Search Results (255)

The rise in online communication platforms has significantly increased exposure to harmful discourse, presenting ongoing challenges for digital moderation and user well-being. This paper introduces the EsCorpiusBias corpus, designed to enhance the automated detection of sexism and racism within Spanish-language online dialogue, specifically sourced from the Mediavida forum. By means of a systematic, context-sensitive annotation protocol, approximately 1000 three-turn dialogue units per bias category are annotated, ensuring the nuanced recognition of pragmatic and conversational subtleties. Here, annotation guidelines are meticulously developed, covering explicit and implicit manifestations of sexism and racism. Annotations are performed using the Prodigy tool (v1. 16.0) resulting in moderate to substantial inter-annotator agreement (Cohen’s Kappa: 0.55 for sexism and 0.79 for racism). Models including logistic regression, SpaCy’s baseline n-gram bag-of-words model, and transformer-based BETO are trained and evaluated, demonstrating that contextualized transformer-based approaches significantly outperform baseline and general-purpose models. Notably, the single-turn BETO model achieves an ROC-AUC of 0.94 for racism detection, while the contextual BETO model reaches an ROC-AUC of 0.87 for sexism detection, highlighting BETO’s superior effectiveness in capturing nuanced bias in online dialogues. Additionally, lexical overlap analyses indicate a strong reliance on explicit lexical indicators, highlighting limitations in handling implicit biases. This research underscores the importance of contextually grounded, domain-specific fine-tuning for effective automated detection of toxicity, providing robust resources and methodologies to foster socially responsible NLP systems within Spanish-speaking online communities. Full article

Soil acidification, salinization, and heavy metal pollution pose serious threats to global food security and sustainable agricultural development. Biochar, with its high porosity, large surface area, and abundant functional groups, can effectively improve soil properties. However, due to variations in feedstocks and pyrolysis conditions, it may contain potentially harmful substances. Industrial wastes such as fly ash, steel slag, red mud, and phosphogypsum are rich in minerals and show potential for soil improvement, but direct application may pose environmental risks. The co-application of biochar with these wastes can produce composite amendments that enhance pH buffering capacity, nutrient availability, and pollutant immobilization. Therefore, a review of biochar-industrial waste composites as soil amendments is crucial for addressing soil degradation and promoting resource utilization of wastes. In this study, the literature was retrieved from Web of Science, Scopus, and Google Scholar using keywords including biochar, fly ash, steel slag, red mud, phosphogypsum, combined application, and soil amendment. A total of 144 articles from 2000 to 2025 were analyzed. This review summarizes the physicochemical properties of biochar and representative industrial wastes, including pH, electrical conductivity, surface area, and elemental composition. It examines their synergistic mechanisms in reducing heavy metal release through adsorption, complexation, and ion exchange. Furthermore, it evaluates the effects of these composites on soil health and crop productivity, showing improvements in soil structure, nutrient balance, enzyme activity, and metal immobilization. Finally, it identifies knowledge gaps as well as future prospects and recommends long-term field trials and digital agriculture technologies to support the sustainable application of these composites in soil management. Full article

Rice wine, as a traditional fermented beverage, has its quality and flavor influenced by a combination of multiple factors. This review provides an overview of the key aspects of rice wine production, including raw material selection and processing, the regulation of quality by brewing techniques, the mechanisms of microbial community interaction during fermentation, and the types and formation mechanisms of major compounds in rice wine (including flavor compounds and non-volatile components). The study highlights that different raw materials and processing methods significantly impact the fundamental flavor profile of rice wine, while fermentation conditions and dynamic changes in microbial communities determine its flavor complexity and stability. Additionally, this review examines various factors affecting the quality and flavor of rice wine, such as fermentation environment, microbial metabolism, and control of harmful substances, and summarizes modern research and technological advancements, emphasizing the potential of digital and intelligent technologies in enhancing the quality and safety of rice wine. Finally, future research directions are proposed to promote modernization and quality improvement of the rice wine industry. Full article

