VictorJuiz/thesis huggingface dataset:
Greedy Dictionary Learning Algorithms for Sparse Surrogate Modelling

In the field of engineering design, numerical simulations are commonly used to forecast system performance before physical prototypes are built and tested. However the fidelity of predictive models has outpaced advances in computer hardware and numerical methods, making it impractical to directly apply numerical optimization algorithms to the design of complex engineering systems modelled with high fidelity. A promising approach for dealing with this computational challenge is the use of surrogate models, which serve as approximations of the high-fidelity computational models and can be evaluated very cheaply. This makes surrogates extremely valuable in design optimization and a wider class of problems: inverse parameter estimation, machine learning, uncertainty quantification, and visualization. This thesis is concerned with the development of greedy dictionary learning algorithms for efficiently constructing sparse surrogate models using a set of scattered observational data. The central idea is to define a dictionary of basis functions either a priori or a posteriori in light of the dataset and select a subset of the basis functions from the dictionary using a greedy search criterion. In this thesis, we first develop a novel algorithm for sparse learning from parameterized dictionaries in the context of greedy radial basis function learning (GRBF). Next, we develop a novel algorithm for general dictionary learning (GGDL). This algorithm is presented in the context of multiple kernel learning with heterogenous dictionaries. In addition, we present a novel strategy, based on cross-validation, for parallelizing greedy dictionary learning and a randomized sampling strategy to significantly reduce approximation costs associated with large dictionaries. We also employ our GGDL algorithm in the context of uncertainty quantification to construct sparse polynomial chaos expansions. Finally, we demonstrate how our algorithms may be adapted to approximate gradient-enhanced datasets. Numerical studies are presented for a variety of test functions, machine learning datasets, and engineering case studies over a wide range of dataset size and dimensionality. Compared to state-of-the-art approximation techniques such as classical radial basis function approximations, Gaussian process models, and support vector machines, our algorithms build surrogates which are significantly more sparse, of comparable or improved accuracy, and often offer reduced computational and memory costs.

Keywords: Dictionary learning
Greedy algorithm
Machine learning
Regression
Supervised learning
Surrogate modelling
Advisor: Nair, Prasanth B
Influenza A Virus NS1 Inhibits Type I IFN Responses

Type I IFNs shape innate and adaptive immune responses by upregulating the expression of antiviral and immunomodulatory genes. Pathogenic viruses have evolved effective mechanisms to inhibit the type I IFN response, and IAVs are no exception – IAVs express NS1, a multifunctional protein that downregulates type I IFN production and signaling. The studies described herein characterize the contributions of both strictly conserved and strain-dependent residues in the NS1 putative SH2-binding domain (Y84) and the CPSF4-binding domain (F103 and M106), respectively, to NS1-mediated inhibition of type I IFN signaling and ISG expression. Using site-directed mutagenesis and reverse genetics, we generated rIAVs expressing NS1s encoding Y84F or F103L and/or M106I mutations. We provide evidence that a Y84F mutation abrogates NS1-mediated inhibition of IFN-β-inducible STAT1/2 phosphorylation and IFNAR1 expression. As a result, in human A549 lung epithelial cells and in C57BL/6 mice, rIAVs expressing NS1-Y84F replicate to lower titers and are more susceptible to the antiviral effects of IFN- treatment. rIAVs expressing NS1-F103L/M106I/F103L+M106I are also attenuated in A549 cells. Notably, in A549 cells infected with rIAV expressing NS1-M106I/F103L+M106I and treated with IFN- we identified increased polysome-associated ISG expression – indicative of increased translation initiation – compared with cells infected with rIAV expressing wt NS1. Viewed altogether, our data highlight the ability of IAV NS1 to antagonize multiple aspects of an effective host type I IFN response, and the importance of both conserved and strain-dependent residues in NS1 for IAV replication. In a supplementary chapter, we describe the elevated antiviral ISG signature present in the peripheral blood of three patients with Aicardi-Goutières Syndrome (AGS), an early-onset autoimmune disease associated with overactive type I IFN production. Our data suggest that ISG expression is a more sensitive biomarker for AGS than standard readouts for inflammation, including ESR, CRP, and WBC counts.

