This study investigated the effects of direct-contact ultrasonic vacuum drying on the drying characteristics and quality of dandelion. Dandelion samples were dried under different ultrasonic power levels and compared with samples processed via vacuum freeze-drying, shade drying, and hot-air drying in terms of color, flavonoid content, and cichoric acid content. Results showed that the drying rate increased with increasing ultrasonic power and drying temperature. The Page and Two-term models provided the best fit for the drying kinetics. The color of samples dried via direct-contact ultrasonic vacuum drying at 192 W was closest to that of fresh samples among all considered methods. At 192 W, the flavonoid content in the solution after rehydration was significantly higher than that obtained using other drying methods(p<0.05). In addition, total flavonoid and cichoric acid contents at 192 W were 57.09 and 12.35 mg/g, respectively. Furthermore, comprehensive evaluation using the entropy weight-grey relational analysis method showed that the samples dried at 192 W exhibited the highest correlation degree and ranked first overall among all drying methods. This study confirms that direct-contact ultrasonic vacuum drying can effectively improve the drying characteristics and quality of dandelion, providing references for applications in food and traditional Chinese medicine.

By establishing high-performance liquid chromatography (HPLC) fingerprints of Qingxiao Wuwei Decoction (QXWWD) and integrating chemical pattern recognition with in vivo and in vitro component identification methods, this study aimed to screen differential compounds and provide reference data for consistency evaluation and the development of compound preparations. The fingerprints of 18 batches of QXWWD were established evaluated for similarity. Bioinformatics methods were used to analyze potential quality markers. HPLC-Q-Exactive-MS was used to identify in vitro chemical components and serummigration components of QXWWD.Based on the integrated “fingerprint-pattern recognition-serum-migrant components” strategy, quality-difference markers were screened. A total of 28 peaks were identified in the fingerprints of QXWWD, among which 8 quality-difference markers, such as chrysophanol, were selected. In total,85 in vitro chemical components and 55 serummigration components of QXWWD were identified. By finding the intersection of the fingerprint-identified components and those identified in vivo and in vitro using a Venn diagram, we identified chrysophanol as the core quality-difference marker. This study established a simple and reproducible analytical method that can effectively evaluate the quality stability and batch consistency of QXWWD. This method provides reliable data to support process optimization, quality-standard development,and the subsequent development of this prescription.

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) was used to analyze the differences in chemical composition of dried and baked ginger.Then, network pharmacology was applied to investigate the mechanisms underlying their differences in efficacy. The chemical components of dried and baked ginger were analyzed using UPLC-Q-TOF-MS/MS, and the differential compounds were screened using partial least squares-discriminant analysisand random forest methods. SuperPRED and GeneCards databases were employed to retrieve drug and disease targets, respectively.Common targets were identified using Venn diagram mapping. Protein-protein interaction networks were constructed using the STRING database, and key targets were subjected to GO and KEGG enrichment analyses using the DAVID database.The UPLC-Q-TOF-MS/MS identified 61 chemical components, screening out 13 differential compounds (e.g., 7-gingerol, 12-gingerol, and gingerenone A). The network pharmacology results revealed that dried ginger mainly acts on targets such as MAPK1, PTGS1, and OPRD1, mediating the expression of signaling pathways such as interleukin-17, toll-like receptor, and TNF to alleviate inflammatory responses, exerting a “warming the middle to relieve pain” effect. Baked ginger mainly targets APEX1, SLC6A5, and NFKB1, mediating the HIF-1 signaling pathway, neurotrophin signaling pathways, and apoptosis to block pain signal transmission, exerting a “warming the middle to dispelling cold” effect. By integrating chemical composition analysis and network pharmacology, this study elucidated the mechanisms underlying the distinct therapeutic effects of dried and baked ginger, providing a scientific basis for their clinical applications.

