• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.469-475
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• 2008

The design of a scramjet inlet is a process to search global optimization results among those factors influencing the geometry of scramjet in their ranges for some requirements. An optimization algorithm of hybrid genetic algorithm based on genetic algorithm and simplex algorithm was established for this purpose. With the sample provided by a uniform method, the compressive angles which also are wedge angles of the inlet were chosen as the inlet design variables, and the drag coefficient, total pressure recovery coefficient, pressure rising ratio and the combination of these three variables are designed specifically as different optimization objects. The contrasts of these four optimization results show that the hybrid genetic algorithm developed in this paper can capably implement the optimization process effectively for the inlet design and demonstrate some good adaptability.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1585-1592
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• 2013

Functional food for prevention of chronic diseases is one of this century's key global challenges. Cancer is not only the first or second leading cause of death in China and other countries across the world, but also has diet as one of the most important modifiable risk factors. Major dietary factors now known to promote cancer development are polished grain foods and low intake of fresh vegetables, with general importance for an unhealthy lifestyle and obesity. The strategies of cancer prevention in human being are increased consumption of functional foods like whole grains (brown rice, barley, and buckwheat) and by-products, as well some vegetables (bitter melon, garlic, onions, broccoli, and cabbage) and mushrooms (boletes and Tricholoma matsutake). In addition some beverages (green tea and coffee) may be protective. Southwest China (especially Yunnan Province) is a geographical area where functional crop production is closely related to the origins of human evolution with implications for anticancer influence.

• Genomics & Informatics
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• v.21 no.4
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• pp.48.1-48.8
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• 2023

Liver cancer is the fourth leading cause of death worldwide. Well-known risk factors include hepatitis B virus and hepatitis C virus, along with exposure to aflatoxins, excessive alcohol consumption, obesity, and type 2 diabetes. Genomic variants play a crucial role in mediating the associations between these risk factors and liver cancer. However, the specific variants involved in this process remain under-explored. This study utilized a bioinformatics approach to identify genetic variants associated with liver cancer from various continents. Single-nucleotide polymorphisms associated with liver cancer were retrieved from the genome-wide association studies catalog. Prioritization was then performed using functional annotation with HaploReg v4.1 and the Ensembl database. The prevalence and allele frequencies of each variant were evaluated using Pearson correlation coefficients. Two variants, rs2294915 and rs2896019, encoded by the PNPLA3 gene, were found to be highly expressed in the liver tissue, as well as in the skin, cell-cultured fibroblasts, and adipose-subcutaneous tissue, all of which contribute to the risk of liver cancer. We further found that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. Positive associations with the prevalence rate were more frequent in East Asian and African populations. We highlight the utility of this population-specific PNPLA3 genetic variant for genetic association studies and for the early prognosis and treatment of liver cancer. This study highlights the potential of integrating genomic databases with bioinformatic analysis to identify genetic variations involved in the pathogenesis of liver cancer. The genetic variants investigated in this study are likely to predispose to liver cancer and could affect its progression and aggressiveness. We recommend future research prioritizing the validation of these variations in clinical settings.

• Journal of the Ergonomics Society of Korea
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• v.33 no.6
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• pp.465-475
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• 2014

Objective: The aim of this study is to investigate the effect of workload on musculoskeletal degeneration. Background: It is important that workers maintain a health body for a long time as a measure of aging workers. In order do so, it is necessary to find out if workload can effect on musculoskeletal degeneration. Method: Epidemiological studies on workload or occupation and disc degeneration, osteoarthritis of knee were identified through database and bibliography searches. Results: Epidemiological studies showed that workload certainly effect on musculoskeletal degeneration. But we couldn't know which of individual factors and occupational factors further contribute to the musculoskeletal degeneration. And we could find that studies on workload and genetic factors were very few. In addition, there was also very few studies that it was possible interaction between individual factors as obesity and occupational factors as heavy manual lifting. Conclusion: Our reviews suggest that it need to conduct study between workload and genetic factors for musculoskeletal degeneration. This further study can identify attributable risk of workload for musculoskeletal degeneration, and contribute to the measure of aging workers. Application: This paper can help to establish research plan for the measure of aging workers.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.9
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• pp.1345-1352
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• 2016

The hindgut of horses is an anaerobic fermentative chamber for a complex and dynamic microbial population, which plays a critical role in health and energy requirements. Research on the gut microbiota of Mongolian horses has not been reported until now as far as we know. Mongolian horse is a major local breed in China. We performed high-throughput sequencing of the 16S rRNA genes V4 hypervariable regions from gut fecal material to characterize the gut microbiota of Mongolian horses and compare them to the microbiota in Thoroughbred horses. Fourteen Mongolian and 19 Thoroughbred horses were used in the study. A total of 593,678 sequence reads were obtained from 33 samples analyzed, which were found to belong to 16 phyla and 75 genera. The bacterial community compositions were similar for the two breeds. Firmicutes (56% in Mongolian horses and 53% in Thoroughbred horses) and Bacteroidetes (33% and 32% respectively) were the most abundant and predominant phyla followed by Spirochaete, Verrucomicrobia, Proteobacteria, and Fibrobacteres. Of these 16 phyla, five (Synergistetes, Planctomycetes, Proteobacteria, TM7, and Chloroflexi) were significantly different (p<0.05) between the two breeds. At the genus level, Treponema was the most abundant genus (43% in Mongolian horses vs 29% in Thoroughbred horses), followed by Ruminococcus, Roseburia, Pseudobutyrivibrio, and Anaeroplasma, which were detected in higher distribution proportion in Mongolian horses than in Thoroughbred horses. In contrast, Oscillibacter, Fibrobacter, Methanocorpusculum, and Succinivibrio levels were lower in Mongolian horses. Among 75 genera, 30 genera were significantly different (p<0.05) between the two breeds. We found that the environment was one of very important factors that influenced horse gut microbiota. These findings provide novel information about the gut microbiota of Mongolian horses and a foundation for future investigations of gut bacterial factors that may influence the development and progression of gastrointestinal disease in horses.

