UC Irvine

Digital markets are built on data, low-friction access, and user trust. This dissertation studies what happens when each of these pillars is disrupted. Across three essays, it shows that privacy regulation, registration-based access barriers, and public revelations of workplace misconduct can materially alter consumer purchasing, attention allocation, and platform choice. The first essay examines the unintended consequences of the California Consumer Privacy Act (CCPA) for consumer commerce. Using the CCPA as a natural experiment and combining billions of payment transactions with browsing data and firm-level measures of advertising technologies, the essay shows that Californians purchased less, returned more, and spent more time browsing after the law took effect. Firms subject to the regulation also reduced their use of ad-related technologies. These findings suggest that stronger privacy protections may unintentionally weaken personalization and product-consumer matching, reducing commercial activity even as they expand consumers' control over personal data. The second essay studies the New York Times' introduction of a registration wall as a first-party data collection strategy. Using web browsing data together with a regional measure of privacy salience based on cumulative exposure to data breaches, the essay finds that registration walls generate heterogeneous responses across user segments. News-singlehomers reduce engagement after the wall is introduced, whereas news-multihomers slightly increase engagement. Higher privacy salience attenuates the decline among singlehomers and strengthens the positive response among multihomers. When users disengage, their attention shifts primarily toward search engines and video-sharing platforms, revealing broader ecosystem consequences of registration-based access barriers for news consumption. The third essay investigates how public whistleblowing about workplace sexual harassment and discrimination affects consumer demand in platform competition. Exploiting a blog post by a former Uber employee describing sexual harassment, discrimination, and the company’s response—an account that quickly went viral on social media—as an exogenous reputational shock, the essay shows that Uber usage declines while Lyft usage rises among riders most able to switch between the two platforms. These effects are strongest in markets with greater local attention to the event and among riders predicted to be female, highlighting how misconduct toward minorities can translate into meaningful demand-side consequences in consumer markets. Taken together, the three essays demonstrate that consumer behavior in digital markets is shaped not only by prices and product attributes, but also by data governance, access design, and corporate legitimacy. The dissertation contributes to research on privacy regulation, digital media monetization, and platform competition, while offering practical implications for firms and policymakers seeking to balance personalization, access, and accountability in the digital economy.

English academic writing is a critical yet challenging skill for learners in English as a Foreign Language (EFL) contexts. The rapid integration of digital tools, accelerated by the COVID-19 pandemic, has transformed writing instruction; however, evidence of its pedagogical effectiveness remains fragmented and often overlooks teacher perceptions and genre-specific impacts. This three-study dissertation addresses these gaps by investigating the role of digital tools in EFL writing instruction within the EFL higher education context, employing a multi-method approach to triangulate evidence from student outcomes, meta-analytic synthesis, and teacher experiences.Study 1 conducted a classroom experiment with 111 Chinese undergraduates, comparing infographic-based pre-writing to traditional outlining. Results showed that infographic creation significantly improved summary-writing quality, source use, and self-efficacy, but not opinion writing, highlighting the genre-sensitive nature of tool effectiveness.Study 2 synthesized 17 experimental and quasi-experimental studies (N = 1,085) through a meta-analysis. It found a statistically significant, moderate overall effect favoring web-based collaborative writing (WBCW) over non-technological collaboration on writing quality (Hedges’ *g* = 0.51). Moderator analyses indicated that training was a significant factor enhancing outcomes.Study 3 explored the perceptions of seven Chinese university writing instructors through qualitative interviews. Grounded in the TPACK framework, the findings revealed that while digital tools are deeply embedded in instruction, their use is shaped by teachers' knowledge, institutional support, and access. Teachers exhibited cautious and limited integration of emerging Generative Artificial Intelligence (GenAI) tools due to concerns over academic integrity and a lack of institutional guidance.Collectively, the findings demonstrate that technology enhances EFL academic writing most effectively when tools are aligned with genre demands, collaboration is scaffolded by design and training, and implementation is supported by teacher knowledge and institutional context. The dissertation concludes by advocating for a situated, tool-genre-task alignment perspective in future research and practice, moving beyond technocentric adoption to support equitable and effective writing instruction in diverse EFL settings.

