VictorJuiz/thesis huggingface dataset:
Elucidating the roles of retinoic acid and enteric glia in colorectal cancer
Keywords: Immunology.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and third leading cause of cancer mortality in the United States, highlighting an urgent need for greater understanding of the mechanisms underpinning CRC development. Here, we find that mice with colitis-associated CRC exhibit a marked decrease in colonic all-trans retinoic acid (atRA) due to alterations in the atRA metabolic enzymes. Patients with ulcerative colitis (UC), UC-associated CRC, and sporadic CRC additionally exhibit similar alterations, consistent with reduced colonic atRA. In mice, inhibition of atRA signaling promoted tumorigenesis, whereas supplementation of atRA reduced tumor burden. This anti-tumor effect was mediated by CD8+ T cells, which were activated as a result of MHC I upregulation on the tumor epithelial cells. Consistent with these findings, increased colonic expression of the atRA catabolizing enzyme, CYP26A1, in CRC patients was found to correlate with reduced frequencies of tumoral cytotoxic CD8+ T cells and with worse disease prognosis. Additionally, we also discovered that enteric glial cells play a critical role in early CRC development. Although the mechanism remains elusive, we demonstrate that the pro-tumorigenic function of the glia does not depend on effects on CD8+ T cells or intestinal inflammation. Altogether, our work here reveals two heretofore undescribed mechanisms of CRC tumor development and identifies potential new targets for prevention and treatment of CRC.
Elucidating the temporal dynamics of human visual cortex [electronic resource]
Keywords: Psychology.

The world around us is constantly changing and in many more ways than we can see. As visual stimuli bombard us at different rates, some changes occur on timescales that are too fast or slow to detect with the naked eye. However, the human visual system is able to perceive a broad enough range of temporal dynamics to distinguish stable aspects of the environment from rapidly changing ones and operate on them in real time. While this may seem effortless, the neural mechanisms that give rise to this fundamental perceptual ability are largely unknown. In the three experiments described here, we use functional magnetic resonance imaging (fMRI) and computational techniques to model how neurons in the visual system code changes to the appearance of the world over time. First, we examine how the transient and sustained aspects of a stimulus are processed in the visual system focusing on regions in early visual cortex in Study 1 and regions in high-level visual cortex in Study 2. Both studies reveal differential response dynamics between ventral temporal cortex (VTC) and lateral temporal cortex (LTC). That is, we find that brain regions in VTC receive contributions from both sustained and transient channels, whereas regions in LTC are dominated by contributions from the transient channel. In Study 3, we test whether the distinct temporal dynamics observed across domain-specific regions in Study 2 have behavioral consequences. Contrary to prevailing theories, we find that different regions have different processing capacities, which have behavioral implications. Specifically, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. Together, these results suggest that temporal processing capacity is a characteristic of synchronized domain-specific networks in high-level visual cortex and contributes to the segregation of cortical regions.
Emigration and the industrial revolution in German Europe, 1820-1900
Keywords: History.

Starting around 1850, the economically backward region of German central Europe embarked on a period of rapid economic growth that would soon transform it into a global economic powerhouse. Looking beyond the standard list of explanatory factors and conditions for industrialization (including proximity to Britain or German technological ingenuity), this dissertation offers a historically contingent interpretation by situating the region in its Atlantic World context. Between 1820 and 1900, some five million German speakers emigrated to North America. The study argues that this movement helped to catalyze development back in Europe because it exposed large, otherwise isolated segments of the population to an unfamiliar world of economic behaviors, mores, ideas, and institutions. Six chapters explore how this exposure mobilized the rural, working population for a centralized, industrial production regime; how it sparked the creation of new financial institutions like 'universal banks, ' often described as key during later stages of development; and how subtle changes in economic morality forced the introduction of innovative commercial laws upon which subsequent iterations of German industrialization would built.
Emotion and emotion regulation in groups
Keywords: Psychology.

People tend to respond emotionally to events that are related to their groups, even if these events do not have any direct effect on their lives. However, even as group members experience such group-based emotions, they are not necessarily passive. They frequently regulate not only their own emotions but those of others as well. In so doing, group members use these emotions as tools to influence their environment. The overarching goal of this dissertation was to examine emotion and emotion regulation in group contexts. Four inter-related projects were conducted. The first project provides a theoretical framework for identifying unique aspects in the unfolding and regulation of emotions in groups. The second and third projects empirically address current gaps in the literature. More specifically, the second project examines how people aggregate and summarize emotional expressions of multiple people, and how they categorize these emotional responses as generated by ingroup or outgroup members. The third project examines how group members are influenced by the emotions of their ingroup and assesses whether motivational forces may assist individuals in resisting or enhancing such influence. Finally, the fourth project introduces an emotion regulation intervention designed to increase group members' hope regarding the possibility of group change in the context of intergroup conflicts. Taken together, these four projects provide new theory, empirical findings, and an intervention related to emotions in groups. The dissertation concludes with a discussion of future research directions.
Emotional diversity in organizational settings : how culture and ideal affect shape employment and leadership outcomes
Keywords: Psychology.

