VictorJuiz/thesis huggingface dataset:
The impact of environmental exposures on the human and mouse gut microbiome
Keywords: Genetics.

Advances in sequencing technologies have enabled unprecedented opportunities to characterize the effects of the microbiome on host physiology and the development of disease. Understanding the factors that influence microbiome colonization and stability and that shape immune responses is critical to harness the microbiome as a therapeutic target. In this dissertation, I explore microbiome associations with aberrant immunological conditions. I present my research in human and mouse models characterizing the impact of microbiome altering exposures during critical immune development windows. Chapter 2 describes the first interventional study to assess the impact of common household antimicrobials on the developing gut microbiome during the first year of life. Chapter 3 evaluates the efficacy of prebiotics to enrich for microbes that produce immunomodulatory compounds to offset life-threatening gut inflammatory responses. Chapter 4 describes leveraging the known microbiome differences in mouse models to mine for putative protective species in colonic inflammation. Chapter 5 addresses the application of novel sequencing technologies to overcome the current limitations of measuring the gut microbiome. Overall these chapters provide a better understanding of measuring host-microbial interactions in the context of immune regulation.
Implementation and Testing of Reduced-Order Models in a General Reservoir Simulation Setting
Keywords:  Energy Resources Engineering
School of Earth Energy &amp; Environmental Sciences
Reduced Order Modeling
Reservoir Simulation
Simulation Acceleration
Thesis

Reduced-order modeling can lead to computational savings in reservoir management applications when many related models must be simulated, as is the case, for example, in production optimization. In this study, we implement two reduced-order modeling procedures into our in-house simulator AD-GPRS (Automatic Differentiation General Purpose Research Simulator). The methods considered are a POD-Only (proper orthogonal decomposition) technique and a Gauss-Newton with approximated tensors (GNAT) procedure. We believe this to be the first implementation of these methods in a general-purpose reservoir simulation setting. Both approaches entail offline (training runs plus preprocessing) and online (runtime) computations. POD-Only involves expensive online matrix multiplications, which greatly limit the attainable speedup. GNAT, by contrast, entails much less costly runtime computations.
The methods are applied to a 2D oil-water model and to a 3D, four-component, oil-gas compositional case. These models contain 13,000 and 4800 grid blocks, respectively. Some amount of numerical experimentation is required to determine the appropriate POD-Only and GNAT parameters. We show that, using parameters that provide accurate reduced-order model results, POD-Only is actually slower than the full-order AD-GPRS simulations, but GNAT can provide speedup of around 2-3X for the cases considered. More substantial speedup is achieved in some compositional cases for which AD-GPRS encounters numerical difficulties. Speedup could be further enhanced by eliminating the AD-GPRS computations that are not required for GNAT. Application of POD-Only and GNAT on locally refined versions of the original models is, unfortunately, not very successful. This may be due to some of our detailed numerical treatments. This issue should be clarified and, if possible, rectified in future work.
Improved drug development and disease diagnosis using tailored light-molecule interactions
Keywords: Applied Physics.

Light-matter interactions are critical for many modern biomedical techniques, from fluorescence-based DNA sequencing to photoablation of tumors. Even so, existing optical diagnostic tools can be slow and existing drug treatments often have adverse side effects. Here, we explore two methods for improving drug purification and disease diagnosis based on tailored light-molecule interactions. First, I will discuss how the optical-frequency magnetic resonances of dielectric nanoparticles can be used to separate chiral molecules for enantiopure pharmaceuticals. Currently, half of pharmaceuticals on the market are chiral, but 90% of these are sold as mixtures since existing chemical methods are expensive and time consuming. Yet, the non-therapeutic enantiomer can reduce efficacy and lead to adverse side effects. Illumination with circularly polarized light provides a potentially cost-effective and versatile alternative but can due to the weak nature of chiral light-matter interactions. Using silicon nanospheres as a model system, I explore electromagnetic design parameters to enhance enantioselective light absorption in chiral molecules while maintaining total molecular absorption rates. With optimized particles, enhancements in the rates of enantioselective absorption can reach 7X, leading to a projected 50% increase in yield for the separation of the molecule camphor. Next, I will discuss how Raman spectroscopy can enable rapid identification of bacteria. I acquire Raman spectra from over 60,000 bacterial cells, spanning 30 strains from 22 species and covering 95% of all bacterial infections treated at Stanford Hospital. This large reference dataset allows us to apply machine learning techniques to accurately identify bacteria strains and antibiotic treatments. I show how this method translates to clinical patient samples, predicting treatment for 25 patient isolates with 99.0±1.9% accuracy. This work lays the foundation for a technique that could allow for accurate and targeted treatment of bacterial infections within hours, reducing healthcare costs and antibiotics misuse, limiting antimicrobial resistance, and improving patient outcomes.
Improved Referral of Very Low Birthweight Infants to High-Risk Infant Follow-Up in California
Keywords:  Department of Health Research & Policy
neonatology
Thesis

