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Predicting college retention rates from Google Street View images of campuses

Dileep et al. | Jan 02, 2024

Predicting college retention rates from Google Street View images of campuses
Image credit: Dileep et al. 2024

Every year, around 40% of undergraduate students in the United States discontinue their studies, resulting in a loss of valuable education for students and a loss of money for colleges. Even so, colleges across the nation struggle to discover the underlying causes of these high dropout rates. In this paper, the authors discuss the use of machine learning to find correlations between the built environment factors and the retention rates of colleges. They hypothesized that one way for colleges to improve their retention rates could be to improve the physical characteristics of their campus to be more pleasing. The authors used image classification techniques to look at images of colleges and correlate certain features like colors, cars, and people to higher or lower retention rates. With three possible options of high, medium, and low retention rates, the probability that their models reached the right conclusion if they simply chose randomly was 33%. After finding that this 33%, or 0.33 mark, always fell outside of the 99% confidence intervals built around their models’ accuracies, the authors concluded that their machine learning techniques can be used to find correlations between certain environmental factors and retention rates.

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Buttermilk and baking soda increase pancake fluffiness by liberating carbon dioxide

Rojas et al. | Sep 18, 2022

Buttermilk and baking soda increase pancake fluffiness by liberating carbon dioxide

Here, seeking a better understanding of what determines the fluffiness of a pancake, the authors began by considering a chemical reaction that results in the production of carbon dioxide gas from recipe ingredients, specifically sodium bicarbonate or baking soda. The substitution of homemade buttermilk for milk and adding more baking soda was found to result in significantly fluffier pancakes.

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Inhibiting the ERK pathway and the TRPM7 ion channel in gastric and bladder cancer cells

Yang et al. | Oct 14, 2021

Inhibiting the ERK pathway and the TRPM7 ion channel in gastric and bladder cancer cells

In this work the authors investigate new possible treatment methods for gastric and bladder cancers. They specifically targeted the transient receptor potential cation subfamily M member 7 (TRPM7), an ion channel that plays an important role in the survival of both of these cancers, and extracellular regulated kinases (ERKs),which contributes to the carcinogenesis of many cancers including gastric cancer. As a result, the authors consider the effects of Ginsenoside Rd, NS8593, curcumin, and icariin , known to inhibit TRPM7 and ERK. The authors found that these treatments decrease proliferation and induce apoptosis in studies of gastric and bladder cancer cells.

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