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Related Concept Videos

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is formed in...
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The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
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Related Experiment Video

Updated: May 31, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Keyword extraction by nonextensivity measure.

Ali Mehri1, Amir H Darooneh

  • 1Department of Physics, Zanjan University, Zanjan, Iran. alimehri@znu.ac.ir

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|July 7, 2011
PubMed
Summary
This summary is machine-generated.

Human writing shows long-range word correlations, unlike random text. Nonextensive statistical mechanics and its parameter offer a new way to measure these word correlations and rank keywords.

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Related Experiment Videos

Last Updated: May 31, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Area of Science:

  • Computational Linguistics
  • Statistical Physics
  • Information Science

Background:

  • Human-written texts exhibit unique spatial correlations in word occurrences.
  • Distinguishing relevant word patterns from random noise is crucial for text analysis.
  • Existing methods for analyzing text structure and extracting keywords may have limitations.

Purpose of the Study:

  • To classify word correlations in texts using nonextensive statistical mechanics.
  • To introduce the nonextensivity parameter as a novel metric for spatial correlation.
  • To compare the effectiveness of different keyword extraction techniques.

Main Methods:

  • Application of nonextensive statistical mechanics to model word-ranking processes.
  • Analysis of spatial distribution and occurrence patterns of word types.
  • Utilizing the nonextensivity parameter to quantify word correlations.
  • Comparative evaluation of various keyword extraction algorithms.

Main Results:

  • Demonstrated the ability of nonextensive statistical mechanics to classify long-range word correlations.
  • Identified the nonextensivity parameter as a viable metric for spatial text analysis.
  • Showcased ranking of words based on their spatial correlation measure.
  • Provided a comparative analysis of different keyword extraction methods.

Conclusions:

  • Nonextensive statistical mechanics offers a robust framework for analyzing text structure.
  • The nonextensivity parameter serves as an effective measure for spatial word correlations.
  • This approach enhances understanding of linguistic patterns and keyword identification.