VictorJuiz/thesis huggingface dataset:
3D reconstruction in the wild [electronic resource]
Keywords: Electrical Engineering.

Are existing RGB-D reconstruction pipelines ready for broad deployment? To answer this question and assist future research, I present a dataset of thorough RGB-D videos of more than 10,000 objects, produced in the wild by paid operators for the purpose of reconstruction. An evaluation of existing RGB-D reconstruction approaches reveals that they often fail on the collected data, in part due to insufficiently robust loop closure detection and global optimization. I thus present a new approach to object and indoor scene reconstruction from RGB-D video. The key idea is to combine geometric registration of fragments with robust global optimization based on line processes. Geometric registration is error-prone due to sensor noise, which leads to aliasing of geometric detail and inability to disambiguate different surfaces in the scene. The presented optimization approach disables erroneous geometric alignments even when they significantly outnumber correct ones. The objective has a least-squares form and is optimized by a high-performance pose graph solver. Experimental results demonstrate that the presented approach substantially increases the accuracy of reconstructed models on challenging real-world sequences.
A correctional algorithm for intracranial electrode localization through the simulation of post-operative brain surface deformation
Keywords: electrode localization
finite element analysis
surgical planning
electrocorticography
brain shift
Thesis

Electrocorticography can be used to measure and understand electrical potentials on the brain surface which underlie cognitive function of the cerebral cortex. In order to derive understanding between cortical function and structure, the precise locations of the electrodes must be known. However, due to deformation of the brain surface that occurs during craniotomy, the positions of electrodes cannot be determined from alignment of CT with MRI scans, and additional corrective measures become necessary. While current leading methods rely on computing linear projections from the deformed post-operative brain onto the non-deformed preoperative brain, these methods experience limitations in areas of the brain with more variable curvature. In order to account for variable curvature, the post-operative brain was biomechanically simulated using finite element methods in order to map and invert brain surface deformation.
This approach was tested on 4 patients who were candidates for epilepsy surgery at Stanford Hospital. The algorithm localized electrodes with average error of 3.70 +/- 0.15 mm, (median +/- s.e.) measured as radial arc length in the plane of the cortical surface. While this error is slightly higher than that of competing methods, the standard error is lower, suggesting improved robustness. Additionally, this error it is measured in the plane of the brain as opposed to the plane of intraoperative photography, removing spatial distortion induced from 3D projection and providing a more realistic margin of error. Gold-standard electrode positions were determined by manually coregistering intraoperative photography with pre-operative MRI and back-projecting electrodes onto a three-dimensional mesh. This algorithm is entirely automatic, and provides a fast (< 1 minute) processing pipeline for electrode localization and display. These results suggest possible future viability of the algorithm for use in clinical and research settings, where it may improve spatial precision of electrocorticography in epilepsy surgery and cognitive research.
A Functionality-Driven Process for Rapidly Building Semantic Parsers
Keywords: semantic parsing
natural language processing
computer science
Thesis

Imagine being able to build and train a parser over any domain of knowledge, starting from zero training data, over the course of a few hours. In this thesis, my research goal is to develop a new functionality-driven methodology in an attempt to achieve this. My attempt uses a domain-general grammar and a domain-specific seed lexicon to generate logical forms paired with canonical utter- ances that capture the meaning of the logical forms. By construction, the domain-general grammar ensures complete coverage of the desired set of compositional operators. I then use crowdsourcing to paraphrase these canonical utterances into natural utterances. The resulting data is used to train the semantic parser. I further study the role of compositionality in the resulting paraphrases. Finally, I test our methodology on eight domains and show that I can build an adequate semantic parser in just a few hours.
A Molecular Switch: The Role of β-catenin Tyrosine Phosphorylation in Regulating Adherens Junctional Stability
Keywords:  Department of Biology
Biology
Adherens Junction
β-catenin
tyrosine phosphorylation
ITC
cancer
Y142
Y654
structural biology
biophysics
Thesis

β-catenin functions in the contexts of (1) cell development as a transcription factor for Wnt target genes and (2) cell-cell adhesion as an adaptor in cadherin-based adherens junctions. Mutations in β-catenin or in molecules regulating its localization and stability are associated with inappropriately triggered cell growth, weakened cell adhesion, and oncogenesis. Such correlation underscores the need to understand the molecular mechanisms by which β-catenin’s localization, and thereby its function, is regulated. An increasing body of evidence has suggested that the extent to which β-catenin partakes in either function may be influenced by phosphorylation. In particular, tyrosine phosphorylation of β-catenin has been qualitatively shown to modulate the affinities of two key binding partners at adherens junctions: cadherin and α-catenin. This study seeks to quantitatively assess the impact of tyrosine phosphorylation at specific sites on β-catenin’s affinity for cadherin and α-catenin. Through in vitro thermodynamic measurements by isothermal titration calorimetry (ITC) with β-catenin Y to E phosphomimics we show that tyrosine phosphorylation at Y142 and Y654 weakens β-catenin’s affinity for α-catenin and cadherin respectively. These results help construct a model of β-catenin regulation and may offer future therapeutic approaches for cancer.
A New Switzerland? 21st Century German Foreign Policy Reconsidered
Keywords: German Foreign Policy
Neorealism
Domestic Culture
Domestic Politics
Pacifism
Center for International Security and Cooperation
Thesis

