Application of artificial intelligence for the assessment of the status of power transformers

The Dissolved Gas Analysis (DGA) a non destructive test procedure, has been in vogue for a long time now, for assessing the status of power and related transformers in service. An early indication of likely internal faults that may exist in Transformers has been seen to be revealed, to a reasonable degree of accuracy by the DGA. The data acquisition and subsequent analysis needs an expert in the concerned area to accurately assess the condition of the equipment. Since the presence of the expert is not always guaranteed, it is incumbent on the part of the power utilities to requisition a well planned and reliable artificial expert system to replace, at least in part, an expert. This paper presents the application of Ordered Ant Mner (OAM) classifier for the prediction of involved fault. Secondly, the paper also attempts to estimate the remaining life of the power transformer as an extension to the elapsed life estimation method suggested in the literature.

Inter-helical Interactions in Membrane Proteins: Analysis Based on the Local Backbone Geometry and the Side Chain Interactions

The availability of a significant number of the Structures of helical membrane proteins has prompted us to investigate the mode of helix-helix packing. In the present study, we have considered a dataset of alpha-helical membrane proteins representing Structures solved from all the known superfamilies. We have described the geometry of all the helical residues in terms of local coordinate axis at the backbone level. Significant inter-helical interactions have been considered as contacts by weighing the number of atom-atom contacts, including all the side-chain atoms. Such a definition of local axis and the contact criterion has allowed us to investigate the inter-helical interaction in a systematic and quantitative manner. We show that a single parameter (designated as alpha), which is derived from the parameters representing the Mutual orientation of local axes, is able to accurately Capture the details of helix-helix interaction. The analysis has been carried Out by dividing the dataset into parallel, anti-parallel, and perpendicular orientation of helices. The study indicates that a specific range of alpha value is preferred for interactions among the anti-parallel helices. Such a preference is also seen among interacting residues of parallel helices, however to a lesser extent. No such preference is seen in the case of perpendicular helices, the contacts that arise mainly due to the interaction Of Surface helices with the end of the trans-membrane helices. The Study Supports the prevailing view that the anti-parallel helices are well packed. However, the interactions between helices of parallel orientation are non-trivial. The packing in alpha-helical membrane proteins, which is systematically and rigorously investigated in this study, may prove to be useful in modeling of helical membrane proteins.

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

PVA-PSSA Membrane with Interpenetrating Networks and its Methanol Crossover Mitigating Effect in DMFCs

A membrane with interpenetrating networks between poly(vinyl alcohol) (PVA) and poly(styrene sulfonic acid) (PSSA) coupled with a high proton conductivity is realized and evaluated as a proton exchange membrane electrolyte for a direct methanol fuel cell (DMFC). Its reduced methanol permeability and improved performance in DMFCs suggest the new blend as an alternative membrane to Nafion membranes. The membrane has been characterized by powder X-ray diffraction, scanning electron microscopy, time-modulated differential scanning calorimetry, and thermogravimetric analysis in conjunction with its mechanical strength. The maximum proton conductivity of 3.3×10−2 S/cm for the PVA–PSSA blend membrane is observed at 373 K. From nuclear magnetic resonance imaging and volume localized spectroscopy experiments, the PVA–PSSA membrane has been found to exhibit a promising methanol impermeability, in DMFCs. On evaluating its utility in a DMFC, it has been found that a peak power density of 90 mW/cm2 at a load current density of 320 mA/cm2 is achieved with the PVA–PSSA membrane compared to a peak power density of 75 mW/cm2 at a load current density of 250 mA/cm2 achievable for a DMFC employing Nafion membrane electrolyte while operating under identical conditions; this is attributed primarily to the methanol crossover mitigating property of the PVA–PSSA membrane.

Energy harvesting using ionic electro-active polymer thin films with Ag-based electrodes

In this paper we employ the phenomenon of bending deformation induced transport of cations via the polymer chains in the thickness direction of an electro-active polymer (EAP)-metal composite thin film for mechanical energy harvesting. While EAPs have been applied in the past in actuators and artificial muscles, promising applications of such materials in hydrodynamic and vibratory energy harvesting are reported in this paper. For this, functionalization of EAPs with metal electrodes is the key factor in improving the energy harvesting efficiency. Unlike Pt-based electrodes, Ag-based electrodes have been deposited on an EAP membrane made of Nafion. The developed ionic metal polymer composite (IPMC) membrane is subjected to a dynamic bending load, hydrodynamically, and evaluated for the voltage generated against an external electrical load. An increase of a few orders of magnitude has been observed in the harvested energy density and power density in air, deionized water and in electrolyte solutions with varying concentrations of sodium chloride (NaCl) as compared to Pt-based IPMC performances reported in the published literature. This will have potential applications in hydrodynamic and residual environmental energy harvesting to power sensors and actuators based on micro-andn nano-electro-mechanical systems (MEMS and NEMS) for biomedical,maerospace and oceanic applications.

