Abstract Background Internet of Things (IoT) is growing exponentially and can become an enormous source of information. IoT has provided new opportunities in different domains but also challenges are apparent that must be addressed. Little attention has been paid to the potential use of IoT in the food safety domain and therefore the aim of this study was to fill this gap. Scope and approach This paper reviews the use of IoT technology in food safety. A literature review was conducted using academic documents written in English language and published in peer-reviewed scientific journals. The relevant articles were analysed using the bibliometric networks to investigate the relationships between authors, countries, and content. Key findings and conclusions IoT in food safety is a relatively new approach; the first article appeared in 2011 and has increased since then. Majority of these studies were performed by Chinese universities and the main IoT applications reported were on food supply chains to trace food products, followed by monitoring of food safety and quality. The vast majority of publications were related to food, meat, cold chain products and agricultural products. These studies used sensors to monitor mainly temperature, humidity, and location. The most frequently used communication technologies were Internet, radio frequency identifications (RFID) and wireless sensor networks (WSN). This article identifies knowledge gaps to inform the community, industry, government authorities about research directions for IoT in food safety.
AimHypertension is a major risk factor for cardiovascular and cerebrovascular diseases and may lead to serious health outcomes such as stroke, myocardial infarction, heart failure, and renal failure. Essential hypertension (EH) accounts for approximately 90% of all hypertension cases. In this study, we applied a network meta-analysis (NMA) to quantitatively synthesize evidence from randomized controlled trials (RCTs) and to compare and rank the effects of mind–body therapies (MBTs) on systolic and diastolic blood pressure in patients with EH, with the aim of providing evidence to support informed selection of MBT interventions.MethodsA comprehensive search strategy restricted to English-language RCTs was developed and applied across multiple biomedical databases, including PubMed, Embase, the Cochrane Library, Web of Science, CBM, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP, from database inception to March 2, 2025. (The literature found in the Chinese database did not meet the requirements.) Two authors independently screened studies, extracted data, and performed a frequentist network meta-analysis using STATA version 18.0 to compare and rank MBTs with respect to their effects on systolic blood pressure (SBP) and diastolic blood pressure (DBP). Methodological quality of the included studies was assessed using the Cochrane Risk of Bias tool. Additional analyses were conducted to evaluate network consistency and robustness of the findings.ResultsA total of 15 RCTs involving 949 participants were included, comprising 18 intervention arms and 11 distinct MBT interventions. While most MBTs demonstrated some degree of blood pressure–lowering effect, SUCRA values indicated that Bhramari Pranayama (BP; SUCRA = 75.3%) and Specific Qigong (SQ; SUCRA = 73.7%) had the highest probabilities of ranking among the more effective interventions for reducing SBP. For DBP reduction, Sound Relax Meditation (SRM; SUCRA = 83.0%), Specific Qigong (SQ; SUCRA = 80.2%), and Bhramari Pranayama (BP; SUCRA = 78.1%) showed relatively favorable rankings. These rankings represent relative probabilities and should be interpreted in conjunction with effect sizes and the overall certainty of evidence.ConclusionCompared with other MBTs, Bhramari Pranayama and Specific Qigong demonstrated more favorable relative effects on systolic blood pressure in patients with essential hypertension. Sound Relax Meditation, Specific Qigong, and Bhramari Pranayama showed comparatively better performance in reducing diastolic blood pressure. Given the limited number of studies and modest sample sizes, these findings should be interpreted cautiously, and further large-scale, high-quality RCTs are needed to confirm these comparative effects.
Diseases of the circulatory (Cardiovascular) system
Adolescence is a critical period for brain development, yet the impact of peer environments on brain structure, cognition, and psychopathology remains poorly understood. Here, we capitalized on data from 7806 adolescents (age = 12.02 ± 0.67) from the Adolescent Brain Cognitive Development (ABCD) study, to determine associations between two distinct peer environments (proportion of prosocial or delinquent friends) and the structural and functional architecture of the brain, cognition, as well as behavioral and emotional dysregulation. A higher proportion of prosocial friends was associated with fewer behavioral problems and larger fronto-cingulate and striatal regions. In contrast, a higher proportion of delinquent friends was linked to increased behavioral problems, lower neurocognitive performance, and decreased functional connectivity in the default-mode and fronto-striato-limbic circuits, which spatially overlapped with external dopamine density maps. Moreover, the associations between prosocial friends and behaviors were mediated by brain volumes (e.g., pallidum), while the associations between delinquent friends and behaviors were primarily mediated by fronto-striato-limbic connectivity. Prosocial friends also attenuated the development of internalizing problems, whereas delinquent friends promoted externalizing symptoms. These findings underscore the profound influence of peer environments on adolescent brain development and mental health, highlighting the need for early interventions to promote resilience and healthy neuro-maturation.
