VictorJuiz/thesis huggingface dataset:
The Historical Ecology and Ancient Fisheries of the Central California Coast: Insights from Point Reyes National Seashore and the Santa Cruz Coast

The study of ancient and historic fisheries is essential for understanding past indigenous/neconomies and ways of life that have relevance for modern fisheries management, restoration/necology, and conservation biology. Archaeological sites represent long-term biological/nrepositories; they contain relevant information that provides historical baseline data and/necological reference points for contemporary conservation biology, restoration ecology, and/nfisheries management. Contemporary impacts, historical overfishing, and ecological extinctions/nthreaten coastal ecosystems, as reduced fish populations no longer interact significantly with/nother species in the community. The time-depth of the archaeological record can provide vital/ninformation for scientists, resource managers, policy makers, and sovereign Native American/nnations to prioritize resources for conservation and restoration./nAs a result of collaborative eco-archaeology with the Amah Mutsun Tribal Band, the Federated/nIndians of Graton Rancheria, the National Park Service, and California State Parks, this/ndissertation outlines the ancient fisheries of central California from the Middle Holocene to the/nhistoric era spanning the last 7,000 years. Through the investigation of fourteen archaeological/nsites from Point Reyes National Shore to Santa Cruz County, this dissertation offers three case/nstudies that highlight the value of historical ecology and eco-archaeology of ancient and historic/nfisheries. These data contribute information for tribes and federal and state agencies, to inform/nthe co-management of fisheries by defining the range of organisms used in ancient and historic/ntimes, organism biogeography, and indigenous fishing techniques and technologies.

Advisor: Lightfoot, Kent G.
Magnetometry and Imaging with Nitrogen Vacancy Centers in Diamond

After a brief introduction to nitrogen vacancy (NV) centers and related physics, a description is presented of the principles and methodology of the diamond-based imaging magnetometer using an ensemble of NV centers. The diamond-based magnetic imaging platform is used to realize a force-induced remnant magnetization spectroscopy technique in which specific biomolecular binding is measured and detection is performed with wide-field optical and diamond-based magnetometry. This diamond-based technique that has both optical and magnetic detection modalities may be adapted for massively parallel screening of arrays of nanoscale samples. In a separate, but similarly inspired experiment, a description is given of the methods used to analyze the motion of a microscopic ferromagnetic particle levitated above a superconducting niobium surface.

Advisor: Budker, Dmitry
Computational modeling of behavior under uncertainty: Commonalities and differences between anxiety and depression

Individuals who are prone to experiencing high levels of anxiety and depression often exhibit dysfunctional behavior. For example, anxious individuals often avoid situations that have even the slightest chance of a highly negative outcome (e.g. a plane crash), and depressed individuals often show a reduced pursuit of activities that most people find enjoyable. Progress can be made in understanding dysfunctional behavior by using formal, mathematical frameworks of decision making, which break down behavior into its computational components, and in which we can start to pinpoint the specific abnormalities associated with anxiety and depression. Chapter 1.2 and 1.3 review prior literature, highlighting some of the computations that seem to be altered, such as the overestimation for the probability that rare, extremely negative events will occur. Chapter 2 and Chapter 3 empirically examine behavior in situations that require individuals to accurately estimate the probability that an outcome will (or will not) occur as a result of their actions. In a task where individuals have to estimate action-outcome probabilities by trial-and-error (Chapter 2), individuals with high overall levels of anxiety and depression show a reduced ability to align the rate at which they learn to the rate of change in the environment (i.e. the level of volatility). In a task where individuals have to choose between options that have known (risky) versus unknown (ambiguous) probabilities (Chapter 3), individuals who have high levels of physiological anxiety tend to avoid the ambiguous options more than other individuals, as information is removed about those probabilities. On the other hand, individuals who are prone to experiencing mania are more likely to make the opposite choice, seeking ambiguity, when the outcomes are rewarding. Chapter 4 examines possible sources for dysfunctional beliefs, as opposed to behaviors. In a hypothetical vocational setting where individuals estimate their rank relative to others, individuals with high levels of anhedonia-related symptoms show initial beliefs that are more negative relative to the beliefs of others. Individuals with high levels of anxiety, on the other hand, show negatively biased updating of those beliefs in response to unbiased information. Chapter 5 summarizes the empirical findings and discusses more broadly how anxiety and depression seem to impact behavior (and its underlying computations) in uncertain situations.