• Journal of The Korean Association For Science Education
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• v.34 no.4
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• pp.407-415
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• 2014

Genetic determinism of human behaviors is considered as a philosophical perspective that genes in humans determine biological as well as social traits. However, many biologists agree that human traits are determined by interactions between genes and genes, as well as between genes and environments. In this context, genetic determinism still affect ideas of the general public as well as research directions of biologists. According to Cl$\acute{e}$ment's KVP model (Cast$\acute{e}$ra & Cl$\acute{e}$ment, 2012), teachers' conceptions of genetic determinism influence students' concepts of genetics. This study intends to investigate teachers' conceptions on genetic determinism of human behaviors. For this end, a questionnaire adopted from a previous research (Cast$\acute{e}$ra & Cl$\acute{e}$ment, 2012) has been administered to 308 teachers including 151 pre-service and 157 in-service. Factor analysis has been conducted to extract major factors and one-way ANOVA has been employed to find out differences in extracted factors among different groups of teachers. Four factors have been extracted from 14 items of questionnaire, including factor 1, a perspective of genetic determinism of gender differences in intellectual ability, social status, and emotional traits; factor 2, a perspective of genetic determinism of individual differences in intellectual ability; factor 3, a perspective of genetic determinism of individual differences in biological immune function and behavioral trait; and factor 4, a perspective of genetic determinism of ethnic differences. From the results of One-way ANOVA among teacher groups on four factors, first, it has shown a significant difference in factor 1 (F=3.325, p=.006), factor 3 (F=3.320, p=.006) and factor 4 (F=4.325, p=.001) due to their subject matters. In post-hoc comparison there have been no significant difference between biology teachers and other teachers. It has also been found that there was a significant difference between pre-service and in-service teachers in factor 1 (t=-3.938, p=.000) and factor 4 (t=-3.121, p=.002) and in-service teachers are more genetic deterministic than pre-service teachers. Finally, different religions have no influence on teachers' conceptions of genetic determinism of human behaviors.

• The Journal of the Korean dental association
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• v.51 no.12
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• pp.637-642
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• 2013

Because the implant is regarded as a common treatment. It is clinically important that systemic and local risk factor of threatening peri implant mucosa should be considered during the process. The most risk factors are detected in clinical diagnosis, but it might be difficult and not clear to recognize systemic or combined factors. This article reviews risk factors of peri-implantitis. Local factors are biomechanics, periodontal soft tissue characteristics, infected site and oral hygiene. Systemic factors are alcohol, smoking and genetic traits.

• Korean Journal of Animal Reproduction
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• v.23 no.4
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• pp.371-380
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• 1999

Animal reproductive performance could be affected by several regulatory factors, including nutritional, environmental, and genetic factors. Particularly, during the last half of this century, animal reproductive performance has been remarkably successful in improving the efficiency of livestock production. For some traits efficiency gains have been achieved with little or no knowledge of the genes underlying the traits. And, they have depended upon the phenotypic selection by statistical methods to estimate the genetic parameters of some reproductive traits. In spite of these successes, it is clear that recent advances in both developmental biology and molecular biology are set to revolutionize he practice of animal reproductive performance n the 21th century. (omitted)

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.415-422
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• 2017

Finding influential factors from given clustering result is a typical data science problem. Genetic Algorithm based method is proposed to derive influential factors and its performance is compared with two conventional methods, Classification and Regression Tree (CART) and Chi-Squared Automatic Interaction Detection (CHAID), by using Dunn's index measure. To extract the influential factors of preference towards political parties in South Korea, the vote result of $18^{th}$ presidential election and 'Demographic', 'Health and Welfare', 'Economic' and 'Business' related data were used. Based on the analysis, reverse engineering was implemented. Implementation of reverse engineering based approach for influential factor analysis can provide new set of influential variables which can present new insight towards the data mining field.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.399-408
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• 2001

This paper presents a simultaneous optimization approach of case-based reasoning (CBR) using a genetic algorithm(GA) for the prediction of stock price index. Prior research suggested many hybrid models of CBR and the GA for selecting a relevant feature subset or optimizing feature weights. Most studies, however, used the GA for improving only a part of architectural factors for the CBR system. However, the performance of CBR may be enhanced when these factors are simultaneously considered. In this study, the GA simultaneously optimizes multiple factors of the CBR system. Experimental results show that a GA approach to simultaneous optimization of CBR outperforms other conventional approaches for the prediction of stock price index.