Linear least squares estimation of the first order moving average parameter

We propose an iterative procedure to minimize the sum of squares function which avoids the nonlinear nature of estimating the first order moving average parameter and provides a closed form of the estimator. The asymptotic properties of the method are discussed and the consistency of the linear least squares estimator is proved for the invertible case. We perform various Monte Carlo experiments in order to compare the sample properties of the linear least squares estimator with its nonlinear counterpart for the conditional and unconditional cases. Some examples are also discussed

Keep on moving from English to Catalan : El determinisme lingüístic en la traducció del moviment

El propòsit d'aquest treball és fixar, basant-nos en l'anàlisi tipològica, les diferències lingüístiques en la construcció de les expressions de moviment de l'anglès i el català. Partim de la hipòtesi que en funció de l'origen de la llengua, s'apliquen solucions diferents a determinats problemes lingüístics que apareixen a l'hora de traduir un discurs. Analitzarem, doncs, el grau de fidelitat de la traducció quant a l'expressió del trajecte i de la manera. Per consegüent, estudiarem si hi ha cap pèrdua d'informació, de qualitat o de genuïnitat en relació amb el text original servint-nos de la comparació d'ambdós estils narratius.

Transfer entropy reconstruction and labeling of neuronal connections from simulated calcium imaging

Neuronal dynamics are fundamentally constrained by the underlying structural network architecture, yet much of the details of this synaptic connectivity are still unknown even in neuronal cultures in vitro. Here we extend a previous approach based on information theory, the Generalized Transfer Entropy, to the reconstruction of connectivity of simulated neuronal networks of both excitatory and inhibitory neurons. We show that, due to the model-free nature of the developed measure, both kinds of connections can be reliably inferred if the average firing rate between synchronous burst events exceeds a small minimum frequency. Furthermore, we suggest, based on systematic simulations, that even lower spontaneous inter-burst rates could be raised to meet the requirements of our reconstruction algorithm by applying a weak spatially homogeneous stimulation to the entire network. By combining multiple recordings of the same in silico network before and after pharmacologically blocking inhibitory synaptic transmission, we show then how it becomes possible to infer with high confidence the excitatory or inhibitory nature of each individual neuron.

Equivalent roughness of gravel-bed rivers

The relation between the equivalent roughness and different grain size percentiles of the sediment in gravel-bed rivers was determined under the hypothesis that the vertical distribution of the flow velocity follows a logarithmic law. A set of 954 data points was selected from rivers with gravel size sediment or larger, with a non-sinuous alignment and free of vegetation or obstacles. According to the results, the ks roughness is equivalent to approximately 2.4D90, 2.8D84, and 6.1D50. No correlation was detected between the sediment sorting and the sediment mobility index on one hand, and, on the other, the coefficient of proportionality of each grain size percentile.

Evaluating the impact of filming on the number of errors committed by nursing students to determine the efficacy of simulated clinical situations

Clinic simulation as a training and knowledge method allows people experiment a real event representation with the aim of acquiring knowledge, abilities and aptitudes. The filming of the staging represents a useful tool to review the decisions taken and the actions they did, with the purpose to highlight the strengths, weaknesses and the areas for improvement. The article describes a study carried out by a group of students in second course of nursing, and it tries to evaluate if there is any influence if somebody is filming you during the clinic simulation, does it make you do more errors or not?

Simulated Annealing, High-Order Statistics and Mutual Information for Separation of Sources

In this article, the fusion of a stochastic metaheuristic as Simulated Annealing (SA) with classical criteria for convergence of Blind Separation of Sources (BSS), is shown. Although the topic of BSS, by means of various techniques, including ICA, PCA, and neural networks, has been amply discussed in the literature, to date the possibility of using simulated annealing algorithms has not been seriously explored. From experimental results, this paper demonstrates the possible benefits offered by SA in combination with high order statistical and mutual information criteria for BSS, such as robustness against local minima and a high degree of flexibility in the energy function.