Matching Items (43,917)
Description
One hypothesis for the small size of insects relative to vertebrates, and the existence of giant fossil insects, is that atmospheric oxygen levels have constrained body sizes because oxygen delivery would be unable to match the needs of metabolically active tissues in larger insects. This study tested whether oxygen delivery becomes more challenging for larger insects by measuring the oxygen-sensitivity of flight metabolic rates and behavior during hovering for 11 different species of dragonflies that range in mass by an order of magnitude. Animals were flown in 7 different oxygen concentrations ranging from 30% to 2.5% to assess the sensitivity of their behavior and flight metabolic rates to oxygen. I also assessed the oxygen-sensitivity of flight in low-density air (nitrogen replaced with helium), to increase the metabolic demands of hovering flight. Lowered atmosphere densities did induce higher metabolic rates. Flight behaviors but not flight metabolic rates were highly oxygen-sensitive. A significant interaction between oxygen and mass was found for total flight time, with larger dragonflies varying flight time more in response to atmospheric oxygen. This study provides some support for the hypothesis that larger insects are more challenged in oxygen delivery, as predicted by the oxygen limitation hypothesis for insect gigantism in the Paleozoic.
Contributors
Henry, Joanna Randyl (Author) / Harrison, Jon F. (Thesis advisor) / Kaiser, Alexander (Committee member) / Rutowski, Ronald L (Committee member) / Arizona State University (Publisher)
Created
2011
Analysis of photocatalysis for precursor removal and formation inhibition of disinfection byproducts
Description
Disinfection byproducts are the result of reactions between natural organic matter (NOM) and a disinfectant. The formation and speciation of DBP formation is largely dependent on the disinfectant used and the natural organic matter (NOM) concentration and composition. This study examined the use of photocatalysis with titanium dioxide for the oxidation and removal of DBP precursors (NOM) and the inhibition of DBP formation. Water sources were collected from various points in the treatment process, treated with photocatalysis, and chlorinated to analyze the implications on total trihalomethane (TTHM) and the five haloacetic acids (HAA5) formations. The three sub-objectives for this study included: the comparison of enhanced and standard coagulation to photocatalysis for the removal of DBP precursors; the analysis of photocatalysis and characterization of organic matter using size exclusion chromatography and fluorescence spectroscopy and excitation-emission matrices; and the analysis of photocatalysis before GAC filtration. There were consistencies in the trends for each objective including reduced DBP precursors, measured as dissolved organic carbon DOC concentration and UV absorbance at 254 nm. Both of these parameters decreased with increased photocatalytic treatment and could be due in part to the adsorption to as well as the oxidation of NOM on the TiO2 surface. This resulted in lower THM and HAA concentrations at Medium and High photocatalytic treatment levels. However, at No UV exposure and Low photocatalytic treatment levels where oxidation reactions were inherently incomplete, there was an increase in THM and HAA formation potential, in most cases being significantly greater than those found in the raw water or Control samples. The size exclusion chromatography (SEC) results suggest that photocatalysis preferentially degrades the higher molecular mass fraction of NOM releasing lower molecular mass (LMM) compounds that have not been completely oxidized. The molecular weight distributions could explain the THM and HAA formation potentials that decreased at the No UV exposure samples but increased at Low photocatalytic treatment levels. The use of photocatalysis before GAC adsorption appears to increase bed life of the contactors; however, higher photocatalytic treatment levels have been shown to completely mineralize NOM and would therefore not require additional GAC adsorption after photocatalysis.
