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Automorphisms and homological properties of locally gentle algebras
No full textThesis (Ph.D.)--University of Washington, 2025In this work, we consider the infinite dimensional generalizations of string algebras, referred to as locally string algebras, giving special attention the generalizations of gentle algebras, known as locally gentle algebras. We describe the prime spectrum and Jacobson radical of a locally string algebra. We show that, up to an inner automorphism and a unique graded automorphism, an automorphism of a string algebra acts as permutations on stationary paths and decomposes into a composition of exponential automorphisms. For the locally gentle algebras, we give an explicit injective resolution and combinatorial descriptions of their homological dimensions. We classify the Artin-Schelter Gorenstein, Artin-Schelter regular, and Cohen-Macaulay locally gentle algebras, and provide analogues of Stanley's theorem for locally gentle algebras
The Relationship between Students' Attitude toward Business Ethics and Academic Misbehaviors
Get PDFThis paper attempts to expand the current research area which has explored the association between students' academic dishonesty (i.e., exam cheating or plagiarism/fabrication) and attitude toward business ethics, by empirically testing the relationships between students' undesirable academic behaviors (i.e., disrespectful behaviors or slacker behaviors) and their perception of business ethics. The results based on 133 surveys from the students enrolled in the business program at a northwestern regional comprehensive university, show that there are positive relationships between the focal constructs. Specifically, this study reveals that students who have reported higher frequencies of engaging in exam cheating, disrespectful behavior, or slacker behaviors have perceived the given questionable, unethical employee practices as more acceptable conducts than the students have reported lower frequencies. This study reconfirms that that students who have reported higher frequencies of engaging in plagiarism/fabrication are more accepting of questionable, unethical business operations and questionable, unethical employee practices. In the additional analysis, gender, age and cumulative GPA have been explored as meaningful individual factors, and found to have relationships with students' attitude toward business ethics. Implications and recommendations are illustrated for instructors and administrators in business programs along with the limitation of the study and future research opportunity in the area
Neuromechanical Modeling of Nematode C. elegans via Modular Integration and Deep Learning
Get PDFThesis (Ph.D.)--University of Washington, 2025Neural circuits within the nervous system use coordinated activities to control behavior. The mediation of neural activities by individual neuron dynamics and their integration within the nervous system represents a fundamental question in neuroscience. Computational approaches that integrate modeling of the nervous system, muscles, and the body can assist in investigating functional pathways that guide neural activities and movement. Such approaches are referred to as neuromechanical models, as they incorporate models of the nervous system and biomechanics to achieve simultaneous simulation of neural activities and behavior. Nematode Caernorhabditis elegans (C. elegans) is considered a viable framework for studying neuromechanics due to advances in the resolution of its nervous system connectomics, biomechanics, and electrophysiological recordings of neuronal activity. The availability of data allows for the construction of neuromechanical model candidates with varying scopes and modalities. In my PhD research, I proposed key methods for the identification, construction, and extension of neuromechanical models for C. elegans. In particular, I proposed the modular integration approach and its implementation, modWorm, for modeling and simulating neuromechanical model candidates. The modWorm software allows for the construction of a model as an integrated series of configurable and exchangeable modules, each describing specific biophysical processes. Using modWorm, I proposed an initial candidate for the integrated neuromechanical model of C. elegans. The model integrates the complete connectome and 7 biophysical modules, including intra- and extra-cellular neural dynamics, translation of neural dynamics to muscle dynamics, muscle dynamics to body postures, and proprioceptive feedback from the environment. The model recapitulates i) Known natural behavioral responses, such as forward and backward locomotion in response to associated neural stimuli or external forces, and ii) Transitional behaviors, such as avoidance and turns, through timed stimulus. We performed computational ablation studies on neurons to infer novel neural circuits involved in sensorimotor behaviors (e.g., touch response). Variations of the model’s modules, such as more detailed intra- and extra-cellular dynamics, connectome mappings, and optimizations of associated parameters, can delineate possiblemechanisms of locomotion and directions in which the model can be improved to fit experimental findings. For an extension of modWorm modality, I developed mod-SenseWorm to incorporate environmental stimulus during the simulation of C. elegans behavior (e.g., chemotaxis). In particular, mod-SenseWorm incorporates the dynamic translation of external stimulus