28 resultados para Tor, Network Forensics, Traffic Analysis, Hidden Service, Deanonymization, Traffic Correlation
em Universit
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Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.
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Networks are considered increasingly important for policy-making. The literature on new modes of governance in Europe suggests that their horizontal coordination capacity and flexible and informal structures are particularly suitable for governing the multilevel architecture of the European polity. However, empirical evidence about the effects of networks on policy-making and public policies is still quite limited. This article uses the case of the European network of energy regulators to explore the determinants of the position of network members and, in turn, the domestic adoption of soft rules developed within this network. The empirical analysis, based on multivariate statistics and semi-directive interviews, supports the expectation that institutional complementarities increase actors' centrality in networks, while arguments based on organisational resources and age are disproved. Furthermore, results show that the overall level of adoption is considerable and that centrality might have a small positive effect on domestic adoption.
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This paper investigates the impacts of globalization processes on the Swiss business elite community during the 1980-2010 period. Switzerland has been characterized in the 20th century by its extraordinary stability and by the strong cohesion of its elite community. To study recent changes, we focus on Switzerland's 110 largest firms' by adopting a diachronic perspective based on three elite cohorts (1980, 2000, and 2010). An analysis of interlocking directorates allows us to describe the decline of the Swiss corporate network. The second analysis focuses on top managers' profiles in terms of education, nationality as well as participation in national community networks that used to reinforce the cultural cohesion of the Swiss elite community, especially the militia army. Our results highlight a slow but profound transformation of top management profiles, characterized by a decline of traditional national elements of legitimacy and the emergence of new "global" elements. The diachronic and combined analysis brings into light the strong cultural changes experienced by the national business elite community.
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Ski resorts are deploying more and more systems of artificial snow. These tools are necessary to ensure an important economic activity for the high alpine valleys. However, artificial snow raises important environmental issues that can be reduced by an optimization of its production. This paper presents a software prototype based on artificial intelligence to help ski resorts better manage their snowpack. It combines on one hand a General Neural Network for the analysis of the snow cover and the spatial prediction, with on the other hand a multiagent simulation of skiers for the analysis of the spatial impact of ski practice. The prototype has been tested on the ski resort of Verbier (Switzerland).
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RESUME Introduction : La prophylaxie du système nerveux central lors d'un diagnostic de leucémie lymphoblastique aiguë de l'enfant a permis de réduire le risque de rechute mais a été associée dans certains cas à des neurotoxicités cliniques ou des anomalies radiologiques. Des moyens de prédire ces neurotoxicités font défaut, en particulier en raison de l'absence de corrélation claire entre les signes cliniques et les images radiologiques. Quelques auteurs ont suggéré que les taux de protéine basique de la myéline (MBP) mesurés dans le liquide céphalo-rachidien pouvaient avoir un intérêt dans ce contexte. Uné étude rétrospective de ces taux en relation avec des données cliniques et radiologiques est présentée dans ce travail. Matériel et Méthodes : Les taux de MBP mesurés dans le liquide céphalo-rachidien lors d'administration de chimiothérapie intrathécale, les examens cliniques neurologiques et les rapports radiologiques ont été rétrospectivement étudiés chez nos patients. Les données concernant des difficultés académiques éventuelles, ainsi que le niveau académique atteint ont été récoltées par l'intermédiaire de contacts téléphoniques réguliers organisés dans le cadre du suivi à long terme de nos patients. Résultats : Un total de 1248 dosages de MBP chez 83 patients, 381 examens neurologiques chez 34 patients et 69 rapports d'investigations neuroradiologiques chez 27 patients ont été analysés. Cinquante-deux patients ont eut au moins un taux anormal de MBP. Des anomalies radiologiques ont été décrites chez 47% de ces patients, parmi lesquels 14% ont présenté des difficultés scolaires sous une forme ou sous une autre. La proportion de patients ayant présenté des difficultés scolaires dans les groupes avec taux de MBP normal mais sans anomalies radiologiques décrites ou sans investigations radiologiques étaient respectivement de 0% et 3%, inférieurs dans tous les cas au groupe avec des taux normaux de MBP (100%, 22% and 5% respectivement). Discussion : Tout en prenant en compte les limitations dues à l'aspect rétrospectif de cette étude, nous avons conclu à une utilité limitée de ces dosages systématiques comme indicateur d'une neurotoxicité induite parle traitement dans le contexte de nos patients oncologiques. ABSTRACT Introduction : Central nervous system (CSF) prophylaxis of childhood acute lymphoblastic leukemia has dropped rates of relapses but has been associated wíth neurotoxicity and imaging abnormalities. Predictors of neurotoxícity are lacking, because of inconsistency between clinical symptoms and imaging. Some have suggested CSF Myelin Basic Protein (MBP) levels to be of potential interest. A retrospective analysis of MBP levels in correlation with clinical and radiological data is presented. Materials and Methods : MBP levels obtained at the time of intrathecals, charts, and neuroradiology reports were retrospectively analyzed. Academic achievement data were obtained from phone contacts with patients and families. Results : We retrieved 1248 dosages of MBP in 83 patients, 381 neurological exams in 34 patients and 69 neuroradiological investigations in 27 patients. Fifty-two patients had abnormal MBP levels. Radiological anomalies were present in 47% of those investigated, 14% of them having school difficulties. Proportions of patients with school difficulties in the groups with abnormal MBP levels but no radiological anomalies or with no radiological investigations were 0% and 3% respectively, which was lower than in the group of patients with normal MBP levels (100%, 22% and 5% respectively). Discussion : Notwithstanding the retrospective character of our study, we conclude that there is limited usefulness of systematic dosage of MBP as indicator of treatment-induced neurotoxicity in ALL patients.
