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Reproducible source for the Elaphrocentre paper

Copyright (C) 2018-2020 Mohammad Akhlaghi <mohammad@akhlaghi.org>
Copyright (C) 2020-2021 Marius Peper, Boud Roukema
See the end of the file for license conditions.

This is the reproducible project source for the research paper "The role of
the elaphrocentre in void galaxy formation"", by Marius Peper and Boudewijn
Roukema, submitted for peer review.

To reproduce the results and final paper, the only dependency is a minimal
Unix-like building environment including a C compiler (already available
on your system if you have ever built and installed software from source)
and a downloader (Wget or cURL).  **Git is not mandatory**: if you
don't have Git to run the first command below, go to the URL given in the
command on your browser, and download the project's source (there is a
button to download a compressed tarball of the project). If you have
received this source from arXiv, please see the respective section below.
If you have received this source from [ArXiv:2010.03742][arXiv] or
[Zenodo.4062461][Zenodo] (without any `.git` directory inside),
or [SoftwareHeritage][SoftwareHeritage], please see the
"Building project tarball" section below.

$ git clone https://codeberg.org/boud/elaphrocentre.git
$ cd elaphrocentre
$ ./project configure
$ ./project make

[arXiv]: https://arXiv.org/abs/2010.03742
[Zenodo]: https://doi.org/10.5281/zenodo.4062461
[SoftwareHeritage]: https://archive.softwareheritage.org/swh:1:dir:c4770e81288f340083dd8aa9fe017103c4eaf476

The 'configure' (download/compile/install) component of 'elaphrocentre'
will take about 2-3 hours on 4 cores at 2.0-2.5 GHz and about 5 GB of
disk space in the .build/software/ directory.

The time, disk and cpu resources requirements of the 'analysis'
(calculate/analyse/plot) component of 'elaphrocentre' strongly depend on
the particle resolution (Ncroot); time and cpu usage also depend on
levelmax, which is effectively the softening length. Ncroot is not
a direct constraint on RAMSES memory requirements: these are hardwired
to the values of ngridtot and nparttot; you may decrease these to
reduce the memory requirements - RAMSES will normally give a fatal
error and explain that insufficient memory has been allocated if
that is the case.

The following four calculation time estimates assume that you set
'compare_centres = NO' in
'reproduce/analysis/config/analyse-plot-params.conf'. This will remove
calculations that generate Table 4 of version 2 of our paper, and will
remove the corresponding, final paragraph of Section 4.2 from the
paper. For maximising the simplicity of automated reproducibility, we
intend to keep 'compare_centres = YES' in the second version of this paper
in Zenodo. The YES option will give much longer calculation times than
those below.

We recommend setting 'compare_centres = NO', although the (modest)
scientific cost will be the omission of a small part of version 2 of the
paper (see previous paragraph).

* A 32^3 particle simulation will be rather fast and is recommended for
development and debugging. Many numerical results will be poor. Using 4
cores at 2.0-2.5 GHz, a full 32^3 particle run (levelmax=10) and its
followup analysis will take about 15 minutes of wall time, a maximum of
about 160 Mb of RAM and roughly 2 Gb for .build/n-body-init/ (altogether
about 7 Gb of disk space, when the 5 Gb for .build/software/ are included).

* A 64^3 run, using 4 cores again, will take roughly 25 minutes, up to
1.6 Gb of RAM and 19 Gb of disk space for .build/n-body-init/, and 1.5 Gb
for .build/haloes/, making about 26 Gb altogether.

* Using the parameters of our standard calculation, i.e. a 128^3 particle
run and levelmax=12, will take, using 4 cores, roughly 8 hours, 14.8 Gb of RAM,
about 145 Gb of disk space for .build/n-body-init/, 12 Gb for .build/haloes/,
for a total of about 162 Gb of disk space.

* Do not try running the current version for a 256^3 particle run. The
later steps in the pipeline are not parallelised, and a 20-core calculation
would take you about four weeks.

To learn more about the purpose, principles and technicalities of `maneage`
format reproducible papers, please see `README-hacking.md`, or the
Maneage webpage at https://maneage.org . For a general
introduction to reproducible science as implemented in this project, please
see the [principles of reproducible
science](http://akhlaghi.org/reproducible-science.html), and a
[reproducible paper
template](https://gitlab.com/makhlaghi/reproducible-paper) that is based on

### Building the project

This project was designed to have as few dependencies as possible without
requiring root/administrator permissions.

