VictorJuiz/thesis huggingface dataset:
Optimization of a Laser Plasma Accelerator through Pulse Characterization and Controlled Spatiotemporal Coupling

Unlike conventional accelerators, the accelerating structure in a laser plasma accelerator (LPA) is dynamically created by the interaction of a high-peak-power laser pulse with a plasma target. This dynamic nature allows extensive control over the acceleration process but requires detailed knowledge and regulation of the laser, the plasma target, and their interaction. In this thesis, the effect of laser pulse structure, in particular temporal profile and spatiotemporal coupling, on laser plasma acceleration is investigated through theoretical models and experiments at the BErkeley Laboratory Laser Accelerator (BELLA) Center. The temporal profile of the laser and the density profile of the plasma target are probed by laser spectral shifting. A novel model of laser steering and electron beam deflection due to pulse front tilt is developed. The effects of pulse front tilt are measured in experiments and found to be in good agreement with the theoretical model. The application of these results for the optimization of a laser plasma accelerator is discussed.

Advisor: Leemans, Wim P
Shapiro, Marjorie D
Metareasoning and Mental Simulation

At any given moment, the mind needs to decide how to think about what, and for how long. The mind's ability to manage itself is one of the hallmarks of human cognition, and these meta-level questions are crucially important to understanding how cognition is so fluid and flexible across so many situations. In this thesis, I investigate the problem of cognitive resource management by focusing in particular on the domain of mental simulation. Mental simulation is a phenomenon in which people can perceive and manipulate objects and scenes in their imagination in order to make decisions, predictions, and inferences about the world. Importantly, if thinking is computation, then mental simulation is one particular type of computation analogous to having a rich, forward model of the world./nGiven access to such a model as rich and flexible as mental simulation, how should the mind use it? How does the mind infer anything from the outcomes of its simulations? How many resources should be allocated to running which simulations? When should such a rich forward model be used in the first place, in contrast to other types of computation such as heuristics or rules? Understanding the answers to these questions provides broad insight into people's meta-level reasoning because mental simulation is involved in almost every aspect of cognition, including perception, memory, planning, physical reasoning, language, social cognition, problem solving, scientific reasoning, and even creativity. Through a series of behavioral experiments combined with machine learning models, I show how people adaptively use their mental simulations to learn new things about the world; that they choose which simulations to run based on which they think will be more informative; and that they allocate their cognitive resources to spend less time on easy problems and more time on hard problems.

Advisor: Griffiths, Thomas L.
Kinetic Resolution of Ras and Arf Signaling Activation by GEFs on Lipid Membranes and in Live Cells

Supported Lipid Bilayers (SLBs) were used in conjunction with live cell measurements to better understand the activation of the small GTPases Ras and Arf by their respective GEFs SOS and ARNO. As membranes are crucial for proper activity of these proteins, membrane-mimic assays were developed to quantitatively measure kinetic activation and diffusion./nRas is a common oncogene that causes over 30% of all human cancers. SOS is one of Ras’s activators that is known to play a role in the determination of cell fate. The kinetics of SOS activation of Ras was explored in four of the following chapters. Firstly, a nanofabricated platform that incorporated liposome reaction chambers was developed to assess the kinetic activity of single SOS molecules with single nucleotide turnover resolution. Secondly, the measurement of SOS motility and localization in live cells contributed to an understanding of SOS regulation through a stable membrane-associated active state, resulting in SOS endocytosis. Thirdly, a small molecule inhibitor was shown to impact SOS binding to Ras in vitro and in vivo. Fourthly, the impact of oncogenic Ras mutations on SOS binding and catalytic rate was measured. These results provide insight in the tight regulation of SOS-mediated Ras activation, and also suggest future directions for rational drug design targeting oncogenic Ras./nArf is a small GTPase in the Ras family that regulates membrane traffic and morphology. In the final chapter, a SLB-based assay for GEF-mediated Arf recruitment studies was developed and diffusion rates for both Arf-GTP and Arf-GDP were measured, demonstrating a well-defined, transient membrane interaction for Arf in the GDP state. Additionally, autoinhibition of the GEF ARNO was confirmed. This yields new insight into the mechanism of Arf signaling initiation./nOverall, it is demonstrated that in vitro membrane mimics, in combination with live cell measurements, provide a powerful tool to gain a deeper understanding about the activity and regulation of GTPases.

