Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2022, College of Sciences and Health Professions

Poly-l-lactic acid has been of great interest to the medical profession in recent years because of its biodegradability and biocompatibility. The biodegradation rate can be controlled by its crystallinity content. One method to modify its crystallinity content is by cold drawing. Raman spectroscopy is utilized to distinguish between the different crystalline content on the sample. However, a chemical imaging method is needed to characterize the polymer on the macro level. Chemical imaging using Raman spectroscopy is an important method of characterization that is non-invasive and non-destructive. The emphasis of my research has been to develop a method to characterize the crystalline content of poly-l-lactic acid using Raman chemical imaging and multivariate analysis to construct a robust image of the crystalline map. No Technique exists for this purpose. Multivariate analysis has been beneficial for reducing the time spent on finding correlations in a vast amount of data. Principal component analysis has been one of the most common methods for reducing the data dimensions to those that are the most responsible for the observed variation in the data. However, the method is scale variant and blends qualitative and quantitative information in a way that can render misleading results. Classical least squares has also been used in chemical imaging, but it requires substantial training data. In this document, we introduce a modified version of reduction of spectral images (ROSI), a multivariate analysis method that heavily modifies principal component analysis to reduce the amount of data while still prioritizing the minority pixel population on the image data to retain more of the analytically meaningful characters of the data. Preprocessing of the data is an important step to obtaining robust results and can involve multiple steps depending on the application. It often serves as an essential step for removing irrelevant information from the raw data. One important pr (open full item for complete abstract)

Committee: John Turner II (Advisor); Warren Boyd (Committee Member); Baochuan Guo (Committee Member); Xue-Long Sun (Committee Member); Petru Fodor (Committee Member) Subjects: Biomedical Engineering; Chemistry; Materials Science; Plastics

Doctor of Philosophy, The Ohio State University, 2011, Astronomy

Cosmic rays (CRs) are high energy particles that are found wherever in the Universe star formation is occurring. I investigate several problems in the propagation of CRs in star-forming galaxies. By applying analytic models and numerically solving the “leaky box” differential equation, I calculate the population of primary and secondary CR protons, electrons and positrons in model star-forming galaxies and their nonthermal emission. Observations show that the synchrotron radio emission of star-forming galaxies grows linearly with the infrared emission from dust-obscured young stars; this is the FIR-radio correlation (FRC). To explain the correlation, I constructed one-zone models of galaxies over the dynamic range of the FRC. I found that the FRC is caused by conspiracies of several factors, including CR escape from galaxies, ultraviolet (UV) dust opacity, non-synchrotron cooling, and secondary electrons and positrons generated by CR protons. The conspiracies have great implications for the evolution of the FRC at high redshift, preserving it and allowing variations in the FIR-radio ratio for submillimeter galaxies. Recent gamma-ray observations of M82 and NGC 253 indicate that CR protons lose much of their energy to collisions in these galaxies' dense gas, where they generate unstable pions that decay into gamma rays and secondary particles. The ratio of gamma-ray to radio luminosity indicates that secondary electrons mostly do not cool by synchrotron emission, supporting a conspiracy origin of the FRC. I also compare the intensities of the diffuse cosmic gamma-ray background to the X-ray and radio backgrounds. From this comparison, I find that Inverse Compton is a minority of the X-ray background, and that the radio background is probably not from starbursts. Finally, I modeled the nonthermal X-ray emission from starburst galaxies, both synchrotron from TeV electrons and Inverse Compton from GeV electrons. The synchrotron emission is enhanced by gamma-gamma (open full item for complete abstract)

Committee: Todd Thompson (Committee Chair); John Beacom (Committee Member); Christopher Kochanek (Committee Member) Subjects: Astronomy; Astrophysics

Master of Science in Electrical Engineering (MSEE), Wright State University, 2024, Electrical Engineering

To address the issues of limited target data in the Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) problem set, synthetic data is often used to aid in filling the gap. This paper covers an in depth look at the use of colorization, dynamic range adjustment, and target extraction as data augmentation techniques to improve the accuracy of deep learning networks trained on synthetic SAR data. The use of multiple different data augmentations combine to dramatically improve the accuracy of a common Convolutional Neural Network (CNN) over the use of standard synthetic data. A comparison of increasing fraction of measured data were used to show that the less measured data there is available the more critical these data augmentation techniques are to improve target recognition.

