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814 results for “Routing”

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OpenNeuro52/100

Route Learning

Open the record for dataset details and reuse information.

openCC0Jan 2020View details →
edi52/100

Mean radiant temperature along a common route for people experiencing homelessness in downtown Phoenix, Arizona (USA) on August 20, 2024

This tabular dataset contains mean radiant temperature (Tmrt) measurements collected using MaRTy, a mobile biometeorological, along a route frequently traveled by people experiencing homelessness in downtown Phoenix, Arizona (USA). It includes Tmrt, air temperature (Tair), relative humidity (RH), wind speed, and wind direction at pedestrian height at 2-second intervals for a typical summer day (August 20, 2024; peak air temperature of 43.3 degrees Celsius) at 0700, 1300, and 1700 (local times). This dataset can inform heat mitigation strategies for vulnerable populations in Phoenix.

openCC0Feb 2025View details →
edi52/100

Rabbit survey data on creosotebush and grassland routes from the long-term Small Mammal Exclusion Study at Jornada Basin LTER, 1996-ongoing

This data package contains rabbit survey data from grassland and creosote shrubland habitats on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Two survey routes were established along Jornada Basin roads in 1996; one in black grama grassland and the other in creosotebush shrubland. Quarterly surveys are conducted on these roads at or near the full moon to measure the density of rabbits in the two vegetation types. Each route is about 6 miles long. Parallel studies were established at the Sevilleta LTER site (New Mexico, USA) and Mapimi Biosphere Reserve (Durango, Mexico). Data collection began in April 1996 and includes date and time lagomorphs are spotted, species identification, habitat type, distance/direction from vehicle, and comments on the weather, moon, and anything unusual. This study is ongoing with new data collected quarterly.

openCC (other)Apr 2022View details →
zenodo48/100

RAPID input and output files corresponding to "River Network Routing on the NHDPlus Dataset"

