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The authors looked at the ability of eggshells to slow ice melting. They found that eggshells were able to increase ice melting time when crushed showing that they were an effective thermal barrier.

The authors test various machine learning models to improve the accuracy and efficiency of pneumonia diagnosis from X-ray images.

The authors looked at two peptides, gluteomorphin and casomorphin, that are present after the digestion of bread and cheese. As these peptides can bind opioid receptors the authors want to know if they could be addictive in the same way as conventional opioids (i.e., morphine) are known to be. Their results in a planaria model suggest that both of these peptides are addictive.

The authors use the unique movements of the jumping gall wasp to study momentum transfer with potential applications in robotics and extraterrestrial research.

The authors test the effectiveness of machine learning to predict onset of cardiovascular disease.

The authors looked at the antibacterial effects of oregano and star anise essential oils against E. coli or S. epidermis. They found that oregano oil showed antibacterial activity against both E. coli or S. epidermis, and that star anise oil had a larger zone of inhibition in E. coli than tetracycline, a conventional antibiotic.

The authors looked at renewable energy generators and the ability to utilize green roofs as a solution to climate change.

The goal of this study was to determine the if carbohydrates or complex carbohydrates are better for athlete's performance in anaerobic and aerobic exercise. Ultimately, we found that, when one’s schedule only allows for 30 minutes to eat before a workout, the best pre-workout meal for optimal glycogen levels to prompt muscle hypertrophy, strength increases, and better endurance is one that is simple carbohydrate-heavy.

In this study, the authors present proposed cryptographic controls for election sites with the hypothesis that this will mitigate risk and remediate vulnerabilities.

In the battle against Alzheimer's disease, early detection is critical to mitigating symptoms in patients. Here, the authors use a collection of MRI scans, layering with deep learning computer modeling, to investigate early stages of AD which can be hard to catch by human eye. Their model is successful, able to outperform previous models, and detected regions of interest in the brain for further consideration.