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Near Infrared study of comet C/2022 E3(ZTF) using iSHELL spectrograph at NASA-IRTF
Get PDFWe present a comprehensive analysis of the chemical composition of the Oort Cloud Comet C/2022 E3 (ZTF), in the near-infrared (near-IR) wavelength regime. Observations were conducted using the iSHELL high-resolution spectrograph (R~50000) at the NASA Infrared Telescope Facility (IRTF) on UT 2023 January 20 and January 22, during the comet’s post-perihelion passage. We report rotational temperatures, production rates, and mixing ratios (relative to H2O and C2H6) for the primary volatiles: CH3OH, HCN, CH4, CO, and H2CO. Additionally, we place stringent 3 upper limits on the production rates of NH3, and C2H2. The spatial emission profiles of these outgassing species are also examined to understand their release mechanisms and source regions. A comparative analysis was performed between the results obtained in this work and other observations of E3 (ZTF), as well as data from other comet families, to place the findings in a broader compositional context. Based on this comparison, a taxonomic classification has been conducted of the detected volatiles. Compared to other family of comets, the abundances of CH3OH and C2H6 were found to be typical, whereas other volatile species exhibited significant depletion
Three essays on Corporate Finance and Insider Trading
No full textIn chapter one, we introduce IPO Rival Insider Selling (IRIS) as a novel predictor of IPO underpricing and long-run performance. We argue that incumbent industry rivals possess private, dispersed information about upcoming IPO competition and trade on these insights ahead of IPO events. Aggregating pre-IPO insider trading imbalances among IPO rivals, we construct IRIS, which captures dispersed competitive information that attention or capacity constrained underwriters may miss. We find that IRIS identifies which IPOs eventually outperform: higher IRIS strongly predicts greater first-day underpricing and superior long-run returns. Consistent with informationally constrained underwriters and delayed market efficiency, these effects are driven by non-obvious IPO rivals and are most pronounced when market sentiment (attention) is high (low). Our findings highlight that rival insider trading provides real-time signals about future competitive dynamics and IPO outcomes.
In chapter two, utilizing a sample of 1,899 M&A events from 1996 to 2020, we observe positive and significant abnormal trading volumes in the option market of target firms’ rivals, particularly in out-the-money options. Our analysis further explores the underlying reasons for these patterns based on two major theories from existing literature: the acquisition probability theory, which suggests that rivals of target firms experience abnormal returns due to the increased likelihood of future acquisitions, and the collusion theory, which asserts that horizontal mergers lead to enhanced market power and, consequently, abnormal returns for rivals. Our findings support the acquisition probability theory.
In chapter three, we investigate how investor attention to insider trading disclosures confers an informational advantage in stock market. Using a novel web log data from EDGAR (the SEC’s Electronic Data Gathering, Analysis, and Retrieval system) on Form 4 visits, we show that more sophisticated investors, especially those engaging in high-frequency monitoring of EDGAR, are more likely to identify the most informative insider trading filings. Form 4 filings that attract higher human attention lead to stronger subsequent abnormal returns. The attention-return effect is most pronounced when there is greater information asymmetry, such as indirect insider trading, smaller firms, low analyst coverage, and generally firms with limited public visibility. We also find that when Form 4 filings are viewed by users or IP addresses previously flagged for automated downloading (indicating Human + Machine “Hybrid” information processing), the return reactions are even more pronounced. This suggests a synergistic benefit to combining human judgment with machine power in processing insider information
Understanding the criticality of volumetric defects on the fatigue behavior of additively manufactured aluminum alloys
No full textThis study investigates the criticality of volumetric defects on the fatigue behavior of additively manufactured (AM) Al alloys. The role of various microstructures in determining sensitivity to defects, in particular their effect on the fatigue crack initiation and growth, is examined. Furthermore, the effectiveness of both destructive and non-destructive evaluation methods in characterizing the critical defect features for fatigue life prediction is assessed. The uniaxial fatigue behavior of two Al alloys, AlSi10Mg and Scalmalloy, each possessing distinct microstructures and thus likely to exhibit varying defect sensitivities, is investigated. It is shown that while applying post-process thermal treatments can enhance the tensile properties of AlSi10Mg by altering the microstructures, the fatigue properties are still largely