Identification of metabolites of rupestonic acid in rat urine by liquid chromatography combined with electrospray ionization quadrupole time‐of‐flight tandem mass spectrometry

Rupestonic acid, a potential anti‐influenza agent, is an important and characteristic compound in Artemisia rupestris L., a well‐known traditional Uighur medicine for the treatment of colds. In the present study, high‐performance liquid chromatography combined with electrospray ionization quadrupole time‐of‐flight tandem mass spectrometry was used to detect and identify the metabolites in rat urine after oral administration of rupestonic acid. A total of 10 metabolites were identified or partially characterized. The structure elucidations of the metabolites were performed by comparing the changes in accurate molecular masses and fragment ions with those of the parent compound. The results showed that the main metabolites of rupestonic acid in rat urine were formed by oxidation, hydrogenation and glucuronidation. A metabolism pathway was proposed for the first time based on the characterized structures. This metabolism study can provide essential information for drug discovery, design and clinical application of rupestonic acid. Copyright © 2014 John Wiley & Sons, Ltd.     

迹为整数的3×3阶正交矩阵的谱

讨论了3×3阶正交矩阵的特征值和迹的关系,证明了迹为整数的3×3阶正交矩阵的谱可由迹确定,为应用广泛的3×3阶正交矩阵的谱的计算提供了简单实用的方法.     

Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks

Random walks are a standard tool for modeling the spreading process in social and biological systems.But in the face of large-scale networks,to achieve convergence,iterative calculation of the transition matrix in random walk methods consumes a lot of time.In this paper,we propose a three-stage hierarchical community detection algorithm based on Partial Matrix Approximation Convergence(PMAC) using random walks.First,this algorithm identifies the initial core nodes in a network by classical measurement and then utilizes the error function of the partial transition matrix convergence of the core nodes to determine the number of random walks steps.As such,the PMAC of the core nodes replaces the final convergence of all the nodes in the whole matrix.Finally,based on the approximation convergence transition matrix,we cluster the communities around core nodes and use a closeness index to merge two communities.By recursively repeating the process,a dendrogram of the communities is eventually constructed.We validated the performance of the PMAC by comparing its results with those of two representative methods for three real-world networks with different scales.     

基于热中子探测评价裂缝的示踪剂特性研究

针对裂缝热中子示踪探测方法,从中子双组扩散理论入手结合蒙特卡洛数值模拟方法,分析压裂前后地层热中子分布影响因素,并模拟不同类型示踪剂及含量的热中子裂缝响应规律,筛选最佳示踪剂并给出其在支撑剂中含量的上、下限。结果表明:压裂前后热中子计数变化量主要受裂缝宽度和标记支撑剂中示踪剂含量的影响;钆对裂缝宽度变化反应最灵敏,钆元素是作为标记支撑剂的最佳示踪元素;随支撑剂中Gd 2O 3含量的增加,热中子计数率降低,热中子计数变化量D增加;示踪剂中氧化钆的上、下限值随裂缝宽度呈指数降低,且当裂缝宽度为1.0 cm时,Gd 2O 3的质量分数上限为0.68%,下限为0.03%。     

Effect of the dispersion on multipartite continuous-variable entanglement in optical parametric amplifier

Based on the quantum fluctuations, we adopt the method of generalized V1 criterion to investigate multipartite entanglement characteristics in an optical parametric amplification system with the consideration of dispersion. The nonlinear interaction becomes strong because of the existence of dispersion coefficient σ. Considering the influence of dispersion factor σ, with increasing the pump parameter μ, the value of minimum variance V1 decreases and the squeezing curve nearly equals 1/(1 + μ). The larger particle number N results in a smaller variance and higher entanglement.