<｜begin▁of▁sentence｜>### Instruction:
Imagine we're consulting on an eco-friendly urban development project. Within our planning framework, we have a network of green initiatives, with each node representing a project, and edges reflecting collaborations between these projects. 

We have five initiatives, labeled 0 through 4. We've observed active collaborations between initiative 0 and 1, initiative 1 and 2, initiative 1 and 3, initiative 1 and 4, initiative 2 and 3, as well as between initiative 3 and 4.

Our focus today is on understanding the resilient core of this network, which is akin to nature's most robust ecosystems. Think of it as the "2-core" of a habitat, where every species (or, in our case, every initiative) is connected to at least two others, ensuring biodiversity and resilience. 

Could you visualize for us which of our initiatives and their collaborations would constitute this resilient "2-core" network? Specifically, which initiatives will remain within this durable framework and which links will continue to promote environmental prosperity under this criterion?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (1, 3), (1, 4), (2, 3), (3, 4)])

# Find the 2-core of the graph
k_core_graph = nx.k_core(G, k=2)

# Print the nodes and edges of the 2-core
print('Nodes:', k_core_graph.nodes())
print('Edges:', k_core_graph.edges())
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