Committee: Josh Ash Ph.D. (Committee Co-Chair); Brian Rigling Ph.D. (Committee Co-Chair); Fred Garber Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science in Computer Engineering, University of Dayton, 2024, Electrical and Computer Engineering

Administering the behavior of drivers near roadside restricted areas, such as work zones, accident zones, or natural calamity zones, is necessary for safety. It helps steer vehicles clear of the ongoing blocked region. This ensures the safety of both drivers and people in that area. The vehicles need to be diverted to a different lane away from the restricted area for smooth running of the traffic. A computer vision-based autonomous system could be able to automatically monitor the movements of the vehicles and predict their pathways based on the direction and speed of the vehicles. This would help to provide appropriate signals to the drivers for changing the lanes appropriately. Development of an artificial intelligence-based learning system for detection and tracking vehicles on the road and prediction of their future locations in real-time videos captured by a stationary camera is proposed in this thesis. The videos captured in outdoor environments will be subjected to several challenges due to varying lighting conditions and changes in orientation, viewing angle, and object size. Surrounding objects like trees, buildings, or other vehicles can obscure a vehicle completely or partially, making reliable detection and tracking difficult. Stationary cameras may also capture background regions like buildings, trees, parking lots, etc. Sometimes, the detection vehicles become difficult due to their darker texture in non-uniform lighting conditions. In this thesis research, a YOLO_v8 neural network model is employed to detect the vehicles in the video frames in real-time. The neural network model needs an extensive set of annotated datasets of vehicles in roadside environments. A new annotated dataset named Dayton Annotated Vehicle Image Set (DAVIS) suited for US road conditions is built to train the vehicle detection model. An adaptive image enhancement technique, namely Contrast Limited Adaptive Histogram Equalization (CLAHE) is used in the moving object regions (open full item for complete abstract)

Committee: Vijayan K. Asari (Committee Chair); Theus Aspiras (Committee Member); Eric J. Balster (Committee Member) Subjects: Computer Engineering

Doctor of Philosophy, University of Akron, 2023, Polymer Science

Nanostructured hybrid materials can be formed using self-assembling side chains grafted to a polymer backbone. Small-angle X-ray and neutron scattering (SAXS & SANS) measurements on polyisobutylene graft copolymers with side chains containing β-alanine trimer have revealed that crystalline nanodomains form by self-assembly. Modifying the side chain chemistry allows one to tailor the β-alanine nanocrystal length from over 300nm down to approximately 10nm. The degree of crowding at the nanodomain interfaces impacts the temperature dependence of the microphase separation. Chemical variations in the side chains, such as removing C18 tails and adding C11 spacers between the backbone and β-alanine trimers have dramatic effects on nanocrystal size, domain spacings, order-disorder transition temperature and width of transition, crystal melting temperature, and bulk mechanical properties. The last chapter describes progress in defining the interface morphologies in blends modified with Interfacial Supramolecular Coupling Agents (ISCAs) containing β-alanine. Polyethylene (PE) and polypropylene (PP) constitute the majority of mixed plastic waste produced globally. In the approach studied, it is envisioned that a pair of ISCAs will populate the interfaces between PE-rich and PP-rich phases and anchor the phases together. From SAXS, SANS, Wide Angle X-ray Scattering (WAXS) and Atomic Force Microscopy (AFM) analysis it is evident that the presence of ISCAs alters the crystalline structure of the overall blend.

