Search Results (1,659)

Wildfires have become increasingly frequent and destructive environmental hazards, especially in boreal ecosystems facing prolonged droughts and temperature extremes. This study presents an integrated spatio-temporal framework that combines Spatio-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN), Fire Radiative Power (FRP), and the differenced Normalized Burn Ratio (ΔNBR) to characterize the dynamics and ecological impacts of large-scale wildfires, using the extreme 2023 Quebec fire season as a case study. The analysis of 80,228 VIIRS fire detections resulted in 19 distinct clusters across four fire zones. Validation against the National Burned Area Composite (NBAC) showed high spatial agreement in densely burned areas, with Intersection over Union (IoU) scores reaching 62.6%. Gaussian Process Regression (GPR) revealed significant non-linear relationships between FRP and key fire behavior metrics. Higher mean FRP was associated with both longer durations and greater burn severity. While FRP was also linked to faster spread rates, this relationship varied by zone. Notably, Fire Zone 2 exhibited the most severe ecological impact, with 83.8% of the area classified as high-severity burn. These findings demonstrate the value of integrating spatial clustering, radiative intensity, and post-fire vegetation damage into a unified analytical framework. Unlike traditional methods, this approach enables scalable, hypothesis-driven assessment of fire behavior, supporting improved fire management, ecosystem recovery planning, and climate resilience efforts in fire-prone regions. Full article

The existence of fault zones in high-intensity earthquake areas has a serious impact on engineering structures, and the longitudinal response of tunnels crossing faults needs further in-depth research. To analyze the tangential contact effect between the surrounding rock and the tunnel lining, and the axial deformation characteristics of the tunnel structure, tangential foundation springs were introduced and a theoretical model for the longitudinal response of the tunnel under fault dislocation was established. Firstly, the tunnel was simplified as a finite-length beam. The normal and tangential springs were taken to represent the interaction between the soil and the lining. The fault’s free-field displacement was applied at the end of the normal foundation spring to simulate fault dislocation, and the differential equation for the longitudinal response of the tunnel structure was obtained. The analytical solution of the structural response was obtained using the Green’s function method. Then, the three-dimensional finite difference method was used to verify the effectiveness of the analytical model in this paper. The results show that the tangential contact effect between the surrounding rock and the lining has a significant impact on the longitudinal response of the tunnel structure. Ignoring this effect leads to an error of up to 35.33% in the peak value of the structural bending moment. Finally, the influences of the width of the fault zone, the soil stiffness of the fault zone, and the stiffness of the tunnel lining on the longitudinal response of the tunnel were explored. As the fault width increases, the internal force of the tunnel structure decreases. Increasing the lining concrete grade leads to an increase in the internal force of the structure. The increase in the elastic modulus of the surrounding rock in the fault area reduces the bending moment and shear force of the structure and increases the axial force. The research results can provide a theoretical basis for the anti-dislocation design of tunnels crossing faults. Full article

Urban heat islands (UHIs) are a growing sustainability challenge impacting public health, energy use, and climate resilience, especially in hot, arid cities like San Antonio, Texas, where land surface temperatures reach up to 47.63 °C. This study advances a data-driven, interdisciplinary approach to UHI mitigation by integrating Machine Learning (ML) with physical and socio-demographic data for sustainable urban planning. Using high-resolution spatial data across five functional zones (residential, commercial, industrial, official, and downtown), we apply three ML models, Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM), to predict land surface temperature (LST). The models incorporate both environmental variables, such as imperviousness, Normalized Difference Vegetation Index (NDVI), building area, and solar influx, and social determinants, such as population density, income, education, and age distribution. SVM achieved the highest R² (0.870), while RF yielded the lowest RMSE (0.488 °C), confirming robust predictive performance. Key predictors of elevated LST included imperviousness, building area, solar influx, and NDVI. Our results underscore the need for zone-specific strategies like more greenery, less impervious cover, and improved building design. These findings offer actionable insights for urban planners and policymakers seeking to develop equitable and sustainable UHI mitigation strategies aligned with climate adaptation and environmental justice goals. Full article

