小型教学用局域网络的快速恢复法

要解决大量学生上机练习时会经常碰见网络系统及软件遭破坏的问题 ,可先利用NORTON软件将硬盘某分区所有资料做成扩展名为 .gho的镜像文件并置于服务器 ,再在dos下通过一张自制的网络启动盘启动终端机与服务器之间的网络 ,并通过网络找到 .gho这个文件 ,以迅速恢复网络与系统和软件包。     

我国西部地区生态环境存在的问题及对策

西部地区虽然经济欠发达,但在我国经济社会发展中占有重要位置。一方面西部地区是我国的重要能源基地,也是长江、澜沧江、黄河、黑河、珠江等大江大河的发源地和主要集水区;另一方面,西部地区野生动植物资源丰富,是我国许多珍稀野生动植物的主要栖息地。因此,西部地区的生态环境建设不仅对西部地区自身发     

浅析建筑市场监理运行现状与对策

文章透析了监理单位的外部管理现状 ,内部运行机制及监理业务的竞争环境 ,并提出了相应的对策与建议     

涂附磨具单位面积CaCO3含量分析方法的改进

以铜试剂代替氰化物作掩蔽剂 ,用EDTA容量法测定涂附磨具单位面积CaCO3 含量 ,获得了满意的效果。     

新形势下的插播型电视教材

探讨了新形势下插播型电视教材的制作与应用 ,为更好地适应现代教育技术发展的需要提供了帮助     

整合教育:高校思想政治教育的新思路——应对高校“两课”教学的离散趋向

我国高校将“两课”作为实施思想政治教育的主战场目前存在的最大问题是教育教学的某些方面出现离散趋向。本文通过对高校“两课”中出现的离散趋向的分析，认为在思想政治教育教学实践中要实施整合教育，并提出整合教育的具体构想。     

Empirical likelihood confidence intervals for the mean of a population containing many zero values

If a population contains many zero values and the sample size is not very large, the traditional normal approximation‐based confidence intervals for the population mean may have poor coverage probabilities. This problem is substantially reduced by constructing parametric likelihood ratio intervals when an appropriate mixture model can be found. In the context of survey sampling, however, there is a general preference for making minimal assumptions about the population under study. The authors have therefore investigated the coverage properties of nonparametric empirical likelihood confidence intervals for the population mean. They show that under a variety of hypothetical populations, these intervals often outperformed parametric likelihood intervals by having more balanced coverage rates and larger lower bounds. The authors illustrate their methodology using data from the Canadian Labour Force Survey for the year 2000.     

蛋白组学方法应用于人肺癌组织蛋白表达的研究

采用蛋白组学方法,利用4例中国肺癌患者的切除肺癌组织测定了磷癌(SQCLC)的蛋白表达 从双向电泳(2-DEgel)切下53个点,49个蛋白与数据库搜索结果吻合。在鉴定的24个蛋白中,17个蛋白有报道是与肺癌相关的蛋白其7个蛋白与人类其它癌症相关。所建立的蛋白组学方法能够用于建立一种基于组织的化验方法,发现肺癌患者组织中表达的蛋白标记物以用于癌症的分子学诊断。     

A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

Efficient designs based on orthogonal arrays of type I and type II for experiments using units ordered over time or space

For a wide variety of applications, experiments are based on units ordered over time or space. Models for these experiments generally may include one or more of: correlations, systematic trends, carryover effects and interference effects. Since the standard optimal block designs may not be efficient in these situations, orthogonal arrays of type I and type II, which were introduced in 1961 by C.R. Rao [Combinatorial arrangements analogous to orthogonal arrays, Sankhya A 23 (1961) 283–286], have been recently used to construct optimal and efficient designs for many of these experiments. Results in this area are unified and the salient features are outlined.