into neural stimulation to achieve a closed-loop simulation between neuromechanics and the surrounding environment. The translation algorithms employed by individual neurons can be configured by setting their stimulus encoding properties (e.g., tonic, phasic) and anatomical locations in the body (e.g., anterior, posterior). We applied mod-SenseWorm to study C. elegans O2 aerotaxis behavior and showed that the proposed model, in conjunction with the simulation of an O2 environment, recapitulates empirically observed avoidance behaviors associated with increased O2 levels. Furthermore, through the analysis of simulated neural activities, we show the use case of mod-SenseWorm to infer potential functional circuits associated with chemotactic responses. Deep learning methods can assist in extending the scope of the proposed neuromechanical model by inferring the parameters of biologically detailed modules associated with empirical data. This led me to develop ElectroPhysiomeGAN (EP-GAN), a deep generative method for the estimation of biophysical neuron parameters associated with neuron models from recorded electrophysiological responses. Trained with simulation data, EP-GAN learns the translation from recorded neuron responses (e.g., membrane potential responses, steady-state currents) to biophysical model parameters associated with the detailed Hodgkin-Huxley (HH) model. Validation of EP-GAN by estimating HH-model parameters for 200 simulatednon-spiking neurons, followed by 9 experimentally recorded neurons in C. elegans, showed EP-GAN’s advantages in the accuracy of the estimated parameters and inference speed compared to existing estimation methods. Control strategies can further extend the modality of the neuromechanical model by inferring supplemental mechanisms of neural circuits associated with behavior. In particular, I have introduced a possible employment of deep reinforcement learning (DeepRL) methods to develop control strategies for both neural stimulation (neuromodulatory control) and neural connection mapping (connectome control) that are applied on top of the proposed neuromechanical model to achieve aimed behaviors. The strategies learned by DeepRL can be used to identify dynamic neuromodulatory inputs between neurons (e.g., neuropeptidic currents) and perturbations of the connection wiring map for a local neural circuit, which result in empirically observed chemotactic behavior (e.g., attraction) in response to environmental stimuli. The results highlight the potential of utilizing DeepRL methods in conjunction with the neuromechanical model to infer potential neural interactions and circuitry that lead to specific behaviors
Pardon the Interruption: Assessing the Implementation, Operation, and Sustainment of Hospital-Based Violence Intervention Programs in the United States
Get PDFThesis (Ph.D.)--University of Washington, 2025Background: Hospital-based violence intervention programs (HVIPs) are public health interventions to prevent violent re-injury. We know little about the experience of HVIPs during the early stage of implementation. Specifically, we do not understand the factors that help or hinder programs from achieving stable operation. A threat of survivorship bias exists, as programs failing to reach operational status are not represented in the literature. HVIPs hinge on the ability of violence prevention professionals to assist the recovery of intentionally injured patients to prevent further spread of violence. Yet, we know little about the tactics these professionals use, or whether the tactics developed by one violence prevention professional transfer to another. While there is published guidance on initial program implementation, there is limited evidence or guidance about factors influencing long-term HVIP sustainability. Methods: Semi-structured interviews were conducted with 18 HVIP leaders regarding the barriers and facilitators to program implementation (Study #1). Interviews were conducted between December 2023 and March 2025 and were organized around a nine-stage blueprint for starting an HVIP, developed by the American College of Surgeons. Leaders were asked to articulate the barriers and facilitators encountered during each stage of implementation in as much detail as possible. Inductive coding was used to identify themes emerging at each stage. Semi-structured interviews were also conducted with hospital-based violence prevention professionals to identify tactics used in everyday work (Study #2). Interviews were organized around 10 “hinge points” on the patient’s recovery continuum deemed integral to program success, identified a priori. Inductive thematic analysis was used to identify individual tactics. The Action Actor Context Target Time (AACTT) rubric helped ascertain essential information about each tactic. Finally, a three-round Delphi study was conducted with leaders of established programs to prioritize factors critical for achieving long-term HVIP sustainability (Study #3). Participants submitted factors influencing their program’s sustainability in Round 1. Responses were synthesized using inductive thematic analysis and returned to participants for refinement in Round 2. Maximum-difference scaling with hierarchical Bayes estimation helped prioritize factors by importance in Round 3. This dissertation addressed these gaps in our knowledge through primary data collection across three studies:Study #1: assessed the barriers and facilitators facing HVIPs actively in the early stages of program implementation.
