Viabilidade econômica da venda de energia elétrica em cogeração sob condições de risco: um estudo de caso

The availability of the electrical energy, in sufficient quantities and in competitive prices is a crucial factor to the economic development. The trade-in of the excess electrical energy produced in a system of cogeneration can be seen as an alternative to the creation of an additional source of revenues for ethanol power plants sector, besides contributing to the complementation of the Brazilian electrical headquarter with renewable sources. The objective of this study was to evaluate the economic feasibility of the implementation of a cogeneration electrical central using the excess of sugar cane bagasse and selling the excess of electrical energy with prices of the market. An ethanol power plant located in the state of Sao Paulo was used to this study. It was used the case study methodology, evaluating the potential of the investment under the viewpoint of the Net Present Value (NPV), Payback and Internal Rate of Return (IRR), and complementing the results of the Accounting Results (AC). It was created three alternative scenarios to reflect the level of the risk of every studied situation: the most likely, an optimistic and a pessimistic, each one with its assumptions. The Monte Carlo Simulations was used to insert the elements of risk to each scenario. The results showed that the project is feasible in all NPV scenarios. And the Payback and IRR analysis confirmed these evidences. The valuation with the AR showed that the project is most risky at the pessimistic scenario, but is feasibly in the most likely and the optimistic scenarios. It was concluded that the project is economic viable. However, the economic viability shown in the results is based on the maintenance of the future prices on the levels of the historical prices used in the analysis.

Rentabilidade e Risco da Produção de Milho Safrinha Geneticamente Modificado e Convencional na Região de Guaíra/sp

The objective of this study was to dimension the economic risks and returns on adopters of genetically modified (GM) maize in one of the major corn producing regions of São Paulo state. We performed analysis of variation of the quantities and prices of insecticides used, productivity gains, and variation in the price differentials between GM maize and conventional hybrids seeds, according to account to the maize prices oscillation during the period studied. The net benefits methodology was used, in other words, the economic gains minus the costs of GM technology under risk conditions were calculated. The net benefits was calculated as a function of four critical variables: 1) GM maize productivity; 2) costs of pest control; 3) maize price; 4) GM seeds cost. The probability distribution functions of these critical variables were estimated and included in the net benefit equation. Using the Monte Carlo simulation methodology, the following indicator sets were estimated: central tendency measurements, variability in net benefits (total benefits minus total costs), sensitivity analysis of the net benefits in relation to the critical variables, and finally, a map of the risk to GM technology adopters. These indicators allow one to design economic scenarios associated with their probability of occurring. The results showed probability of 85% to positive gains to the farmers who adopted the transgenic maize seed cultivation. The variable with the greatest impact on the farmers' income was the reduction in productivity loss, that means, as higher is the maize productivity, higher will be the net income. The average gain was US$ 137,41 (R$ 2.45/US$)per hectare with the adoption of transgenic maize seed when compared to conventional maize seed.

Eficiência energética de sistemas de produção de mamona no Estado de Minas Gerais

The objective of this study is to determine the economical and energetic efficiency of the castor bean culture in "Zona da Mata" and South of Minas Gerais. Through the method of simulation "Monte Carlo", we verified the probabilities of occurrence of the economical, cultural and energetic efficiency indexes. In relation to the production systems of castor bean in Minas Gerais in the season 2005/2006, we established that the variables price and productivity were the most noticeable for the producers from "Zona da Mata", while in the South of Minas it was productivity. We verified that the probability of the economical efficiency index to be lower than one was 43,26% for the producers from "Zona da Mata" and 39,57% for the ones from the South of Minas. The medium price received covered the medium costs of production. However, we observed that the medium costs in these regions of Minas Gerais, were over the minimum price. Regarding the energetic analysis, the results showed that the systems in the regions studied in Minas Gerasi, presented average of cultural efficiency indexes of 8,26 and 18,89. We concluded that despite the result being favorable from the energetic point of view, from the economical sustainability point of view there is the need of a more effective support policy for the castor bean, taking into consideration that the expectations of the producers with PNPB were not confirmed.

