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Data to D3.3 - Institutional arrangements of water supply, distribution and uses within and across case studies -identifying the barriers and drivers in place
<p>The transition towards a water circular economy (WCE) in the sense of water reuse may generate new water loops with additional challenges to water governance such as new and different types or qualities of water, new associated risks, new responsibilities,and new sets of actors involved. These challenges demand for clear-defined responsibilities, well-engaging of the various stakeholders, strong cooperation, and coordination among actors to prevent risks. Institutional arrangements, build the formal, and informal, design schemes to ensure adequate procedures and standards to better catalyse such transition. This deliverable analyses the institutional arrangements associated to the water management on the demosites, to assess their preparedness for the implementation of the new water loops as those foreseen with use of Project Ô new technologies. Using the Institutional Analysis and Development Framework, the analysis showed that the more water uses and users a new water loop involves the more critical the institutional arrangements become. Nevertheless, the institutional arrangements of the demosites do not always configure severe barriers. This is the case of Omis (Croatia) where the water reuse loop is located inside a textile company, and Eilat (Israel) where the water reuse loop is located inside amariculture centre. On the contrary, on Almendralejo (Spain) and Lecce (Italy), there are different players involved in the management ofthe water loop,andinstitutional arrangements appear more critical. Among the different institutional design principles, the clearly defined boundaries of responsibilities among stakeholders, the congruence between appropriation and provision rules and local conditions, raise more concerns on the case studies and call for the attention of future research on water circular economy. Fairly share of cost, benefits, and risks, dedicated graduated sanctions, conflict prevention and resolution mechanisms also deserve particular attention given the limited awareness of stakeholders of their features and influence for a successful implementation of demosites. Trust building, stakeholder empowerment and investment on transparency mechanisms related to water monitoring and sharing of communities and environmental benefits and costs of water reuse may be powerful approaches to implement water circular economy.</p>
Additional Files for "Assessing the potential of germplasm collections for the management of genetic diversity: the case of the French National Cryobank"
<p>Additional files for the article entitled "Assessing the potential of germplasm collections for managing genetic diversity: the case of the French National Cryobank".</p> <p><strong>Additional file 1: Table S1</strong></p> <p><strong>Title:</strong> Report on the output of material since the creation of the French National Cryobank</p> <p><strong>Additional file 2: Figure S1</strong></p> <p><strong>Title:</strong> Summary of material outputs from the French National Cryobank since 1999</p> <p><strong>Additional file 3: Table S2</strong></p> <p><strong>Title:</strong> Descriptors from the French National Cryobank data for six species</p> <p><strong>Additional file 4: Figure S2</strong></p> <p><strong>Title:</strong> Distribution of data and definition of intervals regarding breed diffusion (A), donor birth-year classes (B), and classes of donor’s age at 1<sup>st</sup> collection (C)</p> <p><strong>Additional file 5: Table S3</strong></p> <p><strong>Title:</strong> Statistics of the number of effective donors (De) according to species</p> <p><strong>Additional file 6: Table S4</strong></p> <p><strong>Title:</strong> Distribution of donors and doses across breeds</p> <p><strong>Description:</strong> In green, the breeds for which the FNC collections meet FAO conditions for reconstitution of an extinct breed. In blue, the breeds for which the collections of the FNC do not yet meet FAO conditions for reconstitution of an extinct breed. In gray, FAO recommendations not available. Based on the 2012 FAO report, with 100 founder females for ruminants and horses, or 30 founder females for pigs (with a pregnancy rate of 0.6).