<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Selvaraj, Kaliaperumal</style></author><author><style face="normal" font="default" size="100%">Kurian, Reshmi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dependence of Si-29 NMR chemical shielding properties of precursor silicate species, Q(0) on its local structure at the pre-nucleation stages of zeolite synthesis - a DFT based computational correlation</style></title><secondary-title><style face="normal" font="default" size="100%">Microporous and Mesoporous Materials</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Ab initio method</style></keyword><keyword><style  face="normal" font="default" size="100%">Density Functional Theory (DFT)</style></keyword><keyword><style  face="normal" font="default" size="100%">Electron density</style></keyword><keyword><style  face="normal" font="default" size="100%">NBO analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Perturbation theory</style></keyword><keyword><style  face="normal" font="default" size="100%">Q(0) silicate species</style></keyword><keyword><style  face="normal" font="default" size="100%">Si-29 NMR chemical shift</style></keyword><keyword><style  face="normal" font="default" size="100%">synthesis</style></keyword><keyword><style  face="normal" font="default" size="100%">zeolite</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1-3</style></number><publisher><style face="normal" font="default" size="100%">ELSEVIER SCIENCE BV</style></publisher><pub-location><style face="normal" font="default" size="100%">PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS</style></pub-location><volume><style face="normal" font="default" size="100%">122</style></volume><pages><style face="normal" font="default" size="100%">105-113</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The exploration for new zeolite structures with tailored framework architectures for enhanced catalytic applications requires the knowledge about their nucleation and crystallization at molecular level. Nuclear magnetic resonance (NMR) is one of the most widely tried techniques to understand this. However, by NMR, it is difficult to accurately assign the molecular level precursor silicate structures at the pre-nucleation stages of zeolite synthesis. Hence, understanding the chemical shielding of such precursor molecules using quantum mechanical (QM) computations is extremely useful. Alkali is a fundamental component in the alkali based hydrothermal zeolite synthesis and its nature plays a major role. In the present report, we attempt to understand the differences in the local structure of the primary building block such as Si(OH)(4) (Q(0) silicate species) due to the associated alkali and their influence on NMR chemical shielding properties. Present work reports the calculation of Si-29 NMIR isotropic chemical shifts of T species with different cations such as Na, K and Ca using density functional theory (DFT). Results of natural bonding orbital (NBO) analysis, Perturbation theory energy analysis and electron density iso-surfaces were employed to obtain a deeper insight about their influence on the chemical shielding and on zeolite synthesis. (C) 2009 Elsevier Inc. All rights reserved.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1-3</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;3.220&lt;/p&gt;</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dnyane, Pooja A.</style></author><author><style face="normal" font="default" size="100%">Puntambekar, Shraddha S.</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Method for identification of sensitive nodes in boolean models of biological networks</style></title><secondary-title><style face="normal" font="default" size="100%">IET Systems Biology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">biological networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Boolean functions</style></keyword><keyword><style  face="normal" font="default" size="100%">Boolean models</style></keyword><keyword><style  face="normal" font="default" size="100%">fly segment polarity network</style></keyword><keyword><style  face="normal" font="default" size="100%">human melanogenesis signalling network</style></keyword><keyword><style  face="normal" font="default" size="100%">perturbation methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Perturbation theory</style></keyword><keyword><style  face="normal" font="default" size="100%">physiological models</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">FEB</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">1-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Biological systems are often represented as Boolean networks and analysed to identify sensitive nodes which on perturbation disproportionately change a predefined output. There exist different kinds of perturbation methods: perturbation of function, perturbation of state and perturbation in update scheme. Nodes may have defects in interpretation of the inputs from other nodes and calculation of the node output. To simulate these defects and systematically assess their effect on the system output, two new function perturbations, referred to as not of function' and function of not', are introduced. In the former, the inputs are assumed to be correctly interpreted but the output of the update rule is perturbed; and in the latter, each input is perturbed but the correct update rule is applied. These and previously used perturbation methods were applied to two existing Boolean models, namely the human melanogenesis signalling network and the fly segment polarity network. Through mathematical simulations, it was found that these methods successfully identified nodes earlier found to be sensitive using other methods, and were also able to identify sensitive nodes which were previously unreported.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.048</style></custom4></record></records></xml>