Our understanding of foreland basin subsurface structures relies heavily on seismic reflection data. The seismic profile across the eastern Rioni foreland basin in western Georgia is critical for characterizing its deformation structural style. We applied fault-related folding and thrust wedge theories to interpret the seismic profile and construction structural cross-section, which reveals that compressional structures are controlled by multiple detachment levels. Both thin-skinned and thick-skinned structures are identified. The seismic profile and structural cross-section reveal the presence of normal faults, reverse faults, thrust faults, duplexes, triangle zone, and crustal-scale duplexes. The deep-level detachment within the basement is responsible for the development of the crustal-scale duplexes. These structures appear to have formed through the reactivation of pre-existing normal faults during compressive deformation. Based on our interpretation, the imaged duplex system likely represents the western subsurface continuation of the Dzirula Massif. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

This study presents a simulation-based damage modeling and fatigue risk assessment of a reusable ceramic matrix composite thruster designed for short-duration, green bipropellant propulsion systems. The thruster is constructed from a fiber-reinforced ultra-high temperature ceramic matrix composite composed of zirconium diboride, silicon carbide, and carbon fibers. Time-resolved thermal and structural simulations are conducted on a validated thruster geometry to characterize the severity of early-stage thermal shock, stress buildup, and potential degradation pathways. Unlike traditional fatigue studies that rely on empirical fatigue constants or Paris-law-based crack-growth models, this work introduces a simulation-derived stress-margin envelope methodology that incorporates ±20% variability in temperature-dependent material strength, offering a physically grounded yet conservative risk estimate. From this, a normalized risk index is derived to evaluate the likelihood of damage initiation in critical regions over the 0–10 s firing window. The results indicate that the convergent throat region experiences a peak thermal gradient rate of approximately 380 K/s, with the normalized thermal shock index exceeding 43. Stress margins in this region collapse by 2.3 s, while margin loss in the flange curvature appears near 8 s. These findings are mapped into green, yellow, and red risk bands to classify operational safety zones. All the results assume no active cooling, representing conservative operating limits. If regenerative or ablative cooling is implemented, these margins would improve significantly. The framework established here enables a transparent, reproducible methodology for evaluating lifetime safety in ceramic propulsion nozzles and serves as a foundational tool for fatigue-resilient component design in green space engines. Full article

This study developed a copper mineral prospectivity map for the Koldar massif, Kazakhstan, using an integrated approach combining geophysical and satellite methods. A strong spatialgenetic link was identified between faults and hydrothermal mineralization, with faults acting as key conduits for ore-bearing fluids. Lineament analysis and density mapping confirmed the high permeability of the Koldar massif, indicating its structural prospectivity. Hyperspectral and multispectral data (ASTER, PRISMA, WorldView-3) were applied for detailed mapping of hydrothermal alteration (phyllic, propylitic, argillic zones), which are critical for discovering porphyry copper deposits. In particular, WorldView-3 imagery facilitated the identification of new prospective zones. The transformation of magnetic and gravity data successfully delineated geological features and structural boundaries, confirming the fractured nature of the massif, a key structural factor for mineralization. The resulting map of prospective zones, created by normalizing and integrating four evidential layers (lineament density, PRISMA-derived hydrothermal alteration, magnetic, and gravity anomalies), is thoroughly validated, successfully outlining the known Aktogay, Aidarly, and Kyzylkiya deposits. Furthermore, new, previously underestimated prospective areas were identified. This work fills a significant knowledge gap concerning the Koldar massif, which had not been extensively studied using satellite methods previously. The key advantage of this research lies in its comprehensive approach and the successful application of high-quality hyperspectral imagery for mapping new prospective zones, offering a cost-effective and efficient alternative to traditional ground-based investigations. Full article

