VictorJuiz/thesis huggingface dataset:
There's no limit [electronic resource] : mathematics teaching for a growth mindset

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.

Keywords: Education.
Advisor: Boaler Jo
Dweck Carol S.
Stipek Deborah J.
Thermal maturation-induced evolution of the elastic and transport properties of organic-rich shales [electronic resource]

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.

Keywords: Geophysics.
Advisor: Vanorio Tiziana primary advisor. Thesis advisor
Graham S. A. (Stephan Alan)
Mavko Gary
Thermal stability, structure, and electrical properties of amorphous metal alloys for electronic applications [electronic resource]

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.

Keywords: Materials Science and Engineering.
Advisor: Clemens B. M. (Bruce M.) primary advisor. Thesis advisor
Deal Michael D.
Nishi Yoshio
Three essays in causal inference [electronic resource]

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.

Keywords: Economics.
Advisor: Hong Han primary advisor. Thesis advisor
Imbens Guido advisor. Thesis advisor
Wolak Frank A. advisor. Thesis advisor
Tiered representations for audio-based multimedia and speech retrieval [electronic resource]

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.

Keywords: Electrical Engineering.
Advisor: Gray Robert M.
Osgood Brad primary advisor. Thesis advisor
Akbacak Murat
Gill John T.
The ties that bind [electronic resource] : neighborhood civic networks and collective action in San Francisco

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.

Keywords: Sociology.
Advisor: McAdam Doug primary advisor. Thesis advisor
Parigi Paolo
Powell Walter W. advisor. Thesis advisor
Topics in adaptive inference [electronic resource]

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.

Keywords: Statistics.
Advisor: Hastie Trevor primary advisor. Thesis advisor
Candès Emmanuel J. (Emmanuel Jean) advisor. Thesis advisor
Taylor Jonathan E. advisor. Thesis advisor
Tibshirani Robert advisor. Thesis advisor
Topics in modeling the term structure of interest rates [electronic resource]

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.

Keywords: Economics.
Advisor: Singleton Kenneth J. primary advisor. Thesis advisor
Harding Matthew C. advisor. Thesis advisor
Levin Jonathan
Topics in multivariate density estimation and its applications [electronic resource]

This thesis centers around partition based multivariate density estimation and its applications to bioinformatics, data visualisation and two-sample divergence estimation. It is formally divided into three parts: i. Optional P\'{o}lya Tree \citep{Wong2010} and Sequential Bayesian Partitioning \citep{Lu2013} is very computationally intense and face challenges in higher dimensional applications. Since the density is uniform conditioned on each sub-region for the piecewise density function, we attempt to control the uniformity in each sub-region directly. Discrepancy in Quasi-Monte Carlo provides a natural way to control the uniformity quantitatively as well as a theoretical framework on the estimated density function. We demonstrate that our new method is computationally more attractive and the bounds derived are tight. We also apply it to Flow Cytometry analysis and multivariate data visualisation. ii. The original density estimate obtained from Optional P\'{o}lya Tree or Sequential Bayesian Partitioning or Discrepancy is a piecewise constant function supported on binary partitions. However, some applications require a continuous density estimation on the samples. Inspired by the Finite Element Method in numeric partial differential equations, we triangulate the domain and construct a piecewise linear density function with the linear basis (i.e., first order basis). This construction is further recast to a quadratic programming problem which can be effectively solved by optimization packages. iii. Divergence such as KL divergence plays an important role in informatics and statistics \citep{Nguyen2010, Wang2005}. We extend our partition based density estimation to two-sample case and construct a partition capable of capturing the difference between them. We demonstrate that our method provides a unified way to estimate three classes of divergences (KL divergence, Total variation distance as special cases) and achieve good convergence. Some higher dimensional examples are also tested, which are rare in previous research papers.

Advisor: Wong Wing Hung primary advisor. Thesis advisor
Owen Art B. advisor. Thesis advisor
Ying Lexing advisor. Thesis advisor
Topics in the theory of strongly correlated systems [electronic resource]

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.

