Electronic Thesis or Dissertation

Unveiling the secrets of gravity necessitates numerical relativity simulations of gravitational systems, as observations made by gravitational wave detectors expect an interpretation. In the other hand, these numerical simulations require physical and constraint-satisfying initial data. Therefore, the accuracy of simulations go hand in hand with the accuracy of initial data. As such, constructing accurate initial data is an indispensable task and it is the very subject of this dissertation.
Here, we present the newly developed pseudospectral code Elliptica, an infrastructure for construction of initial data for various binary and single gravitational systems of all kinds. The elliptic equations under consideration are solved on a single spatial hypersurface of the spacetime manifold. Using coordinate maps, the hypersurface is covered by patches whose boundaries can adapt to the surface of the compact objects. To solve elliptic equations with arbitrary boundary condition, Elliptica deploys a Schur complement domain decomposition method with a direct solver. In this version, we use cubed sphere coordinate maps and the fields are expanded using Chebyshev polynomials of the first kind. Here, we explain the building blocks of Elliptica and the initial data construction algorithm for black hole-neutron star binary systems. We perform convergence tests and evolve the data to validate our results. Within our framework, the neutron star can reach spin values close to breakup with arbitrary direction, while the black hole can have arbitrary spin with dimensionless spin magnitude ~ 0.8.

Human exposure to arsenic from natural as well as anthropogenic sources can lead to a detrimental impact to the nervous system, cardiovascular system and can also cause cancer. Historical agricultural runoff has led to an accumulation of arsenic in groundwater and soils around Lake Okeechobee and many golf courses in Florida. This research involved studying the removal of aqueous arsenic via adsorption using activated carbon derived from algae. Carbon derived from Sargassum removed 41.47% of arsenic after a contact time of 2 hours. Adsorbents created from blue-green algae showed essentially no arsenic removal under the same conditions. Various chemical additives were tested to improve arsenic adsorption as well. Modification of the adsorbent surface with magnesium chloride demonstrated an arsenic removal efficiency of 98.6% when added to commercial activated carbon. However, when magnesium chloride was used to modify the surface of Sargassum-derived carbon adsorbents, the arsenic removal efficiency after 2 hours was 26.7%. It is recommended to investigate other surface modification agents that can potentially improve adsorption of arsenic.

This study examined whether accuracy of intraset RIR predictions changes over time. Nine resistance trained men completed three bench press training sessions per week for six weeks, with the last set of each session performed until muscular failure. During the set to failure, subjects verbally indicated when they perceived 4 repetitions in reserve (RIR) and 1 RIR during the set. For each RIR prediction, the difference between perceived RIR and actual RIR was calculated as RIRDIFF. We analyzed differences in RIRDIFF using both the raw RIRDIFF (including positive and negative values) and the absolute values of all RIRDIFF using a factorial MANOVA. Covariates included proximity to failure of the RIR prediction, total repetitions performed per set, percentage of one-repetition maximum lifted, the week of training, and the session (1, 2, or 3 within each seek). For the raw RIRDIFF all covariates, except for percentage of 1RM (p > 0.05) were significantly related to the outcome measure at both the predicted 4 and 1 RIR (p < 0.001 to p = 0.04). Specifically, RIRDIFF was significantly higher in weeks 1-4 versus weeks 5-6 (p < 0.001 to p = 0.005). However, the only covariate which significantly impacted the absolute value RIRDIFF at both the predicted 4 (p = 0.033) and 1 RIR (p = 0.022) was total repetitions per set. These results indicate that trained men tend to shift from overpredicting to underpredicting RIR over time and that more repetitions in a set is related to more inaccurate RIR predictions. However, the actual accuracy (i.e., absolute value RIRDIFF) did not significantly change over six weeks of training.

This thesis presents the development a sliding mode controller and vehicle allocation to control a surface vessel platform within a high degree of accuracy. This is part of ongoing development on the WAMV platform at Florida Atlantic University to improve autonomy in marine systems. By developing models for the untested thrusters currently used, the efficacy of a Sliding Mode Controller is evaluated, and a new control allocation developed based on the gradient descent optimization method is developed to manage the thrusters’ constrained angles of thrust generation. The official simulation for the WAMV platform was then modified to include these aspects and the system was tested under wind conditions and was successful in achieving control to waypoints. The gradient descent optimization used for the control allocation did manage to increase the accuracy of both heading and position of the system at convergence. The sliding mode controller navigated to the desired waypoint however maintained oscillations of cross track that were less then 2m and heading error less 20 degrees.

In 1967, Russell Hoban’s first novel, The Mouse and His Child was published and reviewed as a children’s book, despite the fact that the author considered it not to be directed towards a child audience. Since that time, it has been generally analyzed and evaluated as a work of children’s literature (specifically) and not as literature in the general sense. Because the book deals with adult subjects and concepts it has not fared well with those who have measured its success solely on the basis of its being classified as a children’s book. This thesis hopes to liberate the work from this classification by carefully analyzing the concepts which underpin its action, specifically its ontological speculations, its personification of the fall from grace and the felix culpa, the relationship of the protagonists to their complex antagonist Manny Rat, and, finally, in the symbol of “the last visible dog” which represents the infinite and what lies beyond the self (which, in fact, is actually the self). This thesis also examines how Hoban continued working with these themes and concepts in the novels he wrote after publishing The Mouse and His Child.

