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In this study, the authors created a survey to assess misconceptions and knowledge deficits regarding cardiovascular diseases exist among US adults and minors.

In this study, the authors investigate an alternative way to kill bacteria other than the use of antibiotics, which is useful when considering antibiotic-resistance bacteria. They use bacteriophages, which are are viruses that can infect bacteria, and measure cell lysis. They make some important findings that these bacteriophage can lyse both antibiotic-resistant and non-resistant bacteria.

This project investigated whether previously identified genetic risk factors in non-Korean populations were associated with high gastric cancer incidence rates in Koreans.

The authors assess the relationship between supportive family environments and internalized stigma in adolescents.

This study examined whether findings from laboratory studies of baseball cognition also apply during real games. Using 2024 MLB data from 30 players, researchers analyzed batting performance under different levels of feedback and anxiety.

The authors investigated adoption rates of solar photovoltaic power at K-12 schools in California.

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 looked at unionization petitions from Starbucks workers between August 2021 and July 2024 to determine what factors influence votes for or against unionization.

The authors looked at beach nourishment (a way to combat erosion on coasts) and resulting grain size distribution. Their work is important to understand the dynamics of erosion and it's relation to wave action and the implications this has for efforts to mitigate coastal erosion.

Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.