A avaliação da efetividade de um modelo de intervenção breve (método BASICS) para o uso de risco de álcool em estudantes do ensino médio

Pós-graduação em Saúde Coletiva - FMB

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

Estudo da viabilidade de implantação do INOVAR-AUTO utilizando o método do fluxo de caixa sob risco

The automobile industry has a growing importance in the Brazilian economic environment. The industry moves a huge chain that encompasses manufacturers, suppliers of raw materials, auto parts dealers, gas stations, insurance companies, repair shops, tire stores, media companies, advertising agencies, among others. Because of this importance in the current economic environment in Brazil, the federal government, through Law No. 12715 of 17 December 2012 established a Program for the Promotion of Innovation and Densification in the Productive Chain of Motor Vehicles called INOVAR-AUTO in order to support technological development, innovation, safety, environmental protection, energy efficiency and quality of cars, trucks, buses and auto parts. The specific purpose of this study, a simulation for discussion of the viability of the program implementation using the Monte Carlo Simulation combined with the Cash-Flow-at-Risk was performed. To this end, an exploratory and documentary literature on the subject was held as well as a case study in a automobile company of Japanese origin

Understanding the Grafting of Telechelic Polymers on a Solid Substrate to Form Loops

Recent experimental and theoretical studies have demonstrated that relative to singly tethered chains, the presence of polymer loops at interfaces significantly improves interfacial properties such as adhesion, friction, and wettability. In the present study, a simple system was studied to examine the formation of polymeric loops on a solid surface, where the grafting of carboxylic acid terminated telechelic polystyrene from the melt to an epoxy functionalized silicon is chosen. The impact of telechelic molecular weight, grafting temperature, and surface functionality on the telechelic attachment process is studied. It was found that grafting of the telechelic to the surface at both ends to form loops is the primary product of this grafting process. Moreover, examination of the kinetics of the grafting process indicates that it is reaction controlled. Fluorescence tagging of the dangling ends of singly bound chains provides a mechanism to monitor their time evolution during grafting, and these results indicate that the grafting process is accurately described by recent Monte Carlo simulation work. The results also provide a method to control the extent of loop formation at interfaces and therefore provide an opportunity to further understand the role of the loops in the interfacial properties in multicomponent polymer systems.

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

Estudo da viabilidade de implantação do INOVAR-AUTO utilizando o método do fluxo de caixa sob risco

The automobile industry has a growing importance in the Brazilian economic environment. The industry moves a huge chain that encompasses manufacturers, suppliers of raw materials, auto parts dealers, gas stations, insurance companies, repair shops, tire stores, media companies, advertising agencies, among others. Because of this importance in the current economic environment in Brazil, the federal government, through Law No. 12715 of 17 December 2012 established a Program for the Promotion of Innovation and Densification in the Productive Chain of Motor Vehicles called INOVAR-AUTO in order to support technological development, innovation, safety, environmental protection, energy efficiency and quality of cars, trucks, buses and auto parts. The specific purpose of this study, a simulation for discussion of the viability of the program implementation using the Monte Carlo Simulation combined with the Cash-Flow-at-Risk was performed. To this end, an exploratory and documentary literature on the subject was held as well as a case study in a automobile company of Japanese origin

A general threshold stress hybrid hazard model for lifetime data

In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

Distribution and molecular characterization of hepatitis C virus (HCV) genotypes in patients with chronic infection from Pernambuco State, Brazil

Hepatitis C virus (HCV) is a public health problem throughout the world and 3% of the world population is infected with this virus. It is estimated that 3-4 millions individuals are being infected every year. It has been estimated that around 1.5% of Brazilian population is anti-HCV positive and the Northeast region showed the highest prevalence in Brazil. The aim of this study was to characterize HCV genotypes circulating in Pernambuco State (PE), Brazil, located in the Northeast region of the country. This study included 85 anti-HCV positive patients followed up between 2004 and 2011. For genotyping, a 380bp fragment of HCV RNA in the NS5B region was amplified by nested PCR. Phylogenetic analysis was conducted using Bayesian Markov chain Monte Carlo simulation (MCMC) using BEAST v.1.5.3. From 85 samples, 63 (74.1%) positive to NS5B fragment were successfully sequenced. Subtype 1b was the most prevalent in this population (42-66.7%), followed by 3a (16-25.4%), 1a (4-6.3%) and 2b (1-1.6%). Twelve (63.1%) and seven (36.9%) patients with HCV and schistosomiasis were infected with subtypes 1b and 3a, respectively. Brazil is a large country with many different population backgrounds; a large variation in the frequencies of HCV genotypes is predictable throughout its territory. This study reports HCV genotypes from Pernambuco State where subtype 1b was found to be the most prevalent. Phylogenetic analysis suggests the presence of the different HCV strains circulating within this population. (C) 2012 Elsevier B.V. All rights reserved.

