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Rock-avalanche-driven glacier advances in a volcanic mountain revealed by cosmogenic exposure dating

Author Correction: Autophagic cell death restricts chromosomal instability during replicative crisis

Computational evaluation of the interactions of polycyclic aromatic hydrocarbons with a human receptor via DFT and molecular docking

Multimodal temporal feature fusion for teacher competency assessment and precision training resource recommendation

Abstract Assessing teacher competency in a reliable and multidimensional manner remains an open problem, largely because conventional evaluation instruments capture only a fraction of the behavioral repertoire that defines effective instruction. We tackle this challenge by developing an integrated framework that fuses heterogeneous classroom signals—video, audio, transcribed text, and physiological recordings—through modality-specific encoders coupled with a cross-modal attention mechanism. The attention module adaptively re-weights each data stream according to its diagnostic relevance for a given competency dimension, while a hierarchical temporal component jointly models short-term pedagogical adjustments and long-term professional growth trajectories. Competency scores are formulated as a continuous regression task (evaluated via RMSE and MAE) and simultaneously discretized into ordinal proficiency levels for classification-based evaluation (accuracy and F1-score), thereby addressing both assessment perspectives within a unified multi-task objective. A knowledge graph–enhanced recommendation engine then maps diagnosed competency gaps onto targeted training resources. Experiments conducted on multimodal recordings from 856 teachers across 15 schools demonstrate that our model reaches 0.834 classification accuracy and 0.312 RMSE, outperforming all baselines on each of the seven evaluation dimensions. The recommendation module attains 0.478 Precision@5, a 13.0% relative gain over the strongest knowledge-graph baseline. Ablation analyses confirm that every architectural component contributes measurably; removing temporal modeling alone reduces accuracy by 7.1 percentage points. Taken together, these results establish a closed-loop, interpretable pipeline from diagnostic assessment to actionable professional development pathways.

Distinct and combined effects of mental and physical fatigue on prospective time perception in basketball players

Public sentiments toward artificial intelligence in agriculture across the United States and United Kingdom

Abstract Artificial intelligence (AI) is rapidly expanding within agricultural systems, yet public attitudes toward its use remain poorly understood. We analyse single-word responses from public surveys in the United Kingdom ( N  = 1054) and the United States ( N  = 998) to quantify both sentiment polarity and emotional responses to agricultural AI. Using lexicon-based methods, we find that sentiment is relatively more negative in the United States, although the overall emotional structure is similar across both countries. Fear and anticipation emerge as the dominant emotions, indicating persistent ambivalence toward AI in agriculture. Cross-country differences are evident, with statistically significant higher levels of anger in the United States compared to the United Kingdom. Regression and marginal effect estimates show that attitudes toward science and technology are the most consistent predictors of both sentiment and emotional responses, significantly reducing negative emotions while increasing positive ones. Demographic factors play a secondary role, although age accounts for systematic variation, particularly in the United Kingdom. These findings suggest that public sentiments toward agricultural AI are primarily shaped by underlying orientations toward science and technology rather than socioeconomic characteristics. Understanding these dynamics in affective association is critical for designing governance and communication strategies that foster trust and support the responsible adoption of AI in agricultural systems.

Knowledge and attitudes of the community toward human mpox virus infection in, Oromia, Ethiopia: a community-based cross-sectional study

A multinational randomized clinical trial of an eye-tracking-based binocular amblyopia treatment in children aged 4–9 years

Ubiquitination of glycogen and metabolites in cells and tissues

Human haematopoietic stem cells remember inflammatory stress

Abstract Inflammation activates blood cells, contributing to ageing and malignancy 1–3 . Haematopoietic stem cells (HSCs) survive a lifetime of infection to sustain life-long haematopoiesis 1–9 , but how human HSCs respond and adapt to inflammatory stress is largely unknown. Here, to empirically understand this adaptation, we developed xenograft inflammation–recovery models and performed single-cell multiomics on xenografted human HSCs. Two transcriptionally and epigenetically distinct HSC subsets were identified with one, termed HSC inflammatory memory (HSC-iM), retaining a molecular memory of previous inflammatory treatments. The HSC-iM subset exhibited quiescence and restrained haematopoietic output. Molecularly, the HSC-iM program was enriched in HSCs from adult and paediatric samples across conditions ranging from COVID-19 recovery, sickle cell disease, ageing and clonal haematopoiesis, establishing both the validity of our xenograft models and the physiological relevance of HSC-iM. Clonal haematopoiesis mutations in HSC-iM attenuated the effects of inflammatory stress by promoting HSC activation and differentiation. Moreover, transmission of the pro-inflammatory HSC-iM transcriptional program to differentiated immune progeny was demonstrated in xenograft and physiological settings. Finally, HSC-iM program enrichment in circulating blood cells was associated with a heightened risk score for all-cause mortality in population cohort analyses, underscoring the clinical relevance of this newly identified HSC subset in characterizing heterogeneous health outcomes across a lifetime.

