ScholarWorks@Georgia State University
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Publication Embargo Peripheral Taste Function Is Subject To Complex Modulation By Neuropeptide Y Family Peptides(2026-07-13)Neuropeptide Y (NPY) family peptides, such as NPY and peptide tyrosine-tyrosine (PYY), are well known to regulate feeding behavior via cognate receptors expressed throughout the gastrointestinal tract and central nervous system. Interestingly, both NPY family peptides and receptors are also expressed in taste bud cells (TBCs) of the peripheral gustatory system. These cells of the lingual epithelium are the primary sensory cells of the gustatory system responsible for the detection of sapid chemical stimuli (characterized as “sweet”, “sour”, “bitter”, etc.) strongly related to the consumption of foodstuffs. Previous studies have indicated that NPY family peptide signaling can impact upon taste-related behaviors in mice, possibly modulating taste responsiveness and food intake as a function of metabolic state. Yet, it remains unclear whether these impacts are specifically mediated by modulation of the response properties of TBCs or by the influence of NPY family peptide signaling on the functioning of other tissues. The experiments described in this dissertation interrogated the role of NPY family peptides in the modulation of stimulus-evoked taste responsiveness at the cellular and behavioral levels. The functional responsiveness of human and mouse TBCs to prototypical taste stimuli, in the presence and absence of NPY and PYY, was assessed in vitro using calcium imaging and neurotransmitter release measurements. Behavioral responsiveness was measured by brief-access taste testing in mice, with and without oral exposure to NPY and PYY. These studies revealed that both NPY and PYY can modulate cellular and behavioral responsiveness to prototypical taste stimuli. The nature of modulation depended on the peptide and taste quality assessed. Both NPY and PYY enhanced responsiveness to fatty acid stimuli while bitter responsiveness of human TBCs in vitro was suppressed by PYY but enhanced by NPY, though both peptides reduced bitter avoidance in mice. These data suggest that peripheral taste function can be differentially modulated by NPY family peptides. Given the importance of gustation to food choice and intake, the results detailed are consistent with the broader theory that peptidergic signaling in TBCs can shape gustatory sensory information to potentially modulate feeding behavior in different metabolic contexts.Publication Embargo Spatiotemporal Modeling of Brain Networks: A Framework for Capturing Development and Dysfunction(2026-7-13)The human brain is organized as a dynamic network system whose functional architecture changes across time, individuals, development, and disease. Although functional magnetic resonance imaging has enabled large-scale mapping of intrinsic brain networks, many existing approaches emphasize either temporal connectivity dynamics or static spatial organization, leaving important aspects of spatiotemporal network variability under-characterized. This dissertation develops and applies computational frameworks for modeling brain network dynamics across two complementary contexts: network dysfunction in schizophrenia and normative functional brain maturation during early infancy. First, this work examines dynamic default mode network chronnectomics in schizophrenia using an explainable feature-learning framework. Dynamic functional network connectivity states were identified across two independent schizophrenia cohorts, and state occupancy was used to characterize group differences and symptom associations. An iterative feature- importance procedure revealed reproducible default mode network edges contributing to dynamic state organization across datasets, with symptom-relevant effects concentrated in anterior–posterior default mode interactions. These findings support the view of schizophre- nia as a disorder of altered large-scale network dynamics and demonstrate the value of interpretable dynamic feature learning for linking network states to clinical phenotypes. Second, this dissertation characterizes early postnatal functional brain network develop- ment using longitudinal natural-sleep resting-state fMRI data acquired from neurotypical infants between birth and six months of age. Group ICA and individualized network esti- mation were used to identify reproducible infant functional networks, and multiple spatial metrics were developed to quantify network maturation. Initial analyses examined age- related changes in network-averaged spatial similarity, network engagement range, network strength, network size, and network center of mass, revealing network-specific patterns of spatial refinement, expansion, and reorganization. Subsequent nonlinear trajectory analyses showed that infant networks do not mature uniformly; instead, different systems exhibit dis- tinct developmental shapes, suggesting both coordinated maturation and network-specific differentiation during the first half-year of life. Finally, this dissertation introduces a multidimensional framework for infant brain net- work maturation by integrating five previously defined spatial metrics with two new mea- sures: fractal dimension, indexing network spatial complexity, and network center displace- ment, indexing deviation from group-level network location. Using age-specific normaliza- tion, generalized additive models, principal component analysis, inter-network coupling, and joint ICA, this framework maps both within-network maturation and system-level coordina- tion across 15 infant functional networks. Results show that infant functional brain devel- opment is characterized by multiple nonlinear modes of spatial maturation and coordinated coupling, rather than a single global developmental process. Together, these studies advance spatiotemporal modeling of functional