Search Results (8,408)

This study aims to investigate the influence of clay mineral content on the rheological properties and long-term deformation stability of clays, and to establish a unified model capable of quantitatively describing the nonlinear rheological behavior of clays with different mineral compositions. Direct shear rheological tests were conducted on specimens prepared with different mixing ratios of bentonite, kaolin, and quartz. Combined with micro-mechanism analysis, the controlling factors of clay rheological behavior were explored. The experimental results show that the creep stress threshold, elastic viscosity, and average plastic viscosity decrease significantly with increasing clay mineral content. The rheological deformation exhibits distinct nonlinear characteristics, and clay mineral content plays a controlling role in the rheological behavior. Based on experimental and mechanistic analysis, a unified rheological model was established, which reflects the material origin of rheology and captures nonlinear rheological characteristics. This model can predict the entire time-history mechanical behavior of clays with different mineral compositions across the three stages of instantaneous deformation, decay rheology, and steady-state rheology under different shear stress levels using a single set of parameters. Validation was performed through direct shear rheological tests under 50 working conditions for five types of clay specimens, demonstrating good consistency between the model calculations and experimental results. The unified rheological model reveals the material origin and physical essence of clay rheology, demonstrates high universality, and advances the understanding of the influence of mineral composition on rheology from the current phenomenological qualitative description to quantitative calculation for the first time, significantly enhancing its engineering application value. This provides a more reliable tool for predicting long-term deformation and assessing the stability of clay foundations. Full article

Lactic acid bacteria (LABs) produce bacteriocins, which are increasingly recognized as effective biopreservatives for smoked salmon. These bacteriocins may help solve the ongoing problem of controlling Listeria monocytogenes in the smoked salmon industry. L. monocytogenes is a psychrotolerant, salt-tolerant foodborne pathogen capable of surviving the refrigerated, low-oxygen conditions typical of smoked salmon processing. Its presence poses significant public health risks, particularly for immunocompromised individuals, and continues to drive costly product recalls and regulatory pressure. Conventional control strategies, including chemical preservatives and physical treatments, are increasingly limited by consumer demand for clean-label foods and the pathogen’s ability to persist in processing environments. The bacteriocins produced by LABs provide a precise and natural alternative to conventional preservatives. These antimicrobial peptides can inhibit L. monocytogenes through membrane disruption and metabolic interference while maintaining the sensory quality of smoked salmon. Their application in surface treatments, protective coatings, and active packaging has demonstrated strong potential to suppress pathogen growth during chilled storage. As the smoked salmon industry is seeking sustainable and effective biocontrol tools, bacteriocins represent a viable strategy to enhance product safety, extend shelf life, and reduce reliance on synthetic additives. Continued research into their stability, delivery systems, and synergistic combinations will be essential for integrating bacteriocins into modern smoked salmon preservation frameworks. Full article

The incorporation of plant-derived oils into cosmetic formulations has attracted increasing interest due to their natural origin, skin compatibility, and multifunctional formulation roles. Argan and castor oils are widely used in cosmetic products as emollient lipid components with intrinsic antioxidant properties. However, limited studies have systematically evaluated the physicochemical stability and antioxidant performance of emulsions combining these two oils. The aim of this study was to develop and comprehensively characterize a stable oil-in-water (O/W) cosmetic emulsion based on argan and castor oils using a natural non-ionic emulsifier (C14–22 Alcohol (and) C12–20 Alkyl Glucoside). Particular emphasis was placed on formulation stability, as it represents a critical prerequisite for further product evaluation. Stability was investigated through thermal stress testing (4–37 °C), centrifugation assays, droplet size analysis, and zeta potential measurements. Complementary physicochemical and structural characterization was performed using rheological analysis and Fourier transform infrared (FT-IR) spectroscopy. The formulated emulsion exhibited good physical stability with no phase separation under the tested conditions, a skin-compatible pH, a uniform droplet size distribution (4.15 ± 0.68 µm), and pseudoplastic, moderately thixotropic rheological behavior. Antioxidant capacity was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay, yielding an IC₅₀ value of 19.21 ± 1.02 mg/mL. Overall, this study provides a formulation-oriented framework for the development and evaluation of stable natural oil-based O/W emulsions intended for cosmetic applications, supporting future optimization and biological validation. Full article

