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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

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Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
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Simultaneous Live Imaging of Multiple Insect Embryos in Sample Chamber-Based Light Sheet Fluorescence Microscopes08:29

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Light sheet-based fluorescence microscopy is the most valuable tool in developmental biology. A major issue in comparative studies is ambient variance. Our protocol describes an experimental framework for simultaneous live imaging of multiple specimens and, therefore, addresses this issue...
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Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
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Sample Design01:21

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Effective sampling is crucial for ensuring that research results are accurate and applicable. The process starts by identifying the target population, such as regular coffee shop visitors interested in trying new drinks. Clearly defining this group helps focus the study on gathering relevant data from the right people.
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Conducting Multiple Imaging Modes with One Fluorescence Microscope08:32

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Here we present a practical guide of building an integrated microscopy system, which merges conventional epi-fluorescent imaging, single-molecule detection-based super-resolution imaging, and multi-color single-molecule detection, including single-molecule fluorescence resonance energy transfer imaging, into one set-up in a cost-efficient...
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Related Experiment Video

Updated: Jan 19, 2026

Simultaneous Live Imaging of Multiple Insect Embryos in Sample Chamber-Based Light Sheet Fluorescence Microscopes
08:29

Simultaneous Live Imaging of Multiple Insect Embryos in Sample Chamber-Based Light Sheet Fluorescence Microscopes

Published on: September 9, 2020

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Imaging effectiveness calculator for non-design microscope samples.

Stephen M Anthony, Philip R Miller, Jerilyn A Timlin

    Applied Optics
    |September 11, 2019
    PubMed
    Summary
    This summary is machine-generated.

    Microfluidic devices can degrade single-molecule fluorescence microscopy image quality due to non-standard materials. This study offers software to predict and mitigate these optical aberrations for better single-molecule detection.

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    Related Experiment Videos

    Last Updated: Jan 19, 2026

    Simultaneous Live Imaging of Multiple Insect Embryos in Sample Chamber-Based Light Sheet Fluorescence Microscopes
    08:29

    Simultaneous Live Imaging of Multiple Insect Embryos in Sample Chamber-Based Light Sheet Fluorescence Microscopes

    Published on: September 9, 2020

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    Sample Size Calculation
    01:19

    Sample Size Calculation

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    Sample Design
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    Area of Science:

    • Optics
    • Microscopy
    • Biotechnology

    Background:

    • Integrating single-molecule fluorescence microscopy with microfluidic devices presents challenges.
    • Fabrication constraints often necessitate imaging through non-traditional materials, deviating from standard coverslips.
    • Altering material thickness or refractive index significantly degrades image quality, impacting signal-to-noise ratio.

    Purpose of the Study:

    • To develop software for calculating the impact of non-design materials on image formation.
    • To analyze the effects of common microfabrication materials on optical performance metrics like Strehl ratio and ensquared energy.
    • To aid researchers in overcoming optical challenges in integrated microscopy systems.

    Main Methods:

    • Software development for optical aberration calculation.
    • Simulation of light propagation through materials with varying optical properties.
    • Analysis of Strehl ratio and ensquared energy for different material compositions and thicknesses.

    Main Results:

    • Quantified the reduction in image quality (Strehl ratio) caused by common microfabrication materials.
    • Demonstrated that deviations in thickness and refractive index significantly reduce optical performance.
    • Identified specific materials and their optical impact relevant to microfluidic device integration.

    Conclusions:

    • Software provides a predictive tool for assessing optical performance in microfabricated imaging systems.
    • Understanding material optical properties is crucial for successful single-molecule fluorescence detection in integrated devices.
    • Mitigation strategies can be developed based on calculated optical effects to improve image quality.