A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

Race-to-halt energy saving strategies

Energy consumption is one of the major issues for modern embedded systems. Early, power saving approaches mainly focused on dynamic power dissipation, while neglecting the static (leakage) energy consumption. However, technology improvements resulted in a case where static power dissipation increasingly dominates. Addressing this issue, hardware vendors have equipped modern processors with several sleep states. We propose a set of leakage-aware energy management approaches that reduce the energy consumption of embedded real-time systems while respecting the real-time constraints. Our algorithms are based on the race-to-halt strategy that tends to run the system at top speed with an aim to create long idle intervals, which are used to deploy a sleep state. The effectiveness of our algorithms is illustrated with an extensive set of simulations that show an improvement of up to 8% reduction in energy consumption over existing work at high utilization. The complexity of our algorithms is smaller when compared to state-of-the-art algorithms. We also eliminate assumptions made in the related work that restrict the practical application of the respective algorithms. Moreover, a novel study about the relation between the use of sleep intervals and the number of pre-emptions is also presented utilizing a large set of simulation results, where our algorithms reduce the experienced number of pre-emptions in all cases. Our results show that sleep states in general can save up to 30% of the overall number of pre-emptions when compared to the sleep-agnostic earliest-deadline-first algorithm.

Materials selection for a set of multiple parts considering manufacturing costs and weight reduction with structural isoperformance using direct multisearch optimization

Materials selection is a matter of great importance to engineering design and software tools are valuable to inform decisions in the early stages of product development. However, when a set of alternative materials is available for the different parts a product is made of, the question of what optimal material mix to choose for a group of parts is not trivial. The engineer/designer therefore goes about this in a part-by-part procedure. Optimizing each part per se can lead to a global sub-optimal solution from the product point of view. An optimization procedure to deal with products with multiple parts, each with discrete design variables, and able to determine the optimal solution assuming different objectives is therefore needed. To solve this multiobjective optimization problem, a new routine based on Direct MultiSearch (DMS) algorithm is created. Results from the Pareto front can help the designer to align his/hers materials selection for a complete set of materials with product attribute objectives, depending on the relative importance of each objective.

Lean management: aplicação a uma pequena empresa de construção civil

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil Especialização em Edificações

Unsupervised hyperspectral signal subspace identification

Hyperspectral imaging sensors provide image data containing both spectral and spatial information from the Earth surface. The huge data volumes produced by these sensors put stringent requirements on communications, storage, and processing. This paper presents a method, termed hyperspectral signal subspace identification by minimum error (HySime), that infer the signal subspace and determines its dimensionality without any prior knowledge. The identification of this subspace enables a correct dimensionality reduction yielding gains in algorithm performance and complexity and in data storage. HySime method is unsupervised and fully-automatic, i.e., it does not depend on any tuning parameters. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Otimização da produção de biogás com recurso a redes neuronais artificiais

Numa Estação de Tratamento de Águas Residuais (ETAR), são elevados os custos não só de tratamento das águas residuais como também de manutenção dos equipamentos lá existentes, nesse sentido procura-se utilizar processos capazes de transformar os resíduos em produtos úteis. A Digestão Anaeróbia (DA) é um processo atualmente disponível capaz de contribuir para a redução da poluição ambiental e ao mesmo tempo de valorizar os subprodutos gerados. Durante o processo de DA é produzido um gás, o biogás, que pode ser utilizado como fonte de energia, reduzindo assim a dependência energética da ETAR e a emissão de gases com efeito de estufa para a atmosfera. A otimização do processo de DA das lamas é essencial para o aumento da produção de biogás, mas a complexidade do processo constitui um obstáculo à sua otimização. Neste trabalho, aplicaram-se Redes Neuronais Artificiais (RNA) ao processo de DA de lamas de ETAR. RNA são modelos simplificados inspirados no funcionamento das células neuronais humanas e que adquirem conhecimento através da experiência. Quando a RNA é criada e treinada, produz valores de output aproximadamente corretos para os inputs fornecidos. Foi esse o motivo para recorrer a RNA na otimização da produção de biogás no digestor I da ETAR Norte da SIMRIA, usando o programa NeuralToolsTM da PalisadeTM para desenvolvimento das RNA. Para tal, efetuou-se uma análise e tratamento de dados referentes aos últimos quatro anos de funcionamento do digestor. Os resultados obtidos permitiram concluir que as RNA modeladas apresentam boa capacidade de generalização do processo de DA. Considera-se que este caso de estudo é promissor, fornecendo uma boa base para o desenvolvimento de modelos eventualmente mais gerais de RNA que, aplicado conjuntamente com as características de funcionamento de um digestor e o processo de DA, permitirá otimizar a produção de biogás em ETAR.