</p> <p><strong>Additional file 7: Figure S3</strong></p> <p><strong>Title:</strong> Evolution of genetic contributions of sires and their production of direct descendants in the French National Cryobank over the period 2011–2020 for three livestock species</p> <p><strong>Description:</strong> Two breeds of pigs are represented in pink (a, b), three breeds of sheep are represented in blue (c, d, e), and five breeds of cattle are represented in ochre (f, g, h, i, j).</p> <p><strong>Additional file 8: Figure S4</strong></p> <p><strong>Title:</strong> Distribution of individual IDIs of cryopreserved sires for the 17 breeds analyzed</p> <p><strong>Description:</strong> Pig breeds are represented in pink, sheep breeds are represented in blue, and cattle breeds are represented in ochre.</p> <p><strong>Additional file 9: Figure S5</strong></p> <p><strong>Title:</strong> Correlation between IDI values and the year of birth of donors</p> <p><strong>Additional file 10: Figure S6</strong></p> <p><strong>Title:</strong> Prediction of IDI values based on donor’s year of birth and the motivation for entry into collection</p> <p><strong>Description:</strong> Type I (for endangered breeds) is represented in purple and type III (for representative individuals of a breed over a period) is represented in orange.</p>
A case study for measuring the relativistic dipole of a galaxy cross-correlation with the Dark Energy Spectroscopic Instrument: Data Repository
<p>This repository contains the synthetic catalogue for the DESI Bright Galaxy Survey produced wit the N-body code <em>gevolution</em>, which is analysed in the manuscript "<a href="https://arxiv.org/abs/2306.04213">A case study for measuring the relativistic dipole of a galaxy cross-correlation with the Dark Energy Spectroscopic Instrument</a>", as well as the raw data of the analysis results. The catalogue "catalogue.csv.bz2" is in the CSV format and can be directly read using the pandas library of python, for example. The columns in the catalogue contain the following information:</p> <p>0. Column index<br> 1. Comoving coordinate x (in units of Mpc/h)<br> 2. Comoving coordinate y (in units of Mpc/h)<br> 3. Comoving coordinate z (in units of Mpc/h)<br> 4. Observed redshift<br> 5. Cosine of the observed polar angle measured with respect to the axis pointing in the direction (1,1,1) along the box diagonal (the original comoving coordinate system has been rotated with an intrinsic z-y-z Euler rotation, first rotating along the z-axis with <span class="math-tex">\(\phi_1 = \pi/4\)</span>, then rotating along the new y axis with <span class="math-tex">\(\theta_2 = \mathrm{arccos}(1/\sqrt{3})\)</span> and setting the final rotation angle to zero, <span class="math-tex">\(\phi_3 = 0\)</span>; hence to get the unperturbed mu and phi coordinates, one needs to rotate the comoving x, y and z coordinates with the corresponding inverse Euler rotation matrix)<br> 6. Observed azimuthal angle phi measured with respect to axis pointing in the direction (1,1,1) along the box diagonal (the original comoving coordinate system has been rotated with an intrinsic z-y-z Euler rotation, first rotating along the z-axis with <span class="math-tex">\(\phi_1 = \pi/4\)</span>, then rotating along the new y axis with <span class="math-tex">\(\theta_2 = \mathrm{arccos}(1/\sqrt{3})\)</span> and setting the final rotation angle to zero, <span class="math-tex">\(\phi_3 = 0\)</span>; hence to get the unperturbed mu and phi coordinates, one needs to rotate the comoving x, y and z coordinates with the corresponding inverse Euler rotation matrix)<br> 7. Logarithm of the luminosity in units of solar luminosity <span class="math-tex">\(L_\odot\)</span><br> 8. Observed flux (in units of <span class="math-tex">\(L_\odot/\mathrm{Mpc}^2\)</span>)<br> 9. Number of particles in each object, plus a uniform noise between 0 and 1. This quantity is the proxy of the mass that was used to assign luminosity to the objects.<br> 10. Flag that identifies the selected objects within each redshift bin. The Flag is 0 for objects not included in the catalogue, and equal to the mean redshift of the bins <span class="math-tex">\(\bar{z} = 0.25, 0.35, 0.45\)</span> for the selected objects. <br> 11. Flag that identifies the bright and faint objects for case 1 (50% bright, 50% faint, no flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 12. Flag that identifies the bright and faint objects for case 2 (90% bright, 10% faint, no flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 13. Flag that identifies the bright and faint objects for case 3 (50% bright, 50% faint, with flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 14. Flag that identifies the bright and faint objects for case 4 (90% bright, 10% faint, with flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.