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Psychology of Disposal and its Influence on Consumer Behavior
No full textThesis (Ph.D.)--University of Washington, 2024Consumption is a multi-stage process encompassing acquisition, usage, and disposal, and the issues surrounding consumers' disposal are as complex and far-reaching as those of acquisition and usage. Yet research on disposal remains limited, making it imperative to study related issues not only to offer a richer perspective on disposal but also because mindless disposal has contributed to dire environmental and social problems. My dissertation aims to enhance the understanding of disposal by illuminating the psychology behind it, providing insights into how consumers conceptualize disposal and how this influences decision-making at various consumption stages. Chapters 1 and 2 consolidate past research on disposal and provide an integrative framework to help researchers make novel predictions and ask new questions. This framework incorporates ways in which disposal exerts influence across the entire consumption cycle and identifies illustrative questions that can guide the ongoing development of disposal research. This presents an opportunity for consumer research to claim ownership in a domain that is, by definition, a key aspect of consumption. Chapter 3 then demonstrates an example of how the integrative framework can be implemented to broaden the disposal literature by investigating how referencing disposal as part of product information (i.e., disposal reference) influences consumers' product evaluations at purchase. Across eight studies, I show that highlighting disposal at the point of product acquisition negatively impacts consumers' product evaluations by affecting perceptions of the product's wastefulness. I also demonstrate that morality underlies this disposal reference effect. Referencing disposal imbues the product with moral significance, an effect amplified among consumers with a strong moral identity. In documenting a novel effect of considering disposal on product evaluations at purchase, these findings advance our understanding of disposal, wastefulness, and morality. In the concluding chapter, I delineate disposal’s substantive import and discuss further research directions on disposal-related phenomena and areas of inquiry. Overall, my dissertation theoretically and empirically expands our understanding of disposal while highlighting its importance across consumers, businesses, society, and the ecosystem
Solvation Meta Predictor
No full textThesis (Master's)--University of Washington, 2024Predicting the solubility of aqueous mixtures is a critical task in cheminformatics, impacting fields such as drug discovery, chemical engineering, and environmental science. This study aims to enhance the predictive accuracy of machine learning models for solubility by employing advanced ensemble techniques. We evaluated the performance of three individual models: SMI, MDM, and GNN, and compared them to ensemble methods including simple averaging and an Optuna-optimized ensemble. Our results indicate that the Optuna-optimized ensemble model achieved the highest predictive accuracy, with an R2 value of 0.8117, outperforming individual models and simple ensemble techniques. To further improve model performance, we propose the implementation of the Mixture of Experts (MoE) approach. This advanced ensemble technique leverages specialized experts and a gating network to optimize model predictions based on input features. MoE promises to enhance model flexibility, scalability, and specialization, making it a robust tool for handling complex and heterogeneous datasets. Future work will involve integrating additional models and exploring other ensemble strategies to further improve predictive accuracy. The findings of this study highlight the potential of ensemble methods to significantly improve the prediction of solubility in aqueous mixtures, offering valuable insights for various scientific and industrial applications
Characterizing Microsite Conditions of the Endangered Wenatchee Mountains Checkermallow (Sidalcea oregana var. calva)
No full textThesis (Master's)--University of Washington, 2024To effectively protect and recover rare species, we must understand their ecological niches and habitat requirements. My research focused on Wenatchee Mountains checkermallow (Sidalcea oregana var. calva; “SIORC”), an endangered plant taxon found in central Washington. There are currently only five known populations of SIORC, and these populations are highly vulnerable to extirpation from demographic factors or stochastic events due to the limited abundance and range of remaining populations. Successful conservation of this species requires understanding the conditions this plant needs to survive and reproduce. During 2022 and 2023, I conducted a microsite study on the SIORC population at Camas Meadows and measured a variety of fine-scale characteristics in SIORC habitats throughout the meadow. These microsite characteristics