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Shifting notions of belonging: the impact of liberalisation, privatisation and globalisation on two generations in Assam, India
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Investigating the long-term legacies and impact of hosting a cultural event: an analysis of UK City of Culture on Derry/ Londonderry
No full textPenal policy reform at the micro-level: reflections on penal policy change in the criminalisation of grooming in Australia
No full textHybrid CNN–GRU–XGBoost framework for optimized coronary artery disease diagnosis and risk stratification
No full textCoronary artery disease (CAD) remains a leading driver of cardiovascular mortality, requiring diagnostic systems that deliver high discrimination, stability under class imbalance, and reproducible deployment. This work presents a hybrid pipeline that integrates convolutional encoders for localized feature interactions, gated recurrent units (GRUs) for conditional dependency modeling over ordered clinical attributes, and an extreme gradient-boosted tree classifier (XTree) for nonlinear decision refinement and feature-level attribution. The data pathway applies strict train-split isolation with source-aware quantile imputation, proximal denoising, robust trimmed standardization, stratified partitioning that preserves class and source distributions, and manifold-conformal minority augmentation to improve boundary coverage without leakage. Evaluation on the UCI Heart Disease cohort (Cleveland, Long Beach V, Switzerland, Hungary; p=14 attributes) used an 80/20 holdout and standard metrics. The proposed CNN–GRU–XTree attained 96.03% accuracy, 94.70% precision, 97.66% sensitivity, 96.17% F1, and 94.35% specificity. Relative to the strongest non-proposed baseline (CNN–LSTM–XTree: 95.63% accuracy, 94.70% precision, 96.90% sensitivity, 95.80% F1, 94.47% specificity), gains reached ＋0.40 percentage points (pp) in accuracy, ＋0.76 pp in sensitivity, and ＋0.37 pp in F1, with parity in precision and a negligible specificity delta (−0.12 pp). Against CNN–GRU–RF (95.24%/94.70%/96.15%/95.42%/94.18%), improvements were ＋0.79 pp accuracy, ＋1.51 pp sensitivity, ＋0.75 pp F1, and ＋0.17 pp specificity. Case-based simulations (600 min each) probed model behavior under clinically distinct conditions. In severe, unequivocal CAD, sensitivity remained ≥97% with specificity >93%; in low-risk asymptomatic profiles, specificity remained ≥95% with precision ≥93%; in borderline phenotypes with overlapping risk markers, F1 exceeded 94% while maintaining balanced error profiles.</p
A comparison of time-dependent Cloudy astrophysical code simulations with experimental X-ray spectra from keV laser-generated argon plasmas
No full textWe have generated strongly photoionized Ar plasmas in experiments designed to use primarily X-ray l-shell line emission generated from Ag foils irradiated by the VULCAN high-power laser at the UK Central Laser Facility. The principle of the experiment is that use of line emission rather than the usual sub-keV quasi-blackbody source allows keV radiation to play a more dominant role compared to softer X-rays and thus mimic the effect of a blackbody with a higher effective spectral temperature. Our aim is to reproduce in the laboratory the extreme photoionization conditions found in accretion-powered astrophysical sources. In this paper, we compare the experimental results on K-β X-ray Ar spectra with modelling using the time-dependent version of the Cloudy astrophysical code. The results indicate that photoionized laboratory plasmas can be successfully modelled with codes such as Cloudy that have been developed for application to astrophysical sources. Our comparison of simulation and experiment shows that the flux of sub-keV photons that photoionize the outer-shell electrons can have a significant effect, and that detailed measurements of the X-ray drive spectrum across all photon energy ranges are crucial for accurate modelling of experiments.<br/
Oral health interventions and their effectiveness for dependent older adults: a systematic review of outcomes and outcome measures used in clinical research
No full textObjectivesTo identify oral health outcomes and outcome measures reported in studies examining oral health interventions among dependent older adults, as an initial step in the development of a core outcome set (COS).DataIntervention studies aimed at improving oral health of dependent older adults aged ≥60 years, residing in care homes, or at home, were included. The quality of included studies was evaluated using the Cochrane risk-of-bias tool (RoB 2) and Risk of Bias In non-randomized Studies of Interventions (ROBINS-I).SourcesMedline and Embase via Ovid, Cochrane CENTRAL, and Web of Science, up to August 2025Study selection and resultsEighty-four studies were included. Interventions were primarily classified into four categories: caregiver training and education (n = 21), oral healthcare interventions (n = 25), health professionals’ interventions (n = 31) and other interventions (n = 7). The reported outcomes and outcome measures varied considerably across studies and can be broadly grouped into six domains: oral hygiene, dentition status, periodontal status, oral mucosal status, overall oral health, and other outcomes. The most reported outcome was oral hygiene, with the Plaque Index being the most frequently used measure, followed by the Gingival Index. Other commonly reported outcome measures include Decayed, Missing, and Filled Teeth/Surfaces (DMFT/S), salivary levels of bacterial pathogens, and the Oral Health Assessment Tool (OHAT).ConclusionsThe outcomes and outcome measures reported across studies evaluating oral health interventions in dependent older adults were highly heterogenous. There is limited high-quality evidence in this area, highlighting the need for further research with robust study designs. The development and adoption of a COS would be valuable towards improving evidence-based dentistry and quality of care for this population.Clinical SignificanceFindings highlight the need for a COS to guide future research and ensure that outcomes are standardised and relevant to all stakeholders, and enable robust conclusions to inform clinical practice.<br/
Reading processes in English-Chinese sight interpreting/translation tasks
No full textReading is essential during Sight Interpreting/Translation (SiT) and is found to directly affect SiT quality and performance. It is found that SiT consists of several stages: normal reading in the first reading pass, reformulation in the second, followed by error correction. Nonetheless, reading is so far used as an umbrella term in SiT studies with no finer descriptions. This study complements previous understanding of reading in SiT by investigating whether multiple processes of different natures are involved and whether there are characteristic reading patterns. Eleven participants conducted three unprepared English-Chinese (L2-L1) SiT tasks. By using a combination of fixation duration and saccade length and direction, our findings show that different processes are present in the so-called ‘reading’ in SiT. Moreover, reading is highly irregular throughout the task, with a forward saccade following another forward saccade around 30% of the time, while (forward-followed-by-backward) regressions and backward-followed-by-forward movements account for 25%.</p
