Influence of heavy rare earth ions substitution on microstructure and magnetism of nanocrystalline magnetite

In this work we report results on the influence of heavy rare earth ions substitution on microstructure and magnetism of nanocrystalline magnetite. A series of Fe(2.85)RE(0.15)O(4) (RE = Gd, Dy, Ho, Tm and Yb) samples have been prepared by high energy ball milling. Structure/microstructure investigations of two selected samples Fe(2.85)Gd(0.15)O(4) and Fe(2.85)Tm(0.15)O(4), represent an extension of the previously published results on Fe(3)O(4)/gamma-Fe(2)O(3), Fe(2.85)Y(0.15)O(4) and Fe(2.55)In(0.45)O(4) [Z. Cvejic, S. Rakic, A. Kremenovic, B. Antic, C. Jovalekic. Ph. Colomban, Sol. State Sciences 8 (2006) 908], while magnetic characterization has been done for all the samples. Crystallite/particle size and strain determined by X-ray diffractometry and Transmission electron microscopy (TEM) confirmed the nanostructured nature of the mechanosynthesized materials. X-ray powder diffraction was used to analyze anisotropic line broadening effects through the Rietveld method. The size anisotropy was found to be small while strain anisotropy was large, indicating nonuniform distribution of deffects in the presence of Gd and Tm in the crystal structure. Superparamagnetic(SPM) behavior at room temperature was observed for all samples studied. The Y-substituted Fe(3)O(4) had the largest He and the lowest M(S). We discuss the changes in magnetic properties in relation to their magnetic anisotropy and microstructure. High field irreversibility (H>20kOe) in ZFC/FC magnetization versus temperature indicates the existence of high magnetocrystalline and/or strain induced anisotropy. (C) 2008 Elsevier B.V. All rights reserved.

Lower and Upper Neoproterozoic magmatic records in Itaiacoca Belt (Parana-Brazil): Zircon ages and lithostratigraphy studies

The Itaiacoca Belt is a sequence of metavolcanic and metasedimentary rocks that crop out east of Parana and southeast of Sao Paulo states, in southern Brazil. This geologic-geochronologic study supports division of the Itaiacoca Belt into two major lithologic sequences. The older is a carbonate platform sequence (dolomitic meta-limestones/metamarls/calc-phyllites/ carbonate phyllites) with minimum deposition ages related to the end of the Mesoproterozoic/beginning of the Neoproterozoic (1030-908 Ma:U-Pb, zircon of metabasic rocks). The younger sequence contains mainly clastics deposits (meta-arkoses/metavolcanics/metaconglomerates/metapelites) with deposition ages related to the Neoproterozoic (645-628 Ma:U-Pb,zircon of metavolcanic rocks). These ages are quite close to K-Ar ages (fine fraction) of the 628-610 Ma interval, associated with metamorphism and cooling of the Itaiacoca Belt. The contact between the dolomitic meta-limestones and meta-arkoses is marked by intense stretching and high-angle foliation, suggesting that the discontinuity between these associations resulted from shearing. It is proposed here that the term Itaiacoca Sequence, should represent the dolomitic meta-limestones, and the term Abapa Sequence represents the meta-arkoses/metavolcanics/phyllites. in a major tectonic context, these periods are related to the break-up of Rodinia Supercontinent (1030-908 Ma) and the amalgamation of the Gondwana Supercontinent (645-628 Ma). (C) 2008 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

Software maintenance project delays prediction using Bayesian Networks

Managing software maintenance is rarely a precise task due to uncertainties concerned with resources and services descriptions. Even when a well-established maintenance process is followed, the risk of delaying tasks remains if the new services are not precisely described or when resources change during process execution. Also, the delay of a task at an early process stage may represent a different delay at the end of the process, depending on complexity or services reliability requirements. This paper presents a knowledge-based representation (Bayesian Networks) for maintenance project delays based on specialists experience and a corresponding tool to help in managing software maintenance projects. (c) 2006 Elsevier Ltd. All rights reserved.

Covariance matrix formula for Birnbaum-Saunders regression models

The Birnbaum-Saunders regression model is commonly used in reliability studies. We derive a simple matrix formula for second-order covariances of maximum-likelihood estimators in this class of models. The formula is quite suitable for computer implementation, since it involves only simple operations on matrices and vectors. Some simulation results show that the second-order covariances can be quite pronounced in small to moderate sample sizes. We also present empirical applications.