Idioms Research Articles

Postoperative reorganization of the supplementary motor area complex: a possible latent bihemispheric network

Brain plasticity after multistep surgery in low-grade glioma is highly variable; the neurosurgical approach must be individualised and functional imaging can be used for this purpose. In supplementary motor area complex (SMAC) tumors, the early and adequate functional recovery of patients raises the possibility of a latent bihemispheric or "mirror" cortico-subcortical network, which would develop depending on the needs of each patient. Functional and DTI-MR data from 4 right-handed patients with left frontal low grade gliomas near the SMAC, who were operated at least in two occasions were collected. The time of the reintervention was variable (18 months- 8 years), related to the tumor growth. All patients were evaluated by a neuropsychologist and imaged before each surgery, in a 3 T MR, with a 24 multichanel head coil Motor and expressive language task-fMRI and DTI sequences were obtained to evidence the main cortico-subcortical components of the SMAC. Data were processed with Brainwave (GE Medical Systems) and with an Iplan Fiber Tracking tool (MEDTRONIC), respectively RESULTS: None of our patients presented permanent neurological deficits after the first or second functional surgery. Three patients with partial or complete resection of the left middle and / or inferior frontal gyrus, and the left frontal aslant tract evidenced new right hemispherical cortical activity. This right shift were not observed in the patient without left middle gyrus resection, indeed with partial absent of the left frontal aslant tract. SMAC is a latent cortico-subcortical bihemispheric network that allows it to reorganize itself in response to specific neurological deficits. We highlight the importance in the cortical reorganization of the left middle frontal gyrus in the SMAC, closely connected with the essential language areas of this region, but also we focused in the potential cortioco-subcortical changes to compensate the functionality of the FAT.

ZnO Nanowall Network-Based Tactile/Gesture Sensors and Prediction with Machine Learning.

In low-dimensional material systems, augmented physical and chemical properties may be witnessed through a unique morphological evolution. Here, we report the development of an optimized nanowall network of ZnO for the fabrication of a flexible single-electrode triboelectric nanogenerator (STENG)-based tactile and gesture sensors. The chemically grown nanowall network with an adequate pore area endows superior triboelectric output (current ∼0.6 μA and power ∼20 μW/cm2) by offering an optimum surface area and dielectric constant for pressure sensing applications. The rational comparison of the triboelectric properties of nanowall and nanorod structures of ZnO reveals that the higher surface area offered by the hollow walls leads to superior output characteristics. The demonstration of pressure sensitivity of the STENG ∼1 V/N is promising for self-powered tactile sensing applications. The array of STENG sensors, when attached to a user hand, generates distinguishable signals while holding objects of varying curvature and mass. Again, the observation of sensitivity of ∼0.1 V per degree during finger movement activity indicates the gesture sensing ability of the nanowall-based TENG system, facilitating sign language expression through the movement of fingers. Further, the generated electrical signals during tactile and gesture sensing can be classified and recognized through the deployment of machine learning (ML) techniques. In fact, the implementation of Random Forest and K-Nearest Neighbor models has offered an accuracy of 96% while recognizing the output signals generated by the sensor arrays. The demonstration of superior sensing characteristics with the optimized nanowall network may be advantageous in innovating prototype sensors for the differently abled people to distinguish or classify objects on the basis of material, morphology, and mass during their regular activities.

Follow-up of expressive language and general development at 12, 18 and 36 months for children with no canonical babbling at 10 months

ABSTRACT Little is known about the developmental trajectories in children who do not use canonical babbling (CB) at 10 months. The aim was to examine how speech, language, cognitive and motor abilities developed in children without CB. For 15 children identified as not having CB, consonant production, expressive vocabulary and general development were assessed at 12, 18 and 36 months from audio–video recordings. Twelve (79%) children still lacked CB at 12 months. At 18 months, six (40%) had parent-reported expressive vocabulary results below the 10th percentile, and two (14%) did not use dental/alveolar stops. The percentage of consonants correct for the group was at the level of peers at 36 months (89%, SD 0.17), but the group had fewer established target consonants than age norms. Most children had a small expressive vocabulary in comparison with Swedish age norms for younger children as well as with age-matched norms for other Nordic languages. The general development (Bayley-III) for three children (21%) who did not use speech was 1–2 SD below the average range in at least one domain (cognitive, language or motor), but the results for the whole group were within the average range. In conclusion, the heterogeneity in early consonant development in the study group resembles that of children in clinical groups with known risk for speech and language difficulties and the expressive vocabulary resembles that of children with delayed expressive vocabulary. For about one-fifth of the children, the absence of canonical babbling at age 10 months could be seen as an early sign of a more comprehensive developmental disability.

