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Zihong Ye,Junmin Wang,Qian Liu,Minzhou Zhang,Keqin Zou,Xianshu Fu 한국식물학회 2009 Journal of Plant Biology Vol.52 No.3
Using mixed-model-based composite interval mapping and conditional statistical methods, we studied quantitative trait loci (QTLs) with epistatic effects and QTLs by environment interaction effects for rice seed set percent (SSP), filled grain number per plant (FGP), and panicle length (PL). A population of 241 recombinant inbred lines was used which was derived from a cross between “Zhenshan 97” and “Minghui 63.” Its linkage map included 221 molecular markers. Our QTL analysis detected 28, 25, and 32 QTLs for SSP, FGP, and PL, respectively. Each QTL explained 1.37%∼13.19% of the mean phenotypic variation. A comparison of conventional and conditional mapping provided information about the genetic control system involved in the synthetic process of SSP, FGP, and PL at the level of individual QTLs. Conditional QTLs with reduced (or increased) effects were identified for SSP, which were significantly influenced by FGP or PL. Some QTLs could express independently for the given traits, thereby providing possibilities for simultaneous improvement of SSR and PL, and SSR and FGP. Epistasis was more sensitive to environmental conditions than were additive effects.
Optimal Incremental-containment Control of Two-order Swarm System Based on Reinforcement Learning
Haipeng Chen,Wenxing Fu,Kang Chen,Junmin Liu,Dengxiu Yu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.10
In this paper, the optimal incremental-containment control of two-order swarm system based on reinforcement learning (RL) is proposed to avoid the dilemma that the number of agents in a swarm system is immutable, which is essential for a swarm system that cannot meet the containment demands and need more agents to expand the containment range. Notably, the number of agents in a swarm system with a traditional containment controller is immutable, which limits the containment range that the swarm system can achieve. Besides, in traditional optimal control theory, it is obtained by solving the Hamilton-Jacobi-Bellman (HJB) equation, which is difficult to solve due to the unknown nonlinearity. To overcome these problems, several contributions are made in this paper. Firstly, in order to overcome the dilemma that the number of agents in the swarm system is immutable, the incremental-containment control is proposed. Secondly, considering the error and control input as the optimization goal, the optimal cost function is introduced and the optimal incremental-containment control is proposed to reduce resource waste and increase hardware service life. Furthermore, based on the proposed optimal incrementalcontainment control, the controller is designed by a new RL based on the backstepping method. The Lyapunov function is used to prove the stability of controller. The simulation show the efficiency of the proposed controller.
Jinni Hong,Tingting Fu,Weizhen Liu,Yu Du,Junmin Bu,Guojian Wei,Miao Yu,Yanshan Lin,Cunyun Min,Datao Lin The Korean Society for Microbiology and Biotechnol 2024 Journal of microbiology and biotechnology Vol.34 No.3
In this study, we aim to investigate the precise alterations in the gut microbiota during the onset and advancement of diabetic nephropathy (DN) and examine the impact of Ruminococcus gnavus (R. gnavus) on DN. Eight-week-old male KK-Ay mice were administered antibiotic cocktails for a duration of two weeks, followed by oral administration of R. gnavus for an additional eight weeks. Our study revealed significant changes in the gut microbiota during both the initiation and progression of DN. Specifically, we observed a notable increase in the abundance of Clostridia at the class level, higher levels of Lachnospirales and Oscillospirales at the order level, and a marked decrease in Clostridia_UCG-014 in DN group. Additionally, there was a significant increase in the abundance of Lachnospiraceae, Oscillospiraceae, and Ruminococcaceae at the family level. Moreover, oral administration of R. gnavus effectively aggravated kidney pathology in DN mice, accompanied by elevated levels of urea nitrogen (UN), creatinine (Cr), and urine protein. Furthermore, R. gnavus administration resulted in down-regulation of tight junction proteins such as Claudin-1, Occludin, and ZO-1, as well as increased levels of uremic toxins in urine and serum samples. Additionally, our study demonstrated that orally administered R. gnavus up-regulated the expression of inflammatory factors, including nucleotide-binding oligomerization domain-like receptor pyrin domain-containing protein 3 (NLRP3) and Interleukin (IL)-6. These changes indicated the involvement of the gut-kidney axis in DN, and R. gnavus may worsen diabetic nephropathy by affecting uremic toxin levels and promoting inflammation in DN.