cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25573/data.11791827.v3
title: Panama Canal Rainfall (K to Q)

description: Raw precipitation data from the Panama Canal Authority.This is a compressed files with individual station precipitation data. There are four files in this series.<br>This file contains data for station names starting with 'K' to 'Q'<br> Data have been freely provided by the Panama Canal Authority and are in the public domain.Any publication using these data should credit the Panama Canal Authority.Some data has been curated by STRI's Physical Monitoring Program.All data are provided on an 'as is' basis.
DOI: 10.25573/data.11791809.v3
title: Panama Canal Rainfall (D to J)

description: Raw precipitation data from the Panama Canal Authority.This is a compressed files with individual station precipitation data. There are four files in this series.<br>This file contains data for station names starting with 'D' to 'J'<br> Data have been freely provided by the Panama Canal Authority and are in the public domain.Any publication using these data should credit the Panama Canal Authority.Some data has been curated by STRI's Physical Monitoring Program.All data are provided on an 'as is' basis.
DOI: 10.6084/m9.figshare.9959756
title: Environmental data

description: Environmental data used in Chevalier et al.<b> Revisiting the abundant-center hypothesis: a niche perspective.</b><br>The file "env.Rdata" contains the coordinates of each pixel (defined at 2.5 degree resolution) of the world on the two-dimensional space defined by the two first axes of a principal component analyses performed on a set of 56 BioClim/WorldClim variables
DOI: 10.6084/m9.figshare.9959756.v1
title: Environmental data

description: Environmental data used in Chevalier et al.<b> Revisiting the abundant-center hypothesis: a niche perspective.</b><br>The file "env.Rdata" contains the coordinates of each pixel (defined at 2.5 degree resolution) of the world on the two-dimensional space defined by the two first axes of a principal component analyses performed on a set of 56 BioClim/WorldClim variables
DOI: 10.25573/data.11791764.v2
title: Panama Canal Rainfall (A to C)

description: Raw precipitation data from the Panama Canal Authority.This is a compressed files with individual station precipitation data. There are four files in this series.<br>This file contains data for station names starting with 'A' to 'C'<br> Data have been freely provided by the Panama Canal Authority and are in the public domain.Any publication using these data should credit the Panama Canal Authority.Some data has been curated by STRI's Physical Monitoring Program.All data are provided on an 'as is' basis.
DOI: 10.5281/zenodo.5113516
title: Vortex input file -- Humboldt penguin PVA

description: Vortex project input file for PVA of Humboldt penguins, completed by workshop participants in Lima, Peru, 2019. Report of the full PHVA and PVA workshop is provided in: McGill, P., A. Baker, R. Lacy, R. Paredes, J. Reyes, J. Rodriguez, A. Tieber, & R. Wallace, (eds.) 2021. Humboldt penguin (Spheniscus humboldti) Population and Habitat Viability Assessment Workshop Final Report. IUCN SSC Conservation Planning Specialist Group, Apple Valley, MN, USA. A PDF of this workshop report can be downloaded at: www.cpsg.org.<br>
DOI: 10.5281/zenodo.5113515
title: Vortex input file -- Humboldt penguin PVA

description: Vortex project input file for PVA of Humboldt penguins, completed by workshop participants in Lima, Peru, 2019. Report of the full PHVA and PVA workshop is provided in: McGill, P., A. Baker, R. Lacy, R. Paredes, J. Reyes, J. Rodriguez, A. Tieber, & R. Wallace, (eds.) 2021. Humboldt penguin (Spheniscus humboldti) Population and Habitat Viability Assessment Workshop Final Report. IUCN SSC Conservation Planning Specialist Group, Apple Valley, MN, USA. A PDF of this workshop report can be downloaded at: www.cpsg.org.<br>
DOI: 10.5281/zenodo.5113340
title: Near Isotropic D4d Spin Qubits as Nodes of a Gd(III)-Based Metal–Organic Framework

description: Data supporting the original figures 2,3,4 of the related publication.
DOI: 10.5281/zenodo.5113339
title: Near Isotropic D4d Spin Qubits as Nodes of a Gd(III)-Based Metal–Organic Framework