The Impact of Communication Skills on Work Performance in Team Collaboration

Abstract: Team collaboration is one of the increasingly important forms of work today. People also pay more attention to the factors that affect work performance in team collaboration. This article mainly studies the impact of communication skills on work performance in team collaboration. The factors that affect communication skills and the elements that communication skills can influence are also mentioned in this article. The main conclusion is that communication skills in team collaboration have a positive impact on work performance. Both personal factors and external factors can affect communication skills in team collaboration. There are various methods such as improving language expression ability, creating a comfortable communication atmosphere, and establishing more channels for work or emotional communication can help enhance peoples communication skills in team collaboration. Through these improvement measures, peoples work performance can also be improved.

Investigating Translation Students’ Challenges in Rendering Arabic Idioms and Proverbs into English: Insights and Recommendations

This study investigates the challenges faced by 4th-year students majoring in Translation at Al-Buraimi University College in Oman when translating proverbs and idioms from Arabic into English. These expressions pose particular difficulties in translation due to their cultural and linguistic specificity, often requiring more than literal translation to convey their intended meaning accurately in the target language. Understanding these challenges is crucial for enhancing the effectiveness of translation education programs and improving students’ proficiency in handling idiomatic expressions. The findings showed that 4th-year translation students experienced three main difficulties in translating proverbs and idioms, ranging from the semantic and syntactic fields to cultural differences. First, semantically speaking, they struggled to grasp the meaning of the source text and find the closest equivalent proverb or idiom in the English language. Second, from the syntactic perspective, learners showed several deficiencies in making a correct structure in English. Third, the high percentage of wrong answers revealed a lack of cultural awareness regarding the target culture. This research employs qualitative methods to identify common difficulties that students encounter, offering insights into potential strategies and pedagogical approaches to address these challenges effectively. By focusing on idiomatic expressions and proverbs, this study contributes to the broader discourse on translation education and highlights the importance of cultural competence in achieving accurate and nuanced translations.

Chinese-English Translation Strategies for Metaphors Based on Domestication and Foreignization

As an essential rhetorical device in language expression, metaphor deeply reflects the cultural background and social cognition. Metaphor translation needs to convey the meaning of language as well as the cultural connotations behind the metaphor. This study found that when the metaphorical images contain the same symbolic meaning in Chinese and English cultures, applying foreignization to reproduce the original metaphorical images can maintain the uniqueness and writing style of the source text and avoid the loss of cultural connotations in the translation process. Instead, in the case of different metaphorical images, using domestication to replace or omit the original symbolic images in the target language can improve the readability and acceptance of the translation. However, no studies explore applying metaphor translation strategies based on comparing the similarities and differences of metaphors in different languages and cultures, causing subjectivity in selecting metaphor translation strategies. This study compares the symbolic meanings of metaphors in Chinese and English cultures and provides a reliable and objective basis for selecting domestication and foreignization for metaphor translation, which help to achieve more effective faithfulness and cultural transmission. This analysis provides practical references for translation strategies of metaphors and promotes the depth of cross-cultural communication.

Analysis of the "patriotic feelings" and singing of the chinese art song "Wang Xiang Ci"

"Wang Xiang Ci" is one of the representative works of Chinese art songs, composed by the renowned composer Lu Zaiyi to the poem "Wang Da Lu" by the calligrapher Yu Youren. This article discusses various aspects of "Wang Xiang Ci", including its creation background, musical form, musical language, and emotional expression. Through the exploration of the use of national musical elements, the stratification of emotional expression, and the discussion of technique and artistic expression in singing practice, the article further clarifies the expression of the theme of home and country in the song; It also explores how to better convey the sentiment of home and country in singing practice.

Enteral micronutrient supplementation and neurodevelopmental outcomes in preterm or low birth weight infants: A systematic review and meta-analysis.

