Large-scale molecular dynamics simulations illustrate that highly correlated cation–anion motion leads to negative t 0+ on the order of 1 in lithium electrolytes with star-shaped multivalent anions.

In older adults resting-state alpha power is associated with stronger effects of anodal tDCS over prefrontal cortex on dynamic balance.

The paper focuses on the L2 acquisition of Czech light verb constructions (LVCs) with the verbs have, do/make, get and give by Russian learners. It investigates the impact of collocation frequency and the strength of association of the collocates (measured using LogDice) on L1 interference and the acquisition process. The study is based on corpus data from Czech and Russian national corpora, which were used to identify the LVCs that may be problematic for Russian learners, either because of negative transfer from Russian, or due to their absence in L1. A collocation test including 30 sentences with potentially difficult LVCs was then presented to 33 Russian learners who were asked to supply the appropriate light verbs. The results show that the ease of acquisition of the LVCs, as well as the degree of interference, clearly depends on the frequency of collocations and the strenght of their association in the two languages.

At a time when bilingual education is being valued, the correlation between Chinese learning experience and English proficiency development is a hot research topic in the field of second language acquisition. This article is based on the theories of language transfer, cognitive development, and intercultural communication, and systematically explores the promoting effect of Chinese learning on the development of English proficiency from five dimensions. Research has found that the phonological perception, vocabulary construction thinking, and grammatical logic awareness cultivated through Chinese learning are the natural foundation of English learning; The core cognitive abilities formed, such as memory and logical thinking, can be directly transferred to English learning; The cultural accumulation in the Chinese context helps to understand the cultural connotations of English and enhance cross-cultural communication skills; The reuse of methods and strategies for learning Chinese can improve the effectiveness of English learning. Multiple educational practices and studies have shown that those with a solid foundation in Chinese have an advantage in English listening, speaking, reading, and writing abilities. The conclusion of this article provides theoretical and practical references for optimizing bilingual teaching and improving the quality of English teaching, as well as guidance for learners to enhance their English proficiency through Chinese language foundation.

This study explores the morphological deficits in a bilingual Sundanese-Indonesian patient diagnosed with mixed aphasia following typhoid meningitis. While previous research on aphasia has primarily focused on monolingual cases, this study addresses the complexities of bilingual language impairment, particularly in a language pair with typologically distinct morphological structures. The primary aim is to examine how aphasia affects the application of derivational and inflectional morphology, shedding light on cross-linguistic interference and compensatory strategies. This study employs a qualitative intrinsic case study approach analyzing speech samples elicited through spontaneous speech recording, observations, and in-depth interviews. The findings reveal two major patterns of morphological deviation: (1) misapplication of Indonesian and Sundanese affixation rules, resulting in hybrid morphological structures, and (2) systematic overgeneralization of reduplication patterns, leading to the emergence of novel linguistic formations. These errors highlight the impact of bilingual language competition on morphological processing in aphasia. The study concludes that bilingual aphasia induces a restructuring of morphological systems rather than mere attrition, with patients actively reconstructing linguistic forms through rule-based blending. These findings have significant implications for clinical linguistics and speech therapy, emphasizing the need for rehabilitation approaches tailored to bilingual aphasia.

To investigate the effects of the LEG structured curriculum model on the physical fitness of preschool children aged 3 to 6 years.A cluster random sampling method was employed to select a total of 221 preschool children as research subjects, comprising both experimental and control groups.The Chinese National Physical Fitness Standards (Preschool Section) were used to assess the physical fitness development levels of preschool children aged 3 to 6 years.The experimental results were statistically analyzed using independent samples t-tests and paired samples t-tests.After a 12-week experimental intervention, we found that: 1) The level of physical fitness development in young children showed an upward trend with increasing age.2) Both experimental and conventional curricula positively influence the physical development of children aged 3 to 6, but experimental curricula yield superior results compared to conventional ones.3) Gender differences exist in the physical fitness development of young children. Boys and girls in the experimental group showed greater improvements in physical fitness scores compared to the control group, without introducing new gender differences. Meanwhile, children in the control group exhibited more diverse gender differences than those in the experimental group.A 12-week intervention demonstrated that the LEG structured curriculum model significantly enhances physical fitness development in children aged 3 to 6 years without inducing new gender disparities. It is recommended that this course model be incorporated into the kindergarten outdoor activity curriculum system and promoted. Meanwhile, in the design and implementation of structured physical education programs, attention should not be limited to children’s age and gender differences, greater emphasis should be placed on the intrinsic connections and positive transfer between their fundamental motor skills, and systematically promote the development of children’s physical fitness.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-27908-8.

