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Improve coati optimization algorithm for solving constrained engineering optimization problems
Jia Heming,Shi Shengzhao,Wu Di,Rao Honghua,Zhang Jinrui,Abualigah Laith 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.6
The coati optimization algorithm (COA) is a meta-heuristic optimization algorithm proposed in 2022. It creates mathematical models according to the habits and social behaviors of coatis: (i) In the group organization of the coatis, half of the coatis climb trees to chase their prey away, while the other half wait beneath to catch it and (ii) Coatis avoidance predators behavior, which gives the algorithm strong global exploration ability. However, over the course of our experiment, we uncovered opportunities for enhancing the algorithm’s performance. When confronted with intricate optimization problems, certain limitations surfaced. Much like a long-nosed raccoon gradually narrowing its search range as it approaches the optimal solution, COA algorithm exhibited tendencies that could result in reduced convergence speed and the risk of becoming trapped in local optima. In this paper, we propose an improved coati optimization algorithm (ICOA) to enhance the algorithm’s efficiency. Through a sound-based search envelopment strategy, coatis can capture prey more quickly and accurately, allowing the algorithm to converge more rapidly. By employing a physical exertion strategy, coatis can have a greater variety of escape options when being chased, thereby enhancing the algorithm’s exploratory capabilities and the ability to escape local optima. Finally, the lens opposition-based learning strategy is added to improve the algorithm’s global performance. To validate the performance of the ICOA, we conducted tests using the IEEE CEC2014 and IEEE CEC2017 benchmark functions, as well as six engineering problems.
Jia Heming,Lu Chenghao,Wu Di,Wen Changsheng,Rao Honghua,Abualigah Laith 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.4
In 2021, a meta-heuristic algorithm, Reptile Search Algorithm (RSA), was proposed. RSA mainly simulates the cooperative predatory behavior of crocodiles. Although RSA has a fast convergence speed, due to the influence of the crocodile predation mechanism, if the algorithm falls into the local optimum in the early stage, RSA will probably be unable to jump out of the local optimum, resulting in a poor comprehensive performance. Because of the shortcomings of RSA, introducing the local escape operator can effectively improve crocodiles' ability to explore space and generate new crocodiles to replace poor crocodiles. Benefiting from adding a restart strategy, when the optimal solution of RSA is no longer updated, the algorithm’s ability to jump out of the local optimum is effectively improved by randomly initializing the crocodile. Then joining Ghost opposition-based learning to balance the IRSA’s exploitation and exploration, the Improved RSA with Ghost Opposition-based Learning for the Global Optimization Problem (IRSA) is proposed. To verify the performance of IRSA, we used nine famous optimization algorithms to compare with IRSA in 23 standard benchmark functions and CEC2020 test functions. The experiments show that IRSA has good optimization performance and robustness, and can effectively solve six classical engineering problems, thus proving its effectiveness in solving practical problems.
Multi-strategy Remora Optimization Algorithm for solving multi-extremum problems
Jia Heming,LI YONGCHAO,Wu Di,Rao Honghua,Wen Changsheng,Abualigah Laith 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.4
A metaheuristic algorithm that simulates the foraging behavior of remora has been proposed in recent years, called ROA. ROA mainly simulates host parasitism and host switching in the foraging behavior of remora. However, in the experiment, it was found that there is still room for improvement in the performance of ROA. When dealing with complex optimization problems, ROA often falls into local optimal solutions, and there is also the problem of too-slow convergence. Inspired by the natural rule of “Survival of the fittest”, this paper proposes a random restart strategy to improve the ability of ROA to jump out of the local optimal solution. Secondly, inspired by the foraging behavior of remora, this paper adds an information entropy evaluation strategy and visual perception strategy based on ROA. With the blessing of three strategies, a multi-strategy Remora Optimization Algorithm (MSROA) is proposed. Through 23 benchmark functions and IEEE CEC2017 test functions, MSROA is comprehensively tested, and the experimental results show that MSROA has strong optimization capabilities. In order to further verify the application of MSROA in practice, this paper tests MSROA through five practical engineering problems, which proves that MSROA has strong competitiveness in solving practical optimization problems.
