cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5649153
title: finals_2021_367

description: Log and boot files of game 367
DOI: 10.5281/zenodo.5649155
title: finals_2021_368

description: Log and boot files of game 368
DOI: 10.5281/zenodo.5649152
title: finals_2021_367

description: Log and boot files of game 367
DOI: 10.5281/zenodo.5649154
title: finals_2021_368

description: Log and boot files of game 368
DOI: 10.5281/zenodo.5649157
title: finals_2021_369

description: Log and boot files of game 369
DOI: 10.5281/zenodo.5649159
title: finals_2021_370

description: Log and boot files of game 370
DOI: 10.5281/zenodo.5649156
title: finals_2021_369

description: Log and boot files of game 369
DOI: 10.5281/zenodo.5649158
title: finals_2021_370

description: Log and boot files of game 370
DOI: 10.5281/zenodo.5649163
title: finals_2021_371

description: Log and boot files of game 371
DOI: 10.5281/zenodo.5649165
title: finals_2021_372

description: Log and boot files of game 372
DOI: 10.5281/zenodo.5649162
title: finals_2021_371

description: Log and boot files of game 371
DOI: 10.5281/zenodo.5649164
title: finals_2021_372

description: Log and boot files of game 372
DOI: 10.5281/zenodo.5649167
title: finals_2021_373

description: Log and boot files of game 373
DOI: 10.5281/zenodo.5649166
title: finals_2021_373

description: Log and boot files of game 373
DOI: 10.5281/zenodo.5649169
title: finals_2021_374

description: Log and boot files of game 374
DOI: 10.5281/zenodo.5649171
title: finals_2021_375

description: Log and boot files of game 375
DOI: 10.5281/zenodo.5649168
title: finals_2021_374

description: Log and boot files of game 374
DOI: 10.5281/zenodo.5649170
title: finals_2021_375

description: Log and boot files of game 375
DOI: 10.5281/zenodo.5649173
title: finals_2021_376

description: Log and boot files of game 376
DOI: 10.5281/zenodo.5649172
title: finals_2021_376

description: Log and boot files of game 376
DOI: 10.5281/zenodo.5649175
title: finals_2021_377

description: Log and boot files of game 377
DOI: 10.5281/zenodo.5649179
title: finals_2021_378

description: Log and boot files of game 378
DOI: 10.5281/zenodo.5649174
title: finals_2021_377

description: Log and boot files of game 377
DOI: 10.5281/zenodo.5649178
title: finals_2021_378

description: Log and boot files of game 378
DOI: 10.5281/zenodo.5649181
title: finals_2021_379

description: Log and boot files of game 379
DOI: 10.5281/zenodo.5649185
title: finals_2021_380

description: Log and boot files of game 380
DOI: 10.5281/zenodo.5649180
title: finals_2021_379

description: Log and boot files of game 379
DOI: 10.5281/zenodo.5649187
title: finals_2021_381

description: Log and boot files of game 381
DOI: 10.5281/zenodo.5649184
title: finals_2021_380

description: Log and boot files of game 380
DOI: 10.5281/zenodo.5649189
title: finals_2021_382

description: Log and boot files of game 382
DOI: 10.5281/zenodo.5649186
title: finals_2021_381

description: Log and boot files of game 381
DOI: 10.5281/zenodo.5649191
title: finals_2021_383

description: Log and boot files of game 383
DOI: 10.5281/zenodo.5649188
title: finals_2021_382

description: Log and boot files of game 382
DOI: 10.5281/zenodo.5649193
title: finals_2021_384

description: Log and boot files of game 384
DOI: 10.5281/zenodo.5649190
title: finals_2021_383

description: Log and boot files of game 383
DOI: 10.5281/zenodo.5649195
title: finals_2021_385

description: Log and boot files of game 385
DOI: 10.5281/zenodo.5649192
title: finals_2021_384

description: Log and boot files of game 384
DOI: 10.5281/zenodo.5649197
title: finals_2021_386

description: Log and boot files of game 386
DOI: 10.5281/zenodo.5649194
title: finals_2021_385

description: Log and boot files of game 385
DOI: 10.5281/zenodo.5649196
title: finals_2021_386

description: Log and boot files of game 386
DOI: 10.5525/gla.researchdata.1203
title: An atomic compass-detecting 3D magnetic field alignment with vector vortex light.

