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.

This thesis presents two projects focused on the use of polymers to fabricate next-generation sustainable materials and direct the assembly of nanoparticles into ordered architectures. Chapter 1 introduces a brief history of polymer plastic materials, current methods of creating sustainable materials as poly(olefin) replacements, and introduces poly(silyl ether) as a chemically recyclable alternative to traditional poly(olefin) plastics. This chapter also introduces amphiphilic block copolymers as building blocks in the directed assemblies of nanoparticles.Petroleum-derived poly(olefin) plastics produce millions of tons of waste every year, with most waste accumulating in landfills and the natural environment at their end of life. This linear polymer economy encourages and demands new plastic materials to constantly be made to replace those that have been landfilled, ultimately leading to more plastic waste accumulation. Chapter 2 of this thesis presents the synthesis of linear poly(silyl ether) through step-growth and ring-opening metathesis polymerization methods to yield a chemically recyclable material similar to poly(ethylene). A variety of silane monomers and aliphatic diols of varying lengths were synthesized and polymerized, with ring-opening metathesis polymerization yielding polymers with the highest molecular weights.Chapter 3 motivates a different use of organic polymers in materials: the use of amphiphilic block copolymers to direct the assembly of nanoparticles. Nanoparticle organization is a major goal of bottom-up assembly, as these materials can offer emergent properties useful in applications such as sensing and electronics. We report the assembly of CdSe/CdS core/shell quantum dots into highly ordered spherical lattice structures with tunable inter-quantum dot spacing using solvent-induced assembly of poly(styrene)-block-poly(acrylic acid). We prove a spontaneous ligand exchange mechanism between quantum dot ligands and poly(acrylic acid) to result in the precise interparticle spacing observed through electron microscopy and 3D cryo-tomography reconstruction. Small-angle X-ray scattering proves spontaneous ligand exchange occurs over a range of polymer molecular weights, affording tunable interparticle spacings through polymer molecular weight.Finally, Chapter 4 presents the polymer-directed assembly of metallic gold nanoparticles. Using the same poly(styrene)-block-poly(acrylic acid) and solvent-induced self-assembly conditions as in Chapter 3, gold nanoparticles were observed to assemble into hollow, spherical architectures within the polymer colloid. This is hypothesized to be caused by pi-pi interactions between the poly(styrene) ligand on the surface of the gold nanoparticles and the poly(styrene) block of the copolymer forming pseudo-amphiphilic ligands on the gold nanoparticle surface. Transmission electron microscopy and electron tomography indicate a high level of organization in this architecture. Small-angle X-ray scattering proves a precise interparticle spacing between gold nanoparticles that increases with polymer ligand size.This thesis summarizes advancements towards sustainable polymer materials as well as generalizable methods for polymer-directed nanoparticle organization. Step-growth and ring-opening metathesis polymerization methods between different silane and aliphatic co-monomers afforded linear poly(silyl ether), which offers promise towards a circular polymer economy as a chemically recyclable alternative to non-degradable poly(ethylene). Using non-specific chemical interactions between nanoparticle ligands and organic, amphiphilic block copolymers, high levels of nanoparticle organization with tunable interparticle spacing was achieved across multiple types of nanoparticles. This method offers promise as a generalizable, “bottom-up” method to achieving nanoparticle organization.

Enhancer-driven adeno-associated viral (AAV) reporters provide compact tools for targeting genetically defined neuronal populations, but their behavior in aging and Alzheimer's disease model contexts remains uncertain. This thesis evaluated four enhancer-AAV reporter datasets in young wild-type, aged wild-type, and 5xFAD mice: BiCHATe27 for cholinergic neurons, BiPVe3 for PV basket cells, BiPVe4 for PV chandelier cells, and BiSSTe4 for SST Martinotti cells. Cleared brain tissue was imaged by light-sheet microscopy and analyzed within paper-matched regions of interest. Reporter-marker specificity, sensitivity, reporter intensity, and raw cell-count burden were interpreted as descriptive pilot readouts. Corrected BiCHATe27 ChAT analysis, driven by marker-appropriate image-analysis changes rather than by a new imaging modality, restored young wild-type targeting estimates close to the AAV toolbox reference and suggested broadly stable targeting with reduced signal burden in aged and 5xFAD samples. BiPVe3, BiPVe4, and BiSSTe4 showed lower or more variable targeting, including scan-quality and ROI-sensitivity effects. Whole-section pathology images added tissue context but were not used for specificity, sensitivity, or plaque-proximity calculations. Overall, the dataset supports a cautious cell-type/subtype-dependent model that requires manual counting, atlas registration, direct amyloid-pathology assessment, and chromatin-accessibility validation before stronger disease-level interpretation.

