Search Results (7,444)

This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating satellite archives (KH, Landsat series, NASADEM) with ancillary geospatial data (OpenStreetMap) and advanced analytical methods, four decades (1984–2024) of land-use/land-cover (LULC) change and shoreline dynamics were reconstructed. Machine learning classification (Random Forest) achieved high accuracy (Test Accuracy = 0.94; Kappa = 0.89), enabling robust LULC mapping, while predictive modelling of urban expansion, calibrated through a Gradient Boosting Machine, attained a Figure of Merit of 0.157, confirming strong predictive reliability. The results reveal path-dependent urban growth concentrated on low-slope terrains (≤5°) and consistent with proximity to infrastructure, alongside significant shoreline regression after 1974. A Business-as-Usual projection for 2024–2034 estimates 8.676 ha of new anthropisation, predominantly along accessible plains and peri-urban fringes. Beyond quantitative outcomes, this study demonstrates the replicability and scalability of open-source, data-driven workflows using Google Earth Engine and Python 3.14, making them applicable to other high-risk heritage contexts. This transparent methodology is particularly critical in conflict zones or in regions where cultural assets are neglected due to economic constraints, political agendas, or governance limitations, offering a powerful tool to document and safeguard endangered archaeological landscapes. Full article

New quality agricultural productivity is essential for advancing agricultural modernization, consolidating and expanding achievements in poverty alleviation, and driving rural revitalization. However, leveraging this productivity to facilitate industrial upgrading and support the transition of smallholder farmers remains challenging. This paper constructs a tripartite evolutionary game model involving the government, agricultural enterprises, and farmers within the policy framework of new quality agricultural productivity. By applying evolutionary game theory, we analyze the strategic interactions among policy implementation, farmer welfare, and the development of new quality agricultural productivity. Equilibrium analysis reveals that the government, as a regulatory actor, should provide appropriate subsidies to agricultural enterprises and farmers, undertake initial infrastructure improvements, diversify subsidy instruments, establish special incentives for agricultural technology innovation, and increase investment in cultivating new agricultural talent. Agricultural enterprises, as dynamic agents, should adopt proactive and systematic transformation strategies. Furthermore, they need to strengthen benefit-linked mechanisms with farmers to ensure sustained collaboration. Full article

Amid mounting calls for socio-ecological transition, many social sciences studies have been exploring the processes of societal change. The well-known Science Technology Society studies (STS) approach focuses on the diffusion of innovation niches as an open-ended process ultimately leading to the stabilization of a new regime. Other works have suggested reversing the perspective, i.e., ‘thinking about transitions from the end’. This is a defining characteristic of system building perspectives, which are inherently goal- and sustainability-oriented. This paper presents the state of the art in the social sciences based on a review of international academic journals in English. We use both quantitative and qualitative approaches. Using Web of Science data collected for a period of ten years and the free software IRaMuTeQ (version 2), we have conducted statistical, similarity, and textual analyses of a corpus of 151 texts, following the PRISMA methodology. We discuss the findings of the lexicometric analysis by looking at the content of the article abstracts. While system building is not always mentioned as such, this new perspective is reflected in the literature, especially in research on the energy and food transition, in two main ways: (i) the procedural and substantive dimensions of sustainability transition are both taken into account; (ii) the issue of governance occupies a central place—involving the definition of appropriate instrument mixes and policy mixes—given the need to deal with stakeholders with diverging interests and values rather than only focusing on technological innovations. Full article

