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The role of clinical vigilance and awareness in Scottish undergraduate mental health nursing students’ formation of confidence and knowledge in novel psychoactive substance-related healthcare treatment
Get PDFNovel psychoactive substances (NPSs) present a significant challenge to healthcare professionals working in Scotland. An area that has not previously been researched is student nurses’ feelings of knowledge and confidence in relation to NPS. This study aimed to provide data on this topic. An evidence-based presentation on NPS was produced. Five undergraduate mental health nursing students at a Scottish university were recruited as participants. They completed identical quantitative questionnaires assessing perceived levels of knowledge and confidence surrounding NPS pre- and postwatching the presentation. A focus group followed where the participants were asked how their perceived levels related to feelings of competence. The results showed that participants valued knowledge on clinical vigilance and awareness (CVA) over other themes measured, with it appearing to act as a lens by which to understand NPS-related phenomena observed in practice. These findings are explored in relation to the concepts of the theory–practice gap and the null curriculum. The author argues that knowledge pertaining to CVA may play a crucial role in helping to resolve the theory–practice gap in the context of NPS by facilitating nursing student understanding of the relative salience of knowledge and skills developed in other clinical contexts to this area of working, with this also acting as a vehicle by which NPS-relevant knowledge may be transferred from its place in the null and hidden curricula to that of the explicit curriculum. CVA is also considered alongside Rhodes and Lancaster's concept of evidence making and Race's idea of emergent causality, with the author arguing that CVA may help facilitate student nurses’ orientation toward attitudes consistent with the former and avoid problematization (in the Foucauldian sense) of relevant service users aligning to the latter
Systematic review and synthesis without <i>meta</i>-analysis (SWiM) reveals lack of clinical studies and weak preclinical evidence for interaction between glucose regulating drugs and environmental contaminant exposure
Get PDFEnvironmental chemical exposure is associated with T2D incidence and may underly some of the large observed variation in therapeutic responses. Clinical and applicable preclinical studies could help reveal whether environmental chemicals interact with the action of drugs used for glucose management. We systematically searched for studies testing the interaction between environmental contaminants and T2D drug action on glucose regulation outcomes. We found no clinical studies that examined chemical exposure interaction with T2D drug action. Nine of 458 papers were eligible, all of which were preclinical. Four contained in vivo studies, four contained in vitro work and one contained both approaches. Bisphenols were the main focus (n = 4). Inhaled particulates (PM2.5), polychlorinated biphenyls (PCBs), cadmium, arsenic, and per-and-poly-fluorinated-alkalated substances (PFAS) were each examined once. Metformin and rosiglitazone were the most frequently examined drugs (n = 4). Exendin-4 was investigated twice and glibenclamide once. Lack of study design comparability precluded meta-analysis. Instead, we calculated effect sizes and differences in outcome values (mean ± 95 % CI) for synthesis without meta-analysis (SWiM). Five studies reported impairment of drug action. Our analysis shows support for this conclusion was only present in two papers. Small sample sizes, short duration exposures, unrealistic chemical levels, lack of full factorial analysis and absence of testing in suitable T2D models restrict the applicability of the current, limited preclinical evidence for translation to clinical practice. The potential for chemical exposure to impact T2D medication effects on glucose control needs to be addressed with dedicated clinical studies in patients with T2D
Moving beyond tinkering round the edges:a systematic review of the role of the mentor in the assessment of nursing students in practice.
Get PDFAimTo analyse the literature from the introduction of Project 2000, providing insight into the evolution of the role of the mentor and the understanding of assessment in practice, highlighting areas for development.BackgroundThe challenges of assessment in practice have been the subject of much research, but none taking a historical perspective of the UK experience.DesignThe following databases were searched from 1990-2024; CINAHL+, PubMed, APA PsycArticles, SCOPUS, Web of Science and Google Scholar.Review MethodsFirst level screening of titles and abstracts was undertaken by 3 reviewers (n=7888). Second level screening on full text articles (n=145) identified 33 articles for inclusion. A rerun from 2022-2024 produced 3 more articles for inclusion. Quality appraisal excluded 6 articles, leaving 30 articles for inclusion in the review.ResultsArticles were categorised into pre- and post-introduction of the NMC standards and codes identified from findings. Themes and sub-themes were identified, with four factors emerging as integral to effective assessment in practice. Lack of a clear, shared definition of competence is reflected in confusing documentation. Time to undertake assessments and trusted support were also highlighted.ConclusionsWhile standards (NMC, 2008) brought about important changes, this review has highlighted the need for an agreed definition of competence to guide the development of appropriate assessment documentation. Research exploring the benefits in building trusting relationships through the tripartite assessment process is also needed.LimitationsOnly views of UK assessors were considered, while timespan and heterogeneity of data may influence the quality and generalisability of findings
Vigilance towards AI voices can be nudged through a change in 'MINDSET'
