963 resultados para indicators’ improvement method
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Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular - Ramo de especialização: Intervenção Cardiovascular
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A forte competitividade dos mercados a nível nacional e internacional tem levado muitas empresas a estudar métodos e técnicas de incremento à eliminação dos desperdícios, à redução de custos e tempos, ao aumento da qualidade e da flexibilidade, tendo a filosofia lean um papel crucial na prossecução destes objectivos. Desde os seus primórdios, a avaliação da implementação da filosofia lean no universo das empresas é uma questão de investigação na área de conhecimento da gestão industrial. Embora a nível individual as diferentes empresas possam quantificar e avaliar os resultados da aplicação do lean, a grande dificuldade surge quando se pretende obter uma comparação por sector ou tipo de actividade económica. Existem países onde a prática do lean tem sido prioritária e as empresas ocupam a vanguarda nesta área de conhecimento. No entanto, em Portugal, existe uma clara dificuldade em se determinar até que ponto o tecido empresarial português assimilou esta filosofia e que resultados têm obtido com a prática do lean. Este trabalho apresenta um estudo realizado a partir de um inquérito, obtido através de um questionário on-line, às empresas que operam em Portugal de forma a estudar e analisar o estado actual do lean em Portugal e antever tendências futuras numa perspectiva de evolução da aplicação desta metodologia de gestão de processos produtivos. Em resultado deste estudo foi possível identificar quais são os grandes obstáculos à introdução do lean, áreas em que se observou sucesso ou menor impacto e quais as ferramentas e técnicas mais usadas por sector. Como resultado deste estudo é convicção do autor que foi possível obter uma fotografia abrangente do actual estado de implementação do lean e desta forma caracterizar as áreas que seguem na vanguarda da implementação do lean, e as áreas que ainda apresentam um desenvolvimento incipiente. Desta forma parece ao autor que o presente estudo apresenta grande utilidade para o mundo académico bem como para o tecido empresarial português.
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Background: In Portugal, the routine clinical practice of speech and language therapists (SLTs) in treating children with all types of speech sound disorder (SSD) continues to be articulation therapy (AT). There is limited use of phonological therapy (PT) or phonological awareness training in Portugal. Additionally, at an international level there is a focus on collecting information on and differentiating between the effectiveness of PT and AT for children with different types of phonologically based SSD, as well as on the role of phonological awareness in remediating SSD. It is important to collect more evidence for the most effective and efficient type of intervention approach for different SSDs and for these data to be collected from diverse linguistic and cultural perspectives. Aims: To evaluate the effectiveness of a PT and AT approach for treatment of 14 Portuguese children, aged 4.0–6.7 years, with a phonologically based SSD. Methods & Procedures: The children were randomly assigned to one of the two treatment approaches (seven children in each group). All children were treated by the same SLT, blind to the aims of the study, over three blocks of a total of 25 weekly sessions of intervention. Outcome measures of phonological ability (percentage of consonants correct (PCC), percentage occurrence of different phonological processes and phonetic inventory) were taken before and after intervention. A qualitative assessment of intervention effectiveness from the perspective of the parents of participants was included. Outcomes & Results: Both treatments were effective in improving the participants’ speech, with the children receiving PT showing a more significant improvement in PCC score than those receiving the AT. Children in the PT group also showed greater generalization to untreated words than those receiving AT. Parents reported both intervention approaches to be as effective in improving their children’s speech. Conclusions & Implications: The PT (combination of expressive phonological tasks, phonological awareness, listening and discrimination activities) proved to be an effective integrated method of improving phonological SSD in children. These findings provide some evidence for Portuguese SLTs to employ PT with children with phonologically based SSD
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Paracetamol is among the most worldwide consumed pharmaceuticals. Although its occurrence in the environment is well documented, data about the presence of its metabolites and transformation products is very scarce. The present work describes the development of an analytical method for the simultaneous determination of paracetamol, its principal metabolite (paracetamol-glucuronide) and its main transformation product (p-aminophenol) based on solid phase extraction (SPE) and high performance liquid chromatography coupled to diode array detection (HPLC-DAD). The method was applied to analysis of river waters, showing to be suitable to be used in routine analysis. Different SPE sorbents were compared and the use of two Oasis WAX cartridges in tandem proved to be the most adequate approach for sample clean up and pre-concentration. Under optimized conditions, limits of detection in the range 40–67 ng/L were obtained, as well as mean recoveries between 60 and 110% with relative standard deviations (RSD) below 6%. Finally, the developed SPE-HPLC/DAD method was successfully applied to the analysis of the selected compounds in samples from seven rivers located in the north of Portugal. Nevertheless all the compounds were detected, it was the first time that paracetamol-glucuronide was found in river water at concentrations up to 3.57 μg/L.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações
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Component joining is typically performed by welding, fastening, or adhesive-bonding. For bonded aerospace applications, adhesives must withstand high-temperatures (200°C or above, depending on the application), which implies their mechanical characterization under identical conditions. The extended finite element method (XFEM) is an enhancement of the finite element method (FEM) that can be used for the strength prediction of bonded structures. This work proposes and validates damage laws for a thin layer of an epoxy adhesive at room temperature (RT), 100, 150, and 200°C using the XFEM. The fracture toughness (G Ic ) and maximum load ( ); in pure tensile loading were defined by testing double-cantilever beam (DCB) and bulk tensile specimens, respectively, which permitted building the damage laws for each temperature. The bulk test results revealed that decreased gradually with the temperature. On the other hand, the value of G Ic of the adhesive, extracted from the DCB data, was shown to be relatively insensitive to temperature up to the glass transition temperature (T g ), while above T g (at 200°C) a great reduction took place. The output of the DCB numerical simulations for the various temperatures showed a good agreement with the experimental results, which validated the obtained data for strength prediction of bonded joints in tension. By the obtained results, the XFEM proved to be an alternative for the accurate strength prediction of bonded structures.
