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Traditional villages, protected as cultural heritage in our country, are rich in historical information, cultural landscapes, and traditional domestic architecture. This article explores the spatial distribution of traditional villages and proposes a new paradigm for the sustainable development of traditional dwellings. It addresses the challenges these villages face, such as natural, social, and inherent issues, arising from rapid socioeconomic development and urbanization. This study analyzes the spatial distribution and architectural features of traditional villages and dwellings in Northern Shaanxi based on 179 national and provincial villages. Using ArcGIS 10.1, the geographic concentration index, kernel density analysis, and the analytic hierarchy process, this study applied both macro and micro level perspectives. The research shows that: (1) The traditional villages in northern Shaanxi exhibit a spatial distribution pattern of “overall aggregation, local dispersion, and uneven distribution.” This pattern is influenced by interactions between natural and human factors. (2) Traditional dwellings in these villages are primarily cave dwellings and courtyard buildings, each reflecting unique architectural features in terms of floor plan layout, facade form, structure, materials, and decoration. (3) Traditional village dwellings in northern Shaanxi face practical challenges related to protection, development, and governance. The top three challenges, based on weighted indicators, are issues related to inheritance, an imperfect protection mechanism, and inherent shortcomings of the buildings. Based on these findings, this study proposes three practical suggestions for the sustainable development of traditional village dwellings in Northern Shaanxi. These suggestions aim to enhance the comprehensive and multi-dimensional sustainable development of traditional village dwellings. Full article

Generative artificial intelligence (GenAI) shows transformative potential in mathematics education. However, empirical findings remain inconsistent, and a systematic synthesis of its effects across distinct engagement dimensions is lacking. This preregistered meta-analysis (INPLASY2025110051) systematically reviewed 22 empirical studies (46 independent samples, N = 5232) published between 2023 and 2025. The results indicated that GenAI has a moderate positive impact on students’ mathematics learning outcomes (g = 0.534). Moderation analysis further revealed that the level of GenAI integration in teaching, sample size, and learning content are the primary factors influencing this effect. The study found that the effect was most pronounced under the creative transformation (CT) integration mode, was significant when applied to geometry learning, and was stronger in studies with small samples or small class sizes; collaborative learning approaches also significantly enhance these mathematics learning outcomes. By contrast, educational stage and intervention duration did not show significant moderating effects. The GRADE assessment indicated that while the overall evidence is supportive, the certainty of evidence is stronger for cognitive outcomes than for non-cognitive domains. The findings also offer a reference for future research on constructing a human–machine collaborative learning environment. Full article

In recent years, despite the continuous improvement of China’s construction safety management systems and the adoption of advanced technologies, safety accidents remain frequent. This shift highlights the growing importance of human factors in construction safety. As the main labor force, the new generation of construction workers differs significantly from previous generations in values and motivation, reducing the effectiveness of traditional safety management models. This study investigates the direct effect of transformational leadership on the safety behavior of new-generation construction workers. Using survey data collected from construction enterprises in Guangdong Province, China, and applying structural equation modeling (SEM), the results reveal that transformational leadership has a significant positive impact on safety behavior. All four dimensions—idealized influence, inspirational motivation, idealized influence (charisma) and individualized consideration—positively influence both safety compliance and participation, with inspirational motivation exerting the strongest effect (β = 0.509 for compliance; β = 0.446 for participation). These findings indicate that leaders who articulate a compelling shared vision can effectively internalize safety norms and motivate proactive safety participation. This study enriches theoretical understanding of safety leadership mechanisms and provides practical guidance for construction enterprises to enhance safety performance through cultivating transformational leadership among managers. Full article

The present study proposes to identify information from health, educational and sports science studies that used Bronfenbrenner’s theory of human development to verify the complex relationship between factors associated with physical activity (PA) and sedentary behavior (SB) in children and adolescents. The scoping review will be developed across seven databases (PubMed, Scopus, SPORTDiscus, Web of Science, PsycINFO, ERIC, and Scielo). The inclusion criteria were formulated based on the PCC (Population, Concept, Context) framework: (a) children and adolescents (5–17 years); (b) studies on PA and/or SB that used Bronfenbrenner’s theory; (c) any context. Only peer-reviewed journal articles published in English, Spanish, or Portuguese will be included; grey literature will not be included. Finally, two reviewers will screen studies using Rayyan. A standardized charting form will be used to extract data on study characteristics and the factors mapped considering Bronfenbrenner’s theory components. This study is expected to show how Bronfenbrenner’s theory has been applied to explain PA and SB in children and adolescents, as well as to map the methodological tools used in this area, identifying gaps and providing a clear framework for future research on the complex and multilevel determinants of PA and SB in children and adolescents. Full article

