is : $\zeta_{p}={p\over 3}-\sigma_{p}$).\
To extract values of the scaling exponents $\sigma_{p}$ from our data, we again followed the procedure outlined in [@KLWB] (though not with the same refinement!). The inertial or fitting range was determined as the interval of values of $n$, for which a least square fit of the data to a straight line, give $\sigma_{1}$ the closest to zero. A fitting range $5\leq n \leq 10$ proved to be the best for all values of $\beta$ we looked at, with $\sigma_{1}$ as small as $0.01$ for $\beta \sim
 0.33$. Actually the highest moments ($p\geq7$) allow a wider range for an estimation of the exponents, whereas the lowest depend only slightly on this length. In order to get a rough estimate of statistical errors due to the finite length of our temporal signal, we repeated the same operations many times (typically $5$), taking as new initial conditions the state obtained at the end of the precedent run. Error bars drawn in the next figures take into account this only source of uncertainty. Our results for the scaling exponents $\sigma_{p}$ are summarized in Fig. \[tp1\] for three typical values of $\beta $ : $\beta =0.28$, $\beta =0.33$, and $\beta