The rapid rise of virtual hospitals has created an urgent need for secure, interoperable, and patient-centered (PC) access to medical data across distributed healthcare environments. However, most existing hospital information systems and electronic medical records (EMRs) were not designed to support decentralized service delivery or cross-institutional collaboration. While many prior solutions advocate replacing legacy systems with new architectures, such approaches often face significant cost, integration, and adoption challenges. This paper introduces a novel blockchain-based Virtual Care Access Control (VCAC) model that extends—rather than replaces—legacy systems and EMRs to support secure data sharing across virtual hospital ecosystems. Leveraging the core features of distributed ledger technology (DLT)—including immutability, decentralized auditability, and consensus-driven access—the VCAC framework embeds a six-tier PC information classification scheme into a blockchain-based layer. This model enables fine-grained, role-based access to clinical data, supporting PC treatment in comorbidity-aware contexts, emergency access, and policy-driven governance while maintaining institutional autonomy. We demonstrate how VCAC mitigates key confidentiality, integrity, and availability risks common to legacy systems. The model is evaluated through a breast cancer outpatient use case, illustrating its practical potential to transform fragmented infrastructures into secure, interoperable, and PC virtual care platforms—without disrupting existing healthcare operations. Full article

In this paper, we present a collocation algorithm for numerically treating the time-fractional Kuramoto–Sivashinsky equation (TFKSE). Certain orthogonal polynomials, which are expressed as combinations of Chebyshev polynomials, and their shifted polynomials are introduced. Some new theoretical formulas regarding these polynomials have been developed, including their operational matrices of both integer and fractional derivatives. The derived formulas will be the foundation for designing the proposed numerical algorithm, which relies on converting the governing problem with its underlying conditions into a nonlinear algebraic system, which can be solved using Newton’s iteration technique. A rigorous error analysis for the proposed combined Chebyshev expansion is presented. Some numerical examples are given to ensure the applicability and efficiency of the presented algorithm. These results demonstrate that the proposed algorithm attains superior accuracy with fewer expansion terms. Full article

2-methylisoborneol (MIB, d = 0.6 nm) and dimethyl disulfide (DMDS, d = 0.7 nm) produced by algal metabolism are the main olfactory contaminants of drinking water. Activated carbon (AC) adsorption is an effective method to remove MIB/DMDS, yet critical gaps remain regarding the dominant factors and mechanisms governing their different adsorption performance. The microporous filling mechanism is the dominant mechanism for the adsorption of MIB and DMDS by AC. Surface functional groups play a supporting role in the adsorption process by modulating the hydrophilicity/hydrophobicity of the carbon surface. This study systematically evaluated the adsorption performance of three ACs—coconut shell-derived (CSC), coal-based (CAC), and Sargassum-derived (SAC)—for MIB and DMDS removal. Comparative analysis revealed the superior adsorption performance of CSC, achieving 87.41% removal of MIB and 71.2% removal of DMDS at 20 mg/L. Both MIB and DMDS adsorption adhere to the Langmuir isotherm, indicating monolayer coverage with uniform energy. Kinetic studies demonstrated that the PSO model fits the MIB adsorption process best, while the PFO model fits the DMDS adsorption process best. The FTIR confirmed physical adsorption, with no new chemical bonds formed. Furthermore, regenerated CSC retains significant adsorption capacities, achieving 85.89% and 68.49% of the original capacity for MIB and DMDS, respectively, after five regeneration cycles. This research provides fundamental insights into the mechanistic role of AC properties in odorant removal processes, supporting its sustainable application in water treatment. Full article

Environmental information fraud, such as greenwashing, severely impedes the achievement of global Sustainable Development Goals (SDGs). Blockchain technology, as an innovation tool with a sustainability orientation, offers new possibilities for improving the reliability of supply chain information oversight. However, its practical application mechanisms and policy value in green supply chain governance remain unclear. This study focuses on the greenwashing behavior of core enterprises and constructs an incomplete information game model to compare and analyze the inherent mechanisms of traditional regulation (TR) and blockchain-based digital supply chain regulation (DSCR). By simulating the strategic choices of enterprises between “genuine production” and “greenwashing” within a supply chain network, this research finds that when the quality of on-chain information reaches a certain threshold, the blockchain consensus mechanism can more accurately reveal corporate moral hazards, such as information manipulation, significantly reducing the incidence of greenwashing. As the number of enterprises participating in the blockchain network increases, the reliance on high-quality information in the DSCR model decreases, and regulatory efficiency is further enhanced through network effects. The findings provide theoretical support for designing regulatory strategies against greenwashing: Blockchain technology can build a trustworthy supply chain ecosystem through cross-enterprise data verification, directly supporting the SDG 12 goal of “Responsible Production.” Its decentralized nature helps optimize industrial infrastructure (SDG 9) and indirectly promotes climate action (SDG 13). This study suggests that regulatory agencies use policy tools such as “establishing on-chain information quality standards” and “incentivizing enterprises to join the blockchain network” to strengthen the practical application of the model, while also addressing implementation challenges such as data authenticity and digital infrastructure compatibility. Full article

