Showing 99–112 of 27,031 results for "Dou Jingru"

Journals 2026 EN

Multi-objective optimization design method for marine deepwater relief well 3D trajectory

Dou Zijun · Liu Yongsheng · Xia Jianxin +1 more

Deepwater drilling poses a high risk, and uncontrolled blowouts can significantly damage property and the environment. The relief well is considered the ultimate and most effective means for stopping blowouts. To quickly assess the rationality of the relief well trajectory design, 3D models for J-shaped and S-shaped trajectories are constructed using analytic geometry. Subsequently, the target section is represented as a spatial straight line and arc, and trajectory design equations with various known parameters are formulated using vector algebra. Ultimately, the optimal model for the relief well trajectory is established with the objectives of minimizing trajectory length, relative error, and trajectory energy. Case analysis results indicate that the design trajectory’s terminal point meets the connection requirements of coordinates and borehole direction, confirming the accuracy of the design equations. In addition, multi-objective optimization offers significant advantages in relief well trajectory optimization, resulting in shorter trajectory length, minor relative error, and lower trajectory energy. Compared to the existing optimization model, the proposed model reduces trajectory energy by 6.5% and decreases the drilling risk. The relief well trajectory design method can serve as a valuable reference for future marine deepwater relief well construction.

Taylor & Francis
Journals 2026 EN

Research on driver’s wrist motion pattern and fatigue characterization methods

Hongyi Xiang · Lilu Sun · Qiushi Wang +5 more

Studies have shown that driving fatigue leads to changes in driving behavior. The aim of this study was to analyze the effects of sleep deprivation and prolonged driving time on drivers’ wrist motion characteristics. Seventeen participants were recruited to participate in a 90-min simulated driving experiment after normal sleep and sleep deprivation, and wrist-worn wearable sensors were used to record the acceleration of the driver’s wrist and to characterize it in the time domain, frequency domain and entropy. PERCLOS was used as the standard to clarify the wrist motion characteristics of drivers in awake and fatigued states and to explore the trend of wrist motion characteristics with prolonged driving time. Fifteen participants completed two experiments. Sleep deprivation and driving time prolongation induced driving fatigue, which increased the low-frequency power ( p  < 0.05) and decreased the entropy ( p  < 0.05) of the driver’s wrist acceleration, leading to a decrease in the driver’s subtle adjusting maneuvers to the steering wheel and an increase in the rapid and large adjustments. Sleep deprivation led to an earlier onset of driving fatigue. Wrist movement characteristics can be used to reflect the driver’s fatigue state, which is of great value for road traffic accident prevention.

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Journals 2026 EN

Adverse events associated with carbamazepine: a pharmacovigilance study using the FDA Adverse Event Reporting System

Huang Shulan · Dong Hanlin · Luo Dongqiang +5 more

Carbamazepine (CBZ) is a commonly used antiseizures medications (ASM), but its adverse drug reactions (ADRs) can impact the successful management of epilepsy. There are currently limited systematic studies on ADRs related to CBZ, necessitating further investigation. Using the FDA Adverse Event Reporting System (FAERS) database , we extracted reports where CBZ was the primary suspect, conducting subgroup analyses stratified by sex and age. Four risk signal detection methods ROR, PRR, BCPNN, and EGBM were employed to systematically analyze the ADRs associated with CBZ. In the epilepsy population, ADRs related to CBZ often involve examinations, hereditary disorders, and infections. Subgroup analysis showed differences in ADR signals among male, female, elderly, and young patients. Human Herpesvirus 6 Infection and Dermatitis Exfoliative were consistent CBZ-induced ADRs, unaffected by age or sex. The study also identified previously overlooked ADRs such as bone metabolism abnormalities, ocular toxicity, and ototoxicity. Many ADRs linked to CBZ remain underreported. It is crucial to enhance monitoring and information dissemination about CBZ use in epileptic patients. Adjusting medication regimens for high-risk individuals, potentially incorporating acupuncture, traditional Chinese medicine, or alternative anti-seizure medications, should be considered when necessary.

