Search Results (2,343)

Deep stormwater drainage tunnels are increasingly being used to mitigate urban flooding, but in-tunnel sediment deposition reduces their discharge capacity and complicates their maintenance. With direct field observation constrained, numerical simulation is essential, and river-based total sediment load formulas require reassessment for use in deep tunnels. The three-phase (air–water–sediment) CFD solver SedInterFoam is first validated against a benchmark open-channel suspended sediment experiment, and is then applied to a horseshoe tunnel under a fixed design discharge for multiple inlet sediment concentrations spanning urban stormwater conditions. Four classical formulas (Yang, Shen–Hung, Ackers–White, Engelund–Hansen) are evaluated at the CFD-resolved hydraulic state; Toffaleti is omitted because its zone-based formulation is incompatible with the partially filled horseshoe geometry. The CFD consistently shows persistent retention of a substantial fraction of the inlet sediment load, whereas the transport capacity-limited interpretation of the classical formulas predicts near-complete sediment throughput—indicating structural inadequacy for the dilute, supply-limited regime typical of urban stormwater. A Universal Soil Loss Equation (USLE)-style dimensionless deposition formula is therefore proposed, with inlet sediment loading as the explicit independent variable and a tunnel correction factor 𝐾_tunnel absorbing the geometric, hydraulic, and sediment variations. Its regression yields an almost linear scaling and a nearly constant deposition ratio, while analysis of the internal flow and concentration fields shows that the retained sediment is strongly concentrated near the bed and that near-bed turbulent mixing weakens moderately with a rising inlet concentration. While calibrated for a single non-cohesive settleable sand fraction, the framework provides a transferable basis for inlet-loading-dependent deposition prediction in deep stormwater drainage tunnels, and subsequent extension of 𝐾_tunnel to broader sediment conditions with field-based validation is expected to enable maintenance planning, dredging volume estimation, and sediment retention risk assessment. Full article

Background/Objectives: San-Huang-Xie-Xin-Tang (SHXXT) is a classical traditional Chinese herbal formula composed of Coptis chinensis, Scutellaria baicalensis, and Rheum palmatum, with documented anti-inflammatory and anticancer properties. Despite growing interest in its pharmacological potential, systematic evaluation of its gene regulatory effects across multiple cancer types remains limited. This study aimed to assess the prognostic relevance of SHXXT-regulated genes across pan-cancer contexts using publicly available transcriptomic and clinical datasets. Methods: Fifteen active compounds of SHXXT were identified from traditional Chinese medicine databases (Encyclopaedia of Traditional Chinese Medicine (ETCM) 2.0, Chinese Compound Medicine Database (ccTCM), and Integrated Traditional Chinese Medicine Database (ITCM)). Compound-induced gene expression profiles were obtained from MCF7-based transcriptomic perturbation data in the ITCM database and integrated with The Cancer Genome Atlas (TCGA) across 24 cancer types. Survival-associated genes were evaluated using Cox proportional hazards regression and Kaplan–Meier analysis. A weighted prognostic scoring framework, supported by normalization and sensitivity analyses, was developed to prioritize cancer types according to the concordance between SHXXT-induced gene regulation and favorable prognostic patterns. Functional enrichment analysis was performed using Annotation, Visualization, and Integrated Discovery (DAVID), and cancer-related genes were annotated using the OncoKB database. Complementary in vitro studies, including Annexin V/propidium iodide (PI) and MT-1 staining assays, were conducted in Hep3B cells using a Good Manufacturing Practice (GMP)-certified commercial SHXXT preparation. Results: SHXXT-regulated genes were significantly enriched in cancer-related pathways, particularly the PI3K–Akt and MAPK signaling pathways. Pan-cancer analysis revealed substantial heterogeneity in prognostic alignment across cancer types. Among the 24 cancer cohorts analyzed, kidney renal clear cell carcinoma (KIRC) achieved the highest prognostic alignment score within the proposed framework. In KIRC, several genes, including PIK3CA, PIK3CB, KRAS, and RAF1, remained significantly associated with favorable prognostic alignment after multivariable adjustment. Pathway enrichment analysis further identified PI3K–Akt and MAPK signaling as the most significantly represented pathways among favorably aligned genes. In contrast, hepatocellular carcinoma exhibited a relatively low prognostic alignment score, consistent with in vitro observations indicating predominantly non-selective cytotoxic stress rather than cancer-specific therapeutic activity. Conclusions: SHXXT-regulated genes exhibited marked heterogeneity across cancer types, with KIRC was consistently prioritized as the top-ranked cancer type across multiple analytical scenarios, suggesting a strong concordance between SHXXT-associated gene regulation and favorable prognostic signatures. These findings represent computational predictions derived from transcriptomic and survival associations rather than direct evidence of therapeutic efficacy. The study provides a reproducible pan-cancer strategy for prioritizing candidate cancer types for future mechanistic and experimental validation of traditional Chinese medicine formulations. Full article

