VictorJuiz/thesis huggingface dataset:
Mesenchymal Stromal Cells Rescue Hypoxia-Induced Survival Defect in Ex Vivo Acute Myeloid Leukemia Cell Cultures
Keywords:  Department of Biology
Biology
Acute myeloid leukemia
Cancer
Hematopoiesis
Microenvironment
Niche
Conditioned media
Cytokines
Personalized medicine
Drug discovery
Stem cells
Hypoxia
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Thesis

Acute myeloid leukemia (AML) is an aggressive cancer characterized by the clonal accumulation of immature blood cells. The cancer stem cell model hypothesizes that healthy hematopoietic stem cells (HSCs), which populate the entire blood compartment, acquire lesions over time and become leukemia stem cells (LSCs). These mutant cells are responsible for disease progression and act as a reservoir of cancer-forming cells following chemotherapy, causing relapse. In healthy hematopoiesis, mesenchymal stromal cells (MSCs) in the oxygen-poor bone marrow microenvironment are the niche for HSCs, providing factors to maintain and regulate self-renewal and multipotency. Current efforts seek to understand the role of the niche in aberrant hematopoiesis. While efforts to replicate human disease are aided by the in vitro study of primary AML patient sample cells (APSCs), these studies do not typically recapitulate the presence of MSCs or the hypoxic conditions of the niche. I found that hypoxia decreases APSC growth, but this defect can be rescued in a non-contact-dependent manner by co-culture of APSC with MSC or culture of APSC in MSC-conditioned media (CM). Cytokine detection analysis showed that MSC-CM contained high levels of cytokines whose transcripts are also highly expressed in primary MSCs from healthy donors. Although no singular tested cytokine was necessary for APSC survival, I determined that the expression of cytokines and receptors can independently cluster healthy and leukemic cell subsets. Therefore, cytokine combinations may contribute to APSC survival. Collectively, these results show that MSCs are sufficient to enhance APSC survival in physiologic hypoxia. The niche-like ex vivo model I established will enable the translation of laboratory findings into clinical applications.
Methods for leveraging heterogeneity in gene expression and single-cell epigenetic data for systems immunology
Keywords: Medicine. Department of Biomedical Data Science

Traditionally, biomedical and translational studies are designed to be run as a controlled experiment, in which biological, clinical, and technical heterogeneity is controlled. Consequently, such a study does not represent real-world heterogeneity. As such, many results from these studies fail to translate in clinical practice. Frequentist meta-analysis has been repeatedly shown to better leverage heterogeneity across independent datasets and identify robust molecular signatures of a disease, which in turn can accelerate translation to clinical practice. However, this class of techniques has several disadvantages, including, 1) a lack of robustness to outliers, 2) a large number of hyperparameters for gene set selection, and 3) a heavy reliance on hypothesis testing and p-values. To overcome these disadvantages, in Chapter 1, I will introduce a Bayesian meta-analysis approach that addresses these issues and is better able to account for heterogeneity across disparate studies. Heterogeneity is not limited to transcriptomic data but exists in epigenomic data as well. Historically, technologies such as ChIP-seq and ATAC-seq have been able to measure epigenetics at a bulk level. EpiTOF, a recently developed technology, is able to measure abundances of post-translational histone modifications at a single-cell level. This technology has been leveraged to profile hundreds of healthy individuals from around the world presenting unique methodological challenges for analysis, including understanding the heterogeneity of histone modifications in the single-cell data. In Chapters 2 and 3, I will address work developing methods to reduce technical heterogeneity, analyze biological heterogeneity and leverage EpiTOF data to learn about epigenetic regulation at a single-cell level. In addition, I will discuss comprehensive and cell-type specific networks of HPTM interactions and histone modifications profiles associated with the myeloid and lymphoid lineages, as well as cellular life span
Methods for quantifying, representing, and utilizing uncertainty in learning-enabled autonomy
Keywords: Aeronautics and Astronautics.

