VictorJuiz/thesis huggingface dataset:
Learning through Litigation: How Judicial Process Shapes Decision Making in the U.S. District Courts

The U.S. District Courts resolve the vast majority of cases in the U.S. federal legal system, but we know much less about them than we do about the U.S. Courts of Appeals or the U.S. Supreme Court. The disproportionate focus on appellate courts has reinforced the perception that courts are primarily policymaking institutions. However, district courts rarely make new law, and are mostly at the front line of law enforcement. In the aggregate, the quality of their decisions on individual cases determines the degree to which laws are applied fairly and consistently. However, their work is not trivial, and the quality of outcomes depends on whether district judges have sufficient incentives to produce high quality decisions. Indeed, district courts are the primary fact-finders in legal disputes. Judges often have to cajole litigants, witnesses and attorneys into being forthcoming about what they know. They have to rule on a flurry of motions about what information can be discovered or admitted as evidence. District judges are therefore intricately involved in creating the case records, which means that they must engage in some costly effort to figure out the facts of cases they oversee./nA district judge's work on any given case constitutes a process of "learning through litigation." The importance of this process for the enforcement of laws is the point of departure for this dissertation. In a series of three papers, I analyze the agency problem confronting appellate courts: how can district judges be induced to undertake maximum effort to learn the facts and the law pertaining to the legal cases before them when this effort is costly, but imperfectly observed by principals in the appellate courts? Moreover, what are the consequences for litigants (and society more broadly) of district court institutions and practices that serve to induce effort and compliance by district judges?/nTo address these questions, I analyze three original models of district court decision making. The models present three main takeaways: (1) due to their informational advantage, deferring to district judges is often optimal for appellate courts, even when those judges are biased; (2) dispassionate judges are often harder to motivate to exert effort to resolve cases than either activist or biased judges; (3) endogenous appeals by litigants can provide perverse incentives to unbiased "legalist" judges to tilt judgments toward powerful litigants. Moreover, the models I study in these papers offer observationally equivalent explanations for commonly observed empirical phenomena, such as compliance with legal doctrine and in-group bias. Taken together, the models underscore the important role that courts play in enforcing laws effectively and accurately. Indeed, if there is significant variation in district judges' effort to resolve cases, then laws will be enforced inconsistently. Perhaps more insidiously, the results suggest that low quality decision making by district judges may affect different kinds of litigants differently.

Advisor: Gailmard, Sean
Signal-based Bayesian Seismic Monitoring

This thesis presents a new approach to seismic monitoring, the task of detecting seismic events from potentially noisy and cluttered signals recorded across multiple stations. Unlike previous work, which represents seismic signals by a lossy set of discrete detections, we specify a generative probability model of raw seismic waveforms, incorporating a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. Inference in this model recovers the qualitative behavior of geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a network of stations./nOur model of seismic signals combines physically meaningful latent variables such as phase travel times, amplitudes, and signal decay rates, with data-driven models based on historical signals. Detailed waveform structure is represented using Gaussian process models of wavelet coefficients, encoding a general assumption that seismic signals are spatially corre- lated, and allowing us to detect and locate events even from weak signals at a single station. We show that the wavelet coefficients can be marginalized out using message passing applied to a state-space representation of the signal model, allowing for practical inference using a reversible jump Metropolis-Hastings algorithm./nWe evaluate our system, SIGVISA (Signal-based Vertically Integrated Seismic Analysis), on a task of monitoring the western United States for a two-week period following the magnitude 6.0 event in Wells, NV in February 2008. During this period, SIGVISA detects between two to three times as many events as detection-based systems, while reducing mean location errors by a factor of four. We provide evidence that SIGVISA detects some events that are missed even by the regional monitoring networks that we use as a ground-truth comparison. A primary driver of monitoring research is the verification of nuclear test ban treaties, which are particularly concerned with detecting events in regions with no nearby historical seismicity. In our experiments, SIGVISA matches or exceeds the detection rates of existing systems for such events, and even detects a number of such events missed by human analysts.

