Complete Mitochondrial Genome of Echinostoma hortense (Digenea: Echinostomatidae)

Ze-Xuan Liu,Yan Zhang,Yu-Ting Liu,Qiao-Cheng Chang,Xin Su,Xue Fu,Dong-Mei Yue,Yuan Gao,Chun-Ren Wang 대한기생충학열대의학회 2016 The Korean Journal of Parasitology Vol.54 No.2

An Application of Support Vector Machines to Personal Credit Scoring : Focusing on Financial Institutions in China

Xuan-Ze Ding,Young-Chan Lee 대한산업경영학회 2018 산업융합연구 Vol.16 No.4

개인신용평가는 은행이 대출을 승인할 때 수익성 있는 의사결정을 적절히 유도할 수 있는 효과적인 도구이다. 최근 많은 분류 알고리즘 및 모델이 개인신용평가에 사용되고 있다. 개인신용평가 기법은 대체로 통계적 방법과 비 통계 적 방법으로 구분된다. 통계적 방법에는 선형회귀분석, 판별분석, 로지스틱 회귀분석, 의사결정나무 등이 포함된다. 비 통 계적 방법에는 선형계획법, 신경망, 유전자 알고리즘 및 Support Vector Machines 등이 포함된다. 그러나 신용평가모형 개발을 위해 어떠한 방법이 최선인지에 관해서는 일관된 결론을 내리기는 어렵다. 본 논문에서는 중국 금융기관의 개인 신용 데이터를 사용하여 가장 대표적인 신용평가 기법인 로지스틱 회귀분석, 신경망 그리고 Support Vector Machines의 성능을 비교하고자 한다. 구체적으로, 세 가지 모형을 각각 구축하여 고객을 분류하고 분석 결과를 비교하였다. 분석결과 에 따르면, Support Vector Machines이 로지스틱 회귀분석과 신경망보다 더 나은 성능을 가지는 것으로 나타났다. Personal credit scoring is an effective tool for banks to properly guide decision profitably on granting loans. Recently, many classification algorithms and models are used in personal credit scoring. Personal credit scoring technology is usually divided into statistical method and non-statistical method. Statistical method includes linear regression, discriminate analysis, logistic regression, and decision tree, etc. Non-statistical method includes linear programming, neural network, genetic algorithm and support vector machine, etc. But for the development of the credit scoring model, there is no consistent conclusion to be drawn regarding which method is the best. In this paper, we will compare the performance of the most common scoring techniques such as logistic regression, neural network, and support vector machines using personal credit data of the financial institution in China. Specifically, we build three models respectively, classify the customers and compare analysis results. According to the results, support vector machine has better performance than logistic regression and neural networks.

Network Analyses of Gene Expression following Fascin Knockdown in Esophageal Squamous Cell Carcinoma Cells

Du, Ze-Peng,Wu, Bing-Li,Xie, Jian-Jun,Lin, Xuan-Hao,Qiu, Xiao-Yang,Zhan, Xiao-Fen,Wang, Shao-Hong,Shen, Jin-Hui,Li, En-Min,Xu, Li-Yan Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.13

Fascin-1 (FSCN1) is an actin-bundling protein that induces cell membrane protrusions, increases cell motility, and is overexpressed in various human epithelial cancers, including esophageal squamous cell carcinoma (ESCC). We analyzed various protein-protein interactions (PPI) of differentially-expressed genes (DEGs), in fascin knockdown ESCC cells, to explore the role of fascin overexpression. The node-degree distributions indicated these PPI sub-networks to be characterized as scale-free. Subcellular localization analysis revealed DEGs to interact with other proteins directly or indirectly, distributed in multiple layers of extracellular membrane-cytoskeleton/ cytoplasm-nucleus. The functional annotation map revealed hundreds of significant gene ontology (GO) terms, especially those associated with cytoskeleton organization of FSCN1. The Random Walk with Restart algorithm was applied to identify the prioritizations of these DEGs when considering their relationship with FSCN1. These analyses based on PPI network have greatly expanded our comprehension of the mRNA expression profile following fascin knockdown to future examine the roles and mechanisms of fascin action.

Shortest Path Analyses in the Protein-Protein Interaction Network of NGAL (Neutrophil Gelatinase-associated Lipocalin) Overexpression in Esophageal Squamous Cell Carcinoma

Du, Ze-Peng,Wu, Bing-Li,Wang, Shao-Hong,Shen, Jin-Hui,Lin, Xuan-Hao,Zheng, Chun-Peng,Wu, Zhi-Yong,Qiu, Xiao-Yang,Zhan, Xiao-Fen,Xu, Li-Yan,Li, En-Min Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.16

NGAL (neutrophil gelatinase-associated lipocalin) is a novel cancer-related protein involves multiple functions in many cancers and other diseases. We previously overexpressed NGAL to analyze its role in esophageal squamous cell carcinoma (ESCC). In this study, a protein-protein interaction (PPI) was constructed and the shortest paths from NGAL to transcription factors in the network were analyzed. We found 28 shortest paths from NGAL to RELA, most of them obeying the principle of extracellular to cytoplasm, then nucleus. These shortest paths were also prioritized according to their normalized intensity from the microarray by the order of interaction cascades. A systems approach was developed in this study by linking differentially expressed genes with publicly available PPI data, Gene Ontology and subcellular localizaton for the integrated analyses. These shortest paths from NGAL to DEG transcription factors or other transcription factors in the PPI network provide important clues for future experimental identification of new pathways.

