Search Results (1,060)

This study investigates the dynamic performance of mountainous crawler tractors during small-radius slope steering, providing theoretical support for power machinery design in hilly and mountainous regions. Addressing the mechanization demands in complex terrains and existing research gaps, a steering dynamics model is established. The model incorporates an amplitude-varied multi-peak cosine ground pressure distribution, employs position vectors and rotation matrices to characterize 3D pose variations in the tractor’s center of mass, and integrates slope angle, soil parameters, vehicle geometry, center-of-mass shift, bulldozing resistance, and sinkage resistance via d’Alembert’s principle. Numerical simulations using Maple 2024 analyzed variations in longitudinal offset of the instantaneous steering center, bilateral track traction forces, and bulldozing resistance with slope, speed, and acceleration. Variable-gradient steering tests on the “Soil-Machine-Crop” Comprehensive Experimental Platform demonstrated model accuracy, with <8% mean error and <12% maximum relative error between predicted and measured track forces. This research establishes a theoretical foundation for predicting, evaluating, and controlling the steering performance/stability of crawler tractors in complex slope conditions. Full article

Background/Objectives: Positive psychology interventions (PPIs) may enhance well-being in individuals with severe psychiatric conditions (SPCs), yet little is known about individual differences in treatment response. Methods: We conducted a secondary analysis of a single-blind, parallel-group randomized controlled trial. A total of 119 adults receiving outpatient mental health care were randomized to an 11-week multicomponent PPI plus treatment as usual (PPI + TAU) or TAU alone. A priori demographic and baseline clinical variables (e.g., age, gender, education, diagnosis, symptom severity) were tested as predictors and moderators of six well-being outcomes. Moderation analyses were conducted using the PROCESS macro (version 4.1) for SPSS version 29.0, with simple slopes explored for significant interactions. Analyses followed an intention-to-treat approach. Results: Individuals who were unemployed, had a diagnosis within the psychosis spectrum, or exhibited high interpersonal sensitivity showed improvements in well-being irrespective of the treatment modality received. Older patients, those attending more weekly therapy sessions, and individuals with less somatization, hostility, or life satisfaction levels responded particularly well to the specialized PPI + TAU treatment. While several interactions were significant at p < 0.01, none remained significant after Bonferroni–Holm correction. Nevertheless, the patterns were consistent and theoretically grounded. Conclusions: Individual characteristics may influence the effectiveness of PPIs in SPC populations. Identifying predictors and moderators can inform more personalized interventions. The findings warrant replication. Trial registration: ClinicalTrials.gov, NCT01436331. Full article

Snake robots are characterized by their flexibility and environmental adaptability, achieved through various optimized gaits. However, their forward propulsion still requires improvement. This challenge can be addressed by integrating wheels or legs, but these mechanisms often limit the ability of snake robots to perform most optimized gaits. In this article, we develop a novel multimodal snake robot, JiAo-II, with both body-based locomotion and wheeled locomotion to handle complex terrains. The mechanical design and implementation of JiAo-II are presented in detail, with particular emphasis on its innovative elliptical wheels and gear transmission mechanism. Experimental results validate the effectiveness and multifunctionality of JiAo-II across various scenarios, including traversing grasslands, crossing gaps, ascending slopes, navigating pipelines, and climbing cylindrical surfaces. Furthermore, a series of experiments are conducted to evaluate the performance of the wheel–body coordinated locomotion on uneven ground, demonstrating the robustness even without requiring external sensing or sophisticated control strategies. In summary, the proposed multimodal mechanism significantly enhances the locomotion speed, terrain adaptability and robustness of snake robots. Full article

Coseismic landslides are geological events in which slopes, either on the verge of instability or already in a fragile state, experience premature failure due to seismic shaking. On 5 September 2022, an Ms 6.8 earthquake struck Luding County, Sichuan Province, China, triggering numerous landslides that caused severe casualties and property damage. This study systematically interprets 13,717 coseismic landslides in the Luding earthquake’s epicentral area, analyzing their spatial distribution concerning various factors, including elevation, slope gradient, slope aspect, plan curvature, profile curvature, surface cutting degree, topographic relief, elevation coefficient variation, lithology, distance to faults, epicentral distance, peak ground acceleration (PGA), distance to rivers, fractional vegetation cover (FVC), and distance to roads. The analytic hierarchy process (AHP) was improved by incorporating frequency ratio (FR) to address the subjectivity inherent in expert scoring for factor weighting. The improved AHP, combined with the Pearson correlation analysis, was used to identify the dominant controlling factor and assess the landslide susceptibility. The accuracy of the model was verified using the area under the receiver operating characteristic (ROC) curve (AUC). The results reveal that 34% of the study area falls into very-high- and high-susceptibility zones, primarily along the Moxi segment of the Xianshuihe fault and both sides of the Dadu river valley. Tianwan, Caoke, Detuo, and Moxi are at particularly high risk of coseismic landslides. The elevation coefficient variation, slope aspect, and slope gradient are identified as the dominant controlling factors for landslide development. The reliability of the proposed model was evaluated by calculating the AUC, yielding a value of 0.8445, demonstrating high reliability. This study advances coseismic landslide susceptibility assessment and provides scientific support for post-earthquake reconstruction in Luding. Beyond academic insight, the findings offer practical guidance for delineating priority zones for risk mitigation, planning targeted engineering interventions, and establishing early warning and monitoring strategies to reduce the potential impacts of future seismic events. Full article

