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1. Business understanding phase Zan et al. (2007) demonstrated that business understanding can be established via understanding the goals and data mining requirements.
It's since pivoted to build an engine to communicate with artificial intelligence via understanding the context and use of symbols, which can be applied to things like giving characters in games emotions, and licensing this engine to third parties.
This interpretive approach, on the assumptions that deeper understandings of phenomena can only be achieved via understanding the interpretations of those phenomena through experiencing them (Shah & Corley, 2006), suggests that every researcher who is doing this research "will have a unique interpretation of the results" (Labianca, Gray, & Brass, 2000, p. 241).
It has also facilitated the understanding of living cells at a systemic level by linking molecules to biological functions and thus bridging the genotype-to-phenotype gap via understanding the organisation of biological pathways [ 3] and the network of protein interactions [ 4].
Given the importance of developing and supporting adaptive capacity in health and other sectors via understanding and strengthening decision making and governance structures, it is vital to understand the links (or lack thereof) between and within relevant sectors.
If it's true that humans developed language and diversified from other animals via understanding of their prey and hunting / predicting their behavior (Shipman), then it makes sense that animals would be dead last on the list of those spared from violence, I suppose.
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Machiavelli saw action not only as the goal of virtue but also (via historical understanding of great deeds of the past) as the basis for wisdom.
This progress might be achieved via improvement in understanding the membrane structure described at the macromolecular level.
Understanding via empirical experimentation how to effectively combine various types of clustering features allows us to seamlessly export our system to other datasets and languages.
Since mammalian miRNAs tend to bind to target mRNAs via imperfect complementarity, understanding exactly which target mRNAs are recognized by which specific miRNAs is a challenge.
However, practical application of this decision-support process was not without challenges, which included missing or suboptimal data, clearly articulated fuels management objectives, and improved understanding (via re-assessing decision logic from prior years) of trade-offs in decision-making.
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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