942 resultados para Funerary artifacts


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Este artigo descreve o uso de artefatos funerários na reconstituição histórica do processo de trabalho em marmorarias instaladas no município de São Carlos (São Paulo, Brasil), no período 1890-1950. Observação direta e registro fotográfico de artefatos funerários, exame de ferramentas de trabalho e utilização de fontes orais permitiram a reconstituição do processo de trabalho. A composição química de fragmentos de artefatos funerários foi determinada por Difração de Raios X e Microscopia Eletrônica de Varredura, evidenciando matérias-primas e sua combinação e uso no processo de trabalho. Considerando-se as etapas produtivas da indústria de rochas ornamentais (extração, serragem e beneficiamento final), os artefatos funerários indicam que as marmorarias inseriam-se na etapa de beneficiamento final. As marmorarias integravam os setores de base técnica artesanal da indústria brasileira, apresentando: baixo grau de concentração de capital e de operários; predomínio da habilidade do ofício especializado; separação pouco nítida entre trabalhadores e instrumentos de trabalho; identificação do trabalhador com o produto. Artefatos de mármore e granito eram destinados a brasileiros de segmentos sociais abastados, durante o início da imigração na cidade de São Carlos (final do século XIX). A partir de 1920, italianos incorporam-se a clientela dos marmoristas, indicando a mobilidade social do imigrante na cidade.

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A funerary gold mask from the Museum of Sican, Ferranafe, Peru was analyzed in 30 different areas using a portable equipment using energy-dispersive X-ray fluorescence. It was deduced from the measurements that the main sheet of the mask and the majority of the pendants have a similar composition and are made of tumbaga, which means a poor gold alloy enriched at the surface by depletion gilding, and have a similar `equivalent` gilding thickness of about 5 mu m. The nose, also on tumbaga, has different composition and a thickness of about 8 mu m. The clamps are on gilded or on silvered copper. The red pigment dispersed on the surface of the mask is cinnabar. Copyright (C) 2009 John Wiley & Sons, Ltd.

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Radiographs are commonly used to assess articular reduction of the distal tibia (pilon) fractures postoperatively, but may reveal malreductions inaccurately. While Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are potential 3D alternatives they generate metal-related artifacts. This study aims to quantify the artifact size from orthopaedic screws using CT, 1.5T and 3T MRI data. Three screws were inserted into one intact human cadaver ankle specimen proximal to and along the distal articular surface, then CT, 1.5T and 3T MRI scanned. Four types of screws were investigated: titanium alloy (TA), stainless steel (SS) (Ø = 3.5 mm), cannulated TA (CTA) and cannulated SS (CSS)(Ø = 4.0 mm, Ø empty core = 2.6 mm). 3D artifact models were reconstructed using adaptive thresholding. The artifact size was measured by calculating the perpendicular distance from the central screw axis to the boundary of the artifact in four anatomical directions with respect to the distal tibia. The artifact sizes (in the order of TA, SS, CTA and CSS) from CT were 2.0 mm, 2.6 mm, 1.6 mm and 2.0 mm; from 1.5T MRI they were 3.7 mm, 10.9 mm, 2.9 mm, and 9 mm; and 3T MRI they were 4.4 mm, 15.3 mm, 3.8 mm, and 11.6 mm respectively. Therefore, CT can be used as long as the screws are at a safe distance of about 2 mm from the articular surface. MRI can be used if the screws are at least 3 mm away from the articular surface except SS and CSS. Artifacts from steel screws were too large thus obstructed the pilon from being visualised in MRI. Significant differences (P < 0.05) were found in the size of artifacts between all imaging modalities, screw types and material types, except 1.5T versus 3T MRI for the SS screws (P = 0.063). CTA screws near the joint surface can improve postoperative assessment in CT and MRI. MRI presents a favourable non-ionising alternative when using titanium hardware. Since these factors may influence the quality of postoperative assessment, potential improvements in operative techniques should be considered.

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Artifacts in the form of cross peaks have been observed along two- and three-quantum diagonals in single-quantum two-dimensional correlated (COSY) spectra of several peptides and oligonucleotides. These have been identified as due to the presence of a non-equilibrium state of kind I (a state describable by populations which differ from equilibrium) of strongly coupled spins carried over from one experiment to the next in the COSY algorithm.

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One of the most important applications of adaptive systems is in noise cancellation using adaptive filters. Ln this paper, we propose adaptive noise cancellation schemes for the enhancement of EEG signals in the presence of EOG artifacts. The effect of two reference inputs is studied on simulated as well as recorded EEG signals and it is found that one reference input is enough to get sufficient minimization of EOG artifacts. This has been verified through correlation analysis also. We use signal to noise ratio and linear prediction spectra, along with time plots, for comparing the performance of the proposed schemes for minimizing EOG artifacts from contaminated EEG signals. Results show that the proposed schemes are very effective (especially the one which employs Newton's method) in minimizing the EOG artifacts from contaminated EEG signals.

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EEG recordings are often contaminated with ocular artifacts such as eye blinks and eye movements. These artifacts may obscure underlying brain activity in the electroencephalogram (EEG) data and make the analysis of the data difficult. In this paper, we explore the use of empirical mode decomposition (EMD) based filtering technique to correct the eye blinks and eye movementartifacts in single channel EEG data. In this method, the single channel EEG data containing ocular artifact is segmented such that the artifact in each of the segment is considered as some type of slowly varying trend in the dataand the EMD is used to remove the trend. The filtering is done using partial reconstruction from components of the decomposition. The method is completely data dependent and hence adaptive and nonlinear. Experimental results are provided to check the applicability of the method on real EEG data and the results are quantified using power spectral density (PSD) as a measure. The method has given fairlygood results and does not make use of any preknowledge of artifacts or the EEG data used.