Landslides are the most common geological hazards, and chemical reinforcement is an effective method for enhancing the stability of soil slopes. Based on the coupled Eulerian–Lagrangian method, finite element analyses were conducted to develop a simple design approach for soil slope reinforcement using the curing agent. First, the effects of internal friction angle, cohesion, soil unit weight, slope height and angle on the slope stability were systematically quantified through 93 numerical cases. On this basis, an empirical formula was established for the factor of safety (FOS) of soil slope, and a method for determining the failure mode was proposed using a dimensionless parameter and two critical values related to slope angle. Subsequently, the reinforcement performance of the SH curing agent was investigated by varying the reinforcement position and length. The results indicate that the reinforcement of Case I-II-III and Case I-II provide the best performance, and the optimum reinforcement length was determined for different slope conditions. For slope angles ranging from 25° to 65°, the FOS after reinforcement was found to increase by 12.1% to 18.8% compared with that before reinforcement. Based on the FE results, empirical formulae for predicting the FOS of reinforced slope were further developed. Finally, a simple design approach was proposed for soil slope reinforcement with curing agent. The proposed method provides a convenient and effective reference for engineering practice in soil slope reinforcement with curing agents. Full article

The blasting-induced environmental impact of tunneling is a major concern in drill and blast excavation practice, particularly in urban areas. The present paper carries out comprehensive numerical modeling to study the vibration attenuation at the soil surface away from the blasting source as well as the resulting interactions between a historical structure and the surrounding soil, with particular attention to the effects of a millisecond delay. Special attention is given to the interpretation of the role of the local site effects in terms of the frequency-dependent changes of the vibration attenuation mechanism and the response of the historical structure. The velocity responses along the ground surface generally exhibit higher-frequency suppression and low-frequency amplification for both instantaneous blasting and millisecond delay blasting cases in the layered soil–rock site. The millisecond delay blasting can effectively avoid excessive vibration velocity and thus reduce the vibration amplitude at the ground surface by 60–70% (compared with instantaneous blasting), with the predominant frequency mainly concentrated in the high frequence band of 400–500 Hz. The empirical formulae for predicting the vibration attenuation along the scale distance in a soil–rock site has been proposed for both instantaneous blasting and millisecond delay blasting. Through the HHT spectral analyses of the velocity response of the historical structure, it is seen that the difference of structure properties between the wood-frame tower and the base masonry structure has a remarkable influence on the structural vibration. The numerical results can provide a reliable reference for the practical blasting scheme and the systematic study of the dynamic responses of historical structures subjected to blasting-induced vibrations. Full article

The desert bottomland of Northern Shaanxi, China, features an ecologically fragile environment with a pronounced mismatch between abundant coal resources and scarce water resources. Large-scale coal mining often impairs the water-resisting capacity of overlying strata, leading to shallow groundwater depletion, surface drought, and vegetation degradation. This study focuses on determining the height of the water-conducting fractured zone (WCFZ) and assessing shallow groundwater loss in such ecologically sensitive mining areas. Through analysis of measured WCFZ heights, the empirical formulas currently specified in national codes are found to be inapplicable to the study area. A multi-factor nonlinear prediction model, better suited to local conditions, is therefore established using multiple nonlinear regressions. Taking the Jinjitan Coal Mine as a case study, a 3D hydrogeological conceptual model is developed using FEFLOW to simulate phreatic water responses to mining activities. The results indicate a maximum phreatic water drawdown of 3–4 m, with post-mining burial depths predominantly ranging from 5 to 8 m, reaching a warning level that requires attention and mitigation. This study provides a valuable reference for water hazard prevention and ecological protection in desert bottomland regions. Full article

