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Racism, discrimination, and assimilation – some identity issues and effects of the tension between the majority and minority groups
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Amir Guy, accepted the attached license on 2025-03-10 at 16:40.The student, Amir Guy, submitted this Dissertation for approval on 2025-03-10 at 16:59.This Dissertation was approved for publication on 2025-03-17 at 15:49.DSpace SAF Submission Ingestion Package generated from Vireo submission #21667 on 2025-10-19 at 19:14:24This dissertation delves into the complex dynamics of racism, discrimination, and assimilation within majority-minority relations in a Northern California city. It amplifies the perspectives of two leaders from a small religious minority community, exploring how they view minorities as agents of social change through advocacy and technology. The study underscores the crucial role of diverse voices and inclusive narratives, leveraging my varied background in business and education. It critically evaluates the American "melting pot" concept, focusing on the interplay of racism, discrimination, and assimilation. It also assesses how demographic shifts influence racial attitudes and political outcomes, particularly in the context of safeguarding minority rights and representation. The research employs qualitative methods, including interviews with community leaders and demographic data analysis, to gain insights into the experiences of minority groups. The findings indicate that racism and discrimination significantly impede assimilation, resulting in social exclusion, economic disadvantages, and cultural identity loss. The study highlights the pivotal role of minority groups in driving social change through advocacy and technology. It concludes that fostering mutual respect and promoting intercultural dialogue is not just important but vital for protecting minority rights and ensuring social representation. This paper addresses an understudied but highly relevant group within society: the marginalized. It explores their narration and criticism of personal lived experiences of marginalization. These individuals, often perceived to lack traditional forms of power such as public influence, formal authority, education, money, and political positions, still possess the resources to impact their situations and the structures that determine their circumstances. By shedding light on the complex interplay of racism, discrimination, and assimilation, this research contributes to the broader discourse on social justice and equality, offering insights for policymakers, educators, and community leaders committed to creating inclusive environments
Essays on finance
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Jae Jin Lee, accepted the attached license on 2025-04-07 at 10:55.The student, Jae Jin Lee, submitted this Dissertation for approval on 2025-04-07 at 10:56.This Dissertation was approved for publication on 2025-04-08 at 11:43.DSpace SAF Submission Ingestion Package generated from Vireo submission #21718 on 2025-10-19 at 19:14:32My dissertation focuses on the effects of misconduct in financial institutions. The first chapter examines how political connections influence the investment decisions of public pension funds, and the next two chapters investigate how the revelation of financial advisory misconduct affects affiliated banks and the portfolio management of mutual funds. The first chapter investigates how political connections influence public pension funds' investment decisions and performance in private equity markets. Exploiting quasi-random electoral outcomes from a sample of close U.S. state elections, I find that private equity firms donating to winning candidates who become pension board members are about ten times more likely to receive postelection investments from the pension fund than firms donating to losing candidates. Additionally, private equity funds in which public pension funds invest through political connections exhibit about five percentage points lower abnormal internal rate of return, driven partly by abnormal fund fees and home-biased investments. The second chapter examines how the revelation of financial advisory misconduct affect the deposits of their affiliated banks. Exploiting detailed administrative data on financial advisors and the geographic dispersion of bank branches, I find that, after advisory misconduct is exposed in a county, their affiliated bank branches in that county show abnormal decreases in deposits and small business loan originations. These effects are stronger when banks are geographically closer to affiliated advisors, face serious misconduct, have more uninsured deposits, are affiliated with advisors serving fewer retail clients, or are in socially-networked counties. I establish causality through the quasi-natural experiment of the mutual fund late-trading scandal. The results indicate that there are unexplored inter-industry distrust spillovers across financial intermediaries. Finally, the third chapter explores how business ties with portfolio firms affect the asset management strategies of mutual funds. By exploiting the revelation of mutual fund advisory misconduct as an exogenous shock to these business ties, I find that mutual fund management firms with collapsed trust tend to increase their portfolio weights in client stocks following the misconduct revelation. This shift towards client stocks effectively reduces the likelihood of business partnership termination. Additionally, I find that client stocks underperform compared to non-client stocks and exhibit indifference towards net-selling stocks held by the same mutual fund families. These findings raise concerns about fiduciary duty violations and underscore the need for vigilance in aligning investment decisions with shareholder interests
Virtual reality in speech and voice measurements: Investigating sensory streams and a preventative intervention
