University of Glasgow

This study improves the accuracy of junction temperature prediction, as the insulated gate bipolar transistor (IGBT) reliability is important for the safe operation of its working system due to junction temperature is limited in its actual performance and reliability. A model based on an improved sailfish optimization algorithm to optimize support vector machine (ISFO-SVM) is proposed to solve the problem that the junction temperature prediction accuracy is not high enough. The proposed algorithm is improved by adaptive nonlinear iterative factor, Le'vy flight and differential mutation strategy to optimize the support vector machine (SVM) internal parameters to predict junction temperature. The results indicate that ISFO-SVM performs better under the same evaluation indexes. The root mean squared error average value decreased by 67.189%, and the mean absolute percentage error average value decreased by 63.189%, compared with the sailfish optimization algorithm to optimize the SVM. The prediction error of ISFO-SVM is smaller and the error value is in the [-5 °C, 5 °C] range accounting for 98.270% of the total test samples. ISFO-SVM has a higher fitting degree than the actual junction temperature and the R2 has reached 99.660%. The model predicts the junction temperature of IGBT modules and provides scientific guidance for system reliability evaluation to maintain safe and stable operation effectively.

In the realm of the Internet of Things, reconfigurable intelligent surfaces (RISs) have emerged as a pivotal technology, offering unprecedented opportunities to enhance signal quality, coverage, and energy efficiency as part of the ongoing pursuit to overcome the limitations of conventional wireless communication systems. In this context, this paper focuses on the analysis of performance in an integrated air-to-underwater network under the amplified-and-forward relay with variable gain, specifically examining the impact of RISs on a mixed terahertz-underwater optical communication system. This study utilizes the α-μ distribution to characterize the fading effects and pointing error on the THz signal. On the other hand, the underwater turbulence on the optical signal is modeled using the mixture of Exponential Generalized Gamma distribution with pointing error impairments. To provide a basis for comparison, the heterodyne detection technique and the intensity modulation with the direct detection technique are also incorporated. Therefore, analytical expressions of outage probability, average bit error rate, and average channel capacity are demonstrated in terms of the Meijer-G function. To provide more insights, high signal-to-noise approximations of these metrics are also presented. Furthermore, the impact of various modulation schemes, fading severity, pointing errors, atmospheric turbulence conditions, and receiver detection techniques are inspected on the system performance. Finally, the analytical findings are validated through Monte-Carlo simulations, ensuring the robustness of the results.

Millimeter-wave (mmWave) communication is one of the effective technologies for the next generation of wireless communications due to the enormous amount of available spectrum resources. Rate splitting multiple access (RSMA) is a powerful multiple access, interference management, and multiuser strategy for designing future wireless networks. In this work, a multiple-input-single-output mmWave RSMA system is considered wherein a base station serves two users in the presence of a passive eavesdropper. Different eavesdropping scenarios are considered corresponding to the overlapped resolvable paths between the main and the wiretap channels under the considered transmission schemes. The analytical expressions for the secrecy outage probability (SOP) are derived respectively through the Gaussian–Chebyshev quadrature method. Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of system parameters on the SOP of the considered mmWave RSMA systems.

In distributed computing environments, the collaboration of nodes for predictive analytics at the network edge plays a crucial role in supporting real-time services. When a node’s service becomes unavailable for various reasons (e.g., service updates, node maintenance, or even node failure), the rest of the available nodes connot efficiently replace its service due to different data and predictive models (e.g., machine learning [ML] models). To address this, we propose decision-making strategies rooted in the statistical signatures of nodes’ data. Specifically, these signatures refer to the unique patterns and behaviors within each node’s data that can be leveraged to predict the suitability of potential surrogate nodes. Recognizing and acting on these statistical nuances ensures a more targeted and efficient response to node failures. Such strategies aim to identify surrogate nodes capable of substituting for failing nodes’ services by building enhanced predictive models. Our resilient framework helps to guide the task requests from failing nodes to the most appropriate surrogate nodes. In this case, the surrogate nodes can use their enhanced models, which can produce equivalent and satisfactory results for the requested tasks. We provide experimental evaluations and comparative assessments with baseline approaches over real datasets. Our results showcase the capability of our framework to maintain the overall performance of predictive analytics under nodes’ failures in edge computing environments.

