VictorJuiz/thesis huggingface dataset:
Dynamics of DNA gyrase : species differences and antibiotic inhibition mechanisms

Single-molecule techniques have been used to uncover the biophysical mechanisms of antimicrobial targets and their mechanisms of inhibition, and could make important contributions to future drug development pipelines. DNA gyrase is an essential nucleoprotein motor in all bacteria and a major target for the treatment of Mycobacterium tuberculosis (TB) and many other pathogens. Gyrase hydrolyzes ATP to add negative supercoils to DNA, employing a strand passage mechanism that has been previously investigated using biophysical and biochemical approaches, including single-molecule rotor bead tracking (RBT). We have now used RBT to measure rates, processivities, and conformational distributions and dynamics of gyrase from three evolutionarily distant, pathogenically relevant bacterial species: Escherichia coli (EC), TB, and Clostridium difficile (CD). Supercoiling is seen to be processive in all cases, with TB gyrase displaying velocities ~5X slower than EC. Compared with EC, TB gyrase more strongly populates a critical intermediate in which DNA is wrapped around the enzyme and poised for directional strand passage. Our substep measurements reveal some universal states, along with differences in populations and transition rates that may reflect distinct cellular requirements for biophysical properties across species. In preliminary work, we also demonstrate the use of RBT to observe inhibited states of gyrase with example drugs from major classes of antibiotic inhibitors, including widely prescribed fluoroquinolones and recently developed novel bacterial topoisomerase inhibitors (NBTIs). This work shows that RBT can be used to study the dynamics of drug inhibition of DNA gyrase. Further experiments complemented by high-resolution structural characterization of conformational states may help develop improved and novel inhibitors. This dissertation also describes an effort to develop curiosity-driven interdisciplinary science capabilities outside the university setting to promote access and inclusion to science, technology, engineering, and mathematics professions (STEM). We present an outreach program called Future Advancers of Science and Technology (FAST), which has partnered over 200 high school students with over 100 Stanford graduate students to work on year-long science and engineering projects that investigate unknown questions or invent new devices. Previous programs have studied the positive effects of project-based learning and long-term mentorship separately. In FAST, we combined these two approaches to STEM education. Case studies of students who chose to complete biophysics-related projects illustrate anecdotally how student-driven projects can be developed in a relatively resource-limited setting, with positive impacts on students' career growth. We have developed a plan for more rigorously assessing the impact of the program on mentees and mentors in the next cycle.

Advisor: Bryant Zev David 
Huang Kerwyn Casey
Kim Peter
Dynamics of hydrogen bonds and proton defects in the condensed phase

Molecular simulation is a useful tool for investigating the structure and dynamics of wide-ranging chemical systems and can provide information that complements experiments. The objective of this thesis is to relate experimental spectroscopic observables to the chemical structures and dynamics that give rise to them using molecular simulations that include quantum fluctuations of both the electrons and nuclei. Chapter 1 first introduces the approach employed in this thesis to relate chemical structure to vibrational spectra as well as contextualizes some of the limitations and trade-offs associated with molecular simulations. Chapter 2 applies this approach to simulations of concentrated acid solutions with the aim of elucidating recent 2D-IR experiments. Chapter 3 presents work from an experimental collaboration investigating using a vibrational probe to observe proton transfer in solution. Lastly, Chapter 4 treats the inclusion of nuclear quantum effects in the computation of optical absorption spectra of aqueous chromophores.

Keywords: Chemistry.
Advisor: Markland Thomas E.
Fayer Michael D. 
Martinez Todd J. (Todd Joseph)
Dynamics of microbial communities. Cological, game theoretic and evolutionary perspectives

This thesis explores the dynamics of microbial communities from ecological, game theoretic and an evolutionary perspective. Chapter 1 discusses the stability of host-associated microbial ecosystems and related mathematical models and the inference of these models. Chapter 2 addresses the question of microbial interactions. Using a game-theoretic model, I explore ways in which agents (such as cross-feeding bacteria) in a multiagent system can coordinate without explicit communication channels. Chapter 3 explores the evolution of hierarchical structures of bacterial metabolic networks.