description: The data is divided into two different folder for the two different experiments, rotation and splitting. The additional folder is contains the Stokes parameters of the light field we used in our experiment.
DOI: 10.6084/m9.figshare.16947451
title: Biodiversity promotes ecosystem functioning despite environmental change

description: Online dataset for Fig.2 – 5 in Hong <i>et al. </i>''Biodiversity promotes ecosystem functioning despite environmental change".
DOI: 10.14278/rodare.1246
title: Data publication: How 5f electron polarizability drives covalency and selectivity in actinide N-donor complexes

description: Diese Daten beinhalten die Synthese und Charakterisierung neuartiger Actinid (Th, U, Np, Pu) Komplexe mit pyrrolbasierten Liganden, sowie ebenfalls die Ligandsynthese. Darunter fallen SC-XRD, NMR, IR, UV-VIS und EA Daten. Des weiteren quantenchemische Berechnungen zu den Systemen, sowie der Vergleich zum bereits bekannten Salen System.
DOI: 10.14278/rodare.1245
title: Data publication: How 5f electron polarizability drives covalency and selectivity in actinide N-donor complexes

description: Diese Daten beinhalten die Synthese und Charakterisierung neuartiger Actinid (Th, U, Np, Pu) Komplexe mit pyrrolbasierten Liganden, sowie ebenfalls die Ligandsynthese. Darunter fallen SC-XRD, NMR, IR, UV-VIS und EA Daten. Des weiteren quantenchemische Berechnungen zu den Systemen, sowie der Vergleich zum bereits bekannten Salen System.
DOI: 10.5281/zenodo.5653299
title: Mujeres ganadoras del Premio Nobel a lo largo de la historia

description: Conjunto de datos que recoge las mujeres que han ganado un Premio Nobel a lo largo de la historia del galardón.
DOI: 10.5281/zenodo.5653298
title: Mujeres ganadoras del Premio Nobel a lo largo de la historia

description: Conjunto de datos que recoge las mujeres que han ganado un Premio Nobel a lo largo de la historia del galardón.
DOI: 10.6084/m9.figshare.16951408
title: flexural_experiment_RAWdata.rar

description: flexural test data
DOI: 10.6084/m9.figshare.16951408.v1
title: flexural_experiment_RAWdata.rar

description: flexural test data
DOI: 10.34808/en69-pk90
title: Split-beam echosounder data from Gdansk Deep Summer 2019

description: The acoustic data was collected in 2019, in the Gdansk Deep, in the season: Summer. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected while the ship was sailing. To ensure data quality, echosounders were calibrated and passive noise was measured.
DOI: 10.6084/m9.figshare.14762559.v3
title: Data.xlsx

description: Sonication of stainless steel wire as a tool for microbiological diagnosis of diabetic foot infection <b></b>
DOI: 10.5519/qd.75xvygt0
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4933455 records)
DOI: 10.5281/zenodo.5653387
title: Dataset for the publication entitled: "Assessment of lithium ion battery ageing by combined impedance spectroscopy, functional microscopy and finite element modelling""

description: Related to the publication: https://doi.org/10.1016/j.jpowsour.2021.230459 Datasets for the following Figures: Figure 2. Figure 3. Figure 5. Figure 7.
description: Related ot publication: https://doi.org/10.1016/j.jpowsour.2021.230459
DOI: 10.5281/zenodo.5588117
title: Dataset for the publication entitled: "Assessment of lithium ion battery ageing by combined impedance spectroscopy, functional microscopy and finite element modelling""

description: Related to the publication: https://doi.org/10.1016/j.jpowsour.2021.230459 Datasets for the following Figures: Figure 2. Figure 3. Figure 5. Figure 7.
description: Related ot publication: https://doi.org/10.1016/j.jpowsour.2021.230459
DOI: 10.5281/zenodo.5653322
title: A comparative dataset on public perceptions of multiple risks during the COVID-19 pandemic in Italy and Sweden

