VictorJuiz/thesis huggingface dataset:
Three essays on international trade and innovation

This dissertation consists of three essays spanning the topics of international trade and innovation, with specific attention to their underlying legal institutions. In the first chapter, I address the role of non-uniform trade policy in a world where firms are known to be heterogeneous. Since much firm-level policy occurs unilaterally and outside of negotiated most-favored nation tariff rates, exploring governments' strategic incentives in sequential-move environments is of interest. Compared to an existing heterogeneous-firm model with non-uniform tariffs, I add simplifying functional form assumptions that then allow me to add strategic behavior into the model. In particular, I allow one country to act as a Stackelberg leader in setting trade taxes, and I find that it always elects to impose a tax, and that the tax is larger than it would be if the follower were not expected to respond. I also discuss the specific policy avenues that are available to governments for levying non-uniform tariffs on firms and relate the situations in which these avenues may be used to forces and incentives in my model. In the second chapter, joint with Lisa Ouellette, I turn to innovation policy and consider the market for vaccines. We review and synthesize research from a broad array of disciplines including economics, law, and public health, documenting the outsized benefits of vaccines juxtaposed with a seemingly anemic development pipeline. Vaccines have many attributes that are understood in the economic literature to limit the rents that a monopolist can extract. Most importantly, they are durable goods, and they are preventatives. Starting from this understanding, we argue that market-based innovation incentives, such as patents, will under-provide such goods relative to goods without these properties, even though the social benefit of such goods may be far greater. In the third chapter, I consider international patenting flows and leverage the European Patent Office's DOCDB database, which contains detailed international patent bibliographic data, to consider patent application filings as a measure of knowledge diffusion and domestic knowledge production. After describing the international patenting regime and the incentives that drive it, I document a clear relationship between a country's market size and both its domestic knowledge production and its reception of foreign knowledge diffusion. I also find that, although bilateral patent flows resemble bilateral trade flows in that they increase with the size of the source and destination countries, distance does not play as clear a role in moderating patent flows as it does with trade in goods.

Keywords: Humanities and Sciences.
Economics.
Advisor: Bagwell Kyle
Ouellette Lisa Larrimore
Williams Heidi L.
Tools for coronary MR angiography : non-cartesian trajectories and motion-corrected reconstructions

X-ray coronary angiography remains the predominant technique for coronary artery examination, yet it exposes both patients and operators to ionizing radiation and is invasive. Despite strong demand for non-invasive and safer alternatives, the clinical adoption of coronary MR angiography has been slow. The primary challenges in coronary MR angiography are its prolonged scan time and limited resolution. Because coronary arteries often follow tortuous paths and have relatively small diameters, high resolving power is required. Additionally, whole-heart imaging is preferred over target-volume methods, as it reduces operator dependency. Achieving large volumetric coverage at high resolution demands collecting a significant amount of data. However, continuous myocardial movement restricts data collection to specific cardiac cycles, necessitating the segmented data acquisition over multiple heartbeats. Consequently, coronary MR angiography is slow and susceptible to both respiratory and cardiac motion. This dissertation introduces several tools for coronary MR angiography categorized into non-Cartesian trajectory design and non-rigid motion-corrected reconstruction. Non-Cartesian trajectories often exhibit higher sampling efficiency and greater robustness against undersampling compared to traditional rectilinear approaches, making them particularly useful for reducing the overall scan duration. Because non-rigid models capture a wide range of transformations, non-rigid motion-corrected reconstruction reduces resolution loss due to respiratory and cardiac motion.

Keywords: Engineering.
Bioengineering.
Advisor: Nishimura Dwight George
Coleman Todd (Of University of California
Vasanawala Shreyas
Toward preventing traumatic brain injury : evaluation and design of modern helmet technologies

Traumatic brain injury is a prominent global health issue affecting tens of millions of humans per year. Contact sports, in particular, present a particularly high risk of concussion (a form of mild traumatic brain injury) as well as repeated, subconcussive head impacts that can accumulate over a lifetime and are associated with development of neurodegenerative diseases in later life. This dissertation seeks to determine the efficacy of modern head protective technologies being utilized to reduce the risk of brain injury, with a specific focus on American football athletes. First, an instrumented mouthguard device was used in a field study to determine the factors affecting the severity of head impacts experienced in American football athletes, ultimately finding that significant differences in impact severity could not be detected between two existing helmet models on the field. Therefore, three modern devices that represent dramatic changes to helmet technology were evaluated to determine how they could improve impact safety. Using a large-scale test methodology that simulates impacts using the head, neck, and torso of two anthropomorphic test devices, the first technology explored was one that couples a helmet and shoulder pads as one unified piece of protective equipment. Next, both laboratory and field data were collected to determine the efficacy of a widely adopted padded helmet shell cover. While these first two technologies seek to improve safety by making additions to existing helmet technology, soft hydraulic shock absorbers were explored as a means of replacing existing helmet components to improve safety. A physical prototype of a wearable hydraulic shock absorber was developed, tested alongside existing state-of-the-art helmet shock absorbers, and implemented into a full helmet system for impact testing. Finally, a finite element model of an American football helmet comprised entirely of liquid shock absorbers was developed and evaluated alongside existing helmet models for its performance under impact loading representative of concussive and subconcussive impacts. The results of this research demonstrate the promise, and limitations, of modern helmet technologies targeted towards preventing traumatic brain injury.

