[pt] A energia eólica tem crescido de forma estável no Brasil nos últimos anos. Para impulsioná-la, é crucial considerar as mudanças climáticas, já que sua geração é altamente influenciada pelo clima. Por isso, é fundamental incorporar variáveis climáticas externas na modelagem das séries eólicas, contribuindo para reduzir as incertezas. Os Modelos Periódicos Autorregressivos com Variáveis Exógenas (PARX) representam uma abordagem viável para cumprir esse propósito, incluindo a variável exógena ENSO. No presente estudo, realizou-se a modelagem das séries de velocidade do vento nos estados do Rio Grande do Norte, Paraíba, Pernambuco, Alagoas, Sergipe, Rio Grande do Sul e Santa Catarina. Nesse sentido, foi considerada a covariância entre esses estados em cada região brasileira para avaliar a correlação espacial entre eles, criando a modelagem PARX-Cov. Além disso, a correlação entre os indicadores do fenômeno ENSO também foi considerada para viabilizar a previsão out-of-sample das variáveis climáticas, essa utilizada para a simulação de cenários de velocidade de vento. Ao comparar a modelagem do PARX e PARX-Cov, com o modelo vigente no setor elétrico brasileiro, observou-se um desempenho superior nos modelos propostos para a simulação de realizações futuras das séries de velocidade do vento. O modelo PARX-Cov com o índice ONI Acumulado é o mais adequado para Pernambuco, Rio Grande do Sul e Santa Catarina. O PARX-Cov com o índice SOI é mais apropriado para o Rio Grande do Norte. Para Alagoas e Sergipe, o PARX com o índice ONI Acumulado é o mais indicado, enquanto o PARX com Niño 4 Acumulado é melhor para a Paraíba. / [en] Wind energy has been steadily growing in Brazil in recent years. To boost its growth, it is crucial to consider climate change, as wind energy generation is highly influenced by the weather. Therefore, it is essential to incorporate external climatic variables into the modeling of wind series, helping to reduce uncertainties. Periodic Autoregressive Models with Exogenous Variables (PARX) represent a viable approach to achieve this, including the ENSO exogenous variable. In the present study, wind speed series were modeled in the states of Rio Grande do Norte, Paraíba, Pernambuco, Alagoas, Sergipe, Rio Grande do Sul, and Santa Catarina. In this context, the covariance between these states in each Brazilian region was considered to assess the spatial correlation among them, creating the PARX-Cov modeling. Furthermore, the correlation between ENSO phenomenon indicators was also considered to enable out-of-sample forecasting of climatic variables, used for simulating wind speed scenarios. When comparing the PARX and PARX-Cov modeling with the current model in the Brazilian electric sector, the proposed models showed superior performance in simulating future wind speed series. The PARX-Cov model with the Accumulated ONI index is most suitable for Pernambuco, Rio Grande do Sul, and Santa Catarina. The PARX-Cov model with the SOI index is more appropriate for Rio Grande do Norte. For Alagoas and Sergipe, the PARX model with the Accumulated ONI index is the most recommended, while the PARX model with Accumulated Niño 4 is better for Paraíba.