<p><strong>Corresponding peer-reviewed publication</strong></p> <p>This dataset corresponds to all the RAPID input and output files that were used in the study reported in:</p> <ul> <li>David, C&eacute;dric H., David R. Maidment, Guo-Yue Niu, Zong-Liang Yang, Florence Habets and Victor Eijkhout (2011), River Network Routing on the NHDPlus Dataset, Journal of Hydrometeorology, 12(5), 913-934. DOI: 10.1175/2011JHM1345.1.&nbsp;</li> </ul> <p>&nbsp;</p> <p>When making use of any of the files in this dataset, please cite both the aforementioned article and the dataset herein.&nbsp;</p> <p>&nbsp;</p> <p><strong>Time format</strong></p> <p>The times reported in this description all follow the ISO 8601 format.&nbsp; For example 2000-01-01T16:00-06:00 represents 4:00 PM (16:00) on Jan 1<sup>st</sup> 2000 (2000-01-01), Central Standard Time (-06:00).&nbsp; Additionally, when time ranges with inner time steps are reported, the first time corresponds to the beginning of the first time step, and the second time corresponds to the end of the last time step.&nbsp; For example, the 3-hourly time range from 2000-01-01T03:00+00:00 to 2000-01-01T09:00+00:00 contains two 3-hourly time steps.&nbsp; The first one starts at 3:00 AM and finishes at 6:00AM on Jan 1<sup>st</sup> 2000, Universal Time; the second one starts at 6:00 AM and finishes at 9:00AM on Jan 1<sup>st</sup> 2000, Universal Time.</p> <p>&nbsp;</p> <p><strong>Data sources</strong></p> <p>The following sources were used to produce files in this dataset:</p> <ul> <li>The National Hydrography Dataset Plus (NHDPlus) Version 1, obtained from http://www.horizon-systems.com/nhdplus.&nbsp;</li> <li>The National Water Information System (NWIS), obtained from http://waterdata.usgs.gov/nwis.&nbsp; &nbsp;</li> <li>Outputs from a simulation using the community Noah land surface model with multiparameterization options (Noah-MP, Niu et al. 2011, http://www.jsg.utexas.edu/noah-mp). &nbsp;The simulation was run by Guo-Yue Niu, and produced 3-hourly time steps from 2004-01-01T00:00+00:00 to 2008-01-01T00:00+00:00. &nbsp;Further details on the inputs and options used for this simulation are provided in David et al. (2011).</li> </ul> <p>&nbsp;</p> <p><strong>Software</strong></p> <p>The following software were used to produce files in this dataset:</p> <ul> <li>The Routing Application for Parallel computation of Discharge (RAPID, David et al. 2011, http://rapid-hub.org), Version 1.0.0.&nbsp; Further details on the inputs and options used for this series of simulations are provided below and in David et al. (2011).</li> <li>ESRI ArcGIS (http://www.arcgis.com).&nbsp;</li> <li>Microsoft Excel (https://products.office.com/en-us/excel).&nbsp;</li> <li>CUAHSI HydroGET (http://his.cuahsi.org/hydroget.html).&nbsp;</li> <li>The GNU Compiler Collection (https://gcc.gnu.org) and the Intel compilers (https://software.intel.com/en-us/intel-compilers).&nbsp;</li> </ul> <p>&nbsp;</p> <p><strong>Study domain</strong></p> <p>The files in this dataset correspond to two study domains:</p> <ul> <li>The combination of the San Antonio and Guadalupe River Basins, TX.&nbsp; RAPID can only use the river reaches of NHDPlus that have a known flow direction and focus is made on these reaches here (a total of 5,175).&nbsp; The temporal range corresponding to this domain is from 2004-01-01T00:00-06:00 to 2007-12-31 T00:00-06:00.</li> <li>The Upper Mississippi River Basin.&nbsp; RAPID can only use the river reaches of NHDPlus that have a known flow direction and focus is made on these reaches here (a total of 182,240).&nbsp; The temporal range corresponding to this domain spans 100 fictitious days.</li> </ul> <p>&nbsp;</p> <p><strong>Description of files for the San Antonio and Guadalupe River Basins</strong></p> <p>All files below were prepared by C&eacute;dric H. David, using the data sources and software mentioned above.&nbsp;</p> <ul> <li><em>rapid_connect_San_Guad.csv.</em>&nbsp; This CSV file contains the river network connectivity information and is based on the unique IDs of NHDPlus reaches (the COMIDs). &nbsp;For each river reach, this file specifies: the COMID of the reach, the COMID of the unique downstream reach, the number of upstream reaches with a maximum of four reaches, and the COMIDs of all upstream reaches.&nbsp; A value of zero is used in place of NoData.&nbsp; The river reaches are sorted in increasing value of COMID.&nbsp; The values were computed using a combination of the following NHDPlus fields: COMID, DIVERGENCE, FROMNODE and TONODE.&nbsp; This file was prepared using ArcGIS and Excel.</li> <li><em>m3_riv_San_Guad_2004_2007_cst.nc.&nbsp; </em>This netCDF file contains the 3-hourly accumulated inflows of water (in cubic meters) from surface and subsurface runoff into the upstream point of each river reach. The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>. &nbsp;The time range for this file is from 2004-01-01T00:00-06:00 to 2007/12/31T18:00-06:00. &nbsp;The values were computed by superimposing a 900-m gridded map of NHDPlus catchments to the outputs of Noah-MP.&nbsp; This file was prepared using ArcGIS and a Fortran program.</li> <li><em>kfac_San_Guad_1km_hour.csv.