Background and purpose Blood pressure variability, in acute stroke, may be an important modifiable determinant of functional outcome after stroke. In a large international cohort of participants with acute stroke, it was sought to determine the association of blood pressure variability (in the early period of admission) and functional outcomes, and to explore risk factors for increased blood pressure variability. Patients and methods INTERSTROKE is an international case–control study of risk factors for first acute stroke. Blood pressure was recorded at the time of admission, the morning after admission and the time of interview in cases (median time from admission 36.7 h). Multivariable ordinal regression analysis was employed to determine the association of blood pressure variability (standard deviation [SD] and coefficient of variance) with modified Rankin score at 1‐month follow‐up, and logistic regression was used to identify risk factors for blood pressure variability. Results Amongst 13,206 participants, the mean age was 62.19 ± 13.58 years. When measured by SD, both systolic blood pressure variability (odds ratio 1.13; 95% confidence interval 1.03–1.24 for SD ≥20 mmHg) and diastolic blood pressure variability (odds ratio 1.15; 95% confidence interval 1.04–1.26 for SD ≥10 mmHg) were associated with a significant increase in the odds of poor functional outcome. The highest coefficient of variance category was not associated with a significant increase in risk of higher modified Rankin score at 1 month. Increasing age, female sex, high body mass index, history of hypertension, alcohol use, and high urinary potassium and low urinary sodium excretion were associated with increased blood pressure variability. Conclusion Increased blood pressure variability in acute stroke, measured by SD, is associated with an increased risk of poor functional outcome at 1 month. Potentially modifiable risk factors for increased blood pressure variability include low urinary sodium excretion.

Semi-autonomous vehicles allowdrivers to engage with non-driving related tasks (NDRTs). However, these tasks interfere with the driver’s situational awareness, key when they need to safely retake control of the vehicle. This paper investigates if Augmented Reality (AR) could be used to present NDRTs to reduce their impact on situational awareness. Two experiments compared driver performance on a hazard prediction task whilst interacting with an NDRT, presented either as an AR Heads-Up Display or a traditional Heads-Down Display. The results demonstrate that an AR display including a novel dynamic attentional cue improves situational awareness, depending on the workload of the NDRT and design of the cue. The results provide novel insights for designers of incar systems about how to design NDRTs to aid driver situational awareness in future vehicles.

Scale questionnaires are psychometric tools that capture perspectives and experiences. Consequently, these tools need to be reliable and valid. In this paper, we investigate the impact of response widgets - the UI elements that allow users to answer scale items - on the overall scale reliability and construct validity of three varied length scale questionnaires in a user study (N=30). Our results reveal that optimum reliability was achieved using radio buttons and dropdowns in all varied-length questionnaires. Further, valid results were produced utilising the slider and dropdown. No significant differences were found in time consumption, but click count was significantly higher with dropdown. Radio buttons scored lower in format satisfaction than others, and dropdown was the least effective in ease of selection and quick completion. In light of these results, we conclude that response widgets are more than just aesthetics and should be selected as per the researcher’s aims.

Automated embodied moderation has the potential to create safer spaces for children in social VR, providing a protective figure that takes action to mitigate harmful interactions. However, little is known about how such moderation should be employed in practice. Through interviews with 16 experts in online child safety and psychology, and workshops with 8 guardians and 13 children, we contribute a comprehensive overview of how Automated Embodied Moderators (AEMs) can safeguard children in social VR. We explore perceived concerns, benefits and preferences across the stakeholder groups and gather first-of-their-kind recommendations and reflections around AEM design. The results stress the need to adapt AEMs to children, whether victims or harassers, based on age and development, emphasising empowerment, psychological impact and humans/guardians-in-the-loop. Our work provokes new participatory design-led directions to consider in the development of AEMs for children in social VR taking child, guardian, and expert insights into account.

Current understanding of iron-deficient heart failure is based on blood tests that are thought to reflect systemic iron stores, but the available evidence suggests greater complexity. The entry and egress of circulating iron is controlled by erythroblasts, which (in severe iron deficiency) will sacrifice erythropoiesis to supply iron to other organs, e.g. the heart. Marked hypoferraemia (typically with anaemia) can drive the depletion of cardiomyocyte iron, impairing contractile performance and explaining why a transferrin saturation < ≈15%–16% predicts the ability of intravenous iron to reduce the risk of major heart failure events in long-term trials (Type 1 iron-deficient heart failure). However, heart failure may be accompanied by intracellular iron depletion within skeletal muscle and cardiomyocytes, which is disproportionate to the findings of systemic iron biomarkers. Inflammation- and deconditioning-mediated skeletal muscle dysfunction—a primary cause of dyspnoea and exercise intolerance in patients with heart failure—is accompanied by intracellular skeletal myocyte iron depletion, which can be exacerbated by even mild hypoferraemia, explaining why symptoms and functional capacity improve following intravenous iron, regardless of baseline haemoglobin or changes in haemoglobin (Type 2 iron-deficient heart failure). Additionally, patients with advanced heart failure show myocardial iron depletion due to both diminished entry into and enhanced egress of iron from the myocardium; the changes in iron proteins in the cardiomyocytes of these patients are opposite to those expected from systemic iron deficiency. Nevertheless, iron supplementation can prevent ventricular remodelling and cardiomyopathy produced by experimental injury in the absence of systemic iron deficiency (Type 3 iron-deficient heart failure). These observations, taken collectively, support the possibility of three different mechanistic pathways for the development of iron-deficient heart failure: one that is driven through systemic iron depletion and impaired erythropoiesis and two that are characterized by disproportionate depletion of intracellular iron in skeletal and cardiac muscle. These mechanisms are not mutually exclusive, and all pathways may be operative at the same time or may occur sequentially in the same patients.

