VictorJuiz/thesis huggingface dataset:
Re-configurable Swarm of Unmanned Underwater Vehicles for Underwater Wireless Optical Networks

This dissertation addresses fundamental aspects of re-configurable swarms of Unmanned Underwater Vehicles (UUVs) for Underwater Wireless Optical Networks (UWONs) at different scales. At the scale of the swarm, we propose Guidance, Navigation and Control (GNC) systems to enable permanent UWONs. At the scale of the UUV, we present the development of a man-portable hybrid UUV with high-bandwidth wireless communication. Finally, we investigate, at the scale of the Free-Space Optical (FSO) system, Pointing, Acquisition and Tracking (PAT) systems to enable free-space laser communication. This dissertation begins with the report of a demonstration of underwater laser beam relay with two UUVs to illustrate the concept of swarms of UUVs for UWONs. Specifically, two submarine models were modified, localized and controlled to reflect the laser beam stemming from a laser pointer at the bottom of a water tank to the desired location. In the second part of this dissertation, we show that a guidance system combining Decentralized Model Predictive Control with graph theory enables to steer UUVs such that there is continuously a path through the UUV network to relay the optical signal for an unlimited time by re-configuring successive subfleets where a UUV is always within communication range with the neighbouring subfleets. The guidance system forms the high-level block of a hierarchical control scheme with an Adaptive Feedback Linearization Controller (AFLC) and an Extended Kalman Filter (EKF) at the low-level. In the third part of this dissertation, we present a man-portable hybrid UUV equipped with a LED modem on a Pan-Tilt system enabling 3.5Mbps full-duplex wireless communication over a range of 7m in a wave tank despite the motion of the UUV. The hybrid capabilities of the UUV have been simulated with a Software in the Loop (SITL) simulator, which showed the good performance of the AFLC and EKF implemented in the UUV's autopilot. Finally, the fourth part of this dissertation investigates two PAT systems with different configurations. The first configuration enables full PAT capabilities but requires precise alignment and calibration of the opto-mechanical components while a second configuration enables only tracking but has lower manufacturing requirements.

Advisor: Alam, Mohammad-Reza
On the Construction of a Novel Mean Field Platform and Broadly Applicable Variational Principle Methods for Electronically Excited States

Electronic structure theory is an evolving field with abounding potential applications to a multitude of interesting systems, including atoms and molecules in electronically excited states. Central to this dissertation are two critical components of excited state electronic structure methods – the ansatzes that describe a system’s electronic configuration and the algorithms used to optimize them. In this thesis, advancements on both fronts are presented. To contextualize this new work, several prominent excited state ansatzes and optimization methods are reviewed, and their performances in applications to DNA photophysics and organic photovoltaics are examined. The strengths and weakness of the existing ansatzes inspired the construction of a flexible, computationally affordable excited state mean field wave function that is analogous to ground state mean field theory. This qualitatively accurate, state-specific ansatz provides the foundation upon which higher accuracy correlation methods are built that rival the accuracy of existing excited state theories at lower overall cost scaling. Further developments detailed in this thesis occur on the optimization side of electronic structure methods and relate to excited state variational principles. First, a novel analysis on the lack of size consistency within a class of excited state variational principles widely used in stochastic quantum chemistry methods is presented. A unique algorithm that transforms between variational principles on the fly while rigorously maintaining size consistency and state specificity is shown to eliminate this optimization-induced source of error. Finally, a generalized variational principle that guarantees state specificity via a unique global minimum and identifies electronic states based on a list of user-specified properties is defined, and its ability to resolve even energetically degenerate states in dense excitation manifolds is realized. From the construction of a novel mean field excited state wave function, to the analysis and restoration of size consistency in a class of excited state variational principles, to the development of a generalized variational principle, the research herein constitutes significant steps towards more robust, efficient, and accurate modelling of electronically excited states.

