Cuticular Hydrocarbon Phenotypes Do not Indicate Cryptic Species in Fungus-Growing Termites (Isoptera: Macrotermitinae)

In several termite species, distinct differences in the composition of cuticular hydrocarbons among colonies correspond to high genetic divergence of mitochondrial DNA sequences. These observations suggest that hydrocarbon phenotypes represent cryptic species. Different cuticular hydrocarbon phenotypes also are found among colonies of fungus-growing termites of the genus Macrotermes. To determine if these hydrocarbon differences in Macrotermes also indicate cryptic species, we sequenced the mitochondrial CO I gene from species in West and East Africa. Among individuals of a supposed species but belonging to different cuticular hydrocarbon phenotypes, the genetic distances are much smaller than distances between species. Unlike what has been observed in other termites, Macrotermes hydrocarbon phenotypes do not represent cryptic species. Our findings suggest fundamental differences in the evolution and/or function of cuticular hydrocarbons among different termite lineages. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Blind separation of fetal electrocardiograms by annealed expectation maximization

This work explores blind source separation of fetal electrocardiograms by annealed expectation maximization (AEM). The AEM method improves the traditional EM method by relaxation under an annealing process, which is recruited to avoid trappings of tremendous spurious local minima within an objective function that inversely measures quantitative performance of a demixing structure. The derived objective function depends on the demixing structure as well as a set of membership vectors that represent missing data toward encoding statistical dependency of retrieved independent sources. Under the annealing process, the derived E and M steps are iteratively performed to search for expectations of membership vectors and minimizers of the objective function. The state number of membership vectors is related to modulate discretization of observations. Its effects on extraction of fetal electrocardiograms and reliability of the AEM method for blind source separation are extensively explored by numerical simulations.     

Influence of incident beam divergence on the intensity of diffuse streaks

The influence of incident beam divergence on the length of the streak intercepted by the Ewald sphere is considered, as a relpHK·L of a faulted hexagonal crystal, mounted about itsc-axis on the goniometer head attached to the ø-circle, is brought into diffracting condition for the bisecting setting of a 4-circle diffractometer. For the special crystal mounting correction factors required to convert the measured intensities corresponding to a fixed length of the streak are derived. A procedure for experimentally verifying the mathematical approach employed in these derivations is also presented.     

改进LMD及高阶模糊度函数的管道泄漏定位

针对天然气管道泄漏定位的问题,提出一种基于改进局域均值分解(LMD)及高阶模糊度函数的时延估计方法。该方法首先采用改进的LMD对声发射信号进行分解,获得多个PF分量,进而提出根据K-L散度的PF分量自动选择算法,获取含有主要泄漏信息的PF分量,在此基础上,研究了基于高阶模糊度函数计算声发射信号的时频参数,并通过时频分析获取特征频率的到达时间差,最后结合泄漏产生的广义声发射信号的传播速度完成对天然气管道泄漏的定位。实验结果表明,提出的方法能够进行定位且精度较直接相关法明显提高。     

防雷接地电阻测量套用欧姆定律的分析

防雷接地电阻测量套用欧姆定律,测出电阻值的结果是某个方向接地电阻的近似值。给出了套用欧姆定律测试的误差和减小测试误差的办法。将电压辅助极安置在电位散度零区,可减少测试误差,使测量结果更符合真值。     

基于KL散度的含储能机组组合分布鲁棒优化方法

为应对风电场出力的波动性和随机性给机组组合带来的问题,提出了基于Kullback-Leibler(KL)散度的含储能机组组合的两阶段分布鲁棒优化模型。在电池储能的运行模型的基础,将电池储能模型嵌入到传统的火电机组组合模型中,建立了含储能的机组组合两阶段优化模型;基于KL散度构建了风电场出力的模糊集,形成了含储能机组组合的两阶段分布鲁棒优化模型,通过对偶变换和广义Benders分解将其转化成易于求解的混合整数凸优化模型进行求解。通过IEEE RTS 24节点系统仿真结果表明,所提出的分布鲁棒优化方法保守性优于鲁棒优化方法,经济性接近随机优化方法,且随着KL散度增大,机组组合成本缓慢增加。     

中国南方新元古代—早古生代构造演化与盆地原型分析

中元古代末发生的晋宁运动在中国南方扬子陆块的周缘形成碰撞造山带,使华夏、川滇藏等陆块与扬子陆块拼合成统一的华南古大陆,奠定了新元古代—早古生代盆地发育的基底.新元古代—早古生代,中国南方在陆块裂解—离散—聚合不同的构造运动体制下,分别在扬子陆块的边缘和内部形成了不同的盆地原型及其演化序列.在扬子陆块的南、北缘,主要形成了裂陷—被动大陆边缘坳陷—前陆盆地的原型演化序列;在扬子陆内,由陆块离散拉张背景下整体下沉形成的碳酸盐岩台地演化为陆块聚合挤压背景下形成的台内坳陷盆地.而且,经加里东运动后,中国南方大陆得到了新的增生和统一,基本构造格局已经形成.      

Default Bayesian Priors for Regression Models with First-Order Autoregressive Residuals

Abstract. The objective of this paper is to develop default priors when the parameter of interest is the autocorrelation coefficient in normal regression models with first-order autoregressive residuals. Jeffreys' prior as well as reference priors are found. These priors are compared in the light of how accurately the coverage probabilities of Bayesian credible intervals match the corresponding frequentist coverage probabilities. It is found that the reference priors have a definite edge over Jeffreys' prior in this respect. Also, the credible intervals based on these reference priors seem superior to similar intervals based on certain divergence measures.