Search Results (1,459)

Assessing the stress–strain state around interacting mining excavations using the finite element method (FEM) is computationally expensive for parametric studies. This study evaluates tabular machine-learning surrogate models for the rapid prediction of full stress–strain fields in fractured rock masses treated as an equivalent continuum. A dataset of 1000 parametric FEM simulations using the elastoplastic generalized Hoek–Brown constitutive model was generated to train Random Forest, LightGBM, CatBoost, and Multilayer Perceptron (MLP) models based on geometric features. The results show that the best models achieve R² scores of 0.96–0.97 for stress components and 0.99 for total displacements. LightGBM and CatBoost provide the optimal balance between accuracy and computational cost, offering speed-ups of 15 to 70 times compared to FEM. While Random Forest yields slightly higher accuracy, it is resource-intensive. Conversely, MLP is the fastest but less accurate. These findings demonstrate that data-driven surrogates can effectively replace repeated FEM simulations, enabling efficient parametric analysis and intelligent design optimization for mine workings. Full article

Sustainable food production for a growing population requires farming practices that reduce chemical inputs while maintaining soil as a living, renewable foundation for productivity. This review synthesizes current advances in understanding how endophytic fungi (EFs) interact with the soil microbiome and contribute to the physicochemical and biological dimensions of soil health in arable ecosystems. We examine evidence showing that EFs enhance plant nutrition through phosphate solubilization, siderophore-mediated micronutrient acquisition, and improved nitrogen use efficiency while also modulating plant hormones and stress-responsive pathways. EFs further increase crop resilience to drought, salinity, and heat; suppress pathogens; and influence key soil properties including aggregation, organic matter turnover, and microbial network stability. Recent integration of multi-omics, metabolomics, and community-level analyses has shifted the field from descriptive surveys toward mechanistic insight, revealing how EFs regulate nutrient cycling and remodel rhizosphere communities toward disease-suppressive and nutrient-efficient states. A central contribution of this review is the linkage of EF-mediated plant functions with soil microbiome dynamics and soil structural processes framed within a translational pipeline encompassing strain selection, formulation, delivery, and field scale monitoring. We also highlight current challenges, including context-dependent performance, competition with native microbiota, and formulation and deployment constraints that limit consistent outcomes under field conditions. By bridging microbial ecology with agronomy, this review positions EFs as biocontrol agents, biofertilizers, and ecosystem engineers with strong potential for resilient, low-input, and climate-adaptive cropping systems. Full article

Dendritic cells (DCs) are essential for antiviral immunity but are also susceptible to HIV-1 infection. Although sensing and restriction pathways in DCs are well described, the mechanisms underlying latent infection and its functional consequences remain unclear. In this study, we performed transcriptomic profiling of monocyte-derived DCs harboring transcriptionally active (Active-HIV) or latent HIV-1 (Latent-HIV) proviruses using a dual-reporter virus. Gene set enrichment analysis revealed suppression of metabolic and stress-modulatory programs in Active-HIV compared to unexposed DCs. In contrast, Latent-HIV showed broad downregulation of pathways, including interferon and innate responses and metabolic programs, indicating a hyporesponsive and dampened antiviral state despite the absence of differentially expressed genes (DEGs). DEG analysis of Active-HIV versus Latent-HIV showed that active transcription associates with cellular stress, cytoskeletal remodeling, and RNA processing. Functional analyses further demonstrated the activation of RNA processes, the suppression of antigen-presentation pathways, and altered membrane and cytoskeletal signaling in Active-HIV. These pathways suggest that transcriptionally active HIV-1 is linked to cellular programs supporting replication, coinciding with a metabolically strained yet immunologically engaged state that may impair antigen presentation. Conversely, latently infected DCs display a hyporesponsive state consistent with proviral silencing. This dichotomy reveals distinct mechanisms of DC dysfunction that may facilitate HIV-1 persistence and immune evasion. Full article

