VictorJuiz/thesis huggingface dataset:
In-cylinder fuel reforming for small-scale mixed combustion/electrochemical engines

Previous efforts towards increasing the efficiency of piston engine-based systems have been limited in their ability to surpass 60% efficiency on an exergy basis due to the significant exergy destruction associated with combustion. This thesis assesses the prospects of achieving efficiencies in excess of 60% on an exergy basis, and approaching 70% on an LHV basis, through the use of a combined combustion/electrochemical strategy. The proposed strategy utilizes an engine upstream of a fuel cell to provide a combined fuel-reforming and work-producing function in the overall system. The products of rich combustion are then fed downstream, through an additional catalytic reforming step, to a fuel cell for further oxidation. The assessment of the proposed strategy occurs in two major areas. The first focuses on the development of detailed computational models of the major devices in the proposed mixed combustion/electrochemical system architectures. These device models are then used in overall system models to determine if the proposed architectures are able to successfully reduce the overall reaction-related losses. Once a viable system is identified, the focus shifts to addressing the ability of the engine to perform its intended function in the overall system. In the chosen system, the engine must operate at very rich equivalence ratios in an insulated in-cylinder environment that requires a direct-injection, compression-ignition (DI/CI) combustion strategy. To achieve the desired equivalence ratios, without generating large quantities of soot, ethanol and methanol are investigated as the primary fuels for the system. Both fuels have shown promise in their ability to remain below current regulation limits in terms of engine-out soot emissions at stoichiometric equivalence ratios, but the rich-combustion regime has been largely unexplored. This work investigates the rich DI/CI combustion regime in three avenues. The first focuses on performing equivalence ratio sweeps for both fuels of interest on a research engine that approximates the in-cylinder environment of the insulated engine in the combined system. The second involves conducting optical access experiments that attempt to gain more insight into the driving factors that dictate the performance measured in the first. The final step incorporates the findings from the optical access experiments into a phenomenological DI/CI combustion model designed to represent the relevant physical processes in this regime. Ultimately, the results of the computational model are compared to the measured experimental results in an effort to better understand the observed trends.

Keywords: Mechanical Engineering.
Advisor: Edwards C. F. (Christopher Francis) 
Lutz Andrew E. (Andrew Edward) 
Mitchell Reginald
Inferactive

Inferactive is a tool designed to help journalists tell stories with data. It is a free and open source web application where a user can upload a column-based dataset like a CSV file and then rapidly iterate possible visualizations, visualizations which could inform a news story or summarize significant trends or outliers in the data.
The premise is that the process of discovery in the world of data is an inherently hard problem for computers but a more intuitive one for humans. By presenting an interface where the user can quickly scan and iterate visualizations and story ideas, Inferactive hopes to bridge this divide in service of news story discovery.

Keywords:  Department of Communication
data
visualization
story
discovery
journalism
communications
stanford
Thesis
Advisor: Nguyen Dan
Hamilton James T
Inferring structure from multivariate time series sensor data

Many applications, ranging from automobiles to financial markets, generate large amounts of time series data. In most cases, this data is multivariate and heterogeneous, where the readings come from various types of entities, or sensors. These time series datasets are often sparse, unlabeled, dynamic, and difficult to interpret. Therefore, there is a need for methods that learn interpretable structure from such data, especially for methods that can apply across many different domains. Here, we develop three novel optimization methods which can be used for analyzing temporal patterns, identifying outliers and regime changes, and segmenting a time series into a sequence of repeated states in an unsupervised way. Such methods are based on inferring the correlation structure between the different sensors, both instantaneous and across timestamps, as well as how this structure evolves over time. Using these methods, we analyze applications in various real-world domains, both in and beyond time series datasets.

Keywords: Electrical Engineering.
Advisor: Leskovec Jurij 
Boyd Stephen P. 
Garcia-Molina Hector
Influence of Anthropogenic Disturbance on Vertebrate Trampling of the Understory in North American Temperate Woodlands

