Vigilância activa de eventos após vacinação

A vigilância de efeitos indesejáveis após a vacinação é complexa. Existem vários actores de confundimento que podem dar origem a associações espúrias, meramente temporais mas que podem provocar uma percepção do risco alterada e uma consequente desconfiança generalizada acerca do uso das vacinas. Com efeito as vacinas são medicamentos complexos com características únicas cuja vigilância necessita de abordagens metodológicas desenvolvidas para esse propósito. Do exposto se entende que, desde o desenvolvimento da farmacovigilância se tem procurado desenvolver novas metodologias que sejam concomitantes aos Sistemas de Notificação Espontânea que já existem. Neste trabalho propusemo-nos a desenvolver e testar um modelo de vigilância de reacções adversas a vacinas, baseado na auto-declaração pelo utente de eventos ocorridos após a vacinação e testar a capacidade de gerar sinais aplicando cálculos de desproporção a datamining. Para esse efeito foi constituída uma coorte não controlada de utentes vacinados em Centros de Saúde que foram seguidos durante quinze dias. A recolha de eventos adversos a vacinas foi efectuada pelos próprios utentes através de um diário de registo. Os dados recolhidos foram objecto de análise descritiva e análise de data-mining utilizando os cálculos Proportional Reporting Ratio e o Information Component. A metodologia utilizada permitiu gerar um corpo de evidência suficiente para a geração de sinais. Tendo sido gerados quatro sinais. No âmbito do data-mining a utilização do Information Component como método de geração de sinais parece aumentar a eficiência científica ao permitir reduzir o número de ocorrências até detecção de sinal. A informação reportada pelos utentes parece válida como indicador de sinais de reacções adversas não graves, o que permitiu o registo de eventos sem incluir o viés da avaliação da relação causal pelo notificador. Os principais eventos reportados foram eventos adversos locais (62,7%) e febre (31,4%).------------------------------------------ABSTRACT: The monitoring of undesirable effects following vaccination is complex. There are several confounding factors that can lead to merely temporal but spurious associations that can cause a change in the risk perception and a consequent generalized distrust about the safe use of vaccines. Indeed, vaccines are complex drugs with unique characteristics so that its monitoring requires specifically designed methodological approaches. From the above-cited it is understandable that since the development of Pharmacovigilance there has been a drive for the development of new methodologies that are concomitant with Spontaneous Reporting Systems already in place. We proposed to develop and test a new model for vaccine adverse reaction monitoring, based on self-report by users of events following vaccination and to test its capability to generate disproportionality signals applying quantitative methods of signal generation to data-mining. For that effect we set up an uncontrolled cohort of users vaccinated in Healthcare Centers,with a follow-up period of fifteen days. Adverse vaccine events we registered by the users themselves in a paper diary The data was analyzed using descriptive statistics and two quantitative methods of signal generation: Proportional Reporting Ratio and Information Component. themselves in a paper diary The data was analyzed using descriptive statistics and two quantitative methods of signal generation: Proportional Reporting Ratio and Information Component. The methodology we used allowed for the generation of a sufficient body of evidence for signal generation. Four signals were generated. Regarding the data-mining, the use of Information Component as a method for generating disproportionality signals seems to increase scientific efficiency by reducing the number of events needed to signal detection. The information reported by users seems valid as an indicator of non serious adverse vaccine reactions, allowing for the registry of events without the bias of the evaluation of the casual relation by the reporter. The main adverse events reported were injection site reactions (62,7%) and fever (31,4%).

