Our results are consistent with earlier research5,24,25,26,30,31, which collectively indicates that changes in ENSO-driven precipitation variability can be explained in terms of changes in four factors: (i) mean-state moisture content, (ii) the amplitude of ENSO-driven SST variability, (iii) spatially dependent changes in mean-state SST and (iv) in the structure of ENSO-driven SST variability.
Furthermore, future studies should confirm that variability can be reduced in our clinical in vivo data when either the pressure applied to the probe or the time delay between contact and acquisition is controlled.
The overall results suggest that no great negative effect on genetic variability can be expected in the short time in the population analysed by selection of only ARR/ARR males.
Some sequence variability can be observed in the HyLIMP stem (italicized in Fig. 5), usually with complementary mutations in the other branch restoring Watson-Crick base-pairing.
In addition, within-field spatial variability can be considerable in New York, requiring (1) high density sampling (1 stalk per acre at a minimum) for accurate assessment of whole fields, or (2) targeted sampling based on yield zones, elevations, or soil management units.
In documenting all existing surrounding SES-characters, variability can be managed in a traceable way.
Similar levels of variability can be seen in the projected costs of formal and informal care of dementia in Australia.
Thus, stress variability can be characterised in any convenient coordinate system.
Thus, extensive variability can be found in both the total amount of charge as well as how the charge is distributed within the homogalacturonan region.
Despite current findings that consumers, on average, have negative attitudes to biotechnologies such as cloning and genetic engineering, considerable variability can be found in the direction and strength of these attitudes.
