Engineering Commons^™

Experimental And Computational Platforms For Studying Systems Mechanobiology, Brendyn Miller

All Dissertations

Mechanical stimulation through physical activity has been shown to play an important role in treating and preventing several non-communicable diseases such as hypertension, lower back pain (LBP), type-2 diabetes mellitus, and several cancers. This is accomplished through the regulation of cellular behavior and tissue remodeling within the body at both the micro- and macro-scale levels. The goal of mechanobiology research is to gain in-depth knowledge and understanding of how cells sense physical forces in conjunction with other biochemical cues and translate those factors into important biological functions that either maintain tissue homeostasis or lead to pathological states. Understanding these processes …

Ti-6al-4v Β Phase Selective Dissolution: In Vitro Mechanism And Prediction, Michael A Kurtz

All Dissertations

Retrieval studies document Ti-6Al-4V β phase dissolution within total hip replacement systems. A gap persists in our mechanistic understanding and existing standards fail to reproduce this damage. This thesis aims to (1) elucidate the Ti-6Al-4V selective dissolution mechanism as functions of solution chemistry, electrode potential and temperature; (2) investigate the effects of adverse electrochemical conditions on additively manufactured (AM) titanium alloys and (3) apply machine learning to predict the Ti-6Al-4V dissolution state. We hypothesized that (1) cathodic activation and inflammatory species (H₂O₂) would degrade the Ti-6Al-4V oxide, promoting dissolution; (2) AM Ti-6Al-4V selective dissolution would occur …

Predicting Corrosion Damage In The Human Body Using Artificial Intelligence: In Vitro Progress And Future Applications Applications, Michael A. Kurtz, Ruoyu Yang, Mohan S. R. Elapolu, Audrey C. Wessinger, William Nelson, Kazzandra Alaniz, Rahul Rai, Jeremy L. Gilbert

Publications

Artificial intelligence (AI) is used in the clinic to improve patient care. While the successes illustrate the impact AI can have, few studies have led to improved clinical outcomes. A gap in translational studies, beginning at the basic science level, exists. In this review, we focus on how AI models implemented in non-orthopedic fields of corrosion science may apply to the study of orthopedic alloys. We first define and introduce fundamental AI concepts and models, as well as physiologically relevant corrosion damage modes. We then systematically review the corrosion/AI literature. Finally, we identify several AI models that may be Preprint …

Neural Correlates Of Post-Traumatic Brain Injury (Tbi) Attention Deficits In Children, Meng Cao

Dissertations

Traumatic brain injury (TBI) in children is a major public health concern worldwide. Attention deficits are among the most common neurocognitive and behavioral consequences in children post-TBI which have significant negative impacts on their educational and social outcomes and compromise the quality of their lives. However, there is a paucity of evidence to guide the optimal treatment strategies of attention deficit related symptoms in children post-TBI due to the lack of understanding regarding its neurobiological substrate. Thus, it is critical to understand the neural mechanisms associated with TBI-induced attention deficits in children so that more refined and tailored strategies can …

On The Pursuit Of Developer Happiness: Webcam-Based Eye Tracking And Affect Recognition In The Ide, Tamsin Rogers

Honors Theses

Recent research highlights the viability of webcam-based eye tracking as a low-cost alternative to dedicated remote eye trackers. Simultaneously, research shows the importance of understanding emotions of software developers, where it was found that emotions have significant effects on productivity, code quality, and team dynamics. In this paper, we present our work towards an integrated eye-tracking and affect recognition tool for use during software development. This combined approach could enhance our understanding of software development by combining information about the code developers are looking at, along with the emotions they experience. The presented tool utilizes an unmodified webcam to capture …

Breast Density Classification Using Deep Learning, Conrad Thomas Testagrose

UNF Graduate Theses and Dissertations

Breast density screenings are an accepted means to determine a patient's predisposed risk of breast cancer development. Although the direct correlation is not fully understood, breast cancer risk increases with higher levels of mammographic breast density. Radiologists visually assess a patient's breast density using mammogram images and assign a density score based on four breast density categories outlined by the Breast Imaging and Reporting Data Systems (BI-RADS). There have been efforts to develop automated tools that assist radiologists with increasing workloads and to help reduce the intra- and inter-rater variability between radiologists. In this thesis, I explored two deep-learning-based approaches …

Machine Learning And Deep Learning Approaches For Gene Regulatory Network Inference In Plant Species, Sai Teja Mummadi

Dissertations, Master's Theses and Master's Reports

The construction of gene regulatory networks (GRNs) is vital for understanding the regulation of metabolic pathways, biological processes, and complex traits during plant growth and responses to environmental cues and stresses. The increasing availability of public databases has facilitated the development of numerous methods for inferring gene regulatory relationships between transcription factors and their targets. However, there is limited research on supervised learning techniques that utilize available regulatory relationships of plant species in public databases.

This study investigates the potential of machine learning (ML), deep learning (DL), and hybrid approaches for constructing GRNs in plant species, specifically Arabidopsis thaliana, …