Thermo-chemical interpretation of polymer degradation

A correlation has been established between the heat of depolymerization (DeltaH) of vinyl polymers for going from solid polymer state to gaseous monomer state and the activation energy (E) of degradation. On this basis it has been shown that the rate controlling step in the degradation lies in the initiation step. Attempt has been made to correlate theE and DeltaH with glass transition temperature (Tg) and melting temperature (Tm) of the polymers.[/ p]

On quasi-degeneracies in plate vibration problems

In plotting the variation of frequencies with geometric parameters such as side ratio, skew angle, thickness taper, etc. in detailed studies of the vibration characteristics of plates, situations are encountered such as crossing of the frequency curves or the tendency of these curves to come close together and veer away from each other. These have been generally referred to as “frequency crossings” and “transitions” respectively. The latter may preferably be referred to as “quasi-degeneracies”. In the literature there appears to be some ambiguity in the analysis and interpretation of these features. In this paper, a clarification of some of these questions as regards rectangular and skew plates is presented by making use of concepts from physics dealing with molecular vibrations.

Geometrical interpretation of Inönü-Wigner contractions

The Inönü-Wigner contractions which interrelate the Lie algebras of the isometry groups of metric spaces are discussed with reference to deformations of the absolutes of the spaces. A general formula is derived for the Lie algebra commutation relations of the isometry group for anyN-dimensional metric space. These ideas are illustrated by a discussion of important particular cases, which interrelate the four-dimensional de Sitter, Poincaré, and Galilean groups.

Application of molecular orbital theory to the interpretation of x-ray absorption spectra of platinum complexes

X-ray LIII-absorption edges of platinum in nine octahedral complexes have been recorded using a bent crystal spectrograph. The edge features of the discontinuities have been interpreted with the help of qualitative molecular orbital diagrams. A correlation between the energy separation of the first two absorption maxima and the spectrochemical series of the ligands has been arrived at.

Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

Fusion of Multisensor Data:Review and Comparative Analysis

Image fusion is a formal framework which is expressed as means and tools for the alliance of multisensor, multitemporal, and multiresolution data. Multisource data vary in spectral, spatial and temporal resolutions necessitating advanced analytical or numerical techniques for enhanced interpretation capabilities. This paper reviews seven pixel based image fusion techniques - intensity-hue-saturation, brovey, high pass filter (HPF), high pass modulation (HPM), principal component analysis, fourier transform and correspondence analysis.Validation of these techniques on IKONOS data (Panchromatic band at I m spatial resolution and Multispectral 4 bands at 4 in spatial resolution) reveal that HPF and HPM methods synthesises the images closest to those the corresponding multisensors would observe at the high resolution level.

Analysis of short interproton distances in proline peptides as a guide in the interpretation of nuclear overhauser effects

The conformational dependence of interproton distances in model proline peptides has been investigated in order to facilitate interpretation of the results of Nuclear Overhauser Effect (NOE) studies on such peptides. For this purpose two model systems, namely, Ac-Pro-NHMe and Ac-Pro-X-NHMe have been chosen and used. In the former, short interproton distances detectable in NOE experiments permit a clear distinction between conformations with Pro ψ = -300 (helical region) and those in which ψ is around 1200 (polyproline region). For the latter, the variation of distances between the protons of methyl amide and the Pro ring have been studied by superimposing on the Ramachandran map in the (φ3, ψ3) plane. The results show that β-turns and non-β-turn conformations can be readily distinguished from NOE data and such long range NOEs should be detectable for specific non-β-turn conformations. NOEs involving Cβ and Cγ protons are particularly sensitive to the state of pyrrolidine ring puckering.

Biphenyl ethers conjugated CdSe/ZnS core/shell quantum dots and interpretation of the mechanism of amyloid fibril disruption

The biphenyl ethers (BPEs) are the potent inhibitors of TTR fibril formation and are efficient fibril disrupter. However, the mechanism by which the fibril disruption occurs is yet to be fully elucidated. To gain insight into the mechanism, we synthesized and used a new QD labeled BPE to track the process of fibril disruption. Our studies showed that the new BPE-QDs bind to the fiber uniformly and has affinity and specificity for TTR fiber and disrupted the pre-formed fiber at a relatively slow rate. Based on these studies we put forth the probable mechanism of fiber disruption by BPEs. Also, we show here that the BPE-QDs interact with high affinity to the amyloids of A beta(42), lysozyme and insulin. The potential of BPE-QDs in the detection of senile plaque in the brain of transgenic Alzheimer's mice has also been explored. (C) 2010 Elsevier Ltd. All rights reserved.

