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The Presidents of the Institute of Wood Science
Get PDFThe Institute of Wood Science (IWSc) represented the interests and knowledge of wood scientists and wood technologists in the UK and beyond between 1955 and 2009 when it merged with the Institute of Materials, Minerals and Mining (IOM3). In that time 27 presidents served, from industry or academia, leading the IWSc and guiding decisions relating to education, communication and the award of professional qualifications. The broad history of the Institute has been documented in 30th- and 50th-anniversary reviews published in the IWSc Journal. However, the contribution of the presidents to the success of the institute, as well as their reputations in wood science, wood technology or industry, has not been recorded. Approaching the 70th anniversary of what is now the Wood Technology Group of IOM3, this paper reviews the circumstances under which the IWSc was created and examines the contribution of each of the presidents to the health and success of the institute
Opening the door to inclusion report 2024. Making the invisible visible: the inclusion of LGBTQ+ health needs and concerns within nursing and midwifery pre-registration programs
No full textBrain fog and spontaneous coronary artery dissection: a commentary
No full textThis invited commentary refers to ‘Cognitive and physical fatigue—the experience and consequences of ‘brain fog’ after spontaneous coronary artery dissection: a qualitative study’, by J. Weddell et al., https://doi.org/10.1093/eurjcn/zvae097
The RESIST Project Report. National and Transnational Reports on the Formation of Anti-Gender Politics
Get PDFThis Report is focused on mapping anti-gender discourses in media and parliamentary debates across five case studies: the European Parliament, UK, Poland, Switzerland and Hungary. Overall, the research found an animated anti-gender political landscape characterised by ideological agitation and political opportunism, pronounced fixations and a fluid focus on often interchangeable targets and issues. There are clear continuities in the targeting of equality, and gender and sexual diversity, however these intersect with, and are transformed by an emerging repertoire of discourses and practices. Findings demonstrate that to understand anti-gender mobilisations, we need to pay attention to the transnational circulation, unconventional political alliances, strategies of controversy-generation, and competition for media attention – all of which promote anti-gender politics
Multi‐model deep learning system for screening human monkeypox using skin images
Get PDFPurposeHuman monkeypox (MPX) is a viral infection that transmits between individuals via direct contact with animals, bodily fluids, respiratory droplets, and contaminated objects like bedding. Traditional manual screening for the MPX infection is a time-consuming process prone to human error. Therefore, a computer-aided MPX screening approach utilizing skin lesion images to enhance clinical performance and alleviate the workload of healthcare providers is needed. The primary objective of this work is to devise an expert system that accurately classifies MPX images for the automatic detection of MPX subjects.MethodsThis work presents a multi-modal deep learning system through the fusion of convolutional neural network (CNN) and machine learning algorithms, which effectively and autonomously detect MPX-infected subjects using skin lesion images. The proposed framework, termed MPXCN-Net is developed by fusing deep features of three pre-trained CNNs: MobileNetV2, DarkNet19, and ResNet18. Three classifiers—K-nearest neighbour, support vector machine (SVM), and ensemble classifier—with various kernel functions, are used to identify infected patients. To validate the efficacy of our proposed system, we employ a publicly accessible MPX skin lesion dataset.ResultsBy amalgamating features extracted from all three CNNs and utilizing the medium Gaussian kernel of the SVM classifier, our proposed system achieves an outstanding average classification accuracy of 90.4%.ConclusionsDeveloped MPXCN-Net is suitable for testing with a large diversified dataset before being used in clinical settings
Mapping the landscape: surf therapy program delivery
Get PDFSurf therapy is a structured intervention which utilizes surfing as a vehicle to achieve therapeutic benefit (International Surf Therapy Organization [ISTO], 2019). Surf therapy is presently delivered internationally within a diverse array of contexts and populations. Despite the publication of many internal evaluation studies, little research has examined themes common to the process of surf therapy across programs. The present study recruited a sample of ISTO-affiliated surf therapy programs (n = 33) to engage with an online survey, Mapping the Stoke, examining core aspects of surf therapy structure and process internationally. Findings indicated both similarities across current program delivery internationally, with examples of primary similarities including target age (adolescents and young adults) and population (mental health), recruitment (self-referral), and structure (group sessions), geographic delivery (major cities) and challenges (funding). Areas of greater diversity included support staff (roles/qualifications), therapeutic aims, measures (outcome) and therapeutic structures. The present study outlines concrete structures and processes which appear integral to the delivery of surf therapy across cultures
