Microstructure and surface texture driven improvement in in-vitro response of laser surface processed AZ31B magnesium alloy (open access)

Microstructure and surface texture driven improvement in in-vitro response of laser surface processed AZ31B magnesium alloy

This article explores the effects of laser surface melting on microstructure and surface topography evolution in AZ31B magnesium alloy.
Date: January 19, 2021
Creator: Wu, Tso-Chang; Joshi, Sameehan; Ho, Yee-Hsien; Pantawane, Mangesh V.; Sinha, Subhasis & Dahotre, Narendra B.
System: The UNT Digital Library
Classifying Abdominal Fat Distribution Patterns by Using Body Measurement Data (open access)

Classifying Abdominal Fat Distribution Patterns by Using Body Measurement Data

This article aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI), to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs), and to develop a classifier to predict the fat distribution clusters using the BSDs.
Date: February 19, 2021
Creator: Sun, Jingjing; Xu, Bugao; Lee, Jane & Freeland-Graves, Jeanne H.
System: The UNT Digital Library
Bioresorbable stent to manage congenital heart defects in children (open access)

Bioresorbable stent to manage congenital heart defects in children

This article assembles large, pediatric-sized stents (Ø10 - Ø20 mm) from poly(L-lactide) fibers (DH-BDS) at two thicknesses, 250 µm and 300 µm. DH-BDS exhibiting hoop strength similar to metal stents and demonstrating minimal degradation and strength loss over the first year before completely disappearing within 3 to 4.5 years show promise as a pediatric interventional alternative to current strategies.
Date: March 19, 2021
Creator: Wright, Jamie; Nguyen, Annie; D'Souza, Nandika Anne, 1967-; Forbess, Joseph M.; Nugent, Alan; Reddy, Surenderanath R. Veeram et al.
System: The UNT Digital Library
Predicting psoriasis using routine laboratory tests with random forest (open access)

Predicting psoriasis using routine laboratory tests with random forest

Article describes how psoriasis is a chronic inflammatory skin disease that affects approximately 125 million people worldwide. The goal of the authors' study is to derive a powerful predictive model for psoriasis disease based on only routine hospital tests.
Date: October 19, 2021
Creator: Zhou, Jing; Li, Yuzhen & Guo, Xuan
System: The UNT Digital Library