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Variations in Heat Absorption and Release of Earth Surfaces During Fall in Laramie, Wyoming

Ramesh et al. | Sep 08, 2020

Variations in Heat Absorption and Release of Earth Surfaces During Fall in Laramie, Wyoming

Here the authors investigate the contributions of man-made surfaces in Laramie, Wyoming to the Urban Heat Island (UHI) effect. Heat absorption and release by five surfaces were measured in the autumn of 2018. By recording temperatures of man-made and natural surfaces at early morning, mid-afternoon, and evening using an infrared thermometer, the authors determined that man-made surfaces retained more heat in fall than natural surfaces.

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Singlet oxygen production analysis of reduced berberine analogs via NMR spectroscopy

Su et al. | Feb 10, 2023

Singlet oxygen production analysis of reduced berberine analogs via NMR spectroscopy

Berberine is a natural product isoquinoline alkaloid derived from plants of the genus Berberis. When exposed to photoirradiation, it produces singlet oxygen through photosensitization of triplet oxygen. Through qNMR analysis of 1H NMR spectra gathered through kinetic experiments, we were able to track the generation of a product between singlet oxygen and alpha terpinene, allowing us to quantitatively measure the photosensitizing properties of our scaffolds.

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Development of Two New Efficient Means of Wastewater Treatment

Bao et al. | Feb 06, 2014

Development of Two New Efficient Means of Wastewater Treatment

The water we use must be treated and cleaned before we release it back into the environment. Here, the authors investigate two new techniques for purifying dissolved impurities from waste water. Their findings may give rise to more cheaper and more efficient water treatment and help keep the planet greener.

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How has California’s Shelter-in-Place Order due to COVID-19 and the Resulting Reduction in Human Activity Affected Air and Water Quality?

Everitt et al. | Feb 15, 2021

How has California’s Shelter-in-Place Order due to COVID-19 and the Resulting Reduction in Human Activity Affected Air and Water Quality?

As the world struggled to grapple with the emerging COVID-19 pandemic in 2020, many countries instated policies to help minimize the spread of the virus among residents. This inadvertently led to a decrease in travel, and in some cases, industrial output, two major sources of pollutants in today's world. Here, the authors investigate whether California's shelter-in-place policy was associated with a measurable decrease in water and air pollution in that state between June and July of 2020, compared to the preceeding five years. Their findings suggest that, by some metrics, air quality improved within certain areas while water quality was relatively unchanged. Overall, these findings suggest that changing human behavior can, indeed, help reduce the level of air pollutants that compromise air quality.

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Failure of colony growth in probiotic Lactobacillus casei Shirota as result of preservative sorbic acid

Raymond et al. | May 07, 2023

Failure of colony growth in probiotic <i>Lactobacillus casei</i> Shirota as result of preservative sorbic acid

This study tested the proficiency of different concentrations of the antimicrobial sorbic acid to inhibit the probiotic Lactobacillus casei Shirota. It was hypothesized that sorbic acid’s use as a bacterial deterrent would also target this bacterial strain of Lactobacillus. The results supported the hypothesis, with the colony count of L. casei Shirota having significant decreases at all concentrations of sorbic acid. These results additionally suggest that even under the FDA sorbic acid restrictions of 0.03% concentration, damaging effects could be seen in L. casei Shirota.

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Prediction of molecular energy using Coulomb matrix and Graph Neural Network

Hazra et al. | Feb 01, 2022

Prediction of molecular energy using Coulomb matrix and Graph Neural Network

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

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