Scale-Free Networks

Research in bioinformatics is a complex phenomenon as it overlaps two knowledge domains, namely, biological and computer sciences. This paper has tried to introduce an efficient data mining approach for classifying proteins into some useful groups by representing them in hierarchy tree structure. There are several techniques used to classify proteins but most of them had few drawbacks on their grouping. Among them the most efficient grouping technique is used by PSIMAP. Even though PSIMAP (Protein Structural Interactome Map) technique was successful to incorporate most of the protein but it fails to classify the scale free property proteins. Our technique overcomes this drawback and successfully maps all the protein in different groups, including the scale free property proteins failed to group by PSIMAP. Our approach selects the six major attributes of protein: a) Structure comparison b) Sequence Comparison c) Connectivity d) Cluster Index e) Interactivity f) Taxonomic to group the protein from the databank by generating a hierarchal tree structure. The proposed approach calculates the degree (probability) of similarity of each protein newly entered in the system against of existing proteins in the system by using probability theorem on each six properties of proteins. This function generates probabilistic value for deriving its respective weight against that particular property. All probabilistic values generated by six individual functions will be added together to calculate the bond factor. Bond Factor defines how strongly one protein bonds with another protein base on their similarity on six attributes. Finally, in order to group them in hierarchy tree, the aggregated probabilistic value will be compared with the probabilistic value of the protein that resides at the root. If there is no root protein (i.e. at the initial state), the first protein will be considered as the root and depending on the probabilistic value it can change its relative position. Recursively, at each node, we have applied this technique to calculate the highest probable position for a particular protein in the tree.

Synchronous firing peaks at levels greatly exceeding background activity have recently been reported in neocortical tissue. A small subset of neurons is dominant in a large fraction of the peaks. To investigate whether this striking behavior can emerge from a simple model, we constructed and studied a model neural network that uses a modified Hopfield-type dynamical rule. We find that networks having a power-law (''scale-free'') node degree distribution readily generate extremely large synchronous firing peaks dominated by a small subset of nodes, whereas random (Erdö s-Ré nyi) networks do not. This finding suggests that network topology may play an important role in determining the nature and magnitude of synchronous neural activity.

We present an empirical study of user activity in online BBC discussion forums, measured by the number of posts written by individual debaters and the average sentiment of these posts. Nearly 2.5 million posts from over 18 thousand users were investigated. Scale free distibutions were observed for activity in individual discussion threads as well as for overall activity. The number of unique users in a thread normalised by the thread length decays with thread length, suggesting that thread life is sustained by mutual discussions rather than by independent comments. Automatic sentiment analysis shows that most posts contain negative emotions and that the most active users in individual threads express predominantly negative sentiments. It follows that the average emotion of longer threads is more negative and that threads can be sustained by negative comments.

Qualitative evidence suggests that heresy within the medieval Catholic Church had many of the characteristics of a scale-free network. From the perspective of the Church, heresy can be seen as a virus. The virus persisted for long periods of time, breaking out again even when the Church believed it to have been eradicated. A principal mechanism of heresy was through a small number of individuals with very large numbers of social contacts.

Two computations of the KCS model with motions are presented. Self-propulsion in model scale free to sink and trim are studied with the rotating discretized propeller from the Hamburg Model Basin (HSVA) at Fr = 0.26. This case is particularly complex to simulate due to the close proximity of the propeller to the rudder. The second case involves pitch and heave in regular head waves. Computations were performed with CFDShip-Iowa version 4.5, a RANS/DES CFD code designed for ship hydrodynamics. The self-propulsion computations were carried out following the procedure described in Carrica et al.

An effective scale control program for seawater RO is widely recognized as an important factor in ensuring trouble free and cost effective operation. This is especially important under the high feed water pH and temperature conditions found in Southern Europe and Middle East.

