66 resultados para Basis functions

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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A correlated many-body basis function is used to describe the (4)He trimer and small helium clusters ((4)HeN) with N = 4-9. A realistic helium dimer potential is adopted. The ground state results of the (4)He dimer and trimer are in close agreement with earlier findings. But no evidence is found for the existence of Efimov state in the trimer for the actual (4)He-(4)He interaction. However, decreasing the potential strength we calculate several excited states of the trimer which exhibit Efimov character. We also solve for excited state energies of these clusters which are in good agreement with Monte Carlo hyperspherical description. (C) 2011 American Institute of Physics. [doi:10.1063/1.3583365]

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A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

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The n→π* absorption transition of formaldehyde in water is analyzed using combined and sequential classical Monte Carlo (MC) simulations and quantum mechanics (QM) calculations. MC simulations generate the liquid solute-solvent structures for subsequent QM calculations. Using time-dependent density functional theory in a localized set of gaussian basis functions (TD-DFT/6-311++G(d,p)) calculations are made on statistically relevant configurations to obtain the average solvatochromic shift. All results presented here use the electrostatic embedding of the solvent. The statistically converged average result obtained of 2300 cm-1 is compared to previous theoretical results available. Analysis is made of the effective dipole moment of the hydrogen-bonded shell and how it could be held responsible for the polarization of the solvent molecules in the outer solvation shells.

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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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We consider incompressible Stokes flow with an internal interface at which the pressure is discontinuous, as happens for example in problems involving surface tension. We assume that the mesh does not follow the interface, which makes classical interpolation spaces to yield suboptimal convergence rates (typically, the interpolation error in the L(2)(Omega)-norm is of order h(1/2)). We propose a modification of the P(1)-conforming space that accommodates discontinuities at the interface without introducing additional degrees of freedom or modifying the sparsity pattern of the linear system. The unknowns are the pressure values at the vertices of the mesh and the basis functions are computed locally at each element, so that the implementation of the proposed space into existing codes is straightforward. With this modification, numerical tests show that the interpolation order improves to O(h(3/2)). The new pressure space is implemented for the stable P(1)(+)/P(1) mini-element discretization, and for the stabilized equal-order P(1)/P(1) discretization. Assessment is carried out for Poiseuille flow with a forcing surface and for a static bubble. In all cases the proposed pressure space leads to improved convergence orders and to more accurate results than the standard P(1) space. In addition, two Navier-Stokes simulations with moving interfaces (Rayleigh-Taylor instability and merging bubbles) are reported to show that the proposed space is robust enough to carry out realistic simulations. (c) 2009 Elsevier B.V. All rights reserved.

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We study the reconstruction of visual stimuli from spike trains, representing the reconstructed stimulus by a Volterra series up to second order. We illustrate this procedure in a prominent example of spiking neurons, recording simultaneously from the two H1 neurons located in the lobula plate of the fly Chrysomya megacephala. The fly views two types of stimuli, corresponding to rotational and translational displacements. Second-order reconstructions require the manipulation of potentially very large matrices, which obstructs the use of this approach when there are many neurons. We avoid the computation and inversion of these matrices using a convenient set of basis functions to expand our variables in. This requires approximating the spike train four-point functions by combinations of two-point functions similar to relations, which would be true for gaussian stochastic processes. In our test case, this approximation does not reduce the quality of the reconstruction. The overall contribution to stimulus reconstruction of the second-order kernels, measured by the mean squared error, is only about 5% of the first-order contribution. Yet at specific stimulus-dependent instants, the addition of second-order kernels represents up to 100% improvement, but only for rotational stimuli. We present a perturbative scheme to facilitate the application of our method to weakly correlated neurons.

