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The PDF data sets were modelled using structure refinement methods implemented in the PDFgui package53.
Determining the structure corresponding to PDF data, the question tackled by Juhás and colleagues2, is just such an inverse problem.
Experimental and transported probability density function (PDF) data compare reasonably well.
On the other hand, PDF data provide detailed structural information enabling component finger printing as well as supplementary chemical information, for example, information about coordination and oxidation state.
Results show that the two materials may be clearly distinguished using the PDF data above a 15 Å distance.
On page 655 of this issue2, Juhás et al. present an intriguing solution to this question with a novel algorithm for reconstructing three-dimensional structures from 'pair distribution function' (PDF) data.
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Table 2 summarizes simple statistics of the estimation errors given by UM1 and UM2 for both PM10 and ozone, and Table 3, results of corresponding comparison on relative entropy at each indicated time scale, showing the percentage of the spatiotemporal estimates that passed the chi-square tests with the null hypothesis: the two pdfs (data and estimates) are the same.
To address the accuracy of score pdf modeling, we define two spectrum-specific pdfs, data-derived pdf (Dpdf) and model pdf (Mpdf).
European Commission representatives are quietly listening to and learning from (PDF) open data initiatives across Europe.
The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions.
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