cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6875770
title: 3-D view of a slope affected by rockfall

description: In the compressed folder, there is a 3-D view of the slope affected by rockfall and its defence nearby the town of Lauria (South Italy) To create a 3-D interactive view of the mitigation works (that can be used with any browser without installing GIS or other software), we used the Qgis2threejs plugin for QGIS. The LiDAR DTM was used as an elevation layer to create several high-resolution 3-D view models with different layers. Rockfall barriers Location of 2002 rockfall Area interested by 2017 wildfire building full Paper Merging Historical Archives with Remote Sensing Data: A Methodology to Improve Rockfall Mitigation Strategy for Small Communities
description: {"references": ["Notti et al., 2021 Merging Historical Archives with Remote Sensing Data: A Methodology to Improve Rockfall Mitigation Strategy for Small Communities"]}
DOI: 10.6084/m9.figshare.21453867
title: Audios_vowel_A_PD

description: <strong>Data Set Information:</strong> Data consist audios of the vowel /a/ recorded for people with Parkinson's disease (EP) and without Parkinson's disease (noEP). There are two folders, one for each type of audios (A_EP_Audios and A_noEP_Audios). The age and gender of each person were also recorded. For EP, the duration of the disease was also recorded. This information can be found in data_information.csv. <br> <strong>Attribute Information:</strong> People are in one of two classes: EP and noEP EP: person with Parkinson desease noEP: person without Parkinson desease Age: age in years Sex: F: female; M: male <br> <strong>Papers referenced to the dataset:</strong> 1- M. Giuliano, D. Adamec, M.I. Debas, “Construcción de una base de voz de personas con y sin enfermedad de Parkinson”, Revista Digital del Departamento de Ingeniería e Investigaciones Tecnológicas de la Universidad Nacional de La Matanza (REDDI), vol. 6-Nro.1, 2021. https://reddi.unlam.edu.ar/index.php/ReDDi/article/view/141/272 <br> 2- M. Giuliano, L. Fernandez S. Pérez. “Selección de Medidas de Disfonía para la Identificación de Enfermos de Parkinson”. Proceedings IEEE Congreso Bienal de Argentina (ARGENCON), 2020, pp. 1-8, doi: 10.1109/ARGENCON49523.2020.9505554 <br> <br> <br>
DOI: 10.5281/zenodo.7272337
title: DATASET: Predicting Protein Function and Orientation on a Gold Nanoparticle Surface Using a Residue-Based Affinity Scale

description: This upload contains data for the manuscript "<strong>Predicting Protein Function and Orientation on a Gold Nanoparticle Surface Using a Residue-Based Affinity Scale</strong>." It contains kinetics data, UV-vis data, surface calculations, and activity assays for the systems described in the manuscript.
DOI: 10.6084/m9.figshare.19486883
title: Metabolomics: Plasticity of the adult human small intestinal microbiota

description: This is the dataset for metabolomic part of the study. It has two dataset. 1st one is for stable stoma patients metabolomic dataset and 2nd one is the bandit cohort where stoma contents were collected for the metabolomics after feeding.
DOI: 10.6084/m9.figshare.19486883.v1
title: Metabolomics: Plasticity of the adult human small intestinal microbiota

description: This is the dataset for metabolomic part of the study. It has two dataset. 1st one is for stable stoma patients metabolomic dataset and 2nd one is the bandit cohort where stoma contents were collected for the metabolomics after feeding.
DOI: 10.48366/r234068
title: Summary of some related work for an integrated sustainability inventory model

description: Energy saving in production processes is one of the main concerns of companies to ensure their competitiveness and sustainability. Solutions to reduce energy consumption in the supply chain have been studied by many authors. In this comparison, we present some relevant recent works dealing with the different problems of inventory management with consideration of sustainability (energy and environmental aspects).
DOI: 10.5281/zenodo.6799997
title: Model Output and Figure Scripts for: "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records"

description: New climate model output and figure scripts for the paper "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records".
DOI: 10.5281/zenodo.7063172
title: Dataset for "Micromechanics and Strain Localization in Sand in the Ductile Regime"