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A cunicultura é uma atividade pecuária em crescente desenvolvimento e isso traduz-se em novos desafios. Durante muitos anos a criação de coelhos recorreu em demasia ao uso de antimicrobianos com o objetivo de tratar e prevenir o aparecimento de diversas doenças. Paralelamente, estes compostos foram também usados como “promotores de crescimento”, visando essencialmente uma melhoria da eficiência digestiva. Porém, o uso indiscriminado destas substâncias levantou questões de saúde pública, como a emergência de estirpes bacterianas multirresistentes e a inerente disseminação de genes de resistência, possivelmente transferíveis ao Homem através da cadeia alimentar. No presente, existe uma enorme pressão para a adoção de estratégias que possibilitem uma redução massiva na quantidade de antimicrobianos administrados a espécies pecuárias. Este trabalho visou contribuir para o estudo de uma alternativa ao uso de antimicrobianos - os probióticos – enquanto suplementos alimentares constituídos por microrganismos vivos capazes de equilibrar a microbiota intestinal do hospedeiro. Para tal, foram constituídos dois grupos de coelhos com base na alimentação: i) grupo antibiótico, com acesso a um alimento composto suplementado com antibióticos e ii) o grupo probiótico alimentado com a mesma dieta, mas sem antibióticos e inoculado com um probiótico constituído por Escherichia coli e Enterococcus spp.. Ao longo de 22 dias de estudo foram monitorizados alguns indicadores produtivos e efetuadas recolhas periódicas de fezes para estudo microbiológico. A análise dos resultados zootécnicos permitiram verificar que o uso de probióticos em detrimento de antibióticos parece promover o crescimento de coelhos, tornando-se um método mais rentável na produção cunícula. Através de genotipagem por ERIC-PCR e PFGE, pretendeu-se verificar se as estirpes estranhas ao trato gastrointestinal dos coelhos seriam capazes de coloniza-lo, permanecendo ao longo do tempo de estudo. O facto de as estirpes inoculadas no probiótico terem sido encontradas ao longo dos dias de estudo nos coelhos aos quais foram administradas, sugere que os efeitos observados na performance zootécnica estejam relacionados com as estirpes administradas no probiótico, pelo que este poderá ser um sistema viável na substituição de antibióticos na alimentação de coelhos de produção.
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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Especial, domínio Cognição e Multideficiência
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OBJECTIVE: To analyze the strengths and limitations of the Family Health Strategy from the perspective of health care professionals and the community. METHODS: Between June-August 2009, in the city of Vespasiano, Minas Gerais State, Southeastern Brazil, a questionnaire was used to evaluate the Family Health Strategy (ESF) with 77 healthcare professionals and 293 caregivers of children under five. Health care professional training, community access to health care, communication with patients and delivery of health education and pediatric care were the main points of interest in the evaluation. Logistic regression analysis was used to obtain odds ratios and 95% confidence intervals as well as to assess the statistical significance of the variables studied. RESULTS: The majority of health care professionals reported their program training was insufficient in quantity, content and method of delivery. Caregivers and professionals identified similar weaknesses (services not accessible to the community, lack of healthcare professionals, poor training for professionals) and strengths (community health worker-patient communications, provision of educational information, and pediatric care). Recommendations for improvement included: more doctors and specialists, more and better training, and scheduling improvements. Caregiver satisfaction with the ESF was found to be related to perceived benefits such as community health agent household visits (OR 5.8, 95%CI 2.8;12.1), good professional-patient relationships (OR 4.8, 95%CI 2.5;9.3), and family-focused health (OR 4.1, 95%CI 1.6;10.2); and perceived problems such as lack of personnel (OR 0.3, 95%CI 0.2;0.6), difficulty with access (OR 0.2, 95%CI 0.1;0.4), and poor quality of care (OR 0.3, 95%CI 0.1;0.6). Overall, 62% of caregivers reported being generally satisfied with the ESF services. CONCLUSIONS: Identifying the limitations and strengths of the Family Health Strategy from the healthcare professional and caregiver perspective may serve to advance primary community healthcare in Brazil.
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Para obtenção do grau de Doutor pela Universidade de Vigo com menção internacional Departamento de Informática
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In embedded systems, the timing behaviour of the control mechanisms are sometimes of critical importance for the operational safety. These high criticality systems require strict compliance with the offline predicted task execution time. The execution of a task when subject to preemption may vary significantly in comparison to its non-preemptive execution. Hence, when preemptive scheduling is required to operate the workload, preemption delay estimation is of paramount importance. In this paper a preemption delay estimation method for floating non-preemptive scheduling policies is presented. This work builds on [1], extending the model and optimising it considerably. The preemption delay function is subject to a major tightness improvement, considering the WCET analysis context. Moreover more information is provided as well in the form of an extrinsic cache misses function, which enables the method to provide a solution in situations where the non-preemptive regions sizes are small. Finally experimental results from the implementation of the proposed solutions in Heptane are provided for real benchmarks which validate the significance of this work.
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Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.
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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil
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Mestrado em Fiscalidade
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.