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20.05 The parameter use_custom_knapsack_weights and its associated functionality have been removed. (#877) We've changed how the runtime parameters are stored. Previously they were static members of their respective class, but this prevented their use in lambda-capture functions on GPUs. Now the runtime parameters are grouped into namespaces as extern managed data. (#873) We currently have a scheme for storing reactions weightings, which are a measure of the number of RHS evaluations during the burn and therefore a proxy for the difficulty of the burn. These weights were added as separate StateData depending on the runtime option use_custom_knapsack_weights. Now, instead we place the weights directly in the Reactions_Type StateData as a new component. The number of ghost zones in Reactions_Type is increased to 4. The checkpoint version has now been incremented; this version of the code will not be able to restart from a checkpoint generated by earlier versions of the code. (#863) The meaning of dt_cutoff has changed: it is now the fraction of the current simulation time which dt may be no smaller than, instead of being an absolute measure. We now have set a non-zero default (1.e-12) as well. (#865) Backwards compatibility in restarting from a checkpoint is no longer supported. Checkpoints from older versions of the code (as determined by the checkpoint version in the CastroHeader file in the checkpoint directory) cannot be restarted from. (#860) Added an option to do CTU reactions in C++. A compile flag USE_CXX_REACTIONS is added which switches to the C++ integrator in Microphysics. Since we will be doing a phased implementation of the networks in Microphysics, this is opt-in for now. (#836) More of the core routines have been ported to C++, including the hydro and diffusion timestep estimators (#853) and the sponge (#857) AMReX provides CpuBndryFuncFab and GpuBndryFuncFab which are very similar to what generic_fill and hypfill did. The AMReX implementations are now used. We still have a hypfill and denfill function, so that existing problems are not broken, but the main one in Source/ no longer calls amrex_filcc (it only has the ambient code now). The problems that do override bc_fill_nd.F90 are thus no longer required to call amrex_filcc. (#837) We now always issue a timestep retry if the density after an advance is negative (or less than small_dens). The parameter castro.retry_neg_dens_factor is removed. The parameter castro.retry_tolerance is also removed as it no longer has any effect. (#796) The timestep control parameter castro.change_max now also will prevent the timestep by shrinking too much in one timestep (previously it would only prevent it from growing too much). If change_max is violated in a timestep we will do a retry to take more graceful steps. (#844) We now check if the problem setup initialized the density or temperature to a value near small_dens or small_temp and abort. If this happens, the recourse is to adjust small_dens and small_temp to a meaningful value for your problem. (#822) The src_q multifab was removed and instead we convert the conserved state sources to primitive state sources FAB by FAB. This saves a lot of memory at the expense of an EOS call. (#829) The plm_well_balanced option was removed. It was essentially the same as use_pslope except it was lower order and only worked with constant gravity. use_pslope now works with both CTU+PLM and SDC2+PLM. A new test problem, hse_convergence, was added to look at the behavior of the different reconstruction methods with HSE.

PyFOSC is a pipeline toolbox for spectroscopic data reduction written in Python. It can be used for FOSC data from Xinglong/Lijiang 2-meter telescopes. BFOSC (Beijing-Faint Object Spectrograph and Camera) is an instrument of the 2.16-m Telescope in Xinglong Observatory, National Astronomical Observatories, Chinese Academy of Sciences (NAOC) (IAU code: 327, coordinates: 40°23′39″ N, 117°34′30″ E). For more information about BFOSC, please see http://www.xinglong-naoc.org/html/en/gcyq/216/detail-18.html. YFOSC (Yunnan-Faint Object Spectrograph and Camera) is an instrument of the 2.4-m Telescope in Lijiang Observatory, Yunnan Observatories, Chinese Academy of Sciences (YNAO) (IAU code: O44, coordinates: 26°42′33.1″ N, 100°1′51.6″ E). For more information about YFOSC, please see http://wiki.gmg.org.cn/pages/viewpage.action?pageId=557106. This software uses BSD 3-Clause License. Copyright (c) 2019, Yuming Fu All rights reserved. This software contains sources from third-party softwares. The pyfosc$iraf_data/onedstds directory is from IRAF, and it contains standard calibration data for extinction and sensitivity calibration. The pyfosc$iraf_task/lacos_im.cl script is the IRAF version for Laplacian Cosmic Ray Identification by Pieter G. van Dokkum (Yale) from http://www.astro.yale.edu/dokkum/lacosmic/. L.A.Cosmic is an algorithm for robust cosmic ray identification. It detects cosmic rays of arbitrary shapes and sizes, and distinguishes between undersampled point sources and cosmic rays. If you use this program please refer to P. G. van Dokkum, 2001, PASP, 113, 1420. Please see COPYRIGHT file and pyfosc$doc/LICENSES directory for detailed copyright information.

identifying long range chromosomal contacts in Hi-C data. Scripts for prediction of long-range interactions between regions/domains based on Hi-C maps. Establish contact!. HiCEnterprise takes a list of regions/domains and searches for their significant interactions on given Hi-C maps. Package consists of two types of analyses: regions and domains. HiCEnterprise is a software tool for identification of long-range chromatin contacts based on the Hi-C experiments.

