cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc24vcjx
title: CCDC 1991549: Experimental Crystal Structure Determination

description: Related Article: Ramandeep Kaur,  Sajal Sen,  Mads Christian Larsen,  Luciana Tavares,  Jakob Kjelstrup-Hansen,  Masatoshi Ishida,  Anna Zieleniewska,  Vincent M. Lynch,  Steffen Bähring,  Dirk M. Guldi,  Jonathan L. Sessler,  Atanu Jana|2020|J.Am.Chem.Soc.|142|11497|doi:10.1021/jacs.0c03699
DOI: 10.25345/c55740
title: MassIVE MSV000085828 - GNPS SAR-2-Dereplication Cylindrocarpon extract
title: Fungi extract from fermentation with salt additives.
DOI: 10.5281/zenodo.3960321
title: Supporting information for a rapid gamma-ray flux reduction paper

description: Supporting data and information needed to reproduce the described in the paper results and conclusions.
DOI: 10.5281/zenodo.3960320
title: Supporting information for a rapid gamma-ray flux reduction paper

description: Supporting data and information needed to reproduce the described in the paper results and conclusions.
DOI: 10.5281/zenodo.3952557
title: WACA WiFi 5-GHz dataset

description: This folder contains the dataset presented in "<em>Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)</em>". Please, refer to the GitHub repository for more details:<br> https://github.com/sergiobarra/WACA_WiFiAnalyzer -------------------------------------------------------------<br> <strong>*** Dataset structure ***</strong><br> The dataset is composed of 11 scenarios, each with a corresponding folder (campaign duration within brackets): 1_RVA: Rice Village Apartments, Houston; Apartment; 15th February 2019; 9600 iterations (~1 day) 2_RNG: Rice Networks Group, Houston; Campus office; 19th February 2019; 8750 iterations (~1 day) 3_TFA: Technology for All, Houston; Community center; 20th February 2019; 8609 iterations (~1 day) 4_FLO: Flo Paris (at Rice Village), Houston; Cafe; 23rd February 2019; 413 iterations (~1 hour) 5_VIL: Rice Village parking lot, Houston; Shopping mall; 23rd February 2019; 125 iterations (~20 min) 6_FEL: La Sagrera neighborhood, Barcelona; Apartment; 25th March 2019; 59500 iterations (~1 week) 7_WNO: Wireless Networking, Barcelona; Campus office; 3rd April 2019; 9600 iterations (~1 day) 8_22A: 22@ neighborhood, Barcelona; Office area; 2nd July 2019; 9600 iterations (~1 day) 9_GAL: Hotel Gallery, Barcelona; Downtown hotel; 10th July 2019; 9706 iterations (~1 day) 10_SAG: Sagrada Familia, Barcelona; Apartment; 11th February 2019; 38192 iterations (~4 days) 11_FCB: Camp Nou stadium, Barcelona; Futbol (soccer) Stadium; 4th August; 2001 iterations (~ 5 hours) <strong>*** File format ***</strong> RSSI measurements are stored in .mat files inside each scenario folder. .mat files are named "it&lt;iteration number&gt;_&lt;mm-dd-yy&gt;_&lt;hh:mm:ss&gt;.mat". For instance file "it0251_02-19-19_08-03-09.mat" refers to iteration number 251, initiated on 19th February 2019 at 08:03:09. Every .mat file contains 24 arrays 10000x1, one per basic channel, where the <em>i</em>th element represents the RSSI value at sample <em>i </em>(of duration 10 microseconds) inside the iteration (of duration 1 second). The RSSI value is given in the units of the MAX2829 transceiver (10-bit values). Please, refer to the transceiver datasheet or to our GitHub repository to see how to convert from 10-bit values to dBm. Finally, every scenario folder also contains the "experiment_general.mat". This file is auxiliary and contains different constants of interest related to the configuration of the campaigns. <strong>*** How do I process the dataset? ***</strong><br> We provide the RSSI measurements for every channel in every scenario. You may generate a Matlab snippet to process the data.<br> Nevertheless, the Matlab code we used in the paper "<em>Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)</em>" can be found in the GitHub repository.
description: {"references": ["Sergio Barrachina-Mu\u00f1oz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020) (in press)"]}
DOI: 10.5281/zenodo.3952556
title: WACA WiFi 5-GHz dataset

