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Deep Reinforcement Learning for Sustainable Urban Mobility: A Bibliometric and Empirical Review
Full text linkThis paper provides an empirical basis for a Computational Integration Framework (CIF), a systematic and scientifically supported implementation of artificial intelligence (AI) in smart city applications. This study is a methodological framework-with-validation study, where large-scale bibliometric analysis is used as a justification for design in the identification of strategically relevant urban areas rather than a single research study. This evidence determines urban mobility as the most mature and computationally optimal domain for empirical verification. The exploitation of CIF is realized using a DRL-driven traffic signal control system to show that bibliometrically informed domain selection can be put into application by way of an algorithm. The empirical results show that the most traditional control strategies accomplish significant performance gains, such as about 48% reduction in average wait time, over 30% increase in traffic efficiency, and considerable reductions in fuel consumption and CO2 emissions. A federated DRL solution maintains around 96% of central performance while still maintaining data privacy, which suggests that deployment in real-world situations is feasible. The contribution of this study is threefold: evidence-based domain selection through bibliometric analyses; introduction of CIF as an AI decision support bridge between AI techniques and urban application domains; and computational verification of the feasibility of DRL for sustainable urban mobility. These findings reveal policy information relevant to goals governing global sustainability, including the European Green Deal (EGD) and the United Nations Sustainable Development Goals (SDGs), and thus, the paper is a methodological framework paper based on literature and validated through computational experimentation
The Enemy Within: Work-Related Stress and the Education Crisis
No full textStress in the workplace has been recognised by the World Health Organization (WHO) as a global health epidemic. Research examining the most stressful industries to work in the UK consistently ranks education among the highest groups, encompassing early years practitioners to higher education academics. One of the most commonly reported contributory factors is poor work–life balance, with high levels of emotional exhaustion and depersonalisation—key components of burnout—endemic. Related research has highlighted unprecedented mental health difficulties among children and young people; while many educators feel ill-equipped to manage the levels of mental distress they encounter in the classroom and playground on a daily basis, contributing to their own diminished wellbeing. The current author posits that at the heart of a well-functioning learning environment is the holistic wellbeing of every member of the education community. This paper brings together evidence from across different levels of education to expose systemic failures to address work-related stressors, highlighting gaps in effective support mechanisms to meet the needs of both learners and educators. Philosophical questions concerning professional identities and the function of a contemporary education system with mental health on its agenda are considered. Finally, recommendations are put forward to help tackle the current crisis and curb the exodus of professionals from across the sector
Dietary Polyphenols as Modulators of Bifidobacterium in the Human Gut Microbiota
Full text linkBackground: Polyphenols—bioactive compounds abundant in plant-based foods—are increasingly recognised for their capacity to modulate the gut microbiota. As the gut microbiome plays a central role in metabolic regulation, immune function, and disease prevention, understanding how specific polyphenol subclasses influence microbial diversity and functionality remains essential. Despite growing evidence of their benefits, the precise effects of flavonoids, phenolic acids, and anthocyanins on gut microbial composition are not yet fully clarified. Objective: This study aimed to evaluate the impact of dietary polyphenols on gut microbiota composition and function, with a particular focus on the abundance of Bifidobacterium, a key beneficial genus associated with metabolic and immune health. It was hypothesised that polyphenol-rich interventions were associated with increases in Bifidobacterium abundance and enhance overall microbial diversity. Design: A systematic review and meta-analysis were conducted following PRISMA guidelines. Human intervention studies published between January 2015 and February 2025 were retrieved from PubMed, Scopus, and Web of Science. A predefined PICO framework guided study selection. Twenty-two studies were synthesised using thematic analysis, and four of these were eligible for quantitative meta-analysis. The meta-analysis was performed in R (version 4.4.1) using the metafor and meta packages, calculating standardised mean differences (SMD) under a random-effects model to account for heterogeneity. Extracted data included study design, population characteristics, polyphenol subclass, intervention type, microbiome assessment method, and key outcomes. Results: Across the 22 reviewed studies, polyphenols—particularly flavonoids and phenolic acids from foods such as berries, grape pomace, and green tea—consistently increased beneficial microbial taxa including Bifidobacterium, Faecalibacterium, and Lactobacillus. These microbial shifts were associated with improved metabolic markers, reduced inflammation, and enhancements in gut barrier integrity. Polyphenol-rich dietary patterns also showed benefits in conditions such as NAFLD, prediabetes, and depression. However, findings were influenced by interindividual variability, short intervention durations, and inconsistent methodologies. The meta-analysis revealed a significant positive effect of polyphenol intake on Bifidobacterium abundance (SMD = 0.81; 95% CI: 0.18–1.44; p = 0.0114), corresponding to a moderate-to-large effect size. Substantial heterogeneity (I2 = 77.4%) suggested considerable variation in intervention types, dosage, study design, and microbiome analysis methods. Conclusions: Polyphenol-rich diets were associated with increased Bifidobacterium abundance and favourable modulation of gut microbiota composition, supporting their potential as a nutritional strategy to enhance gut and metabolic health. However, interstudy variability highlights the need for more standardised, long-term, and mechanistically focused human trials. Future research should incorporate multi-omics approaches, personalised nutrition frameworks, and consistent microbiome analysis methods to better understand the pathways linking polyphenol intake and host health outcomes