Advisor: Groves, Jay T
Biochemical and Genetic Mechanisms Underlying Basal Salicylic Acid Synthesis In Arabidopsis thaliana

The research of plant –microbe interactions is a field with broad applications and strong economic importance to society, as plants are the primary producers that we rely upon for food, textiles, air quality and ornamental value. Global climate change is predicted have a dramatic impact on plant-microbe and pest interactions, and better understanding of how plants respond to pathogen threats is important. The plant hormone salicylic acid (SA) is a crucial signaling molecule in the response to infection by (hemi)biotrophic microbes, as well as other abiotic stress responses. However, our understanding of the mechanisms governing its synthesis is lacking. Pathogen challenge induces rapid and robust SA synthesis, increasing the amount of the hormone 10-fold within 48 hours. However, SA synthesis also occurs at a low rate in uninfected plants, accumulating as a storage form that can be readily converted to active SA. Herein, I detail two studies using the model dicot Arabidopsis thaliana examining the processes governing SA accumulation through metabolic manipulation of SA precursors and transporters, and show that the pre-infection levels of endogenous SA can play a role in priming plant immunity./nIn chapter 2, I present evidence that chorismate mutases can influence basal SA synthesis by their competition with isochorismate synthase enzymes for the substrate chorismate. Transient overexpression of these enzymes reduced SA accumulation in planta, suggesting these enzymes redirected chorismate flux away from SA synthesis. Plants with reduced expression of chorismate mutase 1 (CM1) exhibited elevated basal SA levels, which conferred enhanced disease resistance to a virulent bacterial Pseudomonas syringae foliar pathogen. This phenotype comes without an obvious fitness cost to the plant; they don’t exhibit increased basal expression of defense genes, or a reduction in plant growth. Rather, it appears that this elevated basal SA quickens early responses to pathogens, a key moment in the infection process./nIn contrast, chapter 3 details the discovery that the transcriptional repressor DEL1, previously characterized for its role as a cell cycle regulator, also mediates basal SA synthesis. Loss of DEL1 repression leads to increased expression of SA biosynthesis and transporter genes, which alters SA signaling responses and primes the plant for greater disease resistance to both bacterial and fungal pathogens. CM1 and DEL1 mutant plants represent a continuum of defense priming by endogenous SA, and illustrate new approaches for modulating increased disease resistance in plants by influencing metabolic flux of chorismate products. The discovery that DEL1 also mediates expression of an SA hub suggests that it plays a broader role in coordinating developmental and stress response cues.

Advisor: Wildermuth, Mary C
Charging of Proteins and Protein Complexes in Native Mass Spectrometry

Electrospray ionization (ESI) mass spectrometry is a powerful analytical tool for investigating the identities, structures, functions, and energetics of biomolecules. ESI transfers intact molecules from buffered aqueous solutions in which they are folded or in native conformations into the gas phase for mass spectral analysis. ESI is widely used for the analysis of proteins in mass spectrometry, but the factors that influence charging of protein ions formed by ESI are not well understood. Higher charge states of protein ions are desirable because they fragment more easily in tandem mass spectrometry methods, leading to more sequence coverage than lower charge protein ions. Lower charge protein ions are advantageous in native mass spectrometry when preservation of native protein conformation is desirable. The work described in this dissertation explores factors that control charging of macromolecular ions in native mass spectrometry. This work provides evidence that the charging of macromolecular ions is not significantly limited by ion evaporation of cations, such as alkylammonium or alkali metal ions, or proton transfer to salts that are commonly added to aqueous buffered ESI solutions. In addition, a novel and simple method for ESI of proteins directly from buffers commonly used in biochemistry laboratories is demonstrated. In native mass spectrometry, protein solutions are typically desalted and buffer exchanged into volatile ammonium salt buffers to prevent salt adduction to the protein ions because salt adduction significantly hinders detection and sensitivity of mass spectral analysis. However, some salts are essential for protein structure and function, and this new method of ion desalting allows formation of protein and protein complex ions directly from buffers that contain high ionic strengths of nonvolatile salts to mimic the intracellular and extracellular environments. This technique greatly impacts the way native mass spectrometry is performed because it eliminates the need to reinvestigate properties of the proteins and protein complexes in traditional ammonium salt buffers used in mass spectrometry. Therefore, biochemists will no longer need to adapt their protein solutions to make them suitable for mass spectrometry.

