Activation barriers for d.c. conductivity in ionic glasses: Classical calculations using the small-cluster approximation

A small-cluster approximation has been used to calculate the activation barriers for the d.c. conductivity in ionic glasses. The main emphasis of this approach is on the importance of the hitherto ignored polarization energy contribution to the total activation energy. For the first time it has been demonstrated that the d.c. conductivity activation energy can be calculated by considering ionic migration to a neighbouring vacancy in a smali cluster of ions consisting of face-sharing anion polyhedra. The activation energies from the model calculations have been compared with the experimental values in the case of highly modified lithium thioborate glasses.

Compressive tidal heating of a disk galaxy in a rich cluster

The restricted three-body method is used to model the effect of the mean tidal field of a cluster of galaxies on the internal dynamics of a disk galaxy falling into the cluster for the first time. In the model adopted the galaxy experiences a tidal field that is compressive within the core of the cluster. The planar random velocities of all components in the disk increase after the galaxy passes through the core of the cluster. The low-velocity dispersion gas clouds experience a relatively larger increase in random velocity than the hotter stellar components. The increase in planar velocities results in a strong anisotropy between the planar and vertical velocity dispersions. It is argued that this will make the disk unstable to the 'fire-hose instability' which leads to bending modes in the disk and which will thicken the disk slightly. The mean tidal fields in rich clusters were probably stronger during the epoch of cluster formation and relaxation than they are in present-day relaxed clusters.

Effect of Sorbate-Zeolite Interaction on Cluster Lifetime and Size of Sorbates: Xe in NaY

Molecular dynamics calculations are reported for Xe in sodium Y zeolite with varying strengths of sorbate-zeolite dispersion interaction. In the absence of any dispersion interaction between the sorbate and the zeolite, the presence of the zeolite has a purely geometrical role. Increase in the strength of the sorbate-zeolite interaction increases the monomer population and decreases the population of dimers and higher sized clusters. The lifetime of the monomers as well as dimers increases with the strength of the dispersion interaction. The observed variations in the lifetime and the population of the different sized clusters is explained in terms of the changes in the potential energy surface caused by the increase in the strength of the dispersion interaction.

A Feature-Based Solution to Forward Problem in Electrical Capacitance Tomography of Conductive Materials

A new feature-based technique is introduced to solve the nonlinear forward problem (FP) of the electrical capacitance tomography with the target application of monitoring the metal fill profile in the lost foam casting process. The new technique is based on combining a linear solution to the FP and a correction factor (CF). The CF is estimated using an artificial neural network (ANN) trained using key features extracted from the metal distribution. The CF adjusts the linear solution of the FP to account for the nonlinear effects caused by the shielding effects of the metal. This approach shows promising results and avoids the curse of dimensionality through the use of features and not the actual metal distribution to train the ANN. The ANN is trained using nine features extracted from the metal distributions as input. The expected sensors readings are generated using ANSYS software. The performance of the ANN for the training and testing data was satisfactory, with an average root-mean-square error equal to 2.2%.

Cloning and characterization of a cluster of genes coding for 5S rRNA and three tRNAs from Azospirillum lipoferum

A genomic library was constructed from a HindIII digest of Azospirillum lipoferum chromosomal DNA in the HindIII site of pUC19. From the library, a clone, pALH64, which showed strong hybridization with 3' end labeled A. lipoferum total tRNAs and which contains a 2.9 kb insert was isolated and restriction map of the insert established. The nucleotide sequence of a 490 bp HindIII-HincII subfragment containing a cluster of genes coding for 5S rRNA, tRNA(Val)(UAC), tRNA(Thr)(UGA) and tRNA(Lys)(UUU) has been determined. The gene organization is 5S rRNA (115 bp), spacer (10 bp), tRNA(Val) (76 bp), spacer (3 bp), tRNA(Thr) (76 bp), spacer (7 bp) and tRNA(Lys) (76 bp). Hybridization experiments using A. lipoferum total tRNAs and 5S rRNA with the cloned DNA probes revealed that all three tRNA genes and the 5S rRNA gene are expressed in vivo in the bacterial cells.

Dependence of the strength of interaction of carbon monoxide with transition metal clusters on the cluster size

The interaction of CO with Cu, Pd, and Ni at different coverages of the metals on solid substrates has been investigated by He II and core-level spectroscopies, after the nature of variation of the metal core-level binding energies with the coverage or the cluster size is established. The separation between the (1 pi + 5 sigma) and 4 sigma levels of CO increases with a decrease in the size of the metal clusters, accompanied by an increase in the desorption temperature. In the case of Cu, the intramolecular shakeup satellite of CO disappears on small clusters. More importantly, CO dissociates on small Ni clusters, clearly confirming that metal-CO interaction strength increases with a decrease in the cluster size.

An interesting feature of the vapour pressure curve

There exists a maximum in the products of the saturation properties such as T(p(c) - p) and p(T-c - T) in the vapour-liquid coexistence region for all liquids. The magnitudes of those maxima on the reduced coordinate system provide an insight to the molecular complexity of the liquid. It is shown that the gradients of the vapour pressure curve at temperatures where those maxima occur are directly given by simple relations involving the reduced pressures and temperatures at that point. A linear relation between the maximum values of those products of the form [p(r)(1 - T-r)](max) = 0.2095 - 0.2415 [T-r(1 - p(r))](max) has been found based on a study of 55 liquids ranging from non-polar monatomic cryogenic liquids to polar high boiling point liquids.