1. Necessary dependencies:

   1.1: Minimal software building tools like C compiler, Make, and other
        tools found on any Unix-like operating system (GNU/Linux, BSD, Mac
        OS, and others). All necessary dependencies will be built from
        source (for use only within this project) by the `./project
        configure` script (next step).

   1.2: (OPTIONAL) Tarball of dependencies. If they are already present (in
        a directory given at configuration time), they will be
        used. Otherwise, a downloader (`wget` or `curl`) will be necessary
        to download any necessary tarball. The necessary tarballs are also
        collected in the archived project at
        [https://doi.org/10.5281/zenodo.4062461](4062461). Unpack the
        tarball and you should see most of the tarballs of this project's
        software (Maneage is a project that is still under development;
        some of the less critical software may not yet be included).
        When `./project configure` asks for the "software tarball
        directory", give the address of the unpacked directory that has all
        the tarballs.

        Software Heritage: https://... [software heritage link]

2. Configure the environment (top-level directories in
   particular) and build all the necessary software for use in
   the next step. It is recommended to set directories that are
   *outside* the current directory. For example, create your
   build (temporary) directory outside the current directory and
   store the full name of that directory (with its full path).

   Please read the description of each necessary input clearly
   and set the best value. The configure script downloads, builds
   and locally installs many programs (project dependencies),
   specifically for this particular project. Please do this
   *without* root privileges. As of September 2020 on a typical
   desktop or laptop computer, this may take a few hours (see
   the estimates for the time and hardware usage above).

     $ ./project configure

   If there is an interruption and you wish to continue or seek help,

    $ ./project configure --existing-conf

   to continue or

    $ ./project --help

   for help.
   We recommend creating log files for the main commands. The command

   (./project configure <options> 2>&1) | tee yyyymmdd<logname>

   will create a log file called yyyymmdd<logname> (where <logname> is
   whatever label you choose) and also print all lines (standard output and
   standard error) to the terminal.  We recommend the equivalent syntax for
   the commands described in the following steps to again create log
   files. Creating logs will be very helpful in tracing bugs, and
   in helping other people to help you to trace bugs. The most powerful
   command for searching through long log files is probably `grep`.
   Try `man grep` or `info grep` or `grep --help` for help on `grep`.

2a. Optionally, as an alternative to the `configure` step in 2, you can
    instead add a parallelisation option:

    $ ./project configure -j4


    $ ./project configure --existing-conf -j4

   The option -j4 is optional, meaning that you choose to build your
   "high-level" software with `4` parallel threads. If your CPU has a
   different number of threads, choose the number that you wish to use (you
   can see the number of threads available on your operating system by
   running `./.local/bin/nproc`).

3.  Run the following command to run the simulations and other galaxy
    pipeline steps:

     $ ./project make full-pipeline

    For help on redoing or removing individual steps:

     $ ./project --help-pipeline

    You will find information on these steps, most of which should be
    run chronologically; 'full-pipeline' should run all of these steps.
    See the paper for explanations.
    ./project make init-conditions        Run the initial conditions.
    ./project make run-simulation         Run the simulations (not run automatically).
    ./project make detect-haloes          Detect dark matter haloes.
    ./project make create-mergertree      Create a merger history tree.
    ./project make create-galaxies        Create galaxies from SFR histories.
    ./project make detect-voids           Detect voids in dark matter distribution.
    ./project make analyse-plot           Analyse and plot.

4. Run the following command to create the pdf file:

     $ ./project make

### Overall directory structure

    The main front-end script is `project`, which calls
    `reproduce/software/shell/configure.sh` and 'configures'
    (does the download, configure, compile, install cycle) if necessary.

    The download, configure, compile, install cycle is coded
    in the `reproduce/software/` directory tree, with, in particular,
    `reproduce/software/make/` - makefiles
    `reproduce/software/config/` - software configure files.

    The calculate, analyse, plot, verify, LaTeX steps are coded
    in the `reproduce/analysis/` directory tree, with, in particular,
    `reproduce/analysis/make/` - makefiles
    `reproduce/analysis/config/` - cosmological configure files.

