VictorJuiz/thesis huggingface dataset:
The effects of government policies on individual education, labor market and health outcomes

I examine the impacts of a state government policy in California, and two national South African government policies on individual outcomes. In Chapter 2 we find evidence that California's Paid Family Leave (PFL) program improved child health outcomes in kindergarten with the greatest improvements experienced among children from less advantaged backgrounds. Chapter 3 demonstrates that the additional income from the South African means-tested unconditional cash transfer program, the child support grant, increases enrollment among all female children and decreases work inside the home for older female adolescents. Lastly, in Chapter 4 I find that the South African need-based college loan program, NSFAS, significantly increased the probability of graduation, and reduced the time taken to complete the qualification among those who graduate. These findings suggest an important role for government intervention in reducing inequality and increasing intergenerational mobility.

Keywords: Economics.
Advisor: Hoxby Caroline Minter 
Abramitzky Ran 
Duggan Mark G. (Mark Gregory)
Effects of Land Use and Land Cover Change (LULC) and Climate Change on Mosquito-Borne Disease Transmission in Colombia: An Integrated Spatiotemporal Approach

Human modification of the natural environment continues to create conditions under which mosquito-borne diseases thrive. In this project, I identify associations between environmental change and the Zika epidemic in Colombia in 2016. Colombia had the second highest number of Zika cases in the Americas after Brazil, totaling over 100,000 suspected and confirmed cases. Zika is an arboviral disease transmitted by Aedes mosquitoes. Previous work has shown that transmission of Zika depends on elevation, forest cover, urban cover, temperature, and precipitation. However, the impacts of changes in these factors, rather than their current states, have yet to be studied. I used spatiotemporal remote sensing imagery to measure the changes in forest cover, urbanization, temperature, and precipitation in Colombia and built a regression model to assess their relationship with the presence and incidence of Zika transmission. For comparison, I also observed the impacts of these variables on other mosquito-borne diseases in Colombia, including dengue and chikungunya (also transmitted by Aedes mosquitoes) and malaria (transmitted by Anopheles mosquitoes). Forest loss was positively associated with the presence of Aedes-borne diseases, whereas forest gain was negatively associated with the incidence of Aedes-borne diseases. In some cases, the environmental drivers' states across space and rates of change across time showed opposite effects on disease
presence, which highlights the importance of assessing environmental drivers spatiotemporally. As highly detailed datasets on environmental change become more accessible, more eco-epidemiological analyses like this project can help to clarify the impacts of environmental change on human health.

Keywords: MacDonald, Andy
Earth Systems
School of Earth
Energy &amp; Environmental Sciences
Thesis
Effects of Latency and Refresh Rate on Force Perception via Sensory Substitution by Force-Controlled Skin Deformation Feedback

Latency and refresh rate are known to adversely affect human force perception in bilateral teleoperators and virtual environments using kinesthetic force feedback, motivating the use of sensory substitution of force. The purpose of this study is to quantify the effects of latency and refresh rate on force perception using sensory substitution by skin deformation feedback. A force-controlled skin deformation feedback device was attached to a 3-degree-of-freedom kinesthetic force feedback device used for position tracking and gravity support. A human participant study was conducted to determine the effects of latency and refresh rate on perceived stiffness and damping with skin deformation feedback. Participants compared two virtual objects: a comparison object with stiffness or damping that could be tuned by the participant, and a reference object with either added latency or reduced refresh rate. Participants modified the stiffness or damping of the tunable object until it resembled the stiffness or damping of the reference object. We found that added latency and reduced refresh rate both increased perceived stiffness but had no effect on perceived damping. Specifically, participants felt significantly different stiffness when the latency exceeded 300 ms and the refresh rate dropped below 16.6 Hz. The impact of latency and refresh rate on force perception via skin deformation feedback was significantly less than what has been previously shown for kinesthetic force feedback.

Keywords:  Department of Mechanical Engineering
Stanford University Department of Mechanical Engineering CHARM Lab
Haptics and Interfaces
Thesis
Advisor: Okamura Allison Mariko
Kamikawa Yasuhisa
The effects of upwelling-driven hypoxia on sea urchins in California current kelp forests

