VictorJuiz/thesis huggingface dataset:
The Role of Sirtuins in the Molecular Topography of Silenced Chromatin

Heterochromatin is key to the appropriate regulation of cell identity. Saccharomyces cerevisiae silent mating loci, HML and HMR, provide a simple, yet elegant model for the regional control of transcriptional repression and its contribution to cell identity. Yeast can be of mating type a or &alpha as is dependent on the alleles at the actively transcribed MAT locus. However, additional copies of the &alpha and a genes are present elsewhere in the genome to facilitate mating-type switching. Interestingly, even though HML and HMR have the exact same promoters as when the genes are at the MAT locus, the genes are not expressed. This promoter-independent repression is due to the Silence Information Regulator (Sir) proteins. Current models of yeast silencing posit that Sir proteins are recruited by transcription factors to HML and HMR. Sir2, whose catalytic activity is necessary for silencing and is the founding member of the sirtuin enzymatic class, deacetylates the neighboring nucleosome creating a high-affinity binding site for the Sir complex. Iterative rounds of this deacetylation results in spreading of Sir proteins across the silenced locus, which is key to silencing. Through a similar mechanism, the Sir-protein complex is also important for silencing telomeres./nThis nucleation and spreading model for silencing makes testable prediction of silencing. For example, if iterative rounds of deacetylation by Sir2 are necessary for silencing, then a Sir complex would occupy each nucleosome at silenced loci. Additionally, this model only attributes Sir-protein association to HML, HMR and telomeres and not elsewhere in the genome. Lastly, if Sir2's only known role is to deacetylate nucleosome tails then its catalytic activity should be bypassed by preemptively removing these histone acetylations./nTo test these predictions of the silencing model I have definitively characterized the distribution of Sir proteins throughout the genome and explored the unaccounted role for Sir2's catalytic activity in silencing. By characterizing the distributions of Sir2, Sir3 and Sir4 at high-resolution I have revealed unappreciated nucleation sites for Sir proteins at HML and HMR and a possible higher-order structure critical to silencing. Characterization of Sir proteins across the genome revealed an unanticipated phenomenon of highly-expressed genes being vulnerable to non-specific ChIP enrichment. Lastly, I performed a forward genetic screen to restore silencing independent of Sir2 catalytic activity. This screen identified a non-sirtuin deacetylase as refractory to silencing and suggested the possible role of a non-histone deacetylase substrate as important for silencing. This dissertation work has refined the Saccharomyces cerevisiae silencing model, contributing to our understanding of regional repression across organisms.

Advisor: Rine, Jasper
High-dimensional statistics with systematically corrupted data

Noisy and missing data are prevalent in many real-world statistical estimation problems. Popular techniques for handling nonidealities in data, such as imputation and expectation-maximization, are often difficult to analyze theoretically and/or terminate in local optima of nonconvex functions---these problems are only exacerbated in high-dimensional settings. We present new methods for obtaining high-dimensional regression estimators in the presence of corrupted data, and provide theoretical guarantees for the statistical consistency of our methods. Although our estimators also arise as minima of nonconvex functions, we show the rather surprising result that all stationary points are clustered around a global minimum. We describe extensions of our work to nonconvex regularizers, and demonstrate that an adaptation of composite gradient descent may be used to compute a global optimum up to statistical precision in log-linear time. Finally, we show how our corrupted regression methods may be applied to structure estimation for undirected graphical models, even when data are observed with systematic corruption. We derive new relationships between augmented inverse covariance matrices and the edge structure of discrete-valued graphs, and combine our population-level results with corrupted estimation methods to create new algorithms for graph estimation. We close with theoretical results and preliminary simulations in the domain of compressed sensing MRI.

Advisor: Wainwright, Martin J
Symmetric Constrained Optimal Control: Theory, Algorithms, and Applications