Effects of membrane channel-forming polypeptides on mitochondrial oxidative phosphorylation. A comparison of alamethicin, gramicidin A, melittin and tetraacetyl melittin

Transmembrane channel-forming polypeptides can function as uncouplers of mitochondrial oxidative phosphorylation. The observed effects are dependent on the phosphate ion (Pi) concentration in the medium. At low Pi (2.5 mM) the order of uncoupling efficiencies is gramicidin A much greater than alamethicin greater than tetraacetyl melittin greater than melittin. The remarkably high activity of gramicidin A suggests insertion of preformed channel dimers into the membrane. It is also suggested that lipid phase association of peptides is necessary in the other cases. At Pi = 100 mM inhibitory effects are observed for alamethicin and tetraacetyl melittin. Less pronounced inhibition is seen for melittin, while no such effect is noted for gramicidin A. The site of inhibition is shown to be complex IV, and the differences in the behavior of the peptides are rationalized in terms of channel structures.

Effects of membrane channel-forming polypeptides on mitochondrial oxidative phosphorylation. A comparison of alamethicin, gramicidin A, melittin and tetraacetyl melittin.

Transmembrane channel-forming polypeptides can function as uncouplers of mitochondrial oxidative phosphorylation. The observed effects are dependent on the phosphate ion (Pi) concentration in the medium. At low Pi (2.5 mM) the order of uncoupling efficiencies is gramicidin A much greater than alamethicin greater than tetraacetyl melittin greater than melittin. The remarkably high activity of gramicidin A suggests insertion of preformed channel dimers into the membrane. It is also suggested that lipid phase association of peptides is necessary in the other cases. At Pi = 100 mM inhibitory effects are observed for alamethicin and tetraacetyl melittin. Less pronounced inhibition is seen for melittin, while no such effect is noted for gramicidin A. The site of inhibition is shown to be complex IV, and the differences in the behavior of the peptides are rationalized in terms of channel structures.

Investigation of true remnant polarization response in heterostructured artificial biferroics

Epitaxial bilayered thin films composed of ferromagnetic La0.6Sr0.4MnO3 and ferroelectric 0.7Pb (Mg1/3Nb2/3)O3-0.3(PbTiO3) were fabricated on LaAlO3 (100) substrates by pulsed laser ablation. Ferroelectric, ferromagnetic and magneto-dielectric characterizations performed earlier indicated the possible existence of strain-mediated magneto-electric coupling in these biferroic heterostructures. In order to investigate their true remnant polarization characteristics, usable in devices, room-temperature polarization versus electric field, positive-up negative-down (PUND) pulse polarization studies and remnant hysteresis measurements were carried out. The PUND and remnant hysteresis measurements revealed the significant contribution of the non-remnant component in the observed polarization hysteresis response of these heterostructures. (C) 2010 Published by Elsevier Ltd

Zervamicins, a structurally characterised peptide model for membrane ion channels

Voltage dependent membrane channels are formed by the zervamicins, a group of α-aminoisobutyric acid containing peptides. The role of polar residues like Thr, Gln and Hyp in promoting helical bundle formation is established by dramatically reduced channel lifetimes for a synthetic apolar analog. Crystal structures of Leu1-zervamicin reveal association of bent helices. Polar contacts between convex faces result in an ‘hour glass’ like arrangement of an aqueous channel with a central constriction. The structure suggests that gating mechanisms may involve movement of the Gln11 carboxamide group. Gln3 may play a role in modulating the size of the channel mouth.

Synthesis of neoglycopeptides and analyses of their biodistributionin vivo to identify tissue specific uptake and novel putative membrane lectins

Complex typeN-linked oligosaccharides derived from fetuin, fibrinogen and thyroglobulin were coupled to acetyltyrosine affording a series of neoglycopeptides with retention of terminal structures and the beta-anomeric configuration of their reducing endN-acetylglycosamine residue. The neoglycopeptides thus synthesized could be labelled to high specific activities with125I in the aromatic side chain of tyrosine. Analysis of the fate of these neoglycopeptides in conjunction with inhibition with asialofetuin and oligosaccharides of defined structure in micein vivo revealed the uptake of galactosylated biantennary compound by kidneys, in addition to the known itinerary of triantennary galactosylated complex oligosaccharide from fetuin to liver and the galactosylated biantennary chain with fucosylation in the core to bone marrows. On the other hand, the agalacto, aglucosamino biantennary chains with and without fucosylation in the core region are taken up by submaxillary glands while the conserved trimannosyl core with fucose is primarily concentrated in stomach tissue. These studies thus define new routes for the uptake of complexN-linked glycans and also subserve to identify lectins presumably involved in their recognition.

Wave propagation in a micropolar fluid contained in a visco-elastic membrane

The aim of the paper is to investigate the propagation of a pulse in a micropolar fluid contained in a visco-elastic membrane. It was undertaken with a view to study how closely we can approximate the flow of blood in arteries by the above model. We find that for large Reynolds number, the effect of micropolarity is hardly perceptible, whereas for small Reynolds numbers it is of considerable importance.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Frequency-Dependent Viscosity of Membrane Solutions

It is shown that dilute suspensions of membranes have strongly frequency-dependent viscosities. This behaviour should be seen in a variety of measurements such as capillary flow, mechanical impedance and ultrasound damping.