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PVC is a widely used plastic that poses harmful health hazards when burned. In this study, the authors ask whether or not burned PVC (PVC char) affects bacterial transformation.

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

Depression affects millions globally, yet identifying symptoms remains challenging. This study explored detecting depression-related patterns in social media texts using natural language processing and machine learning algorithms, including decision trees and random forests. Our findings suggest that analyzing online text activity can serve as a viable method for screening mental disorders, potentially improving diagnosis accuracy by incorporating both physical and psychological indicators.

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

In this study the authors looked at the ability of artificial intelligence to detect tempo, rhythm, and intonation of a piece played on violin. Technology such as this would allow for students to practice and get feedback without the need of a teacher.

The authors looked at how the focus of someone's attention impacted what information was retained in their working memory.

The authors looked at the ability of a convolutional neural network (CNN) to sort contaminated recycling, with varying levels of contamination. They found as contamination levels increased, the CNN faced more difficulty correctly classifying items.

The authors access a panel of leaf traits across ten deciduous tree species to explore adaptive strategies between large and small trees.

The authors assessed the correlation between the stock, commodity, and consumer markets with the housing market.

The authors looked at the potential of different phenolic compounds to reduce oxidative stress (i.e., act as antioxidants).