VictorJuiz/thesis huggingface dataset:
Dissecting the energy, conformational, and evolutionary landscapes of a ubiquitous RNA tertiary structural motif through single-molecule and high-throughput studies

RNA's ability to fold into intricate tertiary structures and undergo precise conformational changes is essential for complex biological processes such as translation and pre-mRNA splicing. Although decades of research have revealed important characteristics of the RNA folding process, such as multiple folding pathways and misfolded states, a predictive and quantitative model of RNA folding is lacking. Previous work has revealed modularity of RNA structural motifs, and recent developments have provided evidence for a generalizable model of RNA folding based on reconstitution of the energetic and conformational properties of individual RNA motifs. In this thesis I discuss experimental and conceptual progress towards developing a predictive understanding of the energetic and conformational properties of a ubiquitous class of RNA tertiary contact motifs, the tetraloop/tetraloop-receptor (TL/TLR). First, I discuss the use of single-molecule FRET to dissect the multistep folding pathway of a subclass of TL/TLRs and identify folding steps that are common and distinct between TL/TLR sequence variants. Second, I discuss the use of a novel high-throughput platform to dissect the stability and conformational properties of hundreds of TL/TLR variants and identify types of TL/TLR thermodynamic and conformational behavior. Overall, the work presented in this thesis provides additional support for a reconstitution model in which RNA folding is quantitatively described from the properties of secondary and tertiary structural motifs and provides quantitative datasets that can be used to engineer RNAs with specified stabilities and defined conformational dynamics.

Keywords: Chemical Engineering.
Advisor: Dunn Alexander Robert 
Herschlag Daniel 
Das Rhiju
Harbury Pehr
Distance from the Ideology: Efforts by North Korean Diplomats to Construct the Rationality in DPRK Policies

North Korea is often considered to be a monolithic society with an omnipotent leader. State party and state ideology are described to possess dominant power over the society and the policies. While acknowledging the importance of the party and the ideology for the North Korean policies, this study argues that there are different interests within the state that might diverge from the party and the ideology. Particularly, North Korean diplomats in the missions abroad endeavor to present their government policies in the most “rational” way possible: namely, more in line with the international laws and norms, in order to accomplish their goals more effectively. To demonstrate these different interests, this study analyzes the difference of narratives within the North Korean government under the Kim Jong Un leadership. The analysis especially focuses on statements at the United Nations of the North Korean delegation from the UN mission in New York, in comparison with the articles and commentaries of Rodong Sinmun, owned by the party. With the analysis, this study finds that North Korean diplomats in UN meetings present their policies more in conformity with the international laws and norms. In the process, the narratives often keep distance from the state ideology, implying the possibility of more practical negotiation with North Korea. In conclusion, this study contends that concept of bureaucracy is applicable in the North Korean government, suggesting the necessity to utilize these bureaucrats including the diplomats more effectively, addressing the North Korean problems.

Keywords:  Stanford Global Studies
North Korea
Democratic People's Republic of Korea (DPRK)
United Nations
diplomacy
bureaucracy
Juche Ideology
Thesis
Advisor: Abrahamian Andray
Diverse genes mediate cell envelope stress response in Sinorhizobium meliloti

Sinorhizobium meliloti, an agriculturally important α-proteobacterium, invades the roots of certain plants to form a nitrogen-fixing symbiotic relationship. During this process, both partners exchange signals and co-differentiate to form a root nodule. At several stages in root nodule formation, S. meliloti transcribes genes that are associated with cell envelope stress. However, the pathways by which S. meliloti responds to cell envelope stress are not well understood and appear to be distinct from the pathways in better-studied bacteria such as E. coli. Previous research probing the S. meliloti response to cell envelope stress has shown that a novel operon esrRAB is strongly upregulated in response to deoxycholate, a generic membrane stressor. However, no research so far has uncovered the pathway responsible for transducing this signal. This work used a mutagenesis screen to identify proteins required for the esr transcriptional response to deoxycholate. Through this screen, seven genes were found to be required for the activation of esr including two transcription factors, emrR and irr. Homologs of another gene revealed in the screen, ppx2, have been found to be capable of cleaving guanosine pentaphosphate into the “alarmone” guanosine tetraphosphate. Further elucidating the pathways used for detecting and responding to cell envelope stress may provide important insights into signaling pathways in other α-proteobacteria. Furthermore, this research may eventually allow more efficient inoculation techniques in commercial alfalfa agriculture through a more comprehensive understanding of the response of S. meliloti to various stresses.

