937 resultados para analysis with NMR
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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.
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Dissertação de Mestrado em Engenharia Informática
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Meshless methods are used for their capability of producing excellent solutions without requiring a mesh, avoiding mesh related problems encountered in other numerical methods, such as finite elements. However, node placement is still an open question, specially in strong form collocation meshless methods. The number of used nodes can have a big influence on matrix size and therefore produce ill-conditioned matrices. In order to optimize node position and number, a direct multisearch technique for multiobjective optimization is used to optimize node distribution in the global collocation method using radial basis functions. The optimization method is applied to the bending of isotropic simply supported plates. Using as a starting condition a uniformly distributed grid, results show that the method is capable of reducing the number of nodes in the grid without compromising the accuracy of the solution. (C) 2013 Elsevier Ltd. All rights reserved.
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ABSTRACT OBJECTIVE Analyze the contextual and individual characteristics that explain the differences in the induced abortion rate, temporally and territorially. METHODS We conducted an econometric analysis with panel data of the influence of public investment in health and per capita income on induced abortion as well as a measurement of the effect of social and economic factors related to the labor market and reproduction: female employment, immigration, adolescent fertility and marriage rate. The empirical exercise was conducted with a sample of 22 countries in Europe for the 2001-2009 period. RESULTS The great territorial variability of induced abortion was the result of contextual and individual socioeconomic factors. Higher levels of national income and investments in public health reduce its incidence. The following sociodemographic characteristics were also significant regressors of induced abortion: female employment, civil status, migration, and adolescent fertility. CONCLUSIONS Induced abortion responds to sociodemographic patterns, in which the characteristics of each country are essential. The individual and contextual socioeconomic inequalities impact significantly on its incidence. Further research on the relationship between economic growth, labor market, institutions and social norms is required to better understand its transnational variability and to reduce its incidence.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau em Mestre em Engenharia Física
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The bending of simply supported composite plates is analyzed using a direct collocation meshless numerical method. In order to optimize node distribution the Direct MultiSearch (DMS) for multi-objective optimization method is applied. In addition, the method optimizes the shape parameter in radial basis functions. The optimization algorithm was able to find good solutions for a large variety of nodes distribution.
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Introduction. IgA nephropathy is the dominant primary glomerular disease found throughout the majority of the world’s developed countries. Accurately identifying patients who are at risk of progressive disease is challenging. We aimed to characterise clinical and histological features that predict poor prognosis in adults. Patients and Methods. We performed a single-centre retrospective observational study of biopsy-proven IgA nephropathy. The primary outcome was renal survival and death from any cause, and the secondary outcome was proteinuria remission. Results. Data from 49 cases were available for analysis with a median follow-up of 4 years. There were no deaths. Univariable analyses identified acute renal failure, low estimated glomerular filtration rate for ≥3 months (low eGFR), arterial hypertension, baseline proteinuria, glomerular sclerosis >50% and interstitial fibrosis >50% as poor prognostic markers. Low eGFR persisted significant by multivariable model that used only clinical parameters. Multivariable models with histopathologic parameters observed that tubular atrophy/interstitial fibrosis >50% was independently associated with the primary outcome. Proteinuria remission throughout follow-up had no prognostic value in our revision. Conclusions. Two independent predictors of poor renal survival at time of biopsy were found: low eGFR and tubular atrophy/interstitial fibrosis >50%.