Reliable prediction of tunnel thruster performance under reverse, or off-design, reverse operating direction (ROD) conditions, is crucial for modern vessels that require bidirectional thrust from a single unit—such as yachts and offshore support vessels. Despite the increasing demand for such a capability, there remains limited understanding of the unsteady hydrodynamic behavior and performance implications of ROD operation. This study addresses this gap through a scale-resolving computational fluid dynamics (CFD) investigation of a full-scale, fixed-pitch propeller with a diameter of 0.62, installed in a tunnel geometry representative of yacht-class side thrusters. Using advanced turbulence modeling, we compare the thruster’s performance under both the normal operating direction (NOD) and ROD. The results reveal notable differences: in ROD, the upstream separation zone was more compact and elongated, average thrust increases by approximately 3–4%, and torque and pressure fluctuations rise by 15–30%. These findings demonstrate that a single tunnel thruster can meet bidirectional manoeuvring requirements. However, the significantly elevated unsteady loads during ROD operation offer a plausible explanation for the increased noise and vibration frequently observed in practice. Full article

On 20 April 2024, an extreme rainfall event occurred in Jiangwan Town Shaoguan City, Guangdong Province, China, where a historic 24 h precipitation of 206 mm was recorded. This triggered extensive landslides that destroyed residential buildings, severed roads, and drew significant societal attention. Rapid acquisition of landslide inventories, distribution patterns, and key controlling factors is critical for post-disaster emergency response and reconstruction. Based on high-resolution Planet satellite imagery, landslide areas in Jiangwan Town were automatically extracted using the Normalized Difference Vegetation Index (NDVI) differential method, and a detailed landslide inventory was compiled. Combined with terrain, rainfall, and geological environmental factors, the spatial distribution and causes of landslides were analyzed. Results indicate that the extreme rainfall induced 1426 landslides with a total area of 4.56 km², predominantly small-to-medium scale. Landslides exhibited pronounced clustering and linear distribution along river valleys in a NE–SW orientation. Spatial analysis revealed concentrations on slopes between 200–300 m elevation with gradients of 20–30°. Four machine learning models—Logistic Regression, Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—were employed to assess landslide susceptibility mapping (LSM) accuracy. RF and XGBoost demonstrated superior performance, identifying high-susceptibility zones primarily on valley-side slopes in Jiangwan Town. Shapley Additive Explanations (SHAP) value analysis quantified key drivers, highlighting elevation, rainfall intensity, profile curvature, and topographic wetness index as dominant controlling factors. This study provides an effective methodology and data support for rapid rainfall-induced landslide identification and deep learning-based susceptibility assessment. Full article

The Inner Mongolia Plateau (IMP), situated in the arid and semi-arid ecological transition zone of northern China, is particularly vulnerable to both climate change and human activities. Understanding the spatiotemporal vegetation dynamics and their driving forces is essential for regional ecological management. This study employs Sen’s slope estimation, BFAST analysis, residual trend method and Geodetector to analyze the spatial patterns of Normalized Difference Vegetation Index (NDVI) variability and distinguish between climatic and anthropogenic influences. Key findings include the following: (1) From 1982 to 2022, vegetation cover across the IMP exhibited a significant greening trend. Zonal analysis showed that this spatial heterogeneity was strongly regulated by regional hydrothermal conditions, with varied responses across land cover types and pronounced recovery observed in high-altitude areas. (2) In the western arid regions, vegetation trends were unstable, often marked by interruptions and reversals, contrasting with the sustained greening observed in the eastern zones. (3) Vegetation growth was primarily temperature-driven in the eastern forested areas, precipitation-driven in the central grasslands, and severely limited in the western deserts due to warming-induced drought. (4) Human activities exerted dual effects: significant positive residual trends were observed in the Hetao Plain and southern Horqin Sandy Land, while widespread negative residuals emerged across the southern deserts and central grasslands. (5) Vegetation change was driven by climate and human factors, with recovery mainly due to climate improvement and degradation linked to their combined impact. These findings highlight the interactive mechanisms of climate change and human disturbance in regulating terrestrial vegetation dynamics, offering insights for sustainable development and ecosystem education in climate-sensitive systems. Full article

