传达什么？对于华为为什么能做到芬兰第一，丙先生说，华为手机在芬兰的口碑很好，在芬兰的冬天，苹果在室外都会被冻得自动关机，但这时华为手机还能正常使用。于此来看，目前芬兰人对华为的最直接印象，应该是可靠。二、据数据显示，在芬兰这个诺基亚的老巢，华为手机的市场份额排到了第一；在整个东北欧区域，华为的市场份额接近了20%，与苹果、三星一道组成了前三的阵营。但在7年前，华为在该区域还处于客户不认可、消费者不了解、没有渠道、没有品牌、没有零售的状态。东北欧区域CMO Tony Rong在接受采访时透露，在其刚来东北欧的2010年，华为在这个区域还属于初创阶段，什么都没有。在开月度经营分析会时，Tony Rong说要搭建三层的渠道体系，从分销商到客户、最后到门店的三层渠道体系，问谁能给提供一下当地的渠道数据：当时所有的人一脸懵的看着他，问这是个什么东西。据Tony Rong回忆，在2010年，华为在赫尔辛基出了5000台8800，而这批产品最终花了三年时间才清库；其他区域的情况也类似，在2011年Tony Rong去捷克跟五大分销商谈合作时，最终只有一家分销商下了2000台产品的订单，花了两年时间才卖完。更让Tony Rong无奈的是，他们当时甚至不知道怎么去给产品定价，只能是在拜访客户时拿出产品问：你觉得这个产品能定多少钱？高于心里预期就直接同意，低于成本就继续跟客户沟通。到2013年的P6发布时，这种情况才得以有所好转；鉴于P6的轻薄及外观，华为借机启动了对消费者的品牌传播。三、即便有了P6的推动，在2014华为消费者业务东北欧区域总裁汪严旻上任时，华为手机在这个区域的市场份额依然不到5%。Tony Rong说，汪严旻上任后，他们集体梳理了一下思路，认为需要先从提高品牌认知度开始着手：据当时做的市场调研显示，华为在东北欧区域的整体品牌认知度仅为30%左右。为了迅速地在短时间内提升品牌知名度，华为最终采取了360度营销的方式：以旗舰机上市为主导，投入大量的市场资源做到让消费者在一定时间内看足信息、并记住华为。360度营销的第一款受益产品是P8。华为在P8上做了很多新的尝试，不仅仅是在本地召开发布会，还做本地的户外广告、在电视广告上进行投入、推出客户的销售激励、提升零售形象等等，并借鉴了以色列的成功经验采用了代言人形式。例如在波兰，他们选择了9分钟进5球的拜仁慕尼黑波兰前锋莱万多夫斯基；他们认为，莱万的奋斗成长故事与华为的品牌调性非常契合，而效果也很明显：正处于从一流球星向顶级球星转变的莱万，跟华为的品牌一起成长了起来。不仅如此，汪严旻在接受网易科技等媒体采访时透露，鉴于低端产品可能导致的消费者体验不佳，因此从2014年开始，华为逐步退出了东北欧区域的低端机市场，主打中高端市场；同时进行的，还有零售、服务体系的建立：此前华为只通过运营商做服务，没有直接面向消费者，从2015年开始，华为逐渐把服务体系推出来直接面向消费者。四、汪严旻和Tony Rong同时得意于他们对东北欧区域市场消费升级的推动。汪严旻在调研中发现，当时仍是哑铃型市场结构（高端、低端市场规模大，中端市场规模小）的东北欧市场已经出现了消费升级的兆头，正在向纺锤形市场结构（高端、低端市场规模小，中端市场规模大）转变，因此华为推出了面向中端市场的lite系列产品。这是聚焦在199欧到399欧价位的产品。到目前为止，中端产品的销售比例已经超过了华为整体销售的50%。据汪严旻透露，通过P8与lite系列的共同发力，发货量从几十万提升到了几百万台；而2017年上半年的市场调研显示，华为在东北欧区域市场的品牌知名度达到了82%，最高的是塞尔维亚，达到了92%。而品牌考虑度最高的是在波兰，已经接近了40%，即有接近40%的人考虑购买华为手机。五、但华为不满足于此。在开放日上，华为消费者业务品牌部发言人David Kim以“Who is HuaWei”为主题，阐述了华为三十年来的成长、组织模式、科技创新等等。汪严旻说，知名度问题解决了，接下来需要解决品牌考虑度问题：80%的人知道华为，但只有40%的人考虑购买华为，另外40%的人为什么不选择华为？在汪严旻看来，这主要是两个因素所导致，第一，他知道华为的名字，但不知道华为到底是谁；第二，他没有机会去体验华为的产品和服务。这也是“Who is HuaWei”活动举办的原因，汪严旻希望通过这个活动来介绍华为到底是什么样的公司、什么样的品牌，又能提供什么样的产品和服务。更重要的是，华为希望借此继续提升自己的品牌，尤其是在高端品牌感知方面。在整体占比接近20%的东北欧区域市场上，华为在高端机市场的占比大约为9%，低于苹果与三星；华为希望通过讲述“Who is HuaWei”，来树立自身科技创新引领者的地位，以此强化消费者对华为高端品牌的感知力。在产品方面，据汪严旻透露，这是华为东北欧区域市场首次大力推广Mate系列产品，华为在市场上推出了Mate10、Mate 10 Pro和Mate10lite；据汪严旻表示，此前华为东北欧区域只是将Mate作为一个小众机器来运营，但随着欧洲用户对大屏产品的接受程度提升，Mate系列产品越来越受欢迎，与中国一样已经出现了断货情况。他认为，Mate系列下半年将给他带来惊喜。 +http://tech.163.com/17/1122/07/D3R4NJNE00097U81.html +这个人与马斯克小扎竞争破解大脑 能成功吗 + + （原标题：INSIDE THE RACE TO HACK THE HUMAN BRAIN） + 在洛杉矶一间普通的医院病房里，名叫劳伦·迪克森（Lauren Dickerson）的年轻女子在等待创造历史的时刻到来。她刚刚25岁，是一所中学的教师助理，目光温柔，非同寻常的是她的头上插满了裹着绷带的信号电缆，像是未来感十足的辫子。三天前，神经外科医生在她头骨上钻了11个洞，将11根细电缆插入她的大脑中，而另一端则连接在电脑上。现在她被医生固定在冷冰冰的铁床上，塑料管扎住了她的手臂，医疗监视器跟踪着她的生命迹象，一动也不能动。房间里挤满了人。当摄像人员做好准备后，两个独立的专家团队准备工作，其中一支是来自南加州大学精英神经科学中心的医学专家团队，另外一支则由来自科技公司Kernel的科学家组成。医学专家们正在寻找一种方法来治疗迪克森的癫痫。到去年为止，他们为迪克森精心制定的癫痫药物治疗方案效果还不错。但随着时间推移，药效开始降低。医学专家之所以使用信号电缆来检索迪克森的大脑，是为了查明癫痫发作的原因。而来自Kernel公司的科学家则出于完全不同的目的：他们为布莱恩·约翰逊（Bryan Johnson）工作，后者是一位现年40岁的科技企业家，在将自己的企业以8亿美元的价格出售后，开始追求一个雄心勃勃的疯狂梦想——约翰逊想控制人类进化并创造出一个更好的人。他打算通过打造一种“神经假体”来做到这一点，这种设备可以让人类更快地进行学习，记住更多的东西，在人工智能的帮助下“共同进化”，解开心灵感应的秘密，甚至可以将人们的思维相连。他还想找到一种方法来让人类瞬间学会武术等技能，就像《黑客帝国》里的那样。他还希望能够在普罗大众中普及这项发明，而不仅仅面向有钱人。迄今为止，约翰逊所拥有的仅仅是一个存储在硬盘上的算法。当他向记者和观众介绍神经假体时，他经常使用媒体易于接受的一种表达方式——“大脑中的一个芯片”，虽然他知道这种需要在人的头骨上钻孔的东西永远不会成为大众市场消费品。目前世界各地的科学家正在开发各种各样的非侵入性接口，通过可以注入大脑的微小传感器，或者可以与头戴式接收器交换数据的基因工程神经元与大脑相连。未来约翰逊将通过这些新型的脑机接口来实现其算法。当然，这些脑机接口还都没被制造出来，所以约翰逊只能使用连接到迪克森海马体的信号电缆来进行一个大胆的实验：当我们用外部设备与大脑相连时，我们可以对大脑传递何种信息。这正是约翰逊的算法将起到的作用。嵌入迪克森头部的电缆将记录大脑神经元在一系列简单的记忆测试中互相传递的生物电信号。这些信号将被上传到硬盘中，算法会把这些信号转换成数字代码，然后进行分析，对其进行功能增强或重写代码，从而提高记忆力。该算法随后会再将代码翻译成电信号发送回大脑。如果这种方法能够帮助迪克森在大脑中显现出一些关于曾经记忆的图像，那么研究人员就会明确算法正在起作用。然后，他们会尝试用间隔更长一段时间的记忆做同样的事情。这是前所未有的尝试，如果这两项测试能够奏效，他们将会破解人脑创造记忆的模式和过程。虽然其他科学家正在使用类似的技术来解决简单的问题，但约翰逊是唯一一个试图开发出一种增强记忆力产品的企业家。几分钟后，他将进行第一次人体测试。对于商业记忆假体，这将是第一次人体临床测试。 “这是历史性的一天，”约翰逊说。 “我非常兴奋。”这一听起来有些匪夷所思的测试，发生在2017年1月30日。读到这里，你或许会认为约翰逊是一个钱多又不切实际的傻瓜。我第一次见到他的时候也抱着同样的想法。他穿着普通的牛仔裤，运动鞋和T恤，充满了孩子般的热情。他滔滔不绝地向我阐述“对人脑进行重新编程”，想法似乎过于天马心空。但是你很快会意识到这种风格是约翰逊的一种伪装或是自己先入为主的看法。约翰逊和许多成功的人一样，既聪明又现实。他拥有充足的活力，好像浑身长满了像章鱼一样的触手，一面应对笔记本电脑，一面应对手机，还不忘谋划全身而退的路线。当他开始谈论他的神经假体时，各种论断会一起向你扑面而来，直到你屈服于他的观点。约翰逊在29岁创办了在线支付公司Braintree，在他36岁的时候被PayPal以8亿美元的价格收购。随后约翰逊向Kernel投资了1亿美元，开始疯狂研究神经假体项目。数十年的动物实验支持着他的科学野心：研究人员已经学会了如何恢复脑损伤的记忆，植入虚假的记忆，人为控制动物的动作，食欲和好斗行为，诱发愉快的感觉和疼痛，甚至可以将大脑信号从一只动物传送给数千英里以外的另一只动物。约翰逊并不孤单。在他进行实验的几周之前，特斯拉首席执行官伊隆·马斯克（Elon Musk）和Facebook首席执行官马克·扎克伯格（Mark Zuckerberg）都公布了他们的破解大脑计划。而一个名为达尔帕Darpa的军事研究小组也已经进行了数十次研究。毫无疑问，其他国家也都在进行相关研究。当然，和约翰逊不同的是，他们不会邀请记者进入任何实验室。马斯克关于其项目公开的要点如下：（1）他想用一种称之为“神经纽带”（neural lace）的神秘装置将我们的大脑与电脑相连接。（2）他创办的公司名为Neuralink。通过去年春季Facebook举办的F8开发者大会上扎克伯格所做的演讲，我们得以了解他的破解大脑计划：（1）迄今为止，该项目一直处于Darpa前董事Regina Dugan和谷歌先进技术小组的监督之下；（2）项目团队工作地点位于Facebook总部的8号楼，这里也是扎克伯格实验室所在地；（3）他们正在研究一种非侵入性的“脑机语音文本界面”，它使用“光学成像”来读取神经元形成单词的相应信号，找到一种方法将这些信号转化为代码，然后再把代码发送到计算机；（4）如果这种方法起效的话，我们只需要通过思考就能够“一分钟”打出100个单词。至于达尔帕，我们知道它所进行的一些项目是对现有技术的改进，还有一些是让士兵更快地掌握一些技能，这与约翰逊的某些想法不谋而合。但是我们对其所知甚少。这使得约翰逊成为我们唯一的向导，他也认为这是他需要承担的工作，因为他认为整个世界需要为即将到来的未来做好准备。但是，所有这些雄心勃勃的计划都面临同样的障碍：大脑有860亿个神经元，没有人知道它们是如何工作的。在大脑研究方面，无疑科学家已经取得了令人印象深刻的进展，比如揭示甚至操纵简单大脑功能背后的神经回路，但是诸如想像力，创造力和记忆等功能却是如此复杂，世界上所有的神经科学家联合起来可能都无法解决这些问题。这就是为什么在让专家对约翰逊的计划发表意见时，日内瓦生物与神经工程中心Wyss中心主任约翰·多诺霍（John Donoghue）回应说：“我很谨慎，这就好像我要求你把斯瓦希里语的东西翻译成芬兰语，你却试图将一种未知的语言翻译成另一种未知的语言。“为了显现出这个挑战的艰巨程度，他补充说，目前所有用于大脑研究的工具都像”两个纸杯之间的一根连线“一样原始，而我们的目标是创造能通话的电话。约翰逊并不清楚到底是100个还是10万个或者是10亿个神经元在控制复杂的大脑功能。在关于大多数神经元如何工作以及它们使用何种方式进行交流的问题上，约翰逊还是一团浆糊，而要解开这些谜团甚至需要几十年的时间。最重要的是，约翰逊没有相关的学术研究背景。他可能会在一个神经科学笑话上跌倒：“如果大脑足够简单，能够让我们理解，那我们也会愚蠢得无法理解。”图示：Kernel公司创始人布莱恩·约翰逊我和你们一样觉得，没有什么比科技乐观主义者的梦想更令人生厌。他们的永生计划和自由主义是青少年的幻想;他们开创的数字革命所摧毁的似乎要比创造的更多，甚至于他们的科学成果也不完全令人鼓舞。但约翰逊的动机源自内心深处。他出生在犹他州一个虔诚的摩门教社区，对于人生有着一套循规蹈矩的精致规则，这在他的脑海中印象如此深刻，以至于在我们首次会面的第一时间他就向我讲述了这些规则：“如果你在8岁时受洗，得到一分 ；如果你在12岁时进入教堂，得到一分；如果你戒色，得分；排斥手淫，得分；每个星期天去教堂，得分“。而最高分的奖励是天堂，一个虔诚的摩门教徒将在天堂与他的亲人团聚，并拥有无穷的创造力。当约翰逊4岁的时候，他的父亲和母亲离婚，也不再去教堂。虽然约翰逊并未向我提及那些不愉快的过往，但他的父亲告诉我，信仰的丧失导致他长时间的吸毒和酗酒。而他的母亲说，她的生活是如此窘迫以至于约翰逊不得不穿着手工缝制的衣服去学校。他的父亲记得约翰逊11岁时开始给他写信，每个星期都会写：“会用100种不同的方式反复说，'我爱你，我需要你'。他还是个孩子，而他的父亲是个吸毒酗酒的人渣。“约翰逊中毕业后仍然是一位虔诚的信徒，还曾前往厄瓜多尔进行传统的摩门教仪式。他在那里不停地祷告，一天重复数百次关于约瑟夫·史密斯（Joseph Smith）的话语，但他对于那些让生病和饥饿的孩子们在天堂里过上更美好的生活的故事感到越来越羞愧。减轻他们在现实中的痛苦不是更好吗？他的父亲说：“布莱恩回来了，完全变了一个人。”他有了一个新的目标，自我救赎。他的妹妹还记得约翰逊的言之凿凿：“他说，他想在30岁时成为百万富翁，这样他就可以利用手中的资源来改变世界。”他的第一步是在杨百翰大学（Brigham Young University）取得了学位，通过销售手机来支付自己的学费，并阅读会对未来有用的每一本书。其中一本给他留下深刻印象的是《忍耐》（Endurance），这是一本关于英国著名探险家欧克内斯·沙克尔顿（Ernest Shackleton）前往南极点探险的书。如果纯粹的勇气可以让一个人熬过如此多的艰辛，那么他就会信仰纯粹的勇气，约翰逊也是如此。他娶了“一个好摩门教女孩”，生了三个摩门教的孩子，并找了一份上门推销的工作来养家。在工作中，约翰逊还赢得了年度最佳推销员的奖项，手中的业务业越来越多，这让他进入芝加哥大学攻读了商业学位。2008年毕业后，他留在了芝加哥，创办了Braintree，开始向成为世界级的摩门教企业家努力。那时候，约翰逊与生活作着一系列斗争。他无法入睡，脾气暴躁，头痛得厉害。为此他采取了一系列无用的治疗方法：抗抑郁药，生物反馈，能量治疗师的治疗，甚至盲地服从教会规则。2012年，在约翰逊35岁时，他似乎到了人生的最低谷。在生活的痛苦中，他想起了沙克尔顿，并抓住了最后的希望，也许自己可以通过痛苦的磨难来找到答案。他计划攀登乞力马扎罗山，结果行程的第二天就得了胃病，第三天又患上了严重的高原反应。当他终于抵达峰顶时流下了眼泪，然后不得不被担架抬下山。这次经历过后，他是时候做出改变了。约翰逊开始不再掩饰自己的弱点，不再坚持怀疑态度，也放弃了生活斗士的姿态。在接下来的18个月里，他和妻子离了婚，卖掉了Braintree公司 ，并切断和教会的联系。为了缓解生活变故对孩子的影响，他在家附近买了一栋房子，几乎每天都去看望他们。他知道自己是在重复父亲的错误，但却别无选择——他要么在错误中沉沦，要么开始寻找他一直想要的生活。从厄瓜多尔回来时约翰逊曾经许下承诺，他将以此为起点，改变这个世界。他首先在华盛顿倡议善政，失败之后转向创立“人体器官芯片”等未来主义产品的风险投资基金。但他发现，即使这些做法获得成功，也无法改变世界的规则。最后，约翰逊想：如果人类的根本问题源自意识，那就让我们改变意识。此时，神经科学领域正在发生很多神奇的事，其中一些听起来就像圣经中所述的奇迹一样。比如科学家正在将假肢通过微芯片连接到大脑，并通过患者的视觉皮层进行控制。在多伦多大学，一位名叫安德烈斯·M·洛扎诺(Andres M. Lozano)的神经外科医生使用深度脑刺激减缓了老年痴呆症患者的认知衰退，并在某些情况下能够逆转患者的病情。在纽约州北部的一家医院，一位名叫格温史克（GerwinSchalk）的神经科学专家要求工程师记录听众在听摇滚乐队平克·弗洛伊德（Pink Floyd）的乐曲时听觉神经元的放电模式。当工程师们将这些模式转化为声波时，他们制作出一张几乎完全一模一样的单曲。在华盛顿大学，坐在不同楼的两位教授在脑电波帽的帮助下一起合作玩起了视频游戏。当一位教授想到要在游戏中发射子弹时，另一位教授有按下游戏按键的冲动。约翰逊还听说了一位名叫西奥多·伯杰（Theodore Berger）的生物医学工程师。在近20年的研究中，伯杰和南加利福尼亚大学以及维克森林大学的合作者联合开发出一种神经假体来改善老鼠的记忆力。在2002年开始测试时，实验材料只有一块老鼠大脑切片和一块电脑芯片。但是研究的关键之处在于芯片内置的算法，可以将神经元的放电模式转换成与实际记忆相对应的莫尔斯电码。以前从来没有人做过这样的事情，有些人认为这个想法过于激进——把我们最宝贵的意识归结成零和一未免太过狭隘了。著名医学伦理学家指责伯格篡改了自我认同的本质。但其意义是巨大的：如果伯杰能够把大脑的语言变成代码，也许他可以弄清楚如何解决与神经疾病相关的代码问题。与人类一样，大鼠海马体中神经元在放电时会产生相应信号或代码，而大脑会将其认定为长期记忆。伯格训练了一群老鼠来完成一项任务，并研究了所形成的代码。他了解到，当老鼠的神经元发出“强代码”时，大鼠关于相应任务的记忆更加清晰明确，他通过将其与收音机的音量进行类比来解释这个现象：在低音量下，你听不到所有的话语，但是在加大音量时， 就能清楚辨别出每一个单词。然后，他开始研究大鼠记忆或遗忘时产生的代码差异性。?2011年，通过对训练过的老鼠进行相关实验，伯格证实他可以记录大鼠大脑产生的初始记忆代码，并将代码输入算法进行处理，然后再将更强的代码反馈到大鼠的大脑中。当他完成实验时，忘记了如何推杆的老鼠突然想起来该如何去做。五年后，当伯杰仍在寻求人类临床试验所需的支持时，约翰逊出现了。2016年8月，约翰逊宣布投资1亿美元创办Kernel公司，伯格将加入公司担任首席科学官。在得知南加利福尼亚大学将在迪克森脑部植入信号电缆以治疗癫痫时，约翰逊与迪克森实验的首席医生、南加利福尼亚大学医学院神经重建部门负责人查尔斯·刘（Charles Liu）进行了接触。约翰逊要求刘允许其通过迪克森的信号电缆测试算法。事实上，早在刘六岁的时候，就痴迷于电视剧《无敌金刚》中的情节，也梦想着用技术增强人的能力。他协助约翰逊征得了迪克森的同意，并说服了南加利福尼亚大学机构研究委员会批准这个实验。在2016年底，实验的绿灯向约翰逊亮起。他准备着手开始他的第一次人体临床试验。在医院的房间里，迪克森正在等待实验的开始，我问她对于自己成为第一个实验对象有何感想。“如果我一定要做这场手术，”她说，“那正巧可以做一些有用的事情。”有用？关于机械超人的光辉梦想？ “你知道他在试图让人类更聪明，对吗？“这不是很酷吗？”她回答道。在电脑旁边，我向一位科学家询问屏幕上的五彩网格的含义。一位研究人员说：“每一个方格都对应着她大脑中的电极。”他解释说，每当迪克森大脑中的神经元连接到一条信号电缆时，一条粉红色的线就会跳进相应的方块中。首先约翰逊的研究团队将进行简单的记忆测试。这位科学家向迪克森解释说：“我们将向你展示一些单词。随后会提出一些数学问题，以确保你不会在脑海中反复回想之前的单词。你需要做的，是记住尽可能多的单词。“其中一位研究人员把平板电脑举到迪克森面前，在场的每个人都安静下来。迪克森读出屏幕中显示出的一个个单词。几分钟后，在数学问题打乱了一切之后，迪克森开始回想记忆中的单词。 “烟......蛋......泥......珍珠”接下来，他们加大了困难，开始尝试一连串的记忆。正如Kernel公司的一位科学家向我解释的，他们的信号电缆只能连接到30或40个神经元，从而收集到部分数据。收集到的数据重现一张面孔应该不太难，但是要获得足够的数据来再现一场电影中的场景几乎是不可能的。坐在迪克森床边的科学家开始发问，“你能告诉我上次去的餐馆吗？”迪克森说：“大概是五六天前。我去了观澜湖边的一家墨西哥餐馆。我们点了薯条和沙拉。”随后科学家向她抛出了更多问题。当迪克森绞尽脑汁回想时，另一位科学家递给我一个连接到处理电脑的耳机。我一开始听到了嘶嘶的声音。 在20或30秒后，我听到正在播放的流行音乐。他说：“这是一个神经元在放电。”随着迪克森的叙述，我开始听到大脑中那些神秘的语言，流行音乐让我们的腿不由自主的跟着抖动，我们的梦想随之震颤。她记得上次去好市多（Costco）超市时正在下雨，我听到了耳机中有好市多的音乐，还有下雨的声音。当迪克森的眼皮开始下垂的时候，医疗团队说她已经做的够多了，约翰逊的研究团队开始整理收集到的数据。在接下来的几天里，他们的算法会将迪克森的神经元突触活动转化为代码。如果他们把这些代码反馈回迪克森的大脑，她会想到自己用薯片沾了沙拉酱，而约翰逊或许离自己人类意识进行编程又近了一步。现在还剩下另一个挑战——约翰逊的研究团队需要经过两天的疯狂编码后返回医院，将新的代码反馈到迪克森的大脑中。正当他们得到一个消息说实验可以提早开始的时候，忽然又传达来一个消息：实验必须终止。实验被叫停的原因在于约翰逊和伯格之间出现了问题。伯格表示他对于正在进行的实验并不知晓，约翰逊没有得到他的允许就进行了受监管部门管控的实验。约翰逊说，伯格的指责让他感到困惑。 “我不知道他怎么会不知道这件事。我们整个实验室都在和他的团队一起工作。“他们之间的关系在不久之后就破裂了，伯格带着自己的算法离开了公司，他把责任完全归咎于约翰逊。伯格说道， “像大多数投资者一样，他希望尽快获得高回报。他没有意识到他必须等待七八年才能获得FDA的批准?-?我原以为他会认同这一点。”但约翰逊不想放慢速度。他有更大的计划，他太急了。八个月后，我回到了加利福尼亚，去拜访约翰逊，在实验结束之后他看起来似乎更轻松。我造访了Kernel公司位于洛杉矶的新办公地，有人在约翰逊办公桌后面的白板上用大大的字母写下了几首歌曲的播放列表。 “那是我儿子写的，”他说，“今年夏天他在这里实习。”这一年是约翰逊和一位31岁的演员兼电影制片人Taryn Southern合作的蜜月期。自从与伯格决裂以来，约翰逊已经把Kernel人员增加了两倍，现在他已经有36名员工，招募了芯片设计和计算神经科学等领域的专家。他的新科学顾问是麻省理工学院合成神经生物学组主任、神经科学界的超级巨星埃德·博伊登（Ed Boyden）。在新办公大楼的地下室里，有一个弗兰肯斯坦博士实验室，科学家们在那里建立原型，并在玻璃头模型上进行试验。看到约翰逊的工作一切顺利之后，我提到了访问的目的。 “你说你有东西给我看？”约翰逊有些犹豫。我已经答应不透露敏感的细节，但现在我必须再次承诺。然后他指给我两个小型的塑料陈列柜。里面是搁在泡沫橡胶上的两对弯曲的精致电缆。它们看起来很有科技感，也相当怪异，就像未来机器人的触角。我看到的是约翰逊的全新神经调节器的原型机。从一个角度说，这个神经调制器只是目前市场上深层脑刺激器和其他神经调节器的微型版。但不同于发射电脉冲的普通神经刺激器，这个神经调节器的功能是读取神经元发送给其他神经元的信号。它也许能采集超过100个神经元的信号，这比市面上最好的设备还厉害。这个设备本身不仅仅是一个巨大的进步，它也具有更为深远的意义：使用约翰逊的神经调节器，科学家可以从数千名患者那里收集大脑数据，从而可以编写精确的代码来治疗各种神经疾病。在短期内，约翰逊希望他的神经调节器能够帮助他“实现神经科技领域的淘金热”——金融分析师们预测在六年内神经设备市场规模将达到270亿美元，世界各国的科学家都在竞相破解大脑。从长远来看，约翰逊认为他的信号采集型神经调节器将以两种方式拓展他的计划：（1）通过为神经科学家提供一个巨大的新型数据库，从而用来破解大脑的运作模式；（2）在获得超高利润后，Kernel有能力推出一系列具有创新性且有利可图的神经工具，使公司深入涉足神经科学领域。有了这两项成就，约翰逊就可以推动神经科学达到他所需要的复杂程度，再用一种提高思维的神经假体来激发人类进化。痴迷于《无敌金刚》的神经学家查尔斯·刘将约翰逊在神经科学领域的野心比拟于人类最初的飞行梦。 “回到古希腊时代，人类一直有飞行的梦想。我们没有翅膀，所以我们发明了飞机。很多时候，这些人为创造的解决方案比自然创造的能力还要大，因为没有一只鸟能飞到火星。”但现在人类正在学习如何重塑自己的能力，我们真的可以选择我们的进化方向。“我们必须围绕这一点思考。这是世界上最具颠覆性的事情。“关键的因素还在于利润驱动，它总能推动科学的快速创新。这就是为什么刘认为约翰逊可以成为我们的翅膀。他说：“我从来没有遇到任何急于将此技术推向市场的人。”这场革命何时到来？ “比你想象的还要快，”刘说。现在我们回到了开始的问题。约翰逊是个傻瓜吗？他是在疯狂造梦中浪费自己的时间和财富吗？有一件事是肯定的：约翰逊永远不会停止尝试改进世界。在威尼斯海滩租赁的后现代造型的房子中，约翰逊想出一个又一个主意。他甚至把怀疑主义作为有用的信息——当我表示他的神经假体听起来像另一个版本的摩门教天堂时，他很高兴。“好主意！我喜欢它！”每隔一段时间，他都会停下来去探究我的“约束程序”。“首先，你有好奇心这种生物倾向。你想要得到数据。而当你使用这些数据时，你就有了意识的界限。““你想破解我的思维吗？”我问。他说，一点也不。他只是希望分享我们的思维。他说：“这就是生活中的乐趣，这个难题有着无穷解。我想，如果我们能够使数据传输速度快上千倍呢？如果我的意识看到的只是现实的一小部分呢？我们会讲出什么样的故事？”约翰逊在空闲时间写了一本关于控制人类进化的书，并且描绘了我们人类未来的光明一面。每当我和他谈话的时候，他都会提起这件事。很长一段时间，我把这个想法和他关于重新编程人类意识的梦想混为一体：未来正在扑面而来，比任何人想象的都快，光明的未来在呼唤我们，我们将很快为奇点的到来而欢呼。这让我很想用“炸弹客宣言”来打击他滔滔不绝的兴奋劲，我这样对他说：“你如何回应泰德·卡辛斯基（Ted Kaczynski）的恐惧？技术对人类来说会是一种自残吗？”（网易编辑注：卡辛斯基1995年发表论文《论工业社会及其未来》，文中指出工业革命及其带来的后果，对于人类社会来说是一场灾难，在论文的结束部分，作者作出预言：工业技术体系在未来的变革，将最终剥夺人类的自由。）“我想说他可能站在了历史发展的对立面。”“是吗？那气候变化呢？“他回答说：“这就是为什么我感到如此的急切。我们正在与时间赛跑。”他问及我的意见。我告诉他，我认为即便当饥民毁掉他实验室寻找食物时，他还会坚持研究机械大脑——而这也是我第一次揭示出他梦想背后的困境。事实是，他也有同样的恐惧。他说，世界变得太复杂了。金融体系摇摇欲坠，人口老龄化，机器人正在取代我们的工作，人工智能正在迎头赶上赶上，气候变化正在加速。他说：“感觉一切都在失控。”他总是反问，“为什么我们不能自我进化？为什么我们不能尽己所能更快地适应环境变化呢？”我转向一个更加轻松的话题。如果他发明出神经假体来革新我们使用大脑的模式，他会首先给我们带来什么？超人？心灵感应？集体智慧？还是功夫？他毫不犹豫地回答。因为我们的思维总是受到习惯的禁锢，他说，我们无法想象一个新世界。但是我们必须想象一些比现实更好的东西。所以他会试图让我们更有创意，这会给未来带来新的可能性。雄心壮志能让人坚持走过漫长的路途。当众人嘲笑不可能时，沙克尔顿抵达了南极；当约翰逊濒临死亡时，他登上了乞力马扎罗山，还在36岁打造了一个价值8亿美元的公司。而现在，约翰逊的雄心壮志是实现人类最古老的梦想：掌控意识。通过破解我们的大脑，他想让人类拥有一切。（翻译:晗冰 校对：王华春） +http://tech.163.com/17/1122/07/D3R3JP7900097U7R.html +乐视网停牌坑了融资炒股:不仅巨亏 还要交2亿利息 + + （原标题：乐视网停牌之殇：券商下调公允价值 融资客陷亏损黑洞） + 乐视网的“无限期”停牌，已经让越来越多的融资客面临亏损黑洞。在公募基金集体调降乐视网估值的同时，部分券商两融业务也开始下调乐视网的公允价值，最大调整幅度较这家公司的停牌价“腰斩”。第一财经了解到，由于乐视网财务状况严重恶化，国金证券将自11月22日起，调整乐视网的公允价值至11.18元，调整后，融资客将按照11.18元计算持有乐视网的市值，维持担保比例也随之变化。此前不久，中信证券、海通证券等券商也已下调乐视网的公允价值，其中，中信证券下调至7.82元。记者从两融投资者以及券商两融人士处了解到，随着券商下调公允价值，不少融资客面临爆仓，持仓比例高者已资不抵债，违约纠纷恐将产生。尽管10月27日深交所已将乐视网调出两融标的，但33亿两融盘仍将存续。自乐视网停牌以来，融资客所承担的利息已有近2亿元，受访融资客认为，乐视网的“无限期”停牌在两融领域并无先例，对两融交易规则也提出了挑战。除了沉重的利息外，众多的乐视网融资客都处于“准爆仓”状态。但证券法人士则表示，现有的法规下，若无监管认定乐视网违规，两融投资者很难追回损失。在乐视网公布三季报后，券商也加入了下调其股价预期的队伍。11月初，中信证券就发布业务公告称， 乐视网停牌时间较长，且于2017年10月28日发布三季报，根据融资融券业务规则及《融资融券业务合同》的约定，中信证券决定自11月6日起，调整乐视网的公允价格至7.82元，并按照调整后的公允价格计算维持担保比例。有资深的两融投资者对记者分析称，对于乐视网的融资客来说，这一价格将让仓位在三四成以上的，基本都处于一个“准爆仓”状态，损失普遍在50%～60%，很多千万级重仓面临的肯定是爆仓的“致命亏损”。不仅中信证券，部分券商也在适时调整乐视网公允价值。以海通证券为例，海通证券11月20日公告的乐视网最新公允价值13.87元。而国金证券则于日前公告，因乐视网三季报显示财务状况严重恶化，多家基金公司和券商对该证券下调了估值。为防范风险，将于11月22日调整乐视网公允价值至11.18元，并称根据后续市场和乐视网情况，可能还将多次调整。“我们目前还在观望， +没有下调（公允价值），只要能付利息，担保比例是正常的，就还是给客户进行展期。客户有钱还掉是最好了，复牌以后亏多少谁都说不定。”上海一券商两融业务负责人接受第一财经采访时表示，如果按照个别券商给出的低价公允价值，很多乐视网的两融投资者已到了平仓线，将出现诸多爆仓。该人士认为，乐视网的停牌是市场第一例，后期如何处理更多券商也都在观望，不排除更多券商继续下调乐视网公允价值。前述两融投资者则认为，相比公募基金下调估值而言，券商的公允价值下调带给投资者的亏损更为惨烈。“如果公允价格继续下调，很多人爆仓两三次都够了，重仓的、集中度高的，身家性命都可能赔进去。按照之前的情况，很多人就会选择违约，彻底不要了。”该人士称。两融爆仓违约在2015年股市异常波动出现，融资客与券商为此对簿公堂。不止一位券商两融人士认为，由于乐视网的长期停牌以及资金风险带来的两融投资者亏损，券商并没有更多责任，只是履行合同。相反，作为债权人，当融资客明确不还债务后，券商有权进行诉讼。“出了这种‘黑洞’之后，（客户）亏损是非常大的，很多资不抵债了，让券商平仓，这种情况是比较无奈和尴尬的。”北京的两融人士告诉记者，面对乐视网的停牌，融资客似乎没有什么比较好的办法，只能根据合同去支付利息，履行相关义务还债。他给出的建议同样是“能拿钱了结就赶紧了结”。数据显示，乐视网的两融余额高峰时曾达到50亿元，占比流通市值超过11%。到其今年4月18日停牌，两融余额仍有逾44亿，10月27日最后公开余额是32.98亿元，占比流通市值仍有8.47%的比例。停牌7个月以来，乐视网每天均存在百万至千万不等的融资赎回。记者了解到，目前两融的利息在年化8.5%左右，部分大客户最低年化也有至少6个百分点。按此计算，32.98亿元的融资盘，自乐视网停牌以来利息超过1.6亿元。对于高额的利息，此前已有投资者对第一财经表示“不堪重负”。乐视网在长期无先例停牌中，意味着融资客仍要在无法交易的状态中支付利息。对此，有两融投资者颇为不满，认为乐视网应对融资客的亏损负有一定责任，后续或遭到融资客起诉。北京市问天律师事务所主任合伙人张远忠告诉记者，尽管融资客有追偿意愿，但前提必须有监管认定乐视网有相关违规，而融资客又因此遭受亏损。“乐视网目前的停牌是监管所允许的，如果后面证监会认定它停牌违规或者存在其他问题，两融投资者包括一般投资者都可以追究损失。”实际上，令接受第一财经采访的两融投资者感到无奈的是，目前乐视网融资客的亏损“有苦难言”。券商在这之中虽然不存在责任，但相关的交易规则却被认为有更新的空间，比如是否应规定融资融券标的停牌时限，若停牌达到多久将被剔出两融标的等。“在上一次股市异常波动之前，是有对两融标的停牌进行规定的，最长停牌就半年，半年以上要客户还债。之后就放松，只要能正常付利息，担保比例没问题就继续展期。”受访的两融负责人认为，乐视网的两融盘，未来可能出现更多的投资纠纷，这让券商也十分尴尬，券商所能做的也只是跟着合同走。 +http://mobile.163.com/17/1122/16/D3S0RVT700118017.html +高通5G专利收费政策：3000元手机最多交150元 +近日，高通公布了3GPP 5G NR相关专利授权的条款框架，首次披露了5G专利授权的许可费率，完全满足3GPP Release 15的设备都必须照此交钱。高通的专利墙根据高通的专利许可计划，全球范围内使用高通移动网络核心专利的5G手机都必须依照下列条款缴纳专利费：－ 单模5G手机：2.275％－ 多模5G手机(3G/4G/5G)：3.25％而对于那些同时使用了高通移动网络标准核心专利、非核心专利的5G手机，收费标准为：－ 单模5G手机：4％－ 多模5G手机(3G/4G/5G)：5％考虑到网络兼容性，未来的5G手机几乎都必须是多模设计，因此每卖出100元钱，都必须交给高通3.25元或者5元。如果是一台3000元的高端机，就得上交97.5元甚至是150元。高通特别指出，上述条款与2015年以来高通在中国签署的150多个3G/4G手机专利授权许可协议保持一致，而在未来的谈判中，高通会增加4G后续版本、5G首个版本相关内容，不会在现有框架下提高许可费率。目前，高通在全球拥有超过13万项移动通信专利，还有大量审核中的专利申请。高通预计首批5G手机将在2019年商用。 +http://mobile.163.com/17/1122/08/D3R6PUOF0011819H.html +富士康用实习生加班生产iPhone X 被获苹果证实 + + （原标题：富士康被指用实习生加班生产iPhone X，获苹果证实） + 科技博客MacRumors北京时间11月21日报道，苹果公司及其代工商富士康今天证实，富士康工厂确实存在实习生加班生产iPhone X的情况，双方正在采取补救措施。据《金融时报》报道，6名接受采访的高中生表示，他们在富士康郑州工厂组装iPhone X，采用11小时轮班制。“我们被学校强迫到这里工作，”一位姓杨的18岁女生表示，“这些工作与我们的学业无关”。她表示，自己每天要组装最多1200个iPhone X摄像头。这些学生的年龄在17岁至19岁，来自郑州城轨交通学校。他们表示，学校告诉他们，要想毕业就必须在富士康实习三个月，获得“工作经验”。另外，今年9月，该校有3000名学生被派往富士康工作。苹果在实施审计后证实，存在实习生在其供应商中国工厂加班的情况。“我们可以证实，这些学生是自愿工作的，也获得了报酬和福利，但是他们不应该被允许加班的，”苹果称。富士康对此表示：“所有学生都是自愿工作的，并获得了相应的报酬”。不过，富士康也承认，这些实习生加班工作违反了公司的政策。按照富士康的规定，实习生每周工作时间不得超过40个小时。作为供应商责任审计的一部分，苹果要求富士康等代工商把工人每周工作时间限制在60个小时以内，每7天强制休息一天。 +http://mobile.163.com/17/1122/08/D3R64CC80011819H.html +小窍门：面容ID一下子没认出你脸的解决方法 + + （原标题：小窍门：面容ID一下子没认出你的脸的解决方法） + 我们都知道，iPhone X已经不再使用Touch ID指纹识别，取而代之的是面容ID脸部识别。这一变化，带来的是体验的大不同。手机利用上脸部识别，这就意味着我们在需要解锁设备，或是付费验证的时候几乎什么都不用做，只需要看着iPhone X的屏幕就好。系统识别到用户正在关注着手机的时候，就会凭借原深感摄像头扫描其面部，如果通过，那么验证就这样完成了。最值得一提的是，完成面部识别我们不需要正对手机直勾勾地盯着它。哪怕放在桌面上，只要我们双眼看着iPhone X，它也会自动完成识别。如果这样的功能一直都保持工作正常，毫无疑问那就太方便了。然而，事情总是有不能让自己满意的时候。这里我们可以介绍一个小窍门——当iPhone X第一次扫描没有识别到你的时候，你可以怎么办？有用户发现一种新办法，那就是用手指从锁屏界面向上稍微拖拽那么一点点，然后再放下来，这样面容ID扫描就会重置，设备就重新开始尝试识别你的脸了。为什么了解这个操作很重要呢？假设当iPhone X放在桌上，你当时不太想把它拿起来，但偏偏手机的脸部识别失败了一次，面对这种尴尬的情况你该怎么办？且不说把脑袋别开再看一次的办法能不能成功，傻倒是够傻的。把手机拿起来操作一番又很费时间。所以这种情况下，最好的办法就是把屏幕点击唤醒，然后做一遍上文说到的操作，重置面容ID的扫描。即使你当时是将手机拿起的状态，这个操作也能够加快流程，省下你的时间。当然了，你可能会问，如果那个时候我正好连一只手都腾不出来怎么办？那就没有办法了。不过老实讲，这种状况其实非常少见。况且如果双手都腾不出来，那也没办法唤醒手机启动面容ID扫描了。不过话又说回来，用户们能够发现这样的办法，就说明面容ID在识别准确率上确实还不够理想，至少时不时会给人们带去这样的小困扰。要在根本上解决问题，那也就只有苹果自己去提高技术规格了。但是之前我们也听到传闻说，苹果为了保证下一代新机的产量，暂时不打算对原深感摄像头的任何规格进行改动和升级。那么苹果能不能通过改进算法来进一步提高面容ID的识别准确率？我们不妨这样期待一下。 +http://mobile.163.com/17/1122/07/D3R45I3D0011819H.html +小米看了很无语 又一国产山寨机叫“MIX 2” + + （原标题：小米看了很无语 又一国产神机叫“MIX 2”） + 说起全面屏手机就不得不提小米，MIX的出现让消费者第一次真正的了解全面屏，可以说开创了一个新的时代。前段时间，小米MIX 2正式和大家见面了，在保留前作优势的前提下，在手感上有明显提升，再加上骁龙835处理器，和小米6同规格的CMOS索尼IMX386，综合来看MIX 2都是一款非常出色的旗舰产品。曾经我们报道过，在小米MIX 2发布的第二天就被“山寨”了，近日，又有一家厂商加入了“山寨大军”，这家厂商名家OUCITEL，推出的全面屏新机也叫MIX 2。虽说名字叫MIX 2，但是在外观上和配置上和小米MIX 2不尽相同。从已知的消息上看，OUCITEL MIX 2和很多全面屏手机一样，保留了额头和下巴，背部是玻璃材质，双摄像头位居左上角，并配有背部指纹识别。