Search Results (4,425)

Traditional hypergolic propellants, such as hydrazine derivatives combined with nitrogen tetroxide, present severe toxicity, operational, and environmental hazards. High-test peroxide has emerged as a leading green oxidiser replacement due to its low volatility, high density, and benign decomposition products. This review comprehensively analyses recent advancements in HTP-based hypergolic fuel formulations, categorising them into three major emerging families: catalytically-promoted, reactive, and ionic liquid-based systems. By evaluating key parameters such as ignition delay times, specific impulse and toxicity, this work identifies a clear technological shift from fundamental chemical screening to increasingly more mature solutions. While historical targets defined hypergolicity below 100 ms, recent advanced formulations routinely achieve it under 10 ms requiring minimal additive concentrations (<5 wt%), directly competing with legacy systems. Furthermore, this review highlights critical open challenges that limit commercial adoption, including the long-term storage stability of catalytic blends, high toxicity of reactive systems, and the lifecycle toxicity and high cost of frequently employed ionic liquids. Ultimately, it is concluded that rather than a single universal replacement, the future of green hypergolic propulsion lies in a plurality of solution, where each family is tailored to specific niches defined by mission requirements and cost structures. Full article

The oxygen reduction reaction (ORR) is the cathode cornerstone of fuel cells and metal-air batteries. Its inherent spin mismatch between triplet O₂ and singlet products causes sluggish kinetics that conventional catalyst designs cannot fully overcome. This review critically summarizes the past three years’ breakthroughs in spin-regulated ORR electrocatalysis and offers a fresh perspective beyond traditional electronic and geometric optimization. We first dissect the physical mechanism of spin-selective electron transfer required for the 4e⁻ pathway. We then systematically present four strategies for modulating the spin state of transition-metal active sites, namely strain engineering, defect engineering, heteroatom doping, and interfacial heterostructures. Subsequently, we highlight the emerging chirality-induced spin selectivity effect, where chiral organic molecules or intrinsically chiral inorganic materials act as spin filters without an external magnetic field, enabling spin-matched electron transfer and enhanced ORR performance. At the end of our review, we identify several key challenges, including the lack of in situ techniques to dynamically track spin states under operating conditions, the limited stability and universality of chiral catalysts, and the insufficient understanding of synergistic effects between spin control and traditional design parameters. We also outline future research directions, such as developing operando spin characterization, constructing robust chiral inorganic nanostructures, and employing high-throughput computational screening to integrate spin, geometric, and electronic level design. Our review provides a timely and comprehensive framework that bridges spin physics with electrocatalyst design, offering critical mechanistic insights and practical guidelines. Full article

The integration of AI-generated content into higher education has intensified interest in how students form and calibrate trust toward algorithmic outputs and whether pedagogical relationships can serve as conduits for that trust. Grounded in Trust Transfer Theory, this between-subjects randomized experimental study (N = 320) investigated whether teacher endorsement shapes students’ perceptions of AI-generated educational content across four dimensions: Perceived AI Competence, Academic Integrity, Perceived Human-Mediated Reliability, and Behavioral Intention to adopt. Participants from Saudi Arabian universities were randomly assigned to an endorsed or non-endorsed vignette condition and responded to a validated 13-item Trust and Acceptance Scale. Independent-samples t-tests confirmed statistically significant differences across all four dimensions in favor of the endorsed condition, with effect sizes ranging from small to large, and findings remained robust after controlling for gender via ANCOVA. Within-condition regression analyses further established Perceived Human-Mediated Reliability as a structurally stable positive predictor of trust outcomes in both conditions, with predictive power consistently amplified under endorsement. Postgraduate students placed greater emphasis on human oversight, while no disciplinary differences emerged, confirming the cross-disciplinary universality of the trust transfer mechanism. These findings are consistent with positioning the teacher as a trust guarantor in AI-mediated learning environments and carry direct implications for pedagogical design and institutional AI governance. Full article

