Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (p. 103-108).

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (leaves 116-123).

Zugl.: Karlsruhe, Univ., Diss., 2008 / Hergestellt on demand

Thesis (Ph.D.)--Boston University / Advances in remote sensing and associated capabilities are expected to proceed in a number of ways in the era of the Earth Observing System (EOS). More complex multitemporal, multi-source data sets will become available, requiring more sophisticated analysis methods. This research explores the applications of artificial neural networks in land-cover mapping, forward and inverse canopy modeling and change detection. For land-cover mapping a multi-layer feed-forward neural network produced 89% classification accuracy using a single band of multi-angle data from the Advanced Solidstate Array Spectroradiometer (ASAS). The principal results include the following: directional radiance measurements contain much useful information for discrimination among land-cover classes; the combination of multi-angle and multi-spectral data improves the overall classification accuracy compared with a single multi-angle band; and neural networks can successfully learn class discrimination from directional data or multi-domain data. Forward canopy modeling shows that a multi-layer feed-forward neural network is able to predict the bidirectional reflectance distribution function (BRDF) of different canopy sites with 90% accuracy. Analysis of the signal captured by the network indicates that the canopy structural parameters, and illumination and viewing geometry, are essential for predicting the BRDF of vegetated surfaces. The inverse neural network model shows that the R2 between the network-predicted canopy parameters and the actual canopy parameters is 0.85 for canopy density and 0.75 for both the crown shape and the height parameters. [TRUNCATED]

abstract: Stratification is a dominant feature of all planetary interiors. Fine-scale structure associated with layering, as well as heterogeneities hold important clues on a planet's compositional, thermal, and dynamical state, as well as its evolution. This research centers on using data from seismic arrays, networks of seismic sensors, and array processing methodologies to map the fine scale structure in the Earth's upper mantle and deep layering in the Moon - Earth and Moon are the only two planetary bodies with seismic available data for such analyses. Small-scale structure in the Earth's upper mantle can give rise to seismic wave scattering. I studied high frequency data from the Warramunga Array in Australia using array seismology. I developed and employed back-projection schemes to map the possible upper mantle scattering or reflection locations. Mapped scatterers show good correlation to strong lateral P-wave velocity gradients in tomography models and may be associated with the complex tectonic history beneath north of Australia. The minimum scale of scatterers relates to the seismic wavelength, which is roughly between 5 and 10 km in the upper mantle for the frequencies we study. The Apollo Passive Seismic Experiment (APSE) consisted of four 3-component seismometers deployed between 1969 and 1972 that continuously recorded lunar ground motion until late 1977. I studied the deep lunar interior with array methods applied to the legacy APSE dataset. The stack results suggest the presence of a solid inner and fluid outer core, overlain by a partially molten boundary layer, but their reflector impedance contrasts and reflector depths are not well constrained. With a rapidly increasing number of available modern broadband data, I developed a package, Discovery Using Ducttape Excessively (DUDE), to quickly generate plots for a comprehensive view of earthquake data. These plots facilitate discovery of unexpected phenomena. This dissertation identifies evidence for small-scale heterogeneities in Earth's upper mantle, and deeper lunar layering structure. Planetary interiors are complex with the heterogeneities on many scales, and discontinuities of variable character. This research demonstrates that seismic array methods are well-suited for interrogating heterogeneous phenomena, especially considering the recent rapid expansion of easily available dense network data. / Dissertation/Thesis / Ph.D. Geological Sciences 2011

Orientador: Patrícia Pintor dos Reis / Resumo: Introdução: o Edema de Reinke (ER) é uma lesão laríngea considerada benigna relacionada ao tabagismo. Dados em literatura relatam associações entre o ER e a detecção de diferentes graus de displasia e carcinoma in situ, bem como alterações na imunoexpressão de proteínas tumorais como a p53. Alguns autores classificam o ER entre as lesões pré-malignas, com risco de transformação e progressão para carcinoma de laringe. Não havendo consenso na literatura, torna-se necessária a realização de estudos moleculares. Objetivos: caracterizar o perfil genômico global de alterações no número de cópias do DNA em amostras de pacientes com ER. Métodos: oito amostras removidas por microcirurgia foram submetidas à extração do DNA. Os perfis de alteração no número de cópias genômicas e os genes candidatos associados foram analisados pela metodologia da hibridação genômica comparativa (CGH array), utilizando-se a plataforma de 4x180K (Agilent Technologies). Os dados de microarranjos foram analisados utilizando o programa CytoGenomics v4.0.2.21 (Agilent Technologies). As alterações no número de cópias (CNAs) obtidas foram comparadas com o banco de dados Database of Genomic Variants (DGV). A classificação dos genes selecionados para análise foi realizada baseada em dados descritos no National Center for Biotechnology Information (NCBI). Resultados: Foram encontrados perdas, ganhos ou deleções em 54 genes, um RNA não codificador longo intergênico (lincRNA), seis sequências hipotéticas e 10 microRN... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

