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This study explored how green spaces, climate, traffic, and air quality (GCTA) collectively influence asthma-related emergency department visits in the U.S using machine learning models and explainable AI.

Using machine learning to predict the risk of algae bloom

This study investigated how well food labels from 280 different brands across multiple food and drink categories in India and the US adhered to recommended nutritional labeling standards as outlined by the Codex Alimentarius.

The authors looked at alternative production processes for PHB plastic in an effort to reduce environmental impact. They found that no alternative process was able to significantly decrease the environmental impact of PHB production, but that optimizing dewatering steps during production could lead to the largest improvement on environmental impact.

Here the authors aimed to understand factors influencing adolescent fentanyl exposure, hypothesizing a positive association between social media usage, socioeconomic factors, and fentanyl abuse among U.S. teens. Their analysis of the Monitoring the Future dataset revealed that a history of suspension and use of marijuana or alcohol were linked to higher fentanyl use, and while not statistically significant, a notable positive correlation between social media use and fentanyl frequency was observed.

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.

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.

This article helps in understanding the effect of various social determinants on maternal mortality in the United States. It explains the relationship between maternal mortality rates and factors like race, income, education, and health insurance access.

Recent research confirms that climate change, driven by CO2 emissions from burning fossil fuels, poses a significant threat to humanity. In response, authors explore methods to remove CO2 from the atmosphere, including breaking its molecular bonds through high-speed collisions.

The authors looked at student behaviors around disposal of face masks. The goal of the study was to bring awareness to improper mask disposal and how the resulting litter contributes to overall environmental pollution.