ライフサイエンスコーパス: approximation

1 m a 2D array of 2048 elements and a paraxial approximation.

2 ncorporating interactions via a Hartree-Fock approximation.

3 o is a JCM without needing the rotating-wave approximation.

4 olecular interpenetration in the hard-sphere approximation.

5 es due to a failure of the local equilibrium approximation.

6 imal goals can be achieved through heuristic approximation.

7 m-mechanically derived atomic-level pressure approximation.

8 ractions and the quasi-particle random-phase approximation.

9 solving the process in a pseudo-first order approximation.

10 s using an analytically solvable, well-mixed approximation.

11 the test statistic by using the saddlepoint approximation.

12 te that for FN networks this is a reasonable approximation.

13 velopment of the Gross-Pitaevskii mean-field approximation.

14 alescent time below that given by the simple approximation.

15 e red-detuned regime under the rotating wave approximation.

16 in polynomial time and guarantees an O(ln n) approximation.

17 ses are typically not conducted or are crude approximations.

18 se, simulations use small-strain and jointed approximations.

19 all) than correlations with all 7 binocular approximations.

20 lk-based models and probabilistic analytical approximations.

21 and has been the subject of many subsequent approximations.

22 ely with reported functioning than binocular approximations.

23 inner potential by simple algorithms without approximations.

24 nal with respect to parameters of the chosen approximations.

25 omputations, without the need for asymptotic approximations.

26 that cannot be explained by effective medium approximations.

27 ebrovascular risk (root mean square error of approximation = 0.02).

28 in all countries (root mean square error of approximation = 0.02-0.05; comparative fit index/Tucker-

29 wis Index = 0.951, Root Mean Square Error of Approximation = 0.030, Standardized Root Mean Square Res

30 950; CFI = 0.950; root means square error of approximation = 0.055 (90% confidence interval [0.052 -

31 fit with the data (root mean square error of approximation = 0.06; comparative fit index = 0.95; Tuck

32 i-square p-value of 0.74, root mean error of approximation: 0.001 [95% CI: 0.001-0.083], comparative

33 s: chi(2)=370.233, root mean square error of approximation=0.075, and comparative-fit index=0.901.

34 electrodynamics typically invoke the dipole approximation(1,2), in which atoms are treated as point-

35 d using a unified and accurate local-density approximation-1/2 approach under the density-functional

36 ial-time exact algorithm and the linear-time approximation algorithms are implemented as PedKin in C+

37 trization procedure and the black box use of approximation algorithms for symmetric graphs.

38 able performance guarantees, better known as approximation algorithms.

39 The model, built on several assumptions and approximations, allows us to formalize the phylogenetic

40 o an adverse environment, and develop a pair approximation analysis taking into account the two-node

41 computation: (a) (heterogeneous) mean field approximation and (b) belief propagation.

42 function of the islet as a unit is the close approximation and communication among heterogeneous cell

43 t potential approximation in the single site approximation and is exact when the number of sites in t

44 ny theoretical studies use an inviscid fluid approximation and lump the viscous effect to viscous dam

45 a single 24HDR: values near 1 indicate close approximation and near 0 indicate bias toward null.

46 y reduction methods such as Uniform Manifold Approximation and Projection (UMAP) can be very valuable

47 In this work, uniform manifold approximation and projection (UMAP) is applied for nonli

48 Here, we use the Uniform Manifold Approximation and Projection (UMAP) method on published

49 ected onto a 2D space using Uniform Manifold Approximation and Projection (UMAP), a novel non-linear

50 rhood embedding (t-SNE) and uniform manifold approximation and projection (UMAP).

51 Like LargeVis and Uniform Manifold Approximation and Projection, the model produces embeddi

52 tic neighbor embedding, and uniform manifold approximation and projection.