采用了5.99英寸显示屏，分辨率为2160×1080，屏幕纵横比为18:9。其他方面，OUCITEL MIX 2搭载联发科Helio P25处理器，配备6GB内存+64GB存储，拥有后置1600万+200万像素双摄像头，前置摄像头为800万像素，电池容量为4080mAh，支持9V/2A快充，提供亮蓝、黑色和银色三种配色。至于售价方面，官方还没有给出确切的消息。 +http://mobile.163.com/17/1122/07/D3R3TS820011819H.html +传三星S9相机硬件升级 售价有可能上涨 + + （原标题：传三星S9相机硬件升级 售价有可能上涨） + 不出意外，三星S9会在MWC 2018前夕正式发布。而如今，这款全新旗舰的消息也越来越多。有消息称，三星S9的相机将有大幅度升级，最高将支持1000fps慢动作视频拍摄，并采用3层堆栈式图像传感器。至于其他相机规格，则将与三星Note8保持一致。不过，相机硬件的升级，也将导致三星S9整体硬件成本的增加，可能造成售价上涨。但根据消息人士透露的信息，三星S9不会引入太多创新功能，其主抓的还是改善用户体验，这可能会让大家失望了。配置方面，三星S9将搭载Exynos 9810/骁龙845处理器，屏幕则采用5.77英寸（S9）/6.22英寸（S9+）全视曲面屏。假设三星S9系列创新不大的话，那么为了保证超高的屏占比，其指纹识别可能仍放在机身背部。这么看来，在生物识别功能上，以及更大的创新方面，三星似乎有些落后于苹果。 +http://mobile.163.com/17/1122/10/D3RCHPCK0011819H.html + 华为全面屏新机现身工信部：或为nova 3 + + （原标题： 华为全面屏新机现身工信部：或为nova 3） + 本月28号，荣耀将举行一场重磅发布会，正式推出V10全面屏新旗舰。日前，一款型号为“HWI-AL00”的新机亮相工信部，申请单位是华为技术有限公司。这款手机会不会就是荣耀V10呢？按理说，V10下周二将发布，现在亮相工信部并不稀奇。但仔细看手机图片，可以发现背面上方的英文logo为“HUAWEI”，因此可以断定为华为新机。而从目前已知的消息看，该机最有可能的就是华为nova 3，其与此前曝光的nova 3真机几乎外形一致。整体来看，这款华为全面屏手机采用蓝色配色以及双面玻璃+金属中框的设计，中框为亮蓝色，同时正面的指纹键也为蓝色，预计真机的颜值很高。其他方面，该机采用全面屏设计，屏占比较高，搭载平行双摄，其他配置不详，工信部还没有放出具体参数。 +http://mobile.163.com/17/1122/10/D3RCAAC90011819H.html +要取代安卓：谷歌自主新系统支持苹果Swift语言 + + （原标题：要取代安卓：谷歌自主新系统支持苹果Swift语言） + 对于谷歌来说，开源的Android系统一定不是他们的最终目标，做出一套能够让手机、平板甚至是个人PC都能够融合在一起的系统，才是最完美的解决方案。谷歌也早已将这个想法努力实现中，而它就是Fuchsia。谷歌的这套全新系统Fuchsia拒绝使用Linux内核，而是启用了自己开发的微内核Magenta。Fuchsia就是要统一安卓和Chrome OS，其支持多达4个程序同屏同时运行（平板模式下），并且主页以直列的方式显示各种故事卡、应用集、系统组件等，有点类似多任务、多标签页的做法，但更简洁。对于苹果来说，谷歌的思路显然更激进，不过他们多次表示，不会让iOS和Mac OS融合在一起。 +http://mobile.163.com/17/1122/10/D3RC7SLP0011819H.html +价格上涨！三星S9带保护壳照片曝光：竖排双摄 + + （原标题：价格上涨！三星S9带保护壳照片曝光：竖排双摄/指纹） + 三星新旗舰机Galaxy S9离我们越来越近，外媒BGR独家拿到了保护壳厂商Ghostek为S9制作的保护壳。虽然这是一款全包的产品，但依然可以确认出全面屏的设计语言，尤其是背部元件的排列位置。消息人士向BGR透露，三星Galaxy S9的黑边将会更窄。另外，evleaks在推特给出了三星S9的型号是SM-G960，内部代号Star-1，S9 Plus是SM-G965，内部代号Star-2。 +http://mobile.163.com/17/1122/08/D3R6TG510011819H.html +三星出狠招：推Note 8体验计划抢夺iPhone用户 + + （原标题：三星出狠招：推Note8体验计划抢夺iPhone用户） + 据SamMobile报道，日前，三星宣布推出一个新的项目，允许用户试用Galaxy Note8和?Galaxy S8智能手机一个月。这个项目被称为“三星Galaxy体验计划”，将于今天在韩国开始接受申请，并于11月27日结束。期间，三星将从申请参与该计划的人中挑选1万人，并将于11月30日通知被选中的人。随后，在12月1日至11日，被选中的人可以前往三星数码广场领取Galaxy S8或Galaxy Note8手机。三星官员表示，该计划是为了给iPhone用户有机会体验“?Galaxy设备的差异化”。值得注意的是，参加试用的用户需要缴纳45美元的费用，如果最后这部分用户决定保留试用手机，那么这部分费用将会退还。最重要的是，所有在一个月的试用期后购买Galaxy智能手机的用户都可免费获得JBL Go蓝牙音箱。但是，在试用后不想保留Galaxy Note8或Galaxy S8的用户将失去参与费用。 +http://mobile.163.com/17/1122/07/D3R422LJ0011819H.html +最美安卓旗舰 三星S8枫叶红本月28日开卖 + + （原标题：最美安卓旗舰 三星S8枫叶红本月28日开卖） + 细数现如今市面上的旗舰手机，三星S8绝对是成功者之一，作为首款全视曲面屏手机，发布至今赢得了外界的广泛好评。除了惊艳的工业设计外，多种颜色也成功吸睛，而就在前段时间，三星又公布了一款新配色-枫叶红。经过了几周的等待，这款新配色终于要和用户们见面了。据外媒报道，三星将在本月28日发布这款新配色，目的是希望用新配色来重新勾起消费者对S8的购买欲望。枫叶红这款配色与目前的季节及当下流行的配色趋势十分应景，前面板为纯黑色，背部则是枫叶红配色，极具辨识度。配置方面和其他版本的S8一致，5.8英寸全视曲面屏，分辨率为2960×1440，搭载高通骁龙835处理器，配备4GB内存+64GB存储，主摄像头为1200万像素，电池容量为3000mAh。有些遗憾的是，这款新配色仅在韩国发售，至于会不会推向其他国家还不得而知。 +http://mobile.163.com/17/1122/10/D3REF0AM0011819H.html +国内将于下周发布 看外媒如何评价一加5T + + （原标题：全面屏双摄旗舰 看外媒如何评价一加5T） + 北京时间11月17日凌晨，一加5T在美国纽约布鲁克林正式发布。发布后海外多家媒体迅速跟进，对这款搭载全面屏、高清双摄、高通骁龙835和8GB超大运存的一加5T进行多维度评测。那么，这款全面屏双摄旗舰在海外媒体们的眼里表现如何呢？看一看各家权威媒体对一加5T的评价。全球知名日报《卫报》《卫报》给一加5T打出了五星满分好评。著名安卓社区《AndroidAuthority》《AndroidAuthority》称：对于那些想在预算内买到高品质Android手机的用户来说，一加5T就是当下的最佳选择。知名科技媒体《techradar》《techradar》对一加5T的评价简短有力：旗舰杀手回来了！权威科技媒体《The Verge》《The Verge》给出的评价则是：5T这款手机定价$499，性能和外型却足以秒杀市面上定价为其两倍的手机。在相同预算情况下，你不可能找到比它更值得推荐的手机。权威科技媒体《engadget》《engadget》评价一加5T“更大的屏幕，更好的旗舰”。知名科技媒体《Pocket-lint》《Pocket-lint》给一加5T打出了5星的编辑推荐好评，并评价道：旗舰杀手回来了，比之前更大更好。知名科技杂志《Stuff》《Stuff》评价一加5T“全面屏和更出色的相机，价格一如既往的诚意”。知名科技媒体《9to5google》《9to5google》给用户推荐道：你想知道到底怎么选择一款好手机，一加5T一定是最好的选择之一。看得出来，国外科技媒体在第一时间给予一加5T的评价都还不错，该机采用18：9的6.01英寸全面屏，支持面部识别和指纹识别，拥有1600万像素+2000万像素组合的高清全彩双摄镜头，双f/1.7大光圈，人像和夜景拍摄都非常出色。一加5T搭载高通骁龙835处理器和最高8GB大运存，“双8”硬件组合运行任何大型游戏和程序都毫无压力。一加5T依旧支持边玩边充的Dash极速闪充。一加5T国内发布会将于11月28日14：00在北京举行，届时将公布一加5T在国内的售价，并将于12月1日正式开售。 +http://mobile.163.com/17/1122/10/D3RCT46T0011819H.html +Instagram推新功能：用户可申请加入他人直播 + + （原标题：Instagram推新功能：用户可申请加入他人直播） + 据外媒报道，几个月前，Instagram推出了邀请好友加入流媒体直播的功能。现在，这家社交媒体平台公司进一步扩展了这项功能--用户可向其他人发出请求加入其直播。当用户在观看某人直播时可以在评论区看到一个“请求”按钮。点击之后就能申请加入直播，一旦得到对方确认就能加入。据悉，这一功能现已经在Android和iOS两大移动平台上上线。 +http://bj.house.163.com/17/1122/09/D3R8MVEU000788HN.html +深圳烂尾楼拆迁赔了1.3亿?警方:中介造谣 将被拘 +（原标题：深圳烂尾楼拆迁赔了1.3亿？警方：造谣者为地产中介将被拘）“深圳北站烂尾楼拆迁赔1.3亿”谣言从嫌疑人孙某朋友圈传出，孙某的微信好友多达两千，该谣言发布以后迅速发酵，还产生各种不一样的版本，对社会造成不良影响。今日上午，深圳网警联合龙华警方已将编造散布谣言的嫌疑人孙某抓获，孙某对违法事实供认不讳。嫌疑人为地产中介据孙某介绍，他在龙华开了一家房地产中介公司，当天看到朋友圈里传播拆楼的视频以后，为了吸引客户来龙华买房，他便通过估算烂尾楼的面积和周边商品房的房价，得出赔偿1.2亿的谣言，并在朋友圈进行传播。就在警方抓捕嫌疑人孙某的时候，孙某还把朋友圈里的相关信息删除，企图蒙混过关。业主回应真实情况：补偿1600万对于外界对补偿金额的猜测，业主杨女士直言，房子是按照违法建筑来补偿的，加起来就是1600万，并不是谣传的2000万，甚至1.3亿。嫌疑人被抓目前，根据治安管理处罚法，孙某涉嫌扰乱公共秩序将被处于五日以上十日以下行政拘留并处罚金。深圳网警提醒市民：网上造谣需承担法律责任，切莫随意转发未经确认的信息。 +http://bj.house.163.com/17/1122/08/D3R6F5PU000788HN.html +报告：深圳1600万人租房 1100万人住在城中村 +（原标题：李宇嘉：从“深圳样本”看如何为租客守住低租金防线）近期，链家地产发布《深圳租赁》白皮书，第一次将1600万深圳租客的微观数据展示出来。不过，并不像有些媒体笔下的租房是何等“不易”，或如易居研究院的报告称，深圳的房租收入比（月租金/月可支配收入）高达54%。相反，深圳租客租金负担比较低。数据显示，目前有超过52%的深圳租客，其月租金支付不到2000元，18.2%的租客其月租金支付甚至在1000元以内；80%的租客租金占可支配收入的比例不到30%，还有近20%的租客，租金支出不到家庭可支配收入的10%。目前，深圳实际管理人口超过2000万，80%的人租房居住。全市1040万套住房中，70%的房子在出租。不管从租赁人群占比看，还是租赁房屋占比看，深圳不愧为全球住房租赁占比最高的城市，而且比租赁占比最高的国家——德国（租赁人群占比为60%）要高很多。尽管租赁需求很大，深圳寸土寸金，房价也很高，但广大租客守得一方宁静，并通过低成本租赁在深圳“扎根”。事实上，深圳商品住房的租金非常高，2017年1~8月的套均租金高达5005元，高于居民4000元的月可支配收入，比2010年上涨67.5%。但是，深圳城中村的存在，稀释了住房租赁成本，让上千万的深圳居民（特别是外来人口、大学生、创业人群等）有了安身立命的依靠。目前，城中村是深圳住房供应的主体，全市各类住房总面积大约5.20亿平方米（截至到2015年），其中商品住房和保障性住房合计占比仅为27.9%，而城中村住房占比高达50.3%。此外，上世纪80~90年代，外向型制造业主导深圳经济，并留下了6549万平方米的工业区配套宿舍，占存量住房总面积的12.7%，这也是深圳超低租赁成本的组成部分。据统计，深圳有740万套租赁住房，其中城中村租赁住房达450万套，占比为60.8%。据统计，73.8%的城中村住房租金在2000元以内，26.1%的租金水平在1000元以内。眼下深圳有1600万人在租房，1100万人住在城中村，这其中超过70%的租客住在租金低于1500元的城中村住房中，单间或一房一厅的租金甚至在600元左右。调查显示，90%的深圳租客为年轻人群（20~35岁）。20~25岁的租客中，月租金支付在1000~2000元的占比49.6%；26~30岁的租客中，月租金在1000~3000元的占比61%；26~35岁的租客中，月租金支付在3000元以内的占比70%。深圳的城中村租赁，不仅租金很低，生活成本也很低。不管是餐饮、零售，还是生活服务，其价格都比商品房小区要低30%左右。另外，经营场所成本高企、社区物业整治、城市公共环境管理等影响下，修雨伞、擦皮鞋、裤子锁边、配钥匙、修理家电等伴随居住的日常基本生活需求，提供服务的小摊贩在商品房小区已经很难找到了。但是，这类小摊贩不仅在城中村遍地都是，而且物美价廉。另外，早在2010年，深圳就在全国率先进入了存量房时代，经过政府主导的综合整治，加上原村民和村集体长期租赁经营，2/3的城中村引进了规范的物业管理、治安管理，不仅中低收入人群租住城中村，高学历人群租住城中村的比例也很高。目前，高中、专科和本科毕业等三个租客类别中，租住在城中村住房的比例分别达到65.35%、63.2%和49.9%。更重要的是，深圳城中村的住房，80%是违法建筑。但是，本着尊重历史、尊重现实的原则，政府认可立于其上的租赁关系，即有形的房屋或是不合法的，但无形的租赁关系是合法的。由此，深圳创新性地将有形的城中村与无形的租赁关系剥离，提出依据合法的租赁关系，分配公共服务的模式，在全国较早实现了“租售同权”、公共服务均等化。这也意味着，只要持有城中村租赁合同，并到市政府租赁办公室设在各街道的办事处备案，租客就可以加入全市所有居民（包括户籍居民）必须参与的公共服务排队分配，并通过“积分制”申请就近接受义务教育、接种疫苗等基本服务。据悉，绝大多数租住在城中村的家庭，小孩都可凭租赁合同入读公办学校。同时，城中村注册的企业，也可凭租赁合同获得合法产地证明，从而降低了企业营商成本。因此，各地发展住房租赁，最应该关注两点，即租赁低成本、服务全覆盖。作为租赁占比最高、房价高企、空间逼仄的城市，深圳上千万租客之所以能实现低成本“安居”，一方面在于，深圳本来就是由外地人构成的移民城市，从上世纪80年代建设特区伊始，深圳就自发确立“包容发展”的理念。既然都是外来人口、都怀揣创业梦想，就应该平等享受城市化红利。更重要的是，深圳是国内最早大规模利用集体土地建设租赁住房的城市。尽管深圳在2004年宣布全域土地国有化，但70%的城中村住房在这之前就已在集体性质的土地上建起了。顺应快速城市化、外向型经济，经营出租屋如同种粮食，这是原村民、村集体细水长流分享城市化红利的载体。上世纪80~90年代快速城市化过程中，为降低城市化成本，政府在征收原农村集体土地的同时，并没有将原村民完全纳入城市化管理，而是变相鼓励原村民、村集体通过自建出租屋的方式“自我城市化”，从而出租屋经济的体量越来越大，城中村租赁住房占全市住房的50.3%。目前，深圳917.8平方公里建设用地中，成本低、高密度的出租住房占了300多平方公里。而且，围绕原农村集体土地开发城市的过程，也造就了城中村在各区域点状分布，区域位置优良。链家报告显示，城中村租客通过地铁、公交出行分别占比30%和26.1%，30分钟左右的通勤占比55%。而且，长期以来，城中村租住人群已形成了以乡缘和业缘聚集的传统，这对于从“落脚”深圳到“扎根”深圳的外地人“本地化”进程、新型城镇化进程是一条自然的低成本的路径。近期，国土资源部和住建部下发《利用集体建设用地建设租赁住房试点方案》，决定在北京、上海等13个城市先行试点，核心内容是“试点城市村镇集体经济组织，可自行开发运营，也可通过联营、入股等方式，建设运营集体租赁住房”。笔者认为，利用集体土地高位蓄水（大城市集体土地和国有土地“对半开”）及巨大的“级差地租”，可有计划释放低成本供地，降低租赁供应成本。另外，村集体和农民掌握入市主动权（而不是被征收），借此可长期分享集体土地入市红利、城市化红利，相比一次性补偿的“征收模式”、建设并出售小产权房，建设并运营租赁住房具有细水长流地分享红利的特征，能避免资本对农地的觊觎，也能够调动村民和村集体的积极性。近日，北京已发布本地试点内容，2017~2021年计划供应1000公顷集体土地，占新增租赁住房用地的77%。这是一个好开端，其他城市如果能够跟进，将降低租赁住房供应成本。（作者为深圳市房地产研究中心研究员） +http://bj.house.163.com/17/1122/08/D3R6BQPN000788HN.html +高价地难卖出"高溢价" 去年地王"被破发"或亏本 +“限价”政策并未大面积放松，“地王”不亏逻辑或将被打破。对于2016年一、二线城市的地王和高价地来说，当初开发商拿到地王的兴奋，甚至喝酒庆祝的场景，很有可能将演变为财务报表上的亏损数据。昨日，同策研究院表示，在今年银行信贷紧缩、成交量普遍下滑的持续影响下，短期内确实令这些“地王”尚未开建便已“被破发”，或难以以盈利方式推盘入市，高昂的地价和趋稳的房价将形成尖锐矛盾，让绝大部分地王项目亏本。另据《证券日报》记者了解，关于2016年诞生的地王的命运，有些仍趴着不动，有些在缓慢建设当中，有些则找到了合作伙伴，正在酝酿入市。但不管是哪一种，短期内确实都面临着无法再以预期价格入市的压力，这意味着不但难以实现高溢价卖房，亏本也将成为大概率事件。入市遭拖延“高溢价”卖房难实现以现在开发商的能力来看，一般从拿地到销售可以控制在6个月-8个月之间，高价地可能稍微缓慢一些，但依然可以实现高周转。简言之，根据地产项目开发周期，大部分去年招拍挂诞生的“地王”，都会在今年或是明年上市销售。但从目前的市场环境来看，调控短期内不会放松。更重要的是，今年不少城市的“限价”政策严重拖长了这类地块的开发周期。据同策研究院监测，今年不少城市卖房都要按当地政府批准的价格来卖。这一限价措施2016年在南京、苏州等地首现，2017年则已经推广到了全国十几个城市。因此，有些房企迫于资金压力或是拿地必须动工的时效限制影响，“亏本买卖”也只能硬着头皮做，而且现在市场上也已经出现了这样的苗头。例如，前不久南京某楼盘毛坯均价25700元-25900元/平方米，该楼盘楼面地价22000元/平方米，房价仅比地价高3000元/平方米左右，接近“地价”卖房。有这么一类公司，公司定位于做高端精品，过去几年一直号称产品力较强，可以做“高溢价”，在拿地的时候也不惜代价，频频拿“地王”，也号称可以通过“高溢价”实现“地王”项目的收益。但是在今年市场长时间处于低迷期，“高溢价”就很难实现。而且这一低迷期将继续延长。同时，由于这类公司产品线偏高端，能够购买得起高端产品的客户往往被限购限贷，会导致“地王”楼盘成交不是很理想，难以实现溢价收益，最终影响这类企业的资金面。事实上，除了去年的地王项目，过去的高价地也受到了冲击。据《证券日报》记者获悉，北京某个豪宅项目，曾计划去年入市，但“8万元红线”限制之下，该项目预计以“10万元+”的销售单价入市遭到阻碍，其开发商为了盈利考虑，至今仍未入市，项目具备预售条件一年以上尚未开售，资金压力可见一斑。而在北京楼市，这类项目并不少，时间拖得越长，资金成本越高，对项目的利润侵蚀程度也随之越高。地王或陷入亏本激进抢地房企压力陡增盘点2016年争抢地王的房企，《证券日报》记者发现，有扩张需求的中小房企更为激进。事实上，这类房企信用评级较低，拿到低成本融资能力比大型房企更差，高价地在手无法快速变成现金，将会把企业拖进危机之中。对此，同策研究院也表示，以闽系房企为代表的激进型房企逆袭土地市场，激进拿地，频频制造“地王”，甚至个别房企的拿地金额已明显超过销售金额，房企拿地能力严重透支。这类房企在今年银行信贷紧缩的市场背景下，此前以高周转策略回笼资金的手段失灵。同时，资本市场融资成本居高不下，此时，这类企业拿“地王”的快感不在，已经受到资金链濒临断裂的煎熬。另外，过度依赖民间资本的企业和没有战略规划与风险控制标准的企业也将遭遇巨大压力。同策研究院认为，过度依赖民间资本的企业，最终因为拿地成本、融资成本过高等因素，导致项目定价偏离市场主力需求，销售上遇到瓶颈，企业遭遇资金链危机；没有明确拿地战略与风险评估机制的企业抢地王，属于市场跟风者，尤其是在招拍挂拿地现场，意气用事，赢了当时拿地的赌局，但是，随后市场瞬息万变，这类企业对“地王”楼盘难以把持，赢得赌局已变得更为非常艰难。值得关注的是，对市场有预判的开发商早有所准备。比如，信达地产与泰禾集团合作开发项目，或者一些房企将高价地转让部分股权，合作开发，分摊风险。“在激烈的市场竞争环境和楼市调控的背景下，土地更贵、融资更难、开发周期拉长、消费者对品质要求更高等，都成为越来越多房企选择合作开发项目的原因。”同策研究院认为，房企由竞争转为“竞合”，优化市场资源配置，有可能实现高价地的最大收益。更重要的是，开发商需要准备充裕的资金流支撑“地王”继续生存。企业需要寻求银行财团的大力支持，或是拥有充裕的现金流与融资渠道。今年，为了获得更多资金，无论是重回A股，海外融资、中期票据、债券融资等，越来越多房企在努力开拓创新融资方式，甚至一些表外高成本的融资，这也有可能成为房企的利润黑洞。 +http://bj.house.163.com/17/1122/09/D3R9V2HC000788HN.html +碧桂园等地产商跟投风劲 高杠杆捆绑管理层利益 +前10月，当碧桂园以4841.7亿的合同销售额站上行业之巅，行业内已经没有人怀疑，这家公司将把万科、恒大拉下马，成为今年的年度规模“一哥”。身处中国房地产行业第一阵营，碧桂园连续两年的翻倍增长一边让市场瞩目，一边让追随者们看到“规模没有天花板”。“给我一个支点，我便能撬动地球。”对于碧桂园来说，这个支点便是其在2014年推出的内部跟投机制。如今，在碧桂园的示范效应之下，国内对于“规模”仍有着执念的多数地产公司争相效仿，推出各自不同的跟投机制，以激发团队活力，将企业的“蛋糕”做大。时代的马蹄声中，越来越多房企都在开始加码跟投，无论是为了激励员工，还是绑定职业经理人，跟投似乎成为了地产圈的时髦热词。从一开始碧桂园、万科、旭辉的跟投推出，到目前中梁、阳光城等公司的跟投加盟，房企正在不断推行跟投。碧桂园等地产商跟投风劲 高杠杆捆绑管理层利益大公司示范效应国内最早将具有“合伙人”概念的跟投机制引入管理运营的公司并非碧桂园，而是行业多年来的“带头大哥”万科。万科旗下项目跟投制度的实施是在2014年3月，万科第十七届董事会第一次会议审议通过了《关于建立项目跟投制度的议案》。一年后的2015年3月，公司第十七届董事会第五次会议对项目跟投制度进行了第一次修订。项目跟投制度是万科事业合伙人制度的重要内容。事业合伙人制度包括事业合伙人持股计划和项目跟投，合伙人持股计划发生在公司层面，即公司合伙人通过券商集合计划购入股票；跟投制度则具体到项目层面，即建立跟投机制，公司员工在一定比例内可以投资公司的新项目，而项目的管理人员必须投资。数据显示，万科2014年全年公司开放跟投项目47个，申请跟投达到9089人次，到了2015年，全年累计开放76个项目。紧随万科之后，碧桂园将跟投机制发挥到极致。碧桂园的跟投机制晚万科半年，起始于2014年年末。据悉，在碧桂园董事局主席杨国强的大力推动下，碧桂园旗下的所有新项目都将采用跟投机制，即项目经过内部审批定案后，集团投资占比85%以上，员工跟投的资金池可投入不高于15%的股权比例。碧桂园员工跟投的15%的资金池分为三级：第一级是在总部的平台共同组成一个基金，每个项目投5%，保证对每个项目的平均支持；第二级是区域团队跟投5%；第三层是项目本身的团队也投5%。碧桂园对于项目公司主要负责人的跟投起点做了一些硬性规定，以确保项目管理团队对于所管辖项目保持较高的责任心。也正是因为这样，该集团区域总的投资比例较大，也使得这些“封疆大吏”拥有较高的投资回报。2016年末，碧桂园旗下投资及奖金收益最高的区域总裁，合计年收入超过1个亿。碧桂园2017年中期业绩报告显示，该公司旗下已有973个项目引入合伙人跟投机制，其中435个项目已然开盘销售，员工跟投资金池合计投入7.2亿本金。无论碧桂园内部，还是行业内，均将碧桂园过去几年来取得的快速发展归因于公司的制度建设，尤其是跟投机制对于公司效率提升的作用十分明显。该公司披露的数据显示，跟投机制实施以来，公司项目平均开盘时间由过去的9～11个月缩短为6.9个月，净利润率由此前的10%提升至12%，年化自有资金收益率由过去的30%左右提升到81%，现金流回正周期由原来的10~12个月缩短至9.1个月。跟进者风格趋于激进鉴于碧桂园在经营上取得的良好表现，以及较为成熟的跟投机制，多数地产公司将碧桂园模式列为模仿目标，并在细节上针对各自企业做了调整。“我们内部一直对管理层是强行跟投，通过跟投和扁平化管理来提高效能。”三盛集团董事长林荣滨告诉记者。不断扩张的中梁地产通过跟投机制不断激励自己的员工。其推出的成就共享及项目跟投激励机制，中梁的一个销售30亿的区域团队能够拿走五六千万的奖金。区域部门负责人以上必须跟投，中梁的项目跟投制度，控股集团8%，区域集团8%，区域公司8%，合计24%，远高于行业水平。核心管理层强制跟投，其他人员自愿跟投。与行业内其他企业要跟投几个项目公司才配杠杆不同，中梁一跟投就配杠杆，提供内部1∶4的高杠杆，加上中梁大部分是十几二十万平方米的项目，周转速度快，平均6个月就开盘，7~8个月现金流就能回正并分配本金，利润则分两次分配：回款达到70%时分配一半的利润，回款达到90%利润全部分配。中梁内部将跟投的员工叫战略股东，优先分利润。员工跟投的自有资金收益多数项目达到200%以上。除了较为传统和保守的跟投机制，不少公司在跟投机制设计上十分激进。第一财经记者从一家上市房企内部人士处了解到，目前该公司正在内部推行自己的全面跟投机制，按照每个业务条线和岗位的不同而有不同的倍数。其中，总监级杠杆预计大概在8倍，总经理级杠杆大概在12倍。由于这样的杠杆放大，这意味着高管团队可以分享超过10倍的投资收益，同时也需要承担亏损的10倍放大风险。同时，在自有资金部分，公司给每个管理层划分了跟投的金额，在自有资金不够的情况下，公司还可以提供有息借款。这样的跟投虽然是风险共担，但是从目前房地产行业的特性看基本都是盈利的，可以看出公司对高管的激励非常大。不过，鉴于该公司的跟投资金中有相当大一部分是将年终奖部分的激励拿到跟投进去，因此实际倍数并没有那么多。也就是说，公司把企业的经营状况和管理层进行绑定，希望借此来提高管理效率。监管壁垒随着国内房地产行业的高速发展，人才缺失已经在很大程度上制约着许多企业的发展，房地产行业的跳槽也因为猎头的活跃而变得十分频繁。最大限度留住人才，捆绑员工和企业收益，是许多地产公司推出项目跟投机制的初衷。随着跟投规模的扩大，这项制度背后涉及的股东与管理团队利益之争，成为一个难以绕开的问题。虽然无论万科还是碧桂园，跟投机制的实施对于提升公司绩效有着积极作用，但回归到公司运营上，公司内部人士通过跟投分享了股东原有收益，这涉及到上市公司的道德风险。数据显示，自从万科实行跟投机制以来，其利润分配情况发生了轻微变化。2014年，万科实现净利润192.9亿元，同比增长5.41%，其中，归属于股东的净利润为157.5亿元，较2013年的151.2亿元增长4.2%，增速低于净利润增幅，而此时少数股东的损益是35.42亿元，同比增幅为11.42%，增速高于净利润。少数股东分走的净利润占比为18.36%。2015年，万科实现净利润259.49亿元，同比增长34.53%，其中，归属母公司股东净利润仅为181.19亿元，少数股东损益为78.3亿元，同比增长121.06%，分走的净利润占比提高至30.17%。为限制内部通过跟投分走股东收益，今年年初，万科通过公告发布修订项目跟投制度细则的通知，这是该公司跟投制度的第二次修订，此番修订的出发点，便是试图限制跟投，协调股东与管理团队之间的利益分配。在全行业层面，监管层也对房地产企业的跟投出台监管措施。11月3日晚间，深圳证券交易所下发关于《行业信息披露指引第3号——上市公司从事房地产业务（2017年修订）》（下称《指引》）的通知。《指引》新增对房地产行业上市公司与员工共同投资房地产业务的规范等，这被认为是对风靡房企的“跟投制度”的规范。 +http://bj.house.163.com/17/1122/09/D3R8PT6C000788HN.html +毕业生租房被要求办"分期" 房管员:不办就搬走 +（原标题：租房“被网贷”？ 不接招就请搬起走）不愿因租房而背上贷款，21岁的赵国琴和刚大学毕业的严明娟从刚租了半个月的房子里，搬了出去。两人从成都蓉和家园房地产经纪有限公司成都第三分公司(以下简称蓉和家园)以“押一付一”的方式租下一间房子，不料半个月后却被要求通过某分期产品支付房租，担心自己被贷款，两人拒绝。11月16日，两人被要求搬离，同时被搬离的还有其他三名不愿意接受“应花分期”的房客。成都商报记者调查两个房产中介发现，对于押一付一的租客，两个中介公司均要求租客以“分期产品”贷款方式支付月租，不少租客在不知情下“被贷款”。中国人民银行成都分行营业管理部征信服务大厅工作人员告诉记者，贷款之后一旦逾期未缴纳房租，贷款不良记录将被记录在征信中。一个月前，赵国琴和严明娟一起到了成都工作，急需租一间房子，在58同城搜索租房信息，租房信息“押一付一”的付款方式吸引了两人。赵国琴说，房源位于武城大街三洲娇子苑小区，由蓉和家园出租。看房后，10月14日，她们在该公司签订了租赁合同，并通过支付宝支付了1个月押金和1个月15天的房租。差不多同一时间，同一套房的其他3名租客先后入住这套房子。“室友都是刚出社会不久的，房子环境不错，大家相处挺愉快，打算长期住下去。”赵国琴说，11月14日，应该缴纳下个月房租时，蓉和家园房管员来了，要求所有租客必须办理“应花分期”产品，且将手机、银行卡、身份证提供给他操作。被拒绝后，房管员表示，如果不办理分期产品，将会视为违约，搬离房子，且不退押金和剩余15天房租。“当时签合同的时候只说分期产品是一个交房租平台，从来没有说这是一个贷款软件。”赵国琴说，事后她了解到，“应花分期”是一个贷款软件。11月16日下午，赵国琴和其他3户租户一起到蓉和家园协商，要求退押金退房租，公司答应退费用，但要求4户租户必须立即搬离房屋。这几天，刚大学毕业的赵鑫(化名)正在能不能搬家发愁。今年7月，他从小家联行房地产经纪(北京)有限公司(以下简称小家联行)以“押一付一”、月租为1000元的价格在青羊区万和苑租了一间房子，先缴纳一个月房租和押金。8月他入职银行，才了解到每月用于缴纳房租的“会分期”是一个贷款软件，仔细核对合同的约定内容，确定自己“被贷款”了，不过令他疑惑的是，整个合同约定中，没有一个字提及到贷款。“知道自己被贷款，房东服务不好我也不敢大声跟他们反映。”赵鑫说，在得知自己被贷款后，他曾想搬走，但让他担心的是，剩余贷款期数他还需要还么?“当时签合同时，就说是一个分期支付房租的产品，协议从头到尾没有提贷款一个字，而且整个操作都是中介公司人员引导操作。”对于“应花分期”和“会分期”这两种分期产品，蓉和家园娇子苑房管员刘先生说：“不止我们公司，基本上所有房地产经纪公司对押一付一的租客都用这种分期产品。”该公司区域经理苏孟行说：“分期产品不是贷款软件，就是一个交房租分期月付产品，如果不租房子自动解除，不会对征信有任何影响。”小家联行成都城市经理李先生也基本是这个解释。“应花分期”所属的上海前隆信息科技有限公司品牌公关总监张琳向成都商报记者介绍，应花分期就是一种消费贷款软件，该公司就是一家消费金融服务机构。成都商报记者通过“会分期”公司客服向该公司提交了采访请求，但截至发稿时没有收到回复。中国人民银行成都分行营业管理部征信服务大厅工作人员告诉成都商报记者，如果贷款出现了逾期，只要贷款公司将数据上报给征信中心，贷款逾期记录将作为不良信用报告记录在征信中。“不管你是逾期一天还是两天，只要贷款公司上报，逾期一天也是不良记录。” +http://bj.house.163.com/17/1122/06/D3QU4BLB0007823B.html +北京新房成交均价逼近6万 低价房源买一套少一套 +网易房产数据中心统计显示，上周（11月13日-11月19日）北京全市新建住宅（不含保障房、两限房）网上签约369套，成交面积约为5.47万平方米，成交均价为59622元/平。不同价格成交段成交金额榜 +http://bj.house.163.com/17/1122/09/D3R9TQAL000788HN.html +男子因宅基地纠纷砍邻居致2死2伤 称为自我保护 +（原标题：宅基地纠纷 男子砍邻居两死两伤）因两家的宅基地纠纷，40岁的周建军与强行踹门闯入的邻居发生冲突。后周建军拿铁锤、菜刀，将邻居家4人的头面部和四肢砍伤，致其中父子二人因颅脑损伤合并创伤失血性休克死亡，婆媳两人受伤。昨日上午，周建军因涉嫌故意杀人案在北京市二中院受审。被害人家属作为刑事附带民事原告出席，要求周建军进行赔偿。被告人称为自保持刀“乱挥”昨日上午，因涉嫌故意杀人罪，40岁的周建军在二中院出庭受审。公诉机关指控，今年4月29日傍晚6点，周建军因宅基地纠纷与邻居发生口角，对方进入周建军家中，双方互殴。周建军拿铁锤、菜刀将4人的头面部和四肢砍伤，其中父子二人均因颅脑损伤合并创伤失血性休克死亡、婆媳二人受伤。事发后，周建军选择报警，被随后赶到的民警控制，后被刑事拘留。公诉机关认为，周建军多次反复击打被害人头面部、四肢等要害部位，已经构成故意杀人罪。建议法庭判处无期徒刑以上处罚。“我们认为这种行为非常恶劣，建议法庭判处死刑。”被害人家属补充说。周建军在庭审中称，两家住宅紧挨着，因邻居家新建的屋檐伸到自家这边，双方产生矛盾。据周建军描述，事发时他正在垒砌砖墙，试图把这个通道堵住，并因此与邻居发生冲突，受到对方的攻击，于是他抄起菜刀，对着众人“乱挥”。“我就是怕他们打我，我想自我保护。”公诉方指伤害集中在头面部庭审现场，被害人家属作为附带民事原告，要求周建军赔偿死亡赔偿金、丧葬费数百万元。对于周建军持刀“乱挥”的说法，被害人亲属表示不认可，当庭追问“老太太都倒在地上了，你为什么还拿着家伙往她身上打？”“你记得砍了多少刀吗？”“你有意识到会造成死亡吗？”公诉人也表示，被害人身上的重物击打伤、刀伤都集中在头面部，有10多处创伤。公诉人认为周建军犯罪事实清楚，证据完整，其否认不是用刀“砍”而是“乱挥”；与其他证据不符合，建议法庭不予采纳。周建军则回答，“当时很乱，我记不清楚了”、“当时已经蒙了。”周建军辩护人则认为，被告人属于激情犯罪，主观恶性较小。双方一直有纠纷，没有得到有效解决，才会导致事情的激化。拿刀是在紧急情况下的迫不得已。周建军没有前科，属于首犯，且主动报警，属于法律上的自首，希望得到从轻处罚。该案当庭未宣判，双方就附带民事部分达成和解意向。 +http://bj.house.163.com/17/1122/09/D3R9Q0OO000788HN.html +万科股价再创新高 郁亮：行业已到危急关头 +（原标题：万科股价再创新高，郁亮：行业已到危急关头，要转型租赁企业）万科A（000002.SZ）股价再创历史新高。截至11月21日收盘，万科A报31.79元/股，尾盘封涨停。万科A早盘低开后快速走强，午后股价即达到31元/股，达到历史新高。目前万科第二大股东，由广东商人姚振华所实际控制的宝能系合计持有28.04亿股万科A股份，占上市公司总股本的25.4%。按照摩根大通此前发布的一份报告显示，宝能系累计共斥资约451亿元买入万科。以此计算，宝能系持有的这部分万科股份的市值约为888.21亿元，浮盈约437.21亿元。而万科的第一大股东深圳地铁集团，持股比例为29.38%，目前持有万科A的这部分市值约为1027.38亿元。5个多月前，中国恒大（03333.HK）以18.80元/股的价格将持有万科A的1553210974股股份转让给深铁。根据此前披露的数据显示，恒大系持有万科A的成本为23.35元/股，恒大系在收购万科A方面耗资362.73亿元。从目前万科A的股价来看，如若恒大系持有万科A这部分股权至今，恒大系可获得浮盈约131.03亿元。而此前中国恒大将万科A的股权转让给深铁之时，产生的亏损为70.7亿元。近期，万科董事会主席、首席执行官郁亮提出，万科集团（A股代码：000002.SZ；港股代码：02202.HK）未来要成为美好生活的场景师。郁亮在11月10月曾对澎湃新闻（www.thepaper.cn）表示，万科集团要顺应时代发展的趋势，成为城市配套服务商，希望成为美好生活的场景师。“美好生活场景师的区别在于，没有指标，没有赚钱的目标，这没有硬性的衡量指标。我们只能做农民做的事情，继续努力工作，给大家提供粮食。”据新华网报道，郁亮称，下一步万科要在恢复住房的居住属性、回归房地产初心上作出努力和贡献。郁亮说：“高速扩张期过后，中国房地产行业已经到了危急关头。提出房地产行业属性的回归，不仅是中国经济稳健成长的需要，也是房地产行业自身发展的需要。” 此外，郁亮表示，万科计划数年后，成为全球领先的住房租赁企业。但这不是万科转型的所有。万科未来的发展理念，就是以人民的美好生活为中心，成为美好生活场景师、创新探索试验田、实体经济生力军、和谐生态建设者。此外，从10月18日起，万科内部进行各类形式的学习党的十九大精神活动。讨论中，“人民美好生活”“共建共享”等词汇频频出现。郁亮表示，党的十九大精神对万科而言是调整发展策略、经营计划、管理制度的根本指引。 +http://home.163.com/17/1122/07/D3R36DJ100108C5E.html +25万改造90平旧房显艺术范 比意大利的民居还洋气 +蛋彩画是一种古老的绘画技法，盛行于欧洲文艺复兴时期，是用蛋黄或蛋清调和颜料绘制而成，多画在敷有石膏表面的画板上，其特点不易剥落，不易龟裂，色彩鲜明而保持长久。这套旧房改造的设计初衷是希望这一份美丽，能在时光中保持长久，历经时间的冲刷也依然在记忆中保留鲜明。这套旧房的改造，设计师提供了由旧到新的变革途径，运用古旧的元素来诠释现代人的生活方式，隐喻文艺复兴时期对个性的解放，对生活的歌颂赞美，肯定“人”在现世生活中的创造和享受。不到90平的总面积，容纳了大于其表象的更多东西。1、改变陈旧落后的家具及软装；2、在有限的空间内加强收纳功能。玄关地面采用黑白棋盘格瓷砖，让空间显得活泼有趣，只要一眼就会爱上。客厅整体色彩鲜明而活泼，在高纯度色彩的家具中，墙上挂画的大理石纹自然凸显。艳红三座布艺沙发与鹅黄单人沙发碰撞出强烈的色彩冲击力，加上角落的青翠绿植，使得空间呈现出生机勃勃的感觉。阳光透过大大的落地窗洒满地面，让人自然感受四季的变化，将户外景色尽收眼中。