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Journal articleHamdan S, Pinson P, Treluyer J-M, et al., 2025,
Trends of Opioids and Nefopam Use Among French Children: A Population-Based Study From 2009 to 2023
, CLINICAL DRUG INVESTIGATION, ISSN: 1173-2563 -
Journal articleBoufelja Y S, Quinn A, Shorten R, 2025,
Randomized transport plans via hierarchical fully probabilistic design
, Information Sciences, Vol: 718, ISSN: 0020-0255An optimal randomized strategy for design of balanced, normalized mass transport plans is developed. It replaces—but specializes to—the deterministic, regularized optimal transport (OT) strategy, which yields only a certainty-equivalent plan. The incompletely specified—and therefore uncertain—transport plan is acknowledged to be a random process. Therefore, hierarchical fully probabilistic design (HFPD) is adopted, yielding an optimal hyperprior supported on the set of possible transport plans, and consistent with prior mean constraints on the marginals of the uncertain plan. This Bayesian resetting of the design problem for transport plans—which we call HFPD-OT—confers new opportunities. These include (i) a strategy for the generation of a random sample of joint transport plans; (ii) randomized marginal contracts for individual source-target pairs; and (iii) consistent measures of uncertainty in the plan and its contracts. An application in fair market matching is outlined, in which HFPD-OT enables the recruitment of a more diverse subset of contracts—than is possible in classical OT—into the delivery of an expected plan.
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Journal articleCardenas MK, Anza-Ramirez C, Bernabe-Ortiz A, et al., 2025,
Validation and cost-effectiveness of an mHealth tool for cognitive impairment detection in Peru: protocol for the IMPACT Salud observational study
, BMJ Open, Vol: 15, ISSN: 2044-6055Introduction Dementia is a chronic and progressive neurological condition characterised by cognitive and functional impairment. It is often associated with multimorbidity and imposes a significant economic burden on healthcare systems and families, especially in low-income and middle-income countries. In Peru, where dementia cases are increasing rapidly, timely detection and referral for diagnosis is crucial. This protocol is part of the IMPACT Salud project in Peru. Here, we focus on a specific component aimed at validating an mHealth tool for the detection of cognitive and functional impairment and assessing its cost-effectiveness. We will also assess changes in cognitive and functional impairment as well as health economic outcomes over 1 year.Methods and analysis This observational study will be conducted in four geographically diverse regions of Peru. Community health workers are expected to contact approximately 32 000 participants (≥60 years) to apply an mHealth-enabled tool that includes cognitive and functional instruments: Ascertain Dementia 8, Peruvian version of Rowland Universal Dementia Assessment Scale and Pfeffer Functional Activities Questionnaire. From this large sample, we aim to find 3600 participants and their study partners to enrol and interview at baseline regarding sociodemographic characteristics, lifestyles, comorbidities and health economic data including resource use, costs and health-related quality of life (HR-QoL). Psychologists, blind to previous results, will assess dementia stage of the participants using an abbreviated Clinical Dementia Rating (CDR) scale. At 6-month follow-up, participants will complete a brief health economics questionnaire on resource use, costs and HR-QoL. To validate the accuracy of the detection tool, a subsample of 600 participants who completed the baseline will undergo a gold-standard clinical neuropsychological assessment. This subsample will participate in a 12-month follow-up, including healt
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Journal articleQi N, Pinson P, Almassalkhi MR, et al., 2025,
Capacity credit evaluation of generalized energy storage considering strategic capacity withholding and decision-dependent uncertainty
, APPLIED ENERGY, Vol: 397, ISSN: 0306-2619 -
Conference paperZHOU J, Aloufi R, Porat T, et al., 2025,
Human-AI collaboration in high-stakes decision-making: work in progress
, 38th International BCS Human-Computer Interaction Conference (BCS HCI 25), Publisher: BCS Learning and Development Ltd, Pages: 465-470This work in progress investigates human interaction with an LLM-powered chatbot, presented as either a fellow human or a transparently disclosed AI collaborator, in a high-stakes decision-making simulation—the NASA Moon Survival Task. We will employ a one-way between-subjects design to examine how individuals’ collaboration and communication are influenced by the identity of their partner (AI vs. human). Specifically, we will evaluate individuals’ collaboration processes (i.e., collaborative behaviour and communicative dynamics) and outcomes, alongside their retrospective interaction experience andperceptions of the partner. We will also examine dyadic-level linguistic coordination during the interaction and conduct user profiling to uncover variations in AI collaborative benefits. We anticipate that this studywill have four key impacts: safeguarding human-AI collaboration, democratising AI benefits, guiding modelimprovement, and making methodological contributions. The anonymised dialogues and associated data will be open-sourced upon study completion.