In order to leverage the advances of machine learning (ML) to enable reliable robot autonomy in the unpredictable and unstructured real world, we must design ML models that can effectively quantify and represent uncertainty, and design planning algorithms that can leverage these estimates of uncertainty to ensure safe performance during deployment. However, standard ML methods often fail to effectively capture key sources of uncertainty that arise when deploying robots in the real world; in particular, the environmental uncertainty arising from partial observability, and the epistemic uncertainty arising from limited training data from test-time conditions. In the first part of this thesis, we develop tools for quantifying and representing uncertainty in ML models. Our algorithms combine a Bayesian perspective on uncertainty quantification with the expressive modeling capabilities of deep neural networks to yield efficient and dynamic representations of uncertainty. In the second part, we address how a learning-enabled autonomy stack should leverage uncertainty estimates when planning actions to take. In particular, we explore the notion of optimality when considering risk while planning with model uncertainty, and propose a Monte-Carlo planning algorithm which introduces a notion of robustness onto the classic explore-exploit tradeoff of reinforcement learning. We also extend these ideas to the continuous control setting, where we develop an approach for planning and learning in uncertain environments while maintaining probabilistic guarantees on safety, and demonstrate this approach in hardware. We conclude with a discussion of next steps and a broader discussion of the role of uncertainty modeling in learning-enabled autonomy, including key challenges and opportunities for future research
Methods for robust diffusion weighted body magnetic resonance imaging
Keywords: Electrical Engineering.

Diffusion weighted (DW) imaging is an increasingly common Magnetic Resonance Imaging (MRI) contrast in the clinic. There are several clinical applications that do not yet benefit from diffusion weighted imaging, owing to image artifacts encountered by conventional diffusion acquisitions. DW Fast Spin Echo (FSE) sequences are robust to field non-uniformities, but the non Carr-Purcell-Meiboom-Gill (CPMG) artifact must be addressed. Two different novel imaging reconstructions that can be applied to address the non CPMG artifact, were developed. The first reconstruction leverages calibrationless imaging and compressed sensing ideals to reduce the effect of T2 blur using shot locally low rank regularization. Combined with a diffusion prepared stimulated echo FSE sequence, it is shown to have reduced image distortion compared to conventional multi-shot DW-EPI techniques, and improved apparent resolution compared to vendor provided distortionless DW-FSE PROPELLER. The second reconstruction is a joint linear reconstruction for multi-shot quadratic phase increment data that can be acquired without a signal penalty. This reconstruction corrects ghosting artifacts from both shot-to-shot phase and intra-shot signal oscillations. A thorough analysis on the condition number of the proposed linear system shows that the conditioning is the same as applying parallel imaging to each shot, in the worst case, and the same as a standard multi-shot reconstruction in the best case. A clinically feasible sequence that achieves DW imaging near metal with moderate b-values and volumetric coverage in clinically feasible scan times, using diffusion-prepared FSE, was developed. Application of root-flipped Shinnar-Le Roux refocusing pulses permits preparation of a high spectral bandwidth, which improves imaging times by reducing the number of excitations required to cover the desired spectral range. B1 sensitivity is reduced by employing an excitation that satisfies the CPMG condition in the preparation. The gradient waveform used for ADC quantification was shown theoretically and experimentally to be insensitive to background gradients. Application in vivo demonstrates complementary contrast to conventional multispectral acquisitions and improved visualization compared to DW-EPI. Finally, a computationally efficient tool for optimizing the Cramér-Rao Lower Bound (CRLB) of quantitative sequences without using approximations or an analytical expression of the signal was developed. Automatic differentiation was applied to Bloch simulations and used to optimize several quantitative sequences without the need for approximations or an analytical expression. The results were validated with in vivo measurements and comparisons to prior art. The CRLB of the Magnetic Resonance Fingerprinting (MRF) sequence, which has a complicated analytical formulation, was optimized using automatic differentiation
Microbial life on and below the seafloor : trends in anabolic activity in space and deep time
Keywords: Earth System Science.

