1000 resultados para método Bayesiano


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Pós-graduação em Matematica Aplicada e Computacional - FCT

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A expansão da obesidade em diversos países do mundo na última década tem resultado no aumento da morbidade e mortalidade por hipertensão arterial e suas complicações. O objetivo deste trabalho é analisar a distribuição espacial da obesidade e hipertensão arterial no estado de São Paulo no período de 2000 a 2010, a partir de registros hospitalares e internação do Sistema de Informações Hospitalares do Sistema Único de Saúde (SIH - SUS). Foram utilizados coeficientes de prevalência das doenças em cada município suavizadas pelo método bayesiano empírico, permitindo uma visualização do padrão espacial dessas morbidades no Estado. Foi explorada a dependência espacial destes padrões verificando a autocorrelação entre os indicadores por meio do cálculo do Índice de Autocorrelação Espacial de Moran. Além disso, estudou-se a correlação positiva (Pearson) entre obesidade e hipertensão. Os dados e os mapas mostraram clusters de 87 municípios onde há maior e menor prevalência de hipertensão e obesidade no espaço com forte autocorrelação entre os municípios vizinhos. O coeficiente correlação de Pearson encontrado para esses municípios foi de 0,404 e sugere associação entre as morbidades. As técnicas de análise espacial mostraram-se úteis para o planejamento de ações de saúde pública.

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INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

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En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

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En esta Tesis Doctoral se emplean y desarrollan Métodos Bayesianos para su aplicación en análisis geotécnicos habituales, con un énfasis particular en (i) la valoración y selección de modelos geotécnicos basados en correlaciones empíricas; en (ii) el desarrollo de predicciones acerca de los resultados esperados en modelos geotécnicos complejos. Se llevan a cabo diferentes aplicaciones a problemas geotécnicos, como es el caso de: (1) En el caso de rocas intactas, se presenta un método Bayesiano para la evaluación de modelos que permiten estimar el módulo de Young a partir de la resistencia a compresión simple (UCS). La metodología desarrollada suministra estimaciones de las incertidumbres de los parámetros y predicciones y es capaz de diferenciar entre las diferentes fuentes de error. Se desarrollan modelos "específicos de roca" para los tipos de roca más comunes y se muestra cómo se pueden "actualizar" esos modelos "iniciales" para incorporar, cuando se encuentra disponible, la nueva información específica del proyecto, reduciendo las incertidumbres del modelo y mejorando sus capacidades predictivas. (2) Para macizos rocosos, se presenta una metodología, fundamentada en un criterio de selección de modelos, que permite determinar el modelo más apropiado, entre un conjunto de candidatos, para estimar el módulo de deformación de un macizo rocoso a partir de un conjunto de datos observados. Una vez que se ha seleccionado el modelo más apropiado, se emplea un método Bayesiano para obtener distribuciones predictivas de los módulos de deformación de macizos rocosos y para actualizarlos con la nueva información específica del proyecto. Este método Bayesiano de actualización puede reducir significativamente la incertidumbre asociada a la predicción, y por lo tanto, afectar las estimaciones que se hagan de la probabilidad de fallo, lo cual es de un interés significativo para los diseños de mecánica de rocas basados en fiabilidad. (3) En las primeras etapas de los diseños de mecánica de rocas, la información acerca de los parámetros geomecánicos y geométricos, las tensiones in-situ o los parámetros de sostenimiento, es, a menudo, escasa o incompleta. Esto plantea dificultades para aplicar las correlaciones empíricas tradicionales que no pueden trabajar con información incompleta para realizar predicciones. Por lo tanto, se propone la utilización de una Red Bayesiana para trabajar con información incompleta y, en particular, se desarrolla un clasificador Naïve Bayes para predecir la probabilidad de ocurrencia de grandes deformaciones (squeezing) en un túnel a partir de cinco parámetros de entrada habitualmente disponibles, al menos parcialmente, en la etapa de diseño. This dissertation employs and develops Bayesian methods to be used in typical geotechnical analyses, with a particular emphasis on (i) the assessment and selection of geotechnical models based on empirical correlations; on (ii) the development of probabilistic predictions of outcomes expected for complex geotechnical models. Examples of application to geotechnical problems are developed, as follows: (1) For intact rocks, we present a Bayesian framework for model assessment to estimate the Young’s moduli based on their UCS. Our approach provides uncertainty estimates of parameters and predictions, and can differentiate among the sources of error. We develop ‘rock-specific’ models for common rock types, and illustrate that such ‘initial’ models can be ‘updated’ to incorporate new project-specific information as it becomes available, reducing model uncertainties and improving their predictive capabilities. (2) For rock masses, we present an approach, based on model selection criteria to select the most appropriate model, among a set of candidate models, to estimate the deformation modulus of a rock mass, given a set of observed data. Once the most appropriate model is selected, a Bayesian framework is employed to develop predictive distributions of the deformation moduli of rock masses, and to update them with new project-specific data. Such Bayesian updating approach can significantly reduce the associated predictive uncertainty, and therefore, affect our computed estimates of probability of failure, which is of significant interest to reliability-based rock engineering design. (3) In the preliminary design stage of rock engineering, the information about geomechanical and geometrical parameters, in situ stress or support parameters is often scarce or incomplete. This poses difficulties in applying traditional empirical correlations that cannot deal with incomplete data to make predictions. Therefore, we propose the use of Bayesian Networks to deal with incomplete data and, in particular, a Naïve Bayes classifier is developed to predict the probability of occurrence of tunnel squeezing based on five input parameters that are commonly available, at least partially, at design stages.