黄铜、大理石、原木、麻黄藤编，不同的材质之间充分交织，表达出强烈的艺术情感和对审美的追求，这种表现形式使艺术更具生命力和吸引力。茶余饭后，躺在摇椅上，听一首自己喜欢的音乐，或读一本最近爱看的书，或者什么都不做，只是静静地看日落，简简单单就把日子过成了诗。跳跃的玫瑰金收纳架满足了工作上的收纳需求，需要的用品，顺手一拿即可。透过屏幕都能感受到业主在工作台前活动的自在和惬意，踏踏实实用心做自己喜欢的东西，安安静静看自己喜欢的书，就是生活最美好的样子。餐厅的艺术气息不输美术馆的café，不但能安抚你的艺术魂，还能顺便满足你的挑剔味觉。空间配色跳跃又意外地和谐，空间错落精巧，风格出众，很难不被吸引。长条形的白色餐桌上铺着一块颇具民族风的桌布，在这个颜色素雅的餐厅里面，成了最亮眼的一块。玫瑰金球形吊灯比较耀眼，在照明的同时又体现了餐厅的浮华气息。石膏像置于餐边柜上，业主一家坐在这里用餐，便能在一片艺术氛围中享用珍馐与美酒。墙壁上黑色的铁艺收纳架带点锈迹的时光感，文艺又复古，在这里摆放几盆可爱的多肉、或是挂上几张明信片，都散发着浓浓的生活气息。线条简约的餐边柜承担着重要的收纳功能，既可放置碗碟、杯盘等餐厨用品，又可以摆放业主最爱的艺术作品。餐桌上藤制桌垫搭配布艺桌布，彰显出特别的和谐之美，精巧的布置让人从视觉上就能先饱餐一顿。小空间的厨房更需要布置的巧思。L型橱柜设计充分利用了空间，常用的餐具都放在墙壁的置物柜上，不占用做饭的空间。洗菜盆紧靠着明亮的窗户，在通透的自然光中下厨也能让心情愉悦起来哦。米色橱柜搭配白色墙壁让空间显得干净整洁；色彩靓丽的菠萝造型花瓶，为厨房增添一抹亮色，在这样清新的环境里烹饪，自然会有一份好心情。杏色、大地色、藕荷色与水绿色，在半倾斜的户外阳光下，呈现出莫兰迪静物写生般的和谐色调，让人进入卧室能不自觉地安静下来，没有一丝焦躁的感觉。床头上方选择了对称的复古黄铜吊灯，使空间趋于平衡，在明媚的阳光下沉淀着光阴。卧室采光很棒，拉开双层柔纱窗帘，便能让阳光悠悠地泻下。卧室粉红、粉蓝的世界，没有浮尘杂质，有的只是纯粹透明。以简单圆形小边几作床头柜，粉色的花瓶搭配鲜花为空间注入了一点点的跳跃色彩，并呈现优雅气质。卫生间干湿分离，淋浴区的墙壁大面积铺贴大理石纹的瓷砖，显得清爽整洁，又带有一丝丝原始粗犷的气息。简洁而不失高雅的黑白浴室柜体与金属把手完美融合，瞬间提升了卫生间的颜值。 +http://home.163.com/17/1122/07/D3R1FJSO001081EI.html +董事长住一年3㎡垃圾箱 将其逆袭成送快递的豪宅 +最近几天，全国大范围降温，冬天的气息越来越浓烈。家居姐裹着厚厚的羽绒服有时候都会觉得冷，看到街上的流浪汉们更是觉得冬天他们的生活更不容易了。冬天的寒冷让流浪者更难寻找到合适的栖身之所，有的流浪者甚至会睡到垃圾箱里。但是，睡垃圾箱的并不只是流浪汉，有一个董事长就住垃圾箱住了好久。美国Kasita董事长兼联合创始人杰夫·威尔森，花费自己的一整个学年的时间，住在3㎡的垃圾箱里测试可居住空间的限制，虽然实验是极端的，但他获得了灵感。下面就跟家居姐来看看这个代价不低的灵感能带来什么样的好发明！ +http://home.163.com/17/1122/07/D3R21Q77001081EI.html +投资大佬全球各地买房做特色民宿 光日本就7座 +最近的天气真是有点疯狂啊，北方的各位（女）汉子们，今天穿秋裤了吗？都说“美丽的外表千篇一律，有趣的灵魂万里挑一”，如果这个“有趣的灵魂”还痴恋装修事业，那会装出怎样的家呢？今天要和大家分享的这个“有趣的灵魂”就是薛蛮子，就是那个开生日Party半个投资圈的投资人都会到场的知名天使投资人，风趣幽默的老顽童，同时也是热爱美食的吃货。就是这个对世界怀有无限好奇心的人，在世界各地旅游的时候，突然发现自己喜欢改造老房子，并且希望能够拥有自己改造的民宿。野心无比大的他，希望他改造的民宿是一个“阅览世界”的窗口。因为痴迷京都的古老气息，他一口气买下了位于京都得7栋百年老屋。为了保留町屋的原汁原味，对一些老屋薛蛮子只做适当调整软装的打造，做了兼具度假体验的软装设计，让每个角落都是一幅唐风宋韵的画卷。这次京都的改造实验让薛蛮子彻底爱上了装修这个活儿，他买下了无人岛，并且打算无色一个法国古堡，作为他接下来“练手”的载体~这么有趣的老顽童，会设计出怎样的房子呢？ +http://home.163.com/17/1122/07/D3R21R4T001086FG.html +你家的浴室安全吗？浴室装修5大重点拿走不谢 +装修浴室千万别本末倒置，虽然好看的外在很重要，但浴室的功能性才是装修的关键。浴室里面有很多安全隐患要考虑，比如说地板是不是防滑，热水器等用电安全吗。那么，怎么才能打造一个安全舒适的浴室空间呢？小编为此特意整理了几个浴室装修重点，来看一看吧。浴室装修1、安全的扶手安全的扶手通常是为老人和小孩安装的，可借力让使用上更便利，但是为了安全起见，我们建议有需要的家庭可以安装。因为不知道什么时候会在卫浴空间摔倒。浴室装修2、舒适的水温在冷冷的天气可以泡个暖呼呼的澡，是最舒服的事了！但是没有注意到水温会被烫伤的，我们建议可以把热水器的调至40℃以下。这样，即使是小朋友打开热水，也不会被烫伤了。浴室装修3、防滑的地砖铺上止滑的板岩砖地坪，可以防止走出浴缸或淋浴后，有滑倒的情况发生。若还是喜欢大理石的质材，我们则建议在表面做特殊的安全处理，例如喷砂或纹理交错的方式，产生具有防滑的效果。浴室装修4、吸水的踏垫一些家庭会在卫浴空间干湿交界区，放置一块毛巾可以把脚擦干。我们建议可以选购一块具有吸水的地毯，带走脚上的水分。浴室装修5、暖风的设备冷天洗澡最痛苦了，长辈们更是有心脏负荷上的问题，其实目前市面上已推出具备科技人性化的设备，例如暖风干燥机，它包括换气、暖风、干燥、凉风等功能。使是寒冷的冬天，也能在入浴时保持舒适的温度，让大小朋友都不会着凉。（来源：齐家网）装修严选免费设计免费提供多种设计方案 +http://home.163.com/17/1122/07/D3R1FHBO001086FG.html +重装修时代已经过去 必须知道的软装搭配知识 +经历了繁复华丽的重装修时代之后，我们进入了"轻装修，重装饰"的时代。其实，过软和过硬其实都只是一种失衡，真正的和谐，应当是二者的融会贯通，和谐共生--让硬装带好软装的面具，让软装穿上硬装的外衣。装修是件麻烦事，你要有机敏的反应，来跟无数的商家打交道；要有丰富的备战知识，来辨别所有物质或非物质商品的真实价值；你要有充沛的精力和体力，来维持自己燕子筑巢般的每一步；而在这些之前，你必须首先要有一个敏锐的触角，才能跟得上，甚至可以领先于整个市场潮流，才能让你家的大工程，不至于刚一完工，就已不再新鲜。装修市场发展到今天，人们已经越来越认识到硬装的灵活性和软装的功能性，是可以相辅相生的，彼此渗透，相互替代。这种融合了简单、灵活、个性、创意和功能于一体的理念，正在迎合着新一代装修者的心态而慢慢的崛起，在未来的装修业中，必然会占据越来越多的位置和分量。东汉班固的《酋都赋》中有"屋不呈材，墙不露形，毅以蘸绣，绍以纶连"的描写。硬装完全可以放下它的"架子"，去完成软装饰"灵活"的使命，而软装饰也可以成为硬装的一部分，去构筑个性化的、属于主人自己的空间。（来源：齐家网）装修严选免费设计免费提供多种设计方案 +http://home.163.com/17/1122/07/D3R21QLQ001086FG.html +阳台太空不用苦恼 做个地柜好看又实用 +阳台是一个永久不过时的话题，懂生活的人，会把阳台布置得实用又美观，如果在阳台做吊柜，下面是放洗衣机，如果洗衣机不放阳台，不防试试做成地柜。基本上我们看到的阳台地柜有两种呈现形式，一种是在阳台两侧做，这种方法一般比较适合两侧也为窗户的阳台。地柜搭配吊柜做在阳台一侧也可以这种方法比单做一个地柜的储物量会更大一点另一种就是沿窗做一整排的地柜收纳能力也比第一种强得多当然，如果你愿意，还可以做一整面墙的收纳柜看起来会更大气一些这种阳台柜子，最适合放棉被、过季的衣物等易潮易发霉的杂物另外，如果玄关比较小，放不了几双鞋的话，把鞋放阳台柜也不错。不过需要注意的是阳台做柜子，背面的防水层一定要做好，防水层如果没做好以后可能会发霉，根本存放不了东西。而且阳台要晾晒衣物，底部可能会有积水，所以柜子距离底部最好留一点空间，防止板材经常在水里泡着，影响板材使用寿命。阳台地柜用的板材和吊柜没什么差别同样需要性能稳定、不易变形常见的有密度板、胶合板、生态板等。（来源：和家网）装修严选免费设计免费提供多种设计方案 +http://home.163.com/17/1122/07/D3R1FK83001086FG.html +闺蜜入住新房，送这些家居装饰品好看寓意又吉祥 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重视“人性”的复苏譬如空间设计要求明亮，这样能够使人保持心情的愉悦，点缀明亮的色彩，增添活泼的气息。同时在需要隔绝视线的地方，则使用中式的屏风或窗棂，通过这种新的分隔方式，单元式住宅就展现出中式家居的层次之美。餐厅 古典风格与现代风格的激情碰撞新中式风格家具配饰上多以线条简练的明式家具为主。通过中式元素与现代材质的巧妙兼柔，明清家具、窗棂、布艺床品相互辉映，再现了移步变景的精妙小品。吧台 对文化韵味的无限释放他可以不华丽，却一定栖息着心灵的本真和至臻品格。为自己营造一个遗兴的闲适空间，偶尔情趣使然小酌一杯，正式结合了时代与文化的灵魂。卧室 灵与静的唯美境界卧室设计在保留传统中式风格含蓄秀美的设计精髓之外，更呈现现代、简约、秀逸的空间，使环境和心灵都达到灵与静的唯美境界，迸发出更多可能性。影音 放松身心的空间影音室是休闲放松的空间，所有的陈设都放置到了最舒适的位置，深蓝色的沙发与烟墨色的背景画搭配同会客空间相呼应。本期网易装修套餐推荐:点此免费报名预约：华浔双11优惠返场：人工费8折，设计费4.8折 http://zhuangxiu.home.163.com/combos/103.shtml装修严选免费设计免费提供多种设计方案 +http://lady.163.com/17/1121/15/D3PDOEO500267VQQ.html +43岁的贾静雯生三个娃却依旧美成少女 秘诀是... 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+昨晚的维密大秀，除了奚梦瑶的一摔，亮点还挺多，比如国内来看秀的嘉宾们...连195cm的高以翔都能拍成这样，摄影师昨晚心情估计不是很好....其中的重灾区，就是我们的pgone同学.....摄影师怕是没被rapper打过....为了给万万挽尊，必须上官方的精修图了，明明是同一件衣服，腿长了一截不说，气场都不一样了...后期必须加鸡腿！港真，明星们真的应该给工作室的修图师们涨工资了，不上个对比图你们都不知道人家有多努力！这双鞋子，被网友diss惨了...然而，拯救这双鞋子的，是修图师！你们说，是不是应该给修图师涨工资？！上个月赵丽颖生日，她的工作室发了一组庆生照↓赵丽颖在下面和工作室开起了玩笑：“你们的图修的，真的惨不忍睹啊....”其实还好，哪有什么惨不忍睹。不过丽颖啊，其实工作室的小伙伴，已经很努力了，真的。你们再看看工作室发的精修图，画风秒变，年轻了10岁，也没那么油了。毛衣都从中黄色变成了柠檬黄。你们看，这程度的话，工作室已经很厉害了吧.....工作室发的照片，明明是同一个动作，瞬间高大上有木有。但是再看工作室发的精修图之后，首先整个皮肤变得都很通透，而且还很紧致，瞬间觉得有精神了。皮皮刚想硕给修图师加个鸡腿的时候，发现下面这张精修图是不是有点太夸张了，连胳肢窝都给磨平了...之前参加某活动的时候，他的现场照是这样的...嗯......比例嘛...有点....为了证明的确是现场照，上个动图↓然而，你们看看人家工作室之后发的图！是不是对修图师肃然起敬了，腿长两米有木有！甚至有些官媒发的图，还把裤腿给拉直了233333333333333....修图师下手好像重了些....对比照太残忍了......对大长腿有执念的，还有我们的晓明哥...结果有网友发现，为了拉腿，修图师把轮胎都给p成椭圆的了....后来豆瓣八组的网友，非常厉害的把轮胎恢复了原来的形状，晓明哥的腿也随之....短了一截....所以你们看看，一个靠谱又合格的修图师是多么重要！修图的时候下手不能太轻，不然跟原图没差，更不能太重，因为容易看出破绽....必须给那些有“起死回生之效”的修图师涨工资！最后一句你和明星只差一个负责的修图师！ +http://lady.163.com/17/1122/07/D3R2C68G00267VA9.html +现在的90后每个月收入多少算正常？ +看看大家晒自己的收入同为90后的你，收入如何呢 +http://lady.163.com/17/1122/07/D3R2PFAA00267VA9.html +近期被这样美好的爱情甜炸刷屏了！ +作者：院长说起来实在有些羞射……你们院长我，一个见多识广的老司机，一个玻璃心已经被炼成金刚心的老少女，最近竟然又掉进了一部青春网剧的大坑。来，一起打着滚回到久违的青春时代吧！(*??*)《致我们单纯的小美好》港真，最早听到剧名时，院长心里还是拒绝的...总觉得像这种叫《致XX》的影视作品，有强行贩卖青春炒冷饭的嫌疑。但不得不说，好看的剧就是套路多啊！前段时间，我先被下面这组截图刷屏了——图书馆里，娇小的女生想拿高架上的书，偏偏够不着。于是，男生出手了……乍看没啥特别对吧？就是颜值高点，身高差和对视也挺萌。然而，镜头一转——What???少女你跑图书馆里看这什么鬼？！哈哈哈哈哈哈嗝~于是结局就来了……说好的浪漫偶遇、你侬我侬、学霸夫妇一起努力携手走向明天什么的……不存在的！只有萌到哭的身高差是真的！！《致我们单纯的小美好》是个不大不小的IP剧，改编自赵乾乾的同名小说。没什么狗血刺激的套路，也不会强行重口耍另类，就像片名那样，只是希望观众从中看到美好和心动，然后在角色的一举一动一眼神中仿佛回到了那些单纯美好的旧时光，砰的一下少女心就炸成了烟花！它有个最难得的地方：在扩展原著没有的情节、人设的同时，也没有失去原著又甜又萌又俏皮的精髓。无论是选角还是新加的剧情，书粉大多都表示满意。这在IP改编里简直是一股清流。女主陈小希，非典型学渣。在青春里，喜欢的心藏都藏不住。于是，陈小希开始了自己的倒追之旅。而在这段旅程中，她的单纯、笨拙制造了不少笑料。早上家门口堵，上学路上追，学校热烈表白；上网学大招，每天送早餐，再日夜研究情书……最后当然是——全搞砸！这大概就是学渣本渣了...男主江辰，则是高度还原的高冷学霸本霸。不缺脑子不缺颜，更不缺妹子们的爱慕眼神。对待陈小希的热烈追求，他从来只有一个反应：大写的拒绝。但——陈小希这枚少女分外与众不同。她受尽挫折不气馁，坚定一个江辰不动摇。你不爱吃包子，我明天早上送油条；江辰退后一步，她就厚着脸皮再往前走。为了达到目标，这个有点“死心眼”的少女什么都干得出来！于是，两人相处时就很像在台上说相声。一个蠢蠢的不知道自己有多萌，一个暗戳戳吐槽宛如冷面笑匠。江辰却故作冷漠脸丢了个嘲讽炮：然而……火炮就像被丢进了大海，一点用都没有。妹子根本听不懂嘲讽，光顾着庆幸分数线低了五分，“不然我差一分就考不上了”！真是好单纯好不做作……你可长点心吧！暗示听不懂，但人家会百度啊！感受一下来自学渣灵魂深处的疑问：“如何赢得男生好感？”这下好了，一路被坑——为了蹭人家车，放自己自行车的气：装学霸，被当众拆穿。号称写了首情诗，一念出来：“我的爱如潮水，爱如潮水将我想你推。”你是怎么忍住不唱出来的？！哈哈哈哈哈哈！最搞笑的还有这个梗——陈小希站在楼道里突然戏精上身，拉着江辰就陪自己演戏。“尔康，是你吗尔康？！”“不是。”哈哈哈哈紫薇看了想打人！每一次蓄意接触，每一次告白失败，每一次你追我跑……花招频出，笑料不断。因为陈小希的出现，江辰变成了全校最口嫌体正直的人。他并不想承认，但眼神和举止却出卖了他那颗被撩动的心。陈小希因为能跟江辰一起上学，会忍不住地偷笑，多希望这段路能够长一点，再长一点……而江辰呢，看似不屑，其实他明明会在不经意间偷瞄陈小希，嘴角还带着浅笑。生怕别人看到，又赶快敛起笑意……这一连串微表情真是要把我看醉了，啊啊啊傲娇的学霸敲可爱！还有“你的单车后座只有我能坐”这个梗——陈小希撒娇卖萌求上车，江辰虽然嘴巴里说着“不带”，还坏坏地嫌她重：但其实他自己大长腿迈上车后，就站在原地等着陈小希跳上后座。感受着对方的靠近，在不动声色间就脸红心跳了起来！“陈小希，你脸皮呢？” “送你啦！”这台词配合两人远去的背影，真是甜出糖尿病了！！还有一起坐公车时，江辰忙着保护陈小希。不小心碰触到对方时，他会忍不住地眼神闪烁，紧张到吞口水。然后低头发现自己胸口留了根她的头发，他竟然撩起来对着头发偷笑……对着头发偷笑...偷笑...你的高冷男神范儿呢？就被一根头发俘获少男心了吗？！！不知道大家有没有发现，在面对喜欢的人的时候，你的心就变得毛茸茸的，一丝一毫都容易被对方撩动；而对方在你眼里也变成了仿佛小动物、小婴儿一样的存在，又呆萌又可爱又让人想保护……不知不觉间，江辰面对陈小希就是这么个态度——陈小希被锁在家里，面对防盗门里的他，江辰表示有些尴尬：陈小希还不知道为什么，瞪大了双眼：于是...江辰就又害羞又尴尬了起来。因为更想给她喂东西吃了啊！！这两人一个害羞闪躲一个害羞追问的状态真是萌哭了！放学路上，因为袖子被陈小希哭湿，到家弟弟问他怎么了。他回答的是，被小狗舔了。科科科科小心思都暴露了哦江辰同学ヾ(?●?●)?嘴上永远嫌弃，然而陈小希一给他打电话，从来都是秒接。即使对方巴拉巴拉巴拉的说个一大堆，他也会静静的听，而且嘴边还挂着笑。这种溶于无形中的宠溺，简直是太致命。更夸张的是，当陈小希为了等自己上学，而在路边哭到睡着的时候。他居然已经把持不住开始偷摸了！然后又露出了宠溺的微笑……陈小希，你知道自己那一刻有多幸福吗？真是让人羡慕到面目全非啊！！其实，这一幕也是剧中出现多次的互文手法——在江辰生病的时候，陈小希偷偷跑去照顾他。面对那么帅又安静的一张脸，她也忍不住伸出手指……无论是学渣还是学霸，无论是热情还是冷静，无论是感性还是理性，在面对喜欢的人的时候，你的一举一动都会暴露自己的心，因为喜欢是藏不住的啊！不是一家人，不进一家门啊、，还是那个字：甜！(′`〃)除了口嫌体正直，江辰还是吃醋界的一把好手。知道有其他男生送她回家，下意识开始黑脸。看到吴柏松给她夹鸡蛋，眼神开始不对。再看到两个人搂搂抱抱……紧蹙的眉头、眼中的怒火，已经快要憋不住了！然而在陈小希遇到难题的时候，他看似不关心，其实又在意得不得了！即使是迎着老师的批评，他也会不顾形象地站起来维护陈小希。毕竟谁能舍得这么萌的腿部挂件？校园青春片难拍，难就难在观众都上过学，都经历过那些兵荒马乱又单纯美好的日子。所以，如果制作不走心演员又浮夸，就很容易显得假大空。而《小美好》很机智——首先在剧本上就避开了浮夸的空中楼阁，而是着力营造角色们的“青涩感”。无数恰到好处的细节堆起来的细腻情感，才是打动人的关键。打开这部剧，你就能看到无数只有17岁才会经历的小甜蜜。比如，偷看可以说是青春时期感情懵懂的初始象征，而剧中女主无时无刻不在偷看男主。教室的偷瞄：操场的注视：还有主动一点的，花式祈求坐男主的单车后座。另外，剧组在服化道和其他细节设置上也十分接地气，高度还原十年前的环境，分分钟就让人感觉穿越到了青春时期，代入感特别强烈。然后就有女生改裤脚，或者有美术大神在衣服上作画。老师每天都打着复习的名义，把音乐课换成英语课。即使校长每天三申五令不让早恋，大家还是暗戳戳地进行各种地下情书活动。最后就一起进办公室写检讨书……2005年，大街小巷都是《超级女声》的录像和海报，火得能上天。陈小希就是李宇春的死忠粉，天天想着上大街让路人帮忙投票。注意她穿的黄色回复和玉米标志！班上女生追的剧也都是什么暑期大戏，百播不厌的《还珠格格》和《新白娘子穿传奇》。于是就出现了陈小希看小燕子五阿哥接吻，被老爸发现的一幕……还有这个把我笑出猪叫的镜头——陈小希披着床单挂着纸巾唱白娘子，又被老爸发现。老爸：我这女儿怕不是个傻子吧？？？哈哈哈哈哈哈哈哈哈哈！！！这些接地气的剧情台词和有趣的梗无处不在。它们与观众们的记忆交织，不但引起共鸣，也让一颗颗少女心开始沦陷……当然，如果套路不喜欢，导演还准备了反套路——比如院长开头提到的那一幕，打脸来的太快就像龙卷风。还有两位主角的拥抱，是这样的：温柔的戴围巾，结果是这样的：猝不及防的转变，让观众在懵逼和傻笑之间成功得炸成一朵烟花。看着看着，你会情不自禁地深陷其中，会忍不住感慨：这就是青春啊！不需要那么华丽，更不需要那些狗血的多角关系和撕逼，只需要桌面上垒得高高的辅导资料和假装不在意却心慌意乱的一个个眼神……最后还有重要的一点——演员。之前院长就说过，好一点的青春片，通常都有一张对得起青春的脸。所谓青春，靠的不是老黄瓜刷嫩漆和矫揉造作的演技，而是骨子里的单纯、青涩与执着。在这一点上，两个主角虽然演技都不够纯熟，但正是这样的青涩使得他们的表演恰到好处，更有说服力。男主胡一天，93年出生的真·鲜肉。颜高腿长的绝佳优势加上逗比的性格，在《小美好》播出后吸粉无数。由他出演外冷内热的男神江辰，几乎没有任何违和感。一个眼神秒杀一切。无论是忧郁日系范儿，还是阳光少年，他都能呈现。可塑性特别强。女主沈月则凭着清纯少女感和可爱无敌的大眼，在《小美好》开播前就把人彻底萌翻。穿上学生制服坐在教室中，一秒让人回想起学生时代暗恋过的女生。笑容特别治愈。到现在，《致我们单纯的小美好》只播了8集，但我身边的妹子几乎都沦陷了……评论区也是各种被甜到牙疼。其实，除了甜，院长觉得这剧还有个特别打动我的地方——陈小希身上的勇气。当第一集里她向江辰告白后，得到的是“我不喜欢你”的答复。如果是一般女孩子，或者是历经世事的人，听到这句话肯定会伤心、甚至气急而怒。然而，陈小希只是转转眼睛，失望了一小下就撂下一句话：“那我再想想办法。”那一刻，我不知为何有种泪目的冲动……时光会一点点偷走你胸口的勇，岁月会教导你服从现实。当你回顾青春时，看到一个女孩毫无畏惧的眼神，并且用行动去追求自己的梦想，这才是青春里最好的事吧！ +http://lady.163.com/17/1122/07/D3R48BTK00267VA9.html +男子蜗居“脑瘫村”捡垃圾养活智障妻与脑瘫儿 +谭湘平带着儿子在医院 本文图片均为澎湃新闻记者 蒋格伟 摄谭湘平一手端着脸盆，一手拿着尿不湿，来回踱步在湖南省儿童医院儿童重症监护室门口。他不时凑近监护室的玻璃门，眯着眼睛瞄一眼躺在病床上的儿子轩轩（化名）。与一周前澎湃新闻（www.thepaper.cn）见到谭湘平情景不同的是，那时，他佝偻着身子，左手用一根麻绳牵着妻子，右手推着一辆破旧的儿童车，车里坐着仅两岁的儿子轩轩。每经过一个垃圾堆，他都会驻足，然后上前在垃圾堆里捣鼓一番，试图能找出一点能换钱的废品来。正在重症监护室门口等候11月13日上午11点50分，儿子轩轩身体突然抽搐，被紧急送往湘雅博爱医院治疗，花400多元后，治疗无果。当日下午两点，轩轩又被紧急送往湖南省人民医院治疗。挂号前，谭湘平搜遍了全身，仅有11.5元，而挂号需要12.5元。谭湘平稍犹豫了下，然后把攥在手里的11.5元伸向了挂号窗口，希望里面的工作人员可以给他挂个号。最终，在志愿者的帮助下，挂号成功，轩轩做了检查。谭湘平说，虽然很苦，但他不会放弃老婆和儿子轩轩的。妻儿谭湘平必须得撑起这个家，因为“一家人都得靠自己照顾。”“也许是上辈子造了什么孽”，谭湘平说，父亲前几年中风，没有了劳动能力；母亲患有30多年的精神疾病，妻子智力有障碍，儿子又是脑瘫。一家三口?2014年，谭湘平与老乡刘伟平相识后结婚，组建了自己的家庭。打击接踵而至。2015年，儿子轩轩出生。生下来不久，他发现儿子“头跟没骨头一样，很软，身上多处关节无法直立。”根据随后湘乡市人民医院与湘雅博爱医院的检查，轩轩被诊断为脑瘫，当时医生说，通过治疗可以改善。儿子轩轩（化名）从此，谭湘平每周6天都要带着孩子去湘雅博爱医院做六个项目的康复治疗，经过两年多的坚持治疗，“现在脖子可以撑起脑袋了。”当问及“轩轩能不能开口说话”时，谭湘平说：“还是期待他好起来。”澎湃新闻试着与谭湘平妻子刘伟平交流，“你喜欢你的孩子吗？”“喜欢！”她微笑着说。“最喜欢孩子什么?”她愣住了，谭湘平过来解释说：“你问的问题超出她智力范围了。”刘伟平站在原地，不知所措，傻笑，眼神里透着迷茫。父母亲也是谭湘平的牵挂，在湘潭县湘乡老家，母亲经常走丢。谭湘平打开手机，翻出母亲的照片。“我担心她再次走丢，所以给她拍了一张照片。”谭湘平喃喃道。15平方米的家11月10日，澎湃新闻走进谭湘平15平方米的租赁房。38岁的谭湘平，个子不高，不喜欢说话，看上去，满脸疲惫。只有主动和他交谈的时候，他才会聊上几句。他带着记者来到住所，穿过一个综合市场，巷道里很黑，没有路灯。一家三口拾荒走到他家楼下时，看见一辆婴儿手推车，上面堆了一些杂物。谭湘平指着手推车说，“这是与老乡在医院捡的一辆手推车。”楼道很窄，很难想象谭湘平是如何同时抱着手推车和儿子下楼的。穿过楼道就是谭湘平租来的家——位于湖南长沙县星沙城西安置小区的一间包括卫生间在内15平米的二楼出租房。房租300元，按月支付。房间里杂乱、充满了压迫感。一张放着被子的小床，几个小板凳，一张放着油盐酱醋的桌子。桌子上有一个电磁炉，地下放着两个电饭煲，其中一个，已经坏了。屋中放置一个小推车，衣柜放在小床的一侧，旁边堆满了杂物。妻子刘伟平正侧身坐在床上，眼神呆滞。看见有陌生人进来，她抬头微笑了一下。谭湘平调侃三口之家做饭艰难，“我们就在窗台做饭”。他走向前，将窗户打开让记者看，一边将电磁炉放到上面，“因为上面挂了袜子，有水。所以我就把电磁炉拿了进来。”谭湘平说。澎湃新闻发现，在谭湘平租赁房对面，也是一户脑瘫家庭，他们同样在窗台上做饭。窗台做饭邻居何先生说：“谭湘平是一个很节俭的人。他很少买菜，很多时候是去附近的菜市场捡一些菜叶子做饭。”“他很少向人诉说苦处。记得有一次。他家里没米，没有跟大家说，他就自己去商店里面赊了一包米。住在这里的人，很少诉苦，因为大家都为生活所逼，都很苦。”何先生说，谭湘平唯恐给他人添麻烦，少见求助于人。“没想过要放弃”谭湘平目前唯一的经济来源就是捡垃圾，一个月也就是三百多块收入。一家人的生活必需，每天开销要二十块左右。一天三餐就是一些炒青菜或者青菜煮汤，偶尔会买几块钱瘦肉，给孩子煮一些肉末。家中的桌子?虽然生活充满了不幸和艰辛，但在谭湘平说自己每天在感恩中度过，因为很多爱心人士惦记着他们。“家里很多的物品都是爱心人士捐赠的，例如衣服、玩具、厨房用具。”谭湘平已经很久没有买过衣服了，孩子身上穿的基本都是捐赠的衣服。谭湘平回忆道，去年给孩子买过一件很薄的衣服，结果今年穿就小了。他的脸上表现了一种无奈，并且说：“我不会买（小孩子）衣服。”谭湘平撸起自己的袖子，指着袖口磨出的破洞说，“我这衣服穿了五年了，还很好。”澎湃新闻注意到，他裤子的口袋和裤边也已经磨破。妻子依旧坐在身旁，一言不发，只是偶尔抖抖腿。谭湘平起身走向衣柜，从衣柜里面拿出一件玫红色的呢子衣，这是他今年给妻子买的一件衣服。妻子一人坐在家中?谭湘平拿着玫红色衣服在妻子身边比划着，妻子抬头看着谭湘平，微笑了起来。面对眼前生活的艰辛，谭湘平说：“生活上有难处，撑不住了，但是没想过要放弃。周围还有那么多人（同样在）坚持。”捡垃圾在小屋里谈了约一个半小时，谭湘平面带尴尬的说，我要出去“工作”了。他口中的工作，就是出去捡垃圾。少了一个轮子的手推车佝偻着身子，左手用一根麻绳牵着妻子，右手推着一辆破旧的儿童推车，里面坐着2岁的轩轩。每经过一个垃圾堆，他都会驻足，然后在堆里捣鼓一番，这是谭湘平每天的日常生活。与别人不同的是，谭湘平是选择每天晚上带着妻子和孩子出去捡垃圾。“早上的时候，一些环卫工人会捡一些垃圾，他们也需要生活。所以我会晚上出去捡垃圾。”谭湘平每天晚上七点多，都会带着孩子和妻子出门捡垃圾。他首先会将儿子连人带车端下楼，然后在妻子的手腕上系一条布绳牵着走。“我走得快，怕她跟不上我。”差不多晚上10点的时候，他会带孩子和妻子回家，因为那时候，孩子要睡觉了。等孩子和妻子入睡后，他再次出门捡垃圾。“他经常一个人凌晨两点多才回来。”隔壁邻居何先生告诉记者。“有时候一天收入五六块，好的话有十多块钱，一个月可以挣三百元左右。”谭湘平说，捡垃圾是一家人主要的经济来源。仅仅依靠捡垃圾，一个月收入只有三百元，显然不够。“如果没有爱心人士的帮助，我很难坚持到今天。”谭湘平数次提及，“真的特别感谢丫丫妈妈，是我们这个小家长期的守护神”。谭湘平口中的“丫丫妈妈”，是帮助他们的义工彭望平女士。收到爱心人士筹集的善款?彭望平告诉澎湃新闻，“自己是去年开始帮助谭湘平一家人的，经常送油米和衣服。”彭望平说，除了自己之外，其他爱心人士也经常前来援助。在彭望平眼中，谭湘平是一个老实而有责任心的人，“对待自己的妻子和孩子一直没有放弃，而且都很有耐心，这让我很感动。”挂号轩轩病情突然发作，让一直默默坚持的谭湘平不知所措。11月13日上午11点50分，轩轩身体突发抽搐被送往湘雅博爱医院治疗，花了四百多元后，治疗无果。当日下午两点，轩轩又被紧急送往湖南省人民医院治疗。在挂号前，谭湘平身上仅有11.5元钱，而挂一个号需要12.5元。差一元钱，谭湘平犹豫了下，他还是鼓足了勇气，把攥在手里的11.5元钱伸向挂号窗口，希望里面的工作人员给他挂个号。?最后在彭望平帮助下，轩轩挂了号，做了检查。医生告诉谭湘平，轩轩需要马上转院，住重症监护室进行治疗，大概需要花费一万多。这对谭湘平来说无疑是一个打击，身无分文的他，不知拿什么让孩子转院接受治疗。听到这个消息后，彭望平在朋友圈里发起筹集善款，为轩轩筹集治疗费用。截至11月14日凌晨0点47分，共筹集12051.72元。这些善款是由彭望平的朋友以及爱心人士捐赠的，“有捐五块的、十块的，还有捐几百的、一千的”，彭望平拿着登记捐款数额的本子告诉澎湃新闻。目前，轩轩转院至湖南省儿童医院，14日中午，已住进重症监护室接受治疗。谭湘平日常背的书包谭湘平说，从14日中午入住医院起，他已交了5000元押金，到15日中午，窗口显示已欠住院费300元，花费近7000元。11月15日，轩轩这次发病被确诊患有癫痫，仍在重症监护室。谭湘平说，“我不会放弃老婆和轩轩的。” +http://lady.163.com/17/1122/11/D3RFOA6P00267VA9.html +这六种女人最贪钱，男人们怕了吗？ +吝啬型：典型表现爱财如命，喜欢不劳而获吝啬鬼不必多说了吧。她在大多数时候拼命地存钱，不过她攒钱不是为了别人，而是为了在很短的时间里将所有的钱挥霍一空。她会因为拥有了金钱本身而快乐，她要的就是财富的增加，无论以什么形式拥有了什么东西，她都会感到无比欣慰。不过，别指望她随意扔掉点什么东西，比如残旧的家具、过时的衣服，这对她来说是件难事。人们有很多获取金钱的方式，继承、赢取、挣得，但对大多数人来说，钱是劳动所得。但是吝啬型的她在想象金钱的时候，却很少会联想到自己要做的工作。她在某些方面很节约，但在某些方面却会大肆挥霍。好比一个人交替患上了便秘和腹泻。她最怕的就是别人向她索取礼物，或者向她借钱，这些行为真的如同摘她的肋骨般让她感到痛楚。她是最需要改善自己的心理状况的。她必须正确认识金钱的意义，必须以实用的价值观来看待金钱。喜欢收集的她一定要培养收集金钱之外的一些爱好，比如集邮。这能令她转移收藏的热情，以便以更轻松的角度来看待金钱。天真型：典型表现不会算计、更重精神世界其实，她的生活是很简朴的，住什么房子，穿什么衣服对她来说都无所谓。她不修边幅，这也和她的自我感觉有关，天真的她深深沉醉在自己的精神世界中，对于她来说，一切外在的修饰和她的精神世界相比都显得黯然失色。因此，有些邋遢的形象根本不会对她造成任何负面影响。恐惧型：典型表现认为金钱带来了混乱她害怕金钱，因为大笔能支配的金钱对她来说是太过放任和太过自由了。在她看来，有了金钱，她可能就会有随心所欲的行为，从而陷入困境的可能性也更大。所以她喜欢存定期储蓄，为的就是使自己不能轻易地提取这些钱。她花钱的时候相当谨慎，并会询问各方面的意见，如果她下不了决定，就将钱存入银行。最终，她可能因为不花一分钱而攒下了一笔可观的财富。低享受型：典型表现只懂攒钱，不懂享受她经常幻想，如果有朝一日自己拥有了一大笔的财富的话，她会买些什么。遗憾的是，即使拥有了这么一大笔钱财，她也不懂得合理消费，享受生活。是的，她根本缺乏享受的能力。她天生与有质量的生活绝缘，她的存折上可能有着惊人的数字，那都是她省吃俭用的成果。这笔钱是她预留给孩子的，她会因此非常欣慰。她是在为别人储蓄。由于无私奉献的行为在我们的社会中一直起着积极的作用，因此这种人给人的形象当然是不错的。她也偶尔挥霍，那就是当她的无私奉献没有换来相应的感谢的时候，她会抑郁，会在某个时间段内开始对自己不那么苛刻了。不过，当她忘却了这种伤害以后，一切消费习惯又打回原形。冲动型：典型表现不考虑支付能力，追求随心所欲的感觉她永远没有计划地支出，在购物的时候她永远那么冲动。即使自己的账户透支了，她也不愿意记录一下开销的状况，从而使自己对收支状况做到心里有数。她不愿意那样做，她想保留那种放任冲动的快感。倘若她一旦开始计划一下自己的财务，那么她的冲动本能和自由都将受到限制。她不愿意承认钱是挣来的这样一个事实，她们认为钱是可以从天上掉下来的。倘若有人批评她为了这些东西花费了太多的金钱，她会立刻兴奋起来，并不停地为自己辩解。而在她振振有辞的辩解中，却能听到很多天真的想法。她一见到大减价的东西就会立刻抢购，尽管买回家后这些东西就长久地躺到了柜子里，永无用武之地，但她一定要买—因为就物品本身来说是合算的，她已经管不上它们实用价值了。虚荣型：典型表现只为体面花钱，不考虑实用价值怎么一眼看出她是虚荣型的消费者呢?不妨观察一下她对于汽车的选择，如果大家都认为别克车是老板身份的象征的话，她买的一定是别克，尽管美国车对汽油的消耗量超级惊人，尽管她买车的用途只是家用，而不是商务。而且，她还会给自己的车加上市面上能搜罗到的所有奢华装饰：什么卫星定位系统、车载电视、按摩座椅。她实在太喜欢用钱购买别人的认可了，尽管自己囊中羞涩，但同学聚会时她还是咬牙为整个饭局买单—为的只是显示自己混得不错。对于虚荣型的消费者来说，最好尝试与自己虚荣的欲望保持一定的距离，努力做到有目的的消费，每次花钱时都不妨迫使自己的虚荣心做出一些让步。 +http://lady.163.com/17/1122/11/D3RG86PI00267VA9.html +扶奚梦瑶的那个模特火了，网友说她是天使本人 +我不想再去赘述奚梦瑶摔倒的原因，也不想去探讨奚梦瑶本人的业务能力，当然更不想安慰。奚梦瑶当时摔得有点厉害，头饰错位，脚也肿了，一直跪在地上整理容颜，花了足足十秒钟。十秒钟其实已经够一个模特走半圈了，奚梦瑶没有立即站起来，其实是严重打乱了后面的节奏。但是她的素养特别好，她还是从容的掐着时间走了出去，因为这个时候只有她能带起节奏来。有人说她走到面前扶奚梦瑶的动作很正常，任何一个普通人都会这样做，是，我相信都会。但这不是普通路上，是维秘秀场，她这样扶的举动，直接意味着她可能和奚梦瑶一起被后期剪辑掉。如果她直接跃过奚梦瑶走掉，是一点问题都没有的，但是她还是站稳脚跟，扶奚梦瑶，让她先走。而她自己站在原地，和旁边的观众互动，并且，和后面的超模一起给奚梦瑶鼓掌加油。等到奚梦瑶定点动作完成之后，她才开始走，她的情绪完全没有被奚梦瑶带走，而是自信从容的亮相。但是因为后面排了很多人，Gizele Oliveira不得不加快自己的脚步，可能原本二十秒走完的路，她用力缩减到了十几秒，维持了应该有的节奏。也不能怪国外的媒体抨击奚梦瑶，因为她的失误导致了后面的人损失了时间，要知道巴西喜欢她的观众也都在等待她的出现。好像这是她去面试维秘的照片，感觉非常的自然，又干练，脸蛋长得也小巧玲珑。她本人是非常重视这次的走秀，看她的ins都知道，一连更新了四张维秘的现场照片。虽然遇到这样的情况，但是她的应急能力是看得出来的，首先是个人，然后才是一个模特。她这样的举动也得到了不少群众的表扬，她的粉丝是蹭蹭的往上涨，ins上面都爆炸了，全是过去感谢的。包括维秘的大老板，也对这件事情发了话，安慰奚梦瑶是小，主要的呢，是在表扬Gizelle，说她简单雄辩的姿态，是一个伟大的胜利，他很骄傲。虽然言语之间有点官方的意思，但是也足以说明她的名字已经被大老板给记住了。奚梦瑶明年走不走说不准，但是这个Gizelle明年肯定还是会走的，毕竟要兑现自己的姿态。Gizelle真的是很棒了，但是光是心地善良还不说，她本人其实也是被低估的超模，她很漂亮。她的身材很好，随便躺在湖面上，就能拍出这样的大片。地铁上都没人拦得住，随便往地铁一靠，一张杂志封面的照片就出来了。根本都不用用力的去凹造型，随便一张侧脸杀，背影杀，调成白黑，就非常的有质感。而且脸蛋也极小，天使的脸蛋，五官非常的立体，轮廓的线条也是比较的硬朗。当然和我们审美的锥子脸肯定不同，她是有点方的，但是柳叶眉特别的黑弄，眼里散发着巴西得天独厚的阳光。不用夸张的修饰，就本身就有那种感觉和属性。有个段子说，超模和普通的模特不一样，超模就是超级模特，就是要时时刻刻分分秒秒都都保持最佳状态。我觉得这句话用在Gizelle身上就恰到好处，翻了她几十页的照片，不管是街拍还是抓拍，她都是很好的样子和状态。这么好的资本，还有一颗善良的心，肯定能走的更好，虽然这次不那么完美，但是这个举动赢得了掌声。 +http://lady.163.com/17/1121/07/D3OI1PR100267VA9.html +维密：同款睡袍 谁最会撩？ +还有Karlie Kloss的银发出镜，柔美的姿势，轻撩头发的瞬间，都是超级有气场超级美的！秀前当然也不忘敷眼膜唇膜，Alanna Arrington真的是美得一丝不苟！当然如此的造型也能成功吸睛。当然除了个人照还有集体合照，“群模共舞”的瞬间当然也不能错过!还有这几乎没穿上的睡袍，大秀好身材的维密天使，属实赚足眼球！最后一句Hot body看不尽啊~ +http://lady.163.com/17/1121/14/D3P71AP700267VA9.html +“中国居里夫人”的传奇人生 +这成为诺贝尔奖的遗憾。从2005年开始，温家宝总理先后6次去看望她。这位巨匠名字叫何泽慧，山西省晋中市灵石县两渡人，她的成就绝不亚于刚获诺贝尔奖的屠呦呦，她才是正真的明星。她是山西成就最高的科学家。她一生简朴，温家宝评价她：何先生在女科学家中是少有的，是人中麟凤。她生于1914年，2011年去世。世界物理界对何泽慧三个字充满敬意。1913年山西灵石声名显赫的何家在苏州的"灵石何寓"落成。第二年，何泽慧出生在苏州园林式的大宅院。《灵石县志》记载，清朝，何家就先后考取15名进士，29名举人，22名贡生，65名监生，74名生员，故在山西流传着"无何不开科"的说法。而何泽慧的父亲何澄也是山西首批留日学生。承载着家族的期望和父亲的教育，何泽慧同她的兄弟姐妹们个个都非常有出息。18岁时，何泽慧考入清华大学，26岁时，她在德国柏林高等工业学校成功拿到了博士学位。后来成为她丈夫的钱三强当时考到了法国巴黎大学居里实验室，跟随居里夫人学习镭学。几年后，何泽慧也去了钱三强的实验室，与钱一起发现了铀核的三分裂，又独自发现了铀核的四分裂。这项发现在国际科学界引起很大反响，因为三分裂出现的概率是三百分之一，四分裂出现的概率是万分之一。何泽慧因此也被赞誉为中国的"居里夫人"。和居里夫人的合影1948年回国，先后在北平研究院原子学研究所、中国科学院原子能研究所、中国科学院高能物理研究所工作。在高能天体物理、宇宙线物理和超高能核物理等领域，取得了具有中国特色的科研成果。86岁时，何先生每周还要坚持几次到高能物理所上班。晚了就从食堂买几个包子、馒头带回去吃，渴了就喝点白开水。她家住在中关村，所里想派车接送，她坚决不要，还是挤公共汽车。何先生也经常会一个人坐公交车去买菜。她就像一个普通老太太，让你感觉不到大科学家的派头。她的生活一丁点儿也不讲究，书桌上的镇纸是老人自己捡来的鹅卵石。