The seafloor covers two thirds of our planet's surface and plays an essential role in maintaining planetary habitability and climate stability. In particular, microorganisms on and below the seafloor are the final gatekeepers of organic carbon burial, affecting oxygen production and carbon sequestration on geologic timescales. Although marine sediment archaea and bacteria are fundamental in Earth's elemental cycles, we know little about their anabolic activity rates, the physicochemical drivers of their metabolisms, the dominant players, and how their activity might change spatially and temporally. In the research described in this dissertation, I set up around 840 microcosm experiments to measure rates of specific benthic microbial metabolisms (total anabolic activity, heterotrophy, inorganic carbon fixation, and nitrogen fixation) in two global oceans. I used both manipulative and correlative approaches to identify key physicochemical controls on activity, and extrapolated rates of activity through space and deep time. In chapter 1, I improved the quantitation of cell-specific anabolic activity rates by tracking the effect of sample preparation on cellular isotope enrichments. I found that sample preparation decreases isotope enrichments by up to 80% -- much more than previously reported. I make recommendations for how to account for this effect experimentally and analytically. In chapter 2, I found that microbial anabolic activity in Pacific and Atlantic deep-sea sediments is primarily controlled by the availability of organic carbon and/or energy, not bioavailable nitrogen, and can be predicted by distance from shore. Using this insight, I demonstrated that shifting continental configurations in the last 400 million years might have significantly impacted benthic microbial activity, making a novel link between tectonics and microbiology. In chapter 3, I further explored carbon and energy limitation in surface sediments from Monterey Bay, California, and discovered that the microbial community is in fact limited by energy, not carbon. And in chapter 4, I found that the hydrothermally-influenced, deep marine biosphere at Guaymas Basin is active, and is exclusively composed of heterotrophs. But interestingly, these deep subsurface heterotrophs obtain ~5% of their carbon from inorganic sources. Together, marine benthic microorganisms live on the micron-scale, but they have outsized, long-term impacts on global biogeochemical cycles due to their sheer abundance and vast distribution
Microwave-optics quantum frequency conversion and optically heralded microwave photons
Keywords: Applied Physics.

The internet has greatly changed the way we live our daily lives. One of the enabling components of the internet is the telecom transceiver. It converts information in the electrical signals from our phones and laptops, to variations of light in an optical fiber, where the light propagates kilometers without significant loss. Similar to how the internet revolutionized processing of classical information, a quantum internet that connects different quantum systems could enable secure communication, powerful new computers and sensors. Superconducting circuits form one of the leading platforms for manipulating quantum information, offering great nonlinearity, decent coherence, and accessible control and readout. However, they operate at millikelvin temperatures with microwave photons, which are easily overwhelmed by loss and thermal noise at room temperature. As a result, quantum frequency converters between microwave and telecom photons that resemble the classical transceivers are desired. In this dissertation, I will describe our efforts towards realizing such a converter. Our approach utilizes a gigahertz mechanical resonance as an intermediary between microwave and optics. I will first discuss how we strongly couple telecom frequency photons and gigahertz mechanical vibrations with cavity-optomechanics. Such coupling offers the nonlinearity required for the frequency conversion. Meanwhile, the mechanical vibrations can be driven and readout with microwave circuits using piezoelectric effect. To realize this two-step conversion process, we began with design and fabrication of optomechanical crystals using an emerging photonic circuit material platform, thin-film lithium niobate, which also possess great piezoelectric properties. I will uncover the challenges and solutions of using piezoelectric effect to drive and readout the mechanical resonance with interdigital transducers and microwave circuits. Improving the optomechanical interaction eventually led us to a hybridized material platform of lithium niobate on silicon on insulator. Combining efficient optomechanical and piezoelectric coupling resulted in a fully integrated converter with unprecedented efficiency to let us observe a microwave photon from the device heralded by optical single photon detection. The potential improvements and applications of our converter are discussed
Millions of Voices, Suddenly Silenced: Using Science Fiction to Understand Genocide
Keywords: Genocide
Holocaust History
Science fiction
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Thesis

