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.

Seismic risk assessment of code-noncompliant reinforced concrete (RC) frames faces significant challenges due to structural heterogeneity and the complex interplay of site-specific hazard conditions. This study aims to introduce a novel framework that integrates three key concepts specifically targeting these challenges. Central to the methodology are fragility fuses, which employ a triplet of curves-lower bound, median, and upper bound-to rigorously quantify within-class variability in seismic performance, offering a more nuanced representation of code-noncompliant building behavior compared to conventional single-curve approaches. Complementing this, spectrum-consistent transformations dynamically adjust fragility curves to account for regional spectral shapes and soil categories, ensuring site-specific accuracy by reconciling hazard intensity with local geotechnical conditions. Further enhancing precision, the framework adopts a nonlinear hazard model that captures the curvature of hazard curves in log-log space, overcoming the oversimplifications of linear approximations and significantly improving risk estimates for rare, high-intensity events. Applied to four RC frame typologies (2-5 stories) with diverse geometries and material properties, the framework demonstrates a 15-40 % reduction in risk estimation errors through nonlinear hazard modeling, while spectrum-consistent adjustments show up to 30 % variability in exceedance probabilities across soil classes. Fragility fuses further highlight the impact of structural heterogeneity, with older, non-ductile frames exhibiting 25 % wider confidence intervals in performance. Finally, risk maps are presented for the four frame typologies, making use of non-linear hazard curves and spectrumconsistent fragility fuses accounting for both local effects and within-typology variability.

Granular materials usually copossess inherent and stress-induced anisotropy that significantly influences their mechanical behaviors. This paper presents a series of true-triaxial tests on aeolian sands to consider the inherent and stress-induced anisotropy in terms of soil deposition angles and intermediate principal stress coefficients, respectively. These results show that the deposition angle primarily affected the elastic-plastic stage under axisymmetric conditions. Otherwise, the deposition angle affects all deformation processes after the elastic stage when the intermediate principal stress coefficient changes. Moreover, the critical state is not unique but depends on the combined effect of the deposition angle and the intermediate principal stress coefficient, which indicates that the strength, stress-strain response, and dilatancy behavior of sands are affected by both inherent and stress-induced anisotropy.

The horizontal displacement of monopile under cyclic loading is subject to uncertainty due to variations in metocean conditions and soil parameters at offshore wind farms. However, the current design for cyclically loaded monopiles relies on the p-y method recommended by API and DNV, which does not accurately capture the horizontal displacement of the monopiles. In this study, finite element simulations are performed using ABAQUS, where the soil is modeled with the Einav-Randolph model to account for soil softening effects. The impact of parameter uncertainties, such as soil stiffness, undrained shear strength, and the pile-soil friction coefficient, on the reliability index of the monopile's horizontal displacement for different length diameter (L/D) ratios is investigated. A case study is provided to assess the horizontal displacement reliability of a monopile under cyclic loading. The results show that the horizontal displacement reliability index decreases as the coefficient of variation (COV) of the random variables, the correlation coefficient, and the monopile's L/D ratio increase. Conversely, the reliability index increases with an increase in the allowable horizontal displacement. The horizontal displacement reliability index is most sensitive to soil stiffness, followed by undrained shear strength and pile-soil friction coefficient. The findings of this study offer valuable insights into how parameter uncertainties influence the horizontal displacement of monopiles under cyclic loading.

Aeolian sand along the Hojiakueri Railway in the Taklimakan Desert exhibits poor mechanical properties for direct use as a filler for railway subgrades. Although cemented soil reinforced with single fibers can improve mechanical properties, its limited effectiveness and high cement usage pose significant economic and environmental concerns. This study investigated the improvement of splitting tensile strength (STS) in cemented aeolian sand through hybrid fiber reinforcement. An orthogonal test was designed to evaluate four factors-fiber types (pairwise combinations of basalt, polypropylene, and glass fibers), fiber lengths (3, 6, and 9 mm), hybridization ratios (1:1, 1:3, and 3:1), and fiber contents (4 %o, 8 %o, and 12 %o) - along with their interactions. The performance of cemented aeolian sand reinforced with hybrid fiber (CASRHF) was evaluated through STS tests and scanning electron microscopy (SEM). The results identified the optimal combination as a 1:1 mix of 6 mm basalt and polypropylene fibers with a fiber content of 12 %o. The interaction between hybrid fiber type and fiber length was the most critical factor influencing STS, followed by hybrid fiber type, fiber length, and fiber content. SEM analysis further revealed a linear negative correlation between STS and porosity, providing new insights into the microscopic mechanisms. The findings underscore the importance of optimizing hybrid fiber combinations to meet the performance requirements of railway subgrade beds in aeolian sand regions.