Study #2: identified the tactics violence prevention professionals use to meet the recovery needs of violently injured patients while preventing future violence exposure.
Study #3: developed a prioritized list of factors influencing the achievement of long-term HVIP sustainability. Results: Barriers to implementation included insufficient program infrastructure to secure outside investment in an HVIP; challenges hiring violence prevention professionals with criminal histories; and maintaining relationships with community organizations mistrustful of the hospital system. Key facilitators included early identification of executive-level hospital champions; hospitals budgeting for initial HVIP funding; and external capacity-building support to grow program infrastructure. Interviews in Study #2 surfaced 214 tactics used by violence prevention professionals. Tactics addressing the initial bedside encounter (n=49) and trustbuilding with patients and families (n=44) represented both the largest and most diverse share of those identified (n=96). Navigating administrative bureaucracy was particularly challenging and required a distinct set of tactics. (n=39) Comparably few tactics engaged patient retention (n=11) or aftercare as patients exited the program (n=3). Finally, 27 sustainability factors were initially synthesized from 108 submissions by 32 participants in Round 1. Leaders added four factors and removed three during Round 2, with 28 factors rated in Round 3. Participants prioritized frontline violence prevention professionals in six of the first nine factors. Funding-related factors (e.g., government grants, operating support) received moderate priority. Administration (e.g., hospital leadership) and community stakeholders (e.g., community champions) received lower priority. External institutions (e.g., police) received lowest priority. Significance: Study #1 represents the first known attempt to identify and describe the barriers and facilitators influencing early HVIP implementation. These findings may equip nascent HVIPs to recognize and respond to factors that accelerate or hinder implementation. Study #2 is the first known study focusing on the role of the hospital-based violence prevention professional. Dissemination of tactics used to conduct their work will strengthen the skillsets of current HVIP professionals, while enhancing the training of future violence prevention personnel. Findings may support the creation of practical, readily deployable toolkits to translate tactical insight to diverse contexts where HVIPs operate, including HVIPs not yet established. Finally, Study #3 represents the first known study of HVIP sustainability. Priorities for program stability differ from priorities in blueprints for program startup (Study #1). Results may indicate the need for program adaptability during their implementation journey and for HVIP leadership to recalibrate priorities over time
Accessing Increased Sustainability in Commodity Polymers: Post-Polymerization Modification of Polybutadiene and Mechanochemical Synthesis of Polyacrylates
No full textThesis (Ph.D.)--University of Washington, 2025As plastics and polymer materials are integral to modern life, wasted polymerproducts continue to accumulate and cause environmental damage. Further harm is done
through the resource-intensive synthesis of virgin materials from petroleum feedstocks under
harsh conditions. Through this work I show two parallel efforts to increase the sustainability
of commodity polymers; firstly, I focus addressing the end-of-life accumulation polymer
waste by the post-polymerization modification (PPM) of polybutadiene (PBD) with the goal
of adding value to and prolonging the lifespan of post-consumer rubber waste, as well as
creating reprocessable, crosslinked rubber. Secondly, I demonstrate the use of
piezoelectrically mediated mechanochemistry to generate diverse polyacrylates by reversible
addition-fragmentation chain-transfer (RAFT) polymerizations. The PPM of PBD occurs
through the addition of sulfonamides and sulfamates; these aminations proceed via selenium-
catalyzed, one-pot, room-temperature reactions. A myriad of functionalities can be imparted
by varying both the R group of the sulfonamides or sulfamates and the mole percent
functionalization of the polymer backbone. I present initial proof-of-concept work, where
PBD is modified with a family of sulfonamides, generating polymers with tunable thermal
and surface wetting properties. Further work explores applications of allylic amination by
generating reversibly crosslinked rubber. Current crosslinking of PBD is commonly executed
through di- and tri-sulfide linkages, creating vulcanized rubber; these materials are energy-
intensive to de-crosslink and in the process generate toxic byproducts, including sulfur
dioxide and hydrocarbons. I present a means of crosslinking PBD by amination with
1,1,1,3,3,3-hexafluoroisopropyl sulfamate followed by transesterification with a variety of
diols. Further substitution with phenol regenerates a thermoplastic with free amines on the