Review of David Fraser, Nazi Antisemitism and Jewish Legal Self-Defense: The Turn to Law in Liberal Democracies, 1932–39 (Abingdon, Oxon: Routledge 2024)
No full text© 2025 Taylor & Francis. This is an author produced version of a paper published in Comparative Legal History uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it
Key Sources of Information and Support for Adults With Coeliac Disease: Coeliac Associations, Dietitians, Social Media and Cookbooks
No full textThere is variable and often inadequate access to dietitians with expertise in coeliac disease (CeD) and limited data on where patients access support for their only treatment: adhering to a gluten-free diet. This study aimed to provide an up-to-date report of where adults with CeD source useful information. A cross-sectional online survey was undertaken during 2024. The survey was designed by specialist dietitians and a gastroenterologist. Questions addressed diagnosis, demographics, sources of gluten‑free diet information, their perceived usefulness, and exposure to inaccurate information. Adults with CeD were recruited through a customer database of GF foods in the UK and via social media. Data from 675 adults with CeD showed that a high proportion rated information from coeliac associations (74%), peers with CeD (61%), cookbooks (56%), dietitians (50%), and the internet (52%) as highly useful, whereas only 15% reported information from General Practitioners (GPs) as highly useful. Among participants who regularly used social media (n = 360), 87% reported feeling connected to the CeD community; primary motivations for using social media were seeking peer support, gluten‑free recipes, information on new foods, dining options, and travel. However, nearly half (46%) indicated that they had received or accessed incorrect information via social media. Only 20% reported following a dietitian on social media. Coeliac associations remain a highly valued source of information and support. Social media is also widely used by adults with CeD, highlighting the need for greater dietitian engagement on these platforms as part of patient education and ongoing support. [Abstract copyright: © 2026 The Author(s). Journal of Human Nutrition and Dietetics published by John Wiley & Sons Ltd on behalf of British Dietetic Association.
Correction: Ali et al. Real-Time Recognition of NZ Sign Language Alphabets by Optimal Use of Machine Learning. Bioengineering 2025, 12, 1068
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CSR, firm financial performance and corporate life cycle: empirical evidence from china’s pharmaceutical industry
Full text linkThis paper examines the relationship between corporate social responsibility (CSR) performance and firm financial performance (FFP) across corporate life cycle (CLC) stages and different stakeholder groups for 210 Chinese pharmaceutical firms for the 2010–2018 period. The study employs a wide range of econometric models such as pooled ordinary least squares (OLS), fixed effects and random effects models using four different estimators to address endogeneity. Our findings indicate a strong association between CSR and FFP, particularly for shareholders. We observe a positive and significant relationship between overall CSR performance (inclusive of all stakeholders’ responsibility) and FFP across all CLC stages when return on equity (ROE) and return on assets (ROA) are applied. Also, we find that state-owned firms exhibit better CSR performance but are less efficient in terms of market and financial performance. The results of this study can inform and guide managers and investors on the effect of CLC stages and different stakeholders on firm performance
Promoting mental health among at-risk adolescents in Malaysia (MyHeRo): Study protocol for a cluster randomised controlled trial to evaluate the effectiveness and cost-effectiveness of a school-based intervention compared with study skills condition for adolescents identified as at risk for anxiety and depression
No full textBeliefs about the biological nature of mental disorders and how they affect antidepressant use and withdrawal
No full textDeep-Learning-Based Classification of Lung Adenocarcinoma and Squamous Cell Carcinoma Using DNA Methylation Profiles: A Multi-Cohort Validation Study
No full textBackground/Objectives: The precise classification of non-small-cell lung cancer (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) has important role in treatment decisions and in prognosis. Proper subtyping ensures that patients receive the most appropriate therapeutic strategies and allows clinicians to make informed evaluations regarding disease outcomes. This study presents a deep neural-network-based classification approach utilizing genome-wide DNA methylation profiles from the Illumina HumanMethylation450 BeadChip platform. Methods: A total of 5000 of the most discriminative CpG probes are identified through variance-based feature selection in the presented methodology, which are then classified through a five-layer deep neural network with batch normalization and dropout regularization. Training and validation were performed using data from The Cancer Genome Atlas (TCGA), with external validation conducted on two independent Gene Expression Omnibus (GEO) datasets: GSE39279 and GSE56044. Results: The model achieved 96.92% accuracy with an area under the receiver-operating characteristic curve (AUC-ROC) of 0.9981 on the TCGA test set. Robust generalization was obtained in cross-dataset validation experiments, with the GEO-trained model achieving 88.92% accuracy and 0.9724 AUC-ROC when validated on TCGA data. The most influential CpG biomarkers contributing to classification decisions are analysed using SHAP (Shapley Additive Explanations). Conclusions: These findings demonstrate the potential of DNA methylation-based deep learning approaches for reliable NSCLC subtype classification with clinical applicability