<p> X-ray absorption spectromicroscopy combines microscopy and spectroscopy to provide rich information about the chemical organization of materials down to the nanoscale. But with richness also comes complexity: natural materials such as biological or environmental science specimens can be composed of complex spectroscopic mixtures of different materials. The challenge becomes how we could meaningfully simplify and interpret this information. Approaches such as principal component analysis and cluster analysis have been used in previous studies, but with some limitations that we will describe. This leads us to develop a new approach based on a development of non-negative matrix approximation (NNMA) analysis with both sparseness and spectra similarity regularizations. We apply this new technique to simulated spectromicroscopy datasets as well as a preliminary study of the large-scale biochemical organization of a human sperm cell. NNMA analysis is able to select major features of the sperm cell without the physically erroneous negative weightings or thicknesses in the calculated image which appeared in previous approaches.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3669280 |
| Date | 29 January 2015 |
| Creators | Mak, Rachel Y. C. |
| Publisher | Northwestern University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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