Browse Articles

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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Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification

Balaji et al. | Sep 11, 2021

Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification

The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.

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Synergistic Effects of Metformin and Captopril on C. elegans

Kadıoğlu et al. | Jul 10, 2018

Synergistic Effects of Metformin and Captopril on <em>C. elegans</em>

Kadıoğlu and Oğuzalp study the synergistic effects of Metformin and Captopril, two commonly prescribed drugs for type 2 diabetes and hypertension, respectively. Using C. elegans nematodes as a model system, the authors find that the nematodes decreased in average body length when exposed to Metformin or Captopril individually, but grew 11% in body length when both drugs were used together. Because C. elegans body size is regulated in part by the TGF-β signaling pathway, the authors suggest that synergistic effects of these two drugs may be modulating TGF-β activity, a previously uncharacterized phenomenon.

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Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

Mukai et al. | Oct 27, 2020

Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

In this study, the authors tested different approaches for removing arsenic from rice. Due to higher arsenic levels in water, some areas grow rice with higher levels as well. This is a health hazard and so developing methods to remove arsenic from the rice will be helpful to many. Using a rapid arsenic kit, the authors found that activated charcoal was the most effective at removing arsenic from rice.

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