VictorJuiz/thesis huggingface dataset:
"Resocialize to Conquer the Future": Incarceration and Reform in Rio de Janeiro

This dissertation examines the interventions made in the lives and futures of those incarcerated in Rio de Janeiro’s men’s prisons in the name of “resocialization.” I argue that resocialization – the network of practices oriented towards “reforming” or rehabilitating those in prison – animates the prison system and structures how both prison workers and the incarcerated apprehend and navigate the institution. That is, prisons come to understand, treat, analyze, punish, and ultimately release, those within their custody based on a simultaneous promise and demand for resocialization. They do so despite the prevalence of violence, overcrowding, and an entrenched culture of punitivism both within the criminal justice system and in Brazil more broadly. At the same time, many of those in prison are invested within the same normative trajectory of reform against which they are held accountable by prison workers. As such, the motto of the state prison administration – “Resocialize to Conquer the Future” – represents a legal and moral injunction to reform that structures prison life and governance./nThe analytical focus of the dissertation centers on the points of encounter between incarcerated people and those workers or volunteers whose work falls under the broad mandate to resocialize. I examine the engagements of public defenders, evangelical missionaries, and psychosocial “technicians” with rehabilitative projects and procedures. Additionally, I follow incarcerated people both during and after their imprisonment, as they endeavor to build and pursue futures for themselves while also struggling to pursue the ideals and expectations set out by resocialization’s narrative. The relationship between these two groups, I argue, channels a series of anxieties surrounding race, gender and kinship, concerns that shape what becomes recognizable within the institution as a properly reformed subject. As a result, resocialization functions through foreclosure as much as potential or possibility; it becomes a tool wielded within prisons towards both punitive and emancipatory ends, often blurring the distinction between the two./nThrough this analysis, the dissertation offers a new form of engagement with resocialization, and rehabilitation more broadly, that remains open to its variegated effects beyond any ostensible successes or failures. I also demonstrate that the social continues to serve as an anchor for the project of incarceration, since both prisons and the imprisoned come to be understood in reference to “society” even as they are positioned as outside it. By underlining the anticipatory nature of prisons, I contend that incarceration constitutes a key site that determines what individual and collective futures are imaginable, particularly in the context of Brazilian democracy and its expanding penal state.

Advisor: Holston, James
Mapping the Cosmic Evolution of Hydrogen: Analysis and Inference Techniques for Next-Generation 21 cm Cosmology

The path towards detecting the cosmological 21 cm signal from the Epoch of Reionization and Cosmic Dawn has seen tremendous progress over the past decade: interferometric experiments have placed increasingly stringent upper-limits on the 21 cm power spectrum, and global signal experiments have made a tentative first-detection of the 21 cm monopole signal. As next-generation experiments are designed, built, and begin taking data, the road towards maximizing their scientific potential hinges crucially upon the development of robust data analysis techniques for isolating the 21 cm signal from foregrounds and low-level instrumental systematics. This thesis is a compilation of work that describes new and old techniques and applies them to the up-and-coming Hydrogen Epoch of Reionization Array (HERA), a second-generation low-frequency experiment that aims to make a detection of the 21 cm power spectrum from redshifts 6 < z < 20. Such a feat would dramatically improve our understanding of the intergalactic medium at these redshifts, and would shed light on the formation and properties of the first stars, galaxies, and compact objects in the universe. Towards this goal, this work touches on some of the current challenges facing the analysis of 21 cm data, from instrument commissioning and calibration to astrophysical parameter inference. In particular, we develop a detailed understanding of low-level systematics in the HERA system, yielding improved sensitivity in the measured power spectrum by over two orders of magnitude. As HERA construction is finished and full-sensitivity observing commences, the algorithms and analysis frameworks discussed here are setting the stage for a future full-sensitivity HERA analysis and the next-generation of 21 cm cosmology.

Advisor: Parsons, Aaron
Compositionality and Modularity for Robot Learning

Humans are remarkably proficient at decomposing and recombiningconcepts they have learned. In contrast, while deep learning-based methods have been shown to fit large datasets and out-perform humans at some tasks, they often fail when presented with conditions even just slightly outside of the distribution they were trained on. In particular, machine learning models fail at compositional generalization, where the model would need to predict how concepts fit together without having seen that exact combination during training. This thesis proposes several learning-based methods that take advantage of the compositional structure of tasks and shows how they perform better than black-box models when presented with novel compositions of previously seen subparts. The first type of method is to directly decompose neural network into separate modules that are trained jointly in varied combinations. The second type of method is to learn representations of tasks and objects that obey arithmetic properties such that tasks representations can be summed or subtracted to indicate their composition or decomposition. We show results in diverse domains including games, simulated environments, and real robots.

