Sun, 14 Jul 2024

Package SetTest updated to version 0.3.0 with previous version 0.2.0 dated 2018-03-22

Title: Group Testing Procedures for Signal Detection and Goodness-of-Fit
Description: It provides cumulative distribution function (CDF), quantile, p-value, statistical power calculator and random number generator for a collection of group-testing procedures, including the Higher Criticism tests, the one-sided Kolmogorov-Smirnov tests, the one-sided Berk-Jones tests, the one-sided phi-divergence tests, etc. The input are a group of p-values. The null hypothesis is that they are i.i.d. Uniform(0,1). In the context of signal detection, the null hypothesis means no signals. In the context of the goodness-of-fit testing, which contrasts a group of i.i.d. random variables to a given continuous distribution, the input p-values can be obtained by the CDF transformation. The null hypothesis means that these random variables follow the given distribution. For reference, see [1]Hong Zhang, Jiashun Jin and Zheyang Wu. "Distributions and power of optimal signal-detection statistics in finite case", IEEE Transactions on Signal Processing (2020) 68, 1021-1033; [2] Hong Zhang and Zhey [...truncated...]
Author: Hong Zhang and Zheyang Wu
Maintainer: Hong Zhang <hzhang@wpi.edu>

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Package tor updated to version 1.1.3 with previous version 1.1.2 dated 2020-03-07

Title: Import Multiple Files From a Single Directory at Once
Description: The goal of tor (to-R) is to help you to import multiple files from a single directory at once, and to do so as quickly, flexibly, and simply as possible.
Author: Mauro Lepore [aut, cre]
Maintainer: Mauro Lepore <maurolepore@gmail.com>

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Package tidystats updated to version 0.6.2 with previous version 0.6.1 dated 2024-04-09

Title: Save Output of Statistical Tests
Description: Save the output of statistical tests in an organized file that can be shared with others or used to report statistics in scientific papers.
Author: Willem Sleegers
Maintainer: Willem Sleegers <w.sleegers@me.com>

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Package SIMPLE.REGRESSION updated to version 0.1.9 with previous version 0.1.6 dated 2023-02-24

Title: OLS, Moderated, Logistic, and Count Regressions Made Simple
Description: Provides SPSS- and SAS-like output for least squares multiple regression, logistic regression, and Poisson regression. Detailed output is also provided for OLS moderated regression, interaction plots, and Johnson-Neyman regions of significance. The output includes standardized coefficients, partial and semi-partial correlations, collinearity diagnostics, plots of residuals, and detailed information about simple slopes for interactions. There are numerous options for model plots, including plots of interactions for both lm and lme models.
Author: Brian P. O'Connor
Maintainer: Brian P. O'Connor <brian.oconnor@ubc.ca>

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Package nls2 updated to version 0.3-4 with previous version 0.3-3 dated 2022-05-02

Title: Non-Linear Regression with Brute Force
Description: Adds brute force and multiple starting values to nls.
Author: G. Grothendieck, R Core Team
Maintainer: G. Grothendieck <ggrothendieck@gmail.com>

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Package cubature updated to version 2.1.1 with previous version 2.1.0 dated 2023-06-11

Title: Adaptive Multivariate Integration over Hypercubes
Description: R wrappers around the cubature C library of Steven G. Johnson for adaptive multivariate integration over hypercubes and the Cuba C library of Thomas Hahn for deterministic and Monte Carlo integration. Scalar and vector interfaces for cubature and Cuba routines are provided; the vector interfaces are highly recommended as demonstrated in the package vignette.
Author: Balasubramanian Narasimhan [aut, cre], Manuel Koller [ctb], Steven G. Johnson [aut], Thomas Hahn [aut], Annie Bouvier [aut], Kien Kieu [aut], Simen Gaure [ctb]
Maintainer: Balasubramanian Narasimhan <naras@stat.stanford.edu>

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Package CICA updated to version 1.1.1 with previous version 1.1.0 dated 2024-07-11

Title: Clusterwise Independent Component Analysis
Description: Clustering multi-subject resting state functional Magnetic Resonance Imaging data. This methods enables the clustering of subjects based on multi-subject resting state functional Magnetic Resonance Imaging data. Objects are clustered based on similarities and differences in cluster-specific estimated components obtained by Independent Component Analysis.
Author: Jeffrey Durieux [aut, cre], Tom Wilderjans [aut], Juan Claramunt Gonzalez [ctb]
Maintainer: Jeffrey Durieux <durieux.jeffrey@gmail.com>

