Search Results (1,565)

Mining activities are conducted to extract valuable minerals from the Earth, which are used to manufacture many objects. However, these operations generate landform alterations, such as deep excavations, artificial embankments, and landscape reshaping. In this study, landform changes were monitored in a mining area in Mazapil, Zacatecas, Mexico, using geomatic techniques. Multitemporal Landsat satellite images and digital elevation models (DEMs) from different years were used to detect and quantify landform alterations and estimate the volumes of removed material. The results show ground depressions greater than −333 m and waste material accumulations greater than +152 m, with an average standard deviation of ±3.6 m. A total excavation volume of 413.524 million m³ and a total fill volume of 431.194 million m³ were quantified, with an estimated standard deviation of ±810 m³. The proposed methodology proved effective for the remote quantification of large-scale relief disturbances in open-pit mining areas. It can also be used for environmental monitoring and hydrological risk assessment in active and inactive mining areas. Full article

Climate-change-induced thermal stress poses a significant threat to cold-adapted aquatic species, particularly fish endemic to high-altitude ecosystems such as Gymnocypris eckloni, which is native to the Qinghai-Tibetan Plateau. To elucidate the molecular and metabolic mechanisms underlying their response to elevated temperatures, we integrated RNA-seq, miRNA-seq, and LC-MS-based metabolomic analyses of liver tissue from fish exposed to chronic thermal stress (HT) versus control (CT) conditions. Although no significant differences were observed in growth parameters, histopathological examination revealed structural damage under heat stress. Transcriptomic analysis identified widespread dysregulation of genes involved in energy metabolism, with significant downregulation of pathways related to amino acid, fatty acid, glucose, and oxidative phosphorylation. In contrast, upregulated DEGs were enriched in N-glycan biosynthesis, protein processing in the endoplasmic reticulum, and phagosome. Concomitant miRNA profiling revealed differentially expressed miRNAs, including miR-196a-5p, miR-132-3p, and miR-181b-5p, which were predicted to regulate key metabolic genes such as ugt1a1, pepck, and calr. Metabolomic analysis further demonstrated significant alterations in metabolic profiles, with glutathione metabolism, tryptophan metabolism, steroid hormone biosynthesis, and pyruvate metabolism emerging as central pathways in the heat stress response. Integrated multi-omics analysis confirmed coordinated regulation of these pathways, highlighting the critical role of glutathione and tryptophan, as well as disruptions in purine and energy metabolism. The DEMiR-DEG-DEM networks involving miR-196a-5p-pepck-PEP, miR-133a-3p-gne-UDP-GlcNAc, and miR-132-3p-ugt1a1-Bilirubin may play an important role in thermal stress. This study provided a new perspective on the molecular, regulatory, and metabolic adaptations of Gymnocypris eckloni to thermal stress, identifying potential biomarkers and regulatory networks that may inform conservation strategies for cold-water fish under global warming. Full article

Urban heat island (UHI), a significant environmental issue caused by urbanization, is a pressing challenge in modern society. To mitigate it, urban thermal policies have been implemented globally. However, despite differences in topographical and environmental characteristics between cities and within the same city, these policies are largely uniform and fail to reflect contexts, creating notable drawbacks. This study analyzed three cities in Korea with high land surface temperatures (LSTs) to identify factors influencing LST by applying Extreme Gradient Boosting (XGBoost) with Shapley Additive explanations (SHAP) and Geographically Weighted Regression (GWR). Each variable was derived by calculating the average values from May to September 2020. LST was the dependent variable, and the independent variables were chosen based on previous studies: Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), ALBEDO, Population Density (POP_D), Digital Elevation Model (DEM), and SLOPE. XGBoost-SHAP was used to derive the relative importance of the variables, followed by GWR to assess spatial variation in effects. The results indicate that NDBI, reflecting building density, is the primary factor influencing the thermal environment in all three cities. However, the second most influential factor differed by city: SLOPE had a strong effect in Daegu, characterized by surrounding mountains; POP_D had greater influence in Incheon, where population distribution varies due to clustered islands; and DEM was more influential in Seoul, which contains a mix of plains, mountains, and river landscapes. Furthermore, while NDBI and ALBEDO consistently contributed to LST increases across all regions, the effects of the remaining variables were spatially heterogeneous. These findings highlight that urban areas are not homogeneous and that variations in land use, development patterns, and morphology significantly shape heat environments. Therefore, UHI mitigation strategies should prioritize improving urban form while incorporating localized planning tailored to each region’s physical and socio-environmental characteristics. The results can serve as a foundation for developing strategies and policy decisions to mitigate UHI effects. Full article

