Related Experiment Video

Updated: Jan 31, 2026

Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes
10:10

Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes

Published on: October 4, 2018

9.3K

Global Synchronization of Coupled Fractional-Order Recurrent Neural Networks

Peng Liu, Zhigang Zeng, Jun Wang

    IEEE Transactions on Neural Networks and Learning Systems
    |December 25, 2018
    PubMed

    More Related Videos

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.1K
    A Neural Network-Based Identification of Developmentally Competent or Incompetent Mouse Fully-Grown Oocytes10:04

    A Neural Network-Based Identification of Developmentally Competent or Incompetent Mouse Fully-Grown Oocytes

    Published on: March 3, 2018

    7.1K

    Related Concept Videos

    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,...
    4.5K
    Global Climate Change01:50

    Global Climate Change

    Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
    28.9K
    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...
    16.2K
    Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

    Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)

    Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
    The central atom need not be NMR-active because its electrons are affected by the electron polarization of the spin-active atoms. However, spin information is transmitted less effectively than in one-bond coupling, and 2J values are usually weaker than 1J values. The energy of...
    1.7K
    Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

    Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)

    Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
    The extent of coupling depends on the C‑C bond length, the two H‑C‑C angles, any electron-withdrawing substituents, and the dihedral angle between the involved orbitals. The...
    1.5K
    Simplified Synchronous Machine Model01:30

    Simplified Synchronous Machine Model

    The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
    In this model, each generator is connected to a...
    778