</p> <p>The example script "example-script.ipynb" demonstrates how to query the catalogue to extract e.g. the redshift distribution of the objects for the different cases considered in Table 4 of the manuscript.</p> <p>Additionally, the measured dipole data vectors with the jackknife covariance matrices (<span class="math-tex">\(\mathrm{cov}^\mathrm{JK}_{ij}\)</span>), as well as the theoretical data vectors with the theoretical measurement covariance (<span class="math-tex">\(\mathrm{cov}^\mathrm{th}_{ij}\)</span>) and the theoretical prediction covariance (<span class="math-tex">\(\mathrm{cov}^\mathrm{pred}_{ij}\)</span>) are provided within this repository:</p> <ul> <li>In the measurements.tar.gz archive, the measured data for the flux-limited case can be found in the /flux-limit subdirectory, while the data for the case without flux-limit is in /no-flux-limit. The data vectors are named "dipole_<redshift bin>_<% of bright galaxies>.txt. The first column in each of those files is the separation bin <span class="math-tex">\(d\)</span> in <span class="math-tex">\(\mathrm{Mpc}/h\)</span>, the second column is the mean two-point correlation function dipole of the 100 jackknife subsamples, and the third column is the square root of the diagonal part of the jackknife covariance matrix (<span class="math-tex">\(\mathrm{cov}^\mathrm{JK}_{ij}\)</span>). The corresponding jackknife covariance matrices are named "cov_<redshift bin>_<% of bright galaxies>.txt.</li> <li>In the theory.tar.gz archive, the theoretical predictions are found in /flux-limit for the case with flux limit and in /no-flux-limit for the case without flux limit. The theoretical data vectors are named "dipole_<% of bright galaxies>B_z<redshift bin>_gevol.dat". The first column in each of those files is the separation bin <span class="math-tex">\(d\)</span> in <span class="math-tex">\(\mathrm{Mpc}/h\)</span>, the second column the theoretical two-point correlation function dipole and the third column is the square root of the diagonal part of the theoretical prediction covariance matrix (<span class="math-tex">\(\mathrm{cov}^\mathrm{pred}_{ij}\)</span>) . The theoretical measurement covariance matrices are named "covariance_Lp6_<% of bright galaxies>B_z<redshift bin>_gevol.dat", and the theoretical prediction covariance matrices are named "covtheo_<% of bright galaxies>B_z<redshift bin>_gevol.dat". </li> </ul> <p>The example script also demonstrates how to use these data files to reproduce plots of the dipole measurement vs the theoretical prediction like in Figures 6, 7, C1 and C2. The archives need to be unpacked before using the example script to access the data.</p>
The effects of N-addition on litter mixture effects depend on decomposition time: a case from mixed-litter decomposition in the Gurbantunggut Desert
<p>Changes in nitrogen (N) deposition and litter mixtures have been shown to influence ecosystem processes such as litter decomposition. However, the interactive effects of litter mixing and N-deposition on decomposition process in desert regions remain poorly identified. We assessed the simultaneous effects of both N addition and litter mixture on mass loss in a litterbag decomposition experiment using six native plants in single-species samples with diverse quality and 14 species-combinations in the Gurbantunggut Desert under two N addition treatments (control and N addition). The N addition had no significant effect on decomposition rate of single-species litter (except <em>Haloxylon ammodendron</em>), whereas litter mass loss and decomposition rate differed significantly among species, with variations positively correlated with initial phosphorus concentration and negatively correlated with initial lignin concentration. After 18 months, the average mass loss across litter mixtures did not overall differ from those predicted from single-species either in control or N addition treatments, that is, mixing of different species had no non-additive effects on decomposition. The N addition, however, did modify the direction of mixture effects, and interacted with incubation time. Added N transformed synergistic effects of litter mixtures to antagonistic effects on mass loss after 1 month of decomposition, while transforming neutral effects of litter mixture to synergistic effects after 6 months of decomposition. Our results demonstrated that initial chemical properties played an important role in litter decomposition, while no effects of litter mixture on decomposition process in this desert region. The N addition altered the litter mixture effects on mass loss with incubation time, implying that increased N deposition in the future may have profound effects on carbon turnover to a greater extent than previously thought in desert ecosystems.</p>
