The Ethical Choice of Business English Interpreters under Chesterman’s Model of Translation Ethics

This paper explores the ethical challenges encountered by business English interpreters using Chesterman’s Model of Translation Ethics,set against the context of economic globalization and the“Belt and Road”initiative.With the increasing demand for interpreters,the paper delves into the ongoing discussion about the role of AI in translation and its limitations,especially concerning cultural subtleties and ethical issues.It highlights the importance of human interpreters’cross-cultural understanding and the ethical principles that inform their work,such as the Ethics of Representation,Service,Communication,Norm-based Ethics,and Commitment.Moreover,the paper examines how these ethical models are applied in practical business situations,including business banquets,business negotiations,business talks and business visits,etc.,and investigates the cultural misunderstandings that may occur during these interactions.The study concludes that although AI provides efficiency and cost savings,human interpreters are essential for their capacity to handle the intricacies of cross-cultural communication with cultural awareness and ethical discernment.

Research on Interpreters'Psychological Stress and Stress Management

Interpreting has been known as and proven a stressful job.This paper introduces the phenomena and symptoms of psychological stress that often,if not always,occur in the profession of interpreting.It then pinpoints the factors that expose interpreters to stress,which include biological factors,environmental factors,cognitive factors and personality factors.At last,practical stress management strategies are proposed,namely to improve the comfort level of the physical working environment for interpreters,to improve their physical fitness,to increase support and cooperation from concerned parties,and finally to rethink,relax and release stress.

Training Interpreters With Compound Abilities From the Perspective of Signed and Spoken Language Interpretation

Signed language is a natural language for verbal communication of the deaf and people hard of hearing. Both signed and oral language interpretation are activities that convert one language into another. They are similar with each other in terms of interpreting strategy, model, skills and so on. Sign language interpretation teaching and research can be integrated with oral interpretation teaching and research. China today urgently needs more multi-talented people than skillful language users. This paper holds if English majors learn signed language and can interpret between CSL, Chinese, and English, they must be warmly welcome in the employment market. Such interpreters with compound abilities are able to bridge the gap between hearing and deaf people even from different countries. This is of necessity and feasibility.

Fundamental Qualities of Diplomatic Interpreters

With the more and more frequent of international communications, diplomatic work has come to a totally new age.The diplomatic interpreters must meet higher requirments and challenges. Hence what qualities they should have becomes an important problem.this thesis focus on four aspects to deal with it.

Requirements on Business Interpreters

On the whole, the requirements on business interpreters are almost the same with other interpreters. However, the characteristics of business activities requires that the interpreter should have wide knowledge of the business proper names and phrases, the sensitivity against numbers and the awareness of the different cultures in trade. To be an interpreter in business, one should pay special attention to these aspects.

Do Interpreters Indeed Have Superior Memory in Interpreting

With the frequent communications between China and western countries in the field of economy, politics and culture, etc, Interpreting becomes more and more important to people in all walks of life.This paper aims to testify the author's hypothesis 'professional interpreters have similar short-term memory with unprofessional interpreters, but they have superior working memory.' After the illustration of literatures concerning with consecutive interpreting, short-term memory and working memory, experiments design and analysis are described. Based on the experiment results, this paper further discussed three influential factors contributing to the test results such as interpreting experience, background knowledge.

Education on Qualified Interpreters—Strategies of Cultivation on Psychological Quality

In the modern era, educators have to attach importance on the requirements of talent quality training in the 21st century and make unremitting efforts to meet these requirements. How to help students overcome state fright and adapt to the actual scene of interpreting has been a major concern for professors and teachers. Psychological quality, which is as important as other interpretation skills, such as listening, is a premise of a successful and qualified interpretation. This essay will analyze how to educate a qualified interpreter in terms of psychological quality by various aspects, including putting more emphasis on bilingual learning, enriching students’ cultural connotations, enhancing teachers’ comprehensive quality, cultivating students’ English public speaking ability, creating authentic interpretation environments, improving students’ adaptability of different interpretation environments, and using other practical skills.

Liaison Interpreters’Empowerment under Michel Foucault’s Thought of Power

Michel Foucault’s thought of power believes that everyone within a relational network plays a role and holds certain power in hand to stabilize and strengthen the function of the network.Liaison interpreters,clients,and the communication context are three most important components of the communication network.During the interpreting process,interpreters hold some power in hand and they will use this power when necessary through the action of empowerment.In this paper,with analysis on liaison interpreters’empowerment under different occasions,three kinds of empowerment can be concluded;liaison interpreters empower themselves;liaison interpreters empower clients;interpreters empower context.It also proves that proper empowerment could facilitate the communication while over-empowerment could hinder the communication.

A Study on Student Interpreters＇ Note-Taking, Interpreting Process and Output

Interpretation, either consecutive or simultaneous, demands more advanced linguistic skills as well as higher cognitive strategies than translation. This paper investigates the characteristics of the notes taken by student interpreters in relation to the output and the process of interpretation with the purpsoe of identifying the role of note-taking in the process of interpretation, its relations with the production quality, and the factors that constrain the development of the students＇ potential as future interpreters. Statistical and qualitative analysis of the notes and think-aloud protocol reveals that students majoring in English should further improve their overall English proficiency. Note-taking, either in source language or target language, or both, should be practiced until students are able to use it expertly. Inspite of the importance of note-taking in interpretation, students should be trained to rely more on memory rather than solely on the notes.

