Effective contrast recovery in rapid dynamic near-infrared diffuse optical tomography using l(1)-norm-based linear image reconstruction method

Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ l(2)-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of l(1)-norm based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional l(2)-based techniques. Moreover, it is shown that the proposed l(1)-based technique is computationally efficient compared to its counterpart (l(2)-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.

Thermal degradation kinetics of thermoresponsive poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) copolymers prepared via RAFT polymerization

Reversible addition-fragmentation chain transfer polymerization at 70 A degrees C in N,N-dimethylformamide was used to prepare poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) copolymers in various compositions to afford well-defined polymers with pre-determined molecular weight, narrow molecular weight distribution, and precise chain end structure. The copolymer compositions were determined by H-1 NMR spectroscopy. The reactivity ratios of N-isopropylacrylamide (NIPAM) and N,N-dimethylacrylamide (DMA) were calculated as r (NIPAM) = 0.838 and r (DMA) = 1.105, respectively, by the extended Kelen-Tudos method at high conversions. The lower critical solution temperature of PNIPAM can be altered by changing the DMA content in the copolymer chain. Differential scanning calorimetry and thermogravimetric analysis at different heating rates were carried out on these copolymers to understand the nature of thermal degradation and to determine its kinetics. Different kinetic models were applied to estimate various parameters like the activation energy, the order, and the frequency factor. These studies are important to understand the solid state polymer degradation of N-alkyl substituted polymers, which show great potential in the preparation of miscible polymer blends due to their ability to interact through hydrogen bonding.

Sequential alternating proximal method for scalable sparse structural SVMs

Structural Support Vector Machines (SSVMs) have recently gained wide prominence in classifying structured and complex objects like parse-trees, image segments and Part-of-Speech (POS) tags. Typical learning algorithms used in training SSVMs result in model parameters which are vectors residing in a large-dimensional feature space. Such a high-dimensional model parameter vector contains many non-zero components which often lead to slow prediction and storage issues. Hence there is a need for sparse parameter vectors which contain a very small number of non-zero components. L1-regularizer and elastic net regularizer have been traditionally used to get sparse model parameters. Though L1-regularized structural SVMs have been studied in the past, the use of elastic net regularizer for structural SVMs has not been explored yet. In this work, we formulate the elastic net SSVM and propose a sequential alternating proximal algorithm to solve the dual formulation. We compare the proposed method with existing methods for L1-regularized Structural SVMs. Experiments on large-scale benchmark datasets show that the proposed dual elastic net SSVM trained using the sequential alternating proximal algorithm scales well and results in highly sparse model parameters while achieving a comparable generalization performance. Hence the proposed sequential alternating proximal algorithm is a competitive method to achieve sparse model parameters and a comparable generalization performance when elastic net regularized Structural SVMs are used on very large datasets.

Method of designing an access mechanism for social networks

The rapid development of communication and networking has lessened geographical boundaries among actors in social networks. In social networks, actors often want to access databases depending upon their access rights, privacy, context, privileges, etc. Managing and handling knowledge based access of actors is complex and hard for which broad range of technologies need to be called. Access based on dynamic access rights and circumstances of actors impose major tasks on access systems. In this paper, we present an Access Mechanism for Social Networks (AMSN) to render access to actors over databases taking privacy and status of actors into consideration. The designed AMSN model is tested over an Agriculture Social Network (ASN) which utilises distinct access rights and privileges of actors related to the agriculture occupation, and provides access to actors over databases.

The effect of Sb on the electrical and magnetic properties of Ni-Zn ferrites prepared by sol-gel autocombustion method

Polycrystalline Ni-Zn ferrites with a well-defined composition of Ni0.4Zn0.6Fe2-xSbxO4 synthesized using sol-gel method. Morphological characterizations on the prepared samples were performed by high resolution transmission electron and field emission scanning electron microscopy. The powders were densified using microwave sintering method. The room temperature complex permittivity (epsilon' and epsilon aEuro(3)) and permeability (mu' and mu aEuro(3)) were measured over a wide frequency range from 1 MHz-1.8 GHz. The real part of permittivity varies as `x' concentration increases and the resonance frequency was observed at much higher frequencies and there is a significant decrease in the loss factor (tan delta). The electrical resistivity and permeability of NiZn ferrites increased with an increase of Sb content. As the concentration of `x' increases from 0 to 0.08 the saturation magnetisation decreases. The saturation magnetization (M-s) a parts per thousand aEuro parts per thousand 52.211 A.m(2)/Kg for x = 0 at room temperature. The room temperature electro paramagnetic resonance (EPR) were studied.

