VictorJuiz/thesis huggingface dataset:
Control of salmonella transmission by the intestinal microbial community [electronic resource]

Disease transmission is a multifaceted process mediated by the interactions between the pathogen and host. Salmonella enterica serovars are important human pathogens that cause disease ranging from food poisoning to persistent systemic infections, such as typhoid fever. Transmission occurs via the fecal-oral route, and epidemiological analyses have revealed heterogeneity in host transmission capabilities. A minority of hosts are persistent carriers of disease that are responsible for a large majority of new infections. These carriers are thus termed supershedders, but relatively little is known about the factors that dictate pathogen transmission. The focus of this dissertation work is to identify critical principles and determinants that govern Salmonella transmission. Chapter 1 introduces what is known about S. Typhimurium colonization and supershedding in a mouse model of typhoid fever. The role of the host immune response and intestinal microbiota in modulating infection are highlighted. In Chapter 2, ecological theories are applied to predict S. Typhimurium transmission dynamics. There is intense Salmonella intraspecies competition to colonize transmission niches in the cecum and colon. Salmonella interacts with trillions of commensal microbes within these distal gut sites, and another goal of this study is to investigate how the intestinal microbiota influences supershedding. Host diet can drastically alter the microbiota, and Chapter 3 details the development of a supershedder microbiota induced by a high cholesterol diet. Differences in host genetic backgrounds also influence microbiota composition, and in Chapter 4, we demonstrate that supershedding can be conferred by fecal microbiota transplantation. This body of work reveals that the host microbiota controls levels of Salmonella excreted in feces, as well as host tolerance to infection. Chapter 5 reflects on the importance of the microbiota in influencing Salmonella transmission, and considers the implications on best treatment practices and disease control.

Keywords: Microbiology and Immunology.
Advisor: Monack Denise M. primary advisor. Thesis advisor
Amieva Manuel advisor. Thesis advisor
Fukami Tadashi
Schneider David (David Samuel)
Sonnenburg Justin
Controlling light at the nanoscale for broadband metamaterials, efficient solar cells, and subwavelength 3D imaging [electronic resource]

The iridescent wings of a butterfly, the vivid colors of a stained glass window, the mesmerizing rainbow in a soap bubble - all of these beautiful optical phenomena are made possible by the interaction of light with nanoscale materials. Beyond brilliant colors, rational control of the unique and often surprising ways in which light interacts with materials at extremely small length scales has enabled novel optical phenomena, devices, and characterization techniques. In this thesis, we discuss three such applications of nanophotonic engineering: metamaterials, solar cells, and nanoscale optical tomography. First, we describe the design of a metamaterial - a composite material with a tunable refractive index spanning positive, zero, and negative values - that operates over a broad spectral range. While metamaterials have made possible previously unthinkable phenomena including invisibility cloaking and sub-diffraction-limited imaging, designing a metamaterial with a broad operational bandwidth at visible frequencies is an outstanding challenge. Here we demonstrate theoretically a broadband metamaterial presenting negative indices across hundreds of nanometers in the visible and near-infrared, more than doubling previous record bandwidths. Second, we discuss optical methods for increasing photocurrent from solar cells by making use of low energy subbandgap photons. Upconversion - the process of converting low energy light to high energy light - promises to be an economical solution to this problem, but existing upconverting materials require substantial improvements to become viable. Here we describe the realistic improvements achievable with an upconverter enhanced solar cell and propose a nanophotonic system to improve the efficiency of the upconversion process itself. Last, we introduce a new method for probing light-matter interactions with nano\-meter scale resolution in three dimensions. Our technique, called cathodoluminescence tomography, extends sub-diffraction limited imaging from two to three spatial dimensions, while also revealing spectral information across visible and near infrared frequencies. This new imaging capability could be used, for example, to probe the distribution of defect states in photovoltaics, or locate recombination centers in light emitting diodes.

Keywords: Materials Science and Engineering.
Advisor: Dionne Jennifer Anne primary advisor. Thesis advisor
Brongersma Mark L. advisor. Thesis advisor
McGehee Michael
Controlling light transmission with nanostructured metallic surfaces [electronic resource] : applications in polarimetry, transparent electrodes, and anti-reflective coatings

