23 resultados para 029900 OTHER PHYSICAL SCIENCES


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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.

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Volcán de Colima has been continuously erupting since the onset of dome growth in 1998. This period of unrest has had 4 prominent periods; 1998-1999, 2003, 2004-2005, and the current dome growth that began in February of 2007. Each of these episodes was marked by lava extrusion forming a dome and lava flows, followed by explosions that destroyed the dome. The Correlation Spectrometer (COSPEC) was used to determine SO2 emission rates on 164 days from May 2003 to February 2007, using both stationary ground based scans and some flight traverses. Scans were separated into the categories of explosive degassing and passive, or background degassing. These scans show variation in the SO2 flow rate from below detection limit (~3 t/d depending on environmental conditions) during background, passive emissions to a peak of 2949 t/d (34 kilograms/second) during an explosion on 9 October, 2004. Both passive and explosive degassing increased when there was lava extrusion in 2004 and with the increased explosive activity in 2005. These two different processes of degassing wax with each other when activity increases and wane together as well, indicating a parallel cyclicity in the volcanic eruption and degassing rates, where the conduit partially seals (pressurizes) between explosions. Colima’s gas and eruptive behavior is compared to similar systems such as Santiaguito and Soufrière Hills, Montserrat. About 2/3 of Colima’s SO2 degassing, amounting to 1.3 x 105 tonnes in 3.74 yrs has come in short lived small (VEI=0-1) vertical explosions that occurred at the rate of 100-3000explosions/ month, and the remaining third has occured in continuous passive degassing. Colima emits sulfur at a rate equivalent to about 0.04 to 0.08 wt % S, similar to other andesitic convergent plate boundary volcanoes. There has been an explosive destruction of the dome in every cycle for that past 5 years, and it is assumed that the current dome which began growth in February, 2007 (just at the end of this study) will be destroyed. Higher emission rates seen in the quiescence of 2006 may have eased the pressure at the time, resulting in the slow effusion of the current dome and lack of explosivity.

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Maderas volcano is a small, andesitic stratovolcano located on the island of Ometepe, in Lake Nicaragua, Nicaragua with no record of historic activity. Twenty-one samples were collected from lava flows from Maderas in 2010. Selected samples were analyzed for whole-rock geochemical data using ICP-AES and/or were dated using the 40Ar/39Ar method. The results of these analyses were combined with previously collected data from Maderas as well as field observations to determine the eruptive history of the volcano and create a geologic map. The results of the geochemical analyses indicate that Maderas is a typical Central American andesitic volcano similar to other volcanoes in Nicaragua and Costa Rica and to its nearest neighbor, Concepción volcano. It is different from Concepción in one important way – higher incompatible elements. Determined age dates range from 176.8 ± 6.1 ka to 70.5 ± 6.1 ka. Based on these ages and the geomorphology of the volcano which is characterized by a bisecting graben, it is proposed that Maderas experienced two clear generations of development with three separate phases of volcanism: initial build-up of the older cone, pre-graben lava flows, and post-graben lava flows. The ages also indicate that Maderas is markedly older than Concepción which is historically active. Results were also analyzed regarding geologic hazards. The 40Ar/39Ar ages indicate that Maderas has likely been inactive for tens of thousands of years and the risk of future volcanic eruptions is low. However, earthquake, lahar and landslide hazards exist for the communities around the volcano. The steep slopes of the eroded older cone are the most likely source of landslide and lahar hazards.

