Bedrock-soil layer slopes (BSLSs) are widely distributed in nature. The existence of the interface between bedrock and soil layer (IBSL) affects the failure modes of the BSLSs, and the seismic action makes the failure modes more complex. In order to accurately evaluate the safety and its corresponding main failure modes of BSLSs under seismic action, a system reliability method combined with the upper bound limit analysis method and Monte Carlo simulation (MCS) is proposed. Four types of failure modes and their corresponding factors of safety (Fs) were calculated by MATLAB program coding and validated with case in existing literature. The results show that overburden layer soil's strength, the IBSL's strength and geometric characteristic, and seismic action have significant effects on BSLSs' system reliability, failure modes and failure ranges. In addition, as the cohesion of the inclination angle of the IBSL and the horizontal seismic action increase, the failure range of the BSLS gradually approaches the IBSL, which means that the damage range becomes larger. However, with the increase of overburden layer soil's friction angle, IBSL's depth and strength, and vertical seismic actions, the failure range gradually approaches the surface of the BSLS, which means that the failure range becomes smaller.

Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

To investigate the effect of interface temperature on the soil-reinforcement interaction mechanism, a series of pullout tests were conducted considering different types of reinforcement (geogrid and non-woven geotextile), backfill (dry sand, wet sand, and clay), and six interface temperatures. The test results indicate that at interface temperatures of 0 degrees C and above, reinforcement failure didn't occur during the pullout tests, whereas it predominantly occurred at subzero temperatures. Besides, the pullout resistance for the same soil-reinforcement interface gradually decreased as the interface temperature rose. At a given positive interface temperature, the pullout resistance between wet sand and reinforcement was significantly higher than that of the clayreinforcement interface but lower than that of the dry sand-reinforcement interface. Compared with geotextile reinforcements, geogrids were more difficult to pull out under the same interface temperature and backfill conditions. In addition, the lag effect in the transfer of tensile forces within the reinforcements was significantly influenced by the type of soil-reinforcement interface and the interface temperature. Finally, the progressive deformation mechanism along the reinforcement length at different interface temperatures was analyzed based on the strain distribution in the reinforcement.

To investigate the coupled time effects of root reinforcement and wet-dry deterioration in herbaceous plant-loess composites, as well as their microscopic mechanisms, this study focused on alfalfa root-loess composites at different growth stages cultivated under controlled conditions. The research included measuring root morphological parameters, conducting wet-dry cycling tests, and performing triaxial compression tests and microscopic analyses (CT scanning and nuclear magnetic resonance) on both bare loess and root-loess composites under various wet-dry cycling conditions. By obtaining shear strength parameters and microstructural indices, the study analyzed the temporal evolution of the shear strength and microstructural characteristics of root-loess composites under wet-dry cycling. The findings indicated that the alfalfa root-loess composite effective cohesion was significantly higher than that of the plain soil in the same growth stage. The alfalfa root-loess composite effective cohesion increased during the growth stage in the same dry-wet cycles. The alfalfa root-loess composite effective cohesion in the same growth stage was negatively correlated with the number of dry-wet cycles. The fatigue damage of the soil's microstructure (pore coarsening, cement hydrolysis, and crack development) increased continuously with the number of dry-wet cycles. However, due to the difference in mechanical properties between roots and the soil, the root-soil composite prevented the deterioration of the soil matrix strength by the dry-wet cycles. As the herbaceous plants grow, the time effect observed in the shear strength of the root-soil composite under the action of dry-wet cycles is the result of the interaction and dynamic coordination between the soil-stabilizing function of the herbaceous plant roots and the deterioration caused by drywet cycles.

Ensuring the accuracy of free-field inversion is crucial in determining seismic excitation for soil-structure interaction (SSI) systems. Due to the spherical and cylindrical diffusion properties of body waves and surface waves, the near-fault zone presents distinct free-field responses compared to the far-fault zone. Consequently, existing far-fault free-field inversion techniques are insufficient for providing accurate seismic excitation for SSI systems within the near-fault zone. To address this limitation, a tailored near-fault free-field inversion method based on a multi-objective optimization algorithm is proposed in this study. The proposed method establishes an inversion framework for both spherical body waves and cylindrical surface waves and then transforms the overdetermined problem in inversion process into an optimization problem. Within the multi-objective optimization model, objective functions are formulated by minimizing the three-component waveform differences between the observation point and the delayed reference point. Additionally, constraint conditions are determined based on the attenuation property of propagating seismic waves. The accuracy of the proposed method is then verified through near-fault wave motion characteristics and validated against real downhole recordings. Finally, the application of the proposed method is investigated, with emphasis on examining the impulsive property of underground motions and analyzing the seismic responses of SSI systems. The results show that the proposed method refines the theoretical framework of near-fault inversion and accurately restores the free-field characteristics, particularly the impulsive features of near-fault motions, thereby providing reliable excitation for seismic response assessments of SSI systems.