Granular materials usually require the design of specialised equipment for their processing and transport. Nowadays, equipment design increasingly relies on modelling techniques to support decision-making during the design process. The Discrete Element Method (DEM) is a numerical technique that enables the prediction of forces and displacements acting on individual particles. The design of ship loaders, dumpers, screw conveyors, conveyor belts, moving floors, bucket elevators, truck feeders, hoppers, and silos can all benefit from DEM-based predictions of particle behaviour. To develop DEM models able to accurately predict the particle behaviour, it is essential to characterise the material by determining its physical and mechanical properties. Key parameters include particle density, elastic modulus, Poisson’s ratio, particle-to-wall friction, and particle-to-particle friction. In this research, a methodology is proposed for determining the particle-to-particle friction coefficient. For this purpose, a test apparatus was designed and constructed to perform direct measurements of sliding angles. The proposed method yielded an average particle-to-particle friction coefficient of μ = 0.62, based on twelve independent sliding-angle tests. The measurements showed an overall relative standard deviation of 3.4%, indicating good repeatability and demonstrating that the developed apparatus provides reliable and consistent friction values for granular particles. The primary aim of the study was to validate the test method. Hand-made clay samples were produced, arranging the particles in different configurations and placing them in various orientations on the apparatus. The results confirm that the proposed method is suitable for determining representative particle-scale friction parameters, offering a simple and repeatable approach that can support DEM calibration and enhance the predictive capability of granular flow simulations. Full article

Deep coalbed methane (DCBM) reservoirs often experience severe proppant flowback during large-scale hydraulic fracturing, which undermines fracture conductivity and limits long-term recovery. The critical flowback velocity (CFVP) is the key parameter controlling proppant pack instability and flowback. In this study, the instability and flowback behavior of proppant packs throughout the entire production process, from early water flowback to late gas-dominated stages, were systematically investigated. Proppant flowback under closure stress was simulated using a CFD–DEM approach to clarify the flowback process and mechanical mechanisms. Laboratory experiments on coal fracture surfaces under gas-liquid two-phase and gas-liquid-solid three-phase conditions were then conducted to quantify CFVP and its variation across different production stages. Finally, a semi-empirical CFVP predictive model was developed through dimensional analysis. Results show that proppant flowback proceeds through three distinct stages—no flowback, gradual flowback, and rapid flowback. Increasing fracture width reduces proppant pack stability and lowers CFVP but allows higher flow capacity, and within the typical gas and water production ranges of deep coalbed methane reservoirs, flowback is significantly reduced when the width exceeds about 8 mm. Closure stress enhances CFVP below 15 MPa but has little effect above this threshold, while higher stresses progressively stabilize the proppant pack and minimize flowback. Larger average proppant size raises CFVP and preserves conductivity, whereas higher gas–liquid ratios elevate CFVP and reduce flowback, with ratios above 40 sustaining consistently low flowback levels. These findings clarify the mechanisms and threshold conditions of proppant flowback, establish quantitative CFVP benchmarks, and deliver theoretical as well as experimental guidance for optimizing DCBM production. Full article

Visible cameras are widely adopted low-cost instruments for volcano monitoring. Images can be used to characterize volcanic activity of variable intensity and style and to estimate key eruption source parameters that are essential for assessing volcanic hazards. Nevertheless, the analysis of images from visible cameras is subject to significant sources of uncertainty and operational limitations. In addition to visibility issues caused by meteorological phenomena and variable illumination, assigning the pixel position of an object of interest (e.g., volcanic plumes, ballistic projectiles) to a specific geographic location and elevation is not straightforward, introducing substantial uncertainty in the estimation of eruption parameters. We present PhixCam, a Python tool that allows the user to georeference in the 3D space the visual field of surveillance cameras from minimal input data: a DEM, the camera position, and a reference image where the framed relief can be outlined. The software includes functions to construct conversion matrices that can be adopted to translate the position of pixels into elevation above sea level when different emission directions of volcanic products are considered, thereby allowing users to assess the confidence of the results. This code was tested on a series of cameras of the Chilean Volcanic Surveillance Network, showing its operative potential in volcanic observatories, and on historical pictures, allowing us to estimate data of interest in volcanology for poorly monitored volcanic events. Full article

