Search Results (23,306)

The present review paper focuses on the peculiar environmental and health implications of fibrous amphibole “fluoro-edenite”, a new mineral first reported in Biancavilla (Etna Mount, Sicily, Italy). Its presence has been linked to an unusually high incidence of malignant pleural mesothelioma, as seen from national surveys during 1988–1997, marking the first case study of natural occurrence of fibrous amphibole in a volcanic context. Despite remediation efforts since the cessation of quarrying activities at the “Il Calvario” quarry, the risk of fiber exposure may extend beyond urban areas to surrounding soils and volcanic formation, not fully characterized yet. This review synthesizes relevant existing literature on mineralogical and chemical features of fluoro-edenite, while also enriching current understanding with new observations from optical microscopy, stereomicroscopy, and Scanning Electron Microscopy (SEM). Our analyses reveal the presence of fluoro-edenite amphibole not only in the altered samples but, significantly, within the massive rock samples. This finding expands its known distribution and offers initial consideration on public health implications related to massive lava rock, which crops out. This study highlights the importance of ongoing monitoring, detailed geological surveys, and further research into fiber occurrences and distribution in the volcanic systems, of which Mt. Etna represents the first case of natural occurrences, in order to fully assess their impact on public health. Full article

Background: Adolescence is a formative period for lifelong dietary patterns, yet Korean adolescents show low fruit and vegetable intake, high sugar and sodium consumption, and rising obesity, highlighting the importance of multidimensional assessment that integrates behavioral, cultural, environmental, and competency-related factors. Methods: A total of 1010 adolescents aged 12–18 years completed an online cross-sectional survey assessing food intake, dietary and physical activity behaviors, dietary culture, and Food Literacy (FL) competencies. Standardized scores were used for hierarchical and K-means clustering to identify dietary practice patterns, and between-cluster differences were examined using ANOVA. Correlation and regression analyses were conducted to examine associations between Dietary Guideline Adherence (DGA) and FL. Results: Four clusters were identified—selective intake–low support (20.4%), regular habits–unbalanced intake (33.3%), high adherence (23.2%), and low adherence (23.1%)—with significant differences in DGA total and domain scores (p < 0.001). The high-adherence cluster showed balanced intake, regular routines, and strong household support, whereas the low-adherence cluster showed poor diet quality, irregular behaviors, and lower socioeconomic status. FL differed across clusters (p < 0.001) and correlated with DGA (r = 0.496, p < 0.01). Total FL predicted DGA (β = 0.496, p < 0.001), explaining 25% of its variance (R² = 0.246). Conclusions: Adolescent diet quality appears to be associated with behavioral, cultural, and competency-related factors. These findings suggest that cluster-specific strategies—such as fat–sugar–sodium reduction, promotion of low-sodium and diverse diets, and maintenance of balanced-dietary patterns—may support tailored school- and community-based nutrition programs and inform further longitudinal and intervention research. Full article

Background/Objectives: Cyber bystanders can choose from several different strategies during cyberbullying incidents and have a significant effect on the situation. Hence, cyber bystanders are specifically targeted by prevention programmes and research investigating variables influencing cyber bystander responses is crucial for such programmes. The aim of our study was (1) to explore contextual factors’ effect on cyberbullying incidents’ perceived severity and (2) the most frequent cyber bystander responses. We also aimed (3) to learn how the context of cyberbullying incidents affects cyber bystander responses and the joint effect of individual and contextual variables on cyber bystander responses. Methods: In total, 314 Hungarian high school students participated in our online survey (mean age = 16.15, SD = 3.28). The respondents filled in self-administered questionnaires that measured cyber bystander responses, severity of different cyberbullying incidents, empathy, moral disengagement, social desirability, and cyberbullying engagement. Results: First, our results showed that the respondents perceived public and visual cyberbullying, and when the victim was upset by it the most severe incidents. Second, in almost every condition, the two most likely cyber bystander responses were ignorance and emotional support for the victim. Third, the individual and contextual variables had a joint effect influencing cyber bystander responses except for emotional support to the victim that was only influenced by individual variables, i.e., empathy, moral disengagement, and social desirability. Conclusions: All in all, our results showed that all cyberbullying contexts were associated with cyber bystander responses and the prominent association between moral disengagement, social desirability, empathy, and prosocial cyber bystander responses. Moreover, these results could guide cyberbullying prevention to focus on cyber bystanders’ empathy training, decreasing their moral disengagement, and educating them about the effects of online contextual variables. Full article

