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Implications of various pure tones on Phaseolus vulgaris and Gaultheria shallon

Judit et al. | Jul 13, 2026

Implications of various pure tones on <i>Phaseolus vulgaris</i> and <i>Gaultheria shallon<i>

This study investigated how different sound frequencies (0, 1,000, 5,000, and 15,000 Hz) affect the growth of Phaseolus vulgaris and the transpiration rates of Gaultheria shallon. Although some differences in plant growth were observed, the authors found no consistent evidence that sound frequency enhanced overall growth or transpiration, highlighting the need for further research.

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Exploring the Factors that Drive Coffee Ratings

Agarwal et al. | May 19, 2025

Exploring the Factors that Drive Coffee Ratings

This study explores the factors that influence coffee quality ratings using data from the Coffee Quality Institute. Through a regression model based on gradient descent, the authors aimed to predict coffee ratings (total cup points) and hypothesized that sweetness and the coffee producer would be the most influential factors.

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Changing the surface properties of the backside of a silicon wafer to repel oil and prevent particle binding

Choi et al. | Feb 14, 2025

Changing the surface properties of the backside of a silicon wafer to repel oil and prevent particle binding

Wafers, essential in microchip production, can develop issues like leveling problems and wafer slip due to the formation of silanol bonds on their backside, which attract silica particles and oil. Authors tested addressing this issue with a coating of [acetoxy(polyethyleneoxy)propyl]triethoxysilane (APTS) applied to the wafer’s backside, preventing particle binding and oil adherence.

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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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