From gridmap-file to VOMS: managing authorization in a Grid environment

Grids are potentially composed of several thousands of users from different institutions sharing their computing resources (or using resources provided by third parties). Controlling access to these resources is a difficult problem, as it depends on the policies of the organizations the users belong to and of the resource owners. Moreover, a simple authorization implementation, based on a direct user registration on the resources, is not applicable to a large scale environment. In this paper, we describe the solution to this problem developed in the framework of the European DataGrid [M. Draoli, G. Mascari, R. Piccinelli, Project Presentation, DataGrid-11-NOT-0103-_1] and DataTAG [http://www.datatag.org/] projects: the Virtual Organization Membership Service (VOMS) [R. Alfieri, et al., Managing Dynamic User Communities in a Grid of Autonomous Resources, TUBT005, in: Proceedings of the CHEP 2003, 2003]. VOMS allows a fine grained control of the use of the resources both to the users' organizations and to the resource owners

Angiopoietin-1 variant reduces LPS-induced microvascular dysfunction in a murine model of sepsis

Introduction: Severe sepsis is characterised by intravascular or extravascular infection with microbial agents, systemic inflammation and microcirculatory dysfunction, leading to tissue damage, organ failure and death. The growth factor angiopoietin (Ang-1) has therapeutic potential but recombinant Ang-1 tends to aggregate and has a short half-life in vivo. This study aimed to investigate the acute effects of the more stable Ang-1 variant matrilin-1-angiopoietin-1 (MAT.Ang-1) on the function of the microcirculation in an experimental model of sepsis, and whether any protection by MAT-Ang-1 was associated with modulation of inflammatory cytokines, angiogenic factors or the endothelial nitric oxide synthase (eNOS)-Akt and vascular endothelial (VE)-cadherin pathways. Methods: Aluminium window chambers were implanted into the dorsal skinfold of male C3H/HeN mice (7 to 10 weeks old) to expose the striated muscle microcirculation. Endotoxemia was induced by intraperitoneal injection of lipopolysaccharide (LPS, 1 mg/kg at 0 and 19 hours). MAT.Ang-1 was administered intravenously 20 hours after the onset of sepsis. Microcirculatory function was evaluated by intravital microscopy and Doppler fluximetry. Results: Endotoxemia resulted in macromolecular leak, which was ameliorated by MAT.Ang-1 post-treatment. LPS induced a dramatic reduction in tissue perfusion, which was improved by MAT.Ang-1. Proteome profiler array analysis of skeletal muscle also demonstrated increased inflammatory and reduced angiogenic factors during endotoxemia. MAT.Ang-1 post-treatment reduced the level of IL-1β but did not significantly induce the expression of angiogenic factors. MAT.Ang-1 alone did not induce leak or increase angiogenic factors but did reduce vascular endothelial growth factor expression in controls. Conclusion: Administration of MAT.Ang-1 after the onset of sepsis protects the microcirculation from endotoxemia-induced vascular dysfunction through reducing inflammation but without pro-angiogenic actions, thus representing a novel, potential pharmacotherapeutic agent for the treatment of sepsis

A comparison of node vaccination strategies to halt SIR epidemic spreading in real-world complex networks

: We compared seven node vaccination strategies in twelve real-world complex networks. The node vaccination strategies are modeled as node removal on networks. We performed node vaccination strategies both removing nodes according to the initial network structure, i.e., non-adaptive approach, and performing partial node rank recalculation after node removal, i.e., semi-adaptive approach. To quantify the efficacy of each vaccination strategy, we used three epidemic spread indicators: the size of the largest connected component, the total number of infected at the end of the epidemic, and the maximum number of simultaneously infected individuals. We show that the best vaccination strategies in the non-adaptive and semi-adaptive approaches are different and that the best strategy also depends on the number of available vaccines. Furthermore, a partial recalculation of the node centrality increases the efficacy of the vaccination strategies by up to 80%

Network structure indexes to forecast epidemic spreading in real-world complex networks

