Comparison of mean distance in superposed networks

AbstractIn this paper, we consider the problem of the superposition of two networks in the structure of local telecommunication networks: the physical one, determined by the ways of the means of communication, and the interconnection one. We compare the mean-distance of the graphs associated to these two networks

Achieving the Optimal Steaming Capacity and Delay Using Random Regular Digraphs in P2P Networks

In earlier work, we showed that it is possible to achieve $O(\log N)$ streaming delay with high probability in a peer-to-peer network, where each peer has as little as four neighbors, while achieving any arbitrary fraction of the maximum possible streaming rate. However, the constant in the $O(log N)$ delay term becomes rather large as we get closer to the maximum streaming rate. In this paper, we design an alternative pairing and chunk dissemination algorithm that allows us to transmit at the maximum streaming rate while ensuring that all, but a negligible fraction of the peers, receive the data stream with $O(\log N)$ delay with high probability. The result is established by examining the properties of graph formed by the union of two or more random 1-regular digraphs, i.e., directed graphs in which each node has an incoming and an outgoing node degree both equal to one

Characteristics of broadband lightning emissions associated with terrestrial gamma ray flashes

To characterize lightning processes that produce terrestrial gamma ray flashes (TGFs), we have analyzed broadband (<1 Hz to 30 kHz) lightning magnetic fields for TGFs detected by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) satellite in 2004-2009. The majority (96%) of 56 TGF-associated lightning signals contain single or multiple VLF impulses superposed on a slow pulse that reflects a process raising considerable negative charge within 2-6 ms. Some TGF lightning emissions also contain VLF signals that precede any appreciable slow pulse and that we term precursor sferics. The analyses of 9 TGFs related to lightning discharges with location uncertainty <100 km consistently indicate that TGFs are temporally linked to the early portion of the slow process and associated VLF impulses, and not to precursor sferics. The nearly universal presence of a slow pulse suggests that the slow process plays an important role in gamma ray production. In all cases the slow process raises negative charge with a typical mean current moment of +30 kA km. The resulting charge moment change ranges from small values below +10 C km to a maximum of +200 C km, with an average of +64 C km. The current moment waveform extracted from TGF sferics with single or multiple VLF impulses also shows that the slow process initiates shortly before the major TGF-associated fast discharge. These features are generally consistent with the TGF-lightning sequence reported by Lu et al. (2010), suggesting that the majority of RHESSI TGFs are produced during the upward negative leader progression prevalent in normal polarity intracloud flashes

Information content based model for the topological properties of the gene regulatory network of Escherichia coli

Gene regulatory networks (GRN) are being studied with increasingly precise quantitative tools and can provide a testing ground for ideas regarding the emergence and evolution of complex biological networks. We analyze the global statistical properties of the transcriptional regulatory network of the prokaryote Escherichia coli, identifying each operon with a node of the network. We propose a null model for this network using the content-based approach applied earlier to the eukaryote Saccharomyces cerevisiae. (Balcan et al., 2007) Random sequences that represent promoter regions and binding sequences are associated with the nodes. The length distributions of these sequences are extracted from the relevant databases. The network is constructed by testing for the occurrence of binding sequences within the promoter regions. The ensemble of emergent networks yields an exponentially decaying in-degree distribution and a putative power law dependence for the out-degree distribution with a flat tail, in agreement with the data. The clustering coefficient, degree-degree correlation, rich club coefficient and k-core visualization all agree qualitatively with the empirical network to an extent not yet achieved by any other computational model, to our knowledge. The significant statistical differences can point the way to further research into non-adaptive and adaptive processes in the evolution of the E. coli GRN.Comment: 58 pages, 3 tables, 22 figures. In press, Journal of Theoretical Biology (2009)

Modeling Ferro- and Antiferromagnetic Interactions in Metal-Organic Coordination Networks

Magnetization curves of two rectangular metal-organic coordination networks formed by the organic ligand TCNQ (7,7,8,8-tetracyanoquinodimethane) and two different (Mn and Ni) 3d transition metal atoms [M(3d)] show marked differences that are explained using first principles density functional theory and model calculations. We find that the existence of a weakly dispersive hybrid band with M(3d) and TCNQ character crossing the Fermi level is determinant for the appearance of ferromagnetic coupling between metal centers, as it is the case of the metallic system Ni-TCNQ but not of the insulating system Mn-TCNQ. The spin magnetic moment localized at the Ni atoms induces a significant spin polarization in the organic molecule; the corresponding spin density being delocalized along the whole system. The exchange interaction between localized spins at Ni centers and the itinerant spin density is ferromagnetic. Based on two different model Hamiltonians, we estimate the strength of exchange couplings between magnetic atoms for both Ni- and Mn-TCNQ networks that results in weak ferromagnetic and very weak antiferromagnetic correlations for Ni- and Mn-TCNQ networks, respectively.Comment: 27 pages, 6 figures, accepted for publication; Journal of Physical Chemistry C (2014