Roadway deformation failure is often related to the presence of weak structural planes (WSPs) in the surrounding rock mass. Especially in coastal mining environments, WSP-induced deformation can create pathways that connect faults with seawater, accelerating groundwater seepage and inrush hazards. This study employs an optimized Finite–Discrete Element Method (Y-Mat) to simulate WSP-driven fracture evolution, introducing an elastoplastic failure criterion and enhanced contact force calculations. The results show that the farther the WSP is from the roadway, the lower its influence; its existence alters the shape of the plastic zone by lengthening the failure zone along the fault direction, while its angle changes the shape and location of the failure zone and deflects fracture directions, with the surrounding rock between the roadway and WSP suffering the most severe failure. The deformation failure of roadway surrounding rock is influenced by WSPs. Excavation unloading reduces the normal stress and shear strength in the weak structural plane of surrounding rock, resulting in slip and deformation. Additionally, WSP-induced fractures act as groundwater influx conduits, especially in fault-proximal roadways or where crack angles align with hydraulic gradients, so mitigation in water-rich mining environments should prioritize sealing these pathways. The results provide a theoretical basis for roadway excavation and support engineering under the influence of WSPs. Full article

Amidst the intensification of global climate change and the increasing impacts of human activities, ecosystem patterns and processes have undergone substantial transformations. The distribution and evolutionary dynamics of mountain ecosystems have become a focal point in ecological research. The Surkhan River Basin is located in the transitional zone between the arid inland regions of Central Asia and the mountain systems, where its unique physical and geographical conditions have shaped distinct patterns of vertical zonation. Utilizing Landsat imagery, this study applies a hierarchical classification approach to derive land cover classifications within the Surkhan River Basin. By integrating the NDVI (normalized difference vegetation index) and DEM (digital elevation model (30 m SRTM)), an “NDVI-DEM-Land Cover” scatterplot is constructed to analyze zonation characteristics from 1980 to 2020. The 2020 results indicate that the elevation boundary between the temperate desert and mountain grassland zones is 1100 m, while the boundary between the alpine cushion vegetation zone and the ice/snow zone is 3770 m. Furthermore, leveraging DEM and LST (land surface temperature) data, a potential energy analysis model is employed to quantify potential energy differentials between adjacent zones, enabling the identification of ecological transition areas. The potential energy analysis further refines the transition zone characteristics, indicating that the transition zone between the temperate desert and mountain grassland zones spans 1078–1139 m with a boundary at 1110 m, while the transition between the alpine cushion vegetation and ice/snow zones spans 3729–3824 m with a boundary at 3768 m. Cross-validation with scatterplot results confirms that the scatterplot analysis effectively delineates stable zonation boundaries with strong spatiotemporal consistency. Moreover, the potential energy analysis offers deeper insights into ecological transition zones, providing refined boundary identification. The integration of these two approaches addresses the dimensional limitations of traditional vertical zonation studies, offering a transferable methodological framework for mountain ecosystem research. Full article