Advisor: Neuscamman, Eric
The Breathing of Halogenated Volatile Organic Compounds (HVOCs) from Human-impacted Ecosystems

Atmospheric methyl chloride (CH3Cl) and methyl bromide (CH3Br) are the largest natural gaseous carriers of reactive chlorine and bromine, which contribute to stratospheric ozone depletion. Chloroform (CHCl3) also contributes to total stratospheric chlorine load and ozone destruction, with a much smaller impact. This dissertation investigates and quantifies emissions of these halogenated volatile organic compounds (HVOCs) from some natural ecosystems impacted by human activities.Chapter two describes a study on HVOCs flux measurements at an intermediate zone of coastal ecosystems in South Carolina, which are subject to seawater intrusion induced by storm surges combined with sea level rise. The degraded forested wetland showed significant CHCl3 emission rates and remained a net CH3Cl sink and a negligible CH3Br source/sink, unlike the saltmarsh which was a significant source for both. This study suggested that sea level rise and frequent storm surges derived from global climate change, in the long term, may increase CHCl3 emissions from coastal degraded forested wetlands and of methyl halides if salt marshes expand, with potential impacts for stratospheric ozone depletion. Chapter three describes a project that measured life-cycle fluxes of CH3Cl, CH3Br and CH3I from rapeseed (Brassica napus “Empire”). The results showed that rapeseed emitted 5.3 ± 1.3 Gg CH3Cl year−1, 2.8 ± 0.7 Gg CH3Br year−1, and 4.0 ± 0.8 Gg CH3I year−1 as of 2018. Assuming the future global rapeseed production follows the same rate of increase as the past 60 years, the atmospheric sources of CH3Cl, CH3Br and CH3I may increase to 13.1 Gg year-1, 7.0 Gg year-1, and 9.8 Gg year-1, respectively by 2050, becoming an ever-larger global source. Chapter four describes a study which showed that CuSO4, in conjunction with either hydrogen peroxide (H2O2) or solar radiation, significantly enhanced CH3Cl and CH3Br production from organic matter in soil or seawater. This study identified a new abiotic pathway of methyl halide production occurring in agricultural fields and water bodies facilitated by the widespread application of Cu (II) based pesticides, herbicides and fungicides. A rough quantification suggested this mechanism had the potential to account for a significant part of the missing sources of CH3Cl and CH3Br. These aforementioned studies highlight the increasing contribution from natural sources of ozone depleting substances (ODSs) influenced by human activities, which may offset some of the ODSs reductions achieved by the Montreal Protocol.

Advisor: Rhew, Robert RCR
An investigation into the rates and processes affecting the atmospheric deposition of organic nitrates and the broader role of deposition in the NOx cycle

Alkyl and multifunctional nitrates (RONO2) and peroxynitrates (RO2NO2) influence the atmosphere through their role in sequestering or recycling atmospheric NO and NO2 (ie. NOx). This effect modulates the production of tropospheric ozone (O3), which has consequences for human and ecosystem health. The chemical processing of RONO2, RO2NO2, and NOx typically leads to the recycling of NOx, which in most environments leads to higher ozone production. The deposition of these nitrogen oxide compounds, however, leads to the permanent loss of these compounds from the atmosphere. Recent results have indicated that nitrogen oxides can deposit rapidly from the atmosphere, but the rates, mechanisms, and properties that influence deposition are not well understood. Further, an understanding of the impact of nitrogen oxide deposition on the lifetime of nitrogen oxides as well as its role in the NOx cycle is needed./nLaboratory chamber experiments were run using a variety of RONO2 and RO2NO2 compounds and tree species to gain insight into the leaf-level processes driving organic nitrate deposition to vegetation. These experiments revealed that the deposition of RONO2 and RO2NO2 occurred solely through leaf stomatal uptake. The deposition of RO2NO2 was found to scale linearly with stomatal conductance. The deposition of RONO2 did not scale with stomatal conductance and the deposition rates differed for each RONO2 compound tested. The rates of uptake observed for all RONO2 and RO2NO2 studied were too fast to be explained through a dissolution and hydrolysis mechanism within the leaf, suggesting uptake via an alternative mechanism. Scaling the observed RO2NO2 deposition rates to the canopy-level indicated that the deposition of these organic nitrates from the atmosphere could compete with their thermochemical losses. Scaled canopy deposition rates for RONO2 led to the conclusion that deposition was unlikely to be an important atmospheric loss of these compounds./nIn parallel with these laboratory experiments, a remote sensing canopy conductance model was developed to estimate the stomatal uptake of atmospheric nitrogen oxides on a regional scale. The model was shown to accurately capture real-time canopy stomatal conductance diffusion rates across the continental United States using satellite retrievals of solar-induced fluorescence. The model was able to successfully reproduce the spatial distribution of nitrogen oxide fluxes that were estimated from leading chemical transport models. A key advantage of the canopy conductance model was its ability to capture real changes in deposition over the growing season driven by environmental factors such as drought. The canopy conductance model was used to estimate the lifetime of PAN and NO2 over the USA and indicated that the lifetime to deposition of these compounds was shortest in heavily forested coastal regions.