Strongyloides stercoralis (S. stercoralis) is a soil-transmitted nematode that is endemic to tropical and subtropical regions. S. stercoralis has the ability to cause autoinfection, potentially leading to a chronic disease that can last for decades or result in severe hyperinfection especially in individuals who are taking corticosteroids or other immunosuppressive medications. Here, we report the case of a patient presenting a two-week history of symptoms including cough, fatigue, weight loss, pruritus, and rash. Due to a significant increase in the percentage of eosinophils, the patient was referred to the hematology clinic. The patient underwent a comprehensive evaluation that included an autoimmune panel, genetic testing, and imaging methods. The results of these investigations were found to be normal. The upper gastrointestinal system endoscopy revealed eosinophilic duodenitis and corticosteroid treatment was initiated. The commencement of corticosteroid therapy resulted in a worsening of the patient's symptoms. In the repeated endoscopy of the upper gastrointestinal tract, the presence of S. stercoralis larvae was observed between the crypts. Subsequently, stool tests for S. stercoralis diagnosis were also found to be positive. The patient was at risk of developing a hyperinfection syndrome. Corticosteroids are commonly used to reduce inflammation and manage symptoms associated with eosinophilic disorders. The immunosuppressive effects of corticosteroids are known to precipitate S. stercoralis hyperinfection syndrome, which can result in significant morbidity and mortality. This case highlights the importance of maintaining a high index of suspicion for S. stercoralis in patients undergoing immunosuppressive therapy, particularly when presenting with unexplained eosinophilia.

Understanding the mechanical properties of continental submarine slopes is critical for the assessment of geo-marine slope stability hazards. This paper presents the first detailed geomechanical study on sediment profiles associated with a geologically recent sliding event at the Goliath submarine complex offshore southern Israel. Sediment samples were extracted from similar to 5-m-long piston cores collected from three representative sites: on the recent slide headscar (PHS3), the adjacent undisturbed slope seafloor (PSL4), and at the dextral tail-depositional lobe (PTL3). The investigation included Gamma-ray and CT scanning, sediment phase measurement, laboratory T-bar penetration, and vane shear testing. The evaluated properties for the three sites are the undrained shear strength, over-consolidation ratio, soil sensitivity, water content, and density. The experimental results show a strong correlation between the findings of the various investigation tools regarding the original soil condition before sliding, the slide scar location, the degradation in properties of the disturbed soil, and the post-slide deposited soil properties. Despite the variation in properties among the different sites, the paper presents a prediction model for the soil strength in the Goliath slide area. Beyond the geomechanical characterization, the analysis of the test results highlights two unique findings: (1) evidence of a long-term strength softening phenomenon in the post-slide period, and (2) insights into the transition of geomechanical properties with depth within the slide scar.