Current research on net ecosystem productivity (NEP) still lacks sufficient attention to the impacts of extreme climate events, particularly in understanding the interactive response mechanisms of carbon sinks under extreme climate conditions. This study investigated the spatiotemporal dynamics of NEP and its interactive mechanisms in Dongying, China, from 2001 to 2023 under extreme climate conditions. Using trend slope estimation, geographical detector, and XGBoost methods, we systematically revealed the responses of NEP to the factors including climatic changes, human activities, vegetation growth status, and topographic features. The results indicated that NEP exhibited an overall fluctuating yet increasing trend during 2001–2023. The normalized difference vegetation index (NDVI, for vegetation growth status) and the digital elevation model (DEM, for terrain features) were identified as the dominant factors influencing the spatial heterogeneity of NEP. However, extreme precipitation and high temperature events significantly diminished the positive contribution of the NDVI to NEP, while simultaneously amplifying the negative influence of the DEM on NEP. These two concurrent changes superimposed on each other, especially after 2017, further constrained the potential for carbon sequestration. Furthermore, a lag effect was observed in the response mechanisms of NEP to factors under the influence of precipitation and high-temperature climates. These findings highlight the critical and complex role of extreme climate in reorganizing the contributions of factors and intensifying pressure on the carbon sequestration capacity of ecosystems. Full article

Landscape character assessment (LCA) is a systematic approach used to classify, describe, and analyze the physical and cultural attributes that define the landscape. The traditional approaches to LCA are fundamentally subjective and descriptive, relying on human evaluations of aesthetic value, and they often show inconsistencies in results when assessed by different observers for the same landscape. This research aims to establish a spatial and quantitative methodology through GIS for evaluating the landscape character of King Khalid University (KKU)’s campus in the Southern Province of Saudi Arabia, which is considered crucial for designing a sustainable and context-sensitive landscape. To identify the feasible developed areas and their sustainable characteristics, three key landscape variables were measured and spatially expressed, subsequently averaged to categorize landscape character. The variables include land use and land cover, which were obtained from Sentinel 2 remote sensing data through supervised classification, as well as landforms and hydrological settings derived from a digital elevation model (DEM) utilizing GIS functionalities. The findings revealed three distinct landscape characters, each characterized by quantifiable landscape attributes. The landscapes exhibiting the most significant character encompass approximately 20% (1074 ha) of the study area, whereas those with the least significance account for 6.5% (342 ha). The remaining 73.5% (3884 ha) is classified as landscapes with an average significance character. The results provide a solid scientific basis for choosing locations in the campus’s study area that promote environmentally friendly and sustainable landscape development. This method improves objectivity in LCA and offers a reproducible framework for implementation in arid and semi-arid areas. Full article

Camel poll gland tissues (PGs) secrete amber liquid and volatile substances during the breeding season, inducing estrus and mating in female camels. These processes are mainly regulated by steroid hormones and their receptors, including the Androgen Receptor (AR). However, the functional components of PGs and their regulatory mechanisms in camel reproduction remain unclear. Therefore, in this study, we identified candidate differentially expressed metabolites (DEMs) and differentially expressed proteins (DEPs) associated with steroids through a multi-omics analysis of PGs during the male camel breeding season. We found that total cholesterol and testosterone concentrations were significantly increased in camel PGs at different stages of the breeding season. DEMs and DEPs related to cholesterol or steroids were analyzed using metabolomics and data-independent acquisition proteomics in the PGs of male Bactrian camels at different stages (early and peak breeding seasons), and the potential mechanism of steroid hormone synthesis was further explored. The metabolomics results identified 13 DEMs related to steroids in PGs at different stages. The proteomics results revealed seven GO terms and 69 DEPs related to steroids, with apolipoprotein E (APOE) identified as the core DEP. Pathway analysis confirmed that APOE and related DEPs were involved in cholesterol and steroid hormone synthesis. Immunostaining showed that APOE and AR were co-localized in the cytoplasm of acinar epithelial cells, and exhibited opposite expression trends in PGs during different breeding stages. These findings demonstrate that APOE- and AR-mediated cholesterol metabolism plays an important role in steroid hormone synthesis during camel reproductive activity, providing valuable insights into the mechanisms of steroid synthesis in PGs. This study offers a theoretical framework for understanding camel reproductive biology, particularly the interplay between APOE and AR in regulating cholesterol metabolism and steroidogenesis. Full article