&nbsp; </em>This CSV file contains a first guess of Muskingum k values (in seconds) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on the following NHDPlus fields: COMID, LENGTHKM, Equation (13) in David et al. (2011), and using a wave celerity of 1 km/h.&nbsp; This file was prepared using a Fortran program.</li> <li><em>kfac_San_Guad_celerity.csv.&nbsp; </em>This CSV file contains a first guess of Muskingum k values (in seconds) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on the following NHDPlus fields: COMID, LENGTHKM, Equation (13) in David et al. (2011), and using the wave celerity numbers of Table 2 in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>k_San_Guad_2004_1.csv.&nbsp; </em>This CSV file contains Muskingum k values (in seconds) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on the following NHDPlus fields: COMID, LENGTHKM, and using Equation (17) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>k_San_Guad_2004_2.csv.&nbsp; </em>This CSV file contains Muskingum k values (in seconds) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on the following NHDPlus fields: COMID, LENGTHKM, and using Equation (18) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>k_San_Guad_2004_3.csv.&nbsp; </em>This CSV file contains Muskingum k values (in seconds) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on the following NHDPlus fields: COMID, LENGTHKM, and using Equation (19) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>k_San_Guad_2004_4.csv.&nbsp; </em>This CSV file contains Muskingum k values (in seconds) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on the following NHDPlus fields: COMID, LENGTHKM, and using Equation (21) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>x_San_Guad_2004_1.csv.&nbsp; </em>This CSV file contains Muskingum x values (dimensionless) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on Equation (17) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>x_San_Guad_2004_2.csv.&nbsp; </em>This CSV file contains Muskingum x values (dimensionless) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on Equation (18) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>x_San_Guad_2004_3.csv.&nbsp; </em>This CSV file contains Muskingum x values (dimensionless) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on Equation (19) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>x_San_Guad_2004_4.csv.&nbsp; </em>This CSV file contains Muskingum x values (dimensionless) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_San_Guad.csv</em>.&nbsp; The values were computed based on Equation (21) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.</li> <li><em>basin_id_San_Guad_hydroseq.csv. &nbsp;</em>This CSV file contains the list of unique IDs of NHDPlus river reaches (COMID) in the San Antonio and Guadalupe River Basins.&nbsp; The river reaches are sorted from upstream to downstream. &nbsp;The values were computed using the following NHDPlus fields: COMID and HYDROSEQ.&nbsp; This file was prepared using Excel.</li> <li><em>Qout_San_Guad_1460days_p1_dtR=900s.nc.</em> &nbsp;This netCDF file contains the 3-hourly averaged outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2007-12-31-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (17) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>Qout_San_Guad_1460days_p2_dtR=900s.nc.&nbsp; </em>This netCDF file contains the 3-hourly averaged outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2007-12-31-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (18) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>Qout_San_Guad_1460days_p3_dtR=900s.nc.&nbsp; </em>This netCDF file contains the 3-hourly averaged outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2007-12-31-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (19) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>Qout_San_Guad_1460days_p4_dtR=900s.nc. &nbsp;</em>This netCDF file contains the 3-hourly averaged outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2007-12-31-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (21) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>QoutR_San_Guad_182days_p1_dtR=900s.nc. </em>This netCDF file contains the 15-min outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2004-07-01-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (17) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>QoutR_San_Guad_182days_p2_dtR=900s.nc. </em>This netCDF file contains the 15-min outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2004-07-01-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (18) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>QoutR_San_Guad_182days_p3_dtR=900s.nc. </em>This netCDF file contains the 15-min outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2004-07-01-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (19) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>QoutR_San_Guad_182days_p4_dtR=900s.nc. </em>This netCDF file contains the 15-min outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_San_Guad_hydroseq.csv</em>.&nbsp; The time range for this file is from 2004-01-01T00:00-06:00 to 2004-07-01-00:00-06:00. The values were computed using the Muskingum method with parameters of Equation (21) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> <li><em>gage_id_San_Guad_2004_2007_full.csv.