In order to address the pressing challenge posed by the proliferation of fake news in the digital age, we emphasize its profound and harmful impact on societal structures, including the misguidance of public opinion, the erosion of social trust, and the exacerbation of social polarization. Current fake news detection methods are largely limited to superficial text analysis or basic text–image integration, which face significant limitations in accurately identifying deceptive information. To bridge this gap, we propose the UC-CMAF framework, which comprehensively integrates news text, images, and user comments through an adaptive co-attention fusion mechanism. The UC-CMAF workflow consists of four key subprocesses: multimodal feature extraction, cross-modal adaptive collaborative attention fusion of news text and images, cross-modal attention fusion of user comments with news text and images, and finally, input of fusion features into a fake news detector. Specifically, we introduce multi-head cross-modal attention heatmaps and comment importance visualizations to provide interpretability support for the model’s predictions, revealing key semantic areas and user perspectives that influence judgments. Through the cross-modal adaptive collaborative attention mechanism, UC-CMAF achieves deep semantic alignment between news text and images and uses social signals from user comments to build an enhanced credibility evaluation path, offering a new paradigm for interpretable fake information detection. Experimental results demonstrate that UC-CMAF consistently outperforms 15 baseline models across two benchmark datasets, achieving F1 Scores of 0.894 and 0.909. These results validate the effectiveness of its adaptive cross-modal attention mechanism and the incorporation of user comments in enhancing both detection accuracy and interpretability. Full article

This study aimed to explore how social media usage influenced both parent and adolescent mental health and social identity during and after the COVID-19 pandemic through the theoretical foundational lens of social comparison theory. In-depth interviews with 24 mothers of adolescent children (ages 10–19) were conducted to address the research questions. Qualitative thematic analysis of the interview transcripts revealed eight emerging themes: (1) learning and entertainment, (2) maternal fears related to content binging and cyberbullying, (3) finding connection and comfort through social media during the pandemic, (4) ongoing digital care work as lasting maternal labor, (5) iterative dialogue: platform restrictions and content curation boundaries, (6) upward and downward social comparison, (7) fear of missing out (FoMO), and (8) third-person perception (TPP). The findings show that mothers perceive social media usage as either beneficial or harmful among adolescents (their children); upward and downward social comparison via social media exhibits more dynamic mechanisms. Moreover, this study enhances our theoretical understanding by linking social media usage to social identity, social comparison, and mental health during a global health crisis. Full article

The reduction of environmental pollutant emissions—including greenhouse gases, particulate matter, and other harmful substances—represents one of the foremost challenges in climate policy, economics, and industrial management today. Excessive emissions of CO₂, NO_X, and suspended particulates exert significant impacts on climate change as well as human health and welfare. Consequently, numerous studies and regulatory and technological initiatives are underway to mitigate these emissions. One critical area is intra-plant transport within manufacturing facilities, which, despite its localized scope, can substantially contribute to a company’s total emissions. This paper aims to assess the potential of computer simulation using FlexSim software as a decision-support tool for planning inter-operational transport, with a particular focus on environmental aspects. The study analyzes real operational data from a selected production plant (case study), concentrating on the optimization of the number of transport units, their routing, and the layout of workstations. It is hypothesized that reducing the number of trips, shortening transport routes, and efficiently utilizing transport resources can lead to lower emissions of carbon dioxide (CO₂) and nitrogen oxides (NO_X). The findings provide a basis for a broader adoption of digital tools in sustainable production planning, emphasizing the integration of environmental criteria into decision-making processes. Furthermore, the results offer a foundation for future analyses that consider the development of green transport technologies—such as electric and hydrogen-powered vehicles—in the context of their implementation in the internal logistics of manufacturing enterprises. Full article

Social media refers to digital platforms that enable users to create, share, and engage with content within virtual communities. Platforms like Facebook, X, Instagram, and TikTok have democratized content creation, allowing individuals to share ideas, opinions, and experiences with global audiences. Social media has revolutionized the way information is shared and consumed, offering unprecedented opportunities for learning, engagement, and democratic participation. However, this accessibility comes with significant ethical challenges, particularly centered around the paradox of freedom versus harm—the tension between upholding freedom of expression and mitigating the harms of misinformation, privacy violations, and AI-driven bias. This entry explores the dilemmas and opportunities associated with social media, examining how these platforms shape public discourse, influence consumer behavior, and challenge traditional notions of truth and accountability. It aims to provide policymakers, educators, and platform designers with actionable insights to foster ethical social media environments. Full article

