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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 articleDing Z, Attar HR, Wang H, et al., 2024,
Integrating convolutional neural network and constitutive model for rapid prediction of stress-strain curves in fibre reinforced polymers: a generalisable approach
, Materials and Design, Vol: 241, ISSN: 0264-1275Despite recent advancements in using machine learning (ML) techniques to establish the microstructure-property linkage for composites’ representative volume elements (RVEs), challenges persist in effectively characterising the effect of microstructural randomness on material properties. This complexity arises from the difficulty of expressing randomness as definitive variables and its intertwined relations with other factors, such as material constituents. Such complexities result in limitations in generalising ML models across different material constituents. Conventional solutions to these challenges usually necessitate large datasets, which require considerable computational resources, for an accurate and generalisable ML models to be trained. This paper presents an innovative approach to tackling these challenges by integrating a high-accuracy convolutional neural network (CNN) with a novel microstructure-factored constitutive model (MCM). The MCM, rooted from classic empirical constitutive modelling, effectively segregates the microstructural and constituting material effects, extending the generalisability and thus significantly enhancing the efficacy of the CNN. This new approach enabled a CNN trained on the transverse stress-strain curves of one set of material constituents (CF/PEEK at 270 °C) to be generalised for the rapid prediction of various sets of material constituents at different temperatures, unseen by the CNN during training, with an average mean absolute percentage error around 3 %.
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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, Pages: 234395-234395, ISSN: 0378-7753 -
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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Journal articleKirby P, Lai H, Horrocks S, et al., 2024,
Patient and public involvement in technology-related dementia research: a scoping review
, JMIR Aging, Vol: 7, ISSN: 2561-7605Background:Technology-related research for people with dementia and their carers often aims to enable people to remain living at home for longer and to prevent unnecessary hospital admissions. To develop research that is person-centred, effective and ethical, patient and public involvement (PPI) is necessary, though may be perceived as more difficult with this cohort. With recent and rapid expansions in health and care related technology, this review explores how, and with what impact, collaborations between researchers and stakeholders such as people with dementia have taken place.Objective:To describe approaches to PPI used to date in technology-related dementia research, along with the barriers and facilitators and impact of PPI in this area.Methods:A scoping review of literature relating to dementia, technology and patient and public involvement was conducted using Medline, PsycINFO, EMBASE and CINAHL. Papers were screened for inclusion by two authors. Data was then extracted using a pre-designed data extraction table by the same two authors; a third author supported resolution of any conflicts at each stage. Barriers and facilitators of undertaking PPI were then examined and themed.Results:Thirty-one papers were included for analysis. The majority (21/31) did not make clear distinctions between activities undertaken as PPI and activities undertaken by research participants, and as such their involvement did not fit easily into the NIHR definition of PPI. Most of this mixed involvement focused on the reviewing or evaluating of technology prototypes. A range of approaches was described, most typically using focus groups or co-design workshops. Nine studies described involvement at multiple stages through the research cycle, sometimes with evidence of sharing of decision-making power. Some studies commented on barriers or facilitators to effective PPI. Challenges identified were often around issues of working with people with significant cognitive impairments, and
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Journal articlePan X, Yan M, Liu Q, et al., 2024,
Electric-field-assisted proton coupling enhanced oxygen evolution reaction.
, Nat Commun, Vol: 15The discovery of Mn-Ca complex in photosystem II stimulates research of manganese-based catalysts for oxygen evolution reaction (OER). However, conventional chemical strategies face challenges in regulating the four electron-proton processes of OER. Herein, we investigate alpha-manganese dioxide (α-MnO2) with typical MnIV-O-MnIII-HxO motifs as a model for adjusting proton coupling. We reveal that pre-equilibrium proton-coupled redox transition provides an adjustable energy profile for OER, paving the way for in-situ enhancing proton coupling through a new "reagent"- external electric field. Based on the α-MnO2 single-nanowire device, gate voltage induces a 4-fold increase in OER current density at 1.7 V versus reversible hydrogen electrode. Moreover, the proof-of-principle external electric field-assisted flow cell for water splitting demonstrates a 34% increase in current density and a 44.7 mW/cm² increase in net output power. These findings indicate an in-depth understanding of the role of proton-incorporated redox transition and develop practical approach for high-efficiency electrocatalysis.
