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A novel bio-inspired caterpillar fungus (Ophiocordyceps sinensis) optimizer for SOFC parameter identification via GRNN
Get PDFAccurate parameter identification is crucial for the optimal control and performance assessment of solid oxide fuel cells (SOFCs) due to the high non-linearity in its modeling. To solve this, this study develops a novel caterpillar fungus optimizer (CFO) for SOFC parameter identification, coupled with generalized regression neural network (GRNN) for data preprocessing. The proposed CFO is characterized by powerful searching capabilities and strategic operators designed to overcome the challenges of local optimums. For a comprehensive validation, twenty-three standard benchmark functions are applied for analysis, demonstrating the effectiveness of CFO in finding the optimal solution and proficiency in escaping local optimums. Regarding the implementation for SOFC parameter identification, initially, GRNN is employed to filter out noise from the experimental data. The refined data are then transferred to CFO alongside four other competitive algorithms to identify unknown SOFC parameters. In this work, two widely studied SOFC models, i.e., electrochemical model (ECM) and simple electrochemical model (SECM) are adopted for validation under MATLAB and SimuNPS. The simulation results demonstrate that CFO, after data preprocessing, can identify the optimal parameters with robustness, speed, and accuracy. For instance, it achieves a maximum improvement in identification accuracy of 94.41 % and 94.10 % for ECM and SECM, respectively
Double-stranded sperm DNA fragmentation assessed using comet assay is associated with recurrent pregnancy loss
No full textResearch question: Do men attending a recurrent miscarriage clinic have high double-stranded sperm DNA damage compared with a sperm donor population? Design: This prospective cohort study included 100 men attending a recurrent miscarriage clinic, and 81 sperm donors from a European sperm bank who had proven fertility. All semen samples were evaluated using the Examen Lab alkaline (Exact) comet assay, which identifies the global (single and double strand) DNA damage, and the neutral (Extend) comet assay, measuring only double-stranded sperm DNA fragmentation (dsSDF). Results: Semen analysis showed that 66 male partners of women with a history of recurrent miscarriage were classified as being within normal parameters. Of these, however, 66 men (61%) had raised global SDF, and 52% had raised dsSDF. When evaluating each test separately, the Exact comet (global SDF) assay presented an area under the curve (AUC) of 0.690 (95% CI 0.623–0.756), with the neutral Extend comet (dsSDF only) assay having an AUC of 0.876 (95% CI 0.834–0.914), and the incidence of damage showed an improved AUC of 0.909 (95% CI 0.874–0.940). Conclusions: This study of male factor SDF in a large cohort of men attending a recurrent miscarriage clinic, where they are rarely the focus of clinical investigation, shows a strong association with dsSDF and male factor-driven miscarriage contribution, highlighting the importance of male investigation in couples experiencing recurrent pregnancy loss
Retail chain adaptation and emerging high street retail collaboration in response to polycrisis
Get PDFThis study investigates how polycrisis-induced strategic shifts in Scandinavian retail chains affect their dynamic capabilities and interconnectedness with high streets, and the implications for city center resilience and revitalization. The research addresses a significant gap in understanding how retail chains strategically adapt to polycrisis challenges in ways that could contribute to city center regeneration. By integrating dynamic capabilities theory with systems thinking and a multi-stakeholder place lens, we develop a holistic framework for analyzing retail adaptation within broader city center ecosystems. The study employs a qualitative longitudinal methodology, conducting 60 semi-structured interviews with 12 senior executives from seven Swedish retail chains across diverse sectors during 2020–2022. Using template analysis guided by sensemaking principles, we examined how retail chains developed collaborative capabilities in response to the evolving polycrisis conditions. Our findings reveal three key adaptive strategies: cost-sharing initiatives (including condominium-style property management and joint logistics operations), innovation alliances (such as cross-industry knowledge sharing and flexible pop-up concepts), and recognition of interdependency with local environments. The study demonstrates that retailers exercise nonlinear capability development, fundamentally altering the temporal logic of adaptation by requiring concurrent rather than sequential learning, experimentation, and transformational processes. We identify a paradigm shift from firm-centric to place-oriented approaches, where retail capabilities are co-created and shaped by specific city center contexts. The research contributes a novel ‘systems-based territorial capabilities perspective’ that operationalizes the synthesis of dynamic capabilities, multi-stakeholder collaboration, and systems theory. However, cultural inertia limits implementation, as retailers recognize their interdependence while not seeing themselves as primarily responsible for placemaking. The study suggests that successful city center revitalization requires transcending traditional isolated retail roles through collaborative territorial development processes that cross-leverage community assets
Personalising renal function monitoring and interventions in people living with heart failure: a protocol for co-designing a care pathway in the RENAL-HF programme.
