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Journal articleRiley S, Vamvakeros A, Quino G, et al., 2026,
Acute deformation characteristics of standard and flexible lithium-ion battery electrodes
, Communications Materials, Vol: 7Understanding the strain tolerance of both standard and mechanically flexible battery electrodes is prerequisite for optimizing performance, safety, and longevity, particularly in heavy-duty applications, flexible electronics and wearables. Achieving this requires a deeper understanding of how mechanical strain drives electrode degradation. In this work, we directly compare the strain response of electrospun (flexible) and slurry-cast (conventional) electrodes. To simulate acute mechanical stress, electrodes underwent a controlled 180° folding, pressing, and unfolding protocol designed to induce measurable damage, we then employed a combination of characterization techniques, including synchrotron X-ray nano-computed tomography, X-ray diffraction mapping, electrochemical analysis, and in situ Tensiometer-scanning electron microscopy to assess both structural and electrochemical degradation modes and provide a standardised upper-bound for strain induced damage. Our results reveal that electrospun electrodes exhibit significantly greater resilience to deformation, attributed to their freestanding architecture and fibrous morphology. These findings underscore the importance of characterizing deformation mechanisms to guide the design of high-performance batteries.
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Journal articleCieslak C, Rivers S, Childs P, 2026,
In-situ wind turbine blade inspection using ultrasonic non-destructive testing
, Journal of Fluids Engineering, Transactions of the ASME, Vol: 148, ISSN: 0098-2202Offshore and onshore wind turbine blades present significant inspection, maintenance and repair challenges arising from location, economic drivers, environment and the specific blade architecture concerned. In-situ tasks have traditionally been undertaken by people abseiling from the tower or use of gantries. Harsh conditions associated with windy environs, along with pressures to limit downtime, have led to a range of new technologies becoming available. This paper presents results from the use of ultrasonic nondestructive testing (NDT) measurements of subsurface blade topography arising from in situ and static blade inspection for a range of wind turbine types. The measurements have been enabled using a hexapod robot that can accommodate NDT scanners within its chassis and can, using pneumatic suction for the robot pedipulators, navigate the convex, concave, and flexing form of in situ wind turbine blades. The arising NDT tomographic scans provide detailed information on blade integrity, the presence or otherwise of bonding materials, and local feature condition. Measurements, presented over a 600 mm traverse span, have confirmed the reliability of the robotic platform to deliver high-quality, consistent, and reliable data to be acquired with limited NDT experience and to allow subsurface inspections to be performed and analyzed remotely. In addition to detailed measurement of subsurface blade features, the robot system has also demonstrated the capacity to undertake functions such as lightning protection system verification.
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Journal articleMa P, Shen Z, Ge Y, et al., 2026,
Soft Auxetic Fingertip (SAF) for Shape-Adaptive and Stable Grasping
, IEEE Robotics and Automation Letters, Vol: 11, Pages: 4219-4226 -
Journal articleMcmeeking A, Dieckmann E, 2026,
Interfibre bridging in bacterial nanocellulose via co-culture-derived polyhydroxybutyrate and solvent-free blending approaches
, Carbohydrate Polymer Technologies and Applications, ISSN: 2666-8939Bacterial nanocellulose (BNC) is a renewable polymer valued for its strength and purity, but its brittleness and hydrophilicity limit wider application. Incorporating biodegradable polyester polyhydroxybutyrate (PHB) offers a pathway to functional, scalable composites. We establish two complementary routes for producing bacterial nanocellulose-polyhydroxybutyrate composites. In-situ co-cultures of Komagataeibacter rhaeticus (KR) and Cupriavidus necator (CN) were optimised through inoculation timing, medium screening, and pH buffering. 2-(N-morpholino)ethanesulfonic acid (MES) at 50 mM stabilised culture conditions, improved cellulose output, and enabled PHB co-localisation of 4% total wet weight. These natural incorporation levels provided benchmarks for a solvent-free blending strategy, in which powdered PHB was introduced into plasticised sterilised BNC using Gellan gum, Glycerol, PEG400, and CaCl₂ at loadings of 0.1%, 0.3%, 0.7%, and 2.0% (approximately 10%, 30%, 70%, and 200% relative to dry BNC mass) and heat pressed. Blended films reproduced co-culture PHB levels and tolerated up to 0.7% (wet weight) before shrinkage and brittleness were observed. Heat pressing promoted PHB diffusion between cellulose fibrils, enhancing interfibre bonding; in blended films at 0.3 % PHB (heat-pressed), this yielded a 6.3-fold increase in ultimate tensile strength and a 9.5-fold increase in Young's modulus. Co-culturing defined the biological starting point, while blending enabled scalable processing and systematic characterisation, offering complementary routes to manufacture BNC-PHB composites.
