VictorJuiz/thesis huggingface dataset:
Time-lapse inverse theory [electronic resource]
Keywords: Geophysics.

Compaction in reservoir overburden can impact production facilities and lead to a significant risk of well-bore failures. Prevalent practice of time-lapse seismic processing of 4D data above compacting reservoirs relies on picking time displacements and converting them into estimated velocity changes and subsurface deformation. This approach relies on prior data equalization, and requires a significant amount of manual interpretation and quality control. In this thesis I develop methods for automatic detection of production-induced subsurface velocity changes from seismic data, and computational techniques of subsurface characterization from measurable surface deformation. In the first part of my work I describe a time-lapse inversion technique based on a simultaneous regularized full-waveform inversion of multiple surveys. I provide a theoretical foundation of the proposed method, and analyze its sensitivity to a realistic 1-2% velocity deformation in the overburden. The method is applied in a study of overburden dilation above the Gulf of Mexico Genesis field and achieves a stable recovery of "blocky" negative velocity anomalies above compacting reservoirs. I propose a multi-scale extension of the method for recovering both long and short-wavelength velocity changes. In the second part I describe a geomechanical model of overburden deformation in response to fluid extraction or injection. I provide a method for inverting pore pressure changes from noisy and sparse measurements of surface deformation. The method is applied to estimating the efficiency of Cyclic Steam Stimulation (CSS) of a heavy oil reservoir. Inverted subsurface pore pressure changes indicate a significant heterogeneity of the propagating steam fronts. The method is extended to a study of sharp contrasts in reservoir attributes by using a new splitting algorithm for solving large-scale constrained regularized optimization problems.
Tomographic full waveform inversion [electronic resource]
Keywords: Geophysics.

Full waveform inversion (FWI) is an extremely powerful yet challenging procedure for inverting seismic data in exploration seismology. Its great potential lies in its ability to produce high resolution subsurface models of the earth by directly inverting the recorded waveform using the full wave equation. This direct matching approach allows FWI to simultaneously invert all components of the data resulting in the least possible ambiguity and most accurate results that can be extracted out of the seismic data. However, the high accuracy of FWI comes with high sensitivity to errors in the starting velocity model and local minima issues. In other words, the same reasons that give FWI its great features also give it its most challenging requirement: a very accurate starting model. Failure to satisfy this requirement results in cycle skipping. This strict initial model requirement is more pronounced when inverting reflection data because of the increased complexity and depth ambiguity. As a result, most of the successful applications of FWI only use the early arrival data. The central goal of this thesis provides a new inversion procedure that retains all the advantages and benefits of FWI while avoiding its strict initial model requirement and cycle-skipping challenges. To achieve this goal, I modified FWI by combining its classical form with a modified form of wave-equation migration-velocity analysis (WEMVA). This combination manifests itself as an extension of the velocity model through virtual axes. I named the new method tomographic full waveform inversion (TFWI). By extending the velocity model with the appropriate axis, the modeling operator can match the observed data regardless of the accuracy of the starting model by using kinematic information from the extended axis even when cycle skipping occurs. We set up the inversion to extract all the necessary information from the virtual axes and smoothly collapse them back into the physical, nonextended form of the model. While it avoids the cycle-skipping problem, TFWI does come with its own challenges—namely, its high-computational costs and high number of iterations required. Throughout this thesis, several modifications, analysis, and solutions are provided to overcome these challenges and allow TFWI to be both robust and feasible. The final algorithm is applied to both synthetic and field data sets. In all examples, the initial model is very inaccurate, resulting in cycle skipping in all frequencies of the residual. The results show remarkable reconstructions of most features of the models for all scales where TFWI successfully inverts the kinematic and dynamic information of the data with outstanding robustness and accuracy.
Topics in causal and high dimensional inference [electronic resource]
Keywords: Statistics.

Causality is a central concept in science and philosophy. With the ever increasing amount and complexity of data being collected, statistics is playing a more and more significant role in the inference of causes and effects. This thesis consists of three Parts. Part I reviews the necessary mathematical languages so we can talk about causality. Three major approaches (by potential outcomes in Chapter 2, by graphs in Chapter 3, and by functions in Chapter 4) are described. They are in many senses equivalent or complementary to each other, and excel in different causal tasks. Part II considers the statistical inference of a single causal effect in the potential outcome framework. Chapter 5 reviews state-of-the-art matching and weighting methods. Chapter 6 proposes a new loss function tailored for propensity score estimation, which can boost the performance of the weighting methods. Chapter 7 reviews outcome regression and doubly robust inference and provides some insight to selecting propensity score models and constructing confidence intervals. Part III considers the statistical inference of multiple confounded effects. Chapter 8 introduces a confounding problem in linear model with latent variables. Two examples are given, one in genetics and one in finance. Chapter 9 proposes a twp-step procedure to adjust for the hidden confounding variables in high dimensional data. Chapter 10 presents the performance of this method in simulations and the two read data examples.
Topological phenomena in condensed matter physics [electronic resource]
Keywords: Physics.