Background: Acute myocardial infarction (AMI) remains the most lethal critical emergency worldwide. Although Angong Niuhuang Pill (ANP) is an established rescue medicine that has demonstrated outstanding therapeutic potential for cardiovascular diseases, its modern molecular mechanism has never been systematically elucidated because of its chemical complexity and unidentified targets. Methods: This study utilizes a multi-layer analytical pipeline of AI mining, network pharmacology, transcriptomics, and experimental confirmation. The components of ANP were comprehensively identified by UHPLC-Q Exactive Orbitrap HRMS. The TranSiGen algorithm was utilized to deeply mine the data and rank the components according to their relevance to AMI. The top 20 components were selected as prior weights and introduced into network pharmacology for analysis. Subsequently, a mouse model of AMI was established by ligating the left coronary artery. Cardiac function in the mice was evaluated by echocardiography and serum biochemical indicators. The pathological changes in the heart tissue were assessed by hematoxylin-eosin (H&E) and Masson staining. Cardiac transcriptome sequencing was performed, and pathway enrichment was analyzed by KEGG. The key pathways were verified by qPCR and immunofluorescence, achieving cross-validation between AI prediction and experimental findings. Results: The identification of ANP resulted in the detection of a total of 73 compounds, and the TranSiGen algorithm was employed to prioritize these compounds, yielding a ranked list of the top 20 candidates. Functional evaluation using echocardiography, serum biochemical markers, and histopathological examination demonstrated that ANP significantly ameliorated cardiac function in mice following myocardial infarction. Integration of network pharmacology and transcriptomic enrichment identified convergent axes of IL-17 signaling and mitochondrial quality control, which were subsequently experimentally validated as mechanisms by which ANP ameliorated cardiac injury. Experimental validation confirmed that ANP downregulated protein expression of IL-17A and TNF-α, normalized PINK1 and LC3-II/LC3-I marker profiles, with concomitant p62 reduction, thereby providing comprehensive molecular evidence at both transcriptional and translational levels to support the AI-driven predictions. Conclusions: This study identified IL-17 signaling and mitochondrial quality control as pathway axes associated with ANP-mediated cardioprotection against AMI, supported by AI-driven compound screening, transcriptome-network cross-validation, and experimental confirmation. This analytical framework may be adaptable to other complex TCM formulas for mechanism exploration and clinical translation. Full article

Background: Accurate endotracheal tube (ETT) insertion depth is critical in infants and young children, where tracheal malposition carries significant risk. Formula-based depth estimation is widely used at the bedside, but the performance of published formulas in children under two years of age admitted to a general PICU remains poorly characterized. Methods: A retrospective, single-center study was conducted at the PICU of King Saud Medical City, Riyadh. A total of 115 patients aged 1–24 months requiring orotracheal intubation were included. ETT depth was predicted using five established formulas: height-based [(H/10)+5], weight-based [W+6], ETT size-based [ETT×3], Lee weight-based [5.5+0.5W], and Lee height-based [3+0.1H]. Agreement between predicted and radiographically confirmed insertion depth was assessed using Lin’s concordance correlation coefficient (CCC), Bland–Altman analysis, and clinical classification of predictions. Results: None of the five formulas achieved acceptable concordance (CCC < 0.75 for all). The height-based formula performed best among published formulas, with negligible bias and the highest proportion of clinically acceptable predictions. Both Lee formulas showed near-universal systematic underestimation and are not suitable for this age group. Over half of all intubations resulted in non-ideal ETT position on the first post-intubation chest X-ray. Novel cohort-derived regression equations outperformed all published formulas, with the weight-based equation (Depth = 0.385 × Weight + 9.145) emerging as the strongest predictor of insertion depth. Conclusions: No published formula achieved reliable concordance with radiographic ETT depth in children aged 1–24 months. The cohort-derived weight-based formula represents a more accurate bedside tool for this population and warrants prospective external validation. Post-intubation radiographic verification remains essential. Full article

