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Articles by Dongmei Li
Total Records ( 6 ) for Dongmei Li
  Dongmei Li and Ambrose Cheung
  The regulatory locus sae is a two-component system in Staphylococcus aureus that regulates many important virulence factors, including alpha-toxin (encoded by hla) at the transcriptional level. The SarA homologs Rot and SarT were previously shown to be repressors of hla in selected S. aureus backgrounds. To delineate the interaction of rot and sae and the contribution of sarT to hla expression, an assortment of rot and sae isogenic single mutants, a rot sae double mutant, and a rot sae sarT markerless triple mutant were constructed from wild-type strain COL. Using Northern blot analysis and transcriptional reporter gene green fluorescent protein, fusion, and phenotypic assays, we found that the repression of hla by rot is dependent on sae. A rot sae sarT triple mutant was not able to rescue the hla defect of the rot sae double mutant. Among the three sae promoters, the distal sae P3 promoter is the strongest in vitro. Interestingly, the sae P3 promoter activities correlate with hla expression in rot, rot sae, and rot sae sarT mutants of COL. Transcriptional study has also shown that rot repressed sae, especially at the sae P3 promoter. Collectively, our data implicated the importance of sae in the rot-mediated repression of hla in S. aureus.
  Feng Xiao , HaiYing Fan and DongMei Li
  Football game video contains huge data and information of the event, in the race study course, the segmentation extraction of the targeted players, football and stadium’s flags line and prediction tracking is an important technique of video analysis. In this study, it uses the Kalman filter to study target motion estimation in soccer video analysis, first analyzed the principle of the filter and its mathematical model, sets filter’s parameters based on the video analysis object in actual football game and gives the calculation method of prediction estimation, finally carries through experimental simulation for the uniform motion of the players and analyzes the estimation data of player’s non uniform motion in the actual video game. The study results show that the error in uniform motion will converges to 0 with the increase of the number of iterations and estimation error for the actual non-uniform motion of the players has no obvious convergence but the Kalman filter has a significant impact on the decreases of motion estimation error for the player.
  Ankun Huang , Dongmei Li and Kuan Lu
  For an intelligent test-sheet composition system, compared with the traditional test-sheet composition using genetic algorithm, cellular genetic algorithm can significantly improve the convergence velocity and further improve the convergence in the process. However, in the process of mutating, both the diversity index of cellular population and the possibility of escaping from local-best will be decreased. Therefore, this study proposes a cellular genetic algorithm with an improved evolutionary rule applied in the process of test-sheet composition. Experimental results show that the convergence velocity is improved and the speed of decreasing diversity index of cellular population is delayed.
  Dongmei Li , Yan Qin , Na Li and Guangxin Wang
  Importing test paper questions into the database is a key part of initializing the question bank. This thesis proposes a method based on SVM (Support Vector Machine) and shallow parsing to recognize massive test paper and automatically finish the initialization of the question bank. This approach first use SVM to build a hyperplane to separate test paper into two parts, which are the question numbers and the questions. Secondly, automata model based on the principle of shallow parsing is constructed to judge the question numbers which are recognized by SVM and revises the wrong results. Finally, the successful recognized questions are imported into the database automatically after confirming. A large number of experimental results demonstrate that this method does not need any artificial pre-processing work. It can be used to recognize the Word test paper that contains pictures, tables and formulas. The algorithm is proved to be feasible, effective and adaptable and the recognition rate can achieve 100%.
  Dongmei Li , Di Zhang , Zhifang Wei and Jianxin Wang
  Program similarity measure technology is to detect the similarity among the programs by certain means. It is widely used in teaching and protection of intellectual property rights. Most current program similarity measure technologies suffer from low accuracy. Based on previous studies of program similarity measure method, this study proposes a method based on tree structure and eigenvector. Firstly, the actual frequency of keywords in the program is counted through employing hierarchical tree structure. Sencondly, the frequency is applied to generate eigenvector of program and the traditional method based on vector is improved. Finally, a program similarity measure system named Cplag is implemented which can be used to measure C language program similarity. Experimental results indicate that CPlag has apparent advantages in some aspects compared with famous Jplag.
  Jingsong Cao , Dandan Shan , Tracy Revett , Dongmei Li , Leeying Wu , Wei Liu , James F. Tobin and Ruth E. Gimeno
  Acyl-CoA-dependent lysophospholipid acyltransferases play an important role in attaining the appropriate molecular species of phospholipids. A number of genes encoding these activities were recently identified. It has become clear that multiple genes can encode one enzymatic activity and that a given gene may encode multiple activities. Here we report the identification of a gene encoding a mammalian acyl-CoA-dependent lysophospholipid acyltransferase with prominent activity toward ethanolamine-containing lysophospholipids, which we termed acyl-CoA:lysophosphatidylethanolamine acyltransferase 2, LPEAT2 (previously annotated as AYTL3 or AGPAT7). LPEAT2 is predominantly expressed in brain, coinciding with an enrichment of phosphatidylethanolamine in this tissue. Ectopic expression of LPEAT2 in mammalian HEK293T cells led to a dramatic increase (up to 9-fold) in LPEAT activity when compared with cells transfected with empty vector or an unrelated acyltransferase. LPEAT2 also exhibited significant acyl-CoA-dependent acyltransferase activity toward 1-O-alkenyl-lysophosphatidylethanolamine, lysophosphatidylglycerol, 1-O-alkyl-lysophosphatidylcholine, lysophosphatidylserine, and lysophosphatidylcholine but lacked appreciable acylating activity toward glycerol 3-phosphate, lysophosphatidic acid, lysophosphatidylinositol, and diacylglycerol, demonstrating multiple but selective functions of LPEAT2 as an enzyme involved in phospholipid remodeling. LPEAT2 recognizes a broad range of medium and long chain fatty acyl-CoA, and its activity was not affected by Ca2+. When overexpressed in mammalian cells, LPEAT2 is localized to the endoplasmic reticulum. siRNA-mediated knockdown of LPEAT2 in HEK293T cells significantly decreased LPEAT and 1-alkenyl-LPEAT activities but did not affect other lysophospholipid acylating activities. These findings identify LPEAT2 as an important enzyme in the biosynthesis of ethanolamine-containing phospholipids, especially in brain.
 
 
 
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