Laos–China relations have evolved for centuries, beginning with a tributary system that established economic and security interdependence. Although political ties were disrupted during the French colonial period and the Cold War, cross-border trade and social interactions persisted. Since the normalization of relations in the 1980s, cooperation has deepened and reached a new phase through the Laos-China High-Speed Railway, a flagship project under the Belt and Road Initiative (BRI). Using a qualitative historical approach, this study examines how the Kunming-Vientiane High-Speed Railway illustrates the historical continuity and asymmetric nature of the bilateral relationship. The findings indicate that while the project enhances connectivity and supports Laos’s aspiration to become a ‘land-linked country’, it also reinforces China’s dominant position in financing, technology, and regional influence. Despite concerns about long-term dependency, the partnership remains mutually beneficial, demonstrating how BRI projects shape the dynamics between major and small states in Southeast Asia.
A large body of research literature in China has been concerned with English Translation of The Analects of Confucius, but few have systematically reviewed the published articles to identify current research focuses and gaps. To address this need, the study applies a bibliometric analysis of 392 research articles from China National Knowledge Infrastructure (CNKI), critically examining the existing research to reveal research trends and methodological challenges. The study conducts an integrated approach of tiered keyword network analysis differing high-quality Chinese Social Sciences Citation Index (CSSCI)-indexed articles from general publications and a subsequent hierarchical clustering for more precise research clusters. Synthesizing the results, it finally identifies three major research thematic areas: translation studies of specific translators, studies of core Confucian concepts as well as ideological studies, which reflects a trend of development from language transformation to a broader discussion of culture, ideology, and philosophy. Based on these findings, the study suggests an underdeveloped area of the integration of emerging theoretical frameworks and technical innovations into translation studies. By locating Chinese scholarship within a global context, this study offers methodological insights and guidance for future research on cross-linguistic studies concerning The Analects of Confucius.
IntroductionAn AI-assisted deep learning strategy was applied to analyze the neurobiological characteristics of depression in mouse models. Integration of weighted gene co-expression network analysis (WGCNA) with the random forest algorithm enabled the identification of critical genes strongly associated with depression onset, offering theoretical support and potential biomarkers for early diagnosis and precision treatment.MethodsGene expression data from depression-related mouse models were obtained from public GEO datasets (e.g., GSE102556) and normalized using Z-score transformation. WGCNA was employed to construct gene co-expression networks and explore associations between modules and depression-like behavioral phenotypes. Depression-related gene modules were identified and subjected to feature selection using the random forest model. The biological relevance of selected genes was further assessed, and model accuracy was validated through performance evaluation.ResultsOur findings revealed significant differential expression of genes such as Oprm1, BDNF, Tph2, and Zfp769 in the depression mouse model (p < 0.05). Notably, Oprm1 exhibited the highest feature importance, contributing to a model accuracy of 94.5%. Gene expression patterns showed strong consistency across the prefrontal cortex (PFC) and nucleus accumbens (NAC).ConclusionThe combined application of machine learning and transcriptomic analysis effectively identified core neurobiological genes in a depression model. Genes including Oprm1 and BDNF demonstrated functional relevance in modulating neural activity and behavior, offering promising candidates for early diagnosis and individualized treatment of depression.
Place names is one of the significant windows to understanding and exploring different language, different culture and different social development of a re-gion. In recent years, the naming, renaming, using and cultural protection of place names have increasingly attracted public attention, with relevant national and provincial laws being enacted one after another. This study centers on op-timizing the application of Pinyin in the standardization practices, with par-tic-ular emphasis on three critical dimensions. Additionally, in special cities mat-ters concerning the addition and modification of existing place names also de-serve our attention. Finally, the study proposes three suggestions: encourag-ing citizens to participate in policy-making, improving legal regulations for place names through moderate pilot programs, as well as strengthening the protec-tion of cultural heritage.
Badr AlKhamissi, Greta Tuckute, Yingtian Tang
et al.