Automatic generation and transfer of Yongju opera language using AIGC technology and style mapping.

The future of drug research is intrinsically connected to the continuous advancement and prudent integration of Artificial intelligence (AI) and mathematics. By addressing challenges and leveraging possibilities, the pharmaceutical industry may fully harness the potential of AI to develop innovative and effective treatments for diverse diseases. In our opinion, finding new drugs takes long time and funds, and in the past, it was mostly done manually. AI has changed this sector completely, making drug manufacturing faster, cheaper, and more specific. This review presents the pertinent literature on drug discovery utilizing mathematical modeling and AI tools and methodologies implemented at every stage of drug development to expedite the research process and mitigate risk and costs in clinical trials, it also presents that how mathematical modeling and AI algorithms can be used together at several stages of drug development. There is a lot of focus on how mathematical frameworks like Linear Algebra, optimization, statistical modeling, graph theory and differential equations may operate along with the techniques of AI like machine learning (ML), deep learning (DL), reinforcement learning (RL), natural language processing (NLP) and transfer learning (TL) and the problems that are now being faced, the tools and datasets that are accessible, and what the future holds for this field, which is changing quickly.

This paper presents the modification and experimental validation of a mathematical model for a single junction thermal voltage converter (SJTC) designed for high-precision alternating current (AC) voltage transfer. The original model is severely constrained by two main issues: (1) computational instability above 50 MHz due to the limitations of the housing impedance approximation, and (2) insufficient accuracy above 1 MHz due to the neglect of high-frequency skin effect and magnetic core effects in the Dumet wire leads. Significant refinements are subsequently implemented to extend the calculable frequency range of the standard from 1 to 100 MHz. This required re-evaluation of the Dumet wire leads’ frequency-dependent resistance and inductance using finite element method (FEM) simulations, which accounted for the skin effect and the magnetic permeability of the FeNi42 core. Additionally, the housing impedance calculation is stabilized using a formulation based on scaled modified Bessel functions, and the electrical conductivity of the input N-type connector pin is explicitly modeled. The improved model is validated against a reference calorimetric thermal voltage converter (CTVC) using 3 and 5 V nominal voltage standards. The results indicated excellent agreement between the calculated and measured AC-direct current (DC) transfer differences up to 10 MHz. In the extended frequency regime, the model correctly predicted the transition to negative transfer differences observed above 2 MHz for the 5 V standard. The largest discrepancies between the measured and calculated values occurred at 100 MHz. The measured transfer difference reached −15,090 (µV/V) with an expanded uncertainty (k = 2) of 190 (µV/V), whereas the calculated value is −12,500 (µV/V) with an expanded uncertainty of 3900 (µV/V). Although the deviation between the model and measurement increased above 30 MHz, the results remained consistent within the expanded measurement uncertainties across the entire 10 kHz to 100 MHz range, demonstrating the model’s suitability for providing traceability in high-frequency voltage metrology.

