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The task here is to apply the "best edge method" on the given graph. This method is often used in graph theory for creating a minimum spanning tree (MST) by sequentially adding the shortest available edge that does not form a cycle.

### Given Information:
1. Graph with vertices \(A, B, C, D,\) and \(E\).
2. Edge weights provided:
   - \(BD = 140\), \(BE = 110\), \(AC = 120\), \(CD = 180\), and \(BD = 140\).
3. Other weights are visible directly on the edges.

### Steps Using Best Edge Method:
1. **Sort all edges by weight** in ascending order.
2. **Add edges** one by one to the MST if they do not form a cycle.
3. **Continue** until we connect all vertices with the minimum weight.

I'll guide you through these steps if you need help. Let me know if you'd like me to list the sorted edges and identify the MST edges step-by-step.

Would you like to proceed with this breakdown, or have any specific questions on applying the best edge method?

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### Further Exploration Questions:
1. What is the minimum spanning tree (MST) concept in graph theory?
2. How does the best edge method compare to Kruskal's or Prim's algorithms?
3. What role do edge weights play in determining paths in a network?
4. How would the MST change if one of the edge weights increased significantly?
5. Can you identify any cycles in the graph, and how do they affect the MST?

### Quick Tip:
In applying the best edge method, always check for cycles when adding each new edge. Use a simple visual check or a union-find data structure for efficiency in larger graphs.

Now use best edge method on the same graph (BD has a weight of 140, BE 110, AC 120, CD 180, BD 140).

Learn how to apply the best edge method to find the minimum spanning tree of a graph. This example involves a graph with vertices A, B, C, D, and E, and weights on edges such as BD (140), BE (110), and more. Suitable for advanced high school or undergraduate students studying graph theory.

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