Combined Electron Transfer Dissociation-Collision-Induced Dissociation Fragmentation in the Mass Spectrometric Distinction of Leucine, Isoleucine, and Hydroxyproline Residues in Peptide Natural Products

Distinctions between isobaric residues have been a major challenge in mass spectrometric peptide sequencing. Here, we propose a methodology for distinction among isobaric leucine, isoleucine, and hydroxyproline, a commonly found post-translationally modified amino acid with a nominal mass of 113 Da, through a combined electron transfer dissociation-collision-induced dissociation approach. While the absence of c and z(center dot) ions, corresponding to the Yyy-Xxx (Xxx = Leu, Ile, or Hyp) segment, is indicative of the presence of hydroxyproline, loss of isopropyl (Delta m = 43 Da) or ethyl radicals (Delta m = 29 Da), through collisional activation of z(center dot) radical ions, are characteristic of leucine or isoleucine, respectively. Radical migration processes permit distinctions even in cases where the specific e ions, corresponding to the Yyy-Leu or -Ile segments, are absent or of low intensity. This tandem mass spectrometric (MSn) method has been successfully implemented in a liquid chromatography MSn platform to determine the identity of 23 different isobaric residues from a mixture of five different peptides. The approach is convenient for distinction of isobaric residues from any crude peptide mixture, typically encountered in natural peptide libraries or proteomic analysis.

Numerical Investigation of Heat Transfer from a Two-Dimensional Sudden Expansion Flow Using Nanofluids

Laminar forced convection heat transfer from two-dimensional sudden expansion flow of different nanofluids is studied numerically. The governing equations are solved using the unsteady stream function-vorticity method. The effect of volume fraction of the nanoparticles and type of nanoparticles on heat transfer is examined and found to have a significant impact. Local and average Nusselt numbers are reported in connection with various nanoparticle, volume fraction, and Reynolds number for expansion ratio 2. The Nusselt number reaches peak values near the reattachment point and reaches asymptotic value in the downstream. Bottom wall eddy and volume fraction shows a significant impact on the average Nusselt number.

Guided-wave based structural health monitoring of built-up composite structures using spectral finite element method

The paper discusses basically a wave propagation based method for identifying the damage due to skin-stiffener debonding in a stiffened structure. First, a spectral finite element model (SFEM) is developed for modeling wave propagation in general built-up structures, using the concept of assembling 2D spectral plate elements and the model is then used in modeling wave propagation in a skin-stiffener type structure. The damage force indicator (DFI) technique, which is derived from the dynamic stiffness matrix of the healthy stiffened structure (obtained from the SFEM model) along with the nodal displacements of the debonded stiffened structure (obtained from 2D finite element model), is used to identify the damage due to the presence of debond in a stiffened structure.

Reduction of aromatic nitro compounds to amines using zinc and aqueous chelating ethers: Mild and efficient method for zinc activation

A mild, environmentally friendly method for reduction of aromatic nitro group to amine is reported, using zinc powder in aqueous solutions of chelating ethers. The donor ether acts as a ligand and also serves as a co-solvent. Water is the proton source. This procedure is also a new method for the activation of zinc for electron transfer reduction of aromatic nitro compounds. The reduction is accomplished in a neutral medium and other reducing groups remained unaffected. The ethers used are dioxolane, 1,4-dioxane, ethoxymethoxyethane, dimethoxymethane, 1,2-dimethoxyethane, and diglyme.

Common Ground Method of Current Injection in Electrical Impedance Tomography

Surface electrodes are essentially required to be switched for boundary data collection in electrical impedance tomography (Ell). Parallel digital data bits are required to operate the multiplexers used, generally, for electrode switching in ELT. More the electrodes in an EIT system more the digital data bits are needed. For a sixteen electrode system. 16 parallel digital data bits are required to operate the multiplexers in opposite or neighbouring current injection method. In this paper a common ground current injection is proposed for EIT and the resistivity imaging is studied. Common ground method needs only two analog multiplexers each of which need only 4 digital data bits and hence only 8 digital bits are required to switch the 16 surface electrodes. Results show that the USB based data acquisition system sequentially generate digital data required for multiplexers operating in common ground current injection method. The profile of the boundary data collected from practical phantom show that the multiplexers are operating in the required sequence in common ground current injection protocol. The voltage peaks obtained for all the inhomogeneity configurations are found at the accurate positions in the boundary data matrix which proved the sequential operation of multiplexers. Resistivity images reconstructed from the boundary data collected from the practical phantom with different configurations also show that the entire digital data generation module is functioning properly. Reconstructed images and their image parameters proved that the boundary data are successfully acquired by the DAQ system which in turn indicates a sequential and proper operation of multiplexers.

