diff --git a/.ipynb_checkpoints/Balance_Binary-checkpoint.ipynb b/.ipynb_checkpoints/Balance_Binary-checkpoint.ipynb
index 39e88f671bc24d38ae981b169ee3e0c6aed91155..7359f472dc557dc785cda30070d345f94243ad41 100644
--- a/.ipynb_checkpoints/Balance_Binary-checkpoint.ipynb
+++ b/.ipynb_checkpoints/Balance_Binary-checkpoint.ipynb
@@ -10,10 +10,10 @@
       "views": {
        "grid_default": {
         "col": 0,
-        "height": 3,
+        "height": 2,
         "hidden": false,
         "row": 0,
-        "width": 10
+        "width": 12
        }
       }
      }
@@ -37,10 +37,10 @@
       "views": {
        "grid_default": {
         "col": 0,
-        "height": 20,
+        "height": 11,
         "hidden": false,
-        "row": 3,
-        "width": 5
+        "row": 2,
+        "width": 6
        }
       }
      }
@@ -62,8 +62,8 @@
     "\n",
     "* eine binäre Bilanz summiert __zwei__ (binär) Größen zu einer Dritten\n",
     "    * Beispiele:\n",
-    "        * $m_{AB} = m_A + m_B $\n",
-    "        * $n_{AB} = n_A + n_B $\n",
+    "        * $ m_{AB} = m_A + m_B $\n",
+    "        * $ n_{AB} = n_A + n_B $\n",
     "        * $H_{AB} = H_A + H_B $\n",
     "\n",
     "\n",
@@ -83,11 +83,11 @@
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 5,
-        "height": 5,
+        "col": 3,
+        "height": 4,
         "hidden": false,
-        "row": 3,
-        "width": 5
+        "row": 13,
+        "width": 6
        }
       }
      }
@@ -103,31 +103,29 @@
    ]
   },
   {
-   "attachments": {
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-    }
-   },
    "cell_type": "markdown",
-   "id": "e9ef6dfa-3343-4a59-b87e-3259c9d3b464",
+   "id": "cc5ef378-a52e-4ced-9050-a82292513eb0",
    "metadata": {
     "extensions": {
      "jupyter_dashboards": {
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 5,
-        "height": 14,
+        "col": 6,
+        "height": 11,
         "hidden": false,
-        "row": 8,
-        "width": 5
+        "row": 2,
+        "width": 6
        }
       }
      }
     }
    },
    "source": [
-    "![biary_balance_1.jpg](attachment:fd6be7dd-f8a4-4b4d-8ba6-9936489a7e98.jpg)"
+    "<img src=\"pics/binary_balance_1.jpg\" alt=\"My picture\"\n",
+    "\ttitle=\"A cute kitten\" width=\"400px\" />\n",
+    "\n",
+    "Dieses Bild zeigt den Bilanzknoten mit den  extensiven und intensiven Größen"
    ]
   },
   {
@@ -178,7 +176,50 @@
      }
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4368c6e2350c4b0c92d6cf8f7d734a7b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1606140b05984266b85bef715826cc19",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5bd5724182034d35b60cd23fa0a4bc9b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "bilanz_1 = no_bi.binary_node('bilanz_1') # Umgebungs\n",
     "step = no_ba.step_single('step')\n",
@@ -222,11 +263,11 @@
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 5,
-        "height": 8,
+        "col": 6,
+        "height": 5,
         "hidden": false,
-        "row": 23,
-        "width": 5
+        "row": 17,
+        "width": 6
        }
       }
      }
@@ -237,7 +278,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7a92df3acd14402ea5ff7ebd1d353569",
+       "model_id": "96c8c956f265470da69a1253e650b386",
        "version_major": 2,
        "version_minor": 0
       },
@@ -264,10 +305,10 @@
       "views": {
        "grid_default": {
         "col": 0,
-        "height": 5,
+        "height": 4,
         "hidden": false,
-        "row": 23,
-        "width": 5
+        "row": 17,
+        "width": 4
        }
       }
      }
@@ -277,7 +318,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1461e095163a482a8bb86ba8a917be4c",
