Browse Articles

This study evaluates the potential of natural language processing (NLP) models in an emotion-driven bibliotherapy framework to improve mental health challenges.

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

The authors access a panel of leaf traits across ten deciduous tree species to explore adaptive strategies between large and small trees.

The authors test the antioxidant content of Taiwanese high mountain teas grown in or processed under differing conditions.

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

The authors studied the impact of drying blood as a storage solution for space travel.

This study analyzes genetic alterations and expression patterns of protein kinases involved in phagocytosis across multiple cancers using TCGA data.

This paper looks at the antibacterial and toxic effects of silver nanoparticles (AgNPs) on Escherichia coli bacteria and Drosophila melanogaster fruit flies. They modified the AgNPs size, concentration, and surface coating to determine the effects on each of the organisms. For both organisms, increased AgNP concentration demonstrated increased toxicity but particle size and surface coating had opposing effects.

Recent advances in generative AI have made it increasingly hard to distinguish real images from AI-generated ones. Traditional detection models using CNNs or U-net architectures lack precision because they overlook key spatial and frequency domain details. This study introduced a hybrid model combining Convolutional Neural Networks (CNN) with Fast Fourier Transform (FFT) to better capture subtle edge and texture patterns.

The authors looked at how the length of an audio clip used of a song impacted the ability to properly classify it by musical genre.