cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34808/18a8-7q15
title: Morse decompositions for a two-dimensional discrete neuron model (limited range)

description: This dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
The parameter space a=0.89, b∊[0,1], c=0.28, k∊[0.015,0.030] was sampled at the resolution of 200×75. The phase space [−0.1,9] × [−5,3] was sampled at the resolution of 1024×1024. A collection of isolating neighborhoods that enclose Morse sets in a Morse decomposition was computed for each box of parameters, and a Conley-Morse graph was determined, with the Conley indices of the Morse sets computed where feasible. Clutching graphs between Morse decompositions found for adjacent boxes were also computed, and the parameter space was subdivided into classes of equivalent Morse decompositions, as described in the paper.
The dataset contains the Morse decompositions found for all the parameter boxes. A collection of combinatorial Morse sets, that is, isolating neighborhoods of the actual Morse sets in each Morse decomposition, is encoded in terms of a PNG image. In this image, a single pixel corresponds to a square in the phase space. All the images are compressed together in the zipped archive file. The name of each file is in the format "pn_m.png", where n,m are the integer coordinates of the parameter box, both starting with 0. Each combinatorial Morse set comprises of a collection of pixels drawn in a specific color. The colors used for the consecutive sets are listed at the bottom of the image as squares: black, blue, red, green, etc. The order is the same as in the corresponding Conley-Morse graphs available in a separate dataset.
An interactive browser of all the Conley-Morse graphs and phase space portraits of the Morse decompositions provided in the current series of datasets is available at the address https://www.pawelpilarczyk.com/neuron/.
DOI: 10.34808/5b59-ha87
title: Conley-Morse graphs for a two-dimensional discrete neuron model (low resolution)

description: This dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
The parameter space a=0.89, b∊[0,0.5], c=0.28, k∊[0.017,0.027] was sampled at the resolution of 200×50. The phase space [−0.1,7.5] × [−1.3,2.7] was sampled at the resolution of 256×256. A collection of isolating neighborhoods that enclose Morse sets in a Morse decomposition was computed for each box of parameters, and a Conley-Morse graph was determined, with the Conley indices of the Morse sets computed where feasible. Clutching graphs between Morse decompositions found for adjacent boxes were also computed, and the parameter space was subdivided into classes of equivalent Morse decompositions, as described in the paper.
The dataset contains the Conley-Morse graphs computed for all the parameter boxes. Each graph is encoded in the text format compatible with the "dot" program from the Graphviz Graph Visualization Software package (https://graphviz.org/). All the text files are compressed together in the zipped archive file. The name of each file is in the format "gn_m.txt", where n,m are the integer coordinates of the box, both starting with 0. For example, in order to obtain a PDF file with the visualization of the graph contained in the file "g12_0.txt" one could run the command "dot g12_0.txt -T pdf -o g12_0.pdf". Each node of the graph contains the information on the corresponding isolating neighborhood of a Morse set: the consecutive number of the neighborhood (starting with 0), the number of boxes comprising the neighborhood, and if a Conley index pair was constructed successfully then additionally the homology of the index pair, followed by the index map at each homology level, and the eigenvalues of the map at each homology level. The nodes have different shapes and colors for easy visual identification of the set type; for example, a yellow box indicates an attractor, and a cyan-filled oval stands for an isolating neighborhood with a non-trivial exit set. The directed edges between the nodes show direct connections between the sets (the transitive reduction should be taken for the full set of possible connections).
An interactive browser of all the Conley-Morse graphs and phase space portraits of the Morse decompositions provided in the current series of datasets is available at the address https://www.pawelpilarczyk.com/neuron/.
DOI: 10.5281/zenodo.7540559
title: Resilience indicators used in the multidimensional characterization of the resilience of urban areas prone to flash floods in the region of Castilla y León (Spain)