Several kinds of astronomical observations, interpreted in the framework of the standard Friedmann-Robertson-Walker cosmology, have indicated that our universe is dominated by a Cosmological Constant. The dimming of distant Type Ia supernovae suggests that the expansion rate is accelerating, as if driven by vacuum energy, and this has been indirectly substantiated through studies of angular anisotropies in the cosmic microwave background (CMB) and of spatial correlations in the large-scale structure (LSS) of galaxies. However there is no compelling direct evidence yet for (the dynamical effects of) dark energy. The precision CMB data can be equally well fitted without dark energy if the spectrum of primordial density fluctuations is not quite scale-free and if the Hubble constant is lower globally than its locally measured value. The LSS data can also be satisfactorily fitted if there is a small component of hot dark matter, as would be provided by neutrinos of mass ∼ 0.5 eV. Although such an Einstein-de Sitter model cannot explain the SNe Ia Hubble diagram or the position of the 'baryon acoustic oscillation' peak in the autocorrelation function of galaxies, it may be possible to do so e.g. in an inhomogeneous Lemaitre-Tolman-Bondi cosmology where we are located in a void which is expanding faster than the average. Such alternatives may seem contrived but this must be weighed against our lack of any fundamental understanding of the inferred tiny energy scale of the dark energy. It may well be an artifact of an oversimplified cosmological model, rather than having physical reality.

An effective scale control program for seawater RO is widely recognized as an important factor in ensuring trouble free and cost effective operation. This is especially important under the high feed water pH and temperature conditions found in Southern Europe and Middle East.

The paper analyses methodological issues concerning selection of indicators, making them scale-free and construction of composite indices within the framework of measuring human development. It reviews the existing literature in the area and highlights the key areas of concern from the viewpoint of methodology of aggregation. It discusses the implications of the assumptions underlying different techniques, currently being used in India, in the context of an empirical exercise of constructing an index of human development at state level. It examines the advantages and disadvantages of these techniques and proposes improvements therein for bringing them closer to empirical reality and thereby increasing their acceptability among the planners and policy-makers. The study suggests that exercises at determining the levels of human development at the state or district level by official agencies like the Planning Commission, concerned ministries or an international agency must enjoy large ...

Effective quantitative land surface analyses in soil science need scale-free land surface attributes (morphometric variables, MVs) to be introduced for making comparable results obtained at different scales. To investigate the problem in more detail, a conceptual scheme and curvatures studied earlier in ) [Math. Geol. 27 (1995 373] are further developed in this paper, formulae for a complete system of 12 curvatures and some other MVs are given, and modified Evans -Young algorithm for curvature calculation is described that does not emphasize grid directions. The conceptual scheme is based on that MVs often describe not the land surface itself, but rather the system ''land surface + vector field'', where vector fields of common interest are gravitational field and solar irradiation. Correspondingly, morphometric variables and concepts may (1) refer to this system description (field-specific), or (2) be invariant with respect to any vector field (fieldinvariant), that is, describing the land surface itself, its geometrical form. From the other side, MVs and concepts may be (1) local, (2) regional, which need extended portions of a restricted part of land surface for their determination at a given point, or (3) global (planetary), when elevations of all the Earth are needed for their determination at a given point. Global MVs do not consist subject of this paper; so, the four classes of MVs are considered here: class A (local field-specific MVs), class B (regional field-specific), class C (local field-invariant), and class D (regional field-invariant). MVs of these classes permit description of geometrical land form, pre-requisits of surface runoff, thermal regime of slopes, and altitude zonality. Class A contains three independent MVs expressed by first derivatives of elevation Z by plan coordinates (slope steepness, slope direction, solar insolation) and seven curvatures expressed by second derivatives of Z; class C contains five curvatures; class B contains two variables (catchment and dispersal areas); MVs of class D are not introduced yet. Also, 0016-7061/02/$ -see front matter D 2002 Elsevier Science B.V. All rights reserved. PII: S 0 0 1 6 -7 0 6 1 ( 0 1 ) 0 0 1 3 6 -7 * Corresponding

RCIS) aimed at providing an international forum for scientists, researchers, engineers and developers from a wide range of information science areas to exchange ideas and approaches in this evolving field. While presenting research findings and state-of-art solutions, authors were especially invited to share experiences on new research challenges. High quality papers in all information science areas were solicited and original papers exploring research challenges did receive especially careful interest from reviewers. Papers that had already been accepted or were currently under review for other conferences or journals were not to be considered for publications at RCIS'07.

A control-based analysis and characterization of a free-piston Stirling engine is presented, and proposed as a lightweight power supply for untethered robots. Typically, such devices are designed from the point of view of a thermodynamic cycle in terms of traditional thermodynamic equations of state. Such equations of state are independent of time and therefore lend little insight when dynamic elements are incorporated into the design. The approach presented here is from a system dynamics and control perspective. Equations of state are replaced by dynamic system modeling elements. Utilizing these dynamic elements, control concepts are applied to evaluate a given configuration and ensure an unstable oscillatory response and therefore transform heat into useful work. A simulation of a commercially available free-piston engine is presented, and standard control design tools are applied to its linearized model. The results show promising potential in utilizing small-scale free-piston Stirling engines as portable power supply for robotic systems.

