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Related Concept Videos

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Cyclic Processes And Isolated Systems01:19

Cyclic Processes And Isolated Systems

A thermodynamic system with zero heat exchange and work is an isolated system. For these systems, the internal energy remains constant.
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state. 
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each path...
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
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,...
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression results...
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.
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Related Experiment Video

Updated: Jul 2, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Evolving complex networks with conserved clique distributions.

Gregor Kaczor1, Claudius Gros

  • 1Institute for Theoretical Physics, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 4, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel hierarchical algorithm for generating complex networks with specific clique distributions. The method allows for random or preferential attachment, creating graphs that mimic real-world network properties.

Related Experiment Videos

Last Updated: Jul 2, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Area of Science:

  • Graph theory
  • Network science
  • Computational mathematics

Background:

  • Understanding the structure of complex networks is crucial in various scientific domains.
  • Real-world networks often exhibit specific subgraph properties, such as clique distributions.
  • Generating synthetic networks with controlled properties aids in theoretical analysis and simulation.

Purpose of the Study:

  • To propose and investigate a hierarchical algorithm for generating graphs.
  • To control the distribution of cliques (fully connected subgraphs) within generated graphs.
  • To analyze the statistical properties of these synthetic graphs and compare them to empirical networks.

Main Methods:

  • Development of a hierarchical graph generation algorithm.
  • Incorporation of both random and preferential attachment construction mechanisms.
  • Evaluation of graph properties including degree distribution and network diameter.

Main Results:

  • The algorithm successfully generates graphs with a predetermined clique distribution.
  • Analysis reveals key statistical properties of the generated networks.
  • Comparisons show similarities between generated and real-world network characteristics.

Conclusions:

  • The proposed hierarchical algorithm provides a flexible method for synthesizing complex networks.
  • This approach facilitates the study of network structures with controlled clique distributions.
  • The generated graphs serve as valuable models for understanding real-world network phenomena.