It is very important for the selection of plants. Some plants have good stability and high color fastness, such as Dioscorea cirrhosa, persimmon, betel nut, turmeric, etc. Personal experience is that the stability of gardenia is not so good, and the color is easy to fade when washed too much. For reference only. In dyeing, try to choose some plants with good stability to dye, or carry out re-dyeing, which can stabilize the color fastness. For example, we use onion skin to cover with blue dye, and persimmons have higher color fastness after covering with blue dye, and basically will not fade. Of course, according to their own needs of color and luster, other cover dyeing can also be tried.
过去的一场意外，让年幼的慈惠被吴父照顾至今，为了报达养育之恩，在吴父罹患肺癌晚期的同时，慈惠痛心舍弃了恋人天云，决定嫁给了吴家独子家栋，而这桩看似幸福的婚事，竟为她的人生带来剧烈的变化。吴母一直对慈惠怀有偏见，加上一心想当吴家少奶奶的玉琴总是在一旁搧风点火，让吴母对慈惠总是没有好脸色，误会连连，甚至趁着家栋不在吴家期间，两人联手欺骗慈惠，说慈惠生下死胎，慈惠震惊而精神崩溃。充满愧疚痛苦的慈惠黯然离开吴家，本想求死，却在无意间被海生给救了回来，从此在一个小渔村定居。而玉琴虽然得逞，但家栋却因为慈惠的离去伤心欲绝不想再婚，而家栋一场意外瘫痪，又让玉琴毅然离开吴家，从此各自分散。时光匆匆流逝，二十年后，缘分又把他们都重新绑在一起。
高智慧球ZI濒临毁灭，居民逃离了自己的家园，奔向地球。在旅途中内战爆发，宇宙船坠毁在地球上，索斯机兽散落在地球的各个角落，危害人间。拥有机兽手臂的少年雷欧遇见了握有神秘力量的少女纱丽，带着机兽伙伴狮牙猛虎踏上拯救地球的征途。
万金集团总裁段苏洋遭遇袭击，身旁的保镖不堪一击，危机时刻女秘书叶雨晴挺身而出。经过一番激战，叶雨晴带着段苏洋突出重围，却不料遭到黑玫瑰伏击，叶雨晴身受重伤，她嘱咐段苏洋找到风依雪。逃出生天的段苏洋惊魂未定，他问安保队长王金龙谁是风依雪，王金龙告诉他，风依雪是退役的第一女保镖，隐居民间多年，行踪诡异，一般人很难找到她，正当两人无计可施时，一个妙龄女孩找上门来自称是风依雪。与此同时各路势力粉墨登场，开启了对风依雪和段苏洋的围剿。
一座充满梦想机遇的公寓，六位青春个性的怪咖，机缘巧合之下，六位帝欢聚在一起，从此瞬息万变，玩转创业江湖，或温情或爆笑，或神机妙算或脑洞大开，一个个百转千回的励志故事轮番上演，在这个秋季陪你狂玩到底
CAST方面，饰演茂野大吾的藤原夏海、饰演佐仓睦子的花泽香菜将继续出演。风林中学棒球部的成员，成为大吾后辈的仁科明一役由山下大辉出演了。此外，导演渡边步、动画制作オー・エル・エム也将继续参加制作。
最后在FBI探员的帮助下，詹妮弗成功地逃脱了昏迷杀手的大脑，同时她也获知了最后幸存女孩的下落。他们找到那个女孩并将变态杀手绳之于法。
不想主外，想在家做针线带娃吧？那可不成。
尹旭坐在石台上，也有些惊讶，没想到绿萝竟然有这样的准备。
同时尹旭也感叹，这自然是多么的纯净美好，不曾有过一丁点的破话。
光绪二十四年，戊戌变法失败，皇帝被囚，朝野上下一片混乱，不成气的刽子手孟小山巧遇江湖女儿柳青青，两人冤家路窄，却棒打不散，妓院春风楼内，大太监李莲英出宫密谋，不巧被孟柳二人撞上，李莲英暗藏鬼胎，收两人作心腹，冒充太监入宫，唯有任性妄为的多罗格格不知天高地厚，却又至情至性，孟小山精灵古怪，在各种关系中游刃有余，更令多罗格格由恨生爱，对其百依百顺，言听计从，被青青曾受护军统领唐啸天救命之恩，对其暗生情愫，得知唐啸天潜伏宫中准备营救皇上，决心冒死相助。孟小山财迷心窍，一心偷宝求财，无奈柳青青连求带逼，只得同意救驾，几个平凡的小人物一跃成为宫廷纷争的焦点，他们巧妙利用大总管，二总管及大格格之间复杂的关系，相互制约，开始进行救驾的计划，宫廷纷争风云变幻，几个屡历险境，躲过了一次又一次的杀身之祸。然而就在救驾计划最关键的时刻，孟小山和柳青青身份败露..
扮演主人公天下一的就是首次主演连续剧的松田翔太，他曾经凭借不少电影作品捧走许多新人大奖，在年轻一代演员中拥有很强的实力，今次则是他第一次挑战演出一名侦探。
可越拖，就越难啃。
斯卡姆正在翻拍一部法国电影。拍摄从9月25日开始，我们将有四个赛季。萨娜现在被称为伊玛尼（17-20岁，中东和北非或非洲，必须说阿拉伯语）：她自信，强大，有保护性，非常成熟。
Arts and Sports Candidates Fill in Arts and Sports Books and Specialist Volunteers
At this time, the actual person in charge of Zhongren Wealth has already hid himself. What about my communication with Daihei:
Tang Lin, producer of CCTV's financial channel "Charming China City", Reveals Innovative Highlights of the Second Season's Purpose: First, the timing of the second season of the program is better than that of the first season. The 19th National Congress and the National Two Sessions have been held one after another. At the same time, the 40th anniversary of reform and opening-up is a great moment. From the perspective of the country, we can see the pace of our city and the pace of China. Second, humanistic care is more intense. We only do two rounds of competition, so that the city can focus on the program and carry out intensive cultivation, so that the charm of the city can be better released. Third, we should use real elements to express our love for the city. We will follow the process of filming all the city competitions and rehearsals, and aspire to set up a biography for each city. Competition is only a means, reality is the end.
For codes of the same length, theoretically, the further the coding distance between any two categories, the stronger the error correction capability. Therefore, when the code length is small, the theoretical optimal code can be calculated according to this principle. However, it is difficult to effectively determine the optimal code when the code length is slightly larger. In fact, this is an NP-hard problem. However, we usually do not need to obtain theoretical optimal codes, because non-optimal codes can often produce good enough classifiers in practice. On the other hand, it is not that the better the theoretical properties of coding, the better the classification performance, because the machine learning problem involves many factors, such as dismantling multiple classes into two "class subsets", and the difficulty of distinguishing the two class subsets formed by different dismantling methods is often different, that is, the difficulty of the two classification problems caused by them is different. Therefore, one theory has a good quality of error correction, but it leads to a difficult coding for the two-classification problem, which is worse than the other theory, but it leads to a simpler coding for the two-classification problem, and it is hard to say which is better or weaker in the final performance of the model.