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Journal articleKoczias C, Demirel P, 2025,
The impact of green skills and green capabilities on firms’ financial performance: a systematic literature review
, Journal of Innovation & Knowledge, Vol: 10, ISSN: 2444-569XGreen skills and capabilities in organisations are important enablers of net-zero transition as they determine firms’ ability to adopt sustainability as a core business strategy. This study conducts a systematic literature review of 84 scholarly articles and 7 industry publications to examine the conceptualisation of green skills and green capabilities in firms, their influence on firms’ financial performance, and the factors shaping these complex relationships. Findings reveal that the green skills and green capabilities concepts are broad and ambiguously defined, necessitating greater conceptual clarity, especially with respect to how the green skills and capabilities relate to each other. Accordingly, the study develops a framework outlining different green skill and capability typologies and their interconnections. Additionally, six key performance categories—(1) costs, (2) profitability, (3) efficiency and productivity, (4) firm growth, (5) liquidity, and (6) market performance— are identified inductively, with evidence from the literature indicating that both green skills and green capabilities positively impact each of these areas. Results suggest that while the overall effect of green skills and capabilities on financial performance is positive, several contextual factors, such as firm size, sector, and region, influence this relationship. The study highlights the most significant caveats and their implications, contributing to a more nuanced understanding of the knowledge–performance link for the net-zero transition.
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Journal articleJin B, Kobayashi A, Bhattacharya D, et al., 2025,
Automated Straight-Line Sewing of Stretchable Fabrics With Different Lengths
, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 10, Pages: 12165-12172, ISSN: 2377-3766 -
Journal articleIkeya K, Cardin M-A, Cilliers J, et al., 2025,
Multi-objective decision-making for flexible design and planning of oxygen production facilities in an uncertain lunar environment
, ACTA ASTRONAUTICA, Vol: 236, ISSN: 0094-5765 -
Journal articleLu X, Owen RE, Du W, et al., 2025,
Unravelling electro-chemo-mechanical processes in graphite/silicon composites for designing nanoporous and microstructured battery electrodes
, NATURE NANOTECHNOLOGY, ISSN: 1748-3387 -
Journal articleZHOU J, Van Zalk N, 2025,
A person-oriented approach to social anxiety and depression: latent profiles and emotional functioning in adults
, Frontiers in Psychology, Vol: 16, ISSN: 1664-1078Objectives: Symptoms of social anxiety and depression often co-occur, but many questions remain about symptom-level co-occurrence and the heterogeneity of symptom presentations across individuals, as well as their emotional functioning. This study aimed to investigate the co-occurrence of social anxiety and depressive symptoms in adults and variations in emotional functioning linking symptom heterogeneity. Methods: This study used a person-oriented approach, Latent Profile Analysis (LPA), to identify distinct profiles (i.e., subgroups) in a UK adult sample (N = 222) varying in presentations of social anxiety and depressive symptoms. Further analyses examined between-profile differences in emotional functioning, including daily affect and emotion regulation. Results: Four profiles were identified: Comorbid (12.61%), Dysphoric (10.36%), Socially Anxious (36.94%), and Low Distress (40.09%), replicating the four-profile solution revealed in prior research on adolescents. The Comorbid subgroup reported the most pronounced emotional dysfunction, with higher daily negative affect, lower positive affect, and greater emotion dysregulation than the other three subgroups. The Low Distress subgroup reported the best emotional functioning. Conclusions: The cross-sectional study design restricts our ability to evaluate the long-term stability of the identified profiles. Nevertheless, this study illuminates the diverse ways social anxiety and depression intertwine, underscoring the necessity of transdiagnostic interventions that cater to a wide range of symptom patterns and emotional functioning.
