VictorJuiz/thesis huggingface dataset:
Controllers for an Autonomous Vehicle Treating Uncertainties as Deterministic Values

This thesis presents disturbance estimators and controllers for autonomous vehicles. In particular,/nit focuses on a longitudinal distance controller and a lateral lane keeping controller./nFirst, in order to estimate road bank angle as a disturbance term in the lane keeping controller,/na kinematic relationship between road shape and sensor measurements was proposed./nUtilizing longitudinal and lateral vehicle dynamics, longitudinal road gradient and lateral/nroad bank angle were estimated simultaneously using the Unscented Kalman Filter (UKF)/napproach. Second, a lane keeping controller associated with the road bank angle estimator/nwas proposed. For the controller, a steady state dynamic vehicle model was derived to/ndescribe lateral vehicle dynamics. A Receding Horizon Sliding Control (RHSC) approach/nwas implemented to guarantee simple formulation and easy constraint consideration for the/nreceding horizon technique./nFor the longitudinal control systems, the front vehicle's future motion was considered as a/ndisturbance term in a longitudinal distance controller for the ego vehicle. To predict the motion,/na new car-following model was proposed. To extract the current front vehicle driver's/ndriving style, a driver aggressivity factor was derived and estimated in real-time through the/nUKF approach. Adopting a base car-following model and an aggressivity factor estimator on/nthe front vehicle, the front vehicle's future motion sequence was propagated. Furthermore,/nas a distance controller associated with the front vehicle's future motion, a Fuel Eciency/nAdaptive Cruise Control (ACC) was presented. A new fuel consumption model was included/nin the optimization problem in order to improve fuel eciency. The nonlinear Model Predictive/nControl approach was applied to the controller, and the front vehicle's future motion/nwas considered in the prediction horizon./nTwo disturbance estimators for longitudinal and lateral motion were veried under simulation/nand real vehicle tests in real-time. The lane keeping controller was proven to have/nbetter performance with the bank angle estimator on public roads. Furthermore, for a distance/ncontroller, fuel economy using a Fuel Eciency ACC has been veried in simulation.

Advisor: Hedrick, Karl
Mechanism of CRISPR–Cas Immunological Memory

Immunological memory, defined as the ability for cells to rapidly respond to previously encountered pathogens, has long been thought to be present solely in eukaryotes. Recently, it was discovered that bacteria and archaea also possess analogous adaptive immune systems called CRISPR–Cas (clustered regularly interspaced short palindromic repeats–CRISPR associated). CRISPRs are distinct genomic loci comprising of repeating 20-50 base pair (bp) sequences that are separated by foreign DNA-derived segments called spacers. Upon viral infection, a ~30 bp fragment of the foreign DNA is acquired into the CRISPR locus as a new spacer, serving as a molecular memory of that specific infection. The CRISPR RNA (crRNA) products of CRISPR loci are used as guides by Cas proteins to silence infectious foreign genetic elements containing sequence complementarity to the crRNA. The research presented in this dissertation elucidates the mechanisms underlying spacer acquisition during CRISPR immunity./nCas1 and Cas2, the only universally conserved Cas proteins present in CRISPR-harboring organisms, are sufficient to elicit spacer acquisition in E. coli. Using a combination of biochemical, bacterial genetics and X-ray crystallography experiments, we reveal the requirement of Cas1 and Cas2 to associate as a protein complex during CRISPR immunity. Cas1 is the catalytic subunit, whereas Cas2 functions as a scaffold within the complex. By determining crystal structures of Cas1–Cas2 bound to a 33 bp DNA from M13 bacteriophage, we uncover Cas1–Cas2 as a molecular ruler that precisely measures the foreign DNA across the entire complex with each DNA end terminating in the catalytic Cas1 active sites. Collectively, our structural data uncover how Cas1–Cas2 captures, measures and prepares foreign DNA for insertion into the CRISPR locus./nA hallmark of CRISPR immunological memory is the addition of foreign DNA spacers into CRISPR loci. By developing an in vitro assay to study spacer acquisition, we reveal that purified Cas1–Cas2 can be loaded with 18-50 bp spacer DNA for integration into a plasmid encoding the CRISPR locus. Cas1–Cas2 integrates spacers adjacent to the CRISPR repeats via a nucleophilic reaction of the DNA 3'–OH ends into the target DNA, in a mechanism similar to many retroviral integrases and transposases. Furthermore, the integration host factor (IHF) protein in E. coli binds the CRISPR leader to induce sufficient DNA bending required for the integration reaction, explaining the mechanistic basis for leader-proximal spacer acquisition observed in vivo. Together, these in vitro assays fully recapitulate immunological memory during prokaryotic CRISPR immunity.

