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1.
A primer on disease mapping and ecological regression using <EquationSource Format="TEX">$${\texttt{INLA}}$$</EquationSource>
Title:
A primer on disease mapping and ecological regression using <EquationSource Format="TEX">$${\texttt{INLA}}$$</EquationSource>
Author:
Birgit Schrödle
;
Leonhard Held
Birgit Schrödle
;
Leonhard Held
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Description:
Disease mapping, Ecological regression, INLA, Spatiotemporal models
Disease mapping, Ecological regression, INLA, Spatiotemporal models
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Document Type:
article
URL:
http://hdl.handle.net/10.1007/s0018001002082
http://hdl.handle.net/10.1007/s0018001002082
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RePEc: Research Papers in Economics
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2.
Predictive assessment of a nonlinear random effects model for spacetime surveillance data
Title:
Predictive assessment of a nonlinear random effects model for spacetime surveillance data
Author:
LEONHARD HELD, MICHAELA PAUL
LEONHARD HELD, MICHAELA PAUL
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Description:
Notification data collected by national surveillance systems are typically available as weekly time series of counts of confirmed new cases, stratified e.g. by geographic areas. This work outlines the statistical modeling framework in Paul and
Held
(2011) for the analysis of such data. Inherent (spatio)temporal dependencies are incorporated via...
Notification data collected by national surveillance systems are typically available as weekly time series of counts of confirmed new cases, stratified e.g. by geographic areas. This work outlines the statistical modeling framework in Paul and
Held
(2011) for the analysis of such data. Inherent (spatio)temporal dependencies are incorporated via an observationdriven formulation. Using regionspecific and possibly spatially correlated random effects, we are able to address heterogeneous incidence levels. Inference is based on penalized likelihood methodology for mixed models. The predictive performance of models is assessed using probabilistic onestepahead predictions and proper scoring rules.
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Year of Publication:
2011
Document Type:
conference presentation  intervento a convegno
Language:
eng
Subjects:
Time series of counts; infectious diseases; proper scoring rules; INGIND/09  Sistemi per l'Energia e L'Ambiente
Time series of counts; infectious diseases; proper scoring rules; INGIND/09  Sistemi per l'Energia e L'Ambiente
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Rights:
open
open
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Relations:
Spatial2: Spatial Data Methods for Environmental and Ecological processes. Proceedings.
URL:
http://hdl.handle.net/10446/25260
http://hdl.handle.net/10446/25260
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Aisberg  Archivio istituzionale dell'Università di Bergamo
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3.
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Open Access
Title:
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Author:
Volker J. Schmid
;
Leonhard Held
Volker J. Schmid
;
Leonhard Held
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Description:
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and...
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.
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Publisher:
University of California at Los Angeles, Department of Statistics
Year of Publication:
20071001T00:00:00Z
Document Type:
article
Language:
English
Subjects:
Bayesian hierarchical models ; ageperiodcohort models ; prediction ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Scien...
Bayesian hierarchical models ; ageperiodcohort models ; prediction ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA14737 ; LCC:Social Sciences ; LCC:H
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DDC:
310 Collections of general statistics
(computed)
;
050 General serial publications
(computed)
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CC by
CC by
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Relations:
http://www.jstatsoft.org/v21/i08/paper
URL:
http://doaj.org/search?source=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22term%22%3...
http://doaj.org/search?source=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22term%22%3...
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4.
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A nomogram for P values
Open Access
Title:
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A nomogram for P values
Author:
Leonhard Held
;
Leonhard Held
;
Leonhard Held
Leonhard Held
;
Leonhard Held
;
Leonhard Held
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Description:
This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. A nomogram for P values
This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. A nomogram for P values
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20100524
Source:
http://www.stat.columbia.edu/~cook/movabletype/mlm/ppvalues.pdf
http://www.stat.columbia.edu/~cook/movabletype/mlm/ppvalues.pdf
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Document Type:
text
Language:
en
Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.9487
http://www.stat.columbia.edu/~cook/movabletype/mlm/ppvalues.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.9487
http://www.stat.columbia.edu/~cook/movabletype/mlm/ppvalues.pdf
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5.
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Title:
Bayesian AgePeriodCohort Modeling and Prediction  BAMP
Author:
Leonhard Held
;
Volker J. Schmid
Leonhard Held
;
Volker J. Schmid
Minimize authors
Description:
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and...
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an ageperiodcohort model. A hierarchical model is assumed with a binomial model in the firststage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.
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Document Type:
article
URL:
http://www.jstatsoft.org/v21/i08/paper
http://www.jstatsoft.org/v21/i08/paper
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Content Provider:
RePEc: Research Papers in Economics
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6.