&nbsp; </em>This CSV file contains the list of COMIDs of rivers containing USGS gauges and with full daily data record.&nbsp; &nbsp;The river reaches are sorted in increasing value of COMID.&nbsp; The time range used for determining a full record is daily from 2004-01-01T00:00-06:00 to 2008-01-01T00:00-06:00.&nbsp; The values were computed using the following NHDPlus field: COMID.&nbsp; This file was prepared using ArcGIS, HydroGET, and Excel.</li> <li><em>Qobs_San_Guad_2004_2007_full.csv.&nbsp; </em>This CSV file contains daily averaged measured stream flow (in cubic meters per second). &nbsp;The river reaches have the same COMIDs and are sorted similarly to <em>gage_id_San_Guad_2004_2007_full.csv</em>.&nbsp; The time range for the daily values is from 2004-01-01T00:00-06:00 to 2008-01-01T00:00-06:00.&nbsp; The values were computed using the following NHDPlus field: COMID, and the observations from NWIS.&nbsp;&nbsp; This file was prepared using ArcGIS, HydroGET, and Excel.</li> </ul> <p>&nbsp;</p> <p><strong>Description of files for the Upper Mississippi River Basin</strong></p> <p>All files below were prepared by C&eacute;dric H. David, using the data sources and software mentioned above.&nbsp;</p> <ul> <li><em>rapid_connect_Reg07.csv.&nbsp; </em>This CSV file contains the river network connectivity information and is based on the unique IDs of NHDPlus reaches (the COMIDs).&nbsp; For each river reach, this file specifies: the COMID of the reach, the COMID of the unique downstream reach, the number of upstream reaches with a maximum of four reaches, and the COMIDs of all upstream reaches.&nbsp; A value of zero is used in place of NoData.&nbsp; The river reaches are sorted in increasing value of COMID.&nbsp; The values were computed using a combination of the following NHDPlus fields: COMID, DIVERGENCE, FROMNODE and TONODE.&nbsp; This file was prepared using ArcGIS and Excel.&nbsp;</li> <li><em>m3_riv_Reg07_100days_dummy.nc.&nbsp; </em>This netCDF file contains the 3-hourly accumulated inflows of water (in cubic meters) from surface and subsurface runoff into the upstream point of each river reach. The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_Reg07.csv</em>.&nbsp; The time range for this file is for 100 fictitious days.&nbsp; The values were computed using a unique value of 1 cubic meter for all river reaches and all time steps.&nbsp; This file was prepared using a Fortran program.</li> <li><em>kfac_Reg07_2.5ms.csv.&nbsp; </em>This CSV file contains a first guess of Muskingum k values (in seconds) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_Reg07.csv</em>.&nbsp; The values were computed based on the following NHDPlus fields: COMID, LENGTHKM, and using Equation (22) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.&nbsp;&nbsp;&nbsp;&nbsp;</li> <li><em>xfac_Reg07_0.3.csv.&nbsp; </em>This CSV file contains a first guess of Muskingum x values (dimensionless) for all river reaches.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>rapid_connect_Reg07.csv</em>.&nbsp; The values were computed based on Equation (22) in David et al. (2011).&nbsp; This file was prepared using a Fortran program.&nbsp;&nbsp;&nbsp;&nbsp;</li> <li><em>basin_id_Reg07_hydroseq.csv.&nbsp; </em>This CSV file contains the list of unique IDs of NHDPlus river reaches (COMID) in the Upper Mississippi River Basin.&nbsp; The river reaches are sorted from upstream to downstream.&nbsp; The values were computed using the following NHDPlus fields: COMID and HYDROSEQ.&nbsp; This file was prepared using Excel.</li> <li><em>Qout_Reg07_100days_pfac_dtR900s.nc.</em> This netCDF file contains the 3-hourly averaged outputs (in cubic meters per second) from RAPID corresponding to the downstream point of each reach.&nbsp; The river reaches have the same COMIDs and are sorted similarly to <em>basin_id_Reg07_hydroseq.csv</em>.&nbsp; The time range for this file spans 100 fictitous days. The values were computed using the Muskingum method with parameters of Equation (22) in David et al. (2011).&nbsp; This file was prepared using RAPID v1.0.0 running with the preonly ILU solver on one core.</li> </ul> <p>&nbsp;</p> <p><strong>Known bugs and limitations in this dataset or the associated manuscript.</strong></p> <p>The confluence of the Missouri River and the Upper Mississippi River upstream of Saint Louis, MO was overlooked.&nbsp; The contribution from the Missouri River is therefore not accounted for in the network connectivity corresponding to the Upper Mississippi River Basin.&nbsp; This has no effect on the conclusions of David et al. (2011) since the Upper Mississippi River Basin was studied with synthetic data and solely to evaluate parallel performance of RAPID.</p> <p>&nbsp;</p> <p><strong>Funding</strong></p> <p>This work was partially supported by the U.S. National Aeronautics and Space Administration under the Interdisciplinary Science Project NNX07AL79G; by the U.S. National Science Foundation under project EAR-0413265: CUAHSI Hydrologic Information Systems; by Ecole des Mines de Paris, France; and by the American Geophysical Union under a Horton (Hydrology) Research Grant.</p>