GRASS GIS Location for urban growth case study in Triangle area, NC, USA
<p>GRASS GIS Location containing data prepared for a FUTURES urban growth modeling case study for the broader Raleigh-Durham area in North Carolina, USA. Contains NLCD 2001-2019 (land cover for all years; 2001 and 2019 impervious descriptor), county boundaries, USGS DEM, PAD-US protected areas.</p>
Photovoice and case based learning activities in higher education (University of Zaragoza - Social Work degree)
<p>The collected variables are: students data (gender, age, university admittance marks from 0 to 14), academic perforrnace of photovoice (PV) activity (from 0 to 10), academic performance of Case based learning (CBL) activity (form 0 to 10), order of the exercises, satisfaction with the photovoice activity, satisfaction with the CBL activity, items and overall self-efficacy scale score</p>
Test cases for the Geospatial Probabilistic Estimation Package (GPEP)
<p>The dataset contains test cases for the Geospatial Probabilistic Estimation Package (GPEP, https://github.com/NCAR/GPEP) and relevant publications. The two current test cases are based on prior implementations for GMET version 2.0 (https://github.com/NCAR/GMET and https://zenodo.org/records/5498408) for applications, and include:</p><ul><li>a GMET version 2.0 test case of daily meteorological forcing generation at 1/16th degree resolution for February 2017 for a region of the US Southwest encompassing California, US (Bunn et al, 2022).</li><li>a test case for daily meteorological forcing generation at 0.01 degree resolution from 1970-2022 for a smaller region of the US Southwest encompassing the upper Colorado River basin and Colorado Front Range.</li></ul><p>The associated meteorological station forcings and gridded parameter inputs were developed for water resources research projects at NCAR (PI A. Wood) sponsored by the United States Army Corps of Engineers Climate Preparedness and Resilience Program and the United States Bureau of Reclamation Science and Technology Program. </p><p>References:</p><p>Bunn, PTW, AW Wood, AJ Newman, H Chang, CL Castro, MP Clark and JR Arnold, 2022, Improving station-based ensemble surface meteorological analyses using numerical weather prediction: A case study of the Oroville Dam crisis precipitation event. <i>J. Hydromet.</i> 23(7), 1155-1169. https://doi-org.cuucar.idm.oclc.org/10.1175/JHM-D-21-0193.1<br> </p>
Bearing database - Evaluation of isolated cases
<p><strong>Induced failure test data on outer race, inner race and rolling elements of a spherical roller bearing (FAG 22205E1KC3)</strong><br> This site allows access to vibration records of a bearing, in normal state and under localized induced faults in outer race (OR), inner race (IR) and rolling elements (RE). The experiment is developed in a test bench, to validate the performance of a low-cost data acquisition system proposed by the Technological Research Group of Railways (CITEF) of the Polytechnic University of Madrid. The characteristics of the developed database are specified in the attached document "READ_ME.docx".</p> <p>The article link is available at: <a href="https://doi.org/10.3390/math11163498">https://doi.org/10.3390/math11163498</a></p>
The Metadata of "Are the Lists of Questionable Journals Reasonable: A Case Study of Early Warning Journal List"
<p>The metadata of the article (<em>Are the Lists of Questionable Journals Reasonable: A Case Study of Early Warning Journal List</em>).</p>
Artifact description for PMBS'23 paper: Calculating Primes the Expensive Way: A Case Study in Write-Allocate Evasion on Intel Ice Lake SP