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Journal articleChakrabarti BK, Bree G, Dao A, et al., 2024,
Lightweight Carbon-Metal-Based Fabric Anode for Lithium-Ion Batteries.
, ACS Appl Mater InterfacesLithium-ion battery electrodes are typically manufactured via slurry casting, which involves mixing active material particles, conductive carbon, and a polymeric binder in a solvent, followed by casting and drying the coating on current collectors (Al or Cu). These electrodes are functional but still limited in terms of pore network percolation, electronic connectivity, and mechanical stability, leading to poor electron/ion conductivities and mechanical integrity upon cycling, which result in battery degradation. To address this, we fabricate trichome-like carbon-iron fabrics via a combination of electrospinning and pyrolysis. Compared with slurry cast Fe2O3 and graphite-based electrodes, the carbon-iron fabric (CMF) electrode provides enhanced high-rate capacity (10C and above) and stability, for both half cell and full cell testing (the latter with a standard lithium nickel manganese oxide (LNMO) cathode). Further, the CMFs are free-standing and lightweight; therefore, future investigation may include scaling this as an anode material for pouch cells and 18,650 cylindrical batteries.
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Journal articleKallitsis E, Lindsay JJ, Chordia M, et al., 2024,
Think global act local: The dependency of global lithium-ion battery emissions on production location and material sources
, Journal of Cleaner Production, Vol: 449, ISSN: 0959-6526The pursuit of low-carbon transport has significantly increased demand for lithium-ion batteries. However, the rapid increase in battery manufacturing, without adequate consideration of the carbon emissions associated with their production and material demands, poses the threat of shifting the bulk of emissions upstream. In this article, a life cycle assessment (LCA) model is developed to account for the cradle-to-gate carbon footprint of lithium-ion batteries across 26 Chinese provinces, 20 North American locations and 19 countries in Europe and Asia. Analysis of published LCA data reveals significant uncertainty associated with the carbon emissions of key battery materials; their overall contribution to the carbon footprint of a LIB varies by a factor of ca. 4 depending on production route and source. The links between production location and the gate-to-gate carbon footprint of battery manufacturing are explored, with predicted median values ranging between 0.1 and 69.5 kg CO2-eq kWh−1. Leading western-world battery manufacturing locations in the US and Europe, such as Kentucky and Poland are found to have comparable carbon emissions to Chinese rivals, even exceeding the carbon emissions of battery manufacturing in several Chinese provinces. Such resolution on material and energy contributions to the carbon footprint of LIBs is essential to inform policy- and decision-making to minimise the carbon emissions of the battery value chain. Given the current status quo, the global carbon footprint of the lithium-ion battery industry is projected to reach up to 1.0 Gt CO2-eq per year within the next decade. With material supply chain decarbonisation and energy savings in battery manufacturing, a lower estimate of 0.5 Gt CO2-eq per year is possible.
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Journal articleMohammed AA, Yao K, Ragaisyte I, et al., 2024,
Stable and homogeneous SPION-infused Photo-Resins for 3D-printing magnetic hydrogels
, Applied Materials Today, Vol: 373D printing of magnetic stimuli hydrogels has shown promise in low-resolution extrusion printing but integrating superparamagnetic iron oxide nanoparticles (SPION) into water-based photo-resins has posed challenges. Rapid agglomeration and sedimentation of SPION in photo-resins require continuous mixing during printing, leading to uneven nanoparticle (NP) distribution and inconsistent magnetic actuation. Here, we optimise the use of citric acid (CA) and l-sodium ascorbate (LA) as capping agents on the SPION's surface, before trialling them with photo-resins. Ultimately, we present a two-step approach to overcome these limitations, enabling high-resolution SLA-based 3D printing of hydrogels. By employing CA in both SPION and photo-resin preparation, we achieve a highly stable mixture that requires no agitation during printing, resulting in magnetically responsive hydrogels. This methodology can be applied to various photo-resin formulations, ensuring uniform NP distribution and enabling the 3D printing of stimuli-responsive materials for applications in soft robotics, aquatic micro-swimmers, and soft actuators. The breakthrough in stable and homogenous SPION-infused photo-resins has broad implications for tissue engineering, drug delivery, and regenerative medicine, offering novel biocompatible materials with resistance to stress and deformation. This approach can be extended to other NP with poor dispersion in hydrogels, paving the way for advanced functional materials in diverse applications.
