Development of a simple analytical method for the simultaneousdetermination of paracetamol, paracetamol-glucuronide andp-aminophenol in river water

Paracetamol is among the most worldwide consumed pharmaceuticals. Although its occurrence in the environment is well documented, data about the presence of its metabolites and transformation products is very scarce. The present work describes the development of an analytical method for the simultaneous determination of paracetamol, its principal metabolite (paracetamol-glucuronide) and its main transformation product (p-aminophenol) based on solid phase extraction (SPE) and high performance liquid chromatography coupled to diode array detection (HPLC-DAD). The method was applied to analysis of river waters, showing to be suitable to be used in routine analysis. Different SPE sorbents were compared and the use of two Oasis WAX cartridges in tandem proved to be the most adequate approach for sample clean up and pre-concentration. Under optimized conditions, limits of detection in the range 40–67 ng/L were obtained, as well as mean recoveries between 60 and 110% with relative standard deviations (RSD) below 6%. Finally, the developed SPE-HPLC/DAD method was successfully applied to the analysis of the selected compounds in samples from seven rivers located in the north of Portugal. Nevertheless all the compounds were detected, it was the first time that paracetamol-glucuronide was found in river water at concentrations up to 3.57 μg/L.

Precursors’ order effect on the properties of sulfurized Cu2ZnSnS4 thin films

A dc magnetron sputtering-based method to grow high-quality Cu2ZnSnS4 (CZTS) thin films, to be used as an absorber layer in solar cells, is being developed. This method combines dc sputtering of metallic precursors with sulfurization in S vapour and with post-growth KCN treatment for removal of possible undesired Cu2−xS phases. In this work, we report the results of a study of the effects of changing the precursors’ deposition order on the final CZTS films’ morphological and structural properties. The effect of KCN treatment on the optical properties was also analysed through diffuse reflectance measurements. Morphological, compositional and structural analyses of the various stages of the growth have been performed using stylus profilometry, SEM/EDS analysis, XRD and Raman Spectroscopy. Diffuse reflectance studies have been done in order to estimate the band gap energy of the CZTS films. We tested two different deposition orders for the copper precursor, namely Mo/Zn/Cu/Sn and Mo/Zn/Sn/Cu. The stylus profilometry analysis shows high average surface roughness in the ranges 300–550 nm and 230–250 nm before and after KCN treatment, respectively. All XRD spectra show preferential growth orientation along (1 1 2) at 28.45◦. Raman spectroscopy shows main peaks at 338 cm−1 and 287 cm−1 which are attributed to Cu2ZnSnS4. These measurements also confirm the effectiveness of KCN treatment in removing Cu2−xS phases. From the analysis of the diffuse reflectance measurements the band gap energy for both precursors’ sequences is estimated to be close to 1.43 eV. The KCN-treated films show a better defined absorption edge; however, the band gap values are not significantly affected. Hot point probe measurements confirmed that CZTS had p-type semiconductor behaviour and C–V analysis was used to estimate the majority carrier density giving a value of 3.3 × 1018 cm−3.

Fractional dynamics of genetic algorithms using hexagonal space tessellation

The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.

Tensile behaviour of a structural adhesive at high temperatures by the extended finite element method

Component joining is typically performed by welding, fastening, or adhesive-bonding. For bonded aerospace applications, adhesives must withstand high-temperatures (200°C or above, depending on the application), which implies their mechanical characterization under identical conditions. The extended finite element method (XFEM) is an enhancement of the finite element method (FEM) that can be used for the strength prediction of bonded structures. This work proposes and validates damage laws for a thin layer of an epoxy adhesive at room temperature (RT), 100, 150, and 200°C using the XFEM. The fracture toughness (G Ic ) and maximum load ( ); in pure tensile loading were defined by testing double-cantilever beam (DCB) and bulk tensile specimens, respectively, which permitted building the damage laws for each temperature. The bulk test results revealed that decreased gradually with the temperature. On the other hand, the value of G Ic of the adhesive, extracted from the DCB data, was shown to be relatively insensitive to temperature up to the glass transition temperature (T g ), while above T g (at 200°C) a great reduction took place. The output of the DCB numerical simulations for the various temperatures showed a good agreement with the experimental results, which validated the obtained data for strength prediction of bonded joints in tension. By the obtained results, the XFEM proved to be an alternative for the accurate strength prediction of bonded structures.

