![Understanding investors behaviors during the COVID-19 outbreak using Twitter sentiment analysis](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBckVQIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--15772d1c4910d165b426d6774432b77f2a5a524e/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJY0c1bkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--33b2b080106a274a4ca568f8742d366d42f20c14/feature.png)
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...Evaluating TensorFlow image classification in classifying proton collision images for particle colliders
In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.
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...Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques
Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.
Read More...The Effect of Anubias barteri Plant Species on Limiting Freshwater Acidification
Research relating to freshwater acidification is minimal, so the impact of aquatic plants, Anubias barteri var. congensis and Anubias barteri var. nana, on minimizing changes in pH was explored in an ecosystem in Northern California. Creek water samples, with and without the aquatic plants, were exposed to dry ice to simulate carbon emissions and the pH was monitored over an eight-hour period. There was a 25% difference in the observed pH based on molar hydrogen ion concentration between the water samples with plants and those without plants, suggesting that aquatic plants have the potential to limit acidification to some extent. These findings can guide future research to explore the viable partial solution of aquatic plants in combating freshwater acidification.
Read More...Use of drone with sodium hydroxide carriers to absorb carbon dioxide from ambient air
In this study, the authors address the current climate concern of high CO2 levels by testing solid forms of hydroxide for CO2 reduction and designing a drone to fly it in ambient air!
Read More...Androgen Diffusion Patterns in Soil: Potential Watershed Impacts
Androgens are natural or synthetic steroid hormones that control secondary male sex characteristics. Androgens are excreted in cattle urine and feces, and can run off or seep into nearby waters, negatively impacting aquatic life and potentially polluting human water sources. Here, the authors investigated the effectiveness of soil as a natural barrier against androgen flow into vulnerable waterways. Their results, obtained by testing diffusion patterns of luminol, an androgen chemical analog, indicated that soil is a poor barrier to androgen diffusion.
Read More...Voltage, power, and energy production of a Shewanella oneidensis biofilm microbial fuel cell in microgravity
The authors looked at the ability of Shewanella oneidensis to generate energy in a microbial fuel cell under varying conditions. They found that the S. Onedensis biofilm was able to produce energy in microgravity and that one of the biggest factors that limited energy production was a decrease in growth medium present.
Read More...A spatiotemporal analysis of OECD member countries on sugar consumption and labor force participation
In this article the authors look at sugar consumption and the relationship to productivity in the work/labor force.
Read More...Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.
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