Advisor: Cohen, Ronald C
Acquiring Motor Skills Through Motion Imitation and Reinforcement Learning

Humans are capable of performing awe-inspiring feats of agility by drawing from a vast repertoire of diverse and sophisticated motor skills. This dynamism is in sharp contrast to the narrowly specialized and rigid behaviors commonly exhibited by artificial agents in both simulated and real-world domains. How can we create agents that are able to replicate the agility, versatility, and diversity of human motor behaviors? Manually constructing controllers for such motor skills often involves a lengthy and labor-intensive development process, which needs to be repeated for each skill. Reinforcement learning has the potential to automate much of this development process, but designing reward functions that elicit the desired behaviors from a learning algorithm can itself involve a laborious and skill-specific tuning process. In this thesis, we present motion imitation techniques that enable agents to learn large repertoires of highly dynamic and athletic behaviors by mimicking demonstrations. Instead of designing controllers or reward functions for each skill of interest, the agent need only be provided with a few example motion clips of the desired skill, and our framework can then synthesize a controller that closely replicates the target behavior./nWe begin by presenting a motion imitation framework that enables simulated agents to imitate complex behaviors from reference motion clips, ranging from common locomotion skills such as walking and running, to more athletic behaviors such as acrobatics and martial arts. The agents learn to produce robust and life-like behaviors that are nearly indistinguishable in appearance from motions recorded from real-life actors. We then develop models that can reuse and compose skills learned through motion imitation to tackle challenging downstream tasks. In addition to developing controllers for simulated agents, our approach can also synthesize controllers for robots operating in the real world. We demonstrate the effectiveness of our approach by developing controllers for a large variety of agile locomotion skills for bipedal and quadrupedal robots.

Advisor: Levine, Sergey
Abbeel, Pieter
Safety Methods for Robotic Systems

Recently there have been vast interests in introducing robotic systems such as autonomous cars and UAVs into the real world. Ensuring the safety of these systems when they are deployed is thus a highly crucial and urgent problem. Safety problems can arise from various different settings such as when there are multiple vehicles or human-operated vehicles in the environment. Different safety-critical settings often require different approaches for addressing the safety of vehicles. In this dissertation, we contribute novel methods for safety problems that arise from three different scenarios./nFirst, we have seen a surge of interests in deploying autonomous vehicles into the everyday lives of people. Developing accurate and generalizable algorithms for modeling and predicting human behavior thus becomes important. We present a method for generating the probabilistic forward reachable set of a human-controlled vehicle in an environment where a robot is operating in close proximity to the human-controlled vehicle./nSecond, motivated by the recent advances in deploying unmanned aerial vehicles into the airspace, we tackle the problem of multi-vehicle safety. We first contribute a planning and control strategy for guaranteeing safety of multiple vehicles while vehicles complete their objectives. We also present an initialization strategy based on machine learning to enhance the safety of multi-vehicle systems when they adopt least-restrictive safety-aware algorithms. Finally, machine learning has emerged as a promising tool to enable robots to accomplish challenging tasks under uncertainty in the dynamics of the robots or the environment. However, the safety of the robot while it's learning online is often not taken into account, which could lead to unsafe behavior of the robot. We present an online learning framework that enables a robot to learn about its dynamics, accomplish a task, and update its safe set simultaneously online.

