Here, the authors sought to better understand how and why people experience beauty in music. They explored this fundamental aesthetic response by considering numerous emotional responses of participants to diverse musical excerpts using a 42-item Aesthetic Emotions Scale assessment. They found that the highly nuanced emotional experience of beauty in music includes positive, negative, and knowledge-related feelings.

In this study, the authors test the effect that the tilt angle of a solar panel has on the amount of energy it generates. This investigation highlights a simple way that people can harvest renewable energy more efficiently and effectively.

In this study, the authors measure the relationship between the Gini coefficient, a common measure of income inequality, and Black and White maternal mortality rates by state and year.

This study assesses the capacity for milkweed species, an important host plant for Monarch butterflies, to grow in desert environments with different water levels.

The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.

The authors test the usefulness of zinc oxide microparticles relative to zinc oxide nanoparticles as antibacterial agents.

Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.

The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.

In this study, the authors tested the ability and accuracy of a neural net to identify patterns in complex number matrices.

The authors explore how similar exoplanets are to Earth and whether they could be inhabited by humans and other living organisms.