Estudo e caracterização mecânica por via experimental de modelos de subestruturas eletromecânicas aplicadas ao fabrico de transformadores de grande potência

Dissertação de mestrado integrado em Engenharia Mecânica

Optimization of magnetoelectric composites based on electroactive polymers for energy harvesting and sensor application

Tese de Doutoramento em Engenharia de Materiais.

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Continuous fungal treatment of non-sterile veterinary hospital effluent: pharmaceuticals removal and microbial community assessment

Source point treatment of effluents with a high load of pharmaceutical active compounds (PhACs), such as hospital wastewater, is a matter of discussion among the scientific community. Fungal treatments have been reported to be successful in degrading this type of pollutants and, therefore, the white-rot fungus Trametes versicolor was applied for the removal of PhACs from veterinary hospital wastewater. Sixty-six percent removal was achieved in a non-sterile batch bioreactor inoculated with T. versicolor pellets. On the other hand, the study of microbial communities by means of DGGE and phylogenetic analyses led us to identify some microbial interactions and helped us moving to a continuous process. PhAC removal efficiency achieved in the fungal treatment operated in non-sterile continuous mode was 44 % after adjusting the C/N ratio with respect to the previously calculated one for sterile treatments. Fungal and bacterial communities in the continuous bioreactors were monitored as well.

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Definição de indicadores para estimar custos de projeto e análise paramétrica dos eurocódigos estruturais

Dissertação de mestrado integrado em Engenharia Civil

Optimization of low-cost nutritional supplementation for lignocellulosic ethanol fermentation

[Excerpt] Bioethanol from lignocellulosic materials (LCM), also called second generation bioethanol, is considered a promising alternative to first generation bioethanol. An efficient production process of lignocellulosic bioethanol involves an effective pretreatment of LCM to improve the accessibility of cellulose and thus enhance the enzymatic saccharification. One interesting approach is to use the whole slurry from treatment, since allows economical and industrial benefits: washing steps are avoided, water consumption is lower and the sugars from liquid phase can be used, increasing ethanol concentration [1]. However, during the pretreatment step some compounds (such as furans, phenolic compounds and weak acids) are produced. These compounds have an inhibitory effect on the microorganisms used for hydrolysate fermentation [2]. To overcome this, the use of a robust industrial strain together with agro-industrial by-products as nutritional supplementation was proposed to increase the ethanol productivities and yields. (...)

Continuous-flow precipitation as a route to prepare highly controlled nanohydroxyapatite

[Excerpt] Hydroxyapatite Ca10(PO4)6(OH)2 (HAp) has been widely used for biomedical purposes because of its exceptional biocompatibility, bioactivity and osteoconductivity [1]. As these properties are directly related to HAp particles characteristics (size, morphology and purity), a very good control of the reaction conditions is required to obtain particles with the desired properties. Usually, HAp is synthesized by wet chemical precipitation in stirred tank batch reactors that often lead to inconsistencies in product specifications due to their low mixing efficiency [2]. (...)

Optimization of peptide nucleic acid fluorescence in situ hybridization (PNA-FISH) for the detection of bacteria: the effect of pH, dextran sulfate and probe concentration

Fluorescence in situ hybridization (FISH) is a molecular technique widely used for the detection and characterization of microbial populations. FISH is affected by a wide variety of abiotic and biotic variables and the way they interact with each other. This is translated into a wide variability of FISH procedures found in the literature. The aim of this work is to systematically study the effects of pH, dextran sulfate and probe concentration in the FISH protocol, using a general peptide nucleic acid (PNA) probe for the Eubacteria domain. For this, response surface methodology was used to optimize these 3 PNA-FISH parameters for Gram-negative (Escherichia coli and Pseudomonas fluorescens) and Gram-positive species (Listeria innocua, Staphylococcus epidermidis and Bacillus cereus). The obtained results show that a probe concentration higher than 300 nM is favorable for both groups. Interestingly, a clear distinction between the two groups regarding the optimal pH and dextran sulfate concentration was found: a high pH (approx. 10), combined with lower dextran sulfate concentration (approx. 2% [w/v]) for Gram-negative species and near-neutral pH (approx. 8), together with higher dextran sulfate concentrations (approx. 10% [w/v]) for Gram-positive species. This behavior seems to result from an interplay between pH and dextran sulfate and their ability to influence probe concentration and diffusion towards the rRNA target. This study shows that, for an optimum hybridization protocol, dextran sulfate and pH should be adjusted according to the target bacteria.

