Research on high-performance English translation based on topic model

Retelling extraction is an important branch of Natural Language Processing(NLP),and high-quality retelling resources are very helpful to improve the performance of machine translation.However,traditional methods based on the bilingual parallel corpus often ignore the document background in the process of retelling acquisition and application.In order to solve this problem,we introduce topic model information into the translation mode and propose a topic-based statistical machine translation method to improve the translation performance.In this method,Probabilistic Latent Semantic Analysis(PLSA)is used to obtains the co-occurrence relationship between words and documents by the hybrid matrix decomposition.Then we design a decoder to simplify the decoding process.Experiments show that the proposed method can effectively improve the accuracy of translation.

Regenerative Medicine in Orthopaedics: Microsurgery Achievements for Translational Animal Model

Purpose: Despite many scientific advances, Regenerative Medicine is still in the preclinical stages in many areas. In this article, we intend to discuss the role of microsurgery in the bench-to-bedside transition of such primary findings. Method: By searching the papers related to the history of Regenerative Medicine (RM) and the news of Tissue Engineering (TE) in orthopedics in Pubmed, Scopus, and Google Scholar databases, we accessed a complete archive of various topics related to this field. Result: We first assessed the history and achievements of regenerative medicine, then we realized the importance of translational medical sciences and the role of animal models in this incipient phenomenon. Finally, after mastering the capabilities of microsurgery and the useful contribution of this technique to the advancement of clinical applications of regenerative medicine in various branches such as skin, skeletal system, nerves, and blood vessels, we decided to express the gist of our studies through this article. Conclusion: Considering the widespread use of small animals in regenerative medicine projects and the inevitable role of microsurgery in performing the best intervention on these animal models, the significant progress of regenerative medicine clinical application requires special attention to microsurgery in associated research.

The Jerome Model and the Horace Model in Translation Research

In the research of translation theory,many scholars propose and construct translation models,the purpose of which is to try to describe the translating process and find out the nature of translation.This thesis mainly introduces and analyses the characteristics of the Jerome Model and the Horace Model,and try to make a comparison between these two models for studying translations,in the hope of leading to deeper recognition and research of the translation process.

Analysis on Application of Pragmatic Translation Skill Structure Model in Translation Teaching

As the core content of pragmatic translation teaching research,pragmatic translation skill is closely correlated with translation technique and operation field.Viewed from the current English teaching situation in colleges and universities,translation skill is not cultivated as an independent language competence.Moreover,its research is insufficient.On account of this,the author first gives an introduction to pragmatic translation skill and pragmatic translation skill structure model in this paper.On this basis,the author also analyzes the application of pragmatic translation skill structure model in translation teaching.

A Theoretic Study on the Translation Model from Relevance Theory

Relevance Theory holds that the language communication of human beings is an ostensive-inferential process of searching for relevance.Translation as a communication across language and culture,involves a dual process of communication among the source language author,the translator and the target language readers,during which the translator infers the communicative intention of the source language author,then by assessing the cognitive environments of the target language readers,makes the optimally relevant translation so that the translation can be equivalent in relevant aspects.

Improving Language Translation Using the Hidden Markov Model

Translation software has become an important tool for communication between different languages.People’s requirements for translation are higher and higher,mainly reflected in people’s desire for barrier free cultural exchange.With a large corpus,the performance of statistical machine translation based on words and phrases is limited due to the small size of modeling units.Previous statistical methods rely primarily on the size of corpus and number of its statistical results to avoid ambiguity in translation,ignoring context.To support the ongoing improvement of translation methods built upon deep learning,we propose a translation algorithm based on the Hidden Markov Model to improve the use of context in the process of translation.During translation,our Hidden Markov Model prediction chain selects a number of phrases with the highest result probability to form a sentence.The collection of all of the generated sentences forms a topic sequence.Using probabilities and article sequences determined from the training set,our method again applies the Hidden Markov Model to form the final translation to improve the context relevance in the process of translation.This algorithm improves the accuracy of translation,avoids the combination of invalid words,and enhances the readability and meaning of the resulting translation.

Unified deep learning model for predicting fundus fluorescein angiography image from fundus structure image

The prediction of fundus fluorescein angiography(FFA)images from fundus structural images is a cutting-edge research topic in ophthalmological image processing.Prediction comprises estimating FFA from fundus camera imaging,single-phase FFA from scanning laser ophthalmoscopy(SLO),and three-phase FFA also from SLO.Although many deep learning models are available,a single model can only perform one or two of these prediction tasks.To accomplish three prediction tasks using a unified method,we propose a unified deep learning model for predicting FFA images from fundus structure images using a supervised generative adversarial network.The three prediction tasks are processed as follows:data preparation,network training under FFA supervision,and FFA image prediction from fundus structure images on a test set.By comparing the FFA images predicted by our model,pix2pix,and CycleGAN,we demonstrate the remarkable progress achieved by our proposal.The high performance of our model is validated in terms of the peak signal-to-noise ratio,structural similarity index,and mean squared error.

A General Introduction of the Main Similarities and Differences between the Three Translation Models

This study focuses on the three translation models,the Jerome model,the Horace model,the Schleiermacher model.The study intends to compare the three models,there are some similarities and differences between the three models.By analyzing two kinds of the translation strategies,literal translation and free translation,this study argues that different source texts need different translation strategies.Translators should know the proper translation strategies and rich knowledge.

