AUETD (Auburn University)
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Rapid and Reliable Quantitative MRI of Central Nervous System (CNS) at Ultra-High Field MRI (7T)
No full textQuantitative Magnetic Resonance Imaging (qMRI) surpasses traditional MRI, which primarily focuses on local image contrast. It reveals specific physical parameters related to the nuclear spin of protons in water and macromolecules. Parameters from qMRI, including longitudinal and transverse relaxation rates, magnetic susceptibility, proton density, and magnetization transfer, provide key insights into myelination, iron content, and cell membranes in the living central nervous system (CNS). qMRI has identified crucial, highly sensitive biomarkers in both health and disease, continually aiding longitudinal clinical trials as a non-invasive means to monitor changes in tissue. It offers insights into disease mechanisms that may precede visible changes in anatomical or structural images. Given the complementary nature of qMRI methods- such as T2* relaxometry, myelin imaging, magnetization transfer, and quantitative susceptibility mapping- to traditional contrast-weighted MRI, developing and implementing reliable acquisition and processing qMRI methods tailored to ultra-high field (7T) MR settings is vital for reliably assessing biophysical measures within a clinically feasible timeframe.
The specific goals of this work were: (i) to implement a protocol to accurately quantify T2*, QSM, qMT and MWF in-vivo at 7T ; (ii) to assess the reproducibility of the quantified values using scan-rescan experiments; (iii) to develop a robust technique for fast imaging of the human CNS; and (iv) to use the developed custom sequence to quantify myelin content with an increased acquisition speed by Compressed Sensing (CS). The primary aim of this work is to develop time-efficient, innovative, and non-invasive techniques capable of delivering quantitative insights into pathology, assisting in the monitoring of disease progression, and evaluating treatment effectiveness
Spatiotemporal Monitoring of Desertification of the Sahel Region Using Remote Sensing and GIS, Case Study of Sudan
No full textDesertification is a significant global environmental challenge, historically affected arid and semi-arid Sudan within the vulnerable Sahel region. Driven by climatic variability and human activities, prior research on Sudan had limitations regarding temporal/spatial coverage and integrated factor analysis. This study comprehensively analyzed the spatial distribution and extent of LULC in Sudan between 2003 and 2022, evaluated spatiotemporal variations in vegetation cover, and assessed the relationships between NDVI, climatic factors (precipitation, temperature), and population density. Utilizing readily available remote sensing data, the research employed MODIS (MOD13Q1, MCD12Q1), CHIRPS precipitation data, ERA5 Land Surface Temperature data, and WorldPop population density data. The findings of the study revealed a complex environmental narrative for Sudan, balancing persistent challenges with encouraging signs of vegetation growth. A notable shift toward increased vegetation cover was observed across significant portions of the country. The study also found rainfall to be a highly statistically significant positive predictor of vegetation health. While extreme maximum temperatures in the northern regions act as a dominant limiting factor for vegetation, high population densities, particularly around urban centers like Khartoum, were found to exert pressure on surrounding land resources. The findings of the study underscore the need for spatially differentiated and integrated land management strategies that leverage natural regeneration, implement smart water management, and address human pressures for sustainable development and resilience in the face of ongoing climate change
Conceptual and Modeling Approaches to Investigate Coastal Road Vulnerability to High Water Tables and Flooding
Full text linkLow-lying coastal areas face increasing risks from elevated groundwater levels and surface flooding due to sea-level rise (SLR), extreme precipitation, and storm surges. The objective of this research is to develop and apply a transferable framework to assess the vulnerability of coastal road infrastructure to shallow groundwater tables and flooding, using Alabama State Route 180 (AL-180) as a case study. The methodology integrates a data-driven empirical model and a physics-based distributed hydrologic model to evaluate sub-daily interactions between precipitation, tidal fluctuations, and groundwater dynamics. The empirical model estimates groundwater level (GWL) time series using simplified inputs such as rainfall, tidal elevation, surface elevation, and distance from tidal bodies. It was validated with field data from monitoring wells along AL-180. Performance metrics include Nash–Sutcliffe Efficiency (NSE) values of up to 0.73 and root mean squared errors (RMSE) as low as 0.06 m. This model was implemented along longer segments of the road using a Geographic Information System (GIS) platform at 100-meter intervals and used in conjunction with spatiotemporal analysis tools to detect long-term trends and identify vulnerable segments. Additionally, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model was calibrated and validated in a coastal setting to simulate surface and groundwater processes during moderate and extreme events. Results show that combined surface-subsurface interactions have a significant impact on flood extent and pavement saturation, particularly during extreme rainfall events. Together, the modeling approaches identified road segments with high saturation persistence, informing locations for infrastructure maintenance and adaptation. This framework supports transportation agencies in developing resilient road systems and can be applied to other coastal corridors with minimal data requirements
Students with Attention-Deficit/Hyperactivity Disorder Trusting Teachers
