Browse Articles

This study explores global trends in average total cholesterol levels among adults from 1980 to 2018, finding a significant decline in both men and women, with a sharper decrease among men. While these improvements likely reflect advances in public health and medical treatment, the persistent gender gap highlights the need for more targeted approaches to cardiovascular disease prevention.

Galaxy clusters offer several advantages for measuring H₀ compared to traditional methods, such as Cepheid variables or Type Ia supernovae. Unlike individual stars or supernovae, clusters are less affected by local variations in stellar population or interstellar medium properties, providing a more stable and consistent measure over large cosmological distances. This work proposes using galaxy clusters as an alternative method for determining the H₀. It provides an independent perspective on the H₀ debate and contribute to ongoing efforts to reconcile the differing values obtained from the other two measurements.

This study compares traditional and discovery-based instructional methods in online middle school mathematics education. Findings show that discovery-based learning significantly improves students’ academic performance and attitudes, highlighting the value of inquiry-driven instruction for enhancing both understanding and motivation.

The authors assess the relationship between supportive family environments and internalized stigma in adolescents.

This study aimed to combat widespread hydrocarbon residue persistently polluting global water sources by developing and testing the ability of modified iron(III) oxide-hydroxide (FeO(OH)) nanoparticles to remove small amounts of motor oil from freshwater

Tax incentives for sustainable technology are a key part of the push for a greener future. However, these incentives may not reach all income strata equally. Using a machine learning approach, this study analyzed the distributional effects of residential energy tax credits across different income levels in the United States.

The authors looked at which measurements from the NFL combine were the most predictive of success for defensemen in the NFL.

The authors looked at the ability to detect heart disease before the onset of severe clinical symptoms.

The authors looked at the ability of different machine learning algorithms to predict the level of financial corruption in different countries.

The authors looked at different factors, such as age, pre-existing conditions, and geographic region, and their ability to predict what an individual's health insurance premium would be.