character n. 1.性格,品格;特性,性状,特征;【生物学】形质。 2.身分,地位,资格。 3.名声,声望。 4.(戏剧、小说中的)角色,人物。 5.人,〔口语〕怪人,奇人。 6.字,字母;数字;(印刷)符号;电码组合;【计算机】字符。 7.品德证明书,鉴定,推荐书。 8.人物[性格]素描。 a man of character有个性[骨气]的人。 the national character=the character of a people 国民性。 a generic character【生物学】属的特征,属性。 a leading character主角。 a bad character 坏人,歹徒,恶棍。 He is quite a character. 他简直是一个怪人。 a Chinese character汉字。 character portrayal 性格描写。 character sketch 人物简评[素描]。 get a good [bad] character得好[坏]名。 give (sb.) a good [bad] character 推奖[攻击](某人)。 have an insight into character 有知人之明。 in character (在)性格上;正合担任[扮演];适当,相称。 in the character of 以…的资格;扮演。 out of character 不适当[适合],不称( go out of character越分妄为)。 take away sb.'s character 夺人名誉。 take on character 有特征[特色]。 vt. 1.〔诗、古〕写,画;刻。 2.表现…的特性;使具有特性。 adj. -less 无特征的,平凡的。
Consists of more than one line , you can separate the lines using a carriage return character 包含多行,则可以在每行之间使用回车符chr
First , the author confirms that there is not significant relation between fund return and size as well as investment style by examining the data of closed - end funds . it is also proved that the evaluation method is feasible by evaluating the closed - end funds and open - end funds in china respectively . the author compares risk - return character between closed - end funds and open - end funds and the results show open - end funds " performance is not better than that of closed - end funds according to their risk - return character 首先用封闭式基金的数据验证了基金的收益与基金规模、投资风格并无显著关系,因此本文暂时不分规模、风格进行评价;然后用本文建立的评价系统分别评价开放式基金和封闭式基金,证明方法是切实可行的;最后就开放式基金和封闭式基金的风险收益特征进行了比较,结果显示开放式基金并不优于封闭式基金。
Considering the defects in the practical application of traditional paragraph alignment method based on carriage - return character , this thesis puts forward a segmental alignment algorithm based on the anchor sentence pairs . to combine the merits of two methods above , a multi - level segment alignment method is suggested in this research . the final experiments prove the method is highly efficient and practical 然后本文考虑到基于回车符的方法在实际应用中的缺陷,提出了一种基于锚点句对的分段对齐方法,并根据需要,将上述两种方法相结合,形成了一种多层次分段对齐方法,进一步提高了句子对齐的运行效率和正确率。