The authors examine a relationship between tweet sentiment and stock market behavior during the early weeks of the COVID-19 pandemic.
Read More...Understanding investors behaviors during the COVID-19 outbreak using Twitter sentiment analysis
The authors examine a relationship between tweet sentiment and stock market behavior during the early weeks of the COVID-19 pandemic.
Read More...Building deep neural networks to detect candy from photos and estimate nutrient portfolio
The authors use pictures of candy wrappers and neural networks to improve nutritional accuracy of diet-tracking apps.
Read More...Analysis of complement system gene expression and outcome across the subtypes of glioma
Here the authors sought to better understand glioma, cancer that occurs in the glial cells of the brain with gene expression profile analysis. They considered the expression of complement system genes across the transcriptional and IDH-mutational subtypes of low-grade glioma and glioblastoma. Based on their results of their differential gene expression analysis, they found that outcomes vary across different glioma subtypes, with evidence suggesting that categorization of the transcriptional subtypes could help inform treatment by providing an expectation for treatment responses.
Read More...Effects of copper sulfate exposure on the nervous system of the Hirudo verbana leech
In this study, the authors test whether excess copper exposure has neurobehavioral effects on Hirudo verbana leeches.
Read More...Innovative Treatment for Reducing Senescence and Revitalizing Aging Cells through Gene Silencing
Cellular senescence plays a key role in aging cells and is attributed to a number of disease and pathology. These authors find that genetic editing of both RPS6KB1 and PPARGC1A revitalizes a human skin fibroblast cell line.
Read More...Demographic indicators of voter shift between 2016 and 2020 presidential elections
In this study, the authors investigate the demographic indicators for voter shift between the 2016 and 2020 presidential elections based on demographic data put through a K-nearest neighbors classification algorithm and Principal Component Analysis.
Read More...Attitudes towards mental health in Indians who practice yoga regularly and those who do not
Whether it is through implicit association or intentional practice, yoga has been known to help individuals maintain good mental health. However, many communities, such as South Asian communities, often project the stereotype that embodies neglecting topics such as mental health and considering them taboo. In this online survey-based study, the authors focused on examining whether yoga would alter individuals’ attitudes toward mental health. They hypothesized that 1) participants who regularly practiced yoga would be more familiar with the term mental health, 2) participants who practiced yoga would value their mental health more, and 3) participants who practiced yoga regularly would be more open about their mental health and be more likely to reach out for professional help if needed. They did not find a statistical significance for any of our hypotheses which suggests that yoga may not have an effect on perceptions of mental health in yoga-practicing Indian adults.
Read More...Effects of Coolant Temperature on the Characteristics of Soil Cooling Curve
In this article, the authors investigate whether coolant temperature affects soil cooling curves of soil with otherwise identical properties. The coolant temperature is representative of environmental temperature, and the authors hypothesized that differences in this temperature would not affect the freezing temperature of soil. Their findings validated their hypothesis providing helpful information relevant to understanding how frost heaves happen and how to predict their occurrence more accurately.
Read More...Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires
This study hypothesized that a machine learning model could accurately predict the severity of California wildfires and determine the most influential meteorological factors. It utilized a custom dataset with information from the World Weather Online API and a Kaggle dataset of wildfires in California from 2013-2020. The developed algorithms classified fires into seven categories with promising accuracy (around 55 percent). They found that higher temperatures, lower humidity, lower dew point, higher wind gusts, and higher wind speeds are the most significant contributors to the spread of a wildfire. This tool could vastly improve the efficiency and preparedness of firefighters as they deal with wildfires.
Read More...Heavy metal and bacterial water filtration using Moringa oleifera and coconut shell-activated carbon
One-third of the world's people do not have access to clean drinking water. Nadella and Nadella tackle this issue by testing a low-cost filtration system for removing heavy metal and bacteria from water.
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