Electronic Thesis or Dissertation

A nearshore ridge complex (NRC) sits less than 250 m from the coast of Pompano Beach in Southeast Florida, and the varied bottom types within this complex may represent critical habitat for benthic mollusks. In order to document the diversity of mollusks within the NRC, SCUBA-based roving surveys were conducted between 2011 and 2019. Between 2021 and 2022, sediment samples were also collected from each of the bottom types to study mollusk diversity patterns. This combination of survey methods resulted in the identification of 325 species of hard-shelled mollusks, representing 103 families and 4 classes. To test for differences in community structure between bottom types, relative abundance data from the sediment samples was used for multivariate analyses including NMDS ordination, ANOSIM, and hierarchical cluster analysis. Results indicated statistically significant differences in mollusk species composition between NRC bottom types.

Effective communication and a sense of togetherness between people from different backgrounds happen on a platform of mutual understanding. The boundaries of differences between people from various cultures limit our understanding of each other's conditions, problems, and concerns. As a designer, I seek to fade the boundaries between cultures and facilitate a conversation, promoting mutual understanding by blending visual elements from American and Iranian cultures. With interactive visual media and storytelling, I have created diverse visual artworks that combine traditional Iranian arts and crafts elements with visuals from American popular culture. This body of work includes illustrations, patterns, motion design, audio, and augmented reality. Through these shared visual experiences, I aim to introduce new values into the sphere of design, enrich the design world with diversity, and build a shared visual experience that talks both to Iranians and the cultural milieu of the United States. Producing art pieces with the theme of Shared Visual Experiences can aid in promoting diversity, fostering connection, encouraging innovation and creativity, and bringing attention to significant social and cultural issues. It is a meaningful way to contribute to a more interconnected world that benefits everyone.

Since the emergence of stony coral tissue loss disease (SCTLD) in 2014, 60% of live coral cover on Florida’s coral reefs have been lost. This study assessed the efficacy of outplanting microfragment colony arrays of three SCTLD-susceptible coral species (Montastraea cavernosa, Orbicella faveolata, and Pseudodiploria clivosa) as remediation technique in two SCTLD-degraded reef areas, St. Lucie Reef and Palm Beach, in southeast Florida. After approximately 2 years, outplanted colonies at both reefs experienced ≥ 75 % survivorship, net positive growth rates, and fragment fusion, with some variation between species and across reefs. Additionally, outplanting SCTLD-susceptible species did not increase local disease prevalence and resulted in low disease prevalence on the outplanted colonies. The results from this study will be used to inform and optimize ongoing and future outplanting based coral restoration projects throughout Florida’s coral reefs and the wider Caribbean.

Liposuction is a common invasive procedure. Liposuction is performed for cosmetic and non-cosmetic reasons. Its use in regenerative medicine has been increasing. Its invasive nature renders it to have complications which can cause limitations in patients' recovery and patient lives. This thesis’s aim is to create an analytical framework to assess the liposuction procedure and its outcomes. The fundamental requirement to create this framework is to have a complete understanding of the procedure which includes preparation and planning of the procedure, correctly performing the procedure and ensuring patient safety on day 0, week 2, week 4, and week 12 of the procedure. 54 patient’s liposuction outcomes were followed till week 12. Data collection is the first part of the framework, which involves understanding the complex surgical outcomes. Algorithms that have been previously studied to assess morbidities and mortalities have been used in this framework to assess if they can assess liposuction outcomes. In this framework algorithms like decision tree, XG boost, random forest, support vector classifier, k nearest neighbor, k means, k fold validation have been used. XG boost performed best to assess liposuction outcomes without validation. However, after cross validation other algorithms which are random forest, support vector machine and KNN classifier outperformed XG boost. This framework allows to assess liposuction outcomes based on the performance of the algorithms. In future, researchers can use this framework to assess liposuction as well as other surgical outcome.

