Intervertebral disc degeneration (IVDD) is a globally prevalent disease, yet achieving dual repair of tissue and function presents significant challenges. Considering reactive oxygen species (ROS) is a primary cause of IVDD, and given the decrease of nucleus pulposus cells (NPCs) and extensive degradation of extracellular matrix (ECM) during IVDD development, the present study, inspired by the seeds-and-soil strategy, has developed NPCsloaded TBA@Gel&Chs hydrogel microspheres. These microspheres serve as exogenous supplements of NPCs and ECM analogs, replenishing seeds and soil for nucleus pulposus repair, and incorporating polyphenol antioxidant components to interrupt the oxidative stress-IVDD cycle, thereby constructing a microsphere system where NPCs and ECM support each other. Experiments proved that TBA@Gel&Chs exhibited significant extra-cellular ROS-scavenging antioxidant capabilities while effectively upregulating intracellular antioxidant proteins expression (Sirt3 and Sod2). This dual-action antioxidant capability effectively protects the vitality and physiological functions of NPCs. The therapeutic effects of microspheres on IVDD were also confirmed in rat models, which was found significantly restore histological structure and mechanical properties of degenerated discs. Additionally, RNA-seq results have provided evidences of antioxidant mechanism by which TBA@Gel&Chs protected NPCs from oxidative stress. Therefore, the NPCs-loaded TBA@Gel&Chs microspheres developed in this study have achieved excellent therapeutic effects, offering a paradigm using antioxidant biomaterials combined with cellular therapy for IVDD treatment.

Destructive earthquakes result in significant damage to a wide variety of buildings. The resulting damage data is crucial for evaluating the seismic resilience of buildings in the region and investigating urban resilience. Field damage data from 38 destructive earthquakes in Sichuan Province were collected, classified, and statistically analysed according to the criteria of the latest Chinese seismic intensity scale for evaluating building damage levels. Meanwhile, the construction features and seismic damage characteristics of these buildings were also examined. These results facilitated the development of a damage probability matrix (DPM) for various building typologies, such as raw-soil structures (RSSs), stone-wood structures (SWSs), brick-wood structures (BWSs), masonry structures (MSs), and reinforced concrete frame structures (RCFSs). The damage ratio was employed as the parameter for vulnerability assessment, and a comprehensive analysis was performed on the differences in damage levels among all buildings in various intensity zones and time frames. Furthermore, the DPMs were further refined by simulating additional data from high-intensity zones to more accurately represent the seismic resistance of existing buildings in multiple-intensity zones. Vulnerability prediction models were developed using the biphasic Hill model, which elucidates varying damage trends across different construction typologies. Finally, empirical fragility curves were established based on horizontal peak ground acceleration (PGA) as the damage indicator. This study is based on multiple seismic damage samples from various regions, accounting for the influence of earthquake age. The DPMs, representative of the regional characteristics of Sichuan Province, were developed for different building types. Furthermore, multidimensional vulnerability regression models and empirical fragility curves are established based on these DPMs. These models and curves provide a theoretical foundation for seismic disaster scenario simulations and the seismic capacity analysis of buildings within Sichuan Province.

Soil-rock mixtures (SRMs) are characterized by heterogeneous structural features that lead to multiscale mechanical evolution under varying cementation conditions. However, the shear failure mechanisms of cemented SRMs (CSRMs) remain insufficiently explored in existing studies. In this work, a heterogeneous threedimensional (3D) discrete element model (DEM) was developed for CSRMs, with parameters meticulously calibrated to examine the role of matrix-block interfaces under different volumetric block proportions (VBPs). At the macroscopic scale, significant influences of the interface state on the peak strength of CSRMs were observed, whereas the residual strength was found to be largely insensitive to the interface cementation properties. Pronounced dilatancy behaviour was identified in the postpeak and residual phases, with a positive correlation with both interface cementation and VBP. Quantitative particle-scale analyses revealed substantial heterogeneity and anisotropy in the contact force network of CSRMs across different components. A highly welded interface was shown to reduce the number of interface cracks at the peak strength state while increasing the proportion of tensile cracks within the interface zone. Furthermore, the welding degree of the interface was found to govern the formation and morphology of shear cracking surfaces at the peak strength state. Nevertheless, a reconstruction method for the shear slip surface was proposed to demonstrate that, at the same VBP, the primary roughness of the slip surfaces remained consistent and was independent of the interface properties. Based on the extended simulations, the peak strength of the weakly welded CSRMs progressively decreased with increasing VBP, whereas further exploration of the enhanced residual strength is needed.