What is the role of culture and emotion in organizational settings? The present dissertation addresses this question in three sets of studies. Using cross-cultural methods and sampling from participants in the United States (European Americans and Asian Americans) and East Asia (Hong Kong Chinese), we examine how emotions influence behaviors and outcomes from the lowest levels of organizations (i.e., self-presentation and hiring decisions for entry-level positions) to the highest levels of organizations (i.e., leadership choice). Part 1 examines whether culture and ideal affect (i.e., the emotions that we value and ideally want to feel) shape how participants present themselves in an employment setting. Next, Part 2 investigates whether culture and ideal affect shape hiring decisions. Finally, Part 3 examines how these processes shape whom we choose as leaders of organizations that vary in performance (i.e., growth, stability, and crisis) and across different occupational sectors (i.e., business, government, research). Across 8 studies, we show that European Americans and Asian Americans want to and actually do present themselves as excited and enthusiastic on job applications, hire excited job candidates, and choose excited leaders more than do Hong Kong Chinese, in part because they value excitement states more. In contrast, Hong Kong Chinese want to and actually do present themselves as calm on job applications, hire calm job candidates, and choose calm leaders more than do European Americans and Asian Americans. Together, these findings have implications for how emotions shape individual and group outcomes in organizational settings. In addition, by focusing on the under-investigated area of cultural differences in emotions, we suggest a promising area for interventions aimed to increase diversity and inclusiveness in organizational settings.
Empire of hunger : famine and the French colonial state, 1867-1945
Keywords: History.

Based on archival research in Europe, Africa, and Asia, "Empire of Hunger: Famine and the French Colonial State, 1867-1945, " traces changing conceptions of famine in the French Empire. Though French administrators once dismissed famine as an act of god or a misfortune of nature, developments in nutrition science, social engineering, and notions of race and gender suggested new tools for managing food and bodies in the colonies. At the same time, an emerging sense of the French Empire as a participant in an international humanitarian project, largely centered around the League of Nations, profoundly altered ideas of what colonialism was supposed to accomplish. In the interwar period, the high modernist confidence in the ability to mitigate hunger, coupled with the acknowledgement of the political obligation to do so, marked a turning point in the French Empire's relationship to its subjects and to nature itself. Increasingly sophisticated understandings of famine saddled the French colonial state with commitments that they were unable and unwilling to fulfill, undermining the ideological justifications of empire. This study shows how modern liberal ethics and norms of governance emerged from a contested history of imperialism.
Employment mindsets for promoting job-skill training
Keywords: Education.

Unemployed and underemployed adults in the United States are not getting trained fast enough to meet demand in "middle-skilled" fields such as healthcare support, some skilled manual trades, and some computer programming jobs (National Skills Coalition, 2017; National Academies of Sciences & Medicine, 2017). Research suggests that psychological factors play an important mediating role in the decision to get job-skill training (Colquitt, LePine, & Noe, 2000). In this dissertation, I apply an academic mindset framework (Paunesku, 2015) to the domain of job-skill training by exploring two novel "employment mindsets": a growth mindset about job skills (a belief in "skill-acquirability"), and the belief that there are good jobs available to be claimed in the economy (a belief in "job-availability"). In Chapters 1-3, I provide evidence from ~6,000 US adults that both of these employment mindsets can be influenced with targeted activities and that this influence translates into changes in self-reported intent to seek training. Employment mindsets may also play a role in the decisions of supporters and gatekeepers in society who can make training easier or harder to obtain for others. In Chapters 4-5, I explore the relationships between employment mindsets, the willingness to politically support pro-retraining policies, and the willingness to train hypothetical applicants of different backgrounds in a work-training scenario.
Enabling "more than Moore" with graphene electronics [electronic resource] : interconnects, devices, and circuits
Keywords: Electrical Engineering.