The integration of Artificial Intelligence (AI) in higher education offers a potential solution to the scalability of personalized learning, yet empirical frameworks connecting diagnostic data with teacher-mediated interventions remain limited in developing contexts. This study adopts a sequential multi-phase research design to address this gap. Phase 1 comprised a diagnostic quantitative analysis of the National Survey on Access and Permanence in Education (ENAPE 2021), involving a representative sample of 3422 Mexican undergraduate students. Using Exploratory Factor Analysis (KMO = 0.96) and Pearson correlations, the study established a structural baseline. Phase 2 implemented a quasi-experimental exploratory pilot (N = 23) across two academic clusters (Civil Engineering and Nutrition) using “ActivAI”, a custom GPT configured with Retrieval-Augmented Generation (RAG). Results from Phase 1 revealed a strong, statistically significant correlation ($r=0.72$, $p<0.01$) between the perceived impact of education on daily life and the perception of equity, identifying “relevance” as a key driver of accessibility. Phase 2 results demonstrated high student satisfaction with AI-driven personalization (M = 4.49, SD = 0.64), although disciplinary variations in engagement were observed (SD = 0.85 in Nutrition versus 0.45 in Engineering). The study concludes by proposing the Dynamic Integration Model, which leverages AI not as a replacement for instruction but as a scalability toolkit for teacher-led orchestration, ensuring that personalization addresses dynamic student needs rather than static learning styles. Full article

The rapid evolution of wireless communication toward Fifth Generation (5G) networks has enabled unprecedented performance improvement in terms of data rate, latency, reliability, sustainability, and connectivity. Recent years have witnessed an excessive deployment of new 5G networks worldwide. This deployment lead to an exponential growth in traffic flow and a massive number of connected devices requiring a new generation of energy-hungry base stations (BSs). This results in increased power consumption, higher operational costs, and greater environmental impact, making energy efficiency (EE) a critical research challenge. This paper presents a comprehensive survey of EE optimization strategies in 5G networks. It reviews the transition from traditional methods such as resources allocation, energy harvesting, BS sleep modes, and power control to modern artificial intelligence (AI)-driven solutions employing machine learning, deep reinforcement learning, and self-organizing networks (SON). Comparative analyses highlight the trade-offs between energy savings, network performance, and implementation complexity. Finally, the paper outlines key open issues and future directions toward sustainable 5G and beyond-5G (B5G/Sixth Generation (6G)) systems, emphasizing explainable AI, zero-energy communications, and holistic green network design. Full article

Invasive alien species pose a major threat to global biodiversity, especially within Europe. Understanding their spatial and temporal dynamics is essential for effective management planning and implementation. The ring-necked parakeet (Psittacula krameri, hereafter RNP) has been established in Greece for over four decades, yet its invasion dynamics remain unstudied despite pilling evidence of ecological impacts. During 2024 and 2025, we conducted repeated transect surveys across 99 1 km² grid squares within the urban complex of Thessaloniki to assess environmental factors influencing occupancy and abundance, and to estimate RNP population trends. Dynamic occupancy and N-mixture models revealed that both the presence and abundance of RNP were positively associated with the proportion of dense urban fabric and urban green areas. The proportion of occupied sites increased by more than 10% between survey years (2024–2025), while the estimated population growth rate for this interval was 1.64, signaling a substantial short-term increase. Our findings provide the first detailed evidence of an established and growing RNP population within the urban complex of Thessaloniki, Greece. Continued monitoring and research on ecological impacts are essential, while any management actions should be developed with public engagement to ensure social acceptance and long-term effectiveness. Full article