Uncertainty quantification in science and engineering has become increasingly important due to advances in computational mechanics and numerical simulation techniques. In this work, the relationship between uncertainty in soil material parameters and the variability of failure loads and displacements of a shallow foundation is investigated. A Drucker–Prager constitutive law is implemented within a stochastic finite element framework. The random material variables considered are the critical state line slope c, the unload–reload path slope $\kappa$, and the hydraulic permeability k defined by Darcy’s law. The novelty of this work lies in the integrated stochastic u–p finite element framework. The framework combines Drucker–Prager plasticity with spatially varying material properties, and Latin Hypercube Sampling. This approach enables probabilistic prediction of failure loads, displacements, stresses, strains, and limit-state initiation points at reduced computational cost compared to conventional Monte Carlo simulations. Statistical post-processing of the output parameters is performed using the Kolmogorov–Smirnov test. The results indicate that, for the investigated configurations, the distributions of failure loads and displacements can be adequately approximated by Gaussian distributions, despite the presence of material nonlinearity. Furthermore, the influence of soil depth and load eccentricity on the limit-state response is quantified within the proposed probabilistic framework. Full article

To elucidate the micromechanical origins of the macroscopic anisotropic behavior of granular materials, this study develops a micromechanically based elastoplastic constitutive model for sand. First, anchored in the static equilibrium hypothesis and granular micromechanics theory, a true stress tensor is introduced to characterize the authentic inter-particle contact forces. Serving as a coupled variable of the macroscopic stress and the microscopic fabric tensor, this formulation not only quantifies the directional distribution of the contact network but also enables the mapping of anisotropic yielding and deformation analyses into an equivalent isotropic true stress space. Subsequently, a comprehensive constitutive framework is established by integrating critical state theory, an anisotropic fabric evolution law, and an energy-based stress–dilatancy relationship that explicitly accounts for the evolution mechanism of the microscopic coordination number. The physical interpretation, calibration procedure, and sensitivity analysis of the model parameters are also presented. The predictive capability of the model is rigorously validated against conventional triaxial tests on Ottawa sand, true triaxial numerical simulations, and experimental data for Toyoura sand with inherent anisotropy. The comparisons demonstrate that the model accurately captures not only the stress–strain response and volumetric deformation under conventional loading but also the strength dependency on loading direction and mechanical characteristics under complex stress paths, substantiating the validity and universality of the proposed micromechanical approach. Full article

Silica-rich dust intrusion is a persistent challenge for lubrication systems in agricultural machinery, where abrasive third-body particles can accelerate wear and shorten component service life. Here, molecular dynamics simulations are employed to elucidate how SiO₂ nanoparticle contamination degrades polyalphaolefin (PAO) boundary lubrication at the atomic scale. Two confined sliding models are compared: a pure PAO film and a contaminated PAO film containing 7 wt% SiO₂ nanoparticles between crystalline Fe substrates under a constant normal load and sliding velocity. The contaminated system exhibits a higher steady-state friction force, faster lubricant film disruption and migration, and consistently higher interfacial temperatures, indicating intensified energy dissipation. Substrate analyses reveal deeper and stronger von Mises stress penetration, increased severe plastic shear strain, elevated Fe potential energy associated with defect accumulation, and reduced structural order. Meanwhile, PAO molecules store more intramolecular deformation energy (bond, angle, and dihedral terms), reflecting stress concentration and disturbed shear alignment induced by nanoparticles. These results clarify the multi-pathway mechanisms by which abrasive SiO₂ contaminants transform PAO from a protective boundary film into an agent promoting abrasive wear, providing insights for designing wear-resistant lubricants and improved filtration strategies for particle-laden applications. Full article

With the advancement in deep-sea resource development, the creep behavior of deep-sea remolded sediments under coupled temperature, confining pressure (σ₃), and stress effects has become a critical issue threatening engineering stability. The traditional Singh–Mitchell model, limited by its neglect of temperature effects and prediction of infinite strain, struggles to meet deep-sea environmental requirements. Based on low-temperature, high-pressure triaxial tests (with temperatures ranging from 4 to 40 °C and confining pressures ranging from 100 to 300 kPa), this study proposes a modified model incorporating temperature–stress–time coupling. The model introduces a hyperbolic creep strain rate decay function to achieve strain convergence, establishes a saturated strain–stress exponential relationship, and quantifies the effect of temperature on characteristic time via coupling through the Arrhenius equation. The modified model demonstrates R² values > 0.96 for full-condition creep curves. The results show several key findings: a 10 °C increase in temperature leads to a 30–50% growth in the steady-state creep rate; a 100 kPa increase in confining pressure enhances long-term strength by 20–30%. 20 °C serves as a critical temperature point. At this point, strain amplification reaches 2.1 times that of low-temperature ranges. These experimental findings provide crucial theoretical foundations and technical support for incorporating soil creep effects in deep-sea engineering design. Full article

