19684 research outputs found
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Lessons learned:Teachers’ perceptions of incorporating police expertise into PSHE lessons
No full textThis article presents the findings of an initial evaluation of an innovative contribution by West Yorkshire Police (WYP) to Personal, Social, Health, and Economic (PSHE) teaching in schools within the region, namely the Police-Education (Pol-Ed) programme. Pol-Ed contributes police specific knowledge into the PSHE curriculum with the aim of keeping children safe from crime and victimisation. This article details the findings of a mixed-methods study using ten semi-structured interviews and an online questionnaire (n = 94) with PSHE teachers in West Yorkshire to explore their perceptions of the Pol-Ed programme. Additionally, we explore this type of expert-informed teacher resource to contribute to the school PSHE curriculum in a meaningful way. The quantitative results suggest that teachers perceived that Pol-Ed helps them teach children how to keep safe, understand risks and the law, and to make positive choices. The qualitative findings suggest that teachers perceived that Pol-Ed increases pupils’ awareness of risk of crime and victimisation, is locally relevant, builds trust and strengthens community relations, and supports teacher confidence, knowledge, and awareness. We conclude by offering some reflections on the potential of this type of programme to add value to the school curriculum in a range of ways by sharing of expertise across organisations.</p
<i>Untitled (Bog Flash)</i>
No full textUntitled (Bog Flash no.2), 2025Transparency, light box, 64cm x 46cm x 18cmUntitled (Bog Flash no.3), 2025Transparency, light box, 45cm x 30cm x 10cm<br/
Automated Scoliosis Diagnosis in Spinal Imaging:Laboratory Validation, Clinical Limitations, and Systematic Implementation Challenge Review
No full textTechnological advances in automated medical imaging diagnosis have created translation gaps between laboratory achievements and clinical implementation, with traditional manual Cobb angle measurement requiring considerable time with inevitable measurement errors. This review analyzes translation challenges in automated diagnosis systems using scoliosis assessment as a case study, examining 55 articles from 1948-2025 across three domains: Cobb angle measurement, classification, and segmentation. Despite research investment, fully automated approaches have not surpassed semi-automated performance in comparable validation studies. Within the 23 Cobb angle measurement studies, traditional methods outperform sophisticated deep learning systems with average error rates of 1.8° ± 0.4° MAD versus 4.2° ± 1.8° MAE, while validation degradation occurs with performance dropping from 95.28% to 85.9% when transitioning to real-world datasets. Nonstandard classification achieves high accuracy but lacks clinical utility, while standard systems struggle with automation, revealing a translation paradox where technical sophistication does not correlate with clinical adoptability. Main problems include testing method gaps, performance drops, different automation approaches, and cost issues. This review recommends standard testing methods and step-by-step clinical implementation to help these systems work in real clinics.</p
Detecting Narcissistic Personality Disorder (NPD):A Hybrid Regex and NLP based AI Approach with Phase-Aware Classification
No full textNarcissistic Personality Disorder (NPD) is considered one of the three malevolent personality traits comprising the ’Dark Triad’ alongside Machiavellianism and Psychopathy. Recent advances in computational psycholinguistics have demonstrated the potential of natural language processing (NLP) for the detection of personality disorders. To address the complexities of detecting nuanced linguistic patterns associated with NPD and abuse cycles, hybrid models that integrate rule-based and deep learning approaches have been proposed. Our approach synergises a transparent Regex based system for explicit markers with a fine-tuned, domain-adapted BERT model for implicit, contextual patterns. Crucially, we validated this hybrid system through a rigorous three-stage process, demonstrating a replicable methodology that successfully bridges the domain gap to real-world proxy data for toxic online discourse. This work provides a robust foundation for developing computational tools to aid researchers and clinicians in analysing textual data for patterns relevant to narcissistic dynamics.</p
Inclús Festival Internacional de Cine y Discapacidad de Barcelona:Freedom to Move
No full textWorld premiere of short documentary FREEDOM TO MOVE in international competition at Inclús 13th Festival Internacional de Cine y Discapacidad de Barcelona
<i>This centre holds and spreads</i>
No full textAn installation consisting of the following works.Untitled (Heather and Dam no.1), 2025. Giclée print (91cm x 122cm), wood, rocks, giclée print, polaroid. Overall dimensions: 350cm x 400cm x 130cm Untitled (Heather and Dam no.2), 2025. Giclée print (91cm x 122cm), wood, rock, dried moss, silver gelatin print (18cm x 12cm) Overall dimensions: 80cm x 150cm x 71cmUntitled (Heather and Dam no.3), 2025. Giclée print (91cm x 122cm), wood, rocks. Overall dimensions: 80cm x 150cm x 81cm<br/
Nurse Practitioners’ Practice Patterns in Primary Care in Finland:A Descriptive Qualitative Study
No full textHealthcare demands continue to increase across the globe, Advanced Practice Nurses (APNs) including Nurse Practitioners (NPs) are recognised as a valuable workforce that can increase access and improve the quality of care. However, NPs are underrepresented in Finland. This study explored Finnish NPs’ practice patterns and identified the common visit types to NP clinics in primary care. This descriptive qualitative study is part of a multiple-method and action research project that aims to develop and evaluate advanced practice nursing models in primary care within a wellbeing services county of Western Finland. Responses to open-ended questions and interview data from 16 NPs working in primary care were analysed using inductive content analysis. The findings highlight key aspects of NPs’ work, including the types of patients they care for—those with both acute and longterm health needs—and the core elements of their practice, such as conducting health assessments, providing counselling and coaching, engaging in collaborative care, and prescribing medications. The analysis also revealed persistent ambiguity surrounding certain aspects of NP practice. Overall, the findings indicate that NPs in Finland utilise a wide range of knowledge and skills to care for patients presenting with acute and long-term health problems