Get PDFAI-assisted technology is used to create synthetic voices that are highly naturalistic, making it difficult for listeners to distinguish between real and synthetic speech. While listeners often show a bias towards classifying these voices as human, this effect is even stronger when the voices use underrepresented regional or non-standard dialects—presumably because listeners are not used to such varieties being represented by speech technology. This MINDSET—Minority, Indigenous, Non-standard, and Dialect-Shaped Expectations of Technology—could leave some language communities more at risk of AI-voice based deception. To address this, the current study tested whether simple informational nudges could shift listeners’ default assumptions away from ‘Human’ and increase their vigilance towards categorizing voices as ‘AI’. Experiment 1 (N = 150) investigated whether nudges outlining AI’s ability to produce (Scottish) accents and dialects would affect human categorization responses. The results demonstrated a significant reduction in ‘Human’ responses for a nudge outlining AI’s capabilities at authentically producing these varieties. In Experiment 2 (N = 150), a vigilance-based nudge warning about the risks of AI deception was tested alone and in combination with the capability message. Only the nudge containing the capability-based information had a measurable effect, suggesting that updating expectations about what AI can convincingly reproduce is more effective than simply warning listeners to be cautious. These findings have practical applications for cybersecurity, fraud prevention, and public awareness campaigns. As AI-generated voices become increasingly used in scams, deception and misinformation, informational nudges which update expectations about AI’s linguistic capabilities may offer a low-cost, scalable way to increase vigilance—particularly in language communities historically marginalized or excluded from speech technology systems
Sewage sludge management in small tropical island communities:towards building a methodological framework for Mauritius
Get PDFThe rising rate of economic development and improved standard of living in small island states around the globe has led to an increasing rate of wastewater generation. Moreover, the current global push towards a sustainable environment requires wastewater regulators and managers to effectively manage wastewater and its by-products, sludge. This study aimed at establishing a methodological framework for the management of sewage sludge in small island economies using Mauritius as a case study. The framework constituted three elements, namely, inventory analysis, observational analysis, expert analysis, and stakeholder analysis. Most of the responses obtained from both technical and scientific experts, together with the compositional analytical results, practically led towards the selection of land application for sludge management. This approach is believed to be accompanied by ways to make biofertilizer acceptable to the public. This paper provides a practical framework for managing sewage sludge in small island states, where land availability for landfilling and manpower for technical sludge management options pose a big challenge. By using Mauritius as an example, it offers valuable insights and actionable recommendations for other small island nations facing similar challenges. The proposed management framework provides a balanced and feasible approach to addressing environmental, economic, and social concerns
From waste to wonder:the ultrasonic-enzyme-fermentation process transforms virgin coconut oil press cake into a food ingredient
Get PDFVirgin coconut oil press cake (VCOPC), a protein and fiber rich byproduct of coconut oil extraction, remains underutilized despite its nutritional potential. In this study, we developed a continuous bioprocessing strategy that integrates ultrasonication, enzyme-assisted hydrolysis, and lactic acid bacteria fermentation to transform VCOPC into a food ingredient with enhanced nutritional and functional properties. The ultrasonication process achieved a 63% solubilization of the press cake under optimized conditions (1.62 bar, 95 min), it effectively broke down the rigid polysaccharide–protein–lipid matrix and reducing particle size from 2.5 µm to 0.35 µm. Enzymatic treatment markedly increased soluble protein content (up to 137 mg/g) and free amino groups (up to 11.8 mmol/g), while fermentation with L. acidophilus and L. rhamnosus resulted in a 3-log increase in bacterial growth. Functional assessment of the various ingredients obtained by this bioprocessing approach showed high solubility and foaming capacity due to superior interfacial activity. This study demonstrates the successful conversion of coconut by-products into a nutritionally enriched food ingredient with enhanced techno-functional properties. Ultrasonication contributed to the highest yield, while enzymatic and microbial processes delivered the desired biochemical transformations. Combining initial mechanical disruption with enzyme hydrolysis and fermentation represents an effective and sustainable pathway for by-products upcycling and fosters circular innovation within the tropical food economy.</p
Sewage sludge management in small tropical island communities:towards building a methodological framework for Mauritius
Get PDFThe rising rate of economic development and improved standard of living in small island states around the globe has led to an increasing rate of wastewater generation. Moreover, the current global push towards a sustainable environment requires wastewater regulators and managers to effectively manage wastewater and its by-products, sludge. This study aimed at establishing a methodological framework for the management of sewage sludge in small island economies using Mauritius as a case study. The framework constituted three elements, namely, inventory analysis, observational analysis, expert analysis, and stakeholder analysis. Most of the responses obtained from both technical and scientific experts, together with the compositional analytical results, practically led towards the selection of land application for sludge management. This approach is believed to be accompanied by ways to make biofertilizer acceptable to the public. This paper provides a practical framework for managing sewage sludge in small island states, where land availability for landfilling and manpower for technical sludge management options pose a big challenge. By using Mauritius as an example, it offers valuable insights and actionable recommendations for other small island nations facing similar challenges. The proposed management framework provides a balanced and feasible approach to addressing environmental, economic, and social concerns
