ライフサイエンスコーパス: mean-square displacement

1 t the surface diffusion coefficient from the mean square displacement.

2 impose tortuosity within the diffusion root mean-square displacement.

3 the high q data were interpreted in terms of mean square displacements.

4 on that can fit experimental measurements of mean-square displacements.

5 lated the propagation of these errors on the mean-squared displacement.

6 itatively predicts the rapid increase of the mean-square displacement above approximately 200 K, show

7 The extracted mean square displacements also reveal a greater motional

8 We show that image mean square displacement analysis, applied to single pla

9 Mean-square displacement analysis of individual trajecto

10 ct on confined molecules because the typical mean-square-displacement analysis does not account for t

11 showed anomalous diffusion, as determined by mean-square-displacement analysis.

12 s unveiled by the confidence interval of the mean square displacement and by the dynamical functional

13 ants were determined from linear fits to the mean square displacement and from the mean displacement

14 The root mean square displacement and the corresponding absolute

15 By comparing the mean squared displacement and the response function we d

16 , picosecond timescale, small changes in the mean-square displacement and <k'> are observed, which ar

17 hat captures the power law dependence of the mean-square displacement and can be shown to rigorously

18 ormational space is examined in terms of the mean-square displacement and principal component analysi

19 Mean-square displacements and protein resilience on the

20 at equivalent hydration level, GFP dynamics (mean-square displacements and quasielastic intensity) ar

21 ions or nanoparticles in mucus have measured mean-square displacements and reported diffusion coeffic

22 re analyzed to yield interaction potentials, mean-square displacements, and colloid-surface associati

23 lowed us to achieve higher resolution in the mean-squared displacement, and thus to increase the accu

24 combine this analysis with the image-derived mean-square displacement approach and gain information o

25 rrors in interparticle separation, angle and mean square displacement are significantly reduced by ap

26 The mean square displacements are well described by a stocha

27 Our results for the mean-square displacement are consistent with a recent ex

28 ega is the frequency, (ii) shear modulus and mean-squared displacement are inversely proportional wit

29 n averaging of the displacements such as the mean square displacement, are not adapted to the analysi

30 theory is a sigmoid curve of the observable mean square displacement as a function of the ratio of d

31 and also yields the correct amplitude of its mean square displacement at long times.

32 in the gradient with T of the average atomic mean-square displacement at approximately 220 K.

33 alization errors in the determination of the mean-squared displacement by separating the sources of t

34 ent technique applies the calculation of the mean square displacement commonly used in single-molecul

35 The mean-squared displacement correlation with time lag had

36 revealed a previously unreported grouping of mean-squared displacement curves at short timescales (<1

37 als that, in the absence of a net force, the mean squared displacement depends on time as t(0.7), in

38 Anomalous diffusion, in which mean squared displacement does not increase linearly wit

39 iting factors that alter the accuracy of the mean-squared displacement estimation.

40 moved with significantly higher subdiffusive mean square displacement exponents than previously repor

41 an order of magnitude over the perpendicular mean-square displacements for both surfaces.

42 For 28 computed structures, the root mean squared displacement from the average structure exc

43 denotes random molecular motion in which the mean square displacements grow as a power law in time wi

44 The movement is superballistic with the mean square displacement growing with time as [Formula:

45 ge Correlation Spectroscopy (RICS) and image-Means Square Displacement (iMSD) were applied to quantif

46 ed from the temperature dependence of atomic mean-squared displacements in molecular dynamics simulat

47 higher diffusion coefficient, and increased mean-squared displacements in neutron scattering experim

48 give both the rate at which single-particle mean square displacements increase and the rate at which

49 reveal unusual Brownian motion in which the mean square displacement increases as a fractional power

50 In classical diffusion, the mean-square displacement increases linearly with time.

51 ch media foster anomalous subdiffusion (with mean-squared displacement increasing less than linearly

52 anomalous diffusion may occur, in which the mean-square displacement is proportional to a nonintegra

53 ents using single-particle tracking in which mean-square displacement is simply proportional to time

54 oves with a constant intermediate speed, the mean-square displacement is strongly enhanced.

55 fusion models defined by arbitrary nonlinear mean-squared displacement <x2> versus time relations.

56 t exposure levels are very low and the image mean square displacement method does not require calibra

57 and dynamic properties often evaluated using mean square displacement (MSD) analysis.

58 alyses of random walks traditionally use the mean square displacement (MSD) as an order parameter cha

59 The ensemble-averaged mean square displacement (MSD) exhibits superdiffusive b

60 A three-stage dynamics governs the mean square displacement (MSD) of water molecules, with

61 The combination of mean squared displacement (MSD) and cumulative distribut

62 of particles in mucus, based on the measured mean squared displacements (MSD).

