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Journal articleChen L, Cai Z, Jiang Z, et al., 2024,
AskNatureNet: a divergent thinking tool based on bio-inspired design knowledge
, Advanced Engineering Informatics: the science of supporting knowledge-intensive activities, Vol: 62, ISSN: 0954-1810Divergent thinking is a process in design by exploring multiple possible solutions, is crucial in the early stages of design to break fixation and expand the design ideation. Design-by-Analogy promotes divergent thinking, by studying solutions have solved similar problems and using this knowledge to make inferences and solve problems in new and unfamiliar situations. Bio-inspired design (BID) is a form of design by analogy and its knowledge provides diverse sources for analogy, making BID knowledge as a potential source for divergent thinking. Existing BID database has focused on collecting BID cases and facilitating the retrieval of biological knowledge. Despite its success, applying BID knowledge into divergent thinking still encounters challenge, as the association between source domain and target domain are always limited within a single case. In this work, a novel approach is proposed to support divergent thinking from three subsequent phases: encoding, retrieval and mapping. Specifically, biological knowledge is encoded in a triple form by employing a large language model (LLM) to extract key information from a well-known BID knowledge base. The created triples are implemented in a semantic network to facilitate bidirectional retrieval modes: problem-driven and solution-driven, as well as mapping for divergent thinking. The mapping algorithm calculates the semantic similarity between nodes in the semantic network based on their attributes in three progressive steps by following the paradigm of divergent thinking. The proposed approach is implemented as tool called AskNatureNet,1 which supports divergent thinking by retrieving and mapping knowledge in a visualized interactive semantic network. An ideation case study on evaluating the effectiveness of AskNatureNet shows that our tool is capable of supporting divergent thinking efficiently.
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Journal articleBallou N, Denisova A, Ryan R, et al., 2024,
The Basic Needs in Games Scale (BANGS): A new tool for investigating positive and negative video game experiences
, INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, Vol: 188, ISSN: 1071-5819 -
Journal articleJakobsson Støre S, Van Zalk N, Granander Schwartz W, et al., 2024,
The relationship between social anxiety disorder and ADHD in adolescents and adults: a systematic review
, Journal of Attention Disorders, Vol: 28, Pages: 1299-1319, ISSN: 1087-0547Objective:This review aimed to systematically gather empirical data on the link between social anxiety disorder and ADHD in both clinical and non-clinical populations among adolescents and adults.Method:Literature searches were conducted in PsycInfo, PubMed, Scopus, and Web of Science, resulting in 1,739 articles. After screening, 41 articles were included. Results were summarized using a narrative approach.Results:The prevalence of ADHD in adolescents and adults with SAD ranged from 1.1% to 72.3%, while the prevalence of SAD in those with ADHD ranged from 0.04% to 49.5%. Studies indicate that individuals with both SAD and ADHD exhibit greater impairments. All studies were judged to be of weak quality, except for two studies which were rated moderate quality.Discussion:Individuals with SAD should be screened for ADHD and vice versa, to identify this common comorbidity earlier. Further research is needed to better understand the prevalence of comorbid ADHD and SAD in adolescents.
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Journal articleBonkile M, Jiang Y, Kirkaldy N, et al., 2024,
Is silicon worth it? Modelling degradation in composite silicon–graphite lithium-ion battery electrodes
, Journal of Power Sources, Vol: 606, ISSN: 0378-7753The addition of silicon into graphite lithium-ion battery anodes has the potential to increase cell energy density. However, understanding the complex degradation behaviour in these composite systems remains a research challenge. Here, we developed a coupled electrochemical–mechanical model of a composite silicon/graphite electrode, including stress-driven crack formation and solid electrolyte interphase layer growth for each material, validated with experimental degradation data from an LG M50T cell. The model reveals self-limiting loss of silicon due to decreasing stress in the silicon as the silicon activity shifts to a lower state-of-charge. Higher C-rates can lead to lower degradation due to lower phase utilisation as voltage cut-offs are reached earlier. Increasing silicon content can reduce the stress in the silicon by distributing reaction current density over more material. Using this model, we explored whether the extra capacity from silicon is generally ‘worth’ the faster degradation compared to graphite-only electrodes. The model shows if you use the silicon, you lose it, as the higher initial capacity is rapidly lost with regular high depth-of-discharge events. However, silicon does have value if it enables full graphite utilisation without range anxiety; if high depth-of-discharge events are minimised then graphite’s superior longevity can be utilised while exploiting silicon’s high specific capacity. The model is integrated into PyBaMM (an open-source physics-based modelling platform); providing the research community and industry with the capability to reproduce our results and further explore the dynamic lifetime behaviour of composite electrodes.
