Responsibility chain mode:
《我在故宫修文物》是一部拍摄故宫稀世文物修复故事的纪录片，近距离展示稀世珍宝的“复活”技术，文物修复师的日常生活与修身哲学 。
周篁呵呵笑道：那我让人叫她吧。
讲述了毫无灵力却元气满满的废柴女路卿卿与表面纨绔却睿智暖心的傲娇王爷南宫一昕的故事。
[Traffic] Bus routes: No.1, No.12, No.15, No.18, No.2, No.28, No.30, No.33, No.39, No.40, No.46, No.7, No.9.
1. Download a Google Earth software and enter Google Earth.
一天陈清告诉周渔，说他要去边疆支教。这一决定最终成全了周渔和张强，还是让周渔看清了该如何决断？
李昇基饰演正直的年轻刑警，面对不公正的事就据理力争，将与让全国陷入恐怖的先天精神病患的罪犯对峙，完全改变自己人生的角色。
骤然涌来这么多人口，哪里能够从容应对。
一番喧闹吵嚷后，老老小小都从各屋涌了出来。
而在这时，一个更大的变故产生。苹果怀孕了，而到底谁才是这个孩子的父亲成了林东与安坤赌博的筹码，四人签订协议，如果是林东的骨肉，他将给二人十二万元的补偿费，而如果是安坤的，则双方互不相欠......
东北老汉赵本山因为女儿闹离婚痛失爱孙，只得假扮保姆混入女婿家，不料却引来亲家爷郭达和邻居老头的爱慕和追求，这个荒唐的局面让人忍俊不禁，而赵本山的老太太装扮更让人捧腹，当他忸怩作态时连剧组人员也认他不出。
被导演赶走，青年也没有多失落，这里是哪里？这里可是横河影视城。
13. Encourage employees to make more correct suggestions and plans. The Company will pay full attention to them. Those who formally resume and adopt written suggestions will be given certain rewards to encourage employees to actively participate in the Company's management and enhance their sense of ownership.
有趣，有趣。
说完三口两口，简直像没长喉咙般，飞快地将一碗饭给吞了，也不知是他没吃到石头呢，还是连石头都吞下去了。
宋运辉（王凯饰）天资聪颖，却出身不好，一直倍受歧视，但是他把握住了1978年恢复高考的机会，抓住机遇，勤学苦干，当上了国企的技术人员，一步步晋升，奠定了成功人生的基础，但也在新时代的变革中逐渐迷失。与宋运辉不同的是他的姐夫雷东宝（杨烁饰）。他出身贫寒、属于苗正根红的“大老粗”，行动力十足。在乡村改革的浪潮中带领村民紧跟政策，一直走在时代的前沿。但由于自身文化水平不高，眼界不够开阔，最终绊倒在新事物脚下。如果说宋运辉和雷东宝的经历是国营经济和集体经济的缩影。那么个体户杨巡（董子健饰）无疑就是个体经济的典型代表，在翻滚向前的时代中，他手忙脚乱抓住过商机，也踩踏过陷阱，生意场上几经波折，最终拥有了自己的产业，成为了那个时代个体经济的典型代表。
Sorry to force a wave of chicken soup. Originally, I planned to write a machine learning series last year, but after writing three articles for work and physical reasons, there was no more. In the first half of this year, I was tired to death after doing a big project. In the second half of this year, I just took a breath of relief, so the follow-up that I owed before will definitely continue to be even more. In order not to let everyone worship blindly, I decided to write a series of in-depth study, one article per week, which will end in about three months. Teach Xiaobai how to get started. And finished! All! No! Fei! ! It is not simply to write demo and tuning parameters that are available on the Internet. Reject demo, start with me! If you don't understand, please leave a message under my article. I will try my best to reply when I see it. This series will mainly adopt the in-depth learning framework of PaddlaPaddle, and will compare the advantages and disadvantages of Keras, TensorFlow and MXNET (because I have only used these four frameworks, there are too many people writing TensorFlow, and I am using PaddlePaddle well at present, so I decided to start with this). All codes will be put on github (link: https://github.com/huxiaoman7/PaddlePaddle_code). Welcome to mention issue and star. At present, only the first article () has been written, and there will be more in-depth explanation and code later. At present, I have made a simple outline. If you are interested in the direction, you can leave me a message, and I will refer to the addition ~
一名中年男子与一只狗的遗体，被人在深山中的一辆汽车内发现。该男子已死亡半年，而狗却是在一个月前毕命的。这究竟是怎么回事？另外，死者身份无法确认，市政府福利科的一位青年开始调查此案。
