As empresas municipais: um contributo para a caraterização da sua posição financeira

Dissertação de Mestrado em Finanças Empresariais

Plataforma de gestão de incidentes

Mestrado em Engenharia Electrotécnica e de Computadores. Área de Especialização de Telecomunicações.

Software de gestão de manutenção como ferramenta de apoio à melhoria da eficiência da gestão de infraestruturas

Este trabalho académico surge no âmbito da realização da dissertação do Mestrado em Engenharia e Gestão Industrial. Tem como objetivo a melhoria da gestão do Departamento de Infraestruturas, numa empresa de produção de motores elétricos para a indústria automóvel, através da análise, implementação e melhoria de um software de gestão de manutenção, de forma a aumentar a eficiência do Departamento. Este estudo foi desenvolvido durante um estágio curricular na empresa Globe Motors Portugal Lda, localizada em Vila do Conde. Para sua sustentação, foi efetuada uma análise funcional, suportada por um Software de gestão de manutenção, de forma a perceber qual a importância que o mesmo tem no funcionamento do Departamento de Infraestruturas. Pretendeu-se compreender quais as vantagens e desvantagens da sua utilização. Posteriormente, implementou-se uma nova versão deste software, analisando-se os pontos fortes e as oportunidades de melhoria, de forma a tornar o Departamento de infraestruturas mais eficiente, através da utilização desta renovada ferramenta de trabalho. Como objetivo último, pretendeu-se à melhoria da organização e gestão do Departamento de infraestruturas, contribuindo para um desenvolvimento de toda a empresa, uma vez que comungamos a ideia de que só é possível ser competitivo, num mercado altamente exigente, através de processos eficientes, possibilitando a redução de custos a todos os níveis.

Localização de jogos

Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Tradução e Interpretação Especializadas, sob orientação do Doutor Manuel Moreira da Silva Esta versão não contém as críticas e sugestões dos elementos do júri

Comparative analysis of the ground reaction forces, during the support phase, in a group of pregnant women on their 3rd trimester of pregnancy and in a group of not pregnant women

PURPOSE: To analyze and compare the Ground Reaction Forces (GRF), during the stance phase of walking in pregnant women in the 3rd trimester of pregnancy, and non pregnant women. METHODS: 20 women, 10 pregnant and 10 non pregnant, voluntarily took part in this study. GRF were measured (1000 Hz) using a force platform (BERTEC 4060-15), an amplifier (BERTEC AM 6300) and an analogical-digital converter of 16 Bits (Biopac). RESULTS: The study showed that there were significant differences among the two groups concerning absolute values of time of the stance phase. In what concerns to the normalized values the most significant differences were verified in the maximums values of vertical force (Fz3, Fz1) and in the impulse of the antero-posterior force (Fy2), taxes of growth of the vertical force, and in the period of time for the antero-posterior force (Fy) be null. CONCLUSIONS: It is easier for the pregnant to continue forward movement (push-off phase). O smaller growth rates in what concerns to the maximum of the vertical force (Fz1) for the pregnant, can be associated with a slower speed of gait, as an adaptation strategy to maintain the balance, to compensate the alterations in the position of her center of gravity due to the load increase. The data related to the antero-posterior component of the force (Fy), shows that there is a significant difference between the pregnant woman’s left foot and right foot, which accuses a different functional behavior in each one of the feet, during the propulsion phase (TS).

Multi-dimensional scaling applied to histogram-based DNA analysis

This paper aims to study the relationships between chromosomal DNA sequences of twenty species. We propose a methodology combining DNA-based word frequency histograms, correlation methods, and an MDS technique to visualize structural information underlying chromosomes (CRs) and species. Four statistical measures are tested (Minkowski, Cosine, Pearson product-moment, and Kendall τ rank correlations) to analyze the information content of 421 nuclear CRs from twenty species. The proposed methodology is built on mathematical tools and allows the analysis and visualization of very large amounts of stream data, like DNA sequences, with almost no assumptions other than the predefined DNA “word length.” This methodology is able to produce comprehensible three-dimensional visualizations of CR clustering and related spatial and structural patterns. The results of the four test correlation scenarios show that the high-level information clusterings produced by the MDS tool are qualitatively similar, with small variations due to each correlation method characteristics, and that the clusterings are a consequence of the input data and not method’s artifacts.

The role of functional polymorphisms in immune response genes as biomarkers of BCG Immunotherapy outcome in bladder cancer: Establishment of a predictive profile in a Southern Europe population

OBJECTIVE: To evaluate the predictive value of genetic polymorphisms in the context of BCG immunotherapy outcome and create a predictive profile that may allow discriminating the risk of recurrence. MATERIAL AND METHODS: In a dataset of 204 patients treated with BCG, we evaluate 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY technology. Stepwise multivariate Cox Regression was used for data mining. RESULTS: In agreement with previous studies we observed that gender, age, tumor multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox Regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules (SNPs in TNFA-1031T/C (rs1799964), IL2RA rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, ICAM1 K469E (rs5498), FASL-844T/C (rs763110) and TRAILR1-397T/G (rs79037040) in association with clinicopathological variables. This risk score allows the categorization of patients into risk groups: patients within the Low Risk group have a 90% chance of successful treatment, whereas patients in the High Risk group present 75% chance of recurrence after BCG treatment. CONCLUSION: We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.