Self-renewing hematopoietic stem cells (HSCs) produce billions of blood cells a day to maintain peripheral blood and immune cells in circulation. Inflammation can alter the balance of steady-state hematopoiesis, and disrupted hematopoiesis can lead to blood disorders or cancers. Over a lifetime of cell divisions, HSCs may acquire somatic mutations that provide a competitive advantage over their wild-type counterparts. The clonal expansion of a mutant HSC population is termed “clonal hematopoiesis” (CH). CH is linked to an increased overall risk of mortality due to incidences of cardiovascular disease and transformation into hematological malignancy. Tobacco and nicotine use remain the leading preventable drivers of cancer risk, and both direct and secondhand exposure to combustible cigarettes or electronic nicotine devices perturbs immune function and hematopoiesis. The World Health Organization estimates more than 100 million people across the world are using electronic cigarettes, or e-cigarettes, but the health impacts of these “safer” e-cigarette alternative have yet to be fully elucidated. E-cigarettes have been associated with inflammation and oxidative stress, which can provide selective pressures for the outgrowth of CHIP mutant cells.Here, we evaluate the impact of e-cigarette vapor and combustible cigarette smoke on in vitro cell inflammatory responses and in vivo long-term hematopoietic differentiation. The overarching goal of this project was to understand further how an inflammatory lifestyle stressor, such as smoking, contributes to aberrant hematopoiesis in wild-type normal stem cells, Tet2- deficient cells, and JAK2V617F mutant cells. In cell-based studies, cigarette smoke extract (CSE) and e-cigarette vapor extract (EVE) consistently suppress LPS-induced TNF-α secretion across macrophage/monocyte models, including primary mouse and human cells and complementary cell lines, indicating a reproducible immunosuppressive effect on mature myeloid cells. To assess consequences of smoking behavior in vivo, we used a custom nose-cone inhalation system to deliver controlled exposures to combustible cigarette smoke or e-cigarette aerosol to mice. Chronic exposure increased myeloid proliferation, a hallmark of HSC aging. Taken together, these results support a model in which tobacco exposures blunt innate immune responsiveness while simultaneously driving myeloid expansion conditions that accelerate hematopoietic aging and promote the expansion of mutant hematopoietic cells.

The distributed training of machine learning models via gradient descent is generally conducted by iteratively computing the local gradients of a loss function and aggregating them across all processors. Communicating these gradients during aggregation is often a major cost but sparsification techniques can greatly improve efficiency. One such technique, Top-k gradient compression, ensures that only the k largest components of each local gradient are sent. However, effectively scaling this method can be challenging. The standard ring AllReduce algorithm, which is frequently used to aggregate dense gradients, lacks a counterpart that is optimized for sparse data. Notably, ring algorithms are contention-free, which generally make them easier to scale than other collective communication algorithms. Thus, in practice, the ring AllGather algorithm, which can be trivially adapted for sparse data, may be used instead, even though its bandwidth costs are proportional to the number of utilized processors (unlike ring AllReduce). To provide a more scalable contention-free alternative, we present a variant of ring AllReduce that has been better optimized for sparse data. We compare it to the standard dense ring AllReduce and ring AllGather algorithms, and we evaluate it empirically using gradients sampled from fine-tuning Llama 2 7b.

One-dimensional (1D) and quasi-1D (q-1D) van der Waals (vdW) materials, which have strong bonding along only one crystallographic axis, have emerged as powerful class of solids that hosts novel electronic, optical, and quantum properties useful for next-generation electronics. These materials can, in theory, be thinned to the angstrom scale due to the ideal vdW surfaces along two axes. In practice, achieving atomically precise single chains of these materials poses a significant challenge, as conventional top-down exfoliation and bottom-up growth techniques consistently retain interchain bonding, especially in q-1D materials with anisotropic interchain bonding motifs. The question then arises: Is there a synthetic approach that would enable the suppression of all inter-chain interactions, leaving only intra-chain covalent bonding in one dimension? Using the model q-1D pnictogen chalcogenides (Pn2Ch3; Pn = Sb, Bi; Ch = S, Se, Te), chosen for the highly anisotropic structural complexity and strong inter-chain bonding combined with distinct photophysical properties, we explore encapsulation within ultranarrow nanotube growth templates to precisely define the growth of the material in sub-nanometer length scales. The deployment of these nanotube templates as encapsulants overcomes the inter-chain interactions in these phases to isolate single q-1D chains by affording physical space that directly matches the size of a single chain. More importantly, we can also probe many chains simultaneously in a collective using conventional spectroscopic techniques used in ensemble samples, allowing us to access nanoscale properties through bulk measurements. Herein, not only do we gain insight into structural and electronic properties of these single chains, but we also further our understanding of anisotropic bonding in the bulk structure by understanding how it affects single chain accessibility. As technological devices advance through shrinking and densification, understanding material properties at the atomic limit becomes increasingly vital. Our results demonstrate a powerful tool for synthesizing and studying precisely defined single inorganic chains that approach the atomic limit.