Keywords:  Department of Biology
Biology
Sinorhizobium meliloti
cell envelope stress
mutagenesis
transcription
Thesis
Advisor: Long Sharon
Welander Paula
Diversity of microglial transcriptional responses during opioid exposure and neuropathic pain

Opioids, such as morphine, remain some of the most widely prescribed medications in the world for the treatment of pain despite their detrimental side effects. In particular, analgesic tolerance and opioid-induced hyperalgesia (OIH) can lead to dose escalation and increased risk of addiction and overdose death. As we are experiencing an Opioid Epidemic with high rates of mortality, there is a strong need to both understand and miti-gate these detrimental opioid effects or to identify alternative non-opioid analgesics. Mi-croglia, the resident tissue macrophages of the central nervous system, take on altered morphology in response to chronic opioid treatment, similarly to their response to pe-ripheral nerve injury (PNI). Functional studies have suggested that microglial activation by PNI or opioids engage common mechanisms to alter spinal neural excitability, con-tributing to chronic neuropathic pain after PNI or to opioid tolerance and OIH, which counteract morphine analgesia. We thus sought to determine if there was a common pro-nociceptive state of microglia that could be a potential target for novel pain therapeutics. To this aim, we conducted RNA sequencing (RNA-seq) of acutely isolated spinal cord microglia, first to comprehensively interrogate transcriptional state commonality between multiple PNI pain models over time. We identified a common early proliferative event, corresponding to the greatest transcriptional variance, and preceding the peak of histo-logical markers of microglia activation. This initial transcriptional profile was followed by a weak transcriptional signature of immune activation that varied between models. We next probed the effects of chronic morphine with the same RNA-seq approach. Strikingly, contrary to the prevailing view in the pain and opioid fields, we found that microglia did not express the classic receptor for morphine, the mu opioid receptor, nor was this receptor required for opioid-induced microglia activation. In support of an ab-sence of a singular and common pronociceptive microglial response, we demonstrate that the transcriptional responses following PNI did not occur with morphine treatment. Meta-analysis further revealed dynamic transcriptional signatures of microglial reactivity that diverge between PNI, OIH, and CNS pathology, despite similar histological out-comes. Collectively, our results provide a resource of pain-associated microglial tran-scriptomes that expand our understanding of microglial responses to insults and caution against extrapolation of microglial activation status based on morphological analysis.

Advisor: Scherrer Gregory
Buckwalter Marion
Goodman Miriam Beth 
Plant Giles
DNA as a crystal ball : predicting outcomes in complex traits and genome editing

