Search Results (40)

Water pollution and its ecological consequences have become central concerns in watershed governance and aquatic ecosystem conservation. Conventional ecotoxicological research on water pollution has long relied on physicochemical monitoring, laboratory-based single-species exposure tests, and morphology-based biological surveys. Although these approaches have provided essential support for pollutant identification, toxicity characterization, and environmental standard setting, they remain insufficient for resolving community-level responses, food-web perturbations, and ecosystem degradation under multiple-stressor conditions. Environmental DNA (eDNA) has emerged as a promising molecular tool because it is non-invasive, highly sensitive, high-throughput, and capable of detecting multiple taxa simultaneously. In aquatic systems, eDNA applications have expanded from biodiversity detection to pollution diagnosis, ecological health assessment, restoration monitoring, and early warning of ecological risk, while increasingly being integrated with eRNA, multi-omics approaches, machine learning, hydrological modeling, and ecological network analysis. However, several challenges still constrain its broader application, including incomplete methodological standardization, false-positive and false-negative detections, insufficient reference databases, limited quantitative capacity, scale mismatches caused by transport and mixing, and difficulties in causal attribution. This review synthesizes recent progress in the use of eDNA for water-pollution research, with emphasis on its technical workflow, major application domains, integrative analytical frameworks, and methodological boundaries. More specifically, three main points are highlighted: (1) eDNA is shifting water-pollution research from single-species toxicity characterization toward community- and ecosystem-level ecological interpretation; (2) its greatest value lies in its integrative role at the interface of biodiversity monitoring, ecological risk assessment, and management-oriented decision support; and (3) future progress will depend on improvements in standardization, quantitative inference, regional reference databases, and multi-source data integration. Overall, this review clarifies how eDNA can contribute to more robust, ecologically meaningful, and management-relevant assessment of water pollution. Full article

Freshwater resources constitute a fundamental component of coupled natural–human systems, underpinning ecosystem functioning, biogeochemical cycling, and socio-economic development. Anthropogenic climate change (i.e., climate change attributable to human activity, as distinct from natural climatic variability), driven primarily by greenhouse gas emissions and land-use change, is exerting significant pressure on the global hydrological cycle, resulting in increased hydroclimatic variability, intensification of extreme hydrometeorological events, and progressive degradation of freshwater quality and availability. This review synthesizes recent scientific evidence on climate-induced impacts on water systems together with emerging adaptation and resilience strategies. The analysis is based on a systematic assessment of 100 peer-reviewed studies indexed in the Web of Science Core Collection (2010–2025) and synthesized following a PRISMA-informed (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) narrative review protocol. Beyond confirming well-established trends in precipitation regimes, cryospheric decline, increasing evapotranspiration, and the growing frequency of droughts and floods, this review quantifies the magnitude of these changes across the reviewed literature, including an approximately 134% increase in flood-related disasters since 1980 and a 29% increase in drought duration since 2000. More importantly, it provides an integrated synthesis that links physical climate impacts with adaptation strategies and socio-ecological resilience frameworks within a unified analytical perspective, thereby complementing previous domain-specific reviews that have generally examined these dimensions separately. Prominent adaptation pathways identified across the reviewed literature include nature-based solutions, integrated water resources management frameworks, and the deployment of digital water technologies. In parallel, resilience is increasingly conceptualized as the adaptive capacity of socio-hydrological systems to absorb disturbances, reorganize, and transform under changing climatic conditions. The findings highlight the need to strengthen integrated and cross-sectoral water governance, enhance climate-informed decision-making, and expand monitoring and data infrastructures to improve long-term water security and socio-ecological resilience under accelerating climate change. Full article

