Comparison study of typical algorithms for reconstructing time series from the recurrence plot of dynamical systems

The three most widely used methods for reconstructing the underlying time series via the recurrence plots (RPs) of a dynamical system are compared with each other in this paper. We aim to reconstruct a toy series, a periodical series, a random series, and a chaotic series to compare the effectiveness of the most widely used typical methods in terms of signal correlation analysis. The application of the most effective algorithm to the typical chaotic Lorenz system verifies the correctness of such an effective algorithm. It is verified that, based on the unthresholded RPs, one can reconstruct the original attractor by choosing different RP thresholds based on the Hirata algorithm. It is shown that, in real applications, it is possible to reconstruct the underlying dynamics by using quite little information from observations of real dynamical systems. Moreover, rules of the threshold chosen in the algorithm are also suggested.     

气相色谱-质谱法结合偏最小二乘-判别分析用于血清和血浆中代谢物的比较分析

建立了肟化-硅烷化衍生血清和血浆中代谢物的方法,结合气相色谱-质谱法,可实现有机酸、氨基酸、脂肪酸和胆固醇等多类代谢物的同时分析测定。方法学考察结果表明,该方法准确可靠,重复性、精密度和回收率良好,满足血清和血浆样本代谢物分析的要求。利用建立的方法,对40个健康人血清样本和34个健康人血浆样本中的代谢物进行对比分析。结果表明,吲哚-3-乙酸是血浆中特有的代谢物;共有的39个代谢物中,有32种在血清和血浆中的含量有显著性差异。采用偏最小二乘-判别分析(PLSDA)建立血清和血浆的判别模型,并筛选出了5种区分血清和血浆的重要代谢物,即磷酸、异亮氨酸、2,3,4-三羟基丁酸、柠檬酸和硬脂酸。研究结果为代谢组学研究中血清和血浆样本的选择提供了依据。