Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Optimal coexistence of long-term and short-term contracts in labor Markets

We consider a market where firms hire workers to run their projects and such projects differ in profitability. At any period, each firm needs two workers to successfully run its project: a junior agent, with no specific skills, and a senior worker, whose effort is not verifiable. Senior workers differ in ability and their competence is revealed after they have worked as juniors in the market. We study the length of the contractual relationships between firms and workers in an environment where the matching between firms and workers is the result of market interaction. We show that, despite in a one-firm-one-worker set-up long-term contracts are the optimal choice for firms, market forces often induce firms to use short-term contracts. Unless the market only consists of firms with very profitable projects, firms operating highly profitable projects offer short-term contracts to ensure the service of high-ability workers and those with less lucrative projects also use short-term contracts to save on the junior workers' wage. Intermediate firms may (or may not) hire workers through long-term contracts.

A combined analysis of the short-term effects of photochemical air pollutants on mortality within the EMECAM project.

In recent years, some epidemiologic studies have attributed adverse effects of air pollutants on health not only to particles and sulfur dioxide but also to photochemical air pollutants (nitrogen dioxide and ozone). The effects are usually small, leading to some inconsistencies in the results of the studies. Furthermore, the different methodologic approaches of the studies used has made it difficult to derive generic conclusions. We provide here a quantitative summary of the short-term effects of photochemical air pollutants on mortality in seven Spanish cities involved in the EMECAM project, using generalized additive models from analyses of single and multiple pollutants. Nitrogen dioxide and ozone data were provided by seven EMECAM cities (Barcelona, Gijón, Huelva, Madrid, Oviedo, Seville, and Valencia). Mortality indicators included daily total mortality from all causes excluding external causes, daily cardiovascular mortality, and daily respiratory mortality. Individual estimates, obtained from city-specific generalized additive Poisson autoregressive models, were combined by means of fixed effects models and, if significant heterogeneity among local estimates was found, also by random effects models. Significant positive associations were found between daily mortality (all causes and cardiovascular) and NO(2), once the rest of air pollutants were taken into account. A 10 microg/m(3) increase in the 24-hr average 1-day NO(2)level was associated with an increase in the daily number of deaths of 0.43% [95% confidence interval (CI), -0.003-0.86%] for all causes excluding external. In the case of significant relationships, relative risks for cause-specific mortality were nearly twice as much as that for total mortality for all the photochemical pollutants. Ozone was independently related only to cardiovascular daily mortality. No independent statistically significant relationship between photochemical air pollutants and respiratory mortality was found. The results in this study suggest that, given the present levels of photochemical pollutants, people living in Spanish cities are exposed to health risks derived from air pollution.

Improving electricity market price scenarios by means of forecasting factor models

In liberalized electricity markets, generation Companies must build an hourly bidthat is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.

Three essays on short-term macroeconomics : business fluctuations, large devaluations and inflation dynamics

Résumé: At least since the Great Depression, explaining why there are business fluctuations has been one of the biggest challenges that the science of economics has had to face. The hope is that if we could better understand recessions, then we could also be more successful in overcoming them. This dissertation consists of three papers that are part of the general endeavor of economists to understand these fluctuations. The first paper discusses, for a particular model, whether a result related to fluctuations would still hold if time were modeled as continuous rather than discrete. The two other papers focus on price stickiness. The second paper discusses why, after a large devaluation, prices of non-tradables may change by only a small amount in comparison to the magnitude of the devaluation. The third paper examines price adjustment in a model in which information is imperfect and it is costly to change prices.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.