governed by the presence of volumetric defects. In contrast, Scalmalloy, which possesses a bimodal grain structure, exhibits similar sensitivity to crack-initiating defects. However, microstructural effects become more apparent in the near-threshold regime. Specifically, the location of defects within the microstructure influences fatigue behavior in Scalmalloy, and microstructural features become increasingly influential approaching the crack growth threshold. Nevertheless, it is found that by considering both the short and long crack growth rates, the fatigue behavior can be sufficiently described within scatter bands of ±3 for both alloys. Moreover, non-destructive part qualification methods are explored and the efficacy of x-ray computed tomography (XCT) examination in capturing critical defect features is quantified. The results show that the probability of detection (POD) of defects is a function of the XCT scan parameters, coupon geometry and AM defect types. At a given scan resolution and defect size, lack-of-fusions (LoFs) exhibit a lower POD compared to spherical defects such as keyholes (KHs) and gas-entrapped pores (GEPs). While LoFs are more difficult to capture in lower resolutions, even when detected, the errors in their size measurements are greater compared to spherical defects which can be reliably detected with good accuracy in their sizing. A distance-criterion based correction is proposed, which allows critical information for LoFs to be recovered in low-resolution scans by reconstructing the defect geometry. It is demonstrated that the procedure can significantly reduce the sizing errors, allowing for rapid and accurate defect characterization. To assess the effectiveness of the distance-criterion approach for fatigue life predictions, AlSi10Mg and Scalmalloy fatigue specimens are examined by XCT prior to testing and the representations of the critical defects are identified in the XCT scans. The XCT data is post-processed by applying the distance-criterion based correction and incorporated into crack-growth based fatigue models. While the uncorrected data provides mostly non-conservative predictions due to the underestimation of defect sizes, the corrected data input into the fatigue models can provide accurate, moderately conservative fatigue life predictions within scatter bands of ±3
#TeacherQuitTok: Social Media’s Shaping of Teacher Exit Culture
Get PDFThis dissertation investigates how TikTok, specifically #teacherquittok, influences teacher exit culture through multimodal narratives and the processes outlined in social influence theory. Teacher attrition has long been a concern in education, but recent shifts in digital communication have created new public arenas for educators to share their experiences and decisions to leave the profession. By analyzing how resignation narratives are constructed and amplified on TikTok, this study explores the ways in which social media contributes to evolving perceptions of the teaching profession. Grounded in social influence theory, particularly Kelman’s (1958) processes of compliance, identification, and internalization, this qualitative case study applied multimodal content analysis to a purposive sample of 50 TikTok videos tagged with #teacherquittok. The study analyzes visual, textual, auditory, and graphic elements within the videos, along with user engagement metrics, to understand the emotional tone, narrative structure, and social resonance of the posts. Sentiment analysis was used to assess the tone and authenticity of the content and its potential to influence peer perception and engagement. Findings reveal that teachers use TikTok to frame and share narratives about personal well-being, workplace conditions, and career transitions. Through candid expression, authenticity, and emotional appeal, these videos convey dissatisfaction and reflect broader conversations about the profession. Social media not only captures these stories but also operates as a mechanism of social influence, where educators’ decisions may be shaped by the collective narratives they encounter. This study contributes to the growing body of research on digital teacher communities by examining how TikTok serves as a space where educators construct and share exit narratives that influence peer perceptions, amplify conversations around attrition, and reflect the social influence processes shaping decisions to leave the profession. These findings provide insight into how social media narratives reflect the factors influencing teacher attrition, offering implications for recruitment, retention, and how education stakeholders respond to evolving perceptions of the profession
Data-Driven Machine Learning Aided Fine Scale Reconstruction for Hierarchical Parameter Systems and the Geometry of Adaptive Learners
No full textWhile statistical uncertainty is observable in many real-world systems and data, its incorporation into numerical prediction and optimization algorithms presents numerous challenges in terms of accuracy, efficiency and storage costs. In this dissertation, we make two contributions to numerical algorithms that account for uncertainties.
