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Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

Chaudhuri et al. | Oct 12, 2020

Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

In this study, the authors investigate the effects of different algal growth media on algae's ability to perform carbon dioxide biofixation, or utilize carbon dioxide by fixing it into fatty acids within the cells. More specifically, carbon dioxide biofixation of Chlorella vulgaris was cultured in one of four media options and carbon dioxide was measured and compared to controls. The study results demonstrated that the use of media can enhance algae's capacity for biofixation and this has important implications for developing methods to reduce carbon dioxide in the environment.

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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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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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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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A Study on the Coagulating Properties of the M. oleifera Seed

Lakshmanan et al. | Feb 14, 2020

A Study on the Coagulating Properties of the <em>M. oleifera</em> Seed

In this study, the authors investigate whether Moringa Oleifera seeds can serve as material to aid in purifying water. M. oleifera seeds have coagulating properties and the authors hypothesized that including it in a water filtration system would reduce particles, specifically bacteria, in water. Their results show that this system removed the largest percent of bacteria. When used in combination with cilantro, it was actually more efficient than the other techniques! These findings have important implications for creating better and more economical water purification systems.

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Cleaning up the world’s oceans with underwater laser imaging

Gurbuz et al. | Jul 07, 2023

Cleaning up the world’s oceans with underwater laser imaging
Image credit: Naja Bertolt Jensen

Here recognizing the growing amount of plastic waste in the oceans, the authors sought to develop and test laser imaging for the identification of waste in water. They found that while possible, limitations such as increasing depth and water turbidity result in increasing blurriness in laser images. While their image processing methods were somewhat insufficient they identified recent methods to use deep learning-based techniques as a potential avenue to viability for this method.

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A study on the stretching behavior of rubber bands

Davuluri et al. | Jan 18, 2022

A study on the stretching behavior of rubber bands

Here, the authors considered the stretching behavior of rubber bands by exposing the rubber bands to increasing loads and measuring their stretch response. They found that a linear stretch response was observed for intermediate loading steps, but this behavior was lost at lower or higher loads, deviating from Hooke's Law. The authors suggest that studies such as these can be used to evaluate other visco-elastic structures.

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