Objective Bayesian Model Selection in Generalised Additive Models with Penalised Splines
Title:
Objective Bayesian Model Selection in Generalised Additive Models with Penalised Splines
Author:
Daniel Sabanés Bové
;
Leonhard Held
;
Göran Kauermann
Daniel Sabanés Bové
;
Leonhard Held
;
Göran Kauermann
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Publisher:
Figshare
Year of Publication:
2014
Document Type:
Dataset ; Dataset
Rights:
CCBY ; http://creativecommons.org/licenses/by/3.0/us/
CCBY ; http://creativecommons.org/licenses/by/3.0/us/
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URL:
http://dx.doi.org/10.6084/M9.FIGSHARE.1006465
http://dx.doi.org/10.6084/M9.FIGSHARE.1006465
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Content Provider:
DataCite Metadata Store (German National Library of Science and Technology)
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7.
Towards Joint Disease Mapping
Open Access
Title:
Towards Joint Disease Mapping
Author:
Leonhard Held Department
;
Leonhard Held
;
Sarah Elaine Fenton
;
Nikolaus Becker
Leonhard Held Department
;
Leonhard Held
;
Sarah Elaine Fenton
;
Nikolaus Becker
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Description:
This paper discusses and extends statistical models to jointly analyse the spatial variation of rates of several diseases with common risk factors.
This paper discusses and extends statistical models to jointly analyse the spatial variation of rates of several diseases with common risk factors.
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20090418
Source:
http://www.math.ntnu.no/~hrue/reports/SMMRrevision.ps.gz
http://www.math.ntnu.no/~hrue/reports/SMMRrevision.ps.gz
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Document Type:
text
Language:
en
Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.5841
http://www.math.ntnu.no/~hrue/reports/SMMRrevision.ps.gz
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.5841
http://www.math.ntnu.no/~hrue/reports/SMMRrevision.ps.gz
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8.
Bayesian Estimation of the Size of a Population
Open Access
Title:
Bayesian Estimation of the Size of a Population
Author:
Michael Höhle
;
Leonhard Held
Michael Höhle
;
Leonhard Held
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Description:
We consider the following problem: estimate the size of a population marked with serial numbers after only a sample of the serial numbers has been observed. Its simplicity in formulation and the inviting possibilities of application make this estimation well suited for an undergraduate level probability course. Our contribution consists in a B...
We consider the following problem: estimate the size of a population marked with serial numbers after only a sample of the serial numbers has been observed. Its simplicity in formulation and the inviting possibilities of application make this estimation well suited for an undergraduate level probability course. Our contribution consists in a Bayesian treatment of the problem. For an improper uniform prior distribution, we show that the posterior mean and variance have nice closed form expressions and we demonstrate how to compute highest posterior density intervals. Maple and R code is provided on the authors ’ webpage to allow students to verify the theoretical results and experiment with data.
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20150114
Source:
http://epub.ub.unimuenchen.de/2094/1/paper_499.pdf
http://epub.ub.unimuenchen.de/2094/1/paper_499.pdf
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Document Type:
text
Language:
en
Subjects:
Bayesian inference ; Combinatorics ; Hypergeometric functions ; Maple ; R
Bayesian inference ; Combinatorics ; Hypergeometric functions ; Maple ; R
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Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.531.1060
http://epub.ub.unimuenchen.de/2094/1/paper_499.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.531.1060
http://epub.ub.unimuenchen.de/2094/1/paper_499.pdf
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9.
RESEARCH ARTICLE Open Access
Open Access
Title:
RESEARCH ARTICLE Open Access
Author:
Leonhard Held
Leonhard Held
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Description:
Background: P values are the most commonly used tool to measure evidence against a hypothesis. Several attempts have been made to transform P values to minimum Bayes factors and minimum posterior probabilities of the hypothesis under consideration. However, the acceptance of such calibrations in clinical fields is low due to inexperience in inte...
Background: P values are the most commonly used tool to measure evidence against a hypothesis. Several attempts have been made to transform P values to minimum Bayes factors and minimum posterior probabilities of the hypothesis under consideration. However, the acceptance of such calibrations in clinical fields is low due to inexperience in interpreting Bayes factors and the need to specify a prior probability to derive a lower bound on the posterior probability. Methods: I propose a graphical approach which easily translates any prior probability and P value to minimum posterior probabilities. The approach allows to visually inspect the dependence of the minimum posterior probability on the prior probability of the null hypothesis. Likewise, the tool can be used to read off, for fixed posterior probability, the maximum prior probability compatible with a given P value. The maximum P value compatible with a given prior and posterior probability is also available. Results: Use of the nomogram is illustrated based on results from a randomized trial for lung cancer patients comparing a new radiotherapy technique with conventional radiotherapy. Conclusion: The graphical device proposed in this paper will enhance the understanding of P values as measures of evidence among nonspecialists.
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20130925
Source:
ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/ac/49/BMC_Med_Res_Methodol_2010_Mar_16_10_21.tar.gz
ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/ac/49/BMC_Med_Res_Methodol_2010_Mar_16_10_21.tar.gz
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Document Type:
text
Language:
en
DDC:
310 Collections of general statistics
(computed)
Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.354.9681
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.354.9681
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10.
