VictorJuiz/thesis huggingface dataset:
Statistical Learning for Efficient Industrial Robot Control

This dissertation presents a series of statistical learning methods to improve the overall/nperformance for industrial robots, which are always required to perform accurate and fast/nmotions in sensing limited scenarios, and/or changing environments. Statistical methods/nemphasize on system uncertainties and adaptation to the environment by learning from/nthe experience. Four aspects have been studied in detail including robust visual servo,/noptimal trajectory planning, intelligent system identication for feedforward compensation,/nand optimal gain tuning./nFor visual servo requiring high precision and high speed but suffering from limited sensing/ncapability and system uncertainties, a statistical learning approach based on sensor fusion/nand robust vision is adopted for sensor data filtering and on-line parameter adaptation./nThis method can compensate for the large sensing latency and estimate system parameters/nsimultaneously. The algorithm is tested on an 6-axis industrial robot performing precision/nglass handling task but with only limited quality vision sensors. Trajectory planning is/nanother fundamental problem for industrial robot, especially for robots operating in extremely/nlimited workspace. In order to generate obstacle-free trajectories with shortest cycle/ntime, a statistical learning method, Probabilistic Roadmap (PRM), is first used for optimal/ntrajectory planning. An optimization problem is then formulated based on spline parameterization./nThe planning algorithm is tested on a 3-axis industrial robot, and the result shows/nthe efficiency of the planning method. Statistical learning approaches are also studied for/nthe precision motion control and vibration suppression for industrial robots. Model-based/ncontroller for parallel robots is always hard to design due to the complexity of the robots. A/nmodel based feedforward controller is designed with dynamic identification with a regression/nperformed using data generated by experiments with designed trajectory. Also, an experiment/nbased guided gain search is proposed with direct end-effector sensing for vibration/nsuppression. An optimization scheme is utilized to guide the searching direction with experiments/nand data learning. It is proved by experiments that the tracking error and vibration/nare greatly reduced on an 8-link wafer handling robot.

Advisor: Tomizuka, Masayoshi
Regression Modeling and Bias Correction of Ribosome Profiling Data

Translational regulation is an important control point for gene expression, modulating the quantity and isoforms of proteins produced in a cell. The ribosome profiling method measures translation dynamics and output directly, by sampling the distribution of ribosomes across all mRNA transcripts in a sample. This method has demonstrated that ribosomes do not move at a uniform rate across transcripts, and that synonymous codon choice can have large effects on ribosome speed, RNA stability, and protein expression. We present a regression model using a feedforward neural network to predict the ribosome density at each codon in a transcriptome as a function of the local sequence neighborhood around that codon. This approach demonstrated a collection of sequence features that contain substantial predictive information about translation elongation rates. We apply this model to characterize the translation rates of naturally occurring genes, and also to design translation optimized coding sequences for a given protein. We present a novel and efficient algorithm that finds the fastest and slowest predicted coding sequences for a given protein. We validated our regression model and optimization procedure by designing synonymous variants of eCitrine, a yellow fluorescent protein, across a range of predicted translation rates. Our results showed that the levels of expressed protein closely tracked the predicted overall translation rates of the synonymous coding sequences. This demonstrated that our model captures information determining translation dynamics in vivo, that we can harness this information to design coding sequences, and that control of translation elongation alone is sufficient to produce large, quantitative differences in protein output. Analysis of our regression model also demonstrated that the terminal regions of ribosome footprints are important predictors of footprint density at a given codon. This suggests that ligation events in the experimental protocol are differentially recovering footprints based on their terminal sequences. We characterized this recovery bias both computationally and experimentally, and demonstrated that it can have a large impact on the count of footprints recovered at a given codon. To correct for this error, we developed a generative model of ribosome footprint experiments that incorporates both the biological distribution of footprints across transcripts and the experimental steps that introduce recovery bias. We developed a software tool to estimate the parameters of this model, and present a statistical method to correct recovery bias and estimate the biological distribution of ribosomes across transcripts. This method enables improved estimates of translation for the many applications in which ribosome profiling data is used.

Advisor: Lareau, Liana F
Pachter, Lior S
Application of an Oxygen Stitching Strategy in the Syntheses of Complex Terpenoids