The association of enteral micronutrient supplementation and the neurodevelopmental outcomes of preterm or low birth weight (LBW) infants is controversial. This research was prospectively registered (CRD42023454034). We searched MEDLINE, Embase, PsycInfo, ClinicalTrials. gov, and the Cochrane Library for randomised clinical trials (RCTs) or quasi-RCTs comparing any enteral micronutrients supplementation with placebo or no supplementation in preterm or LBW infants. The primary outcome was neurodevelopmental impairment (NDI), with secondary outcomes involving various neurodevelopmental tests and disabilities. There was no evidence of an association between enteral micronutrients supplementation and the risk of NDI (RR, 1.03; 95% CI, 0.93-1.14; moderate certainty evidence). There was no evidence that the supplemented groups enhanced cognitive (MD, 0.65; 95% CI, -0.37 to 1.67; low certainty evidence), language (SMD, -0.01; 95% CI, -0.11 to 0.09; moderate certainty evidence), or motor scores (SMD, 0.04; 95% CI, -0.06 to 0.15; very low certainty evidence) or IQ (SMD, -0.20; 95% CI, -0.53 to 0.13; very low certainty evidence). Subgroup analysis showed that multiple micronutrients supplementation improved expressive language score (MD, 1.42; 95% CI, 0.39-2.45), and zinc supplementation enhanced fine motor score (SMD, 1.70; 95% CI, 0.98-2.43). The overall heterogeneity was low. This study demonstrates that enteral micronutrient supplementation is associated with little or no benefits in neurodevelopmental outcomes for preterm or LBW infants. Well-designed RCTs are needed to further ascertain these associations.

Challenging Case: Family Navigation for Autism Spectrum Disorder.

Leo is a 28-month-old boy from a monolingual Spanish-speaking family who was referred to a developmental-behavioral pediatrics (DBP) clinic for concerns regarding autism. His parents migrated to the United States 8 years ago and currently live and work on a farm. He was born in a US hospital after an uncomplicated pregnancy and has been generally healthy. His parents first became concerned about his development when he was 16 months old. He stopped saying mama/dada in Spanish and started lining up random objects. He had frequent temper tantrums and was difficult to console during unexpected changes in his routine. He screened positive on the Modified Checklist for Autism in Toddlers,Revised with Follow-Up (M-CHAT-R/F) at his 18-month well-child visit, and his pediatrician referred him to the local early intervention program. Calls from the early intervention program to his parents were unanswered. At his 24-month well-child visit, he again screened positive on the M-CHAT-R/F, and his pediatrician placed a referral for a DBP consultation. During the DBP visit at 28 months of age, developmental testing indicated his receptive and expressive language skills to be in the extremely low range, with significant scatter in his cognitive and adaptive skills. Behavioral observations were consistent with parental history and showed differences in social communication and interaction, the presence of repetitive behaviors, and extreme distress with transitions. He was diagnosed with autism spectrum disorder. Recommendations, including referral to early intervention, applied behavior analysis therapy, speech and language therapy, audiology evaluation, and genetic testing, were discussed with his parents through an interpreter. An autism packet, written in Spanish, with detailed information about autism and community resources was given to the family. By the time of a follow-up DBP visit 6 months later, Leo had not started on any early intervention or therapeutic services. Where do you go from here?

The pragmatism of emotional-expressive words in Kazakh linguistics: A study of M. Auezov’s ‘The Way of Abai’

Abstract The issue of the research of emotional lexemes is conditioned upon pragmatic relations, which constitute an important basis in the definition of expressive language units. The purpose of the research is to analyse features of emotional and expressive linguistic units, considering the cognitive and linguistic nature of words in M. Auezov’s work ‘The Way of Abai.’ The methods used to achieve the research objectives were: generalization, axiomatic, content analysis, and comparative analysis. The results of the work have determined that using words depends on a different range of emotions, where a particular situation influences the traditions and perceptions of the period concerned, developing a linguistic picture of the world. The practical significance of the research is in using the results of the research by linguists, experts, and specialists in the field of pedagogy and linguistics.

Exploring linguistic and cultural barriers in literary translation: an analysis of undergraduate students' strategies and challenges in translating Albanian texts into English

Purpose: Investigate the challenges undergraduate students face when translating Albanian literary texts into English, focusing on the cultural and linguistic considerations that impact the translation process and the concept of translation loss. Methodology: Qualitative analysis of the translation methods used by non-English-speaking students, examining the types of cultural loss, challenges, and solutions encountered. Data were collected by studying translated excerpts from the Albanian literary work "Prilli i Thyer" (Broken April), with attention to the strategies employed by students to address translation challenges. Findings: Students predominantly used literal translation, resulting in implicit, modified, and complete cultural losses. Key challenges included translating Albanian cultural words, idiomatic expressions, and grammatical differences. Despite these challenges, students demonstrated proficiency and versatility in literary translation, employing strategies such as adaptation, direct translation, borrowing, and omission. Implications: The findings highlight the need for enhanced cultural competence and linguistic skills in translation education. Recommendations include using Albanian-Albanian dictionaries and a deeper engagement with Albanian culture to improve translation accuracy and reduce cultural loss. Recommendations: Students should be encouraged to develop a comprehensive understanding of the source culture and to utilize creative translation solutions. Peer collaboration and feedback are also recommended to refine translation skills and strategies. Conclusion: This research contributes to the field of translation studies by shedding light on the intricacies of translating Albanian literature into English. It underscores the importance of cultural sensitivity and linguistic proficiency in producing accurate and culturally resonant translations, ultimately fostering a more interconnected and diverse literary world

