浅谈混凝土配合比设计应注意的问题

本文对混凝土配合比设计中值得注意的几个问题进行分析,并提出相应的防治措施。     

吉林地区沥青路面开裂影响因素分析

以吉林地区沥青路面开裂破损情况调研资料为基础,阐述了低温地区沥青路面开裂状态,并进行成因分析,从选材和结构设计提出基本的防治建议,对同类地区的沥青路面设计和材料研究工作具有一定的借鉴作用。     

环氧树脂改性水性聚氨酯胶粘剂的研究

采用环氧树脂E-44交联对水性PU胶粘剂进行改性,并经红外光谱测定其结构.文中采用正交试验方法探索环氧树脂含量、异氰酸根与羟基摩尔比、乙醇浓度等因素对改性PU胶粘剂性能的影响,结果表明组合A3B3C1D2E4是最佳条件,并对最佳条件进行分析,乳化过程采用室温条件下用50%乙醇分散同时中和、TDI/PEG2000摩尔比(―NCO:―OH)为2.3:1、交联剂SaC-100用量为2.5%,固化时间为60 h,可以得到最佳的性能.     

水泥砼路加铺沥青混凝土面层的探析

在旧水泥混凝土路面加铺沥青面层是目前比较普遍的城市道路改造方法,但由于其基层的特殊性,出现反射性裂缝在所难免。文章对基层的修复处理、加铺沥青面层施工的要点以及抑制和延缓反射性裂缝产生的若干方案进行了比较分析,以期对提高加铺工程质量、减少道路病害提供参考。     

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.     

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).     

Models and Strategies for Factor Mixture Analysis: An Example Concerning the Structure Underlying Psychological Disorders

The factor mixture model (FMM) uses a hybrid of both categorical and continuous latent variables. The FMM is a good model for the underlying structure of psychopathology because the use of both categorical and continuous latent variables allows the structure to be simultaneously categorical and dimensional. This is useful because both diagnostic class membership and the range of severity within and across diagnostic classes can be modeled concurrently. Although the conceptualization of the FMM has been explained in the literature, the use of the FMM is still not prevalent. One reason is that there is little research about how such models should be applied in practice and, once a well-fitting model is obtained, how it should be interpreted. In this article, the FMM is explored by studying a real data example on conduct disorder. By exploring this example, this article aims to explain the different formulations of the FMM, the various steps in building a FMM, and how to decide between an FMM and alternative models.     

Disentangling Shape from Level Effects in Person-Centered Analyses: An Illustration Based on University Teachers’ Multidimensional Profiles of Effectiveness

This study compares alternative ways of disentangling the effects of level (the tendency for a person to be high, medium, or low across all factors) and shape (the tendency for a person to have a distinct pattern of factors on which they are high, medium, or low) in profile analyses. This issue is particularly relevant to performance appraisals where it is often useful to identify specific strengths and weaknesses over and above a person global performance, but also to person-centered analyses more generally where the observation of qualitative (shape) differences between profiles is often used as justification for the added value of profiles. Substantively, this study illustrates these issues in the identification of profiles of teachers based on multidimensional students’ ratings of their effectiveness, using an archival data set of 31,951 class-average ratings based on the Students’ Evaluations of Educational Quality (SEEQ) instrument collected over a 13-year period. The results show the superiority of a factor mixture operationalization of teaching effectiveness in which a global effectiveness factor was used to control for unnecessary level effects in the profiles.     

Modeling Nonlinear Structural Equation Models: A Comparison of the Two-Stage Generalized Additive Models and the Finite Mixture Structural Equation Model

Researchers have devoted some time and effort to developing methods for fitting nonlinear relationships among latent variables. In particular, most of these have focused on correctly modeling interactions between 2 exogenous latent variables, and quadratic relationships between exogenous and endogenous variables. All of these approaches require prespecification of the nonlinearity by the researcher, and are limited to fairly simple nonlinear relationships. Other work has been done using mixture structural equation models (SEMM) in an attempt to fit more complex nonlinear relationships. This study expands on this earlier work by introducing the 2-stage generalized additive model (2SGAM) approach for fitting regression splines in the context of structural equation models. The model is first described and then investigated through the use of simulated data, in which it was compared with the SEMM approach. Results demonstrate that the 2SGAM is an effective tool for fitting a variety of nonlinear relationships between latent variables, and can be easily and accurately extended to models including multiple latent variables. Implications of these results are discussed.     

温度影响下的橡胶沥青应力吸收层的应力分析

高温开裂已经成为沥青路面的主要危害之一。橡胶沥青是良好的沥青改性剂,其具有吸收应力,改善沥青高温性能、延长路面使用寿命、延缓反射裂缝等优点。利用ABAQUS有限元软件,选取15℃、20％和60℃下沥青路面的热特性参数,分析在不同温度下橡胶沥青应力吸收层对半刚性基层路面结构和柔性基层路面结构的应力应变规律,推荐合理的沥青路面结构层设计参数,为工程实践提供理论依据。