Under the influence of engineering disturbances, the loading rate of surrounding rock is in a state of continuous adjustment. This study conducts experimental investigations on the mechanical response characteristics under different strain rates (10⁻⁵ s⁻¹, 10⁻⁴ s⁻¹, and 10⁻³ s⁻¹). During the uniaxial loading process of coal–rock composite specimens, multi-parameter monitoring was implemented, and a systematic study was carried out on the ring-down count induced by microcracks, the energy values of acoustic emission (AE) events, the stage-dependent strain characteristics on the specimen surface, and the surface temperature variation characteristics. Additionally, the stress–strain curve characteristics under different strain rates were comparatively analyzed in stages. The loading process of the coal–rock composite specimens was reproduced using the Particle Flow Code (PFC3D 6.0) simulation software. The simulation results indicate that the stress–strain results obtained from the simulation are in good agreement with the laboratory test results; based on these simulation results, the energy accumulation and dissipation characteristics of the coal–rock composite specimens under the influence of strain rate were revealed. Furthermore, a microscopic damage model considering strain rate was constructed based on the Weibull probability statistics theory. The results show that strain rate has a significant impact on the strength, elastic modulus, and failure mode of the coal–rock composite specimens. At low strain rates, the specimens exhibit obvious progressive failure characteristics and strain localization phenomena, while at higher strain rates, they show brittle sudden failure characteristics. Meanwhile, the thermal imaging results reveal that at high strain rates, the overall temperature rise in the composite specimens is rapid, whereas at low strain rates, the overall temperature rise is slow—but the temperature rise in the coal portion is faster than that in the rock portion. The peak temperature at high strain rates is approximately 2 °C higher than that at low strain rates. The PFC simulation results demonstrate that the larger the strain rate, the faster the growth rate of plastic energy in the post-peak stage and the faster the release rate of elastic energy. Full article

Stress is a pervasive global health concern that adversely contributes to morbidity and reduced productivity, yet it often remains unquantified due to its subjective and variant presentation. Although artificial intelligence offers an encouraging path toward automated monitoring of mental states, current state-of-the-art approaches are challenged by the reliance on single-source data, sparsity of labeled samples, and significant class imbalance. This paper proposes NeuroStrainSense, a novel deep multimodal stress detection model that integrates three complementary datasets—WESAD, SWELL-KW, and TILES—through a Transformer-based feature fusion architecture combined with a Variational Autoencoder for generative data augmentation. The Transformer architecture employs four encoder layers with eight multi-head attention heads and a hidden dimension of 512 to capture complex inter-modal dependencies across physiological, audio, and behavioral modalities. Our experiments demonstrate that NeuroStrainSense achieves a state-of-the-art performance with accuracies of 87.1%, 88.5%, and 89.8% on the respective datasets, with F1-scores exceeding 0.85 and AUCs greater than 0.89, representing improvements of 2.6–6.6 percentage points over existing baselines. We propose a robust evaluation framework that quantifies discrimination among stress types through clustering validity metrics, achieving a Silhouette Score of 0.75 and Intraclass Correlation Coefficient of 0.76. Comprehensive ablation experiments confirm the utility of each modality and the VAE augmentation module, with physiological features contributing most significantly (average performance decrease of 5.8% when removed), followed by audio (2.8%) and behavioral features (2.1%). Statistical validation confirms all findings at the p < 0.01 significance level. Beyond binary classification, the model identifies five clinically relevant stress profiles—Cognitive Overload, Burnout, Acute Stress, Psychosomatic, and Low-Grade Chronic—with an expert concordance of Cohen’s κ = 0.71 (p < 0.001), demonstrating the strong ecological validity for personalized well-being and occupational health applications. External validation on the MIT Reality Mining dataset confirms the generalizability with minimal performance degradation (accuracy: 0.785, F1-score: 0.752, AUC: 0.849). This work underlines the potential of integrated multimodal learning and demographically aware generative AI for continuous, precise, and fair stress monitoring across diverse populations and environmental contexts. Full article

