ライフサイエンスコーパス: exponent

1 RNA raised to the power of an 'amplification exponent'.

2 engths, but each type has a distinct scaling exponent.

3 ximate entropy, fractal dimension, and Hurst exponent.

4 ates a negative value in the LLK scaling-law exponent.

5 Golden Mean [Formula: see text] as dynamical exponent.

6 ly 2 regardless of the underlying population exponent.

7 tic process, including its anomalous scaling exponent.

8 e systems with a spatially varying anomalous exponent.

9 ases proportional to population raised to an exponent.

10 1 + nu, respectively, where nu is the Flory exponent.

11 are characterized by a continuously varying exponent.

12 ased more steeply, corresponding to a higher exponent.

13 the mRNA level and defines the amplification exponent.

14 s diffusion models with adjustable anomalous exponents.

15 sition and compatible values of the critical exponents.

16 be characterized by their power-law scaling exponents.

17 t support the hypothesis of fixed allometric exponents.

18 s, exact knowledge of the universal critical exponents.

19 observables, governed by universal critical exponents.

20 ethods, all results were normalized to Hurst exponents.

21 eaningful taxonomic heterogeneity in scaling exponents.

22 odel we manage to explain the novel critical exponents.

23 m critical point, and constrain the critical exponents.

24 can be classified according to few critical exponents.

25 is able to produce power laws with arbitrary exponents.

26 each characterized by its specific critical exponents.

27 lations, with only three independent scaling exponents.

28 ed by a surprisingly small power-law scaling exponent (0.22) between the radius-of-gyration and Q-len

29 ltiscale correlation of SERCA group (scaling exponent: 0.77 +/- 0.07), on the other hand, is weaker t

30 than that of the control Drosophila (scaling exponent: 0.85 +/- 0.03) (p = 0.016).

31 g-dominated and characterized by a power-law exponent 1/2.

32 smaller and follows a different sequence of exponents, 1 and (1/2).

33 spectrum of cosmic rays, with the universal exponent -2, which is independent of the multiplication

34 severe sensitivity to a stem cell expansion exponent (20% variation causing 2-fold turnover change)

35 t rate and wingbeat frequency (raised to the exponent 3.5) and estimated metabolic power and wingbeat

36 be recognized by a power-law dependence with exponent 3/2 of the shear modulus on stress, whereas the

37 ated metabolic power and wingbeat frequency (exponent 7) of migratory bar-headed geese.

38 Absorption Angstrom exponent (A(a)) (fitted between 300 and 600 nm wavelengt

39 on only the crown area-to-diameter allometry exponent: a well-conserved value across tropical forests

40 s is because the aerosol absorption Angstrom exponent (AAE) largely controls the color and larger par

41 t lambda = 550 nm and an absorption Angstrom exponent (AAE) of 1.03 +/- 0.09 (2sigma).

42 organic aerosol with an absorption Angstrom exponent (AAE) of 2.5-2.7 and estimated Brown Carbon con

43 at lambda = 550 nm with absorption Angstrom exponents (AAE) between 3.5 and 6.2.

44 The allometric exponent (AE) derived for the entire cohort (1.27) using

45 al depth, AOD), dominant size mode (Angstrom exponent, AE), and relative magnitude of radiation scatt

46 xample, the specific values of the dynamical exponent allow us to identify the relevant mesoscopic st

47 to claims that Levy flights with a critical exponent alpha = 1 are optimal for the search of sparse

48 face exhibit transient subdiffusion, with an exponent alpha approximately 0.5 for times of less than

49 - D)) is valid, however for 1.5 < D < 2, the exponent alpha is different and equal to 2(D - 1)/D.

50 ted in a decrease in the anomalous diffusion exponent alpha of the lipid.

51 function of the normal contact load with an exponent alpha within the whole range of fractal dimensi

52 of variation of PEF (CVpef) and the scaling exponent alpha, reflecting self-similarity of PEF, in re

53 detrended fluctuation analysis (DFA) scaling exponent alpha.

