Search Results (3,109)

The subgrade is a critical component of highway infrastructure that directly affects pavement performance and traffic safety. With the rapid expansion of highway networks and increasing heavy-truck traffic, latent subgrade distresses, such as insufficient base strength, uneven settlement, and base cracking, have become key factors limiting pavement serviceability. These distresses are often difficult to detect at early stages and may evolve into sudden structural failures if not properly identified. This study investigates the evolution mechanisms and spatial characteristics of representative subgrade distresses through an integrated framework combining FWD screening, GPR imaging, core sampling, and Abaqus-based finite element simulation. Field data were collected from the Changshen Expressway. Potential weak zones were first identified using FWD testing and further localized by GPR, while multilayer constitutive parameters were obtained from core sample analyses. The field-derived material parameters were then incorporated into an FE model to simulate pavement responses under loading and to interpret the underlying distress mechanisms. The proposed framework enables identification of dominant distress types, quantification of stiffness degradation, and clarification of deterioration pathways within the subgrade system. The results provide practical support for condition assessment, health monitoring, and maintenance decision-making in highway infrastructure. Full article

A low-carbon economy serves as a core pathway and pivotal engine for advancing the SDGs. Drawing on provincial panel data across 30 Chinese administrative regions spanning 2011–2023, the present study empirically examines how new infrastructure interacts with low-carbon economic development levels and their underlying transmission mechanisms by building an econometric model. Empirical results demonstrate that “new infrastructure” generates a notably positive facilitating impact on low-carbon economic development, with this influence being more pronounced in the central and western regions of China and policy pilot zones, while a rebound effect is identified in eastern China. Among various types of new infrastructure, information infrastructure and innovation infrastructure play particularly prominent roles, while integrated infrastructure shows a positive yet statistically insignificant impact. Mechanism analysis reveals that new infrastructure advances low-carbon economic progress primarily by curbing capital factor misallocation, while the elevation of the population urbanization level can amplify the facilitative impact of new infrastructure on the low-carbon economy. On this basis, it is imperative to raise investment in new infrastructure and enhance its systematic coordination with traditional infrastructure; implement differentiated layout strategies aligned with regional features; rationally steer the population urbanization process; and effectively facilitate the decoupling of carbon emissions from economic growth, thereby furnishing a robust underpinning for the full attainment of SDGs. Full article

This report describes the development and deployment of the Public Health Quality Tool (PHQTool), an online resource designed to help mobile health clinics (MHCs) assess and improve the quality of their public health services. MHCs provide essential clinical and public health services to underserved populations but have historically lacked tools to assess and improve the quality of their work. To address this gap, the PHQTool was developed as an online, evidence-based, self-assessment resource for MHCs, hosted on the Mobile Health Map (MHMap) platform. This report documents the collaborative development process of the PHQTool and presents preliminary evaluation findings related to usability and relevance among mobile health clinics. Drawing from national public health frameworks and Honore et al.’s established public health quality aims, the PHQTool focuses on six aims most relevant to mobile care: Equitable, Health Promoting, Proactive, Transparent, Effective, and Efficient. Selection of the six quality aims was guided by explicit criteria developed through pilot testing and stakeholder feedback. The six aims were those that could be directly implemented through mobile clinic practices and were feasible to assess within diverse mobile clinic contexts. The remaining three aims (“population-centered,” “risk-reducing,” and “vigilant”) were determined to be less directly actionable at the program level or required system-wide or data infrastructure beyond the scope of individual mobile clinics. Development included expert consultation, pilot testing, and iterative refinement informed by user feedback. The tool allows clinics to evaluate practices, identify improvement goals, and track progress over time. Since implementation, 82 MHCs representing diverse organizational types have used the PHQTool, reporting high usability and identifying common improvement areas such as outreach, efficiency, and equity-driven service delivery. Across pilot and post-pilot implementation phases, a majority of respondents agreed or strongly agreed that the tool was user-friendly, relevant to their work, and appropriately scoped for mobile clinic practice. Usability and acceptance were assessed using descriptive statistics, including percentage agreement across Likert-scale items as well as qualitative feedback collected during structured debriefs. Reported findings reflect self-reported perceptions of feasibility, clarity, and relevance rather than inferential statistical comparisons. The PHQTool facilitates systematic quality assessment within the mobile clinic sector and supports consistent documentation of public health efforts. By providing a standardized, accessible framework for evaluation, it contributes to broader efforts to strengthen evidence-based quality improvement and promote accountability in MHCs. Full article

