VictorJuiz/thesis huggingface dataset:
Empire of hunger : famine and the French colonial state, 1867-1945

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.

Keywords: History.
Advisor: Daughton J. P. (James Patrick) 
Roberts Richard L.
Satia Priya
Empirical evaluation of privacy regulation [electronic resource]

For decades, legal and policy analysis of data privacy issues have tended to be informed by factual assumptions rather than rigorous empirics. The motivation for this dissertation is to recast these assumptions into a set of empirical computer science research questions. Decision makers are, in essence, relying on a set of heuristics to analyze data privacy issues. Are the assumptions behind those heuristics accurate, and what are the consequences of applying those heuristics? The first chapter of this dissertation examines third-party web tracking and advertising, an area that has vexed policymakers in both the United States and Europe. The chapter contributes new methodologies for measuring web tracking, including instrumenting an ordinary web browser and simulating user activity (FourthParty) and collecting tracking-related data directly from ordinary users (BrowserSurvey). The results include new perspectives on the web tracking marketplace, identification of numerous non-cookie tracking technologies, and evidence of inconsistent performance and usability from consumer control mechanisms. The chapter also presents a new design for privacy-preserving third-party advertising (Tracking Not Required) that would provide a specific privacy guarantee, would not require modifying browsers, and would be externally auditable. The second chapter analyzes the distinction between metadata and content, a concept that is foundational to surveillance law and policy in the United States and worldwide. The chapter contributes a new crowdsourcing methodology for studying telephone metadata privacy. It then uses a crowdsourced dataset to demonstrate that telephone metadata is densely interconnected, susceptible to re-identification, and enables highly sensitive inferences. The third chapter assesses data territoriality, another surveillance distinction that is shared by the United States and across the globe. Results from simulated browsing activity indicate that data territoriality is a poor fit for modern web architecture; Americans unknowingly send a large volume of domestic online activity outside the United States, and foreign citizens send a large volume of (from their perspective) domestic online activity into the United States. The conclusion considers the relationship between the computer science community and policymaking about data privacy. It suggests how computer scientists can and must play a greater role in government decision making, to ensure that policy and law reflect the best available privacy science.

Advisor: Mitchell John C. primary advisor. Thesis advisor
Boneh Dan
Winstein Keith advisor. Thesis advisor
Employment mindsets for promoting job-skill training

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.

Keywords: Education.
Advisor: Domingue Ben 
Dweck Carol S.
Mitchell John C.
Enabling "more than Moore" with graphene electronics [electronic resource] : interconnects, devices, and circuits

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.

Keywords: Electrical Engineering.
Advisor: Pop Eric primary advisor. Thesis advisor
Murmann Boris
Wong Hon-Sum Philip
Enabling multimodal robots via controllable adhesives

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.

Keywords: Mechanical Engineering.
Advisor: Cutkosky Mark R. 
Mitiguy Paul
Pavone Marco
Enabling Robust, Secure, and Efficient Cellular Networks with Fine-Grained Radio-Layer Analytics

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.

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
Advisor: Katti Sachin
Schulman Aaron
Enantioselective chlorination in the synthesis of polychlorinated natural products

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.

Keywords: Chemistry.
Advisor: Burns Noah
Du Bois Justin 
Xia Yan
Energy-efficient receiver design for the internet of everything

The nascent Internet of Everything (IoE) will likely be dominated by highly asymmetrical links with bursty communication, shifting the focus away from power consumption and to an obsession with low energy per bit or per packet. This thesis focuses on the challenges involved in designing an energy-efficient receiver for the IoE and the choice of the superregenerative architecture to meet these challenges. We will show that the superregenerative receiver can be analyzed as a linear time variant system and exploit insights into design tradeoffs obtained from such an analysis. We will discuss the design of a 28 GHz superregenerative receiver with symbol-by-symbol automatic gain control fabricated in 65 nm CMOS technology. The synthesizer-free receiver enables fast startup to reduce energy by close to an order of magnitude for short packets and achieves a steady-state energy consumption of 125 pJ/bit for a data rate of 40 Mb/s. The peak power dissipation of 5 mW and active area of 0.36 mm2 make it a particularly attractive receiver for the IoE.

Keywords: Electrical Engineering.
Advisor: Lee Thomas H.
Arbabian Amin 
Murmann Boris
Engineering inequality : public policy, school finance, and the roots of educational inequality in California, 1850-1950

"Engineering Inequality" provides a social, intellectual, and political history of inequality in school funding. Various approaches to school finance competed for dominance during the nineteenth and early twentieth centuries, with western states adopting alternatives to district-property taxation and the inequities produced by local financing. With California as its focal point, this dissertation explains why those alternatives were eventually rejected. The project explores the process through which politicians, reformers, residents of expanding communities, and experts in emerging fields like school administration and public finance came not only to accept inequities in school funding, but to recast them as inevitable and natural features of American public schooling. Based on government documents, regional newspapers, personal papers, court cases, and digitized quantitative and spatial data, this study examines the political and ideological struggles shaping school finance and situates those struggles within the broader history of public education, the state, and inequality. Ultimately, "Engineering Inequality" upends familiar historical narratives about how Americans have paid for their schools in the past, narratives that overstate the use of the district property tax and underestimate the extent to which inequality in school finance emerged through state action. In explaining how state policies created funding inequities at the precise moment that public education became the path to economic opportunity for many Americans, this project brings into view the role of educational finance, as an often neglected domain of social policy, in expanding and entrenching inequality in modern America.

