VictorJuiz/thesis huggingface dataset:
Closing the Data Gap: Case Studies on Gender Biases in Global Health Surveys
Keywords: center on democracy development and the rule of law
global health
gender equality
demographic and health survey
world value survey
gallup world poll
Thesis

Global surveys are critical to conducting global health research on a variety of topics, which are directly responsible for shaping national health policies and informing monitoring and evaluation programs internationally. In recent years, various organizations including the United Nations and Gates Foundation have called attention to gender gaps in knowledge for key public health data. Although, we now have a strong understanding of where gender data is completely missing, we have a ways to go to understand how existing data may hold gender biases. In this thesis we assess how questionnaire formation can carry gender biases that may impact data collected and in turn future analyses. First, we studied gender-nonspecific questionnaires to understand the forms of gender bias and domains of interest targeted. Second, we studied the evolution of a gender-specific questionnaire over time to track changes in the focus of men’s and women’s versions of the survey. We utilized the results from both case studies to develop a series of general guidelines for future questionnaire design to minimize the amount of gender bias.
Closing the Floodgates: The Origins of U.S. Immigration Policy Towards Latin America in the 1965 Hart-Celler Act
Keywords:  Program in International Relations
immigration
Hart-Celler Act
Latin America
History
Stanford University Program in International Relations Thesis
Thesis

In the 1965 Hart-Celler Act, the US Congress placed a cap on immigration from the Western Hemisphere for the first time. Previously, the number of Latin American immigrants who entered per year was not restricted by a quota. Why did Congress enact this policy at this time?
Previous scholars have dismissed it as a hazy compromise behind closed doors that the Johnson Administration made in order to pass this landmark piece of legislation. Yet given that this policy is one of the founding blocks of our immigration policy toward Latin America today, it is important to study it further: what exactly drove members of Congress to curb immigration from Latin America? My thesis contributes a new statistical analysis on the breakdown of the Western Hemisphere vote in the House and in the Senate. I then apply my statistical findings to a historical analysis in order to provide a more comprehensive narrative on the inclusion of this provision.
In my regression analysis, I find that the economic ideology of congress members and the number of Mexican immigrants in their district were the most predictive variables. This is interesting given that most of the literature on the Hart-Celler Act ignores the economic debate and focuses on the issue of race. Therefore, in my historical analysis, I highlight the economic debate over immigration from Latin America with quotes from the House and Senate floor.
This paper contributes to the current literature on the Hart-Celler Act by creating a more robust picture of the Western Hemisphere amendment: the economic debate was more determinative than previously thought. Arriving to a more complete understanding of the roots of our immigration policies toward Latin America is especially important today, at a time when the debate over immigration from the region is front and center in our national politics.
CMOS image sensor design for always-on object detection
Keywords: Electrical Engineering.

Object detection is an important vision task in embedded systems like smartphones, real-time monitoring devices, and augmented reality. A standard approach is to embed a CMOS image sensor with a backend detection algorithm. Deep neural networks (DNNs) are currently the best-performing algorithms for such applications and there has been extensive work on improving the efficiency of algorithms and hardware. Despite these efforts, customized DNN ASICs are relatively energy-hungry due their large computational footprint. Therefore, to achieve efficient object detection in an embedded device, it is attractive to consider less complex, prior-art algorithms that use low-complexity hand-crafted features as a wakeup for a more powerful DNN. For instance, histograms of oriented gradients (HOGs) present a good tradeoff between computational requirements and detection accuracy. To optimize the wakeup detector for always-on functionality, we can build the feature-extraction directly into the CMOS image sensor. Towards this end, this dissertation presents an application-optimized QVGA image sensor for low-power, always-on object detection using HOGs. In contrast to conventional CMOS imagers that feature linear and high-resolution ADCs, this readout scheme extracts logarithmic intensity gradients at 1.5 or 2.75 bits of resolution. This eliminates unnecessary illumination-related data and allows the HOG feature descriptors to be compressed by up to 25x relative to a conventional 8-bit readout. As a result, the digital backend detector, which typically limits system efficiency, incurs less data movement and computation, leading to an estimated 3.3x energy reduction. The imager employs a column-parallel readout with analog cyclic-row buffers that also perform arbitrary-sized pixel-binning for multi-scale object detection. The log-digitization of pixel gradients is realized by using a ratio-to-digital converter, which performs successive capacitive divisions to its input voltages. The prototype IC was fabricated in a 0.13 um CIS process with standard 4-T, 5 um pixels and consumes 99 pJ/pixel. The power consumption is comparable to conventional low-power designs showing there is little energy overhead in the novel readout. Experiments using a deformable parts model detector for three object classes (persons, bicycles and cars) indicate detection accuracies that are on par with conventional systems.
Coastal Ocean Microclimates: Temperature Dynamics in Nearshore Kelp Forests of Isla Natividad, Baja California, Mexico
Keywords:  Earth Systems Program
School of Earth Energy and Environmental Sciences
Earth Systems Program
coastal oceanography
marine refuges
Thesis

