Doctoral Dissertations

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  • Mechanism and Function of TrkB.T1 Astrocyte Expression
    Wei, Xiaoran (Virginia Tech, 2024-07-23)
    Astrocytes are the most abundant glial cell type in the central nervous system (CNS). Most astrocytes are born during the early postnatal period in the rodent brain and mature alongside neurons, demonstrating remarkable morphological structural complexity, and attaining maturity in the second postnatal month. We have shown that astrocyte morphogenesis is regulated in part by brain-derived neurotrophic factor (BDNF) via signaling through the truncated tropomyosin receptor kinase B (TrkB) receptor. TrkB is the primary receptor for BDNF which is broadly expressed and released by neurons in developing and mature brain. TrkB has two predominant isoforms expressed in central nervous system (CNS), the full length TrkB (TrkB.FL) receptor and truncated TrkB (TrkB.T1) receptor. We recently demonstrated in the adult rodent cortex that TrkB.T1 is largely specific to astrocytes and over 90% of all Ntrk2 expression in astrocytes attributed to TrkB.T1. In contrast TrkB.FL is the predominant isoform expressed by neurons. It is not known how astrocytes and neurons regulate their specific TrkB isoform expression, although previous studies in bulk frontal cortical tissue from human postmortem samples indicate that DNA methylation level in promoter region and 3' UTR region of NTRK2 is negatively correlated with TrkB.T1 expression levels, but not with TrkB.FL expression. The mechanism of TrkB.T1 isoform-specific expression and the role of TrkB.T1 in astrocyte developmental process are unknown. In this dissertation, we aimed to determine in the DNA methylation contributes to isoform specific expression of TrkB.T1. We thus profiled the 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in neurons, astrocytes and microglia utilizing nanopore sequencing. We identified robust differences in cell-type specific TrkB isoform expression is associated with significantly different 5mC and 5hmC patterns in neurons and astrocytes. Further, we investigated the role of TrkB.T1 in cortical astrocyte developmental processes and astrocyte function during early postnatal development (postnatal day (P) 8, P14, P28 and P60). RNA sequencing of TrkB.T1 deficient astrocytes isolated at these timepoints revealed aberrant gene expression in astrocyte maturation, while pathway analysis indicated disruptions in synapse organization, neurotransmitter transport and exocytotic processes. Subsequent functional secretory proteomics highlighted disruptions in metabolism and lipid regulation, particularly cholesterol transport, suggesting potential implications for synapse formation. We observed dysregulated spine density in the motor and somatosensory cortices from TrkB.T1-deficient astrocytes relative to control astrocytes. These findings suggest that TrkB.T1 deficiency adversely affects normal astrocyte development, which in turn affects neuronal synapse development. This study provides new insights into the role of BDNF/TrkB.T1 signaling in CNS development and lays the groundwork for evaluating astrocyte BDNF/TrkB.T1 signaling in neurological diseases.
  • Bridging Machine Learning and Experimental Design for Enhanced Data Analysis and Optimization
    Guo, Qing (Virginia Tech, 2024-07-19)
    Experimental design is a powerful tool for gathering highly informative observations using a small number of experiments. The demand for smart data collection strategies is increasing due to the need to save time and budget, especially in online experiments and machine learning. However, the traditional experimental design method falls short in systematically assessing changing variables' effects. Specifically within Artificial Intelligence (AI), the challenge lies in assessing the impacts of model structures and training strategies on task performances with a limited number of trials. This shortfall underscores the necessity for the development of novel approaches. On the other side, the optimal design criterion has typically been model-based in classic design literature, which leads to restricting the flexibility of experimental design strategies. However, machine learning's inherent flexibility can empower the estimation of metrics efficiently using nonparametric and optimization techniques, thereby broadening the horizons of experimental design possibilities. In this dissertation, the aim is to develop a set of novel methods to bridge the merits between these two domains: 1) applying ideas from statistical experimental design to enhance data efficiency in machine learning, and 2) leveraging powerful deep neural networks to optimize experimental design strategies. This dissertation consists of 5 chapters. Chapter 1 provides a general introduction to mutual information, fractional factorial design, hyper-parameter tuning, multi-modality, etc. In Chapter 2, I propose a new mutual information estimator FLO by integrating techniques from variational inference (VAE), contrastive learning, and convex optimization. I apply FLO to broad data science applications, such as efficient data collection, transfer learning, fair learning, etc. Chapter 3 introduces a new design strategy called multi-layer sliced design (MLSD) with the application of AI assurance. It focuses on exploring the effects of hyper-parameters under different models and optimization strategies. Chapter 4 investigates classic vision challenges via multimodal large language models by implicitly optimizing mutual information and thoroughly exploring training strategies. Chapter 5 concludes this proposal and discusses several future research topics.