Committee: Mark Foster (Advisor); Mesfin Tsige (Committee Chair); Bi-min Zhang Newby (Committee Member); Toshikazu Miyoshi (Committee Member); Li Jia (Committee Member) Subjects: Engineering; Materials Science; Nanoscience; Nanotechnology; Physics

PhD, University of Cincinnati, 2023, Arts and Sciences: Physics

The cosmic microwave background (CMB) is a snapshot of the universe at recombination, the moment when the universe became transparent. Understanding the CMB could allow us to constrain or rule out aspects of inflation theory, which suggests that the Universe underwent a period of rapid expansion mere moments after the Big Bang. Specifically, we hope to detect primordial gravitational waves (PGW), an as yet unobserved phenomenon predicted by many inflationary models. BICEP/Keck is an experiment based at the South Pole with telescopes that are specified to observe B-mode polarization patterns caused by PGW at microwave wavelengths. The tensor-to-scalar ratio r is a parameter which if constrained could provide indirect evidence of PGWs. Presented is the work I have done in an internal linear combination (ILC) component separation method to separate the CMB signal from galactic foregrounds while minimizing noise, and the likelihood analysis I performed with the ILC results in an effort to constrain r.

Committee: Colin Bischoff Ph.D. (Committee Chair); L. C. R. Wijewardhana Ph.D. (Committee Member); Kay Kinoshita Ph.D. (Committee Member); Adam Aurisano Ph.D. (Committee Member) Subjects: Astrophysics

Doctor of Philosophy, Case Western Reserve University, 2023, Molecular Medicine

Autism Spectrum Disorders (ASDs) are a group of neurodevelopmental disorders for which there is no direct treatment. Understanding the disease mechanisms may lead to future therapeutic targets. In this thesis, we performed bi-directional CRISPR-Cas9 genome editing on induced pluripotent stem cells (iPSCs) derived from individuals with ASD with macrocephaly as well as controls, and uncovered that in addition to PTEN p.Ile135Leu variant, ASD genetic backgrounds also contributed to dysregulating cortical neurogenesis in both 2D neural progenitor cells and 3D cortical organoid models. Surprisingly, ASD specifc PTEN p.Ile135Leu variant dysregulates cortical neurogenesis in an ASD genetic background dependent fashion, as we found that this variant led to overproduction of neural progenitor cell (NPC) subtypes including intermediate progenitor cells (IPCs) and outer radial glia cells (oRGs) as well as neuronal subtypes such as deep and upper layer neurons in the ASD genetic background but not in the control genetic background in the cortical organoids. This study provides strong evidence that both an ASD-specifc PTEN p.Ile135Leu variant and autism genetic background are contributing to the cortical neurogenesis dysregulation. We also developed a lineage tracing system to track neurogenesis in human cortical organoids and applied this system to a control iPSC line as well as autistic isogenic CTNNB1 iPSC lines, we uncovered that the majority of the cortical neurons in the cortical organoids were indirectly generated through IPCs, and neurons derived from diferent lineages were transcriptionally distinct. An ASD-linked CTNNB1 p.Gln76* variant altered the lineage specific production of deep and upper layer neurons as well as the landscape of gene expression profiles among and within different neural progenitor lineages of both deep and upper layer neuron production. Overall, this thesis provides direct evidence that variants in the PTEN and WNT pathways as well as ASD (open full item for complete abstract)

Committee: Anthony Wynshaw-Boris M.D., Ph.D. (Advisor); Justin Lathia Ph.D. (Committee Chair); Tara DeSilva Ph.D. (Committee Member); Fulai Jin Ph.D. (Committee Member); Charis Eng M.D., Ph.D. (Committee Member) Subjects: Genetics; Neurosciences

Bachelor of Science (BS), Ohio University, 2023, Astrophysics

The Local Volume Complete Cluster Survey is a large sky imaging survey, targeting 107 clusters in the local sky. The analysis of these clusters is being done using weak lensing measurements. To make the measurements from weak lensing more significant, the noise must be reduced. Most noise is from background structures projected onto the 2 dimensional image used for the measurements. Described is a method for the detection of large background structures that effect the measurements made on the images created. This method also provides a way to find systematic errors in the photometric redshift measurements of objects within the target cluster.

