Summary: GPS coordinates for survey sites in Sitka Sound and Torch Bay, Alaska from 2003 to 2019 (High Latitude Kelp Dynamics project) For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/852763

Summary: This dataset is part of a suite of studies conducted in Southeast Alaska to determine how benthic communities respond to variable environmental conditions. In an effort to determine how temperature and carbonate chemistry combine to affect primary consumer bioenergetics and research the indirect effects of ocean acidification and warming on primary consumers, the sea urchin population was investigated. The frequency of occurrence and test diameter was recorded for sea urchins at Sitka Sound and Torch Bay, Alaska from 1988 to 2019. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/842621

Summary: This dataset is part of a suite of studies conducted in Southeast Alaska to determine how kelp communities respond to variable environmental conditions arising from seasonal variability as well as changing ocean temperature and acidification conditions. The benthic communities in Sitka Sound and Torch Bay, Alaska were investigated at 19 sites from 1988 through 2019. Twenty quadrats were placed at random locations along a transect line, then benthic species were counted or the percent cover of the species was estimated in each quadrat. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/842632

Summary:

This is the dataset (ver. 2017.02.13) for the manuscript "Soil fluxes of carbonyl sulfide (COS), carbon monoxide, and carbon dioxide in a boreal forest in southern Finland" submitted to the journal Atmospheric Chemistry and Physics.

Summary:

MATLAB and Fortran Implementations of ETD and IMEX spectral deferred correction schemes as well as ETDRK4. Code also contains files to reproduce numerical experiments from Buvoli T. "A Class of Exponential Integrators based on Spectral Deferred Correction", 2014.

Summary:

https://pillow.readthedocs.io/en/stable/releasenotes/9.2.0.html

Changes

• Fixed null check for fribidi_version_info in FriBiDi shim #6376 [@nulano]
• Added GIF decompression bomb check #6402 [@radarhere]
• Handle PCF fonts files with less than 256 characters #6386 [@dawidcrivelli]
• Improved GIF optimize condition #6378 [@raygard]
• Reverted to array_interface with the release of NumPy 1.23 #6394 [@radarhere]
• Pad PCX palette to 768 bytes when saving #6391 [@radarhere]
• Fixed bug with rounding pixels to palette colors #6377 [@btrekkie]
• Use gnome-screenshot on Linux if available #6361 [@radarhere]
• Fixed loading L mode BMP RLE8 images #6384 [@radarhere]
• Fixed incorrect operator in ImageCms error #6370 [@LostBenjamin]
• Limit FPX tile size to avoid extending outside image #6368 [@radarhere]
• Added support for decoding plain PPM formats #5242 [@Piolie]
• Added apply_transparency() #6352 [@radarhere]
• Fixed behaviour change from endian fix #6197 [@radarhere]
• Use python3 #6222 [@radarhere]
• Allow remapping P images with RGBA palettes #6350 [@radarhere]
• Revert "Skip test_realloc_overflow unless libtiff 4.0.4 or higher" #6354 [@radarhere]
• [pre-commit.ci] pre-commit autoupdate #6353 [@pre-commit-ci]
• Only import ImageFont in ImageDraw when necessary #6341 [@radarhere]
• Fixed drawing translucent 1px high polygons #6278 [@radarhere]
• Pad COLORMAP to 768 items when saving TIFF #6232 [@radarhere]
• Fix P -> PA conversion #6337 [@RedShy]
• Once exif data is parsed, do not reload unless it changes #6335 [@radarhere]
• Only try to connect discontiguous corners at the end of edges #6303 [@radarhere]
• Improve transparency handling when saving GIF images #6176 [@radarhere]
• Do not update GIF frame position until local image is found #6219 [@radarhere]
• Netscape GIF extension belongs after the global color table #6211 [@radarhere]
• Only write GIF comments at the beginning of the file #6300 [@raygard]
• Separate multiple GIF comment blocks with newlines #6294 [@raygard]
• Always use GIF89a for comments #6292 [@raygard]
• Ignore compression value from BMP info dictionary when saving as TIFF #6231 [@radarhere]
• If font is file-like object, do not re-read from object to get variant #6234 [@radarhere]
• Raise ValueError when trying to access internal fp after close #6213 [@radarhere]
• Support more affine expression forms in im.point() #6254 [@benrg]
• Include 'twine check' in 'make sdist' #6305 [@hugovk]
• Ensure that furthest v is set in quantize2 #6256 [@radarhere]

Dependencies

• Updated harfbuzz to 4.4.1 #6401 [@radarhere]
• Updated harfbuzz to 4.4.0 #6397 [@radarhere]
• Use SourceForge auto mirror capability #6345 [@raygard]
• Updated libtiff to 4.4.0 #6339 [@radarhere]
• Updated harfbuzz to 4.3.0 #6315 [@radarhere]

Deprecations

• Deprecate ImageFont.getsize and related functions #6381 [@nulano]

