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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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Mechanical vibrators are instrumental in compacting newly poured concrete within formwork and around reinforcements. This process is essential to eliminate trapped air pockets and establish a dense concrete mass. One widely used method is vibrating by internal vibrators, often referred to as a poker vibrator or immersion vibrator. It is rapidly inserted through the full depth of the freshly laid concrete and slightly extends into the layer below it (which remains in a plastic state). Consistent...
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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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Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
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Frequency Range Selection Method for Vibrational Spectra.

T Q Teodoro1,2, M A J Koenis3, S E Galembeck2

  • 1Amsterdam Center for Multiscale Modeling, Faculty of Science , Vrije Universiteit Amsterdam , de Boelelaan 1083 , 1081 HV Amsterdam , The Netherlands.

The Journal of Physical Chemistry Letters
|November 20, 2018
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Summary

This study introduces an efficient computational method for calculating specific vibrational frequency ranges in large molecules, significantly reducing computation time and maintaining accuracy. This approach optimizes theoretical calculations for experimental spectral analysis.

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Area of Science:

  • Computational Chemistry
  • Spectroscopy
  • Quantum Mechanics

Background:

  • Theoretical calculations of vibrational properties are crucial for interpreting experimental spectra.
  • Standard quantum chemical methods are computationally expensive for large molecules as they consider all molecular motions.

Purpose of the Study:

  • To develop an efficient computational method for calculating only selected vibrational frequency intervals.
  • To reduce the computational cost of vibrational property calculations for large molecules.

Main Methods:

  • A computationally inexpensive low-level estimate of molecular motions is performed first.
  • The computational time is then tailored to the number of normal modes required for the selected frequency range.
  • An optional intensity-selection procedure can further enhance computational savings.

Main Results:

  • The proposed method significantly reduces computational time, up to one order of magnitude for a medium-sized molecule.
  • Accuracy is maintained with negligible loss compared to standard methods.
  • The efficiency is directly related to the size of the selected frequency interval.

Conclusions:

  • The developed method offers a substantial improvement in computational efficiency for vibrational property calculations.
  • This approach is particularly beneficial when only specific spectral regions are of experimental interest.
  • Further optimizations are possible through intensity-based selection, enabling even greater computational savings.