Full text linkThis qualitative narrative study explored how students diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD) experience trust in their relationships with teachers and how that trust influences their decision to graduate or drop out of high school. Guided by the theoretical framework of Hoy and Tschannen-Moran’s (2000) five dimensions of trust—benevolence, reliability, competence, honesty, and openness—the study sought to center student voices and lived experiences. Six participants, diagnosed with ADHD and either high school graduates or dropouts, shared their stories through in-depth interviews. Data were analyzed using Clandinin and Connelly’s (2000) three-dimensional space approach, a priori coding based on trust facets, and thematic analysis. Findings revealed that students who experienced positive, trusting relationships with teachers were more likely to complete high school, while those with predominantly negative experiences often disengaged and dropped out. Trust was built through teacher behaviors such as active listening, availability, care, respect, and high expectations. The study affirms the vital role of trust in student-teacher relationships, especially for students with ADHD, and calls for educators to intentionally foster emotional connection, consistency, and competence in order to support academic persistence
Auxiliary Robust Integral of the Sliding ModE (ARISE) Control Approaches for Rehabilitation of Neuromuscular Disorders
No full textIn the United States alone, tens of millions of individuals are affected by neurological conditions (NCs), including but not limited to stroke, Parkinson’s disease (PD), multiple sclerosis (MS), cerebral palsy (CP), and spinal cord injury (SCI). As the global population continues to age, the incidence of these conditions is rising, with millions of new cases reported worldwide each year. NCs often lead to various physical impairments such as muscle weakness, paralysis, and a loss of voluntary limb control. These limitations can also contribute to secondary health issues like obesity, diabetes, and cardiovascular disease, largely due to reduced physical activity. As a result, individuals with NCs face significant challenges while performing everyday tasks, and their associated healthcare costs in the U.S. alone exceed $150 billion annually. Thus, there is a need to improve the quality of life for those with NCs. Many potential solutions have been introduced, but each are limited in someway. For example, functional electrical stimulation (FES), which bypasses typical neurological processes to activate an individual's muscles to provide active therapy, is one of the more capable solutions, but it results in the patient becoming fatigued quicker than normal. The focus of this thesis is on the improvement of FES-based therapies. More precisely, this thesis develops a novel robust and adaptive control structure for a combined FES and robotic system called a hybrid exoskeleton. Specifically, for the first time, a recently developed ARISE control approach is modified for a hybrid exoskeleton. Furthermore, the control law is augmented with neural networks (NNs) that learn uncertainties in the dynamic model.
The first half of this thesis proposes and develops an ARISE controller for a general, uncertain, and switched Euler-Lagrange (EL) dynamic model, which could model an exoskeleton alone (i.e., without FES). To demonstrate the generality of the proposed approach, a switched and uncertain control effectiveness matrix was assumed. In this half of the thesis, a SM term is injected through a filtered auxiliary error signal into the closed-loop dynamics (i.e., an ARISE controller is developed). The control law is designed in a way such that it has an integral of the SM term in it, which will help in reducing the chattering effect that is prevalent in SM controllers. Furthermore, an adaptive update law is defined to address the unknown terms in the control effectiveness matrix. In addition, through a Lyapunov-like stability analysis, a semi-global result with exponential trajectory tracking towards an ultimate bound is achieved, provided that certain conditions on the gains and initial values are satisfied. Moreover, the performance of the proposed controller was evaluated and compared against a traditional SM controller through simulations in Matlab/Simulink. Due to limitations in the available experimental tools, physical experiments were conducted on a non-switched dynamic system; a lower-limb exoskeleton platform. The comparative results are presented through a series of graphical analyses. The findings indicate that the proposed ARISE controller outperforms the SM controller in managing a both a switched and a continuous dynamic system. This superior performance remains consistent across varying dynamic parameters and external disturbances.
In the second half of this thesis, the ARISE controller is developed for a hybrid-exoskeleton. Particularly, hybrid exoskeletons have both motor and FES inputs, requiring the design of multiple controllers, and the control effectiveness that maps stimulation to torque output is unknown and nonlinear. Consequently, this work approximates the uncertain FES control effectiveness using a NN, increasing the optimality of the FES control design and slowing the onset of fatigue. Furthermore, another NN is designed to approximate additional uncertainties in the dynamic model and ARISE is used to compensate for unstructured and time-varying disturbances, yielding an improved trajectory tracking performance. Additionally, a Lyapunov-based stability analysis was conducted to ensure the stability and safety of the proposed control framework, establishing semi-global exponential trajectory tracking convergence within an ultimate bound. To demonstrate the proposed approach, this work considered a leg extension exercise. Subsequently, experiments were carried out by augmenting the exoskeleton used in the first part of the study with FES. The experiments included a total of two healthy subjects to evaluate the proposed control system's potential for an enhanced rehabilitation performance
Unraveling Communication Dynamics of University Outreach
Full text linkThis qualitative investigation examines the communication dynamics of university outreach from the perspective of higher education administration, addressing the notable gap in how non-traditional scholarship and outreach activities are recognized and communicated within academic settings. Insufficient communication and recognition of diverse scholarly contributions can misalign academic output and impede institutional objectives, creating a discrepancy between institutions’ emphasis on societal benefits of outreach and its valuation for faculty tenure and promotion. Rooted in the American Public Land-Grant Universities’ call for supportive environments valuing publicly impactful work, this study analyzes the structure and channels used to describe and recognize university outreach, aiming to improve communication and acknowledge non-traditional scholarship.
