985 resultados para transfer reactions
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The knowledge-based society we live in has stressed the importance of human capital and brought talent to the top of most wanted skills, especially to companies who want to succeed in turbulent environments worldwide. In fact, streams, sequences of decisions and resource commitments characterize the day-to-day of multinational companies (MNCs). Such decision-making activities encompass major strategic moves like internationalization and new market entries or diversification and acquisitions. In most companies, these strategic decisions are extensively discussed and debated and are generally framed, formulated, and articulated in specialized language often developed by the best minds in the company. Yet the language used in such deliberations, in detailing and enacting the implementation strategy is usually taken for granted and receives little if any explicit attention (Brannen & Doz, 2012) an can still be a “forgotten factor” (Marschan et al. 1997). Literature on language management and international business refers to lack of awareness of business managers of the impact that language can have not only in communication effectiveness but especially in knowledge transfer and knowledge management in business environments. In the context of MNCs, management is, for many different reasons, more complex and demanding than that of a national company, mainly because of diversity factors inherent to internationalization, namely geographical and cultural spaces, i.e, varied mindsets. Moreover, the way of functioning, and managing language, of the MNC depends on its vision, its values and its internationalization model, i.e on in the way the MNE adapts to and controls the new markets, which can vary essentially from a more ethnocentric to a more pluricentric focus. Regardless of the internationalization model followed by the MNC, communication between different business units is essential to achieve unity in diversity and business sustainability. For the business flow and prosperity, inter-subsidiary, intra-company and company-client (customers, suppliers, governments, municipalities, etc..) communication must work in various directions and levels of the organization. If not well managed, this diversity can be a barrier to global coordination and create turbulent environments, even if a good technological support is available (Feely et al., 2002: 4). According to Marchan-Piekkari (1999) the tongue can be both (i) a barrier, (ii) a facilitator and (iii) a source of power. Moreover, the lack of preparation for the barriers of linguistic diversity can lead to various costs, including negotiations’ failure and failure on internationalization.. On the other hand, communication and language fluency is not just a message transfer procedure, but above all a knowledge transfer process, which requires extra-linguistic skills (persuasion, assertiveness …) in order to promote credibility of both parties. For this reason, MNCs need a common code to communicate and trade information inside and outside the company, which will require one or more strategies, in order to overcome possible barriers and organization distortions.
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This study aimed to carry out experimental work to obtain, for Newtonian and non-Newtonian fluids, heat transfer coefficients, at constant wall temperature as boundary condition, in fully developed laminar flow inside a helical coil. The Newtonian fluids studied were aqueous solutions of glycerol, 25%, 36%, 43%, 59% and 78% (w/w) and the non-Newtonian fluids aqueous solutions of carboxymethylcellulose (CMC), a polymer, with concentrations 0.1%, 0.2%, 0.3%, 0.4% and 0.6% (w/w) and aqueous solutions of xanthan gum (XG), another polymer, with concentrations 0.1% and 0.2% (w/w). According to the rheological study performed, the polymer solutions had shear thinning behavior and different values of elasticity. The helical coil used has internal diameter, curvature ratio, length and pitch, respectively: 0.004575 m, 0.0263, 5.0 m and 11.34 mm. The Nusselt numbers for the CMC solutions are, on average, slightly higher than those for Newtonian fluids, for identical Prandtl and generalized Dean numbers. As outcome, the viscous component of the shear thinning polymer tends to potentiate the mixing effect of the Dean cells. The Nusselt numbers of the XG solutions are significant lower than those of the Newtonian solutions, for identical Prandtl and generalized Dean numbers. Therefore, the elastic component of the polymer tends to diminish the mixing effect of the Dean cells. A global correlation, for Nusselt number as a function of Péclet, generalized Dean and Weissenberg numbers for all Newtonian and non-Newtonian solutions studied, is presented.
