对立与融合的可能——从现象出发论"新诗与歌词"的关系

新诗与歌词由于各自的特征经常被人们当作两个范畴,而新诗与歌词的“对立”正是在这种区别中产生的。然而,无论从起源上,还是从音乐性上看,诗与歌词的关系是非常密切的并可以适当融合的,同时,90年代以来的新诗与歌词各自存在的问题也促使了这种融合趋势的产生。本文正是在强调对立与融合的前提下展开论述的,至于其目的就是希望由此能为当前的新诗与歌词找到可以共同发展的结合点。     

Latent Class Trees with the Three-Step Approach

Latent class (LC) analysis is widely used in the social and behavioral sciences to find meaningful clusters based on a set of categorical variables. To deal with the common problem that a standard LC analysis may yield a large number classes and thus a solution that is difficult to interpret, recently an alternative approach has been proposed, called Latent Class Tree (LCT) analysis. It involves starting with a solution with a small number of “basic” classes, which may subsequently be split into subclasses at the next stages of an analysis. However, in most LC analysis applications, we not only wish to identify the relevant classes, but also want to see how they relate to external variables (covariates or distal outcomes). For this purpose, researchers nowadays prefer using the bias-adjusted three-step method. Here, we show how this bias-adjusted three-step procedure can be applied in the context of LCT modeling. More specifically, an R-package is presented that performs a three-step LCT analysis: it builds a LCT and allows checking how splits are related to the relevant external variables. The new tool is illustrated using a cross-sectional application with multiple indicators on social capital and demographics as external variables and with a longitudinal application with a mood variable measured multiple times during the day and personality traits as external variables.     

水合物法分离含氢气体混合物的实验研究

利用高压水合物分离装置,在不同的温度、压力及液体流量下,分别测定了H2、CH4二元混合物与水合物促进剂进行水合反应时分离效果随时间的变化.结果表明,温度越低,体系压力越高,液体流量越大,H2浓度增加越快,但较高的压力对分离效果影响较小,过大的液体流量会加大液体夹带量.适宜的条件为:温度5~10℃,压力4.5~5.0 MPa,合适的液体流量应根据实际情况确定.     

Do eco-innovations harm productivity growth through crowding out? Results of an extended CDM model for Italy

This paper discusses the results for Italy of a CDM model (Crepon et al., 1998) further extended with the objective of evaluating drivers and productivity effects of environmental innovations. The particular nature of environmental innovations, especially as regards the need of government intervention to create market opportunities, is likely to affect the way through which they are pursued (innovation equation within the CDM model) and their effect on productivity (productivity equation).     

Detecting Mixtures From Structural Model Differences Using Latent Variable Mixture Modeling: A Comparison of Relative Model Fit Statistics

The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) × 3 (exogenous latent mean difference) × 3 (endogenous latent mean difference) × 3 (correlation between factors) × 3 (mixture proportions) factorial design. In addition, the efficacy of several likelihood-based statistics (Akaike's Information Criterion [AIC], Bayesian Information Ctriterion [BIC], the sample-size adjusted BIC [ssBIC], the consistent AIC [CAIC], the Vuong-Lo-Mendell-Rubin adjusted likelihood ratio test [aVLMR]), classification-based statistics (CLC [classification likelihood information criterion], ICL-BIC [integrated classification likelihood], normalized entropy criterion [NEC], entropy), and distributional statistics (multivariate skew and kurtosis test) were examined to determine which statistics best recover the correct number of components. Results indicate that the structural parameters were recovered, but the model fit statistics were not exceedingly accurate. The ssBIC statistic was the most accurate statistic, and the CLC, ICL-BIC, and aVLMR showed limited utility. However, none of these statistics were accurate for small samples (n = 500).     

认知诊断理论在数学教育评价中的应用

质性地比较论证了基于认知诊断理论的数学教育评价工具开发的可行性。通过分析实际测试数据,比较几种不同认知诊断模型中的参数估计方法实际应用于分析数学评价测验的可能性。研究发现,认知属性概念可以帮助研究者和实践者分析影响学生解答数学题目背后的认知结构。人工神经网络模型能够充分利用理论设计的认知模型,克服测验题目有限、题型多样、认知属性差异大等不易分析的困难,较好评价学生的数学学业成就,为后续教学提供诊断性信息,达到了诊断性测验的目的。     

基于V-I-AP模型的兰州市不透水面与植被盖度时空格局分析

本文构建了V-I-AP模型,以兰州市Landsat TM影像为数据源,利用线性光谱混合模型进行亚像元分解,以获取不透水面比例及植被覆盖度的空间分布。在此基础上采用景观格局指数对研究区植被覆盖景观的空间格局及其分异进行测度,为利用中等分辨率遥感数据定量评价河谷型城市生态环境提供更精确的方法。研究结果表明:与常规景观分类相比,基于亚像元分解的不透水表面与植被覆盖提取方法具有更高的精度,并可以表征地表覆盖的生物物理组分构成特点;1999年—2006年,兰州市中心城区不透水面盖度和面积增加明显,而植被盖度则急剧降低,植被破碎程度减缓,植被分布聚集度增加。     

An Adaptive Bayesian Lasso Approach with Spike-and-Slab Priors to Identify Multiple Linear and Nonlinear Effects in Structural Equation Models

In applied research, such as with motivation theories, typically many variables are theoretically implied predictors of an outcome and several interactions are assumed (e.g., Watt, 2004). However, estimation problems that might arise when several interaction and/or quadratic effects are analyzed simultaneously have not been investigated because simulation studies on interaction effects in the structural equation modeling framework have mainly focused on small models that contain single interaction effects. In this article, we show that traditional approaches can provide estimates with low accuracy when complex models are estimated. We introduce an adaptive Bayesian lasso approach with spike-and-slab priors that overcomes this problem. Using a complex model in a simulation study, we show that the parameter estimates of the proposed approach are more accurate in situations with high multicollinearity or low reliability compared with a standard Bayesian lasso approach and typical frequentist approaches (i.e., unconstrained product indicator approach and latent moderated structures approach).     

贵州省CDM项目开发利用状况及未来开发优势领域

为了总结在《京都议定书》第一期承诺期内我国西部贫困省区CDM项目的发展现状、所处的水平以及出现的问题,以贵州省为例,运用对比分析的研究方法,对省内各项目类型数据做横向对比分析和对国内各省区项目数分别做纵向对比分析,结果发现贵州CDM项目对开发水力资源依赖度高,其他类型项目开发不足,开发程度低,开发能力不足,落后于全国平均发展水平。在此基础上,提出了贵州未来CDM项目发展的优势领域和促进CDM发展的政策建议。     

乳化沥青厂拌冷再生在高速公路下面层的应用

为研究乳化沥青厂拌冷再生在高速公路路面下面层中的应用,通过对旧路面回收材料的性能评价和再生混合料矿料组成设计,研究再生混合料中用水量、乳化沥青含量和水泥掺量对乳化沥青厂拌冷再生的混合料性能影响。结果表明,乳化沥青冷再生混合料配合比中随着用水量的增加最大干密度先增大后减小;随着乳化沥青含量的增加,乳化沥青再生混合料的干、湿劈裂强度先增大后减小;当水泥掺量控制在1.5%时,乳化沥青厂拌冷再生混合料具有最佳的抗裂性能。