This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

Displaying 1 - 10 of 98
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Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a

The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The ribosome is a ribozyme and central to the biosynthesis of proteins in all organisms. It has a strong bias against non-alpha-L-amino acids, such as alpha-D-amino acids and beta-amino acids. Additionally, the ribosome is only able to incorporate one amino acid in response to one codon. It has been demonstrated

The ribosome is a ribozyme and central to the biosynthesis of proteins in all organisms. It has a strong bias against non-alpha-L-amino acids, such as alpha-D-amino acids and beta-amino acids. Additionally, the ribosome is only able to incorporate one amino acid in response to one codon. It has been demonstrated that reengineering of the peptidyltransferase center (PTC) of the ribosome enabled the incorporation of both alpha-D-amino acids and beta-amino acids into full length protein. Described in Chapter 2 are five modified ribosomes having modifications in the peptidyltrasnferase center in the 23S rRNA. These modified ribosomes successfully incorporated five different beta-amino acids (2.1 - 2.5) into E. coli dihydrofolate reductase (DHFR). The second project (Chapter 3) focused on the study of the modified ribosomes facilitating the incorporation of the dipeptide glycylphenylalanine (3.25) and fluorescent dipeptidomimetic 3.26 into DHFR. These ribosomes also had modifications in the peptidyltransferase center in the 23S rRNA of the 50S ribosomal subunit. The modified DHFRs having beta-amino acids 2.3 and 2.5, dipeptide glycylphenylalanine (3.25) and dipeptidomimetic 3.26 were successfully characterized by the MALDI-MS analysis of the peptide fragments produced by "in-gel" trypsin digestion of the modified proteins. The fluorescent spectra of the dipeptidomimetic 3.26 and modified DHFR having fluorescent dipeptidomimetic 3.26 were also measured. The type I and II DNA topoisomerases have been firmly established as effective molecular targets for many antitumor drugs. A "classical" topoisomerase I or II poison acts by misaligning the free hydroxyl group of the sugar moiety of DNA and preventing the reverse transesterfication reaction to religate DNA. There have been only two classes of compounds, saintopin and topopyrones, reported as dual topoisomerase I and II poisons. Chapter 4 describes the synthesis and biological evaluation of topopyrones. Compound 4.10, employed at 20 µM, was as efficient as 0.5 uM camptothecin, a potent topoisomerase I poison, in stabilizing the covalent binary complex (~30%). When compared with a known topoisomerase II poison, etoposide (at 0.5 uM), topopyorone 4.10 produced similar levels of stabilized DNA-enzyme binary complex (~34%) at 5 uM concentration.
ContributorsMaini, Rumit (Author) / Hecht, Sidney M. (Thesis advisor) / Gould, Ian (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Photosynthesis, one of the most important processes in nature, has provided an energy basis for nearly all life on Earth, as well as the fossil fuels we use today to power modern society. This research aims to mimic the photosynthetic process of converting incident solar energy into chemical potential energy

