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Promoting Physical Activity Participation among Inactive University PhD Students using Educational and Implementation Intentions Interventions
No full textBackground: Physical inactivity is prevalent among university PhD students, impacting their health and well-being. This study explores the effectiveness of combining educational and intention-based interventions to promote physical activity among inactive PhD students.
Objectives: To assess whether improving knowledge about physical activity and/or intentions to engage in physical activity increases physical activity levels among inactive PhD students.
Methods: A 4-week pre-post study design was employed, involving 67 PhD students (age 36.45± 8.58, 31 male/36 female) from a university in the East Midlands in the United Kingdom. Participants were randomly assigned to four groups: education and intentions, education only, intentions only, and control. Interventions included educational materials and implementation intentions templates. Outcome measures were taken at baseline and post-intervention, assessing physical activity levels, knowledge, and intentions.
Results: Participants in the education and intentions group showed the highest increase in total physical activity levels and time spent in physical activity weekly (1067.6 ± 140.94 MET-minutes/week and 194.9± 6.76 minutes/week), followed by the intentions only (1039.0 ± 156.44 MET-minutes/week and 179.9 ± 7.50 minutes/week), education only (874.4 ± 136.73 MET-minutes/week and 174.8 ± 6.56 minutes/week), and control (483.8 ± 145.03 MET-minutes/week and131.0 ± 6.95 minutes/week) groups. No significant gender differences were found in total physical activity levels, but males spent more time in physical activity weekly. Higher knowledge about physical activity benefits and risks (Level 4 knowledge) was associated with increased physical activity engagement.
Conclusion: Combining educational and intentions-based interventions effectively increases physical activity levels among inactive PhD students. Future interventions should integrate knowledge about the risks of physical inactivity and consider gender differences in physical activity engagement
IoT-UAV Enabled Intelligent Resource Management in Low-Carbon Smart Agriculture Using Federated Reinforcement Learning
No full textThe Internet of Things (IoT) and unmanned aerial vehicles (UAVs) continue to advance the low-carbon smart agriculture technologies for next-generation consumer electronics and unlock more informed agricultural practices. Reinforcement learning (RL), federated learning (FL), and federated reinforcement learning (FRL) have demonstrated notable achievements in resolving complex problems, including resource allocation, energy efficiency, anomaly detection, and bandwidth utilization for multimodal tasks. This research explores multimodal data analysis and resource optimization using FRL for agricultural consumer electronics. The proposed framework employs IoT devices to monitor temperature, humidity, soil temperature, and soil moisture in real time, while UAVs provide aerial imagery for soil moisture, crop growth, and pest identification across three fields. This framework supports distributed learning, which trains local RL models on each node and combines them into the global model. The proposed FRL model demonstrated significant enhancements, including a 17% reduction in energy consumption for IoT devices and a 15% reduction for UAVs compared to non-FRL methods. This research emphasizes the effectiveness of FRL in integrating IoT and UAV for efficient resource allocation, energy efficiency, and reduced carbon emissions for low-carbon agricultural consumer electronics
‘Oh you’re really good for a girl’: Sexism, Stereotypes & Subcultural Capital in Board Gaming Culture
No full textThis study explores gender dynamics in hobby board gaming culture through 43 semi-structured interviews with women who play these games. While recent scholarship indicates potentially decreasing toxicity in geek and video game spaces, less is known about gender relations in analogue gaming communities, and specifically, hobby board games. Similar to other geek spaces, this research demonstrates how women are often stereotyped as having particular interests and competences and are thus frequently relegated to lower status positions within the community. Some women were, however, able to elevate their status through demonstrations of subcultural capital, even if these instances served to reconfirm the established, male-coded status quo. Finally, this research highlights how sexist encounters were sometimes reframed as individuals with poor social skills and being no different to wider societal experiences rather than be understood as board games culture itself having a problem with sexism. Accordingly, this research provides important insight into how sexism is experienced and understood within these gaming environments as well as providing deeper insight into how women make sense of and navigate sexism more broadly
RAPTOR: Generative AI for Parsing Colorectal Cancer Referrals to Streamline Faster Diagnostic Standard Pathways
No full textDelays in processing urgent cancer referrals hinder Faster Diagnostic Standards (FDS), with manual extraction of patient data (demographics, symptoms and test results) remaining a bottleneck in colorectal two-week wait (2WW) pathways. We evaluate generative AI (GenAI) for automating structured data extraction from colorectal cancer (CRC) 2WW referrals, comparing the reasoning capabilities of GPT-4o-Mini and DeepSeek-R1 against clinician-led extraction. Both models achieved near-human precision (GPT-4o-Mini: 94.83%, DeepSeek-R1: 93.72%) while reducing the processing time by 10-fold. Key challenges included non-deterministic output, OCR noise (e.g. handwritten annotations, overlapping text), and contextual ambiguity, notably misclassified checkboxes, symptom misattribution, and numerical inconsistencies (e.g. fecal immunochemical test (FIT) unit conversions). We also proposed an uncertainty quantification mechanism to flag uncertain extractions for human review. Despite residual limitations, GenAI shows the potential to improve efficiency, standardisation, and equity in cancer pathways by alleviating administrative burdens. Future work should prioritise hybrid AI-clinician workflows, domain-specific fine-tuning, and real-world validation to ensure reliable clinical integration
Leak Management in Water Distribution Networks Through Deep Reinforcement Learning: A Review
