Sequential estimation of time-varying multipath channel for MIMO-OFDM systems

In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.

Materials and Mix Optimization Procedures for PCC Pavements, March 2006

Severe environmental conditions, coupled with the routine use of deicing chemicals and increasing traffic volume, tend to place extreme demands on portland cement concrete (PCC) pavements. In most instances, engineers have been able to specify and build PCC pavements that met these challenges. However, there have also been reports of premature deterioration that could not be specifically attributed to a single cause. Modern concrete mixtures have evolved to become very complex chemical systems. The complexity can be attributed to both the number of ingredients used in any given mixture and the various types and sources of the ingredients supplied to any given project. Local environmental conditions can also influence the outcome of paving projects. This research project investigated important variables that impact the homogeneity and rheology of concrete mixtures. The project consisted of a field study and a laboratory study. The field study collected information from six different projects in Iowa. The information that was collected during the field study documented cementitious material properties, plastic concrete properties, and hardened concrete properties. The laboratory study was used to develop baseline mixture variability information for the field study. It also investigated plastic concrete properties using various new devices to evaluate rheology and mixing efficiency. In addition, the lab study evaluated a strategy for the optimization of mortar and concrete mixtures containing supplementary cementitious materials. The results of the field studies indicated that the quality management concrete (QMC) mixtures being placed in the state generally exhibited good uniformity and good to excellent workability. Hardened concrete properties (compressive strength and hardened air content) were also satisfactory. The uniformity of the raw cementitious materials that were used on the projects could not be monitored as closely as was desired by the investigators; however, the information that was gathered indicated that the bulk chemical composition of most materials streams was reasonably uniform. Specific minerals phases in the cementitious materials were less uniform than the bulk chemical composition. The results of the laboratory study indicated that ternary mixtures show significant promise for improving the performance of concrete mixtures. The lab study also verified the results from prior projects that have indicated that bassanite is typically the major sulfate phase that is present in Iowa cements. This causes the cements to exhibit premature stiffening problems (false set) in laboratory testing. Fly ash helps to reduce the impact of premature stiffening because it behaves like a low-range water reducer in most instances. The premature stiffening problem can also be alleviated by increasing the water–cement ratio of the mixture and providing a remix cycle for the mixture.

Seismic attenuation in heterogeneous partially saturated rocks

We study wave-induced fluid flow effects in porous rocks partially saturated with gas and water, where the saturation patterns are governed by mesoscopic heterogeneities associated with the dry frame properties. The link between the dry frame properties and the gas saturation is defined by the assumption of capillary pressure equilibrium, which in the presence of heterogeneity implies that neighboring regions can exhibit different levels of saturation. In order to determine the equivalent attenuation and phase velocity of the synthetic rock samples considered in this study, we apply a numerical upscaling procedure, which permits to take into account mesoscopic heterogeneities associated with the dry frame properties as well as spatially continuous variations of the pore fluid properties. We consider numerical experiments to analyze such effects in heterogeneous partially saturated porous media, where the saturation field is determined by realistic variations in porosity. Our results indicate that the spatially continuous nature of gas saturation inherent to this study is a critical parameter controlling the seismic response of these environments, which in turn suggests that the physical mechanisms governing partial saturation should be accounted for when analyzing seismic data in a poro-elastic context.

Parallel imaging with phase scrambling.

PURPOSE: Most existing methods for accelerated parallel imaging in MRI require additional data, which are used to derive information about the sensitivity profile of each radiofrequency (RF) channel. In this work, a method is presented to avoid the acquisition of separate coil calibration data for accelerated Cartesian trajectories. METHODS: Quadratic phase is imparted to the image to spread the signals in k-space (aka phase scrambling). By rewriting the Fourier transform as a convolution operation, a window can be introduced to the convolved chirp function, allowing a low-resolution image to be reconstructed from phase-scrambled data without prominent aliasing. This image (for each RF channel) can be used to derive coil sensitivities to drive existing parallel imaging techniques. As a proof of concept, the quadratic phase was applied by introducing an offset to the x(2) - y(2) shim and the data were reconstructed using adapted versions of the image space-based sensitivity encoding and GeneRalized Autocalibrating Partially Parallel Acquisitions algorithms. RESULTS: The method is demonstrated in a phantom (1 × 2, 1 × 3, and 2 × 2 acceleration) and in vivo (2 × 2 acceleration) using a 3D gradient echo acquisition. CONCLUSION: Phase scrambling can be used to perform parallel imaging acceleration without acquisition of separate coil calibration data, demonstrated here for a 3D-Cartesian trajectory. Further research is required to prove the applicability to other 2D and 3D sampling schemes. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Angiotensin II-induced cardiac hypertrophy is associated with different mitogen-activated protein kinase activation in normotensive and hypertensive mice.

