Search Results (493)

This study examines the impacts of climate change on fisheries and aquaculture in Bangladesh, one of the most climate-vulnerable countries in the world. The fisheries and aquaculture sectors contribute significantly to the national GDP and support the livelihoods of 12% of the total population. Using a Critical Literature Review (CLR) approach, peer-reviewed articles, government reports, and official datasets published between 2006 and 2025 were reviewed across databases such as Scopus, Web of Science, FAO, and the Bangladesh Department of Fisheries (DoF). The analysis identifies major climate drivers, including rising temperature, erratic rainfall, salinity intrusion, sea-level rise, floods, droughts, cyclones, and extreme events, and reviews their differentiated impacts on key components of the sector: inland capture fisheries, marine fisheries, and aquaculture systems. For inland capture fisheries, the review highlights habitat degradation, biodiversity loss, and disrupted fish migration and breeding cycles. In aquaculture, particularly in coastal systems, this study reviews the challenges posed by disease outbreaks, water quality deterioration, and disruptions in seed supply, affecting species such as carp, tilapia, pangasius, and shrimp. Coastal aquaculture is also particularly vulnerable to cyclones, tidal surges, and saline water intrusion, with documented economic losses from events such as Cyclones Yaas, Bulbul, Amphan, and Remal. The study synthesizes key findings related to climate-resilient aquaculture practices, monitoring frameworks, ecosystem-based approaches, and community-based adaptation strategies. It underscores the need for targeted interventions, especially in coastal areas facing increasing salinity levels and frequent storms. This study calls for collective action through policy interventions, research and development, and the promotion of climate-smart technologies to enhance resilience and sustain fisheries and aquaculture in the context of a rapidly changing climate. Full article

The recent growth of generative artificial intelligence (AI) has brought new possibilities and revolutionary applications in many fields. It has also, however, created important ethical and security issues, especially with the abusive use of deepfakes, which are artificial media that can propagate very realistic but false information. This paper provides an extensive bibliometric, statistical, and trend analysis of deepfake research in the age of generative AI. Utilizing the Web of Science (WoS) database for the years 2014–2024, the research identifies key authors, influential publications, collaboration networks, and leading institutions. Biblioshiny (Bibliometrix R package, University of Naples Federico II, Naples, Italy) and VOSviewer (version 1.6.20, Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands) are utilized in the research for mapping the science production, theme development, and geographical distribution. The cutoff point of ten keyword frequencies by occurrence was applied to the data for relevance. This study aims to provide a comprehensive snapshot of the research status, identify gaps in the knowledge, and direct upcoming studies in the creation, detection, and mitigation of deepfakes. The study is intended to help researchers, developers, and policymakers understand the trajectory and impact of deepfake technology, supporting innovation and governance strategies. The findings highlight a strong average annual growth rate of 61.94% in publications between 2014 and 2024, with China, the United States, and India as leading contributors, IEEE Access among the most influential sources, and three dominant clusters emerging around disinformation, generative models, and detection methods. Full article

Smart tourism destinations, shaped by the integration of tourism and information technology, have become a central theme in international academic research. This study employs bibliometric methods using CiteSpace to conduct co-authorship, co-citation, keyword co-occurrence, and burst analyses, with the aim of mapping the knowledge structure and research evolution of the field. Drawing on 232 articles from the Web of Science Core Collection (2013–2025), the results reveal a shift from technology-centered approaches toward themes of visitor experience, collaborative governance, and sustainable development. The Universitat d’Alacant (Spain) and The Hong Kong Polytechnic University (China) have emerged as leading research hubs, with Ivars-Baidal and colleagues as major contributors. Foundational studies by Buhalis and Gretzel continue to shape the domain. Keyword trends highlight increasing attention to technological efficiency and sustainable ethics. Overall, the study traces the developmental trajectory of smart tourism destinations, proposes a systematic knowledge framework, and identifies future directions for theoretical integration and methodological innovation. The findings provide both conceptual insights for academic research and strategic guidance for destination governance and policy. Full article

Humanized mouse models offer human-specific platforms for investigating complex host–pathogen interactions, addressing shortcomings of conventional preclinical models that often fail to replicate human immune responses accurately. This integrative review examines the intersection of advanced morphological phenotyping and artificial intelligence (AI) to enhance predictive capacity and translational relevance in infectious disease research. A structured literature search was conducted across PubMed, Scopus, and Web of Science (2010–2025), applying defined inclusion and exclusion criteria. Evidence synthesis highlights imaging modalities, AI-driven phenotyping, and standardization strategies, supported by comparative analyses and quality considerations. Persistent challenges include variability in engraftment, lack of harmonized scoring systems, and ethical governance. We propose recommendations for standardized protocols, risk-of-bias mitigation, and collaborative training frameworks to accelerate adoption of these technologies in translational medicine. Full article