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Journal articleWang H, Ding Z, Chen X, et al., 2024,
Experimental characterisation and constitutive modelling of the intra-ply tensile and shear properties of unidirectional fibre reinforced thermoplastics (UD FRTPs) under solid-state stamp forming conditions
, Composites Part A: Applied Science and Manufacturing, Vol: 179, ISSN: 1359-835XTo enable the success of solid-state stamp forming of unidirectional fibre reinforced thermoplastics (UD FRTPs), it is essential to accurately characterise and model the material deformation under desired conditions. This paper comprehensively investigates the intra-ply tensile and shear properties of unidirectional carbon fibre reinforced polyamide 6 (UD CF/PA6), which is a type of commonly used UD FRTP. To accomplish this, tensile and V-Notched Rail (VNR) shear tests are conducted for characterising the intra-ply transverse tensile and longitudinal shear properties, respectively. The temperature effects (180 – 220 ℃, at 0.01 /s for the transverse tensile deformation and at 0.04 /s for longitudinal shear deformation) and strain-rate effects (0.001 – 0.25 /s for transverse tensile deformation and 0.004 – 0.4 /s for the longitudinal shear deformation, both are at 200 ℃) are studied. It is found that temperature has significant effects on the intra-ply deformation properties, while the strain-rate effects are marginal. This paper also proposes a new physically based constitutive model considering all the deformable constituents, i.e., the polymer constituent reinforced by fibres (PrF) and the polymer-fibre interface (P-F). This model not only shows good prediction of the thermomechanical properties of UD CF/PA6 under intra-ply deformations, but also gives insights into the deformation mechanisms. The new physically based constitutive model is successfully embedded into Finite Element Analysis (FEA) software and validated through accurate prediction of intra-ply deformation of a CF/PA6 specimen under bias-extension. The methodologies and model developed here offer an effective tool for predicting the intra-ply deformation behaviours and guiding the solid-state stamp forming process of UD FRTPs.
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Journal articleYu X, Singh G, Kaur A, et al., 2024,
An assessment of Sikh turban's head protection in bicycle incident scenarios
, Annals of Biomedical Engineering, Vol: 52, Pages: 946-957, ISSN: 0090-6964Due to religious tenets, Sikh population wear turbans and are exempted from wearing helmets in several countries. However, the extent of protection provided by turbans against head injuries during head impacts remains untested. One aim of this study was to provide the first-series data of turbans' protective performance under impact conditions that are representative of real-world bicycle incidents and compare it with the performance of bicycle helmets. Another aim was to suggest potential ways for improving turban's protective performance. We tested five different turbans, distinguished by two wrapping styles and two fabric materials with a size variation in one of the styles. A Hybrid III headform fitted with the turban was dropped onto a 45 degrees anvil at 6.3 m/s and head accelerations were measured. We found large difference in the performance of different turbans, with up to 59% difference in peak translational acceleration, 85% in peak rotational acceleration, and 45% in peak rotational velocity between the best and worst performing turbans. For the same turban, impact on the left and right sides of the head produced very different head kinematics, showing the effects of turban layering. Compared to unprotected head impacts, turbans considerably reduce head injury metrics. However, turbans produced higher values of peak linear and rotational accelerations in front and left impacts than bicycle helmets, except from one turban which produced lower peak head kinematics values in left impacts. In addition, turbans produced peak rotational velocities comparable with bicycle helmets, except from one turban which produced higher values. The impact locations tested here were covered with thick layers of turbans and they were impacted against flat anvils. Turbans may not provide much protection if impacts occur at regions covered with limited amount of fabric or if the impact is against non-flat anvils, which remain untested. Our analysis shows that turbans can
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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, ISSN: 2377-3766 -
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, ISSN: 1087-0547 -
Journal articleBallou N, Sewall CJR, Ratcliffe J, et al., 2024,
Registered Report Evidence Suggests No Relationship Between Objectively Tracked Video Game Playtime and Wellbeing Over 3 Months