  • Robust State Estimation, Uncertainty Quantification, and Uncertainty Reduction with Applications to Wind Estimation
    Gahan, Kenneth Christopher (Virginia Tech, 2024-07-17)
    Indirect wind estimation onboard unmanned aerial systems (UASs) can be accomplished using existing air vehicle sensors along with a dynamic model of the UAS augmented with additional wind-related states. It is often desired to extract a mean component of the wind the from frequency fluctuations (i.e. turbulence). Commonly, a variation of the KALMAN filter is used, with explicit or implicit assumptions about the nature of the random wind velocity. This dissertation presents an H-infinity (H∞) filtering approach to wind estimation which requires no assumptions about the statistics of the process or measurement noise. To specify the wind frequency content of interest a low-pass filter is incorporated. We develop the augmented UAS model in continuous-time, derive the H∞ filter, and introduce a KALMAN-BUCY filter for comparison. The filters are applied to data gathered during UAS flight tests and validated using a vaned air data unit onboard the aircraft. The H∞ filter provides quantitatively better estimates of the wind than the KALMAN-BUCY filter, with approximately 10-40% less root-mean-square (RMS) error in the majority of cases. It is also shown that incorporating DRYDEN turbulence does not improve the KALMAN-BUCY results. Additionally, this dissertation describes the theory and process for using generalized polynomial chaos (gPC) to re-cast the dynamics of a system with non-deterministic parameters as a deterministic system. The concepts are applied to the problem of wind estimation and characterizing the precision of wind estimates over time due to known parametric uncertainties. A novel truncation method, known as Sensitivity-Informed Variable Reduction (SIVR) was developed. In the multivariate case presented here, gPC and the SIVR-derived reduced gPC (gPCr) exhibit a computational advantage over Monte Carlo sampling-based methods for uncertainty quantification (UQ) and sensitivity analysis (SA), with time reductions of 38% and 98%, respectively. Lastly, while many estimation approaches achieve desirable accuracy under the assumption of known system parameters, reducing the effect of parametric uncertainty on wind estimate precision is desirable and has not been thoroughly investigated. This dissertation describes the theory and process for combining gPC and H-infinity (H∞) filtering. In the multivariate case presented, the gPC H∞ filter shows superiority over a nominal H∞ filter in terms of variance in estimates due to model parametric uncertainty. The error due to parametric uncertainty, as characterized by the variance in estimates from the mean, is reduced by as much as 63%.
  • Adaptive Predictive Controllers for Agile Quadrupedal Locomotion with Unknown Payloads
    Amanzadeh, Leila (Virginia Tech, 2024-07-12)
    Quadrupedal robots play a vital role in various applications, from search and rescue operations to exploration in challenging terrains. However, locomotion tasks involving unknown payload transportation on rough terrains pose significant challenges, requiring adaptive control strategies to ensure stability and performance. This dissertation contributes to the advancement of adaptive motion planning and control solutions that enable quadrupedal robots to traverse unknown rough environments while tasked with transporting unknown payloads. In the first project, a novel hierarchical planning and control framework for robust payload transportation by quadrupedal robots is developed. This framework integrates an adaptive model predictive control (AMPC) algorithm with a gradient-descent-based adaptive updating law applied to reduced-order locomotion (i.e., template) models. At the high level of the control hierarchy, an indirect adaptive law estimates unknown parameters of the reduced-order locomotion model under varying payloads, ensuring stability during trajectory planning. The optimal trajectories generated by the AMPC are then passed to a low-level and full-order nonlinear whole-body controller (WBC) for tracking. Extensive numerical investigations and hardware experiments on the A1 quadru[pedal robot validate the framework's capabilities, showcasing significant improvements in payload transportation on both flat and rough terrains compared to conventional MPC strategies. Specifically, the robot demonstrates proficiency in transporting unmodeled, unknown static payloads up to 109% of its own mass in experiments on flat terrains and 91% on rough experimental terrains. Moreover, the robot successfully manages dynamic payloads with 73% of its mass on rough terrains. Adaptive controllers must also address external disturbances inherent in real-world environments. Therefore, the second project introduces a hierarchical planning and control scheme with an adaptive L1 nonlinear model predictive control (ANMPC) at the high level, which integrates nonlinear MPC (NMPC) with an L1 adaptive controller. The prescribed optimal state and control input profiles generated by the ANMPC are then fed to the low-level nonlinear WBC. This approach aims to stabilize locomotion gaits in the presence of parametric uncertainties and external disturbances. The proposed controller is analyzed to accommodate uncertainties and external disturbances. Comprehensive numerical simulations and experimental validations on the A1 quadrupedal robot demonstrate its effectiveness on rough terrains. Numerical results suggest that ANMPC significantly improves the stability of the gaits in the presence of uncertainties and external disturbances compared to NMPC and AMPC. The robot can carry payloads up to 109% of its own mass on its trunk on flat and rough terrains. Simulation results show that the robot achieves a maximum payload capacity of 26.3 (kg), which is equivalent to 211% of its own mass on rough terrains with uncertainties and disturbances.
