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Related Concept Videos

Poisson Probability Distribution01:09

Poisson Probability Distribution

A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
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Poisson's Ratio

Poisson's ratio is a material property that indicates their stress response. It explains the connection between the elongation or compression a material undergoes in the direction of an applied force and the contraction or expansion it experiences perpendicular to that force. When a slender bar is loaded axially, it stretches in the direction of the force and contracts laterally. Poisson's ratio is the negative ratio of this lateral contraction to the axial elongation. The negative sign ensures...
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Poisson's And Laplace's Equation

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Pore Size Distribution01:23

Pore Size Distribution

In concrete, the pore size distribution significantly influences the material's properties. Capillary pores, markedly larger than gel pores, form a vast network within partially hydrated cement paste, reducing the concrete's strength and increasing its permeability. This heightened permeability leads to a greater risk of damage from environmental factors like freeze-thaw cycles and chemical attacks, with the extent of vulnerability also being tied to the water-to-cement ratio.
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Testing a Claim about Population Proportion01:24

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A complete procedure for testing a claim about a population proportion is provided here.
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Fisher's Exact Test

Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of the...

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High Throughput Single-cell and Multiple-cell Micro-encapsulation
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High Throughput Single-cell and Multiple-cell Micro-encapsulation

Published on: June 15, 2012

Beating Poisson encapsulation statistics using close-packed ordering.

Adam R Abate1, Chia-Hung Chen, Jeremy J Agresti

  • 1School of Engineering and Applied Sciences/Department of Physics, Harvard University, Cambridge, Massachusetts, USA.

Lab on a Chip
|August 26, 2009
PubMed
Summary
This summary is machine-generated.

Efficiently loading microfluidic drops with particles or cells is crucial for assays. We developed a method using deformable particles for controlled, efficient loading, ensuring every drop contains the desired number of objects.

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Area of Science:

  • Biotechnology
  • Microfluidics
  • Particle encapsulation

Background:

  • Microfluidic devices are essential for chemical and biological assays.
  • Efficient loading of discrete objects like particles and cells into microfluidic drops is a significant challenge.
  • Current random loading methods result in many empty or unusable drops, reducing assay efficiency.

Purpose of the Study:

  • To develop a novel method for efficient and controllable particle loading in microfluidic drops.
  • To overcome the limitations of random loading techniques in microfluidic assays.
  • To ensure a predictable number of particles are encapsulated in every microfluidic drop.

Main Methods:

  • Utilizing deformable particles for close packing within microfluidic drops.
  • Implementing a controlled loading strategy based on particle deformability and packing.
  • Testing the efficiency and controllability of the developed loading technique.

Main Results:

  • Demonstrated efficient encapsulation of a controllable number of particles in every drop.
  • Significantly reduced the number of empty or unusable drops compared to random loading.
  • Showcased the flexibility of the method for various particle types and sizes.

Conclusions:

  • The developed method offers a simple and flexible solution for efficient particle loading in microfluidics.
  • This technique enhances the reliability and throughput of microfluidic-based chemical and biological assays.
  • Controlled particle encapsulation is achievable using deformable particles and close-packing principles.