VictorJuiz/thesis huggingface dataset:
¡Saca Mi Foto!: The Visual Cultures of Undocumented Migration

This interdisciplinary study traces the emergence of two competing visual cultures of undocumented migration in the U.S. borderlands between the 1950s and the 1990s. One was a nativist visual culture crafted by the Immigration and Naturalization Service (INS) and its backers in the wake of the bracero program. Photographers affiliated with the agency, popular magazines, and the news media objectified Latin American migrants and depicted the border as vulnerable territory that required constant surveillance but would never be completely controlled. In doing so, they fortified xenophobic law and practice by framing sovereignty as a visual project that depended on rigorous oversight and the regulation of racialized migrants. Through this visual regime, the state cemented the ontological divide between citizens and “illegals” and helped forge the stereotype of the Latinx “alien”: a criminal trespasser who posed a persistent, insidious threat to the nation. In response, an eclectic cohort of artists, photojournalists, and documentary photographers based in Arizona, California, Florida, and Texas generated a critical, humanitarian visuality attuned to migrants’ subjectivities and lived realities. They collaborated with activists, new labor unions, and outlets from the radical and mainstream press. In the 1970s and 1980s, their work critiqued the militarization of the border, displayed the intimate bonds and rich culture that sustained transnational communities, condemned the exploitation that Latinx workers experienced under U.S. capitalism, and propelled movements for the rights of the undocumented. To access the perspectives of photographers, migrants, and spectators, I draw on evidence from memoirs, photo-essays, newspapers, oral history interviews, archival documents, private collections, and gallery exhibits. In doing so, I demonstrate that photographers played a pivotal role in creating—and reimagining—the modern image of “illegality.” In the hands of the state and its boosters, the camera was a disciplinary technology that fueled xenophobia and naturalized surveillance. But for migrants and their advocates, it was a tool of resistance that questioned nativist tropes and promoted solidarity with Latinx communities.

Keywords: Borderlands
Latinx History
Photography
Surveillance
Undocumented Migration
Visual Culture
Advisor: Coleman, Kevin
Kazal, Russell
Building a Scalable Sensing Foundation for Contextual and Precise Interaction

A majority of our interactions with computing devices are localized to surfaces that are physically on the device or in their vicinity. However, emerging modes of computational interaction such as mixed reality and voice based intelligent agents demonstrate a pressing need for the ability to interact on any surface, at any time, pervasively and reliably. Traditional sensor deployments, instrumentation of the user and the environment begin to address this problem. However, doing this at scale presents multiple challenges in the form of prohibitive cost of deployment, reliability and obtrusiveness. This goal of interacting with arbitrary surfaces easily and unobtrusively has been elusive.In this dissertation, we make the case for pervasive sensing that relies on passive or no instrumentation of the environment. We demonstrate two different technologies with ID’em detailing a centimeter scale localization through the embedding of tags into materials and pressAR showcasing the ability to sense finger presses and touch precisely using off the shelf camera systems. We believe that this highly scalable approach to sensing empowers designers, engineers, and researchers to deploy rich, ubiquitous interactions at a large scale.

Keywords: Human Computer Interaction
Scalable Sensing
Ubiquitous Computing
Advisor: Wigdor, Daniel J
Downstream Regulators of Pollen-stigma Interactions in Arabidopsis thaliana

In the Brassicaceae, sexual reproduction is tightly controlled through a series of cell-to-cell communication events between the male pollen and the female pistil. This communication can result in either the acceptance or rejection of pollen, which ultimately controls the plant’s reproductive success. The basal compatible pollen response pathway is initiated by a Brassicaceae-wide recognition system, which results in polarized vesicle secretion in the pistil towards the site of pollen contact, providing water and other resources to the pollen grain. Conversely, the self-incompatible pollen response pathway is triggered by a genetically linked receptor-ligand interaction and results in the block of vesicle secretion, leaving the pollen physiologically inactive. Although the broad mechanisms of these two pathways are understood, knowledge of the mechanisms through which they are carried out remains elusive. This thesis describes the identification of several new factors involved in pollen acceptance or rejection. During compatible pollen acceptance, the vesicle-fusing SNARE complex was found to be involved in the early stages of compatible pollen responses. Each component of this ubiquitously used protein complex was targeted through a combination of T-DNA insertions, CRISPR/Cas9-mediated mutations, or stigma-specific RNAi knockdowns, resulting in impaired pollen hydration. Additionally, live-cell fluorescent imaging was used to directly observe the secretory network during the compatible pollen responses in the stigma. In the self-incompatible pollen response pathway, the role of autophagy was investigated through the introduction of autophagy-deficient mutants into transgenic self-incompatible Arabidopsis thaliana. Disrupting autophagy was sufficient to break down self-incompatibility, indicating it was an essential mechanism in pollen rejection. Live-cell imaging was again used to observe autophagosomes and secretory components during this response. Thus, several new key cellular players were added to both pathways in the pollen-pistil interaction, opening new avenues for future research into either the acceptance or rejection of pollen in the Brassicaceae.