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The diazocarbene radical, CNN, and the ions CNN(+) and CNN(-) were investigated at a high level of theory. Very accurate structural parameters for the states X(3)Sigma(-) and A(3)Pi of CNN, and X(2)Pi of both CNN(+) and CNN(-) were obtained with the UCCSD(T) method using correlated-consistent basis functions with extrapolations to the complete basis set limit, with valence only and also with all electrons correlated. Harmonic and anharmonic frequencies were obtained for all species and the Renner parameter and average frequencies evaluated for the Pi states. At the UCCSD(T)/CBS(T-5) level of theory, Delta(f)H(0 K) = 138.89 kcal/mol and Delta(f)H(298 K) = 139.65 kcal/mol were obtained for diazocarbene; for the ionization potential and the electron affinity of CNN, 10.969 eV (252.95 kcal/mol), and 1.743 eV (40.19 kcal/mol), respectively, are predicted. Geometry optimization was also carried out with the CASSCF/MRCI/CBS(T-5) approach for the states X(3)Sigma(-) A(3)Pi, and a(1)Delta of CNN, and with the CASSCF/MRSDCI/aug-cc-pVTZ approach for the states b(1)Sigma(+), c(1)Pi, d(1)Sigma(-), and B(3)Sigma(-), and excitation energies (T(e)) evaluated. Vertical energies were calculated for 15 electronic states, thus improving on the accuracy of the five transitions already described, and allowing for a reliable overview of a manifold of other states, which is expected to guide future spectroscopic experiments. This study corroborates the experimental assignment for the vertical transition X (3)Sigma(-) <- E (3)Pi.

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Background: Thyroid receptors, TRa and TR beta, are involved in important physiological functions such as metabolism, cholesterol level and heart activities. Whereas metabolism increase and cholesterol level lowering could be achieved by TR beta isoform activation, TRa activation affects heart rates. Therefore, beta-selective thyromimetics have been developed as promising drug-candidates for treatment of obesity and elevated cholesterol level. GC-1 [ 3,5-dimethyl-4-(4'-hydroxy- 3'-isopropylbenzyl)-phenoxy acetic acid] has ability to lower LDL cholesterol with 600-to 1400-fold more potency and approximately two-to threefold more efficacy than atorvastatin (Lipitor(C)) in studies in rats, mice and monkeys. Results: To investigate GC-1 specificity, we solved crystal structures and performed molecular dynamics simulations of both isoforms complexed with GC-1. Crystal structures reveal that, in TRa Arg228 is observed in multiple conformations, an effect triggered by the differences in the interactions between GC-1 and Ser277 or the corresponding asparagine (Asn331) of TR beta. The corresponding Arg282 of TR beta is observed in only one single stable conformation, interacting effectively with the ligand. Molecular dynamics support this model: our simulations show that the multiple conformations can be observed for the Arg228 in TR alpha, in which the ligand interacts either strongly with the ligand or with the Ser277 residue. In contrast, a single stable Arg282 conformation is observed for TR beta, in which it strongly interacts with both GC-1 and the Asn331. Conclusion: Our analysis suggests that the key factors for GC-1 selectivity are the presence of an oxyacetic acid ester oxygen and the absence of the amino group relative to T(3). These results shed light into the beta-selectivity of GC-1 and may assist the development of new compounds with potential as drug candidates to the treatment of hypercholesterolemia and obesity.

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We continue the investigation of the algebraic and topological structure of the algebra of Colombeau generalized functions with the aim of building up the algebraic basis for the theory of these functions. This was started in a previous work of Aragona and Juriaans, where the algebraic and topological structure of the Colombeau generalized numbers were studied. Here, among other important things, we determine completely the minimal primes of (K) over bar and introduce several invariants of the ideals of 9(Q). The main tools we use are the algebraic results obtained by Aragona and Juriaans and the theory of differential calculus on generalized manifolds developed by Aragona and co-workers. The main achievement of the differential calculus is that all classical objects, such as distributions, become Cl-functions. Our purpose is to build an independent and intrinsic theory for Colombeau generalized functions and place them in a wider context.

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New basis sets of the atomic natural orbital (ANO) type have been developed for the lanthanide atoms La-Lu. The ANOs have been obtained from the average density matrix of the ground and lowest excited states of the atom, the positive ions, and the atom in an electric field. Scalar relativistic effects are included through the use of a Douglas-Kroll-Hess Hamiltonian. Multiconfigurational wave functions have been used with dynamic correlation included using second-order perturbation theory (CASSCF/CASPT2). The basis sets are applied in calculations of ionization energies and some excitation energies. Computed ionization energies have an accuracy better than 0.1 eV in most cases. Two molecular applications are inluded as illustration: the cerium diatom and the LuF3 molecule. In both cases it is shown that 4f orbitals are not involved in the chemical bond in contrast to an earlier claim for the latter molecule.

