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Optimising RNA extraction for paddy bulk soil samples for metatranscriptome sequencing
Get PDFObjective: Extraction of high-quality RNA is crucial for understanding the molecular dynamics of microbiomes in the growth and development of paddy plants. However, paddy soil poses challenges due to contaminants such as humic substances and its clayish nature, which lead to RNA adsorption and reduced yield. This study aimed to improve existing RNA extraction methods for bulk soil samples collected from a paddy field in Perak, Malaysia. We first evaluated different published protocols, selected the best based on RNA yield and quality, and further optimized it for highly pigmented soil samples. The resulting RNA was subjected to metatranscriptome sequencing, de novo assembly and annotation. Results: Upon evaluation, the RNA extraction protocol by Peng et al., 2018 (method B3) was optimized by incorporating 20% and 30% PEG-based precipitation to remove carry-over pigmentation. Comparative testing showed that 20% PEG produced the highest quality RNA, yielding pigment-free RNA (> 100 ng/µl, integrity > 7, and A260/A280 of 2.02 ± 0.02). Metatranscriptome sequencing and analysis with Trinity, BUSCO, and Kraken2 confirmed superior quality and higher bacterial read assignment for RNA extracted with 20% PEG, highlighting its effectiveness for downstream microbial transcriptomic applications
Effects of low glucose microenvironment on the proliferation, migration and senescence of meniscus-derived stem cells
Get PDFMeniscus-derived stem cells (MeSCs) hold great promise for cytotherapy of the meniscus. Large-scale cell expansion in vitro is usually accompanied by decreased proliferation and migration and increased senescence, leading to a decrease in treatment efficiency. Therefore, the present study aimed to compare the effects of different concentrations of glucose on the proliferation, migration, senescence and protein expression of MeSCs. In this study, human MeSCs were cultured in two types of expansion media: low-glucose (LG) DMEM (5.5 mM glucose) and high-glucose (HG) DMEM (25 mM glucose). At specific passage number, the proliferation rate was evaluated by cell counting, the migration rate was evaluated by a scratch-wound assay, cell senescence was evaluated by β-GAL assays, and protein expression/phosphorylation was evaluated by ELISA. The results showed that a lower concentration of glucose promoted proliferation and migration, reduced cell senescence, and activated PI3K/Akt-related signaling pathways. This study provides a preliminary basis for the use of this medium composition for MeSC expansion
Integrating deep learning and machine learning for ceramic artifact classification and market value prediction
Get PDFThis study proposes an intelligent framework for the automated classification and valuation of ceramic artifacts, integrating deep learning and machine learning techniques. An improved YOLOv11 model was constructed to identify key ceramic attributes such as decorative patterns, shapes, and craftsmanship styles. The model achieved a mean Average Precision (mAP@50) of 70.0% and a recall of 91.0%, demonstrating strong capability in detecting complex visual features. Based on the extracted visual attributes, a Random Forest classifier was employed to predict price categories using multi-source auction data, achieving a test accuracy of 99.52%. Feature importance analysis further revealed manufacturing techniques and shape as key predictors of market value. The integrated framework effectively combines visual feature extraction and market-informed valuation, providing a scalable solution for intelligent ceramic appraisal and digital heritage curation. This approach supports both expert and non-expert applications, laying a foundation for future development of intelligent cultural heritage management systems
Effects of leaf ages, altitude and clone types on nutrient elements and antioxidant activity of tea (Camellia sinensis L. (O) Kuntze) in tropical conditions
Get PDFTea is a globally popular heritage beverage consumed by over three billion people. The unique taste and health benefits of tea are linked to its nutrient composition and antioxidant activity (AOA). As a plant species, tea's nutrient elements and AOA vary based on season, altitude, clone type and leaf age. This study examined the nutrient composition and AOA of young and mature tea leaves from four clones (BC1248, TRI2024, AT53 and TV9) grown at different altitudes under tropical conditions in Malaysia. The results demonstrated that altitude and clone type significantly influenced (p 0.05). On the other hand, foliar nutrient elements varied significantly among lowland tea clones, except for N and Ca. The highest AOA was recorded in young tea leaves of clone BC1248 at the lowland plantations, with total polyphenol contents (TPC), 2,2-diphenyl-1-picrylhydrazylradical (DPPH IC50), and ferric reducing antioxidant power (FRAP) values of 19.60 ± 0.15 mg GAE/g, 50.70 ± 1.86 µg/mL, 2.10 ± 0.14 mM Fe (II)/g, respectively. The DPPH IC50 and FRAP varied significantly (p < 0.05), except for TPC among the lowland and highland clones. Based on principal component analysis (PCA), we identified that the tropical lowlands of Malaysia were more suitable for growing tea with high AOA. These findings provide valuable insights for growers to develop sustainable tea farming strategies, ensuring optimal yield and targeted quality under tropical conditions
Cutting-edge cooling techniques for photovoltaic systems: a comprehensive review
