Here, seeking to identify the possible role of sports in helping teenagers navigate the troubles associated with societal changes during a pandemic, the authors surveyed 50 adolescents to collect Beck Depression Inventory scores. They found that 9 out of students with severe depressions did not do sports, while no significant relationship between depressive symptoms and either gender or place of exercise was observed.
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Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste
About 25% of the food grown never reaches consumers due to spoilage, and 11.5 billion pounds of produce from gardens are wasted every year. Current solutions involve farmers manually looking for and treating diseased crops. These methods of tending crops are neither time-efficient nor feasible. I used a convolutional neural network to identify signs of plant disease on leaves for garden owners and farmers.
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.
Read More...Blockchain databases: Encrypted for efficient and secure NoSQL key-store
Although commonly associated with cryptocurrency, blockchains offer security that other databases could benefit from. These student authors tested a blockchain database framework, and by tracking runtime of four independent variables, they prove this framework is feasible for application.
Read More...Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization
Here, seeking to identify the risk of coronary artery disease (CAD), a major cause of cardiovascular disease, the authors used Mendelian randomization. With this method they identified several traits such as blood pressure readings, LDL cholesterol and BMI as significant risk factors. While other traits were not found to be significant risk factors.
Read More...An accessible experiment to assess the impact of shapes of buildings and roofs on wind resistance
In this study, the authors determine which house model is most resistant to high winds by building smaller prototypes that could be tested with a handheld source of wind.
Read More... Machine learning-based enzyme engineering of PETase for improved efficiency in plastic degradation
Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.
Read More...Comparing the performance of lateral control algorithms on long rigid vehicles in urban environments
Here, seeking to better understand the control algorithms used in autonomous vehicles, the authors compared the Stanley and pure pursuit control algorithms along with a new version of each. Unexpectedly, they found that no control algorithm offered optimal performance, but rather resulted in tradeoffs between the various ideal results.
Read More...The relationship between income inequality and maternal mortality for black and white mothers
In this study, the authors measure the relationship between the Gini coefficient, a common measure of income inequality, and Black and White maternal mortality rates by state and year.
Read More...Using economic indicators to create an empirical model of inflation
Here, seeking to understand the correlation of 50 of the most important economic indicators with inflation, the authors used a rolling linear regression to identify indicators with the most significant correlation with the Month over Month Consumer Price Index Seasonally Adjusted (CPI). Ultimately the concluded that the average gasoline price, U.S. import price index, and 5-year market expected inflation had the most significant correlation with the CPI.
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