This study focuses on the diversity of phytoplankton in the Koh Yaa region of Thailand and their relationship with environmental variables, aiming to assess whether human activities (primarily tourism) pose potential threats to the marine ecosystem and provide scientific support for eco-sustainable tourism management decisions in the region. In April, August, and December 2024, corresponding to peak season, off-season, and shoulder season, a total of 156 discrete samples were collected from four coastal sites to analyze water quality parameters such as temperature, pH, total nitrogen (TN), and total phosphorus (TP), along with plankton diversity and abundance. Statistical analyses including two-way ANOVA with Duncan’s Multiple Range Test (DMRT), Pearson correlation analysis, and principal component analysis (PCA) were applied. The results showed a declining trend in plankton abundance over time, peaking at 1009 × 10⁶ cells/m³ in April and dropping to 281 × 10⁶ cells/m³ by December. A total of 15 types of phytoplankton were identified across four phyla: Bacillariophyta, Cyanobacteria, Dinoflagellata, and Chlorophyta. Notably, Chaetoceros from Bacillariophyta accounted for 47% of phytoplankton, while Oscillatoria from Cyanobacteria made up 29.6%. The diversity index and evenness index improved from 1.34 and 0.46 in April to 1.88 and 0.64 in December, respectively. Environmental factors like pH, temperature, and TP significantly affected phytoplankton abundance (p < 0.01), with TP levels ranging from 0.27 to 0.69 mg/L. These results indicate possible pollution in this region, and changes in phytoplankton abundance were linked to seasonal climate variations—especially during peak tourist seasons—which may exacerbate eutrophication affecting community structures. Full article

Phishing attacks continue to evolve and exploit fundamental human impulses, such as trust and the need for a rapid response, as well as emotional triggers. This makes the human mind both a valuable asset and a significant vulnerability. The proliferation of zero-day vulnerabilities has been identified as a significant exacerbating factor in this threat landscape. To address these evolving challenges, we introduce CrossPhire: a multimodal deep learning framework with an end-to-end architecture that captures semantic and visual cues from multiple data modalities, while also providing methodological insights for anti-phishing multimodal learning. First, we demonstrate that markup-free semantic text encoding captures linguistic deception patterns more effectively than DOM-based approaches, achieving 96–97% accuracy using textual content alone and providing the strongest single-modality signal through sentence transformers applied to HTML text stripped of structural markup. Second, through controlled comparison of fusion strategies, we show that simple concatenation outperforms a sophisticated gating mechanism so-called Mixture-of-Experts by 0.5–10% when modalities provide complementary, non-redundant security evidence. We validate these insights through rigorous experimentation on five datasets, achieving competitive same-dataset performance (97.96–100%) while demonstrating promising cross-dataset generalization (85–96% accuracy under distribution shift). Additionally, we contribute Phish360, a rigorously curated multimodal benchmark with 10,748 samples addressing quality issues in existing datasets (96.63% unique phishing HTML vs. 16–61% in prior benchmarks), and provide LIME-based explainability tools that decompose predictions into modality-specific contributions. The rapid inference time (0.08 s) and high accuracy results position CrossPhire as a promising solution in the fight against phishing attacks. Full article

Enhancing agricultural green total factor productivity (AGTFP) under ecological and environmental constraints is essential for advancing green agricultural development in the Beijing–Tianjin–Hebei (BTH) region. Using panel data from 13 prefecture-level cities from 2001 to 2022, this study applies a super-efficiency EBM model incorporating undesirable outputs together with the Malmquist–Luenberger index to measure AGTFP. Global and local Moran’s I indices as well as the spatial Durbin model are then employed to examine the temporal evolution, spatial disparities, and spatial interaction effects of AGTFP during 2001–2022. The findings indicate that: (1) From 2001 to 2022, the AGTFP in the BTH region grew at an average annual rate of 7.7%. This trend reflects a growth pattern primarily driven by green technological progress in agriculture, while substantial disparities in AGTFP persist across different subregions. (2) the global Moran’s I values show frequent shifts between positive and negative spatial autocorrelation, suggesting that a stable and effective regional coordination mechanism for green agricultural development has yet to be formed; (3) the determinants of AGTFP exhibit pronounced spatiotemporal heterogeneity, and the fundamental drivers of the region’s green agricultural transition increasingly rely on endogenous growth generated by technological innovation and rural human capital; (4) policy recommendations include strengthening benefit-sharing and policy coordination mechanisms, promoting cross-regional cooperation in agricultural science and technology, and implementing differentiated industrial layouts to support green agricultural development in the BTH region. These results provide valuable insights for promoting coordinated and sustainable green agricultural development across regions. Full article