Background
A statewide initiative was implemented in California in June 2013 to address disparities in referral of very low birthweight (VLBW, birthweight less than 1500 grams) infants to high-risk infant follow-up programs. We examined the change in high-risk infant follow-up referral rates and identified risk factors associated with non-referral in the pre- and post-initiative periods.
Methods
We included VLBW infants born 2010-2016 in the population-based California Perinatal Quality Care Collaborative who survived to discharge home. We used multivariable logistic regression to examine factors associated with referral and derive risk-adjusted referral rates by NICU and region.
Results
83% of VLBW infants were referred in the pre-initiative period (January 2010-June 2013); 95% were referred in the post-initiative period (July 2013-December 2016). Referral rates improved the most (greater than or equal to 15%) for infants born at greater than 33 weeks gestation, with birthweight 1251-1500 grams, and born in intermediate and lower-volume NICUs. Post-intervention, Hispanic race-ethnicity, small for gestational age status, congenital anomaly, and major morbidity were no longer associated with decreased odds of referral. Lower birthweight, outborn status and higher NICU volume were no longer associated with increased referral. African-American race-ethnicity was associated with lower odds of referral, and higher NICU level with higher odds, during both time periods. Referral improved in many previously poor-performing NICUs and regions.
Conclusion
High-risk infant follow-up referral of VLBW infants improved significantly and disparities decreased following the statewide improvement initiative. Our results demonstrate the benefit of a targeted initiative in California, which may be applicable to other quality collaboratives.
Impurity quantum phase transitions in quantum dot nanostructures
Keywords: Physics.

Electronic systems subject to competing interactions can end up in different phases as the balance between these interactions shifts. When a quantum critical point separates these phases, exotic electronic behavior often marks the vicinity of the transition. In this work, we construct nanopatterned devices to probe such critical phenomena. The basic element of our devices is the GaAs/AlGaAs quantum dot, an isolated region of electronic charge which is coupled to a two-dimensional gas of weakly interacting electrons. We use different designs of quantum dots to realize different models. The first device studied in this work realizes the spin two-channel Kondo ('spin 2CK') model. In this model, a single impurity (i.e. a single spin-degenerate dot) is coupled to two separate reservoirs. When the couplings to both reservoirs are unequal, the more strongly coupled reservoir screens the impurity spin degeneracy and forms a many-body singlet; this is known as the Kondo effect. When both reservoirs are coupled equally strongly, a non-Fermi liquid ground state arises as a result of the overscreening by both reservoirs. We probe the anomalous scaling properties of this state, and show how it transitions into a more conventional Fermi liquid under the influence of various perturbations. The second device is first operated as a single metallic quantum dot in the quantum Hall regime. Spin degeneracy is broken, but the device can be tuned such that there is now a charge degeneracy which can then be screened by coupling to a reservoir. We tune to and away from equal couplings to see the effect of the two-channel Kondo state. Finally, we operate the second device in its full form as a double-dot device, to explore the competition between dot-lead and interdot interactions.
In depth study of in situ combustion kinetics and coupling to flow
Keywords: Energy Resources Engineering.

