cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25093913
title: Mecodema and Zeopoecilus data for Takapourewa Oct to Jan 2023/4

description: Mark recapture analysis, investigation of board size on captures, effects of captures in pitfall traps vs boards and inside v outside of a predator fence
DOI: 10.6084/m9.figshare.25093913.v1
title: Mecodema and Zeopoecilus data for Takapourewa Oct to Jan 2023/4

description: Mark recapture analysis, investigation of board size on captures, effects of captures in pitfall traps vs boards and inside v outside of a predator fence
DOI: 10.25346/s6/xo8e8a
title: Drone image-derived digital elevation models ('flight of terraces' site)

description: Drone image-derived digital elevation model at 'flight of terraces' site in "Microcontinent Breakup and Links to Possible Plate Boundary Reorganization in the Northern Gulf of California, México" created with Agisoft Photoscan software. WGS1984 UTM Zone 12N.
DOI: 10.25346/s6/h4vh7e
title: Drone image-derived digital elevation models ('sag pond' site)

description: Drone image-derived digital elevation model at sag pond site in "Microcontinent Breakup and Links to Possible Plate Boundary Reorganization in the Northern Gulf of California, México" created with Agisoft Photoscan software. WGS1984 UTM Zone 12N.
DOI: 10.25346/s6/kmijt4
title: Southern Isla Ángel de la Guarda 3-m resolution digital elevation model

description: This is the 3-m resolution digital elevation model from "Microcontinent Breakup and Links to Possible Plate Boundary Reorganization in the Northern Gulf of California, México". Digital elevation was constructed from two 0.5-m resolution Pleiades satellite images (product type: 50cm Panchromatic + 2m (4-Band) Multispectral Bundle) using the NASA Ames Stereo Pipeline software. WGS1984 UTM Zone 12N.
DOI: 10.25346/s6/yiwag5
title: OSL results

description: Dosimetry data, equivalent doses, and single grain post-infrared infrared stimulated luminescence (p-IR IRSL) ages from "Microcontinent Breakup and Links to Possible Plate Boundary Reorganization in the Northern Gulf of California, México". Also shown in Table S2 of publication's supplementary file.
DOI: 10.34740/kaggle/dsv/7494625
title: Financial_Data
DOI: 10.6084/m9.figshare.25095923
title: <b>Pace or Inverse Error Provide Improved Approximations to Response Time or Response Time Residuals in Assessments</b>

description: Network analysis of assessment data suggested a close conjoint relationship between pace and question time intensity to response time (RT), independent of person speed. Theoretical consideration indicated that this was a necessary consequence of the relationship of pace and its inverse error to the inverse cumulative distribution function, assuming a normal dependent variable. Empirical data derived from four independent sources confirmed that pace and inverse error<i> </i>were linearly related to the residuals of logarithmic RT (R<sup>2</sup> &gt;0.90). Importantly, response times in either their logarithmic transform or raw metric (seconds), were also well predicted. Accordingly, pace or inverse error<i> </i>provides approximations to response time residuals in assessments and in conjunction with question time intensity can also predict assessment response times. Thus, the accuracy of these question-level measures may be particularly useful for evaluations of time-dependent processes associated with assessment outcomes.
DOI: 10.5281/zenodo.10576420
title: Characterising long COVID-like COVID-19 vaccine reactions

description: Dataset for a cross-sectional study asking participants identifying as having chronic long COVID-like reactions to COVID-19 vaccinations about symptoms, tests, diagnoses, treatments, and healthcare experience.
DOI: 10.5281/zenodo.10576421
title: Characterising long COVID-like COVID-19 vaccine reactions

description: Dataset for a cross-sectional study asking participants identifying as having chronic long COVID-like reactions to COVID-19 vaccinations about symptoms, tests, diagnoses, treatments, and healthcare experience.
DOI: 10.6084/m9.figshare.25093841.v2
title: 0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec

description: düşük hapı 0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec0543 529 72 06 medikal kürtaj hapı düşük hapı cytotec
DOI: 10.34740/kaggle/dsv/7494755
title: Public Opinion Russia Ukraine War (Updated Daily)
DOI: 10.6084/m9.figshare.25096601
title: wvSlpFailureML: A dataset for slope failure occurrence predictive modeling using machine learning and LiDAR -derived topographic variables for the entirety of the state of West Virginia, USA.

