VictorJuiz/thesis huggingface dataset:
Dissecting pathway-level complex traits in yeast
Keywords: Genetics.

Understanding the genetic and evolutionary basis of complex traits is an outstanding question in genetics. In contrast to Mendelian traits which are usually affected by one or a few genes, complex traits are affected by variation in multiple genes, often hundreds to thousands. This complexity makes it difficult to determine which biological processes and genetic variants affect these traits. Furthermore, identifying natural selection affecting these traits can be difficult without knowledge of which variants are relevant. One method for identifying the genetic basis of complex traits is quantitative trait locus (QTL) mapping using offspring from genetic crosses of laboratory organisms. In Chapter 2, S. cerevisiae offspring from two parental strains between which polygenic selection on gene expression in the ergosterol pathway was identified are examined to see the effect of this selection on metabolite levels, a more downstream endophenotype. While metabolite QTL and expression QTL overlapped well, the selection on gene expression did not lead to the expected changes in metabolite levels. A new test was developed to identify selection on the metabolite levels, and while there was significant evidence of natural selection affecting metabolite levels, it was clear that the selection on gene expression did not predict the selection on metabolite levels, suggesting the need for studying pathways at multiple levels of endophenotypes to understand selection on complex traits. An additional complexity in understanding complex traits is the effects of environment. Not only can the environment in which an organism lives directly affect a complex trait, but some genetic variants will have different effects on fitness or other traits based on the environment. These effects are known as gene-by-environment interactions (GxE). In chapter 3, we develop an improved method for precisely measuring the effects of natural genetic variants in yeast using precision editing and growth competitions. We then use this technique to identify natural variants in S. cerevisiae which have GxE interactions, first within QTL regions and then within the ergosterol biosynthesis pathway. Together, these two chapters advance our understanding of complex traits at the pathway-level, first by looking between levels of endophenotypes, and then looking at complexity imparted by the environment through GxE interactions
Distributed and error resilient convex optimization formulations in machine learning
Keywords: Electrical Engineering.

Neural networks have been very successful across many domains in machine learning. Training neural networks typically requires minimizing a high-dimensional non-convex function. Stochastic gradient descent and variants are often used in practice for training neural networks. In this thesis, we describe convex optimization formulations for optimally training neural networks with polynomial activation functions. More specifically, we present semidefinite programming formulations for training neural networks with second degree polynomial activations and show that its solution provides a globally optimal solution to the original non-convex training problem. We then extend this strategy to train quantized neural networks with integer weights. We show that we can globally optimize the training loss with respect to integer weights in polynomial time via semidefinite relaxations and randomized rounding. In the second part of the thesis, we describe a distributed computing and optimization framework to train models, including our convex neural networks. The proposed second order optimization methods in this part rely on approximating the Hessian matrix via random projections. In particular, we describe how to employ randomized sketches in reducing the problem dimensions as well as preserving privacy and improving straggler resilience in asynchronous distributed systems. We present novel approximation guarantees as well as closed-form expressions for debiasing the update directions of the optimization algorithm. Finally, we establish a novel connection between randomized sketching and coded computation. The proposed approach builds on polar codes for straggler-resilient distributed computing
Distributed ice penetrating radar sounding using passive synchronization
Keywords: Electrical Engineering.

A passive wireless synchronization approach is presented for distributed radar arrays. The application to bistatic radar tomography and orthogonal wave beamforming is investigated. Rather than using a separate synchronization channel, the passive synchronization approach uses the transmit phase and time information embedded in the direct path signal to synchronize echoes. Coherent summation recovery of echoes is demonstrated from the bottom of a 1 km thick glacier up to antenna separations of 1.45 km. The system achieves the largest bistatic offsets in glaciological literature and opens the door to bistatic radar tomography. The proof-of-concept demonstration could enable observations with antenna separations of 4 km or longer, which would provide sufficient inversion constraints for 2D mapping of a glacier's subsurface structure. Based on a simulated experiment with a 4 km transect, the system is expected to estimate temperature distribution on 50 m x 50 m grids with a predicted performance of 0.84±0.34°C mean temperature error, 3.62±0.89°C maximum temperature error and an error in relative basal permittivity of 0.65±0.46 using a Newton's Method inversion approach. This new measurement approach can provide valuable insight into the processes controlling shear margins and improve modeling of ice streams behavior, evolution, and projected sea level contribution. In-situ, high fidelity observations such as this are most valuable when paired with continent-scale measurements that enable extrapolation and placing the findings in a larger glaciological context. Therefore, the Jet Propulsion Laboratory is developing a distributed orbital radar sounder to obtain high coverage with sufficient clutter suppression for ice sheet sounding from orbit. This dissertation matures orthogonal wave beamforming which is required to passively synchronize the CubeSat radars. Specifically, an analytical orthogonality scheme titled Sinusoidal Frequency Modulated Continuous Wave is developed for radar applications. In total, our passively synchronized radar system is providing new measurement techniques for monitoring glaciers at scales that were not previously feasible
Distributed simulation and optimization of large-area metasurfaces
Keywords: Electrical Engineering.