Photosynthesis, one of the most important processes in nature, has provided an energy basis for nearly all life on Earth, as well as the fossil fuels we use today to power modern society. This research aims to mimic the photosynthetic process of converting incident solar energy into chemical potential energy in the form of a fuel via systems capable of carrying out photo-induced electron transfer to drive the production of hydrogen from water. Herein is detailed progress in using photo-induced stepwise electron transfer to drive the oxidation of water and reduction of protons to hydrogen. In the design, use of more blue absorbing porphyrin dyes to generate high-potential intermediates for oxidizing water and more red absorbing phthalocyanine dyes for forming the low potential charge needed for the production of hydrogen have been utilized. For investigating water oxidation at the photoanode, high potential porphyrins such as, bis-pyridyl porphyrins and pentafluorophenyl porphyrins have been synthesized and experiments have aimed at the co-immobilization of this dye with an IrO2-nH2O catalyst on TiO2. To drive the cathodic reaction of the water splitting photoelectrochemical cell, utilization of silicon octabutoxy-phthalocyanines have been explored, as they offer good absorption in the red to near infrared, coupled with low potential photo-excited states. Axially and peripherally substituted phthalocyanines bearing carboxylic anchoring groups for the immobilization on semiconductors such as TiO2 has been investigated. Ultimately, this work should culminate in a photoelectrochemical cell capable of splitting water to oxygen and hydrogen with the only energy input from light. A series of perylene dyes bearing multiple semi-conducting metal oxide anchoring groups have been synthesized and studied. Results have shown interfacial electron transfer between these perylenes and TiO2 nanoparticles encapsulated within reverse micelles and naked nanoparticles. The binding process was followed by monitoring the hypsochromic shift of the dye absorption spectra over time. Photoinduced electron transfer from the singlet excited state of the perylenes to the TiO2 conduction band is indicated by emission quenching of the TiO2-bound form of the dyes and confirmed by transient absorption measurements of the radical cation of the dyes and free carriers (injected electrons) in the TiO2.
ContributorsBergkamp, Jesse J (Author) / Moore, Ana L (Thesis advisor) / Mariño-Ochoa, Ernesto (Thesis advisor) / Gust, Devens J (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The biological and chemical diversity of protein structure and function can be greatly expanded by position-specific incorporation of non-natural amino acids bearing a variety of functional groups. Non-cognate amino acids can be incorporated into proteins at specific sites by using orthogonal aminoacyl-tRNA synthetase/tRNA pairs in conjunction with nonsense, rare, or

The biological and chemical diversity of protein structure and function can be greatly expanded by position-specific incorporation of non-natural amino acids bearing a variety of functional groups. Non-cognate amino acids can be incorporated into proteins at specific sites by using orthogonal aminoacyl-tRNA synthetase/tRNA pairs in conjunction with nonsense, rare, or 4-bp codons. There has been considerable progress in developing new types of amino acids, in identifying novel methods of tRNA aminoacylation, and in expanding the genetic code to direct their position. Chemical aminoacylation of tRNAs is accomplished by acylation and ligation of a dinucleotide (pdCpA) to the 3'-terminus of truncated tRNA. This strategy allows the incorporation of a wide range of natural and unnatural amino acids into pre-determined sites, thereby facilitating the study of structure-function relationships in proteins and allowing the investigation of their biological, biochemical and biophysical properties. Described in Chapter 1 is the current methodology for synthesizing aminoacylated suppressor tRNAs. Aminoacylated suppressor tRNACUAs are typically prepared by linking pre-aminoacylated dinucleotides (aminoacyl-pdCpAs) to 74 nucleotide (nt) truncated tRNAs (tRNA-COH) via a T4 RNA ligase mediated reaction. Alternatively, there is another route outlined in Chapter 1 that utilizes a different pre-aminoacylated dinucleotide, AppA. This dinucleotide has been shown to be a suitable substrate for T4 RNA ligase mediated coupling with abbreviated tRNA-COHs for production of 76 nt aminoacyl-tRNACUAs. The synthesized suppressor tRNAs have been shown to participate in protein synthesis in vitro, in an S30 (E. coli) coupled transcription-translation system in which there is a UAG codon in the mRNA at the position corresponding to Val10. Chapter 2 describes the synthesis of two non-proteinogenic amino acids, L-thiothreonine and L-allo-thiothreonine, and their incorporation into predetermined positions of a catalytically competent dihydrofolate reductase (DHFR) analogue lacking cysteine. Here, the elaborated proteins were site-specifically derivitized with a fluorophore at the thiothreonine residue. The synthesis and incorporation of phosphorotyrosine derivatives into DHFR is illustrated in Chapter 3. Three different phosphorylated tyrosine derivatives were prepared: bis-nitrobenzylphosphoro-L-tyrosine, nitrobenzylphosphoro-L-tyrosine, and phosphoro-L-tyrosine. Their ability to participate in a protein synthesis system was also evaluated.
ContributorsNangreave, Ryan Christopher (Author) / Hecht, Sidney M. (Thesis advisor) / Yan, Hao (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Automating aspects of biocuration through biomedical information extraction could significantly impact biomedical research by enabling greater biocuration throughput and improving the feasibility of a wider scope. An important step in biomedical information extraction systems is named entity recognition (NER), where mentions of entities such as proteins and diseases are located