In the first part, we discuss the statistical simulation of a known physical system with spatially varying random model parameters. The resulting ensembles of model outputs can be used to determine statistical properties, such as means and confidence bounds, of related quantities of interest. In these simulations, the complexity (dimensionality) of the system parameter's statistical description, which often reflects the spatial scale at which the parameters are resolved, may affect both the statistical accuracy of resulting outputs and the spatial accuracy of the model solution, especially when the parameter fields are rough. In particular, very low-complexity models, while amenable to efficient sampling methods, may introduce a statistical modeling error by underestimating the true variation in the output. On the other hand, high-dimensional parameter representations, while more detailed, may result in model responses that require a higher resolution computational mesh, thereby increasing the computational cost. We propose a method to generate high-complexity samples conditional from low-complexity ones by means of a conditional variational autoencoder.
In the second part of the dissertation, we propose GeoAdaler, a new stochastic optimization algorithm, whose step length selection is based on a scalar measure of steepness of the objective function's sample gradient, based on the angle of its normal vector with the horizontal plane. We show how the resulting family of algorithms relate to existing adaptive steplength selection techniques and establish regret bounds in the case of convex functions. We also demonstrate numerically that GeoAdaLer is capable of being extended to nonconvex settings
FORM FOLLOWS FUNCTION: ASSESSING THE ROLE OF DYNAMIC CNIDARIAN PHENOTYPES DURING STRESS
No full textThe overarching goal of this dissertation is to explore how dynamic phenotypes influence the ability of cnidarian species to respond to environmental stress, with a particular focus on the upside-down jellyfish (Cassiopea xamachana) and the Florida false coral (Ricordea florida). By connecting morphology, physiology, and molecular biology, this work provides novel insights into the resilience of these species under conditions of climate-induced stress and highlights the potential adaptive mechanisms that support their success in rapidly changing marine environments.
In Chapter 2, we establish that temperature acclimation significantly increases the thermal tolerance of C. xamachana medusae. Animals pre-conditioned to elevated temperatures display enhanced bell pulsation rates and improved survival under acute heat stress. Interestingly, while environmental history (i.e., collection site) does not influence thermal tolerance, pigmentation does. Specifically, individuals with blue-colored appendages demonstrate significantly higher survival rates under extreme temperatures compared to their brown counterparts. This observation suggests that pigmentation is correlated with underlying physiological or molecular mechanisms that confer resilience.
Chapter 3 addresses the molecular underpinnings of blue pigmentation. Using a multi-omics approach that combined transcriptomics, genomics, and protein expression studies, we identified a novel gene family that appears to be responsible for the striking blue pigmentation in Cassiopea. Candidate genes exhibited tissue-specific expression patterns, with strong upregulation in pigmented tissues relative to non-pigmented tissues. Our attempts to heterologously express the pigment in E. coli were unsuccessful, very likely because its expression requires specific cofactors or chaperones. The findings support the hypothesis that Cassiopea pigment production is under tight transcriptional regulation and potentially linked to photoprotective, antioxidative, or stress-buffering roles.
