ライフサイエンスコーパス: GCM

1 GCM treated-cortical neuronal culture induced a concentr

2 GCMs also vary greatly in their projections of future cl

3 GCMs are physics-based simulators that combine a numeric

4 pected to decline by 17%-86% for 7 of the 10 GCM/RCP scenarios.

5 In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios

6 nd future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the centur

7 KZ approaches were compared with the full 20-GCM ensemble.

8 Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over

9 ulation is projected under five SSPs, and 31 GCM runs as well as temperature-mortality relation curve

10 ted annual heat-related deaths across the 33 GCMs varied greatly by RCP and adaptation and population

11 nt approaches that were employed to select 5 GCMs from a 20-member ensemble of GCMs from the CMIP5 en

12 o outperform a subset of randomly selected 5 GCMs in terms of a smaller error and a larger range.

13 ads of the simulated crop yields using the 5-GCM subsets selected by T&P and KKZ approaches were comp

14 Our results showed that the 5-GCM subsets selected by the two approaches could produce

15 ight Coupled Model Intercomparison Project 6 GCMs and three Shared Socioeconomic Pathways.

16 A GCM's realization of present-day (1970-1999) and future

17 After reducing this bias in a GCM, underestimations of humid heat waves in energy-limi

18 Here we present a GCM that combines a differentiable solver for atmospheri

19 as highly variable future projections across GCMs.

20 century, based on median projections across GCMs.

21 ies large uncertainties that directly affect GCM predictions, such as climate sensitivity.

22 al that IITM-ESM is the most effective among GCM models.

23 samples from fulminant myocarditis (n=2) and GCM (n=13) contained human endogenous retrovirus K.

24 LL-AML Leukemia data, Breast Cancer data and GCM data).

25 ods for large-class datasets (e.g. NCI60 and GCM).

26 The difference between RCM- and GCM-based scenarios is due to greater warming and larger

27 we find strong agreement between the VKE and GCM estimates with respect to electricity generation rat

28 vealed that, although climatic scenarios and GCMs used have a significant influence on model outputs,

29 Once a bias correction is applied, GCM- and RCM-driven US maize yields are essentially indi

30 g suggests that the selection of appropriate GCMs should be much more emphasized than that of a param

31 u measurements coupled with state-of-the-art GCM simulations enables us to quantify the mitigation po

32 Rarer causes of myocarditis such as GCM should be sought in patients who develop ventricular

33 Atrial GCM represents a distinct clinicopathologic entity with

34 (median age 67.5 years, 4 male) with atrial GCM in our pathology consultation practices from 2010 to

35 Furthermore, combining BOLD fMRI-based GCM and DTPM analysis could provide a novel means to stu

36 to take into account the differences between GCM-simulated and observed rainfall regimes in the 20th

37 internal variability and variability between GCMs from 1979-2014, showing modern GCMs do not plausibl

38 ion, and decreased neuronal death induced by GCM.

39 alue analysis for projected runoff driven by GCMs' output indicates extreme floods are more severe in

40 tation is equivalent to climate projected by GCMs for California by 2020-2030 and that under these co

41 n quantity of emitted dust has likely caused GCMs to underestimate the global dust emission rate.

42 e overestimation of the clay fraction causes GCMs to also overestimate the radiative cooling of a giv

43 h (NCAR) Community Earth System Model (CESM) GCM to align with the new observations and evaluate the

44 CMIP5 GCM model output data were then used to investigate the

45 observed raising temperatures and the CMIP6 GCM simulations.

46 ent from that obtained by using a comparable GCM-based scenario, under which these species retain 81%

47 waves to anthropogenic warming by comparing GCM simulations with and without anthropogenic emissions

48 reases in coastal temperatures, compromising GCMs' ability to provide realistic scenarios of future c

49 upled CO2 simulations between a conventional GCM in which convection is parameterized and a "superpar

50 patible with tasks performed by conventional GCMs and can enhance the large-scale physical simulation

51 tude computational savings over conventional GCMs, although our model does not extrapolate to substan

52 Current GCMs parameterize cloud droplet size distributions as br

53 Our climate model is unusual among current GCMs in that it is able to reproduce this relationship a

54 Currently, GCM includes >368 000 strains from 103 culture collectio

55 oat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska.

56 eement in climate predictions from different GCMs, we focused on the GCM projections that produced th

57 was still adequate, based on the downscaled GCM climate projections.