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Neste trabalho propomos o uso de um método Bayesiano para estimar o parâmetro de memória de um processo estocástico com memória longa quando sua função de verossimilhança é intratável ou não está disponível. Esta abordagem fornece uma aproximação para a distribuição a posteriori sobre a memória e outros parâmetros e é baseada numa aplicação simples do método conhecido como computação Bayesiana aproximada (ABC). Alguns estimadores populares para o parâmetro de memória serão revisados e comparados com esta abordagem. O emprego de nossa proposta viabiliza a solução de problemas complexos sob o ponto de vista Bayesiano e, embora aproximativa, possui um desempenho muito satisfatório quando comparada com métodos clássicos.

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Population aging is a global demographic trend. This process is a reality that merits attention and importance in recent years, and cause considerable impact in terms of greater demands on the health sector, social security and special care and attention from families and society as a whole. Thus, in the context of addressing the consequences of demographic transition, population aging is characterized as a major challenge for Brazilian society. Therefore, this study was conducted in two main objectives. In the first article, variables of socioeconomic and demographic contexts were employed to identify multidimensional profiles of elderly residents in the Northeast capitals, from specific indicators from the 2010 Census information Therefore, we used the Grade of Membership Method (GoM), whose design profiles admits that an individual belongs to different degrees of relevance to multiple profiles in order to identify socioeconomic and demographic factors associated with living conditions of the elderly in the Northeastern capitals. The second article examined the possible relationship between mortality from chronic diseases and socio-economic indicators in the elderly population, of the 137 districts in Natal, broken down by ten-year age groups (60 to 69 years, 70-79 years and 80 and over. The microdata from the Mortality Information System (SIM), was used, provided by the Health Secretariat of Christmas, and population information came from the Population Census 2010. The method refers to the Global and Local Index neighborhood logic (LISA) Moran, whose spatial distribution from the choropleth maps allowed us to analyze the mortality of the elderly by neighborhoods, according to socioeconomic and demographic indicators, according to the presence of special significance. In the first article, the results show the identification of three extreme profiles. The Profile 1 which is characterized by median socioeconomic status and contributes 35.5% of elderly residents in the area considered. The profile 2 which brings together seniors with low socioeconomic status characteristics, with a percentage of 24.8% of cases. And the Profile 3 composing elderly with features that reveal better socioeconomic conditions, about 29.7% of the elderly. Overall, the results point to poor living conditions represented by the definition of these profiles, mainly expressed by the results observed in more than half of the northeastern elderly experience a situation of social vulnerability given the large percentage that makes up the Profile 1 and Profile 2, adding 60% of the elderly. In the second article, the results show a higher proportion of elderly concentrated in the neighborhoods of higher socioeconomic status, such as Petrópolis and LagoaSeca. Mortality rates, according to the causes of death and standardized by the empirical Bayesian method were distributed locally as follows: Neoplasms (Reis Santos, New Discovery, New Town, Grass Soft and Ponta Negra); Hypertensive diseases (Blue Lagoon, Potengi, Redinha, Reis Santos, Riverside, Lagoa Nova, Grass Soft, Neópolis and Ponta Negra); Acute Myocardial Infarction (Northeast, Guarapes and grass Soft); Cerebrovascular diseases (Petrópolis and Mother Luiza); Pneumonia (Ribeira, Praia do Meio, New Discovery, Grass Soft and Ponta Negra); Chronic Diseases of the Lower Way Airlines (Igapó, Northeast and Thursdays). The present findings at work may contribute to other studies on the subject and development of specific policies for the elderly.

