Search Results (2,169)

Colmation phenomena play a critical role in long-term gas flow through porous media, significantly influencing methane migration, mine ventilation efficiency, and emission control in both active and abandoned coal mines. In colmation modeling, three fundamental kinetic types are commonly distinguished, with the third kinetic providing a generalized nonlinear formulation capable of describing state-dependent and spatially variable permeability degradation. However, the strong nonlinearity of the coupled transport–colmation equations prevents the derivation of closed-form solutions, which necessitates the application of linearization techniques. In this study, gas flow with colmation governed by third-kinetics is analyzed with particular emphasis on methane migration in underground mining environments. Linearization of nonlinear kinetic terms is applied at the level of the coupled mass balance and colmation equations, resulting in an approximate form of Darcy’s law and an explicit analytical solution describing the evolution of the porous medium state. The primary objective of the study is to quantify the error introduced by the adopted linearization and to analyze its spatial and temporal propagation with respect to the nonlinear reference solution. A rigorous error estimation based on Taylor series truncation is developed, yielding an explicit criterion that defines the validity range of the linearized solution. The results demonstrate that the approximation remains reliable within the regime of weak colmation, while the associated error is locally generated and propagates through transport mechanisms without exhibiting uncontrolled growth. Full article

Digital transformation is frequently argued to improve how agricultural businesses compete, coordinate, and capture value in markets, yet evidence remains limited of how regional innovation ecosystems shape farms’ digital readiness and how this readiness translates into accounting-relevant outcomes. This study addresses that gap by linking regional innovation capacity, observed farm digital readiness, and accounting performance within a single regional analytical framework. Using cross-sectional data for 180 EU NUTS2 regions (2023), we estimate a moderated mediation model with formative constructs based on harmonized secondary indicators. This study is original in shifting the analysis from the farm or firm level to the regional scale and in operationalizing digital readiness through observable uptake of precision technologies, robotics, livestock-management machinery, internet access, and management information systems. Regional innovation capacity is positively associated with farmers’ digital readiness, and digital readiness is positively associated with accounting performance in the baseline specification. The indirect pathway from innovation capacity to accounting performance via digital readiness is significant, consistent with digital readiness acting as a transmission channel through which ecosystems relate to measurable economic outcomes. Managerial composition conditions these relationships: the share of managers under 40 weakens both the ecosystem-to-digital link and the digital-to-performance link, while female managerial share shows only marginal moderation of the first stage and no significant moderation of the second. The findings provide a basis for future multilevel research and place-based policies and advisory actions aimed at strengthening digital uptake where regional innovation capacity is weaker. Full article

Given that the construction industry is a major source of energy consumption and carbon emissions, its green transition holds significant implications for both economic development and environmental sustainability. This study takes the digital economy as its point of departure and systematically examines its impact on the carbon emission intensity in the construction industry, as well as underlying transmission mechanisms. Based on theoretical analysis, this study employs fixed-effects and mediation-effects models for empirical testing. The study finds that the digital economy can significantly reduce the carbon emission intensity of the construction industry, a conclusion that remains robust after a series of robustness tests. Mechanism analysis shows that industrial structure optimization plays an important mediating role in the process through which the digital economy promotes the reduction of carbon emission intensity in the construction industry. Heterogeneity analysis indicates that the impact of the digital economy on the carbon intensity in the construction industry is greater in the central and western regions than in the eastern regions. However, this impact is relatively smaller in regions with high urbanization levels than in those with average urbanization levels. At the same time, the impact of the digital economy on the carbon intensity in the construction industry is greater in low-income regions than in high-income regions. Finally, the study proposes measures to reduce the carbon emission intensity of the construction industry. Full article