It is well known that the microstructures of the transition-metal oxides 1-3 , including the high-transition-temperature (high-T c ) copper oxide superconductors 4-7 , are complex. This is particularly so when there are oxygen interstitials or vacancies 8 , which influence the bulk properties. For example, the oxygen interstitials in the spacer layers separating the superconducting CuO 2 planes undergo ordering phenomena in Sr 2 O 11y CuO 2 (ref. 9), YBa 2 Cu 3 O 61y (ref. 10) and La 2 CuO 41y (refs 11-15) that induce enhancements in the transition temperatures with no changes in hole concentrations. It is also known that complex systems often have a scale-invariant structural organization 16 , but hitherto none had been found in high-T c materials. Here we report that the ordering of oxygen interstitials in the La 2 O 21y spacer layers of La 2 CuO 41y high-T c superconductors is characterized by a fractal distribution up to a maximum limiting size of 400 mm. Intriguingly, these fractal distributions of dopants seem to enhance superconductivity at high temperature.

While the majority of approaches to the characterization of complex networks has relied on measurements considering only the immediate neighborhood of each network node, valuable information about the network topological properties can be obtained by considering further neighborhoods. The current work considers the concept of virtual hierarchies established around each node and the respectively defined hierarchical node degree and clustering coefficient (introduced in cond-mat/0408076), complemented by new hierarchical measurements, in order to obtain a powerful set of topological features of complex networks. The interpretation of such measurements is discussed, including an analytical study of the hierarchical node degree for random networks, and the potential of the suggested measurements for the characterization of complex networks is illustrated with respect to simulations of random, scale-free and regular network models as well as real data (airports, proteins and word associations). The enhanced characterization of the connectivity provided by the set of hierarchical measurements also allows the use of agglomerative clustering methods in order to obtain taxonomies of relationships between nodes in a network, a possibility which is also illustrated in the current article.

The advent of business oriented and social networking sites on the Internet have seen a huge increase in number of people using them in recent years. With the expansion of Web 2.0, new types of websites have emerged such as online social networks, blogs and wikis. Their popularity has resulted in exponential growth of information on the web and interactions overload thus making it harder to access useful or relevant information. Recommender systems are one of the applications employed to address this problem by filtering relevant information and enhancing user experience. They traditionally use either the content of items of the websites (content-filtering recommender systems) or the collaboration between the users and items such as rating (collaborative-filtering recommender systems) or a combination of them (hybrid recommender systems). However due to the nature of data they use, they all have one or more weaknesses such as cold start, sparsity of data, scalability problems and overspecialised recommendation. Social networks and other similar websites have new types of data which can be used in recommender systems thus have the potential to overcome these shortcomings. However without a good understanding of the properties and structure of these online social websites, the applications can not be accurate. This paper presents an empirical measurement study of the properties and structure of one such social websites. It examines an online movie database, and the interactions between reviewers and attempts to construct a social network graph based on the network of reviewers. The resulting network is confirmed as the power-law, small-world and scalefree. It identifies the highly connected clusters and shows that the content of these subgroups are diversified and not limited to similar tags. Finally the implication of these finding is discussed in order to enhance current recommender systems enabling them to provide diverse results while overcome their shortcomings.

In this paper, we investigate the diameter in preferential attachment (PA-) models, thus quantifying the statement that these models are small worlds. The models studied here are such that edges are attached to older vertices proportional to the degree plus a constant, i.e., we consider affine PA-models. There is a substantial amount of literature proving that, quite generally, PA-graphs possess power-law degree sequences with a power-law exponent τ > 2.

... |EvalAi(Gk)-EvalAj(Gk)| is the similarity of the content evaluation in the contents category Gk between two agents Ai and Aj, - EvalAj(Gk) is the parameter defining ... 2 shows that, in the range of edge 16, the probability is P(k)～k-α ;-1.5<α<2.1, and that it is clearly a scale-free net-...