, Technology, Mind, and Behavior, ISSN: 2689-0208Recent years have seen intense research, media, and policy debate on whether amount of time spent playing video games (“playtime”) affects players’ well-being. Existing research has used cross-sectional designs with easy-to-obtain but unreliable self- report measures of playtime or, in rare instances, obtained industry data on objectively tracked playtime but only for individual games, not a player’s total playtime across games. Further, researchers have raised concerns that publication bias and a lack of differentiation between exploratory and con rmatory research have undermined the credibility of the evidence base. As a result, we still do not know whether well-being affects playtime, playtime affects well-being, both, or neither. To track people’s playtime across multiple games, we developed a method to log playtime on the Xbox platform. In a 12-week, six-wave panel study of adult U.S./U.K. Xbox-predominant players (414 players, 2036 completed surveys), we investigated within-person temporal relations between objectively measured playtime and well-being. Across multiple preregistered model speci cations, we found that the within-person prospective relationships between playtime and well-being, or vice versa, were not practically signi cant—even the largest associations were unlikely to register a perceptible impact on a player’s well-being. These results support the growing body of evidence that playtime is not the primary factor in the relationship between gaming and mental health for the majority of players and that research focus should be on the context and quality of gameplay instead.
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Journal articleBallou N, Sewall CJR, Ratcliffe J, et al., 2024,
Supplemental Material for Registered report evidence suggests no relationship between objectively tracked video game playtime and well-being over 3 months.
, Technology, Mind, and Behavior, Vol: 5 -
Journal articleHogg A, Jenkins M, Liu H, et al., 2024,
HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection
, IEEE Transactions on Audio, Speech and Language Processing, ISSN: 1558-7916An individualised (HRTF) is very important for creating realistic (VR) and (AR) environments. However, acoustically measuring high-quality HRTFs requires expensive equipment and an acoustic lab setting. To overcome these limitations and to make this measurement more efficient HRTF upsampling has been exploited in the past where a high-resolution HRTF is created from a low-resolution one. This paper demonstrates how (GAN) can be applied to HRTF upsampling. We propose a novel approach that transforms the HRTF data for direct use with a convolutional (SRGAN). This new approach is benchmarked against three baselines: barycentric upsampling, (SH) upsampling and an HRTF selection approach. Experimental results show that the proposed method outperforms all three baselines in terms of (LSD) and localisation performance using perceptual models when the input HRTF is sparse (less than 20 measured positions).
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Journal articleTooby J, Till K, Gardner A, et al., 2024,
When to pull the trigger: conceptual considerations for approximating head acceleration events using instrumented mouthguards
, Sports Medicine, ISSN: 0112-1642Head acceleration events (HAEs) are acceleration responses of the head following external short-duration collisions. The potential risk of brain injury from a single high-magnitude HAE or repeated occurrences makes them a significant concern in sport. Instrumented mouthguards (iMGs) can approximate HAEs. The distinction between sensor acceleration events, the iMG datum for approximating HAEs and HAEs themselves, which have been defined as the in vivo event, is made to highlight limitations of approximating HAEs using iMGs. This article explores the technical limitations of iMGs that constrain the approximation of HAEs and discusses important conceptual considerations for stakeholders interpreting iMG data. The approximation of HAEs by sensor acceleration events is constrained by false positives and false negatives. False positives occur when a sensor acceleration event is recorded despite no (in vivo) HAE occurring, while false negatives occur when a sensor acceleration event is not recorded after an (in vivo) HAE has occurred. Various mechanisms contribute to false positives and false negatives. Video verification and post-processing algorithms offer effective means for eradicating most false positives, but mitigation for false negatives is less comprehensive. Consequently, current iMG research is likely to underestimate HAE exposures, especially at lower magnitudes. Future research should aim to mitigate false negatives, while current iMG datasets should be interpreted with consideration for false negatives when inferring athlete HAE exposure.
