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  • Journal article
    Cacciarelli D, Kulahci M, 2024,

    Active learning for data streams: a survey

    , Machine Learning, Vol: 113, Pages: 185-239, ISSN: 0885-6125

    <jats:title>Abstract</jats:title><jats:p>Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream. The problem of minimizing the cost associated with collecting labeled observations has gained a lot of attention in recent years, particularly in real-world applications where data is only available in an unlabeled form. Annotating each observation can be time-consuming and costly, making it difficult to obtain large amounts of labeled data. To overcome this issue, many active learning strategies have been proposed in the last decades, aiming to select the most informative observations for labeling in order to improve the performance of machine learning models. These approaches can be broadly divided into two categories: static pool-based and stream-based active learning. Pool-based active learning involves selecting a subset of observations from a closed pool of unlabeled data, and it has been the focus of many surveys and literature reviews. However, the growing availability of data streams has led to an increase in the number of approaches that focus on online active learning, which involves continuously selecting and labeling observations as they arrive in a stream. This work aims to provide an overview of the most recently proposed approaches for selecting the most informative observations from data streams in real time. We review the various techniques that have been proposed and discuss their strengths and limitations, as well as the challenges and opportunities that exist in this area of research.</jats:p>
  • Journal article
    Zhao L, Ferraro P, Shorten R, 2024,

    A smart mask to enforce social contracts based on IOTA Tangle.

    , PLoS One, Vol: 19

    In this paper we present the design for a smart-mask to mitigate the impact of an airborne virus such as COVID-19. The design utilises recent results from feedback control theory over a distributed ledger that have been developed to enforce compliance in a pseudo-anonymous manner. The design is based on the use of the IOTA distributed ledger. A hardware-in-the-loop simulation based on indoor positioning, paired with Monte-Carlo simulations, is developed to demonstrate the efficacy of the designed prototype.
  • Journal article
    Hogg A, Jenkins M, Liu H, Squires I, Cooper S, Picinali Let al., 2024,

    HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection

    , IEEE Transactions on Audio, Speech and Language Processing, Vol: 32, Pages: 2085-2099, ISSN: 1558-7916

    An 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).
  • Journal article
    Sadan MK, Lian GJ, Smith RM, Cumming Det al., 2023,

    Co, Ni-free ultrathick free-standing dry electrodes for sustainable lithium-ion batteries

    , ACS Applied Energy Materials, Vol: 6, Pages: 12166-12171, ISSN: 2574-0962

    The conventional method of manufacturing lithium-ion battery electrodes employs a complex slurry casting process with solvents that are not environmentally friendly and process parameters that are often difficult to control. This study explores a solvent-free dry electrode fabrication process of Co- and Ni-free LiMn2O4 (LMO) cathodes using a fibrillated polymer, polytetrafluoroethylene (PTFE). A thick, dry electrode (265–368 μm, 30–64 mg cm–2) of LMO cathode was prepared successfully for the first time. Altering the conductive additives in the LMO dry electrode revealed multiwalled carbon nanotubes (CNTs) as the best conducting agent for dry electrode formulation in terms of conductivity and rate performance. Additionally, an all-dry electrode full cell consisting of both a dry electrode cathode (LMO) and an anode (LTO) delivered a stable cycling performance with a capacity retention of 82.8% after 200 cycles, demonstrating the scope for all-dry electrode full cells for future applications.
  • Journal article
    Pan Y, Ruan H, Regmi YN, Wu B, Wang H, Brandon Net al., 2023,

    A Machine Learning Accelerated Hierarchical 3D+1D Model for Proton Exchange Membrane Fuel Cells

