普通野生稻和药用野生稻种子休眠性的研究

对普通野生稻和药用野生稻种子休眠的原因进行了探讨,表明野生稻种的遗传特性、形态性状、颖壳的透性和种子的生理特性与种子休眠有关。研究结果为打破野生稻种子休眠、提高其发茅力提供了依据和适宜的方法。     

Uncertainty Analysis for Computer Model Projections of Hurricane Losses

Projecting losses associated with hurricanes is a complex and difficult undertaking that is wrought with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from 2 to 3 billion dollars in losses late on August 12 to a peak of 50 billion dollars for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm hit the resort areas of Charlotte Harbor near Punta Gorda and then went on to Orlando in the central part of the state, with early poststorm estimates converging on a damage estimate in the 28 to 31 billion dollars range. Comparable damage to central Florida had not been seen since Hurricane Donna in 1960. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has recognized the role of computer models in projecting losses from hurricanes. The FCHLPM established a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a Holland B parameter hurricane wind field model. Uncertainty analysis quantifies the expected percentage reduction in the uncertainty of wind speed and loss that is attributable to each of the input variables.     

A general approximation to quantiles

For many continuous distributions, a closed-form expression for their quantiles does not exist. Numerical approximations for their quantiles are developed on a distribution-by-distribution basis. This work develops a general approximation for quantiles using the Taylor expansion. Our method only requires that the distribution has a continuous probability density function and its derivatives can be derived to a certain order (usually 3 or 4). We demonstrate our unified approach by approximating the quantiles of the normal, exponential, and chi-square distributions. The approximation works well for these distributions.     

佛山市教师阅读现状调查

学校层次对教师的阅读有明显的影响．总体上．大学教师纸质图书的阅读率高于中学教师．中学教师的阅读率高于小学教师，专著和专业期刊的阅读率情况与此相似。性别和年龄因素对阅读也有一定的影响；而网络在线阅读将成为最有影响力的阅读方式。     

CET阅读理解题:问题与方法(二)

本文通过对CET阅读理解考题、提问(问题)以及原文和提问中一些关键词语之间的内含百分比进行分析和对比,探索如何准确解题的方法与捷径。     

Computation of the percentage points and the power for the two-sided Kolmogorov-Smirnov one sample test

Two recursive schemes are presented for the calculation of the probabilityP(g(x)≤S _n (x)≤h(x) for allx∈®), whereS _n is the empirical distribution function of a sample from a continuous distribution andh, g are continuous and isotone functions. The results are specialized for the calculation of the distribution and the corresponding percentage points of the test statistic of the two-sided Kolmogorov-Smirnov one sample test. The schemes allow the calculation of the power of the test too. Finally an extensive tabulation of percentage points for the Kolmogorov-Smirnov test is given.     

A modified Kolmogorov-Smirnov test for a rectangular distribution with unknown parameters: Computation of the distribution of the test statistic

A recursive scheme for the calculation of the distribution of the test statistic of a modified Kolmogorov-Smirnov-test for a rectangular distribution with unknown parameters is given.     

Bayesian model selection for join point regression with application to age-adjusted cancer rates

Summary.  The method of Bayesian model selection for join point regression models is developed. Given a set of K +1 join point models M ₀,  M ₁, …,  M _K with 0, 1, …,  K join points respec-tively, the posterior distributions of the parameters and competing models M _k are computed by Markov chain Monte Carlo simulations. The Bayes information criterion BIC is used to select the model M _k with the smallest value of BIC as the best model. Another approach based on the Bayes factor selects the model M _k with the largest posterior probability as the best model when the prior distribution of M _k is discrete uniform. Both methods are applied to analyse the observed US cancer incidence rates for some selected cancer sites. The graphs of the join point models fitted to the data are produced by using the methods proposed and compared with the method of Kim and co-workers that is based on a series of permutation tests. The analyses show that the Bayes factor is sensitive to the prior specification of the variance σ ², and that the model which is selected by BIC fits the data as well as the model that is selected by the permutation test and has the advantage of producing the posterior distribution for the join points. The Bayesian join point model and model selection method that are presented here will be integrated in the National Cancer Institute's join point software ( http://www.srab.cancer.gov/joinpoint/ ) and will be available to the public.     

鲤鱼胚胎冷却至-196℃的试验

鱼类胚胎的低温保存是世界范围内尚未解决的课题,在对鲤鱼胚胎低温保存的初步试验中,我们发现在溶液冰点至-60℃范围内,降温速率对胚胎存活率来说是个决定性因素。如降温速率大于0.5℃/min,胚胎很难存活,而最佳降温速率应小于0.07℃/min,对于鱼类胚胎保存而言,慢复温是比较合适的。在我们的试验研究中,若以2.0mol/LDMSO为抗冻剂,降温速率为0.07℃/min,复温速率为8℃/min时,兴国紅鲤尾芽期胚胎经降温至液氮温度(-196℃),并保存一段时间后复温,仍能存活并孵化为幼鱼。试验达到的最大存活率为25%,出苗率为18%。     

Charts for finding upper percentage points of Student's t in the range .01 to .00001

The Bonferroni t-statistic is a versatile tool in multiple comparisons problems. The need for "oddball percentage points" may lead to extensive tables or heavy computation. Charts of t_p as a function of log p enable near two-decimal accuracy for any percentage point between .01 and .00001