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Affect recognition in immersive room-scale environments: A large-scale VR study with custom facial sensing at the Science Museum in London
Get PDFRecent technological advances have provided the chance to conduct Virtual Reality (VR) experiments with increased ecological validity, which in turn can elicit more naturalistic responses in immersed users. However, many studies still prefer highly controlled setups and passive stimulation, often due to the practical complexities in effectively associating cause (stimulus) to response in highly interactive and dynamic VR experiences. Many of these studies also rely on subjective ratings from participants recorded either after the experience (relying on memory) or during the experience (interrupting immersion). In this paper, we advance this experimental protocol in a large-scale feasibility study by (1) investigating affective changes in terms of valence and arousal ratings in various interactive 3D room-scale VR environments with (2) continuous valence and arousal self-ratings from a controller and (3) a novel wireless physiological facial EMG and PPG sensor setup specifically designed to record affect, without relying on memory or interrupting immersion. In this study, n=291 participants experienced neutral, positive and negative virtual environments in 'passive' and 'active' conditions. Continuous self-ratings and physiological measures confirmed the feasibility of detecting affective states in room-scale VR conditions. To our knowledge, this is the highest n in a feasibility study in affect detection to date. Our study generated the most populated physiological data library collected in VR, which also compares passive and active VR settings. This setup can provide a solid experimental foundation for VR affective computing studies in more unconstrained, ecologically valid environments
Beyond Food Security: Unleashing the Potential of Sustainable Communities to Transform the UK Food System
Get PDFThis study delves into the urgent task of comprehending and tackling the questions arising from climate change and food security by advocating for sustainable community approaches. Motivated by the urgency of these issues, this research aims to assess the transformative ability of sustainable community practices in mitigating carbon emissions and reshaping the current food system. Drawing on findings from semi-structured interviews with local organisers of sustainable community practices in Bournemouth, UK, this study assesses and examines how these practices contribute to a localised sustainable food system. The findings reveal the multifaceted role of sustainable community practices in the UK, highlighting their collaborative nature, emphasis on environmental conservation, and resilience-building initiatives. Despite challenges such as funding constraints and climate change disruptions, sustainable practices demonstrate resilience and offer opportunities for positive change. This article concludes with recommendations that inform policy development and practical applications
Entropy-aware dynamic path selection network for multi-modality medical image fusion
No full textDeep learning has achieved significant success in multi-modality medical image fusion (MMIF). Nevertheless, the distribution of spatial information varies across regions within a medical image. Current methods consider the medical image as a whole, leading to uneven fusion and susceptibility to artifacts in edge regions. To address this problem,we delve into regional information fusion and introduce an entropy-aware dynamic path selection network (EDPSN). Specifically, we introduce a novel edge enhancement module (EEM) to mitigate artifacts in edge regions through central concentration gradient (CCG). Additionally, an entropy-aware division (ED) module is designed to delineate the spatial information levels of distinct regions in the image through entropy convolution. Finally, a dynamic path selection (DPS) module is introduced to enable adaptive fusion of diverse spatial information regions. Experimental comparisons with some state-of-the-art image fusion methods illustrate the outstanding performance of the EDPSN in three datasets encompassing MRI-CT, MRI-PET, and MRI-SPECT. Moreover, the robustness of the proposed method is validated on the CHAOS dataset, and the clinical value of the proposed method is validated by sixteen doctors and medical students
Neuronal Mesh Reconstruction from Image Stacks Using Implicit Neural Representations
Get PDFReconstructing neuronal morphology from microscopy image stacks is essential for understanding brain function and behavior. While existing methods are capable of tracking neuronal tree structures and creating membrane surface meshes, they often lack seamless processing pipelines and suffer from stitching artifacts and reconstruction inconsistencies. In this study, we propose a new approach utilizing implicit neural representation to directly extract neuronal isosurfaces from raw image stacks by modeling signed distance functions (SDFs) with multi-layer perceptrons (MLPs). Our method accurately reconstructs the tubular, tree-like topology of neurons in complex spatial configurations, yielding highly precise neuronal membrane surface meshes. Extensive quantitative and qualitative evaluations across multiple datasets demonstrate the superior reliability of our approach compared to existing methods. The proposed method achieves a volumetric reconstruction accuracy of up to 98.2% and a volumetric IoU of 0.90
Importance of hue: color discrimination of three-dimensional objects and two-dimensional discs
Get PDFWhile flat, 2D stimuli have traditionally been used to measure color discrimination, our everyday interactions typically involve 3D objects. Here, we compare discrimination thresholds for rendered matte 3D objects and uniform discs. Participants performed a 4AFC odd-one-out task, where the odd stimulus reflectance differed in hue or chroma in four quadrants of DKL color space. Hue thresholds for 3D objects and 2D discs were equal, while object chroma thresholds were significantly higher, suggesting that hue is especially important for object discrimination. Chroma-to-hue threshold ratios were above 1 in all quadrants, particularly the bluish and orangish where a preponderance of natural object reflectances plot. This supports the idea that hue is also more important for the object colors we see most in our environment