Committee: Douglas Clowe (Advisor); David Drabold (Advisor) Subjects: Astronomy; Astrophysics

Doctor of Philosophy, Case Western Reserve University, 2023, Physics

SPT-3G is a new camera on the South Pole Telescope, currently being used to observe the sky in the millimeter-wavelength and make maps of the Cosmic Microwave Background (CMB). The CMB can be used to probe the origins of the universe and understand its subsequent evolution and the growth of structure. Clusters of galaxies, the largest gravitationally bound objects in the universe, trace out the distribution of matter across the universe. Observations of the CMB can be used to detect and characterize galaxy clusters via the Sunyaev Zel'dovich effect, wherein CMB photons are inverse Compton scattered off of hot gas within galaxy clusters. This effect can be used to measure the temperature evolution of the CMB as the universe expanded. In this thesis I give background on cosmology, describe the SPT-3G instrument and my role in its development, describe the software pipeline I wrote to detect galaxy clusters using SPT-3G, and give the new constraint on CMB temperature evolution that we have made using the 2019 and 2020 SPT-3G observations.

Committee: John Ruhl (Advisor); Aviva Rothman (Committee Member); Idit Zehavi (Committee Member); Benjamin Monreal (Committee Member) Subjects: Astrophysics; Physics

Doctor of Philosophy, The Ohio State University, 2022, Astronomy

The composition and evolution of galaxies have been an elemental but long-standing mystery in Astronomy. In the last century, the advent of telescopes across the electromagnetic spectrum has revolutionized our perception of galaxies from a mere assembly of stars to a complex ecosystem. Both observational and theoretical studies have pointed towards the existence of a gaseous medium beyond the stellar component of galaxies, aka, the circumgalactic medium (CGM). The CGM is a multi-phase gas surrounding the stellar disk of a galaxy, filling up its dark-matter halo. The CGM is simultaneously the fuel tank, waste dump, and recycle hub of galaxies. It is expected to harbor the baryons, metals, and feedback that are missing from the stellar disk. I have studied the two extreme phases of the CGM to investigate how the feeding (accretion) and the feedback (outflow) at the galactic scale govern the evolution of the Milky Way and similar nearby galaxies. The ≥106 K hot CGM, despite being challenging to detect, is a treasure trove of galaxy evolution. By probing the hot CGM of the Milky Way (MW) using X-ray absorption lines of multiple metal ions, I have discovered a super-virial 107 K phase coexisting with the well-known virialized 106 K phase, featuring non-solar abundance ratios of light elements, α-enhancement, and non-thermal line broadening. I have also detected this super-virial phase of MW CGM in X-ray emission analyses. Detection of these surprising properties of the CGM along multiple directions in the sky suggests a strong connection between the hot CGM and past Galactic outflow(s). Observations of MW-like galaxies complement our observations of the Milky Way. I have discovered the hot CGM emission of an MW-mass galaxy NGC 3221 that is extended (~150-200 kpc) and is massive enough to account for its missing baryons. The CGM is not isothermal, with the CGM within 100 kpc of NGC 3221 being super-virial, and fainter along the minor axis than the global a (open full item for complete abstract)

Committee: Smita Mathur (Advisor); Paul Martini (Committee Member); Annika Peter (Committee Member); Adam Leroy (Committee Member) Subjects: Astronomy; Astrophysics

Doctor of Philosophy, University of Akron, 2022, Polymer Science

Photoelectrochemical (PEC) conversion of biomass (e.g., lignin) to hydrogen, a carbon-negative emission technology, is characterized by four key processes: (i) photo-generated electron-hole pairs, (ii) electron transport from the anode to the cathode, (iii) hydrogen generation at the cathode and (iv) biomass oxidation by photogenerated holes in the valence band. Overall performance of the photoelectrochemical cell is governed by step (i), electron-hole generation, followed by step (iv), charge transfer at the semiconductor/electrolyte interface. This dissertation will discuss the development of an in situ infrared spectroscopic (IR) approach to study charge dynamics during PEC reactions. Accumulated photogenerated electrons on the semiconductor surface in PEC reactions exhibit a structureless, and featureless spectrum centered around 2000 cm-1. The intensity and rate of the IR profile of photogenerated electrons at this wavenumber correlates to the charge transport in the PEC process, qualitatively characterizing the efficiency of the catalyst. Electron accumulation can also be observed under dark conditions with negative voltage bias. Adsorbed water on the semiconductor surface serves as a hole scavenger and shields the catalyst surface from oxygen, preventing electron-hole recombination, while simultaneously promoting the formation of a double layer of electrons and protons on the semiconductor surface. The effect of voltage on the performance of the PEC cell is investigated through the analysis of the IR profile (i.e., relative concentration) of photogenerated electrons. The results of charge dynamics shed a light on the PEC mechanism and provide a scientific basis for devising novel approaches to enhance the PEC efficiency. The observations of the dynamics of accumulated electrons and water coverage in PEC reactions revealed the applicability of the in situ IR approach to electro-swing CO2 capture in liquid monoethanolamine (MEA). CO2 reacts with amines (open full item for complete abstract)