Class of 2010 Abstract / OBJECTIVES: The objective of this study is to compare the number of medication refill errors that occur between the Pyxis Medstation 3500 and the Pyxis PARx automated dispensing systems. The accuracy of refilling Pyxis Medstation 3500 automated dispensing machines by pharmacy technicians at the University Medical Center (UMC) was assessed during six days in July 2009. The accuracy was then reassessed over the course of five days in September 2009, one month after implementation of the new Pyxis PARx barcode technology in August. All medications in both the morning and afternoon Pyxis refill reports generated by the UMC inpatient pharmacy were audited during the chosen days. METHODS: The accuracy of refilling Pyxis Medstation 3500 automated dispensing machines by pharmacy technicians at a 350-bed, tertiary-care, teaching hospital with a total of 50 automated dispensing systems was assessed during five days in July 2009. The accuracy was then reassessed over the course of five days in September 2009, one month after implementation of the new Pyxis PARx barcode technology in August. It was assumed that the following types of medication refill errors would be reduced: 1)Wrong drug, Wrong strength 2) Wrong drug, Right strength 3) Right drug, Wrong strength 4) Filling error/Wrong pocket 5) Overfill of pocket 6) Expired medication 7) Right drug, Wrong form. This study was a prospective evaluation of medication refill errors between an older automated dispensing system (Pyxis Medstation) and a newer system (Pyxis PARx). The addition of PARx barcode technology automates the pick and delivery method in order to enhance security during the medication refill process. When the appropriate drawer is opened, the medication must be scanned using the handheld scanner to make sure the correct medication is being refilled. All medications from each Pyxis refill report on the chosen days were audited during pre and post implementation of the new Pyxis PARx barcode technology. Medications to be audited were identified by collecting data from each automated dispensing system listed on the refill reports for the previous day. Audits were performed on the following day (i.e., Monday’s refill reports was audited on Tuesday) by study investigators. Each completed refill was audited for the above medication errors and a brief description of any errors found was noted. RESULTS: A total of 825 refilled items were audited prior to PARx installation (from dates 7/14/09-7/19/09) and a total of five errors were found. Post PARx installation, 959 items were audited (from dates 9/24/09-9/29/09) and a total of two errors were found. Overall, the types of errors encountered were Right Drug/Wrong Form (1/7, 14.3%), Filling Error/Wrong Pocket (2/7, 28.6%), Overfill (1/7, 14.3%), Expired Medication (2/7, 28.6%) and Right Drug/Wrong Strength (1/7, 14.3%). A Chi-square analysis was done to compare pre and post-PARx implementation errors found. The Chi square value was found to be 1.79 with a p-value of 0.18, meaning that there is an 18% probability that any deviation from expected is due to chance. Thus, per our investigation the installation of PARx did not significantly decrease refill error rates. CONCLUSIONS: In Progress

[pt] Apesar do crescimento exponencial da instalação de novas usinas eólicas nos últimos anos, a matriz energética Brasileira é composta, principalmente, por usinas hidrelétricas. Uma das principais características dos sistemas de geração com predominância hidráulica é a forte dependência dos regimes hidrológicos. Atualmente, o setor elétrico brasileiro utiliza a Energia Natural Afluente para gerar cenários hidrológicos a partir de um modelo PAR. Tal modelo é ajustado a partir dos parâmetros estimados do histórico da série temporal, isto é, não considera quaisquer informações exógenas que possam afetar os regimes hidrológicos e, consequentemente, a produção de energia. Estudos recentes identificaram que o uso de variáveis climáticas na modelagem de séries de afluências nas bacias brasileiras pode servir como fator de diminuição de incertezas devido a existência de correlação entre essas variáveis. Também foram identificados benefícios ao decompor as séries hidrológicas em sinal e ruído e utilizar somente o sinal para a modelagem. Neste contexto, o desenvolvimento de modelos híbridos que combinem técnicas de de composição das séries hidrológicas e modelos de séries temporais com variáveis exógenas são objetos de estudo deste trabalho,assim como o desenvolvimento de modelos que associem tais variáveis de formação-linear e periódica. Essas novas abordagens contemplam o uso das técnicas de decomposição SSA e MSSA em combinação com PAR, a aplicação do modelo PARX e o desenvolvimento do modelo PGAM. Como conclusão tem-se que os modelos aplicados se mostraram eficientes para os objetivos propostos e também apresentaram melhor performance, em alguns casos, quando comparados com modelos já publicados na literatura. / [en] Despite the exponential growth of wind farms in recent years, the Brazilian energy matrix is mainly composed of hydroelectric plants.One of the main characteristics of hydroelectric generation systems is the strong dependence on hydrological regimes. Currently, the Brazilian electric sector uses the Natural Energy In flow to generate hydrological scenarios from a PAR model.Such model is adjusted from the estimated parameters of the time series history, that is, it does not consider any exogenous information that could affect the hydrological regimes and, consequently, the energy production. Recent studies indicate that the use of climatic variables in the modeling of inflow series in the Brazilian basins may serve as a factor to reduce uncertainties due to the existence of correlation between these variables. It was also identified benefits by decomposing hydrological series into signal and noise and using only the signal for modeling. In this context, the development of hybrid models that combine techniques of decomposition of the hydrological series and time series models with exogenous variable are study objects of this work, as well as the development of models that associate such variables in a non-linear and periodic way. These new approaches contemplate the use of SSA and MSSA decomposition techniques in combination with PAR, the application of the PARX and the development of the PGAM model. As conclusion, the applied models were efficient for the proposed objectives and also presented better performance, in some cases, when compared with models already published in the literature.

