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In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.

Gun violence has been a serious issue in the South Side of Chicago for a long time. To intervene, regulators have passed legislation they hoped to curb -if not completely eradicate- the issue. However, there is little analysis done on how effective the various laws have been at reducing gun violence. Here the authors explore the association between firearm purchase laws passed between 1993-2018 and the incidence of gun homicide in Chicago's South Side. Their analysis suggests that some laws have been more effective than others, while some might have exacerbated the issue. However, they do not consider other contributing factors, which makes it difficult to prove causation without further investigation.

Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.

Here, seeking to identify the risk of coronary artery disease (CAD), a major cause of cardiovascular disease, the authors used Mendelian randomization. With this method they identified several traits such as blood pressure readings, LDL cholesterol and BMI as significant risk factors. While other traits were not found to be significant risk factors.

Here, based on the identification of androgapholide as a potential therapeutic treatment against cancer, Alzheimer's disease, diabetes, and multiple sclerosis, due to its ability to inhibit a signaling pathway in immune system function, the authors sought ways to optimize the natural product human systems by manipulating its chemical structure. Through the semisynthesis of a natural product along with computational studies, the authors developed an understanding of the kinetic mechanisms of andrographolide and semisynthetic analogs in the context of Michael additions.

In this study, the authors share their work on improving the frame rate of videos to reduce data sent to users with both 2D and 3D footage. This work helps improve the experience for both types of footage!

Expanded polystyrene (EPS) is a plastic used to make food containers and packing materials that poses a threat to the environment. Mealworms can degrade EPS, but at a slow rate. Here, researchers assessed the impact of food waste compost and oats on the speed of EPS consumption by mealworms, superworms, and waxworms. A positive correlation was found between food waste compost supplementation and EPS consumption, especially by mealworms, indicating a potential industrial application.

The "Uncanny Valley" is a phenomenon in which humans feel discomfort in the presence of objects that are almost, but not quite, human-like. In this study, the authors tested whether this phenomenon could be overcome by sharing a stressful experience with a humanoid robot. They found that human subjects more readily accepted a robot partner that they had previously shared a stressful experience with, suggesting a potential method for increasing the effectiveness of beneficial human-robot interactions by reducing the Uncanny Valley effect.

Here the authors used morphological characters and DNA barcoding to identify arthropods found within a residential house. With this method they identified their species and compared them against pests lists provided by the US government. They found that none of their identified species were considered to be pests providing evidence against the misconception that arthropods found at home are harmful to humans. They suggest that these methods could be used at larger scales to better understand and aid in mapping ecosystems.

Saccharomyces cerevisiae yeast is used to produce bioethanol, an alternative to fossil fuels. In this study, authors take advantage of this well studied yeast by genetically engineering them to increase fatty acid biosynthesis and culturing in a cost-effective wastewater based medium; potentially providing a sustainable alternative to petrochemicals.