A Data-Based Feedback Relearning Algorithm for Uncertain Nonlinear Systems

In this paper,a data-based feedback relearning algorithm is proposed for the robust control problem of uncertain nonlinear systems.Motivated by the classical on-policy and off-policy algorithms of reinforcement learning,the online feedback relearning(FR)algorithm is developed where the collected data includes the influence of disturbance signals.The FR algorithm has better adaptability to environmental changes(such as the control channel disturbances)compared with the off-policy algorithm,and has higher computational efficiency and better convergence performance compared with the on-policy algorithm.Data processing based on experience replay technology is used for great data efficiency and convergence stability.Simulation experiments are presented to illustrate convergence stability,optimality and algorithmic performance of FR algorithm by comparison.

Modeling Methods of 3D Model in Digital Twins

To understand the current application and development of 3D modeling in Digital Twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D modeling to DTs modeling is analyzed,as well as the current application of DTs modeling in various industries.The application of 3D DTs modeling in the􀀀elds of smartmanufacturing,smart ecology,smart transportation,and smart buildings in smart cities is analyzed in detail,and the current limitations are summarized.It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles.At the same time,the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data,Internet of Things,Cloud Computing,Articial Intelligence,and game technology.Therefore,although some results have been achieved,there are still limitations.This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

Endoplasmic reticulum-related E3 ubiquitin ligases: Key regulators of plant growth and stress responses

Accumulating evidence has revealed that the ubiquitin proteasome system plays fundamental roles in the regulation of diverse cellular activities in eukaryotes.The ubiquitin protein ligases(E3s)are central to the proteasome system because of their ability to determine its substrate specificity.Several studies have demonstrated the essential role of a group of ER(endoplasmic reticulum)-localized E3s in the positive or negative regulation of cell homeostasis.Most ER-related E3s are conserved between plants and mammals,and a few plant-specific components have been reported.In this review,we summarize the functions of ERrelated E3s in plant growth,ER-associated protein degradation and ER-phagy,abiotic and biotic stress responses,and hormone signaling.Furthermore,we highlight several questions that remain to be addressed and suggest directions for further research on ER-related E3 ubiquitin ligases.

ERAD Tuning of the HRD1 Complex Component AtOS9 Is Modulated by an ER-Bound E2, UBC32

Dear Editor When membrane proteins and secretory proteins are incom- pletely folded or mis-folded, they are retained in the endo- plasmic reticulum （ER） for further folding or degradation. Two major degradation systems involved in removing the mis-folded or unfolded proteins retained in the ER have been identified： ER-associated degradation （ERAD）, which targets misfolded proteins for ubiquitination and subsequent degradattion through the proteasome pathway （McCracken and Brodsky, 1996）.

Two new species of Flavoperla(Plecoptera:Perlidae)from China

In this paper,two new species are described and illustrated from China:Flavoperla separata Liu,Li&Shali,sp.nov.from Hubei and Shaanxi Provinces and F.qinlinga Liu,Li&Li,sp.nov.from Shaanxi and Sichuan Provinces,with the discussion of their congeners.All type specimens are deposited in the Entomological Museum of China Agricultural University(CAU)and the Henan Institute of Science and Technology(HIST).