VictorJuiz/thesis huggingface dataset:
MEASURING PM2.5 VARIATION AND ITS EFFECTS ON LIVED COMMUNITY EXPERIENCE AND HEALTH IN SAN FRANCISCO

Given the clear importance of air quality on health and the sparse amount of air quality monitoring stations around California, Brightline Defense Project (“Brightline Defense” or “Brightline”), a Bay Area based environmental justice non-profit, deployed an air quality monitoring network to better understand air quality and low-income urban resident experience of air quality in San Francisco. This project arose as part of the California Air Resources Board’s (CARB’s) response to AB617. CARB established the Community Air Protection Program
(CAPP) with the goal to reduce exposure in communities most impacted by air pollution. Based on community identified need for accurate and timely data of specific air pollutant levels at more locations than the single BAAQMD monitor was providing in San Francisco, Brightline began their localized air monitoring project. Brightline targeted disadvantaged communities who historically may not have had the resources to monitor air quality with personal low cost sensors. They deployed low cost sensors in five San Francisco neighborhoods, two categorized as disadvantaged communities, two requested by community partners, and one for co-location. They also conducted community surveys with the aim to better understand how air quality is affected by wildfires, the differences in air quality between neighborhoods and across time, and how residents of different neighborhoods feel air quality impacts their health.

Keywords: Air Pollution
PM
San Francisco
Health Disparities
Community Health and Prevention Research
Thesis
Measuring the quality of teaching and teacher training in low-income settings

Despite increases in access to education in recent decades, student learning remains a huge challenge, with 250 million children around the world still unable to read or write. Controlling for socioeconomic factors, teaching is well established as the most important school-based determinant of student learning. High quality teaching is able to offset the learning shortfalls of marginalized students and improve long-term outcomes, such as university graduation rates and wages. However, many teachers in developing countries are under-prepared, lacking the knowledge and skills to support student learning. Beyond the simple knowledge that good teachers are important, it is imperative that policymakers understand which specific teaching practices most contribute to student learning and how to develop these through teacher training. This dissertation measures the quality of teaching practices and of professional development (PD) programs intended to improve teaching and thereby student learning in several low-income settings. Each paper applies a different method to solving this measurement problem and informing the design of future PD programs. The first is a large-scale, randomized evaluation of a national PD program in China. The second develops a survey instrument to standardize reporting on teacher PD programs and applies it PD programs in low- and middle-income countries in a meta-analysis. The third leverages the random assignment of teachers to students in six U.S. school districts to estimate the impact of teaching practices on student learning and how these vary with student characteristics

Keywords: Education.
Advisor: Carnoy Martin
Loyalka Prashant
Domingue Ben
Media manipulation at home and abroad : evidence from the Arab world

This dissertation examines how Arab autocrats use media to influence domestic and foreign publics. While much of the literature on authoritarian media focuses on indoctrination, signaling, and censorship, this dissertation investigates how autocrats manipulate narratives and discourse to maintain their power at home and further their influence abroad. The first paper claims that autocrats advance narratives about threats and conspiracies to reduce dissent. These narratives can shape public beliefs about the regime's competence and are difficult to fact-check by independent media. Using topic modeling on hundreds of thousands of articles from Egypt and Syria, the paper shows that protests were often associated with an increase in discussions of threats and conspiracies. The second paper then turns to the effects of these narratives on public attitudes and online behavior. To do so, the paper uses data from the Arab barometer, twitter followers of major Egyptian newspapers, and an original survey experiment in Egypt. The results show that discussions of conspiracies and threats increase the likelihood that the public prioritizes foreign threats over domestic problems and improve public trust in the government. The third paper examines how regimes employ transnational media to manipulate foreign publics. Using the cases of Al-Arabiya and Al-Jazeera, the paper claims that Saudi Arabia and Qatar utilize the agenda-setting and framing powers of transnational media to influence regional publics. Specifically, the two countries deploy transnational media to highlight topics that advance their influence, undermine competitors, and support the interests of their sponsor countries

Keywords: Political Science.
Advisor: Blaydes Lisa
Weinstein Jeremy M.
Fearon James D.
Schultz Kenneth A.
Meet the Mother: Maternity, Identity, and Agency in The Tale of Genji

The Tale of Genji, the 11th century classic work of Japanese literature, has never ceased to be the focus of scholars’ curiosity and exploration. Despite the inclination of contemporary readers to reflect ourselves in the premodern figures who are almost a thousand years away from us—to be confounded by the notorious affairs of the protagonist and sympathize with the female characters—we witness the recent effort of researchers to detach our standard understanding of agency and gender from the study of premodern Japanese literature. This thesis follows the path and aims to complicate the previously constructed definitions of agency/passivity, freedom/restriction, and empowerment/victimization. This study mainly investigates the following three elements in the tale: the mother figures, the fluidity of roles and privileges, and the female characters’ agency. In general, the analysis shows multiple possibilities of interpreting the story.