Avaliação do débito máximo da tosse (peak cough flow) na doença pulmonar obstrutiva crónica

Resumo Objectivos: Avaliação da Tosse em doentes com Doença Pulmonar Obstrutiva Crónica (DPOC). Identificar e determinar a relação dos factores preditivos que contribuem para a deterioração da capacidade de tosse nestes indivíduos. Tipo de estudo: Estudo observacional descritivo de natureza transversal. Definição dos casos: Os critérios de diagnóstico da DPOC são o quadro clínico e o Gold standard para diagnóstico da DPOC – a espirometria. População-alvo: Todos os utentes com patologia primária de DPOC diagnosticada que se desloquem ao serviço de função respiratória do Hospital de Viseu, para realizar provas. Método de Amostragem: Foi utilizada uma amostra aleatória constituída por todos os indivíduos, que cumpriram os critérios de inclusão, conscientes e colaborantes, que aceitaram participar neste estudo. Dimensão da amostra: Uma amostra de 55 indivíduos que se deslocaram ao serviço de função respiratória, entre Janeiro e Junho de 2009, para realizar provas de função respiratória. Condução do estudo: Os utentes que aceitaram participar neste estudo foram sujeitos a um questionário de dados clínicos e realizaram 5 testes: índice de massa corporal (IMC), estudo funcional respiratório e gasometria arterial, avaliação da força dos músculos respiratórios (PImax e PEmax) e avaliação do débito máximo da tosse (Peak Cough Flow). Análise estatística: Foram obtidos dados caracterizadores da amostra em estudo, sendo posteriormente correlacionado o valor de débito máximo da tosse (Peak Cough Flow) com os resultados obtidos para as avaliações do IMC, estudo funcional respiratório, PImax e PEmax, gasometria, avaliação da capacidade de Tosse e número de internamentos no último ano por agudização da DPOC. Tendo sido encontrados os valores de correlação entre o Peak Cough Flow e os restantes parâmetros. Resultados: Após análise dos resultados, foram obtidos os valores de Peak Cough Flow para a população com DPOC e verificou-se valores diminuídos em comparação com os valores normais da população, tendo-se verificado maiores valores de PCF em indivíduos do sexo masculino, em comparação aos valores do sexo feminino. Foi analisada a relação entre o PCF e a idade, peso, altura e IMC, não tendo sido encontrada relação, dado que a tosse não apresenta uma variação segundo os valores antropométricos, tal como a relação com os valores espirométricos. Quanto aos parâmetros funcionais respiratórios foram analisadas as relações com o PCF. Verificou-se relações significativas entre o PCF e o FEV1, a FVC, o PEF, apresentando uma relação positiva, onde maiores valores destes parâmetros estão correlacionados com maiores picos de tosse. Quanto a RAW e RV, o PCF apresenta uma relação negativa, onde uma maior resistência da via aérea ou doentes mais hiperinsuflados leva a menores valores de PCF. Por outro lado não foi encontrada relação entre o PCF e a FRC e o TLC. Quanto à força dos músculos respiratórios, verificou-se relação significativa com o PImax e a PEmax em que a fraqueza ao nível dos músculos respiratórios contribuem para um menor valor de PCF. Relativamente aos valores da gasometria arterial, verificou-se relação entre o PCF e a PaO2 de forma positiva, em que doentes hipoxémicos apresentam menores valores de tosse, e a PaCO2, de forma negativa, em que os doentes hipercápnicos apresentam menores valores de PCF tendo sido verificada relação entre o PCF e o pH e sO2. Quanto à relação entre o número de internamentos por agudização da DPOC no último ano e o PCF verificou-se uma relação significativa, onde um menor valor de PCF contribui para uma maior taxa de internamento por agudização da DPOC. Conclusão: Este conjunto de conclusões corrobora a hipótese inicialmente formulada, de que o Peak Cough Flow se encontra diminuído nos indivíduos com Doença Pulmonar Obstrutiva Crónica onde a variação do PCF se encontra directamente relacionada com os parâmetros funcionais respiratórios, com a força dos músculos respiratórios e com os valores de gasometria arterial. ABSTRACT: Aims: Cough evaluation in Chronic Obstructive Pulmonary Disease (COPD) patients. Identify and determine the relation of the predictive factors that contribute to the cough capacity degradation in this type of patients. Type of study: Descriptive observational study of transversal nature. Case definition: The COPD diagnosis criteria are the clinical presentation and the gold standard to the COPD diagnosis- the Spirometry. Target Population: Every patients, with primary pathology of COPD diagnosed, who went to the respiratory function service of Viseu hospital to perform tests. Sampling Method: It was used a random sample constituted by all the, conscious and cooperating individuals, who complied with the inclusion criteria and who accepted to make part of this study. Sample size: A sample of 55 individuals that went to the respiratory function service between January and June 2009 to perform respiratory function tests. Study: The patients who accepted to make part of this study were submitted to a clinical data questionary and performed 5 tests: body mass index (BMI), respiratory functional study, arterial blood gas level, evaluation of respiratory muscles strength (maximal inspiratory pressure (MIP) and maximum expiratory pressure (MEP)), and Peak Cough Flow evaluation. Statistic Analysis: Were obtained characterizing data of the sample in study, and later correlated the value of the Peak Cough Flow with the results from the evaluation of the body mass index (BMI), the respiratory functional study the MIP and MEP, the arterial blood gas level and also with the ability to cough evaluation and the number of hospitalizations in the last year for COPD exacerbations. The values of correlation between the Peak Cough Flow and the other parameters were found. Results: After analyzing the results, were obtained the values of Peak Cough Flow for the population with COPD. There were decreased values compared with the population normal values, having been found higher values of PCF in males compared to female values. It was analyzed the relation between the PCF and the age, weight, height and BMI but no relation was found on account of the fact that the cough does not show a variation according to anthropometric parameters, such as the relation with spirometric values. As for the respiratory functional parameters were analyzed relations with the PCF. There were significant relations between the PCF and FEV1, the FVC, the PEF, presenting a positive relation, where higher values of these parameters are correlated with higher incidence of cough. Concerning the RAW and RV, the PCF has a negative relation, in which a higher airway resistance or in more hyperinflated patients, leads to lower values of PCF. On the other hand no correlation was found between the PCF and the FRC and TLC. Regarding the respiratory muscle strength, there was a significant relation with the MIP and MEP, in which the weakness at the level of respiratory muscles contribute to a lower value of PCF. For values of arterial blood gas level, there was no relation between the PCF and PaO2, in a positive way, in which patients with hypoxemia present lower values of cough, and PaCO2, in a negative way in which hypercapnic patients had lower values of PCF, having being founded a relation between the PCF and the pH and sO2. As for the relation between the number of hospitalizations for COPD exacerbation in the last year and the PCF was found a significant relation, in which a smaller value of PCF contributes to a higher rate of hospitalization for COPD exacerbation. Conclusion: This set of findings supports the hypothesis first formulated that Peak Cough Flow is decreased in individuals with Chronic Obstructive Pulmonary Disease, in which the variation of the PCF is directly related to the respiratory function parameters, the strength of respiratory muscles and the values of arterial blood gases.

