Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Alternative oxidase in the branched mitochondrial respiratory network: an overview on structure, function, regulation, and role

Plants and some other organisms including protists possess a complex branched respiratory network in their mitochondria. Some pathways of this network are not energy-conserving and allow sites of energy conservation to be bypassed, leading to a decrease of the energy yield in the cells. It is a challenge to understand the regulation of the partitioning of electrons between the various energy-dissipating and -conserving pathways. This review is focused on the oxidase side of the respiratory chain that presents a cyanide-resistant energy-dissipating alternative oxidase (AOX) besides the cytochrome pathway. The known structural properties of AOX are described including transmembrane topology, dimerization, and active sites. Regulation of the alternative oxidase activity is presented in detail because of its complexity. The alternative oxidase activity is dependent on substrate availability: total ubiquinone concentration and its redox state in the membrane and O2 concentration in the cell. The alternative oxidase activity can be long-term regulated (gene expression) or short-term (post-translational modification, allosteric activation) regulated. Electron distribution (partitioning) between the alternative and cytochrome pathways during steady-state respiration is a crucial measurement to quantitatively analyze the effects of the various levels of regulation of the alternative oxidase. Three approaches are described with their specific domain of application and limitations: kinetic approach, oxygen isotope differential discrimination, and ADP/O method (thermokinetic approach). Lastly, the role of the alternative oxidase in non-thermogenic tissues is discussed in relation to the energy metabolism balance of the cell (supply in reducing equivalents/demand in energy and carbon) and with harmful reactive oxygen species formation.

Novel supramolecular network in tri- and mono-nuclear oxovanadium(V)-salicyl-hydroximate: Synthesis, structure and catalytic oxidation of hydrocarbons using H2O2 as terminal oxidant

oxovanadium(V) salicylhydroximate complexes, [VO(SHA)(H2O)]center dot 1.58H(2)O (1) and [V3O3(CSHA)(3) (H2O)(3)]center dot 3CH(3)COCH(3) (2) have been synthesized by reaction of VO43- with N-salicyl hydroxamic acid (SHAHS) and N-(5-chlorosalicyl) hydroxamic acid (CSHAH(3)), respectively, in methanol medium. Compound 1 on reaction with pyridine 2,6-dicarboxylic acid (PyDCH2) yields mononuclear complex [VO(SHAH(2))(PyDC)] (3). Treatment of compound 3 with hydrogen peroxide at low pH (2-3) and low temperature (0-5 degrees C) yields a stable oxoperoxovanadium(V) complex H[VO(O-2)(PyDC)(H2O)]center dot 2.5H(2)O (4). All four complexes (1-4) have been characterized by spectroscopic (IR, UV-Vis, V-51 NMR) and single crystal X-ray analyses. Intermolecular hydrogen bonds link complex 1 into hexanuclear clusters consisting of six {VNO5} octahedra surrounded by twelve {VNO5} octahedra to form an annular ring. While the molecular packing in 2 generates a two-dimensional framework hydrogen bonds involving the solvent acetone molecules, the mononuclear complexes 3 and 4 exhibit three-dimensional supramolecular architecture. The compounds 1 and 2 behave as good catalysts for oxygenation of benzylic, aromatic, carbocyclic and aliphatic hydrocarbons to their corresponding hydroxylated and oxygenated products using H2O2 as terminal oxidant; the process affords very good yield and turnover number. The catalysis work shows that cyclohexane is a very easily oxidizable substrate giving the highest turnover number (TON) while n-hexane and n-heptane show limited yield, longer time involvement and lesser TON than other hydrocarbons. (C) 2008 Elsevier Ltd. All rights reserved.

Percolation in a network with long-range connections: Implications for cytoskeletal structure and function

Cell shape, signaling, and integrity depend on cytoskeletal organization. In this study we describe the cytoskeleton as a simple network of filamentary proteins (links) anchored by complex protein structures (nodes). The structure of this network is regulated by a distance-dependent probability of link formation as P = p/d(s), where p regulates the network density and s controls how fast the probability for link formation decays with node distance (d). It was previously shown that the regulation of the link lengths is crucial for the mechanical behavior of the cells. Here we examined the ability of the two-dimensional network to percolate (i.e. to have end-to-end connectivity), and found that the percolation threshold depends strongly on s. The system undergoes a transition around s = 2. The percolation threshold of networks with s < 2 decreases with increasing system size L, while the percolation threshold for networks with s > 2 converges to a finite value. We speculate that s < 2 may represent a condition in which cells can accommodate deformation while still preserving their mechanical integrity. Additionally, we measured the length distribution of F-actin filaments from publicly available images of a variety of cell types. In agreement with model predictions, cells originating from more deformable tissues show longer F-actin cytoskeletal filaments. (C) 2008 Elsevier B.V. All rights reserved.