opencc-by-4.0Sep 2011View details →
zenodo48/100

Economical routes to size-specific assembly of self-closing structures

<p>This data contains images related to a publication on the self-assembly of DNA origami particles (<a href="https://www.science.org/doi/10.1126/sciadv.ado5979">https://www.science.org/doi/10.1126/sciadv.ado5979</a>). In this work, we conduct self-assembly experiments with various unique subunit types that target two different diameters of tubule structures.</p> <p>We provide image data of tubules that are associated with the probability distributions reported across several figures in the main text. Images of tubules are in the ZIP archives and show the section of tubules we analyzed to produce the probability distributions in the manuscript. Each folder of images has an associated CSV file that relates an image name to the type of tubule that the image was identified as. Tubule types have "m" and "n" values.</p> <p>We provide full tomogram reconstruction data for the multicomponent tubules that are shown in Figure 2 of the main text. In the ZIP archive, each tubule image has two files associated with it: a REC file that contains the tomogram reconstruction data and an MDOC file that contains imaging metadata. REC files can be opened with the open-source software IMOD.</p> <p>We provide raw image data of pitch- and width-controlled tubules that have been labeled with gold nanoparticles. These accompany the representative images in Figure 4 in the main text. (Pitch Controlled 4-color with GNPs.zip, Width Controlled 4-color with GNPs.zip).</p> <p>We provide raw image data of length-controlled tubules. These images accompany Figure 5 in the main text. (Length Controlled Tubule Images.zip)</p> <p><strong>Associated publication citation:</strong></p> <div> <p><span>Thomas E. Videb&aelig;k&nbsp;<em>et al.,&nbsp;</em></span><span>Economical routes to size-specific assembly of self-closing structures. </span><span><em>Sci. Adv. </em></span><span><strong>10</strong>, </span><span>eado5979 </span><span>(2024). </span><span>DOI:<a href="https://doi.org/10.1126/sciadv.ado5979">10.1126/sciadv.ado5979</a></span></p> </div>

opencc-by-4.0Nov 2023View details →
zenodo48/100

Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing (code, data and scripts to reproduce paper results)

<p>This repository contains the data, code, and scripts required to reproduce the results of the paper &quot;Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing&quot; by Daniele De Sensi, Salvatore Di Girolamo and Torsten Hoefler, presented at the 2019 International Conference for High Performance Computing, Networking, Storage, and Analysis.&nbsp;</p> <p>This repository does not contains the code of the library used to automatically tune the routing algorithm, which can be found at http://doi.org/10.5281/zenodo.3372785</p>

opencc-by-4.0Aug 2019View details →
zenodo48/100

Planetary Boundaries Analysis of Low-Carbon Ammonia Production Routes

<p>Dataset associated with the publication "Planetary Boundaries Analysis of Low-Carbon Ammonia Production Routes" by Sebastiano C. D'Angelo, Selene Cobo, Abhinandan Nabera, Antonio J. Mart&iacute;n, Javier P&eacute;rez-Ram&iacute;rez, and Gonzalo Guill&eacute;n-Gos&aacute;lbez,&nbsp;available at&nbsp;<a href="https://doi.org/10.1021/acssuschemeng.1c01915">https://doi.org/10.1021/acssuschemeng.1c01915</a>. The dataset includes the numeric&nbsp;data required to plot all the figures embedded in the main manuscript and in the Supporting&nbsp;Information (SI), as well as the tables presented in the SI converted in a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>LCA-Total</strong>: numerical values associated with the total share of safe operating space for all the assessed control variables of the seven planetary boundaries quantified in the study, for all the considered scenarios. The results are presented for the three different downscaling approaches considered in the study. The global warming impacts for all the scenarios, calculated with the ReCiPe 2016 methodology (hierarchist approach), are here reported, as well.</li> <li><strong>LCA-Breakdown</strong>: numerical values associated with the breakdown of the environmental impacts for the selection of scenarios&nbsp;reported in the main manuscript, for all the assessed control variables.</li> <li><strong>Economics</strong>: numerical values associated with the breakdown of the economic impacts reported in the main manuscript, for all the assessed scenarios.</li> <li><strong>SI-Tables-LCI</strong>: tables reported in the SI associated with the environmental assessment of all the scenarios.</li> <li><strong>SI-Tables-Economics</strong>: tables reported in the SI associated with the economic assessment of all the scenarios.</li> </ul>

opencc-by-4.0Jul 2021View details →
zenodo48/100

Hybridization of Fossil- and CO2-Based Routes for Ethylene Production using Renewable Energy

