Search Results (8,618)

Industry 5.0 challenges higher education to adopt human-centred and sustainable uses of artificial intelligence, yet many current deployments still treat generative AI as a stand-alone tool, neurophysiological sensing as largely laboratory-bound, and governance as an external add-on rather than a design constraint. This article introduces Nested Learning as a neuro-adaptive ecosystem design in which generative-AI agents, IoT infrastructures and multimodal deep learning orchestrate instructional support while preserving student agency and a “pedagogy of hope”. We report an exploratory two-phase mixed-methods study as an initial empirical illustration. First, a neuro-experimental calibration with 18 undergraduate students used mobile EEG while they interacted with ChatGPT in problem-solving tasks structured as challenge–support–reflection micro-cycles. Second, a field implementation at a university in Madrid involved 380 participants (300 students and 80 lecturers), embedding the Nested Learning ecosystem into regular courses. Data sources included EEG (P300) signals, interaction logs, self-report measures of engagement, self-regulated learning and cognitive safety (with strong internal consistency; $\alpha /\omega \ge 0.82$), and open-ended responses capturing emotional experience and ethical concerns. In Phase 1, P300 dynamics aligned with key instructional micro-events, providing feasibility evidence that low-cost neuro-adaptive pipelines can be sensitive to pedagogical flow in ecologically relevant tasks. In Phase 2, participants reported high levels of perceived nested support and cognitive safety, and observed associations between perceived Nested Learning, perceived neuro-adaptive adjustments, engagement and self-regulation were moderate to strong ($r=0.41$–$0.63$, $p<0.001$). Qualitative data converged on themes of clarity, adaptive support and non-punitive error culture, alongside recurring concerns about privacy and cognitive sovereignty. We argue that, under robust ethical, data-protection and sustainability-by-design constraints, Nested Learning can strengthen academic resilience, learner autonomy and human-centred uses of AI in higher education. Full article

Design studios remain a core component of architectural education, yet their pedagogical structure, alignment with international standards, and contribution to professional formation are often insufficiently examined. This study evaluates master-level design studios using a three-track analytical framework that integrates pedagogical innovation, alignment with the UNESCO-UIA Charter for Architectural Education, and the development of professional capabilities specified in the UNESCO-UIA Validation System. The methodology combines qualitative profiling and quantitative benchmarking, employing a structured six-parameter innovation framework, an ordinal evidence scale, and a cross-track correlation analysis. Learning and professional capabilities were assessed and analyzed through Pearson correlation matrices in JASP (0.95.4). Findings reveal that all studios share a common grounding in heritage- and environment-responsive learning, yet demonstrate distinctive pedagogical signatures shaped by thematic focus, design scale, and temporal orientation. Strong positive alignments emerge between context-driven learning and applied professional readiness, while structural gaps indicate capability areas insufficiently supported by studio pedagogies. The study demonstrates that bridging policy frameworks with pedagogical and professional capability assessments provides a replicable method for evaluating architectural curricula, offering insights for improving design-studio models and strengthening evidence-based educational practice. Full article

The vibration compaction behavior of fully graded fresh concrete differs fundamentally from that of conventional two-graded concrete. Based on measured vibration responses of an internal vibrator and sinking-ball tests, an energy transfer model for fully graded concrete was established by incorporating the effects of aggregate-specific surface area, paste–aggregate ratio, dynamic damping, and natural frequency, and the spatiotemporal attenuation of vibration energy in fresh concrete was systematically analyzed. Experimental results indicate that fully graded concrete exhibits a higher energy absorption capacity during the early stage of vibration, with a maximum energy absorption rate of 423 W and a peak energy transfer efficiency of 76.3%, both of which are significantly higher than those of two-graded concrete at the same slump. However, as a dense aggregate skeleton rapidly forms, the energy absorption efficiency of fully graded concrete decreases more rapidly during the middle and later stages of vibration, showing a characteristic pattern of “high initial absorption followed by rapid attenuation.” Through segregation assessment and porosity analysis, a safe vibration energy range for fully graded concrete was quantitatively determined, with lower and upper energy thresholds of 159.7 J·kg⁻¹ and 538.5 J·kg⁻¹, respectively. In addition, the experiments identified recommended vibration durations of 30–65 s and effective vibration influence radii of 22–85 mm for fully graded concrete under different slump conditions. These findings provide a quantitative basis for the control of vibration parameters and energy-oriented construction of fully graded concrete. Full article

