VictorJuiz/thesis huggingface dataset:
The roles of life stage and climate change on the persistence of juvenile giant kelp, Macrocystis pyrifera, under herbivory

Giant kelp forests are some of the most productive and biodiverse ecosystems in the world, but they are vulnerable to stressors associated with global climate change. As a foundation species, giant kelp (Macrocystis pyrifera) provides habitat, food, and refuge for hundreds of species, many of which are economically important. Much of what is known about giant kelp is focused on the adult stage and the abiotic factors influencing the persistence and recovery of this species. However, under increasing environmental variability, it is critical to understand the factors impacting the survival of juvenile kelp, which has direct implications for the success of the adults. One of the largest gaps in our knowledge of giant kelp forests is the role of a diversity of grazers on the early life stages of M. pyrifera, and virtually nothing is known about the impacts of climate change on these species interactions. In this dissertation, I use both laboratory and field experiments to quantify the impacts of four grazers on two life stages of juvenile kelp under ocean acidification and hypoxia. I found that grazers are a significant source of mortality on juvenile kelp, and that an often overlooked herbivore in the literature, the brown turban snail, emerges as a dominant grazer on both microscopic and macroscopic stages. Under climate change, consumption is significantly reduced, increasing estimated kelp survival, and hypoxia drives these decreases in consumption across all four grazing species. By utilizing natural variability regimes within an upwelling season, I found through field experiments that grazing rates decreased with high monthly oxygen variance, suggesting that cumulative impacts of more extreme conditions may also impact herbivore feeding behavior. Overall, the results of this dissertation demonstrate that herbivory can play a significant role influencing the persistence of giant kelp, and that under the threat of climate change, these species interactions will be significantly weakened, which has implications for kelp forest ecosystems and the transfer of primary productivity through these diverse food webs. This dissertation provides critical information on the ecology and persistence of giant kelp forests and gives us a greater understanding of climate change impacts on marine communities.

Keywords: Biology.
Advisor: Micheli Fiorenza 
Barry James
Crowder Larry B.
Dirzo Rodolfo
Root causes of lead exposure in rural Bangladesh

Pre-natal and early childhood lead exposure to irreversibly lowers IQ. In low- and middle- income countries, the associated losses in lifetime productivity from lead exposure are estimated at nearly 1 trillion dollars. In non-industrial rural populations in Bangladesh, several studies have found unexpectedly high blood lead levels despite a lack of apparent lead sources. My dissertation contributes to understanding how rural residents are exposed to lead and what can be done to prevent future exposure. Specifically, in Chapters 1 and 2, I use epidemiologic population-based methods, combined with environmental sampling and isotopic analyses, to ask i) what is the prevalence of elevated blood lead levels in pregnant women living in three rural districts? and ii) what are the sources of lead? My results indicate that 31% of women have elevated blood lead levels. Although I find several sources of lead, my isotopic analyses indicate that turmeric adulterated with a lead chromate-based pigment contributes most to human exposure. In Chapter 3, I aim to understand the incentive structure that perpetuates the use of lead in turmeric processing. My results highlight the influence of production, consumption, and regulatory factors that incentivize the use of lead chromate-based yellow pigments to make turmeric more colorful and attractive to customers. Ultimately, I provide recommendations for incentive-compatible solutions to reduce lead exposure from turmeric.

Advisor: Ardoin Nicole M. (Nicole Michele) 
Luby Stephen
Fendorf Scott 
Winch Peter
Rural labor market frictions in developing countries

This dissertation explores several issues affecting the labor supply decisions of individuals living in rural parts of developing countries. In the following three chapters, I investigate 1) information failures that suppress rural-urban migration, 2) labor rationing in agricultural markets, and 3) interactions in the rural-urban migration decisions across sibling cohorts. The first chapter is titled "Hidden Income and the Perceived Returns to Migration: Experimental Evidence from Kenya." I use two randomized controlled trials and collect new data linking migrants to sending households to show that rural households substantially underestimate urban incomes, and that this holds migrants back from migrating to a big city. The second chapter is titled "When Time is Not Money, Cash is Priceless." We find evidence of credit constraints and labor rationing, and offer and test a methodology for researchers to measure the shadow wage in agricultural labor markets. The third chapter is titled "Intrahousehold Spillovers in the Migration Decision: Evidence from Thailand's Regional Cities Program." I use an instrumental variables approach combined with historical information about a federal government infrastructure development program in Thailand to identify a migration spillover effect across sibling cohorts. I show that results are consistent with a model in which villagers learn about the returns to migration from migrant siblings.