Keywords:  Stanford Global Studies
Premodern Japanese Literature
Heian Literature
The Tale of Genji
Motherhood
Agency
Gender
Stanford Center for East Asian Studies
Thesis
Advisor: Stilerman Ariel
Mesostructure design and analysis of additive manufactured polymers

Additive manufacturing (AM) is revolutionizing how designers, engineers, manufacturers, and end-users create, fabricate, and interact with products. It enables the fabrication of complex parts with novel mechanical, thermal, electrical, and optical properties not found in any natural materials. In addition, AM has spurred development of novel design and analysis tools that can handle the extreme intricacy of AM parts. By combining powerful computational tools with the rapid turnaround of AM, new products can be created at breakneck speeds. However, there are still several barriers to widespread adoption of AM technologies, including a lack of reliable mechanical models. This research investigates the most widespread AM process: material extrusion of polymers. Despite its extremely low cost, material extrusion is rarely used for production-grade parts due to its high anisotropy. Being able to predict the anisotropy will lead to greater adoption. However, existing mechanical models for material extrusion parts tend to be empirical or numerical without explaining the fundamental origin of observed anisotropy, leading to results that differ from printer to printer. This work proposes a geometric explanation for the anisotropic mechanical properties found in material extrusion parts. First, this work investigates the mesostructure of material extrusion parts and provides a parameterization for the void geometry. Next, a closed-form constitutive model is developed based on the void geometry and porosity. Numerical and empirical studies conducted show the closed-form model is accurate within 10% for porosity values below 10%. Finally, the model is used to develop a hybrid stress-aligned/concentric infill scheme that accounts for optimal print path orientation as well as printability constraints. The hybrid infill scheme is evaluated against a baseline rectilinear infill scheme for the classical open hole notch test, yielding 9% higher stiffness and 8% higher strength than the baseline rectilinear infill

Keywords: Aeronautics and Astronautics.
Advisor: Senesky Debbie
Borja Ronaldo I. (Ronaldo Israel)
Chang Fu-Kuo
Methods and metrics for efficient video object detection

Understanding video contents by object detection is an essential task for machine intelligence. Video is an abundant data source, yet detecting objects from videos is computationally intensive or even prohibitive on edge devices. We start with efficient video object detection methods, which require fewer average FLOPs per video frame. We also find out that current widely adopted metrics do not fully describe a video object detector; therefore, we propose new metrics that measure the swiftness of an algorithm. By combining the proposed methods and evaluating them with the new metrics, we design a video object detection system that achieves high average accuracy, low response time, and a balanced workload under a limited computation budget. Two efficient methods for video object detection described in this thesis are CaTDet, which reduces the spatial area of detection, and PatchNet, which reduces the detection frequency with little accuracy drop. Experiments on multiple datasets show that CaTDet and PatchNet can reduce computation by 3.8x-13.0x and 3.4-4.9x, respectively. Combining CaTDet and PatchNet, we design SwiftDet, which performs joint spatial-temporal reduction and reduces FLOPs by 6.0x on ImageNet for Faster R-CNN ResNet-101. Evaluation with average delay and average latency further demonstrates that SwiftDet achieves a lower response time than CaTDet or PatchNet alone

Keywords: Electrical Engineering.
Advisor: Dally William J.
Horowitz Mark (Mark Alan)
Fatahalian Kayvon
Methods for imaging brain function using BOLD and viscoelastic contrast