Mining leads to soil degradation and land subsidence, resulting in decreased soil quality. However, there are limited studies on the detailed effects of mining activities on soil properties, particularly in western aeolian sand. This study, therefore, quantitatively assessed the aeolian sandy soil disturbance induced by mining activities in the contiguous regions of Shanxi, Shaanxi, and Inner Mongolia. The following soil physical quality indices were measured in the pre (May 2015), mid (October 2015), and postmining period (April 2016), such as the soil water content (SWC), particle size (PS), soil penetration (SP), and soil saturated hydraulic conductivity (SSHC). The results showed that mining activities brought irreversible effects on soil structures. In the pre-mining period, land subsidence broke up large soil particles, destroying soil structure, leading to decreased PS (218.33 vs. 194.36 mu m), SP (4615.56 vs. 2631.95 kPa), and subsequently decreased SSHC (1.12 vs. 0.99 cm/min). Rainfall during the midmining period exacerbated this fragmentation. Thereafter, low temperatures and humidity caused the soil to freeze, allowing the small soil particles to merge into larger ones. Meanwhile, the natural re-sedimentation, subsidence, and heavy mechanical crushing in the post-mining period increased PS and SP. The SSHC hence increased to 1.21 cm/min. Furthermore, the evaluation of soil indices from different stress zones showed that the external pulling stress zone always had a higher SSHC than the neutral zone in any mining period, possibly due to the presence of large cracks and high SWC. This study contributes to the understanding of the impact of mining activities on soil physical qualities, providing a theoretical basis and quantitative guidance for the surface damage caused by coal mining in the aeolian sandy area in Western China.

Cadmium (Cd) contamination in agricultural soils poses a serious threat to crop productivity and food security, necessitating effective mitigation strategies. This study investigates the role of silicon nanoparticles (SiNPs) in alleviating Cd-induced stress in maize (Zea mays L.) under controlled greenhouse conditions. Sterilized maize seeds were sown in sand-filled pots and treated with varying SiNP concentrations (0%, 0.75%, 1.5%, 3%, and 6%) with or without Cd (30 ppm). Physiological, biochemical, and antioxidant parameters were analyzed to assess plant responses. Results demonstrated that SiNPs significantly enhanced photosynthetic pigment concentrations, with chlorophyll-a, chlorophyll-b, and carotenoids increasing by 45%, 35%, and 50%, respectively, in the 6% SiNP + 30 ppm Cd treatment. Biochemical analyses revealed improved osmotic adjustment, as indicated by higher soluble protein (6.52 mg/g FW) and proline (314.43 mu mol/g FW) levels. Antioxidant enzyme activities, including superoxide dismutase, catalase, and ascorbate peroxidase, were markedly higher in SiNP-treated plants, mitigating oxidative damage. Additionally, SiNPs reduced Cd accumulation in plant tissues, suggesting a protective role in limiting metal toxicity. These findings highlight SiNPs as a promising approach for enhancing maize resilience against Cd stress, with potential applications in sustainable agriculture for improving crop health in contaminated soils.

Introduction Verticillium wilt is a severe soil-borne disease that affects cotton growth and yield. Traditional monitoring methods, which rely on manual investigation, are inefficient and impractical for large-scale applications. This study introduces a novel approach combining machine learning with feature selection to identify sensitive spectral features for accurate and efficient detection of cotton Verticillium wilt.Methods We conducted comprehensive hyperspectral measurements using handheld devices (350-2500 nm) to analyze cotton leaves in a controlled greenhouse environment and employed Unmanned Aerial Vehicle (UAV) hyperspectral imaging (400-995 nm) to capture canopy-level data in field conditions. The hyperspectral data were pre-processed to extract wavelet coefficients and spectral indices (SIs), enabling the derivation of disease-specific spectral features (DSSFs) through advanced feature selection techniques. Using these DSSFs, we developed detection models to assess both the incidence and severity of leaf damage by Verticillium wilt at the leaf scale and the incidence at the canopy scale. Initial analysis identified critical spectral reflectance bands, wavelet coefficients, and SIs that exhibited dynamic responses as the disease progressed.Results Model validation demonstrated that the incidence detection models at the leaf scale achieved a peak classification accuracy of 85.83%, which is about 10% higher than traditional methods without feature selection. The severity detection models showed improved precision as disease severity of damage increased, with accuracy ranging from 46.82% to 93.10%. At the canopy scale, UAV-based hyperspectral data achieved a remarkable classification accuracy of 93.0% for disease incidence detection.Discussion This study highlights the significant impact of feature selection on enhancing the performance of hyperspectral-based remote sensing models for cotton wilt monitoring. It also explores the transferability of sensitive spectral features across different scales, laying the groundwork for future large-scale early warning systems and monitoring cotton Verticillium wilt.