998 resultados para POLY(TETRAHYDROFURAN) NETWORKS


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In this paper, we propose an efficient source routing algorithm for unicast flows, which addresses the scalability problem associated with the basic source routing technique. Simulation results indicate that the proposed algorithm indeed helps in reducing the message overhead considerably, and at the same time it gives comparable performance in terms of resource utilization across a wide range of workloads.

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Novel amphiphilic poly(meta-phenylene)s were prepared by an oxidative coupling approach. These polymers were synthesized to shed light on their solution properties with special emphasis on aggregation and folding behavior. The polymers were characterized by NMR spectroscopy and molecular weights were determined by Gel Permeation Chromatography using Universal calibration. Literature studies revealed that the backbone of these PMPs can be helical moreover, the light emitting properties of this conjugated polymer can be used as a handle to study the possible aggregation or self-assembling behavior. In this report we show the synthesis, characterization and preliminary aggregation properties that points out that one of the synthesized PMP behave as a polysoap.

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We consider a network in which several service providers offer wireless access to their respective subscribed customers through potentially multihop routes. If providers cooperate by jointly deploying and pooling their resources, such as spectrum and infrastructure (e.g., base stations) and agree to serve each others' customers, their aggregate payoffs, and individual shares, may substantially increase through opportunistic utilization of resources. The potential of such cooperation can, however, be realized only if each provider intelligently determines with whom it would cooperate, when it would cooperate, and how it would deploy and share its resources during such cooperation. Also, developing a rational basis for sharing the aggregate payoffs is imperative for the stability of the coalitions. We model such cooperation using the theory of transferable payoff coalitional games. We show that the optimum cooperation strategy, which involves the acquisition, deployment, and allocation of the channels and base stations (to customers), can be computed as the solution of a concave or an integer optimization. We next show that the grand coalition is stable in many different settings, i.e., if all providers cooperate, there is always an operating point that maximizes the providers' aggregate payoff, while offering each a share that removes any incentive to split from the coalition. The optimal cooperation strategy and the stabilizing payoff shares can be obtained in polynomial time by respectively solving the primals and the duals of the above optimizations, using distributed computations and limited exchange of confidential information among the providers. Numerical evaluations reveal that cooperation substantially enhances individual providers' payoffs under the optimal cooperation strategy and several different payoff sharing rules.

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Symmetrized DMRG calculations on long oligomers of poly- para-phenylene (PPP) and poly-para-phenylene vinylene (PPV) systems within a `U-V' model have been carried out to obtain the one-photon, two-photon and singlet-triplet gaps in these systems. The extrapolated gaps (in eV) are 2.89, 3.76 and 2.72 in PPP and 3.01, 3.61 and 2.23 in PPV for the one- photon, two-photon and spin gaps respectively. By studying doped systems, we have obtained the exciton binding energies. The larger exciton binding energies, compared to strongly dimerized linear chains emphasizes the role of topology in these polymers. Bond orders, charge and spin correlations in the low-lying states bring out the similarities between the lowest one-photon, the lowest triplet and the lowest bipolaronic states in these systems. The two-photon state bond orders show evidence for strong localization of this excitation in both PPP and PPV systems.

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The Radius of Direct attraction of a discrete neural network is a measure of stability of the network. it is known that Hopfield networks designed using Hebb's Rule have a radius of direct attraction of Omega(n/p) where n is the size of the input patterns and p is the number of them. This lower bound is tight if p is no larger than 4. We construct a family of such networks with radius of direct attraction Omega(n/root plog p), for any p greater than or equal to 5. The techniques used to prove the result led us to the first polynomial-time algorithm for designing a neural network with maximum radius of direct attraction around arbitrary input patterns. The optimal synaptic matrix is computed using the ellipsoid method of linear programming in conjunction with an efficient separation oracle. Restrictions of symmetry and non-negative diagonal entries in the synaptic matrix can be accommodated within this scheme.