Browse Articles

Here the authors present an autonomous drone air filtration system that uses a novel algorithm, the gradient ascent ML particle filter (GA/MLPF), to efficiently locate and mitigate outdoor air pollution. They demonstrate that their GA/MLPF algorithm is significantly more efficient than the conventional gradient ascent algorithm, reducing both the time and number of waypoints needed to find the source of pollution.

Investigation of the largest rigid shape that can be moved through a circular hallway of unit width with an arbitrary turn angle

The authors looked at the correlation between being able to speak more than one language (multilingualism) and visual imagery. They found multilingual individuals had higher visual imagery as measured by the VVIQ.

In this study the authors looked at the ability of the Discrete Fourier Transform (DFT) to analyze different musical elements. They found that DFT is a powerful method to analyze recorded music.

This study explores how to predict and minimize distortion in 3D printed parts, particularly when using affordable PLA filament. The researchers developed a model using a gradient boosting regressor trained on 3D printing data, aiming to predict the necessary CAD dimensions to counteract print distortion.

The authors investigate the relationship between self-esteem, social desirability, and emotion regulation in children and adolescents.

This article describes the classification of medical text data using vector databases and text embedding. Various large language models were used to generate this medical data for the classification task.

Kalirin is a guanine nucleotide exchange factor (GEF) for the GTPase RAC1, linked to schizophrenia and Alzheimer’s Disease. It plays a crucial role in synaptic plasticity by regulating dendritic spine formation and actin cytoskeleton remodeling, which are essential for creating new synapses. Authors developed two novel compounds targeting kalirin, confirming that predictive modeling can indicate biological activity.

The authors looked at whether CBD and THC would decrease reproductive rates in a Drosophila melanogaster model. They found that CBD had a greater impact on reducing hatching rates than THC, and that THC resulted in unexpected mortalities.

As AI becomes more integrated into healthcare, public trust in AI-developed treatment plans remains a concern, especially for emotionally charged health decisions. In a study of 81 community college students, AI-created treatment plans received lower trust ratings compared to physician-developed plans, supporting the hypothesis. The study found no significant differences in AI trust levels across demographic factors, suggesting overall skepticism toward AI-driven healthcare.