Automating aspects of biocuration through biomedical information extraction could significantly impact biomedical research by enabling greater biocuration throughput and improving the feasibility of a wider scope. An important step in biomedical information extraction systems is named entity recognition (NER), where mentions of entities such as proteins and diseases are located within natural-language text and their semantic type is determined. This step is critical for later tasks in an information extraction pipeline, including normalization and relationship extraction. BANNER is a benchmark biomedical NER system using linear-chain conditional random fields and the rich feature set approach. A case study with BANNER locating genes and proteins in biomedical literature is described. The first corpus for disease NER adequate for use as training data is introduced, and employed in a case study of disease NER. The first corpus locating adverse drug reactions (ADRs) in user posts to a health-related social website is also described, and a system to locate and identify ADRs in social media text is created and evaluated. The rich feature set approach to creating NER feature sets is argued to be subject to diminishing returns, implying that additional improvements may require more sophisticated methods for creating the feature set. This motivates the first application of multivariate feature selection with filters and false discovery rate analysis to biomedical NER, resulting in a feature set at least 3 orders of magnitude smaller than the set created by the rich feature set approach. Finally, two novel approaches to NER by modeling the semantics of token sequences are introduced. The first method focuses on the sequence content by using language models to determine whether a sequence resembles entries in a lexicon of entity names or text from an unlabeled corpus more closely. The second method models the distributional semantics of token sequences, determining the similarity between a potential mention and the token sequences from the training data by analyzing the contexts where each sequence appears in a large unlabeled corpus. The second method is shown to improve the performance of BANNER on multiple data sets.
ContributorsLeaman, James Robert (Author) / Gonzalez, Graciela (Thesis advisor) / Baral, Chitta (Thesis advisor) / Cohen, Kevin B (Committee member) / Liu, Huan (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
As the genetic information storage vehicle, deoxyribonucleic acid (DNA) molecules are essential to all known living organisms and many viruses. It is amazing that such a large amount of information about how life develops can be stored in these tiny molecules. Countless scientists, especially some biologists, are trying to decipher

As the genetic information storage vehicle, deoxyribonucleic acid (DNA) molecules are essential to all known living organisms and many viruses. It is amazing that such a large amount of information about how life develops can be stored in these tiny molecules. Countless scientists, especially some biologists, are trying to decipher the genetic information stored in these captivating molecules. Meanwhile, another group of researchers, nanotechnologists in particular, have discovered that the unique and concise structural features of DNA together with its information coding ability can be utilized for nano-construction efforts. This idea culminated in the birth of the field of DNA nanotechnology which is the main topic of this dissertation. The ability of rationally designed DNA strands to self-assemble into arbitrary nanostructures without external direction is the basis of this field. A series of novel design principles for DNA nanotechnology are presented here, from topological DNA nanostructures to complex and curved DNA nanostructures, from pure DNA nanostructures to hybrid RNA/DNA nanostructures. As one of the most important and pioneering fields in controlling the assembly of materials (both DNA and other materials) at the nanoscale, DNA nanotechnology is developing at a dramatic speed and as more and more construction approaches are invented, exciting advances will emerge in ways that we may or may not predict.
ContributorsHan, Dongran (Author) / Yan, Hao (Thesis advisor) / Liu, Yan (Thesis advisor) / Ros, Anexandra (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Data mining is increasing in importance in solving a variety of industry problems. Our initiative involves the estimation of resource requirements by skill set for future projects by mining and analyzing actual resource consumption data from past projects in the semiconductor industry. To achieve this goal we face difficulties like