### Building project tarball (possibly from arXiv)

If the paper is also published on arXiv, it is highly likely that the
authors also uploaded/published the full project there along with the LaTeX
sources. If you have downloaded (or plan to download) this source from
arXiv, some minor extra steps are necessary as listed below. This is
because this tarball is mainly tailored to automatic creation of the final
PDF without using Maneage (only calling LaTeX, not using the './project'

You can directly run 'latex' on this directory and the paper will be built
with no analysis (all necessary built products are already included in the
tarball). One important feature of the tarball is that it has an extra
`Makefile` to allow easy building of the PDF paper without worring about
the exact LaTeX and bibliography software commands.

#### Only building PDF using tarball (no analysis)

1. If you got the tarball from arXiv and the arXiv code for the paper is
   1234.56789, then the downloaded source will be called `1234.56789` (no
   suffix). However, it is actually a `.tar.gz` file. So take these steps
   to unpack it to see its contents.

     $ arxiv=1234.56789
     $ mv $arxiv $arxiv.tar.gz
     $ mkdir $arxiv
     $ cd $arxiv
     $ tar xf ../$arxiv.tar.gz

2. No matter how you got the tarball, if you just want to build the PDF
   paper, simply run the command below. Note that this won't actually
   install any software or do any analysis, it will just use your host
   operating system (assuming you already have a LaTeX installation and all
   the necessary LaTeX packages) to build the PDF using the already-present
   plots data.

   $ make              # Build PDF in tarball without doing analysis

3. If you want to re-build the figures from scratch, you need to make the
   following corrections to the paper's main LaTeX source (`paper.tex`):
   uncomment (remove the starting `%`) the line containing
   `\newcommand{\makepdf}{}`, see the comments above it for more.

#### Building full project from tarball (custom software and analysis)

As described above, the tarball is mainly geared to only building the final
PDF. A few small tweaks are necessary to build the full project from
scratch (download necessary software and data, build them and run the
analysis and finally create the final paper).

1. If you got the tarball from arXiv, before following the standard
   procedure of projects described at the top of the file above (using the
   `./project` script), its necessary to set its executable flag because
   arXiv removes the executable flag from the files (for its own security).

     $ chmod +x project

2. Make the following changes in two of the LaTeX files so LaTeX attempts
   to build the figures from scratch (to make the tarball; it was
   configured to avoid building the figures, just using the ones that came
   with the tarball).

   - `paper.tex`: uncomment (remove the starting `%`) of the line
     containing `\newcommand{\makepdf}{}`, see the comments above it for

   - `tex/src/preamble-pgfplots.tex`: set the `tikzsetexternalprefix`
     variable value to `tikz/`, so it looks like this:

3. Remove extra files. In order to make sure arXiv can build the paper
   (resolve conflicts due to different versions of LaTeX packages), it is
   sometimes necessary to copy raw LaTeX package files in the tarball
   uploaded to arXiv. Later, we will implement a feature to automatically
   delete these extra files, but for now, the project's top directory
   should only have the following contents (where `reproduce` and `tex` are
   directories). You can safely remove any other file/directory.

     $ ls
     COPYING  paper.tex  project  README-hacking.md  README.md  reproduce/  tex/

### Building in Docker containers

Docker containers are a common way to build projects in an independent
filesystem, and an almost independent operating system. Containers thus
allow using GNU/Linux operating systems within proprietary operating
systems like macOS or Windows. But without the overhead and huge file size
of virtual machines. Furthermore containers allow easy movement of built
projects from one system to another without rebuilding. Just note that
Docker images are large binary files (+1 Gigabytes) and may not be usable
in the future (for example with new Docker versions not reading old
images). Containers are thus good for temporary/testing phases of a
project, but shouldn't be what you archive for the long term!

Hence if you want to save and move your maneaged project within a Docker
image, be sure to commit all your project's source files and push them to
your external Git repository (you can do these within the Docker image as
explained below). This way, you can always recreate the container with
future technologies too. Generally, if you are developing within a
container, its good practice to recreate it from scratch every once in a
while, to make sure you haven't forgot to include parts of your work in
your project's version-controlled source. In the sections below we also
describe how you can use the container **only for the software
environment** and keep your data and project source on your host.