Emerging pollutants (EPs) associated with the petroleum industry present considerable challenges to environmental management and sustainable development. To support sustainable development and improve the control of EPs in the petroleum industry, this review systematically examines the functional uses of EPs as chemical additives across the entire petroleum supply chain—from extraction and transportation to refining and product blending. It also summarizes the environmental emissions, health impacts, mitigation strategies, and current regulatory frameworks of EPs. In addition, some challenges have been found, namely unclear data on EPs in chemical additives, insufficient attention to high-risk areas, undefined health risks of mixing EPs, lack of green assessment of alternative technologies, and regional policy disparities, which collectively hinder the effective prevention and management ofEPs. In response, we propose future perspectives including enhanced screening and substitution of high-EP-risk additives, development of source-specific fingerprinting techniques, expanded monitoring of mixed contaminants and understudied regions, accelerated deployment of green technologies, and strengthened global cooperation under sustainability-oriented governance frameworks. This study underscores the necessity of integrated, science-based approaches to align petroleum industry practices with global sustainability goals. This review underscores the critical need for a proactive and integrated approach toward the sustainable development of the petroleum industry through the control of and reduction in EPs. Full article

Nanotechnology has become a transformative field in modern science and engineering, offering innovative approaches to enhance conventional thermal and fluid systems. Heat and mass transfer phenomena, particularly fluid motion across various geometries, play a crucial role in industrial and engineering processes. The inclusion of nanoparticles in base fluids significantly improves thermal conductivity and enables advanced phase-change technologies. The current work examines Powell–Eyring nanofluid’s heat transmission properties on a stretched Riga plate, considering the effects of magnetic fields, porosity, Darcy–Forchheimer flow, thermal radiation, and activation energy. Using the proper similarity transformations, the pertinent governing boundary-layer equations are converted into a set of ordinary differential equations (ODEs), which are then solved using the boundary value problem fourth-order collocation (BVP4C) technique in the MATLAB program. Tables and graphs are used to display the outcomes. Due to their significance in the industrial domain, the Nusselt number and skin friction are also evaluated. The velocity of the nanofluid is shown to decline with a boost in the Hartmann number, porosity, and Darcy–Forchheimer parameter values. Moreover, its energy curves are increased by boosting the values of thermal radiation and the Biot number. A stronger Hartmann number M decelerates the flow (thickening the momentum boundary layer), whereas increasing the Riga forcing parameter Q can locally enhance the near-wall velocity due to wall-parallel Lorentz forcing. Visual comparisons and numerical simulations are used to validate the results, confirming the durability and reliability of the suggested approach. By using a systematic design technique that includes training, testing, and validation, the fluid dynamics problem is solved. The model’s performance and generalization across many circumstances are assessed. In this work, an artificial neural network (ANN) architecture comprising two hidden layers is employed. The model is trained with the Levenberg–Marquardt scheme on reliable numerical datasets, enabling enhanced prediction capability and computational efficiency. The ANN demonstrates exceptional accuracy, with regression coefficients $R\approx 1.0$ and the best validation mean squared errors of $8.52\times {10}^{-10}$, $7.91\times {10}^{-9}$, and $1.59\times {10}^{-8}$ for the Powell–Eyring, heat radiation, and thermophoresis models, respectively. The ANN-predicted velocity, temperature, and concentration profiles show good agreement with numerical findings, with only minor differences in insignificant areas, establishing the ANN as a credible surrogate for quick parametric assessment and refinement in magnetohydrodynamic (MHD) nanofluid heat transfer systems. Full article

As artificial intelligence (AI) technologies are increasingly integrated into emergency management, ethical considerations demand greater attention. Essential components of comprehensive emergency management include mitigation, preparedness, response, and recovery, which should serve as the foundation for integrating AI-driven science and technologies to effectively safeguard populations and infrastructure in times of crisis. This paper reviewed the ethical challenges of AI in emergency management in terms of critical issues, best practices, applications, emerging ethical considerations, and strategies addressing ethical challenges. Three core ethical themes are identified: algorithmic bias; privacy, transparency and accountability; and human–AI collaboration. This paper thoroughly analyzed the associated ethical challenges, reviewed the theoretical frameworks and proposed strategies to mitigate ethical challenges by strengthening the audits of algorithms, enhancing transparency in AI decision-making, and incorporating stakeholder engagement. Finally, the importance of creating policies to govern AI ethics was discussed. Full article

