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The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.

The authors looked at the emissions from a small, carbureted engine that was being powered by a mix of ethanol and methanol compared to E10 gasoline. The found that across all four pollutants measured, the ethanol-methanol mixture resulted in less emissions compared to the E10 fuel.

The authors examine a relationship between tweet sentiment and stock market behavior during the early weeks of the COVID-19 pandemic.

The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.

The authors looked at the ability to grow S. platensis on a larger scale with reduced cost given that it is currently quite expensive to grow, but poses as an important food source in the future.

Recent research suggests that the "American Dream" of income mobility may be becoming increasingly hard to obtain. Datta and Schmitz explore the role of government spending in socioeconomic opportunity by determining which state government spending components are associated with increased income mobility.

The authors investigate whether human blood cancers carrying mutations in DNA repair genes possess increased sensitivity to common chemotherapy drugs cisplatin or gemcitabine.

Here recognizing the potential for pollution to impact the ecosystems of local waterways, the authors investigated the growth of tiger lilies, which are invasive to the Potomac River, in relation to the level of pollution. The authors report that increasing levels of pollution led to increased growth of the invasive species based on their study.

In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.

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.