Constraining dark energy interacting models with WMAP

We determine the range of parameter space of an interacting quintessence (IQ) model that best fits the luminosity distance of type Ia supernovae data and the recent WMAP measurements of Cosmic Microwave Background temperature anisotropies. Models in which quintessence decays into dark matter provide a clean explanation for the coincidence problem. We focus on cosmological models of zero spatial curvature. We show that if the dark energy (DE) decays into cold dark matter (CDM) at a rate that brings the ratio of matter to dark energy constant at late times, the supernovae data are not sufficient to constrain the interaction parameter. On the contrary, WMAP data constrain it to be smaller than $c^2 < 10^{-2}$ at the $3\sigma$ level. Accurate measurements of the Hubble constant and the dark energy density, independent of the CMB data, would support/disprove this set of models.Comment: 4 pages, 3 figures. Uses AIP style. To be published in the AIP Proceedings of the XXVIII Spanish Relativity Meetin

Santuario Mirador Cerro la Virgen la Montana de Teno

122 p.Un lugar Múltiple, capaz de ser soporte de actividades que beneficien a la comunidad, de ser referente y conector. Ese es el potencial del Cerro La Virgen en La Montaña de Teno. Lugar ubicado en la precordillera, y en el que se desarrollo el ejercicio en comento. El proyecto “Santuario-Mirador Cerro La Virgen” se inscribe dentro del contexto de proyectos de titulo de la Universidad de Talca y, en ese marco, pretende con una obra de bajo costo lograr un mejoramiento en la calidad de vida de La comunidad en la cual se inserta La iniciativa consiste a nivel territorial en colocar a una comunidad en el mapa mental de una Región, con el fin de referenciar y orientar a un territorio y su comunidad a un mejor concepto y autovaloración territorio a través de un hito reconocible y referente y en el ámbito local crear un lugar de encuentro, a través de la recuperación para la comunidad del Cerro La Virgen y la legitimación de las actividades que en éste se desarrollan

A Bayesian Monte Carlo Markov Chain Method for the Statistical Analysis of Geodetic Time Series

Geodetic time series provide information which help to constrain theoretical models of geophysical processes. It is well established that such time series, for example from GPS or gravity measurements, contain time-correlated noise which is usually assumed to be a combination of a long-term stochastic process (characterized by a power-law spectrum) and random noise. Therefore, when fitting a model to geodetic time series it is essential to also estimate the stochastic parameters beside the deterministic ones. In many cases the stochastic parameters have included the power amplitudes of both time-correlated and random noise as well as the spectral index of the power-law process. To date the most widely used method for obtaining these model parameter estimates is based on maximum likelihood estimation (MLE). We present a new Bayesian Monte Carlo Markov Chain (MCMC) method to estimate the deterministic and stochastic model parameters of geodetic time series. This method provides a sample of the likelihood function and thereby, using Monte Carlo integration, all parameters and their uncertainties are estimated simultaneously. One advantage of this method over MLE is that the computation time required increases linearly with the number of parameters, hence being very suitable for dealing with a large number of parameters. Another advantage is that the properties of the estimator used by the MCMC method do not depend on the stationarity of the time series. We assess the MCMC method through comparison with MLE, using a data set of 300 synthetic GPS-like time series and the JPL daily position time series for 90 GPS stations (the IGS core network)

La relación entre la evaluación formativa y el aprendizaje de habilidades cognitivas de los estudiantes de la carrera de técnico en ciencias policiales del IES-ANSP"

La evaluación formativa (EF) es parte del proceso de enseñanza aprendizaje (PEA), se convierte en una estrategia didáctica importante en el desarrollo de las habilidades cognitivas y en la búsqueda de fortalecer la calidad educativa del Instituto Especializado de Nivel Superior, en adelante IES-ANSP o Instituto.Estudiar de forma permanente el sistema de evaluación, permite contribuir a los cambios curriculares; es decir, orientar los procesos educativos y las competencias docente

Effect of forest landscapes composition and configuration on bird community and its functional traits in a hotspot of biodiversity of Chile