Coarse-grained soil is a commonly used filling material in foundation engineering, and its static shear characteristics are significantly affected by the initial stress state. For coarse-grained soils, clearly defining the drainage conditions and improving the accuracy of pore water pressure measurements are crucial in static shear tests. Based on GDS dynamic and static true triaxial equipment, this paper systematically conducts static shear tests on coarse-grained soil under three-dimensional initial isotropic, three-dimensional initial anisotropic, and plane strain states. The effects of initial mean principal stress, initial generalized shear stress, initial intermediate principal stress coefficient, and water content on the stress–strain relationship, strength, modulus, and friction angle of coarse-grained soil are analyzed. The research shows that under the same initial mean principal stress, the peak strength under a plane strain state is the largest, and that under a three-dimensional initial anisotropic state is the smallest. The peak strength of coarse-grained soil with optimal water content is generally higher than that under a saturated state; under a three-dimensional initial anisotropic state, the peak strength decreases with an increase in the initial generalized shear stress and increases with an increase in the initial intermediate principal stress coefficient. The research results provide a theoretical basis for the analysis of mechanical behavior of coarse-grained soil in foundation engineering. Full article

With the ubiquitous connectivity and exposure of social network service (SNS), the stressors it causes have received extensive attention in the academic community. Unlike previous studies, this research focuses on the cross-cultural dimension and explores the different effects of multiple SNS-generated stressors on user behavior outcomes. Based on the “Stressors-Strain-Outcome” (SSO) theoretical framework, we constructed a “technical stressors—exhaustion—reduced SNS usage intention” pathway to systematically investigate five types of technical stressors. These were perceived information overload, perceived social overload, perceived compulsive use, perceived privacy concern, and perceived role conflict. We introduce “fear of missing out” (FOMO) as a moderating variable to explore its moderating role in SNS exhaustion and reduced SNS usage intention. In this study, we took SNS users from China and the United States as the research subjects (338 samples from China and 346 samples from the United States), and conducted empirical tests using structural equation models and multiple comparative analyses. The results show that there are significant cultural differences between Chinese and American users in terms of the perceived intensity of technostress, the path of stress transmission, and the moderating effect of FOMO. Against the background of collectivist culture in China, perceived information overload, privacy concerns, and role conflicts have a significant positive impact on SNS exhaustion, and SNS exhaustion further positively drives the intention to reduce usage of SNS. However, the direct impacts of perceived social overload and perceived compulsive usage are not significant, and FOMO does not play a significant moderating role. In the context of the individualistic culture found in the United States, only perceived information overload and perceived social overload have a significant positive impact on SNS exhaustion, and FOMO significantly negatively moderates the relationship between exhaustion and reduced SNS usage intention, as high FOMO levels will strengthen the driving effect of exhaustion on reduced usage intention. The innovation this study exhibits lies in verifying the applicability of the SSO model in social media behavior research from a cross-cultural perspective, revealing the cultural boundaries of the FOMO moderating effect, and enriching the cross-cultural research system of reduced usage intention of SNS. The research results not only provide empirical support for a deep understanding of the psychological mechanisms of users’ SNS usage behaviors in different cultural backgrounds, but also offer important references that SNS enterprises can use to formulate differentiated operation strategies and optimize cross-cultural user experiences. Full article

Inter-pass forging with different degrees of deformation during WAAM of Inconel 718 specimens (single-stage, three passes; two-stage, six passes) was investigated. Macrostructural analysis of the specimens showed that inter-pass forging led to a recrystallized structure. Alternation of layers with different grain shapes (columnar and equiaxed) is observed throughout the height of the specimens. Increasing the number of passes improves the mechanical properties of the material (tensile strength, yield strength, microhardness). A finite element model of inter-pass forging was developed to determine the effect of inter-pass surface deformation during WAAM on the residual stress–strain state. The non-stationary formulation was replaced with a quasi-static one. Johnson–Cook material constants were obtained for the deposited Inconel 718 material, including the effect of forging. Verification of the mathematical model was performed using a wall (specimen 2) deposited with single-stage forging. The deviation between the simulation results and the experiment did not exceed 15%. It was found that the sequence and number of passes significantly affect residual strain and displacements but have little effect on residual stress. Numerical modeling showed that the depth of plastic deformation exceeds the melting depth when depositing the subsequent layer, ensuring the preservation and accumulation of the inter-pass forging effect throughout the deposition process. Full article

