134 resultados para Scale-insects


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Exascale systems of the future are predicted to have mean time between failures (MTBF) of less than one hour. Malleable applications, where the number of processors on which the applications execute can be changed during executions, can make use of their malleability to better tolerate high failure rates. We present AdFT, an adaptive fault tolerance framework for long running malleable applications to maximize application performance in the presence of failures. AdFT framework includes cost models for evaluating the benefits of various fault tolerance actions including checkpointing, live-migration and rescheduling, and runtime decisions for dynamically selecting the fault tolerance actions at different points of application execution to maximize performance. Simulations with real and synthetic failure traces show that our approach outperforms existing fault tolerance mechanisms for malleable applications yielding up to 23% improvement in application performance, and is effective even for petascale systems and beyond.

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During outbreaks, locust swarms can contain millions of insects travelling thousands of kilometers while devastating vegetation and crops. Such large-scale spatial organization is preceded locally by a dramatic density-dependent phenotypic transition in multiple traits. Behaviourally, low-density solitarious individuals avoid contact with one another; above a critical local density, they undergo a rapid behavioural transition to the gregarious phase whereby they exhibit mutual attraction. Although proximate causes of this phase polyphenism have been widely studied, the ultimate driving factors remain unclear. Using an individual-based evolutionary model, we reveal that cannibalism, a striking feature of locust ecology, could lead to the evolution of density-dependent behavioural phase-change in juvenile locusts. We show that this behavioural strategy minimizes risk associated with cannibalistic interactions and may account for the empirically observed persistence of locust groups during outbreaks. Our results provide a parsimonious explanation for the evolution of behavioural plasticity in locusts.

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Recent studies show that fast climate response on time scales of less than a month can have important implications for long-term climate change. In this study, we investigate climate response on the time scale of days to weeks to a step-function quadrupling of atmospheric CO2 and contrast this with the response to a 4% increase in solar irradiance. Our simulations show that significant climate effects occur within days of a stepwise increase in both atmospheric CO2 content and solar irradiance. Over ocean, increased atmospheric CO2 warms the lower troposphere more than the surface, increasing atmospheric stability, moistening the boundary layer, and suppressing evaporation and precipitation. In contrast, over ocean, increased solar irradiance warms the lower troposphere to a much lesser extent, causing a much smaller change in evaporation and precipitation. Over land, both increased CO2 and increased solar irradiance cause rapid surface warming that tends to increase both evaporation and precipitation. However, the physiological effect of increased atmospheric CO2 on plant stomata reduces plant transpiration, drying the boundary layer and decreasing precipitation. This effect does not occur with increased solar irradiance. Therefore, differences in climatic effects from CO2 versus solar forcing are manifested within days after the forcing is imposed.

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We report on the large scale synthesis of millimetre long buckled multiwalled carbon nanotubes by one-step pyrolysis. Current carrying capability of a highly buckled region is shown to be more as compared to a less buckled region.

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Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change ``signal'' in the hydrological observations, above the natural internal climate variability ``noise'' shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.

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Critical applications like cyclone tracking and earthquake modeling require simultaneous high-performance simulations and online visualization for timely analysis. Faster simulations and simultaneous visualization enable scientists provide real-time guidance to decision makers. In this work, we have developed an integrated user-driven and automated steering framework that simultaneously performs numerical simulations and efficient online remote visualization of critical weather applications in resource-constrained environments. It considers application dynamics like the criticality of the application and resource dynamics like the storage space, network bandwidth and available number of processors to adapt various application and resource parameters like simulation resolution, simulation rate and the frequency of visualization. We formulate the problem of finding an optimal set of simulation parameters as a linear programming problem. This leads to 30% higher simulation rate and 25-50% lesser storage consumption than a naive greedy approach. The framework also provides the user control over various application parameters like region of interest and simulation resolution. We have also devised an adaptive algorithm to reduce the lag between the simulation and visualization times. Using experiments with different network bandwidths, we find that our adaptive algorithm is able to reduce lag as well as visualize the most representative frames.