Importance. The need to improve methodological approaches to teaching Russian pronunciation to Vietnamese students learning Russian as a foreign language is a promising research direction. A particular challenge for this category of learners is the intonation and rhythmic features of Russian speech, which differ from analogous characteristics in the Vietnamese language. The scientific and methodological rationale for using songs in pronunciation training remains insufficiently developed. Therefore, this work aims to investigate the features of Russian pronunciation and intonation that are particularly difficult for Vietnamese students and to develop an algorithm for organizing a Russian as a Foreign Language lesson using song materials and artificial intelligence technologies to optimize the Russian as a Foreign Language learning process. The objective of the study is to examine the didactic potential of songs in teaching pronunciation and to provide a rationale and methodological recommendations for the development and use of song materials and artificial intelligence technologies in teaching Russian as a Foreign Language to Vietnamese students, with the aim of improving their pronunciation and developing listening skills. Aim of the research is to identify the didactic potential of Russian-language songs in developing pronunciation skills among Vietnamese students and to substantiate methodological recommendations for their use in the Russian as a Foreign Language system. Tasks: 1) analyze the cross-linguistic differences between the Russian and Vietnamese phonetic systems; 2) identify the typical difficulties Vietnamese students face in perceiving and reproducing Russian intonation and rhythm; 3) characterize the didactic factors that facilitate and hinder the development of pronunciation skills when working with song material; 4) propose an algorithm for organizing an Russian as a Foreign Language lesson utilizing songs and artificial intelligence technologies. Research Methods. The content analysis of scientific literature on the problem, structural and semantic analysis of song texts from the point of view of their phonetic value are used (the study includes a selection of songs ( “Katyusha” , “Moscow evenings” , “Oh, frost, frost” , “Dark night” , “Oh, the viburnum blooms” , “I’m walking on Moscow” , “Kalinka” , etc.), their phonetic analysis (rhythm, intonation, stress), as well as pedagogical observation of students’ reactions), generalization and systematization of pedagogical experience. Results and Discussion. The analysis showed that the use of song material contributes to the development of the intonation-rhythmic component of pronunciation as a particular aspect of phonetic and phonological competence. Positive didactic factors were identified: authenticity (with simultaneous linguistic complexity), emotional involvement (despite possible interference of the native language), rhythmic organization (at the risk of distortion of prosodic models). Popular Russian songs (“Katyusha”, “Moscow evenings”, “How delightful evenings are in Russia”) with high potential for the development of auditory and pronunciation skills are considered as examples of song material. Based on them, exercises have been developed aimed at perceiving rhythmic patterns, working out reduction, accentuation and intonation patterns. Based on the proposed model, an algorithm for organizing Russian as a Foreign Language lesson using songs and artificial intelligence technologies has been developed, including the stages of goal setting, material selection and adaptation, task creation, visualization and control of results. Conclusion. The use of Russian songs in pronunciation training contributes to the formation of phonetic and phonological competence of Vietnamese students, the development of rhythmic, intonation and articulation skills, and also increases the motivation and involvement of students. The developed algorithm and methodological recommendations can be used both in pronunciation courses for students with tonal native languages, and in advanced training programs for Russian as a Foreign Language teachers.

To address the engineering challenge of detecting fine cracks on hybrid wind turbine towers, especially against complex water seepage backgrounds, this study aims to explore optimal image segmentation strategies. The core challenges of this task lie in the severe class imbalance caused by the extremely low pixel ratio of crack targets and the visual interference from seepage areas. To this end, a dedicated dataset for this specific scenario, named HTSCD, was first constructed. Subsequently, based on the U-Net segmentation model, this study systematically compared the effects of various combinations of data processing strategies (original, tiled, tiled and augmented) and loss functions (Cross-Entropy, Weighted Cross-Entropy, Dice Loss). Furthermore, to investigate the potential performance improvement from external data, the effectiveness of transfer learning using public crack datasets and programmatically synthesized data was also evaluated. The experimental results demonstrate that the combination of the tiled and augmentated dataset strategy and the Dice Loss function is the optimal solution for this task, achieving the best balance between precision and recall. A key finding is that conventional transfer learning strategies exhibited significant “negative transfer” in this task, where the introduction of external data impaired model performance. This research not only establishes an effective baseline solution for wind tower crack detection in this specific scenario but also provides important practical insights into the limitations of transfer learning for highly specialized visual inspection tasks.

