VictorJuiz/thesis huggingface dataset:
Dislocation dynamics of face-centered cubic metals and alloys [electronic resource]
Keywords: Mechanical Engineering.

Face-centered cubic (FCC) metals and alloys—such as aluminum, copper, and austenitic stainless steel—are ubiquitous in the automotive, aerospace, and oil and gas industries. To further our understanding of the nature of plastic deformation in these materials, we have utilized dislocation dynamics (DD) simulations. We begin with a study of time integration in dislocation dynamics, examining the time-step-limiting aspects of DD, and developing a new subcycling-based time integrator that improves efficiency 100-fold. We then utilize this time integrator to study the basics of plasticity in pure, single crystalline copper. DD simulations were run over a wide range of strain rates and initial dislocation densities, examining how the yield strength and hardening rate vary, and making comparisons against the available experimental data. A detailed study on the contribution of binary dislocation junctions to hardening is then presented, showing that these junctions are an essential ingredient for hardening to occur. We then go on to study the most common strengthening mechanisms employed in FCC metals: solid solution strengthening and precipitation strengthening. After deriving the suitable chemical potential for the solute atoms comprising a solid solution, the influence of an "atmosphere" of solutes surrounding a dislocation on the stress field and line tension of the dislocation are examined, showing that these effects are generally small. The drag force exerted on dislocations by their atmospheres is then studied. We find these drag forces are often larger than those due to lattice friction, and can influence plasticity in FCC materials significantly. To study precipitation strengthening, a new algorithm for simulating dislocation-precipitate interactions is developed, which allows for ellipsoidal inclusions with arbitrary aspect ratio and arbitrary misfit. The new formulation is used to study Orowan looping in overaged aluminum-copper alloys, which have plate-like precipitates. The results and methods presented here constitute a broad set of advancements towards a more sound understanding of plastic deformation in FCC metals and alloys.
Does Calcineurin Regulate the Osmotic Stress Response in S. cerevisiae Through the Smp1 Transcription Factor?
Keywords:  Department of Biology
Biology
Calcineurin
Phosphatase
Osmotic Stress
Smp1
Hog1 MAP Kinase
Thesis

Calcineurin is a conserved Ca2+/calmodulin-regulated phosphatase that regulates the T cell immune response, as well as many other processes, and is the direct target of immunosuppressant drugs (cyclosporin A and FK506). Because of its ubiquitous expression and prevalence in a broad spectrum of disorders, long term suppression of calcineurin also results in harmful side effects (Safa, Riella, and Chandraker 2013). The lack of sequence similarity in bona fide calcineurin substrates, save for conserved calcineurin docking sites ('PxIxIT' and 'LxVP' ), has hindered candidate substrate identification. However, there have been recent efforts in systematically screening potential substrates for these docking sites. This study investigates the possible interaction between calcineurin and Smp1, a yeast transcription factor that is activated via phosphorylation by Hog1 MAP Kinase (Hog1 MAPK) under hyperosmotic conditions. Using computational analysis, all possible 6-mers in Smp1 were screened for the potential to interact with calcineurin as a ‘PxIxIT’ site, generating seven high-scoring peptide sequences. The goal of this project was to investigate the potential interaction between Smp1 and calcineurin, using two approaches: 1) testing for direct binding of Smp1 and calcineurin in vitro, and 2) studying regulation of Smp1 activity by calcineurin in the presence of osmotic stress in vivo. Co-purification assays revealed that full length GST-tagged Smp1 binds to yeast calcineurin in vitro, and may bind at one of the computationally predicted ‘PxIxIT’ sites. In vivo functional assays revealed that calcineurin both positively and negatively regulated Smp1 activity, suggesting that calcineurin may regulate the Hog1 MAPK pathway through multiple substrates. Overall, these results suggest that calcineurin is intimately involved in the Hog1 MAPK pathway, and substantiates this computational approach for de novo identification of calcineurin interaction sites. This approach may be used for future identification of novel calcineurin substrates, and provide insight on how to selectively target calcineurin substrates.
The drift and minorization method for reversible Markov chains [electronic resource]
Keywords: Mathematics.

