Sentence examples for effects that support from inspiring English sources
Finally, the consolidation of international migration is usually related to network effects that support transnational movements generated by particular institutions in the host and the receiving country.
We turn around the counterfactual from the previous experiment and apply it to pre-crisis projects ("−1bl.,+1n").. Given one additional bidder and lower capacity utilization before the crisis on the very same projects before the crisis leads to counterfactual effects that support the evidence from the first counterfactual.
EVs derived from cancer mostly have immunosuppressive effects that support tumor progression and metastasis.
Most of the genes we tested have both cilia and cell cycle effects that support the idea that these two cellular processes are intimately involved.
These results illustrate the scale of mortality effects that supported programs may have achieved in recent years, despite margins of uncertainty and covering only selected intervention components.
In collagen-induced arthritis, a PAD inhibitor reduced the severity of arthritis, an effect that supports an arthritogenic role for citrullination and ACPA production in RA [45].
Reviewers complimented the graphics for both the ghostly "Crossroads" and the fire-ravaged real world; Butts expressed that "the levels all benefit from great color choices and fantastic lighting effects that really support the mood".
In addition, a large review carried out by Riemsma et al. [ 13] found mainly mixed effects in the five trials aimed at dietary change, with only two trials reporting significant effects that would support stage-based intervention.
We use Y. lipolytica to evaluate the effects of each mutation, revealing a set of highly variable effects that provide varying support for their assignment as pathogenic.
To this end, the current study uses actual differences in curves between genotypes from real data for effects that have strong support for representing true biology.
In several cases you make strong statements about effects that are not supported by your stats.
