cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2dd8gk
title: CCDC 2216328: Experimental Crystal Structure Determination

description: Related Article: Baolin Liu, Qingsong Deng, Lei Zhang, Aimin Yu, Xiangtai Meng|2022|Org.Biomol.Chem.|20|9639|doi:10.1039/D2OB01764D
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: 10.5281/zenodo.7437809
title: pionites_melanocephalus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7437808
title: pionites_melanocephalus_zanfona_1.fasta.gz

description: .
DOI: 10.6073/pasta/4b6d52010d42e7d018a2451e21e6f544
title: Springtails (Arthropoda, Collembola) from Greater Puerto Rico: species list and distribution

description: The data archive is here: https://doi.org/10.2737/RDS-2018-0063 please use this DOI when citing this dataset. The Collembola fauna of Puerto Rico is reasonably well known, but many recent reports are scattered in published literature and unpublished theses. Here we present a summary of all springtail species identified from the Bank of Puerto Rico since 1927 and 2011. This includes new, previously unpublished records. In the present review we list 119 species in 59 genera and 17 families. Most species (37) belong in family Entomobryidae, but this reflects the taxonomic expertise of specialists working in Puerto Rico rather than a real bias in the distribution of higher taxa in the islands. In addition to the new reports, these data provide information on the distribution of the species outside the island bank. This current list of species is an update to original species lists from Puerto Rico (Mari Mutt 1982 and Thibaud 2014). In addition to the list of species, we make available a data set that includes a catalog of species, their habitats, historical reports and distribution maps on Greater Puerto Rico. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
DOI: 10.6084/m9.figshare.6849641
title: The association between adipocytokines and glycemic control in women with gestational diabetes mellitus

description: <b>Objective:</b> To evaluate the relationship between adipocytokines and glycemic control. <b>Study design:</b> Prospective observational trial of gestations with gestational diabetes mellitus (GDM). Fasting glucose (FG), insulin, adiponectin, leptin, chemerin, retinol-binding protein 4 (RBP-4), osteocalcin, and resistin were measured. HomeOstasis model assessment of insulin resistance (HOMA-IR) and QUantitative insulin sensitivity ChecK Index (QUICKI) were calculated. Women who required medications for glycemic control were compared to women using nutritional therapy only. <b>Results:</b> Overall, 75 women were included −26 (34.7%) required medications to achieve good glycemic control. Factors associated with poor control are as follows: low resistin (aOR 0.84), HOMA-IR (aOR 1.96), QUICKI (aOR 0.62), first trimester FG (aOR 1.43), and maternal age (aOR 1.26). HOMA-IR and QUICKI performed highest for prediction. Resistin, first trimester FG, maternal age, and QUICKI had an AUC of 0.878, sensitivity and specificity of 87.5% for the prediction of the need for medications. <b>Conclusions:</b> Low resistin is associated with poor control. A model utilizing maternal age, first trimester fasting glucose, and first visit QUICKI yields good predictability.
DOI: 10.6084/m9.figshare.6849641.v1
title: The association between adipocytokines and glycemic control in women with gestational diabetes mellitus

description: <b>Objective:</b> To evaluate the relationship between adipocytokines and glycemic control. <b>Study design:</b> Prospective observational trial of gestations with gestational diabetes mellitus (GDM). Fasting glucose (FG), insulin, adiponectin, leptin, chemerin, retinol-binding protein 4 (RBP-4), osteocalcin, and resistin were measured. HomeOstasis model assessment of insulin resistance (HOMA-IR) and QUantitative insulin sensitivity ChecK Index (QUICKI) were calculated. Women who required medications for glycemic control were compared to women using nutritional therapy only. <b>Results:</b> Overall, 75 women were included −26 (34.7%) required medications to achieve good glycemic control. Factors associated with poor control are as follows: low resistin (aOR 0.84), HOMA-IR (aOR 1.96), QUICKI (aOR 0.62), first trimester FG (aOR 1.43), and maternal age (aOR 1.26). HOMA-IR and QUICKI performed highest for prediction. Resistin, first trimester FG, maternal age, and QUICKI had an AUC of 0.878, sensitivity and specificity of 87.5% for the prediction of the need for medications. <b>Conclusions:</b> Low resistin is associated with poor control. A model utilizing maternal age, first trimester fasting glucose, and first visit QUICKI yields good predictability.
DOI: 10.5281/zenodo.7436437
title: MarsWRF outputs