  • Tritium Matters: Constructing Nuclearity and Navigating Ambivalence of a Unique Material
    Loy, Taylor Andrew (Virginia Tech, 2024-07-10)
    This dissertation surveys the history of tritium beginning in Ernest Rutherford's lab in 1934 with its discovery and ending at the Fukushima Daiichi disaster site in 2023 when TEPCO began releasing tritiated wastewater into the Pacific ocean. In this time, expert conceptions of tritium have experienced interdependent and overlapping phases. Each phase is characterized by a dominant "nuclearity" and situated in context of "nuclear exceptionalism" (Hecht 2014) that directly and indirectly affects material conditions, elite decision-making, and radiological impacts on the environment and human health. Because it is pervasive, diffuse, and laborious to measure, a great deal of uncertainty surrounds tritium's contribution to radiological risks. Beyond various commercial and scientific uses, it is also integral to both nuclear energy as a waste and nuclear weapons as a mechanism for dramatically increasing explosive yields. This versatile and powerful material operates at the technological nexus of two existential risks for humanity: climate change and nuclear weapons. I divide the history of tritium into three distinct phases. First, super nuclearity characterizes early designs for the "superbomb" by Manhattan project scientists who believed vast amounts of tritium would be required. This phase extends to the late 1950s when thermonuclear warheads based on more feasible designs requiring significantly less tritium were beginning to be incorporated into the U.S. nuclear weapon stockpile. Second, special nuclearity describes the status of tritium throughout the Cold War as a critical nuclear weapons material that was referred to and treated as a special nuclear material (SNM) in practice even though it was never legally defined as such. Third, byproduct nuclearity is the current post-Cold War paradigm defining tritium as a form of incidental waste or as an innocuous "other accountable material" intentionally produced by the nuclear fission process. While tritium's super nuclearity proved to be an animating fiction with political and material impacts on the early U.S. post war nuclear weapons program, tritium's special and byproduct nuclearities have since been fully embodied in technological artifacts—primarily nuclear weapons and nuclear power plants—and remain in dynamic tension. Tritium does not fit neatly into existing nuclearity narratives. It is accurately referred to as both "highly" and "weakly" radioactive. Having a half-life of ~12 years and being the lightest radioisotope, it has high activity by weight, but when it decays into stable helium-3 it emits only a relatively weak beta particle which poses a potential risk as internal dose. I argue that the nuclearity processes constituting various conceptualizations of tritium provide insight into navigating the complex sociotechnical relationships between humans and nuclear technology. Additionally, I anticipate tritium's next nuclearity transformation as reactor fuel for a still nascent fusion power industry. I argue that rather than allowing fusion energy proponents to dictate the next phase of tritium's nuclearity, efforts should be made to assess and synthesize salient aspects of this unique material to provide a more holistic accounting of its risks, benefits, and tradeoffs.
  • The Impact of Three Dimensional Flow Anisotropy and Transients on Turbulence Ingestion Noise in Open Rotors
    Banks, Jarrod Thomas (Virginia Tech, 2024-06-27)
    The effect of flow anisotropy and three dimensional separation on the turbulent structure and radiated turbulence ingestion noise of a rotor in two experimental configurations is studied. The first consists of a non-axisymmetric boundary layer wake ingested by a rotor mounted at the aft of a body of revolution inclined at 5 degree angle of attack. In the second configuration a transient disturbance is generated by an upstream wing body junction pitching from zero to 20 degree angle of attack . This disturbance is convected downstream and ingested into a rotor immersed in a wall boundary layer. In both cases flow velocimetry at the rotor inflow is done and the far field sound is measured. The flow velocimetry in the wake of the inclined body of revolution shows evidence of three dimensional separation and vortex rollup between the lee and body sides. A boundary layer embedded shear layer develops as the turbulent kinetic energy is pulled off the wall by the flow separation and is visible in the port side velocimetry. The turbulent structure of this shear layer and the boundary layer on the lee of the body is visualized using compact eddy structure representation and the modes on the port side are shown to be stretched versions of similar modes seen in an equilibrium, zero pressure gradient boundary layer. The effect these structures had on the radiated sound served to both increase blade to blade correlation and the overall broadband levels of the sound. Measurements of the sound using an acoustic array showed directivity effects that resulted from the location of the embedded shear layer and rollup vortices. Although the vortices likely have some effect on the spectra, most of the noise is dominated by the turbulence ingestion of the embedded shear layer. For the second experimental configuration the transient motion was documented through repeated measurements of the flow field and sound, and an ensemble average of the measurements taken. Overall the flow was unsteady, particularly in the outer region of the boundary layer. The sound radiated was shown to be tonal during the first half of the interaction, where the flow is dominated by a deterministic mean flow change, and attributed to a form of periodic unsteady loading. During the latter half of the disturbance the broadband and overall sound levels increased significantly and are associated with the interaction of the rotor with flow separation over the wing body junction when it reached a critical, 16 degree angle of attack.
  • Is Corporate Taxation Bad for the Environment? An Empirical Analysis of the Association between State-Level Taxation and Corporate Environmental Performance
    Meersman, James Elliot (Virginia Tech, 2024-07-09)
    I investigate the impact of statutory tax rates on U.S. firms' environmental performance. Prior literature emphasizes the effect of manager influence on the relation between tax avoidance and environmental activities. However, it is unclear how taxes imposed on a firm impact environmental performance. Firms subject to higher statutory tax rates experience more restricted cash flows. As such, higher statutory tax rates may limit managers' ability to address environmental concerns. Firms that experience higher statutory tax rates may not prioritize environmental efforts, which are often non-essential to a firm's operations, despite government incentives. Alternatively, higher tax rates may encourage firms to address environmental concerns due to the tax shield that these expenses provide and the relatively lower cost to shareholders. Observing tax rate variation at the state level, I find higher state tax rates are associated with weaker environmental performance. My study contributes to regulators' understanding of the interaction between tax policy and firms' abilities to address their environmental impact.