Keywords: Biology.
Advisor: Feldman Marcus W. 
Borenstein Elhanan
Leskovec Jurij
Early Childhood Education: An Analysis of Its Effects on Student Achievement in Central America

This research aimed to explore the potential effects of early childhood education in Honduras, Guatemala, Costa Rica, Nicaragua and Panama with a special emphasis on Honduras. My main research question was how effective is early childhood education for elementary school success in reading and math in five target countries in Central America? To answer it, I analyzed a dataset from UNESCO which applied standardized assessment exams to elementary school students in different subjects including math and reading. In addition, this dataset identified the associated factors that influence its results. I then used ordinary least squares regression analysis to understand what the impact of early childhood education was on students’ achievement, if any. Although there is a great amount of literature that vouches for the positive effects of early childhood education, the major findings of my study showed that for all the countries, when dividing the population by socioeconomic status, early childhood education had no effect on the poorer two thirds of the student population. In terms of policy, this implies that while the current efforts to make early childhood education universal may or may not be having positive effects in other areas, in terms of student achievement the effects are insignificant. This may be due to the fact that early childhood education programs are of such poor quality for lower social class students that they have no impact in terms of student achievement. Alternatively, it could also mean that early childhood education is of decent quality; however, primary education is so poor that the effects of preschool are wiped out in the first three years of elementary school. Regardless of the cause, if no efforts are directed towards improving the quality of early childhood educational centers, we will continue to see similar results.

Keywords: Early Childhood Education
Student Achievement
Math
Reading
Central America
Honduras
Regression Analysis
Thesis
Advisor: Carnoy Martin
Early-Stage Gentrification in America’s Heartland: Analyzing College-Age Experiences of Rapid Transformation inside Fayetteville, Arkansas

Fayetteville, Arkansas is the largest city in one of the fastest-growing metropolitan areas in the United States – Northwest Arkansas. Projected to grow from its current population of 86,000 to 143,000 people in 2040, Fayetteville is adding 48 new residents every week. Using Fayetteville as a case study, this qualitative study explores individual and community perceptions in smaller American cities experiencing high growth and subsequent gentrification. Twenty-six one-hour-long interviews with 13 Fayetteville residents (two meetings each) aged 18 to 25 conducted between July and October 2018 reveal the student population’s pressured and competitive interactions when searching and securing rental housing along with their perceptions of the area’s socioeconomic changes before, during, and after college. This research uses qualitative data analysis on frequencies and themes to conclude that the University of Arkansas and the area’s Fortune 500 companies have reinforced Fayetteville’s state of early gentrification as indicated by a constrained housing market, a shift in demographics, and the transformation of the social and political landscape of the city. This study addresses the assertion by scholars Japonica Brown-Saracino, Lyn Macgregor, and Michael Barton that recent gentrification scholarship is limited by focusing on larger, post-gentrified, and geographically-biased cities such as San Francisco, California, and Boston, Massachusetts. This study, intended for academic scholars and policy advocates alike, urges further research on early gentrification trends and reactions inside smaller, rapidly growing cities such as Bend, Oregon, and St. George, Utah along with those with a significant university presence such as Fort Collins, Colorado, and Boise, Idaho.

Keywords:  Program on Urban Studies
Stanford University
Urban Studies
Program on Urban Studies
Fayetteville
Arkansas
University of Arkansas
Northwest Arkansas
Gentrification
Qualitative
Thesis
Advisor: McAdam Douglas
Chan Deland
Hurd Clayton
Ecotourism Visitation Correlates with Bird Biodiversity in Costa Rica