53 onitoring demonstrates that diaphragmatic re-approximation and sub-diaphragmatic relocation has a gre

54 set of equations derived from the small-load approximation and the acoustic multilayer formalism (som

55 ilar to that of the well-known excess buffer approximation and the linear approximation but with para

56 Using analytic approximations and Monte-Carlo simulations, we demonstra

57 These rules are based on approximations and symmetries which may break down when

58 Using some approximations and taking into account emerging applicat

59 with the Zhang formula and parabolic barrier approximation) and spin-dependent drift-diffusion model.

60 tegy likely works by limiting APP and BACE-1 approximation, and we also delineate mechanistic events

61 g constants calculated using DFT/B3LYP/pcJ-1 approximation applied to conformations optimized at DFT/

62 istribution Decomposition (DDD), an operator approximation approach to infer a continuous distributio

63 Using suitable physical approximations, approximate analytical solution of equat

64 ccess primary human brain tissue; therefore, approximations are made using alternative sources such a

65 s to Rayleigh-Sommerfeld diffraction and its approximations are readily available, benefiting our met

66 y and pairwise formulation, and random phase approximation-based approaches.

67 erative mode line shifts of the point dipole approximation begin to rapidly diverge at small separati

68 elated technical noise has an accurate gamma approximation, both population and cell-level inference

69 In particular, the Gaussian approximation breaks down whenever a qubit is strongly c

70 that emerge in parameter regimes where this approximation breaks down.

71 n excess buffer approximation and the linear approximation but with parameters estimated using two no

72 transition is not captured using mean-field approximations but instead arises due to composition flu

73 tive method for LSA statistical significance approximation by computing the local similarity score of

74 at emotions may implement such metareasoning approximations by restricting the range of behaviors and

75 the integral over time was represented by an approximation calculated as the product of the time tl o

76 oximation (PSA), the Ion Mobility Projection Approximation Calculation Tool (IMPACT), and Collidoscop

77 Additionally, simulation in ESTIpop via approximation can be performed many times faster than ex

78 ate to the selection coefficient, the simple approximation can be substantially inaccurate.

79 a a nonlinear logistic growth model, and our approximations capture the effects of intrinsic noise on

80 ly constructing low-rank drug-disease matrix approximations consistent with known associations can be

81 er and more spectrally wide, the widely used approximation consisting of writing the optical waveform

82 te approximations such as coherent potential approximation (CPA) and dynamical mean field theory (DMF

83 ther with a hierarchy of increasingly severe approximations culminating in a generalized version of t

84 ite approximations such as dynamical cluster approximation (DCA).

85 Even for simple models, the analytical approximations derived demonstrate a surprising richness

86 elf-interaction errors in density functional approximations (DFAs) for the case of water clusters.

87 After diaphragmatic re-approximation, DI decreased by a median 0.77 mm2/mm Hg [

88 e processes that guide the deployment of the approximations, discerning between innate, model-free, h

89 e show that, contrary to crystals, the Debye approximation does not hold.

90 n of the olfactory periphery to a very close approximation during lesion-induced regeneration begs th

91 Under virtual crystal approximation, electron effective masses of h- and c-pha

92 orating a regularization term to balance the approximation error and the rank properties.

93 tive populations is negligible compared with approximation errors of the HR hybrid method itself, and

94 esent a systematic pipeline to produce first-approximation estimates for most of the missing informat

95 changes (band shifts, deviation from linear approximation, etc.) for common sample parameters in the

96 w that the strict adiabatic Born-Oppenheimer approximation fails badly.

97 ends are mostly captured by the RPA, but the approximation fails catastrophically at low concentratio

98 However, these model-free approximations fall short of comprehensively capturing l

99 ncentration still adheres to the first order approximation (FOA3), and this agreement is maintained o

100 Often, reaching an epsilon-approximation for a particular set of partition function

101 Our method produces a better approximation for ACS(k) and is applicable for the align

102 re program, hFRET, that uses the variational approximation for Bayesian inference to estimate the par

103 reaction yield at an early time point as an approximation for catalytic activity/efficiency and chel

104 In contrast, an approximation for delay representations result from esti

105 ice by employing one calibration curve as an approximation for different regions across the hemispher

106 polyurethane mattresses, and provides first approximation for inhalation exposure during sleep, base

107 centrosymmetric meta-atom designs where the approximation for meta-atoms breaks down.