Keywords: Influenza A virus
Innate immunity
NS1
Pathogen-host interactions
Type I interferon
Virus infection
Advisor: Fish, Eleanor N
Essays in Public Economics

The first chapter sheds new light on the desirability of the minimum wage in the presence of optimal income taxation. Using a search-and-matching framework, I derive a novel condition that links the desirability of the minimum wage to three sufficient statistics: (1) the macro labor force participation response to the minimum wage by low skilled individuals; (2) the macro employment response to the minimum wage for low-skilled individuals; and (3) the welfare weight on low-skilled workers. This condition shows that the minimum wage is welfare improving if it pushes the labor market tightness – the ratio of the aggregate number of vacancies to low-skilled job seekers – closer to its efficient level. I estimate the first two sufficient statistics using an event study design, as well as state and federal minimum wage variation between 1979-2014. I estimate a macro participation elasticity of -0.24 and a macro employment elasticity of -0.32. With these estimates in hand, I simulate the welfare gains from introducing a minimum wage. The second chapter studies the effect of raising contribution limits on retirement saving by exploiting the ‘catch-up limit’ provision, a rule which allows those over the age of 50 to make higher IRA and 401(k) contributions than those under 50. Using a regression discontinuity design, I find that eligibility for ‘catch-up limits’ leads to a large increase in total tax-deferred contributions for those without access to a 401(k) plan. This is driven by a 25 percent increase in average IRA contributions and a 21 percent increase in the likelihood of making an IRA contribution, with no significant effects on overall 401(k) contributions. The findings suggest that, contrary to the neoclassical life-cycle model, the response to eligibility for ‘catch-up limits’ was not limited to constrained savers. The final chapter, joint with Michael Smart, studies the savings effect of Canadian Tax-Free Savings Account (TFSAs). Using a new instrumental variables strategy, we whether TFSA balances crowd-out saving in taxable financial assets and traditional tax-deferred plans. We find that TFSA balances crowd-out saving in taxable fixed income assets and have no statistically significant effect on balances in tax-deferred accounts.

Advisor: Kroft, Kory
Fluorophosphonium Chemistry: Applying Strategies Learned from Boron to Phosphorus

Since the inception of frustrated Lewis pair chemistry, interest in main group catalysts has undergone a resurgence. Central to the success of many main group systems is the pentafluorophenyl substituent, which provides both chemical stability and electrophilicity to the catalyst. Pentafluorophenyl substituents have been used with boranes, alanes and recently with fluorophosphonium cations. This thesis investigates a range of related aryl substituents applied to fluorophosphonium cations. Nitrene insertion into the bonds of borane substituents, including pentafluorophenyl groups, was used a means to tune the electrophilicity of main group systems. Sterically demanding perchlorophenyl substituents were employed to add protection to sensitive fluorophosphonium catalysts. The perchlorophenyl substituents also provided insight into the effect of mesomeric stabilization on electrophilicity of tetrahedral phosphorus systems. Perfluorobiphenyl and 3,5-bis(trifluoromethyl)phenyl substituents are also investigated as means of developing catalysts with electrophilicity exceeding that of pentafluorophenyl substituted phosphonium salts. Finally, binaphthyl substituents were applied to fluorophosphonium cations to generate chiral catalysts. The effect of constrained geometry was investigated using bridged binaphthyl substituted phosphorus species were investigated.

Keywords: Electrophilic
Lewis Acid
Phosphonium
Advisor: Stephan, Douglas
Three Essays in the Economics of Education

In principal, public education provides a child's key means of skill accumulation, irrespective of background. In practice, however, the actual performance of public schooling is a disappointment, with stakeholders concerned that the current state of public education heightens inequality and prepares students inadequately for the workforce or higher learning. This thesis develops and applies novel econometric techniques to highlight education policies that may increase student achievement and reduce the pervasive test score gaps that plague public education today. Chapter 1 sets out a new approach that enables me to credibly identify dynamic interactions among school inputs for the first time. Such an approach is rarely adopted in empirical research due to stringent requirements: in an observational setting, identifying dynamic interactions requires period-by-period randomization. I overcome this challenge by combining rich administrative data with a rule whereby students are held accountable only if there are forty or more students in their demographic group. The rule provides useful year-to-year variation, supplying the backbone of my identification strategy. I then estimate the technology structurally and consider the efficacy of alternative accountability schemes: conditioning on initial test scores rather than prior test scores can increase average achievement and reduce inequality. Chapter 2 proposes an approach that allows researchers to identify separate treatment components from a single discontinuity. As an application, I consider the discontinuity associated with class size caps -- a widespread education policy used to reduce class sizes. My approach exploits the asymmetry between school-grades entering versus exiting treatment to distinguish the pure effect of changes in class size from the effect of a newly-hired teacher. Using data from New York City, I find that class size reductions increase student achievement, though these gains are counteracted by the newly-hired teacher. Chapter 3 uses a regression discontinuity design to investigate the merits of decentralized public goods provision in the context of Title I, the largest U.S. federal education funding program. My results indicate that the negligible impact of Title I is caused by its centralized nature: in a decentralized form, Title I generates a substantial improvement in student achievement, particularly for the socioeconomically disadvantaged.