Researchers have tried hard to study the toxic effects of single pollutants like certain antibiotics and nanoplastic particles on plants. But we still know little about how these pollutants interact when they're together in the environment, and what combined toxic effects they have on plants. This study assessed the toxic effects of polystyrene nanoplastics (PS-NPs) and ciprofloxacin (CIP), both individually and in combination, on soybean (Glycine max L.) seedlings by various concentration gradients treatments of PS-NPs (0, 10, 100 mg/L) and CIP (0, 10 mg/L). The results indicated that high concentrations of PS-NPs significantly impeded soybean seedling growth, as evidenced by reductions in root length, plant height, and leaf area. CIP predominantly affected the physiological functions of leaves, resulting in a decrease in chlorophyll content. The combined exposure demonstrated synergistic effects, further intensifying the adverse impacts on the growth and physiological functions of soybean seedlings. Metabolomic analyses indicated that single and combined exposures markedly altered the metabolite expression profiles in soybean leaves, particularly related to amino acid and antioxidant defense metabolic pathways. These results indicate the comprehensive effects of NPs with antibiotics on plants and provide novel insights into toxic mechanisms.

Biological soil crusts (BSCs; biocrusts) are well developed in drylands, which are crucial to the stability and resilience of dryland ecosystems. In the southeastern Gurbantunggut Desert, a typical sandy desert in the middle part of central Asia, engineering development has an increasing negative impact on ecosystems. Fortunately, ecological restoration measures are being implemented, but the exact effect on soil quality is still unclear. In artificial sand-fixing sites on reshaped dunes along the west-east desert road, a total of 80 quadrats (1 m x 1 m) of reed checkerboards after the implementation of sand-fixing measures for 10 years were investigated to determine the BSC development status and soil properties. The algal and lichen crusts accounted for 48.75 % and 26.25 % of the total quadrat number, respectively, indicating an obvious recovery effect of BSC (only 25 % for bare sand). The developmental level of BSC gradually increased from the top to the bottom of the dunes (Li 0 -> Li 6),which was consistent with the distribution pattern of BSCs on natural dunes. Compared with bare sand, the soil organic carbon (13.85 % and 23.07 % increases), total nitrogen (12.55 % and 23.95 % increases), total potassium (9.30 % and 8.24 % increases), and available nitrogen (23.97 % and 61.41 % increases) contents of algal and lichen crusts were significantly increased, and lichen crusts had markedly higher increase effect than algal crusts. The BSC development markedly reduced soil pH (0.49 % and 0.50 % decreased) and increased electrical conductivity(11.99 % and 10.68 % increases), resulting in improved soil microenvironment. Soil properties showed significant linear relationships with BSC development level, and an optimal fitting (R2 = 0.770 or 0.780) was detected for the soil fertility index. Based on the soil property matrix, the bare sands, algal, and lichen crusts were markedly separated along the first axis in the PCA biplot, which once again confirmed the significant positive effect of BSC recovery on soil fertility improvement. Consequently, in the early stage of sand-fixation (e.g., < = 10 years) by reed checkerboards on the damaged desert surface, BSC recovery can well promote and predict soil fertility in this area. The results provide a reliable theoretical basis for the restoration technology and scientific management of degraded sandy desert ecosystems.

Hurricane Otto caused sequential changes in tropical soil microbiota over 5 years.Acidobacteria were critical early decomposers of deposited canopy debris for 3 years.Complex C degrading fungi were critical later decomposers of debris starting at 4 years.A suite of C, N and microbial indicators should prove valuable for forest managers.Hurricanes cause significant damage to tropical forests; however, little is known of their effects on decomposition and decomposer communities. This study demonstrated that canopy debris deposited during Hurricane Otto stimulated sequential changes in soil carbon (C) and nitrogen (N) components, and decomposer microbial communities over 5 years. The initial response phase occurred within 2 years post-hurricane and appeared associated with decomposition of the labile canopy debris, suggested by: increased DNA sequences (MPS) of the Acidobacterial community (as common decomposers of labile plant material), decreases in total organic C (TOC), increased biomass C, respiration, and NH4+, conversion of organic C in biomass, and decreased MPS of complex organic C decomposing (CCDec) Fungal community. After 3 years post-hurricane, the later response phase appeared associated with decomposition of the more stable components of the canopy debris, suggested by: increased MPS of the Fungal CCDec community, TOC, stabilized Respiration, decreased Biomass C, the return to pre-hurricane levels of the conversion of organic C to biomass, and decreased MPS of Acidobacterial community. These changes in the microbial community compositions resulted in progressive decomposition of the hurricane-deposited canopy material within 5 years, resulting several potential indicators of different stages of decomposition and soil recovery post-disturbance.