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Journal articleZou Y, Childs P, 2026,
Shifting Workflow Practices with Implementation of AI in Design in Apparel and Fashion
, International Journal of Industrial and Manufacturing Engineering -
Journal articlePoole KC, With S, Martin V, et al., 2026,
Spatial auditory change detection in listeners with hearing loss.
, Hear Res, Vol: 474Everyday listening relies on the auditory system's ability to automatically monitor background ("non-target") sounds that lie outside the focus of attention to detect new or changing sources. Although change detection is a fundamental aspect of this situational awareness, little is known about how hearing impairment affects this ability. This study examined how variability in sensorineural hearing loss influences spatial auditory change detection. Older hearing-impaired listeners (N = 30) completed a spatial change detection task requiring them to identify the appearance of a new sound source within a complex spatialised acoustic scene. Hearing loss was characterised by three factors measured with standard clinical tests: audiometric hearing thresholds, sensitivity to small level changes, and sensitivity to spectrotemporal modulation. These factors were used to predict reaction time, hit rate, and false alarm rate. Listeners with poorer spectrotemporal sensitivity, higher audiometric hearing thresholds, and older age showed slower and less accurate detection, whereas sensitivity to small level changes did not predict outcomes. Detection also varied with spatial location, where appearing sources from behind were detected more slowly and less accurately than those from the front or sides. Numerical analysis using HRTFs suggested that these rear-field effects are not fully explained by acoustic level differences alone, indicating that attentional factors may play a role. These results reveal that hearing loss, age, and spatial factors jointly shape listeners' ability to monitor dynamic auditory scenes. Additionally, testing spectrotemporal sensitivity offers a promising clinical measure of non-speech auditory processing with relevance for hearing-aid fitting and situational awareness.
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Journal articleDhopatkar R, Sadan MK, George C, 2026,
Infrared Active Actuators Mimicking Locomotion Patterns of Soft-Bodied Invertebrates
, ACS Applied Polymer Materials, Vol: 8, Pages: 1595-1602Soft-bodied invertebrates such as caterpillars and leeches transduce muscle contraction and relaxation sequences toward their locomotion ability. Mimicking these complex locomotory patterns to design soft robots with predictable gaits remains a significant challenge to date. Here we report infrared responsive actuators based on graphite ink-coated low-density polyethylene (LDPE) sheets, capable of performing caterpillar-like crawling and somersaulting motion with high predictability, reversibility and rapidity. By strategically patterning graphite ink on LDPE and performing thermal imaging, we show that the heat generation across actuators upon photoirradiation correlates to actuation response time and magnitude. These actuators achieve a curvature angle of 270° in 9 s and return consistently to their original state, with over 70% improvement in the restoration time. Similarly, somersaulting (in 5 s) and wave-like crawling (30.8 mm/min) achieve over 60% improvement in the actuation speed. Our findings therefore open possibilities of designing untethered actuators with high precision and adaptable locomotion modes.
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Journal articleGao X, Yan Z, Lin L, et al., 2026,
Microsized Sn-Hard Carbon Composite Anode with Capacities of 583 mAh g–1and 1073 mAh cm–3for Sodium-Ion Batteries
, ACS Energy Letters, Vol: 11, Pages: 1916-1925Sodium-ion batteries (SIBs) are applied for large-scale energy storage systems, yet their energy density remains capped by hard carbon (HC) anodes with modest gravimetric and volumetric capacities. Herein, we report an alloying-carbon strategy that applies microsized Sn particles with microsized HC particles to form thick-film anodes. The optimized Sn-HC composite couples the high capacity and compaction density of Sn with the structural robustness of HC, displaying the gravimetric and volumetric capacities of 583 mAh g<sup>–1</sup> and 1073 mAh cm<sup>–3</sup>, an initial Coulombic efficiency of 90.5%, a capacity retention of ∼89.5% after 1000 cycles at 0.5 A g<sup>–1</sup>, and limited electrode swelling of 33.7%. Coupled with the Na<inf>3</inf>V<inf>2</inf>(PO<inf>4</inf>)<inf>3</inf> cathode, the SIB full cell delivers an energy density of 254 Wh kg<sup>–1</sup> and high-rate capabilities. Such Sn-HC architecture offers a scalable and industrially relevant route to simultaneously increase the gravimetric and volumetric capacities of anodes for SIBs.
