In this study, the authors investigate whether the addition of microbes from native soil enhanced the seed germination and growth of mung beans, pumpkins, and pea flower plants.

In this experiment, the authors modify the heat equation to account for imperfect insulation during heat transfer and compare it to experimental data to determine which is more accurate.

In this study, the authors test different infill patterns to determine which would be the strongest and most durable for 3D printing applications, which have become an integral part of many facets of life.

The purpose of our study was to determine if direct administration of CXCL1/KC to cardiomyocytes causes negative changes to cell density or proliferation. This molecule has been shown to reduce inflammation in certain instances. Homocysteine models the direct effect of an inflammatory agent on cardiomyocytes. Our question was whether these molecules directly impact cell density through an interaction with the cell proliferation process. We hypothesized that cells treated with CXCL1/KC would maintain the same cell density as untreated cells. In contrast, cells treated with Homocysteine or both Homocysteine and CXCL1/KC, were expected to have a higher cell density that than that of untreated cells.

In this study, the biodiversity of marine animals was studied at different locations along a mangrove, which is a salt-tolerant shrub with elaborate root structures that is found on tropical coastlines.

Every year, around 40% of undergraduate students in the United States discontinue their studies, resulting in a loss of valuable education for students and a loss of money for colleges. Even so, colleges across the nation struggle to discover the underlying causes of these high dropout rates. In this paper, the authors discuss the use of machine learning to find correlations between the built environment factors and the retention rates of colleges. They hypothesized that one way for colleges to improve their retention rates could be to improve the physical characteristics of their campus to be more pleasing. The authors used image classification techniques to look at images of colleges and correlate certain features like colors, cars, and people to higher or lower retention rates. With three possible options of high, medium, and low retention rates, the probability that their models reached the right conclusion if they simply chose randomly was 33%. After finding that this 33%, or 0.33 mark, always fell outside of the 99% confidence intervals built around their models’ accuracies, the authors concluded that their machine learning techniques can be used to find correlations between certain environmental factors and retention rates.

In this study, the authors developed a model named DNA Sequence Embedding Network (DNA-SEnet) to classify DNA-asthma associations using their genomic patterns.

The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.

Each day we are flooded with new items that promise us a better experience at a better price. This forces buyers to continuously chose between sticking to what they know, or trying something new. In turn, companies need to be aware of the factors affecting consumer choices, that too within the different fractions of society. In this study the authors investigate the effect of survey-based price setting on profits made based on African American teen purchases, and how African-American teen loyalty to a particular brand affects their willingness to pay a higher price than the market average for their preferred brand items.

Oligodendrocytes are specialized brain cells that can change to cells that produce myelin and protect nerves. This study investigates the capacity for different extracellular matrix cues to induce this effect in culture.