In this thesis, we study the topological phenomena in 2+1 dimensional topologically ordered states with additional extrinsic structures. One type of extrinsic structures we will study in this thesis is extrinsic defect. We first introduce the conceptual scheme of extrinsic twist defects which are point-like defects associated with symmetries of the 2+1 dimensional topological states. We explicitly study several classes of examples. In particular, we study several class the projective non-Abelian braiding statistics of the twist defects which are fundamentally different from the statistics of intrinsic excitations in topological systems. We also find an example where the projective non-Abelian statistics of twist defects can be exploited for universal topological quantum computation, while the host state itself is not suitable for this purpose. Apart from twist defects, extrinsic defects in 2+1 dimensional topological states can take various other forms including line-like defects and point-like defects. For 2+1 dimensional Abelian topological states, we establish a general classification of all line-like and point-like defects. We develop a general method to analyze the quantum dimensions of all the point-like defects, a general understanding of their localized "parafermion" zero modes, and study the projective non-Abelian statistics of them. Another type of extrinsic structure this thesis focuses on is the layering structure of 2+1 dimensional topological states. We propose a general formalism for constructing a large class of 3+1 dimensional topological states by stacking layers of 2+1 dimensional topological states and introducing coupling between them. Using this construction, we can study interesting topological phenomena in 3+1 dimensions, including surface topological orders and 3+1 dimensional topological orders. As an interesting consequence of this construction, we obtain example systems with nontrivial braiding statistics between string-like excitations. In addition to studying the string-string braiding in the example system, we propose a generic topological field theory description which can capture both string-particle and string-string braiding statistics. Lastly, we provide a proof of a general identity for Abelian string statistics, and discuss an example system with non-Abelian strings.
Toughening materials with polymers in molecular-scale confinement [electronic resource]
Keywords: Materials Science and Engineering.

This work explores the mechanical and fracture properties of polymers in the extreme limits of molecular confinement, where a stiff inorganic phase confines polymer chains to dimensions far smaller than their bulk radius of gyration. We show that polymers confined at molecular length scales dissipate energy through a novel, confinement-induced toughening mechanism that involves the bridging and pullout of individual polymer chains. This mechanism contrasts with toughening processes in bulk and weakly-confined polymers and describes behavior that cannot be explained by existing entanglement-based theories of polymer deformation and fracture. We support the confined molecular bridging mechanism with a model that quantifies the nanomechanical processes occurring on the length scale of individual polymer chains. We show that the toughening is controlled by the molecular size and the degree of confinement, but is ultimately limited by the strength of individual molecules. This represents a fundamental limit on the ability of polymers to toughen nanocomposite materials. These insights overturn traditional expectations of how the toughness of a composite would change with increasing confinement of a constituent polymer phase. As the length scales of nanoscale devices and nanostructured materials continue to shrink, this unique property of confined polymers can increasingly be used in device and nanocomposite design.
Toward an objective neurophysiological measure of musical engagement [electronic resource]
Keywords: Music.

Engaging listeners is an inherent goal of music. The concept of 'musical engagement', however, carries multiple connotations and remains difficult to quantify or even define. In particular, an objective measure of musical engagement is lacking. Over past decades, cortical responses have been used to investigate processing of music. While these responses are objective and can be recorded in real time, they suffer from a low signal-to-noise ratio and reflect, at best, an abstraction of the corresponding stimuli. As a result, approaches to this research have historically focused primarily on controlled stimuli with limited ecological validity, and event-related averaging of responses, which requires short stimulus epochs and numerous stimulus presentations. Responses to real-world stimuli have proven challenging to analyze and interpret. How can we move beyond these limitations to derive a measure of engagement with 'real' music (i.e., naturalistic and complete musical works) from the brain response? In this thesis, we address these limitations by introducing a novel analysis framework for interpreting listeners' responses to music, with the ultimate goal of developing a meaningful, quantitative, and dynamically changing index of musical engagement. We draw from recent approaches in neuroscience and physiology that use synchrony of audience responses to study engagement in other domains. Specifically, we examine time-resolved inter-subject correlations (ISCs) of cortical, physiological, and behavioral responses to musical pieces heard in their entirety. The current approach is facilitated by a recently developed method that efficiently extracts relevant, stimulus-related activity from a complex, noisy response. This method allows for full-length, ecologically valid stimuli to be presented in a single-listen experimental paradigm. The proposed methodologies are tested and evaluated in two experiments. First, we validate the approach by deriving cortical components from scalp-recorded electroencephalographic (EEG) responses to intact and scrambled songs and computing their ISCs. In a second experiment, we broaden the context of the approach by comparing EEG-ISCs to the activity and synchrony of physiological and continuous behavioral responses. This work makes several novel contributions to the field of music cognition. First, we show that the presence of temporally relevant musical features produces a consistent component topography in the brain response. Furthermore, the ISCs computed from this component are higher when such musical features are retained. We additionally employ a novel approach to experimental design, choosing highly engaging stimuli that were unknown to our participants, and introducing computational procedures for manipulating the stimuli. Finally, we demonstrate that brain responses to full-length musical works from various genres and styles can be successfully analyzed in a single-listen paradigm.
Towards an organizational theory of occupational expansion : an ethnography of sales in design consulting
Keywords: Management Science and Engineering.