    , ECS Meeting Abstracts, Vol: MA2023-02, Pages: 1706-1706

    <jats:p> Physics-based continuum models for proton exchange membrane fuel cells (PEMFCs) are an essential tool for fuel cell design and management. To date, many continuum models, ranging from 1D to 3D, have been developed for PEMFCs. Although computationally efficient, 1D models do not account for heterogeneity in flow fields, which negatively impact their accuracy. In contrast, 2D and 3D models are usually more representative of actual operating conditions but computationally intensive due to the coupled partial differential equations and large number of mesh elements involved. To overcome these issues, a hierarchical approach that combines a 2D/3D description of flow fields, gas diffusion layers (GDLs) and a simplified microporous layer (MPL)/catalyst layer (CL)/membrane sub-model has been proposed in the literature. However, studies based on this method often use a simplified or 0D MPL/CL/membrane sub-model, whose results may deviate from a full 1D description due to the neglected nonlinearity, especially at higher loads.</jats:p> <jats:p>In this study, we present a computationally efficient 3D+1D hierarchical model for PEMFCs accelerated by machine learning. The 3D model, which captures the two-phase flow in the gas channels and GDLs, is coupled with a full 1D description of the MPLs, membrane, CLs, and CL agglomerates by exchanging boundary values and fluxes, as shown in the figure. To avoid the high computing cost increase associated with the full 1D description, we develop a physics-informed neural network to replace the 1D sub-model for coupling with the 3D model, while maintaining the full description of fuel cell internal states. Large synthetic datasets are generated using the 1D model for training the neural network, ensuring the accuracy of the model. The proposed 3D+1D model is validated against experimentally obtained polarization curves and high frequency resistances under different relative humidities. The proposed
  • Journal article
    Govey-Scotland J, Johnstone L, Myant C, Friddin Met al., 2023,

    Towards a skin-on-a-chip for screening the dermal absorption of cosmetics

    , Lab on a Chip: miniaturisation for chemistry, physics, biology, materials science and bioengineering, Vol: 23, Pages: 5068-5080, ISSN: 1473-0189

    Over the past few decades, there have been increasing global efforts to limit or ban the use of animals for testing cosmetic products. This ambition has been at the heart of international endeavours to develop new in vitro and animal-free approaches for assessing the safety of cosmetics. While several of these new approach methodologies (NAMs) have been approved for assessing different toxicological endpoints in the UK and across the EU, there remains an absence of animal-free methods for screening for dermal absorption; a measure that assesses the degree to which chemical substances can become systemically available through contact with human skin. Here, we identify some of the major technical barriers that have impacted regulatory recognition of an in vitro skin model for this purpose and propose how these could be overcome on-chip using artificial cells engineered from the bottom-up. As part of our future perspective, we suggest how this could be realised using a digital biomanufacturing pipeline that connects the design, microfluidic generation and 3D printing of artificial cells into user-crafted synthetic tissues. We highlight milestone achievements towards this goal, identify future challenges, and suggest how the ability to engineer animal-free skin models could have significant long-term consequences for dermal absorption screening, as well as for other applications.
  • Journal article
    Morley JD, George C, Hadler K, BritoParada PRet al., 2023,

    Crystallography of active particles defining battery electrochemistry

    , Advanced Energy Materials, ISSN: 1614-6832

    Crystallographic features of battery active particles impose an inherent limitation on their electrochemical figures of merit namely capacity, roundtrip efficiency, longevity, safety, and recyclability. Therefore, crystallographic properties of these particles are increasingly measured not only to clarify the principal pathways by which they store and release charge but to realize the full potential of batteries. Here, state-of-the-art advances in Li+, K+, and Na+ chemistries are reviewed to reiterate the links between crystallography variations and battery electrochemical trends. These manifest at different length scales and are accompanied by a multiplicity of processes such as doping, cation disorder, directional crystal growth and extra redox. In light of this, an emphasis is placed on the need for more accurate correlations between crystallographic structure and battery electrochemistry in order to harness crystallographic beneficiation into electrode material design and manufacture, translating into high-performance and safe energy storage solutions.
  • Journal article
    Yasin L, Atkinson A, Cooper SJ, Bertei Aet al., 2023,

    Identifiability of the mechanisms governing the reaction kinetics of MIEC electrodes in solid oxide cells