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Charles Nudelman, accepted the attached license on 2025-04-14 at 10:22.The student, Charles Nudelman, submitted this Dissertation for approval on 2025-04-14 at 10:38.This Dissertation was approved for publication on 2025-04-16 at 15:38.DSpace SAF Submission Ingestion Package generated from Vireo submission #21761 on 2025-10-19 at 19:14:41The purpose of this work is to investigate a potential method for improving ecological validity of speech and voice recordings in laboratory and clinical settings. This work focuses on implementing simulation technologies during voice recordings and examining the effects of their sensory features. Additionally, a brief virtual reality (VR) intervention is executed, and its effects are analyzed. The first experiment evaluated the effects of simulated background noise, reverberation, and visual VR room size and VR room occupancy (number of occupants present) on voice acoustic outcome parameters and self-reported vocal status. Forty-one participants recorded reading and spontaneous speech samples in six different simulated acoustic experiences and six different visual VR experiences separately. Linear mixed effects regression models revealed that auralized occupancy (background noise) and reverberation significantly affected the participants’ acoustic voice parameters, while only the auralized occupancy significantly affected their self-reported vocal status ratings. The second experiment involved forty-one participants and evaluated the effects of multisensory simulations on the same outcomes. Linear mixed effects regression models indicated that densely occupied and large VR rooms significantly influenced voice-related outcomes in comparison to sparsely occupied and small VR rooms. A secondary set of statistical models were implemented to analyze results across the first two experiments. These models revealed that multisensory simulations and unisensory (i.e., single-sensory) auditory simulations tended to significantly influence acoustic voice parameters and self-reported vocal status, compared to unisensory visual VR simulations. From these two studies, it can be determined that speech and voice production adapt significantly to audiovisual sensory input in VR, both when evaluating different aspects of the sensory input itself and when comparing multisensory simulations to unisensory simulations. Such multisensory simulations could improve voice recordings obtained in traditional contexts, such as laboratory and clinical settings. The third experiment endeavored to pilot a brief VR intervention for the clinical prevention of voice disorders using an evidence-based voice therapy. Ten pre-professional teachers recorded speech samples in three different conditions – a control condition (conversational speech), a teaching style condition in a sound booth, and a VR condition with voice-related cues provided by a certified and licensed speech-language pathologist. Linear mixed effects regression models revealed that the VR intervention condition contributed to the adoption of a teaching style of speech for all participants. The VR intervention condition resulted in significantly improved voice acoustic outcomes and significantly increased self-reported vocal discomfort compared to the control condition. Finally, responses on a VR questionnaire indicated that in the VR intervention condition, participants endorsed a strong sense of presence and immersion. This VR intervention demonstrates early feasibility that multisensory simulations can feasibly elicit vocal adaptations in a clinician-patient interaction. Future work should explore the efficacy of the VR intervention for speakers with speech and voice disorders
Solar energy harvesting and grid integration: Data visualization, MPPT optimization, and advanced PQ control of inverters
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Muhao Tian, accepted the attached license on 2025-04-21 at 07:29.The student, Muhao Tian, submitted this Thesis for approval on 2025-04-21 at 07:45.This Thesis was approved for publication on 2025-04-21 at 13:04.DSpace SAF Submission Ingestion Package generated from Vireo submission #21772 on 2025-10-19 at 19:14:55This thesis presents the design and analysis of an integrated solar energy system with data visualization and grid-tied inverter control capabilities. The research addresses two system architectures: Level One, focusing on solar panel monitoring and maximum power point tracking (MPPT); and Level Two, targeting grid-connected power conversion with advanced control strategies. The Level One system implements a data decoding framework for Controller Area Net- work (CAN) signals, a real-time visualization interface, the Incremental Conductance MPPT algorithm, and the real-time monitoring Graphical User Interface (GUI) surface optimized for solar energy harvesting. Short-circuit testing validates system performance under ex- treme operating conditions. The Level Two system develops a grid-connected inverter with synchronous reference frame PQ control for independent regulation of active and reactive power. The Two inductors (L) and One Capacitor (C) (LCL) filter is designed at the resonance frequency and tuned parameters with cascaded Proportional Integral (PI) controllers. Performance analyses prove excellent steady-state and transient responses, power tracking with minimum error in unity power factor. Simulink simulations validate both system levels, demonstrating high conversion effi- ciency and robust control performance. This research establishes a foundation for hardware implementation and contributes to advancing renewable energy systems through improved monitoring capabilities, optimized power extraction, and efficient grid integration
An educational “queery:” What is the relationship between gender affirming practices and the sense of school belonging and emotional wellbeing for trans high school students in North Carolina?