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Journal articleWang P, Zhang X, Wei L, et al., 2026,
Human-AI co-ideation via combinational generative model
, Journal of engineering design, Vol: 37, Pages: 458-494, ISSN: 0954-4828Ideation is a critical step in the engineering design process, enabling designers to develop creative and innovative concepts and prototypes. Currently, the ideation workflow requires designers to generate new designs based on product requirements, heavily relying on their personal expertise and experience. To advance human-AI collaboration design and assist designers in the idea-generation process, this paper proposes an Object Combination Generative Adversarial Network (OC-GAN) for combinational creativity. The proposed method includes an image encoder module and a cross-domain object combination generator module. The image encoder module captures and encodes image structure information into latent space, while the cross-domain object combination generator module leverages GANs to combine object images based on user preferences, producing new design images. A design case study is used to evaluate the new ideation approach and reveal not only strong cross-domain concept combination capabilities but also improvement in designers' workflow and provision of novelty to the design case.HighlightsAn AI approach to improve the efficiency of idea generation in the design process.A case study evaluates its support for idea generation and design creativity.The OC-GAN is used for multi-domain object image combining tasks.Exemplifies the feasibility of human-AI collaboration design for enhancing creativity.
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Journal articleHuppe M, Myant C, 2026,
3D tibial HU reconstruction from biplanar X-rays utilizing a hybrid PCA-CNN framework
, Computers in Biology and Medicine, Vol: 202, ISSN: 0010-4825High-resolution Computed Tomography (CT) is the gold standard medical imaging technique for bone assessment. However, its clinical use is limited by high radiation dose (8.8 mSv; biplanar X-rays 1.4 mSv), cost, and reduced accessibility. These barriers are particularly significant for patients requiring frequent imaging. This study introduces a novel hybrid framework combining statistical intensity modeling with Deep Learning to reconstruct 3D tibial CT volumes including internal density distributions from biplanar radiographs. The method employs principal component analysis (PCA) to capture intensity variations in a compact latent space and trains a convolutional neural network (CNN) to regress PCA coefficients directly from radiographs. The framework was developed and validated using 60 subjects from the publicly available Korea Institute of Science and Technology Information (KISTI) database. Compared to ground truth CT, it achieved a mean absolute error of 127.17 ± 12.08 Hounsfield Units (HU), a structural similarity index of 0.8558 ± 0.0215, and a peak signal-to-noise ratio of 21.40 ± 0.78 dB. The method has the potential to achieve substantial radiation dose reduction compared to conventional CT while preserving sufficient anatomical detail for potential clinical tasks such as patient-specific implant planning and bone quality triage. However, the actual dose reduction depends on clinical imaging protocols and requires validation through protocol-matched dosimetry on actual radiographs. Moreover, it produces interpretable outputs that reflect anatomical intensity variations (e.g., cortical vs. trabecular regions), demonstrating feasibility for hybrid statistical-Deep Learning bone reconstruction. The proposed pipeline establishes a foundation for reduced-dose 3D bone imaging and offers a pathway toward clinical translation pending validation on real-world radiographic data.
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Journal articleMcKenzie T, Meyer-Kahlen N, Schlecht SJ, 2026,
On the role of speech similarity in the detection of room acoustic differences.
, J Acoust Soc Am, Vol: 159, Pages: 1373-1384Spatial audio systems are typically evaluated in comparative listening tests using the same source signal for each condition {such as ABX: ITU-R BS.1116-3 [(2015a) Methods for the Subjective Assessment of Small Impairments in Audio Systems (International Telecommunication Union, Geneva, Switzerland)] and multiple stimulus with hidden reference and anchor ITU-R BS.1534-3 [(2015b) Methods for the Subjective Assessment of Intermediate Quality Level of Audio Systems (International Telecommunication Union, Geneva, Switzerland)]}. However, in augmented reality (AR) scenarios, it is infeasible that the same sound source would exist at the same position in space, both real and virtual; instead, each sound source will emit a different signal. To investigate this discrepancy, a perceptual study is conducted on the effect of source signal similarity when distinguishing different room acoustics conditions. Specifically, these conditions are binaural room impulse responses measured at different distances from the source, modified to all use the same direct sound. Three classes of source signal are investigated in a three-alternative forced choice paradigm: the same speech signal for all conditions, the same speaker but a different sentence for each condition, and a different speaker and a different sentence for each condition. Results show that using different speech recordings significantly reduces the ability to identify differences in room acoustics. This suggests that spatial audio system fidelity requirements could vary depending on the source signals used in the target application; AR audio evaluation should use different signals for comparisons.
