<｜begin▁of▁sentence｜>### Instruction:
Imagine you're a Quality Assurance Analyst tasked with evaluating the integrity of a networking application that visualizes intricate circuit designs. These circuit designs are analogous to graphs, and you're currently examining a particular case where a design has incorporated two distinct loops. The first loop navigates from a junction point marked as "0" through connectors labeled "1," "2," and "3," eventually returning to the starting junction "0." The second loop also commences at the junction "0," but instead proceeds via alternate pathways "4" and "5," reaching the common connection point "3" and returning back to "0."

In this context, your role is to ensure the software can effectively identify the most basic set of loops—that is, the minimum cycle basis—within this circuit design so that potential redundancies can be minimized and the design optimized. To facilitate this, you'll employ the NetworkX library.

Could you illustrate how the application is capable of computing the minimum cycle basis for the given circuit layout, ensuring the procedure is accurately represented and functions according to the design specifications? More technically, you are looking for a means to engage NetworkX in determining the minimum cycle basis in a graph where these two loops (cycles) are present. The details of the graph can be referred to through the equivalent digital structure in a GML file, should you require specific identifiers or properties associated with each junction or connector.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add cycle
G.add_cycle([0, 1, 2, 3])
G.add_cycle([0, 3, 4, 5])

# Find a minimum cycle basis
mcb = nx.minimum_cycle_basis(G)

print(mcb)
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