VictorJuiz/thesis huggingface dataset:
The Role of Hedgehog signaling and other factors in taste cell maintenance
Keywords:  Department of Biology
Biology
Stem Cell Biology
Taste
Regenerative Medicine
Hedgehog Signaling
Organoid
Thesis

In adult life, stem cells are crucial for normal tissue maintenance and repair of damaged tissues. Cell signaling pathways control stem cell activity by regulating self-renewal and proliferation of progenitors that give rise to all cell-types. One such pathway, Hedgehog signaling (Hh), is highly active during embryonic development and important in injury-induced regenerative responses in adult. Hh-hyperactivation has also been implicated in basal-cell carcinoma leading to the use of Hh-antagonist drug, vismodegib, as a cancer therapy. A surprising side-effect of vismodegib is dysguesia, or taste loss, in approximately half of treated patients. This finding, combined with previous results showing ablation of taste receptor cells (TRCs) upon Hh-inhibition, led me to hypothesize that Hh activation in basal lingual epithelial cells is required for maintenance of taste sensation in adult. To test this hypothesis, I optimized a previously described lingual epithelial cell organoid culture system to model proliferation and differentiation of lingual epithelial cells under various culture conditions. I found that while Hh-activation was sufficient to induce organoid population growth, activation of another developmental pathway, BMPR2, severely stunted organoid proliferation. Interestingly, cotreatment with agonists of both Hh and BMPR2 pathways actually enhanced expression of the Hh ligand, sonic hedgehog (Shh). These results imply a complex interaction between developmental pathways in lingual epithelial cells in which Hh-induced cell proliferation may be regulated by other pathways including BMPR2.
The Role of Prostaglandin F2α in a cichlid brain: Investigating the neural mechanisms of signal integration
Keywords:  Department of Biology
Prostaglandin F2α
cichlid fish
Astatotilapia burtoni
CRISPR
Spawning
Female Reproduction
Thesis

The brain integrates internal and external cues to initiate reproduction. To study this integration, we used a well-studied model organism, an African cichlid fish, Astatotilapia burtoni. When female A. burtoni ovulate, a rise in the hormone prostaglandin F2α (PGF2α) signals to the brain that she is ready to spawn. If a male courts her and stimulates her through visual, auditory and olfactory cues, then spawning will occur. However, the mechanisms and location of external and internal signal integration is not well understood. In mammals and goldfish, PGF2α is known to regulate reproductive behavior, and it has been shown to be sufficient to induce spawning in female A. burtoni. My research asked whether PGF2α is necessary for spawning in A. burtoni. To test this hypothesis, we mutated the gene for the PGF2α receptor (Ptgfr), using clustered, regularly interspaced, short palindromic repeats (CRISPR). Fish carrying mutations in this gene failed to spawn during 30-minute assays, while all the control females spawned. These experiments show that PGF2α is necessary for spawning in female A. burtoni, setting the groundwork for identifying brain regions and neurons important for integrating internal and external signals. Further studies will determine how this hormone works in conjunction with external signals in the A. burtoni brain to regulate reproduction. These experiments could be broadly informative across vertebrate species since PGF2α plays a conserved role in vertebrate reproduction.
Theoretical electrocatalysis for renewable fuels and chemicals [electronic resource]
Keywords: Chemical Engineering.

Energy storage is a key concern to the grid-scale use of intermittent renewable sources like solar and wind. Electrolysis of such compounds as CO2, N2, and H2O into higher chemical potential products represents a possible route towards this goal, yet the conversion process is often severely limited due to inecient catalysis of the associated chemical reactions. In this work, the electrocatalytic conversion of these three molecules is explored using density functional theory (DFT) methods with the goals of both explaining existing trends in experiment and determining criteria for the design of new systems with improved eciency. CO2 electroreduction into ethylene and ethanol is highly attractive, since higher hydrocarbons are essential to much of our current fuel and chemical economy. In the first section, the formation of C-C bonds in CO2 electroreduction is discussed. The primarily focus of this section is copper, a catalyst known to convert CO2 into C2 products, and scaling relations for the coupling of *CO to its first hydrogenated derivative, *CHO, can rationalize why it is uniquely suited to do so. Insights into the mechanism of CO dimerization in alkaline conditions on Cu 100, as postulated previously from experiment, are also reported. Water-splitting into hydrogen and oxygen is another possible electrochemical energy storage method, and the oxidation of water into gaseous oxygen is typically coupled to other electroreduc- tions discussed herein as well. In the second section, DFT-predicted oxygen evolution activities on perovskite oxides are correlated with the electronic structure of the catalytic surface. In addition, predicted OER and HER overpotentials on photoabsorbing perovskites suggest that materials with optical properties suitable for water splitting likely do not possess the surface chemistry for ecient catalysis, thus motivating the need for co-catalytic systems in photoelectrochemical water splitting. The last section concerns trends in the theoretical overpotentials for the electroreduction of nitrogen gas to ammonia. Nitrogen electroreduction is severely limited in overpotential by the reductive adsorption of N2 to form *N2H on most materials, and may be limited by reductive desorption of NH and NH2 on more reactive materials. By scaling these two reaction energies on a 2-D volcano, we show that no single transition-metal catalyst is likely to produce ammonia eciently. This scaling relation does provide a strategy, however, for making new catalysts that might be less limited by these steps, since the selective stabilization of *N2H or selective destabilization of *NH2 should then result in less negative overpotential requirements. In summary, this dissertation uses DFT to describe and rationalize trends in electrocatalysis for three key reactions relevant to the conversion of electricity into chemical fuels. It is our hope that the principles outlined herein may guide the design of new catalytic systems that may ultimately realize the goal of ecient storage of renewable energy.
Theoretical study of novel concepts for compact, high-gain free electron lasers [electronic resource]
Keywords: Physics.

