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The explored the potential of an epitope-based vaccine for Rocio virus using computational methods and M13 bacteriophage technology. Researchers identified 30 promising B- and T-cell epitopes and designed vaccine candidates using both phage display and E. coli expression systems.

This study examines how socioeconomic status (SES) influences student mathematics achievement across countries by conducting multiple regression analyses to the Trends in International Mathematics and Science Study (TIMSS) 2019 dataset.

This study aims to examine the demographic factors that predict patterns of co-use of alcohol and marijuana in the United States. Significant findings were identified using data from the National Survey on Drug Use and Health (2012-2022), showing that there were significant differences in the prevalence of substance use among demographic groups, with young adults showing the highest co-use of alcohol and marijuana.

This study used machine learning models to examine which factors most influenced U.S. household energy consumption in 2020 using data from 18,496 households.

This study investigates PFAS contamination in Santa Clarita groundwater, focusing on potential sources. The study employs statistical analysis to assess data quality and trends which allowed them to identified domestic waste, fire extinguisher materials, and food packaging as the most likely sources of contamination.

The authors examined the impact of mutations to CDK2 on protein expression.

The authors combine fine needle aspiration biopsy and machine learning algorithms to develop a breast cancer detection method suitable for resource-constrained regions that lack access to mammograms.

Improving the classifier of the difficulty level of Sudoku.

Wind turbines are a valuable source of renewable energy, but face challenges related to unpredictable wind speed. The turbine must be able to control its angle to catch enough wind to generate electricity, while avoiding excess wind that may damage the turbine. Zhou and Wang explore different types of smart turbine controllers to see which appears optimal for electricity generation.

The authors compare rates of renewable energy adoption between states that historically vote for democrats versus republicans in presidential elections.