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The effect of floating plant on water purification: Comparison of the water purification capability of Water Hyacinth, Duckweed, and Azolla

Park et al. | Nov 21, 2020

The effect of floating plant on water purification: Comparison of the water purification capability of Water Hyacinth, Duckweed, and Azolla

Clean water is a necessity for every household, yet water pollution is a serious problem in many parts of the world and plays a major role in compromising water security in the 21st century. In this paper, the authors address the utility of several plants as natural water purifiers. They estimate the effectiveness of duckweed, hyacinth, and azolla in improving the quality of water from the Mithi river in India by measuring several metrics. They conclude that all three plants are effective in improving water quality, suggesting that these plants as eco-friendly options for water treatment.

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Banana-based Biofuels for Combating Climate Change: How the Composition of Enzyme Catalyzed Solutions Affects Biofuel Yield

Klein-Hessling Barrientos et al. | May 27, 2020

Banana-based Biofuels for Combating Climate Change: How the Composition of Enzyme Catalyzed Solutions Affects Biofuel Yield

The authors investigate whether amylase or yeast had a more prominent role in determining the bioethanol concentration and bioethanol yield of banana samples. They hypothesized that amylase would have the most significant impact on the bioethanol yield and concentration of the samples. They found that while yeast is an essential component for producing bioethanol, the proportion of amylase supplied through a joint amylase-yeast mixture has a more significant impact on the bioethanol yield. This study provides a greater understanding of the mechanisms and implications involved in enzyme-based biofuel production, specifically of those pertaining to amylase and yeast.

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Evaluating machine learning algorithms to classify forest tree species through satellite imagery

Gupta et al. | Mar 18, 2023

Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Image credit: Sergei A

Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.

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