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Journal articleLou Z, Min X, Li G, et al., 2024,
Advancing sensing resolution of impedance hand gesture recognition devices
, IEEE Journal of Biomedical and Health Informatics, ISSN: 2168-2194Gestures are composed of motion information (e.g. movements of fingers) and force information (e.g. the force exerted on fingers when interacting with other objects). Current hand gesture recognition solutions such as cameras and strain sensors primarily focus on correlating hand gestures with motion information and force information is seldom addressed. Here we propose a bio-impedance wearable that can recognize hand gestures utilizing both motion information and force information. Compared with previous impedance-based gesture recognition devices that can only recognize a few multi-degrees-of-freedom gestures, the proposed device can recognize 6 single-degree-of-freedom gestures and 20 multiple-degrees-of-freedom gestures, including 8 gestures in 2 force levels. The device uses textile electrodes, is benchmarked over a selected frequency spectrum, and uses a new drive pattern. Experimental results show that 179 kHz achieves the highest signal-to-noise ratio (SNR) and reveals the most distinct features. By analyzing the 49,920 samples from 6 participants, the device is demonstrated to have an average recognition accuracy of 98.96%. As a comparison, the medical electrodes achieved an accuracy of 98.05%.
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Journal articleLiu H, You SS, Gao Z, et al., 2024,
Next generation of gastrointestinal electrophysiology devices
, NATURE REVIEWS GASTROENTEROLOGY & HEPATOLOGY, ISSN: 1759-5045 -
Journal articleWorrell C, Pollard R, Weetman T, et al., 2024,
Exploring the research needs, barriers and facilitators to the collection of biological data in adolescence for mental health research: a scoping review protocol paper.
, BMJ Open, Vol: 14INTRODUCTION: While research into adolescent mental health has developed a considerable understanding of environmental and psychosocial risk factors, equivalent biological evidence is lacking and is not representative of economic, social and ethnic diversity in the adolescent population. It is important to understand the possible barriers and facilitators to conduct this research. This will then allow us to improve our understanding of how biology interacts with environmental and psychosocial risk factors during adolescence. The objective of this scoping review is to identify and understand the needs, barriers and facilitators related to the collection of biological data in adolescent mental health research. METHODS AND ANALYSIS: Reviewers will conduct a systematic search of PubMed, Medline, Scopus, Cochrane, ERIC, EMBASE, ProQuest, EBSCO Global Health electronic databases, relevant publications and reference lists to identify studies published in the English language at any time. This scoping review will identify published studies exploring mental health/psychopathology outcomes, with biological measures, in participants between the ages of 11 and 18 and examine the reported methodology used for data collection. Data will be summarised in tabular form with narrative synthesis and will use the methodology of Levac et al, supplemented by subsequent recommendations from the Joanna Briggs Institute Scoping Review Methodology. ETHICS AND DISSEMINATION: Ethical approval is not required for this scoping review. The scoping review will be conducted with input from patient and public involvement, specifically including young people involved in our study ('Co-producing a framework of guiding principles for Engaging representative and diverse cohorts of young peopLE in Biological ReseArch in menTal hEalth'-www.celebrateproject.co.uk) Youth Expert Working Group. Dissemination will include publication in peer-reviewed journals, academic presentations and on the project website.
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Conference paperSmith F, Sadek M, Mougenot C, 2024,
Empowering end-users in co-designing AI: an AI literacy card-based toolkit for non-technical audiences
, 36th International BCS Human-Computer Interaction Conference -
Journal articleDocherty R, Squires I, Vamvakeros A, et al., 2024,
SAMBA: a trainable segmentation web-app with smart labelling
, Journal of Open Source Software, Vol: 9, Pages: 6159-6159, ISSN: 2475-9066Segmentation is the assigning of a semantic class to every pixel in an image and is a prerequisite for various statistical analysis tasks in materials science, like phase quantification, physics simulations or morphological characterisation. The wide range of length scales, imaging techniques and materials studied in materials science means any segmentation algorithm must generalise to unseen data and support abstract, user-defined semantic classes. Trainablesegmentation is a popular interactive segmentation paradigm where a classifier is trained to map from image features to user drawn labels. SAMBA is a trainable segmentation tool that uses Meta’s Segment Anything Model (SAM) for fast, high-quality label suggestions and arandom forest classifier for robust, generalisable segmentations. It is accessible in the browser (https://www.sambasegment.com/), without the need to download any external dependencies. The segmentation backend is run in the cloud, so does not require the user to have powerfulhardware.