The global aging population, particularly those aged 60 and above, is increasingly vulnerable to communicable diseases. Building ventilation (BV) plays a key role in residential aged-care (RAC) facilities, where COVID-19 has had a significant impact. This study systematically reviews the published literature to examine the influence of BV systems (BVSs) on airborne disease (COVID-19) transmission in RACs and recommends strategies to protect vulnerable residents. Using the PRISMA framework, articles published in the last decade were sourced from Scopus, Web of Science, and PubMed. Bibliometric analyses revealed key research clusters on risk factors, transmission, facilities and services, and gender-based and retrospective studies. Australia, the USA, Africa, and the UK have made the most scholarly contributions to this field. Three main research areas emerged: BVS functionality, ventilation’s role in COVID-19 transmission, and spatial building design for effective airflow. Findings reveal that inadequate ventilation and poor indoor air quality are major contributors to disease spread, further influenced by ventilation rate, airflow, temperature, humidity, and air distribution. A hybrid ventilation design that integrates natural and mechanical systems with technologies such as HEPA filters, UVGI, and HVAC is recommended in the current study. In addition, building form and layout should incorporate spatial, engineering, administrative, and hierarchical controls in line with sustainable ventilation design guidelines. This study adds to the growing body of knowledge on the roles of ventilation and design in infection control. It offers practical recommendations for architects, RAC managers, government agencies, and policymakers involved in designing and managing RACs to reduce the risk of communicable disease transmission. Full article

This article explores the converging challenges and opportunities at the intersection of underwater cultural heritage, digital archaeology, and participatory science. In an era of accelerated climate change, data fragmentation, and rapid technological advancement, underwater archaeology is being reshaped by the rise of generative artificial intelligence (GAI), FAIR (Findable, Accessible, Interoperable, and Reusable) data governance, and the growing role of public archaeology. We argue for an ethical and epistemologically inclusive framework that recognizes the importance of co-authorship, data transparency, and multisensory narratives in interpreting submerged sites. Drawing on case studies from Latin America and Europe, this article demonstrates how socio-technical networks, collaborative models, and culturally sensitive ontologies offer a pathway toward a decolonized, accessible, and sustainable archaeology. This paper concludes with recommendations for integrated public policy and citizen-driven heritage protection, highlighting digital archaeology’s transformative potential in the Anthropocene. Full article

Illegal waste dumping poses a severe challenge to sustainable urban and regional development, undermining environmental integrity, public health, and the efficient use of resources. This study contributes to sustainability science by proposing a circular data feedback loop that enables dynamic, scalable, and cost-efficient monitoring and prevention of illegal dumping, aligned with the goals of sustainable waste governance. Historical data from the Slovenian illegal dumping register, UAV-based surveys and a newly developed application were used to update, monitor, and validate waste site locations. A comprehensive risk model, developed using machine learning methods, was created for the Municipality of Maribor (Slovenia). The modelling approach combined unsupervised and semi-supervised learning techniques, suitable for a positive-unlabeled (PU) dataset structure, where only confirmed illegal waste dumping sites were labeled. The approach demonstrates the feasibility of a circular data feedback loop integrating updated field data and predictive analytics to support waste management authorities and illegal waste dumping prevention. The fundamental characteristic of the stated approach is that each iteration of the loop improves the prediction of risk areas, providing a high-quality database for conducting targeted UAV overflights and consequently detecting locations of illegally dumped waste (LNOP) risk areas. At the same time, information on risk areas serves as the primary basis for each field detection of new LNOPs. The proposed model outperforms earlier approaches by addressing smaller and less conspicuous dumping events and by enabling systematic, technology-supported detection and prevention planning. Full article

While scientific and technological advancements drive societal progress, they have concurrently contributed to environmental pollution and climate change. Given the intrinsic interconnection between communication and environmental studies, this research leverages data from the Chinese General Social Survey (CGSS 2021) as its sample. Employing structural equation modeling (SEM), the study investigates the impact of media usage and perception of climate change issues on willingness to pay (WTP) for environmental protection. This study aims to investigate the interrelationships between media usage, climate perception, and WTP for environmental protection among Chinese residents through innovative model construction and variable selection, seeking to contribute to the enhancement of environmental protection from the perspective of media usage. Results indicate that media usage frequency (MU) positively predicts environmental concern (EC), climate risk perception (CRP), and WTP. Media trustworthiness (MT) positively influences climate impact perception (CIP), EC, and environmental satisfaction (ES). Climate impact perception negatively predicts WTP, while climate risk perception negatively affects ES. Environmental concern positively predicts both ES and WTP, and ES further positively predicts WTP. To enhance public environmental awareness, improve ES, and strengthen WTP for sustainable climate governance, we recommend that media institutions intensify climate risk communication and construct science-based narrative frameworks, while governmental bodies should improve environmental governance systems to elevate public satisfaction. Full article