Contributors
Daugherty, Erin (Author) / Abbaszadegan, Morteza (Thesis advisor) / Fox, Peter (Committee member) / Mayer, Brooke (Committee member) / Arizona State University (Publisher)
Created
2011
Description
With the advent of the X-ray free-electron laser (XFEL), an opportunity has arisen to break the nexus between radiation dose and spatial resolution in diffractive imaging, by outrunning radiation damage altogether when using single X-ray pulses so brief that they terminate before atomic motion commences. This dissertation concerns the application of XFELs to biomolecular imaging in an effort to overcome the severe challenges associated with radiation damage and macroscopic protein crystal growth. The method of femtosecond protein nanocrystallography (fsPNX) is investigated, and a new method for extracting crystallographic structure factors is demonstrated on simulated data and on the first experimental fsPNX data obtained at an XFEL. Errors are assessed based on standard metrics familiar to the crystallography community. It is shown that resulting structure factors match the quality of those measured conventionally, at least to 9 angstrom resolution. A new method for ab-initio phasing of coherently-illuminated nanocrystals is then demonstrated on simulated data. The method of correlated fluctuation small-angle X-ray scattering (CFSAXS) is also investigated as an alternative route to biomolecular structure determination, without the use of crystals. It is demonstrated that, for a constrained two-dimensional geometry, a projection image of a single particle can be formed, ab-initio and without modeling parameters, from measured diffracted intensity correlations arising from disordered ensembles of identical particles illuminated simultaneously. The method is demonstrated experimentally, based on soft X-ray diffraction from disordered but identical nanoparticles, providing the first experimental proof-of-principle result. Finally, the fundamental limitations of CFSAXS is investigated through both theory and simulations. It is found that the signal-to-noise ratio (SNR) for CFSAXS data is essentially independent of the number of particles exposed in each diffraction pattern. The dependence of SNR on particle size and resolution is considered, and realistic estimates are made (with the inclusion of solvent scatter) of the SNR for protein solution scattering experiments utilizing an XFEL source.
Contributors
Kirian, Richard A (Author) / Spence, John C. H. (Committee member) / Doak, R. Bruce (Committee member) / Weierstall, Uwe (Committee member) / Bennett, Peter (Committee member) / Treacy, Michael M. J. (Committee member) / Arizona State University (Publisher)
Created
2011
Description
The properties of materials depend heavily on the spatial distribution and connectivity of their constituent parts. This applies equally to materials such as diamond and glasses as it does to biomolecules that are the product of billions of years of evolution. In science, insight is often gained through simple models with characteristics that are the result of the few features that have purposely been retained. Common to all research within in this thesis is the use of network-based models to describe the properties of materials. This work begins with the description of a technique for decoupling boundary effects from intrinsic properties of nanomaterials that maps the atomic distribution of nanomaterials of diverse shape and size but common atomic geometry onto a universal curve. This is followed by an investigation of correlated density fluctuations in the large length scale limit in amorphous materials through the analysis of large continuous random network models. The difficulty of estimating this limit from finite models is overcome by the development of a technique that uses the variance in the number of atoms in finite subregions to perform the extrapolation to large length scales. The technique is applied to models of amorphous silicon and vitreous silica and compared with results from recent experiments. The latter part this work applies network-based models to biological systems. The first application models force-induced protein unfolding as crack propagation on a constraint network consisting of interactions such as hydrogen bonds that cross-link and stabilize a folded polypeptide chain. Unfolding pathways generated by the model are compared with molecular dynamics simulation and experiment for a diverse set of proteins, demonstrating that the model is able to capture not only native state behavior but also partially unfolded intermediates far from the native state. This study concludes with the extension of the latter model in the development of an efficient algorithm for predicting protein structure through the flexible fitting of atomic models to low-resolution cryo-electron microscopy data. By optimizing the fit to synthetic data through directed sampling and context-dependent constraint removal, predictions are made with accuracies within the expected variability of the native state.
Contributors
De Graff, Adam (Author) / Thorpe, Michael F. (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Matyushov, Dmitry (Committee member) / Ozkan, Sefika B. (Committee member) / Treacy, Michael M. J. (Committee member) / Arizona State University (Publisher)
Created
2011
Description
The oceans play an essential role in global biogeochemical cycles and in regulating climate. The biological carbon pump, the photosynthetic fixation of carbon dioxide by phytoplankton and subsequent sequestration of organic carbon into deep water, combined with the physical carbon pump, make the oceans the only long-term net sink for anthropogenic carbon dioxide. A full understanding of the workings of the biological carbon pump requires a knowledge of the role of different taxonomic groups of phytoplankton (protists and cyanobacteria) to organic carbon export. However, this has been difficult due to the degraded nature of particles sinking into particle traps, the main tools employed by oceanographers to collect sinking particulate matter in the ocean. In this study DNA-based molecular methods, including denaturing gradient gel electrophoresis, cloning and sequencing, and taxon-specific quantitative PCR, allowed for the first time for the identification of which protists and cyanobacteria contributed to the material collected by the traps in relation to their presence in the euphotic zone. I conducted this study at two time-series stations in the subtropical North Atlantic Ocean, one north of the Canary Islands, and one located south of Bermuda. The Bermuda study allowed me to investigate seasonal and interannual changes in the contribution of the plankton community to particle flux. I could also show that small unarmored taxa, including representatives of prasinophytes and cyanobacteria, constituted a significant fraction of sequences recovered from sediment trap material. Prasinophyte sequences alone could account for up to 13% of the clone library sequences of trap material during bloom periods. These observations contradict a long-standing paradigm in biological oceanography that only large taxa with mineral shells are capable of sinking while smaller, unarmored cells are recycled in the euphotic zone through the microbial loop. Climate change and a subsequent warming of the surface ocean may lead to a shift in the protist community toward smaller cell size in the future, but in light of these findings these changes may not necessarily lead to a reduction in the strength of the biological carbon pump.