Sentido de coerência : ligação materno-fetal e estilo de vida da mulher durante a gravidez

RESUMO - Um dos grandes desafios actuais enfrentados pela Saúde Pública diz respeito ao fardo representado pelas doenças crónicas não transmissíveis enquanto co-responsáveis pela maioria das mortes que ocorrem no mundo, pela significativa e progressiva redução da qualidade de vida e aumento das incapacidades dos indivíduos afectados e por uma fasquia bastante elevada das despesas em saúde. Entretanto, a complexa dinâmica genética, biológica, psicológica, afectiva, sócio-cultural e ambiental que envolve o comportamento humano, tão amplamente relacionado com algumas destas doenças – doenças cardiovasculares, alguns tipos de cancro, obesidade, hipertensão, diabetes e doenças osteo-articulares – impõe o desafio constante da busca de novas e efectivas intervenções em promoção da saúde que influenciem positivamente os estilos de vida dos indivíduos, dos grupos e das comunidades. Sendo o sentido de coerência um traço da personalidade do indivíduo desenvolvido sob a influência directa ou indirecta dos mesmo factores acima referidos, o estabelecimento de uma relação entre este constructo e os comportamentos humanos pode revelar-se promissor para a elaboração de novas intervenções em promoção da saúde. Por sua vez, a gravidez, talvez por influência da ligação materno-fetal, pode representar um ponto de viragem na vida da mulher no que respeita ao sentido de coerência e aos comportamentos de saúde e um bom começo na vida do bebé que irá nascer sob a influência dos mesmos. Com a finalidade de contribuir para a construção de intervenções efectivas em promoção da saúde, através da descoberta de prováveis potencialidades salutogénicas dos constructos referidos – sentido de coerência e ligação materno-fetal –, foi desenvolvido um estudo quantitativo, observacional que teve por objectivos: ampliar o conhecimento sobre as mudanças do sentido de coerência no decorrer da vida, especificamente durante a gravidez; ampliar o conhecimento acerca das relações de alguns factores de natureza sócio-demográfica, psico-afectiva e obstétrica com o sentido de coerência das mulheres grávidas e com a ligação materno-fetal; e identificar possíveis relações entre o sentido de coerência, a ligação materno-fetal e o estilo de vida das mulheres grávidas, este último representado pelos hábitos alimentares, consumo de cafeína, consumo de álcool, hábitos tabágicos, prática regular de actividade física e ganho de peso durante a gravidez. O presente relatório descreve a concepção e os resultados deste estudo, que envolveu a uma amostra de 61 mulheres grávidas que estavam a ser acompanhadas nos serviços de saúde materna dos Centros de Saúde de Carnaxide extensão Linda-a-Velha e de Oeiras, no Distrito de Lisboa, Portugal, entre os meses de Fevereiro e Julho de 2005. Os resultados demonstram que, para a amostra de 61 mulheres grávidas que responderam ao inquérito por questionário de auto-resposta, foram encontradas associações estatisticamente significativas entre o sentido de coerência e a escolaridade e entre o sentido de coerência e a percepção do próprio estado de saúde. Além disso, foi encontrada alguma evidência das associações entre o sentido de coerência e a faixa etária, estado civil e rendimento mensal familiar e foi observada alguma tendência para que as mulheres grávidas com níveis de sentido de coerência mais elevados consumissem menos álcool do que as mulheres grávidas com níveis de sentido de coerência inferiores. Entretanto, as demais associações testadas não foram confirmadas. Relativamente à ligação materno-fetal, foram encontradas, para a amostra de 41 mulheres grávidas que participaram do segundo momento de colheita de dados do estudo, entre a 20ª e a 24ª semanas de gravidez, associações estatisticamente significativas com a escolaridade e o nível de rendimento familiar das mulheres grávidas, não tendo sido confirmadas as demais associações testadas. Embora não tenham sido estatisticamente evidenciadas as relações entre o sentido de coerência e a ligação materno-fetal e entre estes e os comportamentos de saúde, o carácter preliminar destes resultados, devido à subjectividade do processo de selecção não probabilístico da amostra estudada e à reduzida dimensão desta amostra, e a escassez de estudos descritos na literatura fazem com que seja prudente a realização de estudos de follow-up, com amostras de maiores dimensões, aleatórias e representativas da população, para que sejam estabelecidas quaisquer conclusões acerca destas questões.