108 ce wavelength, thus invalidating the dipolar approximation for meta-atoms.

109 tends to behave like the gradient expansion approximation for small reduced gradients.

110 o-cell embryo and thus represent an in vitro approximation for studying ZGA transcription regulation.

111 res arising from the breakdown of the dipole approximation for the emission.

112 idely used Barabasi-Albert model can be poor approximations for dynamic networks.

113 ght be involved or does not provide accurate approximations for rare variant data.

114 The main theoretical and conceptual approximations for the simulation of oxygen K-edges are

115 rved at a tl of 96 h, with deviations of the approximation from the time integral of median +5% (rang

116 Tissue-specific deviations of the approximation from the time integral were calculated for

117 one (FBZ) is casual, in contrast to previous approximation fully crystal electron wave vector, q, dep

118 The 3D safety factor is obtained through the approximation function and the Mohr-Coulomb strength cri

119 ruct a reasonable normal stress distribution approximation function.

120 often used spherical, concentric core-shell approximation generally overestimates the absorption by

121 ispersion (HARD) experiments and a geometric approximation (geoHARD) has been shown to have several a

122 Diaphragmatic re-approximation had a higher percent contribution to diste

123 r mitral valve repair (TMVr) through leaflet approximation had reduced rates of HF hospitalization an

124 e and accurate method, SPACox (a saddlepoint approximation implementation based on the Cox PH regress

125 able and accurate method, SPAGE (SaddlePoint Approximation implementation of G x E analysis), that is

126 The correlation between time integral and approximation improved with increasing time tl Pearson r

127 It recovers coherent potential approximation in the single site approximation and is ex

128 n electrons and ions relies on the adiabatic approximation in which ions interact via forces derived

129 gn a greedy algorithm to obtain near-optimal approximations in a computationally efficiently manner.

130 We quantify error from two common approximations in EV emission analysis, ignoring hourly

131 ailed study for the validity of point dipole approximations in small systems of strongly coupled plas

132 view describes how to use quasi-steady state approximations in the right context, to prevent drawing

133 nfirm that thermal conductance is to a first approximation independent of molecular length, consisten

134 At low resolution, these approximations inflate bending resistance and delay buck

135 Integrated Nested Laplace Approximation (INLA) was used to determine the most impo

136 ded examples using integrated nested Laplace approximations (INLA) and Template Model Builder (TMB) f

137 mental insights, beyond the Born-Oppenheimer approximation, into the light-induced spin-state trappin

138 ly calculate it, ensuring that the necessary approximations involved yield a correct result.

139 p-orbital tight-binding basis, although our approximation is "atomically adiabatic": the basis p-orb

140 A Galerkin approximation is applied to discretize the nonlinear equ

141 A novel EV emission approximation is introduced, validated (<1% error), and

142 Gaussian sub-domains to the extent that this approximation is permissible.

143 e overbinding of the water clusters in these approximations is not a density-driven error.

144 ty functionals, from the basic local density approximation (LDA) to our most advanced general purpose

145 lized gradient families [i.e., local density approximation (LDA), Perdew-Burke-Ernzerhof (PBE), and s

146 The simplest approximation leads to a short solvent (SS) model, with

147 mooth cylindrical pores using the centerline approximation leads to an optimum pore radius of about 8

148 or measurements after 24, 48, and 144 h, the approximation led to large deviations for some of the pa

149 The linear noise approximation (LNA) has recently been proposed to addres

150 energy functional that relies upon different approximations (mean-field and Bethe respectively).