Guided by the central question, “How does higher education administration describe university outreach?” the research employs a phenomenological approach to capture the lived experience of outreach messaging alongside Actor-Network Theory to analyze the intricate network of human and non-human actors influencing communication structure. Data from document analysis of land-grant institutions’ websites and supplemental interviews with executive leadership unraveled how mission, vision, and promotion themes define outreach through service, engagement, policies, and recognition mechanisms, primarily conveyed through institutional websites. Findings emphasize valuable insights for strategic management supporting clearer articulation of university outreach operations, ensuring alignment with the institutional mission and vision, and strengthening relationships with campus stakeholders and alternative forms of community engagement.
Experimental Characterization and Predictive Modeling of 100% Silicon Nanowire Anode Pouch Cells
No full textThe need for next-generation energy storage technologies has made silicon a leading prospect for next-generation anode materials in lithium-ion batteries, due to its theoretical capacity nearly ten times that of conventional graphite. However, the actual application of silicon has faced significant physical challenges, notably extreme mechanical degradation and rapid capacity fading due to the large volume expansion of silicon upon lithiation. This thesis discusses a comprehensive study and modeling of these behaviors in full pouch-type cells with 100\% silicon nanowire (SiNW) anodes.
To achieve this, a multiphysics framework was developed that combined rigorous experimental characterization with advanced computational modeling. A custom designed isothermal calorimeter allowed precise quantification of the electrochemical and thermal behavior of the cells in different C-rates (C/10, C/5, and C/3) and temperatures (10°C, 25°C, and 50°C). Simultaneously, a physics-based reduced order model (ROM) was developed to represent the coupled electrochemical, thermal, and mechanical behaviors.
The model was validated by comparison with the experimental results, showing accurate prediction of the cell voltage behavior and heat generation rate (HGR), with a root-mean-square error (RMSE) below 30 mV for all C-rates and temperatures considered. This work provides valuable insight into the performance of pure SiNW anodes in a full cell configuration, with a validated modeling framework that may enable the development of high-capacity lithium-ion batteries in future applications
International Diffusion of Privatized National Defense: A Comparative Analysis of the Privatization of War
No full textThis dissertation examines the rapid rise of the privatization of war phenomenon from 1998 to 2022, exploring why some states have adopted military privatization policies in the last 25 years while others have not. In other words, it assesses a state’s use or non-use of private military contractors. This study aims to address the gaps in the security privatization literature by developing a more generalizable theory for the global spread of military privatization policies since the start of the Global War on Terror. Using the diffusion of innovation theory—a novel framework—this research investigates whether this military innovation has spread to other states after exposure to U.S. military privatization practices in response to the terror attacks on 9/11.
Using data from 163 states, a logistic regression is employed to assess the effects of U.S. military exposure, terrorism threats, and privatization on a state’s decision to adopt or not adopt military privatization policies. Four paired case studies are then conducted to explore more deeply why states within the same region and those in different regions may choose to adopt or reject these policies. Overall, this study finds that a state’s decision is influenced by both U.S. military exposure (external diffusion) and terrorism threats (internal motivators), but not by prior acceptance of general privatization policies. Notably, three common patterns emerge: the prominence of a U.S. relationship, the severity of terror attacks combined with the effectiveness of state security forces, and the perceived operational effectiveness of private military contractors—all of which increase a state’s likelihood of adopting military privatization policies
Cultivated Meat in the Hospitality Industry: Perception and Adoption
No full textCultivated Meat in the Hospitality Industry: Perception and Adoption
Abstract
As global concerns around sustainability, food security, and ethical consumption intensify, cultivated meat (CM) has emerged as a promising alternative protein source. However, research on CM in the hospitality industry is still lacking. Therefore, this mixed-methods study aimed to fill this research gap by exploring perception towards CM and its potential adoption within the hospitality industry guided by the Stakeholder, Social Exchange, and Trust Theory.
