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A Temperature-Based Comparison of Compounds Found in Bao Chong Tea, Green Tea, and Black Tea

Lin et al. | May 14, 2019

A Temperature-Based Comparison of Compounds Found in Bao Chong Tea, Green Tea, and Black Tea

While tea has a complex history, recently the health benefits of this beverage have come into focus. In this study, researchers sought to compare the levels of caffeine, catechins and L-theanine between different types of tea using NMR spectroscopy. Further, the impact of brewing temperature on the release of these compounds was also assessed. Of those tested, Bao Chong tea had the highest levels of these compounds. Brewing temperatures between 45ºC and 75ºC were found to be optimal for compound release. These results can help consumers make informed choices about their tea preparation and intake.

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Detection and Control of Spoilage Fungi in Refrigerated Vegetables and Fruits

Chari et al. | May 16, 2021

Detection and Control of Spoilage Fungi in Refrigerated Vegetables and Fruits

Food spoilage leads to a significant loss in agricultural produce each year. Here, the authors investigate whether certain essential oils can protect against fungus-mediated spoilage of fruits and vegetables. Their results suggest that the compounds they tested might indeed inhibit fungal growth, at various temperatures, a promising result that could reduce food wasting.

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Mutation of the Catalytic Cysteine in Anopheles gambiae Transglutaminase 3 (AgTG3) Abolishes Plugin Crosslinking Activity without Disrupting Protein Folding Properties

Pham et al. | May 02, 2014

Mutation of the Catalytic Cysteine in <em>Anopheles gambiae</em> Transglutaminase 3 (AgTG3) Abolishes Plugin Crosslinking Activity without Disrupting Protein Folding Properties

Malaria is a major public health issue, especially in developing countries, and vector control is a major facet of malaria eradication efforts. Recently, sterile insect technique (SIT), or the release of sterile mosquitoes into the wild, has shown significant promise as a method of keeping vector populations under control. In this study, the authors investigate the Anopheles gambiae transglutaminase 3 protein (AgT3), which is essential to the mating of the Anopheles mosquito. They show that an active site mutation is able to abolish the activity of the AgT3 enzyme and propose it as a potential target for chemosterilant inhibitors.

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A land use regression model to predict emissions from oil and gas production using machine learning

Cao et al. | Mar 24, 2023

A land use regression model to predict emissions from oil and gas production using machine learning

Emissions from oil and natural gas (O&G) wells such as nitrogen dioxide (NO2), volatile organic compounds (VOCs), and ozone (O3) can severely impact the health of communities located near wells. In this study, we used O&G activity and wind-carried emissions to quantify the extent to which O&G wells affect the air quality of nearby communities, revealing that NO2, NOx, and NO are correlated to O&G activity. We then developed a novel land use regression (LUR) model using machine learning based on O&G prevalence to predict emissions.

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Machine learning on crowd-sourced data to highlight coral disease

Narayan et al. | Jul 26, 2021

Machine learning on crowd-sourced data to highlight coral disease

Triggered largely by the warming and pollution of oceans, corals are experiencing bleaching and a variety of diseases caused by the spread of bacteria, fungi, and viruses. Identification of bleached/diseased corals enables implementation of measures to halt or retard disease. Benthic cover analysis, a standard metric used in large databases to assess live coral cover, as a standalone measure of reef health is insufficient for identification of coral bleaching/disease. Proposed herein is a solution that couples machine learning with crowd-sourced data – images from government archives, citizen science projects, and personal images collected by tourists – to build a model capable of identifying healthy, bleached, and/or diseased coral.

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Discovery of the Heart in Mathematics: Modeling the Chaotic Behaviors of Quantized Periods in the Mandelbrot Set

Golla et al. | Dec 14, 2020

Discovery of the Heart in Mathematics: Modeling the Chaotic Behaviors of Quantized Periods in the Mandelbrot Set

This study aimed to predict and explain chaotic behavior in the Mandelbrot Set, one of the world’s most popular models of fractals and exhibitors of Chaos Theory. The authors hypothesized that repeatedly iterating the Mandelbrot Set’s characteristic function would give rise to a more intricate layout of the fractal and elliptical models that predict and highlight “hotspots” of chaos through their overlaps. The positive and negative results from this study may provide a new perspective on fractals and their chaotic nature, helping to solve problems involving chaotic phenomena.

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Survival of Escherichia coli K-12 in various types of drinking water

Hanna et al. | Sep 25, 2022

Survival of <i>Escherichia coli</i> K-12 in various types of drinking water

For public health, drinking water should be free of bacterial contamination. The objective of this research is to identify the fate of bacteria if drinking water becomes contaminated and inform consumers on which water type enables the least bacteria to survive. We hypothesized that bottled mineral water would provide the most sufficient conditions for E. coli to survive. We found that if water becomes contaminated, the conditions offered by the three water types at room temperature allow E. coli to survive up to three days. At 72 hours, the bottled spring water had the highest average colony forming units (CFUs), with tap and mineral water CFU values statistically lower than spring water but not significantly different from each other. The findings of this research highlight the need of implementing accessible quality drinking water for the underserved population and for the regulation of water sources.

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