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AI-Driven Transformations in Smart Buildings: A Review of Energy Efficiency and Sustainable Operations
No full textThis comprehensive review examines the transformative impact of artificial intelligence (AI) technologies on smart buildings and real estate management through a systematic narrative analysis of peer-reviewed articles and industry reports published between 2016-2024. Using a thematic synthesis approach across five primary domains, property valuation, predictive maintenance, tenant screening, marketing and sales, and smart building operations, we investigated AI's role in enhancing energy efficiency and sustainable operations. Key findings reveal that AI-powered systems achieve remarkable performance improvements: valuation accuracy increased from 70% to 95%, operational costs reduced by 17.6%, maintenance costs decreased by 13.2%, and energy savings reached 14% while maintaining 91% resident satisfaction. Our analysis identifies critical implementation barriers including data quality challenges, algorithmic bias risks, substantial upfront investments, and skills gaps. The review reveals that ensemble machine learning techniques achieve 85-100% accuracy in energy forecasting, while IoT-integrated predictive maintenance systems extend equipment lifespan by 25-30%. Despite promising benefits, ethical considerations around privacy, transparency, and fairness demand immediate attention. This review contributes novel insights into the economic-environmental nexus of AI adoption, demonstrating that sustainable building operations and profitability are not mutually exclusive but rather synergistic outcomes of intelligent system integration
Evaluating a virtual community of practice for recurrent care practitioners
Full text linkThe Supporting Parents Community of Practice supports practitioners and service leads working with birth mothers who have had children removed from their care, with a particular focus on supporting their positive sexual and reproductive health. Its evaluation comprised a mixed methods approach via a baseline survey, follow-up survey and interviews with practitioners. Overall, the CoP was valued by members, their levels of knowledge/skills and confidence in a range of areas and working practices increased, and the CoP supported members’ professional development and service development. The evaluation also identified challenges experienced in establishing and sustaining this innovative CoP and made recommendations to address these
Utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting: A multicentre survey
Full text linkRationale and objective
The purpose of this study was to investigate the utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting.
Materials and methods
A national survey was conducted across healthcare facilities nationwide in Ghana. The survey included questions relating to facility demographic information, MRI scanner work functions, and utility of MRI for clinical and research purposes.
Results
Most MRI scanners were private-owned, with General Electric being the dominating scanner brand, and a high prevalence of 1.5 T MRI scanners. Most facilities have 1 – 4 radiologists and radiographers, and brain MRI prices were higher in private facilities compared to the public facilities. Most (84.6 %) facilities indicated the availability of PACS; however, none indicated the integration of artificial intelligence into their clinical workflow. Average weekly availability of MRI services was 7 days in most facilities (53.8 %). Most (69.2 %) facilities provide a 24-hour window to offer brain MRI services. A total of 1 – 4 brain MRI cases were performed daily. Only 4 (30.8 %) facilities indicated the availability of brain MRI protocol for research purposes. For clinical purposes, most facilities indicated their acquisition of 3D-T1-weighted (11 facilities), diffusion tensor imaging (DTI) (7 facilities), and perfusion imaging (7 facilities). Conversely, fMRI (3 facilities), 1H-MRS (2 facilities), and DTI (1 facility) were in use for research purposes. Approximately 85 % of respondents indicated that they 'rarely' or 'never' utilize the scanners for research purposes.
