Differences of Functional Connectivity Brain Network in Emotional Judgment

Using combined emotional stimuli, combining photos of faces and recording of voices, we investigated the neural dynamics of emotional judgment using scalp EEG recordings. Stimuli could be either combioned in a congruent, or a non-congruent way.. As many evidences show the major role of alpha in emotional processing, the alpha band was subjected to be analyzed. Analysis was performed by computing the synchronization of the EEGs and the conditions congruent vs. non-congruent were compared using statistical tools. The obtained results demonstrate that scalp EEG ccould be used as a tool to investigate the neural dynamics of emotional valence and discriminate various emotions (angry, happy and neutral stimuli).

Network characteristics of film tourism websites in Catalonia: an application of network analysis in tourism

This master thesis presents a research on the analysis of film tourism stakeholders in Catalonia applying the network analysis approach. The research aims to provide an analysis of the relations between local tourism stakeholders with local film offices through their websites. Therefore, the development of the present work involved the review of literature on the themes of film tourism and network analysis. Then the main stakeholders of film and tourism of Catalonia were identified and their websites analyzed. The measures indicators for network analysis such as centrality, closeness and betweenness degree have been applied on the analysis of the websites to determine the extent of the relations of film and tourism stakeholders in Catalonia. Results and conclusions are presented on the referred sections

Study of the robustness of the European air routes network

working paper

The Network Company in Catalonia : ICT, Productivity, Competitiveness, Salaries and Performance in Catalonia's Companies. Research report (synthesis document)

Resum en anglès del projecte de recerca L'empresa xarxa a Catalunya. TIC, productivitat, competitivitat, salaris i beneficis a l'empresa catalana té com a objectiu principal constatar que la consolidació d'un nou model estratègic, organitzatiu i d'activitat empresarial, vinculat amb la inversió i l'ús de les TIC (o empresa xarxa), modifica substancialment els patrons de comportament dels resultats empresarials, en especial la productivitat, la competitivitat, les retribucions dels treballadors i el benefici. La contrastació empírica de les hipòtesis de treball l'hem feta per mitjà de les dades d'una enquesta a una mostra representativa de 2.038 empreses catalanes. Amb la perspectiva de l'impacte de la inversió i l'ús de les TIC no s'aprecia una relació directa entre els processos d'innovació digital i els resultats de l'activitat de l'empresa catalana. En aquest sentit, hem hagut de segmentar el teixit productiu català per a buscar les organitzacions en què el procés de coinnovació tecnològica digital i organitzativa és més present i en què la intensitat de l'ús del coneixement és un recurs molt freqüent per a poder copsar impactes rellevants en els principals resultats empresarials. Això és així perquè l'economia catalana, avui, presenta una estructura productiva dual.

Superstars need social benefits: an experiment on network formation

We investigate contributions to the provision of public goods on a network when efficient provision requires the formation of a star network. We provide a theoretical analysis and study behavior is a controlled laboratory experiment. In a 2x2 design, we examine the effects of group size and the presence of (social) benefits for incoming links. We find that social benefits are highly important. They facilitate convergence to equilibrium networks and enhance the stability and efficiency of the outcome. Moreover, in large groups social benefits encourage the formation of superstars: star networks in which the core contributes more than expected in the stage-game equilibrium. We show that this result is predicted by a repeated game equilibrium.

On an asymptotic formula for the maximum voltage drop in a on-chip power distribution network

We present a new asymptotic formula for the maximum static voltage in a simplified model for on-chip power distribution networks of array bonded integrated circuits. In this model the voltage is the solution of a Poisson equation in an infinite planar domain whose boundary is an array of circular pads of radius ", and we deal with the singular limit Ɛ → 0 case. In comparison with approximations that appear in the electronic engineering literature, our formula is more complete since we have obtained terms up to order Ɛ15. A procedure will be presented to compute all the successive terms, which can be interpreted as using multipole solutions of equations involving spatial derivatives of functions. To deduce the formula we use the method of matched asymptotic expansions. Our results are completely analytical and we make an extensive use of special functions and of the Gauss constant G

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Cab45 is required for Ca(2+)-dependent secretory cargo sorting at the trans-Golgi network

Ca(2+) import into the lumen of the trans-Golgi network (TGN) by the secretory pathway calcium ATPase1 (SPCA1) is required for the sorting of secretory cargo. How is Ca(2+) retained in the lumen of the Golgi, and what is its role in cargo sorting? We show here that a soluble, lumenal Golgi resident protein, Cab45, is required for SPCA1-dependent Ca(2+) import into the TGN; it binds secretory cargo in a Ca(2+)-dependent reaction and is required for its sorting at the TGN.

Kinesin-5/Eg5 is important for transport of CARTS from the trans-Golgi network to the cell surface

Here we report that the kinesin-5 motor Klp61F, which is known for its role in bipolar spindle formation in mitosis, is required for protein transport from the Golgi complex to the cell surface in Drosophila S2 cells. Disrupting the function of its mammalian orthologue, Eg5, in HeLa cells inhibited secretion of a protein called pancreatic adenocarcinoma up-regulated factor (PAUF) but, surprisingly, not the trafficking of vesicular stomatitis virus G protein (VSV-G) to the cell surface. We have previously reported that PAUF is transported from the trans-Golgi network (TGN) to the cell surface in specific carriers called CARTS that exclude VSV-G. Inhibition of Eg5 function did not affect the biogenesis of CARTS; however, their migration was delayed and they accumulated near the Golgi complex. Altogether, our findings reveal a surprising new role of Eg5 in nonmitotic cells in the facilitation of the transport of specific carriers, CARTS, from the TGN to the cell surface.

APTIC : a social network to improve the quality of life of members of patients' associations

Peer-reviewed

SiMR: A simulator for learning computer architecture

This paper presents SiMR, a simulator of the Rudimentary Machine designed to be used in a first course of computer architecture of Software Engineering and Computer Engineering programmes. The Rudimentary Machine contains all the basic elements in a RISC computer, and SiMR allows editing, assembling and executing programmes for this processor. SiMR is used at the Universitat Oberta de Catalunya as one of the most important resources in the Virtual Computing Architecture and Organisation Laboratory, since students work at home with the simulator and reports containing their work are automatically generated to be evaluated by lecturers. The results obtained from a survey show that most of the students consider SiMR as a highly necessary or even an indispensable resource to learn the basic concepts about computer architecture.