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In seasonal frozen regions, asphalt pavements face accelerated degradation due to extreme environmental stressors-including cyclic freeze-thaw transitions and intense ultraviolet radiation-that induce severe thermo-oxidative and UV aging effects. These compounded aging mechanisms lead to premature cracking, raveling, and functional failure of road surfaces, imposing significant economic burdens on infrastructure maintenance. To address this critical challenge, this study systematically investigates the alterations in the rheological properties of AH-90 base asphalt, SBR-modified asphalt, and SBS-modified asphalt under natural aging conditions over varying time intervals using temperature sweep tests, bending beam rheometer tests, and multi-stress creep recovery tests. The influence of natural weather conditions on the microstructure of asphalt binders was examined by Fourier transform infrared spectroscopy and fluorescence microscopy before and after different nature aging conditions. The findings demonstrate that the use of modifiers can modify the natural aging characteristics of asphalt binders. Compared to BA, SBS demonstrates superior resilience to natural aging, while SBR is more susceptible to aging. After natural aging, the stiffness modulus of BA, SBS, and SBR increased by 21%, 10%, and 39% respectively. T30 (The temperature at which the limiting phase angles grades reaches 30°) exhibits a robust association with the intrinsic aging features of asphalt binders, facilitating the assessment of natural aging impacts on asphalt qualities. Throughout natural aging, the modifier deteriorates due to the oxidation of the unsaturated polybutadiene component by chain scission, while SBS exhibits a more stable phase structure than SBR during the aging process.

To investigate the damage mechanisms in granite’s physical and mechanical properties after high-temperature water quenching, this study employed MTS815.04 for uniaxial compression tests on thermally treated specimens, with concurrent acoustic emission monitoring, and utilized nanoindentation for micromechanical analysis. The results show that with increasing temperature, granite's peak strength and elastic modulus decrease, with a sharp decline after 400–500 °C, corresponding to a significant increase in the internal damage, which can be detected by acoustic emission monitoring. Below 500 °C, macroscopic mechanical degradation is due to mineral thermophysical property differences, while above 500 °C, microcrack development is the main deterioration factor. The failure mode shifts from tensile to tensile-shear complex to shear failure, with transition points at 400 °C and 800 °C. The results of this study are of certain reference value for improving the efficiency of extracting thermal energy from dry-hot rocks and providing security guidance for the tunnel restoration process following fire damage.

The advantages of asphalt pavement in terms of driving comfort, construction efficiency, and ease of maintenance have established it as the predominant choice for high-grade pavements at present. However, being highly sensitive to temperature and stress, asphalt performance is significantly influenced by external environmental conditions and loading, making it susceptible to various distress phenomena. Particularly in high-latitude regions, asphalt pavement cracking severely limits asphalt pavement’s functional performance and service lifespan under cold climatic conditions. To enhance the low-temperature cracking resistance of asphalt pavement in cold regions, tools such as VOS viewer 1.6.20 and Connected Papers were utilized to systematically organize, analyze, and summarize relevant research from the past 40 years. The results reveal that temperature shrinkage cracks and thermal fatigue cracks represent the primary forms of asphalt pavement distress in these regions. Cracking in asphalt pavement in cold regions is primarily influenced by structural design, pavement materials, construction technology, and climatic conditions. Among these factors, surface layer stiffness, base layer type, and the rate of temperature decrease exert the most significant impact on cracking resistance, collectively accounting for approximately 45.4% of all cracking-related factors. The low-temperature performance of asphalt pavement can be effectively improved through several strategies, including adopting full-thickness asphalt pavement with a skeleton-dense structure or reduced average particle size, incorporating functional layers, appropriately increasing the thickness of the upper layer and the compaction temperature of the lower layer, utilizing continuous surface layer construction techniques, and applying advanced materials. High-performance modifiers such as SBR and SBS, nanomaterials with good low-temperature performance, and warm mixing processes designed for cold regions have proven particularly effective. Among various improvement methods, asphalt modification has demonstrated superior effectiveness in enhancing the deformation capacity of asphalt and its mixtures, significantly boosting the low-temperature performance of asphalt pavements. Asphalt modification accounts for approximately 50% of the improvement methods evaluated in this study, with an average improvement in low-temperature performance reaching up to 143%. This paper provides valuable insights into the underlying causes of cracking distress in asphalt pavements in cold regions and offers essential guidance for improving the service quality of such pavements in these challenging environments.

This study explores how aristolochic acid I (AAI) drives hepatocellular carcinoma (HCC). We first employ network toxicology and machine learning to map the key molecular target genes. Next, our research utilizes molecular docking to evaluate how AAI binds to these targets, and finally confirms the stability and dynamics of the resulting complexes through molecular dynamics simulations. We identified 193 overlapping target genes between AAI and HCC through databases such as PubChem, OMIM, and ChEMBL. Machine learning algorithms (SVM-RFE, random forest, and LASSO regression) were employed to screen 11 core genes. LASSO serves as a rapid dimension-reduction tool, SVM-RFE recursively eliminates the features with the smallest weights, and Random Forest achieves ensemble learning through decision trees. Protein–protein interaction networks were constructed using Cytoscape 3.9.1, and key genes were validated through GO and KEGG enrichment analyses, an immune infiltration analysis, a drug sensitivity analysis, and a survival analysis. Molecular-docking experiments showed that AAI binds to each of the core targets with a binding affinity stronger than −5 kcal mol−1, and subsequent molecular dynamics simulations verified that these complexes remain stable over time. This study determined the potential molecular mechanisms underlying AAI-induced HCC and identified key genes (CYP1A2, ESR1, and AURKA) as potential therapeutic targets, providing valuable insights for developing targeted strategies to mitigate the health risks associated with AAI exposure.

