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Related Concept Videos

Range00:59

Range

13.9K
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
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
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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.
In alkenes, spin information is communicated via σ–π overlap, as seen in allylic (four-bond) and homoallylic (five-bond) couplings. These coupling interactions are stronger when the σ bond is parallel to the alkene...
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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

781
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...
781
Range Rule of Thumb to Interpret Standard Deviation01:13

Range Rule of Thumb to Interpret Standard Deviation

13.4K
The range rule of thumb in statistics helps us calculate a dataset's minimum and maximum values with known standard deviation. This rule is based on the concept that 95% of all values in a dataset lie within two standard deviations from the mean.
For instance, the range rule of thumb can be used to find the tallest and the shortest student in a class, given the mean student height and standard deviation. If the mean student height is 1.6 m and the standard deviation, s is 0.05 m, the height...
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Circular Shaft - Stresses in Linear Range01:13

Circular Shaft - Stresses in Linear Range

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Consider a scenario where a circular shaft is subject to torque that remains within the boundaries of Hooke's Law, avoiding any permanent deformation. So, the formula for shearing strain is revisited. This formula is multiplied by the modulus of rigidity, and then Hooke's Law for the shearing stress and strain is applied. As a result, the equation for shearing stress in a shaft can be derived.
713

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Associated Chromosome Trap for Identifying Long-range DNA Interactions
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Multi-resolution dimer models in heat baths with short-range and long-range interactions.

Ravinda S Gunaratne1, Daniel B Wilson1, Mark B Flegg2

  • 1Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK.

Interface Focus
|May 9, 2019
PubMed
Summary
This summary is machine-generated.

This study explores multi-resolution simulation methods for dimer models. These techniques efficiently model heat baths interacting with monomers, offering a valid alternative to macroscopic Langevin equations.

Keywords:
Langevin dynamicsgeneralized Langevin equationintermolecular interactionsmolecular dynamicsmulti-resolution modellingmultiscale methods

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Area of Science:

  • Computational chemistry
  • Molecular dynamics
  • Multiscale modeling

Background:

  • Simulating dimer models requires efficient methods for handling heat bath interactions.
  • Solvent particles interact with dimer monomers via short-range collisions and long-range harmonic springs.

Purpose of the Study:

  • To investigate multi-resolution methodologies for simulating dimer models.
  • To analyze the impact of shared versus uncoupled heat baths on dimer dynamics.
  • To validate these methods against macroscopic Langevin equations.

Main Methods:

  • Developing and applying two multi-resolution approaches.
  • Method (a): Coarser representation of distant solvent particles.
  • Method (b): Differentiated resolution models for individual monomers.

Main Results:

  • The study successfully implemented and tested multi-resolution simulation techniques.
  • Investigated the distinct effects of shared and uncoupled heat baths.
  • Demonstrated the validity of the multi-resolution methods through comparison with Langevin dynamics.

Conclusions:

  • Multi-resolution methodologies offer an efficient approach for simulating dimer models with complex heat bath interactions.
  • These methods provide a computationally tractable way to study system dynamics.
  • The findings support the use of multiscale modeling in molecular simulations.