Advisor: Bishop, Sonia J
Maize Development and Immunity and the Importance of CLEAR Science Communication

Plants adapt to a variety of harsh environments with built-in resilience. Be it pathogen attacks or temperature stress, integrating these environmental signals is key for proper growth and development. liguleless narrow1 (lgn) encodes a plasma membrane-localized receptor-like kinase that is required for normal maize development including leaf shape, internode elongation, and fertility. The semi-dominant mutation (Lgn-R) lacks kinase activity. We assayed the phenotype in multiple environments and genetic backgrounds and found dramatic variations in expressivity. Analysis using a subset of the NAM founder lines revealed five inbred lines, including B73, that exhibit increased death rates in hot conditions and severe phenotypes in cool conditions. Four additional inbred lines, including Mo17, survive to exhibit severe phenotypes in hot conditions but are nearly indistinguishable from their non-mutant siblings at cool temperatures. A QTL analysis combined with additional mapping techniques identified one of the second site modifiers between these two lines, Sympathy for the ligule (Sol). Inbred lines that have the most severe phenotypes for Lgn-R show constitutive induction of Sol in the mutant background as well as a predilection for a particular set of indels and SNPs within the coding sequence. Rescuing lines do not show an induction of this gene in the mutant background. An EMS mutation further confirmed the identity of Sol to be this gene, a maize homolog of Arabidopsis ENHANCED DISEASE RESISTANCE4 (EDR4)./nSol, like EDR4, is induced in response to pathogen associated molecular patterns such as flg22. Integrated transcriptomic and phosphoproteomic analyses suggest that Lgn-R plants constitutively activate an immune response. We propose that the severe Lgn-R developmental phenotypes are the result of constitutive defense induction and that SOL potentially functions in repressing this response in Mo17 but not B73. Identification of LGN and SOL provide insight into the integration of developmental control and immunity.

Advisor: Hake, Sarah
Condensin, Cohesin and Cdc5 function as choreographers of chromosome condensation.

During cellular division, chromosomes undergo a series of cytological events that allow for the maintenance and inheritance of genetic information from one generation to the next. While the necessity of these morphological changes has been appreciated for over a hundred years, we still have but a rudimentary understanding of the basic principles underlying how chromosomes are formed./nOver the past two decades, we have gained an appreciation for the integral role of two related, multi-subunit Structural Maintenance of Chromosomes (SMC) protein complexes, cohesin and condensin, play in chromosome condensation. The necessity of both protein complexes is particularly evident in the budding yeast, Saccharomyces cerevisiae, where loss of either cohesin or condensin leads to cytologically indistinguishable loss of chromosome condensation./nIn this dissertation, I address some of the gaps in our knowledge of the mechanisms governing mitotic chromosome condensation. This body of work was sparked by the fundamental question of how condensin and cohesin orchestrate their functions to ensure that chromosome condensation occurs in a tightly regulated spatio-temporal manner. To that end, we used a combination of yeast genetics, cytology, sequencing and chromosome conformation capture methodologies to dissect the relative contributions of cohesin and condensin to mitotic chromosome condensation./nFirst, we describe the role of a kinase, Polo (Cdc5), as part of an interactome of early condensation factors along with cohesin and condensin. In particular, we describe how cohesin modulation of this kinase may impact condensin function. Next, we utilize a chromosome conformation capture technique, Micro-C, to elucidate features of yeast mitotic structures at nucleosome resolution. There, we also begin to dissect the contributions of mitotic factors in these structures. Lastly, we investigate the molecular defects of a unique cohesin mutant that allow us to dissect cohesin’s role in condensation./nAltogether, these findings reshape our understanding how higher order chromosome structures are formed and inspire us to reevaluate some of our fundamental assumptions about how SMCs coordinate their function. Additionally, this work highlights how yeast can serve as a genetically-tractable model for studying the formation of chromosome loops.

Advisor: Koshland, Douglas E
Production of multi-methyl-branched fatty methyl ketones via a chimeric polyketide synthase pathway

Petroleum and its derivatives revolutionized every aspect of human life, from how we work and travel to what we wear and eat. However, mitigation and prevention of climate change are of utmost ethical and economical importance. Biology is a potential means for reducing greenhouse gas emissions, while maintaining or even diversifying and improving the goods and services the world has grown to depend on. Biofuels, for example, can be made with renewable waste feedstocks and can supplement or replace petroleum-derived fuels but lack optimal molecular properties. We therefore sought a means for customizing biologically-produced carbon backbones. To this end, we engineered enzymes from microbial antibiotic biosynthesis called polyketide synthases. These enzymes form modular “assembly lines” where the activity of each catalytic unit can be predicted with reasonable confidence. We envisioned combining individual enzymes to form a new biosynthetic assembly line which, until this work, did not exist in nature. We first investigated the main biosynthetic chassis, an iterative polyketide synthase, BorM5, from the borrelidin pathway. We discovered that BorM5 is promiscuous for both starting and elongation substrates, producing a variety of mid-length branched and linear saturated fatty acyl intermediates. We next characterized the trans-acting thioesterase, BorB, hoping to use it as an offloading mechanism. We propose that BorB acts to remove dead-end intermediates from the borrelidin pathway, increasing its efficiency. We then engineered on- and off-loading neighbors for BorM5 and observed production of new-to-Nature C11 and C14 methyl branched methyl ketones. Diversification and high-titer production of these compounds, combined with materials testing, may lead to improved biofuels and the environmental, economic, and social benefits that accompany them.

