ASU Electronic Theses and Dissertations
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.
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- Creators: Pan, Rong
- Creators: Fromme, Petra
Description
Nowadays product reliability becomes the top concern of the manufacturers and customers always prefer the products with good performances under long period. In order to estimate the lifetime of the product, accelerated life testing (ALT) is introduced because most of the products can last years even decades. Much research has been done in the ALT area and optimal design for ALT is a major topic. This dissertation consists of three main studies. First, a methodology of finding optimal design for ALT with right censoring and interval censoring have been developed and it employs the proportional hazard (PH) model and generalized linear model (GLM) to simplify the computational process. A sensitivity study is also given to show the effects brought by parameters to the designs. Second, an extended version of I-optimal design for ALT is discussed and then a dual-objective design criterion is defined and showed with several examples. Also in order to evaluate different candidate designs, several graphical tools are developed. Finally, when there are more than one models available, different model checking designs are discussed.
ContributorsYang, Tao (Author) / Pan, Rong (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Borror, Connie (Committee member) / Rigdon, Steve (Committee member) / Arizona State University (Publisher)
Created2013
Description
There is a critical need for the development of clean and efficient energy sources. Hydrogen is being explored as a viable alternative to fuels in current use, many of which have limited availability and detrimental byproducts. Biological photo-production of H2 could provide a potential energy source directly manufactured from water and sunlight. As a part of the photosynthetic electron transport chain (PETC) of the green algae Chlamydomonas reinhardtii, water is split via Photosystem II (PSII) and the electrons flow through a series of electron transfer cofactors in cytochrome b6f, plastocyanin and Photosystem I (PSI). The terminal electron acceptor of PSI is ferredoxin, from which electrons may be used to reduce NADP+ for metabolic purposes. Concomitant production of a H+ gradient allows production of energy for the cell. Under certain conditions and using the endogenous hydrogenase, excess protons and electrons from ferredoxin may be converted to molecular hydrogen. In this work it is demonstrated both that certain mutations near the quinone electron transfer cofactor in PSI can speed up electron transfer through the PETC, and also that a native [FeFe]-hydrogenase can be expressed in the C. reinhardtii chloroplast. Taken together, these research findings form the foundation for the design of a PSI-hydrogenase fusion for the direct and continuous photo-production of hydrogen in vivo.
ContributorsReifschneider, Kiera (Author) / Redding, Kevin (Thesis advisor) / Fromme, Petra (Committee member) / Jones, Anne (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the rapid development of mobile sensing technologies like GPS, RFID, sensors in smartphones, etc., capturing position data in the form of trajectories has become easy. Moving object trajectory analysis is a growing area of interest these days owing to its applications in various domains such as marketing, security, traffic monitoring and management, etc. To better understand movement behaviors from the raw mobility data, this doctoral work provides analytic models for analyzing trajectory data. As a first contribution, a model is developed to detect changes in trajectories with time. If the taxis moving in a city are viewed as sensors that provide real time information of the traffic in the city, a change in these trajectories with time can reveal that the road network has changed. To detect changes, trajectories are modeled with a Hidden Markov Model (HMM). A modified training algorithm, for parameter estimation in HMM, called m-BaumWelch, is used to develop likelihood estimates under assumed changes and used to detect changes in trajectory data with time. Data from vehicles are used to test the method for change detection. Secondly, sequential pattern mining is used to develop a model to detect changes in frequent patterns occurring in trajectory data. The aim is to answer two questions: Are the frequent patterns still frequent in the new data? If they are frequent, has the time interval distribution in the pattern changed? Two different approaches are considered for change detection, frequency-based approach and distribution-based approach. The methods are illustrated with vehicle trajectory data. Finally, a model is developed for clustering and outlier detection in semantic trajectories. A challenge with clustering semantic trajectories is that both numeric and categorical attributes are present. Another problem to be addressed while clustering is that trajectories can be of different lengths and also have missing values. A tree-based ensemble is used to address these problems. The approach is extended to outlier detection in semantic trajectories.
