14 resultados para Cobalt aluminate. Curing method of complex (CPM). Inorganic pigments. Fractional factorial planning

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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The aim of this study was to develop a fast capillary electrophoresis method for the determination of inorganic cations (Na(+), K(+), Ca(2+), Mg(2+)) in biodiesel samples, using barium (Ba(2+)) as the internal standard. The running electrolyte was optimized through effective mobility curves in order to select the co-ion and Peakmaster software was used to determine electromigration dispersion and buffer capacity. The optimum background electrolyte was composed of 10 mmol L(-1) imidazole and 40 mmol L(-1) of acetic acid. Separation was conducted in a fused-silica capillary (32 cm total length and 23.5 cm effective length, 50 mu m I.D.), with indirect UV detection at 214 nm. The migration time was only 36 s. In order to obtain the optimized conditions for extraction, a fractional factorial experimental design was used. The variables investigated were biodiesel mass, pH, extractant volume, agitation and sonication time. The optimum conditions were: biodiesel mass of 200 mg, extractant volume of 200 mu L. and agitation of 20 min. The method is characterized by good linearity in the concentration range of 0.5-20 mg kg(-1) (r > 0.999), limit of detection was equal to 0.3 mg kg(-1), inter-day precision was equal to 1.88% and recovery in the range of 88.0-120%. The developed method was successfully applied to the determination of cations in biodiesel samples. (c) 2010 Elsevier B.V. All rights reserved.

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Searching in a dataset for elements that are similar to a given query element is a core problem in applications that manage complex data, and has been aided by metric access methods (MAMs). A growing number of applications require indices that must be built faster and repeatedly, also providing faster response for similarity queries. The increase in the main memory capacity and its lowering costs also motivate using memory-based MAMs. In this paper. we propose the Onion-tree, a new and robust dynamic memory-based MAM that slices the metric space into disjoint subspaces to provide quick indexing of complex data. It introduces three major characteristics: (i) a partitioning method that controls the number of disjoint subspaces generated at each node; (ii) a replacement technique that can change the leaf node pivots in insertion operations; and (iii) range and k-NN extended query algorithms to support the new partitioning method, including a new visit order of the subspaces in k-NN queries. Performance tests with both real-world and synthetic datasets showed that the Onion-tree is very compact. Comparisons of the Onion-tree with the MM-tree and a memory-based version of the Slim-tree showed that the Onion-tree was always faster to build the index. The experiments also showed that the Onion-tree significantly improved range and k-NN query processing performance and was the most efficient MAM, followed by the MM-tree, which in turn outperformed the Slim-tree in almost all the tests. (C) 2010 Elsevier B.V. All rights reserved.

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In this communication, we report on the formation of calcium hexahydroxodizincate dehydrate, CaZn(2)(OH)(6)center dot 2H(2)O (CZO) powders under microwave-hydrothermal (MH) conditions. These powders were analyzed by X-ray diffraction (XRD), Field-emission gum scanning electron microscopy (FEG-SEM), ultraviolet-visible (UV-vis) absorption spectroscopy and photoluminescence (PL) measurements. XRD patterns confirmed that the pure CZO phase was obtained after MH processing performed at 130 degrees C for 2 h. FEG-SEM micrographs indicated that the morphological modifications as well as the growth of CZO microparticles are governed by Ostwald-ripening and coalescence mechanisms. UV-vis spectra showed that this material have an indirect optical band gap. The pure CZO powders exhibited an yellow PL emission when excited by 350 nm wavelength at room temperature. (C) 2009 Elsevier Masson SAS. All rights reserved.

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Modern medical imaging techniques enable the acquisition of in vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all, but the Most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder assumption. We directly exploit local neighborhood intensities and extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile. We present a new method to capture the common properties shared by polar neighborhood intensity profiles for all the types of vascular points belonging to the vascular system. The new method enables us to detect vessels even near complex extreme points, including branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and 3D animal and clinical vascular images, particularly close to vessel branching regions. (C) 2008 Elsevier B.V. All rights reserved.

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Based on the fact that streamwater quality reflects landscape conditions, the objectives of this study were: to investigate nitrogen (N), carbon (C), and major ion concentrations in six streams crossing minimally disturbed Atlantic Forest areas, with similar geomorphological characteristics; to determine N and C fluxes in one of these pristine streams (Indaia); and assess the impact of human activity on the biogeochemistry of two other streams in the same region, crossing urbanized areas. The distribution pattern of carbon and inorganic nitrogen dissolved forms, as well as the major ion and biogenic gas concentrations in the streamwater, was similar in pristine streams, indicating that the C and N dynamics were determined by influence of some factors, such as climate, atmospheric deposition, geology, soil type, and land covering, which were analogous in the forested watersheds. The urban streams were significantly different from the pristine streams, showing low dissolved oxygen concentrations, high respiration rates, and high concentrations of carbon dioxide, dissolved inorganic nitrogen, dissolved inorganic carbon, and major ion. These differences were attributed to anthropogenic impact on water quality, especially domestic sewage discharge. Additionally, in the Indaia stream, it was possible to observe the importance of rainfall over temporal dynamics of dissolved carbon forms, and also, the obtained specific flux of dissolved inorganic nitrogen was relatively elevated (approximately 11 kg ha(-1) year(-1)). These results reveal the influence of human activity over the biogeochemistry of coastal streams and also indicate the importance N export of Atlantic Forest to the ocean.

