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

Impact of carbon tax and dividend on financial security

Autonomous drone imaging combined with machine learning offers a promising approach for early detection of invasive species. In this study, students built an autonomous drone and compared three models: CNN, SGDC, and XGBoost, to identify Brassica nigra from aerial footage. Their results show that CNNs most effectively recognize key visual features, demonstrating strong potential for supporting conservation and invasive plant management.

The authors analyzed racial and ethnic representation in studies on PFAS and neurological health outcomes.

The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.

The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.

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.

This study uses a fruit fly model of type 1 diabetes (T1D) to determine whether strengthening intestinal tight junctions to reduce intestinal permeability would improve T1D symptoms.

This study examines how environmental conditions influence the abundance and ecological role of the sea cucumber Opheodesoma spectabilis in Kāneʻohe Bay. Field observations and laboratory experiments showed that the species is more common in algae-dominated sandy habitats, where it improves water clarity and increases dissolved oxygen through bioturbation. However, exposure to very high temperatures caused rapid mortality, suggesting that marine heat waves could threaten this species and the ecological functions it provides.

The authors looked at the impact of citrate and lactate on glioblastoma progression. Their results provide important insights for future immunotherapies aimed at treating glioblastoma.