The impact of vertebrate herbivores on plant communities varies depending on environmental conditions and the type of damage, which can be consumptive or nonconsumptive. While medium-to-large herbivores are known to significantly impact plant populations through trampling and other nonconsumptive interactions, it remains unclear how human disturbance influences this impact. Previous work suggests that disturbance can cause vertebrates to shift their habitat usage to less disturbed areas. Accordingly, I predicted that vertebrate herbivores would have a stronger impact on plant populations in areas removed from human disturbance. Furthermore, most previous studies have not distinguished between consumptive and nonconsumptive effects when examining vertebrate herbivore impact. Using an experimental approach, I examined how the impact of deer on plant communities through nonconsumptive interactions may vary under contrasting levels of human disturbance. The impact of deer and other vertebrates was measured using artificial seedling models in Maryland and Washington D.C. woodland areas with contrasting disturbance defined by the proximity to human walking trails. My results indicate that deer have a greater nonconsumptive impact on understory plants in less disturbed habitats and suggest that the reduction of nonconsumptive herbivory in disturbed areas may affect plant communities’ regeneration patterns. These findings shed light on how herbivores interact with their environment in heterogeneously disturbed urban landscapes. Understanding variable deer impact on plants through trampling has implications for management of natural and human-dominated landscapes, with regulation of human disturbance having the potential to be used as a plant-protection strategy. This research contributes to our understanding of how human activity may influence the structure of herbivore-plant interactions by demonstrating that anthropogenic disturbance decreases the effects of nonconsumptive herbivory on plant communities. Further research is warranted to determine how this may translate into community regeneration patterns along disturbance gradients.

Keywords:  Department of Biology
trampling
nonconsumptive herbivory
deer
anthropogenic disturbance
ecology
biology
Thesis
Advisor: Dirzo Rodolfo
Fukami Tadashi
Infrastructural Investment ‘Warfare’?: The security risks of the Belt and Road Initiative investments in maritime Southeast Asia

China’s Belt and Road Initiative (BRI) promises to boost economic growth through its infrastructure investments. However, China’s complicated relationship with its Southeast Asian neighbors has aroused concerns about Chinese intentions. This thesis thus explores the possible security risks that Chinese infrastructure investments may pose to countries in maritime Southeast Asia (MSEA). A three-step analysis will be made of the potential risks, assessing Chinese intentions and capabilities, as well as the vulnerability of MSEA states to possible threats posed by China. Four key risks are identified — The threats to external and internal sovereignty, operational concerns, and regional implications. A primarily qualitative approach is taken, using the framework of risk assessment, since many projects have not been completed and remain in preliminary talks. This thesis shows how there is a need for a broader definition of security to fully appreciate the risks posed by the BRI. The current risks in MSEA through investment dependency are manageable but are particularly high in Malaysia. The greatest leverage that China has is passive or the promise of investment. However, the BRI enhances China’s ability to undermine both intra and inter-state unity to advance its interests and must be carefully managed to avoid fissures. The concerns over the security implications of the BRI investments may originate from threat perceptions of China but are nonetheless a real threat.

Keywords:  Stanford Global Studies
Stanford Global Studies
East Asian Studies
China
Southeast Asia
Belt and Road Initiative
Security
Thesis
Advisor: Oi Jean
Inquiry into politics : a study of Plato's Politicus

Plato's Politicus depicts a philosophical investigation of the knowledge that characterizes a good political ruler. I argue that the Politicus develops a complex, general purpose methodology for inquiring into subjects about which one's starting beliefs may not be reliable. The methodology relies on a metaphysical comparison between the objects of philosophical inquiry and the letters and words of language. I show how the political content of the Politicus, including its criticism of the rule of law and its treatment of the virtues of courage and moderation, is shaped by the methodology and its metaphysical basis.

Keywords: Philosophy.
Advisor: Bobonich Christopher 
Code Alan Dodd
Ober Josiah
Insider Trading: A Quantitative Analysis of Premature Market Reactions in Thailand’s Stock Exchanges

This paper analyzes various firm, exchange and political power specific characteristics that affect intensity of insider trading in Thailand’s equity markets. Using data from 2007 to 2017 provided by the Stock Exchange of Thailand (SET), the study utilizes an event-driven analysis and tracks abnormal stock returns, calculated using a three-factor Fama-French model, leading up to quarterly earnings announcements. These daily returns are normalized and are regressed on various fixed effects to capture variables that intensify and ameliorate premature stock price movements. This paper illustrates that military control in Thailand has non- negligible effects of lessening premature price movements across all equity markets, while capturing exchange-specific effects that diminish as the impact of the earnings announcements on the absolute value of the change equity prices rise.

Keywords: Department of Economics
Stock Exchange of Thailand
Market for Alternative Investment
abnormal price fluctuations
insider trading
financial markets
Thailand
Thesis
Advisor: Shoven John B.
Insights into the sequence-structure-function relationship of the GLMS ribozyme from single-molecule force spectroscopy and massively-parallel biochemistry of sequence variants