Bacillus subtilis (B. subtilis) spores present unique opportunities for practical application due to their genetic tractability, generally regarded as safe (GRAS) status, and extreme stress tolerance. By engineering the surface of B. subtilis spores, researchers have been able to display active enzymes, antigens, and protein-protein interaction motifs for myriad applications. However, traditional techniques resulted in relatively low protein expression (102-104 proteins/spore), limiting utility. Chapter 2 begins by leveraging a high-density spore display strategy developed in the lab called TIED to arrive at stimuli-responsive biomaterials. B. subtilis spores displaying a high density of pH-responsive protein-protein interaction motifs, referred to simply as “A”, displayed pH-responsive erosion stability by remaining stable at low pH, when A-A interactions are occurring, and disassociating at high pH when A is known to disassociate. Compared to wild-type spores and spores displaying a low-density of A on the spore surface, stability was significantly improved. This highlights the utility of TIED high-density spore display in achieving more pronounced engineered behaviors, while also showing the limitations of weak non-covalent protein-protein interaction motifs to achieve biomaterials - the mechanical properties remained unchanged with different pH’s despite the extent of A-A interactions changing. Chapter 3 represents an improvement to TIED itself. TIED requires genetically engineering each new B. subtilis strain from scratch to display a new protein of interest. This is an arduous multi-step process that requires empirical optimization of each new construct. Chapter 3 describes a new strategy utilizing the SpyTag/SpyCatcher and SnoopTag/SnoopCatcher protein-peptide pairs. When mixed together, SpyTag and SpyCatcher rapidly and irreversibly form a covalent isopeptide bond in what can be considered a biomolecular “click” chemistry reaction. TIED-Click spores displaying a high density of SpyCatcher and/or SnoopCatcher were created, tested, and were utilized to display three enzymes – galactose oxidase, APEX2, and carbonic anhydrase. TIED-Click displaying APEX2 showed improved stability over the previously used high-density display strategy, and TIED-Click displaying galactose oxidase were reused daily for catalysis for over one week with no detectable loss in activity. TIED-Click spores co-displaying galactose oxidase and APEX2 were successfully used in facile tandem catalysis, and showed improved activity over a mixture of spores individually displaying each enzyme. To demonstrate that the strategy can enable facile display of new enzymes, the system was used to display carbonic anhydrase, an enzyme previously unknown to B. subtilis spore display. In each case, display of a new enzyme or multiple enzymes required only the expression and purification of the target enzyme in E. coli. As a further proof-of-concept, direct enzyme immobilization from E. coli lysate expressing galactose oxidase was achieved, although the method was not generalizable to other enzymes, and required significant optimization.

Alzheimer’s Disease (AD) is one of the most prevalent neurodegenerative diseases. It’s estimated that by 2060 there will be 13.8 million people aged 65 and older with AD (Alzheimer’s Association, 2025). Neurodegeneration is a primary pathological feature of late-stage Alzheimer’s Disease (AD), including dendritic atrophy, axonal destabilization and neuronal death yet mechanisms are not well understood. Early in disease onset, AD is primarily characterized by the accumulation of extracellular amyloid beta (Aß) plaques and intracellular neurofibrillary tangles in neurons. The prevailing hypothesis, “amyloid hypothesis,” driving the field has been that neuronal dysfunction and degeneration are driven by extracellular Aß in one form or another. New antibody treatments that target Aß have been approved by the FDA, but so far, these result in only mild delays in cognitive impairment, have potentially serious side effects, and may not delay neurodegeneration. Accordingly, there is a major un-met need to identify mechanisms underlying neurodegeneration and identify potential interventions to slow down its rate and progression. In chapter 2, we validate a method for labeling and tracking neurodegeneration in a mouse model of AD. In chapter 3, we test whether Adeno-associated Virus (AAV)-based interventions that activate the AKT/Mechanistic target of Rapamycin (mTOR) pathway are a potential therapeutic target for promoting neuronal survival. In chapter 4, we assess whether mTOR activation, via PTEN deletion, in corticospinal neurons (CSNs) delays motor deficits in AD.

