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Related Concept Videos

What is Variation?01:14

What is Variation?

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Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
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Variation01:19

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An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
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Conservative Site-specific Recombination and Phase Variation02:53

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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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The coefficient of variation measures the dispersion of the data points or distribution around the mean. Using the coefficient of variation, we can compare two data series with drastically different means or different units of measurement. The coefficient of variation for a sample and a population is expressed as a percentage of the ratio of standard deviation to the mean.
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Spatial variations of pollutants from sewer interception system overflow.

Sidian Chen1, Hua-Peng Qin1, Yu Zheng1

  • 1Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, 518055 Shenzhen, China.

Journal of Environmental Management
|October 15, 2018
PubMed
Summary
This summary is machine-generated.

Sewer interception system overflows (ISOs) increase downstream, with runoff being a key COD source. Sewer separation reduces sewage pollution but not runoff pollution, necessitating improved downstream capacity and source control.

Keywords:
Interception system overflowRunoffSWMMSewageSpatial variationUrbanization

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Area of Science:

  • Environmental Engineering
  • Urban Hydrology
  • Water Quality Management

Background:

  • Rapid urbanization leads to misconnections in sewer systems, causing combined sewage overflows (CSOs) into rivers.
  • Interception system overflows (ISOs) can spatially vary due to interactions between different overflow points.

Purpose of the Study:

  • To understand the spatial variation of pollutants from ISOs in urban river systems.
  • To analyze the impact of sewer separation on ISOs and inform mitigation strategies.

Main Methods:

  • Utilized the Storm Water Management Model (SWMM) for simulation.
  • Analyzed an urbanized catchment in China as a case study.
  • Examined pollutant sources (runoff vs. sewage) and their downstream trends.

Main Results:

  • Overflows trigger at lower rainfall amounts downstream, while ISO volumes and pollutant loads increase downstream.
  • Runoff is the primary source of Chemical Oxygen Demand (COD), and sewage is the primary source of Ammonia Nitrogen (NH3-N).
  • Sewer separation effectively reduces sewage-derived pollutant loads but has limited impact on runoff-derived loads.

Conclusions:

  • Downstream interceptor capacity should be increased to mitigate ISO pollution.
  • Separating sewage from runoff and implementing source control for urban runoff are crucial for highly urbanized areas.