Maximal-entropy random walks in complex networks with limited information

J.G.-G. was supported by MICINN through the Ramon y Cajal program and by grants FIS2008-01240 and MTM2009-13848

Measuring and modeling correlations in multiplex networks

The authors acknowledge the support of the EU Seventh Framework Programme through the Project LASAGNE (Grant No. FP7-ICT-318132). This research utilized Queen Mary’s MidPlus computational facilities, supported by QMUL Research-IT and funded by EPSRC Grant No. EP/K000128/1

Evaluating the effects of sediment transport on pipe flow resistance

In this paper, the applicability of a theoretical flow resistance law to sediment-laden flow in pipes is tested. At first, the incomplete self-similarity (ISS) theory is applied to deduce the velocity profile and the corresponding flow resistance law. Then the available database of measurements carried out by clear water and sediment-laden flows with sediments having a quasi-uniform sediment size and three different values of the mean particle diameter Dm (0.88 mm, 0.41 mm and 0.30 mm) are used to calibrate the Γparameter of the power-velocity profile). The fitting of the measured local velocity to the power distribution demonstrates that (i) for clear flow the exponent δ) can be estimated by the equation of Castaing et al. and (ii) for the sediment-laden flows δ is related to the diameter Dm. A relationship for estimating the parameter Гv obtained by the power-velocity profile) and that Гf of the flow resistance law) is theoretically deduced. The relationship between the parameter Гv, the head loss per unit length and the pipe flow Froude number is also obtained by the available sediment-laden pipe flow data. Finally, the procedure to estimate the Darcy–Weisbach friction factor is tested by the available measurements

Quantifying ethnic segregation in cities through random walks

Socioeconomic segregation has an important role in the emergence of large-scale inequalities in urban areas. Most of the available measures of spatial segregation depend on the scale and size of the system under study, or neglect large-scale spatial correlations, or rely on ad-hoc parameters, making it hard to compare different systems on equal grounds. We propose here a family of non-parametric measures for spatial distributions, based on the statistics of the trajectories of random walks on graphs associated to a spatial system. These quantities provide a consistent estimation of segregation in synthetic spatial patterns, and we use them to analyse the ethnic segregation of metropolitan areas in the US and the UK. We show that the spatial diversity of ethnic distributions, as measured through diffusion on graphs, allow us to compare the ethnic segregation of urban areas having different size, shape, or peculiar microscopic characteristics, and exhibits a strong association with socio-economic deprivation

Network structure of multivariate time series.

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail

Effects of biochar addition on rill flow resistance

The development of rills on a hillslope whose soil is amended by biochar remains a topic to be developed. A theoretical rill flow resistance equation, obtained by the integration of a power velocity distribution, was assessed using available measurements at plot scale with a biochar added soil. The biochar was incorporated and mixed with the arable soil using a biochar content BC of 6 and 12 kg m 122. The developed analysis demonstrated that an accurate estimate of the velocity profile parameter \u413v can be obtained by the proposed power equation using an exponent e of the Reynolds number which decreases for increasing BC values. This result pointed out that the increase of bio-char content dumps flow turbulence. The agreement between the measured friction factor values and those calculated by the proposed flow resistance equation, with \u413v values estimated by the power equation calibrated on the available measurements, is characterized by errors which are al-ways less than or equal to \ub110% and less than or equal to \ub13% for 75.0% of cases. In conclusion, the available measurements and the developed analysis allowed for (i) the calibration of the relationship between \u413v, the bed slope, the flow Froude number, and the Reynolds number, (ii) the assessment of the influence of biochar content on flow resistance and, (iii) stating that the theoretical flow resistance equation gives an accurate estimate of the Darcy\u2013Weisbach friction factor for rill flows on biochar added soils

Multilayer motif analysis of brain networks

This work was partially supported by the EU-LASAGNE Project, Contract No. 318132 (STREP)