Advisor: Goring, Daphne R.
Algorithms for Data-driven Geometric Stylization Acceleration

In this thesis, we investigate computer algorithms for creating stylized 3D digital content and numerical tools for processing high-resolution geometric data.This thesis first addresses the problem of geometric stylization. Existing 3D content creation tools lack support for creating stylized 3D assets. They often require years of professional training and are tedious for creating complex geometries. One goal of this thesis is to address such a difficulty by presenting a novel suite of easy-to-use stylization algorithms. This involves a differentiable rendering technique to generalize image filters to filter 3D objects and a machine learning approach to renovate classic modeling operations. In addition, we address the problem by proposing an optimization framework for stylizing 3D shapes. We demonstrate how these new modeling tools can lower the difficulties of stylizing 3D geometric objects. The second part of the thesis focuses on scalability. Most geometric algorithms suffer from expensive computation costs when scaling up to high-resolution meshes. The computation bottleneck of these algorithms often lies in fundamental numerical operations, such as solving systems of linear equations. In this thesis, we present two directions to overcome such challenges. We first show that it is possible to coarsen a geometry and enjoy the efficiency of working on coarsened representation without sacrificing the quality of solutions. This is achieved by simplifying a mesh while preserving its spectral properties, such as eigenvalues and eigenvectors of a differential operator. Instead of coarsening the domain, we also present a scalable geometric multigrid solver for curved surfaces. We show that this can serve as a drop-in replacement of existing linear solvers to accelerate several geometric applications, such as shape deformation and physics simulation. The resulting algorithms in this thesis can be used to develop data-driven 3D stylization tools for inexperienced users and for scaling up existing geometry processing pipelines.

Keywords: Computer Graphics
Geometry Processing
Machine Learning
Advisor: Jacobson, Alec
A Solution to the Multimodal Binding Problem

Known as the multimodal binding problem, a long-standing question in the cognitive sciences has asked how the mind forms complex object representations from basic sensory features. Integrating features into object representations is fundamental to human experience, yet there remains little theoretical consensus towards how the mind accomplishes this remarkable ability. In Chapter 1, I first describe how existing theoretical perspectives differ in their levels of analysis in terms of how feature integration is understood, focusing on the working memory literature. I then provide a link between seemingly contradictory perspectives, interpreting memory performance in terms of mental representations. In Chapter 2, I show how shape representations can be quantified through similarity judgments, constructing the first perceptually uniform shape space comparable to the ‘color wheel’. In Chapter 3, I combine perceptually uniform shape and color space together, creating a novel simultaneous reproduction task to quantify visual object representations along a continuous metric. Critically, objects in working memory were represented hierarchically as both independent and integrated features, providing evidence for one solution towards how the mind constructs objects from their basic features. In Chapter 4, I directly ask how the brain solves the binding problem, recording brain activity using multi-echo functional neuroimaging as participants experienced 3-dimensional multimodal objects. Using a novel 4-day learning task, I found that the brain constructs multimodal object representations through a hierarchical architecture: experience-dependent integrative coding in the anterior temporal lobes distinct from individual features coded across distributed sensory regions. In Chapter 5, I conclude with future research directions, including how these findings may relate to the design of more human-like artificial neural networks that aim to learn multimodal object concepts. These results provide one solution to the multimodal binding problem, revealing that a hierarchical neural architecture supports the representation of multimodal objects in working memory. Furthermore, I introduce several new tools to quantify object representations, revealing that how we understand feature integration is fundamentally intertwined with the level of analysis by which we measure and interpret human behaviour in the first place.

Keywords: Isomorphism
Multi-echo fMRI
Multimodal binding problem
Perceptually uniform space
Representation
Working memory
Advisor: Barense, Morgan D
Public-Private Partnership Schools in Punjab: Is there a Learning Premium that can be Explained by Management Practices?