Advisor: Levine, Sergey
Darrell, Trevor
Microenvironmental Cues Driving CD44-mediated Glioblastoma Invasion through Hyaluronic Acid-rich Matrix

Interactions between tumor cells and the extracellular matrix (ECM) play a critical role in tumor invasion. Glioblastoma (GBM) is a highly malignant primary brain cancer characterized by diffuse infiltration, with tumor cells invading slowly through the hyaluronic acid (HA)-rich parenchyma toward vascular beds and then migrating rapidly along microvasculature rich in collagen, fibronectin, and laminin. Nonetheless, little is known about how cells navigate nonfibrillar 3D matrices, such as the HA-rich brain parenchyma, or how plasticity in cell migration modes between intraparenchymal and perivascular spaces influences invasion. Progress in understanding local infiltration, vascular homing, and perivascular invasion is further limited by the absence of culture models that recapitulate these hallmark processes. The transmembrane receptor CD44 directly facilitates tumor cell invasion by engaging HA in brain matrix and is therefore a likely candidate for mediating invasive plasticity./nIn this dissertation, we investigate how topographical cues in the perivascular niche instruct cell invasion modality and how CD44 coordinates with the cytoskeleton to facilitate invasion through HA-rich matrices. We first describe the development of a platform for GBM invasion consisting of a tumor-like cell reservoir and a parallel open channel “vessel” embedded in the 3D HA matrix. We show that this simple paradigm is sufficient to capture multi-step invasion as well as transitions in cell morphology and speed reminiscent of those in GBM. Tumor cells within the model grow into multicellular masses that expand and invade the surrounding HA-rich matrices while extending long (10–100 µm), thin protrusions before encountering the open channel. We then assess how HA signals arise in vivo and how these signals are generally incorporated into in vitro models to mechanistically investigate HA-mediated motility. Finally, we employ our HA hydrogel platform to probe the role of CD44 in cytoskeletal motility. We show that continuous and patient-derived GBM tumor cells interacting with both 2D and 3D HA substrates exploit CD44-based microtentacles (McTNs) to support cell migration. These McTNs are stabilized by a balance between microtubule-driven protrusion and actomyosin-driven retraction, which are mechanistically coupled by an IQGAP1-CLIP170 complex. Cells approaching vascular structures transition from McTN-based motility to a quasi-2D mesenchymal motility involving actomyosin bundles. McTN-driven motility and/or the transition to mesenchymal motility may represent an important new target for GBM discovery and therapeutics.

Advisor: Kumar, Sanjay
Quantifying the agreement between computational models and experimental data under uncertainty

Bound-to-bound data collaboration (abbreviated B2BDC) is a deterministic optimization-based approach for uncertainty quantification. The framework combines models and data from multiple sources by formulating inequality constraints over a parameter space. This dissertation explores the following question: how can agreement between computational models and experimental data be quantified while necessarily accounting for uncertainty in both model parameters and observations? In a typical B2BDC application, this is performed by constructing a dataset -- a collection of constraints over an uncertain parameter space involving surrogate models, experimental data, and prior knowledge -- and then assessing its consistency. Our first contribution is a formalization of this procedure within an iterative context. This new strategy effectively extends the applicability of the B2BDC technique and can be viewed as a natural extension of previous work. Oftentimes, demonstrating model-data disagreement is just as important as verifying agreement. In B2BDC, this is manifested through dataset inconsistency. Our second contribution is a new tool for analyzing inconsistency called the vector consistency measure. This measure provides a more thorough diagnosis of an inconsistent dataset by computing minimal constraint corrections that lead to consistency. The inclusion of weights facilitates domain expert knowledge and opinions to be incorporated in the process of resolving an inconsistency. The primary developments in this thesis are methodological. Their application is illustrated on various examples, ranging from the small-scale instances drawn from the literature to larger-scale realistic gas combustion datasets.

Advisor: Frenklach, Michael
When Dodge v. Ford Meets Ben & Jerry’s: Reconciling 100 Years of Bad Precedent with the Reality of Modern Business

