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One or both approaches allow to test an average number of patterns, denoted by N TEP in the following, significantly smaller than (N_{text {TEP}}^{max }).
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Both approaches allow carmakers to do things that would be far more complicated and expensive using conventional hardware and software.
Both approaches allow single pass imaging, thereby reducing phototoxicity and the risk of acceptor photobleaching.
Examining results from both approaches allows researchers to look at the data from different perspectives and extract the best possible amount of information from the data.
This combination of both approaches allowed us to look beyond the traditional method of change scores, as it created a hierarchy of outcomes for the QoL scores over time on the basis 1) of the degree of change and 2) of the classification of the total score.
The proposed LMI-based approach allows to estimate both delay margin and decay rate.
In both cases, the difference-in-difference approach allows to control for country and industry-size effects, thereby minimizing problems of omitted variable bias and other misspecifications.
This approach allows to reduce both acquisition and reconstruction times, whilst retaining the same reconstruction quality.
A repeated cell approach allows to simulate NCs and NWs.
The local approach allows to effectively detect partially occluded objects.
This approach allows to satisfy exactly the Piola compatibility condition.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com