+       "model_id": "35ea6dda14f247d5b73577a34d87eab4",
        "version_major": 2,
        "version_minor": 0
       },
@@ -303,11 +344,11 @@
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 0,
-        "height": 3,
+        "col": 4,
+        "height": 2,
         "hidden": false,
-        "row": 28,
-        "width": 5
+        "row": 18,
+        "width": 2
        }
       }
      }
@@ -317,7 +358,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0f7812802d0b4f4f80f7da3f313f7210",
+       "model_id": "90ce2d0e300749099caa10a06a4563e6",
        "version_major": 2,
        "version_minor": 0
       },
@@ -331,7 +372,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5138f46b0a4e4ac6b63b61b8d36c668f",
+       "model_id": "749407c2429a4eae8e8d4f623bb02505",
        "version_major": 2,
        "version_minor": 0
       },
@@ -379,7 +420,7 @@
     "views": {
      "grid_default": {
       "cellMargin": 2,
-      "defaultCellHeight": 40,
+      "defaultCellHeight": 50,
       "maxColumns": 12,
       "name": "grid",
       "type": "grid"
diff --git a/Balance_Binary.ipynb b/Balance_Binary.ipynb
index 8f0e77040e7d85979a87a5361ed1607e299aad3e..7359f472dc557dc785cda30070d345f94243ad41 100644
--- a/Balance_Binary.ipynb
+++ b/Balance_Binary.ipynb
@@ -10,10 +10,10 @@
       "views": {
        "grid_default": {
         "col": 0,
-        "height": 3,
+        "height": 2,
         "hidden": false,
         "row": 0,
-        "width": 10
+        "width": 12
        }
       }
      }
@@ -37,10 +37,10 @@
       "views": {
        "grid_default": {
         "col": 0,
-        "height": 20,
+        "height": 11,
         "hidden": false,
-        "row": 3,
-        "width": 5
+        "row": 2,
+        "width": 6
        }
       }
      }
@@ -62,8 +62,8 @@
     "\n",
     "* eine binäre Bilanz summiert __zwei__ (binär) Größen zu einer Dritten\n",
     "    * Beispiele:\n",
-    "        * $m_{AB} = m_A + m_B $\n",
-    "        * $n_{AB} = n_A + n_B $\n",
+    "        * $ m_{AB} = m_A + m_B $\n",
+    "        * $ n_{AB} = n_A + n_B $\n",
     "        * $H_{AB} = H_A + H_B $\n",
     "\n",
     "\n",
@@ -83,11 +83,11 @@
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 5,
-        "height": 5,
+        "col": 3,
+        "height": 4,
         "hidden": false,
-        "row": 3,
-        "width": 5
+        "row": 13,
+        "width": 6
        }
       }
      }
@@ -103,31 +103,29 @@
    ]
   },
   {
-   "attachments": {
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-    }
-   },
    "cell_type": "markdown",
-   "id": "e9ef6dfa-3343-4a59-b87e-3259c9d3b464",
+   "id": "cc5ef378-a52e-4ced-9050-a82292513eb0",
    "metadata": {
     "extensions": {
      "jupyter_dashboards": {
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 5,
-        "height": 14,
+        "col": 6,
+        "height": 11,
         "hidden": false,
-        "row": 8,
-        "width": 5
+        "row": 2,
+        "width": 6
        }
       }
      }
     }
    },
    "source": [
-    "![biary_balance_1.jpg](attachment:fd6be7dd-f8a4-4b4d-8ba6-9936489a7e98.jpg)"
+    "<img src=\"pics/binary_balance_1.jpg\" alt=\"My picture\"\n",
+    "\ttitle=\"A cute kitten\" width=\"400px\" />\n",
+    "\n",
+    "Dieses Bild zeigt den Bilanzknoten mit den  extensiven und intensiven Größen"
    ]
   },
   {
@@ -182,7 +180,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c14793f1a8c34dcbb290b0466961a8c6",
+       "model_id": "4368c6e2350c4b0c92d6cf8f7d734a7b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -196,7 +194,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "bb22dc2094444c5badef1bb437e5d993",
