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 ionally relies on calculating the trajectory mean squared displacement.

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

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

7 ble surface area (4.09 +/- 0.04 nm) and root mean square displacement (3.51 +/- 0.00261 nm).

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

9 The extracted mean square displacements also reveal a greater motional

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

11 Mean-square displacement analysis of individual trajecto

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

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

14 le quantification of the "hard corona" using mean-squared displacement analysis.

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

16 tin dynamics in real time and determined the mean square displacement and diffusion constant for the

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

18 The root mean square displacement and the corresponding absolute

19 sults closely matching experimental plots of mean square displacements and probability density functi

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

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

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

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

24 Mean-square displacements and protein resilience on the

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

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

27 of glassy dynamics, such as plateaus in the mean-squared displacement and the self-intermediate scat

28 hat ensemble-averaged quantities such as the mean-squared displacements and velocity autocorrelation

29 s that includes trajectories, motile speeds, mean squared displacement, and turning angles-while prov

30 Correlation functions, mean squared displacements, and velocity distributions r

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

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

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

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

35 The mean square displacements are well described by a stocha

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

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

38 ort and the related anomalous scaling of the mean-squared displacement are regulated by cytoskeleton

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

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

41 cales and 2) their inversion to retrieve the mean-squared displacement associated with the process un

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

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

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

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

46 The mean-squared displacement correlation with time lag had

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

48 Average diffusion coefficients obtained from mean square displacement (D(MSD)) data were 20-100% larg

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

50 e of the cell migration, such as cell speed, mean-squared displacement, diffusivity, persistence, spe

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

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

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

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

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

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

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

58 opulations has shown evidence of diffusion - mean squared displacements growing linearly in time - an

59 We calculate an imaging-derived Mean Squared Displacement (iMSD), which simultaneously p

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

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

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

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

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

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

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

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

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

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

70 meters and compute key observables-including mean square displacement, kinetic energy, potential ener

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

72 h fluids are differentiated by measuring the mean-squared-displacement <Deltar(2)> of embedded tracer

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

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

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

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

77 of the mixtures were investigated using the mean square displacement (MSD) of the centers of mass of

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

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

80 so predicts the subdiffusive behavior of the mean squared displacement (MSD) on short, intermediate t

81 y densifying glass and measure the resulting mean squared displacement (MSD).

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

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

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

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

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

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

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

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

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

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

92 iculate trajectory data have been limited to mean-squared displacement (MSD) analysis.

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

94 urth equation, the usual characterization of mean-squared displacement (MSD) curves for migrating cel

95 Mean-squared displacements (MSD) and protein resilience

96 lective scattering significantly affects DWS mean-square displacements (MSDs) in dense colloidal emul

97 alpha, which is typically obtained from the mean-square displacements (MSDs).

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

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

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

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

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

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

104 g passive microrheology via videomicroscopy, mean square displacements of tracer particles suspended

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

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

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

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

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

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

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

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

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

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

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

116 The mean-square displacement of single, bound proteoglycans

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

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

119 Mean-square displacements of localized internal motions

120 Finally, we develop a method based on mean-square-displacement of single particle trajectories

121 lls: the anomalous non-linear scaling of the mean-squared displacement of a 150-nm-diameter particle

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

123 s' net incomes as random walks, we study the mean-squared displacement of net income and related quan

124 The mean-squared displacement of the resulting trajectories

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

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

127 regardless of Gaussianity, to retrieve their mean-squared displacement over several orders of magnitu

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

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

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

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

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

133 ns in the cell membrane mostly relies on the mean-squared displacement plots, much information is los

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

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

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

137 The image-mean square displacement technique applies the calculati

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

139 ovements from this experiment showed greater mean squared displacement than predicted by both a simpl

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

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

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

143 At a gross level, this is characterized by mean-squared displacements that deviate from the standar

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

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

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

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

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

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

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

151 l described by a power-law dependence of the mean-square displacement with observation time.