This dissertation examines two forms of redox-controlled reactivity. First, bio-inspired organic carriers for carbon capture are examined (Chapters 1–3). Second, studies of alkene conversion methods using cobalt catalysis are described (Chapters 4–6).Chapter 1 traces quinone and flavin chemistry from their biological roles as membrane and cofactor electron carriers to synthetic redox carriers for electrochemical carbon capture, and develops the thermodynamic framework that connects reduction potential, hydrogen bonding, and CO₂ or proton affinity. Chapter 2 applies this framework to hydroxymethylated benzoquinones (HMQ A–D), designed so that a flexible proximal hydroxymethyl group can hydrogen-bond to the reduced quinone without blocking the site of CO₂ attack. In the MQ → MMQ → HMQ A control series, computed reduction free energies separate the inductive contribution of the ether oxygen from the hydrogen-bonding contribution of the hydroxymethyl donor. The inductive increment is nearly identical for both reductions, whereas the hydrogenbonding increment more than doubles at the dianion. Crystallography shows the donor engaged intermolecularly in the neutral solid, while conformer calculations show that folded, intramolecularly hydrogen-bonded dianions may dominate in solution. ¹H and ¹³C NMR spectroscopy identify an aryl-carbonate CO₂ adduct, and Benesi–Hildebrand analysis of spectrophotometric titrations gives log KCO2 = 3.34 for HMQ A. Chlorination shifts the reductions anodically by up to 250 mV while CO₂ binding remains substantial (log KCO2 = 3.1– 3.3 for HMQ B–D), and TD-DFT calculations assign the spectra of the oxidized, dianion, and CO₂-bound states, connecting the redox shifts to stabilization of the redox-active π* orbital. Positioned hydrogen-bond donors and electron-withdrawing substituents together are observed to mitigate the trade-off between reduction potential and CO₂ affinity that constrains quinone-based capture.Chapter 3 extends the design question to water with flavin derivatives, where the design relies on proton transfer, not on direct CO₂ binding. Three water-soluble N10-aryl flavins bearing anionic (Fl-1) or cationic (Fl-2, Fl-3) side chains were characterized across five oxidation and protonation states by voltammetry, Pourbaix analysis, spectroelectrochemistry, pulse radiolysis, and TD-DFT. In buffered pH 7 electrolyte the two-electron potentials of all three fall within 10 mV, showing that a remote solvated charge is a weak handle on flavin potential, while the pendant hydroxyl of Fl-3 lowers the hydroquinone pKₐ from ~7.1 to 6.4 and thereby sets the proton-uptake window. Pulse radiolysis resolved the neutral and anionic semiquinone spectra that electrolysis cannot accumulate. Bulk electrolysis of Fl-2 and Fl-3 in CO₂-containing electrolyte raised the solution pH by 2.1 units for Fl-2 and 3.5 units for Fl-3, and headspace CO₂ fell on reduction and recovered on reoxidation. At 63–80 mM solubility, and with the release half of the cycle not quantified, Fl-2 and Fl-3 serve as mechanistic probes, not as candidate mediators.Chapters 4–6 turn to cobalt-hydride-mediated alkene chemistry, where oxidation-state control directs carbon-centered reactivity. Chapter 4 reviews metal-hydride hydrogen-atom transfer (MHAT) and oxidative radical–polar crossover, the sequence that converts an alkene into a carbocation equivalent under mild conditions. Chapter 5 describes cobalt(II)-salencatalyzed hydroazolation and Markovnikov hydration of alkenes; H₂¹⁸O labeling studies established water as the dominant oxygen source in THF, and the survey of catalysts and substrates located the central limitation in substrate-dependent stereocontrol of intermolecular capture, not in water incorporation. Chapter 6 develops a cobalt-catalyzed oxidative Grob fragmentation that converts cyclic homoallylic alcohols into acyclic alkene-containing ketones without a pre-installed leaving group, in ¹H NMR yields up to 73%. Component controls, an intact cyclopropyl radical clock, and the water-suppressed side chemistry of a dioxolane substrate support a shared cationic pathway after oxidation, with a second MHAT at the product alkene as the principal competing pathway.Across both halves of this dissertation, the redox state of a molecule, set electrochemically at an electrode or chemically by a catalyst, is the control element that turns weak, reversible interactions into selective bond formation, whether the electrophile is CO₂ approaching a quinone dianion or a carbocation completing a fragmentation.