Advisor: El Ghaoui, Laurent
Halting Progress: Meanings of Kemadjoean in Adinegoro's Asmara Djaja

Abstract/nHalting Progress: Meanings of Kemadjoean in Adinegoro’s Asmara Djaja/nby/nShawn Easton Callanan/nDoctor of Philosophy in Southeast Asian Studies/nUniversity of California, Berkeley/nProfessor Sylvia Tiwon, Chair/n“Kemadjoean” (“progress”) is a key concept in the thinking of the early twentieth century Indonesian writer Adinegoro, particularly in his 1928 novel Asmara Djaja. Kemadjoean is a metaphor of forward movement and implies change. This study aims to explore the effects of kemadjoean as depicted in this novel. To explore the claim of this dissertation, that kemadjoean, despite being a metaphor connoting change and movement, actually inhibits development and begets stasis, I analyze a number of passages in the text via close reading, and in the light of other relevant writings, in order to better understand the implicit and explicit meanings of those passages. In Chapter One, I show how the increasing proliferation of written language and other representations depicted in Asmara Djaja, in the form of handwritten letters, telegrams, newspapers, typewritten letters, and the like, can accentuate the stasis-producing effects of kemadjoean. In Chapter Two, I explore how the increasing bufferedness of interpersonal relationships within kemadjoean can fortify kemadjoean’s stilling effects. One of the most powerful means to bring about this attenuation of relationships is simple physical distance of people from one another, whether that be facilitated by steamships, telegrams, or other technologies. In Chapter Three, I write about the powerful universalizing tendencies of kemadjoean. Associated with this universalization are the prevalence of clock time and clocks that regulate characters’ lives in the novel, and the increasingly anthropologically-inflected ways in which characters at this time are now understanding and explaining their world. In Chapter Four, I discuss the role of the Malay language in kemadjoean. Malay is depicted as a central language, in that it is metaphorically located between its linguistic neighbors, and positioned as the most appropriate linguistic medium, and the one able to best translate and signify for the community Adinegoro portrays in his novel. These readings show the various ways that kemadjoean creates stasis, problematizing the implicit claims inherent in a metaphor of movement, and complicating commonly accepted understandings of kemadjoean. In so doing, these readings help us to better understand some of the forces that shape the context in which this novel was written, and that influence Indonesian writing, language, and life to this day.

Advisor: Tiwon, Sylvia
Generating Diversity and Maintaining Stability in the Nervous System, From Synapses to Behavior

A central question in neuroscience is how synapses are assembled within neuronal circuits to regulate and maintain complex behaviors. These fundamental nodes of information transfer must be malleable yet maintain stability, all within a nervous system of a developing, learning, and behaving animal. In my thesis work, I have sought to help bridge some of these divides between the many scales of the nervous system and disentangle the overwhelming intricacy that lies between molecules at the synapse and emergent behavior. Behavioral variability in animal populations is thought to increase fitness and aid adaptation to environmental change, yet the underlying neural mechanisms are poorly understood. We found that variation between individuals in neuromodulatory input contributes to individuality in short-term habituation of the zebrafish (Danio Rerio) acoustic startle response (ASR). From here, I studied heterogeneity on a different scale and began researching the synaptic diversity of the model system, the Drosophila neuromuscular junction (NMJ). Most electrophysiological studies of the NMJ have ignored the functional differences between its two distinct motor neuron inputs, the Ib and Is, both of which are comprised of hundreds of synapses of varying vesicular release properties. We found that the Ib and Is inputs generate distinct forms of excitatory drive during crawling and differ in key transmission properties. Finally, after a desire to connect the synaptic level of the NMJ to the behavioral level of the larval zebrafish, my most recent work investigates how circuits increase motor neuron output to maintain normal behavior in response to a reduction in synaptic strength at the NMJ. Although diverse in nature, these model systems provide a unique insight into the complex interplay between generating diversity and maintaining stability in the nervous system.

