An affected core drives network integration deficits of the structural connectome in 22q11.2 deletion syndrome.

Chromosome 22q11.2 deletion syndrome (22q11DS) is a genetic disease known to lead to cerebral structural alterations, which we study using the framework of the macroscopic white-matter connectome. We create weighted connectomes of 44 patients with 22q11DS and 44 healthy controls using diffusion tensor magnetic resonance imaging, and perform a weighted graph theoretical analysis. After confirming global network integration deficits in 22q11DS (previously identified using binary connectomes), we identify the spatial distribution of regions responsible for global deficits. Next, we further characterize the dysconnectivity of the deficient regions in terms of sub-network properties, and investigate their relevance with respect to clinical profiles. We define the subset of regions with decreased nodal integration (evaluated using the closeness centrality measure) as the affected core (A-core) of the 22q11DS structural connectome. A-core regions are broadly bilaterally symmetric and consist of numerous network hubs - chiefly parietal and frontal cortical, as well as subcortical regions. Using a simulated lesion approach, we demonstrate that these core regions and their connections are particularly important to efficient network communication. Moreover, these regions are generally densely connected, but less so in 22q11DS. These specific disturbances are associated to a rerouting of shortest network paths that circumvent the A-core in 22q11DS, "de-centralizing" the network. Finally, the efficiency and mean connectivity strength of an orbito-frontal/cingulate circuit, included in the affected regions, correlate negatively with the extent of negative symptoms in 22q11DS patients, revealing the clinical relevance of present findings. The identified A-core overlaps numerous regions previously identified as affected in 22q11DS as well as in schizophrenia, which approximately 30-40% of 22q11DS patients develop.

NG2 glia are required for vessel network formation during embryonic development.

The NG2(+) glia, also known as polydendrocytes or oligodendrocyte precursor cells, represent a new entity among glial cell populations in the central nervous system. However, the complete repertoire of their roles is not yet identified. The embryonic NG2(+) glia originate from the Nkx2.1(+) progenitors of the ventral telencephalon. Our analysis unravels that, beginning from E12.5 until E16.5, the NG2(+) glia populate the entire dorsal telencephalon. Interestingly, their appearance temporally coincides with the establishment of blood vessel network in the embryonic brain. NG2(+) glia are closely apposed to developing cerebral vessels by being either positioned at the sprouting tip cells or tethered along the vessel walls. Absence of NG2(+) glia drastically affects the vascular development leading to severe reduction of ramifications and connections by E18.5. By revealing a novel and fundamental role for NG2(+) glia, our study brings new perspectives to mechanisms underlying proper vessels network formation in embryonic brains.

Conflicting claims problem associated with cost sharing of a network

A minimum cost spanning tree (mcst) problem analyzes the way to efficiently connect individuals to a source when they are located at different places. Once the efficient tree is obtained, the question on how allocating the total cost among the involved agents defines, in a natural way, a confliicting claims situation. For instance, we may consider the endowment as the total cost of the network, whereas for each individual her claim is the maximum amount she will be allocated, that is, her connection cost to the source. Obviously, we have a confliicting claims problem, so we can apply claims rules in order to obtain an allocation of the total cost. Nevertheless, the allocation obtained by using claims rules might not satisfy some appealing properties (in particular, it does not belong to the core of the associated cooperative game). We will define other natural claims problems that appear if we analyze the maximum and minimum amount that an individual should pay in order to support the minimum cost tree. Keywords: Minimum cost spanning tree problem, Claims problem, Core JEL classification: C71, D63, D71.

jxSensor: a sensor network integration layer for JXTA

Nowadays, Wireless Sensor Networks (WSN) arealready a very important data source to obtain data about the environment. Thus, they are key to the creation of Cyber-Physical Systems (CPS). Given the popularity of P2P middlewares as ameans to efficiently process information and distribute services, being able to integrate them to WSN¿s is an interesting proposal. JXTA is a widely used P2P middleware that allows peers to easily exchange information, heavily relying on its main architectural highlight, the capability to organize peers with common interests into peer groups. However, right now, approaches to integrate WSNs to a JXTA network seldom take advantage of peer groups. For this reason, in this paper we present jxSensor, an integrationlayer for sensor motes which facilitates the deployment of CPS¿s under this architecture. This integration has been done taking into account JXTA¿s idiosyncrasies and proposing novel ideas,such as the Virtual Peer, a group of sensors that acts as a single entity within the peer group context.

A Social Network Analysis of Twitter: Mapping the Digital Humanities Community

Defining digital humanities might be an endless debate if we stick to the discussion about the boundaries of this concept as an academic "discipline". In an attempt to concretely identify this field and its actors, this paper shows that it is possible to analyse them through Twitter, a social media widely used by this "community of practice". Based on a network analysis of 2,500 users identified as members of this movement, the visualisation of the "who's following who?" graph allows us to highlight the structure of the network's relationships, and identify users whose position is particular. Specifically, we show that linguistic groups are key factors to explain clustering within a network whose characteristics look similar to a small world.