description: This dataset consists of 575,670 point locations across the state of West Virginia. Those mapped to the “slpF” class (n = 116,413) were interpreted to be initiation locations of slope failures (e.g., landslides, debris flows, rock topples, etc.). Each slope failure location was collected as a point feature at the interpreted slope failure initiation location by an analyst then subsequently checked by another interpreter. Interpretation primarily relied on light detection and ranging (LiDAR)-derived hillshades and slopeshades and other ancillary geospatial data. All non-slope failure points are labeled as “not” (n=459,257) and were collected as random points at least 30 meters away from the mapped slope failure locations and occurring within the state extent. The “not” points serve as pseudo-absence samples. All topographic variables were derived from a 2 m spatial resolution digital terrain model (DTM) produced from LiDAR data. For topographic measures requiring a moving window, a circular window with a 7 cell radius was used. Physiographic regions are defined relative to Major Land Resource Areas (MLRAs): https://www.nrcs.usda.gov/resources/data-and-reports/major-land-resource-area-mlra. The wvSlpFailures.csv file provides only the attributes while the wvSlpFailures.shp file includes the spatial coordinates. We have included a Word document and PDF that further describes the data.
DOI: 10.5063/f1qj7fst
title: Nectar bat foraging data at flowering agaves, Nuevo Leon and Coahuila, Mexico, May 26-July 31, 2017 and April 28-July 28, 2018 (Lear et al.)

description: Data for "Agave distribution and floral display influence foraging rates of an endangered pollinating bat and implications for conservation" (Lear et al.). Data collected on nectarivorous bat foraging data at flowering agaves in Nuevo Leon and Coahuila, Mexico in summers 2017 and 2018. These data were used to run statistical models to assess the relationship between an endangered pollinating bat species, the Mexican long-nosed bat (Leptonycteris nivalis), and floral resource availability by addressing individual plant and local-scale (30 m) characteristics that influence bat visitation rates to flowering agave plants.
DOI: 10.5519/qd.eicndfyy
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2620 records)
DOI: 10.6084/m9.figshare.25096598.v1
title: Supplementary Table 10B/Figure 3 source data

description: Results from differential gene expression analysis comparing embryonal tumors to non-tumor brain tissue in the adjusted for cell type proportions and tumor purity.
DOI: 10.5519/qd.26s7f9x1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3200 records)
DOI: 10.5281/zenodo.10576463
title: Dataset of my research on self-efficacy beliefs

description: Dataset of my research on self-efficacy beliefs, including qualitative and quantitative data from questionnaires and (group) interviews
DOI: 10.5281/zenodo.10576464
title: Dataset of my research on self-efficacy beliefs

description: Dataset of my research on self-efficacy beliefs, including qualitative and quantitative data from questionnaires and (group) interviews
DOI: 10.57967/hf/1699
title: vaers-outcomes
DOI: 10.34740/kaggle/dsv/7494873
title: crypto-data-daily-updates
DOI: 10.6084/m9.figshare.25096640
title: topoDL: A deep learning semantic segmentation dataset for the extraction of surface mine extents from historic USGS topographic maps

description: Input topographic maps, surface mine extents, and quad boundaries used in the following study:Maxwell, A.E., M.S. Bester, L.A. Guillen, C.A. Ramezan, D.J. Carpinello, Y. Fan, F.M. Hartley, S.M. Maynard, and J.L. Pyron, 2020. Semantic segmentation deep learning for extracting surface mine extents from historic topographic maps, <i>Remote Sensing</i>, 12(24): 1-25. https://doi.org/10.3390/rs12244145.Associated code and descriptions of the data are provided on GitHub: https://github.com/maxwell-geospatial/topoDL. The surface mine extent data were obtained from the USGS prospect- and mine-related features from USGS topographic maps dataset: https://mrdata.usgs.gov/usmin/. Topographic maps were downloaded from TopoView/The National Map. We have simply prepared the data for easier ingestion into deep learning semantic segmentation workflows by aligning the vector polygon data with the associated topographic map and including topographic map boundaries to remove the collar information. Vector data can be rasterized and combined with the topographic maps to generate image chips and masks for semantic segmentation deep learning.The chip prep script on GitHub can be used to create chips and masks from these data. This compressed folder contains the following subfolders (ky_mines, ky_quads, ky_topos, oh_mines, oh_quads, oh_topos, va_mines, va_quads, va_topos). The mines folders contain the mine extents for each topographic map used in the study while the quads folders contain the quadrangle boundaries. All vector data are in shapefile format. The topos folders contain the topographic maps in TIFF format.
DOI: 10.5281/zenodo.10576474
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by W. Titz, http://www.wikidata.org/entity/Q21610793. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21610793
DOI: 10.5281/zenodo.10576475
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by W. Titz, http://www.wikidata.org/entity/Q21610793. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21610793
DOI: 10.5281/zenodo.10576484
title: How Marginal Value of Time Influences Optimality when Remanufacturing to Multiple Generations

description: Code and data used for results in the above titled paper accepted for publication by IISE Transactions on 26 Jan 2024.
DOI: 10.5281/zenodo.10576485
title: How Marginal Value of Time Influences Optimality when Remanufacturing to Multiple Generations

description: Code and data used for results in the above titled paper accepted for publication by IISE Transactions on 26 Jan 2024.
DOI: 10.5281/zenodo.10557924
title: Data and model for 'JWST transmission spectroscopy of HD 209458b: a super-solar metallicity, a very low C/O, and no evidence of CH4, HCN, or C2H2'

description: Supplementary materials for https://arxiv.org/abs/2310.03245 

include:

1. spectra_final.csv: transmission spectrum reduced by Eureka! and SPARTA (Figure 6), the best-fit model presented in Figure 1(a).

