897 resultados para 0299 Other Physical Sciences


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Chapter 1 is used to introduce the basic tools and mechanics used within this thesis. Most of the definitions used in the thesis will be defined, and we provide a basic survey of topics in graph theory and design theory pertinent to the topics studied in this thesis. In Chapter 2, we are concerned with the study of fixed block configuration group divisible designs, GDD(n; m; k; λ1; λ2). We study those GDDs in which each block has configuration (s; t), that is, GDDs in which each block has exactly s points from one of the two groups and t points from the other. Chapter 2 begins with an overview of previous results and constructions for small group size and block sizes 3, 4 and 5. Chapter 2 is largely devoted to presenting constructions and results about GDDs with two groups and block size 6. We show the necessary conditions are sufficient for the existence of GDD(n, 2, 6; λ1, λ2) with fixed block configuration (3; 3). For configuration (1; 5), we give minimal or nearminimal index constructions for all group sizes n ≥ 5 except n = 10, 15, 160, or 190. For configuration (2, 4), we provide constructions for several families ofGDD(n, 2, 6; λ1, λ2)s. Chapter 3 addresses characterizing (3, r)-regular graphs. We begin with providing previous results on the well studied class of (2, r)-regular graphs and some results on the structure of large (t; r)-regular graphs. In Chapter 3, we completely characterize all (3, 1)-regular and (3, 2)-regular graphs, as well has sharpen existing bounds on the order of large (3, r)- regular graphs of a certain form for r ≥ 3. Finally, the appendix gives computational data resulting from Sage and C programs used to generate (3, 3)-regular graphs on less than 10 vertices.

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Interest in the study of magnetic/non-magnetic multilayered structures took a giant leap since Grünberg and his group established that the interlayer exchange coupling (IEC) is a function of the non-magnetic spacer width. This interest was further fuelled by the discovery of the phenomenal Giant Magnetoresistance (GMR) effect. In fact, in 2007 Albert Fert and Peter Grünberg were awarded the Nobel Prize in Physics for their contribution to the discovery of GMR. GMR is the key property that is being used in the read-head of the present day computer hard drive as it requires a high sensitivity in the detection of magnetic field. The recent increase in demand for device miniaturization encouraged researchers to look for GMR in nanoscale multilayered structures. In this context, one dimensional(1-D) multilayerd nanowire structure has shown tremendous promise as a viable candidate for ultra sensitive read head sensors. In fact, the phenomenal giant magnetoresistance(GMR) effect, which is the novel feature of the currently used multilayered thin film, has already been observed in multilayered nanowire systems at ambient temperature. Geometrical confinement of the supper lattice along the 2-dimensions (2-D) to construct the 1-D multilayered nanowire prohibits the minimization of magnetic interaction- offering a rich variety of magnetic properties in nanowire that can be exploited for novel functionality. In addition, introduction of non-magnetic spacer between the magnetic layers presents additional advantage in controlling magnetic properties via tuning the interlayer magnetic interaction. Despite of a large volume of theoretical works devoted towards the understanding of GMR and IEC in super lattice structures, limited theoretical calculations are reported in 1-D multilayered systems. Thus to gauge their potential application in new generation magneto-electronic devices, in this thesis, I have discussed the usage of first principles density functional theory (DFT) in predicting the equilibrium structure, stability as well as electronic and magnetic properties of one dimensional multilayered nanowires. Particularly, I have focused on the electronic and magnetic properties of Fe/Pt multilayered nanowire structures and the role of non-magnetic Pt spacer in modulating the magnetic properties of the wire. It is found that the average magnetic moment per atom in the nanowire increases monotonically with an ~1/(N(Fe)) dependance, where N(Fe) is the number of iron layers in the nanowire. A simple model based upon the interfacial structure is given to explain the 1/(N(Fe)) trend in magnetic moment obtained from the first principle calculations. A new mechanism, based upon spin flip with in the layer and multistep electron transfer between the layers, is proposed to elucidate the enhancement of magnetic moment of Iron atom at the Platinum interface. The calculated IEC in the Fe/Pt multilayered nanowire is found to switch sign as the width of the non-magnetic spacer varies. The competition among short and long range direct exchange and the super exchange has been found to play a key role for the non-monotonous sign in IEC depending upon the width of the Platinum spacer layer. The calculated magnetoresistance from Julliere's model also exhibit similar switching behavior as that of IEC. The universality of the behavior of exchange coupling has also been looked into by introducing different non-magnetic spacers like Palladium, Copper, Silver, and Gold in between magnetic Iron layers. The nature of hybridization between Fe and other non-magnetic spacer is found to dictate the inter layer magnetic interaction. For example, in Fe/Pd nanowire the d-p hybridization in two spacer layer case favors anti-ferromagnetic (AFM) configuration over ferromagnetic (FM) configuration. However, the hybridization between half-filled Fe(d) and filled Cu(p) state in Fe/Cu nanowire favors FM coupling in the 2-spacer system.

