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Many cardiac diseases are characterized by an increased late sodium current, including heart failure, hypertrophic cardiomyopathy, and inherited long QT syndrome type 3 (LQT3). The late sodium current in LQT3 is caused by a gain-of- function mutation in the voltage-gated sodium channel Nav1.5. Despite a well- defined genetic cause of LQT3, treatment remains inconsistent due to incomplete penetrance of the mutation and variability of anti-arrhythmic efficacy. Here, we investigate the relationship between LQT3-associated mutation incomplete penetrance and variability in ion channel expression, simulating a population of 1,000 “individuals” using the O’Hara-Rudy model of the human ventricular myocyte. We first simulate healthy electrical activity (i.e., in the absence of a mutation), then in- corporate heterozygous expression for three LQT3-associated mutations (Y1795C, I1768V, and ∆KPQ), to directly compare the effects of each mutation on individuals across a diverse population. For all mutations, we find that susceptibility, defined either by the presence of an early afterdepolarization (EAD) or prolonged action potential duration (APD), primarily depends on the balance between the conductance of IKr and INa, for which individuals with a higher IKr-INa ratio are less susceptible. Further, we find distinct differences across the population, observingiiindividuals susceptible to zero, one, two, or all three mutations. Individuals tend to be less susceptible with an appropriate balance of repolarizing currents, typically via increased IKs or IK1. Interestingly, the more critical repolarizing current is mutation-specific. We conclude that balance between key currents plays a significant role in mutant-specific presentation of the disease phenotype in LQT3.

Pore diffusion from a bulk sour gas phase to a bulk potassium carbonate liquid phase was modelled based solely on pore diffusion resistances. This modelling was done for ideal solutions at varying kinetic rates for the carbon dioxide-water reaction as well as various system parameters. The modelling was done utilizing Python and several pre-built libraries such as Scipy and Jax. The model was constructed starting from the original continuity equations combined with Fick’s Law, and numerically solving the resultant system of differential equations. Primarily, two different methods were required to assess systems with and without kinetic reaction-based diffusion resistances. Assuming infinitely fast reaction in all cases allowed the system to be integrated directly, while the system with kinetic resistances required a collocation algorithm to solve.

In the first chapter, I investigate the role of prefrontal cortex activity in working memory. Here, I am motivated by inconsistencies in the neural substrates for working memory across studies, species, and recording techniques. For instance, non-human primate electrophysiology research finds that prefrontal circuitry maintains working memory representations, while human neuroimaging suggests that working memory content is instead stored in sensory cortices. These seemingly incompatible accounts for working memory are often confounded by differences in the amount of task training and stimulus exposure across studies, suggesting that long-term learning may influence the role of prefrontal function in working memory maintenance. To answer these questions, we longitudinally trained and scanned participants on a working memory task with complex stimuli. Then, we used multivariate analyses of functional neuroimaging (fMRI) data to test how representational structures of working memory activity patterns in prefrontal cortex change across intensive learning. We show that human prefrontal cortex develops stimulus- selective working memory responses with learning, more akin to results from electrophysiology studies. This approach uses a unique training and analysis framework to establish novel evidence for long-term memory influences on working memory maintenance.In the second chapter, we investigate how working memory is constantly used to guide our moment to moment behaviors. This reliance on working memory can lead us to make mistakes, like saying aloud the wrong word in a conversation. Such “action slips” are common occurrences but especially pronounced in individuals with prefrontal lesions, who may often pour salt instead of sugar into one’s coffee, or mistakenly type “pizza” in an immediate texting conversation when thinking about your upcoming lunch (Lhermitte et al. 1986). To study this interaction between working memory and ongoing behavior, I implemented a dual-task experiment in which directional words must be held in working memory while more immediate, but unrelated, motor movements are performed. We show that motor behaviors unrelated to current working memory information are still influenced by one’s working memory content (Miller et al. 2020). We are currently testing these behaviors with predictions from cortico-striatal circuit models of working memory gating (e.g., O’Reilly and Frank, 2006) by using transcranial magnetic stimulation. By causally perturbing prefrontal functioning and cortico-striatal connectivity, can we alter when and how often working memory content influences our immediate actions?In the final chapter, I outline how investigating human-specific neuroanatomical structures in frontal cortex is critical for a wider investigation of human cognition. The prefrontal cortex is disproportionately expanded in the human brain even relative to other advanced primates, and some structures such as tertiary sulci, small folds in the cerebral cortex, are often human-specific. I use multi-modal neuroimaging data to investigate relationships between microstructural and functional properties in human prefrontal cortex. We show that careful identification of often overlooked individual-level anatomical features (such as tertiary sulci) serve as a bridge between the microanatomical and functional properties of prefrontal cortex (Miller et al. 2021). Identifying these structures has implications for both individual-level prefrontal functioning and broader mappings between prefrontal anatomy, functioning, and cognitive domains. We propose that such careful investigations of individual-level neuroanatomy will help to generate structural-functional relationships in areas of cortex previously thought to have little or no consistent links between individual-level structure and function (Miller et al. 2021).

