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Epilepsy is a multifaceted neurological disorder characterized by superfluous and recurrent seizure activity. Electroencephalogram (EEG) signals are indispensable tools for epilepsy diagnosis that reflect real-time insights of brain activity. Recently, epilepsy researchers have increasingly utilized Deep Learning (DL) architectures for early and timely diagnosis. This research focuses on resolving the challenges, such as data diversity, scarcity, limited labels, and privacy, by proposing potential contributions for epilepsy detection, prediction, and forecasting tasks without impacting the accuracy of the outcome. The proposed design of diversity-enhanced data augmentation initially averts data scarcity and inter-patient variability constraints for multiclass epilepsy detection. The potential features are extracted using a graph theory-based approach by analyzing the inherently dynamic characteristics of augmented EEG data. It utilizes a novel temporal weight fluctuation method to recognize the drastic temporal fluctuations and data patterns realized in EEG signals. Designing the Siamese neural network-based few-shot learning strategy offers a robust framework for multiclass epilepsy detection.

Deep learning strategies combined with wearable sensors have advanced the capabilities of monitoring systems in biomedical applications, offering precise and efficient solutions for diagnosing and managing diseases. However, applying these systems faces several challenges. One of the challenges is the diminishing performance when these systems encounter new data with more complex patterns than those seen before. Another challenge is the limited availability of labeled data, on which deep learning-based systems depend highly. Additionally, obtaining high-quality labeled data to train deep learning models is often expensive, requiring significant time and resources. Another significant challenge is ensuring the practicality, accessibility, and convenience of the monitoring systems.
This dissertation proposes an innovative deep learning framework to overcome these challenges and improve system generalization performance in classification and regression tasks, specifically monitoring patients with neurological disorders like Parkinson’s.

Anthropogenic impacts, including urbanization and development of the Greater Everglades ecosystem, have severely reduced and fragmented populations of Bletia purpurea. Differences across populations in Florida, such as habitat preferences, blooming periods, and self-fertilization abilities have been documented. Genetic data is becoming essential for developing effective conservation strategies to prevent the disappearance of threatened orchids from the wild. Using a target capture method with the Orchidaceae963 baitset, we assessed the genetic diversity of eight wild populations and five cultivated sources of B. purpurea. Our findings reveal two areas of concern; S1 which forms a distinct genetic cluster, and E3, where inbreeding rates are notably high. Additionally, three of the five cultivated sources showed significant differentiation from the wild populations, highlighting the need for more diverse maternal lines in cultivation efforts. These results emphasize the critical role of genetic assessments in informing conservation strategies for threatened orchid populations.

Emerging research in mammals supports relationships between an animal’s health, including the stress response and cognition, and its gut microbiome. Most of what is known about this “microbiota-gut-brain-HPA axis” stems from captive mammalian research, while these relationships are largely untested in wild, non-mammalian populations. To test this in avian taxa, I conducted a series of studies with captive Zebra Finches (Taeniopygia guttata) and a wild population of Northern Cardinals (Cardinalis cardinalis). First, I quantified performance by Zebra Finches on cognitive tasks measuring learning and memory for comparison to alpha and beta diversity of the gut microbiome sampled via cloacal swab. Performance on cognitive tasks related to beta diversity but not alpha diversity, providing some of the first evidence of an avian microbiota-gut-brain axis. Next, testing for relationships between host fitness and the microbiome, I sought baseline relationships between free-living cardinals’ microbiomes and their sexual ornamentation, stress response, and body condition index. Bacterial diversity related to individual variation in body condition and several sexual ornaments, but not glucocorticoid concentrations. Finally, in an empirical test that an acute stress response can cause microbiome dysbiosis, I captured wild cardinals to sample their gut microbiome, stress response, body condition, and beak ornamentation, then recaptured and resampled individuals after ~11 days. Between captures, I administered one of two challenges to each cardinal: a temporary hold of an additional hour in a cage post-capture, repeated simulated territorial intrusions (STIs), or no challenge (as a control). Challenge type had no effect on change in alpha diversity between sample timepoints, but it had a significant impact on microbiome dissimilarity assessed by beta diversity between timepoints. Overall, the birds that showed the largest beta diversity and greatest decrease in alpha diversity between samples experienced the greatest increase in CORT scope; there were mixed results supporting a link between a reduction in beak ornamentation and microbiome dysbiosis. This is some of the first evidence of a proximate effect of a fitness challenge on the microbiome of an adult free-living songbird, with concurrent data on shifts in glucocorticoids, body condition, and ornamentation.

