Browse Articles

Advancement in DNA sequencing technology has greatly increased our understanding about the role of bacteria in soil. The authors of this study examine the microbial content of soil samples taken from three locations in southern New Hampshire with varying pH and plant composition.

Physics‑Informed Neural Networks (PINNs) offer a promising way to estimate blood‑flow behavior in arteries, especially near the vessel wall where traditional methods struggle. In this study, students tested how sensor density and placement affect PINN accuracy in modeling carotid artery flow and found that accuracy improves up to a moderate sensor density and depends strongly on how close sensors are placed to the arterial wall. Applying the optimized configuration to a patient‑specific carotid model produced velocity predictions closely matching computational fluid dynamics results, highlighting PINNs’ potential for future personalized cardiovascular assessment.

Content warning: This article discusses the frequency and impact of mass violence incidents, particularly school shootings. Gun violence, threats of gun violence, firearm supply, fatalities among minors, and bullying are discussed but not graphically described.

This study contributes to our understanding of how urban energy systems respond to climate variability and inform strategies for enhancing power grid resilience. The findings can help inform urban planners and infrastructure developers by identifying the factors that make regions within a power grid more vulnerable.

The authors analyzed racial and ethnic representation in studies on PFAS and neurological health outcomes.

The authors looked at the immunogenicity of a newly developed pneumococcal conjugate vaccine compared to a previously developed one. They found the newly developed vaccine did elicit an immune response.

Using machine learning to predict the risk of algae bloom

Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.

This study explores how to predict and minimize distortion in 3D printed parts, particularly when using affordable PLA filament. The researchers developed a model using a gradient boosting regressor trained on 3D printing data, aiming to predict the necessary CAD dimensions to counteract print distortion.

In this study, the authors investigate the suitability of using bacterial cellulose as a scaffold for cell transplants. Interestingly, this cellulose is a can be found in the discard from a symbiotic culture of bacteria and yeast (SCOBY) used to make kombucha.