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Journal articleBevan PA, BanksLeite C, Kovac M, et al., 2025,
Robotics‐assisted acoustic surveys could deliver reliable, landscape‐level biodiversity insights
, Remote Sensing in Ecology and Conservation, ISSN: 2056-3485Terrestrial remote sensing approaches, such as acoustic monitoring, deliver finely resolved and reliable biodiversity data. However, the scalability of surveys is often limited by the effort, time and cost needed to deploy, maintain and retrieve sensors. Autonomous unmanned aerial vehicles (UAVs, or drones) are emerging as a promising tool for fully autonomous data collection, but there is considerable scope for their further use in ecology. In this study, we explored whether a novel approach to UAV-based acoustic monitoring could detect biodiversity patterns across a varied tropical landscape in Costa Rica. We simulated surveys of UAVs employing intermittent locomotion-based sampling strategies on an existing dataset of 26,411 h of audio recorded from 341 static sites, with automated detections of 19 bird species (n = 1819) and spider monkey (n = 2977) vocalizations. We varied the number of UAVs deployed in a single survey (sampling intensity) and whether the UAVs move between sites randomly, in a pre-determined route to minimize travel time, or by adaptively responding to real-time detections (sampling strategy), and measured the impact on downstream ecological analyses. We found that avian species detections and spider monkey occupancy were not impacted by sampling strategy, but that sampling intensity had a strong influence on downstream metrics. Whilst our simulated UAV surveys were effective in capturing broad biodiversity trends, such as spider monkey occupancy and avian habitat associations, they were less suited for exhaustive species inventories, with rare species often missed at low sampling intensities. As autonomous UAV systems and acoustic AI analyses become more reliable and accessible, our study shows that combining these technologies could deliver valuable biodiversity data at scale.
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Journal articleBhattacharya D, Cheung TK, Wang Y, et al., 2025,
Kinematic and dynamic modeling of cable-object interference and wrapping in complex geometrical-shaped cable-driven parallel robots
, Mechanism and Machine Theory, Vol: 214, ISSN: 0094-114XCable-Driven Parallel Robots (CDPRs) use cables as actuators to maneuver rigid mobile-platform in a parallel mechanism setup. Typically, CDPR kinematic and dynamic models avoid cable-object (cable-mobile-platform and cable-obstacle) interferences to prevent sudden cable tension changes that could deviate the end-effector’s trajectory. However, allowing these interferences can lead to cable wrapping, where cables wrap around complex-shaped surfaces upon contact, enhancing the CDPR’s workspace and reducing its footprint. Despite the potential benefits, there currently exists no kinematic and dynamic model that effectively incorporates cable wrapping around such complex-shaped surfaces. This paper introduces a novel numerical-based kinematic and dynamic modeling framework for CDPRs that detects and then manages cable wrapping around mobile-platform and multiple obstacles with the assumption that the cables remain taut and for every position along the cable, there is a unique and smooth way to describe its location on the surface. Simulation and hardware results on various complex-shaped mobile-platform and obstacles show that the proposed model framework can be conveniently and effectively applied to the real-time modeling of cable wrapping. Code and videos available at: https://github.com/bhattner143/GeoWrapSim-CDPR.git.