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Methylmercury is a known neurotoxic organometal which affects visual functions and few studies concerns to wild fish are available. The autometallography mercury distribution in the retina of Danio rerio was mapped using light and electron microscopy. Abundant mercury deposits were found in the photoreceptor layer (outer and inner segments of the photoreceptors) and in the inner and outer nuclear layers. Occasionally, the presence of mercury deposits in plexiform layers was observed and very rarely in the ganglion cell layer. Also the occurrence of mercury deposits in cells from the disc region was observed, but not in the nerve fiber layer. An interesting difference was found between mercury accumulation in the central and peripheral regions of the retina. These results demonstrate that mercury after trophic exposure to Danio rerio is able to cross the blood-retina barrier and accumulate in the cells of the retina even under subchronic exposure. (C) 2010 Elsevier Inc. All rights reserved.

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An important approach to cancer therapy is the design of small molecule modulators that interfere with microtubule dynamics through their specific binding to the ²-subunit of tubulin. In the present work, comparative molecular field analysis (CoMFA) studies were conducted on a series of discodermolide analogs with antimitotic properties. Significant correlation coefficients were obtained (CoMFA(i), q² =0.68, r²=0.94; CoMFA(ii), q² = 0.63, r²= 0.91), indicating the good internal and external consistency of the models generated using two independent structural alignment strategies. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the 3D contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of discodermolide analogs, and should be useful for the design of new specific ²-tubulin modulators with potent anticancer activity.

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Reproductive failures are still common grounds for complaint by commercial swine producers. Porcine parvovirus (PPV) is associated with different clinical reproductive signs. The aim of the present study was to investigate PPV fetal infection at swine farms having ongoing reproductive performance problems. The presence of virus in fetal tissues was determined by nested-polymerase chain reaction assay directed to the conserved NS1 gene of PPV in aborted fetuses, mummies and stillborns. Fetuses show a high frequency of PPV infection (96.4%; N = 28). In 60.7% of the fetuses, PPV were detected in all tissue samples (lung, heart, thymus, kidney, and spleen). Viral infection differed among fetal tissues, with a higher frequency in the lung and heart (P < 0.05). Fetuses with up to 99 days of gestational age and from younger sows showed a higher frequency of PPV (P < 0.05). No significant difference in the presence of PPV was detected among the three clinical presentations. The results suggest that PPV remains an important pathogenic agent associated with porcine fetal death.

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We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

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This study aimed to investigate the immunological mechanisms involved in the gender distinct incidence of paracoccidioidomycosis (pcm), an endemic systemic mycosis in Latin America, which is at least 10 times more frequent in men than in women. Then, we compared the immune response of male and female mice to Paracoccidioides brasiliensis infection, as well as the influence in the gender differences exerted by paracoccin, a P. brasiliensis component with carbohydrate recognition property. High production of Th1 cytokines and T-bet expression have been detected in the paracoccin stimulated cultures of spleen cells from infected female mice. In contrast, in similar experimental conditions, cells from infected males produced higher levels of the Th2 cytokines and expressed GATA-3. Macrophages from male and female mice when stimulated with paracoccin displayed similar phagocytic capability, while fungicidal activity was two times more efficiently performed by macrophages from female mice, a fact that was associated with 50% higher levels of nitric oxide production. In order to evaluate the role of sexual hormones in the observed gender distinction, we have utilized mice that have been submitted to gonadectomy followed by inverse hormonal reconstitution. Spleen cells derived from castrated males reconstituted with estradiol have produced higher levels of IFN-gamma (1291+/-15 pg/mL) and lower levels of IL-10 (494+/-38 pg/mL), than normal male in response to paracoccin stimulus. In contrast, spleen cells from castrated female mice that had been treated with testosterone produced more IL-10 (1284+/-36 pg/mL) and less IFN-gamma (587614 pg/mL) than cells from normal female. In conclusion, our results reveal that the sexual hormones had a profound effect on the biology of immune cells, and estradiol favours protective responses to P. brasiliensis infection. In addition, fungal components, such as paracoccin, may provide additional support to the gender dimorphic immunity that marks P. brasiliensis infection.