Catalytic partial oxidation of organic molecules is critically enabling for production of commodity and specialty chemicals. Metal and metal-oxide surfaces can facilitate specified selective oxidation routes, but concurrent unselective reactions also occur. Minimizing the profusion of deleterious pathways through increasing selectivities of target oxidation products offers economic and environmental benefits. Although unselective oxidation of some molecules, such as ethylene, produces almost exclusively CO2, multiple organic byproducts of varying size (C1-C7+) are formed in appreciable quantities during oxidations of other molecules such as acrolein. Along with decreasing overall process yield, these byproducts lead in many cases to difficulties in downstream separation and processing of target oxidation products. This dissertation focuses on the identification of deleterious oxidation pathways responsible for the formation of undesired products during partial oxidation reactions through utilization of product stability analysis, co-feed reactions, isotopic labeling studies, and probe molecule co-feed reactions conducted in gas-phase batch and flow reactors. We present studies of oxidation pathways in two catalytic systems: acrolein oxidation to acrylic acid over a mixed-metal oxide (promoted MoVOx) catalyst and ethylene epoxidation over a supported metal (promoted Ag/α-Al2O3) catalyst. Results of acrolein oxidation reaction studies performed in a gradientless, recirculating batch reactor are rationalized by a mechanistic reaction network and a kinetic model rationalizing unselective C-C bond scission and formation pathways and show that reactions of both acrolein and acrylic acid generate byproducts. Batch and flow reactor studies of degradation of ethylene oxide show that catalyst metal and support surfaces contribute to its consumption.

While quantum computers can achieve dramatic speedups over the classical computers familiar to us, identifying the origin of this quantum advantage in physical systems remains a major goal of quantum information science. A useful tool here is measurement-based quantum computation (MQC), a computational framework utilizing the quantum entanglement found in many-body resource states. Not all resource states are useful for quantum computation however, so an important question is what properties of many-body entanglement characterize universal resource states, which can implement any quantum computation. Many-body states are also studied in condensed matter physics, where the collective behavior of quantum many-body systems sometimes define topological phases of matter. These phases are defined by nonlocal many-body entanglement, making topologically-ordered states natural candidates for MQC. We might wonder if these topological phases could be organized as phases of quantum computation, so that every state within the phase is universal for MQC. While phases of symmetry-protected topological order (SPTO) have arisen as natural candidates, previous attempts to demonstrate an MQC-SPTO correspondence were mostly limited to nonuniversal 1D spin chains, leaving the important 2D setting wide open. In this dissertation, we explore the wide and varied connections between MQC and SPTO, and obtain new results for 1D and 2D systems. After identifying a new MQC-SPTO correspondence within 1D spin chains, we move up and explore the operational use of 2D states with two complementary forms of SPTO. We create a new Union Jack resource state, whose different form of SPTO than previous 2D resource states permits a hierarchical notion of MQC universality. This state leads us to consider an idealized model of 2D SPTO, where we show that an additional symmetry condition makes these model states form universal resources for MQC only when they have nontrivial SPTO. We finally study the intrinsic complexity of SPTO-inspired states for classically intractable sampling, and identify inherent advantages of MQC for this purpose. Our work highlights the rich complexity available in states of entangled quantum matter, providing new evidence which sharpens our understanding of the diverse connections between MQC and SPTO.

The continued improvement of additive manufacturing (3D printing) is progressively eliminating the geometric limitations of traditional subtractive processes. Because parts are built up in thin layers, such as in processes like Laser Powder Bed Fusion, complex parts can be manufactured easily. However, this manufacturing method likely causes the parts to have rougher surfaces and decreased density compared to their traditional counterparts. The effect of this difference has not been researched thoroughly, but may have a significant impact on the properties of the parts. For example, the 3D printed parts could more easily collect micro-organisms that produce sulfuric acid as byproducts of their metabolic processes. Uninhibited microbial growth on the sample surface could produce enough sulfuric acid to degrade the parts through hydrogen embrittlement. This research contrasts the tensile stress and corrosion behavior of 316L stainless steel between traditional and additive manufactured parts based on exposure time to a 0.75 molar sulfuric acid solution, which mimics microbial metabolic byproducts.

