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In this study, the authors survey students and adults about how the COVID-19 pandemic has impacted their sleep patterns, eating habits, mood, physical activity, and screen time.

This study investigates the presence of alkaloids in a variety of medicinal plants using the Marquis reagent. They reveal some surprising results and how useful the Marquis reagent is.

This study explored sunscreen storage temperature affects the efficacy of sunscreen to block UV light.

This study investigated perceptions of the emerging workforce toward the use of artificial intelligence in hiring, specifically for assessing subjective "culture fit." Through a mixed-methods survey of 150 high school and early-college students in Nepal, we found a significant disconnect between organizational adoption of AI and the profound skepticism of young job candidates, who express deep concerns about fairness, transparency, and the potential for AI to perpetuate systemic discrimination.

The authors studied optimized delivery routes to reduce travel times using different traveling salesman algorithms.

α-amylase breaks down starch into glucose, which can cause blood sugar spikes and increase the risk of type II diabetes. This study tested natural extracts from cassia cinnamon and green tea as alternatives to synthetic inhibitors like acarbose, which can be costly and cause side effects.

To address the limitations in predicting the severity of Atrial Septal Defect (ASD), here the authors utilized a fluid-filled chamber model to quantify the relationship between defect size and right atrial fluid output. The findings confirmed that larger ASD diameters result in a linear increase in fluid output, validating a cost-effective model that can improve clinical prognosis and treatment planning for heart failure risks.

The authors looked at the difference in investing in stock vs. mutual funds.

The authors looked at the ability of berberine in combination with melatonin to have anticancer effects when tested in an in vitro cell model.

The authors compare current machine learning algorithms with a new Explainable AI algorithm that produces a human-comprehensible decision tree alongside predictions.