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Journal articleMissoni F, Poole KC, Picinali L, et al., 2025,
Effects of auditory distance cues and reverberation on spatial perception and listening strategies
, npj Acoustics, Vol: 1, ISSN: 3005-141XSpatial hearing—the brain’s ability to identify sound origins using auditory cues—is inherently multisensory, integrating vision, hearing, and proprioception to reduce uncertainty and support adaptive interaction with the environment. While simplified experimental paradigms have advanced our understanding, their limited ecological validity limits real-world applicability. This study investigates how listener movement, reverberation, and distance affect localisation accuracy in more naturalistic settings. Participants performed an active localisation task without prescribed listening strategies, in either anechoic or reverberant conditions. Sound sources were positioned around them in both horizontal and vertical planes, at varying distances. Results show increased head movement in reverberant environments, suggesting an adaptive response to degraded binaural cues. While distance did not influence listening strategies, it significantly affected localisation accuracy. These findings highlight the importance of considering ecological factors when studying spatial hearing and suggest that natural listener behaviour plays a key role in maintaining spatial accuracy under different reverberant conditions.
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Journal articleKormushev P, 2025,
Rescue robots for casualty extraction: a comprehensive review
, IEEE Access, ISSN: 2169-3536The development of robotic systems for search and rescue (SAR) operations holds greatpotential in reducing risks to rescue workers and enhancing the likelihood of successful rescue operations. Although many studies have been conducted on search and rescue robotics, more emphasis should be placed on developing rescue robots, especially those intended for physical rescue interventions, such as loading and transporting injured individuals (i.e., casualties) to a secure area—the process known as casualty extraction. The enabling technologies for such robots remain challenging due to the complexity of the tasks, significantly high safety considerations, and strict standards—since the robots are designed to interact with casualties physically. In addition to academic institutions, most research and technical implementations of state-of-the-art casualty extraction robots are carried out by military organisations. This paper presents a comprehensive review of the current state of the art in developing mobile rescue robots for casualty extraction. The existing casualty extraction robot proposals publicly available in the literature are discussed and evaluated in terms of their design and morphology. Moreover, this review details the proposed casualty extraction procedure that corresponds to the robot designs, the operation method, and the levels of autonomy of these robots. The existing state-of-the-art technologies are discussed and compared to evaluate the pros and cons of each system, providing a guideline for further research into areas where more effort could be applied. Based on the review and evaluation of the existing state-of-the-art, we identify critical research gaps that require further investigation to enhance the current state of the art and facilitate long-term development in rescue robotics research.
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Journal articleRakotomalala Robinson D, Pennisi I, Cavuto M, et al., 2025,
Sensitive near point-of-care detection ofasymptomatic and sub-microscopicPlasmodium falciparum infections in Africanendemic countries
, Nature Communications, ISSN: 2041-1723Limited diagnostic capacity for detecting asymptomatic malaria infections with low parasite densities hinders elimination efforts in Africa. Here, we adapt a near point-of-care, LAMP-based diagnostic platform for malaria diagnosis using capillary blood. This Pan/Pf detection method meets the Malaria Eradication Research Agenda (malERA) criteria for community-level screening, witha limit of detection of 0.6 parasites/μL and a sample-to-result time under 45 minutes. We evaluate its performance on 672 capillary blood samples collected at the community level in The Gambia and Burkina Faso, including 146Plasmodium falciparum positives confirmed by qPCR. The diagnostic platform achieves 95.2% sensitivity (95% CI: 90.4–98.1) and 96.8% specificity (95% CI: 94.9–98.0). It also detects 94.9% (130/137) of asymptomatic infections and 95.3% (41/43) of sub-microscopic cases (<16 parasites/μL), outperforming expert microscopy (70.1% and 0%) and rapid diagnostic tests (49.6% and 4.7%). This field-deployable molecular diagnostic method offers a sensitive, scalable solution to support test-and-treat strategies for malaria elimination across Africa.