#### Dockerfile for a Maneaged project, and building a Docker image

Below is a series of recommendations on the various components of a
`Dockerfile` optimized to store the *built state of a maneaged project* as
a Docker image. Each component is also accompanied with
explanations. Simply copy the code blocks under each item into a plain-text
file called `Dockerfile`, in the same order of the items. Don't forget to
implement the suggested corrections (in particular step 4).

**NOTE: Internet for TeXLive installation:** If you have the project
software tarballs and input data (optional features described below) you
can disable internet. In this situation, the configuration and analysis
will be exactly reproduced, the final LaTeX macros will be created, and all
results will be verified successfully. However, no final `paper.pdf` will
be created to visualize/combine everything in one easy-to-read file. Until
[task 15267](https://savannah.nongnu.org/task/?15267) is complete, we need
internet to install TeXLive packages (using TeXLive's own package manager
`tlmgr`) in the `./project configure` phase. This won't stop the
configuration, and it will finish successfully (since all the analysis can
still be reproduced). We are working on completing this task as soon as
possible, but until then, if you want to disable internet *and* you want to
build the final PDF, please disable internet after the configuration
phase. Note that only the necessary TeXLive packages are installed (~350
MB), not the full TeXLive collection!

 0. **Summary:** If you are already familiar with Docker, then the full
    Dockerfile to get the project environment setup is shown here (without
    any comments or explanations, because explanations are done in the next
    items). Note that the last two `COPY` lines (to copy the directory
    containing software tarballs used by the project and the possible input
    databases) are optional because they will be downloaded if not
    available. You can also avoid copying over all, and simply mount your
    host directories within the image, we have a separate section on doing
    this below ("Only software environment in the Docker image"). Once you
    build the Docker image, your project's environment is setup and you can
    go into it to run `./project make` manually.

    FROM debian:stable-slim
    RUN apt-get update && apt-get install -y gcc g++ wget
    RUN useradd -ms /bin/sh maneager
    USER maneager
    WORKDIR /home/maneager
    RUN mkdir build
    RUN mkdir software
    COPY --chown=maneager:maneager ./project-source /home/maneager/source
    COPY --chown=maneager:maneager ./software-dir   /home/maneager/software
    COPY --chown=maneager:maneager ./data-dir       /home/maneager/data
    RUN cd /home/maneager/source \
        && ./project configure --build-dir=/home/maneager/build \
                               --software-dir=/home/maneager/software \

 1. **Choose the base operating system:** The first step is to select the
    operating system that will be used in the docker image. Note that your
    choice of operating system also determines the commands of the next
    step to install core software.

    FROM debian:stable-slim

 2. **Maneage dependencies:** By default the "slim" versions of the
    operating systems don't contain a compiler (needed by Maneage to
    compile precise versions of all the tools). You thus need to use the
    selected operating system's package manager to import them (below is
    the command for Debian). Optionally, if you don't have the project's
    software tarballs, and want the project to download them automatically,
    you also need a downloader.

    # C and C++ compiler.
    RUN apt-get update && apt-get install -y gcc g++

    # Uncomment this if you don't have 'software-XXXXXXX.tar.gz' (below).
    #RUN apt-get install -y wget

 3. **Define a user:** Some core software packages will complain if you try
    to install them as the default (root) user. Generally, it is also good
    practice to avoid being the root user. After building the Docker image,
    you can always run it as root with this command: `docker run -u 0 -it
    XXXXXXX` (where `XXXXXXX` is the image identifier). Hence with the
    commands below we define a `maneager` user and activate it for the next

    RUN useradd -ms /bin/sh maneager
    USER maneager
    WORKDIR /home/maneager

 4. **Copy project files into the container:** these commands make the
    assumptions listed below. IMPORTANT: you can also avoid copying over
    all, and simply mount your host directories within the image, we have a
    separate section on doing this below ("Only software environment in the
    Docker image").

    * The project's source is in the `maneaged/` sub-directory and this
      directory is in the same directory as the `Dockerfile`. The source
      can either be from cloned from Git (highly recommended!) or from a
      tarball. Both are described above (note that arXiv's tarball needs to
      be corrected as mentioned above).

