The ‘91 Roos is a sports documentary focused in Killeen, Texas. exploring the 1991 Killeen Kangaroos high school football team and their journey to their city's one and only state championship in football. Killeen is a small central Texas town that is directly adjacent and provides support to Ft Hood, one of the world's largest military bases. With the Persian Gulf War raging in 1991, soldiers that lived in Killeen were being sent off to fight, leaving the city almost like a ghost town. In October 1991, the Luby's Massacre occurred in Killeen, bringing the already depleted city further down by tragedy. At the time, this was the worst mass shooting in US history. This high school football team went on a fairy tale type of run during their 1991 season, resulting in winning a state title and bringing big hope back to a small town in need. Using direct interviews, narration and archival footage, this film provides an emotional yet inspirational look at a small town football team and their improbable season.

Access Points explores the different relationships that humans have to land, focusing on the various ways that the area known as the Wichita Mountains Wildlife Refuge is used, appreciated, and preserved by disparate groups. The natural beauty of this Wildlife Refuge and its striking appearance amidst encircling plains makes it a popular destination for many groups of people, including the local rock-climbing community and generations of indigenous peoples whose connection with this land is as deep as it is longstanding. While climbing organizations have long had to negotiate access and rules regarding climbing within the park, members of the Kiowa community negotiate a much different relationship to a natural area that is now managed by the United States government. These disparate voices, identities, and ways of thinking about land all impact the modern-day Wildlife Refuge in terms of its appearance, individuals' access to the land, and the conservation efforts happening there.

Oil spills are well-known adverse anthropogenic events, as they can induce severe impacts on the environment and negative economic consequences. Still, much remains to be learned regarding the effects of crude oil exposure to aquatic organisms. The objectives of this dissertation were to fill some of those knowledge gaps by examining the effects of Deepwater Horizon (DWH) crude oil exposure on teleost kidney development and function. To this end, I analyzed how these effects translate into potential osmoregulatory impairments and investigated the interactive effects of ubiquitous natural factors, such as dissolved organic carbon (DOC) and ultraviolet (UV) light, on acute crude oil toxicity. Results demonstrated that acute early life stage (ELS) crude oil exposure induces developmental defects to the primordial kidney in teleost fish (i.e., the pronephros) as evident by alterations in: (1) transcriptional responses of key genes involved in pronephros development and function and (2) alterations in pronephros morphology. Crude oil-exposed zebrafish (Danio rerio) larvae presented defective pronephric function characterized by reduced renal clearance capacity and altered filtration selectivity, factors that likely contributed to the formation of edema. Latent osmoregulatory implications of crude oil exposure during ELS were observed in red drum (Sciaenops ocellatus) larvae, which manifested reduced survival …

Identity is a powerful concept that influences behavior and health. For over thirty years, researchers in sport psychology have been using the Athletic Identity Measurement Scale (AIMS) as a research instrument providing insights into the relationships between athletic identity and health variables. While musician identity is recognized as an important factor to be investigated in relation to occupational health, there are no known robust instruments like the AIMS in music psychology research. The current study aimed to adapt and validate the athletic identity measurement scale for use with musicians. The AIMS history includes episodes of modifications for performance enhancement of the instrument that resulted in five different models. The validation process includes evaluating the psychometrical properties across all five models. The sample included student musicians and non-student musicians (N = 1040). The traditional confirmatory factor analysis (CFA) and the maximum likelihood (ML) estimation method were used. The exploratory structural equation modeling (ESEM) and robust weighted least squares (WLS) was utilized to explore a new method of estimation that was known to resolve issues consistent with the CFA and ML method. The goodness-of-fit indices of CFA and ESEM were compared. The results showed that the MIMS is a reliable and valid …

