Did the COVID-19 pandemic and travel restrictions improve air quality? The authors investigate this question in New York City using existing pollution data and forecasting trends.

The authors tested environmentally-friendly alternatives to wastewater treatment chemicals, including activated charcoal for filtration and citrus peels for preventing bacterial growth.

In this study, the authors survey middle and high school students in different states in the U.S. to evaluate stress levels, learning experiences, and activity levels during the COVID-19 pandemic.

In this study, the authors report their successful efforts to increase voltage production in a Microbial Fuel Cell (MFC), which is a system in which microorganisms produce electricity while performing their normal metabolism.

Household detergents have surfactants that can potentially harm the soil and broader ecosystems. In this study, the authors investigate whether eco-friendly and less-eco-friendly detergents affect soil pH, phosphorus, nitrogen, and potassium levels.

In order to determine whether unmarked soybeans in the market were genetically modified crops, the authors developed a polymerase chain reaction (PCR) screen for DNA lectin.

Modern artificial neural networks have been remarkably successful in various applications, from speech recognition to computer vision. However, it remains less clear whether they can implement abstract concepts, which are essential to generalization and understanding. To address this problem, the authors investigated the above vs. below task, a simple concept-based task that honeybees can solve, using a conventional neural network. They found that networks achieved 100% test accuracy when a visual target was presented below a black bar, however only 50% test accuracy when a visual target was presented below a reference shape.

In this article, the authors investigate whether stock selection across various sectors is efficient enough to outperform an overall market. Stocks from 2006 to 2020 were selected across sectors to calculate beta values using the Capital Asset Pricing Model.

Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.

The authors investigate various methods to decrease heart rate after drinking caffeine.