Rapid microwave synthesis of the iron arsenides NdFeAsO and NdFe0.9Co0.1AsO

The future of iron pnictide superconductors in technology is still undecided. While these materials are now known to possess relatively high critical temperatures and critical magnetic fields, processing methods for these superconductors are still in the development stage. Recently we have been investigating possible ways to speed up the synthetic process for obtaining polycrystalline iron arsenide superconductors and other transition metal pnictides. Here we report the synthesis of NdFeAsO and NdFe_0.9Co_0.1AsO in less than 1 h total exposure to microwave radiation using an additional microwave susceptor to surround the reaction ampoule. Structure and property measurements reveal the samples to be of high quality and superconducting when Co doped.     

ADSORPTION,KINETICS, AND EQUILIBRIUM STUDIES ON REMOVAL OF 4,4-DDT FROM AQUEOUS SOLUTIONS USING LOW-COST ADSORBENTS

The removal of a chlorinated pesticide (4,4-DDT) from aqueous solutions by a batch adsorption technique using different low-cost adsorbents was investigated. Two adsorbents, wood sawdust (A) and cork wastes (B), were used to determine adsorption efficiency. The influence of the adsorbent particle size and the organic matter of water (humic acids) on the removal process was studied. The obtained results were compared to those obtained with a commercial powdered activated carbon (PAC, F400, Chemviron) (C). Kinetic studies were performed to understand the mechanistic steps of the adsorption process. The rate of the adsorption kinetics of 4,4-DDT on the low-cost adsorbents was found best fitted with a pseudo-second-order kinetic model. This is in contrast to the rate of the adsorption kinetics of the PAC F400, which was best fitted with the Lagergren model. The application of the Morris-Weber equation showed that the adsorption process of 4,4-DDT on these adsorbents was complex. Both the adsorption on the surface and the intraparticle diffusion were the rate-controlling mechanisms. Langmuir and Freundlich adsorption isotherms were applicable to the adsorption process and their constants were evaluated. The adsorption capacity (q_m) calculated from the Langmuir isotherm (69.44 mg·g^?1, 19.08 mg·g^?1, and 163.90 mg·g^?1, respectively, for A, B, and C) showed that the process is highly particle size dependent, that the organic matter influenced the adsorption process negatively, and that wood sawdust is the most effective adsorbent for the removal of 4,4-DDT from aqueous solutions. The adsorbents studied exhibited a possible application in water decontamination, as well as in treatment of industrial and agricultural waste waters.     

Hybrid Approach for Energy Aware Management of Multi-cloud Architecture Integrating user Machines

The arrival and development of remotely accessible services via the cloud has transfigured computer technology. However, its impact on personal computing remains limited to cloud-based applications. Meanwhile, acceptance and usage of telephony and smartphones have exploded. Their sparse administration needs and general user friendliness allows all people, regardless of technology literacy, to access, install and use a large variety of applications. We propose in this paper a model and a platform to offer personal computing a simple and transparent usage similar to modern telephony. In this model, user machines are integrated within the classical cloud model, consequently expanding available resources and management targets. In particular, we defined and implemented a modular architecture including resource managers at different levels that take into account energy and QoS concerns. We also propose simulation tools to design and size the underlying infrastructure to cope with the explosion of usage. Functionalities of the resulting platform are validated and demonstrated through various utilization scenarios. The internal scheduler managing resource usage is experimentally evaluated and compared with classical methodologies, showing a significant reduction of energy consumption with almost no QoS degradation.     

Regression models with correlated errors based on functional random design

This paper deals with the study of the estimation of the functional regression operator when the explanatory variable takes its values in some abstract space of functions. The main goal of this paper is to establish the exact rate of convergence of the mean squared error of the functional version of the Nadaraya–Watson kernel estimator when the errors come from a stationary process under long or short memory and based on random functional data. Moreover, these theoretical results are checked through some simulations with regular (smooth) and irregular curves and then with real data.