Profiling Standards to Improve Practical Interoperability

Abstract. Standard data models are key to enable a set of data integration functionalities, often characterised using the Findability, Accessibility, Interoperabilty and Reusability (FAIR) principles. However, standardisation is a process of trying to meet many requirements, and standard data models are inherently either very abstract or very comprehensive in the details. This results in several ambiguity pitfalls, inconsistent implementation of standard data models, which in turn hinders trust in the interoperability potential of standardised data, and complicates any integration processes. In practice profiling such standards is useful to overcome such issues to create more useful forms of standardised data for specific applications. However defining custom profiles typically requires a great deal of technical expertise in the underlying expression language of the standard. Maintaining access to this level of expertise is a challenge as profiles become outdated through the time and lose connection with the maintenance of the parent standard from which they originate. Therefore, in this paper, a scalable methodology is proposed, built on the OGC Building Blocks Model approach, that uses semantic modelling to support an easier composition of geospatial data models profiles which directly derive from available standards without losing the relevant dependencies that inform stakeholders which components are interoperable with other standards. The approach is tested within a digital building permit project (CHEK), in which data requirements derive from the semantics of city regulations and common geospatial standards (i.e., CityGML and INSPIRE) are used as reference.

Issues in Machine Translation with reference to the Story “Thakur ka kuan” by Munshi Premchand

This paper explores the issues encountered in machine translation, specifically using Google Translate, in translating Munshi Premchand's short story Thakur Ka Kuan ("Thakur's Well"). The study identifies key challenges, including the misinterpretation of cultural references, idiomatic expressions, and contextual meaning that are integral to Premchand's narrative style. Machine translation often produces literal translations that lack the nuance and emotional depth present in the original text, leading to misrepresentation of the story’s themes. For instance, socio-cultural terms and metaphors central to the story's message are frequently mistranslated or omitted entirely. The translation also struggles with maintaining consistency in tense and sentence structure, further diluting the narrative. This paper argues that while machine translation offers convenience for basic translations, it remains insufficient for complex literary works, where cultural, emotional, and contextual understanding is crucial. A comparative analysis with a human-translated version highlights these deficiencies and suggests that human input remains essential for accurate literary translations. The findings underscore the need for improved machine learning models to address these linguistic and cultural intricacies.

Pattern Recognition in the Processing of Electromyographic Signals for Selected Expressions of Polish Sign Language.

Gesture recognition has become a significant part of human-machine interaction, particularly when verbal interaction is not feasible. The rapid development of biomedical sensing and machine learning algorithms, including electromyography (EMG) and convolutional neural networks (CNNs), has enabled the interpretation of sign languages, including the Polish Sign Language, based on EMG signals. The objective was to classify the game control gestures and Polish Sign Language gestures recorded specifically for this study using two different data acquisition systems: BIOPAC MP36 and MyoWare 2.0. We compared the classification performance of various machine learning algorithms, with a particular emphasis on CNNs on the dataset of EMG signals representing 24 gestures, recorded using both types of EMG sensors. The results (98.324% versus ≤7.8571% and 95.5307% versus ≤10.2697% of accuracy for CNNs and other classifiers in data recorded with BIOPAC MP36 and MyoWare, respectively) indicate that CNNs demonstrate superior accuracy. These results suggest the feasibility of using lower-cost sensors for effective gesture classification and the viability of integrating affordable EMG-based technologies into broader gesture recognition frameworks, providing a cost-effective solution for real-world applications. The dataset created during the study offers a basis for future studies on EMG-based recognition of Polish Sign Language.

