Matrix crack detection in spatially random composite structures using fractal dimension

Fractal dimension based damage detection method is studied for a composite structure with random material properties. A composite plate with localized matrix crack is considered. Matrix cracks are often seen as the initial damage mechanism in composites. Fractal dimension based method is applied to the static deformation curve of the structure to detect localized damage. Static deflection of a cantilevered composite plate under uniform loading is calculated using the finite element method. Composite material shows spatially varying random material properties because of complex manufacturing processes. Spatial variation of material property is represented as a two dimensional homogeneous Gaussian random field. Karhunen-Loeve (KL) expansion is used to generate a random field. The robustness of fractal dimension based damage detection methods is studied considering the composite plate with spatial variation in material properties.

Belief propagation for minimum weight many-to-one matchings in the random complete graph

In a complete bipartite graph with vertex sets of cardinalities n and n', assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as n -> infinity, with n' = n/alpha] for any fixed alpha > 1, the minimum weight of many-to-one matchings converges to a constant (depending on alpha). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.

Thermoelectric properties of Pb0.75-xMnxSn0.25Te alloys with variable manganese content

Lead tin telluride is one of the well-established thermoelectric materials in the temperature range 350-750 K. In the present study, Pb0.75-xMnxSn0.25Te1.00 alloys with variable manganese (Mn) content were prepared by solid state synthesis and the thermoelectric properties were studied. X-ray diffraction, (XRD) showed that the samples followed Vegard's law, indicating solid solution formation and substitution of Mn at the Pb site. Scanning Electron Microscopy (SEM) showed that the grain sizes varied from <1 mu m to more than 10 mu m and MnTe rich phase was present for higher Mn content. Seebeck coefficient, electrical resistivity and thermal conductivity were measured from room temperature to 720 K. At 300 K, large Seebeck values were obtained, possibly due to increased effective mass on Mn substitution and low carrier concentration of the samples. At higher temperatures, transition from n-type to p-type indicated the presence of thermally generated carriers. Temperature dependent electrical resistivity showed the transition from degenerate to non-degenerate behavior. For thermal conductivity, low values (similar to 1 W/m-K at 300 K) were obtained. At higher temperatures bipolar conduction was observed, in agreement with the Seebeck and resistivity data. Due to low power factor, the maximum thermoelectric figure of merit (zT) was limited to 0.23 at 329 K for the sample with lowest Mn content (x=0.03). (C) 2015 Elsevier Ltd. All rights reserved.

Specificity of the ModA11, ModA12 and ModD1 epigenetic regulator N-6-adenine DNA methyltransferases of Neisseria meningitidis

Phase variation (random ON/OFF switching) of gene expression is a common feature of host-adapted pathogenic bacteria. Phase variably expressed N-6-adenine DNA methyltransferases (Mod) alter global methylation patterns resulting in changes in gene expression. These systems constitute phase variable regulons called phasevarions. Neisseria meningitidis phasevarions regulate genes including virulence factors and vaccine candidates, and alter phenotypes including antibiotic resistance. The target site recognized by these Type III N-6-adenine DNA methyltransferases is not known. Single molecule, real-time (SMRT) methylome analysis was used to identify the recognition site for three key N. meningitidis methyltransferases: ModA11 (exemplified by M.NmeMC58I) (5'-CGY(m6)AG-3'), ModA12 (exemplified by M.Nme77I, M.Nme18I and M.Nme579II) (5'-AC(m6)ACC-3') and ModD1 (exemplified by M.Nme579I) (5'-CC(m6)AGC-3'). Restriction inhibition assays and mutagenesis confirmed the SMRT methylome analysis. The ModA11 site is complex and atypical and is dependent on the type of pyrimidine at the central position, in combination with the bases flanking the core recognition sequence 5'-CGY(m6)AG-3'. The observed efficiency of methylation in the modA11 strain (MC58) genome ranged from 4.6% at 5'-GCGC(m6)AGG-3' sites, to 100% at 5'-ACGT(m6)AGG-3' sites. Analysis of the distribution of modified sites in the respective genomes shows many cases of association with intergenic regions of genes with altered expression due to phasevarion switching.