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Journal articleLei G, Docherty R, Cooper SJ, 2024,
Materials science in the era of large language models: a perspective
, Digital Discovery, ISSN: 2635-098XLarge Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code generation to heuristic finding for combinatorial problems. In this paper we offer a perspective on their applicability to materials science research, arguing their ability to handle ambiguous requirements across a range of tasks and disciplines means they could be a powerful tool to aid researchers. We qualitatively examine basic LLM theory, connecting it to relevant properties and techniques in the literature before providing two case studies that demonstrate their use in task automation and knowledge extraction at-scale. At their current stage of development, we argue LLMs should be viewed less as oracles of novel insight, and more as tireless workers that can accelerate and unify exploration across domains. It is our hope that this paper can familiarise materials science researchers with the concepts needed to leverage these tools in their own research.
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Journal articleZhou Y, Sun Y, Li Y, et al., 2024,
A highly durable and UV‐resistant graphene‐based knitted textile sensing sleeve for human joint angle monitoring and gesture differentiation
, Advanced Intelligent Systems, ISSN: 2640-4567Flexible strain sensors based on textiles have attracted extensive attention owing to their light weight, flexibility, and comfort when wearing. However, challenges in integrating textile strain sensors into wearable sensing devices include the need for outstanding sensing performance, long-term monitoring stability, and fast, convenient integration processes to achieve comprehensive monitoring. The scalable fabrication technique presented here addresses these challenges by incorporating customizable graphene-based sensing networks into knitted structures, thus creating sensing sleeves for precise motion detection and differentiation. The performance and real-world application potential of the sensing sleeve are evaluated by its precision in angle estimation and complex joint motion recognition during intra- and intersubject studies. For intra-subject analysis, the sensing sleeve only exhibits a 2.34° angle error in five different knee activities among 20 participants, and the sensing sleeves show up to 94.1% and 96.1% accuracy in the gesture classification of knee and elbow, respectively. For inter-subject analysis, the sensing sleeve demonstrates a 4.21° angle error, and it shows up to 79.9% and 85.5% accuracy in the gesture classification of knee and elbow, respectively. An activity-guided user interface compatible with the sensing sleeves for human motion monitoring in home healthcare applications is presented to illustrate the potential applications.
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Journal articleDudkina E, Bin M, Breen J, et al., 2024,
A comparison of centrality measures and their role in controlling the spread in epidemic networks
, International Journal of Control, Vol: 97, Pages: 1325-1340, ISSN: 0020-7179The ranking of nodes in a network according to their centrality or ``importance'' is a classic problem that has attracted the interest of different scientific communities in the last decades. The COVID-19 pandemic has recently rejuvenated the interest in this problem, as the ranking may be used to decide who should be tested, or vaccinated, first, in a population of asymptomatic individuals. In this paper, we review classic methods for node ranking and compare their performance in a benchmark network that considers the community-based structure of society. The outcome of the ranking procedure is then used to decide which individuals should be tested, and possibly quarantined, first. Finally, we also review the extension of these ranking methods to weighted graphs and explore the importance of weights in a contact network by providing a toy model and comparing node rankings for this case in the context of disease spread.
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Journal articleGodden T, Mulvey B, Redgrave E, et al., 2024,
PaTS-wheel: a passively-transformable single-part wheel for mobile robot navigation on unstructured terrain
, IEEE Robotics and Automation Letters, Vol: 9, Pages: 5512-5519, ISSN: 2377-3766Most mobile robots use wheels that perform well on even and structured ground, like in factories and warehouses. However, they face challenges traversing unstructured terrain such as stepped obstacles. This letter presents the design and testing of the PaTS-Wheel: a Passively-Transformable Single-part Wheel that can transform to render hooks when presented with obstacles. The passive rendering of this useful morphological feature is guided purely by the geometry of the obstacle. The energy consumption and vibrational profile of the PaTS-Wheel on flat ground is comparable to a standard wheel of the same size. In addition, our novel wheel design was tested traversing different terrains with stepped obstacles of incremental heights. The PaTS-Wheel achieved 100% success rate at traversing stepped obstacles with heights ≈70% its diameter, higher than the results obtained for an equivalent wheel ( ≈25% its diameter) and an equivalent wheg ( ≈61% its diameter). This achieves the design objectives of combining the energy efficiency and ride smoothness of wheels with the obstacle traversal capabilities of legged robots, all without requiring any sensors, actuators, or controllers.
