获取复配农药最佳增效配方的一种简易方法

借鉴共毒因子法评价农药复配联合作用的思想,将参与复配的单剂引起25％死亡率的剂量定为零水平,利用二次回归通用旋转组合设计安排实验研究氯氰菊酯和喹硫磷复配对斜纹夜蛾（Spodoptera litura）2龄幼虫的增效作用,得出杀虫剂使用量与斜纹夜蛾幼虫死亡率机率值之间的关系,从共毒系数（CTC）的计算公式推导出共毒系数与杀虫混剂中两单剂使用浓度N1、N2之间的数学关系,CTC＝100／N1／α N2/b（α、b分别为氯氰菊酯和喹硫磷的LC50）,进而确定最优化问题的目标函数j=N1/α＋N2／b,利用国际统计分析软件SAS的NLP过程求最大共毒系数和最优配方,所得结论与共毒系数法一致。     

适用于获取最优化配方的一种算法

本文应用印楝种仁提取物（F3）与敌敌畏混配为例,以斜纹夜蛾（Spodopteralitura）为目标害虫,介绍一种适用于获取最优化配方的算法,在二次通用回归旋转组合设计的基础上,经参数辨识,获取二次回归方程,经失拟性、回归显著性检验,本方程基本能够反映杀虫剂用量与斜纹夜蛾幼虫死亡机率值之间的关系．在害虫防治实践中,要求在防治费用最小的基础上,目标害虫有最大的死亡率.因此,以防治目标害虫的费用作为优化算法的目标函数,以害虫死亡机率值最大作为约束条件,有如下的一组优化算式为目标函数约束条件式中a1,a2分别为参试杀虫剂1,2最低用量,b1,b2则为相应的最高用量．C1,C2分别为杀虫剂1,2的单价,N1,N2为杀虫剂l,2的用量．Y为目标害虫死亡机率值回归方程．本文所依据的试验设计中,以对数函数关系变换编码值与使用浓度之间的关系,所以应用拉格朗日求极值原理求取最优化配方．由计算所得的混配比例与其他方法所获结果一致．     

Online Calculation of Efficient Designs for Multi‐Factor Models

A class of “incomplete” multivariate polynomial regression models on the q‐cube is considered. A simple algorithm for the determination of D‐optimal product designs is developed and illustrated by specific examples. The methods are implemented on an IBM compatible PC under MS‐DOS and provide an effective method for the numerical solution of an optimal design problem, which was unsolved in nearly all cases of practical interest.     

Covariate-adjusted varying coefficient models

Covariate-adjusted regression was recently proposed for situations where both predictors and response in a regression model are not directly observed, but are observed after being contaminated by unknown functions of a common observable covariate. The method has been appealing because of its flexibility in targeting the regression coefficients under different forms of distortion. We extend this methodology proposed for regression into the framework of varying coefficient models, where the goal is to target the covariate-adjusted relationship between longitudinal variables. The proposed method of covariate-adjusted varying coefficient model (CAVCM) is illustrated with an analysis of a longitudinal data set containing calcium absorbtion and intake measurements on 188 subjects. We estimate the age-dependent relationship between these two variables adjusted for the covariate body surface area. Simulation studies demonstrate the flexibility of CAVCM in handling different forms of distortion in the longitudinal setting.     

wombsoft: an r package that implements the Wombling method to identify genetic boundary

wombsoft is an r package that analyses individually georeferenced multilocus genotypes for the inferences of genetic boundaries between populations. It is based on the Wombling method that estimates the systemic function by looking for the local variation of the allele frequencies. This study presents an original way of estimating the systemic function, based on the local polynomial regression, and a binomial test to assess the significance of boundaries. The method applies to codominant or dominant markers and allows for missing data. The software r can be downloaded from http://www.r‐project.org/ and wombsoft from http://www‐leca.ujf‐grenoble.fr/logiciels.htm or http://www.r‐project.org/ .     

Geographical variation in age at menarche in Britain

The geographical distribution of age at menarche in great Britain is analysed in two successive generations. It appears that the variances for age at menarche are equal throughout the country. The means, however, show significant and complicated patterns of regional variation. In the southern and eastern parts of the country, menarche was earlier than in the northern parts in both generations. This patterning is not due to social class differentiation. Except for the sparsely populated areas in northern and western Scotland and for the extreme south-western parts of England and Wales all areas show evidence of a decline in age at menarche from the mothers' to the daughters' generation.     