The 1919 Michigan Supreme Court case Dodge v. Ford Motor Company has come to stand for the common belief that the primary purpose of all corporations is to create shareholder wealth. This unfortunate misinterpretation of the opinion has never fit comfortably with the reality of business practices or academic theories of the corporation and its state-sanctioned role in the marketplace. The tension between caselaw and reality has only increased in the century since Dodge was decided, and has ultimately culminated in the first direct challenge to the shareholder primacy norm: public benefit corporations, for-profit firms that are required by charter and law to pursue at least one prosocial goal in addition to monetary gain. I argue that the increasing influence of public benefit corporations represents the first unavoidable crisis facing Dodge v. Ford caselaw and its progeny, one that creates increasing risk of deadweight loss and ought to be addressed by both Congress and the courts. This turning point in the demographic composition of business also offers social planners a unique opportunity, however, to address the current defects in the law’s approach to the social obligation of incorporated firms without overturning the unfortunate but nevertheless settled precedent. Specifically, this crossroads in the evolution of corporations and their place in modern society provides a chance to: (1) Remedy flaws in the regulation of corporate charity so that good- and bad-faith donations can be distinguished, and (2) Radically improve corporate governance mechanisms to allow social enterprises to thrive.

Advisor: Edelman, Lauren B
The Health Benefits of Clean Energy Policy in the United States

In the past 10 years, a drastic shift towards the use of less greenhouse gas intensive fuels for electricity generation has occurred in the United States. At the same time, the U.S. government, states, cities, and businesses began to pursue policies to address climate change. This dissertation advances three research topics. First, this dissertation summarizes how environmental health played a role in advancing U.S. climate policy in the Obama Administration from 2009 – 2016 and identifies additional environmental health literature that could provide evidence to support climate change policy in the future. Second, this dissertation reviews the public health and econometric literature monetizing the health benefits of shifting to lower carbon fuels for electric power generation in the U.S. and identifies the strongest model predictors. Third, this dissertation evaluates whether an innovative exposure metric measuring the shift to lower carbon electricity generation in the U.S. from 2011 - 2012 is directly associated with a change in mortality in the Medicare cohort. The analysis in Chapter 2 found that environmental health literature helped to provide the legal foundation for regulating greenhouse gases through the Clean Air Act and that environmental health literature provided the information necessary to build the economic case for the U.S. Environmental Protection Agency (EPA) to promulgate greenhouse gas standards. Four of the eleven Obama-Biden Administration’s major climate change rulemakings would not have been cost-effective without monetizing the health, environmental, and societal benefits. The literature review in Chapter 3 revealed that the range of the monetized benefits of shifting to solar energy is 1-2.7 cents/kWh and 1.3-9 cents/kWh for wind energy in the United States. The analysis in Chapter 4 is the first national epidemiology study examining the direct association between phasing out the generation of traditional high carbon fossil-based electricity and the effect on mortality in the Medicare cohort. Using a difference-in-difference (DID) approach, no statistically significant change in mortality in Medicare enrollees was found when comparing the three intervention groups to the control groups and adjusting for confounding. This dissertation provides further evidence supporting the need to conduct multi-step analyses to determine the health effects of energy policy interventions. The results of this research will be used to advance environmental health science and U.S. energy and climate change policy.

Advisor: Balmes, John R
Mechanisms of Lipid Homeostasis in the Endoplasmic Reticulum and Lipid Droplets

The endoplasmic reticulum (ER) serves as the entry point to the secretory system where nearly one-third of the cellular proteome must undergo synthesis, folding, and maturation events before being deployed. Proteins that fail to successfully navigate these processes and achieve their native conformation are detained by endoplasmic reticulum-associated degradation (ERAD), a quality-control mechanism responsible for targeting misfolded proteins for degradation by the cytosolic 26S proteasome4. Recent studies have demonstrated that treatment with the long chain acyl-CoA synthetase inhibitor triacsin c disrupts lipid droplet (LD) biogenesis and ERAD, suggesting a functional connection between the processes. However, whether LDs are involved in ERAD remains an outstanding question./nLDs are highly dynamic neutral lipid storage organelles that function as central hubs of lipid metabolism charged with storing lipids and maintaining energy homeostasis of the cell. The specific metabolic role of LDs is dictated by the cell type and the metabolic state of the cell, which can fluctuate in response to a number of cellular stimuli. LD functions are regulated by a complement of integral and peripheral proteins that associate with the bounding LD phospholipid monolayer. The ability to define a high-confidence LD proteome is paramount to understanding LD functions and dynamics. However, accurate analysis of the LD proteome composition has remained a challenge due to the presence of contaminating proteins in LD-enriched buoyant fractions./nIn chapter one, we discuss the connection between protein and lipid regulatory systems within the ER and LDs, highlighting the importance of ERAD and lipophagy in maintaining cellular homeostasis. In chapter two, we use chemical and genetic approaches to disrupt LD biogenesis to explore a potential role for LDs in ERAD, ultimately providing evidence that LDs are dispensable for mammalian ERAD. Instead, our results suggest that triacsin c causes global alterations to the lipid landscape that disrupt ER proteostasis by interfering with the glycan trimming and dislocation steps of ERAD. Finally, in chapter three we develop a proximity labeling strategy that exploits LD-targeted APEX2 to biotinylate LD proteins in living cells. We apply this approach to two different cell types and are able to identify the vast majority of previously validated LD proteins, exclude common contaminating proteins, and identify the autophagy adaptor p62 as a mediator of hepatic lipophagy. Together these studies advance our understanding of the mechanisms that regulate lipid dynamics in the ER and LDs and their contribution towards maintaining cellular homeostasis.