This study examines how a professional service firm intentionally wins aspirational projects at the edge of the constituent occupation's typical domain of work, thereby expanding the occupation's social mandate. This approach to studying occupational expansion contrasts with most prior organizational scholarship which has typically focused on how, within integrated organizations, different occupations undercut each other and conflict with norms of bureaucratic administration. Drawing on an ethnography of salespeople and design practitioners at two design consultancies, I detail the challenges and tactics uniquely attendant on accomplishing occupational mandate expansion as a firm dedicated to that goal. The findings suggest that accounts of firm-based occupational expansion will likely depend on understanding three kinds of dynamics as they play out through cycles of new business acquisition: (1) maintaining fidelity of occupational representation across a distribution of business acquisition labor; (2) conducting search for aspirational projects in an unanalyzable client environment; and (3) managing organizational knowledge in such a way that the firm can regularly improvise ad hoc models of occupational expertise that map to a prospective client's situation.
Towards industry-ready high-order flow solvers [electronic resource] : increasing robustness and usability
Keywords: Aeronautics and Astronautics.

High-order methods are truer to the flow physics and more accurate per degree of freedom than low-order methods. Their high computational intensity relative to their communication requirements makes them prime candidates for implementation in the latest hyper-parallel computing architectures like Graphical Processing Units (GPUs). Why are they not more prevalent in the toolset of design teams? One of the main barriers to wide adoption of high-order numerical methods in industrial applications is the schemes' low robustness relative to low-order methods. Their stability is highly dependent on the quality of the grid, even when the solution is relatively smooth. Aliasing, underresolution, and non-smoothness are the main causes of instabilities. This dissertation proposes solutions from two fronts: the creation of a set of families of numerical schemes with guaranteed linear stability and tunable dispersion- dissipation properties, and the formulation of filters with spectral effectiveness and element-local stencil. To ease the adoption, or increase usability, of high-order methods in industry and academia, a well-documented, validated, verified, and constantly improved source code is needed. This dissertation walks the reader through the efforts by the Aerospace Computing Laboratory (ACL) to provide such code: High-Fidelity Large Eddy Simulation (LES) Open Source Code (HiFiLES) (hifiles.stanford.edu).
Towards multi-wavelength observations of relativistic jets from general relativistic magnetohydrodynamic simulations [electronic resource]
Keywords: Physics.

A methodology for reverse engineering current and anticipated observations of astrophysical relativistic jets using self-consistent, general relativistic magnetohydrodynamic (GRMHD) simulations is detailed from data-hosting and manipulation to mimicking instrument-specific properties such as point spread function convolution. This pipeline handles particle acceleration prescriptions, synchrotron and inverse Compton emission and absorption, Doppler boosting, time-dependent transfer of polarized radiation and light-travel time effects. Application of this pipeline to low-frequency radio observations is exemplified using the famous jet in the giant elliptical galaxy M87. High-frequency gamma-ray observations are represented by the powerful quasar 3C 279. Though the work presented here focuses on a single simulation of a magnetically arrested disk and a wind-collimated, approximately force-free jet, it can readily be adapted to simulations with different spatiotemporal resolutions and/or plasma initial conditions. Stationary, axisymmetric semi-analytic models are also developed, providing a quantitative understanding of the simulated jet flow and its electromagnetic properties. Using the 3D time-dependent \say{observing} routines for synchrotron models, predictions such as bilateral asymmetry of intensity maps and enhanced limb brightening for models with high velocity shear are advanced. Using gamma ray prescriptions in the routines resulted in rapid variability. User-friendly Python and UNIX guides are included for didactic purposes. With the advent of the state-of-the-art gamma ray Cerenkov Telescope Array, the Event Horizon Telescope-- which promises to resolve Schwarzshild radius ( _S$) scale features at the Galactic Center and M87-- and more sophisticated GRMHD simulations with similar resolution coupled with dynamical range
Towards personalized medicine in understudied populations [electronic resource] : coagulation and anti-coagulation in African Americans
Keywords: Genetics.

