ZnO/AlN复合压电薄膜的研制

各种超高频电子整机需要高性能的表声波压电器件。介绍了新的压电薄膜——ZnO/AIN复合压电薄膜的制速、结构和性能,并给出主要研制结果。     

论翻译再现的层次

翻译是一种双语行为。既要侧重于研究原语、解读原文文本,又要侧重于研究译语,在原文与译文文本表现法之间找到一个平衡点。表现法的目的是探讨如何将“获得的意义”落实到得体的目的语文本中。本文着重研究翻译表现法的基本原则,根据译者对意义把握和意义表达程度的深浅,翻译再现的层次可分为表层翻译、中介层翻译和深层翻译。     

邓小平理论科学体系逻辑结构的再认识

邓小平理论继承并发展了马克思主义 ,是我们党和国家建设社会主义的指导思想。邓小平理论围绕“什么是社会主义 ,怎样建设社会主义”这个主题展开 ,是内含完整的逻辑结构的科学体系。邓小平理论科学体系由核心理论、基础理论、应用理论和边缘理论四个层次构成有机的逻辑结构。准确地把握邓小平理论的逻辑结构是完整地把握邓小平理论体系的内在要求 ,对于坚持和发展邓小平理论 ,指导社会主义建设具有重要意义。     

试析毛泽东社会主义民主思想的基本特点与主要内涵

毛泽东思想体系中社会主义民主思想占有非常重要的地位,曾是中国共产党的建设、国民经济建设与国家民主政治建设的指导思想原则。它是在二战结束之际的特殊的国内外条件下的产物,具有明显的时代特点。毛泽东的社会主义民主观具有鲜明的阶级特色、包涵国家政体形式与现代化道路选择的双重意义、目的论与方法论的双重意义。社会主义的民主形式是群众运动的大民主,其主要对象一是阶级敌人,二是领导干部的官僚主义。执政党的民主机制建设,是毛泽东社会主义民主思想的核心内容之一。对毛泽东社会主义民主思想,应该本着历史唯物主义的立场,客观准确地加以评价。     

用数学函数分析法对统计指数因素分析的进一步改良——谈综合指数体系的缺陷与消除

指数因素分析法是一种重要的统计分析方法,而其分析结果的正确与否取决于所用的指数体系。利用传统的综合指数体系从事因素分析虽方便,使用,但也存在一些不足。本文提出用其他指数体系进行因素分析的思想,以弥补传统综合指数体系在因素分析中的缺陷。     

复合地基承载力标准值取值方法探讨

结合具体工程实例,对静载试验极差大于平均值30%的复合地基,如何确定承载力标准值进行探讨,提出较为合理的取值方法.     

Local composite quantile regression estimation of time-varying parameter vector for multidimensional time-inhomogeneous diffusion models

This paper is dedicated to the study of the composite quantile regression (CQR) estimations of time-varying parameter vectors for multidimensional diffusion models. Based on the local linear fitting for parameter vectors, we propose the local linear CQR estimations of the drift parameter vectors, and verify their asymptotic biases, asymptotic variances and asymptotic normality. Moreover, we discuss the asymptotic relative efficiency (ARE) of the local linear CQR estimations with respect to the local linear least-squares estimations. We obtain that the local estimations that we proposed are much more efficient than the local linear least-squares estimations. Simulation studies are constructed to show the performance of the estimations proposed.     

Bias correction for parameter estimates of spatial point process models

When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best.     

Extended scaled prediction variance optimality for modified central composite design

Robust parameter designs (RPDs) enable the experimenter to discover how to modify the design of the product to minimize the effect due to variation from noise sources. The aim of this article is to show how this amount of work can be reduced under modified central composite design (MCCD). We propose a measure of extended scaled prediction variance (ESPV) for evaluation of RPDs on MCCD. Using these measures, we show that we can check the error or bias associated with estimating the model parameters and suggest the values of α recommended for MCCS under minimum ESPV.     

Composite quantile regression for massive datasets

Analysis of massive datasets is challenging owing to limitations of computer primary memory. Composite quantile regression (CQR) is a robust and efficient estimation method. In this paper, we extend CQR to massive datasets and propose a divide-and-conquer CQR method. The basic idea is to split the entire dataset into several blocks, applying the CQR method for data in each block, and finally combining these regression results via weighted average. The proposed approach significantly reduces the required amount of primary memory, and the resulting estimate will be as efficient as if the entire data set is analysed simultaneously. Moreover, to improve the efficiency of CQR, we propose a weighted CQR estimation approach. To achieve sparsity with high-dimensional covariates, we develop a variable selection procedure to select significant parametric components and prove the method possessing the oracle property. Both simulations and data analysis are conducted to illustrate the finite sample performance of the proposed methods.