The presence and development of pathogens in the human body remains a serious problem. The existence of microorganisms is primarily related to their ability to adhere to various surfaces. The aim of this study was to evaluate the ability of Si(C,N) coatings on a nickel-chromium alloy surface to reduce bacterial and fungal adhesion and to provide antimicrobial activity. This publication also focused on determining which coating variant is most effective in reducing microbial adhesion. Si(C,N) coatings were sputtered onto the surface of the prosthetic alloy using the magnetron sputtering method. Observation was performed using a fluorescence microscope and a flow cytometer. The number of adhered bacterial cells decreased compared to the samples without coating (sample series A) by approximately 84% in sample series B and by 29% in sample series F. In the case of adhesion of fungal cells, their number decreased compared to the samples without coating (sample series A) by approximately 76% in sample series B and by 47% in sample series F. The applied one-way analysis of variance test indicated a statistically significant effect of the tested factor at a level below 0.001. Based on the conducted research, it was noticed that the use of Si(C,N) layers on the surface of the prosthetic alloy limits the adhesion of bacteria and fungi. Full article

This qualitative single-case study examines how spirituality promotes mental health within a stigmatized occupation by analyzing an in-depth interview with “Perla,” a 62-year-old Mexican woman with decades of experience in sex work. Guided by Virginia Satir’s Transformational Systemic Therapy (STST), specifically the Self-Mandala and Iceberg Metaphor, we conceptualize spirituality as a universal human dimension of meaning, moral orientation, and relational connection that may be expressed within or beyond formal religion. Narrative thematic analysis identifies processes through which Perla cultivates congruence (alignment of inner experience and outward conduct), safeguards dignity, and sustains hope amid systemic constraints. Her Catholic practices (prayer, ritual boundaries regarding Eucharist) coexist with a broader spiritual agency that supports self-worth, emotional regulation, boundary-setting, and coherent identity, factors associated with mental well-being. Interdisciplinary implications bridge marriage and family therapy, psychology, pastoral care, and cultural studies. Clinically, we translate Satir’s constructs (yearnings, perceptions, expectations, coping stances) into practical assessment and intervention steps that can be applied in secular settings without religious presuppositions. Analytic rigor was supported through reflective memoing, a structured three-level coding process, constant comparison, and verification by a second coder. The case challenges pathologizing frames of sex workers by demonstrating how spirituality can function as a protective, growth-oriented resource that fosters agency and moral coherence. Full article

In an increasingly technologized and automated world, workplace safety and health remain a major global challenge. After decades of regulatory frameworks and substantial technical and organizational advances, the expanding interaction between humans and machines and the growing complexity of work systems are gaining importance. In parallel, the digitalization of Industry 4.0/5.0 is generating unprecedented volumes of safety-relevant data and new opportunities to move from reactive analysis to proactive, data-driven prevention. This review maps how artificial intelligence (AI), with a specific focus on natural language processing (NLP) and large language models (LLMs), is being applied to occupational risk prevention across sectors. A structured search of the Web of Science Core Collection (2013–October 2025), combined OSH-related terms with AI, NLP and LLM terms. After screening and full-text assessment, 123 studies were discussed. Early work relied on text mining and traditional machine learning to classify accident types and causes, extract risk factors and support incident analysis from free-text narratives. More recent contributions use deep learning to predict injury severity, potential serious injuries and fatalities (PSIF) and field risk control program (FRCP) levels and to fuse textual data with process, environmental and sensor information in multi-source risk models. The latest wave of studies deploys LLMs, retrieval-augmented generation and vision–language architectures to generate task-specific safety guidance, support accident investigation, map occupations and job tasks and monitor personal protective equipment (PPE) compliance. Together, these developments show that AI-, NLP- and LLM-based systems can exploit unstructured OSH information to provide more granular, timely and predictive safety insights. However, the field is still constrained by data quality and bias, limited external validation, opacity, hallucinations and emerging regulatory and ethical requirements. In conclusion, this review positions AI and LLMs as tools to support human decision-making in OSH and outlines a research agenda centered on high-quality datasets and rigorous evaluation of fairness, robustness, explainability and governance. Full article

River ecosystems play a crucial role in the global water cycle and regional ecological security, yet they face severe challenges under the dual pressures of human activities and climate change. To systematically assess the spatiotemporal characteristics and driving mechanisms of river ecological impacts, this study proposes a modular and transferable method, which is Quantitative Analysis of Spatiotemporal Variations in Ecological Water-Supplementation Benefits of Rivers Based on Remote Sensing (QASViewSBR). Taking the Yongding River (Beijing section) from 2016 to 2023 as a case study, this research integrates multi-source remote sensing and ground monitoring data to extract river water bodies using an improved Normalized Difference Water Index and Vertical–Horizontal polarization characteristics. The Seasonal and Trend decomposition using Loess (STL) method was employed for time-series trend decomposition, Pearson correlation analysis was applied to identify driving factors of area changes, and the Pelt algorithm was used to quantify the response range of riparian vegetation to changes of river water levels. An integrated analytical framework of “dynamic monitoring—time series analysis—driving factor identification—spatial heterogeneity assessment” was established, enabling standardized end-to-end analysis from data acquisition to evaluation. The results indicate that the river water area in the basin increased significantly after 2019, with enhanced seasonal fluctuations. Under the ecological water supplementation policy, the “human-initiated, natural-response” mechanism was clearly observed, and the ecological responses along both riverbanks exhibited significant spatial heterogeneity due to variations in surface features and topography. QASViewSBR exhibits good universality and transferability, providing methodological support for ecological restoration and management in different river basins. Full article

