The density of stomata, or stomatal index, in plant leaves is correlated with the plant's rate of photosynthesis, and affected by the plant's climate. In this paper, authors measure the stomatal index of five plant species to derive their rates of photosynthesis. These results could help track changes in plants' photosynthetic rates with changing climate.

To address whether odor sensory circuits are organized topographically, the authors investigate whether the neuronal responses to similar odors amongst different mice mapped similarly in brain.

In this study, the authors determine optimal pH levels for maximizing isopropanol degradation in water. This has important applications for cleaning up polluted wastewater in the environment.

The authors look at malnutrition in children and how socio-economic factors impact this.

In this study, the authors explore contrast-enhanced magnetic resonance imaging at Earth's field.

Playing video games may improve mental performance by encouraging practicing logical reasoning skills. Students who played video games in between two tests tended to perform better on the second test than those that did not play video games.

In this article, Choi and Rossitto investigated the limitations of virtual learning by examining in-person dance learning compared to virtual dance learning while wearing EEG headsets. They found that in-person learners outperformed virtual learners and that virtual learners had higher mirror neuron activity as assessed by Mu rhythm power.

Oligodendrocytes are specialized brain cells that can change to cells that produce myelin and protect nerves. This study investigates the capacity for different extracellular matrix cues to induce this effect in culture.

The authors looked at how the addition of NaCl to crystalline nanocellulose capacitors could improve performance in transistor applications. They found that NaCl can improve performance, but that further work is needed to determine the optimal concentration used depending on the intended application.

The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.