Superconductivity of embedded lead nano particles in metallic and amorphous matrices

Nanodispersed lead in metallic and amorphous matrices was synthesized by rapid solidification processing. The optimum microstructure was tailored to avoid percolation of the particles. With these embedded particles it is possible to study quantitatively the effect of size on the superconducting transition temperature by carrying out quantitative microstructural characterization and magnetic measurements. Our results suggest the role of the matrices in enhancement or depression of superconducting transition temperature of lead. The origin of this difference in behavior with respect to different matrices and sizes is discussed.

Closed form solutions for element equilibrium and flexibility matrices of eight node rectangular plate bending element using integrated force method

Closed form solutions for equilibrium and flexibility matrices of the Mindlin-Reissner theory based eight-node rectangular plate bending element (MRP8) using integrated Force Method (IFM) are presented in this paper. Though these closed form solutions of equilibrium and flexibility matrices are applicable to plate bending problems with square/rectangular boundaries, they reduce the computational time significantly and give more exact solutions. Presented closed form solutions are validated by solving large number of standard square/rectangular plate bending benchmark problems for deflections and moments and the results are compared with those of similar displacement-based eight-node quadrilateral plate bending elements available in the literature. The results are also compared with the exact solutions.

Functionalized and Postfunctionalizable Porous Polymeric Films through Evaporation-Induced Phase Separation Using Mixed Solvents

Condensation of water droplets during rapid evaporation of a polymer solution, under humid conditions, has been known to generate uniformly porous polymer films. Similar porous films are also formed when a solution of the polymer in THF containing small amounts of water, is allowed to evaporate rapidly under air flow; this suggests that water droplets may be formed during the final stages of film formation. In the presence of added surfactants, the interface of water droplets could become lined with the surfactants and consequently the internal walls of the pores generated, upon removal of the water, could become decorated with the hydrophilic head groups of the surfactant molecules. In a series of carefully designed experiments, we have examined the effect of added surfactants, both anionic and cationic, on the formation of porous PMMA films; the films were prepared by evaporating a solution of the polymer in THF containing controlled amounts of aqueous surfactant solutions. We observed that the average size of the pores decreases with increasing surfactant concentration, while it increases with increasing amounts of added water. The size of the pores and their distribution were examined using AFM and IR imaging methods. Although IR imaging possessed inadequate resolution to confirm the presence of surfactants at the pore surface, exchange of the inorganic counterion, such as the sodium-ion of SDS, with suitable ionic organic dyes permitted the unequivocal demonstration of the presence of the surfactants at the interface by the use of confocal fluorescence microscopy.

Gel Sculpture: Moldable, Load-Bearing and Self-Healing Non-Polymeric Supramolecular Gel Derived from a Simple Organic Salt

An easy access to a library of simple organic salts derived from tert-butoxycarbonyl (Boc)-protected L-amino acids and two secondary amines (dicyclohexyl- and dibenzyl amine) are synthesized following a supramolecular synthon rationale to generate a new series of low molecular weight gelators (LMWGs). Out of the 12 salts that we prepared, the nitrobenzene gel of dicyclohexylammonium Boc-glycinate (GLY.1) displayed remarkable load-bearing, moldable and self-healing properties. These remarkable properties displayed by GLY.1 and the inability to display such properties by its dibenzylammonium counterpart (GLY.2) were explained using microscopic and rheological data. Single crystal structures of eight salts displayed the presence of a 1D hydrogen-bonded network (HBN) that is believed to be important in gelation. Powder X-ray diffraction in combination with the single crystal X-ray structure of GLY.1 clearly established the presence of a 1D hydrogen-bonded network in the xerogel of the nitrobenzene gel of GLY.1. The fact that such remarkable properties arising from an easily accessible (salt formation) small molecule are due to supramolecular (non-covalent) interactions is quite intriguing and such easily synthesizable materials may be useful in stress-bearing and other applications.

Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices

In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.

Fast Likelihood Computation in Speech Recognition using Matrices

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 Large Vocabulary Continuous Speech Recognition (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 1,138 work vocabulary RM1 task and 6,224 word vocabulary TIMIT task using Sphinx 3.7 system show that, for a typical case the matrix multiplication based approach leads to overall speedup of 46 % on RM1 task and 115 % for TIMIT task. Our low-rank approximation methods provide a way for trading off recognition accuracy for a further increase in computational performance extending overall speedups up to 61 % for RM1 and 119 % for TIMIT for an increase of word error rate (WER) from 3.2 to 3.5 % for RM1 and for no increase in WER for TIMIT. We also express pairwise Euclidean distance computation phase in Dynamic Time Warping (DTW) in terms of matrix multiplication leading to saving of approximately of computational operations. In our experiments using efficient implementation of matrix multiplication, this leads to a speedup of 5.6 in computing the pairwise Euclidean distances and overall speedup up to 3.25 for DTW.

Field extension code based dispersion matrices for coherently detected space-time shift keying

Motivated by the recent Coherent Space-Time Shift Keying (CSTSK) philosophy, we construct new dispersion matrices for rotationally invariant PSK signaling sets. Given a specific PSK signal constellation, the dispersion matrices of the existing CSTSK scheme were chosen by maximizing the mutual information over randomly generated sets of dispersion matrices. In this contribution we propose a general method for constructing a set of structured dispersion matrices for arbitrary PSK signaling sets using Field Extension (FE) codes and then study the attainable Symbol Error Rate (SER) performance of some example constructions. We demonstrate that the proposed dispersion scheme is capable of outperforming the existing dispersion arrangement at medium to high SNRs.

