Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Probability Distributions01:32

Probability Distributions

13.0K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
13.0K
Methods of Medium Optimization01:28

Methods of Medium Optimization

1
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
1
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

687
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
687
Binomial Probability Distribution01:15

Binomial Probability Distribution

16.4K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
16.4K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

309
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
309
Pharmacodynamic Models: Additive and Proportional Drug Effect Model01:09

Pharmacodynamic Models: Additive and Proportional Drug Effect Model

55
Drug response models describe how pharmacological agents interact with biological systems to produce measurable effects. Baseline responses are inherent physiological activities without a drug significantly influencing the observed pharmacological outcomes. Depending on the drug response model employed, these baseline responses may combine with the drug's effect in either an additive or proportional manner.Additive Drug Response ModelIn the additive model, the drug effect is independent of the...
55

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Time-dependent personalized PageRank for temporal networks: Discrete and continuous scales.

Chaos (Woodbury, N.Y.)·2024
Same author

Can the PageRank centrality be manipulated to obtain any desired ranking?

Chaos (Woodbury, N.Y.)·2023
Same author

Distances in Higher-Order Networks and the Metric Structure of Hypergraphs.

Entropy (Basel, Switzerland)·2023
Same author

A comprehensive approach for discrete resilience of complex networks.

Chaos (Woodbury, N.Y.)·2023
Same author

Parametric controllability of the personalized PageRank: Classic model vs biplex approach.

Chaos (Woodbury, N.Y.)·2020
Same author

On the edges' PageRank and line graphs.

Chaos (Woodbury, N.Y.)·2018
Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
Same journal

State estimation in spatiotemporal chaos via low-rank StatFEM.

Chaos (Woodbury, N.Y.)·2026
Same journal

Universal response functions in driven dissipative tunneling dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

A network-based approach to characterize the dynamics of the coupling field of thermoacoustic oscillators in annular geometry.

Chaos (Woodbury, N.Y.)·2026
See all related articles

Related Experiment Video

Updated: Mar 18, 2026

Rapid Development of Cell State Identification Circuits with Poly-Transfection
09:21

Rapid Development of Cell State Identification Circuits with Poly-Transfection

Published on: February 24, 2023

2.0K

Optimal distributions for multiplex logistic networks.

Luis E Solá Conde1, Javier Used2, Miguel Romance3

  • 1Dipartimento di Matematica, Università di Trento, Trento, Italy.

Chaos (Woodbury, N.Y.)
|July 3, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces mathematical models for optimizing goods distribution in complex logistic networks using spectral analysis. It presents algorithms to improve convergence rates for network equilibrium, with applications to Germany and Spain.

More Related Videos

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications
13:14

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Published on: April 14, 2015

9.8K
Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors
06:32

Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors

Published on: August 18, 2023

3.2K

Related Experiment Videos

Last Updated: Mar 18, 2026

Rapid Development of Cell State Identification Circuits with Poly-Transfection
09:21

Rapid Development of Cell State Identification Circuits with Poly-Transfection

Published on: February 24, 2023

2.0K
Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications
13:14

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Published on: April 14, 2015

9.8K
Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors
06:32

Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors

Published on: August 18, 2023

3.2K

Area of Science:

  • Operations Research
  • Network Science
  • Applied Mathematics

Background:

  • Optimizing distribution networks is crucial for efficient supply chains.
  • Complex network analysis offers novel approaches to logistic challenges.
  • Spectral analysis provides tools for understanding network dynamics.

Purpose of the Study:

  • To develop mathematical models for goods distribution in logistic networks.
  • To compute network weights for achieving equilibrium dynamics with high convergence rates.
  • To apply and analyze these models to real-world logistic networks.

Main Methods:

  • Spectral analysis of complex networks.
  • Development of numerical algorithms for weight computation.
  • Equilibrium dynamics and convergence rate analysis.

Main Results:

  • Mathematical models for goods distribution were established.
  • Algorithms were presented for computing multiplex logistic network weights.
  • High convergence rates towards equilibrium dynamics were achieved.
  • Application to German and Spanish logistic networks demonstrated effectiveness.

Conclusions:

  • The proposed models and algorithms enhance the efficiency of logistic networks.
  • Spectral analysis is a valuable tool for optimizing distribution systems.
  • The study provides insights into the convergence properties of real-world logistic networks.