<｜begin▁of▁sentence｜>### Instruction:
Imagine you're a sleep specialist and you've conceptualized the sleep architecture of a patient as a kind of 'social network' of sleep phases. You've decided to model this using a barbell graph with parameters (10, 0), where each node represents a distinct phase of sleep, and the connections between them—akin to the deepening and lightening of sleep stages. In this 'sleep network model', you're curious about the resilience of the sleep structure. Specifically, you're considering the connections that, if disrupted, would isolate a phase of sleep, much like how a single night of poor sleep can impact someone's whole day. To investigate this, you ponder whether there are any 'critical connections' within this model, analogous to bridges in a network graph that, just as in the case of disturbed sleep, can isolate parts of the network when removed. You're planning to utilize the NetworkX has_bridges function to explore this feature within the graph structure. Would you identify any such critical sleep phase connections (or 'bridges') in this 'sleep network model' based on the given parameters?
### Response:
import networkx as nx

# Create a barbell graph with parameter zero which has a single bridge
G = nx.barbell_graph(10, 0)

# Check if the graph has any bridges
has_bridge = nx.has_bridges(G)

print('Does the graph have bridges?', has_bridge)
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