Emerging technologies such as augmented reality, lidar, and mobile imaging have opened a large market for complex, compact, and mass-producible optical systems. Metasurfaces are a promising building block for such next-generation systems. These flat optical elements can use subwavelength scatterers to control light, and can be mass-produced in the same advanced semiconductor foundries that have enabled successful scaling of consumer electronics. However, although metasurface functionality can be experimentally demonstrated, simulating metasurfaces is a central challenge in metasurface design. This simulation challenge arises because metasurfaces typically span thousands of wavelengths in linear dimension, rendering traditional electromagnetic simulation techniques (e.g. Finite-Difference and Finite-Element methods) intractable. Here, we present a metasurface simulation distribution strategy that can preserve the simulation accuracy while allowing scalability to arbitrarily-large areas. Using this distribution strategy with a GPU-based implementation of the Transition-matrix (T-matrix) method, we show a record-size 3-dimensional metasurface simulation (over 600 lambda by 600 lambda) that accurately accounts for scatterer-scatterer interactions significantly beyond the commonly-used locally periodic approximation. We then demonstrate gradient-based optimization of single and multilayer metasurfaces using our distributed T-matrix method. Finally, we discuss using the distribution strategy with Finite-Difference Time-Domain solvers to handle arbitrary scatterer geometries
Do Levees Redistribute Floodwater Risk? A Bayesian Assessment with the National Levee Database
Keywords: Levees
Statistics
Bayesian Models
Flood control
Text
Thesis

Since the 1800s, levees, embankments that prevent water from entering a floodplain, have played a critical role in U.S. flood management.
While physics-based models are used by engineers prior to construction projects to limit adverse impacts, flood victims, law suits, and academic papers have asserted that in redistributing floodwater, levees redistribute flood risk up or downstream—to communities without this infrastructure. However, there has been little empirical research examining the actual effect of levees on stage (surface water level). We examine this question at a national scale, extending the simple statistical method of a small-scale study (in IL, IA) to levees in the National Levee Database, then generalize this approach to a fully Bayesian treatment using a multi-level model.
While the original small-scale study found that levee construction significantly increased stage upstream and adjacent to levees, we find that this result does not generalize nationally. However, the mutli-level model offers many advantages over the previous methods in this application, and allows us to study effect heterogeneity, where preliminary results suggest that non-accredited levees and those in regions with high silt soil composition may be more likely to exhibit stage increases.
Does Distance Matter at Scale? Extending the “Distance Matters” Framework from Distributed Teams to Distributed Organizations
Keywords: remote work
distributed work
collaboration
organizations
CSCW
distance matters
Symbolic Systems Program
Management Science and Engineering
Computer Science
Text
Thesis

Distributed work has been a major area of focus for CSCW for the past two decades, as improved collaboration tools have made it possible to assemble distributed teams, abandon physical offices, and engage with collaborators across the world. Much of the CSCW literature on distributed work, however, focuses on intra-team dynamics. Notably, the "Distance Matters" framework has been influential in outlining five dimensions along which distributed teams must coordinate in order to work effectively: common ground, collaboration readiness, collaboration technology readiness, coupling of work, and organizational managerial aspects.
However, an under-considered aspect of the literature is the question of how distributed collaboration scales from a single team to an entire organization. As remote work takes hold on an increasingly large scale, this question becomes crucial. Indeed, teams do not exist in a vacuum; realistically, they exist in relation to other teams, which in turn exist within a broader organization. An effective distributed organization must therefore engage with three levels of analysis: intra-team, inter-team, and organizational.
In this paper, we expand the canonical "Distance Matters" framework and introduce a three-tiered model for studying distributed work, in which we describe how the canonical five dimensions of remote collaboration, developed at the intra-team level, should also be considered in a separate design process for the inter-team and organizational levels. The inter-team and organizational levels both produce novel collaboration and coordination challenges, as well as novel opportunities for resolving these challenges. Finally, we build this theory by presenting supporting ethnographic data from a field study at a major California National Laboratory, which transitioned the majority of its workforce to remote operations in the wake of the COVID-19 pandemic.
Doing "accomplished" teaching : discourses and performances of English language arts pedagogy in National Board Certification
Keywords: Education.