Metallic structures such as antennas and waveguides are widely used to concentrate and guide electromagnetic radiation into electronic circuits at radio and microwave frequencies. Because of their high conductivity, metals are also used for the wiring in electronic circuitry. At near infrared and visible frequencies, however, metals have been underutilized. In this spectral range, dielectric elements such as lenses and waveguides are used to manipulate electromagnetic radiation. Recent progress in nanotechnology has opened up opportunities to make and characterize metallic structures at the nano scale, which are requirements for use of metals in this spectral range. Miniaturized metallic devices could potentially replace some of their bulky dielectric counterparts at near IR and visible frequencies, while simultaneously performing an additional electronic function. This would enable new optical applications that are not possible with dielectrics alone. This dissertation presents our work on controlling light transmission with nanostructured metallic films for three applications, all of which are typically the domain of dielectrics: polarimeters, anti-reflective coatings, and transparent electrodes. In all three applications, the nanostructured metallic film simultaneously performs optical (light transmission) and electronic (charge extraction) functions. We perform full-field electromagnetic simulations to characterize and optimize these metallic nanostructures. We also experimentally show the applicability of these designs for real devices through integration with semiconductor photodetectors and performing photocurrent and reflection measurements. The demonstrated devices extend the reach of metal optics to a wide range of optoelectronic applications including displays, touch screens, solar cells, and polarimetric imagers and sensors.

Keywords: Electrical Engineering.
Advisor: Brongersma Mark L. primary advisor. Thesis advisor
Fan Shanhui
Miller D. A. B. advisor. Thesis advisor
Crowdsourcing ontology verification [electronic resource]

Biomedicine and healthcare rely heavily on ontologies, with ontology development and use increasing rapidly in the domain. However, as the scale and complexity of these ontologies increases, so too do errors and engineering challenges. There are both automated and manual methods that provide ontology quality assurance and identify ontology errors. However, these methods do not readily scale as ontology size increases, and they do not necessarily identify the most salient errors. Recently, crowdsourcing has enabled solutions to complex problems that computers alone cannot solve. Crowdsourcing presents an opportunity to develop methods for ontology quality assurance that overcome the current limitations of scalability and applicability. Toward that end, the work described in this dissertation has the following aims: (1) to examine the effect of ontology errors in biomedical applications, (2) to develop and tests a scalable framework for ontology verification via crowdsourcing that overcomes current ontology quality assurance method limitations, (3) to apply this framework to ontologies in-use, and (4) to evaluate the methodology and its effect in the context of a the biomedical domain. In the preliminary studies, I found that crowd workers perform best when answering questions about concrete (not abstract) ontology concepts, when presented with a simply stated natural language representation of an ontology axiom, and when provided textual definitions of ontology concepts. After completing these early studies, I refined and applied the crowd-based methodology to biomedical ontologies in-use. On SNOMED CT, the crowd identified 39 errors in a set of 200 expert-verified relationships, it was indistinguishable from any single expert by inter-rater agreement, and it performed on par with any single expert compared against the consensus standard that five subject-matter experts developed, with a mean AUC of 0.83. On the Gene Ontology, a different set of subject-matter experts identified 16 errors, generally in relationships referencing acids and metals. The crowd performed poorly in identifying those errors, with an AUC ranging from 0.44 to 0.73, depending on the methods configuration. However, when the crowd verified what experts considered to be easy relationships with useful definitions, they performed reasonably well. The results of the crowd's performance in verifying SNOMED CT and GO suggest that the crowd can indeed assist with ontology engineering tasks and, rather than serving as a complete replacement, the crowd can serve as an assistant, helping experts with ontology verification by completing the easy tasks and allowing experts to focus on the difficult tasks.

Advisor: Musen Mark A. primary advisor. Thesis advisor
Khatri Purvesh
Noy Natalya F.
Cryptography in the age of quantum computers [electronic resource]

It is well established that full-fledged quantum computers, when realized, will completely break many of today's cryptosystems. This looming threat has led to the proposal of so-called "post-quantum" systems, namely those that appear resistant to quantum attacks. We argue, however, that the attacks considered in prior works model only the near future, where the attacker may be equipped with a quantum computer, but the end-users implementing the protocols are still running classical devices. Eventually, quantum computers will reach maturity and everyone - even the end-users - will be running quantum computers. In this event, attackers can interact with the end-users over quantum channels, opening up a new set of attacks that have not been considered before. This thesis puts forth new security models and new security analyses showing how to ensure security against such quantum channel attacks. In particular, we re-build many core cryptographic functionalities, including pseudorandom functions, encryption, digital signatures, and more, resulting in the first protocols that are safe to use in a ubiquitous quantum computing world. Along the way, we resolve several open problems in quantum query complexity, such as the Collision Problem for random functions, the Set Equality Problem, and the Oracle Interrogation Problem.