    , Electrochimica Acta, Vol: 472, ISSN: 0013-4686

    The oxygen reduction reaction (ORR) is the main phenomenon occurring in mixed ionic and electronic conductors (MIECs) used as air electrodes in solid oxide cells. Their optimisation requires the identification of the ORR regime, which is typically performed via electrochemical impedance spectroscopy (EIS). In this study we present a physics-based model to simulate the impedance spectra of p-type oxygen-deficient perovskite MIEC materials. The EIS response of four extreme kinetic scenarios, characterised by the rate-determining step (electron-transfer or ion-transfer) and the high/low surface coverage of adsorbed oxygen, is mechanistically interpreted for both dense films and porous electrodes. A strategy for kinetic identification is proposed based on distinctive EIS fingerprints at different oxygen partial pressures (pO2) and cathodic bias. However, distinguishing the kinetic scenarios is not free from ambiguity even in dense films since some scenarios are discriminated only via a quantitative analysis, which may be susceptible to experimental errors in real measurements, and reverse behaviours appear when combining cathodic bias with pO2 variation. More difficulties arise in porous electrodes since bulk oxygen vacancy transport interacts with the ORR response. Application of the proposed strategy using literature data for some common MIEC materials shows the typical challenges of kinetic identification when relying solely on EIS.
  • Journal article
    Bigestans D, Cardin M-A, Kazantzis N, 2023,

    Economic performance evaluation of flexible centralised and decentralised blue hydrogen production systems design under uncertainty

    , Applied Energy, Vol: 352, ISSN: 0306-2619

    Blue hydrogen is viewed as an important energy vector in a decarbonised global economy, but its large-scale and capital-intensive production displays economic performance vulnerabities in the face of increased market and regulatory uncertainty. This study analyses flexible (modular) blue hydrogen production plant designs and evaluates their effectiveness to enhance economic performance under uncertainty. The novelty of this work lies in the development of a comprehensive techno-economic evaluation framework that considers flexible centralised and decentralised blue hydrogen plant design alternatives in the presence of irreducible uncertainty, whilst explicitly considering the time value of money, economies of scale and learning effects. A case study of centralised and decentralised blue hydrogen production for the transport sector in the San Francisco area is developed to highlight the underlying value of flexibility. The proposed methodological framework considers various blue hydrogen plant designs (fixed, phased, and flexible) and compares them using relevant economic indicators (net present value (NPV), capex, value-at-risk/gain, etc.) through a detailed Monte Carlo simulation framework. Results indicate that flexible centralised hydrogen production yields greater economic value than alternative designs, despite the associated cost-premium of modularity. It is also shown that the value of flexibility increases under greater uncertainty, higher learning rates and weaker economies of scale. Moreover, sensitivity analysis reveals that flexible design remains the preferred investment option over a wide range of market and regulatory conditions except for high initial hydrogen demand. Finally, this study demonstrates that major regulatory and market uncertainties surrounding blue hydrogen production can be effectively managed through the application of flexible engineering system design that protects the investment from major downside risks whilst allowing access to
  • Journal article
    Yi Y, Demirel P, 2023,

    The impact of sustainability-oriented dynamic capabilities on firm growth: investigating the green supply chain management and green political capabilities

    , Business Strategy and the Environment, Vol: 32, Pages: 5873-5888, ISSN: 0964-4733

    Building on the dynamic capabilities literature and natural-resource-based view, the paper examines whether firms can attain sales growth through a range of sustainability-oriented dynamic capabilities including (1) internal green supply chain management capabilities, (2) external green supply chain management capabilities and (3) green political capabilities. Based on a dataset of 277 public US firms between 2010 and 2020, a panel quantile model of firm growth showcases that while internal green supply chain capabilities and green political capabilities affect firms' growth performance positively, external green supply chain capabilities are associated with slower growth. Importantly, the results indicate that the positive growth effects of green political capabilities are short-lived, while those of internal green supply chain capabilities are long-lived. The study contributes to the sustainability-oriented dynamic capabilities literature by showing that different capabilities have different implications for firm growth depending on the firm's base performance and the time periods under consideration.
  • Journal article
    Sadek M, Calvo R, Mougenot C, 2023,

