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Related Concept Videos

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...
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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...
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Sample Handling01:02

Sample Handling

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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...
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Sampling Theorem01:15

Sampling Theorem

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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.
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Bandpass Sampling01:17

Bandpass Sampling

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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....
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Sampling Distribution01:12

Sampling Distribution

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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...
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Related Experiment Video

Updated: Jan 31, 2026

Clean Sampling and Analysis of River and Estuarine Waters for Trace Metal Studies
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Microbacterium ureisolvens sp. nov., isolated from a Yellow River sample.

Li-Jiao Cheng1, Hong Ming2, Zhuo-Li Zhao1

  • 11​College of Fisheries, Henan Normal University, Xinxiang, 453007, PR China.

International Journal of Systematic and Evolutionary Microbiology
|December 22, 2018
PubMed
Summary

A novel bacterium, Microbacterium ureisolvens sp. nov., was discovered in Yellow River sediment. This Gram-positive, aerobic bacterium exhibits unique physiological and chemotaxonomic traits, distinguishing it as a new species within the Microbacterium genus.

Keywords:
Microbacterium ureisolvens sp. novYellow Riverpolyphasic taxonomy

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Area of Science:

  • Microbiology
  • Bacteriology
  • Taxonomy

Background:

  • The genus Microbacterium comprises diverse Gram-positive bacteria found in various environments.
  • Accurate taxonomic classification is crucial for understanding microbial diversity and ecological roles.

Purpose of the Study:

  • To characterize a newly isolated bacterial strain, CFH S00084T, from a sediment sample.
  • To determine the phylogenetic and taxonomic position of strain CFH S00084T within the Microbacterium genus.

Main Methods:

  • Isolation and cultivation of strain CFH S00084T from Yellow River sediment.
  • Phylogenetic analysis using 16S rRNA gene sequences.
  • Physiological, chemotaxonomic, and genomic analyses (including whole-cell sugars, peptidoglycan composition, menaquinones, fatty acids, genome size, and G+C content).
  • Average Nucleotide Identity (ANI) and digital DNA-DNA hybridization (dDDH) calculations.

Main Results:

  • Strain CFH S00084T is a Gram-positive, aerobic, non-motile, short-rod-shaped bacterium.
  • Phylogenetic analysis showed close relatedness to Microbacterium yannicii and Microbacterium arthrosphaerae, but with significant genetic divergence.
  • Optimal growth observed at 25–37 °C, pH 7.0, and 0–3% NaCl.
  • Chemotaxonomic data revealed rhamnose and glucose as major sugars, with specific peptidoglycan and fatty acid profiles.
  • Genomic analysis indicated a genome size of 4.03 Mbp with 70.5% G+C content.
  • Low ANI (<85%) and dDDH (<24%) values confirmed its distinction from known Microbacterium species.

Conclusions:

  • Strain CFH S00084T represents a novel species within the genus Microbacterium.
  • The proposed name for this new species is Microbacterium ureisolvens sp. nov.
  • The type strain is CFH S00084T (=KCTC 39802T=DSM 103157T).