Retracted: MiR-10b alleviates high glucose-induced human retinal endothelial cell injury by regulating TIAM1 signaling

This article previously published in Volume 19 Issue 8 of this journal in August 2020 has been retracted in line with the guidelines from the Committee on Publication Ethics (COPE, http://publication ethics.org/resources/guidelines).Retraction: Chen Y, Zhu Y, Zhao S. MiR-10b alleviates high glucose-induced human retinal endothelial cell injury by regulating TIAM1 signaling. Trop J Pharm Res, 2020, 19(8): 1577-1583.To the editor:I am retracting this article because some of the results we presented are irreproducible.Signed: Sheng Zha

Study of Deformation-Compensated Modeling for Flexible Material Path Processing Based on Fuzzy Neural Network and Fuzzy Clustering

In this paper, the Flexible Material Path Processing (FMPP) deformation compensation modeling method based on T-S fuzzy neural network is proposed. This method combined with T S fuzzy reasoning and fuzzy neural network.Firstly, fuzzy clustering is introduced to extract fuzzy membership functions and the fitness of fuzzy rules of T S fuzzy neural network antecedent from historical processing data; secondly, through back-propagation iteration to calculate connection weights of the network. Processing experiments shows that T S fuzzy neural network modeling in this paper is superior to typical T S model，the angle error and straightness error processing by NTS FNN is decreased than these of STS FNN

Controlling Lethal Browning of \u3cem\u3eHemarthria compressa\u3c/em\u3e Tissue Cultures

Hemarthria compressa is an important warm-season forage grass for use in Southwest China. However, due to poor seed set, it is propagated by vegetative cuttings of stolons, rhizomes, and nodal sections. The in vitro propagation of H. compressa is still faced with difficulties including blackening or browning of tissues prior to culturing due to the oxidation of phenolic compounds by polyphenolic oxidase enzyme present in excised tissue (Yang et al. 2008). The objectives of the study were to investigate possible means of successful initiation of cultures through elimination of phenolic browning

Deformation-compensated modeling of flexible material processing based on T-S fuzzy neural network and fuzzy clustering

According to the factors that influence flexible material processing (FMP), the deformation compensation modeling method based on T-S fuzzy neural network is proposed. This method combines T-S fuzzy reasoning with a fuzzy neural network. Firstly, fuzzy clustering is introduced to extract fuzzy membership functions and the fitness of fuzzy rules of T-S fuzzy neural network antecedent from the past processing data. Secondly, with the steepest descent method, back-propagation iteration is used to calculate the connection weights of the network. The processing of experiments shows that T-S fuzzy neural network modeling is superior to typical T-S model. The angle error and the straightness error processed by NTS-FNN is 40.4 %, 28.8 % lower than those of STS-FNN. The minimum processing time processed by NTS-FNN is lower by 46.1 % than that of STS-FNN