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Journals 2026 EN

Mendelian randomization analysis of labor anesthesia and adverse neonatal outcomes

Qu Danyang · Zhang Yajun · Wang Shanshan +5 more

Despite the lack of data from randomized controlled trials, studies have indicated that labor anesthesia may be associated with neonatal asphyxia, neonatal respiratory distress and adverse neonatal neurological outcomes. Therefore, we performed a two-sample Mendelian randomization analysis to explore the potential causal relationships between labor anesthesia methods and adverse neonatal outcomes. We collected genome-wide association study (GWAS) data, including on spinal ( n  = 3,780), epidural ( n  = 3,970), and other labor anesthesia methods ( n  = 4,094), as well as neonatal asphyxia ( n  = 499,936), neonatal respiratory distress (NRDS) ( n  = 499,974) and cerebral palsy ( n  = 496,311), attention-deficit hyperactivity disorder (ADHD) ( n  = 495,160), and intellectual disability ( n  = 363,663). Data on different delivery analgesia methods that were sourced from the Integrative Epidemiology Unit (IEU) OpenGWAS project were used as exposure data. Neonatal asphyxia, neonatal respiratory distress and neurological adverse outcomes sourced from the FinnGen consortium R12 were used as the outcome data. A two-sample MR was used to evaluate the effects of different delivery analgesia methods on neonatal asphyxia, neonatal respiratory distress and three adverse neurological outcomes in newborns to determine the existence of a causal relationship between them. The inverse-variance weighted (IVW) method was used for MR analysis and a series of sensitivity analyses were conducted. The MR-Egger intercept test was used to assess directional horizontal pleiotropy. Heterogeneity was evaluated using the Cochran’s Q statistic. Instrument strength was assessed using F-statistics, with values greater than 10 indicating a low risk of weak instrument bias. Spinal, epidural, and other methods of labor anesthesia were not found to be strongly associated with neonatal asphyxia (OR = 0.707, 95% CI = 0.176–2.832, p  = 0.624; OR = 3.222, 95% CI = 0.973–10.664, p  = 0.055; OR = 0.732, 95% CI = 0.166–3.230, p  = 0.681, respectively), NRDS (OR = 0.941, 95% CI = 0.381–2.321, p  = 0.894; OR = 1.116, 95% CI = 0.505–2.465, p  = 0.786; OR = 0.801, 95% CI = 0.329–1.950, p  = 0.624), cerebral palsy (OR = 0.930, 95% CI = 0.442–1.959, p  = 0.849; OR = 0.636, 95% CI = 0.318–1.271, p  = 0.200; OR = 1.112, 95% CI = 0.544–2.271, p  = 0.771, respectively), intellectual disability (OR = 1.586, 95% CI = 0.917–2.743, p  = 0.099; OR = 0.809, 95% CI = 0.454–1.440, p  = 0.471; OR = 0.774, 95% CI = 0.380–1.575, p  = 0.479, respectively), or attention deficit hyperactivity disorder (OR = 0.827, 95% CI = 0.621–1.102, p  = 0.195; OR = 0.998, 95% CI = 0.739–1.346, p  = 0.988; OR = 1.136, 95% CI = 0.771–1.673, p  = 0.519, respectively). The sensitivity analyses, performed with Cochran’s Q test and the MR-Egger intercept, showed little evidence of substantial heterogeneity or directional horizontal pleiotropy. Our MR study based on genetic data does not support the existence of a causal relationship between different labor anesthesia methods and neonatal asphyxia, neonatal respiratory distress or adverse neonatal neurological outcomes. Thus, labor pain relief methods can be selected based on the mother’s needs and condition without increasing associated risks.

