Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix.

Polymer-Derived In-Situ Metal Matrix Composites Created by Direct Injection of a Liquid Polymer into Molten Magnesium

We show that a liquid organic precursor can be injected directly into molten magnesium to produce nanoscale ceramic dispersions within the melt. The castings made in this way possess good resistance to tensile deformation at 673 K (400 degrees C), confirming the non-coarsening nature of these dispersions. Direct liquid injection into molten metals is a significant step toward inserting different chemistries of liquid precursors to generate a variety of polymer-derived metal matrix composites. (C) The Minerals, Metals & Materials Society and ASM International 2013

Connectivity analysis of multichannel EEG signals using recurrence based phase synchronization technique

Real world biological systems such as the human brain are inherently nonlinear and difficult to model. However, most of the previous studies have either employed linear models or parametric nonlinear models for investigating brain function. In this paper, a novel application of a nonlinear measure of phase synchronization based on recurrences, correlation between probabilities of recurrence (CPR), to study connectivity in the brain has been proposed. Being non-parametric, this method makes very few assumptions, making it suitable for investigating brain function in a data-driven way. CPR's utility with application to multichannel electroencephalographic (EEG) signals has been demonstrated. Brain connectivity obtained using thresholded CPR matrix of multichannel EEG signals showed clear differences in the number and pattern of connections in brain connectivity between (a) epileptic seizure and pre-seizure and (b) eyes open and eyes closed states. Corresponding brain headmaps provide meaningful insights about synchronization in the brain in those states. K-means clustering of connectivity parameters of CPR and linear correlation obtained from global epileptic seizure and pre-seizure showed significantly larger cluster centroid distances for CPR as opposed to linear correlation, thereby demonstrating the superior ability of CPR for discriminating seizure from pre-seizure. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. (C) 2013 Elsevier Ltd. All rights reserved.

Calibration Curve with Improved Limit of Detection for Cadmium in Soil: An Approach to Minimize the Matrix Effect in Laser-Induced Breakdown Spectroscopic Analysis

The present article describes a working or combined calibration curve in laser-induced breakdown spectroscopic analysis, which is the cumulative result of the calibration curves obtained from neutral and singly ionized atomic emission spectral lines. This working calibration curve reduces the effect of change in matrix between different zone soils and certified soil samples because it includes both the species' (neutral and singly ionized) concentration of the element of interest. The limit of detection using a working calibration curve is found better as compared to its constituent calibration curves (i.e., individual calibration curves). The quantitative results obtained using the working calibration curve is in better agreement with the result of inductively coupled plasma-atomic emission spectroscopy as compared to the result obtained using its constituent calibration curves.

Correlation between local structural dynamics of proteins inferred from NMR ensembles and evolutionary dynamics of homologues of known structure

Conformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and beta-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues.

Correlation between thermodynamic anomalies and pathways of ice nucleation in supercooled water

The well-known classical nucleation theory (CNT) for the free energy barrier towards formation of a nucleus of critical size of the new stable phase within the parent metastable phase fails to take into account the influence of other metastable phases having density/order intermediate between the parent metastable phase and the final stable phase. This lacuna can be more serious than capillary approximation or spherical shape assumption made in CNT. This issue is particularly significant in ice nucleation because liquid water shows rich phase diagram consisting of two (high and low density) liquid phases in supercooled state. The explanations of thermodynamic and dynamic anomalies of supercooled water often invoke the possible influence of a liquid-liquid transition between two metastable liquid phases. To investigate both the role of thermodynamic anomalies and presence of distinct metastable liquid phases in supercooled water on ice nucleation, we employ density functional theoretical approach to find nucleation free energy barrier in different regions of phase diagram. The theory makes a number of striking predictions, such as a dramatic lowering of nucleation barrier due to presence of a metastable intermediate phase and crossover in the dependence of free energy barrier on temperature near liquid-liquid critical point. These predictions can be tested by computer simulations as well as by controlled experiments. (C) 2014 AIP Publishing LLC.