brain networks by providing interpretable tools for quantifying dynamic dysfunction in schizophrenia and multidimensional maturation in infancy. This work contributes a unified perspective in which brain networks are understood not only by where they are located or how strongly they connect, but by how their spatial organization, temporal dynamics, and inter-network relationships evolve across development and disease.Publication Embargo Inequities In Violence Victimization Among Sexual and Gender Minorities: Examining Social Determinants of Health(2026-08-12)Objective: The objectives of this dissertation were to estimate the overall burden of suicides among Lesbian, Gay, Bisexual, Transgender, Queer/Questioning (LGBTQ+) individuals, including health disparities between LGBTQ+ and non-LGBTQ+ individuals. Methods: Quantitative surveillance data from 2015 to 2022 from the National Violent Death Reporting System (NVDRS) were analyzed. This analysis included victims aged 10 years and older who died by suicide between 2015-2022 in 50 states and Washington, D.C. Descriptive analyses were conducted for victim and incident characteristics and precipitating circumstances. Victim characteristics included age (years), sex and gender identity, race/ethnicity, education level, and relationship status; incident characteristics included the mechanism of injury and the location where the victim was injured. Precipitating circumstances were those that were thought to have contributed to the death. Additionally, county-level data from the County Health Rankings were merged with NVDRS to examine structural and community-level predictors of suicide risk. Bivariate logistic regression and multivariate Poisson regression were conducted to examine predictive associations between variables and LGBTQ+ status. Adjusted odds ratios (AOR), incidence rate ratios (IRR), and corresponding 95% confidence intervals were calculated. Results: Among 290,373 suicide victims from 2015-2022, 4,009 (1.4%) were identified as sexual or gender minority (SGM). LGBTQ+ individuals tended to be younger than non-LGBTQ+ individuals. Additionally, the most common method of injury of LGBTQ+ decedents was hanging, strangulation, or suffocation, followed by firearm vs. firearm, followed by hanging, strangulation, or suffocation in the comparison group. LGBTQ+ persons who died by suicide had significantly higher odds of almost all circumstances commonly contributing to suicide, including. current diagnosed mental health problem (AOR=2.02, 95% CI=1.90, 2.16), ever treated for mental health/substance use (AOR=1.89, 95% CI=1.78, 2.02), history of self-harm (AOR=2.44, 95% CI=2.11, 2.82), and school problem (AOR=2.13, 95% CI= 1.80, 2.52). Lastly, the incidence rate ratios were significantly different for structural and community-level predictors at the county level among LGBTQ+ suicide decedents. Conclusions: These findings suggest that individuals identifying as Sexual and Gender Minorities (SGM) are more prone to face multiple, intricate factors that lead to suicide. Consequently, suicide prevention strategies need to focus on identifying and mitigating the underlying circumstances that increase risk in SGM groups. Recognizing the structural and community hurdles linked to suicide among SGM persons should guide the creation of targeted interventions that address these specific issues. Additionally, support systems- covering mental health, substance use, and medical care- must be carefully designed to prevent reinforcing existing biases, which could unintentionally worsen the conditions that heighten suicide risk.Publication Embargo An Intelligent Web Platform For Officiating in Cricket Sport(2026-07-13)While international cricket uses elite technology like the Decision Review System (DRS), regional and grassroots leagues are forced to accept game-changing officiating errors with no way to challenge them. This research was born from the frustration of losing matches to decisions that could not be reviewed. To address this, we developed an intelligent, low-cost umpiring platform designed to run on consumer hardware. The system uses a multi-modal AI stack combining YOLOv8 for object detection and MediaPipe for pose estimation to turn raw match footage into objective rulings, complemented by a custom Digital Signal Processing pipeline built on librosa and scipy for acoustic edge detection. The platform renders pose landmarks and ball-trajectory overlays onto decision video, giving umpires a transparent, frame-accurate view of every call. Field trials conducted in North Georgia demonstrate that the platform can deliver structured, evidence-based officiating on consumer hardware, bringing DRS-style fairness to levels of the game that have historically gone without it.Publication Open Access A Polynomial-Time Algorithm for the Fractional f-Density(2026-08-06)This thesis studies the exact computation of fractional f-density in loopless multigraphs with positive rational edge weights. Fractional f-density is a weighted density parameter arising in f-edge coloring, where each color may be used at a vertex v up to a prescribed capacity f(v). It gives a structural lower bound for the f-chromatic index and generalizes the classical density parameter from ordinary edge-coloring theory. The method uses a linear-fractional optimization framework whose fixed-threshold subproblems are solved through minimum-cut and minimum T-cut computations on an auxiliary graph. The analysis supplies an explicit T-cut encoding of the f-parity condition, restores admissibility for relaxed cut solutions, and handles rational edge weights through denominator-clearing integral scaling. The main result gives an exact computation of fractional f-density with a denominator-aware polynomial-time bound in the graph-size and scaled-weight parameters, placing the computation on a rigorous algorithmic foundation.
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