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The feasibility of carbon sequestration in cement kiln dust (CKD) was investigated in a series of batch and column experiments conducted under ambient temperature and pressure conditions. The significance of this work is the demonstration that alkaline wastes, such as CKD, are highly reactive with carbon dioxide (CO2). In the presence of water, CKD can sequester greater than 80% of its theoretical capacity for carbon without any amendments or modifications to the waste. Other mineral carbonation technologies for carbon sequestration rely on the use of mined mineral feedstocks as the source of oxides. The mining, pre-processing and reaction conditions needed to create favorable carbonation kinetics all require significant additions of energy to the system. Therefore, their actual net reduction in CO2 is uncertain. Many suitable alkaline wastes are produced at sites that also generate significant quantities of CO2. While independently, the reduction in CO2 emissions from mineral carbonation in CKD is small (~13% of process related emissions), when this technology is applied to similar wastes of other industries, the collective net reduction in emissions may be significant. The technical investigations presented in this dissertation progress from proof of feasibility through examination of the extent of sequestration in core samples taken from an aged CKD waste pile, to more fundamental batch and microscopy studies which analyze the rates and mechanisms controlling mineral carbonation reactions in a variety of fresh CKD types. Finally, the scale of the system was increased to assess the sequestration efficiency under more pilot or field-scale conditions and to clarify the importance of particle-scale processes under more dynamic (flowing gas) conditions. A comprehensive set of material characterization methods, including thermal analysis, Xray diffraction, and X-ray fluorescence, were used to confirm extents of carbonation and to better elucidate those compositional factors controlling the reactions. The results of these studies show that the rate of carbonation in CKD is controlled by the extent of carbonation. With increased degrees of conversion, particle-scale processes such as intraparticle diffusion and CaCO3 micropore precipitation patterns begin to limit the rate and possibly the extent of the reactions. Rates may also be influenced by the nature of the oxides participating in the reaction, slowing when the free or unbound oxides are consumed and reaction conditions shift towards the consumption of less reactive Ca species. While microscale processes and composition affects appear to be important at later times, the overall degrees of carbonation observed in the wastes were significant (> 80%), a majority of which occurs within the first 2 days of reaction. Under the operational conditions applied in this study, the degree of carbonation in CKD achieved in column-scale systems was comparable to those observed under ideal batch conditions. In addition, the similarity in sequestration performance among several different CKD waste types indicates that, aside from available oxide content, no compositional factors significantly hinder the ability of the waste to sequester CO2.

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The occurrence of elevated uranium (U) in sandstone aquifers was investigated in the Upper Peninsula of Michigan, focusing on aquifers of the Jacobsville Sandstone. The hydrogeochemical controls on groundwater U concentrations were characterized using a combination of water sampling and spectral gamma-ray logging of sandstone cliffs and residential water wells. 235U/238U isotope ratios were consistent with naturally occurring U. Approximately 25% of the 270 wells tested had U concentrations above the U.S. Environmental Protection Agency Maximum Contaminant Level (MCL) of 30 μg/L, with elevated U generally occurring in localized clusters. Water wells were logged to determine whether groundwater U anomalies could be explained by the heterogeneous distribution of U in the sandstone. Not all wells with relative U enrichment in the sandstone produced water with U above the MCL, indicating that the effect of U enrichment in the sandstone may be modified by other hydrogeochemical factors. Well water had high redox, indicating U is in its highly soluble (VI) valence. Equilibrium modeling indicated that aqueous U is complexed with carbonates. In general, wells with elevated U concentrations had low 235U/238U activity ratios. However, in some areas U concentrations and 235U/238U activity ratios were simultaneously high, possibly indicating differences in rock-water interactions. Limited groundwater age dating suggested that residence time may also help explain variations in well water U concentrations. Low levels of U enrichment (4 to 30 ppm) in the Jacobsville sandstone may make wells in its oxidized aquifers at risk for U concentrations above the MCL. On average, U concentrations were highest in heavy mineral and clay layers and rip up conglomerates. Uranium concentrations above 4 ppm also occurred in siltstones, sandstones and conglomerates. Uranium enrichment was likely controlled by deposition processes, sorption to clays, and groundwater flow, which was controlled by permeability variations in the sandstone. Low levels of U enrichment were found at deltaic, lacustrine and alluvial fan deposits and were not isolated to specific depositional environments.