In recent years, the free-electron laser (FEL) has demonstrated its value as a tunable source of bright, coherent radiation with photon energies up to the X-ray region. For such short radiation wavelengths, three-dimensional (3D) effects (due to diffraction, emittance and focusing) become significant and must be taken into consideration. In this work, we present a systematic, fully 3D theoretical formalism applicable to a range of concepts for compact, high-gain FELs. These include novel schemes involving the use of transverse gradient (TGU) or laser undulators. Our approach utilizes either a standard eigenmode analysis for constant-parameter systems or a non-eigenmode expansion technique in terms of orthogonal transverse modes for cases where the parameters of the electron beam and/or the undulator vary along the longitudinal direction. The results we obtain fully characterize the system (electron beam and radiation) in the linear regime of the interaction and are shown to be in excellent agreement with simulation. Moreover, the formalism developed here can be used in comprehensive, theory-based optimization studies, with significant applications in FEL design.
There's no limit [electronic resource] : mathematics teaching for a growth mindset
Keywords: Education.

People's beliefs about math ability tend to fall along a spectrum, ranging from a fixed mindset, the belief that ability is innate and limited, to a growth mindset, the belief that ability is malleable and can be developed (Dweck, 2006). Despite evidence supporting the value of growth mindsets for student achievement, little is known about how teachers might influence student mindsets, particularly in relation to mathematics -- a subject where fixed mindset beliefs abound. To further our understanding of math teachers' potential influence on student mindset, this study seeks to examine: a) the relationship between teacher beliefs and student mindset, b) how mindset messages might be communicated in the mathematics classroom, and c) how instruction varies across teachers with different mindset beliefs. This study contributes to our understanding of domain specific mindset beliefs and has implications for math teacher training and practice.
Thermal maturation-induced evolution of the elastic and transport properties of organic-rich shales [electronic resource]
Keywords: Geophysics.

The primary focus of this dissertation is to improve the applicability of rock physics models for elastic anisotropy and fluid transport in organic-rich shale through the development and implementation of practical workflows and pioneering experimental methodologies. Shale accounts for the vast majority of rocks in sedimentary basins and, subsequently, the elastic anisotropy of shale must be comprehensively understood for proper processing and interpretation of surface seismic studies. Additionally, as unconventional reservoirs are increasingly targeted, the development of detailed physical relationships between geochemical indicators of hydrocarbon generation and retention with parameters quantifiable from remote sensing surveys, such as elastic anisotropy from seismic surveys, are key to improving unconventional exploration procedures and workflows. Further, the development of relationships between these geochemical indicators and transport properties, such as porosity and permeability, will be vital to the identification of sweet spots and the development of improved recovery efforts in unconventional reservoirs. However, previous attempts at developing these relationships by comparing shale samples from a vast range of formations are suspected to be contaminated by issues of heterogeneity in mineralogy, organic matter type, texture, and burial history between the samples. In this dissertation, I provide further evidence that relationships developed by comparing samples from multiple formations are obfuscated, or indeed corrupted, by inter-sample heterogeneity. Subsequently, I develop a pioneering methodology for the characterization of a single sample before and after inducing hydrocarbon generation (also called thermal maturation) on individual core plugs. This process is implemented in two manners: firstly, an experimentally simple method in which samples are thermally matured without any applied confining pressure, and, secondly, an experimentally taxing method in which samples are matured in a purpose-built vessel under in situ confining pressures.
Thermal stability, structure, and electrical properties of amorphous metal alloys for electronic applications [electronic resource]
Keywords: Materials Science and Engineering.

