Ce travail est consacré à l'étude de la source sismique en utilisant des données de champ proche. Selon la quantité et la qualité des données disponibles, nous avons appliqué différentes méthodes pour caractériser la rupture sismique. Nous avons, tout d'abord, validé des méthodes macrosismiques sur des séismes français récents. Ces données permettent d'estimer la localisation et la taille des séismes historiques et sont utilisées pour caractériser les séismes à prendre en compte lors de l'évaluation de l'aléa dans des régions à sismicité modérée. Les données géodésiques (SAR, GPS) nous ont permis d'estimer la distribution du glissement sur la faille lors du séisme californien de Landers (1992). Ces données nous ont permis de préciser la localisation et la géométrie des failles ayant joué lors des principaux événements de la séquence sismique italienne de Colfiorito (1997). Enfin les données de mouvement fort nous ont permis d'estimer le pendage de la faille ayant rompu lors du séisme indien de Chamoli (1999). Nous avons utilisé des données de mouvement fort pour contraindre le développement de la rupture lors du séisme mexicain de Oaxaca (1999). Les données de mouvement fort ont été utilisées en association avec des données géodésiques pour remonter au développement temporel de la rupture lors du séisme de Landers et de la séquence sismique de Colfiorito. En ce qui concerne le séisme de Landers, la qualité et la complémentarité des données nous ont permis d'obtenir un véritable film du glissement. La rupture est hétérogène. On note la présence de zones où le glissement est plus important qu'ailleurs. Ces zones sont séparées par des régions qui correspondent aux zones de relais entre les segments de faille où le glissement est moindre et où la vitesse de rupture diminue.

<p>The goal of this thesis work is to enable an existing UHF radar to operate in the VHF band instead. In order to achieve this, new coherent local oscillators are required. Different options are suggested and one of them is implemented and analyzed.</p>

<p>Rational conversion of biologically active peptides to nonpeptide compounds with retained activity is an appealing approach in drug development. One important objective of the work presented in this thesis was to use computational modeling to aid in such a conversion of the peptide angiotensin II (Ang II, Asp-Arg-Val-Tyr-Ile-His-Pro-Phe). An equally important objective was to gain an understanding of the requirements for ligand binding to the Ang II receptors, with a focus on interactions with the AT₂ receptor.</p><p>The bioactive conformation of a peptide can provide important guidance in peptidomimetic design. By designing and introducing well-defined secondary structure mimetics into Ang II the bioactive conformation can be addressed. In this work, both γ- and β-turn mimetic scaffolds have been designed and characterized for incorporation into Ang II. Using conformational analysis and the pharmacophore recognition method DISCO, a model was derived of the binding mode of the pseudopeptide Ang II analogues. This model indicated that the positioning of the Arg side chain was important for AT₂ receptor binding, which was also supported when the structure–activity relationship of Ang II was investigated by performing a glycine scan.</p><p>To further examine ligand binding, a 3D model of the AT₂ receptor was constructed employing homology modeling. Using this receptor model in a docking study of the ligands, binding modes were identified that were in agreement with data from point-mutation studies of the AT₂ receptor.</p><p>By investigating truncated Ang II analogues, small pseudopeptides were developed that were structurally similar to nonpeptide AT₂ receptor ligands. For further guidance in ligand design of nonpeptide compounds, three-dimensional quantitative structure–activity relationship models for AT₁ and AT₂ receptor affinity as well as selectivity were derived. </p>

Despite the vast myriad of applications and the long way it has come, MRI is still a relatively new field of knowledge with much prospect for more advancement and expansion. This work is mainly concerned with two gradient echo imaging methods which are directly or indirectly related to blood vessel imaging as well as iron depiction in the human brain. In each case, new methods are introduced that overcome existing limitations. For blood vessel imaging, 3D Time-of-Flight (TOF) MR angiography (MRA) with its known capability to image arteries as well as veins was implemented at 3.0 T. At this field strength, the significant RF profile variability due to RF inhomogeneity is a liability for circle-of-Willis imaging in the human brain that was overcome by introducing a new means to counter the RF effects through increased slope of the ramped pulse. In addition a new method is introduced for TOF MRA with two-in-one arterial and venous 3D TOF imaging to overcome the significant scan time overhead of a traditional second venous scan and for cutting down RF power utilization. Using this method, total scan time could be reduced by as much as 46% and specific absorption rate (SAR) due to spatial saturation could be reduced by as much as 92%. For iron sensitive imaging, Susceptibility Weighted Imaging (SWI) was developed at 4.7 T. The phase SWI method was used to visualize lesions in Multiple Sclerosis (MS) patients and was experimentally compared to the visibility on standard T2 weighting with results demonstrating visualization of new lesions, with 18% of total lesions exclusively visible on SWI. A new approach to 3D imaging was also introduced to enable accurate oblique SWI scanning while overcoming the current restriction to axial imaging to produce correct phase effects for oblique imaging. New results from oblique phase imaging were presented and the phase measurements from key brain structures were successfully validated against images obtained by the current standard of axial imaging.

