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The authors looked at two peptides, gluteomorphin and casomorphin, that are present after the digestion of bread and cheese. As these peptides can bind opioid receptors the authors want to know if they could be addictive in the same way as conventional opioids (i.e., morphine) are known to be. Their results in a planaria model suggest that both of these peptides are addictive.

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 use of gamification in cybersecurity education, particularly through capture-the-flag competitions, involves scoring challenges based on their difficulty and the number of teams that solve them. The study investigated how changing the scoring formulas affects competition outcomes, predicting that different formulas would alter score distributions.

In this article the authors look at phantom loads of common kitchen appliances and found that the appliances looked at have a phantom load of 10.9%. Understanding phantom loads is important as it can reduce energy grid usage and energy bill costs for homeowners.

The authors explore how diversity in data sets contributes to bias in artificial intelligence.

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.

Here, the authors investigated the effects of an interventional psychology on the study habits of high school students specifically related to the use of electronic distractions such as social media or texting, listening to music, or watching TV. They reported varying degrees of success between the control and intervention groups, suggesting that the methods of habit-breaking for students merits further study.

Here, the authors sought to develop a new metric to evaluate the efficacy of baseball pitchers using machine learning models. They found that the frequency of balls, was the most predictive feature for their walks/hits allowed per inning (WHIP) metric. While their machine learning models did not identify a defining trait, such as high velocity, spin rate, or types of pitches, they found that consistently pitching within the strike zone resulted in significantly lower WHIPs.

The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.

With increased screen time and exposure to blue light, an increasing number of people have sleep deprivation. Blue light suppresses the release of melatonin and hinders sleep at night. We hypothesized that people could get a greater amount of sleep by controlling the blue light exposure from screen time before bedtime. BBG’s effect on reducing time to fall asleep was significant within the teenage group, but not significant in the adult group. This indicated that BBG could improve the time taken to sleep for young teenagers post screen time in the evening.