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Data-Driven Event-Triggered Fixed-Time Load Frequency Control for Multi-Area Power Systems With Input Delays
No full textLoad frequency control is essential for maintaining power system stability, especially under uncertainties and input delays. This paper proposes a reinforcement learning-based dual-channel dynamic event-triggered fixed-time load frequency control approach for uncertain multi-area power systems with input delays. A non-singular fast terminal sliding mode technique is employed to guarantee that the tracking error converges within a fixed time. To address system uncertainties and input delays, actor neural networks are designed to estimate the modeling uncertainties and provide compensation, and critic neural networks evaluate execution costs. To further enhance efficiency, a dual-channel event-triggered mechanism is designed, reducing communication overhead through independent dynamic event-triggering strategies for control input and output channels. The stability of the proposed method is rigorously analyzed using the Lyapunov method. Simulation results demonstrate faster convergence, reduced communication costs, and improved frequency stability compared to existing methods
Evaluating the Feasibility and Acceptability of a Prototype Hospital Digital Antibiotic Review Tracking Toolkit: A Qualitative Study Using the RE-AIM Framework
Get PDFBackground: Internationally, digital health interventions have increasingly been adopted within hospital settings. Optimising their clinical implementation requires user involvement, but there is a lack of evidence regarding how this should be done. Objectives: This study was carried out to understand the acceptability and usability of a prototype Digital Antibiotic Review Tracking Toolkit and identify modifications required to optimise it ahead of a trial. Methods: The optimisation process involved online semi-structured interviews with a purposive sample of fifteen healthcare professionals recruited from Scotland and England, along with three service users, to gather feedback on the prototype’s design, content and delivery. Participants’ negative views were specifically sought to identify adaptations needed to ensure that the intervention’s components aligned optimally with end-user needs. Data were analysed using Framework Analysis guided by the RE-AIM implementation science framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance) to identify key themes. Results: Participants mostly voiced positive views regarding the prototype, finding it acceptable, feasible and engaging. They also identified concerns relating to its adoption, system functionality, accessibility and maintenance that needed to be addressed. Anticipated low adoption rates were linked to issues surrounding computer literacy. This detailed user feedback informed rapid adjustments to the intervention to enhance its acceptability, perceived future credibility and usability in hospitals. Conclusions: This novel study illustrates how to identify, modify and adapt a digital intervention quickly and efficiently using qualitative iterative methods. Findings highlight the critical importance of contextualising end-user experience with health interventions to facilitate future engagement, uptake, and long-term use. This study also demonstrates how core elements of the MRC framework can be operationalised to help refine prototype digital interventions pre-trial
Navigating Artificial Intelligence for Cultural Heritage Organisations
Get PDFThe question of how artificial intelligence and machine learning should be applied to data in libraries and other cultural institutions is a challenge shared by heritage professionals, computer scientists and digital humanities scholars. As the number of digitised and born-digital records grows, archival practices are looking to automated systems to manage workloads and make cultural records more accessible. AI is playing a crucial role in data management systems within the cultural heritage sector, and information professionals are looking for ways to navigate current challenges and opportunities. Additionally, sector professionals and scholars are benefiting from the many new affordances and innovative research questions offered by using large-scale digital collections as data. Navigating Artificial Intelligence for Cultural Heritage Organisations explores the innovative technologies and approaches to digitised and born-digital records within libraries and archives across the UK and US, and beyond. It brings together chapters from experts across the fields of digital humanities, computer science and information science, alongside professionals within the library and archival sector. The authors explore technologies being applied to digitised and born-digital records within libraries, archives and other heritage organisations, including innovative approaches in computer vision, Chat GPT, and user experience. The volume has been designed to reflect current and state-of-the-art technologies and innovations for the preservation and accessibility of digitised and born-digital records, to help navigate the future of AI for cultural heritage organisations
Upcycling Alum Sludge as a Reinforcement in PBAT Composites: A Sustainable Approach to Waste Valorisation