The driven damped pendulum is a foundational model in nonlinear dynamics, with applications ranging from Josephson junctions to MEMS oscillators. Conventional dimensionless treatments obscure the common physical origin of damping and driving in the inertia coefficient. Here we restore this dependence and establish inertia as a master control parameter governing stability, resonance, and bifurcations. Through linear analysis and perturbation theory, we derive universal scaling laws revealing a fundamental dichotomy: quantities at resonance—peak amplitude and nonlinear frequency shift—are independent of inertia due to exact algebraic cancellation between the inertia dependence of the effective driving amplitude and effective damping coefficient. Off resonance, however, amplitude scales inversely with inertia, bandwidth narrows proportionally, and the bistability threshold exhibits an even steeper dependence. A critical inertia separates underdamped from overdamped regimes, yielding non-monotonic relaxation times that maximize attractor memory at extreme inertia values. These scaling laws provide design guidelines: low inertia promotes broadband response for energy harvesting; high inertia suppresses off-resonant vibrations for precision timing and quantum applications. By establishing inertia as a physically realizable path through parameter space, this work unifies disparate phenomena and provides a framework for understanding stability in inertial-driven systems. Full article

Forest height is a key structural parameter for characterizing forest architecture and estimating carbon storage. However, under complex terrain and heterogeneous forest conditions, Polarimetric synthetic aperture radar (PolSAR)-based forest height inversion using multi-category features still faces several challenges, including feature redundancy, insufficient characterization of the nonlinear couplings among high-dimensional features by deep learning models, and the difficulty of jointly achieving model stability and interpretability. In this paper, to address these issues, we propose a method for SHapley Additive exPlanations (SHAP) interpretability-driven PolSAR forest height inversion based on deep learning and multi-category feature fusion. Firstly, a deep neural network (DNN) is constructed, and SHAP is introduced to interpret the model decision process, enabling the identification of key feature interactions with clear physical significance and guiding the iterative model optimization in an explainability-driven manner. Furthermore, a SHAP-guided feature attention DNN is developed, in which the feature contribution scores are incorporated as prior knowledge for attention weight initialization, thereby establishing a closed-loop modeling framework from “interpretation” to “optimization”. Experiments were conducted at the site of the Huangfengqiao forest farm, Youxian County, Hunan province, China, using ALOS-2 L-band fully polarimetric SAR imagery. The experimental results demonstrated that the proposed method can significantly outperform the conventional machine learning approaches and various deep learning architectures for forest height inversion. The final model achieved a coefficient of determination (R²) score of 0.75 and a root-mean-square error (RMSE) of 1.35 m on the test dataset. These findings indicate that the combination of SHAP-driven multi-category feature fusion and deep learning can effectively enhance both the inversion accuracy and physical interpretability, providing a reliable solution for PolSAR-based forest structural parameter retrieval at the Huangfengqiao study site, with potential applicability to complex terrain conditions. Full article

Industrial Control Systems (ICSs) are the backbone of modern critical infrastructure, such as electric power, water treatment, oil and gas distribution, and manufacturing operations. While the convergence of IT and OT has greatly increased efficiency and observability, it has also greatly expanded the attack surface of these once-isolated systems. High-profile cyber-physical attacks, including Stuxnet (2010), TRITON (2017), and the Colonial Pipeline ransomware attack (2021), have shown that ICS-targeted cyberattacks can cause physical damage, disrupt economic stability, and put public safety at risk. Despite the growing prevalence and intensity of such threats, ICS-based cybersecurity education remains largely under-resourced and underfunded. Traditional ICS training laboratories require highly specialized hardware, vendor-specific tools, and expensive licensing that significantly raise barriers to entry. Traditional labs typically require on-site participation and pose physical safety concerns when cyber-physical attack scenarios are performed. These barriers leave students unable to get necessary security training for ICSs. Therefore, this paper introduces AE${}^3$GIS: Agile Emulated Educational Environment for Guided Industrial Security—a fully virtual, lightweight, open-source platform designed to democratize ICS cybersecurity education. Based on the GNS3 network simulation tool, AE${}^3$GIS enables rapid deployment of comprehensive ICS environments containing IT and OT systems, industrial communication protocols, control logic, and diverse security tools. AE${}^3$GIS is designed to provide practical training for students using realistic ICS cybersecurity scenarios through a local or remote training platform without the cost, safety, or accessibility limitations of hardware-based labs. Full article

