As one of the main methods of microbial community functional diversity measurement, biolog method was favored by many researchers for its simple oper- ation, high sensitivity, strong resolution and rich data. But the ...As one of the main methods of microbial community functional diversity measurement, biolog method was favored by many researchers for its simple oper- ation, high sensitivity, strong resolution and rich data. But the preprocessing meth- ods reported in the literatures were not the same. In order to screen the best pre- processing method, this paper took three typical treatments to explore the effect of different preprocessing methods on soil microbial community functional diversity. The results showed that, method B＇s overall trend of AWCD values was better than A and C＇s. Method B＇s microbial utilization of six carbon sources was higher, and the result was relatively stable. The Simpson index, Shannon richness index and Car- bon source utilization richness index of the two treatments were B〉C〉A, while the Mclntosh index and Shannon evenness were not very stable, but the difference of variance analysis was not significant, and the method B was always with a smallest variance. Method B＇s principal component analysis was better than A and C＇s. In a word, the method using 250 r/min shaking for 30 minutes and cultivating at 28 ℃ was the best one, because it was simple, convenient, and with good repeatability.展开更多
针对极化敏感阵列信号波达方向(direction of arrival,DOA)估计问题,提出了一种基于塔克张量域序贯截断高阶奇异值分解的正则极化旋转不变参数估计(Tucker tensor based regularized polarimetric estimation of signal parameters via ...针对极化敏感阵列信号波达方向(direction of arrival,DOA)估计问题,提出了一种基于塔克张量域序贯截断高阶奇异值分解的正则极化旋转不变参数估计(Tucker tensor based regularized polarimetric estimation of signal parameters via rotational invariance technique,trpESPRIT)方法。首先对阵列接收信号进行塔克张量建模,之后通过序贯截断高阶奇异值分解获得塔克张量域信号子空间,最后利用多旋转不变子空间幅相关系获得信号DOA估计。相比于传统矩阵建模方法,塔克张量建模更便于组织多维数据结构,实现高维的数据匹配操作,而序贯截断高阶奇异值分解则可以获得更高的信号子空间估计精度以及后续的DOA估计。仿真结果表明,trpESPRIT方法较之常规矩阵方法和矢量方法可以更好地抑制噪声,具有更高的信号DOA估计精度,在低信噪比和低快拍条件下仍然具有良好的分辨能力。展开更多
基金Supported by National and International Scientific and Technological Cooperation Project"The application of Microbial Agents on Mining Reclamation and Ecological Recovery"(2011DFR31230)Key Project of Shanxi academy of Agricultural Science"The Research and Application of Bio-organic Fertilizer on Mining Reclamation and Soil Remediation"(2013zd12)Major Science and Technology Programs of Shanxi Province"Key Technology Research and Demonstration of mining waste land ecosystem Restoration and Reconstruction"(20121101009)~~
文摘As one of the main methods of microbial community functional diversity measurement, biolog method was favored by many researchers for its simple oper- ation, high sensitivity, strong resolution and rich data. But the preprocessing meth- ods reported in the literatures were not the same. In order to screen the best pre- processing method, this paper took three typical treatments to explore the effect of different preprocessing methods on soil microbial community functional diversity. The results showed that, method B＇s overall trend of AWCD values was better than A and C＇s. Method B＇s microbial utilization of six carbon sources was higher, and the result was relatively stable. The Simpson index, Shannon richness index and Car- bon source utilization richness index of the two treatments were B〉C〉A, while the Mclntosh index and Shannon evenness were not very stable, but the difference of variance analysis was not significant, and the method B was always with a smallest variance. Method B＇s principal component analysis was better than A and C＇s. In a word, the method using 250 r/min shaking for 30 minutes and cultivating at 28 ℃ was the best one, because it was simple, convenient, and with good repeatability.
文摘针对极化敏感阵列信号波达方向(direction of arrival,DOA)估计问题,提出了一种基于塔克张量域序贯截断高阶奇异值分解的正则极化旋转不变参数估计(Tucker tensor based regularized polarimetric estimation of signal parameters via rotational invariance technique,trpESPRIT)方法。首先对阵列接收信号进行塔克张量建模,之后通过序贯截断高阶奇异值分解获得塔克张量域信号子空间,最后利用多旋转不变子空间幅相关系获得信号DOA估计。相比于传统矩阵建模方法,塔克张量建模更便于组织多维数据结构,实现高维的数据匹配操作,而序贯截断高阶奇异值分解则可以获得更高的信号子空间估计精度以及后续的DOA估计。仿真结果表明,trpESPRIT方法较之常规矩阵方法和矢量方法可以更好地抑制噪声,具有更高的信号DOA估计精度,在低信噪比和低快拍条件下仍然具有良好的分辨能力。