+       "model_id": "1606140b05984266b85bef715826cc19",
        "version_major": 2,
        "version_minor": 0
       },
@@ -210,7 +208,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ee0f4cb0a68a43e587a6337cddeec13e",
+       "model_id": "5bd5724182034d35b60cd23fa0a4bc9b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -265,11 +263,11 @@
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 5,
-        "height": 8,
+        "col": 6,
+        "height": 5,
         "hidden": false,
-        "row": 23,
-        "width": 5
+        "row": 17,
+        "width": 6
        }
       }
      }
@@ -280,7 +278,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1fb138e47cfb4fc295c6cbdb11ccafd8",
+       "model_id": "96c8c956f265470da69a1253e650b386",
        "version_major": 2,
        "version_minor": 0
       },
@@ -307,10 +305,10 @@
       "views": {
        "grid_default": {
         "col": 0,
-        "height": 5,
+        "height": 4,
         "hidden": false,
-        "row": 23,
-        "width": 5
+        "row": 17,
+        "width": 4
        }
       }
      }
@@ -320,7 +318,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5909d959cded4e95bda0ab33a9bb8add",
+       "model_id": "35ea6dda14f247d5b73577a34d87eab4",
        "version_major": 2,
        "version_minor": 0
       },
@@ -346,11 +344,11 @@
       "activeView": "grid_default",
       "views": {
        "grid_default": {
-        "col": 0,
-        "height": 3,
+        "col": 4,
+        "height": 2,
         "hidden": false,
-        "row": 28,
-        "width": 5
+        "row": 18,
+        "width": 2
        }
       }
      }
@@ -360,7 +358,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "870ccb5a6094410ca1beab78b97d484f",
+       "model_id": "90ce2d0e300749099caa10a06a4563e6",
        "version_major": 2,
        "version_minor": 0
       },
@@ -374,7 +372,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7fae8a23e52440a49b155ecbe11c7542",
+       "model_id": "749407c2429a4eae8e8d4f623bb02505",
        "version_major": 2,
        "version_minor": 0
       },
@@ -422,7 +420,7 @@
     "views": {
      "grid_default": {
       "cellMargin": 2,
-      "defaultCellHeight": 40,
+      "defaultCellHeight": 50,
       "maxColumns": 12,
       "name": "grid",
       "type": "grid"
diff --git a/__pycache__/nowo1_base.cpython-39.pyc b/__pycache__/nowo1_base.cpython-39.pyc
index 1bd10108762bb53080d1177eb354221287479a43..bb87322a8938399ac0d954e6213a26f2a2d9a223 100644
Binary files a/__pycache__/nowo1_base.cpython-39.pyc and b/__pycache__/nowo1_base.cpython-39.pyc differ
diff --git a/__pycache__/nowo1_gui_base.cpython-39.pyc b/__pycache__/nowo1_gui_base.cpython-39.pyc
index a0994e8ffebf914333ad6632dd787b4236ad041f..15a7176630f60e529166bdb2ec6ae66a5a2f08b1 100644
Binary files a/__pycache__/nowo1_gui_base.cpython-39.pyc and b/__pycache__/nowo1_gui_base.cpython-39.pyc differ
diff --git a/__pycache__/nowo1_log_base.cpython-39.pyc b/__pycache__/nowo1_log_base.cpython-39.pyc
index c07db9d3b7d5b8b6b355ad790fc0eaefe475fdc1..954395163caf1a7416f6657917e8e4bcbc8746ff 100644
Binary files a/__pycache__/nowo1_log_base.cpython-39.pyc and b/__pycache__/nowo1_log_base.cpython-39.pyc differ
diff --git a/nowo1_base.py b/nowo1_base.py
index a871aa82298b3c6bb6d284da6c8d452c030476fc..2d07f83837baa1dc218417f716ac35fbb23f7dd4 100644
--- a/nowo1_base.py
+++ b/nowo1_base.py
@@ -383,8 +383,7 @@ class step_base():
     def on_start_clicked(self, args):
         parent = args.parent
         parent.reset()
-        with self.info:
-            print('on click')
+        #with self.info:print('on click')
        
