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Exploring the perception and reality of professionalism in UK nursing
Get PDFFor the individual nurse, professionalism includes attributes such as ethical practice, accountability, empathy and a commitment to ongoing professional development. A lack of nursing professionalism can negatively affect public trust, patient satisfaction and healthcare outcomes. This article examines whether professionalism is a reality in UK nursing or simply a perception. The author argues that professionalism in UK nursing is generally supported by education, adherence to standards and ethical conduct. However, challenges such as workload pressures, staffing shortages and negative portrayals of nursing in the media can undermine both the perception and the practice of nursing professionalism. Addressing these challenges requires comprehensive strategies from policymakers, healthcare leaders and nurse educators. While professionalism in UK nursing is a reality, continuous efforts are needed to maintain standards, including from nurses themselves
Neon, for the Lonely: Exploring Gay Men's History and Well-Being through Memoir-Based Reality Reconstructions
Get PDFNeon, for the Lonely: Exploring Gay Men’s History and Well-Being through Memoir-Based Reality Reconstructions is both an adapted memoir and an exegesis that charts a PhD journey of self-empowerment, and healing through the lens of a queer individual's past. The memoir, set against the backdrop of 1990s gay men’s London, offers an exploration of the era's cultural complexities, history, memory and documents the genesis of a personal descent into addiction. The exegesis critically examines the transformative potential of such narratives. To do this I investigate the writing process used to produce the work, narrative development, influences, and narrative development
Correction to: Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter (Systems Science & Control Engineering, (2025), 13, 1, (2449156), 10.1080/21642583.2024.2449156)
Get PDFArticle title: Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter Authors: Rezoug, A., Iqbal, J., & Nemra, A. Journal:Systems Science & Control EngineeringBibliometrics: Volume 13, Number 01, pages 1–25 DOI:http://dx.doi.org/10.1080/21642583.2024.2449156 When this article was first published online, Figure 13, parts g and h, were misprinted. Wrong Figure 13: (Figure presented.) Correct Figure 13: (Figure presented.)
Ensemble Supervised Learning-based Approaches for Mobile Network Coverage and Quality Predictions in a University Setting
Get PDFThis research explores the application of predictive analytics through Machine Learning (ML) algorithms to enhance Mobile Network Key Performance Indicators (KPIs), specifically focusing on Reference Signal Received Power (RSRP) as coverage and Reference Signal Received Quality (RSRQ) as quality. Various regression and classification modelling techniques were applied to drive-test measurements collected around the University of Hull, utilizing supervised ML algorithms such as Decision Tree (DT), Logistic Regression (LogisticR), Random Forest (RF), Support Vector Machine/Regressor (SVM/SVR), Light Gradient Boosting Machine (LightGBM), K-Nearest Neighbour (KNN), Extra Trees (ET), Extreme Gradient Boosting (XGB), Multi-Layer Perceptron (MLP), Deep Neural Network (DNN), Gaussian Naïve Bayes (GNB), and Gradient Boosting (GB) to benchmark the performance of four Mobile Net-work Operators (MNOs)/Mobile Virtual Network Operators (MVNOs) at various locations around the University of Hull, with additional model validation conducted in Hull City Centre, Barton Upon Humber, and Newland as use cases.The Random Forest (RF) model emerged as the best-performing algorithm, achieving a Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) below 3.7, a Mean Absolute Percentage Error (MAPE) under 7.03, a Coefficient of Determination (R²) greater than 74%, a Receiver Operating Characteristic Area Under the Curve (ROC_AUC) above 93%, and an Accuracy exceeding 82%. Additionally, the ensemble learning (EL) model, which combined the strengths of RF, GB, ET, SVR, XGB, and LightGBM for regression, and LogisticR, SVM, MLP, GB, ET, and RF for classification, delivered an overall performance with RMSE and MAE below 4, R² above 72%, accuracy exceeding 81%, and ROC_AUC above 85%. This highlights the EL model’s ability to predict network coverage (RSRP) and quality (RSRQ) as excellent, good, fair, bad, or poor with high precision.This study demonstrates the uniqueness of integrating multiple KPIs (RSRP and RSRQ) and prediction techniques (regression and classification) within an Artificial Intelligence (AI)-driven solution, providing a robust framework for improving network performance, particularly in scenarios where data collection through drive testing is limited
Sustainable Pedagogy in Early Childhood and Beyond
No full textThe seminar will consider how adults and children are preparing to manage sustainability in the 21st Century. UNESCO (2017) reminds us of the urgency of the current planetary situation. Gunther and colleagues (2024) stress the need for children to have the capacity and ability to question and be critically open to acquiring new knowledge. Sustainable Pedagogy promotes a children’s rights-based philosophy led from practice
Innovative Pathways: Rethinking Higher Education Through Inclusion and Participation
Get PDFOpening paragraph:Higher education should be a space of opportunity for all, yet for many people, particularly those without formal qualifications, from disadvantaged backgrounds, or balancing work and caring responsibilities, it remains an unreachable goal. At the University of Hull, a pioneering programme is transforming this reality through inclusive and innovative educational practices
Domestic abuse in later life: A secondary analysis of the crime survey for England and Wales