Get PDFThe efficiency of photovoltaic (PV) systems is often limited due to surface temperature increases, which result from absorbed solar energy being converted into heat. This rise in temperature reduces power output, system performance, and panel lifespan. To address these challenges, combined photovoltaic thermal (PVT) systems have emerged, enabling the simultaneous generation of electricity and thermal energy. This review provides a detailed analysis of the factors affecting PV panel efficiency, explores various feasible cooling techniques including innovative methods to mitigate excessive heating, and highlights opportunities for future research in this field. The article focuses on the experimental and theoretical advancements in PV cooling over the past decade, offering valuable insights and practical guidelines for researchers aiming to improve PV module cooling strategies. Additionally, an economic assessment of PVT systems is conducted, evaluating their financial feasibility in terms of payback periods and costs. The review also presents a comparative analysis of PVT techniques, addressing their benefits, challenges, and potential applications. This work aims to serve as a comprehensive resource for researchers exploring the viability and industrial applications of PVT systems, paving the way for more efficient and sustainable solar energy solutions
Combined effects of constant temperature and radio frequency exposure on Aedes mosquito development
Get PDFMosquito-borne diseases, such as dengue, Zika, and chikungunya, pose significant public health threats, particularly in tropical regions like Malaysia. Aedes aegypti and Aedes albopictus are primary vectors of these diseases, with their developmental stages being highly sensitive to environmental factors. While temperature is a well-known driver of mosquito biology, the potential influence of anthropogenic factors such as radio frequency (RF) exposure remains underexplored. This study investigates the combined effects of temperature and RF exposure on the developmental stages of these mosquito species to provide insights into their population dynamics and inform vector control strategies. A factorial experimental design was employed, incorporating four temperature conditions (20 °C, 25 °C, 30 °C, and 35 °C) and three RF exposure levels (900 MHz, 18 GHz, and a control group with no RF exposure). The developmental durations for hatching, larval, pupation, and adult emergence stages were monitored daily under controlled laboratory conditions. Data were analyzed using a quadratic response surface model to evaluate the main effects and interactions between temperature and RF exposure. Temperature emerged as the dominant factor influencing developmental durations, with optimal conditions observed at 30–32 °C. RF exposure, particularly at 18 GHz, acted as a secondary modulating factor, accelerating developmental stages under certain temperature conditions. Ae. aegypti exhibited greater sensitivity to temperature changes compared to Ae. albopictus, which displayed higher adaptability and resilience to environmental variations. Interaction effects were most evident at intermediate temperatures (25–30 °C), where RF exposure synergistically reduced developmental durations. However, extreme RF exposure levels and suboptimal temperatures prolonged developmental periods. This study highlights the critical role of temperature in mosquito development while identifying RF exposure as a potential modulator under specific conditions. The findings underscore the importance of considering both environmental and anthropogenic factors in vector management strategies. Future research should explore the molecular mechanisms underlying these interactions to refine predictive models and enhance vector control efforts in rapidly urbanizing regions
University english teaching evaluation using artificial intelligence and data mining technology
Get PDFThis work intends to drive reform and innovation in English teaching evaluation and support personalized English instruction. It utilizes deep learning (DL) and artificial intelligence (AI)-driven data mining technology to explore a reliable and efficient method for university English teaching evaluation. By employing DL, this work explores innovative English teaching models and introduces a Bayesian framework to enable personalized teaching strategies. In the data mining process, the Transformer architecture is applied to English teaching evaluations. This capitalizes on its powerful feature extraction and sequence modeling capabilities to gain a comprehensive understanding and precise evaluation of students’ English proficiency. Additionally, an AI-based method for English teaching evaluation is proposed. Data from the English teaching and evaluation system for Computer Science students in the 2018 class at Tianjin University of Science and Technology are collected, analyzed, and processed. Group profiles of students are created to predict exam outcomes. The findings show that over 70% of students engage in active English learning only occasionally, with a higher proportion among females. More than 80% of males recognize the importance of listening and speaking skills, a sentiment shared by over 90% of female students. In terms of factors influencing students’ passing exams, scores in various question types play a central role, significantly impacting final grades. These scores reflect students’ mastery of English knowledge and application abilities. This work applies the Transformer architecture from natural language processing to the education domain, achieving interdisciplinary integration and innovation. This cross-disciplinary approach not only enriches teaching assessment methods but also provides new solutions for broader educational challenges. The proposed method enhances the objectivity and accuracy of teaching evaluation, minimizing the influence of human bias assessment results
