MODELING VERY LONG BASELINE INTERFEROMETRIC IMAGES WITH THE CROSS-ENTROPY GLOBAL OPTIMIZATION TECHNIQUE

We present a new technique for obtaining model fittings to very long baseline interferometric images of astrophysical jets. The method minimizes a performance function proportional to the sum of the squared difference between the model and observed images. The model image is constructed by summing N(s) elliptical Gaussian sources characterized by six parameters: two-dimensional peak position, peak intensity, eccentricity, amplitude, and orientation angle of the major axis. We present results for the fitting of two main benchmark jets: the first constructed from three individual Gaussian sources, the second formed by five Gaussian sources. Both jets were analyzed by our cross-entropy technique in finite and infinite signal-to-noise regimes, the background noise chosen to mimic that found in interferometric radio maps. Those images were constructed to simulate most of the conditions encountered in interferometric images of active galactic nuclei. We show that the cross-entropy technique is capable of recovering the parameters of the sources with a similar accuracy to that obtained from the very traditional Astronomical Image Processing System Package task IMFIT when the image is relatively simple (e. g., few components). For more complex interferometric maps, our method displays superior performance in recovering the parameters of the jet components. Our methodology is also able to show quantitatively the number of individual components present in an image. An additional application of the cross-entropy technique to a real image of a BL Lac object is shown and discussed. Our results indicate that our cross-entropy model-fitting technique must be used in situations involving the analysis of complex emission regions having more than three sources, even though it is substantially slower than current model-fitting tasks (at least 10,000 times slower for a single processor, depending on the number of sources to be optimized). As in the case of any model fitting performed in the image plane, caution is required in analyzing images constructed from a poorly sampled (u, v) plane.

Site-directed mutagenesis and structural modeling of Coq10p indicate the presence of a tunnel for coenzyme Q6 binding

Coq10p is a protein required for coenzyme Q function, but its specific role is still unknown. It is a member of the START domain superfamily that contains a hydrophobic tunnel implicated in the binding of lipophilic molecules. We used site-directed mutagenesis, statistical coupling analysis and molecular modeling to probe structural determinants in the Coq10p putative tunnel. Four point mutations were generated (coq10-K50E, coq10-L96S, coq10-E105K and coq10-K162D) and their biochemical properties analysed, as well as structural consequences. Our results show that all mutations impaired Coq10p function and together with molecular modeling indicate an important role for the Coq10p putative tunnel. (C) 2010 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Components Separation Technique With Limited Subcutaneous Undermining A Cadaver Study

The purpose of this study is to evaluate the influence of the undermining of the subcutaneous tissue on the tension of the abdominal wall, after the components separation of the abdominal muscles. Twenty adult cadavers were studied. The resistance of the medial advancement of both anterior and posterior recti sheaths was represented by the traction index and measured in 2 levels-3 cm above and 2 cm below the umbilicus. Traction indices were compared in the following 3 consecutive dissection situations: (1) after the subcutaneous tissue undermining laterally to the semilunaris line; (2) after the dissection of the rectus muscle from its posterior sheath associated with the release of the external oblique muscle; (3) after the subcutaneous tissue undermining laterally to the anterior axillary line. Friedman and Spearman tests were used to compare the results. There was no statistical significant difference between the subcutaneous tissue undermining laterally to the semilunaris line and that laterally to the anterior axillary line, when associated with the musculoaponeurotic dissections. In conclusion, limited subcutaneous undermining does not influence the tension of closure of the musculoaponeurotic layer after the components separation technique in cadavers.

On modeling and evaluating multicomputer transcoding architectures for live-video streams

The pervasive and ubiquitous computing has motivated researches on multimedia adaptation which aims at matching the video quality to the user needs and device restrictions. This technique has a high computational cost which needs to be studied and estimated when designing architectures and applications. This paper presents an analytical model to quantify these video transcoding costs in a hardware independent way. The model was used to analyze the impact of transcoding delays in end-to-end live-video transmissions over LANs, MANs and WANs. Experiments confirm that the proposed model helps to define the best transcoding architecture for different scenarios.

Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.

An evaluation of three upwinding approximations for numerical modeling the flow in tubular membrane of Newtonian and non-Newtonian fluids

In this paper, the laminar fluid flow of Newtonian and non-Newtonian of aqueous solutions in a tubular membrane is numerically studied. The mathematical formulation, with associated initial and boundary conditions for cylindrical coordinates, comprises the mass conservation, momentum conservation and mass transfer equations. These equations are discretized by using the finite-difference technique on a staggered grid system. Comparisons of the three upwinding schemes for discretization of the non-linear (convective) terms are presented. The effects of several physical parameters on the concentration profile are investigated. The numerical results compare favorably with experimental data and the analytical solutions. (C) 2011 Elsevier Inc. All rights reserved.

Water quality assessment of Toledo River and determination of metal concentrations by using SR-TXRF technique

The region of Toledo River, Parana, Brazil is characterized by intense anthropogenic activities. Hence, metal concentrations and physical-chemical parameters of Toledo River water were determined in order to complete an environmental evaluation catalog. Samples were collected monthly during one year period at seven different sites from the source down the river mouth, physical-chemical variables were analyzed, and major metallic ions were measured. Metal analysis was performed by using the synchrotron radiation total reflection X-ray fluorescence technique. A statistical analysis was applied to evaluate the reliability of experimental data. The analysis of obtained results have shown that a strong correlation between physical-chemical parameters existed among sites 1 and 7, suggesting that organic pollutants were mainly responsible for decreasing the Toledo River water quality.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

Modeling connectivity in terms of network activity

A new complex network model is proposed which is founded on growth, with new connections being established proportionally to the current dynamical activity of each node, which can be understood as a generalization of the Barabasi-Albert static model. By using several topological measurements, as well as optimal multivariate methods (canonical analysis and maximum likelihood decision), we show that this new model provides, among several other theoretical kinds of networks including Watts-Strogatz small-world networks, the greatest compatibility with three real-world cortical networks.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.