Tax systems worldwide face a compliance gap that OECD data places at USD 100–240 billion annually in corporate avoidance alone, before accounting for the shadow economy and crypto-asset transactions. FinTech mandatory e-invoicing, real-time transaction matching, and machine-learning audit selection is narrowing the informational conditions that enable evasion, while simultaneously introducing governance risks: opaque algorithmic audit targeting, contested blockchain forensic evidence, and the surveillance potential of programmable money. This article presents a PRISMA 2020 systematic literature review of 59 peer-reviewed articles (Scopus, Web of Science, and ScienceDirect), complemented by IRAMUTEQ lexicometric analysis and an extension of the Allingham Sandmo compliance model to incorporate algorithmic detection probabilities, bomb-crater belief dynamics, and Zero-Knowledge Proof verification. Four thematic clusters emerge: tax compliance behaviour and FinTech adoption (19.92%), digital transformation and corporate performance (35.34%), bibliometric and emerging-technology research (16.54%), and cryptocurrency markets and regulatory challenges (28.20%). Across them, FinTech reduces evasion where institutional and technical conditions allow but generates distributional, evidentiary, and constitutional risks that existing legal frameworks have yet to resolve. In response, we propose the Techno-Legal Due Process Framework (TLDPF) three pillars (Techno-Proportionality, Cryptographic Burden of Proof, and Algorithmic Constitutionalism) grounded in EU/OECD constitutional doctrine as a normative design proposal awaiting empirical validation. Full article

This research synthesizes a more than a decade of empirical and conceptual research on Industry 4.0 technologies with circular economy ecosystem in the European context. The shifting from linear to circular economy requires adoption of I4.0 technologies in particular Artificial Intelligence (AI), Internet of Things (IoT), and Virtual Reality (VR). Yet current scholarship on circular economy ecosystems (CEE) remains theoretically fragmented. To address this gap, we conducted a systematic literature review (SLR) of 94 peer-reviewed journal articles (2010–2025) using the Web of Science (WoS) database following the PRISMA protocol by deploying theories, contexts, methods (TCM) framework and thematic analysis. We developed a comprehensive framework based on addressing key barriers e.g., diverse expectations of stakeholders, resistance to change, sustainable leadership challenges, lack of digitally enabled-capabilities and institutional pressure with the help of important enablers such as AI capabilities, collaboration with stakeholders, frugal innovation and supportive government policies. Our findings contribute to the emerging discourse on how combining digital technologies with circular economy practices can support the development of low emission manufacturing systems, in line with current zero-emission policy goals in the European Union. This review contributes fragmented literature by highlighting theoretical, contextual and methodological gaps as previously disparate perspectives to help align and move research forward. This research contributes to SDG 9- “Industry, innovation and infrastructure” and SDG 12 “Responsible Consumption and Production”. Full article

Plastic design enables efficient structural systems by exploiting controlled inelastic deformation and force redistribution. While mature in steel structures due to stable ductility and well-defined yielding, its extension to reinforced concrete (RC) remains challenging because cracking, stiffness degradation, confinement dependency, and progressive damage govern deformation capacity and collapse mechanisms. This paper presents a state-of-the-art review of optimal plastic design methodologies for RC structures by tracing the evolution from classical plasticity theory to modern damage-informed, reliability-oriented, and sustainability-driven formulations. A systematic and structured literature review of more than 90 peer-reviewed journal articles (1990–2025) was conducted using Scopus, Web of Science, and ScienceDirect. The selected studies are classified by structural system type, plastic analysis approach, constitutive modeling strategy, and strengthening technique, including CFRP and hybrid fiber systems, optimization framework, and uncertainty treatment. The review highlights how nonlinear elasto-plastic and damage–plasticity models improve the prediction of plastic hinge development, redistribution, and failure-mode transitions, and how metaheuristic optimization, topology optimization, surrogate modeling, and machine learning are increasingly used to manage discrete design variables and computational cost. Reliability-based methods (e.g., FORM/SORM and simulation) are shown to be essential for quantifying deformation-capacity uncertainty and ensuring consistent collapse-prevention performance. A comparative assessment of nine plastic design methodologies is also provided, identifying their core assumptions, limitations, and domains of applicability within a structured evaluative framework. Remaining challenges include robust deformation-capacity prediction, reproducible calibration of damage models, and integration of life-cycle sustainability criteria within reliability-constrained plastic optimization. Future research directions are proposed toward multi-objective reliability-based design, durability-informed plastic modeling, and hybrid physics-informed AI-assisted workflows. Full article