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Conference paperLissillour O, Deterding S, Evans A, 2026,
What’s the point? How users functionalise points in gamified systems
, New York, 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26), Publisher: ACMPoints are widely used design elements in gamified systems. Yet how they motivate is still unclear: what motivational meaning or functional significance do users ascribe to points and when? To answer this question, we conducted a semi-structured interview study with 27 users of two popular gamified platforms, Duolingo and Habitica. Through reflexive thematic analysis, we constructed six different types of functionalisation variously proposed in prior gamification and personal informatics work but often not empirically supported. We highlight the importance of functional design detail (such as points should proportionally reward effort) and derive design guidelines.
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Journal articleThrän J, Green TC, Shorten R, 2026,
Levelised cost of demand response: estimating the cost-competitiveness of flexible demand
, Energy Conversion and Management, Vol: 349, ISSN: 0196-8904To make well-informed investment decisions, energy system stakeholders require reliable cost frameworks for demand response and storage technologies. While the levelised cost of storage permits comprehensive cost comparisons between different storage technologies, no generic cost measure for the comparison of different demand response schemes exists. This paper introduces the levelised cost of demand response, which is an analogous measure to the levelised cost of storage but crucially differs from it by considering consumer reward payments. Additionally, the value factor from cost estimations of variable renewable energy is adapted to account for the variable availability of demand response. The levelised cost of demand response is estimated for four direct load control schemes and twelve storage applications, and then contrasted against literature values for the levelised cost of the most competitive storage technologies. The direct load control schemes are vehicle-to-grid, smart charging, smart heat pumps, and heat pumps with thermal storage. The results show that only heat pumps with thermal storage consistently outcompete storage technologies, with EV-based schemes being competitive for some applications. The results and the underlying methodology offer a tool for energy system stakeholders to assess the competitiveness of demand response schemes even with limited user data.
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Journal articleServi A, Gardner-Bougaard E, Mohamed S, et al., 2026,
Early Evaluation of IMAGINATOR 2.0 Intervention Targeting Self-Harm in Young People: Single-Arm Feasibility Trial.
, JMIR Form Res, Vol: 10BACKGROUND: Self-harm (SH) affects around 20% of all young people in the United Kingdom. Treatment options for SH remain limited and those available are long and costly and may not suit all young people. There is an urgent need to develop new scalable interventions to address this gap. IMAGINATOR is a novel imagery-based intervention targeting SH initially developed for individuals aged 16 to 25 years. It is a blended digital intervention delivering functional imagery training via therapy sessions and a smartphone app. OBJECTIVE: This study aimed to pilot a new version of the app, IMAGINATOR 2.0, extended to adolescents from the age of 12 years and coproduced with a diverse group of young people with lived experience. Our aim was also to test the feasibility and acceptability of delivering IMAGINATOR 2.0 in secondary mental health services. METHODS: A total of 4 co-design workshops were conducted online with UK-based lived-experience co-designers aged 14-25 years to develop the IMAGINATOR 2.0 app. The intervention was then piloted with participants recruited from West London NHS Trust Tier 2 Child and Adolescent Mental Health Services and adult Mental Health Integrated Network Teams. Participants received 3 face-to-face functional imagery training sessions in which the app was introduced and 5 brief phone support sessions. Outcome assessments were conducted after completing therapy, approximately 3 months post baseline. Two focus groups gathered the therapists' perspectives on IMAGINATOR 2.0's acceptability and means of improvement. For quantitative data, descriptives are reported. Qualitative data were analyzed using a coproduced thematic analysis method with young people with lived experiences. RESULTS: Overall, 83 participants were referred, and 29 (gender: n=28 women, n=1 transgender; mean age 18.9, SD 3.74 years) were eligible and completed screening. Of the 27 participants who started, 59% (n=16) completed therapy per protocol, while only 15 (55.6%) completed
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Journal articleAngeliki M, Picinali L, Vicente T, 2026,
A pilot study to assess the challenges and efficacy of two hearing loss simulations
, npj Acoustics, ISSN: 3005-141XDeveloping accurate and customisable hearing loss (HL) simulations is crucial for understanding and raising awareness of the challenge faced by individuals with HL. This pilot study assesses challenges in perceptually validating two real-time audio effects plugin HL simulations: the 3D Tune-In (3DTI) Toolkit and the Queen Mary University of London (QMUL) plugin. Both simulatecommon HL deficits, with 3DTI offering greater customization. A pilot listening study was conducted involving normal-hearing listeners with simulated HL and those with real HL, focusing on mild-to-moderate high-frequency hearing loss. Audiometric tests and psychoacoustic tasks were employed, including gap and tone detection in noise, perceived sound intensity, andintelligibility tests. Results from two real HL listeners guided simulation adjustments for normal-hearing participants. Initial findings suggest reasonable accuracy in replicating spectral resolution and perceived sound intensity, but variability in intelligibility and temporal resolution tests indicates room for improvement in both implementations. This study highlights the need forenhanced customisation to improve accuracy and applicability, offering insights into development challenges. Furthermore, the employed methodology proves to be effective, offering valuable insight into challenges and biases that can occur during testing sessions, while highlighting the necessity for further research. This could include additional HL listeners in order to refine and develop more precise tools for understanding and addressing HL.