         # for obj in parent.work_objs:
         #     if obj._GUI_is_visible:
@@ -444,7 +443,7 @@ class step_base():
             logger.ready_for_start(self)
 
         if self._GUI_visible: pass 
-        with self.info: print(logger.name, 'work 1')
+        #with self.info: print(logger.name, 'work 1')
         while self.step() == 1:
             self._node_success()
             
@@ -452,7 +451,7 @@ class step_base():
             obj.ready_for_end()
 
         for logger in self._loggerlist:
-            with self.info: print(logger.name, 'work 2')
+            #with self.info: print(logger.name, 'work 2')
             logger.ready_for_end()
          
 
@@ -644,7 +643,7 @@ class work_base():
         self.GUI_Item =  None
         self._GUI_is_visible = False
         self.info = widgets.Output()
-        display(self.info)
+        #display(self.info)
    
     def Init(self): pass
        
diff --git a/nowo1_gui_base.py b/nowo1_gui_base.py
index 36ca1cfb59dea31c7d2087c9a3359e04732b1730..e79b9aa7ad649073d16aa5c2655a8260e5bf415f 100644
--- a/nowo1_gui_base.py
+++ b/nowo1_gui_base.py
@@ -22,22 +22,17 @@ class gui_ipysheet(nowo.gui_base):
 
 
     def Init_by_dataframe(self, dataframe):
-        with self.info: print(self.name, 'Init_by')
+        #with self.info: print(self.name, 'Init_by')
         self.sheet_data = dataframe
         self.sheet_colnames = list(self.sheet_data.head())
         self.sheet_rownames = list(self.sheet_data.index.tolist())
 
 
     def ready_for_end(self):
-        with self.info: print(self.name, 'ready_1')
+        #with self.info: print(self.name, 'ready_1')
         buffer = self.sheet_data.values.T.tolist()
-        # self.sheet.cells = (ipysheet.Cell(
-        #     column_end=0, column_start=1, row_end=1, row_start=1, type='text', value='Hello'), 
-        #     ipysheet.Cell(column_end=0, column_start=0, row_end=0, row_start=0, type='text', value='Hello'))
-
         ipysheet.cell_range(buffer[0], column_start=1)
-       # self.dataframe_out = ipysheet.to_dataframe(self.sheet)
-        #self.sheet_data.to_clipboard()
+      
                
     def _create_gui(self):
        # sheet = ipysheet.sheet(rows = len(self.sheet_rownames) + 1, columns= len(self.sheet_colnames) + 1) 
diff --git a/nowo1_log_base.py b/nowo1_log_base.py
index 8da4e91b46e14f8d92203c3cf0736fd87d002ccb..6112f2922c884460e1cee33dc7de90764b84535f 100644
--- a/nowo1_log_base.py
+++ b/nowo1_log_base.py
@@ -37,7 +37,7 @@ class log_sheet(nowo.port_base):
 
 
     def Init(self,  Values = [], Gui_For_Data  = None):
-        with self.info: print(self.name, 'init')
+        #with self.info: print(self.name, 'init')
         super().Init(Values, Gui_For_Data)
         for name in self.buffer_data.keys():
             split_name = name.split('.', 1)
@@ -53,15 +53,15 @@ class log_sheet(nowo.port_base):
     def ready_for_end(self):
         super().ready_for_end()
         # self.log_data = pd.DataFrame(dict([ (k,pd.Series(v)) for k,v in self.buffer_data.items() ]))
-        with self.info: print(self.name, 'ready')
+        #with self.info: print(self.name, 'ready')
         for col_name in self.sheet_colnames:
             for row_name in self.sheet_rownames:
                 key_name = col_name + '.' + row_name
                 value = self.buffer_data[key_name]
                 self.sheet_data.at[row_name, col_name] = value
-        self.sheet_data.to_clipboard()
+        #self.sheet_data.to_clipboard()
         if self.Gui_For_Data:
-            with self.info: print(self.Gui_For_Data.name, 'ready_2')
+            #with self.info: print(self.Gui_For_Data.name, 'ready_2')
             self.Gui_For_Data.ready_for_end()
 
 
diff --git a/pics/biary_balance_1.jpg b/pics/binary_balance_1.jpg
similarity index 100%
rename from pics/biary_balance_1.jpg
rename to pics/binary_balance_1.jpg