Extreme Energy Cosmic Rays (EECR) Observation Capabilities of an "Airwatch from Space'' Mission

The longitudinal development and other characteristics of the EECR induced atmospheric showers can be studied from space by detecting the fluorescence light induced in the atmospheric nitrogen. According to the Airwatch concept a single fast detector can be used for measuring both intensity and time development of the streak of fluorescence light produced by the atmospheric shower induced by an EECR. In the present communication the detection capabilities for the EECR observation from space are discussed.Comment: 3 pages (LaTeX). To appear in the Proceedings of TAUP'9

The neutral endopeptidase-24.11 inhibitor SCH 34286 does not change opioid binding but reduce D1 dopamine receptors in rat brain

The effect of repeated administration of the neutral endopeptidase-24.11 (NEP) inhibitor SCH 34826 on the kinetic properties of opioid and dopamine binding in the rat cerebral cortex and striatum was investigated. SCH 34826, given at 100 and 300 mg/kg orally twice a day for 14 days, did not alter either Bmax or Kd for the mu, delta, or kappa opioid receptor type in the cortex, as measured by studying binding parameters for the mu-selective ligand [3H][D-Ala2, Me-Phe4,Gly(ol)5]enkephalin (DAGO), the delta-selective ligand [3H][D-Pen2,D-Pen5]enkephalin (DPDPE) and the kappa ligand [3H]ethylketazocine (EKC). SCH 34826 reduced significantly the number of D1 dopamine receptors labeled with [3H]SCH 23390 in the striatum (Bmax was 90 and 84% of controls at 100 and 300 mg/kg, respectively). The number of D2 receptors, measured by [3H]spiperone binding was unaltered. The Kd values for both receptor types were not affected. The data demonstrate that chronic inhibition of enkephalin degradation by SCH 34826 does not alter opioid receptors, whereas it reduces the number of D1 receptors. These findings provide further support for the role of opioids in modulating central dopaminergic systems. As a reduction in the number of D1 receptors is an effect common to antidepressant treatments, the antidepressant potential of NEP inhibitors should be investigated

Development of Best Practices for Large-scale Data Management Infrastructure

The amount of available data for processing is constantly increasing and becomes more diverse. We collect our experiences on deploying large-scale data management tools on local-area clusters or cloud infrastructures and provide guidance to use these computing and storage infrastructures. In particular we describe Apache Hadoop, one of the most widely used software libraries to perform large- scale data analysis tasks on clusters of computers in parallel and provide guidance on how to achieve optimal execution time when performing analysis over large-scale data. Furthermore we report on our experiences with projects, that provide valuable insights in the deployment and use of large- scale data management tools: The Web Data Commons project for which we extracted all Microformat, Microdata and RDFa data from the Common Crawl web corpus, the largest and most up-to-date web corpus that is currently available to the public. SciLens, a local-area cluster machine that has been built to facilitate research on data management issues for data-intensive scientific applications. CumulusRDF, an RDF store on cloud-based architectures. We investigate the feasibility of using a distributed nested key/value store as an underlying storage component for a Linked Data server, which provides functionality for serving large quantities of Linked Data. Finally we describe the News Aggregator Pipeline, which is a piece of software to perform the acquisition of high volume textual streams, it’s processing into a suitable form for further analysis and the distribution of the data