description: This folder contains the dataset presented in "<em>Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)</em>". Please, refer to the GitHub repository for more details:<br> https://github.com/sergiobarra/WACA_WiFiAnalyzer -------------------------------------------------------------<br> <strong>*** Dataset structure ***</strong><br> The dataset is composed of 11 scenarios, each with a corresponding folder (campaign duration within brackets): 1_RVA: Rice Village Apartments, Houston; Apartment; 15th February 2019; 9600 iterations (~1 day) 2_RNG: Rice Networks Group, Houston; Campus office; 19th February 2019; 8750 iterations (~1 day) 3_TFA: Technology for All, Houston; Community center; 20th February 2019; 8609 iterations (~1 day) 4_FLO: Flo Paris (at Rice Village), Houston; Cafe; 23rd February 2019; 413 iterations (~1 hour) 5_VIL: Rice Village parking lot, Houston; Shopping mall; 23rd February 2019; 125 iterations (~20 min) 6_FEL: La Sagrera neighborhood, Barcelona; Apartment; 25th March 2019; 59500 iterations (~1 week) 7_WNO: Wireless Networking, Barcelona; Campus office; 3rd April 2019; 9600 iterations (~1 day) 8_22A: 22@ neighborhood, Barcelona; Office area; 2nd July 2019; 9600 iterations (~1 day) 9_GAL: Hotel Gallery, Barcelona; Downtown hotel; 10th July 2019; 9706 iterations (~1 day) 10_SAG: Sagrada Familia, Barcelona; Apartment; 11th February 2019; 38192 iterations (~4 days) 11_FCB: Camp Nou stadium, Barcelona; Futbol (soccer) Stadium; 4th August; 2001 iterations (~ 5 hours) <strong>*** File format ***</strong> RSSI measurements are stored in .mat files inside each scenario folder. .mat files are named "it&lt;iteration number&gt;_&lt;mm-dd-yy&gt;_&lt;hh:mm:ss&gt;.mat". For instance file "it0251_02-19-19_08-03-09.mat" refers to iteration number 251, initiated on 19th February 2019 at 08:03:09. Every .mat file contains 24 arrays 10000x1, one per basic channel, where the <em>i</em>th element represents the RSSI value at sample <em>i </em>(of duration 10 microseconds) inside the iteration (of duration 1 second). The RSSI value is given in the units of the MAX2829 transceiver (10-bit values). Please, refer to the transceiver datasheet or to our GitHub repository to see how to convert from 10-bit values to dBm. Finally, every scenario folder also contains the "experiment_general.mat". This file is auxiliary and contains different constants of interest related to the configuration of the campaigns. <strong>*** How do I process the dataset? ***</strong><br> We provide the RSSI measurements for every channel in every scenario. You may generate a Matlab snippet to process the data.<br> Nevertheless, the Matlab code we used in the paper "<em>Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)</em>" can be found in the GitHub repository.
description: {"references": ["Sergio Barrachina-Mu\u00f1oz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020) (in press)"]}
DOI: 10.5519/qd.1mux6uet
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (77 records)
DOI: 10.5281/zenodo.3960339
title: Hydrological Data for "Après nous, le déluge: A human-triggered jökulhlaup from a subglacial lake"

description: Hydrological Data for the manuscript "Après nous, le déluge: A human-triggered jökulhlaup from a subglacial lake", submitted to Geophysical Research Letters. See the README.txt file for file formats, descriptions, and references.
DOI: 10.5281/zenodo.3960338
title: Hydrological Data for "Après nous, le déluge: A human-triggered jökulhlaup from a subglacial lake"

