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Driving safety excellence: A multifaceted analysis of leading indicators across industries
Full text linkSeveral studies have examined Safety Leading Indicators (SLIs) and their impact on safety performance in diverse industries. However, no study has comprehensively synthesised these findings across industries to offer a holistic perspective. This lack of integration impedes safety professionals from effectively implementing critical SLIs and adopting measures to enhance safety performance universally. To fill this gap, this study employs a comprehensive hybrid methodological approach, including a Systematic Literature Review (SLR), a questionnaire survey, and expert interviews. Using the SLR undertaken, 67 SLIs impacting safety performance across industries were identified. Analysis of the survey data from safety experts revealed that “training and education”, “incident investigation and analysis”, and “safety observation” were seen to be the top three critical SLIs. These results were further validated using the expert interviews. Additionally, findings from the interviews revealed that “safety performance improvement” and “establishing effective measurement methods” were, respectively, the most crucial drivers and barriers to SLI adoption across industries. The outcomes of this study provide safety professionals with the vital areas to focus on, improving the effectiveness of safety performance enhancement in diverse industries
Localisation of defects on carbon fibre surfaces using deep learning
Full text linkThis study explores the application of deep learning for localization and classification of common defects in carbon fibre materials. A Sony IMX250MZR polarisation camera was employed to leverage the polarising properties of CFRP surfaces. However, analysis revealed that the additional polarisation data provided minimal advantages. Instead, promising results were obtained using a standard monochrome output from the sensor. Defects were classified into two categories: "carbon fibre defects" and "foreign bodies". A dataset comprising of 2400+ annotated instances for each type was analysed using two state-of-the-art deep learning models: YOLOv11-seg,for instance segmentation, and SegFormer for pixel-wise classification. Images were captured under three different illumination conditions including specialized dome lighting and strip lights in ambient environments. Each lighting configuration yielded promising results, with dome lighting demonstrating superior performance. YOLOv11 achieved an average precision score of 0.817 under dome lighting, compared to 0.672 in the least favourable lighting scenario. SegFormer slightly outperformed YOLOv11 in segmentation accuracy, achieving a mean Intersection over Union (mIoU) of 0.742 compared to 0.678 for YOLOv11. The consistently high detection rates demonstrate the potential of both models for reliable identification of critical and minor defects, making them well-suited for industrial quality assurance
The representativeness of the Annual Survey of Hours and Earnings and its implications for UK wage policy
No full textThe Annual Survey of Hours and Earnings (ASHE) is based on an annual one per cent sample of employee jobs and provides many of the UK’s official earnings statistics. These statistics are produced using official weights designed to make the achieved sample in each year representative of the population of employee jobs in Britain by gender, age, occupation, and region. However, we show that jobs in small, young, private-sector organisations remain significantly under-represented after applying these weights. To address this issue, we develop new weights and demonstrate their importance through policy-relevant examples. Our new estimates suggest that the bite of the National Living Wage is greater than previously reported, and the gender pay gap is wider. We conclude that a new official review of the methodology for ASHE is merited, to improve the accuracy and reliability of data informing earnings analysis and research in the UK
An introductory guide to battery storage for Village Halls
No full textExecutive summaryWe think that you will definitely get the most out of this guide by reading the whole thing to develop your knowledge and understand some of the details and nuance related to this topic. However, the ten key points are provided in this summary for your convenience and three checklists on what to think about before you get a battery and what your battery professional should do are provided at the end of the guide. A roadmap of theprocess is also provided at the end of the guide.1. Batteries store electricity for later use which can have benefits for energy costs and climate change by shifting demand from peak times. Batteries can also have benefits for resilience to power cuts in certain scenarios but require extra systems for this to work.2. LiFePO4 lithium-ion batteries and Sodium-ion batteries are probably the most suitable for village halls. Sodium-ion batteries have less environmental and ethical challenges; only limited sizes are currently available, but more are in development and costs are comparable.3. Batteries have their own terminology which is important to understand when considering a battery system. All batteries require inverters and the most suitable will depend on your hall’s circumstances and type of electricity connection.4. Smart electricity meters are beneficial and allow you to take full advantage of your battery system, it is possible to use a battery without a smart meter, but its