5 resultados para Persistence

em Universidad Politécnica de Madrid


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In the southern Duero Basin of central Spain, there are vast areas of aeolian sand sheets and dune fields. A comprehensive survey of the sand quarries in this area identified a number of palaeosols in sedimentary sequences. The identification and AMS radiocarbon dating of soil charcoal fragments collected in these palaeosols indicate the persistence of Pinus pinaster in this area throughout most of the Holocene. Although potential natural vegetation models have usually considered the Pinus pinaster forests in this inland area of artificial origin, soil charcoal analysis provides firm evidence of a natural origin. Our data fit perfectly with the pattern of Holocene vegetation development for inland areas of Iberia, which are characterised by stability of pine forests throughout the Holocene. Finally, the growing body of palaeobotanical evidence from Iberia (macrofossils and pollen) is contributing to improve our knowledge of P. pinaster ecology, showing that this species has been present in most Iberian regions during the Holocene, where it has inhabited areas characterised by a very diverse set of climatic and soil conditions.

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Many neurodegenerative diseases are characterized by malfunction of the DNA damage response. Therefore, it is important to understand the connection between system level neural network behavior and DNA. Neural networks drawn from genetically engineered animals, interfaced with micro-electrode arrays allowed us to unveil connections between networks’ system level activity properties and such genome instability. We discovered that Atm protein deficiency, which in humans leads to progressive motor impairment, leads to a reduced synchronization persistence compared to wild type synchronization, after chemically imposed DNA damage. Not only do these results suggest a role for DNA stability in neural network activity, they also establish an experimental paradigm for empirically determining the role a gene plays on the behavior of a neural network.

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This paper describes a model of persistence in (C)LP languages and two different and practically very useful ways to implement this model in current systems. The fundamental idea is that persistence is a characteristic of certain dynamic predicates (Le., those which encapsulate state). The main effect of declaring a predicate persistent is that the dynamic changes made to such predicates persist from one execution to the next one. After proposing a syntax for declaring persistent predicates, a simple, file-based implementation of the concept is presented and some examples shown. An additional implementation is presented which stores persistent predicates in an external datábase. The abstraction of the concept of persistence from its implementation allows developing applications which can store their persistent predicates alternatively in files or databases with only a few simple changes to a declaration stating the location and modality used for persistent storage. The paper presents the model, the implementation approach in both the cases of using files and relational databases, a number of optimizations of the process (using information obtained from static global analysis and goal clustering), and performance results from an implementation of these ideas.

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This paper describes a model of persistence in (C)LP languages and two different and practically very useful ways to implement this model in current systems. The fundamental idea is that persistence is a characteristic of certain dynamic predicates (i.e., those which encapsulate state). The main effect of declaring a predicate persistent is that the dynamic changes made to such predicates persist from one execution to the next one. After proposing a syntax for declaring persistent predicates, a simple, file-based implementation of the concept is presented and some examples shown. An additional implementation is presented which stores persistent predicates in an external database. The abstraction of the concept of persistence from its implementation allows developing applications which can store their persistent predicates alternatively in files or databases with only a few simple changes to a declaration stating the location and modality used for persistent storage. The paper presents the model, the implementation approach in both the cases of using files and relational databases, a number of optimizations of the process (using information obtained from static global analysis and goal clustering), and performance results from an implementation of these ideas.

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BACKGROUND: The immediate lethality caused by spinosad has been widely studied on Spodoptera exigua (H ¿ ubner). However, long-term effects can also provide valuable information on insecticide toxic action. Here, the persistence of spinosad on Capsicum annuum L. foliage and the lethal and sublethal effects of greenhouse-aged foliar residues of this insecticide on third instars of S. exigua are reported. RESULTS: Foliage was collected at 0, 3, 5, 10, 20, 30, 40 and 50 days after application, and spinosad residues were measured. Residues decreased over time according to first-order kinetics. The average rate constant and half-life of disappearance were 4.44×10?3 and156 daysand5.80×10?3 and120 days for60and120 mg L?1 respectively. Larval mortalitygradually decreased, corresponding to the residues, but was still appreciable (35 and 65% for 60 and 120 mg L?1 respectively) when the larvae were fed with foliage collected 50 days after treatment. Subsequently, pupal development was reduced and varied between 20 and 60% and between 21 and 41% for 60 and 120 mg L?1, respectively, in all ages of leaf residues that were bioassayed. At all time points, the consumption rate by the larvae was reduced between 62 and 84% for both concentrations that were bioassayed. CONCLUSION: It is concluded that, under the present greenhouse conditions, the degradation of spinosad was slower than that reported by other authors in the field, and, because of that, its residues could cause lethal and sublethal effects to S. exigua larvae.