The agricultural sector is undergoing a profound digital transformation driven by artificial intelligence, the Internet of Things, remote sensing, robotics, blockchain, and edge computing, which are being integrated into crop monitoring, irrigation management, disease detection, and supply chain transparency systems. This study employs systematic evidence mapping to characterize the applications of emerging digital technologies in sustainable agriculture; it delineates technological trajectories, areas of application, implementation gaps, and opportunities for improvement. Adhering to the PRISMA 2020 reporting protocol, 101 peer-reviewed articles indexed in Scopus and Web of Science (2020–2025) were identified, screened, and subjected to integrated thematic and bibliometric synthesis, using RStudio Version: 2026.01.1+403 and VOSviewer 1.6.20 for data mining on keywords and technological evolution patterns. Results show that deep learning and computer vision models achieved diagnostic accuracies of 90–99%, smart irrigation systems reduced water consumption by 10–30%, predictive yield models frequently reported R² values above 0.80, and greenhouse automation reduced energy consumption by approximately 20–30%. Blockchain-based architectures improved traceability and secure data transmission by 15–20%, while remote sensing integration enhanced spatial estimation accuracy up to R² = 0.92. The findings demonstrate a measurable transition toward data-driven, resource-efficient agricultural ecosystems supported by validated digital architectures. However, interoperability limitations, lack of standardized performance metrics, scalability challenges, and uneven geographical implementation—identified in nearly 40% of studies—highlight the need for harmonized evaluation frameworks, cross-platform integration standards, and long-term field validation to ensure sustainable and scalable digital transformation. Full article

Against the backdrop of an accelerated green transition and increasingly stringent climate policies, climate transition risk has emerged as a significant exogenous shock to the financial system. Using a panel of 57 listed commercial banks in China over the period 2010–2024, this study investigates whether and how climate transition risk shapes bank risk-taking behavior and identifies the mechanisms involved. Empirical evidence shows that rising climate transition risk significantly lowers bank risk-taking, a conclusion that holds consistently under various endogeneity and robustness checks. Second, the evidence suggests that climate transition risk may indirectly reduce bank risk-taking by impairing growth capacity and increasing operational costs per unit. Third, moderating effect analysis reveals that higher levels of digital transformation and the implementation of the Paris Agreement help alleviate the adverse effects of climate transition risk, whereas increased economic policy uncertainty amplifies this effect. Fourth, heterogeneity analysis shows that large banks exhibit greater resilience, while banks with higher carbon-intensive exposure are more sensitive to climate transition risk. Overall, these findings provide empirical evidence and policy implications for enhancing climate-related financial regulation and facilitating the green transformation of the financial system. Full article

Post-quantum cryptography (PQC) artifacts are one to three orders of magnitude larger than their classical counterparts and must be segmented via ISO-TP across a shared CAN-FD bus while coexisting with periodic safety-critical traffic. No prior work has quantitatively mapped the transport-level feasibility of these artifacts under realistic multi-electronic control unit (ECU) contention. This paper presents a validated discrete-event simulator and evaluates 29 parameter sets from nine algorithm families—spanning the KpqC final portfolio, NIST FIPS 203–205 standards, and the draft FIPS 206—across 534 scenarios classified as feasible, borderline, or infeasible. Results show that key encapsulation mechanism (KEM) feasibility is scenario-dependent: domain scale and startup coordination dominate over algorithm choice, with 4-ECU staggered deployments feasible for all Level-1 candidates, while 16-ECU simultaneous startup is universally infeasible. For digital signatures, FN-DSA achieves the best transport feasibility due to its compact signature, while HQC is uniformly infeasible and SLH-DSA is nearly uniformly infeasible, quantifying the CAN-FD bandwidth premium of algorithmic diversity. System-side traffic shaping—staggered startup and reserved bus windows—outperforms algorithm substitution as a mitigation strategy. To the best of our knowledge, these findings constitute the first design-space map of PQC artifact transport on CAN-FD and provide actionable deployment guidelines for post-quantum transition. Full article