151 We have developed an approximation method that calculates TFEs of TM residues

152 he size of the patterned holes by using a dc approximation method.

153 Although many approximation methods have been introduced, the complexi

154 the mode wavelength is increased, the dipole approximation no longer holds and the atom is referred t

155 ror using constrained optimization by linear approximation, non-linear optimization solver.

156 differs in that we do not make the diffusion approximation, nor do we reduce the state space to a sin

157 pped around an ellipsoidal three-dimensional approximation of an embryo.

158 enhanced sampling of molecular dynamics with approximation of continuum solvent), to investigate the

159 Overall, our approach enables robust approximation of metabolic and functional states in indi

160 SUV4.0 gave a good approximation of MTV in 105 (76%) scans, with simple edi

161 We have developed miniMDS, an approximation of multidimensional scaling (MDS) that par

162 Our analytical approximation of NTCP could help optimise radiotherapy p

163 fluid drag, diffusion) provide a sufficient approximation of overall particle behavior.

164 ization allowing for improved spatial-visual approximation of patient and image.

165 Doppler US has been proposed for noninvasive approximation of perfusion.

166 d path-integral ring-polymer methods for the approximation of quantum vibrational spectra and reactio

167 ly to heuristic methods based on the drastic approximation of relying on the geometry of the network

168 nt state-of-the-art: t-SNE or the Barnes-Hut approximation of t-SNE.

169 r embedding (t-SNE), and the Barnes-Hut (BH) approximation of t-SNE.

170 struction is a technique that finds the best approximation of the acoustic stimulus from the populati

171 While faecal metagenomics provided a good approximation of the average gut mucosal microbiome comp

172 n this study, we challenge the commonly used approximation of the circular cross-section of the aorta

173 to the sequential Markov coalescent (SMC)-an approximation of the coalescent with crossover recombina

174 The mean-field approximation of the discrete process gives rise to 22 d

175 for this reaction in water (as a first-order approximation of the enzymatic reaction) are evaluated b

176 ed nucleic acids is used to generate a first approximation of the extensive interaction of nucleic ac

177 e, taum, was calculated from a 3-exponential approximation of the FAF decays.

178 tine use, DSM-IV nicotine dependence, and an approximation of the Fagerstrom Test for Nicotine Depend

179 Hopper realizes the optimal polynomial-time approximation of the Hausdorff distance between the full

180 rrangements of this sort provide only a poor approximation of the imaging environment in real patient

181 uperparamagnetic bead based on the Karlqvist approximation of the magnetic field created by a tape he

182 niche models can provide a reasonable first approximation of the magnitude of species' potential ran

183 Lastly, we present a mean field approximation of the newly introduced models.

184 based on the "genetic circuit" metaphor, an approximation of the operation of silicon-based computer

185 ain regions suggests these models are a good approximation of the perceptual representation generated

186 orithm to determine the optimal second-order approximation of the population-based haplotype likeliho

187 ferential centrifugation alone gives a first approximation of the stress granule transcriptome, this

188 he human brain and investigated the topology approximation of the VMI network to the Allen Human Brai

189 In addition to predicting forward approximation of transmission response for any given top

190 The binocular approximations of binocular visual function were better

191 of each atom in a protein based on classical approximations of interatomic forces, giving researchers

192 All such methods are limited to coarse approximations of only a few cell subpopulations, howeve

193 except for numerical simulations, adiabatic approximations of promoter kinetics are not appropriate.

194 of a soil property can be used for a priori approximations of the effective scale space for contextu

195 nals producing better energies become better approximations of the exact functional.

196 rom statistical physics based on random walk approximations of the excitation in the antenna.