Large language models (LLMs) exhibit remarkable similarity to neural activity in the human language network. However, the key properties of language shaping brain-like representations, and their evolution during training as a function of different tasks remain unclear. We here benchmark 34 training checkpoints spanning 300B tokens across 8 different model sizes to analyze how brain alignment relates to linguistic competence. Specifically, we find that brain alignment tracks the development of formal linguistic competence -- i.e., knowledge of linguistic rules -- more closely than functional linguistic competence. While functional competence, which involves world knowledge and reasoning, continues to develop throughout training, its relationship with brain alignment is weaker, suggesting that the human language network primarily encodes formal linguistic structure rather than broader cognitive functions. We further show that model size is not a reliable predictor of brain alignment when controlling for feature size and find that the correlation between next-word prediction, behavioral alignment and brain alignment fades once models surpass human language proficiency. Finally, using the largest set of rigorous neural language benchmarks to date, we show that language brain alignment benchmarks remain unsaturated, highlighting opportunities for improving future models. Taken together, our findings suggest that the human language network is best modeled by formal, rather than functional, aspects of language.
According to Futrell and Mahowald [arXiv:2501.17047], both infants and language models (LMs) find attested languages easier to learn than impossible languages that have unnatural structures. We review the literature and show that LMs often learn attested and many impossible languages equally well. Difficult to learn impossible languages are simply more complex (or random). LMs are missing human inductive biases that support language acquisition.
Oral English competence is crucial for the learners’ life and potential professional success. Numerous studies on communicative language teaching were conducted; however, there is a dearth of literature on the application of CLT strategies in Chinese vocational colleges. The objective of this study was to identify CLT techniques that can improve the oral English skills of vocational college students in China. Specifically, it sought to answer the following: (1) What CLT strategies can be adapted for improving the oral proficiency of Chinese vocational college students? (2) What activities can be designed integrating adapted CLT strategies to help enhance Chinese vocational college students’ oral proficiency? The study made use of a developmental research design using systematic document analysis as the method. Findings showed that group-oriented CLT strategies like role-play, pair and group work, interviews, information gap activities, etc., and individual-oriented CLT tactics like storytelling, picture description, and opinion-sharing activities can be adapted to improve Chinese vocational college students’ oral proficiency. To help enhance Chinese vocational college students’ oral proficiency, communicative language activities that integrate these identified CLT strategies were designed as instructors’ guide in implementing CLT. Teachers are the primary change agents in educational practice, only by being more aware of what is truly going on in their classrooms can they assist students to achieve their learning goals. In the hands of a well-balanced instructor, CLT can breathe new life and enthusiasm into the classroom and truly make a difference in enhancing student’s oral proficiency.
BACKGROUND Over the past several decades the prevalence of adolescent non-suicidal self-injury (NSSI) has been rising steadily. Understanding the factors associated with NSSI is a critical public health concern. The current study aims to explore the critical factors related to NSSI among Chinese adolescents. METHODS A systematic literature search was conducted to identify the studies meeting our eligibility criteria (published until June 2022) in PubMed, Web of Science, Science Direct, Springer Link, CNKI, VIP, and Wanfang data. The meta-package of R language was used to perform a meta-analysis to compute the pooled effect (r). RESULTS A total of 59 studies were included in this analysis, with a sample size of 192,546. Twenty-four democratic, personal, and social factors were examined in current study. The pooled effect value (r) has revealed that 23 factors are associated with NSSI behaviors among Chinese adolescents. The factor, Internet addiction, has demonstrated the greatest association with NSSI compared to other factors. CONCLUSION Consistent with previous studies on adolescent NSSI, findings have demonstrated that a number of demographic, personal, and social factors significantly contribute to NSSI behaviors among Chinese adolescents. Future research on prevention and intervention for adolescent NSSI may benefit from targeting these factors.
Abstract The Chinese language is known for its resistance to lexical borrowing. Transliterations can hardly be retained in this language that use pre-existing characters to simply transcribe the pronunciation of the source word in the donor language. This exclusion can be attributed to the ideographic nature of Chinese characters. Given the stable graphic-meaning correspondence, novel use of characters is expected to be consistent with their usage in previous literature, while the association between the graphic form and the phonetic form has always been loose, rendering it meaningless to use characters as a mere phonetic representation. Here writing is having an effect on the assimilation of loanwords, and more generally, the purist language ideology, which runs counter to the traditionally assumed derivative position of writing, thus shedding light on the implicit effect of writing on language ideology.
