Simultaneous A8344G heteroplasmy and mitochondrial DNA copy number quantification in Myoclonus Epilepsy and Ragged-Red Fibers (MERRF) syndrome by a multiplex Molecular Beacon based real-time fluorescence PCR

The association of a particular mitochondrial DNA (mtDNA) mutation with different clinical phenotypes is a well-known feature of mitochondrial diseases. A simple genotype–phenotype correlation has not been found between mutation load and disease expression. Tissue and intercellular mosaicism as well as mtDNA copy number are thought to be responsible for the different clinical phenotypes. As disease expression of mitochondrial tRNA mutations is mostly in postmitotic tissues, studies to elucidate disease mechanisms need to be performed on patient material. Heteroplasmy quantitation and copy number estimation using small patient biopsy samples has not been reported before, mainly due to technical restrictions. In order to resolve this problem, we have developed a robust assay that utilizes Molecular Beacons to accurately quantify heteroplasmy levels and determine mtDNA copy number in small samples carrying the A8344G tRNALys mutation. It provides the methodological basis to investigate the role of heteroplasmy and mtDNA copy number in determining the clinical phenotypes.

Estimation of evolutionary distances under stationary and nonstationary models of nucleotide substitution

Estimation of evolutionary distances has always been a major issue in the study of molecular evolution because evolutionary distances are required for estimating the rate of evolution in a gene, the divergence dates between genes or organisms, and the relationships among genes or organisms. Other closely related issues are the estimation of the pattern of nucleotide substitution, the estimation of the degree of rate variation among sites in a DNA sequence, and statistical testing of the molecular clock hypothesis. Mathematical treatments of these problems are considerably simplified by the assumption of a stationary process in which the nucleotide compositions of the sequences under study have remained approximately constant over time, and there now exist fairly extensive studies of stationary models of nucleotide substitution, although some problems remain to be solved. Nonstationary models are much more complex, but significant progress has been recently made by the development of the paralinear and LogDet distances. This paper reviews recent studies on the above issues and reports results on correcting the estimation bias of evolutionary distances, the estimation of the pattern of nucleotide substitution, and the estimation of rate variation among the sites in a sequence.

Real time measurements of elongation by a reverse transcriptase using surface plasmon resonance.

A rapid direct assay for polymerase-induced elongation along a given template is an obligate requirement for understanding the processivity of polymerization and the mode of action of drugs and inhibitors on this process. Surface plasmon resonance can be used to follow the association and the dissociation rates of a given reverse transcriptase on DNA.RNA and DNA.DNA hybrids immobilized on a biotin-streptavidin surface. The addition of nucleotides complementary to the template strand produces an increase in the local mass, as deduced from an increase in the measured signal, due to elongation of the primer strand that allows an estimation of both the extent and rate of the polymerization process. The terminator drug 3'-deoxy-3'-azidothymidine triphosphate completely abolishes the increase in signal as would be expected from an inhibition of elongation. This technique provides a sensitive assay for the affinities of different polymerases for specific templates and for the effects of terminators of the elongation process.

Algebraic derivative estimation applied to nonlinear control of magnetic levitation.

The subject of this thesis is the real-time implementation of algebraic derivative estimators as observers in nonlinear control of magnetic levitation systems. These estimators are based on operational calculus and implemented as FIR filters, resulting on a feasible real-time implementation. The algebraic method provide a fast, non-asymptotic state estimation. For the magnetic levitation systems, the algebraic estimators may replace the standard asymptotic observers assuring very good performance and robustness. To validate the estimators as observers in closed-loop control, several nonlinear controllers are proposed and implemented in a experimental magnetic levitation prototype. The results show an excellent performance of the proposed control laws together with the algebraic estimators.

Estudo da remediação de um aquífero contaminado com sulfato e metais através de barreira reativa permeável orgânica.