  • Computational Methods for Optimizing Rotating Detonation Combustor (RDC) to Integrate with Gas Turbine
    Raj, Piyush (Virginia Tech, 2024-07-05)
    Pressure Gain Combustion (PGC) systems have gained significant focus in recent years due to its potential for increased thermodynamic efficiency over a constant pressure cycle (or Brayton cycle). A rotating detonation combustor (RDC) is a type of PGC system, which is thermodynamically more efficient than the conventional gas turbine combustor. One of the main aspects of the detonation process is the rapid burning of the fuel-oxidizer mixture, due to which there is not enough time for the pressure to equilibrate. Therefore, the process is thermodynamically closer to a constant volume process, which is thermodynamically more efficient than a constant pressure cycle. RDC, if integrated successfully with a turbine, can increase thermal efficiency and reduce carbon emissions, especially when hydrogen is introduced into the fuel stream. However, due to highly unsteady flow generated from RDC, a systematic approach to transition the flow exiting the RDC to supply steady, subsonic flow at the turbine inlet has not been developed so far. Numerical simulations serve as a valuable tool to provide insight into the flow physics and to optimize the RDE design. Numerical studies have explored RDC by utilizing high-fidelity 3D simulations. However, these CFD studies require significant computational resources, due to the large differences in length and time scales between the flow field and the chemical reactions involved. The motivation of this dissertation is to investigate these research gaps and to develop computationally efficient methods for RDC designs to be integrated with downstream turbine section. First, this research work develops a methodology to predict the unsteady flow field exiting an RDC using 2D reacting simulations and to validate the approach using experimental measurements. Next, computational techniques are applied to condition the flow within the annulus by strategically constricting the flow area. A design of experiment (DoE) study is used to optimize the area profiling of the combustor. Additionally, the performance of the profiled design is compared against the baseline and the conventional nozzle design used in the literature. However, these numerical works use a perfectly premixed condition, whereas, the actual setup consists of discrete fuel/oxidizer injectors providing a non-uniform mixture in the combustor. To eliminate the assumption of perfectly premixed conditions, a method is developed to model the dynamic injector response of fuel/oxidizer plenums. The goal of this approach is to provide an inhomogeneous mixture composition without having to resolve/mesh the individual injectors. This research work provides a robust and computationally efficient methods for minimizing unsteadiness, maximizing pressure gain, and modeling dynamic injector response of an RDC.
  • An Exploration of Nonlinear Locally Resonant Metamaterials with Electromechanical and Topological elements
    Malla, Arun Lee (Virginia Tech, 2024-07-02)
    In recent years, the study of metamaterials has been a subject of much interest, with acoustic metamaterials being applied to a wide range of applications. This utility is in part due to the incorporation of various elements in their design. The addition of local resonators provides greater versatility in controlling vibrations. Nonlinear elements introduce features such as discrete breathers and frequency shift. Electromechanical metamaterials have been established to have great potential for use in simultaneous energy harvesting in addition to vibration control. Furthermore, metamaterials with quasiperiodic patterning have been shown to possess useful properties such as edge-localized modes. However, no works investigate the interaction between all these elements, especially in the nonlinear regime. In this work, we investigate a unique metamaterial with local resonators, nonlinearity, electromechanical elements, and quasiperiodicity. The proposed metamaterial is examined using both analytical and numerical techniques in order to firmly establish the effects of each element. First, a nonlinear metamaterial with electromechanical local resonators is studied using the perturbation method of multiple scales, wavepacket excitation and direct integration, and specto-spatial processing techniques. The effect of the electromechanical local resonators is established for both the linear and nonlinear regimes, notably including the addition of new bandgaps and pass bands. The influence of electrical parameters on the system dynamics is explored through parametric analysis, demonstrating their use in tuning the system response. It is also shown that nonlinear phenomena such as localized solitons and frequency shift are present in the voltage response of the electromechanical metamaterial. Next, a nonlinear metamaterial with local resonators and quasiperiodicity is investigated using the method of multiple scales as well as numerical solution of the method of harmonic balance. Topological features stemming from quasiperiodicity are observed in the linear and nonlinear regimes. The presence of local resonators is shown to result in an additional, topologically trivial bandgap. The influence of quasiperiodic parameters and the source of quasiperiodicity on the system's band structure and mode shapes are established in both the linear and nonlinear regimes. Nonlinearity is also shown to affect topological features such as edge modes, resulting in amplitude dependence that can affect the localization of these modes in the nonlinear regime. Finally, a metamaterial with nonlinearity, electromechanical local resonators, and quasiperiodic patterning is modeled and investigated. Multiple configurations are examined, including different shunt circuits coupled to the electromechanical resonators and different sources of quasiperiodic patterning. It is shown that electromechanical local resonators produce two topologically trivial bandgaps, compared to the single trivial bandgap of the purely mechanical resonator. The influence of mechanical, electrical, and quasiperiodic parameters is explored to establish the effects of these parameters on bandgap formation in the linear regime. The behavior of the metamaterial in the nonlinear regime was found to be consistent with a purely mechanical system, with no adverse effects from the presence of electromechanical elements. The impact of nonlinear and quasiperiodic phenomena on energy harvesting is also investigated. Through exploration of this unique metamaterial, it is shown that beneficial features from all elements can be present at once, resulting in a versatile metamaterial with great potential for numerous applications.
  • Assessment of Cyber Vulnerabilities and Countermeasures for GPS-Time Synchronized Measurements in Smart Grids
    Khan, Imtiaj (Virginia Tech, 2024-07-02)
    We aim at expanding the horizon of existing research on cyberattacks against the time-syncrhonized devices such as PMUs and PDCs, along with corresponding countermeasures. We develop a PMU-PDC cybersecurity testbed at Virginia Tech Power and Energy Center (PEC) lab. The testbed is able to simulate real-world GPS-spoofing attack (GSA) and false data injection attack (FDIA) scenarios. Moreover, the testbed can incorporates cyberattack detection algorithm in pseudo real-time. After that, we propose three stealthy attack scenarios that exploit the vulnerabilities of time-synchronization for both PMU and PDC. The next part of this dissertation is the enhancement of Hankel-matrix based bad data detection model. The existing general Hankel-matrix based bad data detection model provide satisfactory performance. However, it fails in differentiating GPS-spoofing attack from FDIA. We propose an enhanced phase angle Hankel-matrix model that can conclusively identify GPS-spoofing attack. Furthermore, we reduce the computational burden for Hankel-matrix based bad data and cyberattack detection models. Finally, we verify the effectiveness of our enhanced Hankel-matrix model for proposed stealthy attack scenarios.