<p>Dataset associated with the publication &quot;Hybridization of Fossil- and CO<sub>2</sub>-Based Routes for Ethylene Production using Renewable Energy&quot; by Iasonas Ioannou, Sebastiano C. D&#39;Angelo,&nbsp;Antonio J. Mart&iacute;n, Javier P&eacute;rez-Ram&iacute;rez, and Gonzalo Guill&eacute;n-Gos&aacute;lbez,&nbsp;available at&nbsp;<a href="https://doi.org/10.1002/cssc.202001312">https://doi.org/10.1002/cssc.202001312</a>. The dataset includes the numeric&nbsp;data associated with most of the scenarios described in the main manuscript and in the Supporting&nbsp;Information (SI), as well as the tables presented in the main manuscript and in the&nbsp;SI converted in a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>MS-Results</strong>: numerical values associated with the economic and environmental results included in both the main manuscript and the SI, for all the considered scenarios. The results include the total price for the assessed scenarios, with and without externalities, with uncertainty ranges, as well as the environmental results for human health, ecosystems, resources, and global warming potential (GWP).</li> <li><strong>MS-Tables</strong>: table reported in the main manuscript associated with the price and breakeven point of four assessed scenarios dependent on different CO<sub>2</sub> source assumptions.</li> <li><strong>SI-Tables-Economics</strong>: tables reported in the SI associated with the economic assessment of all the scenarios.</li> <li><strong>SI-Tables-LCI</strong>: tables reported in the SI associated with the environmental assessment of all the scenarios.</li> <li><strong>SI-Tables-AdditionalResults</strong>: tables reported in the SI associated with additional results presented in the work.</li> </ul>

opencc-by-4.0Jul 2020View details →
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Neritina snails upstream migrations at the intersection of Rio Mameyes with road PR Route 3 (bridge 1771)

This data set includes N. virginea densities and sizes from two channels in lower Rio Mameyes under PR Route 3 bridge during the upstream migration season Aug-Dec 2000. Microhabitat use (near-bed water velocities and depth) within both channels is also included. Massive migrations in long trails occurring on the sloped concrete embankment of the main channel were also documented during 99 weeks. Individual size from migratory aggregations was measured during selected dates. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

openCC (other)Nov 2023View details →
zenodo44/100

A route to school informational intervention for air pollution exposure reduction

<p>iSCAPE Dataset Reference No. = DS_PD_020</p> <p>Following datasets are gathered during the implementation of route to school intervention study in Antwerp&nbsp;(Belgium)</p> <ol> <li>Introductory Questionnaire Responses</li> <li>Feedback Questionnaire Responses</li> </ol>

opencc-by-4.0Dec 2019View details →
zenodo44/100

Magnetism and anomalous transport in the Weyl semimetal PrAlGe: Possible route to axial gauge fields

<p>The file ManuscriptDataFiles.7z&nbsp;contains the raw experimental data from which the figures&nbsp;are made in the manuscript entitled &quot;Magnetism and anomalous transport in the Weyl semimetal PrAlGe: Possible route to axial gauge fields&quot; that appeared in npj Quantum Materials <strong>5</strong>, 5&nbsp;(2020).</p> <p>Paper Abstract:&nbsp;In magnetic Weyl semimetals, where magnetism breaks time-reversal symmetry, large magnetically sensitive anomalous transport responses are anticipated that could be useful for topological spintronics. The identification of new magnetic Weyl semimetals is therefore in high demand, particularly since in these systems Weyl node configurations may be easily modified using magnetic fields. Here we explore experimentally the magnetic semimetal PrAlGe, and unveil a direct correspondence between easy-axis Pr ferromagnetism and anomalous Hall and Nernst effects. With sizes of both the anomalous Hall conductivity and Nernst effect in good quantitative agreement with first principles calculations, we identify PrAlGe as a system where magnetic fields can connect directly to Weyl nodes via the Pr magnetization. Furthermore, we find the predominantly easy-axis ferromagnetic ground state co-exists with a low density of nanoscale textured magnetic domain walls. We describe how such nanoscale magnetic textures could serve as a local platform for tunable axial gauge fields of Weyl fermions.</p>

opencc-by-4.0Dec 2019View details →
zenodo44/100

Techno-economic sustainability analysis methodology for conversion routes of renewable feedstock resources to bio-based products – case studies