58 a high-resolution alternative to downscaled GCM outputs for near-term ecological forecasts.

59 PCA may improve upon application of existing GCMs in study of human brain effective connectivity.

60 ber of the small transcription factor family GCM (glial cells missing), which are important regulator

61 arctic ice core records alongside input from GCM modelling.

62 evant amounts in cardiac tissue samples from GCM or in blood samples from other types of myocarditis.

63 Nine patients (27%) had GCM and 4 patients (13%) had fulminant myocarditis.

64 ry cortical neuronal culture and evaluate if GCM-KL (medium from glia culture pretreated alpha-Klotho

65 Importantly, GCMs appear to accurately estimate the observed latitudi

66 do not exclude a role for viral infection in GCM but do suggest that if viruses are implicated, the m

67 led liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phas

68 regional currents, a feature not resolved in GCMs.

69 ticosteroid treatment inhibits IL-13-induced GCM of the airways in asthma, possibly through its effec

70 hange and compare frameworks for integrating GCM output into ecological models.

71 ominated by broad-scale (100s of kilometers) GCM systematic errors that RCMs cannot compensate for.

72 I use a set of five large GCM ensembles, and CMIP6 simulations, to quantify GCM in

73 f wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach der

74 at are present in the Global Cancer Mapping (GCM) data set.

75 nvestigated using Granger causality mapping (GCM).

76 l amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (R

77 edures i) to generate the Genome-CYP Matrix (GCM) that lists all occurrences of CYPs across the genom

78 e treated with LPS (glia conditioned medium (GCM) was used to induce neuronal death of primary cortic

79 A ceramic/graphene metamaterial (GCM) with microstructure-derived superelasticity and str

80 Bronchial epithelial goblet cell metaplasia (GCM) with hyperplasia is a prominent feature of asthma,

81 analysis (PCA) and Granger causality method (GCM) is proposed to study directional influence between

82 employed both the group contribution method (GCM) and a semisupervised learning (SSL) strategy to add

83 udy, we develop a group contribution method (GCM) to predict the mass transfer coefficients by fragme

84 Global Catalogue of Microorganism (GCM) gathers strain catalogue information and provides a

85 y of the Global Catalogue of Microorganisms (GCM) 10K prokaryotic type strain sequencing project, Glo

86 We also learned that glial cells missing (GCM), a key transcription factor of the endomesoderm gen

87 ase family 3 (FMO3) and glial cells missing (GCM).

88 een identified in the germinal center model (GCM) of EBV persistence in humans.

89 The germinal center model (GCM) of Epstein-Barr virus (EBV) persistence in humans p

90 According to the germinal center model (GCM), latently infected B cells transit the germinal cen

91 t phase 6 (CMIP6) General Circulation Model (GCM) ensemble output.

92 ns generated by a general circulation model (GCM) in "normal" and "hosing" experiments.

93 ) are driven with general circulation model (GCM) output--to produce fine-spatial-scale climate proje

94 g with downscaled general circulation model (GCM) projections of warming and streamflow change to est

95 ice cores, prior general circulation model (GCM) studies have supported the assumption of constant u

96 th an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbi

97 th an atmospheric general circulation model (GCM) that tracks oxygen isotopes in vapor.

98 ies (GISS) ModelE General Circulation Model (GCM) to the regional scale using the Weather Research Fo

99 Using an advanced general circulation model (GCM), we demonstrate that an ocean can be stable, even i

100 Global climate model (GCM) estimates of the equilibrium global mean surface te

101 in species' ranges use global climate model (GCM) output, regional climate model (RCM) output may be

102 We review Global Climate Model (GCM) performance along different dimensions of change an

103 based on 20 projected global climate model (GCM) realizations, while considering uncertainties of tr

104 ith trends, across 146 Global Climate Model (GCM) runs and two elevated greenhouse gas (GHG) emission

105 Here, we use a global climate model (GCM) to show that a cloud greenhouse can warm a Mars-lik

106 The genotypic covariance model (GCM) and the structured linear model (SLM) rely on the s

107 ions of SIE from General Circulation Models (GCM) of Earth's climate included in the most recent Inte

108 ut from numerous General Circulation Models (GCMs) also exhibits positive trends in PFP(LM) over 1950

109 in both multiple general circulation models (GCMs) and multi-parameter ensembles to hydrological proj

110 y exists between general circulation models (GCMs) and satellite observations: The multimodel mean te

111 ent global-scale General Circulation Models (GCMs) and two Representative Concentration Pathways scen

112 General circulation models (GCMs) are the foundation of weather and climate predicti

113 General circulation models (GCMs) are the tool for predicting future climate, but th

114 rature data from General Circulation Models (GCMs) for different Shared Socio-economic Pathway (SSP)

115 st generation of general circulation models (GCMs) from the sixth phase of the Coupled Model Intercom

116 on scenarios, and global circulation models (GCMs) on final model outputs.

