美国大学本科教育研究

本文分析了几所著名的美国大学本科教学的课程体系及教学计划 ,总结了其基本共性 ,同时分析了各大学的教学特色。通过对各大学电子工程类专业的教学计划进行剖析 ,给出了公共基础、专业基础、专业核心、专业选修课规定的课程及学分 ,并与我国的大学本科教学计划进行比较 ,提出了我国大学本科教育应改进的几个方面。     

论应用写作中的语篇思维模式

思维是写作过程运思阶段的核心 ,应用文的语言和结构是思维的外化形式 ,应用文体有特殊的语篇思维模式 ,本文认为大部分应用文体呈现出直线型语篇思维模式 ;并探讨了应用写作实践中常见的语篇思维模式的特点及相关思维能力的培养     

Markov Properties for Acyclic Directed Mixed Graphs

We consider acyclic directed mixed graphs, in which directed edges ( x → y ) and bi-directed edges ( x ↔ y ) may occur. A simple extension of Pearl's d -separation criterion, called m -separation, is applied to these graphs. We introduce a local Markov property which is equivalent to the global property resulting from the m -separation criterion for arbitrary distributions.     

A Sparse Implementation of the Average Information Algorithm for Factor Analytic and Reduced Rank Variance Models

Factor analytic variance models have been widely considered for the analysis of multivariate data particularly in the psychometrics area. Recently Smith, Cullis & Thompson (2001) have considered their use in the analysis of multi‐environment data arising from plant improvement programs. For these data, the size of the problem and the complexity of the variance models chosen to account for spatial heterogeneity within trials implies that standard algorithms for fitting factor analytic models can be computationally expensive. This paper presents a sparse implementation of the average information algorithm (Gilmour, Thompson & Cullis, 1995) for fitting factor analytic and reduced rank variance models.     

地方理工院校英语专业人才培养研究——英语教师调查篇

教学大纲、课程规划的执行、实现和教师对其的理解有很大关系。文章旨在通过调查，了解地方理工类院校英语教师对英语专业培养模式、课程设置的观点、对学生学业水平的评价和就业需求关注度，以便为此类院校的人才培养、课程规划、课程设置和教学管理提供信息、依据和建议。     

一类非线性混合整规划的无约束连续化解法

将整系数多项式 0 - 1混合整规划问题化成无约束多项式规划问题。通过解该问题 ,能得到原问题的近似解。处理方法的特点是能够直接处理不等式约束情形 ,而不需要先将不等式约束化成等式约束再来处理     

论吴稚晖20世纪初期的科学教育思想

在吴稚晖当时看来,教育是一个国家盛衰的"总因",而配称教育二字者只是科学工艺,近代中国的落后挨打就在于科学工艺发展的迟滞。在批判国内旧式教育的同时,他编报印书,普及科学常识以提高国民素质,鼓吹科学工艺来倡导青年劳作。特别是他创造性发起的留法俭学运动和创办海外中国大学,为近代中国培养了一大批急需的高科技人才,在近代中国教育史、中外文化交流史上写下了光辉的一页。     

Human Salmonellosis: Estimation of Dose-Illness from Outbreak Data

The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al . Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.     

ADDITIVE MODELS WITH PREDICTORS SUBJECT TO MEASUREMENT ERROR

This paper develops a likelihood‐based method for fitting additive models in the presence of measurement error. It formulates the additive model using the linear mixed model representation of penalized splines. In the presence of a structural measurement error model, the resulting likelihood involves intractable integrals, and a Monte Carlo expectation maximization strategy is developed for obtaining estimates. The method's performance is illustrated with a simulation study.     

利用光敏核不育性进行水稻轮回选择的程序探讨

本文对利用光敏核不育性进行水稻轮回选择进行了探讨。提出基本轮回选择方案和综合轮回选择方案。基本轮回选择方案是以一个光敏核不育材料为母本与多个亲本组配构成轮回选择的综合群体,而其后按常规轮回选择法进行育种的方案。综合轮回选择方案是以两个或两个以上的光敏核不育材料作为母体与多个亲本组配,在 F_2代群体中不同质源的优良植株相互交配构成综合群体,其后按基本方案进行的轮回选择。