This dissertation develops the theory of symmetry for constrained linear systems. We use symmetry to design model predictive controllers for constrained linear systems with reduced complexity./nThe dissertation is divided into three parts. In the first part we review the relevant results from model predictive control and group theory. In particular we present algorithms and data structures from computational group theory used to efficiently search groups./nIn the second part we develop the theory of symmetry for constrained linear systems and model predictive control problems. Symmetries of constrained linear systems are linear transformations that preserve the dynamics and constraints. A symmetry of a model predictive control problem is a symmetry of the underlying constrained system that also preserves the cost. We use a group theoretic formalism to derive properties of symmetric constrained linear systems and symmetric model predictive control problems. We prove conditions under which the model predictive controller is symmetric and present a procedure for efficiently computing the symmetries of constrained linear systems and model predictive control problems. Our method transforms the problem of finding generators for the symmetry group into a graph automorphism problem. These symmetries are used to design model predictive control algorithms with reduced complexity./nWe also present two novel explicit model predictive control designs. Both reduce memory requirements by discarding symmetrically redundant pieces of the control-law. The control-law in the eliminated pieces can be reconstructed online using symmetry. We show that storing the symmetries of the problem requires less memory than storing the controller pieces./nIn the third part of this dissertation we apply our symmetry theory to the battery balancing problem. We use symmetry to reduce the memory requirements for explicit model predictive controllers for seven battery-balancing hardware designs proposed in the literature. This application demonstrates that our symmetric controller designs can significantly reduce the memory requirements of explicit model predictive control. In particular for four out of seven of the designs in our numerical study, the number of pieces in the symmetric controller did not increase as the battery pack-size was increased.

Advisor: Borrelli, Francesco
Online Trajectory Generation for Robot Manipulators in Dynamic Environment -- An Optimization-based Approach

Interest in robot manipulators interacting with dynamic environments has been continuously growing because of the increasing demand for industrial robot collaboration. Human-robot collaboration and robot-robot collaboration are the two scenarios of robot collaboration that have generally been considered. The difficulties of such applications may be described from two perspectives: a good perception of environment and a proper algorithm to react to the dynamic environment for the robot manipulators. Online trajectory generation is one of the approaches for robot reaction. In the generation of the trajectory, the transformation between joint space and task space is necessary since the sensor measurement of the environment is in task space and the trajectory of the robot manipulator is in joint space. The transformation needs to be done online in a dynamic environment and hence easily results in an exponential increase of the computational load./nThis dissertation proposes a safety index and the associated robot safety system in order to assess and ensure the safety of the agent in the collaboration scenarios. The agent could be a human worker in human-robot collaboration or another robot in robot-robot collaboration. In the robot safety system, the online trajectory generation algorithm is formulated in the optimization-based trajectory planning framework. The safety index is evaluated using the ellipsoid coordinates attached to the robot links that represents the distance between the robot manipulator and the agent. To account for the inertial effect, the momentum of the/nrobot links are projected onto the coordinates to generate additional measures of safety. The safety index is used as a constraint in the formulation of the optimization problem so that a collision-free trajectory within a finite time horizon is generated online iteratively for the robot to move toward the desired position. To reduce the computational load for real-time implementation, the formulated optimization problem is further approximated by a quadratic problem. Moreover, a heuristic strategy is proposed to select the active constraints for the next iteration so as to further reduce the computational load. The safety index and/nthe proposed online trajectory generation algorithm are simulated and validated in both a two-link planar robot and a seven-DOF robot in human-robot collaboration and robot-robot collaboration. Simulation results show that the proposed algorithm and robot safety system are capable of generating collision-free and smooth trajectories online./nThe proposed algorithm has been extended to consider measurement noise in the agent information. Two possible approaches have been proposed for handling zero-mean Gaussian noise in the agent information.

Advisor: Tomizuka, Masayoshi
Lobbying Behavior: Evidence from Proposed Changes in Lease Accounting

This dissertation examines the motivations that lead some firms to lobby against the proposed change in accounting for leases. There are at least three distinct motivations for a company to lobby against the proposed change: a high perceived cost of implementation, a belief that the change will increase the cost of capital, and the/nmanagement's desire to avoid incurring any personal costs associated with the change (i.e. an increase in workload). My research suggests that companies that engage in lobbying are concerned with the costs of implementing such changes (renegotiation of debt covenants, an increase in auditor fees, the replacement of IT systems, etc.), but companies also seem to be motivated by the desire of accounting managers to avoid any additional eort that the change would require.