Constructive heuristic algorithm in branch-and-bound structure applied to transmission network expansion planning

A constructive heuristic algorithm to solve the transmission system expansion planning problem is proposed with the aim of circumventing some critical problems of classical heuristic algorithms that employ relaxed mathematical models to calculate a sensitivity index that guides the circuit additions. The proposed heuristic algorithm is in a branch-and-bound algorithm structure, which can be used with any planning model, such as Transportation model, DC model, AC model or Hybrid models. Tests of the proposed algorithm are presented on real Brazilian systems.

Structure, characterization and near-infrared emission of a novel 6-connected uninodal 3D network of Nd(III) containing 2,5-thiophenedicarboxylate anion

The novel coordination polymer with the formula {[Nd2(2,5-tdc)3(dmf)2(H2O)2].dmf.H2O}n (2,5-tdc2-=2,5-thiophedicarboxylate anion and dmf=dimethylformamide) has been synthesized and characterized by thermal analysis (TG/DTA), vibrational spectroscopy (FTIR) and single crystal X-ray diffraction analysis (XRD). Structure analysis reveals that Nd(III) ions show dicapped trigonal prism coordination geometry. The 2,5-tdc2- ligands connect four Nd(III) centers, adopting (κ1 - κ1) - (κ1 - κ1) - μ4 coordination mode, generating an interesting 6-connected uninodal 3D network. Photophysical properties were studied using diffuse reflectance spectroscopy (DR) and excitation/emission spectra. The photoluminescence data show the near infrared emission (NIR) with the characteristic 4F3/2→4IJ (J=9/2, 11/2 and 13/2) transitions of Nd(III) ion, indicating that 2,5-tdc2- is able to act as a sensitizer for emission in NIR region. © 2013 Elsevier B.V.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

ACKNOWLEDGMENTS MW and RVD have been supported by the German Federal Ministry for Education and Research (BMBF) via the Young Investigators Group CoSy-CC2 (grant no. 01LN1306A). JFD thanks the Stordalen Foundation and BMBF (project GLUES) for financial support. JK acknowledges the IRTG 1740 funded by DFG and FAPESP. MT Gastner is acknowledged for providing his data on the airline, interstate, and Internet network. P Menck thankfully provided his data on the Scandinavian power grid. We thank S Willner on behalf of the entire zeean team for providing the data on the world trade network. All computations have been performed using the Python package pyunicorn [41] that is available at https://github.com/pik-copan/pyunicorn.

Breaking down complex saproxylic communities: understanding sub-networks structure and implications to network robustness

Saproxylic insect communities inhabiting tree hollow microhabitats correspond with large food webs which simultaneously are constituted by multiple types of plant-animal and animal-animal interactions, according to the use of trophic resources (wood- and insect-dependent sub-networks), or to trophic habits or interaction types (xylophagous, saprophagous, xylomycetophagous, predators and commensals). We quantitatively assessed which properties of specialised networks were present in a complex networks involving different interacting types such as saproxylic community, and how they can be organised in trophic food webs. The architecture, interacting patterns and food web composition were evaluated along sub-networks, analysing their implications to network robustness from random and directed extinction simulations. A structure of large and cohesive modules with weakly connected nodes was observed throughout saproxylic sub-networks, composing the main food webs constituting this community. Insect-dependent sub-networks were more modular than wood-dependent sub-networks. Wood-dependent sub-networks presented higher species degree, connectance, links, linkage density, interaction strength, and were less specialised and more aggregated than insect-dependent sub-networks. These attributes defined high network robustness in wood-dependent sub-networks. Finally, our results emphasise the relevance of modularity, differences among interacting types and interrelations among them in modelling the structure of saproxylic communities and in determining their stability.

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.

Analysis of a stochastic SIR epidemic on a random network incorporating household structure

This paper is concerned with a stochastic SIR (susceptible-infective-removed) model for the spread of an epidemic amongst a population of individuals, with a random network of social contacts, that is also partitioned into households. The behaviour of the model as the population size tends to infinity in an appropriate fashion is investigated. A threshold parameter which determines whether or not an epidemic with few initial infectives can become established and lead to a major outbreak is obtained, as are the probability that a major outbreak occurs and the expected proportion of the population that are ultimately infected by such an outbreak, together with methods for calculating these quantities. Monte Carlo simulations demonstrate that these asymptotic quantities accurately reflect the behaviour of finite populations, even for only moderately sized finite populations. The model is compared and contrasted with related models previously studied in the literature. The effects of the amount of clustering present in the overall population structure and the infectious period distribution on the outcomes of the model are also explored.