8 resultados para Average method

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


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Definition of the long-term variation of the geomagnetic virtual dipole moment requires more reliable paleointensity results. Here, we applied a multisample protocol to the study of the 130.5 Ma Ponta Grossa basaltic dikes (southern Brazil) that carry a very stable dual-polarity magnetic component. The magnetic stability of the samples wits checked using thermomagnetic curves and by monitoring the magnetic Susceptibility evolution through the paleointensity experiments. Twelve sites containing the least alterable samples were chosen for the paleointensity measurements. Although these rocks failed stepwise double-heating experiments, they yielded coherent results in the multisample method for all sites but one. The coherent sites show low to moderate field intensities between 5.7 +/- 0.2 and 26.4 +/- 0.7 mu T (average 13.4 +/- 1.9 mu T). Virtual dipole moments for these sites range from 1.3 +/- 0.04 to 6.0 +/- 0.2 x 10(22) A m(2) (average 2.9 +/- 0.5 x 10(22) A m(2)). Our results agree with the tendency for low dipole moments during the Early Cretaceous, immediately prior to the Cretaceous Normal Superchron (CNS). The available paleointensity database shows a strong variability of the field between 80 and 160 Ma. There seems to be no firm evidence for a Mesozoic Dipole Low, but a long-term tendency does emerge from the data with the highest dipole moments Occurring at the middle of the CNS.

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Knowing the best 1D model of the crustal and upper mantle structure is useful not only for routine hypocenter determination, but also for linearized joint inversions of hypocenters and 3D crustal structure, where a good choice of the initial model can be very important. Here, we tested the combination of a simple GA inversion with the widely used HYPO71 program to find the best three-layer model (upper crust, lower crust, and upper mantle) by minimizing the overall P- and S-arrival residuals, using local and regional earthquakes in two areas of the Brazilian shield. Results from the Tocantins Province (Central Brazil) and the southern border of the Sao Francisco craton (SE Brazil) indicated an average crustal thickness of 38 and 43 km, respectively, consistent with previous estimates from receiver functions and seismic refraction lines. The GA + HYPO71 inversion produced correct Vp/Vs ratios (1.73 and 1.71, respectively), as expected from Wadati diagrams. Tests with synthetic data showed that the method is robust for the crustal thickness, Pn velocity, and Vp/Vs ratio when using events with distance up to about 400 km, despite the small number of events available (7 and 22, respectively). The velocities of the upper and lower crusts, however, are less well constrained. Interestingly, in the Tocantins Province, the GA + HYPO71 inversion showed a secondary solution (local minimum) for the average crustal thickness, besides the global minimum solution, which was caused by the existence of two distinct domains in the Central Brazil with very different crustal thicknesses. (C) 2010 Elsevier Ltd. All rights reserved.

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The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode-cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode-anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode-cathode axis and 2.02 mm parallel to the anode-cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.

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The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.

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In this work, we report on the magnetic properties of nickel nanoparticles (NP) in a SiO(2)-C thin film matrix, prepared by a polymeric precursor method, with Ni content x in the 0-10 wt% range. Microstructural analyses of the films showed that the Ni NP are homogenously distributed in the SiO(2)-C matrix and have spherical shape with average diameter of similar to 10 nm. The magnetic properties reveal features of superparamagnetism with blocking temperatures T (B) similar to 10 K. The average diameter of the Ni NP, estimated from magnetization measurements, was found to be similar to 4 nm for the x = 3 wt% Ni sample, in excellent agreement with X-ray diffraction data. M versus H hysteresis loops indicated that the Ni NP are free from a surrounding oxide layer. We have also observed that coercivity (H (C)) develops appreciably below T (B), and follows the H (C) ae [1 - (T/T (B))(0.5)] relationship, a feature expected for randomly oriented and non-interacting nanoparticles. The extrapolation of H (C) to 0 K indicates that coercivity decreases with increasing x, suggesting that dipolar interactions may be relevant in films with x > 3 wt% Ni.

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Bismuth germanate films were prepared by dip coating and spin coating techniques and the dependence of the luminescent properties of the samples on the resin viscosity and deposition technique was investigated. The resin used for the preparation of the films was obtained via Pechini method, employing the precursors Bi(2)O(3) and GeO(2). Citric acid and ethylene glycol were used as chelating and cross-linking agents, respectively. Results from X-ray diffraction and Raman spectroscopy indicated that the films sintered at 700 degrees C for 10 h presented the single crystalline phase Bi(4)Ge(3)O(12). SEM images of the films have shown that homogeneous flat films can be produced by the two techniques investigated. All the samples presented the typical Bi(4)Ge(3)O(12) emission band centred at 505 nm. Films with 3.1 mu m average thickness presented 80% of the luminescence intensity registered for the single crystal at the maximum wavelength. Published by Elsevier B.V.

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We report a novel method for calculating flash points of acyclic alkanes from flash point numbers, N(FP), which can be calculated from experimental or calculated boiling point numbers (Y(BP)) with the equation N(FP) = 1.020Y(BP) - 1.083 Flash points (FP) are then determined from the relationship FP(K) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901 For it data set of 102 linear and branched alkanes, the correlation of literature and predicted flash points has R(2) = 0.985 and an average absolute deviation of 3.38 K. N(FP) values can also be estimated directly from molecular structure to produce an even closer correspondence of literature and predicted FP values. Furthermore, N(FP) values provide a new method to evaluate the reliability of literature flash point data.

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Flash points (T(FP)) of organic compounds are calculated from their flash point numbers, N(FP), with the relationship T(FP) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901. In turn, the N(FP) values can be predicted from boiling point numbers (Y(BP)) and functional group counts with the equation N(FP) = 0.974Y(BP) + Sigma(i)n(i)G(i) + 0.095 where G(i) is a functional group-specific contribution to the value of N(FP) and n(i) is the number of such functional groups in the structure. For a data set consisting of 1000 diverse organic compounds, the average absolute deviation between reported and predicted flash points was less than 2.5 K.