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000207281 1001_ $$0P:(DE-HGF)0$$aMak, Rachel$$b0
000207281 245__ $$aNon-Negative Matrix Analysis for Effective Feature Extraction in X-ray Spectromicroscopy
000207281 260__ $$aCambridge [u.a.]$$bSoc.$$c2014
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000207281 520__ $$aX-Ray absorption spectromicroscopy provides rich information on the chemical organization of materials down to the nanoscale. However, interpretation of this information in studies of “natural” materials such as biological or environmental science specimens can be complicated by the complex mixtures of spectroscopically complicated materials present. We describe here the shortcomings that sometimes arise in previously-employed approaches such as cluster analysis, and we present a new approach based on non-negative matrix approximation (NNMA) analysis with both sparseness and cluster-similarity regularizations. In a preliminary study of the large-scale biochemical organization of human spermatozoa, NNMA analysis delivers results that nicely show the major features of spermatozoa with no physically erroneous negative weightings or thicknesses in the calculated image.
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000207281 7001_ $$0P:(DE-HGF)0$$aLerotic, Mirna$$b1
000207281 7001_ $$0P:(DE-H253)PIP1011659$$aFleckenstein, Holger$$b2
000207281 7001_ $$0P:(DE-HGF)0$$aWild, Stefan M.$$b3
000207281 7001_ $$0P:(DE-HGF)0$$aLeyffer, Sven$$b4
000207281 7001_ $$0P:(DE-HGF)0$$aSheynkin, Yefim$$b5
000207281 7001_ $$0P:(DE-H253)PIP1018246$$aJacobsen, Chris$$b6$$eCorresponding author
000207281 7001_ $$0P:(DE-H253)PIP1016741$$aVogt, Stefan$$b7
000207281 773__ $$0PERI:(DE-600)1472891-6$$a10.1039/C4FD00023D$$gVol. 171, p. 357 - 371$$p357 - 371$$tFaraday discussions$$v171$$x1364-5498$$y2014
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