Genotype x environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Electroluminescence of phenylene-vinylene random copolymers with different conjugation lengths

PPV random derivates were synthesized and characterized. Polymer light emitting diodes (PLEDs) were assembled using the random copolymers as emissive layer and showed EL in the blue-green region in function of the method of preparation. The increase in the average conjugation degree in the polymer chain led to the reduction of the turn-on voltage of the device. The addition of Alq3 as ETL increased tenfold the luminescence efficiency. (C) 2009 Elsevier B.V. All rights reserved.

SPATIAL PATTERN OF FOUR FOREST COMMUNITIES BY RIPLEY'S K FUNCTION IN SAO PAULO STATE

Investigating tree's spatial patterns according to their size classes and according to their more abundant species can provide evidences about the structure of the vegetal community, since the spatial pattern is a key question for forestry ecology studies. The tree spatial organization patterns on the environment depend on several ecological processes and on the specific characteristics of each environment, so that the best understanding of this frame provides important elements for the knowledge on forestry formation. This paper aimed to study tree spatial patterns, according to the diameter classes and from four most abundant species in different forests, in order to provide evidences regarding to the ecology of each vegetal community. The spatial pattern description in each forestry formation was developed using Ripley's K function. The studied forestry formations were: Ombrophilous Forest, Cerradao, Seasonal Forest and Restinga Forest. In this work, a 10.24 ha plot was installed in each forestry formation, and every tree, with a circumference at breast height (CBH) larger than 15 cm were measured, georeferenced and identified. The obtained data highlights the aggregated character in tropical forests, as observed in every studied forest. The 'Cerraddo' and 'Restinga' forest trees showed close aggregate patterns. In the Ombrophilous forest, for all distance scales, the aggregate pattern was meaningful. In the seasonal forest, a random tendency was observed, although a meaningful aggregation was observed in all short distances. The spatial pattern by diameter classes was generally aggregated for trees smaller than 10 cm of diameter and between 10 and 20 cm and random for the others, proving the existence of a tendency which in young trees is more aggregated than in old ones. The spatial pattern of the dominant species is always strongly similar to the general pattern of each forestry formation. The differences between the spatial patterns of two or three coincident species, among the forestry formations, indicate that its pattern is influenced by each different environment. This stands out the importance of its self-ecology and of its ecological processes, intrinsic of each community that can explain the observed patterns.

Asymptotic integral kernel for ensembles of random normal matrices with radial potentials

The method of steepest descent is used to study the integral kernel of a family of normal random matrix ensembles with eigenvalue distribution P-N (z(1), ... , z(N)) = Z(N)(-1)e(-N)Sigma(N)(i=1) V-alpha(z(i)) Pi(1 <= i<j <= N) vertical bar z(i) - z(j)vertical bar(2), where V-alpha(z) = vertical bar z vertical bar(alpha), z epsilon C and alpha epsilon inverted left perpendicular0, infinity inverted right perpendicular. Asymptotic formulas with error estimate on sectors are obtained. A corollary of these expansions is a scaling limit for the n-point function in terms of the integral kernel for the classical Segal-Bargmann space. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3688293]

The C-4-Dicarboxylate carriers DcuB and DctA of Escherichia coli: function as cosensors and topology

