To test the parallelization of phew, we have performed a scaling experiment on a snapshot from a cosmological dark matter simulation.
The experimental results were used to perform a scale up exercise that predicts a compact CCTC flow path for 500 and 2000 L batches using commercially available membranes.
We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time.
We also perform a scaling analysis of the absolute returns in both the artificial and real stock markets.
Further work in our lab would be required to remove the requirement for a silica treatment and then to perform a scale-up campaign (Additional file 1).
We describe in great detail the parallel algorithm and perform a scaling experiment which proves the capability of phew to run efficiently on massively parallel systems.
We performed a large scale assessment on a total of 152 protein binding sites.
We performed a small scale study to correlate RMEL expression levels with clinical and histopathological features.
Here, we performed a large scale evaluation of the use of bacteriophages as ICs in routine molecular diagnosis.
We have performed a large scale comparison of oligo and BAC platforms using a set of 19 patient samples.