No full textLeak management in water distribution networks (WDNs) is essential for minimising water loss, improving operational efficiency, and supporting sustainable water management. However, effectively identifying, preventing, and locating leaks remains a major challenge owing to the ageing infrastructure, pressure variations, and limited monitoring capabilities. Leakage management generally involves three approaches: leakage assessment, detection, and prevention. Traditional methods offer useful tools but often face limitations in scalability, cost, false alarm rates, and real-time application. Recently, artificial intelligence (AI) and machine learning (ML) have shown growing potential to address these challenges. Deep Reinforcement Learning (DRL) has emerged as a promising technique that combines the ability of Deep Learning (DL) to process complex data with reinforcement learning (RL) decision-making capabilities. DRL has been applied in WDNs for tasks such as pump scheduling, pressure control, and valve optimisation. However, their roles in leakage management are still evolving. To the best of our knowledge, no review to date has specifically focused on DRL for leakage management in WDNs. Therefore, this review aims to fill this gap and examines current leakage management methods, highlights the current role of DRL and potential contributions in the water sector, specifically water distribution networks, identifies existing research gaps, and outlines future directions for developing DRL-based models that specifically target leak detection and prevention
Numerical analysis of copper foam-enhanced hybrid battery thermal management systems for lithium-ion batteries: advancing energy density and thermal control
No full textWith the growing demand for efficient and safe energy storage solutions, this study explores the effective and optimised integration of copper metal foam in hybrid battery thermal management systems (HBTMS). A novel HBTMS design is proposed, combining cooling plates with enhanced liquid cooling by metal foam layers in copper tubes and phase change material (PCM) cooling improved by copper foam longitudinal fins. Numerical simulations were conducted using a lumped-capacitance thermal model for transient battery heat generation, the enthalpy-porosity method for PCM, Darcy-Brinkman-Forchheimer (DBF), local thermal equilibrium (LTE) and non-equilibrium (LTNE) models for metal foam. Unlike previous studies that address passive and active cooling separately, present investigation uniquely integrates copper foam into both domains by enhancing conduction in the PCM and improving convection in the coolant channels. This integrated approach achieves superior thermal control, improved energy density, and ensures operational safety. The system’s performance under high 5C discharge rates demonstrated a significant reduction of about 9 K in the maximum battery surface temperature compared to pure PCM cooling while maintaining the maximum battery surface temperature difference below 1 K. The study highlights the optimal copper foam layer thickness of 4 mm, balancing improved heat transfer and minimal pressure drop. Furthermore, the incorporation of the metal foam layers reduced the number of required cooling plates, resulting in an 11 % improvement in energy density
Experiences of pregnancy and reproductive health for women living with epilepsy: A systematic review
No full textPurpose
This study provides an up-to-date systematic review and thematic synthesis of pregnancy and reproductive health experiences of women with epilepsy. Understandings of women’s experiences are essential to designing effective quality of care interventions that will lead to needed improvements in maternal health outcomes.
Methods
We undertook a systematic search of medical, social science and psychology databases to identify studies conducted from 2012 to 2024 that employed qualitative methods or qualitative methods within a mixed method design. We conducted a thematic analysis of qualitative results from identified studies to synthesize findings.
Results
Eleven publications from nine studies were identified. Six focused on the experiences of women with epilepsy during pregnancy, while five explored their experiences of reproductive health more generally. Most publications (n = 10) were of high methodological quality. Across the pre-pregnancy, antenatal, and postnatal periods, women navigate a landscape defined by uncertainty, inadequate and conflicting information, and poorly coordinated care, all while managing significant anxieties and stigma.
Conclusion
A persistent inertia exists in improvements to healthcare practice supporting the pregnancies of women with epilepsy. Gaps remain in the provision of timely pre-conception counselling, clear guidance on medication and breastfeeding, and crucially, of sensitive communication on the risk of Sudden Unexpected Death in Epilepsy. More research with women from a diversity of socio-cultural, ethnic, and socioeconomic backgrounds is needed to ensure interventions are informed by their experiences. Moving beyond the identified inertia requires a commitment to transforming care from a model of management to one of holistic, woman-centered support
Integrating Diversity, Equity and Inclusion in Management Education: An Empathy Framework
No full textAre future managers well equipped to drive the transformation towards more inclusive and just societies? This paper presents the perspectives of business school students on integrating diversity, equity and inclusion (DEI) principles into management education. We engage students as participants, co‐researchers and consultants in a student voice‐informed, multi‐method qualitative study taking place in the United Kingdom (East and West Midlands, South East and West and North regions) and in the United States (Midwest region), focusing on marketing as a case discipline. Findings illuminate student critiques of the prevalent normative coverage of DEI, to the detriment of applied knowledge and action‐oriented learning. We draw on the concept of empathy as a foundational lens for understanding and conceptualizing student expectations and develop a theoretical framework for holistically integrating DEI into management education. Our framework offers a theoretical understanding of shortcomings in current DEI learning in business schools and advances empathy as integral to both DEI and responsible management education. It proposes a novel direction for pedagogical innovations addressing social justice broadly and DEI specifically and showcases the value of student‐voice‐informed methodologies in education research for curriculum change