Sequential visibility-graph motifs

Visibility algorithms transform time series into graphs and encode dynamical information in their topology, paving the way for graph-theoretical time series analysis as well as building a bridge between nonlinear dynamics and network science. In this work we introduce and study the concept of sequential visibility graph motifs, smaller substructures of n consecutive nodes that appear with characteristic frequencies. We develop a theory to compute in an exact way the motif profiles associated to general classes of deterministic and stochastic dynamics. We find that this simple property is indeed a highly informative and computationally efficient feature capable to distinguish among different dynamics and robust against noise contamination. We finally confirm that it can be used in practice to perform unsupervised learning, by extracting motif profiles from experimental heart-rate series and being able, accordingly, to disentangle meditative from other relaxation states. Applications of this general theory include the automatic classification and description of physical, biological, and financial time series

Study of RPC gas mixtures for the ARGO-YBJ experiment

The ARGO-YBJ experiment consists of a RPC carpet to be operated at the Yangbajing laboratory (Tibet, P.R. China), 4300 m a.s.l., and devoted to the detection of showers initiated by photon primaries in the energy range 100 GeV - 20 TeV. The measurement technique, namely the timing on the shower front with a few tens of particles, requires RPC operation with 1 ns time resolution, low strip multiplicity, high efficiency and low single counting rate. We have tested RPCs with many gas mixtures, at sea level, in order to optimize these parameters. The results of this study are reported.Comment: 6 pages, 3 figures. To be published in Nucl. Instr. Meth. A, talk given at the "5th International Workshop on RPCs and Related Detectors", Bari (Italy) 199

Functional Multiplex PageRank

(7 pages, 5 figures)(7 pages, 5 figures)(7 pages, 5 figures

Urinary Bladder Volume Reconstruction Based on Bioimpedance Measurements: Ex Vivo and In Vivo Validation Through Implanted Patch and Needle Electrodes

Restoring bladder sensation in patients with bladder dysfunctions by performing urinary volume monitoring is an ambitious goal. The bioimpedance technique has shown promising results in wearable solutions but long-term validation and implantable systems are not available, yet. In this work, we propose to implant commercial bioimpedance sensors on bladder walls to perform bladder volume estimation. Two commercial sensor types (Ag/AgCl patch and needle electrodes) were selected to this purpose. Injected current frequency of 1.337 MHz and electrodes pair on the same face of the bladder allowed to correlate the changes in impedance with increasing volumes. Two volume reconstruction algorithms have been proposed, based on the direct correlation between bioimpedance readings and bladder volume (Algorithm A) or bioimpedance readings and inter-electrode distance (Algorithm B, bladder shape approximated to a sphere). For both algorithms, a better fit with a second-degree fitting polynomial was obtained. Algorithm A obtained lower estimation errors with an average of 20.35% and 21.98% (volumes greater than 150 ml) for patch and needle electrodes, respectively. The variations in ions concentration led to a slight deterioration of volume estimation, however the presence of tissues surrounding the bladder did not influence the performance. Although Algorithm B was less affected by the experimental conditions and inter-subject biological variability, it featured higher estimation errors. In vivo validation on suine model showed average errors of 29.36% (volumes greater than 100 ml), demonstrating the potential of the proposed solution and paving the way towards a novel implantable volume monitoring system

Triadic closure as a basic generating mechanism of communities in complex networks

R.K.D. and S.F. gratefully acknowledge MULTIPLEX, Grant No. 317532 of the European Commission

A general estimator of the primary cosmic ray energy with the ARGO-YBJ experiment

The determination of the primary cosmic ray all-particle spectrum with ground-based air shower experiments usually depends on the assumed elemental composition and hadronic interaction model. Here we show that an energy estimator independent of the primary mass composition can be defined by means of shower parameters measured in the core region, as carried out in the ARGO-YBJ experiment. The energy resolution is <10% above 100 TeV and gets better with energy increasing. Being insensitive to the number of muons, this energy determination has only a weak dependence on the hadronic interaction model. The features of this energy estimator have been validated by extensive MC simulations and used in the analysis of the ARGO-YBJ data