The Influence of Chinese and Western Cultural Differences on English Translation and Its Countermeasures

Abstract English plays an irreplaceable role as a bridge of global communication. However, the cultural differences between China and the West have a profound impact on English learning and translation practice, resulting in the reduction of semantic accuracy and information richness, which damages the effect of communication and restricts the style of translation. These cultural differences not only lead to understanding errors in the translation process, but also lead to the loss of cultural connotation, the conflict of expression and the mismatch of logical structure, thus increasing the complexity and challenge of English translation. To solve these problems, this paper suggests some strategies to alleviate the influence of Chinese and Western cultural differences on English translation, such as enhancing the training of cultural awareness, improving the accurate grasp of the context, flexibly adjusting the ways of language expression and optimizing the logical expression structure. In addition, it is emphasized that while mastering language skills, English learners should deeply understand and respect the cultural background of the source language and the target language, so as to improve the quality of translation and the effectiveness of communication. These measures will help English learners to translate and apply English more accurately and freely, not only in the literal sense of the language, but also in the cultural level.

Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships.

The traditional analytical framework taken by neuroimaging studies in general, and lesion-behavior studies in particular, has been inferential in nature and has focused on identifying and interpreting statistically significant effects within the sample under study. While this framework is well-suited for hypothesis testing approaches, achieving the modern goal of precision medicine requires a different framework that is predictive in nature and that focuses on maximizing the predictive power of models and evaluating their ability to generalize beyond the data that were used to train them. However, few tools exist to support the development and evaluation of predictive models in the context of neuroimaging or lesion-behavior research, creating an obstacle to the widespread adoption of predictive modeling approaches in the field. Further, existing tools for lesion-behavior analysis are often unable to accommodate categorical outcome variables and often impose restrictions on the predictor data. Researchers therefore often must use different software packages and analytical approaches depending on whether they are addressing a classification vs. regression problem and on whether their predictor data correspond to binary lesion images, continuous lesion-network images, connectivity matrices, or other data modalities. To address these limitations, we have developed a MATLAB software toolkit that supports both inferential and predictive modeling frameworks, accommodates both classification and regression problems, and does not impose restrictions on the modality of the predictor data. The toolkit features both a graphical user interface and scripting interface, includes implementations of multiple mass-univariate, multivariate, and machine learning models, features built-in and customizable routines for hyper-parameter optimization, cross-validation, model stacking, and significance testing, and automatically generates text-based descriptions of key methodological details and modeling results to improve reproducibility and minimize errors in the reporting of methods and results. Here, we provide an overview and discussion of the toolkit features and demonstrate its functionality by applying it to the question of how expressive and receptive language impairments relate to lesion location, structural disconnection, and functional network disruption in a large sample of patients with left hemispheric brain lesions. We find that impairments in expressive vs. receptive language are most strongly associated with left lateral prefrontal and left posterior temporal/parietal damage, respectively. We also find that impairments in expressive vs. receptive language are associated with partially overlapping patterns of fronto-temporal structural disconnection, and that the associated functional networks are also similar. Importantly, we find that lesion location and lesion-derived network measures are highly predictive of both types of impairment, with predictions from models trained on these measures explaining ~30-40% of the variance on average when applied to data from patients not used to train the models. We have made the toolkit publicly available, and we have included a comprehensive set of tutorial notebooks to support new users in applying the toolkit in their studies.

Language Profiles of School-Age Children With 16p11.2 Copy Number Variants in a Clinically Ascertained Cohort.

Individuals with proximal 16p11.2 copy number variants (CNVs), either deletions (16p11.2DS) or duplications (16p11.2Dup), are predisposed to neurodevelopmental difficulties and disorders, such as language disorders, intellectual disability, and autism spectrum disorder. The purpose of the current study was to characterize language profiles of school-age children with proximal 16p11.2 CNVs, in relation to the normative sample and unaffected siblings of children with 16p11.2DS. Standardized language tests were conducted in 33 school-age children with BP4-BP5 16p11.2 CNVs and eight unaffected siblings of children with 16p11.2DS to evaluate language production and comprehension skills across various language domains. A standardized intelligence test was also administered, and parents completed a standardized questionnaire to assess autistic traits. Language profiles were compared across 16p11.2 CNVs and intrafamilial pairs. The influence of nonverbal intelligence and autistic traits on language outcomes was investigated. No significant differences were found between children with 16p11.2DS and those with 16p11.2Dup, although both groups exhibited significantly poorer language skills compared to the normative sample and unaffected siblings of children with 16p11.2DS. Severe language deficits were identified in 70% of individuals with 16p11.2 CNVs across all language subdomains, with significantly better receptive vocabulary skills than overall receptive language abilities. In children with 16p11.2DS, expressive language deficits were more pronounced than receptive deficits. In contrast, only in children with 16p11.2Dup did nonverbal intelligence influence their language outcomes. The current study contributes to the deeper understanding of language profiles in 16p11.2 CNVs in a clinically ascertained cohort, indicating generalized deficits across multiple language domains, rather than a syndrome-specific pattern targeting specific subdomains. The findings underscore the importance of early diagnosis, targeted therapy, and monitoring of language skills in children with 16p11.2 CNVs. https://doi.org/10.23641/asha.27228702.

