What happens when a net operating loss carryforward is exhausted?

I study how firm behavior changes after the firm exhausts its NOLC. Prior literature has provided evidence that NOLCs affect firm behavior. Firms that exhaust their NOLC are losing a tax shield and experience a significant change in tax status. Theoretically, firms should change behavior when their NOLC exhausts. However, it appears that not all firm behaviors change when the NOLC is exhausted. I examine firm investment, debt financing, and cash holdings decisions using a six-year window surrounding the NOLC exhaustion to understand the timing and extent of behavior changes. Consistent with my expectations, I provide evidence that investment increases when the firm no longer has an NOLC. However, I fail to find strong evidence that firms change their debt financing or cash holdings decisions in the predicted direction after the NOLC exhaustion. Overall, these findings indicate potential variations in behavior changes. It appears that firms change investment behavior immediately after the NOLC is exhausted, whereas the absence of discernible changes in debt financing and cash holding decisions implies that, if there are changes in behavior in response to the NOLC exhaustion, they are not statistically significant within the observed timeframe. This suggests potential challenges for managers in adapting to full taxation and incorporating muti-year tax benefits

WHEN TO FOLLOW, WHEN TO BREAK, WHO TO BLAME: CITIZEN PERCEPTIONS OF STREET-LEVEL SERVICE INTERACTIONS

In this dissertation, I combine insights from public administration with those of political science, public policy, and social psychology to better understand how citizens think about and understand their governments. In each of three studies, I unpack a different decision-making process with relevance to public administration. The first explores how information about clients shapes citizens’ agreement with street-level bureaucrats’ rule compliance (or lack thereof). The second is similar, this time assessing how client information influences how citizens assign blame when clients experience negative outcomes. The third focuses on factors that drive bureaucrats to support other bureaucrats’ rule compliance decisions, this time paying special attention to the effects of respondents’ just-world beliefs. While I expected that clients’ identities—and particularly their identity congruence with respondents—would significantly affect each of these processes, what I find is more interesting and complex. Though they did not express strong disagreement with bureaucrats’ prosocial rule-breaking decisions—or decisions to break the rules for the explicit purpose of better serving a client— citizens always preferred that bureaucrats followed agency rules, regardless of the client’s identity, deservingness, and outcome. When assigning blame for a client’s negative outcome, citizens overwhelmingly blamed the client, allocating over twice as much blame to the client than the serving bureaucrat or agency. While, this time, the client’s deservingness had large effects on citizens’ decisions, even deserving clients received more blame than any other category. Finally, respondents—both citizens and bureaucrats—with high just-world beliefs were much more likely to support bureaucrats’ rule decisions, irrespective of the actual decision. As I will argue, together, the findings provide room for optimism in some ways while painting a worrying picture for social equity in others

Signal Processing Techniques for Spatial and Frequency-Varying Wave Propagation Through Multi-Layer Stack-Ups

Radar is classically used over optical sensors to sense objects regardless of weather or daylight conditions. In this case, a waveform is transmitted through the air and reflects off the outside of an object back to the radar. Radar has since been extended to sense within objects. Common applications are non-destructive evaluation, ground penetrating radar, and remote sensing. In this case, the incident wave is reflected by the contrast of electrical properties between materials. More recently, radar has been leveraged for biomedical applications, such as vital sign sensing and imaging within the body. Biomedical imaging radar (BIR) is a promising non-ionizing method to sense within the body. Some potential features to extract could be tumors, brain bleeds, or foreign objects. A general assumption in radar operation is that the reflected waveform has the same structure as the transmitted waveform. The wave's velocity of propagation is dependent upon the medium and the frequency. Thus, if the reflected wave has traveled through a medium other than air, the received waveform is more stretched out in time than the transmitted waveform. Applying a traditional matched filter in this case yields a degraded range profile, and the returns do not appear at the correct physical location. If the wave only travels through air and one other non-dispersive medium, the range calculation can be easily adjusted. This scenario is commonly encountered in remote sensing. However, more complex scenes such as the human body, are composed of several media with electrical properties that vary across frequency at different rates. Existing techniques are not able to fully leverage radar's pulse compression gain in this case. In this research, the challenge of radar wave propagation through multiple media is addressed. First, the wave propagation mechanics are studied to understand how the received waveform is distorted. Then, a matched filter is adapted to compensate for this spatial and frequency-dependent distortion in the frequency-modulated continuous wave (FMCW) radar case. The compensation scheme is demonstrated in simulation, and then an FMCW prototype system is built to apply the velocity correction to measured data. The proposed compensation technique is successfully applied to measure a scene with a metal plate placed immersed in a box of oil at various ranges, and more advanced range profile enhancement is explored. The proposed technique is shown to overcome a crucial challenge faced by a BIR

