Understanding racial literacy through acts of (un)masking: Latinx teachers in a new Latinx diaspora community

As Latinx teachers are recruited to work in U.S. schools, a continued agenda to understand their experiences is warranted. This multiple case study considers the storytelling of six Latinx teachers in a new Latinx diaspora community. It documents both their racial literacy (the ability to resolve racially stressful issues) and their experiences with (un)masking (literal and figurative ways to cover or embrace racial markers). This study reveals the tensions that arise when Latinx teachers attempt to define their identity in social spaces where their languages, bodies, and names, among other markers, are racialized when read by others. Implications for teacher education include a call to include storytelling as a pedagogical tool to develop Latinx teachers’ racial literacy skills. By experiencing storytelling in their own schooling, Latinx teachers are more likely to model such racial literacy skills in their schooling communities; thereby, empowering a generation of students to enact more humanizing behaviors.     

Deciphering blog users: young adults’ personalities,motivations, and perceived importance of blog features

The present study examines the cyberpsychology of blog readership as well as the digital content preferences of the Millennial generation by examining the links between college students’ personality traits, motivations to read blogs, and preferred blog features. Results indicate that personality influences motivations for reading blogs, which in turn helps predict perceived importance of blog characteristics. Notably, extraversion and neuroticism were related to reading blogs for social interaction; extraversion negatively predicted use of blogs to meet identity needs; openness was related to blog reading for entertainment purposes; and conscientiousness was positively associated with information seeking via blogs. Additionally, motivations for blog readership as explanatory mechanisms for the relationships found between personality traits and perceived importance of blog features are discussed.     

A Case Study Using Photovoice to Explore Racial and Social Identity Among Young Black Men: Implications for Social Work Research and Practice

This article describes an exploratory qualitative case study using a research method novel to social work known as Photovoice. This case study of the Photovoice process assesses its value as a community-based participatory research (CBPR) method with marginalized communities within social work research. Photovoice was used to engage young Black men as researchers into their own lived experience. Through a photographic and group participatory project, participants discussed how intersections of race, gender, and sexuality affect their lives and health. While this methodology has proliferated within public health literature, little research exists within social work. Photovoice represents a research well-aligned with core social work values of empowerment and social justice. This method offers our profession a participatory, action-oriented tool to inform practice and policy and does so in the voices of communities who often go unheard.     

A new algorithm for clustering based on kernel density estimation

In this paper, we present an algorithm for clustering based on univariate kernel density estimation, named ClusterKDE. It consists of an iterative procedure that in each step a new cluster is obtained by minimizing a smooth kernel function. Although in our applications we have used the univariate Gaussian kernel, any smooth kernel function can be used. The proposed algorithm has the advantage of not requiring a priori the number of cluster. Furthermore, the ClusterKDE algorithm is very simple, easy to implement, well-defined and stops in a finite number of steps, namely, it always converges independently of the initial point. We also illustrate our findings by numerical experiments which are obtained when our algorithm is implemented in the software Matlab and applied to practical applications. The results indicate that the ClusterKDE algorithm is competitive and fast when compared with the well-known Clusterdata and K-means algorithms, used by Matlab to clustering data.     

Spatially Balanced Sampling of Continuous Populations

When sampling from a continuous population (or distribution), we often want a rather small sample due to some cost attached to processing the sample or to collecting information in the field. Moreover, a probability sample that allows for design‐based statistical inference is often desired. Given these requirements, we want to reduce the sampling variance of the Horvitz–Thompson estimator as much as possible. To achieve this, we introduce different approaches to using the local pivotal method for selecting well‐spread samples from multidimensional continuous populations. The results of a simulation study clearly indicate that we succeed in selecting spatially balanced samples and improve the efficiency of the Horvitz–Thompson estimator.     

A robust automatic clustering algorithm for probability density functions with application to categorizing color images

This study develops a robust automatic algorithm for clustering probability density functions based on the previous research. Unlike other existing methods that often pre-determine the number of clusters, this method can self-organize data groups based on the original data structure. The proposed clustering method is also robust in regards to noise. Three examples of synthetic data and a real-world COREL dataset are utilized to illustrate the accurateness and effectiveness of the proposed approach.     

Several least-squares problems related to the Hodrick–Prescott filtering

The Hodrick–Prescott (HP) filtering is frequently used in macroeconometrics to decompose time series, such as real gross domestic product, into their trend and cyclical components. Because the HP filtering is a basic econometric tool, it is necessary to have a precise understanding of the nature of it. This article contributes to the literature by listing several (penalized) least-squares problems that are related to the HP filtering, three of which are newly introduced in the article, and showing their properties. We also remark on their generalization.     

Non uniform exponential bounds on normal approximation by Stein’s method and monotone size bias couplings

It is known that the normal approximation is applicable for sums of non negative random variables, W, with the commonly employed couplings. In this work, we use the Stein’s method to obtain a general theorem of non uniform exponential bound on normal approximation base on monotone size bias couplings of W. Applications of the main result to give the bound on normal approximation for binomial random variable, the number of bulbs on at the terminal time in the lightbulb process, and the number of m runs are also provided.     

高校思想政治理论课“三进”方式方法探析——以《马克思主义基本原理概论》为例

为了让习近平新时代中国特色社会主义思想“进教材、进课堂、进头脑”，需要从方式、方法层面进行分析。在深耕教材的基础上，发现2018版《马克思主义基本原理概论》教材在融入习思想时，依据不同内容主要采取了文献参考式、引入说明式、说明原理式、补充创新式、替代更新式等方法。为有效做好教材体系向教学体系转换，针对教材中对习思想融入的不同方式，可以因内容分别或组合选择活动拓展法、课前一语法、习近平话语中心式教学法、问题式教学法、案例教学法等。在转化过程中，在方法论上必须坚持马克思主义辩证法，具体问题具体分析，做到转化有法但无定法；在转化的内容和方法的关系上，必须坚持内容和方法的有机统一，从习思想和教材整体视角审视转化，处理好整体与部分的关系；在思政课的价值引领方面，必须处理好真理与价值的关系，把转化最终落脚于价值转化，使习思想真正入脑、入心。     

基于雨课堂的电工电子学混合式智慧教学方法研究

《电工电子学》是高等学校针对非电类工科专业开设的一门有关电工、电子技术的重要专业基础课。针对《电工电子学》传统理论教学空洞乏味、师生互动不足、学生学习兴趣不足等问题，在《电工电子学》课程教学中引入雨课堂智慧教学工具，论述了雨课堂从课前、课上和课后三个方面实践的特点和使用方法，实践表明，基于PPT和微信的雨课堂混合传统教学的教学方法可以实现师生实时线上互动，建立多元化科学评价机制，激发学生学习主动性，活跃课堂气氛，提高学生学习积极性，改善本门课程的教学效果。