Creeping landslides constitute the predominant form of long-term, slow-moving geohazards in high mountain gorge regions. Under the combined influence of gravity and external triggering factors, these landslides undergo persistent deformation, posing continuous threats to major transportation corridors, hydropower infrastructures, and nearby settlements. Li County is located within the active tectonic belt along the eastern margin of the Tibetan Plateau, characterized by highly variable topography, intensely fractured rock masses, and dense development of creeping landslides. The slip surfaces are typically deeply buried and concealed. Consequently, conventional drilling and profile-based investigations, limited by high costs, sparse sampling points, and poor spatial continuity, are insufficient for identifying the deep-seated structures of such landslides. To address this challenge, this study applies Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) to obtain ascending and descending deformation rate fields for 2022–2024, revealing pronounced spatial heterogeneity and persistent activity across three types of landslides. Based on the principle of mass conservation, the sliding-surface depths of eight typical landslides were inverted, revealing pronounced heterogeneity. The maximum sliding-surface depths range from 32 to 98 m and show strong agreement with borehole and profile data (R² > 0.92; RMSE ±4.96–±16.56 m), confirming the reliability of the inversion method. The GeoDetector model was used to quantitatively evaluate the dominant factors controlling landslide depth. Elevation was identified as the primary control factor, while slope aspect exhibited significant influence in several landslides. All factor combinations showed either “bi-factor enhancement” or “nonlinear enhancement”, indicating that slip-surface depth is governed by synergistic interactions among multiple factors. Boxplot-based statistical analyses further revealed three typical patterns of slip-surface variation with elevation and slope, based on which the landslides were classified into rotational, push-type translational, and traction-type translational categories. By integrating statistical patterns with mechanical models, the study achieves a transition from “form” to “state”, enabling inference of the internal mechanical conditions and evolutionary stages from the observed surface morphology. The results of this study provide an effective technical approach for deep structural detection, identification of controlling factors, and stability evaluation of creeping landslides in high mountain gorge environments. Full article

This study presents the first evaluation of plastic particle contamination along a complete drinking water supply chain within the distribution system of Milan, Northern Italy. Fourteen grab water samples were collected from various points, including groundwater extraction, post-treatment stages, a public fountain, and ten household taps. Plastic particles were identified using µFTIR spectroscopy and characterized by polymer type, shape, size, and color. Overall, low concentrations of plastic particles were detected, ranging from 0.3 ± 0.5 particles/L in the accumulation tank to an average of 1.9 ± 1.4 particles/L in household tap water, with no significant increase observed along the supply chain. The entire data set was dominated by cellulose particles (76%), as plastics accounted for only 8%. Microplastics (1 µm–1 mm) were the most commonly detected (90%), while the remaining 10% were large microplastics (1–5 mm). Qualitatively, polyester fibers were the most prevalent particles identified. However, greater variability and higher concentrations were found in private residence samples, suggesting that internal plumbing systems may be a primary source of contamination. Estimated human exposure through this supply system, based on a current theoretical model, was minimal compared to global benchmarks. These findings highlight the necessity of integrating private distribution infrastructure into future regulatory frameworks to assist stakeholders in making informed decisions to mitigate potential plastic contamination. Full article

The global shipping industry is surging ahead, and with it, a quiet revolution is taking place on the water: marine lithium-ion batteries have emerged as a crucial clean energy carrier, powering everything from ferries to container ships. When these vessels dock, they increasingly rely on shore power charging systems to refuel—essentially, plugging in instead of idling on diesel. But predicting how much power they will need is not straightforward. Think about it: different ships, varying battery sizes, mixed charging technologies, and unpredictable port stays all come into play, creating a load profile that is random, uneven, and often concentrated—a real headache for grid planners. So how do you forecast something so inherently variable? This study turned to the Monte Carlo method, a probabilistic technique that thrives on uncertainty. Instead of seeking a single fixed answer, the model embraces randomness, feeding in real-world data on supply modes, vessel types, battery capacity, and operational hours. Through repeated random sampling and load simulation, it builds up a realistic picture of potential charging demand. We ran the numbers for a simulated fleet of 400 vessels, and the results speak for themselves: load factors landed at 0.35 for conventional AC shore power, 0.39 for high-voltage DC, 0.33 for renewable-based systems, 0.64 for smart microgrids, and 0.76 when energy storage joined the mix. Notice how storage and microgrids really smooth things out? What does this mean in practice? Well, it turns out that Monte Carlo is not just academically elegant, it is practically useful. By quantifying uncertainty and delivering load factors within confidence intervals, the method offers port operators something precious: a data-backed foundation for decision-making. Whether it is sizing infrastructure, designing tariff incentives, or weighing the grid impact of different shore power setups, this approach adds clarity. In the bigger picture, that kind of insight matters. As ports worldwide strive to support cleaner shipping and align with climate goals—China’s “dual carbon” ambition being a case in point—achieving a reliable handle on charging demand is not just technical; it is strategic. Here, probabilistic modeling shifts from a simulation exercise to a tangible tool for greener, more resilient port energy management. Full article

