47 resultados para OPEN CLUSTERS


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Nine classes of integrable open boundary conditions, further extending the one-dimensional U-q (gl (212)) extended Hubbard model, have been constructed previously by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary systems are now solved by using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained for all nine cases.

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In contrast to other mammalian defensins, rhesus theta defensin-1 (RTD-1) is composed of just 18 amino acids with the backbone cyclized through peptide bonds. Antibacterial activities of both the native cyclic peptide and a linear form were examined, showing that the cyclic form was 3-fold more active than the open chain analogue, oRTD-1, although both peptides adopt very similar structures in water. It was suggested that the additional charges at the termini of oRTD-1 are the cause for its lower antimicrobial activity. Therefore, we studied the interaction of both peptides with membrane mimics composed of zwitterionic (PC) and negatively charged (PG) phospholipids, major lipid components of erythrocyte and bacterial cell membranes, respectively. Microcalorimetry showed that RTD-1 and oRTD-1 did not affect the phase behavior of PC liposomes, while in PG liposomes both peptides induced new phase transitions above the chain melting transition of the lipid. The shape and fraction differed between both peptides, depending also on their concentration, which will be discussed in terms of their antimicrobial activity.

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The integrable open-boundary conditions for the Bariev model of three coupled one-dimensional XY spin chains are studied in the framework of the boundary quantum inverse scattering method. Three kinds of diagonal boundary K-matrices leading to nine classes of possible choices of boundary fields are found and the corresponding integrable boundary terms are presented explicitly. The boundary Hamiltonian is solved by using the coordinate Bethe ansatz technique and the Bethe ansatz equations are derived. (C) 2001 Elsevier Science B.V. All rights reserved.

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The QU-GENE Computing Cluster (QCC) is a hardware and software solution to the automation and speedup of large QU-GENE (QUantitative GENEtics) simulation experiments that are designed to examine the properties of genetic models, particularly those that involve factorial combinations of treatment levels. QCC automates the management of the distribution of components of the simulation experiments among the networked single-processor computers to achieve the speedup.