A smart city can be defined as an urban ecosystem that combines new technologies related to digitalization in infrastructure, governance models, and everyday life, as well as inclusivity and stakeholder participation for achieving effectiveness and long-term sustainability. Although many frameworks and co-creative governance approaches emphasize the importance of integrating diverse perspectives in urban innovation, the practical implementation of stakeholder engagement remains a significant challenge in the development of digital strategies. This persistent difficulty often stems from factors such as varying levels of digital literacy, power asymmetries among stakeholders, and insufficient mechanisms for meaningful participation. As a result, there is a risk that smart city initiatives may fall short of their potential to deliver inclusive and sustainable outcomes, ultimately undermining both the legitimacy and the long-term effectiveness of urban digital transformation processes. This is especially relevant in the Italian context. Indeed, despite the relevant number of papers dedicated to stakeholder engagement in smart cities, few studies have explored how municipalities implement these innovative strategies, and even fewer have within the Italian context. This research aims to fill this gap by analyzing the stakeholder engagement in Rome’s smart city strategy and the effectiveness of participatory and co-creative approaches in transforming a city into an effective smart city. The research results reveal that the experience of the Rome Smart City Lab (RSCL) creates a model of participatory governance where the stakeholders can co-create the digital innovation strategies of a municipality and where the stakeholder techniques are fully implemented. The research results provide interesting results useful for both academics and policymakers involved in the digital transformation of a smart city, since the RSCL’s approach confirms that digitalization initiatives become more effective and efficient when they are shaped by the very individuals and groups responsible for their implementation. This participatory process seems to enhance the adaptability and sustainability of digital strategies over time, ultimately contributing to the realization of truly inclusive smart cities. Full article

The Eastern Sag of the Liaohe Depression, situated in the Bohai Bay Basin, represents a key area for hydrocarbon exploration in northeastern China. Despite decades of research, the mechanisms governing its complex structural evolution remain unclear, largely due to multiple tectonic reactivations associated with the Tan–Lu Fault Zone. In this study, newly acquired deep seismic reflection data were used to interpret representative structural profiles across the sag. Complementary sandbox modeling experiments were conducted to reconstruct the basin’s prototype and to verify the structural kinematics inferred from the seismic data. Integration of seismic interpretation, physical modeling, and thin-section microstructural observations of fault-related cores allowed us to establish a comprehensive Cenozoic evolutionary model of the sag. The results reveal three main tectonic evolution stages: (1) an extensional fault-depression stage during the Shahejie period, (2) a strike-slip modification phase during the Dongying period, and (3) a subsequent thermal-subsidence stage in the Guantao period. Pre-existing basement faults exerted a significant control on fault geometry, subsidence patterns, and the segmentation of four sub-sags. Moreover, transtensional and transpressional deformation during the late stages reshaped the basin architecture and fault linkage systems. These findings provide new insights into the structural evolution and controlling mechanisms of the Eastern Sag, offering valuable guidance for deep hydrocarbon exploration in the Bohai Bay Basin. Full article