description: MarsWRF outputs
DOI: 10.5281/zenodo.7436438
title: MarsWRF outputs

description: MarsWRF outputs
DOI: 10.5281/zenodo.7437972
title: MarsWRF outputs

description: MarsWRF outputs
DOI: 10.48331/scielo.cublxd/kaqwav
title: preservacao-digital-si_rondineli-saad.pptx

description: :unav
DOI: 10.48331/scielo.cublxd
title: Preservação digital e segurança da informação

description: Apresentação de Rondineli Saad realizada na Reunião Anual SciELO 2022.
DOI: 10.6084/m9.figshare.21623829.v2
title: Pearl millet transcription factor family characterization data

description: Presented are datasets derived from analyzing sequences of putative transcription factors and some other proteins in pearl millet (<em>Pennisetum glaucum</em>). These datasets shows families which those protiens belong to, a phylogenetic tree and conserved motifs for each of these family, and their predicted subcellular localization.
DOI: 10.57745/ehnyds
title: Readme.pdf

description: Readme first to know the content of the zip file
DOI: 10.57745/mmzjjf
title: FD_Faleyras.zip

description: Zip file with all necessary materiels (data, codes) to reproduce the results
DOI: 10.5281/zenodo.7074324
title: Classification of Artificial Intelligence and eXplainable Artificial Intelligence publications in Air Traffic Management

description: v1.0 version used and partially published in "A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory". In this version, it references mainly Transportation Reasearch Part C, ICRAT, Journal of ATM, and ATM Seminar, IEEE transaction on ITS, but not only
DOI: 10.5281/zenodo.7074323
title: Classification of Artificial Intelligence and eXplainable Artificial Intelligence publications in Air Traffic Management

description: v1.0 version used and partially published in "A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory". In this version, it references mainly Transportation Reasearch Part C, ICRAT, Journal of ATM, and ATM Seminar, IEEE transaction on ITS, but not only
DOI: 10.6073/pasta/88af6940b9a8dcbc472daeef54ab76d8
title: Daily streamflow (Bisley area, 5 stations: Q1, Q2, Q3, Sabana, Puente Roto)

description: The daily data are summarized to monthly as follows: Daily average CFS are summed for each month and multiplied by 86400 (seconds per day) to yield cubic feet per month. This value is divided by the particular watershed area and multiplied by another conversion factor to yield cm water equivalent depth discharged by each watershed per month. This allows direct hydrologic comparison of watersheds of different sizes. Time series plots illustrate the biennial periodicity of high and low discharges, and particular floods and droughts. October 1970 was the historic flood for PR, recently exceeded during the passage of Hurricane Hortense in September 1996. The historic drought occurred during 1993-1994 and is clearly visible in these records. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
DOI: 10.6084/m9.figshare.21724949
title: 167074976571.zip

description: a test for this web
DOI: 10.6084/m9.figshare.21724949.v2
title: 167074976571.zip

description: a test for this web
DOI: 10.6084/m9.figshare.21724949.v1
title: 167074976571.zip

description: a test for familiar with this web
DOI: 10.5281/zenodo.7437968
title: Virtual Reality Dataset used for Proof of Concept in the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION)

description: This dataset contains the <strong>dataset </strong>used in the Virtual Reality POC for the validation of the Conflict Detection and Resolution (CD&R) use case. This dataset represent a extract of different (using K-means) candidate solution, either good or bad ones.
DOI: 10.5281/zenodo.7437969
title: Virtual Reality Dataset used for Proof of Concept in the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION)

description: This dataset contains the <strong>dataset </strong>used in the Virtual Reality POC for the validation of the Conflict Detection and Resolution (CD&R) use case. This dataset represent a extract of different (using K-means) candidate solution, either good or bad ones.
DOI: 10.5281/zenodo.7437563
title: Scenarios used for the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION )

