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Essays on Learning and Econometrics
Get PDFThis dissertation consists of two essays that focus on learning under state uncertainty and econometric applications for it, in which agents learn hidden state variables from their noisy measures sequentially.
In Chapter 2, "Nonparametric Learning Rules from Bandit Experiments: The Eyes Have It!", which is coauthored with Yingyao Hu and Matthew Shum, we assess, in a model-free manner, subjects' belief dynamics in a two-armed bandit learning experiment. A novel feature of our approach is to supplement the choice and reward data with subjects' eye movements during the experiment to pin down estimates of subjects' beliefs. Estimates show that subjects are more reluctant to "update down" following unsuccessful choices, than "update up" following successful choices. The profits from following the estimated learning and decision rules are smaller (by about 25% of typical experimental earnings) than what would be obtained from an fully rational Bayesian learning model, but comparable to the profits from alternative non-Bayesian learning models, including reinforcement learning and a simple "win-stay" choice heuristic.
In Chapter 3, I examine the optimal learning models for predicting price dynamics under outlier risk. Two kinds of outlier risk in price processes are considered here; A price process in which outliers occur as its fundamental value has changed, and that with little fundamental change. In the latter process outliers occur as observation error, which are often referred as price anomalies in behavioral finance. The two optimal learning models are characterized with non-Gaussian Kalman filter as Bayesian reinforcement learning and are solved numerically using sequential Monte Carlo sampling. Several key features are summarized in their learning rate and prediction error; The learning rate with outlier risk in fundamental value is a monotonically increasing function of absolute value of prediction error, while the learning rates with outlier risk in observation noise is a monotonically decreasing function. Interestingly, the uncertainly of the learning is seemingly identical among the two models, having a hump-shaped function of absolute value of prediction error.</p
The Physics of Ultracold Neutrons and Fierz Interference in Beta Decay
Get PDFtype of reflector that directs UCN upward in to vertical paths. Next we examine UCN passing through thin, multilayered foils. In the remaining sections we investigate the so-called Fierz interference term of free neutron beta decay, denoted bn. It is theorized that contributions to scalar and tensor interactions from physics beyond the Standard Model could be detectable in the spectrum of neutron beta decay, manifest as a nonzero value for bn. We investigate three techniques for measuring bn. The first is to use the primordial helium abundance fraction and compare that to predictive Big Bang nucleosynthesis calculations. Second we extract bn from the spectral shape generated by the 2010 data set of the UCNA experiment. Third, we discuss progress toward constructing the UCNb experimental prototype. We present the design of this new experiment that uses the UCN source at LANSCE for measuring bn, in which UCN are guided into a shielded 4π calorimeter where they are stored and decay. From Big Bang nucleosynthesis we can place the limit 0.021 < bn < 0.277 (90\% C.L.) on the neutron Fierz term and from the UCNA 2010 data we set -0.044 < bn < 0.218 (90\% C.L.).</p
Probing the Roles of Receptor Structure, Drug-Receptor Interactions, and Receptor Crosstalk in Ligand-Gated Ion Channel Function
Get PDFLigand-gated ion channels are multi-subunit transmembrane proteins that play crucial roles in synaptic transmission in the nervous system. These include the Cys-loop receptor superfamily, the ionotropic glutamate receptor (iGluR) family, and the purinergic P2X receptor family. Binding of specific neurotransmitters at the ligand-binding site triggers a series of conformational changes that ultimately leads to ion channel opening. This dissertation describes three molecular-scale functional studies on these receptors.
The first project (Chapter 2) describes structure-function studies of the conserved Phe-Pro motif in the Cys loop of the nicotinic acetylcholine receptor (nAChR) of the Cys-loop superfamily. Both residues were substituted with natural and unnatural amino acids. A strong interaction between the Phe and Pro residues is evident, as is a preference for aromaticity at the Phe site. Hydrophobicity is preferred at both sites. A correlation between receptor function and the cis bias at the proline backbone suggests a significant role for the cis proline conformer in receptor function.
