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Two-Phase Flow Simulation of Bubble Cross-Membrane Removal Dynamics in Boiling-Desorption Mode for Microchannel Membrane-Based Generators
Get PDFCompact and efficient absorption refrigeration systems can effectively utilize waste heat and renewable energy when operated in a boiling-desorption mode, which maximizes the desorption rate. Hydrophobic membranes play a critical role in microchannel membrane-based generators; however, limited research has addressed bubble cross-membrane removal dynamics under boiling-desorption conditions, particularly the influence of membrane hydrophobicity. In this study, a two-phase flow bubble-removal model was developed to accurately represent boiling-desorption behavior. Numerical simulations were performed to investigate the effects of membrane hydrophobicity and heating power on bubble dynamics, wall temperature, venting rate, and channel pressure drop. Results show that bubble venting proceeds through four stages: nucleation and growth, liquid-film rupture with deformation, lateral spreading, and sustained vapor removal. Hydrophobicity effects become most significant from the third stage onwards. Increased hydrophobicity reduces wall temperature, with greater reductions at higher heat fluxes, and enhances venting performance by increasing total vapor removal and reducing removal time. Channel pressure fluctuations comprise high-frequency components from bubble growth and low-frequency components from venting-induced flow interruptions, with relative contributions dependent on hydrophobicity and heat flux. These findings provide new insights into bubble-removal mechanisms and offer guidance for the design and optimization of high-performance microchannel membrane-based generators
Implementing the Action Falls Program Into Care Homes in England (the FinCH Imp Study)
No full textObjectives Falls for care homes residents are a major cause of morbidity, mortality, and increased health and social care costs. The Action Falls program incorporates a multifactorial falls risk assessment checklist, training, and support for care home staff, which has been shown to reduce falls in care homes by 43%. This study explores the barriers, facilitators, and feasibility of implementing the Action Falls program into daily use in care homes. Design Implementation study using the normalization process theory. Setting and Participants Care homes were trained and supported to use Action Falls for 12 months. Care home staff were invited to complete Normalization MeAsure Development questionnaires at baseline and 9 months, and attend Action Falls Collaborative events where observational notes were taken. Methods Staff readiness use Action Falls, training uptake, and costs were reported. Feasibility of collecting falls data was also measured. Quantitative data were analyzed with descriptive statistics and regression models; qualitative data underwent thematic analysis. Results A total of 60% of care home staff received Action Falls training across 175 sessions. A total of 660 Normalization MeAsure Development questionnaires indicated that staff trained in Action Falls reported greater confidence in adopting the program. Confidence decreased over time, and barriers to training, including staff turnover and time constraints, were evident. The integration of the Action Falls checklist into digital care records was a key barrier to implementation. The average cost of training per care home was £331.60. Data on falls were returned by 88% of participating homes, with a mean of 2.53 falls per person-year. Conclusions and Implications Care homes were engaged and motivated to use Action Falls, which can be implemented with modest cost. Results emphasize the importance of ongoing support, digital integration, and policy backing to embed the Action Falls program into care homes. Overcoming logistical and technologic challenges is critical for its success
Optimised Model Predictive Control for MMCs: Enhancing Performance and Reducing Computational Burden
Get PDFThis paper proposes an Improved Folding Model Predictive Control (IFMPC) strategy for Modular Multilevel Converters (MMCs) that significantly reduces computational complexity while enhancing control accuracy and real-time feasibility. Although a Finite Control Set MPC (FCS-MPC) uses actual capacitor voltages, the state-of-the-art methods rely on averaged capacitor voltages for prediction, which can introduce inaccuracies. The proposed IFMPC consistently employs instantaneous capacitor voltages to generate voltage vectors during the prediction stage, thereby reducing prediction errors and enhancing both transient and steady-state performance. The proposed approach integrates four critical control objectives AC current tracking, circulating current suppression, arm energy balancing, and leg energy distribution into a unified cost function with only two tunable weighting factors, simplifying the tuning process without compromising robustness. Real-time hardware-in-the-loop (HIL) validation on a scaled MMC prototype demonstrates rapid dynamic response, effective disturbance rejection, and reduced total harmonic distortion (THD) under various operating conditions, including parameter mismatches and grid harmonic distortions. Comparative analysis against existing indirect MPC techniques reveals that IFMPC achieves superior control performance with reduced computational burden, making it well suited for MMCs with a high number of submodules (SMs). The proposed method offers a scalable and industry-ready solution for advanced MMC control in high-power applications
Physicochemical profiling of Bambara groundnut (Vigna subterranea L.) reveals variation in cooking quality relevant to breeding programs
