VictorJuiz/thesis huggingface dataset:
Transcriptional feedback links lipid synthesis to synaptic vesicle pools in Drosophila photoreceptors [electronic resource]

Neurons can maintain stable synaptic connections across adult life. However, the signals that regulate expression of synaptic proteins in the mature brain are incompletely understood. Here we describe a transcriptional feedback loop between the biosynthesis of specific phospholipids containing long chain polyunsaturated fatty acids (LC-PUFAs) and the synaptic vesicle pool in adult Drosophila photoreceptors. Mutations that disrupt biosynthesis of these phospholipids cause degeneration of the axon terminal and loss of synaptic vesicles. While degeneration of the axon terminal is dependent on neural activity, activation of Sterol Regulatory Element Binding Protein (SREBP) is both necessary and sufficient to cause synaptic vesicle loss. Our studies demonstrate that SREBP regulates synaptic vesicle levels by controlling tetraspanins, critical organizers of membranous organelles. SREBP is an evolutionarily conserved regulator of lipid biosynthesis in non-neuronal cells; these studies reveal a surprising role for this feedback loop in maintaining synaptic vesicle pools in the adult brain.

Advisor: Clandinin Thomas R. (Thomas Robert)
Barres Ben
Reimer Richard J. advisor. Thesis advisor
Wang Xinnan advisor. Thesis advisor
Transcriptional regulation of epidermal differentiation by ZNF750 [electronic resource]

The epidermis is a continuously self-renewing tissue that forms a critical barrier between the inside of the body and the outside world. Self-renewing progenitor keratinocytes are located in the basal layer of the epidermis, and a subset of their progeny will differentiate and migrate outwards to form the epidermal permeability barrier. The process of epidermal differentiation is tightly regulated and disruption of this process can lead to skin cancer or other skin disorders. Thus, we sought to identify and functionally characterize novel regulators of epidermal differentiation. To identify novel regulators of epidermal differentiation, we searched for genes whose expression changed during this process. ZNF750 was identified by its significant increase in expression during epidermal differentiation. ZNF750 was completely uncharacterized, with the exception of several studies linking mutations in ZNF750 to psoriasis. Depletion of ZNF750 in organotypic epidermal tissue results in decreased expression of late epidermal differentiation genes. Enforced expression of ZNF750 in progenitor keratinocytes is sufficient to induce epidermal differentiation, and ZNF750-driven epidermal differentiation depends on a single C2H2 motif. The transcription factor p63 binds to the ZNF750 promoter and induces ZNF750 expression. ZNF750 then binds to the KLF4 promoter and induces KLF4 expression. To further understand how ZNF750 regulates epidermal differentiation, we identified ZNF750 direct target genes and interacting proteins. ZNF750 binds near differentiation genes it activates and progenitor genes it represses at a sequence-specific DNA motif. ZNF750-interacting proteins were identified to include KLF4, RCOR1, KDM1A, and CTBP1/2. ZNF750 protein-protein interactions occur through two PLNLS motifs and ZNF750 binds DNA through its C2H2 motif. KLF4 co-localizes ~10bp from ZNF750 near differentiation genes to facilitate their activation, but is unnecessary for progenitor gene repression. In contrast, KDM1A co-localizes with ZNF750 at progenitor genes to facilitate their repression. RCOR1 and CTBP1/2 are required for both effects. Thus, ZNF750 as a p63 target gene that interacts with KLF4, RCOR1, and CTBP1/2 to induce epidermal differentiation genes and interacts with KDM1A, RCOR1, and CTBP1/2 to repress epidermal progenitor genes.

Keywords: Biology.
Advisor: Khavari Paul A. primary advisor. Thesis advisor
Chang Howard
Gozani Or Pinchas advisor. Thesis advisor
Morrison Ashby J.
Transportation techniques for geometric data processing [electronic resource]

Modeling and understanding low- and high-dimensional data is a recurring theme in graphics, optimization, learning, and vision. Abstracting away application domains reveals common threads using geometric constructs like distances, similarities, and curvatures. This shared structure suggests the possibility of developing geometric data processing as a discipline in itself. To this end, this thesis introduces optimal transportation (OT) as a versatile component of the geometric data processing toolkit. Originally proposed for minimizing the cost of shipping products from producers to consumers, OT links probability and geometry using distributions to encode geometric features and developing metric machinery to quantify their relationships. To transition OT from theory to practice, we show how to solve previously intractable OT problems efficiently on discretized domains and demonstrate a wide range of applications enabled by this new machinery. We illustrate the advantages and challenges of OT for geometric data processing by outlining my recent work in geometry processing, computer graphics, and machine learning. In each case, we consider optimization aspects of the OT problem for relevant geometric domains---including triangulated surfaces, graphs, and subsets of Euclidean space---and then show how the resulting machinery can be used to approach outstanding problems in surface correspondence, modeling, and semi-supervised learning.