Das fakultativ anaerobe Enterobakterium Escherichia coli nutzt C4-Dicarboxylate sowohl unter aeroben als auch anaeroben Bedingungen als Kohlenstoff- und Energiequelle. Die Aufnahme der C4-Dicarboxylaten und die Energiekonservierung mittels Fumaratatmung wird durch das Zweikomponentensystem DcuSR reguliert. Die Sensorhistidinkinase DcuS und der nachgeschaltete Responseregulator DcuR aktivieren bei Verfügbarkeit von C4-Dicarboxylaten die Expression der Gene für den Succinat Transporter DctA, den anaeroben Fumarat/Succinat Antiporter DcuB, die Fumarase B sowie die Fumaratreduktase FrdABCD. Die Transportproteine DctA und DcuB wiederum regulieren die Expression der DcuSR-abhängigen Gene negativ. Fehlen von DctA oder DcuB resultiert bereits ohne Effektor in einer maximalen Expression von dctA bzw. dcuB. Durch gerichtete und ungerichtete Mutagenese wurde gezeigt, dass die Transportfunktion des Carriers DcuB unabhängig von seiner regulatorischen Funktion ist. DcuB kann daher als Cosensor des DcuSR Systems angesehen werden.rnUnter Verwendung von Reportergenfusionen von C-terminal verkürzten Konstrukten von DcuB mit der Alkalischen Phosphatase und der β-Galactosidase wurde die Topologie des Multitransmembranproteins DcuB bestimmt. Zusätzlich wurde die Zugänglichkeit bestimmter Aminosäurereste durch chemische Modifikation mit membran-durchlässigen und membran-undurchlässigen Thiolreagenzien untersucht. Die erhaltenen Ergebnisse deuten auf die Existenz eines tief in die Membran reichenden, hydrophilen Kanal hin, welcher zum Periplasma hin geöffnet ist. Mit Hilfe der Topologie-Studien, des Hydropathie-Blots und der Sekundärstruktur-Vorhersage wurde ein Modell des Carriers erstellt. DcuB besitzt kurze, periplasmatisch liegende Proteinenden, die durch 12 Transmembranhelices und zwei große hydrophile Schleifen jeweils zwischen TM VII/VIII und TM XI/XII verbunden sind. Die regulatorisch relevanten Reste K353, T396 und D398 befinden sich innerhalb von TM XI sowie auf der angrenzenden cytoplasmatischen Schleife XI-XII. Unter Berücksichtigung der strukturellen und funktionellen Aspekte wurde ein Regulationsmodell erstellt, welches die gemeinsam durch DcuB und DcuS kontrollierte C4-Dicarboxylat-abhängige Genexpression darstellt. rnDer Effekt von DctA und DcuSR auf die Expression einer dctA´-´lacZ Reportergenfusion und auf die aerobe C4-Dicarboxylat-Aufnahme wurde untersucht. In-vivo FRET-Messungen weisen auf eine direkte Wechselwirkung zwischen dem Carrier DctA und dem Sensor DcuS hin. Dieses Ergebnis stützt die Theorie der Regulation von DcuS durch C4-Dicarboxylate und durch die Cosensoren DctA bzw. DcuB mittels direkter Protein-Protein Interaktion.rn

Equations for the Drag Force and Aerodynamic Roughness Length of Urban Areas with Random Building Heights

We use a conceptual model to investigate how randomly varying building heights within a city affect the atmospheric drag forces and the aerodynamic roughness length of the city. The model is based on the assumptions regarding wake spreading and mutual sheltering effects proposed by Raupach (Boundary-Layer Meteorol 60:375-395, 1992). It is applied both to canopies having uniform building heights and to those having the same building density and mean height, but with variability about the mean. For each simulated urban area, a correction is determined, due to height variability, to the shear stress predicted for the uniform building height case. It is found that u (*)/u (*R) , where u (*) is the friction velocity and u (*R) is the friction velocity from the uniform building height case, is expressed well as an algebraic function of lambda and sigma (h) /h (m) , where lambda is the frontal area index, sigma (h) is the standard deviation of the building height, and h (m) is the mean building height. The simulations also resulted in a simple algebraic relation for z (0)/z (0R) as a function of lambda and sigma (h) /h (m) , where z (0) is the aerodynamic roughness length and z (0R) is z (0) found from the original Raupach formulation for a uniform canopy. Model results are in keeping with those of several previous studies.

Posterior Simulation in the Generalized Linear Model with Semiparmetric Random Effects

Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model, normal base measures and Gibbs sampling procedures based on the Pólya urn scheme are often used to simulate posterior draws. These algorithms are applicable in the conjugate case when (for a normal base measure) the likelihood is normal. In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998) and Neal (2000) are often applied to generate posterior samples. Some common problems associated with simulation algorithms for non-conjugate MDP models include convergence and mixing difficulties. This paper proposes an algorithm based on the Pólya urn scheme that extends the Gibbs sampling algorithms to non-conjugate models with normal base measures and exponential family likelihoods. The algorithm proceeds by making Laplace approximations to the likelihood function, thereby reducing the procedure to that of conjugate normal MDP models. To ensure the validity of the stationary distribution in the non-conjugate case, the proposals are accepted or rejected by a Metropolis-Hastings step. In the special case where the data are normally distributed, the algorithm is identical to the Gibbs sampler.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Risk of severe asthma episodes predicted from fluctuation analysis of airway function

Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Analytical form of the Probability Density Function of travel times in rectangular zone with Tchebyshev’s metric

Geometrical dependencies are being researched for analytical representation of the probability density function (pdf) for the travel time between a random, and a known or another random point in Tchebyshev’s metric. In the most popular case - a rectangular area of service - the pdf of this random variable depends directly on the position of the server. Two approaches have been introduced for the exact analytical calculation of the pdf: Ad-hoc approach – useful for a ‘manual’ solving of a specific case; by superposition – an algorithmic approach for the general case. The main concept of each approach is explained, and a short comparison is done to prove the faithfulness.

