Chagas' disease: an algorithm for donor screening and positive donor counseling

Classical serological screening assays for Chagas' disease are time consuming and subjective. The objective of the present work is to evaluate the enzyme immuno-assay (ELISA) methodology and to propose an algorithm for blood banks to be applied to Chagas' disease. Seven thousand, nine hundred and ninety nine blood donor samples were screened by both reverse passive hemagglutination (RPHA) and indirect immunofluorescence assay (IFA). Samples reactive on RPHA and/or IFA were submitted to supplementary RPHA, IFA and complement fixation (CFA) tests. This strategy allowed us to create a panel of 60 samples to evaluate the ELISA methodology from 3 different manufacturers. The sensitivity of the screening by IFA and the 3 different ELISA's was 100%. The specificity was better on ELISA methodology. For Chagas disease, ELISA seems to be the best test for blood donor screening, because it showed high sensitivity and specificity, it is not subjective and can be automated. Therefore, it was possible to propose an algorithm to screen samples and confirm donor results at the blood bank.

Life cycle and reproductive patterns of Triatoma rubrovaria (Blanchard, 1843) (Hemiptera: Reduviidae) under constant and fluctuating conditions of temperature and humidity

The aim of this study was to evaluate the temperature and relative humidity influence in the life cycle, mortality and fecundity patterns of Triatoma rubrovaria. Four cohorts with 60 recently laid eggs each were conformed. The cohorts were divided into two groups. In the controlled conditions group insects were maintained in a dark climatic chamber under constant temperature and humidity, whereas triatomines of the ambiental temperature group were maintained at room temperature. Average incubation time was 15.6 days in the controlled conditions group and 19.1 days in the ambiental temperature. In group controlled conditions the time from egg to adult development lasted 10 months while group ambiental temperature took four months longer. Egg eclosion rate was 99.1% and 98.3% in controlled conditions and ambiental temperature, respectively. Total nymphal mortality in controlled conditions was 52.6% whereas in ambiental temperature was 51.8%. Mean number of eggs/female was 817.6 controlled conditions and 837.1 ambiental temperature. Fluctuating temperature and humidity promoted changes in the life cycle duration and in the reproductive performance of this species, although not in the species mortality.

Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

Mechanical characterization of aortas using 2D ultrasound elastography

Rupture of aortic aneurysms (AA) is a major cause of death in the Western world. Currently, clinical decision upon surgical intervention is based on the diameter of the aneurysm. However, this method is not fully adequate. Noninvasive assessment of the elastic properties of the arterial wall can be a better predictor for AA growth and rupture risk. The purpose of this study is to estimate mechanical properties of the aortic wall using in vitro inflation testing and 2D ultrasound (US) elastography, and investigate the performance of the proposed methodology for physiological conditions. Two different inflation experiments were performed on twelve porcine aortas: 1) a static experiment for a large pressure range (0 – 140 mmHg); 2) a dynamic experiment closely mimicking the in vivo hemodynamics at physiological pressures (70 – 130 mmHg). 2D raw radiofrequency (RF) US datasets were acquired for one longitudinal and two cross-sectional imaging planes, for both experiments. The RF-data were manually segmented and a 2D vessel wall displacement tracking algorithm was applied to obtain the aortic diameter–time behavior. The shear modulus G was estimated assuming a Neo-Hookean material model. In addition, an incremental study based on the static data was performed to: 1) investigate the changes in G for increasing mean arterial pressure (MAP), for a certain pressure difference (30, 40, 50 and 60 mmHg); 2) compare the results with those from the dynamic experiment, for the same pressure range. The resulting shear modulus G was 94 ± 16 kPa for the static experiment, which is in agreement with literature. A linear dependency on MAP was found for G, yet the effect of the pressure difference was negligible. The dynamic data revealed a G of 250 ± 20 kPa. For the same pressure range, the incremental shear modulus (Ginc) was 240 ± 39 kPa, which is in agreement with the former. In general, for all experiments, no significant differences in the values of G were found between different image planes. This study shows that 2D US elastography of aortas during inflation testing is feasible under controlled and physiological circumstances. In future studies, the in vivo, dynamic experiment should be repeated for a range of MAPs and pathological vessels should be examined. Furthermore, the use of more complex material models needs to be considered to describe the non-linear behavior of the vascular tissue.