Financial time-series data are noisy, volatile, and nonlinear. The classic statistical linear models may not capture those underlying structures of the data. The rapid advancement in artificial intelligence and machine learning techniques, availability of large-scale data, and increased computational capabilities of a machine opens the door to developing sophisticated deep learning models to capture the nonlinearity and hidden information in the data. Creating a robust model by unlocking the power of a deep neural network and using real-time data is essential in this tech era. This study constructs a new computational framework to uncover the information in the financial time-series data and better inform the related parties. It carries out the comparative analysis of the performance of the deep learning models on stock price prediction with a well-balanced set of factors from fundamental data, macroeconomic data, and technical indicators responsible for stock price movement. We further build a novel computational framework through a merger of recurrent neural networks and random compression for the time-series analysis. The performance of the model is tested on a benchmark anomaly time-series dataset. This new computational framework in a compressed paradigm leads to improved computational efficiency and data privacy. Finally, this study develops a custom trading simulator and an agent-based hybrid model by combining gradient and gradient-free optimization methods. In particular, we explore the use of simulated annealing with stochastic gradient descent. The model trains a population of agents to predict appropriate trading behaviors such as buy, hold, or sell by optimizing the portfolio returns. Experimental results on S&P 500 index show that the proposed model outperforms the baseline models.

This study analyzed two different inlet management strategies being utilized in Palm Beach County and compared how the downdrift beaches were affected by those strategies throughout the year. Cross-sectional beach profiles, Digital Elevation Model comparisons, and subaerial volumetric change were analyzed for patterns in postplacement beach morphology. Trends in cross- and alongshore grainsize were also analyzed. In Boca Raton the inlet was dredged multiple times a month depending on the level of infilling and the material was placed on the beach immediately downdrift of the inlet. The downdrift beach of the Boca Raton inlet underwent a cycle of shoreline advance in the summer and shoreline retreat in the winter. It was dominated by seasonal processes and its morphologic change was the direct result of shifts in the wind and waves without having a beach more than 60 to 80 meters over the course of the study. In Jupiter, the inlet was dredged on a near annual basis and the material was placed 600m south of the inlet. The size and scope of the larger one-time annual nourishment project resulted in beach widths upwards of 120 meters. The equilibration process that followed in both the cross- and alongshore are what dominated the morphological trends experienced at the site. The results of this study should help coastal managers without current inlet management strategies, compare and overview two different successful inlet management options. For future studies, researchers should extend the monitoring period and extend profiles to the depth of closure to capture. Sediment is a valuable resource, and it’s important for best management practices to maximize benefits and protect downdrift beaches for long-term resiliency of coastal communities.

Research shows intrusions in memory tests can predict cognitive impairment in abnormal aging. However, there still is a need for additional research regarding the association of intrusions in verbal fluency tasks and clinical diagnosis of mild cognitive impairment, and dementia. The aim of my master’s thesis research is to determine if there is an association between intrusion totals in verbal fluency tasks and diagnosis, longitudinally (across 3 years), if there are significant differences between category and phonemic fluency tasks in intrusion total scores, and if progression from CN to MCI or dementia and from MCI to dementia can be indicated through differences in intrusion scores. Results indicated that intrusions are significantly associated with diagnosis in Phonemic fluency tasks, however this was not the case in progressors versus non-progressors.

This study examines how children learn emotional information and management from their primary caretakers during interactions with positive and negative narratives. Fifty-six preschoolers and their parents participated in a storytelling and discussion task, where each parent presented a happy and a sad story. Preschoolers were coded for their involvement, emotional comprehension, and concern, while parents were rated on their support, scaffolding, and expressiveness. Findings reveal that warm responsive and expressive parental behaviors contribute significantly to children’s cognitive and emotional skills during both positive and negative narrative interactions. Parents high in support and expressiveness (both during the task and within the home) had children who showed higher total expression, in addition to being more positively expressive, more involved, and more understanding of emotional concepts. These results reinforce previously established beliefs on the importance of emotionally open, positively expressive, and cognitively stimulating parent-child interactions on emotional, social, and regulatory competence.

Reverse mortgages are designed to allow house-rich but cash-poor homeowners the ability to tap the equity in their homes. This unique mortgage product has several features that distinguish it from a traditional mortgage, including that no principal or interest payments are made to the lender. Using 2018 - 2020 HMDA data, I test for disparate treatment in outcomes by race, ethnicity and gender. I test for redlining disparate outcomes using the census track minority population percentage as a proxy for neighborhood and test for loan pricing disparate outcomes using the interest rate charged. I test for origination disparate outcomes by comparing approval denial rates. My findings indicate (i) that lenders are more likely to reject applications from borrowers in census tracks with higher percentages of minorities, (ii) that lenders are more likely to reject applications from minority borrowers and (iii) that lenders charge higher interest rates to minority borrowers. I do not find that lenders charge higher interest rates in census tracks with higher percentages of minorities.