Data mining is increasing in importance in solving a variety of industry problems. Our initiative involves the estimation of resource requirements by skill set for future projects by mining and analyzing actual resource consumption data from past projects in the semiconductor industry. To achieve this goal we face difficulties like data with relevant consumption information but stored in different format and insufficient data about project attributes to interpret consumption data. Our first goal is to clean the historical data and organize it into meaningful structures for analysis. Once the preprocessing on data is completed, different data mining techniques like clustering is applied to find projects which involve resources of similar skillsets and which involve similar complexities and size. This results in "resource utilization templates" for groups of related projects from a resource consumption perspective. Then project characteristics are identified which generate this diversity in headcounts and skillsets. These characteristics are not currently contained in the data base and are elicited from the managers of historical projects. This represents an opportunity to improve the usefulness of the data collection system for the future. The ultimate goal is to match the product technical features with the resource requirement for projects in the past as a model to forecast resource requirements by skill set for future projects. The forecasting model is developed using linear regression with cross validation of the training data as the past project execution are relatively few in number. Acceptable levels of forecast accuracy are achieved relative to human experts' results and the tool is applied to forecast some future projects' resource demand.
ContributorsBhattacharya, Indrani (Author) / Sen, Arunabha (Thesis advisor) / Kempf, Karl G. (Thesis advisor) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Contemporary online social platforms present individuals with social signals in the form of news feed on their peers' activities. On networks such as Facebook, Quora, network operator decides how that information is shown to an individual. Then the user, with her own interests and resource constraints selectively acts on a

Contemporary online social platforms present individuals with social signals in the form of news feed on their peers' activities. On networks such as Facebook, Quora, network operator decides how that information is shown to an individual. Then the user, with her own interests and resource constraints selectively acts on a subset of items presented to her. The network operator again, shows that activity to a selection of peers, and thus creating a behavioral loop. That mechanism of interaction and information flow raises some very interesting questions such as: can network operator design social signals to promote a particular activity like sustainability, public health care awareness, or to promote a specific product? The focus of my thesis is to answer that question. In this thesis, I develop a framework to personalize social signals for users to guide their activities on an online platform. As the result, we gradually nudge the activity distribution on the platform from the initial distribution p to the target distribution q. My work is particularly applicable to guiding collaborations, guiding collective actions, and online advertising. In particular, I first propose a probabilistic model on how users behave and how information flows on the platform. The main part of this thesis after that discusses the Influence Individuals through Social Signals (IISS) framework. IISS consists of four main components: (1) Learner: it learns users' interests and characteristics from their historical activities using Bayesian model, (2) Calculator: it uses gradient descent method to compute the intermediate activity distributions, (3) Selector: it selects users who can be influenced to adopt or drop specific activities, (4) Designer: it personalizes social signals for each user. I evaluate the performance of IISS framework by simulation on several network topologies such as preferential attachment, small world, and random. I show that the framework gradually nudges users' activities to approach the target distribution. I use both simulation and mathematical method to analyse convergence properties such as how fast and how close we can approach the target distribution. When the number of activities is 3, I show that for about 45% of target distributions, we can achieve KL-divergence as low as 0.05. But for some other distributions KL-divergence can be as large as 0.5.
ContributorsLe, Tien D (Author) / Sundaram, Hari (Thesis advisor) / Davulcu, Hasan (Thesis advisor) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
A clean and sustainable alternative to fossil fuels is solar energy. For efficient use of solar energy to be realized, artificial systems that can effectively capture and convert sunlight into a usable form of energy have to be developed. In natural photosynthesis, antenna chlorophylls and carotenoids capture sunlight and transfer