included soil moisture, canopy density, Leaf Area Index (LAI), soil texture, and associated vegetation. I used cluster analyses and PERMANOVAs to relate SIORC presence and abundance to each of these microsite variables. I did not find support for any significant relationships between SIORC and physical microsite variables (soil moisture, canopy density, LAI, soil texture). However, an analysis using more precise, lab-based soil texture data from 2023 found that soil clay vs silt content significantly affected SIORC presence in 2023. Analysis of vegetation characteristics found significant relationships with SIORC presence and SIORC abundance. Species richness, forb cover, and grouping based on overall vegetation characteristics significantly related to SIORC presence. Grouping based on vegetation characteristics did not significantly affect SIORC abundance, but total cover on its own was strongly associated with SIORC abundance. Indicator Species Analyses identified Achillea millefolium as an indicator for SIORC presence. Additionally, I installed 30 continuous soil moisture sensors and measured soil moisture during the growing season. I used a cluster analysis to identify groups of sensors based on soil moisture characteristics and found that, while SIORC abundance was higher for the wettest groups of sensors in July and August, SIORC presence and number of SIORC were the same across all groups. These results suggest that physical microsite characteristics are not driving SIORC distribution, and that other factors such as vegetation characteristics, seed predation, and fire suppression likely play a stronger role in determining SIORC presence and abundance
Privacy’s Algorithmic Turn: An Intellectual History
No full textThesis (Ph.D.)--University of Washington, 2024Between 1990 and 2020, the concept of information privacy in American privacy law scholarship experienced an “algorithmic turn,” gradually expanding to encompass a new set of privacy harms, as well as a different kit of legal tools. This dissertation traces, in detail, the intellectual history of this sociotechnical phenomenon. Taking the scholarly work produced around the Privacy Law Scholars Conference (PLSC) as well as earlier scholarship that preceded and inspired it as my primary object of study, I conducted document analysis of 574 law review articles written between 1990 and 2020, as well as fifteen oral history interviews with a purposely drawn representative sample of privacy law scholars. In my analysis, I take a Ground Theory approach and draw from the methodological framework of Intellectual History, following the discursive contextual approach proposed by intellectual historian David A. Hollinger. In this dissertation I tell a history of how, over the past thirty years, the community of privacy scholars that has developed around PLSC transitioned from focusing primarily on autonomy-based harms to raising a vast array of harms that share the following three characteristics: being objective, originating from the actual processing phase of the data cycle, and having architectural effects. In this process, scholars shifted twice from states of regulatory innovation and flux to those of relative convergence regarding the preferred tools to protect information privacy. Thus, while between 2000 and 2007 scholars almost unanimously supported the legal implementation of the Fair Information Practices (“FIPs”) principles in order to empower individuals, by the end of the 2010s several of them seemed to be coalescing around a hands-on set of substantive requirements, duties, and prohibitions intended to take power away from corporations.
In addition, building on Science & Technology Studies (STS) literature on “imaginaries” as well as on interdisciplinary scholarship where this concept has been applied to legal endeavors, I propose the theoretical concept of “techno-legal imaginaries” and apply it to the case of the American privacy law scholars here examined. I suggest that the transformation of the scholars’ techno-legal imaginaries over the period of time covered by this study can provide us with some insight into the evolution of the tools proposed by scholars to protect information privacy.
Back in the late 1990s and early 2000s, many American privacy law scholars aimed for Information Privacy law to contribute to a pluralist, free, and democratic society that promoted liberty, autonomy, and self-determination. Within that normative framework, procedural standards that gave individuals control over their personal information, such as the FIPs, stood out as appropriate. Over the years, however, scholars’ techno-legal imaginaries have radically changed. Several scholars now expect Information Privacy law to promote a socially just society that besides protecting individuals’ autonomy, defends the vulnerable and marginalized, protects individuals from data extraction and its consequent power imbalances, and holds corporations accountable. The most recent batch of hands-on tools makes sense within these normative commitments.
