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The difficulties we found fell into five categories as listed in Table 1: the experimental subject itself (difficulty I), variables (difficulty II, A F), measures of experimental outcomes (difficulty III), dealing with variability (difficulty IV, A E), and interpreting experimental conclusions (difficulty V, A B).
Dealing with variability is an important matter affecting many aspects of systems-on-chips (SoC) design.
Software product line (SPL) community has allocated huge amount of effort to develop various approaches to dealing with variability related challenges during the last two decade.
Furthermore, there is no consensus on the best approach for dealing with variability in the treatment selection process across clinical centers.
Determining the appropriate level of capacity is often challenging, particularly when dealing with variability from multiple sources.
3. Dealing with variability of phenotypic responses: A challenge in analyzing data from whole-organism screens involving schistosomes is that they cannot yet be cloned.
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This chapter deals with variability at a specific level, the organismal phenotype.
We argue that our best attempts to assess the ability of states to deal with variability in the future rest with considering how agreements have fared in the past.
Geographic diversity, flexible conventional generation, load control, and curtailment can be used to deal with variability.
For example, the open-source model generator TEMOA applies stochastic programming [31] to deal with variability uncertainty.
As higher levels of VRE are integrated into electric power system, the main technical challenges deal with variability, uncertainty, and asynchronous operations.
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