Chapter 4 extended our exploration of organismal responses to stress by examining the mucus microbiome of Ricordea florida. The mucus of this soft-bodied corallimorpharian harbored a highly diverse bacterial community dominated by Vibrio species. This microbiome was markedly distinct from surrounding seawater, suggesting selective enrichment by the host organism. Although traditionally viewed as pathogens, some Vibrio strains may play mutualistic roles in nutrient cycling or protection from other microbial invaders. Our results open the door for future exploration of host-microbe interactions in non-coral anthozoans, with important implications for understanding resilience and immune responses in cnidarians under stress
Forearc Basins Complexity and Evolution in Controlling Earthquake Rupture Segmentation of the Cascadia Subduction Zone
No full textThe Cascadia subduction zone is a prominent seismic risk for North America. The primary objective is to comprehend the long-term behavior of the subduction zone by examining the structural and stratigraphic changes documented in the Cascadia forearc basin. I utilized long-offset multichannel seismic reflection profiles of the Cascadia Seismic Imaging Experiment 2021 (CASIE21) to interpret stratigraphic units and structural features in the region. The CASIE21 dataset comprises approximately 5,500 km of seismic data collected in a quasi-regular grid encompassing margin-crossing and parallel profiles. I interpreted the seismic sections and identified key geological horizons, including the base of the forearc basin, a major unconformity, strike-slip faults, and normal faults, through analysis of reflection characteristics and integration with legacy seismic data. I focused on studying the extent and inactive periods of the forearc basin by analyzing a regional upper Miocene angular subaerial erosional unconformity, associated significant faults, and the tectonic evolution of the basins. The results cover multiple forearc basins with a maximum thickness of ~4.85 km, and the basins formed after the upper Miocene unconformity are ~1.9 km thick. The greatest depth for this unconformity is near the Newport syncline, with the northwest portion reaching ~2.5 km. I propose that the upper plate’s geological complexity, compositional heterogeneity, and structures, such as the Siletz terrane, influence how the forearc crust reacts to subduction, ultimately affecting segmentation and coupling zones, rupture lengths, and propagation
Breaking Down Barriers: Advancing Solvent Based Chemical Recycling Technologies for Multilayer Plastics from Food Packaging Waste
No full textThe goal of the research provided in this dissertation is primarily focused on the solvent-based chemical recycling of multilayer plastic waste from food packaging. Additionally, elucidation of the crosslinking mechanism of ethylene vinyl alcohol (EVOH) under thermo-oxidative degradation was completed to further the understanding of its thermal processing and recyclability. The significant accumulation of global plastic waste year-by-year has motivated considerable interest in improved recycling technologies. The inability to individually reclaim all the constituents within multilayer plastics, especially in food packaging, greatly contributes to the increasing plastic waste generated annually. Multilayer plastics are notoriously difficult to efficiently separate and recycle using traditional thermomechanical techniques because of the chemical and physical differences amongst the constituent polymers, which generally lead to worsened properties. However, solvent-based chemical recycling strategies have been recently explored for multilayer plastics to extract the individual polymers from these wastes. Solvent-based chemical recycling technologies offer a new approach to mitigating plastic waste by taking advantage of the differences in thermodynamic solubilities. Using this principle, each constituent polymer in multilayer plastic systems is selectively dissolved and recovered by antisolvent precipitation prior to reprocessing by traditional thermomechanical means.
Multilayer food packaging is commonly made up of layers of polyolefins or polyethylene terephthalates (PET), tie layers, and one or more barrier layers. The outer and inner layers are usually made of polyethylene, PET, or other polyolefins. These layers are adjoined to tie layers which are responsible for the compatibilization of adjacent barrier layers to non-polar permeants. Typically, the innermost layer is the barrier layer. The barrier layer in food packaging is often EVOH or a nylon copolymer, both of which are extremely effective at preventing gas permeation, hence keeping food products fresh. Because of its high value and growing market demand, substantial recycling efforts have been investigated specifically to recover and reclaim EVOH.
The first portion of this work explored the thermo-oxidative degradation of EVOH by using time-resolved rheology and nuclear magnetic resonance (NMR) spectroscopy along with gel permeation chromatography (GPC) to identify the crosslinking mechanism during degradation. EVOH is extremely susceptible to degradation under heat and air which quickly changes its microstructure, properties, and resultant processing. Time-resolved rheology was used to understand the temporal dynamics, crosslinking, and degradation kinetics of EVOH under thermo-oxidative conditions to further the understanding of its processability in recycling applications. Three EVOH copolymers with ethylene contents of 27, 32, and 48 mole percent were used in the investigation. The storage moduli of the long chains (and large structures) greatly increased during the duration of the tests, increasing by several orders of magnitude. Additionally, the complex viscosity versus frequency was completely altered; the flow behavior was initially a Carreau fluid, which completely shifted to a power law fluid after ~200 minutes at 200 °C in air. This suggested a significant change in the flow mechanics and correspondingly, processability. The Han plots displayed a plateau of G’ after ten cycles of SAOS, which corresponded to a notable microstructural alteration. Additionally, a complete arrest of the relaxation process was observed from the Cole-Cole plots, where the initial relaxation behavior was near Maxwellian. Lastly, a novel model was developed to understand the change in the chain dynamics during time-resolved rheology which led to the conclusion, within the studied range, that copolymer content did not influence crosslinking kinetics. To elucidate the crosslinking mechanism which arose during thermo-oxidation, various NMR spectroscopy techniques were employed including 1H, DEPT-135, COSY, and HMQC NMR spectroscopy methods. It was found that after the thermo-oxidative treatment, the terminal gamma lactone moieties were ring-opened which led to crosslinking and increased the degree of polymerization as determined by DEPT-135 13C NMR spectroscopy. This led to a crosslinked network, which was also detected using time-resolved rheology and further verified by increases in molecular weight noted from GPC. From this work, a mechanism for the crosslinking and degradation of EVOH was determined.
