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The authors monitored water quality over time looking for influences from construction and deforestation.

In this study, the authors hypothesized that the unique redox properties of cobalt oxide (Co₃O₄), combined with the conductive nature of the nickel foam (NF) substrate, synergistically enhances the catalytic performance for furfural oxidation. The study showed successful synthesis of Co₃O₄ nanoflowers directly grown on NF and tested their capacity to serve as a highly efficient electrocatalyst for furfural oxidation. Beyond furfural oxidation, this study also offers broader implications for sustainable chemistry by establishing design principles for efficient nucleophilic oxidation reaction catalysts, demonstrating an energy-saving alternative to conventional oxygen evolution reaction-coupled processes, and showcasing how biomass conversion can be integrated with renewable energy systems.

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.

This study used surveys, interviews, and XGBoost analysis to examine how experienced and novice entrepreneurs differ in their thinking and decision-making.

The authors looked at how different blends of synthetic and non-synthetic fabrics protected against UV radiation.

The authors survey high school students regarding preferences for taking notes by hand versus typing.

The authors looked at the importance of different point breakdowns needed to win in a game of tennis.

The authors employ computational protein design to identify a mini-protein with the potential to enhance binding of the tight junction protein, claudin-5, at the blood-blood barrier with therapeutic potential for neurodegenerative diseases.

The authors looked at what conditions with host stars favor development of exoplanets.

The authors compare current machine learning algorithms with a new Explainable AI algorithm that produces a human-comprehensible decision tree alongside predictions.