A possible solution to seed within the domain of possible sequences would be to start with a position randomly collected from a uniform distribution, as indeed used in the original USM paper [14]. However, that too will cause a bias, this time towards missing conservation of initial units in a sequence if that is the case. A negligible few false negatives may be an acceptable outcome for pattern recognition and would have no effect elsewhere in the sequence. However, it falls short of what is required for a kernel generating truly scale independent density distribution of patterns.