Essential dynamics and sidechain hydrogen bond cluster studies on eosinophil cationic protein

Eosinophil Cationic Protein (ECP) is a member of RNase A superfamily which carries out the obligatory catalytic role of cleaving RNA. It is involved in a variety of biological functions. Molecular dynamics simulations followed by essential dynamics analysis on this protein are carried out with the goal of gaining insights into the dynamical properties at atomic level. The top essential modes contribute to subspaces and to the transition phase. Further, the sidechain-sidechain/sidechain-mainchain hydrogen bond clusters are analyzed in the top modes, and compared with those of crystal structure. The role of residues identified by these methods is discussed in the context of concerted motion, structure and stability of the protein.

Optimal feature extraction for bilingual OCR

Feature extraction in bilingual OCR is handicapped by the increase in the number of classes or characters to be handled. This is evident in the case of Indian languages whose alphabet set is large. It is expected that the complexity of the feature extraction process increases with the number of classes. Though the determination of the best set of features that could be used cannot be ascertained through any quantitative measures, the characteristics of the scripts can help decide on the feature extraction procedure. This paper describes a hierarchical feature extraction scheme for recognition of printed bilingual (Tamil and Roman) text. The scheme divides the combined alphabet set of both the scripts into subsets by the extraction of certain spatial and structural features. Three features viz geometric moments, DCT based features and Wavelet transform based features are extracted from the grouped symbols and a linear transformation is performed on them for the purpose of efficient representation in the feature space. The transformation is obtained by the maximization of certain criterion functions. Three techniques : Principal component analysis, maximization of Fisher's ratio and maximization of divergence measure have been employed to estimate the transformation matrix. It has been observed that the proposed hierarchical scheme allows for easier handling of the alphabets and there is an appreciable rise in the recognition accuracy as a result of the transformations.

Very large array detection of radio recombination lines from the radio nucleus of NGC 253: Ionization by a weak active galactic nucleus, an obscured super star cluster, or a compact supernova remnant?

We have imaged the H92alpha and H75alpha radio recombination line (RRL) emissions from the starburst galaxy NGC 253 with a resolution of similar to4 pc. The peak of the RRL emission at both frequencies coincides with the unresolved radio nucleus. Both lines observed toward the nucleus are extremely wide, with FWHMs of similar to200 km s(-1). Modeling the RRL and radio continuum data for the radio nucleus shows that the lines arise in gas whose density is similar to10(4) cm(-3) and mass is a few thousand M., which requires an ionizing flux of (6-20) x 10(51) photons s(-1). We consider a supernova remnant (SNR) expanding in a dense medium, a star cluster, and also an active galactic nucleus (AGN) as potential ionizing sources. Based on dynamical arguments, we rule out an SNR as a viable ionizing source. A star cluster model is considered, and the dynamics of the ionized gas in a stellar-wind driven structure are investigated. Such a model is only consistent with the properties of the ionized gas for a cluster younger than similar to10(5) yr. The existence of such a young cluster at the nucleus seems improbable. The third model assumes the ionizing source to be an AGN at the nucleus. In this model, it is shown that the observed X-ray flux is too weak to account for the required ionizing photon flux. However, the ionization requirement can be explained if the accretion disk is assumed to have a big blue bump in its spectrum. Hence, we favor an AGN at the nucleus as the source responsible for ionizing the observed RRLs. A hybrid model consisting of an inner advection-dominated accretion flow disk and an outer thin disk is suggested, which could explain the radio, UV, and X-ray luminosities of the nucleus.

Strategies for Rescheduling Tightly-Coupled Parallel Applications in Multi-Cluster Grids

As computational Grids are increasingly used for executing long running multi-phase parallel applications, it is important to develop efficient rescheduling frameworks that adapt application execution in response to resource and application dynamics. In this paper, three strategies or algorithms have been developed for deciding when and where to reschedule parallel applications that execute on multi-cluster Grids. The algorithms derive rescheduling plans that consist of potential points in application execution for rescheduling and schedules of resources for application execution between two consecutive rescheduling points. Using large number of simulations, it is shown that the rescheduling plans developed by the algorithms can lead to large decrease in application execution times when compared to executions without rescheduling on dynamic Grid resources. The rescheduling plans generated by the algorithms are also shown to be competitive when compared to the near-optimal plans generated by brute-force methods. Of the algorithms, genetic algorithm yielded the most efficient rescheduling plans with 9-12% smaller average execution times than the other algorithms.

An Adaptive Feature Based Low Power Motion Estimation Algorithm

Motion Estimation is one of the most power hungry operations in video coding. While optimal search (eg. full search)methods give best quality, non optimal methods are often used in order to reduce cost and power. Various algorithms have been used in practice that trade off quality vs. complexity. Global elimination is an algorithm based on pixel averaging to reduce complexity of motion search while keeping performance close to that of full search. We propose an adaptive version of the global elimination algorithm that extracts individual macro-block features using Hadamard transform to optimize the search. Performance achieved is close to the full search method and global elimination. Operational complexity and hence power is reduced by 30% to 45% compared to global elimination method.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

Regional Flood Frequency Analysis using Two-level Clustering Approach

Clustering techniques are used in regional flood frequency analysis (RFFA) to partition watersheds into natural groups or regions with similar hydrologic responses. The linear Kohonen's self‐organizing feature map (SOFM) has been applied as a clustering technique for RFFA in several recent studies. However, it is seldom possible to interpret clusters from the output of an SOFM, irrespective of its size and dimensionality. In this study, we demonstrate that SOFMs may, however, serve as a useful precursor to clustering algorithms. We present a two‐level. SOFM‐based clustering approach to form regions for FFA. In the first level, the SOFM is used to form a two‐dimensional feature map. In the second level, the output nodes of SOFM are clustered using Fuzzy c‐means algorithm to form regions. The optimal number of regions is based on fuzzy cluster validation measures. Effectiveness of the proposed approach in forming homogeneous regions for FFA is illustrated through application to data from watersheds in Indiana, USA. Results show that the performance of the proposed approach to form regions is better than that based on classical SOFM.