956 resultados para next of kin
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In recent years, progress has been made in modelling long chain branched polymers by the introduction of the so-called pompom model. Initially developed by McLeish and Larson (1998), the model has undergone several improvements or alterations, leading to the development of new formulations. Some of these formulations however suffer from certain mathematical defects. The purpose of the present paper is to review some of the formulations of the pom-pom constitutive model, and to investigate their possible mathematical defects. Next, an alternative formulation is proposed, which does not appear to exhibit mathematical defects, and we explore its modelling performance by comparing the predictions with experiments in non-trivial rheometric flows of an LDPE melt. The selected rheometric flows are the double step strain, as well as the large amplitude oscillatory shear experiments. For LAOS experiments, the comparison involves the use of Fourier-transform analysis.
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The paper proposes a methodology especially focused on the generation of strategic plans of action, emphasizing the relevance of having a structured timeframe classification for the actions. The methodology explicitly recognizes the relevance of long-term goals as strategic drivers, which must insure that the complex system is capable to effectively respond to changes in the environment. In addition, the methodology employs engineering systems techniques in order to understand the inner working of the system and to build up alternative plans of action. Due to these different aspects, the proposed approach features higher flexibility compared to traditional methods. The validity and effectiveness of the methodology has been demonstrated by analyzing an airline company composed by 5 subsystems with the aim of defining a plan of action for the next 5 years, which can either: improve efficiency, redefine mission or increase revenues.
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The only Iberian lower Jurassic palcomagnetic pole come from the "Central Atlantic Magmatic Province"-related Messejana Plasencia dyke, but the age and origin of its remanence have been a matter of discussion. With the aim of solving this uncertainty, and to go further into a better understanding of its emplacement and other possible tectonic features, a systematic paleomagnetic investigation of 40 sites (625 specimens) distributed all along the 530 kin of the Messejana Plasencia dyke has been carried out. Rock magnetic experiments indicate PSD low Ti-titanomagnetite and magnetite as the minerals carrying the NRM. The samples were mostly thermally demagnetized. Most sites exhibit a characteristic remanent component of normal polarity with the exception of two sites, where samples with reversed polarities have been observed. The paleomagnetic pole derived from a total of 35 valid sites is representative of the whole structure of the dyke, and statistically well defined, with values of PLa = 70.4 degrees N, PLo = 237.6 degrees E, K= 47.9 and A(95) = 3.5 degrees. Paleomagnetic data indicates that: (i) there is no evidence of a Cretaceous remagnetization in the dyke, as it was suggested; (ii) most of the dyke had a brief emplacement time; furthermore, two dyke intrusion events separated in time from it by at least 10,000 y have been detected; (iii) the high grouping of the VGPs directions suggests no important tectonic perturbations of the whole structure of the dyke since its intrusion time; (iv) the pole derived from this study is a good quality lower Jurassic paleopole for the Iberian plate; and (v) the Messejana Plasencia dyke paleopole for the Iberian plate is also in agreement with quality-selected European and North American lower Jurassic paleopoles and the magnetic anomalies data sets that are available for rotate them to Iberia.
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OBJECTIVE: Before the Aids pandemic, demographic transition and control programs prompted a shift in the age of incidence of tuberculosis from adults to older people in many countries. The objective of the study is to evaluate this transition in Brazil. METHODS: Tuberculosis incidence and mortality data from the Ministry of Health and population data from the Brazilian Bureau of Statistics were used to calculate age-specific incidence and mortality rates and medians. RESULTS: Among reported cases, the proportion of older people increased from 10.5% to 12% and the median age from 38 to 41 years between the period of 1986 and 1996. The smallest decrease in the incidence rate occurred in the 30--49 and 60+ age groups. The median age of death increased from 53 to 55 years between 1980 and 1996. The general decline in mortality rates from 1986 to 1991 became less evident in the 30+ age group during the period of 1991 to 1996. A direct correlation between age and mortality rates was observed. The largest proportion of bacteriologically unconfirmed cases occurred in older individuals. CONCLUSIONS: The incidence of tuberculosis has begun to shift to the older population. This shift results from the decline in the annual risk of infection as well as the demographic transition. An increase in reactivation tuberculosis in older people is expected, since this population will grow from 5% to 14% of the Brazilian population over the next 50 years. A progressive reduction in HIV-related cases in adults will most likely occur. The difficulty in diagnosing tuberculosis in old age leads to increased mortality.
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With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.
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International Conference: A Child's World - Next Steps, 25 June 2012 - 27th June 2014.