    Co-designing conversational agents: a comprehensive review and recommendations for best practices

    , Design Studies, Vol: 89, ISSN: 0142-694X

    This paper presents a comprehensive review of fifty-two studies co-designing conversational agents (CAs). Its objectives are to synthesise prior CA co-design efforts and provide actionable recommendations for future endeavours in CA co-design. The review systematically evaluates studies' methodological and contextual aspects, revealing trends and limitations. These insights converge into practical recommendations for co-designing CAs, including (1) selecting the most suitable design technique aligned with desired CA outcomes, (2) advocating continuous stakeholder involvement throughout the design process, and (3) emphasising the elicitation and embodiment of stakeholder values to ensure CA designs align with their perspectives. This paper contributes to standardising and enhancing co-design practices, promising to improve the quality of outcomes in the case of CAs while benefiting stakeholders and users.
  • Journal article
    Bonkile MP, Jiang Y, Kirkaldy N, Sulzer V, Timms R, Wang H, Offer G, Wu Bet al., 2023,

    Coupled electrochemical-thermal-mechanical stress modelling in composite silicon/graphite lithium-ion battery electrodes

    , Journal of Energy Storage, Vol: 73, ISSN: 2352-152X

    Silicon is often added to graphite battery electrodes to enhance the electrode-specific capacity, but it undergoes significant volume changes during (de)lithiation, which results in mechanical stress, fracture, and performance degradation. To develop long-lasting and energy-dense batteries, it is critical to understand the non-linear stress behaviour in composite silicon-graphite electrodes. In this study, we developed a coupled electrochemical-thermal-mechanical model of a composite silicon/graphite electrode in PyBaMM (an open-source physics-based modelling platform). The model is experimentally validated against a commercially available LGM50T battery, and the effects of C-rates, depth-of-discharge (DoD), and temperature are investigated. The developed model can reproduce the voltage hysteresis from the silicon and provide insights into the stress response and crack growth/propagation in the two different phases. The stress in the silicon is relatively low at low DoD but rapidly increases at a DoD >~80%, whereas the stress in the graphite increases with decreasing temperature and DoD. At higher C-rates, peak stress in the graphite increases as expected, however, this decreases for silicon due to voltage cut-offs being hit earlier, leading to lower active material utilisation since silicon is mostly active at high DoD. Therefore, this work provides an improved understanding of stress evolution in composite silicon/graphite lithium-ion batteries.
  • Journal article
    Miguel Angel M, Pinson P, Kazempour J, 2023,

    Online decision making for trading wind energy

    , Computational Management Science, Vol: 20, Pages: 1-31, ISSN: 1619-697X

    We propose and develop a new algorithm for trading wind energy in electricity markets, within an online learning and optimization framework. In particular, we combine a component-wise adaptive variant of the gradient descent algorithm with recent advances in the feature-driven newsvendor model. This results in an online offering approach capable of leveraging data-rich environments, while adapting to the nonstationary characteristics of energy generation and electricity markets, also with a minimal computational burden. The performance of our approach is analyzed based on several numerical experiments, showing both better adaptability to nonstationary uncertain parameters and significant economic gains.
  • Journal article
    Harkin R, Wu H, Nikam S, Quinn J, McFadden Set al., 2023,

    Reuse of grade 23 Ti6Al4V powder during the laser-based powder bed fusion process