    * (OPTIONAL) By default the project's necessary software source
      tarballs will be downloaded when necessary during the `./project
      configure` phase. But if you already have the sources, its better to
      use them and not waste network traffic (and resulting carbon
      footprint!). Maneaged projects usually come with a
      `software-XXXXXXX.tar.gz` file that is published on Zenodo (link above).
      If you have this file, put it in the same directory as your
      `Dockerfile` and include the relevant lines below.

    * (OPTIONAL) The project's input data. The `INPUT-FILES` depends on the
      project, please look into the project's
      `reproduce/analysis/config/INPUTS.conf` for the URLs and the file
      names of input data. Similar to the software source files mentioned
      above, if you don't have them, the project will attempt to download
      its necessary data automatically in the `./project make` phase.

    # Make the project's build directory and copy the project source
    RUN mkdir build
    COPY --chown=maneager:maneager ./maneaged /home/maneager/source

    # Optional (for software)
    COPY --chown=maneager:maneager ./software-XXXXXXX.tar.gz /home/maneager/
    RUN tar xf software-XXXXXXX.tar.gz && mv software-XXXXXXX software && rm software-XXXXXXX.tar.gz

    # Optional (for data)
    RUN mkdir data
    COPY --chown=maneager:maneager ./INPUT-FILES /home/maneager/data

 5. **Configure the project:** With this line, the Docker image will
    configure the project (build all its necessary software). This will
    usually take about an hour on an 8-core system. You can also optionally
    avoid putting this step (and the next) in the `Dockerfile` and simply
    execute them in the Docker image in interactive mode (as explained in
    the sub-section below, in this case don't forget to preserve the build
    container after you are done).

    # Configure project (build full software environment).
    RUN cd /home/maneager/source \
           && ./project configure --build-dir=/home/maneager/build \
                                  --software-dir=/home/maneager/software \

 6. **Project's analysis:** With this line, the Docker image will do the
    project's analysis and produce the final `paper.pdf`. The time it takes
    for this step to finish, and the storage/memory requirements highly
    depend on the particular project.

    # Run the project's analysis
    RUN cd /home/maneager/source && ./project make

 7. **Build the Docker image:** The `Dockerfile` is now ready! In the
    terminal, go to its directory and run the command below to build the
    Docker image. We recommend to keep the `Dockerfile` in **an empty
    directory** and run it from inside that directory too. This is because
    Docker considers that directories contents to be part of the
    environment. Finally, just set a `NAME` for your project and note that
    Docker only runs as root.

    sudo su
    docker build -t NAME ./

#### Interactive tests on built container

If you later want to start a container with the built image and enter it in
interactive mode (for example for temporary tests), please run the
following command. Just replace `NAME` with the same name you specified
when building the project. You can always exit the container with the
`exit` command (note that all your changes will be discarded once you exit,
see below if you want to preserve your changes after you exit).

docker run -it NAME

#### Running your own project's shell for same analysis environment

The default operating system only has minimal features: not having many of
the tools you are accustomed to in your daily command-line operations. But
your maneaged project has a very complete (for the project!) environment
which is fully built and ready to use interactively with the commands
below. For example the project also builds Git within itself, as well as
many other high-level tools that are used in your project and aren't
present in the container's operating system.

# Once you are in the docker container
cd source
./project shell

#### Preserving the state of a built container

All interactive changes in a container will be deleted as soon as you exit
it. THIS IS A VERY GOOD FEATURE IN GENERAL! If you want to make persistent
changes, you should do it in the project's plain-text source and commit
them into your project's online Git repository. As described in the Docker
introduction above, we strongly recommend to **not rely on a built container
for archival purposes**.

But for temporary tests it is sometimes good to preserve the state of an
interactive container. To do this, you need to `commit` the container (and
thus save it as a Docker "image"). To do this, while the container is still
running, open another terminal and run these commands:

# These two commands should be done in another terminal
docker container list

# Get 'XXXXXXX' of your desired container from the first column above.
# Give the new image a name by replacing 'NEW-IMAGE-NAME'.

