民办幼儿园教师专业素养培训方式实验研究

随着现代教育的发展，提升幼儿园教师专业素养已成为促进学前教育发展的必然要求。以探究民办幼儿园教师专业素养为视角，提出通过干预行为提升教师专业素养水平的构想。实验随机选取成都市某民办幼儿园的20名教师为实验组，再选取与其办园环境、办园背景相似的另一所民办幼儿园的20名教师为对照组，对实验园教师的专业理念与师德、专业知识、专业能力3个维度进行干预。实验结果表明：与对照园相比，实验园教师的专业能力提升显著；与实验园实验前后相比，教师在专业知识、专业能力维度及专业素养总体水平方面均有提升。对教师培训的具体建议为：（1）单一与混合相结合的培训方式对提升民办幼儿园教师专业素养总体水平有现实意义；（2）民办幼儿园教师专业知识的提升需理论培训与自主学习相结合；（3）专家"现场诊断-指导式"培训方式对提升民办幼儿园教师专业能力有显著作用。综上，建议民办幼儿园在了解本园教师专业素养水平的基础上，针对教师专业素养的不同方面，分别采取不同的有效培训方式。     

Multiparameter evidence synthesis in epidemiology and medical decision-making: current approaches

Summary.  Alongside the development of meta-analysis as a tool for summarizing research literature, there is renewed interest in broader forms of quantitative synthesis that are aimed at combining evidence from different study designs or evidence on multiple parameters. These have been proposed under various headings: the confidence profile method, cross-design synthesis, hierarchical models and generalized evidence synthesis. Models that are used in health technology assessment are also referred to as representing a synthesis of evidence in a mathematical structure. Here we review alternative approaches to statistical evidence synthesis, and their implications for epidemiology and medical decision-making. The methods include hierarchical models, models informed by evidence on different functions of several parameters and models incorporating both of these features. The need to check for consistency of evidence when using these powerful methods is emphasized. We develop a rationale for evidence synthesis that is based on Bayesian decision modelling and expected value of information theory, which stresses not only the need for a lack of bias in estimates of treatment effects but also a lack of bias in assessments of uncertainty. The increasing reliance of governmental bodies like the UK National Institute for Clinical Excellence on complex evidence synthesis in decision modelling is discussed.     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

立足高起点发展新方向培养应用型复合型人才——对我院法学专业教学的认识及建议

我院法学专业培养目标是为社会培养应用型、复合型人才 ,针对实际情况 ,作者提出应改革教学内容 ,优化课程体系 ;改革教学方法 ,完善教学手段 ;提高教师业务水平 ,加强学术梯队建设等建议。     

Variance (Non) Causality in Multivariate GARCH

This paper extends the current literature on the variance-causality topic providing the coefficient restrictions ensuring variance noncausality within multivariate GARCH models with in-mean effects. Furthermore, this paper presents a new multivariate model, the exponential causality GARCH. By the introduction of a multiplicative causality impact function, the variance causality effects becomes directly interpretable and can therefore be used to detect both the existence of causality and its direction; notably, the proposed model allows for increasing and decreasing variance effects. An empirical application evidences negative causality effects between returns and volume of an Italian stock market index future contract.     

Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t-distribution

Summary . A fairly general procedure is studied to perturb a multivariate density satisfying a weak form of multivariate symmetry, and to generate a whole set of non-symmetric densities. The approach is sufficiently general to encompass some recent proposals in the literature, variously related to the skew normal distribution. The special case of skew elliptical densities is examined in detail, establishing connections with existing similar work. The final part of the paper specializes further to a form of multivariate skew t -density. Likelihood inference for this distribution is examined, and it is illustrated with numerical examples.     

Multivariate outlier detection in incomplete survey data: the epidemic algorithm and transformed rank correlations

Summary.  As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project.     

刘熙载楚辞学的研究方法

刘熙载在研究楚辞时,运用了以意逆志法、多重比较法、举借概括法等方法,从而形成了一套颇具特色的文学批评法。     

约束优化问题的异步并行拟牛顿方法

提出了一种求解等式约束优化问题的异步并行拟牛顿方法 .若假设目标函数 f和约束函数h至少三次连续可微 ,且△h(x)对任意x∈Rn 均为满秩矩阵 ,证明了所提出的异步并行算法是 q—超线性收敛的 .     

毛泽东农村调查研究方法简论

毛泽东农村调查研究方法是一个完整的科学体系,马克思的辩证唯物主义和历史唯物主义是毛泽东农村调查研究方法的理论基础,即方法论。矛盾分析法和阶级分析法是毛泽东农村调查研究的基本方法。典型调查、类型调查、普遍调查、实地访问、开调查会、表格调查法、文献法、历史法等是毛泽东农村调查研究的方式和具体方法。