Keywords: Physics.
Advisor: Kivelson Steven primary advisor. Thesis advisor
Raghu Srinivas
Qi Xiaoliang advisor. Thesis advisor
Toward a coinsurance theory of group formation under risk [electronic resource]

Five experiments show that people's tendency to join resource-sharing groups under environmental risk, or coinsure, depends on the availability of resources. People seek to form groups as a means to diminish the impact of risk in situations characterized by abundance; in situations where resources are scarce, people tend to avoid groups as risk increases to have a chance at a better outcome. This effect generalizes across different levels of wealth (i.e., variance in endowed resources) within groups. Independently of the level of external risk, group formation decisions under conditions of abundance are driven by self-transcendent values and concern for others, while group formation decisions under conditions of scarcity are driven by conservation values. Taken together, these studies introduce a novel perspective on cooperation that provides a useful lens for group formation.

Keywords: Business.
Advisor: Halevy Nir
Miller Dale T. primary advisor. Thesis advisor
Flynn Francis J. advisor. Thesis advisor
Kramer Roderick M. (Roderick Moreland)
Toward understanding the function of the G2 phase in the mammalian somatic cell cycle [electronic resource]

This thesis contains studies on the G2 phase of the cell cycle, which is arguably the most mysterious aspect of how cells prepare for cell division. Chapter 1 gives a historical overview of research on G2 and introduces key concepts and molecular players. G2 phase differs across model systems. It is absent in budding yeast as well as the early embryos of Xenopus and Drosophila. It is particularly well-understood in later embryonic development of Drosophila and in fission yeast, where an important regulator is mitotic phosphatase Cdc25. In mammalian tissue culture cells, the model system that is closest to cells of the human body, both Cdc25 and RCC1, a protein that emerged out of the analysis of mammalian cell-cycle mutants, present tantalizing possibilities for how the G2 phase may be regulated, but many unanswered questions remain. Chapter 2 presents results on how the duration of G2 phase affects mitotic progression, in particular the timeliness of anaphase. This work uses MCF10A cells that express fluorescently tagged PCNA, a marker of DNA replication, and fluorescently tagged histone H2B, a marker of DNA morphology, in live-cell microscopy to directly measure durations of all cell-cycle phases. G2 phase is then shortened by PD0166285, a drug known to induce premature mitosis. Shortening G2 phase results in a prolonged interval from nuclear envelope breakdown to anaphase that is partially rescued by inhibiting the spindle assembly checkpoint and not affected by inhibiting protein synthesis. Chapter 3 presents possible future directions for these studies. It contains preliminary data on the effect of shortened G2 on microtubule-kinetochore attachment, repair of DNA damage, and the centrosome.

Keywords: Chemical and Systems Biology.
Advisor: Ferrell James Ellsworth primary advisor. Thesis advisor
Cimprich Karlene advisor. Thesis advisor
Meyer Tobias advisor. Thesis advisor
Stearns Tim advisor. Thesis advisor
Transactions for software defined networks [electronic resource]

Computer networks have evolved tremendously over the past fifty years, evolving from their humble beginnings as interconnections for only several dozen academic hosts in the 1970s to vast hundred million dollar pieces of infrastructure supporting commerce and communication and communication services fundamental to our modern way of life. A major goal of the networking community is to build services, tools, and systems to manage these large, important networks efficiently while enforcing target policies — e.g., filtering packets from black-listed sources or preventing congestion on target links. Software defined networking (SDN) has been a transformative architecture for building management services that ensure such policies. We propose and implement a new transactional execution model for software defined networks. This execution model explicitly guarantees that either all management commands execute and their changes take effect or none do, resolving serious bugs discovered in existing software defined networking systems. Using fine-grained locking, a split execution model, and a sharded architecture, a transactional execution model can scale to provide tens of thousands of transactions per second. Finally, we show that a transactional model provides the versatility to express almost all network policies achievable in non-transactional systems, and allows new classes of debugging applications for software defined networks.

Keywords: Electrical Engineering.
Advisor: Levis Philip primary advisor. Thesis advisor
Aiken Alexander advisor. Thesis advisor
McKeown Nick advisor. Thesis advisor