User-interface technologies for the industrial environment: towards the cyber-factory

In the past few years the so-called gadgets like cellular phones, personal data assistants and digital cameras are more widespread even with less technological aware users. However, for several reasons, the factory-floor itself seems to be hermetic to this changes ... After the fieldbus revolution, the factory-floor has seen an increased use of more and more powerful programmable logic controllers and user interfaces but the way they are used remains almost the same. We believe that new user-computer interaction techniques including multimedia and augmented rcaliry combined with now affordable technologies like wearable computers and wireless networks can change the way the factory personal works together with the roachines and the information system on the factory-floor. This new age is already starting with innovative uses of communication networks on the factory-floor either using "standard" networks or enhancing industrial networks with multimedia and wireless capabilities.

Projecto de avaliação de interfaces – PAI

Para obtenção do grau de Doutor pela Universidade de Vigo com menção internacional Departamento de Informática

A preliminary idea for an 8-competitive, log2 DMAX + log2 log2 1/U asymptotic-space, interface generation algorithm for two-level hierarchical scheduling of constrained-deadline sporadic tasks on a uniprocessor

Consider a single processor and a software system. The software system comprises components and interfaces where each component has an associated interface and each component comprises a set of constrained-deadline sporadic tasks. A scheduling algorithm (called global scheduler) determines at each instant which component is active. The active component uses another scheduling algorithm (called local scheduler) to determine which task is selected for execution on the processor. The interface of a component makes certain information about a component visible to other components; the interfaces of all components are used for schedulability analysis. We address the problem of generating an interface for a component based on the tasks inside the component. We desire to (i) incur only a small loss in schedulability analysis due to the interface and (ii) ensure that the amount of space (counted in bits) of the interface is small; this is because such an interface hides as much details of the component as possible. We present an algorithm for generating such an interface.

Analysis of temperature time-series: embedding dynamics into the MDS method

Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.

A pseudo-medium-wide 8-competitive interface for two-level compositional real-time scheduling of constrained- deadline sporadic tasks on a uniprocessor

Compositional real-time scheduling clearly requires that ”normal” real-time scheduling challenges are addressed but challenges intrinsic to compositionality must be addressed as well, in particular: (i) how should interfaces be described? and (ii) how should numerical values be assigned to parameters constituting the interfaces? The real-time systems community has traditionally used narrow interfaces for describing a component (for example, a utilization/bandwidthlike metric and the distribution of this bandwidth in time). In this paper, we introduce the concept of competitive ratio of an interface and show that typical narrow interfaces cause poor performance for scheduling constrained-deadline sporadic tasks (competitive ratio is infinite). Therefore, we explore more expressive interfaces; in particular a class called medium-wide interfaces. For this class, we propose an interface type and show how the parameters of the interface should be selected. We also prove that this interface is 8-competitive.

Simulation relations, interface complexity, and resource optimality for real-time hierachical systems

Compositional schedulability analysis of hierarchical realtime systems is a well-studied problem. Various techniques have been developed to abstract resource requirements of components in such systems, and schedulability has been addressed using these abstract representations (also called component interfaces). These approaches for compositional analysis incur resource overheads when they abstract components into interfaces. In this talk, we define notions of resource schedulability and optimality for component interfaces, and compare various approaches.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Interface between Intellectual Disability and Mental Health: hermeneutic review

A literature review was conducted aiming to understand the interface between the Intellectual Disability and Mental Health fields and to contribute to mitigating the path of institutionalizing individuals with intellectual deficiencies. The so-called dual diagnosis phenomenon remains underestimated in Brazil but is the object of research and specific public policy internationally. This phenomenon alerts us to the prevalence of mental health problems in those with intellectual disabilities, limiting their social inclusion. The findings reinforce the importance of this theme and indicate possible diagnostic invisibility of the development of mental illness in those with intellectual disabilities in Brazil, which may contribute to sustaining psychiatric institutionalization of this population. 