Slicing functionality makes it possible for an operator to share a 5G physical infrastructure between several virtual networks operated by different institutions. The deployed slices can support a wide range of applications with conflicting QoS targets. The coexistence of these slices on top of a common infrastructure is challenging and remains an open issue. Identifying traffic associated with a given type of slice is required to operate and control network resources in an efficient and secure way. This work proposes new algorithms operating at the physical and MAC layers. The solutions designed identify traffic generated by URLLC and eMBB slices by defining a new LightGBM framework. The algorithms can operate at the base station level in an O-RAN-type architecture. They provide a valuable input to radio resource management and traffic steering procedures. Full article

This observation-based and explainable approach demonstrates the applicability of multi-source remote sensing for flood assessment in data-scarce regions, offering a robust scientific basis for flood management and spatial planning in monsoon-affected areas. Floods are among the most frequent and devastating natural hazards, particularly in developing countries such as Myanmar, where monsoon-driven rainfall and inadequate flood-control infrastructure exacerbate disaster impacts. This study presents a satellite-driven and interpretable framework for high-resolution flood susceptibility and risk assessment by integrating multi-source remote sensing and geospatial data with ensemble machine-learning models—Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM)—implemented on the Google Earth Engine (GEE) platform. Eleven satellite- and GIS-derived predictors were used, including the Digital Elevation Model (DEM), slope, curvature, precipitation frequency, the Normalized Difference Vegetation Index (NDVI), land-use type, and distance to rivers, to develop flood susceptibility models. The Jenks natural breaks method was applied to classify flood susceptibility into five categories across Myanmar. Both models achieved excellent predictive performance, with area under the receiver operating characteristic curve (AUC) values of 0.943 for XGBoost and 0.936 for LightGBM, effectively distinguishing flood-prone from non-prone areas. XGBoost estimated that 26.1% of Myanmar’s territory falls within medium- to high-susceptibility zones, while LightGBM yielded a similar estimate of 25.3%. High-susceptibility regions were concentrated in the Ayeyarwady Delta, Rakhine coastal plains, and the Yangon region. SHapley Additive exPlanations (SHAP) analysis identified precipitation frequency, NDVI, and DEM as dominant factors, highlighting the ability of satellite-observed environmental indicators to capture flood-relevant surface processes. To incorporate exposure, population density and nighttime-light intensity were integrated with the susceptibility results to construct a natural–social flood risk framework. This observation-based and explainable approach demonstrates the applicability of multi-source remote sensing for flood assessment in data-scarce regions, offering a robust scientific basis for flood management and spatial planning in monsoon-affected areas. Full article

Geostructures, such as foundations, embankments, retaining structures, bridge abutments, and both natural and engineered slopes, interact with the ground to ensure structural safety and functionality. One significant factor influencing these systems is climate, which continuously affects soil conditions through dynamic processes. Over the past century, climate change has intensified, increasing uncertainties regarding the safety of both existing and planned geostructures. While the impacts of climate change on geostructures are evident, effective methods to address them remain uncertain. This paper presents an approach for mitigating and adapting to climate change impacts through a stepwise geomechanical analysis and geotechnical design framework that incorporates expected climatic conditions. A novel framework is introduced that systematically integrates projected climate scenarios into geomechanical modeling, enabling climate-resilient design of geostructures. The concept establishes an interface between climate effects and geomechanical data, capturing the causal chain of climate hazards, their effects, and potential consequences. The proposed interface provides a practical tool for integrating climate considerations into geotechnical design, supporting adaptive and resilient infrastructure planning. The approach is demonstrated across different geostructure types, with a detailed slope stability analysis illustrating its implementation. Results show that the interface, reflecting processes such as water infiltration, soil hydraulic conductivity, and groundwater flow, is often critical to slope stability outcomes. Furthermore, slope stability can often be maintained through simple, timely implemented nature-based solutions (NbS), whereas delayed actions typically require more complex and costly interventions. Full article