Keywords: Economics.
Advisor: Dupas Pascaline 
Abramitzky Ran 
Chandrasekhar Arun G. 
Morten Melanie
Sanctified commodities : the Buddhist paintings of Wu Bin (c. 1540-1626) and the late Ming Buddhist revival

My dissertation intervenes in the current approaches to China's late Ming (c. 1572--1644) Buddhist revival by analyzing the paintings of the elite gentleman and devout lay Buddhist, Wu Bin (c. 1540--1626). As a lower-elite individual who maintained the aura of painting for leisure yet made his living with his brush, Wu Bin's life and works offer a new perspective on the late Ming Buddhist revival, outside of the current focus on official examination elites, famous monks, and the imperial family. In tracing the sociocultural environments, artistic choices, and reception of Wu Bin's Buddhist paintings, I first identify the Buddhist network of support that developed around significant temples in China, revealing an undiscovered motivation for the sixteenth-century rise in figure painting. I analyze Wu Bin's responses to this alternate form of support, investigating his donation of a set of 500 Luohans paintings to Nanjing's Qixia Temple and his self-fashioning of a deeply devout Buddhist persona. Then, turning to his key works, my research uncovers Wu Bin's engagement with broader late Ming discourse around the problematic nature of Buddhist visual representation. Wu Bin's paintings expose his responses to contemporaneous debates surrounding the incursion of images into traditionally textual spaces and the potential pitfalls of colorful images enticing the viewer away from a deeper understanding of Buddhist philosophy. Within the context of the sixteenth and seventeenth-century publishing boom, which helped create an audience steeped in Buddhist visual and doctrinal material, Wu Bin formulated engaging, efficacious images that embodied religious concepts as well as economic concerns. By realigning Wu Bin, an artist currently associated predominantly with landscape painting, into the contemporaneous understanding of him as primarily a Buddhist painter, my dissertation brings religious and art-historical methodological frameworks into dialogue, establishing a previously overlooked source for reconstructing the complex role of Buddhist painting and lived religion across wide cultural and social strata in early modern China.

Keywords: Art and Art History.
Advisor: Vinograd Richard Ellis 
Harrison Paul M. (Paul Maxwell)
Kieschnick John
Kwon Marci
A scalable and interoperable cyberinfrastructure platform for civil infrastructure monitoring

Civil infrastructure monitoring is an important technology that provides accurate and objective data on the health condition of a structure by leveraging sensor technologies. Together with routine maintenance and inspection, civil infrastructure monitoring enables the diagnosis of potential structural problems and the prognosis for the need of structural strengthening and repairs. As sensor technologies mature and become economically affordable, their deployment for civil infrastructure monitoring will continue to grow to collect more detailed data about the structures. The data collected from civil infrastructure monitoring systems offers promising opportunities to find meaningful information, knowledge and insight that can improve decision making processes. Furthermore, advances in sensing and communication technologies will eventually realize the concept of cyber-physical systems (CPS) that tightly integrate physical systems and cyber systems to monitor, analyze, coordinate and control the operations of physical systems. Nevertheless, the increasing use of sensors will also lead to significant data management issues. Civil infrastructure monitoring systems instrumented with dense sensor networks will be inundated with unprecedented volume and diverse types of data that need to be processed, interpreted and brought forth to support system operations. The utilization of such "big data" will be significantly limited unless a proper data management platform, which can efficiently store, manage, retrieve, share, interface, link and integrate data, is developed. This thesis describes a cyberinfrastructure platform for civil infrastructure monitoring with an emphasis on system scalability and interoperability. The cyberinfrastructure platform brings together information and communication technologies (ICT), including information modeling, NoSQL database, cloud computing and web services, for effective data management. An information modeling framework with application to bridge monitoring is designed to facilitate data interoperability and data integration. A NoSQL-based data management system is developed to enable scalable, flexible and fault-tolerant management of monitoring data. Cloud computing is adopted as a scalable, reliable and accessible computing infrastructure. Platform-neutral web services are developed to enable easy access to the cloud resources and data involved in engineering systems via standard communication protocols. For demonstration, the cyberinfrastructure platform is implemented for the monitoring of bridges along the I-275 corridor in the State of Michigan. The results show that the cyberinfrastructure platform can effectively manage the sensor data and domain-specific information and facilitate data sharing, integration and utilization.

Advisor: Law K. H. (Kincho H.) 
Kiremidjian Anne S. (Anne Setian) 
Lynch Jerome P. (Jerome Peter)
Scalar fields in cosmology

The QCD axion and Higgs boson are widely-studied scalar fields with interesting cosmological behavior. We demonstrate that the QCD axion can be a natural dark matter candidate, without tuning or additional new physics, over a much wider range of masses than previously assumed. We also show that, in the presence of certain higher-dimensional operators, the Higgs boson can act as an inflaton without violating unitarity during preheating.