Advisor: Isacoff, Ehud
Exploration of magnetic edge and dopant states in Nanographenes

While the discovery of 2D graphene offered incredible promise for next generation electronics, device fabrication was severely hindered by the semi metallic nature of graphene. Graphene nanoribbons (GNRs) are quasi-1D nanostructures with similar electronic properties to the parent graphene, and the additional benefit of a widely tunable band gap. The ability to modulate the band gap in GNRs makes them particularly promising candidates for high-performance electronic devices. The band gap in these materials is intimately linked to the atomic structure of the GNR and it is essential to understand the connection between electronic structure and various parameters such a width, dopant position/concentration, and edge topology. To determine this relationship, the synthesis of atomically precise GNRs is crucial. Traditional synthetic techniques for GNR synthesis (e.g. lithographic patterning or the unzipping of carbon nanotubes) fail to meet this requirement. Instead, this thesis will focus on bottom-up synthetic techniques where a molecular precursor is sublimed onto a metallic substrate to yield the desired GNR. Moreover, the metallic substrate provides the ideal platform for electronic and atomic structure characterization using Scanned Probe Microscopy (SPM) techniques./nIn this thesis, I will begin by explaining exotic magnetic phenomena that emerge from graphene nanoribbons with zigzag edge topology (Chapter 2). This chapter will discuss all-carbon GNRs and GNRs with nitrogen dopants to ascertain the effect of the dopant atom. Next, I provide information about low band gap GNRs that could be ideal candidates for next generation electronic devices (Chapter 3). Afterwards, I will consider the potential to form Nitrogen bonds with the underlying metallic substrate (Chapter 4). The final chapters in this thesis will take advantage of topological engineering to access low band gap GNRs (Chapter 5) and metallic GNRs (Chapter 6) that can be used to construct high-performance electronic devices entirely from GNRs.

Advisor: Fischer, Felix
Retinal mechanisms shaping neural encoding of motion

Vision is a fundamental component of the human sensory experience. In order to construct visual percepts and mediate appropriate behaviors, the brain uses myriad neural circuits to enact diverse computations and process visual information. Motion is a particularly prevalent feature of the visual world, representations for which are seen through the visual systems of many mammals. By studying neural circuits for motion processing, we gain insights into an important visual information channel utilized by the brain, and thus establish a foothold from which to further understand mechanisms of perception and behavior. The retina in particular provides the opportunity for study of relatively tractable circuits by which to understand how neural signals are integrated in space and time. This work investigates the mechanisms of neural processing within the early visual system. Chapter 1 provides an introduction to motion processing in the retina. This chapter reviews the literature on the diversity of retinal motion detectors which have thus far been catalogued, and discusses what is presently known about their mechanisms of computation. Chapter 2 focuses on a comparative study of two retinal motion detectors in particular: the ON and ON-OFF direction selective ganglion cells. This chapter presents original research findings on the synaptic mechanisms by which these circuits jointly encode the direction and velocity of motion using electrophysiology, pharmacology, genetic knockout animals, and computational modeling. Chapter 3 concludes with a discussion of the computational role of the retina compared to central brain areas, and examines modern physiological findings alongside insights from evolutionary biology, comparative neuroanatomy and theory studies. In sum, the work within this thesis expands our understanding of the mechanisms by which retinal circuits encode motion, and in so doing contributes to our knowledge of how neural signals are integrated by the brain to mediate vision.

Advisor: Feller, Marla B