This research builds upon the Legal Construction of Technology method, to present privacy’s algorithmic turn as a complex sociotechnical phenomenon, placing it within a broader context where technological, social, legal, and—as I hope to demonstrate here—cognitive elements interact and become entangled
Protein-level regulation of oncogenic RIT1 in non-small cell lung cancer
No full textThesis (Ph.D.)--University of Washington, 2024Lung cancer is the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer is the most diagnosed type of lung cancer, and lung adenocarcinoma is the most prevalent subtype. Approximately 50% of lung adenocarcinoma tumors harbor druggable mutations in genes such as EGFR and ALK, and targeted therapies are highly effective at reducing tumor burden. Indeed, targeted therapies have revolutionized cancer treatment and are becoming standard of care over cytotoxic chemotherapy; however, many mutations are not clinically actionable. Up to 15% of lung adenocarcinoma tumors are driven by mutation or amplification of the RAS-family gene RIT1, and RIT1 mutations do not co-occur with other canonical driver mutations. There is a growing understanding that the protein abundance of RIT1 is essential for its function. Therefore, inhibiting positive regulators of RIT1 abundance could be a tractable means of reducing tumor burden and abrogating the growth of tumors driven by RIT1 mutations and amplifications. Development of a RIT1-specific inhibitor is unlikely to succeed due to the structure of RIT1 as a GTPase. In 2013, groundbreaking work on KRAS resulted in the development of the first mutant-specific inhibitors, which represents a major advance in this field and for patient care. Such an approach for RIT1, however, would be quite difficult due to the resources required and our lack of knowledge pertaining to RIT1 biology and oncogenic mechanisms. Because of this, innovative approaches are needed to understand RIT1 genetic dependencies and uncover druggable targets. The Berger Lab developed a CRISPR screening approach to discover genes required for RIT1-driven cellular transformation. From this work, we found that RIT1-mutant cells are uniquely dependent on genes associated with the Spindle Assembly Checkpoint (SAC), including Aurora kinases A and B. RIT1-mutant cells are more sensitive than KRAS-mutant cells to alisertib (an Aurora kinase A inhibitor) and barasertib (an Aurora kinase B inhibitor). Expression of mutant RIT1 weakens the SAC, prompting cells to prematurely exit mitosis and accumulate mitotic abnormalities. In addition to the SAC vulnerability, we identified the deubiquitinase USP9X as a top essential gene in RIT1-mutant cells. This was particularly intriguing given that previous work has suggested that the protein abundance of RIT1 is important for its function. Indeed, although RIT1 shows high sequence homology to KRAS, RIT1 does not appear to be regulated in a similar manner (i.e. at the level of GAP resistance). Instead, RIT1 appears to be regulated at the level of protein abundance. Here, I explore the hypothesis that RIT1 is a substrate of USP9X and found that USP9X binds to and deubiquitinates RIT1. I find that USP9X depletion decreases RIT1 protein abundance and stability, and loss of USP9X abrogates RIT1-driven cell growth and proliferation. These findings increase our understanding of RIT1 biology and oncogenic mechanisms and nominate USP9X as a therapeutic target for the treatment of RIT1-driven diseases
Targeting the Innate Immune System Using Protein Design
No full textThesis (Ph.D.)--University of Washington, 2024Subunit vaccines require adjuvants to create a robust immune response. Adjuvants are limited by formulation difficulties and the types of immune responses they elicit. There is a need for a new generation of adjuvants. An ideal adjuvant would be easy to characterize with a protein antigen, hyperstable, specific to a defined immune pathway, and easily modified. In this thesis, I describe the application of protein design to create protein based adjuvants. We created novel minibinders that can be linked together to agonize TLR3. Additional stories are presented which describe the efforts to create protein binders for TLR5, TREM-2, and FcγRIIA
RNA structures within Venezuelan equine encephalitis virus E1 alter macrophage replication fitness and contribute to viral emergence
No full textThesis (Ph.D.)--University of Washington, 2024Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne positive-sense single-stranded RNA genome virus belonging to the Togaviridae. Present throughout Central and South America, VEEV is responsible for significant outbreaks of epidemic/epizootic VEEV causing febrile disease and encephalitis in both equids and humans. While endemic/enzootic VEEV persists in nature and circulates between reservoir host rodents and mosquitoes, periodic mutation of enzootic VEEV gives rise to the emergence of epizootic VEEV. Using equines as amplification hosts, epizootic VEEV can have devastating outcomes for equine populations as well as cause large spill over events and disease in humans. The main mutations linked to epizootic VEEV emergence involve amino acid mutations within the E2 glycoprotein, which enhance viral entry and equine amplification. Interestingly, the majority of mutations found within epizootic strains are synonymous, indicating that other viral factors, such as RNA secondary structure, may play a critical role in their emergence. Understanding these mechanisms is crucial for predicting and mitigating future outbreaks.In this study, we discovered novel RNA structures within the E1 coding sequence that specifically affect VEEV replication in macrophages, which are critical early targets during infection. Using mass spectrometry and targeted gene knockdown, we identified several RNA-binding proteins essential for the altered macrophage phenotype, none of which had previously been associated with VEEV replication. Our findings also revealed the conservation of single-nucleotide polymorphisms (SNPs) within epizootic VEEV lineages, as well as the preservation of RNA structures across all lineages. Taken together, these findings suggest a previously unrecognized role for RNA secondary structure in the emergence of epizootic VEEV
