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Numerical analysis of Markovian models is relevant for performance evaluation and probabilistic analysis of systems' behavior from several fields in science and engineering.
In grappling sports (e.g. judo, wrestling and Brazilian jiu-jitsu), the mesomorphy component has been highlighted as the most relevant for performance [8, 10, 11], and one that also allows discrimination of athletes from different performance levels [27, 28].
Finally, the mode of energy achievement is relevant for performance and competitiveness (e.g. [42], [43]).
Spider-web diagrams allow easy comparisons across multiple dimensions, which is relevant for performance measurement.
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The surface with a long range order, i.e. single crystal Pd (1 0 0), was far more active that the corresponding polycristalline surface, suggesting an actual correlation between structure and reactivity, extremely relevant for performances.
All the relevant characteristics for performance estimation can then be easily extracted: application throughput, latency, utilization of resources, memory utilization, etc.
The performances of the ANNs were determined by the Taguchi method considering factors relevant for ANNs' performance.
This motivational salience signal is highly relevant for behavioral performance, which predicts successful detection of a near-threshold sound (Lin and Nicolelis, 2008) as well as performance in the oddball task.
While the BF motivational salience signal is highly relevant for behavioral performance, which predicts successful detection of a near-threshold sound (Lin and Nicolelis, 2008) as well as performance in the oddball task, the relationship between BF activity and behavioral performance is more complex and involves more than the phasic bursting response that encodes motivational salience.
First, metrics that are relevant for the performance of a DTN system are identified.
Further, the location of land use and land cover change (LULCC) is highly relevant for the performance of certain ES (Bryan and Crossman 2008; Rounsevell et al. 2012).
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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