Humans often cooperate in public goods games 1-3 and situations ranging from family issues to global warming 4,5 . However, evolutionary game theory predicts 4,6 that the temptation to forgo the public good mostly wins over collective cooperative action, and this is often also seen in economic experiments 7 . Here we show how social diversity provides an escape from this apparent paradox. Up to now, individuals have been treated as equivalent in all respects 4,8 , in sharp contrast with real-life situations, where diversity is ubiquitous. We introduce social diversity by means of heterogeneous graphs and show that cooperation is promoted by the diversity associated with the number and size of the public goods game in which each individual participates and with the individual contribution to each such game. When social ties follow a scale-free distribution 9 , cooperation is enhanced whenever all individuals are expected to contribute a fixed amount irrespective of the plethora of public goods games in which they engage. Our results may help to explain the emergence of cooperation in the absence of mechanisms based on individual reputation and punishment 10-12 . Combining social diversity with reputation and punishment will provide instrumental clues on the self-organization of social communities and their economical implications.

The comprehensive characterization of the structure of complex networks is essential to understand the dynamical processes which guide their evolution. The discovery of the scale-free distribution and the small world property of real networks were fundamental to stimulate more realistic models and to understand some dynamical processes such as network growth. However, properties related to the network borders (nodes with degree equal to one), one of its most fragile parts, remain little investigated and understood. The border nodes may be involved in the evolution of structures such as geographical networks. Here we analyze complex networks by looking for border trees, which are defined as the subgraphs without cycles connected to the remainder of the network (containing cycles) and terminating into border nodes. In addition to describing an algorithm for identification of such tree subgraphs, we also consider a series of their measurements, including their number of vertices, number of leaves, and depth. We investigate the properties of border trees for several theoretical models as well as real-world networks.

Field research on step-pool channels has largely focused on the dimensions and sequence of steps and pools and how these features vary with slope, grain sizes and other governing variables. Measurements by different investigators are frequently compared, yet no means to identify steps and pools objectively have been used. Automated surveying instruments record the morphology of streams in unprecedented detail making it possible to objectively identify steps and pools, provided an appropriate classification procedure can be developed. To achieve objective identification of steps and pools from long profile survey data, we applied a series of scale-free geometric rules that include minimum step length (2.25% of bankfull width (W b )), minimum pool length (10% of W b ), minimum residual depth (0.23% of W b ), minimum drop height (3.3% of W b ), and minimum step slope (10°greater than the mean slope). The rules perform as well as the mean response of 11 step-pool researchers who were asked to classify four long profiles, and the results correspond well with the channel morphologies identified during the field surveys from which the long profiles were generated. The method outperforms four other techniques that have been proposed. Sensitivity analysis shows that the method is most sensitive to the choice of minimum pool length and minimum drop height. Detailed bed scans of a step-pool channel created in a flume reveal that a single long profile with a fixed sampling interval poorly characterizes the steps and pools; five or more long profiles spread across the channel are required if a fixed sampling interval is used and the data suggest that survey points should be located more frequently than the diameter of the step-forming material. A single long profile collected by a surveyor who chooses breaks in slope and representative survey points was found to adequately characterize the mean bed profile.

Draining soil water is an important runoff generator. This study aims to describe runoff-generating processes on a plot scale (1 m 2 ) in hydromorphic soils with different initial soil water contents. We irrigated 16 hydromorphic soils in the northern Pre-Alps in Switzerland and recorded the variations in water content with time domain reflectometry (TDR) at five different depths per plot. Sprinkling was repeated three times at approximately 23-h intervals and lasted for 1 h with a volume flux density of 70 mm h 1 . The comparison between the measured water content of the drainages with two physically based models revealed which of the flow processes dominated during water recessions. We distinguished between vertical drainage, lateral outflow and infiltration without drainage. Approximately 45% of all recorded time series of soil water content did not drain within approximately 20 h after the end of irrigation, about 25% drained laterally and 10% of the outflow was vertical. The drainage of the remaining 20% was the result of both lateral and vertical water flow (³12%), or was not interpretable with the approaches applied (³8%). Vertical flow was only observed in layers without any or with just a few hydromorphic features. Lateral draining horizons had approximately half the storage capacity and amplitude of water recession of those with vertical flow. Vertical flow was only observed in the upper soil horizons. Thus, vertical flow transmitted water to layers with lateral outflow and did not delay runoff by deep percolation. Increasing initial soil moisture increased the percentage of water content recordings according to a lateral outflow slightly, while vertical flow was less frequent.

