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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

2.0K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
842
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

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Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
1.9K
Rapidly Varying Flow01:24

Rapidly Varying Flow

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Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
370
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

634
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
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Gradually Varying Flow01:29

Gradually Varying Flow

360
Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...
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Related Experiment Video

Updated: Jan 3, 2026

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
06:37

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

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CArtesian sampling with Variable density and Adjustable temporal resolution (CAVA).

Adam Rich1, Michael Gregg1,2, Ning Jin3

  • 1Biomedical Engineering, The Ohio State University, Columbus, OH, USA.

Magnetic Resonance in Medicine
|November 14, 2019
PubMed
Summary
This summary is machine-generated.

A new method, CArtesian sampling with Variable density and Adjustable temporal resolution (CAVA), allows MRI scans to adjust temporal resolution after data acquisition. This technique is effective for real-time phase contrast MRI (PC-MRI) applications.

Keywords:
BayesianCMRgolden ratiophase contrastreal-time

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging Physics

Background:

  • Dynamic MRI applications require precise temporal resolution for accurate physiological measurements.
  • Current methods for adjusting temporal resolution in phase contrast MRI (PC-MRI) are often limited or require pre-acquisition planning.

Purpose of the Study:

  • To develop and validate a novel variable density Cartesian sampling method for dynamic MRI.
  • To enable retrospective adjustment of temporal resolution in real-time PC-MRI.

Main Methods:

  • The CArtesian sampling with Variable density and Adjustable temporal resolution (CAVA) method generates phase encoding indices using a golden ratio increment.
  • Variable density is achieved through nonlinear stretching of these indices, followed by rounding to the nearest integer.
  • CAVA's performance was assessed using a pulsatile flow phantom and real-time, free-breathing PC-MRI data from healthy volunteers.

Main Results:

  • CAVA successfully enabled image recovery with retrospectively selected temporal resolutions.
  • Image quality and flow quantification accuracy using CAVA were comparable to existing pseudo-random sampling techniques.
  • Flow quantification results obtained with CAVA showed good agreement with breath-held segmented acquisitions.

Conclusions:

  • The CAVA method offers a flexible approach for dynamic MRI by allowing retrospective adjustment of temporal resolution.
  • This technique enhances the utility of PC-MRI for real-time, free-breathing applications.