OBJECTIVE: In addition to its haemodynamic effects, angiotensin II (AngII) is thought to contribute to the development of cardiac hypertrophy via its growth factor properties. The activation of mitogen-activated protein kinases (MAPK) is crucial for stimulating cardiac growth. Therefore, the present study aimed to determine whether the trophic effects of AngII and the AngII-induced haemodynamic load were associated with specific cardiac MAPK pathways during the development of hypertrophy. Methods The activation of the extracellular-signal-regulated kinase (ERK), the c-jun N-terminal kinase (JNK) and the p38 kinase was followed in the heart of normotensive and hypertensive transgenic mice with AngII-mediated cardiac hypertrophy. Secondly, we used physiological models of AngII-dependent and AngII-independent renovascular hypertension to study the activation of cardiac MAPK pathways during the development of hypertrophy. RESULTS: In normotensive transgenic animals with AngII-induced cardiac hypertrophy, p38 activation is associated with the development of hypertrophy while ERK and JNK are modestly stimulated. In hypertensive transgenic mice, further activation of ERK and JNK is observed. Moreover, in the AngII-independent model of renovascular hypertension and cardiac hypertrophy, p38 is not activated while ERK and JNK are strongly stimulated. In contrast, in the AngII-dependent model, all three kinases are stimulated. CONCLUSIONS: These data suggest that p38 activation is preferentially associated with the direct effects of AngII on cardiac cells, whereas stimulation of ERK and JNK occurs in association with AngII-induced mechanical stress.

Quetiapine affects neuropeptide Y and corticotropin-releasing hormone in cerebrospinal fluid from schizophrenia patients: relationship to depression and anxiety symptoms and to treatment response.

Cumulative evidence indicates that neuropeptides play a role in the pathophysiology of schizophrenia. Early data showed increased neuropeptide Y (NPY) in cerebrospinal fluid (CSF) from schizophrenia patients and data from rodents show that antipsychotic drugs modulate NPY levels in and release from selected rat brain regions. In view of these findings we investigated whether the atypical antipsychotic quetiapine, originally used as an antipsychotic but subsequently shown to be efficient also in major depressive disorder and in both poles of bipolar disorder, would affect NPY-like immunoreactivity (-LI), and corticotropin-releasing hormone (CRH)-LI levels in CSF of schizophrenia patients. NPY-LI and CRH-LI in CSF were determined in 22 patients with schizophrenia. Lumbar puncture was performed at baseline and again after 4 wk of quetiapine treatment (600 mg/d). Patients were assessed with the Positive and Negative Syndrome Scale (PANSS) at baseline and at weekly intervals. Quetiapine treatment was associated with a significant increase in NPY-LI (p<0.001) and decrease in CRH-LI (p<0.01). Stepwise multiple regression analysis revealed that ΔNPY-LI and ΔCRH-LI levels predicted 63% (p<0.001) of the variability of the ΔPANSS total score, ΔNPY-LI 42% (p<0.05) of the ΔPANSS anxiety items (G2) and ΔCRH-LI 40% (p=0.05) of the ΔPANSS depression items (G6). These results suggest that while quetiapine's effects on monoamines are probably related to its antipsychotic properties, the modulation of NPY and CRH accounts for its antidepressant and anxiolytic effects and can be markers of response.

Contribución al diseño de GNSS-SDR, un receptor GNSS de código abierto

[ANGLÈS] This project introduces GNSS-SDR, an open source Global Navigation Satellite System software-defined receiver. The lack of reconfigurability of current commercial-of-the-shelf receivers and the advent of new radionavigation signals and systems make software receivers an appealing approach to design new architectures and signal processing algorithms. With the aim of exploring the full potential of this forthcoming scenario with a plurality of new signal structures and frequency bands available for positioning, this paper describes the software architecture design and provides details about its implementation, targeting a multiband, multisystem GNSS receiver. The result is a testbed for GNSS signal processing that allows any kind of customization, including interchangeability of signal sources, signal processing algorithms, interoperability with other systems, output formats, and the offering of interfaces to all the intermediate signals, parameters and variables. The source code release under the GNU General Public License (GPL) secures practical usability, inspection, and continuous improvement by the research community, allowing the discussion based on tangible code and the analysis of results obtained with real signals. The source code is complemented by a development ecosystem, consisting of a website (http://gnss-sdr.org), as well as a revision control system, instructions for users and developers, and communication tools. The project shows in detail the design of the initial blocks of the Signal Processing Plane of the receiver: signal conditioner, the acquisition block and the receiver channel, the project also extends the functionality of the acquisition and tracking modules of the GNSS-SDR receiver to track the new Galileo E1 signals available. Each section provides a theoretical analysis, implementation details of each block and subsequent testing to confirm the calculations with both synthetically generated signals and with real signals from satellites in space.