117 that regional and global circulation models (GCMs) overestimate the emitted fraction of clay aerosols

118 pecially as some general circulation models (GCMs) predict a severe drying of Amazonia in the twenty-

119 However, general circulation models (GCMs) predict future increase in summer temperature and

120 ic CO2, high-end general circulation models (GCMs) simulate an accumulation of energy at the top of t

121 Phase 5 (CMIP5) general circulation models (GCMs) suggest that warmer winter temperatures in 2080-21

122 alyzing eighteen General Circulation Models (GCMs) to identify the most suitable one.

123 We used five Global Circulation Models (GCMs) to make future (2011 to 2100) rainfall and tempera

124 projections from general circulation models (GCMs) to predict changes in vectorial capacity, an indic

125 simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologicall

126 ojections by five Global Circulation Models (GCMs) under the Representative Concentrations Pathway (R

127 runoff model with global circulation models (GCMs), CCSM4, HadGEM3, and GFDL-CM4.0, projections as mo

128 ased on multiple general circulation models (GCMs), emission scenarios, and migration scenarios, to p

129 General circulation models (GCMs), forced by sea surface temperatures (SSTs) from th

130 time periods, and global circulation models (GCMs).

131 pitation based on global circulation models (GCMs).

132 rage of multiple general circulation models (GCMs).

133 ojections from the 33 global climate models (GCMs) and two Representative Concentration Pathways (RCP

134 esentative subsets of global climate models (GCMs) are often used in climate change impact studies to

135 ons around the world, global climate models (GCMs) consistently project drier futures.

136 Global climate models (GCMs) consistently underestimate the response of Septemb

137 eriment (CORDEX), and Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Pha

138 tion (~1 degrees ) of Global Climate Models (GCMs) have informed debate but have not helped target lo

139 ate simulations by 19 global climate models (GCMs) in this context and find that most tend to underes

140 tions derived from 20 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase

141 Current global climate models (GCMs) overestimate light rain.

142 Global climate models (GCMs) predict enhanced warming and nutrient decline acro

143 Global climate models (GCMs) predict future conditions at large spatial scales,

144 Global climate models (GCMs) project great spatial variation in the timing of a

145 e to the inability of global climate models (GCMs) to resolve essential small-scale cloud and convect

146 ad with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both

147 ns from 20 downscaled global climate models (GCMs) were used with the 3-PG model to predict the futur

148 ta simulated by seven Global Climate Models (GCMs) which belong to the newest Coupled Model Intercomp

149 tures simulated by 21 global climate models (GCMs), projecting the effects of warming on the demand f

150 using data from seven global climate models (GCMs), used to compare power outage risks at the census

151 Uncertainties in global climate models (GCMs)-particularly in projecting changes in remote drive

152 drizzle transition in global climate models (GCMs).

153 tions from downscaled global climate models (GCMs).

154 poorly represented in global climate models (GCMs).

155 between GCMs from 1979-2014, showing modern GCMs do not plausibly estimate the response of SIA to wa

156 caling exponent Z [group conflict mortality (GCM)].

157 On a global scale, the dust cycle in most GCMs is tuned to match radiative measurements, such that

158 study demonstrated that the impact of multi-GCM ensemble uncertainty on direct runoff projections fo

159 finality was more influential than the multi-GCM ensemble uncertainty.

160 d increasing by as much as 9.5% at the multi-GCM median.

161 Giant cell myocarditis (GCM) typically causes fulminant heart failure, arrhythmi

162 t been implicated in giant cell myocarditis (GCM).

163 t likely that the histological appearance of GCM was due to the presence of mycobacterial infection w

164 Our patient is the first reported case of GCM and a concurrent diagnosis of tuberculosis.

165 than, uncertainty arising from the choice of GCM.

166 nal toxicity induced by low concentration of GCM-LPS.

167 easures of MUC5AC and MUC5B and induction of GCM.

