cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/23gwn43ygp.1
title: Data describing the regional Industry 4.0 readiness index

description: The data article presents a dataset suitable to measure regional Industry 4.0 (I4.0+) readiness. The I4.0+ dataset includes 101 indicators aggregated to NUTS 2 statistical level) based on open data in the field of education (ETER, Erasmus), science (USPTO, MA-Graph, GRID), government (Eurostat) and media coverage (GDELT). Indicators consider the I4.0-specific domain of higher education and lifelong learning, innovation, technological investment, labour market and technological readiness as indicators. A composite indicator, the I4.0+ index was constructed by the Promethee method, to identify regional rank regarding their I4.0 performance. The index is validated with economic (GDP) and innovation indexes (Regional Innovation Index).
DOI: 10.17632/97ntvyj9cr.1
title: A study of the inclusion of vulnerable consumers in energy communities with peer-to-peer exchanges

description: This dataset is associated with the article "A study of the inclusion of vulnerable consumers in energy communities with peer-to-peer exchanges" by the same authors submited to the International Conference on Smart Energy Systems and Technologies (SEST 2020). These data are used to model residential agents demand, generation and storage, according to the equations presented in the paper and the ones in "Gonçalves, I., Á. Gomes, and C. H. Antunes, “Optimizing the management of smart home energy resources under different power cost scenarios,” Appl. Energy, vol. 242, pp. 351–363, 2019". Pricing data used by the residential agents and the community manager agent is also provided. Please see the publication for more information about this dataset.
DOI: 10.17632/bn8n76tfgy.1
title: Essential oil obtained from plants juniper (Juniperus) and spruce (Picea) leaves by water distillation
DOI: 10.17632/svz8hmccsv.1
title: Tabel 3 _data in the first round of orthogonal tests

description: statistics and calcuation in the first round of orthogonal tests for intelligent ship navigational information monitoring system
DOI: 10.17632/yxmy2sytrp.1
title: Data for "Cross-Flow Suppression of Dendrite Growth in Microfluidics"

description: This repository contains information relevant to the publication "Cross-Flow Suppression of Dendrite Growth in Microfluidics"
DOI: 10.17632/xzv6bjm9x2.1
title: Dataset for gait analysis and assessment of fall risk for older adults

description: This five-part dataset is intended for human gait analysis in an older adult population (37 women and seven men; age 69.98 ± 8.57 years, body mass index 27.71 ± 4.57). Part 1 compromises demographic data for the 44 participants, along with the results of the Short Physical Performance Battery (SPPB) motor function test and the Mini-Mental State Examination (MMSE). We used the MMSE to ensure the participants could understand the experimental protocol instructions. Part 2 presents the anthropometric measurements of the participants. Part 3 shows the results for each item of the Gait component of the Performance Oriented Mobility Assessment (POMA-G). Part 4 contains five files per participant, storing motion-capture data for the lower limb in the Coordinate 3D (C3D) format. These files were generated using a Vicon motion analysis system, consisting of 24 reflective markers and seven cameras (Vantage V5) sampled at 100 Hz. Part 5 contains 26 gait parameters for each C3D file obtained using Nexus 2.9.3.
DOI: 10.17632/ywsbh3ndr8.4
title: Dataset of Breast mammography images with Masses

description: The dataset contains mammography with benign and malignant masses. Images in this dataset were first extracted 106 masses images from INbreast dataset, 53 masses images from MIAS dataset, and 2188 masses images DDSM dataset. Then we use data augmentation and contrast-limited adaptive histogram equalization to preprocess our images. After data augmentation, Inbreast dataset has 7632 images, MIAS dataset has 3816 images, DDSM dataset has 13128 images. In addition, we also integrate INbreast, MIAS, DDSM together. All the images were resized to 227*227 pixels.
DOI: 10.17632/ywsbh3ndr8.3
title: Dataset of Breast mammography images with Masses

description: The dataset contains mammography with benign and malignant masses. Images in this dataset were first extracted 106 masses images from INbreast dataset, 53 masses images from MIAS dataset, and 2188 masses images DDSM dataset. Then we use data augmentation and contrast-limited adaptive histogram equalization to preprocess our images. After data augmentation, Inbreast dataset has 7632 images, MIAS dataset has 3816 images, DDSM dataset has 13128 images. In addition, we also integrate INbreast, MIAS, DDSM together. All the images were resized to 227*227 pixels.
DOI: 10.17632/kk2pmbsfsf.1
title: Support Information for "Tectonic setting and provenance of Cretaceous strata in the Main Central Thrust zone, Eastern Nepal: implications for the archipelago paleogeography of Neo-Tethys"

