941 resultados para Boudon, Raymond: The origin of values
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The snap-trap leaves of the aquatic waterwheel plant (Aldrovanda) resemble those of Venus' flytrap (Dionaea), its distribution and habit are reminiscent of bladderworts (Utricularia), but it shares many reproductive characters with sundews (Drosera). Moreover, Aldrovanda has never been included in molecular phylogenetic studies, so it has been unclear whether snap-traps evolved only once or more than once among angiosperms. Using sequences from nuclear 18S and plastid rbcL, atpB, and matK genes, we show that Aldrovanda is sister to Dionaea, and this pair is sister to Drosera. Our results indicate that snap-traps are derived from flypaper-traps and have a common ancestry among flowering plants, despite the fact that this mechanism is used by both a terrestrial species and an aquatic one. Genetic and fossil evidence for the close relationship between these unique and threatened organisms indicate that carnivory evolved from a common ancestor within this caryophyllid clade at least 65 million years ago.
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The radiation chemical yields G(S) and G(X) for H-linking and Y-linking models for Ultem have been calculated from molecular weight analysis by gel permeation chromatography. These G-values have been compared with the G-values obtained from analysis of soluble fractions above the gel dose, Which have been reported in previous works. An analysis of the molecular weight data in terms of H-linking and Y-linking mechanisms yielded values of G(S-H) = 1.0 x 10(-3) and G(H) = 6.0 x 10(-3) and G(S-Y) = 1.3 x 10(-2) and G(Y) = 1.8 x 10(-2). The corresponding values obtained from the solubility data were G(SH) = 0.53 x 10(-2), G(H) = 1.39 x 10(-2), G(S-Y) = 4.2 x 10(-2) and G(Y) - 4.6 x 10(-2). The origin of the disagreement between the molecular weight and solubility values is not clear, but it could arise as a result of observed microgel formation below the reported gel dose of 0.13 MGy. Whether the crosslink mechanism proceeds by an H-linking or Y-linking process is also unclear and will require direct observation of the crosslinking structures.
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Since collaborative networked organisations are usually formed by independent and heterogeneous entities, it is natural that each member holds his own set of values, and that conflicts among partners might emerge because of some misalignment of values. In contrast, it is often stated in literature that the alignment between the value systems of members involved in collaborative processes is a prerequisite for successful co-working. As a result, the issue of core value alignment in collaborative networks started to attract attention. However, methods to analyse such alignment are lacking mainly because the concept of 'alignment' in this context is still ill defined and shows a multifaceted nature. As a contribution to the area, this article introduces an approach based on causal models and graph theory for the analysis of core value alignment in collaborative networks. The potential application of the approach is then discussed in the virtual organisations' breeding environment context.
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Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.
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Dust is a complex mixture of particles of organic and inorganic origin and different gases absorbed in aerosol droplets. In a poultry unit include dried faecal matter and urine, skin flakes, ammonia, carbon dioxide, pollens, feed and litter particles, feathers, grain mites, fungi spores, bacteria, viruses and their constituents. Dust particles vary in size and differentiation between particle size fractions is important in health studies in order to quantify penetration within the respiratory system. A descriptive study was developed in order to assess exposure to particles in a poultry unit during different operations, namely routine examination and floor turn over. Direct-reading equipment was used (Lighthouse, model 3016 IAQ). Particle measurement was performed in 5 different sizes (PM0.5; PM1.0; PM2.5; PM5.0; PM10). The chemical composition of poultry litter was also determined by neutron activation analysis. Normally, the litter of poultry pavilions is turned over weekly and it was during this operation that the higher exposure of particles was observed. In all the tasks considered PM5.0 and PM10.0 were the sizes with higher concentrations values. PM10 is what turns out to have higher values and PM0.5 the lowest values. The chemical element with the highest concentration was Mg (5.7E6 mg.kg-1), followed by K (1.5E4 mg.kg-1), Ca (4.8E3 mg.kg-1), Na (1.7E3 mg.kg-1), Fe (2.1E2 mg.kg-1) and Zn (4.2E1 mg.kg-1). This high presence of particles in the respirable range (<5–7μm) means that poultry dust particles can penetrate into the gas exchange region of the lung. Larger particles (PM10) present a range of concentrations from 5.3E5 and 3.0E6 mg/m3.