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Journals 2026 EN

Network pharmacology and experimental verification to explore the anti-inflammatory activities of triterpenoids from Siraitia grosvenorii

Wei Yulu · Fang Xiuyun · Lu Fenglai +3 more

Siraitia grosvenorii (Swingle) C. Jeffrey (SG), a Chinese medicinal plant, exhibits promising anti-inflammatory properties. Based on previous reports, aglycone and mogrosides bearing lesser glucosyl groups may contribute to the bioactivity of SG in vivo . However, research has rarely been conducted to compare their activities and analyse the structure–activity relationship. In this study, the anti-inflammatory potency of triterpenoids from SG and possible mechanisms of action based on network pharmacology were investigated. Furthermore, eighteen triterpenoids were chosen to assess their anti-inflammatory activities and structure–activity relationship in LPS-induced RAW 264.7 cells, among which 11-oxo-mogrol performed the best. Western blotting and molecular docking identified that 11-oxo-mogrol could regulate the PI3K/AKT signalling pathway. These findings provide valuable insights into the molecular mechanisms underlying the anti-inflammatory properties of triterpenoids from SG and support their application as potential therapeutic agents for inflammatory diseases.

Taylor & Francis
Journals 2026 EN

Mechanics-based design and sealing performance evaluation of bridge plug rubber cylinders with gradient porous structures

Zhang Yafei · Wei Shengrong · Wang Qihui +3 more

To overcome shoulder stress concentration and sealing failure in traditional bridge plug rubber cylinders, three optimized gradient-structure designs are proposed. Finite-element simulations were used to analyze the mechanical responses of uniform, central-gradient, and negative-gradient structures under different setting loads. Considering the contact stress distribution between the rubber cylinder and the casing, a new sealing performance evaluation method was established, and the sealing performance of all four types of rubber cylinders was assessed. Results show that, compared with the traditional structure, the new designs increase compression distance by 14.56–15.91% and reduce maximum equivalent stress by 10.14–15.26%. They also increase average contact stress by 8.01–16.03% and eliminate shoulder bulging. Among them, the negative-gradient structure provides optimal stress distribution and superior mechanical stability, while the central-gradient structure achieves the best sealing performance index K *, with a 26.44% improvement over the traditional design. Both designs significantly enhance sealing performance and service life.

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Journals 2026 EN

Mechanisms of transverse compression damage and reinforcement strategies for Larch wood

Huang Lei · Wang Ying · Han Xu +2 more

Transverse compression damage frequently affects active wooden components of ancient architecture, such as beams and Dou-gong, compromising structural safety. Larch ( Larix gmelinii var. principis-rupprechtii (Mayr) Pilger) wood, commonly used in ancient northern Chinese architecture, has limited studies on its transverse compression damage mechanisms. Traditional reinforcement methods are often ineffective. The present study integrated plastic equilibrium theory and static loading experiments to examine the transverse compression damage mechanism of larch wood under significant deformation. It also introduced an innovative method for parcel constraints to enhance the compression strength of wooden components in ancient architecture. Results showed the transverse compressive strength of larch wood ranges from 3 to 17 MPa, with maximum load-bearing capacity doubling after enhancement. End-wrapping confinement increased the load-bearing capacity by over 16%. Load-displacement curves under different compression conditions followed a three-stage pattern: elastic, plastic, and densification. Damage in larch wood began in the plastic stage. Under localized compression, samples exhibited a sudden drop in load-bearing capacity and secondary failure at 60–70% strain. This study offers valuable insights into the damage and residual load-bearing capacity of transversely compressed wooden components. The proposed compression enhancement strategy can reinforce damaged wooden components in ancient architecture, contributing to preserving cultural heritage.