Overview
Open Access
Title:
Overview
Author:
Leonhard Held
Leonhard Held
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Description:
1. Motivating problem Forecasting cancer rates 2. Predictive model comparison and criticism Goals Proper scoring rules Tools for model criticism 3. Case study 4. Discussion Motivating problem II: Forecasting cancer rates I Bayesian ageperiodcohort models are used increasingly to project cancer incidence and mortality rates. I Data from younger...
1. Motivating problem Forecasting cancer rates 2. Predictive model comparison and criticism Goals Proper scoring rules Tools for model criticism 3. Case study 4. Discussion Motivating problem II: Forecasting cancer rates I Bayesian ageperiodcohort models are used increasingly to project cancer incidence and mortality rates. I Data from younger age groups (typically age < 30 years) for which rates are low are often excluded from the analysis. I However, a recent empirical comparison (Baker and Bray, 2005) based on data from Hungary suggests that agespecific predictions based on full data are more accurate. { Question how to quantify the accuracy of probabilistic forecasts { Forecast evaluation for model comparison Case study: Forecasting larynx cancer rates in Germany I We will investigate if the same conclusion can be drawn for mortality data on larynx cancer from Germany, 19521997. I To assess the predictive quality of the different models, we have predicted the mortality counts in the years 19982002. I For all different models, we looked at the predictions in the 12 age groups with age above 30 years. I Onestepahead forecasts have also been calculated. Forecasting cancer rates cont. Observed (×) and fitted/predicted number of deaths (per 100,000) for larynx cancer among males. Shown are posterior means and 90% pointwise credible intervals for the mean, calculated with software BAMP.
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Contributors:
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Year of Publication:
20150304
Source:
http://www.statoo.ch/gss06/presentations/
Held
.pdf
http://www.statoo.ch/gss06/presentations/
Held
.pdf
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Document Type:
text
Language:
en
DDC:
310 Collections of general statistics
(computed)
Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.565.2341
http://www.statoo.ch/gss06/presentations/Held.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.565.2341
http://www.statoo.ch/gss06/presentations/Held.pdf
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(2) model diagnostics
(2) multivariate time series of counts
(2) ordinal response
(2) paired comparisons
(2) physics data analysis
(2) pneumonia
(2) predictive deviance
(2) predictive performance
(2) r
(2) research article
(2) statistics and probability
(2) statistics computation
(2) stochastic differential equations
(2) theologie
(2) time varying regression parameters
(2) validation
(2) variable selection
(1) 170 ethics
(1) 340 law
(1) 360 social problems social services
(1) 570 life sciences biology
(1) 610 medical sciences medicine
(1) 62c12
(1) 62j02
(1) age period cohort model
(1) age period cohort models
(1) and science
(1) articles
(1) autopsy
(1) auxiliary variables
(1) base prior
(1) bayes theorem
(1) bayesian binary and multinomial regression
(1) bayesian robustness
(1) binary data
(1) binomial data
(1) block updating
(1) c15
(1) cancer atlas
Subject:
Dewey Decimal Classification (DDC)
(51) Statistics [31*]
(20) Medicine & health [61*]
(8) Computer science, knowledge & systems [00*]
(2) Mathematics [51*]
(2) Sports, games & entertainment [79*]
(1) Magazines, journals & serials [05*]
(1) Economics [33*]
(1) Social problems & social services [36*]
(1) Earth sciences & geology [55*]
(1) Life sciences; biology [57*]
Dewey Decimal Classification (DDC):
Year of Publication
(35) 2014
(30) 2009
(22) 2013
(15) 2011
(12) 2012
(9) 2015
(6) 2004
(6) 2006
(6) 2008
(6) 2010
(5) 1999
(5) 2005
(4) 2003
(3) 2001
(3) 2007
(2) 1995
(2) 1996
(2) 1997
(2) 2000
(1) 1643
(1) 1663
(1) 1669
(1) 1679
(1) 1998
Year of Publication:
Content Provider
(42) CiteSeerX
(35) Zurich Univ.: ZORA
(26) Munich LMU: Open Access
(17) DataCite Metadata Store
(10) RePEc.org
(8) ArXiv.org
(7) Project Euclid
(7) EconStor
(6) Bern Univ.: BORIS
(5) HighWire Press
(5) PubMed Central
(3) BioMed Central
(3) DOAJ Articles
(3) Berlin State Library: Digitalisierte Sammlungen
(2) Zurich ETH: ECollection
(2) Illinois Univ. Chicago: EJournals
(2) Warwick Univ.: Warwick Research Archive Portal
(1) Wolfenbüttel Digital Library (WDB)
(1) Aachen RWTH: Publications
(1) Aarhus Univ.: Pure
(1) Basel Univ.: edoc
(1) Bergamo Univ.: Aisberg
(1) Minho Univ.: Repositorium
(1) Queensland Univ.: UQ eSpace
Content Provider:
Language
(129) English
(59) Unknown
(2) German
Language:
Document Type
(68) Text
(59) Article, Journals
(34) Reports, Papers, Lectures
(21) Unknown
(7) Books
(1) Primary Data
Document Type:
Access
(116) Unknown
(74) Open Access
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