This thesis furthers understanding of three topics that are critical to In Situ Combustion (ISC) processes: crude oil kinetics, the tools used to model accurately and practically complex kinetic behavior and how oil kinetics couples with flow, especifically in systems with complex permeability distributions. On kinetics, we study the effects of pressure on crude oil kinetics for a large range of pressures and heating rates (1.5, 2.0, 5.0, 7.5, 8.0, 10.0, 15.0, 20.0, and 30.0 °C/min. Our results show that the activation energy of global reactions is not affected by changes in both partial pressure (21, 42, 50, 84, 209, and 250 psi) and absolute pressure (100-2000 psi) with values ranging 50 and 60 kJ/mol for the LTO regime and 90-100 kJ/mol for the HTO regime. Three different crude oils were tested. For one of the crude oils, we observe an increasing trend in oxygen consumption as absolute pressure is increased up to a critical pressure (~500 psi), after which it remains constant. This is associated to light component evaporation at low pressures, decreasing the amount of oil available for fuel generation. Total oxygen consumption starts to decrease again at very large pressures (> 1500 psi) and we associate it to water phase behavior at these conditions. We then propose a workflow and construct the corresponding tools to match Arrhenius-based reaction models for lab-scale numerical simulation models. The workflow is validated by matching multiple reaction models to experimental data obtained for a large range of heating rates (1.5-30 °C/min). On flow, we study instabilities that have been observed during combustion tube experiments by analyzing simple analogous problems and performing perturbation analysis from which we derive a new stability parameter. Finally, we propose and test a new experimental approach to observe directly how oil kinetics evolve under flow conditions by using thermal imaging and combining images with ramped temperature oxidation (RTO) experimental data. Results show that the reaction zone in lab conditions is in the order of centimeters. Reaction zone thicknesses range between 10-30 cm for the LTO zone and 10-50 cm for the HTO zone. Furthermore, we show how the new approach can help investigate complex systems and behaviors, such as oscillations, that could not otherwise be studied with conventional experiments.
In the mind of the beholder : neural and computational mechanisms underlying perceiver-driven biases in information processing
Keywords: Psychology.

Rather than being passive observers, people can be better described as active perceivers of the world around them. Incoming information is not passively taken in, but is selectively filtered and altered by a perceiver's beliefs, goals and motivational states. The current work examines the neural and computational underpinnings of such perceiver-driven biases in information processing. In one study, we combined computational modeling and functional magnetic resonance imaging to provide a mechanistic account of motivational biases in perceptual judgments of ambiguous images. We showed that motivational biases can be dissociated into response and perceptual components, each associated with distinct neural processes. In a second study, we extended our work to a more naturalistic setting with dynamic audio-visual stimuli. We scanned participants watching videos about immigration policy and showed that political attitudes modulated neural responses to the videos. In particular, activity timecourses in the DMPFC was more similar between participants with similar political attitudes, than between participants with opposing political attitudes. Furthermore, the neural divergence between conservative-leaning and liberal-leaning participants was associated with increased use of moral-emotional language. Together, these studies explore the neural processes involved in biasing information processing, and provide illustrative examples of how the tools of cognitive neuroscience allow us to peer into the mind of the beholder.
In Word, Not Deed: The Politicization and Decentralization of the National HIV/AIDS Program in the Philippines
Keywords:  Fisher Family Honors Program in Democracy
infectious disease
HIV/AIDS
HIV
decentralization
Philippines
health systems
human biology
CDDRL
Center for Democracy
Development
and Rule of Law
Thesis

This year-long project explores the nuances of the Philippine National AIDS/STI Prevention and Control Program (NASPCP) within the context of a decentralized health system. The Philippines, unlike the rest of its Southeast Asian counterparts, has experienced a rapid increase of HIV cases within the last decade. This rising epidemic has mainly been isolated within marginalized and underserved populations such female sex workers (FSWs), males who have sex with males (MSMs), and people who use intravenous drugs (PWID). Nevertheless, the 140 percent increase in cases have also reflected a demographic shift to the young adult cohort, with a serious potential for the epidemic to spill over in the general population. In order to understand the gaps and barriers of the NASPCP in a different perspective, this study employed a mixed methods approach that involved qualitative research coding and a qualitative case study on three specific cities in Metro Manila with high prevalence of HIV/AIDS. This study incorporated the framework of decentralized local decision spaces to better understand the perspectives of those involved in HIV/AIDS care, research, and advocacy. Data analysis revealed the following main themes: (1) tension between national policy and local implementation; (2) local heterogeneity of HIV responses; (3) narrow decision spaces for regional and local public health stakeholders; and (4) interference of national and local politics on the proper flow of resources and information. Overall, the politicization of health and the extent at which the Philippine HIV healthcare system is truly devolved can constrain the comprehensive objectives of the NASPCP. HIV/AIDS is a serious public health and development problem for this developing nation. This study offers specific technical suggestions and research recommendations for those in the field to move forward. This study proposes that when working within HIV/AIDS program implementation and delivery of care, it is necessary to fix certain mechanisms of this decentralized system and seriously consider the role of politics in health.
Inclusive Innovation: Overcoming the Gender Gap in India's Emerging Mobile Health Ecosystem
Keywords: mobile phones
gendered innovation
mHealth
ICTs
ICT4D
inclusive innovation
India
STS
Thesis