As complementary metal oxide semiconductor (CMOS) transistors continue to scale down, the work function variation (WFV) of the metal gates is becoming a dominant factor of the threshold voltage variation. This is due to the different grain orientations present in polycrystalline metal gates. Replacing these with amorphous or near-amorphous metals can reduce WFV. Furthermore, amorphous materials are known to have superior diffusion barrier properties due to their lack of grain boundaries. This can help prevent work function change due to the diffusion of metals in contact with the gate. In the first part of this thesis, a CoTiN metal alloy is introduced as a potential gate material. Using TiN-based material allows for an easy integration with the current technology as polycrystalline TiN is commonly used as the gate. With the addition of cobalt, thin films of TiN become more amorphous, consisting of nanocrystals in an amorphous matrix. Reducing the nitrogen content further decreases the film's crystallinity. In addition, CoTiN films also exhibit good thermal stability, low resistivity, and low roughness. Even though these materials are not completely amorphous, their small crystal size and an amorphous matrix can potentially reduce WFV and improve the diffusion barrier behavior. The second part focuses on the barrier properties of TiN and CoTiN against the diffusion of metal in contact with the gate. The work function (WF) of the bilayer-metal gate structure (Al/CoTiN/HfO2/SiO2/Si or Al/TiN/HfO2/SiO2/Si) varies with the amount of Al that diffuses to the metal/dielectric interface and is used to measure the diffusion. The WF as a function of the bottom metal layer thicknesses is extracted using capacitance-voltage measurements. A thickness above 15 nm appears to be necessary for maintaining the WF without any effects from the top metal layer. Depending on the reactivity between different elements in different metal layers, an additional barrier may be needed to prevent unwanted diffusion and reaction. Investigating the thermodynamics of different elements within the gate stack is important and can help in choosing appropriate materials. In the last part of the thesis, the diffusion barrier properties of another amorphous metal, TaWSiC, is studied for interconnect application. Copper/barrier/Si structures are annealed at different temperatures and characterized for phase and structural changes. Unlike polycrystalline Ta, 5 nm of TaWSiC is able to prevent Cu reaction with Si up to 550C.
Three essays in causal inference [electronic resource]
Keywords: Economics.

This thesis is a collection of three essays on causal inference. Chapter 1 considers the problem of constructing confidence intervals or bands for the quantiles of treatment effects under settings where point identification is impossible. I show that under settings where selection is only on observables bounds for the entire quantile function can nonetheless be estimated, and this enables the estimation of confidence bands. I also extend these results to instrumental variable settings. Computational complexity analysis demonstrates that the methodology I propse is computationally attractive. Chapters 2 and 3 consider extending the synthetic control approach of Abadie, Diamond, and Haimueller (2010) to two different settings where individual-level data is available. In Chapter 2 I consider estimating average treatment effects by constructing for every subject in the treatment group a synthetic twin composed of individuals in the control group. I show that the resulting estimator is unbiased when selection is dependent only on observables. I also show that matching estimators and OLS estimators can be viewed as special cases of synthetic control estimators. Furthermore, I demonstrate that the estimator is highly scalable computationally. In Chapter 3, I consider settings where either panel data or repeated cross-sectional data is available. I show that the synthetic control estimator in this setting can yield asymptotically valid standard errors when aggregation is done from individual-level data, unlike the original work of Abadie, Diamond, and Hainmueller (2010). To demonstrate asymptotic properties, two types of asymptotic analysis are carried out: one appropriate when the number of observations at each point in time in each subpopulation tends to infinity, and one suitable for stationary aggregate data and in which the number of pre-intervention periods gets large.
Tiered representations for audio-based multimedia and speech retrieval [electronic resource]
Keywords: Electrical Engineering.

As society continues to move into an information age, millions of digital documents are created and stored for private or public viewing every day. Beyond text (e.g., searching for websites or emails), these documents can come in many forms, including speech, audio or video. With a rapidly increasing quantity of digital content floating around there is an increasing demand and challenge in retrieving those items effectively. In many cases the meaningful information for matching a query with the relevant documents is embedded in a raw signal (e.g., digitized sound wave), and this makes the retrieval even more challenging. This dissertation proposes methods for performing retrieval in two particularly challenging scenarios where both the query and retrieval item are in an audio format. The first scenario involves personalized spoken utterances and the second involves audio-based retrieval of videos that contain specific events (e.g., a birthday party). In both cases, because the audio is in a raw format, it first needs to be converted into a meaningful representation that allows for comparison with the previously created documents. Further, the audio is recorded from personal recording devices which introduces additional challenges. There are various ways to represent an audio signal, ranging from the unsupervised frame level (tens of milliseconds) to the supervised, concept level (a few seconds). Since each tier of representation has its own strengths and weaknesses, in addition to a presentation of my work in developing diverse representations for audio retrieval, I also present how these diverse representations can be combined to leverage the benefits of both tasks.
The ties that bind [electronic resource] : neighborhood civic networks and collective action in San Francisco
Keywords: Sociology.