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / A hegemonia da hidroeletricidade na matriz de energia elÃtrica brasileira impÃe cautelosa anÃlise sobre o regime fluvial, tendo em vista o significativo impacto que possÃveis variaÃÃes das vazÃes possam produzir na oferta de energia e consequentemente em toda a economia nacional. Com base nisto, modelos estatÃsticos de previsÃo de afluÃncias tÃm sido uma ferramenta importante no suporte à tomada de decisÃes, no planejamento e na gestÃo de recursos hÃdricos aplicados ao Sistema Interligado Nacional (SIN). Neste sentido, a presente tese propÃe metodologias de previsÃo simultÃneas e elaboraÃÃo de cenÃrios de vazÃes mensais afluentes aos Postos Base (PBâs) do SIN atravÃs de modelos estatÃsticos; visando ao melhor aproveitamento dos dados disponÃveis a partir da inserÃÃo de mÃtodos que mantenham a estrutura espacial da rede hidrogrÃfica nacional. Esta visa tambÃm a analisar o impacto da incorporaÃÃo de informaÃÃes climÃticas na previsÃo de vazÃes mensais. Os modelos propostos de previsÃo de afluÃncia utilizam os dados de vazÃes naturais gerados pelo Operador Nacional do Sistema (ONS) e tÃcnicas estatÃsticas com as de RegressÃo Linear MÃltipla, AnÃlise de Componentes Principais, mÃtodo Stepwise para escolha de variÃveis explanatÃrias; alÃm de modelos do tipo PeriÃdico Autorregressivo (PAR) e periÃdico Autorregressivo com variÃveis exÃgenas (PARX). Os modelos do tipo PAR apresentam os melhores desempenhos, de acordo com o Ãndice de DistÃncia MulticritÃrio, na maioria dos meses e dos PBâs do SIN quando comparados aos modelos PARX. Entre os mÃtodos de correlaÃÃo espacial para os modelos PAR, destacam-se a correlaÃÃo entre os ruÃdos da regressÃo (CRD) e a anÃlise de componentes principais (ACP). NÃo hà um predomÃnio entre esses mÃtodos para todos os meses e PBâs do SIN. Os melhores modelos do tipo PARX sÃo os que fazem uso de Ãndices climÃticos como variÃveis exÃgenas, dentre os quais se destacam os Ãndices AMO (OscilaÃÃo AtlÃntica Multidecadal) e TNI (TransâNINO). Estes apresentam melhor desempenho no perÃodo seco das bacias do norte do Brasil â Amazonas e Araguaia-Tocantins; centro-leste brasileiro â AtlÃntico Leste e na maioria dos rios que formam a Bacia do ParanÃ.

This project seeks to include the historical significance of women in the Foreign Service and subsequently the United States Department of State between 1942 and 1964. Using the life and experience of Margaret Parx Hays, one of fewer than three hundred female foreign service officers before 1960, this study explores the importance of examining women at the "ground level." This narrative examines the life of Hays at several different duty stations and her experience navigating a male-dominant workplace congruent to the political and diplomatic missions of each stations. Hays was stationed in Buenos Aires, Argentina (1942-1945); Bogota, Columbia (1945-1947); Rio de Janeiro, Brazil (1948-1950); Washington D.C., U.S. (1951-1954; 1959-1962); Manila, Philippines (1954-1956); Mexico City, Mexico (1956-1958); and Hong Kong, China (1962-1964). Throughout the deployment at each station, Hays was confronted with major political events in her duty station's history or in the intersection of American foreign and domestic policy. Through the use of Hays's archived collection of personal papers, including letters and newspapers, this thesis presents a more representative story about women and about the Department of State as a larger whole than previous scholarship that has ignored how gender affected diplomatic history.