Browse Articles

This study, uses SimulATe to model changes in microbial diversity and community structure upon administering a cocktail of antibiotics versus a single antibiotic. The authors hypothesized that antibiotic cocktails, particularly those combining broad-spectrum drugs like tetracyclines and trimethoprims, would cause a more significant reduction in gut microbial diversity compared to single-drug treatments. The findings confirmed a greater loss of microbial diversity with combinatorial treatments compared to single-drug treatments. While individual antibiotics dynamically reshaped the surviving species of the microbiome, antibiotic cocktails frequently cleared all species of the gut microbiome.

This study strongly illustrates that optimizing 3D printing parameters would enhance a triboelectric nanogenerator's performance. The design improvements substantiate the potential of optimized, 3D-printed TENGs for developing scalable, cost-effective solutions for powering low-energy electronics, particularly in applications such as structural health monitoring.

This study aims to examine the demographic factors that predict patterns of co-use of alcohol and marijuana in the United States. Significant findings were identified using data from the National Survey on Drug Use and Health (2012-2022), showing that there were significant differences in the prevalence of substance use among demographic groups, with young adults showing the highest co-use of alcohol and marijuana.

This study used machine learning models to examine which factors most influenced U.S. household energy consumption in 2020 using data from 18,496 households.

Detecting cervical spondylosis using deep learning

The authors looked at the ability subjects to rotation a 4D cube and how the ability to practice cube rotation impact their ability to understand 4D space.

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

The authors looked at if there was any correlation between the phase of the moon and admissions for psychiatric concerns.

The authors looked the ability of sound sensors to predict clogged pipes when the sound intensity data is run through a machine learning algorithm.

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