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The authors test the effect of petroleum-based and bio-based microplastics on the growth of two microalgae species.

The authors used a particle-in-cell simulation to determine the effects on extensive and intensive metrics. They found that preliminary simulations could be run quickly with much lower particle counts before more technically demanding and comprehensive simulations are performed.

The authors studied the impact of AI face-tracking technology on the immersiveness of videogames as an alternative to virtual reality gaming.

The authors looked at energy efficient ways to generate small nitrogenous compounds.

The study developed Loving Words, a free AI-powered poetry tutor designed to help writers improve their poetry and experience its therapeutic benefits. Two groups of participants wrote poems—one without assistance and one using Loving Words.

The authors looked at how soil temperature changes with fire to develop a sensor system that could aid in earlier detection of fires.

The authors looked at how storage temperature of potatoes can impact the sweetness of potatoes (due to the break down of the starch into simple sugars).

Due to a critical shortage of donor hearts, researchers are exploring cardiac xenotransplantation—transplanting animal hearts into humans—as a potential solution. This study synthesized nearly two decades of preclinical research to evaluate multiple factors affecting xenograft survival.

This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.

The global issue of water quality has led to the use of machine learning models, like ANN and SVM, to predict water potability. However, these models can be complex and resource-intensive. This research aimed to find a simpler, more efficient model for water quality prediction.