Diff between CICA versions 1.1.0 dated 2024-07-11 and 1.1.1 dated 2024-07-14

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Package bsvars updated to version 3.1 with previous version 3.0.1 dated 2024-06-28

Title: Bayesian Estimation of Structural Vector Autoregressive Models
Description: Provides fast and efficient procedures for Bayesian analysis of Structural Vector Autoregressions. This package estimates a wide range of models, including homo-, heteroskedastic, and non-normal specifications. Structural models can be identified by adjustable exclusion restrictions, time-varying volatility, or non-normality. They all include a flexible three-level equation-specific local-global hierarchical prior distribution for the estimated level of shrinkage for autoregressive and structural parameters. Additionally, the package facilitates predictive and structural analyses such as impulse responses, forecast error variance and historical decompositions, forecasting, verification of heteroskedasticity, non-normality, and hypotheses on autoregressive parameters, as well as analyses of structural shocks, volatilities, and fitted values. Beautiful plots, informative summary functions, and extensive documentation complement all this. The implemented techniques align closely with thos [...truncated...]
Author: Tomasz Wozniak [aut, cre]
Maintainer: Tomasz Wozniak <wozniak.tom@pm.me>

Diff between bsvars versions 3.0.1 dated 2024-06-28 and 3.1 dated 2024-07-14

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New package zippeR with initial version 0.1.0
Package: zippeR
Title: Working with United States ZIP Code and ZIP Code Tabulation Area Data
Version: 0.1.0
Description: Provides a set of functions for working with American postal codes, which are known as ZIP Codes. These include accessing ZIP Code to ZIP Code Tabulation Area (ZCTA) crosswalks, retrieving demographic data for ZCTAs, and tabulating demographic data for three-digit ZCTAs.
Depends: R (>= 3.5)
License: Apache License (>= 2)
URL: https://github.com/pfizer-opensource/zippeR
BugReports: https://github.com/pfizer-opensource/zippeR/issues
Encoding: UTF-8
LazyData: true
Imports: datasets, dplyr, httr, jsonlite, purrr, readr, sf, spatstat.univar, stats, stringr, tibble, tidycensus, tidyr, tigris
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-07-12 15:44:37 UTC; prenec
Author: Christopher Prener [aut, cre] , Timothy Wiemken [aut] , Angela Cook [aut]
Maintainer: Christopher Prener <Christopher.Prener@pfizer.com>
Repository: CRAN
Date/Publication: 2024-07-14 12:40:02 UTC

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New package modisfast with initial version 0.9.1
Package: modisfast
Title: Fast and Efficient Access to MODIS Earth Observation Data
Version: 0.9.1
Description: Programmatic interface to several NASA Earth Observation 'OPeNDAP' servers (Open-source Project for a Network Data Access Protocol) (<https://www.opendap.org/>). Allows for easy downloads of MODIS subsets, as well as other Earth Observation datacubes, in a time-saving and efficient way : by sampling it at the very downloading phase (spatially, temporally and dimensionally).
License: GPL (>= 3)
URL: https://github.com/ptaconet/modisfast
BugReports: https://github.com/ptaconet/modisfast/issues
Depends: R (>= 2.10)
Imports: curl, dplyr, httr, lubridate, magrittr, parallel, purrr, rvest, sf, stats, stringr, terra, xml2
Suggests: ggplot2, knitr, mapview, rmarkdown, spelling, testthat
Encoding: UTF-8
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2024-07-12 12:08:40 UTC; ptaconet
Author: Paul Taconet [aut, cre, cph] , Nicolas Moiroux [fnd] , French National Research Institute for Sustainable Development, IRD [fnd]
Maintainer: Paul Taconet <paul.taconet@gmail.com>
Repository: CRAN
Date/Publication: 2024-07-14 12:10:02 UTC