Contributors
Amacher, Jessica (Author) / Neuer, Susanne (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Lomas, Michael (Committee member) / Wojciechowski, Martin (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created
2011
Description
Real-world environments are characterized by non-stationary and continuously evolving data. Learning a classification model on this data would require a framework that is able to adapt itself to newer circumstances. Under such circumstances, transfer learning has come to be a dependable methodology for improving classification performance with reduced training costs and without the need for explicit relearning from scratch. In this thesis, a novel instance transfer technique that adapts a "Cost-sensitive" variation of AdaBoost is presented. The method capitalizes on the theoretical and functional properties of AdaBoost to selectively reuse outdated training instances obtained from a "source" domain to effectively classify unseen instances occurring in a different, but related "target" domain. The algorithm is evaluated on real-world classification problems namely accelerometer based 3D gesture recognition, smart home activity recognition and text categorization. The performance on these datasets is analyzed and evaluated against popular boosting-based instance transfer techniques. In addition, supporting empirical studies, that investigate some of the less explored bottlenecks of boosting based instance transfer methods, are presented, to understand the suitability and effectiveness of this form of knowledge transfer.
Contributors
Venkatesan, Ashok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Li, Baoxin (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created
2011
Description
The theory of geometric quantum mechanics describes a quantum system as a Hamiltonian dynamical system, with a projective Hilbert space regarded as the phase space. This thesis extends the theory by including some aspects of the symplectic topology of the quantum phase space. It is shown that the quantum mechanical uncertainty principle is a special case of an inequality from J-holomorphic map theory, that is, J-holomorphic curves minimize the difference between the quantum covariance matrix determinant and a symplectic area. An immediate consequence is that a minimal determinant is a topological invariant, within a fixed homology class of the curve. Various choices of quantum operators are studied with reference to the implications of the J-holomorphic condition. The mean curvature vector field and Maslov class are calculated for a lagrangian torus of an integrable quantum system. The mean curvature one-form is simply related to the canonical connection which determines the geometric phases and polarization linear response. Adiabatic deformations of a quantum system are analyzed in terms of vector bundle classifying maps and related to the mean curvature flow of quantum states. The dielectric response function for a periodic solid is calculated to be the curvature of a connection on a vector bundle.