A Book Review of Hedges in Chinese-English Conference Interpreting:A Corpus-based Discourse Analysis of Interpreters’Role Deviations

Hedges is widely employed in conference interpreting and can be used to unveil interpreters’role deviation.However,few empirical studies have been made to explore conference interpreters’role deviation through the use of hedges.This piece of book review offers a comprehensive examination of the book on interpreters’role deviation in interpreting at Chinese government press conferences from conceptual,methodological and empirical aspects.With in-depth discussion on some critical aspects covered by the volume,the book review can help readers to gain a more nuanced understanding on the relationship between the use of hedges and interpreters’role deviation.

How Effortful Are Interpreters in Translation Related Reading Tasks?:An Eye-Tracking Study

Readingto comprehend the source text is a necessary part in translation process.However,the cognitive processing in various reading tasks related to translation is far from well-understood.The present study investigated interpreters’eye movement behavior in E-C language pair across different reading tasks.The participants are instructed to perform four tasks involving reading for specific purposes.The four tasks are as follows:(1)reading for comprehension(monolingual);(2)reading for summary;(3)reading in preparation for translating;and(4)reading while speaking a translation(sight translating).The results showed that reading purposes have a clear effect on interpreters’eye movement behaviors.By tasks both groups of interpreters spent more task time,more and longer fixations as they dealt with increasingly cognitive-demanding tasks.Across groups student interpreters spend more time,more and longer fixations than do professionals in most of the tasks.The study revealed that the increasing cognitive efforts required by reading is dependent on various reading tasks and translation expertise,which provided tentative implications for understanding and modelling the way interpreters read.The study also provided evidence for the validity of eye-tracking as a methodology in different translation modalities.

Lofty Expectations and Bitter Reality： Chinese Interpreters for the US Army during the Second World War, 1941-1945

Between 1941 and 1945, the Nationalist government supervised a program that trained more than 3,300 male college students and recent graduates to serve as interpreters for the US military in the China-Burma-India （CB1） Theater. These interpreters made the Sino-US alliance a reality by enabling American servicemen to communicate with other Chinese. But despite the program＇s operational success, interpreters suffered from intractable morale problems. Interpreters began their service with lofty expectations. Senior officials and intellectuals encouraged them to see themselves as central figures in China＇s struggle for nafonal rejuvenation. They would uplift the country by convincing American servicemen to see Chinese as equals and by introducing American technology, traits, and habits to the Chinese Army. It all sounded glorious to cadets undergoing training, but actual interpreter service proved bitterly disappointing to most young men. They found their monotonous duties unworthy of their position The Nationalist government, for its part, lacked the capacity to keep them clothed, paid, and fed. Their own compatriots--soldiers and civilians alike--regarded them with suspicion. Most frustrating of all, American soldiers refused to treat them as equals. By examining interpreter morale problems in China fronl 1941 to 1945, this article enriches our understanding of wartime interpreting, China in a global World War II, and sources of friction in the Sino-US alliance

Lured by Tradition A famous Chinese vlogger is using social media to promote intangible cultural heritage

In the digital age,where traditional culture is in danger of gradually disappearing,one iconic figure has taken it upon herself to reverse the trend by reviving traditional skills.A prominent Chinese vlogger,Li Ziqi,whose birth name is Li Jiajia,has amassed a vast online following by reinterpreting traditions that date back thousands of years.Following a threeyear absence from social media,she made a highly anticipated return with the release of three new videos in mid-November 2024.These videos represent the culmination of several months of behind-the-scenes work.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

A method to interpret fracture aperture of rock slope using adaptive shape and unmanned aerial vehicle multi-angle nap-of-the-object photogrammetry

The aperture of natural rock fractures significantly affects the deformation and strength properties of rock masses,as well as the hydrodynamic properties of fractured rock masses.The conventional measurement methods are inadequate for collecting data on high-steep rock slopes in complex mountainous regions.This study establishes a high-resolution three-dimensional model of a rock slope using unmanned aerial vehicle(UAV)multi-angle nap-of-the-object photogrammetry to obtain edge feature points of fractures.Fracture opening morphology is characterized using coordinate projection and transformation.Fracture central axis is determined using vertical measuring lines,allowing for the interpretation of aperture of adaptive fracture shape.The feasibility and reliability of the new method are verified at a construction site of a railway in southeast Tibet,China.The study shows that the fracture aperture has a significant interval effect and size effect.The optimal sampling length for fractures is approximately 0.5e1 m,and the optimal aperture interpretation results can be achieved when the measuring line spacing is 1%of the sampling length.Tensile fractures in the study area generally have larger apertures than shear fractures,and their tendency to increase with slope height is also greater than that of shear fractures.The aperture of tensile fractures is generally positively correlated with their trace length,while the correlation between the aperture of shear fractures and their trace length appears to be weak.Fractures of different orientations exhibit certain differences in their distribution of aperture,but generally follow the forms of normal,log-normal,and gamma distributions.This study provides essential data support for rock and slope stability evaluation,which is of significant practical importance.