This project introduces a flexible mathematical model used to represent problems of separating objects in space. Specifically, the notion of disentangling objects is formalized, and the definitions of this model are adapted from several used in the study of topology. Since spatial separation problems have been studied using computational models, methods were considered for translating problems from the mathematical model to that of computation. Upon acknowledging the assumptions made between the models, there is a review of computational complexity results for both determining the ability to disentangle objects and finding the fastest untangling motion.

Many of the lake-dwelling fish species of Lake Erie rely on shallow, heavily vegetated bays as spawning grounds to increase offspring probability of survival during early life stages. Multiple complex abiotic and biotic factors can affect mortality especially during early life stages; the loss or absence of suitable habitat is one of these key factors leading to poor recruitment of fish species. Submerged aquatic vegetation (SAV)/macrophyte beds in clearwater systems act as refuges for juvenile fish decreasing mortality from predation while foraging on prey resources. However, it also has been shown that river discharge “plumes” (areas of high turbidity) may act as habitat/refuge for young-of-the-year fishes. The Maumee River and Maumee Bay, once with abundant macrophyte beds, have experienced substantive increases in suspended solids over the last century. Historical introduction of benthivorous feeding carp (especially Cyprinus carpio), sediment pollution from surface runoff in the surrounding watershed and relatively high wave energy further increases the levels of turbidity in bays and decrease the amount of SAV habitat. The potential colonization of western Lake Erie by Grass Carp (Ctenopharyngodon idella) could further reduce the distribution of the SAV that may serve as a crucial habitat for economically and ecologically important Lake Erie fish species.I mapped the distribution of macrophytes in the northern section of Maumee Bay to quantify the utilization of SAV by juvenile fishes and the current distribution of SAV. In summer 2014 I used side scan sonar images processed in Quester Tangent™ computer programs in order to provide this baseline distribution. The 300-hectare mapped area was primarily inhabited by two SAV species, eel grass (Vallisneria americana) and variable pondweediv(Potamogeton gramineus), and this SAV was distributed over 43.7% of the area (131.2 hectares). The distribution of SAV seemed to be more related to the influx of sediments (increased turbidity) from the Ottawa and Maumee Rivers than depth, since the depth was fairly consistent throughout the surveyed area.Using an active capture gear (neuston net, 9.5 mm mesh), I sampled the communities of juvenile fish utilizing the open (turbid) and SAV habitat areas. The areas of SAV contained a greater species richness than the surrounding turbid habitat (averaging 8.6 species vs. 5 species), and was dominated by juvenile centrarchids including Largemouth Bass (Micropterus salmoides), Bluegill (Lepomis macrochirus) and Black Crappie (Pomoxis nigromaculatus) (3,334 individuals vs 99 individuals). The ecologically valuable fish species Western Banded Killifish (Fundulus diaphanus menona), Logperch (Percina caprodes) and Bluntnose Minnow (Pimephales notatus) serve as important food resource for larger piscivorous games fish species and preferred SAV habitat.This evidence suggests that SAV still serves as a crucial habitat for juvenile fish species even when the surrounding water column is turbid. SAV distributions should be preserved and enhanced in the western bays of Lake Erie to maintain/expand a crucial nursery habitat for economically and ecologically valuable fish species.

As part of its mission, the Department of Energy generates transuranic waste materials. Some of these wastes are present in large waste containers. The accurate assay of these waste materials in large containers poses unique challenges. These wastes have radioactive sources that are spread throughout the container with a variety of waste matrices that provide shielding. Although multiple well established and validated methods that use active and/or passive neutron detection in conjunction with gamma spectroscopy exist to assay these waste materials, these methods are expensive and not readily available at any given facility. As a result, less expensive alternatives, such as gamma spectroscopy alone, are often used. This paper researches the impact of a distributed shielding medium on a distributed transuranic source and the physical limitations of using gamma spectroscopy alone, without the benefit of either active or passive neutron counting. This included comparing the assay results from a gamma spectroscopy based system to one that uses passive neutron counting in addition to gamma spectroscopy. The differences between these systems were noted, and then evaluated through modeling using MCNPX to determine the cause of the observed discrepancies.