AUETD (Auburn University)
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Exploring Mechanomyography as a Tool for Fatigue Monitoring in Neurorehabilitation
No full textNeurological conditions such as stroke often result in motor impairments that limit functional independence and quality of life. Neurorehabilitation aims to restore motor function through intensive, repetitive therapy, relying increasingly on technologies that provide objective measures and therapeutic assistance. Among these, functional electrical stimulation (FES) is a widely used technique that activates paralyzed or weakened muscles to produce functional movements and promote recovery. However, a significant limitation of FES is the rapid onset of muscle fatigue, which shortens the duration of effective contractions, reducing the therapeutic benefits of treatment. Addressing this challenge requires reliable, real-time monitoring of fatigue to enable adaptive control of stimulation parameters.
This thesis investigates mechanomyography (MMG) as a robust, low-cost tool for detecting muscle fatigue during both static and dynamic tasks. Experimental studies showed that MMG features reflected fatigue development in static contractions and continued to perform
reliably during dynamic movements. A direct comparison between MMG and electromyography (EMG) revealed that MMG offers comparable sensitivity to fatigue-induced changes while avoiding several practical limitations inherent to EMG recordings. A fatigue-thresholding
method using MMG signal features was proposed for integration into real-time FES control systems, aiming to adjust stimulation parameters dynamically to prolong effective contractions. Overall, the findings highlight MMG’s potential to improve fatigue detection and support next generation neurorehabilitation technologies like adaptive FES
Remote sensing for adaptive management: Leveraging Landsat-based tools to support spatially explicit decision-making in Alabama’s Wildlife Management Areas
No full textAdaptive management emphasizes continuous improvement by learning from outcomes and adjusting strategies. It requires real-time data that static models cannot provide. To address this, we developed a land cover classification model using freely available data sources, multi-temporal Landsat imagery, digital elevation models, and field observations, combined using the Random Forest algorithm. We applied this model to lands managed by the Alabama Department of Conservation and Natural Resources (ADCNR) and classified landscapes into 11 management-relevant categories with ~89% accuracy. To support adaptive management, we turned this model into an interactive R Shiny web application, LANDCURATE. LANDCURATE allows users to upload a shapefile and receive land cover classifications for specified areas and years using our pre-trained model. This tool transforms complex workflows into an accessible, real-time decision-support platform, helping ADCNR overcome limitations of costly field surveys. LANDCURATE empowers land managers to track habitat changes and adapt strategies aligned with long-term conservation goals
Designing and Validating a Dual-Layer HCI Framework for OCD Mobile Training: Cognitive System Architecture and User-Centered UI with Emotional Ease
No full textObsessive-Compulsive Disorder (OCD) is a chronic psychological condition affecting approximately
1.2% of adults in the United States and 1%–2% of individuals worldwide. The urgency for scalable, self-
guided interventions has increased in the aftermath of the COVID-19 pandemic, especially for individuals
with mild OCD-like symptoms who lack access to formal clinical care.
This dissertation presents the design, implementation, and validation of HOOM, a mobile-based OCD
training system grounded in cognitive behavioral therapy principles (CBT) and informed by a dual-level
application of human-computer interaction principles (HCI). The system integrates (1) system-level usability
engineering, such as sequential module progression and real-time task logic, with (2) UI-level emotional
design strategies, including nature-inspired visuals, gamified badge feedback, and affective interface cues.
These complementary HCI strategies aim to support both functional usability and emotional user comfort
and engagement.
To evaluate this dual-layer design, the dissertation employs a threefold validation strategy: system-level
software testing confirmed efficiency, effectiveness,clarity, and accuracy of interaction logic; user-based UX
testing—including surveys and open-ended feedback—validated emotional comfort, task satisfaction, and
ease of use; and heuristic expert evaluation, based on Nielsen’s design principles (e.g., #4 Consistency and
#8 Aesthetic & Minimalist Design), assessed whether the UI design aligned with established aesthetic and
usability standards. Results demonstrate that well-established HCI principles, when applied at both system
and emotional levels, can yield measurable improvements in usability and user experience.