  • A study of the Rayleigh-Taylor Instability during deceleration in inertial confinement fusion relevant conditions
    Samulski, Camille Clement (Virginia Tech, 2024-07-01)
    The Rayleigh-Taylor instability (RTI) is one of the primary hydrodynamic instabilities that acts as a disputer to achieving high yield inertial confinement fusion (ICF). The potential for RTI to grow on the interior surface of ICF capsules, caused by deceleration during the implosion, further emphasises the need to better understand the seed mechanisms for RTI and possible mitigation methods for damping the instability growth. Reducing the growth of RTI during deceleration could preserve the spherical symmetry of ICF implosions and reduce the amount of mix between the solid capsule liner and fuel hot-spot. Additionally, it has been shown that magnetic fields do damp RTI growth, and the presence of a magnetic field lowers the threshold for achieving fusion and increases the yield. Understanding the seed mechanisms of the RTI, especially on the interior surface of ICF capsules, further allows for better understanding of the morphology of the RTI growth dur- ing deceleration. Classically RTI has been studied using single or multi-mode sinusoidal perturbations, which result in bubble and spike morphology. However in addition to si- nusoidal perturbations, single-feature perturbation, such as voids or divots, can seed RTI. This form of RTI is considered the thin-layer RTI, where the perturbation's wavelength is longer than the dense layer's thickness. This specific RTI evolution results in a morphology consisting of a single central spike and arms that extend horizontally away from the spike and eventually fall back towards the interface. Thin-layer RTI is important to explore dur- ing deceleration due to the presence of the fill-tubes in ICF capsules causing holes in the shell. Creating experimental platforms for current laser configurations on Omega and the Na- tional Ignition Facility (NIF) is necessary to study deceleration-stage RTI experimentally and validate computational modeling. A comprehensive exploration of potential experimen- tal designs on Omega, Omega-EP, and NIF are explored to identify a platform with which deceleration-stage RTI can be studied with and without the presence of an externally applied magnetic field. Additionally, the design of a novel experimental platform for Omega-EP to study thin-layer RTI during deceleration with and without an externally applied magnetic field is presented, along with data collected during the first experiments performed utilizing the platform. Lastly, a first of it's kind RTI platform for NIF is fielded and the results are presented, including an exploration of the possible impacts high-intensity-laser generated hot-electrons can have on experimental targets. The results of these experimental platforms are used to benchmark computational models, and demonstrate the potential for magnetized RTI to be studied comprehensively in future experiments.
  • Phosphate use for Sequestration, Anti-Scaling, and Corrosion Control: Critical Review, Simultaneous Optimization of Polyphosphate Dosing, Sequestration Mechanisms, and Stabilization of Magnesium Silicate Scale
    Lytle, Christian J. (Virginia Tech, 2024-07-01)
    Phosphates are used by drinking water utilities to 1) reduce iron/manganese aesthetic problems by sequestration, 2) inhibit calcium carbonate scale formation via threshold inhibition, and 3) reduce corrosion of pipes by forming protective pipe scales. Orthophosphates can control lead, copper and iron corrosion through the formation of durable, low solubility scale, but are widely believed ineffective for sequestration or anti-scaling. Conversely, polyphosphates are effective sequestrants and anti-scalants, but can increase corrosion of plumbing materials. Here, we first critically reviewed the current state of the science, operational guidance, and knowledge gaps related to use of orthophosphate and polyphosphates for all three objectives. Three major gaps in understanding were identified and then addressed in subsequent chapters: 1) use of phosphates to achieve both sequestration and anti-scaling 2) mechanisms of iron sequestration, and 3) stabilization of magnesium silicate scale linings in a distribution system. In the critical review, we holistically conceptualize phosphate use as a three-dimensional (3-D) challenge of optimizing sequestration, anti-scaling and corrosion control. Despite nearly a century of widespread use, there is a poor scientific and practical understanding of how to use phosphates to achieve each of these key objectives, much less achieve synergies and avoid antagonistic effects. Many water systems are reliant on trial-and-error methods, or guidance from vendors of these proprietary chemicals, creating potential inefficiencies or even adverse unintended consequences. Effective sequestration of iron and manganese, to prevent formation of visible discoloration, can occur through four possible mechanisms which are undoubtedly dependent on the water chemistry (e.g., pH, hardness, redox). Anti-scaling of calcium carbonate occurs through threshold inhibition and crystal distortion, but sometimes phosphates can encourage scaling due to the precipitation of calcium phosphate. Corrosion control via orthophosphate is often effective, but polyphosphates can sometimes increase lead or copper levels in drinking water. Despite their widespread use in scientific studies, it was discovered that standardized measurements of color and turbidity do not fully account for the range of subjective consumer observations regarding cloudy or discolored water. At a constant apparent color of 110 Pt-Co, testing illustrated that relatively non-offensive air bubbles had a high turbidity of 74 NTU compared to just 0.1 NTU for offensively orange fulvic acid. Additionally, factors such as background color, type of light source, and direction of light significantly influenced perception of discolored water. For instance, under typical laboratory lighting conditions (light from above) with a white background, colors caused by iron, manganese, and fulvic acid were very prominent, whereas white calcium carbonate and magnesium silicate particles were more challenging to see. But white particles became much more prominent when the light source was from below or there was a darker background. A study of Fe sequestration was conducted to elucidate a mechanistic basis for the empirical trends revealed in the utility field study. As revealed in the literature review, polyphosphates could sequester Fe by inhibiting any step of the reaction