ライフサイエンスコーパス: parametric

1 and SA can generate quantitatively accurate parametric (18)F-FLT VT images in NSCLC patients before

2 and SA can generate quantitatively accurate parametric (18)F-FLT VT images in NSCLC patients before

3 ed Ti:Sapphire spectrum, followed by optical parametric amplification (OPA) of the DFG pulse.

4 on a silicon chip enforced by phase-matched parametric amplification in four-wave mixing.

5 Parametric amplification is sensitive to the relative ph

6 experimentally demonstrate high-gain optical parametric amplification using USRN, which is compositio

7 Based on the principle of parametric amplification, the detector can harvest wirel

8 enerate modes, and demonstrate nonreciprocal parametric amplification.

9 and a broadband-pumped dual-chirped optical parametric amplifier (DC-OPA), respectively.

10 tum information tap by using a fiber optical parametric amplifier (FOPA) with correlated inputs, whos

11 synthesiser based on a mid-infrared optical parametric amplifier and its application to high-harmoni

12 zed microwave field generated by a Josephson parametric amplifier.

13 rce to this end which is based on an optical parametric amplifier.

14 ct of noise on accuracy and precision of the parametric analyses of dynamic (18)F-FLT PET/CT to asses

15 Parametric analyses of MBEA Pitch and Rhythm scores show

16 ion than previously thought, while our multi-parametric analysis defined common pathophysiological pa

17 Moreover, a parametric analysis is presented in order to fit the exp

18 Finally, the unique feature of multi-parametric analysis of analytes by lateral flow device h

19 Parametric analysis of DWI and DCE MR imaging was perfor

20 Parametric analysis of release characteristics of CRFs i

21 The Ki and k3 parametric analysis provided information on tumor hypoxi

22 plots and multivariable analyses by Flexible Parametric and Cox regression models.

23 Both parametric and distribution-free measures of central ten

24 For regional correlation of parametric and functional measures, the left ventricle w

25 RP1 and P-gp expression in the lung by using parametric and nonparametric tests.

26 In NSCLC primary tumors, parametric and static baseline (18)F-FDG PET images prov

27 Parametric, non-parametric, and mixed effects logistic regression statis

28 oids and other natural products with the new parametric approach and demonstrate that the accuracy of

29 We use a non-parametric approach based on Gaussian Process regression

30 such coding sequences, suggesting that a non-parametric approach to modeling the recombination proces

31 ideas on a toy example, and the power of the parametric approach to TDA modeling in an analysis of co

32 Multi-delay multi-parametric ASL perfusion MRI overcomes the limitations o

33 We applied multi-delay multi-parametric ASL perfusion MRI to investigate the patterns

34 effects have been observed to violate these parametric assumptions for such coding sequences, sugges

35 en used when researchers are willing to make parametric assumptions.

36 are performances of conventional statistical parametric (based on Nakagami distribution) and entropy

37 lak analysis, the R(2) between NLR-based and parametric-based (Patlak) tumor Ki was 0.95 (slope, 0.71

38 A high R(2) and agreement between NLR- and parametric-based Ki values was found, showing that Ki im

39 : A high R(2) and agreement between NLR- and parametric-based Ki values was found, showing that Ki im

40 There was no bias between NLR and parametric-based Ki values.

41 This novel non-parametric Bayesian approach is demonstrated on a variet

42 me Atlas (TCGA) and developed iDriver, a non-parametric Bayesian framework based on multivariate stat

43 zation, a viewpoint compatible both with non-parametric Bayesian modelling and with sub-symbolic meth

44 signatures, in terms of frequency-dependent parametric beta-band modulation, have been observed rece

45 contrast was 1.6 and 2.0 times higher in the parametric BFM Ki images and 2.3 and 3.0 times in the Pa

46 Whereas optical amplifiers, laser and parametric, boost the energy, their gain bandwidth restr

47 mated using a two-stage cluster-adjusted non-parametric bootstrap method.

48 h analyses are often further studied through parametric bootstrap procedures, using sequence simulato

49 s the standard Gumbel distribution; (ii) our parametric bootstrap simulator is approximately 40 000 t

50 With this simple model, the parametric bootstrap yields an accurate and rapid assess

51 A simple, non-parametric branching model that randomly categorizes ite

52 rtially observed outcome and when performing parametric causal mediation analyses with a partially ob

53 detection of ablation-associated MR imaging parametric changes was developed and demonstrated.