在人们都开始用名牌武装到牙齿的时代，老人依旧提着一个人造革书包，那书包带子已经断了，用绳子系着，革裂开了，用针线缝了起来。她的衣服上还有补丁，脚穿老式解放鞋。单位几次来说可以搬到条件更好的院士楼居住，但都被何泽慧拒绝了。在1994年国家科学出版社出版《中国现代科学家传记大辞典》时，她坚决不同意立传。故在此系列丛书第六集"物理学"部分，没有她的名字。她的传记出现在了书中最后。编者不得不加了特别说明："此篇传记虽早已约稿，但因何泽慧本人谦让不同意立传，后在本书编辑组一再要求和催促下，作者才着手撰写并于全书付印前交稿。因全书页码已定，不便插入相应学科，故补排在最后。特此说明。"何泽慧常放在嘴边的一句话是："国家是这样一种东西，不管对得起对不起你，对国家有益的，我就做。"1992年6月28日，钱三强逝世。1999年9月，中共中央、国务院、中央军委授予他"两弹一星功勋奖章"。自钱三强去世后，家里的东西几乎没有变过。不论是卧室还是书房，何泽慧都尽可能地保持着钱三强生前的样子，也许这就是她纪念钱三强的最好方式。2005年，温家宝总理首次前往何泽慧的住处探望她。已经满头银发、91岁高龄的她，却依然还在工作。她不缺钱，生活却是非常简朴，衣服上都是补丁，穿的是解放鞋，挤公交车上班。有时候就在单位食堂买几个馒头带回去吃。这种淡泊名利，不求任何享受的品质让温家宝总理极为敬佩。何泽慧说："作为一名科学家，本来就应该朴素、真实、勤奋、诚实、讲真话。"温总理答应何泽慧说："我一定不失约，每年都来看您，希望您身体健康。"2011年6月20日7时39分，何泽慧院士在北京协和医院逝世，享年97岁，居里夫人的外孙女发来唁电。党和国家领导人都发来唁电，对何泽慧院士的逝世表示沉痛哀悼。一位画家形容何泽慧：“她是一块纯白的玉，非常质朴。”附：何泽慧的家人外祖母：王谢长达，近代女教育家，振华女子学校创始人。父亲：何澄，近代实业家，同盟会成员。母亲：王季山，物理学翻译家、曲学家王季烈妹妹。丈夫：钱三强，著名科学家。大姐：何怡贞，著名金属物理学家。大哥：何泽明，原北京钢铁学院院长。弟弟：何泽涌，山西医科大学著名教授。妹妹：何泽瑛，南京植物院资深研究员弟弟：何泽源、何泽诚、何泽庆均为高级工程师、资深教授。女儿：钱民协，北京大学化学与分子工程学院教授。儿子：钱思进，北京大学物理学院教授。看完，心中只有敬意，她才是正真的明星。 +http://lady.163.com/17/1121/13/D3P4IJ5U00267VA9.html +华媒：大马情感诈骗案 七成受害者为华裔女性 +文章摘编如下：“如果受害者能在汇款前，先致电或前往银行询问，便可避免受害，但大多受害者被爱情蒙蔽双眼，任自己的血汗钱被人骗。”达威根说，在2017年前十个月中，大马警方共接获102273宗商业罪案的报警，总损失额竟超过23亿令吉。他指出，这些案件中，有22587宗案件涉及诈骗成分，其他案件未归入商业罪案。这也意味2万多宗的案件里，涉及的损失额超过23亿令吉，损失非常惊人。达威根指出，若警方发现居民的银行户头涉及不正常的交易活动，警方将援引刑事法典第420(诈骗)条文，展开逮捕行动。为全力打击诈骗行为，大马警方与贸消部紧密配合，监督可疑的公司。达威根指出，马来西亚国内合法投资集团一年能获得最高10%的报酬，一旦高于此数目，必定有诈。某些诈骗集团推出每日1%或每周10%的高额报酬，吸引人们投资，而这些行为皆是诈骗集团的诱饵。他说，网络诈骗案的金钱流动来去无踪，尽管不容易集齐证据，但警方已着手处理，并会在掌握证据后，将调查报告交由副检察司定夺。 +http://lady.163.com/17/1121/11/D3OV1LFE00267VA9.html +如果重返20岁，你还会选择那个他吗？ +也许真是贫贱夫妻百事哀，俩人被生活的重担压得喘不过气来，大学谈恋爱时的甜蜜浪漫早就消失得无影无踪，只留互相埋怨，心中怨怼。马珍珠怪崔半岛赚不到钱，也不帮忙带孩子，崔半岛嫌弃马珍珠人丑事多脾气差，俩人对对方的称呼也从恋爱时的“亲爱的”变成“大婶和小气鬼”，最后终于在大吵一架里结束了婚姻。之所以剧名叫《GO back夫妇》是因为，离婚后，俩人一觉醒来，发现意外穿越到了自己20岁的躯壳里，他们刚刚相遇的年纪。20岁，充满胶原蛋白的年纪，无忧无虑的年纪，编剧给落到低谷的主人公一个绝佳的大礼包。两人唯一不满的地方恐怕是，对方也穿越回去了，开始的时候，他们依然冤家一样，一碰上就互相斗嘴埋汰，想要老死不相往来，却还是因为对对方的牵挂扯上了关系，至于电视剧最后是“爱与和平”还是“主角就此分道扬镳”就不在这里剧透了。本剧分为18年前和现在两个阶段，虽然横跨了18年，饰演主角的演员依然没变，对他们的演技考验很大。男主孙浩俊可以说是大器晚成，1984年出生的他，直到快而立之年才在《请回答1994》里被观众熟知。女主张娜拉是大家的老熟人，最让人惊讶的是她的保鲜技能，笔者小学时候张娜拉就长这样，过了十几年她仿佛更年轻了。81年出生的她不管是双马尾还是粉红西装配短裙都毫无违和感，扮演20岁的大学女生依然有信服力，反而是扮演中年人的时候，即使穿得再邋遢朴实，男主角和路人喊她一万遍大婶，也很难让人信服。看到她只能感慨，岁月这把杀猪刀只杀猪，对张娜拉毫无用处。从中年穿越到青年，电视剧就此实现了中年人和年轻人的互相审视。一方面赤裸裸地展示了中年人随着年龄增长失去的东西，一方面又提醒了年轻人应该珍惜却忽视了的地方。穿越到了20岁，两位主角以前那些不屑做也不敢做的事都能做了。38岁的崔半岛宁愿多带一把伞也不要和马珍珠同撑伞，回到20岁了宁愿淋湿肩膀也要和初恋撑一把伞。38岁的马珍珠不敢穿膝盖以上的裙子，回到20岁了短裙立刻就穿上了身。剧中直接借马珍珠的独白说出了原因。简单说就是，“我”被年龄束缚，向年龄妥协了。38岁的崔半岛和马珍珠已经不会互叫爱称、提前准备纪念日礼物，甚至对话也不再有耐心，只是争吵和互相诋毁。这一切改变都在“老夫老妻”或是“那么大年纪了”的理由之下理直气壮，殊不知，正是这些才让他们的婚姻最终走向了终点。一反常态的男女主人公立刻被家人觉察出了不同，崔半岛早上不再赖床了，味道不好的补药也愿意喝了；马珍珠吃饭又快又香，也不会因为妈妈不买手机而离家出走了，家人朋友很快说出了这些不同，主人公回想起自己年轻时的样子也觉得不可思议，时光对一个人的变化如此展现了出来。中年人比起年轻人，更懂事、利落了，做事也讲究实际结果了，但那是因为失去了任性和试错的资本。只有体验过才知道，拥有这些资本的青春是多么宝贵。这些道理，20岁无忧无虑的青年们是不知道的，不知道看了这部电视剧的青年们能不能稍稍有些触动？剧中最感人的地方或许是亲情了，马珍珠38岁的时候，妈妈已经去世好几年了，回到20岁，一张冰冷的遗像又变成了看得到摸得着的妈妈，马珍珠只想紧紧搂着妈妈，时刻看着妈妈，帮妈妈做家务，给妈妈买好吃的，而她真正20岁的时候，还在为妈妈不给自己买手机想着离家出走，还因为妈妈不给挑鱼刺就不动筷子。年轻的时候总觉得一切都会越来越好，没想到所有事物都在暗中标好了有效期限，真正能够体恤父母想要回馈父母的时候，他们已经不在了。对于作为儿女的他们，穿越仿佛一剂后悔药，让他们尽了孝道，可是作为父母的马珍珠和崔半岛，一想到自己不知道在哪里的儿子，就泪如雨下，马珍珠每次起床都下意识找儿子，发现自己仍在20岁，立刻失声痛哭。不管是母女之情还是母子父子之情，这部剧的穿越因为它们，变得沉甸甸的。穿越是个老噱头，内涵才是真正吸引人的地方，老瓶装新酒，不管有人从这里面看到亲情、爱情还是任何对生活的启示，只要有一点，这部剧，就成功了。 +http://lady.163.com/17/1121/11/D3OUDAV200267VA9.html +最易沦为剩女的十种女人 你中招没？ +　　爱情创伤女　　白领繁忙女生活中除了工作还是工作，根本没有时间好好地恋爱。心中呐喊：我好想恋爱，可是自己没有这个时间。社会的激烈竞争，让她除了工作别无旁骛。慢慢地变成想恋爱可是无法恋爱的剩女。　　强势气势女　　养尊处优女　　挑三拣四女做着灰姑娘变白雪公主的美梦，希看找到一个可以照顾自己一辈子的男人，有钱有势，疼爱自己，长得又很帅的。从不考虑自己的自身条件，慢慢地由于自己的嫌弃变成剩女。　　水性杨花女周旋在一个又一个男人之间，觉得自己的条件很好，有权利挑选。经常脚踏两只船，最后阴沟里翻船。水性杨花的女子，男人敬而远之，害怕自己变成缩头乌龟。美少女渐渐地变成剩女，只由于她们的花心。　　情痴读书女她们视书本比生命更重要，面对男人的追求，迷惑地看一眼，然后持续追寻着理论。专研于书中，研究着一个又一个论理，拿着一个又一个文凭。文凭高了，年纪大了，变成了不折不扣的剩女。　　劣质拜金女　　自甘堕落女征服着一个又一个的男人，原因很简单，不想动真情，想看看他们被抛弃之后的情况。抢夺着一个又一个的男人，然后再抛弃，一次又一次的持续着。然后自己慢慢地老往，根本不知道什么是真爱的肉食女。　　深陷泥潭女有些女性，一旦犯了错误，就再也解脱不出来，总以为假如爱了，知道了自己的过往，还是会无情地抛弃。女性有苦难说，由于她们也希看没有过往，可是事实摆在眼前，不得不沦为剩女。 +http://lady.163.com/17/1121/11/D3OU5SFJ00267VA9.html +丈夫为买房“假离婚” 妻子却携财产与初恋私奔 +只是这算盘打得好，风险也很大啊!武汉一男子李文(化名)也悲催了，遭遇了“假戏真做”的尴尬事。为了买二套房，刚刚离婚没多久，老婆跑了，“假离婚”变“真离婚”。昨天，男子李文来到武汉市妇联求助，希望能够挽回与前妻的婚姻。李文说，上个月武汉限购再升级，前妻周丽(化名)主动提出买房设想，“她当时说，手上的闲钱放着也是放着，就当做个投资。”李文本来就有买房打算，于是很快同意周丽的建议。根据当时的购房政策，两人如果想买二套房，首付要交五成以上，但两人手头并没有那么多钱，于是周丽提出“假离婚”，买了房之后，再复婚，还逼迫李文签下协议，如果“假离婚”期间，李文变心，要支付周丽30万元。看着周丽这架势，李文很安心，“我当时想，她肯定是怕我变心。”因为是“假”离婚，签字时，两人并未对财产、孩子的抚养权做详细协商。如今，孩子由外婆带，李文进不了家门，家里的银行卡都在周丽手中，“现在看来，她是蓄谋已久的，她婚内有情夫，属于婚姻过错方，可事实却是我被净身出户了，这不公平!”法律上并没有假离婚这种说法，只要离婚是双方当时真实意思的表示，并在民政局办理了离婚手续，离婚就是合法的。案中李文和周丽离婚已成事实，如果双方当时未就夫妻共同财产如何分配进行约定，可以向法院起诉请求分割。律师提醒法律上从来没有“假离婚”※ 我国《婚姻法》第五条规定，结婚必须男女双方完全自愿，不许任何一方对他方加以强迫或任何第三者加以干涉。※ 我国《婚姻法》第八条规定，结婚的男女双方必须亲自到婚姻登记机关进行结婚登记。符合本法规定的，予以登记，发给结婚证。取得结婚证，即确立夫妻关系。未办理结婚登记的，应当补办登记。由此可以看出，我国的婚姻制度实行的是登记主义，只要婚姻双方当事人依法办理了离婚登记手续，双方当事人的婚姻关系即宣告解除，所谓的“假离婚”产生的法律后果与“真离婚”是一样的。然而，有人却心存侥幸，最终后悔莫及。弄假成真会导致人财两空因为是“假离婚”，双方都心照不宣，在办理离婚登记时，往往考虑得简单，会出现夫妻共有财产归一方所有，另一方净身出户的离婚协议。这种状况下，如果未能复婚，净身出户一方将很难推翻财产归另一方所有的“不合理”协议，除非有充足的证据能够证明存在欺诈、胁迫的情形，而且必须在离婚登记之日起一年内起诉。因“假离婚”而弄假成真，一方见异思迁，抛弃另一方，拒绝复婚的案例并不鲜见。“假离婚”前，双方协商签订“假离婚”协议，能否保障双方权益呢?具有人身依附性质的感情保证、协议，都是违反法律禁止性规定的，是无效的。因此对于复婚保证书的“假离婚”协议均是无效的。对于财产分割，“假离婚”协议的效力，比民政局婚姻登记处备案的离婚协议效力要低，一方当事人可能会落得人财两空。“假离婚”后丧失相互继承权总结婚姻非儿戏，离婚需谨慎，假离婚同真离婚产生的法律后果一致，切不要为了房产等利益而破坏了原本长久的承诺，提醒各位切勿因小失大。 +http://baby.163.com/17/1122/09/D3RB2N8Q00367V0V.html +爸爸妈妈这样培养孩子的团队合作精神 +“一枝筷子易折断，一把筷子难掰弯。”相信爸爸妈妈们都明白teamwork的重要性，并且在现代社会处处存在合作，因此培养宝宝的合作精神是很重要的。一、注意培养孩子良好的性格根据几年的教育经验，我发现有良好性格的孩子合作意识与合作能力都比较强，这种良好性格包括开朗、自信、友爱、平等以及探索精神，具有这种品质的孩子会主动与别人合作，而且会合作得很好。所以，培养孩子良好的性格是促进幼儿迈向合作的必备条件。二、帮助幼儿形成很好的合作态度一般地，在体育游戏和角色游戏中，孩子们合作比较好，但是在建构游戏中，往往会出现合作的不愉快。究其原因，便是合作态度的问题，因为矛盾往往发生在游戏材料比较缺乏时，孩子们会将一部分游戏材料据为己有，担心一合作，就没自己的份了。这时候，就需要教师及时引导，帮助幼儿消除一些顾虑，必要时教师参加游戏，示范合作，引导拒绝合作的幼儿和老师一起游戏，逐步形成良好的合作态度。三、教给幼儿正确的合作方法合作不是一个人的事情，所以不能随心所欲。在一次教学活动延伸中，我让孩子们分组合作做画，给一棵大树添画树叶，结果只有一组孩子在真正地合作，他们在商量分工，分别完成大树的某一部分。而其余几组幼儿虽然都在同一棵树上做画，但却在各行其是，并未真正合作。我便让合作得较好的孩子向大家介绍他们的方法，然后再进行示范合作，结果孩子们马上明白应该怎样和别人合作了。由此可见，教给幼儿正确的合作方法非常重要。四、充分利用幼儿活动中的合作机会幼儿在一起游戏、学习，所以彼此间合作的机会很多。但是教师如果不善于捕捉的话，就会错失很多良机，比如孩子们都喜欢玩“猫捉老鼠”的游戏，这就需要每一个幼儿都有良好的合作精神，因为孩子们都喜欢扮演猫和老鼠，却不愿意拉圈，我便让孩子们换位，试一试别人不合作时，自己如何游戏，通过事实教育让孩子懂得，游戏的顺利进行，离不开大家的合作。此外，教师还要有意识地为幼儿安排创造合作的机会。五、向幼儿充分展示合作的成果 +http://baby.163.com/17/1122/09/D3RB2VCP00367V0V.html +家长们 不要遏制了孩子的好奇心 +从孩子呱呱坠地开始，就会用好奇的目光东张西望，打量着周围多彩的世界；而自孩子说话起，就爱问这问那，还常会提出一些稀奇古怪的问题。知道吗？有的家长最烦孩子提出这样的问题：“妈妈，为什么天空是蓝的？”“为什么飞机不会从天上掉下来？”“为什么猪没有翅膀？”有些父母会对孩子说：“问这么多，烦不烦？”孩子的好奇心，就在父母这样的不断呵斥声中被毁灭了！很多孩子长大后，便再也不会问“为什么”之类的问题了。1、让“十万个为什么”贯穿孩子一生从心理学观点看，好奇心是人们对新鲜事物进行探索的一种心理倾向，是推动人们积极地去观察世界，开展创造性思维的内部动因。好奇心是非常宝贵的，它是推动幼儿获取新知识的主要动力。文森特？鲁基洛曾说过，“好奇心、求知欲和善提问是创造性思维的引擎。”在儿童的心灵深处，都有一种根深蒂固的需要，就是希望自己是一个发现者、探究者和成功者。好奇是小孩子得到知识一个最紧要的门，是探索科学知识的动力，是启迪孩子智慧的火花。古人云：“学贵有疑，小疑则小进，大疑则大进，不疑则不进”。近代教育家陶行知也说过：“发明千千万，起始在一问。”孩子好奇，他们必然对不懂的新事物产生怀疑，进而发问或从实践中去探索。记得爱因斯坦曾说过，一个人的想像力比一个人的知识多少都要重要。从这点来说，孩子的好奇心和想像力对孩子的成长与成才是非常关键的。孩子提出的问题很多，可见孩子天生就有好奇心和想像力，可惜的是很多都被我们的家长给消灭在萌芽状态。如果你的孩子已经把自然界的事物，都看成了习以为常的事情，对自然界没有任何疑问，那是因为家长从小就不耐烦地告诉他们“本来就那样”，这样的孩子长大了，就会发现他思考问题的角度是那么狭窄，目光是那么短小，所有问题的答案对他而言只有一个标准。2、保持孩子好奇心的诀窍失去好奇心的孩子，一定有一对自以为是的父母。他们一定很权威、很自负、很要面子，但他们也许没想到，自己的太“强”，也就剥夺了孩子的“强”。这是一件非常得不偿失的事情！要想孩子超过自己，就一定要保住孩子的好奇心！而保持孩子好奇心的诀窍则是：首先，大人要有童心，要学会换位思考，尊重孩子的好奇。其次，不要敷衍孩子，要给孩子好奇心的提问以满意的回答，如果不懂，就带孩子一起去找答案。另外，家长要学会说这样一句话：“我真喜欢你爱提问题”，有时对孩子的提问，还可以不马上提供答案，而是进一步提出一个疑问和悬念，激起他的更强的好奇心。最后，允许孩子探索。家中如果有贵重东西，尽量放在孩子看不到的地方，只要他看到了给拆了，就千万不要责备他。否则对孩子的好奇心是致命的打击。孩子好奇，是他对科学探索研究的起步，锲而不舍，才能步入科学发明的殿堂。一个人如果没有好奇心，对什么事物都感到平淡无奇，那他就不可能会有发明创造，更不可能做出伟大的事业。因此，家长对孩子的好奇心，要因势利导、循循善诱，培养孩子“打破砂锅问到底”的坚韧毅力。切不可当头一棒，去挫伤孩子的好奇心和自尊心。保护好孩子的好奇心，你会发现孩子的心里有如此多鬼灵精怪的想法，能给你的生活增添如此多的乐趣。你会感叹孩子是上帝带给你的最好的礼物，感叹生活的美好！让我们一起努力保护孩子的好奇心吧！ +http://baby.163.com/17/1122/10/D3REOMR600367V0V.html +超早早产儿数量飙升 增幅近277% +武汉儿童医院发布数据称，根据近两年的统计，胎龄小于32周的极早早产儿增加三成，胎龄小于28周的超早早产儿增幅近277%。专家分析，这与二胎放开、生育年龄变大、生殖技术发展、环境变化等多重因素相关。在武汉儿童医院，像小乖这样的超早产儿，前几年只是零星出现，而近一两年数量有明显增长。武汉儿童医院新生儿内科曾凌空介绍，该科统计了2015年7月到2016年6月、2016年7月到2017年6月共24个月的NICU（新生儿重症监护室）的住院数据，结果显示，这两年时间里，NICU收治早产儿病人数有明显增加，从759增长到1038例。变化更为明显的是，出生胎龄小、出生体重轻者明显增多，胎龄小于32周的极早产儿收治总数增加44人（从143例到187例），增加幅度30.7%，胎龄小于28周的超早产儿收治人数从9例增加到34例，增幅为277.7%。科里住院时间超过30天的，绝大多数为早产儿。如今，医院每个月收治的早产儿比例也呈增加趋势，极早和超早产儿比例增加，这给救治和护理工作大大增加了难度和工作量。曾凌空指出，早产儿增多，与二胎放开、生育年龄变大、生殖技术发展、环境变化等多重因素相关。对于早产儿的救治犹如“闯关”，尤其是一些超早产儿，有可能经历呼吸衰竭，严重感染及喂养不耐受等难关，还有颅内出血，高胆红素血症，持续胎儿循环等关口。同时，早产儿由于胎龄小，出生体重低，全身各器官系统发育不成熟，生命力非常脆弱。对于这些小宝宝来说，治疗和护理都非常重要。 +http://baby.163.com/17/1122/09/D3RB36I400367V0V.html +父母的教养方式影响孩子的性格 +俗话说："有其父必有其子"，父母的教养方式对子女的个性发展起到了至关重要的作用。现在的家庭环境中，父母对孩子的教养方式已经出现了很大的偏差，有的父母甚至不知道该如何教养自己的孩子，有的父母教孩子时"下手之狠"让人痛心；有的父母爱孩子时"没有分寸"让人费解，不管是"爱"还是"恨"都会对孩子的人生造成深远的影响。那么父母的教育方式和孩子的个性性格的形成是一种什么关系呢？父母应该以怎样的教养方式来培养孩子的优良的个性品质呢？美国加利福尼亚大学教授、心理学家鲍姆令德曾经进行了长达10年的研究，他的研究已经成为发展心理学史上具有里程碑意义的经典研究之一。一、实验目的父母教养模式与儿童个性特点之间的关联二、实验过程首次是将学前儿童按个性（儿童的独立性、自信、探究、自我控制、交往等方面）成熟水平分出最成熟的、中等成熟的和最不成熟的三个组，然后对这三组儿童父母的教养水平从A控制，B成熟的要求，C父母与儿童的交往，D教养四个方面进行评定。三、实验结论首次试验的测评结果是最成熟组儿童的父母教养水平最高，依次往下，最不成熟组儿童父母得分最低。鲍姆令德将这三组儿童的父母分别称为权威型、专制型和娇宠型。第二、三次的实验结果发现，权威型父母的男女孩子在认知能力和社会能力发展方面都胜过其他两组儿童；专制型父母的孩子发展平平；娇宠型父母的女孩在认知和社会能力方面的得分都低于平均值，男孩的认知能力特别低。从鲍姆令德的实验中明显可以看出，权威性的父母教养方式对于孩子的培养和发展是最有利的。在进一步的研究中，鲍姆令德提出了划分教养方式的两个维度，要求和反应性。根据这两个维度，把父母的教养方式分为权威型、专制型、溺爱型、忽视型四种。（2）"专制型"父母，即"高要求、低反应"型。这类父母会拿自己的标准来要求孩子，而没有意识到过高的要求对孩子的个性是一种变相的扼杀；他们不能接受孩子的反馈，对孩子缺乏热情和关爱，要求孩子无条件服从，不能及时鼓励和表扬孩子。在这种"专制"下，孩子容易形成对抗、自卑、焦虑、退缩、依赖等不良的性格特征。（3）"溺爱型"父母，即"低要求、高反应"型。因父母过度的溺爱而有了今天的"小皇帝、小公主"，这类父母对孩子充满了无尽的期望和爱，无条件的满足孩子的要求，但他们很少对孩子提出要求。这些孩子会随着年龄的增长，变的依赖、任性、冲动、幼稚、自私，做事没有恒心、耐心。（4）"忽视型"父母，即"低要求、低反应"型。这类父母不关心孩子的成长，他们不会对孩子提出要求和行为标准，对孩子冷漠，缺少对孩子的教育和爱。这类孩子自控能力差，对一切都采取消极的态度，还会有其他的不良心理特征。"专制型"教养方式会导致儿童缺反独立思考的能力，做事优柔寡断，心理上容易产生抑郁和焦虑，缺乏学习的灵活性；"溺爱型"会使儿童缺乏创新能力，影响儿童创造性思维和个性发展；"忽视型"会使儿童学习注意力转移，如果得不到有效的引导将会荒废学业。只有在"权威型"的父母教养方式下，孩子思维活跃，富有想象力，自控能力强，做事有主见，并且能够听取意见，积极改进，学习灵活刻苦，善于和同学交流。"权威"体现了两层含义，一是体现父母对孩子的要求，即"权力"，父母具有养育孩子的义务，同时也有教养的权力；二是体现孩子对父母的反馈态度，继父母在孩子心目中的"威信"。这是亲子间互动的结果。如何做才能成为一个合格的"权威型"父母呢？1、以身作则，坚持基本原则，严格要求自己，注意自己的言行。2、对孩子的要求要采取一致的态度，不可一个唱黑脸一个唱白脸。3、根据孩子的实际情况，提出合理的目标和要求，并且协助孩子达成目标，不管是失败还是成功都要态度一致，不可以成喜、以败悲。4、以良好的心态和情绪面对孩子，善于倾听孩子的心声，对孩子的要求及时的作出反馈，避免"权威"变成"专制"。孩子的教育没有一定之规，这需要做父母在日常生活之中多一些耐心和细心，及时的发现孩子成长过程中出现的问题，随时修正自己的教养方式，通过学习以及和孩子的互动来寻找出适合自己孩子的教养方式。孩子是不断发展的人，父母在教育孩子的同时就是继续完善自我的过程。 +http://baby.163.com/17/1122/15/D3RUT8K000367V0V.html +熊黛林分享第一次胎动感受 字里行间幸福满溢 + + （原标题：熊黛林和网友分享胎动感受 字里行间幸福满溢） + 熊黛林在微博发文表示，昨天晚上肚子抽了一下，因为事发突然不确定怎么回事，感到很害怕，好一会都不敢动，今天她问了妈妈才知道，原来是“宝宝踢我了”，并附上脸红红、眨眼睛的表情符号。 +http://baby.163.com/17/1122/12/D3RJVAOM00367V0V.html +塑料父子情！王栎鑫儿子遭亲爹玩坏 P图成姑娘 +11月21日，歌手王栎鑫更新微博，配文写到“你是谁？看看你二姑娘@大脸猫吴雅婷_ 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2017年8月吴雅婷又产下儿子，小名番薯弟弟。看了照片也有很多网友表示“唯伊、番薯傻傻分不清楚”“王栎鑫基因太强大，一家四口三个王栎鑫，完全分不出”。                                                 王栎鑫一家                                               王栎鑫与吴雅婷 +http://baby.163.com/17/1122/10/D3RBLOKU0036950E.html +《一线儿童工作者能力素养与行为准则指南》发布 +2017年11月20日是第28个联合国儿童权利日。20日当日，国际救助儿童会、北京博源拓智儿童公益发展中心、深圳壹基金公益基金会、北京市社会组织发展服务中心、北京市协作者社会工作发展中心在北京联合举办联合国《儿童权利公约》28周年纪念暨《一线儿童工作者能力素养与行为准则指南》倡导活动。来自国务院妇女儿童工作委员会办公室、民政部社会事务司未成年人保护处、共青团中央维护青少年权益部维权工作处、北京市社会团体管理办公室服务发展处及北京师范大学社会发展与公共政策学院等嘉宾进行主题发言，从政府监管、社会监督、专业人才培养等角度阐述了提升一线儿童工作者能力素养、规范行为准则的必要性和重要性。主题发言后，来自北京市民政局儿童福利和保护处、中国儿童中心等多位政府有关部门代表和中国扶贫基金会、爱佑慈善基金会等社会组织代表从政策倡导和机构管理的角度，就如何推进公益组织一线儿童工作者专业化和规范化发展、推动《指南》的落地开展对话。来自全国儿童公益行业近70名代表参加了此次活动。 +http://baby.163.com/17/1122/14/D3RQJL0G00367V0V.html +家长必读：孩子有“心事”根源在父母 +“医生，我最近睡不着心情坏，吃不下饭，我肿么了？”“你今年多大了？”“11岁。”“你作业没做完吧。”八成孩子因成绩烦恼负责心理辅导的焦锦荣老师告诉记者，学校的“知心姐姐信箱”每个学期都能收到上百封孩子写来的“心里话”，反映的都是他们成长中遇到的烦恼。“知心姐姐，为什么我很努力，可是考试成绩却不好？”“每天都有这么多的课外辅导要参加，我快烦死了。”焦锦荣说看着孩子稚嫩的笔迹，感到很心疼。焦锦荣说，现在孩子心眼多了，懂事早了，但也让他们过早地感受到了来自父母、老师、社会等各方面的压力。焦锦荣说，大约80%孩子的烦恼来自学习成绩不好。背负着几辈人的“理想”，孩子们的负担是比较重的，很多学生有着这个年纪不该有的忧愁。“我真想学习好，像有些同学一样快快乐乐的。可是我的学习总上不去，我该怎么办呢？”一名4年级学生写给“知心姐姐”的信中充满了焦急的语气。溺爱让她被同学孤立“不懂感恩、以自我为中心……”这是很多人形容独生子女的词汇，记者采访中了解到，长辈、父母对孩子的过分溺爱已经影响到了孩子的心理健康，他们认为自己在家里被照顾，在学校里也得有人照顾自己；他们认为不管自己做什么都是对的，别的同学都得让着自己；就连别人玩具也得给自己玩。“这个孩子特别敏感，即使同学不小心碰她一下，她也会向老师、家长告状说同学打她。”四方区一所小学的老师告诉记者，这名女生现在是6年级，来自单亲家庭。从低年级起，学校老师就观察到她与其他同学似乎不大一样。“好像总是怀着心事，很少与其他同学在一起玩儿。”后来老师发现她会污蔑同学偷她的文具，而且随着年级的增加，这名女生的“心事”越来越重，与其他三五成群的小学生不同，她总是独来独往，甚至有意排斥身边的同学。“我们跟家长沟通过几次，但家长根本就不听我们的，坚称自己的孩子很听话，是同学故意刁难她。”这名老师无奈地告诉记者，这位母亲因为想弥补家庭缺失给女儿造成的遗憾，对孩子有求必应，无条件相信孩子说的任何话，在与老师的沟通中也一直强调 “我家孩子是最好的，不可能有这些问题”。“父母溺爱和单亲家庭父母角色的缺失，已成为影响孩子心理的重要原因。”多名小学老师告诉记者，这两种环境下成长的孩子，心理特别脆弱、敏感，要么不愿意跟别人交流、沉默寡言、自我封闭；要么过分张扬，以欺负弱小同学为乐。爸爸揍他他就打同学“家长不当的管教方式真是把这个孩子给毁了。”在青岛市一所知名小学的心理辅导室里，几名老师一起讨论学校一名男生的表现，这名6年级的男生一直是学校老师重点关注的对象。记者了解到，老师们对这个孩子既可怜又可气，可怜的是他在家里经常遭到父亲的毒打，“真的是毒打，经常是身上带着伤来学校。”班主任老师告诉记者，这个孩子确实比较调皮，但调皮是男孩子的天性，老师们平常大都以鼓励为主，并给他“委以重任”以培养他的自我约束力，但家长的管教方式则比较粗鲁，只要他不听话就是一顿打，导致孩子的叛逆心理特别强，甚至离家出走。班主任告诉记者，受家庭暴力的影响，这名男生也习惯了比较粗鲁的处事方式，暴力倾向特别明显，“他现在基本不会与同学交流，他如果想和谁亲近，惟一的方式就是上去捣别人两拳，搞得同学们都对他敬而远之。”班主任老师告诉记者，学校校长出面跟男生的父母谈了三四次，现在父亲基本克制住了，但孩子心理已经留下了阴影，“现在知道父母不打他了，他更无法无天了。”记者在采访中了解到，因为父母的家庭暴力给孩子留下心理阴影的不在少数，“我没有这个臭爸爸，他打我的腿和脸，还打我的头，我不想在这个家，我想离家出走，到别的地方住，但是我还要上学。知心姐姐，你可不可以惩罚我妈妈和爸爸？”这是香港路小学二年级学生写给知心姐姐的信。孩子有心事根源在父母鞍山二路小学心理老师孙老师认为，良好的家教环境是学生心理健康发展的一个重要前提。小学阶段学习过程中，孩子遇到什么事都愿意和父母说，如果父母对犯错误的学生一味指责、打骂，学生幼小的心灵就会受到伤害。他们就会慢慢地封闭自己的内心世界，拒人于千里之外。市立医院副院长、心理专家王冠军表示，小学阶段的孩子年龄较小，心理上出现问题，家长和老师没必要过度紧张，但也不能不闻不问，应该多注意、多观察学生的一言一行、一举一动，看到孩子的表现与平常不一样，或者和其他孩子有明显不同的时候，要向专业人士咨询。“家长是孩子的第一任教师，孩子的很多问题其实都是受父母影响，解决孩子的问题首先父母要自我成长和改变。”王冠军表示，大部分的家庭暴力都会对孩子产生特别大的影响，小时候，孩子往往表现为害怕、孤单，但随着年龄的增长，孩子在学校常常表现为有暴力倾向，脾气暴躁，喜欢用拳头解决问题，很难融入群体，不大擅长处理人际关系。对于父母过分溺爱孩子，王冠军认为这样不是爱孩子，而是害他们，容易给孩子养成娇生惯养、自私自利的性格，“长此以往，这些孩子眼高手低，不能正确对待困难，难以在社会上立足。” +http://baby.163.com/17/1122/07/D3R1FFMM00367V0V.html +改善儿童八字脚 三种锻炼来帮忙 +专家回复，儿童初学走路时，要尽量少穿或不穿硬质皮鞋，小孩的骨骼太软，脚腕力差，皮鞋又硬又重，扭曲了孩子的步态，硬质皮鞋穿久了就容易形成“内八字脚”或“外八字脚”，不但步态不美，也有损孩子的健康。儿童患“八字脚”最常见的原因是由于缺乏维生素D所引起的佝偻病，缺乏维生素D会造成钙、磷代谢紊乱，以及人体对钙的吸收障碍，从而导致骨质出现软化。家长如发现孩子有“八字脚”的情况，除了补充钙及维生素D以外，还可以用以下三种锻炼方法进行补救：基本练习法矫正孩子的“八字脚”，要先让孩子坐、站、走、跑姿势正确。先给孩子摆正步型，然后教他踏着节拍迈步，循序渐进，不要太累。划线迈步法用粉笔在地上画两条直线，其距离为8至10厘米，然后教孩子沿着直线走，步伐由小到大，由慢到快，多走几个来回，简便易行。直线跑步法在地上拉一条布带，让孩子踩着布带跑，在跑步时提醒孩子不要出现“八字脚”。 +http://baby.163.com/17/1121/07/D3OF2PQP00367V0V.html +张子萱半夜帮女儿搭配衣服 好穿不贵一起来学！ +陈赫和张子萱虽然刚开始公布婚姻的时候很网友都不接受，不过慢慢的大家都接受了这对为女儿着想的夫妻。11月19日深夜，张子萱就突然在社交网发动态，配文说：“安安的新衣，以及半夜蓬头垢面还非帮安姐搭配好拍可爱平铺图的执念的中年母亲”。照片中，她时而站在床边，时而踩在床上认真的为女儿拍下新衣服的照片，扎马步的姿势十分豪迈。网友评论说“隔着屏幕都能感受到满满的母爱”。照片中，身穿白色毛衣的张子萱用手机拍摄已经在床上摆好的小女生衣服，这就是女儿安安的新衣服啦。弄得那么整齐，看来花费了不少心思。在床边拍照还不够，这次张子萱以扎马步的姿势踩在床上，十分豪迈。接下来的这四张就是为安安搭配好的新衣服啦。深蓝色碎花外套搭配黑色小纱裙，内搭是一件乳白色的娃娃领长袖线衣，下身的乳白色裤子看起来也是软乎乎的，颜色呼应非常好看。外套的衣角还是有个小点缀，这次是一只毛绒绒北极熊，一下子就营造出了一种“萌萌的”“软乎乎”的感觉。很多妈妈在为宝宝买衣服时，会挑选过于花哨颜色的衣服，因为她们觉得纯色的衣服不好看，但是纯色衣服如果在衣角、裤角有些可爱的点缀就很不一样啦，比如上面的衣服如果去掉小樱桃、去掉北极熊就像缺少了点睛之笔。学会这些，自家娃也能穿出明星搭配！ +http://travel.163.com/17/1122/00/D3QANCNN00067VF3.html +这个签证含金量不输美国的国家 即将涨价! + + （原标题：这个签证含金量不输美国的国家 马上要收紧了!） + 好在，为了方便，加拿大在原有的5个签证中心（北京、上海、广州、重庆、香港）的基础上，再增设了7个签证中心：成都、杭州、济南、昆明、南京、沈阳、武汉。所以，有意向去加拿大并不想太麻烦的朋友，可以在这一两个月内抓紧时间把加国签证办了，毕竟（通常）加拿大旅游签证的有效期会给到护照过期的半年前左右。加签的含金量也丝毫不输美国（持有加拿大10年有效签证，可免签菲律宾、洪都拉斯、多米尼加、韩国、秘鲁等10个国家！）。但是，一说到加拿大旅游，最有画面感的还是班芙公园。比起游客多、旅游设施完善的班芙公园，贾斯珀公园却显得更有个性。他们之间只相隔了一条冰原大道(Icefields Parkway)，即93号公路，这还是曾被《国家地理杂志》誉为"世界上最美的公路"之一。它在无声中抵制过度开发，极其最大努力还保护野生动植物的家园。这里可谓是"精灵们的据住所"，像北美红鹿(Elk)、山羊、驼鹿、大脚野绵羊、落基山鼠兔和熊的踪迹，在这座野生动物园里从不难被发觉。加拿大落基山脉有5座国家公园，已经在1985年正式成为了联合国教科文组织的世界遗产，比起最为国人熟知的班芙(Banff)公园，同属于艾伯塔省的贾斯珀(Jasper)，其实藏有更多让人激动不已的加拿大特色。每年11月~次年5月，就是贾斯珀国家公园的滑雪季，众多滑雪爱好者特意从全国各地飞来感受这里美轮美奂的雪与景。小飞君早已在今年3月份为大家探过路，整段行程实在是有趣又梦幻。两天之内经历四季。大雪纷飞之时，偶遇成群麋鹿在觅食；阳光普照之时，感受雪橇在粉晶雪上的滑动。穿上大脚鞋，在冰封的湖面上行走，一边探索野生动物的踪迹，一边感受落基山脉的震撼雪景。恰逢今年还是加拿大建国150周年纪念日，加拿大的所有国家公园将对所有人免收门票!今天，就让Feekr带你深入体验贾斯珀国家公园(Jasper National Park)，顺道好好玩一把埃德蒙顿——艾伯塔省省会，加拿大的第五大城市。以为这是个高冷的国家公园原来是个滑雪场、动物园、探险乐园贾斯珀国家公园的冬日体验。|| 滑雪 - 冬季贾斯珀的另类体验▲图by托斯卡纳▲图by托斯卡纳对于冬季的贾斯珀来讲，滑雪，是另一番体验国家公园魅力的方式。从最高处海拔2312米滑道往山下滑，一边用雪橇感受粉晶雪的质感，一边用双眼享受贾斯珀国家公园的美景。▲图by托斯卡纳▲图by托斯卡纳每到十一月至五月，Jasper Ski Marmot迎来了它的高峰期，这里有着满足不同滑雪水平的8多条滑雪道。无论是前来训练的小孩子还是滑雪发烧友，都可以找到适合他们自己的滑道。|| 探索野生动物(Wildlife Tour) - 公园里的真正主人这里是野生动植物的家园，而探索野生动物，成了贾斯珀永恒且有趣的项目。每天的午餐时间，运送粮食的火车伴着笛鸣声和轰隆隆的轨道声驶进小镇，此时你能看到散落八方的麋鹿开始聚集起来，低头找食从车厢散落于地的粮食。▲向导手上所拿的是公麋鹿春天后自然脱落的角▲按照熊掌脚印所做的熊掌模型若你驱车前往距离贾斯珀镇40公里的玛琳湖，你会从一丝丝痕迹中辨得野生动物的踪迹：在雪地里一深一浅的鼠兔脚印、低矮灌木丛里叶子上的新鲜齿印，或是小道旁那颗白桦树上的大熊爪印.....|| 徒步玛琳峡谷(Maligne Canyon Ice walk) - 身在地狱，眼在天堂▲图by托斯卡纳玛琳峡谷，典型的喀斯特地貌，被誉为是加拿大最壮丽、最狭长的峡谷之一。冬天，玛琳峡谷的瀑布被完全冰封，此时便成为了户外爱好者的聚集地之一。其中，3.5公里的徒步体验，是最初级也是最容易被人们接受的。你需要在向导的带领下，穿上特定的冰地防滑鞋，行走于峡谷底部，沿着冰封的河道，探索结冰的瀑布、冰洞和美丽的冰层。在徒步的过程中，还会遇见一些专业的攀冰团队在训练。Tips：1、徒步时长3—3.5小时2、为保证安全，徒步玛琳峡谷最好参与半日团。Sun Dog Tour是承接该项目的团队，每天从贾斯珀出发时间：9：30am、1：30pm、6：30pm|| 冰湖探险(Snowshoe Tour) - 即梦幻又地道的加拿大场景▲图by托斯卡纳如果说春夏的贾斯珀美得让人有距离感，那冬日里的它则因冰封的湖而变得更具有探索性。距离贾斯珀小镇不远的金字塔湖(Pyramid Lake)，则以倒映着的金字塔山(Pyramid Mountain)闻名。穿着大脚鞋(Snowshoes)在冰湖上漫步，心旷神怡的景色以及各种野生动植物的出现，总让人激动不已。▲图by托斯卡纳你甚至可以在Patricia Lake旁烤火小憩：围坐在铺着印第安地毯的木凳上，捧着一杯热气腾腾的可可，吃着一份刚烤暖的棉花糖，望着眼前如画如梦般的落基山雪景。一群人有说有笑，突然，从远处传来铃铛声，原来是一部梦幻又可爱的马车经过。恍惚间，以为自己掉进了哪部北美文艺片或童话故事里的场景。只有一条主商业街的小镇却藏有令人赞不绝口的美食小店贾斯珀小镇上的美食推荐。|| Jasper Brewing Classics - 精酿啤酒与加拿大特色美食艾伯塔有着最优质的小麦，因此艾伯塔省几乎每座城市都会有自己的精酿啤酒厂。而在Jasper小镇上的Jasper Brewing Classics，也是一家有着精酿小酒坊的特色餐馆。在品味经典的加拿大美食之前，还可以先去地下一层参观专门的精酿酒坊，了解一下啤酒酿造的过程。推荐这里的薯条、西班牙辣香肠烤干酪玉米片，但是分量都太大啦~|| Evil Dave's Grill - 适合亚洲胃的高分餐馆不大的Jasper小镇，却藏有很多让味蕾惊喜的味道。这家Evil Dave's餐馆完美融合亚洲与北美菜系的口味，从好几道菜里还能找到中国味道，十分适合亚洲胃。作为前菜，鲜嫩多汁的虾串、肉饼、地狱烤鸡已经能让人一饱口福。继而上来的主菜，烤三文鱼饭、咖喱鸡饭、泰式炒面(typhoon noodles)等，无论是摆盘和味道，都获得了一致好评！1、旺季的晚餐时间前往，最好提前预定，特别周末人非常多；2、强烈推荐这里的鸡尾酒Drak N Stromy去贾斯珀路上必经的中转站是一座现代又怀旧、艺术又工业的小城埃德蒙顿玩法。|| Whyte Ave(怀特大街) - 老城区的中心▲二手旧书店怀特大街(Whyte Ave)位于斯特拉思科纳(Strathcona)市中心，也就是埃德蒙顿的发源地。因此一路上你可以看到现代建筑中夹杂着不少历史感十足的大楼。