Parametric instability of stochastic columns

Columns which have stochastically distributed Young's modulus and mass density and are subjected to deterministic periodic axial loadings are considered. The general case of a column supported on a Winkler elastic foundation of random stiffness and also on discrete elastic supports which are also random is considered. Material property fluctuations are modeled as independent one-dimensional univariate homogeneous real random fields in space. In addition to autocorrelation functions or their equivalent power spectral density functions, the input random fields are characterized by scale of fluctuations or variance functions for their second order properties. The foundation stiffness coefficient and the stiffnesses of discrete elastic supports are treated to constitute independent random variables. The system equations of boundary frequencies are obtained using Bolotin's method for deterministic systems. Stochastic FEM is used to obtain the discrete system with random as well as periodic coefficients. Statistical properties of boundary frequencies are derived in terms of input parameter statistics. A complete covariance structure is obtained. The equations developed are illustrated using a numerical example employing a practical correlation structure.

Bayesian Learning for Joint Sparse OFDM Channel Estimation and Data Detection

The impulse response of a typical wireless multipath channel can be modeled as a tapped delay line filter whose non-zero components are sparse relative to the channel delay spread. In this paper, a novel method of estimating such sparse multipath fading channels for OFDM systems is explored. In particular, Sparse Bayesian Learning (SBL) techniques are applied to jointly estimate the sparse channel and its second order statistics, and a new Bayesian Cramer-Rao bound is derived for the SBL algorithm. Further, in the context of OFDM channel estimation, an enhancement to the SBL algorithm is proposed, which uses an Expectation Maximization (EM) framework to jointly estimate the sparse channel, unknown data symbols and the second order statistics of the channel. The EM-SBL algorithm is able to recover the support as well as the channel taps more efficiently, and/or using fewer pilot symbols, than the SBL algorithm. To further improve the performance of the EM-SBL, a threshold-based pruning of the estimated second order statistics that are input to the algorithm is proposed, and its mean square error and symbol error rate performance is illustrated through Monte-Carlo simulations. Thus, the algorithms proposed in this paper are capable of obtaining efficient sparse channel estimates even in the presence of a small number of pilots.

Influence of poling methods on the orientational dynamics of 2-methyl-4-nitro-aniline in poly(methyl methacrylate) studied by second harmonic generation

The magnitude and stability of the induced dipolar orientation of 2-methyl-4-nitroaniline (MNA)/poly(methyl methacrylate) (PMMA) guest/host system is investigated. The chromophores are aligned using both the corona discharge and contact electrode poling techniques. The magnitude of order parameter (also an indicator for the second order nonlinear susceptibility) is measured by recording absorbances of the poled (by the two different techniques) and unpoled PMMA films at different concentrations of MNA. Under the same conditions the corona poling technique creates a higher alignment of molecules along the field direction. The time dependence of the second harmonic intensity of the MNA/PMMA film prepared by the two techniques can be described by a Kohlrausch-Williams-Watts stretched exponential. The temperature dependence of the decay time constant is found to generally follow a modified Williams-Landel-Ferry (WLF) or Vogel-Tamann-Fulcher (VTF) equation. The glass transition temperature seems to be the single most important parameter for determining the relaxation time tau(T).

Stability of stochastic Leipholz column with stochastic loading

The Leipholz column which is having the Young modulus and mass per unit length as stochastic processes and also the distributed tangential follower load behaving stochastically is considered. The non self-adjoint differential equation and boundary conditions are considered to have random field coefficients. The standard perturbation method is employed. The non self-adjoint operators are used within the regularity domain. Full covariance structure of the free vibration eigenvalues and critical loads is derived in terms of second order properties of input random fields characterizing the system parameter fluctuations. The mean value of critical load is calculated using the averaged problem and the corresponding eigenvalue statistics are sought. Through the frequency equation a transformation is done to yield load parameter statistics. A numerical study incorporating commonly observed correlation models is reported which illustrates the full potentials of the derived expressions.

First-order hyperpolarizabilities and pKa of weak organic acids in protic solvents are lineraly related

Second-order nonlinearities (beta) of five weak organic acids in protic solvents have been measured by the double-quantum Rayleigh scattering (DRS) technique. beta is found to bear a linear relationship to the pK(a) of these compounds in those solvents. A direct implication of this observation is that the DRS technique can be used to determine the pK(a) of weak organic acids in any solvent.

First-Order Hyperpolarizabilities of Sulfophthalein Dyes

In this paper we report the first hyperpolarizabilities (beta) of 12, sulfophthalein dyes. Since these dyes are ionic in nature, their second-order nonlinearities were measured by the hyper-Rayleigh scattering technique in solution. The measured beta values are large and highly solvent dependent. Inclusion of solvent polarity in ab initio estimates of static second-order polarizability does not fully account for the experimental beta values. Contributions from the dissociated forms of the dye in different solvents seem to play an important role in enhancing beta in these systems.