DNA copy number alterations (CNAs) are genetic changes that can produce adverse effects in numerous human diseases, including cancer. CNAs are segments of DNA that have been deleted or amplified and can range in size from one kilobases to whole chromosome arms. Development of array comparative genomic hybridization (aCGH) technology enables CNAs to be measured at sub-megabase resolution using tens of thousands of probes. However, aCGH data are noisy and result in continuous valued measurements of the discrete CNAs. Consequently, the data must be processed through algorithmic and statistical techniques in order to derive meaningful biological insights. We introduce model-based approaches to analysis of aCGH data and develop state-of-the-art solutions to three distinct analytical problems. In the simplest scenario, the task is to infer CNAs from a single aCGH experiment. We apply a hidden Markov model (HMM) to accurately identify CNAs from aCGH data. We show that borrowing statistical strength across chromosomes and explicitly modeling outliers in the data, improves on baseline models. In the second scenario, we wish to identify recurrent CNAs in a set of aCGH data derived from a patient cohort. These are locations in the genome altered in many patients, providing evidence for CNAs that may be playing important molecular roles in the disease. We develop a novel hierarchical HMM profiling method that explicitly models both statistical and biological noise in the data and is capable of producing a representative profile for a set of aCGH experiments. We demonstrate that our method is more accurate than simpler baselines on synthetic data, and show our model produces output that is more interpretable than other methods. Finally, we develop a model based clustering framework to stratify a patient cohort, expected to be composed of a fixed set of molecular subtypes. We introduce a model that jointly infers CNAs, assigns patients to subgroups and infers the profiles that represent each subgroup. We show our model to be more accurate on synthetic data, and show in two patient cohorts how the model discovers putative novel subtypes and clinically relevant subgroups. / Science, Faculty of / Computer Science, Department of / Graduate

Small Cell Lung Cancer (SCLC) is a very aggressive neuroendocrine tumour of the lung, which demonstrates a 5 year survival of only 10% for extensive stage disease (20-30% for limited stage), with only modest improvement over the last few decades. Identification of new molecular diagnostic and therapeutic targets is thus imperative. Previous efforts in identifying molecular changes in SCLC by gene expression profiling using microarrays have facilitated disease classification but yielded very limited information on SCLC biology. Previous DNA studies have been successful in identifying several loci important to SCLC. However the low resolution of conventional chromosomal Comparative Genomic Hybridization (CGH) has limited the findings to large chromosomal regions with only a few specific candidate genes discovered to date. Thus, to further understand the biological behaviour of SCLC, better methods for studying the genomic alterations in SCLC are necessary. This thesis highlights the development of array CGH technology for the high resolution dissection of aneuploidy in cancer genomes and the application of this new technology to the study of SCLC. I present the development of the first whole genome CGH array which offered unprecedented resolution in the profiling of cancer genomes allowing fine mapping of genes in a single experiment. Through application of DNA based analysis in conjunction with integrated expression analysis and comparison of SCLC to less aggressive non-small cell lung tumours I have identified novel patterns of pathway disruption specific to SCLC. This included alteration to Wnt pathway members and striking patterns of cell cycle activation through predominantly downstream disruption of signalling pathways including direct activation of the E2F transcription factors, which are normally repressed by the Rb gene. Analysis of targets of the E2F/Rb pathway identified EZH2 as being specifically hyper-activated in SCLC, compared to NSCLC. EZH2 is a polycomb group gene involved in the control of many cellular functions including targeted DNA methylation and escape from senescence in hematopoietic stem cells. Taken together these results suggest that in SCLC, downstream disruption may replace multiple upstream alterations leading to activation independent of a specific mitogenic pathway, and that EZH2 represents a potentially important therapeutic target. / Medicine, Faculty of / Pathology and Laboratory Medicine, Department of / Graduate

No description available.

Multiple wave energy devices supported by a common structure represent one possible method of efficiently converting ocean wave energy into electricity. In this study, experimental measurements of multiple small-scale wave energy devices are reported to assist the development and validation of numerical models. Through observation and measurement, the response of two float geometries subjected to a range of wave conditions and device settings were determined. A range of regular wave conditions were identified that caused a linear relationship to occur between the heave displacement amplitude of the float and the incident wave amplitude. These test cases will enable comparisons to be made with linear simulations of response. Tests conducted in various wave conditions have highlighted the capability of altering the device response by changing the equilibrium draft of one float geometry. Additional damping on the upper surface of the float, due to wave overtopping, could be exploited as a method of limiting the heave response of the device in large amplitude waves. The influence of hydrodynamic interactions on arrays of closely spaced devices has been experimentally investigated for devices subjected to regular and irregular wave conditions. The magnitude and occurrence of interactions and their affect on the individual device response is demonstrably dependent on the incident wave frequency and device separation distance. Compared to an isolated device, positive interactions result in higher average power outputs for an array of devices at certain wave frequencies. Positive interactions occuring at particular wave frequencies are balanced by negative interactions at other wave frequencies, in agreement with published numerical studies of array performance. Varying the level of mechanical damping applied to the float through the power take-off system results in a frequency shift of the calculated power transfer function and alters the motion path of the float. This finding implies that the level of generator torque could be used as an alternative method to tune the response of the device based on the measured incident wave-field. Several time-averaged and time-varying approaches to simulating the response of a wave energy device subjected to wave-field forcing and undergoing free response have been studied. By comparing the simulated and measured responses, the feasibility of using linear and non-linear force terms in a time-varying model has been assessed. In general, single degree-of-freedom simulations based on linear hydrodynamic parameters tend to over-predict device response amplitudes, requiring the application of additional damping. The simulation approach which resulted in the closest agreement with measured responses required the combination of linear diffraction force and radiation added mass terms with non-linear drag and buoyancy force terms, as well as body inertia and gravity forces. This approach goes part way to simulating the complex time-varying hydrodynamics associated with a wave energy device subjected to wave-field forcing.