Aortofemoral thromboendarterectomy

PURPOSE: To study whether endarterectomy is feasible in all patients with aortofemoral atherosclerotic obstruction, considering early and late results. METHODS: A clinical, prospective, and descriptive study carried out in a university hospital. Inclusion criteria were atherosclerotic aortofemoral obstructive disease, clinical status compatible with major surgery, and absence of prior restorative procedure. Exclusion criteria were aneurysm, inflammatory arterial disease, and prior restorative procedure found during surgery. Eighty patients entered the protocol, but 9 were excluded (11.2%). Seventy-one patients, mean age of 57.3 years, underwent endarterectomy. Operative indications were intermittent claudication and critical ischemia. A ring-stripper endarterectomy technique was employed in all patients. Results were related to age, gender, symptoms, presence of diabetes mellitus, extension of endarterectomy, and extent of obstructive disease. Chi square or Fisher exact tests were used when appropriate, and the Wilkoxon (Gehan) test was used to compare survival curves. RESULTS: Sixty-eight (100%) endarterectomies were patent at discharge. The mortality rate was 4.2%. The amputation rate (4.3%) was higher in diabetic patients and when there was associated femoropopliteal obstruction. The 5-year survival rate was 83.3%, and late deaths were mostly cardiovascular. Diabetes mellitus, age above 65 years, and associated femoropopliteal obstruction lowered the survival rate. The 5-year patency rate was 87.0%. Critical ischemia and less extensive endarterectomies were associated with a lower patency rate. There were no anastomotic aneurysms or deep infections. CONCLUSIONS: Aortofemoral thromboendarterectomy is feasible in 90% of patients, early mortality rate is low, diabetic patients and those with associated femoropopliteal obstructive disease have a higher mortality rate, amputation rate is low, late deaths are mostly cardiovascular, and late patency rate is high, and even higher in the intermittent claudication group.

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Ontology-based representation and generation of workflows for micro-task human-machine computation

Doctoral Program in Computer Science

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Aplicação do Building Information Modeling na gestão de projetos de construção

Dissertação de mestrado em Construção e Reabilitação Sustentáveis

Secure multiParty computation protocols

Dissertação de Mestrado em Engenharia Informática

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

A relational algebra approach to ETL modeling

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

Fused deposition modeling with polypropylene

This paper addresses the potential of polypropylene (PP) as a candidate for fused deposition modeling (FDM)-based 3D printing technique. The entire filament production chain is evaluated, starting with the PP pellets, filament production by extrusion and test samples printing. This strategy enables a true comparison between parts printed with parts manufactured by compression molding, using the same grade of raw material. Printed samples were mechanically characterized and the influence of filament orientation, layer thickness, infill degree and material was assessed. Regarding the latter, two grades of PP were evaluated: a glass-fiber reinforced and a neat, non-reinforced, one. The results showed the potential of the FDM to compete with conventional techniques, especially for the production of small series of parts/components; also, it was showed that this technique allows the production of parts with adequate mechanical performance and, therefore, does not need to be restricted to the production of mockups and prototypes.

[Editorial] Current challenges in modeling cellular metabolism

The authors would like to thank the financial support from the NovoNordiskFoundation.

Effect of ionic liquid anion type in the performance of solid polymer electrolytes based on Poly(Vinylidene fluoride-trifluoroethylene)

The effect of different anions within the ionic liquid in the characteristics of solid polymer electrolytes (SPEs) based on P(VDF-TrFE) has been investigated. 1-ethyl-3-methylimidazolium acetate, [C2mim][OAc], 1-ethyl-3-methylimidazolium triflate, [C2mim][(CF3SO3)3], 1-ethyl-3-methylimidazolium lactate, [C2mim][Lactate], 1-ethyl-3-methylimidazolium thiocyanate, [C2mim][SNC] and 1-ethyl-3-methylimidazolium hydrogen sulphate [C2mim][HSO4] have been used in SPE prepared by thermally induced phase separation (TIPS). The polymer phase, thermal and electrochemical properties of the SPE have been determined. The thermal and electrical properties of the SPEs strongly depend on the selected IL, as determined by their different interactions with the polymer matrix. The room temperature ionic conductivity increases in the following way for the different anions: [SNC] > [CF3SO3)3] > [HSO4] > [Lactate] > [OAc], which is mainly dependent on the viscosity of the ionic liquid.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate

The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.

Population Dynamics Modeling of Arapaima gigas

Pirarucu (Arapaima gigas) has been of the most important natural fishing resources of the Amazon region. Due to its economic importance, and the necessity to preserve the species hand, field research concerning the habits and behavior of the pirarucu has been increasing for the last 20 years. The aim of this paper is to present a mathematical model for the pirarucu population dynamics considering the species peculiarities, particularly the male parental care over the offspring. The solution of the dynamical systems indicates three possible equilibrium points for the population. The first corresponds to extinction; the third corresponds to a stable population close to the environmental carrying capacity. The second corresponds to an unstable equilibrium located between extinction and full use of the carrying capacity. It is shown that lack of males’ parental care closes the gap between the point corresponding to the unstable equilibrium and the point of stable non-trivial equilibrium. If guarding failure reaches a critical point the two points coincide and the population tends irreversibly to extinction. If some event tends to destabilize the population equilibrium, as for instance inadequate parental care, the model responds in such a way as to restore the trajectory towards the stable equilibrium point avoiding the route to extinction. The parameters introduced to solve the system of equations are partially derived from limited but reliable field data collected at the Mamirauá Sustainable Development Reserve (MSDR) in the Brazilian Amazonian Region.

Numerical modeling and assessment of the thermal environment in an industrial premise of automotive components

Dissertação de mestrado em Engenharia Industrial