Overall, this work offers a validated, experience-centered design approach for mobile mental health
interventions and provides transferable insights for future cognitive support systems in digital therapeutics
Understanding the effects of volumetric defects on the uniaxial fatigue behavior of additively manufactured metallic materials
No full textVolumetric defects in additively manufactured parts cause significant fatigue scatter due to the variations in their size, shape, and location. This dissertation aimed to identify the morphological features of process-induced volumetric defects that most influence the fatigue behavior of laser powder bed fused (L-PBF) Ti-6Al-4V. Firstly, fatigue test specimens were machined from round bars fabricated using eight distinct process parameter sets and three build orientations to ensure a wide range of defect morphologies and populations. Uniaxial, constant amplitude, fully-reversed fatigue tests were conducted on these specimens. Fractography was performed to identify the defect responsible for the fatigue crack initiation and extract its morphological features. The influence of these features on fatigue behavior was examined by analyzing experimental data and finite element analysis results. While size was the most critical defect feature influencing fatigue behavior, it could not fully explain the variation in fatigue life by itself. For defects of similar size located at the same location, circular defects appeared to be more detrimental than irregularly shaped ones. A new defect size parameter, √area of the maximum inscribed circle, was introduced to account for both the size and shape of the volumetric defects, which exhibited an improved correlation with life compared to existing parameters. Fatigue cracks initiated from the surface and internal defects exhibited distinct crack growth behavior. Using the distinct material constants for surface and internal defects obtained from the Shiozawa plots, a novel fatigue life prediction model was proposed, which accounted for the distinct crack growth rates for surface and internal defects. Additionally, a probabilistic approach was utilized to determine the size of the largest possible defect for a given probability of failure. The fatigue design curve estimated with this defect size, using the proposed crack growth model, has been shown to be a more accurate estimate compared to the design curves developed using conventional approaches for fatigue qualification. Furthermore, the cross-platform transferability of the structure-property relationships, specifically defect-fatigue, was assessed for L-PBF Ti-6Al-4V. The transferability of defect-fatigue relationships established for the specimens fabricated on the EOS M290 platform was tested and validated with those fabricated on the Renishaw RenAM 500Q platform. Fatigue crack growth parameters derived from the EOS M290 specimens could be successfully applied to the fatigue life prediction of the RenAM 500Q specimens. The validity of fatigue design curves constructed using the short crack growth model with parameters from the EOS M290 platform was verified with data from the RenAM 500Q
Development of a Screening Platform and Systems Biology Tools for Enhancing Integrated Biogas Valorization and Wastewater Remediation
No full textAnaerobic digestion (AD) ranks among the top contributors to anthropogenic greenhouse gas (GHG) emissions in the United States. AD is a prevalent technology at wastewater treatment facilities (WWTF’s) that breaks down complex organic wastes into smaller substituents to recycle water from various waste streams. AD produces both biogas, consisting predominantly of methane and carbon dioxide, and a eutrophic liquid effluent. While some WWTF’s separate and harness the methane for the cogeneration of heat and electricity, all the carbon dioxide and produced GHG’s from burning the methane are vented to the atmosphere. In addition, the nitrogen- and phosphorous-containing ions (namely ammonium and orthophosphates) must be removed from liquid effluent before ejecting it from the WWTF. Recent studies have found that methanotroph-photoautotroph cocultures (MPCs) can serve as waste-to-value biocatalysts for the simultaneous treatment of the biogas and liquid effluents. The coculture can valorize the untreated biogas (both the methane and carbon dioxide) and liquid effluent by creating biomass for aquafeed and single-cell protein, as well as generate high titers of bioplastic precursors like formate and acetate. The MPC can also exhibit symbiotic interactions that not only increase the uptake rates of biogas and eutrophic ions but also increase the production of valuable biomass. Given the novelty of the coculture of dual biogas and wastewater remediation, much of the current literature focuses on utilizing methanotrophic communities with eukaryotic photoautotrophs or finding a single methanotrophic and photoautotrophic species that exhibits high growth rates to determine the efficacy of an MPC. However, there is very little research that screens individual pairs of methanotrophs and photoautotrophs to study metabolic cross-linking or to culture MPC’s directly into AD liquid effluent to validate their application potential.
This dissertation addresses these research gaps by developing two experimental reactor designs and one systems biology toolkit to more efficiently study methanotroph-photoautotroph cocultures for biogas and wastewater remediation. The first project involves screening neutrophilic methanotrophs, microalgae, and MPC’s on diluted mesophilic AD effluent from a WWTF and synthetic biogas to actualize their application potential. To do this, a screening station consisting of nine parallel fed-batch bioreactors was constructed that regulated six key abiotic growth factors, greatly decreasing the time needed for screening. In addition, a novel Gompertzian model was developed to assess the growth performance of each monoculture and MPC systematically and unbiasedly. Using the data collected from the screening experiments, the maximum growth rate, delay time, and biomass carrying capacity of each model was used to evaluate the performance of seven methanotrophs and five microalgae previously noted in literature for their potential for wastewater remediation. The top monocultures were combined into six MPC’s, and two MPC’s produced nearly double the stationary biomass titer of their respective monocultures. This elevated biomass, along with results from the modified Gompertz model, indicates the presence of symbiotic interactions within the MPC directly grown on waste products from a WWTF.