sequence Fe2+ oxidation  precipitation of Fe(OH)3  particle agglomeration to visible sizes. Phosphates generally inhibited Fe2+ oxidation above about pH 7-8, dependent on chain length, and catalyzed oxidation at lower pHs. But in oxygenated waters above about pH 7, the dominant mechanism of sequestration was some combination of Fe3+ complexation and colloid stabilization at small particle sizes that were practically invisible. Increasing the phosphate chain length, phosphate concentration, and Si concentration caused more effective Fe sequestration, whereas Ca, Mg, and increased pH hindered its effectiveness. It was also discovered that orthophosphate can be an effective sequestrant under ideal conditions, polyphosphate can sequester more than 1 mg/L Fe despite some claims to the contrary, and Ca at very high doses can precipitate polyphosphates. During this dissertation work, a novel, thick (~1 mm), glassy magnesium silicate (MgSi) scale was discovered covering much of the pipe surfaces in a large water distribution system. This MgSi lining was hypothesized to be an extremely effective means of corrosion control that was important to maintain in its present state, as dissolution could cause it to detach from pipes, whereas further precipitation could clog them. To better understand how to maintain the scale, factors affecting the formation and dissolution of the MgSi solid were examined. Phosphate corrosion inhibitors had little effect on MgSi solubility at pH 8.5 and 10, while hexametaphosphate (HMP) and zinc orthophosphate slightly reduced Mg and Si dissolution rates at pH 7. Zinc orthophosphate reduced Mg dissolution by 50% and completely inhibited Si dissolution from the solid, while HMP decreased dissolution of Mg by 32% and Si by 63%. The magnesium silicate did not precipitate below pH 10 without the presence of a pre-existing seed solid. With a pre-existing seed scale, however, the MgSi further precipitated at a pH 8.5-9 in one source water and 7.5-8 in another. Below these pH levels, scale dissolution was shown to occur. Strategies were evaluated to help identify the equilibration pH for operation of a system with varying concentrations of silica, magnesium and pH. The two-dimensional (2-D) interplay of polyphosphate use for sequestration and anti-scaling was investigated for nine small utilities who rely on groundwater in North Carolina. Bench-top testing methods were developed to determine the 'optimal phosphate doses,' defined here as the lowest level of polyphosphate that maintains visually clear water and acceptable levels of scale formation. One proprietary polyphosphate chemical had an optimal sequestrant dose that depends on the concentration of Fe, Mn, Ca, and Mg. The dose (in mg/L as P) is equal to 58.5[Fe] + 59.7[Mn] + 0.041[Ca + Mg] + 0.4669 (units mM). Interestingly, color was well correlated with particulate (> 0.45 μm) Mn (R2 = 0.79) while turbidity was mostly correlated with particulate iron (R2 = 0.60). Furthermore, neither color nor turbidity measurements were reliable predictors of discoloration detected by eye. In the three utilities with higher hardness (> 100 mg/L as CaCO3), at least 3.6X more phosphate was needed for Fe and Mn sequestration than scale inhibition. But lab testing in very hard water with 300 mg/L as CaCO3 demonstrated that achieving anti-scaling, will sometimes require more polyphosphate than that needed for control of sequestration. Overall, this dissertation advances understanding of phosphate use in relation to important problems arising in water distribution or buildings. The innovative practical testing methods, improved practical understanding, and mechanistic insights can be applied to maximized the benefits of phosphates use while avoiding detriments. This is an important first step towards developing a rational holistic framework to guide utility decision-making regarding phosphate use.
  • Teaching Robots using Interactive Imitation Learning
    Jonnavittula, Ananth (Virginia Tech, 2024-06-28)
    As robots transition from controlled environments, such as industrial settings, to more dynamic and unpredictable real-world applications, the need for adaptable and robust learning methods becomes paramount. In this dissertation we develop Interactive Imitation Learning (IIL) based methods that allow robots to learn from imperfect demonstrations. We achieve this by incorporating human factors such as the quality of their demonstrations and the level of effort they are willing to invest in teaching the robot. Our research is structured around three key contributions. First, we examine scenarios where robots have access to high-quality human demonstrations and abundant corrective feedback. In this setup, we introduce an algorithm called SARI (Shared Autonomy across Repeated Interactions), that leverages repeated human-robot interactions to learn from humans. Through extensive simulations and real-world experiments, we demonstrate that SARI significantly enhances the robot's ability to perform complex tasks by iteratively improving its understanding and responses based on human feedback. Second, we explore scenarios where human demonstrations are suboptimal and no additional corrective feedback is provided. This approach acknowledges the inherent imperfections in human teaching and aims to develop robots that can learn effectively under such conditions. We accomplish this by allowing the robot to adopt a risk-averse strategy that underestimates the human's abilities. This method is particularly valuable in household environments where users may not have the expertise or patience to provide perfect demonstrations. Finally, we address the challenge of learning from a single video demonstration. This is particularly relevant for enabling robots to learn tasks without extensive human involvement. We present VIEW (Visual Imitation lEarning with Waypoints), a method that focuses on extracting critical waypoints from video demonstrations. By identifying key positions and movements, VIEW allows robots to efficiently replicate tasks with minimal training data. Our experiments show that VIEW can significantly reduce both the number of trials required and the time needed for the robot to learn new tasks. The findings from this research highlight the importance of incorporating advanced learning algorithms and interactive methods to enhance the robot's ability to operate autonomously in diverse environments. By addressing the variability in human teaching and leveraging innovative learning strategies, this dissertation contributes to the development of more adaptable, efficient, and user-friendly robotic systems.