Demixing of severely overlapped H-1 NMR resonances and interpretation of anomalous intensity pattern of dipolar coupled A(3) spins in a weakly aligning medium

We report a single C-13 spin edited selective proton-proton correlation experiment to decipher overcrowded 13C coupled proton NMR spectra of weakly dipolar coupled spin systems. The experiment unravels the masked C-13 satellites in proton spectrum and permits the measurement of one bond carbon-proton residual dipolar couplings in I3S and for each diastereotopic proton in I2S groups. It also provides all the possible homonuclear proton-proton residual couplings which are otherwise difficult to extract from the broad and featureless one dimensional H-1 spectrum, in addition to enantiodifferentiation in a chiral molecule. Employment of heteronuclear (C-13) decoupling in the evolution period results in complete demixing of overlapped signals from enantiomers. The observed anomalous intensity pattern in strongly dipolar coupled methyl protons in methyl selective correlation experiment has been interpreted using polarization operator formalism. (C) 2010 Elsevier Inc. All rights reserved.

Characterization of defects in gallium arsenide

It is well-known that the properties of semiconductor materials including gallium arsenide are controlled by defects and impurities. The characterization of these defects is important not only for better understanding of the solid state phenomena but also for improved reliability and performance of electronic devices. We have been investigating the defects in gallium arsenide for several years using deep level transient spectroscopy, photoconductivity, transient photoconductivity, photoluminescence etc. Results drawn from our recent studies are presented here to illustrate some of the problems concerning transition metal impurities, process-induced defects, occurrence of intracentre transitions and metastability of deep levels in gallium arsenide.

A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks

Our study concerns an important current problem, that of diffusion of information in social networks. This problem has received significant attention from the Internet research community in the recent times, driven by many potential applications such as viral marketing and sales promotions. In this paper, we focus on the target set selection problem, which involves discovering a small subset of influential players in a given social network, to perform a certain task of information diffusion. The target set selection problem manifests in two forms: 1) top-k nodes problem and 2) lambda-coverage problem. In the top-k nodes problem, we are required to find a set of k key nodes that would maximize the number of nodes being influenced in the network. The lambda-coverage problem is concerned with finding a set of k key nodes having minimal size that can influence a given percentage lambda of the nodes in the entire network. We propose a new way of solving these problems using the concept of Shapley value which is a well known solution concept in cooperative game theory. Our approach leads to algorithms which we call the ShaPley value-based Influential Nodes (SPINs) algorithms for solving the top-k nodes problem and the lambda-coverage problem. We compare the performance of the proposed SPIN algorithms with well known algorithms in the literature. Through extensive experimentation on four synthetically generated random graphs and six real-world data sets (Celegans, Jazz, NIPS coauthorship data set, Netscience data set, High-Energy Physics data set, and Political Books data set), we show that the proposed SPIN approach is more powerful and computationally efficient. Note to Practitioners-In recent times, social networks have received a high level of attention due to their proven ability in improving the performance of web search, recommendations in collaborative filtering systems, spreading a technology in the market using viral marketing techniques, etc. It is well known that the interpersonal relationships (or ties or links) between individuals cause change or improvement in the social system because the decisions made by individuals are influenced heavily by the behavior of their neighbors. An interesting and key problem in social networks is to discover the most influential nodes in the social network which can influence other nodes in the social network in a strong and deep way. This problem is called the target set selection problem and has two variants: 1) the top-k nodes problem, where we are required to identify a set of k influential nodes that maximize the number of nodes being influenced in the network and 2) the lambda-coverage problem which involves finding a set of influential nodes having minimum size that can influence a given percentage lambda of the nodes in the entire network. There are many existing algorithms in the literature for solving these problems. In this paper, we propose a new algorithm which is based on a novel interpretation of information diffusion in a social network as a cooperative game. Using this analogy, we develop an algorithm based on the Shapley value of the underlying cooperative game. The proposed algorithm outperforms the existing algorithms in terms of generality or computational complexity or both. Our results are validated through extensive experimentation on both synthetically generated and real-world data sets.