197 nd auditory nerve to simple spectrogram-like approximations of the information processing in these st

198 HDMR) to build interpretable low dimensional approximations of the log-likelihood ratio accounting fo

199 Furthermore, we demonstrated that including approximations of the three categories of auditory nerve

200 Results showed that the most common clinical approximations of the vascular cross-section can be a so

201 ctual counts are not available, high quality approximations of their cell proportions using indirect

202 correlated significantly with all binocular approximations of VF, with r values ranging from 0.31 (w

203 These approximations open the door to the development of modif

204 elf-similar solutions of the local induction approximation or Biot-Savart equations.

205 al relative to predictions from the harmonic approximation or vibrational second-order perturbation t

206 Within (semi-)local density functional approximations or Hartree-Fock theory such interactions

207 ction methods, such as through an analytical approximation, or ranking by copy number and/or KD value

208 ixed time for all patients; a sampling-based approximation; or a validated electronic count.

209 Within local-density-approximation plus dynamical mean-field theory (LDA+DMFT

210 asis signals, and motivated by the universal approximation power of deep learning, we propose a neura

211 learning should answer questions about their approximation power, the dynamics of optimization, and g

212 ating projected gradient method to solve the approximation problem.

213 The method is articulated in various approximation protocols which allow to achieve increasin

214 calculated CCS using projected superposition approximation (PSA), the Ion Mobility Projection Approxi

215 mposition and deviations from the core-shell approximation-reconciles absorption enhancement predicti

216 We compare experimental (and random phase approximation) reference values to those of a family of

217 tes good fit) and root-mean-squared error of approximation (RMSEA; <0.06 indicates good fit), and est

218 analytical predictions from the random phase approximation (RPA) and postulated scaling relationships

219 many-body dispersion (MBD), and random-phase approximation (RPA) approaches).

220 vious studies are based on the rotating-wave approximation (RWA) by neglecting the counter-rotating t

221 method is based on the symbolic aggregation approximation (SAX) algorithm that was developed for the

222 sis to construct a satellite-based column BC approximation (sBC*) over remote oceans.

223 Recently, a saddle point approximation (SPA) based single-variant test has been d

224 mputation cost, and SPAGE uses a saddlepoint approximation (SPA) to calibrate the test statistics for

225 me-wide analysis and then uses a saddlepoint approximation (SPA) to calibrate the test statistics.

226 ed general purpose meta-generalized gradient approximation, strongly constrained and appropriately no

227 alization which can't be seen by single site approximations such as coherent potential approximation

228 which isn't observed by previous multi site approximations such as dynamical cluster approximation (

229 IKV dynamics and the complex-step derivative approximation technique to identify parameters that can

230 ncreases with trophic level, exploiting pair-approximation techniques to describe the effect of habit

231 We show that the popular Gaussian approximation tends to perform poorly under extreme dive

232 Perdew-Burke-Ernzerhof generalized gradient approximation tends to underestimate both surface energi

233 Berry formulation is only a phenomenological approximation that captures the emergent character of st

234 large MRI databases, we adapt an interaction approximation that considers the relative orientation of

235 We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into

236 ition allows us to devise a fast Monte Carlo approximation that rapidly converges.

237 impact model outcomes, as compared to static approximations that average contact rates over longer ti

238 ts follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite

239 Using steady-state approximations, the dissociation rate of PS in cavitatin

240 In approximation theory both shallow and deep networks are

241 A surrogate model is an approximation to a costly black-box function that can be

242 ulations must go beyond the Born-Oppenheimer approximation to account for non-adiabatic coupling betw

243 We use this approximation to define a simplified metric (EMOD1) that

244 hastic systems (MSS), applies a linear noise approximation to describe the size of the fluctuations,

245 tem has been studied using the Gaussian beam approximation to design the incident beam such that the

246 e generative model to enable a more faithful approximation to exact inference.

247 ed and in some cases is known to be a better approximation to geodesics than the shortest path.

248 We derive an approximation to gradient-based learning that comports w

249 rgied Sequences, and EWAK*, an Energy Window Approximation to K*.