The quantity, size, and distribution of non-metallic inclusions in High-Strength Low-Alloy (HSLA) steel critically influence its service performance. Conventional detection methods often fail to adequately characterize extreme inclusion distributions in large-section components. This study developed an integrated full-process inclusion analysis system combining high-precision motion control, parallel optical imaging, and laser spectral analysis technologies to achieve rapid and automated identification and compositional analysis of inclusions in meter-scale samples. Through systematic investigation across the industrial process chain—from a dia. 740 mm consumable electrode to a dia. 810 mm electroslag remelting (ESR) ingot and finally to a dia. 400 mm forged billet—key process-specific insights were obtained. The results revealed the effective removal of Type D (globular oxides) inclusions during ESR, with their counts reducing from over 8000 in the electrode to approximately 4000–7000 in the ingot. Concurrently, the mechanism underlying the pronounced enrichment of Type C (silicates) in the ingot tail was elucidated, showing a nearly fourfold increase to 1767 compared to the ingot head, attributed to terminal solidification segregation and flotation dynamics. Subsequent forging further demonstrated exceptional refinement and dispersion of all inclusion types. The billet tail achieved exceptionally high purity, with counts of all inclusion types dropping to extremely low levels (e.g., Types A, B, and C were nearly eliminated), representing a reduction of approximately one order of magnitude. Based on these findings, enhanced process strategies were proposed, including shallow molten pool control, slag system optimization, and multi-dimensional quality monitoring. An intelligent analysis framework integrating a YOLOv11 detection model with spectral feedback was also established. This work provides crucial process knowledge and technological support for achieving the quality control objective of “known and controllable defects” in HSLA steel.

Sepsis is a multisystem disease characterized by dysregulation of the host immune response to infection. Immune response kinetics play a crucial role in the pathogenesis and progression of sepsis. Macrophages, which are known for their heterogeneity and plasticity, actively participate in the immune response during sepsis. These cells are influenced by the ever-changing immune microenvironment and exhibit two-sided immune regulation. Recently, the immunomodulatory function of mesenchymal stem cells (MSCs) in sepsis has garnered significant attention. The immune microenvironment can profoundly impact MSCs, prompting them to exhibit dual immunomodulatory functions akin to a double-edged sword. This discovery holds great importance for understanding sepsis progression and devising effective treatment strategies. Importantly, there is a close interrelationship between macrophages and MSCs, characterized by the fact that during sepsis, these two cell types interact and cooperate to regulate inflammatory processes. This review summarizes the plasticity of macrophages and MSCs within the immune microenvironment during sepsis, as well as the intricate crosstalk between them. This remains an important concern for the future use of these cells for immunomodulatory treatments in the clinic.

Adipose-derived mesenchymal stem cells (ADSCs) are promising candidates for mesenchymal stem cell (MSC) therapy due to their ease of isolation from the stromal vascular fraction (SVF) of adipose tissue. However, traditional isolation methods often result in mouse ADSCs with low purity and significant heterogeneity contributing to inconsistencies in results from preclinical and clinical studies. This is partly attributed to the lack of consensus on their surface markers. This study compared three purification methods for isolating mouse ADSCs based on Sca-1 positivity-direct adherence (ADSC-A), magnetic cell sorting followed by adherence (ADSC-M), and adherence to the third generation followed by magnetic cell sorting (ADSC-AM). Third-generation ADSCs were evaluated for proliferative activity, differentiation potential, and functional enrichment using proliferation assays, trilineage differentiation assays, and RNA sequencing. Flow cytometry was employed to assess Sca-1 positivity and the expression of positive (CD44, CD90, CD29) and negative markers (CD31, CD45) in the fourth-generation ADSCs. Among the three methods, ADSC-AM exhibited superior properties, including uniform morphology, enhanced proliferation, and over 95% expression of Sca-1 and CD29. While all methods supported trilineage differentiation, ADSC-AM demonstrated enhanced adipogenesis. Furthermore, RNA sequencing and pathway enrichment analysis revealed that ADSC-AM possessed unique potential in angiogenesis and immune regulation. These findings suggest that the ADSC-AM method offers a simple and reproducible approach for obtaining high-purity mouse ADSCs with better functional properties and provide a fundamental reference for understanding mouse ADSCs surface marker profiles.

