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The authors evaluated the effect of concentration and variant of N-Acetylcysteine in hydrolyzing mucus.

The authors used machine learning to predict the presence of anxiety and burnout in students based on facial expressions and demographic information.

In this study the authors looked at the ability to navigate planes in space between randomly placed planets. They used machine and reinforcement learning to run simulations and found that they were able to identify optimal paths for travel. In the future these techniques may allow for safer travel in unknown spaces.

In this study the authors looked at the ability of the Discrete Fourier Transform (DFT) to analyze different musical elements. They found that DFT is a powerful method to analyze recorded music.

The authors looked at different combinations of risk-adjusted return measures to determine which combination would provide an optimal return for investors. They found that different combinations performed better dependent on investment timeframe.

Domestic waste classification using convolutional neural network

Building on previous work by earlier astronomers, the authors investigate the correlation between the density and size of celestial objects in the universe, including neutron stars, galaxies, and galaxy clusters.

Authors examine the effectiveness of Large Language Models (LLMs) like BERT, MathBERT, and OpenAI GPT-3.5 in assisting middle school students with math word problems, particularly following the decline in math performance post-COVID-19.

Brain-Computer Interface (BCI) allows users, especially those with paralysis, to control devices through brain activity. This study explored using a custom transformer model to decode neural signals into handwritten text for individuals with limited motor skills, comparing its performance to a traditional RNN-based BCI.

Air pollution is thought to increase the prevalence of health conditions like chronic obstructive pulmonary disease (COPD). Ganeshwaran and Ropiak investigate this relationship by determining whether there is a correlation between between one type of air pollution (fine particulate matter concentrations) and COPD hospitalization rates in Massachusetts.