diff --git a/BayesValidRox/tests/PA-A/Benchmark_PAA.py b/BayesValidRox/tests/PA-A/Benchmark_PAA.py
index 1083aa42ca0c1b22f4ff25a61066b3419e85ca7c..3ef7688f75a90c7b964adaa3e39be11ea3bf98af 100755
--- a/BayesValidRox/tests/PA-A/Benchmark_PAA.py
+++ b/BayesValidRox/tests/PA-A/Benchmark_PAA.py
@@ -6,7 +6,7 @@ Created on Thu Feb  6 14:59:50 2020
 @author: mohammadi
 """
 
-import sys, os
+import sys, os, joblib
 import numpy as np
 from scipy import stats
 import pandas as pd
@@ -311,29 +311,29 @@ if __name__ == "__main__":
     # Perturbe data
     data = pd.read_csv('data/stokesDataValid.csv')
     perturbedDataAvg = perturbData(data,['velocity [m/s]', 'p'],nBootstrapItr,BootstrapNoise)
-    np.savetxt('./data/perturbedValidDataAvg.csv',perturbedDataAvg, delimiter=',')
-    #np.loadtxt('./data/perturbedDataAvg.csv',delimiter=',')
+    # np.savetxt('./data/perturbedValidDataAvg.csv',perturbedDataAvg, delimiter=',')
+    perturbedDataAvg = np.loadtxt('./data/perturbedValidDataAvg.csv',delimiter=',')
     paramsAvg = (nInitSamples,nTotalSamples,nBootstrapItr,perturbedDataAvg)
     
     # Perturbe non-averaged data for PNM
     data = pd.read_csv('data/stokesDataValid_without_averaging.csv')
     perturbedData = perturbData(data,['velocity [m/s]', 'p'],nBootstrapItr,BootstrapNoise)
-    np.savetxt('./data/perturbedValidData.csv',perturbedData, delimiter=',')
-    #np.loadtxt('./data/perturbedData.csv',delimiter=',')
+    # np.savetxt('./data/perturbedValidData.csv',perturbedData, delimiter=',')
+    perturbedData = np.loadtxt('./data/perturbedValidData.csv',delimiter=',')
     params = (nInitSamples,nTotalSamples,nBootstrapItr,perturbedData)
     
     
     #==========================================================================
     #====================   Run main scripts for PA-B   =======================
     #==========================================================================
-    # result_folder = './Results_22_06_2021'
+    result_folder = './' #'./Results_22_06_2021'
     
     # Model stokesdarcy-pnm with the averaged data
-    PCEModel_PNM, BayesCalib_PNM, BayesValid_PNM = stokespnm.run(paramsAvg, PCEEDMethod=PCEExpDesignMethod)
+    # PCEModel_PNM, BayesCalib_PNM, BayesValid_PNM = stokespnm.run(paramsAvg, PCEEDMethod=PCEExpDesignMethod)
 
     # Load the objects
-    # with open(result_folder+'/outputs_ffpm-stokespnm/PA_A_Bayesffpm-stokespnm-valid.pkl', 'rb') as input:
-    #     BayesValid_PNM = joblib.load(input)
+    with open(result_folder+'/outputs_ffpm-stokespnm/PA_A_Bayesffpm-stokespnm-valid.pkl', 'rb') as input:
+        BayesValid_PNM = joblib.load(input)
     
     # Model stokesdarcy-pnm without the averaged data
     PCEModel_PNM_NA, BayesCalib_PNM_NA, BayesValid_PNM_NA = stokespnm.run(params, averaging=False,
diff --git a/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py b/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
index 5bdf20fceb333e4831d7ddb7ac8efb42987bfe34..f10a2f2eb2a911fd9d9b111aa5b34650615ad3a9 100755
--- a/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
+++ b/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
@@ -118,7 +118,7 @@ def run(params, errorPerc=0.05, couplingcond='BJ', PCEEDMethod='normal'):
     # Mu = np.log(params[0]**2 / np.sqrt(params[0]**2 + params[1]**2))
     # Sigma  = np.sqrt(np.log(1 + params[1]**2 / params[0]**2))
     # Inputs.Marginals[2].InputValues = chaospy.LogNormal(mu=Mu,sigma=Sigma).sample(MCSize)
-    Inputs.Marginals[2].InputValues = stats.uniform(loc=1e-10, scale=1e-7-1e-10).rvs(size=MCSize)
+    Inputs.Marginals[2].InputValues = stats.uniform(loc=1e-10, scale=1e-8-1e-10).rvs(size=MCSize)
     # params = (1.0e-08, 1.5e-08)
     # Inputs.Marginals[2].DistType = 'lognorm'
     # Inputs.Marginals[2].Parameters = params
diff --git a/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py b/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
index 0b00ac99396d6a30cba7dc35ffcf76f1e79f4b26..0e4de1017a5848b41160e5fffa85240130a7fba0 100755
--- a/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
+++ b/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
@@ -253,7 +253,7 @@ def run(params, averaging=True,errorPerc=0.05, PCEEDMethod='normal'):
         # Load the objects
         saved_Dir = './outputs_ffpm-stokespnm/'
         with open(saved_Dir+'PCEModel_'+'ffpm-stokespnm'+'.pkl', 'rb') as input:
-            PCEModel = pickle.load(input)
+            PCEModel = joblib.load(input)
 
         PCEModel.ModelObj.Name = 'ffpm-stokespnmNA'