Artificial intelligence-driven radiomics study in cancer:the role of feature engineering and modeling

Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians.Moreover,some potentially useful quantitative information in medical images,especially that which is not visible to the naked eye,is often ignored during clinical practice.In contrast,radiomics performs high-throughput feature extraction from medical images,which enables quantitative analysis of medical images and prediction of various clinical endpoints.Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine.However,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical modeling.In this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with cancer.We focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling.Furthermore,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of models.Finally,we offer possible solutions to current challenges in radiomics research.

An improved deep dilated convolutional neural network for seismic facies interpretation

With the successful application and breakthrough of deep learning technology in image segmentation,there has been continuous development in the field of seismic facies interpretation using convolutional neural networks.These intelligent and automated methods significantly reduce manual labor,particularly in the laborious task of manually labeling seismic facies.However,the extensive demand for training data imposes limitations on their wider application.To overcome this challenge,we adopt the UNet architecture as the foundational network structure for seismic facies classification,which has demonstrated effective segmentation results even with small-sample training data.Additionally,we integrate spatial pyramid pooling and dilated convolution modules into the network architecture to enhance the perception of spatial information across a broader range.The seismic facies classification test on the public data from the F3 block verifies the superior performance of our proposed improved network structure in delineating seismic facies boundaries.Comparative analysis against the traditional UNet model reveals that our method achieves more accurate predictive classification results,as evidenced by various evaluation metrics for image segmentation.Obviously,the classification accuracy reaches an impressive 96%.Furthermore,the results of seismic facies classification in the seismic slice dimension provide further confirmation of the superior performance of our proposed method,which accurately defines the range of different seismic facies.This approach holds significant potential for analyzing geological patterns and extracting valuable depositional information.

Characterization and spatial analysis of coseismic landslides triggered by the Luding Ms 6.8 earthquake in the Xianshuihe fault zone, Southwest China

On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.

Model-based interpretation of bottomhole pressure records during matrix treatments in layered formations

During injection treatments, bottomhole pressure measurements may significantly mismatch modeling results. We devise a computationally effective technique for interpretation of fluid injection in a wellbore interval with multiple geological layers based on the bottomhole pressure measurements. The permeability, porosity and compressibility in each layer are initially setup, while the skin factor and partitioning of injected fluids among the zones during the injection are found as a solution of the problem. The problem takes into account Darcy flow and chemical interactions between the injected acids, diverter fluids and reservoir rock typical in modern matrix acidizing treatments. Using the synchronously recorded injection rate and bottomhole pressure, we evaluate skin factor changes in each layer and actual fluid placement into the reservoir during different pumping jobs: matrix acidizing, water control, sand control, scale squeezes and water flooding. The model is validated by comparison with a simulator used in industry. It gives opportunity to estimate efficiency of a matrix treatment job, role of every injection stage, and control fluid delivery to each layer in real time. The presented interpretation technique significantly improves accuracy of matrix treatments analysis by coupling the hydrodynamic model with records of pressure and injection rate during the treatment.

Directly predicting N_(2) electroreduction reaction free energy using interpretable machine learning with non-DFT calculated features

Electrocatalytic nitrogen reduction to ammonia has garnered significant attention with the blooming of single-atom catalysts(SACs),showcasing their potential for sustainable and energy-efficient ammonia production.However,cost-effectively designing and screening efficient electrocatalysts remains a challenge.In this study,we have successfully established interpretable machine learning(ML)models to evaluate the catalytic activity of SACs by directly and accurately predicting reaction Gibbs free energy.Our models were trained using non-density functional theory(DFT)calculated features from a dataset comprising 90 graphene-supported SACs.Our results underscore the superior prediction accuracy of the gradient boosting regression(GBR)model for bothΔg(N_(2)→NNH)andΔG(NH_(2)→NH_(3)),boasting coefficient of determination(R^(2))score of 0.972 and 0.984,along with root mean square error(RMSE)of 0.051 and 0.085 eV,respectively.Moreover,feature importance analysis elucidates that the high accuracy of GBR model stems from its adept capture of characteristics pertinent to the active center and coordination environment,unveilling the significance of elementary descriptors,with the colvalent radius playing a dominant role.Additionally,Shapley additive explanations(SHAP)analysis provides global and local interpretation of the working mechanism of the GBR model.Our analysis identifies that a pyrrole-type coordination(flag=0),d-orbitals with a moderate occupation(N_(d)=5),and a moderate difference in covalent radius(r_(TM-ave)near 140 pm)are conducive to achieving high activity.Furthermore,we extend the prediction of activity to more catalysts without additional DFT calculations,validating the reliability of our feature engineering,model training,and design strategy.These findings not only highlight new opportunity for accelerating catalyst design using non-DFT calculated features,but also shed light on the working mechanism of"black box"ML model.Moreover,the model provides valuable guidance for catalytic material design in multiple proton-electron coupling reactions,particularly in driving sustainable CO_(2),O_(2),and N_(2) conversion.