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Reddit, Foursquare and Quora were among the sites affected by Amazon Web Services suffering network latency and connectivity errors this morning, according to the company's own status dashboard.
Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions.
Transcription factors with high correlation coefficients suggest robustness of the results against connectivity errors.
Since NCA deductions are dependent on the connectivity graph generated by ChIP-chip assays, we endeavoured to determine the effects of connectivity errors on our TFA profiles.
To assess the effect of connectivity errors on our results, we altered up to 10% of the connectivity graph for every subnetwork, by randomly deleting and inserting connections between transcription factors and genes.
With the same sensitivity criterion, 2 (Dand1 and Rlm1) of the 5 putative cell cycle-related regulators and 1 (Fhl1) of the 4 putative forkhead interaction partners were determined to be robust to connectivity errors.
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Indeed, according to predictive theories of perception, neural units sensitive to predictions (i.e. RE voxels) and prediction error (RS voxels) differ in their connectivity, with error signals flowing forward in a bottom-up fashion, and predictions fed back from higher cortical stages in a top-down manner.
The increasing D2D communication in 5G networks has renewed interest in an effective middleware design for MANET where application developers face various challenges such as unstable connectivity, high error rate, mobility induced disruption and disconnection, and limited battery power.
Our results demonstrate that during incidental learning of audio-visual associations changes in both regional activity and underlying connectivity reflect prediction errors.
Such applications require high-speed connectivity and strong error protection.
These results suggest that our analysis is robust to errors in connectivity.
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