中國老齡化問題應對策略研究:集體社會資本視角下的老年人力資源開發

姜萱(Jiang, Xuan),陸競姸(Lu, Jing-yan),金紅花(Jin, Hong-hua),吳偉澤(Wu, Wei-ze) 동아인문학회 2021 동아인문학 Vol.57 No.-

인구의 고령화는 경제발전과 기술진보의 산물이자 삶의 질을 추구하는 인류의 필연적인 결과이다. 이 세계적인 난제를 해결하기 위해서는 인류 공통의 지혜가 필요하다. 중국은 2000년에 인구 고령화 국가 대열에 합류하여 현재는 거의 중등 고령화 수준에 도달했고, “부유해 지기 전의 고령화”, 급속한 고령화, 대규모 고령화의 특징을 보이고 있다. 인구 고령화는 미래 세계에서 영구적인 모습이 될 가능성이 높기 때문에 경제사회의 발전을 위해서는 노인인적자원 활용과 노인 수요 충족에 중점을 두어야 한다. 따라서 노인인적자원개발 사업이 중국의 현 인구 고령화 문제를 해결하는데 기여할 수 있을 것이라 판단된다. 본 연구는 Coleman의 집단의 사회적 자본 개념과 거시적 차원의 사회적 자본 이론을 기반으로 하였으며, 노인인적자원개발의 다자이익 집단은 사회개발, 조직개발, 자기개발의 세 가지 유형으로 구분하였다. 또한 중국의 고령화 현황과 노인인적자원개발의 전제 조건, 미래에 직면할 도전에 대하여 체계적으로 분석하고, 이를 바탕으로 최종적으로 중국의 실정에 맞는 인구 고령화 문제에 대한 해결책을 알아보았다. 본 연구의 목적은 다자이익집단이 함께 참여하여 사회적 자본을 모으고, 시너지 효과를 형성하여 인구 고령화 문제가 가져올 부정적인 결과를 완화하는데 있다. Population aging is the product of economic development and technological progress, as well as the inevitable result of human"s pursuit of high quality of life,which requires the common wisdom of human beings to solve this worldwide problem. China entered the ranks of population aging countries in 2000, and has now reached the aged society, and is characterized by “getting old before getting rich” problem, rapid population aging, and a large-scale elderly population. Since population aging has become an irreversible trend and is likely to become a permanent norm in the future all over the world, economic and social development needs to be closely promoted around the utilization of the elderly human resources and meeting their needs. Therefore, this paper advocates the development of the elderly human resources business as a means to solve the current problem of population aging in China. Based on Coleman"s concept of collective social capital and macro-level social capital theory, this paper classifies the multi-stakeholders in developing elderly human resources into three types: social development, organizational development and self-development. Through this, the paper makes a systematic analysis on the current situation of population aging in China, as well as the preconditions and future challenges of developing elderly human resources. Finally, the paper has constructed a set of solutions to the population aging problem in line with China"s national conditions. The purpose of this paper is to realize the use of multistakeholder groups to participate together, gather social capital and form a synergy to alleviate the adverse consequences of population aging. Findings are as follows: (1) in terms of social development, China should make full preparations under the national strategic framework by taking advantage of the “14th five-year plan” time window period, improve the policy system of elderly human resources development, improve the differences in the degree of aging in different regions according to local conditions, innovate ideas, and encourage high-quality elderly people to return to the labor market. (2) In terms of organizational development, it is necessary to improve the specialization and professionalism of the intermediary services of the elderly labor, break the organizational boundaries of communities. The paper suggests that educational organizations establish lifelong education and training systems, and that enterprises implement flexible management of the elderly human resources. (3) In terms of self-development, both the awareness of selfdevelopment and behavioral change of the elderly should be promoted. We should not only improve the awareness of re-employment and self-learning, but also making full use of the leading role of high-quality elderly human resources. So as to improve more elderly people to integrate into the elderly life with higher social value.

