Synthesis, characterization and crystal structure of a novel thiocyanate–ruthenium(II) complex

The cis-[Ru(dppb)(Me-bipy)(NCS)₂], dppb = 1,4-bis (diphenylphosphino)butane, Me-bipy = 4,4′-dimethyl-2,2′-bipyridine, and NCS = thiocyanate, was synthesized and characterized by spectroscopic and electrochemical techniques and its structure was determined by crystal X-ray analysis. The crystal structure reveals that the coordination geometry around the Ru(II) center is distorted octahedron where two molecules of thiocyanate are bonded to the ruthenium through nitrogen atom in cis orientation. The half-wave formal potential value E_1/2 = 0.8 V (versus Ag/AgCl) observed is considerable higher than that for the cis-[RuCl₂(dppb)(Me-bipy)] complex, E_1/2 = 0.6 V (versus Ag/AgCl), well illustrating the strong π-acceptor effect the NCS ligand toward the backbonding interaction with the Ru(II) metal center. The MLCT absorption bands of the thiocyanate complex present a higher molar absorptivity (about 12%) compared with the cis-[RuCl₂(dppb)(Me-bipy)] complex, in the same experimental conditions. These properties make the complex potentially promising for the photosensitization process.     

OpenCOPI: middleware integration for Ubiquitous Computing

In this paper, we present OpenCOPI (Open COntext Platform Integration), a Service-Oriented Architecture-based middleware platform that supports the integration of services provided by distinct sources, ranging from services offered by simple systems to more complex services provided by context-provision middleware. OpenCOPI offers selection and composition mechanisms to, respectively, select and compose services provided by different sources, considering applications of both Quality of Service and Quality of Context requirements. It also offers an adaptation mechanism that enables to adapt the application execution due to service failures, service quality fluctuation and user mobility. OpenCOPI allows the definition of applications in a higher abstraction level by the specification of a semantic workflow that contains abstract activities. This paper illustrates the use of OpenCOPI in an application from the Gas & Oil Industry and it also shows the evaluation of the main mechanisms of OpenCOPI: the service selection, composition, adaptation and workflow execution.     

Master batch approach for developing PVDF/EVA/CNT nanocomposites with co-continuous morphology and improved electrical conductivity

Conducting polymer composites constituted by co-continuous poly (vinylidene fluoride) (PVDF)/ ethylene- vinyl acetate copolymer (EVA) blends with multiwalled carbon nanotube (CNT) were prepared by melt mixing using different procedures. The effect of the master batch approach on the conductivity, morphology, mechanical, thermal and rheological properties of PVDF/EVA/CNT nanocomposites was compared with that based on one step mixing strategy. The selective extraction experiments revealed that CNT was preferentially localized in the EVA phase in all situations, even when PVDF@CNT master batch was employed. Nanocomposites prepared with EVA@CNT master batch displayed higher conductivity, whose value reached around 10⁻¹ S m⁻¹ with the addition of 0.56 vol% of CNT. The better electrical performance was attributed to the better distribution of the filler, as indicated by transmission electron microscopy and rheological behavior. The electrical and rheological behavior were also investigated as a function of the CNT content.     

Spectroscopic Multicomponent Analysis Using Multi-objective Optimization for Variable Selection

The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II （strength Pareto evolutionary algorithm II）. We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR （near-infrared spectroscopy） spectrometry where the objective is the determination of a variable subgroup with information about E protein content （%）, test weight （Kg/HI）, WKT （wheat kernel texture） （%） and farinograph water absorption （%）. The results of traditional techniques of multivariate calibration as the SPA （successive projections algorithm）, PLS （partial least square） and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.     

Influence of green creativity on organizations: A case study from the perspectives of leaders and subordinates

The sustainability framework has a strong influence on the policies, practices and procedures of companies. Green creativity plays a pivotal role in the development of initiatives and innovations for the environmental pillar of sustainability. Based on a survey applied to a Portuguese company with an accredited environmental management system (N = 146), the findings reveal that green creativity is influenced in different ways when analysed from distinct perspectives. The leader's green creativity is positively influenced by the subordinate's green self-efficacy and personal identification with the leader, whereas the subordinate's green creativity is positively influenced by their green passion and green self-efficacy, and the leaders' green creativity. This study shows that green creativity develops differentially according to distinct job positions and expectations that in practice must be complementary and synergistic for its effective development.     

How can Cleaner Production practices contribute to meet ISO 14001 requirements? Critical analysis from a survey with industrial companies

The companies’ needs to adopt changes in their way of production to maximize the environmental performance required by their stakeholders, and at the same time, to maximize their economic and market performance, have made them seek for environmental strategies and certifications. In this sense, the Cleaner Production and the Environmental Management System based on ISO 14001 have been, respectively, presented, since the main objective of this research is to identify and analyze Cleaner Production contributions to comply with ISO 14001 requirements. For such, a survey research has been carried out in Brazilian industrial companies certified by ISO 14001. We have identified the main performance factors by leading practices and variables of Cleaner Production that contribute to the compliance with the standard requirements by companies. Thus, it has been noted that Cleaner Production is an important strategy for the preparation of companies for certification as well as for improving their environmental performance.     

Detection and characterization of defects using GMR probes and artificial neural networks

This work presents an eddy-current testing system based on a giant magnetoresistive (GMR) sensing device. Non-destructive tests in aluminum plates are applied in order to extract information about possible defects: cracks, holes and other mechanical damages. Eddy-current testing (ECT) presents major benefits such as low cost, high checking speed, robustness and high sensitivity to large classes of defects. Coil based architecture probes or coil-magnetoresistive probes are usually used in ECT. In our application the GMR sensor is used to detect a magnetic field component parallel to a plate surface, when an excitation field perpendicular to the plate is imposed. A neural network processing architecture, including a multilayer perceptron and a competitive neural network, is used to classify defects using the output amplitude of the eddy-current probe (ECP) and its operation frequency. The crack detection, classification and estimation of the geometrical characteristics, for different classes of defects, are described in the paper.     

Water diffusion in polymer nano-films measured with microcantilevers

We present a method to measure the absorption of water molecules from the liquid and the vapour phase into polymer nano-films and the diffusion inside these films. Film thickness can be down to 45 nm. To demonstrate the possibilities of this method we use polymer films that are deposited on the upper side of a silicon cantilever by plasma polymerization of norbornene. When a microdrop of water is deposited onto the initially straight cantilever, the drop causes the cantilever to bend while it evaporates. Evaporation of such small water drops usually takes less than a second. An upwards bending is due to capillary forces and a downwards bending is due to the diffusion of water into the polymer film – and the consequent volume expansion (swelling) of the film. The magnitude of the capillary forces and the extent of swelling continuously change during drop evaporation. When drop evaporation is over the cantilever returns to its initial straight position. We simulate the time dependent bending with a numerical model that qualitatively agrees with the experiment. From the time dependence of cantilever bending we are able to determine the diffusion coefficient of water in the thin polymer film.     

Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.