In the last years, complex networks have become an
increasingly relevant research topic due to the large
number of fields of application. Particularly, complex
networks are specially significant in the area of modern Online Social Networks (OSNs). OSNs are actually a challenge for complex network analysis, as
they present some characteristics that hinder topology processing. Concretely, social-networks volume
is exceedingly big, as they have a high number of
nodes and links. One of the most popular and influential OSN is Twitter. This article proves that twitter is
a complex network computing an estimated value of
luster coefficient, power law, and average path length.

Whether or not a critical threshold exists when epidemic diseases are spread in complex networks is a problem attracting attention from researchers in several disciplines. In 2001, Pastor-Satorras and Vespignani used a computational simulations approach to show that epidemic diseases which spread through scale-free social networks do not have positive critical thresholds. In other words, even if a disease has almost no chance of being transmitted from one person to another, it can still spread throughout a scalefree network. However, they ignored two key factors that have a large impact on epidemic dynamics: economic resource limitations and transmission costs. Every infection event entails tangible or intangible costs in terms of time, energy, or money to the carrier, recipient, or both. Here we apply an agent-based modeling and network-oriented computer simulation approach to analyze the influences of resource limitations and transmission costs on epidemic dynamics and critical thresholds in scale-free networks. Our results indicate that when those resources and costs are taken into consideration, the epidemic dynamics of scale-free networks are very similar to those of homogeneous networks, including the presence of significant critical thresholds. It is hoped that our data will help epidemiologists, public health professionals, and computer scientists working with core questions of epidemic diseases, estimates of epidemic dynamics and spreading, and effective public health policies and immunization strategies.

Many recent advances have been made in understanding the functional implications of the global topological properties of biological networks through the application of complex network theory, particularly in the area of small-world and scalefree topologies. Computational studies which attempt to understand the structure-function relationship usually proceed by defining a representation of cells and an affinity measure to describe their interactions. We show that this necessarily restricts the topology of the networks that can arise-furthermore, we show that although simple topologies can be produced via representation and affinity measures common in the literature, it is unclear how to select measures which result in complex topologies, for example, exhibiting scalefree functionality. In this paper, we introduce the concept of the potential network as a method in which abstract network topologies can be directly studied, bypassing any definition of shape-space and affinity function. We illustrate the benefit of the approach by studying the evolution of idiotypic networks on a selection of scale-free and regular topologies, finding that a key immunological property-tolerance-is promoted by bipartite and heterogeneous topologies. The approach, however, is applicable to the study of any network and thus has implications for both immunology and artificial immune systems.

We investigate the differences between scale-free recursive nets constructed by a synchronous, deterministic updating rule (e.g., Apollonian nets), versus an asynchronous, random sequential updating rule (e.g., random Apollonian nets). We show that the dramatic discrepancies observed recently for the degree exponent in these two cases result from a biased choice of the units to be updated sequentially in the asynchronous version.

The uniform (nonordering) magnetization and heat capacity of FeC12 have been measured simultaneously in the vicinity of the tricritical point. Using. the peak in the heat capacity in the second-order region and the light scattering in the first-order region, we have determined the phase diagram for this metamagnetic tricritical point. A technique is described which permits simultaneous measurement of these properties using the ac calorimetric and Faraday rotation techniques. Data were collected along isotherms as functions of external field and were then corrected to internal field using the measured magnetization and demagnetizing factors. %e demonstrate that the data for the magnetization and heat capacity do not satisfy scaling relations with classical exponents, pe=2 and o. , =-, but may be made to "collapse" in the predicted manner only when o. , is permitted to take an effective value o. , ' =0.65. hen logarithmic correction factors of the form L (r) = 1-a6 ln(r) are included, however, the data collapse with classical exponents. The constant a6 is a nonuniversal amplitude which we find to be a6=0.S+0.2 and the field r is defined to vanish along the logarithmically correctedand experimentally observedsecond-order line. Along the first-order line, the behavior of the step change in magnetization is improved by logarithmic corrections, but the classical exponents are not fully recovered. The logarithmic factors occur in the scaled free energy such that, over any limited range of experimental data, they may be represented by power laws with effective exponents. The logarithmic factors appear to be more important for metamagnets suck as FeC12 and CsCoC13~2H20 (which behaves similarly) than for He-"He mixtures.

