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The use of salt to melt ice is a common and important practice to keep roadways safe during winter months. However, various subtypes of salt differ in their chemical and physical properties, as well as their environmental impact. In this study, the authors measure the effectiveness of different salts at disrupting ice structures and identify calcium chloride as the most effective.

Due to the increase in antimicrobial resistance, alternative medicinal therapies are being explored. Studies have shown that honey and ginger alone have antimicrobial effects on the genera Staphylococcus and Escherichia, including S. epidermidis and E. coli. The authors of this study tested whether a honey-ginger supplement, Jengimiel™, could be used as an antimicrobial agent against S. epidermidis and E. coli K-12.

Chemicals used in fertilizers and pesticides often end up in nearby bodies of water due to runoff and may have negative impacts on these important ecosystems. In this study, the authors use water containing different nitrogen levels to investigate the effect on the growth of the English daisy.

Microorganisms such as bacteria and fungi live everywhere in the world around us. The authors here demonstrate that these predominantly harmless microbes can be isolated from many household locations that appear "clean." Further, they test the cleaning power of 70% ethanol and suggest that many "clean" surfaces are not in fact "sterile."

Machine learning systems are often expected to make fair decisions, yet the most widely used fairness criteria—independence, separation, and sufficiency—cannot generally be satisfied at the same time. In this study, students tested these criteria using a logistic regression model on a real-world student performance dataset and found that each criterion was met only at different prediction thresholds, with no threshold satisfying all three simultaneously. These results illustrate the inherent trade-offs in algorithmic fairness and highlight why achieving perfectly fair machine learning models is often impossible in practice.

The authors studied hippocampal gene expression in Alzheimer's disease.

This study examined behavioral and psychological predictors of burnout among high school and university students in Pakistan using survey data and machine-learning models. Shorter sleep and greater mental fatigue—especially fatigue—were associated with higher burnout risk, while a Random Forest model successfully identified students at risk of burnout.

Tax incentives for sustainable technology are a key part of the push for a greener future. However, these incentives may not reach all income strata equally. Using a machine learning approach, this study analyzed the distributional effects of residential energy tax credits across different income levels in the United States.

Pathogenic bacteria cause major economic losses in agriculture, and widespread antibiotic use has led to increasing resistance. This study tested whether a low-cost DIY method could produce antibacterial colloidal silver effective against both Gram-negative and Gram-positive plant pathogens.

Understanding and predicting cognitive decline in Alzheimer's disease