Assessment of data-driven modeling strategies for water delivery canals

The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.

Development and validation of a novel method for the analysis of chlorinated pesticides in soils using microwave-assisted extraction–headspace solid phase microextraction and gas chromatography–tandem mass spectrometry

A new procedure for determining eleven organochlorine pesticides in soils using microwave-assisted extraction (MAE) and headspace solid phase microextraction (HS-SPME) is described. The studied pesticides consisted of mirex, α- and γ-chlordane, p,p’-DDT, heptachlor, heptachlor epoxide isomer A, γ-hexachlorocyclohexane, dieldrin, endrin, aldrine and hexachlorobenzene. The HS-SPME was optimized for the most important parameters such as extraction time, sample volume and temperature. The present analytical procedure requires a reduced volume of organic solvents and avoids the need for extract clean-up steps. For optimized conditions the limits of detection for the method ranged from 0.02 to 3.6 ng/g, intermediate precision ranged from 14 to 36% (as CV%), and the recovery from 8 up to 51%. The proposed methodology can be used in the rapid screening of soil for the presence of the selected pesticides, and was applied to landfill soil samples.

Multiresidue method for the determination of organophosphorus pesticides in still wine and fortified wine using solid-phase microextraction and gas chromatography – Tandem mass spectrometry

A SPME-GC-MS/MS method for the determination of eight organophosphorus pesticides (azinphos-methyl, chlorpyriphos, chlorpyriphos-methyl, diazinon, fenitrothion, fenthion, malathion, and methidathion) in still and fortified wine was developed. The extraction procedure is simple, solvent free, and without any sample pretreatment. Limits of detection (LOD) and quantitation (LOQ) values in the range 0.1–14.3 lg/L and 0.2–43.3 lg/L, respectively, were obtained. The LOQ values are below the maximum residue levels (MRLs) established by European Regulation for grapes, with the exception of methidathion. Coefficients of correlation (R2) higher than 0.99 were obtained for the majority of the pesticides, in all different wines analyzed.

New sensing materials of molecularly-imprinted polymers for the selective recognition of Chlortetracycline

As a result of the stressful conditions in aquaculture facilities there is a high risk of bacterial infections among cultured fish. Chlortetracycline (CTC) is one of the antimicrobials used to solve this problem. It is a broad spectrum antibacterial active against a wide range of Gram-positive and Gram-negative bacteria. Numerous analytical methods for screening, identifying, and quantifying CTC in animal products have been developed over the years. An alternative and advantageous method should rely on expeditious and efficient procedures providing highly specific and sensitive measurements in food samples. Ion-selective electrodes (ISEs) could meet these criteria. The only ISE reported in literature for this purpose used traditional electro-active materials. A selectivity enhancement could however be achieved after improving the analyte recognition by molecularly imprinted polymers (MIPs). Several MIP particles were synthesized and used as electro-active materials. ISEs based in methacrylic acid monomers showed the best analytical performance according to slope (62.5 and 68.6 mV/decade) and detection limit (4.1×10−5 and 5.5×10−5 mol L−1). The electrodes displayed good selectivity. The ISEs are not affected by pH changes ranging from 2.5 to 13. The sensors were successfully applied to the analysis of serum, urine and fish samples.

Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes

Amulti-residue methodology based on a solid phase extraction followed by gas chromatography–tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC–MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness.

Flow-injection potentiometric method for the routine determination of chloride: application to bread analysis

Bread is consumed worldwide by man, thus contributing to the regular ingestion of certain inorganic species such as chloride. It controls the blood pressure if associated to a sodium intake and may increase the incidence of stomach ulcer. Its routine control should thus be established by means of quick and low cost procedures. This work reports a double- channel flow injection analysis (FIA) system with a new chloride sensor for the analysis of bread. All solutions are prepared in water and necessary ionic strength adjustments are made on-line. The body of the indicating electrode is made from a silver needle of 0.8 mm i.d. with an external layer of silver chloride. These devices were constructed with different lengths. Electrodes of 1.0 to 3.0 cm presented better analytical performance. The calibration curves under optimum conditions displayed Nernstian behaviour, with average slopes of 56 mV decade-1, with sampling rates of 60 samples h-1. The method was applied to analyze several kinds of bread, namely pão de trigo, pão integral, pão de centeio, pão de mistura, broa de milho, pão sem sal, pão meio sal, pão-de-leite, and pão de água. The accuracy and precision of the potentiometric method were ascertained by comparison to a spectrophotometric method of continuous segmented flow. These methods were validated against ion-chromatography procedures.