Hypochlorite (ClO-) is a highly reactive chemical extensively used in households, public areas, and various industries due to its multiple functions of disinfection, bleaching, and sterilization. However, overuse of ClO- may contaminate the water, soil, air and food, leading to negative impacts on the environments, ecosystems and food safety. Meanwhile, excessive ClO- in human body can also cause severe damage to the immune system. Thus, the development of effective and precise detection tools for ClO- is of great significance to better understand its complicated roles in environments and biosystems. Herein, a new high-performance ratiometric fluorescent probe 2-amino-3-((10-propyl-10H-phenothiazin-3-yl)methylene)-amino)maleonitrile (PD) was developed for effective detection of ClO- in various bio/environmental and food samples. Probe PD exhibits highly-specific ratiometric fluorescent response to ClO- with rapid response (< 1 min), excellent sensitivity (detection limit, 47.4 nM), wide applicable pH range (4 -12), and excellent versatility in practical applications. In practical applications, PD enables the sensitive and quantitative detection of ClO- levels in various water samples, bio-fluids, dairy products, fruits and vegetables with high-precision (recoveries, 97.00 -104.40 %), as well as the successful application for visual tracking ClO- in fresh fruits and vegetables. Furthermore, test strips containing PD offer a visual and convenient tool for quick identification of ClO- in aqueous media by the naked eye. Importantly, the good biocompatibility of PD enables its practical applications in real-time bioimaging of endogenous/exogenous ClO- levels in living cells, bacteria, onion cells, Arabidopsis, as well as zebrafish. This study provided an effective method for visual monitoring and bioimaging of ClO- levels in various environments, foods and living biosystems.

Land surface temperature (LST) plays an important role in Earth energy balance and water/carbon cycle processes and is recognized as an Essential Climate Variable (ECV) and an Essential Agricultural Variable (EAV). LST products that are issued from satellite observations mostly depict landscape-scale temperature due to their generally large footprint. This means that a pixel-based temperature integrates over various components, whereas temperature individual components are better suited for the purpose of evapotranspiration estimation, crop growth assessment, drought monitoring, etc. Thus, disentangling soil and vegetation temperatures is a real matter of concern. Moreover, most satellite-based LSTs are contaminated by directional effects due to the inherent anisotropy properties of most terrestrial targets. The characteristics of directional effects are closely linked to the properties of the target and controlled by the view and solar geometry. A singular angular signature is obtained in the hotspot geometry, i.e., when the sun, the satellite and the target are aligned. The hotspot phenomenon highlights the temperature differences between sunlit and shaded areas. However, due to the lack of adequate multi-angle observations and inaccurate portrayal or neglect of solar influence, the hotspot effect is often overlooked and has become a barrier for better inversion results at satellite scale. Therefore, hotspot effect needs to be better characterized, which here is achieved with a three-component model that distinguishes vegetation, sunlit and shaded soil temperature components and accounts for vegetation structure. Our work combines thermal infrared (TIR) observations from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the LEO (Low Earth Orbit) Sentinel-3, and two sensors onboard GEO (geostationary) satellites, i.e. the Advanced Himawari Imager (AHI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI). Based on inversion with a Bayesian method and prior information associated with component temperature differences as constrained, the findings include: 1) Satellite observations throughout East Asia around noon indicate that for every 10 degrees change in angular distance from the sun, LST will on average vary by 0.6 K; 2) As a better constraint, the hotspot effect can benefit from multi-angle TIR observations to improve the retrieval of LST components, thereby reducing the root mean squared error (RMSE) from approximately 3.5 K, 5.8 K, and 4.1 K to 2.8 K, 3.5 K, and 3.1 K, at DM, EVO and KAL sites, respectively; 3) Based on a dataset simulated with a threedimensional radiative transfer model, a significant inversion error may result if the hotspot is ignored for an angular distance between the viewing and solar directions that is smaller than 30 degrees. Overall, considering the hotspot effect has the potential to reduce inversion noise and to separate the temperature difference between sunlit and shaded areas in a pixel, paving the way for producing stable temperature component products.