两互穿电子注-等离子体互作用的相对性理论

由两个等密度、反向电子注与重背景离子互作用所产生的电子注-等离子体互作用已经在理论上和实验上进行了研究。与文献[1]和[2]不同,本文提出一个较少限制的模型来讨论此种互作用机理的特性.该模型简略地示于图1。应用扰动理论,将已有的非相对论性模型推广应用于相对论性电子注和相对论效应对电子注-等离子体互作用的影响。此外已有的模型是被限制于等速、反向电子注在重背景离子等离子体中的互作用。本文根据相对论效应把该模型推广应用于非等速、平行或不平行的两个电子注。这个广义的理论不仅明显地显示了相对论效应.而且便于与熟悉的器件和过程,诸如行波管、邦内曼(Buncman)不稳定性以及皮尔斯(Picrcc}不稳定性相比较。导出了相对论性色散方程,并从这一相对论性互作用出发提出了一种新型自由电子激光。     

浅论一维透射光栅的性能

本文对一维透射光栅话线的衍射角、强度、谱线宽度、色散率、分辩本领等方面的决定因素和性能特点进行了论证。     

非均匀脊波导的横向等效电路分析

均匀平板传输线中的不连续性等效电容已经有了比较满意的求法.由此所得的电容值可应用于均匀脊波导的截止波长的计算.本文考虑含有两种不同介质的脊波导的情况,求得截止和导波状态下横向等效电路中的不连续性等效电容.并由横向谐振法推出这种不均匀情况下脊波导的截止波长和色散关系.     

用固体分散法提高磺胺嘧啶片溶出速度的研究

为了提高磺胺嘧啶（SD）在水中的溶解度、溶出速度,加速其在体内的崩解、溶出、吸收过程,达到速效、高效的目的,以PEG－6000、尿素等材料为载体,采取溶剂熔融法,制备SD的固体分散体,分别测定了固体分散体与原料药的溶解度以及固体分散体片剂与普通片剂的溶出度和溶出速率,固体分散体片剂的溶出度均达到99．0％以上,而普通片剂的最大熔出度为26％,方差分析固体分散体片剂组与普通片剂组具有极显著差异（P＜0．01）,固体分散体能显著提高血的溶解度和溶出速度。     

大气中的光现象

从小学自然到初、高中（包括各类职业技术学校）物理课本中屡屡出现海市蜃景、旭日与夕阳、虹和霓以及峨嵋佛光等大气中光现象的内容．课本中多以定性描述为主,缺乏定量讨论,相关数据也比较分散．本文着重对旭日与夕阳、虹和霓进行定量的讨论,以加深对这些现象的认识．     

继承和发扬民族音乐的优秀传统——重读毛泽东同志《在延安文艺座谈会上的讲话》

《在延安文艺座谈会上的讲话》是毛泽东同志根据马列主义的基本原理,依据对我国文艺事业的实事求是的调查研究和客观分析而写成的一篇杰出文献,其中所阐述的对音乐文化遗产的"继承与借鉴"这个问题的看法,对我们今天继承和发扬民族音乐的优秀传统,仍然具有重大的现实意义。     

Re-weighting estimation of the coefficients in the varying coefficient model with heteroscedastic errors

ABSTRACT

This article explores the estimation problem of the coefficients in the varying coefficient model with heteroscedastic errors. Specifically, we first present a method for estimating the variance function of the error term and the resulting estimator is proved to be consistent. Then, motivated by the generalized least-squares procedure for dealing with heteroscedasticity in the linear regression literature, we re-weight each squared residual term in the local linear smoother with the inverse of the corresponding estimated error variance to construct estimates of the coefficients. Simulation experiments and practical data analysis conducted demonstrate that the re-weighting approach can improve the accuracy of the coefficient estimates under a finite sample size, especially when the error heteroscedasticity is strong.     

Confidence interval for residual mean absolute deviation in regression models

The classic confidence interval for a residual variance is hypersensitive to minor violations of the normality assumption and its robustness does not improve with increasing sample size. An approximate confidence interval for a residual mean absolute deviation is proposed and shown to be robust to moderate violations of the normality assumption with robustness that improves with increasing sample size.     

Varying Dispersion Diagnostics for Inverse Gaussian Regression Models

Homogeneity of dispersion parameters is a standard assumption in inverse Gaussian regression analysis. However, this assumption is not necessarily appropriate. This paper is devoted to the test for varying dispersion in general inverse Gaussian linear regression models. Based on the modified profile likelihood (Cox & Reid, 1987), the adjusted score test for varying dispersion is developed and illustrated with Consumer- Product Sales data (Whitmore, 1986) and Gas vapour data (Weisberg, 1985). The effectiveness of orthogonality transformation and the properties of a score statistic and its adjustment are investigated through Monte Carlo simulations.     

Data depths satisfying the projection property

Summary: Data depth is a concept that measures the centrality of a point in a given data cloud x ₁, x ₂,...,x _n or in a multivariate distribution P ^X on ^{d d} . Every depth defines a family of so–called trimmed regions. The –trimmed region is given by the set of points that have a depth of at least . Data depth has been used to define multivariate measures of location and dispersion as well as multivariate dispersion orders.If the depth of a point can be represented as the minimum of the depths with respect to all unidimensional projections, we say that the depth satisfies the (weak) projection property. Many depths which have been proposed in the literature can be shown to satisfy the weak projection property. A depth is said to satisfy the strong projection property if for every the unidimensional projection of the –trimmed region equals the –trimmed region of the projected distribution.After a short introduction into the general concept of data depth we formally define the weak and the strong projection property and give necessary and sufficient criteria for the projection property to hold. We further show that the projection property facilitates the construction of depths from univariate trimmed regions. We discuss some of the depths proposed in the literature which possess the projection property and define a general class of projection depths, which are constructed from univariate trimmed regions by using the above method.Finally, algorithmic aspects of projection depths are discussed. We describe an algorithm which enables the approximate computation of depths that satisfy the projection property.