Structured Dispersion Matrices From Division Algebra Codes for Space-Time Shift Keying

We propose a novel method of constructing Dispersion Matrices (DM) for Coherent Space-Time Shift Keying (CSTSK) relying on arbitrary PSK signal sets by exploiting codes from division algebras. We show that classic codes from Cyclic Division Algebras (CDA) may be interpreted as DMs conceived for PSK signal sets. Hence various benefits of CDA codes such as their ability to achieve full diversity are inherited by CSTSK. We demonstrate that the proposed CDA based DMs are capable of achieving a lower symbol error ratio than the existing DMs generated using the capacity as their optimization objective function for both perfect and imperfect channel estimation.

Evaluation of microwave assisted grafted sago starch as controlled release polymeric carrier

In the present investigation an attempt has been made to develop a new co-polymeric material for controlled release tablet formulations. The acrylamide grafting was successfully performed on the backbone of sago starch. The modified starch was tested for acute toxicity and drug-excipient compatibility study. The grafted material was used in making of controlled release tablets of lamivudine. The formulations were evaluated for physical characteristics such as hardness, friability, %drug content and weight variations. The in vitro release study showed that the optimized formulation exhibited highest correlation (R) value in case of Higuchi model and the release mechanism of the optimized formulation predominantly exhibited combination of diffusion and erosion process. There was a significant difference in the pharmacokinetic parameters (T-max, C-max, AUC, V-d, T-1/2 and MDT) of the optimized formulation as compared to the marketed conventional tablet Lamivir (R) was observed. The pharmacokinetics parameters were showed controlled pattern and better bioavailability. The optimized formulation exhibited good stability and release profile at the accelerated stability conditions. (c) 2013 Elsevier B.V. All rights reserved.

A novel photodegradable hyperbranched polymeric photoresist

We report the first synthesis of a photodegradable hyperbranched polyacetal, wherein every repeat unit carries a photo-labile 2-nitro-benzyloxy moiety. The pristine HBP serves as a positive photoresist to create micron-size patterns; furthermore, by changing the terminal groups to dipropargyl acetal, clickable photo-patterned substrates can be generated.

Burst error correction using partial fourier matrices and block sparse representation

There is a strong relation between sparse signal recovery and error control coding. It is known that burst errors are block sparse in nature. So, here we attempt to solve burst error correction problem using block sparse signal recovery methods. We construct partial Fourier based encoding and decoding matrices using results on difference sets. These constructions offer guaranteed and efficient error correction when used in conjunction with reconstruction algorithms which exploit block sparsity.

Lipschitz Correspondence between Metric Measure Spaces and Random Distance Matrices

Given a metric space with a Borel probability measure, for each integer N, we obtain a probability distribution on N x N distance matrices by considering the distances between pairs of points in a sample consisting of N points chosen independently from the metric space with respect to the given measure. We show that this gives an asymptotically bi-Lipschitz relation between metric measure spaces and the corresponding distance matrices. This is an effective version of a result of Vershik that metric measure spaces are determined by associated distributions on infinite random matrices.

Perovskite ceramic nanoparticles in polymer composites for augmenting bone tissue regeneration

There is increasing interest in the use of nanoparticles as fillers in polymer matrices to develop biomaterials which mimic the mechanical, chemical and electrical properties of bone tissue for orthopaedic applications. The objective of this study was to prepare poly(epsilon-caprolactone) (PCL) nanocomposites incorporating three different perovskite ceramic nanoparticles, namely, calcium titanate (CT), strontium titanate (ST) and barium titanate (BT). The tensile strength and modulus of the composites increased with the addition of nanoparticles. Scanning electron microscopy indicated that dispersion of the nanoparticles scaled with the density of the ceramics, which in turn played an important role in determining the enhancement in mechanical properties of the composite. Dielectric spectroscopy revealed improved permittivity and reduced losses in the composites when compared to neat PCL. Nanofibrous scaffolds were fabricated via electrospinning. Induction coupled plasma-optical emission spectroscopy indicated the release of small quantities of Ca+2, Sr+2, Ba+2 ions from the scaffolds. Piezo-force microscopy revealed that BT nanoparticles imparted piezoelectric properties to the scaffolds. In vitro studies revealed that all composites support osteoblast proliferation. Expression of osteogenic genes was enhanced on the nanocomposites in the following order: PCL/CT>PCL/ST>PCL/BT>PCL. This study demonstrates that the use of perovskite nanoparticles could be a promising technique to engineer better polymeric scaffolds for bone tissue engineering.

Synthesis and crystal structure of copper (II) uracil ternary polymeric complex with 1,10-phenanthroline along with the Hirshfeld surface analysis of the metal binding sites for the uracil ligand

The study of models for ``metal-enzyme-substrate'' interaction has been a proactive area of research owing to its biological and pharmacological importance. In this regard the ternary copper uracil complex with 1,10-phenanthroline represents metal-enzyme-substrate system for DNA binding enzymes. The synthesis of the complex, followed by slow evaporation of the reaction mixture forms two concomitant solvatomorph crystals viz., {Cu(phen)(mu-ura)(H2O)](n)center dot H2O (1a)} and {Cu(phen)(mu-ura)(H2O)](n)center dot CH3OH (1b)}. Both complexes are structurally characterized, while elemental analysis, IR and EPR spectra were recorded for 1b (major product). In both complexes, uracil coordinates uniquely via N1 and N3 nitrogen atom acting as a bidentate bridging ligand forming a 1-D polymer. The two solvatomorphs were quantitatively analyzed for the differences with the aid of Hirshfeld surface analysis. (C) 2014 Elsevier B.V. All rights reserved.