The article addresses the event‐triggered obstacle avoidance control problem for autonomous
surface vehicles subject to actuator faults. In order to tackle the challenges presented by …

The motor imagery brain–computer interface (MI-BCI) system is currently one of the most
advanced rehabilitation technologies, and it can be used to restore the motor function of stroke …

This paper investigates the path-following control problem with obstacle avoidance of
autonomous surface vehicles in the presence of actuator faults, uncertainty and external …

To develop an efficient brain–computer interface (BCI) system, electroencephalography (EEG)
measures neuronal activities in different brain regions through electrodes. Many EEG-…

Deep learning networks have been successfully applied to transfer functions so that the
models can be adapted from the source domain to different target domains. This study uses …

Background and Objective How to learn robust representations from brain activities and to
improve algorithm performance are the most significant issues for brain-computer interface …

The purpose of this study was to investigate the prevalence of Cronobacter spp. in
commercial powdered infant formula (PIF) from nine provinces in China from March 2018 to …

This paper proposes a safety-critical obstacle avoidance control approach for autonomous
surface vehicles (ASVs) with disturbances and uncertainties. The existing exponential control …

This study describes a method for classifying electrocorticograms (ECoGs) based on motor
imagery (MI) on the brain–computer interface (BCI) system. This method is different from the …

The purpose of this study was to reveal the antibacterial activity and mechanism of Polygonatum
sibiricum extract (PSE) against Bacillus cereus and further analyze the application of …