To clarify the regulatory laws of the fines content (FC) and particle size ratio (SR) on the mechanical properties of sand–fines mixtures and reveal the underlying microscopic mechanical mechanisms, this study takes sand–fines mixtures composed of natural river sand and silt as the research object. It systematically investigates the macro-mechanical behaviors and micro-interaction mechanisms of the mixtures by combining laboratory triaxial tests and discrete element method (DEM) simulations. First, through conducting triaxial drained shear tests on mixtures with three particle size ratios (SR = 9.1, 18.7, and 39.7) under seven fines contents (FC = 0%, 10%, 20%, 30%, 50%, 70%, and 100%), it is found that both the peak friction angle (φ_ps) and critical-state friction angle (φ_cs) of sand–fines mixtures show a “first increase, then decrease” trend with the increase in FC. The peak inflection points of their variation curves are the threshold fines content related to SR; meanwhile, a fines content below this threshold has an inhibitory effect on dilatancy, while that above this threshold exerts a promotive effect on dilatancy. Subsequently, by exploring the microscopic contact behaviors of sand–fines mixtures, it is observed that, under the fines content corresponding to the highest peak strength, the strong contact network and weak contact network inside the material form an optimal coordination between efficient load-bearing and stable support. This coordination enables the macro-strength of the mixture to reach the peak at this fines content. In addition, by modifying the weight coefficient of fabric anisotropy, a unique linear relationship between the fabric anisotropy of strong contacts and the stress ratio can be established, confirming that the strong contact network plays a core mechanical role in mixtures with different FC values. Full article

Current lake and reservoir water body extraction algorithms are confronted with two critical challenges: (1) design dependency on specific geographical features, leading to constrained cross-regional adaptability (e.g., the JRC Global Water Body Dataset achieves ~90% overall accuracy globally, while the ESA WorldCover 2020 reaches ~92% for water body classification, both showing degraded performance in complex karst terrains); (2) information loss due to cloud occlusion, compromising dynamic monitoring accuracy. To address these limitations, this study presents a multi-feature fusion and multi-level hierarchical extraction algorithm for lake and reservoir water bodies, leveraging the Google Earth Engine (GEE) cloud platform and Sentinel-2 multispectral imagery in the karst landscape of Bijie City. The proposed method integrates the Automated Water Extraction Index (AWEIsh) and Modified Normalized Difference Water Index (MNDWI) for initial water body extraction, followed by a comprehensive fusion of multi-source data—including Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Red-Edge Index (NDREI), Sentinel-2 B8/B9 spectral bands, and Digital Elevation Model (DEM). This strategy hierarchically mitigates vegetation shadows, topographic shadows, and artificial feature non-water targets. A temporal flood frequency algorithm is employed to restore cloud-occluded water bodies, complemented by morphological filtering to exclude non-target water features (e.g., rivers and canals). Experimental validation using high-resolution reference data demonstrates that the algorithm achieves an overall extraction accuracy exceeding 96% in Bijie City, effectively suppressing dark object interference (e.g., false positives due to topographic and anthropogenic features) while preserving water body boundary integrity. Compared with single-index methods (e.g., MNDWI), this method reduces false positive rates caused by building shadows and terrain shadows by 15–20%, and improves the IoU (Intersection over Union) by 6–13% in typical karst sub-regions. This research provides a universal technical framework for large-scale dynamic monitoring of lakes and reservoirs, particularly addressing the challenges of regional adaptability and cloud compositing in karst environments. Full article

The ballast consists of angular particles whose main function is to transmit and distribute train loads to the soil. However, under repeated loads, these particles wear down and break, causing permanent settlement, reducing track stability, and increasing maintenance. Characterizing stresses and deformations under monotonic and cyclic loading is essential to predict short- and long-term performance of railway systems. This numerical study evaluates the behavior of improved ballast materials, considering particle breakage. A hybrid Finite Difference and Discrete Element model was used to simulate the multiscale response of the track system under realistic loading conditions. The model was calibrated using data from laboratory tests conducted by various researchers. The performance of conventional ballast was compared with alternative mixtures, analyzing vertical displacements, stress distribution, safety factor, and particle breakage rates. Results show that the basalt-rubber composite significantly enhances ballast performance by reducing settlements and subgrade stresses while improving resistance to particle breakage. The FDM-DEM coupled approach effectively captures micromechanical interactions and breakage mechanisms, offering valuable insights for optimizing track design based on quantifiable performance criteria. Overall, the findings indicate the hybrid model and breakage–contact criteria approximated system behavior, while alternative ballast compositions improved durability, reduced maintenance, and supported resilient railway solutions. Full article

