Guangzhou Henovcom Bioscience Co. Ltd

The South China University of Technology

Qi Guo

Jiancun Zhang

Deyao Li

Yiqian Zhou

Lijun Zhang

Kun Wang

Zhijun Zhang

Lu'nan Zheng

Jufu Zhang

Huajin You

Chen Guo

Jiafeng Chen

Suyong Li

Huixuan Chen

Yanhui Liu

Feng Wu

Wanjun Tang

Xiaoxi He

A novel tetrahydronaphthalene compound is provided, or a stereoisomer, a solvate, a pharmaceutically acceptable salt thereof, or a pharmaceutical composition including the compound, and a use of the compound or the composition for preparing a medicament in prevention and/or treatment of a central nervous system disease, wherein the compound has a structure of formula (I), wherein each of X, Y, Z, W and R is defined as described in the present disclosure.

Tetrahydronaphthalene compounds, pharmaceutical compositions, and uses thereof

The present disclosure relates to compounds for RNA capping and uses thereof, which belong to the technical field of genetic engineering. Compounds of formula I can result in high levels of capping efficiency, and the capped mRNA exhibits a high transcription level and increased expression.

Compounds for RNA capping and uses thereof

Provided is a stable flight control method for a multi-rotor unmanned aerial vehicle based on finite-time neurodynamics, comprising the following implementation process: 1) acquiring real-time flight orientation and attitude data through airborne sensors, and analyzing and processing kinematic problems of the aerial vehicle through an airborne processor to establish a dynamics model of the aerial vehicle; 2) designing a finite-time varying-parameter convergence differential neural network solver according to a finite-time varying-parameter convergence differential neurodynamics design method; 3) solving output control parameters of motors of the aerial vehicle through the finite-time varying-parameter convergence differential neural network solver using the acquired real-time orientation and attitude data; and 4) transmitting results to speed regulators of the motors of the aerial vehicle to control the motion of the unmanned aerial vehicle. Based on the finite-time varying-parameter convergence differential neurodynamics method, the invention can approximate the correct solution of the problem in a quick, accurate and real-time way, and can well solve a variety of time-varying problems such as matrix, vector, algebra and optimization.

Stable flight control method for multi-rotor unmanned aerial vehicle based on finite-time neurodynamics

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Guangzhou, China

Qi Guo