983 resultados para Experimental results
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In this work, we demonstrated the fabrication of two-dimensional (2D) photonic crystals layers (2D-PCLs) by combining holographic recording and the evaporation of antimony-based glasses. Such materials present high refractive indices that can be tuned from 1.8 to 2.4, depending on the film composition; thus, they are interesting dielectric materials for fabrication of 2D-PCLs. The good quality of the obtained samples allowed the measurement of their PC properties through the well-defined Fano resonances that appear in the transmittance spectrum measurements at different incidence angles. The experimental results are in good agreement with the calculated band diagram for the hexagonal asymmetric structure. (C) 2008 American Institute of Physics.
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In this paper, we present an analog of Bell's inequalities violation test for N qubits to be performed in a nuclear magnetic resonance (NMR) quantum computer. This can be used to simulate or predict the results for different Bell's inequality tests, with distinct configurations and a larger number of qubits. To demonstrate our scheme, we implemented a simulation of the violation of the Clauser, Horne, Shimony and Holt (CHSH) inequality using a two-qubit NMR system and compared the results to those of a photon experiment. The experimental results are well described by the quantum mechanics theory and a local realistic hidden variables model (LRHVM) that was specifically developed for NMR. That is why we refer to this experiment as a simulation of Bell's inequality violation. Our result shows explicitly how the two theories can be compatible with each other due to the detection loophole. In the last part of this work, we discuss the possibility of testing some fundamental features of quantum mechanics using NMR with highly polarized spins, where a strong discrepancy between quantum mechanics and hidden variables models can be expected.
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The Brazilian Synchrotron Light Laboratory [Laboratorio Nacional de Luz Sincrotron (LNLS), Campinas, SP, Brazil] is the first commissioned synchrotron light source in the southern hemisphere. The first wiggler macromolecular crystallography beamline (MX2) at the LNLS has been recently constructed and brought into operation. Here the technical design, experimental set-up, parameters of the beamline and the first experimental results obtained at MX2 are described. The beamline operates on a 2.0 T hybrid 30-pole wiggler, and its optical layout includes collimating mirror, Si( 111) double-crystal monochromator and toroidal bendable mirror. The measured flux density at the sample position at 8.7 eV reaches 4.8 x 10(11) photons s(-1) mm(-2) (100 mA)(-1). The beamline is equipped with a MarResearch Desktop Beamline Goniostat (MarDTB) and 3 x 3 MarMosaic225 CCD detector, and is controlled by a customized version of the Blu-Ice software. A description of the first X-ray diffraction data sets collected at the MX2 LNLS beamline and used for macromolecular crystal structure solution is also provided.
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This work reports on the crystallization of amorphous silicon (a-Si) films doped with 1 at. % of nickel. The films, with thicknesses ranging from 10 to 3000 nm, were deposited using the cosputtering method onto crystalline quartz substrates. In order to investigate the crystallization mechanism in detail, a series of undoped a-Si films prepared under the same deposition conditions were also studied. After deposition, all a-Si films were submitted to isochronal thermal annealing treatments up to 1000 degrees C and analyzed by Raman scattering spectroscopy. Based on the present experimental results, it is possible to state that (a) when compared to the undoped a-Si films, those containing 1 at. % of Ni crystallize at temperatures similar to 100 degrees C lower, and that (b) the film thickness influences the temperature of crystallization that, in principle, tends to be lower in films thinner than 1000 nm. The possible reasons associated to these experimental observations are presented and discussed in view of some experimental and thermodynamic aspects involved in the formation of ordered Si-Si bonds and in the development of Ni-silicide phases. (c) 2008 American Institute of Physics.
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Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.
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Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.
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The doubly positively charged gas-phase molecules BrO(2+) and NBr(2+) have been produced by prolonged high-current energetic oxygen (17 keV (16)O(-)) ion surface bombardment (ion beam sputtering) of rubidium bromide (RbBr) and of ammonium bromide (NH(4)Br) powdered ionic salt samples, respectively, pressed into indium foil. These novel species were observed at half-integer m/z values in positive ion mass spectra for ion flight times of roughly similar to 12 mu s through a magnetic-sector secondary ion mass spectrometer. Here we present these experimental results and combine them with a detailed theoretical investigation using high level ab initio calculations of the ground states of BrO(2+) and NBr(2+), and a manifold of excited electronic states. NBr(2+) and BrO(2+), in their ground states, are long-lived metastable gas-phase molecules with well depths of 2.73 x 10(4) cm(-1) (3.38 eV) and 1.62 x 10(4) cm(-1) (2.01 eV); their fragmentation channels into two monocations lie 2.31 x 10(3) cm(-1) (0.29 eV) and 2.14 x 10(4) cm(-1) (2.65 eV) below the ground state minimum. The calculated lifetimes for NBr(2+) (v '' < 35) and BrO(2+) (v '' < 18) are large enough to be considered stable against tunneling. For NBr(2+), we predicted R(e) = 3.051 a(0) and omega(e) = 984 cm(-1); for BrO(2+), we obtained 3.033 a(0) and 916 cm(-1), respectively. The adiabatic double ionization energies of BrO and NBr to form metastable BrO(2+) and NBr(2+) are calculated to be 30.73 and 29.08 eV, respectively. The effect of spin-orbit interactions on the low-lying (Lambda + S) states is also discussed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3562121]
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Early reports stated that Au was a catalyst of choice for the BOR because it would yield a near complete faradaic efficiency. However, it has recently been suggested that gold could yield to some extent the heterogeneous hydrolysis of BH(4)(-),therefore lowering the electron count per BH(4)(-), especially at low potential. Actually, the blur will exist regarding the BOR mechanism on Au as long as no physical proof regarding the reaction intermediates is not put forward. In that frame, in situ physical techniques like FTIR exhibit some interest to study the BOR. Consequently, in situ infrared reflectance spectroscopy measurements (SPAIRS technique) have been performed in 1 M NaOH/1 M NaBH(4) on a gold electrode with the aim to detect the intermediate species. We monitored several bands in B-H ((nu) over bar similar to 1180,1080 and 972 cm(-1)) and B-O bond regions ((nu) over bar =1325 and similar to 1425cm(-1)), which appear sequentially as a function of the electrode polarization. These absorption bands are assigned to BH(3), BH(2) and BO(2)(-) species. At the light of the experimental results, possible initial elementary steps of the BOR on gold electrode have been proposed and discussed according to the relevant literature data.