functionality will be limited.5. Certain types of batteries can provide emergency electricity during power cuts, but this must be specifically set up and requires additional cost and complexity. The amount of back-up electricity a battery will give you depends on its size and how you use it.6. Getting a battery which is the correct size for your hall is very important and to do this you need to think about how and when electricity is used in your hall currently and any planned future changes such as heat pumps or solar panels.7. The upfront cost of a battery varies but for a village hall is likely to cost between £5-20k. Exact operational energy savings will depend oncircumstances, but a battery could realistically save your hall several hundred pounds a year.8. Batteries should be installed outside in a well-ventilated but secure enclosure. You will need to notify your insurance company and the local fire service and update your risk assessments when you install a battery.9. Batteries come with energy management platforms and can be managed with an app on your phone. While you can just fit and forget your battery, you will benefit from tailoring its settings to how your hall is used.10. Battery professionals should be qualified electricians who are MCS certified and have received training for the specific make of battery. The MCS and many battery manufacturers provide options to find installers.Please read on for more details, explanation and rationale about all of the above
A temporally dynamic feature-extraction framework for phishing detection with LIME and SHAP explanations
Full text linkPhishing remains one of the most pervasive social engineering threats, exploiting human vulnerabilities and continuously evolving to bypass static detection mechanisms. Existing machine learning models achieve high accuracy but often act as opaque systems that lack robustness to evolving tactics and explainability, limiting trust and real-world deployment. In this research, we propose a dynamic Explainable AI (XAI) approach for phishing detection that integrates temporally aware feature extraction with dual interpretability through LIME and SHAP applied to the resulting window-level features. The novelty of this research lies in a temporally dynamic feature framework that simulates a plausible email reading progression using a heuristic temporal model and employs a sliding window aggregation method to capture behavioural and temporal patterns within email content. Using an aggregated dataset of 82,500 phishing and legitimate emails, dynamic features were extracted and used to train four classifiers: Random Forest, XGBoost, Multi-Layer Perceptron, and Logistic Regression. Ensemble models demonstrated strong performance with XGBoost achieving 94% accuracy and Random Forest 93%. This research addresses an important gap by combining dynamically constructed temporal features with transparent explanations, achieving high detection performance while preserving interpretability. These findings demonstrate that dynamic temporal modelling with explainable learning can enhance the trustworthiness and practicality of phishing detection systems, highlighting that temporally structured features and explainable learning can enhance the trustworthiness and practical deployability of phishing detection systems without incurring excessive computational overhead
LivDem-Families: Adapting the LivDem group intervention to support families to talk together about dementia
Full text linkIntroduction. LivDem is a psychoeducational group intervention designed to help people living with dementia talk more openly about their condition and adjust emotionally. While the original model focuses solely on individuals with dementia, limited involvement of family members can act as a barrier to wider relational support. Given the importance of maintaining strong relationships in dementia care, this study explores the adaptation of LivDem for couples and families.Method. The adaptation process involved four phases: (1) a survey of trained LivDem facilitators; (2) a stakeholder consultation with 26 participants including people with dementia, family members, facilitators, and professionals; (3) development of a manualised five-session intervention for families and couples, informed by public involvement; and (4) a pilot implementation with seven families. Sessions were delivered either by a clinical psychologist or by assistant psychologists under supervision. Quantitative and qualitative data were collected to assess feasibility, acceptability, and impact.Results. Initial findings from the pilot phase are promising. The seven families rated the intervention highly for acceptability (mean score: 19.3/20), appropriateness (19.3), and feasibility (19.2). Qualitative feedback indicated improved communication, emotional adjustment, and relational resilience. However, the intensity of the sessions led to disclosures of self-harm or harm to others in three families who were assessed or took part, suggesting a need for robust risk assessment and clinical oversight.Conclusion. The LivDem-families intervention shows strong potential for supporting relational adjustment to dementia. However, its emotional intensity necessitates careful screening and delivery by trained facilitators within appropriate clinical settings. A non-randomised feasibility study across two NHS sites is planned to further evaluate its integration into dementia care pathways
Federated learning in IoT environments: Examining the three-way see-saw for privacy, model-performance, and network-efficiency