description: Hydrological Data for the manuscript "Après nous, le déluge: A human-triggered jökulhlaup from a subglacial lake", submitted to Geophysical Research Letters. See the README.txt file for file formats, descriptions, and references.
DOI: 10.5519/qd.9gypfikw
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (12 records)
DOI: 10.5281/zenodo.3960029
title: WACA WiFi 5-GHz dataset (Camp Nou only)

description: This folder contains <strong>ONLY</strong> the Camp Nou campaign included in the dataset presented in "<em>Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)</em>". Please, refer to the GitHub repository for more details:<br> https://github.com/sergiobarra/WACA_WiFiAnalyzer -------------------------------------------------------------<br> <strong>*** Dataset structure ***</strong><br> The dataset is composed of 11 scenarios, each with a corresponding folder (campaign duration within brackets):<br> - 1_RVA: Rice Village Apartments, Houston; Apartment; 15th February 2019; 9600 iterations (~1 day)<br> - 2_RNG: Rice Networks Group, Houston; Campus office; 19th February 2019; 8750 iterations (~1 day)<br> - 3_TFA: Technology for All, Houston; Community center; 20th February 2019; 8609 iterations (~1 day)<br> - 4_FLO: Flo Paris (at Rice Village), Houston; Cafe; 23rd February 2019; 413 iterations (~1 hour)<br> - 5_VIL: Rice Village parking lot, Houston; Shopping mall; 23rd February 2019; 125 iterations (~20 min)<br> - 6_FEL: La Sagrera neighborhood, Barcelona; Apartment; 25th March 2019; 59500 iterations (~1 week)<br> - 7_WNO: Wireless Networking, Barcelona; Campus office; 3rd April 2019; 9600 iterations (~1 day)<br> - 8_22A: 22@ neighborhood, Barcelona; Office area; 2nd July 2019; 9600 iterations (~1 day)<br> - 9_GAL: Hotel Gallery, Barcelona; Downtown hotel; 10th July 2019; 9706 iterations (~1 day)<br> - 10_SAG: Sagrada Familia, Barcelona; Apartment; 11th February 2019; 38192 iterations (~4 days)<br> <em><strong>- 11_FCB: Camp Nou stadium, Barcelona; Futbol (soccer) Stadium; 4th August; 2001 iterations (~ 5 hours)</strong></em> <strong>*** File format ***</strong><br> - RSSI measurements are stored in .mat files inside each scenario folder.<br> - .mat files are named "it&lt;iteration number&gt;_&lt;mm-dd-yy&gt;_&lt;hh:mm:ss&gt;.mat". For instance file "it0251_02-19-19_08-03-09.mat" refers to iteration number 251, initiated on 19th February 2019 at 08:03:09.<br> - Every .mat file contains 24 arrays 10000x1, one per basic channel, where the ith element represents the RSSI value at sample i (of duration 10 microseconds) inside the iteration (of duration 1 second).<br> - The RSSI value is given in the units of the MAX2829 transceiver (10-bit values). Please, refer to the transceiver datasheet or to our GitHub repository to see how to convert from 10-bit values to dBm.<br> - Finally, every scenario folder also contains the "experiment_general.mat". This file is auxiliary and contains different constants of interest related to the configuration of the campaigns. <strong>*** How do I process the dataset? ***</strong><br> We provide the RSSI measurements for every channel in every scenario. You may generate a Matlab snippet to process the data. Nevertheless, the Matlab code we used in the paper "Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)" can be found in the GitHub repository.
DOI: 10.5281/zenodo.3960028
title: WACA WiFi 5-GHz dataset (Camp Nou only)

