The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.
Read More...A 1D model of ultrasound waves for diagnosing of hepatomegaly and cirrhosis
The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.
Read More...Associations between fentanyl usage and social media use among U.S. teens
Here the authors aimed to understand factors influencing adolescent fentanyl exposure, hypothesizing a positive association between social media usage, socioeconomic factors, and fentanyl abuse among U.S. teens. Their analysis of the Monitoring the Future dataset revealed that a history of suspension and use of marijuana or alcohol were linked to higher fentanyl use, and while not statistically significant, a notable positive correlation between social media use and fentanyl frequency was observed.
Read More...Reinforcement learning in 2-D space with varying gravitational fields
In this study the authors looked at the ability to navigate planes in space between randomly placed planets. They used machine and reinforcement learning to run simulations and found that they were able to identify optimal paths for travel. In the future these techniques may allow for safer travel in unknown spaces.
Read More...Exploring the Factors that Drive Coffee Ratings
This study explores the factors that influence coffee quality ratings using data from the Coffee Quality Institute. Through a regression model based on gradient descent, the authors aimed to predict coffee ratings (total cup points) and hypothesized that sweetness and the coffee producer would be the most influential factors.
Read More...Investigating auxin import and export proteins in Chlorella vulgaris
This study explores auxin signaling in Chlorella vulgaris, a green alga with potential for sustainable biofuel and food production. Evidence from protoplast swelling experiments suggests that C. vulgaris secretes auxin and possesses auxin import proteins, highlighting previously uncharacterized signaling pathways. These findings could support more efficient cultivation and resource extraction strategies.
Read More...Temporal characterization of electroencephalogram slowing activity types
The authors use machine learning to analyze electroencephalogram data and identify slowing patterns that can indicate undetected disorders like epilepsy or dementia
Read More...Effects of urban traffic noise on the early growth and transcription of Arabidopsis thaliana
This article explores the largely unstudied impact of noise pollution on plant life. By exposing Arabidopsis thaliana seedlings to urban traffic noise, the study found a significant increase in seedling growth, alongside substantial changes in gene expression. This research reveals critical insights into how noise pollution affects plant physiology and contributes to a broader understanding of its ecological impacts, helping to guide future efforts in ecosystem conservation.
Read More...Ocean, atmosphere, and cloud quantity on the surface conditions of tidally-locked habitable zone planets
The authors assessed the atmospheric and oceanic parameters necessary for tidally-locked exoplanets to be habitable.
Read More...Evaluating the clinical applicability of neural networks for meningioma tumor segmentation on 3D MRI
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Read More...Mismatch repair is not correlated with genomic alterations in glioblastoma patients
The authors looked at biomarkers in glioblastoma patients they hypothesized to be correlated with survival rate. Ultimately they did not find hMSH2 or hMSH6, genes involved in mismatch repair, to be significantly associated with outcomes related to increased survival.
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