Distribution and Variability of n‐Alkanes in Epicuticular Waxes of Sedum Species from the Central Balkan Peninsula: Chemotaxonomic Importance

For the first time, the n‐alkane distribution and variability of the epicuticular waxes within 22 Sedum taxa was reported with focus on the chemotaxonomy of native Sedum representatives from the central Balkan Peninsula, compared to their relations with four other species of the Crassulaceae family. By GC/MS and GC‐FID identification and quantification, it was established that n‐alkanes C₂₇, C₂₉, C₃₁, C₃₃, and C₃₅ were the dominant constituents of the examined epicuticular wax samples. Applying multivariate statistical analyses including agglomerative hierarchical clustering (AHC) and principal component analysis (PCA), the relation according to the n‐alkane composition between the examined samples was established. It was shown that the n‐alkane variability of the central Balkan Sedum species was considerable and that n‐alkanes might not be very reliable taxonomic markers for these species.     

利用家蚕杆状病毒表达家蚕肌质网型钙离子ATP酶蛋白

肌质网型钙离子ATP酶(Sacro/endoplasmic reticulum Ca2+-ATPase,Serca)负责将细胞中多余的Ca2+转运并存储于内质网中,从而维持细胞内适宜的Ca2+环境。家蚕Serca创造的细胞内及细胞外Ca2+平衡对家蚕正常生命活动的维持具有重要作用。由于Serca分子量较大并具有10次跨膜结构,很难在大肠杆菌表达系统中表达。为了获得具有生物学活性的重组Serca蛋白,利用p Fast Bac Dual载体构建了用于表达egfp和serca的双元杆状病毒表达载体,转染细胞后获得重组病毒,将重组病毒感染细胞后,成功地在细胞中表达了EGFP和Serca。通过荧光观察及Western blotting分析表明,感染后细胞中Serca和EGFP表达模式一致,从感染后48 h开始表达,在感染后96 h表达量最大。对获得的重组蛋白进行酶活分析,发现感染后48 h至120 h的细胞Serca酶活显著提高。表明具有生物学活性的Serca在此系统中成功获得表达,为深入研究Serca蛋白的功能奠定了基础。     

Multivariate Polya and Inverse Polya Distributions of Order k

Multivariate Polya and inverse Polya distributions of order k are derived by means of generalized urn models and by compounding the type II multinomial and multivariate negative binomial distributions of order k of PHILIPPOU , ANTZOULAKOS and TRIPSIANNIS (1990, 1988), respectively, with the Dirichlet distribution. It is noted that the above two distributions include as special cases a multivariate hypergeometric distribution of order k, a negative one, an inverse one, a negative inverse one and a discrete uniform of the same order. The probability generating functions, means, variances and covariances of the new distributions are obtained and five asymptotic results are established relating them to the above-mentioned multinomial and multivariate negative binomial distributions of order k, and to the type II negative binomial and the type I multivariate Poisson distributions of order k of PHILIPPOU (1983), and PHILIPPOU , ANTZOULAKOS and TRIPSIAN-NIS (1988), respectively. Potential applications are also indicated. The present paper extends to the multivariate case the work of PHILIPPOU , TRIPSIANNIS and ANTZOULAKOS (1989) on Polya and inverse Polya distributions of order k..     

A “Natural” Agglomerative Clustering Method for Biology

The authors consider that cluster analysis does not objectivize but represents the biologist's subjectivity as to (1) characters considered to be significant and to (2) the way of classification. The latter, however, in authors' opinion, must be specific to the field of application. To this effect some methods are suggested for biology. The methods originate in improvements or transformation of Buser and Baroni-Urbani's method, as well as Watanabe's method, and have the property of processing overall information with no loss or distortion. An agglomerative method which yields a necessarily unique result is suggested, being considered by the authors as a homologue of Watanabe's divisive method. The methods proposed are studied using examples logically constructed. These examples can provide from biology, especially from ecology.     

甘肃酒泉青铜时代人类头骨种系类型的研究

本文对甘肃酒泉干骨崖墓地人头骨的种系类型特征进行了多元分析,全部头骨接近蒙古人种东亚类型,未发现具有西方人种特征的头骨。     

Three Ways of Implementing the EM Algorithm when Parameters are not Identifiable

We consider situations where the incomplete nature of the observed data causes identifiability problem. Rather than imposing identifiability constraints on the parameters and then implement the EM algorithm subject to these constraints, we argue that for certain problems, an easier option is to ignore the constraints during the M‐steps of the EM procedure. We also suggest a way of carrying out constrained maximization approximately by using Cox and Wermuth's (1990) method for approximating the constrained maximizers from the unconstrained ones at each M‐step. The simplicity and validity of the unconstrained EM procedure are demonstrated using three examples involving bivariate probit regression, multivariate normal order statistics model and the multinominal distribution. Potential applications to more complicated models are also outlined.     

On the Numerical Availability of Multiple Comparison Procedures

In the past many multiple comparison procedure were difficult to perform. Usually, such procedures can be traced back to studentized multiple contrast tests. Numerical difficulties restricted the use of the exact procedures to simple, commonly balanced, designs. Conservative approximations or simulation based approaches have been used in the general cases. However, new efforts and results in the past few years have led to fast and efficient computations of the underlying multidimensional integrals. Inferences for any finite set of linear functions of normal means are now numerically feasible. These include all‐pairwise comparisons, comparisons with a control (including dose‐response contrasts), multiple comparison with the best, etc. The article applies the numerical progress on multiple comparisons procedures for common balanced and unbalanced designs within the general linear model.     

Estimation of a Joint Distribution Function with Multivariate Interval‐Censored Data when the Nonparametric MLE is not Unique

A nonparametric estimator of a joint distribution function F₀ of a d‐dimensional random vector with interval‐censored (IC) data is the generalized maximum likelihood estimator (GMLE), where d ≥ 2. The GMLE of F₀ with univariate IC data is uniquely defined at each follow‐up time. However, this is no longer true in general with multivariate IC data as demonstrated by a data set from an eye study. How to estimate the survival function and the covariance matrix of the estimator in such a case is a new practical issue in analyzing IC data. We propose a procedure in such a situation and apply it to the data set from the eye study. Our method always results in a GMLE with a nonsingular sample information matrix. We also give a theoretical justification for such a procedure. Extension of our procedure to Cox's regression model is also mentioned.