VictorJuiz/thesis huggingface dataset:
Global Health Diagnostics via Mobile Phone Microscopy: Improving Contrast and Resolution

A lack of access to proper disease screening and diagnostics continues to plague low-resource countries. As a result, diseases that have long been forgotten in affluent areas still cause an enormous, yet preventable burden in areas without adequate medical systems. In those countries, only the centralized healthcare facilities have the luxury of modern diagnostic equipment, along with the expert personnel required to use that equipment. Advances in consumer technologies, particularly the mobile phone, offer the potential to address the lack of access to healthcare in low-resource regions by creating new data collection and interpretation methods. One example with potential to improve disease diagnosis is the mobile phone microscope. By adding lenses to a conventional mobile phone camera, controlling sample illumination and motion, and automatically interpreting images, mobile phone microscopes have been shown to detect the presence of a pathogens and guide treatment decisions./nThis thesis advances the state-of-the-art in mobile phone microscopy by introducing new applications, new contrast modalities, and resolution enhancements. First, I give an overview of the current prototype implementation of darkfield and fluorescence microscopy on a mobile phone microscopy platform developed by the Fletcher Lab, detailing the physical design of the system along with the assumptions and disadvantages associated with that design. I also show results of the microscope's initial on-site imaging of Fusarium at various banana plantations in the Philippines. Next, I introduce a new illumination scheme to overcome key limitations of the current implementation. I show that by using an LCD screen as the light source, it is possible to finely tune the illumination in a way that simultaneously captures uniform brightfield, darkfield, and phase contrast without the need for larger standard microscope optics. Finally, I take advantage of the smartphone's onboard image stabilizer to displace the sample image relative to the camera sensor. I use this displacement to demonstrate a simple dithering algorithm that requires no additional hardware while more than doubling the microscope's resolution. By combining these new methods, mobile phone microscopes of the future have the potential to provide high-quality disease diagnoses at the point-of-care.

Advisor: Fletcher, Daniel A
Kashaev-Reshetikhin Invariants for SL2(C) at Roots of Unity

An important milestone of the theory of knot invariants is the Reshetikhin-Turaev functor introduced in [RT]. This construction could generate tangle invariants from quantum groups. Later, Kashaev and Reshetikhin generalizes this construction [KR1] based on the idea of the holonomy braiding, the braiding defined for C-colored diagrams. The purpose of this work is to have some discussion of this construction. There are three parts in this thesis: first the full description of the construction is provided. Then in the second part, some examples computed via Mathematica are shown. And some properties and theorems are given in the end.

Advisor: Reshetikhin, Nicolai
Judging emotions as good or bad: Individual differences, links with emotional responses, and implications for psychological health

People are not impassive bystanders to their emotional experiences. Instead, people tend to judge their emotions as good or bad. In this research, I examined individual differences in emotion judgments and their implications for emotional responses and psychological health. In Study 1 (N = 1,136), I developed a questionnaire to assess four types of habitual emotion judgments. The four types of emotion judgments differed according to the valence of the emotion being judged (positive or negative) and the valence of the judgment (positive or negative). In Study 2 (81 participants and 2,999 observations), I examined the relationship between habitual emotion judgments and emotion judgments in daily life. Emotion judgments were common in daily life and were predicted by habitual emotion judgments. In Study 3 (same participants as in Study 1), I examined cross-sectional associations between habitual emotion judgments and psychological health. Positive judgments of positive emotions were associated with greater psychological health and negative judgments of negative emotions were associated with poorer psychological health, above and beyond other types of emotion judgments and key confounds. In Study 4 (111 participants and 835 observations), I examined prospective links between habitual emotion judgments and psychological health over one month and the mediating role of net emotions (emotions that linger after an emotional event has passed). Negative judgments of negative emotions were associated with worse psychological health one month later, and this relationship was partially mediated by daily net emotions. In sum, individuals differ in the types of emotion judgments that they tend to make and these individual differences appear to powerfully shape daily emotional responses and in turn, psychological health.

