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In recent decades, Latin America has observed the massification of so-called alternative spiritualities, such as the Nueva Era (New Age). This research sought to explore the Self of New Age participants within a neoliberal context of subjective transformation. Data was collected by semi-structured life history interviews carried out with six New Age practitioners from southern Chile. Content analysis of the interviewees'stories revealed dimensions in the participants'Self, such as: empowerment, search for fulfillment, reluctance of formal institutions, redemption, a therapist in relationships, which can be conceptualized based on neoliberal elements, resulting compatible with the idea of a spiritual entrepreneur and consumer present in this spirituality of self-worship. [ABSTRACT FROM AUTHOR]

The growth dynamics of Aspidosperma polyneuron and Anacardium excelsum species that grow in the tropical dry forest of the Cesar department were analyzied. We used dendrochronological techniques and regression models (Clench, Negative Exponential, Logistic and Gompertz). The results obtained show that A. polyneuron rings allowed to build a chronology of 161 years (1854-2014) and the rings of A. excelsum a chronology of 128 years (1887-2014). The growth of A. polyneuron showed a positive growth with spontaneous rain in the dry months and A. excelsum with the rainiest months. Temperature and SOI did not show correlations with growth. The rings of A. polyneuron and A. excelsum documented local climatic variations, but not global as SOI. According to the regression models, the two species will take more than 100 years to reach the maximum diameter, so it is necessary to think about the conservation of the species and the avoided deforestation. [ABSTRACT FROM AUTHOR]

The ocean/atmosphere interaction is commonly studied through processes or phenomena such as El Niño / Southern Oscillation (ENSO). Many of the statistical studies on the subject, focus on the use models for continuous time series, adjusting models in the time domain, as in the case of univariate or multivariate ARIMA models. However, not always the primary concern is to determine exactly the magnitude of climatic anomalies such as the amount of rainfall in a period but, categorizing the magnitude of precipitation, to determine the probability of occurrence of class, conditioning on different categorizations (i.e. terciles) of ENSO. The objective of this study is to find and / or develop methodological statistical strategies to estimate these probabilities. In particular, we are interested in assessing and modeling the relationship between the occurrence of El Niño (La Niña) and the variability of precipitation in the Central Region of Costa Rica, in May-June-July season. Data are time series of sea surface temperature (SST) in the area of Niño 3 and the Southern Oscillation Index (SOI) for atmospheric pressure. As the response we used rainfall (R) recorded in Juan Santa Maria airport, Costa Rica. The series were categorized into terciles to build two-way contingency tables. The tables were analyzed using log-linear and proportional odds models, to determine the conditional and joint probabilities of rainfall events. We also estimated a measure of ordinal association. [ABSTRACT FROM AUTHOR]

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We indicate how to handle a large database consisting of nonlinear time series, applying different nonlinear modelling techniques to this kind of times series. Nowadays in the current references there is no explicit guide of how to manipulate data from nonlinear time series; however, there are approaches that can be taken account. To this end we studied a monthly database corresponding to South Oscillation Index (SOI) and between the years 1866 to 2006. It explains how there must manipulated this database whose data possess nonlinear characteristic, which will be used to do forecasts several steps ahead. Two standard tests to this database were applied, the Average Mutual Information (AMI) and the False Nearest Neighbours (FNN). The optimal spacing of the information was obtained as well as the number of values backward necessary to predict values towards the future. Then, several models were designed of artificial neural nets (ANN), with different learning rules, function of transfer, elements of process (or neurons) in the hidden layer, etc., that allowed to do forecasting of up to 20 steps ahead. The best networks were those that possessed the rules of learning called extDBD and Delta-Rule, and sigmoid as well as hyperbolic tangent as function of transfer. The type of used network was one of feedforward multilayer perceptron and trained by means of backpropagation technique. Networks were proved by one, two hidden layers and without any hidden layer. The best model that was obtained it turned out to be one that consisted with an alone hidden layer. [ABSTRACT FROM AUTHOR]

In this paper, we propose the representation of the Southern Oscillation Index (SOI) dynamics using a new class of nonlinear hybrid model. In this new model, the non-linearity in the mean is represented by an adaptive neurofuzzy inference system (ANFIS), while the variance is represented using an autoregressive conditional heterocedastic (ARCH) component. In addition, a specification strategy for the proposed model, which is based on a battery of statistical tests is developed. The results indicate that the proposed model captures in a better way the main features of the studied time series, when compared to other competitive models. [ABSTRACT FROM AUTHOR]