Seventy years ago, Germany was a country known more for conquering its neighbors than cooperating with them. But today, Germany is a country known for its economic power, not military might. Some people argue that Germany today is in fact too pacifist, too reluctant to use force even responsibly. With German reunification in 1990, a new foreign policy developed that was closely aligned with the old West German foreign policy. Both were characterized by a domestic culture driven by multilateralism and pacifism.
German foreign policy in the 1990s was defined by the prioritization of multilateralism and pacifism; does this domestic culture still guide German foreign policy today? This thesis examines the question of what has governed German foreign policy thus far in the 21st century.
In order to answer this question, the thesis develops two frameworks through which to analyze three case studies on the German decision to deploy force abroad – Afghanistan, Iraq, and Libya. The first framework is based on the theory of neorealism. The second framework is based on the theory of domestic politics and culture.
This thesis argues that the framework of domestic politics accurately explains 21st century German foreign policy. Neorealism does not. German foreign policy today is governed by domestic politics, which is itself governed by domestic culture. There are two critical aspects of German domestic culture today. First, Germany today prioritizes the principle of pacifism over the principle of multilateralism. Second, Germany today prioritizes pacifism over that of humanitarianism. Overall, thus far in the 21st century Germany seems to be a country that prioritizes the assurance of never-again German militarism over that of never-again German unilateralism or never-again mass international human right abuses.
A Zero-Sum Game: The Energy-Water Crisis in Northwest China
Keywords: China
energy security
water security
energy-water crisis
nexus
Xinjiang
northwest China
water management
provincial decision-making
Center for International Security and Cooperation
Thesis

China faces significant water security challenges, many of which will be aggravated by increasing energy demands and climate change. This thesis evaluates the magnitude of the water security threats and the effectiveness of current water policies in China.
The analysis demonstrates that China understands the significance of the water scarcity threat but also that its current policies are inadequately managing the country's water resources. As China’s energy sector continues to expand, it will need to balance limited water resources among agriculture, industry, energy, and other needs of the people. All of these complex issues surface in the northwest province of Xinjiang, which has political instability and ethnic conflict, severely limited water resources, an important agricultural industry, and the Tarim shale basin which is attractive for hydraulic fracturing.
To manage water resources effectively, China will need to reform the provincial decision-making process, starting with new incentives for provincial leaderships. China must find ways to incentivize provincial leaders to prioritize water management, regulate industry to improve water efficiency and reduce pollution, develop energy strategies that factor in water withdrawals, and alleviate ethnic tensions in Xinjiang that could be exacerbated by water insecurity. Failure to manage water resources efficiently through effective water policies could seriously constrain China's future economic development.
Accelerator on a chip [electronic resource] : design, fabrication, and demonstration of grating-based dielectric microstructures for laser-driven acceleration of electrons
Keywords: Applied Physics.

The enormous size and cost of current state-of-the-art accelerators based upon conventional radio-frequency (RF) technology has spawned a great interest in developing new acceleration concepts that are more compact and economical. Micro-fabricated dielectric laser accelerators (DLAs) are an attractive approach as such structures can support accelerating fields one to two orders of magnitude higher than RF cavity-based accelerators. DLAs use commercial lasers as a power source, which are smaller and less expensive than RF klystrons that power today's accelerators. In addition, DLAs are fabricated via mass-producible, low cost, lithographic techniques. However, despite several DLA structures being proposed recently, no successful demonstration of acceleration in these structures had been shown until this work. This thesis reports the first observation of high-gradient (exceeding 300 MeV/m) acceleration of electrons in a DLA. Relativistic (60 MeV) electrons are energy modulated over 563 optical periods of a fused silica grating structure, powered by a 800 nm wavelength mode-locked Ti:Sapphire laser. The observed results are in agreement with analytical models and electrodynamic simulations. By comparison, conventional modern linear accelerators operate at gradients of 10-30 MeV/m; and the first linear RF cavity accelerator was 10 RF periods (1 m long) with a gradient of approximately 1.6 MV/m. Our results set the stage for the development of future multi-staged DLA devices composed of integrated on-chip systems. This would enable compact table-top MeV to GeV scale accelerators for security scanners and medical therapy, university-scale x-ray light sources for biological and materials research, portable medical imaging devices, and would substantially reduce the size and cost of a future multi-TeV scale collider.
Acoustic interference between echolocation calls of two species of California bat (Myotis, Vespertilionidae)
Keywords: Electrical Engineering
echolocation
sonar
bat
bats
biosonar
interference
Thesis