Advisor: Williams, Evan R
Functions of nearly maximal Gowers-Host-Kra norms on Euclidean spaces

Let $k\geq 2, n\geq 1$ be integers. Let $f: \mathbb{R}^{n} \to \mathbb{C}$. The $k$th Gowers-Host-Kra norm of $f$ is defined recursively by/n‖
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h/nwith $T^{h}f(x) = f(x+h)$ and $\|f\|_{U^1} = | \int_{\mathbb{R}^{n}} f(x)\, dx |$. These norms were introduced by Gowers [11] in his work on Szemer\'edi's theorem, and by Host-Kra [13] in ergodic setting. These norms are also discussed extensively in [17]. It's shown by Eisner and Tao in [10] that for every $k\geq 2$ there exist $A(k,n)< \infty$ and $p_{k} = 2^{k}/(k+1)$ such that $\| f\|_{U^{k}} \leq A(k,n)\|f\|_{p_{k}}$, with $p_{k} = 2^{k}/(k+1)$ for all $f \in L^{p_{k}}(\mathbb{R}^{n})$. The optimal constant $A(k,n)$ and the extremizers for this inequality are known [10]. In this dissertation, it is shown that if the ratio $\| f \|_{U^{k}}/\|f\|_{p_{k}}$ is nearly maximal, then $f$ is close in $L^{p_{k}}$ norm to an extremizer.

Advisor: Christ, Francis Michael
Structural Approaches to Public Health Theory and Pedagogy

This dissertation is comprised of three separate manuscripts. Each manuscript concerns questions of social structure in relation to health, morbidity, and mortality. The first examines the epidemiologic theories taught most frequently in core master of public health coursework and proposes curricular changes to better engage with the structural determinants of health. The second provides a broad outline of one structural epidemiologic theory—political economy of health theory—for a public health audience. The third proposes a framework for ‘structurally competent’ global health pedagogy by defining and describing individual competencies. Together, these manuscripts seek to contribute to structural approaches to public health theory and pedagogy.

Advisor: Holmes, Seth
A multi model investigation of the global interior structure of the Moon

We consider four modeling efforts to determine the interior structure of the Moon. This includes a geophysical forward model capturing magnetic induction from conducting layers within a vacuum, a plasma induction model capturing the kinetic plasma environment within the wake cavity around a conducting Moon, a multidisciplinary modeling analysis including geochemical, geophysical, and geodynamical considerations, and forward calculate the seismic free oscillations of the Moon./nElectromagnetic Sounding constrains conducting layers of the lunar interior by observing variations in the Interplanetary Magnetic Field disturbing the Moon. We employ the time domain transfer function method locating transient events observed by two magnetometers near the Moon. We consider ARTEMIS and Apollo magnetometer data. We demonstrate our forward model passes benchmarking analyses and solves the magnetic induction response for any input signal as well as any conductivity profile. Plasma hybrid models use the upstream plasma conditions and IMF to capture the wake current systems formed around the Moon. The plasma kinetic equations are solved for ion particles with electrons as a charge-neutralizing fluid. These models accurately capture the large-scale lunar wake dynamics for a variety of solar wind conditions (ion density, temperature, solar wind velocity, and IMF orientation). This method and modeling results are applicable to any airless body with a conducting interior, interacting directly with the solar wind in the absence of a parent body magnetic field as well as any two-point magnetometer constellation./nFor our third analysis, we take a multidisciplinary approach to constrain key parameters of the lunar structure. We use an ensemble of 1D lunar compositional models with chemically and mineralogically distinct layers, and forward calculate physical parameters. We employ a grid search and a differential evolution genetic search algorithm to extensively explore model space, where the thickness of individual compositional layers varies. We find that the proposed partially molten layer within the deep mantle may have been formed by the overturn of an ilmenite rich layer, formed after the crystallization of a magma ocean. Moreover, only a narrow range of core radii are consistent with the mass and moment of inertia constraints. For the models that fit the observed mass and moment of inertia, we compare the deviation in the chemistry to that published, and calculate 1D seismic velocity profiles, the majority of which compare well with those determined by inverting the Apollo seismic data.