Advisor: Olzmann, James A
Fetal immunity and the developing brain: implications for neurodevelopmental disorders.

The brain has innate immune myeloid cells (including microglia and border-associated macrophages) that have dynamic roles in homeostasis and the response to tissue injury and infection. Given the ability of brain myeloid cells to sense a variety of environmental cues, several studies have investigated their roles in neurodegenerative disease onset and progression. But, the impact of fetal myeloid cells on neurodevelopmental disorders is relatively unexplored in comparison. We used two mouse models of neurodevelopmental disorders to uncover the impact of fetal myeloid cell immunity to both normal and abnormal brain development. We found that an inflammatory lytic form of cell death, termed pyroptosis, in microglia may be required for establishing certain normal behavioral circuits. With genetic deficiency in the pyroptosis pathway, or upon pharmacological inhibition thereof, mice have attention-deficit/hyperactivity disorder (ADHD)-like behavior changes. Using the maternal immune activation (MIA) model of autism spectrum disorder (ASD), we identified a fetal myeloid responder population, likely to be border-associated macrophages, which directly sense MIA challenge. Thus, we learned that fetal immunity, mediated by myeloid cells, has important consequences for brain formation. Disruption or activation of these roles may constitute an upstream arm in neurodevelopmental disorder etiology.

Advisor: Saijo, Kaoru
The Design of Stateful Serverless Infrastructure

Serverless computing has become increasingly popular in the last few years because it simplifies the developer's experience of constructing and deploying applications. Simultaneously, it enables cloud providers to pack multiple users' workloads into shared physical resources at a fine granularity, achieving higher resource efficiency. However, existing serverless Function-as-a-Service (FaaS) systems have significant shortcomings around state management—notably, high-latency IO, disabled point-to-point communication, and high function invocation overheads./nIn this dissertation, we present a line of work in which we redesign serverless infrastructure to natively support efficient, consistent, and fault-tolerant state management. We first explore the architecture of a stateful FaaS system we designed called Cloudburst, which overcomes many of the limitations of commercial FaaS systems. We then turn to consistency and fault-tolerance, describing how we provide read atomic transactions in the context of FaaS applications. Finally, we describe the design and implementation of a serverless dataflow API and optimization framework specifically designed to support machine learning prediction serving workloads.

Advisor: Hellerstein, Joseph M
Aspects of Holography And Quantum Error Correction

The holographic principle has been a central theme in most of the progress in the field of quantum gravity in recent years. Our understanding of the AdS/CFT duality, the best known embodiment of the holographic principle, has taken a quantum leap in the last decade. A key role in the elucidation of how the holographic duality functions has been played by ideas from quantum information theory. In particular, the modern understanding of the holographic dictionary is that it works as a quantum error correcting code./nIn this dissertation, we focus on a two-pronged approach to developing a deeper insight into the framework of quantum gravity. Firstly, despite the fact that we have learnt a lot about quantum gravity from AdS/CFT, it is not directly applicable to our universe which is an accelerating cosmological spacetime. Taking inspiration from the holographic principle and formulating ideas from AdS/CFT in the abstract language of quantum error correction, we take some preliminary steps in freeing ourselves from the crutches of AdS spacetimes and understanding features of holography in a wider class of spacetimes. We develop a framework for holography in general spacetimes using the Ryu-Takayanagi formula as a postulate and discuss conditions for bulk reconstruction, the existence of a bulk dual and qualitative features of putative holographic theories in arbitrary spacetimes./nSecondly, the holographic dictionary is not completely understood even within the realm of AdS/CFT. We clarify some aspects and propose novel entries to the AdS/CFT dictionary which shed light on how a gravitational description of a quantum mechanical system emerges holographically. In particular, this includes an understanding of how the holographic computation of Renyi entropy arises from a general feature of quantum error correction, supplemented by the special property that gravitational states have maximally mixed edge modes. Further, we resolve a long standing conjecture about the nature of tripartite entanglement of holographic states. Finally, we propose novel holographic duals to the reflected entropy in the presence of entanglement islands, and the Connes cocycle flow.

Advisor: Nomura, Yasunori