No full textBackgroundHeart failure affects almost one million people in the UK and is increasing in prevalence. Many drugs used to treat heart failure impair renal function and can lead to hospitalisation. Adverse drug problems can be partially mitigated through regular renal monitoring and optimising of drug dose and choice to prevent deterioration of kidney function. This protocol describes part of a wider research programme: personalising renal function monitoring and interventions in people living with heart failure (RENAL-HF).AimThe aim of RENAL-HF is to develop improved processes in primary care to manage kidney health in people living with heart failure.MethodThe protocol covers gathering views of healthcare professionals, patients, and carers, to co-develop a care pathway for use in primary care. Using a mixed-methods approach, the work comprises the following six stages: (1) understanding current practice of optimising heart failure treatment while preserving renal function; (2) co-designing a care pathway including personalised renal function monitoring, thresholds for intervention and clinical guidelines; (3) decision making to identify elements that will support the care pathway; (4) developing training materials for primary care to enable use of the care pathway; (5) testing the usability of the prototype care pathway; and 6) a feasibility and acceptability study to inform the pre-clinical development and usability of the care pathway ahead of a cluster randomised control trial (RCT).ConclusionAll stages will elicit evidence from primary care practices, practitioners, and patients with which to assess and refine the care pathway. The evidence will inform how algorithm-guided individualised treatment can be implemented to improve the outcomes of patients with heart failure
Safe implementation in mixed Nash equilibrium
No full textSafe Implementation (Gavan and Penta, 2025) combines standard implementation with the requirement that the implementing mechanism is such that, if up to k agents deviate from the relevant solution concept, the outcomes that are induced are still ‘acceptable’ at every state of the world. In this paper, we study Safe Implementation of social choice correspondences in mixed Nash equilibrium. We identify a condition, Set-Comonotonicity, which is both necessary and (under mild domain restrictions) almost sufficient for this implementation notion
Event review: exploring the place of sexuality in death studies
Get PDFThe British Sociological Association’s Death, Dying, and Bereavement Study Group held its Annual Symposium on 14 December 2023, exploring a crucial yet often overlooked topic: the role of sexualities in death studies. Researchers from across the globe shared diverse insights and findings on ageing, queerness, identity, and the intersections of these themes with death and dying. The symposium addressed a significant gap in the intersection of death studies and sexuality research, underscoring the need for greater scholarly attention and interdisciplinary engagement in this underexplored area
Medin and transthyretin: a new amyloid double act in the aortic wall and valves
No full textBackground: Cross-seeding and co-assembly of multiple amyloid species are increasingly recognised in various organs and amyloidoses. Medin and wild-type transthyretin (TTR) both form age-related amyloid deposits and have been identified within the aortic wall. Given the emerging role of amyloid in aortic disease, this study investigates the potential colocalisation of TTR and medin in the aorta. Methods: Medin and TTR levels were measured in thoracic aortic wall samples from 30 patients undergoing surgical replacement for aortic aneurysm. Immunohistochemistry was performed on five aortic wall samples and two excised aortic valves to assess colocalisation patterns. In vitro assays, including Thioflavin T fluorescence and immunogold labelling electron microscopy, evaluated protein co-aggregation and fibril formation. Cellular toxicity assays examined the impact of TTR on medin aggregates. Results: A positive correlation was observed between medin and TTR levels in the aortic wall. In vitro assays revealed enhanced fibril formation and co-aggregation, with TTR reducing the cellular toxicity of medin aggregates, suggesting altered fibril properties. Immunohistochemistry confirmed colocalisation of medin and TTR in both aortic wall and valve samples. Conclusions: This study identifies a novel association between medin and TTR, highlighting a potential role for co-aggregation in vascular amyloid deposition