Novel anti IGFBP2 single chain variable fragment inhibits glioma cell migration and invasion

Insulin like growth factor binding protein 2 (IGFBP2) is highly up regulated in glioblastoma (GBM) tissues and has been one of the prognostic indicators. There are compelling evidences suggesting important roles for IGFBP2 in glioma cell proliferation, migration and invasion. Extracellular IGFBP2 through its carboxy terminal arginine glycine aspartate (RGD) motif can bind to cell surface alpha 5 beta 1 integrins and activate pathways downstream to integrin signaling. This IGFBP2 activated integrin signaling is known to play a crucial role in IGFBP2 mediated invasion of glioma cells. Hence a molecular inhibitor of carboxy terminal domain of IGFBP2 which can inhibit IGFBP2-cell surface interaction is of great therapeutic importance. In an attempt to develop molecular inhibitors of IGFBP2, we screened single chain variable fragment (scFv) phage display libraries, Tomlinson I (Library size 1.47 x 10(8)) and Tomlinson J (Library size 1.37 x 10(8)) using human recombinant IGFBP2. After screening we obtained three IGFBP2 specific binders out of which one scFv B7J showed better binding to IGFBP2 at its carboxy terminal domain, blocked IGFBP2-cell surface association, reduced activity of matrix metalloprotease 2 in the conditioned medium of glioma cells and inhibited IGFBP2 induced migration and invasion of glioma cells. We demonstrate for the first time that in vitro inhibition of extracellular IGFBP2 activity by using human scFv results in significant reduction of glioma cell migration and invasion. Therefore, the inhibition of IGFBP2 can serve as a potential therapeutic strategy in the management of GBM.

Identification of dominant modes in random dynamical and aeroelastic systems

Identification of dominant modes is an important step in studying linearly vibrating systems, including flow-induced vibrations. In the presence of uncertainty, when some of the system parameters and the external excitation are modeled as random quantities, this step becomes more difficult. This work is aimed at giving a systematic treatment to this end. The ability to capture the time averaged kinetic energy is chosen as the primary criterion for selection of modes. Accordingly, a methodology is proposed based on the overlap of probability density functions (pdf) of the natural and excitation frequencies, proximity of the natural frequencies of the mean or baseline system, modal participation factor, and stochastic variation of mode shapes in terms of the modes of the baseline system - termed here as statistical modal overlapping. The probabilistic descriptors of the natural frequencies and mode shapes are found by solving a random eigenvalue problem. Three distinct vibration scenarios are considered: (i) undamped arid damped free vibrations of a bladed disk assembly, (ii) forced vibration of a building, and (iii) flutter of a bridge model. Through numerical studies, it is observed that the proposed methodology gives an accurate selection of modes. (C) 2015 Elsevier Ltd. All rights reserved.

Turbulent states and their transitions in mathematical models for ventricular tissue: The effects of random interstitial fibroblasts

We study the dynamical behaviors of two types of spiral-and scroll-wave turbulence states, respectively, in two-dimensional (2D) and three-dimensional (3D) mathematical models, of human, ventricular, myocyte cells that are attached to randomly distributed interstitial fibroblasts; these turbulence states are promoted by (a) the steep slope of the action-potential-duration-restitution (APDR) plot or (b) early afterdepolarizations (EADs). Our single-cell study shows that (1) the myocyte-fibroblast (MF) coupling G(j) and (2) the number N-f of fibroblasts in an MF unit lower the steepness of the APDR slope and eliminate the EAD behaviors of myocytes; we explore the pacing dependence of such EAD suppression. In our 2D simulations, we observe that a spiral-turbulence (ST) state evolves into a state with a single, rotating spiral (RS) if either (a) G(j) is large or (b) the maximum possible number of fibroblasts per myocyte N-f(max) is large. We also observe that the minimum value of G(j), for the transition from the ST to the RS state, decreases as N-f(max) increases. We find that, for the steep-APDR-induced ST state, once the MF coupling suppresses ST, the rotation period of a spiral in the RS state increases as (1) G(j) increases, with fixed N-f(max), and (2) N-f(max) increases, with fixed G(j). We obtain the boundary between ST and RS stability regions in the N-f(max)-G(j) plane. In particular, for low values of N-f(max), the value of G(j), at the ST-RS boundary, depends on the realization of the randomly distributed fibroblasts; this dependence decreases as N-f(max) increases. Our 3D studies show a similar transition from scroll-wave turbulence to a single, rotating, scroll-wave state because of the MF coupling. We examine the experimental implications of our study and propose that the suppression (a) of the steep slope of the APDR or (b) EADs can eliminate spiral-and scroll-wave turbulence in heterogeneous cardiac tissue, which has randomly distributed fibroblasts.