Towards a Network Government? A critical analysis of current assessment methods for e-Government

Contemporary public administrations have become increasingly more complex, having to cordinate actions with emerging actors in the public and the private spheres. In this scenario the modern ICTs have begun to be seen as an ideal vehicle to resolve some of the problems of public administration. We argue that there is a clear need to explore the extent to which public administrations are undergoing a process of transformation towards a netowork government linked to the systematic incorporation of ICTs in their basic activities. Through critically analysing a selection of e-government evaluation reports, we conclude that research should be carried out if we are to build a solid government assessment framework based on network-like organisation characteristics.

Creating a research network for a successful e-portfolio design and implementation

The presence of e-portfolios in educational centres, companies and administrations has emergedstrongly during the last years by creating very different practices coming from different objectives and purposes. This situation has led researchers and practitioners to design and implement e-portfolios with little reference to previous knowledge of them; consequently, developments are disparate with many of the processes and dimensions used both in development and use being unnecessary complex. In order to minimize the inconveniences, unify these developmental processes and improve the resultsof implementation and use of e-portfolios, it seemed necessary to create a network of researchers, teachers and trainers coming from different universities and institutions of different kinds who are interested in the investigation and the practice of e-portfolios in Spain. Therefore, The Network on e-portfoliowas created in 2006, funded by the Spanish Ministry of Education and led by the UniversitatOberta de Catalunya. Besides the goals associatedwith the creation of this network and which wewanted to share with other European researchers and experts of other continents, we will also present in this paper some data concerned with the first study carried out on the use of e-portfolios in our country that shows where we are and which trends are the most important for the near future.

A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning

Peer-reviewed

Complete Analysis of Configuration Rules to Guarantee Reliable Network Security Policies

Peer-reviewed

Aggregating and Deploying Network Access Control Policies

Peer-reviewed

An Experimental Study on Peer Selection in a P2P Network over PlanetLab

Peer-reviewed

Population connectivity buffers genetic diversity loss in a seabird

Background Ancient DNA has revolutionized conservation genetic studies as it allows monitoring of the genetic variability of species through time and predicting the impact of ecosystems" threats on future population dynamics and viability. Meanwhile, the consequences of anthropogenic activities and climate change to island faunas, particularly seabirds, remain largely unknown. In this study, we examined temporal changes in the genetic diversity of a threatened seabird, the Cory"s shearwater (Calonectris borealis). Findings We analysed the mitochondrial DNA control region of ancient bone samples from the late-Holocene retrieved from the Canary archipelago (NE Atlantic) together with modern DNA sequences representative of the entire breeding range of the species. Our results show high levels of ancient genetic diversity in the Canaries comparable to that of the extant population. The temporal haplotype network further revealed rare but recurrent long-distance dispersal between ocean basins. The Bayesian demographic analyses reveal both regional and local population size expansion events, and this is in spite of the demographic decline experienced by the species over the last millennia. Conclusions Our findings suggest that population connectivity of the species has acted as a buffer of genetic losses and illustrate the use of ancient DNA to uncover such cryptic genetic events.

Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities [correcció]

After publication of this work in 'International Journal of Health Geographics' on 13 january 2011 was wrong. The map of Barcelona in Figure two (figure 1 here) was reversed. The final correct Figure is presented here

Authentication and authorization service for a community network

Wireless community networks became popular in uniting people with common interests. This thesis presents authentication and authorization service for a wireless community network using captive portal approach including ability to authenticate clients from associated networks thereby combining multiple communities in a syndicate. The system is designed and implemented to be reliable, scalable and flexible. Moreover, the result includes software management system, which automatically performs software updates at network’s access points. Future development of the system can be concentrated on an improvement of the software management system.

Bayesian Estimation of Noise

In mathematical modeling the estimation of the model parameters is one of the most common problems. The goal is to seek parameters that fit to the measurements as well as possible. There is always error in the measurements which implies uncertainty to the model estimates. In Bayesian statistics all the unknown quantities are presented as probability distributions. If there is knowledge about parameters beforehand, it can be formulated as a prior distribution. The Bays’ rule combines the prior and the measurements to posterior distribution. Mathematical models are typically nonlinear, to produce statistics for them requires efficient sampling algorithms. In this thesis both Metropolis-Hastings (MH), Adaptive Metropolis (AM) algorithms and Gibbs sampling are introduced. In the thesis different ways to present prior distributions are introduced. The main issue is in the measurement error estimation and how to obtain prior knowledge for variance or covariance. Variance and covariance sampling is combined with the algorithms above. The examples of the hyperprior models are applied to estimation of model parameters and error in an outlier case.