VictorJuiz/thesis huggingface dataset:
Towards dignity in health : from health-white associations to the reclamation of racial-ethnic minority cultures of health
Keywords: Humanities and Sciences.
Psychology.

In 1948, the World Health Organization sought to define health for all peoples beyond the absence of negative symptoms (e.g., illness and disease) to include broad positive aspects (e.g., mental and social well-being), "the enjoyment of which, " it declared, "should be part of the rightful heritage of every human being without distinction of race, religion, political belief, or economic or social condition". Over 75 years later, studies suggest Americans have not adopted this more positive and inclusive definition of health. This dissertation examines the United States' culture of health promotion and how well it resonates with the nation's rapidly growing population of racial-ethnic minority Americans. In this dissertation, I present theory and evidence suggesting that public health promotion in the U.S.--which ought to support the health and well-being of all Americans--privileges some identities and marginalizes others, often the very groups they hope to reach. Using an array of methods, I demonstrate that health and well-being is represented in inequitable ways and suggest how racial-ethnic minority Americans can reclaim a sense of being healthy that feels authentic, affirming, and regenerative of their racial and cultural identity. First, I provide evidence that being healthy is implicitly associated with White people (and being unhealthy with people of color) (Study 1a), an association that extends to health behaviors like eating a nutritious diet (Study 1b). Investigating nutrition promotion more closely, I find that associations between healthy foods and White people also manifest explicitly (Studies 2a-b), and that this conceptualization of health undermines preference for nutritious foods. In light of this problem, I develop and test intervention messaging (Study 3) that more effectively supports racial minorities as they reclaim their healthy food-ways by acknowledging diverse, nourishing culinary traditions beyond those of Euro-centric cultures that currently dominate nutrition promotion. By counteracting stigmatized narratives within healthy eating promotion and offering more affirming and agentic interpretations of health and self, this dissertation presents a critical step towards racial minority Americans reclaiming what it means to eat healthy and be well
Towards high-performance discontinuous Galerkin simulations of reacting flows using legion
Keywords: Engineering.
Aeronautics and Astronautics.

High-fidelity scale-resolving computational fluid dynamics (CFD) simulations may provide a path towards predictive capabilities for many engineering-relevant applications, in particular those involving the interaction between multiple physics such as turbulent multi-component reacting flows. However, their routine use is hindered by their cost. The throughput of the fastest supercomputers is fortunately still increasing but this comes at the cost of specialized devices and hardware heterogeneity. Modern supercomputing thus imposes new requirements onto numerical algorithms and their implementation for leveraging the available compute while significantly complicating the design, development, and maintenance of massively parallel computational physics software. This dissertation focuses on addressing numerical and implementation challenges of CFD of multi-component reacting flows. It considers high-order discontinuous Galerkin (DG) discretization methods as a way towards a more efficient use of modern compute architectures for performing high-fidelity simulations of configurations involving complex geometries. Both the high accuracy requirement and the ability to accommodate unstructured meshes are key motivations for investigating this class of numerical schemes. The entire content of this manuscript is based on DG-Legion, a novel unstructured DG CFD solver for the compressible Navier-Stokes equations written on top of the Legion system for targeting distributed heterogeneous architectures. The main challenge related to the computer science aspect was to scale the code on GPU supercomputers. An explicit ghost formulation is proposed which results in performance competitive with state-of-the-art solvers based on the message-passing interface (MPI) system while the application code remains free of explicit communication and synchronization, i.e. it has sequential semantics. The contribution related to the numerics addresses two important questions. First, the issue of spurious pressure oscillations generated by fully-conservative schemes for thermally perfect mixtures is analyzed in detail. A generic framework is developed in order to generate systematic variations of the baseline scheme with improved properties. When applied to the problem at hand, several techniques that were previously proposed independently are recovered as special cases in a rigorous way. Finally, a hybrid strategy for preserving the positivity of DG solutions for the composition-describing scalars is introduced. The method based on the composition of subcell finite volume schemes and linear-scaling limiters leads to an overall positivity-preserving scheme in the inviscid limit, compatible with higher-order quadrature rules, and better preserving the subcell resolution compared to only using rescaling techniques
Towards longitudinal mapping of transportation infrastructure with spatio-temporal generative modeling
Keywords: Super-Resolution
Remote-sensing images
Transportation > Planning
Generative Adversarial Networks (GANs)
Climate change mitigation
Artificial intelligence > Industrial applications
Machine learning > Industrial applications
Text
Thesis

