poor positive “smooth component”, as it is the case far away from the transition where the mean energy transfer is very small. When on the contrary the smooth component is important, $\epsilon _n$ is almost always positive and $\langle |\epsilon_{n}|\rangle$ is very close to a constant in the inertial range as $\langle \epsilon_{n}\rangle $ should be in a statistically stationnary state. In any case the bias disappears at higher values of $p$ since the strongest fluctuations are always positive.\
We have calculated $\Sigma_{n,p}$ for $p$ up to $12$. For each run we integrated the equations over $1000$ turn-over or unit times and sampled the signal with a step much smaller than the characteristic time-scales of the more intense structures (in practice we took $\Delta t =10^{-4})$. The length of each run was enough to ensure the stationarity of the statistics, at least for moments of order $p$ smaller than $7-8$. As shown on Fig. \[exscal\] for $\beta =0.33$, these quantities obey nice power laws on a rather wide range of shell numbers. We may thus define exponents $\sigma_{p}$ such that in the inertial range $\Sigma_{n,p}\sim {k_{n}}^{\sigma_{p}}$ (the relation between $\sigma_{p}$ and the usual exponent $\zeta_{p}$ associated to the velocity field 