Mechanisms of perceptual learning of depth discrimination in random dot stereograms.

Perceptual learning is a training induced improvement in performance. Mechanisms underlying the perceptual learning of depth discrimination in dynamic random dot stereograms were examined by assessing stereothresholds as a function of decorrelation. The inflection point of the decorrelation function was defined as the level of decorrelation corresponding to 1.4 times the threshold when decorrelation is 0%. In general, stereothresholds increased with increasing decorrelation. Following training, stereothresholds and standard errors of measurement decreased systematically for all tested decorrelation values. Post training decorrelation functions were reduced by a multiplicative constant (approximately 5), exhibiting changes in stereothresholds without changes in the inflection points. Disparity energy model simulations indicate that a post-training reduction in neuronal noise can sufficiently account for the perceptual learning effects. In two subjects, learning effects were retained over a period of six months, which may have application for training stereo deficient subjects.

Regularity conditions in the realisability problem in applications to point processes and random closed sets

We study existence of random elements with partially specified distributions. The technique relies on the existence of a positive ex-tension for linear functionals accompanied by additional conditions that ensure the regularity of the extension needed for interpreting it as a probability measure. It is shown in which case the extens ion can be chosen to possess some invariance properties. The results are applied to the existence of point processes with given correlation measure and random closed sets with given two-point covering function or contact distribution function. It is shown that the regularity condition can be efficiently checked in many cases in order to ensure that the obtained point processes are indeed locally finite and random sets have closed realisations.

A fitting algorithm for random modeling the PLC channel

The characteristics of the power-line communication (PLC) channel are difficult to model due to the heterogeneity of the networks and the lack of common wiring practices. To obtain the full variability of the PLC channel, random channel generators are of great importance for the design and testing of communication algorithms. In this respect, we propose a random channel generator that is based on the top-down approach. Basically, we describe the multipath propagation and the coupling effects with an analytical model. We introduce the variability into a restricted set of parameters and, finally, we fit the model to a set of measured channels. The proposed model enables a closed-form description of both the mean path-loss profile and the statistical correlation function of the channel frequency response. As an example of application, we apply the procedure to a set of in-home measured channels in the band 2-100 MHz whose statistics are available in the literature. The measured channels are divided into nine classes according to their channel capacity. We provide the parameters for the random generation of channels for all nine classes, and we show that the results are consistent with the experimental ones. Finally, we merge the classes to capture the entire heterogeneity of in-home PLC channels. In detail, we introduce the class occurrence probability, and we present a random channel generator that targets the ensemble of all nine classes. The statistics of the composite set of channels are also studied, and they are compared to the results of experimental measurement campaigns in the literature.

Node sampling using random centrifugal walks

Sampling a network with a given probability distribution has been identified as a useful operation. In this paper we propose distributed algorithms for sampling networks, so that nodes are selected by a special node, called the source, with a given probability distribution. All these algorithms are based on a new class of random walks, that we call Random Centrifugal Walks (RCW). A RCW is a random walk that starts at the source and always moves away from it. Firstly, an algorithm to sample any connected network using RCW is proposed. The algorithm assumes that each node has a weight, so that the sampling process must select a node with a probability proportional to its weight. This algorithm requires a preprocessing phase before the sampling of nodes. In particular, a minimum diameter spanning tree (MDST) is created in the network, and then nodes weights are efficiently aggregated using the tree. The good news are that the preprocessing is done only once, regardless of the number of sources and the number of samples taken from the network. After that, every sample is done with a RCW whose length is bounded by the network diameter. Secondly, RCW algorithms that do not require preprocessing are proposed for grids and networks with regular concentric connectivity, for the case when the probability of selecting a node is a function of its distance to the source. The key features of the RCW algorithms (unlike previous Markovian approaches) are that (1) they do not need to warm-up (stabilize), (2) the sampling always finishes in a number of hops bounded by the network diameter, and (3) it selects a node with the exact probability distribution.