description: Database containing resilience indicators used in the characterization of all dimensions of resilience (social, economic, ecosystemic, physical, institutional and cultural) in those municipalities susceptible to flash floods in the region of Castilla y León (Spain). The database includes a total of 191 resilience indicators, of which 48 correspond to social resilience, 32 to economic resilience, 34 to ecosystem resilience, 44 to physical resilience, 27 to institutional resilience and 6 to cultural resilience. The Excel (.xlsx) file is organized by dimensions, where the prefix "SOC_" corresponds to the social dimension, "ECON_" to the economic dimension, "ECOS_" to the ecosystemic dimension, "PHY_" to the physical dimension, "INS_" to the institutional dimension and "CUL_" to the cultural dimension. Each dimension of resilience occupies two tabs: the first tab (suffixes "_data") contains the description of the indicators included (i.e., indicator code, unit of measurement, year of information, source of information, direct link to the information and bibliographic references that support the consideration of the different indicators); while the second tab (suffixes "_variables") contains the values of the different indicators (identified by their codes, which appear in the first tab) for each unit of analysis.
DOI: 10.5281/zenodo.7540558
title: Resilience indicators used in the multidimensional characterization of the resilience of urban areas prone to flash floods in the region of Castilla y León (Spain)

description: Database containing resilience indicators used in the characterization of all dimensions of resilience (social, economic, ecosystemic, physical, institutional and cultural) in those municipalities susceptible to flash floods in the region of Castilla y León (Spain). The database includes a total of 191 resilience indicators, of which 48 correspond to social resilience, 32 to economic resilience, 34 to ecosystem resilience, 44 to physical resilience, 27 to institutional resilience and 6 to cultural resilience. The Excel (.xlsx) file is organized by dimensions, where the prefix "SOC_" corresponds to the social dimension, "ECON_" to the economic dimension, "ECOS_" to the ecosystemic dimension, "PHY_" to the physical dimension, "INS_" to the institutional dimension and "CUL_" to the cultural dimension. Each dimension of resilience occupies two tabs: the first tab (suffixes "_data") contains the description of the indicators included (i.e., indicator code, unit of measurement, year of information, source of information, direct link to the information and bibliographic references that support the consideration of the different indicators); while the second tab (suffixes "_variables") contains the values of the different indicators (identified by their codes, which appear in the first tab) for each unit of analysis.
DOI: 10.5281/zenodo.7540400
title: Data for Sleep cycle-dependent vascular dynamics and the predicted effects on perivascular cerebrospinal fluid flow and solute transport

description: Datasets containing derived data and results used by code in: https://github.com/AlexandraVallet/PVSflow for "Sleep cycle-dependent vascular dynamics and the predicted effects on perivascular cerebrospinal fluid flow and solute transport", Bojarskaite et al. 2023. Please see github for instructions.
DOI: 10.34740/kaggle/dsv/4859296
title: 2021 World Population (updated daily)
DOI: 10.7294/21899328
title: South Carolina Results of the Wildlife Viewer Survey

description: Through a 2021 AFWA MultiState Conservation Grant, Virginia Tech and the AFWA Wildlife Viewing and Nature Tourism Working Group conducted national and state level surveys to gather more data on wildlife viewers. This dataset is from the survey conducted in South Carolina. It contains: 1. South Carolina Wildlife Viewer Survey.pdf: a pdf version of the survey instrument 2. South Carolina_WildlifeViewerSurvey.csv: a csv (comma-separated values) file of the dataset 3. South Carolina_WildlifeViewerSurvey.sav: a sav (compatible with SPSS, the Statistical Package for Social Science) file of the dataset 4. WildlifeViewerSurveyData_VariableGuide: a guide to each variable name in the datasets.
DOI: 10.7294/21899328.v1
title: South Carolina Results of the Wildlife Viewer Survey

description: Through a 2021 AFWA MultiState Conservation Grant, Virginia Tech and the AFWA Wildlife Viewing and Nature Tourism Working Group conducted national and state level surveys to gather more data on wildlife viewers. This dataset is from the survey conducted in South Carolina. It contains: 1. South Carolina Wildlife Viewer Survey.pdf: a pdf version of the survey instrument 2. South Carolina_WildlifeViewerSurvey.csv: a csv (comma-separated values) file of the dataset 3. South Carolina_WildlifeViewerSurvey.sav: a sav (compatible with SPSS, the Statistical Package for Social Science) file of the dataset 4. WildlifeViewerSurveyData_VariableGuide: a guide to each variable name in the datasets.
DOI: 10.6084/m9.figshare.21901842.v2
title: Supplimentary Information.docx