The current literature on electrical system maintenance highlights three technology domains—Building Information Modeling (BIM), Digital Twin (DT), and extended reality (XR)—that have independently demonstrated strong potential for improving lifecycle information management, predictive analytics, and operational support. However, their convergence remains largely underexplored, particularly in electrical system maintenance. This paper provides a structured review of BIM–DT–XR convergence in electrical system lifecycle management, examining their roles across lifecycle phases and their integration through literature synthesis and cross-domain implementation evidence. BIM is analyzed as a basis for modeling and integrating facility management with electrical asset lifecycles; DT as a framework for dynamic system representation and applications in electrical and power systems; and XR as a means of visualizing and interacting with BIM-DT environments. Cross-domain implementation evidence from an industrial electrical facility and a tertiary smart-building pilot shows that BIM–DT–XR integration is technically feasible at pilot scale. However, the analysis identifies five structural integration gaps: semantic misalignment between building-oriented IFC and grid-oriented CIM ontologies; fragmented standard adoption; inconsistent data governance and naming practices; validation approaches focused on syntactic rather than dynamic model fidelity; and the separation of XR visualization from predictive DT capabilities. The implementation evidence further indicates that real-world deployment remains constrained by data quality limitations, integration complexity, cost factors, and interoperability with legacy systems. The review concludes that, despite the maturity of individual technologies, their effective application depends on advances in semantic alignment, lifecycle data governance, validation of dynamic models, and scalable integration frameworks, enabling the transition toward integrated, interoperable, and lifecycle-aware infrastructures for electrical system maintenance. Full article

Within the context of regional energy governance, land use has emerged as a critical regulatory interface for managing energy demand. Clarifying the land-use–energy nexus is a technical prerequisite for evidence-based and spatially explicit energy planning. This study develops a digital modeling framework that integrates machine learning (Random Forest, achieving R² = 0.95/0.91 for training/testing) and spatial simulation (Patch-generating Land Use Simulation model, with 82.5% accuracy for industrial land) to quantify land-use-driven energy dynamics in Shaanxi Province, China (2005–2030). Key findings reveal: (1) socioeconomic factors dominate land-use expansion, with service industries (14.8–22.4%) and infrastructure (13.5–18.9%) acting as primary drivers, leading to a projected 94.2% growth in urban built-up areas and a tripling of total energy consumption; (2) structural transitions indicate a declining industrial energy share (from 68% to 54%) and reduced coal dependency (from 78% to 62%), though with significant regional disparities; (3) spatial analysis identifies critical energy path-dependency risks in Xi’an City and Yulin City, which are projected to account for 70% of provincial consumption by 2030. These results demonstrate that land-use structure constitutes a direct physical interface linking regional development with energy demand trajectories. The findings underscore the necessity of transitioning from generalized energy policies toward data-driven, land-use-based energy constraints, providing a digital evidentiary base for more precise and stable regional energy governance. Full article

Background: As Taiwan transitions into a super-aging society, the government has launched “Long-term Care (LTC) 3.0,” a policy initiative that marks a strategic shift from service expansion to integrated quality verification, digital oversight, and social resilience. This transition demands a robust quality verification mechanism. Ensuring perceptual consistency between service providers and external evaluators is critical for systemic fairness and sustainable service quality. Objective: This study utilized a two-dimensional gap analysis to examine the discrepancy in service quality benchmarks between home-based LTC center managers and assessment committee members, identifying critical divergence zones for institutional improvement. Methods: A cross-sectional evaluative study was conducted, involving center managers (evaluatees, n = 50) and external experts (evaluators, n = 28). The data were collected via a structured instrument covering 20 consensus benchmarks. Results: Significant perceptual gaps were identified across all dimensions (p < 0.001), with “Professional Care Quality” exhibiting the largest effect size (Cohen’s d > 1.5). Benchmarks with low external scores but high internal ratings were categorized into the “Overestimation (Management Blind Spot)” quadrant, signaling a systemic overestimation bias in administrative and clinical risk management. Conclusions: This study provides empirical evidence for the refinement of LTC 3.0 assessment systems. The results offer a strategic roadmap for policymakers to enhance organizational resilience by transitioning from subjective self-perception to objective, data-driven quality management through the two-dimensional gap model. Full article

A major connectivity gap arises from the misalignment between the forward-looking climate disclosures required by IFRS S2 and the historically rooted asset valuations mandated by IAS 36. This misalignment can cause the overvaluation of carbon-intensive assets and disrupt capital allocation decisions. This research specifically examines transition risks, such as carbon pricing, regulatory shocks, and technological disruption, and quantifies the financial externality using a combination of deterministic impairment testing and stochastic climate scenarios. We create a constructive framework and develop a model of a Synthetic Representative Firm, calibrated to major integrated steel producers in Europe. To generate nonlinear Green Swan shocks for Value-in-Use, the process combines Monte Carlo simulation with the Merton Jump-Diffusion model. This comparison shows the difference between the steady Management View and the volatile Market View. Empirical results reveal a material Sustainability Discount, representing a substantial erosion in the recoverable amount under IFRS S2 transition risk scenarios compared to the IAS 36 Deterministic Baseline. Simulations show a strong probability of asset stranding due to restricted cost pass-through, indicating that older assets may face elevated impairment risks under disorderly transition scenarios. Traditional deterministic models may not fully capture aspects of Double Materiality, potentially leaving balance sheets less responsive to transition risks. Integrating digitalization and the Circular Carbon Economy (CCE) framework presents a strategic method for averting value destruction. Therefore, this research supports the integration of stochastic transition risk modeling into impairment testing to achieve faithful financial representation. Full article