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Journal articleTu Y, Wu B, Martínez-Pañeda E, 2026,
Phase field modelling of cracking and capacity fade in core-shell cathode particles for lithium-ion batteries
, Applied Energy, Vol: 403, ISSN: 0306-2619Core-shell electrode particles are a promising morphology control strategy for high-performance lithium-ion batteries. However, experimental observations reveal that these structures remain prone to mechanical failure, with shell fractures and core-shell debonding occurring after a single charge. In this work, we present a novel, comprehensive computational framework to predict and gain insight into the failure of core-shell morphologies and the associated degradation in battery performance. The fully coupled chemo-mechano-damage model presented captures the interplay between mechanical damage and electrochemical behaviours, enabling the quantification of particle cracking and capacity fade. Both bulk material fracture and interface debonding are captured by utilising the phase field method. We quantify the severity of particle cracking and capacity loss through case studies on a representative core-shell system (NMC811@NMC532). The results bring valuable insights into cracking patterns, underlying mechanisms, and their impact on capacity loss. Surface cracks are found to initiate when a significantly higher lithium concentration accumulates in the core compared to the shell. Interfacial debonding is shown to arise from localised hoop stresses near the core-shell interface, due to greater shell expansion. This debonding develops rapidly, impedes lithium-ion transport, and can lead to more than 10 % capacity loss after a single discharge. Furthermore, larger particles may experience crack branching driven by extensive tensile zones, potentially fragmenting the entire particle. The framework developed can not only bring new insight into the degradation mechanisms of core-shell particles but also be used to design electrode materials with improved performance and extended lifetime.
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Journal articleAlmukhtar A, Batcup C, Jagannath S, et al., 2026,
Understanding sustainability in operating theatres: an ethnographic study to determine drivers of unsustainable behaviours
, Annals of Surgery Open, ISSN: 2691-3593BackgroundClimate change is the biggest threat to human health. Paradoxically, the healthcare sector is a major contributor to climate change, and operating theatres are among the highest sources of emissions. Unsustainable practices are actions that compromise environmental, social, and financial sustainability, leading to unnecessary resource use, avoidable harm to the wider population, and reduced ability to provide effective healthcare in the future. Drivers of unsustainable practices and barriers to sustainability in practice (a top priority identified by the James Lind Alliance Priority Setting Partnership) are unexplored, hindering interventions which can help meet net-zero targets within healthcare. We conducted the first known ethnographic study to investigate behaviours related to sustainability in operating theatres, and their influences on those behaviours to inform the design of effective behaviour change interventions.MethodsNon-participant ethnographic observations with opportunistic discussions in elective general surgical operating theatres were conducted between June and December 2023 at two university hospitals in Central London. Data were collected until saturation using a template developed during the initial observations. Inductive thematic analysis was conducted, with sub-themes (influences) deductively mapped to the Theoretical Domains Framework (TDF).ResultsTwenty-six procedures were observed (42 hours). Unsustainable behaviours included: (i) unnecessary and inappropriate glove use, potentially compromising safety (average 8-10 pairs per operation), (ii) incorrect waste disposal, (iii) unnecessary package opening, and (iv) energy waste. Thematic analysis generated 6 themes and 16 influences (mapped to 9 TDF domains). Key themes were that sustainable practices are “infrequent and inconsistent” due to limited awareness (Knowledge) and low environmental concerns (Memory, Attention and Decision Processes). Unsustainable behaviours we
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Journal articleJin X, Yu Z, Nanayakkara T, 2026,
Bioinspired Tapered-Spring Turbulence Sensor for Underwater Flow Detection
, IEEE Sensors Journal, ISSN: 1530-437XThis paper presents a bio-inspired underwater whisker sensor for robust hydrodynamic disturbance detection and efficient signal analysis based on Physical Reservoir Computing (PRC). The design uses a tapered nylon spring with embedded accelerometers to achieve spatially distributed vibration sensing and frequency separation along the whisker. Towing-tank experiments and computational fluid dynamics simulations confirmed that the whisker effectively distinguishes vortex regimes across different fin angles and maintains Strouhal scaling with flow velocity, where higher speeds increase vibration intensity without affecting the dominant frequencies. Frequency-domain analysis, Shannon entropy, and machine learning further validated the sensing performance: vortex shedding frequencies were identified with less than 10% error, entropy captured the transition from coherent vortex streets to turbulence, and logistic regression achieved 86.0% classification accuracy with millisecond-level inference. Importantly, the sensing objective of this work is to characterize repeatable and physically interpretable hydrodynamic disturbances, which provide a controlled basis for evaluating how the tapered geometry encodes flow-induced vibrations. Under this scope, the demonstrated frequency–spatial decoupling and multi-modal responses show that structurally encoded whisker sensing provides a scalable and real-time solution for underwater perception, wake tracking, and turbulence-aware navigation in autonomous marine robots.