Kelp forests are resource-rich coastal ecosystems that provide livelihoods to coastal communities. Climate change is negatively impacting these ecosystems through heat waves, acidification and hypoxia. Nearshore transport and mixing, combined with coastline morphology, can result in refuges from these stressors in kelp forests. Such refuges have been identified in Isla Natividad, B. C., Mexico but their characterization is still in progress. This study focuses on 4 locations transected with a linear configuration of 3 moorings perpendicular to the coast, with 3-7 temperature sensors cabled to each mooring line. Local oceanographic variability was analyzed using spectral methods on temperature and pressure data, satellite imagery of synoptic events, and linear interpolation of binned current data in the vertical axis. The high spatial resolution of this study shows that tidal frequencies are stronger near the seafloor, although not necessarily attributed to tidal wave forcing, and surface heat forcing is stronger near the surface. Greater distance from the shore reduces the role of kelp in current dampening, where stronger surface currents result in lower coherence between surface and bottom of the water column at moorings further from shore. Frequencies of temperature oscillation drive the residence time of some water masses, affecting the length of exposure of organisms to extreme temperature ranges, and tend to fall in lower frequencies at the west side compared to the east side. However, weather events such as hurricanes can impact both sides of the island and the resilience of existing climate refuges to such events is uncertain. Increased frequency of extreme weather events due to climate change might decrease the effectiveness of climate refuges in coastal ecosystems, reducing survival and resilience of organisms that inhabit them. Understanding the strengths and weaknesses of these coastal microclimates as climate refuges is critical to their consideration and use in marine spatial planning and conservation.
Coding for computation : learning with limited information
Keywords: Electrical Engineering.

The emerging paradigm of ubiquitous low-cost sensors with wireless connectivity and data processing in the cloud promises to be an enabling technology for applications such as smart cities, industrial automation, intelligent energy or traffic management. However, the addition of billions of these low cost sensors can considerably increase wireless network capacity requirements, which are already strained with current demands. In order to minimize communication across a network, we explore the problem of compressing or coding data from distributed sensors for transmission over a noisy communication channel, and study algorithms for performing computation with this partial information. We first look at low-complexity randomized approaches such as sampling or compressive coding of transmissions to reduce the communication requirements of transmissions. In the scenario, where sensors feed measurements from an underlying unknown time-series to a fusion center, communication bottlenecks preclude the collection of all such measurements. To address this challenge we develop algorithms to learn the parameters of the time-series from randomized coding comprised of subsamples or compressed sampling of measurements transmitted by the sensors. We do this by first estimating the covariance of the measurements from the partial information received and using that to estimate the time-series parameters. Non-asymptotic convergence bounds for these algorithms are derived. Moreover, we show that modifications to the algorithm allow for tighter convergence bounds given priors such as low rankness and sparsity. This procedure is applied for the estimation and control of linear dynamical systems. We also consider a decentralized learning paradigm where nodes on a network cooperate to solve a global optimization problem using their local information. Current techniques to solve this problem such as distributed gradient methods assume that nodes can transmit arbitrarily large messages at each time instant. We use randomized compression approaches mentioned earlier to reduce the size of the messages transmitted and adapt these distributed optimization algorithms for networks with limited communication capabilities. We show an inverse relationship between compression and accuracy of the distributed optimization algorithm. The algorithm is also robust to the use of stochastic gradients, noisy communication links, or time varying networks. Finally, we introduce an approach where coding of structured data such as text or audio is done over its learned representations produced by neural-network based autoencoders. For the transmission of text using limited length encoding, we show how this approach retains more of the semantic content of sentences compared to traditional source and channel coding techniques.
Coherent feedback for wavelength transfer of atomic-optical nonlinearity
Keywords: Applied Physics.