Advisor: Russell, Stuart J
A combinatorial approach to the q,t-symmetry in Macdonald polynomials

Using the combinatorial formula for the transformed Macdonald polynomials of Haglund, Haiman, and Loehr, we investigate the combinatorics of the symmetry relation H_mu(X;q,t)=H_{mu*}(X;t,q). We provide a purely combinatorial proof of the relation in the case of Hall-Littlewood polynomials (q=0) when mu is a partition with at most three rows, and for the coefficients of the square-free monomials in X={x_1,x_2,...} for all shapes mu. We also provide a proof for the full relation in the case when mu is a hook shape, and for all shapes at the specialization t=1. Our work in the Hall-Littlewood case reveals a new recursive structure for the cocharge statistic on words.

Advisor: Haiman, Mark D
Songs of the Self: Authorship and Mastery in Minnesang

Despite the centrality of medieval courtly love lyric, or Minnesang, to the canon of German literature, its interpretation has been shaped in large degree by what is not known about it—that is, the lack of information about its authors. This has led on the one hand to functional approaches that treat the authors as a class subject to sociological analysis, and on the other to approaches that emphasize the fictionality of Minnesang as a form of role-playing in which genre conventions supersede individual contributions. I argue that the men who composed and performed these songs at court were, in fact, using them to create and curate individual profiles for themselves. The project of these poets is to persuade the audience of their own ethical insight and aesthetic skill. Each, in his own way, seeks to portray himself as the master of all possibilities offered by courtly song./nIn chapter one, using the manuscript versions of a song by Heinrich von Morungen, I develop a new concept of authorship for the unstable medium of medieval lyric. Drawing on the insights of Material Philology, I show that Morungen anticipated and made use of this instability (or mouvance), imbuing his songs with the imprint of his authorship in a way that allows for the vagaries of oral and even written transmission. In chapter two, I explore the tension between a stable author figure and an unstable medium. Modern editorial practices have oversimplified the transmission of the lyric of Reinmar der Alte in the service of an exaggerated image of him as the virtuoso of joy in suffering unrequited love. Through a close reading of four versions of one of Reinmar’s songs, I argue that the author emerges as the master of the sum of a flexible array of aesthetic and ethical possibilities. In chapter three, I use the conceptual framework developed in these close readings to sketch a broader picture of one poet as an author. Through a survey of Heinrich von Veldeke’s songs, I show that juxtaposing contrasting perspectives throws into relief the implied author as a clerically educated figure who has mastered varied domains of intellectual and aesthetic knowledge and skill. By means of a comparison with the Latin poetry of Peter of Blois, I sharpen the contours of Veldeke’s mode of clerical authorship. The form of authorship that I identify in this dissertation—the author as master of possibilities—is specific to Minnesang, but suggests that there are types of authorship particular to other genres and other moments in time that remain to be defined.

Advisor: Largier, Niklaus
Service Operations in the Presence of Strategic Consumer Behavior

This dissertation analyzes pricing and information provision in the presence of strategic consumer behavior, with a focus on service industries. Using both analytical and empirical methods, I analyze two tools that firms may use to match supply with demand when customers are strategic: reservation no-show fees and inventory announcements./nFirst, I study a common problem in the service sector: reservation no-shows. Many firms allow customers to make reservations for service at a specified time in the future. Reservations are valuable to consumers because they insure against the service not being available, but are costly for the firm because valuable capacity may be held for customers who fail to show up. No-show fees, payable only if a reservation-holder fails to show up in the service period, are one tool that firms can use to mitigate the loss from wasted capacity. I analyze the performance of a no-show fee pricing scheme for a capacity-constrained service firm in a market with both forward-looking customers and a walk-in demand segment. I characterize three types of optimal policies that emerge in equilibrium and examine the social welfare implications of charging an optimal fee. In equilibrium, social welfare may strictly increase under a no-show fee policy; that is, the utility gain from using a no-show fee to allocate capacity more efficiently may be greater than the cost it imposes on consumers./nIn the second half of the dissertation, I analyze the information content and sales impact of inventory announcements, i.e. messages such as ``3 seats left at this price.'' I use an expansive original dataset to study the impact of these announcements in the market for airline tickets. My data include itinerary listing and seat map information/nfor thousands of flights on three major U.S. carriers, with travel dates in the winter and spring of 2015. I measure the ``informativeness'' of announcements, which I define as their ability to improve customer predictions of future price changes, and estimate the impact that these messages have on ticket sales. I find that announcements contain significant information about future price changes (both direction and magnitude), and are most informative early in the booking horizon. To measure the customer response, I use an instrumental variables model to address potential endogeneity between sales and announcements. My findings provide evidence that for at least some airlines, consumer ticket purchases increase immediately after new inventory messages, a result that is consistent with rational consumer behavior.