This thesis proves upper bounds on the convergence time to stationarity for reversible discrete time Markov chains on general state spaces. The method of proof is the well-established drift and minorization approach, which imposes a regenerative structure on the Markov chain according to a particular recipe. The resulting bounds are computable in terms of the ingredients of the recipe. The convergence theorems in this thesis are developed using a new perspective on the interplay between regeneration and reversibility. They are more widely applicable than previous results and provide better numerical bounds on the time to stationarity in specific examples. Two Gibbs samplers from Bayesian statistics are treated in detail. When applied to these chains, the new bounds improve on earlier work but are still quite conservative compared with the true convergence rates. For certain classes of finite chains, the drift and minorization method can give precise bounds on the mixing time. A striking result of this type is a sharp upper bound on the cutoff window for birth and death chains. In addition, an inductive argument shows that the spectral gap of the random walk on the hypercube can be recovered using drift and minorization up to a constant factor of 2. The thesis also contains: (1) An exposition of the drift and minorization method, explaining both the renewal theory approach of Meyn and Tweedie and the coupling approach of Rosenthal, and showing how the bounds improve when the chain is reversible or stochastically monotone. (2) A development of the properties of different types of regeneration times for general state space Markov chains. Defining a randomized stopping time usually requires enlarging the sample space to incorporate independent randomness. In full generality, this operation raises subtle questions of measurability, which are resolved using a new "compatibility condition." (3) A brief consideration of quantile estimation in Markov chain Monte Carlo, focusing on concentration inequalities that provide finite-sample guarantees at specified confidence levels. The goal is to prove inequalities that rely as little as possible on theoretical convergence bounds (of the sort proved elsewhere in this thesis) and as much as possible on the empirical sample.
Dynamic strategy for personalized medicine [electronic resource] : an application to metastatic breast cancer
Keywords: Management Science and Engineering.

Planning for treatment of cancer is challenging due to the complexity of the disease. Oncologists have to select and switch therapies considering the trade-off between treatment efficacy and therapy sides effects for an increasing number of therapies and combinations. Moreover, cancer varies with different patient characteristics and past treatment history. We develop a framework for computing a dynamic strategy for therapy choice in a large class of breast cancer patients, as an example of approaches to personalize therapies for individual characteristics and each patient's response to therapy. Our model maintains a Markov belief about the effectiveness of the different therapies and updates it as therapies are administered and tumor images are observed. We compare three different approximate methods to solve our analytical model against standard medical practice and show significant potential benefit of the computed dynamic strategies to limit tumor growth and to reduce the number of time periods patients are given chemotherapy, with its attendant side effects. We test robustness of our model with sensitivity analysis on key model parameters, seeing how the optimal dynamic strategy changes when patient characteristics differ. We also demonstrate the scalability of our model and recommended algorithm, showing that it has potential of providing real time advice to patients and oncologists.
Dynamics of photosynthetic pigment-protein complexes in Chlamydomonas reinhardtii [electronic resource]
Keywords: Biology.

Photosynthesis, the conversion of solar energy into fixed chemical energy, is a critical biological process that supports nearly all life on earth. This process involves the absorption of light by pigment-protein complexes that make up thylakoid or photosynthetic membranes, and electron transfer reactions that ultimately generate NADPH and establish a proton gradient used to synthesize ATP. These cellular reducing equivalents and high energy compounds are then utilized in carbon fixation reactions that occur in the Calvin Benson Bassham Cycle (reductive pentose phosphate pathway). However, photosynthesis is also an inherently dangerous process as excess absorbed light that cannot be used for photochemistry (electron transport and CO2 fixation) can elicit the formation of reactive oxygen species that can severely damage the cell. Therefore, photosynthesis must be a highly regulated and extremely flexible process. We are just beginning to understand all of the components of the photosynthetic apparatus and how they function in the face of an ever-changing environment. This thesis explores novel components and functions associated with photosynthesis, with an emphasis on pigment-protein complex dynamics. All of the work was performed using the single-celled green alga Chlamydomonas reinhardtii, an excellent model for the study of photosynthesis. The first introductory chapter highlights unifying themes related to the control and plasticity of photosynthesis. The second chapter focuses on two novel thylakoid membrane proteins, CPLD38 and CPLD49, both of which are critical for photoautotrophic growth and impact the accumulation of the cytochrome b6f complex. The third chapter highlights a critical, yet previously undiscovered role for linear tetrapyrroles (bilins) in the maintenance of photosystem I. Central to this study is the control of photosynthetic processes as cells transition from darkness to light. The fourth chapter focuses on a critical redox carrier protein, FDX5, which is absolutely required for growth in the dark where it may be involved in maintaining proper membrane structure and composition, and other processes that are potentially redox-associated. The fifth chapter addresses how photosynthesis is adjusted during nutrient deprivation and specifically elucidates unique aspects of photoautotrophic nitrogen deprivation (an often encountered condition in the environment) that allow the photosynthetic apparatus to be preserved even though the cells are unable to fix much inorganic carbon. The sixth chapter presents preliminary evidence that identifies specific steps in the assembly of the photosynthetic apparatus that appear to be protected from atmospheric O2. Overall, this work unmasks novel components associated with the function and biogenesis of thylakoid membranes, revealing mechanisms critical for maintaining photosynthetic function in a dynamic environment.
Dynamics of plasma discharges used for space propulsion [electronic resource]
Keywords: Mechanical Engineering.

