The authors looked at the ability of different machine learning algorithms to predict the level of financial corruption in different countries.
Read More...Predicting and explaining illicit financial flows in developing countries: A machine learning approach
The authors looked at the ability of different machine learning algorithms to predict the level of financial corruption in different countries.
Read More...The effect of economic downturns on the frequency of mass shootings
Researching gun violence and mass shootings in the U.S. is difficult due to the lack of consistent data collection. Some studies have linked mass shootings to personal financial stress, but little formal research exists on the impact of broader economic conditions. This study hypothesized an inverse relationship between mass shootings and economic performance, using the S&P 500 and unemployment rate as indicators.
Read More...Comparative life cycle analysis: Solvent recycling and improved dewatering scenarios in PHB plastic production
The authors looked at alternative production processes for PHB plastic in an effort to reduce environmental impact. They found that no alternative process was able to significantly decrease the environmental impact of PHB production, but that optimizing dewatering steps during production could lead to the largest improvement on environmental impact.
Read More...Computational Study of Erosion Effects on a Triangular Aerofoil's Aerodynamics at Reynolds number of 10,000
This study examined the impact of erosion on the performance of a triangular aerofoil at a low Reynolds number (Re = 10,000), relevant for harsh conditions like those on Mars.
Read More...Contribution of Indian Women to the National GDP
The authors assessed the degree of women participation in India's economy as a way to estimate woman's participation in India's economic growth.
Read More...The effect of music on teenagers in combatting stress and improving performance
Here, the researchers investigated how exposure to active versus passive music affects a teenager's ability to perform a challenging task, namely a Sudoku puzzle, under stressful conditions. Following testing 75 high school teenagers split into two group, the researchers found that singing in a choir (active music) yielded a greater improvement in performance compared to passive listening for brief time periods.
Read More...Near-infrared activation of environmentally-friendly gold and silver nanoparticles for unclogging arteries
Coronary artery disease, the leading cause of death worldwide, results from cholesterol build-up in coronary arteries, limiting blood and oxygen flow to the heart. This study investigated the use of gold and silver nanoparticles coated with aspirin and activated by near-infrared light to improve blood flow in a clogged artery model. The nanoparticles increased simulated blood flow rates, demonstrating potential as a less invasive and more targeted treatment for cardiovascular disease.
Read More...Does language familiarity affect typing speed?
In cognitive psychology, typed responses are used to assess thinking skills and creativity, but research on factors influencing typing speed is limited. This study examined how language familiarity affects typing speed, hypothesizing that familiarity with a language would correlate with faster typing. Participants typed faster in English than Latin, with those unfamiliar with Latin showing a larger discrepancy between the two languages, though Latin education level did not significantly impact typing speed, highlighting the role of language familiarity in typing performance.
Read More...Analyzing the relationships between years of experience and performance anxiety in teen volleyball players
Athletes with performance anxiety may struggle to play their best and enjoy the game. Various factors may impact how much anxiety an athlete feels, including how much experience they have in the sport. Concha-Ortiz and Navins survey teenage club volleyball players to look for relationships between years of experience and performance anxiety symptoms.
Read More...Diagnosing hypertrophic cardiomyopathy using machine learning models on CMRs and EKGs of the heart
Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.
Read More...