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Journal articleKalossaka LM, Mohammed AA, Bastos L, et al., 2025,
Green light vat‐photopolymerisation for 3D printing hydrogels with complex lattice structures
, Advanced Materials Technologies, Vol: 10, ISSN: 2365-709XMoving beyond UV curing systems opens new potential application spacessuch as biological, portable printing solutions, as well as innovative chemistriesand material properties. A novel visible light printer is proposed for the first timeusing green Digital Light Processing (gDLP) at a wavelength of 514 nm. GreenLED lights are integrated into a commercial desktop DLP printer to 3D printhydrogels with complex designs at high resolution. A workflow process is pre-sented to develop and optimize formulations for gDLP, resulting in two novel in-house photoresin formulations made specifically for green light printing. Theseformulations comprise PEGDA 700 with and without acrylamide, using a type IIphotoinitiating system of Eosin Y, triethylamine, and N-vinylpyrrolidone. Thephotoresins are optimized to achieve highly vascularized lattice prints by mod-ulating layer light exposure, chemical components, and photoinitiator concen-trations. The gDLP successfully printed hydrogels with a layer height of 50 𝛍mand feature dimensions as small as 0.3 mm by adjusting light duration per layer.3D printed hydrogels using both formulations are tested for varying designcomplexity, including ISO/ASTM standards, and evaluated with optical imag-ing, SEM, and mechanical testing. This study highlights gDLP technology’s po-tential for diverse applications in tissue engineering and sustainable materials.
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Journal articleLee KY, Meyer-Kahlen N, Schlecht SJ, et al., 2025,
Evaluating Reverberation Models for Augmented Reality
, AES Journal of the Audio Engineering Society, Vol: 73, Pages: 619-632, ISSN: 1549-4950The ultimate goal of the reverberation model for augmented reality is to create an auditory illusion, making simulated sound sources indistinguishable from real, measured ones. However, existing evaluation methods are not tailored to achieve this objective. This paper adopts the evaluation paradigm of auditory illusion tests to evaluate reverberation models under two distinct tasks: authenticity and transferring. The listening test uses the three-alternative forced-choice design, where subjects are asked to detect the speech signal processed with a model-generated room impulse response (RIR) among the signals processed with measured RIRs. For the authenticity task, the three signals contain the same speech sample, while for the transferring task, they contain different samples from different speakers. A Bayesian analysis shows that detecting model-generated RIRs is significantly more challenging in the transferring task than in the authenticity task across all models. Additionally, while the listening test results positively correlate with the selected objective metrics, the reliability and generalizability of these correlations for predicting listening test outcomes remain uncertain. The proposed evaluation framework for reverberation models can serve as a precursory analysis for developing dynamic, binaural rendering for augmented reality applications.
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Journal articleYin Y, Zuo H, Jennings T, et al., 2025,
Use and potential of AI in assisting surveyors in building retrofit and demolition - a scoping review
, Buildings, Vol: 15, ISSN: 2075-5309Background: Pre-retrofit auditing and pre-demolition auditing (PRA/PDA) are important in material reuse, waste reduction, and regulatory compliance in the building sector. An emphasis on sustainable construction practices has led to a higher requirement for PRA/PDA. However, traditional auditing processes demand substantial time and manual effort and are more easily to create human errors. As a developing technology, artificial intelligence (AI) can potentially assist PRA/PDA processes. Objectives: This scoping review aims to review the potential of AI in assisting each sub-stage of PRA/PDA processes. Eligibility Criteria and Sources of Evidence: Included sources were English-language articles, books, and conference papers published before 31 March 2025, available electronically, and focused on AI applications in PRA/PDA or related sub-processes involving structured elements of buildings. Databases searched included ScienceDirect, IEEE Xplorer, Google Scholar, Scopus, Elsevier, and Springer. Results: The review indicates that although AI has the potential to be applied across multiple PRA/PDA sub-stages, actual application is still limited. AI integration has been most prevalent in floor plan recognition and material detection, where deep learning and computer vision models achieved notable accuracies. However, other sub-stages—such as operation and maintenance document analysis, object detection, volume estimation, and automated report generation—remain underexplored, with no PRA/PDA specific AI models identified. These gaps highlight the uneven distribution of AI adoption, with performance varying greatly depending on data quality, available domain-specific datasets, and the complexity of integration into existing workflows. Conclusions: Out of multiple PRA/PDA sub-stages, AI integration was focused on floor plan recognition and material detection, with deep learning and computer vision models achieving over 90% accuracy. Other stages such as operation
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Journal articleMarggraf-Turley N, Pontoppidan NH, Picinali L, 2025,
The impact of individual head-related transfer function augmentation on spatial release from masking.