Discrete multiple-cavity models coupled with quasi-two-dimensional (quasi-2D) friction models are effective solutions to simulating transient cavitation pipe flows. The simulation accuracy of such models hinges upon the understanding of key parameters of the models, which remains elusive so far. To address such an open issue, this paper employs the discrete vapor cavity model (DVCM) and the discrete gas cavity model (DGCM), combined with the quasi-2D friction model, with a particular focus on revealing the sensitivity of these models to the key parameters such as grid number and weighting parameters. Based on the quantitative analysis and pressure fluctuation history, a method is developed to evaluate the accuracy of numerical results. Results show that the inclusion of the quasi-2D friction model improves the accuracy of predicting time of cavity formation and collapse; however, it does not affect the selection of grid number. Meanwhile, numerical results are sensitive to the weighting parameter of the viscous term in the quasi-2D friction model except for the case of low-intensity cavitation and its value of 1 is suggested for all cases. From the practical point of view, our finding is helpful to understand the feature of discrete multiple-cavity models and improve the simulating accuracy of transient cavitation pipe flows.

The foaming process effectively reduces the viscosity of asphalt, thereby lowering energy consumption during mixture construction. However, conventional foamed asphalt production depends on specialized equipment and strict control of foaming conditions. Incorporating additives that contain water of crystallization to induce micro-foaming in asphalt presents a promising alternative. In this study, three highly crystalline hydrates, namely KAl(SO4)2 · 12H2O, Na2CO3 · 10H2O, and Na2HPO4 · 12H2O, were introduced into base asphalt to achieve micro-foaming. The effects of the micro-foaming process on the physical properties and chemical structure of asphalt were evaluated through ductility, penetration, softening point, viscosity, and Fourier-transform infrared spectroscopy (FTIR). Additionally, dynamic shear rheometer (DSR) and bending beam rheometer (BBR) were conducted to assess the evolution of viscosity, moisture content, high- and low-temperature performance, and morphological characteristics of micro-foamed asphalt over the foaming period. The results shows that the optimal dosages of KAl(SO4)2 · 12H2O, Na2CO3 · 10H2O, and Na2HPO4 · 12H2O are 3%, 5%, and 1%, respectively, achieving viscosity reduction rates ranging from 9.92% to 14.62%. Compared to mechanically foamed asphalt, the micro-foamed asphalt exhibited improved physical properties, including an approximately 40% increase in low-temperature ductility and a 60% enhancement in viscosity-reduction stability. Relative to conventional warm-mix processes, the micro-foamed asphalt showed improvements of approximately 141% in fatigue resistance and 215% in cracking resistance. The viscosity-reducing effect remained above 70% for up to 2 h, while moisture content decreased exponentially during micro-foaming, with the final residual water content below 0.05%. Furthermore, a strong linear correlation was observed between apparent and internal bubble sizes, whereas the apparent bubble density exhibited a logarithmic relationship with internal bubble density. These findings demonstrate that the internal foaming state can be effectively characterized by analyzing the apparent bubble parameters of micro-foamed asphalt.

Plain concrete specimens and FRP(Fiber Reinforced Polymer)-reinforced concrete specimens were fabricated to investigate concrete’s mechanical and surface degradation behaviors reinforced with carbon, basalt, glass, and aramid fiber-reinforced polymer under coupled sulfuric acid and freeze–thaw cycles. The compressive strength of fully wrapped FRP cylindrical specimens and the flexural load capacity of prismatic specimens with FRP reinforced to the pre-cracked surface, along with the dynamic elastic modulus and mass loss, were evaluated before and after acid–freeze cycles. The degradation mechanism of the specimens was elucidated through analysis of surface morphological changes captured in photographs, scanning electron microscopy (SEM) observations, and energy-dispersive spectroscopy (EDS) data. The experimental results revealed that after 50 cycles of coupled acid–freeze erosion, the plain cylindrical concrete specimens showed a mass gain of 0.01 kg. In contrast, after 100 cycles, a significant mass loss of 0.082 kg was recorded. The FRP-reinforced specimens initially demonstrated mass loss trends comparable to those of the plain concrete specimens. However, in the later stages, the FRP confinement effectively mitigated the surface spalling of the concrete, leading to a reversal in mass loss and subsequent mass gain. Notably, the GFRP(Glassfiber Reinforced Polymer)-reinforced specimens exhibited the most significant mass gain of 1.653%. During the initial 50 cycles of acid–freeze erosion, the prismatic and cylindrical specimens demonstrated comparable degradation patterns. However, in the subsequent stages, FRP reduced the exposed surface area-to-volume ratio of the specimens in contact with the acid solution, resulting in a marked improvement in their structural integrity. After 100 cycles of acid–freeze erosion, the compressive strength loss rate and flexural load capacity loss rate followed the ascending order: CFRP-reinforced < BFRP(Basalt Fiber Reinforced Polymer)-reinforced < AFRP(Aramid Fiber Reinforced Polymer)-reinforced < GFRP-reinforced < plain specimens. Conversely, the ductility ranking from highest to lowest was AFRP/GFRP > control group > BFRP/CFRP. A probabilistic analysis model was established to complement the experimental findings, encompassing the quantification of hazard levels and reliability indices.