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Yanxia Chen,Xuedong Liu,Xiaoguang Yang,Yuhui Liu,Xiaomeng Pi,Qingzhen Liu,Dong Zheng 한국유전학회 2015 Genes & Genomics Vol.37 No.5
Deer antlers are the only mammalian appendages subject to an annual cycle of epimorphic regeneration. Within the rapid-growth stage, they display the fastest cartilage development in the animal kingdom. To identify microRNA (miRNA) profiling in red deer (Cervus elaphus) antler cartilage, we applied deep sequencing technology to a small RNA library constructed from pooled cartilage (three antlers from three individuals). We generated 9,520,645 mappable reads with a size distribution of between 15 and 30 nucleotides (miRNAs of 18 nucleotides were the most abundant group: 31 %). Bioinformatics data mining revealed 399 miRNAs in antler cartilage, of which 345 were highly conserved and expressed in 25 other mammals, including the cattle (Bos taurus) and in humans (Homo sapiens). The remaining 54 miRNAs we identified were novel and likely to be antler-cartilage specific, but were expressed at low levels. The identification of these known and newly identified miRNAs in antler cartilage significantly enhances our understanding of the miRNA profiling of regenerating antler cartilage. Further studies are necessary to better understand miRNAs-regulated antlerogenesis.
Fuzzy Risk Measures and its Application to Portfolio Optimization
Xiaoxian Ma,Qingzhen Zhao,Fangai Liu 한국전산응용수학회 2009 Journal of applied mathematics & informatics Vol.27 No.3
In possibility framework, we propose two risk measures named Fuzzy Value-at-Risk and Fuzzy Conditional Value-at-Risk, based on Credibility measure. Two portfolio optimization models for fuzzy portfolio selection problems are formulated. Then a chaos genetic algorithm based on fuzzy simulation is designed, and finally computational results show that the two risk measures can play a role in possibility space similar to Value-at-Risk and Conditional Value-at-Risk in probability space. In possibility framework, we propose two risk measures named Fuzzy Value-at-Risk and Fuzzy Conditional Value-at-Risk, based on Credibility measure. Two portfolio optimization models for fuzzy portfolio selection problems are formulated. Then a chaos genetic algorithm based on fuzzy simulation is designed, and finally computational results show that the two risk measures can play a role in possibility space similar to Value-at-Risk and Conditional Value-at-Risk in probability space.
FUZZY RISK MEASURES AND ITS APPLICATION TO PORTFOLIO OPTIMIZATION
Ma, Xiaoxian,Zhao, Qingzhen,Liu, Fangai The Korean Society for Computational and Applied M 2009 Journal of applied mathematics & informatics Vol.27 No.3
In possibility framework, we propose two risk measures named Fuzzy Value-at-Risk and Fuzzy Conditional Value-at-Risk, based on Credibility measure. Two portfolio optimization models for fuzzy portfolio selection problems are formulated. Then a chaos genetic algorithm based on fuzzy simulation is designed, and finally computational results show that the two risk measures can play a role in possibility space similar to Value-at-Risk and Conditional Value-at-Risk in probability space.
Two-Stream Convolutional Neural Network for Video Action Recognition
( Han Qiao ),( Shuang Liu ),( Qingzhen Xu ),( Shouqiang Liu ),( Wanggan Yang ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.10
Video action recognition is widely used in video surveillance, behavior detection, human-computer interaction, medically assisted diagnosis and motion analysis. However, video action recognition can be disturbed by many factors, such as background, illumination and so on. Two-stream convolutional neural network uses the video spatial and temporal models to train separately, and performs fusion at the output end. The multi segment Two-Stream convolutional neural network model trains temporal and spatial information from the video to extract their feature and fuse them, then determine the category of video action. Google Xception model and the transfer learning is adopted in this paper, and the Xception model which trained on ImageNet is used as the initial weight. It greatly overcomes the problem of model underfitting caused by insufficient video behavior dataset, and it can effectively reduce the influence of various factors in the video. This way also greatly improves the accuracy and reduces the training time. What’s more, to make up for the shortage of dataset, the kinetics400 dataset was used for pre-training, which greatly improved the accuracy of the model. In this applied research, through continuous efforts, the expected goal is basically achieved, and according to the study and research, the design of the original dual-flow model is improved.
Biochemical Characterization of Exoribonuclease Encoded by SARS Coronavirus
Chen, Ping,Jiang, Miao,Hu, Tao,Liu, Qingzhen,Chen, Xiaojiang S.,Guo, Deyin Korean Society for Biochemistry and Molecular Biol 2007 Journal of biochemistry and molecular biology Vol.40 No.5
The nsp14 protein is an exoribonuclease that is encoded by severe acute respiratory syndrome coronavirus (SARS-CoV). We have cloned and expressed the nsp14 protein in Escherichia coli, and characterized the nature and the role(s) of the metal ions in the reaction chemistry. The purified recombinant nsp14 protein digested a 5'-labeled RNA molecule, but failed to digest the RNA substrate that is modified with fluorescein group at the 3'-hydroxyl group, suggesting a 3'-to-5' exoribonuclease activity. The exoribonuclease activity requires $Mg^{2+}$ as a cofactor. Isothermal titration calorimetry (ITC) analysis indicated a two-metal binding mode for divalent cations by nsp14. Endogenous tryptophan fluorescence and circular dichroism (CD) spectra measurements showed that there was a structural change of nsp14 when binding with metal ions. We propose that the conformational change induced by metal ions may be a prerequisite for catalytic activity by correctly positioning the side chains of the residues located in the active site of the enzyme.
Anti-cancer Effect of a Rare Ginsenoside Compound K on Prostate Cancer in vitro
Garam Park(박가람),Hye Young Park(박혜영),Ji Hye Lee(이지혜),Seun Eui Kim(김선의),Myoung Hoon Lee(이명훈),Qingzhen Liu(류청정),Wan Taek Im(임완택),Hye Myoung Jang(장혜명),Joo Hyun Kim(김주현),Gwang Joo Jeon(전광주) 한국약용작물학회 2021 한국약용작물학회 학술대회논문집 Vol.2021 No.1