Background: Colorectal cancer (CRC) is a major health problem globally. Among older adults, the burden is particularly substantial, yet there is a lack of evidence comparing clinical presentation, comorbidity burden, and treatment patterns between older-onset colorectal cancer (OLDCRC) and late-onset colorectal cancer (LOCRC).Methods: This study used electronic health record (EHR) data from the University of California Health Data Warehouse (UCHDW). Late-onset CRC patients (50–74 years) and older CRC patients (75–90 years) were identified and matched at a 1:2 ratio based on gender, year of diagnosis, and UCHDW enrollment duration before cancer diagnosis. A secondary 1:2 matched cohort compared older CRC patients to individuals without CRC (NOCRC). Demographic characteristics, tumor location, comorbidity profiles, diagnostic and surgical procedures, and treatment patterns were compared using descriptive statistics and chi-square tests. A loglinear regression was performed to evaluate the association between age cohort and acute clinical presentation, using emergency room visits and inpatient admissions as proxies. Results: Compared with late-onset CRC patients, older CRC patients had a greater burden of several age-related comorbidities but were less likely to undergo diagnostic screening and cancer treatment. Compared with patients without CRC, older CRC patients demonstrated a greater utilization of CRC-related diagnostic screenings. Although no significant difference in acute healthcare utilization was observed between age cohorts after adjusting for comorbidities, several chronic comorbidities, including type II diabetes, obesity, hypertension, hyperlipidemia, myocardial infarction, and stroke were independently associated with increased healthcare utilization, highlighting the importance of overall medical complexity rather than CRC age alone. Conclusion: Older adults with CRC exhibit distinct epidemiologic and clinical characteristics compared with patients with late-onset CRC. These findings improve understanding of CRC in older adults and provide real-world evidence to support more age-appropriate screening, diagnostic evaluation, and treatments.

Wildland firefighters experience intermittent and spatially variable particulate matter (PM) exposure during wildfire and prescribed-fire operations, yet current smoke-monitoring systems are not designed to measure worker-scale exposure at the fire line. Regional monitors, satellite aerosol optical depth (AOD), smoke-plume products, and community sensor networks provide important context but cannot consistently resolve near-breathing-zone exposure or determine when respiratory protection is most needed. This dissertation addresses this gap through three linked studies spanning regional smoke assessment, sensor calibration, and wearable field monitoring.First, satellite AOD and surface PM2.5 were evaluated during two coastal California wildfires under contrasting transport conditions. The Mountain Fire occurred during Santa Ana-type offshore flow, whereas the Gifford Fire occurred under onshore marine-boundary-layer conditions. Column-surface coupling depended on boundary-layer structure, transport, topography, and monitor location. During the Mountain Fire, AOD correlated with combined frontside PM2.5 (Spearman ρ = 0.565, p = 0.012), whereas the Gifford Fire showed weaker, non-significant coupling despite higher fire-window AOD. AOD-only models had limited predictive value, but model skill improved when meteorological and smoke-context variables were included.Second, a dynamic cross-sensor calibration approach was developed for low-cost PM1.0 monitoring using an SPS30 optical particle counter and the blue-channel response of an ADPD188BI photometric sensor. Monodisperse polystyrene latex (PSL) sphere and combustion-aerosol experiments showed source- and size-dependent sensor responses. The ADPD188BI-toSPS30 response ratio predicted source-specific calibration behavior (R² = 0.9469) and was used to adjust PM1.0 estimates toward gravimetric-equivalent measurements. The dynamic calibration reduced root mean square error (RMSE) from 783.79 to 121.49 µg/m³, corresponding to an 84.5% reduction in error.Third, a system containing both the dynamically calibrated wearable PM1.0 sensor and an air-purifying respirator with a pressure sensor was evaluated during prescribed-burn operations. The system combined real-time PM1.0 monitoring with in-mask pressure sensing to identify respirator wear periods. Corrected field profiles showed shift-average PM1.0 concentrations of 62.0-151.8 µg/m³ and peaks of 5,930.9-10,148.8 µg/m³. Across pilot burn-day data, APR wear time was strongly associated with estimated PM1.0 reduction (R² = 0.70), with a median reduction of 48 ± 19% corresponding to APR wear time of 40 ± 33 min, or approximately 14% of the burn shift. Together, these studies show that calibrated, wearable, near-breathing-zone PM monitoring can improve upon regional monitoring by providing higher temporal resolution, identifying shortduration high-exposure periods, and alerting wildland firefighters when PM levels are elevated, thereby supporting timely respirator use when most needed and reducing particulate matter exposure.