Since the isolation of graphene in 2004, researchers have sought to exploit its unique electrical, thermal, and mechanical properties to extend "Moore's Law". However, most attempts have focused on conventional digital or analog applications. In this dissertation, I describe several technologies tailored to the unique properties of graphene that may enable greater performance unattainable with only "Moore's Law" scaling. First, I explore active graphene electronics in "beyond Moore" applications and describe a process to improve the quality and yield of graphene field-effect transistors via yttrium (Y) sacrificial layers. The Y sacrificial processing improves yield (from 73% to 97%), average device performance (3x mobility, 58% lower contact resistance), and device-to-device variability. Then, I explore wafer-scale graphene circuits for dot-product computation (GDOT), an essential kernel for emerging image processing and neural net applications. The GDOT utilizes high mobility GFETs to lower branch resistances, resulting in more effective low-pass filtering and enabling a higher effective number of bits (ENOB) over silicon CMOS-based implementations. Experimental, simulation, and mathematical analyses provide insight on device to circuit optimizations—specifically on the tradeoffs between device on/off ratio, output ripple, dot-product convergence accuracy, and power. Finally, I assess the capability of graphene in a passive electronic application: as an interconnect in very large scale integrated (VLSI) digital circuits, where the increasing resistivity of conventional copper wires restrict performance. Benchmarking in the context of a future 7-nm FinFET technology at several levels of abstraction (from standard cell to 32-bit commercial processor) elucidates VLSI design considerations. Full-core energy-delay-product (EDP) projections show ~8% improvement with graphene over copper interconnects. However, benefits could be larger through further design-technology co-optimization (DTCO) at the core level.
Enabling multimodal robots via controllable adhesives
Keywords: Mechanical Engineering.

This thesis is about the design and analysis of robots that use adhesives to combine multiple modes of operation. Examples of multimodal operation include ballistic or powered flight combined with perching and crawling. In each case, the robots are made possible by a proliferation of components -- from microprocessors to sensors and motors -- that have accompanied the growth of drones or quadrotors in consumer markets. The components are compact and light enough that it is possible to support multiple modes of operation on a small platform. The thesis takes a cue from small creatures such as insects, most of which have multiple modes of operation (e.g. flying and crawling) and which can often move objects many times their weight through the use of attachment mechanisms at the tarsus of each limb. Examining the strategies of insects such as wasps leads to insights for designing and modeling the multimodal robots outfitted with gecko-inspired adhesives. The resulting platforms are capable of tasks that no single mode of operation can support. For example, one of these platforms, named FlyCroTugs, can fly rapidly to remote sites, attach a tether to a heavy object, land and then pull that object with a force many times the robot's weight. The FlyCroTugs use gecko-inspired adhesives to anchor themselves when applying large forces. Another example involves a small robot, named KlingOn, that can transition from ballistic flight to crawling on a vertical surface, using the same gecko-inspired adhesives. A third example involves a gripper that can capture free-floating objects with a flexible-backed adhesives. Further insights arise when considering scaling laws applicable to small multimodal robots that use adhesion. At the scale of these robots, contact forces typically dominate the dynamics when the robots are interacting with objects. Therefore, modeling the force constraints associated with the adhesives leads to corresponding dynamic constraints on the robots, in terms of their trajectories and velocities. The adhesive force constraints also have implications for the dimensions, geometry, stiffness and damping of the robot attachment pads and grippers. Ultimately this thesis posits that increased attention to robotic end-effectors and attachment mechanisms can promote the efficacy of small, multimodal robotic systems interacting with their environment.
Enabling Robust, Secure, and Efficient Cellular Networks with Fine-Grained Radio-Layer Analytics
Keywords:  Department of Electrical Engineering
Stanford School of Engineering
Department of Electrical Engineering
Cellular Networks
Mobile Computing
Computer Networking
Network Security
LTE
Mobile Application Performance
Thesis