Keywords: Physics.
Advisor: Graham Peter (Peter Wickelgren) 
Dimopoulos Savas
Kachru Shamit
SCALING CHOICE MODELS TO RELATIONAL SOCIAL NETWORK DATA THROUGH SAMPLING OF ALTERNATIVES

Many prediction problems on social networks, including anomaly detection and recommendations,
can be framed as modeling a sequence of relational events, and leveraging that model for prediction.
Discrete choice models have recently been advanced as a natural approach to modeling relational
events as “choices”, a framework that envelops and extends many long-studied models of network
formation. However, choices in social networks typically tend to concentrate in an individual’s social
neighborhood, which often is a small subset of the network. Meanwhile, efficient inference for choice
models becomes very difficult when features are rare within the population (if encoding “is a friend
of a friend” as a feature) or when using mixture models (which can restrict one or more modes of
the mixture to friends or friends-of-friends).
In this work, we identify two avenues for scaling choice models to overcome these challenges. Pri-
marily, we study the use of importance sampling—a standard technique for approximate inference—
and find it can greatly speed up the inference of conditional logit models of network choice. Addi-
tionally, we introduce a model simplification technique for mixture models that we call “de-mixing”,
whereby standard mixture models of network formation are reformulated to operate their modes over
disjoint choice sets. This reformulation reduces mixed logit models to conditional logit models, cir-
cumventing standard challenges with maximizing the likelihoods of mixture models and opening the
door to straight-forward importance sampling. We illustrate the relative gains of the two improve-
ments on synthetic datasets with known ground truth behavior as well as on a large-scale dataset
of public transactions on the Venmo platform. We find that non-uniform importance sampling is
especially effective for rare features that commonly drive network formation. Model de-mixing,
meanwhile, makes it possible to efficiently estimate conditional logit models that reliably approxi-
mate otherwise challenging mixture models.

Keywords: Ugander, Johan
Symbolic Systems
Management Science and Engineering
Stanford University
Thesis
Scaling decision analysis

The problem that motivates this dissertation is why some decision problems have automated support tools, while others remain manual. Economic theory suggests that for any good or service where demand increases, an entrepreneur will appear to help fill the gap between supply and demand. The framework of decision analysis has shown a normative approach to the decision-making process, and since its inception, many have tried to explain the technical requirements needed to achieve intelligent decision systems or automated decision support. But the market has thus far failed to leverage this body of knowledge to create automated decision support business at scale. This dissertation presents an analytic framework for the creation of automated decision businesses and allows entrepreneurs who wish to enter this market to have a quantitative approach to understand which barriers have the most significant effect on the lag of automated decision support. This theory provides us with the ability to measure the impact of implementing new ideas and how future research could affect those barriers for any particular decision problem. One of the main barriers to automation is the need for personalization that is common in most decision problems. This barrier stems from the difficulty of eliciting preferences from decision-makers and encoding the elicitation process in a way that lends itself to automation. This dissertation provides a mathematical approach to preference elicitation (Preference Thresholds) that significantly improves the ability of decision-makers to interact with automated decision systems as well as reducing the implementation costs of automation, and lowering the cognitive burden on untrained decision-makers. Preference Thresholds allow for the piecewise discretization of continuous value functions around points of interest (preference) to each decision-maker. PTs also represent a way to reduce the size of uncertainties around preferences and to frame problems to eliminate alternatives that do not fit in with the decision maker's values.\ Another critical barrier to automation is the difficulty of implementing these models at scale. This dissertation provides an example of how broad model templates can be used to reduce the difficulty by providing willing entrepreneurs with a starting point for a particular type of decision. In the application chapter, this dissertation introduces a broad model template for patient-centric medical decision making and proposes a way to customize that template to many conditions as well as a way to automate the customization process. The template, together with preference thresholds (PT), is used to create, develop, and deploy an automated decision support tool to aid with the treatment selection decision of prostate cancer patients. The tool is implemented at Stanford Cancer Center for patients with clinically localized prostate cancer who come for a consult with a radiation oncologist.