An increasing number of scholars are raising concerns about the sustainability of digital health, calling for action to prevent its harmful effects on the environment. At this point, however, the comprehensive appraisal of emerging technology in the health sector remains theoretically challenging, and highly difficult to implement in practice and in ecological design. Indeed, background factors such as the rapid evolution of technology or effectiveness–efficiency tradeoffs complicate the task of distinguishing the benefits of digital health from its drawbacks, rendering early Health Technology Sustainability Assessment (HTSA) extremely complex. Within this context, the aim of this article is to draw attention to the pragmatism that should be adopted when anticipating the sustainability of technological innovation in the medical field, while simultaneously proposing an assessment framework grounded in a structural and conceptual dissection of the fundamental purpose of smart technologies and the Internet of Medical Things (IoMT). Building on this, we demonstrate how our framework can be strategically applied through a rapid back-of-the-envelope assessment of the economic and ecological balance when introducing IoMT prototypes for treating a specific condition, based on a preliminary simulation of a defined clinical outcome. In this manner, the article presents evidence that challenges two primary hypotheses, and also encourages reflection on the central role of information and its interpretation when addressing key barriers in the HTSA of digital health. Thereby, it contributes to advancing cost–benefit and cost-effectiveness evaluation tools that support eco design strategies and guide informed decision-making regarding the integration of sustainable IoMT systems into healthcare. Full article

Online safety guidance is frequently delivered as a specialist technology issue without considering adolescents’ home lives, offline vulnerabilities, or wellbeing. Yet, while the digital world offers connection, autonomy, and entertainment, vulnerable teens also encounter more violent content, sexual exploitation, and content concerning body image, self-harm or suicide than their non-vulnerable peers. Many struggle with social inclusion or less engaged and credible caregiver e-safety support, which may contribute to their negative experiences online. To improve their online safety and resilience, caregivers and educators might consider offline factors that can mediate exposure to online harms. This study compared the experiences of 213 adolescents with family vulnerabilities to 213 age- and gender-matched non-vulnerable adolescents. The contribution of (a) e-safety education, (b) close friendships, (c) a trusted adult at school, and (d) life-affecting worry was considered. No differences were found for exposure to, or engagement with, e-safety education. However, despite having received e-safety education, those with family vulnerabilities were more at risk of encountering severe online harms. This was mediated by life-affecting worry and parental e-safety guidance. These findings provide unique insights into the impact of family vulnerabilities on adolescents’ exposure to online harms and suggest a more holistic intervention framework for caregivers. Full article

Nitric oxide (NO) is a well-known member of the reactive oxygen species (ROS) family. The extent of its concentration influences whether it produces beneficial physiological effects or harmful toxic reactions. In a blood system, NO is generally produced by nitric oxide synthase (NOS) in the endothelium. Then, it diffuses into the smooth muscle wall causing a vasodilatation, and it can also be diluted in a lumen blood stream. In the present study, we analyzed a convectional reaction–diffusion of NO in a 3D digital phantom of a short segment of small arteries. NO concentrations were analyzed by applying numerical solutions to the boundary problems, which included the Navier–Stokes equation, Darcy’s law, varying consumption of NO, and the dependence of NOS activity on shear stress. All the boundary problems were evaluated using COMSOL Multiphysics software ver. 5.5. The role of two diffusive barriers surrounding the endothelium producing NO was theoretically proven. When the eNOS rate remains unchanged, an increase in the fenestration of the internal elastic lamina (IEL) and a decrease in the diffusive permeability of a thin layer of endothelial surface glycocalyx (ESG) lead to a notable rise in the NO concentration in the vascular wall. The alterations in pore count in IEL and the viscosity of ESG are considered to be involved in the physiological and pathological regulation of NO concentrations. Full article

The rapid progress of generative AI has enabled remarkable creative capabilities, yet it also raises urgent concerns regarding the safety of AI-generated visual content in real-world applications such as content moderation, platform governance, and digital media regulation. This includes unsafe material such as sexually explicit images, violent scenes, hate symbols, propaganda, and unauthorized imitations of copyrighted artworks. Existing image safety systems often rely on rigid category filters and produce binary outputs, lacking the capacity to interpret context or reason about nuanced, adversarially induced forms of harm. In addition, standard evaluation metrics (e.g., attack success rate) fail to capture the semantic severity and dynamic progression of toxicity. To address these limitations, we propose Perception–Retrieval–Judgement (PRJ), a cognitively inspired framework that models toxicity detection as a structured reasoning process. PRJ follows a three-stage design: it first transforms an image into descriptive language (perception), then retrieves external knowledge related to harm categories and traits (retrieval), and finally evaluates toxicity based on legal or normative rules (judgement). This language-centric structure enables the system to detect both explicit and implicit harms with improved interpretability and categorical granularity. In addition, we introduce a dynamic scoring mechanism based on a contextual toxicity risk matrix to quantify harmfulness across different semantic dimensions. Experiments show that PRJ surpasses existing safety checkers in detection accuracy and robustness while uniquely supporting structured category-level toxicity interpretation. Full article