Toroid inductor development for a SIC DC-DC converter up to 150kW, based on finite element method

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Otimização de placas compósitas laminadas utilizando redes neuronais e enxames de partículas

Trabalho Final de mestrado para obtenção do grau de Mestre em engenharia Mecância

Multiobjective optimization for node adaptation in the analysis of composite plates using a meshless collocation method

The bending of simply supported composite plates is analyzed using a direct collocation meshless numerical method. In order to optimize node distribution the Direct MultiSearch (DMS) for multi-objective optimization method is applied. In addition, the method optimizes the shape parameter in radial basis functions. The optimization algorithm was able to find good solutions for a large variety of nodes distribution.

Multiobjective optimization of viscoelastic laminated sandwich structures using the Direct MultiSearch method

A multiobjective approach for optimization of passive damping for vibration reduction in sandwich structures is presented in this paper. Constrained optimization is conducted for maximization of modal loss factors and minimization of weight of sandwich beams and plates with elastic laminated constraining layers and a viscoelastic core, with layer thickness and material and laminate layer ply orientation angles as design variables. The problem is solved using the Direct MultiSearch (DMS) solver for derivative-free multiobjective optimization and solutions are compared with alternative ones obtained using genetic algorithms.

Manual de procedimentos ferramenta CRM. Projeto para a empresa Ibero Linhas (Porto) Transportes, Lda.

