Estimation of Generalized DINA Model with Order Restrictions

Cognitive diagnostic models provide valuable information on whether a student has mastered each of the attributes a test intends to evaluate. Despite its generality, the generalized DINA model allows for the possibility of lower correct rates for students who master more attributes than those who know less. This paper considers the use of order-constrained parameter space of the G-DINA model to avoid such a counter-intuitive phenomenon and proposes two algorithms, the upward and downward methods, for parameter estimation. Through simulation studies, we compare the accuracy in parameter estimation and in classification of attribute patterns obtained from the proposed two algorithms and the current approach when the restricted parameter space is true. Our results show that the upward method performs the best among the three, and therefore it is recommended for estimation, regardless of the distribution of respondents’ attribute patterns, types of test items, and the sample size of the data.     

Divisive Latent Class Modeling as a Density Estimation Method for Categorical Data

Traditionally latent class (LC) analysis is used by applied researchers as a tool for identifying substantively meaningful clusters. More recently, LC models have also been used as a density estimation tool for categorical variables. We introduce a divisive LC (DLC) model as a density estimation tool that may offer several advantages in comparison to a standard LC model. When using an LC model for density estimation, a considerable number of increasingly large LC models may have to be estimated before sufficient model-fit is achieved. A DLC model consists of a sequence of small LC models. Therefore, a DLC model can be estimated much faster and can easily utilize multiple processor cores, meaning that this model is more widely applicable and practical. In this study we describe the algorithm of fitting a DLC model, and discuss the various settings that indirectly influence the precision of a DLC model as a density estimation tool. These settings are illustrated using a synthetic data example, and the best performing algorithm is applied to a real-data example. The generated data example showed that, using specific decision rules, a DLC model is able to correctly model complex associations amongst categorical variables.     

Improved Classification for Compositional Data Using the <Emphasis Type="Italic">α</Emphasis>-transformation

In compositional data analysis, an observation is a vector containing nonnegative values, only the relative sizes of which are considered to be of interest. Without loss of generality, a compositional vector can be taken to be a vector of proportions that sum to one. Data of this type arise in many areas including geology, archaeology, biology, economics and political science. In this paper we investigate methods for classification of compositional data. Our approach centers on the idea of using the α-transformation to transform the data and then to classify the transformed data via regularized discriminant analysis and the k-nearest neighbors algorithm. Using the α-transformation generalizes two rival approaches in compositional data analysis, one (when α=1) that treats the data as though they were Euclidean, ignoring the compositional constraint, and another (when α = 0) that employs Aitchison’s centered log-ratio transformation. A numerical study with several real datasets shows that whether using α = 1 or α = 0 gives better classification performance depends on the dataset, and moreover that using an intermediate value of α can sometimes give better performance than using either 1 or 0.     

Civic Meaningfulness ‘Revisited’: A Final Reply to Honohan and Dekker

This final reply responds to Honohan’s invitation to articulate the Arendtian tone of the key-note paper. It spells out the philosophical intuition that the political life of citizens, at least potentially, is capable of making visible what makes human life worthwhile and fully meaningful, and the philosophical curiosity to see whether traces of this deep political awareness can be retrieved in dialogues with volunteers. In response to Dekker’s critical doubts, this final reply clarifies the central stakes of Claes’s paper. The core argument was not to show that the biographical model of meaningfulness is the prevailing approach of meaning in/of volunteering, but to assess the potentials and limits of the model’s interpretive power. Moreover, the paper argues for an alternative, existential model of meaningfulness. This approach refers to deep experiences of meaning that emerge from the practice of volunteering and that shift into powerful political experiences of hope, and a lived sense of equality.     

Reasons of Love: Response to Wolf

According to Wolf’s fitting fulfillment view, meaningfulness depends on the person’s subjective attraction to an activity being grounded in ‘reasons of love’ that concern the objective value of those activities. In this short comment, I argue that ‘reasons of love’—and thus reasons for regarding as meaningful—are not limited to those having to do with the objective value of activities and relationships, but include also what I call ‘reasons for the initiated’ and ‘reasons for me’.     