54 s mass-produced, low-cost, disposable, multi-parametric chemical sensing diagnostic platforms.

55 osphide (ZGP) in a narrowband-pumped optical parametric chirped pulse amplifier (OPCPA) and a broadba

56 chirped pulse amplifier (CPA) or an optical parametric chirped pulse amplifier (OPCPA) for achieving

57 fficient moment expansion approximation with parametric closures that integrates well with the IPytho

58 a cloud-of-points, and developed a novel non-parametric clustering algorithm to cluster all the genot

59 A parametric comparator model specified that the observed

60 given survival to S2P) was calculated using parametric conditional survival analysis.

61 In this case, errors in the parametric control of induced stepping and its effective

62 We show that parametric corrections to DFT-computed chemical shifts i

63 Quantitative analysis was based on parametric CVRC maps generated by voxelwise image subtra

64 Parametric data for all subpopulations were tested by us

65 ters, such as blood flow, were calculated by parametric deconvolution for each myocardial voxel.

66 These decision times, and their parametric dependence on task parameters, as well as the

67 f ICSs than 24-hour UFC excretion and that a parametric determination of LLGR increases the sensitivi

68 We observed no significant difference in parametric determined LLGR caused by the child's age or

69 examined with the help of a relatively fast parametric/DFT hybrid computational method, DU8+.

70 We propose a new Joint density based non-parametric Differential Interaction Network Analysis and

71 A Bayesian non-parametric (Dirichlet process) approach is used to clust

72 ing Tbx5 and Osr1 was identified using a non-parametric distance metric, distance correlation.

73 Parametric distribution volume (VT) and influx rate (K1)

74 ical Bayesian approach can be applied to any parametric distribution, removing the need for lengthy d

75 pectrum of the entangled photons produced by parametric down-conversion and report a broad spectrum w

76 Single-photon sources based on parametric down-conversion are currently used, and while

77 The pairs are created via spontaneous parametric downconversion in a lithium niobate waveguide

78 ssimilar quantum nodes, as elements based on parametric downconversion sources, quantum dots, colour

79 l device based on the process of spontaneous parametric downconversion to confirm it behaves as a gen

80 elated intensity measurements of spontaneous parametric downconversion using a commercially available

81 a orthogonal quasi-phase-matched spontaneous parametric downconversion.

82 Parametric effects of cue predictability in valid and in

83 kbone structure can uniquely be described by parametric equations.

84 derived white matter-based reference region (parametric estimate of reference signal intensity [PERSI

85 We present a new technique, PERSI (Parametric Estimation of Reference Signal Intensity), fo

86 round state, we show that in our experiment, parametric excitation from the quantum ground state lead

87 Although parametric excitation of a classical system is ineffecti

88 rathin ferromagnetic nanowire results in the parametric excitation of a propagating spin wave, which

89 n states of an atomic Bose gas that realizes parametric excitation of many-body collective spin state

90 mulus information, while visual areas encode parametric feature information.

91 d non-smokers (n=21), a previously validated parametric flanker task is employed to characterize addi

92 e transmon and individual eigenmodes through parametric flux modulation of the transmon frequency.

93 A parametric frailty model was combined with a logistic re

94 e existing schedule (every 3 months) using a parametric frailty model.

95 omized trials, 2 possible approaches are the parametric g-formula and agent-based models (ABMs).

96 ttachment loss (CAL) was estimated using the parametric g-formula in adults aged 31 years from the 19

97 using an ABM to a similar analysis using the parametric g-formula.

98 es, heart disease, and lung cancer using the parametric g-formula.

99 while controlling for confounding using the parametric g-formula.

100 Optical parametric gain of 42.5 dB, as well as cascaded four-wav

101 dge, representing one of the largest optical parametric gains to date on a CMOS platform.

102 Here, Zeng and Zhou develop a non-parametric genetic prediction method based on latent Dir

103 Functional MRI and performance during a Parametric Go/No-go test were used to predict per cent r

104 rwood to S2P and (2) S2P to 3 years by using parametric hazard analysis.

105 The R(2) between NLR-based and parametric image-based (BFM) tumor Ki values was 0.98 (s

106 Results: The R(2) between NLR-based and parametric image-based (BFM) tumor Ki values was 0.98 (s

107 eity, correlated strongly between static and parametric images (r = 0.70-0.98, P </= 0.0006), exhibit

108 Conclusion Parametric images are not superior to static images for

109 Constructing ultrasound statistical parametric images by using a sliding window is a widely

110 These parametric images could be used for voxel-based comparis

111 for quantitative analysis and generation of parametric images for the novel tau ligand (S)-(18)F-THK

112 the best method for generating quantitative parametric images of (18)F-DPA-714 binding.