In the first chapter of this dissertation, a three-step total synthesis of the antimalarial (+)-cardamom peroxide, an endoperoxide-containing monoterpene dimer, is reported. This concise synthesis utilized (–)-myrtenal as an inexpensive terpene building block, and applied a novel oxygen stitching strategy to install all the oxygen atoms in the natural product from molecular oxygen. This strategy has enabled the preparation of large quantities of (+)-cardamom peroxide, and subsequent studies have determined its absolute configuration, and this molecule’s reactivity in iron(II)-induced reductive cleavage. Additionally, the antimalarial activities of cardamom peroxide against the clinical isolates of Plasmodium falciparum from several Cambodia provinces have been evaluated./nIn the second chapter, a double allylation strategy for the construction of the [5,7,5]-fused carbocyclic system found in guaianolide sesquiterpenoids is disclosed. This strategy features a robust intramolecular allylation mediated by tin(II) chloride to assemble the seven-membered core. An efficient and scalable total synthesis of the trans-fused 8,12-guaianolide (+)-mikanokryptin via this strategy is reported in nine to ten steps from the abundant monoterpene (+)-carvone, which constitutes the first example of gram-scale total synthesis of any guaianolide natural product./nSubsequently, the oxygen stitching strategy has been expanded from the synthesis of endoperoxides to the strategic installation of multiple oxygen atoms on complex guaianolides in a stereocontrolled manner. A concise total synthesis of (–)-nortrilobolide and a formal synthesis of the anticancer agent (–)-thapsigargin are achieved by merging the oxygen stitching strategy and double allylation strategy./nPreliminary studies on a modular synthesis of guaianolides from the Apiaceae family of plants are also disclosed via an intramolecular allylation strategy. These studies include concise total syntheses of sinodielide A and grilactone from chiral-pool building block linalool, and studies towards the total syntheses of prutenin, ammolactone A, and montanolide. Notably, this strategy has the potential to access the Apiaceae guaianolides encompassing all the oxidation levels in this family.

Advisor: Maimone, Thomas J
Engineering industrial brewing yeast for flavor production

Yeast has been used by various peoples for thousands of years to make beer, wine, and other alcoholic beverages. During fermentation, yeast impart a host of flavor and aroma molecules to wine and beer, derived from both central and secondary metabolism. Many of these compounds are derived from the interactions between yeast enzymes and compounds contributed by hops, in the case of beer, and grapes, in the case of wine. The field of metabolic engineering has opened up new avenues for flavor production in microbes such as yeast. In addition to the overexpression or deletion of yeast endogenous enzymes responsible for flavor modulation, de novo production of flavors in yeast is also possible. In the work presented in this doctoral dissertation I describe how these tools have been applied to the engineering of brewer’s yeast strains in order to reduce, and perhaps eventually replace, aromatic hop additions used in the brewing process./nChapter 1 presents a review of genetically engineered brewing and wine yeasts. Commercial and academic examples are discussed. Traits that have been engineered encompass flavor production and off-flavor reduction, flocculation, sugar consumption, and other fermentation performance characteristics./nChapter 2 presents my work engineering California Ale Yeast to biosynthesize the compounds linalool and geraniol, which impart hoppy flavor and aroma to beer. At least one engineered strain was shown to produce beer perceived as hoppier than traditionally hopped beer by a sensory panel in a double-blind tasting./nChapter 3 describes additional engineering of the monoterpene-producing strains and suggests future work to more fully reconstitute the complex flavor imparted by traditional hop additions. Engineered strains provide an avenue for improvement and innovation of the brewing process by making it possible to generate new and distinctive flavors with consistency and reproducibility.

Advisor: Keasling, Jay D
Flexible supercapacitors based on micro/nanofibers

Flexible energy storage components are indispensable in the field of flexible electronics. Supercapacitors featuring high power density, fast charge/discharge rate, long cycle life, and safe operation are desirable devices. Micro/nanofiber-based electrode materials, fabrication processes, and device configurations are investigated towards flexible supercapacitors applications./nMicro flexible supercapacitors (FSCs) prepared using direct-write nanofibers is demonstrated for flexible integrated microelectronics. The micro electrodes with porous network are fabricated by the near-field electrospinning process of polypyrrole (PPy) nanofibers on a patterned metal layer on flexible substrate. Such conductive nanofiber network with a pseudocapacitance effect greatly increases the capacitance and facilitates ion transport in the electrodes. The prototype micro FSCs are experimentally proved to be highly flexible with excellent electrochemical performance and cycling stability. The approach is simple, versatile, and compatible with different substrates for the direct integration of energy storage devices in flexible microsystems./nAn ultra-thin micro coaxial fiber supercapacitor (μCFSC) with high energy and power densities, and excellent mechanical properties is demonstrated. The prototype with the smallest reported overall diameter of 13 μm is fabricated by successive coating of functional layers onto a single micro carbon fiber via a scalable process. Combining the simulation results via the electrochemical model, the high performance is attributed to the well-controlled thin coatings that make full use of the electrode materials and minimize the ion transport path between electrodes. Moreover, the μCFSC features high bending flexibility and large tensile strength (more than 1 GPa), which make it promising as a building block for various flexible energy storage applications./nFree-standing woven supercapacitor fabrics that can store high electrical energy and sustain large mechanical loads are demonstrated as flexible power sources. The prototype with reduced package weight/volume provides an impressive overall energy density of 2.58 mWh g-1 or 3.6 mWh cm-3, high tensile strength of over 1000 MPa, and bearable pressure of over 100 MPa. The nanoporous thread electrodes are prepared by the activation of commercial carbon fibers to have three-orders of magnitude increase in the specific surface area and 86% retention of the original mechanical strength. The novel device configuration woven by solid electrolyte-coated threads shows excellent flexibility and stability during repeated mechanical bending tests. Such scalable energy storage fabrics can be woven into daily graments as flexible power sources for a variety of wearable electronics.