description: These datasets are the result of two nation-wide surveys conducted in Italy and Sweden in August 2020 and in november 2020. The surveys (which are identical in the two rounds) explore the respondents' risk perception, preparedness, knowledge, and experience regarding a set of hazards, namely: epidemics, floods, droughts, earthquakes, wildfires, terror attacks, domestic violence, economic crises, and climate change. The data files include the questionnaire survey (the Italian and Swedish versions as well as the English translation) and the two datasets of all the answers to the two surveys. Each column in the dataset refers to an item in the survey (e.g. a question or a sub-question), and each row represents a single respondent. For additional information on the August 2020 dataset, see Mondino et al. (2020).
DOI: 10.5281/zenodo.4034276
title: A comparative dataset on public perceptions of multiple risks during the COVID-19 pandemic in Italy and Sweden

description: These datasets are the result of two nation-wide surveys conducted in Italy and Sweden in August 2020 and in november 2020. The surveys (which are identical in the two rounds) explore the respondents' risk perception, preparedness, knowledge, and experience regarding a set of hazards, namely: epidemics, floods, droughts, earthquakes, wildfires, terror attacks, domestic violence, economic crises, and climate change. The data files include the questionnaire survey (the Italian and Swedish versions as well as the English translation) and the two datasets of all the answers to the two surveys. Each column in the dataset refers to an item in the survey (e.g. a question or a sub-question), and each row represents a single respondent. For additional information on the August 2020 dataset, see Mondino et al. (2020).
DOI: 10.5281/zenodo.5651229
title: Urinary biomarkers for the non-invasive diagnosis of endometriosis: a systematic literature review

description: Raw dataset from a systematic literature review performed until August 2021 in which the research question was 'Are there urine biomarkers sensitive and specific enough for endometriosis detection?' and the Medical Subject Heading (MeSH) terms were (endometrios*) AND (urin*).
DOI: 10.5281/zenodo.5651228
title: Urinary biomarkers for the non-invasive diagnosis of endometriosis: a systematic literature review

description: Raw dataset from a systematic literature review performed until August 2021 in which the research question was 'Are there urine biomarkers sensitive and specific enough for endometriosis detection?' and the Medical Subject Heading (MeSH) terms were (endometrios*) AND (urin*).
DOI: 10.5281/zenodo.4896777
title: Fleshy red algae mats act as temporary reservoirs for sessile invertebrate biodiversity - Raw data for biodiversity analysis, species list and detailed output data from iNEXT procedure

description: Raw data for biodiversity analysis, species list and detailed output data from iNEXT procedure for manuscript entitled "Fleshy red algae mats act as temporary reservoirs for sessile invertebrate biodiversity".
DOI: 10.6084/m9.figshare.16951372
title: Evergreen plants with drupe and birds with low dietary specialization dominate the urban highly seasonal plant-frugivore network: A case study in Nanjing Botanical Garden Mem. Sun Yat-Sen

description: Our research displayed the structure and characteristics of the plant-frugivore network in urban parks using ecological network analysis and explored the effects of ecological traits of species on their network role.
DOI: 10.6084/m9.figshare.16951372.v1
title: Evergreen plants with drupe and birds with low dietary specialization dominate the urban highly seasonal plant-frugivore network: A case study in Nanjing Botanical Garden Mem. Sun Yat-Sen

description: Our research displayed the structure and characteristics of the plant-frugivore network in urban parks using ecological network analysis and explored the effects of ecological traits of species on their network role.
DOI: 10.25392/leicester.data.16941040
title: Solar wind observations from BepiColombo MPO-MAG and BERM during Nov-Dec 2020

