Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

An oligonucleotide primer set for PCR amplification of the complete honey bee mitochondrial genome

Mitochondrial DNA markers have been widely used to address population and evolutionary questions in the honey bee Apis mellifera. Most of the polymorphic markers are restricted to few mitochondrial regions. Here we describe a set of 24 oligonucleotides that allow PCR amplification of the entire mitochondrial genome of the honey bee A. mellifera in 12 amplicons. These fragments have important applications for the study of mitochondrial genes in different subspecies of A. mellifera and as heterospecific probes to characterize mitochondrial genomes in other bee species.

Estimation of the thickness and the optical parameters of several stacked thin films using optimization

The reverse engineering problem addressed in the present research consists of estimating the thicknesses and the optical constants of two thin films deposited on a transparent substrate using only transmittance data through the whole stack. No functional dispersion relation assumptions are made on the complex refractive index. Instead, minimal physical constraints are employed, as in previous works of some of the authors where only one film was considered in the retrieval algorithm. To our knowledge this is the first report on the retrieval of the optical constants and the thickness of multiple film structures using only transmittance data that does not make use of dispersion relations. The same methodology may be used if the available data correspond to normal reflectance. The software used in this work is freely available through the PUMA Project web page (http://www.ime.usp.br/similar to egbirgin/puma/). (C) 2008 Optical Society of America

Non-exhaustive tests for critical power estimation

Objective. - The aim of this study was to propose a new method that allows for the estimation of critical power (CP) from non-exhaustive tests using ratings of perceived exertion (RPE). Methods. - Twenty-two subjects underwent two practice trials for ergometer and Borg 15-point scale familiarization, and adaptation to severe exhaustive exercise. After then, four exercise bouts were performed on different days for the estimation of CP and anaerobic work capacity (AWC) by linear work-time equation, and CP(15), CP(17), AWC(15) and AWC(17) were estimated using the work and time to attainment of RPE15 and RPE17 based on the Borg 15-point scale. Results. - The CP, CP(15) and CP(17) (170-177W) were not significantly different (P>0.05). However, AWC, AWC(15) and AWC(17) were all different from each other. The correlations between CP(15) and CP(17), with CP were strong (R=0.871 and 0.911, respectively), but the AWC(15) and AWC(17) were not significantly correlated with AWC. Conclusion. - Sub-maximal. RPE responses can be used for the estimation of CP from non-exhaustive exercise protocols. (C) 2009 Elsevier Masson SAS. All rights reserved.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Estimation of Mass Transfer Velocity Based on Measured Turbulence Parameters

The aim of this study is to quantify the mass transfer velocity using turbulence parameters from simultaneous measurements of oxygen concentration fields and velocity fields. The surface divergence model was considered in more detail, using data obtained for the lower range of beta (surface divergence). It is shown that the existing models that use the divergence concept furnish good predictions for the transfer velocity also for low values of beta, in the range of this study. Additionally, traditional conceptual models, such as the film model, the penetration-renewal model, and the large eddy model, were tested using the simultaneous information of concentration and velocity fields. It is shown that the film and the surface divergence models predicted the mass transfer velocity for all the range of the equipment Reynolds number used here. The velocity measurements showed viscosity effects close to the surface, which indicates that the surface was contaminated with some surfactant. Considering the results, this contamination can be considered slight for the mass transfer predictions. (C) 2009 American Institute of Chemical Engineers AIChE J, 56: 2005-2017; 2010

Distribution systems fault analysis considering fault resistance estimation

Fault resistance is a critical component of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies. This paper presents an iterative fault analysis algorithm for unbalanced three-phase distribution systems that considers a fault resistance estimate. The proposed algorithm is composed by two sub-routines, namely the fault resistance and the bus impedance. The fault resistance sub-routine, based on local fault records, estimates the fault resistance. The bus impedance sub-routine, based on the previously estimated fault resistance, estimates the system voltages and currents. Numeric simulations on the IEEE 37-bus distribution system demonstrate the algorithm`s robustness and potential for offline applications, providing additional fault information to Distribution Operation Centers and enhancing the system restoration process. (C) 2011 Elsevier Ltd. All rights reserved.

Recursive linear estimation for general discrete-time descriptor systems

This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.