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Journal articleFerraro P, Penzkofer A, King C, et al., 2024,
Feedback control for distributed ledgers: an attack mitigation policy for DAG-based DLTs
, IEEE Transactions on Automatic Control, Pages: 1-8, ISSN: 0018-9286In this paper we present a feedback approach to the design of an attack mitigation policy for DAG-based Distributed Ledgers. We develop a model to analyse the behaviour of the ledger under the so called Tips Inflation Attack , which endangers the liveness of transactions, and we design a control strategy to counteract this attack strategy. The efficacy of this approach is showcased through a theoretical analysis, in the form of two theorems about the stability properties of the ledger with and without the controller, and extensive Monte Carlo simulations of an agent-based model of the distributed ledger.
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Journal articleAbayazid FF, Ghajari M, 2024,
Viscoelastic circular cell honeycomb helmet liners for reducing head rotation and brain strain in oblique impacts
, Materials and Design, Vol: 239, ISSN: 0264-1275Rotational head motion is one of the major contributors to brain tissue strain during head impacts, which damages axons and vessels and leads to traumatic brain injury. Helmet technologies have come to market promising enhanced protection against such rotational head motion. We recently introduced novel air-filled viscoelastic cell arrays and showed that their shear response under oblique impacts can be tailored through altering the cell wall curvature. We found that concave cells provide shear stiffness that is a few folds larger than that of convex cells. Here we test whether altering the cell curvature can reduce head rotational kinematics and brain strain and whether the viscoelastic cell arrays outperform the reference EPS foam-based liner. To test these hypotheses, we incorporate the viscoelastic cell arrays in a bicycle helmet liner. We use validated finite element models of the helmet and replace the liner with validated finite element models of the cellular cell arrays. We simulate oblique impacts at different locations to represent a wide range of real-world bicycle head impacts. In all cases, the head kinematics and brain deformation metrics indicate significant improvements with the novel cell arrays over the conventional EPS liner. We show that the shear-compliant cell arrays can reduce head rotational acceleration by as much as 64 % and brain strain by 69 %, but not in all impact locations. Cell arrays with similar axial stiffness yet lower shear stiffness often bottomed out, indicating that a considerable amount of energy is dissipated via cell shearing around the impact zone. Our results show that placement of cells with varying amounts of shear stiffness should be optimised, with the most shear-compliant cells near the crown and the least near the temples. This study shows the promising performance of viscoelastic cell arrays in protecting the head and brain under oblique impacts and provides avenues for optimising the distribution of their compress
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Journal articleBallou N, Sewall CJR, Ratcliffe J, et al., 2024,
Registered report evidence suggests no relationship between objectively-tracked video game playtime and wellbeing over 3 months
, Technology, Mind, and Behavior, Vol: 5, ISSN: 2689-0208Recent years have seen intense research, media and policy debate on whether amount of time spent playing video games (“playtime”) affects players’ wellbeing. Existing research has used cross-sectional designs with easy-to-obtain but unreliable self-report measures of playtime, or, in rare instances, obtained industry data on objectively-tracked playtime but only for individual games, not a player’s total playtime across games. Further, researchers have raised concerns that publication bias and a lack of differentiation between exploratory and confirmatory research have undermined the credibility of the evidence base. As a result, we still do not know whether wellbeing affects playtime, playtime affects wellbeing, both, or neither. To track people’s playtime across multiple games, we developed a method to log playtime on the Xbox platform. In a 12-week, 6-wave panel study of adult US/UK Xbox-predominant players (414 players, 2036 completed surveys), we investigated within-person temporal relations between objectively-measured playtime and wellbeing. Across multiple preregistered model specifications, we found that the within-person prospective relationships between playtime and wellbeing, or vice versa, were not practically significant—even the largest associations were unlikely to register a perceptible impact on a player’s wellbeing. These results support the growing body of evidence that playtime is not the primary factor in the relationship between gaming and mental health for the majority of players, and that research focus should be on the context and quality of gameplay instead.