一路上走走停停，不经意间便会经过一两家整齐而七彩的二手旧书店、有着浓厚历史感的公主剧院，或者农贸市场、古玩中心等有趣的地方。|| 艾伯塔艺术中心 - 孩子们艺术启蒙的最好场所▲图by托斯卡纳比起国内的艺术馆，艾伯塔艺术中心(Art Gallery Alberta)并不算大，但在这里却能窥得埃德蒙顿的艺术氛围。馆内有着摄影、肖像艺术、装置艺术等多个展馆，其中还专门有着给小孩子"玩乐"的小房子，无论是简单的涂涂画画，还是需要耐心才能完成的艺术拼接，孩子们都能在这里开展艺术启蒙般的体验。|| 西埃德蒙顿中心 - 上世纪80年代最大的世界商场西埃德蒙顿购物中心（West Edmonton Mall）在1981年建成开放时，是世界上最大的购物中心，目前该购物中心仍然是北美最大，也是艾伯塔省旅游胜地之一。简单来说，要想买买买，这里是不二之选了。经实测，某些非加拿大牌子的产品并不会便宜太多。|| 麋鹿岛 - 有着北美最大和最小的哺乳动物在距离埃德蒙顿35公里左右，驱车半小时左右，便可抵达麋鹿岛国家公园(Elk Island National Park)。这里是观察野生动物的最佳地区，成群的野牛、麋鹿、红鹿自由自在地生活在这里。但若是午餐时间左右前来探索，可能就不太好了，因为此时的野生动物们通常会选择睡个午觉...埃德蒙顿的餐馆推荐一种味道，承载一个故事来到艾伯塔省，必尝鲜嫩牛肉与精酿啤酒！|| Little Brick - 红房子里的网红餐馆看似现代化的埃德蒙顿，某些角落里总会藏有一丝过去的痕迹，Little Brick餐馆就是这样的存在。过去，这片社区是当地一座著名的地标性建筑——砖厂，其先后养活了几代人，因而为了纪念砖厂主人J.B.Little，这家开设在他原住宅里的餐馆便命名为Little Brick。▲图by赵骞▲图by赵骞同时，这里的每道美食都是惊喜连连。一份简单的前菜沙拉，里面的食材是当天从附近农场里及时运来，鲜甜小胡萝卜甚至可以征服从不吃胡萝卜的人。一份貌不惊人的浓汤，搭配鸡胸肉三明治，咬一口就可以感受到新鲜烘焙面包的松软。一份可爱的焦糖布丁，甜度适当，作为饭后甜点，实在是让人饱足得幸福。|| Kitchen by Brad Smoliak - 曾为英女王服务的私厨▲图by托斯卡纳当国内流行私厨餐饮的时候，国外的私厨却更加强调互动性和参与性。在埃德蒙顿市中心，有一所Brad私厨(Kitchen by Brad Smoliak)，专门接待一些喜好切磋厨艺或讲求隐私安静的客人。▲图by托斯卡纳你可以先到附近的农贸市场亲自选购食材，再到这里和Brad一起下厨。幽默可爱的Brad曾为英女王服务，在面对面烹饪的同时，还会为你一一说明每道食材的来源以及处理技巧。这样的体验，想必是每位厨房能手的最爱了。|| Ampersand 27 - 可能是埃德蒙顿美食的首选地地理位置优越(位于怀特大街上)、优雅细腻的环境、热情到位的服务，都使餐馆&27(Ampersand 27)成为了不少本地人举行生日、周年纪念日的首选地。人的双手能制作无数令人回味无穷的美食，而人的手骨正是有27根，餐馆便取"27"作为店名。对于游客来说，这里也是品味艾伯塔美食的不二之选。艾伯塔著名的柔嫩小牛肉搭配各式干酪，对于某些中国胃来说可能难以接受，但敢于尝试的话，这口鲜味的生牛肉，绝对让你惊叹不已。另外，seafood cioppino和特色精酿啤酒(Alberta Draft Beer)也非常值得一尝哦。地址：餐馆Ampersand 27就位于Edmonton VARSCONA酒店楼下|| ROSTIZADO墨西哥餐厅 - 埃德蒙顿排名第五的美食餐厅在埃德蒙顿排名第五的最美味餐馆Rostizado里，无论是作为小吃还是配菜，墨西哥餐厅里最经典的tacos是无处不在的。每道菜品的份量之大，让人恨不得多长几个胃。即使在饱到撑的情况下，还是忍不住多尝几口牛肉，来到艾伯塔，一定要品尝一下上好的牛肉，鲜嫩多汁，嚼完嘴里还回甘！实用信息【天气】Jasper的滑雪季是每年的十一月至次年五月。温差较大，有可能两个距离车程一小时左右的地方，就已经是夏季与冬季的温度差。【其他】1、加拿大的酒店都是禁止吸烟的，一旦被发现，就会罚款，一般会有指定的吸烟区。 +http://travel.163.com/17/1122/00/D3QAFNTG00067VF3.html +别拦我!我要去故宫吸那181只皇家猫 + + （原标题：别拦我!我要去故宫吸那181只皇家猫） + 相传故宫里养了181只御猫红墙内的殿宇，常有喵出没它们吃住在故宫，有名有记号还一点都不认生，长得贼胖更被众人称为sh ǐ史shàng上zuì最méng萌hu护mi ā o喵~时而高冷，时而卖萌话不多说，你要来吸一口猫吗？宫喵传说网友称他去故宫游玩的时候看见一只橘猫正俯身去扑小鸟保安小哥哥突然赶过来一把按住它既宠溺又责备地说" 不是刚刚才把你喂饱吗？咱不杀生咱不杀生 "......@被萌一脸的网友两大萌物算是组成联盟了经过数周的亲切会面与深入交流慈宁宫花园园喵 " 香菜 "已经与来自承德的小鹿结下了闪耀着金子般光芒的友谊！@故宫博物院传说这是一只酷爱沙井盖的喵（井盖桑，你好）@嘿我偏不改名字猫：我是景仁宫的 " 鳌拜 "@十分想消失爱睡在椅子扶手下的喵就算你趁机摸它几把它只眯眯眼望你一眼接着继续补眠（喵：嘿，我叫金宝）@康木言猫粮？@亮亮▽看完网友版的宫喵传说，很多人惊讶又疑惑，" 原来故宫也是吸猫圣地？"，但为何故宫会养着那么多猫呢？而且一看它们的身体形态，就晓得伙食肯定不差！故宫的工作人员表示，这些猫咪并非好吃懒做，由于它们的每日 " 巡院查岗 "，基本上鼠患这一问题已经绝迹了，从前这可是木结构古建的一大威胁。《戏猫图》宋 , 佚名自古以来，不少书籍都有关于猫的记载，据太监刘若愚在《酌中志 · 内府衙门职掌》中记载：" 猫儿房，近侍三四人，专饲御前有名分之猫，凡圣心所钟爱者，亦加陞管事职衔 "。你瞅啥？瞅你故宫工作人员很照顾这些宫猫，嘴上说着它们太胖了，下一秒又忍不住喂它们；每个办公室都必备猫粮；冬天担心外面的水结冰，众人特意放置温暖的水供猫咪们喝；大家还设立了宫猫基金、猫账本 ......从 2009 年开始统计，故宫已为 181 只猫咪做绝育手术，遵循的是 " 捕捉（Trap）、绝育（Neuter）、放生（Release）" 的 TNR 国际通行方法，控制流浪猫的数量，提高它们的生活质量。正式将这些流浪猫收编后，" 故宫看门人 " 单霁翔还帮他们取名字，例如 " 平安 "，寓意着 " 平安故宫 "，还有 " 小崽子 "、" 金宝 "、" 二毛 " 等等 ......可以说是炒鸡萌的故宫文创收集宫喵大计划@刘顺儿妞旅行摄影师，正在养 8 只猫的高级铲屎官摄影师顺妞喜爱拍故宫的一年四季，而与宫喵结缘是正是一张无心拍摄的照片，当时正在拍建筑时，突然猫咪乱入，事后发现这张照片莫名有意思，猫和红墙古建筑香结合，一动一静，颇有趣味。于是，她便开始专心寻猫，开展了 " 收集宫喵大计划 "。在故宫里碰见猫咪的几率还是挺小的，因为它们不习惯呆在人多的地方，游走的地方离游客区较远，但想要找到它们，其实并不难。每只猫都占据一个 " 地盘 "，基本上你想找某只猫，去它的专属地盘就可以了，因此顺妞一直在摸索宫喵出没的地盘分布。顺妞的寻猫路线：（＊ 据说这条线路遇到的猫咪的几率很高，ps：要看准时机，请避开猫咪的午休时间）每只猫的性格不一，顺妞提到 " 例如二毛，属于高冷傲娇喵型，每逢见到陌生人便往屋顶跑，趴着不动，死活不肯下来，不过这也挺好，它很容易和飞檐斗拱、雕梁画栋结合起来，画面感挺有意思的 "。" 而景仁宮的猫咪很软萌，一点都不怕生，不怯镜头，粘人得很，它们爱跟在游客身后跑，撒娇地求喂食。"顺妞告诉城画君，" 过去的三个月里，专门去故宫六七次，也没法遇见很多猫 "，而她继续打算拍摄故宫里的猫，也许花上几年时间也未必能完成这个宫猫特辑，但不要紧，每次去故宫都能遇到不同的惊喜。最后附上拍猫技巧：1、猫到处都有，只有把它和故宫的特色结合起来，才能强调他们是 " 故宫的猫 "。所以我在拍摄时，很少拍摄猫的大头特写，而是会退后几步，把猫和建筑结构的特点结合起来。故宫的光影也极具特色，把猫和这样的光影结合，会让照片更有趣。（换别的拍摄背景，也是同样道理）2、尽量用低机位，让视线跟猫持平。我会使用连拍模式不停抓拍，记录下它更自然的状态，比如小憩、到处张望等等，尽量避免刻意看镜头之类的画面。3、哄好拍摄对象也很重要，我自己养了八只猫，所以对猫的性格喜好了如指掌。每次拍摄前我会特地带一些猫喜欢的小零食给他们，让他们熟悉我，更好的放松。果然，猫是都市青年的多巴胺来源，你还不赶快来吸一口！ +http://edu.163.com/17/1122/06/D3QU1K4400297VGM.html +"中国制造"课程受学生热捧:2000个名额一小时抢光 +2000个名额，1个小时内就被学生抢光了。孩子们抢的并非热门演出票，而是制作鲁班锁、非遗绢人等三项科学实践活动的参加名额。本学期，初中开放性科学实践活动中新增的人文与历史类项目，50个主打京味儿和中国制造的项目受到学生们的欢迎。小朋友在体验益智古典玩具鲁班锁。东方IC 资料图在《谜之鲁班》课堂上，初中生在老师的引导下制作鲁班锁。不少学生是第一次使用中式传统的锯、凿子和锉等工具。“因为平时接触少，很多孩子一出手就锯歪了。”一位助教向记者介绍上课情况。“原来提起科学活动，我首先想到的是无人机、电脑等现代的科技，中国古代的科学制造只知道四大发明。所以我希望通过开放科学活动，更多了解中国的科技历史。”一位正在上课的学生说，“以前从来没有用过锯和凿子，浑身都较劲儿。但是作为一名中国人，我觉得应该学会使用这些传统工具。”这堂课上，成功制成鲁班锁的孩子不到一半。授课老师说：“制作鲁班锁，需要各部件严丝合缝，学生要用锉一点点儿地找角度。也希望通过这个过程，让他们体会工匠精神。”已经开课的50门“中国制造”课程，都蕴含着科学技术。比如通过制作鲁班锁，学生会学习到基础榫卯结构、三视图原理等。在《非遗绢人——原来你是穿越千年的“芭比”》课堂上，北师大实验学校初一学生刘清扬则在笔记中记下：“北京绢人在创新的路上应用了3D打印技术、激光切割和球性关节等，原本制作周期两三个月的北京绢人生产周期缩短，变得更时尚。”“我们希望学生通过制作，不仅能了解到中国的非遗项目，更希望启发他们今后可以成为这些优秀技艺的推广者，将更多新科技、高科技引入。”授课老师说。“今年，仅我们学校就推出了鲁班锁、非遗绢人、香料制作三门‘中国制造’类的课程，明年还将增加金银错和枫香染两门新课。”刘凯说，“还有一些项目也在酝酿中，我们还邀请专门的非遗老师一同研发适合初中生的非遗动手课程。”北京市教委相关负责人表示，明年起，人文与历史类项目的数量和比例都将继续提高，以丰富学生的人文历史知识，开拓眼界视野，希望引领他们形成良好的公民意识和家国情怀。 +http://edu.163.com/17/1122/09/D3RAOSKD00297VGM.html +美国哈佛大学招生考核种族背景 遭司法部调查 +据美媒报道，美国司法部现正调查知名学府哈佛大学(Harvard University)以种族背景做为招收学生考虑是否有触法之嫌，调查结果初步认定，校方作法确实违反(out of compliance)了联邦法律。根据美国有线电视新闻网取得两封来自司法部民权司(Civil Rights Division)的函件，内容指出哈佛大学对于司法部是否有权调查该校招生程序提出异议。信中也指出，司法部民权司已对哈佛大学下令，如果无法在今年12月1日之前呈交相关文件资料，就会遭到被告上法院的下场。2015年5月，哈佛大学遭控招生程序明显对于亚裔学生有歧视之嫌，共有64名亚裔学生出面向联邦政府提出申诉。纽约时报今年8月则报道，司法部正在组成一支律师团队，打算追究“大学院校招生过程手段刻意种族歧视可能衍生的法律诉讼”预做准备。当时司法部答复媒体询问时，并未透露哈佛大学是否已经遭到调查。华尔街日报于当地时间21日上午率先披露，从司法部民权司信函内容来看，司法部已经针对哈佛大学以种族为考虑条件的招生标准展开调查，而且司法部也指控哈佛大学拒绝配合接受调查。司法部发言人欧麦利(Devin O'Malley)21日则对美国有线电视新闻网发表声明指出：“对于任何可能触犯个人民权以及宪法权利的指控，司法部向来严肃面对，对于个案目前则不便评论。”哈佛大学律师卫斯曼(Seth Waxman)21日上午则未对媒体发表评论。 +http://edu.163.com/17/1122/06/D3QU34OQ00297VGM.html +西安女童幼儿园里掉进开水桶 教育局：该园无资质 +每个孩子都是父母的心头肉，父母都不希望孩子受到任何伤害。但是，今年10月19日，陕西省西安市一名名叫炫炫的女童在幼儿园里遭遇不幸，落入了盛满开水的桶里。受伤女童妈妈：“老师抱着娃，我揭开被子一看，整个人都崩溃了。孩子身上皮都脱掉了，当时娃说妈妈，妈妈，我好疼。听到这句话，我的心都在流血。”女童幼儿园里掉进开水桶，遭大面积烫伤。 本文图片来源：西部网说起10月19号在幼儿园里见到孩子的惨状，孩子的妈妈再一次泪如雨下。受伤女童的妈妈：“当时正在买饭， 老师突然打电话说孩子被烫了， 掉到开水桶里了。”幼儿园里磕磕碰碰似乎常有发生，可是教学场地内，孩子怎么就能掉到开水桶里，让人匪夷所思。当天幼儿园里到底是怎样的情形呢？受伤女童的妈妈：“幼儿园的一位负责人说， 一个老师提了一桶开水放在那，然后上厕所去了。娃在那玩呢，不知道怎么回事娃突然掉到水桶里去了，老师说水有七八十度，我感觉有100多度，因为看见娃的时候，娃身上的皮都掉了。”受伤女童的父母在西安市甘家寨村内做餐饮生意，半年前将3岁的孩子炫炫送到附近的“成长”幼儿园内。虽然硬件设施一般，不过孩子能在自己身边上学，总算比较安心。不过10月19号幼儿园里传来孩子被烫伤的消息，瞬间让全家人都陷入悲痛当中，在他们看来，这一切其实完全可以避免。住院诊断证明书受伤女童的妈妈：“我真的想不通幼儿园教室里怎么能放开水桶呢？ 就算老师上厕所，也应该将开水放到小孩摸不到的地方，或者叫个老师过来照看一下小孩，想不通你们的责任心在哪。”孩子的父亲说，孩子烫伤送医后，根据医院给出结果，女儿的腰部，屁股，腿部等全身4分之一的面积被烫伤。医生对全身多处脱皮部位进行处理时，听着孩子的阵阵哀嚎，他们心如刀绞。而他们更为担心的是，承受如此大的痛苦给孩子内心的创伤。时至今日，一个月过去了，虽说有些好转，可是炫炫身上依然留有大面积的疤痕。受伤女童的爸爸：“孩子根本就没有痊愈人家就让我出院，后续治疗，还有孩子心理阴影，以及后遗症，都是我当父亲接受不了的事情。这些幼儿园是什么态度？现在就抱着不管的态度。”今天早上炫炫的爸爸、妈妈再一次找到这家“成长”幼儿园。幼儿园老师：“监控是盲区，看不成。”受伤女童的家人：“那你们老师咋能把开水提到教室？”幼儿园老师：“现在不说那， 都是我们的责任。”两位老师承认，孩子掉入开水桶，确实是幼儿园及老师失职。并表示，前期治疗费用园里已经承担，至于其它后续治疗和赔偿问题，还需要找园长协商。幼儿园老师：“园长不在。”随后，孩子的家人通过电话联系上了幼儿园的园长，希望能当面聊聊此事，但是遭到了园长的拒绝。对于后续治疗等问题，园长只字不谈，对于幼儿园的资质也表示不予回答。工作人员：“这个幼儿园没有资质，西安市雁塔区教育局基教科已经对此事展开调查。”作为教育行业内最受关注的年度颁奖盛典之一，以“教育无边界”为主题的2017年网易金翼奖颁奖典礼将于12月在北京举行。届时，全球教育行业精英汇聚一堂，共同聚焦“教育无边界”这一主题，敬请点击关注。 + +http://edu.163.com/17/1122/09/D3RB0HC300297VGM.html +毛坦厂、国际部、学区房都是家长的“刚需” +考生急眼：我们的书都撕了啊！很多人只能去垃圾堆里找书。曾有专家称，考前撕书表达了学生对中学教育的不满与仇恨，过了啊！刚刚收摊儿的高考补习班重新开张，纷纷开设“一周密集班”。他们以“最后七天冲击班”“上帝送你的七天班”等惊悚的广告吸引考生，每小时收费约五六百元人民币。这是刚刚因大学招生舞弊案把总统赶下台的韩国。就在地震前一天，14日，首尔中央地方法院就朴槿惠亲信崔顺实的女儿郑某“走后门”入学一案作出二审判决。与一审判决结果一样，崔顺实因妨碍公务罪等罪名被判处3年监禁。前梨花女子大学校长崔京姬和前梨花女子大学新产业融合学院院长金庆淑被判处有期徒刑2年，前招生处长南宫坤被判处有期徒刑1年零6个月。韩国人对高考的重视，素来比我们还要夸张。高考日，政府机关上班时间推迟一个小时，股市开盘和收盘时间顺延一个小时。按政府要求，机场的飞机在听力测试期间禁止起飞、降落，汽车和火车司机行经考点附近不得鸣笛，以避免产生噪音影响考生。有的考场附近甚至实行交通管制，警察骑摩托车护送考生到考场。每年的这一天，寺庙里都跪满了祈福的家长。想想看，当他们听说总统密友的女儿假冒体育特长生混入了韩国最好的女子大学，会激起怎样的滔天愤怒！东亚民族大概是全世界最重视子女教育的民族。每一代人都会毫不犹豫地为下一代人的成长做出牺牲。这种文化传统超越国界和政治制度，华裔、韩裔、日裔，几乎走到哪儿都是考场上的优胜者。众所周知，美国的高校招生普遍实行“逆向歧视”政策。以满分1600分的美国大学入学考试SAT分数来算，录入常春藤名校的白人学生平均分数要比非洲裔学生高300多分，亚裔平均又要比白人学生高100多分。对非洲裔和拉丁裔学生的成绩要求低于白人学生，这是有道理的，是为了大学校园的多元化，也是为偿还历史旧债。但是，为什么又要求我们亚裔学生比白人学生的入学成绩高一截儿？这个就没有道理了，纯粹是亚裔学生成绩太好，强行打压你一下。为此，2014年曾有60多个亚裔团体联合向美国联邦教育部和司法部投诉哈佛大学，指责其在招生过程中歧视亚裔学生。据说，在去年年底的美国大选中，很多美籍华人第一次投了共和党候选人的票，因为特朗普提出取消以上差别对待，“分数面前人人平等”。是的，凭什么呀——我们节衣缩食，买高价学区房，送孩子进高价课外班，甚至放弃自己的事业当“全职妈妈”，最后你把我孩子的入学分数给打个折？一个犹太人和一个华人结合，就谱写出了《虎妈战歌》。蔡美儿和她的犹太丈夫都是耶鲁大学法学院教授。但他们教育孩子的方式，和安徽六安毛坦厂中学周边出租房里的学生家长几乎如出一辙：除了体育和戏剧课，所有的课程必须得第一名；不能碰钢琴和小提琴之外的乐器；不能玩电脑游戏；不能自己选择课外活动，等等。最后，两个女儿都成功地考进了哈佛。此书出版后，在中国媒体上遭到了众口一词的批判，不少人指责作者把中国残酷的应试教育带到了美国。但实际上，蔡美儿的父母是菲律宾移民，她就出生在美国的大学校园，一天也不曾在中国生活过。中华民族极端重视子女教育的文化传统，是一切改革都不能忽视的背景。韩国地震那天，我正巧在毛坦厂中学，听李振华副校长说：“我们的办学目标，就是让学生和家长满意。”——这句话，可以让该校抵挡住学界和媒体的所有指责。毛坦厂、新东方、国际部、学区房，都是中国家长的“刚需”。教育改革的道理有千万条，“让学生和家长满意”也许不是最重要的一条，但它肯定是足以“一票否决”的那一条。时习之　来源：中国青年报　（ 2017年11月22日11版）作为教育行业内最受关注的年度颁奖盛典之一，以“教育无边界”为主题的2017年网易金翼奖颁奖典礼将于12月在北京举行。届时，全球教育行业精英汇聚一堂，共同聚焦“教育无边界”这一主题，敬请点击关注。 + +http://edu.163.com/17/1122/09/D3RB3SMC00297VGM.html +无人售货纸箱亮相重庆西南大学 付款全靠自觉 +西南大学学生自创的无人售货纸箱。无人售货纸箱 亮相西南大学付款全靠自觉，但从未出现过差钱的情况无人售货超市，你也许有所耳闻，选择自己想要的东西后，只要通过手机或其他方式付款便可完成购物。近日，西南大学内出现无人售货纸箱，纸箱内除了学习用品外还有不少日常所需小物品，挑选商品后全靠学生自觉付款。学生全都自觉付款昨天中午，重庆晨报记者在西南大学图书馆门外见到了这个无人售货纸箱。纸箱是普通包装所用纸箱，里面分门别类将日常所需的纸手帕、小贴画，以及平时学习中用到的草稿纸等物整齐地摆放好。纸箱内放有一个小罐子用于收放零钱，一旁张贴有微信、支付宝的收款二维码，学生只要通过投放零钱或扫码付款即可拿走想要的小商品。正值午餐时间，不少同学都收拾好书本准备前往用餐，路过纸箱都会停下脚步观察一番。记者在纸箱旁停留近20分钟，其间有一名女生从箱内挑选一包纸巾，并使用微信付款。记者继续寻找无人售货纸箱，在几处离超市较远的宿舍楼下和几个公共教学楼门口也发现了它的身影。不少同学对于无人售货纸箱的出现都表示挺新奇：“只在新闻中看过的事情，没想到居然出现在学校。”方便同学没想赚钱记者联系上了其中一个无人售货纸箱的主人——西南大学2016级播音主持专业学生黄毓如，她表示初衷纯粹是为了方便同学。“学校公共教学楼和图书馆都离商店较远。”黄毓如介绍，自己曾经在图书馆看书时遇到过这样的问题，想买便笺纸，但商店离图书馆又有一段距离。正好看到无人售货商店的新闻，便萌生了放置无人售货纸箱的想法。“没想过从中赚钱，只是想利人利己方便大家。”黄毓如介绍，一开始她也曾担心是否会出现别人拿走东西不付钱的情况，所以只敢摆一些不值钱的小东西。但在每天清算核对时，却从来没出现过少钱的情况。黄毓如说，自从她在学校内摆放了三个无人售货纸箱后，如今又有新的同学加入，无人售货纸箱也越来越多。“纸箱虽小，却能感受到人与人之间诚信交往的温暖。我会继续做下去。”  + +http://edu.163.com/17/1122/09/D3RB05ND00297VGM.html +高校图书馆现"劝诫表情包" 学生:吓得我赶紧学习 +“刚准备玩手机，就发现一个‘表情包’盯着我，吓得我赶紧继续学习！”刚从图书馆走出的研一学子沈甜笑言。近日，四川农业大学成都校区图书馆出现一批“劝诫系列表情包”，引发广大学子的热议。图为张贴在该校图书馆的“表情包”。中国青年网通讯员 谢菲 摄记者了解到，表情包的“问世”得益于志愿者段绪泉对生活细节的观察留意：“我是在看到微博热搜的‘高校垃圾桶呆萌表情包’，联想到之前学校农院青工制作的‘食堂表情包’，突然意识到这是一种被当代青年喜爱、被如今社会认可的潮流文化，我想将这种良性文化引入学习区。”一番深思熟虑，志愿者们找到了图书馆馆长黄映国老师，恰巧，针对同学们近期频频反映在意见栏里的馆内不文明现象，诸如：自习室大声讨论聊天、占座占位、不在规定区域倒水、浪费水资源、不冲厕所、情侣在公众场合行为举止过于亲密等，黄老师正打算制作一批警示标语。在志愿者两小时的耐心陈述下，黄老师选择并认可这一批特殊的“警示标语”。图为张贴在该校图书馆的“表情包”。中国青年网通讯员 谢菲 摄自十一月初，图书馆与资源学院共同设计出120余张“图书馆专用表情包”系列图片，张贴在在馆内主要学习区和第二楼道、厕所、饮水处等生活区，以期达到督促大家专心学习，减声降噪，文明如厕，文明恋爱，节约用水等目的，进而营造文明良好的学校图书馆学习氛围。记者了解到，“表情包”的空降引起了在校学生诸多反响。“图书馆本来是枯燥又严肃的，突然来了一些‘表情包’，有点猝不及防，但是又觉得很有趣。”2017级新生何同学如是感慨，他告诉记者，表情包”的确能够吸引大学生的注意力，多多接受它们的提醒，大家都可以文明入馆了。长期“驻扎”在馆内的“考研党”学生称赞说：“学累了就起来四处转转，看看那些表情包，感觉精神又回来了。”图为学生在图书馆张贴“表情包”。中国青年网通讯员 谢菲 摄据志愿者调查了解，自“表情包”投放后数日，馆内常见不文明现象得到明显改善。还有许多被近期寒冷天气“困”在寝室的同学，为一睹表情包的“芳容”，也纷纷开启通往图书馆求学的“破冰之旅”。图书馆二馆馆长黄映国表示，志愿者们将“表情包”的生动活泼带入传统理念中安静肃穆的图书馆，原本就是新旧结合的一次尝试，动静相宜，营造出不一样的学习氛围。 + +http://edu.163.com/17/1122/09/D3RATIJQ00297VGM.html +选择热门专业需谨慎 这些岗位可能在20年内消失 +你是否还记得科幻电影里被机器人主导的未来世界？现在看来，这样的日子离我们已经并不遥远。会计基本上，如果财务软件能够解决你的问题，那也就不再需要会计了。越来越多的公司开始选择在线处理财税事务，只有大型企业才需要专职会计，而普通人也可以通过软件完成财税计算。会计专业不再需要大量处理数据，而应该具有更深刻的洞察力。更好地选择是与金融学结合，能够提升你的职业竞争力。接待与旅游大家都在机场有过自助值机的经历吧？未来的酒店也将成为这样。选择接待与旅游专业可能就会成为错误，因为大多数相关工作都能轻易依靠科技完成。接待员或导游等等工作的需求必定会逐渐减少。律师辅助在现在，大多数律师助手的工作都能藉由电脑代劳。我们可以在网上即时完成文书和研究工作，并不需要额外的人力。法律很有可能以某种形式完成技术化，首先被淘汰的就是律师辅助工作。广播电视传播广播电视领域的发展一直未曾停歇，但电视已经不是最主要的传播媒介，相关专业仍在教授过时的技术。传播手段日新月异，从Snapchat到Facebook，我们获取信息的方式不再局限。药学机器人有朝一日也能为病人开出处方，这是不言而喻的。越来越多的药店和工厂开始尝试自动化生产与配给，专职的药师已经没有前景。大型制药公司依然需要人来进行药物合成，但这一需求也将逐渐减弱。不如进一步学习成为一名医生，在短期内将会很难被机器人取代。 +http://edu.163.com/17/1122/11/D3RF8D5S00297VHH.html +英语知识：生活中常用的五星级英文句子 +1. After you.你先请。这是一句很常用的客套话，在进／出门，上车等场合你都可以表现一下。 (好像现在女士不愿意你这么做，特别是那些女权主义者，我还记得这么一段话：一个女士对一个让她先行的男士说：You do this because I am a woman?那个男士回答说：I do this not because you are a woman but because I am a man!)2. I just couldn't help it.我就是忍不住。想想看，这样一个漂亮的句子可用于多少个场合？下面是随意举的一个例子：I was deeply moved by the film and I cried and cried. I just couldn't help it.3. Don't take it to heart. 别往心里去，别为此而忧虑伤神。生活实例：This test isn't important. Don't take it to heart. 安慰人的超级句子。4. We'd better be off.我们该走了。生活实例：It's getting late. We'd better be off.5. Let's face it. 面对现实吧。常表明说话人不愿意逃避困难的现状。参考例句：I know it's a difficult situation. Let's face it, ok?很棒啊，年轻人犯错误，上帝都会原谅，但是犯了错误，你必须面对他，Let's face it.或者是：Let's face the music.6. Let's get started.咱们开始干吧。劝导别人时说：Don't just talk. Let's get started.Let's get started.Let's start.Let's do it right now.Let's hit the road.Let's rock&roll.Let's put our hands on sth.7. I'm really dead.我真要累死了。坦诚自己的感受时说：After all that work, I'm really dead.8. I've done my best.我已尽力了。这句话，很有用，失败有时难免，但是你要是可以说，I've done my best. I spare no efforts.就不必遗憾，毕竟，Man proposes, God disposes.9. Is that so? 真是那样吗？常用在一个人听了一件事后表示惊讶、的怀疑。10. Don't play games with me! 别跟我耍花招！11. I am not very sure.我不确定。Stranger: Could you tell me how to get to the town hall?Tom: I am not very sure. Maybe you could ask the policeman over there.12. I'm not going to kid you.我不是跟你开玩笑的。Karin: You quit the job? You are kidding.Jack: I'm not going to kid you. I’m serious.13. That's something. 太好了，太棒了。A: I'm granted a full scholarship for this semester.B: Congratulations. That's something.14. Brilliant idea! 这主意真棒！这主意真高明！15. Do you really mean it? 此话当真？Michael: Whenever you are short of money, just come to me.David: Do you really mean it?16. You are a great help.你帮了大忙17. I couldn't be more sure. 我再肯定不过了。18. I am behind you.我支持你。Whatever decision you're going to make, I am behind you.19. I'm broke.我身无分文。也可表达为：I am penniless.20. Mind you! 请注意！听着！(也可仅用mind。)模范例句：Mind you! He's a very nice fellow though bad-tempered.（中国日报） + +http://news.163.com/17/1122/21/D3SHGCML0001875P.html +泰国小哥赴韩整容术后堪比明星 帅得亲妈都认不出 + + （原标题：泰国小哥鼻歪嘴斜赴韩整容，术后堪比韩国明星，帅得连亲妈都认不出） + 【泰国小哥鼻歪嘴斜赴韩整容，术后堪比韩国明星，帅得连亲妈都认不出】泰国整形节目《Let Me In》第三季中，一名22岁的泰国小伙面部严重不对称而非常自卑。因为下颌骨错位，他无法正常咀嚼和说话。他赴韩整容后判若两人，亲妈见后哭着连声问：“真的是你吗？” +http://news.163.com/17/1122/20/D3SH6O830001875P.html +24岁女孩重度烧伤病情危重 母亲探望途中车祸身亡 + + （原标题：24岁女孩重度烧伤病情危重，母亲赴粤途中车祸身亡） + 11月19日，因为住的单身公寓发生火灾，在广东中山坦洲打工的24岁山东女孩闫娇娇被严重烧伤，在中山市人民医院抢救，至今仍未脱离生命危险，预估需要60万-100万元的治疗费用。更不幸的是，她的妈妈在闻讯赶往探望女儿的途中，在山东济南遭遇连环车祸身亡。目前，女孩的同事和朋友正在发起募捐，希望能帮她度过难关。24岁少女遭遇火患被严重烧伤11月19日上午8时至9时许，位于中山市坦洲镇的一处单身公寓内突发火灾并冒起滚滚浓烟，24岁的山东女孩闫娇娇正是意外单位的住户，她被严重烧伤。当天上午9时许，在坦洲镇某酒店值班的当班经理杨先生陆续听到消防警笛从耳边经过，驶往该酒店多数员工租住的一处单身公寓，“当时还担心自家员工会不会有危险，没想到悲剧真的发生了”。几分钟后，坦洲消防的几位消防官兵赶到该酒店，告知酒店旗下员工闫娇娇在火患中被烧伤，已送往坦洲医院。“当时去到坦洲医院后，坦洲医院判断娇娇烧伤面积过大，随即又被紧急送往了中山市人民医院外科ICU接受治疗”。治疗费用需60万-100万据闫娇娇的主管医生、中山市一医院烧医生介绍，闫娇娇被诊断为全身63%烧伤，大部分为重度。“她大概是中午1点多送到我院，当时第一时间就做了抢救工作，由于担心她发生窒息，我们进行了气管切开手术，进行了静脉插刺，补液等工作，目前虽然她的情况已经比较稳定，但仍旧没有脱离生命危险。预计后天（本周五）将对她进行第一次的植皮手术，目前最怕的就是发生感染以及并发症，需要做两次手术才能确定是否能够把她救回来。”田医生称，预估闫娇娇需要60万-100万元的治疗费用。中山市人民医院外科监护室出具的一份病情介绍，24岁的闫娇娇因“全身多处烧伤”被诊断为：烧伤面积达63%，大部分为重度烧伤；吸入性损伤。患者现神智清醒，通过呼吸机辅助通气，创面肿胀明显，病情危重，预计病程长，花费高。南都记者了解到，事发后，坦洲当地消防、公安等部门已介入调查。但因闫娇娇仍未脱离生命危险，无法讲述事发时的情况，这也给调查工作带来难度。目前，相关调查工作仍在进行。母亲赶赴中山探望女儿途中遭车祸身亡祸不单行，太多的不幸在同一天降临到这个来自山东济宁鱼台的普通农村家庭。“获悉娇娇出事后，我们第一时间联系了她的家人，她的家人当天下午就说要过来，但不幸的是，第二天我们再打电话过去，已经没人接听了”，据闫娇娇的同事李小姐介绍。原来，19日傍晚6点左右，济南绕城高速济南东收费站往南3公里处，接连发生四起追尾相撞事故，造成了2人死亡，6人受伤。死亡者中就有急忙赶来探望女儿的娇娇的母亲。据了解，闫娇娇的父亲正在威海的渔船上打工，家里只有一个十多岁的弟弟和母亲。得知女儿病情严重，母亲立马找到了同村邻居。同村邻居当天下午开车从济宁鱼台出发，送闫娇娇母亲和一位中年陪同亲友前往济南机场，准备赶飞机前往广东。“半路上，她母亲一直很难受，哭了几回。”据送闫娇娇母亲、在车祸中受伤的司机称，闫娇娇自己孤身一人在广州，突然出现这么大的意外，母亲特别担心女儿的病情。“眼看着就快到机场了，没想到堵车的时候会出现事故。”“谁也没想到，女儿出事，母亲也离开了。她（死者）平时务农，丈夫在外打工，家里条件本来就不好。”司机的看护人感慨。“与家属失联以后，我们一开始都不知道原因，后来才知道竟然发生了不幸的事。”同事李小姐感叹道。同事：她是一个开朗、充满正能量的人据同事李小姐介绍，1993年出生的闫娇娇今年2月来到坦洲该酒店担任前台服务工作，“她是一个充满正能量、很有耐心的服务人员”。李小姐清楚地记得，由于处在酒店接待“第一线”，闫娇娇经常会碰到一些急躁的客人，她总是会耐心地向客人解释，并保持微笑，“直到解释到客人满意为止”。“她工作起来很理性，不会将自己的个人感情反映出来，时刻都保持微笑”，该酒店人事经理表示。“闫娇娇也是一个很开朗、很大方的北方女孩”，虽然赚得不多，但每次出去聚餐，她都抢着去买单，对待客人、对待同事都极为友善，“她出事以后，不少她以前接待过的客人都主动过来捐款就可以看出来”，同事李小姐介绍说。 +http://news.163.com/17/1122/20/D3SGC28U0001875P.html +15岁初二女生离家9天未归 疑与男友"私奔" + + （原标题：初二女生离家9天未归，疑和男友私奔） + 【初二女生离家9天未归，疑和男友私奔】近日，浙江宁波，梁先生报警称，他15岁的女儿小芳（化名）一夜之间失踪了。监控拍下小芳和一名男生一起离开的背影。该男生或是小芳男友。警方正在全力寻找。 +http://news.163.com/17/1122/20/D3SFK52Q0001875P.html +派出所获"救我狗命"锦旗 警察:失主本想写救我汪命 + + （原标题：派出所获赠“救我狗命”锦旗背后：失主本想写“救我汪命”） + 还记得前几天浙江东阳南市派出所民警因为帮失主找回一条走失的宠物狗而获赠了一面“破案神速，救我狗命”锦旗的事情吗？当时江苏省公安厅网络安全保卫总队的官方微博将这张狗主赠送锦旗的照片发到了网上令人哭笑不得，迅速引发网友围观热议。随后当事民警就此事接受采访时说：“失主本来想写‘救我汪命’，但怕别人不理解最后就写成了‘救我狗命’。”事情是这一样的，11月20日，江苏省公安厅网络安全保卫总队在其官方微博上发了一张民警接受锦旗的照片，并配文“浙江东阳南市派出所获赠‘破案神速，救我狗命’锦旗”。照片中一只可爱的白色萨摩耶冲着镜头咧着嘴“微笑”，而民警和萨摩耶的主人手持着锦旗，锦旗的落款人是“咖喱的主人”，一旁的小女孩比着剪刀手，看样子是很开心民警叔叔救回了自家的狗狗。据当事民警介绍，这只萨摩耶是11月15日中午走失，失主一家经多次寻找无果后遂向警方求助，最终在当晚找到失踪的宠物狗。11月19日，狗主人带着女儿到派出所送来锦旗，以表示对民警的感谢之意，于是就有了照片中的一幕。但据民警介绍最开始狗主人是想写“救我汪命”，怕别人不理解于是就写成了“救我狗命”，没想到这句话在网上引起如此大的反应。当事民警称：“我们公安民警出于‘群众利益无小事的出发点’总要尽心尽力为他们解决困难。”像治你猫病，救我狗命，这些让人苦笑不得的锦旗其实经常流传在网络上，来自人民群众的真诚真是让人笑出猪叫。就在今年7月，有网友晒出一张落款叫“豆汁”的狗狗送给救治自己的宠物医院一副锦旗，上面直白地写了七个“汪”，这是狗狗表达感激的最高级别吗？哈哈哈！小编真是为豆汁能有有这样狗语十级的狗主人而感到欣慰。像这样的锦旗，还不止是这一家宠物医院收到过。比如还有一主人带着猫去做绝育，最后送来的锦旗也是直抒胸臆“喵喵喵”。生活中养了宠物的各位铲屎官们不仅变的越来越有爱，幽默感也是直线上升。对于这些治好自己家狗子和猫子的医生，或许是不知道怎么感谢才好，所以出了这么多搞笑的“锦旗”。 +http://news.163.com/17/1122/19/D3SCG5T10001875P.html +母亲因给不起儿子彩礼自杀? 官方:不满意儿子对象 +【母亲因给不起儿子彩礼轻生？ 宁陵县：系误传，不满意儿子对象自杀】近日，一则母亲因给不起儿子彩礼而轻生的视频在网络热传。今日，事发地河南省商丘市宁陵县发布通报称，网传为彩礼轻生说法不实，死者林某某是因对儿子相中的对象不满意而跳河自杀。北京青年报记者从网络视频中看到，在一条河边，一男子趴在一女性尸体上哭泣，随后突然转身跳河，后被民警和周围群众救起。负责处理此事的河南省商丘市宁陵县黄冈乡派出所民警杜传峰对媒体表示，轻生者的儿子前不久刚刚订婚，女方彩礼要求一辆车，男方这边付不起因而酿成悲剧。11月22日下午，宁陵县宣传部发通报回应此事，称网传说法不实。通报称，死者林某某因为其儿子谈对象订媒意见不一致，儿子对象与其同乡，林某某因相不中儿子谈的对象，嫌弃其个子低，林某某便以死相逼，一时想不开，骑电动车来到宁陵县黄岗镇张桥村境内废黄河境内跳河自杀。事发后，在不知真相的情况下，误认为林某某是因为高额彩礼致跳河自杀。通报中表示，事发后，临界的黄岗派出所接到报警后，及时出警将死者林某某打捞出来。死者林某某丈夫赶到现场后，见到妻子已经死亡，当时情绪失控跳河，其儿子看到父亲跳河也跳下河救父亲，现场民警随即跳入河中将父子二人救上河岸。 +http://news.163.com/17/1122/19/D3SBBMTT0001875P.html +高校教授"薅走"珍贵标本 暴露后交出54个空材料袋 + + （原标题：“掳走”南京中山植物园标本的竟是一高校副教授） + 现代快报讯11月22日上午，现代快报记者来到南京中山植物园，通过标本馆负责人了解到，事发次日，已经将所有丢失的标本追回。据介绍，此次共计受损标本12份，涉事人员为山东某高校一名副教授及两名学生，发现时已经私自取样7袋，还交出了54个同样的空材料袋，但已标好植物名。“预谋性”查阅？