Dow Jones Industrial Average

Le Dow Jones Industrial Average souvent raccourci en Dow Jones est un indice du New York Stock Exchange. C'est le plus vieil indice boursier du monde. L'indice repose sur la capitalisation boursière des 30 plus grosses entreprises cotées au New York Stock Exchange. Les entreprises présentes évoluent avec le temps. La marque Dow Jones est la propriété de Dow Jones Indexes, une coentreprise détenue à 90% par CME Group et à 10 % par Dow Jones and Company. Origine et création L'indice a été créé en 1896 par Charles Dow (1851-1902) et Edward Jones, deux journalistes qui travaillaient auparavant dans une agence de presse financière, le Wall Street Financial News Bureau. Ils créèrent la société Dow Jones avec pour ambition d'estimer quelles valeurs industrielles ont le plus fort potentiel de la Bourse. Histoire et évolution Composition historique du Dow Jones Industrial Average

1884 : fondation de l'indice par Charles Dow. Sur onze sociétés, neuf sont des c

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Semantically Enriched Industry Data & Information Modelling: A feasibility study on Shop-floor Incident Recognition

Damiano Nunzio Arena, Dimitrios Kyritsis, Apostolos Perdikakis

Knowledge modelling at industrial level consists an importunate activity nowadays due to the ceaseless advances in technologies and standards applied as well as the extensive amount of unrelated real-time and historical data at shop-floor level. A Common Interface Data Exchange Model (CIDEM) is hereby introduced towards unifying continuously produced data from heterogeneous and distributed information sources - on different levels and granularities - into a shared vocabulary that can unobtrusively communicate with industrial standards and protocols (i.e. B2MML, gbXML, MIMOSA). For further enhancing the information model a conceptual definition is employed leading to a semantically enriched model which enables more understandable high level knowledge diffusion. This model has been applied to various industrial applications, one of the most important being industrial safety, through incident recognition.

IEEE2016

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Interleaving with Coroutines: A Practical Approach for Robust Index Joins

Anastasia Ailamaki, Georgios Psaropoulos

Index join performance is determined by the efficiency of the lookup operation on the involved index. Although database indexes are highly optimized to leverage processor caches, main memory accesses inevitably increase lookup runtime when the index outsizes the last-level cache; hence, index join performance drops. Still, robust index join performance becomes possible with instruction stream interleaving: given a group of lookups, we can hide cache misses in one lookup with instructions from other lookups by switching among their respective instruction streams upon a cache miss. In this paper, we propose interleaving with coroutines for any type of index join. We showcase our proposal on SAP HANA by implementing binary search and CSB+-tree traversal for an instance of index join related to dictionary compression. Coroutine implementations not only perform similarly to prior interleaving techniques, but also resemble the original code closely, while supporting both interleaved and non-interleaved execution. Thus, we claim that coroutines make interleaving practical for use in real DBMS codebases.

VLDB Endowment Inc.2017

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Emergence of diauxie as an optimal growth strategy under resource allocation constraints in cellular metabolism

Vassily Hatzimanikatis, Pierre Guy Rémy Salvy

Diauxie, or the sequential consumption of carbohydrates in bacteria such as Escherichia coli, has been hypothesized to be an evolutionary strategy which allows the organism to maximize its instantaneous specific growth-giving the bacterium a competitive advantage. Currently, the computational techniques used in industrial biotechnology fall short of explaining the intracellular dynamics underlying diauxic behavior. In particular, the understanding of the proteome dynamics in diauxie can be improved. We developed a robust iterative dynamic method based on expression- and thermodynamically enabled flux models to simulate the kinetic evolution of carbohydrate consumption and cellular growth. With minimal modeling assumptions, we couple kinetic uptakes, gene expression, and metabolic networks, at the genome scale, to produce dynamic simulations of cell cultures. The method successfully predicts the preferential uptake of glucose over lactose in E. coli cultures grown on a mixture of carbohydrates, a manifestation of diauxie. The simulated cellular states also show the reprogramming in the content of the proteome in response to fluctuations in the availability of carbon sources, and it captures the associated time lag during the diauxie phenotype. Our models suggest that the diauxic behavior of cells is the result of the evolutionary objective of maximization of the specific growth of the cell. We propose that genetic regulatory networks, such as the lac operon in E. coli, are the biological implementation of a robust control system to ensure optimal growth.

NATL ACAD SCIENCES2021

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