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Boron nitride nanotubes (BNNTs) are structurally similar to carbon nanotubes (CNTs), but exhibit completely different physical and chemical properties. Thus, BNNTs with various interesting properties may be complementary to CNTs and provide an alternative perspective to be useful in different applications. However, synthesis of high quality of BNNTs is still challenging. Hence, the major goals of this research work focus on the fundamental study of synthesis, characterizations, functionalization, and explorations of potential applications. In this work, we have established a new growth vapor trapping (GVT) approach to produce high quality and quantity BNNTs on a Si substrate, by using a conventional tube furnace. This chemical vapor deposition (CVD) approach was conducted at a growth temperature of 1200 °C. As compared to other known approaches, our GVT technique is much simpler in experimental setup and requires relatively lower growth temperatures. The as-grown BNNTs are fully characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), Energy Filtered Mapping, Raman spectroscopy, Fourier Transform Infra Red spectroscopy (FTIR), UV-Visible (UV-vis) absorption spectroscopy, etc. Following this success, the growth of BNNTs is now as convenient as growing CNTs and ZnO nanowires. Some important parameters have been identified to produce high-quality BNNTs on Si substrates. Furthermore, we have identified a series of effective catalysts for patterned growth of BNNTs at desirable or pre-defined locations. This catalytic CVD technique is achieved based on our finding that MgO, Ni or Fe are the good catalysts for the growth of BNNTs. The success of patterned growth not only explains the role of catalysts in the formation of BNNTs, this technique will also become technologically important for future device fabrication of BNNTs. Following our success in controlled growth of BNNTs on substrates, we have discovered the superhydrophobic behavior of these partially vertically aligned BNNTs. Since BNNTs are chemically inert, resistive to oxidation up to ~1000°C, and transparent to UV-visible light, our discovery suggests that BNNTs could be useful as self-cleaning, insulating and protective coatings under rigorous chemical and thermal conditions. We have also established various approaches to functionalize BNNTs with polymeric molecules and carbon coatings. First, we showed that BNNTs can be functionalized by mPEG-DSPE (Polyethylene glycol-1,2-distearoyl-sn-glycero-3-phosphoethanolamine), a bio-compatible polymer that helps disperse and dissolve BNNTs in water solution. Furthermore, well-dispersed BNNTs in water can be cut from its original length of >10µm to(>20hrs). This success is an essential step to implement BNNTs in biomedical applications. On the other hand, we have also succeeded to functionalize BNNTs with various conjugated polymers. This success enables the dispersion of BNNTs in organic solvents instead of water. Our approaches are useful for applications of BNNTs in high-strength composites. In addition, we have also functionalized BNNTs with carbon decoration. This was performed by introducing methane (CH4) gas into the growth process of BNNT. Graphitic carbon coatings can be deposited on the side wall of BNNTs with thicknesses ranging from 2 to 5 nm. This success can modulate the conductivity of pure BNNTs from insulating to weakly electrically conductive. Finally, efforts were devoted to explore the application of the wide bandgap BNNTs in solar-blind deep UV (DUV) photo-detectors. We found that photoelectric current generated by the DUV light was dominated in the microelectrodes of our devices. The contribution of photocurrent from BNNTs is not significant if there is any. Implication from these preliminary experiments and potential future work are discussed.

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The exsolution of volatiles from magma maintains an important control on volcanic eruption styles. The nucleation, growth, and connectivity of bubbles during magma ascent provide the driving force behind eruptions, and the rate, volume, and ease of gas exsolution can affect eruptive activity. Volcanic plumes are the observable consequence of this magmatic degassing, and remote sensing techniques allow us to quantify changes in gas exsolution. However, until recently the methods used to measure volcanic plumes did not have the capability of detecting rapid changes in degassing on the scale of standard geophysical observations. The advent of the UV camera now makes high sample rate gas measurements possible. This type of dataset can then be compared to other volcanic observations to provide an in depth picture of degassing mechanisms in the shallow conduit. The goals of this research are to develop a robust methodology for UV camera field measurements of volcanic plumes, and utilize this data in conjunction with seismoacoustic records to illuminate degassing processes. Field and laboratory experiments were conducted to determine the effects of imaging conditions, vignetting, exposure time, calibration technique, and filter usage on the UV camera sulfur dioxide measurements. Using the best practices determined from these studies, a field campaign was undertaken at Volcán de Pacaya, Guatemala. Coincident plume sulfur dioxide measurements, acoustic recordings, and seismic observations were collected and analyzed jointly. The results provide insight into the small explosive features, variations in degassing rate, and plumbing system of this complex volcanic system. This research provides useful information for determining volcanic hazard at Pacaya, and demonstrates the potential of the UV camera in multiparameter studies.