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On Specificity of Politeness —— Contrastive Study of Western and Chinese Concepts of Politeness 被引量:1
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作者 Xinke Tian Haiyan Zhao 《Sino-US English Teaching》 2006年第2期75-78,共4页
Politeness is a social phenomenon, a means to achieve good interpersonal relationships, and a norm imposed by social conventions. Politeness is universal, that is, it can be observed as a phenomenon in all cultures. I... Politeness is a social phenomenon, a means to achieve good interpersonal relationships, and a norm imposed by social conventions. Politeness is universal, that is, it can be observed as a phenomenon in all cultures. It is resorted to by speakers of different languages as a means to an end, and it is recognized as a norm in all societies. Despite its universality, the actual manifestations of politeness, the ways to realize politeness, and the standards differ in different cultures. Politeness is, to some extent, culture-specific. 展开更多
关键词 positive face negative face the face theory specificity
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RF-PSSM:A Combination of Rotation Forest Algorithm and Position-Specific Scoring Matrix for Improved Prediction of Protein-Protein Interactions Between Hepatitis C Virus and Human
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作者 Xin Liu Yaping Lu +3 位作者 Liang Wang Wei Geng Xinyi Shi Xiao Zhang 《Big Data Mining and Analytics》 EI CSCD 2023年第1期21-31,共11页
The identification of hepatitis C virus(HCV)virus-human protein interactions will not only help us understand the molecular mechanisms of related diseases but also be conductive to discovering new drug targets.An incr... The identification of hepatitis C virus(HCV)virus-human protein interactions will not only help us understand the molecular mechanisms of related diseases but also be conductive to discovering new drug targets.An increasing number of clinically and experimentally validated interactions between HCV and human proteins have been documented in public databases,facilitating studies based on computational methods.In this study,we proposed a new computational approach,rotation forest position-specific scoring matrix(RF-PSSM),to predict the interactions among HCV and human proteins.In particular,PSSM was used to characterize each protein,two-dimensional principal component analysis(2DPCA)was then adopted for feature extraction of PSSM.Finally,rotation forest(RF)was used to implement classification.The results of various ablation experiments show that on independent datasets,the accuracy and area under curve(AUC)value of RF-PSSM can reach 93.74% and 94.29%,respectively,outperforming almost all cutting-edge research.In addition,we used RF-PSSM to predict 9 human proteins that may interact with HCV protein E1,which can provide theoretical guidance for future experimental studies. 展开更多
关键词 protein-protein interactions hepatitis C virus position specific scoring matrix two-dimensional principal component analysis rotation forest
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