Get PDFUnderstanding seed physicochemical properties allows breeders to select traits that contribute to desirable cooking characteristics (texture, taste, and nutritional content). Breeding programs can optimize resources by focusing on traits directly related to cooking time and quality. A total of 156 Bambara groundnut (BGN) recombinant inbred lines were analysed for physicochemical properties [hydration capacity (HC), hydration index (HI), swelling index (SI), pH, texture and cooking time (CT)], proximate and nutrient compositions. Analysis of variance showed significant differences (p < 0.05) in variables measured. Shortest CT (40 min) was recorded in S19/Ankpa4-100-87, while S19/Ankpa4-106-92 has the longest CT (147 min). Cooking time was negatively correlated with HC (r = − 0.42), HI (r = − 0.45) and swelling capacity (SC) (r = − 0.55). Neutral Detergent Fibre (NDF) and protein content showed significant differences between raw and cooked BGN (p < 0.05). Cooking significantly increased protein, fat, NDF, Zn, and Cu; however, cooking also significantly reduced Fe and total mineral (ash). Texture, CT and electrical conductivity (EC) of the genotypes varied significantly, which aided classification into five groups, namely: A (soft-cooking genotypes), B (slightly soft-cooking genotypes), C (slightly hard-cooking genotypes), D (moderately hard-cooking genotypes) and E (hard-cooking genotypes). A total of 14 genotypes (DodR, BURKINA, ANKPA 4, TIGD, NAV 4, S19/Ankpa4-100-87 IITA686/LunT-292-233, IITA686/LunT, S19/Ankpa4-130-1, S19/Ankpa4-50-43, S19/Ankpa4-92, IITA686/LunT-403-314, S19/Ankpa4-141-121 and S19/Ankpa4-234-197) were grouped as soft-cooking. These soft-cooking genotypes could be available as genetic stock to confirm this attribute or reanalysis by breeders
Patient Outcomes in the management of Finger Fractures and Joint Injuries (the OFFJI study) -a Prospective Cohort Clinical Study
No full textA prospective cohort study of patients with finger injuries found that patient reported outcomes showed improvement over 6 months but did not return to pre-injury levels. The Patient Evaluation Measure was the most sensitive of the outcome measures used
A versatile fluorescence polarization-based deubiquitination assay using an isopeptide bond substrate mimetic (IsoMim)
Get PDFDeubiquitinases (DUBs) play a critical role in the regulation of various cellular processes, such as protein homeostasis and signaling, rendering them attractive drug targets. However, the generation of reagents for measuring DUB activity typically involves several steps and is not straightforward. Here, we report the development and characterization of a novel fluorescent polarization assay using an isopeptide bond substrate mimetic (IsoMim) that can be made recombinantly in high yields. The IsoMim assay was able to discern the differential activity of ubiquitin-specific protease family members (USP4, USP15, USP11, and USP2), the ubiquitin C-terminal hydrolase UCHL3, and the Machado-Joseph Domain deubiquitinase JOSD2. A competition assay format of the assay was developed that discerned differences between the close paralogues USP15, USP4, and USP11 in interacting with mono-ubiquitin, the isopeptide mimetic ubiquitin-GGG, and the C-terminal truncation variant ubiquitin (1–74). Moreover, dose–response curves and associated pIC50 values using the broad-spectrum inhibitor PR-619 confirmed differential inhibition in the low μM range for four tested DUBs. The successful discrimination of DUB activity and inhibition and the easily scalable generation of the substrate make the IsoMim assay method applicable for high-throughput screening (HTS). This was ascertained in a “pseudo HTS screen” for USP4 inhibitors in which PR-619 was successfully identified as a “pseudo hit.” The developed assay provides a valuable tool for probing DUB activity and the identification and characterization of DUB inhibitors and has the potential to accelerate drug discovery efforts in this area
Artificial Intelligence's Potential in Zoo Animal Welfare
Get PDFThe thorough, objective, and regular assessment of animal welfare in zoos and aquariums is rapidly becoming an essential task for these institutions. Traditional welfare assessment methods are, however, difficult to scale to the number of species and individuals housed in zoos and aquariums. Automation, using artificial intelligence (AI) can provide solutions to these challenges. This literature review provides an overview of recent advances in this field, with a focus on studies relevant to zoo and aquarium animal welfare. AI in animal behavior and welfare monitoring, particularly in farm animals, has become increasingly commonplace in recent years. Recent studies have investigated AI's capability to identify and assess animal behavior in poultry, pigs, sheep, and cattle, including estrus prediction in cows; classification of animal vocalizations; and detection of potential welfare concerns, including early signs of lameness in cattle and sheep. In companion animals, AI has been used for facial recognition, vocalization-based emotion recognition, and behavioral monitoring. Laboratory animal behavior monitoring through AI tools has also rapidly increased since 2000. AI is increasingly used in zoos, including the identification of individual animals; monitoring of their movement within their enclosure; and quantifying behavior, including time spent using enrichment. The rapid increase in AI use in animal welfare shows promise in improving animal management and welfare in zoos and aquariums, through improved and more efficient monitoring and prediction
C∗-Categorical Prefactorization Algebras for Superselection Sectors and Topological Order
