Search Results (334)

The growing concerns over nuclear power plant safety in the wake of extreme impact events have highlighted the need for containment structures with superior resistance to large commercial aircraft strikes. Conventional reinforced concrete containment has shown limitations in withstanding high-mass and high-velocity impacts, posing potential risks to structural integrity and operational safety. Addressing this challenge, this study focuses on the dynamic impact resistance and vibration behavior of steel–ultra-high-performance concrete (S-UHPC) composite containment, aiming to enhance nuclear facility resilience under beyond-design-basis aircraft impact scenarios. Validated finite element models in LS-DYNA were developed to simulate impacts from four representative large commercial aircraft types, considering variations in wall and steel plate thicknesses, UHPC grades, and soil–structure interaction conditions. Unlike existing studies that often focus on isolated parameters, this work conducts a systematic parametric analysis integrating multiple aircraft types, structural configurations, and foundation conditions, providing comprehensive insights into both global deformation and high-frequency vibration behavior. Comparative analyses with conventional reinforced concrete containment were performed, and floor response spectra were evaluated to quantify high-frequency vibration characteristics under different site conditions. The results show that S-UHPC containment reduces peak displacement by up to ~24% compared to reinforced concrete of the same thickness while effectively localizing core damage without through-thickness failure. In addition, aircraft impacts predominantly excite 90–125 Hz vibrations, with soft soil conditions amplifying acceleration responses by more than four times, underscoring the necessity of site-specific dynamic analysis in nuclear containment and equipment design. Full article

This paper analyzes the seismic performance and damage characteristics of high-rise frame-core-tube structures on soft soil, explicitly incorporating dynamic soil–pile–structure interaction (SSI). A refined 3D finite element model of a 52-storey soil–pile–structure system was developed in ABAQUS, utilizing viscous-spring boundaries and the equivalent nodal force method for seismic input. Nonlinear analyses under six seismic waves were compared to a fixed-base model neglecting SSI. Key findings demonstrate that SSI significantly alters structural response; it amplifies lateral displacements and inter-storey drift ratios throughout the structure, particularly at the top level. While total base shear decreased, frame column base shear forces substantially increased. SSI also reduced peak top-storey accelerations, diminished short-period spectral components, and prolonged the predominant period of response spectra. Analysis of member damage revealed SSI generally reduced compressive and tensile damage in core walls, floor slabs, and frame beams. Principal compressive stresses at the base of frame columns increased under SSI. These results highlight the necessity of including dynamic SSI in seismic analysis for high-rises on soft soil, specifically due to its detrimental amplification of forces in frame columns. Full article

In arid and semi-arid regions, soil salinization has emerged as an escalating environmental challenge. Soil salinity not only alters the soil structure but also influences water movement and distribution. The coupled processes of water movement, heat transfer, and solute transport in the vadose zone interact dynamically, warranting an in-depth investigation into coupled processes of matter and energy. This study developed a numerical model of coupled water-vapor–heat–salt transport in the vadose zone, validated through evaporation experiments and compared with a conventional model excluding osmotic potential. It is found that salt presence reduces evaporation rates while enhancing soil moisture movement. Liquid water movement is primarily governed by matric and osmotic potential gradient, whereas water vapor movement is dominated by temperature gradients. Matric potential influences water vapor movement only at the soil surface, and the impact of salt on water vapor movement diminishes with increasing water content. Notably, matric potential significantly affects water vapor movement only when soil water vapor relative humidity is below unity. The proposed model effectively describes multi-field coupling transport and clarifies the role of osmotic potential in regulating liquid and vapor water dynamics. Full article