In the context of global climate change and the green transformation of the tourism industry, low-carbon tourism has emerged as an important topic within the field of sustainable development research. Consequently, there is a pressing need to systematically review and synthesize its knowledge domain. This study utilizes bibliometric analysis, employing CiteSpace, to review 468 articles published in the Web of Science Core Collection from 2010 to 2026, thereby elucidating publication trends, keyword clustering, and research hotspots within the field of low-carbon tourism. Additionally, it employs content analysis to provide an in-depth discussion of the knowledge system in this research area. Key findings are as follows: (1) The number of published papers on low-carbon tourism exhibits a phased growth pattern, with contributions predominantly centered around scholars such as Gössling and institutions such as the Chinese Academy of Sciences. Moreover, keyword co-occurrence and clustering analyses uncover a development from essential concepts such as low-carbon tourism and climate change to a more extensive range of themes, including carbon emission accounting, tourist behavior, and systemic governance, and research topics have undergone a phased evolution, moving from macro-level cognition to quantitative analysis, and then to systemic governance. (2) The research hotspots encompass five key areas: basic cognition and related concepts, carbon emission accounting methods and applications, factors influencing emissions and assessment frameworks, tourists’ low-carbon behaviors and decision-making mechanisms, and pathways for multi-party collaborative governance. (3) Current research is still facing four challenges, i.e., the absence of a standardized framework for assessing carbon emissions, outdated assessment methods, a disconnect between behaviors and governance, and fragmented governance entities. This indicates that research on low-carbon tourism has progressed beyond the initial macro-level discussions and has entered a critical phase closely linked to substantive governance. Future research needs to focus on deeply exploring the standardization of accounting methods, the development of dynamic assessment models, the design of behavioral intervention mechanisms, and the establishment of multi-level collaborative governance mechanisms. These efforts are essential to provide scientific evidence and practical guidelines for the global tourism industry to achieve neutrality goals. Full article

Despite the growing importance of Environmental, Social, and Governance (ESG) performance in shaping brand perception and consumer trust, limited empirical evidence exists on how ESG indicators translate into measurable digital consumer engagement outcomes, particularly in ethically driven markets such as the vegan food sector. This study addresses this gap by examining how ESG performance translates into digitally observable consumer engagement and frames this relationship as a strategic performance measurement and decision-support problem. Building on the sector’s reliance on ethical positioning, trust, and online visibility, we integrate ESG indicators with digital marketing and web analytics metrics (e.g., traffic and engagement proxies) for a panel of five leading vegan food firms [Nestlé SA (Vevey, Switzerland), Kellanova (Chicago, IL, USA), Beyond Meat Inc. (El Segundo, CA, USA), Danone SA (Paris, France), and Conagra Brands Inc. (Chicago, IL, USA)], using data from the Semrush web analytics platform and the Eikon Refinitiv ESG database for the period January–December 2024. We employ a mixed-method design combining descriptive analytics with correlation analysis and simple linear regression to estimate the direction and strength of ESG–digital performance links, and we extend inference through Fuzzy Cognitive Mapping (FCM) using the MentalModeler platform to simulate “what-if” scenarios that support managerial foresight under digital uncertainty. Results indicate that stronger ESG profiles are associated with more favorable digital outcomes, with specific ESG mechanisms (e.g., human-capital and environmental initiatives) aligning with deeper engagement signals. The FCM scenarios further suggest that coordinated ESG improvements can amplify digital traction and reinforce sustainable brand growth. The proposed framework contributes to strategic management by operationalizing an ESG-enabled digital performance measurement system and a lightweight Decision Support System (DSS) that can guide resource allocation, KPI monitoring, and risk-aware positioning in sustainability-oriented markets. Full article