In Vietnamese public schools serving ethnic minority learners, English language instruction often unfolds in linguistically complex and culturally mismatched classrooms. This narrative case study explores how one Vietnamese English as a foreign language (EFL) teacher responds to the challenges of teaching English to Khmer learners in a rural secondary school in the Mekong Delta. Drawing on a written reflection composed during a professional development course, the study examines how the teacher makes sense of her learners’ persistent grammatical difficulties, rooted in first language (L1) transfer from Khmer, and how she navigates the cultural dissonance between textbook content and learners’ lived experiences. Findings reveal that the teacher reframes language “errors” as patterned responses to structural distance, and that she enacts responsive teaching through chunk-based instruction, visual scaffolding, and culturally localized tasks. Her practice illustrates how small, context-driven adaptations are reconfigured when English is learned through Vietnamese by Khmer-speaking learners, making visible the interpretive work teachers do to turn structural distance into pedagogical resource. By foregrounding the voice of a teacher working in a triadic language environment (Khmer, Vietnamese, and English), the study theorises teacher responsiveness in such settings and offers an empirically grounded account of multilingual pedagogy and teacher agency in under-researched Southeast Asian classrooms.

In the context of globalization, English proficiency constitutes a crucial component of intercultural communication and educational competitiveness. However, Chinese primary English-as-a-Foreign-Language (EFL) classrooms have long disproportionately focused on segmental features at the expense of suprasegmentals such as rhythm, reduction, and connected speech(liaison). This study employs literature analysis and case analysis to explore how Mandarin transfer both facilitates and hinders children’s acquisition of English inter-word transitions. Furthermore, it investigates the localization of these theoretical insights into practical pedagogical designs. Findings from previous research indicate that connected speech can be explicitly taught through perception-to-production tasks, and that first language (L1)-based pre-task planning enables learners in allocating cognitive resources to pronunciation and prosody, thereby improving accuracy and fluency. Under the lens of superdiversity, this paper also emphasizes the pedagogical value of translanguaging, which legitimizes the strategic use of Mandarin as a pedagogical scaffold to enhance intelligibility and reduce learner anxiety. Synthesizing the reviewed evidence and case interpretation, a five-step pedagogical framework—contrast, annotate, L1 outline, shadow, and bilingual reflection—is proposed to integrate positive transfer and mitigate negative transfer in primary EFL contexts. The study aims to provide a theoretically grounded yet contextually adaptable framework for teachers seeking to enhance pupils’ connected-speech competence, particularly within the constraints of exam-oriented classrooms.

Learning a second or foreign language (L2/FL) involves mastering basic language skills, with writing being the most challenging and often problematic for L2 learners. Despite its importance, writing has historically been overlooked in L2 instruction (Carter & Nunan, 2001), even though it is regarded as one of the most difficult aspects of L2 learning (Hyland, 2004). Errors are considered inevitable and important in L2 learning (James, 2001), providing insight into what learners have or have not yet mastered. L2 learners often make errors in writing due to various factors, including negative transfer or interference from their first language (L1), which are classified as interlingual errors. In contrast, errors arising from a lack of knowledge of L2 rules are referred to as intralingual errors (Saville-Troike, 2008). This study aimed to identify errors in L2 English essay writing among students. Fifty-three students from a higher education institution training primary school teachers, who had taken English as a Foreign Language classes as part of their study programme, participated in the research. The students were tasked with writing a 350-word opinion essay on a specified topic. Quantitative and qualitative error analysis has revealed that the students made more interlingual than intralingual errors, with the most frequent errors involving articles, prepositions, spelling, and capitalisation. The study also found that although the first language was not the only source of errors, it still influenced the L2 English writing process. These findings align with other studies (e.g., Phuket & Othman, 2015; Patekar, 2017; Shakir, Rasool & Khan, 2020). The study results suggest that more practice in explicit L2 teaching and targeted instruction is needed to enhance students’ writing skills at the higher education level.