The bore field in ground source heat pump (GSHP) systems usually encounters thermal accumulation in long-term operation, but there is no quantitative index evaluating this process and its magnitude. A heat accumulation evaluation metric has been proposed, based on the linear trend Slope (°C/a) of the curve of soil temperature variation. Using this metric, the influence of various factors on soil temperature has been quantitatively analyzed. The results indicate that, under constant heating durations, each 10-day extension of cooling periods leads to an increase of 0.038 °C/a in soil temperature. Extending the recovery period within an annual cycle facilitates soil self-recovery and mitigates subsurface thermal accumulation. Increasing the spacing between boreholes effectively reduces thermal interference, whereas a greater number of boreholes exacerbates thermal accumulation. Deepening vertical boreholes from 100 m to 200 m reduces the average annual soil temperature increase by 0.1076 °C. Appropriately increasing backfill thermal conductivity enhances heat exchange efficiency and suppresses thermal accumulation. Higher water flow rates result in logarithmic increases in the evaluation metric, thereby intensifying soil thermal accumulation. Intermittent operation extends recovery periods, thereby alleviating soil thermal imbalance. Under balanced cooling and heating loads, increasing the system lifespan from 10 a to 30 a reduces the evaluation metric by 47.2%. Full article

Gas hydrate-bearing sediments in marine environments represent both a future energy source and a geohazard risk, prompting increasing international research attention. In the Shenhu area of the South China Sea, a large volume of drilling and laboratory data has been acquired in recent years, yet a comprehensive framework for evaluating the characteristics of key reservoir parameters remains underdeveloped. This study presents a spatially integrated and statistically grounded framework that captures regional-scale heterogeneity using multi-source in situ datasets. It incorporates semi-variogram modeling to assess spatial variability and provides statistical reference values for geological and geotechnical properties across the Shenhu Area. By synthesizing core sampling results, acoustic logging, and triaxial testing data, representative probability distributions and variability scales of hydrate saturation, porosity, permeability, and mechanical strength are derived, which are essential for numerical simulations of gas production and slope stability. Our results support the development of site-specific reservoir models and improve the reliability of early-phase hydrate exploitation assessments. This work facilitates the rapid screening of hydrate reservoirs, contributing to the efficient selection of potential production zones in hydrate-rich continental margins. Full article

Glaciers and glacierets of the Kuznetsky Alatau Mountains are distributed at altitudes of 1200–1500 m above sea level, which is not typical for continental areas. The main factor contributing to the persistence of glaciation here is abundant winter precipitation. According to ground surface temperature measurements, the negative annual values are typical for upper glacier boundaries only. Since intensive study during the compilation of the USSR Glacier Inventory (1965–1980), the glaciation of the region has undergone notable changes. To assess the current state of glaciation, Sentinel-2 satellite images were used; contours of the glaciers were traced on the basis of images from 2021 to 2023. In total, 78 glaciers and 57 glacierets were identified. UAV imagery and field inspection were used for validation. The total glaciated area has reduced from 8.5 to 3.1 km², which is 50–75% for selected river basins, with slope morphological types decreasing the most. According to our opinion, the morphological classification requires clarification due to absence of hanging glaciers, described previously. Full article

The commented paper uses arbitrary and unsubstantiated hypotheses to attribute land subsidence phenomena in the Amyntaion basin to the operations of the Public Power Corporation (PPC) surface coal mine, disregarding, or at least grossly underestimating, the effect of about 600 pumped deep wells for irrigation purposes all over the basin. In addition to the huge difference in the pumped quantities of water from the aquifer, ground water table lowering due to the PPC mine has negligible influence at distances over 500 m from the edge of the mine, while the areas examined in the paper are at distances of several kilometers from the edge of the mine. Furthermore, the authors attribute the landslide that occurred in the mine in 2017 to the steep excavation slopes of the mine and the increased groundwater pore pressure due to reduced peripheral pumping, which is completely inaccurate. To build their case, the authors of the commented paper disregard multiple references in research publications on the above issues, as explained in the main text of this discussion. Full article

