For the evaluation of biocrusts functions and their impact on soil carbon pools, the analysis of the interrelationship between photosynthetic activity and the variations of spatial distribution pattern and types of biocrust is indispensable.
Included in the analysis of the interrelationship of disease and pregnancy were only the data of the first pregnancy beyond 16 weeks gestational age after the diagnosis of Crohn's disease was made, further mentioned as the index pregnancy.
In the area of evaluation, for example, analysis of the interrelationship between concepts within a knowledge network (concept mapping analysis, CMA) has been proposed as a tool for evaluating both pre-existing knowledge and knowledge gained as a result of an educational intervention [ 5, 6].
Obesity and in particular abdominal obesity has been recognized to be linked to an increase in cardiovascular risk and therefore the present analysis on the interrelationship of both measures and their relation to cardiovascular risk has been conducted.
It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient.
The analysis of the interrelationships between these factors provides a useful tool to predict the effects of different "technical designs" on the human resources they affect.
An analysis of the interrelationships and possible correlations between bone, cartilage and inflammation metabolism reflected by biomarkers is invariably useful but was overlooked.
The analysis of the interrelationships between these factors provides a useful tool to predict the effects of different 'technical designs' on the elements of health systems that they affect.
Figure 5 illustrates Metacore's analysis of the interrelationships of the identified mitotic regulatory genes including STAG2, NEK2, KPNA4, IPO5, TNPO1, CCNB1, CDK1, CDK6, NCAPG, NCAPG2, TOP2A, NUF2, CENPE, CENPF, ZWILCH, PDS5A, WEE1, KIF11, CHUK, and PPP1CB.
This study incorporates both objective and subjective measures of all these potential treatment effects, thereby permitting an analysis of the interrelationships among these factors and their association with treatment satisfaction and preference.
The use of fluorescent reporters to quantify DNA damage and p53 levels in live cells provided a quantitative analysis of the complex interrelationships between both processes.
