The results obtained showed a precision of 2% (1σ) and the results deviated from the expected values by < 4% on average.
This allows us to conclude that in post-float Australia the results deviate significantly from the mainstream Friedman paradigm on inflation and its uncertainty.
In this paper we report molecular dynamics (MD) simulation results on the fundamental and secondary resonant frequencies f of cantilever graphene nanostrips with different layer number n and different nanostrip length L. The results deviate significantly from the prediction of not only the Euler Bernoulli beam theory (f∝nL−2), but also the Timoshenko's model.
For higher loads on the frame, the results deviate significantly from the linearity.
Therefore, to assess how gender influences the formation of transitive relationships we observe to what extent the results deviate from the ones expected according to our null model, by comparing the proportion of triangles observed in the real networks with the average proportion obtained over 10 of the networks in which we have reshuffled user attributes.
Since the results deviate very little, they are not shown here in detail, but it should be noted that the proposed method with robust PCA achieved an average accuracy of 90.3 % while the proposed method with PCA achieved an average accuracy of 90.0 %, which is not significantly different (p>0.5, paired t-test).
Similar results are observed with AdaBoost, Bagging and decision tree as were observed for the random forest algorithm, while for the other learning algorithms that are neither tree-based nor ensemble models, the results deviate from the previous pattern.
The second GRADE criterion the inconsistency of results across studies included in a systematic review means that the results deviate from each other, and this naturally leads to decreased confidence in the effectiveness estimates.
Despite the small overlap of RAMs between Ctr vs. MG and UG vs. MG comparisons, the genomic and CGI distributions of the differential regions were highly similar, and unlike the Ctr vs. UG comparison, the results deviated from the genomic background.
At macro scales the optimised geometry agrees well with Murray's Law for optimal branching of vascular networks; however, at nanoscales, the optimum result deviates from Murray's Law, and a corrected equation is presented.