Background:Adverse drug reactions (ADRs) are harmful side effects of medications. Social media provides real-time, patient-generated data, though its unstructured format presents challenges. Natural language processing and transfer learning offer promising solutions.Objective:This study aimed to evaluate whether transformer-based models fine-tuned on a general ADR dataset can effectively classify ADRs from tweets related to glucagon-like peptide-1 (GLP-1) receptor agonists and to benchmark their performance against state-of-the-art large language models (LLMs).Design:This study employed a machine learning approach using transformer-based language models to classify ADRs in social media.Methods:BERT (bidirectional encoder representations from transformers)-base, BERTweet-base, and GPT-2 (Generative Pre-Trained Transformer-2) models were fine-tuned using Sarker and SIDER (Side Effect Resource) datasets for ADR classification. The test dataset comprised 396 tweets mentioning GLP-1 receptor agonists that were categorized as personal experiences. Model performance was primarily evaluated using the F1 score, which was used to select the optimal model. In addition, the fine-tuned transformer models were benchmarked against state-of-the-art LLMs, including ChatGPT 4o, ChatGPT 4o-mini, and Gemini 2.5 Flash.Results:Among 396 tweets, 116 (29.3%) were classified as ADRs and 280 (70.7%) as non-ADRs. Among the transformer-based models, BERTweet-base achieved the highest performance (accuracy: 0.835, F1: 0.729), outperforming both BERT-base (accuracy: 0.826, F1: 0.679) and GPT-2 (accuracy: 0.766, F1: 0.628). Among the LLMs, ChatGPT 4o-mini demonstrated the best results (accuracy: 0.970, F1: 0.948), followed by Gemini 2.5 Flash (accuracy: 0.954, F1: 0.919) and ChatGPT 4o (accuracy: 0.936, F1: 0.895). Overall, LLMs substantially outperformed the fine-tuned transformer-based models.Conclusion:Fine-tuned transformer-based models demonstrated reasonable performance in ADR detection from GLP-1 receptor agonist tweets, with BERTweet-base performing best. However, state-of-the-art LLMs, particularly ChatGPT 4o-mini, substantially outperformed these models, highlighting their potential for pharmacovigilance tasks.

Objective. To enhance the decoding accuracy and information transfer rate of steady-state visual evoked potential-based brain-computer interface (SSVEP-BCI) systems and to reduce inter-subject variability for broader SSVEP-BCI applications, a dual-channel TRCA-net (DC-TRCA-net) method is proposed, based on cross-subject positive transfer. The proposed method incorporates an innovative Transfer-Accuracy-based Subject Selection (T-ASS) strategy and a deep learning network integrated with the SSVEP Domain Adaptation Network (SSVEP-DAN) to enhance SSVEP-BCI decoding performance. The T-ASS strategy constructs contribution scores by computing each subject's self-accuracy and transfer accuracy, and enables effective source subject selection while mitigating negative transfer risks. DC-TRCA-net is further developed to improve model generalization through cross-subject data augmentation. The effectiveness of the proposed method is validated on two large-scale public benchmark datasets. Experimental results demonstrate that DC-TRCA-net outperforms existing networks across both datasets, with particularly substantial performance gains observed in complex experimental scenarios.

This study discusses the syntactic patterns of Pakistani English posts in social media and with focus and especially on Facebook posts by Pakistani university students. The purpose of the study is to name and discuss the most frequent grammatical mistakes in informal online communication. A sample of 30 Facebook posts was identified and analyzed on five significant syntactic properties namely use of articles, verb forms, parts of speech, capitalization and punctuation. The results indicate that punctuation errors were the most common then the article and capitalization mistakes, and errors of verb form and parts of speech were also frequent. These results show that even educated users are likely to disregard grammatical correctness in social media which indicates the power of informal first language interference and communication habits. This research contains the conclusion that Facebook promotes a casual style in writing in which there is breaking of grammatical rules. The study adds to the field of knowledge regarding the usage of English online in Pakistan and emphasizes the necessity of spreading grammar consciousness and syntactic accuracy even in informal writing on the Internet. The results can help linguists, educators and learners to enhance writing standards in academic and social mediums.