中药青蒿化学成分的研究Ⅰ

 近年来我们对中药青篙的化学成分进行了较系统的研究,其中抗疟有效成分一青蓄素(qinghaosu)为具有过氧墓的新倍半萜内酸,有专文报道^1-4。本文报道其它倍半萜内酣,黄酮,香豆素及挥发油的分离鉴定,其中青简甲素及丙素(qinghaosu I及III)为新化合物。     

岩墙群圆柱状节理的发现和成因机制探讨

在鲁西地区前寒武纪基性岩墙群内发育一种罕见的原生圆柱状节理,由同轴圆柱状节理和放射状节理组成,垂直于岩墙走向,沿岩墙走向排列,是一种指示岩浆水平侵位的流动构造。岩墙发育圆柱状节理表明出露的是岩墙的顶部,反映基性岩墙群侵位时岩浆具有黏滞性剪切作用的流变学特征。柱状节理长轴的倾伏向垂直岩墙的两壁,可以反映岩墙的产状。岩墙圆柱状节理的倾伏角反映了岩墙所在地块的掀斜程度。岩墙发育圆柱状节理表明岩墙侵位时地块已经处于上地壳脆性构造环境,中元古代鲁西地区是一个脆性伸展的大地构造环境。     

AC-PDP结构对串扰的影响

采用二维数值模拟的方法计算了表面放电型PDP在不同结构下相邻3个显示单元的放电过程.研究了放电过程中各单元内电子、氙谐振态浓度分布和其平均浓度随时间的变化情况.在流体模型计算基础上,采用蒙特卡罗模型对单元内大量谐振光子的辐射、捕获过程进行模拟跟踪,从而得出各放电单元内所产生谐振光子在荧光粉层上的分布.研究了放电过程中相邻单元之间的影响,结果表明,对传统条形障壁结构,单元内维持电极间距增大,放电空间高度增加会使放电串扰和发光串扰加强,Waffle型障壁结构不仅能提高放电效率,而且能有效阻止串扰的发生.     

Electro-deoxidation of V<Subscript>2</Subscript>O<Subscript>3</Subscript> in molten CaCl<Subscript>2</Subscript>-NaCl-CaO

The electro-deoxidation of V₂O₃ precursors was studied. Experiments were carried out with a two-terminal electrochemical cell, which was comprised of a molten electrolyte of CaCl₂ and NaCl with additions of CaO, a cathode of compact V₂O₃, and a graphite anode under the potential of 3.0 V at 1173 K. The phase constitution and composition as well as the morphology of the samples were studied by X-ray diffraction (XRD) and scanning electron microscopy (SEM). 3 g of V₂O₃ could be converted to vanadium metal powder within the processing time of 8 h. The kinetic pathway was investigated by analyzing the product phase in samples prepared at different reduction stages. CaO added in the reduction path of V₂O₃ formed the intermediate product CaV₂O₄.     

Electrochemical properties of LiNi<Subscript>0.5</Subscript>Mn<Subscript>1.3</Subscript>Ti<Subscript>0.2</Subscript>O<Subscript>4</Subscript>/Li<Subscript>4</Subscript>Ti<Subscript>5</Subscript>O<Subscript>12</Subscript> cells

Spinel compounds LiNi_0.5Mn_1.3Ti_0.2O₄ (LNMTO) and Li₄Ti₅O₁₂ (LTO) were synthesized by different methods. The particle sizes of LNMTO and LTO are 0.5–2 and 0.5–0.8 μm, respectively. The LNMTO/LTO cell exhibits better electrochemical properties at both a low current rate of 0.2C and a high current rate of 1C. When the specific capacity was determined based on the mass of the LNMTO cathode, the LNMTO/LTO cell delivered 137 mA·h·g⁻¹ at 0.2C and 118.2 mA·h·g⁻¹ at 1C, and the corresponding capacity retentions after 30 cycles are 88.5% and 92.4%, respectively.