Keywords: Engineering.
Bioengineering.
Advisor: Camarillo David
Delp Scott
Kuhl Ellen
Zeineh Michael
A transcriptional switch underlies the pro-and anti-inflammatory activities of afucosylated and sialylated IGG glycoforms

Antibodies play a crucial role in bridging the gap between the innate and adaptive immune systems by serving as a link that connects these two components of the immune response. They recognize specific antigens on pathogens, facilitating recognition and response by innate immune cells. Additionally, antibodies contribute to immunological memory, allowing the adaptive immune system to mount a faster and more specific response upon re-exposure to the same pathogen. This coordination enhances the overall effectiveness of the immune defense against infections. IgG Fc glycosylation serves as a mechanism to enhance the versatility of antibody function by altering its affinity for specific activating and inhibitory Fc-gamma receptors. This, in turn, regulates Fc-mediated effector functions and influences the innate immune response directed toward target pathogens. However, the precise impact of different IgG glycoforms on immunity in frequently infected sites, such as the lungs, remains unclear. In Chapter I, I review the literature regarding IgG Fc glycosylation, Fc-gamma receptor functions, and the impact of both on human disease outcomes. In Chapter 2, my colleagues and I use mass spectrometry to identify specific IgG glycoforms that correlate with COVID-19 disease trajectories. We identify a correlation between afucosylated IgG abundance and more severe disease outcomes as well as an enrichment of sialylated IgG in protected patient populations. In Chapter 3, we investigate how these glycoforms impact the local immune response within the lungs of Fc-gamma receptor-humanized mice at the functional and transcriptional levels. We identify the transcription factors NF-κB and REST as likely regulators of immune complex-mediated inflammation within the lung. Altogether, we identify a transcriptional switch that underlies the pro- and anti-inflammatory activity of afucosylated and sialylated IgG in the lung mediated by the transcription factors NF-κB and REST that may have relevance in human disease.

Keywords: Medicine.
Advisor: Wang Taia
Engleman Edgar G.
Mellins Elizabeth
Utz Paul
Untouchable : on the cultural politics of hands in Modern China

This dissertation explores the representation of touch and tactile culture in modern Chinese literature, film, and visual culture. The project investigates the many powers invested in human hands through narrative, taking a particular interest in the discourses that contribute to the construction of "untouchable" people and groups at various historical junctures. I argue that hands and protocols of touch are situated at the crux of major ideological and political tensions from the early Republican era to the new millennium. By examining how contentions about labor, sexuality, modernity, and national survival are played out in discourses of hands, my analysis offers fresh readings of seminal cultural texts and interrogates existing assumptions about intimacy and alienation in the modern era. This project not only contributes to the China field's emerging interest in sensory experience—which has been mostly limited to discussions of visuality, sound, and taste—but also opens up a new vista for sustained future inquiry about how tactility interacts with sight, taste, scent, and sound in a comprehensive aesthetic discourse of the body.

Keywords: Humanities and Sciences.
East Asian Languages and Cultures.
Advisor: Lee Haiyan
Wang Ban
Kohrman Matthew
Sommer Matthew Harvey
Using foundation models to learn how to represent electronic health records

The invention and use of electronic health records has enabled new applications of machine learning in the field of healthcare. One particularly important application is the use of machine learning to predict the risk of a variety of clinical outcomes given electronic health records. However, training machine learning models on electronic health records is often challenging due to limited data set sizes and the intrinsic complexity of electronic health record data. In this dissertation, I propose and validate the use of foundation models as a way to learn representations for electronic health records, taking advantage of the longitudinal structure of medical record data to learn transferable representations. These representations can then be used to improve our ability to predict patient risk, achieving superior ranking performance, increased robustness across both time and space, and better label efficiency.