Rational conversion of biologically active peptides to nonpeptide compounds with retained activity is an appealing approach in drug development. One important objective of the work presented in this thesis was to use computational modeling to aid in such a conversion of the peptide angiotensin II (Ang II, Asp-Arg-Val-Tyr-Ile-His-Pro-Phe). An equally important objective was to gain an understanding of the requirements for ligand binding to the Ang II receptors, with a focus on interactions with the AT2 receptor. The bioactive conformation of a peptide can provide important guidance in peptidomimetic design. By designing and introducing well-defined secondary structure mimetics into Ang II the bioactive conformation can be addressed. In this work, both γ- and β-turn mimetic scaffolds have been designed and characterized for incorporation into Ang II. Using conformational analysis and the pharmacophore recognition method DISCO, a model was derived of the binding mode of the pseudopeptide Ang II analogues. This model indicated that the positioning of the Arg side chain was important for AT2 receptor binding, which was also supported when the structure–activity relationship of Ang II was investigated by performing a glycine scan. To further examine ligand binding, a 3D model of the AT2 receptor was constructed employing homology modeling. Using this receptor model in a docking study of the ligands, binding modes were identified that were in agreement with data from point-mutation studies of the AT2 receptor. By investigating truncated Ang II analogues, small pseudopeptides were developed that were structurally similar to nonpeptide AT2 receptor ligands. For further guidance in ligand design of nonpeptide compounds, three-dimensional quantitative structure–activity relationship models for AT1 and AT2 receptor affinity as well as selectivity were derived.

The hepatitis C virus (HCV), with a global prevalence of roughly 2%, is among the most serious diseases today. Among the more promising HCV targets is the NS3 protease, for which several drug candidates have entered clinical trials. In this work, computational methods have been developed and applied to the design of inhibitors of the HCV NS3 protease. Comparative molecular field analysis (CoMFA) modeling and molecular docking are the two main computational tools used in this work. CoMFA is currently the most widely used 3D-QSAR method. Methodology for improving its predictive performance by evaluating 6120 combinations of non-default parameters has been developed. This methodology was tested on 9 data sets for various targets and found to consistently provide models of enhanced predictive accuracy. Validation was performed using q2, r2pred and response variable randomization. Molecular docking was used to develop SARs in two series of inhibitors of the HCV NS3 protease. In the first series, preliminary investigations indicated that replacement of P2 proline with phenylglycine would improve potency. Docking suggested that phenylglycine-based inhibitors may participate in two additional interactions but that the larger, more flexible phenylglycine group may result in worse ligand fit, explaining the loss in potency. In the second series, β-amino acids were explored as α-amino acid substitutes. Although β-amino acid substitution may reduce the negative attributes of peptide-like compounds, this study showed that β-amino acid substitution resulted in reduced potency. The P3 position was least sensitive to substitution and the study highlighted the importance of interactions in the oxyanion hole. Finally, docking was used to provide the conformations and alignment necessary for a CoMFA model. This CoMFA model, derived using default settings, had q2 = 0.31 and r2pred = 0.56. Application of the optimization methodology provided a more predictive model with q2 = 0.48 and r2pred = 0.68.

The capability to observe ocean swell using spaceborne Synthetic Aperture Radar (SAR) has been demonstrated starting with ERS-1 mission in 1992. This dissertation shows how ocean swell properties can be used to combine swell observations of heterogeneous quality and acquired at various times and locations for the observation and forecast of ocean swell fieldsusing ASAR instrument on-board ENVISAT. The first section is a review of how ocean swell spectra can be derived from the SAR complex images of the ocean surface using a quasi-linear transformation. Then, significant swell heights, peak periods and peak directions from in situ measurements are used to assess the accuracy of the SAR observed swell spectra. Using linear propagation in deep ocean, a new swell field reconstruction methodologyis developed in order to gather SAR swell observations related to the same swell field. Propagated from their generation region, these observations render the spatio-temporal properties of the emanating ocean swell fields. Afterwards, a methodology is developed for the exclusion of outliers taking advantage of the swell field consistency. Also, using the irregularly sampled SAR observations, quality controlled estimations of swell field integral parameters are produced on a regular space-time grid. Validation against in situ measurements reveals the dramatic impact of the density of propagated observations on the integral parameters estimated accuracy. Specifically, this parameter is shown to be very dependent on the satellite orbit. Finally, comparisons with the numerical wave model WAVEWATCH-III prove it could potentially benefit from the SAR swell field estimates for assimilation purposes.

