1000 resultados para basic red 51
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Electrochemical oxidation of propanil in deuterated solutions was studied by cyclic, differential pulse, and square wave voltammetry using a glassy carbon microelectrode. The oxidation of propanil in deuterated acid solutions occurs at the nitrogen atom of the amide at a potential of +1.15 V vs Ag/ AgCl. It was also found that, under the experimental conditions used, protonation at the oxygen atom of propanil occurs, leading to the appearance of another species in solution which oxidizes at +0.60 V. The anodic peak found at +0.79 V vs Ag/AgCl in deuterated basic solutions is related to the presence of an anionic species in which a negative charge is on the nitrogen atom. The electrochemical data were confirmed by the identification of all the species formed in acidic and basic deuterated solutions by means of NMR spectroscopy. The results are supported by electrochemical and spectroscopic studies of acetanilide in deuterated solutions.
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Devido ao acréscimo significativo de viaturas e peões nas grandes cidades foi necessário recorrer aos mecanismos existentes para coordenar o tráfego. Nesta perspectiva surge a implementação de semáforos com o objectivo de ordenar o tráfego nas vias rodoviárias. A gestão de tráfego, tem sido sujeita a inovações tanto ao nível dos equipamentos, do software usado, gestão centralizada, monitorização das vias e na sincronização semafórica, sendo possível a criação de programas ajustados às diferentes exigências de tráfego verificadas durante as vinte e quatro horas para pontos distintos da cidade. Conceptualmente foram elaborados estudos, com o objectivo de identificar a relação entre a velocidade o fluxo e o intervalo num determinado intervalo de tempo, bem como a relação entre a velocidade e a sinistralidade. Até 1995 Portugal era um dos países com maior número de sinistros rodoviários Na sequência desta evolução foram instalados radares de controlo de velocidade no final de 2006 com o objectivo de obrigar ao cumprimento dos limites de velocidade impostos pelo código da estrada e reduzir a sinistralidade automóvel na cidade de Lisboa. Passados alguns anos sobre o investimento realizadoanteriormente, constatamos que existe a necessidade de implementar novas tecnologias na detecção das infracções, sejam estas de excesso de velocidade ou violação do semáforo vermelho (VSV), optimizar a informação disponibilizada aos automobilistas e aos peões, coordenar a interacção entre os veículos prioritários e os restantes presentes na via, dinamizar a gestão interna das contra ordenações, agilizar os procedimentos informatizar a recolha deinformação de modo a tornar os processos mais céleres.
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The fractional order calculus (FOC) is as old as the integer one although up to recently its application was exclusively in mathematics. Many real systems are better described with FOC differential equations as it is a well-suited tool to analyze problems of fractal dimension, with long-term “memory” and chaotic behavior. Those characteristics have attracted the engineers' interest in the latter years, and now it is a tool used in almost every area of science. This paper introduces the fundamentals of the FOC and some applications in systems' identification, control, mechatronics, and robotics, where it is a promissory research field.
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This text is based on a research, which is still in progress, whose main objective is to identify and understand what are the main difficulties of future mathematics teachers of basic education are, regarding their content knowledge in geometry in the context of the curricular unit of Geometry during their undergraduate degree. We chose a qualitative approach in the form of case study, in which data collection was done through observation, interviews, a diverse set of tasks, a diagnostic test and other documents. This paper focuses on the test given to prospective teachers at the beginning of the course. The preliminary analysis of the data points to a weak performance of preservice teachers in the test issues addressing elementary knowledge of Geometry
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En enero de 2014, continuando con la intención expresada en Guimarães (Portugal), en noviembre de 2013, durante la VII Reunión de la Geografía Física y Medio Ambiente (EGFA VII), la Asociación Portuguesa de Prevención de Riesgos y Seguridad (RISCOS) creó las condiciones para el establecimiento de una sección temática dedicada al estudio de los efectos de los incendios sobre los suelos y que vendría a ser conocida “Red Nacional para el Estudio de los Incendios Forestales y sus Efectos sobre los Suelos” (RIS). Esta fue una iniciativa inspirada en Fuegored (Red Temática Nacional Efectos de los Incendios Forestales sobre los Suelos) y que, de esta manera, desea establecer una red nacional de investigadores con el fin de facilitar la promoción y difusión de los resultados de sus pesquisas científicas sobre este tema, realizadas en Portugal, así como la interacción entre el mundo científico y el manejo forestal . La RIS fue fundada por 12 miembros, que representan 7 universidades portuguesas y en la actualidad cuenta con 23 miembros de 9 universidades y escuelas politécnicas. Se espera que crezca y que puede añadir todos los que participan en la investigación científica de los incendios forestales y sus efectos en los suelos.