2. Opacities used in the retrieval that are compatible with PLATON described in section 3.

All opacity numpy pickle files are generated by Python 3.9.7 and Numpy 1.24.2.

 

**Bestfit in spectra_final.csv and all opacities are updated on Jan 23, 2024

For any additional data requests or questions, please contact: qiaox@uchicago.edu
DOI: 10.5281/zenodo.8339132
title: Data and model for 'JWST transmission spectroscopy of HD 209458b: a super-solar metallicity, a very low C/O, and no evidence of CH4, HCN, or C2H2'

description: Supplementary materials for https://arxiv.org/abs/2310.03245 

include:

1. spectra_final.csv: transmission spectrum reduced by Eureka! and SPARTA (Figure 6), the best-fit model presented in Figure 1(a).

2. Opacities used in the retrieval that are compatible with PLATON described in section 3.

All opacity numpy pickle files are generated by Python 3.9.7 and Numpy 1.24.2.

 

**Bestfit in spectra_final.csv and all opacities are updated on Jan 23, 2024

For any additional data requests or questions, please contact: qiaox@uchicago.edu
DOI: 10.5281/zenodo.10545572
title: PEPAdb (Prehistoric Europe's Personal Adornment database) raw and processed tabular data

description: Data from the PEPAdb project (https://pepadb.us.es/).

- Raw data: sites.csv and structures.csv

- Processed data: records.csv and structuresRecords.csv
DOI: 10.5281/zenodo.10545573
title: PEPAdb (Prehistoric Europe's Personal Adornment database) raw and processed tabular data

description: Data from the PEPAdb project (https://pepadb.us.es/).

- Raw data: sites.csv and structures.csv

- Processed data: records.csv and structuresRecords.csv
DOI: 10.17632/psy3scjjvv.1
title: GDP-MILEX

description: India is a country that has survived several upheavals. To achieve stability, peace, and prosperity, the nation's leaders have long sought to strike a balance between funding a powerful military and a growing economy. This article investigates and clarifies the relationship between India's military spending and economic growth from 1960 to 2021. This research examines the short- and long-run equilibrium link between military expenditures and economic development in India using the Gregory Hansen cointegration test, allowing for structural breaks, and the ARDL bounds test approach. The findings show a favorable association between military spending and economic growth in India across the research period in the short run. It also finds a short and long-term bidirectional causal relationship between military expenditure (MILEX) and gross domestic product (GDP), verifying the Wagnerian and Keynesian hypotheses in the defense sector. For the Indian government, this conclusion has significant policy ramifications because it supports the shift of resources to the military by demonstrating that it has not had a detrimental effect on economic growth.
DOI: 10.17632/56ck8cjx57.1
title: Capillary electrophoresis method for creatine quantification

description: Method development and optimisation for quantification of fetal lung tissue creatine content using capillary electrophoresis.
DOI: 10.17632/64fy3hhbtk.1
title: Test-Dataset

description: This is a Mendeley Data Create Test
DOI: 10.5517/ccdc.csd.cc213szy
title: CCDC 1880490: Experimental Crystal Structure Determination

description: Related Article: Prantika Das, G. B. Dharma Rao, Subhrajyoti Bhandary, Koushik Mandal, Saikat Kumar Seth, Deepak Chopra|2023|Cryst.Growth Des.|24|703|doi:10.1021/acs.cgd.3c01096
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.cc213thh
title: CCDC 1880506: Experimental Crystal Structure Determination

description: Related Article: Prantika Das, G. B. Dharma Rao, Subhrajyoti Bhandary, Koushik Mandal, Saikat Kumar Seth, Deepak Chopra|2023|Cryst.Growth Des.|24|703|doi:10.1021/acs.cgd.3c01096
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.cc213t66
title: CCDC 1880497: Experimental Crystal Structure Determination

description: Related Article: Prantika Das, G. B. Dharma Rao, Subhrajyoti Bhandary, Koushik Mandal, Saikat Kumar Seth, Deepak Chopra|2023|Cryst.Growth Des.|24|703|doi:10.1021/acs.cgd.3c01096
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.cc213t22
title: CCDC 1880493: Experimental Crystal Structure Determination