Digestive ripening: a synthetic method par excellence for core-shell, alloy, and composite nanostructured materials

The solvated metal atom dispersion (SMAD) method has been used for the synthesis of colloids of metal nanoparticles. It is a top-down approach involving condensation of metal atoms in low temperature solvent matrices in a SMAD reactor maintained at 77 K. Warming of the matrix results in a slurry of metal atoms that interact with one another to form particles that grow in size. The organic solvent solvates the particles and acts as a weak capping agent to halt/slow down the growth process to a certain extent. This as-prepared colloid consists of metal nanoparticles that are quite polydisperse. In a process termed as digestive ripening, addition of a capping agent to the as-prepared colloid which is polydisperse renders it highly monodisperse either under ambient or thermal conditions. In this, as yet not well-understood process, smaller particles grow and the larger ones diminish in size until the system attains uniformity in size and a dynamic equilibrium is established. Using the SMAD method in combination with digestive ripening process, highly monodisperse metal, core-shell, alloy, and composite nanoparticles have been synthesized. This article is a review of our contributions together with some literature reports on this methodology to realize various nanostructured materials.

Fast acoustic likelihood computation using low-rank matrix approximation

Acoustic modeling using mixtures of multivariate Gaussians is the prevalent approach for many speech processing problems. Computing likelihoods against a large set of Gaussians is required as a part of many speech processing systems and it is the computationally dominant phase for LVCSR systems. We express the likelihood computation as a multiplication of matrices representing augmented feature vectors and Gaussian parameters. The computational gain of this approach over traditional methods is by exploiting the structure of these matrices and efficient implementation of their multiplication.In particular, we explore direct low-rank approximation of the Gaussian parameter matrix and indirect derivation of low-rank factors of the Gaussian parameter matrix by optimum approximation of the likelihood matrix. We show that both the methods lead to similar speedups but the latter leads to far lesser impact on the recognition accuracy. Experiments on a 1138 word vocabulary RM1 task using Sphinx 3.7 system show that, for a typical case the matrix multiplication approach leads to overall speedup of 46%. Both the low-rank approximation methods increase the speedup to around 60%, with the former method increasing the word error rate (WER) from 3.2% to 6.6%, while the latter increases the WER from 3.2% to 3.5%.

Hybrid online non-negative matrix factorization for clustering of documents

When document corpus is very large, we often need to reduce the number of features. But it is not possible to apply conventional Non-negative Matrix Factorization(NMF) on billion by million matrix as the matrix may not fit in memory. Here we present novel Online NMF algorithm. Using Online NMF, we reduced original high-dimensional space to low-dimensional space. Then we cluster all the documents in reduced dimension using k-means algorithm. We experimentally show that by processing small subsets of documents we will be able to achieve good performance. The method proposed outperforms existing algorithms.

Adiabatic eigenfunction-based approach for coherent excitation transfer: An almost analytical treatment of the Fenna-Matthews-Olson complex

We suggest a method of studying coherence in finite-level systems coupled to the environment and use it for the Hamiltonian that has been used to describe the light-harvesting pigment-protein complex. The method works with the adiabatic states and transforms the Hamiltonian to a form in which the terms responsible for decoherence and population relaxation are separated out. Decoherence is then accounted for nonperturbatively and population relaxation using a Markovian master equation. Almost analytical results can be obtained for the seven-level system, and the calculations are very simple for systems with more levels. We apply the treatment to the seven-level system, and the results are in excellent agreement with the exact numerical results of Nalbach et al. Nalbach, Braun, and Thorwart, Phys. Rev. E 84, 041926 (2011)]. Our approach is able to account for decoherence and population relaxation separately. It is found that decoherence causes only damping of oscillations and does not lead to transfer to the reaction center. Population relaxation is necessary for efficient transfer to the reaction center, in agreement with earlier findings. Our results show that the transformation to the adiabatic basis followed by a Redfield type of approach leads to results in good agreement with exact simulation.

Hybrid aggregated-vector algorithm for efficient parallelization of fast multipole method

An efficient parallelization algorithm for the Fast Multipole Method which aims to alleviate the parallelization bottleneck arising from lower job-count closer to root levels is presented. An electrostatic problem of 12 million non-uniformly distributed mesh elements is solved with 80-85% parallel efficiency in matrix setup and matrix-vector product using 60GB and 16 threads on shared memory architecture.