Committee: Steven S.C. Chuang (Advisor); Toshikazu Miyoshi (Committee Member); Zhenmeng Peng (Committee Member); Mesfin Tsige (Committee Member); Yu Zhu (Committee Member) Subjects: Alternative Energy; Analytical Chemistry; Polymers

Doctor of Philosophy (Ph.D.), University of Dayton, 2022, Aerospace Engineering

Combinations of various trends in global weather point towards an increased severity and frequency of wildfires. A handful of attempts have been made in the past that try to determine retardant ground deposits and their spatial distribution resulting from aerial drops in an effort to curtail fire growth. This study takes a multipronged approach at determining retardant ground deposits and spatial distribution at various coverage levels to better achieve fire control and extinguishment. The first approach fuses the dependent parameters, (line length, width, area, and ground distribution of the retardant), with the independent parameters using statistical regression in hopes to identify the probable parameters that are complicit in affecting the ground contours and their prediction the most. While the coverage prediction for the lower coverage levels (up to 3 GPC – Gallons per 100 ft.2) is accurate to 85% for area prediction with a variability of ±15% from actual while the length prediction is only accurate 58% of the time. This value was obtained using volume bounds on the input conditions. The estimate at higher coverage levels was poor along with the retardant's spatial distribution. An alternate approach was to model the drop phenomena in a relatively controlled, scaled down environment which was performed in the University of Dayton's Low Speed Wind Tunnel (UD – LSWT) facility. A 1 mm circular jet of water emanating from the underbelly of a model fuselage was placed in varying velocity crossflow (0 < Weber number < 101) of air. Shadowgraphs were initially performed, and the jet breakup was captured at 2000 frames per second which aided in discovery of breakup location with respect to surface waves. Experiments with Background Oriented Schlieren and Particle Image Velocimetry were also planned, however, they ultimately were not successful. Historical data points to two instabilities that govern the breakup process in jets, either in crossflow or quiescent a (open full item for complete abstract)

Committee: Aaron Altman (Advisor); Markus Rumpfkeil (Committee Member); Wiebke Diestelkamp (Committee Member); Sidaard Gunasekaran (Committee Member) Subjects: Aerospace Engineering

Doctor of Philosophy, Case Western Reserve University, 2022, Communication Sciences

Purpose: Speech recognition in the presence of competing speech can be challenging, and individuals vary considerably in their ability to accomplish this complex auditory-cognitive task. Speech-in-speech recognition can vary due to factors that are intrinsic to the listener, such as hearing status and cognitive abilities, or due to differences in the short-term audibility of the target speech. The primary goal of the current experiments was to characterize the effects of glimpsed target audibility and intrinsic listener variables on speech-in-speech recognition. Methods: Three experiments were conducted to evaluate the effects of glimpsed target audibility, intrinsic listener variables, and acoustic-perceptual difference cues on speech-in-speech and speech-in-noise recognition. Listeners were young adults (18 to 28 years) with normal hearing. Speech recognition was measured in two stages in each experiment. In Stage 1, speech reception thresholds were measured adaptively to estimate the signal-to-noise ratio (SNR) associated with 50% correct keyword recognition for each listener in each stimulus condition. In Stage 2, keyword recognition was measured at a fixed-SNR in each stimulus condition. All participants completed a battery of cognitive measures that assessed central abilities related to masked-speech recognition. The proportion of audible target glimpses for each target+masker keyword stimulus presented in the fixed-SNR testing was measured using a computational glimpsing model of speech recognition. Results: Results demonstrated that variability in both speech-in-speech and speech-in-noise recognition depends critically on the proportion of audible target glimpses available in the target+masker mixture, even across stimuli presented at the same global SNR. Glimpsed target audibility requirements for successful speech recognition varied systematically as a function of informational masking. Young adult listeners required a greater proportion of audibl (open full item for complete abstract)