β-Arrestin condensates regulate G-protein-coupled receptor function

Revealing competitive interfacial reactions in high-energy Li–S batteries

Daily briefing: Mutation lets octopuses make proteins with precision

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‘This time, it’s the other way around’: how Indonesia is reclaiming the science of human history

LARES-2 satellite measures frame-dragging effect around the Earth

Predicting temporal stability and resilience from resistance and recovery

Protocol for a Delphi consensus study to identify priority characteristics of integrated care for individuals with severe mental illness and comorbid physical disorders in Europe

Introduction Individuals with severe mental illness (SMI) experience persistent and complex physical health needs that remain insufficiently addressed. While integrated care represents a promising solution, there is no consensus among stakeholders regarding what constitutes best-practice organizational models for this population. As part of the European Mental and Physical Health Initiative for People with Severe Mental Disorders (EU-MIND), this study aims to identify expert consensus on the key characteristics of integrated care models for individuals with SMI to support their sustainable implementation across Europe. Methods This study will use an online Delphi process, with up to three rounds, to engage stakeholders from six European countries (Denmark, Finland, France, Italy, Poland, and Sweden). Participants will include people living with SMI, their relatives, health and care professionals, public decision-makers and institutional actors with relevant experience related to the research topic. A minimum sample size of 33 participants per country will be targeted, with the aim of ensuring balanced representation across the different categories of participants. They will be asked to rate the importance of potential key characteristics of integrated care models using Likert scales. A characteristic will be considered to have reached consensus if more than 70% of the respondents agree on its degree of importance. This study complies with the Delphistar reporting guidelines for Delphi studies and has received ethical approval from the Aix-Marseille University Ethics Committee and the Swedish Ethical Review Authority. Discussion This study will provide expert-based guidance on the core characteristics of integrated care for individuals living with SMI. By capturing diverse stakeholder perspectives across countries and healthcare systems, it will help define shared priorities and inform future service design, implementation and policy, supporting sustainable and context-sensitive care development in Europe.

Specific expansion of motor cortical projections in a singing mouse

Theoretical assessment design at a South African school of nursing: A multimethod qualitative exploration

Introduction Theoretical assessment design is crucial in nursing education, ensuring students develop cognitive and problem-solving skills for clinical practice. However, misalignment with learning outcomes and inconsistent cognitive level distribution remain complex issues. Methods and findings This multimethod qualitative study explored theoretical assessment design in a South African nursing school through in-depth interviews with nurse educators and a document review of moderators’ reports. Stratified purposive sampling ensured diverse representation across National Qualifications Framework Levels 5–8. Data saturation was reached after nine interviews, analysed using Creswell and Creswell’s six-step thematic framework. The document review analysed 70 moderation reports (22 internal and 48 external) from 2015 to 2019, focusing on feedback related to final theoretical assessments. Content analysis, following Krippendorff’s framework, was used to identify themes and patterns. Findings revealed an overemphasis on lower-order cognitive skills (Bloom’s taxonomy), inconsistent question distribution, and misalignment with national qualification standards. Educators acknowledged these issues but cited time constraints, inadequate training, and institutional pressures as contributing factors. Moderation reports confirmed assessment inconsistencies, emphasising the need for better alignment with constructive alignment principles. Triangulation of data highlighted a gap between perceived best practices and actual assessment quality, suggesting assessments do not fully support higher-order cognitive skill development. Conclusion To improve the validity and reliability of theoretical assessments, nursing programmes should prioritise training in assessment design, strengthen alignment with learning outcomes, and implement moderation strategies to address inconsistencies. These findings contribute to the broader discourse on improving assessment practices in nursing education globally.