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Supporting people with chronic kidney disease to self-manage their condition: understanding the lived experiences, needs and requirements, and barriers and facilitators
No full textBackground Self-management has been identified as an essential component in the effective management of patients with chronic kidney disease (CKD). To effectively develop interventions that support patients with CKD to self-manage, it is crucial to understand their experiences and the factors that may influence their ability to self-manage. This study explored awareness, attitudes and participation with self-management in people living with non-dialysis CKD to understand factors influencing self-management behaviours. Methods Semi-structured interviews were conducted with 22 individuals living with non-dialysis CKD. Topics explored included perspectives and experiences of self-management, health and lifestyle behaviours, healthcare professional support, and self-management support, including future interventional approaches. Data were audio recorded and transcribed verbatim. Thematic analysis was used to analyse the data and to identify and report themes. Results Six themes were identified encompassing perspectives, barriers and facilitators of self-management: “perceptions and experiences of (self-)managing CKD”, “perceived needs and requirements for self-management education and support”, “knowledge and capability-related factors”, “skills and opportunity-related factors”, “confidence and motivational-related factors” and “social support”. Conclusion Participants perceived that their CKD was not a significant problem, given the lack of concern from their doctor. Despite reporting a lack of awareness and understanding of CKD and its management, participants expressed interest in learning more and implementing appropriate self-management strategies. It was perceived that information and support were provided when it was almost too late, and not when it could potentially have the greatest impact. Perceived barriers and facilitators must be considered when developing interventions to support self-management for people with CKD. Graphical abstract</p
The Challenging Records Toolkit: Supporting staff who encounter challenging records unexpectedly
No full textThis resource was created by Sarah Wood, Assistant Archivist at the University of Leicester and The National Archives & Research Libraries UK Professional Fellow, 2024-2025.The Toolkit has been influenced by the Archives & Records Association’s ‘Emotional Support Guides’, The National Archives ‘Potential risks, impacts and mitigations’ webpages and the online course ‘A Trauma-Informed Approach to Managing Archives’.It has been shaped by current academic literature and data collected through interviews with a small number of participants working in the UK archive sector. Anonymised quotations from these interviews feature in the Toolkit.The Toolkit includes discussion templates that have been modelled on the HSE’s Talking Toolkit and workplace guidance developed by the CIPD & mental health charity Mind.Early versions of the Toolkit were piloted during workshops held at The National Archives and the University of Leicester between January-February 2025. Feedback was also received from the University’s Occupational Health Service Manager.</p
Multi-objective Optimization of Permanent Magnet-assisted Synchronous Reluctance Machine Based on Dual-Driven Model with Search Space Reduction Method
No full textPermanent magnet-assisted synchronous reluctance machines (PMa-SynRM) are widely used for low cost, high efficiency, and have great potential for widespread application in the pump application. However, the design optimization of PMa-SynRM will be time-consuming by using conventional optimization algorithms due to complex geometric structure with a large number of parameters. In this paper, a novel design optimization method is proposed to improve the optimization efficiency while securing accuracy, by utilizing a physics-data dual driven model. The proposed method employs the low-fidelity simplified magnetic equivalent circuit to rapidly locate promising subregions in the global search space. Besides, high-fidelity (HF) finite element analysis cases are used to establish the surrogate model to accurately predict the optimization results in the local search space. Furthermore, a constrained space Latin hypercube sampling method is proposed for sampling in constrained local space to ensure the feasibility of sample to reduce the global search space. The proposed dual-driven model can reduce over 50% required time compared to traditional HF surrogate models with similar prediction accuracy. Finally, a 15 kW prototype is designed by the proposed optimization method, and fabricated and tested to validate the final optimization results.</p
Aflatoxin exposure and mortality in acutely ill children: Results from the CHAIN network cohort
No full textBackground Chronic exposure to aflatoxins is associated with liver cancer, impaired child growth, and compromised immune function. The Childhood Acute Illness and Nutrition (CHAIN) Network cohort was established to identify risk factors for mortality in acutely ill children admitted to nine hospitals in four African and two South Asian countries. We examined the role of aflatoxin exposure in inpatient and post-discharge mortality. Methods In a nested case-cohort from the CHAIN cohort, we compared aflatoxin exposure at admission and discharge with death or survival in hospital (n=755) or up to 180-days post-discharge (n=585) and with community participants (CP, n=222). Children were stratified into non-wasting, medium-wasting and severe-wasting groups based on mid-upper arm circumference. Serum samples were analysed for an aflatoxin exposure biomarker, the aflatoxin-albumin adduct (AF-alb) using ELISA. Findings Overall, 56% of hospitalised participants tested positive for AF-alb at admission. The AF-alb level was higher in deceased (geometric mean and 95% CI (GM and 95% CI) 5.9 (4.9 to 7.1)) than in survivors (4.2 (3.8 to 4.7)) and CP (3.7 (3.1 to 4.3)) pg/mg alb. AF-alb concentration was higher at admission (4.7, (4.2 to 5.1)) than at discharge (3.7, (3.3 to 4.1)) and in the CP group (3.7, (3.1 to 4.3)) pg/mg alb (p</p
The argument for justice: a critical taxonomy of citizenship