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Journal articleDocherty R, Vamvakeros A, Cooper SJ, 2026,
Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation
, Advanced Intelligent SystemsThe features of self-supervised vision transformers (ViTs) contain strong semantic and positional information relevant to downstream tasks like object localization and segmentation. Recent works combine these features with traditional methods like clustering, graph partitioning or region correlations to achieve impressive baselines without finetuning or training additional networks. Upsampled features are leveraged from ViT networks (e.g., DINOv2) in two workflows: in a clustering-based approach for object localization and segmentation and paired with standard classifiers in weakly supervised materials segmentation. Both show strong performance on benchmarks, especially in weakly supervised segmentation where the ViT features capture complex relationships inaccessible to classical approaches. It is expected that the flexibility and generalizability of these features will both speed up and strengthen materials characterization, from segmentation to property-prediction.
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Journal articleZhao Y, Chen Q, Li H, et al., 2026,
Recurrent U-Net-based Graph Neural Network (RUGNN) for accurate deformation predictions in sheet material forming
, Advanced Engineering Informatics, Vol: 69, ISSN: 1474-0346In recent years, various artificial intelligence-based surrogate models have been proposed to provide rapid manufacturability predictions of material forming processes. However, traditional AI-based surrogate models, typically built with scalar or image-based neural networks, are limited in their ability to capture complex 3D spatial relationships and to operate in a permutation-invariant manner. To overcome these issues, emerging graph-based surrogate models are developed using graph neural networks. This study developed a new graph neural network surrogate model named Recurrent U Net-based Graph Neural Network (RUGNN). The RUGNN model can achieve accurate predictions of sheet material deformation fields across multiple forming timesteps. The RUGNN model incorporates Gated Recurrent Units (GRUs) to model temporal dynamics and a U-Net inspired graph-based downsample/upsample mechanism to handle spatial long-range dependencies. A novel ’node-to-surface’ contact representation method was proposed, offering significant improvements in computational efficiency for large-scale contact interactions. The RUGNN model was validated using a cold forming case study and a more complex hot forming case study using aluminium alloys. Results demonstrate that the RUGNN model provides accurate deformation predictions closely matching ground truth FE simulations and outperforming several baseline GNN architectures. Model tuning was also performed to identify suitable hyperparameters, training strategies, and input feature representations. These results demonstrate that RUGNN is a reliable approach to support sheet material forming design by enabling accurate manufacturability predictions.
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Journal articleVicente T, González-Toledo D, Cuevas-Rodríguez M, et al., 2026,
Exploring the relationship between task difficulty, head-related transfer function and spatial release from masking in a speech-on-speech experiment
, Hearing Research, Vol: 470, ISSN: 0378-5955It is known that individuals make use of spatial hearing cues to improve the audibility of a target signal and separate it from competing sounds. This phenomenon is known as spatial release from masking (SRM). Recent research has shown that this happens also when sources are located in the median plane, where interaural differences are limited. When assessing this within virtual conditions, it has been shown that employing individually measured head-related transfer functions (HRTFs) results in higher SRM abilities compared to using non-individual filters. In a previously published work, we found that Spanish speakers benefit from individual HRTFs when discriminating a target English speech from a single masker in the median plane. This study replicates the protocol of that previous work, varying the number of maskers and participants’ English proficiency levels to explore relationships among task difficulty and HRTF use. Results from a first experiment show that English speakers behave differently to Spanish ones; their SRM advantage is not significant. We suggest that this is due to their language proficiency, which allows them to rely on spectral glimpsing alone, that is, exploiting spectro-temporal gaps between voices rather than spectral cues introduced by spatial separation. A second experiment introduces a second speech masker, co-located with the first; by making the task more complex, participants seem to increase their reliance on spatial cues, resulting in significant effects of masker position and HRTF. This highlights a trade-off between the use of target glimpsing and spatial cues and the need for further exploration into how task difficulty influences SRM with different HRTFs.