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INTRODUCTION: Central nervous system prophylaxis of childhood acute lymphoblastic leukemia has dropped rates of relapses but has been associated with neurotoxicity and imaging abnormalities. Predictors of neurotoxicity are lacking, because of inconsistency between clinical symptoms and imaging. Some have suggested that cerebrospinal fluid myelin basic protein (MBP) levels to be of potential interest. A retrospective analysis of MBP levels in correlation with clinical and radiologic data is presented. MATERIALS AND METHODS: MBP levels obtained at the time of intrathecals, charts, and neuroradiology reports were retrospectively analyzed. Academic achievement data were obtained from phone contacts with patients and families. RESULTS: We retrieved 1248 dosages of MBP in 83 patients, 381 neurologic examinations in 34 patients and 69 neuroradiologic investigations in 27 patients. Fifty-two patients had abnormal MBP levels. Radiologic anomalies were present in 47% of those investigated, 14% of them having school difficulties. Proportions of patients with school difficulties in the groups with abnormal MBP levels but no radiologic anomalies or with no radiologic investigations were 0% and 3%, respectively, which was lower than in the group of patients with normal MBP levels (100%, 22%, and 5%, respectively). DISCUSSION: Notwithstanding the retrospective character of our study, we conclude that there is limited usefulness of systematic dosage of MBP as indicator of treatment-induced neurotoxicity in acute lymphoblastic leukemia patients.
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Purpose: Recent studies showed that pericardial fat was independently correlated with the development of coronary artery disease (CAD). The mechanism remains unclear. We aimed at assessing a possible relationship between pericardial fat volume and endothelium-dependent coronary vasomotion, a surrogate of future cardiovascular events.Methods: Fifty healthy volunteers without known CAD or cardiovascular risk factors (CRF) were enrolled. They all underwent a dynamic Rb- 82 cardiac PET/CT to quantify myocardial blood flow (MBF) at rest, during MBF response to cold pressure test (CPT-MBF) and adenosine stress. Pericardial fat volume (PFV) was measured using a 3D volumetric CT method and common biological CRF (glucose and insulin levels, HOMA-IR, cholesterol, triglyceride, hs-CRP). Relationships between MBF response to CPT, PFV and other CRF were assessed using non-parametric Spearman correlation and multivariate regression analysis of variables with significant correlation on univariate analysis (Stata 11.0).Results: All of the 50 participants had normal MBF response to adenosine (2.7±0.6 mL/min/g; 95%CI: 2.6−2.9) and myocardial flow reserve (2.8±0.8; 95%CI: 2.6−3.0) excluding underlying CAD. Simple regression analysis revealed a significant correlation between absolute CPTMBF and triglyceride level (rho = −0.32, p = 0.024) fasting blood insulin (rho = −0.43, p = 0.0024), HOMA-IR (rho = −0.39, p = 0.007) and PFV (rho = −0.52, p = 0.0001). MBF response to adenosine was only correlated with PFV (rho = −0.32, p = 0.026). On multivariate regression analysis PFV emerged as the only significant predictor of MBF response to CPT (p = 0.002).Conclusion: PFV is significantly correlated with endothelium-dependent coronary vasomotion. High PF burden might negatively influence MBF response to CPT, as well as to adenosine stress, even in persons with normal hyperemic myocardial perfusion imaging, suggesting a link between PF and future cardiovascular events. While outside-to-inside adipokines secretion through the arterial wall has been described, our results might suggest an effect upon NO-dependent and -independent vasodilatation. Further studies are needed to elucidate this mechanism.