The article addresses the problem of the insufficient empirical recognition of the determinants of trust in artificial intelligence (AI) algorithms in organizations operating under conditions of sustainable development. The aim of the study was to identify the factors shaping organizational trust in AI and to examine how perceived trustworthiness, transparency, and effectiveness of algorithms influence their acceptance in the work environment. The research was conducted using a quantitative survey-based approach among organizational employees, which enabled the analysis of relationships between key variables and the identification of factors that strengthen or limit trust. The results indicate that algorithmic transparency, the reliability of generated outcomes, and the perceived effectiveness of AI applications significantly foster trust, whereas concerns related to errors and the decision-making autonomy of systems constitute important barriers to acceptance. Based on the findings, a conceptual and exploratory model of trust in AI was proposed, which may be used to diagnose the level of technology acceptance and to support the responsible implementation of artificial intelligence-based solutions in organizations. The contribution of the article lies in integrating organizational and technological perspectives and in providing an empirical approach to trust in AI within the context of sustainable development. Full article

Modern Earth observation combines high spatial resolution, wide swath, and dense temporal sampling, producing image grids and sequences far beyond the regime of standard vision benchmarks. Convolutional networks remain strong baselines but struggle to aggregate kilometre-scale context and long temporal dependencies without heavy tiling and downsampling, while Transformers incur quadratic costs in token count and often rely on aggressive patching or windowing. Recently proposed visual state-space models, typified by Mamba, offer linear-time sequence processing with selective recurrence and have therefore attracted rapid interest in remote sensing. This survey analyses how far that promise is realised in practice. We first review the theoretical substrates of state-space models and the role of scanning and serialization when mapping two- and three-dimensional EO data onto one-dimensional sequences. A taxonomy of scan paths and architectural hybrids is then developed, covering centre-focused and geometry-aware trajectories, CNN– and Transformer–Mamba backbones, and multimodal designs for hyperspectral, multisource fusion, segmentation, detection, restoration, and domain-specific scientific applications. Building on this evidence, we delineate the task regimes in which Mamba is empirically warranted—very long sequences, large tiles, or complex degradations—and those in which simpler operators or conventional attention remain competitive. Finally, we discuss green computing, numerical stability, and reproducibility, and outline directions for physics-informed state-space models and remote-sensing-specific foundation architectures. Overall, the survey argues that Mamba should be used as a targeted, scan-aware component in EO pipelines rather than a drop-in replacement for existing backbones, and aims to provide concrete design principles for future remote sensing research and operational practice. Full article

Cultivating a green innovation-oriented work climate exerts a positive effect on employees’ participation in green knowledge sharing and other co-creation behaviors. Previous studies analyzed the influential factors of green value co-creation from the perspective of green motivation and green dynamic capabilities, but there is a lack of research on the antecedents of green value co-creation from the perspective of green innovation climate. Therefore, based on the social information processing theory, this paper make an in-depth research on the impact mechanism of green innovation climate on employee green value co-creation, through perception of corporate social responsibility and employees’ sense of belonging. A questionnaire survey was conducted on Chinese enterprises implementing green innovation, and 337 valid questionnaires were collected. The effect mechanism of green innovation climate on employees’ green value co-creation was analyzed by the hierarchical regression analysis method. Process regression analysis was used to explore the moderating effect of inclusive leadership. The result of the research shows that green innovation climate has a significant relation to employees’ sense of belonging, perception of corporate social responsibility and employees’ sense of belonging. Perception of corporate social responsibility and employees’ sense of belonging have mediating effects on the relations between green innovation climate and employees’ green value co-creation. Inclusive leadership can moderate the relationship between perception of corporate social responsibility and employees’ green value co-creation. In theory, from the perspectives of green innovation climate and inclusive leadership, it further enriches the research on the driving factors of green value co-creation. In practice, It provides a theoretical reference for enterprises to utilize the strategy of green innovation climate and inclusive leadership to promote green value co-creation of enterprises effectively. Full article

