978 resultados para spectra analysis


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LiAlO2 single crystals doped with Ti at concentration 0.2 at.% are grown by the Czochralskl technique with dimensions Phi 42 x 55 mm. Ti ions in the crystal are quadrivalence proven by comparing the absorption and fluorescence spectra of pure LiAlO2 and Ti: LiAlO2. After air and Li-rich atmosphere annealing, the absorption peaks in the range of 600-800nm disappear. We conclude that 682 and 756nm absorption peaks are attributed to the V-Li and V-O absorptions, respectively. The peaks at 716nm and 798nm may stem from the V-Li(+) and F+ absorptions. The colour-centre model can be applied to explain the experimental phenomena. Ti4+-doping produces more lithium vacancies in the LiAlO2 crystal. The intensities of [LiO4] and the associated bonds remain unchanged, which improves the anti-hydrolyzation and thermal stability of LiAlO2 crystals.

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The spectral decomposition analysis was applied to the optical absorption spectra of green and colorless beryl crystals from the Brazilian Eastern Pegmatitic province in the natural state, Submitted to heat treatment and irradiated with UV light The attributions of the lines were made taking into account highly accurate quantum mechanical calculations The deconvolution of the green beryl spectra revealed four lines, two of them around 12,000 cm(-1) (1 5eV) and two of them around 34,000 cm(-1) (4.2 eV) attributed to Fe(2+) and Fe(3+), respectively The deconvolution of the colorless beryl spectra without any treatment, after heating and for the same heat treatment followed by UV light irradiation revealed five lines The analysis of ratio relations showed that the lines at 36,400 cm(-1) (4.5 eV) and 41,400 cm(-1) (5 1 eV) belongs to a single defect attributed to a silicon dangling bond defect (=Si). Discussions and comparison with reported defects in quartz have supported the allocation of the lines at 61,000 cm(-1) (7.6 eV) and 43,800 cm(-1) (5 4 eV) to diamagnetic oxygen vacancy defect ( Si-Si ) and unrelaxed ( Si Si ) defect, respectively Finally, the line at 39.100 cm(-1) (4.8 eV), quite polarized along the c-axis, was attributed to a (Fe(2+) OH(-)) defect in the structural channels (C) 2009 Elsevier B V All rights reserved

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For many clustering algorithms, such as K-Means, EM, and CLOPE, there is usually a requirement to set some parameters. Often, these parameters directly or indirectly control the number of clusters, that is, k, to return. In the presence of different data characteristics and analysis contexts, it is often difficult for the user to estimate the number of clusters in the data set. This is especially true in text collections such as Web documents, images, or biological data. In an effort to improve the effectiveness of clustering, we seek the answer to a fundamental question: How can we effectively estimate the number of clusters in a given data set? We propose an efficient method based on spectra analysis of eigenvalues (not eigenvectors) of the data set as the solution to the above. We first present the relationship between a data set and its underlying spectra with theoretical and experimental results. We then show how our method is capable of suggesting a range of k that is well suited to different analysis contexts. Finally, we conclude with further  empirical results to show how the answer to this fundamental question enhances the clustering process for large text collections.

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The platform-independent software package consisting of the oligonucleotide mass assembler (OMA) and the oligonucleotide peak analyzer (OPA) was created to support the analysis of oligonucleotide mass spectra. It calculates all theoretically possible fragments of a given input sequence and annotates it to an experimental spectrum, thus, saving a large amount of manual processing time. The software performs analysis of precursor and product ion spectra of oligonucleotides and their analogues comprising user-defined modifications of the backbone, the nucleobases, or the sugar moiety, as well as adducts with metal ions or drugs. The ability to expand the library of building blocks and to implement individual structural variations makes it extremely useful for supporting the analysis of therapeutically active compounds. The functionality of the software tool is demonstrated on the examples of a platinated doublestranded oligonucleotide and a modified RNA sequence. Experiments also reveal the unique dissociation behavior of platinated higher-order DNA structures.