Artificial intelligence literacy in higher education and implications for nursing education: A scoping review.

Religion is a central aspect of many people's lives worldwide. While most research has concentrated on individual religiosity, less attention has been paid to the broader social and structural dimensions of religious affiliation, particularly how affiliation to minority religious groups influences mental health through experiences of discrimination, marginalisation, and unequal social, economic, and political position. We conducted a systematic review across four databases from inception to December 2024 of quantitative studies on mental health outcomes among religious minorities and differences acrossreligious groups. Findings were synthesised narratively and with vote counting. We also mapped mechanisms linking religious minority status to mental health. 152 quantitative studies were included, mostly cross-sectional with small convenience samples. More than half of studies focused on one religious minority group in a country without comparison to other groups (57%), limiting our understanding of inequalities between groups. Where investigated, religious minority groups consistently demonstrated worse mental health outcomes compared to majority groups. Risk, protective, and contextual factors contributing to the mental health of religious minorities were also mapped from included studies and inform the development of a conceptual framework. Our systematic review highlights the limited scope and quality of studies examining religious disparities in mental health. Building on the mechanisms mapped from the review, we propose a conceptual framework integrating existing evidence with broader literature to advance our understanding of religious affiliation as a social determinant of mental health.

A "Seesaw Effect" resolving the paradox in microzooplanktonic ciliate-environment interactions in the tropical Qinzhou Bay estuary-offshore continuum.

Midwifery practice in perinatal palliative care: A scoping review and conceptual framework.

A feast of knowledge: How AI-powered food councils can transform policymaking in the digital era

With the rapid integration of generative AI (GenAI) into higher education, concerns over cognitive offloading, overreliance, and diminished critical thinking underscore an urgent need to prioritize learning-to-learn (L2L) competencies. However, the lack of a clear and detailed conceptualization of L2L, a key 21st-century skill for lifelong learning, hinders interdisciplinary research and limits the development of informed, pedagogically sound AI applications. This paper presents a scoping review of L2L definitions within pedagogical and psychological literature, based on sources retrieved from ERIC, Scopus, and Web of Science. The review follows the PRISMA-ScR framework and identifies 21 relevant publications. We propose a novel three-layered framework organized by conceptual broadness: Dimensions (dispositions like cognitive and metacognitive skills), Processes (actionable activities such as self-regulation), and Tools (concrete strategies like retrieval practice), providing entry points for researchers from varying disciplines. We further highlight existing GenAI research efforts addressing these layers, outline current limitations, and propose directions for future exploration, with a focus on higher education. By unifying L2L theory with GenAI practice, this framework provides an actionable foundation for educational technologies in an AI-driven era. • Three-layer learning-to-learn (L2L) framework (Dimensions, Processes, Tools) to guide AI‑enhanced learning system design. • Synthesizes L2L definitions from 21 studies identified by a PRISMA-ScR review and offers actionable paradigms for teaching L2L, for example, using AI-supported systems. • Maps L2L components to GenAI application use cases in higher education. • Positions L2L as key to reducing GenAI overreliance and fostering learner agency.

Critical factors for sustainable perishable food supply chains: Insights from Malawi banana supply chain

Social and emotional learning in practice: An instructional case study of Scotland’s approach to address gender stereotypes and homophobia in upper primary schools

Barriers and facilitators to healthcare access for migrants in Morocco: A narrative review.

How does social health impact cognitive function and brain reserve? Findings from the SHARED Consortium.

Smart grid cyber-physical systems: Components, vulnerabilities, mitigations, opportunities, and conceptual framework

A Critical Perspective on the Dietary Guidelines for Americans 2025-2030: Methodological, Conceptual, and Communication Challenges.

Biochar is an increasingly studied material due to its remarkable structural versatility and multifunctionality, which make it suitable for applications ranging from environmental remediation to catalysis, agriculture, and advanced material synthesis. This review presents a comprehensive and structured analysis of the relationships between biochar synthesis parameters (e.g., feedstock type, pyrolysis conditions, activation strategy, and post-treatment) and the resulting physicochemical properties of the material, including porosity, surface area, functional groups, and surface charge. Particular attention is given to how these characteristics influence performance in key application fields, including pollutant adsorption, catalysis, bioenergy (e.g., hydrogen, and methane production), carbon-based nanomaterials, and soil improvement. The review highlights the complexity of the synthesis–structure–function relationships and emphasizes the importance of rational design approaches. By consolidating diverse experimental findings, this work aims to provide a conceptual and design-oriented framework for guiding the tailored design of biochar, offering qualitative predictive insights into how synthesis conditions and feedstock characteristics influence material properties and application-specific performance. • Intermediate pyrolysis enhances metal and hydrophilic organic adsorption. • Woody biomass boosts metal adsorption; sludges are best for lead removal. • Woody biomass at moderate temperature enhances anaerobic digestion. • Biochar can replace graphite in carbon nanomaterial synthesis. • Rational design links synthesis, structure, and application performance.