54 Kardar-Parisi-Zhang (KPZ) model with scaling exponents alpha = 0.71 +/- 0.12, beta = 0.36 +/- 0.03, a

55 The principal differences are the exponent (alpha) for the activity of available surface s

56 ched exponential modeling (ADCSE), anomalous exponent (alpha) obtained at stretched exponential DWI,

57 exponential and segmented scaling laws with exponents (alpha) typically between 0.85 (Horwitz) and 1

58 anisms are expected to yield the same growth exponent, alpha = 1/3, where domain radius grows as time

59 Detrended Fluctuation Analysis (DFA) scaling exponent, alpha.

60 The behavioral exponents also were correlated with neuronal scaling law

61 scaling theory (MST) posits that the scaling exponents among plant height H, diameter D, and biomass

62 aw behavior for the rates with the power law exponent, an effective state space dimensionality, being

63 ive diagnosed from health, by characteristic exponent analysis of pulse signals accessed from volunte

64 Specifically, the values of the mean MSD exponent and effective diffusion coefficients can be tra

65 a discrepancy between the observed power-law exponent and that predicted from the noise parameters.

66 ous measures of complexity, through Lyapunov exponents and entropy.

67 However, the relationships between scaling exponents and normalization constants remain unclear.

68 Our statistical approach allows mean scaling exponents and taxonomic heterogeneity in scaling to be a

69 ion d + zLambda(T), where z is the dynamical exponent, and temperature-depending parameter Lambda(T)

70 lley transitions, effective mass, scattering exponent, and the Fermi energy may deteriorate or amelio

71 endence of diffusion coefficients, anomalous exponents, and the effective viscosity experienced by bi

72 lay a scale-free power-law distribution with exponent approximately 2.

73 concentration in a power law manner with an exponent approximately 2/3.

74 We tested whether allometric scaling exponents are generally constant across plant sizes as p

75 ngth [Formula: see text] Mean-field critical exponents are predicted, since the upper critical dimens

76 The fitted scaling exponents are typically less than 1, implying that the v

77 regimes with at least nine positive Lyapunov exponents are used here.

78 This suggests that low Raman exponents arise from the unique spin-phonon coupling of

79 ymptotes to zero with no need to fit unknown exponents as previously proposed in critical power law b

80 eriodic avalanche bursts and higher critical exponents as the strain rate is decreased.

81 of the critical point and universal critical exponents, as well as the ground state fidelity.

82 Variability in scaling exponents at both order and species levels was comparabl

83 piecewise power-law functions with different exponents at different ranges of k.

84 Thus, the sample exponent b approximately 2 may indeed be a statistical a

85 Is the widely reported sample exponent b approximately 2 the result of ecological proc

86 of measurements is distributed in space, the exponent b of this power law is conjectured to reflect a

87 Greater synchrony typically decreases the exponent b of TL.

88 t a broad range of values for the population exponent b pertaining to the mean and variance of popula

89 The sample exponent b(jk) depends predictably on the number of samp

90 -dependent and (2) at a community level, the exponents b and d of the relationships N ~ M (b) and N ~

91 Sample exponents b measured empirically via the scaling of samp

92 ralized TL in terms of sample and population exponents b(jk) for the scaling of the kth vs. the jth c

93 i's fractal dimension, and generalized Hurst exponent based estimates were most successful by all cri

94 and city population with average allometric exponent beta = 1.46 across all cities in the US.

95 where Tc is the critical temperature and the exponent beta was close to (1/4), as predicted for a tri

96 ed ferromagnetic region yields 3D Heisenberg exponents beta = 0.3460 +/- 0.040, gamma = 1.344 +/- 0.0

97 apparent elastic modulus, Ea, and power-law exponent, beta.

98 d city population, with allometric power-law exponents, beta = 0.84 +/- 0.02 and 0.87 +/- 0.01, for a

99 s 301.51 +/- 0.1 K, and that of the critical exponent, betac = 0.391 +/- 0.02.

100 f a difference in the values of the critical exponents between the bond and site percolation models i

101 s, and leaf mass) the empirically calculated exponents broadly overlapped among species from diverse

102 the refractive indices can vary the Angstrom exponent by up to 0.1 across the range 310 to 550 nm.