Structured RNAs play a range of essential roles in the cell, including central functions in protein synthesis and gene regulation. These important RNAs include ribozymes, which catalyze chemical reactions, and riboswitches, mRNA elements which modulate gene expression in response to metabolite ligands. Structured RNAs ultimately enact their function by folding from linear sequences into elaborate three-dimensional conformations with specific biochemical properties. A mechanistic understanding of the relationships between RNA sequence, folding, and function should allow for increasingly sophisticated engineering of RNAs with desired functions, as well as the design of drugs targeting naturally occurring RNAs. In my PhD thesis research, I delved into these relationships in the context of the glmS ribozyme riboswitch. This widespread bacterial riboswitch regulates the production of an essential cell wall precursor, glucosamine 6-phosphate (GlcN6P), making it a compelling target for antibiotic development efforts. The key step for gene regulation is a self-cleavage reaction performed by the ribozyme riboswitch only when GlcN6P is bound in its active site. I investigated this structured RNA using two powerful and complementary approaches: (1) single-molecule force spectroscopy using a high-resolution optical tweezers apparatus to study folding, ligand binding, and catalysis, and their interrelationship; and (2) massively-parallel biochemistry on an RNA array to systematically dissect the sequence-dependence of self-cleavage activity and mutational interactions between residues.

Advisor: Block Steven M.
Das Rhiju
Moerner W. E. (William Esco)
Integrated infrastructure health monitoring : detection, estimation, and learning

Buildings, bridges, power grids, and other infrastructure are essential parts of the urban system. It is critical to diagnose their health conditions continuously. The availability of low-cost sensing, wireless communications, and data processing technologies has made it possible to deploy large-scale sensor networks to monitor urban infrastructure. The data from these networks offer opportunities to integrate spatial and temporal information for infrastructure health monitoring. Effective detection and localization of damage require models and inference algorithms that combine sensor data, knowledge of the underlying system dynamics, and the spatial and temporal aspects of measurements. In the first part of this dissertation, we design statistical and machine learning based methods to recover spatial and temporal representations of the data. For example, graphical models are utilized to model dependencies between infrastructure damage and sensor measurements. The methods can also recover the underlying infrastructure network and its connectivity. We illustrate the approach by demonstrating a provably correct method to recover the distribution power grid topology from power measurements at the network endpoints. The algorithm is tested on a large-scale data set of power measurements from a local utility. In the second part of this dissertation, we focus on designing algorithms for detection and localization of damage. Practically useful detection algorithms utilize a stream of data to decide about damage state continuously. Change point detection algorithms utilize the fact that the statistical distribution of the data changes before and after damage. When these distributions are known, optimal algorithms that minimize the delay in detecting damage for a given false alarm level can be designed. When the post-damage distribution is not known, some form of inference needs to be performed simultaneously with detection. In addition, when multiple types or locations of damage are present, then multiple change points need to be considered. We propose utilizing graphical models to create algorithms that can learn the post-damage distributions and cooperatively detect multiple change points leading to localizing damage in space and time. A cooperative Bayesian damage detection and localization method is shown to isolate the damage location in an optimal way and can be even computed in a distributed manner. The methods are tested utilizing various datasets collected from experiments with buildings subject to different ground motions in shake table tests. Then, we transfer the learning in structural damage detection to identify power line outage in distribution grid. We demonstrate the same data-driven method can solve problems in two different physical systems. We conclude the dissertation by presenting a novel wireless sensor system, SnowFort, that is designed for infrastructure health monitoring, with the integration of decision making system.

Advisor: Rajagopal Ram 
Baker Jack W. 
Kiremidjian Anne S. (Anne Setian)
International Remittances and Blockchain Technology

Remittances are an important component of the economic livelihood of migrants and their families. Recently, blockchain-based attempts to improve remittances have garnered a great deal of attention. Specifically, proponents believe blockchain is uniquely suited to overhauling and streamlining the decades old correspondent banking system, the “pipes” through which most international money flows through. However, on closer investigation, the picture is much more complicated. Firstly, while being careful to generalize given the heterogeneity of remittance corridors, the literature challenges the commonly cited view amongst blockchain proponents that remittance markets are dysfunctional and costs are exorbitantly high. Secondly, it appears that blockchain initiatives in the cross-border payment space only address two of the four key cost drivers in the remittance business: the inefficient correspondent banking system and lack of market competition in certain corridors. But blockchain does not address other cost drivers such as regulation and agent network infrastructure. Thirdly, the two models of blockchain startups impacting the remittance space are still in the early stages of development, with mixed evidence on their success. These nascent efforts in the cross-border payments space have also revealed the difficulty of realizing blockchain’s myriad benefits in a theoretical sense – security, speed, de-centralization, lower costs – when the technology is put into a real world operating environment.