Microscopic and macroscopic polarization within a combined quantum mechanics and molecular mechanics model

A polarizable quantum mechanics and molecular mechanics model has been extended to account for the difference between the macroscopic electric field and the actual electric field felt by the solute molecule. This enables the calculation of effective microscopic properties which can be related to macroscopic susceptibilities directly comparable with experimental results. By seperating the discrete local field into two distinct contribution we define two different microscopic properties, the so-called solute and effective properties. The solute properties account for the pure solvent effects, i.e., effects even when the macroscopic electric field is zero, and the effective properties account for both the pure solvent effects and the effect from the induced dipoles in the solvent due to the macroscopic electric field. We present results for the linear and nonlinear polarizabilities of water and acetonitrile both in the gas phase and in the liquid phase. For all the properties we find that the pure solvent effect increases the properties whereas the induced electric field decreases the properties. Furthermore, we present results for the refractive index, third-harmonic generation (THG), and electric field induced second-harmonic generation (EFISH) for liquid water and acetonitrile. We find in general good agreement between the calculated and experimental results for the refractive index and the THG susceptibility. For the EFISH susceptibility, however, the difference between experiment and theory is larger since the orientational effect arising from the static electric field is not accurately described

Programació d'una aplicació gràfica per l'anàlisi de senyals usant LDB (Local Discriminant Bases) i MLDB (Modified LDB)

Tot seguit presentem un entorn per analitzar senyals de tot tipus amb LDB (Local Discriminant Bases) i MLDB (Modified Local Discriminant Bases). Aquest entorn utilitza funcions desenvolupades en el marc d’una tesi en fase de desenvolupament. Per entendre part d’aquestes funcions es requereix un nivell de coneixement avançat de processament de senyals. S’han extret dels treballs realitzats per Naoki Saito [3], que s’han agafat com a punt de partida per la realització de l’algorisme de la tesi doctoral no finalitzada de Jose Antonio Soria. Aquesta interfície desenvolupada accepta la incorporació de nous paquets i funcions. Hem deixat un menú preparat per integrar Sinus IV packet transform i Cosine IV packet transform, tot i que també podem incorporar-n’hi altres. L’aplicació consta de dues interfícies, un Assistent i una interfície principal. També hem creat una finestra per importar i exportar les variables desitjades a diferents entorns. Per fer aquesta aplicació s’han programat tots els elements de les finestres, en lloc d’utilitzar el GUIDE (Graphical User Interface Development Enviroment) de MATLAB, per tal que sigui compatible entre les diferents versions d’aquest programa. En total hem fet 73 funcions en la interfície principal (d’aquestes, 10 pertanyen a la finestra d’importar i exportar) i 23 en la de l’Assistent. En aquest treball només explicarem 6 funcions i les 3 de creació d’aquestes interfícies per no fer-lo excessivament extens. Les funcions que explicarem són les més importants, ja sigui perquè s’utilitzen sovint, perquè, segons la complexitat McCabe, són les més complicades o perquè són necessàries pel processament del senyal. Passem cada entrada de dades per part de l’usuari per funcions que ens detectaran errors en aquesta entrada, com eliminació de zeros o de caràcters que no siguin números, com comprovar que són enters o que estan dins dels límits màxims i mínims que li pertoquen.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Spatial variability of aggregate stability in latosols under sugarcane

The spatial variability of soils under a same management system is differentiated, as expressed in the properties. The spatial variability of aggregate stability of a eutrophic Red Latosol (ERL) and a dystrophic Red Latosol (DRL) under sugarcane was characterized. Samples were collected in a regular 10 m grid, in the layers 0.0-0.2 and 0.2-0.4 m, with 100 points per area, and the following properties were determined: geometric mean diameter (GMD) of aggregates, mean weight diameter (MWD) of aggregates, percent of aggregates in the > 2.0 mm class and organic matter (OM) content. The eutrophic Red Latosol (ERL) had a higher aggregate stability thn the dystrophic Red Latosol (DRL), which may be attributed to the higher clay and OM content and the gibbsitic mineralogy of this soil class. The differentiated evolution of the studied Oxisols explains the wider range and lower variation coefficient and variability, for all properties studied in the eutrophic Red Latosol.