In this article, the authors investigate the shear modulus of different types of paper in the setting of the crumpling effect.

The Young's Modulus of a structural material is a measure of its elasticity and is defined as the ratio of the tensile stress to tensile strain. This study aims to investigate the Young's Modulus of pasta with different diameters.

In this study, the authors investigate the effects that flagella have on E. coli's ability to adhere to glass surfaces.

Scientists are always on the quest to improve the body's healing abilities and broken bones are no exception. In this article, the authors investigate properties of 3D-printed biocompatible polymers used to improve bone healing. With such efforts, we can hope to, one day, improve bone scaffolding materials in ways that make the natural healing processes more efficient, reducing the time needed for recovery from bone fractures.

The authors looked at previous studies to evaluate the ability to use serum levels of certain cytokines as biomarkers for pneumoconiosis.

The authors explore hearing students' misconceptions about the Deaf and Hard of Hearing (HoH) community. Results indicate that some misconceptions are more common than others, and that personal experience with individuals in the Deaf and HoH community reduces the frequency of such misconceptions.

Here, the authors considered the stretching behavior of rubber bands by exposing the rubber bands to increasing loads and measuring their stretch response. They found that a linear stretch response was observed for intermediate loading steps, but this behavior was lost at lower or higher loads, deviating from Hooke's Law. The authors suggest that studies such as these can be used to evaluate other visco-elastic structures.

Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.

Enzyme chemotaxis is a thermodynamic phenomenon in which enzymes move along a substrate concentration gradient towards regions with higher substrate concentrations and can be used to steer nanovehicles towards targets along natural substrate concentrations. In patients with Alzheimer’s disease, a gradient of tau protein forms in the bloodstream. Tau protein is a substrate of the enzyme CDK5, which catalyzes the phosphorylation of tau protein and can travel using chemotaxis along tau protein gradients to increasing concentrations of tau and amyloid-beta proteins. The authors hypothesized that CDK5 would be able to overcome these barriers of Brownian motion and developed a quantitative model using Michaelis-Menten kinetics to define the necessary parameters to confirm and characterize CDK5’s chemotactic behavior to establish its utility in drug delivery and other applications.

The diagnosis of malaria remains one of the major hurdles to eradicating the disease, especially among poorer populations. Here, the authors use machine learning to improve the accuracy of deep learning algorithms that automate the diagnosis of malaria using images of blood smears from patients, which could make diagnosis easier and faster for many.