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Chenguang Zhu,Shilin Chen,Guimin Zhang,Wei Wang,Yuanping Tang,Bing Mei,Rentao Song 한국식물생명공학회 2015 Plant biotechnology reports Vol.9 No.4
The overexpression of algal glutamine synthetase (GS) gene DvGS2 in Arabidopsis thaliana resulted in higher plant biomass and better growth phenotype. The purpose of this study was to understand the biological mechanism for the improvement of growth phenotype of DvGS2-transgenic Arabidopsis. A series of molecular and biochemical investigation related to nitrogen and carbon metabolism in DvGS2-transgenic line was, respectively, conducted. Analysis of nitrogen use efficiency (NUE)-related gene expression and enzymatic activity revealed that the transcriptional level and enzymatic activity of genes encoding glutamate synthase, glutamate dehydrogenase and alanine aminotransferase were significantly up-regulated especially under low nitrate condition. The DvGS2- transgenic line showed higher total nitrogen content and lower carbon: nitrogen ratio than the wild type. Significant reduced concentration of leaf free ammonium, higher concentrations of total amino acids, individual amino acid (glutamine, methionine, alanine, asparagine) together with increased concentrations of glucose, fructose and starch, confirmed the higher efficiency of nitrogen and carbon assimilation. These improved metabolisms of nitrogen and carbon conferred the DvGS2-transgenic Arabidopsis more biomass, better growth phenotype and higher NUE compared with the wild type plant.
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Chengzhi Zhu,Yiming Jiang,Chenguang Yang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.1
Most of the existing identification/control algorithm of uncertain robot manipulators have been proposed to achieve model identification and trajectory tracking with expected precision, but the convergence time and transient tracking performance have been rarely discussed. In this paper, an adaptive fixed-time estimation algorithm is proposed for an uncertain robot. A recursive update law combined with an auxiliary filtering technique has been exploited such that the measurement of acceleration signals could be avoided during the estimation process. Based on the results of parameter identification, we propose a fixed-time control scheme which can guarantee the specified motion performance and prescribed convergence time simultaneously. The tiny practical error of parameter identification can be effectively handled with the proposed control scheme. Finally, the simulation results based on an uncertain 2-DOF robot have demonstrated the effectiveness of the proposed identification/control algorithm.
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