Mobile health (mHealth) leverages the unprecedented reach of digital technologies to improve healthcare delivery. However, in comparison to Indian men, Indian women are 28% less likely to own cell phones and 58% less likely to use mobile internet. This thesis seeks to elucidate the implications of this gender gap for the Indian mHealth space, with a focus on how gendered innovation methodologies might contribute to greater gender equity. To do so, I begin by synthesizing currently disconnected literatures on mHealth, Information and Communication Technology for Development (ICT4D), and the role of gender in Indian society. The practical implications of gendered mobile phone dynamics are further expounded with a case study analyzing Kilkari, a maternal health audio-messaging mHealth program. This thesis then draws on semi-structured interviews with a range of actors in the Indian mHealth space to explore the potential relevance of gendered innovation methodologies. The discussion concludes with an analysis of systemic barriers to gender equity in Indian health care. If mHealth innovations are to truly benefit Indian women, the entire mHealth ecosystem must pursue a more inclusive approach to innovation.
Indigenous Fashion: Innovation through Enterprise
Keywords: Indigenous
Native American
American Indian
Native American Studies
Center for Comparative Studies in Race and Ethnicity
Fashion
Entrepreneur
Designer
Artist
Tradition
Culture
Mentorship
Expansion
Contemporary
Thesis

This Honors Thesis investigates the experiences of contemporary Native fashion entrepreneurs who are trailblazing Indigenous design and representation through innovative artistic and business practices. Through qualitative analysis of common themes shared between participatory entrepreneurs using the software NVivo, this work explores the opportunities for mentorship and industry expansion offered by their enterprises. Private enterprise is largely underdeveloped in Indian Country which motivated my exploration into the fashion industry. Given mentoring, support, and a vision, artists can and are finding innovative ways to expand this industry and promote compelling, authentic, respectful representations of Native nations. The participants in this study are inspirational examples of Indigenous artists who have begun their own enterprises by drawing on tradition and showcase the enduring and continuously evolving nature of Indigenous cultures. They center their businesses on core values of community, growth, respect, and advocacy. By proliferating their work, these entrepreneurs contribute to a growing industry of Native fashion which is actively combating appropriative practices. They are taking the means of production back into their own hands and have unlimited potential to empower themselves, other artists, and their communities.
Inference of Sub-Resolution Stacking Patterns from Seismic Data in Spatially Coupled Models
Keywords:  Department of Energy Resources Engineering
School of Earth Energy &amp; Environmental Sciences
inverse problem
reservoir characterization
hidden markov model
Thesis

Geological modeling and characterization of energy reservoirs greatly relies on the interpretation of seismic data due to its extensive spatial availability. Owing to many factors, including subsurface complexities, heterogeneity and limited seismic resolution, accurate description of subsurface geological configuration becomes a major challenge, giving rise to tremendous uncertainty in reservoir evaluation. The ability to reason about arrangements of thin sub-seismic scale beds is particularly important in the development of strongly heterogeneous unconventional formations due to complex completion strategies. This work is focused on quantitative interpretation of individual seismic traces and extraction of information relevant to recognition of various geological parasequences. The proposed workflow involves stochastic modeling of stratigraphic sequences comprising thin subresolution beds, and subsequent application of a generative statistical model to invert for those sequences from the respective acoustic responses.
Information processing : of humans, by humans and for humans
Keywords: Electrical Engineering.

The core mission of information science is to design information processing tools that aid human communication and scientific discovery. Naturally, the development of such tools is shaped by concurrent understandings of human biology and behavior. In our 21st century world, myriad human-focused investigations have opened up rich potential markets for tool design. My research explores such intersections between human biology and information processing tool design, and the bidirectional influence between the two. In this dissertation, I detail three genres of information processing: of humans, by humans and for humans. For information processing of humans--that is, of humans' genomic sequencing data--I present two bioinformatics pipelines. To demonstrate information processing by humans, I describe a novel lossy image compression framework that is rooted in the human abilities to recognize, describe and generate images. Finally, I describe a science communication effort that employs computational tools to process information and produce journalistic media for human consumption. Together, these projects support the thesis of this dissertation: that information processing tools can be used to improve our understanding of human communication needs, and that an improved understanding of human communication can, in turn, be used to design better information processing tools.