Hall thrusters are a mature form of electric propulsion for spacecraft well suited for north-south station keeping, orbit transfer maneuvers, and eventually deep space travel. Despite decades of development, producing propulsion systems with high operating efficiency and specific impulse, key aspects of the physics governing these complex devices remain poorly understood and fundamental experimental and computational studies persist. This work concerns the development and implementation of laser-induced fluorescence (LIF) diagnostics for probing time-resolved dynamics in systems with a quasi-periodic forced or naturally occurring oscillation. Relaxing the requirement of a fixed frequency spectrum over time distinguishes the sample-hold and fast switching LIF methods studied here from others currently in use. The methods are validated against a collisional-radiative model of a 60 Hz xenon test discharge, successfully predicting the time evolution of excited xenon state populations. The sample-hold method is then applied to studying xenon neutral and ion dynamics and transport in two Hall thruster discharges: a laboratory model in the Stanford Plasma Physics Laboratory similar to the SPT-100 class of devices, and a commercial Busek Co. BHT-600 Hall thruster at the Air Force Research Laboratory at Edwards Air Force Base, California. Time-resolved ion velocity measurements in the channels and near-field plumes of these thrusters reveal propagating propellant ionization and acceleration fronts undergoing periodic motion that are fundamentally linked to the breathing mode ionization instability common to such devices. The presence of low ion velocity populations exhibiting different dynamic behavior than the main accelerated population is likely due to residual ionization of neutral propellant in the near-field plume of the thrusters. A study of the poorly understood central jet in the BHT-600 also reveals new details about the asymmetric nature of this plasma feature in both space and time. Finally, the measured ion dynamics in the Stanford Z-70 thruster are compared with those predicted by a two-dimensional hybrid particle-in-cell simulation of the device with a dynamically updating electron mobility modeled after the turbulent dissipation of energy in the electron fluid. Somewhat similar modulations in ion velocity are observed in the simulation results, but the limits of these types of simulations in tracking accurate time-resolved behavior are revealed.
Economic recovery and the determinants of productivity and innovation [electronic resource] : evidence from post-WWII Italy
Keywords: Economics.

This dissertation explores the process of economic development of Italy which between the late 1940s and the early 1970s moved from being a war-ravaged agricultural country to the seventh most industrialized power of the world. Chapter 1 investigates the extent to which the Marshall Plan affected the Italian economic recovery from WWII and its subsequent industrial production expansion. Chapter 2 assesses the long-run effects of management and technology transfer on firm performance. Chapter 3 studies the series of Italian reforms that promoted university STEM education among a group of high-school students, who were trained in STEM, but historically denied access to scientific university studies.
The effect of context on children's understanding of negation [electronic resource]
Keywords: Psychology.

Words like "and", "or", "not", and "if" are powerful tools of human cognition, allowing us to form connections between expressions and reason about the world around us. Past work on children's acquisition of these words suggests a puzzle: Children begin producing these words at a very young age, but struggle on comprehension tasks for several years. In this dissertation, I focus on negation to explore two possible pieces to this puzzle: context and processing demands. I present several experiments demonstrating that context influences our understanding and use of negation. My data indicate that both adults and children expect negative sentences to be produced in relevant and informative contexts, and comprehension is reduced when negative sentences are presented without any context. I also present work suggesting that children have difficulty processing negative sentences, even when the sentences are presented in an informative context. This work collectively suggests that both context and processing demands are important factors to consider in order to understand children's acquisition of complex words.
An effective field theory approach to cosmological structure formation [electronic resource]
Keywords: Physics.

One of the main frontiers of observational cosmology is to map out how matter is distributed throughout the universe. The clustering patterns of galaxies and other astrophysical objects contain imprints of the universe's expansion history, the properties of the quantum fluctuations that are believed to have seeded the late-time structures we observe, and possibly other new and exotic physical processes. To extract this information from observations, we require a robust theoretical framework for how gravitational clustering works at large distances. This dissertation presents such a framework, which adapts the ideas of "effective field theory" (originally developed in the context of particle physics and quantum fields) to describe how small perturbations in an initially homogeneous distribution of matter evolve through cosmic time. In this framework, the perturbations are described as an effective fluid at long distances, with a stress tensor that parametrizes the effects of short-wavelength processes on the long-distance dynamics of the fluid. This stress tensor can be written as an expansion in long-wavelength fields (such as the matter overdensity) and spatial derivatives, and the coefficients of this expansion can be matched either to observations or to numerical simulations of gravitational clustering. Through several explicit calculations of correlation functions (particularly the power spectrum) of the cosmic density field, I demonstrate how the presence of this stress tensor renders the theory free of many of the issues that have plagued other perturbative approaches to gravitational clustering. I also perform several comparisons of the theory's predictions to measurements from dark matter-only N-body simulations, demonstrating the theory's ability to reproduce these measurements at over a wider range of scales and at higher precision than previously possible. The results in this dissertation represent significant advances in our understanding of cosmological perturbation theory, and their eventual application to observations of large-scale structure will likely be a great help in furthering our knowledge about the universe we inhabit.
The effective field theory of large-scale structure in cosmology [electronic resource]
Keywords: Physics.

