Electromagnetic plasma modeling in circuit breaker within the finite volume method

In order to ensure the galvanic isolation of an electrical system following a manual operation or a default strike, current limitation properties of the electric arc are used, forcing a fast decrease to zero current. Modeling this process reveals complex, since it involves a large amount of physical phenomena (radiation, phase transitions, electromagnetism, fluid dynamics, plasma physics). In order to get a robust solving, enhancing strongly coupled resolution and time constants compatibility, the Finite Volume Method has been chosen. This method was first implemented on intrinsic electromagnetism problems (current flow, magnetostatics including non-linear materials, and magnetodynamics). Once validated, the models have been successfully used in the Schneider's current-interruption dedicated software, thus allowing a significantly improved simulation of Schneider Electric circuit breakers

The ESCAPE project : Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure. The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors. This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche a l'Operationnel a Meso-Echelle) and ALADIN (Aire Limitee Adaptation Dynamique Developpement International); and COSMO-EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf. The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU-GPU arrangements

Next Generation European Research Vessels: Current Status and Foreseeable Evolution

The European research vessel fleet plays a vital role in supporting scientific research and development not just in Europe but also across the globe. This document explores how the fleet has developed since the publication of the European Marine Board Position Paper 10 (EMB PP 10) "European Ocean Research Fleets – Towards a Common Strategy and Enhanced Use" (Binot et al., 2007). It looks at the current fleet and its equipment and capabilities (Chapter 2), the deep sea (Chapter 3) and Polar regions (Chapter 4) as study areas of ever- increasing importance for science and for the vessels that explore them, the role that research vessels play in the wider ocean observing landscape (Chapter 5), the importance of training personnel for research vessels (Chapter 6), and considers management of the European research vessel fleet (Chapter 7). This Position Paper considers what has changed since 2007, what the status is in 2019, and future directions for the European fleet, with a 10-year horizon to 2030. This Position Paper finds that the current European research vessel fleet is highly capable, and is able to provide excellent support to European marine science and wider scientific research and can lead on the world stage. However, with a typical life expectancy of a research vessel of 30 years, the fleet is ageing and urgently requires further investment and reinvestment to continue to be as efficient and capable as the scientific community expects and requires. The capabilities of the fleet have increased considerably since 2007, and vessels have kept up with fast-paced technological developments. The demand for complex and highly capable vessels will continue, and research vessel designs and the fleet as a whole will need to keep pace in order to remain fit-for-purpose and continue to be a key player globally. There is huge diversity in vessel types and designs in terms of capabilities and equipment, management structures and processes, and training possibilities. While it would not be possible or appropriate to highlight any one approach as the only one to use, a growing trend in collaboration through community groups, agreements, legal entities and funded projects now enables more strategic thinking in the development of these vital infrastructures. However, some issues remain in enabling equal access to research vessel time for all researchers across Europe regardless of country, and regardless of whether or not that country owns a suitable research vessel for their scientific needs

Ancient horizontal gene transfer and the last common ancestors

Background The genomic history of prokaryotic organismal lineages is marked by extensive horizontal gene transfer (HGT) between groups of organisms at all taxonomic levels. These HGT events have played an essential role in the origin and distribution of biological innovations. Analyses of ancient gene families show that HGT existed in the distant past, even at the time of the organismal last universal common ancestor (LUCA). Most gene transfers originated in lineages that have since gone extinct. Therefore, one cannot assume that the last common ancestors of each gene were all present in the same cell representing the cellular ancestor of all extant life. Results Organisms existing as part of a diverse ecosystem at the time of LUCA likely shared genetic material between lineages. If these other lineages persisted for some time, HGT with the descendants of LUCA could have continued into the bacterial and archaeal lineages. Phylogenetic analyses of aminoacyl-tRNA synthetase protein families support the hypothesis that the molecular common ancestors of the most ancient gene families did not all coincide in space and time. This is most apparent in the evolutionary histories of seryl-tRNA synthetase and threonyl-tRNA synthetase protein families, each containing highly divergent “rare” forms, as well as the sparse phylogenetic distributions of pyrrolysyl-tRNA synthetase, and the bacterial heterodimeric form of glycyl-tRNA synthetase. These topologies and phyletic distributions are consistent with horizontal transfers from ancient, likely extinct branches of the tree of life. Conclusions Of all the organisms that may have existed at the time of LUCA, by definition only one lineage is survived by known progeny; however, this lineage retains a genomic record of heterogeneous genetic origins. The evolutionary histories of aminoacyl-tRNA synthetases (aaRS) are especially informative in detecting this signal, as they perform primordial biological functions, have undergone several ancient HGT events, and contain many sites with low substitution rates allowing deep phylogenetic reconstruction. We conclude that some aaRS families contain groups that diverge before LUCA. We propose that these ancient gene variants be described by the term “hypnologs”, reflecting their ancient, reticulate origin from a time in life history that has been all but erased”.National Science Foundation (U.S.) (Grant DEB 0830024)Exobiology Program (U.S.) (Grant NNX10AR85G)United States. National Aeronautics and Space Administration (Postdoctoral Program

The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

Abstract. In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure. The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors. This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche à l'Opérationnel à Meso-Echelle) and ALADIN (Aire Limitée Adaptation Dynamique Développement International); and COSMO–EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf. The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU–GPU arrangements

Direct mass spectrometry approaches to characterize polyphenol composition of complex samples

cited By 39International audienceLower molecular weight polyphenols including proanthocyanidin oligomers can be analyzed after HPLC separation on either reversed-phase or normal phase columns. However, these techniques are time consuming and can have poor resolution as polymer chain length and structural diversity increase. The detection of higher molecular weight compounds, as well as the determination of molecular weight distributions, remain major challenges in polyphenol analysis. Approaches based on direct mass spectrometry (MS) analysis that are proposed to help overcome these problems are reviewed. Thus, direct flow injection electrospray ionization mass spectrometry analysis can be used to establish polyphenol fingerprints of complex extracts such as in wine. This technique enabled discrimination of samples on the basis of their phenolic (i.e. anthocyanin, phenolic acid and flavan-3-ol) compositions, but larger oligomers and polymers were poorly detectable. Detection of higher molecular weight proanthocyanidins was also restricted with matrix-assisted laser desorption ionization (MALDI) MS, suggesting that they are difficult to desorb as gas-phase ions. The mass distribution of polymeric fractions could, however, be determined by analyzing the mass distributions of bovine serum albumin/proanthocyanidin complexes using MALDI-TOF-MS. © 2008 Elsevier Ltd. All rights reserved

Effect of winemaking treatment and wine aging on phenolic content in Vranec wines

Phenolic compounds and colour stability of red wines produced from Vranec Vitis vinifera L. grape variety were investigated by means of different maceration times (3, 6 and 10 days), two doses of SO2 (30 and 70 mg/L SO2), two yeasts for fermentation (Vinalco and Levuline), temperature of storage and time of aging (3, 6 and 16 months). In general, maceration time influenced the phenolics extraction from the grapes into the wine. Highest concentrations of phenolic components were observed in the wines produced with 6 days of maceration, except for the flavan-3-ols which were present in highest amounts in the wines macerated for 10 days. Higher doses of SO2 increased the extraction of polyphenols, preventing the wines from oxidation, while the effect of yeast on phenolics extraction was not significant. Wine aging affected the phenolic content of wines produced with 3 days of maceration and caused intensive decrease of anthocyanins during the storage period. Wines aged at higher temperature showed lower anthocyanin levels and less intense coloration. Principal component analysis revealed that separation of the wines was performed according to the hue value in correlation with the maceration time and time of wine aging