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Journal articleKakadellis S, Muranko Ż, Harris ZM, et al., 2024,
Closing the loop: enabling circular biodegradable bioplastic packaging flow through a systems-thinking framework
, Cleaner and Responsible Consumption, Vol: 12, ISSN: 2666-7843Within a circular bioeconomy, biodegradable bioplastics (BBPs) have been promoted in fast-moving consumer goods to contribute towards closed-loop material flows. Consumers play a key role as enablers of these flows, provided they accept, understand and dispose of BBPs appropriately. Informed by focus groups, a framework combining multiple behavioural and design theories was developed to identify and structure systemic factors influencing the flow of BBPs through the consumption phase, with a focus on disposal. An exploratory network analysis based on a survey of 457 and 284 participants from two universities in the United Kingdom and the United States was then conducted to explore the interplay between factors and intentions to dispose of BBPs in different waste streams. Access to adequate organic waste infrastructure and pre-existing knowledge of BBP terminology and disposal routes were most strongly associated with intentions to dispose of BBPs alongside food waste. Mapping and facilitating consumer behaviour in tackling BBP waste is pivotal in designing sustainable systems for these materials.
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Journal articleSadek M, Kallina E, Bohné T, et al., 2024,
Challenges of responsible AI in practice: scoping review and recommended actions
, AI and Society: the journal of human-centered systems and machine intelligence, ISSN: 0951-5666Responsible AI (RAI) guidelines aim to ensure that AI systems respect democratic values. While a step in the right direction, they currently fail to impact practice. Our work discusses reasons for this lack of impact and clusters them into five areas: (1) the abstract nature of RAI guidelines, (2) the problem of selecting and reconciling values, (3) the difficulty of operationalising RAI success metrics, (4) the fragmentation of the AI pipeline, and (5) the lack of internal advocacy and accountability. Afterwards, we introduce a number of approaches to RAI from a range of disciplines, exploring their potential as solutions to the identified challenges. We anchor these solutions in practice through concrete examples, bridging the gap between the theoretical considerations of RAI and on-the-ground processes that currently shape how AI systems are built. Our work considers the socio-technical nature of RAI limitations and the resulting necessity of producing socio-technical solutions.
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Journal articlePandey SR, Pinson P, Popovski P, 2024,
Strategic Coalition for Data Pricing in IoT Data Markets
, IEEE Internet of Things Journal, Vol: 11, Pages: 6454-6468This article establishes a market for trading Internet of Things (IoT) data that is used to train machine learning (ML) models. The data, either raw or processed, is supplied to the market platform through a network, and the price of such data is controlled based on the value it brings to the ML model under the adversity of the correlation property of data. Eventually, a simplified distributed solution for a data trading mechanism is derived that improves the mutual benefit of devices and the market. Our key proposal is an efficient algorithm for data markets that jointly addresses the challenges of availability and heterogeneity in participation, as well as the transfer of trust and the economic value of data exchange in IoT networks. The proposed approach establishes the data market by reinforcing collaboration opportunities between devices with correlated data to limit information leakage. Therein, we develop a network-wide optimization problem that maximizes the social value of coalition among the IoT devices of similar data types; at the same time, it minimizes the cost due to network externalities, i.e., the impact of information leakage due to data correlation, as well as the opportunity costs. Finally, we reveal the structure of the formulated problem as a distributed coalition game and solve it following the simplified split-and-merge algorithm. Simulation results show the efficacy of our proposed mechanism design toward a trusted IoT data market, with up to 32.72% gain in the average payoff for each seller.
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Journal articleHan H, Qin C, Xu D, et al., 2024,
Elevating intracellular action potential recording in cardiomyocytes: A precision-enhanced and biosafe single-pulse electroporation system.
