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The authors looked at what conditions with host stars favor development of exoplanets.

The authors looked at different factors, such as age, pre-existing conditions, and geographic region, and their ability to predict what an individual's health insurance premium would be.

In this study the authors looked at the ability to navigate planes in space between randomly placed planets. They used machine and reinforcement learning to run simulations and found that they were able to identify optimal paths for travel. In the future these techniques may allow for safer travel in unknown spaces.

The authors assessed the atmospheric and oceanic parameters necessary for tidally-locked exoplanets to be habitable.

Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.

The authors compare the predicted versus actual geyser eruption times for the Old Faithful and Beehive Geysers at Yellowstone National Park.

Here, the authors investigated engagement with #GMOFOODS, a hashtag on TikTok. They hypothesized that content focused on the negative effects of genetically modified organisms would receive more interaction driven by consumers. They found that the most common cateogry focused on the disadvantages of GMOs related to nutrition and health with the number of views determining if the video would be provided to users.

The authors test whether basil can grow in a simulated Martian soil improved with a waste-based fertilizer called Milorganite.

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 propose a method to recycle Christmas tree needles into a non-toxic reducing agent for synthesizing copper nanoparticles.