A clean and sustainable alternative to fossil fuels is solar energy. For efficient use of solar energy to be realized, artificial systems that can effectively capture and convert sunlight into a usable form of energy have to be developed. In natural photosynthesis, antenna chlorophylls and carotenoids capture sunlight and transfer the resulting excitation energy to the photosynthetic reaction center (PRC). Small reorganization energy, λ and well-balanced electronic coupling between donors and acceptors in the PRC favor formation of a highly efficient charge-separated (CS) state. By covalently linking electron/energy donors to acceptors, organic molecular dyads and triads that mimic natural photosynthesis were synthesized and studied. Peripherally linked free base phthalocyanine (Pc)-fullerene (C60) and a zinc (Zn) phthalocyanine-C60 dyads were synthesized. Photoexcitation of the Pc moiety resulted in singlet-singlet energy transfer to the attached C60, followed by electron transfer. The lifetime of the CS state was 94 ps. Linking C60 axially to silicon (Si) Pc, a lifetime of the CS state of 4.5 ns was realized. The exceptionally long-lived CS state of the SiPc-C60 dyad qualifies it for applications in solar energy conversion devices. A secondary electron donor was linked to the dyad to obtain a carotenoid (Car)-SiPc-C60 triad and ferrocene (Fc)-SiPc-C60 triad. Excitation of the SiPc moiety resulted in fast electron transfer from the Car or Fc secondary electron donors to the C60. The lifetime of the CS state was 17 ps and 1.2 ps in Car-SiPc-C60 and Fc-SiPc-C60, respectively. In Chapter 3, an efficient synthetic route that yielded regioselective oxidative porphyrin dimerization is presented. Using Cu2+ as the oxidant, meso-β doubly-connected fused porphyrin dimers were obtained in very high yields. Removal of the copper from the macrocycle affords a free base porphyrin dimer. This allows for exchange of metals and provides a route to a wider range of metallporphyrin dimers. In Chapter 4, the development of an efficient and an expedient route to bacteriopurpurin synthesis is discussed. Meso-10,20- diformylation of porphyrin was achieved and one-pot porphyrin diacrylate synthesis and cyclization to afford bacteriopurpurin was realized. The bacteriopurpurin had a reduction potential of - 0.85 V vs SCE and λmax, 845 nm.
ContributorsArero, Jaro (Author) / Gust, Devens (Thesis advisor) / Moore, Ana (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Solar energy is a promising alternative for addressing the world's current and future energy requirements in a sustainable way. Because solar irradiation is intermittent, it is necessary to store this energy in the form of a fuel so it can be used when required. The light-driven splitting of water into

Solar energy is a promising alternative for addressing the world's current and future energy requirements in a sustainable way. Because solar irradiation is intermittent, it is necessary to store this energy in the form of a fuel so it can be used when required. The light-driven splitting of water into oxygen and hydrogen (a useful chemical fuel) is a fascinating theoretical and experimental challenge that is worth pursuing because the advance of the knowledge that it implies and the availability of water and sunlight. Inspired by natural photosynthesis and building on previous work from our laboratory, this dissertation focuses on the development of water-splitting dye-sensitized photoelectrochemical tandem cells (WSDSPETCs). The design, synthesis, and characterization of high-potential porphyrins and metal-free phthalocyanines with phosphonic anchoring groups are reported. Photocurrents measured for WSDSPETCs made with some of these dyes co-adsorbed with molecular or colloidal catalysts on TiO2 electrodes are reported as well. To guide in the design of new molecules we have used computational quantum chemistry extensively. Linear correlations between calculated frontier molecular orbital energies and redox potentials were built and tested at multiple levels of theory (from semi-empirical methods to density functional theory). Strong correlations (with r2 values > 0.99) with very good predictive abilities (rmsd < 50 mV) were found when using density functional theory (DFT) combined with a continuum solvent model. DFT was also used to aid in the elucidation of the mechanism of the thermal relaxation observed for the charge-separated state of a molecular triad that mimics the photo-induced proton coupled electron transfer of the tyrosine-histidine redox relay in the reaction center of Photosystem II. It was found that the inclusion of explicit solvent molecules, hydrogen bonded to specific sites within the molecular triad, was essential to explain the observed thermal relaxation. These results are relevant for both advancing the knowledge about natural photosynthesis and for the future design of new molecules for WSDSPETCs.
ContributorsMéndez-Hernández, Dalvin D (Author) / Moore, Ana L (Thesis advisor) / Mujica, Vladimiro (Thesis advisor) / Gust, Devens J. (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2014