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Using machine learning to develop a global coral bleaching predictor

Madireddy et al. | Feb 21, 2023

Using machine learning to develop a global coral bleaching predictor
Image credit: Madireddy, Bosch, and McCalla

Coral bleaching is a fatal process that reduces coral diversity, leads to habitat loss for marine organisms, and is a symptom of climate change. This process occurs when corals expel their symbiotic dinoflagellates, algae that photosynthesize within coral tissue providing corals with glucose. Restoration efforts have attempted to repair damaged reefs; however, there are over 360,000 square miles of coral reefs worldwide, making it challenging to target conservation efforts. Thus, predicting the likelihood of bleaching in a certain region would make it easier to allocate resources for conservation efforts. We developed a machine learning model to predict global locations at risk for coral bleaching. Data obtained from the Biological and Chemical Oceanography Data Management Office consisted of various coral bleaching events and the parameters under which the bleaching occurred. Sea surface temperature, sea surface temperature anomalies, longitude, latitude, and coral depth below the surface were the features found to be most correlated to coral bleaching. Thirty-nine machine learning models were tested to determine which one most accurately used the parameters of interest to predict the percentage of corals that would be bleached. A random forest regressor model with an R-squared value of 0.25 and a root mean squared error value of 7.91 was determined to be the best model for predicting coral bleaching. In the end, the random model had a 96% accuracy in predicting the percentage of corals that would be bleached. This prediction system can make it easier for researchers and conservationists to identify coral bleaching hotspots and properly allocate resources to prevent or mitigate bleaching events.

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The most efficient position of magnets

Shin et al. | Mar 28, 2024

The most efficient position of magnets
Image credit: immo RENOVATION

Here, the authors investigated the most efficient way to position magnets to hold the most pieces of paper on the surface of a refrigerator. They used a regression model along with an artificial neural network to identify the most efficient positions of four magnets to be at the vertices of a rectangle.

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Effects of various alkaline carbonic solutions on the growth of the freshwater algae Chlorophyceae

Jani et al. | Aug 11, 2023

Effects of various alkaline carbonic solutions on the growth of the freshwater algae Chlorophyceae
Image credit: Jordan Whitfield

Modern day fossil fuels are prone to polluting our environment, which can provide major habitat loss to many animals in our ecosystems. Algae-based biofuels have become an increasingly popular alternative to fossil fuels because of their sustainability, effectiveness, and environmentally-friendly nature. To encourage algae growth and solidify its role as an emerging biofuel, we tested basic (in terms of pH) solutions on pond water to determine which solution is most efficient in inducing the growth of algae.

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Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Sun et al. | Dec 18, 2020

Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Berberine, a natural product alkaloid, and its analogs have a wide range of medicinal properties, including antibacterial and anticancer effects. Here, the authors explored a library of alkyl or aryl berberine analogs to probe binding to double-stranded and G-quadruplex DNA. They determined that the nature of the substituent, the position of the substituent, and the nucleic acid target affect the free energy of binding of berberine analogs to DNA and G-quadruplex DNA, however berberine analogs did not result in net stabilization of G-quadruplex DNA.

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The Non-Thermal Effect of UV-B Irradiation on Onion Growth

Nashnoush et al. | Jun 09, 2020

The Non-Thermal Effect of UV-B Irradiation on Onion Growth

UV-B radiation due to the depletion of ozone threatens plant life, potentially damaging ecosystems and dismantling food webs. Here, the impact of UV-B radiation on the physiology and morphology of Allum cepa, the common onion, was assessed. Mitosis vitality decreased, suggesting UV-B damage can influence the plant’s physiology.

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