Self-drilling hollow bar micropiles (HBMPs), which integrate drilling, grouting, and reinforcement into a single process, have broad application prospects in mountainous transmission lines and offshore wind power projects. However, existing research has focused mainly on friction piles in soil layers, and there is a lack of systematic understanding of the load-transfer mechanism and bearing capacity calculation method for rock-socketed HBMPs. Based on field static load tests of rock-socketed HBMPs, this study systematically investigates the vertical bearing behavior and capacity calculation method of single rock-socketed HBMPs through a combination of test data analysis, finite element numerical simulation, and theoretical analysis. The field test results show that the load-settlement curves of rock-socketed HBMPs are of a slowly varying type, exhibiting mixed friction-end-bearing characteristics. After data screening, the average Q-s curve of Pile No. 1 and Pile No. 5 was taken as the benchmark, and the representative ultimate bearing capacity of a single pile determined by the 40 mm settlement criterion is 5860 kN. The test data of Pile No. 3 and Pile No. 4 were retained as independent validation data. A three-dimensional finite element model considering the cohesive contact behavior at the pile–rock/soil interface was established using ABAQUS. After calibration with the test results, the error between the simulated and measured bearing capacity is −3.4%, demonstrating good model reliability. Parametric analysis indicates that the bearing capacity increases linearly with the grouting volume increase rate $V_{\mathrm{inc}}$, with the expansion effect being the main enhancement mechanism; the improvement amplitude under hard rock conditions is significantly smaller than that in cohesive soils. The effect of uniaxial compressive strength $q_u$ of hard rock on bearing capacity is negligible because the capacity is controlled by the pile–rock interface shear strength. The bearing capacity increases approximately linearly with the rock-socketed depth $L_r$, and a minimum rock-socketed depth of 1.0 m is recommended. Analysis of the load-transfer mechanism shows that rock-socketed HBMPs rely mainly on shaft resistance (accounting for 90.6%), and the axial force decays significantly along the pile length. Elastic compression of the pile accounts for 78% of the pile head settlement, and the limited displacement at the pile tip leads to insufficient mobilization of end bearing. A modified bearing capacity formula considering the grouting expansion effect is established with shaft resistance as the core. A hierarchical validation strategy is adopted to test its predictive ability: for the finite element cases not participating in parameter calibration, the prediction error is within ±2%; for the field test piles, the prediction error is +7.9%; and for Pile No. 3 and Pile No. 4, the errors are +1.7% and −2.1%, respectively. These values are significantly better than those of existing methods (errors ranging from −72.1% to +54.5%). The research results can provide a theoretical basis for the design of single HBMP bearing capacity under rock-socketed conditions. Full article

This study addresses the challenge of modeling the complex non-linear relationship between process parameters and relative density in selective laser melting (SLM) of IN718 nickel-based superalloy under small-sample conditions. A data-driven prediction framework integrating data augmentation, physics-informed feature engineering, machine learning, and model interpretability analysis was developed and systematically validated. Fourteen sets of experimental data covering both vertical and horizontal building directions were collected by varying laser power (P), scan speed (v), and hatch spacing (h). To overcome the small-sample limitation, three augmentation strategies—radial basis function (RBF) interpolation, generative adversarial network (GAN), and K-nearest neighbors (KNN)—were systematically compared under unified physical constraints combining local perturbation and volumetric energy density (E_vol) filtering, with Pearson correlation coefficient consistency used to select the optimal strategy. Eight physically meaningful input features were constructed, including E_vol and line energy density (E_line), explicitly embedding SLM process physics into the learning framework. Support vector regression (SVR), random forest (RF), and artificial neural network (ANN) models were trained and their hyperparameters were systematically optimized via exhaustive grid search combined with leave-one-out cross-validation (LOO-CV), ensuring robust model selection under small-sample constraints. A physics-based baseline model (E_vol quadratic fitting, LOO-CV average R² = 0.2534) was established to quantify the gain of machine learning over empirical formulas. LOO-CV results show that ANN achieves the highest average R² of 0.9269, followed by SVR (0.9148) and RF (0.8393), all of which substantially outperform the physical baseline. Feature importance analysis reveals that E_vol accounts for 51.58% of the predictive power, and ablation experiments confirm that introducing physics-derived features improves the average R² by 0.0246 compared with raw process parameters alone. To further elucidate the predictive mechanism of the optimal ANN model, Partial Dependence Plot (PDP) analysis was conducted for all eight input features, visualizing their marginal effects on predicted density and confirming physical consistency with SLM mechanisms. This framework provides a reliable, interpretable, data-driven solution for intelligent SLM process optimization with limited experimental data. Full article