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This paper attempts a quantitative understanding of the effect of length scale on two phase eutectic structure. We first develop a model that considers both the elastic and plastic properties of the interface. Using Al-Al2Cu lamellar eutectic as model system, the parameters of the model were experimentally determined using indentation technique. The model is further validated using the results of bulk compression testing of the eutectics having different length scales. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4761944]

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In macroscopic and even microscopic structural elements, surface effects can be neglected and classical theories are sufficient. As the structural size decreases towards the nanoscale regime, the surface-to-bulk energy ratio increases and surface effects must be taken into account. In the present work, the terahertz wave dispersion characteristics of a nanoplate are studied with consideration of the surface effects as well as the nonlocal small-scale effects. Nonlocal elasticity theory of plate is used to derive the general differential equation based on equilibrium approach to include those scale effects. Scale and surface property dependent wave characteristic equations are obtained via spectral analysis. For the present study the material properties of an anodic alumina with crystallographic of < 111 > direction are considered. The present analysis shows that the effect of surface properties on the flexural waves of nanoplates is more significant. It can be found that the flexural wavenumbers with surface effects are high as compared to that without surface effects. The scale effects show that the wavenumbers of the flexural wave become highly non-linear and tend to infinite at certain frequency. After that frequency the wave will not propagate and the corresponding wave velocities tend to zero at that frequency (escape frequency). The effects of surface stresses on the wave propagation properties of nanoplate are also captured in the present work. (C) 2012 Elsevier Ltd. All rights reserved.

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Ultrasonic wave propagation in a graphene sheet, which is embedded in an elastic medium, is studied using nonlocal elasticity theory incorporating small-scale effects. The graphene sheet is modeled as an one-atom thick isotropic plate and the elastic medium/substrate is modeled as distributed springs. For this model, the nonlocal governing differential equations of motion are derived from the minimization of the total potential energy of the entire system. After that, an ultrasonic type of wave propagation model is also derived. The explicit expressions for the cut-off frequencies are also obtained as functions of the nonlocal scaling parameter and the y-directional wavenumber. Local elasticity shows that the wave will propagate even at higher frequencies. But nonlocal elasticity predicts that the waves can propagate only up to certain frequencies (called escape frequencies), after which the wave velocity becomes zero. The results also show that the escape frequencies are purely a function of the nonlocal scaling parameter. The effect of the elastic medium is captured in the wave dispersion analysis and this analysis is explained with respect to both local and nonlocal elasticity. The simulations show that the elastic medium affects only the flexural wave mode in the graphene sheet. The presence of the elastic matrix increases the band gap of the flexural mode. The present results can provide useful guidance for the design of next-generation nanodevices in which graphene-based composites act as a major element.

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Eclogites and associated high-pressure (HP) rocks in collisional and accretionary orogenic belts preserve a record of subduction and exhumation, and provide a key constraint on the tectonic evolution of the continents. Most eclogites that formed at high pressures but low temperatures at > 10-11 kbar and 450-650 degrees C can be interpreted as a result of subduction of cold oceanic lithosphere. A new class of high-temperature (HT) eclogites that formed above 900 degrees C and at 14 to 30 kbar occurs in the deep continental crust, but their geodynamic significance and processes of formation are poorly understood. Here we show that Neoarchaean mafic-ultramafic complexes in the central granulite facies region of the Lewisian in NW Scotland contain HP/HT garnet-bearing granulites (retrogressed eclogites), gabbros, Iherzolites, and websterites, and that the HP granulites have garnets that contain inclusions of omphacite. From thermodynamic modeling and compositional isopleths we calculate that peak eclogite-facies metamorphism took place at 24-22 kbar and 1060-1040 degrees C. The geochemical signature of one (G-21) of the samples shows a strong depletion of Eu indicating magma fractionation at a crustal level. The Sm-Nd isochron ages of HP phases record different cooling ages of ca. 2480 and 2330 Ma. We suggest that the layered mafic-ultramafic complexes, which may have formed in an oceanic environment, were subducted to eclogite depths, and exhumed as HP garnet-bearing orogenic peridotites. The layered complexes were engulfed by widespread orthogneisses of tonalite-trondhjemite-granodiorite (TTG) composition with granulite facies assemblages. We propose two possible tectonic models: (1) the fact that the relicts of eclogitic complexes are so widespread in the Scourian can be taken as evidence that a >90 km x 40 km-size slab of continental crust containing mafic-ultramafic complexes was subducted to at least 70 km depth in the late Archaean. During exhumation the gneiss protoliths were retrogressed to granulite facies assemblages, but the mafic-ultramafic rocks resisted retrogression. (2) The layered complexes of mafic and ultramafic rocks were subducted to eclogite-facies depths and during exhumation under crustal conditions they were intruded by the orthogneiss protoliths (TTG) that were metamorphosed in the granulite facies. Apart from poorly defined UHP metamorphic rocks in Norway, the retrogressed eclogites in the central granulite/retrogressed eclogite facies Lewisian region, NW Scotland have the highest crustal pressures so far reported for Archaean rocks, and demonstrate that lithospheric subduction was transporting crustal rocks to HP depths in the Neoarchaean. (C) 2012 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