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This dissertation involves study of various aspects of sulfoxide chemistry. Specifically designed t-butyl and propanenitrile sulfoxides tethered to indole-2-carboxamide were used as a source of intramolecular sulfenylating agents to synthesize novel indolo[3,2-b]-1-5-benzothiazepinones which are structurally analogous to the other biologically active benzothiazepinones. This study reveals that the intramolecular cyclization of sulfoxide follows an electrophilic sulfenylation (Sulfoxide Electrophilic Sulfenylation, SES) reaction pathway. Evidence of the absence of sulfenic acid as a transient reactive intermediate in such intramolecular cyclization is also provided. In another study, sulfoxide was used as a “protecting group” of thioether to synthesize 8-membered, indole substituted, thiazocine-2-acetic acid derivative via Ring Closing Metathesis (RCM). Protection (oxidation) of inert (to RCM) sulfide to sulfoxide followed by RCM produced cyclized product in good yields. Deprotection (reduction) of sulfoxide was achieved using Lawessons Reagent (L.R.). Application of the sulfide-sulfoxide redox cycle to solve the existing difficulties in using RCM methodology to thioethers is illustrated. A new design of a “molecular brake”, based on the sulfide-sulfoxide redox cycle is described. N-Ar rotation in simple isoindolines is controlled by the oxidation state of the proximate sulfur atom. Sulfide [S(II)] shows “free” [brake OFF] N-Ar rotation whereas sulfoxide displayed hindered [brake ON] N-Ar rotation. The semi-empirical molecular orbital (PM3) calculations revealed concerted pyramidalization of amidic nitrogen with N-Ar rotation.

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In 1969, Lovasz asked whether every connected, vertex-transitive graph has a Hamilton path. This question has generated a considerable amount of interest, yet remains vastly open. To date, there exist no known connected, vertex-transitive graph that does not possess a Hamilton path. For the Cayley graphs, a subclass of vertex-transitive graphs, the following conjecture was made: Weak Lovász Conjecture: Every nontrivial, finite, connected Cayley graph is hamiltonian. The Chen-Quimpo Theorem proves that Cayley graphs on abelian groups flourish with Hamilton cycles, thus prompting Alspach to make the following conjecture: Alspach Conjecture: Every 2k-regular, connected Cayley graph on a finite abelian group has a Hamilton decomposition. Alspach’s conjecture is true for k = 1 and 2, but even the case k = 3 is still open. It is this case that this thesis addresses. Chapters 1–3 give introductory material and past work on the conjecture. Chapter 3 investigates the relationship between 6-regular Cayley graphs and associated quotient graphs. A proof of Alspach’s conjecture is given for the odd order case when k = 3. Chapter 4 provides a proof of the conjecture for even order graphs with 3-element connection sets that have an element generating a subgroup of index 2, and having a linear dependency among the other generators. Chapter 5 shows that if Γ = Cay(A, {s1, s2, s3}) is a connected, 6-regular, abelian Cayley graph of even order, and for some1 ≤ i ≤ 3, Δi = Cay(A/(si), {sj1 , sj2}) is 4-regular, and Δi ≄ Cay(ℤ3, {1, 1}), then Γ has a Hamilton decomposition. Alternatively stated, if Γ = Cay(A, S) is a connected, 6-regular, abelian Cayley graph of even order, then Γ has a Hamilton decomposition if S has no involutions, and for some s ∈ S, Cay(A/(s), S) is 4-regular, and of order at least 4. Finally, the Appendices give computational data resulting from C and MAGMA programs used to generate Hamilton decompositions of certain non-isomorphic Cayley graphs on low order abelian groups.

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Boron is an 'electron deficient' element which has a rather fascinating chemical versatility. In the solid state, the elemental boron has neither a pure covalent nor a pure metallic character. As a result, its vast structural dimensionally and peculiar bonding features hold a unique place among other elements in the periodic table. In order to understand and properly describe these unusual bonding features, a detailed and systematic theoretical study is needed. In this work, I will show that some of the qualitative features of boron nanostructures, including clusters, sheets and nanotubes can easily be extracted from the results of first principles calculations based on density functional theory. Specifically, the size-dependent evolution of topological structures and bonding characteristics of boron clusters, Bn will be discussed. Based on the scenario observed in the boron clusters, the unique properties of boron sheets and boron nanotubes will be described. Moreover, the ballistic electron transport in single-walled carbon nanotubes will be considered. It is expected that the theoretical results obtained in the present thesis will initiate further studies on boron nanostructures, which will be helpful in understanding, designing and realizing boron-based nanoscale devices.