Many species of bats rely on echolocation—a biological sonar system—to carry out essential survival tasks such as hunting and orienting in their nighttime environments. How bats echolocate so successfully despite considerable physical and acoustic obstacles is a fascinating problem in signal processing. Because bats often live in large groups, they encounter substantial acoustic interference from echolocating conspecifics that may impede their own ability to echolocate.
In the present study, I examine the theoretical effect of interference from conspecifics and congenerics on the target detection ability of two cohabiting species of vespertilionid bat found in California (Myotis californicus and M. yumanensis). I use the wideband ambiguity function, a tool for analyzing human-made radar and sonar systems, to assess whether it is theoretically possible for a bat to shift its call in frequency to reduce the effect of conspecific interference. I apply the same methods to investigate the effect of interfering calls from M. californicus on the target detection ability of M. yumanensis and vice versa.
Results indicate that these two species experience considerable interference from both within- and between-species calls. Incorporating data from the field suggest that a bat’s calls are shaped such that most interference an individual is likely to encounter manifests as a reduction in the bat’s ability to accurately locate a target rather than as an increase in likelihood that the bat will mistake one object for another—an adaptation that may prevent the bat from becoming disoriented or losing track of an acquired target. Differences in calls between M. californicus and M. yumanensis may reflect adaptations to environmental clutter. Further research should focus on the implications of congeneric interference for the spatial and temporal distribution of these species.
Adaptive myelination in the mammalian brain [electronic resource]
Keywords: Stem Cell Biology and Regenerative Medicine Interdisciplinary PHD Program.

Myelin sheaths, specialized segments of oligodendrocyte plasma membranes in the central nervous system, facilitate fast, saltatory conduction of action potentials down axons. Myelination of the central nervous system requires the generation of functionally mature oligodendrocytes from oligodendrocyte precursor cells. Changes to the fine structure of myelin in a neural circuit are expected to affect conduction velocity of action potentials. Recent evidence from humans and animal models suggests that myelination may be sensitive to experiences during development and adulthood, and that varying levels of neuronal activity may underlie these experience-dependent changes in myelin and myelin-forming cells, perhaps selectively instructing myelination of an active neural circuit. In this thesis, I present work using optogenetic stimulation of premotor cortex in awake, behaving mice to demonstrate that neuronal activity elicits a mitogenic response of neural and oligodendrocyte precursor cells, promotes oligodendrogenesis and increases myelination within the deep layers of the premotor cortex and subcortical white matter. Neuronal activity-regulated oligodendrogenesis and myelination is associated with improved motor function of the corresponding limb. Oligodendrogenesis and myelination appear necessary for the observed functional improvement, as epigenetic blockade of oligodendrocyte differentiation and myelin changes prevents the activity-regulated behavioral improvement. A deeper understanding of adaptive myelination may provide insights into diseases involving damage and dysregulation of myelin and myelin-forming cells.
Adaptive particle filters for high signal-to-noise ratios with applications to robotics [electronic resource]
Keywords: Electrical Engineering.

Dynamic state-space models are useful for describing data in various fields, including robotics. An important problem that may be solved by using dynamic state-space models is the estimation of underlying state processes from given observations. When the models are non-linear and the noise not Gaussian, it is impossible to solve the problem analytically; thus, particle filters, also known as sequential Monte Carlo methods, tend to be employed. However, because particle filters are based on sequential importance sampling, the problem arises of how to select the importance density function. Handling unknown parameters in the model presents another significant difficulty in particle filtering. Simultaneous localization and mapping (SLAM) in robotics is one well-known but difficult problem for which particle filters have been used. This dissertation is motivated by SLAM problems and related particle filtering approaches. In this dissertation, we design a new proposal distribution that better approximates the optimal importance function, using a novel way of combining information from observations and state transition dynamics. In the first part of our study, after reviewing representative approaches for SLAM problems, we justify our method of combining information with a series of examples and offer an efficient means of constructing the new proposal distribution. In the second part, we focus on the problems inherent in handling unknown parameters in state-space models. We suggest the application of one-step recursive expectation-maximization (EM) algorithm to learn unknown parameters, and recommend pairing it with the new proposal distribution into an adaptive particle filter algorithm. Furthermore, we propose a new SLAM filter based on the adaptation of the new adaptive particle filter to SLAM problems. In Chapter 3, we conduct simulation studies on localization and SLAM problems to demonstrate the superior numerical performance of the proposed algorithms.
Adhesion and reliability of solar module materials [electronic resource]
Keywords: Materials Science and Engineering.