Advisor: Dechow, Patricia
The Holographic Principle and the Emergence of Spacetime

Results within string theory and quantum gravity suggest that spacetime is not fundamental but rather emergent, with the fundamental degrees of freedom living on a boundary surface of one lower dimension than the bulk. This thesis is devoted to studying the holographic principle and its realization for spacetimes with both negative and positive cosmological constant./nThe holographic principle is most explicitly realized in the context of the AdS/CFT correspondence. We examine the extent to which AdS/CFT realizes the holographic principle and study the UV/IR relation. We study aspects of how bulk locality emerges within AdS/CFT. To this effect, we study how to reconstruct the bulk from boundary data. We study how such a reconstruction procedure is sensitive to large changes in the bulk geometry. We study if it is possible to reconstruct a subset of the bulk from a subset of the boundary data. We explore both local and nonlocal CFT quantities as probes of the bulk. One nonlocal quantity is entanglement entropy, and to this effect we construct a framework for computing entanglement entropy within the field theory./nThe most ambitious application of the holographic principle would be finding the holographic dual to the multiverse. We investigate properties of this putative duality. We extend the UV/IR relation of AdS/CFT to the multiverse, with the UV cutoff of the theory on future infinity being dual to a late time cutoff (measure) in the bulk. We compare various measure proposals and examine their predictions.

Advisor: Bousso, Raphael
First Principles Exploration of Molecular Excited States at Interfaces

Highly structured nanomaterials offer promise to revolutionize numerous areas of energy conversion technology. Many of the best designs are hybrid systems involving mixed domains of organic materials, organic/inorganic contacts, and important energy transfers between these different materials. While much attention has focused on 10's of nm length scale structuring of these systems, the actual atomistic detail of the interfaces between molecules and between molecules and inorganic interfaces is also important. In this dissertation we explore the excited states of molecules and the changes in these states at interfaces with a range of ab initio theoretical methods. We examine the accuracy of both high level theory and efficient approximations in the treatment of interfacial and environmental effects. Additionally we draw initial design guidance for further applications in nanoscience from our results. Specifically we consider the electron addition and removal energies of small molecules, a fundamental building block if we want to understand more complex systems, the neutral excitations of small donor/acceptor complexes, the alteration of electron additional and removal energies for molecules bound to semiconductors and their alignment with the semiconductor band edges, and the effect of interfacial driven charging on the vibrational spectrum of a molecule in a metallic single molecule junction.

Advisor: Neaton, Jeffrey B
Head-Gordon, Martin P
Security of Freeway Traffic Systems: A Distributed Optimal Control Approach

This dissertation develops a general, scalable framework for controlling dynamical, networked systems based on mathematical optimization theory, with a strong focus on applications to freeway traffic management. The generality of the framework allows for controllers to consider high-level objectives applied to systems with complex, nonlinear dynamics./nA continuous freeway traffic model and its discretization was developed specifically for onramp metering control. The application serves as the motivating example behind the theory developed subsequently. To apply effective control on such systems, a discrete-adjoint-based model-predictive-control (MPC) approach for controlling networked systems of conservation laws is presented, with explicit derivations for ramp metering applications. Linear scalability of the method with respect to network size and time horizon is derived for the discrete adjoint computations. To enable a more asynchronous control architecture, the dissertation presents a distributed optimization algorithm for dynamical, networked systems. The algorithm allows for a physical network to be partitioned into subnetworks that optimize locally and communicate only with adjacent subnetworks to achieve a globally optimal performance./nWithin the context of the Connected Corridors project associated with UC Berkeley PATH, the developed theory was implemented in a production-level traffic management and simulation environment. Numerical examples applied to the San Diego I15 freeway are presented alongside the theory to motivate the highly practical aspects of the work. Simulations demonstrate the superiority of the MPC approach over existing methods widely used in practice./nThe optimization tools are applied to an investigation of security and vulnerabilities of traffic control systems. The potential impact of a compromise of freeway traffic metering lights is analyzed using MPC and multi-objective optimization tools. Several realizable scenarios that exploit traffic system vulnerability locations are constructed and simulated to illustrate the severity of compromises./nInvestigations are made into optimal rerouting strategies while controlling only a subset of network flow. A novel behavioral model is developed to account for the interaction of controllable and uncontrollable agents sharing a single flow network, where latency is a function of total flow. Using static freeway traffic models and communication network models, a framework based on convex optimization techniques is presented for computing rerouting policies, with numerical examples given for both freeway and communication networks.