Keywords: Education.
Advisor: Gordon Leah N.
Labaree David F.
Chang Gordon H. 
Reardon Sean F.
Engineering Resistance: A CRISPR/Cas9-mediated Gene Drive for Schistosomiasis Control

Schistosomiasis is a neglected tropical disease that afflicts over 200 million people worldwide, primarily in Sub-Saharan Africa. Schistosomes are parasitic worms that infect humans, feed on blood nutrients, and may cause anemia, tissue damage, and cognitive impairments. The disease persists despite mass drug administration efforts, partially because schistosomiasis transmission depends on several environmental factors. Schistosomes spend a significant portion of their lives as parasites of aquatic snails. Targeting the snails may better control the disease. Gene drives represent one snail control method. A CRISPR/Cas9-mediated drive could engineer snails to be resistant to schistosome infection, over several host generations. This type of gene drive could prevent disease transmission to humans. However, design and implementation of a gene drive faces barriers from complex host-parasite genetics. Previous studies focused on a single gene that dictates snail resistance against schistosomiasis, but in reality, resistance depends on highly variable genetic loci. Snails use multiple genes that confer compatibility, recognition, and removal of schistosomes during infection. The thesis uses an originally designed model to monitor gene drive performance in these complex conditions. We found that neither polymorphic genetic conditions nor compatibility-based infections affected gene drive performance as much as its ability to persist within a genetically diverse population. In a multi-faceted genetic environment, with many levels of wild-type resistance, the gene drive must outcompete other genotypes in order to become fixed in a population. Field implementation of a gene drive must consider existing, wild-type resistant genotypes of resistance.

Keywords:  Department of Bioengineering
Bioengineering
biology
global health
CRISPR
Cas9
gene drive
schistosomiasis
modeling
python
genetics
gene editing
genetic engineering
disease
infectious disease
disease control
Thesis
Advisor: De Leo Giulio
Wang Bo
Engineering virus-like particles for targeted delivery of macromolecular therapeutics

Nanoparticles, carrying therapeutic cargo, offer a potential solution to a number of diseases or disorders where targeted delivery could improve efficacy while at the same time reducing off-target side-effects. Previously in the Swartz lab, virus-like particles (VLPs) from the Hepatitis B core viral capsid have been heavily engineered for stability and host immune system avoidance. Using this as a basis, I have expanded the functionalities of these VLPs to include improved VLP assembly, targeted cell specificity, and loading of therapeutic payloads. We have shown efficient loading of multiple types of cargo, including mimics of siRNA and therapeutic proteins, using VLPs that can assemble at significantly reduced ionic strengths. Using Prostate Cancer cells as a model disease target, we observed specificity of our construct for the targeted cells. Furthermore, these engineered VLPs can be easily modified for treating other cancers or genetic disorders and, in the future, for neurological disorders. The modularity and flexibility of this targeted delivery platform offers great promise for a broad range of medical applications.

Keywords: Chemical Engineering.
Advisor: Swartz James R. 
Covert Markus 
Khosla Chaitan
Enhanced sampling methods for kinetics of biomolecules and application to triazine polymers

Molecular dynamics (MD) simulations are becoming essential tools for many different fields, including biology, chemistry, and materials science, that provide us with a molecular picture of what is really happening at the molecular level for many biophysical phenomena. With MD simulations, we can see how the molecule forms and moves and obtain insight into its mechanisms with higher resolution than experiments. Unfortunately, MD simulations are not without limitations. They are restricted in predictive power because the molecules routinely get "stuck" in metastable states and do not change their conformations for an extended period. Hence, there is currently a huge gap between what MD simulations can model and the timescales of biological processes. Consequently, many methods have been developed for MD simulations over the past few decades to overcome this timescale barrier between MD simulations and biological processes. These are referred to as enhanced sampling methods. We need these methods to overcome the timescale barrier so that critical biophysical phenomena can be observed in a computationally tractable period. Current enhanced sampling methods have demonstrated that they can efficiently obtain thermodynamic and/or kinetic properties. However, there is still a need for an enhanced sampling method that requires little a priori knowledge about the system, is less heuristic, can obtain both thermodynamic and kinetic properties, and can be easily parallelized over the available computational resources for computational efficiency. I will go over several classes of enhanced sampling methods before diving into my new enhanced sampling methods that aim to address the issues mentioned above.

Keywords: Chemistry.
Advisor: Darve Eric 
Dror Ron
Martinez Todd J. (Todd Joseph)