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Toxic particulates in the atmosphere pose significant health risks, and while modern masks can help reduce inhalation of these pollutants, their availability may be limited during health crises. This study evaluated the effectiveness of household fabrics (cotton, fleece, wool, and rayon) as particulate filters, finding that cotton outperformed the others in filtration efficiency, while rayon was the least effective. The findings suggest that cotton is a preferable alternative for filtration purposes, while rayon should be avoided.

In this study, the authors investigate the crystallization kinetics of vanillin thin films from a solution or a melt, as well as how a silane coating on the glass surface affects these properties.

This study uses interpretable machine learning models, lasso and ridge regression with Shapley analysis, to identify key sales drivers for Corporación Favorita, Ecuador’s largest grocery chain. The results show that macroeconomic factors, especially labor force size, have the greatest impact on sales, though geographic and seasonal variables like city altitude and holiday proximity also play important roles. These insights can help businesses focus on the most influential market conditions to enhance competitiveness and profitability.

This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.

In this study the authors looked at the ability of the Discrete Fourier Transform (DFT) to analyze different musical elements. They found that DFT is a powerful method to analyze recorded music.

The authors looked at different ways to build computational resources that would analyze shooting form for basketball players.

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.

This study investigates the effects of the PROTAC compound A1874 on CT26 colon carcinoma cells, focusing on its ability to degrade the protein BRD4 and reduce cell viability. While A1874 had previously shown effectiveness in other colon cancer cell lines, its impact on CT26 cells was unknown.

Default opt-ins and social proof tags effect on decision making in an e-commerce context

Improving the classifier of the difficulty level of Sudoku.