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The authors test different machine learning algorithms to remove background noise from audio to help people with hearing loss differentiate between important sounds and distracting noise.

The authors use pictures of candy wrappers and neural networks to improve nutritional accuracy of diet-tracking apps.

In this study the authors looked the trajectories of cosmic rays moving through a dipole field. They found that the trajectories of cosmic rays are determined by a particle's energy and interaction with Earth's B field.

An integrated plant that would generate energy from solar power and provide clean water would help solve multiple sustainability issues. The feasibility of such a plant was investigated by looking at the efficacy of several different modules of such a plant on a small scale.

Hydroponics is often promoted as a highly efficient alternative to traditional soil farming, but its effectiveness in small indoor polyculture systems is not well understood. In this study, students compared plant growth and maturity across hydroponic and soil-based indoor polycultures and found that soil grown plants were generally taller and more mature than those grown hydroponically. These results suggest that soil-based methods may outperform hydroponics in certain household polyculture settings.

This study found that anxiety induced by a suspenseful story increased communication between the brain’s salience, default mode, and central executive networks, with the central executive network acting as a bridge during peak tension. These findings suggest that anxiety alters large-scale brain connectivity patterns and may help inform future diagnostic tools and personalized treatments for anxiety disorders.

In this study, the authors investigate the crystallization kinetics of vanillin thin films from a solution or a melt, as well as how a silane coating on the glass surface affects these properties.

This study explores the factors that influence coffee quality ratings using data from the Coffee Quality Institute. Through a regression model based on gradient descent, the authors aimed to predict coffee ratings (total cup points) and hypothesized that sweetness and the coffee producer would be the most influential factors.

The authors train a neural network to detect text-based emotions including joy, sadness, anger, fear, love, and surprise.

Pulmonary diseases like lung cancer and valley fever pose serious health challenges, making accurate and rapid diagnostics essential. This study developed a MATLAB-based software tool that uses computer vision techniques to differentiate between these diseases by analyzing features of lung nodules in CT scans, achieving higher precision than traditional methods.