Biodiversity loss is an ongoing worldwide crisis: over 100 vertebrate species have gone extinct in the last 100 years alone, far higher than pre-human rates of loss (Johnson et al., 2017). Arguments to conserve biodiversity based on its concrete benefits to humans are often most compelling to decision-makers (Braat & de Groot, 2012). One remarkable example of a such a benefit is the economic revenue generated by ecotourism to observe biodiverse ecosystems. Costa Rica contains high levels of biodiversity (Myers et al., 2000) with a well-developed ecotourism industry (Instituto Costariccense de Turismo, 2017a). We aimed to deepen understanding of the connection between bird biodiversity and ecotourism visitation in Costa Rica by answering the following questions: 1) What is the spatial distribution of bird biodiversity across Costa Rica?; and 2) Is bird biodiversity a good predictor of ecotourism visitation rates in Costa Rica? We used MaxEnt (a range map modelling software) to model the distribution of over 650 Costa Rican bird species. We aggregated individual range maps into 6 different metrics of bird biodiversity based on total species richness, threatened species richness, and endemic species richness. We used protected area visitation as an on-the-ground metric of tourist visitation, and used photo uploads on the social media site Flickr and bird checklist uploads on the birding app eBird to assess tourism value spatially. We found that park visitation was significantly positively correlated with both total species richness and regional endemic species richness. Our analysis using MaxEnt revealed that total bird species diversity as a strong predictive factor for both Flickr photo upload locations and eBird bird checklist upload locations. Our results strongly support the hypothesis that bird biodiversity promotes tourism in Costa Rica.

Keywords:  Department of Biology
Stanford University Department of Biology
Biology
Ecology
Biodiversity
Birdwatching
Costa Rica
Ecotourism
Ecosystem Services
Tourism
Species Distribution Modeling
Thesis
Advisor: Daily Gretchen
Fukami Tadashi
Ecotype partitioning and metabolic diversity within Thaumarchaeota populations in the coastal ocean

The discovery of ammonia oxidation within the domain Archaea caused a paradigm shift in our understanding of the global nitrogen cycle. Ammonia-oxidizing archaea (AOA) of the phylum Thaumarchaeota are now recognized as an abundant and ubiquitous archaeal group that plays a critical role in the global nitrogen and carbon cycles. As chemolithoautotrophs, AOA fix CO2 using the energy derived from oxidizing ammonia to nitrite, and have been shown to carry out the majority of ammonia oxidation in the marine environment. Despite the important biogeochemical consequences of their metabolism, large gaps remain in our understanding of the ecology of this abundant archaeal group. Functional gene-based marine water column surveys have suggested the diversification of AOA into ecologically distinct phylotypes (or ecotypes). These ecotypes are thought to represent subpopulations occupying differential niche spaces in the pelagic realm. In this dissertation, I examine the ecology of marine Thaumarchaeota, particularly in relation to the depth-related diversification patterns. I use a time-series microbial community dataset generated from the Monterey Bay upwelling system to investigate phylogenetic and metabolic diversity within pelagic thaumarchaeal populations. I discuss the relative utility of different molecular markers for characterizing intra-clade diversity within pelagic AOA. Association patterns of subpopulations are examined using modeling approaches, which reveal biogeochemically-relevant differences in the co-occurrence relationships of ecotype groups. Phylogenetic and metabolic diversity within thaumarchaeal sub-lineages are discussed based on population genomes reconstructed from metagenomes. Overall, this dissertation highlights previously unrecognized microscale diversity and metabolic adaptations within marine Thaumarchaeota.

Keywords: Environmental Earth System Science.
Advisor: Francis Christopher 
Casciotti Karen Lynn
Dekas Anne
Edgeworth approximations for spiked PCA models and applications

We study improved approximations to the distributions of the largest eigenvalues of the sample covariance matrix of i.i.d. zero-mean Gaussian random vectors, in the high-dimensional regime where the ratio of the dimension of each observation to the number of observations converges to a positive constant. Assuming that a fixed number of population principal components have "supercritical" variances and that the remaining noise components have common variance 1, we derive Edgeworth corrections to the limiting Gaussian distributions of the supercritical sample eigenvalues. The Edgeworth correction involves a quadratic polynomial, as in classical settings, but the coefficients reflect the high-dimensional structure and exhibit the repulsion between supercritical eigenvalues. The methods involve Edgeworth expansions for sums of independent non-identically distributed variates obtained by conditioning on the other sample eigenvalues, and the limiting bulk properties and fluctuations of these eigenvalues. As an application, we consider post-selective inference for supercritical eigenvalues. Empirical study shows that Edgeworth approximations can improve the inference, along with a better asymptotic accuracy guarantee than the normal approximation.

