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.

Ten years after the Prestige Oil Spill: seabird trophic ecology as indicator of long-term effects on the coastal marine ecosystem

Major oil spills can have long-term impacts since oil pollution does not only result in acute mortality of marine organisms, but also affects productivity levels, predator-prey dynamics, and damages habitats that support marine communities. However, despite the conservation implications of oil accidents, the monitoring and assessment of its lasting impacts still remains a difficult and daunting task. Here, we used European shags to evaluate the overall, lasting effects of the Prestige oil spill (2002) on the affected marine ecosystem. Using δ15N and Hg analysis, we trace temporal changes in feeding ecology potentially related to alterations of the food web due to the spill. Using climatic and oceanic data, we also investigate the influence of North Atlantic Oscillation (NAO) index, the sea surface temperature (SST) and the chlorophyll a (Chl a) on the observed changes. Analysis of δ15N and Hg concentrations revealed that after the Prestige oil spill, shag chicks abruptly switched their trophic level from a diet based on a high percentage of demersal-benthic fish to a higher proportion of pelagic/semi-pelagic species. There was no evidence that Chl a, SST and NAO reflected any particular changes or severity in environmental conditions for any year or season that may explain the sudden change observed in trophic level. Thus, this study highlighted an impact on the marine food web for at least three years. Our results provide the best evidence to date of the long-term consequences of the Prestige oil spill. They also show how, regardless of wider oceanographic variability, lasting impacts on predator-prey dynamics can be assessed using biochemical markers. This is particularly useful if larger scale and longer term monitoring of all trophic levels is unfeasible due to limited funding or high ecosystem complexity.

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.

Stable isotopes unveil habitat partitioning among the marine mammals off NW Africa and reveal unique trophic niches for two globally threatened species.

Stable isotope abundances of carbon (δ13C) and nitrogen (δ15N) in the bone of 13 species of marine mammals from the northwest coast of Africa were investigated to assess their positions in the local trophic web and their preferred habitats. Also, samples of primary producers and potential prey species from the study area were collected to characterise the local isotopic landscape. This characterisation indicated that δ13C values increased from offshore to nearshore and that δ15N was a good proxy for trophic level. Therefore, the most coastal species were Monachus monachus and Sousa teuszii, whereas the most pelagic were Physeter macrocephalus and Balaenoptera acutorostrata. δ15N values indicated that marine mammals located at the lowest trophic level were B. acutorostrata, Stenella coeruleoalba and Delphinus sp., and those occupying the highest trophic level were M. monachus and P. macrocephalus. The trophic level of Orcinus orca was similar to that of M. monachus, suggesting that O. orca preys on fish. Conservation of coastal and threatened species (M. monachus and S. teuszii) off NW Africa should be a priority because these species, as the main apex predators, cannot be replaced by other marine mammals.

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.

Cosmological networks

Networks often represent systems that do not have a long history of study in traditional fields of physics; albeit, there are some notable exceptions, such as energy landscapes and quantum gravity. Here, we consider networks that naturally arise in cosmology. Nodes in these networks are stationary observers uniformly distributed in an expanding open Friedmann-Lemaitre-Robertson-Walker universe with any scale factor and two observers are connected if one can causally influence the other. We show that these networks are growing Lorentz-invariant graphs with power-law distributions of node degrees. These networks encode maximum information about the observable universe available to a given observer.

Generalization transitions in Hidden-Layer neural networks for third-order feature discrimination

Stochastic learning processes for a specific feature detector are studied. This technique is applied to nonsmooth multilayer neural networks requested to perform a discrimination task of order 3 based on the ssT-block¿ssC-block problem. Our system proves to be capable of achieving perfect generalization, after presenting finite numbers of examples, by undergoing a phase transition. The corresponding annealed theory, which involves the Ising model under external field, shows good agreement with Monte Carlo simulations.