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Population aging is a global demographic trend. This process is a reality that merits attention and importance in recent years, and cause considerable impact in terms of greater demands on the health sector, social security and special care and attention from families and society as a whole. Thus, in the context of addressing the consequences of demographic transition, population aging is characterized as a major challenge for Brazilian society. Therefore, this study was conducted in two main objectives. In the first article, variables of socioeconomic and demographic contexts were employed to identify multidimensional profiles of elderly residents in the Northeast capitals, from specific indicators from the 2010 Census information Therefore, we used the Grade of Membership Method (GoM), whose design profiles admits that an individual belongs to different degrees of relevance to multiple profiles in order to identify socioeconomic and demographic factors associated with living conditions of the elderly in the Northeastern capitals. The second article examined the possible relationship between mortality from chronic diseases and socio-economic indicators in the elderly population, of the 137 districts in Natal, broken down by ten-year age groups (60 to 69 years, 70-79 years and 80 and over. The microdata from the Mortality Information System (SIM), was used, provided by the Health Secretariat of Christmas, and population information came from the Population Census 2010. The method refers to the Global and Local Index neighborhood logic (LISA) Moran, whose spatial distribution from the choropleth maps allowed us to analyze the mortality of the elderly by neighborhoods, according to socioeconomic and demographic indicators, according to the presence of special significance. In the first article, the results show the identification of three extreme profiles. The Profile 1 which is characterized by median socioeconomic status and contributes 35.5% of elderly residents in the area considered. The profile 2 which brings together seniors with low socioeconomic status characteristics, with a percentage of 24.8% of cases. And the Profile 3 composing elderly with features that reveal better socioeconomic conditions, about 29.7% of the elderly. Overall, the results point to poor living conditions represented by the definition of these profiles, mainly expressed by the results observed in more than half of the northeastern elderly experience a situation of social vulnerability given the large percentage that makes up the Profile 1 and Profile 2, adding 60% of the elderly. In the second article, the results show a higher proportion of elderly concentrated in the neighborhoods of higher socioeconomic status, such as Petrópolis and LagoaSeca. Mortality rates, according to the causes of death and standardized by the empirical Bayesian method were distributed locally as follows: Neoplasms (Reis Santos, New Discovery, New Town, Grass Soft and Ponta Negra); Hypertensive diseases (Blue Lagoon, Potengi, Redinha, Reis Santos, Riverside, Lagoa Nova, Grass Soft, Neópolis and Ponta Negra); Acute Myocardial Infarction (Northeast, Guarapes and grass Soft); Cerebrovascular diseases (Petrópolis and Mother Luiza); Pneumonia (Ribeira, Praia do Meio, New Discovery, Grass Soft and Ponta Negra); Chronic Diseases of the Lower Way Airlines (Igapó, Northeast and Thursdays). The present findings at work may contribute to other studies on the subject and development of specific policies for the elderly.

