An exploration framework to identify and track movement of cloud systems

We describe a framework to explore and visualize the movement of cloud systems. Using techniques from computational topology and computer vision, our framework allows the user to study this movement at various scales in space and time. Such movements could have large temporal and spatial scales such as the Madden Julian Oscillation (MJO), which has a spatial scale ranging from 1000 km to 10000 km and time of oscillation of around 40 days. Embedded within these larger scale oscillations are a hierarchy of cloud clusters which could have smaller spatial and temporal scales such as the Nakazawa cloud clusters. These smaller cloud clusters, while being part of the equatorial MJO, sometimes move at speeds different from the larger scale and in a direction opposite to that of the MJO envelope. Hitherto, one could only speculate about such movements by selectively analysing data and a priori knowledge of such systems. Our framework automatically delineates such cloud clusters and does not depend on the prior experience of the user to define cloud clusters. Analysis using our framework also shows that most tropical systems such as cyclones also contain multi-scale interactions between clouds and cloud systems. We show the effectiveness of our framework to track organized cloud system during one such rainfall event which happened at Mumbai, India in July 2005 and for cyclone Aila which occurred in Bay of Bengal during May 2009.

Analysis of network architectures for zigbee sensor clusters

We provide a comparative performance analysis of network architectures for beacon enabled Zigbee sensor clusters using the CSMA/CA MAC defined in the IEEE 802.15.4 standard, and organised as (i) a star topology, and (ii) a two-hop topology. We provide analytical models for obtaining performance measures such as mean network delay, and mean node lifetime. We find that the star topology is substantially superior both in delay performance and lifetime performance than the two-hop topology.

Cluster analysis of rainfall stations of the Indian peninsula

Principal component analysis is applied to derive patterns of temporal variation of the rainfall at fifty-three stations in peninsular India. The location of the stations in the coordinate space determined by the amplitudes of the two leading eigenvectors is used to delineate them into eight clusters. The clusters obtained seem to be stable with respect to variations in the grid of stations used. Stations within any cluster occur in geographically contiguous areas.

On the breakdown of the most probable distribution for mayer clusters

We present an analysis of the breakdown of the most probable approximation to the Mayer cluster size distribution for clusters of size comparable to the size of the system. This failure is illustrated by considering an ideal Bose gas for which exact volume dependent reducible cluster integrals are available.

Chlorinated Hypoelectronic Dimetallaborane Clusters: Synthesis, Characterization, and Electronic Structures of (eta(5)-C5Me5W)(2)B5HnClm (n=7, m=2 and n=8, m=1)

Pyrolysis of (eta(5)-C5Me5WH3)B4H8, 1, in the presence of excess BHCl2 center dot SMe2 in toluene at 100 degrees C led to the isolation of (eta(5)-C5Me5W)(2)B5H9, 2, and B-Cl inserted (eta(5)-C5Me5W)(2)B5H8Cl, 3, and (eta(5)-C5Me5W)(2)B5H7Cl2, (four isomers). All the Chlorinated tungstaboranes were isolated as red and air and moisture sensitive solids. These new compounds have been characterized in solution by H-1, B-11, C-13 NMR, and the structural types were unequivocally established by crystallographic analysis of compounds 3, 4, and 7. Density functional theory (DFT) calculations were carded out on the model molecules of 3-7 to elucidate the actual electronic structures of these chlorinated species. On grounds of DFT calculations we demonstrated the role of transition metals, bridging hydrogens, and the effect of electrophilic substitution of hydrogens at B-H vertices of metallaborane structures.

An innovative clustering technique for unsupervized learning in the context of remotely sensed earth resources data analysis

A new clustering technique, based on the concept of immediato neighbourhood, with a novel capability to self-learn the number of clusters expected in the unsupervized environment, has been developed. The method compares favourably with other clustering schemes based on distance measures, both in terms of conceptual innovations and computational economy. Test implementation of the scheme using C-l flight line training sample data in a simulated unsupervized mode has brought out the efficacy of the technique. The technique can easily be implemented as a front end to established pattern classification systems with supervized learning capabilities to derive unified learning systems capable of operating in both supervized and unsupervized environments. This makes the technique an attractive proposition in the context of remotely sensed earth resources data analysis wherein it is essential to have such a unified learning system capability.

Vertex-Fused Metallaborane Clusters: Synthesis, Characterization and Electronic Structure of [(eta(5)-C5Me5Mo)(3)MoB9H18]

The reaction of the [(eta(5)-C5Me5)MoCl4] complex with [LiBH4 - TH F] in toluene at - 70 degrees C, followed by pyrolysis at 110 degrees C, afforded dark brown [(eta(5)-C5Me5Mo)(3)MoB9H18], 2, in parallel with the known [(eta(5)-C5Me5Mo)(2)B5H9], 1. Compound 2 has been characterized in solution by H-1, B-11, and C-13 NMR spectroscopy and elemental analysis, and the structural types were unequivocally established by crystallographic studies. The title compound represents a novel class of vertex-fused clusters in which a Mo atom has been fused in a perpendicular fashion between two molybdaborane clusters. Electronic structure calculations employing density functional theory yield geometries in agreement with the structure determinations, and on grounds of density functional theory calculations, we have analyzed the bonding patterns in the structure,

A feedback-based algorithm forMotion analysis with application to object tracking

We present a motion detection algorithm which detects direction of motion at sufficient number of points and thus segregates the edge image into clusters of coherently moving points. Unlike most algorithms for motion analysis, we do not estimate magnitude of velocity vectors or obtain dense motion maps. The motivation is that motion direction information at a number of points seems to be sufficient to evoke perception of motion and hence should be useful in many image processing tasks requiring motion analysis. The algorithm essentially updates the motion at previous time using the current image frame as input in a dynamic fashion. One of the novel features of the algorithm is the use of some feedback mechanism for evidence segregation. This kind of motion analysis can identify regions in the image that are moving together coherently, and such information could be sufficient for many applications that utilize motion such as segmentation, compression, and tracking. We present an algorithm for tracking objects using our motion information to demonstrate the potential of this motion detection algorithm.