Three-phase harmonic distortion state estimation algorithm based on evolutionary strategies

This paper presents a new methodology to estimate unbalanced harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The problem solving algorithm herein proposed makes use of data from various power quality meters, which can either be synchronized by high technology GPS devices or by using information from a fundamental frequency load flow, what makes the overall power quality monitoring system much less costly. The ES based harmonic estimation model is applied to a 14 bus network to compare its performance to a conventional Monte Carlo approach. It is also applied to a 50 bus subtransmission network in order to compare the three-phase and single-phase approaches as well as the robustness of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.

Harmonic Distortion State Estimation Using an Evolutionary Strategy

This paper presents a new methodology to estimate harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The main advantage in using such a technique relies upon its modeling facilities as well as its potential to solve fairly complex problems. The problem-solving algorithm herein proposed makes use of data from various power-quality (PQ) meters, which can either be synchronized by high technology global positioning system devices or by using information from a fundamental frequency load flow. This second approach makes the overall PQ monitoring system much less costly. The algorithm is applied to an IEEE test network, for which sensitivity analysis is performed to determine how the parameters of the ES can be selected so that the algorithm performs in an effective way. Case studies show fairly promising results and the robustness of the proposed method.

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence

We examine the representation of judgements of stochastic independence in probabilistic logics. We focus on a relational logic where (i) judgements of stochastic independence are encoded by directed acyclic graphs, and (ii) probabilistic assessments are flexible in the sense that they are not required to specify a single probability measure. We discuss issues of knowledge representation and inference that arise from our particular combination of graphs, stochastic independence, logical formulas and probabilistic assessments. (C) 2007 Elsevier B.V. All rights reserved.

Estimating wave spectra from the motions of moored vessels: Experimental validation

The practicability of estimating directional wave spectra based on a vessel`s 1st order response has been recently addressed by several researchers. Different alternatives regarding statistical inference methods and possible drawbacks that could arise from their application have been extensively discussed, with an apparent preference for estimations based on Bayesian inference algorithms. Most of the results on this matter, however, rely exclusively on numerical simulations or at best on few and sparse full-scale measurements, comprising a questionable basis for validation purposes. This paper discusses several issues that have recently been debated regarding the advantages of Bayesian inference and different alternatives for its implementation. Among those are the definition of the best set of input motions, the number of parameters required for guaranteeing smoothness of the spectrum in frequency and direction and how to determine their optimum values. These subjects are addressed in the light of an extensive experimental campaign performed with a small-scale model of an FPSO platform (VLCC hull), which was conducted in an ocean basin in Brazil. Tests involved long and short crested seas with variable levels of directional spreading and also bimodal conditions. The calibration spectra measured in the tank by means of an array of wave probes configured the paradigm for estimations. Results showed that a wide range of sea conditions could be estimated with good precision, even those with somewhat low peak periods. Some possible drawbacks that have been pointed out in previous works concerning the viability of employing large vessels for such a task are then refuted. Also, it is shown that a second parameter for smoothing the spectrum in frequency may indeed increase the accuracy in some situations, although the criterion usually proposed for estimating the optimum values (ABIC) demands large computational effort and does not seem adequate for practical on-board systems, which require expeditious estimations. (C) 2009 Elsevier Ltd. All rights reserved.

Effects of weld strength mismatch on J and CTOD estimation procedure for SE(B) specimens

This work examines the effect of weld strength mismatch on fracture toughness measurements defined by J and CTOD fracture parameters using single edge notch bend (SE(B)) specimens. A central objective of the present study is to enlarge on previous developments of J and CTOD estimation procedures for welded bend specimens based upon plastic eta factors (eta) and plastic rotational factors (r (p) ). Very detailed non-linear finite element analyses for plane-strain models of standard SE(B) fracture specimens with a notch located at the center of square groove welds and in the heat affected zone provide the evolution of load with increased crack mouth opening displacement required for the estimation procedure. One key result emerging from the analyses is that levels of weld strength mismatch within the range +/- 20% mismatch do not affect significantly J and CTOD estimation expressions applicable to homogeneous materials, particularly for deeply cracked fracture specimens with relatively large weld grooves. The present study provides additional understanding on the effect of weld strength mismatch on J and CTOD toughness measurements while, at the same time, adding a fairly extensive body of results to determine parameters J and CTOD for different materials using bend specimens with varying geometries and mismatch levels.