The second project (Chapter 3) concerns the key binding interaction of memantine, a prescribed drug for Alzheimer’s disease, on the N-methyl-D-aspartate (NMDA) receptor of the iGluR family. The data suggest that the special property of memantine as an NMDA receptor blocker stems from the presence of the two methyl groups and a proper shape-matching to the binding site. Comparing affinities of memantine and amantadine, a structurally related drug, in response to pore mutations allows an identification of the methyl group binding pockets on the NMDA channel pore.
The final project (Chapter 4) involves a study of inhibitory crosstalk between two families of ion channels: α6β4-containing nAChRs and P2X receptors. When these two distinct receptors are co-expressed, their properties are modulated from their normal behavior when expressed alone. The effect is constitutive and does not require channel activation. When they are co-activated by their respective agonists, the observed current is smaller than the sum of the currents evoked by individual application of their agonists. This functional interaction between these nicotinic and purinergic receptors in dorsal root ganglion neurons is proposed to be involved in pain sensation.</p
Ring-Opening Metathesis of Bulky Norbornene Monomers and the Radical-Mediated Hydrophosphonation of Olefins
Get PDFThis thesis discusses two major topics: the ring-opening metathesis polymerization (ROMP) of bulky monomers and the radical-mediated hydrophosphonation of olefins. The research into the ROMP of bulky monomers is further divided into three chapters: wedge-shaped monomers, the alternating copolymerization of 1-methyloxanorbornene derivatives with cyclooctene, and the kinetic resolution polymerization of 1-methyloxanorbornene derivatives. The wedge-shaped monomers can be polymerized into diblock copolymers that possess photonic crystal properties. The alternating copolymerization of 1-methyloxanorbornene derivatives with cyclooctene is performed with > 90% alternation via two different routes: typical alternating copolymerization and a sequence editing approach. The kinetic resolution polymerization of these same 1-methyloxanorbornene monomers achieves only modest selectivity (S=4), but there is evidence that the growing polymer chain forms a helix that influences the selectivity of the resolution. The last topic is the radical-mediated hydrophosphonation of olefins. This synthetic method provides access to Wittig reagents that are capable of highly cis-selective olefinations of aldehydes
Characterization of Exoplanet Atmospheres: Spectral Retrieval and Chemistry
Get PDFThe study of exoplanets is rapidly evolving into an important and exciting field of its own. My investigations over the past half-decade have focused on understanding just a small sliver of what they are trying to tell us. That small sliver is their atmospheres. Atmospheres are the buffer between the bulk planet and the vacuum of space. The atmosphere is an important component of a planet as it is the most readily observable and contains the most information about the physical processes that can occur in a planet. I have focused on two aspects of exoplanetary atmospheres. First, I aimed to understand the chemical mechanisms that control the atmospheric abundances. Second, I focused on interpreting exoplanet atmospheric spectra and what they tell us about the temperatures and compositions through inverse modeling. Finally, I interpreted the retrieved temperature and abundances from inverse modeling in the context of chemical disequilibrium in the planetary atmospheres
Proteomic Analysis of the Cdc48/Ubx Network Identifies a Role for Ubx2 in the Regulation of Lipid Biosynthesis
Get PDFCdc48/p97 is an essential, highly abundant hexameric member of the AAA (ATPase associated with various cellular activities) family. It has been linked to a variety of processes throughout the cell but it is best known for its role in the ubiquitin proteasome pathway. In this system it is believed that Cdc48 behaves as a segregase, transducing the chemical energy of ATP hydrolysis into mechanical force to separate ubiquitin-conjugated proteins from their tightly-bound partners.
Current models posit that Cdc48 is linked to its substrates through a variety of adaptor proteins, including a family of seven proteins (13 in humans) that contain a Cdc48-binding UBX domain. As such, due to the complexity of the network of adaptor proteins for which it serves as the hub, Cdc48/p97 has the potential to exert a profound influence on the ubiquitin proteasome pathway. However, the number of known substrates of Cdc48/p97 remains relatively small, and smaller still is the number of substrates that have been linked to a specific UBX domain protein. As such, the goal of this dissertation research has been to discover new substrates and better understand the functions of the Cdc48 network. With this objective in mind, we established a proteomic screen to assemble a catalog of candidate substrate/targets of the Ubx adaptor system.
