Tokyo/Model
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'''Condition 1. Bistable state''' | '''Condition 1. Bistable state''' | ||
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The system is stable containing nodes A and B at certain ratio. | The system is stable containing nodes A and B at certain ratio. | ||
'''Condition 2. Unstable state with node A removed''' | '''Condition 2. Unstable state with node A removed''' | ||
| - | + | figure2 | |
Removed of node A, the system contains only node B and becomes unstable. Node B detects the removal of node A from the system and knows that there is only node B left. | Removed of node A, the system contains only node B and becomes unstable. Node B detects the removal of node A from the system and knows that there is only node B left. | ||
'''Condition 3. From unstable to stable state''' | '''Condition 3. From unstable to stable state''' | ||
| - | + | figure3 | |
In an unstable state, some node B become A while the others remain B. The system then becomes stable again. | In an unstable state, some node B become A while the others remain B. The system then becomes stable again. | ||
Revision as of 13:22, 15 October 2007
Model
To establish a system following Pareto’s principle, the system must satisfy the following three cases. In our model, all nodes have the same genetic circuits and take two states, A (worker) and B (idler), depending on the surrounding circumstances.
Condition 1. Bistable state figure1
The system is stable containing nodes A and B at certain ratio.
Condition 2. Unstable state with node A removed figure2
Removed of node A, the system contains only node B and becomes unstable. Node B detects the removal of node A from the system and knows that there is only node B left.
Condition 3. From unstable to stable state figure3
In an unstable state, some node B become A while the others remain B. The system then becomes stable again.