<p>The article investigates a new hardware feature introduced with the Intel Ice Lake SP microarchitecture that automatically avoids write-allocate traffic for streaming write accesses. The analysis uses the CloverLeaf benchmark code from the SPEChpc2021 suite and micro-benchmarks to assess the effectiveness. The artifact description contains scripts to make CloverLeaf a stand-alone application without the SPEC benchmarking harness and patches for code changes applied to the CloverLeaf benchmark code for the in-depth analysis. Moreover, depending on the task, there are scripts that gather data for multiple parameters, commonly thread counts.</p> <p>All data collecting scripts produce CSV files for further analysis or plotting. For reference, the CSV files with the results shown in the paper are part of the artifact description. Moreover, the artifact description contains the TeX sources to plot all figures presented in this work. They contain the transformations done to the data (scaling from GByte to Byte, etc.) before plotting.</p> <p>With a working installation of the SPEChpc2021 suite, an Intel Ice Lake SP system and applied patches from this artifact description, all benchmarks can be re-run and reproduce the data presented in this work. It is important to note that the write-allocate avoidance feature behaves differently on different Ice Lake SP chips. For a full reproduction of the shown results, one has to use systems with Intel Xeon Platinum 8360Y as well. Furthermore, for disabling certain hardware features like the hardware prefetchers, SpecI2M or other undocumented prefetchers, one needs root access to the system.</p>
Data from: Beyond the case study: Characterizing natural floodplain heterogeneity in the United States
<p>As river channels move across the valley floor, they create diverse topography including natural levees, cutoff meanders, secondary channels, and floodplain wetlands. These features increase the spatial heterogeneity of the floodplain. Many studies indicate that this heterogeneity strongly influences habitat abundance and diversity, storage of flood waters and excess nitrate or phosphate, and other floodplain functions. However, no one has systematically measured floodplain heterogeneity across multiple rivers and different geographic regions. We measured the heterogeneity of natural floodplains at 14 sites in the continental United States using metrics developed by landscape ecologists. We find that natural floodplains have distinctive heterogeneity signatures that relate to drainage area, the size of the floodplain, and other characteristics. The data included here are the original field data associated with 14 of the field sites, including GPS locations of floodplain transects, floodplain patches, sediment cores, and large wood; and delineated floodplain shapefiles.</p>
Data repository supporting the JGR article: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming
<p>This dataset contains the meteor radar wind measurements and the background atmospheric data fields used to produce the results in the Journal of Geophysical Research - Space Physics article titled: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming.</p> <p>The nav_2013_ERAn_1dm_grid.dat file contains gridded latitude-longitude-altitude daily mean winds and temperatures for the composite atmosphere described in the article. The full range of dates span from the 1st of December 2012 to the 1st of April 2023. The composite atmosphere is constructed using ERA5 winds and temperatures below 85 hPa, NAVGEM-HA winds and temperatures between 85-0.001 hPa, and HWM14 + MSISE00 winds and temperatures above 0.001 hPa.</p> <p>The meteor_radars.zip file contains a folder containing the hourly meteor radar wind measurements for the Collm (Col), CMOR (CMO), and Kiruna (Kir) radars, as described in the supporting paper. The .hdf5 files contain both the horizontal and meridional wind measurements for December, January, February, and March (winter of 2012/2013).</p>
Data repository in support of the article: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming
<p>This dataset contains the meteor radar wind measurements and the background atmospheric data fields used to produce the results in the Journal of Geophysical Research - Space Physics article titled: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming.</p> <p>The nav_2013_ERAn_1dm_grid.dat file contains gridded latitude-longitude-altitude daily mean winds and temperatures for the composite atmosphere described in the article. The full range of dates span from the 1st of December 2012 to the 1st of April 2023. The composite atmosphere is constructed using ERA5 winds and temperatures below 85 hPa, NAVGEM-HA winds and temperatures between 85-0.001 hPa, and HWM14 + MSISE00 winds and temperatures above 0.001 hPa.</p> <p>The meteor_radars.zip file contains a folder containing the hourly meteor radar wind measurements for the Collm (Col), CMOR (CMO), and Kiruna (Kir) radars, as described in the supporting paper. The .hdf5 files contain both the horizontal and meridional wind measurements for December, January, February, and March (winter of 2012/2013).</p> <p> </p> <p> </p> <p> </p>