Global climate change is increasingly exposing marine organisms, communities, and ecosystems to a variety of physiologically stressful conditions. Understanding how organisms respond to realistic exposures to physiological stressors, and how these responses may scale up to population- and ecosystem-level impacts, is crucial to understanding and predicting the impacts of climate change. Most earlier experimental approaches to this problem have focused on assessing organism responses to constant levels of a single physiological stressor, but physiological stresses on marine organisms often occur at sublethal levels, with temporally variable exposure patterns, and in combination with other stressors. In this dissertation, I use sea urchins in California Current kelp forests as a model system to address questions about the roles of sublethal exposures, temporal exposure patterns, and multiple-stressor interactions in shaping organisms' and ecosystems' responses to upwelling-driven coastal hypoxia. By using a decade-long dataset of nearshore dissolved oxygen conditions from the Monterey Bay kelp forest as a basis for designing and interpreting laboratory experiments, I find that coastal hypoxia is most likely to impact kelp forest ecosystems via sublethal effects on the ecological roles of sea urchins, that longer-term patterns of exposure to sublethal hypoxia have potential impacts on sea urchin populations and kelp forest ecosystems, and that realistic combinations of multiple stressors produce interactive and unexpected responses in sea urchins. Taken together, the results of this dissertation suggest that sublethal exposures, temporal exposure patterns, and multiple-stressor interactions all modulate individual sea urchin responses to upwelling-driven hypoxia, with potential consequences for populations and ecosystems. More broadly, the results indicate that climate change experiments need to take these different aspects of realistic stressor exposure into account, in order to produce useful and informative results. To that end, the fourth chapter of this dissertation describes a low-cost, versatile experimental control system that other researchers and students can use to implement realistic, temporally variable experimental exposures to multiple stressors. Therefore, this dissertation contributes to both the conceptual and technical advancement of experimental climate change research in marine systems.

Keywords: Biology.
Advisor: Micheli Fiorenza 
De Leo Giulio A. 
Palumbi Stephen R.
Somero George
Efficient second-order methods for machine learning

Due to the large-scale nature of many modern machine learning applications, including but not limited to deep learning problems, people have been focusing on studying and developing efficient optimization algorithms. Most of these are first-order methods which use only gradient information. The conventional wisdom in the machine learning community is that second-order methods that use Hessian information are inappropriate to use since they can not be efficient. In this thesis, we consider second-order optimization methods: we develop new sub-sampled Newton-type algorithms for both convex and non-convex optimization problems; we prove that they are efficient and scalable; and we provide a detailed empirical evaluation of their scalability as well as usefulness. In the convex setting, we present a subsampled Newton-type algorithm (SSN) that exploits non-uniform subsampling Hessians as well as inexact updates to reduce the computational complexity. Theoretically we show that our algorithms achieve a linear-quadratic convergence rate and empirically we demonstrate the efficiency of our methods on several real datasets. In addition, we extend our methods into a distributed setting and propose a distributed Newton-type method, Globally Improved Approximate NewTon method (GIANT). Theoretically we show that GIANT is highly communication efficient comparing with existing distributed optimization algorithms. Empirically we demonstrate the scalability and efficiency of GIANT in Spark. In the non-convex setting, we consider two classic non-convex Newton-type methods --- Trust Region method (TR) and Cubic Regularization method (CR). We relax the Hessian approximation condition that has been assumed in the existing works of using inexact Hessian for those algorithms. Under the relaxed Hessian approximation condition, we show that worst-case iteration complexities to converge an approximate second-order stationary point are retained for both methods. Using the similar idea of SSN, we present the sub-sampled TR and CR methods along with the sampling complexities to achieve the Hessian approximation condition. To understand the empirical performances of those methods, we conduct an extensive empirical study on some non-convex machine learning problems and showcase the efficiency and robustness of these Newton-type methods under various settings.

Advisor: Ré Christopher 
Mahoney Michael 
Ying Lexing
Efficient sequential reliability-based design optimization with adaptive kriging inverse reliability analysis

In this thesis, new methods for reliability-based design optimization (RBDO) are presented. The Adaptive Kriging Inverse Reliability Analysis (AKIRA) algorithm and a multifidelity sequential RBDO algorithm are introduced and demonstrated on a complex multidisciplinary supersonic nozzle design problem. AKIRA demonstrates competitive performance with other reliability analysis algorithms while also benefiting from the solution of the inverse reliability analysis problem during RBDO. The proposed sequential RBDO algorithm mitigates the cost of solving the RBDO problem by decoupling the optimization and reliability analyses, thereby reducing its solution to a series of deterministic optimizations. The method is motivated by anchored decomposition, has guaranteed convergence inherited from trust region methods, and is shown in certain cases to be a generalization of existing sequential RBDO methods. It also derives enhanced efficiency by incorporating lower-fidelity models when available. The final demonstration of the proposed algorithms on an industrial-type problem, the supersonic nozzle, shows that the solution of RBDO problems for complex realistic engineering applications is well within reach.