<p>The dataset provides a set of sustainability principles, criteria and indicators for the evaluation of the conversion routes stage of a bio-based product. &nbsp;The selected case studies on the employment of alternative feedstocks and production of the bio-based products are implemented in order to evaluate the proposed methodology. Mass and energy balances for all case studies, estimated techno-economic metrics, cost of externalities and risk assessment results are provided</p>

opencc-by-4.0Apr 2020View details →
zenodo44/100

Hassan #2 Route binaural recording in Duwiqa, Cairo (Egypt), 28-09-2012

<p>&laquo;&nbsp;Mics in the Ears&nbsp;&raquo; binaural experiment in Cairo (Egypt): Vincent Battesti &amp; Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See&nbsp;<a href="https://vbat.org/article831">https://vbat.org/article831</a></p>

opencc-by-4.0Jul 2020View details →
zenodo44/100

Migration Route of Swiss Ring Ouzels with Multi-Sensor Geolocator

<p>This GeoLocator Datapackage contains the raw data for 5 multi-sensor geolocators and 4 light-level geolocators data equipped on Alpine Ring Ouzels (Turdus torquatus alpestris) in Switzerland between 2017-2020. The data has been processed using the GeoPressureR package to produce trajectories for the 5 multi-sensor tags. Code can be found on Github <a href="https://github.com/Rafnuss/migration-route-of-swiss-ring-ouzels">Rafnuss/migration-route-of-swiss-ring-ouzels</a>. The raw data has been used in <a href="https://doi.org/10.1111/jav.02860">10.1111/jav.02860</a></p> <p>&nbsp;</p>

opencc-by-4.0Nov 2024View details →
zenodo44/100

Phlorest phylogeny derived from Grollemund et al. 2015 'Bantu expansion shows habitat alters the route and pace of human dispersals'

<p>Cite the source of the dataset as:</p> <blockquote> <p>Grollemund R, Branford S, Bostoen K, Meade A, Venditti C &amp; Pagel M. 2015. Bantu expansion shows habitat alters the route and pace of human dispersals. Proceedings of the National Academy of Sciences of the USA, 112(43), 13296-13301.</p> </blockquote>

opencc-by-4.0Aug 2023View details →
zenodo44/100

Data archive for journal paper "Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments"

<p>The datasets archived here include data assimilation results presented in the journal paper, "Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments" (https://doi.org/10.1175/JHM-D-22-0198.1). The output was produced by combining land surface modeling (Noah-MP with HYMAP river routing) and Sentinel-1 backscatter data, applying a 1D Ensemble Kalman Filter using the NASA Land Information System. We provide Netcdf daily output files for 6 different experiments</p><p>- OLfd and OLgw: model-only (open-loop, OL) for two different model settings (fd: free drainage and gw: SIMTOP groundwater option)&nbsp;<br>- DASMfd and DASMgw: data assimilation (DA) with soil moisture (SM) updating for two different model settings (fd: free drainage and gw: SIMTOP groundwater option)&nbsp;<br>- DASMLAIfd and DASMLAIgw: data assimilation (DA) with soil moisture (SM) and leaf area index (LAI) updating for two different model settings (fd: free drainage and gw: SIMTOP groundwater option)&nbsp;</p><p>Each experiment directory contains five subdirectories (DAOBS, EnKF, ROUTING, RTM, SURFACEMODEL) with corresponding outputs as described in https://nasa-lis.github.io/LISF/LIS_users_guide/LIS_users_guide.html</p>

opencc-by-4.0Nov 2023View details →
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Hypersonic Transport: 3D Emission Inventory of STRATOFLY-MR3 Fleet Operated on Brussels to Sydney Route in 2075