  • Host-pathogen interactions and conservation implications of snake fungal disease over broad geographical scales
    Blanvillain, Gaelle Jh (Virginia Tech, 2024-06-27)
    Emerging infectious diseases represent a threat to biodiversity, posing significant challenges to wildlife conservation globally. Infectious diseases can cause population declines, local extirpations and, in rare cases, complete species extinction. Among emerging pathogens, pathogenic fungi have been responsible for drastic declines in several high-profile vertebrate taxa, such as Batrachochytrium dendrobatidis causing chytridiomycosis in many species of amphibians worldwide. Recently, an emerging infectious disease, 'snake fungal disease' (SFD), caused by the fungal pathogen Ophidiomyces ophidiicola, is affecting the health of snake populations in North America by causing skin infections which can be fatal. Given the potential impact of this disease on snake biodiversity worldwide, compounded by the pressure of anthropogenic stressors that already jeopardize the viability of many snake populations, there is a clear need for ecological research in this understudied system. This dissertation is comprised of 4 data chapters focusing on the disease dynamics of snake fungal disease in Europe, and the factors resulting in differential infection. In chapter 2, I develop a large field-based data collection in 10 countries in Europe to investigate the presence of disease hotspots and the variation of disease prevalence across host species, and to examine the pathogen genotypes that are present on the landscape. I found isolated areas of disease hotspots, and models including an interactive effect of host species and which pathogen clade are present on the landscape were best at explaining disease prevalence. In chapter 3, I perform a virulence challenge assay using 120 corn snakes (Pantherophis guttatus) and 7 strains of O. ophidiicola (3 collected from Europe, 4 from the USA). This experiment reveals that pathogen genotypes associated with higher disease prevalence in Europe also have higher pathogen virulence, and that different strains from the USA show variation in virulence. These results also match both physiological host responses measured in the lab and landscape patterns of disease. In chapter 4, I explore two mitigation-driven snake translocation projects in Europe that were complicated due to O. ophidiicola outbreaks. One snake species, N. tessellata, appears highly susceptible to SFD, indicating that under stressful conditions, O. ophidiicola can cause mortality regardless of pathogen genotype, and that this snake species may be important in pathogen maintenance. Finally in chapter 5, I report the presence of a different fungal pathogen in Spain, Parannannizziopsis sp., never reported in wild snakes in Europe before. Broadly, my dissertation demonstrates coevolutionary relationships between hosts and pathogens and has important implications to snake conservation over large scales.
  • Perceptions of Technology/Engineering Education Influence on Integrated STEM Teaching and Learning
    Greene, Clark Wayland (Virginia Tech, 2024-06-27)
    The dynamics of successfully integrating science, technology/engineering and math content, practice, and delivery in K-12 education is still evolving. "A number of questions remain about the best methods by which to effectively teach engineering at the K-12 level and how they play into the integration of other STEM disciplines" (Moore, Glancy, Tank, Kersten, Smith, and Stohlmann, 2014). The International Technology and Engineering Educators Association (ITEEA) has declared that technology and engineering within STEM education as delivered by the technology education content area is defined by the Standards for Technological Literacy™ (ITEEA, 2000). Lack of applied technology/engineering pedagogical content knowledge via technology teacher collaboration may be excluding valuable contributions to more effective STEM teaching and learning. Absence of developed and identified perceptions resulting from such collaborations could be an impediment to application of valuable technology/engineering practices, beliefs, content, and structure within integrated STEM instruction. Collaboration inclusive of all STEM subject teachers is critical to effective practice and delivery of integrated STEM teaching. To achieve this, integrated STEM experiences need "to be researched and evaluated to build knowledge and understanding about the effectiveness of these experiences in promoting STEM learning and engagement within and across disciplines." (Honey et al., 2014). The purpose of this study was to examine and identify science, math, and technology education teacher perceptions of technology/engineering education influence within existing STEM collaborations. The objective was to provide useful information pertinent to further improving STEM education practice and effectiveness. A three round, mixed method, Delphi approach was employed to determine common perceptions among all STEM teachers included in this study. Consensus among study participants identified strategies specific to technology/engineering education that were perceived to positively impact STEM education. The results of this study illustrate that content, practice, and pedagogical attributes specific to technology education do exist and that those attributes are perceived to enhance student learning of STEM content and practice. Synthesized from initial qualitative responses in Round One, of the 28 presented technology/engineering strategies, 24 achieved consensus as determined by an applied two factor threshold of a 7.5 median agreement score and interquartile rating of 2.0 or less from among all participants. In a comparison of represented STEM subjects taught, there also appeared significant agreement among all groups. The level of agreement between science and the other groups was weakest, although still sizeable. Engineering design knowledge, skilled use of tools and materials to produce models and prototypes, promotion of designerly critical thinking and problem-solving skills, and both tacit and contextual knowledge of technology and engineering applications were found to be general themes specific to technology/engineering education teachers.
