115 research outputs found
Simulation of Resource Monitoring and Discovery in Grids
The proliferation of huge computer centers with thousands of processors available, summed up with the new computing paradigms as cloud computing, make distributed environment a maze of new perspectives. Dynamics of resource information is increasing in complexity, and nowadays is almost impossible to be captured using a static hierarchy. Consequently, we focused on developing new tools to attack this new challenges. Grid-Matrix is a framework with an user-friendly GUI, based on the famous grid simulator SimGrid. It is focused on the analysis of information propagation policies, including automatic generation of very varied network topologies, and many different policies scenarios. As a case study, we present the generation of clique and ring networks under three different policies: hierarchical, super-peer and random. These preliminary results shows the potential of this powerful framework, plenty of features for the profound analysis of information propagation.Sociedad Argentina de Informática e Investigación Operativ
Gaining insight in the analysis of performance for Resource Monitoring and Discovery in Grids
Nowadays, many High Performance Computing (HPC) centers with thousands of cores are available. The interconnection and synchronization between them is one of objectives of Grid Computing, as all these centers tend to form a global shared computing facility. In such scenario, dynamics of resource information is increasingly complex, and may become almost impossible to be captured using a static hierarchy. One of the key features needed in Grid Computing is to maintain up-to-date information about resources and services. Two important parameters that must be selected are the information refresh and expiration times. In this work, R is presented for studying the relation between these important parameters in three policies: Hierarchical, Super-peer and Random. The results reveal an interesting relation between expiration and refresh times in all studied policies. The study of this new parameter is essential to provide a deeper knowledge in new information distribution policies and in the configuration or deployment of existing ones.Sociedad Argentina de Informática e Investigación Operativ
Impact of Universal Health Coverage on Child Growth and Nutrition in Argentina
Objectives. To estimate trends of undernutrition (stunting and underweight) among children younger than 5 years covered by the universal health coverage programs Plan Nacer and Programa Sumar. Methods. From 2005 to 2013, Plan Nacer and Programa Sumar collected high-quality information on birth and visit dates, age (in days), gender, weight (in kg), and height (in cm) for 1.4 million children in 6386 health centers (13 million records) with broad coverage of vulnerable populations in Argentina. Results. The prevalence of stunting and underweight decreased 45.0% (from 20.6% to 11.3%) and 38.0% (from 4.0% to 2.5%), respectively, with differences between rural versus urban areas, gender, regions, age, and seasons. Conclusions. Undernutrition prevalence substantially decreased in 2 programs in Argentina as a result of universal health coverage.Fil: Nuñez, Pablo Alfredo. Ministerio de Salud. Instituto Nacional de Medicina Tropical; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fernández Slezak, Diego. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación. Laboratorio de Inteligencia Artificial Aplicada; ArgentinaFil: Farall, Andrés. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; ArgentinaFil: Szretter Noste, María Eugenia. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; ArgentinaFil: Salomón, Oscar D.. Ministerio de Salud. Instituto Nacional de Medicina Tropical; ArgentinaFil: Valeggia, Claudia Rita. University of Yale; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
When the optimal is not the best: parameter estimation in complex biological models
Background: The vast computational resources that became available during the
past decade enabled the development and simulation of increasingly complex
mathematical models of cancer growth. These models typically involve many free
parameters whose determination is a substantial obstacle to model development.
Direct measurement of biochemical parameters in vivo is often difficult and
sometimes impracticable, while fitting them under data-poor conditions may
result in biologically implausible values.
Results: We discuss different methodological approaches to estimate
parameters in complex biological models. We make use of the high computational
power of the Blue Gene technology to perform an extensive study of the
parameter space in a model of avascular tumor growth. We explicitly show that
the landscape of the cost function used to optimize the model to the data has a
very rugged surface in parameter space. This cost function has many local
minima with unrealistic solutions, including the global minimum corresponding
to the best fit.
Conclusions: The case studied in this paper shows one example in which model
parameters that optimally fit the data are not necessarily the best ones from a
biological point of view. To avoid force-fitting a model to a dataset, we
propose that the best model parameters should be found by choosing, among
suboptimal parameters, those that match criteria other than the ones used to
fit the model. We also conclude that the model, data and optimization approach
form a new complex system, and point to the need of a theory that addresses
this problem more generally
<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties
Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7.
Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release.
Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue.
Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7.
Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data
Gaia Focused Product Release: Radial velocity time series of long-period variables
The third Gaia Data Release (DR3) provided photometric time series of more
than 2 million long-period variable (LPV) candidates. Anticipating the
publication of full radial-velocity (RV) in DR4, this Focused Product Release
(FPR) provides RV time series for a selection of LPVs with high-quality
observations. We describe the production and content of the Gaia catalog of LPV
RV time series, and the methods used to compute variability parameters
published in the Gaia FPR. Starting from the DR3 LPVs catalog, we applied
filters to construct a sample of sources with high-quality RV measurements. We
modeled their RV and photometric time series to derive their periods and
amplitudes, and further refined the sample by requiring compatibility between
the RV period and at least one of the , , or
photometric periods. The catalog includes RV time series and variability
parameters for 9\,614 sources in the magnitude range , including a flagged top-quality subsample of 6\,093 stars
whose RV periods are fully compatible with the values derived from the ,
, and photometric time series. The RV time series
contain a mean of 24 measurements per source taken unevenly over a duration of
about three years. We identify the great most sources (88%) as genuine LPVs,
with about half of them showing a pulsation period and the other half
displaying a long secondary period. The remaining 12% consists of candidate
ellipsoidal binaries. Quality checks against RVs available in the literature
show excellent agreement. We provide illustrative examples and cautionary
remarks. The publication of RV time series for almost 10\,000 LPVs constitutes,
by far, the largest such database available to date in the literature. The
availability of simultaneous photometric measurements gives a unique added
value to the Gaia catalog (abridged)Comment: 36 pages, 38 figure
The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain
The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates
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Gaia Early Data Release 3: The celestial reference frame (Gaia-CRF3)
Context. Gaia-CRF3 is the celestial reference frame for positions and proper motions in the third release of data from the Gaia mission, Gaia DR3 (and for the early third release, Gaia EDR3, which contains identical astrometric results). The reference frame is defined by the positions and proper motions at epoch 2016.0 for a specific set of extragalactic sources in the (E)DR3 catalogue. Aims. We describe the construction of Gaia-CRF3 and its properties in terms of the distributions in magnitude, colour, and astrometric quality. Methods. Compact extragalactic sources in Gaia DR3 were identified by positional cross-matching with 17 external catalogues of quasi-stellar objects (QSO) and active galactic nuclei (AGN), followed by astrometric filtering designed to remove stellar contaminants. Selecting a clean sample was favoured over including a higher number of extragalactic sources. For the final sample, the random and systematic errors in the proper motions are analysed, as well as the radio-optical offsets in position for sources in the third realisation of the International Celestial Reference Frame (ICRF3). Results. Gaia-CRF3 comprises about 1.6 million QSO-like sources, of which 1.2 million have five-parameter astrometric solutions in Gaia DR3 and 0.4 million have six-parameter solutions. The sources span the magnitude range G = 13-21 with a peak density at 20.6 mag, at which the typical positional uncertainty is about 1 mas. The proper motions show systematic errors on the level of 12 μas yr-1 on angular scales greater than 15 deg. For the 3142 optical counterparts of ICRF3 sources in the S/X frequency bands, the median offset from the radio positions is about 0.5 mas, but it exceeds 4 mas in either coordinate for 127 sources. We outline the future of Gaia-CRF in the next Gaia data releases. Appendices give further details on the external catalogues used, how to extract information about the Gaia-CRF3 sources, potential (Galactic) confusion sources, and the estimation of the spin and orientation of an astrometric solution
Gaia Data Release 3: Mapping the asymmetric disc of the Milky Way
With the most recent Gaia data release the number of sources with complete 6D
phase space information (position and velocity) has increased to well over 33
million stars, while stellar astrophysical parameters are provided for more
than 470 million sources, in addition to the identification of over 11 million
variable stars. Using the astrophysical parameters and variability
classifications provided in Gaia DR3, we select various stellar populations to
explore and identify non-axisymmetric features in the disc of the Milky Way in
both configuration and velocity space. Using more about 580 thousand sources
identified as hot OB stars, together with 988 known open clusters younger than
100 million years, we map the spiral structure associated with star formation
4-5 kpc from the Sun. We select over 2800 Classical Cepheids younger than 200
million years, which show spiral features extending as far as 10 kpc from the
Sun in the outer disc. We also identify more than 8.7 million sources on the
red giant branch (RGB), of which 5.7 million have line-of-sight velocities,
allowing the velocity field of the Milky Way to be mapped as far as 8 kpc from
the Sun, including the inner disc. The spiral structure revealed by the young
populations is consistent with recent results using Gaia EDR3 astrometry and
source lists based on near infrared photometry, showing the Local (Orion) arm
to be at least 8 kpc long, and an outer arm consistent with what is seen in HI
surveys, which seems to be a continuation of the Perseus arm into the third
quadrant. Meanwhile, the subset of RGB stars with velocities clearly reveals
the large scale kinematic signature of the bar in the inner disc, as well as
evidence of streaming motions in the outer disc that might be associated with
spiral arms or bar resonances. (abridged
Gaia Early Data Release 3 Acceleration of the Solar System from Gaia astrometry
Context. Gaia Early Data Release 3 (Gaia EDR3) provides accurate astrometry for about 1.6 million compact (QSO-like) extragalactic sources, 1.2 million of which have the best-quality five-parameter astrometric solutions. Aims. The proper motions of QSO-like sources are used to reveal a systematic pattern due to the acceleration of the solar systembarycentre with respect to the rest frame of the Universe. Apart from being an important scientific result by itself, the acceleration measured in this way is a good quality indicator of the Gaia astrometric solution. Methods. Theeffect of the acceleration was obtained as a part of the general expansion of the vector field of proper motions in vector spherical harmonics (VSH). Various versions of the VSH fit and various subsets of the sources were tried and compared to get the most consistent result and a realistic estimate of its uncertainty. Additional tests with the Gaia astrometric solution were used to get a better idea of the possible systematic errors in the estimate. Results. Our best estimate of the acceleration based on Gaia EDR3 is (2.32 +/- 0.16) x 10(-10) m s(-2) (or 7.33 +/- 0.51 km s(-1) Myr-1) towards alpha = 269.1 degrees +/- 5.4 degrees, delta = -31.6 degrees +/- 4.1 degrees, corresponding to a proper motion amplitude of 5.05 +/- 0.35 mu as yr(-1). This is in good agreement with the acceleration expected from current models of the Galactic gravitational potential. We expect that future Gaia data releases will provide estimates of the acceleration with uncertainties substantially below 0.1 mu as yr(-1).Peer reviewe
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