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Resurgence and Altered States outdoor sculpture exhibition
No full textThis output is the selection of a 3D printed public art sculpture for Altered States, a curated outdoor sculpture exhibition at Shaw House, Newbury, Berkshire, UK. It is an annual exhibition for the months of August and September. Selection for the exhibition is an open competition. For 2025 the exhibition featured 75 selected works including Resurgence by Lionel T Dean. The piece is 3D printed in recycled plastic which has then been wrapped in a structural skin of glass reinforced plastic, GRP, aka fiberglass. It is the result of experiments in ‘democratic’ open-source technologies that would be accessible to the independent arts practitioner. The exhibition ran from 2nd August – 28th September 2025
Entrepreneurial leadership and MSME performance in resource-constrained uncertain contexts: insights from Ethiopia
Get PDFopen access articleThis study examines the influence of entrepreneurial leadership (EL) attributes on the effectiveness of Micro, Small, and Medium Enterprises (MSMEs) in Ethiopia, a context characterised by institutional voids and resource constraints. Drawing on survey data from 356 MSME leaders, hierarchical regression analysis was employed to test the impact of five EL dimensions—creativity, opportunity-seeking, vision, decision-making, and risk-taking. The findings reveal that creativity and opportunity-seeking positively and significantly improve firm effectiveness, underscoring their importance in enabling adaptability and resilience in resource-constrained settings. In contrast, vision and decision-making exhibit no significant influence, reflecting the challenges of long-term strategic orientation under volatile institutional and political conditions. Counterintuitively, risk-taking demonstrates a negative and significant effect, highlighting how high uncertainty and weak institutional support exacerbate entrepreneurial vulnerability. Environmental dynamism emerges as a positive moderator, enabling leaders to navigate complexities through informal networks and adaptive strategies. These results suggest that the effectiveness of EL is heavily contingent upon contextual conditions rather than leadership attributes alone. The study contributes to entrepreneurship and leadership scholarship by advancing context-sensitive understandings of EL and offers policy insights for fostering MSME growth in fragile institutional environments
From apothecary to ‘McPharmacist’? Skills utilisation amongst community pharmacists in England
Get PDFThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This article speaks to ongoing sociological debate around the fast-changing organisation of medicine and the implications for skills utilisation – with a specific focus on community pharmacy. While the professional status of pharmacists has been the subject of much debate, the closely related theme of skills deployment has been significantly overlooked. Any coverage of skills has largely been restricted to the de-skilling effect of technology; analysis of the role other contextual factors might play has been piecemeal and fragmented. Drawing on qualitative data, this article aims to offer a more nuanced view of the skill trajectory, exploring employer and national policy and professional drivers of change. The results show these factors constrain and enable human agency, depending on the setting, opening up possibilities for both reskilling and deskilling. As such, the findings stress the important mediating influence exerted by ‘place’ i.e. the clinical setting on opportunities for skills development
Master of uncertainty: How strategic resilient organizations navigate crisis
Get PDFopen access articleStrategic resilient organizations (SROs) adapt and recover from adversity by drawing on dynamic and context-specific internal capabilities. This study investigates the combinatory conditions under which small and medium-sized enterprises (SMEs) achieve strategic resilience. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), we analyze how different configurations of internal mechanisms such as slack, planning, expertise, resources, and strategic innovation, interact to produce resilience outcomes. Our findings identify three distinct configurational paths, each sufficient for achieving high levels of strategic resilience, though non-reliant on a single factor alone. Across all configurations, organizational slack consistently emerges as a critical enabler, though not universally sufficient in isolation. Contrary to linear or additive models, our results support a configurational approach where resilience arises through interdependent mechanisms. The study advances theory by integrating insights from dynamic capabilities and the resource-based view, challenging the notion of a homogeneous path to resilience. Managerially, the findings offer actionable guidance on how SMEs can cultivate resilience by aligning internal features to context-specific demands. Future research should explore the temporal dynamics and cross-sector applicability of these configurations
Strategic adaptation in a cold funding climate: Third sector experiences of employability funding and commissioning in the UK after ‘Brexit’
Get PDFThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The ability of third sector organisations (TSOs) to strategically navigate commissioning environments in ‘marketized’ public services is much debated. This article addresses those delivering employability support outside the UK’s marketized public employment system following the end of European funding. Focusing on the UK Shared Prosperity Fund and No One Left Behind in Scotland, it examines TSOs’ views on the localisation of employability support under ‘austerity localism’ in the contrasting governance contexts of England and Scotland. The data derives from two surveys of TSOs and interviews with 17 chief executives/senior managers. Reductions in the amount and duration of funding are compounded by fragmented and inefficient commissioning processes as well as competition for funding with local authorities. Whilst organisations of all sizes have been adversely affected, smaller organisations are particularly at risk of closure. The findings indicate common problems across both governance contexts, raising important questions for the ‘localisation’ of employment support