A calibration method to generate seasonal hatching profiles for the fiddler crabs Uca pugnax (Smith, 1870) and Uca minax (LeConte, 1855) (Decapoda : Brachyura)

A statistical method for generating seasonal egg hatching profiles is applied to the brachyuran crabs Uca pugnax (Smith) and U. minax (LeConte) in New Jersey. Calibration experiments quantified the time course of egg development, using serial egg sampling at 1- to 2- day intervals from marked ovigerous females maintained in cages in the field. Egg stage was ranked from 1 to 10, based on morphological changes during development. Equations for predicting the number of days remaining until hatching from egg developmental stage were obtained from the calibration experiments, using stepwise polynomial regression. To cover the reproductive season, three consecutive calibration experiments using 15 or more females were run for U. pugnax; two for U. minax. Significant seasonal differences in the time course of egg development were detected. Weekly collections of females for each species were made; the date of larval release for each ovigerous female was predicted from the proximate calibration equation, yielding weekly hatching profiles. Weekly hatching profiles were summed to obtain seasonal hatching profiles. The average number of broods produced per female over the reproductive season was 1.9 for U. pugnax and 1.6 for U. minax. Hatching peaks for both species were associated with spring tides. The merits of this and other methods used to estimate daily variation in egg hatching of crabs are discussed.     

Using local correlation in kernel-based smoothers for dependent data

We consider the general problem of smoothing correlated data to estimate the nonparametric mean function when a random, but bounded, number of measurements is available for each independent subject. We propose a simple extension to the local polynomial regression smoother that retains the asymptotic properties of the working independence estimator, while typically reducing both the conditional bias and variance for practical sample sizes, as demonstrated by exact calculations for some particular models. We illustrate our method by smoothing longitudinal functional decline data for 100 patients with Huntington's disease. The class of local polynomial kernel-based estimating equations previously considered in the literature is shown to use the global correlation structure in an apparently detrimental way, which explains why some previous attempts to incorporate correlation were found to be asymptotically inferior to the working independence estimator.     

A matrix‐based method of moments for fitting the multivariate random effects model for meta‐analysis and meta‐regression

Multivariate meta‐analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between‐study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta‐regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example.     

用科学试验的原理和方法进行食用菌实验教学

分析原有食用菌实验教学中可能存在的问题,提出食用菌科学试验课程的任务,陈述在食用菌实验教学中进行科学试验的具体内容和方法,讨论实验教学中进行科学试验的目的意义。     

Cubic regression-based degree of correction predicts the performance of whole bisulfitome amplified DNA methylation analysis

Epigenetic mechanisms, including DNA methylation, are important determinants in development and disease. There is a need for technologies capable of detecting small variations in methylation levels in an accurate and reproducible manner, even if only limited amounts of DNA are available (which is the case in many studies in humans). Quantitative methylation analysis of minute DNA amounts after whole bisulfitome amplification (qMAMBA) has been proposed as an alternative, but this technique has not been adequately standardized and no comparative study against conventional methods has been performed, that includes a wide range of methylation percentages and different target assays. We designed an experiment to compare the performance of qMAMBA and bisulfite-treated genomic (non-amplified) DNA pyrosequencing. Reactions were performed in duplicate for each technique in eight different target genes, using nine artificially constructed DNA samples with methylation levels ranging between 0% and 100% with intervals of 12.5%. Cubic polynomial curves were plotted from the experimental results and the real methylation values and the resulting equation was used to estimate new corrected data points. The use of the cubic regression-based correction benefits the accuracy and the power of discrimination in methylation studies. Additionally, dispersion of the new estimated data around a y = x line (R²) served to fix a cutoff that can discriminate, with a single 9-point curve experiment, whether whole bisulfitome amplification and subsequent qMAMBA can produce accurate methylation results. Finally, even with an optimized reagent kit, DNA samples subjected to whole bisulfitome amplification enhance the preferential amplification of unmethylated alleles, and subtle changes in methylation levels cannot be detected confidently.     

Cubic regression-based degree of correction predicts the performance of whole bisulfitome amplified DNA methylation analysis

Epigenetic mechanisms, including DNA methylation, are important determinants in development and disease. There is a need for technologies capable of detecting small variations in methylation levels in an accurate and reproducible manner, even if only limited amounts of DNA are available (which is the case in many studies in humans). Quantitative methylation analysis of minute DNA amounts after whole bisulfitome amplification (qMAMBA) has been proposed as an alternative, but this technique has not been adequately standardized and no comparative study against conventional methods has been performed, that includes a wide range of methylation percentages and different target assays. We designed an experiment to compare the performance of qMAMBA and bisulfite-treated genomic (non-amplified) DNA pyrosequencing. Reactions were performed in duplicate for each technique in eight different target genes, using nine artificially constructed DNA samples with methylation levels ranging between 0% and 100% with intervals of 12.5%. Cubic polynomial curves were plotted from the experimental results and the real methylation values and the resulting equation was used to estimate new corrected data points. The use of the cubic regression-based correction benefits the accuracy and the power of discrimination in methylation studies. Additionally, dispersion of the new estimated data around a y = x line (R²) served to fix a cutoff that can discriminate, with a single 9-point curve experiment, whether whole bisulfitome amplification and subsequent qMAMBA can produce accurate methylation results. Finally, even with an optimized reagent kit, DNA samples subjected to whole bisulfitome amplification enhance the preferential amplification of unmethylated alleles, and subtle changes in methylation levels cannot be detected confidently.