Constraining complex aquifer geometry with geophysics (2-D ERT and MRS measurements) for stochastic modelling of groundwater flow

Stochastic modelling is a useful way of simulating complex hard-rock aquifers as hydrological properties (permeability, porosity etc.) can be described using random variables with known statistics. However, very few studies have assessed the influence of topological uncertainty (i.e. the variability of thickness of conductive zones in the aquifer), probably because it is not easy to retrieve accurate statistics of the aquifer geometry, especially in hard rock context. In this paper, we assessed the potential of using geophysical surveys to describe the geometry of a hard rock-aquifer in a stochastic modelling framework. The study site was a small experimental watershed in South India, where the aquifer consisted of a clayey to loamy-sandy zone (regolith) underlain by a conductive fissured rock layer (protolith) and the unweathered gneiss (bedrock) at the bottom. The spatial variability of the thickness of the regolith and fissured layers was estimated by electrical resistivity tomography (ERT) profiles, which were performed along a few cross sections in the watershed. For stochastic analysis using Monte Carlo simulation, the generated random layer thickness was made conditional to the available data from the geophysics. In order to simulate steady state flow in the irregular domain with variable geometry, we used an isoparametric finite element method to discretize the flow equation over an unstructured grid with irregular hexahedral elements. The results indicated that the spatial variability of the layer thickness had a significant effect on reducing the simulated effective steady seepage flux and that using the conditional simulations reduced the uncertainty of the simulated seepage flux. As a conclusion, combining information on the aquifer geometry obtained from geophysical surveys with stochastic modelling is a promising methodology to improve the simulation of groundwater flow in complex hard-rock aquifers. (C) 2013 Elsevier B.V. All rights reserved.

A composition-dependent ``re-entrant'' crystallographic phase transition in the substitutional metal acetylacetonate complex (Cr1-xGax)(acac)(3)

The formation of a complete solid solution between acetylacetonate (acac) complexes of chromium and gallium, (Cr1-x,Ga-x)(acac)(3) for 0.1 method. Wellcrystallised, subliming solids are found to form for each nominal value of x, with thermal analysis confirming each composition to have a congruent melting point, making it a substitutional complex. Whereas the pure complexes (i.e. the end members of the solid solution, x = 0 and x = 1) are both centro-symmetric, a composition-dependent crystallographic phase transition to a non-centrosymmetric structure is found to occur for compositions with 0.4 < x < 0.9. Such a ``re-entrant'' crystallographic transition is interpreted to be due to the drive to overcome the disorder present in certain centrosymmetric chromium-rich compositions, by going over to a non-centrosymmetric structure with a doubling of the unit cell. The substitutional complex is shown to lead to a substitutional oxide with the beta-gallate structure. (C) 2014 Elsevier Ltd. All rights reserved.

A spectral multiscale method for wave propagation analysis: Atomistic-continuum coupled simulation

In this paper, we present a new multiscale method which is capable of coupling atomistic and continuum domains for high frequency wave propagation analysis. The problem of non-physical wave reflection, which occurs due to the change in system description across the interface between two scales, can be satisfactorily overcome by the proposed method. We propose an efficient spectral domain decomposition of the total fine scale displacement along with a potent macroscale equation in the Laplace domain to eliminate the spurious interfacial reflection. We use Laplace transform based spectral finite element method to model the macroscale, which provides the optimum approximations for required dynamic responses of the outer atoms of the simulated microscale region very accurately. This new method shows excellent agreement between the proposed multiscale model and the full molecular dynamics (MD) results. Numerical experiments of wave propagation in a 1D harmonic lattice, a 1D lattice with Lennard-Jones potential, a 2D square Bravais lattice, and a 2D triangular lattice with microcrack demonstrate the accuracy and the robustness of the method. In addition, under certain conditions, this method can simulate complex dynamics of crystalline solids involving different spatial and/or temporal scales with sufficient accuracy and efficiency. (C) 2014 Elsevier B.V. All rights reserved.

The phenanthroimidazole-based dizinc(II) complex as a fluorescent probe for the pyrophosphate ion as generated in polymerase chain reactions and pyrosequencing

A highly selective and sensitive phenanthroimidazole tagged Mannich base type dizinc(II) fluorescent probe (R-Zn2+) has been developed for the pyrophosphate ion (PPi) with a very low limit of detection (LOD) of 0.25 ppm; this also assesses PPi from DNA polymerization chain reaction (PCR).

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

Estimation of Power Input to Complex Dielectric Barrier Discharge Reactor Geometries used in NOx Cleaning

Studies were carried out to estimate the power input to Dielectric Barrier Discharge (DBD) reactors powered by AC high voltage in the context of their application in non-thermal plasma cleaning of exhaust gases. Power input to the reactors was determined both theoretically and experimentally. Four different reactor geometries energized with 50 Hz and 1.5 kHz AC excitation were considered for the study. The theoretically estimated power using Manley's equation was found to agree with the experimental results. Results show that the analytically computed capacitance, without including the electrode edge effects, gives sufficiently good results that are matching with the measured values. For complex geometries where analytical calculation of capacitance is often difficult, a novel method of estimating the reactor capacitance, and hence the power input to the reactor, was introduced in this paper. The predicted results were validated with experiments.

Quick measurement of H-1-F-19 scalar couplings from the complex NMR spectra by real-time spin edition

Most often the measurement of VHF from the conventional 1D H-1 NMR spectrum is severely hindered consequent to similar magnitudes of JHF and JHH couplings and the spectral multiplicity pattern. The present study reports a new 1D NMR technique based on real time spin edition, which removes all JHF and JHH while retaining only VHF of a chosen fluorine. The obtained spectrum is significantly simplified and permits straightforward determination of all possible VHF values of a chosen fluorine. Due to one dimensional nature, the method is much faster compared to 2D GET-SERF by 1-2 orders of magnitude. (C) 2015 Elsevier B.V. All rights reserved.