description: Data supporting the original figures 2,3,4 of the related publication.
DOI: 10.15468/562pjq
title: Luciola lambkinae Keller and Ballantyne, new replacement name for Luciola roseicollis Pic, 1935 (Coleoptera: Lampyridae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Keller, Oliver, Ballantyne, Lesley (2021): Luciola lambkinae Keller and Ballantyne, new replacement name for Luciola roseicollis Pic, 1935 (Coleoptera: Lampyridae). Insecta Mundi 2021 (874): 1-3, DOI: http://doi.org/10.5281/zenodo.5113782
DOI: 10.15468/vkmvzr
title: Naviauxella horii, a new tiger beetle species from Myanmar (Coleoptera: Cicindelidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wiesner, Jürgen, Phyu, Moe Hnin (2021): Naviauxella horii, a new tiger beetle species from Myanmar (Coleoptera: Cicindelidae). Insecta Mundi 2021 (876): 1-5, DOI: http://doi.org/10.5281/zenodo.5113796
DOI: 10.5066/p9b4rweu
title: Shell Island East Barrier Island Restoration (BA-0110): 2013 habitat pre-construction and post-construction (as-built) classification (ver. 1.1, July 2021)

description: This data set includes mosaicked aerial photographs for the Shell Island East Barrier Island Restoration (BA-0110) project both pre and post-construction for 2013. This data is used as a basemap habitat classification. If repeated, it can also serve as a visual tool for project managers to help them identify any obvious problems or land loss within their project boundary. To better evaluate the effectiveness of restoration efforts, a habitat classification was performed on specific projects to help assess landscape changes.
DOI: 10.5281/zenodo.5113200
title: Britain Breathing 2020 Air Quality and Meteorological Regional Estimates Dataset

description: This data set is a collection of estimated daily mean and maximum values for a range of air quality and meterological measurements and model forecasts for UK postcode districts (e.g. 'AB') for the year 2020. The data uses a 'concentric regions' method to estimate the measurement for all regions, as follows. If measurements exist within the region, the mean of those measurements is used, if not, then a ring of neighbouring postcode regions are selected, and the mean of their measurement values used. If no measurement sites/data are found in the first ring, the process continues, taking the next ring of postcode district regions, working outwards until one or more sensors are found in a ring. As well as the measurement estimations, the number of rings required to find site data and make the estimations is also published. <strong>As a result, please note that estimations with higher ring counts ('rings') are likely to be calculated from more distant sensors. This distance depends upon the size of the postcode regions surrounding the location being estimated. Please use the ring count ('rings') to limit/filter estimations based on your required level of confidence.</strong> The meteorological, pollen and air quality measurement data used to make the regional estimations can be found at this Zenodo archive. The data there contains Temperature, Relative Humidity, and Pressure data, downloaded from the Met Office MIDAS archives via the MEDMI server (https://www.data-mashup.org.uk/). Also downloaded from the MEDMI server are daily pollen measurements for the UK. PM10, PM2.5, NO2, NOx (as NO2), O3, and SO2 measurements from the DEFRA AURN network, and also model forecasts of the same made using the EMEP model. The code used to make the estimations is available at this Zenodo archive. The data-set is presented in CSV format, as two files: turing_regional_estimates_aq_daily_met_pollen_pollution_original_data.csv: uses original site data (timestamp, region_id, ...[measurement name, rings]) ('rings' is the number of rings required to make the estimation) turing_regional_estimates_aq_loc_type_daily_original_data.csv: uses original data. Air quality regional estimates are calculated using specific AQ site location types* separately. (To prevent, for example, 'Traffic Urban' type sites being used to estimate 'non-traffic' or rural regions.) * Air quality site types: Industrial: comprises 'urban industrial' (9 sites) and suburban industrial (2 sites) 'Rural background' (14 sites) 'Urban background' (48 sites) 'Urban traffic' (47 sites)
DOI: 10.6084/m9.figshare.14258450
title: Supplementary File_Data Extraction Table.xlsx

description: Data Extraction Table used for producing qualitative systematic review on women's safety in South Asian LMICs.
DOI: 10.6084/m9.figshare.14258450.v2
title: Supplementary File_Data Extraction Table.xlsx

description: Data Extraction Table used for producing qualitative systematic review on women's safety in South Asian LMICs.
DOI: 10.6084/m9.figshare.14258450.v1
title: Supplementary File_Data Extraction Table.xlsx

description: Data Extraction Table used for producing qualitative systematic review on women's safety in South Asian LMICs.
DOI: 10.6084/m9.figshare.15016266
title: Data Extraction Table for systematic review.xlsx

description: Data Extraction Table for a systematic Review on safety interventions in public transport in South Asian LMICS
DOI: 10.6084/m9.figshare.15016266.v1
title: Data Extraction Table for systematic review.xlsx

description: Data Extraction Table for a systematic Review on safety interventions in public transport in South Asian LMICS
DOI: 10.5517/ccdc.csd.cc25wznq
title: CCDC 2022894: Experimental Crystal Structure Determination