Retained-austenite transformation precedes grain fragmentation in carbon-partitioned QP1180 steel
Get PDFUnderstanding the mechanistic interplay between phase transformation and grain fragmentation is critical for microstructural control in advanced structural steels subjected to severe shear. Here, we investigate the activation sequence of retained-austenite transformation and grain fragmentation along the radial strain gradient of a single
QP1180 steel disk processed by high-pressure torsion. Synchrotron-based high-energy X-ray diffraction and microscopy reveal a pronounced austenite (γ) → martensite (α′/α) transformation that saturates at a critical equivalent von Mises strain ε ̅� ~8.5. Concomitantly, γ grain size decreases sharply up to ε ̅�, while γ peak broadening and
microstructural analysis suggest limited grain fragmentation of austenite during transformation. These findings demonstrate that γ-phase reduction is primarily driven by phase transformation prior to the onset of defect-induced fragmentation. This mechanistic activation order and the critical strain ε ̅� provide key inputs for calibrating physics-based constitutive models and defining robust process windows for industrial forming operations and component design
No clear line in the sand: Student perceptions of ethical and practical uses of generative AI
Get PDFThe discourse surrounding artificial intelligence (AI) in higher education has reached a critical juncture, often framed as a crisis. This paper, co-authored with undergraduate social science students, explores the nuanced and evolving role of generative AI (GenAI) in academic settings. Through a focus group discussion, we examine how students engage with GenAI as a means to enhance learning and augment cognitive practices, structure assignments, and managing time constraints. Our findings challenge dominant narratives that view AI use as binary—either wholly unacceptable or entirely embraced—highlighting instead a spectrum of engagement shaped by ethical considerations, institutional uncertainty, and evolving student competencies. Students express anxieties about AI detection, fairness, and broader socio-economic concerns, yet also demonstrate a pragmatic approach to integrating GenAI into their studies. This paper argues for a pedagogical shift: rather than positioning GenAI as an external threat, we suggest universities incorporate structured, transparent AI literacy into curricula, fostering informed and ethical usage. Our recommendations emphasise student collaboration to shape policy-making, create discipline-specific AI guidelines, and the integration of GenAI as a skill development tool
Corrigendum to “Impact of obesity on outcomes after total hip and knee replacement: A study on hospital length of stay and readmission rates in NHS Scotland” [Int. J. Orthopaedic Trauma Nurs. 58 (2025) 101216] (International Journal of Orthopaedic and Trauma Nursing (2025) 58, (S1878124125000619), (10.1016/j.ijotn.2025.101216))
Get PDFThe authors regret that we have made a mistake in Table 2, in which the categories “obese” and “non-obese” were inadvertently switched. Specifically, the values in the first row should correspond to the “obese” category, and the values in the second row should correspond to the “non-obese” category. This error does not affect any conclusions of the work but is sufficiently important to require correction. The authors would like to apologise for any inconvenience caused. [Table presented
A Review of Quantum Modeling and Simulation Approaches for Lithium-ion Batteries
Get PDFLithium-ion batteries (LIBs) are critical in modern energy storage systems, powering everything from portable electronics to electric vehicles. However, optimizing their performance and longevity remains a significant challenge. Quantum simulation has emerged as a promising tool to model the complex electrochemical processes within LIBs, offering insights into charging mechanisms and degradation pathways th'at classical methods struggle to capture. This paper presents a systematic literature review of quantum simulation techniques applied to LIBs, focusing on charging and degradation modeling. We analyze the current state-of-the-art, identify key techniques, and discuss the potential of quantum computing to revolutionize battery research. Our findings highlight the advantages of quantum simulations in capturing quantum mechanical and quantum chemistry effects which are critical for accurate battery modeling. Trends in the literature suggest a move toward algorithm optimization, integration with classical methods, and the development of quantum-inspired techniques
Exploring handwashing knowledge and practice among lactating mothers in Kathmandu’s slum communities, Nepal
Get PDFHand hygiene is an evolving public health issue in low-income countries such as Nepal. Poor water, sanitation, and hygiene infrastructure and practices lead to high morbidity in children under five. This study focuses on handwashing practices and disease occurrence among breastfeeding mothers in two slum settlements in Kathmandu along the Bishnumati River: Samakhusi and Tangkesower. A cross-sectional study using a semi-structured questionnaire was conducted with 127 breastfeeding mothers having at least one child. Both univariate and bivariate analyses were conducted using SPSS version 25. In the bivariate analysis, p < 0.05 was considered statistically significant. The majority of lactating mothers demonstrated good knowledge and appropriate practices in handwashing; many (81.1%) had good handwashing practices. Significant associations were found between maternal education level and childhood illness (p < 0.001); the prevalence of illness among children whose mothers had only basic education was 26% higher than children who had mothers with secondary education. Family income and handwashing practice were also significantly associated with child health (p < 0.01). Notably, 73.2% of children had experienced diarrhoea in the past 6 months. Strengthening maternal hand-hygiene education programmes, particularly for lactating mothers, and improving WASH infrastructure are necessary, as well as promoting affordable handwashing solutions in urban slums