description: This folder contains <strong>ONLY</strong> the Camp Nou campaign included in the dataset presented in "<em>Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)</em>". Please, refer to the GitHub repository for more details:<br> https://github.com/sergiobarra/WACA_WiFiAnalyzer -------------------------------------------------------------<br> <strong>*** Dataset structure ***</strong><br> The dataset is composed of 11 scenarios, each with a corresponding folder (campaign duration within brackets):<br> - 1_RVA: Rice Village Apartments, Houston; Apartment; 15th February 2019; 9600 iterations (~1 day)<br> - 2_RNG: Rice Networks Group, Houston; Campus office; 19th February 2019; 8750 iterations (~1 day)<br> - 3_TFA: Technology for All, Houston; Community center; 20th February 2019; 8609 iterations (~1 day)<br> - 4_FLO: Flo Paris (at Rice Village), Houston; Cafe; 23rd February 2019; 413 iterations (~1 hour)<br> - 5_VIL: Rice Village parking lot, Houston; Shopping mall; 23rd February 2019; 125 iterations (~20 min)<br> - 6_FEL: La Sagrera neighborhood, Barcelona; Apartment; 25th March 2019; 59500 iterations (~1 week)<br> - 7_WNO: Wireless Networking, Barcelona; Campus office; 3rd April 2019; 9600 iterations (~1 day)<br> - 8_22A: 22@ neighborhood, Barcelona; Office area; 2nd July 2019; 9600 iterations (~1 day)<br> - 9_GAL: Hotel Gallery, Barcelona; Downtown hotel; 10th July 2019; 9706 iterations (~1 day)<br> - 10_SAG: Sagrada Familia, Barcelona; Apartment; 11th February 2019; 38192 iterations (~4 days)<br> <em><strong>- 11_FCB: Camp Nou stadium, Barcelona; Futbol (soccer) Stadium; 4th August; 2001 iterations (~ 5 hours)</strong></em> <strong>*** File format ***</strong><br> - RSSI measurements are stored in .mat files inside each scenario folder.<br> - .mat files are named "it&lt;iteration number&gt;_&lt;mm-dd-yy&gt;_&lt;hh:mm:ss&gt;.mat". For instance file "it0251_02-19-19_08-03-09.mat" refers to iteration number 251, initiated on 19th February 2019 at 08:03:09.<br> - Every .mat file contains 24 arrays 10000x1, one per basic channel, where the ith element represents the RSSI value at sample i (of duration 10 microseconds) inside the iteration (of duration 1 second).<br> - The RSSI value is given in the units of the MAX2829 transceiver (10-bit values). Please, refer to the transceiver datasheet or to our GitHub repository to see how to convert from 10-bit values to dBm.<br> - Finally, every scenario folder also contains the "experiment_general.mat". This file is auxiliary and contains different constants of interest related to the configuration of the campaigns. <strong>*** How do I process the dataset? ***</strong><br> We provide the RSSI measurements for every channel in every scenario. You may generate a Matlab snippet to process the data. Nevertheless, the Matlab code we used in the paper "Sergio Barrachina-Muñoz, Boris Bellalta, and Edward Knightly. 2020. Wi-Fi All-Channel Analyzer. WinTech (2020)" can be found in the GitHub repository.
DOI: 10.5281/zenodo.3960362
title: Preadolescents' Healthy Eating Behavior: Peeping Through the Social Norms Approach

description: This is the data set used to execute calculations made for the publication titled "Preadolescents’ Healthy Eating Behavior: Peeping Through the Social Norms Approach" published in BMC Public Health.
DOI: 10.21227/j1dz-vq94
title: Influence and compensation of temperature effects for damage detection and localization in aerospace composites

description: This dataset contains several acquired Lamb Waves from a thermoset matrix composite plate at different temperatures (-40ºC:+50ºC).The dataset corresponds to the article with the same name.
DOI: 10.21227/23md-nr46
title: Influence and compensation of temperature effects for damage detection and localization in aerospace composites

description: This dataset contains several acquired Lamb Waves from a thermoset matrix composite plate at different temperatures (-40ºC:+50ºC).The dataset corresponds to the article with the same name.
DOI: 10.5281/zenodo.3960373
title: Coimbra Mass Movement Files and Feature Data