Personalized genomic medicine uses a patient's genetic information to assess disease risk or to make decisions about drug dosing. However, genetic risk variants in one population do not always represent risk in another population. Research across a diverse set of populations identify important population-specific risk variants, and reveal new biology by associating new pathways to a phenotype. In this thesis, I undertook multiple studies that addressed personalized genomic medicine in the context of diverse populations. First, I developed a tool for assessing ClinVar designated pathogenic variants in genetic data. I studied the distribution of variation across different populations and found differences between populations in the number of Clinvar designated pathogenic variants. Most studies look at genetic variants in isolation -- that is, each variant is tested for an association with a phenotype. However, these methods make it difficult to detect signal from rare variants and variants of modest effect. I created a method of aggregating variants across a biologically relevant pathway to detect signal missed in single loci analysis. With this method, I showed that the aggregate variation across the warfarin metabolic pathway explains some of the missing heritability in that phenotype. Finally, I focus on the genetics of diagnosing and treating clotting disorders in African Americans, a population with great phenotypic variability and understudied genetic risk. In this domain, I (1) created a method of aggregating variants across a biologically relevant pathway to detect signal missed in single loci analysis, which showed that the aggregate variation across the warfarin metabolic pathway explains some of the missing heritability in that phenotype; (2) identified a missense mutation (Val510Met) in the anti-coagulant Protein S which is associated with abnormal clotting in the African American population using a family study and a case-control analysis of 205 individuals; (3) using an extreme phenotype design and exome sequencing, I identified a population-specific regulatory variant in folylpolyglutamate synthase (FPGS), which is associated with lower warfarin dose in the African American population. In order to broadly understand the genetic risk factors affecting disease and drug phenotypes, we need studies in diverse populations. Here, I identified new, population specific variation associated with two such phenotypes -- coagulation and anticoagulation -- in an African American population.
Trade politics and China's image in the United States [electronic resource] : congressional discourse on the People's Republic
Keywords: Political Science.

China has played a role in American politics since the nineteenth century when politicians worried about a flood of immigrants coming across the Pacific, while today, their concerns center on topics such as trade policy, human rights, and national security. With China's growing international clout, understanding the logic behind politically motivated depictions of the PRC becomes increasingly important. This dissertation seeks to do that with a systematic analysis of the nature of American political rhetoric about China and how it has varied across time and space. Examining twenty-five years of Senate speeches, using natural language processing techniques and machine learning, demonstrates that trade politics play an important role in shaping rhetoric. First, while congressional conversations about China in the 1990s covered a variety of topics, since the early 2000s, they have focused primarily on trade, often with the goal of depicting China as an economic threat. Likewise, trade interests determine the sentiment of language used, as senators from states highly dependent on manufacturing are more negative, while senators from states that send a lot of exports to China are less so. Public opinion data confirm that there is a public constituency for negative rhetoric about the PRC.
Trajectory planning and control for an autonomous race vehicle [electronic resource]
Keywords: Mechanical Engineering.

Autonomous vehicle technologies offer potential to eliminate the number of traffic accidents that occur every year, not only saving numerous lives but mitigating the costly economic and social impact of automobile related accidents. The premise behind this dissertation is that autonomous cars of the near future can only achieve this ambitious goal by obtaining the capability to successfully maneuver in friction-limited situations. With automobile racing as an inspiration, this dissertation presents and experimentally validates three vital components for driving at the limits of tire friction. The first contribution is a feedback-feedforward steering algorithm that enables an autonomous vehicle to accurately follow a specified trajectory at the friction limits while preserving robust stability margins. The second contribution is a trajectory generation algorithm that leverages the computational speed of convex optimization to rapidly generate both a longitudinal speed profile and lateral curvature profile for the autonomous vehicle to follow. The final contribution is a set of iterative learning control and search algorithms that enable autonomous vehicles to drive more effectively by learning from previous driving maneuvers. These contributions enable an autonomous Audi TTS test vehicle to drive around a race circuit at a level of performance comparable to a professional human driver. The dissertation concludes with a discussion of how the algorithms presented can be translated into automotive safety systems in the near future.