Keywords: Statistics.
Advisor: Johnstone Iain 
Donoho David Leigh 
Owen Art B.
The effect of interfaces on phase change memory switching

With faster read and write speeds than NAND Flash and higher densities than DRAM, emerging storage class memories (SCMs) are an exciting new addition to the modern storage/memory hierarchy. Additionally, SCMs show significant promise in helping solve the computing bottleneck, commonly known as the "memory wall, " where computation speed is limited by memory rather than logic. Among the emerging SCMs, phase change memory has been the first to "emerge" with commercial products, such as Intel and Micron's 3D XPoint, now being available to consumers. PCM relies on a resistive storage material that can be reversibly switched through Joule heating in crystallization and melt-quench processes. However, due to the thermal nature of PCM's switching, achieving energy efficient writing is challenging. In an effort to alleviate this problem, we take an interface focused approach starting with finite element modeling. From modeling, we determine that significant current and energy benefits can be achieved by increasing both the thermal and electrical resistivity of the interface between the confined electrode and the phase change material. To realize these benefits, we fabricate devices with thin TiN interfacial layers in order to increase the electrical contact resistance. Unfortunately, this approach is met with limited success so we next move on to using two-dimensional (2D) materials, a class of atomically thin materials that allows us to reach the limits of interface engineering. After fabricating devices with two of these materials, graphene and molybdenum disulfide, we find that the latter shows a 40% reduction in the current required to reset.

Keywords: Electrical Engineering.
Advisor: Wong Hon-Sum Philip
Pop Eric 
Saraswat Krishna
Effective usage of muscle simulation and deep learning for high-quality facial performance capture

This dissertation explores the problem of the uncanny valley in digital facial performances; however, it is unclear what exactly causes the psychological rejection of near-realistic digital human faces. While the uncanny valley may be, in part, caused by an imperfect digital rendering of the face, this dissertation hypothesizes that the largest hurdle to solving the uncanny valley problem are unrealistic facial shapes and motions. Such imperfections are due to sources of error in the facial deformation model, the minimized objective function(s), as well as the regularization and optimization method of choice. Linear blendshape-based deformation models have parameter spaces which permit a wide range of subtly to implausible facial shapes. Commonly used objective functions assume that one has perfect correspondences between the captured data and the synthetic model; this is an assumption that is rarely correct. Lastly, in an attempt to prevent the model from wandering into uncanny territory, simple regularization terms are used to restrain the parameter values to tend towards zero. This dissertation addresses these problems by introducing and exploring the usage of a fully differentiable muscle simulation model, deep learning in objective functions, and an alternative minimization method that avoids ad hoc regularization. Firstly, we build upon the previously introduced facial muscle track simulation model and make it fully differentiable from end-to-end. This is accomplished by driving the muscle tracks using a parallel set of blendshape parameter values. We prove that this model is not only fully differentiable but also as expressive as the muscle track simulation model and, in certain cases, mathematically equivalent. We also demonstrate that this model can be used and is effective as the deformation model in an optimization problem for targeting 3D geometry and 2D monocular RGB images. Furthermore, we show that the resulting activation values are a promising basis for future work on semantic interpretability. Secondly, we address the manual correspondence problem when capturing 2D RGB images by applying the same pretrained deep neural networks to both the captured image and a synthetic differentiable render of the face model. Such an approach can seamlessly be used in an optimization problem due to the fully differentiable nature of both the neural network and differentiable renderer. We demonstrate the efficacy of this approach for estimating facial pose and expression using facial alignment and optical flow networks. By relying on a trained network, we can remove human judgement from the facial performance capture process which presents a clear path towards improvement in future work. Lastly, we briefly explore the usage of regularization for facial performance capture and demonstrate how an alternative nonlinear least squares optimization method can produce comparable results without modifying the energy landscape.