description: This dataset contains tomography images and stress-strain curves used in the publication titled "Micromechanics and Strain Localization in Sand in the Ductile Regime" in the Journal of Geophysical Research: Solid Earth
DOI: 10.5281/zenodo.7063171
title: Dataset for "Micromechanics and Strain Localization in Sand in the Ductile Regime"

description: This dataset contains tomography images and stress-strain curves used in the publication titled "Micromechanics and Strain Localization in Sand in the Ductile Regime" in the Journal of Geophysical Research: Solid Earth
DOI: 10.5281/zenodo.7270829
title: NON-ANESTHESIOLOGIST ADMINISTERED PROPOFOL SEDATION IN SCREENING COLONOSCOPY

description: These data came from a. prospective cohort study about cardiorespiratory complications in colorectal cancer screening colonoscopy, comparing two sedation schemes: traditional sedation with fentanyl and midazolam, versus combined Propofol sedation administered by non-anesthesiologists. These screening colonoscopies were performed between 2018 and 2019. We used the ASA and Ramsay scales to evaluate comorbidities and sedation levels. Cardiopulmonary adverse events were defined as: systolic blood pressure&lt;90 mmHg, oxygen saturation &lt;90% or disrrythmia lasting for more than 60 seconds..We recorded the management and outcomes of all these unplanned events. Other data as age, gender and body mass index were recorded as well., We have stored our data as a csv fyle.
DOI: 10.5281/zenodo.7270830
title: NON-ANESTHESIOLOGIST ADMINISTERED PROPOFOL SEDATION IN SCREENING COLONOSCOPY

description: Data from a. prospective cohort study in colorectal cancer screening colonoscopy comparing traditional sedation with fentanyl and midazolam, versus combined Propofol sedation administered by non-anesthesiologists. These colonoscopies were performed between 2018 and 2019. We used the ASA and Ramsay scales for comorbidities and sedation levels. Cardiopulmonary adverse events were defined as: systolic blood pressure&lt;90 mmHg, oxygen saturation &lt;90% or disrrythmia lasting for more than 60 seconds..We recorded as well the management and outcomes of all these events.
DOI: 10.5281/zenodo.7271370
title: NON-ANESTHESIOLOGIST ADMINISTERED PROPOFOL SEDATION IN SCREENING COLONOSCOPY

description: These data came from a. prospective cohort study about cardiorespiratory complications in colorectal cancer screening colonoscopy, comparing two sedation schemes: traditional sedation with fentanyl and midazolam, versus combined Propofol sedation administered by non-anesthesiologists. These screening colonoscopies were performed between 2018 and 2019. We used the ASA and Ramsay scales to evaluate comorbidities and sedation levels. Cardiopulmonary adverse events were defined as: systolic blood pressure&lt;90 mmHg, oxygen saturation &lt;90% or disrrythmia lasting for more than 60 seconds..We recorded the management and outcomes of all these unplanned events. Other data as age, gender and body mass index were recorded as well., We have stored our data as a csv fyle.
DOI: 10.6084/m9.figshare.15157965
title: Data and code for: Nutrients and consumers impact tree colonization differently from growth in a successional old field

description: Data and code used for analyses in the manuscript "Nutrients and consumers impact tree colonization differently from growth in a successional old field"
DOI: 10.5281/zenodo.7272435
title: tmp us image test

description: tmp us image test
DOI: 10.5281/zenodo.7272434
title: tmp us image test

description: tmp us image test
DOI: 10.15131/shef.data.21400008
title: Burst Random Amplitude Ramp : 0.4V Repetition 1

description: First repetition for burst random (white noise) excitation at 0.4V LMS output voltage. This test is performed on the starboard wing of the BAE T1A Hawk housed at the Labratory for Verification and Validation (lvv.ac.uk). The wing is excited using a single shaker and data is recorded using 55 uni-accelerometers and the excitation load cell. <br> The significance of the naming conventions is explained in the "ORDA_Readme.pdf" file. This file also contains the code needed to load the files into python for analysis. The testing parameters is stored is the "BR_AR_1_test_info.pickle" file. The data is separated into one pickle file per accelerometer. These files contain both time and frequency information with more details in the readme file. <br> This test was performed under the Alan Turing Institute funded project <em>Digital Twins for High-Value Engineering Systems (DTHIVE)</em> with continuing support from the EPSRC funded project <em>Digital Twins for Improved Dynamic Design (DigiTwin)</em>. For more information, please contact the PI, Professor David Wagg.
DOI: 10.15131/shef.data.21400008.v1
title: Burst Random Amplitude Ramp : 0.4V Repetition 1