This study explores the development potential of thematic tourism in the Municipality of Pella, Northern Greece. It examines local residents’ perceptions regarding tourism as a growth strategy, evaluates current informational and promotional efforts by the local government, and assesses the public’s willingness to participate in tourism activities. A structured questionnaire was distributed to a representative sample of residents that was given both in person and via the internet. Quantitative analysis revealed that while respondents generally support the idea of tourism development and feel moderately informed, there is a strong perception that the municipality’s efforts to promote tourism are insufficient. Key factors influencing residents’ attitudes include age, level of education, and personal involvement with tourism. The findings suggest that thematic tourism could serve as a viable development path, provided that local authorities implement targeted education, infrastructure, and promotion strategies. This study recommends enhanced cooperation between public institutions and local stakeholders to support sustainable tourism growth. It is suggested, therefore, to increase the depth of focus given in the development of an innovative agricultural area development model that will combine traditional agriculture with agritourism and the remaining types according to each place’s capabilities. Full article

Waste electrical and electronic equipment (WEEE) is one of the fastest-growing waste streams globally. Disposable e-cigarettes are among the products that have gained popularity in recent years. Their complex construction and embedded lithium-ion batteries (LIBs) present environmental, safety, and resource recovery challenges. Despite growing research interest, integrated analyses linking material composition with user disposal behavior remain limited. This study is the first to incorporate device-level mass balance, material contamination assessment, battery residual charge measurements, and user behavior to evaluate the waste management challenges of disposable e-cigarettes. A mass balance of twelve types of devices on the Polish market was performed. Plastics dominated in five devices, while non-ferrous metals prevailed in the others, depending on casing design. Materials contaminated with e-liquid residues accounted for 4.4–10.7% of device mass. Battery voltage measurements revealed that 25.6% of recovered LIBs retained a residual charge (greater than 2.5 V), posing a direct fire hazard during waste handling and treatment. Moreover, it was estimated that 7 to 12 tons of lithium are introduced annually into the Polish market via disposable e-cigarettes, highlighting substantial resource potential. Survey results showed that 46% of users disposed of devices in mixed municipal waste, revealing a knowledge–practice gap largely independent of gender or education. Integrating technical and social findings demonstrates that improper handling is a systemic issue. The findings support the relevance of eco-design requirements, such as modular casings for battery removal, alongside the enforcement of Extended Producer Responsibility (EPR) schemes. Current product fees (0.01–0.03 EUR/unit) remain insufficient to establish an effective collection infrastructure, highlighting a key systemic barrier. Full article

Empirical approaches alone have significant limitations for accurate estimation of the fracture toughness of welds in gas line pipes being considered for repurposing to hydrogen service. These problems arise because most samples machined from ex-service welds contain a range of microstructures. The different microstructural zones have different properties and even when compact tension samples with side grooves are utilized, it is unlikely that plane strain conditions are achieved during laboratory testing. Thus, the measured toughness may not be directly relevant to assessing in-service performance. The present research has been undertaken as part of an integrated series of projects seeking to define a robust protocol for assessing the damage tolerance of piping used for the transmission of hydrogen, especially when considering repurposing existing infrastructure. The key work described in this paper involved establishing heat treatments which produced microstructures relevant to the constituents found in ex-service welds of X46 type steel. Following comprehensive microstructural characterization, these heat treatments were applied to steel sections which allowed for the fabrication of standard compact tension specimens, which were subsequently tested in hydrogen to measure fracture toughness. The results obtained showed that the fracture behavior varied for different microstructures. To identify the influence that hydrogen gas has on the performance of pipeline steels, it is important to assess microstructures relevant to the welds present, as testing only on base metal may not provide conservative information. However, the results from well-planned and carefully executed programs can be used to identify the relative performance in hydrogen. The data can also be used as critical input to models which form part of an integrated approach to structural integrity assessment. Full article

