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The characteristics of optical and microwave remote sensing (active and passive) data have been discussed in monitoring and management of desert regions.
These implications of using administrative data have been discussed in our previous work [ 21].
The data have been discussed extensively in previous papers [38,48,49]; here we only provide a brief overview.
The new features in SHELXL for refinement against neutron data have been discussed recently by Gruene et al. (2014 ▶).
As many issues to the motivation and examination of this kind of data have been discussed in the previous review, I will not dwell on them here.
Alternatives to the use of Hill's considerations for assessing causality for toxicologic data have been discussed (Gray et al. 2001; Guzelian et al. 2005; Weed 2005).
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Additionally, the sensor mote platform that harvests the corrosion energy has been designed for corrosion monitoring, and then how to network these sensors to remotely access the corrosion data has been discussed.
The quality of the case study data has been discussed elsewhere[ 28].
The limitation of SITS-ISTR data has been discussed extensively in previous publications.
However, an overall low specific activity for PrpC was detected, and difficulties to correlate transcriptome and proteome data has been discussed previously: differing half-life times of RNA and protein molecules and differing RNA and protein turnover can have a large impact on the obtained data (Hedge et al. 2003).
Various challenges related to data center have been discussed and neural network has been implemented to build the mathematical framework.
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