Compared with chasing far away, being cautious about the end may be of more practical significance.
不过，我们家不像在清南村的时候了。
大苞谷愣了一下，才嘀咕道：不就是烧了一片山嘛，这荒郊野外又没人……看着那满山沸腾的火焰，又有些心虚。
Mkproject mic: create mic projects and operating environments mic
Difference
红椒在旁听了半天，心中早就愤愤，不禁问道：可是那老婆子要卖了招弟咋办？娘——郑氏淡淡问道：咋了？你想把她买回来？红椒见娘脸色不好，瑟缩了一下，低头不敢再吭声。
而丈母娘游萍(白冰冰饰)见状，便趁此机会要求殷雄要负起照顾母女之责任，并且百般纠缠殷雄，殷雄如何躲避都终将逃不了母女俩的手掌心。
徐文长十分确定，他是真的疯了。
Its specific UML structure diagram is as follows:
买房子铺面？陈老爷疑惑地问，咱们要在京城做生意？这主意好是好，可如今你这事儿这么麻烦，哪还有心思张罗生意？还是不要费心了。
一代大侠李寻欢（关礼杰）身怀绝技，豪爽慷慨。但一生为情所困，不能自拔。深爱林诗音（关宝慧），却拱手相让予义兄龙啸云（陈捷文），自己终生抱撼。李寻欢淡薄名利，虽出身三代探花，却弃功名、散家财，自我放逐。惟人在江湖，身不由己，屡被卷入江湖旋涡，与义兄云反目成仇。云之子龙天赐（邓兆尊）更誓将他置诸死地。欢一生为情为义，无奈往往遭人误解，含冤莫解，为千夫所指，只叹命运不得我挑选。
The second season of "Charming China City" has been upgraded completely, "Charming China City? The establishment of the" City Alliance "and the official launch of the" Charming Card "program mean that there is a broad prospect for the deep integration of culture and tourism, and the sustainable development of the city will also usher in a new breakthrough. CCTV's combination of boxing to help the poor through tourism shows the sense of responsibility and mission of the national big station.
烧锅屯的村民连续十年拖欠国家税款，而且拒绝干部进村，村民在村头挂了一口钟，每当上级派干部来，钟声便响起，村民闻声而动，阻拦干部进村……
30. It is suggested that the company organize some middle-level managers to expand their training in the next step, change their ideas, develop their ideas and improve their management ability. (urgent)
霍元甲进入天津城后，开始接触进步思想，认识到民族存亡是大事，继续惩恶扬善，消灭海匪，挫败日本人的阴谋，整合津门的门派之争，救护抗击八国联军的英雄，打败俄罗斯大力士，成为津门爱国义士的一面旗帜。
希芭·哈特(凯特·布兰切特)是学校里新来的美术老师，她年轻美丽，气质高雅。老教师芭芭拉(朱迪·丹奇)悄悄的关注起希芭，并渐渐和希芭结成好友。希芭把芭芭拉当成密友，向她倾诉年迈丈夫的无趣，女儿的叛逆和儿子的低能。两个女人结为看起来温馨又和谐的忘年之交。
好事成双，所有的战略目标全部达成了，卢绾也被剿灭，一万多汉军全军覆没。
抗战时期的上海，进步女青年韩疏影被婶婶陷害，被迫嫁给苏北大亨谢丙炎做妾室。在爱国教师历文轩的感召下，韩疏影决定逃婚投入救国行列，却因和谢家大少爷谢天赐的同学关系，被谢家大小姐谢若雪发现。飞扬跋扈的谢若雪不仅向父亲告发，还把韩疏影的‘逃婚’演绎成“私奔”，妄图置韩疏影这个“后妈”于死地。正当韩疏影命悬一线之际，谢丙炎因不愿出卖祖国被日本人枪杀。目睹一切的韩疏影深深被谢丙炎的爱国气节感动，毅然选择留在谢家，以谢夫人的名义保全了谢家老小，并在历文轩的帮助下，带着谢若雪逃到上海，用实际行动感动了谢若雪。在金戈铁马的时代背景下，韩疏影和谢若雪这两个女人不仅以“母女”的身份相依为命，也以“姐妹”的身份演绎了一段抗战救国的传奇
Use reasonable data sampling: It is necessary to ensure that a small number of entities (including IP or users) cannot account for most of the model training data. In particular, care should be taken not to pay too much attention to false positives and false negatives reported by users. This may be achieved by limiting the number of examples that each user can contribute or using attenuation weights based on the number of reported examples.
