VictorJuiz/thesis huggingface dataset:
Endoplasmic reticulum remodeling during budding yeast meiosis

The endoplasmic reticulum (ER) is a membrane-bound organelle that carries out a range of essential cellular functions, from protein trafficking to lipid homeostasis to inter-organelle signaling. These functions rely on the maintenance of an intricate membrane architecture that is rapidly remodeled in response to changes in cellular demand, such as the presence of external stressors or the onset of cell differentiation. Work in the last fifteen years has greatly expanded our knowledge of how ER membranes are shaped in unperturbed cells, but mechanisms controlling dynamic ER remodeling under changing conditions, especially during cell differentiation, are not well understood. Here, we use budding yeast meiosis as a model system to study gene regulation and ER remodeling in a developmental context./nIn chapter 2, we identify a series of developmentally regulated changes in ER morphology and composition that simultaneously control organelle inheritance and degradation. During meiosis, the cortical ER undergoes reticulon-dependent fragmentation before dramatically collapsing away from the plasma membrane (PM). While the vast majority of ER collapses during this process, a subset of ER fragments is retained at the cell cortex via ER-PM tethering proteins and thereby excluded from gametes. Cortically retained ER is degraded late in spore packaging, while collapsed ER is subject to selective autophagy, indicating that multiple parallel pathways exist to eliminate unwanted ER during meiosis. These findings raise new questions about the role of ER remodeling events in developmental quality control, which we discuss in chapter 3./nIn chapter 4, we leverage a genomics approach to address a fundamental question in gene regulation: why does mRNA expression often fail to predict protein abundance? Using global parallel measurements of mRNA abundance, translation, and protein levels over the course of meiosis, we identify genes with poor mRNA:protein correlation over time. We show that hundreds of these genes are regulated by transcript isoform toggling, in which a poorly translated extended transcript isoform prevents expression of an efficiently translated canonical isoform. Thus, apparent transcriptional upregulation can lead to protein downregulation in an isoform-dependent manner, with important implications for the interpretation of genomics datasets.

Advisor: Brar, Gloria A
Practical Algorithms for Reliable Autonomy

In this dissertation, I present several ideas for building practical algorithms for building more reliable autonomous systems. That is, each of the ideas below is, from the outset, designed to be physically implementable on real hardware and operate in real-time. In Chapter 1, I provide a high-level overview of some of the key challenges in autonomy today and how this work addresses some of those challenges. Chapter 2 presents an approach for reachability-based robust motion planning, which for the first time attains adversarial robustness for real-time motion planning problems. Chapter 3 introduces the prediction problem which arises in multi-agent situations, and describes a Bayesian approach for determining how confident one should be in a given predictive model. Chapter 4 combines elements of the prediction and motion planning problems in a multi-player differential game and presents a novel real-time solution strategy. Finally, Chapter 5 lists several open problems and discusses several exciting next steps.

Advisor: Tomlin, Claire J
Design Principles for Trap-Free Cesium Lead Halide Perovskite Nanocrystals

This dissertation will introduce a general surface passivation mechanism for cesium lead halide perovskite materials (CsPbX3, X = Cl, Br, I) that is supported by a combined experimental and theoretical study of the nanocrystal surface chemistry. A variety of spectroscopic methods are employed together with ab initio calculations to identify surface halide vacancies as the predominant source of charge trapping. The number of surface traps per nanocrystal is quantified by 1H NMR spectroscopy, and that number is consistent with a simple trapping model in which surface halide vacancies create deleterious under-coordinated lead atoms. These halide vacancies exhibit trapping behavior that differs between CsPbCl3, CsPbBr3, and CsPbI3./nAb initio calculations suggest that introduction of anionic X-type ligands can produce trap-free band gaps by altering the energetics of lead-based defect levels. General rules for selecting effective passivating ligand pairs are introduced by considering established principles of coordination chemistry. Introducing softer, anionic, X-type Lewis bases that target under-coordinated lead atoms results in absolute quantum yields approaching unity and monoexponential luminescence decay kinetics, thereby indicating full trap passivation. This work provides a systematic framework for preparing highly luminescent CsPbX3 nanocrystals with variable compositions and dimensionalities, thereby improving fundamental understanding of these materials and informing future synthetic and post-synthetic efforts towards trap-free CsPbX3 nanocrystals.