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This work presents the results of the experimental study of proton induced nuclear reactions in lithium, namely the 7Li(p,α) 4He, 6Li(p,α) 3He and 7Li(p,p)7Li reactions. The amount of 7Li and 6Li identified as primordial and observed in very old stars of the Milky Way galactic halo strongly deviates from the predictions of primordial nucleosynthesis and stellar evolution models which depend, among other factors, on the cross sections of reactions like 7Li(p,α) 4He and 6Li(p,α) 3He. These discrepancies have triggered a large amount of research in the fields of stellar evolution, cosmology, pre-galactic evolution and low energy nuclear reactions. Focusing on nuclear reactions, this work has measured the 7Li(p,α) 4He and 6Li(p,α) 3He reactions cross sections (expressed in terms of the astrophysical S -factor) with higher accuracy, and the electron screening effects in these reactions for different environments (insulators and metallic targets). The 7Li(p,α) 4He angular distributions were also measured. These measurementstook place in two laboratory facilities, in the framework of the LUNA (Laboratory for Undergroud Nuclear Astrophysics) international collaboration, namely the Laboratorio ´ de Feixe de Ioes ˜ in ITN (Instituto Tecnologico ´ e Nuclear) Sacavem, ´ Portugal, and the Dynamitron-TandemLaboratorium in Ruhr-Universitat¨ Bochum, Germany. The ITN target chamber was modified to measure these nuclear reactions, with the design and construction of new components, the addition of one turbomolecular pump and a cold finger. The 7Li(p,α) 4He and 6Li(p,α) 3He reactions were measured concurrently with seven and four targets, respectively. These targets were produced in order to obtain adequate and stable lithium depth profiles. In metallic environments, the measured electron screening potential energies are much higher than the predictions of atomic-physics models. The Debye screening model applied to the metallic conduction electrons is able to explain these high values. It is a simple model, but also very robust. Concerning primordial nucleosynthesis and stellar evolution models, these results are very important as they show that laboratory measurements are well controlled, and the model inputs from these cross sections are therefore correct. In this work the 7Li(p,p)7Li differential cross section was also measured, which is useful to describe the 7Li(p,α) 4He entrance channel.
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Eur. J. Biochem. 271, 1329–1338 (2004)
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Journal of Electroanalytical Chemistry 541 (2003) 153-162
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.
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The present study aims to characterize ultrafine particles emitted during gas metal arc welding of mild steel and stainless steel, using different shielding gas mixtures, and to evaluate the effect of metal transfer modes, controlled by both processing parameters and shielding gas composition, on the quantity and morphology of the ultrafine particles. It was found that the amount of emitted ultrafine particles (measured by particle number and alveolar deposited surface area) are clearly dependent from the main welding parameters, namely the current intensity and the heat input of the Welding process. The emission of airborne ultrafine particles increases with the current intensity as fume formation rate does. When comparing the shielding gas mixtures, higher emissions were observed for more oxidizing mixtures, that is, with higher CO2 content, which means that these mixtures originate higher concentrations of ultrafine particles (as measured by number of particles. by cubic centimeter of air) and higher values of alveolar deposited surface area of particles, thus resulting in a more hazardous condition regarding welders exposure.
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The main objective of this work was to evaluate the hypothesis that the greater transfer stability leads also to less volume of fumes. Using an Ar + 25%CO2 blend as shielding gas and maintaining constant the average current, wire feed speed and welding speed, bead-on-plate welds were carried out with plain carbon steel solid wire. The welding voltage was scanned to progressively vary the transfer stability. Using two conditions of low stability and one with high stability, fume generation was evaluated by means of the AWS F1.2:2006 standard. The influence of these conditions on fume morphology and composition was also verified. A condition with greater transfer stability does not generate less fume quantity, despite the fact that this condition produces fewer spatters. Other factors such as short-circuit current, arcing time, droplet diameters and arc length are the likely governing factors, but in an interrelated way. Metal transfer stability does not influence either the composition or the size/morphology of fume particulates. (c) 2014 Elsevier B.V. All rights reserved.
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Background: Brown adipose tissue (BAT) plays an important role in whole body metabolism and could potentially mediate weight gain and insulin sensitivity. Although some imaging techniques allow BAT detection, there are currently no viable methods for continuous acquisition of BAT energy expenditure. We present a non-invasive technique for long term monitoring of BAT metabolism using microwave radiometry. Methods: A multilayer 3D computational model was created in HFSS™ with 1.5 mm skin, 3-10 mm subcutaneous fat, 200 mm muscle and a BAT region (2-6 cm3) located between fat and muscle. Based on this model, a log-spiral antenna was designed and optimized to maximize reception of thermal emissions from the target (BAT). The power absorption patterns calculated in HFSS™ were combined with simulated thermal distributions computed in COMSOL® to predict radiometric signal measured from an ultra-low-noise microwave radiometer. The power received by the antenna was characterized as a function of different levels of BAT metabolism under cold and noradrenergic stimulation. Results: The optimized frequency band was 1.5-2.2 GHz, with averaged antenna efficiency of 19%. The simulated power received by the radiometric antenna increased 2-9 mdBm (noradrenergic stimulus) and 4-15 mdBm (cold stimulus) corresponding to increased 15-fold BAT metabolism. Conclusions: Results demonstrated the ability to detect thermal radiation from small volumes (2-6 cm3) of BAT located up to 12 mm deep and to monitor small changes (0.5°C) in BAT metabolism. As such, the developed miniature radiometric antenna sensor appears suitable for non-invasive long term monitoring of BAT metabolism.