Advisor: Doudna, Jennifer A
Distributed Machine Learning with Communication Constraints

Distributed machine learning bridges the traditional fields of distributed systems and machine learning, nurturing a rich family of research problems. Classical machine learning algorithms process the data by a single-thread procedure, but as the scale of the dataset and the complexity of the models grow rapidly, it becomes prohibitively slow to process on a single machine. The usage of distributed computing involves several fundamental trade-offs. On one hand, the computation time is reduced by allocating the data to multiple computing nodes. But since the algorithm is parallelized, there are compromises in terms of accuracy and communication cost. Such trade-offs puts our interests in the intersection of multiple areas, including statistical theory, communication complexity theory, information theory and optimization theory./nIn this thesis, we explore theoretical foundations of distributed machine learning under communication constraints. We study the trade-offs between communication and computation, as well as the trade-off between communication and learning accuracy. In particular settings, we are able to design algorithms that don't compromise on either side. We also establish fundamental limits that apply to all distributed algorithms. In more detail, this thesis makes the following contributions:/n* We propose communication-efficient algorithms for statistical optimization. These algorithms achieve the best possible statistical accuracy and suffer the least possible computation overhead./n* We extend the same algorithmic idea to non-parametric regression, proposing an algorithm which also guarantees the optimal statistical rate and superlinearly reduces the computation time./n* In the general setting of regularized empirical risk minimization, we propose a distributed optimization algorithm whose communication cost is independent of the data size, and is only weakly dependent on the number of machines./n* We establish lower bounds on the communication complexity of statistical estimation and linear algebraic operations. These lower bounds characterize the fundamental limits of any distributed algorithm./n* We design and implement a general framework for parallelizing sequential algorithms. The framework consists of a programming interface and an execution engine. The programming interface allows machine learning experts to implement the algorithm without concerning any detail about the distributed system. The execution engine automatically parallelizes the algorithm in a communication-efficient manner.

Advisor: Jordan, Michael I
Wainwright, Martin J
Smartphone-based assessment of food environment, diet and obesity risk

300 million adults and 16 million children in China are now obese. The rapid economic development, urbanization and associated environmental changes occurring in China are thought to be responsible for this growing obesity epidemic. My dissertation research has gradually developed into four interconnected parts which are presented in Chapter 1, 2, 3 and future work. First (Chapter 1), culturally specific food environment survey instruments were developed and used to document the longitudinal changes in food availability in six representative neighborhoods in Kunming via field audits. Second (Chapter 2), to pilot test our integrated methodology, a 12-person cohort was recruited in Kunming, and individual dietary behavior was modeled and topologies were proposed. Third (Chapter 3), to further test our methodology on a larger cohort aiming to examine the relationship between food environment and sugar-sweetened beverage consumption, we worked with Carolina Population Center on their China Beverage Validation Study in urban and rural Shanghai. Lastly (future work), to examine the health impacts of the changing food environment, a 300 adolescent cohort was recruited from two high schools in Kunming, and followed for two years. Their dietary, physical activity, mental, social and physical changes were assessed via traditional research surveys, smartphone-based activity tracking and Internet datamining. Preliminary results on the cohort’s BMIs are presented.