description: This distribution includes MIDI, MusicXML and PDF files for the anonymous and doubtfully attributed mass movements of the Coimbra Manuscripts, edited by María Elena Cuenca. This distribution also includes the "Renaissance-safe" features extracted by Cory McKay using jSymbolic 2.2 (http://jmir.sourceforge.net) from the MIDI encodings of these Coimbra mass movements, as well as from a secure reference set of Franco-Flemish and Iberian Renaissance mass movements and motets. The MIDI encodings of the latter two datasets cannot be included here due to legal constraints. Those interested in accessing the MIDI files directly should consult The Josquin Research Project (https://josquin.stanford.edu) and The Archive of Iberian Polyphony (https://iberianpolyphony.fcsh.unl.pt), respectively.
description: Version 1.1 now contains MusicXML versions of the Coimbra mass movements, in addition to the MIDI and PDF versions already in Version 1.0.
DOI: 10.5281/zenodo.3732651
title: Coimbra Mass Movement Files and Feature Data

description: This distribution includes MIDI, MusicXML and PDF files for the anonymous and doubtfully attributed mass movements of the Coimbra Manuscripts, edited by María Elena Cuenca. This distribution also includes the "Renaissance-safe" features extracted by Cory McKay using jSymbolic 2.2 (http://jmir.sourceforge.net) from the MIDI encodings of these Coimbra mass movements, as well as from a secure reference set of Franco-Flemish and Iberian Renaissance mass movements and motets. The MIDI encodings of the latter two datasets cannot be included here due to legal constraints. Those interested in accessing the MIDI files directly should consult The Josquin Research Project (https://josquin.stanford.edu) and The Archive of Iberian Polyphony (https://iberianpolyphony.fcsh.unl.pt), respectively.
description: Version 1.1 now contains MusicXML versions of the Coimbra mass movements, in addition to the MIDI and PDF versions already in Version 1.0.
DOI: 10.21227/d7ch-2p14
title: Measurement and Simulation of Human Sitting and Standing Movement Biomechanics

description: Although regenerative actuators can extend the operating durations of robotic lower-limb exoskeletons and prostheses, these energy-efficient powertrains have been exclusively designed and evaluated for continuous level-ground walking. Objective: Here we analyzed the lower-limb joint mechanical power during stand-to-sit movements using inverse dynamic simulations to estimate the biomechanical energy available for electrical regeneration. Methods: Nine subjects performed 20 sitting and standing movements while lower-limb kinematics and ground reaction forces were measured. Subject-specific body segment parameters were estimated using parameter identification, whereby differences in ground reaction forces and moments between the experimental measurements and inverse dynamic simulations were minimized. Joint mechanical power was calculated from net joint torques and rotational velocities and numerically integrated over time to determine joint biomechanical energy. Results: The hip produced the largest peak negative mechanical power (1.8 ± 0.5 W/kg), followed by the knee (0.8 ± 0.3 W/kg) and ankle (0.2 ± 0.1 W/kg). Negative mechanical work from the hip, knee, and ankle joints per stand-to-sit movement were 0.35 ± 0.06 J/kg, 0.15 ± 0.08 J/kg, and 0.02 ± 0.01 J/kg, respectively. Conclusion and Significance: Assuming an 80-kg person and previously published regenerative actuator efficiencies (i.e., maximum 63%), robotic lower-limb exoskeletons and prostheses could theoretically regenerate ~26 Joules of total electrical energy while sitting down, compared to ~19 Joules per walking stride. Given that these regeneration performance calculations are based on healthy young adults, future research should include seniors and/or rehabilitation patients to better estimate the biomechanical energy available for electrical regeneration among individuals with mobilityimpairments.Reference:Laschowski B, Razavian RS, and McPhee J. (2020). Simulation of Stand-to-Sit Biomechanics for Design of Lower-Limb Exoskeletons and Prostheses with Energy Regeneration. Under Review.
DOI: 10.5519/qd.rq1j0jlv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.3960357
title: eeg-workshops/mkpy_data_examples/data

description: EEG data files for eeg-workshops/mkpy_data_examples. For more information see the docs and github source.
DOI: 10.5517/ccdc.csd.cc24w62b
title: CCDC 1992341: Experimental Crystal Structure Determination