description: This dataset contains unreleased data from the BepiColombo mission for the period 2020-11-27 to 2020-12-15 during the cruise phase to Mercury. In particular, it contains magnetic field observations from the MPO-MAG instrument (Heyner et al. 2021), and energetic particles from the BERM instrument (Pinto et al. 2022).<br><br>****************IMPORTANT NOTE****************<br>These data have not been released yet to the Planetary Science Archive (PSA). As consequence, they may still suffer some changes due to future calibrations before they are released to the PSA. Therefore, <b>we strongly encourage all the users to contact the following people before using this dataset.</b><br>- Dr Beatriz Sánchez-Cano, University of Leicester, BepiColombo Guest Investigator, bscmdr1@leicester.ac.uk<br>- Dr Daniel Heyner, TU Braunschweig, Principal Investigator of MPO-MAG, d.heyner@tu-bs.de<br>- Dr Richard Moissl, European Space Agency, Principal Investigator of BERM, richard.moissl@esa.int<br>*********************************************************<br><br>File descriptions:<br>- MPO-MAG file, named: “MPO-MAG_Nov2020.txt”<br>It contains derived data from the outbound sensor. The file has 7 columns with the following information:<br>1- Time (YYYY-MM-DD HH:MM:SS)2- Total magnetic field in nT.3- Radial component of the magnetic field (Br) in nT and in RTN coordinates.4- Tangential component of the magnetic field (Bt) in nT and in RTN coordinates.5- Normal component of the magnetic field (Bn) in nT and in RTN coordinates.6- Cone angle (theta) of the magnetic field in degrees.7- Clock angle (phi) of the magnetic field in degrees.<br><br>- BERM file, named: “BERM_Nov2020.txt”It contains uncalibrated “raw” counts. A calibration is currently being performed. The file has 7 columns with the following information:All channel units are "counts".<br>1- Time (DD-MM-YYYY HH:MM:SS)2- All particles3- E1 4- E2 5- E3 6- E47- E5 8- P19- P210- P311- P412- P513- P614- P715- P816- H117- H218- H319- H420- H521- O1<br><br>References:<br>• D. Heyner et al.,(2021), The BepiColombo Planetary Magnetometer MPO-MAG: What can we Learn From the Hermean Magnetic Field? Space Sci Rev, 217, 52. https://doi.org/10.1007/s11214-021-00822-x <br>• M. Pinto et al., (2022), The BepiColombo Radiation Monitor, Space Sci Rev.<br>
DOI: 10.25392/leicester.data.16941040.v1
title: Solar wind observations from BepiColombo MPO-MAG and BERM during Nov-Dec 2020

description: This dataset contains unreleased data from the BepiColombo mission for the period 2020-11-27 to 2020-12-15 during the cruise phase to Mercury. In particular, it contains magnetic field observations from the MPO-MAG instrument (Heyner et al. 2021), and energetic particles from the BERM instrument (Pinto et al. 2022).<br><br>****************IMPORTANT NOTE****************<br>These data have not been released yet to the Planetary Science Archive (PSA). As consequence, they may still suffer some changes due to future calibrations before they are released to the PSA. Therefore, <b>we strongly encourage all the users to contact the following people before using this dataset.</b><br>- Dr Beatriz Sánchez-Cano, University of Leicester, BepiColombo Guest Investigator, bscmdr1@leicester.ac.uk<br>- Dr Daniel Heyner, TU Braunschweig, Principal Investigator of MPO-MAG, d.heyner@tu-bs.de<br>- Dr Richard Moissl, European Space Agency, Principal Investigator of BERM, richard.moissl@esa.int<br>*********************************************************<br><br>File descriptions:<br>- MPO-MAG file, named: “MPO-MAG_Nov2020.txt”<br>It contains derived data from the outbound sensor. The file has 7 columns with the following information:<br>1- Time (YYYY-MM-DD HH:MM:SS)2- Total magnetic field in nT.3- Radial component of the magnetic field (Br) in nT and in RTN coordinates.4- Tangential component of the magnetic field (Bt) in nT and in RTN coordinates.5- Normal component of the magnetic field (Bn) in nT and in RTN coordinates.6- Cone angle (theta) of the magnetic field in degrees.7- Clock angle (phi) of the magnetic field in degrees.<br><br>- BERM file, named: “BERM_Nov2020.txt”It contains uncalibrated “raw” counts. A calibration is currently being performed. The file has 7 columns with the following information:All channel units are "counts".<br>1- Time (DD-MM-YYYY HH:MM:SS)2- All particles3- E1 4- E2 5- E3 6- E47- E5 8- P19- P210- P311- P412- P513- P614- P715- P816- H117- H218- H319- H420- H521- O1<br><br>References:<br>• D. Heyner et al.,(2021), The BepiColombo Planetary Magnetometer MPO-MAG: What can we Learn From the Hermean Magnetic Field? Space Sci Rev, 217, 52. https://doi.org/10.1007/s11214-021-00822-x <br>• M. Pinto et al., (2022), The BepiColombo Radiation Monitor, Space Sci Rev.<br>
DOI: 10.5281/zenodo.5653486
title: Data from: Metacommunity theory review and its application in community assembly of soil animals