Navigating the shadows: the impact of mindfulness, cognitive fusion, and coping strategies on psychological distress among mental health workers in Timor Leste
Get PDFBackground: Mental health workers in post-conflict settings such as Timor Leste face distinct stressors stemming from limited human resources, underdeveloped systems, and ongoing socio-political instability, all of which increase the risk of psychological distress among these professionals. Consequently, constructs such as mindfulness, cognitive fusion, and coping strategies are essential not only theoretically significant, but also serve as practical targets for strengthening mental resilience of these professionals in these high-burden environments. This study aims to investigate the relationships between mindfulness, cognitive fusion, coping strategies, and psychological distress (depression, anxiety, and stress) among mental health workers in Timor Leste. Methods: A cross-sectional study design was employed, involving a convenience sample of 37 mental health workers from PRADET and the national referral hospital in Dili. Mindfulness was assessed using the Toronto Mindfulness Questionnaire (TMQ), psychological flexibility using the Acceptance and Action Questionnaire (AAQ-II), cognitive fusion was measured using the Cognitive Fusion Questionnaire (CFQ), and coping strategies were evaluated using the DBT-Ways of Coping Checklist (DBT-WCCL). Depression, anxiety, and stress were measured using the Depression Anxiety Stress Scales (DASS-21). All scales were using English validated versions. Descriptive statistics, Pearson correlation coefficients, and multiple regression analyses were used to analyze the data. Results: Significant positive correlations were found between Depression and Anxiety (Spearman’s rho = 0.649, p < 0.001), and between Depression and Stress (Spearman’s rho = 0.753, p < 0.001). Depression was also significantly correlated with Cognitive Fusion (Spearman’s rho = 0.445, p = 0.006) and Blaming Others (Spearman’s rho = 0.422, p = 0.009), and negatively correlated with Coping Strategies (Skills Use) (Spearman’s rho =– 0.341, p = 0.039). Anxiety and Stress were highly correlated (Spearman’s rho = 0.855, p < 0.001), and both were significantly associated with Cognitive Fusion, General Dysfunctional Coping, and Blaming Others. Mindfulness (De-Centering) showed a strong positive correlation with Mindfulness (Curiosity) (Spearman’s rho = 0.770, p < 0.001), and was also weakly associated with General Dysfunctional Coping (Spearman’s rho = 0.343, p = 0.038). Overall, the results suggest that higher levels of depression, anxiety, and stress are linked to greater cognitive fusion and dysfunctional coping, while effective coping skills are negatively associated with depression. Conclusion: The findings highlight the critical roles of cognitive fusion and coping strategies in predicting psychological distress among mental health workers in Timor Leste. Cognitive fusion and dysfunctional coping strategies were associated with higher levels of depression, anxiety, and stress. Adaptive coping strategies, such as skills use, were linked to lower levels of depression. Given the high risk of vicarious trauma, compassion fatigue, and secondary traumatic stress disorder in this population, targeted interventions promoting mindfulness and adaptive coping skills are essential. Addressing these factors can enhance resilience and well-being among mental health professionals, ultimately improving the quality of care provided to their clients
Influence of short video content on consumers purchase intentions on social media platforms with trust as a mediator
Get PDFShort videos on social media platforms have boomed with the rapid growth of the video consumption industry and have become an important marketing tool for businesses. With the rise of platforms such as TikTok or Douyin, short videos have profoundly impacted consumer behavior, making it crucial to understand their role in shaping consumer purchase intention. However, there is still a need for further research on how short video content promotes consumer purchase intent. Based on the Stimulus–Organism–Response (SOR) model, this study constructs a structural model to explore the impact of short video content on consumer purchase intention, focusing on the mediating role of consumer trust. The model incorporates usefulness, ease of use, and entertainment as external stimuli, consumer trust as internal psychological responses, and purchase intention as the final behavioral outcome. This study collected 372 valid data from Chinese consumers through an online questionnaire and empirically analyzed it using structural equation modeling. The study results show that short-form video content’s usefulness, ease of use, and entertainment significantly affect consumers’ trust and purchase intention. Moreover, consumer trust positively affects purchase intention and mediates the relationship between short video content and purchase behavior. This research extends the application of the SOR model to the context of social media short videos, highlighting the crucial role of consumer trust in shaping consumer purchase decisions. Based on these findings, we propose actionable strategies for businesses to optimize short video content and build consumer trust, ultimately enhancing marketing effectiveness and driving consumer purchases