Advisor: Spear, Robert
Seto, Edmund
Mechanistic Studies of the Rho Helicase

All cellular organisms rely on transcriptional regulatory mechanisms to control the levels and timing of gene expression. Bacterial transcription is in part regulated by Rho, a RecA-family hexameric helicase that utilizes an ATP-dependent 5’→3’ translocation mechanism to terminate synthesis of specific RNA transcripts. Rho is initially recruited to pyrimidine-rich transcripts in an open-ring, loading-competent configuration, and subsequently traps the RNA within Rho’s central pore by transitioning to a closed-ring and catalytically active conformation. Using small-angle X-ray scattering and a novel fluorescence-based assay to monitor Rho’s conformational state in vitro, I discovered that bicyclomycin, a known small molecule inhibitor of Rho, acts by sterically blocking isomerization of Rho into its closed-ring form. Conversely, I also demonstrated that two distinct Rho effectors – pyrimidine-rich nucleic acids (as are found in favored RNA elements) and the transcription factor NusG – directly promote Rho ring closure. To better understand how NusG modulates Rho activity, I determined a crystal structure of closed-ring Rho in complex with the NusG C-terminal domain. This structure reveals that NusG engages the C-terminal face of Rho’s motor domains. Modeling of a Rho/NusG/RNAP complex based on the structure suggests that NusG may position Rho near the RNA exit channel of RNA polymerase to aid in the capture of non-ideal RNAs. Collectively, these findings delineate how a diverse set of ligands regulate bacterial transcription termination, and demonstrate how the conformational state of a hexameric helicase can be controlled by disparate classes of factors.

Advisor: Berger, James
Rio, Donald
Signaling and Morphogenesis of the Ascidian Neural Tube

Formation of the vertebrate neural tube represents one of the premier examples of morphogenesis in animal development. Here, we investigate this process in the simple chordate, Ciona intestinalis. Previous studies have implicated Nodal and FGF signals in the specification of lateral and ventral neural progenitors. We show that these signals also control the detailed cellular behaviors underlying morphogenesis of the neural tube. Live imaging experiments show that FGF controls the intercalary movements of ventral neural progenitors, while Nodal is essential for the characteristic stacking behavior of lateral cells. Ectopic activation of FGF signaling is sufficient to induce intercalary behaviors in cells that have not received Nodal. In the absence of FGF and Nodal, neural progenitors exhibit a default behavior of sequential cell divisions, and fail to undergo the intercalary and stacking behaviors essential for normal morphogenesis. Thus, cell specification events occurring prior to completion of gastrulation coordinate morphogenetic movements underlying the organization of the neural tube.

Advisor: Levine, Michael S
Mapping and manipulating optoelectronic processes in emerging photovoltaic materials

The goal of the work in this dissertation is to understand and overcome the limiting optoelectronic processes in emerging second generation photovoltaic devices. There is an urgent need to mitigate global climate change by reducing greenhouse gas emissions. Renewable energy from photovoltaics has great potential to reduce emissions if the energy to manufacture the solar cell is much lower than the energy the solar cell generates. Two emerging thin film solar cell materials, organic semiconductors and hybrid organic-inorganic perovskites, meet this requirement because the active layers are processed at low temperatures, e.g. 150 °C. Other advantages of these two classes of materials include solution processability, composted of abundant materials, strongly light absorbing, highly tunable bandgaps, and low cost./nOrganic solar cells have evolved significantly from 1% efficient devices in 1989 to 11% efficient devices today. Although organic semiconductors are highly tunable and inexpensive, the main challenges to overcome are the large exciton binding energies and poor understanding of exciton dynamics. In my thesis, I optimized solar cells based on three new solution processable azadipyrromethene-based small molecules. I used the highest performing molecule to study the effect of increasing the permittivity of the material by incorporating a high permittivity small molecule into the active layer. The studies on two model systems, small donor molecules and a polymer-fullerene bulk heterojunction, show that Frenkel and charge transfer exciton binding energies can be manipulated by controlling permittivity, which impacts the solar cell efficiency./nHybrid organic-inorganic perovskite materials have similar advantages to organic semiconductors, but they are not excitonic, which is an added advantage for these materials. Although photovoltaics based on hybrid halide perovskite materials have exceeded 20% efficiency in only a few years of optimization, the loss mechanisms are not understood but critical to systematically improve the efficiency towards the theoretical limit. Thus, I correlated morphology to local power conversion efficiency determining properties by mapping local short circuit current, open circuit voltage, and dark drift current in state-of-the-art methylammonium lead iodide solar cells with sub-30 nm spatial resolution using photoconductive atomic force microscopy. I found, within individual grains, spatially-correlated heterogeneity in short circuit current and open circuit voltage. This heterogeneity is attributed to a facet-dependent density of trap states. These results imply that controlling crystal grain and facet orientation will enable a systematic optimization of hybrid halide perovskite photovoltaics.