113 Parametric images of both (15)O-H2O-derived perfusion (t

114 various methods for generating quantitative parametric images of dynamic (11)C-phenytoin PET studies

115 Static and parametric images of glucose metabolic rate were obtaine

116 , and accordingly there is a need to compute parametric images showing Ki at the voxel level.

117 Parametric images were generated using Logan plot analys

118 Parametric images were generated using plasma input Loga

119 Parametric images were generated using plasma input Loga

120 nerated quantitative (S)-(18)F-THK5117 DVR-1 parametric images with the greatest accuracy and precisi

121 vide insight on the potential added value of parametric images.

122 inding potential obtained with wavelet-aided parametric imaging (WAPI BPND).

123 fectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heteroge

124 In this study, small-window entropy parametric imaging was proposed to overcome the above pr

125 higher than 0.79 obtained using statistical parametric imaging.

126 g a small window for implementing ultrasound parametric imaging.

127 tion limit the practicability of statistical parametric imaging.

128 permutation-based FDR option provides a non-parametric implementation.

129 Dirichlet process regression is non-parametric in nature, relies on the Dirichlet process to

130 identifiability (the analysis of the maximum parametric information available for a model given perfe

131 We observe both amplification into parametric instability (mechanical lasing) and the cooli

132 th an amplitude surpassing the threshold for parametric instability.

133 -retest (TRT) variability was determined for parametric K1 and VT values.

134 Parametric K1 data showed a larger variability in genera

135 ust to noise, yet BFM provided more accurate parametric K1 data.

136 aluate parametric methods for computation of parametric Ki images by comparison to volume of interest

137 tumor-to-liver contrast was superior in the parametric Ki images compared with whole-body images for

138 Parametric Ki images were computed using a basis functio

139 n (R(2)) and agreement between VOI-based and parametric Ki values were assessed using regression and

140 suospatial distance judgment task with three parametric levels of difficulty.

141 not reveal any compelling associations, but parametric linkage analysis of 460 families (1062 affect

142 e performed a variant-level and a gene-level parametric linkage analysis on nine PNTM families (16 af

143 n and is supported as the causal mutation by parametric linkage analysis.

144 linkage on chromosome 1q23.3 to 1q24.3 (non-parametric logarithm of odds score 2.9, model-based loga

145 ar trends, allowing for interrelation of all parametric macromolecular characteristics.

146 Multi-parametric magnetic resonance imaging (MP-MRI) used as a

147 We used the non-parametric Mann-Whitney test to compare NK cell activity

148 Non-parametric Mann-Whitney U test was used for within-group

149 awn in areas of high PF and long MTT on each parametric map.

150 We used statistical parametric mapping (SPM V.12) software to compare groups

151 Images were analyzed with statistical parametric mapping (SPM12).

152 nt of cerebellar hypometabolism (statistical parametric mapping analyses, false discovery rate correc

153 Region of interest and Statistical Parametric Mapping analysis were used to determine longi

154 Statistical parametric mapping software (SPM5) was used to identify

155 Novel quantitative parametric mapping techniques promise to overcome some o

156 cognitive domain, and we used the Biological Parametric Mapping toolbox to further control for local

157 In statistical parametric mapping, striatal hypometabolism was signific

158 el- and region-level analyses in statistical parametric mapping.

159 a voxel level were assessed using Biological Parametric Mapping.

160 cal response were assessed using statistical parametric mapping.

161 ers atlas) and voxel basis using statistical parametric mapping.

162 .12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%)

163 .12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%)

164 and (5) did not provide peak coordinates or parametric maps after contact with the authors.

165 make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations

166 Statistical parametric maps comparing gray matter differences betwee

167 cy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis tec

168 rvised cluster analysis was used to generate parametric maps of 11C-(R)-PK11195 binding potential.

169 performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectra

170 h (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e.,

171 dPET provides the data necessary to generate parametric maps of tumor hypoxia, perfusion, and radiotr

172 avoiding large vessels, on imager-generated parametric maps to measure hepatic PDFF.

173 The feasibility of generating parametric maps was also investigated using graphical an

174 rtmental analysis and providing high-quality parametric maps when applied in voxelwise fashion.

175 fication errors of spectral clustering (SC), parametric maps, and SUV segmentation.