    , Metals, Vol: 10, ISSN: 2075-4701

    Titanium alloy powder used for laser-based powder bed fusion (L-PBF) process is costly. One of the solutions is the inclusion of a powder recycling strategy, allowing unused or exposed powder particles to be recuperated post manufacture, replenished and used for future builds. However, during a L-PBF process, powder particles are exposed to high levels of concentrated energy from the laser. Particularly those in close proximity to the melt pool, leading to the formation of spatter and agglomerated particles. These particles can settle onto the powder bed, which can then influence the particle size distribution and layer uniformity. This study analysed extra-low interstitial (ELI) Ti6Al4V (Grade 23) powder when subjected to nine recycle iterations, tracking powder property variation across the successive recycling stages. Characterisation included chemical composition focusing upon O, N, and H content, particle size distribution, morphology and tapped and bulk densities. On review of the compositional analysis, the oxygen content exceeded the 0.13% limit for the ELI grade after 8 recycles, resulting in the degradation from Grade 23 level.
  • Journal article
    Ratcliffe E, Baxter W, Aurisicchio M, Childs P, Martin Net al., 2023,

    The role of ritual communication in consumption: A consumer coffee experience

    , International Journal of Food Design, ISSN: 2056-6522

    <jats:p>Rituals are part of the consumer experience of goods, especially food and drink, and can contribute to consumer enjoyment of and fidelity to a specific product. However, we lack detailed description of food/beverage-related rituals and their potential impact on consumer perceptions, in particular whether and how communicating those rituals to consumers influences their attitudes. Here we use coffee as an example of a ritualized product within the UK market to explore this potential relationship and identify opportunities for design. In Study 1, we identified rituals associated with coffee preparation and consumption. In Study 2, we found that several procedural aspects of the rituals identified in Study 1 were not consistently conveyed in coffee advertising, indicating a potential gap in communication with consumers. In Study 3, we showed that communicating such rituals to consumers resulted in significantly greater willingness to pay for coffee, mediated by perceptions of social attention. This work connects growing interest in the psychological mechanisms of ritual with work on consumer perceptions and behaviour and carries significant implications for the design of messaging around food experience.</jats:p>
  • Journal article
    Sadek M, Calvo R, Mougenot C, 2023,

    Designing value-sensitive AI: a critical review and recommendations for socio-technical design processes

    , AI and Ethics, ISSN: 2730-5961

    This paper presents a critical review of how different socio-technical design processes for AI-based systems, from scholarly works and industry, support the creation of value-sensitive AI (VSAI). The review contributes to the emerging field of human-centred AI, and the even more embryonic space of VSAI in four ways: (i) it introduces three criteria for the review of VSAI based on their contribution to design processes’ overall value-sensitivity, and as a response to criticisms that current interventions are lacking in these aspects: comprehensiveness, level of guidance offered, and methodological value-sensitivity, (ii) it provides a novel review of socio-technical design processes for AI-based systems, (iii) it assesses each process based on the mentioned criteria and synthesises the results into broader trends, and (iv) it offers a resulting set of recommendations for the design of VSAI. The objective of the paper is to help creators and followers of design processes—whether scholarly or industry-based—to understand the level of value-sensitivity offered by different socio-technical design processes and act accordingly based on their needs: to adopt or adapt existing processes or to create new ones.
  • Conference paper
    Wang E, Davis J, Moro D, Zielinski P, Lim JJ, Coelho C, Chatterjee S, Cheung P, Constantinides Get al., 2023,

    Enabling Binary Neural Network Training on the Edge

    , Workshop on Binary Networks for Computer Vision
  • Journal article
    Chappell D, Bello F, Kormushev P, Rojas Net al., 2023,

    The hydra hand: a mode-switching underactuated gripper with precision and power grasping modes

    , IEEE Robotics and Automation Letters, Vol: 8, Pages: 7599-7606, ISSN: 2377-3766

