Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches

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Not AvailableLac insects belonging to Kerria species are the most commonly used species for commercial lac production. They are also harnessed for the production of lac dye and wax. Using five Exon Primed Intron Crossing (EPIC) PCR primers for Kerria spp., we studied the intra- and interspecific variation among a population of forty eight lac insect lines. The study separated K. chinensis from rest of the lines and also made differentiation between the infrasubspecific forms of K. lacca i.e., kusmi and rangeeni.Not Availabl

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Not AvailableLac insects belonging to the genus Kerria are commercially exploited for lac which has diversified industrial applications. India is the global leader in lac production; much of commercial lac is derived from the Indian lac insect, Kerria lacca (Kerr). Molecular marker studies of Kerria species are limited to RAPD and ISSR. We evaluated genetic diversity among 27 Kerria geographic populations belonging to thirteen species of Kerria, using 31 microsatellite markers developed from transcriptome of the Indian lac insect. The number of alleles per locus ranged between 2 and 6 with a mean of 2.74, showing polymorphism of 66.7- 100%. UPGMA dendrogram based on Jaccard’s similarity coefficient grouped 27 Kerria accessions into three major clusters consisting of 2, 13 and 12 populations respectively and their similarity coefficient ranged between 0.61 and 0.95. Based on similarity coefficients, the closest relationship was observed between Kerria pusana and Kerria pennyae and also between K. lacca and K. pennaye. K. chinensis appeared well separated from all other Kerria species studied. Geographically closer species were found more similar, in general. The present study reveals wide intra- and inter-specific genetic diversity among Kerria populations through EST-microsatellite markers and indicates the potential and usefulness of marker studies for lac insect improvement programmes.Not Availabl

European dermatology forum S1-guideline on the diagnosis and treatment of sclerosing diseases of the skin, Part 2: Scleromyxedema, scleredema and nephrogenic systemic fibrosis

none44noneKnobler, R.*; Moinzadeh, P.; Hunzelmann, N.; Kreuter, A.; Cozzio, A.; Mouthon, L.; Cutolo, M.; Rongioletti, F.; Denton, C.P.; Rudnicka, L.; Frasin, L.A.; Smith, V.; Gabrielli, A.; Aberer, E.; Bagot, M.; Bali, G.; Bouaziz, J.; Braae Olesen, A.; Foeldvari, I.; Frances, C.; Jalili, A.; Just, U.; Kähäri, V.; Kárpáti, S.; Kofoed, K.; Krasowska, D.; Olszewska, M.; Orteu, C.; Panelius, J.; Parodi, A.; Petit, A.; Quaglino, P.; Ranki, A.; Sanchez Schmidt, J.M.; Seneschal, J.; Skrok, A.; Sticherling, M.; Sunderkötter, C.; Taieb, A.; Tanew, A.; Wolf, P.; Worm, M.; Wutte, N.J.; Krieg, T.Knobler, R.; Moinzadeh, P.; Hunzelmann, N.; Kreuter, A.; Cozzio, A.; Mouthon, L.; Cutolo, M.; Rongioletti, F.; Denton, C. P.; Rudnicka, L.; Frasin, L. A.; Smith, V.; Gabrielli, A.; Aberer, E.; Bagot, M.; Bali, G.; Bouaziz, J.; Braae Olesen, A.; Foeldvari, I.; Frances, C.; Jalili, A.; Just, U.; Kähäri, V.; Kárpáti, S.; Kofoed, K.; Krasowska, D.; Olszewska, M.; Orteu, C.; Panelius, J.; Parodi, A.; Petit, A.; Quaglino, P.; Ranki, A.; Sanchez Schmidt, J. M.; Seneschal, J.; Skrok, A.; Sticherling, M.; Sunderkötter, C.; Taieb, A.; Tanew, A.; Wolf, P.; Worm, M.; Wutte, N. J.; Krieg, T