暴露后还交出54个空材料袋11月22日上午10点左右，现代快报记者来到研究所标本馆，在徐馆长的带领下来到了一个工作室，看到在工作台上有7个材料袋放置在对应的7份残缺不全的标本上面，另外在旁边还摆有一沓同样的空置材料袋，每一份上面都写上了不同的植物学名。徐馆长介绍说，11月上旬，山东某高校的副教授许某预约要前来查阅标本。15日，许某进入植物研究所标本馆查阅禾本科植物标本。“我们曾多次向他讲解管理规定，并反复说明不得损坏标本，更不能擅自从标本上取样。”徐馆长告诉现代快报记者，许某等一行三人在查看标本过程中，多次有与正常查阅研究标本不相称的行为，经工作人员多次提醒，但仍未改正。16日上午，工作人员在检查许某已查阅的标本时，发现有多份标本损坏，随即对其叫停了查阅。现代快报记者了解到，许某等人被叫停后，经劝说，当场归还3个已取样的材料袋，并交出54个已写好植物学名但未取样的空袋，当日下午，又归还4袋已取样标本。至此，许某等三人共计私自取样7袋，分别属于7种不同的植物标本。据徐馆长介绍，此次受损标本多达12份，其中严重损伤4份，中度损伤5份，轻度损伤1份。受损标本较多，具体损失正在评估中据了解，在这12份受损标本中历史最久的是1934年采集于河北省的羊茅Festuca ovina L.受损最严重的是1953年采集于黑龙江省的雅库羊茅Festuca jacutica Drob.现代快报记者注意到，在损坏的标本中有一份苇状羊茅Festuca arundinacea Schreber是1985年采集于为美国，据介绍，这是该馆与美国交换的标本，十分珍贵。从残缺的标本上，记者看到，雅库羊茅的种子花序已经所剩无几，这样的情况是否还能修复？标本馆工作人员表示，因为叶片和种子花序没有被损坏揉碎，用胶水粘贴后再以针线进行缝补，尚可进行修复。徐馆长表示，事发后，他们与该副教授及两名学生所在学校取得了联系，学校校长和书记也非常重视，“他们针对此事也正在进一步调查。”事后，许某本人也曾多次表示歉意，但徐馆长认为，标本馆是国家的财产，是社会的财产，是一个基础的科研资料，不是说对某个人表示歉意就解决问题的事。“现在研究所领导一方面，和对方进行沟通，另一方面，正在商讨评估损失。”徐馆长说。私自取样偶有发生，如此大规模还是第一次据了解，该标本馆是重要的科学资料库，通常为半开放机构，即对专业研究人员完全开放，对普通公众一般不开放，但是为了科普和教育，普通公众可团体预约参观，但不允许近距离接触标本。专业人士如果要取样，须向馆内提出申请，标本馆对相应样本进行评估，“如果标本历史悠久，样本罕见，藏量稀少，这样的情况是绝对禁止取样，相反情况下，则获得批准的可能性更大。”许馆长说，凡是入库的标本取样都是有限制的，未经标本馆允许私自取样，对标本进行破坏性取样，在任何馆内都是违规的。一位工作过人员告诉记者，之前也有过类似事件发生，也是业内人士所为，但是还从来没有像这么大规模的。“许某作为一个专业人士，这是最起码的常识，况且我们还再三叮嘱不可随意取样。”徐馆长告诉记者，当时他们一行三人共查阅标本约200余份，有些标本是历经战争和动乱保存下来，非常珍贵。“如果当时没有及时发现，像如此大规模的的取样，对标本的损伤程度很难想象。”据徐馆长介绍，由于每一份标本都采集不易，且具有不可复制性，所以标本上的任何东西都不能动。“包括标签，这是研究标本的学者姓名及鉴定意见。”徐馆长感叹道，与2016年向中山植物园标本馆捐赠6000份植物标本的无锡市民邬文祥相比，“破坏标本的人就显得格调很低下。” +http://news.163.com/17/1122/18/D3S9RAMV0001875N.html +00后CEO回国融资没钱发工资 否认会成另一个贾跃亭 + + （原标题：被雷军关注的00后CEO回国融资 没钱发工资 否认会成另一个贾跃亭） + 河南洛阳少年李昕泽今年17岁，自称中国00后CEO第一人。在之前的一次视频采访中，他出言不逊，称70后企业家为“老一辈”、“不懂互联网”。当时，雷军看到后转发视频截图并调侃自己为“老老老一辈企业家”，结果，李昕泽因此火了。9月，李昕泽前往俄罗斯读哲学，在此之前要学一年俄语。11月初，李昕泽回国，接受了红星新闻采访。他说，这次回来，是为了拍微电影，故事由他开公司改编。同时，他要见一些投资人和合作伙伴。但在上海见投资人时，他的演示网页被黑客攻陷，会面结束后，他说自己并没有慌张，“说点儿投资人想听的就行了。”李昕泽成立了“崇才科技”，“员工”均为00后。这家公司目前拥有300多人，都分散在一个个崇才的QQ群中，此外还有400多人在编外群随时“待命”。但他没有和任何人签合同，不给任何人开工资，因为“没钱”。李昕泽告诉红星新闻，他们公司有鲜明的高低官职，高层职员现有6人。两年过去，他的公司高层选举已经完成了14次，这些人均是李昕泽提名。回国见投资人时网站被黑李昕泽说，“事情已经发生，往下接着聊自己公司的理念和文化，说点儿投资人想听的就行了。2017年9月，李昕泽卸任崇才科技CEO，并提名了崇才科技新的高层管理者。他要去俄罗斯圣彼得堡国立大学读哲学，最初一年主攻俄语。圣彼得堡的生活单纯、轻松，用李昕泽的话说就是“每天上3小时课，和朋友斗地主，自己做饭吃，上网，睡觉”。他从家里带过去大量冬季衣物，还有俄语教材。李昕泽看俄语网站、读俄语书略费劲，整天泡在国内网站上。虽然卸任了崇才科技CEO，在国内的副总裁张泽昊还是习惯性把公司事务、采访都告诉李昕泽，由他定夺。除了张泽昊，在俄罗斯他很少跟公司其他人接触。回国第一天，可能是时差缘故，李昕泽一时想不起来一些公司重要人物的名字，一边想一边嘀咕：“我怎么连他都给忘了。”一方面，他像一个远程遥控；另一方面，他还是大脑中枢。在圣彼得堡，他坐在月租1000元的小房间，一边喝威士忌，一边想崇才科技的未来。他想联合涉及各个领域的公司组成“崇才生态圈”，自己帮助生态圈的公司揽项目，“大家一起赚钱”。由于有人想邀请李昕泽将自己创办公司的故事拍成微电影，他在11月初回国。期间他告诉认识的媒体人这个消息，还约了一些投资人。11月4日凌晨，李昕泽落地上海，住在预订的酒店。他睡到中午12点，走路时有点儿晃晃悠悠，没有准备电脑和计划书，只身搭乘地铁和投资人见面。那是一个新闻导航项目，他掏出手机打开网页向投资人预演，跳出来的却是两个讽刺他抄袭和负面评论的网站。投资人笑笑点开，说：“还是要做好技术，等修复好还可以谈。”李昕泽并没有觉得羞耻，“事情已经发生，往下接着聊自己公司的理念和文化，说点儿投资人想听的就行了。”李昕泽这样对红星新闻说。那位不愿透露姓名的投资人对红星新闻描述着对李昕泽的印象：“00后算比较有想法的，技术不够硬，但毕竟年纪小，没必要妖魔化年轻人。”对李昕泽的抄袭，他说：“如果他拿的是开放源代码改的也不叫抄袭吧。”最后他总结这个年轻人“把商业环境看得比较简单，缺乏经验，但是如果不放弃未来应该还是可以的”。95后王凯歆发过一条关于李昕泽的微博，说：“比我当年还不靠谱！”王凯歆是1998年生人，高二辍学，创立“神奇百货”。之后，王凯歆融资上千万，却最终失败并招来非议。李昕泽看到后随即转发，配文写道：“毕竟不是谁都是梳个杀马特发型上节目哗众取宠取得融资的，所以说还是大姐牛，炒作这方面我比不了。”再提到两个不足20岁年轻人之间的交锋，李昕泽说：“如果‘神奇百货’交给我，我至少能让它活下去。”11月7日，李昕泽和副总裁张泽昊在北京碰面，见了一圈投资者和要建立“崇才生态圈”的合作伙伴。11月12日，李昕泽回到河南洛阳自己的家中。他又想起王凯歆在微博上的言论，凌晨发了微博：“企业嘛，没有什么后悔不后悔的……又回到洛阳了，加油洛阳，加油未来。”否认会成为另一个贾跃亭李昕泽说自己的目标是挣钱，商业化，卖游戏模组，做APP。李昕泽回顾往事，惊奇地发现“崇才的每次重要节点都是我生日前后”。2014年之前，他在一个叫《巴士模拟》的游戏里做游戏模组供玩家下载。后来，他和另一个玩家Vayk成立“凌海工作室”，对抗高年级玩家的嘲讽。然而，李昕泽不喜欢Vayk的做事风格，“遇到外界说我们东西做得不好就回应，撰文道歉，很软。”他回忆，2014年3月27日，生日前一天，自己“掌权”了工作室。从此，他对于批评“不回应，不道歉”。李昕泽说自己的目标是挣钱，商业化，卖游戏模组，做APP。2014年8月，他将工作室改名“崇才工作室”，意为“崇尚人才”。他开始在经常逛的贴吧发招聘，只找00后，联系上一批对编程感兴趣的同龄人，并将他们加入各个挂有“崇才”字眼的QQ群。2014年10月，李昕泽在母亲的陪同下去北京国家会议中心参加了“COCOS全球开发者大会”。他看到与会者的公司名称都带有“科技”，回来后将公司名改为“崇才科技工作室”。2015年3月27日，他和崇才挣到第一笔钱，也是到目前的唯一一笔。他的大伯将他介绍给当地一家旅游服务公司，为公司开发APP，李昕泽拿到1万左右的奖励。他用这笔钱做了一批奖杯，有三个“2014年最高贡献奖”颁给当时的“公司高层”。2015年4月，他独自一人前往北京参加“全球移动游戏大会”，参加了高端酒会，平生第一次喝酒，并在年级群向暗恋的女生表白。当年全国正掀起创业狂潮。据英国会计及咨询公司UHY International统计，2015年中国每天诞生的新公司多达4000家。李昕泽抓住这个时机，2015年7月，用母亲肖蓓的名字注册了公司“洛阳崇才科技网络有限责任公司”。受母亲做生意的影响，李昕泽从小就知道要赚钱，“做东西不就是要赚钱么？”他学着百度百科公司架构设立了CEO、COO、副总裁以及一系列总监。在总监里面，“国际部总监”、“技术总监”、“学科理事”、“谈判总监”又在所有总监职权之上。能受李昕泽重用的人不多，这些职务多有重合。这些听起来不知所谓的职务，是李昕泽的创新，比如学科理事，类似于总裁助理，谈判总监类似于公关。公司成立后，发布了一系列应用软件，并被人迅速指为抄袭，被李昕泽征用的福厦桌面原作者还因自己作品稚嫩感到羞耻。李昕泽9月在接受红星新闻采访时对此回应：“我们的确借鉴了很多，学习了很多。我们借鉴了他们，发展成自己的产品，这样不好吗？”这次再问这个问题，他依然否认是抄袭，“我还保留着很多他们同意我们可以拿来用的聊天记录”。李昕泽留有的大部分是聊天式的证据，他还没有签过正式的合同。2016年，他甚至找到女子团体Sunshine组合，迅速发了公告说明双方要合作，却因为没有签合同被别人从中间“截胡”。再提及此事，他觉得没人可以否认崇才和Sunshine的合作关系，尽管还没什么实质性的成效。后来，Sunshine女团发生变化，李昕泽说她们没有前途了，“都去好好学习了”。副总裁张泽昊向红星新闻介绍，目前崇才科技有300多人，编外400多人，经常活跃的有100多人，多为技术人员。“除了00后，我们也在招90后，目前正在接触的就是一个90后的人力资源。”他告诉红星新闻。李昕泽说，之前开发的被诟病的软件不过是为了“锻炼员工”，“保持专业”，起练兵作用，“现在我的重心都在开发崇才生态圈上。”外界担心李昕泽以后会出现贾跃亭面临的问题，对此，李昕泽说：“我们是不一样的。”他还向红星新闻透露，目前有一个食品公司还未签约，“但是这次我去北京和他们老总吃饭，问题不大。”离开的员工称他独断专行、盲目自大李昕泽喜欢随口提起马云、乔布斯，他说：“我的公司一定是要超过阿里巴巴的。”李昕泽和同龄人有很大不同。高二会考完，李昕泽决定出国读书。他觉得企业家学商科太普遍了，毫无个性，便去俄罗斯读哲学，为了“修身养性”。他用的手机是罗永浩的锤子手机，理由是“苹果买不起，其他牌子都烂大街了”。Vayk是崇才工作室的创始人，由于受不了他的“独断专行”，六进六出后还是离开。Vayk告诉红星新闻，当年读初三，由于耽误学业便选择退出。对于自己在崇才的那段经历，Vayk不想多提，只说：“现在看来崇才很不成熟。”这家公司刚注册两年多，已经召开了14次选举会议。公司高层一般是上届CEO提名，再经过QQ群投票选出。一开始，一个月一次，李昕泽告诉红星新闻，他为了长期当上CEO，便将选举时间缩短为了一个星期，等过了一段时间，也不提选举的事，这个CEO便悄然做下去了。李昕泽在公司高层讨论组里宣布要做一件事情，大家都在下面回复“同意”。只有一次，谈到选哪首歌做“司（公司）歌”时，出现了分歧。大家觉得《明天会更好》不错，他嫌俗，找了另外一首歌，结果遭到全员反对，于是，“司歌”到现在也没有定下来。李昕泽在网上发了很多关于崇才的帖子，大部分都含有口吻成熟老练的词汇。今年提升为副总裁的张泽昊更熟悉这套术语，但李昕泽嫌他啰嗦，开玩笑说：“去采访张泽昊，你什么都问不出来，他只跟你讲意义。”李一龙也是李昕泽所说的“好好学习去了”中的一人。受李昕泽重用时，李一龙提出要举办一个中国青少年创业大会，Vayk说，“因为大会选址，他俩吵过多次，吵得向我互揭老底。” 为此李一龙离开了崇才，他的微博介绍是“晋城一龙网络技术有限公司总裁”。现在李一龙正备战高考，他说：“我对崇才没有印象，只对李昕泽有印象。”提起李昕泽，李一龙用了“自大、盲目、没真才华、善于利用他人、不愿承担”等词汇来形容。李昕泽喜欢随口提起马云、乔布斯，他说：“我的公司一定是要超过阿里巴巴的，这个愿望最近两年有点儿难。”他说自己有个压箱底的创业项目，“用无人机完成贫困山区蔬菜瓜果的买卖。”11月4日傍晚，17岁的李昕泽挤进高峰期的上海地铁，衣服后背印着林则徐的两句诗：“苟利国家生死以，岂因祸福避趋之。” +http://news.163.com/17/1122/18/D3S9E4VL0001875P.html +8岁男孩疑似坠井身亡 家属质疑:井口还没他肩膀宽 + + （原标题：希望学校男童井下死亡之谜：肩比井口宽，校内有施工队） + 这是一口直径约20厘米的井，比一张A4打印纸的短边还少1厘米，一个成年人的脚掌踩在井口会被卡住，起初，没有人把它和一个失踪的8岁男孩联系在一起，直到11月20日，男孩失踪的第6天，遗体从3米多深的井里被发掘出来。孩子课间失踪了?这口井，座落在在安徽阜阳市临泉县医药希望学校内的一片工地旁，失踪男孩巴天宇，是这所学校一年级的学生。医药希望学校是一所规模较大的小学。巴天宇的父亲介绍，学校一年级有9个班，全校32个教学班，学生1998人。学校上午一共有四节课，最后一节课的铃声每天会在十点四十分准时响起。11月15日这天，第四节课一开始，一年级2班的班主任张老师就发现坐在第一排的巴天宇不见了。巴天宇没请过假，此前的三节课也都在座位上正常上课。张老师介绍，天宇之前出现过不按时上课的情况。巴天宇是个不让人省心的孩子，他的母亲徐仅仅没少接到老师的电话。老师说天宇不爱学习，因为爱稿小动作，天宇还被调到第一排靠墙坐，这个位置在老师眼皮底下。发现天宇没在课堂，张老师立刻派班长和几名同学去校园里找他回来上课，厕所、操场都去了，找遍所有能找的地方，还是没找到他。第四节课很快就结束了，天宇还是没出现。上午将近11点，天宇的姥姥做好午饭，出门往学校方向走，准备接外孙回家。学校虽然提供午餐，但天宇的父母觉得在家里吃更放心，况且天宇的家跟学校只有一墙之隔，走路也就五分钟，因此他平时都回家吃午饭。姥姥刚走到学校门口，手机就响了。电话是班主任打来的，问她：天宇是否提前回家？双方一沟通，发现天宇去向不明。姥姥顾不上吃饭，从上午11点找到了下午1点多，也没找到外孙，于是她报了警。天宇的父母巴玉和徐仅仅都在浙江金华，去年，他们开了一家馒头店。天宇上学前，跟在父母身边在浙江“飘着”，去年8月份，才被送回老家阜阳。11月15日凌晨三点多，巴玉夫妇起床开工，准备做馒头。干活时，徐仅仅和丈夫商量，准备招一个工人帮老公打理店铺的活计，她自己回老家照顾儿子。这个念头的热乎劲儿还没过，中午她就接到母亲的电话：天宇失踪了。监控盲区的竖井15日深夜，徐仅仅和老公巴玉连夜赶回阜阳。夫妻俩去了学校。监控记录了天宇的最后行踪。失踪前，他穿着带白花的红色毛衣，下身穿黑色长裤，脚上是一双红色运动鞋。15日上午，第三节课结束之后，天宇和同学一起跑出教室。在走近胡同前，天宇抬头朝教学楼上边望了一眼，身边的小孩与他动作一致。“好像被楼上什么东西吸引了”，巴玉说。此后，天宇自己拐进了教室旁边的一条胡同。胡同是监控盲区，通往教室后面（北面）的一片施工工地，穿过工地就到达学校的操场。拐进胡同之后，天宇的身影就不再出现了。巴玉说，出了胡同，在施工工地旁边安有两处监控，但校方告诉他，这两处监控早就坏了。另外，从学校大门的监控里，也找不到天宇离开学校的身影。施工工地成了寻找天宇的第一现场。官方公布的招标公告显示，临泉医药希望学校工地的在建项目包括一栋五层的教学楼和配套设施。临泉县重点工程建设管理局的负责人韦柏林介绍，这个工程今年3月份开标，4月份动工，目前已基本完工，中标的施工单位是安徽华彩水利工程有限公司。巴玉了解到，出事当天，施工工地上只有七八个工人在作业，整个教学楼的建设已接近尾声。15日白天和16日一整天，警方、救援队以及学校的师生，对施工工地以及周边进行地毯式的排查，找遍工地的每一寸角落，也没有发现天宇——所有人都忽略了两个井口。工地的北侧，有一个略低于地面的缓坑，坑里有少量的积水，坑的外围竖着两口井。井口只有20厘米左右，一个成年人的脚掌踩在井口会被卡住。包括救援队的志愿者、老师、校长和家属在内，所有人都觉得，井口太窄，孩子坠井的可能性不大，用手电筒照看，还能看到井里有水，但没有发现井里有异物。家属们反复查看过两口竖井。他们估算过，天宇一米三的个头，七十多斤的体重，怎么看也和20厘米的井口不匹配，“正常情况下，一个8岁男孩掉下去根本不可能”。徐仅仅一度认为儿子是被拐骗了，她印了一大摞寻人启事，四处发散。她一直处于精神恍惚的状态，每天以泪洗面。而巴玉身为家庭的支柱，硬撑着，面对每一天。井口有新土和线头有很多疑问，巴玉想不通。儿子为什么突然会拐到胡同里？是自己贪玩，还是有什么东西吸引了他？难道是被人给害了？孩子身上应该没什么贵重物品。天宇唯一贵重的物品是一条金链子，但出事那天，天宇也没有戴着它出门。他才8岁，还不太会花钱，平时想要什么，也是直接和姥姥讲，学校和家只有几步路，他身上一分钱都没。出事前几天，天宇看到同学在吃“粘牙糖”，回了家，他通过微信视频跟父亲聊天，希望爸妈从浙江寄糖回来。巴玉有点后悔，他对儿子的这个小小要求没上心，始终没有给天宇买糖。11月19日，孩子失踪的第五天。巴玉越想越不对劲，“监控显示他没出学校，我这孩子不可能凭空就飞了”，于是，他又去了学校里的那片工地。再次来到井边的时候，巴玉发现变化。原来竖井旁边的坑，被填埋了一些。巴玉15日第一次往井里看时，可以看到井水，隔了4天，他趴在地上仔细看，发现井口竟有一层新土，“好像有人动过现场”。更蹊跷的是，巴玉在井口找到几条两厘米左右的红白线头。巧的是，这些线头与天宇失踪时所穿毛衣是一个颜色的。巴玉此时确信，儿子就在井里。井下发现遗体11月20日下午，巴玉找到蓝天救援队，救援人员开始对竖井进行探测。在此之前，一对住在5公里外邻村的老夫妇说，曾有一个和巴天宇年龄相仿，相貌接近的男孩，连续两天向他们讨要食物。巴玉打开手机让他们看照片，这对老人语气笃定，那个讨吃的男孩就是他。这个消息，曾让巴玉夫妇脑中闪现一丝希望，但随着竖井被挖开，希望很快破灭。救援人员用探测设备发现井下3.5米至4米之间有异物。起初并不确定井下是孩子。他们伸下铁钩试探，钩上了孩子的衣服，就是天宇穿的那件毛衣。看来，孩子真的在这口竖井里，且已“出事”。由于井口过于狭窄，直接从井口把天宇拉来上，肯定会破坏孩子的遗体，救援人员和警方决定：利用挖掘机将井口侧方挖开，把孩子从井里挖出来。此时，距离天宇失踪已经过去6天。20日晚，8点左右，挖掘工作正式启动，为防止孩子遗体受到二次伤害，接近孩子被卡住的地方，救援人员用工具手动挖掘。巴玉提供的救援视频显示，井里仍有蓄水，随着井口豁开，井水渗到四周，天宇被救出时身体蜷缩，头朝上。头部上方有些积土。在现场的巴玉夫妇没有亲眼看到孩子被捞出时的样子。他们都晕过去了。法医进行尸检后，天宇的遗体暂存在县殡仪馆。巴玉测量了天宇的遗体。“就算不穿衣服，天宇的肩膀至少也有23厘米宽，加上毛衣有25至28厘米，掉进一个20厘米的洞这不可能，”他说。谜团待解天宇是怎么坠井的，现在还是个谜。根据孩子平时的表现，班主任张老师认为，天宇在智力方面有些反常，跟其他孩子不一样，字也写的不好。“从来不写作业，也不会写（做）”。天宇还会在同桌的书上乱画，影响同学的学习。姥姥给他买的本子，也被他撕得满地都是。张老师评价，天宇在学校算是调皮的孩子，下课的时候会去抓别人一下，拽别人衣服一下什么的，两位任课老师多次跟天宇的家长沟通，说这个孩子在学校不适合大的环境，“他家长说，只要他在教室，学多少是多少，不惹事就行了，只要平平安安。”张老师还说，出事的井是施工用井，并非学校自用的水井，“以前（天宇）也没有发生什么大的问题，没想到会发生这种情况。”巴玉承认，天宇是很调皮，但他否认孩子有智力问题，“就是学习不行，其他事情甚至比大人还聪明”。看到孩子长期不能集中精力学习，巴玉也曾担心他有多动症，去年，他特意带天宇去浙江的大医院做全面检查，结果显示，一切正常。徐仅仅说，唯一能让天宇提起兴趣的只有画画，天宇的作文本上，被他画满了穿裙子的小公主，“没有学过（画画），他就是喜欢”。寻人启事上，注明天宇“口齿有些不清”，巴玉解释，孩子舌根的筋有问题，做过手术。徐仅仅回想，如果孩子留在身边，也许不会发生这种意外。她和丈夫都不相信儿子是自己坠井的。深一度记者联系了临泉医药希望学校的孟校长、施工单位安徽华彩水里工程有限公司的负责人，谈及两口施工竖井的问题时，两人都挂断了电话。目前，此案由临泉县公安局刑警大队进行调查，队长表示，要等尸检结果出来后才能给案件定性。徐仅仅今年29岁，将来还有生小孩的机会。但眼下，夫妻俩只想知道，天宇在落井之前到底遭遇了什么？监控盲区的工地上发生过什么？他们在等尸检报告和调查结论。巴玉把天宇失踪之日当成祭日。21日早上，他走到学校门口烧了一堆纸，这天算是孩子的头七。8岁男孩失踪5天 学校操场直径20余厘米井中现尸体安徽省阜阳市临泉县8岁男孩巴天宇在几天前失踪，家长及警方寻找数日后，在学校操场的一个直径20余厘米的井内发现了孩子的尸体，目前警方正在对此进行调查。 +http://news.163.com/17/1122/17/D3S4VVF700018AOP.html +女大学生取消订单遭外卖员骚扰 短信内容淫秽露骨 + + （原标题：济南一外卖小哥给女大学生发淫秽短信，疑因被投诉） + 最近，小婧（化名）遇到了一件糟心事。11月7日，她从某外卖平台点了一份外卖，但过了送餐时间饭还没有到，她联系外卖小哥试图取消订单，但遭对方大声呵斥。无奈之下，小婧通过商家取消了订单，并投诉了态度恶劣的外卖小哥。没想到外卖小哥竟给她发来骚扰短信，内容淫秽露骨，非常不堪。22日下午，涉事外卖平台回应称，已暂时对当事外卖小哥进行封号处理。小婧是济南某高校的一名在校大学生。11月7日下午2点多，她在宿舍收拾完东西后，考虑到食堂没饭了，就通过 某外卖平台订了两个鱼堡，下单后就在宿舍里等着。但是，等了40多分钟，且已超过了规定送餐时间，仍不见外卖小哥来。小婧说，外卖平台可以显示外卖小哥的实时位置，她打开手机一看，发现外卖小哥在芙蓉街附近，距离她所在的 市中区越来越远。“我说你绕远了怎么给我送来啊，这都到点了你不着急啊？”小婧说，外卖小哥称还有十几分钟才 到，但她觉得已超过了送餐时间，而且鱼堡放得时间久了会有腥味，就提出了退单。听到小婧要退餐，外卖小哥当时就急了，冲着她大声吼“你就退，你退吧”，随即挂断了电话。无奈之下，小婧又找到了商家，说明事情缘由后，商家也很爽快，立刻取消了订单。在订单取消原因一栏中，小婧写道：“骑手送不到态度还极其恶劣”。本以为事情就这样结束了，但下午4点左右时，小婧突然接到一条陌生短信，短信内容让她恶心到不行。记者看到，对方用短信先发了一句“我想和你做*”，随后又发来一段更加露骨的淫秽文字，内容不堪入目。“挺恶心的！”小婧说，她知道短信就是那个外卖小哥发的，因为外卖小哥此前给她打过电话，假借找工作问她是不是学生，自称要找陪读，工作时间是凌晨4点到8点。“谁都懂是什么意思啊！”小婧对外卖小哥的行为很生气， 直接向平台投诉了外卖小哥。投诉后不久，有一名自称外卖平台经理的人和小婧取得联系。经理告诉她，这名外卖小哥比较年轻，家里还有老人和小孩，希望取得她的谅解。“我还是很气，跟他经理说你们不管这样的人吗，经理说他管不了。”小婧说，后来 她从平台客服那里了解到，这名外卖小哥是一名众包骑手，属于众包团队自己处理，他们也管不了，只能扣他的钱。上午10点多，记者拨打了给小婧发送淫秽短信的电话号码。一名男子接通后表示，虽然那条淫秽短信显示是用他的手机号发的，但短信并不是他发送的，他是无辜的。据男子介绍，事发当天下午，他和很多外卖小哥在一起聚餐，认识和不认识都在一起，为了方便吃饭，他把手机放在了桌子上，没想到饭后手机里莫名出现了短信发送记录。“我可以明确告诉你，不是我发的，可能有人拿我手机 发了短信。”就外卖小哥向女大学生发淫秽短信骚扰一事，22日下午，记者联系到了涉事的外卖平台。平台相关负责人表示， 在接到客户的电话投诉后，他们根据客户订单第一时间找到为其配送的骑手为代理商众包骑手。由于骑手接单电话和 用户收到骚扰短信的电话不一致，无法准确定责，当时代理商公司对骑手进行了警告处理。目前，骑手电话无人接听 ，公司已经暂时对其进行封号，接下来会继续寻找骑手本人核实此事。 +http://news.163.com/17/1122/17/D3S4RDRJ0001875O.html +马航MH370失联乘客仍未被宣告死亡：妻子不能改嫁 + + （原标题：MH370乘客家属索赔案召开庭前会议 失联者家属提出10项诉讼请求） + 2014年3月8日，马来西亚航空公司MH370航班从吉隆坡起飞前往北京途中失联。到现在，MH370失联已经3年多了。11月20日、21日，北京铁路运输法院首次就该航班部分失联乘客家属民事索赔案召开庭前会议。庭前会议在北京铁路运输法院的一个法庭召开，原告有49名，他们是马航MH370航班中14名失联乘客的家属，被告有5个，分别是马来西亚航空公司（又称老马航）、马来西亚国际航空有限公司（又称新马航）、美国波音公司、飞机发动机制造商英国罗罗公司、德国安联保险集团。张起淮是这14名失联乘客家属的代理律师，他介绍，5家被告公司都安排高管或诉讼代理人参加了庭前会议。庭前会议是人民法院对疑难复杂或重大案件，在正式开庭前，召集当事各方了解案件事实与证据情况，梳理案件争议焦点，为正式开庭进行的准备活动。MH370航班失联乘客家属代理律师 张起淮：因为涉外案件不像国内案件，发个传票你就来收，而是要通过司法部，去向相对国的司法部、司法机关去送达，传他来参与诉讼，通过这么一个途径，特殊的涉外案件的途径，已经送达到了，这是第一个问题，被告都来了，也答辩了。失联者家属提出10项诉讼请求庭前会议上，法官主持了原被告双方的证据交换。张起淮律师介绍，失联者家属一共向法庭提出了10项诉讼请求，包括要求被告书面告知失联飞机的现状、查明并公布事件原因和责任以及对家属的赔偿等。MH370航班失联乘客家属代理律师 张起淮：第二个问题呢明确了原告的诉讼请求，并且交换了诉状和答辩状，也明确了被告的答辩意见，原被告之间基本明确的观点和要求交换了书面的相关主张，第三个对于双方就诉讼请求中和答辩意见中，主张的观点和依据的事实提供了证据，双方交换了证据，但是没有做质证，会在以后的正式开庭中才去质证发表辩论意见。据了解，49名原告代表了14名失联乘客的家属，涉及到36个家庭，诉请赔偿金额少则一千多万，多的达到7700多万，面对赔偿问题，庭前会议上，5被告也予以了答辩。MH370航班失联乘客家属代理律师 张起淮：五个被告共同的答辩意见是，一飞机现在已经宣告失联了失踪了，二现在还在搜寻之中，这两点是矛盾的，这是第一个特点；第二个呢就是互相推诿，不是我的责任，要么就说是他的责任，要么就说不是我的责任，我不知道是谁的责任，这是共同点。五被告均表示责任不在自己关于具体责任问题，张起淮律师表示，新马航说责任要归老马航，因为新马航经重组后在2015年9月1日才开始运营的；老马航认为飞机摔到哪儿应该找哪儿，飞机没有摔到马来西亚，所以搜救和他无关；赔偿问题上，他们认为按照《蒙特利尔公约》最多赔偿11.31万美元。美国波音公司辩称，失联型号飞机已经运营20余年，飞机质量没有缺陷，不是他们的责任。飞机发动机制造商英国罗罗公司则提出诉讼主体资格有瑕疵，认为诉的对象不是他们。德国安联保险则声称自己并非马航飞机的保险人。具体开庭时间有待进一步通知关于此案的庭前会议已于21日结束，法院具体什么时间开庭还有待进一步通知。失联的MH370航班为马来西亚航空公司的一家波音777飞机，2014年3月8日在由吉隆坡国际机场飞往北京首都国际机场途中失联。航班上共有239名乘客和机组人员，其中中国乘客154名。飞机失联后，马来西亚、越南、中国、菲律宾、美国、澳大利亚、英国、新西兰等多国舰船和飞机参与搜救，目前仍下落不明。诉请赔偿金额1000万-7700万不等记者了解到，在此次庭前会议上，49名原告向马航、波音公司等五被告提出的民事赔偿金额少则一千多万人民币，多的达到7700多万，这样的索赔数额是依照什么标准，怎么计算出来的？另外，记者也了解到，马航MH370航班事件到现在已经有3年零8个多月了，它的状态在给乘客家属造成难以想象的痛苦之外，还带来了许多法律关系上的麻烦。诉请赔偿金额是如何计算出的提起诉讼的是14名失联乘客的49名家属，他们均委托了张起淮律师作为诉讼代理人，诉请赔偿金额从1000多万到7700多万人民币不等。MH370航班失联乘客家属代理律师 张起淮：差异的地方分这么几点，一个我是按照余生计算法，年轻剩余的年限多赔偿的年头多；第二生前的收入，像西方国家美国、英国和欧洲，它是依照交税纳税的多少赔偿的标准多少，那我们这个依照他的收入的高低；第三个根据你所在的地区，山东的、河南的、北京的，以最高的数额来主张，但是它有一个抚养人，当地人均生活水平和抚养人的多少，家里老人多，孩子还很小，我有三个小孩，你一个小孩，现在三个小孩的我要多赔偿，因此这三项在里面就出现了差距，现在就差了好几千万。张起淮律师介绍，索赔金额包括了家属的误工费、精神损害抚慰金等所有款项。并未宣告“死亡” 家属生活遇麻烦采访中记者了解到，虽然马航MH370航班从2014年3月8号失联到现在已过去3年零8个多月，但是由于没有正式宣告机上乘客已死亡，这给乘客家属造成了许多生活上的麻烦。MH370航班失联乘客家属代理律师 张起淮：这个飞机上失联的旅客，到现在为止都没有合法的结论，男人丢了女人不能改嫁，女人丢了男人不能重娶，银行存款不能够去提取，原因是什么，没有宣告死亡，没有宣告死亡，银行是不办理这些变更的，你也无法去婚姻转换的。律师介绍，虽然依照我国民事诉讼法、婚姻法的相关规定，失联乘客的家属可以通过人民法院来主动申请宣告失联亲人的失踪或死亡，以此来解决婚姻等现实问题，但作为亲人，让他们主动这样去做很多家属心理上很难接受。MH370航班失联乘客家属代理律师 张起淮：没有宣告死亡，没有死亡证明，所以我们有几位，154位中国乘客中有人去法院申请要求法院判决宣告死亡，为了取东西，但是心里面还是不愿意的。现在我们中国老百姓有句俗话叫我活着要见人，死了要见尸，人遗体、飞机都没见，你说我怎么在感情上说，我儿子就是不在了，所以他痛苦在这儿，这种痛苦恐怕在人类有航空器以来还是第一次。失联乘客家属在美国等国也有诉讼据了解，张起淮律师还代理了另外28名MH370失联中国乘客家属在美国提起的民事赔偿诉讼。因为根据相关国际公约和我国法律的规定，马航MH370航班上失联乘客的家属，既可以依据国籍在本国内提起诉讼，也可以在航空器承运人所在地马来西亚提起诉讼，如果认为飞机质量存在问题也可以在飞机生产、设计、制造商所在地如美国、英国提起诉讼。另据了解，已有航班上其他国家失联乘客家属在美国、马来西亚、新西兰等国提起民事赔偿诉讼请求。 From 33450060b58d16850ca20ca8a1e90a90bb7ec27a Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Sat, 25 Nov 2017 13:06:05 +0800 Subject: [PATCH 26/30] Add files via upload --- ...350\241\250\350\276\276\345\274\217.ipynb" | 1345 +++++++++++++++++ 1 file changed, 1345 insertions(+) create mode 100644 "chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217.ipynb" diff --git "a/chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217.ipynb" "b/chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217.ipynb" new file mode 100644 index 000000000..47c94f656 --- /dev/null +++ "b/chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217.ipynb" @@ -0,0 +1,1345 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# python正则表达式快速基础教程" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "正则表达式，这个术语不太容易望文生义(没有去考证是如何被翻译为正则表达式的)，其实其英文为Regular Expression，直接翻译就是：有规律的表达式。这个表达式其实就是一个字符序列，反映某种字符规律，用(字符串模式匹配)来处理字符串。很多高级语言均支持利用正则表达式对字符串进行处理的操作。\n", + "\n", + "python提供的正则表达式文档可参见：https://docs.python.org/3/library/re.html" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true, + "scrolled": true + }, + "outputs": [], + "source": [ + "import re" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 首先引入python正则表达式库re" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**1. 初识**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true, + "scrolled": true + }, + "outputs": [], + "source": [ + "s = 'Blow low, follow in of which low. lower, lmoww oow aow bow cow 23742937 dow kdiieur998.'\n", + "p = 'low'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 假设要在字符串s中查找单词`low`，由于该单词的规律就是`low`，因此可将`low`作为一个正则表达式，命名为`p`。" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['low', 'low', 'low', 'low', 'low']" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = re.findall(p, s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `findall(pattern, string)`是re模块中的函数，会在字符串`string`中将所有匹配正则表达式`pattern`模式的字符串提取出来，并以一个`list`的形式返回。该方法是从左到右进行扫描，所返回的`list`中的每个匹配按照从左到右匹配的顺序进行存放。\n", + "- 正则表达式`low`能够将所有单词`low`匹配出来，但是也会将`lower`，`Blow`等含有`low`字符串中的`low`也匹配出来。" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "p = input('请输入字符模式，回车结束！\\n')\n", + "m = re.findall(p,s)\n", + "if not m:\n", + " print('没有找到匹配字符！')\n", + "else:\n", + " print('成功匹配！')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "如果不存在可以匹配的字符模式，则返回空列表。可以利用列表是否为空作为分支条件。" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['low', 'low']" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = r'\\blow\\b'\n", + "m = re.findall(p, s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `\\b`，即`boundary`，是正则表达式中的一种特殊字符，表示单词的边界。正则表达式`r'\\blow\\b'`就是要单独匹配`low`，该字符串两侧为单词的边界(边界为空格等，但是并不对边界进行匹配)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['low', 'low', 'low', 'low', 'low', 'mow', 'oow']" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = r'[lmo]ow'\n", + "m = re.findall(p, s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `[lmo]`，匹配`lmo`字母中的任何一个" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['aow', 'bow', 'cow', 'dow']" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = r'[a-d]ow'\n", + "m = re.findall(p, s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `[a-d]`，匹配`abcd`字母中的任何一个" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['2', '3', '7', '4', '2', '9', '3', '7', '9', '9', '8']" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = r'\\d'\n", + "m = re.findall(p, s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `\\d`，即digit，表示数字，\\d表示数字（一个数字字符）" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['23742937', '998']" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = r'\\d+'\n", + "m = re.findall(p, s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `+`，表示一个或者重复多个对象，对象为`+`前面指定的模式\n", + "- 因此`\\d+`可以匹配长度至少为1的任意正整数字符。