To address issues in traditional vegetable transplanter planting mechanisms such as poor hole-forming quality and low seedling uprightness, a seven-bar linkage planting mechanism with posture compensation of seedling entering soil was designed. By establishing a mathematical model of the planting mechanism and developing visual auxiliary optimization software, the optimal mechanism parameters for the best planting trajectory were determined. A DEM–MBD (Discrete Element Method and Multibody Dynamics) coupling simulation model of planting mechanism-soil-seedlings was established. The planting frequency, opening width, and opening time of the planter were used as factors, and the soil backflow and seedling uprightness were used as evaluation indicators. A quadratic regression orthogonal rotation combination simulation test was carried out. The regression model was established using Design-Expert 12.0 software to analyze the influence of various factors on the indicators. Response surface methodology was simultaneously applied for comprehensive optimization of the influencing factors. The optimal parameter combination obtained was as follows: planting frequency 57 plants/min, opening width 48.5 mm, opening time 0.76 s, corresponding to a soil backflow of 0.67 and seedling uprightness of 80.35°. Field tests were conducted to verify the following mechanism: the soil backflow was 0.64, and the seedling uprightness was 78.49°, which were 4.47% and 2.31% different from the regression model optimization results, respectively. The error variation was small, indicating that the simulation results were effective and the mechanism design was reasonable. This study provides a reference for the development of high-quality and efficient vegetable transplanters. Full article

To address the issue that the current research on TBM disc cutter rock breaking insufficiently considers actual stratified rock masses, this study constructs numerical models of stratified rock masses with different bedding dip angles and bedding spacings based on the discrete element method (DEM). The whole process of TBM disc cutter rock breaking is numerically simulated through the displacement loading mode. The research results show that the bedding dip angle has a significant impact on the crack propagation mode. When α = 45°, the bedding intersects with the contact point of the disc cutter, and cracks penetrate directly along the bedding without an obvious “crushed zone”, resulting in the minimum number of cracks. The bedding spacing regulates the rock-breaking effect in stages. When d = 45°, the “crushed zone” interacts with two beddings to form three branch cracks, reaching the peak number of cracks and achieving the optimal rock-breaking efficiency. The cracks generated by disc cutter rock breaking exhibit the characteristic of “slow initial growth and rapid later surge” with the increase in time steps, which is highly consistent with the actual mechanical process of rock breaking. This study reveals the influence mechanism of bedding properties on TBM disc cutter rock breaking, verifies the reliability of the DEM combined with PB and SJ models in the simulation of stratified rock mass breaking, and provides theoretical support and data references for the parameter optimization of TBM disc cutters and efficient tunneling under complex stratified geological conditions. Full article

(1) Background: This study aims to systematically identify key candidate genes and the regulatory networks governing ovarian development in sheep breeds with divergent fecundity. Focusing on elucidating the central regulatory roles of these factors during distinct ovarian developmental stages in highly prolific breeds, the research seeks to reveal the mechanism by which multilevel regulatory networks synergistically determine ewe reproductive capacity. (2) Methods: This study utilized the ovaries from the low-fecundity sheep breed Ujumqin sheep, the high-fecundity breed small-tailed Han sheep, and various developmental stages of small-tailed Han sheep as research subjects. Through whole-transcriptome sequencing analysis, differentially expressed mRNAs(DEGs) and non-coding RNAs (ncRNAs) were screened, and a ceRNA regulatory network was constructed and subjected to bioinformatic analysis. The dual-luciferase reporter gene detection system was employed to validate the targeting relationships within the obtained key circRNA-miRNA-mRNA networks. Finally, qRT-PCR was used to verify the accuracy of the sequencing results. (3) Results: Our analysis constructed two distinct ceRNA networks: one from different fecundity groups (116 DECs, 46 DEMs, 82 DEGs) and another from different ovarian stages (186 DECs, 143 DEMs, 338 DEGs). Functional enrichment revealed key reproduction-related pathways, including Mitogen-Activated Protein Kinase(MAPK), Janus Kinase-Signal Transducer and Activator of Transcription(JAK-STAT), and WNT signaling in the fecundity comparison, and MAPK, Ras, WNT, Hippo signaling in the developmental stage comparison. Integrated analysis identified a core circRNA-miRNA-mRNA network, pinpointing circRNA2058-miR-9226-5p-MET as a central regulatory axis. The dual-luciferase assay confirmed that circRNA2058 acts as a sponge for miR-9226-5p, thereby mediating MET expression. qRT-PCR validation of randomly selected RNAs confirmed the sequencing reliability. (4) Conclusions: this study deciphers a synergistic regulatory network and identifies, for the first time, the pivotal circRNA2058-miR-9226-5p-MET ceRNA axis as an potential critical molecular switch driving follicular dominance in sheep. This discovery provides a molecular foundation for targeting core regulators of ovine reproductive efficiency and offers significant insights for innovative strategies in enhancing sheep reproduction. Full article