Directed Synthesis of Rocksalt AuCl Crystals

We report the first-time experimental realization of rocksalt AuCl crystals. Our approach involves Au(III) complexing and reduction to Au(I) using an amine-terminated surfactant in a low dielectric permittivity solvent. The low charge screening in nonpolar solvents promotes crystallization of rocksalt AuCl, in which the bonding is predominantly ionic, in preference over tetragonal AuCl. The rocksalt AuCl crystals obtained here will facilitate studies to unveil the nexus between electronic structure and crystal structure in AuCl polymorphs, and provide insights on these relationships in other polymorphic crystal systems. Our approach provides a new means for crystallizing selective polymorphs of inorganic compounds by subtly influencing the cation electronic structure by varying the dielectric permittivity of the synthesis medium. In addition, the AuCl crystals can serve as inexpensive Au(I) precursors for forming a variety of Au nanostructures.

Multi Pattern Dynamic Time Warping For Automatic Speech Recognition

We are addressing the problem of jointly using multiple noisy speech patterns for automatic speech recognition (ASR), given that they come from the same class. If the user utters a word K times, the ASR system should try to use the information content in all the K patterns of the word simultaneously and improve its speech recognition accuracy compared to that of the single pattern based speech recognition. T address this problem, recently we proposed a Multi Pattern Dynamic Time Warping (MPDTW) algorithm to align the K patterns by finding the least distortion path between them. A Constrained Multi Pattern Viterbi algorithm was used on this aligned path for isolated word recognition (IWR). In this paper, we explore the possibility of using only the MPDTW algorithm for IWR. We also study the properties of the MPDTW algorithm. We show that using only 2 noisy test patterns (10 percent burst noise at -5 dB SNR) reduces the noisy speech recognition error rate by 37.66 percent when compared to the single pattern recognition using the Dynamic Time Warping algorithm.

Compressive Sensing For Sparsely Excited Speech Signals

Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived from the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra.

Varied Immune Response to FVIII: Presence of Proteolytic Antibodies Directed to Factor VIII in Different Human Pathologies

The versatility of antibodies is demonstrated by the various functions that they mediate such as neutralization, agglutination, fixation of the complement and its activation, and activation of effector cells. In addition to this plethora of functions, antibodies are capable of expressing enzymatic activity. Antibodies with catalytic function are a result of the productive interplay between the highly evolved machinery of the immune system and the chemical framework used to induce them (antigens). Catalytic antibodies are immunoglobulins with an ability to catalyze the reactions involving the antigen for which they are specific. Catalytic immunoglobulins of the IgM and IgG isotypes have been detected in the serum of healthy donors. In addition, catalytic immunoglobulins of the IgA isotype have been detected in the milk of healthy mothers. Conversely, antigen-specific hydrolytic antibodies have been reported in a number of inflammatory, autoimmune, and neoplastic disorders. The pathophysiological occurrence and relevance of catalytic antibodies remains a debated issue. Through the description of the hydrolysis of coagulation factor VIII as model target antigen, we propose that catalytic antibodies directed to the coagulation factor VIII may play a beneficial or a deleterious role depending on the immuno-inflammatory condition under which they occur.

Robust and High-resolution Voiced/Unvoiced Classification in Noisy Speech Using A Signal Smoothness Criterion

We propose a novel technique for robust voiced/unvoiced segment detection in noisy speech, based on local polynomial regression. The local polynomial model is well-suited for voiced segments in speech. The unvoiced segments are noise-like and do not exhibit any smooth structure. This property of smoothness is used for devising a new metric called the variance ratio metric, which, after thresholding, indicates the voiced/unvoiced boundaries with 75% accuracy for 0dB global signal-to-noise ratio (SNR). A novelty of our algorithm is that it processes the signal continuously, sample-by-sample rather than frame-by-frame. Simulation results on TIMIT speech database (downsampled to 8kHz) for various SNRs are presented to illustrate the performance of the new algorithm. Results indicate that the algorithm is robust even in high noise levels.

Two Stage Transform Vector Quantization of LSFs for Wideband Speech Coding

We investigate the use of a two stage transform vector quantizer (TSTVQ) for coding of line spectral frequency (LSF) parameters in wideband speech coding. The first stage quantizer of TSTVQ, provides better matching of source distribution and the second stage quantizer provides additional coding gain through using an individual cluster specific decorrelating transform and variance normalization. Further coding gain is shown to be achieved by exploiting the slow time-varying nature of speech spectra and thus using inter-frame cluster continuity (ICC) property in the first stage of TSTVQ method. The proposed method saves 3-4 bits and reduces the computational complexity by 58-66%, compared to the traditional split vector quantizer (SVQ), but at the expense of 1.5-2.5 times of memory.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Observation of Peierls transition in nanowires (diameter similar to 130 nm) of the charge transfer molecule TTF-TCNQ synthesized by electric-field-directed growth

We report the growth of nanowires of the charge transfer complex tetrathiafulvalene-tetracyanoquinodimethane (TTF-TCNQ) with diameters as low as 130 nm and show that such nanowires can show Peierls transitions at low temperatures. The wires of sub-micron length were grown between two prefabricated electrodes (with sub-micron gap) by vapor phase growth from a single source by applying an electric field between the electrodes during the growth process. The nanowires so grown show a charge transfer ratio similar to 0.57, which is close to that seen in bulk crystals. Below the transition the transport is strongly nonlinear and can be interpreted as originating from de-pinning of CDW that forms at the Peierls transition.

