Basket of Growth: New Export Industries in Sverdlovsk Region

The authors examine an export basket and reveal the new export goods for Sverdlovsk region, which might be used to transform the productive structure and upgrade export of the region. For each product, in which the region might develop its comparative advantage, the authors develop a measure of efforts, which are supposed to be made to include this good into the export basket, and a measure of the income level for the product. As a result the authors get a cluster of new and the most attractive export goods. Special methodology is used to choose the best cities to allocate the production of the new export goods.Export goods, comparative advantages, industrial cluster, production allocation

QDB: A new database of plasma chemistries and reactions

One of the most challenging and recurring problems when modeling plasmas is the lack of data on the key atomic and molecular reactions that drive plasma processes. Even when there are data for some reactions, complete and validated datasets of chemistries are rarely available. This hinders research on plasma processes and curbs development of industrial applications. The QDB project aims to address this problem by providing a platform for provision, exchange, and validation of chemistry datasets. A new data model developed for QDB is presented. QDB collates published data on both electron scattering and heavy-particle reactions. These data are formed into reaction sets, which are then validated against experimental data where possible. This process produces both complete chemistry sets and identifies key reactions that are currently unreported in the literature. Gaps in the datasets can be filled using established theoretical methods. Initial validated chemistry sets for SF 6 /CF 4 /O 2 and SF 6 /CF 4 /N 2 /H 2 are presented as examples

External Determinants of the Russian Federation's Monetary Policy

This study analyzes potential options for intervention policy, checks certain hypotheses about foreign-trade trends and parameters of exchange-rate and monetary policy, and assesses possibilities for sterilizing money supply growth. It surveys the literature devoted to central bank intervention on foreign exchange markets and related transmission mechanisms in the economy.

WLCG Transfers Dashboard: a Unified Monitoring Tool for Heterogeneous Data Transfers

The Worldwide LHC Computing Grid provides resources for the four main virtual organizations. Along with data processing, data distribution is the key computing activity on the WLCG infrastructure. The scale of this activity is very large, the ATLAS virtual organization (VO) alone generates and distributes more than 40 PB of data in 100 million files per year. Another challenge is the heterogeneity of data transfer technologies. Currently there are two main alternatives for data transfers on the WLCG: File Transfer Service and XRootD protocol. Each LHC VO has its own monitoring system which is limited to the scope of that particular VO. There is a need for a global system which would provide a complete cross-VO and cross-technology picture of all WLCG data transfers. We present a unified monitoring tool – WLCG Transfers Dashboard – where all the VOs and technologies coexist and are monitored together. The scale of the activity and the heterogeneity of the system raise a number of technical challenges. Each technology comes with its own monitoring specificities and some of the VOs use several of these technologies. This paper describes the implementation of the system with particular focus on the design principles applied to ensure the necessary scalability and performance, and to easily integrate any new technology providing additional functionality which might be specific to that technology

Processing of the WLCG monitoring data using NoSQL

The Worldwide LHC Computing Grid (WLCG) today includes more than 150 computing centres where more than 2 million jobs are being executed daily and petabytes of data are transferred between sites. Monitoring the computing activities of the LHC experiments, over such a huge heterogeneous infrastructure, is extremely demanding in terms of computation, performance and reliability. Furthermore, the generated monitoring flow is constantly increasing, which represents another challenge for the monitoring systems. While existing solutions are traditionally based on Oracle for data storage and processing, recent developments evaluate NoSQL for processing large-scale monitoring datasets. NoSQL databases are getting increasingly popular for processing datasets at the terabyte and petabyte scale using commodity hardware. In this contribution, the integration of NoSQL data processing in the Experiment Dashboard framework is described along with first experiences of using this technology for monitoring the LHC computing activities