cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3746966
title: Supporting Data for "Ionic and Nonspherical Polymer Nanoparticles in Nonpolar Solvents" (Macromolecules, doi: 10.1021/acs.macromol.0c00121)

description: All data are named with the monomer composition of the block copolymer (SMA, BzMA, or MOTMA) and the type of data (SAXS, DLS, or TEM). Small-angle X-ray scattering (SAXS) reciprocal space scattering data [Q in 1/Å, I(Q) in arb. unit, uncertainty I(Q)] Dynamic-light scattering (DLS) intensity-weighted size distributions [Bin location in nm, Proportion in %] Transmission electron microscopy (TEM) micrographs [Scale bars are all 200 nm]
DOI: 10.5281/zenodo.3746967
title: Supporting Data for "Ionic and Nonspherical Polymer Nanoparticles in Nonpolar Solvents" (Macromolecules, doi: 10.1021/acs.macromol.0c00121)

description: All data are named with the monomer composition of the block copolymer (SMA, BzMA, or MOTMA) and the type of data (SAXS, DLS, or TEM). Small-angle X-ray scattering (SAXS) reciprocal space scattering data [Q in 1/Å, I(Q) in arb. unit, uncertainty I(Q)] Dynamic-light scattering (DLS) intensity-weighted size distributions [Bin location in nm, Proportion in %] Transmission electron microscopy (TEM) micrographs [Scale bars are all 200 nm]
DOI: 10.6084/m9.figshare.3761562.v1462
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.18716/nmrshiftdb2/77533
title: NMR data for 2-methoxy-5-(trifluoromethyl)aniline
DOI: 10.21227/0pf0-n339
title: Covid19action-radiology-CXR

description: The outbreak of COVID-19 in Wuhan, China in December 2019 has rapidly spread across other countries in the world and has been declared as a global pandemic by WHO on 11th March, 2020. COVID-19 continues to have adverse effects on the health and economy of the global population and has brought immense pressure on the health care systems of the developing as well as developed countries. A critical step in the fight against COVID-19 is the early detection of the patients which not only aids in providing quicker treatment but is also useful in stopping the spread of the virus through proper isolation of the patient. Although the reverse transcription polymerase chain reaction rt-(PCR) test of the sputum is considered as the gold standard for COVID-19 diagnosis, it is a time-consuming process and, in some cases, has led to high False Negatives. The relatively low-cost, wider availability and faster methods for sanitization of the equipment makes Chest X-ray imaging (CXR) a promising modality which is commonly being employed for treatment planning, tracking the progression of the disease and could also be useful in the detection of COVID-19. Our goal is to create a single repository by collating various publicly available CXR image sources and provide a standardized split for performing a five-fold cross-validation based training and a separate held out test set for evaluating different AI models. We hope that it will provide a unified platform for researchers to perform a fair comparison of different AI models. This dataset comprises images acquired from different geographical regions using different scanners and at varying resolutions. The primary task is to classify a given CXR image into “COVID-19”, “Other Pneumonia” and “Non-pneumonia” classes. The “Non-pneumonia” class contains images from healthy subjects as well as subjects suffering from diseases other than pneumonia. Additionally, the ground truth (GT) annotations of 13 radiological observations are also available for the images for a subset of images. These may be used to define an additional auxiliary task for the model or pre-training it to improve generalization.
DOI: 10.21227/s7pw-jr18
title: Covid19action-radiology-CXR