As generative artificial intelligence (GAI) technologies become increasingly integrated into university students’ academic routines, concerns have emerged regarding their associations with critical thinking dispositions during GAI use. The main objective of the present study was to examine whether metacognitive weakness and epistemic laziness individually and sequentially accounted for the association between GAI tool usage and critical thinking dispositions during GAI use across two distinct student samples. The Turkish-speaking sample consisted of 441 students, whereas the English-speaking sample included 218 students. Participants completed measures assessing GAI tool usage, critical thinking dispositions in GAI use, metacognitive weakness in GAI use, and epistemic laziness. Measurement invariance analyses indicated configural and metric invariance across groups. Path analyses revealed that GAI tool usage had significant indirect associations with lower critical thinking dispositions during GAI use via metacognitive weakness, epistemic laziness, and a sequential indirect pathway involving both constructs. The sequential indirect associations were significant in both the Turkish-speaking sample and the English-speaking sample. Overall, the findings suggest that greater GAI tool usage among university students is associated with lower critical thinking dispositions, with this association statistically carried through metacognitive weakness and epistemic laziness. The consistency of this pattern across two distinct student samples provides preliminary support for a process-oriented interpretation of how GAI use may relate to critical thinking dispositions. Full article

Fungicide residues in complex food matrices represent an increasingly important challenge in food safety monitoring because intensive agricultural practices, diverse fungicide chemistries, and tropical production conditions can generate multiclass contamination patterns, particularly in Southeast Asian food systems. This review critically evaluates literature published between 2019 and 2026 on microchemical analytical strategies for multiclass fungicide residue determination in fruits, vegetables, rice, spices, and processed foods. The review focuses on the integration of miniaturized and green sample preparation techniques, including modified QuEChERS, dispersive liquid–liquid microextraction, solid-phase microextraction, hollow-fiber liquid-phase microextraction, magnetic solid-phase extraction, and deep eutectic solvent-based extraction, with advanced chromatographic and mass spectrometric platforms. Current evidence shows that these methods can reduce solvent consumption, improve analytical efficiency, and support sensitive residue determination when coupled with UHPLC–MS/MS, GC–MS/MS, and high-resolution mass spectrometry. However, method performance remains strongly matrix-dependent and is constrained by matrix effects, limited standardization of emerging extraction materials, inconsistent validation practices, and trade-offs among selectivity, throughput, cost, and sustainability. No single extraction strategy is universally optimal for all food matrices or fungicide classes. Future research should therefore prioritize matrix-adapted hybrid workflows, harmonized validation protocols, improved detection of transformation products, and broader use of high-resolution screening strategies to support reliable, sustainable, and regulatory-compliant fungicide residue monitoring. Full article

Ferroptosis is an iron-dependent regulated form of cell death characterized by lethal lipid peroxidation and is increasingly implicated in cancer, neurodegenerative diseases, cardiovascular injury, and metabolic disorders. Metformin, a widely prescribed antidiabetic biguanide, exerts pleiotropic effects beyond glucose lowering and has emerged as a context-dependent regulator of ferroptosis. In malignant cells, metformin may enhance ferroptotic susceptibility through activation of AMP-activated protein kinase (AMPK), suppression of mechanistic target of rapamycin (mTOR) signaling and SLC7A11, induction of ferritinophagy, mitochondrial complex I stress, and promotion of lipid peroxidation. Conversely, in normal or stressed non-malignant tissues, metformin may limit ferroptotic injury by activating nuclear factor erythroid 2-related factor 2 (NRF2), supporting glutathione peroxidase 4 (GPX4) and SLC7A11-dependent antioxidant defenses, improving mitochondrial quality control, and stabilizing iron homeostasis. This review synthesizes the molecular basis of this duality, evaluates therapeutic opportunities in oncology and cytoprotection, and outlines biomarker-driven and clinical trial strategies required for translation. Overall, metformin should not be regarded as a universal ferroptosis inducer or inhibitor, but rather as a context-dependent metabolic regulator whose effects are shaped by cell type, dose, exposure duration, transporter expression, iron status, and antioxidant capacity. Full article