Get PDFUntil recently, older victims – and perpetrators – of domestic abuse were largely absent from both research and policy, leaving a lacuna of empirical and theoretical understandings of abuse in later life. This article presents the findings from the first study to use Crime Survey for England and Wales data on older adults to explore prevalence and risk factors for domestic abuse against adults aged 60–74 years old and, separately, adults aged 16–59 years. We find that risk factors for abuse are similar across the life course. In particular, socio-economic disadvantage, poor health and disability, and victim sex are constant correlates for victimisation, regardless of age. However, there are some important differences in the risk factors for partner and non-partner abuse in later life. Consistent with previous research involving all ages, we found that women were significantly more likely to be victimised by a partner than men (almost three times more likely in our study). However, when looking at abuse by non-partner family members, there was no statistically significant difference between the risk of victimisation for men and women. In other words, partner abuse disproportionately affects older women, but men and women are equally at risk of non-partner abuse. We propose that a move towards life course theories for understanding domestic abuse is required
The Role of Syntactic and Semantic Cues in Preventing Temporary Illusions of Plausibility
Get PDFUnexpected words within a context elicit large N400 brain potentials. However, sometimes the N400 at an unexpected word is small when stereotypical agent and patient roles are reversed, such as at “arrested” in “the cop that the thief arrested.” In a study of 74 native German speakers, we demonstrate evidence that readers can avoid this so-called “N400 semantic illusion” if the verb is delayed with neutral information such as “that evening,” but are less able to do so if the delay contains cues that could further strengthen the canonical interpretation, such as “with handcuffs.” In doing so, we provide a conceptual replication of a relatively new finding and extend previous research by showing that the semantic content of the delay is important. Moreover, we demonstrate evidence that the effect of only the neutral delay increases as the experiment progresses. We propose an interpretation of these findings with reference to the Sentence Gestalt model [Rabovsky, M., Hansen, S. S., & McClelland, J. L. Modelling the N400 brain potential as change in a probabilistic representation of meaning. Nature Human Behaviour, 2, 693, 2018], which accounts for the initial illusion as resulting from uncertainty and an erroneous interpretation based on a strong semantic attractor. Two additional, novel contributions of the work are a demonstration that the illusion can be elicited in German, despite its explicit subject–object case marking, and an exploration of illusion effect among individual readers
DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification
Get PDFHyperspectral image classification (HSIC) presents significant challenges due to spectral redundancy and spatial discontinuity, both of which can negatively impact classification performance. To mitigate these issues, this work proposes the Differential Spatial-Spectral Transformer (DiffFormer), a novel framework designed to enhance feature discrimination and improve classification accuracy. At its core, DiffFormer incorporates a differential multi-head self-attention (DMHSA) mechanism, which accentuates subtle spectral-spatial variations by applying differential attention across neighboring patches. The architecture integrates spectral-spatial tokenization, utilizing 3D convolution-based patch embeddings, positional encoding, and a stack of transformer layers augmented with the SwiGLU activation function—a variant of the gated linear unit (GLU)—to enable efficient and expressive feature extraction. Additionally, a token-based classification head ensures robust representation learning, facilitating precise pixel-wise labeling. Extensive experiments on benchmark hyperspectral datasets demonstrate that DiffFormer consistently outperforms state-of-the-art (SOTA) methods in classification accuracy, computational efficiency, and generalizability. The source code is available at https://github.com/mahmad000/DiffFormer
Delirium prevention in hospices: Opportunities and limitations – A focused ethnography
Get PDFBackground: Delirium is common and distressing for hospice in-patients. Hospital-based research shows delirium may be prevented by targeting its risk factors. Many preventative strategies address patients’ fundamental care needs. However, there is little research regarding how interventions need to be tailored to the in-patient hospice setting. Aim: To explore the behaviours of hospice in-patient staff in relation to delirium prevention, and the influences that shape these behaviours. Design: Focused ethnography supported by behaviour change theory. Observation, semi-structured interviews and document review were conducted. Setting/participants: A total of 89 participants (multidisciplinary staff, volunteers, patients and relatives) at two UK in-patient hospice units. Results: Hospice clinicians engaged in many behaviours associated with prevention of delirium as part of person-centred fundamental care, without delirium prevention as an explicit aim. Carrying out essential care tasks was highly valued and supported by adequate staffing levels, multidisciplinary team engagement and role clarity. Patients’ reduced physical capability limited some delirium prevention behaviours, as did clinicians’ behavioural norms related to prioritising patient comfort. Delirium prevention was not embedded into routine assessment and care decision-making, despite its potential to reduce patient distress. Conclusions: The value placed on fundamental care in hospices supports delirium prevention behaviours but these require adaptation as patients become closer to death. There is a need to increase clinicians’ understanding of the potential for delirium prevention to reduce patient distress during illness progression; to support inclusion of delirium prevention in making decisions about care; and to embed routine review of delirium risk factors in practice