-----------------------------ABSTRACT - One of the greatest challenges faced by Public Health in nowadays is the burden represented by chronic diseases as co-responsible for the majority of deaths that occurs in the world, for the meaningful and progressive reduction of quality of life and increase of disabilities in affected individuals and for an important part of health expenses. However, the complexity of the genetic, biological, psychological, emotional, social, cultural and environmental dynamics that involves human behaviours related to some of these diseases – cardiovascular diseases, some kind of cancers, obesity, hypertension, diabetes and joint and bone diseases – poses the continuous challenge of searching for new and effective interventions of health promotion that positively influence individuals, groups and community lifestyles. Due to the fact that sense of coherence is an individual personality trace directly or indirectly influenced by the same factors listed above, the discovery of a relationship between this construct and human behaviours might be promising to the creation of new health promotion interventions. On the other hand, pregnancy may represent a turn point to the mother’s life and a good start in the baby’s life in relation to sense of coherence and health behaviours and It might occur because of the influence of maternal-fetal attachment. With the purpose of contributing with the creation of effective health promotion interventions through the discovery of probable salutogenic potentials in the referred constructs – sense of coherence and maternal-fetal attachment – , it was developed a quantitative observational study with the following objectives: to increase knowledge about changes in sense of coherence throughout life, specifically during pregnancy; to increase knowledge about the relationship between sense of coherence and maternal-fetal attachment and some social, demographical, psychological, emotional and obstetric factors of pregnant women; to identify probable relationships between sense of coherence, maternal-fetal attachment and pregnant women’s lifestyles, represented by diet habits, caffeine consumption, alcohol consumption, smoking habits, physical activity habits and weigh gain during pregnancy. This report describes the structure and the findings of this study involving a sample of 61 pregnant women who had been followed by health professionals in the mother health services of Carnaxide (Linda-a-Velha unity) and Oeiras Health Centres, in Lisbon, Portugal, between February and July of 2005. The results show that, for the 61 pregnant women who filled the self-reported questionnaire, it was found a statistically significant association between sense of coherence and education level. It was also found some evidence of the associations between sense of coherence and age, marital status and mensal household income and a trend toward pregnant women with higher levels of sense of coherence to drink less alcoholic beverages than pregnant women with lower levels of sense of coherence. However, the others associations tested were not confirmed. Regarding maternal-fetal attachment, it was found, for the sample of 41 women who participated in the second moment of data collection, between the 20th and the 24th week of pregnancy, statistically significant associations with education level and mensal household income. The others associations tested were not confirmed. Although the associations between sense of coherence and maternal-fetal attachment and between these constructs and health behaviours were not confirmed, all findings presented here are considered preliminary because of small dimension of sample and non-probabilistic criteria used for sample selection. What’s more, there are almost no studies described in the literature which could confirm or contradict these findings. Therefore, it is better to be careful and develop follow-up studies, with bigger and representative of population samples, before draw any conclusions about these theme.