The Cyber-Physical Systems (CPSs) and Internet of Things (IoT) have become emerging and essential technologies of the past few decades that connect various heterogeneous systems and devices. Sensors and actuators are fundamental units in most CPS and IoT systems, they are used extensively in vehicle systems, smart health care systems, smart buildings and cities, and many other types of applications. The extensive use of sensors and actuators, coupled with their increasing connectivity, exposes them to a wide range of threats. Given their integration into various systems and the use of multiple technologies, it is very useful to characterize their functions abstractly. For concreteness, we study them here in the context of autonomous cars. An autonomous car is an example of a CPS, which includes IoT applications. For instance, IoT units allow an autonomous car to be connected wirelessly to roadside units, other vehicles, and fog and cloud systems. Also, the IoT allows them to collect and share information on traffic, navigation, roads, and other aspects. An autonomous car is a complex system, not only due to its intricate design but also because it operates in a dynamic environment, interacting with other vehicles and the surrounding infrastructure. To manage these functions, it must integrate various technologies from different sources. Specifically, a diverse array of sensors and actuators is essential for the functionality of autonomous vehicles.

This thesis aims to answer questions about preconquest natives, defined by archaeologists as the Manteño culture (800-1533C.E.), in the cloud forests of Rio Blanco, Ecuador. Descriptions of the excavation units are made focusing on the architectural aspect of their dwelling. The cultural remains of the inhabitants also helped to conclude that this was a domestic house. Using an ethnoarchaeological theory base, modern home building analogies are employed to address questions about the archaeological process.

For nearly 60 years, politicians and policymakers have sought to improve the educational outcomes of students across their states and the country through legislated policies and programs. Despite their efforts, little progress has been made in improving the outcomes of the nation’s most vulnerable students. The achievement gap persists, and poverty divides the haves from the have-nots, especially in reading achievement.
This study was designed to explore the impact of increasing time allocated for reading instruction on student achievement in English Language Arts (ELA). Additional research questions were also included to determine if other factors impacted student achievement in ELA. The objective of this study was to determine if adding instructional time for any number of years improved student outcomes in reading.

This study addressed gaps in research on understanding the preparedness status of emergency management programs within Florida College System (FCS) and State University System (SUS) institutions. The quantitative assessment involved 21 institutions (51% response rate).
A survey instrument was developed from prior studies and measured programmatic factors. These questions explored the current preparedness level regarding emergency management programs within Florida’s FCS and SUS institutions, the involvement of stakeholders in these programs, the perceived preparedness to respond to various hazards, the extent of institutional investment in emergency management efforts, and the organizational frameworks characterizing the emergency management departments or units within these institutions.
Findings revealed that FCS institutions generally have needs, particularly in exercises and financial resources, suggesting foundational elements are present but highlighting opportunities to advance their preparedness. In contrast, SUS institutions report needs in planning and financial support, emphasizing the necessity of comprehensive and updated emergency strategies and plans and sufficient funding as programs advance. Both systems displayed strong leadership commitment that supported their levels of preparedness.

Analysis of fossilized Triceratops horridus remains within the Chicxulub Event Deposit of the uppermost Hell Creek Formation, and footprints of non-avian dinosaurs and flying reptiles from the excavated paleo surface underlying the Cretaceous-Tertiary (K/T) Boundary as marked by the Iridium anomaly, is used to interpret the very last moments of the terminal Cretaceous Period on the latest paleo surface available.
The research included characterization of the Triceratops’ bone histology and taphonomy, in addition to the preservation and diversity of the footprints. The data is used to interpret a “temporal snapshot” of the last days to weeks of the Late Cretaceous, offering insight to the site`s paleoenvironment immediately prior to the K/T impact event. Data from the Triceratops histological analysis indicates the animal died in the Spring, coinciding with the end of the Cretaceous. The tracks indicate a diverse non-avian dinosaur population composed of several families and breeding age individuals.

Fully electric vehicles (EVs) have gained significant popularity and countries such as Norway are leading the world with over 90% EV market share in new car sales. However, older internal combustion engine (ICE) powered vehicles currently on today’s roads are expected to continue to operate until the end of their life cycle. As a result, a mixed vehicle fleet is expected to persist in the coming decade. Unfortunately, there has been an underlying assumption that the traditional internal combustion vehicles are expected to exhibit the same driving behavior when electrified vehicles are introduced in the mixed traffic fleet. Unlike ICE powered vehicles, EVs deliver immediate and strong deceleration via regenerative braking, and this could cause disturbances when the less capable ICE vehicles are following. These differences in driving dynamics may translate to substantial impacts to roadway capacity, especially when mixed with human driven ICE powered vehicles. Although ACC equipped EVs can adopt shorter headways and react quickly to speed changes, potentially improving roadway capacity, our empirically validated simulation study on ACC with ICE and electric powertrain suggestion that the increase in market penetration of EVs could result in greater capacity but mostly at higher EV market penetrations, because EVs mostly interact with other EVs and there would not be many ICE vehicles following EVs undergoing rapid regenerative braking. Conversely, at low market penetrations, there are numerous ICE vehicles interacting with a few EVs that undergo rapid deceleration, causing disturbances and negating the potential capacity benefit of EVs.