Contributors
Sanborn, Barbara (Author) / Suslov, Sergei K (Thesis advisor) / Suslov, Sergei (Committee member) / Spielberg, John (Committee member) / Quigg, John (Committee member) / Menéndez, Jose (Committee member) / Jones, Donald (Committee member) / Arizona State University (Publisher)
Created
2011
Description
The objective of this study was to understand domestic and foreign-born housekeeper's individual perceptions of labor mobility and job satisfaction related to their jobs within the hospitality industry. Literature regarding the bridging of tourism, immigration, and labor supply was addressed to expose broad conceptual frameworks that lead to the development of this study. More specifically, literature regarding labor mobility within tourism industries, migrant decision making, and barriers to mobility and immigration helped to construct a narrowed conceptual framework specific to hospitality labor in Phoenix, Arizona. Similar and previous studies focused on perceived labor mobility during significant economic or industry shifts. This study included the addition of a policy factor to help determine to what degree state policy change effected hospitality workers' perceived labor mobility. Arizona's recently passed and implemented legislative act SB1070 regards immigrant identification and employment, and enforcement of the act in the state of Arizona; this serves as the implicated policy change. Data were collected via on-site survey administered February to May 2011. An overall score was created for the five motivational dimensions: 1 — Status; 2 — Economic; 3 — Refugee; 4 — Entrepreneurial; and, 5 — Political using principle component factor analysis using a varimax rotation with Kaiser normalization. Theory and literature suggest that the economic advancement, status advancement, and the refugee orientation are effective explanatory variables for motivating a career move into the tourism industry. A total of 82 questionnaires were delivered and completed (N = 82), and none were eliminated. The statistically-determined Economic Dimension was characterized by eleven statements explained 51% of the variation and was the overwhelming motivational force. The average coded response for change in job satisfaction was very positive at .75. Ten features of changes in job satisfaction were used as the basis of the second measure of change in job satisfaction. The first Principle Component of the ten features of job satisfaction change explained 45% of the variation in these features and loadings were positive near or above 0.60 for all items. The relationship between variations in each of the measurements of change in job satisfaction and motivating factors was explored using regression analysis. The two dependent variables were Overall Change and First Principle Component, and the independent variables for both regressions included the four motivating factors as measured by the rotated factors scores to represent dimensions of Economic, Status, Refugee and Entrepreneurial. In addition to the motivational factors, four demographic variables were included as independent variables to account for personal and situational differences. None of the regression coefficients were significant at even the 10% level. Although this result was expected, the positive sign of regression coefficients suggest that expectations of working as a housekeepers results in a positive outcome. Understanding this relationship further is necessary, and seeking larger sample sizes over a longer period of time would be most beneficial to this field of research.
Contributors
Casson, Mallory (Author) / Tyrrell, Timothy (Thesis advisor) / Budruk, Megha (Committee member) / Li, Wei (Committee member) / Arizona State University (Publisher)
Created
2011
Description
This study explores how newspapers framed the weight-loss drugs Xenical®(orlistat) and Alli® (over-the-counter orlistat) during the time period of three months prior to their approvals by the U.S. Food and Drug Administration until one year after each became available on the market. As of June 2011, orlistat is the only weight-loss drug available for long-term use in the U.S. Newspapers are influential sources of information about health issues. Agenda-setting, framing, and priming in news articles can have a powerful effect on public perceptions and behaviors. To conduct the content analysis, researchers first developed a codebook containing variables that described the sources of attribution and the features of each drug. They tested the codebook in a series of pilot tests to ensure inter-rater reliability. The sample of texts for the content analysis, drawn from LexisNexis Academic, contained 183 newspaper articles composed of 85 Xenical articles and 98 Alli articles. The overlap was 25% for inter-rater reliability as well as intra-rater reliability. Frequencies were tabulated using Predictive Analytics SoftWare, version 18.0.3. Results demonstrated that Xenical and Alli were framed differently in some critical ways. For example, there were twice as many quotes from the manufacturer for Alli than for Xenical. Researchers concluded that the reporting on Alli was heavily influenced by the manufacturer's multi-media public relations campaign in the months prior to the market-release date.
Contributors
Lehmann, Jessica (Author) / Hampl, Jeffrey S. (Thesis advisor) / Bramlett-Solomon, Sharon (Committee member) / Hall, Richard (Committee member) / Arizona State University (Publisher)
Created
2011
Description
A perceived link between illegal immigration and crime continues to exist. Citizens continue to believe that immigration creates crime and fear that as the immigrant population grows, their safety is jeopardized. Not much research in the field of criminology, however, has focused on examining this perceived relationship between immigration and crime. Those studies which have examined the relationship have mainly relied on official data to conduct their analysis. The purpose of this thesis is to examine the relationship between immigration and crime by examining self report data as well as some official data on immigration status and criminal involvement. More specifically, this thesis examines the relationship between immigration status and four different types of criminal involvement; property crimes, violent crimes, drug sales, and drug use. Data from a sample of 1,990 arrestees in the Maricopa County, Arizona, was used to conduct this analysis. This data was collected through the Arizona Arrestee Reporting Information Network over the course of a year. The results of the logistic regression models indicate that immigrants tend to commit less crime than U.S. citizens. Furthermore, illegal immigrants are significantly less likely than U.S. citizens to commit any of the four types of crimes, with the exception of powder cocaine use.
Contributors
Nuño, Lidia E (Author) / Katz, Charles M. (Thesis advisor) / White, Michael D. (Committee member) / Decker, Scott H. (Committee member) / Arizona State University (Publisher)
Created
2011