This dissertation examines whether certain structural properties of the inter-organizational networks between civic associations in a neighborhood are related to variations in local collective action. Building on the assumption that collective action events, which help foster ties of community within a given area, are mostly organized by local civic associations whose mission it is to build civil society, I argue that each association's ability to engender collective action is directly impacted by its network of ties to other associations in the area. While there is no doubt that an association's own characteristics, such as its age, size, or issue-area may resonate more in one locale and thus render it more powerful in relation to its counterparts, this does not necessarily preclude it from being affected by network ties which are a part of any civic group's social environment. The study utilizes a mix of quantitative and qualitative evidence gathered in San Francisco over the course of 2011 and the findings provide confirmation of a relationship between civic network characteristics and local collective action.
Topics in adaptive inference [electronic resource]
Keywords: Statistics.

The recent rapid expansion in data collection has presented the field of statistics with an inexhaustible array of exciting new applications and problem settings not directly covered by classical methods or theory. In more complex problems, we must choose an appropriate computational algorithm, statistical model, or scientific question that is well-tuned to the sampling distribution we are presented with. Thus the payoff from using methods that adapt to the data set at hand is high. This work details several such methods. Chapter 2, essentially a reproduction of Fithian and Hastie (2014), describes an adaptive subsampling strategy for computationally efficient inference on massive data sets. Using a modified case-control sampling algorithm, we ``compress'' a large data set into a much smaller subsample, enriching for the most informative observations. Our algorithm enables potentially much faster analysis, at a provably small cost to statistical performance. Most statistical inference procedures are formally invalid if they are preceded by ``data snooping.'' However, in most real data problems it is hard to specify a reliable model a priori. Chapter 3, essentially a reproduction of Fithian, Sun, and Taylor (2014), discusses methods for carrying out valid inference after adaptive model selection, correcting for selection by conditioning on the model selected. Chapter 4 is as-yet unpublished work and gives further examples of selective inference applied to specific problems. First, I discuss the problem of ``rank verification'' --- testing, for example, whether the candidate who receives the most votes in a random survey is actually leading in the population from which the survey was taken. Second, I discuss an exact nonparametric selective inference procedure for use when a the data fail a goodness-of-fit test for some set of parametric assumptions.
Topics in modeling the term structure of interest rates [electronic resource]
Keywords: Economics.

This dissertation studies topics of current interest in modeling the term structure of interest rates. Chapter 1 develops and estimates a canonical arbitrage-free dynamic term structure model that incorporates macroeconomic variables. The model allows macroeconomic variables to contain information about future yields that is not reflected in the current cross section of yields ("unspanned" macro variables). Moreover, it accommodates rich feedback between macroeconomic and yield variables. Chapters 2 and 3 analyze the behavior of yields in low-interest environments. Standard Gaussian term structure models do not impose a lower bound on yields. As shown in Chapter 2, this can lead to estimation bias when a lower bound is present in the data. Chapter 3 develops a new technique for fast and accurate approximation of arbitrage-free bond yields in a class of "shadow rate" models that formally impose a lower bound on observed yields. Chapter 4 ties together the previous three chapters. It sets up and estimates a shadow rate term structure model with unspanned macro variables, and uses the model to analyze interest rate expectations before, during, and in the aftermath of the recent financial crisis.
Topics in the theory of strongly correlated systems [electronic resource]
Keywords: Physics.

Electrons in solid state materials display a remarkable diversity of strong correlation effects, many of which are poorly understood theoretically. In this regard, the cuprate high temperature superconductors are the shining example, remaining enigmatic despite decades of study. This dissertation examines basic questions in condensed matter physics inspired by these remarkable materials. In the first part, I consider aspects of the phenomenology of the cuprate and ruthenate unconventional superconductors. Emphasis is placed on the interpretation of existing experiments, and the proposal of new ones, to clarify the electronic structure of these materials and permit a more thorough microscopic understanding. In the second part, I focus on the abstract problem of nematic quantum criticality in metals, which recent experiments suggest may play a crucial role in the physics of both cuprate and iron-based superconductors. I attack this problem using both a field theoretic approach, valid at weak coupling, as well as fully nonperturbative, numerically exact Monte Carlo simulations in the strong coupling regime, yielding simple, unexpected results that are reminiscent of experiment.