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Association between Polymorphisms of Lipoprotein Lipase Gene and Chicken Fat Deposition
Liu, Rui,Wang, Yachun,Sun, Dongxiao,Yu, Ying,Zhang, Yuan Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.10
The objective of this study was to screen single nucleotide polymorphisms (SNPs) of the chicken lipoprotein lipase gene (LPL), using 545 F1 hybrids developed from $4{\times}4$ diallel crossing of four chicken breeds, and to analyze the associations between polymorphisms of the LPL and chicken fat deposition traits. PCR-SSCP was used to detect SNPs in LPL. Fifteen sets of primers were designed to amplify DNA fragments covering the 5'flanking and coding regions of LPL. It showed that there existed 5 polymorphic loci in the 5'flanking region and coding region, respectively. Association analysis was carried out between 10 polymorphic loci and intermuscular fat width, abdominal fat weight, and thickness of subcutaneous fat using ANCOVA, respectively. The results indicated that, in the 5'flanking region, the loci d and e significantly affected thickness of subcutaneous fat (p<0.05), abdominal fat weight (p<0.01) and subcutaneous fat (p<0.05), while in the coding region, synonymous mutation in exon 8 was significantly associated with intermuscular fat width (p<0.05), however, the non-synonymous mutations in exon 7 and exon 9 did not show statistically significant effects on fat deposition traits in this study.
( Hongwei Li ),( Dongxiao Liu ),( Khalid Alharbi ),( Shenmin Zhang ),( Xiaodong Lin ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.4
In smart grid, electricity consumption data may be handed over to a third party for various purposes. While government regulations and industry compliance prevent utility companies from improper or illegal sharing of their customers` electricity consumption data, there are some scenarios where it can be very useful. For example, it allows the consumers` data to be shared among various energy resources so the energy resources are able to analyze the data and adjust their operation to the actual power demand. However, it is crucial to protect sensitive electricity consumption data during the sharing process. In this paper, we propose a fine-grained access control scheme (FAC) with efficient attribute revocation and policy updating in smart grid. Specifically, by introducing the concept of Third-party Auditor (TPA), the proposed FAC achieves efficient attribute revocation. Also, we design an efficient policy updating algorithm by outsourcing the computational task to a cloud server. Moreover, we give security analysis and conduct experiments to demonstrate that the FAC is both secure and efficient compared with existing ABE-based approaches.
Zian He,Lei Xu,Dongxiao Li,Liying Liu,Yanwu Zhang,Yigang Li 한국물리학회 2006 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.49 No.5I
An Er3+/Yb3+ co-doped waveguide amplifier and a lossless power splitter were fabricated by two-step ion exchange on commercial Schott IOG-1 glasses. A two-dimensional ion exchange model was set up, and numerical simulations using a finite-element-method agreed well with experimental results. A total net gain of 6 dB was achieved in a 2.5-cm-long waveguide amplifier, and a lossless power splitter was successfully realized as well.kci
The Application of Principal component Analysis in Comprehensive Evaluation Of Listed Comany
Dong-xiao,Ji-qiu Liu,Xing-zhi Zhang 인하대학교 정석물류통상연구원 2009 인하대학교 정석물류통상연구원 학술대회 Vol.2009 No.10
As the economy system and legal system increasingly perfected, the operating performance of listed companies has become public pop attention as business operator, no matter investor, or ordinary people. The reason is that understand the operating performance of listed companies, then they can carry out the next step to choose better decision for operation and investment. In this way. they can obtain rising investment income while reducing the investment risk. However, through large amounts of data to understand the huge and complicated information of the operation performance of the listed companies is a very troublesome thing. Principal component analysis, which is a method of multi-attribute decision making and comprehensive evaluation, can solve this problem it can change huge information into several straight forward indexed to hepo people make choice rapidly. in this paper, according to their financial statements we adopt principal component analysis to estimate the operating performance of listed companies, and find out primary factors that influence the operating performance, and provide some correlative to help people make true decision.