Research on Intelligent Mining Algorithm of English Translation Text Big Data Based on Deep Learning

This paper explores the translation of English texts by a deep learning algorithm, which aims to intelligently extract relevant records from a large corpus of English-translated texts, especially its shortcomings in processing difficult texts and dealing with long-term dependencies. This research integrates the modern long short-term memory (LSTM) network framework, with the aim of improving the accuracy and processing efficiency of the translation. Using a large number of experimental facts, these LSTM models are comprehensively learned and rigorously optimized. The traditional approach is to adapt the style to the language-specific properties of the translated text, and then use a bunch of evaluation metrics to evaluate the overall performance of the model across a large number of text types. The results of this study show that the method significantly speeds up the extraction and processing of information while maintaining the integrity at the translation level. In addition, the study reveals deep learning models’ ability to recognize complex contextual nuances and subtle formulations of language expression. The results of this research are multifaceted, bringing great improvements to device translation structures and facilitating the development of state-of-the-art text content analysis tools. These advances apply primarily to sectors of considerable statistical volume and complexity, including the criminal, scientific, and technological fields. Therefore, this study lays a foundation for future exploration of improving device understanding of language and automation of translation methods in various professional fields.

Grammatical systematicity of request models in the modern Russian

The article analyzes the grammatical systematicity of models of request expression in modern Russian language. The relevance is determined by the need to identify the grammatical systematicity of the use of syntactic models of different types in expressing a request in Russian speech practice. The aim of the paper is to study syntactic models of request expression in modern Russian language in the aspect of the theory of communicative-pragmatic complexes. The study is conducted on the material representing different contexts of request usage: samples from modern Russian plays by famous playwrighters – A. Vampilov, N. Lakutin, E. Shabalina and A. Yablonskaya, as well as samples from the National Corpus of the Russian Language (NCLR) are used. Research methods: systematic, comparative, functional, contextual, structural-grammatical. Special attention is paid to the phenomenon of systematicity of syntactic models. The peculiarity of expressing the request by the models of sentences on the purpose of utterance – inductive, interrogative and narrative – is shown. The authors come to the conclusion about the peculiarity of linguistic conceptualization of request in three communicative situations – everyday request, official request, request when communicating in an unfamiliar environment, which differ in their communicative role and situations of use. The regularities of use of three types of sentences on the purpose of utterance depending on communicative situations are established. It is shown that the model of inductive sentences serves as the basic and most common grammatical form of expressing a request and is usually used in the communicative situation of a household request. Due to its special communicative characteristics, this model can also be used in the situation of communication with strangers, and with the use of grammatical extensions - and in some situations of official communication. The second most frequent type - interrogative sentences - is usually used when addressing strangers; as a rule, it is accompanied by politeness markers. Models of narrative sentences are used much less frequently than sentences of the other two types; they are most often used in situations of official communication.

Challenges of Translating Idiomatic Expressions: A Cross-Linguistic Analysis at a University in Hanoi, Vietnam

This study investigates the challenges students face when translating idiomatic expressions between English and Vietnamese and explores how linguistic and cultural factors influence the translation process. Utilizing a combination of translation task analysis and focus group discussions, the research reveals that students frequently rely on literal translations, resulting in inaccurate or nonsensical outcomes due to their inability to grasp the figurative meanings of idioms. Cultural mismatches, particularly the absence of equivalent expressions in Vietnamese, further complicate translation efforts, leading to significant misunderstandings. Additionally, linguistic barriers, such as syntactic differences between English and Vietnamese, hinder students' ability to produce natural and accurate translations of idiomatic expressions. The findings emphasize the critical role of cultural knowledge and syntactic flexibility in effective idiomatic translation. To address these challenges, the study recommends that translation training programs place greater emphasis on idiomatic understanding and cross-cultural competence. This study contributes to the growing body of literature on idiomatic translation by highlighting the interplay of linguistic and cultural factors and suggesting strategies to enhance translation accuracy.