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Correlation between shutdowns and CO levels across the United States.

Gupta et al. | Dec 05, 2021

Correlation between shutdowns and CO levels across the United States.

Concerns regarding the rapid spread of Sars-CoV2 in early 2020 led company and local governmental officials in many states to ask people to work from home and avoid leaving their homes; measures commonly referred to as shutdowns. Here, the authors investigate how shutdowns affected carbon monoxide (CO) levels in 15 US states using publicly available data. Their results suggest that CO levels decreased as a result of these measures over the course of 2020, a trend which started to reverse after shutdowns ended.

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The Cohesiveness of the Oscillating Belousov-Zhabotinsky Reaction

Gottlieb et al. | Dec 18, 2018

The Cohesiveness of the Oscillating Belousov-Zhabotinsky Reaction

In this study the author undertakes a careful characterization of a special type of chemical reaction, called an oscillating Belousov-Zhabotinsky (or B-Z) reaction, which has a number of existing applications in biomedical engineering as well as the potential to be useful in future developments in other fields of science and engineering. Specifically, she uses experimental measurements in combination with computational analysis to investigate whether the reaction is cohesive – that is, whether the oscillations between chemical states will remain consistent or change over time as the reaction progresses. Her results indicate that the reaction is not cohesive, providing an important foundation for the development of future technologies using B-Z reactions.

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Analysis of the Exoplanet HD 189733b to Confirm its Existence

Babaria et al. | Sep 21, 2020

Analysis of the Exoplanet HD 189733b to Confirm its Existence

In this study, the authors study features of exoplanet 189733 b. This exoplanet, or planets that orbit stars other than the Sun, is found in the HD star system. Using a DSLR camera, they constructed a high caliber exoplanet transit detection tracker to study the orbital periods, radial velocity, and photometry of 189733 b. They then compared results from their system to data collected by other high precision studies. What they found was that their system produced results supporting previously published studies. These results are exciting results from the solar system demonstrating the importance of validating radial velocity and photometry data using high-precision studies.

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Pichia kudriavzevii Yeast Exposure Increases the Asthmatic Behavior of Alveolar Epithelial Cells In Vitro

Ortega et al. | Jun 07, 2019

<em>Pichia kudriavzevii</em> Yeast Exposure Increases the Asthmatic Behavior of Alveolar Epithelial Cells <em>In Vitro</em>

Asthma affects over 334 million people worldwide and is triggered by inhalation of environmental stimuli. The authors of this study characterized the effect of exposure to common spoilage yeast, Pichia kidriavzevii on alveolar epithelial cells. A direct correlation between infection duration and asthmatic status of these cells was found, indicating the potential for this yeast to be an environmental stimulus of asthma and warranting further study.

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Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques

Chatterjee et al. | Oct 25, 2021

Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques

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.

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The Effects of Micro-Algae Characteristics on the Bioremediation Rate of Deepwater Horizon Crude Oil

Cao et al. | Jun 17, 2013

The Effects of Micro-Algae Characteristics on the Bioremediation Rate of Deepwater Horizon Crude Oil

Environmental disasters such as the Deepwater Horizon oil spill can be devastating to ecosystems for long periods of time. Safer, cheaper, and more effective methods of oil clean-up are needed to clean up oil spills in the future. Here, the authors investigate the ability of natural ocean algae to process crude oil into less toxic chemicals. They identify Coccochloris elabens as a particularly promising algae for future bioremediation efforts.

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