University of Illinois at Chicago
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Me versus Us? Understanding the Role of Personal and Social Motives on Activist Intentions
No full textCurrent social psychological models of activism only consider social identity-based and not personal identity-based motives. Yet, people could be motivated to engage in activism because they want to fulfill needs like being authentic to and consistent with their core personal beliefs more than social identity concerns, such as belonging or group standing. In the current studies, I examine the comparative effects of personal versus social motives on activist intentions using correlational (Study 1; N = 427) and experimental (Study 2; N = 1882) designs. Using reliable measures that assessed the extent to which participants perceive their policy positions as reflective of different identity concerns, the results of Study 1 found that both personal motives and social motives were associated with stronger activist intentions. These associations were consistent across issues of abortion and gun rights. Study 2, however, revealed that when manipulating the salience of different identity motives, it was only when personal motives were made salient, compared to no salience, that activist intentions increased. Taken together, the studies reveal that personal motives are indeed important underpinnings of activist intentions. This suggests that group identity concerns do not always dominate people’s attitudes and political behaviors, but rather that people also have the capacity to act in accordance with their sense of personal and moral authenticity
Intelligent Salivary Biosensors for Systemic Disease Risk Prediction
No full textThe mouth is said to be the mirror to health, but how can health be assessed? With the COVID era, saliva has become the most promising biofluid for disease testing due to its non-invasiveness and its ability to reflect the disease markers as we see in blood. One of the ways to know about overall health is to start with an oral disease and find a linkage to the systemic disease so that the systemic disease’s underlying issues, like oxidative stress, can be detected. The use of non-protein molecules that could be used as biomarkers, with electrochemistry and machine learning models gave an insight to the oxidative stress aspect. As a proof of concept, the oxidative stress and periodontal biomarker Matrix Metallo Proteinase 9 (MMP9) and its usefulness for overall health deduction and systemic disease detection or risk of occurrence were looked into. Together with the broad biomarker MMP9, more specific disease biomarkers interleukin 6 (IL6), human cytokeratin fragment antigen 21-1 (CYFRA21-1), and glutathione (GSH) were also tested electrochemically for simulated Diabetes, Oral Cancer, and Stroke like conditions. The Machine learning-based detection of the electrochemical data was developed which will enable a biomolecule level and associated risk to be predicted for the disease occurrence early on, which could prompt a decision to be healthier. Verification of the developed biosensor and machine learning system was done by testing the simulated stroke-like condition in the microglia HMC3 cell line with Lipopolysaccharide (LPS), and antioxidant Glutathione (GSH) was used to check the continuous monitoring possibilities. Validation of the biosensor system was done with volunteer saliva samples. Intelligent salivary biosensor testing in the future can be turned into affordable point-of-care testing at the dentist's office, workplace, home, or remote setting. Having an early prediction of the disease risk will help with better disease management as well as give the patient and their caregivers a better quality of life. The effect of the drugs as a measure of reduction in biomarkers can also be checked using this salivary diagnosis. This early disease prediction or risk prediction will also reduce the healthcare cost and insurance load on society
UAV-Based Ground Penetrating Radar for Structural Health Monitoring of Bridges
No full textBridges are critical components of transportation infrastructure, requiring regular inspection to ensure safety and longevity. Traditional bridge inspection methods, such as visual assessment and contact-based techniques, often suffer from limitations in accessibility, efficiency, and data consistency. This dissertation presents a UAV-based Ground-Penetrating Radar (GPR) system designed for non-destructive evaluation (NDE) of bridge structures, enabling rapid and high-resolution subsurface imaging. The proposed system integrates a lightweight, airborne GPR mounted on an unmanned aerial vehicle (UAV), providing a novel approach to detecting structural anomalies such as rebar corrosion, voids, and delamination in bridge decks
Photoemission Physics of Wide-Bandgap Semiconductors: An Empirical Development in Photocathode Theory
No full textFor photoinjector applications, a photocathode with a low intrinsic emittance (i.e. low emitted beam divergence) and high quantum yield (i.e. number of emitted electrons per absorbed photon) is desired and, implicitly, physical robustness and reasonable cost are also sought after qualities. These properties are material dependent and one class of material that has the potential to satisfy all these conditions is wide-bandgap semiconductors like those used in high power electronics applications. As a result, some of these materials, specifically diamond, gallium oxide (Ga2O3), and gallium nitride (GaN), were evaluated to determine their feasibility as photocathodes.