description: This dataset contains the scenarios used for one of the validation of the ARTIMATION project: Conflict Detection and Resolution (CD&R) use case. It contains the validation exercice developped at ENAC using real flown data from 2016, and modifying it to respect our constraints.<br> <br> Inside, one can find: -The file "exo_artimation.txt" a file containing the whole scenario, that can be played using REJEU platform. -10 individual files, extracted from "exo_artimation.txt" containing conflicting aircrafts. Those files where used in other steps of the ARTIMATION project, notably in the solution dataset, the heatmatrix, heatmap, storyboard developped (all linked in related identifiers).
DOI: 10.34740/kaggle/dsv/4722878
title: Mahanagar Yatayat Dataset
DOI: 10.5281/zenodo.7437653
title: Solutions and Genetic algorithm dataset of the Scenarios used for the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION )

description: This dataset contains the <strong>solution </strong>of the scenarios used for one of the validation of the ARTIMATION project: Conflict Detection and Resolution (CD&R) use case (link). The solution are computed by a Genetic Algorithm developped by Nicolas Durand.<br> <br> Inside, one can find: -One archive, "GA_Scenario_Solution_Dataset.zip", containing 10 couple of files (so 20 files). Each couple of file "sol_X_1.csv" and "sols_X_1.csv" are reciprocally the solutino given by the Genetic Algorithm to scenario X, and all the candidate solution explroed by the GA while solving scenario X. This archive also contain other versions of the solutions made by the GA with other parameters.<br> <br> -One archive, "GA_Toy_Dataset.zip" , containing solution to random scenarios, used to develop the first interfaces. Those solutions are used to developp the heatmatrix and heatmaps of the project (link), and visualisations for the validation (link).
DOI: 10.5281/zenodo.7437776
title: Heatmatrix and Heatmap Layers and Alternatives used in the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION)

description: This dataset contains the <strong>visualisations </strong>of the solutions of Conflict Detection and Resolution (CD&R) use case. The solution are computed by a Genetic Algorithm developped by Nicolas Durand.<br> <br> Inside, one can find: -One archive, "Heatmatrix.zip" , containing the heatmatrix creating using the solutions dataset. -One archive, "Heatmaps_Layer_Alternatives.zip", containing all the layers created and used to created the heatmaps, the heatmaps, and alternative heatmaps (with other candidate solutions). Those layers and heatmaps are used to develop other visualisation used in the validation.
DOI: 10.5281/zenodo.7437564
title: Scenarios used for the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION )

description: This dataset contains the scenarios used for one of the validation of the ARTIMATION project: Conflict Detection and Resolution (CD&R) use case. It contains the validation exercice developped at ENAC using real flown data from 2016, and modifying it to respect our constraints.<br> <br> Inside, one can find: -The file "exo_artimation.txt" a file containing the whole scenario, that can be played using REJEU platform. -10 individual files, extracted from "exo_artimation.txt" containing conflicting aircrafts. Those files where used in other steps of the ARTIMATION project, notably in the solution dataset, the heatmatrix, heatmap, storyboard developped (all linked in related identifiers).
DOI: 10.5281/zenodo.7437654
title: Solutions and Genetic algorithm dataset of the Scenarios used for the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION )

description: This dataset contains the <strong>solution </strong>of the scenarios used for one of the validation of the ARTIMATION project: Conflict Detection and Resolution (CD&R) use case (link). The solution are computed by a Genetic Algorithm developped by Nicolas Durand.<br> <br> Inside, one can find: -One archive, "GA_Scenario_Solution_Dataset.zip", containing 10 couple of files (so 20 files). Each couple of file "sol_X_1.csv" and "sols_X_1.csv" are reciprocally the solutino given by the Genetic Algorithm to scenario X, and all the candidate solution explroed by the GA while solving scenario X. This archive also contain other versions of the solutions made by the GA with other parameters.<br> <br> -One archive, "GA_Toy_Dataset.zip" , containing solution to random scenarios, used to develop the first interfaces. Those solutions are used to developp the heatmatrix and heatmaps of the project (link), and visualisations for the validation (link).
DOI: 10.5281/zenodo.7437777
title: Heatmatrix and Heatmap Layers and Alternatives used in the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION)

