Matching Items (204)
Description
Chemical and mineralogical data from Mars shows that the surface has been chemically weathered on local to regional scales. Chemical trends and the types of chemical weathering products present on the surface and their abundances can elucidate information about past aqueous processes. Thermal-infrared (TIR) data and their respective models are essential for interpreting Martian mineralogy and geologic history. However, previous studies have shown that chemical weathering and the precipitation of fine-grained secondary silicates can adversely affect the accuracy of TIR spectral models. Furthermore, spectral libraries used to identify minerals on the Martian surface lack some important weathering products, including poorly-crystalline aluminosilicates like allophane, thus eliminating their identification in TIR spectral models. It is essential to accurately interpret TIR spectral data from chemically weathered surfaces to understand the evolution of aqueous processes on Mars. Laboratory experiments were performed to improve interpretations of TIR data from weathered surfaces. To test the accuracy of deriving chemistry of weathered rocks from TIR spectroscopy, chemistry was derived from TIR models of weathered basalts from Baynton, Australia and compared to actual weathering rind chemistry. To determine how specific secondary silicates affect the TIR spectroscopy of weathered basalts, mixtures of basaltic minerals and small amounts of secondary silicates were modeled. Poorly-crystalline aluminosilicates were synthesized and their TIR spectra were added to spectral libraries. Regional Thermal Emission Spectrometer (TES) data were modeled using libraries containing these poorly-crystalline aluminosilicates to test for their presence on the Mars. Chemistry derived from models of weathered Baynton basalts is not accurate, but broad chemical weathering trends can be interpreted from the data. TIR models of mineral mixtures show that small amounts of crystalline and amorphous silicate weathering products (2.5-5 wt.%) can be detected in TIR models and can adversely affect modeled plagioclase abundances. Poorly-crystalline aluminosilicates are identified in Northern Acidalia, Solis Planum, and Meridiani. Previous studies have suggested that acid sulfate weathering was the dominant surface alteration process for the past 3.5 billion years; however, the identification of allophane indicates that alteration at near-neutral pH occurred on regional scales and that acid sulfate weathering is not the only weathering process on Mars.
ContributorsRampe, Elizabeth Barger (Author) / Sharp, Thomas G (Thesis advisor) / Christensen, Phillip (Committee member) / Hervig, Richard (Committee member) / Shock, Everett (Committee member) / Williams, Lynda (Committee member) / Arizona State University (Publisher)
Created2011
Description
Applications of non-traditional stable isotope variations are moving beyond geosciences to biomedicine, made possible by advances in multiple collector inductively coupled plasma mass spectrometry (MC-ICP-MS) technology. Mass-dependent isotope variation can provide information about the sources of elements and the chemical reactions that they undergo. Iron and calcium isotope systematics in biomedicine are relatively unexplored but have great potential scientific interest due to their essential nature in metabolism. Iron, a crucial element in biology, fractionates during biochemically relevant reactions. To test the extent of this fractionation in an important reaction process, equilibrium iron isotope fractionation during organic ligand exchange was determined. The results show that iron fractionates during organic ligand exchange, and that isotope enrichment increases as a function of the difference in binding constants between ligands. Additionally, to create a mass balance model for iron in a whole organism, iron isotope compositions in a whole mouse and in individual mouse organs were measured. The results indicate that fractionation occurs during transfer between individual organs, and that the whole organism was isotopically light compared with food. These two experiments advance our ability to interpret stable iron isotopes in biomedicine. Previous research demonstrated that calcium isotope variations in urine can be used as an indicator of changes in net bone mineral balance. In order to measure calcium isotopes by MC-ICP-MS, a chemical purification method was developed to quantitatively separate calcium from other elements in a biological matrix. Subsequently, this method was used to evaluate if calcium isotopes respond when organisms are subjected to conditions known to induce bone loss: 1) Rhesus monkeys were given an estrogen-suppressing drug; 2) Human patients underwent extended bed rest. In both studies, there were rapid, detectable changes in calcium isotope compositions from baseline - verifying that calcium isotopes can be used to rapidly detect changes in bone mineral balance. By characterizing iron isotope fractionation in biologically relevant processes and by demonstrating that calcium isotopes vary rapidly in response to bone loss, this thesis represents an important step in utilizing these isotope systems as a diagnostic and mechanistic tool to study the metabolism of these elements in vivo.
