Human intelligence is correlated with variation in the protein neuroplastin-65, which is encoded by the NPTN gene. The authors examine the evolution of this gene across different animal species.
Read More...Evolution of Neuroplastin-65
Human intelligence is correlated with variation in the protein neuroplastin-65, which is encoded by the NPTN gene. The authors examine the evolution of this gene across different animal species.
Read More...Bacterial Richness of Soil Samples from Southern New Hampshire
Advancement in DNA sequencing technology has greatly increased our understanding about the role of bacteria in soil. The authors of this study examine the microbial content of soil samples taken from three locations in southern New Hampshire with varying pH and plant composition.
Read More...Allelopathic Effects of Kudzu (Pueraria montana) on Seed Germination and Their Potential Use As a Natural Herbicide
Plants in the wild compete with each other for nutrients and sunlight. Kudzu is a weed that is thought to secrete compounds that inhibit the growth of other plants. Here the authors find that certain parts of kudzu plants can block the germination of clover and dandelion seeds. These experiments may lead to a weed killer that is safe and naturally derived.
Read More...Assessing the accuracy and efficiency of simplified gridded ion thruster simulations
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.
Read More...Quantifying right atrial dilation relative to atrial septal defect size using an experimental model
To address the limitations in predicting the severity of Atrial Septal Defect (ASD), here the authors utilized a fluid-filled chamber model to quantify the relationship between defect size and right atrial fluid output. The findings confirmed that larger ASD diameters result in a linear increase in fluid output, validating a cost-effective model that can improve clinical prognosis and treatment planning for heart failure risks.
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...Testing filtration capabilities of household fabrics for protection against airborne contaminants
Toxic particulates in the atmosphere pose significant health risks, and while modern masks can help reduce inhalation of these pollutants, their availability may be limited during health crises. This study evaluated the effectiveness of household fabrics (cotton, fleece, wool, and rayon) as particulate filters, finding that cotton outperformed the others in filtration efficiency, while rayon was the least effective. The findings suggest that cotton is a preferable alternative for filtration purposes, while rayon should be avoided.
Read More...Tree-Based Learning Algorithms to Classify ECG with Arrhythmias
Arrhythmias vary in type and treatment, and ECGs are used to detect them, though human interpretation can be inconsistent. The researchers tested four tree-based algorithms (gradient boosting, random forest, decision tree, and extra trees) on ECG data from over 10,000 patients.
Read More...School sustainability: The implications of implementing living walls at schools for air purification
The authors compare air quality in the presence and absence of a living wall in a high school hallway in Brooklyn, NY.
Read More...Assessing large language models for math tutoring effectiveness
Authors examine the effectiveness of Large Language Models (LLMs) like BERT, MathBERT, and OpenAI GPT-3.5 in assisting middle school students with math word problems, particularly following the decline in math performance post-COVID-19.
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