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Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

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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.
For extracting a solute from an aqueous phase into an...
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Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

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Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
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Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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Interference: Path Lengths01:10

Interference: Path Lengths

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Consider two sources of sound, that may or may not be in phase, emitting waves at a single frequency, and consider the frequencies to be the same.
Two special sources may be considered when they are in phase. This can be easily achieved by feeding the two sources from the same source. An example would be synchronizing the two speakers by feeding them with the same source, such as the sound waves produced by a tuning fork. This setup ensures that the two sources have the same frequency and are...
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¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

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The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
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Related Experiment Video

Updated: Jul 21, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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Orders between Channels and Implications for Partial Information Decomposition.

André F C Gomes1, Mário A T Figueiredo1

  • 1Instituto de Telecomunicações and LUMLIS (Lisbon ELLIS Unit), Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal.

Entropy (Basel, Switzerland)
|July 29, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces new methods for partial information decomposition (PID) by using ordered information sources. These novel approaches enrich the PID framework and offer new ways to analyze complex information relationships.

Keywords:
channel preordersinformation theoryintersection informationpartial information decompositionredundancyshared information

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Area of Science:

  • Information Theory
  • Computational Neuroscience
  • Machine Learning

Background:

  • Partial Information Decomposition (PID) aims to partition information into redundant, synergistic, and unique components.
  • Classical information theory lacks a unique method for this decomposition, necessitating additional assumptions.
  • Recent axiomatic approaches, like Kolchinsky's, offer new ways to define redundant information measures.

Purpose of the Study:

  • To introduce novel measures of redundant information within the PID framework.
  • To develop new PID methods by leveraging preorders between communication channels.
  • To expand the landscape of information decomposition techniques.

Main Methods:

  • Exploiting Kolchinsky's axiomatic approach for defining redundant information measures.
  • Utilizing well-known preorders between communication channels to construct new PID measures.
  • Analyzing the properties and relationships of the newly proposed decompositions.

Main Results:

  • Introduced three new measures of redundant information and their corresponding PID.
  • Demonstrated how these new measures enrich the existing PID landscape.
  • Proved that Kolchinsky's axioms are compatible with the original Williams and Beer PID axioms.

Conclusions:

  • The proposed methods provide novel and valuable additions to the field of partial information decomposition.
  • The study confirms the consistency of new axiomatic approaches with foundational PID principles.
  • These findings contribute to a deeper understanding of information partitioning in complex systems.