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Related Concept Videos

Range00:59

Range

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The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
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¹H NMR: Long-Range Coupling01:27

¹H NMR: Long-Range Coupling

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The coupling interactions of nuclei across four or more bonds are usually weak, with J values less than 1 Hz. While these are usually not observed in spectra, the presence of multiple bonds along the coupling pathway can result in observable long-range coupling.
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Heat and Free Expansion01:24

Heat and Free Expansion

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The work done by a thermodynamic system depends not only on the initial and final states but also on the intermediate states—that is, on the path. Like work, when heat is added to a thermodynamic system, it undergoes a change of state, and the state attained depends on the path from the initial state to the final state. Consider an ideal gas cylinder fitted with a piston. When the cylinder is heated at a constant temperature, the gas molecules absorb energy and expand slowly in a...
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Thermal Expansion01:22

Thermal Expansion

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The expansion of alcohol in a thermometer is one of many commonly encountered examples of thermal expansion, which is the change in size or volume of a given system as its temperature changes. The most visible example is the expansion of hot air. When air is heated, it expands and becomes less dense than the surrounding air, which then exerts an upward force on the hot air to, for example, make steam and smoke rise, and hot air balloons float. The same behavior happens in all liquids and gases,...
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Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

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In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
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Angle of Twist - Elastic Range01:13

Angle of Twist - Elastic Range

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Consider a cylindrical shaft with a length denoted by L and a consistent cross-sectional radius referred to as r. This shaft undergoes a torque at the free end. The highest shearing strain within the shaft is directly proportional to the twist angle and the radial distance from the shaft axis. When the shaft behaves elastically, this shearing strain can be articulated using variables such as the applied torque, radial distance, the polar moment of inertia, and the modulus of rigidity. By...
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Rapid microevolution during recent range expansion to harsh environments.

Yiyong Chen1,2, Noa Shenkar3,4, Ping Ni1,2

  • 1Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District, Beijing, 100085, China.

BMC Evolutionary Biology
|December 12, 2018
PubMed
Summary
This summary is machine-generated.

Marine tunicates rapidly adapted to the Red Sea

Keywords:
Adaptive genesBiological invasionCiona robustaInvasive speciesRange expansionRapid microevolutionRed Sea

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Area of Science:

  • Evolutionary biology
  • Marine biology
  • Genetics

Background:

  • Adaptive evolution drives species survival in new environments.
  • Rapid evolution is observed during range expansion, but genetic evidence is often lacking.
  • Investigating the genetic basis of rapid microevolution is crucial for understanding environmental adaptation.

Purpose of the Study:

  • To detect genetic signatures of rapid microevolution in Ciona robusta during its Red Sea range expansion.
  • To identify genes and genetic variations responsible for adaptation to harsh environments.

Main Methods:

  • Genome-wide genotyping using gene-associated microsatellites.
  • Analysis of genetic differentiation and allele frequency variation.
  • Correlation analysis between allele frequencies and local environmental factors.

Main Results:

  • The Red Sea Ciona robusta population showed significant genetic differentiation.
  • A set of adaptive genes were identified, with significant allele frequency variations.
  • Allele frequencies correlated with local temperature and salinity, indicating adaptation.

Conclusions:

  • Environment-driven selection leaves detectable genomic signatures within a few generations.
  • Rapid microevolution facilitates adaptation to harsh environments and invasion success.
  • Identified adaptive genes contribute to Ciona robusta's success in diverse aquatic ecosystems.