A discussion is presented on the role of limited conductivity and permittivity on the behavior of electrified jets. Under certain conditions, significant departures with respect to the perfect-conductor limit are to be expected. In addition, an exploration is undertaken concerning the validity of one-dimensional average models in the description of charged jets. To that end, a temporal linear modal stability analysis is carried out of poor-conductor viscous liquid jets flowing relatively to a steady radial electric field. Only axisymmetric perturbations, leading to highest quality aerosols, are considered. A grounded coaxial electrode is located at variable distance. Most available studies in the literature are restricted to the perfect-conductor limit, while the present contribution is an extension to moderate and low electrical conductivity and permittivity jets, in an effort to describe a situation increasingly prevalent in the sector of small-scale free-surface flows. The influence of the electrode distance b, a parameter ␣ defined as the ratio of the electric relaxation time scale to the capillary time scale, and the relative permittivity ␤ on the growth rate has been explored yielding results on the stability spectrum. In addition, arbitrary viscosity and electrification parameters are contemplated. In a wide variety of situations, the perfect-conductor limit provides a good approximation; however, the influence of ␣ and ␤ on the growth rate and most unstable wavelength cannot be neglected in the general case. An interfacial boundary layer in the axial velocity profile occurs in the low-viscosity limit, but this boundary layer tends to disappear when ␣ or ␤ are large enough. The use of a one-dimensional ͑1D͒ averaged model as an alternative to the 3D approach provides a helpful shortcut and a complementary insight on the nature of the jet's perturbative behavior. Lowest-order 1D approximations ͑average model͒, of widespread application in the literature of electrified jets, are shown to be inaccurate in low-viscosity imperfect-conductor jets.

We study structure, eigenvalue spectra and diffusion dynamics in a wide class of networks with subgraphs (modules) at mesoscopic scale. The networks are grown within the model with three parameters controlling the number of modules, their internal structure as scale-free and correlated subgraphs, and the topology of connecting network. Within the exhaustive spectral analysis for both the adjacency matrix and the normalized Laplacian matrix we identify the spectral properties which characterize the mesoscopic structure of sparse cyclic graphs and trees. The minimally connected nodes, clustering, and the average connectivity affect the central part of the spectrum. The number of distinct modules leads to an extra peak at the lower part of the Laplacian spectrum in cyclic graphs. Such a peak does not occur in the case of topologically distinct tree-subgraphs connected on a tree. Whereas the associated eigenvectors remain localized on the subgraphs both in trees and cyclic graphs. We also find a characteristic pattern of periodic localization along the chains on the tree for the eigenvector components associated with the largest eigenvalue equal 2 of the Laplacian. We corroborate the results with simulations of the random walk on several types of networks. Our results for the distribution of return-time of the walk to the origin (autocorrelator) agree well with recent analytical solution for trees, and it appear to be independent on their mesoscopic and global structure. For the cyclic graphs we find new results with twice larger stretching exponent of the tail of the distribution, which is virtually independent on the size of cycles. The modularity and clustering contribute to a power-law decay at short return times.

Wetlands represent an efficient wastewater treatment technique, with several benefits over the conventional activated sludge system. Microfaunal community is of outmost importance in treatment processes as the microorganisms are able to achieve substantial decontamination through biodegradation. The objectives of this work were the monitoring of protozoan's abundance and diversity in the matrix of six bench scale Free Water Surface constructed wetlands and the investigation of their applicability as indicator organisms for treatment efficiency in these systems. A correlation between the phosphorous and Total Coliforms removal rates was observed in the presence of increased protozoan taxa, while removal of organic loading and inorganic nitrogen was increased in the case of increased protozoan diversity in the soil/water interface. Results revealed that protozoa may be used as bioindicators of treatment efficiency in constructed wetlands; in addition their presence was related to the effluent quality.

El presente estudio además de analizar cuáles fueron las principales vías de aprovisionamiento de los productos de carácter suntuario más relevantes en los mercados romanos, pretende ofrecer al lector un nuevo escenario para el debate mediante la incorporación de las teorías de redes a un tema ya de por sí bastante prolífico: el comercio de productos orientales. Así, por primera vez, el uso de las crónicas chinas, junto con las fuentes clásicas (romanas), nos ha permitido comprobar
hasta qué punto existió similitud en los comentarios sobre las riquezas de la región que comprenden los territorios de Egipto y Próximo Oriente. Si a esta concomitancia le sumamos los resultados obtenidos por las teorías de redes, en particular las desarrolladas por Stanley Milgram en 1967, nos percatamos de la existencia de una serie de ciudades entre continentes que destacaron por su paso obligado, a modo de “superconectores” o hubs, como principales mercados suntuarios.