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Journal articleWieberneit F, Crisostomi E, Quinn A, et al., 2026,
Optimal Battery Sizing for Urban Electric Vehicles: Balancing Purchase Cost and Charging Inconvenience
, IEEE Access, Vol: 14, Pages: 10552-10567Electric vehicles (EVs) are central to sustainable mobility systems. The optimal dimensioning of their batteries, however, is a topic of ongoing research. Large battery capacities may provide superior convenience, but this benefit is mediated by the available charging infrastructure and must be weighed against increased cost and mass. This paper introduces a quantitative framework to identify privately optimal EV battery capacities in urban settings, by jointly optimizing upfront vehicle cost and charging inconvenience cost. For this purpose, we: 1) derive a closed form surrogate model for charging inconvenience as a function of EV, user, and infrastructure characteristics, improving on existing studies by explicitly incorporating charging-related detours and infrastructure congestion effects; 2) demonstrate, through simulation and analytical models in abstract as well as realistic (Paris) scenarios, how charging inconvenience is jointly shaped by battery capacity and charging infrastructure; 3) introduce an optimization framework to determine privately optimal battery capacities; and 4) show how optimal battery capacities can be influenced through strategic investments in charging infrastructure and tax/incentive policies. The proposed framework can be used to identify optimal battery capacities in a given charging environment, but also to estimate the convenience benefits of charging infrastructure investments, providing a nuanced framework for optimizing the design of cost-effective, convenient and sustainable EV systems.
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Journal articleJin X, Xiao B, Wang H, et al., 2026,
A Multisensor Wearable Device Based on Capacitive Microphone Sensors for Robust Human–Robot Interaction in Smart Home Environments
, IEEE Sensors Journal, Vol: 26, Pages: 2935-2945, ISSN: 1530-437XThis article presents a capacitive microphone sensor (CMS)-based multisensor fusion wearable system for intuitive and responsive control of mobile manipulators in smart home environments. The wearable integrates structurally optimized CMSs, inertial measurement units (IMUs), vibration motors, and pressure sensors to detect forearm muscle activity and arm motion in real time. To enhance signal fidelity, each CMS is embedded in a conical acoustic chamber filled with damping silicone, significantly improving robustness under noisy conditions. A convolutional neural network (CNN)-based classification model is employed to interpret six combined gesture–force classes, achieving 93.89% offline accuracy. Real-time experiments involving five participants yielded 83.33% practical accuracy with an average system latency of 1.2 s. The wearable system enables real-time gesture recognition, adaptive force feedback, and precise robot control, validated through object manipulation tasks under various texture and weight conditions. These results highlight the feasibility and effectiveness of a CMS-driven multisensor fusion wearable device for low-latency, noise-resilient, and user-adaptive assistive robotics in complex indoor environments.
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Journal articlePinson P, 2026,
Editorial and introduction to the special section on the Bernanke's review of the Bank of England's forecasting activities
, INTERNATIONAL JOURNAL OF FORECASTING, Vol: 42, Pages: 1-2, ISSN: 0169-2070 -
Journal articleGao J, Chaudhuri B, Astolfi A, 2026,
An explicit direct method for transient stability analysis of multimachine power systems with nonzero transfer conductances
, IEEE Transactions on Control Systems Technology, Vol: 34, Pages: 112-122, ISSN: 1063-6536We propose an explicit analytical direct method for the transient stability analysis of multimachine power systems with nonzero transfer conductances (TCs). The proposed method addresses two issues. In the first issue, we study the transient stabilization of the entire power system through excitation control design. To this end, a globally well-defined Lyapunov function is constructed, and a locally well-defined dynamic passivity-based control law is proposed. The closed-loop equilibrium is therefore guaranteed to be locally asymptotically stable. In the second issue, we study the transient stability property of post-fault initial states. To this end, an optimization-based approach to calculate the critical level set of the proposed Lyapunov function is proposed. This allows to estimate an explicit region of attraction of the closed-loop equilibrium. Therefore, the transient stability property of a post-fault initial state can be directly assessed. A case study on the IEEE 10-machine 39-bus power system, to demonstrate the performance and effectiveness of the proposed direct method, is presented.