Modern functional neuroimaging techniques have greatly advanced the field of neuroscience, with different modalities targeting distinctive aspects of brain physiology, functional architecture, and dynamics. Specifically, functional magnetic resonance imaging (fMRI) uses blood-oxygen-level dependent (BOLD) contrast to study the underlying neurovascular coupling. One of the limitations of fMRI is its low temporal resolution for collecting the time series data, which has been partially addressed in human brain imaging with the development of parallel imaging. However, parallel imaging is not attainable in some cases due to infeasibility of high-density phased-array coils. To overcome this, we developed an approach to accelerate fMRI acquisition without parallel imaging by adapting phase-offset multiplanar (POMP) imaging to echo-planar imaging (EPI), using gradient blips inspired by CAIPI to shift each of the simultaneously excited slices into different regions of an extended field-of-view, such that there is no aliasing of the simultaneously excited slices. Since fMRI only provides an indirect measure of neuronal activity, the neuroimaging community has been searching for different contrast mechanisms that can further elucidate the process of neuronal signaling. A new and emerging functional neuroimaging technique, functional magnetic resonance elastography (fMRE), measures changes in brain stiffness due to neural activity. We introduce a novel multi-modal method, fMRI-fMRE, to observe this neuromechanical coupling mechanism in the human brain. The novelty in our approach comes from utilizing a time series acquisition, similar in concept to that employed in fMRI, where the magnitude and phase information from the time series are processed and analyzed separately to arrive at both fMRI and fMRE activation maps. Since our simultaneous fMRI-fMRE method is both multi-modal and concurrent, it allows for comparison of the spatially localized BOLD and stiffness changes within the same scan, removing confounds inherent in separately acquired scans. Motivated by early reports that fMRE could provide an order of magnitude increase in temporal resolution, we initially tested this method with partial-brain scans, demonstrating stiffness increases in the visual cortex in response to visual stimuli. Subsequently, we extended the fMRI-fMRE method to whole-brain imaging to explore global brain stiffness dynamics in response to both visual and motor-planning tasks. The end of my thesis journey coincided with the COVID-19 pandemic, which led to widespread incidence of infection. To diminish the risk of virus transmission, many research MRI scanning facilities started to require continuous facial covering by scan subjects. Since mask-wearing can slightly change the carbon dioxide concentration in inspired air, and carbon dioxide is a potent vasodilator, the final project in this thesis investigates the effect of facial covering on fMRI BOLD signal

Keywords: Bioengineering.
Advisor: Glover Gary H.
Daniel Bruce (Bruce Lewis)
Pauly John (John M.)
Methods for leveraging social media data to quantify and improve pharmacovigilance efforts

Adverse drug reactions impact the health of 100,000s of individuals annually in the United States with associated costs in the hundreds of billions. Pharmacovigilance seeks to improve drug safety and limit patient potential for adverse drug events. Social media has been identified as a promising potential source of information for pharmacovigilance. The adoption of social media data as a component of pharmacovigilance efforts has been hindered by the massive and noisy nature of the data. I present work seeking to (1) identify social media data discussions of drug and drug-related terms, (2) use word embeddings derived from social media data to create quantitative severity scores for adverse drug reactions, and (3) create digital cohorts of social media users and monitor them for changes in prevalence of drug discussion rates in the general US potential, specifically with regards opioids. I present novel methods that enabled these efforts, as well as the results and findings of these efforts. I believe leveraging social media data to enhance pharmacovigilance will benefit U.S. patient populations and further empower public health and regulatory efforts

Keywords: Medicine. Department of Biomedical Data Science
Advisor: Altman Russ 
Chen Jonathan H. 
Eichstaedt Johannes C. 
Liang Percy
Methods to visualize, dissect and simulate complex cellular behaviors

When we consider a problem, like a disease, our instinct is to find the source of the issue and fix it. For some diseases we encounter this is possible because we can identify a single trackable cause of the issue. For example, in the mid-1800's surgeons realized that they could prevent bacterial infections and death in patients by simply washing their hands and wearing gloves during surgery. But for other diseases, like diabetes or schizophrenia the 'cause' is not so evident, and work over time has taught us that these diseases are systemic. It's only through fully understanding the underlying system that we can tackle the disease. Systems large and small have been found to underlie all of biology, not just complex diseases. It's not enough to understand how proteins or pathways or cells work in isolation. If we really want to understand them, we need to piece together how they work as a whole -- as a system. My thesis work is a story of systems on different scales: from a pathway, to a cell, to a population of cells. I will first discuss work we did to understand how increasing stimulus into a pathway is able to produce non-monotonic outputs. Next, I report efforts to experimentally validate a central prediction that arose out of our lab's recent Escherichia coli whole-cell modeling project: sub-generational gene expression. I will then discuss how revelations from this work led to my most recent work, adding operon structure into the whole-cell model. And finally, I will discuss plans we have to experimentally determine the import of this architecture inensuring population survival, and perspectives on the future of model-driven discovery. Although these systems all seem different, they connect through common themes including the presence of emergent phenomena and the need for methods to visualize, dissect and simulate these complex cellular behaviors

Keywords: Bioengineering.
Advisor: Covert Markus
Bryant Zev David 
Lin Michael Z.
Microbes in urban waters : sources of microbial pollution, nature-based solutions, and methods to inform public health decision-making