Over the past few decades, teaching performance assessments (TPAs) have proliferated in credentialing and evaluating teachers. In contrast to traditional, one-off measures of teacher knowledge and practice, such as standardized tests or standalone classroom observations, TPAs use portfolio-based assessments to capture multiple, complex dimensions of teaching (Darling-Hammond & Snyder, 2000). The National Board Certification, the focus of this dissertation, is one such TPA. As TPAs have become part of "multiple and often contradictory" discourses of education reform and accountability (Cochran-Smith & Fries, 2001), they play an increasing role in defining what counts as teacher knowledge and effective practice. In this dissertation, I focus on the National Board Certification process for English Language Arts (ELA). Using sociocultural theory and the lens of figured worlds, I argue that the National Board Standards and assessment are discourses with embedded ideologies, and teachers' representations of teaching within TPAs are situated performances. Through analysis of the National Board ELA Standards, I identify ideological contradictions and inconsistencies within the assessment itself. Drawing on data from teachers' National Board portfolios and interviews, I highlight the range of interpretations of the assessment among teachers as they sought to represent themselves and get recognized as "accomplished" ELA teachers. Finally, I discuss potential implications for this work, including redesigning TPAs to encourage expansive pedagogies and questioning the logic and institutional function of assessments. I also suggest avenues for future research and practice in teacher education
Donepezil mitigates memory deficits in Siberian hamsters
Keywords: Biology
Chronobiology
Circadian rhythms
Text
Thesis

The purpose of this study was to test the effect of donepezil (Aricept) on cognition in circadian arrhythmic Siberian hamsters, an animal model that mimics the breakdown of circadian rhythms in humans. This is because circadian dysfunction is known to accelerate cognitive impairment in not only Alzheimer’s disease, but adult- onset circadian dysfunction. Male Siberian hamsters were split into circadian-intact and circadian-arrhythmic groups and randomly assigned to either vehicle or donepezil treatment group. Animals in the donepezil treatment group received daily oral administration of 3.0mg/kg of donepezil dissolved in sugar water for 21 days. The vehicle group received the same amount of plain sugar water for the same amount of time. All animals were tested before and after treatment in a spontaneous alternation (SA) T-maze to measure cognition and spatial mapping. Surprisingly, the daily sugar water restored rhythms in all animals (vehicle and donepezil). Animals treated with donepezil performed significantly better in the alternation test than did the vehicle-treated group.
Double coset Markov chains
Keywords: Mathematics.

Markov chains and random processes are ubiquitous in statistical and scientific applications. The main contribution of this thesis is to introduce the study of Markov chains on double cosets. Given a group and two sub-groups, the double cosets define equivalence classes of the group. A random walk on the group then induces a random processes on the set of equivalence classes. When is this random process also a Markov chain? Surprisingly, some of the examples capture scientifically (and mathematically) interesting special cases. This thesis develops a general theory for double coset Markov chains. Several cases are investigated in detail. Special attention is given to the example in which parabolic subgroups of the permutation group are indexed by contingency tables. In each of the examples the general theory developed here is applied to understand the eigenvalues, eigenfunctions, and the mixing times of the Markov chains. In the second half of this thesis two more new random processes are studied: A Markov chain on a space of coalescent trees (also related to a double coset space) and an urn model with an infinite color space. The long-term behavior of each is analyzed
Down-to-earth dark matter : novel terrestrial mechanisms for dark matter detection
Keywords: Physics.

There is overwhelming evidence for the existence of dark matter, a component of our universe which is more than five times as abundant as the visible matter we are familiar with. Yet despite longstanding experimental efforts to search for non-gravitational interactions of dark matter, the detection of any such interactions has thus far eluded us. There has therefore arisen an interest within the field in novel methods to detect dark matter. In this thesis, I will outline two new methods which utilize Earth to detect two different types of dark matter. The first searches for an oscillating magnetic field signal of ultralight bosonic dark matter at the surface of the Earth. In analogy to existing cavity/shielded experiments searching for ultralight dark matter, the signal arises because the ground and ionosphere function as conducting cavity walls between which dark matter can source a magnetic field. Based on this effect, we undertake an analysis of global geomagnetic field data from the SuperMAG collaboration in order to set bounds on dark photon and axionlike dark matter parameter spaces. In the latter part of this thesis, I will discuss a proposal to use ancient rocks, dubbed paleo-detectors, as detectors for WIMP dark matter. Over the past O(100) Myr, WIMPs may have induced nuclear recoils within these minerals that disrupted their crystalline structure, leaving long-lived tracks that can be read out today with precision microscopy techniques. I will show that paleo-detectors can give unique sensitivity to dark matter substructure within the Milky Way. This is because paleo-detectors are not only sensitive to the local dark matter density near the Earth today, but also to the dark matter density along Earth's entire galactic trajectory over the lifetime of a paleo-detector
Dwelling in displacement : land rights and heritage activism in post-apartheid Johannesburg
Keywords: Anthropology.