Advisor: Guibas Leonidas J. primary advisor. Thesis advisor
Fedkiw Ronald P.
Savarese Silvio advisor. Thesis advisor
The tribune and the people [electronic resource] : revolutionary leadership in France, 1789-1871

From 1789 Paris until today, revolutions have attempted to reach their goals all the while continuously re-thinking the relationship between leaders and followers in a popular movement. This project takes a look at the era that first defined and explored this dichotomy in revolutionary politics and rhetoric. By examining each key moment in the long century of French revolutions -- the revolution of 1789-1794, the July revolution of 1830, the events of February and June 1848, and, finally, the Paris Commune of 1871 -- I demonstrate the unstable and ever-developing nature of the relationship that the people in revolution has with those who claim to lead it. Presenting and analyzing debates on civic education, popular sovereignty, and revolutionary dictatorship as seen through emblematic novels and political thought of the period, I argue that the controversial figure of a "people's tribune" and its relationship to the people in revolution was central to the expiration of the revolutionary tradition in France.

Keywords: French and Italian.
Advisor: Edelstein Dan primary advisor. Thesis advisor
Baker Keith Michael advisor. Thesis advisor
Landy Joshua
"Tweeting for Tickets:” The Role of Social Media Marketing in Sports Franchises

In recent years, social networks like Facebook and Twitter have become extremely useful marketing tools. Recent literature has shown that the use of social networks by corporations is important for building brand equity and consumer relationships. Additional research has shown that a consumer’s emotional connection to a product or brand can lead to more consistent habits from the consumer. While a general hypothesis that increased use of social media marketing by corporations will lead to higher sales is intuitive, testing this in many consumer-facing businesses is difficult because it is difficult to attribute sales from increased social media activity to a consumer’s emotional attachment to the brand. Additionally, identifying specific time windows to compare changes in social media use and sales is difficult. This study builds on the current literature by looking specifically at social media use in the world of sports, where “fandom”, an extreme form of emotional attachment, is present,
and ticket sales can be measured game-to-game, so there are clear time benchmarks between which we can analyze changes in social media activity. In particular, this paper looks to exploit these characteristics of the sports world by analyzing the Twitter activity of franchises in the National Basketball Association (NBA). The results of the analysis show significant association between game attendances and both short-term and long-term Twitter activity measures. These effects increase and remain significant when looking only at teams located in “small markets”, cities with a TV population less than 3 million. Collectively, these results suggest that social media activity is associated with sales through the construct of consumers’ emotional attachment with a brand.

Keywords:  Department of Economics
Stanford Department of Economics
Thesis
Advisor: Hartmann Wesley
Ultra high-throughput evolution towards the brightest monomeric green fluorescent protein

Since the first demonstration of exogenous Green Fluorescent Protein (GFP) expression in E.coli and C. elegans, fluorescent proteins have served as revolutionary molecular tools in the life sciences. The brightest fluorescent proteins enable super resolution imaging, a microscopic technique with resolution at the nanometer scale. Here, we engineered a green fluorescent protein for enhanced brightness using the ultra-high throughput μSCALE engineering platform. The μSCALE platform utilizes a glass array comprised of millions of densely packed 10um capillaries, enabling the screening and isolation of the brightest clones from libraries with nearly 106 variants. Starting from a single domain of a recently isolated four-domain Anthoathecata protein, a bright dimer with brightness exceeding five times the parent was evolved in only four rounds of evolution. The dimer was rationally monomerized through disruption of a hydrophobic interface to produce a monomer, the desired oligomeric status for a molecular imaging tool. The resulting monomer was again evolved for improved brightness, surpassing that of the parent while retaining monomeric character.

Keywords: fluorescent protein
evolution
Thesis
Advisor: Cochran Jennifer
Altman Russ B.
Deisseroth Karl
Ultrafast multifocal two-photon microscopy for brain imaging [electronic resource]

Two-photon fluorescence microscopy has extensive application in biological studies, but it is typically limited by low full-field frame rates of ∼10-20 Hz. We present a novel multifocal two-photon microscope design that can image 455 × 110 μm2 at 1 kHz frame rate and 455 × 306 μm2 at 400 Hz with micron-level resolution. We utilize an ultrashort-pulsed regenerative fiber laser amplifier as the excitation source, and use a micro-lens array to split the initial laser beam into a rectangular array of beamlets. The array of beamlets is tilted at a fixed angle along the major optical axis in the excitation path, and is scanned laterally along a single dimension with a laser-scanning mirror to cover the entire FOV at the x-y focal plane. We use a low-read-noise scientific CMOS camera to acquire multi-pixel images in the collection path of the microscope. We further demonstrate its ability to track single cell flow trajectories in cerebral arterial networks, capture cerebral bridging vein constriction events near the superior sagittal sinus, and estimate Purkinje cell Ca2+ spike timing, all with millisecond temporal resolution.