description: Data tables and supplementary figures.
DOI: 10.17632/srrgm5dmcx.3
title: Data for: Influence of polysorbates (Tweens) on structural and antimicrobial properties for microemulsions

description: Dataset for the manuscript " Influence of polysorbates (Tweens) on structural and antimicrobial properties for microemulsions". The dataset contains a series of .opju and .ai files corresponding to the plots, table and illustrations in upload files.
DOI: 10.17632/dtb5y4724g.1
title: Spatial structure of Rostov agglomeration

description: We share data on the spatial structure of Rostov agglomeration, which is the administrative center of the Southern federal district and is in the top-ten largest cities of Russia.
DOI: 10.17632/yzgs4yzs89.1
title: Estimating the Impact of Tourism Spending on County Employment in South Carolina

description: Raw data for Estimating the Impact of Tourism Spending on County Employment in South Carolina.
DOI: 10.17632/fs6mhmd5sp.1
title: supplementary files of Dermatological manifestations of COVID-19: a systematic review and meta-analysis

description: Supplementary Figure 1. Funnel plot with trim and fill method. Number of studies combined: k = 48 (with 15 added studies).
DOI: 10.17632/335rmgrfw2.4
title: Sit-to-Stand Test Collected with Elderly People From Centre of Portugal

description: This dataset includes accelerometer data collected with institutionalized elderly people from Centre of Portugal during the performance of Sit-to-Stand Test.
DOI: 10.17632/wyx96j2pcj.2
title: Are the NCCN/SSO COVID-19 guidelines for delay in melanoma treatment associated with mortality risk?: Supplemental Files

description: Supplemental material for publication titled - "Are the NCCN/SSO COVID-19 guidelines for delay in melanoma treatment associated with mortality risk?" to be published in Journal of the American Academy of Dermatology
DOI: 10.17632/3vg2r3ymgk.2
title: Data and Codes for the paper "A Simple, SIR-like but Individual-Based Epidemic Model: Application in Comparison of COVID-19 in New York City and Wuhan"

description: The author has calculated, simulated, and plotted all epidemic curves for the paper "A Simple, SIR-like but Individual-Based Epidemic Model: Application in Comparison of COVID-19 in New York City and Wuhan". All these calculated and simulated curves are shown in Figures 2-11. All data and codes for generating these figures are separately placed in different sheets in one Excel file. Using this Excel file, you can calculate and plot all epidemic curves shown in Figures 2-11. The values of parameters l and i are separately placed in two cells marked in yellow, which are located in top one or two row on the left. After you change either or both of the two parameters, the Excel file will calculate (for Figures 2-6) A, I, R and T, and plot (for Figures 7-11) a new epidemic curve for you. The calculated data for each pair of selected l and i are listed in the columns under the two marked parameters. You can use these calculated data to plot epidemic curves in the excel file by yourself.
DOI: 10.17632/v7nbtxdkgm.1
title: The Structural Basis for Interhemispheric Functional Connectivity: Evidence from Individuals with Agenesis of the Corpus Callosum

description: This dataset consist of the tractography results of 9 subjects of agenesis of corpus callosum. These .trk files can be visualized with the Trackvis software (http://trackvis.org/).
DOI: 10.17632/kwzghfgy7y.2
title: New-onset Depression among Children, Adolescents, and Adults with Hidradenitis Suppurativa Supplementary File

description: New-onset Depression among Children, Adolescents, and Adults with Hidradenitis Suppurativa Supplementary File Table of Contents: Page 2: Supplementary Methods - Propensity score-matched sensitivity analysis Page 3: Table S1. ICD Diagnosis Codes for Depression Page 4: Table S2. Patient eligibility flowchart Page 5: Table S3. Hazard ratios for depression in fully adjusted regression models (adult and pediatric analyses) Page 6: Table S4. Complete case analysis of association between HS and incident depression in adult and pediatric populations Page 7: Table S5. Characteristics of HS and control patients after propensity score matching (adult and pediatric analyses) Page 8: Table S6. Incidence of depression among propensity score-matched HS patients and control patients (adult and pediatric populations) Page 9: References
DOI: 10.17632/g35kd4fmzm.1
title: Monitoring the permeability and strain evolution of fault based on pressure pulses and fibre Bragg grating sensing in the laboratory

description: All data used in Figures 4, 6-10, 12 which will be published with this article.
DOI: 10.17632/kz3j2w57w5.2
title: Processed data_ erosion rate