This work proposes a super-resolution pipeline to generate high resolution satellite imagery for a preferred point in time. We use a spatio-temporal generative model to perform super-resolution of low spatial resolution (LR) satellite imagery from the preferred time, conditioning on high resolution imagery (HR) from another time to generate HR satellite imagery for the preferred time. To train the spatio-temporal generative model, we curated the largest-ever super-resolution dataset of satellite imagery at sub-meter resolution, consisting of over 96, 000 image triplets. We present a proof-of-concept of this approach by evaluating the performance of our generated imagery on a sidewalk segmentation task. Our results demonstrate that our pipeline generates high spatial resolution images that are structurally similar to the original high resolution satellite imagery while accurately reproducing the style and content of the input low resolution imagery. Furthermore, our generated imagery outperforms LR imagery in the sidewalk segmentation task, providing compelling evidence for the utility and effectiveness of our approach. Since LR satellite imagery is available longitudinally at large geographical scale, researchers can use our pipeline to generate HR satellite imagery for their preferred time and location. Future work could leverage generated longitudinally available HR satellite imagery to longitudinally map transportation networks to inform and evaluate transportation planning.
Towards neural graph databases
Keywords: Engineering.

Graph databases are the primary workhorse for storing and organizing structured information over real-world entities. The core task on graph databases is query answering. The objective is to execute a given query of interest and retrieve answers to the query from the underlying graph. However, a major challenge is that data in graph databases are often massive, noisy, and incomplete. Relationships between entities keep changing, which is extremely hard to keep track of. Execution of a query over noisy and missing data leads to answers of poor quality. This significantly limits the application of graph databases in many scenarios. Neural graph query answering algorithms aim to address the challenge via embeddings and representation learning. The idea is to map complex queries and graph data to a latent space. This field has witnessed substantial growth, with extensive research focusing on both theoretical and practical dimensions, addressing various queries and graph types with efficient systems. In this thesis, we introduce the concept of Neural Graph Databases (NGDBs) where neural graph query answering is at its core. NGDB consists of a Neural Graph Storage and a Neural Graph Engine, extending the idea of graph databases. Under NGDB, we provide a collection of neural graph query answering methods, datasets, systems, metrics, and broad applications. In Chapter 2, we start with the definitions of different types of graphs, graph queries, fuzzy logic, and graph representation learning. This serves as the foundation and background of the thesis. In Part I, we discuss two works on query embeddings, Query2box and BetaE. Query2box introduces the first neural graph query answering algorithm that models existential quantification, disjunction, and conjunction operations. BetaE further extends its capabilities to include the negation operation. In Part II, we design the first and most scalable system, SMORE, which allows for the training of neural graph query answering algorithms on extremely large graphs. In Part III, we introduce the overall framework and components of NGDB. We further provide a unified taxonomy of existing neural graph query answering algorithms from the perspectives of graphs, modeling, queries, and datasets. Together the thesis introduces the task of neural graph query answering and the framework of NGDB, presents two novel algorithms, and points out promising directions, unsolved problems, and applications of NGDB.
Towards perceptually realistic gaze-contingent virtual and augmented reality displays
Keywords: Engineering.
Electrical Engineering.

Virtual and augmented reality (VR/AR) display systems strive to generate perceptually realistic user experiences, that is, the ability to render digital objects that a human observer cannot distinguish from a real object. Current-generation systems have made significant progress towards this goal, however still struggle to match the spatio-temporal and depth sensing capabilities of human vision, constrained by the limited compute budgets, hardware, and transmission bandwidths of wearable computing systems. Gaze-contingent rendering and display paradigms have emerged as a promising solution. Enabled by recent developments in wearable eye tracking systems, this suite of techniques utilizes real-time eye movement sensing to adjust content to reduce bandwidth requirements or improve visual experience. In this dissertation, we introduce and evaluate several approaches that aim to create more perceptually realistic VR and AR experiences using gaze-contingent display techniques. We model both the spatio-temporal sensitivity of the human visual system and how perception is affected by the distribution of visual attention. In both cases we demonstrate that exploiting these effects could significantly improve potential bandwidth savings of existing approaches. Next, we demonstrate how these bandwidth savings are directly dependent on the latency of the gaze-contingent display system, showing that reducing the latency of current generation systems could enable up to double the bandwidth savings. Finally, we describe how gaze-contingent stereoscopic rendering can improve the accuracy of disparity and depth rendering, including improving shape distortion in VR and alignment of physical and digitally rendering objects in AR
Towards quieter supersonic flight : a computational aeroacoustic study of high-speed jets
Keywords: Engineering.
Aeronautics and Astronautics.