Full text linkThis survey paper provides an in-depth exploration of Federated Learning (FL) in Internet of Things (IoT) environments , focusing on privacy-preserving techniques and their influence on model performance and network efficiency. It highlights key challenges and opportunities at the intersection of these technologies by offering a comprehensive review of FL applications in IoT. First, a customized taxonomy is introduced to evaluate the privacy levels, quality of service (QoS) and network efficiency of various Privacy-Preserving FL (PPFL) solutions in IoT configurations. Furthermore, the survey investigates strategies to improve FL accuracy while addressing resource and network constraints, both independently and together with privacy preservation techniques. Our findings underscore the complexity of optimizing resource utilization, learning performance, and privacy resilience, revealing that no single PPFL solution universally applies. The paper further identifies future research directions, including the integration of advanced technologies beyond 5G networks, and discusses standards, protocols, real-world PPFL projects from world-renowned industries for potential IoT applications
Custodian entrepreneurship: An examination of entrepreneurial activities in English country houses
No full textEnglish country houses are unique institutions that form an essential fabric in the country’s landscape. They highlight British history and are a significant element in the country heritage sector. The literature on country houses has examined various facets of them but there is a scarcity of literature about the type of entrepreneurial activities that are being undertaken at the houses. By examining 68 English country houses, this paper explores their entrepreneurial activities and determines that they can be organized according to physical areas, products and services, users, stakeholders and tactics. A typology depicting the entrepreneurial activities of these houses has been developed. This study makes an original contribution to both theory and practice by introducing the innovative concept of “custodian entrepreneurship” and opening discussion about entrepreneurship in this distinctive part of the UK’s heritage sector
Fixed-time L2 attitude control guaranteeing anti-unwinding performance and energy efficiency
Full text linkThis article deals with the challenging problem of fixed-time L2 control for flexible spacecraft attitude system with a focus on energy-efficiency, anti-unwinding property, and reducing conservativeness in estimating the settling time upper bound. To this end, we first introduce a novel fixed-time stable system which is applicable to spacecraft attitude system represented by unit quaternion. It provides a more accurate estimation of the settling time. Based on the proposed fixed-time system, we define a singularity-free, anti-unwinding sliding surface that does not include any piecewise continuous functions to address singularity issues due to the use of fractional power. This sliding surface contains the initial scalar part of the quaternion to guarantee fixed-time convergence for both equilibrium points, removing the unwinding problem. Considering the sliding variable as the performance vector, the proposed control framework guarantees that the fixed-time L2 gain of lumped disturbance attenuation is less than a predetermined value. The performance of the proposed control framework is established through numerical simulations and validated using a Speedgoat real-time experimental setup
Implementation of the Nursing Associate in the NHS: A rapid realist synthesis to understand mechanisms of integration and workforce development
No full textAim(s): To develop theories about how Nursing Associate (NA) roles are implemented and working within NHS practice: What works, for whom, in what contexts and how? Methods: Rapid realist synthesis of: (1) empirical and grey literature; (2) realist interviews with stakeholders. Sources were analysed using a realist approach that explored the data for novel or causal insights to generate initial programme theories. Results: Empirical and grey sources (n = 15) and transcripts from stakeholder interviews (n = 11) were synthesised which identified three theory areas relating to NA implementation: (1) Scope of NA role: Communication and expectations; (2) Variations to the NA model of working; and (3) Career progression: Entry point, stepping stone and career in itself. Conclusion: The NA holds the potential to improve nursing workforce stability by encouraging locally based, non‐registered healthcare staff to transition to an NA. However, the lack of collective understanding of the NA scope of practice can cause staff friction. It is unknown whether this friction will reduce over time or if staff divisions will lead to further deterioration of the workforce. Implications for the Profession and/or Patient Care: Ongoing clear communication regarding NA scope of practice needs to be provided to aid understanding of their supplementary role and its potential contribution to nursing teams. Impact: This work represents a first step to support both researchers and nursing workforce leaders in furthering knowledge of the impact of integrating NAs in diverse healthcare contexts and to unearth the mechanisms underpinning the success or failure of this new role. Reporting Method: Realist and meta‐narrative evidence syntheses: Evolving standards. Community Inclusion and Engagement (CIE): Planning of the research design and interpretation of the results was completed with nurse clinicians with experience in the NA role