<p>High-resolution 3D inventories of future hypersonic transport (HST) are compiled for the year 2075, integrating the gaseous engine emissions of a fleet of 200 hydrogen-powered Mach 8 passenger aircraft*. These aircraft are operated once a day for 360 days on a reference route from Brussels (BRU) to Sydney (MYA) with either NO<sub>x</sub>-optimized (ICA**: 114 000 ft; 34.75 km) or H<sub>2</sub>O-optimized (ICA**: 107 500 ft; 32.77 km) flight profiles, derived to minimize environmental impacts in terms of total emissions. The emissions are spatially gridded at a horizontal resolution of 1&deg; in longitude and latitude, with a vertical resolution of 1000 ft, and are temporally accumulated on an annual basis. Note that the 3D emission inventories encompass detailed data on species-specific HST emissions***, fuel burn, and total distance traveled:&nbsp;</p> <ul> <li>Species: NO,&nbsp;H<sub>2</sub>O;&nbsp;H<sub>2</sub></li> <li>Temporal information: 2075; annually</li> <li>Spatial information: 1&deg; x 1&deg; x 1000 ft</li> <li>Data Format: NetCDF</li> </ul> <p>-----------------------------------------------------------------------------------------------------------------------------------------<br>* &nbsp;The hypersonic aircraft concept under consideration is the <a href="https://arc.aiaa.org/doi/abs/10.2514/6.2021-1877">STRATOFLY-MR3</a> vehicle, which was conceptually developed in <br>&nbsp; &nbsp; the framework of the <a href="https://cordis.europa.eu/project/id/769246">H2020 STRATOFLY project</a>.<br>** Initial Cruise Altitude<br>*** with a unit of kg/km<sup>3 </sup>(corrected in v0.2)</p> <p>&nbsp;</p>

opencc-by-4.0Mar 2024View details →
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Tool for the environmental and economic impact assessment of industrial recycling routes for lithium-ion traction batteries

<p>This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).</p> <p>&nbsp;</p> <p>Please send your inquiries regarding the tool to s.bloemeke@tu-braunschweig.de.</p>

opencc-by-4.0Apr 2022View details →
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PaRoutes: a framework for benchmarking retrosynthesis route predictions

<p>PaRoutes is a framework for benchmarking multi-step retrosynthesis methods, i.e. route predictions.</p> <p>It provides:</p> <ul> <li>A curated reaction dataset for building one-step retrosynthesis models</li> <li>Two sets of 10,000 routes</li> <li>Two sets of stock molecules to use as stop-criterion for the search</li> </ul> <p>Homepage:&nbsp;<a href="https://github.com/MolecularAI/PaRoutes">https://github.com/MolecularAI/PaRoutes</a></p>

opencc-by-4.0Feb 2022View details →
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Positions for "First insights into migration routes and nonbreeding sites used by Red-rumped Swallows (Cecropis daurica rufula) breeding in the Iberian Peninsula"

<p><strong>Abstract</strong></p> <p>Using EURING data and geolocation, we describe migration routes and nonbreeding range of Red-rumped Swallows breeding in the Western Palearctic. One bird ringed in southern Spain and recovered in southern Morocco indicates southwestern migration; geolocator data from five birds from central and eastern Iberian Peninsula confirm migration to various nonbreeding sites in sub-Saharan west Africa between Senegal/Mauritania and Ghana. Two swallows showed non-breeding site itinerancy by using more than one nonbreeding site per season. Despite wide ranges in departure for autumn (August- October) and spring migration (February-March), all birds arrived at nonbreeding and breeding sites within &plusmn;1-week from each other.</p> <p><strong>Zusammenfassung</strong></p> <p>Erste Einblicke in Zugrouten und &Uuml;berwinterungsgebiete von R&ouml;telschwalben (<em>Cecropis daurica rufula</em>) der Iberischen Halbinsel.<br> In dieser Studie beschreiben wir Zugrouten und &Uuml;berwinterungsgebiete westpal&auml;arktischer R&ouml;telschwalben basierend auf EURING- und Geolokations-Daten. Eine R&ouml;telschwalbe, die in S&uuml;dspanien beringt und im s&uuml;dlichen Marokko wiedergefunden wurde, spricht f&uuml;r einen s&uuml;dwestlichen Zug. Geolokalisation von f&uuml;nf V&ouml;geln der zentralen und &ouml;stlichen Iberischen Halbinsel zeigen &Uuml;berwinterungsorte im sub-Saharischen Westafrika zwischen Senegal/Mauretanien und Ghana. Zwei der getrackten R&ouml;telschwalben nutzten mehrere &Uuml;berwinterungspl&auml;tze pro Saison. Trotz der gro&szlig;en Schwankungsbreite der Abzugszeiten im Herbst (August-Oktober) und im Fr&uuml;hjahr (Februar-M&auml;rz) erreichten die getrackten V&ouml;gel ihre Nichtbrut- bzw. Brutpl&auml;tze innerhalb von 1&ndash;2&nbsp;Wochen.</p>

opencc-by-4.0Aug 2022View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record