description: First repetition for burst random (white noise) excitation at 0.4V LMS output voltage. This test is performed on the starboard wing of the BAE T1A Hawk housed at the Labratory for Verification and Validation (lvv.ac.uk). The wing is excited using a single shaker and data is recorded using 55 uni-accelerometers and the excitation load cell. <br> The significance of the naming conventions is explained in the "ORDA_Readme.pdf" file. This file also contains the code needed to load the files into python for analysis. The testing parameters is stored is the "BR_AR_1_test_info.pickle" file. The data is separated into one pickle file per accelerometer. These files contain both time and frequency information with more details in the readme file. <br> This test was performed under the Alan Turing Institute funded project <em>Digital Twins for High-Value Engineering Systems (DTHIVE)</em> with continuing support from the EPSRC funded project <em>Digital Twins for Improved Dynamic Design (DigiTwin)</em>. For more information, please contact the PI, Professor David Wagg.
DOI: 10.5281/zenodo.7272038
title: Wallops SuperDARN data in netCDF format (2022-Oct)

description: 2022-Oct Wallops SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7272039
title: Wallops SuperDARN data in netCDF format (2022-Oct)

description: 2022-Oct Wallops SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.26188/21435219
title: LC-MS raw data

description: Raw data for liquid chromatography coupled with mass spectrometry (LC-MS) experiments along with skyline template used to extract peak area from raw data.
DOI: 10.6084/m9.figshare.21453984
title: Dataset 1.sav

description: This is the raw data that I used to research my latest artice.
DOI: 10.26188/21435204.v1
title: Extended data

description: Extended data for <strong>Entry of the antipsychotic drug, olanzapine, into the developing rat brain in mono- and combination therapies</strong> containing: - Tables of numerical values for each figure - Supplementary figures
DOI: 10.26188/21435204
title: Extended data

description: Extended data for <strong>Entry of the antipsychotic drug, olanzapine, into the developing rat brain in mono- and combination therapies</strong> containing: - Tables of numerical values for each figure - Supplementary figures
DOI: 10.26188/21435102
title: Liquid scintillation counting raw data

description: Liquid scintillation counting raw data containing CPM, DPM, weight for all samples as well as sex of all animals used in: - Olanzapine monotherapy - Olanzapine combination therapy <br> <br>
DOI: 10.26188/21435102.v1
title: Liquid scintillation counting raw data

description: Liquid scintillation counting raw data containing CPM, DPM, weight for all samples as well as sex of all animals used in: - Olanzapine monotherapy - Olanzapine combination therapy <br> <br>
DOI: 10.6084/m9.figshare.21454002
title: mtDNA alignment

description: mtDNA alignment
DOI: 10.5281/zenodo.7265771
title: Base de datos violencia y dependencia emocional

description: Base de datos en cuanto a las variables violencia y dependencia emocional a través de un mapeo sistemático.<br> Investigaciones recogidas desde el año 2020-2022.
DOI: 10.5281/zenodo.7265770
title: Base de datos violencia y dependencia emocional

description: Base de datos en cuanto a las variables violencia y dependencia emocional a través de un mapeo sistemático.<br> Investigaciones recogidas desde el año 2020-2022.
DOI: 10.5281/zenodo.7264508
title: Primers for whole genome sequencing of the Sars-Cov-2 virus

description: Here is the primer sequence for amplification and sequencing of the whole genome of the Sars-Cov-2 virus.
DOI: 10.5281/zenodo.7264509
title: Primers for whole genome sequencing of the Sars-Cov-2 virus

description: Here is the primer sequence for amplification and sequencing of the whole genome of the Sars-Cov-2 virus.
DOI: 10.3886/e129241v1-130324
title: Data and code for: Network Externality and Subsidy Structure in Two-Sided Markets: Evidence from Electric Vehicle Incentives