No full textThis paper presents a conceptual and efficient geometric framework to encode the algebraic structures on the category of superselection sectors of an algebraic quantum field theory on the n-dimensional lattice Z n. It is shown that, under the typical assumption of Haag duality, the monoidal C ∗ -categories of localized superselection sectors carry the structure of a locally constant prefactorization algebra over the category of cone-shaped subsets of Z n. Employing techniques from higher algebra, one extracts from this datum an underlying locally constant prefactorization algebra defined on open disks in the cylinder R 1 × S n−1 . While the sphere S n−1 arises geometrically as the angular coordinates of cones, the origin of the line R 1 is analytic and rooted in Haag duality. The usual braided (for n = 2) or symmetric (for n ≥ 3) monoidal C ∗ -categories of superselection sectors are recovered by removing a point of the sphere R 1 × (S n−1 \ pt) ∼= R n and using the equivalence between En-algebras and locally constant prefactorization algebras defined on open disks in R n. The non-trivial homotopy groups of spheres induce additional algebraic structures on these En-monoidal C ∗ -categories, which in the case of Z 2 is given by a braided monoidal self-equivalence arising geometrically as a kind of ‘holonomy’ around the circle S 1 . The locally constant prefactorization algebra structures discovered in this work generalize, under some mild geometric conditions, to other discrete spaces and thereby provide a clear link between the geometry of the localization regions and the algebraic structures on the category of superselection sectors
BestBETs for Vets
No full textEBVM-what is it really? Evidence-based Veterinary Medicine (EBVM) in a nutshell is about good clinical decision making and ensuring that what is decided for an animal or group of animals is as optimal as it can be for all stakeholders involved-part of a balanced, shared decision-making process. There are four important components in evidence-based decision making: the client, the vet professional, the animal/s, and the evidence. The first three are specific to the context of each case and without these viewpoints, circumstances or capabilities being considered, decisions made are more likely to not be enacted or potentially recommendations perceived not to 'work'. What about the 'evidence'? Traditionally the evidence in EBVM is represented by published research studies. This evidence differs, and does so primarily due to the type of research study design used, which influences the number and degree of biases typically found. However, 'evidence' can take other forms if the research-based evidence is not available, out of date or not appropriate to the context/case. In an ideal world, evidence would have been garnered from well designed, executed and reported research studies involving large numbers of animals that can provide us with definitive answers about the common questions we might have in practice (e.g. efficacy of a bovine respiratory disease vaccine in reducing incidence of pneumonia in dairy calves or which dairy fertility protocol results in the highest pregnancy rate in dairy cows treated with follicular cysts). Why can it be difficult to execute in practice? There are many factors that can have an influence on how easy this is to achieve in practice. The one that many vet professionals report is that it is difficult to keep up to date with Making evidence-based decision
The effectiveness of heat prevention plans in reducing heat-related mortality across Europe
No full textHeat-health warning systems and action plans, referred to as heat prevention plans (HPPs), are key public health interventions aimed at reducing heat-related mortality. Despite their importance, prior assessments of their effectiveness have yielded inconsistent results. The objective of this study is to systematically assess the effectiveness of heat prevention plans in reducing heat-related mortality risk across Europe.
We analysed daily mortality and mean temperature data from 102 locations in 14 European countries between 1990 and 2019. Using data from national experts, we identified the year of HPP implementation and categorised their development class. A three-stage analysis was conducted: (1) quasi-Poisson time series models were used to estimate location-specific warm-season exposure-response functions in three-year subperiods; (2) mixed-effect meta-regression models with multilevel longitudinal structures were employed to quantify changes in pooled exposure-response functions due to HPP implementation, adjusted for long-term trends in heat-related mortality risks; and (3) the heat-related excess mortality due to HPP was calculated by comparing factual (with HPP) and counterfactual (without HPP) scenarios. Estimates are reported by country, region, and HPP class.
HPP implementation was associated with a 25.2% [95% CI: 19.8% to 31.9%] reduction in excess deaths attributable to extreme heat, corresponding to 1.8 [95% CI: 1.3 to 2.4] avoided deaths annually per 100,000 inhabitants. This equates to an estimated 14,551 [95% CI: 10,118 to 19,072] total deaths avoided across all study locations following HPP implementation. No significant differences in HPP effectiveness were observed by European region or HPP class.
Our findings provide robust evidence that HPPs substantially reduce heat-related mortality across Europe, accounting for temporal changes and geographical differences in risks. These results emphasise the importance of monitoring and evaluating HPPs to enhance adaptation to a warming climate
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