Energy funneling and macromolecular conformational dynamics: a 2D Raman correlation study of PEG melting

Cascading energy landscapes through funneling has been postulated as a mechanistic route for achieving the lowest energy configuration of a macromolecular system (such as proteins and polymers). In particular, understanding the molecular mechanism for the melting and crystallization of polymers is a challenging fundamental question. The structural modifications that lead to the melting of poly(ethylene glycol) (PEG) are investigated here. Specific Raman bands corresponding to different configurations of the PEG chain have been identified, and the molecular structural dynamics of PEG melting have been addressed using a combination of Raman spectroscopy, 2D Raman correlation and density functional theory (DFT) calculations. The melting dynamics of PEG have been unambiguously explained along the C-O bond rotation coordinate.

Study of phase synchronization in multichannel seizure EEG using nonlinear recurrence measure

Complex biological systems such as the human brain can be expected to be inherently nonlinear and hence difficult to model. Most of the previous studies on investigations of brain function have either used linear models or parametric nonlinear models. In this paper, we propose a novel application of a nonlinear measure of phase synchronization based on recurrences, correlation between probabilities of recurrence (CPR), to study seizures in the brain. The advantage of this nonparametric method is that it makes very few assumptions thus making it possible to investigate brain functioning in a data-driven way. We have demonstrated the utility of CPR measure for the study of phase synchronization in multichannel seizure EEG recorded from patients with global as well as focal epilepsy. For the case of global epilepsy, brain synchronization using thresholded CPR matrix of multichannel EEG signals showed clear differences in results obtained for epileptic seizure and pre-seizure. Brain headmaps obtained for seizure and preseizure cases provide meaningful insights about synchronization in the brain in those states. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. Comparative studies with linear correlation have shown that the nonlinear measure CPR outperforms the linear correlation measure. (C) 2014 Elsevier Ltd. All rights reserved.

In-situ Stabilization of Tin Nanoparticles in Porous Carbon Matrix derived from Metal Organic Framework: High Capacity and High Rate Capability Anodes for Lithium-ion Batteries

It is a formidable challenge to arrange tin nanoparticles in a porous matrix for the achievement of high specific capacity and current rate capability anode for lithium-ion batteries. This article discusses a simple and novel synthesis of arranging tin nanoparticles with carbon in a porous configuration for application as anode in lithium-ion batteries. Direct carbonization of synthesized three-dimensional Sn-based MOF: K2Sn2(1,4-bdc)(3)](H2O) (1) (bdc = benzenedicarboxylate) resulted in stabilization of tin nanoparticles in a porous carbon matrix (abbreviated as Sn@C). Sn@C exhibited remarkably high electrochemical lithium stability (tested over 100 charge and discharge cycles) and high specific capacities over a wide range of operating currents (0.2-5 Ag-1). The novel synthesis strategy to obtain Sn@C from a single precursor as discussed herein provides an optimal combination of particle size and dispersion for buffering severe volume changes due to Li-Sn alloying reaction and provides fast pathways for lithium and electron transport.

Solubility-Hardness Correlation in Molecular Crystals: Curcumin and Sulfathiazole Polymorphs

Curcumin and sulfathiazole exist as three and five polymorphs, respectively. We correlate solubility and mechanical properties in these polymorphic systems. It is seen that hardness (H) is inversely proportional to the solubility of a polymorph. H of the polymorphs is explained on the basis of slip planes in the crystal structure, the Schmid factor (m), and the relative orientation of molecules with respect to the nanoindenter direction. Effectively, H is a useful parameter (compared to melting point, T-m, and density, rho) that correlates well with the solubility of a polymorph. Such a correlation is helpful in systems like curcumin and sulfathiazole in which the Gibbs free energy of the polymorphs are close to one another. To summarize, a softer polymorph is more soluble.

