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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.

In this study, the authors test whether excess copper exposure has neurobehavioral effects on Hirudo verbana leeches.

Here, seeking a better solution to produce downforce that keeps a vehicle grounded at high speeds than wings which tend to result in degraded car performance due to increased air resistance, the authors considered using the Magnus effect as a replacement. The authors found that a spinning cylinder generated significantly more downforce through the Magnus effect than a standard wing at all wind speeds as simulated through the use of a leaf blower. They suggest that a cylinder could be a potential replacement for a wing when downforce is a priority.

A trial study was performed in 2021 to investigate the link between technology and transactive memory. Transactive memory is shared knowledge in which members share the responsibility to encode, store, and retrieve certain tasks or assignments, leading to a successful and collective performance. We hypothesize that a participants’ expected access to an external source affects the recall rate and retrieval of information.

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 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.

In this study, the authors use existing mathematical models to how high school athletes pace 800 m, 1600 m, and 3200 m distance track events compared to elite athletes.

Here, the authors used surface electromyography to measure the effects of caffeine intake on the resting activity of muscles. They found a significant increase in the measured amplitude suggesting that caffeine intake increased the number of activated muscle fibers during rest. While previous research has focused on caffeine's effect on the contraction signals of muscles, this research suggests that its effects extend to even when a muscle is at rest.

Robot-assisted minimally invasive surgery (RMIS) benefits from increased precision and faster recovery, with force feedback from the surgical tool being critical for control. Researchers tested the use of neural networks for detecting the vanishing point of the tool, a key element for force feedback.

In this paper, Thomas et al. introduce a new, affordable way to study characteristics of rocket motors using small-scale rocket motors.