Advisor: Lin, Liwei
Balancing On-Farm Food Safety and Environmental Protection: A Comparative Case Study of Leafy Greens Producers in the United States and the United Kingdom

In the last decade, high-volume industrial production of fresh leafy greens including spinach and romaine lettuce has become increasingly linked to outbreaks of dangerous foodborne pathogens such as E. coli O157:H7. Current approaches to food safety risk management seek to prevent the introduction of pathogens at field level, through wildlife exclusion practices and the removal of habitat near farms, which can damage environmental conservation efforts. Farmers must balance multiple overlapping requirements coming from government regulation and privately-operated food safety standards, in which food safety concerns may be given priority over environmental sustainability./nImproving food safety in fresh leafy greens without compromising environmental health will require policy solutions that consider the structural roots of food safety problems, and how food safety regulation impacts farmers. This dissertation presents an international comparative policy case study of leafy greens production in the United States and the United Kingdom, in which I evaluate public and private risk management mechanisms that have combined to shape national approaches to food safety, in the context of current political and regulatory trends. Deepening traditional comparative politics literature, this study draws on a structural comparison of public and private standards and interviews with leafy greens producers in both nations to illuminate the social and environmental impacts of various regulatory mechanisms. I demonstrate that food safety standards containing a balance of process-oriented and prescriptive requirements, and a balance between food safety and environmental concerns, are correlated with more environmentally friendly agricultural practices and more favorable farmer perceptions of food safety regulation. From a perspective situated at the convergence of agri-food studies, regulatory practice, and comparative policy, I suggest regulatory changes and supply chain solutions for balancing food safety and environmental sustainability.

Advisor: O'Neill, Katherine M.
The Arithmetic of Graph Polynomials

We investigate three graph polynomials including antimagic, super edge-magic, and chromatic polynomials. The Antimagic Graph Conjecture asserts that every connected graph $G = (V,E)$ except $K_2$ admits an edge labeling such that each label $1,2,\ldots,|E|$ is used exactly once and the sums of the labels of the edges incident to each vertex are distinct. We introduce partially magic labelings where the vertex sums are the same in a subset of $V$. By using the quasi-polynomial structure of the partially magic labeling counting function, we show that every bipartite graph satisfies a relaxed version of the Antimagic Graph Conjecture (that is, repetition of labels are allowed). \/nA total labeling $f:E \cup V \to \ZZ_{\ge 0}$ of a graph $G=(V,E)$ is called \emph{super edge-magic} if each vertex label is in $\{1,\ldots, |V|\}$ and the sum of the edge label plus labels of its two ends is the same for all edges of $G$. We prove that the counting function of super edge-magic labelings of every tree is a polynomial. This helps us to show that every tree admits a relaxed super edge magic labeling which is the relaxed version of \emph{Super Edge-Magic Tree Conjecture}. Moreover, we show that every tree with one extra edge that makes a unique even cycle admits a super edge-magic labeling. On the other hand, a \emph{harmonious labeling} is an injective function $L:V \rightarrow \{0, 1, \ldots, |E|-1 \}$ such that the induced edge labels $L^{*}(e) \equiv L(u)+L(v)$ (mod $|E|$) for every edge $e=\{u,v\} \in E,$ are distinct. The \emph{Harmonious Tree Conjecture} indicates that every tree admits a harmonious labeling. We use our results on super edge-magic labelings to prove that every tree admits a relaxed version of the Harmonious Tree Conjecture. \/nLastly, we extend classic order polynomials to a two variable version and we drive a reciprocity theorem for strict and weak order polynomials, reminiscent of Stanley's reciprocity theorem. We also study the \emph{bivariate chromatic polynomial} which counts the number of vertex coloring of $G$ with $1 \le x$ colors allowing the same colors for adjacent vertices if the color is $\ge y$ ($1 \le y \le x$). We decompose bivariate chromatic polynomial into bivariate order polynomials and we find a reciprocity relation linking bivariate chromatic polynomials to acyclic orientations.

