Integrating defeasible argumentation with fuzzy ART neural networks for pattern classification

Many classification systems rely on clustering techniques in which a collection of training examples is provided as an input, and a number of clusters c1,...cm modelling some concept C results as an output, such that every cluster ci is labelled as positive or negative. Given a new, unlabelled instance enew, the above classification is used to determine to which particular cluster ci this new instance belongs. In such a setting clusters can overlap, and a new unlabelled instance can be assigned to more than one cluster with conflicting labels. In the literature, such a case is usually solved non-deterministically by making a random choice. This paper presents a novel, hybrid approach to solve this situation by combining a neural network for classification along with a defeasible argumentation framework which models preference criteria for performing clustering.

Modelling bird species richness with neural networks for forest landscape management in NE Spain

Para preservar la biodiversidad de los ecosistemas forestales de la Europa mediterránea en escenarios actuales y futuros de cambio global mediante una gestión forestal sostenible es necesario determinar cómo influye el medio ambiente y las propias características de los bosques sobre la biodiversidad que éstos albergan. Con este propósito, se analizó la influencia de diferentes factores ambientales y de estructura y composición del bosque sobre la riqueza de aves forestales a escala 1 × 1 km en Cataluña (NE de España). Se construyeron modelos univariantes y multivariantes de redes neuronales para respectivamente explorar la respuesta individual a las variables y obtener un modelo parsimonioso (ecológicamente interpretable) y preciso. La superficie de bosque (con una fracción de cabida cubierta superior a 5%), la fracción de cabida cubierta media, la temperatura anual y la precipitación estival medias fueron los mejores predictores de la riqueza de aves forestales. La red neuronal multivariante obtenida tuvo una buena capacidad de generalización salvo en las localidades con una mayor riqueza. Además, los bosques con diferentes grados de apertura del dosel arbóreo, más maduros y más diversos en cuanto a su composición de especies arbóreas se asociaron de forma positiva con una mayor riqueza de aves forestales. Finalmente, se proporcionan directrices de gestión para la planificación forestal que permitan promover la diversidad ornítica en esta región de la Europa mediterránea.

Protective effects of social networks on disability among older adults in Spain

The loss of autonomy at advanced ages is not only associated with ageing, but also with the characteristics of the physical and social environment. Recent investigations have shown that social networks, social engagement and participation act like predictors of disability among the elderly. The aim of this study is to determine whether social networks are related to the development and progression of disability in the early years of old age. The source of data is the first wave of the survey "Processes of Vulnerability among Spanish Elderly", carried out in 2005 to a sample of 1 244 individuals. The population object of study is the cohort aged 70 to 74 years in metropolitan areas (Madrid and Barcelona) and not institutionalized. Disability is measured by the development of basic activities of daily life (ADL), and instrumental activities of daily life (IADL). The structural aspects of the social relationships are measured through the diversity of social networks and participation. We used the social network index (SNI). For each point over the SNI, the risk of developing any type of disability decreased by 49% (HR = 0.51, 95%CI = 0.31-0.82). The SNI was a decisive factor in all forecasting models constructed with some hazard ratios (HR) that ranged from 0.29 (95%CI = 0.14-0.59) in the first model to 0.43 (95%CI 0.20-0.90) in the full model. The results of the present study showed a strong association between an active social life, emotional support provided by friends and confidents and disability. These findings suggest a protective effect of social networks on disability. Also, these results indicate that some family and emotional ties have a significant effect on both the prevalence and the incidence of disability.

Using narratives to study the impact of social networks on the educational paths of immigrant students

This paper presents the qualitative data collection process aimed at the study of the impactsocial relations and networks have on educational paths of immigrant students. In theframework of a R & D longitudinal study funded by the Ministry of Science and Innovation(2012-2014), the research team tracked the path of 87 immigrant students, from whom only 17successfully achieved the transition through the first and second year of Post-16 Education.A vast range of literature notes that relationships are an important part of migration process andsocial integration analysis, as well as school history in terms of success or failure. Through thefieldwork researchers collect the personal networks of all immigrant students from 3 highschools who were at that time attending last course of compulsory school. The network structureinfluences their social capital and therefore determines the resources, goods and types of supportindividuals can access. All these aspects are influential elements in the configuration anddevelopment of academic trajectories of immigrant students.At the end of the second year of Post-16 Education (two years later), the study captures personalnetworks of these students again, analyses and discusses their evolution and influence on theirpaths through qualitative interviews. Such interviews facilitated the discussion of theirrelationships while providing interesting narratives that are presented in the text. In order to do so, the biographical interpretive narrative method of interviewing is implemented.