Keywords: Engineering.
Advisor: Leskovec Jurij
Shah Nigam
Ré Christopher
Waste monitoring and management for improved water quality and soil health

Good water quality and soil health are fundamentally important to planetary (human and environmental) health, which poor waste management practises can jeopardize. Waste monitoring and management strategies can impact and influence water quality and soil health. The research in this dissertation examines these in specific contexts, with a specific focus on community needs. In so doing, it aims to contribute to achieving Sustainable Development Goals (SDGs) related to zero hunger, clean water and sanitation, responsible consumption and production, and life on land. This thesis consists of three research chapters. Chapter 2 investigates fecal contamination of stored water supplies in rural Kenyan households, identifying ruminant feces as a significant source and elucidating transmission pathways. Chapter 3 explores the production of soil amendment biochar from cacao husks in Malaysia, optimizing reactor designs and characterizing biochar properties. Chapter 4 examines the impact of biochar on soil and cacao sapling growth, which demonstrated mixed results but revealed potential benefits and areas for improvement. The findings in this dissertation underscore the importance of community-centered approaches and highlight the complexity of ensuring that waste management ultimately does remediate and ameliorate water quality and soil health. Recommendations for future research include exploring the conceptual models underpinning the research to ensure that each link of the causal chain is rigorously examined such that risks are adequately quantified, processed improved, or expenditure and effort towards interventions justified. Ultimately, the dissertation emphasizes the value of holistic, locally informed solutions to address environmental degradation and promote sustainable development. While the research presents promising avenues for enhancing water and soil quality, it underscores the need for careful consideration of unintended consequences and community perspectives in advancing sustainable development goals.

Keywords: Engineering.
Advisor: Luby Stephen
Leckie Jim
VinduskovaOlga
Wavefunction-based simulations : dynamics of quantum many-body systems

Many exotic phases of matter, such as quantum spin liquid (QSL) and high temperature superconductivity, are associated with strong correlations between constituent particles. Yet theoretical analysis is largely hindered by the strong interactions. Numeric simulations, although facing the challenge of exponential complexity, have provided valuable theoretical insights and connections to experiments. In this work, I present wavefunction-based numerical methods to study strongly correlated systems with an emphasis on dynamics, which can provide extra information about the excitations in the system, connect theoretical modeling with experimental spectroscopies and can reveal interactions in the system. After an overview, I will first discuss characterizations of the QSL on a triangular lattice through dynamical spin structure factor and Raman scattering. The QSL phase shows distinct spectral features, among which a prominent chiral excitation in Raman spectra signals proximity to chiral ordering. I then present the study of salient spectral features observed in recent angle resolved photoemission spectroscopy experiment on a one-dimensional cuprate. These spectral features can be well reproduced by adding extended electron-phonon couplings, which enhances superconducting pairing correlations in 1D and may help the establishment of superconductivity in 2D. Finally, I present a time-dependent nonequilibrium study and show cuprates superconductivity could potentially be enhanced via laser driven photodoping. I conclude with some ideas to go beyond the results presented in this thesis.

Keywords: Humanities and Sciences.
Applied Physics.
Advisor: Devereaux Thomas Peter
Shen Zhi-Xun
Kivelson Steven
X-Ray Vision at work : diagnosing covert diversity, equity & inclusion dynamics in a non-profit organization

This qualitative case study seeks to understand, from a systems psychodynamics perspective, how employees experience covert dynamics during organizational development and change (ODC) initiatives that are focused on improving diversity, equity, and inclusion (DEI) in the workplace. Using the organizational framework and diagnostic tool "X-Ray Vision," I explored with twenty-seven nonprofit employees the application and effectiveness of the tool as they examined covert DEI dynamics that were influencing implementation of their strategic plan. Specifically, I wanted to know how ODC and DEI researchers and practitioners can use X-Ray Vision as a diagnostic tool to support employees while they are designing, leading, and managing change. Study participants were chosen using a convenience sampling methodology. The primary data collection methods were focus groups and semi-structured interviews, supported by participant-observation and document review. The data were organized, coded, and analyzed using the X-Ray Vision conceptual framework and related concepts in the DEI literature. The research revealed that there were many covert DEI dynamics operating at multiple levels of the organizational system  intrapersonal, interpersonal, group, intergroup, and interorganizational  that were having a negative impact on employee well-being, relationships, motivation, and job satisfaction, as well as organizational culture, climate, and performance. The study's findings suggest that the X-Ray Vision diagnosis is most useful when the researcher or practitioner explicitly links covert concepts in the tool with related DEI concepts and expertly uses self-as-instrument when engaged in DEI-specific organization development and change challenges. The study offers recommendations for ODC and DEI researchers and practitioners who want to diagnose covert DEI dynamics operating beneath the surface of organizational life.