Optimal trading of wind power in the short term market

The energy reform, which is happening all over the world, is caused by the common concern of the future of the humankind in our shared planet. In order to keep the effects of the global warming inside of a certain limit, the use of fossil fuels must be reduced. The marginal costs of the renewable sources, RES are quite high, since they are new technology. In order to induce the implementation of RES to the power grid and lower the marginal costs, subsidies were developed in order to make the use of RES more profitable. From the RES perspective the current market is developed to favor conventional generation, which mainly uses fossil fuels. Intermittent generation, like wind power, is penalized in the electricity market since it is intermittent and thus diffi-cult to control. Therefore, the need of regulation and thus the regulation costs to the producer differ, depending on what kind of generation market participant owns. In this thesis it is studied if there is a way for market participant, who has wind power to use the special characteristics of electricity market Nord Pool and thus reach the gap between conventional generation and the intermittent generation only by placing bids to the market. Thus, an optimal bid is introduced, which purpose is to minimize the regulation costs and thus lower the marginal costs of wind power. In order to make real life simulations in Nord Pool, a wind power forecast model was created. The simulations were done in years 2009 and 2010 by using a real wind power data provided by Hyötytuuli, market data from Nord Pool and wind forecast data provided by Finnish Meteorological Institute. The optimal bid needs probability intervals and therefore the methodology to create probability distributions is introduced in this thesis. In the end of the thesis it is shown that the optimal bidding improves the position of wind power producer in the electricity market.

Electrocardiographic changes during low-dose, short-term therapy of cutaneous leishmaniasis with the pentavalent antimonial meglumine

The pentavalent antimonial (Sb5+) meglumine is the drug of choice for the treatment of cutaneous leishmaniasis (CL) in Brazil. Although the cardiotoxicity of high-dose, long-term Sb5+ therapy is well known, the use of low-dose, short-term meglumine has been considered to be safe and relatively free from significant cardiac effects. In order to investigate the cardiotoxicity of low-dose, short-term therapy with meglumine in cutaneous leishmaniasis, 62 CL patients treated with meglumine were studied. A standard ECG was obtained before and immediately after the first cycle of treatment (15 mg Sb5+ kg-1 day-1). The electrocardiographic interpretation was carried out blindly by two investigators using the Minnesota Code. There were no significant differences in qualitative ECG variables before and after meglumine treatment. However, the corrected QT interval was clearly prolonged after antimonial therapy (420.0 vs 429.3 ms, P<10-6). QTc augmentation exceeded 40 ms in 12 patients, 7 of whom developed marked QTc interval enlargement (500 ms) after meglumine therapy. This previously unrecognized cardiac toxicity induced by short-term, low-dose antimonial therapy has potentially important clinical implications. Since sudden death has been related to QTc prolongation over 500 ms induced by high-dose antimonial therapy, routine electrocardiographic monitoring is probably indicated even in CL patients treated with short-term, low-dose meglumine schedules. Until further studies are conducted to establish the interactions between pentavalent antimonials and other drugs, special care is recommended when using meglumine in combination with other medications, in particular with drugs that also increase the QTc interval.

Short-term follow-up of exercise training program and beta-blocker treatment on quality of life in dogs with naturally acquired chronic mitral valve disease

This study aimed to evaluate the effects of carvedilol treatment and a regimen of supervised aerobic exercise training on quality of life and other clinical, echocardiographic, and biochemical variables in a group of client-owned dogs with chronic mitral valve disease (CMVD). Ten healthy dogs (control) and 36 CMVD dogs were studied, with the latter group divided into 3 subgroups. In addition to conventional treatment (benazepril, 0.3-0.5 mg/kg once a day, and digoxin, 0.0055 mg/kg twice daily), 13 dogs received exercise training (subgroup I; 10.3±2.1 years), 10 dogs received carvedilol (0.3 mg/kg twice daily) and exercise training (subgroup II; 10.8±1.7 years), and 13 dogs received only carvedilol (subgroup III; 10.9±2.1 years). All drugs were administered orally. Clinical, laboratory, and Doppler echocardiographic variables were evaluated at baseline and after 3 and 6 months. Exercise training was conducted from months 3-6. The mean speed rate during training increased for both subgroups I and II (ANOVA, P>0.001), indicating improvement in physical conditioning at the end of the exercise period. Quality of life and functional class was improved for all subgroups at the end of the study. The N-terminal pro-brain natriuretic peptide (NT-proBNP) level increased in subgroup I from baseline to 3 months, but remained stable after training introduction (from 3 to 6 months). For subgroups II and III, NT-proBNP levels remained stable during the entire study. No difference was observed for the other variables between the three evaluation periods. The combination of carvedilol or exercise training with conventional treatment in CMVD dogs led to improvements in quality of life and functional class. Therefore, light walking in CMVD dogs must be encouraged.