Keywords: Mechanical Engineering.
Advisor: Schnitzer Mark Jacob
Carryer J. Edward
Delp Scott advisor. Thesis advisor
Ultrafast response of single ferroelectric nanoparticles [electronic resource]

Ferroelectric nanowires represent fundamental building blocks of complex functional devices due to their large nonlinear optical and piezoelectric responses, related to the large built-in electric polarization of the ferroelectric material. The coupling of light to nanoscale ferroelectrics enables novel means of engineering and manipulating their coupled degrees of freedom and inducing new functionality, including photo-ferroelectric effects and other opto-mechanical responses.Because one dimensional nanowires with subwavelength diameters exhibit modified light-matter interactions, they represent an unexplored means of coupling to these degrees of freedom all-optically. Here we present ultrafast nonlinear-optical measurements of light induced structural and electronic dynamics within single ferroelectric nanowires driven by above band gap femtosecond light pulses. By utilizing second harmonic generation (SHG) processes, which are sensitive to the non-centrosymmetry of the unit cell, we can probe the structural and polarization response in real-time. We can also identify the crystallographic orientation of the nanowire by SHG. In this thesis, the results for single barium titanate nanowires and potassium niobate are discussed. We observe ultrafast modulations in SHG, associated with both photo-refractive effects and polarization rotation under light excitation from single barium titanate nanowires. Then the nonlinear optical measurements probing the dynamics of single potassium niobate nanowires integrated into an optical tweezers setup is discussed. We observe large-amplitude, reversible modulations of the nonlinear optical properties and the associated ferroelectric polarization developing within a few picoseconds, and probe the enhanced coupling of the light into the nanowire. These measurements open up new possibilities for both all-optical manipulation of the nonlinear optical properties of single nanowires and for ultrafast microscopy at sub-wavelength resolution.

Keywords: Electrical Engineering.
Advisor: Lindenberg Aaron Michael primary advisor. Thesis advisor
Fan Shanhui
Miller D. A. B. advisor. Thesis advisor
Ultrasound-guided robotic needle steering for percutaneous interventions in the liver [electronic resource]

Liver cancer is a significant health concern worldwide. Percutaneous ablation of liver tumors is a common treatment that suffers from significant limitations, primarily the inability to treat larger tumors and tumors in certain regions of the liver. Robotic needle steering is a technique for inserting flexible needles along controlled, curved paths through tissue. Applying robotic needle steering in percutaneous ablation of liver tumors could potentially allow clinicians to correct for errors during insertion, steer around obstacles to previously unreachable targets, and reach multiple targets from a single insertion site. To date, however, robotic needle steering has largely been limited to artificial tissues and tightly controlled bench-top settings. The goal of this dissertation was to move robotic needle steering closer to the clinical domain, by solving several technical problems specific to percutaneous ablation of liver tumors. Clinical application of robotic needle steering necessitates real-time medical imaging methods, steerable needles that can curve tightly and reach the majority of the liver volume, and a control approach that allows the clinician to define targets and provide feedback using medical imaging. First, a method for automatically segmenting a steerable needle from 3D ultrasound data is proposed, which uses mechanical vibration of the steerable needle to make it visible in power Doppler images. Second, finite-element and experimental studies of steerable needle insertion are described, and demonstrate that average radius of curvature of approximately 50 mm can be achieved in liver tissue through optimization of bent-tip geometry. An articulated-tip design, which uses a miniaturized rotary joint to articulate a distal section is also presented. Third, to allow closed-loop control of a needle steering robot using ultrasound measurements, an estimation scheme based on an unscented Kalman filter is proposed. Finally, a complete pre-clinical system for image-guided needle steering is presented, which combines the described methods for imaging, needle design and control. Validation testing in a porcine cadaver is described, in which simulated targets are introduced into the liver, and the system is used to place the steerable needle tip at the target.