Antimicrobial resistance (AMR) represents a significant global concern, undermining the efficacy of treatments in both human and veterinary medicine. Livestock production plays a major role in the emergence and dissemination of AMR, primarily due to the extensive use of antibiotics for therapeutic, prophylactic, and metaphylactic purposes. Addressing this multifaceted issue necessitates a One Health approach. At the international level, regulatory frameworks are predominantly non-binding, relying on soft-law instruments developed by the World Health Organization (WHO), the Food and Agriculture Organization (FAO), and the World Organization for Animal Health (WOAH, formerly OIE), which advocate for harmonized guidelines and national action plans. In contrast, the European Union has implemented binding regulations, including Regulation (EU) 2019/6 and Regulation (EU) 2019/4, which restrict non-essential antimicrobial use (AMU) and reinforce veterinary accountability. Initiatives such as the Farm to Fork Strategy and platforms like ClassyFarm further advance antimicrobial stewardship by integrating animal welfare, sustainability, and access to EU funding. Achieving substantial reductions in AMR within livestock systems requires coordinated, cross-disciplinary, and multi-level governance efforts. The EU model illustrates how enforceable legal frameworks, combined with science-based monitoring and welfare incentives, can facilitate prudent antibiotic use and promote sustainable animal production. This review aims to provide an integrated overview of international and European strategies for regulating antibiotic use in food-producing animals, focusing on how scientific, veterinary and legal perspectives contribute to combating AMR and promoting animal welfare by emphasizing prevention, and a prudent and responsible AMU. Full article

This study examines consumer opinions and behavior toward international food standards related to sustainability and environmental responsibility. For the data collection process, a structured questionnaire was distributed online and completed by 1064 participants. The study focuses on assessing consumer awareness of food standards, the extent to which these standards influence purchasing decisions, and the demographic factors affecting such choices. The findings reveal a growing interest in sustainable products, particularly among younger age groups. However, the study also identifies significant gaps in knowledge and understanding of international standards, which hinder the adoption of more responsible consumption practices. It concludes with recommendations to improve awareness, transparency, and food labeling, as well as to promote sustainable consumption through coordinated policies and educational initiatives. Full article

Background/Objectives: The Rett Syndrome Behavior Questionnaire (RSBQ) is a widely used caregiver-reported instrument for assessing behavioral and neurological features of Rett syndrome (RTT). However, a validated Korean version has not been available. This study aimed to translate the RSBQ into Korean (K-RSBQ) and to evaluate its psychometric properties in a Korean RTT population. Methods: The RSBQ was translated and back-translated using standardized procedures and refined through a Delphi process. Primary caregivers of individuals with clinically diagnosed RTT completed an online survey including the K-RSBQ and the Childhood Autism Rating Scale (CARS). Test–retest reliability was assessed in a subset of caregivers who completed the questionnaire twice within one week, and inter-rater reliability was evaluated when an additional caregiver was available. Results: Sixty-six primary caregivers participated. The K-RSBQ demonstrated high internal consistency for the total score (Cronbach’s α = 0.912) and moderate-to-high consistency across most subscales. Test–retest reliability for the total score was moderate (weighted κ = 0.594), while inter-rater reliability between primary and secondary caregivers was generally low. The hand behavior subscale showed low and non-significant test–retest reliability. The K-RSBQ total score exhibited a low-to-moderate correlation with the CARS total score, and the general mood subscale showed a moderate correlation with the CARS emotional response item. Caregivers reported minimal difficulty in understanding the questionnaire items. Conclusions: The K-RSBQ demonstrates acceptable internal consistency and test–retest reliability when administered to primary caregivers, with preliminary evidence supporting its construct validity. Although limitations exist regarding criterion validation and inter-rater agreement, the K-RSBQ represents a feasible and culturally adapted tool for assessing RTT-related behavioral features in Korean clinical and research settings. Full article

