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Here, the authors used surface electromyography to measure the effects of caffeine intake on the resting activity of muscles. They found a significant increase in the measured amplitude suggesting that caffeine intake increased the number of activated muscle fibers during rest. While previous research has focused on caffeine's effect on the contraction signals of muscles, this research suggests that its effects extend to even when a muscle is at rest.

In this study, the authors investigate the effect of remote learning (due to the COVID-19 pandemic) on sleeping habits amongst teenagers in Ohio. Using survey results, sleep habits and attitudes toward school were assessed before and after the COVID-19 pandemic.

This paper looks at using spent coffee grounds as a partial substitute for titanium dioxide (TiO₂) as a catalyst for chemical reactions. Using UV-Vis spectrophotometry, they found that adding the coffee grounds to TiO₂ in a 3:1 ratio, there is still meaningful catalytic activity. This offers a cheaper solution than just using pure TiO₂.

The authors developed a quantum inspired model for stock market fluctuations.

The authors looked at how the length of an audio clip used of a song impacted the ability to properly classify it by musical genre.

The authors survey teenagers within the United States regarding the effect of social media use on sleep quality and attention span.

The authors combine fine needle aspiration biopsy and machine learning algorithms to develop a breast cancer detection method suitable for resource-constrained regions that lack access to mammograms.

This study explored how green spaces, climate, traffic, and air quality (GCTA) collectively influence asthma-related emergency department visits in the U.S using machine learning models and explainable AI.

The authors looked into eco-friendly alternatives for insulating material. They ultimately found that a polyurethane derived from eggshells was an effective insulator and further research into it is warranted.

The authors looked at ways to provide better forecasting on website traffic. They found that deep learning models performed better than statistical models.