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Introduction & Objectives: Several factors may influence the decision to pursue nonsurgical modalities for the treatment of non-melanoma skin cancer. Topical photodynamic therapy (PDT) is a non-invasive alternative treatment reported to have a high efficacy when using standardized protocols in Bowen’s disease (BD), superficial basal cell carcinoma (BCC) and in thin nodular BCC. However, long-term recurrence studies are lacking. The aim of this study was to evaluate the long-term efficacy of PDT with topical methylaminolevulinate (MAL) for the treatment of BD and BCC in a dermato-oncology department. Materials & Methods: All patients with the diagnosis of BD or BCC, treated with MAL-PDT from the years 2004 to 2008, were enrolled. Treatment protocol included two MAL-PDT sessions one week apart repeated at three months when incomplete response, using a red light dose of 37-40 J/cm2 and an exposure time of 8’20’’. Clinical records were retrospectively reviewed, and data regarding age, sex, tumour location, size, treatment outcomes and recurrence were registered. Descriptive analysis was performed using chi square tests, followed by survival analysis with the Kaplan-Meier and Cox regression models. Results: Sixty-eight patients (median age 71.0 years, P25;P75=30;92) with a total of 78 tumours (31 BD, 45 superficial BCC, 2 nodular BCC) and a median tumour size of 5 cm2 were treated. Overall, the median follow-up period was 43.5 months (P25;P75=0;100), and a total recurrence rate of 33.8% was observed (24.4 % for BCC vs. 45.2% for BD). Estimated recurrence rates for BCC and BD were 5.0% vs. 7.4% at 6 months, 23.4% vs. 27.9% at 12 months, and 30.0% vs. 72.4% at 60 months. Both age and diagnosis were independent prognostic factors for recurrence, with significantly higher estimated recurrence rates in patients with BD (p=0.0036) or younger than 58 years old (p=0.039). The risk of recurrence (hazard ratio) was 2.4 times higher in patients with BD compared to superficial BCC (95% CI:1.1-5.3; p=0.033), and 2.8 times higher in patients younger than 58 years old (95% CI:1.2-6.5; p=0.02). Conclusions: In the studied population, estimated recurrence rates are higher than those expected from available literature, possibly due to a longer follow-up period. To the authors’ knowledge there is only one other study with a similar follow-up period, regarding BCC solely. BD, as an in situ squamous cell carcinoma, has a higher tendency to recur than superficial BCC. Despite greater cosmesis, PDT might no be the best treatment option for young patients considering their higher risk of recurrence.
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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial
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Although literature is lacking in the topic of internationalization of services, we manage to apply both the Uppsala model and the Eclectic Theory to the healthcare service. A cross-case study analysis with three international hospitals is done in order to define an internationalization pattern and conditions for a successful process. This is then applied to Associação Protectora dos Diabéticos de Portugal with the purpose of defining an internationalization strategy to the Association.
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A new technique was developed for producing thin panels of a cement based material reinforced with relatively high content of steel fibres originated from the industry of tyre recycling. Flexural tests with notched and un-notched specimens were carried out to characterize the mechanical properties of this Fibre Reinforced Cement Composite (FRCC) and the results are presented and discussed. The values of the fracture mode I parameters of the developed FRCC were determined by performing inverse analysis with test results obtained in three point notched beam bending tests. To appraise the potentialities of these FRCC panels for the increase of the shear capacity of reinforced (RC) beams, numerical research was performed on the use of developed FRCC panel for shear reinforcement by applying the panels in the lateral faces of RC beams deficiently reinforced in shear.
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Existing masonry structures are usually associated to a high seismic vulnerability, mainly due to the properties of the materials, weak connections between floors and load-bearing walls, high mass of the masonry walls and flexibility of the floors. For these reasons, the seismic performance of existing masonry structures has received much attention in the last decades. This study presents the parametric analysis taking into account the deviations on features of the gaioleiro buildings - Portuguese building typology. The main objective of the parametric analysis is to compare the seismic performance of the structure as a function of the variations of its properties with respect to the response of a reference model. The parametric analysis was carried out for two types of structural analysis, namely for the non-linear dynamic analysis with time integration and for the pushover analysis with distribution of forces proportional to the inertial forces of the structure. The Young's modulus of the masonry walls, Young's modulus of the timber floors, the compressive and tensile non-linear properties (strength and fracture energy) were the properties considered in both type of analysis. Additionally, in the dynamic analysis, the influences of the vis-cous damping and of the vertical component of the earthquake were evaluated. A pushover analysis proportional to the modal displacement of the first mode in each direction was also carried out. The results shows that the Young's modulus of the masonry walls, the Young's modulus of the timber floors and the compressive non-linear properties are the pa-rameters that most influence the seismic performance of this type of tall and weak existing masonry structures. Furthermore, it is concluded that that the stiffness of the floors influences significantly the strength capacity and the collapse mecha-nism of the numerical model. Thus, a study on the strengthening of the floors was also carried out. The increase of the thickness of the timber floors was the strengthening technique that presented the best seismic performance, in which the reduction of the out-of-plane displacements of the masonry walls is highlighted.
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The structural analysis involves the definition of the model and selection of the analysis type. The model should represent the stiffness, the mass and the loads of the structure. The structures can be represented using simplified models, such as the lumped mass models, and advanced models resorting the Finite Element Method (FEM) and Discrete Element Method (DEM). Depending on the characteristics of the structure, different types of analysis can be used such as limit analysis, linear and non-linear static analysis and linear and non-linear dynamic analysis. Unreinforced masonry structures present low tensile strength and the linear analyses seem to not be adequate for assessing their structural behaviour. On the other hand, the static and dynamic non-linear analyses are complex, since they involve large time computational requirements and advanced knowledge of the practitioner. The non-linear analysis requires advanced knowledge on the material properties, analysis tools and interpretation of results. The limit analysis with macro-blocks can be assumed as a more practical method in the estimation of maximum load capacity of structure. Furthermore, the limit analysis require a reduced number of parameters, which is an advantage for the assessment of ancient and historical masonry structures, due to the difficult in obtaining reliable data.