Keywords: Mechanical Engineering.
Advisor: Okamura Allison primary advisor. Thesis advisor
Cutkosky Mark R. advisor. Thesis advisor
Rock Stephen
Uncertainity propogation in multiphysics systems [electronic resource]

Multiphysics systems governed by coupled partial differential equations (PDEs) are naturally suited for modular (partitioned) numerical solution strategies. Although widely used in deterministic simulations, several challenges arise in extending the benefits of modularization to stochastic simulation i.e. uncertainty propagation. Monolithic (black-box) Monte Carlo (MC) based sampling methods ignore the potentially exploitable structures within the multiphysics model, and are generally unreliable because the cost of each PDE solve is significantly high. On the other hand, spectral methods, for instance, generalized polynomial chaos (gPC) based methods, would succumb to the curse of dimensionality, if implemented in their standard (traditional) form, as the coupled nature of the model dictates that each module should handle the combined parameter space for uncertainty propagation. In this thesis, we present a practical module-based framework and efficient spectral methods for uncertainty propagation in multiphysics systems with uncertain parameters. Our proposed framework facilitates complete module-based modeling independence, wherein each module only handles its local uncertain parameters, employing the best suited method. Moreover, the proposed reduced non-intrusive (NISP) and reduced intrusive spectral projection (ISP) methods mitigate the curse of dimensionality by constructing reduced dimensional (and order) approximations of the data communicated between modules and iterations. We demonstrate implementations of our proposed methods on several benchmark test problems, and illustrate their superior performance over standard monolithic methods.

Advisor: Iaccarino Gianluca primary advisor. Thesis advisor
Kitanidis P. K. (Peter K.) advisor. Thesis advisor
Tong Charles
Under-constrained symbolic execution [electronic resource] : correctness checking for real code

Software defects pose a frequent challenge to developers, and their consequences are far-reaching. Despite advances in software engineering practices, programming language design, and debugging tools, bugs remain ubiquitous. Traditional testing techniques, while useful, have failed to prevent a significant number of bugs from affecting end users. One promising technique for automatically detecting bugs is dynamic symbolic execution, which aims to test all possible execution paths through a program and identify inputs that cause the program to crash. Unfortunately, symbolic execution suffers from the well-known path explosion problem because the number of distinct execution paths through a program is, in the best case, exponential in the number of branch statements. Consequently, symbolic execution tools are typically ineffective for programs consisting of more than a few thousand lines of code, let alone large codebases with line counts in the millions. This dissertation presents a new, scalable approach to symbolic execution, under-constrained symbolic execution, that targets individual functions rather than whole programs. This technique supports direct symbolic execution of arbitrary C functions and automatically synthesizes their inputs, even for complex, pointer-rich data structures. We demonstrate this technique's feasibility by thoroughly evaluating three use cases, although many others are possible. First, we use it to check the equivalence of library routines from different implementations that share a common interface (e.g., the C standard library). Second, we check whether code patches introduce new bugs by comparing two versions of the same function: before and after a patch is applied. Third, we use under-constrained symbolic execution to test a single version of a function, using a combination of heuristics to separate important errors from those likely to be false positives. In this dissertation, we describe UC-KLEE, a tool we built that implements under-constrained symbolic execution and supports the above use cases. We evaluate our tool on large, mature codebases including BIND, OpenSSL, and the Linux kernel and describe previously-unknown bugs we discovered in each of these codebases.

Advisor: Engler Dawson R. primary advisor. Thesis advisor
Aiken Alexander advisor. Thesis advisor
Dill David L. advisor. Thesis advisor
Understanding and affecting students' path to success in community colleges [electronic resource]

In the four papers of this dissertation, I examine the question of how structural policies and practices affect student outcomes in community colleges. Together, these papers aim to deepen our understanding of how students make decisions in community colleges with an eye toward how such an understanding could influence policy and practice. In papers 1 and 2, I examine the effects of two structural interventions (a more streamlined transfer process from two- to four-year schools and requiring students to declare a major intent when applying) on student course taking behavior. In papers 3 and 4 I use a multi-stage model of choice (observing awareness, consideration and choice) to examine how different groups of students make programmatic and major-choice decisions to gain a more nuanced understanding of how of how this important decision process unfolds.

Keywords: Education.
Advisor: Reardon Sean F. primary advisor. Thesis advisor
Bettinger Eric advisor. Thesis advisor
Dee Thomas S. (Thomas Sean) advisor. Thesis advisor
Kurlaender Michal
Understanding antibiotic resistance in bacteria through molecular dynamics simulations [electronic resource]

An atomic level understanding of how biological molecules and proteins function is an ongoing challenge in chemical biology. Spectroscopic methods are useful for providing information about stable states and overall transition processes but it is impossible to directly observe these processes at an atomistic level of detail. Here, computational techniques are used to supplement experimental measurements in order to provide a more complete picture of a bacterial resistance to antibiotics at the atomic scale. Markov Models are used to analyze Molecular Dynamics simulations in order to propose an activation pathway for the conformational change in a key bacterial signaling protein NtrC. Similar techniques are applied again, in combination with a novel clustering algorithm, to compute the binding affinity of vancomycin to its targets. In sum, the present work demonstrates how simulations can contribute to a better understanding of important biological systems.

Keywords: Chemistry.
Advisor: Pande Vijay primary advisor. Thesis advisor
Cegelski Lynette advisor. Thesis advisor
Martinez Todd J. (Todd Joseph)