VictorJuiz/thesis huggingface dataset:
Thermal and mechanical properties of molecularly-confirmed polymer/glass nanocomposites
Keywords: Materials Science and Engineering.

Development of the next generation of high-performance polymer nanocomposites requires a detailed understanding of the underlying interfaces between constituents and their impact on the thermal and mechanical properties. In particular, the thermal conductivity and cohesive fracture resistance in nanocomposite materials is defined by the nature of interactions at the interface between the constituents. In my research, I have made advances in the performance of hyper-confined polymer nanocomposites using surface functionalization for fine-tuning the interfaces between molecularly confined polymers and the organosilicate glass matrix to improve the thermal and mechanical performance of these nanocomposites. Thermal reflectance and thin-film mechanics techniques were used to measure film thermal conductivity and mechanical properties of these nanocomposites. To correlate the improved thermal and mechanical properties, I used spectroscopic methods to quantify the chemical nature of the interface between functionalized porous organosilicate glass and organic polymers. A positive correlation is found between the extent of bonding at the interface as determined by infrared and X-ray photoelectron spectroscopies for multiple polymers and the resulting thermal and mechanical properties. Hyper-confined polyimide in porous organosilicate glass is a promising candidate for high temperature applications due to high fracture resistance and thermal stability. To characterize the nanocomposite performance, a thermal oxidative aging study was conducted and factors affecting the thermal stability of nanocomposite are analyzed. Using infra-red spectroscopy in addition to other techniques, I identified the key chemical and physical degradation pathways for the nanocomposite of polyimide and organosilicate glass at elevated temperatures. Surprisingly, the polyimide was found to be remarkably stable at > 300°C for over 200 hours in the nanocomposite, with the organosilicate glass being the limiting factor for thermal stability. Overall, I have developed an experimental framework combining chemical and mechanical methodologies to uncover the mechanisms governing the performance of hyper-confined polymer nanocomposites. These results will help further our understanding of the key structural and chemical factors governing the thermal and mechanical properties of nanocomposites
A thesis of minimal degree : two
Keywords: Mathematics.

In this thesis, we study geometry and moduli spaces associated to low degree covers. There are two parts to this thesis. The first part comprises the bulk of the thesis and focuses on covers of degree 2. It is motivated by the Cohen-Lenstra heuristics in number theory. The second part contains three topics. The first relates to certain low degree covers of moduli spaces of elliptic curves, the second topic relates to heights on elliptic curves in characteristic 3, and the third topic relates to the Casnati-Ekedahl structure theorems for covers
Three empirical essays on the historical development of cities
Keywords: Economics.

This dissertation explores several topics related to the historical development of cities. In the three chapters, I investigate 1) labor market consequences of urban displacement, 2) how land supply constraint impedes long-run urban growth, and 3) the phenomenon of urban mortality penalty in early modern Europe. The first chapter is titled "Does Slum Demolition Affect the Economic Outcomes of the Displaced? Evidence from Victorian England". I use a research design that compares displaced slum residents and comparable non-displaced ones living on the same street at baseline. I combine individual-level census data and detailed government archival records on slum demolition to show that displaced slum residents experienced labor market disruptions up to 10 years after eviction. The second chapter is titled "Does Land Use Restriction Impede Long-run Urban Development? Evidence from the Ejido System in Mexico". I find that a historical communal land system that outlawed the conversion of agricultural land for non-agricultural use impeded urban expansion in 20th century Mexico. Using a matched difference-in-difference design, I find cities that became surrounded by ejido land grew 10 percent slower in the second half of the 20th century. The third chapter is titled "Documenting the Urban Mortality Penalty in Early Modern Europe: Evidence from Migrants". I use a crowdsourced genealogy dataset that records the longevity and the migration history of millions of individuals in Europe. I find that, comparing between migrants born in the same area, those who moved to urban areas lived on average 1.6 years shorter than migrants who moved to rural areas
Topics in convex optimization for optimal control and reinforcement learning
Keywords: Electrical Engineering.

Optimal control describes the problem of finding a control to minimize an objective function for a dynamical system over a period of time. It has been applied in a wide variety of applications in robotics, signal processing, and machine learning over several decades. On the other hand, reinforcement learning (RL) assumes the uncertain model of transition dynamics and has achieved great empirical success in recent years including simulated game scenarios and robotics. This thesis focuses on topics in both optimal control and reinforcement learning
Topics in exact asymptotics for high-dimensional regression
Keywords: Statistics.