Keywords: Class Size
Dynamic Complementarities
Human Capital
Regression Discontinuity
School Accountability
School Finance
Advisor: McMillan, Robert
Synthesis of Boron, Silicon, and Phosphorus Lewis Acids and Frustrated Lewis Pair Complexes for C=O and C-F Bond Activations

The recent proliferation of main group catalysts and stoichiometric reagents useful in effecting transformations of organic molecules has been augmented by development of the chemistry of frustrated Lewis pairs (FLPs). In seeking to both complement and emulate the reactivity of transition metal catalysts, both the synthesis of new Lewis acids and FLPs and the discovery of new reactivity with organic substrates has been explored. Boron Lewis acids such as B(C6F5)3 and electrophilic borenium cations are among the most commonly employed main group catalysts, particularly for the hydrogenation of unsaturated bonds. The first chapter of this thesis details explorations in modulating the Lewis acidity of neutral and cationic boron electrophiles by tuning phosphinimine and phosphine-amine ligands. A family of compounds featuring a P-N-B motif are presented. In seeking to broaden the range of main group catalysts, phosphorus Lewis acids have been explored. The third and fourth chapters presented herein detail the synthesis and catalytic activity of electrophilic phosphonium cations (EPCs). Synthesis of a chloride-substituted dication, and ferrocenyl-based mono- and dications are described, with a particular emphasis on their catalytic activity in the deoxygenation of ketones. The fifth chapter details the synthesis of phosphorus cations which attempt to model intermediates in EPC-mediated catalysis. Silylium cations are strongly fluorophilic and have previously been shown to cleave aliphatic C-F bonds. The final chapter presents examples of silylium cations in combination with weak phosphine Lewis bases for the selective cleavage of one C-F bond of an aryl-CF3 functionality. The FLP-captured PhCF2 is then converted to PhCF2H, completing a formal hydrodefluorination process of PhCF3 to PhCF2H. Analogous reactivity is observed with aryl-CF2 compounds.

Keywords: Catalysis
Inorganic synthesis
Advisor: Stephan, Douglas W
Techniques for Constructing Efficient Lock-free Data Structures

Building a library of concurrent data structures is an essential way to simplify the difficult task of developing concurrent software. Lock-free data structures, in which processes can help one another to complete operations, offer the following progress guarantee: If processes take infinitely many steps, then infinitely many operations are performed. Handcrafted lock-free data structures can be very efficient, but are notoriously difficult to implement. We introduce numerous tools that support the development of efficient lock-free data structures, and especially trees. We address the difficulty of using single-word compare-and-swap (CAS) to develop lock-free graph-based data structures by introducing multiword synchronization primitives called LLX and SCX. These primitives fall between multi-compare-single-swap and full multiword-CAS in expressiveness, and can be implemented much more efficiently than multiword-CAS. We use them to implement a tree update template that can be followed to produce lock-free implementations of arbitrary updates in down-trees, and use this template to produce the first lock-free implementations of several advanced trees: chromatic search trees, relaxed AVL trees, and relaxed (a,b)-trees. We also introduce a new variant of a B-tree, called a relaxed B-slack tree, which has significantly better worst-case space complexity, and produce a lock-free implementation using our template. In these implementations, operations dynamically allocate memory for nodes. Additionally, in our implementation of LLX and SCX, each SCX operation allocates a descriptor, which contains information that another process can use to help the SCX operation complete. These implementations must perform dynamic lock-free memory reclamation, but traditional lock-free memory reclamation algorithms are either inefficient or cannot be used with our implementations. So, we introduce a fast epoch-based reclamation (EBR) algorithm called DEBRA+, which is the first lock-free EBR algorithm that can be used with trees. We also devise two techniques for accelerating lock-free data structure implementations. Using the first technique, we can efficiently eliminate dynamic allocation and reclamation of descriptors in SCX, and a large class of other algorithms. Using the second, we exploit hardware transactional memory support in modern processors to produce accelerated implementations of the template.