Background/Objectives: Canine athletes have a higher energy requirement and are more susceptible to nutrient depletion, electrolyte imbalance, and metabolic stress than sedentary pets. The objective of this study was to characterize the plasma metabolome of American Foxhound dogs following a bout of unstructured exercise. Methods: Thirty-nine adult American Foxhound dogs (32 intact males, 7 spayed females; age: 6.2 ± 3.1 yr; BW: 36.3 ± 5.3 kg) were allotted to a standard performance diet (CTRL) or NUTRO^® Natural Choice^® Adult High Endurance Formula (TEST). After 80 d in the study, blood samples were collected prior to (0 h), and 3 h and 25 h post-exercise (average: 17.7 km run over 2–3 h). Plasma samples of the 10 top performers of each treatment group were analyzed for untargeted metabolite profiling. Results: Of the 566 named metabolites identified, >200 and >185 metabolites were impacted (p < 0.05) by exercise and diet, respectively. Principal component analysis indicated distinct clustering by diet. Random forest analysis highlighted several metabolites having a high degree of predictive accuracy based on diet and exercise, with most related to amino acid, lipid, xenobiotic, and cofactor and vitamin metabolism. Relating to exercise, glycolytic end-products and citric acid cycle intermediates were increased at 3 h post-exercise. Similarly, tocopherols and omega-3 polyunsaturated fatty acids were higher in dogs fed TEST than those fed CTRL during recovery, indicating a lower oxidative stress and anti-inflammatory response. Conclusions: Overall, the data suggest a protective effect (lower susceptibility to oxidative stress and muscle fatigue) of feeding a nutrient-fortified diet for dogs undergoing unstructured exercise. Full article

Accurate wind estimation is essential for wind resource assessment. In this study, using scanning lidar measurements and high-resolution WRF simulations from two nearshore areas in Japan, we developed two extensions of the Temporal Correction (TC) method, which corrects wind fields generated by the Weather Research and Forecasting (WRF) model using on-site measurements. First, when using a single measurement point for correction, we derived two empirical formulas to predict appropriate correction coefficients based on reference–target correlation coefficients of wind speed obtained from WRF simulations and developed a method (TC-pred) using these formulas. TC-pred was shown to have higher wind speed estimation accuracy and a broader range of applicability than the conventional TC method. Next, we extended the TC-pred method to allow the use of multiple measurement points as references by introducing a weighting formula for each reference point. Wind speed estimation accuracy improved as the number of reference points increased, primarily because the probability of including reference points with high reference–target correlation coefficients increased. This suggests that it is effective for the suppression of wind estimation uncertainty to determine measurement layout such that the correlation coefficient between at least one reference point and each target point in the target area exceeds a certain value. Full article

In this study, the stability, electronic, structural, and fracture toughness, and mechanical properties of the Half-Heusler(HH) alloys MnCoSb, MnCoAs, MnCoP, and MnNiSb were comprehensively investigated using first-principles calculations based on density functional theory (DFT). The calculated results reveal that all four alloys exhibit half-metallic characteristics, characterized by the presence of a substantial band gap in the spin-down channel. The phonon spectra and negative formation energies confirm that these alloys possess both dynamic and thermodynamic stability. The Born criteria further validate the structural stability in terms of mechanical properties. Three-dimensional representations of the Young’s modulus, bulk modulus, and shear modulus for the four alloys indicate that MnCoP exhibits the most pronounced anisotropy. The overall fracture toughness of the alloys ranges from 1.58 MPa·m^1/2 to 2.63 MPa·m^1/2, which falls within the typical range for half-metallic materials, albeit at the lower end, attributable to the relatively ductile nature of the four alloys. Although the two methods yield different absolute values, the explicit crack model (Method I) is considered more reliable for anisotropic systems because it directly simulates crack propagation and accounts for local relaxations, while the empirical formula (Method II) provides a useful reference for high-throughput screening. Among the alloys, MnCoSb demonstrates a superior mechanical performance, with K_IC values of 2.63 MPa·m^1/2 and 1.58 MPa·m^1/2 and brittleness indices M of 8.97 and 14.94, indicating excellent damage tolerance compared to the other three alloys. In contrast, MnCoP exhibits higher brittleness and lower mechanical reliability, with K_IC values of 2.00 MPa·m^1/2 and 1.63 MPa·m^1/2 and higher M values of 13.83 and 16.99. This study provides quantitative predictions of fracture toughness and establishes a relationship between microscopic and mechanical properties. These findings offer a theoretical foundation for the application of damage-tolerant HH alloys in fields such as spintronics and magnetism. Full article

