Activation analysis in a multitechnique study of trace element imbalances in age-related neurological diseases

Ehmann, W. D.; Ding, Xiaxin; Khare, S. S.; Lovell, Mark A.; Ni, B. F.; Tandon, Lav; Vance, D. E.; Wenstrup, D. E.

doi:10.1007/bf02040894

Cited by 6 publications

(1 citation statement)

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“…The idea of joint analysis of results of polytypic experiments can be found in the literature (Ehmann et al 1993;Bishop et al 2004, Denecke et al 2007. Also, commercial software products are available, which support this analysis for certain experimental techniques.…”

Section: Introductionmentioning

confidence: 99%

Multi-Technique Data Treatment For Multi-Spectral Image Visualization

Chukalina¹,

Somogyi²,

Nikolaev³

et al. 2008

ECMS 2008 Proceedings Edited By: L. S. Louca, Y. Chrysanthou, Z. Oplatkova, K. Al-Begain

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The 'in situ' investigation of different biological, chemical, physical, and environmental processes often requires the knowledge of these sample characteristics with high-(sub)micro-meter-resolution as a valuable complement to the average bulk information. Different microprobe techniques can meet these requirements and their possible combinations would offer the opportunity of thorough study of a given sample or a scientific problem. Although some of the existing software packages allow for multivariate statistical treatment of data-sets obtained by a given experimental technique, none of them permits a simultaneous statistical treatment of datasets obtained by different experimental techniques, e.g. by simultaneous scanning μ-XRF (X-ray fluorescence) and μ-XRD (X-ray diffraction), or measured at several set-ups/beamlines/synchrotrons /laboratories (e.g. combined μ-IR and μ-XRF spectroscopy). The goal of this paper is to describe in detail a sequence of operations which can be applied to multi-technique datasets for obtaining a complete set of sample characteristics and to show that at present this can be realised automatically.

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Section: Introductionmentioning

confidence: 99%