of allowing a spatially varying order parameter and taking the noise into consideration are examined. The Laplacian is discretized as $$\nabla^2 n_i ={1 \over 2d} \sum_{j} (n_j-n_i) \approx \n 
-n_i,$$ where the sum runs over the nearest neighbors of $i$ and a large system dimensionality has been assumed. Similarly, the square gradient term can be written as $${(\nabla n)_i^2 \over n_i} \approx {\langle n^2 \rangle \over n_i}
-2\n + n_i.$$ The one-site stationary probability distribution is then readily obtained from the associated Fokker-Planck equation, $$\begin{aligned}
P_{st}\Big(n,\n\Big) &\propto& {1 \over n^2} \exp \int^n {
(\nabla x)_i^2-2(\nabla x)_i^2/ x_i -(a+1)x_i-bx_i^{p+1} \over x_i^2} \ dx_i,
\nonumber \\
&\approx &{1 \over n^{a+6}} \exp \Bigg(-5{\n \over n}-b {n^p\over p} 
+{\langle n^2 \rangle \over n^2}\Bigg).
\label{pmnminus}\end{aligned}$$ where $\n$ and $\langle n^2 \rangle$ have to be calculated self-consistently. For $a< a_c=-5$, $P_{st}$ is not normalizable what means that the stationary state is the absorbing phase $\n =0$. For $\n \not=0$, however, the non-analyticity of $\exp[\langle n^2 \rangle / n^2]$ at $n=0$ again renders $P_{st}$ non-normalizable. As a result, there is no well-defined active phase at this mean-field level for Eq. (\[pmnminus\]). Similar problems are found if the same type of approach is applied to Eq. (\[BKPZ\]) instead 