The Five Cs of Positive Youth Development: Configurations of Thriving in Four U.S. Adolescent Samples

Positive youth development (PYD) models are widespread, but the empirical evidence for them is primarily nomothetic (i.e., investigations of universal patterns). Contemporary developmental theory suggests that concepts and processes within PYD models should also be explored with respect to specificity. This study demonstrates how the Five Cs Model, a predominant PYD model, can be advanced using group-differential methods. Secondary data from four studies of adolescents were used to test: (1) Whether there were subgroups who varied in their patterns of scores across the Five Cs, and (2) Whether subgroups also varied in Contribution behaviors. Unexpectedly, the four data sets used could not be combined, yielding an opportunity to discuss consistencies and inconsistencies in findings across the four data sets through contextual and sample differences. Findings demonstrate how understanding specificity in theorized concepts and processes in PYD models can complement studies of universal patterns, which are both necessary to advance PYD research and practice.     

Self-Starting control charts for monitoring logistic regression profiles

In some applications, quality engineers cannot monitor the processes at the beginning of the production process. Because the process parameters are unknown and there are not enough initial samples to estimate the process parameters. Self-starting control charts are applied to monitor processes at the start-up stages with no enough initial samples. In this paper, we propose three self-starting control charts to monitor a logistic regression profile which models the relationship between a binomial response variable and explanatory variables. Also, we compare the proposed control charts with each other through simulation studies in terms of average run length (ARL) criterion.     

Identifying change-point in polynomial profiles based on data-segmentation

Profile monitoring is the use of control charts for cases in which the quality of a process or product can be characterized by a functional relationship between a response variable and one or more explanatory variables. Unlike the linear profile's simple structure, the nonlinear profile has relatively less attainment because of high complexity. Regression model is the initial method to analyze the phase I of nonlinear profiles, but it lacks sensitivity for local characteristic changes. This article presents a strategy comprising two major components: data-segmentation, to concisely detect the location of local change by overlaying grid points onto horizontal axis, and change-point detection via the maximum likelihood estimate. Simulated data set of a polynomial profile is used to illustrate the effectiveness of the proposed strategy, and is compared with Williams' T² multi-variable statistics.     

An efficient Bayesian approach for Gaussian Bayesian network structure learning

This article proposes a Bayesian computing algorithm to infer Gaussian directed acyclic graphs (DAGs). It has the ability of escaping local modes and maintaining adequate computing speed compared to existing methods. Simulations demonstrated that the proposed algorithm has low false positives and false negatives in comparison to an algorithm applied to DAGs. We applied the algorithm to an epigenetic dataset to infer DAG's for smokers and nonsmokers.     

A generalized likelihood ratio test for monitoring profile data

Profile data emerges when the quality of a product or process is characterized by a functional relationship among (input and output) variables. In this paper, we focus on the case where each profile has one response variable Y, one explanatory variable x, and the functional relationship between these two variables can be rather arbitrary. The basic concept can be applied to a much wider case, however. We propose a general method based on the Generalized Likelihood Ratio Test (GLRT) for monitoring of profile data. The proposed method uses nonparametric regression to estimate the on-line profiles and thus does not require any functional form for the profiles. Both Shewhart-type and EWMA-type control charts are considered. The average run length (ARL) performance of the proposed method is studied. It is shown that the proposed GLRT-based control chart can efficiently detect both location and dispersion shifts of the on-line profiles from the baseline profile. An upper control limit (UCL) corresponding to a desired in-control ARL value is constructed.     

马汝邺先生事略

马汝邺是民国时期具有一定影响的回族知识女性;从事教育十余年,为女子教育——尤其是回族女子新式教育事业做出了较大贡献;她为人思想开明,节俭自奉,乐于助人,所作所为以宜于社会为准,有着良好的声誉;善书法,能诗文,著有《晦珠馆近稿》。     

我国体育产业的现状及发展对策

改革开放以来,社会主义市场经济得到了迅速的发展,体育也作为一个产业登上了经济舞台,成为第三产业中的重要组成部分．本文通过对我国体育产业现状的分析与研究,指出我国体育产业发展的不足,并从体制、地区差别、主体产业、品牌、人才培养五个方面论证提出加快我国体育产业发展的措施。     

基于语料库的词项整体行为研究方法对一组近义形容词的研究

本研究利用当代美国英语语料库,采用词项整体行为研究(BP)的方法 ,探索一组近义形容词(fantastic,terrific,excellent,wonderful)的内在语义结构。通过调查与这组形容词搭配的名词、副词以及他们在句中做表语时的句法功能,分析它们的语体分布模式,本研究发现这组形容词的语义倾向和使用模式不同,并描述了它们的内在语义结构。另外,本次研究的发现丰富和补充了字典上的解释。同时,研究还表明词项整体行为研究方法不但能有效地研究词汇,还适用于语言学习和教学。     

一种DNA计算系统的有限自动机模型

通过一个实例给出了粘贴系统模型的基本定义，讨论了粘贴系统模型的正则文法特性，并从自动机的角度给出了相当于正则文法表达能力的有限自动机模型。     

基于等距廓形理论的多工位按压机构设计

为设计按钮疲劳寿命测试装置,提出一种新型多工位往复按压机构设计方案,并详细介绍了传动机构等宽凸轮一 框式滑块新的设计方法——基于等距廓形理论,采用数值解析法建立等宽凸轮机构数学模型。通过虚拟样机动力学仿 真技术验证了机构数学模型的有效性以及设计方案的可行性,为多工位按压机构未来原理样机研制提供了理论依据,具 有一定的工程应用价值。