Advisor: Alivisatos, Armand P
Identification of Proteins Responsible for Rapid Displacement of Cas9 from DNA

Cas9 is a prokaryotic RNA-guided DNA endonuclease that binds substrates tightly in vitro but turns over rapidly when used to manipulate genomes in eukaryotic cells. Little is known about the factors that physically interact with or dislodge Cas9 from DNA and how these factors might influence genome engineering tools. I first attempted to identify Cas9 displacement factors by repurposing Cas9 as a proximity sensor in live human cells. In order to reduce the noise derived from unbound Cas9 molecules, I subsequently used cell-free Xenopus laevis egg extract whose lack of a plasma membrane allowed me to tightly control the ratio of Cas9 to its substrate. Label-free proteomics identified the dimeric histone chaperone facilitates chromatin transcription (FACT) as an interactor of substrate-bound Cas9. FACT is both necessary and sufficient to displace dCas9, and FACT immunodepletion converts Cas9’s activity from multi-turnover to single-turnover. In human cells, FACT depletion extends dCas9 residence times, delays genome editing, and alters the balance between indel formation and homology directed repair. FACT knockdown also increases epigenetic marking by dCas9-based transcriptional effectors with a concomitant enhancement of transcriptional modulation. FACT thus shapes the intrinsic cellular response to Cas9-based genome manipulation most likely by determining Cas9 residence times.

Advisor: Corn, Jacob E
Dueber, John E
Succinct Non-Interactive Arguments for Arithmetic Circuits

This thesis describes a family of new constructions of "succinct" non-interactive arguments (SNARGs) for arithmetic circuit satisfiability. An argument is a protocol by which a prover can convince a verifier of the truth of some statement; in this work, the statement will be of the form "there exists w such C(x,w) = 1", where C is an arithmetic circuit. By "succinct", we mean that the communication is polylogarithmic in the size of C./nAll of these constructions are unconditionally secure in the random oracle and quantum random oracle models. In particular, they do not require any private setup. This is achieved in each case by designing an interactive oracle proof and then applying a transformation of Ben-Sasson, Chiesa and Spooner. We show that our argument systems are both asymptotically efficient and feasible in practice, demonstrating the usefulness of this approach./nMore specifically, we obtain the following./n1. A succinct non-interactive argument (Aurora) for general arithmetic circuits, with verification time linear in the size of the circuit./n2. A succinct non-interactive argument for "structured" arithmetic circuits, with verification time polylogarithmic in the size of the circuit./n3. A succinct non-interactive argument with preprocessing (Fractal) for general arithmetic circuits, where the verification time (after offline preprocessing) is polylogarithmic in the size of the circuit.

Advisor: Chiesa, Alessandro
Abstract Causal Inference in Early Childhood

Like many animals, human children learn about the causal structure of the environment and the corresponding opportunities it affords them. Unlike other animals, human children grow up to possess highly abstract causal reasoning abilities that enable to design space stations, write screenplays, and develop scientific theories. What are the ontogenetic origins of humans’ powerful causal imagination?/nExisting work suggests that children between the ages of one and five years old are already prodigious causal reasoners. Very young children rapidly infer causal rules from patterns of statistical contingency between cause and effect, and they readily generalize those rules to novel stimuli. By the preschool years, children are able to determine which of several causes may be responsible for an effect. They reason about evidence from observation and intervention to make causal attributions, and they are able to posit the presence of causal variables they have not yet observed./nHowever, while this literature demonstrates that young children are capable of sophisticated reasoning that enables them to attribute causes to known effects, it does little to illuminate the mechanisms by which human children may infer novel effects—i.e., new outcomes and possibilities. What early, abstract causal inferential abilities do children possess that may develop into the highly abstract causal imagination we see in mature adults?/nIn this dissertation, we argue that two- to five-year-old children are able to learn from evidence about “difference-making” to make abstract inferences that permit them to imagine and generate novel causal outcomes. In Study 1, we demonstrate that three- to five-year-olds are able to transfer knowledge about difference-making variables in one causal system to a similar system with new values of those variables to generate a new effect they have never seen. In Studies 2 and 3, we demonstrate that preschoolers and toddlers are able to infer abstract relational concepts about changes in effect variables in order to predict (Study 2) and generate (Study 3) novel outcomes to solve novel problems. The results of these studies contribute to the developmental causal reasoning literature by demonstrating that abstract causal inference in early childhood is sophisticated not only in terms of causal attribution, but also in imagining genuinely new possibilities.

Advisor: Gopnik, Alison
Toxins of the death cap mushroom, Amanita phalloides

Unlike animals, plants and fungi are largely sessile, and can not move to protect themselves from natural enemies. Instead, they produce a suite of secondary metabolites, ranging from caffeine in coffee, to psilocybin in magic mushrooms, to the spice in chili peppers. Humans have long exploited such compounds for medical use. However, little work has been devoted to understanding the role such secondary chemistry plays in the natural environment. Here, we explore the medical and ecological role of secondary metabolites of a notorious fungus, the death cap mushroom, Amanita phalloides. We first synthesize the medical research, digging deeper into the molecular mechanisms of treatments for amatoxin poisoning, and use these mechanisms to evaluate some of the conflicting medical advice surrounding amatoxin treatment. We then present an extraction protocol that saves time, reduces equipment contamination, and minimizes risk to the researcher. The impact of this faster, safer method may help produce these important toxins faster, for both research and medical use. We also examine toxin levels across several scales in California. Levels of alpha-amanitin are on the high end of published European values, indicating that either this invasive species underwent a genetic bottleneck from an area of Europe with high toxin levels, or A. phalloides may be under active selection to increase toxin levels in its introduced range.