, Hear Res, Vol: 466Binaural hearing underpins effective communication in complex acoustic environments by increasing listeners' abilities to segregate concurrent sound sources. In certain conditions, interaural magnification of binaural cues has been shown to improve speech intelligibility in competing target masker scenarios, yet existing methods primarily comprise hearing aid algorithms, which, due to processing constraints, cause unwanted artefacts. Moreover, the perceptual effects of applying interaural magnification directly to a person's own head-related transfer function (HRTF) remain unclear. We revisit a previous method for magnifying interaural cues, apply it to individual HRTFs, and propose a modified version designed to reduce spatial distortions. We evaluate both approaches using auditory models and listening tests involving speech-on-speech masking with a midline target and symmetrical maskers. Behavioural results show that although magnifying interaural phase and level differences improves overall speech intelligibility compared to unmodified HRTFs, it does not significantly enhance spatial release from masking (SRM). Meanwhile, auditory model predictions suggest greater SRM gains than those observed behaviourally, suggesting an influence of listener familiarity with their individual spatial cues. Finally, interaural magnification benefits diminish for listeners who already exhibit strong SRM with their own HRTFs.
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Journal articleDeterding S, Guckelsberger C, Lintunen EM, et al., 2025,
Advancing Self-Determination Theory via computational modelling: the case of competence and optimal challenge
, MOTIVATION AND EMOTION, ISSN: 0146-7239 -
Journal articleRen Y, Huang M, Liu G, et al., 2025,
Decoding coupled mechanical-electrochemical responses in multi-layer batteries via generalized ultrasonic dynamics
, Energy Storage Materials, ISSN: 2405-8297Characterizing and understanding internal battery physics is essential for stability, safety, and recyclability. Ultrasound provides a non-destructive solution by encoding battery dynamics into mechanical waves. However, the complex multi-layer structure and coupled mechanical-electrochemical behaviors of commercial cells hinder standardized and physically interpretable ultrasonic testing. This study presents a unified ultrasonic framework for multi-layer pouch cells, linking wave dynamics to battery structures, materials, and states across frequency and time domains. Inspired by electrochemical impedance spectroscopy, we examine structure- and state-waveform relationships of batteries under various excitation conditions, decoding ultrasonic responses related to mechanical and electrochemical factors in a generalizable manner. Using first-principles modeling and frequency sweep experiments, we identify battery-specific frequency bandstructures and wave modulation signatures tied to cell architecture and cathode chemistry, allowing mechanical discrimination of these factors in electrochemically steady states. In-operando tests demonstrate that changes in localized ultrasonic resonance associated with shifting bandstructure can map variations in battery state of charge, with the evolution of anode material stiffness as a key driving mechanism. This work establishes a physics-grounded foundation for understanding wave-battery interactions and is expected to guide the development of high-sensitivity, task-specific tools and diagnostic strategies across the in-laboratory, post-manufacture, and in-service stages of a battery’s lifecycle.
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Journal articleZhao Y, Li H, Zhou H, et al., 2025,
Rapid prediction of material deformation in hot stamping of battery box geometries using graph neural network
, Journal of Physics : Conference Series, Vol: 3104, ISSN: 1742-6588The development of lightweight robust structures for battery box is critical for enhancing the performance and energy efficiency of electric vehicles. Hot stamping technology is widely used to form these geometries from high strength-to-weight materials. Recent efforts have leveraged surrogate models to predict material deformation behaviours, offering critical insights into the design of component geometries. However, most surrogate models rely on image-based data representations, which faces challenges in feature representation and permutation invariance. To address these challenges, this study introduces a Recurrent U Net-based Graph Neural Network (RUGNN) surrogate model. The RUGNN model is designed to make spatial-temporal prediction of material deformation under varying contact conditions imposed by different forming tool geometries. This model enables rapid and accurate predictions of spatial-temporal deformation fields under hot stamping conditions. It allows designers to quickly evaluate the effects of forming tools geometry on blank material deformation behaviour and optimise designs during early-stage exploration. Training is conducted on a diverse dataset of deep-drawn corner geometries, which serve as a typical demonstrator in battery box design. The network predictions closely match the ground truth from FE simulations. The RUGNN framework supports early-stage tool design explorations and enables efficient evaluation of complex geometries.