Inland waters are critical nodes in the global nitrogen cycle, where microbial processes govern transformations that impact water quality and ecosystem functioning. Inland waters are critical nodes in the global nitrogen cycle, where microbial processes govern transformations that impact water quality and ecosystem functioning. To systematically map the knowledge structure and to identify evolving trends in this field, a bibliometric analysis was conducted using CiteSpace on 2459 publications from the Web of Science Core Collection (1990–2024). The results reveal a significant increase in publications after 2010, peaking at 228 in 2024, with China (1541 articles) and the Chinese Academy of Sciences (776 articles) being the leading country and institution, respectively. Keyword co-occurrence and cluster analyses identify a core conceptual framework centered on microbial communities, nitrogen transformation processes (e.g., denitrification, anammox), and aquatic habitats (e.g., lakes, rivers). Based on keyword emergence and temporal trends, the analysis suggests an evolution in research focus across four dimensions: research subjects (from microbial biomass to keystone taxa), core questions (from process rates to predictive manipulation), methodological tools (from culturing to multi-omics), and mechanistic understanding (from linear pathways to complex networks). These observed patterns indicate a progressive refinement of the field. The findings provide a structured overview of the literature and may inform future research directions, but should be interpreted as bibliometric trends rather than definitive conclusions about the state of the science. Full article

As global urbanization accelerates, biophilic urbanism has emerged as a key nature-based strategy for enhancing public health. While plants are critical active agents for psychological restoration, the specific pathways through which vegetation characteristics influence human–environment interactions remain fragmented. This knowledge gap hinders the evidence-based translation of biophilic principles into actionable urban design and governance. This study conducts a systematic bibliometric analysis of 443 peer-reviewed articles (2000–2025) at the intersection of restorative landscapes, urban settings, and plant-based interventions retrieved from the Web of Science Core Collection. Employing multiple visualization tools (VOSviewer, bibliometrix, and CiteSpace), we map publication trends, international collaborations, and thematic evolution. The results demonstrate a significant shift in the field, moving beyond the validation of foundational restorative theories (e.g., ART and SRT) to a more precise, implementation-oriented framework. This shift is characterized by the operationalization of vegetation attributes as controllable design variables, increasingly relating biophilic principles to broader nature-based solutions (NbS) agendas and evidence-informed urban governance. Thematic clustering analysis identified three core knowledge domains: (1) the role of plants as active exposure agents and behavioral mediators in psychological restoration; (2) the impact of specific plant characteristics—such as canopy structure, species diversity, and seasonal variation—on therapeutic outcomes; and (3) the integration of urban green spaces into broader governance frameworks to promote health equity and inclusive well-being. Our analysis highlights that plant-based interventions are evolving from aesthetic ornaments into precision design levers for fostering human–nature interactions. This study provides a science-based foundation for developing practical design guidelines and policy frameworks, shifting biophilic urbanism toward a robust governance strategy for creating equitable, restorative, and resilient cities. Full article

This study presents two independently optimised Extreme Gradient Boosting (XGBoost) regression models, one for predicting corrosion current density ($i_{corr}$) and one for predicting corrosion potential ($E_{corr}$) parameters of carbon steel rebar embedded in mortar and immersed in simulated pore solution. An experimental dataset consisting of 216 measurements was curated from a systematic potentiodynamic scan study covering six chloride contamination levels, two carbonation states (non-carbonated and carbonated), four moisture conditions for mortar (65%, 85%, 95% relative humidity, and submerged), and three conditioning durations for simulated pore solution (36 h, 72 h and 20 days). Hyperparameters of the XGBoost models were optimised using a Bayesian optimisation framework with the Tree-structured Parzen Estimator (TPE) sampler over 300 trials. Model performance was assessed using 5-fold cross-validation and a random 80:20 train–test split. The optimised models achieved cross-validation $R^2$ scores of 0.936 and 0.953 for $i_{corr}$ and $E_{corr}$, respectively. On the hold-out test set, $R^2$ values of 0.933 and 0.945 were obtained with test RMSE values of 0.2 log₁₀(µA/cm²) and 41.9 mV, respectively. The contribution of each input feature to model predictions was quantified and visualised using the SHapley Additive exPlanations (SHAP) methodology. SHAP analysis reveals that chloride content has the highest impact on $i_{corr}$, followed by carbonation state and the low-humidity condition, while for $E_{corr}$, chloride content and the Submerged condition have the greatest impact. An interactive web application was developed using Streamlit, enabling researchers and practitioners to obtain corrosion parameter predictions. The findings provide data-driven insights into the relative importance of environmental factors governing rebar corrosion, with direct implications for the development of accurate corrosion prediction models for reinforced concrete service life assessment. Full article

