Abstract: A mathematical statistical model is needed to obtain an option prime and create a hedging strategy. With formulas derived from stochastic differential equations, the primes for US Dollar/Chilean Pesos currency options using a prime calculator are obtained. Furthermore, a backward simulation of the option prime trajectory is used with a numerical method created for backward stochastic differential equations. The use of statistics in finance is highly important in order to develop complex products.

Abstract: The Idealized-Firebrand Ignition Test (I-FIT) protocol was used to evaluate the piloted ignition delay times of fuel beds composed of leaves of Eucalyptus globulus (Labill.). The amount of fuel layer used for evaluation ranged between the fraction volume (������) of 0.03 to 0.07 which are values expected to be found in forest bed fuels. A theoretical model was developed to describe the heating and ignition of the fuel beds, based on the thermal ignition theory. The model, which was originally developed for pine needle beds, considers the penetration of radiation to the porous matrix. The model is able to accurately predict the ignition delay time for different values of ������, but shows a poorer accuracy for the temperature evolution. This is explained by the large variability observed for the Eucalyptus leaves.

Abstract: The risk of cracking in a concrete pavement that is opened to traffic at early ages is related to the maximum tensile stress sigma(I), that develops in the pavement and its relationship to the measured, age dependent, flexural strength of a beam,f(r). The stress that develops in the pavement is due to several factors including traffic loading and restrained volume change caused by thermal or hygral variations. The stress that develops is also dependent on the time-dependent mechanical properties, pavement thickness, and subgrade stiffness. There is a strong incentive to open many pavements to traffic as early as possible to allow construction traffic or traffic from the traveling public to use the pavement. However, if the pavement is opened to traffic too early, cracking may occur that may compromise the service life of the pavement. The purpose of this paper is two-fold: (1) to examine the current opening strength requirements for concrete pavements (typically a flexural strength from beams, f(r)) and (2) to propose a criterion based on the time-dependent changes of sigma(I)/f(r), which accounts for pavement thickness and subgrade stiffness without adding unnecessary risk for premature cracking. An accelerated pavement testing (APT) facility was used to test concrete pavements that are opened to traffic at an early age to provide data that can be compared with an analytical model to determine the effective sigma(I)/f(r), based on the relevant features of the concrete pavement, the subgrade, and the traffic load. It is anticipated that this type of opening criteria can help the decision makers in two ways: (1) it can open pavement sections earlier thereby reducing construction time and (2) it may help to minimize the use of materials with overly accelerated strength gain that are suspected to be more susceptible to develop damage at early ages than materials that gain strength more slowly. (C) 2015 Elsevier Ltd. All rights reserved.

Abstract: The SET DOMAIN GROUP (SDG) proteins represent an evolutionarily-conserved family of epigenetic regulators present in eukaryotes and are putative candidates for the catalysis of lysine methylation in histones. Plant genomes analyses of this family have been performed in arabidopsis, maize, and rice and functional studies have shown that SDG genes are involved in the control of plant development. In this work, we describe the identification and structural characterization of SDG genes in the Vitis vinifera genome. This analysis revealed the presence of 33 putative SDG genes that can be grouped into different classes, as it has been previously described for plants. In addition to the SET domain, the proteins identified possessed other domains in the different classes. As part of our study regarding the growth and development of grapevine, we selected eight genes and their expression levels were analyzed in representative vegetative and reproductive organs of this species. The selected genes showed different patterns of expression during inflorescence and fruit development, suggesting that they participate in these processes. Furthermore, we showed that the expression of selected SDGs changes during viral infection, using as a model Grapevine Leafroll Associated Virus 3-infected symptomatic grapevine leaves and fruits. Our results suggest that developmental changes caused by this virus could be the result of alterations in SDG expression.

Abstract: In this study, we prove the strong consistency of the least squares estimator in a random sampled linear regression model with long-memory noise and an independent set of random times given by renewal process sampling. Additionally, we illustrate how to work with a random number of observations up to time T = 1. A simulation study is provided to illustrate the behavior of the different terms, as well as the performance of the estimator under various values of the Hurst parameter H.

