关于有限群的可解性

利用极大子群的几乎正规的概念得到了有限群为可解群的若干充要条件．     

载体催化元件恒温检测甲烷浓度的研究

基于载体催化元件检测甲烷浓度的基本原理,提出了采用载体催化元件和参比元件组成惠斯登测量电桥,运用温度自动控制系统达到恒定甲烷无焰燃烧温度,实现甲烷浓度的测量。扩展了采用载体催化元件测量甲烷浓度时的测量范围,减轻了催化剂的高温烧结和挥发现象,延长了载体催化元件的使用寿命。并建立了相应的温度自动控制和甲烷浓度测量的数学模型。     

受内压圆柱筒体开孔-接管区应力集中的有限元分析

利用 ANSYS有限元分析软件通过三个算例对圆柱形筒体小开孔直接管区、大开孔直接管区、大开孔斜接管区的应力分布状况进行了研究 .从中了解到了最大第一主应力的变化规律 ,得出在弹性范围内的应力集中系数 ,并且得到ASME规范中的算式较好的验证     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

Interpreting DNA Mixtures with Related Contributors in Subdivided Populations

Abstract.  In this paper, we study the statistical interpretation of forensic DNA mixtures with related contributors in subdivided populations. Compact general formulae for match probabilities are obtained for two situations: a relative of one tested person is an unknown contributor of a DNA mixture; and two related unknowns are contributors. The effect of kinship and population structure is illustrated using a real case example.     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

奇正相生 意趣盎然——当代西方建筑赏析

当代西方一些著名的建筑大师时常在自己的作品中运用斜向构图要素插入到方正的网络之中,并借正和斜的强烈对比而取得意想不到的效果。这种手法不仅有悖于我国传统的审美观念,而且就是在西方传统的建筑构图法则中也不多见。本文就具有代表性的作品作深入细致的分析,以期阐明这种方法的运用是如何赋予作品以生机和活力的。应放手吸取西方当代建筑师行之有效的观念与方法,以使建筑创作更富有时代性。     

数值解法中的单元形状函数技巧

本文介绍从一组互不相关的函数中推导数值法中单元形状函数的简便而有效的算法,以特定的一维内插方法导出各种二维、三维的内插方法,它们对奇异性的模拟是有益的;为了适用于延伸到无限远的单元,假设形状函数类似于Lagrange多项式,但包含了一个按指数衰减的项。     

微量元素与人体健康

本文主要阐述微量元素在人体中的生理作用、需要量及与人体健康和疾病的关系,同时指出了科技工作者在这一领域中所要继续开展的工作.     

Creating a reference to a complex emergency situation using time series methods: war in Guinea-Bissau 1998-1999

Impacts of complex emergencies or relief interventions have often been evaluated by absolute mortality compared to international standardized mortality rates. A better evaluation would be to compare with local baseline mortality of the affected populations. A projection of population-based survival data into time of emergency or intervention based on information from before the emergency may create a local baseline reference. We find a log-transformed Gaussian time series model where standard errors of the estimated rates are included in the variance to have the best forecasting capacity. However, if time-at-risk during the forecasted period is known then forecasting might be done using a Poisson time series model with overdispersion. Whatever, the standard error of the estimated rates must be included in the variance of the model either in an additive form in a Gaussian model or in a multiplicative form by overdispersion in a Poisson model. Data on which the forecasting is based must be modelled carefully concerning not only calendar-time trends but also periods with excessive frequency of events (epidemics) and seasonal variations to eliminate residual autocorrelation and to make a proper reference for comparison, reflecting changes over time during the emergency. Hence, when modelled properly it is possible to predict a reference to an emergency-affected population based on local conditions. We predicted childhood mortality during the war in Guinea-Bissau 1998-1999. We found an increased mortality in the first half-year of the war and a mortality corresponding to the expected one in the last half-year of the war.