description: The outbreak of COVID-19 in Wuhan, China in December 2019 has rapidly spread across other countries in the world and has been declared as a global pandemic by WHO on 11th March, 2020. COVID-19 continues to have adverse effects on the health and economy of the global population and has brought immense pressure on the health care systems of the developing as well as developed countries. A critical step in the fight against COVID-19 is the early detection of the patients which not only aids in providing quicker treatment but is also useful in stopping the spread of the virus through proper isolation of the patient. Although the reverse transcription polymerase chain reaction rt-(PCR) test of the sputum is considered as the gold standard for COVID-19 diagnosis, it is a time-consuming process and, in some cases, has led to high False Negatives. The relatively low-cost, wider availability and faster methods for sanitization of the equipment makes Chest X-ray imaging (CXR) a promising modality which is commonly being employed for treatment planning, tracking the progression of the disease and could also be useful in the detection of COVID-19. Our goal is to create a single repository by collating various publicly available CXR image sources and provide a standardized split for performing a five-fold cross-validation based training and a separate held out test set for evaluating different AI models. We hope that it will provide a unified platform for researchers to perform a fair comparison of different AI models. This dataset comprises images acquired from different geographical regions using different scanners and at varying resolutions. The primary task is to classify a given CXR image into “COVID-19”, “Other Pneumonia” and “Non-pneumonia” classes. The “Non-pneumonia” class contains images from healthy subjects as well as subjects suffering from diseases other than pneumonia. Additionally, the ground truth (GT) annotations of 13 radiological observations are also available for the images for a subset of images. These may be used to define an additional auxiliary task for the model or pre-training it to improve generalization.
DOI: 10.5281/zenodo.3765224
title: Wealth, water and wildlife: landscape aridity intensifies the urban Luxury Effect - data used in meta-analysis

description: The available Excel file contains all data used in the meta-analysis to analyse the Luxury Effect (i.e. the relationship between urban biodiversity and socioeconomic status) and its moderators (wealth status, species provenance and precipitation). Each column in the data set (tab ‘Data’) is defined as follows: <strong>Location</strong>: Location (e.g. city) where a given study took place. If more than one geographical location was considered, they are detailed in the column 'Sample' <strong>Sample: </strong>Any separate samples based either on location or temporal sampling period (e.g. geographical location, habitat types, different years) considered in a given paper. If the column is blank, only one location or period was considered. <strong>Biodiversity measure: </strong>Defined into either diversity or abundance measures as defined in the text. <strong>Response variable: </strong>The precise response variable analysed in the paper. <strong>Socioeconomic variable: </strong>The socioeconomic variable analysed in the paper. <strong>Provenance: </strong>Native or exotic species, where specified. 'All' refers both to papers where it was explicitly stated that both native and exotic species were considered, and those where no information was given, but we assumed that native and exotic species had been considered. <strong>Development status: </strong>Countries with developed economies ('Rich') and countries with developing economies 'Poor') as defined in the text. <strong>Gradient length: </strong>Studies including only urbanized areas ('Short') and those also including rural sampling locations ('Long'). <strong>Precipitation: </strong>in mm. <strong>Pearson's r: </strong>Standardized values used in the meta-analysis. Note the above information is also available in the Excel file in the ‘Notes’ tab.
DOI: 10.5281/zenodo.3765225
title: Wealth, water and wildlife: landscape aridity intensifies the urban Luxury Effect - data used in meta-analysis

description: The available Excel file contains all data used in the meta-analysis to analyse the Luxury Effect (i.e. the relationship between urban biodiversity and socioeconomic status) and its moderators (wealth status, species provenance and precipitation). Each column in the data set (tab ‘Data’) is defined as follows: <strong>Location</strong>: Location (e.g. city) where a given study took place. If more than one geographical location was considered, they are detailed in the column 'Sample' <strong>Sample: </strong>Any separate samples based either on location or temporal sampling period (e.g. geographical location, habitat types, different years) considered in a given paper. If the column is blank, only one location or period was considered. <strong>Biodiversity measure: </strong>Defined into either diversity or abundance measures as defined in the text. <strong>Response variable: </strong>The precise response variable analysed in the paper. <strong>Socioeconomic variable: </strong>The socioeconomic variable analysed in the paper. <strong>Provenance: </strong>Native or exotic species, where specified. 'All' refers both to papers where it was explicitly stated that both native and exotic species were considered, and those where no information was given, but we assumed that native and exotic species had been considered. <strong>Development status: </strong>Countries with developed economies ('Rich') and countries with developing economies 'Poor') as defined in the text. <strong>Gradient length: </strong>Studies including only urbanized areas ('Short') and those also including rural sampling locations ('Long'). <strong>Precipitation: </strong>in mm. <strong>Pearson's r: </strong>Standardized values used in the meta-analysis. Note the above information is also available in the Excel file in the ‘Notes’ tab.
DOI: 10.18716/nmrshiftdb2/88192
title: NMR data for 1-ethenyl-3-nitrobenzene
DOI: 10.21227/aj4b-kd91
title: BEHACOM

