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Many species of trees are distributed widely around the world, though not always in a way that makes immediate sense. The authors here use genetic information to help explain the geographic distribution of various conifer species throughout the world.

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

Autism spectrum disorder (ASD) is hard to correctly diagnose due to the very subjective nature of diagnosing it: behavior analysis. Due to this issue, we sought to find a machine learning-based method that diagnoses ASD without behavior analysis or helps reduce misdiagnosis.

Here, the authors investigated the most efficient way to position magnets to hold the most pieces of paper on the surface of a refrigerator. They used a regression model along with an artificial neural network to identify the most efficient positions of four magnets to be at the vertices of a rectangle.

The authors trained a machine learning model to detect kidney stones based on characteristics of urine. This method would allow for detection of kidney stones prior to the onset of noticeable symptoms by the patient.

One-third of the world's people do not have access to clean drinking water. Nadella and Nadella tackle this issue by testing a low-cost filtration system for removing heavy metal and bacteria from water.

This study hypothesized that sodium chloride was taken up through plant root structures to facilitate water transportation, and that sodium chloride accumulation was directly proportional to the soil salinity. Results showed that most cells within the “bulb” structures were isotonic at a concentration approximately twice as high as that of root tissue and ambient soil salinity, therefore supporting the presented hypothesis.

Here, the authors aimed to apply home soil testing to identify the cause of the growth differences between two lemon trees. They hypothesized that differences in physical and chemical soil characteristics were influencing differences in soil productivity and plant growth. Overall, the study demonstrated the effectiveness of home soil testing to characterize soils and help homeowners solve common gardening problems.

Human intelligence is correlated with variation in the protein neuroplastin-65, which is encoded by the NPTN gene. The authors examine the evolution of this gene across different animal species.

Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.