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"It is a widely accepted fact that the consumption-based capital asset pricing model (CCAPM) fails to provide a good explanation of many important features of the behaviour of financial market returns in a large range of countries over a long period of time. However, within a representative consumer/investor model, it is hard to see how the basic structure of the consumption based model can be safely abandoned." [introdução]
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Dissertação apresentada para obtenção do grau de Doutor em Ciência dos Materiais, especialidade de Metalurgia, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Ano VI; nº 2 - 2008 - p.103-106
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Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.
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A total of 130 Listeria strains were tested in order to evaluate lecithinase production and capacity for Congo red adsorption as markers of pathogenicity. The strains were identified according to acid production from sugars and by the CAMP test and the data were correlated with the ability to produce keratoconjunctivitis in guinea pigs. L. monocytogenes cultures presented 51.8% and 88.8% positivity rates for Congo red adsorption and lecithinase production, respectively, whereas 80.8% and 100% for L. innocua cultures were negative for the two test, respectively
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The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.
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The objective of this study was to compare the histopathological changes and expression of CR3 and CR4 in the liver and spleen of dogs naturally and experimentally infected with L. chagasi. The basic histopathological lesions observed mainly in naturally infected dogs were: epithelioid hepatic granulomas, hyperplasia and hypertrophy of Kupffer cells, Malpigui follicles and mononucleated cells of the red pulp of the spleen. Sections from the liver and spleen by immunocytochemistry technique showed the presence of CD11b,c\CD 18 antigens in the control and infected animals and no qualitative or quantitative differences in the liver. Nevertheless, CD18 was always increased in the spleen of naturally and experimentally infected dogs. These results indicate that there is a difference in the activaton of CD 18 in both experimental and natural cases of canine visceral leishmaniasis that should play an important role in the immunological response to Leishmania chagasi infection.
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Presented at Faculdade de Ciências e Tecnologias, Universidade de Lisboa, to obtain the Master Degree in Conservation and Restoration of Textiles
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Dissertation for the Degree of Master in Technology and Food Safety – Food Quality
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A vitamin E extraction method for rainbow trout flesh was optimized, validated, and applied in fish fed commercial and Gracilaria vermiculophylla-supplemented diets. Five extraction methods were compared. Vitamers were analyzed by HPLC/DAD/fluorescence. A solid-liquid extraction with n-hexane, which showed the best performance, was optimized and validated. Among the eight vitamers, only α- and γ-tocopherol were detected in muscle samples. The final method showed good linearity (>0.999), intra- (<3.1%) and inter-day precision (<2.6%), and recoveries (>96%). Detection and quantification limits were 39.9 and 121.0 ng/g of muscle, for α-tocopherol, and 111.4 ng/g and 337.6 ng/g, for γ-tocopherol, respectively. Compared to the control group, the dietary inclusion of 5% G. vermiculophylla resulted in a slight reduction of lipids in muscle and, consequently, of α- and γ-tocopherol. Nevertheless, vitamin E profile in lipids was maintained. In general, the results may be explained by the lower vitamin E level in seaweed-containing diet. Practical Applications: Based on the validation results and the low solvent consumption, the developed method can be used to analyze vitamin E in rainbow trout. The results of this work are also a valuable information source for fish feed industries and aquaculture producers, which can focus on improving seaweed inclusion in feeds as a source of vitamin E in fish muscle and, therefore, take full advantage of all bioactive components with an important role in fish health and flesh quality.