description: This dataset contains the behavioural data of 12 different users freely utilising their personal computers.The data collection period is composed of 55 days of user interaction, each user having their own activity periods.
DOI: 10.21227/eny4-f015
title: device parameter

description: With PCF scattering applied to the I-V curve calculation, the low-field electron mobility , the low-field RS and RD corresponding to different gate biases are calculated and obtained, the detailed calculation for these parameters can be referenced in Cui et al[6,8], and the values of these parameters for sample 1 and sample 2 are shown in TABLE II and TABLE III, respectively. From TABLE II and TABLE III, it is shown that the low-field RS and RD corresponding to different gate biases for sample 1 and sample 2 are less varied, the reason is that the ratio of the gate length to the source-drain spacing for the both samples are small, the influence of PCF scattering on the RS and RD is weak.
DOI: 10.21227/p1j3-p623
title: device parameter

description: With PCF scattering applied to the I-V curve calculation, the low-field electron mobility , the low-field RS and RD corresponding to different gate biases are calculated and obtained, the detailed calculation for these parameters can be referenced in Cui et al[6,8], and the values of these parameters for sample 1 and sample 2 are shown in TABLE II and TABLE III, respectively. From TABLE II and TABLE III, it is shown that the low-field RS and RD corresponding to different gate biases for sample 1 and sample 2 are less varied, the reason is that the ratio of the gate length to the source-drain spacing for the both samples are small, the influence of PCF scattering on the RS and RD is weak.
DOI: 10.21227/sahk-8y57
title: IMU and accelerometer data from people with and without lower limb amputation during daily life

description: The dataset comprises up to two weeks of activity data taken from the ankle and foot of 14 people without amputation and 17 people with lower limb amputation. Walking speed, cadence, and lengths of strides taken at and away from the home were considered in this study. Data collection came from two wearable sensors, one inertial measurement unit (IMU) placed on the top of the prosthetic or non-dominant foot, and one accelerometer placed on the same ankle. Location information was derived from GPS and labeled as ‘home’, ‘away’, or ‘unknown’. The dataset contains raw accelerometer and IMU signals from bouts of non-sedentary activity during daily life as well as walking speeds and cadences for continuous, level ground steps taken in the laboratory.
DOI: 10.21227/vz36-5n95
title: BEHACOM

description: This dataset contains the behavioural data of 12 different users freely utilising their personal computers.The data collection period is composed of 55 days of user interaction, each user having their own activity periods.
DOI: 10.5281/zenodo.3765902
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Schröder, Christof Nikolaus, https://orcid.org/0000-0002-1359-6961. Claims were made on Bloodhound, https://bloodhound-tracker.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.3765903
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Schröder, Christof Nikolaus, https://orcid.org/0000-0002-1359-6961. Claims were made on Bloodhound, https://bloodhound-tracker.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5519/qd.y97w3n5l
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (309 records)
DOI: 10.15468/cuex25
title: Redescription of the poorly known ghost shrimp species, Scallasis amboinae Bate, 1888, review of the genus, and description of a new species from the Ryukyu Islands, Japan (Decapoda: Axiidea: Callianassidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Komai, Tomoyuki, Poore, Gary C. B., Fujita, Yoshihisa (2020): Redescription of the poorly known ghost shrimp species, Scallasis amboinae Bate, 1888, review of the genus, and description of a new species from the Ryukyu Islands, Japan (Decapoda: Axiidea: Callianassidae). Zootaxa 4766 (3): 401-420, DOI: 10.11646/zootaxa.4766.3.1
DOI: 10.21227/9za9-yk07
title: Covid19action-radiology-CXR

