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RISS 인기검색어
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- 저자 : Yu Helong (검색결과 4 건)
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Yu Helong,Zhao Zisong,Zhou Jing,Heidari Ali Asghar,Chen Huiling 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.4
In recent years, the sine cosine algorithm (SCA) has become one of the popular swarm intelligence algorithms due to its simple and convenient structure. However, the standard SCA tends to fall into the local optimum when solving complex multimodal tasks, leading to unsatisfactory results. Therefore, this study presents the SCA with communication and quality enhancement, called CCEQSCA. The proposed algorithm includes two enhancement strategies: the communication and collaboration strategy (CC) and the quality enhancement strategy (EQ). In the proposed algorithm, CC strengthens the connection of SCA populations by guiding the search agents closer to the range of optimal solutions. EQ improves the quality of candidate solutions to enhance the exploitation of the algorithm. Furthermore, EQ can explore potential candidate solutions in other scopes, thus strengthening the ability of the algorithm to prevent trapping in the local optimum. To verify the capability of CCEQSCA, 30 functions from the IEEE CEC2017 are analyzed. The proposed algorithm is compared with 5 advanced original algorithms and 10 advanced variants. The outcomes indicate that it is dominant over other comparison algorithms in global optimization tasks. The work in this paper is also utilized to tackle three typical engineering design problems with excellent optimization capabilities. It has been experimentally demonstrated that CCEQSCA works as an effective tool to tackle real issues with constraints and complex search space.
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Qiao Shimeng,Yu Helong,Heidari Ali Asghar,El-Saleh Ayman A,Cai Zhennao,Xu Xingmei,Mafarja Majdi,Chen Huiling 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5
The whale optimizer is a popular metaheuristic algorithm, which has the problems of weak global exploration, easy falling into local optimum, and low optimization accuracy when searching for the optimal solution. To solve these problems, this paper proposes an enhanced whale optimization algorithm (WOA) based on the worst individual disturbance (WD) and neighborhood mutation search (NM), named WDNMWOA, which employed WD to enhance the ability to jump out of local optimum and global exploration, adopted NM to enhance the possibility of individuals approaching the optimal solution. The superiority of WDNMWOA is demonstrated by representative IEEE CEC2014, CEC2017, CEC2019, and CEC2020 benchmark functions and four engineering examples. The experimental results show that thes WDNMWOA has better convergence accuracy and strong optimization ability than the original WOA.
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Song Jiuman,Chen Chengcheng,Heidari Ali Asghar,Liu Jiawen,Yu Helong,Chen Huiling 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.2
Swarm salp algorithm is a swarm intelligence optimization algorithm enlightened by the movement and foraging behaviors of the salp population. The salp swarm algorithm (SSA) has a simple structure and fast processing speed and can gain significant results on objective functions with fewer local optima. However, it has poor exploration ability and is easy to suffer from the local optimal solutions, so it performs poorly on multimodal objective functions. Besides, its unfair balance of exploration and exploitation is another notable shortcoming. To ameliorate these shortcomings and enhance the algorithm’s performance on multimodal functions, this research proposes simulated annealing (SA) improved salp swarm algorithm (SASSA). SASSA embeds the SA strategy into the followers’ position updating method of SSA, performs a certain number of iterations of the SA strategy, and uses Lévy flight to realize the random walk in the SA strategy. SASSA and 23 original and improved competitive algorithms are compared on 30 IEEE CEC2017 benchmark functions. SASSA ranked first in the Friedman test. Compared with SSA, SASSA can obtain better solutions on 27 benchmark functions. The balance and diversity experiment and analysis of SSA and SASSA are carried out. SASSA’s practicability is verified by solving five engineering problems and the fertilizer effect function problem. Experimental and statistical results reveal that the proposed SASSA has strong competitiveness and outperforms all the competitors. SASSA has excellent exploration ability, suitable for solving composition functions with multiple peaks. Meanwhile, SASSA brings about a good balance of exploration and exploitation and dramatically improves the quality of the solutions.
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mTORC1 Promotes Metabolic Reprogramming by the Suppression of GSK3-Dependent Foxk1 Phosphorylation
He, Long,Gomes, Ana P.,Wang, Xin,Yoon, Sang Oh,Lee, Gina,Nagiec, Michal J.,Cho, Sungyun,Chavez, Andre,Islam, Tasnia,Yu, Yonghao,Asara, John M.,Kim, Bo Yeon,Blenis, John Elsevier 2018 Molecular cell Vol.70 No.5
<P><B>Summary</B></P> <P>The mammalian Target of Rapamycin Complex 1 (mTORC1)-signaling system plays a critical role in the maintenance of cellular homeostasis by sensing and integrating multiple extracellular and intracellular cues. Therefore, uncovering the effectors of mTORC1 signaling is pivotal to understanding its pathophysiological effects. Here we report that the transcription factor forkhead/winged helix family k1 (Foxk1) is a mediator of mTORC1-regulated gene expression. Surprisingly, Foxk1 phosphorylation is increased upon mTORC1 suppression, which elicits a 14-3-3 interaction, a reduction of DNA binding, and nuclear exclusion. Mechanistically, this occurs by mTORC1-dependent suppression of nuclear signaling by the Foxk1 kinase, Gsk3. This pathway then regulates the expression of multiple genes associated with glycolysis and downstream anabolic pathways directly modulated by Foxk1 and/or by Foxk1-regulated expression of Hif-1α. Thus, Foxk1 mediates mTORC1-driven metabolic rewiring, and it is likely to be critical for metabolic diseases where improper mTORC1 signaling plays an important role.</P> <P><B>Highlights</B></P> <P> <UL> <LI> mTORC1 suppresses GSK3-dependent Foxk1 phosphorylation </LI> <LI> Foxk1 phosphorylation promotes 14-3-3 binding and nuclear exclusion </LI> <LI> Foxk1 transcriptionally regulates Hif1α expression </LI> <LI> Foxk1 and Hif1α contribute to mTORC1-regulated metabolic reprogramming </LI> </UL> </P> <P><B>Graphical Abstract</B></P> <P>[DISPLAY OMISSION]</P>
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