Environmental contamination is unevenly distributed across communities in the United States, reflecting historical and ongoing patterns of structural racism, industrial siting, infrastructure investment, and regulatory protection. Per- and polyfluoroalkyl substances (PFAS), lead, arsenic, and other persistent contaminants may therefore be encountered within broader place-based conditions that shape exposure and health. This dissertation used a riskscape-informed environmental justice framework to examine environmental burden across three analytic scales: U.S. counties, individuals residing in Orange County, California, and residential properties near a secondary lead-smelting facility in the City of Industry, California. The conceptual model situates structural racism as an upstream determinant of differential environmental conditions and exposures, while incorporating biological vulnerability as a pathway through which cumulative stress may alter chemical-health associations.Aim 1 examined associations between PFAS concentrations in public drinking water and all-cause and cause-specific mortality at the county level. All-cause mortality associations were generally null. Cause-specific estimates varied by PFAS compound, mortality definition, and exposure operationalization. PFHpA was positively associated with cerebrovascular mortality in continuous models, and PFHxS was positively associated with skin-cancer mortality in both continuous and detection-based models. Several inverse associations were also observed, particularly for PFHpA and cardiovascular, cancer, and metabolic outcomes. These inverse estimates were not interpreted as protective effects because residual geographic confounding, exposure and outcome misclassification, competing risks, and survival or selection processes could not be distinguished in an ecological design.Aim 2 used data from the Orange County site of the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Multi-Site Study to assess serum PFAS, lipid outcomes, and effect modification by the Environmental Justice Index. Most crude PFAS-lipid associations weakened after covariate adjustment. PFUnDA detection remained associated with higher high-density lipoprotein cholesterol after Bonferroni correction. MeFOSAA detection showed evidence of interaction with selected Environmental Justice Index measures: its association with prevalent high cholesterol was stronger in lower-burden settings and attenuated in higher-burden settings. This exploratory finding did not support a simple cumulative-burden amplification hypothesis and requires replication with larger samples and source-specific exposure data.Aim 3 partnered with Environmental Justice San Gabriel Valley to characterize metals in residential-yard soil near the Ecobat secondary lead-smelting facility. Sampling at 136 properties produced 369 soil samples. Lead concentrations declined with distance from the facility, and elevated concentrations clustered nearby. Although the study could not establish source attribution, 25.2% of samples exceeded the U.S. Environmental Protection Agency’s 2024 recommended residential soil-lead screening level of 200 mg/kg. Together, the findings show that environmental health research benefits from examining exposure within place-based social and environmental context. The dissertation supports cumulative-impact approaches that combine direct monitoring, attention to exposure pathways, and meaningful community participation.

Engineered stone (ES) is a composite material consisting of crystalline silica, pigment, and binding resins, and has become one of the most common materials used in kitchen and bathroom countertops, alongside natural stones such as marble and granite. The rise in popularity of ES in countertops is due to its low maintenance and customizable design; however, fabricating ES countertops generates respirable particles that pose an occupational inhalation hazard to workers. ES particle exposure has been linked to silicosis, a progressive and irreversible fibrotic lung disease resulting from inhalation of crystalline silica. When silica reaches the alveoli, macrophages attempt to clear the particles through phagocytosis while initiating inflammatory responses. Persistent inflammation and cellular injury can promote fibroblasts activation and collagen production, contributing to lung fibrosis. Few studies examine how silica content in ES influences the development of silicosis. This study aims to address this gap by utilizing an in vitro respiratory model to examine cellular responses after exposure to ES particles with varying silica content and to investigate mechanisms relevant to ES-related silicosis.An in vitro co-culture system consisting of three rat cell lines, REL-6TN alveolar type II (AT2) cells, NR8383 alveolar macrophages, and RFL-6 alveolar fibroblasts, were used in this study to mimic aspects of the lung microenvironment. This model was assembled in a Transwell system, with AT2 cells and macrophages in the apical compartment and fibroblasts in the basolateral compartment. Particles generated from four commercially available ES slabs with low (< 40%; sample A and B) or high (> 40%; samples C and D) silica content, along with pure silica (Min-U-Sil 5), were used for exposure. AT2 cells and macrophages were exposed at 0, 1, 2.5, and 5 µg/cm2 via an air-liquid interface (ALI) system. Particle size distribution, z-average, and polydispersity index (PDI) in suspension were assessed by dynamic light scattering (DLS). Cells and cell culture media were collected at 24, 48, and 72 hours after exposure for subsequent analyses of cytotoxicity, inflammatory responses, and fibroblast activation. Barrier integrity of AT2 cells was also assessed through 96 hours post-exposure.At the concentration range used in this study, ES samples exhibited minimal cytotoxicity. At the highest concentration tested (5 µg/cm2 ), AT2 cells showed a significant decline in barrier integrity after exposure to samples A and D. For the inflammatory profile, samples B and C predominantly induced innate pro-inflammatory cytokines, while sample D induced a distinct cytokine profile that included mediators associated with type 2 immune responses. Additionally, sample D triggered the strongest effect in fibroblast activation. Sample C and Min-U-Sil 5 elicited moderate activation, while samples A and B induced minimal effects. In conclusion, the results demonstrated sample-specific patterns of cellular responses that were not consistently associated with the silica content of the ES samples. These findings imply that silica content alone may not predict the biological activity of ES particles and that other particle characteristics or constituents, together with silica, may contribute to cellular responses relevant to ES-related silicosis.

This thesis examines two distinct three-mode degeneracy problems. First, a third-order exceptional point of degeneracy (EPD3) is synthesized in a linear three-resonator RLC circuit. Kirchhoff’s laws yield a six-state model and two physical coupling branches. An op- amp negative-impedance converter (NIC) is then substituted for the ideal negative resistance. Finite gain, bandwidth, output resistance, loading, and saturation cause the simulated circuit to depart from the designed linear EPD3 condition. In the transient simulation, the circuit develops a finite-amplitude oscillation with a dominant spectral peak near 1.178 MHz rather than at the designed frequency of 1.45 MHz. Second, an independent normalized nonlinear coupled-mode-theory model with saturable gain is analyzed. Eliminating the modal amplitudes and saturated gain gives a real- fifth order steady-state frequency equation. A numerical design produces a fivefold real root, defined here as an SS-EPD5. Active-mode frequency detuning exhibits fifth-root frequency scaling. The stability of the steady state oscillation frequency is analyzed using the Lyapunov coefficients and a linearization. This leads to one neutral common-phase eigenvalue (Lyapunov coefficient) and five other eigenvalues with negative real parts, indicating local transverse linear stability of the steady state solution.