The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.

Water scarcity affects upwards of a billion people worldwide today. This project leverages the potential of capturing humidity to build a high-efficiency water condensation device that can generate water and be used for personal and commercial purposes. This compact environment-friendly device would have low power requirements, which would potentially allow it to utilize renewable energy sources and collect water at the most needed location.

Life requires many things, including a hospitable temperature, elements, and energy. Here the authors utilize Newton's laws of physics and information relating a star's luminosity and temperature to determine the minimum and maximum masses and luminosities of planets and stars that would support life as we know it. This work can be used to determine the likelihood of a planet being able to support life based on attributes we can measure from here on Earth.

The authors look at how different food types impact the ability of bacteria to produce electricity.

The authors develop and test a machine learning algorithm for predicting diabetes diagnoses.

The authors test the usefulness of zinc oxide microparticles relative to zinc oxide nanoparticles as antibacterial agents.

Algal blooms pose a threat to ecosystems, but the methods used to combat these blooms might harm more than just the algae. Halepete, Graham, and Lowe-Schmahl demonstrate negative effects of anti-algae treatments on a cyanobacterium (Spirulina major), and the water fleas (Daphnia magna) that live alongside these cyanobacteria.

The facial integument, or external skin tissues, were assessed on set of dinosaurs from the Allosauroidea clade to test whether dermal patterns served specific functions.

The diagnosis of malaria remains one of the major hurdles to eradicating the disease, especially among poorer populations. Here, the authors use machine learning to improve the accuracy of deep learning algorithms that automate the diagnosis of malaria using images of blood smears from patients, which could make diagnosis easier and faster for many.

The authors looked at using genetic algorithms to look at the Indian labor market and what features might best explain any variation seen. They found that features such as economic growth and household consumption, among others, best explained variation.