Exact asymptotic theory refers to a collection of techniques for precisely characterizing the distribution of high-dimensional regression estimators. Examples of the estimators it characterizes include the Lasso, ridge regression, the elastic net, and SLOPE, among others. The theory requires strong assumptions---Gaussian and sometimes independent covariates---and is usually developed for one restricted class of estimators at a time. This thesis expands the scope of exact asymptotic theory by providing generalizations to symmetric but possibly non-separable penalties with independent covariates and to correlated covariates in the context of the Lasso. Further, it provides novel exact asymptotic characterizations of the joint distribution of two regression estimators computed on the same data. It applies these developments and existing theory to important statistical problems, including optimal penalty design, adaptive estimation, inference with the debiased Lasso, hyperparameter tuning, and consistent estimation of low-dimensional parameters when high-dimensional nuisance parameters cannot be estimated well
Toward Few-Shot Response Generation for Conversational Agents
Keywords:  Program in Symbolic Systems
stanford
symbolic systems
response generation
conversational agent
virtual assistant
natural language processing
task oriented dialogue
Thesis

One of the major impediments to the deployment of task-oriented response generation models in real-world scenarios is a lack of labeled in-domain training data. In this thesis, we explore a multi-task learning approach in which we pre-train a model with unlabeled dialogues, and then fine-tuned in a few-shot setting to generate factually accurate and natural agent responses.
We formulate our primary task as utterance paraphrasing, where a template-based agent utterance in the context of the preceding dialogue is converted into a more natural-sounding one. We adapt unlabeled dialogues as pre-training data for this task by using automatically generated paraphrases of the last agent utterance as templates to predict the utterance in the context of the preceding dialogue turns. Since the real templates lack the contextual information embedded in the paraphrases, we introduce an auxiliary task, next sentence prediction, where the last turn of a dialogue is masked in the input and used as the predicted gold output.
Evaluation across several conversational datasets shows that our pre-training strategy improves the quality of responses in an in-domain context, indicating that leveraging unlabeled datasets can be an effective method for improving the quality of responses.
Towards collaborative development of lineage-agnostic cells
Keywords: Electrical Engineering.

Present methods for engineering living organisms tend to rely on "atheoretical" tinker-test or "brute-force" design via large-scale automation. To fully enable a "biology age", we must understand cells -- the fundamental unit of life -- well enough to build them. The two existing cell-building approaches are based on (i) minimizing genomes, and (ii) ab initio synthesis of protocells. Minimization of natural genomes benefits from the viability of existing cells but has failed to resolve the functions of all the genes necessary for life. Conversely, bottom-up cell building efforts start from known components but have yet to produce viable cells. Here, I report methods for building synthetic cells to broadly enable the cell building community. First, I combine the strengths of existing cell building approaches by evaluating the potential of minicells -- cell-like "containers" devoid of genetic material -- as a natural chassis for instantiating fully-understood synthetic genomes. I demonstrate that minicells can be extracted at high purity from a growing culture of progenitors. Next, I show that batches of purified minicells are capable of heterologous gene expression. Finally, I quantify the absolute expression capacity of individual minicells and find that about 13% of gene-expressing minicells should have the capacity to express an entire genome. Thus, minicells should be capable of "booting-up" ab initio genomes sufficient to enable a framework supporting distributed design of lineage-agnostic genomes. Second, as a significant step towards genome design, I determine the degree to which the PURE (protein synthesis using recombinant elements) cell-free system is qualitatively capable of self-regeneration. Specifically, I measure the extent to which single-enzyme depletions of PURE result in significant decreases in protein expression. For those single-enzyme depletions that exhibit substantial decreases in expression, I demonstrate that PURE-produced versions of each enzyme can be used to recover PURE activity, signifying successful self-regeneration. The culmination of my work with PURE is a formalized framework undergirding collaborative development of lineage-agnostic cells
Towards comprehensive action understanding in videos
Keywords: Electrical Engineering.

An enormous amount of videos are created, spread, and watched daily. In the ocean of videos, the actions and activities of humans are often the pivots. We desire machines to understand human actions in videos as this is essential to various applications, including but not limited to healthcare, security system, and human-robot interactions. For these applications to be realized, action understanding must go beyond simply answering "what is the action", but more comprehensive. An intelligent agent should be able to know "who/where is the actor", "what/where is the object", "what interaction is happening between the actor and the object", "when does an action start and end", and more. Achieving comprehensive action understanding is non-trivial since the need for data and labels combinatorially increases when trying to solve multiple problems, not to mention that video data and labels are expensive to collect, store, and consume. Therefore, to obtain comprehensive action understanding, we not only need to perform multiple tasks but also have to ensure data efficiency. In this dissertation, we discuss three questions to realize data-efficient and comprehensive action understanding. How to reduce the need for data and labels? How to perform multiple tasks without combinatorial growth of data? How to solve new problems efficiently with some other problems solved? For the first question, our works on few-shot video classification and semi-supervised temporal action proposals introduce video-specific techniques and strategies for learning with less supervision. For the second question, we demonstrate how to avoid enumerating all combinations of categories from subtasks by knowledge disentanglement in a study on actor-action segmentation. For the third question, we propose constructing compositional representation from human-object relationships in videos, and such representation leads to better generalizability in action recognition models
Towards low temperature solid source synthesis of monolayer molybdenum disulfide and low resistance contacts to molybdenum disulfide-based devices
Keywords: Electrical Engineering.