Advisor: Mauss, Iris B
Essays in Psychology and Economics

This dissertation consists of three chapters which all study parental decision-making for their children in the domain of competition. Willingness to compete is an important determinant of education and labor market outcomes. A growing literature has documented a robust gender differences in competitiveness which may explain the observed differences between men and women in these domains. Parents play an important role in shaping children's preferences and long-term outcomes. The key motivation for the dissertation is to understand the influence of parents on gender differences in competitiveness and later life outcomes./nIn the first chapter, I study how parents make competitiveness choices for their adolescent children in Norway. In an experiment with 1480 parents and children, parents choose if their child will do a task for a competitive or non-competitive pay scheme. The paper establishes a number of novel facts on parents' choices for children. First, parents choose more competition for boys than for girls. The gender gap in parents' choices is smaller than that in children's own choices. Second, two main mechanisms explain the gender gap in parents' choices: their beliefs about children's preferences and paternalistic behavior. Third, parents' choices are more responsive to the ability of boys than girls, which results in many high-ability girls not entering into competition. Fourth, parent gender matters: fathers are more likely than mothers to enter their child into competition. Finally, children are unaware of the gender difference in parents' choices and believe that parents will make the same choices for boys and girls./nThe second chapter uses data from the same experiment as in chapter one, to study the transmission of competitiveness preferences within social networks. I document a positive correlation between preferences both within family and within peer groups. I study parents' beliefs about the correlation of preferences, and find that parents overstate how close their own preferences are to their children's preferences./nIn the third chapter, which is joint work with Edward Miguel (UC Berkeley), we study how parents make competitiveness choices for their young children in Kenya. We present preliminary data from two lab-in-the-field experiments, and highlight three findings. First, in the sample of parents, men are more likely than women to compete. Second, in the sample of children, there is no evidence that boys are more competitive than girls. In fact, girls are more likely to compete than boys, but this difference is not significant. Third, when parents are asked to choose if their child should compete or not, there is a significant gender difference in choices; parents choose more competition for boys than for girls. We study mechanisms for parents' competition choices. Importantly, the difference in choices for boys and girls, is not explained by parents' beliefs about their children's preferences.

Advisor: DellaVigna, Stefano
Queries on Compressed Data

Low-latency, high-throughput systems for serving interactive queries are crucial to today's web services. Building such systems for today's web services is challenging due to the massive volumes of data they must cater to, and the requirement for supporting sophisticated queries (e.g., searches, filters, aggregations, regular expression matches, graph queries, etc.). Several recent approaches have highlighted the importance of in-memory storage for meeting the low-latency and high-throughput requirements, but these approaches are unable to sustain this performance when the data grows larger than DRAM capacity. Existing systems thus achieve these goals either by assuming large enough DRAM (too expensive) or by supporting only a limited set of queries (e.g., key-value stores)./nIn this dissertation, we explore algorithmic and data structure-driven solutions to these system design problems. We present Succinct, a distributed data store that addresses these challenges using a fundamentally new approach --- executing a wide range of queries (e.g., search, random access, range, wildcard) directly on a compressed representation of the input data --- thereby enabling efficient execution of queries on data sizes much larger than DRAM capacity. We then describe BlowFish, a system that builds on Succinct to enable a dynamic storage-performance tradeoff in data stores, providing applications the flexibility to modify the storage and performance fractionally, just enough to meet the desired goals. Finally, we explore approaches that enable even richer query semantics on compressed data, including graph queries using ZipG, a memory efficient graph store, and regular expression queries using Sprint, a query rewriting technique.

Advisor: Stoica, Ion
Emergence of structured representations in neural network learning

Learning is one of the hallmarks of human intelligence. It marks a level of flexibility and adaptation to new information that no artificial model has achieved at this point. This remarkable ability to learn makes it possible to accomplish a multitude of cognitive tasks without requiring a multitude of information from any single task. In this thesis, we describe emergent phenomena which occur during learning for artificial neural network models. First, we observe how learning well-defined tasks can lead to the emergence of structured representations. This emergent structure appears at multiple levels within these models. From semantic factors of variation appearing in the hidden units of an autoencoder to physical structure appearing at the sensory input of an attention model, learning appears to influence all parts of a model. With this in mind, we develop a new method to guide this learning process for acquiring multiple tasks within a single model. Such methods will endow neural networks with greater flexibility to adapt to new environments without sacrificing the emergent structures which have been acquired previously from learning.