Advisor: Feldman, Pnina
Sequencing-based computational methods for identifying impactful genomic alterations in cancers

Recent advances in collecting sequencing data from tumors is promising for both immediate individual patient treatment and investigation of cancer mechanisms. A resultant central goal is identifying changes in tumors that are impactful towards these ends. Here, we develop two tools to identify impactful changes at different levels. We develop both methods in the context of gliomas, a common form of brain cancer. Firstly, we develop and assess a tool for assessing the impact of fusion genes, a type of common mutation using RNA-sequencing data. We validate the tool by working with collaborators in The Cancer Genome Atlas. Secondly, we develop a tool for an overall assessment of patient outcome by integrating data from diverse sequencing platforms. We validate this tool using simulation, data from consortiums, and collaborators at UCSF.

Advisor: Pachter, Lior
Designing custom organelles in bacteria

Despite the vast array of enzymatic activities available to metabolic engineers, many biosyntheses are impractical due to the production of toxic intermediates and off-target products, poor kinetic performance, and cofactor imbalances. We aim to address these roadblocks by organizing biosynthetic pathways inside custom organelles within cells. Bacterial microcompartments, porous proteinaceous organelles found in Salmonella and other bacteria, provide an ideal starting point for the engineering of subcellular bacterial organelles. To this end, we develop tools for the control of microcompartment formation, enzyme encapsulation, and small molecule transport across the compartment shell. Of particular interest is the encapsulation of enzymatic pathways that synthesize fuels, pharmaceuticals, and other products which are challenging to produce in the cytosol./nIn order to tune the catalytic activity of the microcompartments, we orchestrate microcompartment formation at the transcriptional level to control when the organelles are formed and how much heterologous cargo is encapsulated. We also create new localization signals that allow fine control over the loading of multiple enzymes to the compartments simultaneously. We are investigating the role of pore residues in small molecule transport across the shells of virus-like particles and the microcompartments themselves. Lastly, we use computational tools to model microcompartment function in order to facilitate the selection of pathways for encapsulation. Together, these tools allow the creation of custom biosynthetic organelles with user-defined enzyme content and transport properties, enabling the use of biosynthetic pathways which otherwise fail to function.

Advisor: Tullman-Ercek, Danielle
Dynamic Facility Relocation and Inventory Management for Disaster Relief

Disasters strike suddenly and cause destruction which disrupts the availability of basic survival supplies for people living in affected areas. The efficiency of humanitarian organizations in providing relief has a direct and crucial impact on the survival, health, and recovery of affected people and their communities. To better prepare to respond to disasters, many relief organizations use supply pre-positioning. However, the real and potential needs of different locations change over time and when an organization uses traditional warehouse pre-positioning, relief operations are limited by set inventory locations that are difficult to alter. For this reason, a well known organization recently considered including a large supply holding ship in its operations. By holding inventory on a ship, the organization would be able to dynamically relocate its inventory over time in response to changing relief supply demand forecasts./nTo our knowledge, the research contained herein is the first to examine dynamic inventory relocation for responding to disasters over time. Specifically, we examine how to optimally relocate and manage inventory for a single mobile inventory to serve stochastic demand at a number of potential disaster sites over time. While we keep in mind the motivating example of a supply holding ship in the disaster relief setting throughout this dissertation, the model and most of the results are applicable to any type of mobile inventory, facility, or server in any setting./nWe first examine the dynamic relocation problem. We model the problem using dynamic programming and develop analytical and numerical results regarding optimal relocation policies, the optimal path and speed of relocation decisions, and the value of inventory mobility over traditional warehouse pre-positioning. To help overcome the computational complexity of the problem, we develop a heuristic which solves relatively large problem instances in our numerical experiments within 0.5% of optimality in less than 0.1% of the time required by an exact algorithm./nAs it is suboptimal to consider relocation decisions and inventory management decisions separately, we also examine the joint dynamic relocation and inventory management problem. To our knowledge, we are the first to examine the dynamic relocation and inventory management problem with stochastic demand. Similarly to the dynamic relocation problem, we model this problem using dynamic programming. We develop a number of analytical results characterizing the optimal relocation and inventory management policies./nAs the first to examine these problems, we hope this research serves as a catalyst for other research in this area; accordingly, we conclude this dissertation by discussing a number of areas for future research.