The second and third projects act serve as a platform to experimentally and computationally evaluate the synergism of Methylotuvimicrobium buryatense 5GB1 and Arthrospira platensis. Experimentally, due to the need for both shear-sensitive operations for A. platensis and high mass transfer rates for 5GB1, an airlift internal loop reactor was developed and implemented to culture both strains. Computationally, a systems biology toolkit was constructed to assist in analyzing GEMs for the coculture. The toolbox was used to evaluate two Clostridium tyrobutyricum models to demonstrate its capabilities
Volatile Organic Compounds as Biomarkers of Oxidative Stress in Childhood Obesity
No full textChildhood obesity is associated with increased oxidative stress and systemic inflammation, both of which contribute to the development of obesity-related comorbidities. Notably, obesity disproportionately affects certain racial and ethnic minority populations.
While excess body fat is known to drive these complications, abdominal and visceral fat contribute significantly by promoting the release of pro-oxidants, reactive oxygen species (ROS), and pro-inflammatory mediators. This oxidative stress (OS) disrupts the balance between free radical generation and antioxidant defenses, leading to damage at the molecular level, including protein oxidation, lipid peroxidation, and DNA damage. One consequence of these oxidative processes is the production and release of volatile organic compounds (VOCs), which are detectable in various biological matrices such as urine, breath, skin, and feces. This dissertation focuses on VOCs as biomarkers of oxidative stress in childhood obesity.
Through this research, we explored VOCs as noninvasive biomarkers of obesity and OS. In vitro models using differentiated 3T3-L1 adipocytes treated with hydrogen peroxide (H₂O₂) revealed that OS induced significant metabolic shifts and cell apoptosis, with altered VOC profiles. VOCs such as diphenyl ether, 1,3,5-trioxane, 5-methyl tridecane, 2-ethyl-1-hexanol, and 2,4-di-tert-butyl phenol were upregulated and identified as potential markers of oxidative damage.
Furthermore, human studies supported the clinical relevance of VOCs. In a cross-sectional study of 159 children (ages 6–10 years), urinary VOC profiling using solid-phase microextraction gas chromatography–mass spectrometry (SPME-GC-MS) identified sixty-five VOCs differentiating overweight/obese from normal-weight children, with ten VOCs remaining significant predictors of obesity after adjusting for racial and socioeconomic status disparities. Key VOCs such as benzaldehyde, hexanal, furan, 4-heptanone, and 2-pentylfuran emerged as potential biomarkers of obesity. Additionally, urinary 8-isoprostane was significantly elevated in OW/OB children of EA and AA ethnicity. Inflammatory markers AGP and IL-6 were elevated in OW/OB children, especially among AA participants. Multivariable regression showed positive associations of 2-pentylfuran and 4-heptanone with 8-OHdG, and a negative association of furan with 8-OHdG. This study indicated that urinary VOCs, particularly 2-pentylfuran and 4-heptanone, may serve as early non-invasive biomarkers of oxidative and inflammatory stress in childhood obesity.
In conclusion, these results suggest the potential of VOCs as early, noninvasive biomarkers for monitoring oxidative and inflammatory stress in childhood obesity. The differential expression patterns of VOCs and biomarkers across racial/ethnic subgroups further emphasize the importance of considering sociodemographic factors in obesity-related biomarker research. These findings show that urinary VOCs could play a crucial role in advancing our understanding of the pathogenesis of childhood obesity and its associated metabolic complications
A Petrographic and Geochemical Characterization of Magnetite Ore at the Island Queen Skarn, Puerto Rico
No full textSkarns classically form as the result of a multi-stage process including magmatic intrusion, alteration of carbonate-rich host rock, metasomatism, and later introduction of meteoric fluids. These processes transfer and concentrate metals like iron (Fe) into economic deposits. Puerto Rico serves as a natural laboratory to characterize mass transfer across Fe skarns. It is an extinct, unaccreted island arc and has a mining ban, leaving the outcrops available for study with minimal destruction. This research takes advantage of this opportunity to study Fe transport and deposition through fieldwork, petrography, and geochemical analyses of the Island Queen skarn.