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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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This work reports on the results of double immunodiffusion (ID), counterimmunoelectrophoresis (CIE), complement fixation (CF) and indirect immunofluorescence (IIF) techniques in the serodiagnosis of paracoccidioidomycosis. The study was undertaken on four groups of individuals: 46 patients with untreated paracoccidioidomycosis, 22 patients with other deep mycoses, 30 with other infectious diseases (tuberculosis and cutaneous leishmaniasis) and 47 blood donors as negative controls. Data were obtained using Paracoccidioides brasiliensis antigens, i.e.,a yeast culture filtrate for ID, CIE and CF, and a yeast cell suspension for IIF. The sensitivity, specificity and efficiency values were measured according to GALEN & GAMBINO8.The gel precipitation tests (ID and CIE) showed the greatest sensitivity (91.3 and 95.6%, respectively), maximum specificity (100%) and the highest efficiency values when compared to the CF and IIF tests.
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The Moncorvo Ordovician ironstones in northeastern Portugal consist of iron ore sedimentary horizons frequently interbanded with psamites and quartzites. Ore reserves may probably exceed 1 000 million tonnes and this makes Moncorvo the largest iron ore deposit in the European Union. Compact poorly banded massive layers may exceed 90 meters in thickness which is quite an extraordinary feature for a Phanerozoic deposit. If the thickness of Precambrian deposits may reach a few hundred meters, the thickness of Phanerozoic deposits never exceed a maximum of 15 meters generally forming a number of comparatively thin layers confined to a particular member of a sedimentary sequence. A detailed microscopic analysis of the ores revealed that initially a compact magnetite/quartzite layer, detrital in character (the magnetite occasionally showing chromite cores), was deposited by entrapment in near shore lagoons where rivers debouched, rather than in the open sea. This stage was followed by oscilating and transgressive shore lines which gave rise to breaks in sedimentation in combined river delta and shallow water marine environment where detrital material and fine iron oxide and clay suspensions were deposited in fluctuating environments. These events gave rise to layers of both magnetite (martite) and specularite intergrown with quartz, silicates and phosphates. Textural and mineralogical studies show that the deposits consist of ferruginous clastic sediments and are not chemically deposited cherts. Field, geological and palaeontological evidence also supports a detrital origin, the facies being typical of zones rich in oxygen and close to the feeding continent. The uncommon huge development of Moncorvo was due to the fact that the deposits occur in restricted basins on a continental platform were clastic sediments were predominantly deposited. Not only morphologically but also chemically the deposits are more similar to Precambrian iron formations than to Phanerozoic ironstones.