Jia Heming,You Fangkai,Wu Di,Rao Honghua,Wu Hangqu,Abualigah Laith 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.6
The snow ablation optimizer (SAO) is a new metaheuristic algorithm proposed in April 2023. It simulates the phenomenon of snow sublimation and melting in nature and has a good optimization effect. The SAO proposes a new two-population mechanism. By introducing Brownian motion to simulate the random motion of gas molecules in space. However, as the temperature factor changes, most water molecules are converted into water vapor, which breaks the balance between exploration and exploitation, and reduces the optimization ability of the algorithm in the later stage. Especially in the face of high-dimensional problems, it is easy to fall into local optimal. In order to improve the efficiency of the algorithm, this paper proposes an improved snow ablation optimizer with heat transfer and condensation strategy (SAOHTC). Firstly, this article proposes a heat transfer strategy, which utilizes gas molecules to transfer heat from high to low temperatures and move their positions from low to high temperatures, causing individuals with lower fitness in the population to move towards individuals with higher fitness, thereby improving the optimization efficiency of the original algorithm. Secondly, a condensation strategy is proposed, which can transform water vapor into water by simulating condensation in nature, improve the deficiency of the original two-population mechanism, and improve the convergence speed. Finally, to verify the performance of SAOHTC, in this paper, two benchmark experiments of IEEE CEC2014 and IEEE CEC2017 and five engineering problems are used to test the superior performance of SAOHTC.
Mutations in KEOPS-complex genes cause nephrotic syndrome with primary microcephaly
Braun, Daniela A,Rao, Jia,Mollet, Geraldine,Schapiro, David,Daugeron, Marie-Claire,Tan, Weizhen,Gribouval, Olivier,Boyer, Olivia,Revy, Patrick,Jobst-Schwan, Tilman,Schmidt, Johanna Magdalena,Lawson, J Nature Pub. Co 2017 Nature genetics Vol.49 No.10
<P>Galloway-Mowat syndrome (GAMOS) is an autosomal-recessive disease characterized by the combination of early-onset nephrotic syndrome (SRNS) and microcephaly with brain anomalies. Here we identified recessive mutations in OSGEP, TP53RK, TPRKB, and LAGE3, genes encoding the four subunits of the KEOPS complex, in 37 individuals from 32 families with GAMOS. CRISPR-Cas9 knockout in zebrafish and mice recapitulated the human phenotype of primary microcephaly and resulted in early lethality. Knockdown of OSGEP, TP53RK, or TPRKB inhibited cell proliferation, which human mutations did not rescue. Furthermore, knockdown of these genes impaired protein translation, caused endoplasmic reticulum stress, activated DNA-damage-response signaling, and ultimately induced apoptosis. Knockdown of OSGEP or TP53RK induced defects in the actin cytoskeleton and decreased the migration rate of human podocytes, an established intermediate phenotype of SRNS. We thus identified four new monogenic causes of GAMOS, describe a link between KEOPS function and human disease, and delineate potential pathogenic mechanisms.</P>
Xinyi Zhu,Tian Tian,Miao Ruan,Jia Rao,Wentao Yang,Xu Cai,Menghong Sun,Guangqi Qin,Zhonghua Zhao,Jiong Wu,Zhimin Shao,Ruohong Shui,Zhen Hu 한국유방암학회 2018 Journal of breast cancer Vol.21 No.3
Purpose: The characteristic expression of DNA damage response proteins in familial breast cancers with BRCA1, BRCA2, or non-BRCA1/2 mutations has not been analyzed in Chinese patients. Our study aimed to assess the differential expression of microcephalin 1 (BRIT1), ATM serine/threonine kinase (ATM), checkpoint kinase 2 (CHEK2), BRCA1, RAD51 recombinase (RAD51), and poly (ADP-ribose) polymerase 1 (PARP-1) and establish the profile of Chinese familial breast cancers with different mutation status. Methods: We constructed five tissue microarrays from 183 familial breast cancer patients (31 with BRCA1 mutations; 14 with BRCA2 mutations, and 138 with non-BRCA1/2 mutations). The DNA response and repair markers used for immunohistochemistry analysis included BRIT1, ATM, CHEK2, BRCA1, RAD51, and PARP-1. The expressions of these proteins were analyzed in BRCA1/2 mutated tumors. The association between pathologic characteristics with BRCA1/2 mutation status was also analyzed. Results: In familial breast cancer patients, BRCA1 mutated tumors were more frequent with high nuclear grade, estrogen receptor/progesterone receptor/human epidermal growth factor receptor 2 negative, low Ki-67, and positive CK5/6. BRCA1 mutated tumors had lower CHEK2 and higher cytoplasmic BRIT1 expression than BRCA2 and non-BRCA1/2 mutation tumors. BRCA2-associated tumors showed higher CHEK2 and cytoplasmic RAD51 expression than those in other groups. Nuclear PARP-1 expression in BRCA1/2-associated tumors was significantly higher than in non-BRCA1/2 mutation tumors. Moreover, we found quite a few of negative PARP-1 expression cases in BRCA1/2 mutated groups. Conclusion: The clinicopathologic findings of BRCA1-associated Chinese familial breast cancers were similar to the results of other studies. Chinese familial breast cancer patients with BRCA1/2 mutations might have distinctive expression of different DNA damage response proteins. The reduced expression of PARP-1 in Chinese BRCA1/2 mutated breast cancer patients could influence the therapeutic outcome of PARP-1 inhibitors.