VictorJuiz/thesis huggingface dataset:
The Local Langlands Correspondence, Rapoport-Zink Spaces, and Shimura Varieties

The connection between the Langlands correspondence and the co-homology of Rapoport-Zink spaces and Shimura varieties has been the subject of extensive mathematical research over the past few decades. In this thesis, we extend the existing theory in two key ways. Firstly,we give an explicit combinatorial description of the cohomology of Rapoport-Zink spaces of EL-type, building off of earlier work by Harris–Taylor and Shin ([HT01], [Shi12b], [HT01]). Secondly, joint with Alex Youcis, we state a list of axioms for the supercuspidal local Langlands correspondence and prove that they characterize the correspondence in certain cases. The most important of our axioms arises naturally in the study of the cohomology of Shimura varieties and was first stated in work of Scholze and Scholze–Shin ([Sch13b], [SS13]). We verify these axioms in the case of unramified unitary groups.1

Advisor: Shin, Sug Woo
A Tale of Two Dictionary Learning Problems

Learning optimal dictionaries for sparse representation modeling has led to the discovery of characteristic sparse features in several classes of natural signals. However, universal guarantees of the uniqueness and stability of such features in the presence of noise are lacking. This work presents very general conditions guaranteeing when dictionaries yielding the sparsest encodings of a dataset are unique and stable with respect to measurement or modeling error. The stability constants are explicit and computable; as such, there is an effective procedure sufficient to affirm if a proposed solution to the dictionary learning problem is unique within bounds commensurate with the noise./nTwo formulations of the dictionary learning problem are considered. The first seeks a dictionary for which each signal in a dataset is well-approximated by a linear superposition of only a limited number of dictionary elements. In this case, existing guarantees are extended to the noisy regime to demonstrate that such dictionaries and the sparse representations they induce are almost always identifiable up to an error commensurate with the noise. Moreover, a theory of combinatorial designs is introduced to demonstrate this is the case even if the dictionary fails to satisfy the spark condition, the data are distributed over only a polynomial set of subspaces spanned by the dictionary, or (to some extent) even if the dictionary is overestimated in size./nThe second formulation of the problem seeks a dictionary which minimizes the average number of dictionary elements required to approximate each signal in the dataset. The guarantees in this case are the first of their kind in both in the noiseless and noisy regimes and derive from the fact that, given sufficient data, this second problem actually reduces to an instance of the first. Importantly, in both cases, no constraints whatsoever are imposed on learned dictionaries beyond a natural upper bound on their size./nThis work serves to justify, in principle, dictionary learning in general as a means of discovering latent sparse structure in real data. Though much work remains to be done deriving criteria for use in practice, the theoretical tools developed here should be of use to this end.

Advisor: Sommer, Fritz
Theoretical and Experimental Advances in the Development of Isochoric Cryopreservation Techniques

The realization of on-demand organ and tissue availability could yield a benefit to global health comparable to the curing of cancer, unleashing the full potential of modern transplantation science without its current geographic, socioeconomic, and technical limitations. However, a seemingly simple scientific problem has thus far restricted this reality: our inability to preserve organs outside the body for extended periods of time./nGenerally, in order to arrest the metabolism of an ex vivo biologic and prevent it from expiring, one must reduce its temperature to well below the freezing point of water (its principal material component). However, the formation of ice within complex vascularized systems proves catastrophic, and thus a wonderfully fundamental puzzle emerges: How can we prevent water from freezing, when equilibrium thermodynamics demand that it should freeze? Over the past 70 years, efforts to address this question have taken an overwhelmingly chemical approach. However, techniques driven by the use of cytotoxic non-physiological cryoprotectants to modulate freezing point has not yielded clinically-relevant advancements at the whole-organ scale to date, and thus a fundamentally different approach is needed./nThis thesis presents theoretical and experimental explorations of an alternative, non-chemical approach to cryopreservation based on the rich and unexplored thermodynamic and kinetic behaviors of water and ice confined under isochoric (constant-volume) conditions. We herein develop fundamental analytical tools with which to probe isochoric phase equilibria and nucleation kinetics across volumes; reveal critical consequences of water confinement at the micro- and macroscales; experimentally demonstrate previously unrealized phase behaviors in isochoric systems in stable equilibrium, metastable equilibrium, and non-equilibrium scenarios; provide initial biological validation of isochoric cryopreservation with whole mammalian organs and tissues; and evince the additional value of isochoric freezing processes in the food industry. We develop several distinct isochoric techniques for varied preservation applications and generate baseline thermodynamic data for each, which, alongside the biological results reported herein, we hope will serve as a foundation from which the community may further advance the unique domain of isochoric freezing.