Advisor: Keasling, Jay
Miscalibration, Missing Attributions, and Mispredictions: An Exploration of Momentum, Efficacy, and Performance Expectations

Momentum and efficacy are important forces to understand for performance-related outcomes in a variety of contexts, from athletic contests to mental challenges to day-to-day tasks. This dissertation explores perceptions and consequences of those forces, in three chapters./nIn Chapter 1, which includes seven total experiments (N = 3,052), I find that the experience of gaining momentum leads to increased performance expectations (and losing momentum to decreased expectations), but that these expectations are often miscalibrated as compared to actual performance. I further find that participants will bet on their performance expectations when they experience gaining momentum, even though experiencing momentum does not consistently lead to actual performance increases commensurate with expectations./nIn Chapter 2, I discuss the results of four experiments (N = 1,347). I replicate the findings from Chapter 1 that perceived momentum leads to performance expectations, but I find that link only exists if the performer is judged to have control over the outcome of the contest (i.e., perceiving that the performer has efficacy). When efficacy is either attenuated or not present (e.g., in games of chance), observers no longer believe that gaining momentum will lead to improved performance./nIn Chapter 3, I present nine experiments (N = 2,729) which uncover and then correct a misprediction about the effect of task ordering on performers’ efficacy. I find that people predict that completing tasks in increasing-difficulty (vs. decreasing-difficulty) order will lead to greater felt efficacy and that people consequently prefer to complete tasks in increasing-difficulty order. I then expose that misprediction and find instead that there is either no effect of task ordering on efficacy, or that the opposite is true: completing tasks in decreasing-difficulty order leads to more reported efficacy. Finally, I explore a potential mechanism to correct the misprediction: clearer simulation of the actual experience of completing tasks in different orders./nAcross these three chapters and 7,128 total participants, I demonstrate a strong link between momentum perceptions and performance expectations but find that these expectations are often miscalibrated as compared to reality. I also show that perceived momentum must signal efficacy in order to affect performance expectations. Finally, I present evidence that efficacy can be generated by completing tasks in decreasing-difficulty order, despite people’s expectations that completing tasks in increasing-difficulty order will increase perceived efficacy and their preferences for starting with their easiest task.

Advisor: Schroeder, Juliana
Interaction of Higher-Order Laser Modes with Underdense Plasmas

Laser-plasma interactions have become a rapidly growing area of modern plasma physics and an important subfield of it is laser-plasma acceleration. Using high-intensity lasers, one can drive a plasma structure with electric-field gradients three orders of magnitude higher than the gradients found in traditional, radio-frequency accelerators. This promises to enable great technological advances in medicine, spectroscopy, and experimental particle physics, as well as to open up new avenues of studying matter under extreme conditions./nAn important aspect of laser-plasma acceleration is how the transverse electromagnetic field of the laser affects and drives an accelerated particle via longitudinal waves in the plasma. To understand how the laser interacts with the plasma, it is necessary to understand that the transverse characteristics of the laser dictate its longitudinal propagation dynamics. The transverse radiation field of the laser pulse can be described in various ways and decomposed into bases of orthogonal modes. The presence of multiple higher-order modes, copropagating through the plasma, leads to mode beating. Likewise, these modes propagate at different velocities through the plasma and are susceptible to nonlinear interactions with the plasma to varying degrees./nThe primary objective of this thesis is to understand how higher-order laser modes interact with the plasma and with one another. In this work, we discuss the detrimental consequences that mode beating may have on a laser-plasma accelerator and how higher-order modes can be filtered out using specially designed plasma structures. Also discussed is how higher-order mode content can be controlled and utilized to shape and control the wakefields. These ideas are extended to the concept of the plasma undulator as a plasma-based light source. Lastly, we discuss how nonlinear effects can excite higher-order mode content as path to understanding laser pulse break up into multiple filaments.