As artificial intelligence (AI) technologies become increasingly embedded in higher education, concerns have emerged regarding their psychological impact on university faculty. While existing research has largely focused on technological readiness and digital competencies, the social–psychological foundations of faculty well-being in AI-integrated teaching environments remain insufficiently explored. Drawing on social support theory and self-determination theory, this study proposes and tests a structural model of AI-related well-being among university faculty. A total of 523 faculty members in China participated in a cross-sectional survey measuring perceived social support, organizational support, AI literacy, technological self-efficacy, and AI well-being. Structural equation modeling (SEM) was used to examine the hypothesized pathways and mediating mechanisms. The results indicate that both social support and organizational support significantly and positively influence AI literacy and technological self-efficacy. In turn, AI literacy and technological self-efficacy significantly predict AI well-being and serve as key mediators. Among all factors, AI literacy exhibits the strongest total effect on AI well-being, followed by social support, organizational support, and technological self-efficacy. This study contributes to the theoretical understanding of faculty psychological adjustment during technological transitions and offers practical recommendations for institutions seeking to cultivate AI-ready and psychologically supportive academic environments. Full article

Pedestrian Spatial Experience PSE in urban spaces is a multi-faceted topic that requires the thematization of assessment methods due to their fragmentation across studies. Accordingly, this systematic review followed an inductive approach to define a framework of PSE assessment themes reflecting their evaluation in public and university campus spaces. This systematic review included open-access, accessible, peer-reviewed sources based on assessment-focused English research that followed defined frameworks on the effects of urban environments on adult PSE. Studies were excluded if they focused on non-pedestrians or vulnerable user groups, examined non-pedestrian-scale contexts, explored pedestrian experience in virtual environments, assessed interior spaces, lacked a structured attribute-based assessment framework, were review articles, did not specify how urban environments shape pedestrian experience, investigated non-urban or rural areas, or examined urban settings without clearly defined street or square infrastructure. The review relied on querying PSE-related bibliography from the Scopus and Web of Science databases on 12 October 2025; results were processed through a screening procedure according to the inclusion and exclusion criteria. The final sets of sources reviewed included 83 and 24 sources related to PSE assessment in public and university campus spaces, respectively. Risk of Bias (RoB) tools included the Joanna Briggs Institute (JBI) tool for cross-sectional studies, tailored for urban spatial studies, and the Prediction model Risk Of Bias Assessment Tool (PROBAST+AI), tailored for ABM studies. Using a data extraction sheet and codebook to identify the prominent codes in the included sources, in addition to reviewing frequent words and the methods of the included sources, clarified the main conceptual framework of PSE assessment themes. The thematic categorization of PSE studies was followed by analyses of the frequencies of the themes, the prevalence of themes across countries and cities, and the theoretical explorations within the themes over the years in both reviewed contexts. Subsequently, synthesizing both sets clarified the interrelations between themes, methods, and tools as an attempt to address gaps in PSE assessment methods. The main results of this review are the 11 themes of PSE assessment that were identified from the reviewed sources. Data analyses and syntheses indicated a high prevalence of quantitative methods relying on visual aspects, signifying the dominance of the Cognitive and Navigational Experience theme due to its frequent assessment by numerous and diverse sets of methods in both reviewed sets. Nevertheless, the Temporal Experience theme emerged as the least considered. The key limitations of this systematic review include its reliance on accessible articles from bibliographic databases, as well as its focus on adult populations as the common users of public and university campus spaces. This review decodes PSE in terms of its assessment themes through the methods followed and the applied tools within real environments. As an application of the introduced conceptual framework, this systematic review clarifies the comparison of the themes examined between public and university campus spaces. The findings of this systematic review provide a foundation for a comprehensive understanding of PSE, thereby informing the design of more user-centered environments. Full article

