Scalable grid resource allocation for scientific workflows using hybrid metaheuristics

Grid infrastructure is a valuable tool for scientific users, but it is characterized by a high level of complexity which makes it difficult for them to quantify their requirements and allocate resources. In this paper, we show that resource trading is a viable and scalable approach for scientific users to consume resources. We propose the use of Grid resource bundles to specify supply and demand combined with a hybrid metaheuristic method to determine the allocation of resources in a market-based approach. We evaluate this through the application domain of scientific workflow execution on the Grid

Three dimensional structure from intensity correlations

We develop the analysis of x-ray intensity correlations from dilute ensembles of identical particles in a number of ways. First, we show that the 3D particle structure can be determined if the particles can be aligned with respect to a single axis having a known angle with respect to the incident beam. Second, we clarify the phase problem in this setting and introduce a data reduction scheme that assesses the integrity of the data even before the particle reconstruction is attempted. Finally, we describe an algorithm that reconstructs intensity and particle density simultaneously, thereby making maximal use of the available constraints.Comment: 17 pages, 9 figure

Resistivity phase diagram of cuprates revisited

The phase diagram of the cuprate superconductors has posed a formidable scientific challenge for more than three decades. This challenge is perhaps best exemplified by the need to understand the normal-state charge transport as the system evolves from Mott insulator to Fermi-liquid metal with doping. Here we report a detailed analysis of the temperature (T) and doping (p) dependence of the planar resistivity of simple-tetragonal HgBa$_2$CuO$_{4+\delta}$ (Hg1201), the single-CuO$_2$-layer cuprate with the highest optimal $T_c$. The data allow us to test a recently proposed phenomenological model for the cuprate phase diagram that combines a universal transport scattering rate with spatially inhomogeneous (de)localization of the Mott-localized hole. We find that the model provides an excellent description of the data. We then extend this analysis to prior transport results for several other cuprates, including the Hall number in the overdoped part of the phase diagram, and find little compound-to-compound variation in (de)localization gap scale. The results point to a robust, universal structural origin of the inherent gap inhomogeneity that is unrelated to doping-related disorder. They are inconsistent with the notion that much of the phase diagram is controlled by a quantum critical point, and instead indicate that the unusual electronic properties exhibited by the cuprates are fundamentally related to strong nonlinearities associated with subtle nanoscale inhomogeneity.Comment: 22 pages, 5 figure

SIMULATION OF THE FLIGHT DISTANCES OF JAVELINS BASED ON A NEURAL NETWORK APPROACH

INTRODUCTION: The flight distances of javelins are determined by the release parameters as well as by the forces acting on the javelin during flight. The flight phase of the javelin has been under investigation by many researchers using engineering approaches to model the flight phase. The objective is to allow an optimization of the release parameters for maximizing the flight distance. The measurement of release parameters as well as wind influence is not very precise. This means that the models are based on already distorted data. Artificial neural networks (NNs, Haykin 1994) are powerful information processing tools that allow to construct a input-output model of a problem by learning from examples. They are able to generalize , i.e. to produce reasonable outputs for inputs that have not been encountered during learning. NNs handle imprecise data well and could be suitable for modeling the flight distance of javelins as a result of the release parameters. METHODS: Release parameters have been measured using three dimensional film and video analysis. Relevant parameters were determined: the angle of release, the angle of attack (seen from the side), the angle of side attack (seen from behind) as well as the velocity of release. The overall flight was measured as the distance between the throwing line and the athlete’s hand at the point of release plus the distance between the line and the point of touch down of the javelin. Other parameters such as javelin brand, wind speed, etc., were not considered in the model. Multi-Layer-Perceptron Neural Networks (MLPs) were used to construct a model with the release parameters as inputs and the overall distance as output. RESULTS: Several setups were used for the training of the MLPs and 40 sets of release parameters were processed. We used 37 sets for the training of the MLPs and 3 sets were kept for examining the MLPs’ generalization performance (crossvalidation). This was repeated with randomly selected sets for training and crossvalidation. Predictions of the total flight distance using the release parameters were exact up to 5 percent of the overall distance for the cross validation sets. CONCLUSIONS: The MLP simulation of the flight distance is a suitable instrument even though it uses only a small number of parameters. This can be helpful for coaching and provides an alternative to other models. Using more data sets may improve the quality of prediction, and further work will include recording more data sets as well as studies on optimal javelin release parameters. REFERENCES: Haykin, S. (1994). Neural Networks. Englewood Cliffs: Macmillan Publishing Company

q-Gaussians in the porous-medium equation: stability and time evolution

The stability of $q$-Gaussian distributions as particular solutions of the linear diffusion equation and its generalized nonlinear form, \pderiv{P(x,t)}{t} = D \pderiv{^2 [P(x,t)]^{2-q}}{x^2}, the \emph{porous-medium equation}, is investigated through both numerical and analytical approaches. It is shown that an \emph{initial} $q$-Gaussian, characterized by an index $q_i$, approaches the \emph{final}, asymptotic solution, characterized by an index $q$, in such a way that the relaxation rule for the kurtosis evolves in time according to a $q$-exponential, with a \emph{relaxation} index $q_{\rm rel} \equiv q_{\rm rel}(q)$. In some cases, particularly when one attempts to transform an infinite-variance distribution ($q_i \ge 5/3$) into a finite-variance one ($q<5/3$), the relaxation towards the asymptotic solution may occur very slowly in time. This fact might shed some light on the slow relaxation, for some long-range-interacting many-body Hamiltonian systems, from long-standing quasi-stationary states to the ultimate thermal equilibrium state.Comment: 20 pages, 6 figure