Light has for decades proven extremely valuable for high-bandwidth communications over long distances, and is becoming increasingly important at shorter and shorter length scales as demand for bandwidth rises. Much of the enabling optical technology, which includes optical fibers and fiber amplifiers, relies on materials compatible with the telecom band of wavelengths (roughly 1.2-1.6 μm). Additionally, there has been much interest in expanding the reach of optics into switching, logic, and memory, but such applications typically require nonlinear input-output behaviors not easily found in optical systems. The strongest optical nonlinearities in nature are generally resonant (and therefore narrow-band) and don't necessarily fall within the telecom range. A technique to bridge resonant optical nonlinearities to the telecom band would therefore be quite valuable. Such a method would be yet more valuable if it supported tunable signal wavelengths—this would enable transfer of a fixed-wavelength nonlinearity to an array of telecom wavelengths for wavelength division multiplexing (WDM), or allow optical coupling of heterogeneous nonlinearities via a single shared wavelength. In this thesis I'll describe a technique which pairs a below-threshold optical parametric oscillator (OPO) with coherent optical feedback to achieve tunable-wavelength nonlinearity transfer, and present results from a corresponding proof-of-principle implementation which demonstrates the transfer of a sharply resonant atomic-optical nonlinearity.
Compact and Consensus: American Foreign Policy and the Partisan Tide at the Water's Edge
Keywords:  Center for International Security and Cooperation
Center for International Security and Cooperation
Stanford
Honors Program in International Security
Political Science
History
political polarization
U.S. foreign policy
liberal internationalism
bipartisanship
partisanship
World War II
Cold War
Vietnam War
Congress
international institutions
multilateralism
alliances
free trade
foreign aid
military spending
military intervention
substantive polarization
affective polarization
Thesis

Since World War II, it has been conventional to claim that the United States maintains a bipartisan foreign policy based on Vandenberg’s famous maxim that “politics stop at the water’s edge.” However, the extent to which the tradition of bipartisanship in foreign affairs holds true today, amidst rampant political polarization, has become the subject of controversy. This thesis introduces new insights from the growing literature on political polarization to bear on a historical analysis of American foreign policy-making, considering the separate impacts of both substantive, ideological polarization and affective, social polarization. In doing so, this thesis makes the case that scholars should pay attention not only to the substantive ideological consensus that developed between both major political parties in the wake of World War II, due to the external pressure of the Cold War, but also recognize the importance of the affective political compact consummated between them that enabled their cooperation in the foreign-policymaking process. Tracing the history of both compact (cooperation) and consensus (agreement) in American foreign policy from their origins through today, this thesis argues that bipartisan compact collapsed as a result of a breakdown in the collaborative process during the Vietnam War, while bipartisan consensus continued to last through the end of the Cold War, after which it gradually eroded in the absence of a clear and significant external threat to compel agreement. As such, American foreign policy has experienced both substantive and affective polarization, resulting in a present period of neither compact nor consensus.
Comparative analysis of ABA-mediated stress regulatory networks across the Brassicaceae
Keywords: Biology.

Plants are exposed to a wide range of abiotic stresses in the environment including drought, freezing, and soil salinity. Over evolutionary time, plants have acquired adaptive strategies to survive these stressors. A common type of stress-tolerant plant is a halophyte, which lives along ocean shorelines or near hypersaline lakes. Currently, the gene regulatory networks that underlie a halophyte's adaptation to stress are unknown. Studies in stress-sensitive plants like domesticated crops and Arabidopsis have identified the plant hormone ABA (abscisic acid) as a major regulator of several plant stress responses. Upon the onset of stress, transcription factors downstream of ABA signaling, known as ABRE binding factors (ABFs), activate stress-response genes by binding to cis-regulatory elements known as ABA response elements (ABREs). While components of the ABA-mediated gene-regulatory network have been established in stress-sensitive plants, the regulatory map in the halophytes may have a distinct architecture that underlies adaptive traits. Using root growth assays, I found that halophytes are less sensitive to the growth inhibitory effects of ABA than glycophytes. To identify molecular level differences that mediate growth regulation under stress, I used RNA-Seq and DNA affinity purification (DAP-Seq) and found that halophytes differ in the spatial and temporal expression of genes upon ABA treatment. Some of the halophyte specific genes are associated with previously identified stress tolerance pathways in glycophytes, such as those for cell wall modification and for toxin breakdown. The expression pattern differences are partially mediated by changes in the ABF binding landscape, determined using DAP-Seq. These findings suggest a transcriptional rewiring of ABA-mediated gene-regulatory networks in the halophytes that may contribute to their enhanced tolerance to environmental stress.
Comparative Study of Nationalistic Rhetoric in Chinese State Media: U.S.- China Trade War vs Huawei CFO Arrest
Keywords:  Stanford Global Studies
Stanford Global Studies
East Asian Studies
International Relations
Donald Trump
Xi Jinping
Asia
Huawei
US-China Relations
Foreign Policy
Trade War
Tariffs
Media Analysis
Chinese Newspaper
Thesis

