Service Availability Monitoring Framework Based On Commodity Software

The Worldwide LHC Computing Grid (WLCG) infrastructure continuously operates thousands of grid services scattered around hundreds of sites. Participating sites are organized in regions and support several virtual organizations, thus creating a very complex and heterogeneous environment. The Service Availability Monitoring (SAM) framework is responsible for the monitoring of this infrastructure. SAM is a complete monitoring framework for grid services and grid operational tools. Its current implementation tailored for a decentralized operation replaces the old SAM system which is now being decommissioned from production. SAM provides functionality for submission of monitoring probes, gathering of probes results, processing of monitoring data, and retrieval of monitoring data in terms of service status, availability, and reliability. In this paper we present the SAM framework. We motivate the need from moving from the old SAM to a new monitoring infrastructure deployed and managed in a distributed environment and explain how SAM exploits and builds on top of commodity software, such as Nagios and Apache ActiveMQ, to provide a reliable and scalable system. We also present the SAM architecture by highlighting the adopted technologies and how the different SAM components deliver a complete monitoring framework

A Meta-analysis of Immune Parameters, Variability, and Assessment of Modal Distribution in Psychosis and Test of the Immune Subgroup Hypothesis

Immune parameters are elevated in psychosis, but it is unclear whether alterations are homogenous across patients or heterogeneity exists, consistent with the hypothesis that immune alterations are specific to a subgroup of patients. To address this, we examine whether antipsychotic-naïve first-episode psychosis patients exhibit greater variability in blood cytokines, C-reactive protein, and white cell counts compared with controls, and if group mean differences persist after adjusting for skewed data and potential confounds. Databases were searched for studies reporting levels of peripheral immune parameters. Means and variances were extracted and analyzed using multivariate meta-analysis of mean and variability of differences. Outcomes were (1) variability in patients relative to controls, indexed by variability ratio (VR) and coefficient of variation ratio (CVR); (2) mean differences indexed by Hedges g; (3) Modal distribution of raw immune parameter data using Hartigan's unimodality dip test. Thirty-five studies reporting on 1263 patients and 1470 controls were included. Variability of interleukin-6 (IL6) (VR = 0.19), tumor necrosis factor-α (TNFα) (VR = 0.36), interleukin-1β (VR = 0.35), interleukin-4 (VR = 0.55), and interleukin-8 (VR = 0.28) was reduced in patients. Results persisted for IL6 and IL8 after mean-scaling. Ninety-four percent and one hundred percent of raw data were unimodally distributed in psychosis and controls, respectively. Mean levels of IL6 (g = 0.62), TNFα (g = 0.56), interferon-γ (IFNγ) (g = 0.32), transforming growth factor-β (g = 0.53), and interleukin-17 (IL17) (g = 0.48) were elevated in psychosis. Sensitivity analyses indicated this is unlikely explained by confounders for IL6, IFNγ, and IL17. These findings show elevated cytokines in psychosis after accounting for confounds, and that the hypothesis of an immune subgroup is not supported by the variability or modal distribution