63 ansient subdiffusive temporal scaling of the mean-square displacement (MSD proportional, variant tau

64 Conventional mean-square displacement (MSD) analysis of single-partic

65 A local mean-square displacement (MSD) analysis separates ballis

66 lding/nonfolding dynamics is examined by the mean-square displacement (MSD) and the fractional diffus

67 usion at short timescales (t<7 s) with their mean-square displacement (MSD) Deltax(t)2 scaling as t1.

68 nserved waters reflected substantially lower mean-square displacement (msd) in all simulations, excep

69 mpare the distribution of the time-dependent mean-square displacement (MSD) of polystyrene microspher

70 es inside the cell from a tracked particle's mean-square displacement (MSD).

71 Here, we demonstrate, by using mean-square displacements (msd) from Mossbauer and neutr

72 ion and 30Hz temporal resolution, from which mean-squared displacement (MSD) and viscosity distributi

73 Mean-squared displacements (MSD) and protein resilience

74 ion rate constant is shown to scale with the mean square displacement of a receptor-ligand complex.

75 agonist activation resulted in a decline in mean square displacement of both receptors, but the drop

76 Analyzing the mean square displacement of GFP intensity changes in liv

77 pond to the calculation of a certain kind of mean square displacement of the animals relevant to the

78 Finally, the measured mean square displacement of the optical probes, which is

79 backscattering spectroscopy showed that the mean square displacements of H atoms do exhibit an incre

80 riterion to fail in 2D in the sense that the mean squared displacement of atoms is not limited.

81 m might be "anomalous" in the sense that the mean squared displacement of particles follows a power l

82 average particle dynamics, quantified by the mean squared displacement of the individual particles, a

83 by the extent and time-lag dependence of the mean squared displacements of thermally excited nanopart

84 The distribution of the mean squared displacements of these microspheres becomes

85 with a correlation length of 10 A and a root-mean-square displacement of 0.36 A.

86 shows no orientation preference over a root mean-square displacement of 2.5-3.5 microm.

87 At intermediate times, the mean-square displacement of a diffusing object shows a t

88 diffusion is hindered diffusion in which the mean-square displacement of a diffusing particle is prop

89 eir "native" states, we demonstrate that the mean-square displacement of dihedral angles, defined by

90 e and the rotational diffusion, recovers the mean-square displacement of P. putida if the two distinc

91 The mean-square displacement of single, bound proteoglycans

92 ar scattering geometry yielded perpendicular mean-square displacements of 2.7*10(-4) A(2) K(-1) and 3

93 ed, including radial distribution functions, mean-square displacements of lipids and nanoparticle, ch

94 Mean-square displacements of localized internal motions

95 sing a windowing technique by regressing the mean-squared displacement of cells tracked at high magni

96 The mean-squared displacement of the resulting trajectories

97 The time-dependent ensemble-averaged mean-squared displacements of all of the particles were

98 tein perdeuteration, we found similar atomic mean-square displacements over a large temperature range

99 f microscopic displacement, (4) increases in Mean-Squared-Displacement over prolonged time periods ac

100 , mediolateral range (p=0.008), and critical mean square displacement (p=0.012).

101 The image-mean square displacement plot obtained is similar to the

102 displacement plot obtained is similar to the mean square displacement plot obtained using the single-

103 Analysis of the root-mean-squared displacement plots for all of the data reve

104 Analyses of the atomic mean-squared displacement, relaxation time, persistence

105 r estimates, as well as the ensemble average mean square displacement reveal subdiffusive behavior at

106 with a subset of CTP scaffolds with an root-mean-square displacement (RMSD) of approximately 0.5 A.

107 The image-mean square displacement technique applies the calculati

108 that the technique outperforms the classical mean-square-displacement technique when forces act on co

109 m the uncaging spot in all directions with a mean square displacement that varied linearly with time,

110 of competing motion models based on particle mean-square displacements that automatically classifies

111 ed trajectories are exploited to compute the mean-squared displacement that characterizes the dynamic

112 We explain why fits of subdiffusive mean-square displacements to standard diffusion models m

113 ure times reveals negatively curved plots of mean-square displacement versus time.

114 usion models, suggesting how measurements of mean-squared displacement versus time might generally in

115 ined directly from imaging, in the form of a mean-square displacement vs. time-delay plot, with no ne

116 S. cerevisiae cells and improved analysis of mean square displacements, we quantified DNA motion at t

117 specular angles to characterize the parallel mean-square displacements, which were found to increase

118 lasm-embedded particles are transformed into mean-squared displacements, which are subsequently trans