description: This dataset contains the <strong>visualisations </strong>of the solutions of Conflict Detection and Resolution (CD&R) use case. The solution are computed by a Genetic Algorithm developped by Nicolas Durand.<br> <br> Inside, one can find: -One archive, "Heatmatrix.zip" , containing the heatmatrix creating using the solutions dataset. -One archive, "Heatmaps_Layer_Alternatives.zip", containing all the layers created and used to created the heatmaps, the heatmaps, and alternative heatmaps (with other candidate solutions). Those layers and heatmaps are used to develop other visualisation used in the validation.
DOI: 10.5281/zenodo.7437865
title: Validation Videos and eXplainable levels used in the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION)

description: This dataset contains the <strong>explaination levels and the video </strong>used in the validation of the Conflict Detection and Resolution (CD&R) use case. The solution are computed by a Genetic Algorithm developped by Nicolas Durand.<br> <br> Inside the dataset, one can find: -One archive, " Validation_Videos_Traffic.zip ", containing the video of traffic of every scenario. -One archive, " Validation_XAI_levels.zip", containing the Blackbox, Heatmap, and Storyboard eXplainable levels for each scenario. The videos and XAI levels are used in the validation exercice.
DOI: 10.5281/zenodo.7437866
title: Validation Videos and eXplainable levels used in the Validation of the Conflict Detection and Resolution Use Case (ARTIMATION)

description: This dataset contains the <strong>explaination levels and the video </strong>used in the validation of the Conflict Detection and Resolution (CD&R) use case. The solution are computed by a Genetic Algorithm developped by Nicolas Durand.<br> <br> Inside the dataset, one can find: -One archive, " Validation_Videos_Traffic.zip ", containing the video of traffic of every scenario. -One archive, " Validation_XAI_levels.zip", containing the Blackbox, Heatmap, and Storyboard eXplainable levels for each scenario. The videos and XAI levels are used in the validation exercice.
DOI: 10.5281/zenodo.7438006
title: Data for "Convectively Transported Water Vapor Plumes in the Midlatitude Lower Stratosphere"

description: This upload contains the data used in the journal article "Convectively Transported Water Vapor Plumes in the Midlatitude Lower Stratosphere" submitted to Journal of Geophysical Research (JGR).
DOI: 10.5281/zenodo.6413187
title: Six years of submerged aquatic vegetation and nitrogen retention data in a large river

description: Here we provide five datasets that describes plant biomass, environmental variables and nitrogen retention time series in a submerged aquatic vegetation (SAV) meadow at the confluence of two agricultural tributaries with the St. Lawrence River in southern Lake Saint-Pierre. The four datasets are 1) Growing season (June 21 to September 22) daily environmental variables (water level, water temperature, light, tributaries input, and SAV biomass indicator) 2) Mean SAV biomass measured using rake or quadrat samples in the meadow 3) Modelled daily nitrate tributary inputs to the SAV bed 4) Daily nitrate output to the SAV bed estimated from a sensor 5) Daily nitrate budget Original data comes from Lake Saint-Pierre, either from publicly available government agencies data, from a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal) or from Christiane Hudon (ECCC). Data were created for an article on climate-driven variation in nitrogen retention, led by Morgan Botrel and supervisor Roxane Maranger, with Christiane Hudon, James B. Heffernan and Pascale M. Biron.
DOI: 10.5281/zenodo.6413186
title: Submerged aquatic vegetation and nitrogen retention data from 2012 to 2017 in lake Saint-Pierre, Saint Lawrence River