176 relation, energy and homogeneity features of parametric maps.

177 the Logan approach could be used to generate parametric maps.

178 We therefore recommend BFM as the preferred parametric method for analysis of dynamic (18)F-FLT PET/

179 In this paper, we present a non-parametric method for directly comparing sequencing repe

180 is (FIPSA), which is an individual-based non-parametric method for dissecting fine population structu

181 ensional subspace via an extremely efficient parametric method is combined with a judicious Gaussian

182 Here we introduce a non-parametric method to infer first and second time derivat

183 After the settings of each parametric method were optimized, distribution volumes (

184 Results: After the settings of each parametric method were optimized, distribution volumes (

185 leg nonparametric method versus a new 2 leg parametric method.

186 Agreement between parametric methods and SRTM was best for reference Logan

187 The aim of this study was to evaluate parametric methods for computation of parametric Ki imag

188 ective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'-(18

189 Conclusion: Among the various parametric methods tested, the basis function method pro

190 Among the various parametric methods tested, the basis function method pro

191 Biases in VT observed with all parametric methods were less than 5%.

192 Results: Biases in VT observed with all parametric methods were less than 5%.

193 d and accuracy were superior to existing non-parametric methods when the simulated sample size was up

194 ents in nonparametric analysis with standard parametric methods.

195 Here, using a Josephson parametric microwave amplifier combined with high-qualit

196 Here, we demonstrate quantum parametric mode sorting based on nonlinear optics at the

197 Component 1 constructs a Bayesian non-parametric model (Infinite Mixture of Piecewise Linear S

198 ion, for forecasting, we estimated a dynamic parametric model of nursing home use and spending.

199 The Royston-Parmar flexible parametric model showed that in the MMS group, this mort

200 We propose a rank-based semi-parametric model to determine DEGs using information acr

201 We report here a parametric model which introduces a novel mutation featu

202 of PEb was less than that of a prespecified parametric model, particularly for patients with higher-

203 l data are helpful in identifying a specific parametric model-the first of its kind, to our knowledge

204 eved through the generalization of tools for parametric modelling, describing the overall shape of pr

205 d with Cox proportional hazards and flexible parametric models adjusted for stratification factors.

206 ddressed in isolation, largely in restricted parametric models.

207 s of much higher tree diversity derived from parametric models.

208 Commutation is a form of parametric modulation with very high modulation ratio.

209 L contributions to learning, as evidenced by parametric modulations of choice by load and delay and r

210 A parametric multivariable survival model was then used to

211 Parametric, non-parametric, and mixed effects logistic r

212 We conducted parametric, nonparametric, joint linkage and linkage dis

213 locking is achieved with low pumping powers (parametric oscillation threshold powers as low as 5.4 mW

214 states onto two distinct states of classical parametric oscillation: one oscillating state, with 185+

215 monstrated, where a lab-built 500 Hz optical parametric oscillator outputting nanosecond optical puls

216 with a low-maintenance midbandwidth optical parametric oscillator, a few second measurement should y

217 by dispersively coupling it with a Josephson parametric oscillator.

218 coupled time-multiplexed degenerate optical parametric oscillators to implement maximum cut problems

219 n-multiplexed femtosecond degenerate optical parametric oscillators.

220 more recently using the quantum Hall effect, parametric permittivity modulation or Josephson nonlinea

221 rogeneity features extracted from static and parametric PET images of non-small cell lung carcinoma (

222 Both static and parametric PET images were analyzed, with quantitative p

223 Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared betw

224 Whole-tumor-averaged parametric pharmacokinetic parameters were compared with

225 Among the parametric population, vitamin C and reducing sugar conc

226 among genes, or rely on the assumption of a parametric probability distribution of gene measurements

227 ors, without the need of the assumption of a parametric probability distribution of gene measurements

228 ions, owing to the ability to collect highly parametric proteomic data at a single cell level.

229 Such torsional excitation is a form of parametric pumping in the system, which results in the b

230 In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients

231 rporation of machine learning may outperform parametric regression in observational data settings.

232 Our simulation study compares methods under parametric regression misspecification; our results high

233 To estimate PM2.5 concentrations, many parametric regression models have been developed, while

234 c modelling with the powerful methods of non-parametric regression with Gaussian processes.

235 These estimates were included as parametric regressors for analyzing the BOLD time series

236 We found that cortical area V3 has a parametric representation of the rotation symmetries in

237 We propose a methodology for the parametric representation, estimation, and replication o

238 irror was designed based on the principle of parametric resonance and images at 5 frames per second.