Identification of genes associated with tumorigenesis of meibomian cell carcinoma by microarray analysis

Meibomian cell carcinoma (MCC) is a malignant tumor of the meibomian glands located in the eyelids. No information exists on the cytogenctic and genetic aspects of MCC. There is no report on the gene expression profile of MCC. Thus there is a need, for both scientific and clinical reasons, to identify genes and pathways that are involved in the development and progression of MCC. We analyzed the gene expression profile of MCC by the microarray technique. Forty-four genes were upregulated and 149 genes were downregulated in MCC. Differential expression data were confirmed for 5 genes by semiquantitative RT-PCR in MCC tumors: GTF2H4, RBM12, UBE2D3, DDX17, and LZTS1. We found dysregulation of two major pathways in MCC: MAPK and JAK/STAT. Clusters of genes on chromosomes 1, 12, and 19 were dysregUlated in MCC. The data presented here will facilitate the identification of specific markers and therapeutic targets for the treatment of MCC patients. (c) 2007 Elsevier Inc. All rights reserved.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Protein Hydration and Water Structure: X-ray Analysis of a Closely Packed Protein Crystal with Very Low Solvent Content

Low-humidity monoclinic lysozyme, resulting from a water-mediated transformation, has one of the lowest solvent contents (22% by volume) observed in a protein crystal. Its structure has been solved by the molecular replacement method and refined to an R value of 0.175 for 7684 observed reflections in the 10–1.75 Å resolution shell. 90% of the solvent in the well ordered crystals could be located. Favourable sites of hydration on the protein surface include side chains with multiple hydrogen-bonding centres, and regions between short hydrophilic side chains and the main-chain CO or NH groups of the same or nearby residues. Major secondary structural features are not disrupted by hydration. However, the free CO groups at the C terminii and, to a lesser extent, the NH groups at the N terminii of helices provide favourable sites for water interactions, as do reverse turns and regions which connect β-structure and helices. The hydration shell consists of discontinuous networks of water molecules, the maximum number of molecules in a network being ten. The substrate-binding cleft is heavily hydrated, as is the main loop region which is stabilized by water interactions. The protein molecules are close packed in the crystals with a molecular coordination number of 14. Arginyl residues are extensively involved in intermolecular hydrogen bonds and water bridges. The water molecules in the crystal are organized into discrete clusters. A distinctive feature of the clusters is the frequent occurrence of three-membered rings. The protein molecules undergo substantial rearrangement during the transformation from the native to the low-humidity form. The main-chain conformations in the two forms are nearly the same, but differences exist in the side-chain conformation. The differences are particularly pronounced in relation to Trp 62 and Trp 63. The shift in Trp 62 is especially interesting as it is also known to move during inhibitor binding.

Theoretical and Computational Analysis of Static and Dynamic Anomalies in Water-DMSO Binary Mixture at Low DMSO Concentrations

Experiments have repeatedly observed both thermodynamic and dynamic anomalies in aqueous binary mixtures, surprisingly at low solute concentration. Examples of such binary mixtures include water-DMSO, water-ethanol, water-tertiary butyl alcohol (TBA), and water-dioxane, to name a few. The anomalies have often been attributed to the onset of a structural transition, whose nature, however, has been left rather unclear. Here we study the origin of such anomalies using large scale computer simulations and theoretical analysis in water-DMSO binary mixture. At very low DMSO concentration (below 10%), small aggregates of DMSO are solvated by water through the formation of DMSO-(H2O)(2) moieties. As the concentration is increased beyond 10-12% of DMSO, spanning clusters comprising the same moieties appear in the system. Those clusters are formed and stabilized not only through H-bonding but also through the association of CH3 groups of DMSO. We attribute the experimentally observed anomalies to a continuum percolation-like transition at DMSO concentration X-DMSO approximate to 12-15%. The largest cluster size of CH3-CH3 aggregation clearly indicates the formation of such percolating clusters. As a result, a significant slowing down is observed in the decay of associated rotational auto time correlation functions (of the S = O bond vector of DMSO and O-H bond vector of water). Markedly unusual behavior in the mean square fluctuation of total dipole moment again suggests a structural transition around the same concentration range. Furthermore, we map our findings to an interacting lattice model which substantiates the continuum percolation model as the reason for low concentration anomalies in binary mixtures where the solutes involved have both hydrophilic and hydrophobic moieties.

Multifractal analysis, a method to investigate the morphology of materials

Using the multifractal formalism, we discuss the results obtained to characterized the morphology of polymer alloys and granular discontinuous metallic thin films. In the first case we have found a correlation between the multifractality and the mechanical properties of the alloys. In the second case, we have found that it is possible to measure the differences between the morphology of thin films induced by a growth process on a subtrate and that of percolation clusters of the classical theory of percolation.