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In this article the authors looked at arginine synthesis across different bacteria commonly found in different regional diets. They found that B. megaterium and C. sporogenes both caused a higher pH to occur on their agar plates compared to other bacteria tested indicating a greater amount of arginine synthesis.

The authors looked at which measurements from the NFL combine were the most predictive of success for defensemen in the NFL.

Using machine learning to predict the risk of algae bloom

Algorithmic trading has been increasingly used by Americans. In this work, we tested whether including the opening, closing, and highest prices in three supervised learning models affected their performance. Indeed, we found that including all three prices decreased the error of the prediction significantly.

The authors use the unique movements of the jumping gall wasp to study momentum transfer with potential applications in robotics and extraterrestrial research.

Artificial sweeteners are rising in popularity, in part due to the influence of social media platforms like YouTube. However, YouTube commenters often repeat information about artificial sweeteners that is not supported by scientific research. To investigate how misinformation about sweeteners spreads through social media, Kim and Yoo conduct a content analysis of YouTube comments to reveal how many comments repeat misinformation about artificial sweeteners' effects.

The authors develop a new method for training machine learning algorithms to differentiate between hate speech and cultural speech in online platforms.

The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.

The Young's Modulus of a structural material is a measure of its elasticity and is defined as the ratio of the tensile stress to tensile strain. This study aims to investigate the Young's Modulus of pasta with different diameters.

In this study, with consideration for the increasing participation of high school students in indoor rowing, the authors analyzed World Indoor Rowing Championship data. Statistical analysis revealed two key features that can determine the performance of a rower as well as increasing competitiveness in nearly all categories considered. They conclude by offering a 2000-meter ergometer time distribution that can help junior rowers assess their current performance relative to the world competition.