Get PDFThis study explores the valorisation of alum sludge, a byproduct of water treatment processes, as a sustainable reinforcement material in Poly(butylene adipate-co-terephthalate) (PBAT) composites. The research aims to address industrial waste challenges by developing eco-friendly composite materials while promoting circular economy principles. Alum sludge particles, classified into two size distributions (<63 µm and <250 µm), were incorporated into PBAT matrices at varying concentrations. The composites were characterised for their mechanical, thermal, crystallographic, and moisture adsorption properties; and their biodegradation behaviour was evaluated through soil burial tests over 60 days. The results revealed that the 63 µm particle size fraction exhibited superior performance compared to the 250 µm fraction, demonstrating improved mechanical properties, reduced degradation rates, and enhanced interfacial bonding. Composites with 5 wt.% alum sludge achieved a balance between reinforcement and processability, outperforming the other filler concentrations examined. This innovative approach highlights the potential of upcycling alum sludge into functional materials, advancing sustainable waste management and composite manufacturing. Furthermore, the observed variation in degradation rates suggests that these composites can be tailored for applications requiring controlled compostability
Polish women’s experiences of domestic violence: intersecting roles of migration and socio-cultural, religious and policy contexts in Poland and in the UK
Get PDFScholarship on domestic violence and abuse has sought to understand how women's experiences are influenced by gender and its intersections with other social relations of power. We draw upon life history interviews with Polish women and interviews with practitioners to contribute to this intersectional and transnational feminist scholarship by examining how intersections between the migration process, immigration status and socio-cultural, religious and institutional contexts of Poland and the UK shape Polish women’s experiences of domestic violence and abuse. In doing so, we seek to redress the invisibilisation of Polish migrant women in the scholarship on domestic violence and abuse in the UK and beyond, in a context where they are invisibilised as ‘white’ and the particularities of their experiences neglected. Beyond a focus on the specificity of Polish women’s experiences through utilising an intersectional lens to understand the difference that difference makes, we also draw attention to similarities in migrant women’s structural location within exclusionary immigration/welfare bordering regimes in the UK, which creates conducive contexts for such violence. In doing so, we widen the lens used to understand domestic violence beyond family and interpersonal dynamics to the opportunities and constraints posed by intersecting social relations and gendered geographies of power
Sodium Alginate as a Green Consolidant for Waterlogged Wood—A Preliminary Study
Get PDFTraditional consolidants commonly used for waterlogged wood conservation often present long-term drawbacks, prompting research into new and reliable alternatives. Reducing reliance on fossil-based chemicals that are harmful to people, the environment, and the climate is a growing trend, and sustainable materials are now being explored as alternative consolidants for conserving waterlogged archaeological wood. Among these bio-based products, sodium alginate, a natural polysaccharide, has shown promising potential. This study aimed to evaluate its effectiveness in stabilising dimensions of severely degraded archaeological elm wood during drying. Various treatments were tested, and dimensional stabilisation (ASE), weight percent gain (WPG), and volumetric shrinkage (Vs) were assessed. Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) were used to evaluate alginate penetration and interactions with residual wood components. Results indicated that the effectiveness of sodium alginate depends on the treatment method, with the soaking approach and slow drying providing the highest WPG and the best stabilisation without altering the natural wood colour. Although the best achieved anti-shrink efficiency of 40% is insufficient from the conservation perspective, sodium alginate has proven to be a promising consolidant for the conservation of waterlogged wood. Further studies will focus on enhancing its penetration and interactions with residual wood components
Nanocellulose Extraction from Biomass Waste: Unlocking Sustainable Pathways for Biomedical Applications
Get PDFThe escalating global waste crisis necessitates innovative solutions. This study investigates the sustainable production of nanocellulose from biomass waste and its biomedical applications. Cellulose‐rich materials–including wood, textiles, agricultural residues, and food by‐products–were systematically processed using alkaline, acid, and oxidative pretreatments to enhance fiber accessibility. Mechanical techniques, such as grinding and homogenization, combined with chemical methods like acid hydrolysis and 2,2,6,6‐Tetramethylpiperidin‐1‐yl‐oxyl (TEMPO) oxidation, were employed to successfully isolate nanocellulose. Post‐treatment modifications, including surface coating and cross‐linking, further tailored its properties for specific applications. The results demonstrated nanocellulose's biocompatibility, biodegradability, and functional versatility. In wound healing, it enhanced moisture management and exhibited antimicrobial properties. Its high surface area facilitated efficient drug loading and controlled release in drug delivery applications. Nanocellulose bioinks supported cell proliferation in 3D bioprinting for tissue engineering. Additional applications in biosensors and personal care products were also identified. This study advances sustainable materials science, aligning resource conservation with circular economy principles to address biomedical sector needs