The second portion of this work examined the selective extraction of EVOH from multilayer plastics used in food packaging. The sources of real food packaging waste used in this work included K-Cups and Dole fruit jars and bottles. This work set the foundation for the selective removal of EVOH from other polymers like polyolefins and tie layers in real multilayer plastic systems. A variety processing conditions were also explored for this portion of the work using dimethyl sulfoxide (DMSO) as the selective solvent, which preferentially removes EVOH from polyolefins. The effects of selective extraction on EVOH from both plastic waste sources (and compared against neat EVOH pellets) was also explored. Characterization of the extracted EVOH was completed and compared to neat EVOH, which included Fourier-transform infrared spectroscopy (FTIR), melt rheology, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). The EVOH which was extracted from the waste sources were slightly altered compared to their neat counterparts in terms of its spectroscopic and thermal properties. There was a slight spectroscopic signature present for carbonyl structures after extraction. This indicated that a small fraction of the hydroxyl pendant groups were oxidized during the dissolution or precipitation processes. The thermal properties were effectively unchanged compared to their initial counterpart. More interestingly, the extracted EVOH’s rheological properties were shifted higher compared to neat EVOH grades, while maintaining a similar viscoelastic profile (i.e. storage modulus shifted higher but exhibited the same frequency dependence). From this work, a protocol was developed that displayed that EVOH can be selectively extracted from multilayer plastic waste from food packaging using DMSO without the need for the step-by-step dissolution approach proposed in literature.
The third and last portion of this work investigated the application of supercritical fluids as antisolvents for precipitating EVOH from solution as well as understanding the saponification reaction of the recovered EVOH. By using supercritical carbon dioxide (scCO2) as an antisolvent, the disadvantages of liquid antisolvent precipitation methods or temperature swings can be mitigated and greatly reduce energy costs and the need for advanced separation processes. It was found that scCO2 induced precipitation of EVOH out of glacial acetic acid (selective solvent) and appeared to change precipitation characteristics and phase behavior depending on EVOH concentration; for dilute systems, a fine dispersion of particles was created, whereas concentrated solutions formed solid pieces. Glacial acetic acid partially converted a fraction of hydroxyl groups into acetate groups upon heated dissolution in the carboxylic acid solvent. Because of this, saponification with aqueous sodium hydroxide (NaOH) and hot washing of the recovered EVOH was explored to reconvert the acetate groups into hydroxyl units. Based on FTIR spectroscopy, NMR spectroscopy, DSC, and TGA the saponification reaction was deemed successful and resulted in the nearly complete restoration of hydroxyl units. While this technology was primarily explored for solutions of neat EVOH, it also has great potential for real plastic waste products.