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Journals 2026 EN

A novel method to generate simplified model for traditional timber bracket under horizontal load

Hua Quanjun · Chun Qing · Lin Yijie +1 more

As an important part of the traditional timber buildings, the dou-gong not only transmits the roof load vertically but also has strong seismic performance closely related to its complex structure. In this paper, a three-step method is proposed for simplifying the dou-gong using beam elements. The method includes the analysis of the load paths, analysis of the simplified beam system, and calculation of beam sections size. The seven-layers dou-gong between two columns in traditional Chinese timber buildings during AD 960–1368 was selected as a typical case study. Firstly, the quasi-static experiment was carried out on the dou-gong to obtain its load-displacement curve. Secondly, a fine finite element model was established to analyze the load paths inside the dou-gong. After that, the simplified beam system was established systematically according to the results of the above analysis. Finally, a sensitivity-based iterative method was used to solve the size of sections of each component so as to obtain the final simplified model. The experimental results showed that the simplified dou-gong model has high accuracy in the load-displacement curve. Furthermore, the average computational time for the simplified model was only 0.9% of that required by the fine model. HighlightSimplification based on mechanical behavior for typical dou-gong between columns is conducted. Simplified dou-gong model using Timoshenko beams is established. Sensitivity-based solution method for section of simplified model is presented. Simplification based on mechanical behavior for typical dou-gong between columns is conducted. Simplified dou-gong model using Timoshenko beams is established. Sensitivity-based solution method for section of simplified model is presented.

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Journals 2026 EN

High-speed railway hazards detection from GF-2 imagery with multiscale context-aware network

Du Xiaobing · Zhang Lu · Zhu Qi +7 more

While high-speed railway provides safe daily transportation for millions, its operational security is increasingly threatened by external hazards. High-speed railway hazards detection from remote sensing remains challenging due to scale variations and target-background ambiguity. To address these challenges, we propose the Multiscale Context-Aware Network (MSCANet) to capture spatial details and model multiscale contextual information. To extract spatial details, we develop the Local Feature Enhancement Module (LFEM) to aggregate parallel convolutions with diverse receptive fields, thereby enhancing the localization of multi-scale hazards. To capture long-range dependencies while ensuring computational efficiency, the Efficient Transformer Block (ETB) models local pixel similarity relationships via window-based attention, enabling precise discrimination of hazards from complex backgrounds. For feature integration, the Multiscale Feature Refinement Module (MFRM) iteratively integrates hierarchical features to aggregate contextual information. MSCANet achieves the highest mIoU of 87.73%, outperforming leading models on the hazards dataset. MSCANet is further applied to a high-traffic section of the Beijing-Shanghai High-Speed Railway between Jinan West Station and Qufu East Station, generating a detailed hazards map with distinct boundaries. The encouraging results indicate that MSCANet holds promise for high-speed railway hazards detection and presents substantial potential in hazards management. The code is available at https://github.com/smallbingbing/mscanet.

Taylor & Francis
Journals 2026 EN

ECHO: an integrated model fusing remote sensing and AI for dynamic water resource assessment

Zhang Ying · Huang Chunlin · Li Guoshuai +3 more

Achieving a sustainable future for water resources demands accurate models that address the interdisciplinary nature of water dynamics. The eco-hydrological-socioeconomic (ECHO) framework integrates physics-based hydrological models with data-driven machine learning techniques, leveraging reanalysis and multi-source remote sensing data. This enables dynamic estimation of sector-specific water demand and interaction with hydrological estimates. ECHO's modular structure allows coupling with grid-based models and includes modules for runoff, evapotranspiration (ET), groundwater flow, surface water routing, and water demand estimation. Calibration and validation demonstrate robust performance in simulating rainfall-runoff processes, with strong agreement observed for monthly ET estimates and gravity recovery and climate experiment-follow on (GRACE-FO) data on total water storage changes. The model accurately estimates total water demand across sectors and aligns with recorded water use data. Simulation outputs of water stress closely match findings from the China Water Resources Bulletin, while also showing promise to enhance projections aligned with sustainable development goals (SDGs) for global water management strategies. By providing high-resolution, dynamic assessments, ECHO offers a scalable tool for policymakers to identify water stress hotspots and optimize allocation strategies essential for meeting SDG targets.

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