ContributorsMorgan, Jennifer Lynn Louden (Author) / Anbar, Ariel D. (Thesis advisor) / Wasylenki, Laura E. (Committee member) / Jones, Anne K. (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2011
Description
In this study, the influence of fluid mixing on temperature and geochemistry of hot spring fluids is investigated. Yellowstone National Park (YNP) is home to a diverse range of hot springs with varying temperature and chemistry. The mixing zone of interest in this paper, located in Geyser Creek, YNP, has been a point of interest since at least the 1960’s (Raymahashay, 1968). Two springs, one basic (~pH 7) and one acidic (~pH 3) mix together down an outflow channel. There are visual bands of different photosynthetic pigments which suggests the creation of temperature and chemical gradients due to the fluids mixing. In this study, to determine if fluid mixing is driving these changes of temperature and chemistry in the system, a model that factors in evaporation and cooling was developed and compared to measured temperature and chemical data collected downstream. Comparison of the modeled temperature and chemistry to the measured values at the downstream mixture shows that many of the ions, such as Cl⁻, F⁻, and Li⁺, behave conservatively with respect to mixing. This indicates that the influence of mixing accounts for a large proportion of variation in the chemical composition of the system. However, there are some chemical constituents like CH₄, H₂, and NO₃⁻, that were not conserved, and the concentrations were either depleted or increased in the downstream mixture. Some of these constituents are known to be used by microorganisms. The development of this mixing model can be used as a tool for predicting biological activity as well as building the framework for future geochemical and computational models that can be used to understand the energy availability and the microbial communities that are present.
ContributorsOrrill, Brianna Isabel (Author) / Shock, Everett (Thesis director) / Howells, Alta (Committee member) / School of Life Sciences (Contributor) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
A new challenge on the horizon is to utilize the large amounts of protein found in the atmosphere to identify different organisms from which the protein originated. Included here is work investigating the presence of identifiable patterns of different proteins collected from the air and biological samples for the purposes of remote identification. Protein patterns were generated using high performance liquid chromatography (HPLC). Patterns created could identify high-traffic and low-traffic indoor spaces. Samples were collected from the air using air pumps to draw air through a filter paper trapping particulates, including large amounts of shed protein matter. In complimentary research aerosolized biological samples were collected from various ecosystems throughout Ecuador to explore the relationship between environmental setting and aerosolized protein concentrations. In order to further enhance protein separation and produce more detailed patterns for the identification of individual organisms of interest; a novel separation device was constructed and characterized. The separation device incorporates a longitudinal gradient as well as insulating dielectrophoretic features within a single channel. This design allows for the production of stronger local field gradients along a global gradient allowing particles to enter, initially transported through the channel by electrophoresis and electroosmosis, and to be isolated according to their characteristic physical properties, including charge, polarizability, deformability, surface charge mobility, dielectric features, and local capacitance. Thus, different types of particles are simultaneously separated at different points along the channel distance given small variations of properties. The device has shown the ability to separate analytes over a large dynamic range of size, from 20 nm to 1 μm, roughly the size of proteins to the size of cells. In the study of different sized sulfate capped polystyrene particles were shown to be selectively captured as well as concentrating particles from 103 to 106 times. Qualitative capture and manipulation of β-amyloid fibrils were also shown. The results demonstrate the selective focusing ability of the technique; and it may form the foundation for a versatile tool for separating complex mixtures. Combined this work shows promise for future identification of individual organisms from aerosolized protein as well as for applications in biomedical research.
ContributorsStaton, Sarah J. R (Author) / Hayes, Mark A. (Committee member) / Anbar, Ariel D (Committee member) / Shock, Everett (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Rabies disease remains enzootic among raccoons, skunks, foxes and bats in the United States. It is of primary concern for public-health agencies to control spatial spread of rabies in wildlife and its potential spillover infection of domestic animals and humans. Rabies is invariably fatal in wildlife if untreated, with a non-negligible incubation period. Understanding how this latency affects spatial spread of rabies in wildlife is the concern of chapter 2 and 3. Chapter 1 deals with the background of mathematical models for rabies and lists main objectives. In chapter 2, a reaction-diffusion susceptible-exposed-infected (SEI) model and a delayed diffusive susceptible-infected (SI) model are constructed to describe the same epidemic process -- rabies spread in foxes. For the delayed diffusive model a non-local infection term with delay is resulted from modeling the dispersal during incubation stage. Comparison is made regarding minimum traveling wave speeds of the two models, which are verified using numerical experiments. In chapter 3, starting with two Kermack and McKendrick's models where infectivity, death rate and diffusion rate of infected individuals can depend on the age of infection, the asymptotic speed of spread $c^\ast$ for the cumulated force of infection can be analyzed. For the special case of fixed incubation period, the asymptotic speed of spread is governed by the same integral equation for both models. Although explicit solutions for $c^\ast$ are difficult to obtain, assuming that diffusion coefficient of incubating animals is small, $c^\ast$ can be estimated in terms of model parameter values. Chapter 4 considers the implementation of realistic landscape in simulation of rabies spread in skunks and bats in northeast Texas. The Finite Element Method (FEM) is adopted because the irregular shapes of realistic landscape naturally lead to unstructured grids in the spatial domain. This implementation leads to a more accurate description of skunk rabies cases distributions.