250 We also consider an approximation to our dynamic network model in terms of a

251 combined with CASSCF could be a useful first approximation to predict and investigate the structure a

252 onstruct network ensembles which give a good approximation to the degree-degree correlations, and hen

253 e is the permutation test, a widely accepted approximation to the exact finite sample conditional inf

254 We develop an approximation to the first and second moments of a gener

255 Using the Fresnel approximation to the free-space Green's function, we the

256 An approximation to the latter term for the top one metre o

257 aorta and identify the implications of this approximation to the mechanical assessment of stent graf

258 d O(n) space, while producing a high-quality approximation to the optimal solution.

259 hat the in vitro protocol constitutes a good approximation to the physiological gastrointestinal dige

260 tically consistent and qualitatively correct approximation to the S(1) wavefunction can be achieved b

261 often facilitates distortion of rather than approximation to truth.

262 arious heuristics and can only provide rough approximations to alignment distances.

263 SummaryAUC provides accurate approximations to AUCs and their variances.

264 or efforts is the use of continuum mechanics approximations to evaluate this solid mechanics problem.

265 We assessed the ability of different RBF approximations to generate population data in women aged

266 cretization, a method for learning optimized approximations to PDEs based on actual solutions to the

267 e such systems have resulted in point-dipole approximations to resonators that are computationally ef

268 We also provide approximations to the distribution of test statistics wh

269 ulation of cells in order to develop several approximations to the normal tissue complication probabi

270 ensional data is handled using two different approximations to the pairwise couplings.

271 We compared the asymptotic power approximations to the power of analysis attained with Ha

272 Approximations to the true long-time dynamics can be com

273 inetic model (e.g., using the Bragg-Williams approximation) to describe the experimental data over a

274 wn samples at the nanoscale thanks, in first approximation, to the direct comparability of PTIR spect

275 e law, based on the total quasi-steady state approximation (tQSSA).

276 We illustrate that this approximation undertakes electrons localization for one

277 croscopic formalism with its linear response approximation version (PDLD/S-LRA) approaches.

278 simulations, suggesting that the asymptotic approximation was accurate for the null distribution of

279 Nevertheless, a less frequently used average approximation was shown to yield satisfactory results (5

280 Specifically, the equivalent path length approximation was used to rescale the homogeneous DPKs f

281 Derjaguin's approximation was utilized to translate force measuremen

282 Using a mean-field decoupling approximation, we analytically obtain the steady-state e

283 network of spiking neurons and a rate-model approximation, we demonstrate that SWRs emerge as a resu

284 Within a tight-binding approximation, we numerically determine the time evoluti

285 onse of surface plasmons in the random phase approximation, we show that the coherence length of the

286 f the traditionally used Rayleigh-Gans-Debye approximation, we use an exact extended Lorenz-Mie solut

287 Using diffusion approximations, we show that this non-neutrality is a re

288 Additional analytical approximations were developed that could be used to pred

289 variants of coalescent mergers, including an approximation where low probability spectrums are discar

290 he accuracy of a theoretically substantiated approximation, which allows the calculation of absorbed

291 tified by the breakdown of the rotating-wave approximation, which applied to the quantum Rabi model (

292 The common low-injection approximation, which considers that the local carrier de

293 iclassical approaches, based on the Gaussian approximation, which retain phase and width information

294 al calculation based on the first-order Born approximation with correct boundary conditions (CB1), in

295 Bayesian approach (Integrated Nested Laplace Approximation with Stochastic Partial Differential Equat

296 s acquired pre-repair, post-diaphragmatic re-approximation with sub-diaphragmatic EGJ relocation, and

297 showed stronger correlations with binocular approximations, with r values ranging from 0.65 (worse-e

298 There is no reliance on the Born-Oppenheimer approximation within the p-orbital tight-binding basis,

299 cribed using steady-state or pre-equilibrium approximations yielding rate laws similar in form to tho

300 To validate the zeroth order regular approximation (ZORA) method, the same CASSCF analysis us