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Journal articleCaltabiano A, Burke T, Nesi J, et al., 2025,
Virtual reality delivered exposure for fear of needles: a small-scale pilot
, Frontiers in Psychiatry, Vol: 16, ISSN: 1664-0640Background: Fear of needles significantly impacts individual and public health by leading many adults to avoid necessary medical procedures, including vaccinations and blood tests. Virtual Reality Exposure-Based Therapy has shown promise as an effective and accessible intervention for anxiety disorders but remains under-explored. Objectives: This study aimed to evaluate the efficacy and acceptability of a single-session virtual reality intervention targeting fear of needles in adults. Methods: A total of 62 adults reporting needle fear were recruited into experimental (n = 32) and online comparison groups (n = 30). The experimental group completed one Virtual Reality Exposure-Based Therapy session, which comprised of two self-paced virtual reality exposures simulating medical needle procedures. Anxiety and affect were assessed at baseline, during, and immediately following virtual reality exposures, and at a one-month follow-up. Acceptability, usability, presence, plausibility, and virtual reality sickness were also measured. Results: The intervention successfully elicited anxiety during exposure. At one-month follow-up, a modest but statistically significant reduction in symptom severity was observed on one measure (Specific Phobia Questionnaire), though no significant change was noted in life interference or on another severity measure (Medical Fears Survey). Participants rated the intervention highly in terms of usability and acceptability, although some reported symptoms of virtual reality sickness (e.g., disorientation, motion sickness). Conclusions: Virtual Reality Exposure-Based Therapy appears to be an effective and highly acceptable intervention for reducing immediate anxiety related to needle exposure, demonstrating strong potential as a scalable, accessible alternative to traditional exposure therapy. However, further research is necessary to confirm these findings, optimize intervention protocols, and examine long-term effectiveness for fear of needles.
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Journal articleWang P, Khinvasara Y, Creijghton GJ, et al., 2025,
Enhancing designer creativity through human-AI co-ideation: a co-creation framework for design ideation with custom GPT
, AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, Vol: 39, ISSN: 0890-0604 -
Journal articleXuyi H, Jian L, Picinali L, et al., 2025,
Head-related transfer function upsampling using an autoencoder-based generative adversarial network with evaluation framework
, Journal of the Audio Engineering Society, Vol: 73, Pages: 533-547, ISSN: 0004-7554Accurate Head-Related Transfer Functions (HRTFs) are essential for delivering realistic 3D audio experiences. However, obtaining personalised, high-resolution HRTFs for individual users is a time-consuming and costly process, typically requiring extensive acoustic measurements. To address this, spatial upsampling techniques have been developed to estimate high-resolution HRTFs from sparse, low-resolution acoustic measurements. This paper presents a novel approach leveraging the spherical harmonic (SH) domain and an Autoencoder Generative Adversarial Network (AE-GAN) to tackle the HRTF upsampling problem. Comprehensive evaluations are conducted using both perceptualmodels and objective spectral metrics to validate the accuracy and realism of the upsampled HRTFs. The results show that the proposed approach outperforms traditional barycentric interpolation in terms of log-spectral distortion (LSD), particularly in extreme sparsity scenarios involving fewer than 12 measurements. These results go some way to justifying that the proposed AE-GAN approach is able to create high-quality, high-resolution HRTFs from only a few acoustic measurements, helping pave the way for more accessible personalised spatial audio across a range of applications.