Advisor: Rubinsky, Boris
The Application of Peircean Semiotics to the Elder Futhark Tradition: Establishing Parameters of Magical Communication

Abstract/nThe Application of Peircean Semiotics to the Elder Futhark Tradition:/nEstablishing Parameters of Magical Communication/nby/nScott T. Shell/nDoctor of Philosophy in German/nUniversity of California, Berkeley/nProfessor Irmengard Rauch, Chair/nThis dissertation addresses the issue of magical communication found in the Elder Futhark runic inscriptions. The study examines the Kragehul Spear Shaft (DR 196), Björketorp runestone (DR 360), the Horn(s) of Gallehus (DR 12), Gummarp runestone (DR 358), Lindholm amulet (DR 261), Straum whetstone (KJ 50), Ribe skull fragment (DR EM85; 151B), the Noleby runestone (KJ 67), and the Eggja runestone (N KJ 101). It seeks magical communication which may putatively be encompassed by my proposed law of magical semiosis, which reads:/nWhile operating within an Umwelt where we assume magic is a phaneron in the Weltanschauung of the Runemaster, he or she intentionally manipulates signs and sign-relations within a sign-network by the use of icons (like produces like), indices (contagious properties) and/or symbols (learned conceptual properties). While there will be more than one sign within the sign-network, it is the magical sign which is the most salient when working with such an object. This includes—but is not limited to—phonetic iconicity, semantic iconicity, indexical curses, iconic theophany formulas whereby the Runemaster becomes a god (degrees of iconicity), mythic reenactments, Begriffsrunen/n(symbolic indexical icons), and certain word-formulae especially alu ‘ecstatic state’ (disputed)./nI argue that, by setting objective parameters for measuring this law of magical communication, we can then determine whether or not a particular inscription should be understood as magical or non-magical specific to the Umwelt and Weltanschauung of the Runemaster. Essentially, this dissertation is meant to challenge runologists in postulating falsifiable criteria so we may, in an academic setting, discuss magical communication in the world of the Runemaster./nThis study begins by discussing how Charles Sanders Peirce can help provide us with a basic framework regarding the sign. His phenomenological framework is applied to the world of the Runemaster. The next section then addresses the problem with the word “magic,” which goes far beyond the concept of “if it does not make sense, it must be magical.” It then leads to a discussion of runes and numinous qualities and finally to a corpus chapter which applies the theories and methods I have adopted.

Advisor: Rauch, Irmengard
A Hitchhiker’s Guide to the Pleistocene Sea: Using Isotopic Analysis of Fossil Coronulid Barnacles to Reconstruct Prehistoric Whale Migration

Migration is an integral feature of modern mysticete whale ecology, and one that intricately links their behavior to the processes which shape the spatiotemporal distributions of oceanic productivity. Each year, mysticete whales travel thousands of miles to access seasonally productive, high-latitude waters where they feed in the summer before retreating to warm, low-latitude waters to breed and raise their calves in the winter. As the spatial and temporal distribution of oceanic productivity has shifted over geological timeframes, the changing demands of migration may have played key roles in shaping mysticete evolutionary history. And because mysticetes must rely on the most productive of waters to sustain their great mass, understanding how their migration routes have changed through time may also provide unique insight into productivity patterns in the ancient ocean./nUnderstanding what role migration may have played in mysticete evolution and using whale movements as a means of understanding prehistoric productivity patterns depends on having a reliable means of measuring migratory behavior in deep time, yet little is currently known of prehistoric whale migrations. My research seeks to address this knowledge gap via isotopic analysis of coronulids, the commensal barnacles which live attached to the skin of some mysticete lineages. As these barnacles grow, each new shell layer preserves an isotopic signature of the water in which it was formed, providing a mechanism by which to reconstruct the migration of the host whale. I first verify the reliability of the method by demonstrating that isotopic information from modern coronulids accurately reflects the known migratory paths of their host whales. Next, I show that migration was a widespread phenomenon by the Pleistocene, where every sampled population indicates evidence of migration. I then combine isotopic analysis with paleoceanographic modeling to constrain the migratory paths taken by several Pleistocene whales. Along the way, I discuss the implications of an unexpected and unique fossil discovery that could alter our understanding of one mysticete lineage’s evolutionary history.