Advisor: Weber-Bargioni, Alexander
Xu, Ting
Experiments to Improve Nuclear Data for High Energy Density Environments

The work presented in this dissertation used a variety of facilities and methods to make precise measurements of neutron reaction cross sections and γ-ray branching ratios important for the study of high energy density environments. While measurements related to thulium used commercially available detectors, others required the development of a new detection/nsystem. A 4π gas proportional beta counter was designed and characterized specifically for the measurement of fission product branching ratios. Measurements of increasing precision were performed for 147 Nd and 95 Zr. The instrumentation and techniques developed in this dissertation have set the path for an ongoing series of fission product branching ratio measurements. With work towards refinements mentioned here, precision will continue to improve in the measurements and results of future studies with these devices.

Advisor: Norman, Eric B
Integrated 4H-Silicon Carbide Diodes and Bridge Circuits for Harsh Environment Applications

High temperature electronics, micro-electro-mechanical systems (MEMS) and sensors that are able to operate between 300°C to 600°C have broad applications in harsh environments such as oil/gas exploration, geothermal development, industrial manufacturing processes, and space exploration. 4H-silicon carbide (SiC) is a good material for harsh environment applications because of its wide bandgap, high carrier mobilities, excellent thermal and chemical stabilities, and high breakdown electric field strength. Several 4H-SiC devices and integrated circuits have been studied in this work, including p-n diodes, p-n diode temperature sensors, bridge rectifiers, and bridge circuits for differential capacitive pressure sensors./n4H SiC p-n diodes from room temperature to 600°C have been demonstrated with theoretical study, simulation, fabrication, and characterization. The fabricated 4H-SiC p-n diodes show turn on voltages from 2.6 V to 1.3 V which match well with the technology computer-aided design (TCAD) simulation results from 2.7 V to 1.45 V when temperature increases from 17°C to 600°C./nPlanar-integrated 4H-SiC diode bridge rectifier circuits are analyzed, simulated by SPICE (Simulation Program with Integrated Circuit Emphasis), fabricated and characterized. Experimentally, fabricated rectifiers are functional up to 500°C with voltage conversion efficiencies of 73.6% at room temperature and 89.1% at 500°C./nHigh-performance temperature sensors from 17°C to 600°C by using circular-shape 4H-SiC p-n diodes are analyzed, simulated by TCAD Sentaurus, fabricated and tested. The 4H-SiC p-n diode temperature sensors achieve high sensitivities of 2.9 mV/°C at 0.1 μA and 4.7 mV/°C at 1 mA in a wide temperature range from 17°C to 600°C./nFinally, planar integrated 4H-SiC diode bridge circuits for differential capacitive pressure sensor transduction are investigated. The working principle of the transduction circuit is derived. The circuit is simulated by SPICE, fabricated and tested with a sensitivity of 9.3 mV/pF at 1 MHz and a 3dB cut-off frequency of 2.5 MHz./nThese results show great potential for 4H-SiC devices and circuits working in harsh environment electronics, MEMS and sensing applications.