103 rom 20 human subjects, we calculated scaling exponents by four methods-two derived from local propert

104 However, differences among scaling exponents calculated at node- and whole-tree levels chal

105 When approaching a detection limit, the exponents change and approach an apparently Gaussian (al

106 he Cu spins out of the plane with a critical exponent characteristic of 3D transitions.

107 es a connection between the Herschel-Bulkley exponent characterizing the singularity of the flow curv

108 This softening affects the exponents characterizing elasticity at high pressure, le

109 flux distribution, which links the critical exponents characterizing the spatial dependencies in hum

110 The slope of this decay, the noise exponent (chi), is often <-1 for electrophysiological da

111 e anisotropy exponent zeta and the roughness exponents chix,y that characterize these correlations.

112 rameter oscillating around unity, a critical exponent close to -3/2 and a long tail distribution of a

113 reptiles and plants, the relationship has an exponent close to a half.

114 at percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-po

115 lator-metal transition and calculate scaling exponents corresponding to the transition.

116 found that on populated islands size spectra exponents decreased (analogous to size spectra steepenin

117 bined, leaf vs stem and leaf vs root scaling exponents decreased from c. 1.00 for small plants to c.

118 ut that simply inserting asymptotic critical exponents deduced from the immediate vicinity of the cri

119 iently anomalous diffusion and the anomalous exponent depend on the size of model glomeruli and the d

120 f(beta), where beta is the power-law scaling exponent describing the decay in temporal correlations.

121 follows a power law time dependence, with an exponent determined by the 1/f-type resonator frequency

122 However, the scaling exponents differed from those predicted by recent simula

123 act power laws, p(x) ~ x(-lambda), where the exponent directly corresponds to the mixing ratio of the

124 ithout spatial correlations but with scaling exponents distinct from those of original data.

125 adapted to quantify the anomalous diffusion exponent dw from the IOI records.

126 ics near the transition and obtain universal exponents establishing connection between thermal soften

127 Furthermore, scaling exponents estimated for branch length change across bran

128 theories predict that combinations of these exponents explain how metabolic, growth, and other biolo

129 any known relationships between the critical exponents explored by them, despite the fact that they o

130 l gamma = (d + z - 2)/z, where the dynamical exponent for a ferroelectric z = 1 and the dimension is

131 ly lower offset and a possible change in the exponent for Alzheimer's disease subjects compared with

132 The 0.22 value of the scaling exponent for short DNA segments is consistent with theor

133 The exponent for this Cu was close to 0.5, indicating low-di

134 the expectation that the dynamical critical exponent for this universality class is z = 3/2.

135 tinct from the larger and more regular Raman exponents for 2-Dy, 2-Er, and 2-Yb.

136 ely correlated with their associated scaling exponents for D vs. V and H vs. V, whereas normalization

137 diverse environments, except for the scaling exponents for length, which increased with tree cover an

138 We calculated the growth exponents for nucleation and spinodal decomposition usin

139 h length change across branching orders, and exponents for scaling metabolic rate with plant size (or

140 c, and 'global' (i.e. interspecific) scaling exponents for several allometric relationships using tre

141 Critical exponents for the basin width, the weak force distributi

142 The critical exponents for the perforated membrane are compatible wit

143 near features (approximate entropy and Hurst exponent) for the first time to explore post-concussive

144 particular, more ballistic Levy flights with exponent [Formula: see text] are generally believed to o

145 , whose density is described by a nontrivial exponent [Formula: see text] We build a microscopic theo

146 diffusive universality class with dynamical exponent [Formula: see text], another prominent example

147 Remarkably, their dynamical exponents [Formula: see text] are given by ratios of nei

148 comitant increase in the absorption Angstrom exponent from 1.2 +/- 0.4 (5% RH) to 1.6 +/- 0.3 (70% RH

149 ntly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within

150 We extract the values of these exponents from already known numerical or theoretical re

151 traits (radii/lengths) and calculate scaling exponents from five functionally divergent species.