Advisor: Boneh Dan
Valiant Gregory advisor. Thesis advisor
Williams Ryan (Richard Ryan)
Culturally Immersive Programming for Native American/Alaska Native Students: Benefits, Impacts, and Implications Based Upon a Survey of NERDS (Native Education Raising Dedicated Students)

This study seeks to understand the ways in which a culturally immersive, extracurricular program affects Native American /Alaska Native (NA/AN) youth attitudes towards education. Furthermore, this study analyzes how NA/AN youth identities are tied to issues of curriculum, representation, and community involvement. A survey was conducted of 37 NA/AN youth participating in a program entitled Native Education Raising Dedicated Students (NERDS) to examine how they felt represented, engaged, and respected in educational settings. While most previous research has focused on the implementation and pedagogical roots of culturally responsive teaching, this research instead evaluates how students have been affected during their involvement in a culturally responsive program called NERDS. Findings of this research show that there was no measured difference between the attitudes of new and veteran NERDS students. Participating students also stated that their involvement in NERDS allowed them opportunities to connect with and take pride in their NA/AN identity. The survey demonstrates that while NA/AN youth believe NERDS to be a positive representation of NA/ANs, they also feel that they are not represented in what is taught and read during school. The successful influence of the NERDS program offers a promising culturally responsive model for schools seeking to better serve NA/AN students.

Keywords: Native American/Alaska Native
Youth
Culture
Cultural Programming
Education
NERDS
Attitudes
Thesis
Curativity - Exhibit Your Story

A museum has three integral goals – to entertain, support learning, and build dialogue
amongst its visitors and between visitors and the content on display (Simon, 2010).
Informal learning experiences in settings such as museums, zoos, and aquariums can
be powerful drivers of affective and cognitive growth in learners young and old
(DeWitt & Storksdieck, 2008). Specifically, grade school field trips are some of the
most memorable and exciting portions of a student’s educational career. However,
without purposeful pre-visit preparation, students are not oriented to the physical
space of the museum prior to arrival and may not be able to access the concepts
presented in the museum in a single visit (Hein, 1998). In Curativity, we present a new
way to prepare students for learning through a shared project-based experience
before a field trip excursion so that students see field trips, and museums in turn, as
experiences and places that are fun, educational, and accessible.

Keywords: Learning
Design &amp; Technology
Learning
Design
Technology
Museum
Project-Based Learning
PBL
field trip
elementary school
informal learning
Constructionism
maker
makerspace
Stanford Graduate School of Education
Thesis
The dark Camus [electronic resource]

This dissertation explores a seldom-recognized dimension and seeks to complexify our understanding of an author renowned for his "solar" humanism. I begin with a reflection on the shifting, sometimes contradictory role of darkness in Camus's writings. Here I discuss texts like "Le Renégat" and La Chute to contrast more didactic, or typically "Camusian" works like La Peste and L'Homme Révolté in which battling images and metaphors of light and darkness clearly evoke the greater struggle between Good and Evil. The departing question, therefore, is what are we to make of this eternal dualism in Camus when it becomes blurred, and even inverted (the most renowned, and bewildering example of which is Meursault's murder in L'Etranger "à cause du soleil)"? By analyzing works from three distinct periods in Camus's career -- earliest essays, wartime, and last writings -- I argue that Camus suffered from the reputation he himself constructed as a, if not the "belle âme" of his generation. I subsequently trace the varying presence and intensity of his undoubted Shadow: an instinctive, irrational, sometimes violent, and ultimately, deeply cynical response to his equal calls for language, love, justice and measure under the sun.

Keywords: French and Italian.
Advisor: Apostolidès Jean-Marie primary advisor. Thesis advisor
Galvez Marisa advisor. Thesis advisor
Wittman Laura advisor. Thesis advisor
Data mining and modeling of the human microbiome [electronic resource]

The human gut microbiome teems with a dizzying array of microbial flora. Recent studies have demonstrated a causal relationship between microbial diversity and clinical phenotypes such as obesity and cardiovascular disease. Current analytical methods in the field excel at answering "who is there" in terms of the microbial population, yet are limited in answering "what are they doing". In particular, for dysbiosis of the human distal gut, we desire an understanding of microbial community structure at the biochemical level. My approach to revealing the biochemistry of the human microbiome consists of: 1) enhancing single-cell isolate genomes with metagenomic reads, 2) generating hundreds of microbiome-wide metabolic reconstructions spanning thousands of enzymatic reactions, and 3) creating a new modeling framework for complex microbial communities. I will first discuss a new method for recovering a complete genome from a single-cell experiment when there is insufficient coverage from the single-cell reads alone. This new method, called "Barrel of Monkeys", enables the efficient combination of both single-cell and metagenomic reads, with an accuracy of 99%. I demonstrate this method on four isolates of the enigmatic phylum TM7. I then annotate and perform metabolic reconstruction on novel genomes, to shed light on the biology of these organisms. Next, I will review a pipeline for comparative analysis of microbiome metabolic reconstructions, termed the GutCyc Collection. The utility of GutCyc will be motivated in a few vignettes, ranging from applications in metabolic route discovery in cardiovascular disease to pharmaco-microbiomics. Finally, I have modeled the human gut as a set of distinct microbial guilds in order to understand their biochemical thermodynamics. Guilds, or trophic species, are microbial equivalence classes where guild members share the same carbon source, nitrogen source, electron donor, and electron acceptor. I will review the details of a novel methodology for guild identification from reference microbial genomes, a pipeline for normalized abundance computation, and formulation of multi-guild biochemical mass balance equations. I will demonstrate the utility of this approach with applications in data mining and in thermodynamic modeling of an obesity microbiome dataset.