Analyzing the impact of weather conditions on energy efficiency in residential buildings using machine learning techniques with explainable artificial intelligence
No full textThis study utilizes advanced machine learning (ML) algorithms to assess the influence of external weather-related factors on the energy efficiency (EE) of residential buildings. Two deep neural network (DNN) models were developed: a standard DNN and an enhanced one incorporating residual layers and attention mechanisms. The models were trained using a dataset comprising historical meteorological data and energy performance data from residential homes in York, UK. The investigation indicated that energy consumption is substantially influenced by meteorological factors including temperature (denoted as heating degree days (HDD) and cooling degree days (CDD)), humidity, wind velocity, and sun radiation. The random forest model surpassed previous models, attaining root mean square error (RMSE) of 0.0819 and a (Formula presented.) score of 1.0000, underscoring its exceptional capacity to represent the intricate interactions between meteorological factors and energy usage.The advanced deep neural network demonstrated favourable outcomes with an RMSE of 4.12 and a (Formula presented.) of 0.878, underscoring the significance of employing complicated architectures to represent intricate relationships. The results underscore the need of integrating ML for EE forecasting and identify critical domains for enhancing household energy consumption. The study compared multiple ML models, highlighting their benefits and weaknesses for prediction accuracy and resilience. This is followed by the application of SHAP (SHapley Additive exPlanations) to interpret model outputs and obtain an understanding of the significance of these weather features.</p
Remote Digital Health Interventions to Support the Physical, Functional, or Psychological Rehabilitation of Adult Patients With Major Traumatic Injuries:Protocol for a Systematic Review of Randomized Controlled Trials
No full textBackground:The use of digital health (DH) interventions has increased over the past 2 decades, providing patients with alternative remote pathways for receiving health care services. Patients with major trauma frequently require long-term access to health care services to support their mental and physical health and their overall quality of life. DH interventions can help patients stay connected to rehabilitation services, thereby enhancing their health condition and helping them regain their independence, which will enable them to return to the workplace or regain a role in society. There is a need to explore existing evidence on the effectiveness of DH interventions for improving health-related outcomes in patients with major trauma.Objective:This review aims to identify DH interventions that support the physical, functional, or psychological rehabilitation of patients who have experienced major physical trauma.Methods:This review targets randomized controlled trials. Studies investigating DH interventions in adult patients with major traumatic physical injuries (end users of the interventions) are considered eligible for inclusion. Digital interventions that are delivered remotely and studies that report the impact of DH interventions on patients’ health-related outcomes will be included. The search will be limited to publications since 2000 and peer-reviewed journals. No language restrictions will be applied, and articles not written in English will be translated. The search will be conducted in MEDLINE, Embase, AMED, CINAHL Plus, and PsycInfo. Grey literature and bibliographies of included studies and relevant reviews will also be searched for potentially relevant articles. A minimum of two reviewers will independently screen retrieved references. Data extraction will be conducted by 1 reviewer and independently checked by another reviewer. Quality assessment of the included studies will be conducted using the Cochrane Risk of Bias 2 tool. Any disagreements arising at any stage of the review will be resolved through discussion or by consulting a third reviewer, if required. A meta-analysis will be performed where possible, and a descriptive analysis of the included studies will be reported.Results:As of January 2025, the systematic review is in the data extraction stage. Seven studies have been identified as eligible for inclusion. The findings are expected to be published in a peer-reviewed journal by December 2025.Conclusions:The review findings will help identify existing evidence regarding DH interventions used to support the physical, functional, or psychological rehabilitation needs of patients with major trauma. This would help guide practitioners and policy makers to implement effective interventions to better support patient outcomes. The evidence synthesized from this review will also identify existing gaps and direct future research.Trial Registration:PROSPERO CRD42023485748; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023485748International Registered Report Identifier (IRRID):DERR1-10.2196/6767
A grapeful discovery:Reservoir computing with wine beads
No full textIn this work, we introduce encapsulated wine beads as a novel, edible material for unconventional and neuromorphic computing. When encapsulated in alginate beads, wine, a complex mixture of proteins, organic acids, sugars, metal ions, and volatiles, exhibits nonlinear electrical behavior and memory effects governed by ox-redox processes. These responses show plasticity-like features, allowing programmable resistance states. The wine beads can be leveraged for computing, and to demonstrate this potential, the wine bead was used as a single-node reservoir for classification tasks. Our findings indicate that the resistance is programmable, exhibits a high degree of repeatability, and can be used for reservoir computing scenarios.</p
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