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Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

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The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
One type of fragmentation pattern is the cleavage of a single bond in the molecular ion. The cleavage leads to a radical and a cation. The cleavage can occur at...
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Long-patch Base Excision Repair01:02

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Since the discovery of the two BER pathways, there has been a debate about how a cell chooses one pathway over the other and the factors determining this selection. Numerous in vitro experiments have pointed out multiple determinants for the sub-pathway selection. These are:
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Habitat Fragmentation02:31

Habitat Fragmentation

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Habitat fragmentation describes the division of a more extensive, continuous habitat into smaller, discontinuous areas. Human activities such as land conversion, as well as slower geological processes leading to changes in the physical environment, are the two leading causes of habitat fragmentation. The fragmentation process typically follows the same steps: perforation, dissection, fragmentation, shrinkage, and attrition.
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Mass Spectrometry: Branched Alkane Fragmentation01:29

Mass Spectrometry: Branched Alkane Fragmentation

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This lesson delves into the mass spectrometry of branched alkane fragmentation. Branched alkanes possess secondary or tertiary carbon atoms, which generate relatively stable carbocations if the cleavage occurs at the branching point. The high stability of carbocations drives the instant fragmentation of branched alkanes. Accordingly, the branched alkane's molecular ion peak is very weak or invisible in the mass spectra, especially in comparison to a linear alkane.
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Multimachine Stability01:25

Multimachine Stability

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
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Protein Networks02:26

Protein Networks

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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.
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Related Experiment Video

Updated: Mar 30, 2026

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays
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Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

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Fast Fragmentation of Networks Using Module-Based Attacks.

Bruno Requião da Cunha1,2, Juan Carlos González-Avella1,3, Sebastián Gonçalves1

  • 1Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.

Plos One
|November 17, 2015
PubMed
Summary
This summary is machine-generated.

We present a new module-based method to efficiently break complex networks by targeting inter-community links. This approach outperforms traditional methods, significantly fragmenting networks like the US power grid.

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Area of Science:

  • Network Science
  • Complex Systems Analysis
  • Computational Social Science

Background:

  • Efficiently breaking complex networks is crucial for practical applications.
  • Existing methods often rely on node degree or betweenness centrality, with varying success.
  • Understanding network modularity is key to improving fragmentation strategies.

Purpose of the Study:

  • To introduce a novel module-based method for efficient complex network fragmentation.
  • To demonstrate the method's effectiveness across diverse network types (social, infrastructure, biological).
  • To compare the module-based approach against traditional targeted attack strategies.

Main Methods:

  • Identifying topological communities using a heuristic community finding algorithm.
  • Removing nodes participating in inter-community links, ordered by betweenness centrality.
  • Applying the method to social, infrastructure, and biological network examples.

Main Results:

  • The module-based method consistently outperforms node degree and betweenness centrality attacks.
  • Fragmentation efficiency is strongly correlated with the network's modularity.
  • In the US power grid, removing only 3% of nodes resulted in fragments 20 times smaller than betweenness-based attacks.

Conclusions:

  • The module-based approach offers a more efficient strategy for complex network fragmentation.
  • Network modularity is a critical factor influencing the success of fragmentation.
  • This method provides a significant advancement for network analysis and disruption.