Advisor: Shen, Zuo-Jun (Max)
Defending Dissidents from Targeted Digital Surveillance

Computer security research devotes extensive efforts to protecting individuals against indiscriminate, large-scale attacks such as those used by cybercriminals. Recently, the problem of protecting institutions against targeted attacks conducted by nation-states (so-called “Advanced Persistent Threats”) has likewise elicited significant research interest. Where these two problem domains intersect, however---targeted cyber attacks by nation-states against individuals---has received little significant, methodical research attention. This new problem space poses challenges that are both technically complex and of significant real-world importance./nIn this thesis, we undertake to characterize the emergent problem space of nation-state Internet attacks against individuals engaged in pro-democracy or opposition movements. We first present several years of research we have conducted into cases from two Middle Eastern countries, in the aftermath of the Arab Spring. Leveraging our connections in Bahrain and the United Arab Emirates, we encouraged potential targets to send us any ``suspicious'' electronic communications they received. Dissidents forward us messages with malicious attachments, links, and other content designed to deanonymize them and break into their computers and phones. Strong circumstantial evidence ties some of these messages to specific nation-state attackers. We frame the nature of these attacks, and the technology and infrastructure used to conduct them, in the context of their impacts on real people./n/nBuilding on our understanding of attacks targeting dissidents, we engaged with 30 potential targets of Middle Eastern and Horn of Africa-based governments, in order to better understand subjects' perceptions of the risks associated with their online activity. We interviewed subjects, and examined settings and software on their computers and phones. Our data illuminate the ways that dissidents are vulnerable to the types of attacks employed by nation-states./nInformed by our fieldwork, we developed \tool, a defensive approach that readily integrates with targets' workflow to provide near real-time scanning of email messages to check for threats. Our prototype implementation of \tool currently protects 36 subjects, and has found a number of attacks both from scans of past message archives and in live activity.

Advisor: Paxson, Vern
Computational Strategies for Multi-Scale Modeling of Masonry Components and Structures

In the current state of structural engineering, physical experimentation still offers the most reliable means for the determination of parameters for accurate modeling of complex systems. However, engineers usually face time and financial constraints that prevent them from performing such experiments. On the other hand, engineers are in increased need of a reliable predicting computational power so that resources are optimized in the design of new structures and the retrofit of existing ones. Moreover, society expects us to be able to guarantee that structures will have adequate performance during their life. In the present work, a computational framework for the analysis of masonry structures is presented. The framework relies on the well-established theory of micromechanical homogenization. The dissertation consists of two distinct parts: I. Constitutive modeling on the component level and II. Applications at the structural level. First, homogenization is conducted for the elastic parameters. Those parameters are used in a linear elastic analysis of masonry at a macro-scale. Then, with proper engineering judgments, a representative state of strain is determined where the unit cell is subjected to a monotonically increasing state of strain. A stress versus strain relationship is obtained accounting for material regularization so that dimensional effects and proper softening behavior are considered. Effective material parameters are tested against experiments as well as against micro-modeling leading to acceptable results at an affordable computational cost. The framework is applied to the modeling of reinforced concrete frames with masonry infills subjected to in-plane and out-of-plane loading. A three-dimensional model is needed for explicitly accounting for the out-of-plane arching action, which makes the homogenization procedure the only feasible approach for such problem.

Advisor: Mosalam, Khalid M