description: The outbreak of COVID-19 in Wuhan, China in December 2019 has rapidly spread across other countries in the world and has been declared as a global pandemic by WHO on 11th March, 2020. COVID-19 continues to have adverse effects on the health and economy of the global population and has brought immense pressure on the health care systems of the developing as well as developed countries. A critical step in the fight against COVID-19 is the early detection of the patients which not only aids in providing quicker treatment but is also useful in stopping the spread of the virus through proper isolation of the patient. Although the reverse transcription polymerase chain reaction rt-(PCR) test of the sputum is considered as the gold standard for COVID-19 diagnosis, it is a time-consuming process and, in some cases, has led to high False Negatives. The relatively low-cost, wider availability and faster methods for sanitization of the equipment makes Chest X-ray imaging (CXR) a promising modality which is commonly being employed for treatment planning, tracking the progression of the disease and could also be useful in the detection of COVID-19. Our goal is to create a single repository by collating various publicly available CXR image sources and provide a standardized split for performing a five-fold cross-validation based training and a separate held out test set for evaluating different AI models. We hope that it will provide a unified platform for researchers to perform a fair comparison of different AI models. This dataset comprises images acquired from different geographical regions using different scanners and at varying resolutions. The primary task is to classify a given CXR image into “COVID-19”, “Other Pneumonia” and “Non-pneumonia” classes. The “Non-pneumonia” class contains images from healthy subjects as well as subjects suffering from diseases other than pneumonia. Additionally, the ground truth (GT) annotations of 13 radiological observations are also available for the images for a subset of images. These may be used to define an additional auxiliary task for the model or pre-training it to improve generalization.
DOI: 10.5281/zenodo.3765244
title: Predicted carbon-13 NMR data of Natural Products (PNMRNP)

description: PNMRNP is an SDF file that reports the structure, properties and classification of 211,280 natural products. The starting point of this work (January 2019) was https://github.com/oolonek/ISDB/tree/master/Data/dbs which contains csv files of the UNPD data base (Gu J et al., PLOS ONE 2013, 8, e62839, doi:10.1371/journal.pone.0062839) and which are packaged with the ISDB mass spectrometry fragmentation database of ISDB (Allard PM et al., <em>Anal. Chem.</em> 2016, 88, 6, 3317-3323, doi: 10.1021/acs.analchem.5b04804). Starting from InChI strings of compounds, 2D structures with configuration data were produced mainly from the RDKit cheminformatic toolkit (http://www.rdkit.org/). Pubchem (https://pubchem.ncbi.nlm.nih.gov/) identifiers were searched for the compounds and used as keys to give names and synonyms to molecules. Carbon atoms in molecular structures were associated to <sup>13</sup>C NMR chemical shift values using nmrshiftdb2 (https://nmrshiftdb.nmr.uni-koeln.de/). A three-level classification of compounds according to sub-structure presence is proposed. A compound may be classified as a terpene (level 1) as a sesquiterpene (level 2) and as an eudesmane (level 3).
DOI: 10.5281/zenodo.3765330
title: Dataset for Bright x-ray radiation from plasma bubbles in an evolving laser wakefield accelerator

description: This dataset contains the raw data and analysis scripts for results presented in the paper. " Bright x-ray radiation from plasma bubbles in an evolving laser wakefield accelerator"
DOI: 10.5281/zenodo.3765331
title: Dataset for Bright x-ray radiation from plasma bubbles in an evolving laser wakefield accelerator

description: This dataset contains the raw data and analysis scripts for results presented in the paper. " Bright x-ray radiation from plasma bubbles in an evolving laser wakefield accelerator"
DOI: 10.15468/ewkb22
title: Abacaecus n. gen. walterrossii n. sp., a notable hypogean carabid species from Sierra Leone, Western Africa (Coleoptera, Carabidae, Pterostichinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Allegro, Gianni, Giachino, Pier Mauro (2020): Abacaecus n. gen. walterrossii n. sp., a notable hypogean carabid species from Sierra Leone, Western Africa (Coleoptera, Carabidae, Pterostichinae). Zootaxa 4766 (3): 435-446, DOI: 10.11646/zootaxa.4766.3.3
DOI: 10.15468/xk6hnc
title: Tazarcus, a new phylogenetically unplaced genus of two flightless weevils with metapleural ridge from the Eastern Arc Mountains, Tanzania (Coleoptera: Curculionidae: Molytinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Grebennikov, Vasily V. (2020): Tazarcus, a new phylogenetically unplaced genus of two flightless weevils with metapleural ridge from the Eastern Arc Mountains, Tanzania (Coleoptera: Curculionidae: Molytinae). Zootaxa 4766 (3): 421-434, DOI: 10.11646/zootaxa.4766.3.2
DOI: 10.25387/g3.12115857.v2
title: Supplemental Material for Boone et al., 2020