ContributorsLiu, Hao (Author) / Kuang, Yang (Thesis advisor) / Jackiewicz, Zdzislaw (Committee member) / Lanchier, Nicolas (Committee member) / Smith, Hal (Committee member) / Thieme, Horst (Committee member) / Arizona State University (Publisher)
Created2013
Description
Functional magnetic resonance imaging (fMRI) has been widely used to measure the retinotopic organization of early visual cortex in the human brain. Previous studies have identified multiple visual field maps (VFMs) based on statistical analysis of fMRI signals, but the resulting geometry has not been fully characterized with mathematical models. This thesis explores using concepts from computational conformal geometry to create a custom software framework for examining and generating quantitative mathematical models for characterizing the geometry of early visual areas in the human brain. The software framework includes a graphical user interface built on top of a selected core conformal flattening algorithm and various software tools compiled specifically for processing and examining retinotopic data. Three conformal flattening algorithms were implemented and evaluated for speed and how well they preserve the conformal metric. All three algorithms performed well in preserving the conformal metric but the speed and stability of the algorithms varied. The software framework performed correctly on actual retinotopic data collected using the standard travelling-wave experiment. Preliminary analysis of the Beltrami coefficient for the early data set shows that selected regions of V1 that contain reasonably smooth eccentricity and polar angle gradients do show significant local conformality, warranting further investigation of this approach for analysis of early and higher visual cortex.
ContributorsTa, Duyan (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Wonka, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set of 3D morphological differences in the corpus callosum between two groups of subjects. The CCs are segmented from whole brain T1-weighted MRI and modeled as 3D tetrahedral meshes. The callosal surface is divided into superior and inferior patches on which we compute a volumetric harmonic field by solving the Laplace's equation with Dirichlet boundary conditions. We adopt a refined tetrahedral mesh to compute the Laplacian operator, so our computation can achieve sub-voxel accuracy. Thickness is estimated by tracing the streamlines in the harmonic field. We combine areal changes found using surface tensor-based morphometry and thickness information into a vector at each vertex to be used as a metric for the statistical analysis. Group differences are assessed on this combined measure through Hotelling's T2 test. The method is applied to statistically compare three groups consisting of: congenitally blind (CB), late blind (LB; onset > 8 years old) and sighted (SC) subjects. Our results reveal significant differences in several regions of the CC between both blind groups and the sighted groups; and to a lesser extent between the LB and CB groups. These results demonstrate the crucial role of visual deprivation during the developmental period in reshaping the structural architecture of the CC.
ContributorsXu, Liang (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
Image resolution limits the extent to which zooming enhances clarity, restricts the size digital photographs can be printed at, and, in the context of medical images, can prevent a diagnosis. Interpolation is the supplementing of known data with estimated values based on a function or model involving some or all of the known samples. The selection of the contributing data points and the specifics of how they are used to define the interpolated values influences how effectively the interpolation algorithm is able to estimate the underlying, continuous signal. The main contributions of this dissertation are three fold: 1) Reframing edge-directed interpolation of a single image as an intensity-based registration problem. 2) Providing an analytical framework for intensity-based registration using control grid constraints. 3) Quantitative assessment of the new, single-image enlargement algorithm based on analytical intensity-based registration. In addition to single image resizing, the new methods and analytical approaches were extended to address a wide range of applications including volumetric (multi-slice) image interpolation, video deinterlacing, motion detection, and atmospheric distortion correction. Overall, the new approaches generate results that more accurately reflect the underlying signals than less computationally demanding approaches and with lower processing requirements and fewer restrictions than methods with comparable accuracy.
ContributorsZwart, Christine M. (Author) / Frakes, David H (Thesis advisor) / Karam, Lina (Committee member) / Kodibagkar, Vikram (Committee member) / Spanias, Andreas (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cancer is the second leading cause of death in the United States and novel methods of treating advanced malignancies are of high importance. Of these deaths, prostate cancer and breast cancer are the second most fatal carcinomas in men and women respectively, while pancreatic cancer is the fourth most fatal in both men and women. Developing new drugs for the treatment of cancer is both a slow and expensive process. It is estimated that it takes an average of 15 years and an expense of $800 million to bring a single new drug to the market. However, it is also estimated that nearly 40% of that cost could be avoided by finding alternative uses for drugs that have already been approved by the Food and Drug Administration (FDA). The research presented in this document describes the testing, identification, and mechanistic evaluation of novel methods for treating many human carcinomas using drugs previously approved by the FDA. A tissue culture plate-based screening of FDA approved drugs will identify compounds that can be used in combination with the protein TRAIL to induce apoptosis selectively in cancer cells. Identified leads will next be optimized using high-throughput microfluidic devices to determine the most effective treatment conditions. Finally, a rigorous mechanistic analysis will be conducted to understand how the FDA-approved drug mitoxantrone, sensitizes cancer cells to TRAIL-mediated apoptosis.
ContributorsTaylor, David (Author) / Rege, Kaushal (Thesis advisor) / Jayaraman, Arul (Committee member) / Nielsen, David (Committee member) / Kodibagkar, Vikram (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2013