Keywords: Balanced search tree
Concurrency
Data structure
Lock-free
Lock-freedom
Multithreading
Advisor: Ellen, Faith
Applications of algebraic microlocal analysis in symplectic geometry and representation theory

This thesis investigates applications of microlocal geometry in both representation theory and symplectic geometry. Accordingly, there are two bodies of work contained herein. The first part of this thesis investigates a conjectural geometrization of local Arthur packets. These packets of representations of a p-adic group were invented by Arthur for the purpose of classifying the automorphic discrete spectrum of special orthogonal and symplectic groups. While their existence has been established, an explicit construction of local Arthur packets remains difficult. In the case of real groups, Adams, Barbasch, and Vogan showed how one can use a geometrization of the local Langlands correspondence to construct packets of equivariant D-modules that satisfy similar endoscopic transfer properties as the ones defining Arthur packets. We classify the contents of these “microlocal” packets in the analogue of these varieties for p-adic groups, under certain restrictions, for a plethora of split classical groups. The goal of the second part of this thesis is to find a way to make sense of the Duistermaat-Heckman function for a Hamiltonian action of a compact torus on an infinite dimensional symplectic manifold. We show that the Duistermaat-Heckman theorem can be understood in the language of hyperfunction theory, then apply this generalization to study the Hamiltonian T x S 1 action on ΩSU(2). The essential reason for introducing hyperfunction theory is that the local contribution to the Duistermaat-Heckman polynomial near the image of a fixed point is a Green's function for an infinite order differential equation. Since infinite order differential operators do not act on Schwarz distributions, we are forced to use this more general theory.

Keywords: A-packet
Duistermaat
hyperfunction
Langlands
representation theory
Advisor: Jeffrey, Lisa C
Cunningham, Clifton
Application and refinement of fluorescence spectroscopy for organic matter characterization in drinking water

This research examined the use and advancement of fluorescence spectroscopy as an organic characterization method in drinking water treatment, providing novel insight into the performance of and fundamental mechanisms of water treatment processes. Using fluorescence spectroscopy coupled with analysis techniques including parallel factors analysis (PARAFAC) and peak shifts, biofiltration was found to have variable impact on individual fluorophores. The fluorescence method identified production of humic-like matter by the microbial communities, ultimately resulting in a unique treated organic character of the treated water. Through correlations with formation potentials of halogenated furanones, polysaccharides were identified as possible precursors. Pre-oxidation, was suggested to result in increased proportionality of carbonyl-containing functional groups and greater carbon oxidative state. A continuous fluorescence system was developed as part of this research and implemented in two studies focused on fouling mitigation of ultrafiltration (UF) membranes. A full-scale study was conducted that continuously monitored membrane feed water organic character. Utilizing the continuous fluorescence, improved prediction accuracy of membrane fouling was found using a neural network approach. A second study, conducted at bench-scale focused on understanding the role of organic surface changes and irreversible fouling potential. Low coagulant doses (

Keywords: Drinking water treatment
Environmental monitoring
Fluorescence spectroscopy
Machine learning
Natural organic matter
Water quality
Advisor: Andrews, Robert C
Legge, Raymond L
Norm-square localization for Hamiltonian LG-spaces

In this thesis we prove norm-square localization formulas for two invariants of Hamiltonian loop group spaces: twisted Duistermaat-Heckman distributions and a K-theoretic `quantization'. The terms in the formulas are indexed by the components of the critical set of the norm-square of the moment map. These formulas are analogous to results proved by Paradan in the case of Hamiltonian G-spaces. An important application of the norm-square localization formula (for the quantization) is to prove that the multiplicity of the minimal level k representation in the quantization is a quasi-polynomial function of k. This is closely related to the [Q,R]=0 Theorem of Alekseev-Meinrenken-Woodward for Hamiltonian loop group spaces.

Keywords: index theory
localization
loop group
quantization
symplectic geometry
Advisor: Meinrenken, Eckhard
Ultrastructural Analysis of the Role of Voltage-Gated Calcium Channel Intracellular Domains in Synaptic Vesicle Tethering at Presynaptic Terminals

Chemical synaptic transmission is the main basis by which neurons convey information. This transmission is mediated by the fusion of synaptic vesicles (SVs) and the release of their neurotransmitter payloads across the synapse from a presynaptic neuron onto the receptors of a postsynaptic cell. In response to a depolarizing action potential, voltage-gated calcium channels (CaVs) open and allow the influx of calcium ions (Ca2+) into the presynaptic terminal which triggers the fusion of SVs with the active zone membrane (AZ). Evidence that fusion can be gated by the Ca2+ influx from a single CaV suggests a close coupling of SVs and CaVs likely connected by molecular tethers (Stanley, 1993). We developed a method to easily visualize tethers under electron microscopy (EM) through the osmotic rupture of isolated presynaptic terminals (SSM ghosts) which flushes out obscuring organelles and structures. We observed two classes of SV-to-AZ filaments: SVs within 45 nm of the AZ were often observed to be tethered by multiple, short filaments while SVs beyond 45 nm were tethered invariably by single, long filaments of

Keywords: calcium channel
presynaptic
synaptic vesicle
tether
tethering
transmitter release
Advisor: Stanley, Elise F