Advisor: Bayen, Alexandre M
Effects of Internal Wave-Induced Turbulent Mixing on the Stratified Continental Shelf

This work investigates turbulence related to internal waves occurring in shallow, temperature-stratified coastal regions. Motivation for this work comes from two sources: first, a need to extend expensive and logistically taxing turbulent observations to longer time periods using in-situ continuous measurements, and second, a specific need for cross-disciplinary communication about physical-biological interactions important for understanding the global carbon budget. We find that internal waves contribute a significant amount of energy to mixing on the inner shelf of Monterey Bay, as well as in the subsurface thermocline over deep waters in the Southern California Bight./nChapter one provides context for these two problems. Chapter two derives a scaling for the turbulent kinetic energy dissipation rate (epsilon), an indicator of turbulent activity, based on continuous measurements of velocity; dissipation rate is found to scale with shear, S2. This scaling allows us to extend a small number of dissipation rate measurements to describe mixing over time using moored velocity data./nChapter three explores the concept of water column stability in the presence of internal waves, deriving a scaling factor for determining when a stability threshold is reached. Moored density data and derived isopycnal spacing are used as a proxy for stabilizing and destabilizing effects of passing waves. The change in spacing between isopycnals, h', is found to scale the gradient Richardson number through a factor we define as delRi = (1+h')3. When this factor is smaller than unity, the stability is decreased as a wave passes through; if greater, stability is increased. Regions of low delRi are found to occur within and at the edges of the thermocline as internal waves pass. This factor can be derived using moored density data alone./nChapter four explores variation in vertical diffusivity of density across the water column, and indicates the necessity of a varying profile within coastal diffusion models. High diffusivity occurs as expected within the surface and bottom boundary layers, but also at the edges of the thermocline./nChapter five addresses the effect of internal wave-induced turbulence on subsurface phytoplankton layers, focusing on flocculation effects to describe a potential source of large, negatively buoyant aggregates found far below the surface. Turbulent theory is integrated with biological production to suggest a background level of internal wave-induced turbulence may in fact be an important flocculation mechanism. Dissipation within a subsurface mixed layer is sufficient to cause aggregation but not shearing of particles. Internal waves inject energy into the mixed layer slowly but consistently, maintaining aggregation processes. As aggregates settle, they pass through the highly energetic thermocline; the intermittent nature of internal wave-induced shear allows the largest particles to pass through.

Advisor: Stacey, Mark T
Control Theoretic Approach for Attitude Control of High Altitude Scientific Stationary Platforms

Scientific exploration of near-earth space and high altitudes within earth's atmosphere greatly enhance our knowledge of how the earth functions and how it interacts with the sun. These missions have the platforms and need the controller to achieve the specific attitude necessary with limited sensors and actuators. This dissertation introduces the dynamics of the scientific platforms with suitable control rules under various environments and constraints./nThree kinds of science platforms are discussed here: (1) the spin rate and the attitude control of a rigid body, (2) the strategy for the stabilization and the modeling of a multibody system in the space, and(3) the pointing control of a multibody system at the stratosphere. This dissertation also provides the designs and verification procedures for the control software in the embedded system. The simulations and experiments are presented to verify the performance of the attitude controllers.

Advisor: Auslander, David M
Imaging Sleep-Wake Activity in Identified Pontine Cell Populations

An animal's level of arousal transitions rapidly and repeatedly over the course of a day, corresponding with changes in global patterns of neural activity. Decades of research have identified distinct brain regions responsible for the induction and maintenance of sleep and wake states but it has been difficult to determine the precise role of specific neuronal subtypes within these regions. The laterodorsal tegmental nucleus (LDT) in the brainstem is one of the structures important for the induction and maintenance of both rapid eye movement (REM) sleep and wakefulness, and is comprised of multiple, intermingled cell types. In order to characterize the brain state-specific activity of identified neurons in this region, we transfected GABAergic or glutamatergic neurons with the calcium indicator GCaMP6s. We then imaged their activity using a microendoscope and head mountable fluorescence microscope in the feely moving mouse as it transitioned naturally through the sleep wake cycle. This technique allowed us to monitor the activity of multiple cells simultaneously and define their state specific-activity patterns. The populations of both GABAergic and glutamatergic neurons had heterogeneous response properties, but were primarily active during periods of REM, wakefulness or both. Furthermore, changes in the activity of these neurons anticipate transitions in global brain state and the pattern of activation varies depending on the cell's position within the LDT. These results indicate that different cell types within the LDT are modulated by the sleep-wake cycle and may have distinct roles in the regulation of brain state.

Advisor: Dan, Yang