Such a high amount of investments is justified by the benefit that is expected from processing the data, and this is particularly true for omics science.
The use of flow technologies for chemical applications has become a fast growing area with a wide range of reaction types identified as having benefited from flow processing [1].
The accrued benefit gained from processing information can be precisely quantified by comparing benefits returned using distributions prior to, and after collapse, and these often large and immediate benefits can amply justify the evolutionary cost of information processing systems.
But there is a large and insufficiently explored difference between System 1 nudges, which target or benefit from automatic processing, and System 2 nudges, which target or benefit from deliberative processing.
The presented results benefit from advanced processing and presentation techniques.
Being computer-intensive, it can benefit from parallel processing to accelerate its application on realistic structural models.
The first big step was Zuckerberg's decision to drop HTML5 in August 2012, and instead write "native" apps for each platform, specifically to be able to benefit from greater processing speed, despite the extra coding involved.
However, ECA is a computationally intensive algorithm and will benefit from parallel processing and modern computational platforms such as Field Programmable Gate Arrays (FPGAs).
The results show that different scalability options can be used to benefit from additional processing power to shorten the execution time.
