Vortex ratchet reversal: The role of interstitial vortices

Triangular arrays of Ni nanotriangles embedded in superconducting Nb films exhibit unexpected dynamical vortex effects. Collective pinning with a vortex lattice configuration different from the expected fundamental triangular "Abrikosov state" is found. The vortex motion which prevails against the triangular periodic potential is produced by channelling effects between triangles. Interstitial vortices coexisting with pinned vortices in this asymmetric potential, lead to ratchet reversal, i.e. a DC output voltage which changes sign with the amplitude of an applied alternating drive current. In this landscape, ratchet reversal is always observed at all magnetic fields (all numbers of vortices) and at different temperatures. The ratchet reversal is unambiguously connected to the presence of two locations for the vortices: interstitial and above the artificial pinning sites.Comment: 21 pages, 4 figures, 1 Tabl

Simulating the behavior of the human brain on GPUS

The simulation of the behavior of the Human Brain is one of the most important challenges in computing today. The main problem consists of finding efficient ways to manipulate and compute the huge volume of data that this kind of simulations need, using the current technology. In this sense, this work is focused on one of the main steps of such simulation, which consists of computing the Voltage on neurons’ morphology. This is carried out using the Hines Algorithm and, although this algorithm is the optimum method in terms of number of operations, it is in need of non-trivial modifications to be efficiently parallelized on GPUs. We proposed several optimizations to accelerate this algorithm on GPU-based architectures, exploring the limitations of both, method and architecture, to be able to solve efficiently a high number of Hines systems (neurons). Each of the optimizations are deeply analyzed and described. Two different approaches are studied, one for mono-morphology simulations (batch of neurons with the same shape) and one for multi-morphology simulations (batch of neurons where every neuron has a different shape). In mono-morphology simulations we obtain a good performance using just a single kernel to compute all the neurons. However this turns out to be inefficient on multi-morphology simulations. Unlike the previous scenario, in multi-morphology simulations a much more complex implementation is necessary to obtain a good performance. In this case, we must execute more than one single GPU kernel. In every execution (kernel call) one specific part of the batch of the neurons is solved. These parts can be seen as multiple and independent tridiagonal systems. Although the present paper is focused on the simulation of the behavior of the Human Brain, some of these techniques, in particular those related to the solving of tridiagonal systems, can be also used for multiple oil and gas simulations. Our studies have proven that the optimizations proposed in the present work can achieve high performance on those computations with a high number of neurons, being our GPU implementations about 4× and 8× faster than the OpenMP multicore implementation (16 cores), using one and two NVIDIA K80 GPUs respectively. Also, it is important to highlight that these optimizations can continue scaling, even when dealing with a very high number of neurons.This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 720270 (HBP SGA1), from the Spanish Ministry of Economy and Competitiveness under the project Computación de Altas Prestaciones VII (TIN2015-65316-P), the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya, under project MPEXPAR: Models de Programació i Entorns d’Execució Parallels (2014-SGR-1051). We thank the support of NVIDIA through the BSC/UPC NVIDIA GPU Center of Excellence, and the European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement No. 749516.Peer ReviewedPostprint (published version

A spatially-structured PCG method for content diversity in a Physics-based simulation game

This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of di ferent levels of di ficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n- body problem, a classical problem in the fi eld of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the di ficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e:, intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of maps with di ferent di ficulty in Gravityvolve!.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Comparison of Two-Level and Multi-level Modelling for Cloud-Based Applications

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-21151-0_2The Cloud Modelling Framework (CloudMF) is an approach to apply model-driven engineering principles to the specification and execution of cloud-based applications. It comprises a domain-specific language to model the deployment topology of multi-cloud applications, along with a models@run-time environment to facilitate reasoning and adaptation of these applications at run-time. This paper reports on some challenges encountered during the design of CloudMF, related to the adoption of the two-level modelling approach and especially the type-instance pattern. Moreover, it proposes the adoption of an alternative, multi-level modelling approach to tackle these challenges, and provides a set of criteria to compare both approaches.The research leading to these results has received funding from the European Commission’s Seventh Framework Programme (FP7/2007-2013) under grant agreement numbers 317715 (PaaSage), 318392 (Broker@Cloud), and 611125 (MONDO), the Spanish Ministry under project Go Lite (TIN2011-24139), and the Madrid Region under project SICOMORO (S2013/ICE-3006)