The rapid adoption of artificial intelligence (AI) within social media platforms has fundamentally transformed the way Generation Z interacts with and navigates the digital landscape. While AI-driven algorithms enhance user experience through content personalization, they can also reinforce biases that affect the mental health and overall well-being of young individuals. This review delves into the intersections of AI bias, social medial engagement, and youth mental health, with a particular focus on how algorithmic decision-making influences exposure to harmful content, intensifies social comparison and spreads digital misinformation. By addressing these aspects, this article highlights both the risks and opportunities presented by AI-powered social media. It also advocates for evidence-based strategies to mitigate the harms associated with algorithmic bias, urging collaboration among AI developers, mental health experts, policymakers and educators at personal, community (school), and national and international levels to cultivate a safer, more supportive digital ecosystem for future generations. Full article

In the current information era, even preschool children are unable to withstand the “digital flood”. However, excessive exposure to electronic screens not only negatively impacts various aspects of children’s health and adaptation, but also harms family relationships. Based on family systems theory, social–cognitive learning theory, and attachment theory, this study examines the relationships between co-parenting and preschoolers’ problematic media use, as well as the underlying mechanism—the mediating role of parental phubbing and the moderating effect of secure attachment. A sample of 610 parents of preschoolers from three kindergartens in central China completed validated scales, including the Co-Parenting Scale, Parental Phubbing Scale, Children’s Electronic Media Use Questionnaire, and Secure Attachment Dimension of the Waters Attachment Q-sort. A moderated mediation model was tested using the PROCESS macro with bootstrap procedures. The results showed that, after controlling for the subjective family socioeconomic status and parental education level, (1) co-parenting was negatively associated with preschoolers’ problematic media use; (2) parental phubbing significantly mediated the relationship between co-parenting and preschoolers’ problematic media use; (3) secure attachment significantly moderated both the direct relation between co-parenting and the preschoolers’ problematic media use and the mediating effect of parental phubbing (the relation between parental phubbing and children’s problematic media use); furthermore, both of these effects were more pronounced in children with lower levels of secure attachment. These findings extend family systems and attachment theories by elucidating mechanisms underlying early media behaviors. Practically, interventions should promote collaborative co-parenting and reduce parental phubbing to mitigate children’s problematic media use, while fostering secure attachment to buffer digital risks. Full article

We are confronted with an urgent imperative to transition from merely minimizing harm to developing sustainable, regenerative, and net-positive solutions that systematically restore ecosystems, achieve decarbonization, and enhance health outcomes. This study presents a phased Digital Sustainable Regenerative Design Studio framework, which was implemented in a third-year architecture studio at the Canadian University of Dubai. This methodology incorporates bespoke environmental simulation tools alongside quantitative metrics for climate adaptation, biodiversity, carbon sequestration, and health outcomes to inform creative design solutions. The students devised interventions across 20 urban plots in Dubai. A comprehensive analysis, encompassing real-time engagement with computational tools, reflective journals, feedback sessions, project analysis, and surveys, was conducted to assess the framework’s effectiveness in enhancing students’ comprehension of regenerative design and to examine their responses to complex, interdisciplinary challenges. Key findings reveal improved student performance in applying regenerative design principles and the formulation of strategies for climate-adaptive urbanism. The results suggest that this educational framework has the potential to influence and enhance pedagogical approaches, fostering architects committed to advancing sustainable, regenerative, and climate-adaptive urbanism. Full article

Construction remains one of the most hazardous industries, consistently reporting high rates of workplace injuries and fatalities. Despite advancements in safety regulations and technologies, significant risks persist due to hazardous tasks, including working at heights, operating heavy machinery, and exposure to harmful materials. The establishment of the Occupational Safety and Health Administration in 1971 marked a significant turning point in construction safety, resulting in a decline in workplace fatalities. However, evolving construction methodologies and digital transformations demand continuous research to enhance worker protection and mitigate emerging risks. This study conducts a longitudinal bibliometric analysis to examine the evolution of construction safety research from 1972 to 2025. Using a dataset of 14,174 journal publications from Scopus, the analysis identifies key research trends, technological advancements, and regulatory shifts that have shaped the field. Findings reveal a transition from basic safety regulations to AI-driven hazard detection, digital twins, and IoT-enabled safety monitoring. The study also identifies key contributors, including prominent countries. By tracing both historical and contemporary research trends, this study offers insights into knowledge gaps and provides guidance on future directions. The findings provide valuable insights for researchers, policymakers, and industry professionals, supporting the development of research-informed safety strategies and the integration of emerging technologies in an increasingly complex industry. Full article