The culmination of this research provides a basis for solvent-based chemical recycling strategies focuses on the selective extraction techniques for barrier layer recovery. Specifically, this work sets the foundation for the recovery of EVOH from multilayer plastics from food packaging. Moreover, this dissertation has shown that supercritical CO2 is a promising antisolvent for EVOH dissolved in DMSO; CO2 and DMSO can be recycled as solvent and antisolvent streams after precipitation using a pressure swing. Lastly, the thermo-oxidative degradation mechanism of EVOH has been elucidated, which is imperative for understanding how it can be thermomechanically reprocessed after extraction from multilayer plastic systems
Evaluation of Fracture Properties of Additively Manufactured IN-718 Under Quasi-static and Dynamic Loading Conditions
No full textInconel 718 is a Nickel based alloy with many applications in the aerospace and automotive industries. Due to its high strength under intense heat, IN-718 is used
in extreme environments such as rocket engine manifolds and automobile exhaust systems. The focus of this work is on the fracture behavior of additively printed IN-718. Edge notched three-point bending specimens are additively manufactured using laser powder bed fusion (LPBF) and mechanically tested to evaluate the fracture performance under quasi-static and dynamic loading. Several combinations of laser process parameter, heat treatment, and shielding gas are used during manufacturing which influence the microstructure. Two different heat treatment procedures are used along with two different shielding gases, namely argon (A) and nitrogen (N) gas. The laser process parameters can also introduce defects into 3D printed parts. An underpowered laser causes lack of fusion (LoF) defects and an overpowered laser causes keyhole (KH) defects in printed parts. Three laser process parameters, one to induce more LoF defects, one to induce more KH defects, and a middle powered “recommended” (R) laser parameter not meant to induce either kind of defect, are used. Electrical discharge machining (EDM) is used to cut a crack-like notch into the edge of the specimens. A pair of EDM cut side grooves is added to the front and back surfaces along the uncracked ligament to constrain the crack growth to occur self-similarly, mitigate crack tunneling effects, and suppress shear lip formation. A random speckle pattern is applied to the specimens to allow for implementing digital image correlation (DIC)—a full- field optical technique—to measure surface deformation fields during fracture.
The fracture behavior of the specimens are evaluated by conducting quasi-static and dynamic experiments. Under quasi-static loading, notched three-point bend specimens are slowly loaded until the crack initiates and grows. The surface deformation are simultaneously measured by DIC. To evaluate the fracture behavior of IN-718 under dynamic loading, similarly notched three-point bend specimens are tested using a split-Hopkinson pressure bar (SHPB) apparatus to rapidly load the specimen while implementing DIC for full-field deformation measurements. The fracture event is recorded using an ultrahigh-speed camera at 400,000 frames per second. In both quasi-static and dynamic experiments, images are analyzed using DIC to quantify surface displacement fields. The energy release rate (ERR) is extracted at each load-step or time-step by computing the J-integral using a hybrid DIC-Finite Element (DIC-FE) method. The methodology is applicable to both quasi-static and high strain-rate experiments and accounts for elastoplastic stress-strain behavior in the material. A modified least-squares analysis of the measured displacements is also used to evaluate stress intensity factors in the elastic range to further validate the DIC-FE approach. In this case, the DIC-FE method is found to be more robust than the elastic least squares method and allows for the evaluation of fracture properties beyond the point of fracture. Results for the quasi-static specimens are validated with a complementary finite element solution. It is found that the most favorable manufacturing conditions are those which used argon shielding gas and heat treatment 1. The highest quasi-static critical ERR is 163.1 N/mm for the A1K (shielding gas of argon, heat treatment 1, keyhole defects) condition. The lowest is 46.9 N/mm for the N2K (shielding gas of nitrogen, heat treatment 2, keyhole defects) condition. This pattern is found to be the same under high strain-rate loading, with the highest critical energy release rate of 140.1 N/mm for the A1 condition. The lowest energy release rate is 50.2 N/mm for the N2 condition
Impact of Paternal Age and Sperm Storage Duration on Reproductive Performance Traits in Blue Catfish, Ictalurus furcatus
No full textAdvanced hatchery techniques have expanded the production of channel catfish, Ictalurus punctatus ♀ × blue catfish, I. furcatus ♂ hybrids, which exhibit several advantages over other catfish species. However, access to high-quality gametes remains a leading bottleneck for the industry. Paternal age and sperm storage duration (4oC) are critical factors affecting the quality of male gametes, yet it has received less focus in aquatic species. Therefore, establishing links between paternal age, sperm storage duration, and reproductive success is essential for enhancing hybrid catfish production. In this thesis, it was demonstrated that advanced paternal age leads to changes in reproductive performance, which can cause alterations in sperm performance for hybrid catfish. Transcriptomic analysis further showed highest reproductive performance at age 7, followed by a decreasing trend as males aged. Short-term storage of sperm showed increased oxidative stress within 24 h and time-specific microbiome changes in sperm. Overall, these findings identified the importance of paternal age and sperm storage in gamete quality and provided insights to improve hybrid production success