This research project would like to address the common state challenges in handling nationalistic sentiments under the context of the U.S.-China trade war. The main topic of interest lies in inspecting whether the government uses its monopoly over the media to sway Chinese popular opinion and hence fuel nationalism in the form of anti-American sentiments. Looking predominately at relevant publications by party-owned media during a selected period of the trade war, the thesis shall decipher key messages communicated to its readership as well as the particular use of tone and language in official discourse. Analysis of domestic media will furthermore encompass both Chinese and English language publications with the purpose of seeing whether there are any major inconsistencies when speaking to separate audiences. Lastly, coverage of the contentious Huawei CFO Meng Wanzhou arrest will be used as a point of comparison against general commentary of the trade war, without which one cannot quantity the intensity of nationalistic discourse.
The key research question becomes: How does the Chinese government seek to portray itself and regulate nationalism under the context of the U.S.-China trade war through its own media outlet and censorship tactics, and did the controversial Huawei incident change CCP strategies in governing public sentiments?
Compliant whole-body control of humanoid robots
Keywords: Mechanical Engineering.

A major obstacle that prevents humanoid robots from accomplishing real world tasks is their inability to physically interact with, and effectively manipulate, the most common objects generally found in human environments. Even tasks that seem simple for a human remain a significant challenge for most robots. Robots generally employ precision to perform a manipulation task. Humans, in contrast, employ compliance through tactile and force feedback to overcome their imprecision, allowing them to resolve uncertainties associated with the task. The lack of compliance and force control has been indeed a major limiting factor in the ability of robots to interact and manipulate in human environments. One of the major objectives of this research is to endow humanoid robots with whole-body compliant motion abilities. With compliance, a robot overcomes position uncertainties by moving in directions that reduce contact forces, which in turn directs it towards its goal. Whole-body framework was designed to allow the robot to compliantly interact with its environment at multiple contact points. The synthesis of compliant tasks is greatly simplified by being independent of postures and constraints, which are automatically integrated in the control hierarchy. This research focuses on the development of (I) sensor-based whole-body compliant motion primitives, (II) contact sensing and contact force control, (III) whole-body multi-contact for extended support, kneeling, crawling, leaning table, and locomotion strategy to improve support in unstructured terrains, (IV) dynamic collision-free motion planning and (V) dynamic collision-free walking path planning.
Computational linguistic models of police-community interaction
Keywords: Linguistics.

In this dissertation, I use footage from body-worn cameras to analyze the language of police-community interactions during routine traffic stops in three studies exploring officers' words and prosody as well as the back-and-forth structure of these interactions. In the first study, I implement pragmatic theories of politeness in a computational model of officer respect, informed by a thin-slicing study of participant ratings of officer utterances. Inspection of the weights learned by the model shows the strongest influence from negative politeness speech acts like apologizing and reassurance. Using this model I find large-scale evidence that officers speak with consistently less respect towards black versus white community members, even after controlling for contextual factors like the race of the officer and the severity of the infraction. In the second study, I show an analogous racial disparity from prosody alone by obtaining human judgments on content-filtered clips of officer speech. Building a model of human judgments from simple prosodic features I find evidence that officer anxiety is foregrounded as participants judge clips with lower F0, lower intensity, and slower speech rate more highly. In the third study, I develop an ontology of dialog acts unique to the traffic stop interaction, and employ these to show that community members are overwhelmingly compliant in these interactions, but that officers respond differently to less-compliant acts (e.g. rejecting fault or deflecting questions) from black and white community members. Such disparities in common, everyday interactions between police and the communities they serve have important implications for procedural justice, the building of police-community trust, and linguistic theories of interaction. This dissertation presents the first systematic linguistic analysis of officer body-worn camera footage, demonstrating that it can be used as a rich source of data rather than merely archival evidence, and paves the way for developing powerful language-based tools for studying and potentially improving police-community relations.
Computational linking models of human selective visual attention
Keywords: Psychology.

To sample the important parts of the visual world observers make saccades, moving the high-resolution and color-sensitive fovea to informative locations. Choosing to make a saccade requires sampling the periphery and identifying potentially important parts of the visual scene. This covert attention, without eye movement, is essential to selecting information in an efficient manner. At an intuitive level covert attention is a focusing on a feature or a location in the visual world and a suppression of other irrelevant features and locations. When operationalized into the laboratory, cueing an observer with covert attention can be shown to result in improved detection, smaller thresholds of discrimination, faster reaction times, and suppression of distractors. These changes are known to be in part the result of small tweaks to the representation of visual stimuli in sensory cortex, but are also the result of context-dependent selection occurring after sensory processing has gone to completion. How attention implements this balance of sensory change and selection is a central problem for the neuroscience of vision.