Advisor: Bruns, Thomas
Essays on Labor Economics

This dissertation studies the impact of different policies implemented within the sphere of education in Chile. The first chapter, written jointly with Maria Angélica Bautista, Felipe González, Luis Martínez, and Mounu Prem, studies the capture of higher education by the military dictatorship of Augusto Pinochet. Results show that: (i) cohorts that reached college age shortly after the coup experienced a large drop in college enrollment, mostly as a result of the persistent reduction in the number of openings; (ii) these cohorts had worse economic outcomes throughout the life cycle and struggled to climb up the socioeconomic ladder, especially women; (iii) children with parents in the affected cohorts had higher dropout rates in high school and a lower probability of college enrollment. The second chapter, written jointly with Alonso Bucarey and Dante Contreras, studies the labor market returns to a state-guaranteed loan used to finance university degrees. Results from a regression discontinuity design show that: (i) marginally eligible students forgo vocational education in favor of universities but reduce their probability of graduation; (ii) even though university loan takers accumulated more student debt, their labor market outcomes are not different from those of ineligible students; (iii) the lower quality of the institutions receiving these marginal students plausibly explain the later result. In the third chapter, written jointly with Mounu Prem, we study the productivity and labor market of school principals. Using data on the universe of students and school personnel, we show that: (i) there is substantial variation across principals in their ability to improve students' learning; (ii) effective principals are recognized by the school community, increase the retention of teachers, and receive higher wages especially in private schools; (iii) despite relatively rigid wages, public schools can attract better principals by improving personnel selection.

Advisor: Card, David
Sparse-Graph Codes for the Big Data Era: Exploiting Sparsity to Speed Up Computation

We are witnessing an unprecedented growth in the amount of data being sensed, collected and processed to drive modern applications across many domains. This growth has challenged classical algorithms to scale up to big-data regimes. Because time is critically important in settings such as control and decision-making, interventional medical imaging, and security, speeding up widely-used routines has the potential to open up the application space./nIn this thesis, we focus on six problems of fundamental importance, and develop fast algorithms for solving them whenever there is an underlying structure of sparsity, which typically holds in most natural settings. Our algorithms attain their speed by being sample and computationally efficient whenever there is sparsity. In particular, the problems we study and a summary of our results are as follows. (1) We propose a novel architecture for sampling continuous-time signals that have band-limited and sparse spectra at their minimum sampling rate, which can be much lower than the Nyquist rate. (2) We improve the noise robustness of divide-and-conquer-based sparse Discrete Fourier Transform algorithms by developing a novel method for fast and sample-efficient frequency identification. (3) We develop a fast algorithm for recovering sparse wavelet coefficients of a signal from its Fourier domain samples. This setting arises in Magnetic Resonance Imaging, and our approach provides a theoretical framework for fast imaging. (4) We propose a sample and computationally efficient algorithm for recovering sparse pseudo-Boolean functions with application to learning a DNA repair outcomes for CRISPR-Cas9 experiments. (5) We propose a computationally efficient method for coded computation to reduce the effect of slow computational nodes in distributed matrix multiplication. (6) We propose a computationally efficient algorithm for large-scale matrix multiplication whenever the output is sparse with application to database search./nOur approach in tackling these diverse problems is based on a unifying divide-and-conquer strategy, where by leveraging ideas from modern coding theory (in particular, Low Density Parity Check Codes) which have previously been studied in the context of communications, we create structures that enable simple and fast peeling-based recovery.