Ill-defined causes of death in Brazil: a redistribution method based on the investigation of such causes

OBJECTIVE To propose a method of redistributing ill-defined causes of death (IDCD) based on the investigation of such causes.METHODS In 2010, an evaluation of the results of investigating the causes of death classified as IDCD in accordance with chapter 18 of the International Classification of Diseases (ICD-10) by the Mortality Information System was performed. The redistribution coefficients were calculated according to the proportional distribution of ill-defined causes reclassified after investigation in any chapter of the ICD-10, except for chapter 18, and used to redistribute the ill-defined causes not investigated and remaining by sex and age. The IDCD redistribution coefficient was compared with two usual methods of redistribution: a) Total redistribution coefficient, based on the proportional distribution of all the defined causes originally notified and b) Non-external redistribution coefficient, similar to the previous, but excluding external causes.RESULTS Of the 97,314 deaths by ill-defined causes reported in 2010, 30.3% were investigated, and 65.5% of those were reclassified as defined causes after the investigation. Endocrine diseases, mental disorders, and maternal causes had a higher representation among the reclassified ill-defined causes, contrary to infectious diseases, neoplasms, and genitourinary diseases, with higher proportions among the defined causes reported. External causes represented 9.3% of the ill-defined causes reclassified. The correction of mortality rates by the total redistribution coefficient and non-external redistribution coefficient increased the magnitude of the rates by a relatively similar factor for most causes, contrary to the IDCD redistribution coefficient that corrected the different causes of death with differentiated weights.CONCLUSIONS The proportional distribution of causes among the ill-defined causes reclassified after investigation was not similar to the original distribution of defined causes. Therefore, the redistribution of the remaining ill-defined causes based on the investigation allows for more appropriate estimates of the mortality risk due to specific causes.

Direct search optimization application programming interface with remote access

Search Optimization methods are needed to solve optimization problems where the objective function and/or constraints functions might be non differentiable, non convex or might not be possible to determine its analytical expressions either due to its complexity or its cost (monetary, computational, time,...). Many optimization problems in engineering and other fields have these characteristics, because functions values can result from experimental or simulation processes, can be modelled by functions with complex expressions or by noise functions and it is impossible or very difficult to calculate their derivatives. Direct Search Optimization methods only use function values and do not need any derivatives or approximations of them. In this work we present a Java API that including several methods and algorithms, that do not use derivatives, to solve constrained and unconstrained optimization problems. Traditional API access, by installing it on the developer and/or user computer, and remote API access to it, using Web Services, are also presented. Remote access to the API has the advantage of always allow the access to the latest version of the API. For users that simply want to have a tool to solve Nonlinear Optimization Problems and do not want to integrate these methods in applications, also two applications were developed. One is a standalone Java application and the other a Web-based application, both using the developed API.

A straightforward method to obtain the cohesive laws of bonded joints under mode I loading

A simple procedure to measure the cohesive laws of bonded joints under mode I loading using the double cantilever beam test is proposed. The method only requires recording the applied load–displacement data and measuring the crack opening displacement at its tip in the course of the experimental test. The strain energy release rate is obtained by a procedure involving the Timoshenko beam theory, the specimen’s compliance and the crack equivalent concept. Following the proposed approach the influence of the fracture process zone is taken into account which is fundamental for an accurate estimation of the failure process details. The cohesive law is obtained by differentiation of the strain energy release rate as a function of the crack opening displacement. The model was validated numerically considering three representative cohesive laws. Numerical simulations using finite element analysis including cohesive zone modeling were performed. The good agreement between the inputted and resulting laws for all the cases considered validates the model. An experimental confirmation was also performed by comparing the numerical and experimental load–displacement curves. The numerical load–displacement curves were obtained by adjusting typical cohesive laws to the ones measured experimentally following the proposed approach and using finite element analysis including cohesive zone modeling. Once again, good agreement was obtained in the comparisons thus demonstrating the good performance of the proposed methodology.