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Minxiu Zhang,Xianwen Deng,Zhixun Xie,Yanfang Zhang,Zhiqin Xie,Liji Xie,Sisi Luo,Qing Fan,Tingting Zeng,Jiaoling Huang,Sheng Wang 대한수의학회 2022 Journal of Veterinary Science Vol.23 No.5
Background: Chicken anemia virus (CAV) causes chicken infectious anemia, which results in immunosuppression; the virus has spread widely in chicken flocks in China. Objectives: The aim of this study was to understand recent CAV genetic evolution in chicken flocks in Guangxi Province, southern China. Methods: In total, 350 liver samples were collected from eight commercial broiler chicken farms in Guangxi Province in southern China from 2018 to 2020. CAV was detected by conventional PCR, and twenty CAV complete genomes were amplified and used for the phylogenetic analysis and recombination analysis. Results: The overall CAV-positive rate was 17.1%. The genetic analysis revealed that 84 CAVs were distributed in groups A, B, C (subgroups C1-C3) and D. In total, 30 of 47 Chinese CAV sequences from 2005-2020 belong to subgroup C3, including 15 CAVs from this study. There were some specific mutation sites among the intergenotypes in the VP1 protein. The amino acids at position 394Q in the VP1 protein of 20 CAV strains were consistent with the characteristics of a highly pathogenic strain. GX1904B was a putative recombinant. Conclusions: Subgroup C3 was the dominant genotype in Guangxi Province from 2018–2020. The 20 CAV strains in this study might be virulent according to the amino acid residue analysis. These data help improve our understanding of the epidemiological trends of CAV in southern China.
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A many-objective evolutionary algorithm based on integrated strategy for skin cancer detection
( Yang Lan ),( Lijie Xie ),( Xingjuan Cai ),( Lifang Wang ) 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.1
Nowadays, artificial intelligence promotes the rapid development of skin cancer detection technology, and the federated skin cancer detection model (FSDM) and dual generative adversarial network model (DGANM) solves the fragmentation and privacy of data to a certain extent. To overcome the problem that the many-objective evolutionary algorithm (MaOEA) cannot guarantee the convergence and diversity of the population when solving the above models, a many-objective evolutionary algorithm based on integrated strategy (MaOEA-IS) is proposed. First, the idea of federated learning is introduced into population mutation, the new parents are generated through sub-populations employs different mating selection operators. Then, the distance between each solution to the ideal point (SID) and the Achievement Scalarizing Function (ASF) value of each solution are considered comprehensively for environment selection, meanwhile, the elimination mechanism is used to carry out the select offspring operation. Eventually, the FSDM and DGANM are solved through MaOEA-IS. The experimental results show that the MaOEA-IS has better convergence and diversity, and it has superior performance in solving the FSDM and DGANM. The proposed MaOEA-IS provides more reasonable solutions scheme for many scholars of skin cancer detection and promotes the progress of intelligent medicine.
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Water Dispersible Graphene Sheets Produced from Unassembled Graphene–Polyaniline Nanohybrids
Qi Li,Denian Li,Lijie Dong,Fan Sun,Jing Huang,Haian Xie,Chuanxi Xiong 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2015 NANO Vol.10 No.1
We present an effcient process for producing water dispersible graphene sheets from unassembled graphene–polyaniline nanohybrids. The result of atomic force microscopy reveals that over 80% of thus-prepared graphitic sheets are single layers with typical thickness of approximately 0.8 nm. The proportion of modifying molecules in the product is found to be as low as 3.0 wt.%, as determined by elemental analysis. Along with its fascinating water dispersibility and remarkably high electrical conductivity, such material is anticipated to be very promising for use in graphene-based nanoelectronics and high-performance composites.
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