Filling-in Void and Sparse Regions in Protein Sequence Space by Protein-Like Artificial Sequences Enables Remarkable Enhancement in Remote Homology Detection Capability

Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like ``linker'' sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be ``plugged-into'' routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. (C) 2013 Elsevier Ltd. All rights reserved.

Spatially Adaptive Kernel Regression Using Risk Estimation

An important question in kernel regression is one of estimating the order and bandwidth parameters from available noisy data. We propose to solve the problem within a risk estimation framework. Considering an independent and identically distributed (i.i.d.) Gaussian observations model, we use Stein's unbiased risk estimator (SURE) to estimate a weighted mean-square error (MSE) risk, and optimize it with respect to the order and bandwidth parameters. The two parameters are thus spatially adapted in such a manner that noise smoothing and fine structure preservation are simultaneously achieved. On the application side, we consider the problem of image restoration from uniform/non-uniform data, and show that the SURE approach to spatially adaptive kernel regression results in better quality estimation compared with its spatially non-adaptive counterparts. The denoising results obtained are comparable to those obtained using other state-of-the-art techniques, and in some scenarios, superior.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential.

Secrecy in the 2-User Symmetric Deterministic Interference Channel with Transmitter Cooperation

This work presents novel achievable schemes for the 2-user symmetric linear deterministic interference channel with limited-rate transmitter cooperation and perfect secrecy constraints at the receivers. The proposed achievable scheme consists of a combination of interference cancelation, relaying of the other user's data bits, time sharing, and transmission of random bits, depending on the rate of the cooperative link and the relative strengths of the signal and the interference. The results show, for example, that the proposed scheme achieves the same rate as the capacity without the secrecy constraints, in the initial part of the weak interference regime. Also, sharing random bits through the cooperative link can achieve a higher secrecy rate compared to sharing data bits, in the very high interference regime. The results highlight the importance of limited transmitter cooperation in facilitating secure communications over 2-user interference channels.

Fatigue crack propagation at concrete-concrete bi-material interfaces

This paper presents experimental and analytical studies on fatigue crack propagation in concrete-concrete cold jointed interface specimens. Beams of different sizes having jointed interface between two concretes with different elastic properties are tested under fatigue loading. The acoustic emission technique is used for monitoring the fatigue crack growth. It is observed that the interface having a higher moduli mismatch tends to behave in a brittle manner. The CMOD compliances at different loading cycles are measured and the equivalent crack lengths are determined from a finite element analysis. An analytical model for crack growth rate is proposed using the concepts of the dimensional analysis. (C) 2014 Elsevier Ltd. All rights reserved.

PLIC: protein-ligand interaction clusters

Most of the biological processes are governed through specific protein-ligand interactions. Discerning different components that contribute toward a favorable protein-ligand interaction could contribute significantly toward better understanding protein function, rationalizing drug design and obtaining design principles for protein engineering. The Protein Data Bank (PDB) currently hosts the structure of similar to 68 000 protein-ligand complexes. Although several databases exist that classify proteins according to sequence and structure, a mere handful of them annotate and classify protein-ligand interactions and provide information on different attributes of molecular recognition. In this study, an exhaustive comparison of all the biologically relevant ligand-binding sites (84 846 sites) has been conducted using PocketMatch: a rapid, parallel, in-house algorithm. PocketMatch quantifies the similarity between binding sites based on structural descriptors and residue attributes. A similarity network was constructed using binding sites whose PocketMatch scores exceeded a high similarity threshold (0.80). The binding site similarity network was clustered into discrete sets of similar sites using the Markov clustering (MCL) algorithm. Furthermore, various computational tools have been used to study different attributes of interactions within the individual clusters. The attributes can be roughly divided into (i) binding site characteristics including pocket shape, nature of residues and interaction profiles with different kinds of atomic probes, (ii) atomic contacts consisting of various types of polar, hydrophobic and aromatic contacts along with binding site water molecules that could play crucial roles in protein-ligand interactions and (iii) binding energetics involved in interactions derived from scoring functions developed for docking. For each ligand-binding site in each protein in the PDB, site similarity information, clusters they belong to and description of site attributes are provided as a relational database-protein-ligand interaction clusters (PLIC).

Nanodiamond-Based Thermal Fluids

Dispersions of nanodiamond (average size similar to 6 nm) within dielectric insulator mineral oil are reported for their enhanced thermal conductivity properties and potential applications in thermal management. Dynamic and kinematic viscosities-very important parameters in thermal management by nanofluids-are investigated. The dependence of the dynamic viscosity is well-described by the theoretical predictions of Einstein's model. The temperature dependence of the dynamic viscosity obeys an Arrhenius-like behavior, where the activation energy and the pre-exponential factor have an exponential dependence on the filler fraction of nanodiamonds. An enhancement in thermal conductivity up to 70% is reported for nanodiamond based thermal fluids. Additional electron microscopy, Raman spectroscopy and X-ray diffraction analysis support the experimental data and their interpretation.

