Structural Determinants of School Discipline: Examining State-Level Racial Bias and Neighborhood Opportunity.

Objective: Addressing the disproportionate use of school detentions and suspensions among Black youth is crucial for reducing educational and health disparities across the lifespan. Yet, few studies have explored external factors beyond school or individual characteristics as potential contributors to school discipline disparities, such as state-level racial bias and neighborhood opportunity.

Method: A subsample from the larger Adolescent Brain Cognitive Development (ABCD) Study® was used (M age at baseline = 9.

Evaluating climate-related financial policies' impact on decarbonization with machine learning methods.

This study examines how Climate-Related Financial Policies (CRFPs) support decarbonization and renewable energy transitions across 87 countries from 2000 to 2023. Using the Policy Sequencing Score (PSS) and a bindingness-weighted adoption indicator, it explores the relationships between CRFPs, CO2 emissions, and Renewable Energy Production (REP) across diverse economic and institutional contexts. Findings reveal significant variation in outcomes.

English major students' satisfaction with ELSA Speak in English pronunciation courses.

Clear and accurate pronunciation plays an essential role in communicating effectively and significantly affects English learners' proficiency. ELSA Speak has been used in some schools due to its benefits to help learners improve English pronunciation. However, to optimize the application, a better understanding of EFL learners' satisfaction with ELSA Speak is essential.

Developing an Affordable Miniature 3D-Printed Wave Generator for Wave Energy Harvesting Application.

The development of low-frequency and low-amplitude wave energy harvesters has been limited by the lack of an affordable scientific evaluation platform, due to the high cost and land requirements of ground-based water channels. A 3D-printed modular wave generator, combined with the commercially available laboratory-sized wave channel, is proposed to address this. A stepper motor and an Arduino are employed as the driving source and controller.

Unlocking new possibility of FeO@C@Ag nanostructures as an advanced SERS substrate for ultrasensitive detection of low-cross-section urea biomolecules.

Surface-enhanced Raman spectroscopy (SERS) is widely recognized as a powerful analytical technique, offering molecular identification by amplifying characteristic vibrational signals, even at the single-molecule level. While SERS has been successfully applied for a wide range of targets including pesticides, dyes, bacteria, and pharmaceuticals, it has struggled with the detection of molecules with inherently low Raman scattering cross-sections. Urea, a key nitrogen-containing biomolecule and the diamide of carbonic acid, is a prime example of such a challenging target.