98 resultados para 169-1035D


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Methyl 7-keto-1,2,3,4,4a,5,6,7-octahydronaphthoate (Va) has been prepared by the reduction of 7-methoxy-1,2,3,4-tetrahydronaphthoic acid (III) with lithium and ammonia followed by hydrolysis of the enol ether, esterification and migration of the double bond. Alkylation of Va has led to the substitution at the expected 8-position. Methyl 4-keto-7-methoxy-1,2,3,4-tetrahydronaphthoate (X), an intermediate in the preparation of III, has been converted into methyl 3-methyl-3-cyano-4-keto-7-methoxy-1,2,3,4-tetrahydronaphthoate (XIII).

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Mass transfer coefficients have been determined for transfer into a highly viscous phase in a stirred tank involving high Schmidt numbers. The results have been used to compute mass transfer coefficients in the extraction of free fatty acids from oils using alcohol and show good agreement with experimental results

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Charge-order driven magnetic ferroelectricity is shown to occur in several rare earth manganates of the general formula, Ln(1-x)A(x)MnO(3) (In = rare earth, A = alkaline earth). Charge-ordered manganates exhibit dielectric constant anomalies around the charge-ordering or the antiferromagnetic transition temperature. Magnetic fields have a marked effect on the dielectric properties of these compounds, indicating the presence of coupling between the magnetic and electrical order parameters. Magneto-dielectric properties are retained in small particles of the manganates. The observation of magneto-ferroelectricity in these manganates is in accordance with theoretical predictions.

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Charge-order driven magnetic ferroelectricity is shown to occur in several rare earth manganates of the general formula, Ln(1-x)A(x)MnO(3) (In = rare earth, A = alkaline earth). Charge-ordered manganates exhibit dielectric constant anomalies around the charge-ordering or the antiferromagnetic transition temperature. Magnetic fields have a marked effect on the dielectric properties of these compounds, indicating the presence of coupling between the magnetic and electrical order parameters. Magneto-dielectric properties are retained in small particles of the manganates. The observation of magneto-ferroelectricity in these manganates is in accordance with theoretical predictions.

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The radial current density on an MPD arcjet cathode surface is theoretically investigated for five propellants. It is found that excessive current concentration at the upstream end of the cathode occurs in the case of hydrogen. This undesirable effect is traced to the higher electrical conductivity of hydrogen plasma.

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Nanocrystalline Fe powders were synthesized by transmetallation reaction and embedded in silica to form Fe-SiO2 nanocomposite. Thermomagnetic study of the as-prepared Fe sample indicates the presence of Fe3O4 and Fe particles. Oxidation studies of Fe and Fe-SiO2 show an increased thermal stability of Fe-SiO2 nanocomposite over pure Fe. The Fe-SiO2 shows an enhanced oxidation temperature (i.e., 780 K) and a maximum saturation magnetization value of (135 emu/g) with 64 wt.% of Fe content in silica. Electrical and dielectric behaviour of the Fe-SiO2 nanocomposite has been investigated as a function of temperature and frequency. Low frequency ac conductivity and dielectric constants were found to be influenced by desorptions of chemisorbed moisture. High saturation magnetization, thermal stability, frequency-dependent conductivity and low power loss make Fe-silica a promising material for high frequency applications. (C) 2010 Elsevier B.V. All rights reserved.

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Two tripeptides of the type Boc-Pro-ΔZX-Gly-NHEt (where X = Leu, Phe) have been synthesized and their solution conformations investigated by 270 MHz 1H n.m.r. and i.r. spectroscopy. These conformational studies indicated that ΔZLeu, similar to ΔZPhe, has a strong tendency to stabilize folded Type II β-turn conformations when present at i + 2 position.

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Polymer nanocomposites containing different concentrations of Au nanoparticles have been investigated by small angle X-ray scattering and electronic absorption spectroscopy. The variation in the surface plasmon resonance (SPR) band of Au nanoparticles with concentration is described by a scaling law. The variation in the plasmon band of ReO3 nanoparticles embedded in polymers also follows a similar scaling law. Sistance dependence of plasmon coupling in polymer composites f metal nanoparticles. (C) 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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In many problems of decision making under uncertainty the system has to acquire knowledge of its environment and learn the optimal decision through its experience. Such problems may also involve the system having to arrive at the globally optimal decision, when at each instant only a subset of the entire set of possible alternatives is available. These problems can be successfully modelled and analysed by learning automata. In this paper an estimator learning algorithm, which maintains estimates of the reward characteristics of the random environment, is presented for an automaton with changing number of actions. A learning automaton using the new scheme is shown to be e-optimal. The simulation results demonstrate the fast convergence properties of the new algorithm. The results of this study can be extended to the design of other types of estimator algorithms with good convergence properties.

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The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

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We study the Segal-Bargmann transform on M(2). The range of this transform is characterized as a weighted Bergman space. In a similar fashion Poisson integrals are investigated. Using a Gutzmer's type formula we characterize the range as a class of functions extending holomorphically to an appropriate domain in the complexification of M(2). We also prove a Paley-Wiener theorem for the inverse Fourier transform.

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The crystal structures of two ternary metal nucleotide complexes of cobalt, [Co(en)2(H2O)2]-[Co(5?-IMP)2(H2O)4]Cl2·4H2O (1) and [Co(en)2(H2O)2][Co(5?-GMP)2(H2O)4]Cl2·4H2O (2), have been analysed by X-ray diffraction (en = ethylenediamine, 5?-IMP = inosine 5?-monophosphate, and 5?-GMP = guanosine 5?-monophosphate). Both complexes crystallize in the orthorhombic space group C2221 with a= 8.725(1), b= 25.891(5), c= 21.212(5)Å, Z= 4 for (1) and a= 8.733(2), b= 26.169(4), c= 21.288(4)Å, Z= 4 for (2). The structure of (1) was solved by the heavy-atom method, while that of (2) was deduced from (1). The structures were refined to R values of 0.09 and 0.10 for 1 546 and 1 572 reflections for (1) and (2) respectively. The two structures are isomorphous. A novel feature is that the chelate ligand en and the nucleotide are not co-ordinated to the same metal ion. One of the metal ions lying on the two-fold a axis is octahedrally co-ordinated by two chelating en molecules and two water oxygens, while the other on the two-fold b axis is octahedrally co-ordinated by two N(7) atoms of symmetry-related nucleotides in a cis position and four water oxygens. The conformations of the nucleotides are C(2?)-endo, anti, and gauche�gauche. In both (1) and (2) the charge-neutralising chloride ions are disordered in the vacant space between the molecules. These structures bear similarities to the mode of nucleotide co-ordination to PtII complexes of 6-oxopurine nucleotides, which are the proposed models for intrastrand cross-linking in DNA by a metal complex.

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A real or a complex symmetric matrix is defined here as an equivalent symmetric matrix for a real nonsymmetric matrix if both have the same eigenvalues. An equivalent symmetric matrix is useful in computing the eigenvalues of a real nonsymmetric matrix. A procedure to compute equivalent symmetric matrices and its mathematical foundation are presented.

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Thiourea (CS(NH2)2) is one of the few examples of molecular crystals exhibiting ferroelectric properties. The dielectric constant along the ferroelectric axis [100] shows maxima at 169, 177 and 202 K. An inflection point occurs at 170.5 KZ Following Goldsmith and White the phases are named as I (F.E. below 169 K), II (A.F.E. 169 K

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The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.