To that end, a combined theoretic and experimental approach is employed. Specifically, materials were first identified and screened by computationally evaluating their electronic properties using density function theory (DFT) in accordance with predictions made by the (at the time) state-of-the-art photoemission theory. Promising candidates were then procured and subsequently investigated through the use of an ultrafast tunable-UV laser system and DC electron gun. The resulting experimental data, which represents the real photoemission physics that occurred, was then used as an empirical basis to further develop the relevant theories.
None of the investigated materials met the low intrinsic emittance criteria. However, the results obtained through the experimentation have led to the realization of significant new physics in the field of solid-state photoemission devices. In particular, phonon assisted, momentum resonant emission processes (“Franck-Condon Emission”) are a dominant and, potentially, unavoidable aspect of photoemission in many otherwise promising semiconductor photocathodes. Since such processes generally increase intrinsic emittance and since semiconductor photocathodes are ubiquitous in modern photoinjectors, this result has the potential to be of critical importance for the field
Coalition for Growth: The Politics of Chinatown Development in Chicago, New York, and San Francisco
No full textChinatown can be found in almost every major American city, but their development trajectories vary significantly. During the past three decades, while some Chinatowns have achieved consistent economic growth, others have declined in population and commercial activities. What explains the diverse trajectories of Chinatown development? Through a comparative case study of Chinatowns in Chicago, New York, and San Francisco, this dissertation argues that the variation in the trajectory of Chinatown development is contingent upon two major factors, namely, the internal cohesion of Chinatown elites (cohesive versus fragmented) and the political integration of the Chinese community into local politics (strong versus weak). Based on the two dimensions of internal cohesion and political integration, I propose a theoretical framework that categorizes Chinatown development into four ideal types: constrained development, shrinking neighborhood, contested development, and comprehensive development. Chinatown development is conceptualized not solely in terms of economic growth but as the expansion of the community’s collective freedom across three dimensions: economic growth, public goods provision, and social welfare. The findings reveal that the more cohesive Chinatown elites and the stronger the political integration, the more successful the Chinatown development. The typology provides an analytical framework to study the development of Chinatown and other ethnic communities beyond the cases
Exploring Secondary Latinx Dual Language Teacher Experiences via Testimonio and Critical Action Research
No full textSpanish-English Dual Language Bilingual Education (DLBE) programs constitute 80% of the 3,600 DLBE programs in the U.S., reflecting the growing Latinx student population (Galvan, 2022). This expansion necessitates recruiting and supporting skilled bilingual teachers. When well supported, Latinx educators can implement culturally sustaining pedagogies that empower students and strengthen biliteracy. Conversely, inadequate training often leads to the adoption of deficit language ideologies and a content-over-language focus.
This three-phase qualitative study explores these challenges by engaging eight Illinois middle school Latinx DLBE teachers in reflecting on their language learning experiences and collaborating to address internalized language ideologies and their impact on their pedagogical practices. Through a critical action research project, participants redesigned unit plans to integrate language development, critical language awareness, and Spanish language disciplinary literacies into instructional planning for middle school DLBE Math, Science, Social Studies, and Art courses. Findings reveal the importance of addressing the subtractive schooling experiences of pre-service and in-service Latinx secondary DLBE teachers, fostering collaboration among this group of teachers, and providing professional development to prepare secondary Latinx DLBE teachers to integrate critical language awareness, disciplinary literacies, and critical consciousness into their practices
How Do False Alarms, Misses, and Preexisting Beliefs Predict Conservative and Liberal Policy Preferences?