Using narratives to study the impact of social networks on the educational paths of immigrant students

This paper presents the qualitative data collection process aimed at the study of the impactsocial relations and networks have on educational paths of immigrant students. In theframework of a R & D longitudinal study funded by the Ministry of Science and Innovation(2012-2014), the research team tracked the path of 87 immigrant students, from whom only 17successfully achieved the transition through the first and second year of Post-16 Education.A vast range of literature notes that relationships are an important part of migration process andsocial integration analysis, as well as school history in terms of success or failure. Through thefieldwork researchers collect the personal networks of all immigrant students from 3 highschools who were at that time attending last course of compulsory school. The network structureinfluences their social capital and therefore determines the resources, goods and types of supportindividuals can access. All these aspects are influential elements in the configuration anddevelopment of academic trajectories of immigrant students.At the end of the second year of Post-16 Education (two years later), the study captures personalnetworks of these students again, analyses and discusses their evolution and influence on theirpaths through qualitative interviews. Such interviews facilitated the discussion of theirrelationships while providing interesting narratives that are presented in the text. In order to do so, the biographical interpretive narrative method of interviewing is implemented.

Percolation of spatially constrained Erdos-R enyi networks with degree correlations

Motivated by experiments on activity in neuronal cultures [J. Soriano, M. Rodr ́ıguez Mart́ınez, T. Tlusty, and E. Moses, Proc. Natl. Acad. Sci. 105, 13758 (2008)], we investigate the percolation transition and critical exponents of spatially embedded Erd̋os-Ŕenyi networks with degree correlations. In our model networks, nodes are randomly distributed in a two-dimensional spatial domain, and the connection probability depends on Euclidian link length by a power law as well as on the degrees of linked nodes. Generally, spatial constraints lead to higher percolation thresholds in the sense that more links are needed to achieve global connectivity. However, degree correlations favor or do not favor percolation depending on the connectivity rules. We employ two construction methods to introduce degree correlations. In the first one, nodes stay homogeneously distributed and are connected via a distance- and degree-dependent probability. We observe that assortativity in the resulting network leads to a decrease of the percolation threshold. In the second construction methods, nodes are first spatially segregated depending on their degree and afterwards connected with a distance-dependent probability. In this segregated model, we find a threshold increase that accompanies the rising assortativity. Additionally, when the network is constructed in a disassortative way, we observe that this property has little effect on the percolation transition.

Use of social networks for academic purposes: a case study

Purpose- This paper aims to analyse various aspects of an academic social network: the profile of users, the reasons for its use, its perceived benefits and the use of other social media for scholarly purposes. Design/methodology/approach- The authors examined the profiles of the users of an academic social network. The users were affiliated with 12 universities. The following were recorded for each user: sex, the number of documents uploaded, the number of followers, and the number of people being followed. In addition, a survey was sent to the individuals who had an email address in their profile. Findings- Half of the users of the social network were academics and a third were PhD students. Social sciences scholars accounted for nearly half of all users. Academics used the service to get in touch with other scholars, disseminate research results and follow other scholars. Other widely employed social media included citation indexes, document creation, edition and sharing tools and communication tools. Users complained about the lack of support for the utilisation of these tools. Research limitations/implications- The results are based on a single case study. Originality/value- This study provides new insights on the impact of social media in academic contexts by analysing the user profiles and benefits of a social network service that is specifically targeted at the academic community.

Research networks and scientific production in Economics: the recent Spanish experience

This paper studies Spanish scientific production in Economics from 1994 to 2004. It focuses on aspects that have received little attention in other bibliometric studies, such as the impact of research and the role of scientific collaborations in the publications produced by Spanish universities. Our results show that national research networks have played a fundamental role in the increase in Spanish scientific production in this discipline.

Nature of the Epidemic Threshold for the Susceptible-Infected-Susceptible Dynamics in Networks

We develop an analytical approach to the susceptible-infected-susceptible epidemic model that allows us to unravel the true origin of the absence of an epidemic threshold in heterogeneous networks. We find that a delicate balance between the number of high degree nodes in the network and the topological distance between them dictates the existence or absence of such a threshold. In particular, small-world random networks with a degree distribution decaying slower than an exponential have a vanishing epidemic threshold in the thermodynamic limit.

Statistical mechanics of multi-edge networks

Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There are, however, subtle yet important considerations to be made regarding the nature of the weights used in this generalization. Weights can be either continuous or discrete magnitudes, and in the latter case, they can additionally have undistinguishable or distinguishable nature. This fact has not been addressed in the literature insofar and has deep implications on the network statistics. In this work we face this problem introducing multiedge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multiedges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multiedge processes. The implications of these results are important as many real-agent-based problems mapped onto graphs require this treatment for a proper characterization of their collective behavior.

Spectral properties of the Laplacian of multiplex networks.