Sean Gallagher’s capstone project focused on the legal, social, and historical definitions of genocide and how this is constructed in the public imaginary. Through an analysis of Article Two of the Genocide Convention, Sean sought to understand how genocide is conflated with similar terms, such as mass killings, and how this has influenced its relationship to world events. He specifically studied how the Holocaust influenced modern definitions of genocide and blended the concepts of genocide and mass killing in the popular consciousness. To fully understand the underpinnings of the term genocide, Sean also utilized science fiction and the phenomenon of cognitive estrangement as a mechanism to understand genocide from the perspectives of perpetrators, victims, and bystanders, separating the legal concept from the popular (mass-murder focused) concept of genocide.
Mind The Gap: The Impact of the Gender Composition of College STEM Courses on STEM Degree Completion
Keywords:  Department of Economics
Gender Gap
Classroom Peer Effects
STEM Education
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Thesis

Peer effects within classrooms are powerful as they can lead to a more optimal distribution of peers, thus improving educational outcomes, creating more efficient human capital investments, and promoting macroeconomic growth. I attempt to measure gender peer effects within STEM education by employing a strategy that exploits variation in STEM interest among females across cohorts within a particular school as a source of idiosyncratic variation. To measure the effect of gender composition within a STEM classroom on the probability that a student graduates with a STEM degree, I instrument the gender composition of a classroom on the share of women in that cohort who expressed an interest in STEM prior to their freshman year of college. I find that there are indeed gender peer effects in STEM education: a 10 percent increase in the proportion of females within a STEM cohort leads to a 7.77 percent increase in the share of females and a 5.52 percent decrease in the share of males graduating with a STEM degree. I also extend my analysis to examine the effect within certain racial groups and fields of study and find statistically significant results varying in magnitude and direction. I also find evidence that gender peer effects in STEM classrooms are non-linear: both men and women in STEM classrooms with a below-median female share are 32.67-33.24 percent more likely to graduate with a degree in STEM when there is a 10 percent increase in the female share of the classroom.
Mirages past and future : foreign expertise and the political economy of cultural heritage in Qatar
Keywords: Anthropology.

Arabian Peninsula states are investing tens of billions of dollars annually in cultural productions ranging from archaeology research and historic conservation to cultural events and tourism, monumental museums, art programs, and other heritage-based projects. The stakes are high: Qatar has declared cultural preservation is essential to its survival. Yet throughout the Gulf much of this work relies on non-citizens who may not share identities, experiences, and values with the citizens and nations they ostensibly represent. This dissertation uses ethnographic, historical, and archival methods to explore the significance and consequences of this system of international expertise. Gulf scholars typically explain the prevalence of expatriate culture experts as a wealthy society's rational response to a shortage of qualified 'local' professionals, to be rectified through specialized educational development. Instead, my research traces this system's roots to colonial-era archaeology expeditions, demonstrating that Qatar's decades-long construction of its cultural industry constitutes an active negotiation of authenticity rather than a simple nationalist project of modernity. Turning to experts, I show how North Atlantic expatriates' position as guests and at-will employees influence the perception and reception of their expertise. In this context expertise becomes positional, relational, about social life (and its limits) in addition to its technocratic enactments. Conversely, a new generation of Qatari cultural experts remains largely unrecognized due to enduring forms of global discrimination as well as the lenses of political economy through which outsiders typical view the region. Despite contestations of Qatari heritage by knowledgeable citizens, the results are largely productions which reproduce cultural narratives advantageous to the state—obscuring how heritage becomes a powerful mechanism for internal social change in addition to its international political value for Qatar. This research reorients heritage analysis from prevailing value-oriented theories of nationalism toward a concept of smart desire building from anthropology's tradition of studying up and decolonial critiques of Deleuze and Guattari. It also reconsiders the growing anthropology of expertise by delineating the constraints upon expert rule and complex limits of recognition. Anthropological attention to people creating cultural productions moves beyond the limits of political economies of heritage—restoring emphasis on process and agency, even as this project's approach contributes to a critical anthropology of the West
Modeling and Simulation for Sustainable Energy and Resources: Water Filtration systems and Underground Hydrogen Storage
Keywords: Renewable energy
Water > Purification > Reverse osmosis process
Hydrogen > Storage
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Thesis

