The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of d...The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs(on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter(En KF) is introduced to estimate the vehicle's state with observations from navigation satellites and neighborhood vehicles, and the original En KF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in En KF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.展开更多
小分子药物与靶标的结合大都以非共价键结合,氢键、静电、疏水和范德华作用以维持结合力,这些因素越多结合越牢固,活性越强。但往往伴随分子尺寸变大,产生过膜吸收代谢等药代问题,最终影响成药性。基于片段的药物发现(fragment-based dr...小分子药物与靶标的结合大都以非共价键结合,氢键、静电、疏水和范德华作用以维持结合力,这些因素越多结合越牢固,活性越强。但往往伴随分子尺寸变大,产生过膜吸收代谢等药代问题,最终影响成药性。基于片段的药物发现(fragment-based drug discovery,FBDD)是普筛高质量片段以发现苗头分子,结合结构生物学,在片段生长、连接和融合中形成先导物,以及优化出候选物的运行中,始终兼顾化合物活性和物化性质之间的协调性。基于片段的药物发现与基于靶标结构的药物发现存在密切关系。本文以数个上市的药物简释FBDD的应用原理。展开更多
基金Project(4144081)supported by Beijing Natural Science Foundation,ChinaProjects(61403021,U1334211,61490705)supported by the National Natural Science Foundation of China+1 种基金Project(2015RC015)supported by the Fundamental Research Funds for Central Universities,ChinaProject supported by the Foundation of Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control,China
文摘The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs(on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter(En KF) is introduced to estimate the vehicle's state with observations from navigation satellites and neighborhood vehicles, and the original En KF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in En KF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.
文摘小分子药物与靶标的结合大都以非共价键结合,氢键、静电、疏水和范德华作用以维持结合力,这些因素越多结合越牢固,活性越强。但往往伴随分子尺寸变大,产生过膜吸收代谢等药代问题,最终影响成药性。基于片段的药物发现(fragment-based drug discovery,FBDD)是普筛高质量片段以发现苗头分子,结合结构生物学,在片段生长、连接和融合中形成先导物,以及优化出候选物的运行中,始终兼顾化合物活性和物化性质之间的协调性。基于片段的药物发现与基于靶标结构的药物发现存在密切关系。本文以数个上市的药物简释FBDD的应用原理。