Here we describe the implementation and optimization of a cutting-edge quantitative mass spectrometry method to measure relative changes in the Saccharomyces cerevisiae proteome. Utilizing this technology, and in order to better understand the breadth of function of Cdc48 and its adaptors, we then performed a global screen to identify accumulating ubiquitin conjugates in cdc48-3 and ubxΔ mutants. In this screen different ubx mutants exhibited reproducible patterns of conjugate accumulation that differed greatly from each other, pointing to various unexpected functional specializations of the individual Ubx proteins.
As validation of our mass spectrometry findings, we then examined in detail the endoplasmic-reticulum bound transcription factor Spt23, which we identified as a putative Ubx2 substrate. In these studies ubx2Δ cells were deficient in processing of Spt23 to its active p90 form, and in localizing p90 to the nucleus. Additionally, consistent with reduced processing of Spt23, ubx2Δ cells demonstrated a defect in expression of their target gene OLE1, a fatty acid desaturase. Overall, this work demonstrates the power of proteomics as a tool to identify new targets of various pathways and reveals Ubx2 as a key regulator lipid membrane biosynthesis.</p
Completions of ε-Dense Partial Latin Squares
Get PDFA classical question in combinatorics is the following: given a partial Latin square , when can we complete to a Latin square ? In this paper, we investigate the class of textbf{-dense partial Latin squares}: partial Latin squares in which each symbol, row, and column contains no more than -many nonblank cells. Based on a conjecture of Nash-Williams, Daykin and H"aggkvist conjectured that all -dense partial Latin squares are completable. In this paper, we will discuss the proof methods and results used in previous attempts to resolve this conjecture, introduce a novel technique derived from a paper by Jacobson and Matthews on generating random Latin squares, and use this novel technique to study -dense partial Latin squares that contain no more than filled cells in total.
In Chapter 2, we construct completions for all -dense partial Latin squares containing no more than filled cells in total, given that epsilon < frac{1}{12}, delta < frac{ left(1-12epsilonright)^{2}}{10409}. In particular, we show that all -dense partial Latin squares are completable. In Chapter 4, we augment these results by roughly a factor of two using some probabilistic techniques. These results improve prior work by Gustavsson, which required , as well as Chetwynd and H"aggkvist, which required , even and greater than .
If we omit the probabilistic techniques noted above, we further show that such completions can always be found in polynomial time. This contrasts a result of Colbourn, which states that completing arbitrary partial Latin squares is an NP-complete task. In Chapter 3, we strengthen Colbourn's result to the claim that completing an arbitrary -dense partial Latin square is NP-complete, for any .
Colbourn's result hinges heavily on a connection between triangulations of tripartite graphs and Latin squares. Motivated by this, we use our results on Latin squares to prove that any tripartite graph such that
begin{itemize}
item ,
item For every vertex , and
item
end{itemize}
admits a triangulation, if epsilon < frac{1}{132}, delta < frac{(1 -132epsilon)^2 }{83272}. In particular, this holds when .
This strengthens results of Gustavsson, which requires .
In an unrelated vein, Chapter 6 explores the class of textbf{quasirandom graphs}, a notion first introduced by Chung, Graham and Wilson cite{chung1989quasi} in 1989. Roughly speaking, a sequence of graphs is called "quasirandom"' if it has a number of properties possessed by the random graph, all of which turn out to be equivalent. In this chapter, we study possible extensions of these results to random -edge colorings, and create an analogue of Chung, Graham and Wilson's result for such colorings.</p
Earth-Abundant Materials for Solar Hydrogen Generation
Get PDFA critical challenge for the 21st century is shifting from the predominant use of fossil fuels to renewables for energy. Among many options, sunlight is the only single renewable resource with sufficient abundance to replace most or all of our current fossil energy use. However, existing photovoltaic and solar thermal technologies cannot be scaled infinitely due to the temporal and geographic intermittency of sunlight. Therefore efficient and inexpensive methods for storage of solar energy in a dense medium are needed in order to greatly increase utilization of the sun as a primary resource. For this purpose we have proposed an artificial photosynthetic system consisting of semiconductors, electrocatalysts, and polymer membranes to carry out photoelectrochemical water splitting as a method for solar fuel generation.