The rapid rise of low-cost private schools (LCPS) in developing countries has sparked fierce debate. Proponents argue these schools promote access in areas underserved by government schools, as well as benefit from improved autonomy in decision-making and accountability to parents to produce superior learning outcomes. Critics note that they fail to reach the poor, and any learning premium is driven by selection effects. Despite the ongoing debate, in the face of growing demand for schooling, public-private partnerships (PPPs) have become a key feature of the global education landscape. This trend is especially pronounced in the Punjab province of Pakistan, where many private schools participate in public financing schemes through subsidy, charter and voucher programs. With increasing recognition of the global learning crisis, the performance of PPP schools, as well as the drivers of any achievement gap, are of great interest to policy makers. Recent scholarship has foregrounded school management practices – including accountability to clients – as a key factor in school effectiveness. Drawing on data from the Service Delivery Indicator (SDI) Survey from Punjab, this dissertation contributes to these debates: first by asking if there is an achievement gap between PPP and government schools in Punjab (as well as fee-based private schools), and second, assessing the role of school management quality in explaining the achievement gap. I hypothesize that certain management best practices – focusing on the domains of people management, operations, leadership, target setting and monitoring, as measured by the SDI – are driven by increased autonomy for private schools, and should account for part of the hypothesized ‘PPP school premium’. The results suggest that while the achievement gap between PPP and public schools is small after accounting for student background, it is statistically significant and relatively consistent across models. In addition, when comparing the PPP approaches, voucher schools have the strongest achievement followed by subsidy and then charter schools. Second, I find that the index for management practices is positively associated with learning outcomes. However, despite having more autonomy in decision making, fee-based private schools and PPP schools do not appear better managed than government schools, and as a result, management practices do not explain the achievement gap.

Keywords: Education
Management
Pakistan
Privatization
Public-Private Partnerships
Vouchers
Advisor: Mundy, Karen
Chmielewski, Anna
Molecular Characterization and Engineering For the Development of a Transmission-Blocking Malaria Vaccine

Malaria is an ongoing global health crisis with cases and resistance to treatments on the rise. Only one malaria vaccine is currently recommended for use in endemic regions in Africa by the WHO, which has middling efficacy that drops to approximately 35% protection against clinical disease after a year. Novel approaches are urgently needed. Transmission-blocking vaccines aim to inhibit the malaria parasite, Plasmodium falciparum, while in the mosquito vector, so the parasite is not viable to transmit to the human host. However, both biological and biophysical understanding is lacking for most target antigens within the field. This thesis establishes the groundwork for the molecular understanding of antibody recognition of leading transmission-blocking antigens Pfs25 and Pfs48/45 by solving multiple crystal structures of Fabs bound in complex to the antigens. Herein is described the first atomic resolution structure of Pfs25, as well as the molecular characterizations of both murine and human monoclonal antibody epitopes of high and low potency, providing a comprehensive map of the immunogenicity and potency of Pfs25. This thesis also leverages molecular blueprints of Pfs48/45 to stabilize its structure using integrative structural biology approaches leading to increases in recombinant expression (~30x), thermostability (>25°C improvement in melting temperature from wild-type), and potency (1-2 log) of the antibody response elicited through immunization. Overall, this work provides foundational molecular understandings and improvements to two of the most high- priority transmission-blocking vaccine targets against malaria.

Keywords: antibody antigen complexes
Malaria
protein engineering
structural biology
Structure-based vaccine design
transmission-blocking
Advisor: Julien, Jean-Philippe
Connecting the Atmosphere and the Ocean through Reactions at the Sea Surface Microlayer