    Human hands are able to grasp a wide range of object sizes, shapes, and weights, achieved via reshaping and altering their apparent grasping stiffness between compliant power and rigid precision. Achieving similar versatility in robotic hands remains a challenge, which has often been addressed by adding extra controllable degrees of freedom, tactile sensors, or specialised extra grasping hardware, at the cost of control complexity and robustness. We introduce a novel reconfigurable four-fingered two-actuator underactuated gripper—the Hydra Hand—that switches between compliant power and rigid precision grasps using a single motor, while generating grasps via a single hydraulic actuator—exhibiting adaptive grasping between finger pairs, enabling the power grasping of two objects simultaneously. The mode switching mechanism and the hand's kinematics are presented and analysed, and performance is tested on two grasping benchmarks: one focused on rigid objects, and the other on items of clothing. The Hydra Hand is shown to excel at grasping large and irregular objects, and small objects with its respective compliant power and rigid precision configurations. The hand's versatility is then showcased by executing the challenging manipulation task of safely grasping and placing a bunch of grapes, and then plucking a single grape from the bunch.
  • Journal article
    Arteaga JM, Sanchez J, Elsakloul F, Marin M, Zesiger C, Pucci N, Norton GJ, Young DJ, Boyle D, Yeatman E, Hallett PD, Roundy S, Mitcheson PDet al., 2023,

    High frequency inductive power transfer through soil for agricultural applications

    , IEEE Transactions on Power Electronics, Vol: 38, Pages: 13415-13429, ISSN: 0885-8993

    This paper presents 13.56 MHz inductive powertransfer (IPT) through soil for sensors in agricultural ap-plications. Two IPT system designs and their prototypes are presented. The first was designed for gathering data and observing the relationship between the performance of the coil driving circuits in response to water content, salinity, organic matter and compaction of the soil. The second prototype was designed as an application demonstrator, featuring IPT to an in-house sensor node enclosure buried 200 mm under the surface of an agricultural field. The results highlight that from the parameters studied, the combination of high salinity and high water content significantly increases the losses of the IPT system.The experiments demonstrate an over 40% rise in the losses from dc source to dc load after a 16% increase in soil water content and high salinity. In the technology demonstrator we mounted an IPT transmitter on a drone to wirelessly power an in-house bank of supercapacitors in the buried sensor-node enclosure. A peak power transfer of 30 W received at over 40% efficiency was achieved from a 22 V power supply on the drone to the energy storage under the ground. The coil separation in these experiments was 250 mm of which 200 mm correspond to the layer of soil. The coupling factor in all the experiments was lower than 5%. This system was trialled in the field for forty days andwireless power was performed five times throughout.
  • Journal article
    Wang K, Xin G, Xin S, Mistry M, Vijayakumar S, Kormushev Pet al., 2023,

    A unified model with inertia shaping for highly dynamic jumps of legged robots

    , MECHATRONICS, Vol: 95, ISSN: 0957-4158
  • Conference paper
    Deterding S, Cutting J, 2023,

    Objective difficulty-skill balance impacts perceived balance but not behaviour: a test of flow and self-determination theory predictions

    , CHI PLAY 2023, Publisher: Association for Computing Machinery (ACM), Pages: 1179-1205, ISSN: 2573-0142

    Flow and self-determination theory predict that game difficulty in balance with player skill maximises enjoy- ment and engagement, mediated by attentive absorption or competence. Yet recent evidence and methodologi- cal concerns are challenging this view, and key theoretical predictions have remained untested, importantly which objective difficulty-skill ratio is perceived as most balanced. To test these, we ran a preregistered study (n=309) using a Go-like 2-player game with an AI opponent, randomly assigning players to one of three objective difficulty-skill ratios (AI plays to win, draw, or lose) over five matches. The AI successfully ma- nipulated objective balance, with the draw condition perceived as most balanced. However, balance did not impact play behaviour, nor did we find the predicted uniform ‘inverted-U’ between balance and positive play experiences. Importantly, we found both theories too underspecified to severely test. We conclude that balance and competence likely matter less for behavioural engagement than commonly held. We propose alternative factors such as player appraisals, novelty, and progress, and debate the value and challenges of theory-testing work in games HCI.
  • Conference paper
    Whitby MA, Iacovides I, Deterding S, 2023,

    “Conversations with pigeons”: capturing players’ lived experience of perspective challenging games

    , CHI PLAY 2023, Publisher: Association for Computing Machinery (ACM), Pages: 833-855, ISSN: 2573-0142