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El presente proyecto plantea utilizar integralmente la técnica de Resonancia Magnética Nuclear en sólidos como un medio experimental que permite entender fenómenos de la física fundamental, como así también realizar aplicaciones de interés en el campo de la química, los desarrollos farmacéuticos y la biología. Novedosas técnicas experimentales serán empleadas, en conjunción con otras más tradicionales, en la caracterización de nuevas estructuras poliméricas acomplejadas a metales, membranas biológicas y compuestos de interés farmacéutico en vías de desarrollo, los cuales presentan el fenómeno de polimorfismo . Esto se llevará a cabo complementando los resultados de RMN en sólidos con técnicas tanto espectroscópicas como analíticas (Infrarrojo, Difracción de Rayos X, Calorimetría, RMN en solución) y trabajo interdisciplinario. Paralelamente al desarrollo de estos temas, profundizaremos mediante investigación básica, en la compresión de la dinámica cuántica y el surgimiento de la irreversibilidad en sistemas de espines nucleares. Observaremos en particular la generación, evolución y control de las coherencias cuánticas múltiples en sistemas cuánticos abiertos, lo cual nos da información sobre tamaño de clusters de espines. Esto permitirá la correcta implementación de secuencias de pulsos sofisticadas, como así también desarrollar nuevos métodos de medición aplicados a la caracterización estructural y a la dinámica molecular de sólidos complejos. Debemos resaltar que este proyecto está conectado con aspectos tanto básicos como aplicados de la RMN en sólidos como técnica experimental, la cual se desarrolla en el país únicamente en FaMAF-UNC. Se nutre además de trabajo multidisciplinario promoviendo la colaboración con investigadores y becarios de distintas áreas (física, química, farmacia, biología) provenientes de distintos puntos del país. Finalmente podemos afirmar que este plan impulsa la aplicación de la física básica proyectada a diferentes áreas del conocimiento, en el ámbito de la provincia de Córdoba. The aim of the present proyect is to use Nuclear Magnetic Resonance (NMR) as a complete techique that allows the understanding of fundamental physics phenomena and, at the same time, it leads to important applications in the fields of chemistry, pharmaceutical developments and biology. New experiments will be used together with traditional ones, in the characterization of new metal-polymer complexes, biological membranes and pharmaceutical compounds, some of them presenting polymorfism. NMR experiments will be complemented with diverse spectroscopic and analytical techniques: Infrared, X ray Diffraction, Thermal Analysis, solution NMR, as well as multidisciplinary investigation. Additionally, the present proyect plans to study in depth several aspects of quantum dynamics phenomena and decoherence in nuclear spin systems. The present proyect is connected with basic and applied aspects of the solid state NMR technique, developed in our country, only at FaMAF-UNC. It is is composed by multidisciplinary work and it promotes the collaboration with researchers and students coming from different fields (physics, chemistry, pharmaceutical developments, biology) and different points of our country.
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The definition of areas of endemism is central to studies of historical biogeography, and their interrelationships are fundamental questions. Consistent hypotheses for the evolution of Pentatomidae in the Neotropical region depend on the accuracy of the units employed in the analyses, which in the case of studies of historical biogeography, may be areas of endemism. In this study, the distribution patterns of 222 species, belonging to 14 Pentatomidae (Hemiptera) genera, predominantly neotropical, were studied with the Analysis of Endemicity (NDM) to identify possible areas of endemism and to correlate them to previously delimited areas. The search by areas of endemism was carried out using grid-cell units of 2.5° and 5° latitude-longitude. The analysis based on groupings of grid-cells of 2.5° of latitude-longitude allowed the identification of 51 areas of endemism, the consensus of these areas resulted in four clusters of grid-cells. The second analysis, with grid-cells units of 5° latitude-longitude, resulted in 109 areas of endemism. The flexible consensus employed resulted in 17 areas of endemism. The analyses were sensitive to the identification of areas of endemism in different scales in the Atlantic Forest. The Amazonian region was identified as a single area in the area of consensus, and its southeastern portion shares elements with the Chacoan and Paraná subregions. The distribution data of the taxa studied, with different units of analysis, did not allow the identification of individual areas of endemism for the Cerrado and Caatinga. The areas of endemism identified here should be seen as primary biogeographic hypotheses.