Global poultry production continues to expand rapidly to meet the growing demand for affordable and high-quality animal protein. However, this growth raises pressing concerns about environmental sustainability, natural resource use, and public health. Although current initiatives, such as improved housing systems, optimized feeding practices, and partial soybean meal substitution, have helped mitigate some impacts, comprehensive integrated solutions remain underexplored. This review synthesizes emerging nutritional and management innovations that enhance the sustainability of poultry production while maintaining profitability. It addresses three central research questions: (1) Which alternative feed ingredients most effectively preserve animal performance while minimizing environmental burdens? (2) How can environmental management practices enhance resource efficiency and waste valorization? (3) What roles do life cycle assessment methodologies and policy frameworks play in advancing sustainable poultry systems? Evidence from 100 peer-reviewed studies, industrial data, and field analyses reveals that incorporating insect meals, algae, and agro-industrial by-products can reduce dependence on soybean meal by 20–40% and improve feed efficiency by 5–12% across various poultry production systems. Furthermore, integrating environmental management strategies, such as manure valorization, efficient water and energy use, and the adoption of renewable energy, substantially reduces greenhouse gas emissions and promotes circular economic principles. Life cycle assessment studies confirm that combined dietary and management interventions yield greater reductions in carbon footprint than isolated measures. Future research should focus on optimizing interactions among feed strategies, environmental management, and policy frameworks through digital technologies, nanomaterial-based feed additives, and region-specific sustainability plans to accelerate the transition toward resilient, climate-smart poultry production systems. Full article

High-precision time and frequency references are essential for satellite navigation, deep-space exploration, and space science missions. To address the large size, high power consumption, and limited integration of conventional Passive Hydrogen Maser (PHM) servo electronics based on discrete analog chains, this paper proposes a miniaturized digital servo architecture for PHMs based on software-defined radio (SDR) and a field-programmable gate array (FPGA). The AD9364 is used as an integrated RF front end for microwave interrogation signal generation, receiver down-conversion, and analog-to-digital conversion (ADC), while digital demodulation, discriminator construction, and closed-loop control are implemented in the FPGA. A dual-frequency interrogation and time-division multiplexing scheme is introduced to separate the atomic and cavity responses, and an oversampling-based processing method combining outlier rejection and averaging decimation is adopted to improve the observation accuracy and noise immunity of weak error signals. Experimental results demonstrate stable closed-loop locking of the atomic transition spectrum, achieving a frequency stability of 1.46 × 10⁻¹² at 1 s, while significantly improving the compactness and integration level of the servo electronics. Full article

This research delves into the interconnectedness of economic growth, environmental sustainability, and social development within the six Gulf countries (GCC): Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates. Employing ARDL and VECM methodologies, the study examines the short- and long-run dynamics between these variables from 2010 to 2023. Key findings reveal that while digital initiatives, foreign direct investment (FDI), trade openness, and political stability positively influence economic growth and social development, investments in renewable energy and environmental sustainability may initially impose short-term economic costs. However, these investments are crucial for long-term sustainability and contribute to enhanced social well-being. To foster a more sustainable and equitable future, the study recommends that GCC policymakers prioritize balanced strategies that promote economic growth, environmental sustainability, and social development simultaneously. This study details targeted investments in digital infrastructure, fostering innovation, encouraging sustainable practices, and implementing effective policies to mitigate the short-term costs of transitioning to a more sustainable economy. By adopting such a holistic approach, the GCC states can navigate the challenges and opportunities of sustainable development and ensure a prosperous future for their populations. Full article