Silicon (Si) transistors have recently reached nanometer-scale dimensions. Further gate length scaling requires thinner body channels and low resistance contacts. Yet, Si carrier mobility severely degrades at thicknesses below ~3 nm due to surface roughness, leading to lower on-state current for short gate-length transistors. MoS2 is a 2-dimensional (2D) atomically smooth semiconductor that retains its band gap and electrical properties down to single monolayers (3 atoms thick), making it appealing for transistor gate length scaling. In addition, stacking of transistors in 3 dimensions (3D) will be needed to further increase their density when 2D scaling reaches diminishing return. However, synthesizing high mobility MoS2 with thin layers and low resistance contacts has been an ongoing challenge in developing MoS2 for such applications. In addition, for many 3D heterogeneous integration applications, relatively low temperature (400-600°C) material deposition techniques are necessary, on time scales of 2 hours or less. In the first part of this thesis, we describe the chemical vapor deposition (CVD) growth of MoS2 using solid source precursors. By carefully controlling precursor amount and placement as well as optimizing the temperature heating ramp, sulfur (S) injection is optimally timed for efficient reaction with molybdenum trioxide (MoO3). In the second part, we describe efforts to make low-resistance metal contacts to MoS2. By inserting a Ta2O5 insulator layer between metal contacts and multi-layer MoS2, contact resistance can be reduced by up to 3 orders of magnitude along with significant Schottky barrier height reduction. In the final part, we report electrical characteristics of 1L MoS2 grown at 560°C with carrier mobility comparable to 1L MoS2 grown at higher temperatures, within the 600°C thermal budget for back-end-of-line (BEOL) processing and 3D integration. The record high drive currents and effective mobilities achieved on these 560°C 1L films are the best reported for solid source CVD-grown 1L MoS2 below 600°C providing an encouraging path towards utilizing MoS2 to continue transistor density scaling into the future
Towards semantic representations of tissue organization from high-parameter imaging data
Keywords: Bioengineering.

Viewed at a high spatial and molecular resolution, every individual instance of a biological tissue is unique. However, it is a tenet of evolution that prior evolutionary successes are adapted and repurposed for variations on function and for the creation of new functions. Thus, it would be expected that the organization characteristic of a tissue's type can be expressed in terms of a collection of repeated biological units that respect some rules governing their assembly and collective functionality. Advances in high-parameter imaging technologies present the opportunity to observe tissues at high spatial and molecular resolution. What, then, are the repeated biological units and the rules (governing the units' assembly and collective functionality), characterizing the organization of tissue types viewed through the lens of such technologies? We present conceptual, mathematical and algorithmic tools towards possible answers of this question, and their applications to high-parameter tissue imaging data of lymphoid tissues and the tumor microenvironment. The results yield clinically relevant insights into the specific biology of these tissues, as well as hint at general principles of tissue organization that become apparent only when tissues are assayed in such detail
Towards understanding nanoscale and mesoscale order in organic semiconductors
Keywords: Materials Science and Engineering.