Committee: Lauren Calandruccio (Committee Chair); Christopher Burant (Committee Member); Barbara Lewis (Committee Member); Robert Greene (Committee Member) Subjects: Audiology; Behavioral Sciences; Experimental Psychology

Doctor of Education (EdD), Ohio University, 2022, Educational Administration (Education)

This study explored rural educators' perceives surrounding the influence of their own sociocultural background on the glocal curriculum they implement and students' glocal worldview development. Glocal, in this study, referred to the concept of contextualizing globalization through a local lens. Current studies either focused on teacher perceptions from a quantitative viewpoint, an urban education viewpoint, or were based in other professional fields, such as healthcare or economics. While this study was informed by academic literature, it filled a gap in research surrounding rural, Appalachian-based educators through an interpretive qualitative research design. The purpose of this study was to explore the perspectives of rural, secondary-level educators in Appalachian-Ohio and West Virginia regarding the influence of their sociocultural background on glocal curriculum implementation and students' glocal worldviews. I analyzed research through a conceptual framework that fused Vygotsky's Sociocultural Theory, Cooperrider's Appreciative Inquiry approach, and the Hodges' Health Career Model, a glocal framework. Finally, based on the data and implications of the study, I list specific recommendations for educators, educational leaders, policy makers, and teacher preparation programs in Appalachian regions or other rural regions with glocal connection in mind.

Committee: Emmanuel Jean-Francois (Committee Chair); Emmanuel Jean-Francois (Advisor); Michael Kopish (Committee Member); Yegan Pillay (Committee Member); Charles Lowery (Committee Member) Subjects: Cultural Anthropology; Curriculum Development; Education; Educational Leadership; Middle School Education; Secondary Education; Social Research; Social Structure; Sociology; Teacher Education; Teaching

Doctor of Philosophy, The Ohio State University, 2021, Biomedical Engineering

Cardiovascular heart disease (CVD) is the leading cause of mortality in the U.S. and worldwide. Over the past several decades, the healthcare costs associated with CVD have steadily risen to more than 200 billion dollars per year and are expected to rise further with the aging population. Cardiovascular MRI (CMR) is a well-established imaging technique that provides the most comprehensive evaluation of the cardiovascular system. CMR is considered the gold standard for evaluating ventricular function and myocardial viability. Despite the growing evidence of its advantages over other imaging modalities and its potential as a “one-stop-shop” diagnostic tool, the role of CMR in clinical cardiology remains limited. One major impediment to its wider usage is the inefficient acquisition that makes CMR exams excessively long, often lasting for more than an hour; this diminishes its efficiency and cost-effectiveness relative to other imaging modalities. The current paradigm offers either a prolonged segmented acquisition that requires regular cardiac rhythm and multiple breath-holds or a fallback option of real-time, free-breathing acquisition with degraded spatial and temporal resolutions. Recently, 3D imaging has gained significant interest due to its volumetric coverage and isotropic resolution. In particular, 4D flow imaging has emerged as a powerful tool that provides temporally and spatially resolved velocity maps of the blood in the heart and great vessels. A major technical limitation of 4D flow imaging is the long acquisition, which makes the images susceptible to motion artifacts. In this work, we present a framework that provides a whole-heart coverage and enables a rapid, quantitative assessment of hemodynamics. In addition, the method employs self-gating and thus extracts and compensates the physiological motions from the information in the MRI data itself, obviating the need to utilize electrocardiogram or respiratory gating. Novel extensions of the method, whe (open full item for complete abstract)

Committee: Rizwan Ahmad (Advisor); Rengasayee Veeraraghavan (Committee Member); Orlando Simonetti (Committee Member); Jun Liu (Committee Member) Subjects: Biomedical Engineering; Medical Imaging