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Journal articleWeber C, Gatersleben B, Jagannath S, et al., 2024,
Crowding and aggression during the COVID-19 lockdown in the United Kingdom: The relationship between residential density, subjective crowding, privacy, and aggression
, JOURNAL OF ENVIRONMENTAL PSYCHOLOGY, Vol: 96, ISSN: 0272-4944 -
Journal articleJagannath S, Gatersleben B, Ratcliffe E, et al., 2024,
Flexibility of the home and residents' psychological wellbeing
, JOURNAL OF ENVIRONMENTAL PSYCHOLOGY, Vol: 96, ISSN: 0272-4944 -
Journal articleJagannath S, Gatersleben B, Ratcliffe E, 2024,
Flexibility of the home and residents’ psychological wellbeing
, Journal of Environmental Psychology, Vol: 96, ISSN: 0272-4944BackgroundFlexible homes provide residents with choice and control in how they use and modify their homes to suit their changing needs, but the psychological benefits of flexibility for residents' wellbeing have been underexplored. This paper examines to what extent flexible homes support residents’ wellbeing, what architectural qualities (Architectural Flexibility) are important for wellbeing, and to what extent residents can use these qualities to make changes to home (Behavioural Flexibility) to achieve wellbeing.StudiesThree studies were conducted to examine the relationship between flexibility of the home and residents' psychological wellbeing. Study 1 (N = 187) explored the association between Flexibility and wellbeing. Study 2 (N = 212) examined the mediating nature of the Behavioural Flexibility component in the relationship between Architectural Flexibility of the home and residents' wellbeing. Study 3 (N = 300) examined this relationship further by exploring the influence of residents’ individual factors of Capability and Motivation in the Study 2 model using the COM-B model of behaviour.ResultsStudy 1 showed that residents’ perceptions of flexibility of their homes were positively associated with their hedonic and eudaimonic wellbeing at home, explaining 21% and 15.3% of variance respectively. Study 2 showed that Behavioural Flexibility significantly mediated the relationship between Architectural Flexibility and hedonic and eudaimonic wellbeing. Among the three types of Architectural Flexibility explored in Study 3, the COM-B model of Availability of spaces at home explained the most variance in hedonic and eudaimonic wellbeing, compared to Modifiability and Multifunctionality of spaces. In all models, COM-B components showed varying influence on wellbeing. The mediating nature of Behavioural Flexibility was confirmed in the COM-B model of Modifiability.ConclusionsFlexibility in the built home environment and residents' behaviour of mak
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Journal articleTu Y, Wu B, Ai W, et al., 2024,
Influence of concentration-dependent material properties on the fracture and debonding of electrode particles with core–shell structure
, Journal of Power Sources, Vol: 603, ISSN: 0378-7753Core–shell electrode particle designs offer a route to improved lithium-ion battery performance. However, they are susceptible to mechanical damage such as fracture and debonding, which can significantly reduce their lifetime. Using a coupled finite element model, we explore the impacts of diffusion-induced stresses on the failure mechanisms of an exemplar system with an NMC811 core and an NMC111 shell. In particular, we systematically compare the implications of assuming constant material properties against using Li concentration-dependent diffusion coefficient and partial molar volume. With constant material properties, our results show that smaller cores with thinner shells avoid debonding and fracture regimes. When factoring in a concentration-dependent partial molar volume, the maximum values of tensile hoop stress in the shell are found to be significantly lower than those predicted with constant properties, reducing the likelihood of fracture. Furthermore, with a concentration-dependent diffusion coefficient, significant barriers to full electrode utilisation are observed due to reduced lithium mobility at high states of lithiation. This provides a possible explanation for the reduced accessible capacity observed in experiments. Shell thickness is found to be the dominant factor in precluding structural integrity once the concentration dependency is accounted for. These findings shed new light on the performance and effective design of core–shell electrode particles.