Genome-scale molecular biology datasets, unobtainable only twenty years ago, are now routinely generated. New DNA-centric technologies are undoubtedly powerful, yet bias from low specificity hybridization and differential environmental and genetic backgrounds may still dwarf the anticipated effects of genetic elements. Indeed, the deluge of new data types has outpaced assessments of these biases. This work advances methods for maximizing insight and mitigating bias for three nascent tools: CRISPR-associated protein 9 (Cas9), chromatin profiling and genome-wide association studies. Cas9 has proven an extremely adaptable research tool, comprising several technologies that fall under the umbrella of precision genome and epigenome editing: knockout, deletion, activation and silencing of genetic elements, as well as homology-directed repair and base editing of living cells. A race to engineer ever more powerful Cas9 variants is underway, but the fundamental properties underlying Cas9 activity are not known. In turn, this work develops High-Throughput Sequencing followed by Fluorescent Ligand Interaction Profiling (HiTS-FLIP) and massively parallel filter binding to resolve the kinetic and thermodynamic properties that promote successful genome editing and offers an unsupervised method to remove signatures of confounding from large-scale Cas9 screening datasets downstream of editing. Advances in profiling histone marks, chromatin looping and human genetic variation have invited closer study of the significance of non-coding genetic variation. The strongly polygenic architecture indicated by genome-wide association studies for many complex traits has incited further interest and created openings for intersecting heritable signal with other molecular profiling. This work presents numerous approaches for synthesizing these data into novel findings. In particular, the broad enrichment for enhancers, promoters and genic regions, irrespective of whether the genetic elements are ostensibly pertinent to the trait of interest, suggests an extreme conclusion: that nearly all transcribed genes for a cell type can influence the traits derived from that cell type. If true, complex traits are not merely polygenic, but 'omnigenic.' The answers thought to lie in our DNA are perhaps irresistibly tantalizing, yet we gaze at our peril. Fortune-telling is best met with healthy skepticism; otherwise, every suspension of disbelief bolsters an ever more powerful illusion.

Keywords: Genetics.
Advisor: Greenleaf William James 
Pritchard Jonathan (Jonathan K.) 
Bassik Michael 
Fraser Hunter B.
Do Mass Killings Breed Transnational Terrorism?

On September 11th, 2001, the world witnessed the deadliest terrorist attacks in history. At the hands of nineteen terrorists, nearly three-thousand people were killed and over six-thousand more were injured. Only six years earlier, at least two of these hijackers were fighting in the Bosnian genocide alongside other Al Qaeda operatives. But why had Al Qaeda decided to set up operations in Bosnia during the genocide? What were their specific goals? And how did they use post-genocide Bosnia to realize those goals? Utilizing a large-n quantitative analysis on all mass killings and terrorist attacks from 1970 to 2006 in addition to a historical case study on the relationship between the Bosnian genocide of 1992-1995 and Al Qaeda, this thesis attempts to answer the question – do mass killings breed transnational terrorism? – more generally. To do so, terrorist groups that emerge from or claim to represent the victims of mass killings are identified and their attacks are analyzed compared to the attacks of other terrorist groups. In conclusion, this thesis argues that mass killings breed transnational terrorism by prompting the formation of new terrorist groups and by fostering an aggrieved population susceptible to the recruitment mechanisms of preexisting terrorist groups.

Keywords:  Department of International Relations
transnational terrorism
mass killings
Bosnian genocide
Al Qaeda
Stanford Honors Program in International Relations
Thesis
Advisor: Schultz Kenneth
Domestic formalism : comfort, narrative, and the Victorian imaginary

Literary criticism has long treated one of Victorian narrative's favorite hobbyhorses—the pleasures and perils of domestic life—as a fascination born of the historical and political contexts of nineteenth-century Britain. My research rethinks this account by uncovering the distinctly aesthetic stakes of Victorian literature's intense investment in domesticity. With special attention to a tradition that includes Elizabeth Gaskell, Charles Dickens, Wilkie Collins, George Eliot, and Henry James, I argue that nineteenth-century British writers drew on the images and values associated with domestic comfort in order to explore the nature of narrative experience and problems of novelistic form. Seeking to map this field of "domestic formalism, " this dissertation identifies four landmark categories that demonstrate its range across narrative levels, from that of scene and character to that of genre and compositional modes. These categories include coziness, an aesthetic mode intimately related to the novelistic unit of the scene; inclination, a style of identification that mediates between comfort and desire; maternal reminiscence, a genre of shared autobiographical memory; and dictation, a writing practice situated in relations of assisted authorship. Through its focus on the aesthetic resources of domestic formalism, this project demonstrates how the novel at its cultural height developed a robust account of narrative experience, one that affirmed narrative's sociability and manifold pleasures and consolations.

