Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

3.3K
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...
3.3K
Sampling Plans01:23

Sampling Plans

1.0K
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...
1.0K
Sample Handling01:02

Sample Handling

2.7K
Transportation of samples from the collection point to the laboratory, as well as storage and preservation techniques, are crucial for maintaining sample integrity and ensuring accurate and reliable test results.
Samples should be transported carefully from collection points to the laboratory. They should be properly sealed and clearly labeled to prevent cross-contamination. To preserve the sample integrity, optimal temperature conditions during transport are essential. This could involve using...
2.7K
Sampling Theorem01:15

Sampling Theorem

1.4K
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
1.4K
Bandpass Sampling01:17

Bandpass Sampling

550
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
550
Sampling Distribution01:12

Sampling Distribution

18.2K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
18.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Procedural Rigor and Reproducibility in NMR Metabolomics: Community Practices and Challenges.

Critical reviews in analytical chemistry·2026
Same author

Semi-Reduction of Allenes to Access Deuterated Allylic Isotopomers, Isotopologs and Enantioisotopomers.

Angewandte Chemie (International ed. in English)·2026
Same author

Decoherence Principles and Algorithms for One-Dimensional Nonuniform Sampling Schedules for Multidimensional NMR.

Analytical chemistry·2025
Same author

Securing the Future of NMR Metabolomics Reproducibility: A Call for Standardized Reporting.

Analytical chemistry·2025
Same author

Optimizing the Synthesis of Deuterated Isotopomers and Isotopologues of Cyclohexene using Molecular Rotational Resonance Spectroscopy.

Journal of the American Chemical Society·2025
Same author

Remodeling of Cellular Respiration and Insulin Signaling Are Part of a Shared Stress Response in Divergent Bee Species.

Insects·2025
Same journal

Localization-driven exchange contrast in diffusion exchange spectroscopy.

Journal of magnetic resonance (San Diego, Calif. : 1997)·2026
Same journal

4.5 Tesla superconducting miniature magnet in liquid nitrogen.

Journal of magnetic resonance (San Diego, Calif. : 1997)·2026
Same journal

Folding and unfolding dynamics of a DNA aptamer studied by heteronuclear <sup>1</sup>H-<sup>13</sup>C correlation zz-exchange spectroscopy.

Journal of magnetic resonance (San Diego, Calif. : 1997)·2026
Same journal

Multi-spin control from one-spin pulses.

Journal of magnetic resonance (San Diego, Calif. : 1997)·2026
Same journal

Altering MRI rotating frame relaxations by changing the truncation level of Hyperbolic Secant pulse.

Journal of magnetic resonance (San Diego, Calif. : 1997)·2026
Same journal

Effects of proton exchange on the lifetimes of long-lived states in aliphatic chains.

Journal of magnetic resonance (San Diego, Calif. : 1997)·2026
See all related articles

Related Experiment Video

Updated: Feb 14, 2026

An All-in-one Sample Holder for Macromolecular X-ray Crystallography with Minimal Background Scattering
07:55

An All-in-one Sample Holder for Macromolecular X-ray Crystallography with Minimal Background Scattering

Published on: July 6, 2019

13.9K

Nonuniform sampling by quantiles.

D Levi Craft1, Reilly E Sonstrom1, Virginia G Rovnyak2

  • 1Department of Chemistry, Bucknell University, Lewisburg, PA 17837, United States.

Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|February 18, 2018
PubMed
Summary
This summary is machine-generated.

A new quantile-directed sampling strategy offers flexible, reproducible, and dimension-generalizable methods for nonuniformly sampled Nuclear Magnetic Resonance (NMR) experiments. This approach minimizes data gaps by adhering closely to probability distribution functions.

Keywords:
Data samplingNonuniform samplingPoint spread functionQuantilesSensitivitySparse sampling

More Related Videos

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis
10:16

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

Published on: December 16, 2016

51.0K
Seawater Sampling and Collection
08:23

Seawater Sampling and Collection

Published on: June 17, 2009

20.9K

Related Experiment Videos

Last Updated: Feb 14, 2026

An All-in-one Sample Holder for Macromolecular X-ray Crystallography with Minimal Background Scattering
07:55

An All-in-one Sample Holder for Macromolecular X-ray Crystallography with Minimal Background Scattering

Published on: July 6, 2019

13.9K
Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis
10:16

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

Published on: December 16, 2016

51.0K
Seawater Sampling and Collection
08:23

Seawater Sampling and Collection

Published on: June 17, 2009

20.9K

Area of Science:

  • Nuclear Magnetic Resonance (NMR) spectroscopy
  • Data acquisition strategies
  • Statistical sampling methods

Background:

  • Non-uniform sampling (NUS) in NMR reduces experimental time but requires optimized sampling schedules.
  • Existing NUS methods can lack flexibility and reproducibility across different weighting functions and dimensions.

Purpose of the Study:

  • To present a flexible and reproducible sampling strategy for nonuniformly sampled NMR experiments.
  • To develop a method that adheres closely to probability distribution functions, minimizing data gaps.
  • To generalize the strategy for multidimensional NMR experiments.

Main Methods:

  • Utilizing statistical quantiles to divide weighting functions into regions of equal probability for sample selection.
  • Implementing quantile-directed scheduling for 1D and higher-dimensional NUS.
  • Investigating jittering parameters to disrupt subharmonic tracts in unweighted sampling.
  • Proposing supplemental components for nD-NUS: corner sample forcing, triangular backfill, and edge forcing.

Main Results:

  • Quantile scheduling achieves close adherence to probability distribution functions, minimizing gaps for a given subsampling degree.
  • One-dimensional weighted NUS schedules are deterministic; higher-dimensional schedules are similar within a jitter parameter.
  • Minimum jitter criteria for unweighted sampling were investigated and met within 25-50% of the subharmonic gap.
  • Supplemental components enhance nD-NUS schedules for specific sampling requirements.

Conclusions:

  • Quantile-directed scheduling provides an intuitive, flexible, and reproducible strategy for diverse NUS needs.
  • The method is generalizable to multiple dimensions and applicable to current and future NUS implementations.
  • A software program (QSched) implementing 1D and 2D-NUS quantile scheduling is publicly available.