<｜begin▁of▁sentence｜>### Instruction:
As an exercise physiologist, you might be interested in optimizing the efficiency of a fitness facility's layout. Imagine you're tasked with improving the flow of clients from the entrance (vertex 0) to the changing rooms (vertex 5) in a gymnasium. Each corridor connecting different areas has a maximum capacity of 10 people to ensure smooth movement.

To assess the layout's effectiveness, you need to determine the bottleneck or the minimum cut between the entrance and the changing rooms. This essentially means finding the narrowest point where reducing traffic would significantly impede the flow of clients. By identifying this minimum cut, you can strategically allocate resources to alleviate congestion and enhance the overall experience for gym-goers.
### Response:
import igraph as ig

# Create a graph from some edges
edges = [(0, 1), (1, 2), (2, 3), (0, 3), (3, 4), (4, 5)]
capacities = [10, 10, 10, 10, 10, 10]
g = ig.Graph(edges)
g.es['capacity'] = capacities

# Compute the minimum cut value between vertex 0 and vertex 5
mincut_val = g.mincut_value(0, 5, capacity='capacity')
print('The value of the minimum cut between vertex 0 and 5 is:', mincut_val)
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