Advisor: Olshausen, Bruno
Advances in 3ω Measurements to Spatially Track a Moving Interface

Detecting depth varying thermal properties is desirable for applications such as cryosurgery, landmine detection and non-destructive testing. This can be accomplished by periodic heating, exploiting the resulting frequency dependent penetration depth. Using this, objects with thermal conductivity distinct from their surroundings (such as material flaws or landmines) can be detected. In cryosurgery, for treatment of atrial fibrillation, it is desirable to track the location of moving boundaries between two phases (i.e. frozen and thawed tissue) with sub-millimeter precision. This spatial resolution is not attainable with conventional imaging./nIn this dissertation, the 3ω thermal property measurement technique is used to make new types of measurements on systems changing in real time. Analytical understanding of measurements with multiple frequency excitations is first developed, and verified with experiments. Next, the 3ω technique is used to sense thickness of samples (200μm and 500μm ice). The same sensors are used to detect step changes in thermal properties, including phase change, of water and mouse liver samples in real time. Finally an experimental setup is constructed to track an oil-air interface as it moves. Numerical modeling is used to convert measured 3ω voltages into spatial dimensions. For slow front velocities, the location of the oil-air front determined from the 3ω approach is found to be accurate to within an average error of under 18μm (RMS) for front distances between 12 and 360μm.

Advisor: Dames, Chris
Targeted Learning in Estimating Heterogeneous Effects and Transporting Direct and Indirect Effects

Targeted learning offers a framework for applying state-of-the-art machine learning in computing estimates, while providing reliable measures of uncertainty for non-parametric and semi-parametric models. Often when applying data adaptive estimation necessary for accurate prediction to reduce bias we lose the ability to bootstrap non-parametrically for inference. This is where targeted maximum likelihood estimators succeed in providing valid inference under conditions we detail, through very inexpensive computation of the standard deviation of the efficient influence curve approximation. We apply the framework mainly to three new parameters of interest, particularly relevant to the field of causal inference and heterogeneous response to treatment. The first two are the variance and cumulative distribution function of the stratum-specific treatment effect function (VTE and TE CDF). The third is transporting from one site to another treatment effects in the presence of an intermediate confounder as well as a mediator, known as stochastic direct and indirect effects (SDE and SIE). We mainly consider SDE and SIE defined by the data in that the stochastic intervention on the mediator is defined by an estimate of the mediator and intermediate confounder mechanisms. We also consider SDE and SIE for both a restricted and unrestricted model that are relevant in practice. We prove efficiency and robustness properties for all the estimators used in this paper as well as software and provide extensive simulations to verify the properties and compare performance with other estimators.\/nThis manuscript contains a generalized method of deriving efficient influence functions central to applying targeted learning for these parameters and others for large models, including for the fixed transported stochastic direct and indirect effects parameters for both restricted and unrestricted models, where the stochastic intervention is defined by the true mechanisms for the mediator and intermediate confounder. The method comes out of a tutorial, featuring the necessary tools of measure theory, integration, functional analysis and efficiency theory, which enables statisticians to embrace estimation for large models often realistic for practical scientific questions. Lastly, this paper implements a new way to perform the targeting in the TMLE process via the discovery of the canonical least favorable submodels (CLFM's) which, are one-dimensional submodels applicable for high dimensional parameters. CLFM's, used in this paper for estimating many points on the TE CDF, are not only fast but also hold promise for mitigating practical positivity violations. Finally, we employ an easily implementable CV-TMLE procedure, applied on real data for estimating the VTE, that we show retains the attractive properties of Zheng and van der Laan's original CV-TMLE formulation.

Advisor: van der Laan, Mark J
Incorporating Human Beliefs and Behaviors into Wildlife Ecology

Like much of the global biosphere, wildlife species have experienced rapid declines during the Anthropocene. Wildlife ecologists have responded to these crises by developing a range of technologies, techniques, and large datasets, which together have revolutionized the field, provided novel insights into the movements and behaviors of animals, and identified new risks and impacts to wildlife in a human-dominated world. While these advances have been vitally important, wildlife ecology has been slower to recognize and incorporate humans themselves into its new research domains. The chapters of this dissertation explore methods for better incorporating human behaviors, beliefs, actions, and infrastructure into the theories and approaches in wildlife ecology that have flourished in the last two decades. The research presented here demonstrates the importance of linking human beliefs and behaviors to wildlife ecology both by presenting novel findings and by showing the opportunities missed when narrow approaches are applied to complex socio-ecological problems./nIn Chapter 1, I provide a general introduction on the theories underlying this research, contextualize the research questions in light of the loss and recovery of large predators, and describe the research site where I collected much of the data for this dissertation. In Chapter 2, I apply the methods of movement ecology to some of the first fine-scale telemetry data collected on rifle hunters. I draw conclusions about their individual, site-level, and regional-level hunting behaviors and discuss the broad implications of these findings for hunting management. In Chapter 3, I examine livestock-predator conflict using approaches from both ecology and the social sciences. I describe a form of selection bias that is likely widespread but unreported due to the omission of social data from ecological models of conflict, and I offer guidelines for combining and translating ecological and social research on conflict. In Chapter 4, I explore the ecological impacts of one of the most globally widespread human constructions, the fence. I show for the first time the potential extent of fencing at large scales and discuss the wide variety of ecological effects of fences for both humans and ecosystems. I further highlight biases and gaps in fence research that have thus far limited a complete understanding of the environmental effects of these features. In Chapter 5, I conclude by making recommendations regarding how research might better incorporate human perceptions, decisions, and actions into ecology.