Use of structure-directed DNA ligands to probe the binding of recA protein to narrow and wide grooves of DNA and on its ability to promote homologous pairing

We have used circular dichroism and structure-directed drugs to identify the role of structural features, wide and narrow grooves in particular, required for the cooperative polymerization, recognition of homologous sequences, and the formation of joint molecules promoted by recA protein. The path of cooperative polymerization of recA protein was deduced by its ability to cause quantitative displacement of distamycin from the narrow groove of duplex DNA. By contrast, methyl green bound to the wide groove was retained by the nucleoprotein filaments comprised of recA protein-DNA. Further, the mode of binding of these ligands and recA protein to DNA was confirmed by DNaseI digestion. More importantly, the formation of joint molecules was prevented by distamycin in the narrow groove while methyl green in the wide groove had no adverse effect. Intriguingly, distamycin interfered with the production of coaggregates between nucleoprotein filaments of recA protein-M13 ssDNA and naked linear M13 duplex DNA, but not with linear phi X174 duplex DNA. Thus, these data, in conjunction with molecular modeling, suggest that the narrow grooves of duplex DNA provide the fundamental framework required for the cooperative polymerization of recA protein and alignment of homologous sequences. These findings and their significance are discussed in relation to models of homologous pairing between two intertwined DNA molecules.

Anion directed template synthesis of Cu(II) complexes of a N,N,O donor mono-condensed Schiff base ligand: A molecular scaffold forming highly ordered H-bonded rectangular grids

Anion directed, template syntheses of two dinuclear copper(II) complexes of mono-condensed Schiff base ligand Hdipn (4-[(3-aminopentylimino)-methyl]-benzene-1,3-diol) involving 2,4- dihydroxybenzaldehyde and 1,3-diaminopentane were realized in the presence of bridging azide and acetate anions. Both complexes, [Cu-2(dipn)(2)(N-3)(2)] (1) and [Cu-2(dip(n))(2)(OAc)(2)] (2) have been characterized by X-ray crystallography. The two mononuclear units are joined together by basal-apical, double end-on azido bridges in complex 1 and by basal-apical, double mono-atomic acetate oxygen-bridges in 2. Both complexes form rectangular grid-like supramolecular structures via H-bonds connecting the azide or acetate anion and the p-hydroxy group of 2,4- dihydroxybenzaldehyde. Variable-temperature (300-2 K) magnetic susceptibility measurements reveal that complex 1 has antiferromagnetic coupling (J = -2.10 cm (1)) through the azide bridge while 2 has intra-dimer ferromagnetic coupling through the acetate bridge and inter-dimer antiferromagnetic coupling through H-bonds (J = 2.85 cm (1), J' = -1.08 cm (1)). (C) 2009 Elsevier B. V. All rights reserved.

Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

GMM based Bayesian approach to speech enhancement in signal transform domain

Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (GMM) and additive noise by a Gaussian PDF, we derive the minimum mean square error (MMSE) estimator. The derived MMSE estimator is non-linear and the linear MMSE estimator is shown to be a special case. For speech signal corrupted by independent additive noise, by modeling the joint PDF of time-domain speech samples of a speech frame using a GMM, we propose a speech enhancement method based on the derived MMSE estimator. We also show that the same estimator can be used for transform-domain speech enhancement.

Role of histidine residues in EcoP15I DNA methyltransferase activity as probed by chemical modification and site-directed mutagenesis

Towards understanding the catalytic mechanism of M.EcoP15I [EcoP15I MTase (DNA methyltransferase); an adenine methyltransferase], we investigated the role of histidine residues in catalysis. M.EcoP15I, when incubated with DEPC (diethyl pyrocarbonate), a histidine-specific reagent, shows a time- and concentration-dependent inactivation of methylation of DNA containing its recognition sequence of 5'-CAGCAG-3'. The loss of enzyme activity was accompanied by an increase in absorbance at 240 nm. A difference spectrum of modified versus native enzyme shows the formation of N-carbethoxyhistidine that is diminished by hydroxylamine. This, along with other experiments, strongly suggests that the inactivation of the enzyme by DEPC was specific for histidine residues. Substrate protection experiments show that pre-incubating the methylase with DNA was able to protect the enzyme from DEPC inactivation. Site-directed mutagenesis experiments in which the 15 histidine residues in the enzyme were replaced individually with alanine corroborated the chemical modification studies and established the importance of His-335 in the methylase activity. No gross structural differences were detected between the native and H335A mutant MTases, as evident from CD spectra, native PAGE pattern or on gel filtration chromatography. Replacement of histidine with alanine residue at position 335 results in a mutant enzyme that is catalytically inactive and binds to DNA more tightly than the wild-type enzyme. Thus we have shown in the present study, through a combination of chemical modification and site-directed mutagenesis experiments, that His-335 plays an essential role in DNA methylation catalysed by M.EcoP15I.

Structural aspects of semantic-directed clusters

Knowledge-based clusters are studied from the structural point of view. Generalized descriptions for such clusters are stated and illustrated. Peculiarities of certain knowledge-based cluster configurations are highlighted. The adequacy of the connectives logical and (“and”) logical or (“exclusive-or”) in describing such clusters is justified. The definition of “concept” is elaborated from the clustering point of view and used to establish the equivalence between, descriptions of clusters and concepts. The order-independence of semantic-directed clustering approach is established formally based on axiomatic considerations.