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One of the greatest challenges of demography, nowadays, is to obtain estimates of mortality, in a consistent manner, mainly in small areas. The lack of this information, hinders public health actions and leads to impairment of quality of classification of deaths, generating concern on the part of demographers and epidemiologists in obtaining reliable statistics of mortality in the country. In this context, the objective of this work is to obtain estimates of deaths adjustment factors for correction of adult mortality, by States, meso-regions and age groups in the northeastern region, in 2010. The proposal is based on two lines of observation: a demographic one and a statistical one, considering also two areas of coverage in the States of the Northeast region, the meso-regions, as larger areas and counties, as small areas. The methodological principle is to use the General Equation and Balancing demographic method or General Growth Balance to correct the observed deaths, in larger areas (meso-regions) of the states, since they are less prone to breakage of methodological assumptions. In the sequence, it will be applied the statistical empirical Bayesian estimator method, considering as sum of deaths in the meso-regions, the death value corrected by the demographic method, and as reference of observation of smaller area, the observed deaths in small areas (counties). As results of this combination, a smoothing effect on the degree of coverage of deaths is obtained, due to the association with the empirical Bayesian Estimator, and the possibility of evaluating the degree of coverage of deaths by age groups at counties, meso-regions and states levels, with the advantage of estimete adjustment factors, according to the desired level of aggregation. The results grouped by State, point to a significant improvement of the degree of coverage of deaths, according to the combination of the methods with values above 80%. Alagoas (0.88), Bahia (0.90), Ceará (0.90), Maranhão (0.84), Paraíba (0.88), Pernambuco (0.93), Piauí (0.85), Rio Grande do Norte (0.89) and Sergipe (0.92). Advances in the control of the registry information in the health system, linked to improvements in socioeconomic conditions and urbanization of the counties, in the last decade, provided a better quality of information registry of deaths in small areas

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Biplot graphics are widely employed in the study of the genotypeenvironment interactions, but they are only a graphical tool without a statistical hypothesis test. The singular values and scores (singular vectors) used in biplots correspond to specific estimates of its parameters, and the use of uncertainty measures may lead to different conclusions from those provided by a simple visual evaluation. The aim of this work is to estimate the genotype-environment interactions, using AMMI analysis, through Bayesian approach. Therefore the credibility intervals can be used for decision-making in different situations of analyses. It allows to verify the consistency of the selection and recommendation of cultivars. Two analyses were performed. The first analysis looked into 10 regular commercial hybrids and all possible 45 hybrids obtained from them. They were assessed in 15 locations. The second analysis evaluated 28 hybrids in 35 different environments, with imbalance data. The ellipses were grouped according to the standard of interaction in the biplot. The AMMI analysis with a Bayesian approach proved to be a complete analysis of stability and adaptability, which provides important information that may help the breeder in their decisions. The regions of credibility, built in the biplots, allow to perform an accurate selection and a precise genotype recommendation, with a level of credibility. Genotypes and environments can be grouped according to the existing interaction pattern, which makes possible to formulate specific recommendations. Moreover the environments can be evaluated, in order to find out which ones contribute similarly to the interaction and those to be discarted. The method makes possible to deal with imbalanced data in a natural way, showing efficiency for multienvironment trials. The prediction takes into account instability and the interaction standard of the observed data, in order to establish a direct comparison between genotypes of both 1st and 2nd seasons.