This research expands the theoretical concept of human adjustment to floods established by Gilbert F. White and incorporates his adjustment concept to examine the range of adjustments in business operations adopted by Texas' natural and/or cultural resources sites during the first year of the COVID-19 pandemic. This mixed-methods study consisted of an online survey with a follow-up semi-structured phone interview. The survey data was analyzed using descriptive statistics and the interview data was inductively coded for thematic analysis as well as quantitative and qualitative content analyses. Specifically, this study identifies the adjustment measures undertaken by these entities to maintain business operations while reducing the virus spread; analyses the direct and indirect factors influencing adjustment measures; examines new business opportunities that emerged from these adjustments; and evaluates whether the impact of COVID-19 on these entities varied in terms of entity characteristics. Findings indicate that cultural and/or natural resource sites implemented adjustments to maintain their fiscal stability and/or to protect human health; these serve as direct underlying motivating factors for these entities. To support these direct measures, indirect factors influenced the operations thus required adjustments such as staffing, volunteers, technology, funding, and donations. Additionally, new opportunities in business practices emerged while implementing …

This dissertation is organized in a traditional format while including three essays that address specific research questions. Essay 1 examined the relationship between physical activity and community engagement and their effect on mental well-being among older men and women. Data from National Health and Aging Trends Study (NHATS) from 2018 to 2020 were explored and the posited relationships were tested. This essay provides empirical support that older adults who are reasonably active and involved in the community have greater mental well-being than those who isolate themselves. Essay 2 provides insight into older adults' motivation to improve their physical activity through the use of a fitness tracker. The key finding from this study is that wearables, especially fitness trackers, can significantly facilitate increased physical activity. Essay 3 is a mixed-methods study to understand older adults' perception of the usefulness of fitness trackers and interaction with such devices. Findings suggest that to increase the adoption of fitness trackers among older adults, makers could improve the esthetics and quality of the wristband in addition to the battery life of the tracker.

Networked multi-agent systems have attracted lots of researchers to develop algorithms, techniques, and applications.A multi-agent networked system consists of more than one subsystem (agent) to cooperately solve a global problem with only local computations and communications in a fully distributed manner. These networked systems have been investigated in various different areas including signal processing, control system, and machine learning. We can see massive applications using networked systems in reality, for example, persistent surveillance, healthcare, factory manufacturing, data mining, machine learning, power system, transportation system, and many other areas. Considering the nature of those mentioned applications, traditional centralized control and optimization algorithms which require both higher communication and computational capacities are not suitable. Additionally, compared to distributed control and optimization approaches, centralized control, and optimization algorithms cannot be scaled into systems with a large number of agents, or guarantee performance and security. All of the limitations of centralized control and optimization algorithms motivate us to investigate and develop new distributed control and optimization algorithms in networked systems. Moreover, convergence rate and analysis are crucial in control and optimization literature, which motivates us to investigate how to analyze and accerlate the convergence of distributed optimization algorithms.

Compressed sensing has been proposed as a computationally efficient method to estimate the finite-dimensional signals. The idea is to develop an undersampling operator that can sample the large but finite-dimensional sparse signals with a rate much below the required Nyquist rate. In other words, considering the sparsity level of the signal, the compressed sensing samples the signal with a rate proportional to the amount of information hidden in the signal. In this dissertation, first, we employ compressed sensing for physical layer signal processing of directional millimeter-wave communication. Second, we go through the theoretical aspect of compressed sensing by running a comprehensive theoretical analysis of compressed sensing to address two main unsolved problems, (1) continuous-extension compressed sensing in locally convex space and (2) computing the optimum subspace and its dimension using the idea of equivalent topologies using Köthe sequence. In the first part of this thesis, we employ compressed sensing to address various problems in directional millimeter-wave communication. In particular, we are focusing on stochastic characteristics of the underlying channel to characterize, detect, estimate, and track angular parameters of doubly directional millimeter-wave communication. For this purpose, we employ compressed sensing in combination with other stochastic methods such as Correlation Matrix Distance …

In the vast field of signal processing, machine learning is rapidly expanding its domain into all realms. As a constituent of this expansion, this thesis presents contributive work on advancements in machine learning algorithms by building on the shoulder of giants. The first chapter of this thesis contains enhancements to a CNN (convolutional neural network) for better classification of heartbeat arrhythmia. The network goes through a two stage development, the first being augmentations to the network and the second being the implementation of dropout. Chapter 2 involves the combination of CNN and LSTM (long short term memory) networks for the task of short-term energy use data regression. Exploiting the benefits of two of the most powerful neural networks, a unique, novel neural network is created to effectually predict future energy use. The final section concludes this work with directions for future works.