The goal of this thesis work is to enable an existing UHF radar to operate in the VHF band instead. In order to achieve this, new coherent local oscillators are required. Different options are suggested and one of them is implemented and analyzed.

The accurate estimation of snow water equivalent (SWE) in the Canadian sub-arctic is integral to climate variability studies and water availability forecasts for economic considerations (drinking water, hydroelectric power generation). Common passive microwave (PM) snow water equivalent (SWE) algorithms that utilize the differences in brightness temperature (Tb) at 37 GHz – 19 GHz falter in lake-rich tundra environments because of the inclusion of lakes within PM pixels. The overarching goal of this research was to investigate the use of multiple platforms and methodologies to observe and quantify the effects of lake ice and sub-ice water on passive microwave emission for the purpose of improving snow water equivalent (SWE) retrieval algorithms. Using in situ snow and ice measurements as input, the Helsinki University of Technology (HUT) multi-layer snow emission model was modified to include an ice layer below the snow layer. Emission for 6.9, 19, 37 and 89 GHz were simulated at horizontal and vertical polarizations, and were validated by high resolution airborne passive microwave measurements coincident with in situ sampling sites over two lakes near Inuvik, Northwest Territories (NWT). Overall, the general magnitude of brightness temperatures were estimated by the HUT model for 6.9 and 19 GHz H/V, however the variability was not. Simulations produced at 37 GHz exhibited the best agreement relative to observed temperatures. However, emission at 37 GHz does not interact with the radiometrically cold water, indicating that ice properties controlling microwave emission are not fully captured by the HUT model. Alternatively, active microwave synthetic aperture radar (SAR) measurements can be used to identify ice properties that affect passive microwave emission. Dual polarized X-band SAR backscatter was utilized to identify ice types by the segmentation program MAGIC (MAp Guided Ice Classification). Airborne passive microwave transects were grouped by ice type classes and compared to backscatter measurements. In freshwater, where there were few areas of high bubble concentration at the ice/water interface Tbs exhibited positive correlations with cross-polarized backscatter, corresponding to ice types (from low to high emission/backscatter: clear ice, transition zone between clear and grey ice, grey ice and rafted ice). SWE algorithms were applied to emission within each ice type producing negative or near zero values in areas of low 19 GHz Tbs (clear ice, transition zone), but also produced positive values that were closer to the range of in situ measurements in areas of high 19 GHz Tbs (grey and rafted ice). Therefore, cross-polarized X-band SAR measurements can be used as a priori ice type information for spaceborne PM algorithms, providing information on ice types and ice characteristics (floating, frozen to bed), integral to future tundra-specific SWE retrieval algorithms.

In this thesis we develop algorithms for the processing of textures and images using a ladder-based biorthogonal directional filter bank (DFB). This work is based on the DFB originally proposed by Bamberger and Smith. First we present a novel implementation of this filter bank using ladder structures. This new DFB provides non-trivial FIR perfect reconstruction systems which are computationally very efficient. Furthermore we address the lack of shift-invariance in the DFB by presenting a novel undecimated DFB that preserves the computational simplicity of its maximally decimated counterpart. Finally, we study the use of the DFB in combination with pyramidal structures to form polar-separable image decompositions. Using the proposed filter banks we develop and evaluate algorithms for texture classification, segmentation and synthesis. We perform a comparative study with other image representations and find that the DFB provides some of the best results reported on the data sets used. Using the proposed directional pyramids we adapt wavelet thresholding algorithms. We find that our decompositions provide better edge and contour preservation than the best results reported using the undecimated discrete wavelet transform. Finally, we apply the developed algorithms to the analysis and processing of synthetic aperture radar (SAR) imagery. SAR image analysis is impaired by the presence of speckle noise. Our first objective will be to study the removal of speckle to enhance the visual quality of the image. Additionally, we implement land cover segmentation and classification algorithms taking advantage of the textural characteristics of SAR images. Finally, we propose a model-based SAR image compression algorithm in which the speckle component is separated from the structural features of a scene. The speckle component is captured with a texture model and the scene component is coded with a wavelet coder at very low bit rates. The resulting decompressed images have a better perceptual quality than SAR images compressed without removing speckle.