目的探讨HIV/HBV合并感染者经含拉米夫定(3TC)的高效抗反转录病毒治疗(highly active antiretroviral therapy,HAART)后YMDD变异的检出率和影响因素。方法对使用含3TC的HAART治疗的39例HIV/HBV合并感染者采用PCR-反向点杂交法检测HBV Y...目的探讨HIV/HBV合并感染者经含拉米夫定(3TC)的高效抗反转录病毒治疗(highly active antiretroviral therapy,HAART)后YMDD变异的检出率和影响因素。方法对使用含3TC的HAART治疗的39例HIV/HBV合并感染者采用PCR-反向点杂交法检测HBV YMDD变异,并应用SPSS统计软件对YMDD变异检出率和影响YMDD变异的因素进行统计学分析。结果总的YMDD变异检出率为41.0%,随着治疗时间的延长,YMDD变异的检出率逐渐增加,治疗6～12月、12～24月、24～36月后YMDD的检出率分别为10.0%、42.1%和70.0%(P<0.05);YMDD变异组和未变异组的社会人口学特征、感染HIV途径、血清HBeAg状态、基线CD4+细胞水平、基线HBVDNA和ALT水平、有无肝硬化或纤维化、HBV基因型差异无统计学意义(P>0.05)。结论 HIV/HBV合并感染者的YMDD变异与含3TC的HAART治疗时间有关。展开更多
The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode...The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.展开更多
基金supported by the National Natural Science Foundation of China(6110118461174159)
文摘The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.