Coastal environments are an important sources of economic opportunities, recreation, and ecosystem services, however due to population growth and increasing urbanization, many waterways are polluted. Microbial pollution in surface waters is a problem in particular. Various sources of microbial pollution, including wastewater and urban runoff, can transport pathogens to waters where they pose public health risks. Thus a better understanding of the sources and fates of pathogens in stormwater runoff and solutions that reduce the impact of these pollution sources on water resources is needed. At the same time, there are benefits to be gleaned from pollution sources, as they are reflective of the infectious diseases circulating in a community. Therefore, tools to harness the information present in sewage should be developed in tandem with strategies to reduce the impact of pollution sources on the environment. The research described in this dissertation addresses questions about microbial communities and pathogens in urban waters that are of importance to public health decision making. Nature-based solutions to reduce microbial pollution in urban waters are also explored. These contributions will advance our understanding of sources of microbes and pathogens in urbanized coastal environments and the performance of sustainable strategies to mitigate public health risks from contact with polluted waters

Advisor: Boehm Alexandria
Luthy Richard G.
Mitch William A.
The microbial ecology and biogeochemistry of alluvial subsurface systems

At the intersection of terrestrial and aquatic environments, alluvial landscapes link up-land, riverine, and subsurface ecosystems. Floodplains and associated alluvial aquifers are hotspots of the biogeochemical processes influencing surface water and groundwater quality. The microbial communities within these zones are often drivers of these processes, and thus their structure and function may affect water quality. Currently, depth-resolved information about the structure and function of microbial communities within floodplains and their impacts on alluvial aquifers is limited. However, such information is critical for understanding biogeochemical cycles and how elemental stores are altered from perturbations initiated by the water cycle within floodplains. Surveyed from the surface to the sediment-bedrock interface, this dissertation illuminates temporal and depth-specific trends in microbial community dynamics within floodplains of the Western U.S. Here I present results from multiple field projects throughout the Western U.S. sampled under different hydrologic conditions. This work employs complementary molecular approaches in a field-based study, where the microbial ecology and geochemistry of key biogeochemical cycles (N, Fe, S, C) are explored. Through concurrent lines of geochemical and microbial evidence, spatiotemporal in-sights on subsurface microbial dynamics over a record flooding event are presented. Semiarid, intermontane cores (down to 6m depth) sampled under drought conditions in the Western U.S. and over drought-to-flood conditions on the Wind River-Little Wind River floodplain at Riverton, WY. Pairing depth-resolved high-throughput sequencing with detailed geochemical measurements for more than 250 samples from five sites, I identified hydrologic regime transitions drove the development of microbial niches and geochemical redox-stratification patterns within the vertical profiles examined. These findings suggest that transitions from unsaturated to saturated conditions coincided with major changes in microbial diversity and community stability, supporting trends in spatiotemporal succession that hold possible microbial and geochemical implications for subsurface systems and riverine water quality extending beyond this work

Keywords: Environmental Earth System Science.
Advisor: Bargar John
Fendorf Scott
Francis Christopher
Microfoundations and measurement for ambiguity in communication with application to social networks

Extant research often models ambiguity — that one object can have multiple interpretations — as "noise" or "optional" (e.g. McMahan and Evans 2018, Reagans and Zuckerman 2008). This stance is in tension with evidence that ambiguity is common, exists to varying degrees, and is consequential. Ambiguity is therefore better thought of as "more or less" rather than "yes or no". Predictably, literatures that seek to bracket ambiguity find themselves without the analytical tools to specify core theoretical claims and devise measurement strategies. This dissertation works towards taking ambiguity seriously by introducing microfoundations for its analytical specification and a measurement strategy at the level of the word. To demonstrate the benefits and broader ramifications of this orientation, these theoretical and methodological tools are applied to the "brokerage" literature (Burt 1982) to surface, clarify, and resolve a long-standing contradiction: do brokers merely transmit or actively translate?

Keywords: Business.
Advisor: Goldberg Amir 
Potts Christopher
Sorensen Jesper B.
Microlocal analysis with applications to seismic inverse problems

This thesis considers the travel time tomography problem for elastic media, particularly in the transversely isotropic setting. A pseudo-linearization argument reduces the problem to the microlocal analysis of certain operators, bringing the problem in line with certain problems in X-ray tomography and boundary rigidity studied by de Hoop, Stefanov, Uhlmann, Vasy, et al.. In this thesis, we will consider two versions of the travel time tomography problem, with the two versions using different kinds of assumptions, thus leading to the usage of different kinds of mathematical analysis. The analysis involves asking whether we can provide parametrices for certain classes of operators that are not quite elliptic. In one version of the problem, we show recovery under "global" assumptions using an operator calculus first developed by Boutet de Monvel used to provide parametrices for parabolic operators, while in the second version of the problem, we localize the problem by adding an artificial boundary; the analysis then concerns finding parametrices to certain classes of non-elliptic scattering pseudodifferential operators

Keywords: Mathematics.
Advisor: Vasy András
Luk Jonathan (Professor)
Mazzeo Rafe