Keywords: Aeronautics and Astronautics.
Advisor: Alonso Juan José
Iaccarino Gianluca 
Kochenderfer Mykel J.
Eigenvalues in multivariate random effects models

We study principal component analyses in multivariate random and mixed effects linear models. These models are commonly used in quantitative genetics to decompose the variation of phenotypic traits into consistuent variance components. Applications arising in evolutionary biology require understanding the eigenvalues and eigenvectors of these components in high-dimensional multivariate settings. However, these quantities may be difficult to estimate from limited samples when the number of traits is large. We describe several phenomena concerning sample eigenvalues and eigenvectors of classical MANOVA estimators in the presence of high-dimensional noise, including dispersion of the bulk eigenvalue distribution, bias and aliasing of outlier eigenvalues and eigenvectors, and Tracy-Widom fluctuations at the spectral edges. A common theme is that the spectral properties of the MANOVA estimate for one component may be influenced by the other components. In the setting of a simple spiked covariance model, we introduce alternative estimators for the leading eigenvalues and eigenvectors that correct for this problem in a high-dimensional asymptotic regime.

Keywords: Statistics.
Advisor: Johnstone Iain 
Montanari Andrea 
Candès Emmanuel J. (Emmanuel Jean)
Elucidating the Presence and Purpose of Competence and Progression in Primary Mammalian Cells

Mammalian cells require the presence of growth factors in order to enter the cell cycle and divide. However, constant exposure to growth factors is not always required for cells to divide in tissue culture. In fact, giving cells two short pulses of growth factors eight hours apart is just as effective as giving cells constant growth factors in driving them into the cell cycle. This suggests that there are two time points within the G1 phase of the cell cycle during which growth factor stimulation is required. The first, competence, prepares the cell to respond to the second, progression. Progression causes the cell to continue through the restriction point and into the cell cycle. Whether competence and progression are present in primary human lung fibroblasts remains unclear. To characterize the presence of competence and progression in primary mammalian cells, we released primary human lung fibroblasts from serum starvation and measured cell cycle phase and cell size changes over time. In both constant and pulsed growth factor conditions cell cycle progression and cell growth were similar. Furthermore, we show that there is very little cell growth in the period of G1 between competence and progression. This suggests that providing a cell with a competence factor is not sufficient to induce the cell growth required for G1 exit.

Keywords:  Department of Biology
Biology
cell cycle
competence
progression
cell growth
Thesis
Advisor: Skotheim Jan M.
Lipsick Joseph
Elucidating the roles of retinoic acid and enteric glia in colorectal cancer

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and third leading cause of cancer mortality in the United States, highlighting an urgent need for greater understanding of the mechanisms underpinning CRC development. Here, we find that mice with colitis-associated CRC exhibit a marked decrease in colonic all-trans retinoic acid (atRA) due to alterations in the atRA metabolic enzymes. Patients with ulcerative colitis (UC), UC-associated CRC, and sporadic CRC additionally exhibit similar alterations, consistent with reduced colonic atRA. In mice, inhibition of atRA signaling promoted tumorigenesis, whereas supplementation of atRA reduced tumor burden. This anti-tumor effect was mediated by CD8+ T cells, which were activated as a result of MHC I upregulation on the tumor epithelial cells. Consistent with these findings, increased colonic expression of the atRA catabolizing enzyme, CYP26A1, in CRC patients was found to correlate with reduced frequencies of tumoral cytotoxic CD8+ T cells and with worse disease prognosis. Additionally, we also discovered that enteric glial cells play a critical role in early CRC development. Although the mechanism remains elusive, we demonstrate that the pro-tumorigenic function of the glia does not depend on effects on CD8+ T cells or intestinal inflammation. Altogether, our work here reveals two heretofore undescribed mechanisms of CRC tumor development and identifies potential new targets for prevention and treatment of CRC.

Keywords: Immunology.
Advisor: Engleman Edgar G. 
Butcher Eugene 
Habtezion Aida
Negrin Robert S.
Elucidating the temporal dynamics of human visual cortex [electronic resource]

The world around us is constantly changing and in many more ways than we can see. As visual stimuli bombard us at different rates, some changes occur on timescales that are too fast or slow to detect with the naked eye. However, the human visual system is able to perceive a broad enough range of temporal dynamics to distinguish stable aspects of the environment from rapidly changing ones and operate on them in real time. While this may seem effortless, the neural mechanisms that give rise to this fundamental perceptual ability are largely unknown. In the three experiments described here, we use functional magnetic resonance imaging (fMRI) and computational techniques to model how neurons in the visual system code changes to the appearance of the world over time. First, we examine how the transient and sustained aspects of a stimulus are processed in the visual system focusing on regions in early visual cortex in Study 1 and regions in high-level visual cortex in Study 2. Both studies reveal differential response dynamics between ventral temporal cortex (VTC) and lateral temporal cortex (LTC). That is, we find that brain regions in VTC receive contributions from both sustained and transient channels, whereas regions in LTC are dominated by contributions from the transient channel. In Study 3, we test whether the distinct temporal dynamics observed across domain-specific regions in Study 2 have behavioral consequences. Contrary to prevailing theories, we find that different regions have different processing capacities, which have behavioral implications. Specifically, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. Together, these results suggest that temporal processing capacity is a characteristic of synchronized domain-specific networks in high-level visual cortex and contributes to the segregation of cortical regions.