152 The measured critical exponents from M. xanthus are consistent with mean field

153 e is needed in interpreting lag-time scaling exponents from protein assembly data.

154 ecreasing average droplet size and was of an exponent function of size, indicating that the influence

155 ional, variant T(-) (gamma) , with the power exponent gamma = 1.4 +/- 0.1 in the cubic phase, indicat

156 lity varying as 1/T(3), i.e. with a critical exponent gamma = 3.

157 n of the parameter space given by the degree exponent gamma and average degree <k>.

158 ial (TIP4P)]; however, the value of the mass exponent gamma is the same.

159 an interactions with population size with an exponent gamma ranging between 1.11 and 1.21, as observe

160 a near-random power law distribution (degree exponent gamma>/=2.7).

161 also fitted a power law distribution (degree exponent gamma=2.3), which suggested that progestin and

162 s a crucial role in determining the critical exponents governing universal nonequilibrium dynamics in

163 s respond exponentially to temperature (with exponents >1).

164 and extruded flours exhibited higher fractal exponent h in agreement with the extended crystalline st

165 s of the boundary, as measured by its Holder exponent H.

166 Decreases in the Hurst exponent (H), which quantifies scale-free signal, was re

167 The scaling exponent has a drastic effect on the optimal design of s

168 protein concentration as a power law, whose exponent has been used to infer the presence or absence

169 me-averaged optical coefficients, scattering exponent, hemoglobin concentration, oxygen saturation, a

170 on (EC) mass fraction, mass-mobility scaling exponent, hygroscopicity, and light absorption and scatt

171 erstood, with a known anomalous subdiffusion exponent, ideally readily tunable.

172 us to give a precise meaning to the scaling exponent in terms of the degree to which a given process

173 ss implications of the changes in offset and exponent in the data and relate it to existing literatur

174 We suggest that calibration of the repulsive exponent in the LJ potential widens the range of applica

175 Here we show that the dynamical exponent in the time dependence of the diffusion coeffic

176 roughout the neocortex with distinct scaling exponents in different functional brain systems and freq

177 allow us to explain a wide range of scaling exponents in frequency distributions ranging from alpha

178 power law and analyse supercritical scaling exponents in the system above the Frenkel line.

179 how signs of kinks: clear changes in scaling exponent, indicating changes in the dominant molecular m

180 e observed variability of ecological scaling exponents into a coherent statistical framework where pa

181 in a broad class of growth models the sample exponent is b approximately 2 regardless of the underlyi

182 This exponent is different from [Formula: see text] of dilute

183 a tangent bifurcation for which the Lyapunov exponent is negligible or vanishes.

184 Thus, the absorption angstrom exponent is not representative of the fuel used and, the

185 a Levy walk whose characteristic (power-law) exponent is tuned to nearly minimize the time required t

186 and temporal domains with the same algebraic exponent, is reproduced with numerical solutions of stoc

187 f particles follows a power law in time with exponent less than unity.

188 d, and the experimentally reported power law exponent m ranges from approximately 0.2 to 0.5.

189 agonists (E(0)) and the affinity-correlation exponent (M)--allows an entire CRC to be calculated from

190 Angstrom exponent measurements of equivalent black carbon (BCeq)

191 that can be quantitatively evaluated by the exponent n (ca. 3) of the temperature dependence of the

192 The exponent N of the current-voltage characteristics (inver

193 r rates (>500 s(-1)), at which the power law exponent (n) of zebrafish blood was nearly 1 behaving as

194 The diffusional exponent (n) values of Peppas equation explains a non Fi

195 chanism, with changes observed in the Avrami exponent (n).

196 Also, the MC estimate of the critical exponent nu in the NMF region is about twice as large as

197 ions and allowed the estimation of the Flory exponent (nu) of the thermally unfolded polypeptide chai

198 illar size with an inverse power-law scaling exponent of -0.63 independent of orientation.

199 ometer length scales, with the strengthening exponent of -0.68 at room temperature and of -1.00 at 90

200 ze distribution of activity cascades with an exponent of -3/2 and (2) a branching parameter of the cr

201 in translation and directs an amplification exponent of 1.20 with a 95% confidence interval [1.14, 1

202 ted population distribution with a universal exponent of 1.7.

