People react to music by moving and dancing. This study examined if different types of music were correlated with higher heart rates and if this was at all affected by music preferences.
Read More...Does Music Directly Affect a Person’s Heart Rate?
People react to music by moving and dancing. This study examined if different types of music were correlated with higher heart rates and if this was at all affected by music preferences.
Read More...Breaking the Ice: A Scientific Take on the Ice Melting Abilities of Household Salts
The use of salt to melt ice is a common and important practice to keep roadways safe during winter months. However, various subtypes of salt differ in their chemical and physical properties, as well as their environmental impact. In this study, the authors measure the effectiveness of different salts at disrupting ice structures and identify calcium chloride as the most effective.
Read More...The Impact of Age on Post-Concussive Symptoms: A Comparative Study of Symptoms Related and Not Related to the Default Mode Network
The Default Mode Network (DMN) is a network of connected brain regions that are active when the brain is not focused on external tasks. Minor brain injuries, such as concussions, can affect this network and manifest symptoms. In this study, the authors examined correlations between DMN age and post-concussion symptoms in previously concussed individuals and healthy controls.
Read More...Evaluating the predicted eruption times of geysers in Yellowstone National Park
The authors compare the predicted versus actual geyser eruption times for the Old Faithful and Beehive Geysers at Yellowstone National Park.
Read More...Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and is difficult to diagnose in young children. Here magnetoencephalography was used to compare the brain activity in patients with ASD to patients in a control group. The results show that patients with ASD have a high level of activity in different areas of the brain than those in the control group.
Read More...An explainable model for content moderation
The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.
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...Statistical models for identifying missing and unclear signs of the Indus script
This study utilizes machine learning models to predict missing and unclear signs from the Indus script, a writing system from an ancient civilization in the Indian subcontinent.
Read More...Identification of a core set of model agnostic mRNA associated with nonalcoholic steatohepatitis (NASH)
In this study, the authors analyze gene expression datasets to determine if there is a core set of genes dysregulated during nonalcoholic steatohepatitis.
Read More...Examining the Growth of Methanotrophic Bacteria Immersed in Extremely Low-Frequency Electromagnetic Fields
Scientist are investigating the use of methane-consuming bacteria to aid the growing problem of rising greenhouse gas emissions. While previous studies claim that low-frequency electromagnetic fields can accelerate the growth rate of these bacteria, Chu et al. demonstrate that this fundamental ideology is not on the same wavelength with their data.
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