The purpose of this phenomenological study was to explore how individuals from different multiracial/multiethnic groups experience and process the phenomenon of parental racial ethnic socialization (RES). Critical multiracial race theory, critical race theory, and bioecological systems theory offered a conceptual framework to how RES is often presented and processed. This study was guided by two research questions: (1) What are the experiences of RES among multiracial individuals? and (2) How do multiracial individuals process the parental racial ethnic socialization they were offered? Nine qualitative, one-on-one, semistructured interviews were conducted with individuals from three different multiracial/multiethnic groups. Results revealed that experiences of RES varied along with how participants processed RES. Three subthemes and one theme emerged related to the RES experiences of participants. For some participants lack of conversations were evident in their RES, which meant that conversations surrounding multiraciality and other racialized topics were not present. Other participants disclosed the subtheme of preparedness as part of their RES experience, while others mentioned the importance of environment to their RES experience. Additionally, the theme of changes over time arose, demonstrating how different life events can impact RES experiences. As for how multiracial/multiethnic individuals process RES experiences, the main theme of identity …

Frédéric Chopin produced a remarkable body of piano works. Even though most of his works are essential repertoire in piano literature, some of them remain less familiar. One such significant work is the Allegro de Concert in A major, op. 46, which was apparently intended to be the first movement of a third piano concerto. Despite the praise the work has received, it is rarely heard, and references to performance are lacking in the scholarly literature. Some reasons include the substantial technical challenges, such as risky skips, trills in double notes, thick harmonic textures, complex passagework, and the perpetual motion. This study provides a performance guide for the Allegro de Concert, looking at various perspectives of an informed musical performance. The historical backstory of the intended third concerto and a detailed form analysis demonstrate that the work has a combined form, incorporating elements of both concerto and sonata-allegro form. The chapter on performance presents the technical issues and a comparative analysis of various editions and arrangements of this work to inspire musical ideas and suggest appropriate solutions to the musical and technical difficulties.

Recent epidemiological studies have demonstrated a correlation between the manifestation of non-alcoholic fatty liver disease (NAFLD) and ambient air pollution levels, which is exacerbated by the presence of other risk factors, such as diabetes, dyslipidemia, obesity, and hypertension. We investigated the hypothesis that exposure to a mixture of gasoline and diesel engine emissions (MVE) coupled with the concurrent consumption of a high-fat (HF) diet promotes the development of a NAFLD phenotype within the liver. Three-month-old male C57Bl/6 mice were placed on either a low fat or HF diet and exposed via whole-body inhalation to either filtered (FA) air or MVE (30 µg PM/m3 gasoline engine emissions + 70 µg PM/m3 diesel engine emissions) 6 hr/day for 30 days. Histology revealed mild microvesicular steatosis and hepatocyte hypertrophy in response to MVE exposure alone, compared to FA controls, yielding a classification of "borderline NASH" under the criteria of the modified NAFLD active score (NAS) system. As anticipated, animals on a HF diet exhibited moderate steatosis; however, we also observed inflammatory infiltrates, hepatocyte hypertrophy, and increased lipid accumulation, with the combined effect of HF diet and MVE exposure. Immunofluorescence staining and RT-qPCR of the liver revealed the presence of lipid peroxidation, altered expression …

My thesis is to understand the concept of compressive sensing algorithms. Compressive sensing will be a future alternate technique for the Nyquist rate, specific to some applications where sparsity property plays a major role. Software implementation of compressive sensing (CS) takes more time to reconstruct a signal from CS measurements, so we use the orthogonal matching pursuit and basis pursuit algorithms. We have used an image size of 256x256 is used for reconstruction and also implemented a field-programmable gate array (FPGA) of the orthogonal matching pursuit using an image.

As technology has advanced, data has become more and more important. The more breakthroughs are achieved, the more data is needed to support them. As a result, more storage is required in the system's memory. Compression is therefore required. Before it can be stored, the data must be compressed. To ensure that information is not lost, efficient compression is necessary. This also makes sure that there is no redundancy in the data that is being kept and stored. Compressive sensing has emerged as a new field of compression thanks to developments in sparse optimization. Rather than relying just on compression and sensing formulations, the theory blends the two. The objective of this thesis is to analyze the concept of compressive sensing and to study several reconstruction algorithms. Additionally, a few of the algorithms were put into practice. This thesis also included a model of the ECG, which is vital in determining the health of the heart. For the most part, the ECG is utilized to diagnose heart illness, and a modified synthetic ECG can be used to mimic some of these arrhythmias.

