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We next tested whether cross-frequency coupling was related to error adaptation.
MF theta alpha coupling significantly predicted error adaptation at 500 ms (r = 0.54, P = 0.018, Fig. 3 D 1), but OC alpha gamma coupling did not significantly predict error adaptation at 300 700 ms (r = 0.378, P = 0.156).
Subsequent exploratory correlation time course analyses revealed that MF theta alpha coupling was correlated with error adaptation selectively at 500 ms (Fig. 3 D 2), and OC alpha gamma coupling predicted error adaptation during stimulus presentation and response.
The results were also present when statistically regressing out trial count from the behavioral error adaptation measure (Supplementary Fig. S2).
By contrast, genomes that were refactored without the design specification of tandem promoter addition had high error adaptation (〈 ξ〉 > 0.762), except for those refactored considering stress genes.
Hence, we distinguished between positive and negative error adaptation corresponding to environmental states where cell fitness achieved sub- or over-optimal growth, respectively.
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The complex inference was that people in the central region adopted bow-and-arrow technology as an integrated whole, a package deal (therefore, indirect bias), whereas people to the west assimilated the technology piecemeal (therefore, guided variation or trial-and-error adaptation).
Furthermore, we conduct a comparative study between adaptive inverse dynamics, prediction error based adaptation, and passivity based adaptation.
The L1 adaptive output feedback control architecture in this paper includes a state predictor, an error observer, adaptation laws, and a low-pass filter.
It consists of four significant enhancements: enhanced threshold-based training, dynamic input normalization, feedback-based quantization error threshold adaptation, and prediction confidence filtering and forwarding.
In order to make those data accessible, the individual data sets need to be collected, reviewed and harmonized in a number of aspects, including the systematic performance of plausibility checks, the minimization of error, the adaptation of the sequencing ranges and the standardized presentation (alignment and annotation) of the mtDNA haplotypes.
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