Advisor: Brashares, Justin S
Essays on Working Conditions, Labor Markets, and Multinational Buyers in Developing Countries

Chapter 1: Western stakeholders are increasingly demanding that multinationals sourcing from developing countries be accountable for labor rights and working conditions upstream in their supply chains. In response, many multinationals privately enforce labor standards in these countries, but the effects of their interventions on local firms and workers are unknown. I partnered with a set of multinational retail and apparel firms to enforce local labor laws on their suppliers in Bangladesh. I implemented a randomized controlled trial with 84 Bangladeshi garment factories, randomly enforcing a mandate for worker-manager safety committees in 41 supplier establishments. The intervention significantly improves compliance with the labor law. It also has a small, positive effect on indicators of safety committees' effectiveness, including measures of physical safety and awareness. Factories with better managerial practices drive these improvements. In contrast, factories with poor managerial practices do not improve compliance or safety, and in these factories, workers' job satisfaction declines./n/nChapter 2 (joint with Rachel Heath and Tyler McCormick): Many workers in large factories in developing countries are internal migrants from rural areas. In collaboration with Rachel Heath and Tyler McCormick, I examine the relationship between workers' migration status and the working conditions they face in a household survey of garment workers in Bangladesh. We document that migrants are in firms with higher wages but worse working conditions, but as their careers progress, they have higher mobility than locals as they move towards firms with better conditions. These facts are consistent with a model in which migrants are poorly informed about working conditions upon beginning work but learn more as they gain experience in the industry./nChapter 3: I test for the presence of compensating wage differentials for factory building safety in Bangladesh's apparel sector. I find no evidence in support of a compensating wage differential for building safety. This descriptive fact is not explained by heterogeneity in workers' or factories' observable characteristics. Instead, I show that workers have incomplete information about factories' compliance with building safety standards, which I argue is difficult for workers to observe. Workers at high compliance factories underestimate their factories' performance on building safety audits, while workers at low compliance factories dramatically overestimate their factories' performance. I implement a pilot field experiment with 308 garments workers in which I randomly intervene to provide workers with information about their factories performance on the audits relative to other factories nearby. The information causes workers to correctly update their beliefs about their factories' safety. It reduces turnover among workers at high compliance factories. Among workers at low compliance factories, turnover is unaffected, but workers are less likely to make referrals to their factory.

Advisor: Yuchtman, Noam
Biochemical Protecting Groups for a Sustainable Indigo Dyeing Method

Indigo is a widely used dye in the textile industry, but current industry practice uses toxic chemicals to produce and solubilize the compound. I am developing a more environmentally friendly dye process by using microbial fermentation to produce indigo dye. Unlike the industrial procedure, microbes can produce indigo from renewable sources, and many of the hazardous chemicals can be eliminated from the dye synthesis and dye application processes. First, I describe a method to dye with indican, the glucosylated form of an unstable indigo precursor found in indigo-producing plants. I identified the gene sequence for a key biosynthetic enzyme from the indigo plant, and I expressed that gene in an Escherichia coli strain to produce indican. The glucosyl group on indican can be removed by a β-glucosidase, forming indigo. I show that applying indican and β-glucosidase to cotton can dye it an indigo color. Second, I extend this strategy of biological protecting groups towards producing a second-generation dye molecule, isatan B. Although chemically similar to indican, isatan B is hydrolyzed at a basic pH, a desirable property for the indigo dyeing process. I isolated the isatan B molecule from plant leaves and used the purified molecule to characterize isatan B’s stability in the E. coli host. I then describe efforts to construct a biosynthetic pathway for isatan B in E. coli.

Advisor: Dueber, John E