One of the more challenging tasks in the understanding of dynamical properties of models on top of complex networks is to capture the precise role of multiplex topologies. In a recent paper, Gómez et al. [ Phys. Rev. Lett. 110 028701 (2013)], some of the authors proposed a framework for the study of diffusion processes in such networks. Here, we extend the previous framework to deal with general configurations in several layers of networks and analyze the behavior of the spectrum of the Laplacian of the full multiplex. We derive an interesting decoupling of the problem that allow us to unravel the role played by the interconnections of the multiplex in the dynamical processes on top of them. Capitalizing on this decoupling we perform an asymptotic analysis that allow us to derive analytical expressions for the full spectrum of eigenvalues. This spectrum is used to gain insight into physical phenomena on top of multiplex, specifically, diffusion processes and synchronizability.

A systems biology approach identifies molecular networks defining skeletal muscle abnormalities in chronic obstructive pulmonary disease.

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory process of the lung inducing persistent airflow limitation. Extensive systemic effects, such as skeletal muscle dysfunction, often characterize these patients and severely limit life expectancy. Despite considerable research efforts, the molecular basis of muscle degeneration in COPD is still a matter of intense debate. In this study, we have applied a network biology approach to model the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. Our model shows that failure to co- ordinately activate expression of several tissue remodelling and bioenergetics pathways is a specific landmark of COPD diseased muscles. Our findings also suggest that this phenomenon may be linked to an abnormal expression of a number of histone modifiers, which we discovered correlate with oxygen utilization. These observations raised the interesting possibility that cell hypoxia may be a key factor driving skeletal muscle degeneration in COPD patients.

Networks of noisy oscillators with correlated degree and frequency dispersion

We investigate how correlations between the diversity of the connectivity of networks and the dynamics at their nodes affect the macroscopic behavior. In particular, we study the synchronization transition of coupled stochastic phase oscillators that represent the node dynamics. Crucially in our work, the variability in the number of connections of the nodes is correlated with the width of the frequency distribution of the oscillators. By numerical simulations on Erdös-Rényi networks, where the frequencies of the oscillators are Gaussian distributed, we make the counterintuitive observation that an increase in the strength of the correlation is accompanied by an increase in the critical coupling strength for the onset of synchronization. We further observe that the critical coupling can solely depend on the average number of connections or even completely lose its dependence on the network connectivity. Only beyond this state, a weighted mean-field approximation breaks down. If noise is present, the correlations have to be stronger to yield similar observations.

Las entidades sub-nacionales en Norteamérica y la lucha contra el cambio climático: desarrollo normativo y vinculación de sistemas de comercio de derechos de emisión

[spa] Mientras que en Europa la interdependencia y la dimensión transfronteriza de las cuestiones ligadas al cambio climático ha facilitado una cierta"continentalización" de la gestión de este fenómeno, favorecida por el carácter intergubernamental de las medidas que se adoptan en el marco de la Unión Europea, al otro lado del Atlántico la transversalidad de este mismo fenómeno explica la necesidad de que, ante las limitaciones del marco regional, se pongan en marcha mecanismos que faciliten la intervención no sólo estatal sino también de las entidades sub-nacionales. En este sentido, la ausencia de la acción federal tanto en Estados Unidos como en Canadá ha comportado un mayor desarrollo de la acción de las entidades sub-nacionales, que han tomado el liderazgo en la lucha contra el cambio climático. Son estas medidas las que se han visualizado en el escenario internacional. Ello ha favorecido el establecimiento de mecanismos de coordinación de la acción de estas entidades sub-nacionales en el seno de redes transnacionales, que han ido adquiriendo una mayor relevancia en la implementación del Convenio Marco sobre el Cambio Climático y del Protocolo de Kyoto, particularmente en relación a uno de sus instrumentos, el comercio de los derechos de emisión de gases de efecto invernadero. En este contexto, la futura vinculación de los sistemas de comercio de derechos de emisión de gases de efecto invernadero en Norteamérica con el sistema de la Unión Europea presenta diversos retos de carácter material y formal.

Research networks and inventors’ mobility as drivers of innovation evidence from Europe

We investigate the importance of the labour mobility of inventors, as well as the scale, extent and density of their collaborative research networks, for regional innovation outcomes. To do so, we apply a knowledge production function framework at the regional level and include inventors’ networks and their labour mobility as regressors. Our empirical approach takes full account of spatial interactions by estimating a spatial lag model together, where necessary, with a spatial error model. In addition, standard errors are calculated using spatial heteroskedasticity and autocorrelation consistent estimators to ensure their robustness in the presence of spatial error autocorrelation and heteroskedasticity of unknown form. Our results point to the existence of a robust positive correlation between intraregional labour mobility and regional innovation, whilst the relationship with networks is less clear. However, networking across regions positively correlates with a region’s innovation intensity.