Wheeled rovers are widely used in lunar and planetary exploration missions owing to their mechanical simplicity and energy efficiency. However, they face serious mobility challenges on sloped soft terrain, especially in terms of sideslip and loss of attitude angle when traversing across slopes. Previous research proposed using wheelbase extension/contraction and intentionally sinking wheels into the ground, thereby increasing shear resistance and reducing sideslip. Building upon this concept, this study proposes a novel recovery method that integrates beam extension/contraction and Archimedean screw-shaped wheels to enable lateral movement without rotating the rover body. The beam mechanism allows for independent wheel movement, maintaining stability by anchoring stationary wheels during recovery. Meanwhile, the helical structure of the screw wheels helps reduce lateral earth pressure by scraping soil away from the sides, improving lateral drivability. Driving experiments on a sloped sandbox test bed confirmed that the proposed 2DPPL (two-dimensional push-pull locomotion) method significantly reduces sideslip and prevents a drop in attitude angle during slope traversal. Full article

Slope stability assessment is a critical component of engineering safety. Conventional analytical methods frequently struggle to integrate heterogeneous slope data and model intricate failure mechanisms, thereby constraining their efficacy in practical engineering scenarios. To tackle these issues, this study presents a novel slope stability classification model grounded in the Optuna-TPE-CatBoost framework. By leveraging the Tree-structured Parzen Estimator (TPE) within the Optuna framework, the model adaptively optimizes CatBoost hyperparameters, thus enhancing prediction accuracy and robustness. It incorporates six key features—slope height, slope angle, unit weight, cohesion, internal friction angle, and the pore pressure ratio—to establish a comprehensive and intelligent assessment system. Utilizing a dataset of 272 slope cases, the model was trained with k-fold cross-validation and dynamic class imbalance strategies to ensure its generalizability. The optimized model achieved impressive performance metrics: an area under the receiver operating characteristic curve (AUC) of 0.926, an accuracy of 0.901, a recall of 0.874, and an F1-score of 0.881, outperforming benchmark algorithms such as XGBoost, LightGBM, and the unoptimized CatBoost. Validation via engineering case studies confirms that the model accurately evaluates slope stability across diverse scenarios and effectively captures the complex interactions between key parameters. This model offers a reliable and interpretable solution for slope stability assessment under complex failure mechanisms. Full article

Accurate above-ground biomass (AGB) quantification is confounded by signal saturation and data fusion challenges, particularly in structurally complex ecosystems like bamboo forests. To address these gaps, this study developed a two-stage framework to map the AGB of Dendrocalamus giganteus in a subtropical mountain environment. This study first employed Empirical Bayesian Kriging Regression Prediction (EBKRP) to spatialize sparse GEDI and ICESat-2 LiDAR metrics using Sentinel-2 and topographic covariates. Subsequently, a stacked ensemble model, integrating four machine learning algorithms, predicted AGB from the full suite of continuous variables. The stacking model achieved high predictive accuracy (R² = 0.84, RMSE = 11.07 Mg ha⁻¹) and substantially mitigated the common bias of underestimating high AGB, improving the predicted observed regression slope from a base model average of 0.63 to 0.81. Furthermore, SHAP analysis provided mechanistic insights, identifying the canopy photon rate as the dominant predictor and quantifying the ecological thresholds governing AGB distribution. The mean AGB density was 71.8 ± 21.9 Mg ha⁻¹, with its spatial pattern influenced by elevation and human settlements. This research provides a robust framework for synergizing multi-source remote sensing data to improve AGB estimation, offering a refined methodological pathway for large-scale carbon stock assessments. Full article