To meet the real-time computational requirements of active suspension control systems, this study shifts from complex microscopic physical equations to a direct nonlinear functional mapping between the relative motion states (displacement and velocity) and the output force of air springs. This approach aims to preserve critical nonlinear hysteresis characteristics while significantly reducing the computational overhead. A progressive modeling strategy is implemented to characterize these complex behaviors. Initially, polynomial fitting is employed to identify key input features; however, its limited capacity to capture intricate nonlinearities necessitates more advanced methods. Subsequently, standard Feedforward Neural Networks (FNNs) are explored for their nonlinear mapping capabilities, yet their inherent “black-box” nature often leads to convergence difficulties and restricted generalization. To address these issues, a Physics-Informed Neural Network (PINN) architecture is introduced, embedding physical governing equations as regularization constraints within the loss function to integrate data-driven flexibility with mathematical rigor. Recognizing that conventional PINNs often encounter convergence challenges due to conflicts between PDE constraints and data-driven loss terms, this research develops a Physics-Embedded Hierarchical Network (PEHN). By deriving specialized PDE constraints tailored to air spring dynamics and designing a hierarchical architecture aligned with these physical requirements, the PEHN effectively balances physical priors with experimental data. Experimental results demonstrate that, compared to the baseline models, the proposed PEHN exhibits stronger stability and superior accuracy in capturing the complex nonlinearities of air spring dynamics. Full article

Background: The global spread of monkeypox virus (MPXV) highlights an urgent need for thermostable and easily administrable vaccines. Current orthopoxvirus vaccines are limited by cold-chain dependence and inconvenient injection-based delivery. Objectives: This study aimed to develop a dissolvable microneedle (DMN) vaccine against monkeypox based on a replication-deficient orthopoxvirus platform, through systematic formulation screening, stabilization mechanism exploration, and rigorous in vivo immunogenicity evaluation. Methods: A film-based approach was adopted for efficient, high-throughput formulation screening and thermostability assessment. NTV was mixed with excipients and dried into solid films. Stability was monitored via RT-qPCR after storage at 4 °C to 40 °C. The lead formulation was physically characterized, then used to fabricate MVA-BN-loaded DMN patches, which were further evaluated for in vivo immunogenicity via immunization in BALB/c mice. Results: The optimal formulation F2 (containing dextran, L-threonine, and BSA/HSA) showed a potency loss of only ~1 log₁₀ after 2 months at 25 °C, and <1 log₁₀ loss after 1 week at 37 °C. SEM revealed a porous virus-entrapment morphology, and FTIR indicated enhanced hydrogen bonding between the virus and the dextran matrix. The formulation was successfully manufactured into DMNs that dissolved within 5 min. In mice, these DMNs elicited robust MPXV-specific IgG and neutralizing antibody responses, with immunogenicity comparable to that induced by conventional intramuscular injection. Conclusions: This study successfully established a thermostable formulation and dissolvable microneedle delivery platform for replication-deficient orthopoxvirus vaccines against monkeypox. The optimized DMN vaccine induced robust MPXV-specific immune responses in mice with immunogenicity comparable to intramuscular injection, addressing the core limitations of current vaccines and providing a promising solution for monkeypox prevention. Full article

Research using latent profile analysis (LPA) has yielded inconsistent results regarding the number of personality profiles among athletes, the specific configuration of the Big Five traits, and their interpretation. This study seeks to explore personality types by excluding additional variables from the LPA model, aiming to assess how well personality profiles are universal (independent of gender and cultural context) and can predict academic achievement in student athletes. A cross-sectional study was conducted using a paper-and-pencil questionnaire among 424 student athletes from two universities in Poland and Ukraine. The average age of participants was 20 years old (M = 20.01; SD = 2.48), 62% were male, 53% lived in Poland, and 58% studied Sports Sciences vs. 42% Physical Education. The Mini-International Personality Item Pool (Mini-IPIP) was used to assess the Big Five personality traits, and grade point average (GPA) was used to measure students’ academic achievements in the last semester. The LPA identified four personality profiles: (1) Restrained Neurotic (Profile 1, 32%), Open Extravert (Profile 2, 42%), Competitive Neurotic (Profile 3, 17%), and Cooperative Perfectionist (Profile 4, 8%). Profiles 1, 3, and 4 showed similarly low levels of emotional stability, extraversion, and intellect but differed significantly in agreeableness and conscientiousness. Gender and country differences across athletes representing specific profiles were also noted. Profile 2 showed the strongest link with academic achievement. Hierarchical multiple linear regression showed that LPA profiles explained only 2% of GPA variance, compared to Big Five personality traits (9%) and demographic variables, such as sex, country, and study major (8%), which were also included in the following steps in the regression model, explaining only 9% and 8%, respectively. Most student athletes (52%) with personality profiles 1 (Restrained Neurotic), 3 (Competitive Neurotic), and 4 (Cooperative Perfectionist) may require psychological training to better cope with negative emotions and stress arising in competitive and academic settings. Profile 2 (Open Extravert) seems to be the most adaptive and potentially successful personality type. Personality types are, at least to some extent, related to gender and country of residence. More cross-cultural research is required to further verify the types of athletic personalities. Full article

