Browse Articles

Climate change is one of the most controversial challenges humans face. Here the authors investigate the dual role of clouds - to reflect incoming light away from the Earth and to reflect heat energy back toward the Earth's surface. They find that the amount of incident light energy and surface temperature decreases as the sky becomes cloudier. These results will inform longer-term studies that may compare against the amount of energy clouds reflect back toward the Earth.

Here the authors propose integrating magnetic iron (II) oxide nanoparticles into the high-density polyethylene linings of disposable paper cups to create a waterproof, magnetically responsive composite liner. Their findings demonstrate that these nanoparticles successfully bond with the plastic layer without disrupting its structural integrity, offering a viable method to improve plastic recovery through magnetic recycling and mitigate global microplastic pollution.

This study investigates how caffeine and melatonin affect learning in adolescent zebrafish, serving as a model for human teens. Using an automated system to track behavior, we found that melatonin slowed learning while caffeine caused erratic, inconsistent responses, suggesting both substances can negatively impact adolescent learning patterns. These findings highlight the need for further research into their physiological effects and potential implications for human adolescents.

This study examined whether findings from laboratory studies of baseball cognition also apply during real games. Using 2024 MLB data from 30 players, researchers analyzed batting performance under different levels of feedback and anxiety.

The authors examined the relationships between S&P 500 Technology and Financials equity sectors and their corresponding investment-grade fixed-income markets from 1995 to 2025.

The authors investigated adoption rates of solar photovoltaic power at K-12 schools in California.

The authors test symbiotic relationships among cyanobacteria species to generate more robust cultures for potential biofuel production.

This study investigates how the hyperparameters epochs and batch size affect the classification accuracy of a convolutional neural network (CNN) trained on pulsar candidate data. Our results reveal that accuracy improves with increasing number of epochs and smaller batch sizes, suggesting that with optimized hyperparameters, high accuracy may be achievable with minimal training. These findings offer insights that could help create more efficient machine learning classification models for pulsar signal detection, with the potential of accelerating pulsar discovery and advancing astrophysical research.

Investigation of the largest rigid shape that can be moved through a circular hallway of unit width with an arbitrary turn angle

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.