203 density to ionic strength ratio with scaling exponent of 1/3.

204 The inverse power law exponent of 1/f-type noise is shown to decrease from 3.0

205 Our results reveal a power function with an exponent of 2.2 between the amplitude of uIPSCs and intr

206 tes were not spherical, with a mass-mobility exponent of 2.78, so additional SOA was required to fill

207 7), which tallies with a dipolar interaction exponent of 2/3 in EC materials and the well-proven frac

208 emory behavior characterized by a relaxation exponent of [Formula: see text].

209 sorting dynamics follow a power law with an exponent of approximately 0.5.

210 s scale sublinearly with consumer body mass (exponent of approximately 0.85) for 2D interactions, but

211 .85) for 2D interactions, but superlinearly (exponent of approximately 1.06) for 3D interactions.

212 further identify these cells as a functional exponent of ARC(AgRP) neuron-driven hunger.

213 ther observe an unprecedented sixfold-higher exponent of growth rate, faster onset, higher steady-sta

214 olve this problem by considering the scaling exponent of shell thickness as a morphological parameter

215 theory predicts an upper limit of 2 for the exponent of such power laws.

216 c modulus E and fluidity beta (the power-law exponent of the cell deformation in response to a step c

217 the decay in autocorrelation and the scaling exponent of the detrended fluctuation analysis from EEG

218 d nullity in terms of the energy dissipation exponent of the drainage networks.

219 haviour by correctly predicting the critical exponent of the dynamically generated length scale at th

220 leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to

221 As the exponent of the fractional derivative decreases, the wei

222 e aqueous diffusion coefficients, D, and the exponent of the inverse power-law relation between D and

223 al expression for the instantaneous collapse exponent of the macroscopic concentration profiles.

224 anding the sorting dynamics and explains the exponent of the power law behavior.

225 ffusion coefficient and subdiffusive scaling exponent of the stochastic motion.

226 t seems likely that synchrony influences the exponent of TL widely in ecologically and economically i

227 istical power law behaviour, Zipf's law, the exponent of which can provide useful information on the

228 By contrast, scaling exponents of A-P and R-P relationships were altered by P

229 ly, the lower the individual subject scaling exponents of delta/theta oscillations, the greater the c

230 Frequency scaling exponents of finger tapping and amplitude modulation of

231 s are negatively correlated with the scaling exponents of H vs. D.

232 The mean power-law scaling exponents of metabolic rate vs. body mass relationships

233 e the difference in time scales, the scaling exponents of neuronal LRTCs and avalanches were strongly

234 ey fail to predict the correct values of the exponents of power-law degree distributions observed in

235 The exponents of power-law regimen neuronal avalanches and L

236 precentral sites strongly predicted scaling exponents of tapping behavior.

237 The LRTC scaling exponents of the behavioral performance fluctuations wer

238 The scaling exponents of the relationships describing root nutrients

239 dent process, in the sense that the critical exponents of the transition are determined by the geomet

240 We argue that the critical exponents of the yielding transition may be expressed in

241 We demonstrate that the stationary critical exponents of this transition to meso-scale turbulence in

242 By varying only the fractional exponent, our model can reproduce upward and downward sp

243 We find that the repulsion exponent p approximately 6.5 provides an excellent fit f

244 g the resting state indexed by the Power Law Exponent (PLE) in PostCG and AI.

245 ted with a higher short-term fractal scaling exponent (Ptrend=0.003) and lower Poincare ratio (Ptrend

246 also predicted a spectrum of power laws with exponents ranging between 0 and -2/3 for simple movement

247 d V(T) with a set of 30 basis functions with exponents ranging from 0.0175 to 1.9 (R(2), 0.79; ICC, 0

248 zed by quasi-power-law release profiles with exponents ranging from 0.5 to 1, respectively.