    Video games are increasingly designed to provoke reflection and challenge players’ perspectives. Yet we know little about how such perspective-challenging experiences come about in gameplay. In response, we used systematic self-observation diaries and micro-phenomenological interviews to capture players’ (n=15) lived experience of perspective challenges in purposely sampled games including Hatoful Boyfriend, The Stanley Parable, or Papers, Please. We found a sequence of trigger, reflection, and transformation constituting perspective-challenging experiences, matching Mezirow’s model of transformative learning. Most of these were game-related or ‘endo-game’, suggesting that medium self-reflection could be an overlooked part of everyday game reflection and appreciation. Reflections were accompanied by a wide range of emotions, including frequent epistemic emotions, and emotions could change drastically even during short gameplay experiences. Actual perspective change or transformation was rare. We construct a model of granular types of triggers, reflections, and transformations that can aid reflective game design.
  • Conference paper
    Ballou N, Deterding S, 2023,

    ‘I Just Wanted to Get it Over and Done With’: a grounded theory of psychological need frustration in video games

    , CHI PLAY 2023, Publisher: Association for Computing Machinery (ACM), Pages: 217-236, ISSN: 2573-0142

    Psychological need frustration—experiences like failure, loneliness, or coercion—is emerging as a promising explanation for why people disengage with games and other entertainment media, and how media may induce dysregulated use and ill-being. However, existing research on game-related need frustration relies on general instruments with unclear content validity for games. We also do not know how need frustration arises in video games, nor how it leads to disengagement. We therefore conducted a semi-structured interview study with 12 video game players, following grounded theory methods to develop a model of need-frustrating play. We find that need frustration is a common and impactful experience in games, with distinct antecedents not fully captured in existing measures. Felt need frustration arises when observed need-frustrating events negatively violate expected need frustration or satisfaction; repeated violations update players’ expectations, which lead them to modulate or quit play to reduce expected frustration exposure.
  • Journal article
    Turner R, Turner W, Wu H, 2023,

    On the pre-forging heating methods for AA2014 alloy

    , World Journal of Engineering and Technology, Vol: 11, Pages: 893-901, ISSN: 2331-4249

    The aluminium alloy AA2014 is one of the most widely used of the 2xxx series alloys, owing to its superior strength-to-weight ratio and stiffness. It is commonly forged to shape for use in aerospace parts. Three different small pilot-scale AA2014 billets were subjected to different heating operations, to physically simulate a pre-forge heating operation. The unheated sample and heated samples were then analysed for micro structural evolution and mechanical properties, to understand how the pre-forge heat treatments may vary the starting condition of the alloy before being forged. It was shown that an induction heating process has the greatest impact upon the precipitation distribution. Whilst this variation is commonly considered a negative impact, the opportunity to control the induction heating to promote preferential microstructure at specific locations within the billet may be possible.
  • Journal article
    Psarras S, Munoz R, Ghajari M, 2023,

    Compression performance of composite plates after multi-site impacts: A combined experimental and finite element study

    , COMPOSITE STRUCTURES, Vol: 322, ISSN: 0263-8223
  • Journal article
    Zhao Y, 2023,

    Ampere-hour-scale soft-package potassium-ion hybrid capacitors enabling 6-minute fast-charging

    , Nature Communications, Vol: 14, ISSN: 2041-1723

    Extreme fast charging of Ampere-hour (Ah)-scale electrochemical energy storage devices targeting charging times of less than 10 minutes are desired to increase widespread adoption. However, this metric is difficult to achieve in conventional Li-ion batteries due to their inherent reaction mechanism and safety hazards at high current densities. In this work, we report 1 Ah soft-package potassium-ion hybrid supercapacitors (PIHCs), which combine the merits of high-energy density of battery-type negative electrodes and high-power density of capacitor-type positive electrodes. The PIHC consists of a defect-rich, high specific surface area N-doped carbon nanotube-based positive electrode, MnO quantum dots inlaid spacing-expanded carbon nanotube-based negative electrode, carbonate-based non-aqueous electrolyte, and a binder- and current collector-free cell design. Through the optimization of the cell configuration, electrodes, and electrolyte, the full cells (1 Ah) exhibit a cell voltage up to 4.8 V, high full-cell level specific energy of 140 Wh kg−1 (based on the whole mass of device) with a full charge of 6 minutes. An 88% capacity retention after 200 cycles at 10 C (10 A) and a voltage retention of 99% at 25 ± 1 °C are also demonstrated.
  • Journal article
    Ferraro P, Yu JY, Ghosh R, Alam SE, Marecek J, Wirth F, Shorten Ret al., 2023,

