<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working on the design of a complex machine, and you're using network models to represent the interaction between two subsystems for failure analysis. Each subsystem is represented by a graph: Subsystem G has a connection between components 'u1' and 'v1' and also includes an isolated component 'u2'. Subsystem H, on the other hand, has a linkage between parts 'u3' and 'v3' and includes an independent part 'u4'.

To better understand how these subsystems might interact when integrated into a larger system, you need to perform a strong product of the two graphs, using NetworkX as your computational tool. This operation combines the subsystems and will give you insight into all possible interactions between components of G and H.

Could you reframe the problem concerning the graphs' edge sets and list out the edges of the resulting strong product graph? This information is crucial as it represents potential points of interaction or failure in the integrated mechanical system we're analyzing.
### Response:
import networkx as nx

# Create two graphs G and H
G = nx.Graph()
H = nx.Graph()

# Add nodes and edges to G
G.add_edge('u1', 'v1')
G.add_node('u2')

# Add nodes and edges to H
H.add_edge('u3', 'v3')
H.add_node('u4')

# Compute the strong product of G and H
P = nx.strong_product(G, H)

# Print the edges of the strong product P
print(list(P.edges()))
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