So far, the cosmic microwave background has provided most of the significant constraints on cosmological parameters, but because of Silk damping and foreground contamination, the Planck Satellite has essentially reached the limit in constraining non-Gaussianity in scalar modes with the cosmic microwave background. Fortunately, the distribution of galaxies today is correlated with the conditions present in the early universe, so large-scale structure surveys can help us understand the early universe by observing the current-day galaxy distribution. In this way, it is likely that the next leading source of cosmological information will come from large-scale structure surveys like LSST and Euclid. In order for large-scale structure to significantly improve our knowledge of the early universe, for example by constraining f_NL < 1 through bispectrum measurements, the large-scale structure observables must be understood to percent level, even in the quasi-linear regime of structure formation. Recently, a research program called the Effective Field Theory of Large-Scale Structure was launched with this purpose. In this thesis, I will develop two pieces of that program: the effective field theory in redshift space, and the description of baryonic effects in the effective field theory. Finally, I will present work which computes the first slow-roll corrections to the volume of the universe and the universal entropy bound for slow-roll eternal inflation.
Effects of Public Sector Corruption on the Private Sector: Investigating the Market Value of Political Connections
Keywords:  Department of Economics
Stanford Department of Economics
political connections
corruption
firm value
Nigeria
Thesis

This paper exploits public announcements of corruption allegations amongst Nigerian political figures to estimate the impact of political connections on firm value. Specifically, I draw results from market reactions to 27 events to determine whether politically connected firms suffer more from financial malpractice amongst government officials. This paper finds heterogeneous impacts of corruption announcements for firms’ returns. For some events involving larger sums of misallocated funds, politically connected firms suffer greater losses in their returns than unconnected firms. For other events involving smaller amounts of missing funds, I find that unconnected firms are actually punished more than connected firms. Still for other events, there appears to be no significantly differential impact of a government corruption scandal on connected and unconnected firms. Furthermore, surprisingly, some events actually show a positive return for all firms, and when this is the case, politically connected firms experience a larger increase in returns than their unconnected counterparts. To identify an overall impact, I run a pooled regression aggregating over all the events studied. I find that on average, there is a negative albeit insignificant impact on the returns of politically connected firms relative to unconnected firms in the aftermath of a corruption scandal.
Efficient permutation P-value estimation for gene set tests [electronic resource]
Keywords: Statistics.

In a genome-wide expression study, gene set testing is often used to find potential gene sets that correlate with a treatment(disease, drug, phenotype etc.). A gene set may contain tens to thousands genes, and genes within a gene set are generally correlated. Permutation tests are standard approaches of getting p-values for these gene set tests. Plain Monte Carlo methods that generate random permutations can be computationally infeasible for small p-values. Ackermann and Strimmer (2009) finds two families of test statistics that achieve overall best performances - a linear family and a quadratic family. This dissertation first reviews the relative background of gene set testing and permutation tests, and then provides three alternative approaches to estimate small permutation p-values efficiently. The first approach focuses on the linear statistic. Observing the p-value can be written as the proportion of points lying in a spherical cap, the p-value is approximated by the volume of a spherical cap. Error estimates can be derived from generalized Stolarsky's invariance principal, and alternative probabilistic proofs are provided. The second approach focuses on the quadratic statistic. Importance sampling is used to estimate the area of the (continuous) significant region on the sphere, and the volume of the region is used as an approximation for the (discrete proportion) p-value. Different proposal distributions are studied and compared. The third approach estimates the p-value with nested sampling. It may work for both the linear and the quadratic statistic. Similar ideas can be found in literature spanning from combinatorics, sequential Monte Carlo, Bayesian computation, rare event estimation, network reliability etc., and bears different names, e.g. approximate counting, nested sampling, subset simulation, multilevel splitting etc. We give a thorough review of literature in these different areas, and apply the technique to the gene set testing with the quadratic test statistic. Finally, we compare the proposed methods with plain Monte Carlo and saddle- point approximation on three expression studies in Parkinson's Disease patients. This work was supported by the US National Science Foundation under grant DMS-1521145.