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Candida rugosa lipase was immobilized by covalent binding on hybrid matrix of polysiloxane-polyvinyl alcohol chemically modified with different activating agents as glutaraldehyde, sodium metaperiodate and carbonyldiimidazole. The experimental results suggested that functional activating agents render different interactions between enzyme and support, producing consequently alterations in the optimal reaction conditions. Properties of the immobilized systems were assessed and their performance on hydrolytic and synthetic reactions were evaluated and compared with the free enzyme. In hydrolytic reactions using p-nitrophenyl palmitate as substrate all immobilized systems showed higher thermal stability and optima pH and temperature values in relation to the free lipase. Among the activating compounds, carbonyldiimidazole resulted in a total recovery of activity on the support and the highest thermal stability. For the butyl butyrate synthesis, the best performance (molar conversion of 95% and volumetric productivity of 2.33 g L-1 h(-1)) was attained with the lipase immobilized on POS-PVA activated with sodium metaperiodate. The properties of the support and immobilized derivatives were also evaluated by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopies and chemical composition (FTIR). (c) 2007 Elsevier B.V. All rights reserved.
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Performance of different immobilized lipases in palm oil biodiesel synthesis. Optimized conditions for palm oil and ethanol enzymatic biodiesel synthesis were determined with different immobilized lipases SiO(2)-PVA-immobilized lipase from Pseudomonas fluorescens and acrylic resin-immobilized lipase, Novozym (R) 435, from Candida antartica, in solvent-free medium. A full factorial design assessed the influence of temperature (42 - 58 degrees C) and ethanol: palm oil (6:1 - 18:1) molar ratio on the transesterification yield. Main effects were adjusted by multiple regression analysis to linear models and the maximum transesterification yield was obtained at 42 degrees C and 18:1 ethanol: palm oil molar ratio. Mathematical models featuring total yield for each immobilized lipase were suitable to describe the experimental results.
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This article presents the use of fibers residue from textile industry to minimize environmental problems associated with material accumulation. Composite materials utilizing textile fiber residues and high density polyethylene were prepared. Effect of treatment with hot water on fibers to prepare composites was studied to provide an improvement in mechanical properties of these materials. This treatment on fibers was evaluated by X-ray diffraction and scanning electron microscopy techniques. Experimental results of mechanical properties indicated higher mechanical strength for treated fiber composites compared to the untreated fiber composites.
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Experiments based on a 2(3) central composite full factorial design were carried out in 200-ml stainless-steel containers to study the pretreatment, with dilute sulfuric acid, of a sugarcane bagasse sample obtained from a local sugar-alcohol mill. The independent variables selected for study were temperature, varied from 112.5A degrees C to 157.5A degrees C, residence time, varied from 5.0 to 35.0 min, and sulfuric acid concentration, varied from 0.0% to 3.0% (w/v). Bagasse loading of 15% (w/w) was used in all experiments. Statistical analysis of the experimental results showed that all three independent variables significantly influenced the response variables, namely the bagasse solubilization, efficiency of xylose recovery in the hemicellulosic hydrolysate, efficiency of cellulose enzymatic saccharification, and percentages of cellulose, hemicellulose, and lignin in the pretreated solids. Temperature was the factor that influenced the response variables the most, followed by acid concentration and residence time, in that order. Although harsher pretreatment conditions promoted almost complete removal of the hemicellulosic fraction, the amount of xylose recovered in the hemicellulosic hydrolysate did not exceed 61.8% of the maximum theoretical value. Cellulose enzymatic saccharification was favored by more efficient removal of hemicellulose during the pretreatment. However, detoxification of the hemicellulosic hydrolysate was necessary for better bioconversion of the sugars to ethanol.
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BACKGROUND: The combined effects of vanillin and syringaldehyde on xylitol production by Candida guilliermondii using response surface methodology (RSM) have been studied. A 2(2) full-factorial central composite design was employed for experimental design and analysis of the results. RESULTS: Maximum xylitol productivities (Q(p) = 0.74 g L(-1) h(-1)) and yields (Y(P/S) = 0.81 g g(-1)) can be attained by adding only vanillin at 2.0 g L(-1) to the fermentation medium. These data were closely correlated with the experimental results obtained (0.69 +/- 0.04 g L(-1) h(-1) and 0.77 +/- 0.01 g g(-1)) indicating a good agreement with the predicted value. C. guilliermondii was able to convert vanillin completely after 24 h of fermentation with 94% yield of vanillyl alcohol. CONCLUSIONS: The bioconversion of xylose into xylitol by C. guilliermondii is strongly dependent on the combination of aldehydes and phenolics in the fermentation medium. Vanillin is a source of phenolic compound able to improve xylitol production by yeast. The conversion of vanillin to alcohol vanilyl reveals the potential of this yeast for medium detoxification. (C) 2009 Society of Chemical Industry
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This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.
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In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.