PocketMatch (version 2.0): A parallel algorithm for the detection of structural similarities between protein ligand binding-sites

Knowledge of protein-ligand interactions is essential to understand several biological processes and important for applications ranging from understanding protein function to drug discovery and protein engineering. Here, we describe an algorithm for the comparison of three-dimensional ligand-binding sites in protein structures. A previously described algorithm, PocketMatch (version 1.0) is optimised, expanded, and MPI-enabled for parallel execution. PocketMatch (version 2.0) rapidly quantifies binding-site similarity based on structural descriptors such as residue nature and interatomic distances. Atomic-scale alignments may also be obtained from amino acid residue pairings generated. It allows an end-user to compute database-wide, all-to-all comparisons in a matter of hours. The use of our algorithm on a sample dataset, performance-analysis, and annotated source code is also included.

Tuning nuclearity of clusters by positional change of functional group: Synthesis of polynuclear clusters, crystal structures and magnetic properties

Four neutral polynuclear magnetic clusters, (Mn6Mn2Na2I)-Mn-III-Na-II(N-3)(8)(mu(1)-O)(2)(L-1)(6)(CH3OH)(2)] (1), (Mn6Na2I)-Na-III(N-3)(4)(mu(4)-O)(2)(L-2)(4)(CH3COO)(4)] (2), Ni-5(II)(N-3)(4)(HL1)(4)(HCOO)(2)(CH3OH)(2)(H2O)(2)]center dot 2CH(3)OH (3) and (Ni4Na2I)-Na-II(N-3)(4)(HL2)(6)]center dot 2CH(3)OH (4) have been synthesized using tetradentate ligands H2L1-2 along with azide as a co-ligand. H2L1-2 are the products formed in situ upon condensation of 2-hydroxy-3-methoxybenzaldehyde with 1-aminopropan-2-ol and 1-aminopropan-3-ol, respectively. Single crystal X-ray diffraction and bond valence sum calculation showed that complex 1 is composed of both Mn-III and Mn-II. Complex 3 contains coordinated formate, which was formed upon in situ oxidation of methanol. The magnetic study over a wide range of temperatures of all the complexes (1-4) showed that 1 and 2 are antiferromagnetic whereas other two (3-4) are predominantly ferromagnetic. The estimated ground states of the complexes are S approximate to 3(1), S = 4(2), S = 5(3) and S approximate to 4(4), respectively. (C) 2014 Elsevier B.V. All rights reserved.

Gammatone Wavelet Cepstral Coefficients for Robust Speech Recognition

We develop noise robust features using Gammatone wavelets derived from the popular Gammatone functions. These wavelets incorporate the characteristics of human peripheral auditory systems, in particular the spatially-varying frequency response of the basilar membrane. We refer to the new features as Gammatone Wavelet Cepstral Coefficients (GWCC). The procedure involved in extracting GWCC from a speech signal is similar to that of the conventional Mel-Frequency Cepstral Coefficients (MFCC) technique, with the difference being in the type of filterbank used. We replace the conventional mel filterbank in MFCC with a Gammatone wavelet filterbank, which we construct using Gammatone wavelets. We also explore the effect of Gammatone filterbank based features (Gammatone Cepstral Coefficients (GCC)) for robust speech recognition. On AURORA 2 database, a comparison of GWCCs and GCCs with MFCCs shows that Gammatone based features yield a better recognition performance at low SNRs.

Linear filtering methods for fixed rate quantisation with noisy symmetric error channels

This study considers linear filtering methods for minimising the end-to-end average distortion of a fixed-rate source quantisation system. For the source encoder, both scalar and vector quantisation are considered. The codebook index output by the encoder is sent over a noisy discrete memoryless channel whose statistics could be unknown at the transmitter. At the receiver, the code vector corresponding to the received index is passed through a linear receive filter, whose output is an estimate of the source instantiation. Under this setup, an approximate expression for the average weighted mean-square error (WMSE) between the source instantiation and the reconstructed vector at the receiver is derived using high-resolution quantisation theory. Also, a closed-form expression for the linear receive filter that minimises the approximate average WMSE is derived. The generality of framework developed is further demonstrated by theoretically analysing the performance of other adaptation techniques that can be employed when the channel statistics are available at the transmitter also, such as joint transmit-receive linear filtering and codebook scaling. Monte Carlo simulation results validate the theoretical expressions, and illustrate the improvement in the average distortion that can be obtained using linear filtering techniques.

