Febrifugine derivative antimalarial activity: quantum mechanical predictors

Plasmodium falciparum resistant strain development has encouraged the search for new antimalarial drugs. Febrifugine is a natural substance with high activity against P. falciparum presenting strong emetic property and liver toxicity, which prevent it from being used as a clinical drug. The search for analogues that could have a better clinical performance is a current topic. We aim to investigate the theoretical electronic structure by means of febrifugine derivative family semi-empirical molecular orbital calculations, seeking the electronic indexes that could help the design of new efficient derivatives. The theoretical results show there is a clustering in well-defined ranges of several electronic indexes of the most selective molecules. The model proposed for achieving high selectivity was tested with success.

A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Quantum dots: synthesis, functionalization and bioconjugation for biological applications

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

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.

Electrochemical and quantum chemical investigations of the insecticide fipronil.

This work describes an electrochemical and quantum chemical investigation of the fipronil insecticide. Cyclic voltammetry (CV) and square wave voltammetry (SWV) experiments were performed over a graphite-polyurethane (GPU) composite electrode. The fipronil molecule presents an one?electron irreversible oxidation reaction. Profiting the SWV signal a square wave stripping voltammetry (SWSV) procedure to determine the fipronil molecule in a 0.10 mol L-1 Britton-Robinson buffer solution, pH 8.0 was developed with accumulation potential and time of 0.50 V and 120 s, respectively. The limits of detection and quantification were 0.80 and 2.67 ?g L-1, respectively. Recovery tests were performed in three natural waters samples with values ranging from 99.67 to 101.37%. Quantum chemical studies showed that the nitrogen atom of the pyrazole group is the most probable oxidation site of the fipronil molecule.

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

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.

Solution processed quantum dot photodetectors

To find sustainable solutions for the production of energy, it is necessary to create photovoltaic technologies that make every photon count. To pursue this necessity, in the present work photodetectors of zinc oxide embedded with nano-structured materials, that significantly raise the conversion of solar energy to electric energy, were developed. The novelty of this work is on the development of processing methodologies in which all steps are in solution: quantum dots synthesis, passivation of their surface and sol-gel deposition. The quantum dot solutions with different capping agents were characterized by UVvisible absorption spectroscopy, spectrofluorimetry, dynamic light scattering and transmission electron microscopy. The obtained quantum dots have dimensions between 2 and 3nm. These particles were suspended in zinc acetate solutions and used to produce doped zinc oxide films with embedded quantum dots, whose electric response was tested. The produced nano-structured zinc oxide materials have a superior performance than the bulk, in terms of the produced photo-current. This indicates that an intermediate band material should have been produced that acts as a photovoltaic medium for solar cells. The results are currently being compiled in a scientific article, that is being prepared for possible submission to Energy and Environmental Science or Nanoscale journals.

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.

Effect of polymeric matrix on morphology and photoelectric properties of polymer-quantum dots nanocomposites

Recently, CdTe semiconductor quantum dots (QDs) have attracted great interest due to their unique properties [1]. Their dispersion into polymeric matrices would be very for several optoelectronics applications. Despite its importance, there has been relatively little work done on charge transport in the QD polymeric films [2], which is mainly affected by their structural and morphological properties. In the present work, polymer-quantum dot nanocomposites films based on optically transparent polymers in the visible spectral range and CdTe QDs with controlled particle size and emission wavelength, were prepared via solvent casting. Photoluminescent (PL) measurements indicate different emission intensity of the nanocomposites. A blue shift of the emission peak compared to that of QDs in solution occurred, which is attributed to the QDs environment changes. The morphological and structural properties of the CdTe nanocomposites were evaluated. Since better QDs dispersion was achieved, PMMA seemed to be the most promising matrix. Electrical properties measurements indicate an ohmic behavior.

Design of assemblies based on polymer-coated quantum dots and organic dye

During last years, photophysical properties of complexes of semiconductor quantum dots (QDs) with organic dyes have attracted increasing interest. The development of different assemblies based on QDs and organic dyes allows to increase the range of QDs applications, which include imaging, biological sensing and electronic devices.1 Some studies demonstrate energy transfer between QDs and organic dye in assemblies.2 However, for electronic devices purposes, a polymeric matrix is required to enhance QDs photostability. Thus, in order to attach the QDs to the polymer surface it is necessary to chemically modify the polymer to induce electronic charges and stabilize the QDs in the polymer. The present work aims to investigate the design of assemblies based on polymer-coated QDs and an integrated acceptor organic dye. Polymethylmethacrylate (PMMA) and polycarbonate (PC) were used as polymeric matrices, and nile red as acceptor. Additionally, a PMMA matrix modified with 2-mercaptoethylamine is used to improve the attachment between both the donor (QDs) and the acceptor (nile red), as well as to induce a covalent bond between the modified PMMA and the QDs. An enhancement of the energy transfer efficiency by using the modified PMMA is expected and the resulting assembly can be applied for energy harvesting.

Strain induced edge magnetism at zigzag edge of a graphene quantum dot

We study the temperature dependent magnetic susceptibility of a strained graphene quantum dot by using the determinant quantum Monte Carlo method. Within the Hubbard model on a honeycomb lattice, our unbiased numerical results show that a relative small interaction $U$ may lead to a edge ferromagnetic like behavior in the strained graphene quantum dot, and a possible room temperature transition is suggested. Around half filling, the ferromagnetic fluctuations at the zigzag edge is strengthened both markedly by the on-site Coulomb interaction and the strain, especially in low temperature region. The resultant strongly enhanced ferromagnetic like behavior may be important for the development of many applications.