This thesis covers applications of machine learning to the fields of remote sensing and environmental monitoring. First, a generalized background on the concepts, tools, and methods used throughout the remainder of the research project are introduced. Chapter 3 covers the implementation of artificial neural networks to improve low-cost particulate matter sensing networks using collocated high-quality sensors with varying dataset parameters. In Chapter 4, an attention-enhanced LSTM-Convolutional neural network is presented to reconstruct satellite-based aerosol optical depth data lost to atmospheric interference. Chapter 5 applies attention mechanisms and convolutional neural networks to the reconstruction and upsampling of satellite-based land surface temperature maps. Chapter 6 presents a model employing geospatial techniques and machine learning methods with a combination of ground-based and remote sensing data to produce a daily ultra-high resolution 30 meter mapping of the PM2.5 concentration across Denton County, Texas.

I argue that Aristotle aids in understanding the tension between the political art and moral virtue through his examination of courage in The Nicomachean Ethics. The end of the political art is to habituate the city and citizens towards "the good." Aristotle examines five held opinions of non-courage, requiring that we reflect on our own vices. I describe how Aristotle prepares his readers for the task of examining the political art. I then view courage found in the citizen and spiritedness as an example of two common opinions where individuals are inclined towards pleasure, as opposed to being inclined to the noble. To conclude, I show that Aristotle provides opinions of non-courage to emphasize how institutions are, and must remain, a foundational part of society.

The dissertation covers three major topics: metal-assisted aromaticity, synthetic approaches to tailor donor-acceptor supramolecular stacks, and photoluminescence properties of cyclic trinuclear complexes (CTCs) of d10 metals. First, multiple theoretical approaches are adapted to discuss in detail the origin of aromaticity of CTCs, putting forward a metal-assisted aromaticity model. Next are the discoveries of donor-acceptor stacked CTC–CTC' complexes from both experimental and computational perspectives, reporting multiple novel crystallography-determined structures and revealing their pertinent intermolecular ground-state charge transfer. The spontaneous binding behavior is also determined by UV-vis and NMR titrations and rationalized as the cooperation of multiple supramolecular interactions, including metallophilicity, electrostatic attraction, and dispersion. The last part includes systematic investigations of photoluminescence properties of halogen-metal-bonded CTCs and sandwich-like cation–π-bonded heptanuclear clusters based on CTCs. The cooperative effects of metal-centered conformation, the heavy-atom and relativistic effects from both the halogen and metal atoms play complementary roles in the phosphorescence process to promote the inter-system crossing and radiative transitions.

The purpose of this research is to measure the social shifts that take place in a home where artificial intelligent (AI) devices like Echo Dot and Google Home are fully integrated into their everyday life. Research is currently limited, being that the widespread use of these devices is roughly seven years old. Three main outcomes of this study were related to how often Alexa is being used in homes to solve everyday problems, the lack of overall privacy and security concerns users had, and the level of integration into the home as a member of the family. Some limitations and challenges are my ability to compare the households before and after installing these devices in the home; pinpointing when and where the device is used (i.e., room placement); collecting data on whether the device is used often or sparingly; and the depth of interactions these families actually have with the device on a whole. The broader implications behind the increased integration of AI devices is centered around health, labor, social inequality and ethics.

Machine learning is fast growing field as it can be applied to solve a large amount of problems. One large subsection of machine learning are artificial neural networks (ANN), these work on pattern recognition and can be trained with data sets of known solutions. The objective of this thesis is to discuss the creation of an ANN capable of classifying differences in propylene glycol concentrations, up to 10%. Utilizing a micro pipette thermal sensor (MTS) it is possible to measure the heat propagation of a liquid from a laser pulse. The ANN can then be trained beforehand with simulated data and be tested in real time with temperature data from the MTS. This method could be applied to find the thermal conductivity of unknown fluids and biological samples, such as cells and tissues.