Using large-eddy simulations (LES) and the Ffowcs Williams-Hawkings (FW-H) method, this thesis studies aeroacoustic phenomena in high-speed jet flows from supersonic aircraft engines. The work is divided to two parts. The first part focuses on jet screech in an underexpanded rectangular jet plume—a challenging aeroacoustic resonance emitting disruptive tonal noise. A detailed numerical study identifies optimal mesh designs and FW-H sampling, yielding accurate screech results with moderate computational and storage costs. This investigation reveals that screech involves energy transfer between the upstream-traveling guided jet mode and the downstream-traveling Kelvin-Helmholtz wave. Distinct regions in the spatially developing jet can be identified based on the wave energy of oppositely-moving waves. The near-nozzle region is found to be related to the receptivity of the initial shear layers, followed by a region further downstream where the wave energies reach maximal values. The SPOD modes can be used to reconstruct the amplitude and directivity of the fundamental screech tone with Lighthill's acoustic analogy. The second part of the thesis centers on dual-stream coaxial nozzles with internal mixing geometries for noise reduction in supersonic business aircraft. Analysis of nearfield flow turbulence highlights internal shear layers and wakes introduced by the mixing geometry, impacting the near-nozzle external jet flow even in absence of the temperature and velocity differences between the two streams. Two coaxial nozzles with an internal center plug and a mixing duct are studied: one with a 16-lobe mixer and one without. A comparison of the coaxial jet with its fully mixed equivalent single jet condition shows that the coaxial jet is louder in the downstream direction. The equivalent single jet emits acoustic tones in the upstream direction, likely due to the excitation of instability waves in the shear layers. Overall, this study improves the understanding of screech generation and coaxial jet aeroacoustics, offering insights for quieter supersonic aircraft design in the future.
Toxic positivity : integrating folk music and digital instrument design
Keywords: Humanities and Sciences.
Music.

This dissertation focuses on the interactive dynamics between electronic and acoustic instruments fused with the rich and diverse folkloric sounds of Turkey. The performance practices of folk instruments are incorporated into Western symphonic instruments and their capabilities are extended through technological means. Unpredictable pairings of acoustic and electronic instruments are explored to create unconventional timbres as well as subvert traditional instrumental roles. Multiple contrasts merge: Digital vs. Acoustic and Western vs. Folk
Tracing T cell clonal responses to chronic antigen stimulation using single-cell T cell receptor sequencing approaches
Keywords: Medicine.
Microbiology and Immunology.

T cells play a central role in the immune response, protecting the host against immune challenges while maintaining self-tolerance. During acute infection, naïve T cells are activated in response to antigen and differentiate into memory precursors and effector T cells. Upon antigen clearance, effector T cells undergo apoptosis while memory cells survive and persist as long-lived memory T cells that are ready in case of subsequent infection. In settings where antigen stimulation persists, as in chronic infections and cancer, T cell development is modulated, such as through the development of exhausted T cell states characterized by limited effector function and high sustained expression of inhibitory receptors. How T cell responses to chronic antigen stimulation develop and are maintained are not well understood, especially at the level of individual T cell clones. Recently, the development of single-cell genomics technologies has enabled high-resolution profiling of the T cell compartment at the clonal and phenotypic levels. In particular, the ability to sequence the T cell receptor (TCR) of individual cells in parallel with gene expression allows for the dissection of the TCR repertoire in the context of cell states and finer interrogation of T cell clonal dynamics. Here, we dissect various aspects of the T cell response to chronic antigen stimulation by tracing clones using TCR sequencing methods. First, we demonstrate that CD4 T cell responses are maintained during chronic viral infection by a memory-like progenitor population. Then, we profile the T cell response to immune checkpoint blockade and characterize the regional distribution and cell states of T cell clones within the tumor, lymph nodes, and peripheral circulation of patients with lung cancer. Altogether, this work demonstrates how clonal tracing through single-cell TCR sequencing technologies and computational approaches can be leveraged to uncover features of T cell responses to chronic infection and cancer, and how this approach can be extended to other settings of immune challenge.
Transformations of methane and carbon dioxide to chemical feedstocks, fuels, and materials
Keywords: Engineering.
Mechanical Engineering.