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Two hundred and six patients with severe head injury (Glasgow Coma Scale of 8 points or less after nonsurgical resuscitation on admission), managed at Intensive Care Unit-Hospital das Clínicas - Universidade Estadual de Campinas were prospectively analysed. All patients were assessed by CT scan and 72 required neurosurgical intervention. All patients were continuously monitored to evaluate intracranial pressure (ICP) levels by a subarachnoid device (11 with subarachnoid metallic bolts and 195 with subarachnoid polyvinyl catheters). The ICP levels were continuously observed in the bedside pressure monitor display and their end-hour values were recorded in a standard chart. The patients were managed according to a standard protocol guided by the ICP levels. There were no intracranial haemorrhagic complications or hematomas due the monitoring method. Sixty six patients were punctured by lateral C1-C2 technique to assess infectious complications and 2 had positive cerebrospinal fluid samples for Acinetobacter sp. The final results measured at hospital discharge showed 75 deaths (36,40%) and 131 (63,60%) survivors. ICP levels had significantly influenced the final results (p<0,001). The subarachnoid method to continuously assess the ICP levels was considered aplicable, safe, simple, low cost and useful to advise the management of the patients. The ICP record methodology was practical and useful. Despite the current technical advances the subarachnoid method was considered viable to assess the ICP levels in severe head injury.

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The purpose of this study is to introduce a method to evaluate visual functions in infants in the first three months of life. An adaptation of the Guide for the Assessment of Visual Ability in Infants (Gagliardo, 1997) was used. The instrument was a ring with string. It was implemented a pilot study with 33 infants, selected according to the following criteria: neonates well enough to go home within two days of birth; 1 to 3 months of chronological age; monthly evaluation with no absence; subjects living in Campinas/SP metropolitan area. In the first month we observed: visual fixation (93,9%); eye contact (90,9%); horizontal tracking (72,7%); inspects surroundings (97,0%). In the third month, we observed: inspects own hands (42,4%) and increased movements of arms (36,4%). This method allowed the evaluation of visual functions in infants, according to the chronological age. Alterations in this function will facilitate immediate referral to medical services for diagnoses.

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The ONIOM method was used to calculate the proton affinities (PA) of n-alkylamines (CnH2n+1NH2, n = 3 to 6, 8, 10, 12, 14, 16 and 18). The calculations were carried out at several levels (HF, MP2, B3LYP, QCISD(T), ...) using Pople basis sets and at the QCISD(T) level using basis sets developed by the generator coordinate method (GCM) and adapted to effective core potentials. PAs were also obtained through the GCM and high level methods, like ONIOM[QCISD(T)/6-31+G(2df,p):MP2/6-31G+G(d,p))//ONIOM[MP2/6-31+G(d,p):HF/6-31G]. The average error using the GCM, with respect to experimental data, was 3.4 kJ mol-1.

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In this work a simple and sensitive procedure to extract organic mercury from water and sediment samples, using methylene chloride in acidic media followed by CVAFS quantification has been developed. The method was evaluated for possible interferents, using different inorganic mercury species and humic acid, no effects being observed. The detection limit for organic mercury was 160 pg and 396 pg for water and sediment samples respectively. The accuracy of the method was evaluated using a certified reference material of methylmercury (BCR-580, estuarine sediment). Recovery tests using methylmercury as surrogate spiked with 1.0 up to 30.0 ng L-1 ranged from 90 up to 109% for water samples, whereas for sediments, recoveries ranged from 57 up to 97%.

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Alginate microparticles were prepared by an emulsion method aiming oral controlled release of antigens to fish. The effects of emulsification temperature and impeller type on particle morphology, average diameter, and size distribution were evaluated. Microparticles contaning formalin-killed Flavobacterium columnare cells (a model antigen) were prepared and characterized regarding bacterial release and particle stability when exposed to Nile tilapia (Oreochromis niloticus) typical gastrointestinal conditions. This methodology allowed the production of microparticles containing up to 14.3 g/L of bacterin, stable at a pH range from 2.0 to 9.0 for 12 h and smaller than 35 μm.