Documentation

• Install furo if it is not available #6408 [@radarhere]
• Added release notes for #6402 #6403 [@radarhere]
• Docs: remove redundant search page from table of contents #6399 [@hugovk]
• Added pytest-timeout to test dependencies #6301 [@radarhere]
• Fix Sphinx 5 warning by setting docs language #6347 [@hugovk]
• Include #6178 in release notes #6346 [@radarhere]
• Updated macOS tested Pillow versions #6316 [@radarhere]
• Add Sphinx Lint to pre-commit and fix RST bug #6340 [@hugovk]
• Added EMF and SUN to list of supported file formats #6338 [@radarhere]
• Once a GIF comment is loaded, it is kept for subsequent frames #6325 [@radarhere]
• Link to GitHub discussions in CONTRIBUTING #6333 [@radarhere]
• Improved image file formats documentation #6313 [@radarhere]

Testing

• Add Sphinx Lint to pre-commit and fix RST bug #6340 [@hugovk]
• pre-commit autoupdate #6223 [@radarhere]
• Upgrade non-amd64 Ubuntu jobs to Jammy #6306 [@radarhere]

Summary:

On 27 February 2020, the first case of COVID-19 disease was confirmed in The Netherlands by RIVM (National Institute for Public Health and the Environment). In the weeks after, thousands of people were diagnosed with the infectious disease. Data on COVID-19 case counts are important for research and applications on various topics like epidemiology and statistics.

This dataset contains reported case counts derived from official sources like RIVM (National Institute for Public Health and the Environment), LCPS (National Coordination Center for Patient Distribution), and NICE (National Intensive Care Evaluation). Data from these sources are collected, standardized, and published in various formats on a daily basis.

The README document in this repository provides an overview of the available datasets, their file location(s), and codebooks. Copies of the original data are stored in the folder named 'raw_data'. Scripts to process the raw data into standardized files can be found in the folder workflows.

Summary:

the data of study shows a possible drug candidate for COVID-19

Summary:

Release of Version 2.2 of the COVID-19 Closed Population Model developed by researchers at the Kirby Institute. This version includes an updated approach to modelling vaccination and corrects a bug in the Scenario 1 calculations.

Summary: Statistical models for biomolecular dynamics

Summary:

Outputs from the probabilistic projection methods developed or assessed in the European Climate Projection system (EUCP) Horizon2020 project. The data can be previewed through our interactive atlas.

For more information, see the atlas about page, or the corresponding storyboard.

 

Preprocessed data of Atlas in EUCP-WP2

We provide some notebooks that check the original/raw data, fix/add the metadata using CF-conventions https://cfconventions.org/Data/cf-conventions/cf-conventions-1.9/cf-conventions.html and save data in a NetCDF format. See https://github.com/eucp-project/atlas/blob/main/python/README.md.

For two of the methods, REA and ClimWIP, pre-calculated weights have also been included. Note that these weights are only valid in the context of this specific model ensemble. Therefore, the original (pre-processed) model data is published together with the weights.

The pre-processed data follows the following standards:

coordinates

• climatology_bounds (climatology_bounds) datetime64[ns] ['2050-06-01', '2050-09-01', '2050-12-01', '2051-03-01']
• time (time) (datetime64[ns]) [2050-07-16 2051-01-16] # "JJA", "DJF"
• latitude (lat) (float64) [30, ..., 75]
• longitude (lon) (float64) [-10, ..., 40]
• percentile (percentile) (int64) [10, 25, 50, 75, 90]

variables

• tas (time, latitude, longitude, percentile) (float64)
• pr (time, latitude, longitude, percentile) (float64)

attributes

The attributes of variables and coordinates are defined as:

• "tas": {
  "description": "Change in Air Temperature",
  "standard_name": "Change in Air Temperature",
  "long_name": "Change in Near-Surface Air Temperature",
  "units": "K",
  "cell_methods": "time: mean changes over 20 years 2041-2060 vs 1995-2014",
  },
• "pr": {
  "description": "Relative precipitation",
  "standard_name": "Relative precipitation",
  "long_name": "Relative precipitation",
  "units": "%",
  "cell_methods": "time: mean changes over 20 years 2041-2060 vs 1995-2014",
  },
• "latitude": {"units": "degrees_north", "long_name": "latitude", "axis": "Y"},
• "longitude": {"units": "degrees_east", "long_name": "longitude", "axis": "X"},
• "time": {
  "climatology": "climatology_bounds",
  "long_name": "time",
  "axis": "T",
  "climatology_bounds": ["2050-6-1", "2050-9-1", "2050-12-1", "2051-3-1"],
  "description": "mean changes over 20 years 2041-2060 vs 1995-2014. The mid point 2050 is chosen as the representative time.",
  },
• "percentile": {"units": "%", "long_name": "percentile", "axis": "Z"},

The attributes of the data is defined as:

• "description": "Contains modified institute method data used for Atlas in EUCP project.",
• "history": "original institute method data files ...",

output file names

output_file_name = prefix_activity_institution-id_source_method_sub-method_cmor-var

example: atlas_EUCP_CNRM_CMIP6_KCC_cons_tas.nc

Reference:

https://eucp-project.github.io/atlas/about

Summary:

Preprocessed data of Atlas in EUCP-WP2

We provide some notebooks that check the original/raw data, fix/add the metadata using CF-conventions https://cfconventions.org/Data/cf-conventions/cf-conventions-1.9/cf-conventions.html and save data in a NetCDF format. See https://github.com/eucp-project/atlas/blob/main/python/README.md.