Accountability, Ownership, and Satisfaction: An Innovative Approach to Teamwork in Engineering Education

Teamwork skills are essential for engineers to be successful in their careers. Engineers often work in teams to solve complex problems. Unfortunately, learning power skills, such as teamwork, can pose a significant challenge for engineering-minded students. This often results in frustration for students and instructors alike. To address this issue, we implemented an innovative approach toward group lab writing in a lab class for 35 junior-level Chemical Engineering students. In this study, individual contributions were worth 30% toward the group-written lab report. Students were required to complete their individual contribution submission as a completion grade 24 hours before the group-written report was due. The group lab report was graded on quality and was worth the other 70%. The purpose of this initiative was twofold: 1) to enhance accountability among team members, as students’ individual grades now reflect their individual contributions; and 2) to foster better time management skills, reducing last-minute group efforts. Our findings suggest that including an individual portion in lab group assignments positively impacts students. The average scores for the individual contribution portion of the lab reports were 92%. The approach was shown to increase accountability among individual members of the lab groups, as students who self-identified as “waiting to the last minute” were shown to submit individual portions on time (75%). Furthermore, the early submission requirement encouraged effective time management across all students, exemplified by the on-time submission rate of 94% on individual portions, thereby diminishing the likelihood of last-minute, hurried teamwork. Additionally, the entire class exhibited a perfect 100% on-time submission rate for group-written assignments. Finally, students found teamwork more enjoyable with this method of submission. When surveyed, students' opinions of teamwork improved by an average of 1 point (on a 5-point scale). This mixed methods, IRB approved study, highlights the potential benefits of incorporating individual portions in team assignments, paving the way for improved opinions on teamwork, promotion of accountability, and time management skills among students

FIRST PRINCIPLES MACHINE LEARNING IN RADAR: AUGMENTING SIGNAL PROCESSING TECHNIQUES WITH MACHINE LEARNING FOR DETECTION, TRACKING, AND NAVIGATION

Machine learning (ML) provides a set of tools for learning approximate system models from data. It has the potential to improve classic radar signal processing (RSP) algorithms by allowing them to maintain performance when the environmental assumptions used to derive them are violated. This could mitigate performance degradation experienced in more challenging scenarios, like those commonly found in airborne and maritime radar. However, the integration of ML into RSP algorithms presents a unique challenge due to the strict performance requirements of radar systems and often unpredictable nature of ML. This work examines an architectural approach to explainable ML that allows for the seamless integration of ML with more traditional algorithmic methods. This approach is then paired with causal ML concepts to develop a method for mitigating measurement drift in tracking and navigation. Next, an integrated system of low-cost ML systems are developed to enable adaptive detection algorithms to maintain CFAR-like performance across a range of interference distributions. Finally, generative ML techniques are used to reduce sample support requirements for adaptive detectors by directly constructing whitening filters from a small set of interference samples. This dissertation presents a framework for the successful integration of ML into RSP algorithms using a targeted approach based on a clear understanding of the first principles physics at play in a given application

The Invisible Artist: The Editor's Perspective on Rhetoric, Ethics, and Representation in Film Editing

This dissertation explores the impact that the film editor has on films and what their beliefs are when it comes to the content that they create. Examining history, this dissertation shows that film editors have always impacted movies and the story that is shown. Historically film editors have been overlooked, with only a handful of editors, such as Walter Murch, being known amongst film viewers. Very few editors talk about what they do in the editing room and instead, when conversing focus on the story of the film. This dissertation is a qualitative study that interviewed narrative film editors, those that edit fictional films. The study attempted to interpret (1) what editors understand about their editing; (2) what editors think they are doing to the audience; (3) whether an accurate representation of ethnicities and minorities were ever a consideration; and (4) whether the ethics of their own edits are ever a consideration during the editing process. This dissertation attempted to understand what methods narrative film editors use and to what extent these editors understand the rhetorical aspects of editing, and attempted to understand to what extent these film editors recognize the way these editing methods affect their film viewers. Nine editors were interviewed. Among many other things, it was found that the editor always considers the audience of the film, while at the same time the editor believes they are not responsible for any ethical considerations and that these considerations is a job for someone else. At the same time, the editors’ identity determined if representation was a factor in the way they edited

