SU(4) flavor symmetry breaking in D-meson couplings to light hadrons

The validity of SU(4)-flavor symmetry relations of couplings of charmed $D$ mesons to light mesons and baryons is examined with the use of $^3{\rm P}_0$ quark-pair creation model and nonrelativistic quark model wave functions. We focus on the three-meson couplings $\pi\pi\rho$, $KK\rho$ and $DD\rho$ and baryon-baryon-meson couplings $NN\pi$, $N\Lambda K$ and $N\Lambda_c D$. It is found that SU(4)-flavor symmetry is broken at the level of 30% in the $DD\rho$ tree-meson couplings and 20% in the baryon-baryon-meson couplings. Consequences of these findings for DN cross sections and existence of bound states D-mesons in nuclei are discussed.Comment: 5 pages, 3 figure

A Generalized Approach to Complex Networks

This work describes how the formalization of complex network concepts in terms of discrete mathematics, especially mathematical morphology, allows a series of generalizations and important results ranging from new measurements of the network topology to new network growth models. First, the concepts of node degree and clustering coefficient are extended in order to characterize not only specific nodes, but any generic subnetwork. Second, the consideration of distance transform and rings are used to further extend those concepts in order to obtain a signature, instead of a single scalar measurement, ranging from the single node to whole graph scales. The enhanced discriminative potential of such extended measurements is illustrated with respect to the identification of correspondence between nodes in two complex networks, namely a protein-protein interaction network and a perturbed version of it. The use of other measurements derived from mathematical morphology are also suggested as a means to characterize complex networks connectivity in a more comprehensive fashion.Comment: 10 pages, 2 figur

A Fast and Accurate Nonlinear Spectral Method for Image Recognition and Registration

This article addresses the problem of two- and higher dimensional pattern matching, i.e. the identification of instances of a template within a larger signal space, which is a form of registration. Unlike traditional correlation, we aim at obtaining more selective matchings by considering more strict comparisons of gray-level intensity. In order to achieve fast matching, a nonlinear thresholded version of the fast Fourier transform is applied to a gray-level decomposition of the original 2D image. The potential of the method is substantiated with respect to real data involving the selective identification of neuronal cell bodies in gray-level images.Comment: 4 pages, 3 figure

Relativistic model for the nonmesonic weak decay of single-lambda hypernuclei

Having in mind its future extension for theoretical investigations related to charmed nuclei, we develop a relativistic formalism for the nonmesonic weak decay of single-$\Lambda$ hypernuclei in the framework of the independent-particle shell model and with the dynamics represented by the $(\pi,K)$ one-meson-exchange model. Numerical results for the one-nucleon-induced transition rates of ${}^{12}_{\Lambda}\textrm{C}$ are presented and compared with those obtained in the analogous nonrelativistic calculation. There is satisfactory agreement between the two approaches, and the most noteworthy difference is that the ratio $\Gamma_{n}/\Gamma_{p}$ is appreciably higher and closer to the experimental value in the relativistic calculation. Large discrepancies between ours and previous relativistic calculations are found, for which we do not encounter any fully satisfactory explanation. The most recent experimental data is well reproduced by our results. In summary, we have achieved our purpose to develop a reliable model for the relativistic calculation of the nonmesonic weak decay of $\Lambda$-hypernuclei, which can now be extended to evaluate similar processes in charmed nuclei

Strategic CSR shifts towards adaptive food governance under environmental change: A comparison between South African and Brazilian retailers

Governance in the food system has become a key topic of discussion in light of the 2007-08 food price crisis. Of special importance has been the shift to include the role that non-state actors are likely to play in achieving food security under global environmental change (GEC). This paper aims to compare private sector food system governance trends in two emerging economies, Brazil and South Africa. It focuses on practices around adaptation, an area largely neglected in climate change discussion, yet a critical factor in coping with the societal consequences of GEC. This study identifies several processes, particularly within the retail sector, that could indicate normative mechanisms through which 'good governance' can be translated into practice

Learning about knowledge: A complex network approach

This article describes an approach to modeling knowledge acquisition in terms of walks along complex networks. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks, i.e. networks composed of successive interconnected layers, arise naturally as a consequence of compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks, i.e. unreachable nodes, the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barab\'asi-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaux of knowledge stagnation in the case of the preferential movements strategy in presence of conditional edges.Comment: 18 pages, 19 figure

CO013. PREVALÊNCIA DE SÍNDROME METABÓLICA EM CRIANÇAS E ADOLESCENTES COM DIABETES MELLITUS TIPO 1

https://nsuworks.nova.edu/nsudigital_harrison/3368/thumbnail.jp

Performance of networks of artificial neurons: The role of clustering

The performance of the Hopfield neural network model is numerically studied on various complex networks, such as the Watts-Strogatz network, the Barab{\'a}si-Albert network, and the neuronal network of the C. elegans. Through the use of a systematic way of controlling the clustering coefficient, with the degree of each neuron kept unchanged, we find that the networks with the lower clustering exhibit much better performance. The results are discussed in the practical viewpoint of application, and the biological implications are also suggested.Comment: 4 pages, to appear in PRE as Rapid Com