Lu-Hf and U-Pb age determination of Capivarita Anorthosite in the Dom Feliciano Belt, Brazil

The Capivarita Anorthosite, formed in an intraplate environment and later metamorphosed under amphibolites fades conditions, is exposed in the Dom Feliciano Belt as part of the Brasiliano magmatic arc and occurs as a roof-pedant in, or is even intruded by, 0.6 Ga post-collisional granites. In this work, magmatic and metamorphic minerals were dated using the LA-MC-ICP-MS in situ method. U-Pb magmatic and metamorphic zircon dating yielded an age of 1573 +/- 21 Ma and of 606 +/- 6 Ma, respectively, whereas the igneous titanite dating yielded an age of 1530 +/- 33 Ma and the metamorphic ages were 651 +/- 9 Ma and 601 +/- 5 Ma. The Lu-Hf model ages showed two clusters from 1.81 to 2.03 Ga (calf from +2.21 to +6.42) and 2.55-2.62 Ga (epsilon epsilon Hf from -4.59 to -5.64). This intraplate magmatism can be connected to a very important episode of continental accretion in an extensional setting from the fragmentation of the supercontinent during the Early Mesoproterozoic. (C) 2011 Elsevier B.V. All rights reserved.

U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.