We investigated the molecular mechanisms underlying the treatment of recurrent aphthous ulcers (RAU) using the Radix Aconiti-Cortex Phellodendri combination, based on weighted gene co-expression network analysis (WGCNA) and network pharmacology. A total of 301 active compounds were identified from the Radix Aconiti-Cortex Phellodendri combination, associated with 3 273 potential targets.WGCNA was used to analyze RAU-related genes. The Venn diagram package in R software was employed to identify intersections between drug-related targets and WGCNA modules. Pathway and process enrichment analyses, along with hierarchical clustering, were conducted using KEGG Pathway, GO Biological Processes, and Reactome Gene Sets. These analyses highlighted involvement in apoptosis regulation and signaling, glutathione metabolism, PI3K signaling abnormalities, resistance to epidermal growth factor receptor tyrosine kinase inhibitors, cytokine signaling in the immune system, the PPAR-α pathway, and other processes related to immune regulation, metabolism, and tissue repair.Using the MCODE plugin in Cytoscape v3.7.2, key hub genes within functional modules were identified, including ERBB2, CD44, NFKB1, and MMP2. Molecular docking showed that ERBB2 interacted with most active compounds; diterpenoid alkaloids from Aconitum and flavonoids from Phellodendron primarily targeted CD44; alkaloids from Phellodendron targeted MMP2; and both monoester and diester Aconitum alkaloids mainly targeted NFKB1. These findings suggest a complementary and synergistic effect between the two herbs in preventing RAU recurrence.Experimental validation showed that benzoylmesaconine, a core compound, significantly reduced LPS-induced ROS levels in macrophages, indicating thatRadix Aconiti, as the principal herb (Jun Yao), exerts its therapeutic effects primarily through metabolic regulation.

Betukladin is a dietary supplement composed of reindeer lichen powder and birch bark extract, possessing various pharmacological activities such as blood glucose regulation, lipid lowering, anti-inflammatory effects, and anticoagulation. This study investigates the lipid-lowering activity and underlying mechanism of Betukladin, aiming to validate its efficacy and provide a scientific basis for developing safe and economical natural lipid-lowering drugs. Using a zebrafish hyperlipidemia model, we found that Betukladin significantly improved the elevated Oil Red O staining integrated optical density values, triglyceride levels, and total cholesterol levels induced by high-fat modeling, indicating its lipid-lowering activity. Network pharmacology analysis suggested that Betukladin may exert its lipid-lowering effects through multiple coordinated pathways, including lipid and atherosclerosis pathways and the PPAR signaling pathway. RT-qPCR results showed that it can regulate lipid metabolism-related genes (apoA1, LDLR, and ANGPTL3), fatty acid synthesis and oxidation genes (SREBF1, FASN, PPARα, and cpt1a,), and cholesterol metabolism-related genes (CYP7A1, HMGCR, ABCG5, and ABCG8).

Selecting between fixed-route and flexible-route bus systems is a critical strategy for improving the operational efficiency of urban public transit. While most existing studies focus primarily on passenger demand, this study adopts a more comprehensive perspective by incorporating demand intensity, service area size, and block size. Based on the cost structures of both fixed- and flexible-route systems, mathematical models are developed to determine the optimal vehicle capacities and departure intervals that minimize total system costs. Closed-form solutions for these optimal values are derived for both transit modes. In addition, the study identifies the conditions under which each system is preferable, and derives threshold formulas for demand intensity, service area size, and block size. Research demonstrates that the operating costs of flexible bus systems (particularly pickup/drop-off costs) and passenger walking costs in fixed-route systems are pivotal determinants in transit mode selection. These cost factors exhibit threshold-dependent effects: only when their quantitative relationship meets specific conditions do demand intensity, service area scale, and block size significantly influence mode choice. Numerical simulations validate the proposed mode selection methodology between flexible and fixed-route bus systems. The findings provide actionable decision support for real-world transit planning applications.

