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The authors looked at the importance of different point breakdowns needed to win in a game of tennis.

The authors looked at variables associated with identity fraud in the US. They found that national unemployment rate and online banking usage are among significant variables that explain identity fraud.

Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.

The authors looked at how different factors related to practicing and playing chess would impact a player's rating.

In film, anxiety and depressive disorders are often depicted inaccurately. When viewers are exposed to these inaccurate portrayals, they collect misinformation about the disorders, as well as people who live with them, leading to stigma. This study used a mixed-method descriptive approach to analyze 16 teenagers’ attitudes towards people with anxiety and depression. Results found that while participants understood how these portrayals create stigma, they did not attribute this to misinformation. These results can be used to help both the film industry and the movie-going public better understand the effects of inaccurate storytelling and the extent to which it informs public perception

The study explores how music and sports impact cognitive development in young children, particularly in relation to learning disorders like ADHD and dyslexia.

In this article, Choi and Rossitto investigated the limitations of virtual learning by examining in-person dance learning compared to virtual dance learning while wearing EEG headsets. They found that in-person learners outperformed virtual learners and that virtual learners had higher mirror neuron activity as assessed by Mu rhythm power.

The authors looked at the ability subjects to rotation a 4D cube and how the ability to practice cube rotation impact their ability to understand 4D space.

Metal-organic frameworks (MOFs) are promising new nanomaterials for use in the fight against climate change that can efficiently capture and convert CO₂ to other useful carbon products. This research used computational models to determine the reaction conditions under which MOFs can more efficiently capture and convert CO₂. In a cost-efficient manner, this analysis tested the hypothesis that pressure and temperature affect the efficacy of carbon capture and conversion, and contribute to understanding the optimal conditions for MOF performance to improve the use of MOFs for controlling greenhouse CO₂ emissions.

In this study, the authors address the concerns of heavy metal contamination in industrial and feedlot water waste. They test whether added probiotics are capable of taking up heavy metals in water to attenuate pollution.