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Mathematical modeling of plant community composition for urban greenery plans

Fang et al. | Jul 05, 2023

Mathematical modeling of plant community composition for urban greenery plans
Image credit: CHUTTERSNAP

Here recognizing the importance of urban green space for the health of humans and other organisms, the authors investigated if mathematical modeling can be used to develop an urban greenery management plan with high eco-sustainability by calculating the composition of a plant community. They optimized and tested their model against green fields in a Beijing city park. Although the compositions predicted by their models differed somewhat from the composition of testing fields, they conclude that by using a mathematical model such as this urban green space can be finely designed to be ecologically and economically sustainable.

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How CAFOs affect Escherichia coli contents in surrounding water sources

Lieberman et al. | Feb 24, 2023

How CAFOs affect <i>Escherichia coli</i> contents in surrounding water sources
Image credit: CDC

Commercial Concentrated Animal Feeding Operations (CAFOs) produce large quantities of waste material from the animals being housed in them. These feedlots found across the United States contain livestock that produce waste that results in hazardous runoff. This study examines how CAFOs affect water sources by testing for Escherichia Coli (E. coli) content in bodies of water near CAFOs.

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Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

Ramprasad et al. | Mar 18, 2020

Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

In this study, the authors test whether providing a larger dataset of glass transition temperatures (Tg) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and Tg is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's Tg, providing valuable improvements to this useful platform.

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The Effect of Ultraviolet Radiation and the Antioxidant Curcumin on the Longevity, Fertility, and Physical Structure of Drosophila melanogaster: Can We Defend Our DNA?

Lateef et al. | May 18, 2019

The Effect of Ultraviolet Radiation and the Antioxidant Curcumin on the Longevity, Fertility, and Physical Structure of <em>Drosophila melanogaster</em>: Can We Defend Our DNA?

Ultraviolet (UV) radiation is known to alter DNA structure and impair cellular function in all living organisms. In this study, Lateef et al examine the effects of UV radiation to determine whether antioxidant-enriched nutrition can combat the potential deleterious effects of UV radiation on Drosophila melanogaster. They found that UVB (320nm) radiation caused a 59% decrease in the Drosophila lifespan and mutagenic effects on flies' physical appearance, but did not significantly affect fertility. Curcumin significantly prolonged lifespan and enhanced fertility for both UV- and non-UV-exposed flies. The research demonstrates the positive potential of natural antioxidants as weapons against radiation-induced diseases including cancer.

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The Effect of Various Preparation Methods on the Spoilage Rate of Roma Tomatoes (Solanum lycopersicum)

Cataltepe et al. | Feb 22, 2018

The Effect of Various Preparation Methods on the Spoilage Rate of Roma Tomatoes (Solanum lycopersicum)

As levels of food waste continue to rise, it is essential to find improved techniques of prolonging the shelf life of produce. The authors aimed to find a simple, yet effective, method of slowing down spoilage in tomatoes. Linear regression analysis revealed that the tomatoes soaked salt water and not dried displayed the lowest correlation between time and spoilage, confirming that this preparation was the most effective.

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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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