No full textThe present dissertation tested potential ideological differences between conservatives and liberals in false alarm and miss error concerns across policies that offered rewards. A series of three studies tested competing hypotheses, the Asymmetry and Symmetry Hypotheses, which suggested conservative and liberal error concerns depended on individual differences and were contextually stable across policies (asymmetry), or that conservative and liberal error concerns depended on specific policy contexts and corresponded with whether either group preferred a restrictive or permissive policy (symmetry); results support the Symmetry Hypothesis. When conservatives supported a restrictive policy more than liberals, and liberals supported a permissive policy more than conservatives, conservatives were more concerned about false alarms and liberals were more concerned about misses related to the policy (Studies 1A & 2). Additionally, when typical policy preferences flipped and instead conservatives supported a permissive policy more than liberals, and liberals supported a restrictive policy more than conservatives, conservatives were more concerned about misses and liberals were more concerned about false alarms related to the policy (Studies 1B & 2). Together, these studies offered initial evidence that error concerns partially explain support for policies that offer rewards, and ideological differences in error concerns result from the type of policy one supports, rather than individual differences; this work has implications for work on political cognition and motivation
Racial/ethnic Differences in Expanded ACEs: Differential Item Analysis Using the Rasch Model
No full textBackground: Adverse childhood experiences (ACEs) are associated with poor health outcomes and risky health-related behaviors. There are numerous measures of adverse childhood experiences and findings to date have varied across studies. No item-by-item analysis has been conducted to determine how likely it is for individuals from distinct groups, who possess similar abilities, to respond differently to items on the Philadelphia (PHL) ACEs Survey created by Cronholm et al. (2015).
Objectives: To determine whether there is measurement invariance in conventional and community-level ACEs items on the PHL ACEs Survey in non-Hispanic Black, non-Hispanic White, and Hispanic adults.
Methods: Participants aged 18-34 were recruited via ResearchMatch. Participants completed demographic items and the Philadelphia ACEs Survey on REDCap. A differential item functioning (DIF) analysis was completed using a Rasch model, DIF contrast values were identified, and a Mantel-Haenszel test was completed with a Benjamini and Hochberg adjustment to identify DIF.
Results: The sample (N=144) was roughly one third Black, one third Hispanic and one third White adults. Two conventional ACE items exhibited differential item functioning: 1) Did you live with anyone who was suicidal? was easier for Hispanic adults to endorse than Black adults; 2) Did you live with anyone who served time or was sentenced to serve time in a prison, jail, or other correctional facility? was easier for Black adults to endorse than Hispanic adults. One community ACE item: How often did you feel that you were treated badly or unfairly because of your race or ethnicity? was easier for Black adults to endorse than Hispanic and White adults.
Conclusion: This is the first study in which a DIF analysis was conducted on the Philadelphia ACEs Survey to examine measurement invariance in Black, White and Hispanic adults. While most items functioned in the same way across groups, three items performed differently between groups. Due to the historical and ongoing systemic racism in the United States, the items that showed DIF (discrimination, suicidal household member and incarcerated household member) can most likely be classified as benign DIF (true differences) which does not impact measurement quality
It's Something You Have to Work for: Preservice Teacher Enactment of Culturally Sustaining Pedagogy
No full textThe extensive and varied benefits of culturally sustaining pedagogies (CSP)* have been supported by numerous empirical studies (Aronson & Laughter, 2016); further, this approach is undergirded by historic models of education (Muhammad, 2020) and answers ethical questions about how students should be educated (Gay, 2002). However, for this potential to be realized, preservice teachers (PSTs) need to understand culturally sustaining pedagogies while bridging theory to practice by instantiating CSP through their daily practice. The purpose of this qualitative case study was to (1) explore the factors that preservice teachers felt contributed to their understanding and development of CSP; (2) examine how preservice teachers enact CSP through lesson planning; and (3) inquire into how preservice teachers describe the relationship between CSP and lesson planning. This study was conducted at a public, urban, minority-serving university; 22 preservice teachers in their third year of an undergraduate elementary teacher preparation program were the participants. The data sources included PSTs’ lesson plans and individual interviews.