Currently, the application of enhancement techniques with natural additives for soil stabilization is crucial due to growing urbanization and environmental concerns. Contemporary construction methods increasingly need eco-friendly and cost-effective materials, such as natural fibers. Reinforcing the soil sublayers with fibers improves layer quality and increases its load transfer capacity over a larger surface, thereby reducing the required thickness of upper layers. This study utilized raspberry stalks and xanthan biopolymer as natural additives for the first time to improve the mechanical qualities of bentonite expansive soil. Different tests, including compression and indirect tensile strengths, swelling potential, freeze-thaw (F-T) cycles, California bearing ratio (CBR), and scanning electron microscopy (SEM), were performed on samples comprising 0.2, 0.4, and 0.6 % of raspberry fibers and 0.5, 1, and 2 % of xanthan gum, with curing durations of 1, 7, 14, and 28 days. The test results revealed that the combination of 1 % xanthan and 0.4 % fibers, subjected to 28 days of curing, showed the best performance in increasing the mechanical properties of bentonite. The hydrogel structure and the locks and links formed in the soil by the additives led to increases of 353 % and 103 % in compressive and tensile strengths, respectively. The results also indicated that the free-swelling potential of the unstabilized bentonite soil diminished from 280 % to 74 % when stabilized with optimum percentages of xanthan and fiber. Furthermore, the investigation showed that even after exposure to 10 F-T cycles, the durability of xanthan-fiber-stabilized bentonite soil was significantly higher compared to the unstabilized soil. Moreover, the CBR value of the stabilized soil improved by 143 % compared to the unstabilized soil, indicating a significant increase in soil layer quality. The SEM results verified that the additive combination significantly impacted the strength of the samples. The data indicate that the incorporation of xanthan gum as a bio cohesive agent and raspberry fiber as tensile strands enhances soil strength, hence augmenting the viability of these additives in practical applications, including shallow foundations, adobe brick, and subgrade.

The safe application of farm dairy effluent (FDE) to land has proven to be a challenge for dairy farmers and regulatory authorities throughout New Zealand. Poorly performing FDE systems can have deleterious effects on water quality because contaminants such as phosphorus, nitrogen and faecal microbes enter receiving waters with minimal attenuation by soil. We present a decision framework that supports good management of effluent, particularly during its application to land. The framework considers how FDE management can be tailored to account for soil and landscape features of a location that pose varying levels of contaminant transport risk. High risk soils and landscapes are vulnerable to direct losses via preferential and/or overland flow pathways and include sloping land (e.g. slopes greater than 7 degrees) and soils with mole drainage, coarse structure, poor natural drainage or low surface infiltration rates. Soil types that are well-drained with fine structure typically exhibit matrix flow characteristics and represent a relatively low risk of direct contaminant loss following FDE application. Our framework provides guidance on FDE application timings, rates and depths to different landform and soil types so that direct losses of contaminants to water are minimal and the opportunity for plant uptake of nutrients is enabled. Some potential limitations for using the framework include the potentially severe effects of animal treading damage during wet conditions that can reduce soil hydrological function and consequently increase the risk of overland flow of applied FDE. The spatial distribution of such treading damage should be considered in the framework's application. Another limitation is our limited understanding of the effects of soil hydrophobicity on FDE infiltration and application of the framework.

The unified hardening model for clays and sands (CSUH) can adequately represent the stress-strain characteristics of various soil types. However, being an incremental elastoplastic constitutive model, the CSUH model requires extensive iterative computations during parameter identification, resulting in significant computational time. To improve computational efficiency, this study derives the elastoplastic compliance matrix and stress-strain incremental relationships under different stress paths, eliminating the repeated solving of equations typically required during iterative processes. Furthermore, a dynamic step size iterative method is proposed based on the changing slope characteristics of the stress-strain curves. This method divides the total axial strain into two segments: in the initial segment (approximately the first 30% of total strain), where the curve slope is steep, smaller step sizes with arithmetic progression distribution are employed, while in the latter segment (approximately the remaining 70%), characterized by a gentle curve slope, larger and uniformly distributed step sizes are adopted. Comparative analyses between the proposed dynamic step size method and the traditional constant-step iterative method demonstrate that, under the premise of ensuring calculation accuracy, the dynamic step size method significantly reduces the iteration steps from 3000 to 50, thus decreasing the computational time by approximately 47 times. Finally, the proposed method is applied to parameter identification of Fujinomori clay, calcareous sand, and Changhe dam rockfill materials using the CSUH model. The predictions closely match experimental results, confirming the CSUH model's capability in accurately describing the mechanical behaviors of different soils under various stress paths. The dynamic step size iterative approach developed in this study also provides valuable insights for enhancing computational efficiency and parameter identification of other elastoplastic constitutive models.