Analysis of the effects of the continuous electrode paste band on precordial leads of the electrocardiogram

OBJECTIVE - To determine if the application of a continuous electrode paste band on precordial leads results in alteration of the electrocardiographic tracing as compared with an adequate amount of electrode paste, and if the former condition does not cause uniform morphologies from V1 to V6. METHODS - The amplitude and morphology of the electrocardiographic waves on the precordial leads in electrocardiographic tracings, which were performed with standard (control group) or excessive (continuous band) application of the electrode paste, were compared. RESULTS - None of the 106 patients studied showed uniformity of the QRS morphology from V1 to V6. The eletrocardiographic alterations identified in the tracings performed with a continuous electrode paste band that showed statistical significance in relation to the control group were the following: inversion of the P wave in V1; inversion of the T wave in V1, V2, and V3; appearance of R' waves in V1 and V2; disappearance of S waves in V1; appearance of S waves in V5 and V6; alterations in the amplitude of almost all waves, in all leads. CONCLUSION - Application of a continuous electrode paste band in the precordial leads may cause significant alterations in the electrocardiographic tracing obtained.

Growth hormone for optimization of refractory heart failure treatment

It has been reported that growth hormone may benefit selected patients with congestive heart failure. A 63-year-old man with refractory congestive heart failure waiting for heart transplantation, depending on intravenous drugs (dobutamine) and presenting with progressive worsening of the clinical status and cachexia, despite standard treatment, received growth hormone replacement (8 units per day) for optimization of congestive heart failure management. Increase in both serum growth hormone levels (from 0.3 to 0.8 mg/l) and serum IGF-1 levels (from 130 to 300ng/ml) was noted, in association with clinical status improvement, better optimization of heart failure treatment and discontinuation of dobutamine infusion. Left ventricular ejection fraction (by MUGA) increased from 13 % to 18 % and to 28 % later, in association with reduction of pulmonary pressures and increase in exercise capacity (rise in peak VO2 to 13.4 and to 16.2ml/kg/min later). The patient was "de-listed" for heart transplantation. Growth hormone may benefit selected patients with refractory heart failure.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Oxygen therapy, continuous positive airway pressure, or noninvasive bilevel positive pressure ventilation in the treatment of acute cardiogenic pulmonary edema

OBJECTIVE: To compare the effects of 3 types of noninvasive respiratory support systems in the treatment of acute pulmonary edema: oxygen therapy (O2), continuous positive airway pressure, and bilevel positive pressure ventilation. METHODS: We studied prospectively 26 patients with acute pulmonary edema, who were randomized into 1 of 3 types of respiratory support groups. Age was 69±7 years. Ten patients were treated with oxygen, 9 with continuous positive airway pressure, and 7 with noninvasive bilevel positive pressure ventilation. All patients received medicamentous therapy according to the Advanced Cardiac Life Support protocol. Our primary aim was to assess the need for orotracheal intubation. We also assessed the following: heart and respiration rates, blood pressure, PaO2, PaCO2, and pH at begining, and at 10 and 60 minutes after starting the protocol. RESULTS: At 10 minutes, the patients in the bilevel positive pressure ventilation group had the highest PaO2 and the lowest respiration rates; the patients in the O2 group had the highest PaCO2 and the lowest pH (p<0.05). Four patients in the O2 group, 3 patients in the continuous positive pressure group, and none in the bilevel positive pressure ventilation group were intubated (p<0.05). CONCLUSION: Noninvasive bilevel positive pressure ventilation was effective in the treatment of acute cardiogenic pulmonary edema, accelerated the recovery of vital signs and blood gas data, and avoided intubation.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.