description: Processed data_ erosion rate
DOI: 10.17632/d229ykd4x3.2
title: Supplementary Material: Variability in Excess Charges for Dermatology-related Procedures

description: Supplemental Table 1. Top 25 HCPCS Codes for dermatology-related procedures (excludes dermatopathology, E&M codes)
DOI: 10.5281/zenodo.3929478
title: The thermo-chemical evolution of Mars with a strongly stratified mantle (data)

description: The thermo-chemical evolution of Mars with a strongly stratified mantle: derived data
DOI: 10.5281/zenodo.3689444
title: Example computer vision classification training data derived from British Library 19th Century Books Image collection

description: Example computer vision classification training data derived from British Library 19th Century Books Image collection This dataset provides training data for image classification for use in a computer vision workshop. The images are derived from 'Digitised Books - Images identified as Embellishments. c. 1510 - c. 1900. JPG' from the year '1839'. Currently, included are four folders containing a variety of images derived from the BL books corpus. 'cv_workshop_exercise_data' include images of: 'building', 'people', 'coat of arms' 'humancats' contains images of humans and images of cats The 'fashion' and 'portraits' folders both contain images of people organised into 'female' and 'male'. These labels were annotated by a single annotator and these categories may themselves not be meaningful. They are included in the workshop data as a point of discussion about how we should label data both in general and when working with historical data. This data is intended primarily as an educational resource.
DOI: 10.5281/zenodo.3667575
title: Example computer vision classification training data derived from British Library 19th Century Books Image collection

description: Example computer vision classification training data derived from British Library 19th Century Books Image collection This dataset provides training data for image classification for use in a computer vision workshop. The images are derived from 'Digitised Books - Images identified as Embellishments. c. 1510 - c. 1900. JPG' from the year '1839'. Currently, included are four folders containing a variety of images derived from the BL books corpus. 'cv_workshop_exercise_data' include images of: 'building', 'people', 'coat of arms' 'humancats' contains images of humans and images of cats The 'fashion' and 'portraits' folders both contain images of people organised into 'female' and 'male'. These labels were annotated by a single annotator and these categories may themselves not be meaningful. They are included in the workshop data as a point of discussion about how we should label data both in general and when working with historical data. This data is intended primarily as an educational resource.
DOI: 10.21227/qbm0-9254
title: A Large-Scale Dataset for Active Fire Detection/Segmentation (Landsat-8)

description: This dataset was created from all Landsat-8 images from South America in the year 2018. More than 31 thousand images were processed (15 TB of data), and approximately on half of them active fire pixels were found. The Landsat-8 sensor has 30 meters of spatial resolution (1 panchromatic band of 15m), 16 bits of radiometric resolution and 16 days of temporal resolution (revisit). The images in our dataset are in TIFF (geotiff) format with 10 bands (excluding the 15m panchromatic band). We cropped the original Landsat-8 scenes into image patches with 128 x 128 pixels by using a stride overlap of 64 pixels (vertical and horizontal). The masks are in binary format where True (1) represents fire and False (0) represents background and they were generated from the conditions set by Schroeder et al. (2016).
DOI: 10.5281/zenodo.3929510
title: Data and code for 'Telomere length measurement for longitudinal analysis: the role of assay precision'

description: Data and code for<strong> </strong>'Telomere length measurement for longitudinal analysis: the role of assay precision' by Nettle, Gadalla, Susser, Bateson and Aviv' The R script will run both the numerical simulations and the analysis of the empirical data. The exact results of the simulation will vary slightly from run to run. One frozen set of simulation data is also included in the archive.
DOI: 10.25592/uhhfdm.1050
title: 3D Model of Zamiaceae - Encephalartos spec.

description: Zamiaceae_Brotpalmfarn<br> scientific name: Encephalartos spec.<br> vernacular name: bread tree / palm tree<br> object: female cone of a bread palm fern, display object for the flower conditions in the Zamiaceae (bread palm fern family)
DOI: 10.25592/uhhfdm.1129
title: 3D Model of Zamiaceae - Encephalartos spec.