backbone, which can undergo crosslinking again. The second part of this work addresses the
need for more sustainable synthetic methods to create existing polymers. Utilizing
mechanochemistry provides a green chemistry alternative to traditional syntheses as minimal
solvent and less energy is required, and immiscible monomers can be combined without
excessive heating or exotic solvents. Herein we show the synthesis of random-co-polymers
from immiscible monomers, ABA and ABC triblock-co-polymers, and ultrahigh molecular
weight (UHMW) polymers by using ball-milling in the presence of piezoelectric
nanoparticles to drive the reactions. We see comparable control of polymer length and
dispersity compared to solution-state RAFT polymerizations, with significantly lower solvent
and energy requirements. Both aims of this work address increasing sustainability in areas of
polymer synthesis and processing by focusing on the PPM of PBD for valorization of
polymer waste, generating a circular means to crosslink rubber, and minimizing resources
needed to polymerize polyacrylates
Navigating the Ocean of Language Model Training Data
Get PDFThesis (Ph.D.)--University of Washington, 2025One crucial step toward understanding large language models (LLMs) is to understand their training data. Modern LLMs are trained on text corpora with trillions of tokens, hindering them from being easily analyzed. In this thesis, I discuss my research on making these massive text corpora efficiently searchable and revealing insights to the connection between LLMs and their training data. First, I developed infini-gram, a search engine system that enables fast string counting and document retrieval. With infini-gram, I indexed four open text corpora commonly used for LLM pretraining, totaling 5 trillion tokens. A by-product was the biggest n-gram language model ever built as of the date of publication, which I combined with neural LLMs to greatly improve their perplexity. Next, on top of infini-gram, I led the development of a system for tracing LLM generations into their multi-trillion-token training data in real time, named OLMoTrace. OLMoTrace shows long verbatim matches between LLM outputs and the full training data, enabling us to do fact-checking, trace "creative expressions", understand LLM's math capabilities, and much more. Finally, to enable searching in even bigger, Internet-scale corpora with limited budget, more storage-efficient indexing techniques are needed. To that end, we developed infini-gram mini, a search system with 12x less storage requirement than the original infini-gram, conceptually allowing us to index the entirety of Common Crawl (the main source of training data for LLMs). We indexed 83TB of text, including the Common Crawl snapshots between January and July 2025, making it the largest body of searchable text in the open-source community. With infini-gram mini, we revealed that many crucial LLM evaluation benchmarks are heavily contaminated, and we are hosting a public bulletin to continuously monitor this dire evaluation crisis. Together, my research enables everyone to inspect and understand LLM training data at scale, and paves way towards comprehending and debugging LLM behaviors from a data perspective
Novel production of lignocellulosic nanofibrils with diverse physical and chemical characteristics from wheat straw
No full textThesis (Master's)--University of Washington, 2025As the demand for sustainable materials grows, lignocellulosic nanofibrils (LCNFs) have gained attention for their abundance, renewability, and promising properties. However, widespread commercialization remains limited by unsustainable production methods, high costs, and the narrow functionality of currently available nanocellulose, which often lacks tunable properties. Existing LCNF production techniques frequently rely on expensive feedstocks, hazardous chemicals, or lack clarity on how process modifications affect material properties, making it difficult to tailor products for specific applications. This research addresses these challenges by developing process conditions to produce LCNFs with diverse physical and chemical properties from wheat straw. Seven fractionation treatments were conducted, varying sodium hydroxide (7.5–15%), hydrogen peroxide (0–7.5%), and temperature (50–95 °C), followed by chemical composition analysis. Two treatments were oxidized with 7.5% peracetic acid, while three others were oxidized at both 7.5% and 30%. Resulting samples were cast into films and thoroughly characterized using FTIR, conductometric titrations, SEM, XRD, UV–vis spectroscopy, TGA, contact angle measurements, and tensile testing. Lowering fractionation parameters (temperature and chemical charge) increased hemicellulose and lignin retention, enhancing yields and producing LCNFs with smaller diameters, semi-crystalline structure, low UV transmittance, moderate thermal and mechanical properties, and low wettability. Residual lignin content correlated with several properties: higher lignin led to less uniform fibrils, reduced optical transparency, increased UV absorption and haze, and lower thermal mass loss. Mechanical strength and elastic modulus declined with lignin content, except in samples treated with 30% PAA. Lignin also decreased surface hydrophilicity. Additionally, charge demand and mechanical performance were dictated not only on lignin content but also on whether lignin was primarily removed during fractionation or oxidation. This work contributes to sustainable material development by offering an adaptable platform for producing LCNFs with tunable properties suitable for a wide range of end-use applications