Various hydraulic automatic gates play an important role in water resources regulation. This study proposes a novel suspended hydraulic automatic control gate for tidal marine energy generation with adaptive one-sided flow-through characteristics. To evaluate its hydraulic performance and regulation mechanism, model experiments were conducted in a laboratory flume under different upstream and downstream water levels and discharge conditions. Gate opening states, hydraulic parameters, and flow field structures were obtained, while computational fluid dynamics simulations were used to reproduce and analyze the experimental flow field. The results show that the gate opening angle and water level jointly control the discharge capacity, and significant differences exist in the flow structure and discharge behavior between free and submerged outflow conditions. The numerical model further reveals vortex structures, velocity stratification, and gas–liquid two-phase distributions near the gate. Variations in gate structural parameters, discharge, and downstream water level significantly affect moment equilibrium, flow regime, and discharge capacity. The proposed discharge formula effectively predicts variations in gate flow and force characteristics under different hydraulic conditions, showing good applicability and engineering value. The suspended hydraulic automatic control gate has a simple structure, strong adaptability, and promising potential for tidal water regulation and engineering applications. Full article

High-order numerical methods are essential for achieving predictive fidelity in modern computational fluid dynamics, yet many existing schemes face significant trade-offs between accuracy, robustness, and computational efficiency. This study introduces the Compact-Corrected MUSCL (CCMUSCL) scheme, a novel framework that enhances the traditional MUSCL approach by incorporating localized information from high-order, compact finite-difference formulas. Unlike classical compact schemes that require solving global linear systems, this method applies corrections locally to the MUSCL flux. This strategy allows the scheme to maintain spectral-like resolution while preserving the robustness and locality of the original MUSCL framework. The performance of CCMUSCL is evaluated using a series of rigorous 1D and 2D benchmark cases. Numerical results demonstrate that CCMUSCL achieves accuracy comparable to or exceeding that of traditional high-order WENO schemes, particularly in resolving intricate, small-scale flow structures and sharp discontinuities. Furthermore, efficiency analysis reveals that CCMUSCL is significantly more cost-effective than WENO, requiring substantially fewer arithmetic operations in 1D and offering an even more pronounced reduction in operations for 3D flux evaluations. By offering a tunable balance between robustness and accuracy through the use of the van Albada limiter as a localized indicator, the CCMUSCL scheme provides a highly efficient and flexible alternative for large-scale high-speed flow simulations. Full article

Today, billions of bottles are aging in the cellars of traditional-method sparkling wine regions prior to their release on the market. Given the fundamental role of carbon dioxide (CO₂) in both the production and sensory perception of sparkling wines, it is essential to understand and control all stages that influence its pressure and concentration in the bottle throughout the winemaking process. This study addressed the central question of how long traditional-method sparkling wine bottles can age in cellars while maintaining sufficient CO₂ pressure. By considering their capacity to retain the minimum CO₂ pressure of 3.5 bar at 20 °C, as required by European regulations, a predictive formula for the shelf life of older vintages was proposed and discussed, integrating the multiple relevant parameters that govern CO₂ retention. Moreover, based on previously published datasets, a comparison was carried out between CO₂ losses measured for a range of modern crown caps and those observed in collections of older champagne vintages sealed with cork-lined crown caps. The results clearly show that modern crown caps preserve dissolved CO₂ far more effectively in traditional-method sparkling wines than the cork-lined closures commonly used during the last century, leading to substantially longer predicted shelf lives. Full article