Vibration and Stability of Fluid Conveying Pipes with Stochastic Parameters

Flexible cantilever pipes conveying fluids with high velocity are analysed for their dynamic response and stability behaviour. The Young's modulus and mass per unit length of the pipe material have a stochastic distribution. The stochastic fields, that model the fluctuations of Young's modulus and mass density are characterized through their respective means, variances and autocorrelation functions or their equivalent power spectral density functions. The stochastic non self-adjoint partial differential equation is solved for the moments of characteristic values, by treating the point fluctuations to be stochastic perturbations. The second-order statistics of vibration frequencies and mode shapes are obtained. The critical flow velocity is-first evaluated using the averaged eigenvalue equation. Through the eigenvalue equation, the statistics of vibration frequencies are transformed to yield critical flow velocity statistics. Expressions for the bounds of eigenvalues are obtained, which in turn yield the corresponding bounds for critical flow velocities.

Clustering Based Large Margin Classification: A Scalable Approach using SOCP Formulation

This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture distributions, where each component of the mixture has a spherical covariance, the second order statistics of the components can be estimated efficiently using clustering algorithms like BIRCH. For each cluster, the second order moments are used to derive a second order cone constraint via a Chebyshev-Cantelli inequality. This constraint ensures that any data point in the cluster is classified correctly with a high probability. This leads to a large margin SOCP formulation whose size depends on the number of clusters rather than the number of training data points. Hence, the proposed formulation scales well for large datasets when compared to the state-of-the-art classifiers, Support Vector Machines (SVMs). Experiments on real world and synthetic datasets show that the proposed algorithm outperforms SVM solvers in terms of training time and achieves similar accuracies.

Robust formulations for clustering-based large-scale classification

Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.

Eigen-profiles of spatio-temporal fragments for adaptive region-based tracking

We propose a novel space-time descriptor for region-based tracking which is very concise and efficient. The regions represented by covariance matrices within a temporal fragment, are used to estimate this space-time descriptor which we call the Eigenprofiles(EP). EP so obtained is used in estimating the Covariance Matrix of features over spatio-temporal fragments. The Second Order Statistics of spatio-temporal fragments form our target model which can be adapted for variations across the video. The model being concise also allows the use of multiple spatially overlapping fragments to represent the target. We demonstrate good tracking results on very challenging datasets, shot under insufficient illumination conditions.

Correspondence between neutron depolarization and higher order magnetic susceptibility to investigate ferromagnetic clusters in phase separated systems

It is a tough task to distinguish a short-range ferromagnetically correlated cluster-glass phase from a canonical spin-glass-like phase in many magnetic oxide systems using conventional magnetometry measurements. As a case study, we investigate the magnetic ground state of La0.85Sr0.15CoO3, which is often debated based on phase separation issues. We report the results of two samples of La0.85Sr0.15CoO3 (S-1 and S-2) prepared under different conditions. Neutron depolarization, higher harmonic ac susceptibility and magnetic relaxation studies were carried out along with conventional magnetometry measurements to differentiate subtle changes at the microscopic level. There is no evidence of ferromagnetic correlation in the sample S-2 attributed to a spin-glass phase, and this is compounded by the lack of existence of a second order component of higher harmonic ac susceptibility and neutron depolarization. A magnetic relaxation experiment at different temperatures complements the spin glass characteristic in S-2. All these signal a sharp variance when we consider the cluster-glass-like phase (phase separated) in S-1, especially when prepared from an improper chemical synthesis process. This shows that the nonlinear ac susceptibility is a viable tool to detect ferromagnetic clusters such as those the neutron depolarization study can reveal.

Structural evolution and second harmonic properties of lithium niobate-tantalate nanocrystals embedded in a borate glass

Nano-crystals of LiNbxTa1 (-) O-x(3) were evolved by subjecting melt-quenched 1.5Li(2)O-2B(2)O(3)-xNb(2)O(5)-(1 - x)Ta2O5 glasses (where x = 0, 0.25, 0.5, 0.75 and 1.00) to a controlled 3-h isothermal heat treatment between 530 and 560 degrees C. Detailed X-ray diffraction and Raman spectral studies confirmed the formation of nano-crystalline LiNbxTa1 (-) O-x(3) along with a minor phase of ferroelectric and non-linear optic Li2B4O7. The sizes of the nanocrystals evolved in the glass were in the range of 19-37 nm for x = 0-0.75 and 23-45 nm for x = 1.00. Electron microscopic studies confirmed a transformation of the morphology of the nano-crystallites from dendritic star-shaped spherulites for x = 0 to rod-shaped structures for x = 1.00 brought about by a coalescence of crystallites. Broad Maker-fringe patterns (recorded at 532 nm) were obtained by subjecting the heat-treated glass plates to 1064 nm fundamental radiation. However, an effective second order non-linear optic coefficient, d(eff), of 0.45 pm/V, which is nearly 1.2 times the d(36) of KDP single crystal, was obtained for a 560 degrees C/3 h heat-treated glass of the representative composition x = 0.50 comprising 37 nm sized crystallites. (C) 2015 Elsevier B.V. All rights reserved.