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Jess Grant, accepted the attached license on 2025-04-15 at 19:03.The student, Jess Grant, submitted this Dissertation for approval on 2025-04-15 at 19:12.This Dissertation was approved for publication on 2025-04-16 at 15:24.DSpace SAF Submission Ingestion Package generated from Vireo submission #21785 on 2025-10-19 at 19:14:58Transgender and gender-diverse (TGD) high school students face significant challenges in educational environments shaped by cisnormativity, restrictive policies, and inconsistent protections in a rapidly shifting legal landscape. This study investigates the relationship between gender-affirming practices, school belonging, and emotional well-being among TGD students in North Carolina. Using a convergent mixed-methods approach, the research integrates quantitative survey data and qualitative interviews to examine how school policies and practices impact students' experiences. Guided by Critical Trans Theory (CTT), the study highlights how systemic cisnormativity and restrictive legislation create barriers to inclusion while also identifying protective factors that foster resilience. The qualitative data amplifies the voices of TGD students, an often-silenced group in the current political climate, providing crucial insight into their lived experiences. Findings indicate that affirming school environments—where students can use their correct names and pronouns, access gender-neutral facilities, and engage with supportive staff—positively correlate with increased school belonging and improved emotional well-being. Conversely, policies that restrict gender expression, forcibly out students, or limit Lesbian, Gay, Bisexual, Transgender, Queer (LGBTQ)+ curriculum contribute to heightened distress. This research underscores the urgent need for educational policymakers and administrators to implement inclusive policies that support the mental health and academic success of TGD youth
Regional infrastructure resilience assessment and urban planning applications
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Yun-Chi Yu, accepted the attached license on 2025-04-16 at 11:13.The student, Yun-Chi Yu, submitted this Dissertation for approval on 2025-04-16 at 11:37.This Dissertation was approved for publication on 2025-04-20 at 15:48.DSpace SAF Submission Ingestion Package generated from Vireo submission #21794 on 2025-10-19 at 19:14:58Infrastructure is fundamental to the functioning of cities, providing essential services that support economic activity, mobility, and public well-being. However, natural disasters can severely disrupt infrastructure systems (e.g., transportation, potable water, and wastewater). Such disruptions may delay emergency response, extend recovery, and increase socioeconomic losses. Understanding infrastructure risk is essential for strengthening urban resilience. At the same time, with the continuous growth of population and expansion of cities, the role of urban planning becomes increasingly essential. Effective land use planning strengthens infrastructure resilience by guiding development patterns, reducing exposure to hazards, and supporting resilience strategies. It also balances differing priorities by integrating stakeholder interests (e.g., economic development) and broader social benefits (e.g., disaster mitigation) into planning decisions. Prediction models play a critical role in decision-making by connecting past events and literature with future outcomes. Such models help to identify trends, forecast potential risks, and inform decision-making for disaster resilience. Thus, understanding model uncertainty is significant for recognizing potential limitations and improving the robustness of decision-making. A systematic validation protocol is necessary for different prediction models and hazard types. Furthermore, to effectively support policy decisions, models must generate accurate assessments of infrastructure risks and system performance. Regional risk and resilience analysis models usually involve comprehensive prediction models, including nested models in complex multi-step procedures. A systematic approach is needed to integrate multi-level dependencies and incorporate heterogeneous data into model updates for the analysis. This dissertation addresses the fundamental challenges and focuses on transportation infrastructure, particularly roads, as an example among various critical infrastructure. The proposed ideas can further be modified and applied to other critical infrastructure systems. The contributions of this dissertation cover four main parts, specifically focusing on (1) modeling of road network disruption risk, (2) modeling of land use optimization for disaster mitigation, (3) model validation for regional risk and resilience analysis, and (4) multi-level model calibration and updating. This dissertation develops a probabilistic formulation using reliability formulation to estimate the probability of road blockage due to building damaged following an earthquake. The proposed model considers the spatial relationship between debris, building damage, road conditions. The road blockage probability at a given road section