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Genetic and phylogenetic analysis of the honey bee sacbrood virus from jiangxi isolates
Meng Yaping,Yu Xinyue,Huang Qiang,Zhang Li Zhen,Wu Xiaobo,Wang Zilong,Yan Wei Yu 한국응용곤충학회 2022 Journal of Asia-Pacific Entomology Vol.25 No.1
The high prevalence of honeybee viral diseases poses a severe threat to the health of honeybees and causes substantial economic losses worldwide. Sacbrood virus (SBV) is a single-strand RNA virus that infects honeybees at all life stages. The infection can shorten the lifespan of adult bees and is lethal to larvae. SBV is the major cause of honeybee losses in Asia. Genetic and phylogenetic analyses of SBV isolates from different areas have been previously conducted. However, the impact of Apis mellifera Linnaeus and Apis cerana Fabricius coexistence on the infection and phylogeny of SBV remains unknown. In this study, we collected A. cerana and A. mellifera samples from commercial apiaries, only A. cerana in mountainous region. SBV prevalence was evaluated in three commercial apiaries of Jinxi, Tonggu and Nanchang and two mountainous regions of Zixi and Yifeng. In our sampling location, we found a higher SBV prevalence in the mountainous regions than in commercial apiaries. Partial structural polyprotein coding sequences were sequenced and compared with other GenBank SBV isolates. Phylogenetic tree topologies showed that SBV isolates form two major groups based on their host specificity, and isolates from same country tend to cluster together in subclades, indicating that the host and geographic region has significant effects on SBV strain specificity.
Xiaoxue Zhang,Jun Ma,Sunan Huang,Zilong Cheng,Tong Heng Lee 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
Control of autonomous robots (ARs) is a hot topic over the past three decades, and motion planning is becoming one of the major challenges in AR control. Substantial works have been done for motion planning in 2-dimensional (2D) environments, but planning in 3D complex environments is still an open problem to be investigated. In this paper, we propose a trajectory planning method to plan a high-quality and safe trajectory in 3-dimensional (3D) environments with multiple obstacles. The proposed method is based on the integration of a global optimal 3D path planner with a local planner. First, a hierarchical path planning algorithm is used as a global path planner to compute a near-optimal path formed by a set of waypoints. Second, a local path trajectory planner is designed to track the path computed by the global path planner with multiple constraints of dynamics and environment satisfied. Finally, simulations are conducted to validate the effectiveness of the proposed trajectory generation approach subject to the constraints of robot physical limits and environmental requirements.