Structural evolution and second harmonic properties of lithium niobate-tantalate nanocrystals embedded in a borate glass

Nano-crystals of LiNbxTa1 (-) O-x(3) were evolved by subjecting melt-quenched 1.5Li(2)O-2B(2)O(3)-xNb(2)O(5)-(1 - x)Ta2O5 glasses (where x = 0, 0.25, 0.5, 0.75 and 1.00) to a controlled 3-h isothermal heat treatment between 530 and 560 degrees C. Detailed X-ray diffraction and Raman spectral studies confirmed the formation of nano-crystalline LiNbxTa1 (-) O-x(3) along with a minor phase of ferroelectric and non-linear optic Li2B4O7. The sizes of the nanocrystals evolved in the glass were in the range of 19-37 nm for x = 0-0.75 and 23-45 nm for x = 1.00. Electron microscopic studies confirmed a transformation of the morphology of the nano-crystallites from dendritic star-shaped spherulites for x = 0 to rod-shaped structures for x = 1.00 brought about by a coalescence of crystallites. Broad Maker-fringe patterns (recorded at 532 nm) were obtained by subjecting the heat-treated glass plates to 1064 nm fundamental radiation. However, an effective second order non-linear optic coefficient, d(eff), of 0.45 pm/V, which is nearly 1.2 times the d(36) of KDP single crystal, was obtained for a 560 degrees C/3 h heat-treated glass of the representative composition x = 0.50 comprising 37 nm sized crystallites. (C) 2015 Elsevier B.V. All rights reserved.

A New Mechanism For Ferromagnetism In C-60-TDAE

Based on the topology of C-60 and the resulting non-disjoint nature of the lowest unoccupied molecular orbitals, Ne propose a new model for ferromagnetic exchange in C-60-TDAE. Within the Hubbard model, we find that the ferromagnetic exchange integral is stabilized to first order in the inter-ball transfer integral, while the antiferromagnetic coupling is stabilized only to second order. This difference is adequate to counter the larger phase space available for stabilizing the antiferromagnetic state. Thus, the ground state is found to be ferromagnetic for reasonable inter-ball transfer integrals.

Synthesis of some copper(II)-chelating (dialkylamino)pyridine amphiphiles and evaluation of their esterolytic capacities in cationic micellar media

Three new (dialkylamino)pyridine (DAAP)-based ligand amphiphiles 3-5 have been synthesized. All of the compounds possess a metal ion binding subunit in the form of a 2,6-disubstituted DAAP moiety. In addition, at least one ortho-CH2OH substituent is present in all the ligands. Complex formation by these ligands with various metal ions were examined under micellar conditions, but only complexes with Cu(II) ions showed kinetically potent esterolytic capacities under micellar conditions. Complexes with Cu(II) were prepared in host comicellar cetyltrimethylammonium bromide (CTABr) media at pH 7.6. Individual complexes were characterized by UV-visible absorption spectroscopy and electron paramagnetic resonance spectroscopy. These metallomicelles speed the cleavage of the substrates p-nitrophenyl hexanoate or p-nitrophenyl diphenyl phosphate. To ascertain the nature of the active esterolytic species, the stoichiometries of the respective Cu(II) complexes were determined from the kinetic version of Job's plot. In all the instances, 2:1 complex ligand/Cu(II) ion are the most kinetically competent species. The apparent pK(a) values of the Cu(II)-coordinated hydroxyl groups of the ligands 3, 4, and 5, in the comicellar aggregate, are 7.8, 8.0, and 8.0, respectively, as estimated from the rate constant vs pH: profiles of the ester cleavage reactions. The nucleophilic metallomicellar reagents and the second-order "catalytic" rate constants toward esterolysis of the substrate p-nitrophenyl hexanoate (at 25 degrees C, pH 7.6) are 37.5 for 3, 11.4 for 4, and 13.8 for 5. All catalytic systems comprising the coaggregates of 3, 4, or 5 and CTABr demonstrate turnover behavior in the presence of excess substrate.