Leadership speeches delivered within the United Nations and UNESCO play an active role in shaping global policy discourse. As widely circulated texts, they influence how policymakers understand sustainability, responsibility, and education by defining global challenges, allocating responsibility, and communicating shared priorities. This study examines how these concepts are articulated in selected leadership speeches delivered between 2022 and 2025. The analysis adopts a pragmatic framing approach informed by non-linear pragmatic theory. It focuses on six interrelated dimensions: problem definition, causal responsibility, treatment responsibility, value framing, future-oriented framing, and education-specific framing. The findings show that sustainability is consistently framed as a complex ethical challenge linked to climate change, social inequality, and global injustice. Responsibility is presented as shared but uneven, with greater obligations assigned to high-income countries, international institutions, and education systems. Education is addressed both directly, through references to curriculum reform, teacher preparation, and higher education leadership, and indirectly as a means of supporting climate resilience, ethical technological development, and global citizenship. Overall, the study demonstrates that leadership speeches function as influential discursive sites through which sustainability narratives are advanced and priorities for Education for Sustainable Development are communicated, highlighting the value of pragmatic framing for research on international sustainability communication. Full article

Bovine viral diarrhea virus (BVDV) causes severe mucosal inflammation in cattle, and effective treatment options remain limited. Dysregulated activation of the NLRP3 inflammasome, driven by NF-κB and STAT3 signaling, may exacerbate disease pathogenesis, highlighting this axis as a potential therapeutic target. Although traditional Chinese medicine has shown promise in antiviral and anti-inflammatory applications, it remains unclear whether it can inhibit BVDV replication via the NF-κB/STAT3-NLRP3 pathway. The present study aimed to clarify the inhibitory effect of luteolin on bovine viral diarrhea virus (BVDV) replication, and to elucidate its underlying mechanisms from two perspectives: interference with viral internalization and replication processes, as well as regulation of the NF-κB/STAT3-NLRP3 inflammasome pathway. Collectively, this work intended to provide experimental evidence and theoretical support for the development of luteolin as a natural anti-BVDV agent. To this end, BVDV-infected MDBK cells were treated with gradient concentrations of luteolin, followed by quantification of viral load using qRT-PCR and Western blot assays. Meanwhile, the activation status of the NF-κB/STAT3-NLRP3 signaling pathway was evaluated via immunofluorescence staining and luciferase reporter gene assays. Our results demonstrate that luteolin exhibits potent dual antiviral activity against cytopathic BVDV-1m in MDBK (Madin-Darby Bovine Kidney) cells, effectively suppressing both viral replication and inflammatory responses. At non-cytotoxic concentrations, luteolin specifically inhibited the internalization and replication stages of the viral lifecycle, accompanied by reduced NS5B polymerase activity. Importantly, luteolin disrupted the NF-κB/STAT3-NLRP3 axis by suppressing phosphorylation of p65 (Ser536) and STAT3 (Ser727), downregulating NLRP3 and pro-caspase-1 expression, and inhibiting caspase-1 cleavage (p20) as well as maturation of IL-1β and IL-18. Consequently, it attenuated the overexpression of TNF-α and IL-8. To our knowledge, this is the first report of a single compound simultaneously targeting multiple stages of the BVDV lifecycle and counteracting NLRP3-mediated immunopathology, offering a strategic basis for developing flavonoid-based therapies against Flavivirus infections. Full article

Polystigma amygdalinum the causal agent of Red Leaf Blotch (RLB), is responsible for one of the most important foliar diseases affecting almond [Prunus dulcis (Miller) D.A. Webb] in the Mediterranean Basin and the Middle East. The study is aimed at improving knowledge on RLB epidemiology and the role of environmental conditions in disease development. Field monitoring was conducted from 2022 to 2025 in three almond orchards located in Apulia (southern Italy) and characterized by different microclimatic conditions. A total of 39 cultivars, including Apulian local germplasm and international cultivars (‘Belona’, ‘Genco’, ‘Guara’, ‘Ferragnès’, ‘Filippo Ceo’, ‘Lauranne^® Avijor’, ‘Soleta’, and ‘Supernova’), were evaluated. Symptoms occurred from late spring to summer, resulting particularly severe on ‘Guara’ and ‘Lauranne^® Avijor’, whereas ‘Belona’, ‘Ferragnès’, ‘Genco’, and ‘Supernova’ exhibited the highest tolerance. To our knowledge, this is also the first report of RLB tolerance by ‘Filippo Ceo’, ‘Ficarazza’, ‘Centopezze’, and ‘Rachele piccola’ representing potential genetic resources for breeding programs. Moreover, these findings reinforced previous observations proving that RLB was less severe on medium-late and late cultivars. Disease incidence varied significantly among sites and years and was strongly associated with increased rainfall, higher relative humidity, and mild temperatures recorded in November, influencing disease occurrence in the following growing season. P. amygdalinum was consistently detected by qPCR in all RLB-affected tissues and, in some cases, from mixed early RLB + Pseudomonas-like symptoms. From some leaves with early RLB symptoms, P. amygdalinum was also successfully isolated in pure culture. Overall, our results provide clear evidence that P. amygdalinum is the sole fungal pathogen consistently associated with typical RLB symptoms in Apulia (southern Italy) and highlight important cultivar-dependent differences. Its frequent molecular detection in leaves showing atypical or mixed symptoms suggests unresolved epidemiological aspects requiring further investigation. Full article