    On unique ergodicity of coupled AIMD flows

    , INTERNATIONAL JOURNAL OF CONTROL, ISSN: 0020-7179
  • Journal article
    Kallis C, Calvo R, Schuller B, Quint Jet al., 2023,

    Development of an asthma exacerbation risk prediction model for conversational use by adults in England

    , Pragmatic and Observational Research, Vol: 14, Pages: 111-125, ISSN: 1179-7266

    Background: Improving accurate risk assessment of asthma exacerbations, and reduction via relevant behaviour change among people with asthma could save lives and reduce health care costs. We developed a simple personalised risk prediction model for asthma exacerbations using factors collected in routine healthcare data for use in a risk modelling feature for automated conversational systems.Methods: We used pseudonymised primary care electronic healthcare records from the Clinical Practice Research Datalink (CPRD) Aurum database in England. We combined variables for prediction of asthma exacerbations using logistic regression including age, gender, ethnicity, Index of Multiple Deprivation, geographical region and clinical variables related to asthma events.Results: We included 1,203,741 patients divided into three cohorts to implement temporal validation: 898,763 (74.7%) in the training sample, 226,754 (18.8%) in the testing sample and 78,224 (6.5%) in the validation sample. The Area under the ROC curve (AUC) for the full model was 0.72 and for the restricted model was 0.71. Using a cut-off point of 0.1, approximately 27 asthma reviews by clinicians per 100 patients would be prevented compared with a strategy that all patients are regarded as high risk. Compared with patients without an exacerbation, patients who exacerbated were older, more likely to be female, prescribed more SABA and ICS in the preceding 12 months, have history of GORD, COPD, anxiety, depression, live in very deprived areas and have more severe disease.Conclusion: Using information available from routinely collected electronic healthcare record data, we developed a model that has moderate ability to separate patients who had an asthma exacerbation within 3 months from their index date from patients who did not. When comparing this model with a simplified model with variables that can easily be self-reported through a WhatsApp chatbot, we have shown that the predictive performance of the model is
  • Journal article
    Cacciarelli D, Kulahci M, 2023,

    Hidden dimensions of the data: PCA vs autoencoders

    , Quality Engineering, Vol: 35, Pages: 741-750, ISSN: 0898-2112
  • Journal article
    Lu X, Lian GJ, Ge R, Parker J, Sadan MK, Smith R, Cumming Det al., 2023,

    Microstructure of Conductive Binder Domain for Electrical Conduction in Next-Generation Lithium-Ion Batteries

    , Energy Technology, Vol: 11, ISSN: 2194-4288

    The purpose of this work is to investigate the structure and mechanism of long-range electronic contacts which are formed by wet mixing and their interaction and relationship with the structure responsible for ion transfer within the conductive binder domain of next-generation LiNi0.6Mn0.2Co0.2O2 lithium-ion batteries. This article introduces a novel concept involving an efficient adapted structure model, which includes a bridge structure with two “nested” small and large pore systems, and an effective electrode conduction mechanism involving two “nested” percolation systems. The article also highlights a limitation in the improvement of the battery performance by percolation systems for electron transfer, which is restricted by pore systems for ion transfer through the ratio of electrical conductivity (σ) and ionic conductivity (κ) as σ/κ = 10. The findings of this article may provide valuable insight for formulation design and manufacturing of an optimal structure of the conductive binder domain for next-generation lithium-ion batteries.

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