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Extended CT Void Analysis in FDM Additive Manufacturing Components
This article provides an extended analysis of void shape by means of X-ray computed tomography (CT) applied to fused deposition modeling (FDM) samples. Furthermore, a relation between the tensile mechanical properties and digital void measurements is established. The results lead to the formulation of a novel criterion that predicts the mechanical behavior of AM components.
Date:
July 26, 2020
Creator:
Hernandez-Contreras, Adriana; Ruiz-Huerta, Leopoldo; Caballero-Ruiz, Alberto; Moock, Verena & Siller Carrillo, Héctor Rafael
System:
The UNT Digital Library
Fabrication of densified wood via synergy of chemical pretreatment, hot-pressing and post mechanical fixation
Article describes examination of the appearance, color, chemical composition, and physiology and mechanical properties of densified Abies wood before and after densification treatment using a colorimeter, FTIR and mechanical testing machine.
Date:
January 30, 2020
Creator:
Shi, Jiangtao; Peng, Junyi; Huang, Qiongtao; Cai, Liping & Shi, Sheldon
System:
The UNT Digital Library
In-vitro biomineralization and biocompatibility of friction stir additively manufactured AZ31B magnesium alloy-hydroxyapatite composites
Article presents research where friction stir additive manufacturing technique was employed to fabricate AZ31B magnesium-hydroxyapatite composite. The study aims to evaluate effect of hydroxyapatite (HA, Ca₁₀(PO₄)₆OH₂), a ceramic similar to natural bone, into AZ31B Mg alloy matrix on biomineralization and biocompatibility.
Date:
June 30, 2020
Creator:
Ho, Yee-Hsien; Man, Kun; Joshi, Sameehan; Pantawane, Mangesh V.; Wu, Tso-Chang; Yang, Yong et al.
System:
The UNT Digital Library
Inks of dielectric h-BN and semiconducting WS₂ for capacitive structures with graphene
This article presents dispersions of WS₂ and h-BN using cyclohexanone and terpineol as the solvent to subsequently print prototype capacitive nanodevices.
Date:
July 30, 2020
Creator:
Desai, Jay A.; Mazumder, Sangram; Hossain, Ridwan Fayaz & Kaul, Anupama
System:
The UNT Digital Library
JS-MA: A Jensen-Shannon Divergence Based Method for Mapping Genome-Wide Associations on Multiple Diseases
Article develops a a simple, fast, and powerful method, named JS-MA, based on Jensen-Shannon divergence and agglomerative hierarchical clustering, to detect the genome-wide multi-locus interactions associated with multiple diseases.
Date:
October 30, 2020
Creator:
Guo, Xuan
System:
The UNT Digital Library
NRPreTo: A Machine Learning-Based Nuclear Receptor and Subfamily Prediction Tool
Article asserts that the nuclear receptor (NR) superfamily includes phylogenetically related ligand-activated proteins, which play a key role in various cellular activities. The authors developed Nuclear Receptor Prediction Tool (NRPreTo), a two-level NR prediction tool with a unique training approach where in addition to the sequence-based features used by existing NR prediction tools, six additional feature groups depicting various physiochemical, structural, and evolutionary features of proteins were utilized.
Date:
May 30, 2023
Creator:
Madugula, Sita Sirisha; Pandey, Suman; Amalapurapu, Shreya & Bozdag, Serdar
System:
The UNT Digital Library
Phase-Specific Damage Tolerance of a Eutectic High Entropy Alloy
Article describes how phase-specific damage tolerance was investigated for the AlCoCrFeNi2.1 high entropy alloy with a lamellar microstructure of L12 and B2 phases. Distinct differences in micro-scale deformation mechanisms were reflected in post-compression fractography, with L12-phase cantilevers showing typical characteristics of ductile failure, including the activation of multiple slip lanes, shear lips at the notch edge, and tearing inside the notch versus quasi-cleavage fracture with cleavage facets and a river pattern on the fracture surface for the B2-phase cantilevers.
Date:
November 30, 2023
Creator:
Jha, Shristy; Mishra, R. S. & Mukherjee, Sundeep
System:
The UNT Digital Library
PPAD: a deep learning architecture to predict progression of Alzheimer’s disease
Article asserts that Alzheimer’s disease (AD) is a neurodegenerative disease that affects millions of people worldwide. The authors of the article propose two deep learning architectures based on RNN, namely Predicting Progression of Alzheimer’s Disease (PPAD) and PPAD-Autoencoder.
Date:
June 30, 2023
Creator:
Olaimat, Mohammad Al; Martinez, Jared; Saeed, Fahad & Bozdag, Serdar
System:
The UNT Digital Library
Reconstructing aerosol optical depth using spatiotemporal Long Short-Term Memory convolutional autoencoder
Article describes how Aerosol Optical Depth (AOD)is a crucial atmospheric parameter in comprehending climate change, air quality, and its impacts on human health. This study presents a new solution to this challenge by providing a long-term, gapless satellite-derived AOD dataset for Texas from 2010 to 2022, utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) multi-angle implementation of atmospheric correction (MAIAC) products.
Date:
November 30, 2023
Creator:
Liang, Lu; Daniels, Jacob; Biancardi, Micahel & Zhou, Yuye
System:
The UNT Digital Library
Securing Industrial Control Systems: Components, Cyber Threats, and Machine Learning-Driven Defense Strategies
Article describes how Industrial Control Systems (ICS), which include Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers (PLC), play a crucial role in managing and regulating industrial processes. This article presents an overview of ICS security, covering its components, protocols, industrial applications, and performance aspects.
Date:
October 30, 2023
Creator:
Nankya, Mary; Chataut, Robin & Akl, Robert
System:
The UNT Digital Library