History of scholarship and learning. The humanities, Social Sciences
Ziyi Zhang,1,2,* Lili Yin,2,* Jingjie Huang,1,2,* Qiuxuan Wang,1,2 Shanshan Sun,1,2 Shuoshuo Tan1,2 1Tianjin University of Traditional Chinese Medicine, Tianjin, 300000, People’s Republic of China; 2National Clinical Research Center of Chinese Medicine Acupuncture, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lili Yin, National Clinical Research Center of Chinese Medicine Acupuncture, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, People’s Republic of China, Email kintelili@163.comObjective: This study aims to explore the research landscape, hot topics, and future trends of non-pharmacological therapies for post-stroke spastic paralysis globally from 2000 to 2024 through a bibliometric analysis.Methods: We conducted a search in the Web of Science Core Collection database to analyze literature related to non-pharmacological therapies for post-stroke spastic paralysis published between 2000 and 2024. Tools including CiteSpace, VOSviewer, Bibliometrix, Scimago, and R language were used to identify and analyze countries, institutions, journals, references, keywords, as well as the most commonly used therapies and acupuncture points. The results were presented in the form of knowledge maps.Results: The bibliometric analysis identified a total of 297 publications. Over the study period, the number of publications showed an overall upward trend. China had the highest number of publications. The journal *Archives of Physical Medicine and Rehabilitation* published the most articles. The most frequently occurring keywords were “stroke”, “reliability”, and “muscle spasticity.” The most commonly used therapy was “acupuncture.”.Conclusion: From 2000 to 2024, non-pharmacological therapies have shown positive effects in improving post-stroke spastic paralysis; however, more rigorously designed large-scale, high-quality randomized controlled trials are needed to confirm their long-term efficacy and mechanisms. Moving forward, international and domestic research institutions should strengthen collaboration to produce more impactful research and further explore individualized, precision rehabilitation treatment plans.Keywords: stroke, spasticity, non-pharmacological, global trends, bibliometric analysis
BackgroundObstructive sleep apnea-hypopnea syndrome (OSAHS) is correlated with metabolic deterioration in patients experiencing polycystic ovary syndrome (PCOS). Women diagnosed with PCOS exhibit a heightened prevalence of OSAHS. This meta-analysis aims to assess the morbidity of OSAHS in women affected by PCOS and to examine the differences in metabolism-related indicators between OSAHS-positive and OSAHS-negative in women with PCOS.MethodsA comprehensive literature analysis of OSAHS morbidity in women with PCOS was conducted, utilizing databases such as CNKI, EMBASE, PubMed, Web of Science, and Wanfang. A comparison was carried out between patients with OSAHS-positive and those with OSAHS-negative in terms of their clinical characteristics and metabolic differences. The search language included English and Chinese. The acquired data were analyzed by employing RevMan 5.2 and Stata 11.0. Continuous variables with the same units were combined and analyzed through weighted mean differences (WMDs) as effect sizes, while continuous variables with different units were combined and analyzed through standardized mean differences (SMDs) as effect sizes. A conjoint analysis was performed on the basis of I2 value, using either a fixed effect model (I2 ≤ 50%) or a random effect model (I2 > 50%).ResultsA total of 21 articles met the inclusion criteria for this study. The findings indicated that 20.8% of women with PCOS were found to have comorbid OSAHS. The subjects were categorized into various subgroups for meta-analysis on the basis of race, age, disease severity, body mass index (BMI), and diagnostic criteria of PCOS. The results revealed high morbidity of OSAHS in all subgroups. In addition, most metabolic indicators and parameters of metabolic syndrome were notably worse in women suffering from both PCOS and OSAHS in comparison to their counterparts solely diagnosed with PCOS.ConclusionThe current literature indicates higher morbidity of OSAHS among women with PCOS, linking OSAHS with worse metabolic status and obesity in this population. Consequently, clinicians are advised to prioritize the detection and management of OSAHS in women with PCOS.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/#myprospero PROSPERO, identifier (CRD42024528264).