Este trabalho teve como objetivo geral estudar a viabilidade técnica de utilizar bagaço de cana como meio reativo de barreiras reativas permeáveis (BRP) para remoção de sulfato e metais de águas subterrâneas contaminadas. O estudo baseou-se em investigação experimental, por meio de ensaios laboratoriais de coluna, e em modelagem matemática, para a qual utilizaram-se também alguns dados obtidos em um estudo de caso de uma unidade industrial contaminada com sulfato e metais. Neste local contaminado, as características hidrogeológicas e topográficas propiciam a utilização de uma barreira reativa permeável como técnica de remediação. Barreiras reativas permeáveis são uma alternativa para remediação de águas subterrâneas que vem progredindo rapidamente na última década, a partir de ensaios de bancada e coluna em laboratório para implementação em escala real em campo. Três colunas bióticas foram montadas utilizando bagaço de cana como meio reativo e um material de base poroso constituído de areia e cascalho para fornecer adequada condutividade hidráulica, com a proporção de 1:28 em massa seca. Também foi adicionado ao meio reativo um inóculo bacteriano composto por esterco bovino dissolvido. Uma quarta coluna, sem inóculo e contendo um agente biocida, compôs o experimento branco (abiótico). Uma solução sintética foi introduzida nas colunas simulando condições da água subterrânea do estudo de caso, com velocidade de Darcy em torno de 2,0x10-7 m/s composta por sulfato e metais (zinco e níquel) com concentrações de 6.000 mg/L e 15 mg/L, respectivamente. Os resultados das análises da fase líquida das colunas bióticas apresentaram: (i) média da taxa de remoção de sulfato durante todo o tempo do experimento de 49 mg/L/dia; (ii) as concentrações de Zn e Ni diminuíram de 15 mg/L para valores não detectáveis pela técnica analítica utilizada (< 0,01 mg/L); (iii) aumento do pH de 5.5-5.8 para valores entre 6,8-8,0; (iv) redução do valor do potencial de óxido redução (Eh) para valores de até -200mV. Não foram observadas reduções das concentrações de metais e sulfato na fase líquida da coluna abiótica e os valores de pH e Eh permaneceram dentro das faixas iniciais. Análises nas fases sólidas das colunas bióticas por MEV e EDS após o término do experimento identificaram a presença de Ni, Zn, S e Mn, indicando a precipitação desses metais em forma de sulfetos. Estes elementos não foram detectados na fase sólida da coluna abiótica. Assim, pôde-se inferir que toda a remoção de sulfato verificada nas colunas bióticas pode ser atribuída a redução bacteriana de sulfato. A partir das condições experimentais dos ensaios, foi realizada a modelagem e o dimensionamento da BRP. Para a estimativa da cinética de redução de sulfato, aplicou-se a solução analítica de Van Genuchten para transporte de contaminantes com degradação, obtendo-se uma taxa de decaimento de primeira ordem de 0,01 dia-1. A determinação da espessura e tempo de residência da barreira foi realizada considerando que a concentração de sulfato na saída da barreira fosse menor ou igual a 250 mg/L. O resultado do dimensionamento de uma BRP preenchida com bagaço de cana e areia nas proporções de 1:28 em massa seca resultaria em uma BRP de 7,1 m de espessura, com tempo de residência de 950 dias, no local de estudo de caso. Caso fosse utilizado o dobro da proporção de bagaço de cana e areia em massa seca (1:14), a implantação da BRP apresentar-se-ia viável, com espessura aproximada de 4 m. Através destes resultados, pôde ser comprovada a hipótese de que bagaço de cana como substrato e esterco bovino como inóculo compõem um meio reativo viável para a redução de sulfato e precipitação de metais em uma BRP.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

A new algorithm to accelerate harmonic analysis of time series

The Lomb periodogram has been traditionally a tool that allows us to elucidate if a frequency turns out to be important for explaining the behaviour of a given time series. Many linear and nonlinear reiterative harmonic processes that are used for studying the spectral content of a time series take into account this periodogram in order to avoid including spurious frequencies in their models due to the leakage problem of energy from one frequency to others. However, the estimation of the periodogram requires long computation time that makes the harmonic analysis slower when we deal with certain time series. Here we propose an algorithm that accelerates the extraction of the most remarkable frequencies from the periodogram, avoiding its whole estimation of the harmonic process at each iteration. This algorithm allows the user to perform a specific analysis of a given scalar time series. As a result, we obtain a functional model made of (1) a trend component, (2) a linear combination of Fourier terms, and (3) the so-called mixed secular terms by reducing the computation time of the estimation of the periodogram.

3D Hand Pose Estimation with Neural Networks

We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.

Estimation of satellite antenna phase center offsets for Galileo

Satellite antenna phase center offsets for the GalileoInOrbitValidation(IOV) and FullOperationalCapability (FOC) satellites are estimated by two different analysiscenters based on tracking data of a global GNSS network. The mean x- and y-offsets could be determined with a precision of a few centimeters. However, daily estimates of thex-offsets of the IOV satellites show pronounced systematic effects with a peak-to-peak amplitude of up to 70 cm that depend on the orbit model and the elevation of the Sun above the orbital plane. For the IOV y-offsets, no dependence on the orbit model exists but the scatter strongly depends on the elevation of the Sun above the orbital plane. In general, these systematic effects are significantly smaller for the FOC satellites. The z-offsets of the two analysis centers agree within the 10–15 cm level, and the time series do not show systematic effects. The application of an averaged Galileo satellite antenna model obtained from the two solutions results in a reduction of orbit day boundary discontinuities by up to one third—even if an independent software package is used.

Extraterrestrial 3He estimation across the Paleocene-Eocene thermal maximum at ODP Site 208-1266

In the deep-sea, the Paleocene-Eocene Thermal Maximum (PETM) is often marked by clay-rich condensed intervals caused by dissolution of carbonate sediments, capped by a carbonate-rich interval. Constraining the duration of both the dissolution and subsequent cap-carbonate intervals is essential to computing marine carbon fluxes and thus testing hypotheses for the origin of this event. To this end, we provide new high-resolution helium isotope records spanning the Paleocene-Eocene boundary at ODP Site 1266 in the South Atlantic. The extraterrestrial 3He, 3HeET, concentrations replicate trends observed at ODP Site 690 by Farley and Eltgroth (2003, doi:10.1016/S0012-821X(03)00017-7). By assuming a constant flux of 3HeET we constrain relative changes in accumulation rates of sediment across the PETM and construct a new age model for the event. In this new chronology the zero carbonate layer represents 35 kyr, some of which reflects clay produced by dissolution of Paleocene (pre-PETM) sediments. Above this layer, carbonate concentrations increase for ~165 kyr and remain higher than in the latest Paleocene until 234 +48/-34 kyr above the base of the clay. The new chronology indicates that minimum d13C values persisted for a maximum of 134 +27/-19 kyr and the inflection point previously chosen to designate the end of the CIE recovery occurs at 217 +44/-31 kyr. This allocation of time differs from that of the cycle-based age model of Röhl et al. (2007, doi:10.1029/2007GC001784) in that it assigns more time to the clay layer followed by a more gradual recovery of carbonate-rich sedimentation. The new model also suggests a longer sustained d13C excursion followed by a more rapid recovery to pre-PETM d13C values. These differences have important implications for constraining the source(s) of carbon and mechanisms for its subsequent sequestration, favoring models that include a sustained release