Complex networks are the preferential framework to model spreading dynamics in several real-world complex systems. Complex networks can describe the contacts between infectious individuals, responsible for disease spreading in real-world systems. Understanding how the network structure affects an epidemic outbreak is therefore of great importance to evaluate the vulnerability of a network and optimize disease control. Here we argue that the best network structure indexes (NSIs) to predict the disease spreading extent in real-world networks are based on the notion of network node distance rather than on network connectivity as commonly believed. We numerically simulated, via a type-SIR model, epidemic outbreaks spreading on 50 real-world networks. We then tested which NSIs, among 40, could a priori better predict the disease fate. We found that the “average normalized node closeness” and the “average node distance” are the best predictors of the initial spreading pace, whereas indexes of “topological complexity” of the network, are the best predictors of both the value of the epidemic peak and the final extent of the spreading. Furthermore, most of the commonly used NSIs are not reliable predictors of the disease spreading extent in real-world networks

Serological survey for mycoplasma hyopneumoniae in free-living wild boars from Campos Gerais region, Paraná, Brasil.

The south region of Brazil was responsible for 80.3% of total pork meat export in the country in 2015 (2), with the state of Paraná accountable for 21% of the total pork meat production in that year. Pig farming represented 5.7% of the agricultural gross income of the state in 2016, and the Campos Gerais region accounted for 13.2% of that amount (2). Wild boars are the result of crossbreeding between boars (Sus scrofa scrofa) and domestic pigs (Sus scrofa domesticus). The total population of free-living wild boars in Brazil is unknown (11), but sightings are common in the crop fields and near livestock farms of different regions of Paraná state, including in Campos Gerais (9). The health status of pig herds is important in terms of maintenance and growth of pork production and exports and there are evidences that domestic pigs and wild boars share vulnerabilities in certain viral and bacterial pathogen infections (12). Mycoplasma hyopneumoniae (Mhyo) is a bacterial pathogen that causes porcine enzootic pneumonia, an economically important disease that affects both domestic pigs and wild boars. Mhyo was first isolated in 1965, simultaneously in the United Kingdom (UK) and in the United States of America (USA) (3; 7). Economic losses related to this pathogen and mycoplasmal pneumonia in pig herds are associated with decreased feed efficiency, reduced average of the daily weight gain, and increased medication costs. Thus, knowing the health status of free-living wild boars in the regards of this pathogen is important for the biosecurity of the pork production. The aim of this study was to investigate antibodies against Mhyo in serum samples of free-living wild boars in Campos Gerais region

Considering weights in real social networks: A review

Network science offers powerful tools to model complex social systems. Most social network science research focuses on topological networks by simply considering the binary state of the links, i.e., their presence or absence. Nonetheless, complex social systems present heterogeneity in link interactions (link weight), and accounting for this heterogeneity, it is mandatory to design reliable social network models. Here, we revisit the topic of weighted social networks (WSNs). By summarizing the main notions, findings, and applications in the field of WSNs, we outline how WSN methodology may improve the modeling of several real problems in social sciences. We are convinced that WSNs may furnish ideas and insights to open interesting lines of new research in the social sciences

Managing Dynamic User Communities in a Grid of Autonomous Resources

One of the fundamental concepts in Grid computing is the creation of Virtual Organizations (VO's): a set of resource consumers and providers that join forces to solve a common problem. Typical examples of Virtual Organizations include collaborations formed around the Large Hadron Collider (LHC) experiments. To date, Grid computing has been applied on a relatively small scale, linking dozens of users to a dozen resources, and management of these VO's was a largely manual operation. With the advance of large collaboration, linking more than 10000 users with a 1000 sites in 150 counties, a comprehensive, automated management system is required. It should be simple enough not to deter users, while at the same time ensuring local site autonomy. The VO Management Service (VOMS), developed by the EU DataGrid and DataTAG projects[1, 2], is a secured system for managing authorization for users and resources in virtual organizations. It extends the existing Grid Security Infrastructure[3] architecture with embedded VO affiliation assertions that can be independently verified by all VO members and resource providers. Within the EU DataGrid project, Grid services for job submission, file- and database access are being equipped with fine- grained authorization systems that take VO membership into account. These also give resource owners the ability to ensure site security and enforce local access policies. This paper will describe the EU DataGrid security architecture, the VO membership service and the local site enforcement mechanisms Local Centre Authorization Service (LCAS), Local Credential Mapping Service(LCMAPS) and the Java Trust and Authorization Manager.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 7 pages, LaTeX, 5 eps figures. PSN TUBT00

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

This is the final version. Available on open access from the Royal Society via the DOI in this recordData accessibility: This article has no additional data.We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity. This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.European Union FP7Joint UK BEIS/Defra Met Office Hadley Centre Climate Programm