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Severity of amygdala pathology was a predictive factor for memory for emotional items, and severity of hippocampal pathology predicted memory performance for neutral and emotional items (Richardson et al., 2004a).
None of the other phonological features predicted memory performance (all F < 1.0, all p > 0.33).
In facilitation regions such as parahippocampal cortex, greater activity during encoding predicted memory success.
In reorienting regions such as right temporoparietal junction, greater activity during encoding predicted memory failure.
When examining memory for the size adjective only, none of the phonological properties predicted memory performance (all F < 2.9, all p > 0.10).
In the additional analyses at the item level, none of the phonological properties predicted memory performance (all F < 2.5, p > 0.13).
Similar(46)
(B ) The number of episodic-center replays with matches between the predicted memory-guided subtask and the presence of a barrier at the center of the maze, across all rats.
The time spent fixating a word did predict memory performance in the intentional encoding experiments, but critically, the frequency effect on hit rates was independent of this effect.
Irregular parallel algorithms pose a significant challenge for achieving high performance because of the difficulty predicting memory access patterns or execution paths.
The Sparse Linear Algebra Memory Model (SLAMM) is implemented by a source-to-source translator that accepts a MATLAB specification of an algorithm and adds code to predict memory traffic.
Using the Pareto probability distribution for the size of the video frames (of the characteristic video trace) and self-similarity we develop a non-asymptotic model which predicts memory buffer size for a required quality of service.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com