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Journal articlePierrot A, Pinson P, 2024,
On Tracking Varying Bounds When Forecasting Bounded Time Series
, TECHNOMETRICS, ISSN: 0040-1706 -
Conference paperIto A, Taoka Y, Wan E, et al., 2024,
Gaps between reflection frameworks and students’ practice: Implications for design education
, DESIGN 2024, Publisher: Cambridge University Press, Pages: 2865-2874, ISSN: 2732-527XThis paper aims to identify gaps between the reflection frameworks and students’ practice. Through a systematic literature review (PRISMA) and a qualitative survey of students, 12 reflection frameworks were reviewed, and the 13 challenges students faced at design projects in two design schools were identified. The results indicate three gaps between theory and students’ practice: skills of designers, granularities of reflection items, and supports of bridging reflection to next actions. This study provides insights for future development of support tools to bridge the gaps in design education.
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Journal articleSadek M, Calvo RA, Mougenot C, 2024,
Closing the socio–technical gap in AI: the need for measuring practitioners’ attitudes and perceptions
, IEEE Technology and Society Magazine, Pages: 1-4, ISSN: 0278-0097This article discusses the need for artificial intelligence (AI) practitioners to shift their focus from a purely technical mindset toward a more human-centered approach. Technical experts are trained to consider the technical aspects of their work, which can cause them to overlook important socio–technical considerations and implications, resulting in a socio–technical gap in AI-based systems [4]. Unhelpful practitioner cultures can lead to them “rejecting practices or downplaying the importance of values or the possible threats of ignoring them” [1]. While efforts are being made to create ethical and more human-centered AI systems, there is a need for corresponding changes in the attitudes and perceptions of AI practitioners. Practitioners need to move away from a sole focus on compliance with responsible AI guidelines and regulations toward active reflection and empathy based on a true understanding of the profound effects their decisions can have on different stakeholders. However, one problematic barrier to beginning work on interventions that target practitioners’ mindsets and attitudes is the lack of a standardized method for evaluating or measuring the effectiveness of design interventions on their attitudes and perceptions. This article suggests the need for clearer metrics within the human–computer interaction (HCI) community for looking at practitioners’ attitudes toward socio–technical factors in AI design.
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Conference paperSadek M, Constantinides M, Quercia D, et al., 2024,
Guidelines for integrating value sensitive design in responsible AI toolkits
, CHI 2024, Publisher: ACMValue Sensitive Design (VSD) is a framework for integrating human values throughout the technology design process. In parallel, Responsible AI (RAI) advocates for the development of systems aligning with ethical values, such as fairness and transparency. In this study, we posit that a VSD approach is not only compatible, but also advantageous to the development of RAI toolkits. To empirically assess this hypothesis, we conducted four workshops involving 17 early-career AI researchers. Our aim was to establish links between VSD and RAI values while examining how existingtoolkits incorporate VSD principles in their design. Our findings show that collaborative and educational design features within these toolkits, including illustrative examples and open-ended cues, facilitate an understanding of human and ethical values, and empower researchers to incorporate values into AI systems. Drawing on these insights, we formulated six design guidelines for integrating VSD values into the development of RAI toolkits.
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Conference paperRobson N, McPherson A, Bryan-Kinns N, 2024,
Thinking with sound: exploring the experience of listening to an ultrasonic art installation
, CHI Conference on Human Factors in Computing Systems, Publisher: ACMEntanglement theories are well established in HCI discourse. These involve a commitment to view human experience in encounters with technology as relational and contingent, and research apparatuses as co-producers rather than passive observers of phenomena. In this paper, we argue that sound is the sensory modality best suited to the investigation of entanglements. Materialist theoriesof sound and listening guide both the design of a novel interactive sound installation and the methodological approach of a participant study exploring the experience of listening. We present a diffractive analysis whereby micro-phenomenological interview data is read with sonic theories, generating accounts that might otherwise remain mute: the temporal fluctuation and physical feeling ofproximity in listener entanglements with sound, somatic intention setting, and plural interpretations of interactivity. Finally, we offer a series of provocations for HCI to embrace qualities of the sonic and consider epistemological positions grounded in other sense modalities.