Preservice teachers described a variety of factors that contributed to their understanding and development of CSP; the way they leveraged and described those factors demonstrated six unique patterns. Three types of experiences were frequently discussed as contributing factors: classroom placements, teacher education, and PSTs’ schooling experiences. The complexity of planning for shared elements of identity versus a variety of identities emerged as a question and challenge for PSTs; this issue was particularly salient when PSTs considered planning for a component of identity that was not their own. This study examined artifacts of practice (lesson plans) to see not only if key elements of CSP were present but how they emerged in teacher practice; specific patterns were found for each element. There is a significant gap between the ample evidence of CSP enactment in PSTs’ lesson plans and the ways they self-assess or describe their enactment using limited evidence that focused primarily on identity. Preservice teachers expressed a strong sense of alignment and commitment to CSP and self-evaluated their lesson plans in ways that were generally positive but significantly underrepresented the complexity and depth of the ways they were enacting CSP.
*Note: As described in the literature review, for this work, CSP is used as a term that encompasses multiple asset pedagogies such as culturally relevant education, culturally responsive teaching, culturally and historically responsive education, and others
Guided Policy Gradient for Dynamic Treatment Plan Prediction with Symptom Burden in Head and Neck Cancer
No full textHead and Neck Cancer (HNC) accounts for approximately 3–4% of all cancers worldwide, affecting regions such as the lips, tongue, throat, larynx, nose, and salivary glands. The primary risk factors for HNC include excessive tobacco and alcohol consumption or infection with Human Papillomavirus (HPV). Treatment typically follows a sequential three-stage approach, beginning with Definitive Surgery (DS), followed by Inductive Chemotherapy (IC), and concluding with either Radiotherapy (RT) alone or Radiotherapy with Concurrent Chemotherapy (RT/CC). However, treatment plans are highly patient-specific, and specific steps may be omitted based on the patient's condition and multidisciplinary medical decisions.
Determining an optimal Dynamic Treatment Regime (DTR) requires extensive collaboration among specialists, often involving multiple iterations to reach a consensus. To address this challenge, this study proposes a Deep Reinforcement Learning (DRL) framework to automate DTR planning by leveraging historical patient data. Using guided Policy Gradient (PG) methodologies, two approaches—Regularization and Fine Tuning—were explored, with the Behavior Cloning (BC) model serving as the guiding framework. Guidance ensures that the DRL models align with clinical decisions by penalizing deviations only when significant discrepancies occur.
This study utilizes data from 676 patients diagnosed with HNC, all receiving at least a radiation therapy (RT) at MD Anderson Cancer Center (MDACC) between 2010 and 2021. This data consists of patients' medical records and includes clinical, diagnostic, treatment-related, and patient-reported scores (PRS) information. The data was de-identified and collected at the University of Texas under Institutional IRBs and transferred to the University of Illinois Chicago (UIC) under a Material Transfer Agreement. As per the notice of determination of human subject research by the UIC Office for the Protection of Research Subjects, this dataset does not meet the definition of human subject research at UIC.
Further, different variations of the original dataset were created to analyze the impact of PRS on symptoms such as fatigue, pain, and nausea. These include:
A dataset where PRS was excluded before determining any treatment.
A modified dataset where individual PRS values were replaced with high- or low-burden clusters using the Symptom Burden Model (SBM) API was developed at the University of Iowa.
Therefore, this study presents a comprehensive analysis of DRL-based DTR models trained on all datasets, demonstrating the potential of DRL in optimizing personalized HNC treatment plans while reducing the need for extensive manual decision-making
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