The geomorphological characterization of coastal–marine environments is essential for environmental management and biodiversity conservation. The objective of this study was to model the geomorphological diversity of the Punta de Coles National Reserve, located in Puerto de Ilo, Moquegua, Peru, using GNSS geodetic receivers, integrating topographic and bathymetric data to continuously represent both the emerged and submerged relief. The methodology involved establishing two “C”-order geodetic control points, implementing a closed polygon with 13 vertices, conducting a topographic survey, and recording bathymetric data along coastal transects extending 1 km offshore using an echo sounder and GNSS positioning. The data were processed in a GIS environment to generate a Coastal–Marine Digital Terrain Model (CM-DTM) with metric resolution. The results showed a total area of 171.451 ha, with elevation variations ranging from sea level to 71.617 m above sea level. Distinct geomorphological units were identified, such as coastal plains (0–5% slope), hills (15–35%), and cliffs (>45%), in addition to 16 rocky islets covering 1.537 ha. In the underwater environment, the model made it possible to identify submerged terraces, slopes, and local depressions down to a depth of −115 m, revealing a continuous transition between the land and sea topography; additionally, areas with a higher susceptibility to erosion and areas of high ecological importance were identified. This study’s contribution lies in the integration of GNSS geodetic data with topobathymetric surveys, which enabled the generation of a high-precision continuous model in an area with limited prior information, establishing a scientific baseline for coastal and marine management and conservation. Full article

Background: Cervical cancer remains a leading cause of cancer-related deaths among women in Nigeria. In 2023, the Government of Nigeria, with support from Gavi and partners, introduced the single-dose human papillomavirus (HPV) vaccine through a phased, school-based campaign. The first phase was launched in October 2023 across 16 states, followed by a second phase in May 2024 that expanded coverage to the remaining states and the Federal Capital Territory. This study evaluates the additional impact of a behavioral insights–informed digital intervention, comprising a social media campaign amplified by trained pharmacists serving as local influencers, implemented in 2025 to increase acceptance and uptake of HPV vaccination during routine immunization. Methods: A pre-test/post-test quasi-experimental design with a control group was implemented in three Nigerian states in 2025 to assess the additional impact of a behavioral insights–informed social media campaign designed to strengthen social approval for HPV vaccination, increase awareness of vaccination locations, and reinforce caregivers’ recognition of their adolescent daughters’ desire to be vaccinated. Messages were amplified by trained pharmacists who served as local influencers. Caregivers of adolescent girls aged 9–17 years were recruited online through targeted Facebook and Instagram advertisements during Nigeria’s transition from school-based HPV vaccination campaigns to routine immunization. Caregivers in treatment areas were exposed to geofenced social media advertisements on Facebook and Instagram and pharmacist counseling, while those in control areas were not. Logistic regression models using a difference-in-difference approach estimated the campaign’s effect on HPV vaccination, controlling for caregiver and adolescent characteristics. Additional statistical models assessed the campaign’s impact on caregivers’ motivation and ability—key drivers of behavior according to the Fogg Behavior Model. Results: HPV vaccination increased at a significantly higher rate in the treatment compared to the control area. The adjusted odds of an adolescent girl being vaccinated were 1.48 times higher in the treatment area at follow-up (95% CI: 1.14–1.92). Adjusted marginal effects indicated that exposure to the campaign increased the probability of vaccination by 8.9 percentage points relative to the control group. The rate at which caregivers’ motivation (aOR = 1.31, 95% CI: 1.00–1.70) and ability (knowing where to get vaccinated: aOR = 1.38, 95% CI: 1.07–1.79; ease of vaccination: aOR = 1.59, 95% CI: 1.22–2.06) increased was also higher in the treatment area. There was no relative increase in intervention versus control groups in factual knowledge regarding HPV vaccination. Conclusions: A behavioral insights–informed social media campaign in which pharmacists served as influencers was associated with higher HPV vaccine uptake during routine immunization. The higher rate of vaccination observed in intervention areas was associated with higher rates of caregiver motivation and ability but not with higher rates of caregiver knowledge. These findings are consistent with the potential of behavioral insights–informed digital campaigns to complement routine immunization efforts and improve vaccine uptake in low- and middle-income countries. Full article