Questions of land rights deeply structure post-apartheid life in urban South Africa. This dissertation explores land activism through two heritage museums in Johannesburg, South Africa: The Fietas Museum in Fietas, and the Sophiatown Museum in Sophiatown. Both areas suffered catastrophic forced removals under apartheid, and both former and current residents continue to grapple with the implications of land-based justice in the present day. Drawing on extensive ethnographic and archival fieldwork in Johannesburg, this dissertation first argues that as a result of the restitutional delays of a market-driven land claims process, these heritage museums have emerged to catalyze land restitution both within and outside of the legal system. However, these efforts contribute to new forms of displacement and to new forms of dwelling, both for former and current residents. Moreover, I do not position displacement and dwelling as oppositional: instead, I extend a recent trend in the anthropology of migration to retheorize displacement both as physical mobility and as the psychic condition of being unsettled in place. Relatedly, I find that the Sophiatown and Fietas museums emplace certain groups while simultaneously displacing others; mount certain exhibitions by refusing to mount others; champion certain events in history while simultaneously deemphasizing others; and exist within a geographic footprint while simultaneously engaging in political, economic, social, and digital forms of advocacy that may extend their reach beyond their physically inscribed borders. Far from being exceptional in this way, my research instead points to a more general dynamic between absence and presence within heritage sites: there is value in attending to the often "unmarked" (Phelan 1996) silences that give shape to the commemorative acts, museological spaces, objects, and histories that become 'heritagized' through the practices of collecting and display. This dissertation consequently proposes a new framework for analyzing the heritage site that attends equally to absence as to presence
Dynamic matching : a queueing perspective
Keywords: Management Science and Engineering.

This dissertation focuses on frictions that arise in various dynamic marketplaces such as kidney exchange, labor markets, and logistics. The central question that we ask is how do heterogeneity, network structure, liquidity, and stochasticity, which cause these frictions, affect our ability to perform simple policies that can achieve efficient outcomes? In Chapters 2 and 3, we analyze dynamic matching markets. When agents arrive to the market over time, an inherent trade-off arises between short- and long-term allocative efficiency. For example, kidney exchange platforms, which arrange exchanges between incompatible patient-donor pairs, can form a match as soon as it becomes feasible, or wait for the market to thicken in order to generate exchanges that yield more life years from transplants. This trade-off raises several questions. How to optimally match agents over time? If the market is cleared periodically, how does the period length affect allocative efficiency at different times? How does stochastic demand impact desirable clearing times? We study these questions from a queueing perspective, and we propose simple batching and greedy policies with a strong performance guarantee: these policies (nearly) maximize the total match value simultaneously at all times. This suggests that the tension between short- and long-term allocative efficiency is essentially moot. In Chapter 4, we analyze scrip systems, where such systems serve an alternative to sustain cooperation, improve efficiency, and mitigate free riding in economies without monetary transfers. Agents request and provide service over time, and scrips are used as artificial currency to pay for service provision. We study the possibility of agents sustaining cooperation when the market is thin, in the sense that only few agents are available to provide the requested service. We analyze the stability of the scrip distribution of agents, assuming that among the available agents, the one with the minimum amount of scrips is selected to provide service. The analysis suggests that even with minimal liquidity in the market, cooperation can be sustained by balancing service provisions among agents. Simulations based on kidney exchange data propose that scrip systems can lead to efficient outcomes in kidney exchange by sustaining cooperation between hospitals
Dynamic operations over networks : extracting and protecting information
Keywords: Business.

In this dissertation, I investigate the interplay between information and networks in dynamic operations. For this purpose, I study two related settings where a decision maker interacts with information while dynamically operating over a network. In the first setting, this interaction manifests itself as a goal of protecting sensitive information and is the focus of Chapter 1. More specifically, I analyze how a decision maker can efficiently route over a given network without revealing the destination as a result of taking actions over the network. In the second setting, the goal of the decision maker is one of learning, or extracting information, through interactions with a network. In Chapter 2, I study this problem in the context of forensic investigations and address the question of efficiently reconstructing an unobservable network in order to find a target hidden among its vertices. Finally, in Chapter 3, I treat the problems of extracting and protecting information jointly and consider a decision maker who aims to protect sensitive information while conducting a search. In this final chapter, I again analyze the same forensic technique from Chapter 2 and add an additional objective of privacy