Mortality from opioid abuse has risen dramatically in the United States over the last two decades and has become a national health crisis. Bernstein and Chisesi explore whether revised pain management standards for hospitals contributed to this epidemic.

In this study, the authors sample water at different points closer and closer to two different airports to determine if these airports may be contributing to water pollution, specifically by measuring metals, nitrates, and pH.

Caffeine is widely consumed across the globe and is most appreciated for its effects as a stimulant. Here the authors investigate whether caffeine consumption affects performance during endurance or strength training. Their results suggest that caffeine consumption enhances endurance training, but not strength training.

Chemical preservatives are often used to reduce grain spoilage due to mold, but can have harmful heath and environmental effects. In this study, the authors tested three low toxic compounds for their effects on mold growth on corn kernels and found that all three were successful at slowing growth.

Recent declines in the brook trout population of the Lake Champlain Basin have made the genetic screening of this and other trout species of utmost importance. In this study, the authors collected and analyzed 21 DNA samples from Lake Champlain Basin trout populations and performed a phylogenetic analysis on these samples using the cytochrome b gene. The findings presented in this study may influence future habitat decisions in this region.

In this study the authors develop an app for faster chess game entry method to help chess learners improve their game. This culminated in the Augmented Reality Chess Analyzer (ARChessAnalyzer) which uses traditional image and vision techniques for chess board recognition and Convolutional Neural Networks (CNN) for chess piece recognition.

The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.

In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.

Evidence supports that spiders have many ecological benefits including insect control and predation in the food chain. In this study the authors investigate that whether the percent of vegetation coverage and spider density are correlated. They determine that despite the trend there is no statistically significant correlation.

In this study, the authors explored whether students' test scores were significantly higher on online exams during the COVID-19 school lockdown when compared to those of the in-person exams before the lockdown.