, Biosens Bioelectron, Vol: 246Action potentials play a pivotal role in diverse cardiovascular physiological mechanisms. A comprehensive understanding of these intricate mechanisms necessitates a high-fidelity intracellular electrophysiological investigative approach. The amalgamation of micro-/nano-electrode arrays and electroporation confers substantial advantages in terms of high-resolution intracellular recording capabilities. Nonetheless, electroporation systems typically lack precise control, and commonly employed electroporation modes, involving tailored sequences, may escalate cellular damage and perturbation of normal physiological functions due to the multiple or higher-intensity electrical pulses. In this study, we developed an innovative electrophysiological biosensing system customized to facilitate precise single-pulse electroporation. This advancement serves to achieve optimal and uninterrupted intracellular action potential recording within cardiomyocytes. The refinement of the single-pulse electroporation technique is realized through the integration of the electroporation and assessment biosensing system, thereby ensuring a consistent and reliable means of achieving stable intracellular access. Our investigation has unveiled that the optimized single-pulse electroporation technique not only maintains robust biosafety standards but also enables the continuous capture of intracellular electrophysiological signals across an expansive three-day period. The universality of this biosensing system, adaptable to various micro/nano devices, furnishes real-time analysis and feedback concerning electroporation efficacy, guaranteeing the sustained, secure, and high-fidelity acquisition of intracellular data, thereby propelling the field of cardiovascular electrophysiological research.
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Conference paperLi Y, Zhou Y, Shen C, et al., 2024,
E-textile sleeve with graphene strain sensors for arm gesture classification of mid-air interactions
, TEI '24: Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction, Publisher: ACM, Pages: 1-10Arm gestures play a pivotal role in facilitating natural mid-air interactions. While computer vision techniques aim to detect these gestures, they encounter obstacles like obfuscation and lighting conditions. Alternatively, wearable devices have leveraged interactive textiles to recognize arm gestures. However, these methods predominantly emphasize textile deformation-based interactions, like twisting or grasping the sleeve, rather than tracking the natural body movement.This study bridges this gap by introducing an e-textile sleeve system that integrates multiple ultra-sensitive graphene e-textile strain sensors in an arrangement that captures bending and twisting along with an inertia measurement unit into a sports sleeve. This paper documents a comprehensive overview of the sensor design, fabrication process, seamless interconnection method, and detachable hardware implementation that allows for reconfiguring the processing unit to other body parts. A user study with ten participants demonstrated that the system could classify six different fundamental arm gestures with over 90% accuracy.
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Journal articleFan Y, Olsson E, Johannessen B, et al., 2024,
Manipulation of Transition Metal Migration via Cr-Doping for Better-Performance Li-Rich, Co-Free Cathodes
, ACS Energy Letters, Vol: 9, Pages: 487-496The irreversible migration of transition metals is a primary issue, resulting in detrimental structural changes and poor battery performance in Li-rich layered oxide (LLO) cathodes. Herein, we propose that manipulating the migration of transition metals between octahedral and tetrahedral sites effectively inhibits undesirable phase transitions by stabilizing the delithiated structure of LLOs at high potential. This is demonstrated by introducing Cr into the Co-free LLO, Li1.2Ni0.2Mn0.6O2. A new spinel-like phase, accompanied by significant lattice variation, was observed in the heavily cycled Co-free LLO at high potential by using operando synchrotron characterizations. Benefiting from a well-maintained solid-solution reaction after long-term cycling, Cr-doped Li1.2Ni0.2Mn0.6O2 delivers up to 99% of its initial discharge capacity after 200 cycles at 1C (∼200 mAh g-1), far surpassing the pristine material (∼74%). The work provides valuable insights into the structural degradation mechanisms of LLOs and underscores the importance of stabilizing the delithiated structure at high potential.
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Journal articleFerraro P, Zhao L, King C, et al., 2024,
Personalized feedback control, social contracts, and compliance strategies for ensembles
, IEEE Internet of Things Journal, Vol: 11, Pages: 3942-3955, ISSN: 2327-4662This article describes the use of acrlong DLTs as a means to create personalized social nudges and to influence the behavior of agents in a smart city environment. Specifically, we present a scheme to price personalized risk in sharing economy applications. We provide proofs for the convergence of the proposed stochastic system and we validate our approach through the use of extensive Monte Carlo simulations.
