Hepatitis C virus(HCV)helicase is a molecular motor that splits nucleic acid duplex structures during viral replication,therefore representing a promising target for antiviral treatment.Hence,a detailed understanding ...Hepatitis C virus(HCV)helicase is a molecular motor that splits nucleic acid duplex structures during viral replication,therefore representing a promising target for antiviral treatment.Hence,a detailed understanding of the mechanism by which it operates would facilitate the development of efficient drug-assisted therapies aiming to inhibit helicase activity.Despite extensive investigations performed in the past,a thorough understanding of the activity of this important protein was lacking since the underlying internal conformational motions could not be resolved.Here we review investigations that have been previously performed by us for HCV helicase.Using methods of structure-based computational modelling it became possible to follow entire operation cycles of this motor protein in structurally resolved simulations and uncover the mechanism by which it moves along the nucleic acid and accomplishes strand separation.We also discuss observations from that study in the light of recent experimental studies that confirm our findings.展开更多
提出一种基于递归稀疏主成分分析(recursive sparse principal component analysis,RSPCA)的工业过程故障监测与诊断方法,可用于时变工业过程的自适应故障监测与诊断.通过引入弹性回归网,将主成分问题转化为Lasso与Ridge结合的凸优化问...提出一种基于递归稀疏主成分分析(recursive sparse principal component analysis,RSPCA)的工业过程故障监测与诊断方法,可用于时变工业过程的自适应故障监测与诊断.通过引入弹性回归网,将主成分问题转化为Lasso与Ridge结合的凸优化问题,采用秩-1矩阵修正对协方差矩阵进行递归分解,递归更新稀疏载荷矩阵和监测统计量的过程控制限,以实现连续工业过程长时间自适应故障监测,对检测出来的故障通过贡献图法实现对故障的诊断.在田纳西-伊斯曼(TE)过程进行实验验证,结果表明,与传统的故障监测方法相比,所提出的方法有效降低了故障漏检率和误报率,且时间复杂度低,确保了故障监测的灵敏度和实时性.展开更多
在频谱一致性和频谱连续性的约束条件下,弹性光网络运行一段时间后,网络频谱会出现大量碎片的问题。针对碎片以及业务在各节点间分配不均衡的问题,提出了一种基于节点重要度的路由选择与频谱分配算法NIRSA(Route Selection and Spectrum...在频谱一致性和频谱连续性的约束条件下,弹性光网络运行一段时间后,网络频谱会出现大量碎片的问题。针对碎片以及业务在各节点间分配不均衡的问题,提出了一种基于节点重要度的路由选择与频谱分配算法NIRSA(Route Selection and Spectrum Allocation algorithm based on Node Importance)。该算法针对路由选择问题,考虑业务的类型与大小,找出网络中的关键节点,使得业务分配达到均衡。在频谱分配方面,算法考虑到网络链路上频谱资源的分布情况,结合每个业务所需的频隙数,可以尽可能地减少频谱碎片。在NSFNET和USNET两个不同规模的网络拓扑环境下,对所提算法进行了仿真实验。仿真结果显示,所提出的NIRSA算法既可以有效地降低业务阻塞率,又能提高网络的频谱利用率,实现网络性能提升。展开更多
文摘Hepatitis C virus(HCV)helicase is a molecular motor that splits nucleic acid duplex structures during viral replication,therefore representing a promising target for antiviral treatment.Hence,a detailed understanding of the mechanism by which it operates would facilitate the development of efficient drug-assisted therapies aiming to inhibit helicase activity.Despite extensive investigations performed in the past,a thorough understanding of the activity of this important protein was lacking since the underlying internal conformational motions could not be resolved.Here we review investigations that have been previously performed by us for HCV helicase.Using methods of structure-based computational modelling it became possible to follow entire operation cycles of this motor protein in structurally resolved simulations and uncover the mechanism by which it moves along the nucleic acid and accomplishes strand separation.We also discuss observations from that study in the light of recent experimental studies that confirm our findings.
文摘提出一种基于递归稀疏主成分分析(recursive sparse principal component analysis,RSPCA)的工业过程故障监测与诊断方法,可用于时变工业过程的自适应故障监测与诊断.通过引入弹性回归网,将主成分问题转化为Lasso与Ridge结合的凸优化问题,采用秩-1矩阵修正对协方差矩阵进行递归分解,递归更新稀疏载荷矩阵和监测统计量的过程控制限,以实现连续工业过程长时间自适应故障监测,对检测出来的故障通过贡献图法实现对故障的诊断.在田纳西-伊斯曼(TE)过程进行实验验证,结果表明,与传统的故障监测方法相比,所提出的方法有效降低了故障漏检率和误报率,且时间复杂度低,确保了故障监测的灵敏度和实时性.
文摘在频谱一致性和频谱连续性的约束条件下,弹性光网络运行一段时间后,网络频谱会出现大量碎片的问题。针对碎片以及业务在各节点间分配不均衡的问题,提出了一种基于节点重要度的路由选择与频谱分配算法NIRSA(Route Selection and Spectrum Allocation algorithm based on Node Importance)。该算法针对路由选择问题,考虑业务的类型与大小,找出网络中的关键节点,使得业务分配达到均衡。在频谱分配方面,算法考虑到网络链路上频谱资源的分布情况,结合每个业务所需的频隙数,可以尽可能地减少频谱碎片。在NSFNET和USNET两个不同规模的网络拓扑环境下,对所提算法进行了仿真实验。仿真结果显示,所提出的NIRSA算法既可以有效地降低业务阻塞率,又能提高网络的频谱利用率,实现网络性能提升。
