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Here, seeking to identify the possible role of sports in helping teenagers navigate the troubles associated with societal changes during a pandemic, the authors surveyed 50 adolescents to collect Beck Depression Inventory scores. They found that 9 out of students with severe depressions did not do sports, while no significant relationship between depressive symptoms and either gender or place of exercise was observed.

Several studies have applied different machine learning (ML) techniques to the area of forecasting solar photovoltaic power production. Most of these studies use weather data as inputs to predict power production; however, there are numerous practical issues with the procurement of this data. This study proposes models that do not use weather data as inputs, but rather use past power production data as a more practical substitute to weather-based models. Our proposed models demonstrate a better, cheaper, and more reliable alternatives to current weather models.

Here, the authors investigated the role of nonpharmacological interventions in preventing or delaying cognitive impairment in individuals with and without dementia. By using a retrospective case-control study of 22 participants across two senior centers in San Diego, they found no significant differences in self-reported activities. However, they found that their results reflected activity rather than the activity itself, suggesting the need for an alternative type of study.

In this study, the authors determined whether tautomerization dynamics in protic and aprotic solvents displayed differences in reaction rates and in the proportion of the keto and enol tautomers present.

COVID-19 has impacted the way many people go about their daily lives, but what are the main factors driving the changes in the housing market, particular house prices?

In this study, the authors investigate whether Eisenia Fetida nerve signal speed correlates with Withania somnifera ingestion, a possible way to protect against demyelination.

In this article, the authors propose an effective, environmentally-friendly method of producing conductive ink using expired waste oil, polystyrene, and graphene.

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.

As the world moves towards more eco-friendly methods for chemical synthesis, there's a strong interest in employing enzymes in chemical synthetic processes. Here, the authors explore how the activity of enzymes such as trypsin, lipase and nattokinase is affected by the electronic effects of the substrate they are acting on.

Access to green space—an area of grass, trees, or other vegetation set apart for recreational or aesthetic purposes in an urban environment—and clean drinking water can be unequally distributed in urban spaces, which are often associated with income inequality. Little is known about public drinking water and green space inequities in the Bay Area. For our study, we sought to understand how public park access, drinking fountain access, and the quality of public drinking water differ across income brackets in the Bay Area. Though we observed smaller-scale instances of inequalities, in the park distribution in the Bay Area as a whole, and in the Southern Bay’s water quality and park distribution, our results indicate that other factors could be influencing water quality, and park and fountain access in the Bay Area.