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In this paper, a resilient tracking control scheme with cooperative collision avoidance performance is studied for the fixed-wing unmanned aerial vehicle (UAV) leader-follower formation in the presence of actuator failures and external disturbances. Firstly, based on the control objectives of UAV formation tracking and collision avoidance, the transformation tracking errors are obtained using the prescribed performance control technique. Next, a fault detection mechanism is introduced to determine if there is the actuator fault. Subsequently, the event-triggered resilient fault observers are designed based on a dynamic event-triggered mechanism to estimate actuator faults. Furthermore, the prescribed performance functions and the H∞ performance index are employed to ensure the UAV formation collision-free and mitigate the impact of disturbances. Moreover, the resilient controller is designed to minimize the effect of the perturbations for the control gain and the fault observer gain on the system. The stability of the system is also proven through the Lyapunov stability analysis, and the controller gains are calculated by solving the linear matrix inequality. Finally, the validity of the proposed control strategy is demonstrated by the simulation analysis. [ABSTRACT FROM AUTHOR]

Background: CircRNA‐encoded proteins (CEPs) are emerging as new players in health and disease, and function as baits for the common partners of their cognate linear‐spliced RNA encoded proteins (LEPs). However, their prevalence across human tissues and biological roles remain largely unexplored. The placenta is an ideal model for identifying CEPs due to its considerable protein diversity that is required to sustain fetal development during pregnancy. The aim of this study was to evaluate circRNA translation in the human placenta, and the potential roles of the CEPs in placental development and dysfunction. Methods: Multiomics approaches, including RNA sequencing, ribosome profiling, and LC‐MS/MS analysis, were utilised to identify novel translational events of circRNAs in human placentas. Bioinformatics methods and the protein bait hypothesis were employed to evaluate the roles of these newly discovered CEPs in placentation and associated disorders. The pathogenic role of a recently identified CEP circPRKCB119aa in preeclampsia was investigated through qRT‐PCR, Western blotting, immunofluorescence imaging and phenotypic analyses. Results: We found that 528 placental circRNAs bound to ribosomes with active translational elongation, and 139 were translated to proteins. The CEPs showed considerable structural homology with their cognate LEPs, but are more stable, hydrophobic and have a lower molecular‐weight than the latter, all of which are conducive to their function as baits. On this basis, CEPs are deduced to be closely involved in placental function. Furthermore, we focused on a novel CEP circPRKCB119aa, and illuminated its pathogenic role in preeclampsia; it enhanced trophoblast autophagy by acting as a bait to inhibit phosphorylation of the cognate linear isoform PKCβ. Conclusions: We discovered a hidden circRNA‐encoded proteome in the human placenta, which offers new insights into the mechanisms underlying placental development, as well as placental disorders such as preeclampsia. Key points: A hidden circRNA‐encoded proteome in the human placenta was extensively identified and systematically characterised.The circRNA‐encoded proteins (CEPs) are potentially related to placental development and associated disorders.A novel conserved CEP circPRKCB119aa enhanced trophoblast autophagy by inhibiting phosphorylation of its cognate linear‐spliced isoform protein kinase C (PKC) β in preeclampsia. [ABSTRACT FROM AUTHOR]

For the problems of traditional wolf pack algorithm (WPA) in the flight path planning for unmanned autonomous helicopters (UAH), including slower convergence speed and easy failing into local optimum solution, a three-dimensional flight path planning algorithm for UAH based on improved WPA is proposed. Firstly, the three-dimensional environment, constraints and fitness function of UAH flight are modeled. Secondly, the adaptive step-size method is used to improve the step size of the three main steps of wandering behavior, summoning behavior and siege behavior in the traditional WPA. At the same time, the strategy of combing Levy flight and changing direction migration are used for adjusting direction and scope of the search in walking behavior, so as to improve the global optimization ability and convergence speed of the algorithm. Finally, the simulation results show that the improved WPA has faster convergence and better track quality, which verifies the effectiveness of the proposed algorithm in the UAH flight path planning. [ABSTRACT FROM AUTHOR]