Trustworthy Identity and Access Management (IAM) is a foundational requirement for federated data trading platforms, yet existing solutions often rely on centralized Identity Providers (IdPs), lack cross-border interoperability, and offer limited support for user-friendly authorization management. These limitations hinder secure onboarding, fine-grained access control, and regulatory compliance, especially within European Union (EU) data spaces governed by the Electronic Identification, Authentication, and Trust Services (eIDAS) 2.0 framework. This work presents a comprehensive IAM framework designed for federated data trading environments, developed within the EU-funded PISTIS project. The framework is based on Keycloak IAM and offers three major capabilities: (i) a novel IAM architecture tailored to distributed data trading scenarios; (ii) full integration of eIDAS-compliant cross-border authentication and initial support for European Digital Identity (EUDI) Wallets; and (iii) a standalone, web-based Access Policy Editor (APE) that abstracts Keycloak’s policy engine and enables non-technical users to define fine-grained, owner-driven access rules. The approach is evaluated across real-world mobility, energy, and automotive industry pilots, demonstrating its effectiveness in enhancing trust, interoperability, and usability within regulated data-sharing ecosystems. Full article

Wire-arc coatings have received substantial attention for corrosion protection; however, poor bonding often leads to delamination, corrosion initiation, and costly re-coating of structural components. This review combines bibliometric mapping with a focused technical synthesis to clarify how bonding performance has been studied in wire-arc coatings. Specifically, publication trends, keyword co-occurrence networks, and country-level co-authorship maps are used to map the evolution of the field and position adhesion-related studies within the broader literature. The analysis of 762 wire-arc coating publications from Web of Science (among 13,314 thermal spray coating records) reveals that research is centered on microstructure, mechanical properties, and corrosion resistance, with growing links to wire-based additive manufacturing. Keyword co-occurrence networks demonstrate clear process–structure–property relationships, while country-level collaboration maps highlight the leadership of China, the USA, and Germany. Critical to note, only eight publications systematically investigate the combined effects of substrate roughness, coating thickness, and Zn-Al coating composition on bond strength—representing less than 0.01% of the thermal spray literature. This pronounced research gap underscores the novelty of the present review, which synthesizes existing knowledge on adhesion mechanisms, identifies key process parameters, and establishes a research agenda to optimize wire-arc coatings for infrastructure corrosion protection. The technical synthesis highlights that adhesion is governed by the coupled effects of surface preparation (roughness and topography), coating build-up (thickness), and spray conditions (e.g., standoff distance and substrate preheating), which together influence coating microstructure and failure modes. These findings provide a structured framework to guide parameter selection for durable coatings. Full article

Background/Objectives: Musculoskeletal disorders and their surgical treatment significantly affect global disability, healthcare utilization, and costs. Artificial intelligence (AI) is a key enabler of data-driven musculoskeletal care. Their applications include diagnostic imaging, surgical planning, risk prediction, rehabilitation, and digital health ecosystems. This narrative review synthesizes current evidence on the use of AI in orthopaedics and musculoskeletal care across five areas: diagnostic imaging, surgical planning and intraoperative augmentation, predictive analytics and patient-reported outcomes, rehabilitation intelligence and teleorthopaedics, and system-level management. An additional task is to identify translational gaps and priorities for safe, ethical, and equitable implementation of AI. Methods: A structured narrative review was conducted using targeted searches in PubMed, Scopus, and Web of Science supplemented by semantic and citation-based explorations in Semantic Scholar, OpenAlex, and Google Scholar. The main search period was January 2019 to December 2025. The retrieved peer-reviewed articles were analyzed for clinical relevance to human musculoskeletal care, quantitative outcomes, and the translational implications of the results. From the broader pool of eligible publications, 40 clinically relevant studies were selected for detailed synthesis covering imaging, surgical planning, predictive modeling, rehabilitation, and system-level applications. Owing to the significant heterogeneity in the model architectures, datasets, and endpoints, the results were organized into five predefined thematic areas. Results: The most mature evidence is for AI-assisted detection of bone fractures on radiographs, identification of implants, and use of sizing templates in preoperative planning for arthroplasty, where deep learning systems have achieved expert-level diagnostic performance (e.g., fracture detection sensitivity of approximately 90% and specificity of approximately 92% and implant identification accuracy of 97–99%) and improved the accuracy of preoperative planning compared to conventional templating. AI-based planning increases the likelihood of reducing intraoperative corrections, shortening surgery time, reducing blood loss, and improving the final functional outcomes. Predictive models can support the stratification of risk for complications, rehospitalizations, and patient-reported outcomes, although external validation remains limited and is often single-center at this stage of research. Emerging applications in rehabilitation and teleorthopaedics, including sensor-based monitoring and learning systems integrated with Patient-Reported Outcome Measures (PROMs), are conceptually promising, but are mainly limited to feasibility or pilot studies. Conclusions: AI is beginning to influence musculoskeletal care, moving beyond pattern recognition toward integrated, patient-centered decision support throughout the perioperative and rehabilitation periods. Its widespread use remains constrained by limited multicenter validation, dataset bias, algorithmic opacity, and immature regulatory and governance frameworks. Future work should prioritize prospective multicenter impact studies, repeatable revalidation of local models, integration of PROM and teleorthopedic data with health learning systems, and adaptation to changing regulatory requirements to enable safe, ethical, effective, and equitable implementation in routine orthopedic practice. Full article