168 Overall, the uncertainty of GCM projections was dominant for relatively rapid hydrol

169 We describe a novel variant of GCM, primarily involving the atria, that displays distin

170 o select 5 GCMs from a 20-member ensemble of GCMs from the CMIP5 ensemble for projecting canola and s

171 We also assess the latest generation of GCMs from the Coupled Model Intercomparison Project Phas

172 Frequently mentioned as limitations of GCMs are the structural error and uncertainty across mod

173 des or less, consistent with the majority of GCMs.

174 at over 50% of genes selected by BCGA-ELM on GCM data are cancer related biomarkers.

175 beta2 -adrenergic receptor agonist (LABA) on GCM in the bronchial epithelium are unknown.

176 Mosaic knockout of either PKS or GCM revealed spatial lineage commitment in the transitio

177 alpha-Klotho followed by LPS stimulation) or GCM + LPS in the presence of KL can reverse the effect.

178 Traditional general circulation models, or GCMs-that is, three-dimensional dynamical models with un

179 from improvements in forcing driven by other GCM components.

180 nsembles, and CMIP6 simulations, to quantify GCM internal variability and variability between GCMs fr

181 ere, we explore whether local erosion rates, GCM-derived dust fluxes, temperature, and water balance

182 s assessments of dynamically downscaling raw GCM output may not be sufficient to justify its computat

183 ed these scenarios against coarse resolution GCM projections at a regional scale to evaluate their te

184 ics that are not represented by coarse-scale GCMs.

185 nscaled daily climate predictions from seven GCMs to run a continental-scale hydrological model for a

186 ments on mean projected changes from several GCMs.

187 ASB) varies 10 or more years within a single GCM grid cell.

188 Although RCMs correct some GCM biases related to fine-scale geographic features, er

189 Subsequently, GCM can be applied to principal components extracted in

190 ave achieved comparable or better skill than GCMs for deterministic weather forecasting(3,4).

191 The results indicated that GCM improved the model's performance for chemicals outsi

192 The GCM predicts changes in atmospheric circulation and rain

193 The GCM remains the only model that explains EBV biology and

194 e published will continue to increase as the GCM 10K project increases its collaboration with culture

195 ed 1049 type strain genomes sequenced by the GCM 10K project which are preserved in global culture co

196 ccur opposite the direction predicted by the GCM.

197 To extend the GCM for a reference RO membrane, ESPA2-LD, 14 additional

198 over the Great Plains is represented in the GCM as a reduction in vegetation cover and the addition

199 In the GCM mean, this OLR recovery timescale is only 20 y becau

200 sociated cancers have been identified in the GCM.

201 nanolayers of the Al2 O3 ceramic (NAC), the GCM demonstrates a sequence of multifunctional propertie

202 Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0

203 ataset and the two largest categories of the GCM dataset, the results achieved by recursive RR are al

204 rculous therapy has led to resolution of the GCM without the need for continued long-term immunosuppr

205 to perform analyses and visualization of the GCM, including pan-CYPomes (pan- and core-CYPome), CYP c

206 tions from different GCMs, we focused on the GCM projections that produced the best and worst conditi

207 This is accomplished by reformulating the GCM in terms of the Wright-Kempthorne equation.

208 The SLM is generally more accurate than the GCM, the most pronounced differences emerging in simulat

209 re different for the Bahamas compared to the GCM projections.

210 We found that using distance to the GCM together with amino acid type provide a good discrim

211 Even under the GCM predictions most conducive to malaria transmission,

212 Consistent with the GCM simulations, the approach estimates that only compar

213 ure (SST) means and annual cycles in all the GCMs are replaced with observed data from the ~4-km NOAA

214 tions by considering the agreement among the GCMs outage projections.

215 when combined, DLX3 acts as an antagonist to GCM.

216 re effectively captured with the distance to GCM definition.

217 by a variety of climate inputs including two GCMs, each in turn downscaled by two RCMs.

218 The simulation demonstrated that by using GCM with PCA, between-region causalities were better rep

219 usalities were better represented than using GCM with average values.

220 favorable prognosis than classic ventricular GCM.

221 ollows a more benign course than ventricular GCM.

222 sides in an entire hierarchy of models where GCMs will continue to play a central role for the forese

223 The pace and extent to which GCM projections overwhelm historical trends will play a

224 atospheric halogen loading and humidity with GCM-based forecasts of temperature to suggest that condi

225 In addition, KL incubation together with GCM + LPS completely reverts the neuronal toxicity induc