Advisor: Ramchandran, Kannan
Deep Generative Models: Imitation Learning, Image Synthesis, and Compression

Machine learning has its roots in the design of algorithms that extract actionable structure from real world data. For high dimensional and high entropy data, machine learning techniques must cope with a fundamental tension arising from the curse of dimensionality: they must be computationally and statistically efficient despite the sheer size of the exponentially large spaces where meaningful signal is hidden. This thesis explores and attempts to resolve this tension in deep generative modeling./nThe first part of this thesis addresses imitation learning, the problem of reproducing the behavior of experts acting in dynamic environments. Supervised learning, to predict expert actions from states, suffers in statistical efficiency because large amounts of expert data are required to prevent action prediction errors from compounding over long behaviors. We propose a resolution in the form of an algorithm that learns a policy by matching the expert's state distribution. During learning, our algorithm continually executes the policy in the task environment and compares its states to the expert's on a gradually learned reward function. Allowing our algorithm to interact with the environment during training in this manner allows it to learn policies that stay on expert states even when expert data is extremely scarce./nThe second part of this thesis addresses modeling and compressing natural images using likelihood-based generative models, which are generative models trained with maximum likelihood to explicitly represent the probability distribution of data. When these models are scaled to high entropy datasets, they become computationally inefficient to employ for downstream tasks like image synthesis and compression. We present progress on these problems in the form of developments in flow models, a class of likelihood-based generative models that admit fast sampling and inference. We reduce flow model codelengths to be competitive with those of other types of likelihood-based generative models. Then, we develop the first computationally efficient compression algorithms for flow models, making our improved codelengths realizable in practice with fully parallelizable encoding and decoding.

Advisor: Abbeel, Pieter
Early Seventeenth Century Nahua Poetics: Domingo Chimalpahin and the Cemanahuac Archive

My dissertation examines the writings of don Domingo Chimalpahin, a Nahua intellectual who produced a large body of written texts in Nahuatl and Spanish in the sixteenth and seventeenth centuries. My study reframes his work as an Indigenous intellectual project that safeguards the history of Cemanahuac—the Nahua Indigenous world—and preserves for future generations of Nahuas and their descendants the possibility to reclaim their history, government institutions, and land. As such, the archive Chimalpahin compiles and produces forces us to rethink Indigenous intellectual production during a critical time in which the very existence of Indigenous peoples of New Spain was at risk. My dissertation argues that Chimalpahin continues and expands the tradition of an earlier generation of Nahua tlacuiloque—scribes—who painted and wrote in Nahuatl for Nahua readers of the future. My study illustrates that Chimalpahin transcends the altepetl-centered histories of his predecessors and refutes Spanish historiography by revising the narratives of Spanish authors while putting Indigenous history in global context. This intellectual project, I show, entails an alternative political and cultural history rooted in the perspective of an Indigenous commoner./nMy dissertation contributes to scholarship on colonial Latin America by focusing on a time period often neglected or seen as uneventful. Most specifically, it centers on Indigenous voices to illuminate an alternative intellectual project of self-preservation and self-determination that challenges the views of Spanish intellectuals and Indigenous authors appealing to the Spanish Crown as well as Christian friars writing about the history of New Spain.

Advisor: Del Valle, Ivonne
Duality for boolean algebra expansions and its applications

This dissertation consists of four largely independent chapters. The first two chaptersconcern counterparts of classical theorems in modal logic in more general semantics: the Sahlqvist Correspondence Theorem inter alia for possibility semantics in Chapter 1 and the Goldblatt-Thomason Theorem and Fine’s Canonicity Theorem for neighborhood semantics in Chapter 2. Chapter 3 contains various results on Heyting algebras, among which is the topological-dynamical study of the automorphism group of the smallest existentially closed Heyting algebra. The last chapter establishes choice-free duality between the category of ortholattices and a category of certain spectral spaces.

Advisor: Holliday, Wesley H
Establishing the Legal Framework for Crowdfunding in China

Crowdfunding is a rapidly growing means of raising capital from a largecrowd of people via the internet. In the U.S., Title III of the JOBS Act exempts offerings using crowdfunding from registering with SEC. To implement the statutory exemption, SEC issued Regulation Crowdfunding (Reg CF). Reg CF imposes certain obligations on issuers, investors, and funding portals. Now in the U.S., offerings using crowdfunding proliferate. Among all these offerings, common stock, debt, and Simple Agreement for Future Equity (SAFE) are the most-issued types of securities. Revenue sharing note becomes a marked type of debt securities. The SAFE is a convertible security that can convert into equity security, in most cases, preferred stock. It is widely used in crowdfunding offerings and has two variants. Meanwhile, it also gives rise to suspicion over its safety, and even SEC’s failed attempt to ban its use in crowdfunding offerings. However, its popularity shows no sign of decline. In contrast, in China, crowdfunding industry used to prosper but now is dying due to regulatory clampdown. To resurrect the industry, two legal loopholes in China Securities Law (CSL) should be corrected. The first is only a modicum of securities are governed by CSL. Notes and SAFEs are outside of CSL’s reach. The second is CSL’s numeric benchmark for a public offering is neither scientific nor reasonable. But overall, the priority is to provide a statutory exemption for crowdfunding offerings in China. Reg CF and a rich body of relevant cases in the U.S. could be useful for China’s rulemaking undertakings in crowdfunding.

Advisor: Krishnamurthy, Prasad