A method for dense packing discovery

The problem of packing a system of particles as densely as possible is foundational in the field of discrete geometry and is a powerful model in the material and biological sciences. As packing problems retreat from the reach of solution by analytic constructions, the importance of an efficient numerical method for conducting \textit{de novo} (from-scratch) searches for dense packings becomes crucial. In this paper, we use the \textit{divide and concur} framework to develop a general search method for the solution of periodic constraint problems, and we apply it to the discovery of dense periodic packings. An important feature of the method is the integration of the unit cell parameters with the other packing variables in the definition of the configuration space. The method we present led to improvements in the densest-known tetrahedron packing which are reported in [arXiv:0910.5226]. Here, we use the method to reproduce the densest known lattice sphere packings and the best known lattice kissing arrangements in up to 14 and 11 dimensions respectively (the first such numerical evidence for their optimality in some of these dimensions). For non-spherical particles, we report a new dense packing of regular four-dimensional simplices with density $\phi=128/219\approx0.5845$ and with a similar structure to the densest known tetrahedron packing.Comment: 15 pages, 5 figure

Characterization of the self-palmitoylation activity of the transport protein particle component Bet3

Bet3, a transport protein particle component involved in vesicular trafficking, contains a hydrophobic tunnel occupied by a fatty acid linked to cysteine 68. We reported that Bet3 has a unique self-palmitoylating activity. Here we show that mutation of arginine 67 reduced self-palmitoylation of Bet3, but the effect was compensated by increasing the pH. Thus, arginine helps to deprotonate cysteine such that it could function as a nucleophile in the acylation reaction which is supported by the structural analysis of non-acylated Bet3. Using fluorescence spectroscopy we show that long-chain acyl-CoAs bind with micromolar affinity to Bet3, whereas shorter-chain acyl-CoAs do not interact. Mutants with a deleted acylation site or a blocked tunnel bind to Pal-CoA, only the latter with slightly reduced affinity. Bet3 contains three binding sites for Pal-CoA, but their number was reduced to two in the mutant with an obstructed tunnel, indicating that Bet3 contains binding sites on its surface

Wind field and sex constrain the flight speeds of central-place foraging albatrosses

By extracting energy from the highly dynamic wind and wave fields that typify pelagic habitats, albatrosses are able to proceed almost exclusively by gliding flight. Although energetic costs of gliding are low, enabling breeding albatrosses to forage hundreds to thousands of kilometers from their colonies, these and time costs vary with relative wind direction. This causes albatrosses in some areas to route provisioning trips to avoid headwind flight, potentially limiting habitat accessibility during the breeding season. In addition, because female albatrosses have lower wing loadings than males, it has been argued that they are better adapted to flight in light winds, leading to sexual segregation of foraging areas. We used satellite telemetry and immersion logger data to quantify the effects of relative wind speed, sex, breeding stage, and trip stage on the ground speeds (Vg) of four species of Southern Ocean albatrosses breeding at South Georgia. Vg was linearly related to the wind speed component in the direction of flight (Vwf), its effect being greatest on Wandering Albatrosses Diomedea exulans, followed by Black-browed Albatrosses Thalassarche melanophrys, Light-mantled Sooty Albatrosses Phoebatria palpebrata, and Gray-headed Albatrosses T. chrysostoma. Ground speeds at Vwf = 0 were similar to airspeeds predicted by aerodynamic theory and were higher in males than in females. However, we found no evidence that this led to sexual segregation, as males and females experienced comparable wind speeds during foraging trips. Black-browed, Gray-headed, and Light-mantled Sooty Albatrosses did not engage in direct, uninterrupted bouts of flight on moonless nights, but Wandering Albatrosses attained comparable Vg night and day, regardless of lunar phase. Relative flight direction was more important in determining Vg than absolute wind speed. When birds were less constrained in the middle stage of foraging trips, all species flew predominantly across the wind. However, in some instances, commuting birds encountered headwinds during outward trips and tail winds on their return, with the result that Vg was 1.0–3.4 m/s faster during return trips. This, we hypothesize, could result from constraints imposed by the location of prey resources relative to the colony at South Georgia or could represent an energy optimization strategy

Consequences of the H-Theorem from Nonlinear Fokker-Planck Equations

A general type of nonlinear Fokker-Planck equation is derived directly from a master equation, by introducing generalized transition rates. The H-theorem is demonstrated for systems that follow those classes of nonlinear Fokker-Planck equations, in the presence of an external potential. For that, a relation involving terms of Fokker-Planck equations and general entropic forms is proposed. It is shown that, at equilibrium, this relation is equivalent to the maximum-entropy principle. Families of Fokker-Planck equations may be related to a single type of entropy, and so, the correspondence between well-known entropic forms and their associated Fokker-Planck equations is explored. It is shown that the Boltzmann-Gibbs entropy, apart from its connection with the standard -- linear Fokker-Planck equation -- may be also related to a family of nonlinear Fokker-Planck equations.Comment: 19 pages, no figure