239 experimentally confirmed up to 28 orders of parametric resonance in a micromachined membrane resonat

240 has long predicted the onset of n orders of parametric resonance, previously reported experimental o

241 perimental observation of up to 28 orders of parametric resonance, which has thus far only been envis

242 n contrast to the 314 Hz for the first order parametric resonance; furthermore, the half power bands

243 Parametric response mapping (PRM) of paired CT lung imag

244 To determine if parametric response mapping (PRM), a novel computed tomo

245 addition to two novel CT metrics created by parametric response mapping (PRM), a technique pairing i

246 We used parametric response mapping analysis of paired inspirato

247 Parametric response maps (PRMs) were created with multis

248 The parametric response pattern was replicated in the EEG da

249 These parametric responses are seen in several areas of the ve

250 imiting the ability to conduct comprehensive parametric sensitivity analyses.

251 an accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data ass

252 In a parametric simulation using Genetic Investigation of ANt

253 r a nominal familywise error rate of 5%, the parametric statistical methods are shown to be conservat

254 t implements self-contained multivariate non-parametric statistical methods testing a complex null hy

255 gnetic resonance imaging (fMRI) analyses use parametric statistical methods that depend on a variety

256 kage GSAR provides a set of multivariate non-parametric statistical methods that test a complex null

257 confirmed in the flipped analysis and by non-parametric statistical testing (whole brain corrected P-

258 Non-parametric statistical tests were used for between-group

259 c- or, in case of normally distributed data, parametric- statistical tests.

260 school-based differences were analysed using parametric statistics (ANOVA).

261 btraction analyses of lesions as well as non-parametric statistics were conducted.

262 Parametric statistics were used to determine classificat

263 o be designed without the need for extensive parametric studies and simulations.

264 s it an ideal technique for fast mapping and parametric studies including extreme sample environment.

265 We performed parametric studies to show how the salt bridge geometry

266 Parametric studies were conducted to provide insight int

267 36) per experiment further allows for highly parametric studies, which are required when testing mult

268 A parametric study is designed to understand the impact of

269 A parametric study of temperature, pressure, and partial p

270 putational Fluid Dynamics (CFD) to conduct a parametric study to enhance the design and performance o

271 ling angle were extracted after a systematic parametric study using finite element method (FEM) simul

272 We used non-parametric survival analysis methods to estimate gains i

273 Within severity stratum, we used parametric survival analysis to compare length of stay b

274 We used non-parametric survival analysis to estimate a longitudinal

275 nstructed Kaplan-Meier estimates and applied parametric survival analysis to examine proportions of p

276 Weibull parametric survival analysis was used to model the predi

277 rtality time trends estimated using flexible parametric survival modeling.

278 Data were analyzed with flexible parametric survival models that adjusted for potential c

279 We used flexible parametric survival models to estimate the 2-year probab

280 Flexible parametric survival models were built including known pr

281 Here, we present a non-parametric test for the significance of specific pattern

282 Wilcoxon's non-parametric tests assessed the association of APOBEC and

283 occurrence networks were used along with non-parametric tests to identify differences between groups.

284 ng Spearman correlation coefficients and non-parametric tests were utilized to test differences among

285 oculo-visual aspects were compared using non-parametric tests.

286 hological parameters were analyzed using non-parametric tests.

287 Statistical comparisons were made using parametric tests.

288 siloxane) elastomers, we illustrate how this parametric triplet enables the replication of the strain

289 se techniques might have both structural and parametric uncertainties, the new data presented here sh

290 bilistic sensitivity analysis to account for parametric uncertainty in our estimates of the risk of E

291 NCPMDA is a non-parametric universal network-based method that can simul

292 ns of RL and WM to learning, is sensitive to parametric variations in both, and allows us to investig

293 and spectral analysis were used to generate parametric volume of distribution (VT) images.

294 s tested, the basis function method provided parametric VT and K1 values with the least bias compared

295 s tested, the basis function method provided parametric VT and K1 values with the least bias compared

296 h ratio, which helps to develop a new set of parametric wave growth equations.

297 We used parametric Weibull regression models to estimate the tim

298 Fisher's exact and non-parametric Wilcoxon rank-sum tests were used to identify

299 n which brain regions exhibited multivariate parametric WM codes of the maintained frequencies during

300 ndent integration, multisensory integration, parametric working memory, and motor sequence generation