description: Related Article: Prantika Das, G. B. Dharma Rao, Subhrajyoti Bhandary, Koushik Mandal, Saikat Kumar Seth, Deepak Chopra|2023|Cryst.Growth Des.|24|703|doi:10.1021/acs.cgd.3c01096
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.cc213tff
title: CCDC 1880504: Experimental Crystal Structure Determination

description: Related Article: Prantika Das, G. B. Dharma Rao, Subhrajyoti Bhandary, Koushik Mandal, Saikat Kumar Seth, Deepak Chopra|2023|Cryst.Growth Des.|24|703|doi:10.1021/acs.cgd.3c01096
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.cc213srq
title: CCDC 1880483: Experimental Crystal Structure Determination

description: Related Article: Prantika Das, G. B. Dharma Rao, Subhrajyoti Bhandary, Koushik Mandal, Saikat Kumar Seth, Deepak Chopra|2023|Cryst.Growth Des.|24|703|doi:10.1021/acs.cgd.3c01096
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.cc213t00
title: CCDC 1880491: Experimental Crystal Structure Determination

description: Related Article: Prantika Das, G. B. Dharma Rao, Subhrajyoti Bhandary, Koushik Mandal, Saikat Kumar Seth, Deepak Chopra|2023|Cryst.Growth Des.|24|703|doi:10.1021/acs.cgd.3c01096
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: 10.34740/kaggle/dsv/7495177
title: BBC News
DOI: 10.34740/kaggle/dsv/7494503
title: FF | 2023 12 12 | Multi-Modal Dataset [6/6]
DOI: 10.34740/kaggle/dsv/7495215
title: arXiv Dataset
DOI: 10.5281/zenodo.10576568
title: Labeling GitHub issues

description: Data collected at Jan , from   16 to 19, 2024.
DOI: 10.5281/zenodo.10576569
title: Labeling GitHub issues

description: Data collected at Jan , from   16 to 19, 2024.
DOI: 10.5281/zenodo.10576600
title: The Results of the GNSS coordinated timeseries for the 2021 Mw 7.4 Maduo earthquake in china
DOI: 10.5281/zenodo.10576601
title: The Results of the GNSS coordinated timeseries for the 2021 Mw 7.4 Maduo earthquake in china
DOI: 10.6084/m9.figshare.20761462
title: GCN-Code&StreetGraphFor298Cities

description: The package includes (1) Python scripts for the proposed GCN framework on street network analysis with a case study of urban polycentricity measurement, (2) Shapefile of top 128 streets for each city and txt file of corresponding dual graph as inputs of the GCN, (3) Excel file with urban statistics across 298 cities regarding GDP and street complexity.
DOI: 10.6084/m9.figshare.25097213
title: Lyssikatos and Wenzel 2024

description: Refer to ReadMe.xlsx file for details on all data and script files.
DOI: 10.34740/kaggle/dsv/7495331
title: WallStreetBets 2022
DOI: 10.5281/zenodo.10569093
title: Fine scale location data for Blantyre district, Malawi
title: Communities location in Blantyre district, Malawi
title: Residential areas in Blantyre district, Malawi
title: Villages in Blantyre district, Malawi

description: This dataset presents locations of residential communities in Blantyre district, Malawi.
DOI: 10.5281/zenodo.10569094
title: Fine scale location data for Blantyre district, Malawi
title: Communities location in Blantyre district, Malawi
title: Residential areas in Blantyre district, Malawi
title: Villages in Blantyre district, Malawi

description: This dataset presents locations of residential communities in Blantyre district, Malawi.
DOI: 10.5281/zenodo.10576614
title: Fine scale location data for Blantyre district, Malawi
title: Communities location in Blantyre district, Malawi
title: Residential areas in Blantyre district, Malawi
title: Villages in Blantyre district, Malawi

description: This dataset presents locations of residential communities in Blantyre district, Malawi.
DOI: 10.6084/m9.figshare.24219004.v1
title: raw data.xlsx

description: neuroprotection
DOI: 10.6084/m9.figshare.25097219
title: Impacts of Beach stratification on coastal groundwater flow

description: This is the input files of OGS
DOI: 10.6084/m9.figshare.25055612
title: 16S rRNA Sequencing FAFSA files

description: FAFSA files following 16S rRNA bacterial sequencing in fecal samples of adult zebrafish.
DOI: 10.6084/m9.figshare.25055612.v2
title: 16S rRNA Sequencing FAFSA files

description: FAFSA files following 16S rRNA bacterial sequencing in fecal samples of adult zebrafish.
DOI: 10.6084/m9.figshare.25055612.v1
title: 16S Data

description: FAFSA files following 16S rRNA bacterial sequencing in fecal samples of adult zebrafish.