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Conference paperMorrison L, McPherson A, 2024,
Entangling entanglement: a diffractive dialogue on HCI and musical interactions
, CHI Conference on Human Factors in Computing Systems, Publisher: ACMIf, as several recent papers claim, we have entered a new wave of “Entanglement HCI,” then we are still at a liminal stage prior to consensus around which sources underpin this paradigm shift or how they might inform actionable approaches to design practice. Now is the time to interpret technosocial mediation from a range of disciplinary perspectives, rather than settling on a narrow canon of literature. To this end, our paper enacts a diffractive dialogue between researchers from different disciplines, focusing on digital musical instruments to examine how technical knowledge from design and engineering can be read against the grain of critical theories from music, media, and cultural studies. Drawing on two object lessons—keyboards and step sequencers, plus their remediations inrecent musical interaction research—we highlight interdependencies of theory, design, and practice, and we show how the idea of entanglement is itself entangled in a cross-disciplinary web.
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Conference paperKao D, Ballou N, Gerling K, et al., 2024,
How does juicy game feedback motivate? Testing curiosity, competence, and effectance
, New York, CHI 2024, Publisher: ACM‘Juicy’ or immediate abundant action feedback is widely held to make video games enjoyable and intrinsically motivating. Yet we do not know why it works: Which motives are mediating it? Which features afford it? In a pre-registered (n=1,699) online experiment, we tested three motives mapping prior practitioner discourse— effectance, competence, and curiosity—and connected design fea- tures. Using a dedicated action RPG and a 2x2+control design, we varied feedback amplification, success-dependence, and variabil- ity and recorded self-reported effectance, competence, curiosity, and enjoyment as well as free-choice playtime. Structural equa- tion models show curiosity as the strongest enjoyment and only playtime predictor and support theorised competence pathways. Success dependence enhanced all motives, while amplification un- expectedly reduced them, possibly because the tested condition unintentionally impeded players’ sense of agency. Our study ev- idences uncertain success affording curiosity as an underappre- ciated moment-to-moment engagement driver, directly supports competence-related theory, and suggests that prior juicy game feel guidance ties to legible action-outcome bindings and graded success as preconditions of positive ‘low-level’ user experience.
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Conference paperHu X, Li J, Picinali L, et al., 2024,
HRTF spatial upsampling in the spherical harmonics domain employing a generative adversarial network
, 27th International Conference on Digital Audio Effects (DAFx24)A Head-Related Transfer Function (HRTF) is able to capture alterations a sound wave undergoes from its source before it reaches the entrances of a listener’s left and right ear canals, and is imperative for creating immersive experiences in virtual and augmented reality (VR/AR). Nevertheless, creating personalized HRTFs demands sophisticated equipment and is hindered by time-consuming data acquisition processes. To counteract these challenges, various techniques for HRTF interpolation and up-sampling have been proposed. This paper illustrates how Generative Adversarial Networks (GANs) can be applied to HRTF data upsampling in the spherical harmonics domain. We propose using Autoencoding Generative Adversarial Networks (AE-GAN) to upsample low-degree spherical harmonics coefficients and get a more accurate representation of the full HRTF set. The proposed method is bench-marked against two baselines: barycentric interpolation and HRTFselection. Results from log-spectral distortion (LSD) evaluation suggest that the proposed AE-GAN has significant potential for upsampling very sparse HRTFs, achieving 17% improvement over baseline methods.
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Journal articleTillfors M, Van Zalk N, Boersma K, et al., 2024,
Longitudinal links between adolescent social anxiety and depressive symptoms: stressful experiences at home, in school and with peers
, Nordic Psychology, Vol: 76, Pages: 230-249, ISSN: 0029-1463Social anxiety and depressive symptoms often co-occur during early adolescence but contributing factors to this development are still a matter of debate. This study examined the role of daily stressors (peers, school and homelife) in the links between adolescent social anxiety and depressive symptoms. 7-8th graders at Time 1 (N = 2,752, Mage = 13.65; 47.5% girls) were followed across three time-points. Cross-lagged path models showed that depressive symptoms predicted later social anxiety, but not vice versa. Bidirectional links were identified between peer stress and social anxiety, and between school/homelife stress and depressive symptoms, respectively. Indirect effects of social anxiety, depressive symptoms, and daily stressors were found, though stressors did not mediate the links between social anxiety and depressive symptoms (or vice versa). Our findings indicate an intricate role of daily stressors in different domains on the links between social anxiety and depressive symptoms.