Combined Analysis of the Short-Term Effects of Photochemical Air Pollutants on Mortality within the EMECAM Project

In recent years, some epidemiologic studies have attributed adverse effects of air pollutants on health not only to particles and sulfur dioxide but also to photochemical air pollutants (nitrogen dioxide and ozone). The effects are usually small, leading to some inconsistencies in the results of the studies. Furthermore, the different methodologic approaches of the studies used has made it difficult to derive generic conclusions. We provide here a quantitative summary of the short-term effects of photochemical air pollutants on mortality in seven Spanish cities involved in the EMECAM project, using generalized additive models from analyses of single and multiple pollutants. Nitrogen dioxide and ozone data were provided by seven EMECAM cities (Barcelona, Gijón, Huelva, Madrid, Oviedo, Seville, and Valencia). Mortality indicators included daily total mortality from all causes excluding external causes, daily cardiovascular mortality, and daily respiratory mortality. Individual estimates, obtained from city-specific generalized additive Poisson autoregressive models, were combined by means of fixed effects models and, if significant heterogeneity among local estimates was found, also by random effects models. Significant positive associations were found between daily mortality (all causes and cardiovascular) and NO2, once the rest of air pollutants were taken into account. A 10 μg/m3 increase in the 24-hr average 1-day NO2 level was associated with an increase in the daily number of deaths of 0.43% [95% confidence interval(CI), –0.003–0.86%] for all causes excluding external. In the case of significant relationships, relative risks for cause-specific mortality were nearly twice as much as that for total mortality for all the photochemical pollutants. Ozone was independently related only to cardiovascular daily mortality. No independent statistically significant relationship between photochemical air pollutants and respiratory mortality was found. The results in this study suggest that, given the present levels of photochemical pollutants, people living in Spanish cities are exposed to health risks derived from air pollution

Testing the expectations theory of the term structure in threshold models

We test the expectations theory of the term structure of U.S. interest rates in nonlinear systems. These models allow the response of the change in short rates to past values of the spread to depend upon the level of the spread. The nonlinear system is tested against a linear system, and the results of testing the expectations theory in both models are contrasted. We find that the results of tests of the implications of the expectations theory depend on the size and sign of the spread. The long maturity spread predicts future changes of the short rate only when it is high.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.

Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon

This work aims to compare the forecast efficiency of different types of methodologies applied to Brazilian Consumer inflation (IPCA). We will compare forecasting models using disaggregated and aggregated data over twelve months ahead. The disaggregated models were estimated by SARIMA and will have different levels of disaggregation. Aggregated models will be estimated by time series techniques such as SARIMA, state-space structural models and Markov-switching. The forecasting accuracy comparison will be made by the selection model procedure known as Model Confidence Set and by Diebold-Mariano procedure. We were able to find evidence of forecast accuracy gains in models using more disaggregated data

Effects of a probiotic soy product and physical exercise on formation of pre-neoplastic lesions in rat colons in a short-term model of carcinogenic

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Short-term temporal changes in the spatial variability model of CO2 emissions from a Brazilian bare soil

In this work, the spatial variability model of CO2 emissions and soil properties of a Brazilian bare soil were investigated. Carbon dioxide emissions were measured on three different days at contrasted soil temperature and soil moisture conditions, and soil properties were investigated at the same points where emissions were measured. One spatial variability model of soil CO2 emissions was found for each measurement day, and these models are similar to the ones of soil properties studied in an area of 100 x 100 m. (C) 2000 Elsevier B.V. Ltd. All rights reserved.