ContributorsKondaveeti, Anirudh (Author) / Runger, George C. (Thesis advisor) / Mirchandani, Pitu (Committee member) / Pan, Rong (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2012
Description
The need for a renewable and sustainable light-driven energy source is the motivation for this work, which utilizes a challenging, yet practical and attainable bio-inspired approach to develop an artificial oxygen evolving complex, which builds upon the principles of the natural water splitting mechanism in oxygenic photosynthesis. In this work, a stable framework consisting of a three-dimensional DNA tetrahedron has been used for the design of a bio-mimic of the Oxygen-Evolving Complex (OEC) found in natural Photosystem II (PSII). PSII is a large protein complex that evolves all the oxygen in the atmosphere, but it cannot be used directly in artificial systems, as the light reactions lead to damage of one of Photosystem II's core proteins, D1, which has to be replaced every half hour in the presence of sunlight. The final goal of the project aims to build the catalytic center of the OEC, including the Mn4CaCl metal cluster and its protein environment in the stable DNA framework of a tetrahedron, which can subsequently be connected to a photo-stable artificial reaction center that performs light-induced charge separation. Regions of the peptide sequences containing Mn4CaCl ligation sites are implemented in the design of the aOEC (artificial oxygen-evolving complex) and are attached to sites within the tetrahedron to facilitate assembly. Crystals of the tetrahedron have been obtained, and X-ray crystallography has been used for characterization. As a proof of concept, metal-binding peptides have been coupled to the DNA tetrahedron which allowed metal-containing porphyrins, specifically Fe(III) meso-Tetra(4-sulfonatophenyl) porphyrin chloride, to be encapsulated inside the DNA-tetrahedron. The porphyrins were successfully assembled inside the tetrahedron through coordination of two terminal histidines from the orthogonally oriented peptides covalently attached to the DNA. The assembly has been characterized using Electron Paramagnetic Resonance (EPR), optical spectroscopy, Dynamic Light Scattering (DLS), and x-ray crystallography. The results reveal that the spin state of the metal, iron (III), switches during assembly from the high-spin state to low-spin state.
ContributorsRendek, Kimberly Nicole (Author) / Fromme, Petra (Thesis advisor) / Chen, Julian (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2012
Description
With the increase in computing power and availability of data, there has never been a greater need to understand data and make decisions from it. Traditional statistical techniques may not be adequate to handle the size of today's data or the complexities of the information hidden within the data. Thus knowledge discovery by machine learning techniques is necessary if we want to better understand information from data. In this dissertation, we explore the topics of asymmetric loss and asymmetric data in machine learning and propose new algorithms as solutions to some of the problems in these topics. We also studied variable selection of matched data sets and proposed a solution when there is non-linearity in the matched data. The research is divided into three parts. The first part addresses the problem of asymmetric loss. A proposed asymmetric support vector machine (aSVM) is used to predict specific classes with high accuracy. aSVM was shown to produce higher precision than a regular SVM. The second part addresses asymmetric data sets where variables are only predictive for a subset of the predictor classes. Asymmetric Random Forest (ARF) was proposed to detect these kinds of variables. The third part explores variable selection for matched data sets. Matched Random Forest (MRF) was proposed to find variables that are able to distinguish case and control without the restrictions that exists in linear models. MRF detects variables that are able to distinguish case and control even in the presence of interaction and qualitative variables.