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Journal articleLu X, Lian GJ, Parker J, et al., 2024,
Effect of carbon blacks on electrical conduction and conductive binder domain of next-generation lithium-ion batteries
, Journal of Power Sources, Vol: 592, ISSN: 0378-7753High energy and power density are key requirements for next-generation lithium-ion batteries. One way to improve the former is to reduce the binder and conductive additive content. Carbon black is an important additive that facilitates electronic conduction in lithium-ion batteries and affects the conductive binder domain although it only occupies 5–8% of the electrode mass. However, the function of the structure of carbon black on short- and long-range electronic contacts and pores in the electrode is still not clear and has not been systematically researched in detail. In this work, five carbon blacks with different BET surface areas, oil absorption numbers and ordered graphitic carbon content were investigated. It was found that the ratio of disordered amorphous carbon to ordered graphitic carbon in carbon blacks strongly influences the short- and long-range electrical conduction, and the BET surface area highly affects the pore structure and ionic conductivity in the electrode. Its optimum ratio, indicated by the Raman density ID/IG, is 0.93–0.95. The recommended BET surface area was 130–200 m2/g for this experimental range. The results of this study can provide guidance for the screening of carbon blacks in the lithium-ion battery industry.
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Journal articleXu M, Liu Y, Yang K, et al., 2024,
Minimally invasive power sources for implantable electronics
, Exploration, Vol: 4, ISSN: 2766-8509As implantable medical electronics (IMEs) developed for healthcare monitoring and biomedical therapy are extensively explored and deployed clinically, the demand for non-invasive implantable biomedical electronics is rapidly surging. Current rigid and bulky implantable microelectronic power sources are prone to immune rejection and incision, or cannot provide enough energy for long-term use, which greatly limits the development of miniaturized implantable medical devices. Herein, a comprehensive review of the historical development of IMEs and the applicable miniaturized power sources along with their advantages and limitations is given. Despite recent advances in microfabrication techniques, biocompatible materials have facilitated the development of IMEs system toward non-invasive, ultra-flexible, bioresorbable, wireless and multifunctional, progress in the development of minimally invasive power sources in implantable systems has remained limited. Here three promising minimally invasive power sources summarized, including energy storage devices (biodegradable primary batteries, rechargeable batteries and supercapacitors), human body energy harvesters (nanogenerators and biofuel cells) and wireless power transfer (far-field radiofrequency radiation, near-field wireless power transfer, ultrasonic and photovoltaic power transfer). The energy storage and energy harvesting mechanism, configurational design, material selection, output power and in vivo applications are also discussed. It is expected to give a comprehensive understanding of the minimally invasive power sources driven IMEs system for painless health monitoring and biomedical therapy with long-term stable functions.
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Journal articleChiara V, Sara C, Kevin S, et al., 2024,
Spatial hearing training in virtual reality with simulated asymmetric hearing loss
, Scientific Reports, Vol: 14, ISSN: 2045-2322Sound localization is essential to perceive the surrounding world and to interact with objects. This ability can be learned across time, and multisensory and motor cues play a crucial role in the learning process. A recent study demonstrated that when training localization skills, reaching to the sound source to determine its position reduced localization errors faster and to a greater extent as compared to just naming sources’ positions, despite the fact that in both tasks, participants received the same feedback about the correct position of sound sources in case of wrong response. However, it remains to establish which features have made reaching to sound more effective as compared to naming. In the present study, we introduced a further condition in which the hand is the effector providing the response, but without it reaching toward the space occupied by the target source: the pointing condition. We tested three groups of participants (naming, pointing, and reaching groups) each while performing a sound localization task in normal and altered listening situations (i.e. mild-moderate unilateral hearing loss) simulated through auditory virtual reality technology. The experiment comprised four blocks: during the first and the last block, participants were tested in normal listening condition, while during the second and the third in altered listening condition. We measured their performance, their subjective judgments (e.g. effort), and their head-related behavior (through kinematic tracking). First, people’s performance decreased when exposed to asymmetrical mild-moderate hearing impairment, more specifically on the ipsilateral side and for the pointing group. Second, we documented that all groups decreased their localization errors across altered listening blocks, but the extent of this reduction was higher for reaching and pointing as compared to the naming group. Crucially, the reaching group leads to a greater error reduction for the side where th
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