37 resultados para ARI endemicity forecasting
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
A thermodynamic approach to predict bulk glass-forming compositions in binary metallic systems was recently proposed. In this approach. the parameter gamma* = Delta H-amor/(Delta H-inter - Delta H-amor) indicates the glass-forming ability (GFA) from the standpoint of the driving force to form different competing phases, and Delta H-amor and Delta H-inter are the enthalpies for-lass and intermetallic formation, respectively. Good glass-forming compositions should have a large negative enthalpy for glass formation and a very small difference for intermetallic formation, thus making the glassy phase easily reachable even under low cooling rates. The gamma* parameter showed a good correlation with GFA experimental data in the Ni-Nb binary system. In this work, a simple extension of the gamma* parameter is applied in the ternary Al-Ni-Y system. The calculated gamma* isocontours in the ternary diagram are compared with experimental results of glass formation in that system. Despite sonic misfitting, the best glass formers are found quite close to the highest gamma* values, leading to the conclusion that this thermodynamic approach can lie extended to ternary systems, serving as a useful tool for the development of new glass-forming compositions. Finally the thermodynamic approach is compared with the topological instability criteria used to predict the thermal behavior of glassy Al alloys. (C) 2007 Elsevier B. V. All rights reserved.
Resumo:
In this paper, a comparative analysis of the long-term electric power forecasting methodologies used in some South American countries, is presented. The purpose of this study is to compare and observe if such methodologies have some similarities, and also examine the behavior of the results when they are applied to the Brazilian electric market. The abovementioned power forecasts were performed regarding the main four consumption classes (residential, industrial, commercial and rural) which are responsible for approximately 90% of the national consumption. The tool used in this analysis was the SAS (c) program. The outcome of this study allowed identifying various methodological similarities, mainly those related to the econometric variables used by these methods. This fact strongly conditioned the comparative results obtained.
Resumo:
There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.
Resumo:
This article analysed scenarios for Brazilian consumption of ethanol for the period 2006 to 2012. The results show that if the country`s GDP sustains a 4.6% a year growth, domestic consumption of fuel ethanol could increase to 25.16 billion liters in this period, which is a volume relatively close to the forecasted gasoline consumption of 31 billion liters. At a lower GDP growth of 1.22% a year, gasoline consumption would be reduced and domestic ethanol consumption in Brazil would be no higher than 18.32 billion liters. Contrary to the current situation, forecasts indicated that hydrated ethanol consumption could become much higher than anhydrous consumption in Brazil. The former is being consumed in cars moved exclusively by ethanol and flex-fuel cars, successfully introduced in the country at 2003. Flex cars allow Brazilian consumers to choose between gasoline and hydrated ethanol and immediately switch to whichever fuel presents the most favourable relative price.
Resumo:
The aim of this study was to understand the current epidemiology of rickettsial diseases in two rickettsial-endemic regions in Brazil. In the municipalities of Pingo D`Agua and Santa Cruz do Escalvado, among serum samples obtained from horses and dogs, reactivity by immunofluorescent assay against spotted fever group rickettsiae was verified. In some serum samples from opossums (Didelphis aurita) captured in Santa Cruz do Escalvado, serologic response against rickettsiae was also verified. Polymerase chain reaction identified rickettsiae only in ticks and fleas obtained in Santa Cruz do Escalvado. Rickettsiae in samples had 100% sequence homology with Rickettsia fells. These results highlight the importance of marsupials in maintenance of the sylvatic cycle of rickettsial disease and potential integration with the domestic cycle. Our data also support the importance of horses and dogs as sentinels in monitoring circulation of rickettsiae in an urban area.
Resumo:
Every year, autochthonous cases of Plasmodium vivax malaria occur in low-endemicity areas of Vale do Ribeira in the south-eastern part of the Atlantic Forest, state of São Paulo, where Anopheles cruzii and Anopheles bellator are considered the primary vectors. However, other species in the subgenus Nyssorhynchus of Anopheles (e.g., Anopheles marajoara) are abundant and may participate in the dynamics of malarial transmission in that region. The objectives of the present study were to assess the spatial distribution of An. cruzii, An. bellator and An. marajoara and to associate the presence of these species with malaria cases in the municipalities of the Vale do Ribeira. Potential habitat suitability modelling was applied to determine both the spatial distribution of An. cruzii, An. bellator and An. marajoara and to establish the density of each species. Poisson regression was utilized to associate malaria cases with estimated vector densities. As a result, An. cruzii was correlated with the forested slopes of the Serra do Mar, An. bellator with the coastal plain and An. marajoara with the deforested areas. Moreover, both An. marajoara and An. cruzii were positively associated with malaria cases. Considering that An. marajoara was demonstrated to be a primary vector of human Plasmodium in the rural areas of the state of Amapá, more attention should be given to the species in the deforested areas of the Atlantic Forest, where it might be a secondary vector.
Resumo:
A infecção chagásica foi averiguada entre moradores de duas microrregiões geográficas homogêneas do Estado de São Paulo, entre os anos de 1976 a 1980. Campos de Itapetininga, na região de Sorocaba e Encosta Ocidental da Mantiqueira Paulista, na região de Campinas, foram áreas de colonização de Triatoma infestans, no passado, tendo permanecido, na primeira, até o início da década de 70, como reduto da espécie no estado. Atualmente as duas áreas são colonizadas por triatomíneos da espécie Panstrongylus megistus. Perfis de títulos sorológicos caracterizaram ambas as microrregiões como áreas de baixa endemicidade; a interrupção da transmissão foi mais precoce na Encosta, com diferença de 17 anos, em média. Em Campos de Itapetininga, a intensa exposição ao vetor é traduzida pela sororreatividade observada nas idades superiores a 20 anos, correspondentes aos nascidos antes de 1956. Dentre os nascidos entre 1972 e 1977, nessa área, permanece uma baixa positividade, podendo, também, associar-se à transmissão congênita. Na Encosta, a média de idade dos sororreagentes corresponde a nascimentos na década de 1930; os níveis de positividade variaram nos municípios que a compõe segundo o desenvolvimento de capital. Após 1984, com a adoção de novos critérios para o uso da sorologia no Programa de Controle, o encontro de sororreagente não tem sido associado estatisticamente a moradores notificantes de domicílios com presença de triatomíneos.