A new analysis of the GJ581 extrasolar planetary system

We have done a new analysis of the available observations of the GJ581 exoplanetary system. Today this system is controversial due to choices that can be done in the orbital determination. The main ones are the occurrence of aliases and the additional bodies-the planets f and g-announced in Vogt et al. (Astrophys J 723:954-965, 2010). Any dynamical study of exoplanets requires the good knowledge of the orbital elements and the investigations involving the planet g are particularly interesting, since this body would lie in the habitable zone (HZ) of the star GJ581. This region, for this system, is very attractive of the dynamical point of view due to several resonances of two and three bodies present there. In this work, we investigate the conditions under which the planet g may exist. We stress the fact that the planet g is intimately related with the orbital elements of the planet d; more precisely, we conclude that it is not possible to disconnect its existence from the determination of the eccentricity of the planet d. Concerning the planet f, we have found one solution with period a parts per thousand 450 days, but we are judicious about any affirmation concerning this body because its signal is in the threshold of detection and the high period is in a spectral region where the occurrence of aliases is very common. Besides, we outline some dynamical features of the HZ with the dynamical map and point out the role played by some resonances laying there.

Risk assessment of PM2.5 to child residents in Brazilian Amazon region with biofuel production

Background: Exposure to fine fractions of particulate matter (PM2.5) is associated with increased hospital admissions and mortality for respiratory and cardiovascular disease in children and the elderly. This study aims to estimate the toxicological risk of PM2.5 from biomass burning in children and adolescents between the age of 6 and 14 in Tangara da Serra, a municipality of Subequatorial Brazilian Amazon. Methods: Risk assessment methodology was applied to estimate the risk quotient in two scenarios of exposure according to local seasonality. The potential dose of PM2.5 was estimated using the Monte Carlo simulation, stratifying the population by age, gender, asthma and Body Mass Index (BMI). Results: Male asthmatic children under the age of 8 at normal body rate had the highest risk quotient among the subgroups. The general potential average dose of PM2.5 was 1.95 mu g/kg.day (95% CI: 1.62 - 2.27) during the dry scenario and 0.32 mu g/kg. day (95% CI: 0.29 - 0.34) in the rainy scenario. During the dry season, children and adolescents showed a toxicological risk to PM2.5 of 2.07 mu g/kg. day (95% CI: 1.85 - 2.30). Conclusions: Children and adolescents living in the Subequatorial Brazilian Amazon region were exposed to high levels of PM2.5 resulting in toxicological risk for this multi-pollutant. The toxicological risk quotients of children in this region were comparable or higher to children living in metropolitan regions with PM2.5 air pollution above the recommended limits to human health.

Low-temperature thermodynamic properties near the field-induced quantum critical point in NiCl2-4SC(NH2)(2)

We present a comprehensive experimental and theoretical investigation of the thermodynamic properties: specific heat, magnetization, and thermal expansion in the vicinity of the field-induced quantum critical point (QCP) around the lower critical field H-c1 approximate to 2 T in NiCl2-4SC(NH2)(2). A T-3/2 behavior in the specific heat and magnetization is observed at very low temperatures at H = H-c1, which is consistent with the universality class of Bose-Einstein condensation of magnons. The temperature dependence of the thermal expansion coefficient at H-c1 shows minor deviations from the expected T-1/2 behavior. Our experimental study is complemented by analytical calculations and quantum Monte Carlo simulations, which reproduce nicely the measured quantities. We analyze the thermal and the magnetic Gruneisen parameters, which are ideal quantities to identify QCPs. Both parameters diverge at H-c1 with the expected T-1 power law. By using the Ehrenfest relations at the second-order phase transition, we are able to estimate the pressure dependencies of the characteristic temperature and field scales.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.