Reproduction pipeline and necessary data for Sections 7.3 and 3.4 of Bacon et al., (2017) and Inami et al., (2017) respectively (papers I and II of the series of papers on "The MUSE Hubble Ultra Deep Field Survey", published in Astronomy & Astrophysics, 608, A1 and A2). This pipeline will estimate the Hubble Space Telescope (HST) segmentation maps (for paper 1) and make the necessary measurements (for paper 2) for objects that were detected in the MUSE 3D cubes, but didn't correspond to any detection in the Rafelski et al. (2015) catalog. This repository on Zenodo contains all the necessary input data, software and reproduction pipeline (containing the scripts, configuration files and settings to exactly reproduce the results in Sections 7.3 and 3.4 of the papers above). Below is a description of the contents: gnuastro-0.2.51-bc64-bugfix.tar.gz: Gnuastro version 0.2.51 with a small bug fix only relevant to this analysis. The base Gnuastro 0.2.51 was used for this pipeline when it was written, similar to zenodo.1163746. However, a bug relating to estimation of upper-limit magnitudes was later found. This bug was fixed, but along with many other changes that made the whole Gnuastro package incompatible with this pipeline. Hence, this bug-fixed copy of Gnuastro 0.2.51 was used in the catalog of Inami et al. (2017). The reproduction pipeline below contains the fixed file and instructions on how to make this version from version 0.2.51 that is available in the official Gnuastro version controlled history. The library dependencies of this version of Gnuastro can be downloaded from zenodo.1163746 (gnuastro-dependencies.tar.gz). IMPORTANT NOTE: Since version 0.2.51 of Gnuastro was released, CFITSIO (one of Gnuastro's dependencies) has added a dependency for the cURL library (to read https URLs). Therefore, to install Gnuastro 0.2.51, please install CFITSIO version 3.41 or earlier. hst-uvudf.tar.gz: images and weight maps in 0.06 arcsec/pixel resolution from the HST-UVUDF survey. These images are not necessary to run the reproduction pipeline (they will be downloaded from the HST archives if not present). They are stored here for the self-sufficiency of this repository and faster download: in this lossless compressed format, they are roughly 1/4th the volume of the same files in HST archives. hst-xdf.tar.gz: images and weight maps in 0.06 arcsec/pixel resolution from the HST-XDF survey. These are also available from the HST archives and are kept here with similar reasons to above (with a compression ratio of almost 1/3rd). output-v4-2-gf97e.tar.gz: output of the reproduction pipeline. reproduce-v4-2-gf97e.tar.gz: The reproduction pipeline (version 4-2-gf97e) that produces the results (tables) plotted in the paper. The full Git version controlled history of this repository is available on git-cral.univ-lyon1.fr or gitlab.com. We recommend cloning from the Git repository if it is available. This tarball is kept here in case those servers don't work or Git is no longer in common use. Please see the README file in this repository for instructions on how to run the reproduction pipeline and exactly reproduce the results. This pipeline will download all the necessary data if they aren't already present on the system (it is probably just necessary to install the required version of Gnuastro). The Creative Commons Attribution-NonCommercial 4.0 copyright mentioned in the Zenodo webpage is only applicable to files that don't have an explicit copyright within them. The copyright of other files (mainly scripts and software) is mentioned within them (all are free licenses). For any issues with the pipeline/processing, please contact Mohammad Akhlaghi. {"references": ["Illingworth et al. (2013), Astrophysical Journal Supplement, Volume 209, Issue 1, article id. 6", "Rafelski et al. (2015), Astronomical Journal, Volume 150, Issue 1, article id. 31"]}

SAMRI (Small Animal Magnetic Resonance Imaging) - pronounced "Sam-rye" - provides fMRI preprocessing, metadata parsing, and data analysis functions and pipelines. SAMRI integrates functionalities from a number of other packages (listed under the dependencies section below) to create higher-level tools. The resulting interfaces aim to maximize reproducibility, simplify batch processing, and minimize the number of function calls required to generate figures and statistical summaries from the raw data. The package is compatible with small rodent data acquired via Bruker systems.

Tool for intersection and visualization of multiple gene or genomic region sets. Intervene contains three modules: venn to generate Venn diagrams of up to six sets, upset to generate UpSet plots of multiple sets, and pairwise to compute and visualize intersections of multiple sets as clustered heat maps.

macroMS is a image-guided analysis of random objects by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Fiji plugins for qualitative image annotations + analysis workflows This Zenodo entity contains - the supplementary figures to the published article (see reference below) - an archived of the releases (.zip) from the GitHub repository To install the plugins, just activate the Qualitative Annotations update site in Fiji. The latest version of the workflows are available on the GitHub repository or on the KNIME Hub. See the GitHub repository for the documentation or the YouTube tutorials. Zip releases The zip file of the releases contains: - the source code for the Fiji plugins as py files - the KNIME analysis workflows Citation Thomas LSV, Schaefer F and Gehrig J. Fiji plugins for qualitative image annotations: routine analysis and application to image classification [version 1; peer review: awaiting peer review]. F1000Research 2020, 9:1248 (https://doi.org/10.12688/f1000research.26872.1) Version history - v1.0.2bis : Add suppl Figures (pptx) - v1.0.1bis: initial zenodo release with DOI (same as 1.0.1, just newly release to get a DOI) - v1.0.1: initial GitHub release (not archived on Zenodo). A preconfigured Fiji installation is attached to this release on GitHub