16 resultados para Work and Production Organization
em Universidade do Minho
Resumo:
NIPE WP 05/2016
Resumo:
Dissertação de mestrado em Engenharia Industrial
Resumo:
Tese de Doutoramento em Ciências (Especialidade de Geologia)
Resumo:
Cell Sheets of hASCs (hASCs-CS) have been previously proposed for wound healing applications(1, 2) and despite the concern for production time reduction, the possibility of having these hASCs-CS off-the-shelf is appealing. The goal of this work was to define a cryopreservation methodology allowing to preserve cells viability and the properties CS matrix. hASCs-CS obtained from three different donors were created in UP-cell thermoresponsive dishes(Nunc, Germany) as previously reported(1,2). Different cryopreservation conditions were considered: i)FBS plus DMSO(5% and10%); ii)0.4M of Trehalose plus DMSO (5% and 10%); iii)cryosolution PLL (Akron Biotech, USA); and iv)vitrification. The cryopreservation effect was first assessed for cellular viability by flow cytometry using 7-AAD, and after dissociating the hASCs-CS with collagenase and trypsin-EDTA 0.25%. The expression (RT-PCR) and deposition (western blot and immunocytochemistry) of collagen type I, laminin and fibronectin, and the organization (TEM) of the extracellular matrix was further assessed before and after hASCs-CS cryopreservation to determine a potential effect of the method over matrix composition and integrity. The obtained results confirmed that cell viability is affected by the cryopreservation methodology, as shown before for different CS(3). Interestingly, the matrix properties were not significantly altered and the typical cell sheetâ s easiness of manipulation for transplantation was not lost.
Resumo:
Dissertação de mestrado integrado em Engenharia e Gestão Industrial
Resumo:
This study aimed to verify the correlation among the nutritional composition of the food consumed in the work environment, the energy expenditure and the nutritional status of workers from different sectors (administration and production) in different industries. The anthropometric data, in addition to the energy expenditure and food intake at lunch were evaluated for 292 workers, all of them included in the Brazilian Worker Food Program (also called PAT). The food consumption was assessed from the direct observation of the meal, for five consecutive days. The obtained data were analyzed by Pearson correlation test and by a Principal Components Analysis. Prevalence of overweight was detected in the studied population, according to the Body Mass Index (BMI). A statistically significant difference was found in terms of the energy expenditure of physical activity and daily energy expenditure in relation to gender and the working sector. The obtained results indicate that there is significant positive correlation (p < 0.01) between the following variables: body weight and BMI (r = 0.84), weight and daily energy expenditure (DEE) (r = 0.52), BMI and DEE (r = 0.27), DEE and energy (r = 0.38), and energy and lipid intake (r = 0.50). These findings seems to indicate the importance of ensuring an adequate balance of nutrients at meals, due to the heterogeneity of workers, in particular in the case of those workers who perform tasks or functions requiring less energy expenditure.
Resumo:
Dissertação de mestrado integrado em Psicologia
Resumo:
Tese de Doutoramento Engenharia Mecânica
Resumo:
Dissertação de mestrado em Engenharia Industrial
Resumo:
Dissertação de mestrado em Engenharia Industrial
Resumo:
The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.
Resumo:
Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas
Resumo:
Dissertação de mestrado em Engenharia Mecatrónica (área de especialização de Tecnologia de Manufatura)
Resumo:
Dissertação de mestrado integrado em Engenharia Mecânica
Resumo:
Dissertação de mestrado em Comunicação, Arte e Cultura