Distribution of heavy metals in coastal sediments under the influence of multiple factors: A case study from the south coast of an industrialized harbor city (Tangshan, China)
<p><span>This research investigated the spatial distribution of heavy metals, including mercury (Hg), cadmium (Cd), copper (Cu), arsenic (As), nickel (Ni), lead (Pb), chromium (Cr), and zinc (Zn), in surface sediments from the coastal area near to an industrial harbor (the Tangshan Harbor, China) with 161 sediment samples. The results showed that the distribution patterns of Cr, Cu, Zn, Ni, and Pb were similar to each other, high in the northwest, southeast, and southwest regions of the study area and low in the northeast region, which corresponded well with components of sedimental sizes. The uncontaminated specimen proportions for Hg, Cd, Cu, As, Ni, Pb, Cr, and Zn were 6.8%, 4.3%, 31.1%, 28.6%, 42.9%, 64.6%, 44.7%, and 50.3%, respectively. Based on principal component analysis (PCA) and positive matrix factorization (PMF), four distinct sources of pollution were quantitatively attributed, including agricultural activities (22.08%), fossil fuel consumption (24.14%), steel production (29.78%), and natural sources (24.00%). Hg (80.29%), Cd (82.31%) and As (65.33%) in the region's coastal sediments were predominantly contributed by fossil fuel, steel production and agricultural</span> <span>sources, respectively. Cr (40.00%), Cu (43.63%), Ni (47.54%), and Zn (38.98%) were primarily of natural lithogenic origin, while Pb mainly came from the mixed sources of agricultural activities (36.63%), fossil fuel (36.86%), and steel production (34.35%). Multiple factors played important roles in the selective transportation of sedimentary heavy metals, especially sediment properties, and hydrodynamic sorting processes in the study area.</span></p>
Scripts and Data for "Disentangling the Hydrological and Hydraulic Controls on Streamflow Variability in E3SM V2 – A Case Study in the Pantanal Region"
<p>Matlab scripts for processing and showing the coupled ELM-MOSART coupled simulations for Pantanal region.</p> <p>domain_lnd_Pantanal_default.nc, MOSART_Pantanal_default_c211116.nc, and surfdata_Pantanal_default_c220520.nc are the domain file, MOSART input file, and ELM surface dataset, respectively. </p> <p><a href="https://zenodo.org/api/files/6be468b6-cbfa-4ef4-bb10-0f15812be9bd/Pantanal_half_calibration_CLMCRUNCEPv7.sh">Pantanal_half_calibration_CLMCRUNCEPv7.sh</a> is the bash script to run E3SM with coupled ELM-MOSART configuration. ANd detailed instruction of running E3SMV2 can be found at: https://e3sm.org/model/running-e3sm/e3sm-quick-start/ (last access: Aug 2023).</p> <p>Pantanal_GSIM.zip contains the observed streamflow that used in this study, which is downloaded from <a href="https://doi.pangaea.de/10.1594/PANGAEA.887470">https://doi.pangaea.de/10.1594/PANGAEA.887470</a> (last access: Aug 2023). The reference is Gudmundsson, Lukas; Do, Hong Xuan; Leonard, Michael; Westra, Seth (2018): The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment. Earth System Science Data, 10(2), 787-804, https://doi.org/10.5194/essd-10-787-2018.</p> <p>BFI3.mat is the baseflow index from GSCD and processed to the study domain. The GSCD dataset was download from <a href="http://www.gloh2o.org/gscd/">http://www.gloh2o.org/gscd/</a> (last access: Aug 2023). The reference is Beck, H. E., van Dijk, A. I. J. M., Miralles, D. G., de Jeu, R. A. M., Bruijnzeel, L. A., McVicar, T. R., and Schellekens, J.: Global patterns in base flow index and recession based on streamflow observations from 3394 catchments, Water Resour Res, 49, 7843-7863, <a href="https://doi.org/10.1002/2013WR013918">https://doi.org/10.1002/2013WR013918</a>, 2013.</p> <p>runoff_uncertianty.mat contains the annual runoff time series from GRUN, LORA, and GFRF that processed to the study domain. The GRUN runoff dataset was downloaded from <a href="https://doi.org/10.6084/m9.figshare.9228176">https://doi.org/10.6084/m9.figshare.9228176</a> (last access: Aug 2023). The LORA runoff dataset was downloaded from <a href="https://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/ks32/ARCCSS_Data/LORA/v1-0/catalog.xml">https://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/ks32/ARCCSS_Data/LORA/v1-0/catalog.xml</a> (last access: Aug 2023). The reference is Hobeichi, S., Abramowitz, G., Evans, J., and Beck, H. E.: Linear Optimal Runoff Aggregate (LORA): a global gridded synthesis runoff product, Hydrol. Earth Syst. Sci., 23, 851-870, 10.5194/hess-23-851-2019, 2019. The GRFR runoff was downloaded from <a href="http://hydrology.princeton.edu/data/mpan/GRFR/runoff/monthly_1deg/">http://hydrology.princeton.edu/data/mpan/GRFR/runoff/monthly_1deg/</a> (last access: Aug 2023). The reference is Yang, Y., Pan, M., Lin, P., Beck, H. E., Zeng, Z., Yamazaki, D., David, C. d. H., Lu, H., Yang, K., Hong, Y., and Wood, E. F.: Global Reach-level 3-hourly River Flood Reanalysis (1980-2019), B Am Meteorol Soc, 1-49, 10.1175/BAMS-D-20-0057.1, 2021.