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New package mig with initial version 1.0
Package: mig
Title: Multivariate Inverse Gaussian Distribution
Version: 1.0
Description: Provides utilities for estimation for the multivariate inverse Gaussian distribution of Minami (2003) <doi:10.1081/STA-120025379>, including random vector generation and explicit estimators of the location vector and scale matrix. The package implements kernel density estimators discussed in Belzile, Desgagnes, Genest and Ouimet (2024) <doi:10.48550/arXiv.2209.04757> for smoothing multivariate data on half-spaces.
BugReports: https://github.com/lbelzile/mig/issues
Imports: statmod, TruncatedNormal (>= 2.3), Rcpp (>= 1.0.12)
Depends: R (>= 2.10)
Suggests: numDeriv, tinytest, knitr, rmarkdown, minqa
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-07-12 13:32:47 UTC; lbelzile
Author: Frederic Ouimet [aut] , Leo Belzile [aut, cre]
Maintainer: Leo Belzile <belzilel@gmail.com>
Repository: CRAN
Date/Publication: 2024-07-14 12:30:02 UTC

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New package EEML with initial version 0.1.0
Package: EEML
Title: Ensemble Explainable Machine Learning Models
Version: 0.1.0
Author: Dr. Md Yeasin [aut, cre], Dr. Ranjit Kumar Paul [aut], Dr. Dipanwita Haldar [aut], Dr. Suresh Kumar [aut]
Maintainer: Dr. Md Yeasin <yeasin.iasri@gmail.com>
Description: We introduced a novel ensemble-based explainable machine learning model using Model Confidence Set (MCS) and two stage Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The model combined the predictive capabilities of different machine-learning models and integrates the interpretability of explainability methods. To develop the proposed algorithm, a two-stage Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) framework was employed. The package has been developed using the algorithm of Paul et al. <doi:10.1007/s40009-023-01218-x> and Yeasin and Paul (2024) <doi:10.1007/s11227-023-05542-3>.
License: GPL-3
Encoding: UTF-8
Imports: stats, MCS, WeightedEnsemble, topsis
NeedsCompilation: no
Packaged: 2024-07-12 20:22:54 UTC; YEASIN
Repository: CRAN
Date/Publication: 2024-07-14 12:50:02 UTC

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New package ChangePointTaylor with initial version 0.3
Package: ChangePointTaylor
Title: Identify Changes in Mean
Version: 0.3
Date: 2024-07-12
Maintainer: Michael Marks <michaelmarks@analyticaconsulting.com>
Description: A basic implementation of the change in mean detection method outlined in: Taylor, Wayne A. (2000) <https://variation.com/wp-content/uploads/change-point-analyzer/change-point-analysis-a-powerful-new-tool-for-detecting-changes.pdf>. The package recursively uses the mean-squared error change point calculation to identify candidate change points. The candidate change points are then re-estimated and Taylor's backwards elimination process is then employed to come up with a final set of change points. Many of the underlying functions are written in C++ for improved performance.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.4), dplyr, purrr, tidyr, magrittr, rlang
LinkingTo: Rcpp
LazyData: true
Suggests: knitr, rmarkdown, ggplot2, bench
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2024-07-12 20:39:00 UTC; mmark
Author: Michael Marks [aut, cre]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-07-14 13:00:02 UTC

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New package BATSS with initial version 0.7.14
Package: BATSS
Title: Bayesian Adaptive Trial Simulator Software (BATSS) for Generalised Linear Models
Version: 0.7.14
Description: Defines operating characteristics of Bayesian Adaptive Trials considering a generalised linear model response via Monte Carlo simulations of Bayesian GLM fitted via integrated Laplace approximations (INLA).
URL: https://batss-dev.github.io/BATSS/
License: GPL-2
Encoding: UTF-8
Suggests: INLA
Imports: parallel, methods, stats, grDevices, abind, plyr, rlang, R.utils, cli
Additional_repositories: https://inla.r-inla-download.org/R/testing
NeedsCompilation: no
Packaged: 2024-07-12 14:50:23 UTC; research
Author: Dominique-Laurent Couturier [aut, cre] , Liz Ryan [aut] , Rainer Puhr [aut], Thomas Jaki [aut] , Stephane Heritier [aut]
Maintainer: Dominique-Laurent Couturier <dominique.couturier@mrc-bsu.cam.ac.uk>
Repository: CRAN
Date/Publication: 2024-07-14 12:40:06 UTC