The performance of modified asphalt mixtures with different lengths of glass fiber
Get PDFOne practical option for modifying an asphalt mixture's performance is to use additives. This will help the mixture perform better against the damaging effects of traffic, loads, and climatic variations. In this regard, glass fiber (GF) has drawn much interest because of its positive effect. Therefore, this paper attempts to study the effect of glass fiber length and content on the performance and strength of asphalt mixtures. It also aims to determine the optimum glass fiber content and the best glass fiber length of modified asphalt mixtures. An experimental program is carried out, which includes the Marshall test, volumetric properties, freeze-thaw splitting test, immersion Marshall test, and wheel tracking test to characterize related properties of glass fiber incorporated in asphalt mixtures. Seven different percentages (0, 0.25, 0.5, 0.75, 1, 1.25, and 1.5) of glass fiber by total weight of aggregates in three various lengths are used to design 19 asphalt mixtures. Based on the results obtained, the performance of the asphalt mixture was enhanced remarkably after adding glass fiber. The use of various lengths of glass fiber led to a better-quality asphalt mixture in terms of volumetric properties, moisture damage resistance, and permanent deformation resistance. Specifically, asphalt mixtures made with (0.5%) glass fiber illustrated the highest quality, and adding (20 mm) length of glass fiber was better than (10 mm and 30 mm) glass fiber lengths. The results also show that adding (10 mm and 30 mm) lengths of glass fiber can improve the resistance of asphalt mixtures to water damage and permanent deformation compared with the control mixture (M0). The findings indicate the applicability of 20 mm glass fiber length in asphalt mixtures to achieve better resistance against moisture and reduce the chance of irreparable permanent deformation under growing traffic loads and hot climate changes. Although the inclusion of glass fiber in asphalt mixtures led to a modest increase (6%) in overall cost, the effective improvement in performance and extension of the service life of the asphalt pavement constitute a convincing argument for this approach, making it an attractive option. Finally, it was concluded that a higher amount of glass fiber (i.e., > 0.5%) and a length greater than (20 mm) could diminish the positive effect of glass fiber to improve the properties of glass fiber asphalt mixtures
Asynchronous deep reinforcement learning for semantic communication and digital-twin deployment in transportation networks
Get PDFThe dynamically evolving and technologically-driven hybrid landscape of transportation networks integrated with advanced edge computing capabilities has demonstrated efficient communication and computation techniques to guarantee robust quality of services (QoS) to vehicles. However, conventional communication systems in the Internet of Vehicles (IoV) still encounter challenges in providing meaningful low-latency communication and AI-assisted real-time synchronization on the edge. One reason is that it has exhausted the Shannon limit by utilizing cellular, NOMA, and Wi-Fi technologies. Therefore, we present an integrated approach leveraging Semantic Communication (SC), and Digital Twin (DT) deployment to tackle the challenges caused by high-dimensional data exchanges and resource spectrum crunch leading to inevitable latency constraints. SC stimulates meaningful transmission of data to high-mobility vehicles by providing a relevant knowledge base (KB) and DT deployment. In this paper, we established the vehicular SC (VSC) model, and DT deployment strategy. We formulate a multi-objective optimization problem (MOP) to maximize the overall QoS of the system by jointly optimizing VSC and DT deployment. Compared to traditional deep-reinforcement learning (DRL) schemes, we propose a Digital Twin Semantic Sensing using the Multi-vehicle DRL (DTS2 -MVDL) algorithm which addresses the MOP and persistent issues of multi-dimensional, continuous, and discrete nature of the vehicular environment. Lastly, we employ age of Information (AoI), latency, and QoS as the performance metrics to determine the algorithmic efficiency
Understanding the image cues driving the switch from brightness to lightness responses in the Adelson checker-block illusion
Get PDFAdelson's checker-block illusion is an engaging demonstration of the difference between lightness and brightness. The illusory nature of the stimulus derives from participants’ experience of the discrepancy between perceived lightness of two test patches (A, B) despite their physical luminance being identical. The identical nature of the test patches becomes apparent when cues informing the viewer of the scene's illumination and 3D structure are removed. Here we explore which cues drive the transition from ‘brightness’ pixel-based responses to ‘lightness’ material-based responses. Participants (n = 123) viewed versions of the stimulus with various components deleted (top, left and right-sides, shadows, outline-edges) under four between-subjects scenarios: with lighting direction varied (from left or right) and with the scene orientation varied (upside-down or correctly oriented). Participants indicated the perceived difference between A and B by responding on a Likert scale. Generalised linear mixed effects models were used to estimate the strength of each cue in driving the change of responses from brightness towards lightness. The lightness responses were strongest for upright images illuminated from the top-left, with panels adjacent to the test patches present. The stimuli, responses and model fits are shared as a dataset that can be tested against existing models of lightness perception
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