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This study examined how social determinants of health (SDH) relate to vision loss by analyzing publicly available data from 18 northern and southern U.S. states and using Bayesian correlation analysis.

The authors looked at what conditions with host stars favor development of exoplanets.

Impact of carbon tax and dividend on financial security

The authors use machine learning to analyze electroencephalogram data and identify slowing patterns that can indicate undetected disorders like epilepsy or dementia

Asthma is one of the most prevalent chronic conditions in the United States. But not all people experience asthma equally, with factors like healthcare access and environmental pollution impacting whether children are likely to be hospitalized for asthma's effects. Li, Li, and Ruffolo investigate what demographic and environmental factors are predictive of childhood asthma hospitalization rates across Pennsylvania.

The authors looked at survival of honey bees over the winter in regards to native and invasive plant availability. They found that native plants provided greater survivability and overall health compared to environments where there was an abundance of invasive plants.

The authors looked at differences in water quality between Chinatown and Bayside. They wanted to look at the racial and economic demographics of each region and how that correlated to access to clean drinking water. Ultimately they did not find any significant differences in water quality, but identified important future directions for this work.

The authors compare nutritional content of foods found in Western versus Asian grocery stores to determine whether one cultural diet is healthier than the other.

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 authors look at using publicly available data and machine learning to see if they can develop a criminal activity index for counties within the state of California.