A dynamic reliability assessment method for multi-state manufacturing system by merging imprecise observational information
No full textAccurate reliability assessment of advanced manufacturing systems is essential for ensuring production efficiency, reducing downtime, and enabling intelligent maintenance strategies. In practical industrial environments, state observations obtained from sensors or expert evaluations are often imprecise. Effectively utilizing this uncertain information can substantially improve the precision of reliability evaluations. Conventional methodologies often encounter limitations in addressing this challenge, as manufacturing systems are generally characterized by networked production line configurations rather than traditional serial or parallel structures. Moreover, the effective integration of imprecise observational data is essential for the continuous updating of system reliability. This study introduces a novel approach for dynamic reliability evaluation of a multi-state manufacturing system (MSMS), incorporating both rework mechanisms and buffer elements to enhance the accuracy and applicability of system reliability assessments. The MSMS model can effectively depict the gradual degradation processes and diverse performance levels of manufacturing systems, allowing for a more realistic and detailed representation of system behavior over time compared to traditional binary-state models. This study employs the multistate flow network (MFN) model to construct the MSMS reliability assessment framework from a network structure perspective. Dynamic Bayesian networks (DBNs) are developed to update the reliability function of an individual MSMS by incorporating evidential observational data. An illustrative case study on the reliability update of an aluminum alloy wheel production line is presented to demonstrate the proposed methodology. The case study results further confirm the effectiveness of the approach
The retail platform’s green packaging strategy: the interplay between government tax policies and environmentally conscious consumers
Get PDFThe surge in packaging waste presents a critical concern in supply chain management. Motivated by observed green packaging practices of online retail platforms, this paper develops an analytical model to examine the platform’s green packaging strategy. We consider the interaction between government environmental tax policies and consumer environmental awareness. Our findings reveal that green packaging, regardless of taxation, boosts consumer demand and enhances platform profitability. Although green packaging reduces per-unit waste, it may paradoxically increase the total packaging waste due to higher consumer demand. The environmental tax mitigates waste by raising consumer costs, heightening environmental awareness, and enhancing the appeal of green packaging, yet it can suppress platform profitability and may reduce the incentive for greener packaging under certain conditions. The results emphasise the advantages of proactively implementing green packaging as a social responsibility, rather than in response to environmental tax. Policymakers are advised to balance environmental tax policies with incentives, such as subsidies, to promote sustainable practices and achieve both environmental and economic benefits
First excursion probability sensitivity in stochastic linear dynamics by means of multidomain line sampling
Get PDFThis contribution presents a novel framework for estimating the sensitivity of first excursion probabilities. The focus is on linear dynamic systems with non-proportional damping subject to stationary or non-stationary Gaussian excitation. The sensitivity is estimated with respect to structural parameters of the system, including material properties and geometric dimensions of the elements. In dynamical systems, calculating both the first excursion probability and its sensitivity is done in a high-dimensional space, making the task challenging and computationally expensive. In this regard, the multidomain Line Sampling framework exploits linearity to obtain sensitivity estimates as a byproduct of the first excursion probability evaluation. The results show that the presented technique is highly efficient compared to different methods in the literature, as demonstrated through two numerical examples involving small- and large-scale models
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