Mobile devices have now become indispensable to the lives of billions of people around the world. Cellular traffic driven by the use of these devices is projected to increase 7x by 2021 from its levels in 2016, exacerbating already-severe network congestion and security concerns. In this thesis, we respond to these challenges, focusing especially on their impact on popular and nascent media applications such as video streaming, video conferencing, virtual reality, and autonomous vehicles. We show that granular radio-layer analytics provides a powerful lens into network dynamics, exposing patterns in resource allocation that can be used (1) to diagnose security, efficiency, and robustness challenges afflicting mobile networks, and (2) to develop solutions to these problems.
First, we present the design and implementation of eNBsniffer, a passive tool that enables us to characterize the congestion state of any cell tower, using only the fine-grained radio resource allocation data that it streams for all of its users, without requiring any privileged network information. We test it extensively in the field and show that it performs with an error rate not exceeding 5%.
We then demonstrate two use cases of eNBsniffer, revealing its capabilities as a diagnostic engine to identify and address security and efficiency concerns that affect mobile networks. We show that broad classes of popular mobile applications have distinct radio resource allocation signatures, design an application classifier based on this insight, and show that anyone can accurately infer the types of applications being served by any given cell tower using eNBsniffer. We explore the privacy implications of this finding and propose solutions to conceal application identity.
We also present BurstTracker, a tool that mobile application developers can use to pinpoint the root causes of poor application performance on cellular networks. We discuss the design of BurstTracker, which was inspired by our observations with eNBsniffer, and show how it can be used to determine whether the performance of an application is limited by congestion at the cell tower (which an application developer cannot control) or by another network inefficiency. We then demonstrate how BurstTracker is used in practice; we apply it to study mobile video streaming, explain why video performs poorly on cellular networks, and develop a solution that improves video quality on congested networks by 35%.
We conclude by discussing the broader implications of this work, highlighting how the fine-grained radio-layer analytics provided by eNBsniffer can be used to answer a host of societally-relevant questions.
Enantioselective chlorination in the synthesis of polychlorinated natural products
Keywords: Chemistry.

Organochlorides are pervasive in nature, accounting for over 2,500 natural products. This is perhaps not surprising as the ocean covers > 70% of the earth's surface and is rich in soluble chloride. Approximately half of naturally occurring organochlorides contain chlorine-bearing chiral centers. The abundance of chiral organochlorides in nature stands in stark contrast to the number of methods for asymmetric chlorination. Recent work in the synthesis of molecules with chlorine-bearing stereocenters has addressed this methodological deficiency through multistep functional group interconversions. The advent of synthetically relevant, catalytic, enantioselective methods for the direct formation of carbon-chlorine bonds would be of great value in the synthesis of chiral organochlorides. This thesis outlines the development of two new methods for enantioselective chlorofunctionalization of olefins and their application in the synthesis of natural products.
Energy-efficient digital VLSI using carbon nanotube field-effect transistors [electronic resource]
Keywords: Electrical Engineering.

Carbon Nanotube Field-Effect Transistors (CNFETs) are a promising emerging nanotechnology for improving the energy efficiency (quantified by the energy-delay product, EDP) of digital very large-scale integrated (VLSI) circuits. However, the benefits of realistic CNFET digital VLSI circuits at sub-10 nm technology nodes aren't well understood. I begin by quantifying the digital VLSI circuit-level EDP benefits of CNFETs vs. alternative technologies currently under consideration (e.g., progressing from today's FinFETs to nanowires) at the 7 nm and 5 nm technology nodes. I show that CNFETs can enable digital VLSI logic circuits to run 3× faster, while simultaneously consuming 3× less energy, resulting in 9× EDP benefit. This analysis also provides insights into the sources of these benefits. Despite their projected benefits, CNFETs are subject to variations inherent to carbon nanotubes (CNTs): variations in CNT type (semiconducting or metallic), CNT density or CNT diameter, to name a few. Such variations can lead to near-zero functional yield, increase susceptibility to noise, or degrade EDP benefits of CNFET digital circuits. To overcome CNT variations, joint exploration and optimization of CNT processing parameters (to be improved during CNFET fabrication) and CNFET digital circuit design are required. Existing approaches for such exploration and optimization rely on trial-and-error-based ad hoc techniques resulting in very long computation runtimes. I present a new approach that achieves fast runtimes (e.g., 30 minutes for a processor core design vs. a month using existing approaches). I use this approach to derive multiple design points (each representing a combination of parameters for CNT processing and CNFET circuit design) to overcome CNT variations. These design points preserve 90% of the projected EDP benefits of CNFET digital circuits (despite CNT variations), while simultaneously meeting circuit-level yield and noise margin constraints. The derived design points directly influence experimental research on CNFETs. While co-optimized CNT processing and CNFET circuit design can overcome CNT variations, the required CNT processing advances have not yet been achieved. Alternatively, I present a design approach that can deliver EDP benefits of CNFET digital circuits despite CNT variations that exist in today's CNFET fabrication -- without requiring further CNT processing improvements to overcome CNT variations. This new design technique, Technique for Reducing errors using Iterative Gray code (TRIG), is applicable for inference-based applications that rely on serial matrix operations (serial: accumulated over at least 2 clock cycles) to draw conclusions, such as classification, from analyzing large amounts of data. As a case study, I analyze the effectiveness of TRIG for a hardware accelerator targeting image classification. Despite CNT variations that exist today, TRIG can maintain 99% (90%) of projected EDP benefits of CNFET digital circuits for 90% (99%) image classification accuracy target.