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Related Concept Videos

Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
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Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the concentration...
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Diffusion01:21

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Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
Diffusion01:12

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Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...

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Measuring the Switch Cost of Smartphone Use While Walking
07:00

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Published on: April 30, 2020

Decomposing task-switching costs with the diffusion model.

Florian Schmitz1, Andreas Voss

  • 1Institut fur Psychologie, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. florian.schmitz@psychologie.uni-freiburg.de

Journal of Experimental Psychology. Human Perception and Performance
|November 9, 2011
PubMed
Summary
This summary is machine-generated.

This study reveals task switching occurs in phases, with early reconfiguration and later response selection influenced by inertia. Predictable task switches involve response caution impacting costs.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience

Background:

  • Task switching involves cognitive control to shift between tasks.
  • Multiple-component models propose sequential phases in task switching.

Purpose of the Study:

  • Investigate task-switching processes using distinct experimental paradigms.
  • Dissociate components of task-switching costs via the diffusion model.
  • Examine the role of inertia and response caution in task switching.

Main Methods:

  • Employed variants of the alternating runs and explicit cueing paradigms.
  • Utilized the diffusion model for binary decisions to analyze response times and accuracy.
  • Investigated inertia effects and response caution in predictable task switches.

Main Results:

  • Task switching aligns with successive phase models: early task-set reconfiguration/cue-encoding, followed by response selection.
  • Inertia effects impact the later response selection stage.
  • Response caution contributes to both global and local switching costs in predictable scenarios.

Conclusions:

  • Findings support multi-phase models of task switching.
  • Inertia and response caution are key factors influencing switching costs.
  • The diffusion model effectively differentiates task-switching components.