丹巴的墨尔多文化

墨尔多是嘉绒地区的一位名山神,墨尔多神山是嘉绒地区的第一大神山。坐落在丹巴墨尔多神山下的墨尔多庙是一个供奉神祗十分复杂的寺庙,所供神祗有佛教,有苯教,也有道教,呈三教合流状态。墨尔多庙供奉神祗的多样性,是丹巴地区文化多元性的反映。     

悲喜交集的生命之歌——评迟子建的《逝川》

在短篇小说《逝川》中,迟子建写了一条河,一个人,一种鱼。这条河,无疑是一条生命之河,一条时间之河,在这条河边,主人公吉喜经历了充满生机却又不乏辛酸的人生。吉喜与泪鱼的对照,显示出吉喜强韧的生命力。这条河流淌着的,是一曲悲喜交集的生命之歌。     

Optimal design of pressure vessel using an improved genetic algorithm

As the idea of simulated annealing （SA） is introduced into the fitness function, an improved genetic algorithm （GA） is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure constraint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis （FEA）. A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.     

Dynamic response analysis of a moored crane-ship with a flexible boom

The dynamic response of moored crane-ship is studied. Governing equations for the dynamic response of a crane-ship coupled with the pendulum motion of the payload are derived based on Lagrange＇s equations. The boom is modeled based on finite element method, while the payload is modeled as a planar pendulum of point mass. The dynamic response was studied using numerical method. The calculation results show that the large-amplitude responses occur at wave periods near the natural period of the payload. Load swing angle is smaller for crane-ship with flexible boom, in comparison with rigid boom. The ship surge motions have large vibrations for crane-ship with flexible boom, which were not observed for a rigid boom. The analysis identifies the significance of key parameters and reveals how the system design can be adjusted to avoid critical conditions.     

A Mixture IRTree Model for Extreme Response Style: Accounting for Response Process Uncertainty

This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the individual level (within an individual). Simulation analyses reveal the potential of the mixture approach in identifying subgroups of respondents exhibiting response behavior reflective of different underlying response processes. Application to real data from the Students Like Learning Mathematics (SLM) scale of Trends in International Mathematics and Science Study (TIMSS) 2015 demonstrates the superior comparative fit of the mixture representation, as well as the consequences of applying the mixture on the estimation of content and response style traits. We argue that methodology applied to investigate response styles should attend to the inherent uncertainty of response style influence due to the likely influence of both response styles and the content trait on the selection of extreme response categories.     

Testing Measurement Invariance Across Unobserved Groups: The Role of Covariates in Factor Mixture Modeling

Factor mixture modeling (FMM) has been increasingly used to investigate unobserved population heterogeneity. This study examined the issue of covariate effects with FMM in the context of measurement invariance testing. Specifically, the impact of excluding and misspecifying covariate effects on measurement invariance testing and class enumeration was investigated via Monte Carlo simulations. Data were generated based on FMM models with (1) a zero covariate effect, (2) a covariate effect on the latent class variable, and (3) covariate effects on both the latent class variable and the factor. For each population model, different analysis models that excluded or misspecified covariate effects were fitted. Results highlighted the importance of including proper covariates in measurement invariance testing and evidenced the utility of a model comparison approach in searching for the correct specification of covariate effects and the level of measurement invariance. This approach was demonstrated using an empirical data set. Implications for methodological and applied research are discussed.     

轿车副车架模态试验及有限元分析

本文使用了试验与有限元两种手段对轿车副车架进行了模态特性的分析研究。首先对副车架进行了模态试验并提取模态参数,然后建立副车架的有限元模型,通过仿真计算获得其自由状态下的模态参数,之后将试验结果与有限元结果进行对比分析。最后在确定有限元模型可靠的情况下,模拟计算了副车架在真实约束下的模态特性,为分析副车架在工作状态下的动态特性提供有用参考。     

Arc-length technique for nonlinear finite element analysis

Nonlinear solution of reinforced concrete structures, particularly complete load-deflection response, requires tracing of the equilibrium path and proper treatment of the limit and bifurcation points. In this regard, ordinary solution techniques lead to instability near the limit points and also have problems in case of snap-through and snap-back. Thus they fail to predict the complete load-displacement response. The arc-length method serves the purpose well in principle, Received wide acceptance in finite element analysis, and has been used extensively. However modifications to the basic idea are vital to meet the particular needs of the analysis. This paper reviews some of the recent developments of the method in the last two decades, with particular emphasis on nonlinear finite element analysis of reinforced concrete structures.     

Optimization of block-floating-point realizations for digital controllers with finite-word-length considerations

INTRODUCTIONDuetothefinitewordlength (FWL)effect,acasualcontrollerimplementationmaydegradethedesignedclosed loopperformanceorevendestabilizethedesignedstableclosed loopsys tem ,ifthecontrollerimplementationstructureisnotcarefullychosen .Theeffectsoffinite…     

A New Perspective on the Effects of Covariates in Mixture Models

In this simulation study, we explored the effect of introducing covariates to a growth mixture model when covariates were also generated by a mixture model. We varied the association between the latent classes underlying the growth trajectories and the covariates, the degree of separation between the latent classes underlying the covariates, the number of covariates included, and amount of missing data in the growth data. We found that adding covariates to the growth mixture model generally hurt class recovery except where the latent classes underlying the growth trajectories and the covariates were the same or very strongly associated, and there was a large degree of separation between the classes underlying the covariates. We found that when covariates were introduced, entropy might no longer be an accurate indicator of the distinctiveness of the growth trajectory classes.