Understanding the effect of landscape configuration on the bird species richness and their functional traits (dietary preferences) is important to link the conservation and restoration plans to the production of the crops. Our aims were: 1) to study the influence of forest types (native, mixed and plantations) on the bird species richness in two agroforestry landscapes (heterogeneous/homogeneous); 2) to assess the effect of size/density of forest patches in the birds’ functional traits; 3) to evaluate the effect of isolated trees on them, and 4) to discuss conservation and restoration measures for the birds’ functional traits in agroforestry landscapes. We used hierarchical occupancy models to evaluate the effect of different landscape metrics and detectability measures on bird communities. We recorded a total of 64 bird species. The estimated species richness was considerable higher in homogeneous landscape (31.7 ± 2.7) than heterogeneous (27.3 ± 2.5). Our results showed the bird assemblage had a positive trend with native forests, negative with mixed forests and neutral trend for plantations. The granivores and insectivore’s species showed significant preferences for homogeneous landscape, while omnivores had significant preferences for heterogeneous landscape. Carnivores/Piscivores and herbivores/frugivores species did not show preferences by any landscape type. The response of functional traits depended on different forests attributes. The isolated trees had a significant effect on the birds’ functional traits. In conclusion, it is necessary a deep knowledge about the relationship between the landscape configuration and the bird species richness/functional traits. These findings could help in the future with the conservation, restoration, and rewilding policies in this important hotspot of biodiversity, avoiding alterations in the ecosystem services

Total Impact of Periodic Terms and Coloured Noise on Velocity Estimates

The uncertainties of velocity estimates for position time series of Global Navigation Satellite System (GNSS) stations are mainly affected by a misfit of the deterministic model applied to this data. Insufficiently modelled seasonal signals will propagate into the stochastic model and falsify the results of the noise analysis besides the velocity estimates and their uncertainties. In this presentation we derived the General Dilution of Precision (GDP) of velocity uncertainties. We define this dilution as the ratio between the uncertainties of velocities determined when different deterministic and stochastic models are applied. In this way we discuss, referring to previously published results, how insufficiently modelled seasonal signals influence station velocity uncertainties with white and coloured noise. Using simulated and real data from selected (115) IGS (International GNSS Service) stations we show that the noise character affects GNSS data more than seasonals for time series longer than 9 years

The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties

Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series. While the deterministic model generally includes parameters for a linear and several periodic terms, the stochastic model is a representation of the noise character of the time series in form of a power-law process. For both of these models the optimal model may vary from one time series to another while the models also depend, to some degree, on each other. In the past various power-law processes have been shown to fit the time series and the sources for the apparent temporally-correlated noise were attributed to, for example, mismodelling of satellites orbits, antenna phase centre variations, troposphere, Earth Orientation Parameters, mass loading effects and monument instabilities

On the combined effect of periodic signals and colored noise on velocity uncertainties

The velocity estimates and their uncertainties derived from position time series of Global Navigation Satellite System stations are affected by seasonal signals and their harmonics, and the statistical properties, i.e., the stochastic noise, contained in the series. If the deterministic model in the form of linear trend and periodic terms is not accurate enough to describe the time series, it will alter the stochastic model, and the resulting effect on the velocity uncertainties can be perceived as a result of a misfit of the deterministic model. The effects of insufficiently modeled seasonal signals will propagate into the stochastic model and falsify the results of the noise analysis, in addition to velocity estimates and their uncertainties. We provide the general dilution of precision (GDP) of velocity uncertainties as the ratio of uncertainties of velocities determined from to two different deterministic models while accounting for stochastic noise at the same time. In this newly defined GDP, the first deterministic model includes a linear trend, while the second one includes a linear trend and seasonal signals. These two are tested with the assumption of white noise only as well as the combinations of power-law and white noise in the data. The more seasonal terms are added to the series, the more biased the velocity uncertainties become. With increasing time span of observations, the assumption of seasonal signals becomes less important, and the power-law character of the residuals starts to play a crucial role in the determined velocity uncertainties. With reference frame and sea level applications in mind, we argue that 7 and 9 years of continuous observations is the threshold for white and flicker noise, respectively, while 17 years are required for random-walk to decrease GDP below 5% and to omit periodic oscillations in the GNSS-derived time series taking only the noise model into consideration