The implementation of the NIS2 Directive expands the scope of cybersecurity regulation across the European Union, placing new demands on both essential and important entities. Despite its importance, organizations face multiple barriers that undermine compliance, including lack of awareness, technical complexity, financial constraints, and regulatory uncertainty. This study identifies and models these barriers to provide a clearer view of the systemic challenges of NIS2 implementation. Building on a structured literature review, fourteen barriers were defined and validated through expert input. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then applied to examine their interdependencies and to map causal relationships. The analysis highlights lack of awareness and the evolving threat landscape as key drivers (i.e., causal factors) that reinforce each other. Technical complexity and financial constraints act as mediators transmitting the influence of these causal factors toward operational and governance failures. Operational disruptions, high reporting costs, and inadequate risk assessment emerge as the most dependent outcomes (i.e., effect factors), absorbing the impact of the driving and mediating factors. The findings suggest that interventions targeted at awareness-building, resource allocation, and risk management capacity have the greatest leverage for improving compliance and resilience. By clarifying the cause-and-effect dynamics among barriers, this study supports policymakers and managers in designing more effective strategies for NIS2 implementation and contributes to current debates on cybersecurity governance in critical infrastructures. Full article

Cities around the world are facing growing challenges related to climate change, urban sprawl, infrastructure strain, and digital transformation. In response, smart and sustainable urban development has become a global focus, aiming to integrate technology and environmental stewardship to improve the quality of life. The smart and sustainable city concept is typically applied at the city scale; however, its impact is most tangible at the neighborhood level, where residents interact directly with infrastructure, services, and community spaces. A variety of global frameworks have been developed to assess sustainability and technological integration. However, these models often fall short in addressing localized needs, particularly in regions with distinct environmental and cultural contexts. In Saudi Arabia, Vision 2030 emphasizes livability, sustainability, and digital transformation, yet there remains a lack of tailored tools to evaluate smart and sustainable progress at the neighborhood scale. This study develops HayyScore, a localized evaluation framework and prototype digital platform developed to assess neighborhood performance across five core categories: (i) Environment and Urban Resilience, (ii) Smart Infrastructure and Governance, (iii) Mobility and Accessibility, (iv) Quality of Life and Social Inclusion, and (v) Economy and Innovation. The HayyScore platform operationalizes this framework through an interactive web-based tool that allows users to input data through structured forms, calculate scores, receive category-based and overall certification levels, and view results through visual dashboards. The methodology involved a comprehensive review of global frameworks, expert input to define localized indicators, and iterative prototyping of the platform using Python 3.13.5 and Streamlit 1.45.1. To demonstrate its practical application, the prototype was tested on two Saudi neighborhoods: King Abdullah Petroleum Studies and Research Center (KAPSARC) and King Fahd University of Petroleum and Minerals (KFUPM). Key platform features include automated scoring logic, category weighting, certification generation, dynamic performance charts, and a rankings page for comparing multiple neighborhoods. The platform is designed to be scalable, with the ability to add new indicators, support multilingual access, and integrate with real-time data systems in future iterations. Full article

The crisis of research integrity triggered by academic misconduct, such as scientific fraud and paper retractions, has emerged as a critical issue demanding urgent resolution within the academic community. Blockchain (BC), with its core features of distributed ledger, peer-to-peer transmission, consensus mechanisms, timestamps, and smart contracts, offers novel technical solutions for research institutions seeking efficient models of research credit supervision. By incorporating the psychological factors of risk perception among decision-makers and the dynamic evolution of behavioral decision-making, and drawing on prospect theory, this study has constructed an evolutionary game model involving researchers, scientific research institutions, and governmental entities to examine BC-enabled research credit supervision. This model analyzes the key determinants influencing scientific research institutions’ adoption of blockchain regulation (BC regulation), elucidates the behavioral characteristics and boundary conditions of research integrity among researchers under this new regulatory paradigm, and reveals the dynamic evolutionary trajectory of collaborative supervision between governments and scientific research institutions. The findings indicate the following: (1) Compared to traditional regulation, the BC regulation demonstrates superior regulatory effectiveness at equivalent levels of researcher integrity and misconduct costs, as well as under identical settings for reputational loss and penalties. (2) In addition to cost considerations and government subsidies, factors such as loss aversion coefficient, risk preference coefficient, and privacy breach losses are critical in influencing research institutions’ decisions to implement BC regulation. (3) The evolution of blockchain-empowered regulatory models encompasses three distinct evolutionary patterns. This study provides a theoretical foundation and a simulation case to optimize regulatory strategy formulation and resource allocation, thereby enhancing the effectiveness of research credit supervision. Full article