Resumo:
Prevalence of severe food insecurity was estimated for Brazilian municipalities based on the 2004 National Household Sample Survey (PNAD). First, a logistic regression model was developed and tested with this database. The model was then applied to the 2000 census data, generating severe food insecurity estimates for the Brazilian municipalities, which were subsequently analyzed according to the proportion of families exposed to severe food insecurity. Severe food insecurity was mainly concentrated in the North and Northeast regions, where 46.1% and 65.3% of municipalities showed high prevalence of severe food insecurity, respectively. Most municipalities in the Central West region showed intermediate prevalence of severe food insecurity. There was wide intra-regional variation in severe food insecurity, while the South of Brazil showed the most uniform distribution. In conclusion, Brazil displays wide inter and intra-regional variations in the occurrence of severe food insecurity. Such variations should be identified and analyzed in order to plan appropriate public policies.
Resumo:
This multicentric population-based study in Brazil is the first national effort to estimate the prevalence of hepatitis B (HBV) and risk factors in the capital cities of the Northeast, Central-West, and Federal Districts (2004-2005). Random multistage cluster sampling was used to select persons 13-69 years of age. Markers for HBV were tested by enzyme-linked immunosorbent assay. The HBV genotypes were determined by sequencing hepatitis B surface antigen (HBsAg). Multivariate analyses and simple catalytic model were performed. Overall, 7,881 persons were included; < 70 per cent were not vaccinated. Positivity for HBsAg was less than 1 per cent among non-vaccinated persons and genotypes A, D, and F co-circulated. The incidence of infection increased with age with similar force of infection in all regions. Males and persons having initiated sexual activity were associated with HBV infection in the two settings; healthcare jobs and prior hospitalization were risk factors in the Federal District. Our survey classified these regions as areas with HBV endemicity and highlighted the risk factors differences among the settings
Resumo:
Estimou-se a prevalência de insegurança alimentar grave para os municípios brasileiros, com base na Pesquisa Nacional por Amostra de Domicílios (PNAD) 2004. Inicialmente, foi gerado e testado um modelo por regressão logística multivariada com base nesse banco de dados. O modelo foi aplicado à amostra do Censo Demográfico de 2000, gerando estimativas de prevalências de insegurança alimentar grave para os municípios brasileiros, que foram analisadas de acordo com o percentual de famílias em condição de insegurança alimentar grave. Essa insegurança alimentar está mais concentrada nas regiões Norte e Nordeste, onde 46,1 por cento e 65,3 por cento dos municípios, respectivamente, apresentam altas prevalências de insegurança alimentar grave. Predominam nas regiões Sudeste e Sul municípios com baixa exposição à insegurança alimentar grave. No Centro-oeste a maior parte dos municípios mostra estimativas de insegurança alimentar grave classificadas como médias. Verificou-se grande variação intra-regional na ocorrência da insegurança alimentar, sendo a Região Sul a mais uniforme. Conclui-se que o Brasil apresenta grandes variações inter e intra-regionais na ocorrência da insegurança alimentar, sendo importante realçá-las e analisá-las, no intuito de subsidiar políticas públicas
Resumo:
Abstract The importance of thrombosis and anticoagulation in clinical practice is rooted firmly in several fundamental constructs that can be applied both broadly and globally. Awareness and the appropriate use of anticoagulant therapy remain the keys to prevention and treatment. However, to assure maximal efficacy and safety, the clinician must, according to the available evidence, choose the right drug, at the right dose, for the right patient, under the right indication, and for the right duration of time. The first International Symposium of Thrombosis and Anticoagulation in Internal Medicine was a scientific program developed by clinicians for clinicians. The primary objective of the meeting was to educate, motivate and inspire internists, cardiologists and hematologists by convening national and international visionaries, thought-leaders and dedicated clinician-scientists in Sao Paulo, Brazil. This article is a focused summary of the symposium proceedings
Resumo:
Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition S -> I able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and non-time-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.
Resumo:
Compartmental epidemiological models have been developed since the 1920s and successfully applied to study the propagation of infectious diseases. Besides, due to their structure, in the 1960s an interesting version of these models was developed to clarify some aspects of rumor propagation, considering that spreading an infectious disease or disseminating information is analogous phenomena. Here, in an analogy with the SIR (Susceptible-Infected-Removed) epidemiological model, the ISS (Ignorant-Spreader-Stifler) rumor spreading model is studied. By using concepts from the Dynamical Systems Theory, stability of equilibrium points is established, according to propagation parameters and initial conditions. Some numerical experiments are conducted in order to validate the model.
Resumo:
Introduction. This method is used to forecast the harvest date of banana bunches from as early as the plant shooting stage. It facilitates the harvest of bunches with the same physiological age. The principle, key advantages, time required and expected results are presented. Materials and methods. Details of the four steps of the method ( installation of the temperature sensor, tagging bunches at the flowering stage, temperature sum calculation and estimation of bunch harvest date) are described. Possible problems are discussed. Results. The application of the method allows drawing a curve of the temperature sum accumulated by the bunches which have to be harvested at exactly 900 degree-days physiological age.