 Mass-normalized temporal kernels for nail clippings

Mass-normalized temporal kernels for nail clippings assign each earlier material time its fraction of the analyzed sample's mass. They convert a finite clipping into an averaging operator on a time-dependent retained concentration. The weighting is normalized by the assayed material amount, rather than by elapsed time alone.

For an original one-dimensional advection model, let $s$ be the time when a material element crossed a defined anatomical reference, and collect at time $t$. With spatially uniform positive advance speed $v(u)$,Suppose the clipping's retained elements correspond to $s\in [s_1,s_2]$. Let $m(x,t)$ be structural mass per unit length at collection, and assume the marker's concentration per structural mass is preserved along each element. ThenThe kernel has units of inverse time, is nonnegative and integrates to one. It can be treated mathematically like a probability density function for the reference-crossing time of material selected in proportion to its mass. This is a material-accounting interpretation, not a claim that the biological transport is random.

For a stipulated 20-day window, take line density 1 mg/mm, advance 0.10 mm/day in the earlier ten days and 0.20 mm/day in the recent ten days. The two intervals contribute 1 and 2 mg, respectively. Their kernel heights are $1/30$ and $1/15$ per day. A retained concentration of 90 ng/mg only in the earlier interval gives $\overline{c}=30$ ng/mg; a uniform time average would give 45. A constant 30 ng/mg history gives the same sample result. Thus one pooled measurement does not identify a unique history.

A centroid date of a mass-normalized nail kernel summarizes the weighting, while the kernel's spread records its finite time resolution. Neither removes the difference between reference crossing and earlier formation in the hidden nail matrix. The primary nail-marking experiment measures displacement over observation intervals, not the complete kernel or marker retention law.^[ref] Measuring segment mass, geometry and growth history constrains separate parts of this model.