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2. 基本匹配与实例**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "字符模式|匹配模式内容|等价于\n", + "----|---|--\n", + "[a-d]|One character of: a, b, c, d|[abcd]\n", + "[^a-d]|One character except: a, b, c, d|[^abcd]\n", + "abc丨def|abc or def|\n", + "\\d|One digit|[0-9]\n", + "\\D|One non-digit|[^0-9]\n", + "\\s|One whitespace|[ \\t\\n\\r\\f\\v]\n", + "\\S|One non-whitespace|[^ \\t\\n\\r\\f\\v]\n", + "\\w|One word character|[a-zA-Z0-9_]\n", + "\\W|One non-word character|[^a-zA-Z0-9_]\n", + ".|Any character (except newline)|[^\\n]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "固定点标记|匹配模式内容\n", + "----|---\n", + "^|Start of the string\n", + "$|End of the string\n", + "\\b|Boundary between word and non-word characters" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "数量词|匹配模式内容\n", + "----|---\n", + "{5}|Match expression exactly 5 times\n", + "{2,5}|Match expression 2 to 5 times\n", + "{2,}|Match expression 2 or more times\n", + "{,5}|Match expression 0 to 5 times\n", + "*|Match expression 0 or more times\n", + "{,}|Match expression 0 or more times\n", + "?|Match expression 0 or 1 times\n", + "{0,1}|Match expression 0 or 1 times\n", + "+|Match expression 1 or more times\n", + "{1,}|Match expression 1 or more times" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "字符转义|转义匹配内容\n", + "----|---\n", + "\\\\.|. character\n", + "\\\\\\|\\ character\n", + "\\\\*|* character\n", + "\\\\+|+ character\n", + "\\\\?|? character\n", + "\\\\{|{ character\n", + "\\\\)|) character\n", + "\\\\[|[ character" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['010-66677788', '02166697788', '0451-22882828']" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = re.findall(r'\\d{3,4}-?\\d{8}', '010-66677788,02166697788, 0451-22882828')\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 匹配电话号码，区号可以是3或者4位，号码为8位，中间可以有`-`或者没有。" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['测', '试', '汉', '字', '测', '试', '可', '以']" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = re.findall(r'[\\u4e00-\\u9fa5]', '测试 汉 字，abc，测试xia，可以')\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 匹配汉字" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 几个组合实例\n", + "\n", + "正则表达式|匹配内容\n", + "----|---\n", + "[A-Za-z0-9]|匹配英文和数字\n", + "[\\u4E00-\\u9FA5A-Za-z0-9_]|中文英文和数字及下划线\n", + "^[a-zA-Z][a-zA-Z0-9_]{4,15}$`|合法账号，长度在5-16个字符之间，只能用字母数字下划线，且第一个位置必须为字母" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3. 进阶**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.1 python正则表达式常用函数**\n", + "\n", + "函数|功能|用法\n", + "----|---|---\n", + "re.search|Return a match object if pattern found in string|re.search(r'[pat]tern', 'string')\n", + "re.finditer|Return an iterable of match objects (one for each match)|re.finditer(r'[pat]tern', 'string')\n", + "re.findall|Return a list of all matched strings (different when capture groups)|re.findall(r'[pat]tern', 'string')\n", + "re.split|Split string by regex delimeter & return string list|re.split(r'[ -]', 'st-ri ng')\n", + "re.compile|Compile a regular expression pattern for later use|re.compile(r'[pat]tern')\n", + "re.sub|Replaces all occurrences of the RE pattern in string with repl, substituting all occurrences unless max provided. This method returns modified string|re.sub(r'[pat]tern', repl, 'string')" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "<_sre.SRE_Match object; span=(0, 12), match='010-66677788'>" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = re.search(r'\\d{3,4}-?\\d{8}', '010-66677788,02166697788, 0451-22882828')\n", + "m" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'010-66677788'" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m.group()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- search总是返回第一个成功匹配，如果没有匹配，则返回None\n", + "- 利用group()函数，取出match对象中的内容" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(0, 12)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m.span()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "span()函数返回匹配字符串的起始和结束位置" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "010-66677788\n", + "02166697788\n", + "0451-22882828\n" + ] + } + ], + "source": [ + "ms = re.finditer(r'\\d{3,4}-?\\d{8}', '010-66677788,02166697788, 0451-22882828')\n", + "for m in ms:\n", + " print(m.group())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- finditer()是返回所有匹配，放置在一个元组中，每个匹配都是类似search()函数所返回的match对象，内含每个匹配的详细信息\n", + "- 可以对该元组进行迭代，取得每个match对象，进一步可以取得其详细信息\n", + "- 与findall()的区别是，findall()只取得所有匹配字符串，返回包含所有匹配字符串的列表，不关心匹配字符串在原字符串中的各项信息。" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['010', '66677788', '02166697788', '0451', '22882828']" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "words = re.split(r'[,-]', '010-66677788,02166697788,0451-22882828')\n", + "words" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "正则下的split()，是一般split()函数的增强版本，可以对字符串以正则表达式匹配的字符进行切割，返回切割后的列表。" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['010', '66677788', '02166697788', '0451', '22882828']" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = re.compile(r'[,-]')\n", + "p.split('010-66677788,02166697788,0451-22882828')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用compile()函数将正则表达式编译，如以后多次运行，可加快程序运行速度" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.2 分组与引用**\n", + "\n", + "Group Type|Expression\n", + "----|---\n", + "Capturing|**(** ... **)**\n", + "Non-capturing|**(?:** ... **)**\n", + "Capturing group named Y|**(?P<Y>** ... **)**\n", + "Match the Y'th captured group|\\Y\n", + "Match the named group Y|(?P=Y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- (...) 将括号中的部分，放在一起，视为一组，即group。以该group来匹配符合条件的字符串。\n", + "- group，可被同一正则表达式的后续，所引用，引用可以利用其位置，或者利用其名称，可称为反向引用。" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'ababababab'" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = re.compile('(ab)+')\n", + "p.search('ababababab').group()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "('ab',)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.search('ababababab').groups()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 有分组的情况，用groups()函数取出匹配的所有分组" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'1-2-3'" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p=re.compile('(\\d)-(\\d)-(\\d)')\n", + "p.search('1-2-3').group()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "('1', '2', '3')" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.search('1-2-3').groups()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['眼睛', '深情']" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s = '喜欢/v 你/x 的/u 眼睛/n 和/u 深情/n 。/w'\n", + "p = re.compile(r'(\\S+)/n')\n", + "m = p.findall(s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 按出现顺序捕获名词(/n)。" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'1-2-3'" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p=re.compile('(?P\\d)-(\\d)-(\\d)')\n", + "p.search('1-2-3').group()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 在分组内，可通过`?P`的形式，给该分组命名，其中name是给该分组的命名" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'1'" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.search('1-2-3').group('first')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 可利用`group('name')`，直接通过组名来获取匹配的该分组" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[('13', 'Tom'), ('18', 'John')]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s = 'age:13,name:Tom;age:18,name:John'\n", + "p = re.compile(r'age:(\\d+),name:(\\w+)')\n", + "m = p.findall(s)\n", + "m" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['Tom', 'John']" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = re.compile(r'age:(?:\\d+),name:(\\w+)')\n", + "m = p.findall(s)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- `(?:\\d+)`，匹配该模式，但不捕获该分组。因此没有捕获该分组的数字" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The match is bb,the capture group is ('b',)\n" + ] + } + ], + "source": [ + "s = 'abcdebbcde'\n", + "p = re.compile(r'([ab])\\1')\n", + "m = p.search(s)\n", + "print('The match is {},the capture group is {}'.format(m.group(), m.groups()))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "- 此即为反向引用\n", + "- 当分组`([ab])`内的`a`或`b`匹配成功后，将开始匹配`\\1`，`\\1`将匹配前面分组成功的字符。因此该正则表达式将匹配`aa`或`bb`。\n", + "- 类似地，r'([a-z])\\1{3}'，该正则将匹配连续的4个英文小写字母。" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'12'" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s = '12,56,89,123,56,98, 12'\n", + "p = re.compile(r'\\b(\\d+)\\b.*\\b\\1\\b')\n", + "m = p.search(s)\n", + "m.group(1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 利用反向引用来判断是否含有重复数字，可提取第一个重复的数字。\n", + "- 其中`\\1`是引用前一个分组的匹配。" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'12'" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s = '12,56,89,123,56,98, 12'\n", + "p = re.compile(r'\\b(?P\\d+)\\b.*\\b(?P=name)\\b')\n", + "m = p.search(s)\n", + "m.group(1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 与前一个类似，但是利用了带分组名称的反向引用。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3.3 贪婪与懒惰**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "数量词|匹配模式内容\n", + "----|---\n", + "{2,5}?|Match 2 to 5 times (less preferred)\n", + "{2,}?|Match 2 or more times (less preferred)\n", + "{,5}?|Match 0 to 5 times (less preferred)\n", + "*?|Match 0 or more times (less preferred)\n", + "{,}?|Match 0 or more times (less preferred)\n", + "??|Match 0 or 1 times (less preferred)\n", + "{0,1}?|Match 0 or 1 times (less preferred)\n", + "+?|Match 1 or more times (less preferred)\n", + "{1,}?|Match 1 or more times (less preferred)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 当正则表达式中包含能接受重复的限定符时，通常的行为是（在使整个表达式能得到匹配的前提下）匹配尽可能多的字符。(贪婪匹配)\n", + "- 而懒惰匹配，是匹配尽可能少的字符。方法是在重复的后面加一个`?`。" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'perl>'" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = re.compile('<.*>')\n", + "p.search('perl>').group()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 贪婪匹配（默认）将匹配尽可能多的重复" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "''" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = re.compile('<.*?>')\n", + "p.search('perl>').group()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 懒惰匹配(非贪婪匹配)，将匹配尽可能少的重复" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'ababababab'" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = re.compile('(ab)+')\n", + "p.search('ababababab').group()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'ab'" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = re.compile('(ab)+?')\n", + "p.search('ababababab').group()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4. 文本处理中的一些应用实例**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4.1 提取文本中的符合某种模式的字串并进行处理后替换**" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "with open(r'test_re.txt', encoding = 'utf-8') as f:\n", + " text = f.read()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "读入文本文件" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['一九九八年/t 新年/t',\n", + " '一九九七年/t 十二月/t',\n", + " '１２月/t ３１日/t',\n", + " '１９９８年/t 新年/t',\n", + " '１９９９年/t １２月/t',\n", + " '１２月/t ３１日/t',\n", + " '１２月/t ３１日/t',\n", + " '十二月/t 三十一日/t',\n", + " '今天/t 上午/t',\n", + " '上午/t 九时/t']" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p = '[\\S]+/t[^/]+/t'\n", + "lines = re.findall(p, text)\n", + "lines[:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 提取词性标记模式为连续2个时间标记t的子串\n", + "- 模式可构造为：1或多个非空白字符 /t 一或者多个不含`/`的字符 /t\n", + "- 利用findall()函数，返回所有符合模式的子串，并查看前10个子串" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['一九九八年/t 新年/t ',\n", + " '一九九七年/t 十二月/t 三十一日/t ',\n", + " '１２月/t ３１日/t ',\n", + " '１９９８年/t 新年/t ',\n", + " '１９９９年/t １２月/t ',\n", + " '１２月/t ３１日/t ',\n", + " '１２月/t ３１日/t ',\n", + " '十二月/t 三十一日/t ',\n", + " '今天/t 上午/t ',\n", + " '上午/t 九时/t 二十分/t ']" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import re\n", + "p = '((?:[\\S]+/t\\s){2,})'\n", + "matchs = re.findall(p, text)\n", + "matchs[:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 捕获连续两个以上的时间标记词汇\n", + "- findall()函数在应用分组时，将捕获所有分组，不是捕获符合模式的字符串，因此这里将整体作为一个分组\n", + "- `?:`表示不捕获该分组内容" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['19980101-01-001-001/m 迈向/v 充满/v 希望/n 的/u 新/a 世纪/n ——/w 一九九八年新年/t 讲话/n （/w 附/v 图片/n １/m 张/q ）/w ',\n", + " '19980101-01-001-002/m 中共中央/nt 总书记/n 、/w 国家/n 主席/n 江/nr 泽民/nr ',\n", + " '19980101-01-001-003/m （/w 一九九七年十二月三十一日/t ）/w ',\n", + " '19980101-01-001-004/m １２月３１日/t ，/w 中共中央/nt 总书记/n 、/w 国家/n 主席/n 江/nr 泽民/nr 发表/v １９９８年新年/t 讲话/n 《/w 迈向/v 充满/v 希望/n 的/u 新/a 世纪/n 》/w 。/w （/w 新华社/nt 记者/n 兰/nr 红光/nr 摄/Vg ）/w ',\n", + " '19980101-01-001-005/m 同胞/n 们/k 、/w 朋友/n 们/k 、/w 女士/n 们/k 、/w 先生/n 们/k ：/w ']" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def express(line):\n", + " return line.group().replace('/t ', '')+'/t '\n", + "\n", + "txt = re.sub(p, express, text)\n", + "txt.split('\\n')[:5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- express()为一个自定义函数，参数为match对象，可以将match对象中所有的'/t'替换为空，并在结尾加上'/t '\n", + "- re.sub()函数，第二个参数可以是函数，当其为函数时，会将pattern每一次匹配到的结果作为match对象，传参给该函数，接受该函数的返回值来进行字符串替换\n", + "- 本例中将所有连续的时间标记词汇合成为一个" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4.2 网页文件(HTML)处理示例**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **5. 常用正则表达式（待补充）**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**进一步学习可参考官方文档以及《精通正则表达式(第3版)》**" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.0" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 5c0b213c2a99a664963974cbd6bd49f192087183 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Sat, 25 Nov 2017 13:11:34 +0800 Subject: [PATCH 27/30] Add files via upload --- chapter3/test_re.txt | 435 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 435 insertions(+) create mode 100644 chapter3/test_re.txt diff --git a/chapter3/test_re.txt b/chapter3/test_re.txt new file mode 100644 index 000000000..d2bf6e961 --- /dev/null +++ b/chapter3/test_re.txt @@ -0,0 +1,435 @@ +19980101-01-001-001/m 迈向/v 充满/v 希望/n 的/u 新/a 世纪/n ——/w 一九九八年/t 新年/t 讲话/n （/w 附/v 图片/n １/m 张/q ）/w +19980101-01-001-002/m 中共中央/nt 总书记/n 、/w 国家/n 主席/n 江/nr 泽民/nr +19980101-01-001-003/m （/w 一九九七年/t 十二月/t 三十一日/t ）/w +19980101-01-001-004/m １２月/t ３１日/t ，/w 中共中央/nt 总书记/n 、/w 国家/n 主席/n 江/nr 泽民/nr 发表/v １９９８年/t 新年/t 讲话/n 《/w 迈向/v 充满/v 希望/n 的/u 新/a 世纪/n 》/w 。/w （/w 新华社/nt 记者/n 兰/nr 红光/nr 摄/Vg ）/w +19980101-01-001-005/m 同胞/n 们/k 、/w 朋友/n 们/k 、/w 女士/n 们/k 、/w 先生/n 们/k ：/w +19980101-01-001-006/m 在/p １９９８年/t 来临/v 之际/f ，/w 我/r 十分/m 高兴/a 地/u 通过/p [中央/n 人民/n 广播/vn 电台/n]nt 、/w [中国/ns 国际/n 广播/vn 电台/n]nt 和/c [中央/n 电视台/n]nt ，/w 向/p 全国/n 各族/r 人民/n ，/w 向/p [香港/ns 特别/a 行政区/n]ns 同胞/n 、/w 澳门/ns 和/c 台湾/ns 同胞/n 、/w 海外/s 侨胞/n ，/w 向/p 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人民/n 反对/v 种族/n 隔离/vn 的/u 正义/n 斗争/vn 。/w 中国/ns 人民/n 与/p 南非/ns 人民/n 一样/u ，/w 为/p 新/a 南非/ns 的/u 诞生/vn 感到/v 欢欣鼓舞/i ，/w 并/c 为/p 南非/ns 人民/n 近年来/l 在/p 国家/n 建设/vn 各项/r 事业/n 中/f 取得/v 的/u 成就/n 感到/v 高兴/a 。/w +19980101-03-003-005/m 钱/nr 其琛/nr 说/v ：/w “/w 新/a 南非/ns 诞生/v 后/f 的/u 几/m 年/q 里/f ，/w 我们/r 两/m 国/n 尽管/d 没有/d 建交/v ，/w 但/c 人员/n 往来/vn 频繁/a ，/w 经贸/j 合作/vn 发展/v 很/d 快/a ，/w 展现/v 出/v 双边/n 关系/n 的/u 美好/a 前景/n 和/c 经贸/j 合作/vn 的/u 巨大/a 潜力/n 。/w 中国/ns 和/c 南非/ns 经济/n 发展/vn 各有所长/i ，/w 资源/n 各/r 具/Vg 优势/n ，/w 有/v 着/u 很/d 强/a 的/u 互补性/n 。/w 过去/t 几/m 年/q 里/f ，/w 两/m 国/n 贸易/v 发展/v 迅速/a ，/w 双边/n 贸易额/n １９９１年/t 只/d 有/v １４００万/m 美元/q ，/w １９９６年/t 就/d 剧增/v 到/v １３·４亿/m 美元/q ，/w 今年/t 双边/n 贸易额/n 则/d 可望/v 达到/v １６亿/m 美元/q 。/w 中华人民共和国/ns 在/p 南非/ns 的/u 投资/n 近/a 几/m 年/q 增长/vn 势头/n 强劲/a ，/w 在/p 南非/ns 已/d 建立/v 了/u 数十/m 家/q 独资/b 、/w 合资企业/n ，/w 双方/n 最/d 大/a 的/u 合作/vn 项目/n ———/w 北方/s 省/n 的/u 铬铁矿/n 企业/n 在/p 短/a 时间/n 内/f 就/d 开始/v 运作/v ，/w 仅/d 这/r 一/m 项目/n 投资/n 就/d 逾/Vg ７０００万/m 美元/q 。/w ”/w +19980101-03-003-006/m 钱/nr 其琛/nr 还/d 指出/v ：/w “/w 南非/ns 企业/n 也/d 已/d 将/p 目光/n 瞄准/v 了/u 中国/ns 市场/n 。/w 南非/ns 与/p [中国/ns 香港/ns 特别/a 行政区/n]ns 之间/f 更是/d 有/v 着/u 重要/a 的/u 经贸/j 、/w 金融/n 和/c 航空/n 联系/vn 。/w 中国/ns 香港/ns 同/p 南非/ns 之间/f 的/u 贸易额/n 已/d 达到/v １３亿/m 美元/q 。/w ”/w “/w 我们/r 有/v 理由/n 相信/v ，/w 两/m 国/n 关系/n 正常化/v 后/f ，/w 中国/ns 南非/ns 一定/d 会/v 成为/v 越来越/d 重要/a 的/u 经贸/j 合作/vn 伙伴/n 。/w ”/w +19980101-03-003-007/m 钱/nr 其琛/nr 在/p 谈/v 到/v 两/m 国/n 在/p 国际/n 问题/n 上/f 的/u 合作/vn 前景/n 时/Ng 说/v ：/w “/w 中国/ns 南非/ns 同/d 属/v 发展中国家/l ，/w 又/d 分别/d 是/v 亚洲/ns 和/c 非洲/ns 有/v 影响/vn 的/u 大国/n ，/w 我们/r 在/p 许多/m 重大/a 国际/n 问题/n 上/f 有/v 共同语言/n ，/w 两/m 国/n 建交/v 后/f 将/d 更加/d 密切/v 两/m 国/n 在/p 国际/n 事务/n 中/f 的/u 磋商/vn 与/c 合作/vn ，/w 在/p 国际/n 和/c 地区/n 事务/n 中/f 发挥/v 更/d 大/a 的/u 作用/n ，/w 共同/d 维护/v 发展中国家/l 的/u 权益/n ，/w 促进/v 人类/n 和平/n 与/c 发展/vn 事业/n 。/w ”/w +19980101-03-003-008/m 恩佐/nr 在/p 讲话/n 中/f 说/v ：/w “/w 一个/m 非洲/ns 大国/n 与/c 一个/m 亚洲/ns 乃至/c 世界/n 大国/n 没有/v 正式/a 关系/n ，/w 这样/r 的/u 情况/n 继续/v 下去/v 将/d 是/v 毫无道理/l 的/u 。