An unusual distribution of glucose-6-phosphate dehydrogenase deficiency of south Indian newborn population.

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is seen at a higher frequency in many national and ethnic groups in areas of current or former malaria endemicity. A screening programme undertaken to evaluate the gene frequencies for this deficiency in the highly inbred South Indian population of Karnataka revealed that of the 5140 neonates screened, 7.8% were G6PD deficient with no correlation between the reported level of inbreeding and enzyme deficiency. An interesting finding was the equal number of male (198) and female (207) individuals, with G6PD activity of less than 3 IU. The possible implications of this finding with regard to the expression of G6PD gene is discussed.

Calcium ionophore, A23187 and its amino acid complexes: spectroscopic and molecular modeling studies.

The circular dichroism, fluorescence, Nuclear Magnetic Resonance and BLM conductance studies indicate that A23187 forms a stable complex with amino acids at low ionophore concentrations (<10(-4)M). However, A23187 prefers to be in a dimeric structure with no significant binding to amino acids, at concentrations higher than 10(-4)M. It was also observed that at lower concentrations, at which the amino acids bind to the ionophore, the affinity for calcium ions was several orders of magnitude lower than that at higher ionophore concentrations. We have also conducted molecular modeling studies to examine the structure of the A23187 dimer and its amino acid complexes. The results of these modeling studies strongly support our experimental results and validate the formation of a hydrogen bonded and energetically stable A23187 dimer and its amino acid complexes.

Characterization of a variant glucose-6-phosphate dehydrogenase from the south Indian population.

Glucose-6-phosphate dehydrogenase (G6PD) is coded by a gene on the X-chromosome. Earlier studies have shown that the South Indian population has a high incidence of this enzyme deficiency. The electrophoretic mobility, pH optimum and the K-m values for G6PD from normal and variant individuals were identical. However, the specific activity of the variant enzyme was 8 times less compared to the value of the normal enzyme. Western blot analysis of partially purified G6PD from normal and variant individuals performed using equal amounts of total protein showed that the variant protein was 3 times less in concentration. Similar analysis performed using protein corresponding to equal enzyme activity units in the normal and variant samples showed that the variant enzyme was 2.25 times less efficient compared to the normal enzyme. RNA dot blot analysis using full length G6PD cDNA probe (PGDT5B, a kind gift from Prof. L Luzzatto) revealed that lymphocytes from normal and variant individuals had equal amounts of G6PD specific mRNA.

Multiscale Modeling Approach to Acoustic Emission during Plastic Deformation

We address the long-standing problem of the origin of acoustic emission commonly observed during plastic deformation. We propose a framework to deal with the widely separated time scales of collective dislocation dynamics and elastic degrees of freedom to explain the nature of acoustic emission observed during the Portevin-Le Chatelier effect. The Ananthakrishna model is used as it explains most generic features of the phenomenon. Our results show that while acoustic emission bursts correlated with stress drops are well separated for the type C serrations, these bursts merge to form nearly continuous acoustic signals with overriding bursts for the propagating type A bands.

Modeling and design of a solar thermal system for hybrid cooking application

This paper proposes a hybrid solar cooking system where the solar energy is brought to the kitchen. The energy source is a combination of the solar thermal energy and the Liquefied Petroleum Gas (LPG) that is in common use in kitchens. The solar thermal energy is transferred to the kitchen by means of a circulating fluid. The transfer of solar heat is a twofold process wherein the energy from the collector is transferred first to an intermediate energy storage buffer and the energy is subsequently transferred from the buffer to the cooking load. There are three parameters that are controlled in order to maximize the energy transfer from the collector to the load viz, the fluid flow rate from collector to buffer, fluid flow rate from buffer to load and the diameter of the pipes. This is a complex multi energy domain system comprising energy flow across several domains such as thermal, electrical and hydraulic. The entire system is modeled using the bond graph approach with seamless integration of the power flow in these domains. A method to estimate different parameters of the practical cooking system is also explained. Design and life cycle costing of the system is also discussed. The modeled system is simulated and the results are validated experimentally. (C) 2010 Elsevier Ltd. All rights reserved.

Water-modeling study of the surface disturbances in continuous slab caster

The present work is based on four static molds using nozzles of different port diameter, port angle, and immersion depth. It has been observed that the meniscus is wavy. The wave amplitude shows a parabolic variation with the nozzle exit velocity. The dimensionless amplitude is found to vary linearly with the Froude number. Vortex formation and bubble entrainment by the wave occurs at the meniscus beyond a critical flow rate, depending upon the nozzle configuration, immersion depth, and the mold aspect ratio.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

Modeling Of Hydrolytic Polymerization In A Semibatch Nylon 6 Reactor

Hydrolytic polymerization of caprolactam to Nylon 6 in a semibatch reactor is carried out by heating a mixture of water and caprolactam. Evaporation of volatiles caused by heating results in a pressure build-up. After the pressure reaches a predetermined value, vapors are vented to keep the pressure constant for some time, and thereafter, to lower the pressure to a value slightly above atmospheric in a preprogrammed manner. The characteristics of the polymer are determined by the chemical reactions and the vaporization of water and caprolactam. The semibatch operation has been simulated and the predictions have been compared with industria data. The observed temperature and pressure histories were predicted with a fair degree of accuracy. It was found that the predictions of the degree of polymerization however are sensitive to the vapor-liquid equilibrium relations. A comparison with an earlier model, which neglected mass transfer resistance, indicates that simulation using the VLE data of Giori and Hayes and accounting for mass transfer resistance is more reliable.