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The Wheeler-Feynman (WF) absorber theory of radiation though no more of interest in explaining self interaction of an electron, can be very useful in today's research in small scale optical systems. The significance of the WF absorber is the use of time-symmetrical solution of Maxwell's equations as opposed to only the retarded solution. The radiative coupling of emitters to nano wires in the near field and change in their lifetimes due to small mode volume enclosures have been elucidated with the retarded solutions before. These solutions have also been shown to agree with quantum electrodynamics, thus allowing for classical electromagnetic approaches in such problems. It is here assumed that the radiative coupling of the emitter with a body is in proportion to its contribution to the classical force of radiative reaction as derived in the WF absorber theory. Representing such nano structures as a partial WF absorber acting on the emitter makes the computations considerably easier than conventional electromagnetic solutions for full boundary conditions.

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Parabolized stability equation (PSE) models are being deve loped to predict the evolu-tion of low-frequency, large-scale wavepacket structures and their radiated sound in high-speed turbulent round jets. Linear PSE wavepacket models were previously shown to be in reasonably good agreement with the amplitude envelope and phase measured using a microphone array placed just outside the jet shear layer. 1,2 Here we show they also in very good agreement with hot-wire measurements at the jet center line in the potential core,for a different set of experiments. 3 When used as a model source for acoustic analogy, the predicted far field noise radiation is in reasonably good agreement with microphone measurements for aft angles where contributions from large -scale structures dominate the acoustic field. Nonlinear PSE is then employed in order to determine the relative impor-tance of the mode interactions on the wavepackets. A series of nonlinear computations with randomized initial conditions are use in order to obtain bounds for the evolution of the modes in the natural turbulent jet flow. It was found that n onlinearity has a very limited impact on the evolution of the wavepackets for St≥0. 3. Finally, the nonlinear mechanism for the generation of a low-frequency mode as the difference-frequency mode 4,5 of two forced frequencies is investigated in the scope of the high Reynolds number jets considered in this paper.

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We have conceived a supersymmetric Type II seesaw model at TeV scale, which has some additional particles consisting of scalar and fermionic triplet Higgs states, whose masses are around a few hundred GeV. In this particular model, we have studied constraints on the masses of triplet states arising from the lepton flavor violating (LFV) processes, such as mu -> 3e and mu -> e gamma. We have analyzed the implications of these constraints on other observable quantities such as the muon anomalous magnetic moment and the decay patterns of scalar triplet Higgses. Scalar triplet Higgs states can decay into leptons and into supersymmetric fields. We have found that the constraints from LFV can affect these various decay modes.

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The identification of the damage mechanisms involved in the wear process demands the finer scale characterization of the surface, as well as the subsurface region of the wear scar region, and to this end, this article discusses the results obtained with Cu-10 wt% Pb-based metallic nanocomposites using a host of characterization techniques, including transmission electron microscopy and ion milling microscopy. Apart from finer scale characterization to understand deformation and cracking during the wear process, X-ray photoelectron spectroscopy analysis of wear debris confirms the occurrence of oxidation of Pb phase to Pb3O4. In order to understand the role of oxides on friction and wear, sliding wear tests in argon were also carried out and such tests did not result in the formation of any tribo-oxides, as confirmed using electron probe microanalysis. Conclusively, oxidative wear is attributed as the dominant wear mechanism in ambient conditions for Cu-10 wt% Pb composite.

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Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.