Breast cancer is a highly heterogeneous malignancy with multiple molecular subtypes and variable treatment responses. Despite advances in endocrine therapy, HER2-targeted therapy, chemotherapy, and immunotherapy, treatment resistance and disease recurrence remain major clinical challenges. There is growing evidence that transcriptional plasticity and enhancer relinking contribute to tumor progression and treatment adaptation, highlighting the powerful role of epigenetic regulators. CREB-binding protein (CBP) and E1A-associated protein p300 (EP300) are transcriptional coactivators that regulate breast cancer enhancer activity and lineage-specific gene expression. Emerging research suggests that CBP/p300 is more of a context-dependent vulnerability point than a universal carcinogenic driver. ER-positive tumors exhibit a strong dependence on CBP/p300-mediated transcriptional programs, while the triple-negative breast cancer subgroup, including androgen receptor-positive and immunosuppressive tumors, may rely on CBP/p300-dependent signaling to maintain survival and treatment resistance. This is in contrast to their role in HER2-positive breast cancer. This review summarizes the biological functions of CBP/p300 in breast cancer and discusses subtype-specific vulnerability, biomarker-directed patient stratification, drug resistance mechanisms, rational combination strategies, and current translational challenges, emphasizing the need for precise treatment of breast cancer. Full article

Higher education is increasingly asked to prepare learners for societies shaped by artificial intelligence, ecological destabilization, labour-market reconfiguration, and declining institutional trust. Yet many universities remain governed by a scarcity model: knowledge transmission, durable credentials, and economic productivity. This article argues that the model is structurally misaligned with emerging conditions because the central educational challenge is shifting from knowledge scarcity to power abundance. The deeper crisis is not a deficit of knowledge production but a deficit of formation: higher education has underdeveloped the human capacities required to use technologically amplified power wisely, meaningfully and responsibly. The article develops this argument through a conceptual design with an embedded systematized scoping review and thematic synthesis across higher education studies, AI governance, futures and foresight, sustainability transitions, human flourishing, wisdom science, and research metrics. It proposes flourishing stewardship as a new first principle for higher education: the cultivation of persons and institutions capable of pursuing meaningful lives while preserving and advancing the conditions for shared human and planetary flourishing. The article contributes the Flourishing Stewardship Transformation Model, linking external transition conditions, scarcity-model misalignment, the power–wisdom gap, six formation capacities, and five institutional transformation levers. The model is operationalized through design questions, researchable indicators, and propositions for future empirical testing. The paper contributes to technological forecasting and social change by positioning higher education as a socio-technical transition infrastructure whose purpose is not merely to adapt learners to technological change, but to form the human agency needed to govern it. Full article

Artificial Intelligence (AI) is increasingly reshaping customer relationship management (CRM) practices in service industries, yet its perceived effectiveness within emerging regional tourism economies remains underexplored. This study examined respondents’ perceptions of how AI-enabled capabilities influence CRM effectiveness within the tourism sector in Mthatha, in the Eastern Cape, South Africa. Existing AI–CRM research is largely concentrated in developed economies, limiting contextual understanding of its strategic value in resource-constrained and relational tourism environments. A positivist, quantitative explanatory design was adopted, and data were collected through a structured survey administered to managers and staff of tourism enterprises across the Eastern Cape (n = 121). Partial Least Squares Structural Equation Modelling was employed to assess the measurement model and test the hypothesized relationships. The model explained 63.2% of the variance in perceived CRM effectiveness. Sales forecasting and lead scoring exerted the strongest positive influence, followed by sentiment and feedback analysis, while personalization and automation showed positive but statistically insignificant effects. The findings suggest that tourism enterprises may achieve stronger relationship outcomes by prioritizing predictive and analytical AI tools while integrating automation within human-centered service strategies. The study extends AI–CRM theory to an emerging African tourism context and demonstrates that AI effectiveness is context dependent rather than universally transferable. Full article

Background: As construction safety training increasingly shifts toward virtual reality (VR)-based learning platforms, concerns have emerged regarding whether real ambient and virtual visual conditions may affect safety knowledge learning and cognitive responses; Methods: This study examined how real ambient factors (temperature and sound) and virtual visual factors (window view and visual complexity) influenced perceived environmental distraction, subjective workload, learning experience, and EEG-based cognitive responses in a VR classroom. Forty-eight university students completed a construction safety knowledge learning task and were categorized into high- and low-performing groups based on learning gains. Subjective responses were measured using post-experimental questionnaires, while EEG indicators included mental workload, attention, and mental fatigue. Results: Based on independent-samples t-tests, group-specific Spearman correlations, descriptive analyses, and two-way interaction regression, the results revealed: (1) Low-performing students reported greater disturbance from temperature and sound, and higher mental demand and effort. (2) Nominal associations between environmental factors and subjective outcomes were broader in the low-performing group. (3) The EEG results served mainly as supplementary descriptive evidence, showing individual variability in cognitive responses. (4) Learning scores varied across environmental combinations, with Temperature × Sound emerging as the only significant interaction. Conclusions: These findings guide cognitively supportive VR-based construction safety learning environments. Full article