Cybersecurity education requires practical activities such as malware analysis, phishing detection, and Capture the Flag (CTF) challenges. These exercises enable students to actively apply theoretical concepts in realistic scenarios, fostering experiential learning. This article introduces an innovative pedagogical approach relying on gamification in cybersecurity courses, combining technical problem-solving with human factors such as social engineering and risk-taking behavior. By integrating interactive challenges into the courses, engagement and motivation have been enhanced, while addressing both technological and managerial dimensions of cybersecurity. Observations from course implementation indicate that students demonstrate higher involvement when participating in supervised offensive security tasks and social engineering simulations within controlled environments. These findings highlight the potential of gamified strategies to strengthen cybersecurity competencies and promote ethical awareness, paving the way for future research on long-term cybersecurity learning outcomes. Full article

Maize is a water-intensive crop widely cultivated in temperate regions, where irrigation practices strongly influence its environmental performance. This study applies Life Cycle Assessment (LCA) to compare the environmental impacts of surface and drip irrigation for maize green silage production in the Po Valley (Italy), following ISO 14040/44 standards and adopting a cradle-to-farm-gate perspective. Results show that, compared to drip irrigation, surface irrigation leads to lower impacts in 14 out of 15 categories, with reductions ranging from −0.2% (marine eutrophication) to −61% (human toxicity, non-cancer), particularly for human toxicity and resource use due to lower diesel and infrastructure requirements. Conversely, drip irrigation achieves a 58% reduction in water use thanks to its higher irrigation efficiency. The single-score assessment highlights water use as the key differentiating factor, positioning drip irrigation as preferable under scenarios of water scarcity. Contribution and sensitivity analyses confirm that nitrogen fertiliser use and mechanisation are major hotspots, while yield variation (±30%) significantly affects the magnitude of results. These findings emphasise a clear trade-off: surface irrigation shows a lower environmental burden across most impact categories, whereas drip irrigation strongly reduces water scarcity impacts and provides robust, site-specific evidence to guide sustainable irrigation strategies in intensive maize systems. Full article

Dermatomycoses pose significant zoonotic and public health challenges, involving interactions among fungal agents, host immunity, and environmental reservoirs. Eight cases of dermatophyte infection involving five humans, two cats and one dog were investigated in the Umbria region applying a One-Health approach, as recommended by the CDC. Fungal isolates were identified by mycological and molecular methods as Microsporum canis (n = 4), Nannizzia gypsea (n = 3), and Trichophyton mentagrophytes var. mentagrophytes genotype III* (n = 1). The source of infection was identified in four cases enabling the implementation of appropriate treatment, removal of fomites, and environmental sanitization; as a result, no recurrences were observed. In the remaining cases, environmental assessments showed no fungal burden, indicating likely incidental transmission. Close cohabitation or contact with cats emerged as a risk factor. The patient’s medical history should always include exposure to animals in order to facilitate early recognition, correct management, and prevention. Interdisciplinary collaboration among dermatologists, veterinarians, and laboratory technicians is essential to optimize therapeutic outcomes and to prevent potential antifungal resistance phenomena. Moreover, continuous surveillance under a One-Health framework will enable better epidemiological understanding of dermatophyte species dynamics, particularly zoonotic agents. Full article

Despite ongoing advances in maritime safety research, ship accidents persist, with significant consequences for human life, marine ecosystems, and port operations. Because many accidents occur in or near ports, assessing a vessel’s ability to enter or depart safely remains critical. Although ports apply local navigational rules, safety criteria could be strengthened by adopting more adaptive and data-informed approaches. This study presents a mathematical framework that links Key Performance Indicators (KPIs) to a Ship Risk Profile (SRP) for collision/contact/grounding risk indication. Expert-based KPI importance weights were derived using the Average Rank Transformation into Weight method in linear (ARTIW-L) and nonlinear (ARTIW-N) forms and aggregated into a nominal SRP. Using routinely monitored KPIs largely drawn from the Baltic and International Maritime Council and Port State Control/flag-related measures, the results indicate that critical equipment and systems failures and human/organisational factors—particularly occupational health and safety and human resource management deficiencies—are the most influential contributors to the normalised accident-risk index. The proposed framework provides port authorities and maritime stakeholders with an interpretable basis for more proactive risk-informed decision-making and targeted safety improvements. Full article