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

Gd2O3: Eu Nanoparticle-Based Poly(vinylidene fluoride) Composites for Indirect X-ray Detection

Polymer based scintillator composites have been fabricated by combining poly(vinylidene fluoride) (PVDF) and Gd2O3:Eu nanoparticles (50nm). PVDF has been used since it is a flexible and stable binder matrix and highly resistance to thermal and light deterioration. Gd2O3:Eu has been selected as scintillator material due to its wide band gap, high density and suitable visible light yield. The structural, mechanical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. The introduction of Gd2O3:Eu nanoparticles into the PVDF matrix does not influence the morphology of the polymer or the degree of crystallinity. On the other hand, an increase of the Young´s modulus with respect to PVDF matrix is observed for filler contents of 0.1-0.75 wt.%. The introduction of Gd2O3:Eu into the PVDF matrix increases dielectric constant and DC electrical conductivity as well as the visible light yield in the nanocomposite, being this increase dependent upon Gd2O3:Eu content and X-ray input power. In this way, Gd2O3:Eu/PVDF composites shows suitable characteristics to be used as X-ray radiation transducers, in particular for large area applications.

Dielectric relaxation dynamics of high-temperature piezoelectric polyimide copolymers

Polyimide co-polymers have been prepared based on different diamines as co-monomers: a diamine without CN groups and a novel synthesized diamine with two CN groups prepared by polycondensation reaction followed by thermal cyclodehydration. Dielectric spectroscopy measurements were performed and the dielectric complex function, ac conductivity and electric modulus of the co-polymers were investigated as a function of CN group content in the frequency range from 0.1 Hz to 107 Hz at temperatures from 25 to 260 °C. For all samples and temperatures above 150ºC, the dielectric constant increases with increasing temperature due to increaseing conductivity. The α-relaxation is just detected for the sample without CN groups, being this relaxation overlapped by the electrical conductivity contributions in the remaining samples. For the copolymer samples and the polymer with CN groups an important Maxwell-Wagner-Sillars contribution is detected. The mechanisms responsible for the dielectric relaxation, conduction process and electric modulus response have been discussed as a function of the CN groups content present in the samples.

Structural, mechanical and piezoelectric properties of polycrystalline AlN films sputtered on titanium bottom electrodes

Polycrystalline AlN coatings deposited on Ti-electrodes films were sputtered by using nitrogen both as reactive gas and sputtering gas, in order to obtain high purity coatings with appropriate properties to be further integrated into wear resistance coatings as a piezoelectric monitoring wear sensor. The chemical composition, the structure and the morphology of the films were investigated by X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy and atomic force microscopy techniques. These measurements show the formation of highly (101), (102) and (103) oriented AlN films with good piezoelectric and mechanical properties suitable for applications in electronic devices. Through the use of lower nitrogen flow a densification of the AlN coating occurs in the microstructure, with an improvement of the crystallinity along with the increase of the hardness. Thermal stability of aluminum nitride coatings at high temperature was also examined. It was found an improvement of the piezoelectric properties of the highly (10x) oriented AlN films which became c-axis (002) oriented after annealing. The mechanical behavior after heat treatment shows an important enhancement of the surface hardness and Young’s modulus, which decrease rapidly with the increase of the indentation depth until approach constant values close to the substrate properties after annealing. Thus, thermal annealing energy promotes not only the rearrangement of Al–N network, but also the occurrence of a nitriding process of unsaturated Al atoms which cause a surface hardening of the film.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.

Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

New control algorithm for single-phase series active power filter

This paper presents a single-phase Series Active Power Filter (Series APF) for mitigation of the load voltage harmonic content, while maintaining the voltage on the DC side regulated without the support of a voltage source. The proposed series active power filter control algorithm eliminates the additional voltage source to regulate the DC voltage, and with the adopted topology it is not used a coupling transformer to interface the series active power filter with the electrical power grid. The paper describes the control strategy which encapsulates the grid synchronization scheme, the compensation voltage calculation, the damping algorithm and the dead-time compensation. The topology and control strategy of the series active power filter have been evaluated in simulation software and simulations results are presented. Experimental results, obtained with a developed laboratorial prototype, validate the theoretical assumptions, and are within the harmonic spectrum limits imposed by the international recommendations of the IEEE-519 Standard.