The Impact of Formal and Informal Institutional Distances on MNE Corporate Social Performance
Get PDFDoes country selection affect the corporate social performance (CSP) of multinational enterprises (MNEs)? In this study we suggest that greater institutional diversity within an MNE's operating environment may adversely affect its ability to maintain higher levels of CSP. Using institutional distance and organizational learning as our theoretical lenses, we investigate the impact of institutional differences on CSP. We conceptualize the MNE as a unique portfolio of locations and use the MNE's entire operating footprint to explore the effects of average portfolio formal and informal institutional distances on CSP. We hypothesize and find that firms with greater average informal institutional distance within their portfolios have lower overall levels of CSP. Findings also confirm the moderating influence of formal institutional distance; greater formal institutional distance within the MNE portfolio reduces the CSP benefits of international scope
Dietary Habits and Colorectal Cancer: Examining the Impact of Fruit, Vegetable, and Red Meat Consumption on Early- and Later-Onset Diagnosis in a Defined Birth Cohort
No full textThesis (Master's)--University of Washington, 2025The incidence of early-onset colorectal cancer (EoCRC) has risen over recent decades,particularly among younger adults. Shifts in dietary patterns across generations are
hypothesized to contribute to this trend, yet few studies have evaluated whether associations
between diet and age at CRC onset vary within a shared generational context. Using a
case-case design, we analyzed data from two population-based studies comprising 1,991 adults
diagnosed with CRC. We assessed average intake of fruits, vegetables, and red meat two years
prior to diagnosis. Logistic regression models compared dietary intake between participants with
EoCRC (18–49 years) and later-onset CRC (LoCRC, 55–74 years) in the full sample and within
a birth cohort born 1948–1961, with multivariable adjustment. In the overall sample, higher
vegetable intake was associated with lower odds of EoCRC (adjusted odds ratio (OR) for ≥2
servings/day compared to LoCRC: 0.72, 95% confidence interval (CI): 0.57–0.92). No significant
associations were found for fruit or red meat intake. Within the birth cohort, dietary intake was
not significantly associated with age at CRC onset for any dietary variable. Vegetable intake
may be inversely associated with early-onset among individuals diagnosed with CRC, but this
association was not observed within the specific birth cohort we examined. These findings
highlight the potential influence of generational dietary exposures and support the utility of birth
cohort-stratified analyses in clarifying age-related patterns in CRC onset
Topics in Estimation and Inference with Multivariate Missing Data
No full textThesis (Ph.D.)--University of Washington, 2025This dissertation discusses statistical methodologies for complex missing data problems with a focus on multivariate and partially observed structures. Chapter 2 introduces a unified framework for handling multiple missing covariates and partially observed responses using inverse probability weighting, regression adjustment, and a multiply-robust procedure. Applications include the Cox model for survival analysis, missing responses, and binary treatment in causal inference, along with supporting identification and asymptotic theory. Chapter 3 focuses on modeling multivariate bounded discrete outcomes such as those from neuropsychological tests in dementia studies. We propose a flexible modeling strategy based on mixtures of experts and latent class models, extended to handle missing at random outcomes via a nested EM algorithm. The joint model also allows for imputation and clustering. Chapter 4 addresses nonmonotone missing data under missing not at random (MNAR) mechanisms, extending the work in Chapter 3. A tree graph is a directed acyclic graph on the missing patterns, and each one represents a MNAR mechanism. Combining this with the idea of a conjugate odds property, we are able to preserve distributional structure across missing patterns and construct relatively straightforward models for the full data distribution. Throughout the dissertation, we also highlight practical relevance using an Alzheimer's disease data set