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An Analysis of Soil Microhabitats in Revolutionary War, Civil War, and Modern Graveyards on Long Island, NY

Caputo et al. | May 05, 2019

An Analysis of Soil Microhabitats in Revolutionary War, Civil War, and Modern Graveyards on Long Island, NY

Previously established data indicate that cemeteries have contributed to groundwater and soil pollution, as embalming fluids can impact the microbiomes that exist in decomposing remains. In this study, Caputo et al hypothesized that microbial variation would be high between cemeteries from different eras due to dissimilarities between embalming techniques employed, and furthermore, that specific microbes would act as an indication for certain contaminants. Overall, they found that there is a variation in the microbiomes of the different eras’ cemeteries according to the concentrations of the phyla and their more specific taxa.

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Talinum paniculatum root exhibits synergistic antimicrobial activity with Tetracycline, Erythromycin, and Streptomycin against S. aureus but has no observed effect on antibiotic efficacy against E. coli

Patel et al. | Jan 09, 2018

Talinum paniculatum root exhibits synergistic antimicrobial activity with Tetracycline, Erythromycin, and Streptomycin against S. aureus but has no observed effect on antibiotic efficacy against E. coli

Patel et al. explore whether T. paniculatum plant extract can work with modern antibiotics to increase antibiotic efficacy against common disease-causing bacteria. The plant extract in conjunction with the antibiotic shows promise in battling S. aureus. The authors present a cost-effective method to increase antibiotic efficacy in a time where antibiotic resistant bacteria is becoming a growing problem.

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An explainable model for content moderation

Cao et al. | Aug 16, 2023

An explainable model for content moderation

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.

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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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