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The authors looked at the ability of different deep learning models to predict the presence of lung cancer from chest CT scans. They found that a pre-trained CNN model performed better than an autoencoder model.

The authors compare air quality in the presence and absence of a living wall in a high school hallway in Brooklyn, NY.

Here the authors investigated air quality forecasting in India, comparing traditional time series models like SARIMA with deep learning models like LSTM. The research found that SARIMA models, which capture seasonal variations, outperform LSTM models in predicting Air Quality Index (AQI) levels across multiple Indian cities, supporting the hypothesis that simpler models can be more effective for this specific task.

Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.

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.

The authors develop a method for detecting fake AI-generated images from real images.

The authors use machine learning to develop an evidence-based detection tool for identifying human trafficking.

The authors looked at the primary structure of lignin peroxidase in an attempt to identify mutations that would improve both the stability and solubility of the peroxidase protein. The goal is to engineer peroxidase enzymes that are stable to help break down polymers, such as PVC, into monomers that can be reused instead of going to landfills.

Someday, rockets from Earth may be launched towards worlds beyond our solar system. But will these rockets be able to reach their destination within a human lifetime? Ramaswamy and Giovinazzi simulate rocket launches to an Earth-like exoplanet to uncover whether it's physically possible to complete the journey within a lifetime.

Digital compasses are essential in technology that we use in our everyday lives: phones, vehicles, and more. Li and Liu address the accuracy of these devices by presenting a new algorithm for accurately calibrating low-cost magnetometers.