Bin Chai

Natural flavonoid dihydroquercetin blocks Trim14-JAK1-STAT3 signaling and relieves pain-depression comorbidity in rheumatoid arthritis

Xiao-Wei Ni, Bin Chai, Z Li, X G Li et autres

Rheumatoid arthritis (RA) is frequently complicated by chronic pain, anxiety and depression, yet the neuroimmune mechanisms linking peripheral inflammation to central affective dysfunction remain elusive. Here we demonstrate that the natural flavonoid dihydroquercetin (DHQ) blocks Trim14 and relieves pain-depression comorbidity in RA. …

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Hydrogen Spillover-Mediated Spatial Decoupling Process Boosts Syngas Conversion to Higher Oxygenates

Li Su, Zili Ma, Xinyu Zhong, Bo Rong Wu et autres

The direct conversion of syngas to higher oxygenates presents a fundamental challenge in simultaneously achieving high CO conversion, superior oxygenate selectivity, and minimal undesired C 1 byproducts. Here, we develop a series of multifunctional Cu x Pd 1 /SiO 2 |CoMn catalysts …

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A fixed-time convergent robust zeroing neural network for time-varying linear matrix equation with application

Bin Chai, Kaiguo Qian, Xuewen Tan, Shikai Shen et autres

cn, hk (code pays fourni par la source)

A Novel Attitude Tracking Control Method for Rigid Spacecraft

Wanlin He, Bin Chai, Huijie Liu, Lin Liu

cn, th (code pays fourni par la source)

Enhancing long short-term memory for electric load forecasting with multi-batch Bayesian optimization

Bin Chai, Shikai Shen, Xuewen Tan, Yingbai Hu

cn, hk (code pays fourni par la source)

Design of Mobility Mechanism and Motion Control of High-Voltage Hanging-Line Inspection Robots

Bin Chai, Yulong Zhou, Jinxun Liu, Kai Huang et autres

As the demand for inspection of high-voltage transmission lines increases, traditional manual and aerial inspection methods are no longer sufficient to meet the efficiency and safety requirements. Intelligent inspection robots, as an emerging technology, have the potential to enhance both efficiency and …

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A hybrid optimization algorithm for parameter identification in proton exchange membrane fuel cell

Wanlin He, Bin Chai, Huijie Liu, Lin Liu

Purpose To identify parameters in a proton exchange membrane fuel cell. Design/methodology/approach A novel optimization algorithm, the sine-cosine geometric mean optimizer, is proposed for parameter identification in a proton exchange membrane fuel cell. Findings A novel optimization algorithm for parameter identification in …

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Corrigendum to “Highly selective syngas conversion to higher oxygenates over CuZnAl|CoFe multifunctional catalysts” [Int J Hydrogen Energy 110 (2024) 168-180]

Bin Chai, Chao Zhang Huang, Li Su, Maosheng Yang et autres

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A novel zeroing neural network model for the time-varying quadratic optimization problem

Bin Chai, Ke Zhang, Minghu Tan, Ren Wu et autres

The time-varying quadratic optimization problem (TVQOP) is a theoretical foundation for industrial applications. Solving the TVQOP quickly and accurately is difficult, being limited by the complexity of the coefficient matrix dimensions. A novel zeroing neural network (NZNN) model is proposed, targeting the …

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Optimized trajectory tracking control with disturbance resistance for wheeled mobile robot

Bin Chai, Ke Zhang, Minghu Tan

When unavoidable disturbances exist in practical applications, the unicycle wheeled mobile robot (WMR) with non-holonomic constraint is challenging to be accurately controlled in finite time. An optimized dual closed-loop strategy is proposed in this paper to solve the trajectory tracking control problem …

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Human-Machine Collaboration and Intelligent Strategy of Flexible Anti-Falling for Power Transmission Tower Assisted by Unmanned Aerial Vehicle Suspension

Mingyang Li, Yuwei Duan, Bin Chai, Ning Li et autres

This paper explores a series of innovative technologies and strategies to address safety risks and inefficiencies in the maintenance and inspection of transmission towers. Firstly, the drone-assisted suspension technology and flexible anti-falling technology for transmission towers are introduced, and their potential and …

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Meta-learning and U-Net Hybrid-based Defect Identification Method for Converter Valve Thyristor Gate Pole Line Shedding Defects

Tianqi Li, Menggan Ren, Jie Huang, Bin Chai et autres

To accurately recognize images of thyristor gate pole line shedding, a substantial amount of training samples is required. However, in practical engineering applications, such samples are severely lacking. For this reason, this paper proposes a defect recognition method based on a hybrid …

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