Background: Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder, with a prevalence of approximately 16% in Saudi Arabia. PCOS is associated with various health complications. Assessing the quality of life (QoL) of women with PCOS is crucial for effective management. Objectives: This study aims to translate and validate the Polycystic Ovary Syndrome Quality of Life scale (PCOSQOL) into Arabic for use among Arabic-speaking women. The study was designed to evaluate the psychometric properties of the Arabic PCOSQOL, including its reliability, validity, and responsiveness. Methods: A cross-sectional study was conducted among 207 Saudi women diagnosed with PCOS. Participants were recruited from family medicine and obstetrics and gynecology clinics at King Saud University Medical City, Riyadh, through an online survey. The PCOSQOL was translated into Arabic following the World Health Organization’s (WHO) forward–backward translation protocol. Psychometric evaluation included internal consistency, test–retest reliability (ICC), and construct validity. Results: The Arabic PCOSQOL demonstrated excellent psychometric performance, with high internal consistency (Cronbach’s α = 0.951) and good-to-excellent test–retest reliability (ICC = 0.760–0.885). Construct validity was supported by a four-factor structure explaining 62.5% of the total variance (KMO = 0.92; Bartlett’s p < 0.001). The subscales showed strong factor loadings (0.49–0.97). Older women (>25 years), married participants, and residents of the western and central regions reported significantly better quality of life (p < 0.05). Conclusions: The Arabic version of the PCOSQOL demonstrated excellent reliability, validity, and stability, confirming its suitability for assessing quality of life among Arabic-speaking women with PCOS. This validated tool can support both clinical practice and future research across Arabic populations. Full article

With the development of 6G technology, conventional wireless communication systems are increasingly unable to meet stringent performance requirements in complex and dynamic environments. Therefore, integrated sensing and communication (ISAC), which enables efficient spectrum sharing, has attracted growing attention as a promising solution. This paper provides a comprehensive survey of reconfigurable intelligent surface (RIS)-unmanned aerial vehicle (UAV)-assisted ISAC systems. It first introduces a four-dimensional quantitative evaluation framework grounded in information theory. Then, we provide a structured overview of coordination mechanisms between different types of RIS and UAV platforms within ISAC architectures. Furthermore, we analyze the application characteristics of various multiple access schemes in these systems. Finally, the main technical challenges and potential future research directions are discussed and analyzed. Full article

Background/Objective: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have received widespread attention as effective obesity treatments. However, limited research has examined the perspectives of patients contemplating GLP-1RAs. This study explored perceptions, motivations, and barriers among individuals considering GLP-1RA therapy for obesity treatment, with the goal of informing patient-centered care and enhancing clinician engagement. Methods: Adults completed surveys and interviews between June and November 2025. In this pragmatic mixed-methods study, both survey and interview questions explored perceived benefits, barriers, and decision-making processes. Qualitative data, describing themes based on the Health Belief Model, were analyzed using Dedoose (version 9.0.107), and quantitative data were analyzed using SAS (version 9.4). Participant characteristics included marital status, income, educational attainment, employment status, insurance status, age, race/ethnicity, and sex. Anticipated length on GLP-1RA medication and selected self-reported health conditions (depression, anxiety, hypertension, heart disease, back pain, joint pain), reported physical activity level, and perceived weight loss competency were also recorded. Results: Among the 31 non-diabetic participants who were considering GLP-1RA medication for weight loss, cost emerged as the most significant barrier. Life course events, particularly (peri)menopause among women over 44, were commonly cited as contributors to weight gain. Participants expressed uncertainty about eligibility, long-term safety, and treatment expectations. Communication gaps were evident, as few participants initiated discussions and clinician outreach was rare, reflecting limited awareness and discomfort around the topic. Conclusions: Findings highlight that individuals considering GLP-1RA therapy face multifaceted emotional, financial, and informational barriers. Proactive, empathetic clinician engagement, through validation of prior efforts, clear communication of risks and benefits, and correction of misconceptions, can support informed decision-making and align treatment with patient goals. Full article

