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The authors looked at variables and their patterns and how those contribute to the properties of X-ray binaries.

Pulmonary diseases like lung cancer and valley fever pose serious health challenges, making accurate and rapid diagnostics essential. This study developed a MATLAB-based software tool that uses computer vision techniques to differentiate between these diseases by analyzing features of lung nodules in CT scans, achieving higher precision than traditional methods.

Here the authors sought to understand the effects of different variables that may be tied to pollution and climate change on genetic variation of Pacific white-sided dolphins, a species that is currently threatened by water pollution. Based on environmental data collected alongside a genetic distance matrix, they found that ocean currents had the most significant impact on the genetic diversity of Pacific white-sided dolphins along the Japanese coast.

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

The authors looked at ways to provide better forecasting on website traffic. They found that deep learning models performed better than statistical models.

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.

The purpose of this study was to determine the necessity of previous non-algorithmic attacks (Adversarial Training) in light of algorithmic defense methods (Gradient Masking and Defensive Distillation) against FGSM attacks. We found a significant increase in image classification accuracy from defense methods with the non-algorithmic defense method compared to ones without. By analyzing the significance with a McNemar test, we determined that the inclusion of non-algorithmic defense methods is still necessary in light of new algorithmic defense methods.

The authors investigated adoption rates of solar photovoltaic power at K-12 schools in California.

The main goal of this study is to determine what demographics are related to tuberculosis incidence in the United States populations, particularly if changing demographics are related to differences in tuberculosis risk over two discrete time periods. The major finding is that in the two studied time periods, tuberculosis risk factors were somewhat consistent and may be influenced by things such as immigration, healthcare access, and race or ethnicity, although the top predictor did change.

The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.