Advisor: Fedkiw Ronald P.
Grabli Stéphane
Liu Cheng-Yun Karen
The effects of college and career readiness policies on student outcomes

The recent widespread adoption of College and Career Readiness (CCR) standards by states hinges on a growing understanding that the preparation needed to succeed in college overlaps significantly with the skills and knowledge required to thrive in careers. However, the coupling of college and career standards have resulted in higher standards for all students. These higher standards, paired with accountability measures may encourage schools to focus resources towards helping students meet a higher bar. If schools are unable to overcome collective-action challenges the lowest performing students are at-risk of low-achievement and worse outcomes. This dissertation explores how the recent policy shift towards CCR standards impacts students' academic trajectories in three different contexts. In particular, I focus on the heterogeneous impacts of these policies by examining impacts on different student groups (i.e., students of color, language proficiency, prior achievement etc.). Thus, my dissertation is comprised of three standalone but interrelated studies on the widespread enactment of CCR.

Keywords: Education.
Advisor: Dee Thomas S. (Thomas Sean) 
Bettinger Eric 
Loeb Susanna
The effects of genetic and environmental perturbations on craniofacial development

Formation of craniofacial structures is a delicate developmental process that is disrupted in many disease states. These disease states can occur due to genetic anomalies within a developing embryo or environmental irregularities in utero during gestation. Frequently, craniofacial developmental disorders are caused by defects in a particular population of transient, migratory stem cells called neural crest cells. In my Dissertation research, I have endeavored to elucidate the molecular and cellular mechanisms underlying specific genetic disorders and exposure to specific teratogens, with a focus on the fascinating cell type that is the neural crest cell (NCC). To this end, I have studied craniofacial disorder Floating-Harbor Syndrome (FHS), which is caused by heterozygous truncating mutations in SRCAP, a gene encoding a chromatin remodeler that mediates incorporation of histone variant H2A.Z. I demonstrated that FHS-associated mutations result in loss of SRCAP nuclear localization, alter neural crest gene programs in human in vitro models and Xenopus laevis embryos, and cause craniofacial defects. These defects are mediated by one of two H2A.Z subtypes, H2A.Z.2, whose knockdown mimics and whose overexpression rescues the FHS phenotype. Selective rescue by H2A.Z.2 is conferred by one of the three amino acid differences that evolved between the H2A.Z subtypes, S38/T38. I further showed that H2A.Z.2 preferentially occupies AT-rich enhancers, while H2A.Z.1 broadly binds regulatory regions, with the highest enrichment at promoters. Genes associated with H2A.Z.2-enriched enhancers are sensitized to heterozygous SRCAP truncations. Altogether, these results illuminate the mechanism underlying a human syndrome and uncover selective functions of H2A.Z subtypes during development. In addition, I have studied how Zika virus (ZIKV) infection during pregnancy, which is linked to microcephaly, can affect neural crest cell in vitro. In addition to giving rise to most cranial bones, NCCs exert paracrine effects on the developing brain. I reported that NCCs are productively infected by ZIKV, but not by the related dengue virus. These ZIKV-infected NCCs undergo limited apoptosis but secrete cytokines that promote death and drive aberrant differentiation of neural progenitor cultures. Addition of two such cytokines, LIF or VEGF, at levels comparable to those secreted by ZIKV-infected NCCs is sufficient to recapitulate premature neuronal differentiation and apoptotic death of neural progenitors. My results suggest that NCC infection by ZIKV may contribute to associated embryopathies through signaling crosstalk between developing face and brain structures.

Keywords: Developmental Biology.
Advisor: Wysocka Joanna
Beachy Philip Arden 
Cimprich Karlene 
Kingsley David M. (David Mark) 
Sherlock Gavin