description: Related Article: Alexandra C. Brown, Daniel L. M. Suess|2020|J.Am.Chem.Soc.|142|14240|doi:10.1021/jacs.0c05590
DOI: 10.5517/ccdc.csd.cc25wzqs
title: CCDC 2022896: Experimental Crystal Structure Determination

description: Related Article: Alexandra C. Brown, Daniel L. M. Suess|2020|J.Am.Chem.Soc.|142|14240|doi:10.1021/jacs.0c05590
DOI: 10.5517/ccdc.csd.cc27nk5n
title: CCDC 2075331: Experimental Crystal Structure Determination

description: Related Article: Klim O. Biriukov, Mikhail M. Vinogradov, Oleg I. Afanasyev, Dmitry V. Vasilyev, Alexey A. Tsygankov, Maria Godovikova, Yulia V. Nelyubina, Dmitry A. Loginov, Denis Chusov|2021|Cat.Sci.Tech.|11|4922|doi:10.1039/D1CY00695A
DOI: 10.5517/ccdc.csd.cc27nk6p
title: CCDC 2075332: Experimental Crystal Structure Determination

description: Related Article: Klim O. Biriukov, Mikhail M. Vinogradov, Oleg I. Afanasyev, Dmitry V. Vasilyev, Alexey A. Tsygankov, Maria Godovikova, Yulia V. Nelyubina, Dmitry A. Loginov, Denis Chusov|2021|Cat.Sci.Tech.|11|4922|doi:10.1039/D1CY00695A
DOI: 10.5517/ccdc.csd.cc27pg0f
title: CCDC 2076194: Experimental Crystal Structure Determination

description: Related Article: Pragyan J. Hazarika, Poonam Gupta, Anilkumar Gunnam, Suryanarayana Allu, Ashwini K. Nangia, Naba K. Nath|2021|CrystEngComm|23|4910|doi:10.1039/D1CE00478F
DOI: 10.5517/ccdc.csd.cc27pg2h
title: CCDC 2076196: Experimental Crystal Structure Determination

description: Related Article: Pragyan J. Hazarika, Poonam Gupta, Anilkumar Gunnam, Suryanarayana Allu, Ashwini K. Nangia, Naba K. Nath|2021|CrystEngComm|23|4910|doi:10.1039/D1CE00478F
DOI: 10.5517/ccdc.csd.cc27pg3j
title: CCDC 2076197: Experimental Crystal Structure Determination

description: Related Article: Pragyan J. Hazarika, Poonam Gupta, Anilkumar Gunnam, Suryanarayana Allu, Ashwini K. Nangia, Naba K. Nath|2021|CrystEngComm|23|4910|doi:10.1039/D1CE00478F
DOI: 10.5517/ccdc.csd.cc27pg1g
title: CCDC 2076195: Experimental Crystal Structure Determination

description: Related Article: Pragyan J. Hazarika, Poonam Gupta, Anilkumar Gunnam, Suryanarayana Allu, Ashwini K. Nangia, Naba K. Nath|2021|CrystEngComm|23|4910|doi:10.1039/D1CE00478F
DOI: 10.5517/ccdc.csd.cc27x2mw
title: CCDC 2082568: Experimental Crystal Structure Determination

description: Related Article: Fei Zeng, Lin-Li Tang, Juan Liao, Man-Hua Ding, Guang-Chuan Ou|2021|CrystEngComm|23|4901|doi:10.1039/D1CE00644D
DOI: 10.5517/ccdc.csd.cc27x2lv
title: CCDC 2082567: Experimental Crystal Structure Determination

description: Related Article: Fei Zeng, Lin-Li Tang, Juan Liao, Man-Hua Ding, Guang-Chuan Ou|2021|CrystEngComm|23|4901|doi:10.1039/D1CE00644D
DOI: 10.5517/ccdc.csd.cc27x2nx
title: CCDC 2082569: Experimental Crystal Structure Determination

description: Related Article: Fei Zeng, Lin-Li Tang, Juan Liao, Man-Hua Ding, Guang-Chuan Ou|2021|CrystEngComm|23|4901|doi:10.1039/D1CE00644D
DOI: 10.6073/pasta/d558809f1085df6de3c5e6b3f71b280f
title: Dataset of traits of some birds species of Llanos Piedmont and Flooded Savannas in the Colombian Llanos

description: We compiled data for 13 morphological and life-history traits of 364 species reported in Colombian Llanos. The dataset includes morphological and life-history traits that could influence birds’ responses to land-use change based on a literature review. Life-history traits were compiled from scientific literature, while morphological traits were measured on specimens collected in the Colombian Llanos region and preserved in main Colombia’s biological collections.
DOI: 10.25345/c59z67
title: MassIVE MSV000087849 - Identification of PKB substrates in the liver
title: This study was to identify novel PKB substrates in mouse liver through immunoprecipitation with PAS antibody.
DOI: 10.6084/m9.figshare.14731719
title: Distributional (Single) Index Models

