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A model invalidation-based approach for elucidating biological signalling pathways, applied to the chemotaxis pathway in R. sphaeroides
(2009-10-31) Roberts, Mark; August, Elias; Hamadeh, Abdullah; Maini, Philip; McSharry, Patrick McSharry; Armitage, Judith; Papachristodoulou, Antonis; Department of Engineering
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Using the electrodermal activity signal and machine learning for diagnosing sleep
(2023) Piccini, Jacopo; August, Elias; Óskarsdóttir, María; Arnardóttir, Erna Sif; Department of Engineering; Department of Computer Science
Introduction: The use of the electrodermal activity (EDA) signal for health diagnostics is becoming increasingly popular. The increase is due to advances in computational methods such as machine learning (ML) and the availability of wearable devices capable of better measuring EDA signals. One field where work on EDA has significantly increased is sleep research, as changes in EDA are related to different aspects of sleep and sleep health such as sleep stages and sleep-disordered breathing; for example, obstructive sleep apnoea (OSA). Methods: In this work, we used supervised machine learning, particularly the extreme gradient boosting (XGBoost) algorithm, to develop models for detecting sleep stages and OSA. We considered clinical knowledge of EDA during particular sleep stages and OSA occurrences, complementing a standard statistical feature set with EDA-specific variables. Results: We obtained an average macro F1-score of 57.5% and 66.6%, depending on whether we considered five or four sleep stages, respectively. When detecting OSA, regardless of the severity, the model reached an accuracy of 83.7% or 78.4%, depending on the measure used to classify the participant's sleep health status. Conclusion: The research work presented here provides further evidence that, in the future, most sleep health diagnostics might well do without complete polysomnography (PSG) studies, as wearables can detect well the EDA signal.
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Unseen consequences : the effect of activity-based work environments on work recovery
(2025-01) Valgeirsson, Halldor; Halldorsson, Freyr; Kristinsson, Kari; Department of Business and Economics
Leaders implementing activity-based work environments seek benefits for their organizations. These include increasing employee activities such as communication, collaboration, and innovation and reducing housing expenses. While there are several benefits to implementing an activity-based work environment, research has highlighted various issues related to employee well-being in such environments. These include increased noise and distraction, reduced privacy, and heightened workplace stress. This study focuses on a novel issue concerning employee well-being by investigating how an activity-based work environment influences work recovery. Using a longitudinal design, we examine a public sector workplace whose employees were surveyed three times during the implementation of an activity-based work environment. Our results show that satisfaction with activity-based work environments plays an important role in well-being outside work. In contrast, employees less satisfied with activity-based environments are more likely to face difficulties recovering from work. Directions for further research and the implications of these results for organizations are discussed.
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Uniplanar aquatic exercise quantified with inertial sensors and pose estimation
(2025-12) McShane, E. P.; Rantalainen, T.; Gislason, M. K.; Einarsson, I. T.; Baldvinsdottir, R.; Morris, J.; Wilkins, B.; Waller, B.; Department of Engineering; Department of Sport Science
This study presents a concurrent validity analysis of two measurement techniques for quantifying uniplanar human movement during aquatic exercise. Established marker-based biomechanical motion capture systems are labour intensive, and command significant prices, limiting their accessibility in non-specialist environments. Therefore, this study assesses the applicability of alternate measurement methods; inertial measurement unit (IMU) sensors and markerless computer vision (CV) tracking in the form of pose estimation, applied to the quantification and analysis of aquatic exercise. This analysis establishes the validity of each method by deriving several performance-related metrics; range of motion, duration, and angular velocity, of uniplanar aquatic exercise repetitions. Using the proposed methods it was observed that each performance metric demonstrated excellent agreement (ICC 0.94) across methods, based on intraclass correlation coefficients in 20 healthy young adults (n = 9 women, aged 20-26). This analysis encompassed two exercise types, knee flexion-extension and hip flexion-extension. The authors highlight that this contribution represents a step toward establishing robust, accessible methods for objective exercise quantification in aquatic settings, where previously there has been an absence of convenient technical solutions.
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Towards understanding the cathode process mechanism and kinetics in molten lif–alf3 during the treatment of spent pt/al2o3 catalysts
(2021-09) Yasinskiy, Andrey; Padamata, Sai Krishna; Stopic, Srecko; Feldhaus, Dominic; Varyukhin, Dmitriy; Friedrich, Bernd; Polyakov, Peter; Department of Engineering
Electrochemical decomposition of spent catalyst dissolved in molten salts is a promising approach for the extraction of precious metals from them. This article reports the results of the study of aluminum electrowinning from the xLiF–(1-x)AlF3 melt (x = 0.64; 0.85) containing 0–5 wt.% of spent petroleum Pt/γ-Al2O3 catalyst on a tungsten electrode at 740–800◦C through cyclic voltammetry and chronoamperometry. The results evidence that the aluminum reduction in the LiF–AlF3 melts is a diffusion-controlled two-step process. Both one-electron and two-electron steps occur simultaneously at close (or same) potentials, which affect the cyclic voltammograms. The diffusion coefficients of electroactive species for the one-electron process were (2.20–6.50)·10−6 cm2·s–1, and for the two-electron process, they were (0.15–2.20)−6 cm2·s−1. The numbers of electrons found from the chronoamperometry data were in the range from 1.06 to 1.90, indicating the variations of the partial current densities of the one-and two-electron processes. The 64LiF–36AlF3 melt with about 2.5 wt.% of the spent catalysts seems a better electrolyte for the catalyst treatment in terms of cathodic process and alumina solubility, and the range of temperatures from 780 to 800◦C is applicable. The mechanism of aluminum reduction from the studied melts seems complicated and deserves further study to find the optimal process parameters for aluminum reduction during the spent catalyst treatment and the primary metal production as well.

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