description: Zamiaceae_Brotpalmfarn<br> scientific name: Encephalartos spec.<br> vernacular name: bread tree / palm tree<br> object: female cone of a bread palm fern, display object for the flower conditions in the Zamiaceae (bread palm fern family)
DOI: 10.5281/zenodo.3929517
title: Data on Mutillidae distribution and bioclimatic variables

description: Data for paper <strong>Ecogeographic patterns of coloration in velvet ants (Hymenoptera: Mutillidae) </strong><strong>Ecogeographic patterns of coloration in velvet ants (Hymenoptera: Mutillidae) </strong>
DOI: 10.5281/zenodo.3929516
title: Data on Mutillidae distribution and bioclimatic variables

description: Data for paper <strong>Ecogeographic patterns of coloration in velvet ants (Hymenoptera: Mutillidae) </strong><strong>Ecogeographic patterns of coloration in velvet ants (Hymenoptera: Mutillidae) </strong>
DOI: 10.6084/m9.figshare.12602771.v3
title: Example SCPPOD Output

description: Collection of ESRI .gdb which contain solutions to the SCPPOD with the following naming convention:<br><br>e.g.) comparing paths in Network A to Network B (SCCPODarcsPathAtoNetB.gdb for arc elements and SCCPODnodesPathAtoNetB.gdb for node elements)<br>Solutions can be accessed similarly for:<br>a) comparing paths in Network A to Network B SCCPODarcsPathAtoNetB.gdb for arc elements and SCCPODnodesPathAtoNetB.gdb for node elements)<br>b) comparing paths in Network A to Network C SCCPODarcsPathAtoNetC.gdb for arc elements and SCCPODnodesPathAtoNetC.gdb for node elements)<br>c) comparing paths in Network B to Network A SCCPODarcsPathBtoNetA.gdb for arc elements and SCCPODnodesPathBtoNetA.gdb for node elements)<br>d) comparing paths in Network B to Network CSCCPODarcsPathBtoNetC.gdb for arc elements and SCCPODnodesPathBtoNetC.gdb for node elements)<br> e) comparing paths in Network C to Network A <br>SCCPODarcsPathCtoNetA.gdb for arc elements and SCCPODnodesPathCtoNetA.gdb for node elements)<br>f) comparing paths in Network C to Network BSCCPODarcsPathCtoNetB.gdb for arc elements and SCCPODnodesPathCtoNetB.gdb for node elements)<br>Inside each .gdb, the SCPPOD solutions for each path can be found. The naming convention for the node solutions for path id X is ('SN_routeX_X'), while the naming convention for the arc solutions for path id X is ('routX_Rt' for single polyline counterpart path; and 'routeX_Rtsplit' for a polyline representation of the counterpart path based upon the SCPPOD node output).<br>Also included is a collection of ESRI .gdb that represent the original path nodes that could be assigned to the comparison network. In this case, only nodes that were within 20m of the comparison network could be assigned. Each path node is attributed with the distance to its counterpart node in the comparison. For example, the nodes all of the paths from Network A that could be assigned to Network B are contained in the 'PathANodesAssignedtoNetB.gdb'.<br>Solutions can be accessed similarly for:<br>a) Nodes in Network A paths assigned to Network B (PathANodesAssignedtoNetB.gdb)<br>b) Nodes in Network A paths assigned to Network C(PathANodesAssignedtoNetC.gdb)<br>c) Nodes in Network B paths assigned to Network A(PathBNodesAssignedtoNetA.gdb)<br>d) Nodes in Network B paths assigned to Network C(PathBNodesAssignedtoNetC.gdb)<br>e) Nodes in Network C paths assigned to Network A(PathCNodesAssignedtoNetA.gdb)<br>f) Nodes in Network C paths assigned to Network B(PathCNodesAssignedtoNetB.gdb)<br>
DOI: 10.6084/m9.figshare.12602324.v2
title: Example Paths and Network Data

description: This network dataset is an example of a network to which paths from other networks (i.e. Networks A and B) can be compared.<br><br>Contains two directories:<br>a) NetworkC <br>b) NetworkPaths<br>NetworkC contains an ESRI .gdb in which the arcs and nodes for Network C can be found as well as an ArcGIS ND Network Analyst configuration file.<br>NetworkPaths contains ESRI .gdbs representing:<br>a) Polyline representations of the paths in each network (e.g. NetworkAPaths.gdb)<br>b) A point representation of the nodes in each path in each network (e.g. NetworkAPathPoints)<br>c) The origin and destination points for the paths (ODNodes.gdb)<br>
DOI: 10.18112/openneuro.ds002993.v1.0.0
title: MNE-somato-data-bids
DOI: 10.25403/upresearchdata.12235379
title: All tree localities for neighbour distances

description: These are localities, recorded as longitudes and latitudes for three fig species in seven forests.
DOI: 10.25403/upresearchdata.12235379.v1
title: All tree localities for neighbour distances