description: A Distributional (Single) Index Model (DIM) is a semiparametric model for distributional regression, that is, estimation of conditional distributions given covariates. The method is a combination of classical single-index models for the estimation of the conditional mean of a response given covariates, and isotonic distributional regression. The model for the index is parametric, whereas the conditional distributions are estimated nonparametrically under a stochastic ordering constraint. We show consistency of our estimators and apply them to a highly challenging dataset on the length of stay (LoS) of patients in intensive care units. We use the model to provide skillful and calibrated probabilistic predictions for the LoS of individual patients, which outperform the available methods in the literature.
DOI: 10.6084/m9.figshare.14731719.v1
title: Distributional (Single) Index Models

description: A Distributional (Single) Index Model (DIM) is a semiparametric model for distributional regression, that is, estimation of conditional distributions given covariates. The method is a combination of classical single-index models for the estimation of the conditional mean of a response given covariates, and isotonic distributional regression. The model for the index is parametric, whereas the conditional distributions are estimated nonparametrically under a stochastic ordering constraint. We show consistency of our estimators and apply them to a highly challenging dataset on the length of stay (LoS) of patients in intensive care units. We use the model to provide skillful and calibrated probabilistic predictions for the LoS of individual patients, which outperform the available methods in the literature.
DOI: 10.6084/m9.figshare.14854161.v4
title: Supplementary Material-Detail Enhancement Algorithm for Microscopy Images of Diatom Based on Multi-exposure Image Fusion.

description: The multi-exposure image fusion results of nine "Aqualitas" image data sets. Multi-exposure microscopy images are fused for detail enhancement. <br>
DOI: 10.6073/pasta/defc6a198a891b59111b5df4a16fbbbd
title: Assessing the use of bison for savanna restoration at Cedar Creek Ecosystem Science Reserve: Species Percent Cover

description: Oak savanna is the most threatened ecosystem in Minnesota and fire, alone, is not restoring and preserving it. Our savanna restoration research started more than a half century ago in what had once been native savanna at Cedar Creek. It has shown that burning about 4 to 7 times per decade eliminates shrubs and non-savanna tree species and restores prairie grassland species. However, our 50 years of research is also showing that these frequent and intense fires are preventing oaks from regenerating. Bison are now known to be a keystone species for restoring and preserving grasslands, but their roles in savanna ecosystems remain unknown. In grasslands, bison preferentially graze the dominant warm season grasses that would otherwise outcompete wildflowers, thereby promoting plant coexistence and enhancing plant diversity. Here we propose to test whether bison grazing might promote the growth and survivorship of oak seedlings in burned savannas by reducing grass fuel for fires and by knocking back dominant grass competitors. We will maintain the existing fire frequencies and the design of the long-term burning experiment, while adding bison grazing as an additional factor in part of several burn units on the southeast side of the property. Bison will graze during the summer and early fall seasons. Grazing exclosures will be established, and oak seedlings will be planted, to test effects of bison grazing on early oak growth and survivorship. The outcomes we plan to achieve are to: (1) discover better restoration and preservation practices for savanna ecosystems; (2) determine how these practices impact savanna biodiversity; and (3) educate Minnesotans about the ecological heritage of their state, including the roles that bison, fire and biodiversity play in the functioning of savannas and other Minnesota ecosystems. We will achieve these goals and outcomes by: (1) restoring bison grazing to 200 acres of oak savanna; (2) experimentally testing whether bison grazing promotes savanna biodiversity; and (3) disseminating results to K-12 students and visitors.
DOI: 10.15468/kyw8uf
title: Big fruits with tiny tepals: An unusual new species of Lauraceae from southwestern China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Yang, Zhi, Jin, Wei-Yin, Liu, Bing, Ferguson, David Kay, Yang, Yong (2021): Big fruits with tiny tepals: An unusual new species of Lauraceae from southwestern China. PhytoKeys 179: 129-143, DOI: http://dx.doi.org/10.3897/phytokeys.179.62050, URL: http://dx.doi.org/10.3897/phytokeys.179.62050
DOI: 10.48543/e0cd73cf-c0a7-4436-9b65-fb5719c09983
title: VerbaAlpina Version 19/2
DOI: 10.48543/bbc1c88e-3af3-4af4-8468-c684e01e8a87
title: VerbaAlpina Version 19/1
DOI: 10.5281/zenodo.3560886
title: Researchers Hidden Preferences for Metrics - Datasets