Aims To describe the baseline characteristics of participants in the FINEARTS‐HF trial, contextualized with prior trials including patients with heart failure (HF) with mildly reduced and preserved ejection fraction (HFmrEF/HFpEF). The FINEARTS‐HF trial is comparing the effects of the non‐steroidal mineralocorticoid receptor antagonist finerenone with placebo in reducing cardiovascular death and total worsening HF events in patients with HFmrEF/HFpEF. Methods and results Patients with symptomatic HF, left ventricular ejection fraction (LVEF) ≥40%, estimated glomerular filtration rate ≥ 25 ml/min/1.73 m ² , elevated natriuretic peptide levels and evidence of structural heart disease were enrolled and randomized to finerenone titrated to a maximum of 40 mg once daily or matching placebo. We validly randomized 6001 patients to finerenone or placebo (mean age 72 ± 10 years, 46% women). The majority were New York Heart Association functional class II (69%). The baseline mean LVEF was 53 ± 8% (range 34–84%); 36% of participants had a LVEF <50% and 64% had a LVEF ≥50%. The median N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) was 1041 (interquartile range 449–1946) pg/ml. A total of 1219 (20%) patients were enrolled during or within 7 days of a worsening HF event, and 3247 (54%) patients were enrolled within 3 months of a worsening HF event. Compared with prior large‐scale HFmrEF/HFpEF trials, FINEARTS‐HF participants were more likely to have recent (within 6 months) HF hospitalization and greater symptoms and functional limitations. Further, concomitant medications included a larger percentage of sodium–glucose cotransporter 2 inhibitors and angiotensin receptor–neprilysin inhibitors than previous trials. Conclusions FINEARTS‐HF has enrolled a broad range of high‐risk patients with HFmrEF and HFpEF. The trial will determine the safety and efficacy of finerenone in this population.

Background Critical illness survival rates have improved, but patients frequently face prolonged new or worsened physical, cognitive and psychosocial impairments (Josepha op't Hoog et al., 2022 , Aust Crit Care ). These difficulties associated with critical care admission are known as post‐intensive care syndrome (PICS). Aims The multidisciplinary InS:PIRE programme was developed to support patients in the recovery period from critical illness. During the COVID‐19 pandemic, the psychology support offered by this service was adapted from an in‐person group to individual remote review. This audit evaluated both the extent to which this input aligned with the recommended guidelines and the acceptability of this adapted delivery to this patient group, which could help guide post‐pandemic psychology input to the service. Study Design The records of 207 patients were analysed retrospectively. The nature of support offered to a sub‐sample of 50 patients detailed in clinical summary letters was compared with the Faculty of Intensive Care Medicine (2019) guidelines. Telephone calls were made to gather feedback on the virtual psychology support from 10 patients. Results Psychological difficulties were identified by 111 of the 207 patients who attended the virtual clinic. A total of 88 of these patients accepted referral for virtual psychology support and 67 (76%) of those patients attended. The virtual psychology support offered was found to be largely in accordance with ICU aftercare guidance and acceptable to patients. Patients found the summary letters of consultations accurate and helpful. Most patients expressed a preference for in‐person support and the opportunity to meet other patients. Conclusions The adaptations to the psychology support offered by InS:PIRE during the COVID‐19 pandemic were found to be largely in line with ICU aftercare psychology guidelines and were acceptable to patients. Further research is needed on future methods of delivering psychology support for this patient group. Relevance to Clinical Practice This audit highlights issues important to patients in the post‐ICU period based on individual consultations not previously possible. Patient opinion was sought on the impact of changing the delivery of post‐ICU psychological support, which will help guide future improvements in the service.