No full textThis Working Paper introduces a critical taxonomy of citizenship, challenging traditional binary frameworks and revealing the inequalities embedded within constitutional systems. Citizenship, it argues, is not a singular or universal experience but a spectrum of statuses reflecting the divergent realities of individuals within the same polity. Building on Jellinek’s Statustheorie, the Working Paper distinguishes between formal and material status to expose the systemic barriers that marginalised groups face in accessing substantive protections. The proposed taxonomy identifies six statuses –negatory nationality, affirmative nationality, semi-statuses, passive citizenship, receptorycitizenship, and citizenship proper – each representing constitutional positions in relation to rightsand protections. This framework critically examines how mechanisms like sub-standard nationalityand systemic barriers perpetuate exclusion and oppression, emphasising the disconnect betweenthe ideal promises of citizenship and its lived reality. The Working Paper bridges theory and practiceby offering a structured framework to understand and address disparities, equipping scholars,policymakers, and practitioners with tools to understand and challenge oppressive structures.Ultimately, the Working Paper reimagines citizenship as a tool for justice, advocating for systemicreforms that align the real and ideal dimensions of rights. It calls for a transformative approach tocitizenship that ensures equal access and protections, making citizenship an instrument to makejustice a tangible reality rather than a mere aspiration.</p
Thermodynamic based numerical modelling of inclusion removal in a bottom stirring ladle furnace
No full textSteel strength enhancement remains a critical challenge in steelmaking, with non-metallic inclusions significantly impairing mechanical properties. Although bubble blowing in ladle furnaces effectively reduces inclusions, challenges persist in optimizing bubble size, predicting removal efficiency, and characterizing bubbles and inclusions in high-temperature melts. Additionally, while alloying and hot rolling principles are well-established, accurately predicting mechanical properties for diverse steel grades remains complex due to high-dimensional variable interactions.This study addresses these challenges by combining numerical modelling and machine learning. A CFD-based model simulates bubble generation from nozzles of varying sizes and geometries under different gas flow rates, with predicted bubble sizes validated experimentally and integrated into a bubble-inclusion attachment model. To improve removal efficiency prediction, interfacial energy changes during bubble-inclusion collisions were analysed, with the energy gap serving as a criterion for attachment feasibility. A comprehensive model incorporating flow and temperature fields was developed to quantify inclusion removal.For mechanical property prediction, a machine learning approach with statistical feature engineering was proposed, reducing input variables from 46 to 13 while maintaining high accuracy (R > 0.94) on an industrial dataset of 12,000 samples. The model’s reliability was confirmed by aligning feature importance rankings with empirical data. This work demonstrates the potential of integrated CFD and machine learning methods to advance steel quality control and strength prediction.</p
Understanding tropical forest carbon dynamics in Malaysian Borneo: logging disturbance, key drivers and methodology
No full textTropical forests play a critical role in the global carbon budget, yet their extent and functioning has been, and continues to be, threatened by increasing human disturbance and anthropogenic pressures, including deforestation and forest degradation. Consequently, logged and structurally degraded forests are fast becoming one of the most prevalent land-use types throughout the tropics, yet, logged forest landscapes have received little research attention compared to their old-growth counterparts. This thesis aims to quantify the carbon budget along a logging disturbance gradient, examine factors driving carbon fluxes and evaluate the accuracy of measurement methods. Using the heterogeneous mosaic landscape of Malaysian Borneo, this thesis captures a disturbance gradient from old-growth through to heavily logged forest.First, the complete carbon budget is quantified across the disturbance gradient using ground-based biometric methods and validated with measurements collected independently from an eddy covariance flux tower. Similarities and differences in carbon allocation between logged and old-growth forests are explored to understand how tropical forests respond to logging. Secondly, the thesis explores what drives woody stem CO2 efflux at different spatial scales. Stems are the largest contributor to forest biomass, and so the respiratory consumption of stems provides a vital insight into forest metabolism and carbon allocation strategies, and ultimately ecosystem response to logging. Lastly, the thesis investigates how accurate the employed methods are for estimating woody stem CO2 efflux in the field with the intention of providing recommendations to mitigate potential biases. A case study approach is used to quantify vertical and diurnal variations in stem CO2 efflux along with terrestrial LiDAR scanning to investigate the accuracy of allometric equations to estimate total stem surface area.Overall, this research makes a novel contribution to improving our understanding of how tropical forest carbon dynamics respond to logging activities. Given that these ecosystems face an insurmountable threat from anthropogenic climate change and continued pressure from logging and agricultural expansion, increasing our knowledge and understanding enables more informed decisions regarding tropical forest policy, management and protection.</p
Evolution and Homology of Monoaminergic Cell Types: Data
No full textMetacell Objects supporting Chapter 3 of the Thesis: Evolution of Neuronal Regulatory Programs</p
My money endorses my campaign: The influence of entrepreneur's self-pledge on crowdfunding campaign success
No full textThis study investigates the influence of entrepreneurs' self-pledge (ESP)—personal financial contributions to their own campaigns—on the success of reward-based crowdfunding. Drawing on Impression Management (IM) theory, we explore how ESP functions as a strategic tactic to signal commitment and credibility, shaping backers' perceptions of campaign quality. Using a dataset of 1287 campaigns from Zhongchou, China's leading reward-based crowdfunding platform, our analysis reveals that ESP significantly enhances campaign success, measured by funding achievement, total pledges, and fundraising ratios. This effect is partially mediated by perceived campaign quality, reflected in signals like videos and descriptions. These findings extend IM theory by applying it to crowdfunding's unique emotional and symbolic context, providing actionable insights for entrepreneurs and platform operators to improve fundraising outcomes.</p