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- 저자 : Baoquan Gao (검색결과 4 건)
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Baoquan Gao,Dongfang Sun,Jianjian Lv,Xianyun Ren,Ping Liu,Jian Li 한국유전학회 2019 Genes & Genomics Vol.41 No.8
Background Low salinity is one of the main factors limiting the distribution and survival of marine species. As a euryhaline species, the swimming crab (Portunus trituberculatus) is adaptive to relatively low salinity. However, the mechanisms underlying salinity stress responses in P. trituberculatus is not very clear. Objectives The primary objective of this study was to describe the salinity adaptation mechanism in P. trituberculatus. Methods The crabs were exposed to low salinity stress, and gill tissue was sampled at 0, 12, 36, 48 and 72 h and subjected to high throughput sequencing. Subsequently, we tested the accuracy and quality of the sequencing results, and then carried out GO and KEGG bioinformatics on the differentially expressed genes (DEG). Results Each sample yielded more than 1.1 Gb of clean data and 23 million clean reads. The process was divided into early (0–12 h), middle (12–48 h), and late phase (48–72 h). A total of 1971 (1373 up-regulated, 598 down-regulated), 1212 (364 up-regulated, 848 down-regulated), and 555 (187 up-regulated, 368 down-regulated) DEGs with annotations were identified during the three stages, respectively. DEGs were mainly associated with lipid metabolism energy metabolism, and signal transduction from the three stages, respectively. Conclusion A substantial number of genes were modified by salinity stress, along with a few important salinity acclimation pathways. This work provides valuable information on the salinity adaptation mechanism in P. trituberculatus. In addition, the comprehensive transcript sequences reported in this study provide a rich resource for identification of novel genes in this and other crab species.
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Sun, Shizhen,Zhang, Hongjuan,Wang, Xiaoji,Gao, Yan,Jin, Baoquan The Korean Institute of Power Electronics 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.10
In dual-motor drive systems, a supercapacitor is connected to a common direct current (DC) bus through a DC/DC converter for the storage and utilization of regenerative energy, which is an effective energy saving method. However, the uncoordinated control of this type of system results in undesirable power circulation and reduced energy utilization efficiency. In this paper, an optimal power tracking control strategy based on a power flow predictive model is proposed. The power flow of the system is analyzed and a power flow predictive model is established. In addition, an objective function is deduced from the perspective of optimal performance tracking and minimum grid side energy consumption. The reference power of a supercapacitor is obtained in real time under constraints. The power flows among the grid side, the motors, and the energy storage unit are fully coordinated to realize a reasonable energy distribution. Experimental results indicate that the energy utilization efficiency of the system is improved by 25.4% in comparison with double closed-loop control in one working period.
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Yuqing Shao,Hongjuan Zhang,Yan Gao,Baoquan Jin 전력전자학회 2023 JOURNAL OF POWER ELECTRONICS Vol.23 No.10
This paper proposes a dynamic power distribution strategy for the hybrid energy storage systems (HESSs) in electric vehicles (EVs). First, the power loss of a HESS is analyzed based on its structure and model. Second, the optimal objectives for EV range extension, battery degradation mitigation, and HESS energy loss reduction are set, and the corresponding optimization variables are determined. Then, a multi-objective collaborative optimization (MOCO) function is established. It is furthertransformed into a linear programming problem with the battery current as the control variable. Finally, the dynamic power distribution scheme is obtained by analyzing the MOCO problem. The dynamic power distribution strategy using the MOCO is studies through simulations and experiments under the worldwide harmonized light vehicles test cycle. The obtained results indicate that the performances of the three optimal objectives are collaboratively improved.
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