The paper discusses the role of networks in cognition on two levels: on the level of the organization of ideas, and on the level of interpersonal communication. Any interesting system of ideas forms a network: ideas presented in a linear order (the order forced upon us by verbal expression) will necessarily convey a distorted picture of the underlying patterns of thought. Networks of ideas typically consist of a great number of nodes with just a few links, and a small number of hubs with very many links; that is, they are, to employ Albert-László Barabási’s term, “scale-free.” Barabási fits into a specific tradition: Hungarians had an early influence on the philosophy of networks, and on the philosophy of communication as developed at Marshall McLuhan’s Toronto Circle. In fact, this was the circle in which certain Hungarian and Austrian ideas on mediated collective thinking first came together—a telling testimony to the conditions of disturbed communication and idiosyncratic networking typical of East-Central Europe, past and present. The nodes-and-hubs pattern is characteristic, too, of social networks, in particular of scholarly and scientific networks. The paper analyses the role of “invisible colleges”—informal groups of scientific elites through whom the communication of information both within a field and across fields is channelled. By way of conclusion the notion of a new type of personality, the “network individual,” is discussed: the network individual is the person reintegrated, after centuries of relative isolation induced by the printing press, into the collective thinking of society—the individual whose mind is manifestly mediated, once again, by the minds of those forming his/her smaller or larger community.

Esta presentación examina el surgimiento de la teoría de grafos, los desarrollos de la Escuela de Negocios de Harvard, los sociogramas de Jacob Lévy Moreno, los grafos de Bavelas en el MIT y la teoría de las redes sociales de la Escuela de Manchester en antropología, hasta los modelos de pequeños mundos (los “seis grados de separación”) de Milgram, Watts y Strogatz y las redes libres de escala de Barabási.
Los últimos desarrollos de la teoría de grafos y de la teoría de redes sociales complejas en particular ponen en tela de juicio infinidad de supuestos sobre la naturaleza de las redes en la vida real y sus estructuras estadísticas concomitantes, la “distribución normal” en particular. Gran parte de los procedimientos metodológicos usuales en la investigación socio-cultural, comenzando por el muestreo y la prueba estadística de la hipótesis nula, se revelan fallidos allí donde se manifiesta una distribución independiente de escala o ley de potencia.

The application of the network approach to the urban case poses several questions in terms of how to deal with metric distances, what kind of graph representation to use, what kind of measures to investigate, how to deepen the correlation between measures of the structure of the network and measures of the dynamics on the network, what are the possible contributions from the GIS community. In this paper, the author considers six cases of urban street networks characterized by different patterns and historical roots. The authors propose a representation of the street networks based firstly on a primal graph, where intersections are turned into nodes and streets into edges. In a second step, a dual graph, where streets are nodes and intersections are edges, is constructed by means of a generalization model named Intersection Continuity Negotiation, which allows to acknowledge the continuity of streets over a plurality of edges. Finally, the authors address a comparative study of some structural properties of the dual graphs, seeking significant similarities among clusters of cases. A wide set of network analysis techniques are implemented over the dual graph: in particular the authors show that the absence of any clue of assortativity differentiates urban street networks from other non-geographic systems and that most of the considered networks have a broad degree distribution typical of scale-free networks and exhibit small-world properties as well. r (V. Latora).

We construct complex networks from pseudoperiodic time series, with each cycle represented by a single node in the network. We investigate the statistical properties of these networks for various time series and find that time series with different dynamics exhibit distinct topological structures. Specifically, noisy periodic signals correspond to random networks, and chaotic time series generate networks that exhibit small world and scale free features. We show that this distinction in topological structure results from the hierarchy of unstable periodic orbits embedded in the chaotic attractor. Standard measures of structure in complex networks can therefore be applied to distinguish different dynamic regimes in time series. Application to human electrocardiograms shows that such statistical properties are able to differentiate between the sinus rhythm cardiograms of healthy volunteers and those of coronary care patients.