Materials handling in hospitals: An analysis of how the storage and materials handling system can be improved, using the example of Hospital Santa Maria

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Integrated functional genomics for improved manufacture of recombinant enveloped virus

Dissertation presented to obtain the Ph.D degree in Engineering and Technology Sciences-Biotechnology

Improved polymeric medical devices for active substances delivery

The work presented in this thesis was developed in collaboration with a Portuguese company, BeyonDevices, devoted to pharmaceutical packaging, medical technology and device industry. Specifically, the composition impact and surface modification of two polymeric medical devices from the company were studied: inhalers and vaginal applicators. The polyethylene-based vaginal applicator was modified using supercritical fluid technology to acquire self-cleaning properties and prevent the transport of bacteria and yeasts to vaginal flora. For that, in-situ polymerization of 2-substituted oxazolines was performed within the polyethylene matrix using supercritical carbon dioxide. The cationic ring-opening polymerization process was followed by end-capping with N,N-dimethyldodecylamine. Furthermore, for the same propose, the polyethylene matrix was impregnated with lavender oil in supercritical medium. The obtained materials were characterized physical and morphologically and the antimicrobial activity against bacteria and yeasts was accessed. Materials modified using 2-substituted oxazolines showed an effective killing ability for all the tested microorganisms, while the materials modified with lavender oil did not show antimicrobial activity. Only materials modified with oligo(2-ethyl-2-oxazoline) maintain the activity during the long term stability. Furthermore, the cytotoxicity of the materials was tested, confirming their biocompatibilty. Regarding the inhaler, its surface was modified in order to improve powder flowability and consequently, to reduce powder retention in the inhaler´s nozzle. New dry powder inhalers (DPIs), with different needle’s diameters, were evaluated in terms of internal resistance and uniformity of the emitted dose. It was observed that they present a mean resistance of 0.06 cmH2O0.5/(L/min) and the maximum emitted dose obtained was 68.9% for the inhaler with higher needle´s diameter (2 mm). Thus, this inhaler was used as a test and modified by the coating with a commonly-used force control agent, magnesium stearate, dried with supercritical carbon dioxide (scCO2) and the uniformity of delivered dose tests were repeated. The modified inhaler showed an increase in emitted dose from 68.9% to 71.3% for lactose and from 30.0% to 33.7% for Foradil.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.