Urban Water Systems (UWS) are complex infrastructures that interact with energy, food, ecosystems and socio-political systems, and are under growing pressure from climate change and resource depletion. Planning circular interventions in this context requires system-level analysis to avoid fragmented, siloed decisions. This paper develops the Hydrosocial Resource Urban Nexus (HRUN) framework that integrates hydrosocial thinking with the Water–Energy–Food–Ecosystems (WEFE) nexus to guide UWS design. We conduct a structured literature review and analyse different configurations of circular interventions, mapping their synergies and trade-offs across socioeconomic and environmental functions of hydrosocial systems. The framework is operationalised through a typology of circular interventions based on their circularity purpose (water reuse, resource recovery and reuse, or water-cycle restoration) and management scale (from on-site to centralised), while greening degree (from grey to green infrastructure) and digitalisation (integration of sensors and control systems) are treated as transversal strategies that shape their operational profile. Building on this typology, we construct cause–effect matrices for each intervention type, linking recurring operational patterns to hydrosocial functionalities and revealing associated synergies and trade-offs. Overall, the study advances understanding of how circular interventions with different configurations can strengthen or weaken system resilience and sustainability outcomes. The framework provides a basis for integrated planning and for quantitative and participatory tools that can assess trade-offs and governance effects of different circular design choices, thereby supporting the transition to more resilient and just water systems. Full article

The goal of this scientific study is to clarify whether and how digital–intelligent integration contributes to urban carbon efficiency and to identify the conditions under which this contribution becomes nonlinear and policy-relevant. Focusing on 39 prefecture-level cities in the middle reaches of the Yellow River Basin during 2011–2022, we adopt an integrated measurement–modelling approach that combines efficiency evaluation, machine-learning interpretation, and dynamic–spatial validation. Specifically, we construct two super-efficiency DEA indicators: an undesirable-output SBM incorporating CO₂ emissions and a conventional super-efficiency CCR index. We then estimate nonlinear city-level relationships using XGBoost and interpret the marginal effects with SHAP, while panel vector autoregression (PVAR) and spatial diagnostics are employed to validate the dynamic responses and spatial dependence. The results show that digital–intelligent integration is positively associated with both carbon-related and conventional efficiency, but its marginal contribution is strongly conditioned by human capital, urbanisation, and environmental regulation, exhibiting threshold-type behaviour and diminishing returns at higher digitalisation levels. Green efficiency reacts more strongly to short-run shocks, whereas conventional efficiency follows a steadier improvement trajectory. Heterogeneity across urban agglomerations and evidence of spatial clustering further suggest that uniform policy packages are unlikely to perform well. These findings highlight the importance of sequencing and policy complementarity: investments in digital infrastructure should be coordinated with institutional and structural measures such as green finance, environmental standards, and industrial upgrading and place-based pilots can help scale effective digital applications toward China’s dual-carbon objectives. The proposed framework is transferable to other regions where the digital–climate nexus is central to smart and sustainable urban development. Full article

The development of agricultural new productive forces (ANPFs) represents a vital pathway to overcoming the bottlenecks of agricultural modernization and reshaping agricultural competitiveness. As sustainable development and green transformation have become global priorities, the formation of ANPFs is increasingly viewed as a key engine for promoting resource-efficient agriculture, low-carbon production, ecological protection, and resilient food systems. Using panel data from 16 prefecture-level cities in Anhui Province, China, spanning the period 2010–2023, this study employs the entropy-weighted TOPSIS method to measure the levels of ANPFs and sustainable agricultural development (SAD). A panel data model is then applied to examine the impact of ANPFs on SAD, while a mediation-effect model is used to test the underlying transmission mechanisms. Finally, a spatial econometric model is employed to assess the spatial spillover effects between ANPFs and SAD. The results reveal that ANPFs exert a significant and robust positive impact on Anhui’s SAD, with the strength of this effect decreasing gradually from central to southern and northern regions. Further analysis indicates that the driving influence of ANPFs operates through three key mediating pathways: the improvement of new-type infrastructure, the enhancement of agricultural scientific and technological innovation, and the advancement of agricultural digital transformation. Moreover, ANPFs demonstrate a positive spatial spillover effect, suggesting that the development of new productive forces in one region promotes agricultural modernization in neighboring areas. These findings demonstrate that ANPFs not only enhance productivity but also contribute to sustainable agricultural development. Accordingly, strengthening ANPFs development can serve as an effective strategy for promoting long-term agricultural sustainability, indicating that central Anhui should be prioritized as a core hub for fostering ANPFs, enabling the gradient diffusion of infrastructure, innovation capacity, and digital services toward southern and northern Anhui. Strengthening regional coordination mechanisms will further amplify the spatial spillover of ANPFs, thereby advancing high-quality agricultural development across the province. This study provides new evidence for how ANPFs can support sustainable agricultural transformation, offering policy insights for green growth, food security, and rural revitalization. Full article