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Water transport in wood is vital for the survival of trees. With synchrotron radiation X-ray tomographic microscopy (SRXTM), it has become possible to characterize and quantify the three-dimensional (3D) network formed by vessels that are responsible for longitudinal transport. In the present study, the spatial size dependence of vessels and the organization inside single growth rings in terms of vessel-induced porosity was studied by SRXTM. Network characteristics, such as connectivity, were deduced by digital image analysis from the processed tomographic data and related to known complex network topologies.
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Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).
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Patients with Temporal Lobe Epilepsy (TLE) suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor MR Imaging, volumetric and functional MRI studies. Diffusion Spectrum Imaging (DSI) is a diffusion imaging technique with high angular resolution for improving the mapping of white matter pathways. In this study, we used DSI, connectivity matrices and topological measures to investigate how the alteration in structural connectivity influences whole brain structural networks. Eleven patients with right-sided TLE and hippocampal sclerosis and 18 controls underwent our DSI protocol at 3T. The cortical and subcortical grey matters were parcellated into 86 regions of interest and the connectivity between every region pair was estimated using global tractography and a connectivity matrix (the adjacency matrix of the structural network). We then compared the networks of patients and controls using topological measures. In patients, we found a higher characteristic path length and a lower clustering coefficient compared to controls. Local measures at node level of the clustering and efficiency showed a significant difference after a multiple comparison correction (Bonferroni). These significant nodes were located within as well outside the temporal lobe, and the localisation of most of them was consistent with regions known to be part of epileptic networks in TLE. Our results show altered connectivity patterns that are concordant with the mapping of functional epileptic networks in patients with TLE. Further studies are needed to establish the relevance of these findings for the propagation of epileptic activity, cognitive deficits in medial TLE and outcome of epilepsy surgery in individual patients.
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BACKGROUND: Membrane-bound organelles are a defining feature of eukaryotic cells, and play a central role in most of their fundamental processes. The Rab G proteins are the single largest family of proteins that participate in the traffic between organelles, with 66 Rabs encoded in the human genome. Rabs direct the organelle-specific recruitment of vesicle tethering factors, motor proteins, and regulators of membrane traffic. Each organelle or vesicle class is typically associated with one or more Rab, with the Rabs present in a particular cell reflecting that cell's complement of organelles and trafficking routes. RESULTS: Through iterative use of hidden Markov models and tree building, we classified Rabs across the eukaryotic kingdom to provide the most comprehensive view of Rab evolution obtained to date. A strikingly large repertoire of at least 20 Rabs appears to have been present in the last eukaryotic common ancestor (LECA), consistent with the 'complexity early' view of eukaryotic evolution. We were able to place these Rabs into six supergroups, giving a deep view into eukaryotic prehistory. CONCLUSIONS: Tracing the fate of the LECA Rabs revealed extensive losses with many extant eukaryotes having fewer Rabs, and none having the full complement. We found that other Rabs have expanded and diversified, including a large expansion at the dawn of metazoans, which could be followed to provide an account of the evolutionary history of all human Rabs. Some Rab changes could be correlated with differences in cellular organization, and the relative lack of variation in other families of membrane-traffic proteins suggests that it is the changes in Rabs that primarily underlies the variation in organelles between species and cell types.
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Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression ('SCNA-genes') in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer.
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This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.
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Evidence of a sport-specific hierarchy of protective factors against doping would thus be a powerful aid in adapting information and prevention campaigns to target the characteristics of specific athlete groups, and especially those athletes most vulnerable for doping control. The contents of phone calls to a free and anonymous national anti-doping service called 'ecoute dopage' were analysed (192 bodybuilders, 124 cyclists and 44 footballers). The results showed that the protective factors that emerged from analysis could be categorised into two groups. The first comprised 'Health concerns', 'Respect for the law' and 'Doping controls from the environment' and the second comprised 'Doubts about the effectiveness of illicit products, 'Thinking skills' and 'Doubts about doctors'. The ranking of the factors for the cyclists differed from that of the other athletes. The ordering of factors was 1) respect for the law, 2) doping controls from the environment, 3) health concerns 4) doubts about doctors, and 5) doubts about the effectiveness illicit products. The results are analysed in terms of the ranking in each athlete group and the consequences on the athletes' experience and relationship to doping. Specific prevention campaigns are proposed to limit doping behaviour in general and for each sport.