Fabrication of Photopolymer Hierarchical Micronanostructures by Coupling Electrospinning and Photolithography for SERS Substrates

Wen-Yi Zhang,Xin-Ze Xiao,Chao Lv,Jia Zhao,Gong Wang,Xuan Gu,Ran Zhang,Bin-Bin Xu,Dan-Dan Zhang,Ai-Wu Li,Yong-Lai Zhang,Hong-Bo Sun 한국고분자학회 2013 Macromolecular Research Vol.21 No.3

Reported here is the fabrication of photopolymer hierarchical micronanostructures through a combinative process of electrospinning and subsequent photolithography. Electrospun SU-8 (epoxy-based negative photoresist)nanofiber films have been patterned into gratings with periods of 100, 200, 300, and 400 μm, respectively. Deposition of a silver nanolayer on these interlaced nanofiber films would lead to the formation of various plasmonic nanostructures,and therefore, giving rise to abundant surface-enhanced Raman scattering (SERS) “hot spots”. In the detection of Rhodamine 6G (R6G), probing molecule, the resultant SERS substrates show both high sensitivity and good reproducibility. The SERS enhancement factor could reach as high as ~108, indicating high efficiency. The fabrication of patterned, highly efficient SERS substrates may hold a great promise for the integration of SERS substrates in various microdevices such as microfluidic chips.

Recent advances of bioactive proteins/polypeptides in the treatment of breast cancer

Qi-Zhang Li,Ze-Rong Zhou,Cui-Yu Hu,Xian-Bin Li,Yu-Zhou Chang,Yan Liu,Yu-Liang Wang,Xuan-Wei Zhou 한국식품과학회 2023 Food Science and Biotechnology Vol.32 No.3

Proteins do not only serve as nutrients to fulfill the demand for food, but also are used as a source of bioactive proteins/polypeptides for regulating physical functions and promoting physical health. Female breast cancer has the highest incidence in the world and is a serious threat to women’s health. Bioactive proteins/polypeptides exert strong anti-tumor effects and exhibit inhibition of multiple breast cancer cells. This review discussed the suppressing effects of bioactive proteins/polypeptides on breast cancer in vitro and in vivo, and their mechanisms of migration and invasion inhibition, apoptosis induction, and cell cycle arrest. This may contribute to providing a basis for the development of bioactive proteins/polypeptides for the treatment of breast cancer.

Impacts of shape and height of building roof on airflow and pollutant dispersion inside an isolated street canyon

Huang, Yuan-Dong,Xu, Xuan,Liu, Ze-Yu,Deng, Ji-Tong,Kim, Chang-Nyung Taylor and Francis 2016 Environmental forensics Vol.17 No.4

An Application of Support Vector Machines to Personal Credit Scoring: Focusing on Financial Institutions in China

딩쉬엔저,이영찬,Ding, Xuan-Ze,Lee, Young-Chan DAEHAN Society of Industrial Management 2018 산업융합연구 Vol.16 No.4

Personal credit scoring is an effective tool for banks to properly guide decision profitably on granting loans. Recently, many classification algorithms and models are used in personal credit scoring. Personal credit scoring technology is usually divided into statistical method and non-statistical method. Statistical method includes linear regression, discriminate analysis, logistic regression, and decision tree, etc. Non-statistical method includes linear programming, neural network, genetic algorithm and support vector machine, etc. But for the development of the credit scoring model, there is no consistent conclusion to be drawn regarding which method is the best. In this paper, we will compare the performance of the most common scoring techniques such as logistic regression, neural network, and support vector machines using personal credit data of the financial institution in China. Specifically, we build three models respectively, classify the customers and compare analysis results. According to the results, support vector machine has better performance than logistic regression and neural networks. 개인신용평가는 은행이 대출을 승인할 때 수익성 있는 의사결정을 적절히 유도할 수 있는 효과적인 도구이다. 최근 많은 분류 알고리즘 및 모델이 개인신용평가에 사용되고 있다. 개인신용평가 기법은 대체로 통계적 방법과 비 통계적 방법으로 구분된다. 통계적 방법에는 선형회귀분석, 판별분석, 로지스틱 회귀분석, 의사결정나무 등이 포함된다. 비 통계적 방법에는 선형계획법, 신경망, 유전자 알고리즘 및 Support Vector Machines 등이 포함된다. 그러나 신용평가모형 개발을 위해 어떠한 방법이 최선인지에 관해서는 일관된 결론을 내리기는 어렵다. 본 논문에서는 중국 금융기관의 개인 신용 데이터를 사용하여 가장 대표적인 신용평가 기법인 로지스틱 회귀분석, 신경망 그리고 Support Vector Machines의 성능을 비교하고자 한다. 구체적으로, 세 가지 모형을 각각 구축하여 고객을 분류하고 분석 결과를 비교하였다. 분석결과에 따르면, Support Vector Machines이 로지스틱 회귀분석과 신경망보다 더 나은 성능을 가지는 것으로 나타났다.

A study on left ventricular hypertrophy, QTc dispersion and hemodynamic differences in GXT according to excessive endurance exercise

( Piao Shun-zhe ),( Jin Zhong-xuan ),( Wang Guan ),( Zhao Ze-lin ),( Mu Yi-gang ),( Wen Jian-fei ),( Wang Xing ),( Il Su Kwon ),( Young Nam Cha ),( Young Ju Kim ) 대한운동사협회 2020 대한운동사협회 운동사대회자료집 Vol.2020 No.-