The pre-processed data follows the following standards:

coordinates

• climatology_bounds (climatology_bounds) datetime64[ns] ['2050-06-01', '2050-09-01', '2050-12-01', '2051-03-01']
• time (time) (datetime64[ns]) [2050-07-16 2051-01-16] # "JJA", "DJF"
• latitude (lat) (float64) [30, ..., 75]
• longitude (lon) (float64) [-10, ..., 40]
• percentile (percentile) (int64) [10, 25, 50, 75, 90]

variables

• tas (time, latitude, longitude, percentile) (float64)
• pr (time, latitude, longitude, percentile) (float64)

attributes

The attributes of variables and coordinates are defined as:

• "tas": {
  "description": "Change in Air Temperature",
  "standard_name": "Change in Air Temperature",
  "long_name": "Change in Near-Surface Air Temperature",
  "units": "K",
  "cell_methods": "time: mean changes over 20 years 2041-2060 vs 1995-2014",
  },
• "pr": {
  "description": "Relative precipitation",
  "standard_name": "Relative precipitation",
  "long_name": "Relative precipitation",
  "units": "%",
  "cell_methods": "time: mean changes over 20 years 2041-2060 vs 1995-2014",
  },
• "latitude": {"units": "degrees_north", "long_name": "latitude", "axis": "Y"},
• "longitude": {"units": "degrees_east", "long_name": "longitude", "axis": "X"},
• "time": {
  "climatology": "climatology_bounds",
  "long_name": "time",
  "axis": "T",
  "climatology_bounds": ["2050-6-1", "2050-9-1", "2050-12-1", "2051-3-1"],
  "description": "mean changes over 20 years 2041-2060 vs 1995-2014. The mid point 2050 is chosen as the representative time.",
  },
• "percentile": {"units": "%", "long_name": "percentile", "axis": "Z"},

The attributes of the data is defined as:

• "description": "Contains modified institute method data used for Atlas in EUCP project.",
• "history": "original institute method data files ...",

output file names

output_file_name = prefix_activity_institution-id_source_method_sub-method_cmor-var

example: atlas_EUCP_CNRM_CMIP6_KCC_cons_tas.nc

Reference:

https://eucp-project.github.io/atlas/about

Summary:

Data from simulations of COVID-19 spread in Sweden under different public-health measures.  Results from individual-based models.

Summary:

Dataset for individual-based modeling of COVID-19 spread in Sweden.

Summary:

X-ray diffraction images which were collected on 28th March 1999 at the EMBL beamline BW7B at DESY (Hamburg) using a Marresearch 345 image plate detector. More information in the notes. 

Summary:

X-ray diffraction images for Escherichia coli 5-aminolevulinic acid dehydratase (ALAD) which was crystallised in the presence of the inhibitor levulinic acid (15 mM) and bismuth nitrate (1 mM). The data were collected at beamline 9.6 at the SRS Daresbury Laboratory (UK) on 10th March 1994 using a 30 cm Marresearch image plate detector, a crystal temperature of 100 K, a wavelength of 0.88 Å and a crystal-to-detector distance was 300 mm. The oscillation angle was 2.5 degrees and 21 images were collected at constant dose in the time available. A wax image for determining the direct beam position was taken with the detector at a distance of 400 mm.

Summary:

X-ray diffraction images for bovine inositol monophosphatase which were collected using the ESRF beamline ID14-4 to a resolution of around 1.4 Å. The data were collected in two passes, the second for measuring intensities that were overloaded in the first. More details are given in the included notes. 

Summary:

This is the first release of FUSED-Wind v0.1.0.

 

The Framework for Unified Systems Engineering and Design of Wind Plants (FUSED-Wind) is a free open-source framework for multi-disciplinary optimisation and analysis (MDAO) of wind energy systems, developed jointly by the Wind Energy Department at the Technical University of Denmark (DTU Wind Energy) and the National Renewable Energy Laboratory (NREL). The framework is built as an extension to the NASA developed OpenMDAO, and defines key interfaces, methods and I/O variables necessary for wiring together different simulation codes in order to achieve a system level analysis capability of wind turbine plants with multiple levels of fidelity. NREL and DTU have developed independent interfaces to their respective simulation codes and cost models with the aim of offering an environment where these codes can be used interchangeably. The open source nature of the framework enables third parties to develop interfaces to their own tools, either replacing or extending those offered by DTU and NREL.

Official website: http://www.fusedwind.org

GitHub repository:  https://www.github.com/fusedwind

v0.1.0:  https://github.com/FUSED-Wind/fusedwind/tree/v0.1.0

License: Apache v2.0

Summary:

www.planetserver.eu webclient

Summary:

No description provided.