17628 research outputs found
Sort by
Stabilizing the lithium metal interphase by calendar aging for enhanced battery lifespan
No full textThe lifespan of lithium metal batteries mainly depends on the stability of the solid electrolyte interphase (SEI). Battery aging is a non-chemical strategy that leverages the intrinsic reactivity of lithium metal and structural changes in the electrolyte to control SEI morphology, a crucial factor in interfacial stability. In the current study, we stabilize the SEI and extend the lifespan of lithium metal batteries by aging them for over 16 days before testing. This preconditioning process promotes the formation of a stable and porous SEI composed of solvent-anion complexes. The optimal performance of different cell configurations depends on a balance of ionic conductivity, SEI stability, electrochemical stability window, and the availability of the electrolyte during cycling. Consequently, 16 days of aging is optimal for a Li//Li cell, as it reduces the overpotential from 100 mV to 30 mV, and 30 days of aging is ideal for Li//Cu configuration, as it provides high CE and extends the cell's lifespan from 20 cycles to over 100 cycles. For high-voltage operations in LiCoO2//Li cells, 16-day-aged cells demonstrate a higher capacity of 172 mA h g−1 with a CE of 98 %, surpassing that of fresh cells (146 mA h g−1 with a CE of 95 %). Additionally, capacity retention improves significantly from 20 mA h g−1 to 100 mA h g−1 after 90 cycles. This work presents a straightforward approach that challenges the prevailing notion that electrolyte additives or complex formulations are essential to achieving a longer battery lifespan
A novel Quantum Beta distributed multi-objective Particle Swarm Optimization algorithm for fake accounts detection
No full textDetecting fake accounts on Online Social Networks is a pressing issue due to the rise in unethical online activities. This study presents a new Quantum Beta-behaved Multi-Objective Particle Swarm Optimization Algorithm (QB-MOPSO) for machine learning-based fake account detection. QB-MOPSO aims to enhance the learning process of a random forest algorithm by simultaneously minimizing feature dimensionality and classification error rates. It proposes a novel architecture that employs two optimization profiles: one improves exploratory behavior using a quantum-behaved equation, while the other enhances exploitation through a beta function. The main contributions of this study are as follows: the design of a novel Quantum Beta Distributed Multi-Objective Particle Swarm Optimization algorithm that integrates quantum-behaved exploration and beta-distributed exploitation, the application of this algorithm to enhance artificial intelligence–based fake account detection on Twitter datasets, and a comprehensive experimental evaluation demonstrating superior accuracy, F-measure, and MCC compared to existing methods. Experimental results on two Twitter datasets with 1982 and 928 accounts respectively show QB-MOPSO's effectiveness, achieving accuracy rates of about 99.19 % and 97.52 %. Comparisons with the original architecture demonstrate QB-MOPSO's ability to enhance the performance of the random forest algorithm
The Influence of Acute Beta-Hydroxy Beta-Methylbutyrate (HMB) Ingestion on the Human Skeletal Muscle Transcriptome
No full textBackground: Nutritional interventions to mitigate age/disease-related skeletal muscle attrition are much needed given the growing older population. Beta-hydroxy beta-methylbutyrate (HMB), an endogenous metabolite of the essential amino acid leucine, has anabolic properties in skeletal muscle: acutely stimulating muscle protein synthesis and attenuating muscle protein breakdown. While the role of supplemental HMB on muscle protein turnover is established, mechanistic effects on the muscle transcriptome have not been examined. Methods: Total RNA was extracted from m. vastus lateralis muscle biopsies of young males (n = 14) before and ~2.5 h after oral consumption of ~3 g HMB. Global changes in the muscle transcriptome were assessed via RNA sequencing, and differential expression in genes between fasted and ‘fed’ (HMB) conditions was determined. To identify the functional biology of differentially expressed genes, gene set enrichment and active subnetwork-orientated enrichment analyses was performed. Results: Of 15,982 genes detected, 468 were significantly upregulated and 326 were significantly downregulated in response to HMB. These genes were found to be associated with molecular pathways regulating muscle protein turnover, most notably, JAK-STAT signalling (e.g., STAM), circadian rhythm (e.g., NR1D1, NR1D2, PER2, PER3), TNFα signalling (e.g., TNFRSF1A, CCL2, CXCL2), and protein synthesis (e.g., POLR1A, POLR2A, POLR3A, PIK3RR, SGK1). HMB also regulated the expression of AA transporters, evoking a robust increase in SLC36A1 (PAT1) and SLC7A5 (LAT1). Conclusions: HMB evokes transcriptional events important in the homeostasis of muscle, supporting a role in proteostasis and one akin to protein intake, i.e., upregulation of AA transporters. Future work should further define HMB’s transcriptomic/proteomic effects in ageing/disease and synergy with exercise
Strategic development of regional transshipment hubs: leveraging econometric modelling and trade integration between foreland nations and production centres
No full textThis paper shows that transshipment ports can be key contributors to enhancing trade relations and strategic port partnerships between the host country and the connected markets. The paper develops a forecasting model based on international trade dynamics between foreland markets and the world's major production centre, China, and validates with data sourced from the World Integrated Trade Solution and China's Trade Yearbook to determine the port throughput of a regional hub port (the Port of Colombo). The model's validity is confirmed through rigorous statistical tests, and the findings revealed the Port of Colombo's long-term dependence on trade with foreland nations trading with China. The results support the need for the port's host country to adopt trade integration strategies for its sustained growth. The model significantly enhances the forecasting accuracy for transshipment hubs, offering valuable insights for policymakers and port authorities to promote sustainable growth through improved trade integration strategies
