Browse Articles

Friend or Foe: Investigating the Relationship between a Corn Crop and a Native Ragweed Population

Wainwright et al. | May 07, 2014

Friend or Foe: Investigating the Relationship between a Corn Crop and a Native Ragweed Population

Farmers will need to increase crop yields to feed the world's growing population efficiently. The authors here investigate the effects of growing corn in the presence or absence of ragweed, an invasive weed found in many fields and gardens. Surprisingly, the authors found that corn grown in the presence of weeds grew taller and were more productive than corn that had weeds removed. This may help gardeners rethink the necessity of weeding, and may point a way to improve farm yields in the future.

Read More...

Electrocatalytic oxidation of furfural on Co3O4/nickel foam catalyst: performance and mechanistic study

Song et al. | Jul 19, 2026

Electrocatalytic oxidation of furfural on Co<sub>3</sub>O<sub>4</sub>/nickel foam catalyst: performance and mechanistic study
Image credit: Shraga kopstein

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.

Read More...

Early detection of student burnout using data science: a study of behavioral and psychological indicators

Baber et al. | Jul 13, 2026

Early detection of student burnout using data science: a study of behavioral and psychological indicators

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.

Read More...