The concept of digital adaptability of nurses and midwives: A factor analysis
No full textAim/objectiveTo investigate the underlying constructs of the 29 digital adaptability competencies to identify the phenomenon's key or conceptual properties.BackgroundA shift towards a strong and increasing presence of eHealth in future practice requires the competencies of nurses and midwives. This ability to adapt to technological evolutions is called digital adaptability. A set of 29 items representing the competencies of digital adaptability for nurses and midwives provides the first comprehensive description of this relatively new concept. DesignCross-sectional survey with a total sample size of 557 Flemish midwives and nurses.Methods Internal consistency and construct validity were established using Cronbach's alpha, exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA).ResultsEFA revealed two factors: 'me and the digital world' (17 items) and 'me, the digital world, and my patient' (12 items). CFA tested the model and showed a good model-fit. Strong internal consistency was observed.ConclusionsTwo factors were identified. The first, ‘me & the digital world,’ is task-oriented and focuses on nurses/midwives’ personal use of technology. The second, ‘me, the digital world, and my patient,’ is patient-centered and focuses on nurses' and midwives’ use of technology while interacting with their patients during care provision
The Impact of China’s Outward FDI on Agricultural Productivity
No full textChina's outward foreign direct investment (OFDI) has emerged as a critical driver of economic development in Belt and Road (B&R) countries. However, its role in fostering agricultural productivity growth in the region remains underexplored. This study investigates the relationship between China's OFDI and agricultural productivity in 58 B&R countries from 2003 to 2021. Utilizing panel data, we quantitatively assess agricultural productivity while incorporating the influence of Chinese OFDI. Furthermore, the analysis distinguishes between high-income and middle- to low-income countries, offering a nuanced understanding of differential impacts. The results indicate that China's OFDI significantly enhances agricultural productivity across the region, with a particularly pronounced effect in middle- and low-income countries. This suggests that Chinese investments are more impactful in countries with lower income levels, underscoring their critical role in addressing disparities and promoting sustainable agricultural development. The findings provide actionable insights for policymakers in China and B&R countries, emphasizing strategies to deepen investment collaboration and advance agricultural sustainability, food security, and nutrition outcomes
Local bond behavior of partially encased composite steel and recycled concrete structural members
No full textBond failure at the steel–concrete interface is a leading cause of performance degradation in partially encased composite (PEC) structural members. Compared with other composite structures, PEC structural members are more susceptible to bond failure owing to the unique characteristics of their construction, highlighting the need to study and improve the interfacial bond behavior. In this study, the bond behavior of partially encased composite steel and recycled concrete (PERC) structural members was explored via push-out testing, and the influences of diverse parameters (the strength of recycled concrete (RC), anchorage length, and the number of layers) on the bond behavior were assessed based on the gray correlation theory. The results suggest that the average ultimate bond strength has a positive relationship with both the number of stud layers and RC strength. Moreover, the number of stud layers had a more significant effect on the ultimate bond strength than on the RC strength. The average ultimate bond strength increased by 665 % when studs were arranged in a double layer. Conversely, the average ultimate bond strength decreased by 14.3 % and 23.4 % as the anchorage length increased from 300 mm to 400 mm and then to 500 mm, respectively. Furthermore, equations for determining the characteristic points essential for constructing a predictive model of the average bond stress–slip behavior at the PERC bond interface were established through statistical regression of the characteristic points from the average bond–slip curve. The bond stress distribution along the anchorage region was further analyzed based on the strain data from the RC and main steel component. A position function was introduced to describe the spatial distribution of the bond stress along the anchorage depth, enabling a more accurate prediction of the bond–slip behavior at different bonding locations of the main steel component. These findings contribute to a better prediction model for the bond performance in PERC structures, providing valuable insights into the finite element analysis of PERC structure members
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