Iron is a limiting factor for plant and microbial growth because, in soil environments, it is predominantly present as oxyhydroxide minerals, rendering it unavailable to plants and microorganisms. Siderophores are chelating agents secreted to solubilize iron and facilitate its uptake. To understand the evolutionary and ecological dynamics of microbial communities, as well as the evolution of pathogens within hosts, it is essential to study the genes shared between microorganisms for environmental adaptation and survival. In this study, we conducted microbiological assays to evaluate the effect of the siderophore produced by Rouxiella badensis strain SER3 on the mycelial growth of fungal pathogens such as Fusarium brachygibbosum 4BF. Using spectrophotometric techniques and bioinformatics tools, we identified desferrioxamine E (nocardamine) in the culture supernatant, and the corresponding biosynthetic gene cluster in the SER3 genome was confirmed through antiSMASH analysis and synteny comparisons. Gene expression analysis by RT-PCR showed differential expression of biosynthetic precursors when strain SER3 was grown alone or in interaction with fungal pathogen. Finally, scanning electron microscopy revealed structural damage to F. brachygibbosum hyphae during co-culture with strain SER3. These results suggest that the production of desferrioxamine E may act as a biocontrol mechanism employed by R. badensis SER3 against F. brachygibbosum. Full article

The red soil region in southern China is an ecologically fragile area. Although ecological engineering construction has achieved phased results, there are still obvious gaps in research on the mechanisms underlying vegetation dynamics in response to natural and anthropogenic variables. Changting County (CTC) serves as a typical case of vegetation degradation and restoration in the region. We examined the vegetation dynamics in CTC with the fraction vegetation cover (FVC) based on kernel normalized difference vegetation index-based dimidiate pixel model (kNDVI-DPM) and employed the optimal parameter-based geographical detector (OPGD), multiscale geographically weighted regression (MGWR), and partial least square structural equation modeling (PLS-SEM) to analyze interaction mechanisms between vegetation dynamics and underlying factors. The FVC showed a fluctuating upward trend at a rate of 0.0065 yr⁻¹ (p < 0.001) from 2000 to 2020. The spatial distribution pattern was high in the west and low in the east. Soil and terrain factors were the primary factors dominating the spatial heterogeneity of FVC, soil organic matter and elevation showing the most significant influence, with annual mean q-values of 0.4 and 0.3, respectively. Climate, terrain, and soil properties positively and anthropogenic activities negatively impacted vegetation. From 2000 to 2020, the path coefficient of anthropogenic activities to FVC decreases from −0.152 to −0.045, the adverse effects of human activities are diminishing with ongoing ecological construction efforts. Climate and anthropogenic activities act indirectly on vegetation through negative effects on soils and terrain. The impact of climate on soils and terrain is gradually lessening, whilst the influence of anthropogenic activities continues to grow. This study provides an analytical framework for understanding the complex interrelationships between vegetation changes and the underlying factors. Full article

Global climate change has intensified the frequency, intensity, and spatial heterogeneity of drought events, posing severe threats to the stability of terrestrial ecosystems. Plant drought resilience, which encompasses a plant’s capacity for drought resistance, post-stress recovery, and long-term adaptation and transformation to sustain ecosystem functionality, has emerged as a central focus in botanical and ecological research. This review synthesizes the conceptual evolution of plant drought resilience, from early emphasis on resistance and recovery to the current multi-dimensional framework integrating adaptation and transformation, and synthesizes advances in understanding multi-scale drought resilience in terrestrial plants—spanning molecular, physiological, individual, community, and ecosystem levels. Key mechanisms include molecular/physiological adaptations (osmotic adjustment, antioxidant defense, hydraulic regulation, carbon–water reallocation via gene networks and aquaporins), morpho-anatomical traits (root architectural plasticity, leaf structural modifications, and hydraulic vulnerability segmentation), community/ecosystem drivers (biodiversity effects, microbial symbioses, and soil–plant–feedback dynamics). We critically evaluate quantitative metrics and expose critical gaps, including neglect of stress legacy effects, oversimplified spatiotemporal heterogeneity, and limited integration of concurrent stressors. Future research should prioritize multi-scale and multi-dimensional integrated analysis, long-term multi-scenario simulations with field validation, and harnessing plant–microbe interactions to enhance drought resilience, providing a theoretical basis for ecosystem sustainability and agricultural production under climate change. Full article