description: These are localities, recorded as longitudes and latitudes for three fig species in seven forests.
DOI: 10.6084/m9.figshare.12602324
title: Example Paths and Comparison Network Data

description: This network dataset is an example of a network to which paths from other networks (i.e. Networks A and B) can be compared.<br><br>Contains two directories:<br>a) NetworkC <br>b) NetworkPaths<br>NetworkC contains an ESRI .gdb in which the arcs and nodes for Network C can be found as well as an ArcGIS ND Network Analyst configuration file. This network is based upon a subset of the Missouri Department of Transportation (MoDOT) July 2016 road dataset lined in the references.<br><br>NetworkPaths contains ESRI .gdbs representing:<br>a) Polyline representations of the shortest paths between origin-destination nodes in each network (e.g. NetworkAPaths.gdb)<br>b) A point representation of the nodes in each path in each network (e.g. NetworkAPathPoints)<br>c) The origin and destination points for the paths (ODNodes.gdb)<br>
DOI: 10.6084/m9.figshare.12602324.v4
title: Example Paths and Comparison Network Data

description: This network dataset is an example of a network to which paths from other networks (i.e. Networks A and B) can be compared.<br><br>Contains two directories:<br>a) NetworkC <br>b) NetworkPaths<br>NetworkC contains an ESRI .gdb in which the arcs and nodes for Network C can be found as well as an ArcGIS ND Network Analyst configuration file. This network is based upon a subset of the Missouri Department of Transportation (MoDOT) July 2016 road dataset lined in the references.<br><br>NetworkPaths contains ESRI .gdbs representing:<br>a) Polyline representations of the shortest paths between origin-destination nodes in each network (e.g. NetworkAPaths.gdb)<br>b) A point representation of the nodes in each path in each network (e.g. NetworkAPathPoints)<br>c) The origin and destination points for the paths (ODNodes.gdb)<br>
DOI: 10.6084/m9.figshare.12602324.v3
title: Counterpart Paths: Example Paths and Comparison Network Data

description: This network dataset is an example of a network to which paths from other networks (i.e. Networks A and B) can be compared.<br><br>Contains two directories:<br>a) NetworkC <br>b) NetworkPaths<br>NetworkC contains an ESRI .gdb in which the arcs and nodes for Network C can be found as well as an ArcGIS ND Network Analyst configuration file.<br>NetworkPaths contains ESRI .gdbs representing:<br>a) Polyline representations of the paths in each network (e.g. NetworkAPaths.gdb)<br>b) A point representation of the nodes in each path in each network (e.g. NetworkAPathPoints)<br>c) The origin and destination points for the paths (ODNodes.gdb)<br>
DOI: 10.21227/a8bg-qf31
title: A Large-Scale Dataset for Active Fire Detection/Segmentation (Landsat-8)

description: This dataset was created from all Landsat-8 images from South America in the year 2018. More than 31 thousand images were processed (15 TB of data), and approximately on half of them active fire pixels were found. The Landsat-8 sensor has 30 meters of spatial resolution (1 panchromatic band of 15m), 16 bits of radiometric resolution and 16 days of temporal resolution (revisit). The images in our dataset are in TIFF (geotiff) format with 10 bands (excluding the 15m panchromatic band). We cropped the original Landsat-8 scenes into image patches with 128 x 128 pixels by using a stride overlap of 64 pixels (vertical and horizontal). The masks are in binary format where True (1) represents fire and False (0) represents background and they were generated from the conditions set by Schroeder et al. (2016).
DOI: 10.5281/zenodo.3685255
title: Patch-level facilitation fosters high-Andean plant diversity at regional scales

description: Survey of the alpine vegetation in seven mountains of the Patagonian Andes from January to March of 2017 and 2018. On each mountain, we established one study site at each of three elevations (1600, 1800 and 2000 m). Accordingly, we sampled a total of 21 alpine plant communities (i.e., seven mountains x three elevations) dominated by cushion plants. At each community, 50 individual cushion plants were haphazardly selected within an area of approx. 0.5 ha, pairing each cushion with an adjacent non-cushion or open area 50 cm away in a random direction. In order to sample a similar surface in the surrounding open area, a wire hoop was shaped to match the size of the sampled cushion that was then placed on the ground. The number and identity of all plant species were recorded at both cushion and open area plots. Given that cushion plants are roughly elliptical, microsites were defined as elliptical plots, and thus, the longer and shorter axes of each cushion were measured as an approximate estimation of its area. In total, we sampled 2100 plots (1050 cushion plants and 1050 open area plots).