Advisor: Beck, Matthias
Haiman, Mark
Spatiotemporal Patterns of Seasonality in Landslide Deformation from InSAR and GPS

High-resolution characterization of landslide deformation and its spatiotemporal response to external triggering mechanisms is a first step toward improved hazard forecasting. Slope instability in the San Francisco East Bay Hills (EBH), including the Lawrence Berkeley National Laboratory (LBL), has been a prevalent problem since development of the area began. The EBH are home to a number of very slowly moving (~20 mm/yr), earth and rock flow-type landslide complexes whose activity has been shown to vary spatiotemporally in response to seasonal precipitation and seismic activity. Advanced technologies such as Interferometric Synthetic Aperture Radar (InSAR) and continuous Global Positioning Systems (cGPS) are well suited for monitoring these types of processes, as they allow for remote detection and characterization of ground surface displacements with sub-centimeter precision and accuracy. Relying on InSAR and cGPS, two time histories of ground deformation with exceptionally high spatial and temporal resolution are produced for the EBH. The spatiotemporal patterns of variability in each of these signals are identified and related to different ground deformation mechanisms./nAfter careful evaluation of nearly 50 inventoried landslide deposits, a network of 6 autonomous cGPS landslide monitoring stations was instrumented across four select sites. Established in 2012, the network is set to continue monitoring ground deformation at high rates (1Hz and 20Hz) through the foreseeable future. The methodology for this field instrumentation effort is described and the resulting time series are examined. The data reveals seasonally modulated shrink/swelling cycles of the surficial soils and downslope velocities indicative of landslide deformation./nRelying on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSARTM), InSAR time series analysis produces a record of ground deformation over the same study area, with exceptionally dense spatial coverage. Through the use of functional curve fitting, and Principal and Independent Component Analyses the data reveals four distinct spatial and temporal surface deformation patterns which relate to different geo-mechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore-pressure changes controlled by annual seasonal cycles and multi-year drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings.

Advisor: Sitar, Nicholas
Burgmann, Roland
Collaborative Learning Among Health Care Practices and Systems to Improve Patient-Centered Care

Despite a rich literature examining the application of organizational learning to engineering and management contexts, learning in the health care sector has received far less empirical attention. These papers collectively address which organizational factors are precursors to learning within quality improvement collaboratives (QICs) and how participation in QICs impacts patient-centered outcomes. The first paper examines the organizational attributes associated with physician practices’ propensity to participate in QICs. The second paper explores the implementation of a shared decision making intervention within the High Value Healthcare Collaborative (HVHC) and investigates its impact upon hip and knee osteoarthritis patients' treatment preferences and decision certainty. Finally, the third paper interrogates whether surgical utilization varies across patients engaged in shared decision making compared with patients receiving usual care within HVHC.

Advisor: Rodriguez, Hector P
Structural and evolutionary studies on CaMKII oligomerization

Calcium-calmodulin-dependent protein kinase II (CaMKII) plays a critical role in animal learning and memory (Giese et al. 1998). CaMKII operates as a multi-subunit holoenzyme and can detect the frequency of incident Ca2+ pulse trains entering the cell (Chao et al. 2011; De Koninck and Schulman 1998). CaMKII holoenzymes become destabilized and appear to exchange subunits following catalytic activation, which results in the spread of kinase activity to inactive holoenzymes (Stratton et al. 2014; Bhattacharyya et al. 2016). This phenomenon is not fully understood and is under active investigation./nThis work focuses on the structural and biochemical characterization of CaMKII hub domain assemblies, which are essential to holoenzyme formation (Shen and Meyer 1998; Kolb et al. 1998). The crystal structure of a dodecameric human CaMKII-α hub domain assembly shows how the protein may be able to sense the activation state of the CaMKII kinase domain. This helps explain why kinase activation destabilizes CaMKII holoenzymes and promotes subunit exchange./nThe characterization of CaMKII hub domains from evolutionarily divergent organisms is also presented. Hub domains encoded by three related green algae assemble into 16-, 18-, and 20-subunit oligomers. These are the largest known CaMKII hub domain assemblies. A crystal structure of one, the Chlamydomonas reinhardtii 18-mer, revealed multiple intra-chain hydrogen bonds not present in the human isoform./nWhen these hydrogen bonds were engineered into the human CaMKII hub domain by mutation the protein oligomerized into larger assemblies. A larger CaMKII holoenzyme is predicted to be more resistant to deactivation by protein phosphatases and thus may be useful in studying the consequences of aberrant CaMKII activity. These hydrogen bonds are also predicted to inhibit subunit exchange in human CaMKII by dampening structural fluctuations in the hub domain./nWork is also described on an interfacial mutation in the hub domain that weakens the integrity of the CaMKII holoenzyme. CaMKII dimers are present in solution as a result of this mutation. Catalytic activation increases the dimer population, demonstrating that the hub domain interface weakened by the mutation is further destabilized when CaMKII is active. This suggests that dimer release is a central component of activation-triggered subunit exchange between CaMKII holoenzymes.

Advisor: Kuriyan, John