Advisor: Schroeder, Carl B
Bale, Stuart D
Insider Trading, Informed Trading, and Market Mechanisms: A Comparative Perspective from Taiwan

It is the unsolvable paradox of human nature that makes the research of insider trading law wonderfully but strangely attractive. Although nowadays most countries in the world have an insider trading law, hundreds of thousands of scholars still invest their time and efforts in debating whether the acts of insider trading should be banned, and to what scope should the acts be illegalized. In this dissertation, I will lead the readers to a journey of exploring insider trading law. Particularly, the three main chapters of this dissertation are respectively composed by three related but independent papers on different aspects surrounding the insider trading law of the US and Taiwan. In Chapter 2, I am going to examine the recent development of the US insider trading law imposed on market professionals, from the perspective of both law and financial economics. We are going to see how the US courts assess the dual roles of market professionals —— enhancing the price efficiency of stock prices while exploiting the other investors —— and balance the contribution and harm market professionals bring to the market, when they are drawing the line between the illegal insider trading and lawful informed trading. Chapter 3 of this dissertation moves to examine the insider trading law of my home country Taiwan. In this chapter, the methodology of comparative studies will provide the readers with different lenses through which they can compare the philosophy of a civil law country when dealing with the problem of insider trading. Chapter 4 investigates and develops an empirical methodology that allows a government to test whether its insider trading enforcement is successful compared to other jurisdictions. Specifically, it uses the “pre-announcement price run-up” before the good news arrives at the market as the proxy for measuring the effectiveness of an insider trading law. Chapter 5 concludes.

Advisor: Solomon, Steven Davidoff
A Finite Element Method for Modeling Surface Growth and Resorption of Deformable Bodies with Applications to Cell Migration

Surface growth/resorption is the process wherein material is added to or removed from the boundary of a physical body. As a consequence, the set of material points constituting the body is time-dependent and thus lacks a static reference configuration. In this dissertation, kinematics and balance laws are formulated for a body undergoing surface growth/resorption and finite deformation. This is achieved by defining an evolving reference configuration termed the intermediate configuration which tracks the set of material points constituting the body at a given time./nAn extension of the Arbitrary Lagrangian-Eulerian finite element method is introduced to solve the discretized set of balance laws on the grown/resorpted body, alongside algorithmic implementations to track the evolving boundary of the physical body. The effect of accreting material with no prior history of deformation onto a body undergoing rigid motions as well as a loaded body is discussed. Moreover, the correlation between growth/resorption rate and the spatial and temporal convergence of the finite element approximations of fields are illustrated./nThe numerical implementation for surface growth and resorption is used to simulate a migrating cell which moves in an apparent "treadmilling" motion on a substrate by polymerizing and de-polymerizing microfilaments along its boundary. An example is presented which defines a surface growth law based on the nucleation and dissociation of chemical species, and the steady-state treadmilling velocity is computed for various assumed cell shapes. Lastly, simulation results are shown for an idealized cell colliding with external barriers, leading to a re-orientation of the surface growth/resorption direction. The effects of dynamic contact on the surface growth/resorption as well as the stress and deformation are discussed.

Advisor: Papadopoulos, Panayiotis
Taylor, Robert L
Essays on the Political Economy of the American Frontier

This dissertation argues that early land reforms had consequential long-run impacts on the development of the American state. The state-building role of land reform, frequently discussed in the context of comparative political economy, is often overlooked in the study of American political development. I provide evidence that mid-nineteenth century homestead acts had significant long-run impacts that can help explain contemporary differences in state capacity. I find that homestead policy --- or the homestead entries authorized by homestead policy --- had significant and negative effects on the size of state governments lasting a century after passage of the 1862 Homestead Act. This finding implies that in the absence of homestead policy, the average size of frontier state governments would have exceeded the average size of governments in states that were not directly affected by the policy. Potential causal mechanisms include land inequality, which I show to be positively correlated with state capacity, especially at higher levels of inequality. This empirical relationship is consistent with median voter theories of inequality and redistribution./nThe dissertation contributes to a new generation of data-driven machine learning methods for estimating causal impacts of policy interventions on panel data. Machine learning approaches are capable of automatically choosing appropriate predictors without relying on pre-intervention covariates, limiting the 'researcher degrees of freedom' that arise from model specification choices. The proposed method based on recurrent neural networks can learn nonconvex combinations of predictors, are specifically structured for sequential data, and outperform regression-based estimators in high-dimensional data settings. The dissertation also introduces a matrix completion method that is adaptable to settings with staggered treatment adoption and outperforms other regression-based estimators in small-dimensional data settings.

Advisor: Gailmard, Sean