description: Data from : A Global Meta-analysis of Cover Crop Response on Soil Carbon Storage Within a Corn Production System
DOI: 10.6084/m9.figshare.21904446
title: Data for Spatial Signatures: Understanding (urban) spaces through form and function

description: The data resulting from the research article published as Arribas-Bel, D. and Fleischmann, M. ‘Spatial Signatures: Understanding (urban) spaces through form and function’ <em>Habitat International</em>, 128, (102641). doi:10.1016/j.habitatint.2022.102641. <br> The complete data for Dar es Salaam and Houston are available upon request due to the file size over the figshare limit (6.8GB and 22GB respectively). The signature delineation is available for all case studies. <br> The code is available at https://github.com/urbangrammarai/spatial_signatures_concept
DOI: 10.5281/zenodo.5940043
title: 2707 water samples from Vallon de Nant analyzed for stable water isotopes (dD, d17O, d18O) and electric conductivity

description: Database gathering 2707 water samples from the Vallon de Nant (Westerm Swiss Alps) analyzed for stable isotopes of water (dD, d17O, d18O, d-excess, LC-excess, 17O-excess) and electric conductivity. The "VDN_database.csv" file includes the following columns:<br> - time [dd/mm/yyyy HH:MM, UTC]<br> - latitude [decimal degrees, WGS84]<br> - longitude [decimal degrees, WGS84]<br> - elevation [masl]<br> - point: point name<br> - dD [‰]<br> - d17O [‰]<br> - d18O [‰]<br> - d-excess [‰]<br> - LC-excess [‰]<br> - 17O-excess [per meg]<br> - conductivity [µS/cm] Water is sampled from:<br> - 2 points of main stream (Avançon de Nant) at HyS1 and HyS2<br> - 5 different springs at GRAS, AUBG, ROCK, BRDG and ICEC<br> - 3 piezometers at PZ1, PZ2 and PZ3<br> - 2 weather stations for rain at Auberge and Chalet<br> - various locations (GPS points) for the Snowpack<br> - various locations (GPS points) for the Glacier The points with regular sampling are shown on the map "VDN_sampling_points.png".
DOI: 10.5281/zenodo.7540709
title: 2707 water samples from Vallon de Nant analyzed for stable water isotopes (dD, d17O, d18O) and electric conductivity

description: Database gathering 2707 water samples from the Vallon de Nant (Westerm Swiss Alps) analyzed for stable isotopes of water (dD, d17O, d18O, d-excess, LC-excess, 17O-excess) and electric conductivity. The "VDN_database.csv" file includes the following columns:<br> - time [dd/mm/yyyy HH:MM, UTC]<br> - latitude [decimal degrees, WGS84]<br> - longitude [decimal degrees, WGS84]<br> - elevation [masl]<br> - point: point name<br> - dD [‰]<br> - d17O [‰]<br> - d18O [‰]<br> - d-excess [‰]<br> - LC-excess [‰]<br> - 17O-excess [per meg]<br> - conductivity [µS/cm] Water is sampled from:<br> - 2 points of main stream (Avançon de Nant) at HyS1 and HyS2<br> - 5 different springs at GRAS, AUBG, ROCK, BRDG and ICEC<br> - 3 piezometers at PZ1, PZ2 and PZ3<br> - 2 weather stations for rain at Auberge and Chalet<br> - various locations (GPS points) for the Snowpack<br> - various locations (GPS points) for the Glacier The points with regular sampling are shown on the map "VDN_sampling_points.png".
DOI: 10.5517/ccdc.csd.cc2d58b6
title: CCDC 2209597: Experimental Crystal Structure Determination