Advisor: de Pater, Imke
Delory, Greg
Molecular mechanisms and applications of RNA targeting CRISPR endonucleases

Evolutionary pressure to protect against phage-induced lysis and rampant horizontal gene transfer has created a wide repertoire of defensive pathways in bacteria. CRISPR-Cas (clustered regularly interspaced short palindromic repeats, CRISPR-associated) systems are adaptive immune pathways that use RNA-guided nucleases to direct cleavage of invading nucleic acids. The programmable nature of these enzymes has enabled a revolution for DNA-targeting applications including gene editing, transcriptional control, and genomic imaging. In addition to DNA-targeting enzymes, specific subtypes of CRISPR-Cas systems recognize and degrade single stranded RNA (ssRNA) substrates. Repurposing these ssRNA-targeting enzymes into biotechnological tools is currently limited by a lack of mechanistic information. In this work, we address this issue by redirecting a well-studied DNA-targeting CRISPR nuclease, Cas9, to ssRNA targets and investigating the enzymatic mechanisms of a novel ssRNA-targeting CRISPR nuclease, Cas13a (formerly C2c2)./nTypically, Cas9 ignores ssRNA while searching for dsDNA targets due to ssRNA’s inherent single-stranded structure and lack of a protospacer adjacent motif (PAM). We redirected Cas9 to bind and recognize ssRNA targets through addition of a third component, a target-complementary DNA oligonucleotide or PAMmer, that provides a DNA:RNA hybrid PAM. Using primary microRNAs as a model system, we provide proof-of-concept evidence that Cas9:PAMmer complexes can mediate the isolation and subsequent mass spectrometry analysis of protein complexes bound to specific RNAs./nThe complexity of redirecting Cas9 to ssRNA substrates motivated us to investigate CRISPR proteins that natively target RNA. We focused on Cas13a, a predicted ribonuclease from Type VI CRISPR-Cas systems. We discovered that Cas13a possesses two distinct catalytic activities, one for site-specific cleavage of its CRISPR RNA (crRNA) and the second for nonspecific ssRNA degradation activated by target binding. These insights allowed us to establish a revised model for ssRNA-targeting by Type VI CRISPR-Cas systems. Through biochemical characterization of the entire Cas13a protein family, we revealed hidden diversity in substrate preferences and defined orthogonal enzyme subfamilies. These diverse Cas13a homologs can be harnessed in parallel for detection of distinct RNA species within complex mixtures for both bacterial immunity and diagnostic applications. Together, this work presents two novel biotechnological applications of CRISPR-Cas nucleases for RNA isolation and RNA detection.¬¬

Advisor: Doudna, Jennifer A
Predictive Control of Uncertain Systems based on Motion Prediction