is estimated for the four road section types, considering buildings on only one side of the road or both sides, and with or without a raised traffic median. This dissertation then proposes a network-based approach for land use optimization. The optimization framework aims to minimize post-disaster accessibility risk while maximizing housing and urban development in the area. The approach integrates the quantification of infrastructure resilience into the spatial optimization process to enhance decision-making. This approach can also be applied to other infrastructure networks. This dissertation proposes three measures to validate the predictive ability of models used in regional risk analysis (i.e., Accuracy Likelihood, Prediction Error, and Distribution Match). Accuracy Likelihood quantifies the probability of observing the recorded data under the predictive model's hypotheses/assumptions. Prediction Error measures the difference between the recorded value and the values predicted by the models. Distribution Match measures the similarity between the probability distributions of the predicted quantities and the corresponding empirical distributions of the recorded data. As an example, we assess the predictive validity of seismic risk and resilience analysis models using data from the 2016 Kumamoto earthquake in Mashiki City, Kumamoto, Japan. This comparison highlights the predictive performance of available models and informs future research on crucial improvements. Finally, the dissertation proposes a probabilistic formulation using the Bayesian approach to update the model parameters and reduce the uncertainties as data becomes available. As an example, this dissertation applies the proposed methodology to updates the seismic risk analysis in the HAZUS model using data from the 2016 Kumamoto earthquake in Mashiki, Japan. Three levels of updates (i.e., hazard, vulnerability, and functionality) are applied to the risk analysis models for bridges, potable water infrastructure, and wastewater infrastructure. The proposed methodology enables consistent updates across modeling levels when data becomes available
PacketLab - An internet measurement framework for low-cost vantage point sharing
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Tzu-Bin Yan, accepted the attached license on 2025-04-18 at 08:58.The student, Tzu-Bin Yan, submitted this Dissertation for approval on 2025-04-18 at 09:29.This Dissertation was approved for publication on 2025-04-18 at 10:47.DSpace SAF Submission Ingestion Package generated from Vireo submission #21830 on 2025-10-19 at 19:15:09Vantage point sharing is a common and economical approach by Internet measurement community members to procure proper vantage points for measurement campaigns. Sharing, however, is not frictionless and suffers from three obstacles—lack of vantage point compatibility, low incentives to support new measurements, and varying experimenter trust levels—limiting scale. In this dissertation, we present the PacketLab Internet measurement framework to facilitate vantage point access collaboration among community members. We first describe PacketLab’s three-component design: a universal measurement endpoint interface, a certificate/program-based access control mechanism, and a measurement rendezvous mechanism, along with the design benefits, advantages over other sharing approaches, as well as our implementation of the framework that is readily available to the public. We then present an evaluation of the framework on measurement support, which is critical to the framework’s applicability to the community in accommodating community-interested measurements. To further support experimenters’ efforts in framework adoption, we also present a novel network access virtualization tool, pktwrap, which allows existing, unmodified measurement programs to communicate over a PacketLab vantage point to collect less timing-sensitive data, with partial support for network event delay data collection. With our positive evaluation results, readily available implementation, and a capable virtualization tool, we believe the PacketLab framework is a promising candidate for the Internet measurement community in future collaborative Internet data collection efforts
Shear flow modulates oxidative and nutrient stress in Pseudomonas aeruginosa
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Gilberto Padron, accepted the attached license on 2025-04-22 at 08:56.The student, Gilberto Padron, submitted this Dissertation for approval on 2025-04-22 at 09:03.This Dissertation was approved for publication on 2025-04-22 at 15:04.DSpace SAF Submission Ingestion Package generated from Vireo submission #21881 on 2025-10-19 at 19:15:23Batch cell culture is one of the primary methods used to study bacterial stress responses in traditional laboratory experiments. Batch culture is limited, however, in its ability to consider dynamic features commonly found in natural systems such as shear flow. By using microfluidics and single cell microscopy, I can subject Pseudomonas aeruginosa to flow and chemical stress simultaneously. In batch culture, bacteria are capable of rapidly depleting certain stressors and nutrients. In microfluidic conditions, I demonstrate that cells are unable to deplete stressors or nutrients faster than they can be replenished. Here, I demonstrate that under flow, cells are sensitized to concentrations of the chemical stressor H2O2 100 to 1,000 times lower than in batch culture. I further observed that in nutrient limited conditions, flow can sustain growth at concentrations of glucose 1,000 times lower than in batch. Thus, based on my findings I suggest a shift in the thinking of concentrations required to elicit or alleviate chemical stress. More broadly, I emphasize the need for considering flow to better understand how bacterial pathogens may function in their natural environments