description: Related Article: wenpiao ou, xingkuan chen|2022|CSD Communication|||
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: 10.5281/zenodo.1042472
title: Weather dataset from Vallon de Nant, Switzerland (from 16 August 2016 to 14 October 2018)

description: Weather data collected in the Vallon de Nant, Switzerland from 16 August 2016 to 14 October 2018<br> Data collected by the reasearch team of Bettina Schaefli at the Institute of Earth Surface Dynamics (IDYST), Faculty of Geosciences and Environment, University of Lausanne, Lausanne, 1015, Switzerland for further information, please contact:<br> bettina.schaefli@giub.unibe.ch Grant: SNSF PP00P2\_157611
DOI: 10.5281/zenodo.7540728
title: Weather dataset from Vallon de Nant, Switzerland (from 16 August 2016 to 14 October 2018)

description: Weather data collected in the Vallon de Nant, Switzerland from 16 August 2016 to 14 October 2018<br> Data collected by the reasearch team of Bettina Schaefli at the Institute of Earth Surface Dynamics (IDYST), Faculty of Geosciences and Environment, University of Lausanne, Lausanne, 1015, Switzerland for further information, please contact:<br> bettina.schaefli@giub.unibe.ch Grant: SNSF PP00P2\_157611
DOI: 10.5281/zenodo.5780326
title: Alignments from "Caecilian genomes reveal molecular basis of adaptation and convergent evolution of limblessness in vertebrates"

description: Compressed file containing the alignments at both nucleotide and amino acid level for the manuscript "Caecilian genomes reveal molecular basis of adaptation and convergent evolution of limblessness in vertebrates"
DOI: 10.6084/m9.figshare.21904470
title: Data - oxidative stress and bone turnover markers in obesity.xlsx

description: The data concern the oxidative stress markers (MDA, SOD, GPx, CAT, PON1, vitamin A, vitamin E, uric acid, FRAP) as well as bone turnover markers (P1NP, CTX) in obese patients.
DOI: 10.17028/rd.lboro.21904452
title: Supplementary information files for Russian meddling in U.S. elections: How news of disinformation’s impact can affect trust in electoral outcomes and satisfaction with democracy

description: Supplementary files for article Russian meddling in U.S. elections: How news of disinformation’s impact can affect trust in electoral outcomes and satisfaction with democracy <br> Russia’s Internet Research Agency (R-IRA) has been a key focus of disinformation research due to its attempts to use social media to influence the outcome of the 2016 United States presidential election. However, questions remain about the extent to which news coverage of the R-IRA’s efforts may have shaped public perceptions of US democracy. To assess its impact, we ran an experiment involving US social media users (N = 916). We tested whether reading news reports about the R-IRA’s activities heightened perceptions that the R-IRA influenced the public’s vote choices, and whether this influence in turn reduced confidence in the outcomes of the 2016 and 2020 elections and broader satisfaction with democracy. Specifically, we tested if these indirect effects differ depending on whether the R-IRA activity was presented via news frames conveying certainty or uncertainty about the R-IRA’s impact on the US public’s behavior. While the news frames did not significantly influence perceptions that the R-IRA had influenced the US public in general, the degree of certainty with which they described the effects of the R-IRA differently affected perceptions that Republicans and Democrats had been influenced. This, in turn, influenced participants’ confidence in elections and satisfaction with democracy.
DOI: 10.17028/rd.lboro.21904452.v1
title: Supplementary information files for Russian meddling in U.S. elections: How news of disinformation’s impact can affect trust in electoral outcomes and satisfaction with democracy

