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Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

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Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
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Aggregate shape is classified based on the relative sharpness or roundness of the edges and corners. This classification includes categories like rounded, angular, elongated, and flaky, each with specific characteristics. Rounded aggregates, fully shaped by attrition, are typical of river or seashore gravel, while angular aggregates, such as crushed rock, have well-defined edges. Aggregates that are elongated and flaky are less desirable, as they can reduce the workability and strength of...
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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Modeling crowd dynamics through coarse-grained data analysis.

Sebastien Motsch1, Mehdi Moussaïd, Elsa G Guillot

  • 1School of Mathematical and Statistical Sciences, Arizona State University, Tempe, USA.

Mathematical Biosciences and Engineering : MBE
|November 13, 2018
PubMed
Summary
This summary is machine-generated.

We developed a Bi-directional Macroscopic (BM) model to predict crowd movement. Laboratory experiments show the BM model accurately captures pedestrian flow, aiding crowd management and safety.

Keywords:
bi-directional fluxPedestrian trafficcollective behaviourdata-based modelingmacroscopic model

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Area of Science:

  • Physics
  • Urban Planning
  • Social Sciences

Background:

  • Effective crowd management is crucial for urban safety and efficiency.
  • Current systems lack rapid prediction capabilities for dynamic crowd behavior.

Purpose of the Study:

  • To introduce a Bi-directional Macroscopic (BM) model for predicting crowd movement.
  • To validate the model's accuracy using experimental data.
  • To explore optimization strategies for crowd traffic efficiency.

Main Methods:

  • Developed a Bi-directional Macroscopic (BM) model based on pedestrian flux and density.
  • Conducted laboratory experiments with 119 participants in a circular corridor.
  • Utilized experimental data to validate the BM model's predictive performance.

Main Results:

  • The BM model accurately captured experimental data for bi-directional pedestrian flows.
  • The model demonstrated effectiveness in a typical crowd forecasting scenario.
  • A segregation strategy was proposed and analyzed for traffic enhancement.

Conclusions:

  • The BM model provides a reliable core for crowd traffic management systems.
  • It enables on-the-fly prediction of crowd movements for real-time optimization.
  • The model supports the deployment of tailored crowd control strategies.