Self-Powered Piezoelectric Pressure Mapping Footwear for Podiatric Analysis
No full textThis work demonstrates the development and implementation of a flexible piezoelectric-based self-powered sensor for pressure mapping in podiatric analysis. For the development of self-powered sensors, we prepared Ba0.9Sr0.1TiO3/polyvinyl difluoride (B9S1T/PVDF) piezoelectric fibres through electrospinning. The surface morphology of B9S1T/PVDF composite fibres using a scanning electron microscope image shows that the average fibre diameter decreases with increasing B9S1T content, ranging approximately from 0.43 μm to 0.22 μm. The piezoelectric output voltages of the PVDF and B9S1T/PVDF -based devices for frequencies of 5, 10, 15 and 20 Hz indicate a significant rise in generated voltage with the addition of B9S1T fibre with PVDF loading. Using the B9S1T/PVDF composite fibres, we developed pressure sensors, and it was found that 7 wt.% B9S1T /PVDF sensors produced comparatively higher output differential voltage, while the 20% PVDF sensors have better linear response. Based on this, the 7 wt.% B9S1T /PVDF sample was chosen to be embedded in an insole for pressure mapping. The device performance showed that output voltage varies by sensor location, such as 871 mV at the hallux, 939 mV at the 1st metatarsal pad, 701 mV at the 5th metatarsal pad and 1018 mV at the heel. The data obtained was then visualised as a heatmap for gait analysis
Modelling lung permeability of pharmaceuticals: The effectiveness of biomimetic open tubular capillary electrochromatography and immobilised artificial membrane chromatography coupled with mass spectrometry
Get PDFIn this study, the potential of mass spectrometry (MS) −compatible biomimetic chromatography (BMC) was explored to assess drug permeability across biological membranes, pioneering a comparison of its application to model pulmonary absorption. Two BMC techniques were evaluated i.e., immobilised artificial membrane liquid chromatography (IAM-LC) and open-tubular capillary electrochromatography (OT-CEC) on fused silica capillaries coated with phospholipid vesicles. This application was validated on a dataset of 53 structurally diverse compounds whose pulmonary permeability is already evidenced in scientific literature.The IAM-LC model exhibited a stronger correlation with conventional n-octanol/water partitioning metrics (log Po/w and log D7.4) than OT-CEC. Analytical retention appeared to be influenced by a complex interplay of hydrophobic, electrostatic, and structural factors, leading to weaker correlations particularly with log Po/w.Coupling these techniques with MS enabled high-throughput analysis of mixtures and allowed detection of compounds lacking UV chromophores. The MS-based IAM-LC approach demonstrated excellent robustness with data obtained using a C setup with UV detection (R2 = 0.95). On the other hand, stable phospholipid coatings were achieved in OT-CEC-MS providing effectiveness across varying liposomal compositions.IAM-LC, mimicking a phosphatidylcholine (PC) −based lipid bilayer, displayed a strong correlation between log kwIAM and log Papp, with an R2 value of 0.72 observed for compounds with molecular masses > 300 g mol−1 where paracellular diffusion is negligible. Meanwhile, OT-CEC-MS allowed for the incorporation of phospholipids other than PC in the stationary phase, offering complementary insights into drug–membrane interactions beyond partitioning. The strongest correlations between IAM-LC and OT-CEC parameters were observed for cationic species with log KD > 1.5. These techniques demonstrated significant potential to support drug development programmes in both industrial and academic settings by facilitating high-throughput permeability screening and pharmacokinetics −focused lead optimisation
Towards Digital Twin-as-a-Service (DTaaS) Platforms: A Survey on Architecture, Design Requirements, and Performance Metrics
Get PDFDigital Twin-as-a-Service (DTaaS) has emerged as a transformative paradigm to deliver modular, scalable, and intelligent digital twin (DT) functionalities. Regarding this, several studies have investigated DT platforms and their enabling technologies. However, their focus mostly remains domain-specific, thereby limiting the potential for generalisation across diverse contexts. Furthermore, these studies lack a systematic framework to address both architectural elements and their performance evaluation required for an end-to-end DTaaS platform. To bridge this gap, in this survey, we present a comprehensive component-based taxonomy for DTaaS platforms, categorised into core and supportive components. As the core components, we review Data, Model, Service, and Communication, whereas the supportive components include Infrastructure, Orchestration, and Security elements. For each component, we analyse the state-of-the-art methods, enabling technologies, and associated design trade-offs. We further introduce a metric-driven perspective to design measurable and context-aware DTaaS platforms. In this regard, we present several DT performance metrics, including twinning rate, twin fidelity, and age-of-twin and map them to DTaaS components. To demonstrate the applicability of our framework, we present a case study based on our own DTaaS platform. We perform two metric-driven implementations, (i) Radio Access Network (RAN) management and (ii) Distributed Denial of Service (DDoS) attack detection by exemplifying how DT-metrics can be integrated with the DTaaS components. Also, we outline key open issues for context-aware, interoperable, and secure DTaaS platforms. By jointly addressing an end-to-end architectural design and performance metrics, this survey demonstrates a foundational reference for the structured development, evaluation, and operation of DTaaS platforms
