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"It 's a flying bee, Wings are particularly numerous, He was covered in yellow and black, It is the way yellow and black are arranged in such a way. One by one is as big as a slap with an open hand. As soon as it flies, it is a large area. There is a poisonous needle behind the belly, It stings people, One can kill you, My comrades around me, Because there are no fewer than five sacrifices, I remember when the battle was coming to an end, I helped a comrade-in-arms who was stung to squeeze poison out, To squeeze, The wound, which was almost the size of a grain of rice, gushed out a pale yellow 'water', Sprayed directly on my neck, At that time, I felt that my neck was burning, then I felt pain first, then numbness. At the most numbness, my whole head lost consciousness. My neck drooped down and my comrades washed the spilled place several times with river water. It took me a long time to recover. I thought that it was the same when I sprayed it on my body. If I stung it directly into my body, I would basically not live. " Zhang Xiaobo pointed to his neck as he said.清朝，顺治年间。“荆州之役”改变了新月格格的命运，除了克善以外，她在一夜间失去了所有亲人，只剩两个忠心的仆人，云娃和莽古泰。他们逃难途中，新月被人掳去，幸得那让敌人闻名丧胆，绰号“马鹞子”的大将军努达海所救。“荆州之役”平定后，努达海护送新月等人回京，一路上努达海用心的想抚平新月的丧亲之痛，他和新月之间有一份特别的感情在滋长。回京后，新月和克善等住进了努达海的家。努达海的妻子雁姬、儿子骥远和女儿珞琳都十分欢迎新月他们。珞琳多了个年龄相仿的好姐妹，骥远心里更是爱慕着柔情似水的新月。但此时，努达海发现自己对新月的感情已超越了父女的感情，为了逃避这份情感，努达海自动请缨到巫山打仗。电影《故事贩卖机》由四个独立的城市怪谈故事单元组成，其中《鬼打墙》恐怖惊悚，引人尖叫的同时吸引力十足;《官能许愿》则讲述了以失去器官为代价获得超能力的城市穿越爱情故事;《鸡汤泡面》则赋予了普通泡面迷幻剂一般的神奇力量，荒诞的同时又笑料百出;此外，中国著名童话“皮皮鲁与鲁西西”系列也将选择代表故事在电影中重磅呈现。"It's coming! Huawei 5G mobile phone! The reporter measured the download speed. Who is in charge of ups and downs in 5G era?" On the afternoon of 26th, Huawei released its first 5G mobile phone in the Chinese market! How fast is 5G mobile phone? What changes can it bring to our life? (CCTV Finance and Economics)武馆女掌门黄小鱼作误闯娱乐圈，意外成为当红明星袁帆的贴身保镖，正式开始甜喜过招的同居生活。黄小鱼也向袁帆坦白了自己被大热武侠游戏《新斗罗大陆》NPC附身的秘密，开启了一段游戏和现实双线开恋的高甜时光。From the defender's point of view, this type of attack has proved (so far) to be very problematic, because we do not have effective methods to defend against this type of attack. Fundamentally speaking, we do not have an effective way for DNN to produce good output for all inputs. It is very difficult for them to do so, because DNN performs nonlinear/nonconvex optimization in a very large space, and we have not taught them to learn generalized high-level representations. You can read Ian and Nicolas's in-depth articles (http://www.cleverhans.io/security/privacy/ml/2017/02/15/why-attaching-machine-learning-is-easier-than-defending-it.html) to learn more about this.