Bio-electric fields—manifested as Electroencephalogram (EEG), Electrocardiogram (ECG), Electromyogram (EMG), and Electrooculogram (EOG)—are fundamental to modern medical diagnostics but often suffer from severe data imbalance, scarcity, and environmental noise. Generative Adversarial Networks (GANs) offer a powerful, nonlinear solution to these modeling hurdles. This review presents a comprehensive survey of GAN methodologies specifically tailored for bio-electric signal processing. We first establish a theoretical foundation by detailing GAN principles, training mechanisms, and critical structural variants, including advancements in loss functions and conditional architectures. Subsequently, the paper extensively analyzes applications ranging from high-fidelity signal synthesis and noise reduction to multi-class classification. Special attention is given to clinical anomaly detection, specifically covering epilepsy, arrhythmia, depression, and sleep apnea. Furthermore, we explore emerging applications such as modal transformation, Brain–Computer Interfaces (BCI), de-identification for privacy, and signal reconstruction. Finally, we critically evaluate the computational trade-offs and stability issues inherent in current models. The study concludes by delineating prospective research avenues, emphasizing the necessity of interdisciplinary synergy to advance personalized medicine and intelligent diagnostic systems. Full article

Grounded in the Theory of Planned Behavior (TPB), this study examines how perceived educational support influences entrepreneurial intentions among university students in India and the People’s Republic of China (PRC), through the mediating effects of entrepreneurial attitude, subjective norms, and perceived behavioral control. It further explores how gender and cultural context moderate these relationships, extending the TPB into cross-cultural and gendered domains. Using survey data from 734 undergraduate students, structural equation modeling was employed to test the proposed model. The results reveal that perceived educational support significantly enhances entrepreneurial attitude, subjective norms, and perceived behavioral control in both contexts, although the magnitude and pathways differ across gender and country. Entrepreneurial attitude and perceived behavioral control emerge as consistent predictors of entrepreneurial intention, while subjective norms exert a greater influence for Indian women. These results highlight that entrepreneurial intentions are culturally and gender-contingent, challenging TPB’s universal applicability. The study advances TPB-based entrepreneurship research by embedding perceived educational support within a contextualized, gender-sensitive framework, contributing to a deeper understanding of entrepreneurship education in Asia. These insights can guide universities and policymakers in designing entrepreneurship education that fosters inclusive innovation across diverse cultural contexts. Full article

Insufficient investment in wildlife that lacks strong aesthetic or emotional appeal to humans poses a significant obstacle to achieving broader conservation goals. Species that are not considered charismatic are nonetheless vital to ecosystems and deserve attention from conservationists, researchers, and the public. However, effective strategies for bridging the gap between these species and traditionally charismatic ones remain underexplored. Our exploratory study introduced the concept of charisma orientations to examine their influence on pro-bird behaviors, such as following guidelines, reporting disturbances, and participating in community advocacy. We identified six relational and socially negotiated orientations—ecological importance, intrinsic right to exist, protection support, affective meaning, and perceived decline—that together represent key perspectives through which waterbirds are understood. A survey of 615 Texas coastal recreationists revealed that relying solely on positive charisma diminishes the appeal of waterbirds for participants. The species likeability frame was relevant only in the context of reporting disturbances, while a moral policy stance (the belief that waterbirds need protection) was significant in predicting advocacy. Younger males and individuals who felt current regulations were adequate were less likely to engage in waterbird conservation behaviors. Our findings suggest that examining the intersection of contested charismatic species and various charisma orientations can uncover subtle nuances often overlooked due to an overemphasis on positive charisma and emotional resonance, which may only partially apply or not apply at all. Full article