Modes of binding of 2'-AMP to RNase T1. A computer modeling study

The modes of binding of adenosine 2'-monophosphate (2'-AMP) to the enzyme ribonuclease (RNase) T1 were determined by computer modelling studies. The phosphate moiety of 2'-AMP binds at the primary phosphate binding site. However, adenine can occupy two distinct sites--(1) The primary base binding site where the guanine of 2'-GMP binds and (2) The subsite close to the N1 subsite for the base on the 3'-side of guanine in a guanyl dinucleotide. The minimum energy conformers corresponding to the two modes of binding of 2'-AMP to RNase T1 were found to be of nearly the same energy implying that in solution 2'-AMP binds to the enzyme in both modes. The conformation of the inhibitor and the predicted hydrogen bonding scheme for the RNase T1-2'-AMP complex in the second binding mode (S) agrees well with the reported x-ray crystallographic study. The existence of the first mode of binding explains the experimental observations that RNase T1 catalyses the hydrolysis of phosphodiester bonds adjacent to adenosine at high enzyme concentrations. A comparison of the interactions of 2'-AMP and 2'-GMP with RNase T1 reveals that Glu58 and Asn98 at the phosphate binding site and Glu46 at the base binding site preferentially stabilise the enzyme-2'-GMP complex.

Neural network modeling of associative memory: Beyond the Hopfield model

A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

Image reconstruction from incomplete projections data: A multiresolution modeling approach

Computerized tomography is an imaging technique which produces cross sectional map of an object from its line integrals. Image reconstruction algorithms require collection of line integrals covering the whole measurement range. However, in many practical situations part of projection data is inaccurately measured or not measured at all. In such incomplete projection data situations, conventional image reconstruction algorithms like the convolution back projection algorithm (CBP) and the Fourier reconstruction algorithm, assuming the projection data to be complete, produce degraded images. In this paper, a multiresolution multiscale modeling using the wavelet transform coefficients of projections is proposed for projection completion. The missing coefficients are then predicted based on these models at each scale followed by inverse wavelet transform to obtain the estimated projection data.

DockYard-a repository to assist modeling of protein-protein docking

In the absence of interlogs, building docking models is a time intensive task, involving generation of a large pool of docking decoys followed by refinement and screening to identify near native docking solutions. This limits the researcher interested in building docking methods with the choice of benchmarking only a limited number of protein complexes. We have created a repository called dockYard (http://pallab.serc.iisc.ernet.in/dockYard), that allows modelers interested in protein-protein interaction to access large volume of information on protein dimers and their interlogs, and also download decoys for their work if they are interested in building modeling methods. dockYard currently offers four categories of docking decoys derived from: Bound (native dimer co-crystallized), Unbound (individual subunits are crystallized, as well as the target dimer), Variants (match the previous two categories in at least one subunit with 100% sequence identity), and Interlogs (match the previous categories in at least one subunit with >= 90% or >= 50% sequence identity). The web service offers options for full or selective download based on search parameters. Our portal also serves as a repository to modelers who may want to share their decoy sets with the community.

Modeling of a reacting nanofilm on a composite substrate

This article provides a detailed computational analysis of the reaction of dense nanofilms and the heat transfer characteristics on a composite substrate. Although traditional energetic compounds based on organic materials have similar energy per unit weight, non-organic material in nanofilm configuration offers much higher energy density and higher flame speed. The reaction of a multilayer thin film of aluminum and copper oxide has been studied by varying the substrate material and thicknesses. The numerical analysis of the thermal transport of the reacting film deposited on the substrate combined a hybrid approach in which a traditional two-dimensional black box theory was used in conjunction with the sandwich model to estimate the appropriate heat flux on the substrate accounting for the heat loss to the surroundings. A procedure to estimate this heat flux using stoichiometric calculations is provided. This work highlights two important findings. One is that there is very little difference in the temperature profiles between a single substrate of silica and a composite substrate of silicon silica. Secondly, with increase in substrate thickness, the quenching effect is progressively diminished at a given speed. These findings show that the composite substrate is effective and that the average speed and quenching of flames depend on the thickness of the silica substrate, and can be controlled by a careful choice of the substrate configuration. (C) 2011 Elsevier Ltd. All rights reserved.

Sibling rivalry between seeds within a fruit: Some population genetic models

Competition between seeds within a fruit for parental resources is described using one-locus-two-allele models. While a �normal� allele leads to an equitable distribution of resources between seeds (a situation which also corresponds to the parental optimum), the �selfish� allele is assumed to cause the seed carrying it to usurp a higher proportion of the resources. The outcome of competition between �selfish� alleles is also assumed to lead to an asymmetric distribution of resources, the �winner� being chosen randomly. Conditions for the spread of an initially rare selfish allele and the optimal resource allocation corresponding to the evolutionarily stable strategy, derived for species with n-seeded fruits, are in accordance with expectations based on Hamilton�s inclusive fitness criteria. Competition between seeds is seen to be most intense when there are only two seeds, and decreases with increasing number of seeds, suggesting that two-seeded fruits would be rarer than one-seeded or many-seeded ones. Available data from a large number of plant species are consistent with this prediction of the model.