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Journal articleQin D, Pinson P, Wang Y, 2026,
Load Forecasting Model Trading: A Cost-Oriented and Auction-Based Approach
, IEEE Transactions on Smart Grid, Vol: 17, Pages: 766-779, ISSN: 1949-3053Data sharing is essential for accurate load forecasting and efficient energy management, yet data exchange remains severely constrained by a lack of effective economic incentives. Data markets have emerged as a potential solution by incentivizing the exchange of data and forecasting resources among stakeholders. Existing data market mechanisms, often designed around trading raw data or forecast outputs, face multiple barriers—such as privacy concerns, valuation misaligned with real operational benefits, unilateral pricing, computationally intensive allocation, and inflexible asset adaptation—that limit their practicality for real-world energy applications. The aim of this paper is to address these challenges by proposing a novel market framework that treats pre-trained forecasting models as tradable assets, thereby fundamentally redefining the data market paradigm. Specifically, a cost-oriented evaluation approach that links model quality to downstream operational costs is first established as the foundation throughout the entire market process. Subsequently, we propose a bilateral iterative model auction mechanism to enable efficient transactions between the buyer and sellers while maximizing social welfare. Furthermore, we propose a model adaptation strategy, including model fine-tuning and ensembling, for the buyer to enhance the applicability of purchased models to his decision-making problem. Case studies in building energy management based on public datasets demonstrate that our approach converges to the socially optimal solution, allowing all participants to benefit: sellers are appropriately compensated for providing high-quality models, and buyers achieve significant operational cost reductions through the utilization of traded models.
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Journal articleChen L, Cai Z, Cheang W, et al., 2026,
AskNatureGPT: an LLM-driven concept generation method based on bio-inspired design knowledge
, Journal of engineering design, Vol: 37, Pages: 238-272, ISSN: 0954-4828Concept generation is the early stage in the engineering design process to produce initial design concepts. By applying bio-inspired design (BID) knowledge, designers can employ biological analogies for solution-driven BID concepts. Solution-driven BID starts with knowledge of a specific biological system for technical design. Despite the proven benefits of solution-driven BID, the gap between biological solutions and engineering problems hinders its effective application, with designers frequently encountering misaligned problem-solution pairs and facing multidisciplinary knowledge gaps in concept generation. Therefore, this research proposes a large language model (LLM) based concept generation method – AskNatureGPT – to automatically search for problems, transfer biological analogy, and generate solution-driven BID concepts in the form of natural language. A concept generator and two evaluators are identified and fine-tuned based on the LLM. The method is evaluated by an ablation study, machine-based quantitative assessments, subjective human evaluations, and a case study. The results show our method can generate solution-driven BID concepts with high quality.
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Journal articleBallaben R, Astolfi A, Braun P, et al., 2026,
Orchestrating on-board sensors for global hybrid robust stabilization of unicycles
, AUTOMATICA, Vol: 183, ISSN: 0005-1098 -
Journal articlePope VC, Stewart R, Chew E, 2026,
Timing structures in live comedy: A matched-sequence approach to mapping performance dynamics.
, PNAS Nexus, Vol: 5Live performance is a ubiquitous cultural and social behavior that has not yet benefited from systematic scientific study. We present a computational methodology that visualizes and describes timing structures in live performance, showcasing their engineering. This novel analysis framework, Topology Analysis of Matching Sequences (TAMS), automatically detects matching sequences and maps their timing. Locating material that is repeated across performances reveals the skill behind apparently effortless communication between performer and audience. Applying TAMS to two stand-up comedy tours uncovered structural features at the macro- and microlevels, including consistently placed novel material at the beginning of shows and sections dedicated to tightly timed repeated material. TAMS also provides a new frame of reference for examining audience-performer dynamics through speech microtiming and laughter. TAMS can be applied to other forms of repeated speech, such as political stump speeches, as well as extended to other types of performance, such as dance.
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Conference paperBarumerli R, Privitera AG, Fasolato A, et al., 2026,
Spatialized Looming Sounds in Virtual Reality: Reaction Times and Localization Accuracy
, 2025 International Conference on Extended Reality-XR-Annual, Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 254-265, ISSN: 0302-9743
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