Advisor: Finnegan, Seth
Characterizing Extreme Weather in a Changing Climate

Climate change is arguably one of the most pressing challenges facing humanity in the 21st century. Over the past three decades, substantial progress has been made in characterizing the changes in earth's mean climate state under a range of global warming scenarios. However, individuals and governments across the world are now interested in \emph{changes to the extremes} of the climate system. The tails of the distribution, typically associated with extreme weather patterns such as tropical cyclones, atmospheric rivers and extra-tropical cyclones are highly impactful, and cause major disruption to human life, property and economy. This thesis makes an attempt to address the following question: \emph{How will extreme weather events change in the future?}/nIn order to address this question, we first need to address how extreme weather events are identified in climate datasets. For over four decades, climate analysts have applied heuristics on spatial and temporal summaries of complex datasets to identify events. This thesis makes the following major advances in bringing the field of climate analytics to the 21st century: First, we develop the TECA (Toolkit for Extreme Climate Analytics) framework and enable heuristic-based analysis of O(10) TB datasets in 10s of minutes. Second, we introduce Deep Learning to the climate science community, and showcase state-of-the-art results in pattern classification, detection and segmentation. Our Deep Learning implementations have been scaled to the largest CPU- and GPU-based HPC systems in the world; these achievements being recognized by the ACM Gordon Bell Prize in 2018./nPowered by these new capabilities, we characterize changes in the frequency and intensity of tropical cyclones, atmospheric rivers and extra-tropical cyclones in a variety of historical, reanalysis and climate change runs. Deep Learning-powered segmentation provides us with the capability to conduct precision analytics of precipitation \emph{conditional} on these weather patterns. We report on thermodynamic and dynamic mechanisms behind changes in extreme precipitation.

Advisor: Collins, William D
Parameter Estimation in Electrochemical Li-ion Battery Models

This dissertation focuses on novel parameter estimation techniques in electrochemical Li-ion battery models. From electric vehicles and grid energy storage to advanced robotics and mobile electronics, Li-ion batteries have served as an enabling technology across many industries. Within these applications, a battery management system (BMS) is responsible for monitoring the battery’s condition, providing safety measures such as high voltage isolation, and facilitating charging and discharging according to the system demands. Importantly, the battery performance and safety metrics of interest e.g. state-of-charge (SOC), state-of-health (SOH) are unmeasureable; this motivates a model-based approach to estimating internal states and parameters in order to track and control these metrics./nFor any model-based application, parameter estimation represents a core challenge. In electrochemical Li-ion battery models, estimation is particularly difficult due to overparameterization, inherent non-convexity, and an inability to easily validate estimates. Furthermore from a research perspective, parameter estimation stands as the most important, unsolved problem. Novel methods for parameter estimation are necessary to enable reliable SOH estimation and extend existing research areas such as SOC estimation and fast charging, which are dependent on accurate parameter estimation. The work presented in this dissertation analyzes two parameter estimation scenarios: offline and online. For the offline parameter estimation problem, Ch. 2 presents a novel methodology based on optimal experimental design (OED) for performing the initial parameterization of the Doyle-Fuller-Newman (DFN) model. Ch. 3 analyzes the online parameter estimation problem using both the DFN and the Single Particle Model with Electrolyte and Thermal (SPMeT) dynamics. A simulation study is performed to demonstrate how sensitivity analysis can be used to improve estimation. It is shown that a reduced order model can be used to approximate the sensitivity calculation in a computationally tractable way. Additionally, safety challenges associated with common approaches in literature to parameter estimation are highlighted. Highly relevant to the parameter estimation problem, Ch. 4 rigorously evaluates which sensor combinations are best for estimating lithium-ion battery internal states related to SOC and SOH. Overall, this work demonstrates methods for analyzing, solving, validating, and enhancing (via novel sensors) parameter estimation techniques in electrochemical Li-ion battery models.