Morphology controlled synthesis of wurtzite ZnS nanostructures through simple hydrothermal method and observation of white light emission from ZnO obtained by annealing the synthesized ZnS nanostructures

A controllable synthesis of phase pure wurtzite (WZ) ZnS nanostructures has been reported in this work at a low temperature of similar to 220 degrees C using ethylenediamine as the soft template and by varying the molar concentration of zinc to sulphur precursors as well as by using different precursors. A significant reduction in the formation temperature required for the synthesis of phase pure WZ ZnS has been observed. A strong correlation has been observed between the morphology of the synthesized ZnS nanostructures and the precursors used during synthesis. It has been found from Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) image analyses that the morphology of the ZnS nanocrystals changes from a block-like to a belt-like structure having an average length of similar to 450 nm when the molar ratio of zinc to sulphur source is increased from 1 : 1 to 1 : 3. An oriented attachment (OA) growth mechanism has been used to explain the observed shape evolution of the synthesized nanostructures. The synthesized nanostructures have been characterized by the X-ray diffraction technique as well as by UV-Vis absorption and photoluminescence (PL) emission spectroscopy. The as-synthesized nanobelts exhibit defect related visible PL emission. On isochronal annealing of the nanobelts in air in the temperature range of 100-600 degrees C, it has been found that white light emission with a Commission Internationale de I'Eclairage 1931 (CIE) chromaticity coordinate of (0.30, 0.34), close to that of white light (0.33, 0.33), can be obtained from the ZnO nanostructures obtained at an annealing temperature of 600 degrees C. UV light driven degradation of methylene blue (MB) dye aqueous solution has also been demonstrated using as-synthesized nanobelts and similar to 98% dye degradation has been observed within only 40 min of light irradiation. The synthesized nanobelts with visible light emission and having dye degradation activity can be used effectively in future optoelectronic devices and in water purification for cleaning of dyes.

Binaural Signal Processing Motivated Generalized Analytic Signal Construction and AM-FM Demodulation

Binaural hearing studies show that the auditory system uses the phase-difference information in the auditory stimuli for localization of a sound source. Motivated by this finding, we present a method for demodulation of amplitude-modulated-frequency-modulated (AM-FM) signals using a ignal and its arbitrary phase-shifted version. The demodulation is achieved using two allpass filters, whose impulse responses are related through the fractional Hilbert transform (FrHT). The allpass filters are obtained by cosine-modulation of a zero-phase flat-top prototype halfband lowpass filter. The outputs of the filters are combined to construct an analytic signal (AS) from which the AM and FM are estimated. We show that, under certain assumptions on the signal and the filter structures, the AM and FM can be obtained exactly. The AM-FM calculations are based on the quasi-eigenfunction approximation. We then extend the concept to the demodulation of multicomponent signals using uniform and non-uniform cosine-modulated filterbank (FB) structures consisting of flat bandpass filters, including the uniform cosine-modulated, equivalent rectangular bandwidth (ERB), and constant-Q filterbanks. We validate the theoretical calculations by considering application on synthesized AM-FM signals and compare the performance in presence of noise with three other multiband demodulation techniques, namely, the Teager-energy-based approach, the Gabor's AS approach, and the linear transduction filter approach. We also show demodulation results for real signals.

A Contraction Mapping Approach for Robust Estimation of Lagged Autocorrelation

We consider the zero-crossing rate (ZCR) of a Gaussian process and establish a property relating the lagged ZCR (LZCR) to the corresponding normalized autocorrelation function. This is a generalization of Kedem's result for the lag-one case. For the specific case of a sinusoid in white Gaussian noise, we use the higher-order property between lagged ZCR and higher-lag autocorrelation to develop an iterative higher-order autoregressive filtering scheme, which stabilizes the ZCR and consequently provide robust estimates of the lagged autocorrelation. Simulation results show that the autocorrelation estimates converge in about 20 to 40 iterations even for low signal-to-noise ratio.

Thermoelectric Properties of Two-Phase PbTe with Indium Inclusions

The thermoelectric figure of merit (zT) can be increased by introduction of additional interfaces in the bulk to reduce the thermal conductivity. In this work, PbTe with a dispersed indium (In) phase was synthesized by a matrix encapsulation technique for different In concentrations. x-Ray diffraction analysis showed single-phase PbTe with In secondary phase. Rietveld analysis did not show In substitution at either the Pb or Te site, and this was further confirmed by room-temperature Raman data. Low-magnification (similar to 1500x) scanning electron microscopy images showed micrometer-sized In dispersed throughout the PbTe matrix, while at high magnification (150,000x) an agglomeration of PbTe particles in the hot-pressed samples could be seen. The electrical resistivity (rho) and Seebeck coefficient (S) were measured from 300 K to 723 K. Negative Seebeck values showed all the samples to be n-type. A systematic increase in resistivity and higher Seebeck coefficient values with increasing In content indicated the role of PbTe-In interfaces in the scattering of electrons. This was further confirmed by the thermal conductivity (kappa), measured from 423 K to 723 K, where a greater reduction in the electronic as compared with the lattice contribution was found for In-added samples. It was found that, despite the high lattice mismatch at the PbTe-In interface, phonons were not scattered as effectively as electrons. The highest zT obtained was 0.78 at 723 K for the sample with the lowest In content.