Background/Objectives: Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental condition, and pharmacogenetic studies aim to clarify interindividual variability in treatment responses and adverse effects. Despite increasing research, the field remains fragmented. This review provides a bibliometric analysis of ADHD pharmacogenetics (2005–2025), identifying its intellectual foundations, thematic structure, and global distribution. Methods: A bibliometric search was conducted in Scopus and Web of Science, retrieving 711 documents published between 2005 and July 2025. Data were analyzed with the Bibliometrix R package and Biblioshiny interface, applying bibliometric mapping, Bradford’s Law, co-word analysis, and thematic mapping. Only peer-reviewed journal articles, books, and book chapters were included to ensure scientific rigor. Results: The dataset shows a modest annual growth rate but strong impact, with an average of 29.6 citations per article. Highly cited works converge into four domains: (i) clinical guidelines and pharmacological treatments; (ii) cognitive heterogeneity and subtypes; (iii) neurodevelopmental and genetic mechanisms; (iv) environmental and health-related influences. Geographically, the United States leads with 24.8% of publications, followed by Brazil, China, and European countries. Keyword analysis reveals two main clusters: a clinical–therapeutic pole (methylphenidate, atomoxetine, child) and a genetic–molecular pole (dopamine transporter, SNPs, genotype). Conclusions: ADHD pharmacogenetics shows consolidation with strong clinical and genetic cores but limited integration of comorbidity, adult populations, and non-stimulant treatments. Future research should prioritize multi-center cohorts, multi-omic designs, and stronger international collaboration to advance precision medicine in ADHD. Full article

A magnetorheological (MR) damper is an intelligent semi-active control device characterized by its output damping force and adjustable coefficient that vary in response to changes in the internal magnetic field. This study proposes a multiphysics coupling model that takes into account the electromotive force within the magnetorheological fluid, which is related to both the magnetic field intensity and shear stress. The Bingham–Papanastasiou constitutive model was employed to accurately represent the dynamic performance during the simulation of magnetorheological dampers, thereby overcoming its discontinuity. The investigation delves into the unique responses elicited by single-coil and three-coil configurations under identical excitation conditions. Through theoretical and magnetohydrodynamic analyses, the nonlinear rheological behavior of the MR fluid is elucidated. The study also scrutinizes the effects of various internal structural parameters on the mechanical characteristics of the MR damper using the results of simulations. An assessment of parameter sensitivity on the damper’s output was carried out, and the response surface methodology was subsequently utilized to derive a surrogate model expression. Ultimately, an optimized design was obtained, achieving a balance between output damping force and adjustable coefficient. This method lays the groundwork for the mathematical modeling and simulation analysis of multi-coil magnetorheological dampers. Full article

Modernizing public security risk governance demands a paradigm shift from reactive response to proactive, systems-oriented prevention. Prevailing governance models, with their focus on institutions and technology, often neglect the micro-foundational mechanisms of risk generation: the internal psychological processes of individuals. To address this gap, this study develops a novel theoretical model—the F(T, P, C, R) framework—which integrates self-organization theory with a psychological gaming perspective. We conceptualize an individual’s behavioral choice (F_behavior) as an emergent outcome of the dynamic interplay among four constitutive factors: the situational context of Time (T) and Place (P), and the cognitive assessments of perceived Risk Control power (C) and perceived Risk Destructive power (R). Employing automotive driving behavior—specifically decisions regarding safe distance maintenance and the adoption of autonomous driving technologies—as our primary analytical scenario, we derive a dynamic risk-decision matrix. This matrix categorizes behavioral outcomes into four distinct quadrants (Confirm, Tend-to-Confirm, Tend-to-Deny, Deny) based on the subjective calculus between C and R, thereby elucidating the internal logic of risk-related choices. The study’s main contribution is constituted by this novel micro-behavioral analytical framework that integrates cognitive science with systems-based governance principles. It offers theoretical insights for behavioral public policy and provides a structured toolkit for diagnosing and designing targeted interventions, ultimately aiming to enhance proactive risk management and systemic resilience. Full article