Conclusion
The wide variation in the utility of MRI for clinical and research purposes highlights some opportunities for enhanced accessibility and potential recruitment of study participants, including challenges related to standardization in a potential multicentre brain MRI research
Briefing document on Theological Education following the Working Class Clergy Wellbeing Project
Full text linkAs part of wider Living Ministry longitudinal research into clergy wellbeing, Ministry Division commissioned a satellite project into the wellbeing of working-class clergy in October 2022. The researchers are Dr Alex Fry (Bournemouth University), Dr Sharon Jagger (York St. John University) and Becky Tyndall (Durham University). Following interviews with 50 working-class clergy and 4 working groups, the report Let Justice Roll Down Like Waters was published in October 2023. This briefing document additionally explores the experiences of working class ordinands in the context of theological education and training with the purpose of supporting conversations around breaking down a classed environment and culture
Could tactical voting block Reform in future elections? Lessons from the Caerphilly byelection
No full textEarly prediction of Alzheimer’s disease using machine learning algorithm: A convolutional neural network approach
Full text linkAlzheimer’s disease (AD) is a progressive neurodegenerative disorder that severely impacts memory and cognitive functions. Early diagnosis remains crucial for timely intervention and care. This research aims to explore the use of artificial intelligence, specifically deep learning, for the early prediction and Classification of AD using structural magnetic resonance imaging (MRI) images. A dataset comprising approximately 44,000 brain MRI images with four diagnostic classes (mild, moderate, severe, and very severe dementia) was used to train and evaluate multiple convolutional neural network (CNN) architectures. Three deep learning models were developed and tested: A custom CNN built from scratch, a spatial-channel convolutional attention network (SCCAN), and a pre-trained Visual Geometry Group VGG16 model using transfer learning. The methodology included extensive preprocessing, data augmentation, normalization, and a train–validation–test split to ensure robust performance. Evaluation metrics such as accuracy, precision, recall, F1-score, and confusion matrices were used to assess classification efficacy. Among the models tested, the Visual Geometry Group VGG16 model achieved the highest classification accuracy, closely followed by the SCCAN, while the custom CNN demonstrated competitive performance with fewer layers. Grad-CAM visualizations were integrated to provide insight into model decision-making, enhancing interpretability. The results confirm the
effectiveness of deep learning in classifying early AD stages with high accuracy and support its integration into clinical diagnostic tools. However, the study also identifies limitations, including dataset diversity, class imbalance, and generalizability across diverse populations. Future research should consider using larger, multi-center datasets (including positron emission tomography and electroencephalography modalities). This project demonstrates that deep learning can offer reliable, scalable, and interpretable solutions for the early detection of AD, potentially transforming the diagnostic pathway and enabling earlier therapeutic interventions
Review of: Bonsall, Jane. Women and Magic in Medieval Romance: Genre, Intertextuality and Power. Studies in Medieval Romance. Woodbridge: D.S. Brewer, 2025.
No full textFirst woman archbishop of Canterbury can’t preside over communion in hundreds of churches
No full text‘That Profession and Habit that None Other Be of Within this Realm’: The Battel Hall Retable, Visual Culture and Intersections of Community Identity in a Late Medieval English Convent
Full text linkThe Battel Hall Retable – created around the late fourteenth to early fifteenth century and once belonging to the Dominican nuns of Dartford Priory – offers a rare glimpse into the visual lives of late medieval English nuns, inviting an insight into the intersections of communal identities for these women religious. This article builds on scholarship that has predominantly addressed Dartford's textual history, and of the piety and experiences within female monastic communities more widely, by exploring the intersections of English, female and Dominican spiritual identities for the community within, reflected by and provoked by this visual culture. It argues that the iconography, the specific portrayal of the figures and the potential positioning of the altarpiece speak to the engagement of these women with key facets of their identities, partially forming and enhancing a community identity that enabled them to withstand the Dissolution of the Monasteries
Expanding Descriptions of Autistic Rituals and Routines: A Co‐Produced Update
Full text linkDescriptions of rituals and routines inform autism assessment and diagnosis and remain influential when determining what being autistic means. Currently they present autistic characteristics as problematic. Examples slowly catch‐up with research that shows their personal appearances and meanings. We explored what happens when descriptions of autistic rituals and routines are co‐authored by autistic people. In this qualitative participatory study in the UK, 12 autistic adults contributed via interviews, written exchanges, and data analysis/writing sessions. We identified five themes using codebook thematic analysis: (1) ways of talking about rituals and routines; (2) meanings; (3) visibility; (4) what makes a ritual or routine autistic; and (5) when rituals and routines become detrimental. Rituals were frequently hidden. They had superstitious qualities that achieved a subjective sense of things being ‘OK’. They were behaviours, repetitive thoughts, and mental checks. Whilst there were both positive and negative impacts of performing rituals and routines, it was reliability, necessity, and devotion to them that characterised them as autistic behaviours. There is an important re‐narration of the ‘inflexibility’ or ‘rigidity’ of autistic repetitive behaviours when authored by autistic people, which appreciates the demands of navigating neurotypical‐default environments. Autistic adults emphasised a heavily‐tipped scale in the direction of valuing rituals and routines over censoring them