Global warming and associated climate change effects are the defining issue of the 21st century and decarbonization of all sectors is imperative to mitigate the worst consequences of climate change. Of particular importance are new, cost-effective, and greenhouse-gas-emissions-free chemical transformation processes to convert CO2 into chemicals, fuels, and materials. This is in contrast to today's processes for producing chemicals, fuels, and materials, as nearly every such process produces direct and/or indirect CO2 emissions. As a result, the paradigm shift that needs to occur is the transition from fossil-based sources for chemicals, fuels, and materials production to the use of CO2 itself to produce these products, as this would allow for negative emissions by sequestering CO2 in solid form. However, due to CO2's negligible value from a thermodynamic standpoint; nearly every CO2 transformation is endothermic, requiring energy. This required energy can take the form of clean, emissions-free electricity obtained from solar and wind, for example, but widespread proliferation of renewable sources of electricity generation has yet to occur and the challenge of grid-scale energy storage has not yet been adequately addressed. A better alternative for this required energy exists in the form of a co-reactant with high enthalpy, such as CH4. CH4 is arguably the most advantageous co-reactant due to its abundance and relatively low cost. Therefore, CH4 and CO2 are expected to be the feedstocks of the future to produce fuels, chemicals, and materials. Three such processes to transform CO2 and CH4 to chemical and fuels are discussed at length in this dissertation: 1) low temperature CO2 utilization via reverse water-gas-shift chemical-looping, 2) CH4 pyrolysis for the production of CO2-free H2 and carbon nanotubes, and 3) photocatalytic direct CH4 to CH3OH
Translation matters : tracing the transmission of medieval texts from manuscripts to MOOCs
Keywords: Humanities and Sciences.

This dissertation meets at the convergence of three areas of interest: Old English acts and attitudes of translation, manuscript studies both traditional and through a digital humanist lens, and, finally, the pedagogical opportunities that aim to equip and inspire future generations of learners. Using the Oxford English Dictionary's different meanings of the word "translation," it traces translation through acts of conversion, movement, transfer, and transformation. Part One describes these areas of interest and provides an introductory framework for the project. In the sections of Part Two, I examine translation as conversion. In focusing on translation as conversion, this assessment looks particularly at narratives of conversion and translation as described in Bede's Ecclesiastical History through notable figures such as Augustine of Canterbury, King Oswald of Northumbria, and Cædmon of Whitby. In Part Three, I discuss the notion of translation as movement. This section builds on the robust research of manuscript provenance, but this exploration also envisions how this line of inquiry can be reshaped and enriched in the digital age. It does so by discussing a digital mapping project that visualizes manuscript movement—or, the lives of manuscripts. In the next section, I introduce the role of manuscript digitization and curation, paleography, and online learning, specifically through a series of MOOCs created in a collaboration between Stanford University and Cambridge University called "Digging Deeper." Part Five contains a manuscript description of selected manuscripts of the Old English version of the Gospels, giving special consideration to newly discovered and identified artifacts since the publication of a critical edition of this medieval text. I conclude this study looking backward and forward: backward to the traditional mode of manuscript studies in detailed descriptions of textual artifacts, and forward to future opportunities of collaborative, often digital, work. Understanding the relevance of early translation will help new scholars appreciate translational echoes found in an increasingly accessible and inviting scholarly community. Breaking the glass on hermetically sealed texts and their histories both expands how Old English can be accessed by the masses and how Old English can be carried to new heights by non-traditional scholars, celebrating an elevation through equity.
Translational cardiovascular surgical engineering for enhanced biomechanics and device development
Keywords: Engineering.
Mechanical Engineering.

Valvular heart disease is a significant cause of global morbidity and mortality, and most of these diseases are rooted in nuanced biomechanical changes. While surgical intervention has been a mainstay for treatment of many conditions, techniques and devices have been developed primarily based on anatomic principles and guided by appearance and function of the diseased valve, yet new innovations in ex vivo cardiac simulation have enabled the rapid and safe testing of surgical operations and therapies, offering new insights into the nuances of valvular disease and repair. This dissertation contributes to and expands upon the field of study of valvular diseases and surgical treatments and devices as well as modeling modalities and the engineering tools to study these diseases and innovate new solutions for a wide range of diseases including mitral valve prolapse, systolic anterior motion, annular dilation, rheumatic mitral valve, COVID-19, and various aortic pathologies. The following research work has resulted in a significant clinical impact on valvular repair as well as prosthesis and device design, and this work will continue to serve as a foundation for the future expansion of translational cardiovascular surgical engineering, bringing science to art to improve patient care around the world.