Charge stabilization via electron exchange: excited charge separation in symmetric, central triphenylamine derived, dimethylaminophenyl–tetracyanobutadiene donor–acceptor conjugates (open access)

Charge stabilization via electron exchange: excited charge separation in symmetric, central triphenylamine derived, dimethylaminophenyl–tetracyanobutadiene donor–acceptor conjugates

This article hypothesizes and demonstrates a new mechanism to stabilize the charge separated states via the process of electron exchange among the different acceptor entities in multimodular donor–acceptor conjugates. This work constitutes the first example of stabilizing charge-separated states via the process of electron exchange.
Date: November 13, 2020
Creator: Yadav, Indresh S.; Alsaleh, Ajyal Z.; Misra, Rajneesh & D'Souza, Francis
Object Type: Article
System: The UNT Digital Library
Key Challenges and Some Guidance on Using Strong Quantitative Methodology in Education Research (open access)

Key Challenges and Some Guidance on Using Strong Quantitative Methodology in Education Research

Article reviews several common areas of focus in quantitative methods with the hope of providing guidance on conducting and reporting quantitative analyses. The review addresses causal inferences, measurement issues, handling missing data, testing for assumptions, dealing with nested data, and providing evidence for outcomes.
Date: November 13, 2020
Creator: Henson, Robin K.; Stewart, Genéa & Bedford, Lee A.
Object Type: Article
System: The UNT Digital Library

Techniques and Technologies for Teaching and Learning Online

This presentation explores several techniques and technologies used to deliver information to learners in synchronous and asynchronous environments. It was presented at the Art Libraries Society of North America's Texas-Mexico Chapter Annual Meeting on November 13, 2020.
Date: November 13, 2020
Creator: Roy, Meranda M.
Object Type: Presentation
System: The UNT Digital Library
Using Machine Learning to Predict Genes Underlying Differentiation of Multipartite and Unipartite Traits in Bacteria (open access)

Using Machine Learning to Predict Genes Underlying Differentiation of Multipartite and Unipartite Traits in Bacteria

Article describes how, since the discovery of the second chromosome in the Rhodobacter spaeroides 2.4.1 in 1989 and the revelation of gene sequences, multipartite genomes have been reported in over three hundred bacterial species under nine different phyla. In this study, the authors have attempted to leverage machine learning as a means to identify the genetic factors that underlie the differentiation of bacteria with multipartite and unipartite genomes.
Date: November 13, 2023
Creator: Almalki, Fatemah; Sunuwar, Janak & Azad, Rajeev K.
Object Type: Article
System: The UNT Digital Library