The restricted availability of raw materials underscores the significance of recycling asphalt materials that have reached the end of their service life, facilitating their reuse with additives for economic and sustainability benefits. The study includes both empirical investigations and numerical analyses. Empirical studies were conducted in four stages to evaluate the binder and mixture. First, the rheological properties of binders obtained from various sources were assessed in both unmodified and modified states. Second, the binders were subjected to different levels of aging. Third, the presence of additives in the binders was investigated. In the final stage, the analysis of asphalt pavement layers was conducted using the finite element method (FEM) for both modified and unmodified binders. Performance tests were carried out to evaluate the binder’s properties, and physical examinations were conducted to compare these properties. The binders were tested under both unaged and aged conditions using linear amplitude sweep (LAS), frequency sweep (FS), multiple stress creep recovery (MSCR), and bending beam rheometer (BBR) tests. The results indicated that aging increased the stiffness of the binders, regardless of their source. Additionally, the introduction of a rejuvenator reduced the binder’s stiffness, particularly at low temperatures. Findings showed that the growth rate (GR) and rutting parameters increased with binder aging, while the frequency decreased. The R² value of 0.92 demonstrates a strong correlation between the parameters. Polymer-modified binders demonstrated superior deformation resistance and higher stiffness stability. Overall, aging reduced asphalt flexibility, whereas modified binders improved long-term pavement deformation performance. Full article

Wood is the quintessential material for musical instruments due to its superior acoustic properties. However, its inherent susceptibility to environmental degradation—including moisture-induced dimensional changes, photodegradation, and biological attack—presents a fundamental challenge that treatment strategies must address. This critical review systematically examines recent advances in wood modification and surface protection technologies for musical instruments, encompassing chemical and thermal modification, protective coatings, physical densification, and biological treatments. Drawing on studies published over the past two decades, this review synthesizes current knowledge on how these interventions affect wood’s acoustic performance, dimensional stability, mechanical integrity, and long-term durability. A central finding is that treatment outcomes are highly species-specific and involve complex performance trade-offs: acoustic optimization often comes at the expense of mechanical strength or dimensional stability, and the optimal solution varies depending on the functional requirements of specific instrument components (e.g., soundboards versus fingerboards). Emerging bio-based and nanocomposite coatings show promise for enhancing environmental resistance, but their acoustic implications remain largely unexplored. Furthermore, most research remains at the laboratory scale, with limited validation on full instruments and a notable absence of long-term performance data under natural aging conditions. To advance the field from empirical trial-and-error toward predictive, knowledge-based design, this review identifies three priority areas for future research: (1) establishing cross-scale “treatment-structure-performance” correlation models that bridge molecular-level modifications to instrument-level acoustic outcomes; (2) developing intelligently engineered surface systems capable of multi-objective synergistic optimization; and (3) creating comprehensive assessment standards that encompass acoustics, durability, and sustainability. By systematically synthesizing current knowledge and identifying critical gaps, this review provides a foundation for more targeted, interdisciplinary research in instrument wood protection. Full article

Serving students with special educational needs (SENs) involves recognising that their learning is closely linked to their emotional needs. Self-esteem and socio-emotional well-being play a key role in their motivation and adaptation to school. In this context, physical activity-based interventions at school emerge as a possible way to strengthen their self-esteem and socio-emotional well-being. The aim of this study was to analyse the effects of a web-based active break programme on self-esteem in students aged 6 to 10 years with SENs and on socio-emotional well-being in the subgroup of first–second-grade students. A pre-specified sub-analysis was conducted of a multicentre randomised controlled trial with a sample of 161 students with special educational needs (7.8 ± 1.1 years, 32% girls), divided into a control group (85 students) and an experimental group (76 students). A programme of video-guided active breaks was implemented in the classroom, applied twice a day, five days a week for 12 weeks, via a web platform. Self-esteem was assessed using the School Self-Esteem Test (SSET), and socio-emotional well-being was assessed using the Self-Report of Socio-Emotional Well-Being (SRSEWB). A significant Time × Group interaction was observed for self-esteem, F_{(1, 157)} = 5.43, p = 0.021, η²_p = 0.033, but no statistically significant effects were detected for socio-emotional well-being. These findings suggest that active break interventions may help strengthen self-esteem in students with SENs. Future research should examine the temporal stability of these improvements, determine the optimal intervention duration required to generate sustained changes, and evaluate longer-term socio-emotional outcomes. Full article