description: We were interested in community assembly of soil animals and performed a literature study to find out what is known about soil metacommunities. We aimed to study keywords co-occurrence relationships of scientific journal articles in the field of "metacommunity" research from 1992-2017 as a whole. We also investigated the co-occurrence of the top 20 most frequent keywords in five 5-year time periods. In September 2017 we searched the Web of Science with ‘metacommunity’ as the only keyword, and found 1226 English papers published in international journals between January 1992 and September 2017. And we exported these papers from Web of Science as a plain text file (.txt) with the option ‘Full Record and Cited References’, which is archived here. The text file thus contains full records and cited references (in a concise format, so without the titles of the cited papers), and each field is prefaced by a two-character field tag. Afterwards we used the software ‘Citespace’ to create Table 1 and Figure 2 in Guo et al. (2018). We created that Figure 2 using the following settings in Citespace: we choose the “co-occurrence” function and “keyword” as node types, then created keywords co-occurrence relationships (Figure 2). Next, we created lists of the top 20 keywords in different periods, which can reveal the research hotspots (Table 1). The method for extracting the top 20 most frequent keywords was as follows: We use the Web of Science database to retrieve scientific papers from 1992 to 2017, taking into account the relationship between citation and publication time. We calculated the percentage of 200 most cited papers published in each of the 5-year periods. To do so we followed the following steps: Step1: we selected the 200 most cited papers from the entire datset (1226 in the 1992-2017 period). Step 2: we calculated the percentage of those 200 papers published each 5-year period. Step 3: we also calculated an correction coefficient by taking, for each 5-year period, the number of top-200 most cited papers published in that period, and dividing that number by the total number of papers (out of the 1226 selected papers) published in that period. Step 4 Last, we calculate the real keyword frequency by multiplying the keyword frequency in specific 5-year periods with the correction coefficient.
DOI: 10.5281/zenodo.5653485
title: Data from: Metacommunity theory review and its application in community assembly of soil animals

description: We were interested in community assembly of soil animals and performed a literature study to find out what is known about soil metacommunities. We aimed to study keywords co-occurrence relationships of scientific journal articles in the field of "metacommunity" research from 1992-2017 as a whole. We also investigated the co-occurrence of the top 20 most frequent keywords in five 5-year time periods. In September 2017 we searched the Web of Science with ‘metacommunity’ as the only keyword, and found 1226 English papers published in international journals between January 1992 and September 2017. And we exported these papers from Web of Science as a plain text file (.txt) with the option ‘Full Record and Cited References’, which is archived here. The text file thus contains full records and cited references (in a concise format, so without the titles of the cited papers), and each field is prefaced by a two-character field tag. Afterwards we used the software ‘Citespace’ to create Table 1 and Figure 2 in Guo et al. (2018). We created that Figure 2 using the following settings in Citespace: we choose the “co-occurrence” function and “keyword” as node types, then created keywords co-occurrence relationships (Figure 2). Next, we created lists of the top 20 keywords in different periods, which can reveal the research hotspots (Table 1). The method for extracting the top 20 most frequent keywords was as follows: We use the Web of Science database to retrieve scientific papers from 1992 to 2017, taking into account the relationship between citation and publication time. We calculated the percentage of 200 most cited papers published in each of the 5-year periods. To do so we followed the following steps: Step1: we selected the 200 most cited papers from the entire datset (1226 in the 1992-2017 period). Step 2: we calculated the percentage of those 200 papers published each 5-year period. Step 3: we also calculated an correction coefficient by taking, for each 5-year period, the number of top-200 most cited papers published in that period, and dividing that number by the total number of papers (out of the 1226 selected papers) published in that period. Step 4 Last, we calculate the real keyword frequency by multiplying the keyword frequency in specific 5-year periods with the correction coefficient.
DOI: 10.14278/rodare.1228
title: Data: Electrical Characterization of Germanium Nanowires Using a Symmetric Hall Bar Configuration: Size and Shape Dependence

description: The uploaded data are related to electrical measurements including two- and four-probe, Hall effect, and temperature-dependent measurements. The simulation data is included as well.
DOI: 10.14278/rodare.1227
title: Data: Electrical Characterization of Germanium Nanowires Using a Symmetric Hall Bar Configuration: Size and Shape Dependence

description: The uploaded data are related to electrical measurements including two- and four-probe, Hall effect, and temperature-dependent measurements. The simulation data is included as well.