IntroductionPsychological issues continue to pose a critical influence on athletic performance as well as the wellbeing of collegiate-level athletes, as data suggests that one-third of male varsity-level athletes and half of those at the female varsity level experience anxiety and depression. A lack of assessment of the long-term effects of psychological intervention in a collegiate athletic setting, despite the recent realization of its importance, continues to pose a significant issue.MethodsThis randomized comparative effectiveness study, consisting of a sample of 324 student-athletes from a total of 12 higher education institutions, measured the differences between four psychological intervention groups that focused on attention training, cognitive restructuring, goal setting, as well as the regulation of emotions.ResultsResults of MANOVA analysis indicated that attention training (AT) had a greater enhancement in performance (d = 0.73) than cognitive restructuring (CR) (d = 0.56) and goal setting (GS) (d = 0.48). A large gender difference was observed, showing that female participants had greater improvement in emotional regulation (ER) (42.7% vs.31.4%) and psychological resilience (PR), and males had greater improvement in accuracy (36.2% vs.24.8%). Also, results of ANOVA analysis indicated a small regression in AT after 12 months ([3.2% in self-efficacy (SE), 4.3% in PR]), which was again affirmed by 12-month results ([Resilience:92% maintenance, anxiety reduction (AR):68%]). Moreover, AT results had a large positive transfer to academic performance (AP) (r = 0.43, p < 0.001), where self-regulation (SR) had the highest values as a mediator (β = 0.47).DiscussionPsychological integration in college-level PE lead to a large enhancement in athletic as well as academic performance. These results had a long-term positive persistence, which supports inclusion of systematic psychological skills training in athletic programs as a standard feature rather than a one-shot experience. Psychological intervention selection can be suggested according to target performance goals.

Ageing is associated with a loss of fluid intelligence and motor functions which hamper independence and quality of life. Training in a musical instrument can improve fluid intelligence and executive function (EF) in older non-musicians but the neural correlates underpinning the benefits remain elusive. The primary aims of this study are to: i) test the acceptability of Piano Instruction for Adult Novices as Online Cognitive Intervention (PIANO-Cog), a novel bespoke 8-week self-guided piano training programme for adults over the age of 50years; and ii) to test the feasibility (in terms of recruitment, retention and adherence) of a large scale RCT comparing PIANO-Cog to a passive control. Secondary aims of this study are: i) to investigate the effects of online piano training on fluid abilities, EF and motor function; ii) to investigate training-induced microstructural brain changes using ultra-strong gradient (300mT/m) magnetic resonance imaging (MRI) and iii) to investigate how the latter may be linked to cognitive improvements post-training. A two-armed unblinded RCT will be conducted on 50 healthy non-musician adults over the age of 50. Participants will be randomised to a piano training (PT) or passive control group for 8weeks, stratified for age and sex. PT participants will receive a training manual and 20-min video tutorials each week, and will practice 30min, 5days per week. Control participants will receive no intervention for the 8-week period. Cognitive testing and MRI of the brain will take place before and after the intervention. The primary aim of the trial is to determine the acceptability of PIANO-Cog as an online cognitive intervention for adults over 50 who are non-musicians, and the feasibility of conducting a large-scale RCT in terms of recruitment, retention and adherence. Self-guided music training programmes could provide a cost-effective method of maintaining or improving cognitive and motor functions that individuals can implement in their own homes. Secondary aims are regarding the investigation of positive transfer of piano training to EF and fluid abilities in ageing, and to provide evidence for the relationship between training-induced cognitive enhancements and underlying white and grey matter microstructural changes. ISRCTN11023869 (retrospectively registered). 20/10/2025 version 1.5.

The article presents a comprehensive analysis of language errors found in written texts in the Kazakh language (compositions, essays, dictations, and other written works). The study is based on a corpus approach and includes the classification of over 100 types of errors: orthographic, punctuation, grammatical, lexical, stylistic, and technical. The paper analyzes common writing errors occurring in the works of students of different age groups. The relevance of the study lies in the need for a systematic description and digital documentation of writing errors in Kazakh, which contributes to the creation of a specialized Error Corpus – a new research database designed to reveal the patterns of linguistic interference, features of linguistic worldview, and the dynamics of written language norms. The development of this corpus allows not only objective description of language deviations but also their cognitive and psycholinguistic interpretation. The research employs a comprehensive approach combining corpus linguistics and cognitive modeling methods. The results show that the most frequent errors are orthographic, lexical, grammatical, and punctuation errors, arising under the influence of Russian interference, cognitive information processing patterns, and automated speech templates. The obtained data form the foundation for the further development of the Kazakh Error Corpus and contribute to improving written language norms, teaching methodology, and diagnostic practices.