The integrated dispatch of metro firefighting engines (MFEs) and trains during fire emergencies presents unique challenges due to confined tunnel spaces that restrict conventional fire truck access and the often uncertain fire location. This necessitates cross-line deployment of MFEs within the metro network. We decompose the problem into two subproblems: MFE rescue operations and evacuation of trapped trains. For each, a mixed-integer programming model is formulated. To enhance computational efficiency, we propose a line-based decomposition algorithm combined with a constraint filtering technique. The models are validated using the Suzhou metro network as a case study. Results demonstrate that the proposed approach efficiently generates solutions within practical timeframes, enabling effective cross-line MFE dispatch and rapid train evacuation. This research offers both theoretical insights and a practical decision-support tool for emergency management in metro fire scenarios, contributing significant value to metro operation safety and resilience.

To address the issue of low load factors associaated with conventional demand-responsive buses with fixed capacity, this study introduces a modular vehicle system and proposes a cross-regional demand-responsive bus dynamic scheduling optimization method based on modular vehicles. An objective function is established to minimize travel and operational costs for passengers and enterprises, respectively. The concept of coupling stations is introduced, and a dynamic fleet formation model considering coupling stations is designed, which allows for fleet reorganization and passenger transfer across two routes. Using the Big-M method, the model is linearized into a mixed-integer linear programming (MILP) problem for solutions, and the model is validated through a case study of two commuting routes from Jiukeshu to Wangfujing in Beijing. The experimental results show that compared to the introduction of conventional demand-responsive buses with fixed capacity, the introduction of modular buses effectively increases vehicle load factors, reduces operational costs for enterprises, and slightly reduces passenger travel costs. This indicates that the introduction of modular bus systems in urban commuting scenarios can provide a more flexible and efficient operational model for passenger travel and enterprise operations.

To explore the factors influencing the injury severity of cyclists in urban bicycle accidents and mitigate the impact of data heterogeneity and imbalance on the quantification of these factors, this study proposes a method integrating resampling, latent class analysis (LCA), and Bayesian networks (BNs) based on 3 895 bicycle accidents from the CRSS database. First, LCA was used to reclassify accident data into several sub-accident clusters with intra-cluster homogeneity and inter-cluster heterogeneity to reduce the impact of data heterogeneity. Second, random over-sampling (ROS), synthetic minority oversampling technique, and adaptive synthetic sampling approach were used to resample each accident cluster to reduce the impact of data imbalance. Finally, based on various resampled accident clusters, two BN structure learning algorithms and one parameter learning algorithm were applied and the optimal BN model for each accident cluster was selected based on AUC values to enable quantitative and heterogeneity analyses of factors influencing the injury severity of cyclists. Results show that when the overall accident data were divided into three homogeneous sub-clusters, the LCA model achieved an increased entropy value of 0.943. For the C1, C2, C3, and OD accident clusters, 10, 13, 9, and 12 key factors influencing the injury severity of cyclists were identified, respectively. The introduction of LCA and resampling into the BN considerably improved the BN model’s G-mean value, AUC value, and risk factor identification capabilities. Factors such as time period, cyclist’s gender, cyclist’s age, and weather conditions showed substantial heterogeneity across different accident clusters.

To address the efficiency loss caused by traffic congestion and frequent vehicle stops at signalized intersections, in this study we propose an intersection passing strategy based on multiple control modes. The interactions between vehicles and traffic signals as well as vehicle-to-vehicle interactions are analyzed, and six control modes are developed based on variations in traffic flow, signal cycles, and vehicle behavior. The strategy is dynamically adjusted to real-time traffic conditions. To minimize the impact of abrupt acceleration changes, the concept of vehicle jerk is introduced, and a straight-line trajectory model is developed accordingly. In addition, considering the collision-avoidance constraints of preceding vehicles, a polynomial method is used to construct an optimized lane-changing trajectory model to enhance the lane-changing efficiency. A comparative analysis of four control strategies demonstrates that the proposed multi-mode control strategy reduces delay times by 18.93% and 25.79% under low- and high-traffic flow conditions, respectively, compared to traditional strategies. Furthermore, by analyzing the displacement, speed, and acceleration curves of vehicles during travel, vehicle passing time is reduced by 2.60 to 23.52 s under different control modes, confirming the effectiveness of the proposed strategy in improving intersection traffic efficiency.