Organic semiconductors are emerging as promising semiconductor materials for a wide range of electronic and electrochemical device applications including displays, electronics, solar cells, chemical sensors, and energy storage. Recent advances in molecular structure-property relationships and backbone and side chain engineering have enabled significant progress in improving their charge transport properties and carrier mobilities, which are now competitive with amorphous silicon. Moreover, over the past few years, a series of conjugated polymers with polar side chains have been developed to operate as mixed ionic/electronic conductors in aqueous media. Despite these advances, an understanding of the multiscale mechanism for ionic and electronic charge transport remains elusive, limiting further progress in materials development. Charge transport requires continuous coupling across all length scales (i.e., atomic to mesoscale). Understanding the local environments where ionic and electronic charges reside in a semiconducting polymer and the energetic landscape for charge transport are key questions to address in the search for designing better materials. The focus of this dissertation has been on attempting to improve our understanding of the relationship between structure and its impact on macroscopic properties. In this dissertation, I present several methods to characterize the structure of semiconducting polymers and discuss the role of structure on optoelectronic and electrochemical properties. In the first part of this dissertation, I present a series of methods to extract and measure the nanoscale and mesoscale order of semiconducting polymers using low-dose, high-resolution transmission electron microscopy images and data analytics. These results showcase the applicability of developing novel methods to characterize the rich, complex mesoscale structure of conjugated polymers with unprecedented detail. In the second part of this dissertation, I combine a series of electrochemical and structural characterization techniques to study polymer volumetric charging in a series of aqueous electrolytes. These novel semiconducting polymers have been specifically designed for electrochemical device applications that leverage ionic/electronic charge transport. This work elucidates complex polymer- and electrolyte- dependent structure-property relationships, which will help further developments on the rational design and understanding of this new family of materials. Overall, these studies suggest design principles to continue to advance the field of organic electronics
Township-level Positions in the Chinese Bureaucracy: A Study on Tenure and Personnel Mobility Patterns
Keywords:  Stanford Global Studies
East Asian Studies
China
Bureaucracy
Social sciences > Network analysis
Text
Thesis

As the lowest level of government in the Chinese bureaucracy, Township-level government serves as the link both between the state and the society and between urban cities and rural villages. Using the personnel records of the bureaucrats at and beyond the township level among 13 Chinese counties between 1990 and 2012, this thesis studies the structural relationships of the township-level government in the Chinese bureaucracy to understand the interaction pattern among the governments in different townships and between the township- and the upper-level governments. Specifically, this thesis examines 1) the structural characteristic of the township-level government reflected in the tenure of township-level positions; 2) the structural relationships of the township-level government reflected in the personnel mobility; and 3) how the tenure and personnel mobility shape the social relationships among township- and upper-level bureaucrats. This thesis quantitatively reveals the formal organizational rules and patterns at the lowest levels of the Chinese bureaucracy.
Trajectory forecasting in the modern robotic autonomy stack
Keywords: Aeronautics and Astronautics.

Autonomous systems are increasingly nearing widespread adoption, with new robotic platforms constantly being tested and deployed alongside humans in domains such as autonomous driving, service robotics, and surveillance. Accordingly, human-robot interaction will soon be present in many everyday scenarios. However, there are still many challenges preventing autonomous systems from safely and smoothly navigating interactions with humans. For example, while merging into traffic is one of the most common day-to-day maneuvers we perform as drivers, it poses a major problem for state-of-the-art self-driving vehicles. The reason humans can naturally navigate through many social interaction scenarios, such as merging in traffic, is that humans have an intrinsic capacity to reason about other people's intents, beliefs, and desires, applying this reasoning to predict what might happen in the future and make corresponding decisions. As a result, imbuing autonomous systems with the ability to reason about other agents' potential future actions is critical to enabling informed decision making and proactive actions to be taken in human-robot interaction scenarios. Indeed, the ability to predict other agents' behaviors (also known as "trajectory forecasting") has already become a core component of modern robotic systems, especially so in safety-critical applications such as autonomous vehicles. Towards this end, this dissertation tackles the development of trajectory forecasting methods, their effective integration within the robotic autonomy stack, and the injection of task-awareness in their performance evaluation
Transcriptional and functional convergence of coronary endothelial lineages in mouse and human
Keywords: Genetics.

Coronary blood vessels comprise the arteries, veins and capillaries that supply the heart. In mice, the endothelial cells (ECs) that form the inner lining of these vessels are derived primarily from two lineages during embryonic development. The first lineage comes from the endocardium (Endo), the layer of cells lining the inside of the heart chambers. The second lineage comes from the endothelium of the sinus venosus (SV), the major inflow tract of the developing heart. Although these two lineages are known to contribute to complementary regions of the heart during both development and adulthood, it is unknown whether there is any difference in their function or whether they retain any transcriptional markers of their origins. In addition, it is unknown whether ECs in human hearts also originate from the same sources. In order to address these questions, I combined lineage tracing of Endo-derived ECs in murine hearts at various stages with single-cell RNA sequencing. I discovered that while Endo- and SV-derived ECs can be transcriptionally distinguished at e12, they had equivalent transcriptional patterns at e17.5. Additionally, at e17.5 capillary ECs segregated into two populations based on the influences of blood flow and hypoxia. On the other hand, adult ECs from both lineages were transcriptionally homogenous with respect to both lineage and location, and responded similarly to ischemia-reperfusion injury. Finally, developing human hearts contained capillary ECs in similar cell states as e17.5 mouse hearts, indicating that mouse and human coronary development follow similar trajectories