Intercropping is an eco-friendly, sustainable agricultural model that significantly improves yield stability, nutrient use efficiency, and soil health through spatiotemporal niche complementarity, increases biodiversity, and improves soil health. Water and nitrogen play crucial roles in limiting and regulating efficient resource utilization and ecological sustainability in intercropping systems. Synchronizing water and nitrogen inputs to match crop demands optimizes the spatiotemporal distribution of these resources, alleviates interspecific competition, and promotes mutualistic interactions, which significantly impacts crop growth, yield, and soil environment. This paper reviews the mechanisms of intercropping and water–nitrogen coupling regulation, aligning water and nitrogen supply with crop growth patterns, spatial configuration parameters, irrigation management techniques, and environmental climate change, and explores the response mechanisms of water–nitrogen coupling on crop growth, yield, and soil environmental adaptation. It can provide some references for researchers, extension agents, and policymakers. Research indicates that water–nitrogen coupling can enhance photosynthetic efficiency, promote root development, optimize nutrient uptake, and improve soil water dynamics, nitrogen cycling, and microbial community structures. Intercropping enhances the climate resilience of agricultural systems by leveraging species complementarity for resource utilization, strengthening ecosystem stability, and improving buffering capacity against climate change impacts such as extreme precipitation and temperature fluctuations. Future studies should further elucidate the differential effect of water–nitrogen coupling across regions and climatic conditions, focusing on multidimensional integrated administration strategies. Combining precision agriculture technologies and climate change predictions facilitates the development of more adaptive water–nitrogen coupling models to provide theoretical support and technical guarantees for sustainable agriculture. Full article

This study presents an advanced simulation-based methodology for evaluating the dynamic vibrational behavior of the operator–vehicle assembly in autonomous electric agricultural tractors. Using the TE-0 electric tractor as the experimental platform, the research is structured into three integrated stages. In the first stage, a seated anthropometric virtual model of the human operator is developed based on experimental data and biomechanical validation. The second stage involves a detailed modal analysis of the TE-0 electric tractor using Altair Sim Solid, with the objective of determining the natural frequencies and vibration modes in the [0–80] Hz range, in compliance with ISO 2631-1. This analysis captures both the structural-induced frequencies—associated with the chassis, wheelbase, and metallic frame—and the operational-induced frequencies, influenced by the velocity and terrain profile. Subsequently, the modal analysis of the “Grammer Cabin Seat” is conducted to assess its dynamic response and identify critical vibration modes, highlighting how the seat behaves under vibrational stimuli from the tractor and terrain. The third stage extends the analysis to the virtual operator model seated on the tractor seat, investigating the biomechanical response of the human body and the operator–seat–vehicle interaction during simulated motion. Simulations were carried out using SolidWorks 2023 and Altair Sim Solid over a frequency range of [0–80] Hz, corresponding to operation on unprocessed soil covered with grass, at a constant forward speed of 7 km/h. The results reveal critical resonance modes and vibration transmission paths that may impact operator health, comfort, and system performance. The research contributes to the development of safer, more ergonomic, and sustainable autonomous agricultural transport systems. By simulating real-world operation scenarios and integrating a rigorously validated experimental protocol—including vibration data acquisition, biomechanical modeling, and multi-stage modal analysis—this study demonstrates the importance of advanced modeling in optimizing system-level performance, minimizing harmful vibrations, and supporting the transition toward resilient and eco-efficient electric tractor platforms in smart agricultural mobility. Full article

Soil organic matter (SOM) decomposition is a critical biogeochemical process that regulates the carbon cycle, nutrient availability, and agricultural sustainability of cropland systems. Recent progress in multi-omics and microbial network analyses has provided us with a better understanding of the decomposition process at different spatial and temporal scales. Climate factors, such as temperature and seasonal variations in moisture, play a critical role in microbial activity and enzyme kinetics, and their impacts are mediated by soil physical and chemical properties. Soil mineralogy, texture, and structure create different soil microenvironments, affecting the connectivity of microbial habitats, substrate availability, and protective mechanisms of organic matter. Moreover, different microbial groups (bacteria, fungi, and archaea) contribute differently to the decomposition of plant residues and SOM. Recent findings suggest the paramount importance of living microbial communities as well as necromass in forming soil organic carbon pools. Microbial functional traits such as carbon use efficiency, dormancy, and stress tolerance are essential drivers of decomposition in the soil. Furthermore, the role of microbial necromass, alongside live microbial communities, in the formation and stabilization of persistent SOM fractions is increasingly recognized. Based on this microbial perspective, feedback between local microbial processes and landscape-scale carbon dynamics illustrates the cross-scale interactions that drive agricultural productivity and regulate soil climate. Understanding these dynamics also highlights the potential for incorporating microbial functioning into sustainable agricultural management, which offers promising avenues for increasing carbon sequestration without jeopardizing soil nutrient cycling. This review explores current developments in intricate relationships between climate, soil characteristics, and microbial communities determining SOM decomposition, serving as a promising resource in organic fertilization and regenerative agriculture. Specifically, we examine how nutrient availability, pH, and oxygen levels critically influence these microbial contributions to SOM stability and turnover. Full article