Prioritizing humans: HRD’s vital role in AI adoption for workplace success
No full textAbstract unavailable
Effects of catchment land use on temperate mangrove forests
Get PDFHuman land use changes are threatening the integrity and health of coastal ecosystems worldwide. Intensified land use for anthropogenic purposes increases sedimentation rates, pollutants, and nutrient concentrations into adjacent coastal areas, often with detrimental effects on marine life and ecosystem functioning. However, how these factors interact to influence ecosystem health in mangrove forests is poorly understood. This study investigates the effects of catchment human land use on mangrove forest architecture and sedimentary attributes at a landscape-scale. Thirty sites were selected along a gradient of human land use within a narrow latitudinal range, to minimise the effects of varying climatic conditions. Land use was quantified using spatial analysis tools with existing land use databases (LCDB5). Twenty-six forest architectural and sedimentary variables were collected from each site. The results revealed a significant effect of human land use on ten out of 26 environmental variables.Eutrophication, characterised by changes in redox potential, pH, and sediment nutrient concentrations, was strongly associated with increasing human land use. The δ15N values of sediments and leaves also indicated increased anthropogenic nitrogen input. Furthermore, the study identified a positive correlation between human land use and tree density, indicating that increased nutrient delivery from catchments contributes to enhanced mangrove growth. Propagule and seedling densities were also positively correlated with human land use, suggesting potential recruitment success mechanisms. This research underpins the complex interactions between human land use and mangrove ecosystems, revealing changes in carbon dynamics, potential alterations in ecosystem services, and a need for holistic management approaches that consider the interconnectedness of species and their environment. These findings provide essential insights for regional ecosystem models, coastal management, and restoration strategies to address the impacts of human pressures on temperate mangrove forests, even in estuaries that may be relatively healthy
Examining the influence of customers, suppliers, and regulators on environmental practices of SMEs: Evidence from the United Arab Emirates
Get PDFThis study explores which stakeholders have more substantial influence than others and which combinations of stakeholders will have the greatest impact on small‐ and medium‐sized enterprises' environmental practices. A quantitative survey of 150 manager‐owners of SMEs found that while customers and suppliers significantly influence SMEs' sustainability behaviors, the demands and expectations set by regulatory bodies have a more substantial impact on how SMEs shape their environmental practices. Further, the presence of regulatory pressures does more than directly influence SMEs. Pressure from regulatory bodies also amplifies the effect of other forces on SMEs' environmental practices. In other words, when regulatory pressures exist, the impact of customer and supplier pressures on SMEs' sustainability behaviors becomes even more substantial. This synergistic effect underscores the pivotal role of regulatory pressures in shaping and enhancing SMEs' commitment to environmental sustainability
Probabilistic inference of material quantities and embodied carbon in building structures
Get PDFIn an effort to minimise the carbon footprint of building structures, a range of prediction tools and methods have been recently proposed, so to enable design practitioners evaluating how their design choices ultimately affect the carbon embodied in their designs. Such tools are most often targeted for use at the early stage of the design process, that is when exploration of alternative design options is usually undertaken, hence room for potential carbon reductions is greatest and at no extra cost of redesign. The overarching methodology behind existing tools predominantly relies on idealised models to characterise the structural system, usually employing closed-form design equations and/or numerical Finite Element to generate an inventory of material quantity data (that is ultimately required for embodied carbon estimates). Despite the very high level of complexity achieved by some models, the absence of any empirical reference with 'as-built' inventory data of material quantities leaves room for doubt on how accurate such models really are in capturing the complexities and inherent variability of the population of real building structures such models aim to represent. To bypass this limitation, a data-driven probabilistic graphical model is proposed here as alternative to existing approaches. A Bayesian Network was developed and tested as a proof of concept, trained on a dataset of 133 data-points of real building structures, leveraging on six design variables (at most) to fully characterize the entire design space of early design options. Despite the very small set of 'explanatory' design variables, the model exhibited a 73% accuracy (mean average absolute prediction error of 27%) when predicting the embodied carbon on a test sample of unseen real building structures. The study ultimately demonstrates the viability of adopting a probabilistic (data-driven) approach for such an inference task as an inherently robust alternative to data-blind models currently proposed in literature
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