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A novel two-component enzyme system from Escherichia coli involving a flavorubredoxin (FlRd) and its reductase was studied in terms of spectroscopic, redox, and biochemical properties of its constituents. FlRd contains one FMN and one rubredoxin (Rd) center per monomer. To assess the role of the Rd domain, FlRd and a truncated form lacking the Rd domain (FlRd¢Rd), were characterized. FlRd contains 2.9 ( 0.5 iron atoms/subunit, whereas FlRd¢Rd contains 2.1 ( 0.6 iron atoms/subunit. While for FlRd one iron atom corresponds to the Rd center, the other two irons, also present in FlRd¢Rd, are most probably due to a di-iron site. Redox titrations of FlRd using EPR and visible spectroscopies allowed us to determine that the Rd site has a reduction potential of -140 ( 15 mV, whereas the FMN undergoes reduction via a red-semiquinone, at -140 ( 15 mV (Flox/Flsq) and -180 ( 15 mV (Flsq/Flred), at pH 7.6. The Rd site has the lowest potential ever reported for a Rd center, which may be correlated with specific amino acid substitutions close to both cysteine clusters. The gene adjacent to that encoding FlRd was found to code for an FAD-containing protein, (flavo)rubredoxin reductase (FlRd-reductase), which is capable of mediating electron transfer from NADH to DesulfoVibrio gigas Rd as well as to E. coli FlRd. Furthermore, electron donation was found to proceed through the Rd domain of FlRd as the Rd-truncated protein does not react with FlRd-reductase. In vitro, this pathway links NADH oxidation with dioxygen reduction. The possible function of this chain is discussed considering the presence of FlRd homologues in all known genomes of anaerobes and facultative aerobes.
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The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.
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Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm
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We have evaluated the sensitivity of the classical blood subinoculation method, modified through cyclophosphamide treatment of transferred mice, for the detection of occult parasitaemias in Trypanosoma cruzi chronically infected mice. Besides its simplicity, the method was shown to be highly sensitive for both the "chronic" phase parasites (99% of chronic cases were shown to harbour occult parasitaemias) and for the acute phase parasites (T. cruzi could be detected in 53.8% of animals transferred with one Y strain parasite and in 20% of animals transferred with one CL strain parasite). Using acute phase bloodforms, the assay proved to be more sensitive than conventional subinoculation when dealing with the CL, but not the Y strain of the parasite. With the help of this parasite detection tool, we have studied during a one year period, the evolution of subpatent parasitaemias in a group of mice which survived through chemotherapy from lethal acute phase of T. cruzi infection. Cyclophosphamide transfer assay revealed occult parasitaemias in 100% of the chronic animals, nevertheless, continuous and discontinuous patterns of positivity were observed.
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The benzoyl hydrazone based dimeric dicopper(II) complex [Cu2(R)(CH3O)(NO3)]2(CH3O)2 (R-Cu2+), recently reported by us, catalyzes the aerobic oxidation of catechols (catechol (S1), 3,5- itertiarybutylcatechol (S2) and 3-nitrocatechol (S3)) to the corresponding quinones (catecholase like activity), as shown by UV–Vis absorption spectroscopy in methanol/HEPES buffer (pH 8.2) medium at 25 C. The highest activity is observed for the substituted catechol (S2) with the electron donor tertiary butyl group, resulting in a turnover frequency (TOF) value of 1.13 103 h1. The complex R-Cu2+ also exhibits a good catalytic activity in the oxidation (without added solvent) of 1-phenylethanol to acetophenone by But OOH under low power (10 W) microwave (MW) irradiation. 2014 Elsevier B.V. All rights reserved.
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The cleaning of syngas is one of the most important challenges in the development of technologies based on gasification of biomass. Tar is an undesired byproduct because, once condensed, it can cause fouling and plugging and damage the downstream equipment. Thermochemical methods for tar destruction, which include catalytic cracking and thermal cracking, are intrinsically attractive because they are energetically efficient and no movable parts are required nor byproducts are produced. The main difficulty with these methods is the tendency for tar to polymerize at high temperatures. An alternative to tar removal is the complete combustion of the syngas in a porous burner directly as it leaves the particle capture system. In this context, the main aim of this study is to evaluate the destruction of the tar present in the syngas from biomass gasification by combustion in porous media. A gas mixture was used to emulate the syngas, which included toluene as a tar surrogate. Initially, CHEMKIN was used to assess the potential of the proposed solution. The calculations revealed the complete destruction of the tar surrogate for a wide range of operating conditions and indicated that the most important reactions in the toluene conversion are C6H5CH3 + OH <-> C6H5CH2 + H2O, C6H5CH3 + OH <-> C6H4CH3 + H2O, and C6H5CH3 + O <-> OC6H4CH3 + H and that the formation of toluene can occur through C6H5CH2 + H <-> C6H5CH3. Subsequently, experimental tests were performed in a porous burner fired with pure methane and syngas for two equivalence ratios and three flow velocities. In these tests, the toluene concentration in the syngas varied from 50 to 200 g/Nm(3). In line with the CHEMKIN calculations, the results revealed that toluene was almost completely destroyed for all tested conditions and that the process did not affect the performance of the porous burner regarding the emissions of CO, hydrocarbons, and NOx.