Optimal input cross-power spectra in shake table testing of asymmetric structures

The study considers earthquake shake table testing of bending-torsion coupled structures under multi-component stationary random earthquake excitations. An experimental procedure to arrive at the optimal excitation cross-power spectral density (psd) functions which maximize/minimize the steady state variance of a chosen response variable is proposed. These optimal functions are shown to be derivable in terms of a set of system frequency response functions which could be measured experimentally without necessitating an idealized mathematical model to be postulated for the structure under study. The relationship between these optimized cross-psd functions to the most favourable/least favourable angle of incidence of seismic waves on the structure is noted. The optimal functions are also shown to be system dependent, mathematically the sharpest, and correspond to neither fully correlated motions nor independent motions. The proposed experimental procedure is demonstrated through shake table studies on two laboratory scale building frame models.

Determinantal point processes in the plane from products of random matrices

We show that the density of eigenvalues for three classes of random matrix ensembles is determinantal. First we derive the density of eigenvalues of product of k independent n x n matrices with i.i.d. complex Gaussian entries with a few of matrices being inverted. In second example we calculate the same for (compatible) product of rectangular matrices with i.i.d. Gaussian entries and in last example we calculate for product of independent truncated unitary random matrices. We derive exact expressions for limiting expected empirical spectral distributions of above mentioned ensembles.

SPEECH ENHANCEMENT USING DISCRIMINATIVE RANDOM FIELDS

Speech enhancement in stationary noise is addressed using the ideal channel selection framework. In order to estimate the binary mask, we propose to classify each time-frequency (T-F) bin of the noisy signal as speech or noise using Discriminative Random Fields (DRF). The DRF function contains two terms - an enhancement function and a smoothing term. On each T-F bin, we propose to use an enhancement function based on likelihood ratio test for speech presence, while Ising model is used as smoothing function for spectro-temporal continuity in the estimated binary mask. The effect of the smoothing function over successive iterations is found to reduce musical noise as opposed to using only enhancement function. The binary mask is inferred from the noisy signal using Iterated Conditional Modes (ICM) algorithm. Sentences from NOIZEUS corpus are evaluated from 0 dB to 15 dB Signal to Noise Ratio (SNR) in 4 kinds of additive noise settings: additive white Gaussian noise, car noise, street noise and pink noise. The reconstructed speech using the proposed technique is evaluated in terms of average segmental SNR, Perceptual Evaluation of Speech Quality (PESQ) and Mean opinion Score (MOS).

Autoregressive cascades on random networks

A network cascade model that captures many real-life correlated node failures in large networks via load redistribution is studied. The considered model is well suited for networks where physical quantities are transmitted, e.g., studying large scale outages in electrical power grids, gridlocks in road networks, and connectivity breakdown in communication networks, etc. For this model, a phase transition is established, i.e., existence of critical thresholds above or below which a small number of node failures lead to a global cascade of network failures or not. Theoretical bounds are obtained for the phase transition on the critical capacity parameter that determines the threshold above and below which cascade appears or disappears, respectively, that are shown to closely follow numerical simulation results. (C) 2015 Elsevier B.V. All rights reserved.

Autoregressive cascades on random networks

A network cascade model that captures many real-life correlated node failures in large networks via load redistribution is studied. The considered model is well suited for networks where physical quantities are transmitted, e.g., studying large scale outages in electrical power grids, gridlocks in road networks, and connectivity breakdown in communication networks, etc. For this model, a phase transition is established, i.e., existence of critical thresholds above or below which a small number of node failures lead to a global cascade of network failures or not. Theoretical bounds are obtained for the phase transition on the critical capacity parameter that determines the threshold above and below which cascade appears or disappears, respectively, that are shown to closely follow numerical simulation results. (C) 2015 Elsevier B.V. All rights reserved.

A strategy to achieve enhanced electromagnetic interference shielding at ultra-low concentration of multiwall carbon nanotubes in P alpha MSAN/PMMA blends in the presence of a random copolymer PS-r-PMMA

A unique strategy was adopted to achieve an ultra-low electrical percolation threshold of multiwall carbon nanotubes (MWNTs) (0.25 wt%) in a classical partially miscible blend of poly-alpha-methylstyrene-co-acrylonitrile and poly(methyl methacrylate) (P alpha MSAN/PMMA), with a lower critical solution temperature. The polymer blend nanocomposite was prepared by standard melt-mixing followed by annealing above the phase separation temperature. In a two-step mixing protocol, MWNTs were initially melt-mixed with a random PS-r-PMMA copolymer and subsequently diluted with 85/15 P alpha MSAN/PMMA blends in the next mixing step. Mediated by the PS-r-PMMA, the MWNTs were mostly localized at the interface and bridged the PMMA droplets. This strategy led to enhanced electromagnetic interference (EMI) shielding effectiveness at 0.25 wt% MWNTs through multiple scattering from MWNT-covered droplets, as compared to the blends without the copolymer, which were transparent to electromagnetic radiation.