Addressing Behavior Model Inaccuracies for Safe Motion Control in Uncertain Dynamic Environments
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Minjun Sung, accepted the attached license on 2025-04-23 at 16:08.The student, Minjun Sung, submitted this Thesis for approval on 2025-04-23 at 16:16.This Thesis was approved for publication on 2025-04-24 at 16:58.DSpace SAF Submission Ingestion Package generated from Vireo submission #21903 on 2025-10-19 at 19:15:25Uncertainties in the environment and inaccuracies in behavior models critically affect the safety and reliability of autonomous systems in dynamic environment. These inaccuracies compromise the estimation of a dynamic obstacle’s state, leading to biased estimates and shifts in the predicted trajectory distributions. Such prediction errors, if unaddressed, may result in violations of safety constraints and degraded control performance. To address these challenges, we propose a novel framework called SIED-MPC (Simultaneous Input-Estimation and Distributionally robust Model Predictive Control), which unifies Simultaneous State and Input Estimation (SSIE) with Distributionally Robust Model Predictive Control (DR-MPC) through an adaptive model confidence evaluation scheme. Unlike conventional estimation techniques that assume access to accurate behavior models or treat prediction as an isolated module, our SSIE formulation jointly estimates both the obstacle’s state and the input gap—the discrepancy between predicted and actual control inputs—thus correcting for behavior model errors in real-time. This input gap serves as a quantitative proxy for model confidence, which is used to dynamically adjust the size of the ambiguity set in the DR-MPC formulation via a Wasserstein-based uncertainty radius. By integrating this feedback-driven adaptivity into the control pipeline, SIED-MPC systematically accounts for both estimation bias and distributional shift, ensuring safe operation with minimal conservatism. The proposed framework is evaluated in realistic autonomous driving simulations using CARLA. Our method demonstrates superior collision avoidance performance, lower constraint violation rates, and improved computational efficiency
Dynamic imaging of magnetic bioeffects in cells using two-channel two-photon autofluorescence intensity and lifetime microscopy
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Kevin Tan, accepted the attached license on 2025-04-28 at 14:03.The student, Kevin Tan, submitted this Thesis for approval on 2025-04-28 at 16:15.This Thesis was approved for publication on 2025-05-05 at 09:10.DSpace SAF Submission Ingestion Package generated from Vireo submission #21910 on 2025-10-19 at 19:15:26Magnetic fields have long been known to interact with living systems in subtle and often surprising ways. One hypothesis for these effects is the radical pair mechanism which suggests that magnetic fields influence the spin dynamics of redox-active radical pairs, altering the balance of reactive oxygen species (ROS) in cells. These ROS may then initiate signaling and metabolic pathways. In this thesis, a novel two-channel two-photon autofluorescence microscope enabled high-resolution, non-invasive, and simultaneous measurement of autofluorescence intensity and fluorescence lifetime from the metabolic cofactors NAD(P)H and FAD to examine magnetic field effects at the single-cell level. First, A549 lung carcinoma cells were subjected to the redox effects of PEG-SOD and DDC to validate the sensitivity of the microscopy method. While fluorometric assays confirmed altered ROS partitioning, autofluorescence microscopy exhibited limited sensitivity. Next, static magnetic fields ranging from 50 µT to 100 mT were applied for 72 hours. Fluorometric results revealed a significant increase in hydrogen peroxide production in the 0.4–0.8 mT range, consistent with the radical pair mechanism. The autofluorescence microscopy detected subtle changes in fluorescence lifetime features at 0.1 mT, indicating a possible NADPH mediated ROS defense response. Lastly, to probe the dynamics of magnetic bioeffects, a longitudinal imaging protocol including a custom stage-top Helmholtz coil was developed. No statistically significant differences were observed after repeated 2-hour magnetic field exposures, indicating limitations in the sensitivity of the label-free multiphoton imaging. Still, with adjustments, these methods are a promising tool for future investigations of magnetically-induced cellular phenomena