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Auditory event-related potentials (AERPs) are widely used in diverse fields of today’s neuroscience, concerning auditory processing, speech perception, language acquisition, neurodevelopment, attention and cognition in normal aging, gender, developmental, neurologic and psychiatric disorders. However, its transposition to clinical practice has remained minimal. Mainly due to scarce literature on normative data across age, wide spectrumof results, variety of auditory stimuli used and to different neuropsychological meanings of AERPs components between authors. One of the most prominent AERP components studied in last decades was N1, which reflects auditory detection and discrimination. Subsequently, N2 indicates attention allocation and phonological analysis. The simultaneous analysis of N1 and N2 elicited by feasible novelty experimental paradigms, such as auditory oddball, seems an objective method to assess central auditory processing. The aim of this systematic review was to bring forward normative values for auditory oddball N1 and N2 components across age. EBSCO, PubMed, Web of Knowledge and Google Scholarwere systematically searched for studies that elicited N1 and/or N2 by auditory oddball paradigm. A total of 2,764 papers were initially identified in the database, of which 19 resulted from hand search and additional references, between 1988 and 2013, last 25 years. A final total of 68 studiesmet the eligibility criteria with a total of 2,406 participants from control groups for N1 (age range 6.6–85 years; mean 34.42) and 1,507 for N2 (age range 9–85 years; mean 36.13). Polynomial regression analysis revealed thatN1latency decreases with aging at Fz and Cz,N1 amplitude at Cz decreases from childhood to adolescence and stabilizes after 30–40 years and at Fz the decrement finishes by 60 years and highly increases after this age. Regarding N2, latency did not covary with age but amplitude showed a significant decrement for both Cz and Fz. Results suggested reliable normative values for Cz and Fz electrode locations; however, changes in brain development and components topography over age should be considered in clinical practice.
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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em História - Civilizações do Médio Oriente e Ásia Antiga
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Objective: Early onset benign occipital lobe epilepsy (Panayiotopoulos syndrome [PS]) is a common and easily recognizable epilepsy. Interictal EEG spike activity is often multifocal but most frequently localized in the occipital lobes. The origin and clinical significance of the extra-occipital spikes remain poorly understood. Methods: Three patients with the PS and interictal EEG spikes with frontal lobe topography were studied using high-resolution EEG. Independent component analysis (ICA) was used to decompose the spikes in components with distinct temporal dynamics. The components were mapped in the scalp with a spline-laplacian algorithm. Results: The change in scalp potential topography from spike onset to peak, suggests the contribution of several intracranial generators, with different kinetics of activation and significant overlap. ICA was able to separate the major contributors to frontal spikes and consistently revealed an early activating group of components over the occipital areas in all the patients. The local origin of these early potentials was established by the spline-laplacian montage. Conclusions: Frontal spikes in PS are consistently associated with early and unilateral occipital lobe activation, suggesting a posteroanterior spike propagation. Significance: Frontal spikes in the PS represent a secondary activation triggered by occipital interictal discharges and do not represent an independent focus.
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Objective: The epilepsies associated with the tuberous sclerosis complex (TSC) are very often refractory to medical therapy. Surgery for epilepsy is an effective alternative when the critical link between the localization of seizure onset in the scalp and a particular cortical tuber can be established. In this study we perform analysis of ictal and interictal EEG to improve such link. Methods: The ictal and interictal recordings of four patients with TSC undergoing surgery for epilepsy were submitted to independent component analysis (ICA), followed by source analysis, using the sLORETA algorithm. The localizations obtained for the ictal EEG and for the average interictal spikes were compared. Results: The ICA of ictal EEG produced consistent results in different events, and there was good agreement with the tubers that were successfully removed in three of the four patients (one patient refused surgery). In some patients there was a large discrepancy between the localization of ictal and interictal sources. The interictal activity produced more widespread source localizations. Conclusions: The use of ICA of ictal EEG followed by the use of source analysis methods in four cases of epilepsy and TSC was able to localize the epileptic generators very near the lesions successfully removed in surgery for epilepsy. Significance: The ICA of ictal EEG events may be a useful add-on to the tools used to establish the connection between epileptic scalp activity and the cortical tubers originating it, in patients with TSC considered for surgery of epilepsy.
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In any area of study, it is necessary to define the subject of investigation. In the case of evolutionary novelty this is a particularly difficult task, as a clear definition of the concept that is suitable across di↵erent levels of biological organization has yet to emerge. We proceed with a definition for morphological novelty proposed by M¨uller and Wagner (1991), and introduce the dorsal appendages on eggs of Drosophilidae as such a novelty. These structures are part of the eggshell, and help supply oxygen to the embryo. A wide variety of phenotypes can be found, which is thought to have a single origin in the common ancestor of Drosophilidae.(...)