description: Related Article: Addison Nole Desnoyer, Amélie Nicolay, Micah S Ziegler, Nicole A Torquato, T. Don Tilley|2020|Angew.Chem.,Int.Ed.|59|12769|doi:10.1002/anie.202004346
DOI: 10.5517/ccdc.csd.cc24w63c
title: CCDC 1992342: Experimental Crystal Structure Determination

description: Related Article: Addison Nole Desnoyer, Amélie Nicolay, Micah S Ziegler, Nicole A Torquato, T. Don Tilley|2020|Angew.Chem.,Int.Ed.|59|12769|doi:10.1002/anie.202004346
DOI: 10.5517/ccdc.csd.cc24w64d
title: CCDC 1992343: Experimental Crystal Structure Determination

description: Related Article: Addison Nole Desnoyer, Amélie Nicolay, Micah S Ziegler, Nicole A Torquato, T. Don Tilley|2020|Angew.Chem.,Int.Ed.|59|12769|doi:10.1002/anie.202004346
DOI: 10.5517/ccdc.csd.cc24w65f
title: CCDC 1992344: Experimental Crystal Structure Determination

description: Related Article: Addison Nole Desnoyer, Amélie Nicolay, Micah S Ziegler, Nicole A Torquato, T. Don Tilley|2020|Angew.Chem.,Int.Ed.|59|12769|doi:10.1002/anie.202004346
DOI: 10.5517/ccdc.csd.cc24w66g
title: CCDC 1992345: Experimental Crystal Structure Determination

description: Related Article: Addison Nole Desnoyer, Amélie Nicolay, Micah S Ziegler, Nicole A Torquato, T. Don Tilley|2020|Angew.Chem.,Int.Ed.|59|12769|doi:10.1002/anie.202004346
DOI: 10.5519/qd.hs9kj0g0
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.34740/kaggle/dsv/1370334
title: Chicago Crime from 01JAN2001 to 22JUL2020
DOI: 10.5281/zenodo.3960180
title: tmp

description: tmp
DOI: 10.5281/zenodo.3960179
title: tmp

description: tmp
DOI: 10.3886/e117206v1-43305
title: Data and Code for: "The New Tools of Monetary Policy"

description: This repository contains data and programs to replicate Tables 1-4 and footnote 18 found in Bernanke (2020) and Tables 5-7 in the Online Appendix. The repository also contains data and programs to run stochastic simulations of alternative monetary policies using the Fed's FRB/US model.
DOI: 10.3886/e119446v18-43306
title: COVID-19 US State Policy Database

description: Database of state policies on closures, shelter-in-place orders, housing protections, changes to Medicaid and SNAP, physical distancing closures, reopening, and more created by researchers at the Boston University School of Public Health. Policies included are state-wide directives or mandates, not guidance or recommendations. In order for a policy to be included, it must apply to the entire state. We are working quickly to go through state government websites to make the policy database as complete and accurate as possible in a rapidly changing policy context. If you use data on a given policy, we encourage you to triangulate based on additional sources of policy data and to review the source documentation to consider the coding decisions that are right for your work. Of course, please email us if you note a discrepancy so we can improve the database for everyone. State policy source documentation can be found at: tinyurl.com/statepolicysources.
description: other; Contributors: Megan Cole Brahim, Noa Krawczyk, Carolyn Hoffman, Claire Corkish, Elizabeth Ferrara, Elizabeth Long, Emily Baroni, Faith Contador, Hannah Simon, Morgan Simko, Rachel Scheckman, Sarah Brewer, Sue Kulkarni, Felicia Heykoop, Manish Patel, Aishwarya Vidyasagaran, Andrew Chiao, Cara Safon, Samantha Burkhart, Harry Jung, Victor Lee, Marina MacKinnon, Aarohi Rede, Marie Vearling, Sophie Li, Christina Wang, Tim Levengood, María Jordán P. Emma Chistolini
description: State policies. Smallest Geographic Unit: State