</p> <p>GLAD_Pantanal_half.mat, GLAD_Pantanal_8th.mat are the processed surface water fraction from GLAD at half and 8th spatial resoution. Specifically, The GLAD surface water dynamics was downloaded from <a href="https://console.cloud.google.com/storage/browser/earthenginepartners-hansen/water;tab=objects">https://console.cloud.google.com/storage/browser/earthenginepartners-hansen/water;tab=objects</a> (last access: Aug 2023). The reference is Pickens, A. H., Hansen, M. C., Hancher, M., Stehman, S. V., Tyukavina, A., Potapov, P., Marroquin, B., and Sherani, Z.: Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series, Remote Sens Environ, 243, 111792, <a href="https://doi.org/10.1016/j.rse.2020.111792">https://doi.org/10.1016/j.rse.2020.111792</a>, 2020.</p>
Fig. 1 in On the daily activity of the Red Fox (Vulpes vulpes) in two village areas of Bulgaria: a case study
Fig. 1. Red Fox (Vulpes vulpes) feeding in front of a camera trap, Isperihovo village.
Fig. 1 in New Distributional Records and Another Case of Winter Activity of Malpolon insignitus (Geoffroy Saint-Hilaire, 1827) (Reptilia: Psammophiidae) in South-Western Bulgaria
Fig. 1. Distribution of Malpolon insignitus in south-western Bulgaria, based on a 5 km UTM grid.
Data and Code Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"
<p>Code and Data Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"<br> ===========================================================</p> <p>This directory contains the data and scripts used to create the plots from our publication as well as the source<br> code modifications necessary to run this test case within the CESM and MPAS models.</p> <p>Generating Plots<br> ---------------</p> <p>The `netcdf` directory contains the nominal half-degree runs necessary to generate nearly all of the plots from the paper. The one plot which is not reproducible from these data is the volume-integrated Eddy Kinetic Energy in the Spectral Element model. Storing high-resolution 4D wind fields requires a prohibitive amount of space. These data can be provided by the corresponding author, O.K. Hughes (owhughes@umich.edu). However, because this is several hundred GB of data I would strongly recommend generating these high-resolution runs yourself on your local system if you need them. Using 288 Intel Skylake cores (that is, 8 nodes each with two 18C processors) ran on the order of an hour.</p> <p><em>In order to generate the plots from the paper, you need only install NCL and then run</em> run.bash. Instructions for installing NCL<br> can be found in the `run.bash` script.</p> <p>Source Code Modifications<br> ----------------</p> <p><strong>CESM</strong><br> The `src` subdirectory contains the files `user_nl_cam` and `ic_baroclinic.F90`. Create a case using `--compset=FKESSLER` and `--run-unsupported` options when running `create_newcase`. If your case is located at `${CASE_DIR}`, then from within the directory containing this README, run `cp user_nl_cam ${CASE_DIR}/user_nl_cam`, and then run `cp ic_baroclinic.F90 ${CASE_DIR}/SourceMods/src.cam/`. Then build and run the model using the usual workflow.</p> <p><strong>MPAS</strong></p> <p>The MPAS code was run using a branch of the MPAS model provided by the model developers to the authors. While the source code modifications are provided in the `src` directory, I would strongly recommend contacting the corresponding author if you wish to run this test case in the MPAS codebase.</p>
Data from: Climate micro-mobilities as adaptation practice in the Pacific: the case of Samoa
<p>These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4"><strong>10.5061/dryad.bnzs7h4h4</strong></a>. This data set provides the summary of translated interviews with 20 participants from the two research sites in the small Pacific island state of Samoa. The field data was collected between June and August 2021.</p>
Pixelflow Seed Phenotyping Use Case Demo Data
<p>Example 2D and 3D seed phenotyping data for pixelflow use case demo notebooks on the Scivision gallery. Contains original images (.tif) and associated segmented labels of each seed (.npy)</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.