Background: The global use of herbal medicines and research on plant bioactive compounds have steadily increased. In Chile, this growth is linked to ethnobotanical knowledge and advances in phytochemistry, although gaps persist in its evolution, leadership, and regulatory articulation. This study analyzes scientific production on phytochemicals and medicinal plants (1976–2025), identifying growth patterns, leading journals, authorship, and collaboration networks. Methodology: A mixed-methods approach combined bibliometric analysis of Web of Science records with inductive qualitative content analysis from researcher interviews. The quantitative phase applied performance analysis and scientific mapping, using indicators such as Price’s, Lotka’s, Bradford’s, and Zipf’s laws to evaluate evolution, productivity, and impact. The qualitative phase explored perceptions of the field’s current state, limitations, and challenges, thereby contextualizing the bibliometric findings. Results and discussion: Analysis of 2149 articles and 6878 authors shows exponential growth (11.46% annually; R² = 0.952), with 674 publications projected by 2035. Productivity is concentrated among key authors and institutions (University of Chile, Concepción, Talca). Research focuses on antioxidant activity and bioactive compounds. Despite progress, gaps persist in clinical validation, technology transfer, and health system integration, while biodiversity and omics are emerging as strategic assets. Conclusions: Phytochemistry in Chile is expanding rapidly, requiring integrated frameworks that combine clinical validation, sustainable biodiversity management, advanced analytical and computational tools, technology transfer, and adaptive public policies to translate scientific knowledge into evidence-based healthcare, biotechnology, and sustainable innovation. Full article

Violence against children constitutes a global public health emergency, necessitating innovative prevention strategies within the school environment. While the benefits of visual arts on socio-emotional development are well-documented, their specific impact on preventing interpersonal violence remains under-synthesized. This critical narrative review analyzes existing literature (2000–2025) through a corpus of 14 empirical studies (exclusive visual arts interventions and multimodal programs) conducted with children aged 5 to 12. The results reveal a dichotomy: while art-centered interventions demonstrate robust effects on emotional regulation and anger reduction (protective factors), evidence for a direct reduction in violent behaviors primarily stems from large-scale multimodal programs. Although promising as a lever for universal prevention and the facilitation of disclosure, the visual arts require further randomized controlled trials to validate their direct behavioral efficacy. This review proposes an Integrative Mechanisms Model (IMM) to structure future research on visual arts-based violence prevention and advances a renewed evaluative agenda centered on children’s possible selves and future-oriented identity development in the context of violence prevention. Full article

This article develops a local theory for characterizing metric thinking in the measurement of spatial properties from a multilevel curricular perspective, understood as an analytic lens for scaling measurement processes across curricular complexity rather than as empirical evidence from all educational levels. The study adopts a qualitative, explanatory approach and articulates grounded theory with educational design research. The methodological process was organized into four broad moments, operationalized in five phases: an initial literature-based characterization; the design of learning activities involving length, area, volume, center of mass, and angular measure; implementation with engineering students enrolled in integral calculus; analysis of projected and emergent abilities through grounded performance levels; and refinement of the characterization. The findings propose a robust characterization of metric thinking composed of five cognitive processes: perceiving, recognizing, and distinguishing measurable properties; selecting, using comprehensively, and refining measurement instruments; formulating, operationalizing, and optimizing measurement strategies; applying measurement; and developing a critical perspective on measurement. These processes are interpreted as cyclic and mutually connected rather than hierarchical or linear. Within the university engineering tasks analyzed, they also show how measurement can mediate connections between advanced mathematical domains and STEM-related problem contexts. The article concludes by offering a definition of metric thinking that may guide research, curriculum design, and instruction while requiring further validation beyond the university context examined in this study. Full article