This dissertation describes efforts over the last five years to develop critical semiconductor and catalyst components for efficient and scalable photoelectrochemical hydrogen evolution, one of the half reactions for water splitting. We identified and developed Ni–Mo alloy and Ni2P nanoparticles as promising earth-abundant electrocatalysts for hydrogen evolution. We thoroughly characterized Ni–Mo alloys alongside Ni and Pt catalysts deposited onto planar and structured Si light absorbers for solar hydrogen generation. We sought to address several key challenges that emerged in the use of non-noble catalysts for solar fuels generation, resulting in the synthesis and characterization of Ni–Mo nanopowder for use in a new photocathode device architecture. To address the mismatch in stability between non-noble metal alloys and Si absorbers, we also synthesized and characterized p-type WSe2 as a candidate light absorber alternative to Si that is stable under acidic and alkaline conditions.</p
A Study of Protein Targeting Reveals Insights into Mitigating Protein Aggregation
Get PDFA unique chloroplast Signal Recognition Particle (SRP) in green plants is primarily dedicated to the post-translational targeting of light harvesting chlorophyll-a/b binding (LHC) proteins. Our study of the thermodynamics and kinetics of the GTPases of the system demonstrates that GTPase complex assembly and activation are highly coupled in the chloroplast GTPases, suggesting they may forego the GTPase activation step as a key regulatory point. This reflects adaptations of the chloroplast SRP to the delivery of their unique substrate protein. Devotion to one highly hydrophobic family of proteins also may have allowed the chloroplast SRP system to evolve an efficient chaperone in the cpSRP43 subunit. To understand the mechanism of disaggregation, we showed that LHC proteins form micellar, disc-shaped aggregates that present a recognition motif (L18) on the aggregate surface. Further molecular genetic and structure-activity analyses reveal that the action of cpSRP43 can be dissected into two steps: (i) initial recognition of L18 on the aggregate surface; and (ii) aggregate remodeling, during which highly adaptable binding interactions of cpSRP43 with hydrophobic transmembrane domains of the substrate protein compete with the packing interactions within the aggregate. We also tested the adaptability of cpSRP43 for alternative substrates, specifically in attempts to improve membrane protein expression and inhibition of amyloid beta fibrillization. These preliminary results attest to cpSRP43’s potential as a molecular chaperone and provides the impetus for further engineering endeavors to address problems that stem from protein aggregation
Sensor Networks for Geospatial Event Detection - Theory and Applications
Get PDFThis thesis presents theories, analyses, and algorithms for detecting and estimating parameters of geospatial events with today's large, noisy sensor networks. A geospatial event is initiated by a significant change in the state of points in a region in a 3-D space over an interval of time. After the event is initiated it may change the state of points over larger regions and longer periods of time.
Networked sensing is a typical approach for geospatial event detection. In contrast to traditional sensor networks comprised of a small number of high quality (and expensive) sensors, trends in personal computing devices and consumer electronics have made it possible to build large, dense networks at a low cost. The changes in sensor capability, network composition, and system constraints call for new models and algorithms suited to the opportunities and challenges of the new generation of sensor networks.
This thesis offers a single unifying model and a Bayesian framework for analyzing different types of geospatial events in such noisy sensor networks. It presents algorithms and theories for estimating the speed and accuracy of detecting geospatial events as a function of parameters from both the underlying geospatial system and the sensor network. Furthermore, the thesis addresses network scalability issues by presenting rigorous scalable algorithms for data aggregation for detection. These studies provide insights to the design of networked sensing systems for detecting geospatial events.
In addition to providing an overarching framework, this thesis presents theories and experimental results for two very different geospatial problems: detecting earthquakes and hazardous radiation. The general framework is applied to these specific problems, and predictions based on the theories are validated against measurements of systems in the laboratory and in the field.</p