Background/Objectives: The rapid emergence of antibiotic-resistant Escherichia coli in food and clinical environments necessitates new, clean-label antimicrobials. This study assessed eight Greek native essential oils—oregano, thyme, dittany, rosemary, peppermint, lavender, cistus and helichrysum—for activity against six genetically and phenotypically diverse E. coli strains (reference, pNorm, mecA, mcr-1, blaOXA and O157:H7). We aimed to identify oils with broad-spectrum efficacy and clarify the chemical constituents responsible. Methods: Disk-diffusion assays measured inhibition zones at dilutions from 50% to 1.56% (v/v). MIC and MBC values were determined by broth microdilution. GC–MS profiling identified dominant components, and Spearman rank-order correlations (ρ) linked composition to activity. Shapiro–Wilk tests (W = 0.706–0.913, p ≤ 0.002) indicated non-normal data, so strain comparisons used Kruskal–Wallis one-way ANOVA with Dunn’s post hoc and Bonferroni correction. Results: Oregano, thyme and dittany oils—rich in carvacrol and thymol—exhibited the strongest activity, with MIC/MBC ≤ 0.0625% (v/v) against all strains and inhibition zones > 25 mm at 50%. No strain-specific differences were detected (H = 0.30–3.85; p = 0.998–0.571; p_adj = 1.000). Spearman correlations confirmed that carvacrol and thymol content strongly predicted efficacy (ρ = 0.527–0.881, p < 0.001). Oils dominated by non-phenolic terpenes (rosemary, peppermint, lavender, cistus, helichrysum) showed minimal or no activity. Conclusions: Phenolic-rich EOs maintain potent, strain-independent antimicrobial effects—including against multidrug-resistant and O157:H7 strains—via a multi-target mode that overcomes classical resistance. Their low-dose efficacy and GRAS status support their use as clean-label food preservatives or adjuncts to antibiotics or bacteriophages to combat antimicrobial resistance. Full article

The continuous monitoring of forest vegetation conditions is of the utmost importance. The commonly used tools for assessing vegetation conditions are the normalized difference vegetation index (NDVI) and its successor—the enhanced vegetation index (EVI). In this study, the NDVI and EVI were coupled with the data on the number of dead trees removed during sanitation felling in an area of 13,780 km² during the period 2015–2022. In order to determine which satellite-borne index best represents the actual condition of vegetation in forests of the European temperate zone, the classes of the trend in changes in the NDVI and EVI were compared with the respective trends in the volume of dead trees, following the assumption that a positive trend in the spectral index values should be reflected by a negative trend in the volume of dead trees, and vice versa. The analyses were carried out for pixels within the all-species mask in the study area and for pixels representing individual tree species. NDVI is a good predictor of forest vegetation in the European temperate zone and is substantially better than EVI. Spatially, NDVI yields more pixels showing a negative slope for the trend in changes in the spectral index values, while EVI seems to overestimate the number of positive slopes. A larger number of negative slopes in the trend in changes in NDVI seems to agree with the increasing volume of dead trees in the analysed period. Comparing the detected trend class masks for spectral indices and the multi-annual course of dead trees, in 12 out of 16 cases, the slopes of the trend in changes in NDVI agree with the slopes of the trend in the volume of dead trees, while for EVI, this number is reduced to 9. In addition, NDVI reflects the condition of coniferous tree species, Scots pine and Norway spruce, substantially better. Full article

Rockfalls, among the most common natural disasters, pose risks such as traffic congestion, casualties, and substantial property damage. Guizhou Province, with China’s fourth-longest highway network, features mountainous terrain prone to frequent rockfall incidents annually. Consequently, assessing highway rockfall risks in Guizhou Province is crucial for safeguarding the lives and travel of residents. This study evaluates highway rockfall risk through three key components: susceptibility, hazard, and vulnerability. Susceptibility was assessed using information content and logistic regression methods, considering factors such as elevation, slope, normalized difference vegetation index (NDVI), aspect, distance from fault, relief amplitude, lithology, and rock weathering index (RWI). Hazard assessment utilized a fuzzy analytic hierarchy process (AHP), focusing on average annual rainfall and daily maximum rainfall. Socioeconomic factors, including GDP, population density, and land use type, were incorporated to gauge vulnerability. Integration of these assessments via a risk matrix yielded comprehensive highway rockfall risk profiles. Results indicate a predominantly high risk across Guizhou Province, with high-risk zones covering 41.19% of the area. Spatially, the western regions exhibit higher risk levels compared to eastern areas. Notably, the Bijie region features over 70% of its highway mileage categorized as high risk or above. Logistic regression identified distance from fault lines as the most negatively correlated factor affecting highway rockfall susceptibility, whereas elevation gradient demonstrated a minimal influence. This research provides valuable insights for decision-makers in formulating highway rockfall prevention and control strategies. Full article