description: Supplementary files for article Russian meddling in U.S. elections: How news of disinformation’s impact can affect trust in electoral outcomes and satisfaction with democracy <br> Russia’s Internet Research Agency (R-IRA) has been a key focus of disinformation research due to its attempts to use social media to influence the outcome of the 2016 United States presidential election. However, questions remain about the extent to which news coverage of the R-IRA’s efforts may have shaped public perceptions of US democracy. To assess its impact, we ran an experiment involving US social media users (N = 916). We tested whether reading news reports about the R-IRA’s activities heightened perceptions that the R-IRA influenced the public’s vote choices, and whether this influence in turn reduced confidence in the outcomes of the 2016 and 2020 elections and broader satisfaction with democracy. Specifically, we tested if these indirect effects differ depending on whether the R-IRA activity was presented via news frames conveying certainty or uncertainty about the R-IRA’s impact on the US public’s behavior. While the news frames did not significantly influence perceptions that the R-IRA had influenced the US public in general, the degree of certainty with which they described the effects of the R-IRA differently affected perceptions that Republicans and Democrats had been influenced. This, in turn, influenced participants’ confidence in elections and satisfaction with democracy.
DOI: 10.34740/kaggle/dsv/4859398
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.4725468
title: CCG Starter Data Kit: South Sudan

description: A starter data kit for South Sudan
DOI: 10.5281/zenodo.4725469
title: CCG Starter Data Kit: South Sudan

description: A starter data kit for South Sudan
DOI: 10.5281/zenodo.4729552
title: CCG Starter Data Kit: South Sudan

description: A starter data kit for South Sudan
DOI: 10.5281/zenodo.4756765
title: CCG Starter Data Kit: South Sudan

description: A starter data kit for South Sudan
DOI: 10.5281/zenodo.7540557
title: CCG Starter Data Kit: South Sudan

description: A starter data kit for South Sudan
DOI: 10.5281/zenodo.6979853
title: Data Set: Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation

description: This is the Python code and plotted figure data used to create the figures for the submitted manuscript, "Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation" submitted to JGR: Solid Earth in 2022. The manuscript concerns a novel technique developed for EGS stimulation, called pore pressure or effective normal stress preconditioning, which preemptively alters the stress field along a fault prior to injection, such that the risk of induced seismicity is reduced. Using a slightly altered version of a preexisting model (a combination of an analytical pore pressure model and a linear slip weakening seismicity model) the effect of this kind of treatment is evaluated.
DOI: 10.5281/zenodo.6979854
title: Data Set: Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation

description: This is the Python code and plotted figure data used to create the figures for the submitted manuscript, "Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation" submitted to JGR: Solid Earth in 2022. The manuscript concerns a novel technique developed for EGS stimulation, called pore pressure or effective normal stress preconditioning, which preemptively alters the stress field along a fault prior to injection, such that the risk of induced seismicity is reduced. Using a slightly altered version of a preexisting model (a combination of an analytical pore pressure model and a linear slip weakening seismicity model) the effect of this kind of treatment is evaluated.
DOI: 10.21942/uva.21806697
title: Data Description "Schooling Progress, Learning Reversal: Indonesia’s Learning Profiles Between 2000 and 2014"

description: We examine the relationship between schooling completed and mathematics learning from 2000 to 2014 by developing learning profiles for Indonesia. The data we use come from the Indonesian Family Life Survey (IFLS), an on-going longitudinal survey in Indonesia. The sample is representative of about 83% of the Indonesian population and contains over 30,000 individuals living in 13 of the 27 provinces in the country. The IFLS surveys and their procedures were properly reviewed and approved by IRBs (Institutional Review Boards) in the United States (at RAND) and in Indonesia at the University of Gadjah Mada (UGM). We use the third (2000), fourth (2007) and fifth (2014) IFLS rounds.
DOI: 10.21942/uva.21806697.v1
title: Data Description "Schooling Progress, Learning Reversal: Indonesia’s Learning Profiles Between 2000 and 2014"

description: We examine the relationship between schooling completed and mathematics learning from 2000 to 2014 by developing learning profiles for Indonesia. The data we use come from the Indonesian Family Life Survey (IFLS), an on-going longitudinal survey in Indonesia. The sample is representative of about 83% of the Indonesian population and contains over 30,000 individuals living in 13 of the 27 provinces in the country. The IFLS surveys and their procedures were properly reviewed and approved by IRBs (Institutional Review Boards) in the United States (at RAND) and in Indonesia at the University of Gadjah Mada (UGM). We use the third (2000), fourth (2007) and fifth (2014) IFLS rounds.