#### Copying files from the Docker image to host operating system

The Docker environment's file system is completely indepenent of your host
operating system. One easy way to copy files to and from an open container
is to use the `docker cp` command (very similar to the shell's `cp`

docker cp CONTAINER:/file/path/within/container /host/path/target

#### Only software environment in the Docker image

You can set the docker image to only contain the software environment and
keep the project source and built analysis files (data and PDF) on your
host operating system. This enables you to keep the size of the Docker
image to a minimum (only containing the built software environment) to
easily move it from one computer to another. Below we'll summarize the

1. Get your user ID with this command: `id -u`.

2. Put the following lines into a `Dockerfile` of an otherwise empty
directory. Just replacing `UID` with your user ID (found in the step
above). This will build the basic directory structure. for the next steps.

FROM debian:stable-slim
RUN apt-get update && apt-get install -y gcc g++ wget
RUN useradd -ms /bin/sh --uid UID maneager
USER maneager
WORKDIR /home/maneager
RUN mkdir build

3. Create an image based on the `Dockerfile` above. Just replace `PROJECT`
with your desired name.

docker build -t PROJECT ./

4. Run the command below to create a container based on the image and mount
the desired directories on your host into the special directories of your
container. Just don't forget to replace `PROJECT` and set the `/PATH`s to
the respective paths in your host operating system.

docker run -v /PATH/TO/PROJECT/SOURCE:/home/maneager/source \
           -v /PATH/TO/PROJECT/ANALYSIS/OUTPUTS:/home/maneager/build/analysis \
           -v /PATH/TO/SOFTWARE/SOURCE/CODE/DIR:/home/maneager/software \
           -v /PATH/TO/RAW/INPUT/DATA:/home/maneager/data \
           -it PROJECT

5. After running the command above, you are within the container. Go into
the project source directory and run these commands to build the software

cd /home/maneager/source
./project configure --build-dir=/home/maneager/build \
                    --software-dir=/home/maneager/software \

6. After the configuration finishes successfully, it will say so and ask
you to run `./project make`. But don't do that yet. Keep this Docker
container open and don't exit the container or terminal. Open a new
terminal, and follow the steps described in the sub-section above to
preserve the built container as a Docker image. Let's assume you call it
`PROJECT-ENV`. After the new image is made, you should be able to see the
new image in the list of images with this command (in the same terminal
that you created the image):

docker image list      # In the other terminal.

7. Now you can run `./project make` in the initial container. You will see
that all the built products (temporary or final datasets or PDFs), will be
written in the `/PATH/TO/PROJECT/ANALYSIS/OUTPUTS` directory of your
host. You can even change the source of your project on your host operating
system an re-run Make to see the effect on the outputs and add/commit the
changes to your Git history within your host. You can also exit the
container any time. You can later load the `PROJECT-ENV` environment image
into a new container with the same `docker run -v ...` command above, just
use `PROJECT-ENV` instead of `PROJECT`.

8. In case you want to store the image as a single file as backup or to
move to another computer, you can run the commands below. They will produce
a single `project-env.tar.gz` file.

docker save -o project-env.tar PROJECT-ENV
gzip --best project-env.tar

9. To load the tarball above into a clean docker environment (either on the
same system or in another system), and create a new container from the
image like above (the `docker run -v ...` command). Just don't forget that
if your `/PATH/TO/PROJECT/ANALYSIS/OUTPUTS` directory is empty on the
new/clean system, you should first run `./project configure -e` in the
docker image so it builds the core file structure there. Don't worry, it
won't build any software and should finish in a second or two. Afterwards,
you can safely run `./project make`.

docker load --input project-env.tar.gz

#### Deleting all Docker images

After doing your tests/work, you may no longer need the multi-gigabyte
files images, so its best to just delete them. To do this, just run the two
commands below to first stop all running containers and then to delete all
the images:

docker ps -a -q | xargs docker rm
docker images -a -q | xargs docker rmi -f

### Copyright information

This file and `.file-metadata` (a binary file, used by Metastore to store
file dates when doing Git checkouts) are part of the reproducible project
mentioned above and share the same copyright notice (at the start of this
file) and license notice (below).

This project is free software: you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the Free
Software Foundation, either version 3 of the License, or (at your option)
any later version.

This project is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
more details.

You should have received a copy of the GNU General Public License along
with this project.  If not, see <https://www.gnu.org/licenses/>.
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