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Journal articleBaxter W, Mandeno P, Aunger R, et al., 2025,
Setting-driven design: a context-driven approach to behavioural design
, DESIGN SCIENCE, Vol: 11, ISSN: 2053-4701 -
Journal articleMai L, Tian X, Zhao Y, 2025,
Air taxis will soon be in our skies - if batteries can be made safer
, NATURE, Vol: 645, Pages: 36-38, ISSN: 0028-0836 -
Journal articleSmith F, Sadek M, Wan E, et al., 2025,
Codesigning AI with end-users: an AI literacy toolkit for nontechnical audiences
, Interacting with Computers, Vol: 37, Pages: 444-456, ISSN: 0953-5438This study addresses the challenge of limited AI literacy among the general public hindering effective participation in AI codesign. We present a card-based AI literacy toolkit designed to inform nontechnical audiences about AI and stimulate idea generation. The toolkit incorporates 16 competencies from the AI Literacy conceptual framework and employs ‘What if?’ prompts to encourage questioning, mirroring designers’ approaches. Using a mixed methods approach, we assessed the impact of the toolkit. In a design task with nontechnical participants (N = 50), we observed a statistically significant improvement in critical feedback and breadth of AI-related questions after toolkit use. Further, a codesign workshop involving six participants, half without an AI background, revealed positive effects on collaboration between practitioners and end-users, fostering a shared vision and common ground. This research emphasizes the potential of AI literacy tools to enhance the involvement of nontechnical audiences in codesigning AI systems, contributing to more inclusive and informed participatory processes.
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Journal articleXu L, Zou Y, Tian H, et al., 2025,
Cognitive and affective reactions to virtual facial representations in cosmetic advertising: a comparison of idealized and naturalistic features
, Electronics, Vol: 14, ISSN: 2079-9292The rise of virtual models in the digital age presents a new frontier for cosmetic advertising. Nevertheless, the comparative effectiveness of “idealized” versus “naturalistic” facial features in these models remains a topic of debate and an area of development. This study examines the impact of “idealized” and “naturalistic” facial features in virtual models on consumers’ cognitive and affective responses. Using eye-tracking and a structural equation model, we analyzed visual attention patterns and the roles of affective resonance, trustworthiness, likability, and expertise perception. The results indicate that non-homogeneous or defective naturalistic features increase visual attention and purchase intention, with consumers focusing on imperfections such as freckles. In contrast, idealized facial features mainly draw attention to areas such as the eyes and nose. Mediation analysis reveals that likability and affective resonance are primary influences on purchase intention, while expertise perception and trustworthiness are secondary. This experiment suggests that consumers prioritize socio-emotional connections over professional authority when evaluating naturalistic designs. Our findings provide a framework for virtual model design, helping brands balance aesthetics with psychological optimization, and offer insights into the interplay between visual stimuli and human cognitive and emotional processes in decision-making.
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Journal articleWang B, Zhao X, Zuo H, et al., 2025,
From analogy to innovation: a creative conceptual design approach leveraging large language models
, Advanced Engineering Informatics, Vol: 67, ISSN: 1474-0346Integrating creative concepts into Product Design and Manufacturing Systems (PDMS) is important for product innovation. However, current PDMS lack cognitive capabilities, particularly in reasoning and synthesis, which are essential for conceptual design. As a result, designers face challenges in retrieving relevant analogies, establishing meaningful mappings, and integrating knowledge into new design concepts. This paper proposes a computational conceptual product design approach that integrates Large Language Models’ (LLMs) knowledge representation with an analogy-based structured retrieval mechanism, supporting designers to explore and recombine design patterns and functionalities in an intuitive manner. Benefiting from the zero-shot learning and prompting capabilities of LLMs, given a source domain, this approach allows reasoning target domain based on abstract correspondences in both morphological and semantic associations. A template for the combinational regulation of the reuse of analogical knowledge has also been formulated. By decomposing analogical knowledge into ontological distinction, inspirational feature recognition, and associative mapping explanation, a creative conceptual design stimulation path is formed. An interactive tool named ViMimic based on this approach has been developed through a case study with 18 participants. Evaluation results demonstrate that the approach improves creative performance, increasing the novelty and functionality of conceptual designs by 51% and 22% respectively according to expert evaluations. It also boosts the efficiency and diversity of analogy mapping by 30% based on objective measures, while enhancing creative experiences and reducing cognitive load as measured in the participants’ self-assessment.
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