Re-engineered fourth-generation management (R4thGM) emerged in 2022 as an innovative systems approach to make production systems more contemporary (e.g., more sustainable and open to diverse stakeholders), while complex system governance (CSG), as a systems approach, enables the control, coordination, communication, and integration of smart energy systems. However, there remains a lack of literature: (i) discussing how R4thGM, integrated energy system (IES) governance (as CSG), artificial intelligence (AI), advanced simulation, robust optimization methods, and stakeholders should be taken into account in the task of enhancing IES’s resilience and sustainability, particularly against extreme natural events; (ii) discussing the role of IES governance in enhancing control, coordination, integration, and communication of IES infrastructures; (iii) emphasizing the role of R4thGM for enhancing the resilience and sustainability of an IES; (iv) presenting an integrated energy meta-system (IEM) resulting from IES governance and relying on three technical enablers, i.e., (resilience) robust optimization, AI, and advanced simulation methods. This study aims to propose a novel integrative systems approach based on R4thGM and IES governance, using AI, advanced simulation, and optimization methods to enhance the resilience and sustainability of IES infrastructures in the design and operational phases. To achieve this goal, we have reviewed 85 Scopus- and Web of Science-indexed papers published in 2017–2025. The novelty of this study lies in presenting an integrative systems approach best suited to resilient and sustainable IES infrastructures against extreme natural hazards. Moreover, propositions are formulated to reflect on the suggested framework. Finally, research implications and future directions are provided. Full article

Resilience to climate change is a complex concept, especially in metropolitan areas where diverse services and stakeholders interact. Promoting sustainable climate adaptation, a resilience assessment method focused on regional areas and nature-based solutions is presented, along with its open-access, web-based platform, supporting resilience assessment, planning, and monitoring. Floods, droughts, heat or cold waves, windstorms, and forest fires can be assessed. A framework for holistic assessment and other framework, addressing critical infrastructure, are integrated. Four resilience dimensions are assessed: organizational (governance, social aspects, finance); spatial (exposure, impacts, and mapping); functional (service management, interdependencies); and physical (infrastructure robustness, redundancy). Strategic services comprise, e.g., water, waste, and natural areas. Resilience capacities, e.g., to prevent, respond, and recover from disruptions, are also assessed. The paper emphasizes new developments and assessment. Practical step-by-step guidance aligned with assessment purposes is included, aiming to address observed limitations (e.g., fragmented service provision, communication silos, data constraints). Overall results of a Spanish metropolitan area (AMB) and an exploratory application to an Austrian rural case (SLR) are also presented. Following the guidelines, AMB progressed from an essential to a comprehensive assessment. Overall, almost 1/3 of the metrics are advanced or progressing. SLR assessed its resilience capabilities regarding electrical infrastructure. Full article