Nota: 17 valores

Phonological development in relation to native language and literacy: Variations on a theme in six alphabetic orthographies

Phonological development was assessed in six alphabetic orthographies (English, French, Greek, Icelandic, Portuguese and Spanish) at the beginning and end of the first year of reading instruction. The aim was to explore contrasting theoretical views regarding: the question of the availability of phonology at the outset of learning to read (Study 1); the influence of orthographic depth on the pace of phonological development during the transition to literacy (Study 2); and the impact of literacy instruction (Study 3). Results from 242 children did not reveal a consistent sequence of development as performance varied according to task demands and language. Phonics instruction appeared more influential than orthographic depth in the emergence of an early meta-phonological capacity to manipulate phonemes, and preliminary indications were that cross-linguistic variation was associated with speech rhythm more than factors such as syllable complexity. The implications of the outcome for current models of phonological development are discussed.

Local Fractional Variational Iteration Method for Local Fractional Poisson Equations in Two Independent Variables

The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Road drivers performance appraisal using a MCDA method: a case study in the road transport company

Performance evaluation increasingly assumes a more important role in any organizational environment. In the transport area, the drivers are the company’s image and for this reason it is important to develop and increase their performance and commitment to the company goals. This evaluation can be used to motivate driver to improve their performance and to discover training needs. This work aims to create a performance appraisal evaluation model of the drivers based on the multi-criteria decision aid methodology. The MMASSI (Multicriteria Methodology to Support Selection of Information Systems) methodology was adapted by using a template supporting the evaluation according to the freight transportation company in study. The evaluation process involved all drivers (collaborators being evaluated), their supervisors and the company management. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used.

Parallel hyperspectral compressive sensing method on GPU

Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resolution. It is known that the bandwidth connection between the satellite/airborne platform and the ground station is reduced, thus a compression onboard method is desirable to reduce the amount of data to be transmitted. This paper presents a parallel implementation of an compressive sensing method, called parallel hyperspectral coded aperture (P-HYCA), for graphics processing units (GPU) using the compute unified device architecture (CUDA). This method takes into account two main properties of hyperspectral dataset, namely the high correlation existing among the spectral bands and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. Experimental results conducted using synthetic and real hyperspectral datasets on two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN, reveal that the use of GPUs can provide real-time compressive sensing performance. The achieved speedup is up to 20 times when compared with the processing time of HYCA running on one core of the Intel i7-2600 CPU (3.4GHz), with 16 Gbyte memory.

Evaluation of different methods for Plasmodia detection, in well defined population groups in an endemic area of Brazil

In Brazil, more than 500,000 new cases of malaria were notified in 1992. Plasmodium falciparum and P.vivax are the responsible species for 99.3% of the cases. For adequate treatment, precoce diagnosis is necessary. In this work, we present the results of the traditional Plasmodia detection method, thick blood film (TBF), and the results of alternative methods: Immunofluorescence assay (IFA) with polyclonal antibody and Quantitative Buffy Coat method (QBC)® in a well defined population groups. The analysis were done in relation to the presence or absence of malaria clinical symptoms. Also different classes of immunoglobulins anti-P.falciparum were quantified for the global analysis of the results, mainly in the discrepant results. We concluded that alternative methods are more sensitive than TBF and that the association of epidemiological, clinical and laboratory findings is necessary to define the presence of malaria.

Finding a school technological partner: a multicriteria method for school information system producer selection

The choice of an information systems is a critical factor of success in an organization's performance, since, by involving multiple decision-makers, with often conflicting objectives, several alternatives with aggressive marketing, makes it particularly complex by the scope of a consensus. The main objective of this work is to make the analysis and selection of a information system to support the school management, pedagogical and administrative components, using a multicriteria decision aid system – MMASSITI – Multicriteria Method- ology to Support the Selection of Information Systems/Information Technologies – integrates a multicriteria model that seeks to provide a systematic approach in the process of choice of Information Systems, able to produce sustained recommendations concerning the decision scope. Its application to a case study has identi- fied the relevant factors in the selection process of school educational and management information system and get a solution that allows the decision maker’ to compare the quality of the various alternatives.

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.