Diseases of the endocrine glands. Clinical endocrinology
Ancient Chinese is a splendid treasure within Chinese culture. To facilitate its compilation, pre-trained language models for ancient Chinese are developed. After that, researchers are actively exploring the factors contributing to their success. However, previous work did not study how language models organized the elements of ancient Chinese from a holistic perspective. Hence, we adopt complex networks to explore how language models organize the elements in ancient Chinese system. Specifically, we first analyse the characters’ and words’ co-occurrence networks in ancient Chinese. Then, we study characters’ and words’ attention networks, generated by attention heads within SikuBERT from two aspects: static and dynamic network analysis. In the static network analysis, we find that (i) most of attention networks exhibit small-world properties and scale-free behaviour, (ii) over 80% of attention networks exhibit high similarity with the corresponding co-occurrence networks, (iii) there exists a noticeable gap between characters’ and words’ attention networks across layers, while their fluctuations remain relatively consistent, and (iv) the attention networks generated by SikuBERT tend to be sparser compared with those from Chinese BERT. In dynamic network analysis, we find that the sentence segmentation task does not significantly affect network metrics, while the part-of-speech tagging task makes attention networks sparser.
This paper investigates the potential benefits of language-specific fact-checking models, focusing on the case of Chinese. We first demonstrate the limitations of translation-based methods and multilingual large language models (e.g., GPT-4), highlighting the need for language-specific systems. We further propose a Chinese fact-checking system that can better retrieve evidence from a document by incorporating context information. To better analyze token-level biases in different systems, we construct an adversarial dataset based on the CHEF dataset, where each instance has large word overlap with the original one but holds the opposite veracity label. Experimental results on the CHEF dataset and our adversarial dataset show that our proposed method outperforms translation-based methods and multilingual LLMs and is more robust toward biases, while there is still large room for improvement, emphasizing the importance of language-specific fact-checking systems.
Computational modeling plays an essential role in the study of language emergence. It aims to simulate the conditions and learning processes that could trigger the emergence of a structured language within a simulated controlled environment. Several methods have been used to investigate the origin of our language, including agent-based systems, Bayesian agents, genetic algorithms, and rule-based systems. This chapter explores another class of computational models that have recently revolutionized the field of machine learning: deep learning models. The chapter introduces the basic concepts of deep and reinforcement learning methods and summarizes their helpfulness for simulating language emergence. It also discusses the key findings, limitations, and recent attempts to build realistic simulations. This chapter targets linguists and cognitive scientists seeking an introduction to deep learning as a tool to investigate language evolution.
ABSTRACT Despite the promise of English language teaching and the use of English as a medium of instruction, concerns have been growing about the decline in the number of English majors as well as structural problems in elite language education reflected in the rural-urban divide and resulting educational gaps in China. The English education major at a top language-intensive university could serve as a key site for this investigation. However, existing literature has significantly overlooked this important area. This study explored the life course stages of Chinese students who were originally from rural areas or socioeconomically underrepresented regions/districts and majoring in English education at a top language-intensive university located in Shanghai. By adopting a critical narrative ethnographic approach, the authors wrote field notes and conducted in-depth interviews with 18 study participants. The findings showed that mothers’ involvement significantly influenced students’ motivation to learn English, college admission, and academic major choice. However, students also developed personal perceptions about career prospects while in college. By applying the Bourdieusian approach to language and symbolic power, this study interpreted participants’ developmental process of linguistic habitus and capital, regardless of their socioeconomic status. This study further interpreted their management of accumulated linguistic capital, while critiquing existing structural problems of the elite language education system, along with the English major crisis in the Chinese higher education system. As critical narrative ethnographers, the authors presented their reflexive turns on symbolic power and the future of English education in a Sino-Anglo context.
The internet is a valuable resource in a technologically evolved society. The extant literature suggests that their scientific and educational usages are still limited. The current study asserts that the internet can provide new learning environments and opportunities for Chinese university students, hence increasing their motivation to learn. Particularly, the current study considers this to be the case for learning a foreign language (English), which leads to more efficient and effective language learning experiences, as well as more positive attitudes toward the efficiency of the internet for educational purposes. Purposive and convenience sampling techniques were employed to gather data from 15 public and private Chinese universities (406 students), those who are currently enrolled in English language courses. The analysis was performed using partial least squares-structural equation modeling (PLS-SEM) on smart PLS 4 software. Results revealed that student’s attitude toward the use of internet positively and significantly influence English language learning. Moreover, the mediating variable academic self-efficacy positively and significantly mediates the relationship between students’ attitude toward use of internet and English language learning. The current study recommends that students’ academic self-efficacy in learning a new language can be enhanced by giving them opportunities to learn internet skills. Further, students’ confidence in their academic abilities can be boosted using student-centered teaching strategies.