Study of star-forming galaxies in SDSS up to redshift 0.4: I. Metallicity evolution

The chemical composition of the gas in galaxies versus cosmic time provides a very important tool for understanding galaxy evolution. Although there are many studies at high redshift, they are rather scarce at lower redshifts. However, low redshift studies can provide important clues about the evolution of galaxies, furnishing the required link between local and high redshift universe. In this work we focus on the metallicity of the gas of star-forming galaxies at low redshift, looking for signs of chemical evolution. To analyze the metallicity contents star-forming galaxies of similar luminosities and masses at different redshifts. With this purpose, we present a study of the metallicity of relatively massive (log(M_star/M_sun)>10.5) star forming galaxies from SDSS--DR5 (Sloan Digital Sky Survey--Data Release 5), using different redshift intervals from 0.04 to 0.4. We used data processed with the STARLIGHT spectral synthesis code, correcting the fluxes for dust extinction, estimating metallicities using the R_23 method, and segregating the samples with respect to the value of the [NII]6583/[OII]3727 line ratio in order to break the R_23 degeneracy selecting the upper branch. We analyze the luminosity and mass-metallicity relations, and the effect of the Sloan fiber diameter looking for possible biases. By dividing our redshift samples in intervals of similar magnitude and comparing them, significant signs of metallicity evolution are found. Metallicity correlates inversely with redshift: from redshift 0 to 0.4 a decrement of ~0.1 dex in 12+log(O/H) is found.Comment: 11 pages, 9 figures, Accepted for publication in A&

Centinela: A human activity recognition system based on acceleration and vital sign data

This paper presents Centinela, a system that combines acceleration data with vital signs to achieve highly accurate activity recognition. Centinela recognizes five activities: walking, running, sitting, ascending, and descending. The system includes a portable and unobtrusive real-time data collection platform, which only requires a single sensing device and a mobile phone. To extract features, both statistical and structural detectors are applied, and two new features are proposed to discriminate among activities during periods of vital sign stabilization. After evaluating eight different classifiers and three different time window sizes, our results show that Centinela achieves up to 95.7% overall accuracy, which is higher than current approaches under similar conditions. Our results also indicate that vital signs are useful to discriminate between certain activities. Indeed, Centinela achieves 100% accuracy for activities such as running and sitting, and slightly improves the classification accuracy for ascending compared to the cases that utilize acceleration data only

Home Language and Literacy Environments and Early Literacy Trajectories of Low-Socioeconomic Status Chilean Children

This study used Latent Class Analysis to identify groups of children exposed to similar Home Language and Literacy Environments (HLLE) and explored whether belonging to a given HLLE group was related to children's language and early literacy growth from prekindergarten to kindergarten. Participants were 1,425 Chilean mothers and their children (M-age = 52.52 months at baseline) from low-socioeconomic status households. Four HLLE groups were identified, which were associated with different trajectories of language and early literacy development. Children from groups whose mothers either read and talk about past events with them or teach them letters in addition to reading and talking about past events, showed higher relative vocabulary and letter knowledge. Implications for research and interventions are discussed

Vortex ratchet reversal at fractional matching fields in kagom\'e-like array with symmetric pinning centers

Arrays of Ni nanodots embedded in Nb superconducting films have been fabricated by sputtering and electron beam lithography techniques. The arrays are periodic triangular lattices of circular Ni dots arranged in a kagom\'e-like pattern with broken reflection symmetry. Relevant behaviors are found in the vortex lattice dynamics : i) At values lower than the first integer matching field, several fractional matching fields are present when the vortex lattice moves parallel or perpendicular to the reflection symmetry axis of the array showing a clear anisotropic character in the magnetoresistance curves, ii) injecting an ac current perpendicular to the reflection symmetry axis of the array yields an unidirectional motion of the vortex lattice (ratchet effect) as a result of the interaction between the whole vortex lattice and the asymmetric lattice of dots, iii) increasing the input current amplitudes the ratchet effect changes polarity independently of matching field values. These experimental results can be explained taking into account the vortex lattice density.Comment: 9 pages, 4 figures, 1 tabl