The effects of Phellodendron chinense plantations on soil properties, microbial characteristics, and the plant diversity across forest age remain poorly understood. In this study, four forest ages (2-, 5-, 8-, and 12-year-old) were examined to compare soil nutrient status, rhizosphere microbial community composition, and plant diversity. Our results showed that understory vegetation comprised 56 plant species from 29 families, with species richness significantly increasing with forest age. Rhizosphere soils showed a marked decline in pH and a significant increase in organic carbon, while nutrient dynamics followed distinct trends: P and Mg exhibited continuous accumulation; N displayed unimodal patterns; and K and Ca initially decreased before rising. Microbial community structure shifted significantly with forest age—the dominant bacterial phylum transitioned from Proteobacteria in young stands to Acidobacteriota in mature forests, whereas fungal communities underwent a successional sequence from Basidiomycota (2a) to Ascomycota (5–8a) and finally to Rozellomycota (12a). Correlation analyses demonstrated that plant diversity (S index) was positively correlated with P, K, Ca, and Mg, whereas fungal Shannon diversity was primarily driven by soil N and pH. These findings indicate that forest age mediates plant–soil-microbe interactions through rhizosphere environmental changes. For sustainable plantation management, we recommend (1) dynamically optimizing understory vegetation composition, (2) regulating soil pH and moisture during key growth stages, and (3) selecting compatible companion plants to enhance rhizosphere conditions. Full article

Preparing red mud/phosphogypsum-based artificial soils for vegetation restoration is promising. However, how artificial soil develops during vegetation restoration is unclear, especially regarding the relationship between the bacterial community and the development of artificial soil. The bacterial community changes in the early-stage engineering simulation of red mud/phosphogypsum-based artificial soil vegetation restoration were analyzed for the first time in this paper. The results showed that the structure of the bacterial community was simple at the beginning, mainly consisting of Proteobacteria, Firmicutes, and Bacteroidota, with total abundances of 74.5% and 89.3% in the two plots, respectively. The richness, diversity, and evenness of the bacterial communities all significantly increased over time (p < 0.05), indicating that the compositions of the bacterial communities in artificial soils undergo constant development, adjustment, and optimization. There were good correlations between bacterial communities and environmental factors (e.g., pH, W_H2O, OM, TN, TK, AK, TP), which generally reflected the significant synergistic development and interaction between the quality of the soil environmental and bacterial communities. There were complex dynamic changes in the functions of the bacteria during the development of artificial soils, which were mainly reflected in the decline in the abundances of chemoheterotrophy, aerobic chemoheterotrophy, and animal parasites or symbionts, but there was an increase in the abundances of phototrophy, cyanobacteria, and dark sulfide oxidation. This reflects the highly active physiological and biochemical reaction functions of bacterial communities in the development of artificial soils, which is of great significance for continuously enhancing the fertility quality and ecological attributes of artificial soils. Full article