Advisor: Woloch Alex
Cohen Margaret
Ngai Sianne
Driving Mexican migration : constructing technologies and mythologies of mobility, 1940 to 1964

"Driving Mexican Migration" examines the technological and ideological foundations of transnational Mexican migration during the twentieth century. It focuses primarily on the bracero period, when Mexican guest laborers were recruited to work in US agriculture and industry from 1942 to 1964. This dissertation analyzes the post-World War II expansion of binational transportation and irrigation networks, industrialized agriculture, discourses of modernity and mobility, and rural Mexican emigration. This story of modern development explores the intersections of the infrastructures, imaginaries, and policies of mobility that both entrenched a culture of migration in western Mexico and led to the racialization and criminalization of Mexican mobility and migrancy in the United States.

Keywords: History.
Advisor: Wolfe Mikael
Frank Zephyr L.
Minian Andjel Ana Raquel
Droplet microfluidics platform for quantifying pathogens with single-cell resolution

Droplet microfluidics, where micro-droplets are suspended in an immiscible fluid, has enabled a wide range of biochemical applications. The objective of my thesis dissertation is to apply droplet microfluidics to pathogen detection. My thesis covers two parts. The first part involves the suppression of the cross-contamination of droplet content by using nanoparticles as the droplet stabilizer. The second part involves quantifying bacteria using droplet-based microfluidics with single cell resolution. In the first part of my dissertation, I show the development of amphiphilic nanoparticles (NPs) as an emulsion stabilizer to replace surfactants in droplet microfluidics. Compared with state-of-the-art surfactants, amphiphilic NPs not only exhibit comparable droplet stability but also mitigate the cross-contamination of droplet contents. The impact of this research is further validated by the licensing and commercialization of this method by a microfluidics company. In the second part of my dissertation, I present the design and application of droplet-based microfluidic systems to quantitatively detect bacteria with single-cell resolution. Compared with state-of-art bacterial detection methods, our droplet-based microfluidic method offers multiple advantages including higher sensitivity, higher specificity, and lower limit of detection (LOD). Further development of our method can enable rapid low-cost bacterial detection in a wide range of applications to prevent and combat infectious diseases.

Keywords: Mechanical Engineering.
Advisor: Tang Sindy (Sindy K.Y.) 
Andrews Jason Randolph 
Chaudhuri Ovijit
DSLs to reconfigurable hardware : design of the spatial language and compiler

In recent years, the computing landscape has seen an increasing shift towards specialized accelerators. Reconfigurable architectures like field programmable gate arrays (FPGAs) are particularly promising for accelerator implementation as they can offer performance and energy efficiency improvements over CPUs and GPUs while offering more flexibility than fixed-function ASICs. Unfortunately, adoption of reconfigurable hardware has been limited by their associated tools and programming models. The conventional languages for programming FPGAs, hardware description languages (HDLs), lack abstractions for productivity and are difficult to target directly from higher level languages. Commercial high level synthesis (HLS) tools offer a more productive programming solution, but their mix of software and hardware abstractions is ad-hoc, making both manual and automated performance optimizations difficult. As demand for customized accelerators has grown, so too has the demand by software engineers and domain experts for domain-specific languages (DSLs) which provide higher levels of abstraction and hence improved programmer productivity. Unfortunately, in the domains of machine learning and data analytics, most domain-specific methods for generating accelerators are focused on library-based approaches which generate hardware on a per-kernel basis, resulting in excessive memory transfers and missing critical cross-kernel optimizations. As DSLs become more ubiquitous, this approach will not scale. This dissertation describes a new system for compiling high-level applications in domain specific languages to hardware accelerator designs that addresses these productivity, generality, and optimization challenges. To improve results above kernel-based approaches when programming in domain-specific languages, we introduce a waypoint between DSLs and HDLs: a new intermediate abstraction dedicated to representing parameterized accelerator designs targeting reconfigurable architectures. Starting from a common intermediate representation for high-level DSLs based on parallel patterns, we first describe the cross-kernel optimizations the system performs and the methods which used to lower the entire application graph into a parameterized design in the intermediate hardware abstraction. We then describe our implementation of this intermediate abstraction, a language and compiler called Spatial. We discuss some of the compiler optimizations Spatial enables, including rapid design parameter tuning, pipeline scheduling, and memory banking and partitioning. The end result is a compiler stack which can take as input a high-level program in a domain-specific language and translate it into an optimized, synthesizable hardware design coupled with runtime administration code for the host CPU.