The reaction of ozone with chemical species at the ocean surface is a source of volatile molecules, including molecular iodine (I2) and volatile organic compounds (VOCs), including organoiodine molecules. The volatiles released affect air quality and climate by impacting aerosol composition and the atmospheric oxidative budget.One major goal of this thesis was to understand the factors which affect the formation of VOCs from gas-surface ozonolysis. To accomplish this, axenic Thalassiosira pseudonana cultures were used to generate a reproducible and realistic surface ocean proxy. When the culture was exposed to gas-phase ozone, VOCs were observed which were further oxidized to form secondary organic aerosol. The VOC type and yield was linked to the phytoplankton growth cycle, emphasizing the importance of biological processes on VOC precursors. The second and third projects focused on understanding the interaction of ozone with the iodide component of seawater, and how that affected the release of VOCs from ozonolysis. Using a halide solution that matched seawater composition, the ozone loss rate was strongly influenced by iodide depletion. These findings were substantiated with a kinetic multilayer model. Uncertainties in the efficiency of mixing processes in the ocean makes assessment of the importance of iodide depletion in the environment an open question. The formation of gaseous I2 from the ozonolysis of iodide was suppressed in the presence of chloride and phytoplankton organics, which could not be modelled by known chemistry. A sensitivity analysis indicated two key aqueous phase reaction rate constants which could be changed to replicate the trend of decreasing gaseous I2yield in the presence of chloride. Attempts to determine why phytoplankton organics suppress the I2 yield involved measuring I2uptake to the T. pseudonana cultures. However, experimental limitations caused by the rapid hydrolysis of I2 into HOI prevented firm conclusions being made. Finally, preliminary studies comparing the VOC yield from photochemistry and ozonolysis on real Arctic Ocean samples are presented. Overall, this thesis highlights the factors that should be considered when determining the importance of ozonolysis to VOC and iodine emission to the marine atmosphere.

Keywords: Arctic
Atmosphere
Emission
Iodide
Ocean
Advisor: Abbattt, Jonathan
Semidefinite Relaxations for Geometric Problems in Robotics

Mobile robots perceive and move through the three-dimensional space of the approximately Euclidean world we share with them. In order to safely and accurately accomplish their goals, they must be able to reason about the nonlinear and nonconvex geometry of the manifold of rotations. Without this ability, tracking the poses of objects from noisy measurements and avoiding obstacles in their environment becomes impossible. Traditional approaches use local information and structure to estimate and optimize rotations of interest, making them susceptible to suboptimal performance. In this dissertation, we apply recent advancements in global convex optimization to two fundamental geometric problems in robotics: extrinsic sensor calibration and inverse kinematics in cluttered workspaces. We begin with a summary and extension of the semidefinite relaxation machinery that we apply to both problems. This machinery is used to develop fast and accurate extrinsic calibration algorithms with novel performance guarantees provided by certificates of global optimality. We proceed to develop a novel perspective of inverse kinematics inspired by noisy state estimation problems, leading to fast and accurate algorithms appropriate for a variety of challenging scenarios. We provide free and open source implementations of our algorithms, and demonstrate their superiority over conventional approaches on a variety of simulated and real-world data.

Keywords: Inverse kinematics
Optimization
Semidefinite programming
Sensor calibration
Advisor: Kelly, Jonathan
Genome-wide CRISPR Screening in FBXW7-mutant Cells Uncovers Multiple Druggable Synthetic Lethal Interactions Involving Cell Cycle Control

Current standard of care chemotherapeutics broadly target actively dividing cells, with both healthy and cancerous cells being damaged, causing toxic side effects. Personalized oncology aims to selectively target cancerous cells based on their mutational status, minimizing toxic and life-altering side effects, while effectively blocking the cancer’s growth and proliferation. Understanding what is an essential gene or essential process selectively required for the growth of cells with specific mutations is a challenging task. Leveraging genome-wide knockout screens using paired isogenic cell lines that only differ in a cancer-causing mutation of interest provides a path forward to understanding these processes. In this thesis we generated several isogenic cell lines to identify genetic interactions that are synthetic lethal with common cancer-associated mutations in the Wnt signalling pathway and that could therefore represent new therapeutic targets. From this work we identified two novel druggable synthetic lethal interactions with the commonly mutated tumour suppressor gene, FBXW7. We first identified that FBXW7-/- cells require CCNL1 for growth, and discovered that CCNL1 is a novel substrate of FBXW7, tasked with a role controlling progression through mitosis. FBXW7-/- cells, due to their requirement of CCNL1, were more sensitive to the novel CDK11-inhibitor OTS964. The second SL interaction identified in FBXW7-/- cells was the requirement for DNA damage response genes. We identified high levels of replication stress in FBXW7-/- cells and organoids, resulting in increased sensitivity to an inhibitor of the ATR kinase - a mediator of the cellular response to replication stress. We hypothesize that activation of DNA damage response in FBXW7-/- cells leads to persistent ATR activation to mitigate replication stress and that ATR inhibition will force mitotic entry leading to mitotic catastrophe.

Advisor: Angers, Stephane