description: Data collected during conjoint analysis experiments conducted as part of the *metrics-project. Detailed information on the experiments' background, conduction and results can be found in the following article from the Journal of the Association for Information Science and Technology: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24445
DOI: 10.5281/zenodo.3560885
title: Researchers Hidden Preferences for Metrics - Datasets

description: Data collected during conjoint analysis experiments conducted as part of the *metrics-project. Detailed information on the experiments' background, conduction and results can be found in the following article from the Journal of the Association for Information Science and Technology: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24445
DOI: 10.34810/data91/1
title: PERCEIVE_READMEfile_Dataset5_WP2_PartA.docx
DOI: 10.34810/data91/2
title: PERCEIVE_WP2_D2_2_sect6_descriptive_CSregs.csv
DOI: 10.34810/data91/3
title: PERCEIVE_WP2_D2_2_sect6_descriptive_country.csv
DOI: 10.34810/data91/4
title: PERCEIVE_WP2_D2_2_sections6%268_README.rtf
DOI: 10.34810/data91/5
title: PERCEIVE_WP2_D2_2_Principal_Components_Factor_Analysis.tab
DOI: 10.34810/data91/6
title: PERCEIVE_WP2_D2-5_sect2-4-3.tab
DOI: 10.34810/data91/7
title: PERCEIVE_WP2_D2-5_sect2-5.tab
DOI: 10.34810/data91/8
title: PERCEIVE_WP2_D2_5_section2_README.rtf
DOI: 10.34810/data91/9
title: PERCEIVE_WP2_D2_2_Principal_Components_Factor_Analysis_README.rtf
DOI: 10.34810/data91/10
title: PERCEIVE_WP2_D2_3_Composite_Index_EU_Identity.tab
DOI: 10.34810/data91/11
title: PERCEIVE_WP2_D2_3_Composite_Index_EU_Identity_README.rtf
DOI: 10.34810/data91/12
title: PERCEIVE_WP2_D2_4_Classification_Ident_EU.tab
DOI: 10.5281/zenodo.5113898
title: hal-03079617 raw data

description: Raw data of the preprint hal-03079617 "Dynamics of <em>Fucus serratus</em> thallus photosynthesis and community primary production during emersion across seasons: canopy dampening and biochemical acclimation".
DOI: 10.34810/data91/13
title: PERCEIVE_WP2_D2-5_Table2_4.tab
DOI: 10.5281/zenodo.4722892
title: hal-03079617 raw data

description: Raw data of the preprint hal-03079617 "Dynamics of <em>Fucus serratus</em> thallus photosynthesis and community primary production during emersion across seasons: canopy dampening and biochemical acclimation".
DOI: 10.34810/data91/14
title: PERCEIVE_WP2_D2-5_sect2-4-1&sect2-4-2.csv
DOI: 10.34810/data91/15
title: PERCEIVE_WP2_D2-5_sect2-4-4.tab
DOI: 10.34810/data91/16
title: PERCEIVE_WP2_D2_4_Classification_Ident_EU_README.rtf
DOI: 10.5281/zenodo.5113881
title: Gluconobacter oxydans Knockout Collection Finds Improved Rare Earth Element Extraction

description: <strong>Datasets for "<em>Gluconobacter oxydans</em> Knockout Collection Finds Improved Rare Earth Element Extraction":</strong> Data S1. BLAST2GO output with assigned gene ontologies, InterPro IDs, and BLAST hits represented in Fig. 1A. Data S2. Monte Carlo (MC) estimate of the number of genes represented by at least one mutant per number of mutants collected for simulated and real picking events, used to generate Fig. 1B. Data S3. Complete condensed knockout collection with sequencing and screen results. Data S4. Results of TB and BPB validation assays with proxy wild types. Data S5. Results of direct pH measurements. Data S6. Results of bioleaching assay.
DOI: 10.5281/zenodo.5113880
title: Gluconobacter oxydans Knockout Collection Finds Improved Rare Earth Element Extraction

description: <strong>Datasets for "<em>Gluconobacter oxydans</em> Knockout Collection Finds Improved Rare Earth Element Extraction":</strong> Data S1. BLAST2GO output with assigned gene ontologies, InterPro IDs, and BLAST hits represented in Fig. 1A. Data S2. Monte Carlo (MC) estimate of the number of genes represented by at least one mutant per number of mutants collected for simulated and real picking events, used to generate Fig. 1B. Data S3. Complete condensed knockout collection with sequencing and screen results. Data S4. Results of TB and BPB validation assays with proxy wild types. Data S5. Results of direct pH measurements. Data S6. Results of bioleaching assay.