Browse Articles

This study investigates the migration intentions of Syrian high school and university students amid ongoing conflict and economic instability. Drawing on survey data, the research examines how academic stage influences migration motivations, preferred destinations, and return intentions. The findings reveal a widespread desire to emigrate, driven by educational, economic, and security concerns, highlighting significant implications for Syria’s future workforce and post-conflict recovery.

The main goal of this study is to determine what demographics are related to tuberculosis incidence in the United States populations, particularly if changing demographics are related to differences in tuberculosis risk over two discrete time periods. The major finding is that in the two studied time periods, tuberculosis risk factors were somewhat consistent and may be influenced by things such as immigration, healthcare access, and race or ethnicity, although the top predictor did change.

Here the authors evaluate the relationship between state-level abortion policies and maternal mortality across the United States from 2018 to 2021. Their findings reveal that states with restrictive abortion laws consistently experienced higher maternal mortality ratios than those with protective policies, culminating in a 72% increase in deaths within restrictive states by the end of the study period.

The authors looked at student perception on various situations involving third-party tracking to personalize recommendations.

The authors survey adults to assess how childhood adversity may impact adult relationships and ways of giving or receiving affection.

AI analysis of brain scans offers promise for helping doctors diagnose brain tumors. Haider and Drosis explore this field by developing machine learning models that classify brain scans as "cancer" or "non-cancer" diagnoses.

Here, the authors wanted to explore mathematical paradoxes in which there are multiple contradictory interpretations or analyses for a problem. They used ChatGPT to generate a novel dataset of fairy tales. They found statistical differences between the artificially generated text and human produced text based on the distribution of parts of speech elements.

The authors develop a method for detecting fake AI-generated images from real images.

In this article the authors look at phantom loads of common kitchen appliances and found that the appliances looked at have a phantom load of 10.9%. Understanding phantom loads is important as it can reduce energy grid usage and energy bill costs for homeowners.

Autism spectrum disorder (ASD) is hard to correctly diagnose due to the very subjective nature of diagnosing it: behavior analysis. Due to this issue, we sought to find a machine learning-based method that diagnoses ASD without behavior analysis or helps reduce misdiagnosis.