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We present studies of the spatial clustering of inertial particles embedded in turbulent flow. A major part of the thesis is experimental, involving the technique of Phase Doppler Interferometry (PDI). The thesis also includes significant amount of simulation studies and some theoretical considerations. We describe the details of PDI and explain why it is suitable for study of particle clustering in turbulent flow with a strong mean velocity. We introduce the concept of the radial distribution function (RDF) as our chosen way of quantifying inertial particle clustering and present some original works on foundational and practical considerations related to it. These include methods of treating finite sampling size, interpretation of the magnitude of RDF and the possibility of isolating RDF signature of inertial clustering from that of large scale mixing. In experimental work, we used the PDI to observe clustering of water droplets in a turbulent wind tunnel. From that we present, in the form of a published paper, evidence of dynamical similarity (Stokes number similarity) of inertial particle clustering together with other results in qualitative agreement with available theoretical prediction and simulation results. We next show detailed quantitative comparisons of results from our experiments, direct-numerical-simulation (DNS) and theory. Very promising agreement was found for like-sized particles (mono-disperse). Theory is found to be incorrect regarding clustering of different-sized particles and we propose a empirical correction based on the DNS and experimental results. Besides this, we also discovered a few interesting characteristics of inertial clustering. Firstly, through observations, we found an intriguing possibility for modeling the RDF arising from inertial clustering that has only one (sensitive) parameter. We also found that clustering becomes saturated at high Reynolds number.

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In recent years, the bio-conjugated nanostructured materials have emerged as a new class of materials for the bio-sensing and medical diagnostics applications. In spite of their multi-directional applications, interfacing nanomaterials with bio-molecules has been a challenge due to somewhat limited knowledge about the underlying physics and chemistry behind these interactions and also for the complexity of biomolecules. The main objective of this dissertation is to provide such a detailed knowledge on bioconjugated nanomaterials toward their applications in designing the next generation of sensing devices. Specifically, we investigate the changes in the electronic properties of a boron nitride nanotube (BNNT) due to the adsorption of different bio-molecules, ranging from neutral (DNA/RNA nucleobases) to polar (amino acid molecules). BNNT is a typical member of III-V compounds semiconductors with morphology similar to that of carbon nanotubes (CNTs) but with its own distinct properties. More specifically, the natural affinity of BNNTs toward living cells with no apparent toxicity instigates the applications of BNNTs in drug delivery and cell therapy. Our results predict that the adsorption of DNA/RNA nucleobases on BNNTs amounts to different degrees of modulation in the band gap of BNNTs, which can be exploited for distinguishing these nucleobases from each other. Interestingly, for the polar amino acid molecules, the nature of interaction appeared to vary ranging from Coulombic, van der Waals and covalent depending on the polarity of the individual molecules, each with a different binding strength and amount of charge transfer involved in the interaction. The strong binding of amino acid molecules on the BNNTs explains the observed protein wrapping onto BNNTs without any linkers, unlike carbon nanotubes (CNTs). Additionally, the widely varying binding energies corresponding to different amino acid molecules toward BNNTs indicate to the suitability of BNNTs for the biosensing applications, as compared to the metallic CNTs. The calculated I-V characteristics in these bioconjugated nanotubes predict notable changes in the conductivity of BNNTs due to the physisorption of DNA/RNA nucleobases. This is not the case with metallic CNTs whose transport properties remained unaltered in their conjugated systems with the nucleobases. Collectively, the bioconjugated BNNTs are found to be an excellent system for the next generation sensing devices.

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Magmatic volatiles play a crucial role in volcanism, from magma production at depth to generation of seismic phenomena to control of eruption style. Accordingly, many models of volcano dynamics rely heavily on behavior of such volatiles. Yet measurements of emission rates of volcanic gases have historically been limited, which has restricted model verification to processes on the order of days or longer. UV cameras are a recent advancement in the field of remote sensing of volcanic SO2 emissions. They offer enhanced temporal and spatial resolution over previous measurement techniques, but need development before they can be widely adopted and achieve the promise of integration with other geophysical datasets. Large datasets require a means by which to quickly and efficiently use imagery to calculate emission rates. We present a suite of programs designed to semi-automatically determine emission rates of SO2 from series of UV images. Extraction of high temporal resolution SO2 emission rates via this software facilitates comparison of gas data to geophysical data for the purposes of evaluating models of volcanic activity and has already proven useful at several volcanoes. Integrated UV camera and seismic measurements recorded in January 2009 at Fuego volcano, Guatemala, provide new insight into the system’s shallow conduit processes. High temporal resolution SO2 data reveal patterns of SO2 emission rate relative to explosions and seismic tremor that indicate tremor and degassing share a common source process. Progressive decreases in emission rate appear to represent inhibition of gas loss from magma as a result of rheological stiffening in the upper conduit. Measurements of emission rate from two closely-spaced vents, made possible by the high spatial resolution of the camera, help constrain this model. UV camera measurements at Kilauea volcano, Hawaii, in May of 2010 captured two occurrences of lava filling and draining within the summit vent. Accompanying high lava stands were diminished SO2 emission rates, decreased seismic and infrasonic tremor, minor deflation, and slowed lava lake surface velocity. Incorporation of UV camera data into the multi-parameter dataset gives credence to the likelihood of shallow gas accumulation as the cause of such events.

