Rich-club vs rich-multipolarization phenomena in weighted networks

Large scale hierarchies characterize complex networks in different domains. Elements at their top, usually the most central or influential, may show multipolarization or tend to club forming tightly interconnected communities. The rich-club phenomenon quantified this tendency based on unweighted network representations. Here, we define this metric for weighted networks and discuss the appropriate normalization which preserves nodes' strengths and discounts structural strength-strength correlations if present. We find that in some real networks the results given by the weighted rich-club coefficient can be in sharp contrast to the ones in the unweighted approach. We also discuss that the scanning of the weighted subgraphs formed by the high-strength hubs is able to unveil features contrary to the average: the formation of local alliances in rich-multipolarized environments, or a lack of cohesion even in the presence of rich-club ordering. Beyond structure, this analysis matters for understanding correctly functionalities and dynamical processes relying on hub interconnectedness.Comment: 12 pages, 2 figure

Interfaces and the edge percolation map of random directed networks

The traditional node percolation map of directed networks is reanalyzed in terms of edges. In the percolated phase, edges can mainly organize into five distinct giant connected components, interfaces bridging the communication of nodes in the strongly connected component and those in the in- and out-components. Formal equations for the relative sizes in number of edges of these giant structures are derived for arbitrary joint degree distributions in the presence of local and two-point correlations. The uncorrelated null model is fully solved analytically and compared against simulations, finding an excellent agreement between the theoretical predictions and the edge percolation map of synthetically generated networks with exponential or scale-free in-degree distribution and exponential out-degree distribution. Interfaces, and their internal organization giving place from "hairy ball" percolation landscapes to bottleneck straits, could bring new light to the discussion of how structure is interwoven with functionality, in particular in flow networks.Comment: 20 pages, 4 figure

Generalized percolation in random directed networks

We develop a general theory for percolation in directed random networks with arbitrary two point correlations and bidirectional edges, that is, edges pointing in both directions simultaneously. These two ingredients alter the previously known scenario and open new views and perspectives on percolation phenomena. Equations for the percolation threshold and the sizes of the giant components are derived in the most general case. We also present simulation results for a particular example of uncorrelated network with bidirectional edges confirming the theoretical predictions

Clustering in complex networks. I. General formalism

We develop a full theoretical approach to clustering in complex networks. A key concept is introduced, the edge multiplicity, that measures the number of triangles passing through an edge. This quantity extends the clustering coefficient in that it involves the properties of two --and not just one-- vertices. The formalism is completed with the definition of a three-vertex correlation function, which is the fundamental quantity describing the properties of clustered networks. The formalism suggests new metrics that are able to thoroughly characterize transitive relations. A rigorous analysis of several real networks, which makes use of the new formalism and the new metrics, is also provided. It is also found that clustered networks can be classified into two main groups: the {\it weak} and the {\it strong transitivity} classes. In the first class, edge multiplicity is small, with triangles being disjoint. In the second class, edge multiplicity is high and so triangles share many edges. As we shall see in the following paper, the class a network belongs to has strong implications in its percolation properties

Retos y oportunidades de la digitalización en la agricultura, la silvicultura y las áreas rurales

DESIRA- Digitalisation: Social and Economic Impacts in Rural Areas es un proyecto Horizonte 2020, que tiene por objetivo analizar los impactos socioeconómicos de la digitalización en áreas rurales y mejorar la capacidad de respuesta de la sociedad y las entidades políticas ante los retos que la digitalización generará en la agricultura, la silvicultura y las áreas rurales. El proyecto de investigación cuenta con 22 ‘Living Labs’ distribuidos por toda Europa que estudian el proceso de digitalización en diferentes escenarios (certificación maderera, agricultura de precisión, incendios forestales, etc.). En cada uno de ellos se identifican y analizan las circunstancias, medidas y/o normativas que puedan perjudicar o facilitar la adopción de tecnologías digitales en la agricultura, la silvicultura y las áreas rurales. Esta información es crucial para facilitar la transición digital y minimizar los potenciales impactos negativos en la sociedad que la adopción de estas nuevas tecnologías pueda generar en los próximos 10 años. Los resultados de este proyecto proporcionarán información útil para afrontar los retos y explotar al máximo las oportunidades relacionadas con la digitalización en la agricultura y las áreas rurales y para diseñar la proxima generación de políticas para las áreas rurales

Distinguishing the albedo of exoplanets from stellar activity

Light curves show the flux variation from the target star and its orbiting planets as a function of time. In addition to the transit features created by the planets, the flux also includes the reflected light component of each planet, which depends on the planetary albedo. This signal is typically referred to as phase curve and could be easily identified if there were no additional noise. As well as instrumental noise, stellar activity, such as spots, can create a modulation in the data, which may be very difficult to distinguish from the planetary signal. We analyze the limitations imposed by the stellar activity on the detection of the planetary albedo, considering the limitations imposed by the predicted level of instrumental noise and the short duration of the observations planned in the context of the CHEOPS mission. As initial condition, we have assumed that each star is characterized by just one orbiting planet. We built mock light curves that included a realistic stellar activity pattern, the reflected light component of the planet and an instrumental noise level, which we have chosen to be at the same level as predicted for CHEOPS. We then fit these light curves to try to recover the reflected light component, assuming the activity patterns can be modeled with a Gaussian process.We estimate that at least one full stellar rotation is necessary to obtain a reliable detection of the planetary albedo. This result is independent of the level of noise, but it depends on the limitation of the Gaussian process to describe the stellar activity when the light curve time-span is shorter than the stellar rotation. Finally, in presence of typical CHEOPS gaps in the simulations, we confirm that it is still possible to obtain a reliable albedo.Comment: Accepted for publication in A&A, 14 pages, 12 figure

Competition and adaptation in an Internet evolution model

We model the evolution of the Internet at the Autonomous System level as a process of competition for users and adaptation of bandwidth capability. We find the exponent of the degree distribution as a simple function of the growth rates of the number of autonomous systems and the total number of connections in the Internet, both empirically measurable quantities. This fact place our model apart from others in which this exponent depends on parameters that need to be adjusted in a model dependent way. Our approach also accounts for a high level of clustering as well as degree-degree correlations, both with the same hierarchical structure present in the real Internet. Further, it also highlights the interplay between bandwidth, connectivity and traffic of the network.Comment: Minor content changes and inset of fig.

Determinants of profitability in Spanish financial institutions. Comparing aided and non-aided entities

The last financial crisis has led to the greatest contribution of public funds ever made to Spanish banks. This paper studies why the need for support has been asymmetric, with not all of the institutions requiring aid. Based on profitability of assets (ROA), we determine using panel data econometric and logit response models the components of profit and loss accounts that generated profitability as well as the factors leading to some entities to ask for aid. The analyses show that before the beginning of the crisis there were significant differences between entities that needed aid and those that did not. The most profitable banks grounded their success in the traditional revenue components of financial institutions (such as margin on interest rates and commissions), as well as in revenues obtained from participated companies and extraordinary results. The model offers a tool to detect entities in difficulties in advance, reducing the financial and social costs of public interventions. The factors more impacting on profitability of Spanish institutions are also identifie