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New package iPRISM with initial version 0.1.1
Package: iPRISM
Title: Intelligent Predicting Response to Cancer Immunotherapy Through Systematic Modeling
Version: 0.1.1
Maintainer: Junwei Han <hanjunwei1981@163.com>
Description: Immunotherapy has revolutionized cancer treatment, but predicting patient response remains challenging. Here, we presented Intelligent Predicting Response to cancer Immunotherapy through Systematic Modeling (iPRISM), a novel network-based model that integrates multiple data types to predict immunotherapy outcomes. It incorporates gene expression, biological functional network, tumor microenvironment characteristics, immune-related pathways, and clinical data to provide a comprehensive view of factors influencing immunotherapy efficacy. By identifying key genetic and immunological factors, it provides an insight for more personalized treatment strategies and combination therapies to overcome resistance mechanisms.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: ggplot2, Hmisc, tidyr, igraph, pbapply, Matrix, methods
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-07-12 06:27:46 UTC; syc
Author: Junwei Han [aut, cre, ctb], Yinchun Su [aut], Siyuan Li [aut]
Repository: CRAN
Date/Publication: 2024-07-14 12:00:02 UTC

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New package HonestDiD with initial version 0.2.6
Package: HonestDiD
Title: Robust Inference in Difference-in-Differences and Event Study Designs
Version: 0.2.6
Depends: R (>= 3.6.0)
Imports: stats, rlang, foreach (>= 1.4.7), matrixStats (>= 0.63.0), CVXR (>= 0.99-6), latex2exp (>= 0.4.0), lpSolveAPI (>= 5.5.2.0-17), Matrix (>= 1.2-17), pracma (>= 2.2.5), purrr (>= 0.3.4), tibble (>= 1.3.4), dplyr (>= 0.7.4), ggplot2 (>= 2.2.1), Rglpk (>= 0.6-4), mvtnorm (>= 1.1-3), TruncatedNormal (>= 1.0)
Suggests: knitr, testthat, haven, lfe, rmarkdown
Description: Provides functions to conduct robust inference in difference-in-differences and event study designs by implementing the methods developed in Rambachan & Roth (2023) <doi:10.1093/restud/rdad018>, "A More Credible Approach to Parallel Trends" [Previously titled "An Honest Approach..."]. Inference is conducted under a weaker version of the parallel trends assumption. Uniformly valid confidence sets are constructed based upon conditional confidence sets, fixed-length confidence sets and hybridized confidence sets.
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2024-07-12 00:19:14 UTC; asheshr
Author: Ashesh Rambachan [aut, cph, cre], Jonathan Roth [aut, cph]
Maintainer: Ashesh Rambachan <ashesh.a.rambachan@gmail.com>
Repository: CRAN
Date/Publication: 2024-07-14 11:40:02 UTC

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New package hedgedrf with initial version 0.0.1
Package: hedgedrf
Title: An Implementation of the Hedged Random Forest Algorithm
Version: 0.0.1
Description: This algorithm is described in detail in the paper "Hedging Forecast Combinations With an Application to the Random Forest" by Beck et al. (2023) <doi:10.48550/arXiv.2308.15384>. The package provides a function hedgedrf() that can be used to train a Hedged Random Forest model on a dataset, and a function predict.hedgedrf() that can be used to make predictions with the model.
License: GPL-3
Imports: ranger, CVXR
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-07-12 06:41:08 UTC; ubuntu
Author: Elliot Beck [aut, cre]
Maintainer: Elliot Beck <elliot.beck@bf.uzh.ch>
Repository: CRAN
Date/Publication: 2024-07-14 12:00:05 UTC

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New package closeloop with initial version 0.1.0
Package: closeloop
Title: Integrate Single-Arm Observational Data in Network Meta Analysis
Version: 0.1.0
Date: 2024-08-07
Maintainer: Shubhram Pandey <shubhram1992@gmail.com>
Description: Calculate the distance between single-arm observational studies using covariate information to remove heterogeneity in Network Meta-Analysis (NMA) of randomized clinical trials. Facilitate the inclusion of observational data in NMA, enhancing the comprehensiveness and robustness of comparative effectiveness research. Schmitz (2018) <doi:10.1186/s12874-018-0509-7>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: combinat
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/heorlytics/closeloop
NeedsCompilation: no
Packaged: 2024-07-12 12:00:18 UTC; ShubhramPandey
Author: Supreet Kaur [ctb], Akanksha Sharma [ctb], Shubhram Pandey [aut, cre]
Repository: CRAN
Date/Publication: 2024-07-14 12:00:09 UTC