As agricultural land continues to expand, the conversion of forests to farmland has intensified, significantly altering the structure and function of agroecosystems. However, the dynamic ecological responses and their interactions with economic outcomes remain insufficiently modeled. This study proposes an integrated framework that combines a dynamic food web model with the Eco-Economic Benefit and Sustainability (EEBS) model, utilizing empirical data from Brazil and Ghana. A system of ordinary differential equations solved using the fourth-order Runge–Kutta method was employed to simulate species interactions and energy flows under various land management strategies. Reintroducing key species (e.g., the seven-spot ladybird and ragweed) improved ecosystem stability to over 90%, with soil fertility recovery reaching 95%. In herbicide-free scenarios, introducing natural predators such as bats and birds mitigated disturbances and promoted ecological balance. Using XGBoost (Extreme Gradient Boosting) to analyze 200-day community dynamics, pest control, resource allocation, and chemical disturbance were identified as dominant drivers. EEBS-based multi-scenario optimization revealed that organic farming achieves the highest alignment between ecological restoration and economic benefits. The model demonstrated strong predictive power ($R^2$ = 0.9619, RMSE = 0.0330), offering a quantitative basis for green agricultural transitions and sustainable agroecosystem management. Full article

This study focuses on optimizing track and grouser structural parameters to enhance UATV drawbar pull, particularly under soft soil conditions. A numerical soil thrust model for single-track shoes was developed based on track–soil interaction mechanics, revealing distinct mechanistic roles: track structural parameters (length/width) govern pressure–sinkage relationships at the track base, while grouser structural parameters (height, spacing, V-shaped angle) dominate shear stress–displacement dynamics on grouser shear planes. A novel DEM-MBD coupling simulation framework was established through soil parameter calibration and multi-body dynamics modeling, demonstrating that soil thrust increases with grouser height and V-shaped angle, but decreases with spacing, with grouser height exhibiting the highest sensitivity. A soil bin test validated the numerical model’s accuracy and the coupling method’s efficacy. Parametric optimization via the Whale Optimization Algorithm (WOA) achieved a 55.86% increase in drawbar pull, 40.38% reduction in ground contact pressure and 57.33% improvement in maximum gradability. These advancements substantially improve the tractive performance of UATVs in soft beach terrains. The proposed methodology provides a systematic framework for amphibious vehicle design, integrating numerical modeling, high-fidelity simulation, and experimental validation. Full article

This study aims to examine the seismic response of self-centering single-degree-of-freedom (SDOF) systems exhibiting flag-shaped hysteretic behavior, while considering soil–structure interaction, in contrast to prior research that predominantly addressed conventional hysteretic behavior and overlooked soil flexibility. The inelastic displacement ratio, residual displacement, and residual displacement ratio are used to analyze the seismic response of interacting structures. These structural response parameters are calculated based on the nonlinear dynamic analyses of SDOF systems subjected to 56 near-fault pulse-type ground motions. Analyses are conducted for varying values of ductility, energy dissipation coefficient, strain hardening ratio, aspect ratio, structural period, and normalized vibration period by pulse period of the record. New formulas to estimate the inelastic displacement ratio and residual displacement of self-centering SDOF systems with soil–structure interaction are developed based on a statistical analysis of the findings. Full article

Soil salinization in oasis areas of arid regions is recognized as a dynamic and multifaceted environmental threat influenced by both natural processes and human activities. In this study, 13 spatiotemporal predictors derived from field surveys and remote sensing are utilized to construct a spatial probabilistic model of salinization. A Bayesian Belief Network is integrated with spline interpolation in ArcGIS to map the likelihood of salinization, while Partial Least Squares Structural Equation Modeling (PLS-SEM) is applied to analyze the interactions among multiple drivers. The test results of this model indicate that its average sensitivity exceeds 80%, confirming its robustness. Salinization risk is categorized into degradation (35–79% probability), stability (0–58%), and improvement (0–48%) classes. Notably, 58.27% of the 1836.28 km² Keriya Oasis is found to have a 50–79% chance of degradation, whereas only 1.41% (25.91 km²) exceeds a 50% probability of remaining stable, and improvement probabilities are never observed to surpass 50%. Slope gradient and soil organic matter are identified by PLS-SEM as the strongest positive drivers of degradation, while higher population density and coarser soil textures are found to counteract this process. Spatially explicit probability maps are generated to provide critical spatiotemporal insights for sustainable oasis management, revealing the complex controls and limited recovery potential of soil salinization. Full article