Spring Military-PTSD: development and pilot evaluation of a guided digital therapy for military veterans with post-traumatic stress disorder (PTSD)
No full textBackground: Cognitive behavioural therapy with a trauma focus (CBT-TF) is the gold-standard treatment for military post-traumatic stress disorder (PTSD), but access is limited by high costs, therapist shortages, and the demands of in-person delivery. Guided digital CBT-TF, delivered via an app or website with therapist support, offers a scalable alternative. Objective: This study aimed to adapt Spring PTSD, an evidence-based guided digital therapy, for military veterans and conduct an initial pilot test of the adapted version. Method: A two-stage process was used. In Stage 1, veterans with lived experience of PTSD (n = 11) participated in focus groups to guide adaptations. Key themes included the need for a relatable narrator, authentic military representation, diverse visuals, and military-inspired design. Veterans also emphasised addressing emotional regulation. These insights shaped the development of Spring Military-PTSD, which incorporated techniques from Enhanced Skills Training for Affective and Interpersonal Regulation (ESTAIR). In Stage 2, treatment-seeking veterans with PTSD (n = 10) took part in a pilot study that collected qualitative and quantitative data. The primary outcome was change in PTSD severity measured by the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5). Participants received an average of 3 h and 50 min of therapist support. Results: Eight participants completed the pilot; two dropped out. Of the completers, four no longer met diagnostic criteria for PTSD, and six showed reliable improvement on CAPS-5. Statistically significant reductions were also seen in self-reported PTSD, disturbance in self-organisation (DSO), anxiety, and depression. Qualitative feedback supported the relevance and acceptability of the intervention. Conclusions: Findings provide preliminary evidence for the efficacy and acceptability of Spring Military-PTSD. The adapted intervention shows promise as a scalable and engaging treatment for veterans with PTSD. Further research is warranted to evaluate its effectiveness and potential for broader implementation
Rich picture building: A visual method for future serious leisure studies
Get PDFVisual research methods have been gaining attention among leisure studies scholars in recent years. As a form of freehand drawing, this paper mobilises rich picture building (RPB) for future serious leisure studies, and particularly those concerned with devotee work. Employed during focus groups to encourage discussion using pictorial representations of complex social issues, this paper demonstrates the value of RPB for evoking and recording insight into social situations. Through an example of serious leisure via devotee work, this paper presents RPB as a means to support participant discussions since humans are thought to communicate more easily through impressions and symbols than words. Considering serious leisure is inherently social and rooted in human activity, RPB is an innovative approach that can enhance focus group research and triangulate qualitative data across verbal, textual and pictorial data. Through RPB, this paper demonstrates how simplistic pictorial representations of ideas or topics can enhance verbal information collected in traditional focus groups and/or interviews and deepen future serious leisure research
Understanding and Assessing Medical Engagement: A New Toolkit and ‘Killer’ Questions You Might Want to Ask of Doctors
Get PDFPurpose Using theory on institutional logics and identity work, we examine why many doctors disengage from their organisations. We also develop a research-based, practical tool to improve medical engagement and medical leadership. MethodDrawing on earlier qualitative research with senior doctors, we developed the medical identity toolkit (MIT) and tested it by analysing responses from 268 senior doctors (55% response rate) in a case organisation. Our analysis employed exploratory factor analysis (EFA), binary logistic regression, AUROC on quantitative data and thematic analysis of free text items. FindingsWe found doctors’ identity work in response to shifting logics predicted overall levels of medical engagement. Doctors’ overall levels of medical engagement also predicted their advocacy of their employer as a good place to build a medical career. An EFA produced four factors with eigenvalues greater than three, explaining 32.4% of the variance. Significant differences in the mean factor scores for the first three factors were found across the MIT tertiles (each p < 0.001). Additionally, using binary logistic regression and stepwise selection we developed a medical engagement index (MEI) containing the sum of scores of four questionnaire items. The AUROC for the MEI model was 0.9687 (95% CI: 0.9478 to 0.9896), with a threshold of 13 (sensitivity and specificity of 88.6% and 90.9% respectively).OriginalityThe paper enhances our understanding of medical engagement among senior doctors by examining it through the lenses of medical professional identities, identity work and institutional logics. Practical ImplicationsThe MIT has strong practical implications for medical professionals in the NHS and other countries. It is grounded in the perspectives of doctors and provides immediate feedback for individual and collective reflection on medical engagement and doctor’s suitability for medical leadership
Data sources:
Access Repository Dashboard
Do you manage Repository@Napier? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!