Digital Twin (DT) technology has emerged as a transformative tool in urban flood risk management (UFRM), enabling real-time data integration, predictive modeling, and decision support. This systematic review synthesizes existing literature to evaluate the scientific impact, technological advancements, and practical applications of DTs in UFRM. Using the PRISMA 2020 framework, we retrieved 1085 records (Scopus = 85; Web of Science = 1000), merged and deduplicated them using DOI and fuzzy-matched titles, screened titles/abstracts, and assessed full texts. This process yielded 85 unique peer-reviewed studies published between 2018 and 2025. Key findings highlight the role of remote sensing (e.g., satellite imagery, IoT sensors) in enhancing DT accuracy, the integration of machine learning for predictive analytics, and case studies demonstrating reduced flood response times by up to 40%. Challenges such as data interoperability and computational demands are discussed, alongside future directions for scalable, AI-driven DT frameworks. This review identifies key technical and governance challenges while recommending the development of modular, AI-driven DT frameworks, particularly tailored for resource-constrained regions. Full article

Smart mobility has emerged as a transformative enabler for achieving the United Nations Sustainable Development Goals (SDGs), offering technological and systemic solutions to pressing urban challenges such as congestion, environmental degradation, accessibility, and economic inclusion. Realizing this potential, however, depends not only on technological maturity but also on robust education and capacity-building frameworks. This paper addresses two critical gaps: the absence of a systematic review of structured academic curricula, vocational training programs, and professional development pathways dedicated to smart mobility, and the lack of a formal approach to demonstrate how structured, research-oriented education can effectively bridge theory and practice. The review examines a wide spectrum of initiatives, including academic programs, industry training, challenge-based competitions, and community-driven platforms. The analysis shows significant progress in Europe and North America but also reveals important gaps, particularly the limited availability of structured initiatives in the Global South, the underrepresentation of accessibility and inclusivity, and the insufficient integration of governance, ethical AI, policy, and cybersecurity. A case study of the AI for Smart Mobility course, developed using a design science methodology, illustrates how research-oriented education can be operationalized in practice. Since 2020, the course has engaged hundreds of students and professionals, with project dissemination through the AI4SM Medium hub attracting more than 20,000 views and 11,000 reads worldwide. The findings highlight both the progress made and the persistent gaps in smart mobility education, underscoring the need for wider geographic reach, stronger emphasis on inclusivity and governance, and structured approaches that effectively link theory with practice. Full article

This paper explores the rise in voice-based social media as a pivotal transformation in digital communication, situated within the broader era of chatbots and voice AI. Platforms such as Clubhouse, X Spaces, Discord and similar ones foreground vocal interaction, reshaping norms of participation, identity construction, and platform governance. This shift from text-centered communication to hybrid digital orality presents new sociological and methodological challenges, calling for the development of voice-centered analytical approaches. In response, the paper introduces a multidimensional methodological framework for analyzing voice-based social media platforms in the context of surveillance capitalism and AI-driven conversational technologies. We propose a high-level reference architecture machine learning for social science pipeline that integrates digital methods techniques, automatic speech recognition (ASR) models, and natural language processing (NLP) models within a reflexive and ethically grounded framework. To illustrate its potential, we outline possible stages of a PoC (proof of concept) audio analysis machine learning pipeline, demonstrated through a conceptual use case involving the collection, ingestion, and analysis of X Spaces. While not a comprehensive empirical study, this pipeline proposal highlights technical and ethical challenges in voice analysis. By situating the voice as a central axis of online sociality and examining it in relation to AI-driven conversational technologies, within an era of post-orality, the study contributes to ongoing debates on surveillance capitalism, platform affordances, and the evolving dynamics of digital interaction. In this rapidly evolving landscape, we urgently need a robust vocal methodology to ensure that voice is not just processed but understood. Full article

Since the advent of generative AI, research on AI in Education (AIEd) has experienced explosive growth. This study systematically explores publication dynamics, keyword evolution, and research focuses in AIEd by analyzing 2952 papers from the Web of Science (1990–2024). Using bibliometric methods, 2800 English publications were screened, with analyses conducted via VOSviewer v1.6.20 and Python v3.11.5. Findings show a surge in publications post-2020, reaching 612 in 2023 and 1216 by November 2024. The US and China are leading contributors, with the University of London and the University of California system as core institutions. Keywords evolved from “AI” and “machine learning” (2018–2020) to “ChatGPT” and “ethics” (post-2022), reflecting dual focuses on technological applications and ethical considerations. Notably, 68% of highly cited papers address ethical controversies, while higher education and medical education emerge as primary application domains, involving personalized learning and intelligent tutoring systems. Cross-disciplinary research is evident, with education studies comprising the largest category. The study reveals AIEd’s shift toward socio-technical integration, highlighting generative AI’s transformative role yet identifying gaps in ethical governance and K-12 research. These insights inform policymakers, journals, and institutions, advocating for enhanced interdisciplinary collaboration and long-term impact research to balance innovation with educational ethics. Full article