Keywords: Management Science and Engineering.
Advisor: Howard Ronald A. (Ronald Arthur)
Scheinker David 
Shachter Ross D.
Scaling up collective decision making

While the Internet has revolutionized many human endeavors, commerce, education, social networking, to name a few, it has had little impact on collective decision making. This thesis presents the author's work on understanding how to enable large scale collective decision making, from various angles such as: deploying novel mechanisms in practice, and studying them empirically; analyzing preference aggregation algorithms (social choice rules) with respect to provable optimization guarantees, e.g., of fairness; designing theoretical mechanisms of decision making with strategic interaction among agents. The three parts of this thesis are described below. Knapsack Voting for Participatory Budgeting: This part looks at the phenomenon of Participatory Budgeting, and discusses the author's work in overcoming the challenges faced in building a practical voting platform (https://pbstanford.org/) for the same - in particular, the novel Knapsack Voting method, and theoretical and empirical insights as to how it performs better than conventional methods. Metric Distortion and Fairness: Given the promise of algorithmic mechanisms in transforming societal decision making, a theoretical study of their efficiency and fairness becomes imperative. This section of the thesis discusses the usefulness of the metric distortion model in answering such questions. A novel method of quantifying fairness, using ideas from multi-objective optimization, is also presented. In addition to answering several open questions pertaining to metric distortion, it is shown how the simple Copeland rule achieves a constant-factor fairness ratio. Implementing the Lexicographic Maxmin Bargaining Solution: To broaden the scope of decision-making mechanisms to more complex settings, there is a need for protocols that incorporate the interaction of agents into their functioning. To this end, studying bargaining models is the natural first step. This section discusses the author's work on designing bargaining mechanisms which can guarantee (lexicographic) max-min fairness in equilibrium.

Keywords: Electrical Engineering.
Advisor: Goel Ashish 
Pilanci Mert 
Wootters Mary
School-wide practices of equity : a case study of a charter high school

This dissertation investigates school-wide practices of equity observed at a Latino-run charter high school in Northern California, NorCal High. Through a variety of qualitative and ethnographic field methods, I document the ways in which educators and administrators address issues of social inequality throughout the school in a community that is challenged by social, linguistic, political, historical, and economic structures that perpetuate inequitable educational outcomes. I offer recommendations for future research on equity and charter schools and add a number of research questions that can help researchers and educators understand larger unanswered questions about equity and schools in the U.S.

Keywords: Education.
Advisor: Valdés Guadalupe 
McDermott Ray (Raymond Patrick)
Rosa Jonathan
"Scientific" practices of truth : the culture of criminal detection in modern China (1890-1949)

This dissertation offers a cultural study of the epistemology of criminal investigation in Republican China. Chinese detective fiction and the practices of criminal investigation during the Republican period were conventionally considered as espousing the Western epistemology of modern science and promoted the objective methods to produce the truth of a crime. However, the idea of science in these discussions was often taken for granted as if it is a self-evident concept. This dissertation explores how the "scientific methods of crime detection" were conceptualized and represented in both fictional and actual cases during the Republican period. Through a close reading of various genres including the Chinese detective stories, news coverages on real crimes, and the textbooks for police and espionage training, I argue that under the rubric of "science, " the methods of crime detection deployed in both fictional and actual cases were also formed by romantic fantasies of science, the common sense of social norms and rules, and judgments on moral character that was rooted in imperial Chinese legal culture. By revealing how popular literature shaped and was shaped by actual practice in crime detection, this dissertation demonstrates how a capillary mechanism of power was exercised by a civic agent of justice beyond the state apparatus during the Republican period. In this way, this interdisciplinary study sheds light on the shifting paradigms of crime control that complicates the relationship between aesthetics, knowledge, and power in modern China

Keywords: East Asian Languages and Cultures.
Advisor: Wang Ban
Egan Ronald
Lee Haiyan
Ma Jean
Scientists, healers and bioprospectors : the epistemological politics of traditional medicine in Ethiopia, 1930-1998

This dissertation examines local efforts to study, develop and regulate traditional medicine in Ethiopia from 1940-1998. This period (1940-1998) marks the formation of traditional medicine as an object of scientific inquiry and a legal creation—a category of knowledge defined and regulated by the state. The author argues that in Ethiopia, therapeutic pluralism is a longstanding feature of the therapeutic landscape and not simply a consequence of the introduction of biomedicine. Legislative and scientific initiatives that coalesced around traditional medicine were often in tension with the pluralistic and complex intellectual history of Ethiopian therapeutic practice. Public health officials and scientists who sought to codify, categorize and distinguish between "good" and "bad" therapeutic practice were part of a larger effort to shape Ethiopia into a "modern" nation-state. Ethiopian medicinal plant researchers were also part of a global story about the growing scientific interest in medicinal plants on the part of bioprospectors and conservationists. The author combines the use of oral interviews and ethnographic observation with an analysis of archival material in Amharic to situate Ethiopia in both its local and global contexts and understand why traditional medicine became a national priority when it did.

Keywords: History.
Advisor: Roberts Richard L.
Getz Trevor R.
Hecht Gabrielle