The qualitative study (Study 1) involved semi-structured interviews with 14 hospitality professionals to explore hospitality stakeholders’ evaluations, perceptions, and barriers to adapting CM. The interviews were transcribed verbatim and coded to identify themes and subthemes. The qualitative findings indicated that hospitality professionals viewed CM as an emerging food innovation; They further identified sustainability and food security as key benefits of CM. However, concerns about high production costs, limited product access, and lack of sensory evaluation opportunities hindered immediate adoption.
The quantitative study (Study 2) examined how U.S. consumers’ trust in CM influenced their perceived sustainability and food security benefits, and various perceived risks of CM (i.e., health and safety, ethical, hedonic, financial, and sociopsychological), and purchase intention. An online survey was administered to 349 participants, and structural equation modeling (SEM) was used to test evaluate the proposed theoretical framework. The results showed that trust significantly influenced perceptions of benefits and risks but did not directly predict purchase intention. Instead, perceived sustainability benefits, perceived food security benefits, and perceived sociopsychological risks emerged as key mediators linking trust to purchase intention.
Overall, this mixed-methods study provided a comprehensive understanding of CM perceptions from both industry professionals and consumers. Findings suggest that chefs and hospitality professionals are pivotal in shaping public acceptance of CM by leveraging their influence to educate, communicate, and provide sensory and experiential evaluations despite fundamental concerns and uncertainties. At the same time, consumer data revealed that increased trust, especially when linked to clearly communicated sustainability and food security benefits, can positively shape perceptions and indirectly drive purchase intentions. These combined insights show that industry leadership and consumer trust are important for the future adoption of CM in the hospitality industry.
Keywords: cultivated meat, hospitality industry, perceived benefits, perceived risk, trust, mixed method
Enhancing utilization of warm-season forages for beef cattle systems in the southeastern United States
Full text linkIn the southeastern United States, grazing systems play a vital role in the nutrition and production of beef cattle. To further improve the efficiency and sustainability of these programs, it is essential to explore the potential of integrating novel forage species and management practices into conventionally managed systems. To achieve this goal, two studies were performed to explore the digestibility and nutritional value of different warm-season forages.
The first experiment evaluated the digestibility of mixtures of crabgrass (Digitaria sanguinalis [L.] Scop) and pearl millet (Pennisetum glaucum [L.] R. Br.) alone (G) or in a mixture with 30% forage soybeans (Glycine max [L.] Merr.) (G+L). Warm-season annual forages are highly digestible and commonly used to complement perennial grass pastures, providing cattle with high-quality nutrition during the summer months. Forage in vitro and in situ digestibility analyses were conducted using two ruminally cannulated steers from Auburn University’s Stanley P. Wilson Beef Teaching Center (Auburn, AL). Results indicated that in vitro true digestibility (IVTD) decreased as the season progressed, with G samples declining from 63.5% in June to 45.9% in September (P < 0.01). For G+L, there was also an effect of month (P = 0.01), with August and September being less digestible than June or July. For G, digestibility also differed across incubation times (P < 0.01), with digestion plateauing at 48 h. Results from the in situ study indicated the fractional rate of degradation (kd) for G+L was different among months (P = 0.04) in which June was greater than any other month. The potentially degradable fraction (D) was greatest (P < 0.01) in July for G, but there was no difference (P = 0.2) among months for G+L. For both G and G+L, the undegradable fraction (U) was increased with advancing forage maturity (P < 0.01). This study provides insights into the 2 digestibility and fiber degradation rate of warm-season annual forage mixtures including legumes.
The second study was an on-farm demonstration which examined stockpiled bahiagrass (Paspalum notatum Flüggé) at two Alabama locations (Montgomery County and St. Clair County) to assess forage production, nutritive value, and potential use of stockpiled bahiagrass to extend the grazing season during the fall forage production gap. In Year 1, fertilized pastures in St. Clair County produced, 994 kg DM/ha more biomass than unfertilized pastures in Montgomery, AL over a 30-day grazing period. Both locations had similar forage nutritive value, with Montgomery having 7.3% crude protein (CP) and 62.6% total digestible nutrients (TDN) and St. Clair having 6.9% CP and 62.7% TDN. The second year of the study had greater total forage production with a mean yield of 4,364 kg DM/ha across locations compared to Year 1 despite warmer and drier conditions. Forage concentration of neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), CP, and TDN were influenced by location, harvest date, and their interaction. Total digestible nutrients decreased with increasing forage maturity across harvest date (P < 0.01). At both sites, producers were able to provide an additional 30 to 40 days per year of grazing on their operation using stockpiled bahiagrass. Results from this study suggest stockpiling bahiagrass could help close the fall forage gap, but protein supplementation may be required to meet the nutritional needs of most beef cattle classes.
Overall, these findings highlight the potential of stockpiling bahiagrass and incorporating warm-season annuals into grazing systems to enhance year-round forage availability and better understand seasonal forage nutritive value characteristics for use in beef cattle operations