Keywords: Electrical Engineering.
Advisor: Olukotun Oyekunle Ayinde 
Horowitz Mark (Mark Alan) 
Zaharia Matei
Dynamic decoding of RNA

Genetic information encoded in messenger RNA (mRNA) is translated by the ribosome, a molecular machine that maps RNA to protein sequences following the genetic code. Translation of mRNA is regulated to control location, abundance, sequence and structure of the synthesized protein within the cell. Such regulation often involves pausing translation at a specific location within the mRNA, which may result in the local redefinition of the genetic code and synthesis of different protein products. In this dissertation, we investigate distinct pausing events involving actively translating ribosomes observed using single-molecule fluorescence spectroscopy. We particularly focus on the translational pauses induced by the chemical modification of RNA, the formation of stable RNA secondary structure and the nascent protein sequences, and how these lead to local redefinition of the genetic code. Finally, we discuss extension of the current experimental platform to understand how RNA elements induce pausing of different molecular machineries such as human immunodeficiency virus (HIV) reverse transcriptase, serving distinct roles in regulating RNA-based information transfer processes within the cell.

Keywords: Applied Physics.
Advisor: Puglisi Joseph D. 
Quake Stephen Ronald 
Bryant Zev David
Dynamic scheduling in large-scale manufacturing processing systems using multi-agent reinforcement learning

Scheduling in manufacturing plays an essential role in building smart manufacturing from multiple points of view, including social, economic, and environmental. Optimal scheduling, or the allocation of jobs with different requirements for a manufacturing processing system to meet various objectives, has been discussed for several decades. However, advanced scheduling methods in modern processing systems have not significantly improved, nor have they been widely adopted by staff working on manufacturing production lines despite extensive research conducted into scheduling. Most traditional scheduling methods require statistical assumptions, which cannot support operations for a dynamic and stochastic modern processing system. In addition, most proposed scheduling methods are not sufficiently scalable for managing real-world, large-scale processing systems. To address these limitations, we focus on the dynamic scheduling approach, which involves scheduling real-time events in large-scale modern manufacturing systems, from a data-driven perspective. We implement reinforcement learning (RL) to learn adaptive, scalable, and optimal dynamic scheduling policies, since RL can learn the underlying processing system's patterns and adaptively make allocation decisions based on real-time job and server measurements. The direct application of existing RL methods on the scheduling problem in such large-scale processing systems is impractical and undesired due to the extremely high computational complexity of learning a good scheduling policy. This thesis presents a practical and systematic computational framework that integrates RL with existing expert knowledge at three levels: (1) System-level planning. The planning procedure characterizes the processing system by the nominal feasible region of the scheduling problem. (2) Algorithm-level design. The design of the algorithm in RL is carefully selected as the index-policy-based, multi-agent RL, significantly reducing control policy search complexity. (3) Learning-level demonstration. During the learning process of RL, the existing expert knowledge is used as a demonstration to increase search efficiency and stabilize the RL learning process. We conduct various experiments in both real factory scenarios and simulated environments to evaluate the performance of the framework on processing system scheduling problems. The effectiveness of the proposed index-policy-based, multi-agent reinforcement learning (MARL) method is evidenced by its performance over traditional dynamic scheduling methods, with a linear computational time complexity in regard to the number of machines and job classes.

Advisor: Leckie James M.
Law K. H. (Kincho H.) 
Wang Jie (Researcher in adaptive computational learning)