Advisor: Dill David L. primary advisor. Thesis advisor
Relman David A. primary advisor. Thesis advisor
Brutlag Douglas L.
Data mining for demand management [electronic resource] : segmentation, targeting, and analytics visualization

As power generation gets more distributed, and electricity markets become more deregulated throughout the world, utilities have been trying to find a way to match consumption with generation. Recently, advanced metering infrastructure (AMI) has been deployed wide-spread including smart meters, and smart meters make two-way communication possible between the meter and the central system. They provide concrete information about customer electricity consumption and create a unique opportunity to investigate and understand customer consumption behavior much better than before. Integrating the needs of utilities and potential benefits to customers, the ultimate target of the studies in this dissertation is building a data-driven demand management system which is based on smart meter data analytics. Thus, we develop scalable methodologies of data analytics using data mining, machine learning techniques. The methodologies developed in this dissertation include learning customer consumption patterns, segmenting customers by relevant features, selecting the proper customers for various energy programs and implementing a data analytics system.

Keywords: Electrical Engineering.
Advisor: Rajagopal Ram primary advisor. Thesis advisor
El Gamal Abbas A. advisor. Thesis advisor
Fischer Martin
Deconvoluting the immune repertoire [electronic resource]

In this thesis, I will demonstrate how combined functional/genomic analysis of the immune repertoire provides a clearer picture of a patient's immune response. I will show tools that I have advanced and developed for characterizing the immune system: immune repertoire library construction, long read sequencing on the Illumina platform, high throughput functional assays with antibodies cloned from single cells, and a data processing framework for combining functional and repertoire data. I will show influenza specific lineage recall over subsequent years of vaccination with trivalent influenza vaccine and identify several broadly binding anti-influenza antibody lineages. I will show how this platform can be used to identify which antibody lineages comprise segments of the mixed signal from a serum binding assay. Furthermore I will present evidence of low seroprevalence of influenza subtypes with H2, H5, H7 and H9 HA and apply this platform to identify multiple candidate antibodies for treating seasonal and pandemic influenza. Lastly I will show progress on a method for rapid DNA fabrication that could be used to quickly produce antibody genes mined from the repertoire, but has broader potential application in the field of synthetic biology.

Keywords: Bioengineering.
Advisor: Quake Stephen Ronald primary advisor. Thesis advisor
Bryant Zev David advisor. Thesis advisor
Fordyce Polly advisor. Thesis advisor
Deep linear neural networks [electronic resource] : a theory of learning in the brain and mind

Humans and other organisms show an incredibly sophisticated ability to learn about their environments during their lifetimes. This learning is thought to alter the strength of connections between neurons in the brain, but we still do not understand the principles linking synaptic changes at the neural level to behavioral changes at the psychological level. Part of the difficulty stems from depth: the brain has a deep, many-layered structure that substantially complicates the learning process. To understand the specific impact of depth, I develop the theory of gradient descent learning in deep linear neural networks. Despite their linearity, the learning problem in these networks remains nonconvex and exhibits rich nonlinear learning dynamics. I give new exact solutions to the dynamics that quantitatively answer fundamental theoretical questions such as how learning speed scales with depth. These solutions revise the basic conceptual picture underlying deep learning systems--both engineered and biological--with ramifications for a variety of phenomena. I highlight three consequences at different levels of detail. First, the theory shows that layerwise unsupervised learning is a domain general strategy for speeding up subsequent learning, which I link to critical period plasticity in sensory cortices. Second, the theory suggests that depth influences the size and timing of receptive field changes in visual perceptual learning. And third, by considering data drawn from structured probabilistic graphical models, the theory reveals that only deep (and not shallow) networks undergo quasi stage-like transitions during learning reminiscent of those found in infant semantic development. These applications span levels of analysis from single neurons to cognitive psychology, demonstrating the potential of deep linear networks to connect detailed changes in neuronal networks to changes in high-level behavior and cognition.

Keywords: Electrical Engineering.
Advisor: McClelland James C.
Ng Andrew Y.
Shenoy Krishna V. (Krishna Vaughn) advisor. Thesis advisor