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We are launching a long-term study to characterize the biodiversity at different elevations in several Azorean Islands. Our aim is to use the Azores as a model archipelago to answer the fundamental question of what generates and maintains the global spatial heterogeneity of diversity in islands and to be able to understand the dynamics of change across time. An extensive, standardized sampling protocol was applied in most of the remnant forest fragments of five Azorean Islands. Fieldwork followed BRYOLAT methodology for the collection of bryophytes, ferns and other vascular plant species. A modified version of the BALA protocol was used for arthropods. A total of 70 plots (10 m x 10 m) are already established in five islands (Flores, Pico, São Jorge, Terceira and São Miguel), all respecting an elevation step of 200 m, resulting in 24 stations examined in Pico, 12 in Terceira, 10 in Flores, 12 in São Miguel and 12 in São Jorge. The first results regarding the vascular plants inventory include 138 vascular species including taxa from Lycopodiophyta (N=2), Pteridophyta (N=27), Pinophyta (N=2) and Magnoliophyta (N=107). In this contribution we also present the main research question for the next six years within the 2020 Horizon.
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ECER 2015 "Education and Transition - Contributions from Educational Research", Corvinus University of Budapest from 7 to 11 September 2015.
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In the standard Schumpeterian-growth models only follower firms invest in R&D activities and larger economies grow faster. Since these results are counterfactual, this paper reveals that leader firms often support R&D activities and economic growth can be independent of the market size. In particular, the maintenance of R&D leadership increases with: (i) the technological-knowledge gap between leader and followers, since a firm-specific learning effect of accumulated technological knowledge from past R&D is considered, (ii) the leaders’ strategies that delay the next successful R&D supported by some follower firm, (iii) the market size, and (iv) the up-grade of each innovation.
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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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Radio frequency (RF) energy harvesting is an emerging technology that will enable to drive the next generation of wireless sensor networks (WSNs) without the need of using batteries. In this paper, we present RF energy harvesting circuits specifically developed for GSM bands (900/1800) and a wearable dual-band antenna suitable for possible implementation within clothes for body worn applications. Besides, we address the development and experimental characterization of three different prototypes of a five-stage Dickson voltage multiplier (with match impedance circuit) responsible for harvesting the RF energy. Different printed circuit board (PCB) fabrication techniques to produce the prototypes result in different values of conversion efficiency. Therefore, we conclude that if the PCB fabrication is achieved by means of a rigorous control in the photo-positive method and chemical bath procedure applied to the PCB it allows for attaining better values for the conversion efficiency. All three prototypes (1, 2 and 3) can power supply the IRIS sensor node for RF received powers of -4 dBm, -6 dBm and -5 dBm, and conversion efficiencies of 20, 32 and 26%, respectively. © 2014 IEEE.
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The Brazilian National Regulatory Agency for Private Health Insurance and Plans has recently published a technical note defining the criteria for the coverage of genetic testing to diagnose hereditary cancer. In this study we show the case of a patient with a breast lesion and an extensive history of cancer referred to a private service of genetic counseling. The patient met both criteria for hereditary breast and colorectal cancer syndrome screening. Her private insurance denied coverage for genetic testing because she lacks current or previous cancer diagnosis. After she appealed by lawsuit, the court was favorable and the test was performed using next-generation sequencing. A deletion of MLH1 exon 8 was found. We highlight the importance to offer genetic testing using multigene analysis for noncancer patients.
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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We discuss theoretical and phenomenological aspects of two-Higgs-doublet extensions of the Standard Model. In general, these extensions have scalar mediated flavour changing neutral currents which are strongly constrained by experiment. Various strategies are discussed to control these flavour changing scalar currents and their phenomenological consequences are analysed. In particular, scenarios with natural flavour conservation are investigated, including the so-called type I and type II models as well as lepton-specific and inert models. Type III models are then discussed, where scalar flavour changing neutral currents are present at tree level, but are suppressed by either a specific ansatz for the Yukawa couplings or by the introduction of family symmetries leading to a natural suppression mechanism. We also consider the phenomenology of charged scalars in these models. Next we turn to the role of symmetries in the scalar sector. We discuss the six symmetry-constrained scalar potentials and their extension into the fermion sector. The vacuum structure of the scalar potential is analysed, including a study of the vacuum stability conditions on the potential and the renormalization-group improvement of these conditions is also presented. The stability of the tree level minimum of the scalar potential in connection with electric charge conservation and its behaviour under CP is analysed. The question of CP violation is addressed in detail, including the cases of explicit CP violation and spontaneous CP violation. We present a detailed study of weak basis invariants which are odd under CP. These invariants allow for the possibility of studying the CP properties of any two-Higgs-doublet model in an arbitrary Higgs basis. A careful study of spontaneous CP violation is presented, including an analysis of the conditions which have to be satisfied in order for a vacuum to violate CP. We present minimal models of CP violation where the vacuum phase is sufficient to generate a complex CKM matrix, which is at present a requirement for any realistic model of spontaneous CP violation.
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Dissertation presented to obtain a Ph.D. Degree in Chemical Physics