On the Mechanism of Phase Transfer Catalysis in Brust-Schiffrin Synthesis of Metal Nanoparticles

The two-phase Brust-Schiffrin method (BSM) is used to synthesize highly stable nanoparticles of noble metals. A phase transfer catalyst (PTC) is used to bring in aqueous phase soluble precursors into the organic phase to enable particle synthesis there. Two different mechanisms for phase transfer are advanced in the literature. The first mechanism considers PTC to bring in an aqueous phase soluble precursor by complexing with it. The second mechanism considers the ionic species to be contained in inverse micelles of PTC, with a water core inside. A comprehensive experimental study involving measurement of interfacial tension, viscosity, water content by Karl-Fischer titration, static light scattering, H-1 NMR, and small-angle X-ray scattering is reported in this work to establish that the phase transfer catalyst tetraoctylammonium bromide transfers ions by complexing with them, instead of encapsulating them in inverse micelles. The findings have implications for particle synthesis in two-phase methods such as BSM and their modification to produce more monodispersed particles.

Adiabatic Eigenfunction Based Approach to Coherent Transfer: Application to the Fenna-Matthews-Olson (FMO) Complex and the Role of Correlations in the Efficiency of Energy Transfer

We have recently suggested a method (Pallavi Bhattacharyya and K. L. Sebastian, Physical Review E 2013, 87, 062712) for the analysis of coherence in finite-level systems that are coupled to the surroundings and used it to study the process of energy transfer in the Fenna-Matthews-Olson (FMO) complex. The method makes use of adiabatic eigenstates of the Hamiltonian, with a subsequent transformation of the Hamiltonian into a form where the terms responsible for decoherence and population relaxation could be separated out at the lowest order. Thus one can account for decoherence nonperturbatively, and a Markovian type of master equation could be used for evaluating the population relaxation. In this paper, we apply this method to a two-level system as well as to a seven-level system. Comparisons with exact numerical results show that the method works quite well and is in good agreement with numerical calculations. The technique can be applied with ease to systems with larger numbers of levels as well. We also investigate how the presence of correlations among the bath degrees of freedom of the different bacteriochlorophyll a molecules of the FMO Complex affect the rate of energy transfer. Surprisingly, in the cases that we studied, our calculations suggest that the presence of anticorrelations, in contrast to correlations, make the excitation transfer more facile.

Projection Error Propagation-based Regularization (PEPR) method for resistivity reconstruction in Electrical Impedance Tomography (EIT)

A novel Projection Error Propagation-based Regularization (PEPR) method is proposed to improve the image quality in Electrical Impedance Tomography (EIT). PEPR method defines the regularization parameter as a function of the projection error developed by difference between experimental measurements and calculated data. The regularization parameter in the reconstruction algorithm gets modified automatically according to the noise level in measured data and ill-posedness of the Hessian matrix. Resistivity imaging of practical phantoms in a Model Based Iterative Image Reconstruction (MoBIIR) algorithm as well as with Electrical Impedance Diffuse Optical Reconstruction Software (EIDORS) with PEPR. The effect of PEPR method is also studied with phantoms with different configurations and with different current injection methods. All the resistivity images reconstructed with PEPR method are compared with the single step regularization (STR) and Modified Levenberg Regularization (LMR) techniques. The results show that, the PEPR technique reduces the projection error and solution error in each iterations both for simulated and experimental data in both the algorithms and improves the reconstructed images with better contrast to noise ratio (CNR), percentage of contrast recovery (PCR), coefficient of contrast (COC) and diametric resistivity profile (DRP). (C) 2013 Elsevier Ltd. All rights reserved.

An enthalpy method for modeling eutectic solidification

This paper presents a new micro-scale model for solidification of eutectic alloys. The model is based on the enthalpy method and simulates the growth of adjacent alpha and beta phases from a melt of eutectic composition in a two-dimensional Eulerian framework. The evolution of the two phases is obtained from the solution of volume averaged energy and species transport equations which are formulated using the nodal enthalpy and concentration potential values. The three phases are tracked using the beta-phase fraction and the liquid fraction values in all the computational nodes. Solutal convection flow field in the domain is obtained from the solution of volume-averaged momentum and continuity equations. The governing equations are solved using a coupled explicit-implicit scheme. The model is qualitatively validated with Jackson-Hunt theory. Results show expected eutectic growth pattern and proper species transfer and diffusion field ahead of the interface. Capabilities of the model such as lamella width selection, division of lamella into thinner lamellae and the presence of solutal convection are successfully demonstrated. The present model can potentially be incorporated into the existing framework of enthalpy based micro-scale dendritic solidification models thus leading to an efficient generalized microstructure evolution model. (C) 2014 Elsevier Inc. All rights reserved.

A fast NMR method for resonance assignments: application to metabolomics

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled (C-12) or C-13-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D C-13, H-1] HSQC-TOCSY, (2) 2D H-1-H-1 TOCSY and (3) 2D C-13-H-1 HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D C-13, H-1] HSQC-TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete H-1 and C-13 assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.