Al–Al₄C₃ composites exhibit promising mechanical properties including high specific strength, high specific stiffness. However, high reinforcement contents often promote brittle behavior, making it necessary to understand the mechanisms governing their limited toughness. In this work, a microstructural and mechanical study was carried out to evaluate the energy storage capacity in Al–Al₄C₃ composites fabricated by mechanical milling followed by heat treatment using X-ray diffraction (XRD) and Convolutional Multiple Whole Profile (CMWP) fitting method, the microstructural parameters governing the initial stored energy after fabrication were determined: dislocation density (ρ), dislocation character (q), and effective outer cut-off radius (R_e). Compression tests were carried out to quantify the elastic energy stored during loading (Es). The energy absorption efficiency (EAE) in the elastic region of the stress–strain curve was evaluated with respect to the elastic energy density per unit volume stored (Ee), obtained from microstructural parameters (ρ, q, and Re) present in the samples after fabrication and determined by XRD. A predictive model is proposed that expresses Es as a function of Ee and q, where the parameter q is critical for achieving quantitative agreement between both energy states. In general, samples with high EAE exhibited microstructures dominated by screw-character dislocations. High-resolution transmission electron microscopy (HRTEM) analyses revealed graphite regions near Al₄C₃ nanorods—formed during prolonged sintering—which, together with the thermal mismatch between Al and graphite during cooling, promote the formation of screw dislocations, their dissociation into extended partials, and the development of stacking faults. These mechanisms enhance the redistribution of stored energy and contribute to improved toughness of the composite. Full article

Considering the complexity and diversity of water-rich soft soil strata, indoor triaxial shear tests and creep tests were conducted on soft soil to explore its deformation law and creep characteristics. To address the nonlinear characteristics of soft soil creep, a nonlinear pot element was proposed and substituted for the two linear pot elements in the Burgers model, thus establishing an unsteady parametric Burgers model. The one-dimensional creep equation of the unsteady Burgers model was derived, theoretically determining that the unsteady model can describe three stages of creep. Based on this, the creep equation of the unsteady Burgers model was extended to a three-dimensional stress state, and the triaxial compression creep test curves of Ningbo soft soil were fitted and parameters identified. The above model was derived from a three-dimensional finite difference scheme suitable for numerical solution in FLAC3D. A custom constitutive creep model was developed in FLAC3D, and the non-accelerated creep stage and accelerated creep stage of the improved model were analyzed to verify the accuracy and reliability of the constitutive model. The results show that the numerical simulation results and the indoor creep test results are in good agreement in terms of strain increment and the creep change curve, which confirms the effectiveness and applicability of the proposed unsteady Burgers creep constitutive model and its secondary development application. Full article

The study establishes key patterns in the influence of pre-applied impact-oscillatory loading (IOL) of varying intensity—realizing dynamic non-equilibrium processes (DNP)—in liquid nitrogen on the mechanical properties and structural state of stainless steel X10CrNi18-8. Static tensile deformation was investigated at room temperature following impulsive strain levels of ε_imp = 0.06–2.69%. A wave-like mechanical response of the steel to DNP was observed within this ε_imp range, most pronounced at ε_imp = 0.11% and ε_imp = 2.69%. After DNP at ε_imp = 0.11%, despite a maximum increase in ultimate strength by 5.25%, the relative elongation of the specimen increased to 10.3%. The scatter in ultimate tensile strength specimens across all loading regimes was within 6.38%, while the variation in ductility reached up to 21.25%. In contrast, after ε_imp = 2.69%, the stress–strain diagram resembled that of the steel in its initial state. Metallophysical investigations and X-ray diffraction analysis were conducted to explain the observed effects. At ε_imp > 2.7%, the high-strength but low-ductility X10CrNi18-8 steel undergoes brittle failure under impulsive loading. At the same time, the total fraction of the more brittle martensitic phase in the steel microstructure reaches approximately 22%. Full article