Keywords:  Public Policy Program
Stanford University
Humanities and Sciences
Public Policy Program
Remittances
Blockchain
Bitcoin
Migrants
Correspondent Banking
Cross Border Transfers
Migrants
Moneygram
Ripple
Western Union
Thesis
Advisor: Krishnamurthy Arvind
The intestinal microbiota controls intestinal salmonella infection

Salmonella enterica serovars are important human pathogens, leading to millions of infections and hundreds of thousands of deaths worldwide each year. Salmonella infection occurs by the fecal-oral route such that hosts are infected by ingesting contaminated food or water. The pathogen navigates the gastrointestinal tract and replicates to high levels in the distal intestinal site prior to transmission in the feces, where it can infect naïve hosts. Intestinal infection and pathogen transmission is a complex process that is likely controlled by a combination of host, environmental, and pathogen factors. This dissertation focuses on the role of the intestinal microbiota in intestinal Salmonella infection and transmission. Chapter 1 of this dissertation provides an overview of what is known about intestinal Salmonella infection and the role of the intestinal microbiota in this process. In Chapter 2 and 3, I utilize two strains of inbred mice with distinct intestinal Salmonella burdens and kinetics to dissect the role of the intestinal microbiota in intestinal Salmonella infection. Utilization of this system revealed that the composition of the intestinal microbiota dictates the level of Salmonella replication in the intestines and transmission in the feces. In Chapter 3, I identify Bacteroides spp. in resistant mice that mediate colonization resistance to intestinal Salmonella infection through production of the short-chain fatty acid propionate. In contrast, in Chapter 4 I identify Lachnospiraceae spp. present in susceptible mice that facilitate pathogen expansion, likely through the production of amino acids that Salmonella requires for intestinal growth. While host and environmental factors are crucial determinants of enteric infection outcome, pathogen factors are also important regulators of disease as well. Chapter 4 of this dissertation describes a novel surgical Salmonella infection model. In this model, the pathogen is injected directly into the distal intestine, allowing for genome-wide pathogen screens to identify pathogen factors required for colonization of the intestine. Taken together, this dissertation highlights the importance of the intestinal microbiota as a determinant of intestinal Salmonella disease severity and outcome, and advocates for the consideration of the intestinal microbiota as a therapeutic target for ameliorating intestinal infections. Chapter 5 of this dissertation reflects on current microbiota-targeting treatment strategies and future considerations for the development of microbiota-targeting therapies that reduce transmission of Salmonella and other enteric bacterial infections.

Keywords: Microbiology and Immunology.
Advisor: Monack Denise M. 
Bhatt Ami (Ami Siddharth) 
Schneider David (David Samuel)
Sonnenburg Justin
The intimate public : understanding the intersection of public goals and private actions through household sanitation adoption in rural India

Globally, 60% of households without access to sanitation facilities are located in India, and the majority of Indians without sanitation live in rural areas. In this dissertation, I introduce the concept of the intimate public to analyze the constellation of social forces that shape rural Indians' decisions to install household sanitation facilities. This concept uses a place-specific lens to examine social interactions. Considering the social roles within the intimate public, I investigate how social influence varies across the types of relationships that constitute the intimate public. Although households' investments in this amenity have implications for public health outcomes, I find that families' personal efforts to find dignity and belonging within their intimate public, which may not align with the individuals that are impacted by one another's sanitation practices, guide this decision. Certain intimate publics even foster resistance to this public health project. This theoretical concept allows scholars to analyze how physical and social spaces shape social processes in distinct ways. These empirical results make a timely contribution to global health and national policy efforts that seek to improve health by increasing household sanitation adoption across rural India.

Keywords: Sociology.
Advisor: Granovetter Mark S. 
Parigi Paolo
Thiranagama Sharika
Inverse problems in the Pacific : ancestry deconvolution and dimensionality reduction for reconstructing human settlement in Oceania

The settlement of Polynesia represents a uniquely structured final chapter in the historical founding events of the human species; however, the population history of its many islands remains largely unknown. Resolving the detailed sequences of islands settled and dates of settlement requires careful attention to both haplotype and genetic drift based methodologies. These must be developed within a framework that accounts for the confounding effects of subsequent waves of complex admixture. I will describe the novel methods I have developed for a dataset consisting of hundreds of human DNA samples sequenced at seven hundred thousand genomic sites each and spanning the Pacific in order to unravel the peopling of this region, and the timing of island interactions, for the first time from a genomic perspective. I will discuss an algorithm for reconstructing the ancestral migration graph based on combining directionality measures with dissimilarity measures, a method for dating settlement based on haplotypes, and a matrix completion­ based method for visualizing ancestry ­specific patterns of population differentiation. Based on these new methods I will present findings about the origin and timing of specific events, including strong evidence for a complex pre­-European admixture event between Polynesians and Native Americans within several of the easternmost island populations.

Advisor: Bustamante Carlos (Carlos D.) 
Feldman Marcus W. 
Moreno-Estrada Andrés