Espetroscopia (1H) por ressonância magnética do disco intervertebral lombar no adulto e sua aplicação na rotina imagiológica

Objetivos – Demonstrar o potencial da espetroscopia (1H) por ressonância magnética na doença degenerativa discal lombar e defender a integração desta técnica na rotina clínico‑imagiológica para a precisa classificação da involução vs degenerescência dos discos L4‑L5 e L5‑S1 em doentes com lombalgia não relacionável com causa mecânica. Material e métodos – O estudo incluiu 102 discos intervertebrais lombares de 123 doentes. Foram estudados 61 discos de L4‑L5, 41 discos de L5‑S1 e 34 discos de D12‑L1. Utilizou‑se um sistema de ressonância magnética de 1,5 T e técnica monovoxel. Obtiveram‑se os rácios [Lac/Nacetyl] e [Nacetyl/(Lac+Lípidos)] e aplicou‑se a ressonância de lípidos para avaliar a bioquímica do disco com o fim de conhecer o estado de involução vs degenerescência que o suscetibilizam para a instabilidade e sobrecarga. Avaliou‑se o comportamento dos rácios e do teor lipídico dos discos L4‑L5‑S1 e as diferenças apresentadas em relação a D12‑L1. Foi também realizada a comparação entre os discos L4‑L5, L5‑S1 e D12‑L1 na ponderação T2 (T2W), segundo a classificação ajustada (1‑4) de Pfirrmann. Resultados – Verificou‑se que os rácios e o valor dos lípidos dos discos L4‑L5‑S1 apresentaram diferenças estatisticamente significativas quando relacionados com os discos D12‑L1. O rácio [Lac/Nacetyl] em L4‑L5‑S1 mostrou‑se aumentado em relação a D12‑L1 (p=0,033 para os discos com grau de involução [1+2] e p=0,004 para os discos com grau [3+4]). Estes resultados sugerem que a involução vs degenerescência dos discos nos graus mais elevados condiciona um decréscimo do pico do Lactato. O rácio [Nacetyl/(Lac+Lip)] discrimina os graus de involução [1+2] do [3+4] no nível L4‑L5, apresentando os valores dos rácios (média 0,65 e 0,5 respetivamente com p=0,04). O rácio médio de [Nacetyl/(Lac+Lip)] dos discos L4‑L5 foi 1,8 vezes mais elevado do que em D12‑L1. O espetro lipídico em L4‑L5‑S1 nos graus mais elevados não mostrou ter uma prevalência constante quanto às frequências de ressonância. Conclusão – A espetroscopia (1H) dos discos intervertebrais poderá ter aplicação na discriminação dos graus de involução vs degenerescência e representar um contributo semiológico importante em suplemento à ponderação T2 convencional. As ressonâncias de lípidos dos discos L4‑L5 e L5‑S1, involuídos ou degenerados, devem ser avaliadas em relação a D12‑L1, utilizando este valor como referência, pois este último é o nível considerado estável e com baixa probabilidade de degenerescência.

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.

Growth pressure dependence of Cu2ZnSnSe4 properties

In this work, we show a set of growth conditions, for the two step process, with which the growth of CZTSe is successful and reproducible. The properties of the best CTZSe thin films grown by this method were examined by SEM/EDS, XRD, Raman scattering, AFM/EFM, transmittance and reflectance measurements, photoluminescence (PL) measurements and hot point probe. A broad emission band was observed in the photoluminescence spectrum of the CZTSe thin film. The band gap energy was estimated to be around 1.05 eV at room temperature, using the transmittance and reflectance data, and CZTSe samples show p-type conductivity with the hot point probe. The different characterization techniques show that we could grow single phase CZTSe thin films with our optimized process 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.

Projeto de fundações e estrutura de colégio em Ponta Delgada utilizando os eurocódigos estruturais

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas

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.

Análise estática não linear de um edifício em betão armado

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil

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.

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.