249 ifferentiation operation on their input with exponents ranging from zero (no differentiation) to 0.4

250 tic attractor, along with a maximal Lyapunov exponent rate of about 2.94 times the fundamental optome

251 a fat-tailed distribution, with a universal exponent related to the recently observed universal [For

252 In addition, mass-mobility exponents (relates mass and mobility size) were determin

253 m the naive prediction based on the critical exponents relevant for asymptotically long quench times.

254 decreases, whereas the subdiffusive scaling exponent remains constant.

255 These exponents rule an universal scaling behaviour that witne

256 n intensity is described by a power law with exponents sequentially taking values 1, 1/3 and (1/4).

257 scillations as a function of the correlation exponent shows a maximum, therefore indicating the exist

258 1-Ho also exhibits an anomalously low Raman exponent similar to 1-Dy, both being distinct from the l

259 Low P supply increased scaling exponents (slopes) of area-based log-log A-N or R-N rela

260 periodicity of about 2 y, a global Lyapunov exponent statistically indistinguishable from zero, and

261 d 200 degrees C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is cha

262 ing noise systems, and the measured Lyapunov exponent suggests the existence of highly branched EPS.

263 ficiencies of 2-D Levy walks with a range of exponents, target resource distributions and several com

264 km(2) are power-law distributed with a tail exponent (tau = 1.97) and fractal dimension (d = 1.38),

265 exhibit higher intercepts with lower scaling exponents than hind limb parameters.

266 ze savanna trees have greater length-scaling exponents than predicted by MST due to an evolutionary t

267 higher subdiffusive mean square displacement exponents than previously reported, which has implicatio

268 -law distribution for the cell size, with an exponent that depends inversely on the noise in the time

269 ive bodies exhibits a power-law tail with an exponent that depends on the system condition.

270 The JMAK model hinges on an exponent that expresses the growth mechanism of a materi

271 ally ordered phase) is marked by a universal exponent that governs the scaling of the critical temper

272 istinguishable from zero, and local Lyapunov exponents that alternated systematically between negativ

273 tion rates, our analysis yields species-area exponents that are in close agreement with previously ob

274 However, we find nonuniversal exponents that cannot be captured by this mechanism or a

275 distributions of states are power laws with exponents that coincide with the multiplication paramete

276 ied electric current and determined critical exponents that coincided with those for thermodynamic li

277 well approximated by the power law, but with exponents that depend on that rate, and that are quite d

278 dex alpha fixes the distribution's power-law exponent, that for the dual index 2 - alpha ensures the

279 The critical exponents, the symmetry of the order parameter, the role

280 y be expressed in terms of three independent exponents, theta, df, and z, characterizing, respectivel

281 We propose the inference of the repulsion exponent through Hierarchical Bayesian uncertainty quant

282 pectral shape causes the absorption Angstrom exponent to decrease by 0.18 per unit increase in pH.

283 We use these exponents to provide a rigorous test of three plant scal

284 om the aorta to capillaries and uses scaling exponents to quantify these changes.

285 When we compare empirical scaling exponents to the theoretical predictions from the three

286 e found a large variability of the anomalous exponent, used to interpret live cell imaging trajectori

287 equency; varphi = scaling factor; and k = an exponent valued between 0 and 1.

288 The value of the exponent varies by region from 0.36 for India to 0.66 fo

289 SDR exponents vary from 0.06 to 0.45 between regions, underl

290 appears to be ubiquitous, empirical scaling exponents vary with ecosystem type and resource supply r

291 teps drawn from a Levy distribution with the exponent varying from [Formula: see text] to [Formula: s

292 hing parameter was close to 1, the power law exponent was -3/2.

293 The average absorption Angstrom exponent was 1.2 +/- 0.8, suggesting that most of the li

294 bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input feature

295 ricritical scaling characterized by a set of exponents which is independent on the protection strateg

296 Rather, continuous shifts in allometric exponents with plant size during ontogeny and evolution

297 to be a power law function of P with scaling exponent X [demographic conflict investment (DCI)].

298 to be a power law function of W with scaling exponent Y [conflict lethality (CL)].

299 to be a power law function of P with scaling exponent Z [group conflict mortality (GCM)].

300 determine the exact values of the anisotropy exponent zeta and the roughness exponents chix,y that ch