ContributorsKoh, Derek (Author) / Runger, George C. (Thesis advisor) / Wu, Tong (Committee member) / Pan, Rong (Committee member) / Cesta, John (Committee member) / Arizona State University (Publisher)
Created2013
Description
Photosynthesis is the primary source of energy for most living organisms. Light harvesting complexes (LHC) play a vital role in harvesting sunlight and passing it on to the protein complexes of the electron transfer chain which create the electrochemical potential across the membrane which drives ATP synthesis. phycobilisomes (PBS) are the most important LHCs in cyanobacteria. PBS is a complex of three light harvesting proteins: phycoerythrin (PE), phycocyanin (PC) and allophycocyanin (APC). This work has been done on a newly discovered cyanobacterium called Leptolyngbya Heron Island (L.HI). This study has three important goals: 1) Sequencing, assembly and annotation of the L.HI genome - Since this is a newly discovered cyanobacterium, its genome was not previously elucidated. Illumina sequencing, a type of next generation sequencing (NGS) technology was employed to sequence the genome. Unfortunately, the natural isolate contained other contaminating and potentially symbiotic bacterial populations. A novel bioinformatics strategy for separating DNA from contaminating bacterial populations from that of L.HI was devised which involves a combination of tetranucleotide frequency, %(G+C), BLAST analysis and gene annotation. 2) Structural elucidation of phycoerythrin - Phycoerythrin is the most important protein in the PBS assembly because it is one of the few light harvesting proteins which absorbs green light. The protein was crystallized and its structure solved to a resolution of 2Å. This protein contains two chemically distinct types of chromophores: phycourobilin and phycoerythrobilin. Energy transfer calculations indicate that there is unidirectional flow of energy from phycourobilin to phycoerythrobilin. Energy transfer time constants using Forster energy transfer theory have been found to be consistent with experimental data available in literature. 3) Effect of chromatic acclimation on photosystems - Chromatic acclimation is a phenomenon in which an organism modulates the ratio of PE/PC with change in light conditions. Our investigation in case of L.HI has revealed that the PE is expressed more in green light than PC in red light. This leads to unequal harvesting of light in these two states. Therefore, photosystem II expression is increased in red-light acclimatized cells coupled with an increase in number of PBS.
ContributorsPaul, Robin (Author) / Fromme, Petra (Thesis advisor) / Ros, Alexandra (Committee member) / Roberson, Robert (Committee member) / Arizona State University (Publisher)
Created2014
Description
Membrane proteins are a vital part of cellular structure. They are directly involved in many important cellular functions, such as uptake, signaling, respiration, and photosynthesis, among others. Despite their importance, however, less than 500 unique membrane protein structures have been determined to date. This is due to several difficulties with macromolecular crystallography, primarily the difficulty of growing large, well-ordered protein crystals. Since the first proof of concept for femtosecond nanocrystallography showing that diffraction patterns can be collected on extremely small crystals, thus negating the need to grow larger crystals, there have been many exciting advancements in the field. The technique has been proven to show high spatial resolution, thus making it a viable method for structural biology. However, due to the ultrafast nature of the technique, which allows for a lack of radiation damage in imaging, even more interesting experiments are possible, and the first temporal and spatial images of an undamaged structure could be acquired. This concept was denoted as time-resolved femtosecond nanocrystallography.
This dissertation presents on the first time-resolved data set of Photosystem II where structural changes can actually be seen without radiation damage. In order to accomplish this, new crystallization techniques had to be developed so that enough crystals could be made for the liquid jet to deliver a fully hydrated stream of crystals to the high-powered X-ray source. These changes are still in the preliminary stages due to the slightly lower resolution data obtained, but they are still a promising show of the power of this new technique. With further optimization of crystal growth methods and quality, injection technique, and continued development of data analysis software, it is only a matter of time before the ability to make movies of molecules in motion from X-ray diffraction snapshots in time exists. The work presented here is the first step in that process.
This dissertation presents on the first time-resolved data set of Photosystem II where structural changes can actually be seen without radiation damage. In order to accomplish this, new crystallization techniques had to be developed so that enough crystals could be made for the liquid jet to deliver a fully hydrated stream of crystals to the high-powered X-ray source. These changes are still in the preliminary stages due to the slightly lower resolution data obtained, but they are still a promising show of the power of this new technique. With further optimization of crystal growth methods and quality, injection technique, and continued development of data analysis software, it is only a matter of time before the ability to make movies of molecules in motion from X-ray diffraction snapshots in time exists. The work presented here is the first step in that process.
