The authors test the effect of petroleum-based and bio-based microplastics on the growth of two microalgae species.
Read More...Differential physiological response of microalgae exposed to petroleum- and bio-based microplastics
The authors test the effect of petroleum-based and bio-based microplastics on the growth of two microalgae species.
Read More...The growth of bacteria on everyday objects and the antimicrobial effects of household spices
The study investigates the antibacterial properties of household spices on bacteria isolated from everyday objects, aiming to address the limited understanding of bacterial resilience on surfaces and the potential of spices as antibacterial agents. Researchers hypothesized that bacteria would grow faster on some surfaces than others and that spices like honey, chili powder, turmeric, and sumac would inhibit bacterial growth at varying rates. The findings suggest that household spices possess significant antibacterial properties and could be used as emergency disinfectants, particularly in under-resourced settings. However, they cannot replace medical treatments but offer insights into alternative health solutions using common ingredients.
Read More...Optimizing AI-generated image detection using a Convolutional Neural Network model with Fast Fourier Transform
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.
Read More...Predicting voting and union support in certification elections: Evidence from Starbucks workers, 2021-2024
The authors looked at unionization petitions from Starbucks workers between August 2021 and July 2024 to determine what factors influence votes for or against unionization.
Read More...Using advanced machine learning and voice analysis features for Parkinson’s disease progression prediction
The authors looked at the ability to use audio clips to analyze the progression of Parkinson's disease.
Read More...Investigating sustainable insulation materials: Analysis of biofoams and petroleum-derived foams
The authors looked into eco-friendly alternatives for insulating material. They ultimately found that a polyurethane derived from eggshells was an effective insulator and further research into it is warranted.
Read More...Advancing pediatric cancer predictions through generative artificial intelligence and machine learning
Pediatric cancers pose unique challenges due to their rarity and distinct biological factors, emphasizing the need for accurate survival prediction to guide treatment. This study integrated generative AI and machine learning, including synthetic data, to analyze 9,184 pediatric cancer patients, identifying age at diagnosis, cancer types, and anatomical sites as significant survival predictors. The findings highlight the potential of AI-driven approaches to improve survival prediction and inform personalized treatment strategies, with broader implications for innovative healthcare applications.
Read More...Upward social comparison on standardized test performance in adolescents and adults
The authors test the effect of test score comparison on the self-efficacy of adolescents versus adults.
Read More...Investigating Lemna minor and microorganisms for the phytoremediation of nanosilver and microplastics
The authors looked at phytoremediation, the process by which plants are used to remove pollutants from our environment, and the ability of Lemna minor to perform phytoremediation in various simulated polluted environments. The authors found that L. minor could remove pollutants from the environment and that the addition of bacteria increased this removal.
Read More...The effects of social media on STEM identity in adolescent girls
Social media is widely used and easily accessible for adolescents, it has the potential to increase STEM (Science, Technology, Engineering, and Math) identity in girls. We aimed to investigate the effects of exposure to counter-stereotypical portrayals of women in STEM on social media on the STEM identity of adolescent girls. The study concluded that social media alone may not be an effective tool to increase STEM identity in girls. Social media can still be used as a complementary tool to support and encourage women in STEM, but it should not be relied upon solely to address the gender disparity in STEM fields.
Read More...