Novel translational rat models of dopamine transporter deficiency

Dopamine （DA） is one of the brain＇s fundamental neurotransmitters. Despite the fact that the dopaminergic synapses constitute less than 1% of all brain synapses, DA is implicated in a number of critical physiological functions and in the pathogenesis of important psychiatric diseases such as schizophrenia, attention-deficit/hyperactivity disorder （ADHD）, Parkinson＇s disease （PD） and others.

The Renditions Series and Modern Chinese Literature’s “Going-out”: Its Model and Enlightenment of Translation, Communication and Dissemination

In the process of Chinese Literature’s “Going-out” project, it istypical of the dilemma faced by the external translation and dissemination of modernChinese literature. The Renditions Series serves as a classical case of providing aneffective model of “literature’s overseas distribution”. The successful experience of itstranslating-cum-disseminating model can be concluded as follows: all the translatorsare from China and overseas with cross-cultural background; the selection oftranslation is stylistically far-ranging among the Mainland, Taiwan and Hong Kong,and feminine literature in modern China is highly valued; translating method aims atconvoying the original literary aesthetics, and disseminating channels are manifold;the foreign recipients are common and professional readers; the eminent effects canbe proved by its considerable sales, library collections and acceptance in the targetcountries and regions. From the successful model of translation of Renditions Series,five implications can be made out for the modern Chinese literature’s “Going-global”:domestic and overseas translators cooperate well with all-round cultural identities; theselection holds onto diversification and literary character; various spreading channelsshould be broadened; target readers should be accurately located and continuouslywidened; translating and disseminating effects can be focused on and analyzed, so asto adjust and improve the corresponding sections in the model.

Research on the Strategic Model for the Translation of Taoist Classics Based on Adaptation Theory

The core view of the adaptation theory is that language has a systematic propagation law,and language translation should be unfolded and extended according to the basic structure of the system.This paper has conducted an in-depth study on the translation of classics of the Taoist culture,with the purpose of improving the accuracy of the translation strategy.This paper also focuses on adaptation theory and taking the continuation and adaptation process of discourse as the core of the research,and conducts the construction analysis on the strategic model.The content of this paper is predicted to offer some simple translation reference ideas for professional translators who are dedicated to the direction of classics.

Ethical Problems in MTI Students’Escort Interpreting from the Perspective of Chesterman’s Models on Translation Ethics

The professionalization of translation has been discussed by many scholars in recent years,which has inspired the intense discussion of translation ethics.Drawing upon Chesterman’s models on translation ethics,this paper intends to examine the ethical problems in MTI students’escort interpreting for Vanuatu Sport Technical Assistance Project for the Pacific Mini Games in 2017 and China-ASEAN International Capacity Cooperation Forum in 2016.The data was collected by the methods of participant observation and informal interviews in the process of the two interpreting projects,especially the six-month assistance project.The ethical problems in the escort interpreting and the reasons that caused the problems were analyzed through case study.It is found that the major ethical problems that occurred are related to the ethics of communication,the norm-based ethics,and the ethics of commitment.These ethical problems were mainly related to the student escort interpreters’language proficiency,professional qualities,and intercultural/interpersonal communication competence.Some solutions are suggested based on Chesterman’s models on translation ethics.It is hoped that the research findings can provide some references to the implementation of the similar interpreting programs in the future,and enhance interpreting teaching and training programs.

The Application of the Jerome Model and the Horace Model in Translation Practice

The Jerome model and the Horace model have a great influence on translation theories and practice from ancient times. This paper starts from a comparative study of the two models, and mainly discusses similarities, differences and weakness of them. And then, through the case study, it analyzes the application of the two models to English-Chinese translation. In the end,it draws a conclusion that generally accepted translation criterion does not exist, different types of texts require different translation criterion.

Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work,the Slacks-Based Measure(SBM)model within Data Envelopment Analysis was employed to establish a set of indicators for evaluating the energy efficiency of manufacturing workshops.The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed.The findings indicated that aside from a few workshops operating at the production frontier,the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency.Subsequently,a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops.Regression analysis revealed that technological investments,employee quality,workshop production scale,investment in clean energy,and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops.By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors,this research aids company managers in understanding the energy efficiency of the manufacturing process.It optimizes the combination of various production elements,thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops,which can contribute to enhancing the corporation’s overall energy efficiency.

Improving Phrase-Based Statistical Machine Translation Models by Incorporating Syntax-Based Language Models

This paper proposed a method to incorporate syntax-based language models in phrase-based statistical machine translation (SMT) systems. The syntax-based language model used in this paper is based on link grammar,which is a high lexical formalism. In order to apply language models based on link grammar in phrase-based models,the concept of linked phrases,an extension of the concept of traditional phrases in phrase-based models was brought out. Experiments were conducted and the results showed that the use of syntax-based language models could improve the performance of the phrase-based models greatly.

A Study of Simile Translation in Red Sorghum Based on Relevance-Adaptation Model

In Red Sorghum, Mo Yan used about 200 similes, and Howard Goldblatt did an excellent job in translating them intoEnglish. The researcher aims to study the translation of similes in Red Sorghum based on Relevance-Adaptation Model. During theprocess of simile translation, a translator should first make a relevance assumption based on context to find the author's intention;second he should make a relevance adaptation to render the translated text conform to the tradition of the target language;last, aproper choice of utterance style should be made. The findings are as follows: for C-E translation, apart from translating a simile intoa simile, a translator can also translate it into a metaphor, paraphrase it or even omit the translation of it. Based on Relevance-Ad-aptation Model, this paper enriches studies on simile translation as well as on Red Sorghum.

Graph-based Lexicalized Reordering Models for Statistical Machine Translation

Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method.