PhD, University of Cincinnati, 2021, Arts and Sciences: Physics

The Cosmic Microwave Background (CMB) has provided a wealth of information since its discovery in the 1960s. The blackbody nature and the temperature anisotropies of the CMB have helped form the current cosmological paradigm of a hot Big Bang and the ?CDM model of the Universe. We are now looking to the polarization field of the CMB for answers about the early Universe. The theory of Cosmic Inflation postulates that the Universe went through a period of exponential expansion in the earliest moments. This theory generally predicts a stochastic background of primordial gravitational waves which would leave a faint B-mode pattern in the polarization of the CMB. The BICEP/Keck Array telescopes are small aperture multi-frequency microwave polarimeters at the Amundsen–Scott South Pole Station. These telescopes continuously observe a ~1% patch of the Southern sky targeting degree angular scales where the amplitude of the primordial gravitational waves is predicted to peak. The multi-frequency observation allows for the disentanglement of galactic foreground signals from the CMB signal. To date, these experiments provide the tightest constraints on the tensor-to-scalar ratio at r < 0.07 at 95% confidence. The discussion of this thesis is split into two parts. In the first part, it will discuss the design, development, and performance of the BICEP Array Housekeeping system. The Housekeeping system is an electronics data acquisition system designed to read out the thermistors of the cryogenically cooled receivers and provide temperature control. The second part of the thesis will discuss high level data analysis using a multi-component model of the bandpower data. In particular, there will be discussion of a novel minimum variance quadratic estimator used as an alternative to the maximum likelihood estimator.

Committee: Colin Bischoff Ph.D. (Committee Chair); Matthew Bayliss Ph.D. (Committee Member); Alexandre Sousa Ph.D. (Committee Member); Hans-Peter Wagner Ph.D. (Committee Member) Subjects: Physics

Doctor of Musical Arts, The Ohio State University, 2021, Music

The world lost a musical master, Nikolai Kapustin (1937-2020) during the aftermath of the world pandemic. Despite its immediate appeal, his music remains a mystery owing to lack of published scholarship. All that exists is translated interviews, but an ever-growing body of literature in the form of doctoral dissertations. The latter was precipitated by the composer's attendance at Marc-Andre Hamelin's premiere of the Piano Sonata no. 2, op. 54 in London during the year 2000. In the spirit of the increasing popularity of Kapustin's solo piano works, this document adds to the body of extant material, examining specifically the Variations, Op. 41 and Three Etudes, Op. 67. While offering not a theoretical analysis, it offers a look into Kapustin's unique fusion of American jazz music style and classical music forms. Kapustin was devoted to creating a distinctive music style that seamlessly integrates classical structures and vibrant jazz idioms. A heightened interpretive ability can be arrived at by understanding of what is explicitly “classical “or “jazz” in his music and what the performance practices and expectations are in both arenas. This document is intended for the sophisticated classical pianist who already possesses a fully developed technique and is interested in producing an informed interpretation of his music.

Committee: Caroline Hong (Advisor); Arved Ashby (Committee Member); Kenneth Williams (Committee Member) Subjects: Music

Doctor of Philosophy, Case Western Reserve University, 2021, Physics

One of the most outstanding questions in fundamental physics is the nature of dark matter (DM). From multiple independent sources of evidence we infer that DM exists and constitutes nearly 85% of all matter in the universe. However, it is still not known what comprises the DM, how it is formed, and if and how it interacts non- gravitationally with Standard Model particles. In this dissertation, we are by and large concerned with the final question among the aforementioned list of puzzles, i.e., what signatures can DM leave in the observable universe? We propose a new mechanism by which DM can affect the early and late universe. The hot interior of a macroscopic DM, or macro, can behave as a heat reservoir so that energetic photons and neutrinos are emitted from its surface and interior respectively. In Part 1 of this dissertation we focus on the spectral distortions (SDs) of the cosmic microwave background before recombination. The SDs depend on the density and the cooling processes of the interior, and the surface composition of the macros. We use neutron stars as a straw-man for nuclear-density macros and find that the spectral distortions are mass-independent for fixed density. In our work, we find that, for macros of this type that constitute 100% of the dark matter, the μ and y distortions can be near or above detection threshold for typical proposed next-generation experiments such as PIXIE. In Part 2, we study the change in recombination history of hydrogen in the uni- verse caused by macros. We numerically solve the Boltzmann equation to calculate the photon distribution function, electron fraction, and baryonic matter tempera- ture as a function of redshift. During recombination, the excess photons emitted by macros have frequencies well above the excitation and ionization energies of the hydrogen atom. At such high frequencies, the excitation and ionization processes have extremely small cross-sections, thereby limiting the efficiency of the excess p (open full item for complete abstract)

