Dynamical properties of model communication networks

We study the dynamical properties of a collection of models for communication processes, characterized by a single parameter $\xi$ representing the relation between information load of the nodes and its ability to deliver this information. The critical transition to congestion reported so far occurs only for $\xi=1$. This case is well analyzed for different network topologies. We focus of the properties of the order parameter, the susceptibility and the time correlations when approaching the critical point. For $\xi<1$ no transition to congestion is observed but it remains a cross-over from a low-density to a high-density state. For $\xi>1$ the transition to congestion is discontinuous and congestion nuclei arise.Comment: 8 pages, 8 figure

Improving signal stability in a multi-electrode array (MEA) system for cardiac biopsies

This work evaluates the performance of a microelectrode array (MEA) to be used in a specific platform dedicated for measuring field potentials of small human cardiac samples. A test bench has been developed to characterize the electrodes by measuring their impedance as well as to modify their characteristic curve using a replatinization process, where black platinum is deposited on the indicated areas of the MEA flex-pcb. This set-up consists of the array of microelectrodes made of gold, together with its corresponding electronic adapter board, a potentiostat and an electrochemical interface. Phosphate buffered saline (PBS), which is commonly considered for this type of analysis, has been used for impedance characterization. Initially, the impedance presents a highly variable behavior at different frequencies as well as between the different channels of the array. Once the platinization process has been carried out, the impedance in all the recording channels is very similar and has decreased over a large part of the frequency range under study. A complete electrical model of the electrodes has been proposed and analyzed, achieving better results by including the mathematical constant phase element (CPE) associated with capacitive behavior (model fitting error < 2%). Finally, the characterization of the different noise contributions has been carried out. Based on the obtained results, it can be concluded that the evaluated system allows the recording of field potential signals from small human cardiac tissues

Theoretical approach and impact of correlations on the critical packet generation rate in traffic dynamics on complex networks

Using the formalism of the biased random walk in random uncorrelated networks with arbitrary degree distributions, we develop theoretical approach to the critical packet generation rate in traffic based on routing strategy with local information. We explain microscopic origins of the transition from the flow to the jammed phase and discuss how the node neighbourhood topology affects the transport capacity in uncorrelated and correlated networks.Comment: 6 pages, 5 figure

Detecting rich-club ordering in complex networks

Uncovering the hidden regularities and organizational principles of networks arising in physical systems ranging from the molecular level to the scale of large communication infrastructures is the key issue for the understanding of their fabric and dynamical properties [1-5]. The ``rich-club'' phenomenon refers to the tendency of nodes with high centrality, the dominant elements of the system, to form tightly interconnected communities and it is one of the crucial properties accounting for the formation of dominant communities in both computer and social sciences [4-8]. Here we provide the analytical expression and the correct null models which allow for a quantitative discussion of the rich-club phenomenon. The presented analysis enables the measurement of the rich-club ordering and its relation with the function and dynamics of networks in examples drawn from the biological, social and technological domains.Comment: 1 table, 3 figure

Edge based stochastic block model statistical inference

Community detection in graphs often relies on ad hoc algorithms with no clear specification about the node partition they define as the best, which leads to uninterpretable communities. Stochastic block models (SBM) offer a framework to rigorously define communities, and to detect them using statistical inference method to distinguish structure from random fluctuations. In this paper, we introduce an alternative definition of SBM based on edge sampling. We derive from this definition a quality function to statistically infer the node partition used to generate a given graph. We then test it on synthetic graphs, and on the zachary karate club network

Extracting the hierarchical organization of complex systems

Extracting understanding from the growing ``sea'' of biological and socio-economic data is one of the most pressing scientific challenges facing us. Here, we introduce and validate an unsupervised method that is able to accurately extract the hierarchical organization of complex biological, social, and technological networks. We define an ensemble of hierarchically nested random graphs, which we use to validate the method. We then apply our method to real-world networks, including the air-transportation network, an electronic circuit, an email exchange network, and metabolic networks. We find that our method enables us to obtain an accurate multi-scale descriptions of a complex system.Comment: Figures in screen resolution. Version with full resolution figures available at http://amaral.chem-eng.northwestern.edu/Publications/Papers/sales-pardo-2007.pd

Depositional and structural controls on a fault-related dolostone formation (Maestrat Basin, E Spain)

Acknowledgments This research was funded by the Natural Environment Research Council (NERC) Centre for Doctoral Training (CDT) in Oil & Gas, through a PhD grant to EH. Equinor ASA are thanked for providing additional support. Additional funding was provided by the Grup Consolidat de Recerca “Geologia Sedimentària” (2017SGR-824) and DGICYT Spanish Projects CGL2017-85532-P, PGC2018-093903-B-C22 and PID2020-118999GB-I00, all funded by the Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER). EGR acknowledges the Spanish Ministry of Science, Innovation and Universities for the “Ramón y Cajal” fellowship RYC2018-026335-I. EH, EGR, JDM and JN conceived the idea and provided funding whilst field data was collected by EH, EGR, and JDM. EH organised the sampling for geochemical analysis (supervised by JDM) and RS and JG provided the regional stratigraphic context and structural cross-section. Petrographic data was collected by EH (supervised by JN). EH wrote the manuscript with edits and contributions provided by all co authors.Peer reviewedPublisher PD

eBay users form stable groups of common interest

Market segmentation of an online auction site is studied by analyzing the users' bidding behavior. The distribution of user activity is investigated and a network of bidders connected by common interest in individual articles is constructed. The network's cluster structure corresponds to the main user groups according to common interest, exhibiting hierarchy and overlap. Key feature of the analysis is its independence of any similarity measure between the articles offered on eBay, as such a measure would only introduce bias in the analysis. Results are compared to null models based on random networks and clusters are validated and interpreted using the taxonomic classifications of eBay categories. We find clear-cut and coherent interest profiles for the bidders in each cluster. The interest profiles of bidder groups are compared to the classification of articles actually bought by these users during the time span 6-9 months after the initial grouping. The interest profiles discovered remain stable, indicating typical interest profiles in society. Our results show how network theory can be applied successfully to problems of market segmentation and sociological milieu studies with sparse, high dimensional data.Comment: Major revision of the manuscript. Methodological improvements and inclusion of analysis of temporal development of user interests. 19 pages, 12 figures, 5 table