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Design and Biomechanical Evaluation of a Soft Lower Limb Exoskeleton for Elderly Assistance
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Beyond the ban: a theoretical framework for integrating Generative AI in assessment
No full textUniversities can neither ban nor ignore generative AI (GenAI); they must govern and design for it. This paper argues that the core challenge is not “cheating” per se but the misalignment between legacy assessment designs and AI-mediated learning. We contribute (1) a practical, tiered governance model that aligns policy, pedagogy, and assessment operations; (2) an assessment redesign heuristic that integrates authenticity, cognitive demand, and evidence provenance; and (3) a risk-mitigation view adapted from the Swiss-cheese model that places student learning, rather than surveillance, at the centre of integrity work. Building on recent philosophical critiques of instrumental responses to GenAI in education (Peters et al., 2024), we position assessment as a socio-technical system where teacher judgement, student agency, and tool affordances co-evolve. We illustrate the approach with ready-to-adopt patterns (e.g., oral defence with artefact trail; cohort-specific data briefs; constrained-tools practicals) and specify implementable governance levers (role clarity, template language, moderation workflows, analytics). The result is a coherent pathway “beyond bans” toward trustworthy assessment that is educative, fair, and feasible at scale
Health risk behaviours, mental health and HbA1c:an overview of reviews of observational studies
No full textOBJECTIVES: To implement an overview of reviews that discuss the current state of syntheses (such as systematic reviews) of only observational studies on health risk behaviours (HRBs), including smoking, alcohol intake, poor sleep, poor quality diet, common mental health problems (depression and anxiety), and glycated haemoglobin (HbA1c), while excluding synthesis of clinical trials.DESIGN: Overview of reviews or umbrella review following Preferred Reporting Items for Overviews of Reviews (PRIOR) guidelines.DATA SOURCES: PubMed, Scopus, Web of Science, PsycINFO-PsychArticles and Epistemonikos, searched from January 2013 to 30 June 2025.ELIGIBILITY CRITERIA: We included systematic reviews and meta-analyses of observational studies that assessed the relationship between HRBs-including smoking, alcohol intake, poor sleep, poor quality diet, physical activity and common mental health problems such as depression and anxiety-and HbA1c. Reviews of clinical trials were excluded.DATA EXTRACTION AND SYNTHESIS: We synthesised systematic reviews and meta-analyses on the above topic from five databases following the PRIOR protocol. Two independent reviewers screened titles, abstracts and full texts using standardised methods. Data extracted included study design, exposures, outcomes and population characteristics. Risk of bias was assessed using the AMSTAR-2 tool. Overlap across reviews was evaluated using the corrected covered area metric.RESULTS: Eight systematic reviews were included in the final synthesis, encompassing a total sample size of around 307 019 individuals. The study highlights a significant paucity of systematic reviews of observational studies in this area, with no reviews on alcohol and exercise. The existing evidence on poor sleep, poor quality diet and smoking points towards these HRBs leading to worse HbA1c. A bidirectional relationship was found between depression and HbA1c.CONCLUSIONS: This umbrella review highlights the significant association between HbA1c and key health risk factors underscoring the importance of observational studies, highlighting their ability to capture real-world conditions and complex interactions. While in agreement with existing study designs, this review provides convergent evidence of the critical role of HRBs in managing HbA1c levels.</p
Integrative Physiological Strategies for Monitoring Demands in Functional Fitness
No full textAn integrated physiological model would be useful for monitoring internal load in functional fitness, including formats like CrossFit and Hyrox. Traditional performance metrics often neglect internal strain, energy system engagement, and neuromuscular fatigue, central to these modalities. Oxygen uptake kinetics, metabolic profiling, heart rate and heart rate variability monitoring, and neuromuscular fatigue assessment can be employed for load monitoring. Breath-by-breath oxygen uptake analysis characterizes aerobic activation and recovery. Metabolic stress is estimated via indirect calorimetry and capillary blood lactate to quantify oxidative, glycolytic, and phosphagen contributions. Heart rate is tracked continuously to assess session intensity, while heart rate variability provides insights into autonomic recovery. Neuromuscular fatigue can be assessed via countermovement jump performance, offering sensitive measures of recovery and training tolerance. Portable tools such as the Cosmed K5 ™, Lactate Pro 2, heart rate sensors, and force platforms support real-time monitoring in training and competitions. Rather than advocating for the continuous use of advanced tools, the model promotes strategic integration of high-precision methods for research, and practical, low-cost alternatives (e.g., heart rate monitoring, session rating of perceived exertion, or jump analysis apps) for day-to-day coaching. This approach enables early detection of maladaptation, supports individualized training adjustments, and improves safety and performance outcomes. Ultimately, this framework bridges physiological science and real-world practice, providing value across both applied and research settings. </p