Advisor: Pisano, Albert P.
Lin, Liwei
End-to-End Large Scale Machine Learning with KeystoneML

The rise of data center computing and Internet-connected devices has led to an unparalleled explosion in the volumes of data collected across a multitude of industries and academic disciplines./nThis data serves as fuel for statistical machine learning techniques that in turn enable some of today's most advanced applications including those powered by image classification, speech recognition, and natural language understanding, which we broadly term machine learning applications./nUnfortunately, until recently the tools and techniques used to leverage recent advances in machine learning at the scales demanded by modern datasets, and thus develop these applications, have been available only to experts in fields such as distributed computing, statistics, and optimization./nI describe my efforts to render these tools accessible to a broader audience of application developers, and further demonstrate that by taking a holistic approach and capturing end-to-end high level specifications of machine learning applications the systems I present here can make novel, high impact optimizations to decrease resource consumption while simultaneously increasing throughput. These improvements are designed to decrease ML application development time, increase quality, and increase machine learning application developer productivity./nI demonstrate the viability of these optimizations via experiments on a number of real-world applications in domains such as collaborative filtering, computer vision, and natural language processing./nMany of the ideas presented in this thesis have already had practical impact as embodied in the open source software packages KeystoneML and Apache Spark MLlib.

Advisor: Franklin, Michael J
Essays on Behavioral and Experimental Game Theory

This dissertation consists of three chapters, which study the identification of people's reasoning abilities and belief levels in strategic interactions. The first chapter examines the methodology to identify subjects' reasoning levels in the ring games proposed by Kneeland (2015). In the second chapter, an experiment is designed to identify whether it is limited reasoning ability or incorrect belief that prevents people from playing equilibrium strategies. The experiment builds on a series of ring games similar to the ones analyzed in Chapter 1. The third chapter links people's performance in games to a measure of their cognitive ability, which also validates the findings in Chapter 2./nThe ring games are first used by Kneeland (2015) to separate different orders of belief in rationality. Her experiment finds rationality levels higher than those in the literature. The first chapter points out two features in the ring games used by Kneeland (2015) that could potentially bias type classification, and reports the experimental results using two new sets of games with these features removed. Similar type distribution as seen in Kneeland (2015) is reproduced when the rows with the largest sums in the payoff matrices do not coincide with the equilibrium strategies. However, when some rows that have the lowest sums and contain zeros are set to be the best responses, a considerably larger fraction of low types are found. Additionally, the deviation rates from the theoretical prediction are higher in my data, partly due to the lesser performance of the identifying assumption./nThe second chapter reports an experiment to identify the decisive factor that prevents people from using more depth of reasoning: their incorrect belief of others' rationality or their limited reasoning ability. The analysis first classifies subjects into different Lk types by the reasoning steps they use in the games. It then distinguishes between the "Lkb" players, who have high ability and best respond to Lk belief, and the "Lka" players, who could use, at most, k steps of reasoning, and thus could not respond to L(k+1) or higher-order belief. The separation utilizes a combination of simultaneous and sequential ring games. In the sequential games it requires more than k reasoning steps to respond to Lk belief, so Lkb players still best respond but Lka would fail. I find that around half of the L2 and L3 subjects are best responding to L2 or L3 belief, while the rest have reached their upper boundaries of reasoning. The findings suggest that both belief and reasoning ability could be the decisive factors of players' observed levels./nThe third chapter finds positive relationship between the Cognitive Reflection Test (CRT) scores, an indicator of cognitive ability, and the reasoning levels in the ring games in Chapter 2. The CRT scores increase with levels among the lower types (from L0 to L2b), and but do not differ significantly from L2b to L4. Striking difference is found between the CRT scores of L2a and L2b subjects, which suggests that cognitive ability are strongly related to reasoning skills.

Advisor: Kariv, Shachar