Fears regarding the future of coral reefs are reflected in a growing scientific effort, worldwide, to help corals survive and adapt to the impacts of climate change through new management strategies. To be viable, these strategies must not only be ecologically beneficial and technically feasible; they must be developed in partnership with Indigenous peoples and sensitive to the needs and aspirations of local communities, stakeholders and broader publics. This paper synthesizes insights from a comprehensive program of qualitative and quantitative social research, conducted through Australia’s Reef Restoration and Adaptation Program, exploring local community and public perspectives on the Great Barrier Reef (GBR) and the prospect of assisted adaptation. While the results of this research indicate strong support for prospective interventions to help the GBR, they also demonstrate that local communities and the broader Australian public hold multiple visions for the GBR’s future and engage in careful processes to imagine and evaluate assisted adaptation. We discuss the implications of this complexity for the development of technically robust and socially responsible adaptation intervention in the GBR, emphasizing the opportunities it presents for robust and inclusive dialogue, knowledge building, and governance around these strategies. Community and public support, we conclude, is contingent on moving beyond the seemingly straightforward question of whether or not people support intervention and towards forms of engagement that allow space for social and cultural diversity and the co-creation of ethically grounded adaptation pathways. Full article

Addressing the pressing demand for biogas and landfill-gas upgrading within the global energy transition, this work strategically combines thermodynamic and kinetic separation principles to identify, from a cooperative-separation perspective, the effective pore-size range that governs carbon molecular sieve (CMS) performance. Thirty anthracite-derived CMS samples with distinct pore structures were synthesized and employed as a statistical set to link pore architecture with dynamic adsorption performance. The results clarify the effective pore-size range and mechanism for enhanced CMS selectivity: CH₄ uptake depends exclusively on ultramicropores (<10 Å), with a negligible contribution from mesopores (>20 Å), whereas CO₂ uptake is less sensitive to pore-size distribution. CO₂/CH₄ separation performance improves linearly with the volume fraction of mesopores >20 Å, defining a 20–60 Å mesopore window as optimal for cooperative CMS. Mechanistic studies show that a high mesopore fraction significantly slows CH₄ adsorption while maintaining a fast CO₂ uptake, thereby amplifying their intrinsic adsorption-rate difference. This work breaks from the conventional purely thermodynamic or kinetic sieving paradigm and offers new design criteria for CMS tailored to on-site biogas and landfill-gas purification. Full article

Composites of lyotropic liquid crystals with biocompatible luminescent nanoparticles represent multifunctional materials with high potential for application in molecular diagnostics and biomedicine. Their integration with microfluidics is a new and scarcely studied approach that offers unique opportunities for tuning properties of such nanomaterials and simulating the biological environment of their application. This paper analyzes the impact of the governing microfluidic factors, including wall effects and flow dynamics, on the intermolecular structure and optical properties of the mesogenic luminescent nanocomposite of tetraethylene glycol monododecyl ether and carbon dots. The nanoscale and microscale surface structure of microchannel walls was found to be the dominating factor for additional near-wall ordering of the intrinsic lamellar structure of the composite. A combination of controlled shear stress with heating–cooling cycles allowed for a gradual and reversible transformation of multilamellar vesicles into the axial lamellar structure, and provided the composite with anisotropic luminescence capabilities according to the study of the luminescent behavior of carbon dots. The collected experimental datasets, comprising hundreds of texture images, allowed for training the neural network for subsequent accurate recognition of the composite nanoscale organization and dynamic properties in straight and serpentine microchannels. The results will contribute to developing AI-powered microfluidic chips with integrated biocompatible nanocomposite materials for testing drug delivery systems and simulating biological capillary environment in organ-on-chip prototypes. Full article