In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.

The authors use the Lanczos algorithm to computationally solve the Schrodinger equation for 2D potentials with a Python program

In this study, the authors investigate the effects of sodium levels on blood pressure, one of the most common medical problems worldwide. They used a simulated blood vessel constructed from dialysis tubing to carefully analyze pressure changes resulting from various levels of sodium in the external solution. They found that when the sodium concentration in the simulated blood vessel was higher than the external fluid, internal pressure increased, while the reverse was true when the sodium concentration was lower than in the surrounding environment. These results highlight the potential for sodium concentration to have a significant effect on blood pressure in humans by affecting the rate of osmosis across the boundaries of actual blood vessels.

End Stage Renal Disease (ESRD) is a growing health concern in the United States. The authors of this study present a study of ESRD incidence over a 32-year period, providing an in-depth look at the contributions of age, race, gender, and underlying medical factors to this disease.

In this study, the authors investigate just how effectively paper towels can absorb different types of liquid and whether changing the properties of the towel (such as folding it) affects absorbance. Using variables of either different liquid types or the folded state of the paper towels, they used thorough approaches to make some important and very useful conclusions about optimal ways to use paper towels. This has important implications as we as a society continue to use more and more paper towels.

There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.

In this study, the authors investigate a timely and important topic: forest fires. More specifically, they use a wildfire simulator to test how ladder fuels effect the burn area of a forest fire. Ladder fuels are fuels that cause a forest fire to rise up from the forest floor to the canopy, which may affect the overall spread. They simulated fire spread with different levels of ladder fuel treatment and found that the spread of a burn area would indeed decrease with increased ladder fuel treatment. These findings have important implications for forest and forest fire management.

Farmers will need to increase crop yields to feed the world's growing population efficiently. The authors here investigate the effects of growing corn in the presence or absence of ragweed, an invasive weed found in many fields and gardens. Surprisingly, the authors found that corn grown in the presence of weeds grew taller and were more productive than corn that had weeds removed. This may help gardeners rethink the necessity of weeding, and may point a way to improve farm yields in the future.

Powered by the sociological framework that exposure to television bleeds into social biases, limiting media representation of women and minority groups may lead to real-world implications and manifestations of racial and gender disparities. To address this phenomenon, the researchers in this article take a look at primetime fictional representation of minorities and women as lawyers and physicians and compare television representation to census data of the same groups within real-world legal and medical occupations. The authors maintain the hypothesis that representation of female and minority groups as television lawyers and doctors is lower than that of their white male counterparts relative to population demographics - a trend that they expect to also be reflected in actual practice. With fictional racial and gender inequalities and corresponding real-world trends highlighted within this article, the researchers call for address towards representation biases that reinforce each other in both fictional and non-fictional spheres.

Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.