We obtain magnetic properties of magnesioferrite nanoparticles grew in a magnesiowstite crystalline matrix by analyzing the temperature dependence of the coercive field and the magnetization behavior. We introduce a modelling scheme to evaluate those properties in which the input variables are estimated from experimental data. The core of the method relies in sampling for nearby values in order to reach the optimal one that yields the smallest difference between calculated and experimental data. This procedure is efficient and our results match with the ones found in the literature. Thus, our method paves the way for a robust characterization of superparamagnetic nanoparticle materials.

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The use of applications is important to support the business processes of companies. However, most of these applications are not designed to function collaboratively. An integration solution orchestrates a group of applications, allowing data and functionality reuse. The performance of an integration solution depends on the optimum configuration of the number of threads in the runtime engine provided by the integration platforms. It is common that this configuration relies on the empirical knowledge of the software engineers, and it has a direct impact on the performance of integration solutions. The optimum number of threads may be found by means of simulation models. This article presents a methodology and a tool to assist with the generation of simulation models based on queuing theory, in order to find the optimum number of threads to execute an integration solution focusing on performance improvement. We introduce a case of study to demonstrate and experiments to evaluate our proposal.

ZnO nanoparticles have been synthesised via a co-precipitation method using different complexing agents. X-ray diffraction (XRD) analysis revealed that ZnO nanoparticles were composed of a single hexagonal wurtzite phase. Transmission electron microscopy (TEM) analysis indicates that the samples prepared without any complexing agent have slight agglomeration characteristics presenting a prismatic morphology and a wider size distribution from 22 to 72 nm, which provides good material packing density. However, samples synthesised using urea and glycine are similar and show spherical-like morphology. XRD and TEM analyses indicate that complexing agents also have an important role in the size of the ZnO nanoparticles, where the average particle size of 47 and 22 nm were obtained using urea and glycine, respectively.