Use of spot measurements for assessing residential ELF magnetic field exposure: a validity study

The purpose of this study was to evaluate residential short term "spot" measurements as surrogates for long term personal magnetic field (MF) exposure. In an epidemiological study on birth weight and pregnancy delay, MF exposure was assessed by taking five spot measurements in each room. For a subsample of 30 subjects 24 h personal MF measurements were made, and the following exposure metrics were calculated: 24 h arithmetic mean, 24 h median, percentage of time above 0.15 microT, and percentage of time above 0.29 microT. The 24 h exposure metrics were used as gold standards, when evaluating the validity of various summary measures calculated from spot measurements for assessing personal exposure. Based on Spearman correlation coefficient (r), specificity and sensitivity, the average of the spot measurements of a residence resulted in least exposure measurement error (misclassification). Also the above bed spot value correlated better with the 24 h metrics than any room average. Spot measurements performed about equally well in predicting different types of exposure metrics.     

Generalized character process models: estimating the genetic basis of traits that cannot be observed and that change with age or environmental conditions

The genetic analysis of characters that change as a function of some independent and continuous variable has received increasing attention in the biological and statistical literature. Previous work in this area has focused on the analysis of normally distributed characters that are directly observed. We propose a framework for the development and specification of models for a quantitative genetic analysis of function-valued characters that are not directly observed, such as genetic variation in age-specific mortality rates or complex threshold characters. We employ a hybrid Markov chain Monte Carlo algorithm involving a Monte Carlo EM algorithm coupled with a Markov chain approximation to the likelihood, which is quite robust and provides accurate estimates of the parameters in our models. The methods are investigated using simulated data and are applied to a large data set measuring mortality rates in the fruit fly, Drosophila melanogaster.     

Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies

This paper presents a method for analysing longitudinal data when there are dropouts. In particular, we develop a simple method based on generalized linear mixture models for handling nonignorable dropouts for a variety of discrete and continuous outcomes. Statistical inference for the model parameters is based on a generalized estimating equations (GEE) approach (Liang and Zeger, 1986). The proposed method yields estimates of the model parameters that are valid when nonresponse is nonignorable under a variety of assumptions concerning the dropout process. Furthermore, the proposed method can be implemented using widely available statistical software. Finally, an example using data from a clinical trial of contracepting women is used to illustrate the methodology.     

Regulatory Perspectives on the Significance of Ecological Changes as Reported in Ecological Risk Assessments

A broad range of perspectives exists regarding the interpretation of potentially adverse ecological changes in ecological risk assessments conducted under Superfund and RCRA. While USEPA's Proposed Guidelines for Ecological Risk Assessment recommend determining whether predicted changes are adverse based on the nature of effects, intensity of effects, spatial scale, temporal scale, and potential for recovery, the guidelines do not provide specific stan dards for judging adversity. Hence, implementation of the proposed guide lines varies with each risk manager's subjective judgments regarding the relative importance of each of these five criteria. In an effort to increase consistency in the scientific interpretation of ecological risk assessments, the following practices are recommended. First, measures of effects should focus on levels of ecological organization that are more complex than the individual organ ism. Second, multiple lines of evidence should be evaluated for each assessment endpoint. Third, bioequivalence testing should be used in place of traditional statistical testing (e.g., Student t-test) because the goal of bioequivalence testing is to answer the biologically relevant question of whether measurements differ by, at most, a biologically small amount. Fourth, in defining biologically small differences, site-specific and species specific conditions should be considered to the greatest extent possible. Fifth, where the outcomes of multiple lines of evidence contradict one another, the risk assessor should employ a quantitative approach to weighing the evidence based on the scientific defensibility of each measure of effect.     

Some new results on Cox–Czanner divergence and their applications in survival studies

In the present communication, we propose a quantile-based measure for the divergence between two survival functions. This can also be used in a dynamic way where the divergence between survival functions varies with time. Several new properties of the proposed measure are investigated with suitable examples. The behavior of the measure for various reliability models is also investigated. A real data analysis is employed to compare the relative efficacy of two treatment groups using the proposed divergence measure.     

The analysis of oligonucleotide preparations by fractal measures

In this paper we put forward improved mathematical methods for detecting synthesis parameters in connection with analyzing crude products of chemically synthesized oligonucleotides. The crude products experimentally sampled are separated by high-performance capillary electrophoresis and ion-exchange high-performance liquid chromatography. The measured separation profiles of experimental syntheses can be expressed as target and nontarget yields; they are characterized by a few parameters. These parameters account for nonlinear synthesis equations that are solvable by employing iteration procedures. We provide here a theoretical as well as computational analysis based upon specific models for stepwise chain growth. Under nonconstant (nonuniform) conditions we use here an exponential form of growth, with different expressions for calculating the fractal dimension of the biochemical process under study. Step lengths of parameter variations in an interval of finite length have to be adjusted properly to find convergent solutions in a mathematical, regularly four-dimensional parameter space. It is conceivable to have most, if not all, of the calculating and plotting carefully done by a computer. This analysis represents the experimental situation up to 65-mer target oligonucleotides analyzed so far. We thus obtain the dynamics of the polymerization process limited in number by fractal models. The advantage, calculating these new methods as compared to qualitatively judged experimental methods, lies in the satisfactory evaluation of crude products, also of large amounts, of syntheses of these biopolymers. © 1998 John Wiley & Sons, Inc. Biopoly 45: 361–379, 1998     

珍稀濒危植物翅果油树的生物学特性及其保护

翅果油树为我国特有植物,已被列为国家二级重点保护树种。本文较系统地综述了翅果油树的生物学特性,包括其外部形态、内部结构、染色体核型、生长特性、地理分布、生态学和群落学特性、根瘤固氮活性及化学成分等。文章还分析了翅果油树濒危的可能原因并提出了保护措施。