Committee: Glenn Starkman (Advisor); Idit Zehavi (Committee Member); John Ruhl (Committee Member); Stacy McGaugh (Committee Member) Subjects: Astrophysics; Physics

Doctor of Philosophy, Case Western Reserve University, 2020, Physics

The Cosmic Microwave Background (CMB) temperature anisotropies have been mapped with increasing precision in the last 30 years. Although the measurements have been found to be in excellent agreement with statistical predictions of ΛCDM, several large-scale features of CMB temperature were observed to be anomalous, with p-values in the per mille to per cent level. Among those features is the lack of correlation on the largest angles (S1/2 anomaly) and the lack of variance in the ecliptic north. Although well-established results, they remain unexplained. To test the hypothesis that these anomalies are merely statistical fluctuations, we explore simulations of CMB maps constrained by current temperature data. We look at the contribution of the integrated Sachs-Wolfe effect to S1/2 and show how correlations from early-time and late-time physical effects contribute to its value. In anticipation of future polarization experiments, we generate realizations of polarization maps and predict the distribution of the hemispherical variance in polarization, considering different sky-coverage scenarios. We find that the low northern-hemisphere variance seen in temperature is not expected in polarization. We also study how the variance of polarization depends on current measurements of ΛCDM parameters and find that it is noticeably sensitive to present uncertainties in the reionization optical depth (τ). We explore how current improvements in the measurement of τ result in a tighter constraint on polarization-variance expectations, and how future τ measurements can further reduce the uncertainty in the polarization-variance distribution, thus improving our ability to test for the variance anomaly with upcoming polarization data.

Committee: Glenn Starkman (Advisor); Craig Copi (Committee Member); John Ruhl (Committee Member); Stacy McGaugh (Committee Member) Subjects: Astrophysics; Physics; Theoretical Physics

PHD, Kent State University, 2019, College of Arts and Sciences / School of Biomedical Sciences

The basolateral amygdala (BLA) plays a crucial role in determining the the affective nature of sensory stimuli by establishing stimulus valence and salience. Within the BLA, background discharge rate relates both to neuron type and to stimulus responsiveness. The goal of this dissertation is to better understand how the BLA responds to valent vocalizations across the diversity of BLA neuron populations. Crucial to this goal is the ability to directly compare responses across neuron type. This requires solving the significant challenge of direct comparison of response strength among neurons with background discharge rates differing by multiple orders of magnitude. The work in this dissertation firsts solves this challenge (Chapter II), and then applies the solution to achieve the overarching goal (Chapter III). In Chapter II I present and validate the response strength scale (RSS), a new measure for describing response strength in datasets containing background discharge rates spanning several orders of magnitude without bias. This measure describes datasets with background discharge rates both above and below 1 Hz more accurately than the other measures examined, and it has a meaningful threshold criterion that is set according to the variability of the examined dataset. In Chapter III I describe BLA neuron responses to valent vocalizations using a variety of statistical models, including latent class analysis, cluster analysis, and generalized linear modeling. I conclude that both early excitation and persistent firing are important markers of vocalization salience in BLA principle neurons (PNs), and that acoustic context is an important contributor to vocalization salience. Further, I identify two groups of putative PNs based on their responses to valent vocalizations – unresponsive/ selectively-responsive PNs and broadly-responsive PNs. These groups may represent different types of neuron or the same type of neuron in differing states.

Committee: Jeffrey Wenstrup (Advisor); Alexander Galazyuk (Committee Member); Aaron Jasnow (Committee Member); Christopher Vinyard (Committee Member); John Gunstad (Committee Member) Subjects: Biology; Neurosciences