Cultural Preservation Through Community-led Development in Seattle: Community Engagement for Little Saigon’s Vietnamese Cultural and Economic Center
No full textThesis (Master's)--University of Washington, 2024In September 2023, Friends of Little Saigon (FLS) purchased land in Seattle for a new mixed-use development called the Landmark Project, which will accommodate 71 units of affordable housing above a Vietnamese Cultural and Economic Center (VCEC). Mixed-use cultural centers are important “third places” to strengthen a sense of place attachment, social cohesion, and community participation — all of which are social determinants of health. This capstone project engaged community members to inform programming, physical space designs, and aesthetics of the VCEC through four methods: (1) an online survey, (2) interviews with small business owners, (3) an interactive feedback board, and (4) a World Café-style community meeting. Across all methods, community members expressed interest in food-related events, pop-up markets, art gatherings, cultural celebrations, classes, and intergenerational activities. In terms of ambience, community members were clear about their desire for a balance between traditional and modern elements to appeal to the Vietnamese diaspora. These findings will guide the development of the VCEC to ensure that programming and physical design align with community needs
Contemporary Approaches to Classical Econometrics: Measure Transport Applications in Multivariate Inequality Analysis and Fixed Effects
No full textThesis (Ph.D.)--University of Washington, 2024This dissertation contributes to two major research areas: multivariate analysis of eco- nomic inequality and panel data methodology. The focus is on extending popular es- tablished approaches while retaining the features responsible for their enduring appeal. I achieve this by applying optimal transport theory directly to develop inequality or- derings based on Lorenz curves, and indirectly to relax structure imposed in traditional fixed effects models. The first chapter offers a brief introduction on optimal transport. In the second chapter, we propose a multivariate extension of the Lorenz curve based on multivariate rearrangements of optimal transport theory. We define a vector Lorenz map as the integral of the vector quantile map associated with a multivariate resource allocation. Each component of the Lorenz map is the cumulative share of each resource, as in the traditional univariate case. The pointwise ordering of such Lorenz maps defines a new multivariate majorization order, which is equivalent to preference by any social planner with inequality averse multivariate rank dependent social evaluation functional. We define a family of multi-attribute Gini index and complete ordering based on the Lorenz map. We propose the level sets of an Inverse Lorenz Function as a practical tool to visualize and compare inequality in two dimensions, and apply it to income-wealth inequality in the United States between 1989 and 2022. In the third chapter, I extend the linear grouped fixed effects (GFE) panel model to allow for heteroskedasticity from a discrete latent group variable. Key features of GFE are preserved, such as individuals belonging to one of a finite number of groups and group membership is unrestricted and estimated. Ignoring group heteroskedasticity is shown to lead to poor classification, which causes significant finite-sample bias. I intro- duce the “weighted grouped fixed effects” (WGFE) estimator that minimizes a weighted average of group sum of squared residuals. I establish pNT-consistency and normal- ity under a concept of group separation based on second moments. A test of group heteroskedasticity is proposed. A fast computation procedure is provided. Simulations show that WGFE outperforms alternatives that exclude second moment information. I demonstrate this approach by revisiting studies on the effect of unionization on earnings and the link between income and democratization. In the fourth chapter, I reexamine the Rational Addiction model by introducing the type fixed effects (TFE) panel model. The TFE model incorporates heterogeneous coeffi- cients and time-varying patterns of heterogeneity, which reflect differences in preferences and the addiction process. The model assumes the existence of a latent, time-invariant continuous variable referred to as a “type”, which drives the heterogeneity in the pa- rameters. Smoothness of the parameters as functions of the type is key to identification, allowing individuals of similar types to have similar parameter values. Correlation be- tween the parameters, covariates, and instruments stem from type heterogeneity. I pro- pose the type fixed effects generalized method of moments (TFE-GMM) estimator and establish consistency. I provide fast computation procedures based on a stochastic gra- dient descent algorithm. Simulations demonstrate good performance of this estimator. Using yearly household cigarette purchase data to estimate the model shows that most households follow cyclical consumption patterns and insensitivity to prices changes, giving support to educational interventions to curb smoking