The water-holding and strength characteristics of unsaturated expansive soil and modified soil in a high-fill canal embankment along the central line of the South-to-North Water Diversion Project were investigated using a pressure plate apparatus and a GDS unsaturated triaxial test system. The soil-water characteristic curves (SWCCs) of expansive soil and modified soil were obtained by curve-fitting the results of water-holding characteristic tests, thereby revealing the distinctions in water-holding characteristics of the two soil types. The laws governing the effects of matrix suction on the stress-strain relationships and shear strength of the two soil types were explored through unsaturated triaxial drainage shear tests. According to the test results: (1) The moisture content and void ratio of each soil type decreased gradually with the increase in matrix suction, although the void ratio of modified soil decreased at a slower rate than that of expansive soil. (2) Matrix suction induced a transition from strain hardening to strain softening; (3) The shear strength of both soils increases with the matrix suction and confining pressure, with the increment of expansive soil greater than that of modified soil. Notably, the influence of confining pressure became progressively more significant with increasing matrix suction for both soils; (4) The cohesion and internal friction angle of expansive soil and modified soil increases with the matrix suction, with 200 kPa as the critical point of increasing rate; (5) The expansive soil differs from modified soil in cohesion and internal friction angle under different matrix suctions, with matrix suction of 400 kPa as the critical point. (6) The matrix suction thresholds of 200 kPa and 400 kPa can serve as references for engineering design and construction, as well as seepage prevention and slope reinforcement. This study provides technical parameters and theoretical support for the design, construction, and long-term stability of embankments on the expansive soil in the South-to-North Water Transfer Project site.

Surface soil cracking in alpine meadows signifies the transition of degradation from quantitative accumulation to qualitative deterioration. Quantitative research remains insufficient regarding changes in the mechanical properties of degraded meadow soils and the mechanical thresholds for cracking initiation. This study explored the relationships between surface cracking and the physical properties, tensile strength, and matrix suction of root-soil composites in alpine meadow sites with different stages of degradation (undegraded (UD), lightly degraded (LD), moderately degraded (MD), and heavily degraded (HD)) under different water gradients (high water content (HWC), medium water content (MWC), and low water content (LWC)) corresponding to different drying durations at a constant temperature of 40.0 degrees C. The Huangcheng Mongolian Township in Menyuan Hui Autonomous County, Qinghai Province, China was chosen as the study area. The results indicated that as the degradation degree of alpine meadow intensified, both water content of root-soil composite and the fine grain content of soil decreased. In contrast, the root-soil mass ratio and root area ratio initially increased and then decreased with progressive degradation. Under a consistent water content, the tensile strength of root-soil composite followed a pattern of MD>HD>LD>UD. The peak displacement of tensile strength also decreased as the degradation degree of alpine meadow increased. Both the tensile strength and matrix suction of root-soil composite increased as root-soil water content decreased. A root-soil water content of 30.00%-40.00% was found to be the critical threshold for soil cracking in alpine meadows. Within this range, the matrix suction of root-soil composite ranged from 50.00 to 100.00 kPa, resulting in the formation of linear cracks in the surface soil. As the root-soil water content continued to decrease, liner cracks evolved into branch-like and polygonal patterns. The findings of this study provide essential data for improving the mechanical understanding of grassland cracking and its development process.

The stress state is the fundamental for evaluating the soil strength and stability, playing a crucial role. However, during the stress testing, local damage and other uncertain factors may lead to partial sensor data missing, causing the existing three-dimensional stress calculation method to fail. To accurately restore the soil stress state during data missing, a three-dimensional stress calculation method was developed based on three-dimensional stress testing principles, incorporating axisymmetric and one-dimensional compression characteristics. The three-dimensional stress, principal stress , the first invariant of stress I-1, the second in variant of stress J(2) and stress Lode angle of a sandy soil foundation under one-dimensional compression conditions with different data missing were calculated and compared to results with complete data. The results show that the method is highly accurate; as the load increases, the relative error decreases and converges. The principal stresses, the first invariant of stress I-1, the second invariant of stress J(2) and the stress Lode angle align with one-dimensional compression response, suggesting that this calculation method supports advanced data mining. This study offers a novel approach and a practical method for fully utilizing the test data.

The soil packing, influenced by variations in grain size and the gradation pattern within the soil matrix, plays a crucial role in constituting the mechanical properties of sandy soils. However, previous modeling approaches have overlooked incorporating the full range of representative parameters to accurately predict the soaked California bearing ratio (CBRs) of sandy soils by precisely articulating soil packing in the modeling framework. This study presents an innovative artificial intelligence (AI)-based approach for modeling the CBRs of sandy soils, considering grain size variability meticulously. By synthesizing extensive data from multiple sources, i.e. extensive tailored testing program undertaking multiple tests and extant literature, various modeling techniques including genetic expression programming (GEP), multi-expression programming (MEP), support vector machine (SVM), and multi-linear regression (MLR) are utilized to develop models. The research explores two modeling strategies, namely simplified and composite, with the former incorporating only sieve analysis test parameters, while the latter includes compaction test parameters alongside sieve analysis data. The models' performance is assessed using statistical key performance indicators (KPIs). Results indicate that genetic AI-based algorithms, particularly GEP, outperform SVM and conventional regression techniques, effectively capturing complex relationships between input parameters and CBRs. Additionally, the study reveals insights into model performance concerning the number of input parameters, with GEP consistently outperforming other models. External validation and Taylor diagram analysis demonstrate the GEP models' superiority over existing literature models on an independent dataset from the literature. Parametric and sensitivity analyses highlight the intricate relationships between grain sizes and CBRs, further emphasizing GEP's efficacy in modeling such complexities. This study contributes to enhancing CBRs modeling accuracy for sandy soils, crucial for pertinent infrastructure design and construction rapidly and cost-effectively. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).