Browse Articles

Effectiveness of Biodegradable Plastic in Preventing Food Spoilage

Zhang et al. | Mar 20, 2012

Effectiveness of Biodegradable Plastic in Preventing Food Spoilage

Most people put little thought into the type of plastic wrap they use to store their leftovers. This study investigates the differences between biodegradable plastic wrap and non-biodegradable plastic wrap in their ability to prevent food spoilage. Does one work better than the other? Read more to find out!

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Two Wrongs Could Make a Right: Food Waste Compost Accelerated Polystyrene Consumption of Tenebrio molitor

Fu et al. | Jul 13, 2020

Two Wrongs Could Make a Right: Food Waste Compost Accelerated Polystyrene Consumption of <em>Tenebrio molitor</em>

Expanded polystyrene (EPS) is a plastic used to make food containers and packing materials that poses a threat to the environment. Mealworms can degrade EPS, but at a slow rate. Here, researchers assessed the impact of food waste compost and oats on the speed of EPS consumption by mealworms, superworms, and waxworms. A positive correlation was found between food waste compost supplementation and EPS consumption, especially by mealworms, indicating a potential industrial application.

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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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Creating a drought prediction model using convolutional neural networks

Bora et al. | Oct 08, 2024

Creating a drought prediction model using convolutional neural networks
Image credit: The authors

Droughts kill over 45,000 people yearly and affect the livelihoods of 55 million others worldwide, with climate change likely to worsen these effects. However, unlike other natural disasters (hurricanes, etc.), there is no early detection system that can predict droughts far enough in advance to be useful. Bora, Caulkins, and Joycutty tackle this issue by creating a drought prediction model.

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A juxtaposition of the effects of natural and chemical fertilizers on Ocimum basilicum

Wilson et al. | Jun 03, 2024

A juxtaposition of the effects of natural and chemical fertilizers on <i>Ocimum basilicum</i>
Image credit: The authors

Agricultural fertilizer application is a key innovation in providing enough food to feed the world. Fertilizers come in various types and farmers must choose which fertilizer is the best for their applications. To learn more about the effectiveness of various fertilizers, Wilson and Rasmus studied the effects of natural and chemical fertilizers on growth of basil plants.

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Analysis of electrodialysis as a method of producing potable water

Shen et al. | May 03, 2024

Analysis of electrodialysis as a method of producing potable water

Here, seeking a way to convert the vast quantity of seawater to drinking water, the authors investigated the purification of seawater to drinking water through electrodialysis. Using total dissolved solids (TDS) as their measure, they found that electrodialysis was able to produce deionized water with TDS values under the acceptable range for consumable water.

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Groundwater prediction using artificial intelligence: Case study for Texas aquifers

Sharma et al. | Apr 19, 2024

Groundwater prediction using artificial intelligence: Case study for Texas aquifers

Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.

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Enhancing marine debris identification with convolutional neural networks

Wahlig et al. | Apr 03, 2024

Enhancing marine debris identification with convolutional neural networks
Image credit: The authors

Plastic pollution in the ocean is a major global concern. Remotely Operated Vehicles (ROVs) have promise for removing debris from the ocean, but more research is needed to achieve full effectiveness of the ROV technology. Wahlig and Gonzales tackle this issue by developing a deep learning model to distinguish trash from the environment in ROV images.

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