972 resultados para Droplet spectra
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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New compounds with the general formulae [(NH3)(L)ZnFE(CO4] (L = ethylenediamine, N-methylethylenediamine, N,N′-dimethylethylenediamine and 1,3-propanediamine) were prepared and studied by vibrational spectroscopy. The data suggest that they may be formulated as monomers with a trigonal bipyramidal configuration around the iron atom. © 1984.
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The thermal decomposition of pyrrolidinedithiocarbamate and piperidinedithiocarbamate complexes of CoII, NiII, CuII and HgII have been studied by thermogravimetry and differential scanning calorimetry. The decomposition intermediates and final products were identified by their X-ray diffraction patterns. The i.r. spectra are discussed in terms of the thermal decomposition pathways.
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Assuming massive constituent gluons the mass spectroscopy of glueballs and hybrids is analysed in the framework of the potential model. Only pairwise potentials are considered.
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Results of photoluminescence measurements for natural and synthetic alexandrite (BeAl2O4:Cr3+) are presented, where the samples are excited by the 488 nm line of an Ar+ laser, at different temperatures. The main issue is the analysis of the Cr3+ transition in the chrysoberyl matrix (BeAl2O4), with major technological application as active media for laser action. Results indicate anomalous behavior of Cr3+ transition depending on the measurement temperature. A simple model to explain the phenomena is suggested.
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The aim of this work was to evaluate the effect of the addition of different surfactants in physical and chemical properties of spray solutions, droplets spectra and drift potential on agricultural spraying. The surfactants and concentrations (v v-1) were: Haiten (0.1%), Antideriva and Intec (0.05% and 0.1%). The following characteristics were analyzed: surface tension, viscosity, density and electric conductivity. The droplet size spectrum was determined by a laser particle analyzer (Mastersizer S®, version 2.15) including measurements of volume medium diameter (VMD), the percent of droplets below 50 and 100 μm (V50 e V100) and index span. In order to estimate the drift potential, a series of wind tunnel tests were performed with a Teejet XR 8003 flat fan nozzle at 200 kPa (medium droplets) used to apply the spray solutions containing water, the adjuvants and a food color dye (Brilliant blue FD & C no 1) at 0,6% m v-1. The drift was collected on nylon strips transversally fixed along the tunnel at different distances from the nozzle and different high from the bottom part of the tunnel. Drift deposits were evaluated by spectrophotometry. The results showed that the addition of adjuvants changed physical and chemical properties of spray solutions in different magnitudes according to the surfactant. Surfactants changed the droplet spectrum and drift potential, indicating that higher VMD and smaller V100 induced higher percentage of drift.
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In this work, we present a theoretical photoluminescence (PL) for p-doped GaAs/InGaAsN nanostructures arrays. We apply a self-consistent method in the framework of the effective mass theory. Solving a full 8 x 8 Kane's Hamiltonian, generalized to treat different materials in conjunction with the Poisson equation, we calculate the optical properties of these systems. The trends in the calculated PL spectra, due to many-body effects within the quasi-two-dimensional hole gas, are analyzed as a function of the acceptor doping concentration and the well width. Effects of temperature in the PL spectra are also investigated. This is the first attempt to show theoretical luminescence spectra for GaAs/InGaAsN nanostructures and can be used as a guide for the design of nanostructured devices such as optoelectronic devices, solar cells, and others.
Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution
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The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.