Advisor: Moura, Scott J
Zohdi, Tarek I
Essays in Behavioral and Labor Economics

This dissertation uses tools from behavioral and labor economics to study longstanding questions about people and policies./nThe first chapter, co-authored with Evan K. Rose, provides a comprehensive look at what happens to criminal offending around childbirth, marriage, and divorce for women and men. Our event study analysis suggests that pregnancy is a strong inducement for fathers and especially mothers to reduce criminal behavior. For mothers, criminal offending drops precipitously in the first few months of pregnancy, stabilizing at half of pre-pregnancy levels three years after the birth. Men show a 25 percent decline beginning at the onset pregnancy; however, domestic violence arrests spike for fathers immediately after the birth. A design using stillbirths as counterfactuals suggests a causal role for children. In contrast, marriage marks the completion of a 50 percent decline in offending for both men and women. Finally, people headed for divorce show relative increases in crime following childbirth and marriage. The patterns in drug offenses for new mothers are consistent with a Beckerian model of habit formation./nIn the second chapter, I use a new dataset on unemployment insurance recipients to study the effects of benefits on search behavior. In a regression kink design, I find that monetary weekly benefits have a positive effect on unemployment duration but no impact on search behaviors. As evidence against misreporting, I show that reservation wages predict reemployment wages and decrease with unemployment duration and the local unemployment rate. These results suggest that explicitly measured search behaviors may not explain the duration response to benefits.

Advisor: DellaVigna, Stefano
Simulation and Optimization of Fused Deposition Modeling

Since their invention decades ago, various kinds of additive manufacturing (AM) methods have emerged. In recent years additive manufacturing has been growing very rapidly as the technology matures and the cost of production declines. One of the first AM methods, fused deposition modeling (FDM) has evolved with more capable printers and novel materials/nmaking significant progress towards industrialization of the process. However, as it stands now, a lack of understanding of the fundamental physics during the additive manufacturing process leads to some severe drawbacks. For example, additively manufactured parts can suffer from low finish quality and prohibitively long production time./nNumerical simulation has been very helpful in understanding and designing traditional manufacturing processes, such as metal forming and welding. It has huge potential in AM as well. Gaining key knowledge pertaining to the printing process, such as the temperature/nfield change, will help build better printers and enable designers to achieve design goals such as minimum residual stress or surface roughness. As a result, research interest in reliable, robust and efficient numerical models for additive manufacturing has surged in the last decade./nThe objective of this dissertation is to establish a coupled thermomechanical finite element model that accurately simulates the FDM process and computes quantities of interest, such as the shape error. The temperature and deformation history is taken into consideration when depositing new material. The results of two-dimensional example problems are discussed and/ncompared with those from an uncoupled finite element model. In addition, a parameterized PDE-constrained (partial differential equation) optimization study based on the simulation model is performed. Algorithms designed with knowledge gained from the simulation are proposed to find optimal solutions.

Advisor: Papadopoulos, Panayiotis
Improving Student Nutrition through a School Dining Redesign: A Mixed-Methods Evaluation

Despite the link between school-lunch participation and student health, only half of adolescents with the program in their schools participate on a given day. A multi-pronged school lunch promotion intervention was implemented in middle and high schools in an urban, low-income school district to improve school lunch participation and reduce food waste. This dissertation assesses the impact of the intervention on student and teacher perceptions of school lunch and explores how leadership shaped intervention implementation./nUsing student survey data, paper 1 explores the theoretical pathways (perceptions of school-lunch quality and convenience) through which the intervention was expected to increase school-lunch participation and decrease plate waste. We observed modest changes in perceptions of school-lunch quality and no changes in perceptions of school-lunch convenience. Results suggest that additional efforts are needed to improve school-lunch participation and dietary intake./nPaper 2 utilizes teacher survey data to assess the impact of the intervention on teacher perceptions, modeling, and encouragement related to school lunch. Results indicate that the intervention had a modest effect on teacher-reported frequency of eating in the cafeteria with students and on encouraging students to participate in the school lunch program. There was no change, however, in teacher perceptions of or participation in the school lunch program. The paper concludes that improvements in teacher perceptions of school meals may not be needed in order for teachers to promote the school-lunch program to students./nPaper 3 focuses on the implementation of the intervention. Through qualitative interviews, the paper characterizes implementation leadership in the context of the intervention; and contextualizes emergent findings in the existing implementation science literature. Four major themes emerged reflecting the ways in which leaders are perceived to influence implementation effectiveness: (1) leader understanding of the technical and operational details of the intervention; (2) leader ability to develop and communicate intervention plans; (3) leader supervisory oversight over implementation staff and contractors; and (4) leader acknowledgment that ‘innovation’ requires time and stakeholder input —the absence of which can threaten cohesion and buy in. Implementation leadership functions in a school nutrition context appear similar to those identified in the implementation science literature. Results are the first to illustrate how these leadership dimensions are performed in a school nutrition setting.

Advisor: Madsen, Kristine