description: This paper uses new, large-scale vehicle registry data from Norway and a two-sided market framework to show non-neutrality of different subsidies and estimate their impact on electric vehicle adoption when network externalities are present. Estimates suggest a strong positive connection between electric vehicle purchases and both consumer price and charging station subsidies. Counterfactual analyses suggest that between 2010 and 2015 every dollar spent on station subsidies resulted in more than twice as many additional electric vehicle purchases than the same amount spent on price subsidies. However, this relation inverts with increased spending, as station subsidies’ impact tapers off faster. <br>
DOI: 10.25573/serc.20060663
title: 2020 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2020 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060663.v2
title: 2020 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2020 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060663.v1
title: 2020 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2020 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060660
title: 2021 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2021 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060660.v2
title: 2021 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2021 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060660.v1
title: 2021 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2021 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060657.v4
title: 2022 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.25573/serc.20060657.v3
title: 2022 Meteorological Data, Upper Chesapeake Bay, MarineGEO, Smithsonian Environmental Research Center

description: 2022 meteorological data collected on WXT536, PTB110, and LI-190R instrumentation at the MarineGEO Upper Chesapeake Bay observatory (Smithsonian Environmental Research Center, Edgewater, MD, USA). Location: 38.886928, -76.540172
DOI: 10.5517/ccdc.csd.cc27dlpy
title: CCDC 2067690: Experimental Crystal Structure Determination

description: Related Article: Lu Shang, Xiao-Li Chen, Lu Liu, Miao Cai, Rui-Kui Yan, Hua-Li Cui, Hua Yang, Ji-Jiang Wang|2022|J. CO2 Utilization|65|102235|doi:10.1016/j.jcou.2022.102235
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27dlqz
title: CCDC 2067691: Experimental Crystal Structure Determination

description: Related Article: Lu Shang, Xiao-Li Chen, Lu Liu, Miao Cai, Rui-Kui Yan, Hua-Li Cui, Hua Yang, Ji-Jiang Wang|2022|J. CO2 Utilization|65|102235|doi:10.1016/j.jcou.2022.102235
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27qcgt
title: CCDC 2077076: Experimental Crystal Structure Determination

description: Related Article: Samuel H. Newman-Stonebraker, Jason Y. Wang, Philip D. Jeffrey, Abigail G. Doyle|2022|J.Am.Chem.Soc.|144|19635|doi:10.1021/jacs.2c09840
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25952/6bvk-gh27
title: Problematising sustainability in nature play programs

description: The data set consists of 4 Parts. Part 1: 14 transcripts of individual interviews and focus group interviews. Part 2: Interview questions for 3 individual interviews x 2 participants and 2 focus groups. Part 3;  4 photos used for photo elicitation. Part 4: Researcher Reflective Journals.
description: The data set consists of 4 Parts. Part 1: 14 transcripts of individual interviews and focus group interviews. Part 2: Interview questions for 3 individual interviews x 2 participants and 2 focus groups. Part 3;  4 photos used for photo elicitation. Part 4: Researcher Reflective Journals.
DOI: 10.5517/ccdc.csd.cc27qckx
title: CCDC 2077079: Experimental Crystal Structure Determination

description: Related Article: Samuel H. Newman-Stonebraker, Jason Y. Wang, Philip D. Jeffrey, Abigail G. Doyle|2022|J.Am.Chem.Soc.|144|19635|doi:10.1021/jacs.2c09840
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29jd2b
title: CCDC 2130911: Experimental Crystal Structure Determination

description: Related Article: Fengbiao Luo, Hao Dong, Weiwu Ren, Yang Wang|2022|Org.Lett.|24|7727|doi:10.1021/acs.orglett.2c02874
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bljvb
title: CCDC 2162772: Experimental Crystal Structure Determination

description: Related Article: Mei-Jun Zhu, Rong Ye, Wen-Jing Shi, Jing Sun, Chao-Guo Yan|2022|Tetrahedron Lett.|110|154186|doi:10.1016/j.tetlet.2022.154186
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.