The section of the Yellow River from Bailongwan to the Lanjia River in Binzhou, China, is a curved section of the lower reaches of the Yellow River. In recent years, notable changes in the river regime have occurred due to alterations in water and sediment conditions. In certain sections, the mainstream lines have shifted leftward, posing a threat to the safety of the levees. Through data analysis, field investigations and measurements, and basic theoretical analysis, this study focuses on the channel evolution in this reach since the operation of the Xiaolangdi Reservoir and proposes corresponding management strategies. The study shows that the changes in the mainsteam lines are the primary cause of the leftward river regime migration and that flood events during the rainy season further intensify the river's swing. In response to the river regime changes, multiple management strategies are proposed, such as extending five spur dikes downstream of the Bailongwan risk control project and extending three spur dikes downstream of the Wangpingkou guiding structure, to enhance the project's flow-guiding capacity and reduce the hazards of the “cross-river” and “oblique-river” flows to the levees.

Persistent organic pollutants (POPs) generated during coal combustion have become a global focus of environmental governance because of their environmental persistence, bioaccumulation potential, and toxic effects. This study systematically reviews the formation mechanisms, emission characteristics, control technologies, and health risks of coal-derived POPs, such as polycyclic aromatic hydrocarbons (PAHs), halogenated PAHs (HPAHs), polychlorinated biphenyls (PCBs), and dioxins and furans. This study shows that POP formation is regulated by chemical kinetic pathways (precursor generation, halogenation, and surface-catalyzed synthesis) and the coupled effects of combustion conditions, coal properties, and fly ash catalysis. Their emission intensity is determined by the synergistic effects of combustion parameters, coal quality, and end-of-pipe control technologies. Remarkable heterogeneity exists in POP emissions from different combustion devices: PAHs are predominantly enriched in fine particles (particulate matter 2.5, PM_2.5), whereas emissions of HPAHs and PCBs are considerably influenced by coal chlorine content and combustion technologies. Current precombustion treatment, in-combustion control, and postcombustion technologies partially reduced POPs; however, breakthroughs are needed for identifying emerging pollutants, analyzing cross-media migration mechanisms, and improving global governance frameworks. Human exposure to POPs through inhalation and dietary intake may cause respiratory, immune, and reproductive system diseases, with health risks exceeding safety thresholds in some regions. Future research should focus on the characteristics of emerging pollutants, optimizing synergistic emission reduction technology systems, and improving multimedia risk assessment frameworks.

To investigate the characteristics of atmospheric composite pollution and meteorological driving mechanisms in medium-sized industrial cities, this study systematically analyzed the spatiotemporal variations and synergistic effects of PM_2.5 and ozone (O₃) based on air quality data from five national stations and eight county-level monitoring stations in Liaocheng City from 2019 to 2023. The results showed that the annual average PM_2.5 concentration exhibited a fluctuating downward trend but rebounded in 2023 with increased extreme values. O₃ concentrations displayed a “decline followed by rise” pattern, peaking at 230.0 μg/m³ in June during the summer pollution season. Correlation analysis revealed that PM_2.5 and O₃ pollution showed a positive correlation in summer and a negative correlation in winter,Among various meteorological factors, temperature exhibited a significant positive effect on O₃ formation. When humidity was in the 60%-70% range, the risk of simultaneous PM_2.5 and O₃ exceedance increased. Wind analysis further showed that O₃ exceedances predominantly occurred under the presence of southerly winds(0 to 7.5 m/s), displaying a distinct “red tongue” extension pattern, while calm and westerly winds exacerbated PM_2.5 concentration.