Smart Farming Solutions: A User-Friendly GUI for Maize Tassel Estimation Using YOLO With Dynamic and Fixed Labelling, Featuring Video Support
Get PDFopen access articleThe integration of Autonomous Aerial Vehicles (AAVs) has significantly advanced image processing and remote sensing, particularly in precision agriculture. These technologies enhance data collection and agricultural yield estimation, benefiting banks, insurance companies, and government agencies in decision-making for budget allocation and quality assessments. This study addresses the challenge of accurately quantifying corn production by developing an enhanced YOLO-v8-based deep learning model, incorporating dynamic and fixed labeling techniques, tested on 810 images and video data for real-time detection. The research utilized two primary datasets totaling 570 images. The evaluation process comprised four distinct tests: Test 1, conducted on Dataset 1 with 200 images, assessed seven attention mechanisms (SE, CBAM, GA, LKA, CA, SA, and TA) using deep learning metrics (Precision, Recall, mAP50, mAP50-95,
F1-score) and statistical methods (Duncan’s test). Test 2 validated model performance on 370 images from external sources, where YOLO.SA achieved 97.48% accuracy, outperforming YOLO.LKA (95.13%). Test 3, comparing with the MTDC benchmark dataset, confirmed YOLO.SA’s accuracy at 95.93%, exceeding previous reports, while YOLO.LKA achieved 95.71%. Finally, Test 4, utilizing video-based evaluation via a developed GUI, demonstrated YOLO.SA’s superiority (95.77%) over YOLO.LKA (95.48%) and YOLO-v5 (95.72%), significantly outperforming the standard YOLO model (72.79%). This study advances computer vision in agriculture, offering a scalable, high-accuracy model for corn yield estimation, with broad applications in farming optimization, financial planning, and policy-making
Surface Crack Analysis and Quality Enhancement of 30%13 (AISI 420) Martensitic Stainless Steel Gate Valve Shutters via Electrolytic Plasma Hardening
Get PDFopen access articleThis study examines the mechanisms of crack formation in gate valve shutters, identifies the underlying causes, and proposes an effective prevention method through electrolytic plasma surface treatment technology. Scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) with a JSM-6390LV SEM were used to evaluate the chemical composition, morphology, structure, and surface defects of the shutters at nano- and microscale levels. To assess mechanical properties, Vickers microhardness testing (ISO 6507-1) was conducted using a DuraScan 20 microhardness tester, while the phase composition of 30Х13 steel (AISI 420) was examined through X-ray diffraction (XRD) analysis. The results demonstrate a significant increase in surface microhardness in samples subjected to electrolytic plasma hardening, with values reaching up to 650 HV. Furthermore, the phase composition of the treated surface exhibited notable changes, including the dissolution of carbides in austenite and the formation of martensite as the predominant phase. Based on these findings, electrolytic plasma hardening is proposed as an effective alternative to traditional volumetric quenching methods. An optimal treatment mode has been developed for 30 × 13 steel, ensuring enhanced surface properties and improved durability. The experimental results validate the effectiveness of this approach in enhancing the mechanical performance and operational reliability of gate valves
The Psychological Impacts and Coping Strategies of People Under 60 Living With Mesothelioma Cancer: A Qualitative Study
Get PDFopen access articleIntroduction: Mesothelioma is a life-limiting cancer that results in an array of psychological difficulties. While this cancer is associated with older men exposed to asbestos, it can develop in people under 60, though little research has considered the challenges and ways of supporting this younger demographic.
Methods: Online semi-structured interviews were carried out one-to-one with a total of 18 individuals; 6 men and 12 women, aged 26–59 (mean age 45), diagnosed with pleural or peritoneal mesothelioma. Participants could also share and discuss photographs to help further convey their cancer experiences. An interpretative phenomenological approach guided the analysis of transcript and
photographic data.
Results: Two themes with discrete subthemes are presented: “dying young of an older person’s disease,” which explores individuals’ experiences of shock at diagnosis and widespread sense of disrupted living, concern for family members, and lack of peer support, and “living young with an older person’s disease,” which explores psycho-behavioral coping via focus on the atypicality of mesothelioma in young groups, return to everyday living, and via activities and exercise to manage anxiety and foster a sense of agency.
Conclusion: Findings demonstrate the need to develop tailored clinical and psychotherapeutic support to address the practical and psychological difficulties younger people encounter
A nonlinear mixed-frequency grey prediction model with two-stage lag parameter optimization and its application
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.With the advancement of data science, the demand for methods capable of simultaneously processing and utilizing complex mixed-frequency data systems with uncertainty characteristics is increasing. To address this need, a novel nonlinear mixed-frequency grey prediction model with two-stage lag parameter optimization is proposed which integrates frequency-domain analysis and optimization algorithm. The proposed model innovatively incorporates the phase spectrum analysis method into the mixed-frequency modeling framework, determines a reasonable range for lag parameters using frequency-domain analysis, and enhances the characterization of system nonlinearity by introducing a power-driven term. The effectiveness and robustness of the proposed model are validated through both experiments on synthetic data and real-world case studies on electricity consumption. Comparative experiments against existing mixed-frequency grey prediction model, nonlinear grey prediction model, and mixed-frequency sampling regression model demonstrate that proposed model exhibits superior performance in key metrics, including mean absolute percentage error and standard deviation. This study provides a novel solution for modeling relationships among multi-frequency variables in complex systems
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