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Journal articlePuglia M, Parker L, Clube RKM, et al., 2024,
The circular policy canvas: Mapping the European Union's policies for a sustainable fashion textiles industry
, Resources, Conservation and Recycling, Vol: 204, ISSN: 0921-3449Policy plays a major role in enabling and accelerating the shift to a Circular Economy (CE). Transitioning to a CE in the Fashion Textiles Industry (FTI) requires a holistic policy approach through comprehensive and coherent policy interventions across the resource life cycle. This paper introduces the novel Circular Policy Canvas tool to systematically and visually map CE policies across six dimensions (policy environment, resource life cycle, CE loop, CE strategy, system element and circular business model). This is applied to thirty FTI policies in the EU policy landscape. The canvas enables policymakers and researchers to assess policies to identify gaps and priorities for CE policy development. The findings determine the recency of the EU policy agenda for a circular FTI meaning that there are gaps in terms of coverage and coherence. In particular, the study identifies a lack of attention to displacing the linear economy, a concentration of policies in the head and tail of the resource life cycle with gaps in the core, a dominance of policies in the outer over the inner loop and inadequate coverage of policies focused on actors, infrastructure and resources.
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Journal articleSquires I, Foster JM, Galvis A, et al., 2024,
Investigating the Effect of the Separation of Scales in Reduced Order Battery Modelling: Implications on the Validity of the Newman Model
, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 171, ISSN: 0013-4651 -
Conference paperLiuqing C, Zhaojun J, Duowei X, et al., 2024,
BIDTrainer: an LLMs-driven education tool for enhancing the understanding and reasoning in bio-inspired design
, CHI Conference on Human Factors in Computing Systems (CHI ’24), Publisher: ACM, Pages: 1-20Bio-inspired design (BID) fosters innovations in engineering. Learning BID is crucial for developing multidisciplinary innovation skillsof designers and engineers. Current BID education aims to enhancelearners’ understanding and analogical reasoning skills. However,it often heavily relies on the teachers’ expertise. When learnerspursue independent learning using some educational tools, theyface challenges in understanding and reasoning practice withinthis multidisciplinary field. Additionally, evaluating their learningoutcomes comprehensively becomes problematic. Addressing thesechallenges, we introduce a LLMs-driven BID education methodbased on a structured ontology and three strategies: enhancingunderstanding through LLMs-enpowered "learning by asking", assisting reasoning by providing hints and feedback, and assessinglearning outcomes through benchmarking against existing BIDcases. Implementing the method, we developed BIDTrainer, a BID education tool. User studies indicate that learners using BIDTrainerunderstood BID knowledge better, reason faster with higher interactivity than the baseline, and BIDTrainer assessed the learningoutcomes consistent with experts.
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Journal articleRuan H, Kirkaldy N, Offer G, et al., 2024,
Diagnosing health in composite battery electrodes with explainable deep learning and partial charging data
, Energy and AI, Vol: 16, ISSN: 2666-5468Lithium-ion batteries with composite anodes of graphite and silicon are increasingly being used. However, their degradation pathways are complicated due to the blended nature of the electrodes, with graphite and silicon degrading at different rates. Here, we develop a deep learning health diagnostic framework to rapidly quantify and separate the different degradation rates of graphite and silicon in composite anodes using partial charging data. The convolutional neural network (CNN), trained with synthetic data, uses experimental partial charging data to diagnose electrode-level health of tested batteries, with errors of less than 3.1% (corresponding to the loss of active material reaching ∼75%). Sensitivity analysis of the capacity-voltage curve under different degradation modes is performed to provide a physically informed voltage window for diagnostics with partial charging data. By using the gradient-weighted class activation mapping approach, we provide explainable insights into how these CNNs work; highlighting regions of the voltage-curve to which they are most sensitive. Robustness is validated by introducing noise to the data, with no significant negative impact on the diagnostic accuracy for noise levels below 10 mV, thus highlighting the potential for deep learning approaches in the diagnostics of lithium-ion battery performance under real-world conditions. The framework presented here can be generalised to other cell formats and chemistries, providing robust and explainable battery diagnostics for both conventional single material electrodes, but also the more challenging composite electrodes.
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