Keywords: Humanities and Sciences.
Advisor: Markus Hazel Rose
Noumair Debra Ann
Elam Michele
3D Printing Lattice Based Pressure Sensors for Human Health and Performance Monitoring

Capacitive pressure sensors have generated significant interest for applications in human health and performance monitoring. A wide range of potential applications require low cost, compliant sensors that can be tuned to appropriate sensing regimes and sensitivities. Previous literature has shown that microstructuring the dielectric layers of sensors can provide significant increases in sensitivity and that dielectric geometry can directly impact sensor range and performance. Leveraging advances in high resolution 3D printing we have developed a new method for fabricating elastomeric lattices with highly tunable geometric properties for use as capacitive pressure sensor dielectrics. We characterized the impact of microstructure geometry on the capacitive pressure sensors’ mechanical performance and developed a new set of analytical equations suitable for the lattice geometries to predict the capacitance response and sensitives of microstructured sensors under external pressure. This work covers 1) design rationale of lattice unit cells, 2) an analytical expression that directly predicts the capacitance response, and 3) 3D printing elastomeric lattice dielectric layers, which taken together serve as a framework and starting point to design and fabricate capacitive pressure sensors for various biomedical applications as well as for human health and performance monitoring.

Keywords: 3D printing
Dielectrics
Capacitive pressure sensors
Text
Thesis
Advisor: DeSimone Joseph
Dionne Jennifer
3KG v2: Universal Electrocardiogram Representations for Label-Efficient Phenotype Discovery

We propose 3KG v2, a new self-supervised learning method for universal representation learning of electrocardiograms. This method builds upon its predecessor by featuring a new contrastive objective and transformation space. We assess the quality of representations generated by this algorithm by transferring pre- trained models from a large public dataset to various downstream tasks, including some with- out prior clinical association with ECGs. Performance evaluation is conducted in both few- shot and full data settings to account for limited and complete training data availability, respectively. For each task, we perform a linear evaluation to assess the effectiveness of the pretrained representations. For tasks in the full- data setting, we additionally perform a full-fine tuning to determine the performance ceiling of each method in a practical deployment scenario.
Our results demonstrate that 3KG v2 consistently outperforms a randomly initialized model trained solely on the target task across all downstream tasks and settings. Specifically, we achieve state-of-the-art performance in few- shot diagnosis of right ventricular function and aortic valve stenosis, two conditions that typically require large amounts of labeled ECGs for effective model training. Moreover, we find that fine-tuning 3KG v2 on our source task’s labels can lead to exceptional transfer capability across a variety of tasks. Notably, our model demonstrates a high level of accuracy in predicting left atrial volume index, achieving a 0.720 C-index even in a few-shot setting. This achievement appears to be unprecedented, as we are not aware of any other ECG model that performs well on this task. While 3KG v2 out- performs our baselines and shows promising results on the majority of phenotype discovery tasks, there is still room for improvement in the absolute performance of any ECG model on many of these complex tasks. Further research is warranted to continue developing and improving such methods for phenotype discovery tasks on ECGs.

Keywords: Rajpurkar, Pranav
Machine learning
Deep learning (Machine learning)
Artificial intelligence
Cardiology
Electrocardiography
Electrocardiography > Interpretation
Echocardiography
Echocardiography > Digital techniques
Few-shot Learning
Phenotype Discovery
Universal Representations
Text
Thesis
Advisor: Ng Andrew
Piech Chris
A Computational Analysis of Inter-Authorial Influence Within Fanfiction Communities

Although fanfiction is built on existing media properties, its reliance on shared worldbuilding and inspiration makes patterns of influence much more apparent within given communities than in other media environments; some call this derivative. Rather than debating the merits or weaknesses of fanfiction or making value judgments regarding its supposedly derivative nature, this project explores the role that influence — in particular, inter-authorial influence — plays in fanfiction production. Within literary communities where every work is already explicitly based upon one common world or group of characters, what does it mean when a fanfiction author cites a separate piece of fanfiction as inspiration for their work? Is this author’s work more similar to that one fanfic that inspired it than to every other fanfic centered around the same world or characters? My hypothesis is that fanfics that cite another fanfic as their inspiration will be more similar to their inspiration fanfic than to other fanfics within the same fandom in both in terms of the words used in the stories and in terms of the overall emotional arcs of the stories. This project explores whether fanfic pairings in which one work was cited as having inspired the other are more similar to each other than fanfic pairings within the same fandom but without any noted influence according to the metrics of cosine similarity and sentiment-arc variance.

Keywords: fanfiction
Cosine Similarity
Natural language processing (Computer science)
Influence (Literary, artistic, etc.)
Fan magazines
Text
Thesis