This study analyses the integration of Generative Artificial Intelligence (GenAI) in agro-environmental higher education in Ecuador, focusing on its contribution to sustainable digital transformation aligned with Sustainable Development Goals (SDGs) 4 and 9. The research was conducted at the Faculty of Agricultural and Environmental Engineering (FICAYA) of Universidad Técnica del Norte (UTN) using a quantitative, cross-sectional, and analytical design. A validated digital survey grounded in established technology-acceptance frameworks—the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) was administered to 94% of the student population, showing satisfactory internal consistency (Cronbach’s α = 0.87). Data was analysed using descriptive statistics and multivariate techniques, including Principal Component Analysis (PCA) and k-means clustering. The results obtained in Microsoft Forms^® indicate that ChatGPT-5 is the most widely used GenAI tool (54.2%), followed by Gemini (11.9%). Students reported perceived improvements in academic performance (62.5%), conceptual understanding (74.6%), and task efficiency (69.1%). PCA explained 67% of the total variance, identifying three latent dimensions: effectiveness and satisfaction, institutional access and support, and ethical concerns versus operational benefits. Furthermore, k-means clustering (k = 2) segmented users into two distinct profiles Integrators, characterised by frequent use and positive perceptions, and Cautious Users, exhibiting lower usage and greater ethical or technical concerns. Overall, the findings highlight GenAI as a catalyst for sustainable education and underline the need for institutional and ethical frameworks to support its responsible integration in Latin American universities. Full article

The growing reliance on AI-powered EdTech solutions has prompted educators at all levels to rethink teaching and learning methodologies. This shift has fostered a renewed partnership among teachers, students, and society, repositioning AI from a passive support tool into a proactive agent in the classroom. This transformation calls for teachers to exercise leadership and judgement in guiding students’ use of AI, emphasising both responsible practices and ethical considerations within their broader socio-cultural contexts. To harness this potential, we leveraged AI-based solutions within the AECT academic association to reinterpret UNESCO’s four foundational pillars of learning, thereby impacting the broader educational community. This initiative underscores literacy in educational communities emerging from intra-national and international inequity. Hence, it is imperative to examine the exigency of fundamental rights in relation to ethics and norms to uphold the innovative opportunities of AI in education globally. In this regard, this study connects the Pedagogical AI-Tact concept to bridge the gap between theory and practice, fostering both interest and ethical engagement across diverse educational communities. This study valuably upholds Margaret Mead’s proposal that every child deserves universal educational rights, a principle in harmony with justice and freedom. Full article

The construction and operation of reservoirs have made hydrological processes complex, posing challenges to flood modeling. While many hydrological models have incorporated reservoir operation schemes to improve discharge estimation, the influence of reservoir representation on model calibration has not been sufficiently evaluated—an issue that fundamentally affects the spatial reliability of distributed modeling. Additionally, the limited availability of reservoir regulation data impedes dam-inclusive flood simulation. To overcome these limitations, this study proposes a synergistic modeling framework for data-scarce dammed basins. It integrates a satellite-based reservoir operation scheme into a distributed hydrological model and incorporates reservoir processes into the model calibration procedure. The framework was tested using the coupled version of the DRIVE flood model (DRIVE-Dam) in the Nandu River Basin, southern China. Two calibration configurations, with and without dam operation (CWD vs. CWOD), were compared. Results show that reservoir dynamics were effectively reconstructed by combining satellite altimetry with FABDEM topography, successfully supporting the development of the reservoir scheme. Multi-site comparisons indicate that, while CWD slightly improved streamflow estimation (NSE and KGE > 0.75, similar to CWOD) on the calibrated outlet gauge, it enhanced basin-internal process representation, as evidenced by the superior peak discharge and flood event capture with reduced bias, boosting flood detection probability from 0.54 to 0.60 and reducing false alarms from 0.28 to 0.15. The improvements stem from refined parameterization enabled by a physically complete model structure. In contrast, CWOD leads to subdued flood impulses and prolonged recession due to spurious parameters that distort baseflow and runoff response. The proposed methodology provides a practical reference for flood forecasting in dam-regulated basins, demonstrating that reservoir representation enhances model parameterization and underscoring the strong potential of satellite observations for hydrological modeling in data-limited regions. Full article