COMPARISON OF A COMMERCIAL ENZYME IMMUNOASSAY WITH PLAQUE REDUCTION NEUTRALIZATION FOR MATERNAL AND INFANT MEASLES ANTIBODY MEASUREMENT

The most practicable assay for measurement of measles IgG (mIgG) in large numbers of sera is an enzyme immunoassay (EIA). To assess how EIA results would agree with those by the gold standard method of plaque reduction neutralization (PRN) we compared the results from the two methods in 43 pairs of maternal and umbilical cord sera, and sera from the corresponding infants when aged 11 - 14 months. In maternal-cord sera, the differences between mean antibody levels by EIA or PRN were not statistically significant, though in individual sera, differences could be large. However, agreement was less good for infants sera, in which levels of mIgG were very low. The conclusions of a study of transplacental transport of mIgG would not be affected by the use of either technique. When studying waning immunity in infants, PRN should be the method of choice, while results from studies using EIA should be interpreted with caution.

Is There Sufficient Training of Health Care Staff on Noise Reduction in Neonatal Intensive Care Units? a Pilot Study From NeoNoise Project

Evidence indicates that exposure to high levels of noise adversely affects human health, and these effects are dependent upon various factors. In hospitals, there are many sources of noise, and high levels exert an impact on patients and staff, increasing both recovery time and stress, respectively. The goal of this pilot study was to develop, implement and evaluate the effectiveness of a training program (TP) on noise reduction in a Neonatal Intensive Care Units (NICU) by comparing the noise levels before and after the implementation of the program. A total of 79 health professionals participated in the study. The measurements of sound pressure levels took into account the layout of the unit and location of the main sources of noise. General results indicated that LAeq levels before implementation of the training program were often excessive, ranging from 48.7 ± 2.94 dBA to 71.7 ± 4.74 dBA, exceeding international guidelines. Similarly following implementation of the training program noise levels remained unchanged (54.5 ± 0.49 dBA to 63.9 ± 4.37 dBA), despite a decrease in some locations. There was no significant difference before and after the implementation of TP. However a significant difference was found for Lp, Cpeak, before and after training staff, suggesting greater care by healthcare professionals performing their tasks. Even recognizing that a TP is quite important to change behaviors, this needs to be considered in a broader context to effectively control noise in the NICU.

Characterization of Nitric Oxide Reductase (NOR) from pseudomonas nautica, a study on biologic nitric oxide reduction

Dissertation submitted to obtain the phD degree in Biochemistry, specialty in Physical- Biochemistry, by the Faculdade de Ciências e Tecnologia from the Universidade Nova de Lisboa

Proposta de aplicação do sistema de custeio baseado em atividades numa empresa de prestação de serviços aduaneiros

Trabalho de Projeto apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação de Amélia Cristina Ferreira da Silva

A Random Access Protocol incorporating Multi-Packet Reception, Retransmission Diversity and Successive Interference Cancellation

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

RuSe Electrocatalysts and Single Wall Carbon Nanohorns Supports for the Oxygen Reduction Reaction

Selenium modified ruthenium electrocatalysts supported on carbon black were synthesized using NaBH4 reduction of the metal precursor. Prepared Ru/C electrocatalysts showed high dispersion and very small averaged particle size. These Ru/C electrocatalysts were subsequently modified with Se following two procedures: (a) preformed Ru/carbon catalyst was mixed with SeO2 in xylene and reduced in H2 and (b) Ru metal precursor was mixed with SeO2 followed by reduction with NaBH4. The XRD patterns indicate that a pyrite-type structure was obtained at higher annealing temperatures, regardless of the Ru:Se molar ratio used in the preparation step. A pyrite-type structure also emerged in samples that were not calcined; however, in this case, the pyrite-type structure was only prominent for samples with higher Ru:Se ratios. The characterization of the RuSe/C electrocatalysts suggested that the Se in noncalcined samples was present mainly as an amorphous skin. Preliminary study of activity toward oxygen reduction reaction (ORR) using electrocatalysts with a Ru:Se ratio of 1:0.7 indicated that annealing after modification with Se had a detrimental effect on their activity. This result could be related to the increased particle size of crystalline RuSe2 in heat-treated samples. Higher activity of not annealed RuSe/C catalysts could also be a result of the structure containing amorphous Se skin on the Ru crystal. The electrode obtained using not calcined RuSe showed a very promising performance with a slightly lower activity and higher overpotential in comparison with a commercial Pt/C electrode. Single wall carbon nanohorns (SWNH) were considered for application as ORR electrocatalysts' supports. The characterization of SWNH was carried out regarding their tolerance toward strong catalyzed corrosion conditions. Tests indicated that SWNH have a three times higher electrochemical surface area (ESA) loss than carbon black or Pt commercial electrodes.

Seroconvertion to hepatitis B vaccine after weight reduction in obese non-responder

Decreased responses to hepatitis B vaccine have been associated with some host conditions including obesity. Susceptible non-responders to a primary three-dose vaccine series should be revaccinated. Those who maintain a non-responder condition after revaccination with three vaccine doses are unlikely to develop protection using more doses. This is a description of an obese woman who received six doses of hepatitis B vaccine and persisted as a non-responder. She was submitted to a vertical banded gastroplasty Roux-en-Y gastric bypass Capellas's technique. After weight reduction, she received three additional doses of vaccine and seroconverted. Further studies should help clarify the need to evaluate antibody levels and eventually revaccinate the increasing population of individuals who undergo weight reduction.