Carbon-Fiber-Reinforced Polyetheretherketone (CFR-PEEK) instrumentation is increasingly preferred in spinal oncology for its physical properties, minimizing imaging artifacts and facilitating precise postoperative radiotherapy planning and tumor surveillance. However, a significant technical limitation exists: the current unavailability of dedicated CFR-PEEK pedicle screws for the cervical spine. The smallest available implants are designed for thoracic use (minimum diameter 4.5 mm, minimum length 25 mm), posing substantial risks of neurovascular injury when applied to smaller cervical pedicles. We present a technical note/feasibility report illustrated by a single case of robot-assisted placement of thoracic CFR-PEEK screws in the cervical spine for the treatment of a C7 Giant Cell Tumor. Following neoadjuvant therapy with Denosumab, a single-stage, two-step circumferential resection and reconstruction was performed. The anterior step was complicated by an iatrogenic injury to the highly adherent left vertebral artery (VA), which was successfully repaired. Consequently, the posterior step required maximal precision to preserve the sole remaining intact VA on the right side. Given the anatomical mismatch between the 4.5 mm thoracic screws and the narrow cervical pedicles (measuring as narrow as 3.2 mm on the critical right side), robotic navigation (ExcelsiusGPS^®) was utilized to plan and execute safe trajectories. Specifically, on the side of the intact VA, a small, controlled medial cortical violation was planned to avoid lateral vascular compromise. The procedure resulted in rigid, artifact-free stabilization with no immediate neurological sequelae. This single-case experience suggests that robotic guidance may facilitate adaptation of thoracic CFR-PEEK instrumentation to the cervical spine in selected oncologic scenarios; reproducibility, costs, and long-term outcomes remain uncertain. Full article

In situ tunnel expansion provides a cost-effective and environmentally sustainable alternative to new tunnel construction. However, staged widening disturbs the lining–rock system, triggering complex, non-monotonic stability responses. This study integrates physical model tests and FLAC3D simulations to investigate the mechanical evolution of a limestone tunnel widened by the Center Diaphragm (CD) method. Seven cross-sections (S1–S7) were fabricated and tested under uniaxial compression with digital image correlation. Results show that the peak load decreases from 385.73 kN in the lined baseline (S1) to 184.14 kN at the first unilateral cut (S3), a 49% reduction, but recovers to 262.28 kN at the left-half closure (S4) before dropping to 128.16 kN at the upper-right excavation (S5). The final relined stage (S7) regains 200.69 kN, a 40% improvement over the unlined enlarged state (S6). Numerical analyses confirm this non-monotonic trajectory in terms of the peak plastic-zone fraction. It reaches at 86.32% in S3, decreases to 74.03% in S4, and rises to 76.43% in S5. The fractions further reach 88.51% in S6 and 87.70% in S7, reflecting the enlarged span and redistributed yielding. Targeted bolting at weak stages S3 and S5 reduced plastic-zone fraction by 14.73 and 4.75 percentage points, and reduced crown settlement by 68% and 41%, respectively. These findings challenge the conventional monotonic degradation assumption, identify S3 and S5 as critical weak links, and validate selective reinforcement for enhancing stability during tunnel expansion. Full article

Freeze–thaw cycles frequently cause damage to canal slopes in cold regions, which has become a potential adverse factor leading to slope failure. This study investigates the coupled thermo-hydro-mechanical (THM) behavior and stability evolution of canal slopes under freeze–thaw cycle conditions through integrated physical model tests and numerical simulations. The evolution processes of temperature distribution, maximum frozen depth, unfrozen water content, deformation, and safety factor of canal slopes were evaluated. The results showed that both the maximum frozen depth and deformation increased continuously within a reasonable service life of 20 years. The maximum deformation concentrated in the middle of the slope, and the maximum unfrozen water content on the slope surface decreased by 0.06. The stability of a canal slope is subject to the dual influences of service time and seasonal variations. Overall, the safety factor decreases with the increase in service time. The safety factor is influenced by the degree of slope freezing. Compared to November, the safety factor in March of the following year increases by 0.15. As slope failure initiates at the slope toe, necessary engineering measures must be implemented at the slope toe in the design of canals to maintain slope stability. This research provides data support for frost damage mitigation and stability assessment of canals in cold regions. Full article