Sustainable development has emerged as the defining human challenge of this century because of the sharp conflict between sustainability and current development practices. Among those conflicts, many populations are faced with severe water shortages, as well as greenhouse effects due to combustion of fossil fuels. For the purpose of realizing the transition to sustainable development and societies, new technologies and policies must be developed and implemented. While new approaches and technologies span a large variety of methods and application areas, we will focus on the analysis and study of two specific technologies: reverse osmosis (RO) membrane systems for water purification and underground hydrogen storage. In this thesis, we use a combination of mathematical modeling and numerical simulations to investigate, understand and predict the system response.
In the first part of the thesis, we focus on RO membranes, an existing technology whose impact on access to potable water is expected to grow significantly in the near future. Fundamental knowledge of the physical processes governing flow and transport in RO systems is critical to guide their design and optimization for maximum performance under different operating conditions. In particular, we study the impact of turbulent flow on RO systems performance through the extension of the in-house solver SUMembraneFOAM to turbulent flows, and derive a new Reynolds-Sherwood correlation, routinely used to design system-scale modules, in turbulent conditions. A classical approach to quantify membrane performance, and its propensity to foul, is to estimate concentration polarization (CP) in proximity of the membrane surface. Currently, classical thin film theory is used to approximate CP under specific flow conditions. We derive an analytical and exact expression to calculate CP in RO systems and demonstrate its accuracy. In the second part of the thesis, we focus on a preliminary study of subsurface H2 storage. It is currently suggested that H2 subsurface storage does not present additional challenges to those typically associated with CO2 storage. Here, we critically assess this hypothesis by quantitatively investigating the potential (dis)similarities between the behavior of H2 underground and that of CO2. Our preliminary investigation warns that unique and additional modeling challenges may be expected in the context of H2 underground storage, especially in reference to the validity of multiphase Darcy’s law. This knowledge is critical to assess the feasibility to store hydrogen, guide the design, optimize site selection, and achieve the storage capacities that are necessary for the transition to a net-zero emission energy system.
Modeling Brightest Central Galaxy Magnitude and Magnitude Gaps as Galaxy Cluster Formation History Tracers
Keywords:  Department of Physics
galaxy clusters
halo bias
formation history
Text
Thesis

The large scale spatial distributions of galaxy clusters depend on their masses and their formation histories. The latter, known as assembly bias, can be difficult to observe and necessitates the use of observable tracers of formation history to measure the impacts of assembly bias. We have created a new model to demonstrate how the correlation between dark matter concentration, a quantity correlated with cluster formation history, and two observable formation history tracers impact the large scale spatial distribution of high mass galaxy clusters. We introduce correlation between cluster concentration and magnitude gaps as well as brightest central galaxy (BCG) magnitudes in the Buzzard simulated catalogs and compare average galaxy number density profiles with data profiles for clusters with masses M_200 > 10^14 M⊙h^(-1). We demonstrate correlated galaxy number density profiles and comparisons to observed data for the Sloan Digital Sky Survey (SDSS) and Dark Energy Survey (DES) in this thesis. This work will be used as part of a larger effort to constrain the physical correlation between concentration and magnitude gaps and BCG magnitudes.