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Package magick updated to version 2.8.4 with previous version 2.8.3 dated 2024-02-18

Title: Advanced Graphics and Image-Processing in R
Description: Bindings to 'ImageMagick': the most comprehensive open-source image processing library available. Supports many common formats (png, jpeg, tiff, pdf, etc) and manipulations (rotate, scale, crop, trim, flip, blur, etc). All operations are vectorized via the Magick++ STL meaning they operate either on a single frame or a series of frames for working with layers, collages, or animation. In RStudio images are automatically previewed when printed to the console, resulting in an interactive editing environment. The latest version of the package includes a native graphics device for creating in-memory graphics or drawing onto images using pixel coordinates.
Author: Jeroen Ooms [aut, cre]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between magick versions 2.8.3 dated 2024-02-18 and 2.8.4 dated 2024-07-14

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Package gets updated to version 0.38 with previous version 0.37 dated 2022-10-09

Title: General-to-Specific (GETS) Modelling and Indicator Saturation Methods
Description: Automated General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting and testing for structural breaks in the mean, see Pretis, Reade and Sucarrat (2018) <doi:10.18637/jss.v086.i03> for an overview of the package. In advanced use, the estimator and diagnostics tests can be fully user-specified, see Sucarrat (2021) <doi:10.32614/RJ-2021-024>.
Author: Genaro Sucarrat [aut, cre], Felix Pretis [aut], James Reade [aut], Jonas Kurle [ctb], Moritz Schwarz [ctb]
Maintainer: Genaro Sucarrat <genaro.sucarrat@bi.no>

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Package QuickJSR updated to version 1.3.1 with previous version 1.3.0 dated 2024-07-08

Title: Interface for the 'QuickJS' Lightweight 'JavaScript' Engine
Description: An 'R' interface to the 'QuickJS' portable 'JavaScript' engine. The engine and all 'R' to 'JavaScript' interoperability is bundled within the package, requiring no dependencies beyond a 'C' compiler.
Author: Andrew R. Johnson [aut, cre] , Fabrice Bellard [cph] , Charlie Gordon [cph] , QuickJS-NG Authors [cph]
Maintainer: Andrew R. Johnson <andrew.johnson@arjohnsonau.com>

Diff between QuickJSR versions 1.3.0 dated 2024-07-08 and 1.3.1 dated 2024-07-14

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Package ppendemic updated to version 0.1.8 with previous version 0.1.7 dated 2023-08-15

Title: A Glimpse at the Diversity of Peru's Endemic Plants
Description: Introducing a novel and updated database showcasing Peru's endemic plants. This meticulously compiled and revised botanical collection encompasses a remarkable assemblage of over 7,249 distinct species. The data for this resource was sourced from the work of Govaerts, R., Nic Lughadha, E., Black, N. et al., titled 'The World Checklist of Vascular Plants: A continuously updated resource for exploring global plant diversity', published in Sci Data 8, 215 (2021) <doi:10.1038/s41597-021-00997-6>.
Author: Paul E. Santos Andrade [aut, cre] , Lucely L. Vilca Bustamante [aut]
Maintainer: Paul E. Santos Andrade <paulefrens@gmail.com>

Diff between ppendemic versions 0.1.7 dated 2023-08-15 and 0.1.8 dated 2024-07-14

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Package mirt updated to version 1.42 with previous version 1.41 dated 2023-10-17

Title: Multidimensional Item Response Theory
Description: Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported.
Author: Phil Chalmers [aut, cre] , Joshua Pritikin [ctb], Alexander Robitzsch [ctb], Mateusz Zoltak [ctb], KwonHyun Kim [ctb], Carl F. Falk [ctb], Adam Meade [ctb], Lennart Schneider [ctb], David King [ctb], Chen-Wei Liu [ctb], Ogreden Oguzhan [ctb]
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>

Diff between mirt versions 1.41 dated 2023-10-17 and 1.42 dated 2024-07-14

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