Coping With Racism: Moderators of the Discrimination-Adjustment Link Among Mexican-Origin Adolescents

What strategies help ethnic minority adolescents to cope with racism? The present study addressed this question by testing the role of ethnic identity, social support, and anger expression and suppression as moderators of the discrimination-adjustment link among 269 Mexican-origin adolescents (Mage = 14.1 years), 12-17 years old from the Midwestern U.S. Results from multilevel moderation analyses indicated that ethnic identity, social support, and anger suppression, respectively, significantly attenuated the relations between discrimination and adjustment problems, whereas outward anger expression exacerbated these relations. Moderation effects differed according to the level of analysis. By identifying effective coping strategies in the discrimination-adjustment link at specific levels of analysis, the present findings can guide future intervention efforts for Latino youth

Erratum Re: “Coping With Racism: Moderators of the Discrimination—Distress Link Among Mexican-Origin Adolescents”

The publisher's final edited version of this article is available at Child Dev This corrects the article "Coping With Racism: Moderators of the Discrimination—Adjustment Link Among Mexican-Origin Adolescents" in Child Dev, volume 89 on page e293

The Impact of Music Education on Middle School Students’ Attendance Rates and Academic Achievement on Math and English Language Arts

In recent years, students’ standardized test scores have become one of the major measurements for students’ learning. However, music as a non-tested subject is often viewed as a lesser valued subject compared to core subjects. The purpose of this study was to investigate the impact music programs have on student academic achievement and attendance rate. The data was collected from one middle school of a large school district located in the northeast of Missouri. The study population includes sixth, seventh, and eighth-grade students who enrolled in the 2017-2018, 2018-2019, and 2020-2021 school years. The population was divided into students who participated in music classes (band, choir, and orchestra) and students who did not participate in music classes. A survey was also conducted to align with the research question: “What are middle school music educators\u27 perceptions of music education\u27s impact on academic achievement?” The research used descriptive and inferential statistical procedures: t-test, ANOVA, and Chisquare (χ2) tests to examine data for study purposes. The analyzed data proved the proposed hypothesis and theory, that there was statistically significant data from the English Language Art (ELA) and Mathematics (MATH) assessments to show the positive impact music education could have on both ELA and MATH achievements. The students involved and enrolled in music education courses had higher ELA and mathematics assessment scores and performance levels. Though the results of the students’ attendance days were not as significant, it still statistically showed that music education also had a positive effect on student attendance days. From the analysis of the survey, the finding indicated that all the survey participants agreed that music education has a positive impact on students\u27 academic achievement. It also suggested that middle school music teachers believed that not only can music education help students improve their academic performances, but it can also provide students with the principle abilities to learn and to succeed in other core academic areas

Emily Johansen. Beyond Safety: Risk, Cosmopolitanism, and Contemporary Neoliberal Life. Bloomsbury, 2021.

Review of Emily Johansen. Beyond Safety: Risk, Cosmopolitanism, and Contemporary Neoliberal Life. Bloomsbury, 2021. xiii + 171 pp

Thermal/environmental barrier coating system for silicon-based materials

A coating system for a substrate containing a silicon-based material, such as silicon carbide-containing ceramic matrix materials containing silicon carbide and used to form articles exposed to high temperatures, including the hostile thermal environment of a gas turbine engine. The coating system includes a layer of barium strontium aluminosilicate (BSAS) as a bond coat for a thermal-insulating top coat. As a bond coat, the BSAS layer serves to adhere the top coat to a SiC-containing substrate. The BSAS bond coat exhibits sufficient environmental resistance such that, if the top coat should spall, the BSAS bond coat continues to provide a level of environmental protection to the underlying SiC-containing substrate

FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout

Federated Learning (FL) allows machine learning models to train locally on individual mobile devices, synchronizing model updates via a shared server. This approach safeguards user privacy; however, it also generates a heterogeneous training environment due to the varying performance capabilities across devices. As a result, straggler devices with lower performance often dictate the overall training time in FL. In this work, we aim to alleviate this performance bottleneck due to stragglers by dynamically balancing the training load across the system. We introduce Invariant Dropout, a method that extracts a sub-model based on the weight update threshold, thereby minimizing potential impacts on accuracy. Building on this dropout technique, we develop an adaptive training framework, Federated Learning using Invariant Dropout (FLuID). FLuID offers a lightweight sub-model extraction to regulate computational intensity, thereby reducing the load on straggler devices without affecting model quality. Our method leverages neuron updates from non-straggler devices to construct a tailored sub-model for each straggler based on client performance profiling. Furthermore, FLuID can dynamically adapt to changes in stragglers as runtime conditions shift. We evaluate FLuID using five real-world mobile clients. The evaluations show that Invariant Dropout maintains baseline model efficiency while alleviating the performance bottleneck of stragglers through a dynamic, runtime approach