Model predictive control is a very popular control scheme in a wide range of fields including driver assistance systems and autonomous robots. For example, in driver assistance systems, predictive control allows for improved safety and comfort. However, its implementation is a challenge in uncertain environments. Therefore, it is desirable to predict the evolution of the environment in which the controlled system operates. In other words, we pursue a highly accurate forecast of the environment so that we may achieve feasible and reliable action from the controller./nThis dissertation presents a systematic framework that uses predictive control and forecasts of the future environment to operate under uncertainties and constraints. In particular, we focus on enhancing the performance of a predictive control scheme based on an accurate trajectory prediction of any targets controlled by humans (e.g., vehicles driven by human or humans themselves). We propose several motion-prediction-models using physics-based and data-driven approaches to improve the accuracy of the forecast. An interacting-multiple-model approach with Kalman filter techniques is useful in environments where it is difficult to have prior data sets such as disaster sites. Based on collected data from experimental vehicles, machine learning methods including hidden Markov models, convolution neural networks, and recurrent neural networks are used to enhance long-term predictions. Furthermore, we present predictive controls based on a probabilistic view of uncertain forecasts. The effectiveness of the proposed framework is demonstrated via applications such as human-companion robots, automotive adaptive cruise control, and autonomous lane change assist. The results of both simulation and real experimental data show the synergy between the motion prediction models and the predictive control designs.

Advisor: Borrelli, Francesco
Advanced ignition for automotive engines

Spark plugs have been igniting combustible mixtures like those found in automotive engines for over a century, and the principles of the associated ignition techniques using thermal plasma (inductive or capacitive sparks) have remained relatively unchanged during that time. However, internal combustion engines are increasingly operating with boosted intake pressures (i.e. turbo- or super-charged) in order to maintain power output while simultaneously reducing engine size and weight, and they are also operating with increased recirculated exhaust gas dilution to reduce the production of harmful nitrogen oxides. This “downsizing” to increase fuel economy compounded with diluting to decrease emissions leads to challenges in both obtaining traditional ignition and promoting sufficiently fast combustion under this operating paradigm. In conjunction with appropriate electrode design, transient non-thermal plasma can exploit certain non-equilibrium chemistry and physics to bypass these challenges and ultimately promote more reliable ignition and faster combustion. Applied and fundamental experimental investigations of two different advanced ignition techniques are presented: 1) corona discharges igniting gasoline/air/exhaust mixtures in a boosted direct- injection single cylinder research engine and 2) repetitively pulsed nanosecond discharges igniting methane/air mixtures in a constant volume chamber. The engine experimental results show significant decreases in fuel consumption and nitrogen oxide emissions under boosted operation, and both experiments demonstrate more robust ignition and faster flame development. The constant volume chamber results in particular raise important questions about the relative contributions of chemistry and transport to the experimentally observed combustion enhancement. These results highlight the critical importance of electrode design in advanced ignition techniques—the shape and position of electrodes greatly influences the hydrodynamics of developing flame kernels into fuel-air charges. While this work demonstrates that non-thermal plasma ignition is a promising solution to both increase fuel economy and decrease emissions of future automotive engines, much work remains to be done to understand the beneficial coupling between the detailed non-thermal plasma chemistry and the hydrodynamics associated with these real ignition devices.

Advisor: Chen, Jyh-Yuan
Tracing Patterns of Textiles in Ancient Java (8th–15th century)

Few attempts have been made to study the numerous textile depictions in Java from the eighth to fifteenth centuries, also known as the Hindu-Buddhist or the Ancient Javanese Period. This thesis seeks for the textiles that inspired these depictions and considers their techniques. It also traces the evolution of particular patterns in Java over time. To do so, I employ close art-historical analysis of works of art and draw supportive materials from archaeology, epigraphy and literature, as well as ethnography./nAfter the introductory chapter, Chapters One and Two focus each on a different textile pattern: the connected circles and the overlapping circles patterns. These chapters follow the evolution of the patterns with particular interest to search for connections to current textile tradition in Indonesia. A similar approach of inquiry is applied in Chapter Three to a type of short sleeve jacket. Chapter Four investigates the depiction of weavers in Ancient Javanese textual and visual sources./nThis study of textile depictions will underscore the global connection between Java and the outside world, particularly China and India, from where many prototypes of the textile images originated. The study will also reveal that these images, in addition to being historical records, were also ornamentations, which the Javanese artists were adept at translating, decontextualizing, and re-contextualizing—as a whole or in part—into the local aesthetic and usage.

Advisor: Williams, Joanna
Klokke, Marijke