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The goal of this paper is study the global solvability of a class of complex vector fields of the special form L = partial derivative/partial derivative t + (a + ib)(x)partial derivative/partial derivative x, a, b epsilon C(infinity) (S(1) ; R), defined on two-torus T(2) congruent to R(2)/2 pi Z(2). The kernel of transpose operator L is described and the solvability near the characteristic set is also studied. (c) 2008 Elsevier Inc. All rights reserved.

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The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

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Complex networks obtained from real-world networks are often characterized by incompleteness and noise, consequences of imperfect sampling as well as artifacts in the acquisition process. Because the characterization, analysis and modeling of complex systems underlain by complex networks are critically affected by the quality and completeness of the respective initial structures, it becomes imperative to devise methodologies for identifying and quantifying the effects of the sampling on the network structure. One way to evaluate these effects is through an analysis of the sensitivity of complex network measurements to perturbations in the topology of the network. In this paper, measurement sensibility is quantified in terms of the relative entropy of the respective distributions. Three particularly important kinds of progressive perturbations to the network are considered, namely, edge suppression, addition and rewiring. The measurements allowing the best balance of stability (smaller sensitivity to perturbations) and discriminability (separation between different network topologies) are identified with respect to each type of perturbation. Such an analysis includes eight different measurements applied on six different complex networks models and three real-world networks. This approach allows one to choose the appropriate measurements in order to obtain accurate results for networks where sampling bias cannot be avoided-a very frequent situation in research on complex networks.

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Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.

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Differently from theoretical scale-free networks, most real networks present multi-scale behavior, with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by concentric (or hierarchical) measurements. This paper extends previous methodologies based on concentric measurements, by studying the possibility of using agglomerative clustering methods, in order to obtain a set of functional groups of nodes, considering particular institutional collaboration network nodes, including various known communities (departments of the University of Sao Paulo). Among the interesting obtained findings, we emphasize the scale-free nature of the network obtained, as well as identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along concentric levels, contrariwise to the non-uniform pattern found in theoretical scale-free networks such as the BA model. (C) 2008 Elsevier B.V. All rights reserved.

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The comprehensive characterization of the structure of complex networks is essential to understand the dynamical processes which guide their evolution. The discovery of the scale-free distribution and the small-world properties of real networks were fundamental to stimulate more realistic models and to understand important dynamical processes related to network growth. However, the properties of the network borders (nodes with degree equal to 1), one of its most fragile parts, remained little investigated and understood. The border nodes may be involved in the evolution of structures such as geographical networks. Here we analyze the border trees of complex networks, which are defined as the subgraphs without cycles connected to the remainder of the network (containing cycles) and terminating into border nodes. In addition to describing an algorithm for identification of such tree subgraphs, we also consider how their topological properties can be quantified in terms of their depth and number of leaves. We investigate the properties of border trees for several theoretical models as well as real-world networks. Among the obtained results, we found that more than half of the nodes of some real-world networks belong to the border trees. A power-law with cut-off was observed for the distribution of the depth and number of leaves of the border trees. An analysis of the local role of the nodes in the border trees was also performed.

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The properties of complex networks are highly Influenced by border effects frequently found as a consequence of the finite nature of real-world networks as well as network Sampling Therefore, it becomes critical to devise effective means for sound estimation of net work topological and dynamical properties will le avoiding these types of artifacts. In the current work, an algorithm for minimization of border effects is proposed and discussed, and its potential IS Illustrated with respect to two real-world networks. namely bone canals and air transportation (C) 2009 Elsevier B.V. All rights reserved.

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Brazilian sugarcane spirits were analyzed to elucidate similarities and dissimilarities by principal component analysis. Nine aldehydes, six alcohols, and six metal cations were identified and quantified. Isobutanol (LD 202.9 mu gL-1), butiraldehyde (0.08-0.5 mu gL-1), ethanol (39-47% v/v), and copper (371-6068 mu gL-1) showed marked similarities, but the concentration levels of n-butanol (1.6-7.3 mu gL-1), sec-butanol (LD 89 mu gL-1), formaldehyde (0.1-0.74 mu gL-1), valeraldehyde (0.04-0.31 mu gL-1), iron (8.6-139.1 mu gL-1), and magnesium (LD 1149 mu gL-1) exhibited differences from samples.

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An efficient and practical synthesis of tellurium tetrachloride from elemental tellurium and sulfuryl chloride is described. (C) 2008 Elsevier Ltd. All rights reserved.