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The remarkable advances in nanoscience and nanotechnology over the last two decades allow one to manipulate individuals atoms, molecules and nanostructures, make it possible to build devices with only a few nanometers, and enhance the nano-bio fusion in tackling biological and medical problems. It complies with the ever-increasing need for device miniaturization, from magnetic storage devices, electronic building blocks for computers, to chemical and biological sensors. Despite the continuing efforts based on conventional methods, they are likely to reach the fundamental limit of miniaturization in the next decade, when feature lengths shrink below 100 nm. On the one hand, quantum mechanical efforts of the underlying material structure dominate device characteristics. On the other hand, one faces the technical difficulty in fabricating uniform devices. This has posed a great challenge for both the scientific and the technical communities. The proposal of using a single or a few organic molecules in electronic devices has not only opened an alternative way of miniaturization in electronics, but also brought up brand-new concepts and physical working mechanisms in electronic devices. This thesis work stands as one of the efforts in understanding and building of electronic functional units at the molecular and atomic levels. We have explored the possibility of having molecules working in a wide spectrum of electronic devices, ranging from molecular wires, spin valves/switches, diodes, transistors, and sensors. More specifically, we have observed significant magnetoresistive effect in a spin-valve structure where the non-magnetic spacer sandwiched between two magnetic conducting materials is replaced by a self-assembled monolayer of organic molecules or a single molecule (like a carbon fullerene). The diode behavior in donor(D)-bridge(B)-acceptor(A) type of single molecules is then discussed and a unimolecular transistor is designed. Lastly, we have proposed and primarily tested the idea of using functionalized electrodes for rapid nanopore DNA sequencing. In these studies, the fundamental roles of molecules and molecule-electrode interfaces on quantum electron transport have been investigated based on first-principles calculations of the electronic structure. Both the intrinsic properties of molecules themselves and the detailed interfacial features are found to play critical roles in electron transport at the molecular scale. The flexibility and tailorability of the properties of molecules have opened great opportunity in a purpose-driven design of electronic devices from the bottom up. The results that we gained from this work have helped in understanding the underlying physics, developing the fundamental mechanism and providing guidance for future experimental efforts.

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Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.

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Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

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High resolution digital elevation models (DEMs) of Santiaguito and Pacaya volcanoes, Guatemala, were used to estimate volume changes and eruption rates between 1954 and 2001. The DEMs were generated from contour maps and aerial photography, which were analyzed in ArcGIS 9.0®. Because both volcanoes were growing substantially over the five decade period, they provide a good data set for exploring effective methodology for estimating volume changes. The analysis shows that the Santiaguito dome complex grew by 0.78 ± 0.07 km3 (0.52 ± 0.05 m3 s-1) over the 1954-2001 period with nearly all the growth occurring on the El Brujo (1958-75) and Caliente domes (1971-2001). Adding information from field data prior to 1954, the total volume extruded from Santiaguito since 1922 is estimated at 1.48 ± 0.19 km3. Santiaguito’s growth rate is lower than most other volcanic domes, but it has been sustained over a much longer period and has undergone a change toward more exogenous and progressively slower extrusion with time. At Santiaguito some of the material being added at the dome is subsequently transported downstream by block and ash flows, mudflows and floods, creating channel shifting and areas of aggradation and erosion. At Pacaya volcano a total volume of 0.21 ± 0.05 km3 was erupted between 1961 and 2001 for an average extrusion rate of 0.17 ± 0.04 m3 s-1. Both the Santiaguito and Pacaya eruption rate estimates reported here are minima, because they do not include estimates of materials which are transported downslope after eruption and data on ashfall which may result in significant volumes of material spread over broad areas. Regular analysis of high resolution DEMs using the methods outlined here, would help quantify the effects of fluvial changes to downstream populated areas, as well as assist in tracking hazards related to dome collapse and eruption.

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This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.