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The authors use blood smears from individuals with sickle cell disease to correlate sickle cell frequency with the occurrence of vaso-occlusive crises.

The authors looked at different algorithms and their ability to encrypt and decrypt text of various lengths.

The authors re-examine the galactic kinematics of relic galaxy NGC 1277, recently identified as dark matter deficient, by reproducing its rotation curve with data from the George and Cynthia Mitchell Spectrograph.

The authors assess incidence and mortality rates of two cancer types in relation to trihalomethane pollutant concentrations in drinking water.

The authors looked at different factors that influence specific gravity in beverages, including sweetener used, caffeine, carbonation, and sodium.

The authors looked at genes that were differentially expressed in patients who had and had not had febrile seizures to determine what differences in gene expression existed.

The authors looked the ability to predict future stock prices using various machine learning models.

The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.

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.

This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.