In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research into permafrost dynamics. Climate warming has accelerated permafrost degradation, leading to a range of geological hazards, most notably widespread thermokarst landslides. This study investigates the spatiotemporal distribution patterns and influencing factors of thermokarst landslides in Qinghai Province through an integrated approach combining field surveys, remote sensing interpretation, and statistical analysis. The study utilized multi-source datasets, including Landsat-8 imagery, Google Earth, GF-1, and ZY-3 satellite data, supplemented by meteorological records and geospatial information. The remote sensing interpretation identified 1208 cryogenic hazards in Qinghai’s permafrost regions, comprising 273 coarse-grained soil landslides, 346 fine-grained soil landslides, 146 thermokarst slope failures, 440 gelifluction flows, and 3 frost mounds. Spatial analysis revealed clusters of hazards in Zhiduo, Qilian, and Qumalai counties, with the Yangtze River Basin and Qilian Mountains showing the highest hazard density. Most hazards occur in seasonally frozen ground areas (3500–3900 m and 4300–4900 m elevation ranges), predominantly on north and northwest-facing slopes with gradients of 10–20°. Notably, hazard frequency decreases with increasing permafrost stability. These findings provide critical insights for the sustainable development of cold-region infrastructure, environmental protection, and hazard mitigation strategies in alpine engineering projects. Full article

UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R² = 0.98) and vertical (R² = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article

The Mw 7.8 Gorkha Earthquake of 25 April 2015 triggered over 25,000 landslides across central Nepal, with 4775 events concentrated in Gorkha District alone. Despite substantial advances in landslide susceptibility mapping, existing studies often overlook the compound role of post-seismic rainfall and lack robust spatial validation. To address this gap, we validated an ensemble machine learning framework for co-seismic landslide susceptibility modeling by integrating seismic, geomorphological, hydrological, and anthropogenic variables, including cumulative post-seismic rainfall. Using a balanced dataset of 4775 landslide and non-landslide instances, we evaluated the performance of Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) models through spatial cross-validation, SHapley Additive exPlanations (SHAP) explainability, and ablation analysis. The RF model outperformed all others, achieving an accuracy of 87.9% and a Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) value of 0.94, while XGBoost closely followed (AUC = 0.93). Ensemble models collectively classified over 95% of observed landslides into High and Very High susceptibility zones, demonstrating strong spatial reliability. SHAP analysis identified elevation, proximity to fault, peak ground acceleration (PGA), slope, and rainfall as dominant predictors. Notably, the inclusion of post-seismic rainfall substantially improved recall and F1 scores in ablation experiments. Spatial cross-validation revealed the superior generalizability of ensemble models under heterogeneous terrain conditions. The findings underscore the value of integrating post-seismic hydrometeorological factors and spatial validation into susceptibility assessments. We recommend adopting ensemble models, particularly RF, for operational hazard mapping in earthquake-prone mountainous regions. Future research should explore the integration of dynamic rainfall thresholds and physics-informed frameworks to enhance early warning systems and climate resilience. Full article

This study analyzes the lacustrine hydrocarbon source rocks of the Lower Cretaceous in the Erdengsumu sag of the Erlian Basin, evaluating their characteristics and identifying areas with oil resource potential, while also investigating the ancient lake environment, material source input, and controlling factors, ultimately developing a sedimentary model for lacustrine hydrocarbon source rocks. The findings suggest the following: (1) The lower Tengger Member (K₁bt₁) and the Aershan Formation (K₁ba) are the primary oil-producing strata, with an effective hydrocarbon source rock exhibiting a lower limit of total organic carbon (TOC) at 0.95%. The Ro value typically remains below 0.8%, indicating that high-maturity oil production has not yet been attained. (2) The oil generation threshold depths for the Dalestai and Sayinhutuge sub-sags are 1500 m and 1214 m, respectively. The thickness of the effective hydrocarbon source rock surpasses 200 m, covering areas of 42.48 km² and 88.71 km², respectively. The cumulative hydrocarbon generation intensity of wells Y1 and Y2 is 486 × 10⁴ t/km² and 26 × 10⁴ t/km², respectively, suggesting that the Dalestai sub-sag possesses considerable petroleum potential. The Aershan Formation in the Chagantala sub-sag has a maximum burial depth of merely 1800 m, insufficient to attain the oil generation threshold depth. (3) The research area’s productive hydrocarbon source rocks consist of organic matter types I and II₁. The Pr/Ph range is extensive (0.33–2.07), signifying a reducing to slightly oxidizing sedimentary environment. This aligns with the attributes of small fault lake basins, characterized by shallow water and robust hydrodynamics. (4) The low ratio of ∑nC₂₁₋/∑nC₂₂₊ (0.36–0.81), high CPI values (>1.49), and high C₂₉ sterane concentration suggest a substantial terrestrial contribution, with negligible input from aquatic algae–bacterial organic matter. Moreover, as sedimentation duration extends, the contribution from higher plants progressively increases. (5) The ratio of the width of the deep depression zone to the width of the depression in the Erdengsumu sag is less than 0.25. The boundary fault scale is small, its activity is low, and there is not much input from the ground. Most of the source rocks are in the reducing sedimentary environment of the near-lying gently sloping zone. Full article