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Related Concept Videos

Stability of structures01:14

Stability of structures

In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Network Function of a Circuit01:25

Network Function of a Circuit

Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
Network Covalent Solids02:18

Network Covalent Solids

Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
Circuit Terminology01:14

Circuit Terminology

An electrical network is a system composed of interconnected elements, such as resistors, capacitors, inductors, and voltage or current sources. Unlike a circuit, an electrical network does not necessarily form a closed path. In other words, while all circuits can be considered networks due to their interconnected nature, not every network qualifies as a circuit.
A circuit, on the other hand, is also an interconnected system of electrical elements but must contain one or more closed paths.

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Related Experiment Videos

Onion structure and network robustness.

Zhi-Xi Wu1, Petter Holme

  • 1Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou, Gansu 730000, China.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 21, 2011
PubMed
Summary
This summary is machine-generated.

This study links network robustness to an "onion structure" in scale-free networks. A new algorithm generates these robust networks, demonstrating their resilience against attacks and random node removal.

Related Experiment Videos

Area of Science:

  • Network Science
  • Graph Theory
  • Complex Systems

Background:

  • Schneider et al. introduced a novel network robustness measure.
  • Optimized networks with power-law distributions exhibit an
  • onion structure
  • with high-degree nodes forming a core.

Purpose of the Study:

  • To connect the
  • onion structure
  • to graph expander properties.
  • To propose a generative algorithm for robust, scale-free networks with an
  • onion structure
  • .

Main Methods:

  • Relating
  • onion structure
  • to spectral gaps and expander properties.
  • Developing a generative algorithm for synthetic scale-free networks.

Main Results:

  • Networks with skewed degree distributions and large spectral gaps exhibit
  • onion structure
  • .
  • Generated networks demonstrate robustness against malicious attacks and random removals.

Conclusions:

  • The
  • onion structure
  • is a key characteristic of robust networks.
  • The proposed algorithm efficiently generates resilient scale-free networks.