  • Effect of Interstitial Fluid Flow and Radiotherapy on Glioblastoma Invasiveness and Progression
    Atay, Naciye Nur (Virginia Tech, 2024-06-27)
    Glioblastoma (GBM) is the most aggressive and malignant glioma. It accounts for 48.6% of all primary, malignant gliomas with a median survival of 15 months. Infiltration into the surrounding parenchyma is a hallmark of GBM. Radiotherapy is used to address the invasion; however, recent studies have implicated that radiation contributes to increased invasiveness of glioma. Although the effect of radiation on cells has been studied extensively, its effect on the transport of fluid is not well characterized. Transport in the brain which has significant roles in physiology, GBM pathophysiology, and GBM treatment. Thus, understanding the effect of radiation on transport within the lesion and surrounding interstitium will be beneficial in characterizing the effects of radiotherapy in GBM patients. This dissertation seeks to explore the relationship between radiation, transport, and movement of glioma cells and includes the following: 1) Characterizing in vitro motility metrics of glioma stem cell lines in and relating them to in vivo invasion. 2) Studying the effect of radiation on motility, flow-mediated invasion, extracellular matrix components, and transport within the lesion and interstitium. 3) Assessing transport in clinical images and relating transport parameters to progression of GBM. 4) Developing a novel pipeline for applying vector field topology to the study of interstitial fluid flow in glioma. Surprisingly, we found that motility metrics in vitro have a negative correlation trend with in vivo invasion. Next, we found that radiation causes a transient increase in advective flow, and a more sustained decrease in diffusivity in a murine glioma model. Tenascin C was found to correlate significantly with invasion and diffusivity, indicating that it might be a link between radiation, transport, and invasion. Furthermore, interstitial fluid flow was calculated and assessed in clinical images. This showed that interstitial fluid flow velocity magnitude in the tumor correlates with overall survival in GBM patients. Lastly, vector field topology was introduced as a novel method of studying transport that provides more detailed information to identify potential drivers of transport within a flow field. Altogether, this work presents novel insight into the effects of radiation on invasion and transport in GBM. Hopefully, this work can provide a foundation to build upon in efforts of improving treatment planning and clinical outcomes for GBM patients.
  • Inhibition, Synapses, and Spike-Timing: Identification and disruption of pyramidal cell-interneuron interactions in SPW-Rs.
    Gilbert, Earl Thomas (Virginia Tech, 2024-06-25)
    The neural circuitry responsible for memory consists of complex components with dynamic interactions. In hippocampal area CA1, interactions between excitatory pyramidal cells and inhibitory interneurons shape ensemble activity which encodes sequential experience. An extremely diverse set of inhibitory interneurons, with variation in gene expression, synaptic targeting, state-dependent activity, and connectivity, contribute substantially to circuit activity, such as theta and sharp wave-ripple oscillations. The precise roles of each interneuron group is not well understood, though characterization of their activity reveals mechanisms underlying hippocampal circuit computation. In this dissertation, I aim to identify and disrupt interactions between pyramidal cells and local interneurons to clarify their role in shaping cell assembly activity. We characterized axo-axonic cell activity in sharp wave-ripples, and compared their control of pyramidal cell activity and ripple events to parvalbumin expressing neurons. We identified pyramidal cell-interneuron interactions during ripples, suggesting they serve as lateral inhibitors between cell assemblies. We additionally developed and implemented a novel neural device to explore the role of cannabinoid disruption of hippocampal oscillations and organization of assemblies in vivo in awake animals. We demonstrate that cannabinoid receptor type 1 within CA1 is responsible for suppression of theta and SPW-Rs. We also found that cannabinoid activation within CA1 circuitry, regardless of muted input from CA3, was sufficient to disrupt sharp wave-ripples, likely through interference of pyramidal cell-interneuron interactions. The work in this dissertation provides insight suggesting that interneuron activity must be studied at the spiking timescale to characterize their control over cell assembly activity.
  • Dynamics and Electrostatics of Membrane Proteins using Polarizable Molecular Dynamics Simulations
    Montgomery, Julia Mae (Virginia Tech, 2024-06-25)
    Membrane proteins are critical to many biological processes, including molecular transport, signal transduction, and cellular interactions. Through the use of molecular dynamics (MD) simulations, we are able to model this environment at an atomistic scale. However, traditionally used nonpolarizable force fields (FF) are thought to model the unique dielectric gradient posed by the lipid environment with a limited accuracy due to the mean field approximation of charge. Advancements in polarizable FFs and computing efficiency has enabled the explicit modeling of polarization responses and charge distribution, enabling a deeper understanding of the electrostatics driving these processes. Through the use of the Drude FF, we study three specific model systems to understand where explicit polarization is important in describing membranes and membrane proteins. These studies sought to answer the questions: (1) How does explicit electronic polarization impact small molecule permeation and localization preference?, (2) What electrostatic interactions underlie membrane protein secondary structure?, and (3) How do conformational changes propagate between microswitches in G-Protein Coupled Receptors? In this work, we show small molecule dipole moments changing as a function of localization in the bilayer. Additionally, we show differences in the free energy surfaces of permeation for aromatic, polar, and negatively charged species reliant upon force field used. For secondary structure, we showed key interactions which aided to stabilize model helices in bilayers. Finally, we showed potential inductive effects of key microswitch residues underlying prototypical G-Protein coupled receptor activation. This dissertation has helped to show the importance of including explicit polarization in membrane protein systems, especially when considering interactions at the interface and modeling species with charge. This work enables a refined view of the electrostatics occurring in membranes and membrane protein systems, and in the future, can be used as a basis for methodologies in computer aided drug design efforts.