陕西西乡方言的语音差异及混合特 征简

陕西西乡方言内部存在着较大的语音差异,城关及县中部和北部的白龙塘、三花石、柳树、杨河、堰口、罗镇等乡镇属中原官话,县东部的子午、茶镇、白勉,南部的马家湾、高川、两河口、五里坝、司上、峡口、骆家坝、大河,以及西部的沙河、私渡、桑园等乡镇均属西南官话。由于移民源的不同,各片之间表现出既有区别又相互兼容的特征。     

特殊路段沥青玛蹄脂（SMA）碎石路面施工技术探析

文章结合路桥专业顶岗实习期间完成的典型市政道路工程中特殊路段SMA沥青路面施工实践,分析了SMA路面施工工艺及影响路面施工质量的主要因素。     

基于CPLD的高频电路多功能时钟模块设计

文章介绍了一种基于CPLD的高频电路的多路不同频率同步时钟输出模块的设计方法,采用单一高频时钟作为时钟源输入,通过CPLD的分频电路设计实现输出多路不同频率同步时钟,利用有限状态基设计实现CPLD的外部控制接口,实现对CPLD输出时钟频率的任意调节。有效满足复杂的高频电路设计中需要提供多路不同频率同步时钟的要求。     

管状延时熔断器工作特性的有限元分析

熔断器在电路保护中扮演着十分重要的角色。本文对某管状延时熔断器的结构进行合理简化,利用有限元分析软件ANSYS,建立了用于熔断器瞬态温度场计算的三维有限元模型,对该熔断器在不同电流下瞬态温度场变化过程进行了数值模拟。通过一系列数值仿真运算后,本文给出了熔断器工作特性分析。通过单元生死技术,对熔断过程进行了动态模拟。详细分析了环境温度及结构几何尺寸对熔断特性的影响规律。为该熔断器的设计制造以及工程分析提供了理论依据。     

基于ANSYS的高速包装机的椭圆齿轮模态分析

采用有限元法,建立了椭圆齿轮的动力学模型,通过有限元分析软件ANSYS对椭圆齿轮进行模态分析,得到了椭圆齿轮的前六阶固有频率和对应振型。该方法和所得结果为动态设计提供了参考,同时也为椭圆齿轮系统的动态响应计算和分析奠定了基础。     

高校图书馆自习区有限定位管理方式初探

高校图书馆自习区学生占座现象是长期困扰图书馆日常管理工作的一个难题。笔者结合自习区管理实践,从读者需求的角度出发,对现有图书馆自习区座位资源按用途进行分区分类,摸索出一套有限定位的管理方式,通过完善管理、总结经验,初步形成了读者自习室一站式服务体系。图书馆自习区有限定位管理方式的建立对高校图书馆的现代管理模式的构建具有重要的参考意义和实际应用价值。     

Poisson Growth Mixture Modeling of Intensive Longitudinal Data: An Application to Smoking Cessation Behavior

This article illustrates the relation between structural equation modeling (SEM) and canonical correlation analysis (CCA). The representation of CCA in SEM may provide some important interpretive information that is not available from conventional CCA, that is, statistical tests for the canonical function and index coefficients, and statistical tests for individual canonical functions. Hierarchically, the relation between the two analytic approaches suggests that SEM stands to be a more general analytic approach. For researchers interested in these techniques, an understanding of the interrelation among them can be helpful to our choice of analytic method.     

Software review

STATISTICA 5.0. StatSoft, 2325 East 13th Street, Tulsa, OK 74104, (918) 583–4149. $995 retail, academic site license—$2,000 for 10 copies. Requirements: 386 or better, 4 Meg RAM, Microsoft Windows 3.1 or 95.     

General Growth Mixture Analysis of Adolescents' Developmental Trajectories of Anxiety: The Impact of Untested Invariance Assumptions on Substantive Interpretations

Substantively, this study investigates potential heterogeneity in the developmental trajectories of anxiety in adolescence. Methodologically, this study demonstrates the usefulness of general growth mixture analysis (GGMA) in addressing these issues and illustrates the impact of untested invariance assumptions on substantive interpretations. This study relied on data from the Montreal Adolescent Depression Development Project (MADDP), a 4-year follow-up of more than 1,000 adolescents who completed the Beck Anxiety Inventory each year. GGMA models relying on different invariance assumptions were empirically compared. Each of these models converged on a 5-class solution, but yielded different substantive results. The model with class-varying variance–covariance matrices was retained as providing a better fit to the data. These results showed that although elevated levels of anxiety might fluctuate over time, they clearly do not represent a transient phenomenon. This model was then validated in relation to multiple predictors (mostly related to school violence) and outcomes (grade-point average, school dropout, depression, loneliness, and drug-related problems).     

Confidence Intervals for a Semiparametric Approach to Modeling Nonlinear Relations among Latent Variables

Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) Bauer, D. J. 2005. A semiparametric approach to modeling nonlinear relations among latent variables. Structural Equation Modeling, 12: 513–535. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar] proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the service of more flexibly recovering characteristics of the latent aggregate regression function. This article develops and evaluates delta method and parametric bootstrap approaches for obtaining approximate confidence intervals for Bauer's semiparametric approach to modeling latent nonlinear functions. Coverage rates of these approximate point-wise confidence intervals or nonsimultaneous confidence bands are evaluated by Monte Carlo and recommendations for their use are suggested.