description: <b>Table S1 Primers for strain construction and confirmation. </b>Primers for DJ-PCR-based fluorescent tagging were designed as previously described (Hammond <i>et al</i>. 2011b). The center DJ-PCR fragment for <i>nup120-mCherry</i> tagging was obtained from plasmid pEB1.1, which is similar to pTH1112.8 except that <i>mCherry</i> (Castro-Longoria <i>et al</i>. 2010) is present instead of <i>yfpn</i>. The center DJ-PCR fragment for <i>yfpn-cbp20</i> and <i>yfpn-sad-8</i> tagging was obtained from plasmid pNTYN-2, which is similar to pTH1123.1 except that <i>nat1</i> (Lichius and Read 2010) is present instead of <i>hph</i>.
DOI: 10.25919/5ea3341047f56
title: Parkes observations for project P1050 semester 2020APRS_01

description: This is a request for observing time for the initial follow-up of pulsar discoveries from the re-processing of the low-latitude Galactic plane section of the HTRU survey (P630). We have now completed a first pass re-processing of the 60 % of the survey with GPU based coherent acceleration search and template bank search pipelines, and have discovered potential 54 previously unknown pulsars. Interesting science can usually only be derived from a new pulsar after confirmation and a follow-up timing campaign is carried out. One year of initial timing is the minimum timespan required to fully characterise any newly-discovered pulsars, essential for deriving pulsar parameters such as the characteristic age, magnetic field strength, spin-down rate, as well as to detect any unexpected behaviour of the pulsar which might result from emission instabilities. This follow-up and timing project is necessary for following up on any interesting pulsar systems discovered from the HTRU Galactic plane survey. Since all of the pulsars on the observing list here are being followed-up for the first time, they will produce completely new and exciting results. In addition, this timing project will enable a large-scale examination of the Galactic plane pulsar population, exploring the true boundaries of pulsar parameter space.
DOI: 10.5281/zenodo.3765246
title: Effectiveness of Open Science Policies at ESEC/FSE 2019

description: This report summarizes how the ESEC/FSE 2019 open science policies came to life and how they resulted in openness for the conference. In particular, I provide how authors of 277 papers provided data at peer review time, and how authors of 74 published papers provided their papers and data openly. Finally, I discuss on the obtained results, and provide lessons learned for the development of SIGSOFT open science policies. See: https://ineed.coffee/5836/effectiveness-of-open-science-policies-at-esec-fse-2019/
DOI: 10.5281/zenodo.3765247
title: Effectiveness of Open Science Policies at ESEC/FSE 2019

description: This report summarizes how the ESEC/FSE 2019 open science policies came to life and how they resulted in openness for the conference. In particular, I provide how authors of 277 papers provided data at peer review time, and how authors of 74 published papers provided their papers and data openly. Finally, I discuss on the obtained results, and provide lessons learned for the development of SIGSOFT open science policies. See: https://ineed.coffee/5836/effectiveness-of-open-science-policies-at-esec-fse-2019/
DOI: 10.17632/ryw4ttp2vf.5
title: Data for: Petrogenesis and tectonic setting of igneous rocks from the Dongbulage porphyry Mo deposit, Great Hinggan Range, NE China: Constraints from geology, geochronology, and isotope geochemistry

description: Sr-Nd-Pb-Hf isotopic data
DOI: 10.21227/btjg-m909
title: RTC PV DATASET

description: PV dataTemperature (Celsius)33.00Number of cells in series (ns)1Number of cells in parallel (np)1
DOI: 10.21227/remc-6d63
title: Coronavirus Disease (COVID-19) Surveillance

description: As part of preparedness efforts in dealing with this, it is important for Indonesia to prepare guidelines for preparedness in dealing with COVID-19.
DOI: 10.21227/rncr-f422
title: RTC PV DATASET

description: PV dataTemperature (Celsius)33.00Number of cells in series (ns)1Number of cells in parallel (np)1
DOI: 10.21227/zx9s-yq39
title: Coronavirus Disease (COVID-19) Surveillance

description: As part of preparedness efforts in dealing with this, it is important for Indonesia to prepare guidelines for preparedness in dealing with COVID-19.