/w ”/w +19980101-03-003-009/m 他/r 指出/v ，/w 南非/ns 和/c 中国/ns 如果/c 迟迟/d 不/d 能/v 建立/v 外交/n 关系/n ，/w “/w 不/d 符合/v 联合国/nt 和/c [非洲/ns 统一/vn 组织/n]nt 等/u 国际/n 组织/n 的/u 原则/n ，/w 不/d 符合/v 国际法/n 和/c 世界/n 上/f 绝大多数/m 国家/n 遵从/v 的/u 惯例/n 。/w ”/w “/w 这种/r 状况/n 也/d 是/v 与/p 非洲/ns 国家/n １９７１年/t 支持/v 恢复/v 中国/ns 在/p 联合国/nt 的/u 合法/a 席位/n 过程/n 中/f 所/u 起/v 的/u 决定性/n 作用/n 背道而驰/i 的/u 。/w ”/w 他/r 说/v ，/w 要不是/c 受/v 种族/n 隔离/vn 制度/n 的/u 影响/vn ，/w 南非/ns 同/p 中国/ns 建交/v 早已/d 实现/v 。/w +19980101-03-003-010/m 恩佐/nr 说/v ，/w 南非/ns 同/p 中国/ns 建交/v 是/v 两/m 国/n ３００/m 多/m 年/q 交往/v 的/u 自然/a 结果/n 。/w 他/r 说/v ，/w 中国/ns 与/c 非洲/ns 的/u 牢固/a 关系/n 在/p 很/d 大/a 程度/n 上/f 是/v 建立/v 在/p 共同/b 的/u 历史/n 遭遇/vn 基础/n 上/f 的/u 。/w 中国/ns 人民/n 和/c 非洲/ns 人民/n 都/d 遭受/v 过/u 殖民主义/n 的/u 欺凌/vn 。/w 他/r 说/v ，/w 在/p 种族/n 隔离/vn 制度/n 被/p 废除/v 以前/f ，/w 在/p 南非/ns 的/u 中国/ns 侨民/n 同/p 当地/s 广大/b 黑人/n 一样/u 长期/d 遭受/v 种族/n 隔离/vn 的/u 摧残/vn ，/w 但/c 他们/r 同时/d 也/d 顽强/a 地/u 保持/v 了/u 自己/r 的/u 文化/n 传统/n ，/w 为/p 南非/ns “/w 彩虹/n 花园/n 之/u 国/n ”/w 的/u 文化/n 多样性/n 作出/v 了/u 巨大/a 贡献/vn 。/w +19980101-03-003-011/m 恩佐/nr 强调/v ，/w １９４９年/t 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+19980101-07-009-026/m 鸣/Vg 亮/a 白昼/n +19980101-07-009-027/m 也/d 消失/v 夜晚/t +19980101-07-009-028/m 让/v 我们/r 的/u 手心/n +19980101-07-009-029/m 攥/v 满/a 工作/vn +19980101-07-009-030/m 不/d 能/v 懈怠/a +19980101-07-009-031/m 以/p 成功/a 和/c 喜悦/a +19980101-07-009-032/m 献给/v 新/a 的/u 节日/n +19980101-07-009-033/m 庆祝/v 我们/r 新/a 的/u 辉煌/an +19980101-07-010-001/m 国泰民安/i （/w 篆刻/n ）/w +19980101-07-010-002/m （/w 陈/nr 少华/nr ）/w \ No newline at end of file From e4afac8e6b46bdfd06aef820a27438525c8d5b20 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Mon, 27 Nov 2017 20:24:16 +0800 Subject: [PATCH 28/30] =?UTF-8?q?Delete=20python=E6=AD=A3=E5=88=99?= =?UTF-8?q?=E8=A1=A8=E8=BE=BE=E5=BC=8F=E5=9F=BA=E7=A1=80=E5=BF=AB=E9=80=9F?= =?UTF-8?q?=E6=95=99=E7=A8=8B.ipynb?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...351\200\237\346\225\231\347\250\213.ipynb" | 1045 ----------------- 1 file changed, 1045 deletions(-) delete mode 100644 "chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217\345\237\272\347\241\200\345\277\253\351\200\237\346\225\231\347\250\213.ipynb" diff --git "a/chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217\345\237\272\347\241\200\345\277\253\351\200\237\346\225\231\347\250\213.ipynb" "b/chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217\345\237\272\347\241\200\345\277\253\351\200\237\346\225\231\347\250\213.ipynb" deleted file mode 100644 index ad37fbf0f..000000000 --- "a/chapter3/python\346\255\243\345\210\231\350\241\250\350\276\276\345\274\217\345\237\272\347\241\200\345\277\253\351\200\237\346\225\231\347\250\213.ipynb" +++ /dev/null @@ -1,1045 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# python正则表达式基础快速教程\n", - "### By liupengyuan@pku.edu.cn\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "正则表达式，这个术语不太容易望文生义(没有去考证是如何被翻译为正则表达式的)，其实其英文为Regular Expression，直接翻译就是：有规律的表达式。这个表达式其实就是一个字符序列，反映某种字符规律，用(字符串模式匹配)来处理字符串。很多高级语言均支持利用正则表达式对字符串进行处理的操作。\n", - "\n", - "python提供的正则表达式文档可参见：https://docs.python.org/3/library/re.html" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true, - "scrolled": true - }, - "outputs": [], - "source": [ - "import re" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 首先引入python正则表达式库re" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**1. 入门**" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": true, - "scrolled": true - }, - "outputs": [], - "source": [ - "s = 'Blow low, follow in of which low. lower, lmoww oow aow bow cow 23742937 dow kdiieur998.'\n", - "p = 'low'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 假设要在字符串s中查找单词`low`，由于该单词的规律就是`low`，因此可将`low`作为一个正则表达式，可命名为`p`。" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['low', 'low', 'low', 'low', 'low']" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = re.findall(p, s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- `findall(pattern, string)`是re模块中的函数，会在字符串`string`中将所有匹配正则表达式`pattern`模式的字符串提取出来，并以一个`list`的形式返回。该方法是从左到右进行扫描，所返回的`list`中的每个匹配按照从左到右匹配的顺序进行存放。\n", - "- 正则表达式`low`能够将所有单词`low`匹配出来，但是也会将`lower`，`Blow`等含有`low`字符串中的`low`也匹配出来。" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['low', 'low']" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = r'\\blow\\b'\n", - "m = re.findall(p, s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- `\\b`，即`boundary`，是正则表达式中的一种特殊字符，表示单词的边界。正则表达式`r'\\blow\\b'`就是要单独匹配`low`，该字符串两侧为单词的边界(边界为空格等，但是并不是要匹配之)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['low', 'low', 'low', 'low', 'low', 'mow', 'oow']" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = r'[lmo]ow'\n", - "m = re.findall(p, s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- `[lmo]`，匹配`lmo`字母中的任何一个" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['aow', 'bow', 'cow', 'dow']" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = r'[a-d]ow'\n", - "m = re.findall(p, s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- `[a-d]`，匹配`abcd`字母中的任何一个" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['2', '3', '7', '4', '2', '9', '3', '7', '9', '9', '8']" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = r'\\d'\n", - "m = re.findall(p, s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- `\\d`，即digit，表示数字" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['23742937', '998']" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = r'\\d+'\n", - "m = re.findall(p, s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- `+`，元字符，表示一个或者重复多个对象，对象为`+`前面指定的模式\n", - "- 因此`\\d+`可以匹配长度至少为1的任意正整数。" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**2. 基本匹配与实例**" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "字符模式|匹配模式内容|等价于\n", - "----|---|--\n", - "[a-d]|One character of: a, b, c, d|[abcd]\n", - "[^a-d]|One character except: a, b, c, d|[^abcd]\n", - "abc丨def|abc or def|\n", - "\\d|One digit|[0-9]\n", - "\\D|One non-digit|[^0-9]\n", - "\\s|One whitespace|[ \\t\\n\\r\\f\\v]\n", - "\\S|One non-whitespace|[^ \\t\\n\\r\\f\\v]\n", - "\\w|One word character|[a-zA-Z0-9_]\n", - "\\W|One non-word character|[^a-zA-Z0-9_]\n", - ".|Any character (except newline)|[^\\n]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "固定点标记|匹配模式内容\n", - "----|---\n", - "^|Start of the string\n", - "$|End of the string\n", - "\\b|Boundary between word and non-word characters" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "数量词|匹配模式内容\n", - "----|---\n", - "{5}|Match expression exactly 5 times\n", - "{2,5}|Match expression 2 to 5 times\n", - "{2,}|Match expression 2 or more times\n", - "{,5}|Match expression 0 to 5 times\n", - "*|Match expression 0 or more times\n", - "{,}|Match expression 0 or more times\n", - "?|Match expression 0 or 1 times\n", - "{0,1}|Match expression 0 or 1 times\n", - "+|Match expression 1 or more times\n", - "{1,}|Match expression 1 or more times" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "字符转义|转义匹配内容\n", - "----|---\n", - "\\\\.|. character\n", - "\\\\\\|\\ character\n", - "\\\\*|* character\n", - "\\\\+|+ character\n", - "\\\\?|? character\n", - "\\\\{|{ character\n", - "\\\\)|) character\n", - "\\\\[|[ character" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['010-66677788', '02166697788', '0451-22882828']" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = re.findall(r'\\d{3,4}-?\\d{8}', '010-66677788,02166697788, 0451-22882828')\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 匹配电话号码，区号可以是3或者4位，号码为8位，中间可以有`-`或者没有。" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['测', '试', '汉', '字', '测', '试', '可', '以']" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = re.findall(r'[\\u4e00-\\u9fa5]', '测试 汉 字，abc，测试xia，可以')\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 匹配汉字" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 几个实例\n", - "\n", - "正则表达式|匹配内容\n", - "----|---\n", - "[A-Za-z0-9]|匹配英文和数字\n", - "[\\u4E00-\\u9FA5A-Za-z0-9_]|中文英文和数字及下划线\n", - "^[a-zA-Z][a-zA-Z0-9_]{4,15}$`|合法账号，长度在5-16个字符之间，只能用字母数字下划线，且第一个位置必须为字母" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**3. 进阶**" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**3.1 python正则表达式几个函数**\n", - "\n", - "函数|功能|用法\n", - "----|---|---\n", - "re.search|Return a match object if pattern found in string|re.search(r'[pat]tern', 'string')\n", - "re.finditer|Return an iterable of match objects (one for each match)|re.finditer(r'[pat]tern', 'string')\n", - "re.findall|Return a list of all matched strings (different when capture groups)|re.findall(r'[pat]tern', 'string')\n", - "re.split|Split string by regex delimeter & return string list|re.split(r'[ -]', 'st-ri ng')\n", - "re.compile|Compile a regular expression pattern for later use|re.compile(r'[pat]tern')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "<_sre.SRE_Match object; span=(0, 12), match='010-66677788'>" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = re.search(r'\\d{3,4}-?\\d{8}', '010-66677788,02166697788, 0451-22882828')\n", - "m" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'010-66677788'" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m.group()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 利用group()函数，取出match对象中的内容" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "010-66677788\n", - "02166697788\n", - "0451-22882828\n" - ] - } - ], - "source": [ - "ms = re.finditer(r'\\d{3,4}-?\\d{8}', '010-66677788,02166697788, 0451-22882828')\n", - "for m in ms:\n", - " print(m.group())" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['010', '66677788', '02166697788', '0451', '22882828']" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "words = re.split(r'[,-]', '010-66677788,02166697788,0451-22882828')\n", - "words" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['010', '66677788', '02166697788', '0451', '22882828']" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = re.compile(r'[,-]')\n", - "p.split('010-66677788,02166697788,0451-22882828')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 利用compile()函数将正则表达式编译，如以后多次运行，可加快程序运行速度" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**3.2 分组与引用**\n", - "\n", - "Group Type|Expression\n", - "----|---\n", - "Capturing|**(** ... **)**\n", - "Non-capturing|**(?:** ... **)**\n", - "Capturing group named Y|**(?P<Y>** ... **)**\n", - "Match the Y'th captured group|\\Y\n", - "Match the named group Y|(?P=Y)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- (...) 将括号中的部分，放在一起，视为一组，即group。以该group来匹配符合条件的字符串。\n", - "- group，可被同一正则表达式的后续，所引用，引用可以利用其位置，或者利用其名称，可称为反向引用。" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'ababababab'" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = re.compile('(ab)+')\n", - "p.search('ababababab').group()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "('ab',)" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p.search('ababababab').groups()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 有分组的情况，用groups()函数取出匹配的所有分组" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'1-2-3'" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p=re.compile('(\\d)-(\\d)-(\\d)')\n", - "p.search('1-2-3').group()" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "('1', '2', '3')" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p.search('1-2-3').groups()" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['眼睛', '深情']" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s = '喜欢/v 你/x 的/u 眼睛/n 和/u 深情/n 。/w'\n", - "p = re.compile(r'(\\S+)/n')\n", - "m = p.findall(s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 按出现顺序捕获名词(/n)。" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'1-2-3'" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p=re.compile('(?P\\d)-(\\d)-(\\d)')\n", - "p.search('1-2-3').group()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 在分组内，可通过`?P`的形式，给该分组命名，其中name是给该分组的命名" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'1'" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p.search('1-2-3').group('first')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 可利用`group('name')`，直接通过组名来获取匹配的该分组" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "[('13', 'Tom'), ('18', 'John')]" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s = 'age:13,name:Tom;age:18,name:John'\n", - "p = re.compile(r'age:(\\d+),name:(\\w+)')\n", - "m = p.findall(s)\n", - "m" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['Tom', 'John']" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = re.compile(r'age:(?:\\d+),name:(\\w+)')\n", - "m = p.findall(s)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- `(?:\\d+)`，匹配该模式，但不捕获该分组。因此没有捕获该分组的数字" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The match is bb,the capture group is ('b',)\n" - ] - } - ], - "source": [ - "s = 'abcdebbcde'\n", - "p = re.compile(r'([ab])\\1')\n", - "m = p.search(s)\n", - "print('The match is {},the capture group is {}'.format(m.group(), m.groups()))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "- 此即为反向引用\n", - "- 当分组`([ab])`内的`a`或`b`匹配成功后，将开始匹配`\\1`，`\\1`将匹配前面分组成功的字符。因此该正则表达式将匹配`aa`或`bb`。\n", - "- 类似地，r'([a-z])\\1{3}'，该正则将匹配连续的4个英文小写字母。" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'12'" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s = '12,56,89,123,56,98, 12'\n", - "p = re.compile(r'\\b(\\d+)\\b.*\\b\\1\\b')\n", - "m = p.search(s)\n", - "m.group(1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 利用反向引用来判断是否含有重复数字，可提取第一个重复的数字。\n", - "- 其中`\\1`是引用前一个分组的匹配。" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'12'" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s = '12,56,89,123,56,98, 12'\n", - "p = re.compile(r'\\b(?P\\d+)\\b.*\\b(?P=name)\\b')\n", - "m = p.search(s)\n", - "m.group(1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 与前一个类似，但是利用了带分组名称的反向引用。" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**3.3 贪婪与懒惰**" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "数量词|匹配模式内容\n", - "----|---\n", - "{2,5}?|Match 2 to 5 times (less preferred)\n", - "{2,}?|Match 2 or more times (less preferred)\n", - "{,5}?|Match 0 to 5 times (less preferred)\n", - "*?|Match 0 or more times (less preferred)\n", - "{,}?|Match 0 or more times (less preferred)\n", - "??|Match 0 or 1 times (less preferred)\n", - "{0,1}?|Match 0 or 1 times (less preferred)\n", - "+?|Match 1 or more times (less preferred)\n", - "{1,}?|Match 1 or more times (less preferred)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- 当正则表达式中包含能接受重复的限定符时，通常的行为是（在使整个表达式能得到匹配的前提下）匹配尽可能多的字符。\n", - "- 而懒惰匹配，是匹配尽可能少的字符。方法是在重复的后面加一个`?`。" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'ababababab'" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = re.compile('(ab)+')\n", - "p.search('ababababab').group()" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'ab'" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "p = re.compile('(ab)+?')\n", - "p.search('ababababab').group()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**进一步学习可参考官方文档以及《精通正则表达式(第3版)》**" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} From bfc8937f39ebb15daac42563bb89380b49e7ccce Mon Sep 17 00:00:00 2001 From: maluyaoMoMo <32284032+maluyaoMoMo@users.noreply.github.com> Date: Sun, 10 Dec 2017 16:21:19 +0800 Subject: [PATCH 29/30] =?UTF-8?q?Create=20=E5=9F=BA=E4=BA=8E=E7=94=B5?= =?UTF-8?q?=E5=BD=B1=E8=AF=84=E5=88=86=E7=9A=84=E5=8F=AF=E8=A7=86=E5=8C=96?= =?UTF-8?q?=E5=88=86=E6=9E=90?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...\345\217\257\350\247\206\345\214\226\345\210\206\346\236\220" | 1 + 1 file changed, 1 insertion(+) create mode 100644 "chapter4/project_list/\345\237\272\344\272\216\347\224\265\345\275\261\350\257\204\345\210\206\347\232\204\345\217\257\350\247\206\345\214\226\345\210\206\346\236\220" diff --git "a/chapter4/project_list/\345\237\272\344\272\216\347\224\265\345\275\261\350\257\204\345\210\206\347\232\204\345\217\257\350\247\206\345\214\226\345\210\206\346\236\220" "b/chapter4/project_list/\345\237\272\344\272\216\347\224\265\345\275\261\350\257\204\345\210\206\347\232\204\345\217\257\350\247\206\345\214\226\345\210\206\346\236\220" new file mode 100644 index 000000000..aaea0129f --- /dev/null +++ "b/chapter4/project_list/\345\237\272\344\272\216\347\224\265\345\275\261\350\257\204\345\210\206\347\232\204\345\217\257\350\247\206\345\214\226\345\210\206\346\236\220" @@ -0,0 +1 @@ +creat From 1ebb44320fe9192d6dcf0ad3ced1af34bd760393 Mon Sep 17 00:00:00 2001 From: liupengyuan Date: Tue, 12 Dec 2017 20:48:18 +0800 Subject: [PATCH 30/30] Update 8.md --- chapter2/8.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/chapter2/8.md b/chapter2/8.md index 258d32214..74cd1b95c 100644 --- a/chapter2/8.md +++ b/chapter2/8.md @@ -337,9 +337,9 @@ for guess in guesses: ```python # 点字成诗机器人 -def find_poem_sentence(poems, characters): - same_character_number = 0 +def find_poem_sentence(poems, characters): for poem in poems: + same_character_number = 0 for ch in poem: if ch in characters: same_character_number += 1

  • \n", + "yyyyyyyyy\n", + "::after\n", + "