ContributorsKupitz, Christopher (Author) / Fromme, Petra (Thesis advisor) / Spence, John C. (Thesis advisor) / Redding, Kevin (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2014
Description
Accelerated life testing (ALT) is the process of subjecting a product to stress conditions (temperatures, voltage, pressure etc.) in excess of its normal operating levels to accelerate failures. Product failure typically results from multiple stresses acting on it simultaneously. Multi-stress factor ALTs are challenging as they increase the number of experiments due to the stress factor-level combinations resulting from the increased number of factors. Chapter 2 provides an approach for designing ALT plans with multiple stresses utilizing Latin hypercube designs that reduces the simulation cost without loss of statistical efficiency. A comparison to full grid and large-sample approximation methods illustrates the approach computational cost gain and flexibility in determining optimal stress settings with less assumptions and more intuitive unit allocations.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
ContributorsNasir, Ehab (Author) / Pan, Rong (Thesis advisor) / Runger, George C. (Committee member) / Gel, Esma (Committee member) / Kao, Ming-Hung (Committee member) / Montgomery, Douglas C. (Committee member) / Arizona State University (Publisher)
Created2014
Description
In the three phases of the engineering design process (conceptual design, embodiment design and detailed design), traditional reliability information is scarce. However, there are different sources of information that provide reliability inputs while designing a new product. This research considered these sources to be further analyzed: reliability information from similar existing products denominated as parents, elicited experts' opinions, initial testing and the customer voice for creating design requirements. These sources were integrated with three novels approaches to produce reliability insights in the engineering design process, all under the Design for Reliability (DFR) philosophy. Firstly, an enhanced parenting process to assess reliability was presented. Using reliability information from parents it was possible to create a failure structure (parent matrix) to be compared against the new product. Then, expert opinions were elicited to provide the effects of the new design changes (parent factor). Combining those two elements resulted in a reliability assessment in early design process. Extending this approach into the conceptual design phase, a methodology was created to obtain a graphical reliability insight of a new product's concept. The approach can be summarized by three sequential steps: functional analysis, cognitive maps and Bayesian networks. These tools integrated the available information, created a graphical representation of the concept and provided quantitative reliability assessments. Lastly, to optimize resources when product testing is viable (e.g., detailed design) a type of accelerated life testing was recommended: the accelerated degradation tests. The potential for robust design engineering for this type of test was exploited. Then, robust design was achieved by setting the design factors at some levels such that the impact of stress factor variation on the degradation rate can be minimized. Finally, to validate the proposed approaches and methods, different case studies were presented.
ContributorsMejia Sanchez, Luis (Author) / Pan, Rong (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Villalobos, Jesus R (Committee member) / See, Tung-King (Committee member) / Arizona State University (Publisher)
Created2014
Description
Proteins and peptides fold into dynamic structures that access a broad functional landscape, however, designing artificial polypeptide systems continues to be a great chal-lenge. Conversely, deoxyribonucleic acid (DNA) engineering is now routinely used to build a wide variety of two dimensional and three dimensional (3D) nanostructures from simple hybridization based rules, and their functional diversity can be significantly ex-panded through site specific incorporation of the appropriate guest molecules. This dis-sertation describes a gentle methodology for using short (8 nucleotide) peptide nucleic acid (PNA) linkers to assemble polypeptides within a 3D DNA nanocage, as a proof of concept for constructing artificial catalytic centers. PNA-polypeptide conjugates were synthesized directly using microwave assisted solid phase synthesis or alternatively PNA linkers were conjugated to biologically expressed proteins using chemical crosslinking. The PNA-polypeptides hybridized to the preassembled DNA nanocage at room tempera-ture or 11 ⁰C and could be assembled in a stepwise fashion. Time resolved fluorescence anisotropy and gel electrophoresis were used to determine that a negatively charged az-urin protein was repelled outside of the negatively charged DNA nanocage, while a posi-tively charged cytochrome c protein was retained inside. Spectroelectrochemistry and an in-gel luminol oxidation assay demonstrated the cytochrome c protein remained active within the DNA nanocage and its redox potential decreased modestly by 10 mV due to the presence of the DNA nanocage. These results demonstrate the benign PNA assembly conditions are ideal for preserving polypeptide structure and function, and will facilitate the polypeptide-based assembly of artificial catalytic centers inside a stable DNA nanocage. A prospective application of assembling multiple cyclic γ-PNA-peptides to mimic the oxygen-evolving complex (OEC) catalytic active site from photosystem II (PSII) is described. In this way, the robust catalytic capacity of PSII could be utilized, without suffering the light-induced damage that occurs by the photoreactions within PSII via triplet state formation, which limits the efficiency of natural photosynthesis. There-fore, this strategy has the potential to revolutionize the process of designing and building robust catalysts by leveraging nature's recipes, and also providing a flexible and con-trolled artificial environment that might even improve them further towards commercial viability.
ContributorsFlory, Justin David (Author) / Fromme, Petra (Thesis advisor) / Yan, Hao (Committee member) / Buttry, Daniel (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2014