At Island Queen, magnetite ore partially replaces limestone lenses hosted within volcaniclastics. Seventeen samples were analyzed including Fe oxide ore, limestone host rock with varying degrees of replacement, and weakly magnetic volcaniclastics. Petrography revealed predominantly magnetite, frequently with martite rims and evidence of dissolution-reprecipitation, and minor hematite, garnet, quartz, and chlorite. Elemental concentrations were measured in the ore, and electron images and X-ray maps revealed zoning in the magnetite that reflects changes in the ore-forming fluid. The Fe and oxygen (O) isotope compositions of the magnetite and host rocks indicate a dominant meteoric component in the fluid(s) that transported Fe and/or later altered the magnetite
An Approach for Designing a More Sustainable Toy Through Modularity and Multiple Functions
No full textMass-produced and manufactured plastic goods have contributed a significant amount to
the climate crisis. These goods provide little meaning to consumers who buy them as cheap
alternatives or quick solutions. Poorly made plastic toys with no playability beyond their often
licensed appearances contribute little to no purpose to a child’s development, usually ending their
life cycle in landfills once they are no longer relevant. As there are no clear guidelines for
creating a truly modular and adaptable toy system in pursuit of sustainability and playability,
toys must be able to adapt to children as they age to provide more value and to combat the
unnecessary discarding of goods. General principles of modularity, material reduction, and
product simplification can be utilized in conjunction with relevant guidelines to help create toys
for children’s development. To establish a set of rules for designing sustainable, modular toys, an
approach must include knowledge of how to manage resources effectively, how to encourage
creative play, and most importantly how to develop products that evolve with users
Assessment of Geochemical Reactivity of Potential Geological Formations Characterized by Diverse Lithologies
No full textGlobal warming is driven by greenhouse gases, which trap heat in the atmosphere through the greenhouse effect. According to recent projections, rising greenhouse gas levels may drive global temperatures above 1.5ºC as early as 2040. Excess atmospheric CO₂ is typically removed through the natural carbon cycle; however, this cycle is becoming insufficient due to the burning of fossil fuels and human activities. Geologic carbon sequestration, the process of injecting CO₂ into deep geological formations, is a promising technology to mitigate the adverse effects of greenhouse gases. Accurate predictions of subsurface interactions are essential for evaluating the effectiveness of this long-term storage strategy. Reactive transport modeling (RTM) is widely used to simulate geochemical reactions and transport phenomena in subsurface environments. These simulations incorporate formation mineralogy, kinetic data, mineral surface areas, and site-specific temperature and pressure conditions. Therefore, applying accurate and representative parameters is crucial to obtaining meaningful results.
This dissertation presents four studies that advance the understanding of carbon sequestration in diverse geological settings. The first three chapters use RTM to evaluate geochemical interactions between injected CO₂ and formations in the southeastern United States. In the Washita-Fredericksburg formation, simulations showed muscovite dissolution and minor kaolinite precipitation, with limited evidence of secondary mineral trapping. The second study, focused on the Conasauga Group in northwest Georgia, revealed significant calcite and dolomite dissolution and a corresponding increase in porosity. The third study investigated the role of mineralogical heterogeneity in the Tuscaloosa Group. Despite compositional variability, simulation trends were consistent, showing minimal porosity change and sustained acidity, indicating limited buffering capacity. The final chapter develops a microanalytical method using µXRD and µXRF data to improve mineral phase identification in mafic and ultramafic samples. This method enhances the reliability of mineralogical inputs essential for RTM. Together, these projects underscore the importance of detailed mineral characterization and accounting for geological variability to improve predictions of long-term CO₂ storage. Understanding site-specific geochemical reactions is crucial to preventing risks and ensuring permanent storage
Investigation of soy-based protein sources for largemouth bass (Micropterus nigricans) fingerlings on growth performance, health status, and disease susceptibility
No full textThe aquaculture industry faces many concerns as we push to increase production to meet human food demands. This has contributed to an exponential rise in price and demand for marine protein and oil sources. Formulated feed makes up a considerable cost for production. The industry must search for renewable protein sources to lessen the use of FM, which cannot be expanded. Soy ingredients are cheap, sustainable, readily available, and contain high levels of proteins and various amino acids. However, previous studies have shown species-dependent results when using soy proteins within diets as they contain antinutrients. In some species, it may inhibit growth, cause intestinal inflammation, alterations to the gut microflora, and increase disease susceptibility. Still, in others, it has shown promising results within a nutrient constraint. In a long-term study, largemouth bass (Micropterus nigricans) fingerlings were fed formulated diets replacing FM with soy-based protein sources such as conventional soybean meal (SBM), enzyme-treated SBM, and soy protein concentrate (SPC). Compared to a fishmeal-based diet, the largemouth bass displayed comparable growth performance with no overall health concerns when evaluating the blood chemistry and distal intestines via histology, gene expression, and gut microbiome. Likewise, this study reported that when infected with columnaris disease, differences in the survival curves were detected. In a short-term study, largemouth bass were fed formulated diets with a replacement of SBM with either an enzyme-treated SBM (ESBM) or a low-oligosaccharide SBM (LSBM) in varying amounts. This study revealed elevated growth in the largemouth bass fed the formulated diets with the inclusions of ESBM and LSBM compared to just the SBM-only diet. Furthermore, this study reported no health concerns nor signs of gut inflammation, even at higher inclusion rates. Thus, these studies provide crucial data to the industry, displaying that the inclusion of soy ingredients does show potential for largemouth bass culture, leading to a reduction in feed cost, maximizing production, and providing a sustainable outlet to reduce the usage of FM in formulated feed.