Abstract: In this paper, we investigate potential pathways for achieving deep reductions in CO2 emissions by 2050 in the Chilean electric power system. We simulate the evolution of the power system using a long-term planning model for policy analysis that identifies investments and operation strategies to meet demand and CO2 emissions reductions at the lowest possible cost. The model considers a simplified representation of the main transmission network and representative days to simulate operations considering the variability of demand and renewable resources at different geographical locations. We perform a scenario analysis assuming different ambitious renewable energy and emission reduction targets by 2050. As observed in other studies, we show that the incremental cost of reducing CO2 emissions without carbon capture or offset alternatives increases significantly as the system approaches zero emissions. Indeed, the carbon tax is multiplied by a factor of 4 to eliminate the last Mt of CO2 emissions, i.e., from 2000 to almost 8500 USD/tCO(2) in 2050. This result highlights the importance of implementing technology-neutral mechanisms that help investors identify the most cost-efficient actions to reduce CO2 emissions. Our analysis shows that Carbon Capture and Storage could permit to divide by more than two the total system cost of a 100% renewable scenario. Furthermore, it also illustrates the importance of implementing economy-wide carbon emissions policies that ensure that the incremental costs to reduce CO2 emissions are roughly similar across different sectors of the economy.

Abstract: Fishing industry has always been an economic motor in many countries around the world, but the fisheries production faces a lot of uncertainty and instability due to the complex factors involved in its operations. In this article, we consider the problem of modeling Chile fishing data using environmental exogenous variables with generalized autoregressive conditional heteroskedasticity (GARCH-X) type models. We carried out this by proposing an ARMA type model for the mean with GARCH-X noise. First, the ARMA, GARCH and GARCH-X models are briefly introduced and the data is described. The exogenous variables are selected from a group of environmental and climatic indicators by correlational analysis. Then, ARMA GARCH and ARMA GARCH-X models with exogenous variables are fitted and compared by information criteria and classical error measures, and stability of its parameters are checked. The statistical tests and comparisons evidenced that a model with inclusion of external variables in mean and variance with the ARMA GARCH-X specification performed better and adjusted the observed values more rigorously. Finally, some conclusions and possible refinations of the applied techniques are given.

Abstract: In the context of updating the 2015 Nationally Determined Contribution (NDC), the government of Chile has updated its estimates of compliance costs for a series of mitigation actions with an emphasis on the energy sector as the main source of its greenhouse gas emissions. Using the information developed in this process, we assess the impact on compliance costs of increasing the flexibility for sources by introducing different emissions trading schemes. For this we develop a detailed optimization model that represents the operational and investment decisions that could be taken by the energy generation, industrial and mining sectors if an Emissions Trading System (ETS) was implemented. An ETS with two cap and trade options is analysed together with an offset mechanism for sources not included in the ETS. Also, two policy goals are considered: a stringent 76% sectoral reduction goal in 2050 similar to Chile's current strict NDC, and a more lax 46% goal similar to Chile's initial 2015 NDC proposal. The results show that (i) cost reductions from increased flexibility for Chile's current strict NDC are significant, and that offsets can play an important role; (ii) the stringency of the reduction goal affects the magnitude of the cost savings related to flexibility and, surprisingly, total abatement costs are negative (i.e. there are benefits) for the 46% reduction goal. In this latter case, the most significant cost reductions result from compelling firms to comply with their allowances in each sector, not increased flexibility. These results highlight the policy relevance of case by case analysis using a modelling approach similar to the one we develop here. Key policy insights ETS implementation can help Chile meet its mitigation commitment for 2050. The compliance costs can vary significantly depending on the flexibility implemented in the emissions trading schemes. Optimization models can help decision-makers define the attributes of an ETS, such as the sectors that should participate, the cap, and the percentage of offsets. The proposed methodology also highlights and quantifies the offsets that can be acquired from sectors that are not part of an ETS, such as forestry, agriculture, and the waste sector. The possibility to acquire of offsets could reduce significantly the cost for industries that participate of an ETS.

Abstract: The Matern family of covariance functions has played a central role in spatial statistics for decades, being a flexible parametric class with one parameter determining the smoothness of the paths of the underlying spatial field. This paper proposes a family of spatial covariance functions, which stems from a reparameterization of the generalized Wendland family. As for the Matern case, the proposed family allows for a continuous parameterization of the smoothness of the underlying Gaussian random field, being additionally compactly supported.
More importantly, we show that the proposed covariance family generalizes the Matern model which is attained as a special limit case. This implies that the (reparametrized) Generalized Wendland model is more flexible than the Matern model with an extra-parameter that allows for switching from compactly to globally supported covariance functions.
Our numerical experiments elucidate the speed of convergence of the proposed model to the Matern model. We also inspect the asymptotic distribution of the maximum likelihood method when estimating the parameters of the proposed covariance models under both increasing and fixed domain asymptotics. The effectiveness of our proposal is illustrated by analyzing a georeferenced dataset of mean temperatures over a region of French, and performing a re-analysis of a large spatial point referenced dataset of yearly total precipitation anomalies.