Delamination of solar module laminates (encapsulations, backsheets and frontsheets) is the least understood failure mode in the PV industry. It is well known, however, that long-term exposure to environmental stressors, including moisture, temperature and UV light, often leads to laminate degradation and ensuing loss of adhesion. Low levels of mechanical stress (thermal, wind, or handling) can then lead to module debonding, component corrosion and loss of function. Although adhesive failure of module laminates is frequently reported, it has yet to be characterized, understood or quantified. In this dissertation, I present a series of mechanics-based techniques to quantify adhesion in encapsulations, backsheets and frontsheets. Cantilever-beam and cantilever--plate techniques were developed for small specimens and full-size modules. Up to 90% loss of laminate adhesion was measured after small increases of operating temperature (T), relative humidity (RH) and UV light. These metrologies allow the use of an absolute scale (J/m2) to quantify adhesive stability after field or simulated exposures. To estimate module lifetime, the kinetics of debonding of the module laminates were characterized in the presence of environmental stressors. Debonding rates as low as 10-8 m/s were studied as a function of mechanical stress, T, RH and UV light. The debond growth rates of the laminates increased up to 1000-fold with small increases of T (10°C) and RH (15%). To elucidate the mechanisms of environmental debonding, fracture and bond-rupture kinetics models were developed. In these models, the viscoelastic relaxation and reaction-kinetics processes at the debonding-tip are used to predict debond growth. The adhesion metrologies and kinetics models we developed constitute a fundamental basis for developing accelerated aging tests and long-term reliability predictions for solar module materials.
Advanced genome engineering of induced pluripotent stem cells for therapeutic purposes [electronic resource]
Keywords: Genetics.

The ability to precisely modify the genome with high efficiency in a directed manner is dependent on generating and exploiting a double-strand break in DNA. The tools available to generate double-strand breaks include the recombinases and resolvases, the phage integrases, the homing endonucleases, zinc finger nucleases, transcription activator-like effector nucleases, and the CRISPR/Cas9 system, the most recently developed tool. These tools allow for in-depth studies of the function of genes and genome structure, the generation of organisms bearing economically important bio-synthetic pathways, and the development of novel gene and cell therapies for addressing previously untreatable diseases. Taking full advantage of each tool and knowing when to use each one requires a thorough understanding of how the tool functions. For most of the genome engineering toolkit, this understanding has been achieved. The CRISPR/Cas9 system, however, has been assumed to function in the same manner as the zinc finger and transcription activator-like effector nucleases despite generating blunt-end double-strand breaks rather than staggered breaks. This difference is important to understanding how Cas9-mediated double-strand breaks are repaired, and, thus, how best to exploit these breaks for genome engineering. This thesis illustrates the importance understanding how each genome engineering tool functions in developing advantageous methods for gene and cell therapies.
Advancing computational prediction of RNA structures and dynamics [electronic resource]
Keywords: Biochemistry.

RNA plays critical roles in fundamental biological processes, including transcription, translation, post-transcriptional regulation of genetic expression, and catalysis as enzymes. These critical RNA functions are determined by the structures and dynamics of the RNA molecules. Computational methods might be used to predict the structures and dynamics of RNA. Unfortunately, the prediction accuracies of current computational methods are still inferior compared to experiments. In this dissertation, I discuss recent advances I made in improving and developing computational methods to make accurate predictions on the RNA structures and dynamics. The dissertation contains three individual research projects. In the first part, I present a protocol for Enumerative Real-space Refinement ASsisted by Electron density under Rosetta (ERRASER). ERRASER combined RNA structure prediction algorithm with experimental constraints from crystallography, to correct the pervasive ambiguities in RNA crystal structures. On 24 RNA crystallographic datasets, ERRASER corrects the majority of steric clashes and anomalous backbone geometries, improves the average Rfree by 0.014, resolves functionally important structural discrepancies, and refines low-resolution structures to better match higher resolution structures. In the second part, I present HelixMC, a package for simulating kilobase-length double-stranded DNA and RNA (dsDNA and dsRNA) under external forces and torques, which is typical in single-molecule tweezers experiments. It recovered the experimental bending persistence length of dsRNA within the error of the simulations and accurately predicted that dsRNA's "spring-like" conformation would give a two-fold decrease of stretch modulus relative to dsDNA. In the third part, I developed a framework of Reweighting of Energy-function Collection with Conformational Ensemble Sampling (RECCES), to predict the folding free energies of RNA duplexes. With efficient sampling and reweighting, RECCES allows comprehensive exploration of the prediction power of Rosetta energy function, and provides a powerful platform for testing future improvement of the energy function. In all the projects above, I leveraged rich datasets from previous experiments to develop novel algorithms that gave predictions with unprecedented accuracies, which were validated by independent blind tests. These computational methods I developed could also serve as a solid foundation for future efforts of improving prediction accuracies of RNA computational algorithms.