Keywords: Psychology.
Advisor: Grill-Spector Kalanit primary advisor. Thesis advisor
Gardner Justin
Norcia Anthony Matthew
Emigration and the industrial revolution in German Europe, 1820-1900

Starting around 1850, the economically backward region of German central Europe embarked on a period of rapid economic growth that would soon transform it into a global economic powerhouse. Looking beyond the standard list of explanatory factors and conditions for industrialization (including proximity to Britain or German technological ingenuity), this dissertation offers a historically contingent interpretation by situating the region in its Atlantic World context. Between 1820 and 1900, some five million German speakers emigrated to North America. The study argues that this movement helped to catalyze development back in Europe because it exposed large, otherwise isolated segments of the population to an unfamiliar world of economic behaviors, mores, ideas, and institutions. Six chapters explore how this exposure mobilized the rural, working population for a centralized, industrial production regime; how it sparked the creation of new financial institutions like 'universal banks, ' often described as key during later stages of development; and how subtle changes in economic morality forced the introduction of innovative commercial laws upon which subsequent iterations of German industrialization would built.

Keywords: History.
Advisor: Sheffer Edith 
Daughton J. P. (James Patrick) 
Naimark Norman M. 
Satia Priya 
White Richard
Emotion and emotion regulation in groups

People tend to respond emotionally to events that are related to their groups, even if these events do not have any direct effect on their lives. However, even as group members experience such group-based emotions, they are not necessarily passive. They frequently regulate not only their own emotions but those of others as well. In so doing, group members use these emotions as tools to influence their environment. The overarching goal of this dissertation was to examine emotion and emotion regulation in group contexts. Four inter-related projects were conducted. The first project provides a theoretical framework for identifying unique aspects in the unfolding and regulation of emotions in groups. The second and third projects empirically address current gaps in the literature. More specifically, the second project examines how people aggregate and summarize emotional expressions of multiple people, and how they categorize these emotional responses as generated by ingroup or outgroup members. The third project examines how group members are influenced by the emotions of their ingroup and assesses whether motivational forces may assist individuals in resisting or enhancing such influence. Finally, the fourth project introduces an emotion regulation intervention designed to increase group members' hope regarding the possibility of group change in the context of intergroup conflicts. Taken together, these four projects provide new theory, empirical findings, and an intervention related to emotions in groups. The dissertation concludes with a discussion of future research directions.

Keywords: Psychology.
Advisor: Gross James J.
Dweck Carol S.
Zaki Jamil
Emotional diversity in organizational settings : how culture and ideal affect shape employment and leadership outcomes

What is the role of culture and emotion in organizational settings? The present dissertation addresses this question in three sets of studies. Using cross-cultural methods and sampling from participants in the United States (European Americans and Asian Americans) and East Asia (Hong Kong Chinese), we examine how emotions influence behaviors and outcomes from the lowest levels of organizations (i.e., self-presentation and hiring decisions for entry-level positions) to the highest levels of organizations (i.e., leadership choice). Part 1 examines whether culture and ideal affect (i.e., the emotions that we value and ideally want to feel) shape how participants present themselves in an employment setting. Next, Part 2 investigates whether culture and ideal affect shape hiring decisions. Finally, Part 3 examines how these processes shape whom we choose as leaders of organizations that vary in performance (i.e., growth, stability, and crisis) and across different occupational sectors (i.e., business, government, research). Across 8 studies, we show that European Americans and Asian Americans want to and actually do present themselves as excited and enthusiastic on job applications, hire excited job candidates, and choose excited leaders more than do Hong Kong Chinese, in part because they value excitement states more. In contrast, Hong Kong Chinese want to and actually do present themselves as calm on job applications, hire calm job candidates, and choose calm leaders more than do European Americans and Asian Americans. Together, these findings have implications for how emotions shape individual and group outcomes in organizational settings. In addition, by focusing on the under-investigated area of cultural differences in emotions, we suggest a promising area for interventions aimed to increase diversity and inclusiveness in organizational settings.

Keywords: Psychology.
Advisor: Tsai Jeanne Ling 
Markus Hazel Rose 
Zaki Jamil