Work-based and employee-driven informal learning, training and development have been increasing in importance in the last few decades. Concurrently, organizations seek to measure the extent to which they develop a culture and structure that supports individual learning and organizational learning. This study develops and validates a scale that can measure the extent to which an organization is perceived to provide online learning that is personalized for its employees and perceived to recognize skills and competencies acquired through non-degree and other pathways. This research can provide organizations with the ability to measure and benchmark attributes of their learning culture that are important to work-based and lifelong learning as well as talent recruitment and management.

This study examined students' perception between short research experiences (SRE) courses and full-semester course research experiences (CRE) using the Persistence in the Sciences (PITS) survey and the interview questionnaire. The study also aimed to correlate the influence of student's demographic as a predictive indicator for Project Ownership Scores (POS) and Quantitative Literacy (QL) score means. The three courses studied at the University of North Texas were Biology for Science Majors Laboratory (BIOL 1760 SRE), Microbiology with Tiny Earth (BIOL 2042 Tiny Earth SRE), and Introductory Biology Research Laboratory I (BIOL 1750 SEA-PHAGES CRE). The mean scores for the PITS categories leaned favorably towards the research component of each laboratory course assessed in this study. The interview questionnaire showed 66% of the students in the SRE courses and 90% of the students in the CRE course preferred the research component of the lab. Paired survey demographic analysis for BIOL 1760 SRE showed significance for the Science Community Values with associate/bachelor's degree. BIOL 1750 SEA-PHAGES CRE showed significance in three of the six categories when comparing means for Project Ownership Emotion, Self-Efficacy, and Science Identity with Gender. Binary logistics was used to build a regression model to predict demographics with approximately 65% …

Team psychological safety fosters interpersonal risk-taking and constructive debate. Yet, how psychological safety develops in diverse teams needs to be explained. I apply collective regulatory lenses to shed light on how collective prevention focus (status quo) and collective promotion focus (growth) uniquely affect team psychological safety. I believe promotion focus makes it easier to attain psychological safety, while prevention focus makes it harder. Under a collective promotion lens, teams seek growth. Under a collective prevention lens, teams desire protection and not making things any worse. A pilot study of 76 students in 17 student project teams provided initial support for individual relationships in my model. In Study 2, an experiment, I manipulated team regulatory foci in three tasks (building towers, selling a house, negotiating a salary). I did not find significant mean group differences in psychological safety between promotion (n = 17) and prevention (n = 15) teams; yet, promotion teams experienced greater team viability in the final activity. In Study 3, I employed an experimental vignette method that suggested leadership conditions (e.g., leader humility vs transactional leadership) created differences in regulatory foci and subsequent differences in psychological safety with 343 working professionals in 7 scenarios.

The purpose of this study was to examine the intersection of preservice teachers' personal identities as queer individuals with their emerging professional identities as educators. Political and social environments contribute to a separation of these identities, which can further the marginalization of these individuals to the detriment of both their identities as people as well as their professional practice. Guided by a theoretical framework of figured worlds, interviews with students in teacher education programs that identify as queer explore the ways in which unique confluences of contextualizing factors play a role in the lived experiences of these individuals. The study additionally examined the nature of teacher education programs as experienced by these participants in order to discuss the ways in which these programs serve to challenge or reinforce the heteronormativity pervasive in educational spaces.

With the technological improvements, the number of Internet connected devices is increasing tremendously. We also observe an increase in cyberattacks since the attackers want to use all these interconnected devices for malicious intention. Even though there exist many proactive security solutions, it is not practical to run all the security solutions on them as they have limited computational resources and even battery operated. As an alternative, Zero Trust Architecture (ZTA) has become popular is because it defines boundaries and requires to monitor all events, configurations, and connections and evaluate them to enforce rejecting by default and accepting only if they are known and accepted as well as applies a continuous trust evaluation. In addition, we need to be able to respond as quickly as possible, which cannot be managed by human interaction but through autonomous computing paradigm. Therefore, in this work, we propose a framework that would implement ZTA using autonomous computing paradigm. The proposed solution, Autonomic ZTA Management Engine (AZME) framework, focusing on enforcing ZTA on network, uses a set of sensors to monitor a network, a set of user-defined policies to define which actions to be taken (through controller). We have implemented a Python prototype as a proof-of-concept …