Evaluating tourism destination images: Integrating survey, neural responses and artificial intelligence

A conceptual framework for prototyping futures scenarios through narrative design of VR urban scenes

Biomaterial-based strategies for postoperative residual tumors: From margin clearance to immune control and tissue repair.

Are mature firms more sustainable? An analysis of industry 4.0 maturity

Effective knowledge of ecological connectivity at sea and at the land-sea interface is key to supporting global policy goals to conserve and restore ocean biodiversity and function. However, a persistent lack of commonality in terminology and understanding around the concept of connectivity in marine ecological studies hampers its integration across disciplines, and its application in spatial planning and policy. Building on an extensive literature review, we clarify definitions and subcategories of marine connectivity, and propose a unified conceptual framework for Marine Functional Connectivity (MFC) research to support the integration of multidisciplinary scientific knowledge into management and policy. We identify key challenges and future directions for advancing this emerging field, bringing together most strands of marine science to understand changes in biodiversity and functional interdependencies between habitats and regions. Embedding this new integrated MFC research at the core of marine environmental science promises to improve significantly predictions of environmental and socio-economic change and the sustainable use of ecosystems and resources at sea and at the land-sea interface.

Lower urinary tract symptoms (LUTS) such as frequency, urgency, and sensation of incomplete emptying are frequently attributed to bladder or urothelial disorders, but pelvic floor myofascial dysfunction is underrecognized as an etiologic factor. To present a conceptual framework for myofascial pelvic floor dysfunction (MPFD) as a contributor to urinary symptoms, review its urologic manifestations, discuss, and explore occult contributing factors, and propose integrated diagnostic and interventional therapeutic strategies. This is a narrative review and conceptual synthesis anchored on recent observational studies and existing literature on myofascial pelvic floor dysfunction. MPFD involves failure of appropriate muscle relaxation (or paradoxical contraction), often resistant to standard rehabilitation if underlying drivers remain untreated. The pelvic floor should be conceptualized as a biomechanical "cuboid" interacting with the diaphragm, spine, and abdominal wall. Patients may present with a spectrum of urinary, bowel, sexual, neurogenic, and pain symptoms. Success in rehabilitation demands identification and targeting occult contributors (anatomic, biomechanical, inflammatory, neurologic, behavioral, and central nervous system). Recognizing and addressing myofascial dysfunction as part of the multidimensional pathophysiology of LUTS may improve outcomes in patients' refractory to bladder-centric therapies. Prospective trials are needed to validate integrative treatment strategies.

This systematic review synthesizes 64 empirical studies to examine how Generative AI (GenAI) shapes learning in Computer Science Education (CSE), particularly in programming, debugging, algorithmic reasoning, and computational problem-solving contexts. Grounded in Constructivist, Sociocultural, Cognitive Load, Adaptive Learning, and Metacognitive Learning theories, the review adopts an integrative perspective to analyze how GenAI-driven adaptivity, AI output qualities, hallucination dynamics, and cognitive–affective regulation influence learners’ interpretation, cognitive processing, and learning outcomes. Findings reveal a dual impact of GenAI in CSE. On the negative side, hallucinated or misleading outputs can increase extraneous cognitive load during programming and debugging and promote over-reliance on system-generated content. They may also perpetuate inequities due to limited access in low-resource settings or insufficient support for culturally and linguistically diverse learners. These effects can disrupt error detection, self-monitoring, and problem-solving, leading to impaired learning performance, and widened educational disparities. On the positive side, when embedded within structured, equitable, and pedagogically grounded environments, GenAI supports reflective programming practice by promoting self-monitoring, verification, and strategic adjustment, thereby enhancing problem-solving skills, engagement, and personalized learning outcomes. By framing learning performance, hallucination dynamics, and problem-solving as interconnected dimensions of GenAI-supported computing education, this review provides a theoretically coherent and pedagogically grounded lens for understanding how GenAI reshapes learning in CSE. The review’s novelty lies in its integrative conceptual framework, offering actionable insights for designing equitable, cognitively balanced, and instructionally effective GenAI-supported learning environments.