The striatum, a region of the brain responsible for motor control and reward processing, plays a critical role in various neurological disorders, including Parkinson's disease, Huntington's disease, and addiction. Gnal encodes the heterotrimeric G-protein stimulatory alpha subunit, Gαolf. Gαolf is highly expressed in the striatum, a brain region that is highly relevant to psychosis and psychostimulant drug action. The Gγ7 protein is also enriched in the striatum, where we have previously shown that Gγ7 protein is required at the posttranscriptional level for the hierarchical assembly of the striatal-specific Gαo lfβ2γ7 heterotrimer, which represents the rate-limiting step for cAMP production in striatal D1R and D2R-expressing neurons in the D1 dopamine and A2a adenosine pathways.
Multiple transcripts with variable 3’ UTRs are produced from the Gng7 gene. Previous studies have shown that genes with these characteristics are post-transcriptionally regulated and can be subcellularly localized. Thus, we hypothesized that the γ7 transcripts with variable 3’UTRs act as signaling organizers that regulate the abundance and/or subcellular localization required for preferential assembly and specialized signaling by Golf heterotrimer in the brain. Our findings showed that striatal-enriched γ7 transcripts are post-transcriptionally regulated by virtue of regulatory elements outside of the coding region that bind to its long 3’UTR. These regulatory elements are responsible for translational repression of the γ7 protein. The different length 3’UTRs of the γ7 transcripts 1 and 3 allow for subcellar localization in the nuclei and the neuropil respectively.

The thesis focuses on the relationship between artificial intelligence (AI) and graphic design, aiming to understand AI's potential while emphasizing the unique value of human designers. This exploration will involve transforming AI-generated patterns into physical forms using paper, demonstrating the positive possibilities of AI in creative pursuits. By blending AI output with human creativity, the thesis will show how both play essential, distinct roles.
The study addresses concerns about AI's potential to replace human artists. By highlighting AI as a tool that enhances, rather than replaces, human creativity, the thesis debunks the misconception that AI will eradicate human artistry. Instead, AI can inspire and expedite creative processes while artists remain responsible for the final production.
Using Midjourney, a generative AI system, the research underscores AI's limitations in fully understanding or replicating human imagination. The study emphasizes the importance of human touch in design, particularly when using paper—a material with deep historical and cultural roots in graphic design and communication.
Furthermore, paper's use extends beyond art and design, proving its versatility and importance across various fields. The thesis highlights human ingenuity's role in maximizing paper's potential across disciplines, underscoring the critical contribution of human creativity.

Modeling, implementation, field testing and control of a power takeoff (PTO) device equipped with a ball-type continuously variable transmission (B-CVT) for a small marine hydrokinetic (MHK) turbine deployed from a floating unmanned autonomous mobile catamaran platform is described. The turbine is a partially submerged multi-blade undershot waterwheel (USWW). A validated numerical torque model for the MHK turbine has been derived and a speed controller has been developed, implemented and tested in the field. The dependance of the power generated as a function of number and submergence level of turbine blades has been investigated and the number of blades that maximizes power production is determined. Bench and field testing in support of characterizing the power conversion capabilities of MHK turbine and PTO are described. Detailed results of the final torque and power coefficient models, the controls architecture, and the MHK turbine performance with varying numbers of blades are provided.

The purpose of this study is to look at the effects that industry concentration has on the growth of local areas. People will go where the jobs are so by evaluating employment data one can also evaluate the growth of an area. Common economic basis calculations and indices were used to provide useful information about characteristics of growth, competitiveness, and concentrations of local industries compared to the national level. The key results show the complex nature of urban and regional development exemplified by changes in employment and that access to more and complex data will be necessary to gain a greater understanding of urban growth.

The rise of Advanced Driver-Assistance Systems (ADAS) and Autonomous Vehicles (AVs) emphasizes the urgent need to combat distracted driving. This study introduces a fresh approach for improved detection of distracted drivers, combining a pre-trained Convolutional Neural Network (CNN) with a Bidirectional Long Short- Term Memory (BiLSTM) network. Our analysis utilizes both spatial and temporal features to examine a broad array of driver distractions. We demonstrate the advantage of this CNN-BiLSTM framework over conventional methods, achieving significant precision (up to 98.97%) on the combined ’Union Dataset,’ merging the Kaggle State Farm Dataset and AUC Distracted Driver Dataset (AUC-DDD). This research enhances safety in autonomous vehicles by providing a solid and flexible solution for everyday use. Our results mark considerable progress in accurately identifying driver distractions, pushing the boundaries of safety technology in AVs.

Gentrification describes rapid infrastructure development and investment in areas with lower income classes. It may cause potential erasure of the original neighborhood's unique culture and the displacement of residents. Due to rising sea levels and the increase in the frequency and intensity of storms, the inundation of Florida will increase as time passes. This creates an ironic relationship where historical coastal areas inhabited by an affluent population will move inland to historically lower-income populations. This thesis developed a Climate Gentrification Index (CGI) to identify areas at risk of gentrification caused by inundation of storm scenarios in Tampa City, Florida. Socioeconomic data and inundation data produced from a hydrological model were combined to define CGI and areas with high risk were mapped and discussed.