Double burden of COVID-19 knowledge deficit: low health literacy and high information avoidance

Objective: People with lower levels of health literacy are likely to report engaging in information avoidance. However, health information avoidance has been overlooked in previous research on responses to viral outbreaks. The purpose of this cross-sectional survey study was to assess the relationship between health literacy and COVID-19 information avoidance. Students (n = 561) at a university in the south central region of the U.S. completed our online survey conducted from April to June 2020 using simple random sampling. We measured information avoidance and the degree to which people opt not to learn about COVID-19 when given the choice. We assessed participants’ health literacy level using the Newest Vital Sign (NVS), eHealth Literacy Scale (eHEALS), and All Aspect of Health Literacy Scale (AAHLS). Results: Those with lower health literacy were more likely to avoid information about COVID-19. This negative association between health literacy and information avoidance was consistent across all types of health literacy measures: NVS scores (b = − 0.47, p = 0.033), eHEALS scores (b = − 0.12, p = 0.003), functional health literacy (b = − 0.66, p = 0.001), communicative health literacy (b = − 0.94, p < 0.001), information appraisal (b = − 0.36, p = 0.004), and empowerment (b = − 0.62, p = 0.027). The double burden of low health literacy and high information avoidance is likely to lead to a lack of knowledge about COVID-19.Hlth Sci, Couns & Couns Psyc (HCCP

Expected number of real zeros for random orthogonal polynomials

We study the expected number of real zeros for random linear combinations of orthogonal polynomials. It is well known that Kac polynomials, spanned by monomials with i.i.d. Gaussian coefficients, have only (2/π + o(1))logn expected real zeros in terms of the degree n. If the basis is given by the orthonormal polynomials associated with a compactly supported Borel measure on the real line, or associated with a Freud weight defined on the whole real line, then random linear combinations have expected real zeros. We prove that the same asymptotic relation holds for all random orthogonal polynomials on the real line associated with a large class of weights, and give local results on the expected number of real zeros. We also show that the counting measures of properly scaled zeros of these random polynomials converge weakly to either the Ullman distribution or the arcsine distribution.Mathematic

Inclusive Metadata through bibliographic control

As the Metropolitan Library System was implementing Aspen, an open-source discovery system, we decided to complete our first authority and bibliographic control project. An RFP was written, and two vendors responded with quotes. Backstage was chosen as the vendor, and we started the process in August 2023. A major focus of this project was to move from homegrown genre headings to Library of Congress genre headings. As we were working to update all our records to current cataloging standards, we also made inclusive metadata a top focus. Backstage provided headings from Homosaurus ; a local authority file for Indigenous peoples and incorporating the work of the Xwi7Xwa (whei-wha) Library and the Greater Victoria Public Library

Stretching It: Exploring food security status, food insecurity coping strategies, and mental health among single female caregivers

Background: Food insecurity is an ongoing problem in the United States. Certain groups, such as single females heading a household tend to be disproportionately impacted. This study examines food security status among single female caregivers of children and investigates the relationships between food security status, depression, and various food insecurity coping strategies. Methods: Survey data was collected among a convenience sample of single female caregivers (n=94). The survey included measurements assessing food security status, various food insecurity coping strategies, depression, and sociodemographic variables. We examined the relationships between key variables using a series of linear and logistic regressions. Results: Depressive symptoms were high among our sample, with over 70% of participants surpassing the scale’s cutoff for likely depression. There was a significant relationship between higher levels of food insecurity and increased depressive symptomology after controlling for sociodemographic controls (p = .004). We also found that higher levels of food insecurity were associated with use of more community, interpersonal, and intrapersonal coping strategies (p- values < .05). Greater use of community coping, interpersonal coping, and shopping and tradeoffs (intrapersonal) coping strategies were associated with increased depressive symptoms (p-values < .05). Conclusion: The high rates of food insecurity and depression among our sample reiterates the need for further study and intentional interventions among single female caregivers. Examining food insecurity coping strategies may provide deeper insight into understanding food insecurity as well as help to clarify the relationship between food insecurity and depression.Study conducted by the Stress & Health Disparities Lab at the University of OklahomaN