To investigate the relationship of the variation of virulence and the external capsid proteins of the pandemic duck hepatitis A virus type 1(DHAV-1) isolates,the virulence,cross neutralization assays and the complete ...To investigate the relationship of the variation of virulence and the external capsid proteins of the pandemic duck hepatitis A virus type 1(DHAV-1) isolates,the virulence,cross neutralization assays and the complete sequence of the virion protein 1(VP1) gene of nine virulent DHAV-1 strains,which were isolated from infected ducklings with clinical symptoms in Shandong province of China in 2007-2008,were tested.The fifth generation duck embryo allantoic liquids of the 9 isolates were tested on 12-day-old duck embryos and on 7-day-old ducklings for the median embryonal lethal doses(ELD 50 s) and the median lethal doses(LD 50 s),respectively.The results showed that the ELD 50 s of embryonic duck eggs of the 9 DHAV-1 isolates were between 1.9 × 10 6 /mL to 1.44 × 10 7 /mL,while the LD 50 s were 2.39 × 10 5 /mL to 6.15 × 10 6 /mL.Cross-neutralization tests revealed that the 9 DHAV-1 isolates were completely neutralized by the standard serum and the hyperimmune sera against the 9 DHAV-1 isolates,respectively.Compared with other virulent,moderate virulent,attenuated vaccine and mild strains,the VP1 genes of the 9 strains shared 89.8%-99.7% similarity at the nucleotide level and 92.4%-99.6% at amino acid level with other DHAV-1 strains.There were three hypervariable regions at the C-terminus(aa 158-160,180-193 and 205-219) and other variable points in VP1 protein,but which didn't cause virulence of DHAV-1 change.展开更多
针对基于特征点匹配的SLAM(Simultaneous Localization and Mapping)系统在缺乏角点的弱纹理区域无法提取足够的特征点而导致位姿估计失败等问题,提出应用直接视觉里程计算法LDSO(Direct Sparse Odometry with Loop Closure)进行室内机...针对基于特征点匹配的SLAM(Simultaneous Localization and Mapping)系统在缺乏角点的弱纹理区域无法提取足够的特征点而导致位姿估计失败等问题,提出应用直接视觉里程计算法LDSO(Direct Sparse Odometry with Loop Closure)进行室内机器人视觉定位并结合深度估计或深度相机采集到的关键帧深度图,关键帧相机位姿,原始关键帧图像数据,点云拼接生成三维点云稠密地图,实验结果表明,机器人可在复杂环境中准确快速的定位自身位置,且算法在没有全局BA(Bundle Adjustment)的情况下通过位姿图优化显著减少了旋转,平移与尺度漂移等累积误差,算法整体性能与基于特征点匹配的SLAM系统相媲美,耗时更少,实时性更佳,在缺乏角点区域具有较强的鲁棒性.展开更多
基金the Chinese National Natural Sciences Foundation(30871878)Shandong Province Higher Educational Science and Technology Program(J08LF07)the Science and Technology Commission of Shandong Province(2010GNC10914),China
文摘To investigate the relationship of the variation of virulence and the external capsid proteins of the pandemic duck hepatitis A virus type 1(DHAV-1) isolates,the virulence,cross neutralization assays and the complete sequence of the virion protein 1(VP1) gene of nine virulent DHAV-1 strains,which were isolated from infected ducklings with clinical symptoms in Shandong province of China in 2007-2008,were tested.The fifth generation duck embryo allantoic liquids of the 9 isolates were tested on 12-day-old duck embryos and on 7-day-old ducklings for the median embryonal lethal doses(ELD 50 s) and the median lethal doses(LD 50 s),respectively.The results showed that the ELD 50 s of embryonic duck eggs of the 9 DHAV-1 isolates were between 1.9 × 10 6 /mL to 1.44 × 10 7 /mL,while the LD 50 s were 2.39 × 10 5 /mL to 6.15 × 10 6 /mL.Cross-neutralization tests revealed that the 9 DHAV-1 isolates were completely neutralized by the standard serum and the hyperimmune sera against the 9 DHAV-1 isolates,respectively.Compared with other virulent,moderate virulent,attenuated vaccine and mild strains,the VP1 genes of the 9 strains shared 89.8%-99.7% similarity at the nucleotide level and 92.4%-99.6% at amino acid level with other DHAV-1 strains.There were three hypervariable regions at the C-terminus(aa 158-160,180-193 and 205-219) and other variable points in VP1 protein,but which didn't cause virulence of DHAV-1 change.
文摘针对基于特征点匹配的SLAM(Simultaneous Localization and Mapping)系统在缺乏角点的弱纹理区域无法提取足够的特征点而导致位姿估计失败等问题,提出应用直接视觉里程计算法LDSO(Direct Sparse Odometry with Loop Closure)进行室内机器人视觉定位并结合深度估计或深度相机采集到的关键帧深度图,关键帧相机位姿,原始关键帧图像数据,点云拼接生成三维点云稠密地图,实验结果表明,机器人可在复杂环境中准确快速的定位自身位置,且算法在没有全局BA(Bundle Adjustment)的情况下通过位姿图优化显著减少了旋转,平移与尺度漂移等累积误差,算法整体性能与基于特征点匹配的SLAM系统相媲美,耗时更少,实时性更佳,在缺乏角点区域具有较强的鲁棒性.