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

Correlation between Optical Properties and Nanomorphology of Fluoranthene-Based Conjugated Copolymer

Nanoparticles of conjugated polymers are receiving attention due to their interesting optical properties. Here we report nanoparticles of fluoranthene-based conjugated copolymer prepared by the Suzuki coupling reaction. The copolymer forms nanoparticles by the spontaneous self-assembly after evaporation of organic solvent. The mean diameter of the nanoparticles can be manipulated by varying solvent composition. We investigated the parameters that govern the nanostructured morphology of polymer by systematic variation of good and poor solvent. The UV vis and time-resolved fluorescence spectroscopy measurement reveal the use of poor solvent in the organization of nanostructures. Furthermore, transmission electron microscopy highlights the importance of rigidity of the polymer backbone in morphological development.

Diffusing-wave spectroscopy in an inhomogeneous object: Local viscoelastic spectra from ultrasound-assisted measurement of correlation decay arising from the ultrasound focal volume

We demonstrate diffusing-wave spectroscopy (DWS) in a localized region of a viscoelastically inhomogeneous object by measurement of the intensity autocorrelation g(2)(tau)] that captures only the decay introduced by the temperature-induced Brownian motion in the region. The region is roughly specified by the focal volume of an ultrasound transducer which introduces region specific mechanical vibration owing to insonification. Essential characteristics of the localized non-Markovian dynamics are contained in the decay of the modulation depth M(tau)], introduced by the ultrasound forcing in the focal volume selected, on g(2)(tau). The modulation depth M(tau(i)) at any delay time tau(i) can be measured by short-time Fourier transform of g(2)(tau) and measurement of the magnitude of the spectrum at the ultrasound drive frequency. By following the established theoretical framework of DWS, we are able to connect the decay in M(tau) to the mean-squared displacement (MSD) of scattering centers and the MSD to G*(omega), the complex viscoelastic spectrum. A two-region composite polyvinyl alcohol phantom with different viscoelastic properties is selected for demonstrating local DWS-based recovery of G*(omega) corresponding to these regions from the measured region specific M(tau(i))vs tau(i). The ultrasound-assisted measurement of MSD is verified by simulating, using a generalized Langevin equation (GLE), the dynamics of the particles in the region selected as well as by the usual DWS experiment without the ultrasound. It is shown that whereas the MSD obtained by solving the GLE without the ultrasound forcing agreed with its experimental counterpart covering small and large values of tau, the match was good only in the initial transients in regard to experimental measurements with ultrasound.

Processing-microstructure-yield strength correlation in a near beta Ti alloy, Ti-5Al-5Mo-5V-3Cr

A combined set of thermo-mechanical steps recommended for high strength beta Ti alloy are homogenization, deformation, recrystallization, annealing and ageing steps in sequence. Recrystallization carried out above or below beta transus temperature generates either beta annealed (lath type morphology of alpha) or bimodal (lath+globular morphology of alpha) microstructure. Through variations in heat treatment parameters at these processing steps, wide ranges of length scales of features have been generated in both types of microstructures in a near beta Ti alloy, Ti-5Al-5Mo-5V-3Cr (Ti-5553). 0.2% Yield strength (YS) has been correlated to various microstructural features and associated heat treatment parameters. Relative importance of microstructural features in influencing YS has been identified. Process parameters at different steps have been identified and recommended for attaining different levels of YS for this near beta Ti alloy. (C) 2014 Elsevier B.V. All rights reserved.

Interfacial Stresses in Shape Memory Alloy Reinforced Composites

Debonding of Shape Memory Alloy (SMA) wires in SMA reinforced polymer matrix composites is a complex phenomenon compared to other fabric fiber debonding in similar matrix composites. This paper focuses on experimental study and analytical correlation of stress required for debonding of thermal SMA actuator wire reinforced composites. Fiber pull-out tests are carried out on thermal SMA actuator at parent state to understand the effect of stress induced detwinned martensites. An ASTM standard is followed as benchmark method for fiber pull-out test. Debonding stress is derived with the help of non-local shear-lag theory applied to elasto-plastic interface. Furthermore, experimental investigations are carried out to study the effect of Laser shot peening on SMA surface to improve the interfacial strength. Variation in debonding stress due to length of SMA wire reinforced in epoxy are investigated for non-peened and peened SMA wires. Experimental results of interfacial strength variation due to various L/d ratio for non-peened and peened SMA actuator wires in epoxy matrix are discussed.