Language Features in Katherine Mansfield's “The Garden-Party”

This paper analyzes the features of language in"The Garden-Party"of Katherine Mansfield from three aspects of sentencestructure, word selection and characters' discourse. A large number of examples indicate Katherine Mansfield's language in the shortfiction creates a poetic imagery; moreover, the author's words depicting things and portraying figures have a great influence on the ex-pression of the theme and characterization of the short story.

Language Features of Politeness at Lexicon Level in English, Japanese and Chinese

Courtesy language, as an indispensable part of communication, occurs in all languages. However, due to the cultural diversity, different languages have different laws and regulations in the choice of courtesy language, which is very important in cross culture communication. It is significant and instructive to study the similarities and differences of the courtesy language. The article aims to study the language features of politeness at lexicon, syntactic and pragmatic level in English, Japanese and Chinese as well as the underlying reasons and culture roots of the diversities, to make cross-culture communication better.

The Language Features and Translation Strategies of Business English Contract

The thesis aims to offer translation guidelines and strategies of business English contract,through the research on the language features of business English contract. It begins with the importance of the study on the translation strategies of business contract in English. then,review and analysis the traditional translation theories,and gain a detailed discussion on Business English's and contract English's characteristics,provides the translation strategies of business English contract. Finally,put forward some suggestions on further study.

Impact of transcranial electrical stimulation on serum neurotrophic factors and language function in patients with speech disorders

BACKGROUND Speech disorders have a substantial impact on communication abilities and quality of life.Traditional treatments such as speech and psychological therapies frequently demonstrate limited effectiveness and patient compliance.Transcranial electrical stimulation(TES)has emerged as a promising non-invasive treatment to improve neurological functions.However,its effectiveness in enhancing language functions and serum neurofactor levels in individuals with speech disorders requires further investigation.AIM To investigate the impact of TES in conjunction with standard therapies on serum neurotrophic factor levels and language function in patients with speech disorders.METHODS In a controlled study spanning from March 2019 to November 2021,81 patients with speech disorders were divided into a control group(n=40)receiving standard speech stimulation and psychological intervention,and an observation group(n=41)receiving additional TES.The study assessed serum levels of ciliary neurotrophic factor(CNTF),glial cell-derived neurotrophic factor(GDNF),brainderived neurotrophic factor(BDNF),and nerve growth factor(NGF),as well as evaluations of motor function,language function,and development quotient scores.RESULTS After 3 wk of intervention,the observation group exhibited significantly higher serum levels of CNTF,GDNF,BDNF,and NGF compared to the control group.Moreover,improvements were noted in motor function,cognitive function,language skills,physical abilities,and overall development quotient scores.It is worth mentioning that the observation group also displayed superior perfor CONCLUSION This retrospective study concluded that TES combined with traditional speech and psychotherapy can effectively increase the levels of neurokines in the blood and enhance language function in patients with speech disorders.These results provide a promising avenue for integrating TES into standard treatment methods for speech disorders.

Readability Formula for Chinese as a Second Language: An Exploratory Study

Textbook writers,Chinese language teachers,and test designers need to ensure readability of the texts they use or intended to use.They often resort to“expert judgements”based on professional experience rather than apply objective measures.This happens because there is a lack of suitable readability formulas like those established for English.Moreover,in the Singaporean context where Chinese language is taught at a lower level(referred to as a Second Language or Mother Tongue Language),readability formulas developed for Chinese as a First Language for use in,for example,the Chinese mainland and Taiwan,are not suitable for use in Singapore(and other places where Chinese is learned as a heritage language).The present study made use of extant Chinese language textbooks as the source of data and created three readability formulas for Chinese as a Second Language.Predicted grade levels were then compared with the original grade levels of 100 selected texts at Primary 1 to Secondary 4 levels.The formula for the full text was found to be most effective when compared with the two for shorter versions of the texts.Prediction was more accurate when applied to the texts for Primary 1-6 students than to the texts for Secondary 1-4 students.The formula was found to be convenient to use as it entailed just three language features which could be easily hand-calculated,i.e.,the number of Chinese characters,the number of words,and the average sentence length.Practical use and limitations of the formula are discussed.

A Multiple Feature Approach for Disorder Normalization in Clinical Notes

In this paper we propose a multiple feature approach for the normalization task which can map each disorder mention in the text to a unique unified medical language system（UMLS）concept unique identifier（CUI）. We develop a two-step method to acquire a list of candidate CUIs and their associated preferred names using UMLS API and to choose the closest CUI by calculating the similarity between the input disorder mention and each candidate. The similarity calculation step is formulated as a classification problem and multiple features（string features,ranking features,similarity features,and contextual features） are used to normalize the disorder mentions. The results show that the multiple feature approach improves the accuracy of the normalization task from 32.99% to 67.08% compared with the Meta Map baseline.