description: Here we provide seven datasets that describes plant biomass (2012 to 2016), environmental variables and nitrogen retention time series (2012 to 2016) in a submerged aquatic vegetation (SAV) meadow at the confluence of two agricultural tributaries (Saint-François and Yamaska) with the St. Lawrence River in southern Lake Saint-Pierre. Version 2 adds the dataset 6 and 7. The seven datasets are: 1) Growing season (June 21 to September 22) daily environmental variables (water level, water temperature, light, tributaries input, and SAV biomass indicator) 2) Mean SAV biomass measured using rake or quadrat samples in the meadow 3) Modelled daily nitrate tributary inputs to the SAV bed 4) Daily nitrate output to the SAV bed estimated from a sensor 5) Daily nitrate budget 6) Hourly nitrate output to the SAV bed and signal decomposition from ensemble empirical mode decomposition (EEMD) 7) Hourly dissolved oxygen and gas exchange velocities at the SAV bed outflow for 2016 Original data comes from Lake Saint-Pierre, either from publicly available government agencies data, from a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal) or from Christiane Hudon (ECCC). Data were created for an article on climate-driven variation in nitrogen retention, led by Morgan Botrel and supervisor Roxane Maranger, with Christiane Hudon, James B. Heffernan and Pascale M. Biron (https://doi.org/10.1029/2022WR032678).
DOI: 10.5281/zenodo.7052193
title: Submerged aquatic vegetation and nitrogen retention data from 2012 to 2017 in lake Saint-Pierre, Saint Lawrence River

description: Here we provide seven datasets that describes plant biomass (2012 to 2016), environmental variables and nitrogen retention time series (2012 to 2016) in a submerged aquatic vegetation (SAV) meadow at the confluence of two agricultural tributaries (Saint-François and Yamaska) with the St. Lawrence River in southern Lake Saint-Pierre. Version 2 adds the dataset 6 and 7. The seven datasets are: 1) Growing season (June 21 to September 22) daily environmental variables (water level, water temperature, light, tributaries input, and SAV biomass indicator) 2) Mean SAV biomass measured using rake or quadrat samples in the meadow 3) Modelled daily nitrate tributary inputs to the SAV bed 4) Daily nitrate output to the SAV bed estimated from a sensor 5) Daily nitrate budget 6) Hourly nitrate output to the SAV bed and signal decomposition from ensemble empirical mode decomposition (EEMD) 7) Hourly dissolved oxygen and gas exchange velocities at the SAV bed outflow for 2016 Original data comes from Lake Saint-Pierre, either from publicly available government agencies data, from a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal) or from Christiane Hudon (ECCC). Data were created for an article on climate-driven variation in nitrogen retention, led by Morgan Botrel and supervisor Roxane Maranger, with Christiane Hudon, James B. Heffernan and Pascale M. Biron (https://doi.org/10.1029/2022WR032678).
DOI: 10.6084/m9.figshare.1466749.v3
title: Mental Entanglement at distance with a Photomultiplier

description: Raw data (photons/half second) related to the studies "Can our Mind emit light? Mental entanglement at distance with a photomultiplier" and "Can our Mind emit light at distance? A pre-registered confirmatory experiment of mental entanglement with a photomultiplier"
DOI: 10.6084/m9.figshare.20502954
title: Table S1.pdf

description: Cre, TPH1-Cre-ERT2; CNS-NB, CNS neuroblastoma; E-NB, enteric neuroblastoma; SI-ADC, small intestinal adenocarcinoma, ICH, islet cell hyperplasia; n, no tumor found; LM, liver metastasis; PNECH, pulmonary neuroendocrine cell hyperplasia; P-NET, pancreatic neuroendocrine tumor; SCLC, small cell lung carcinoma; SM, spleen metastasis; sp, spontaneous without tamoxifen (TAM); Tom, tdTomato; *, sacrificed due to illness; **, days after TAM treatment; @, age (days) when examined.
DOI: 10.6084/m9.figshare.20502954.v1
title: Table S1.pdf

description: Cre, TPH1-Cre-ERT2; CNS-NB, CNS neuroblastoma; E-NB, enteric neuroblastoma; SI-ADC, small intestinal adenocarcinoma, ICH, islet cell hyperplasia; n, no tumor found; LM, liver metastasis; PNECH, pulmonary neuroendocrine cell hyperplasia; P-NET, pancreatic neuroendocrine tumor; SCLC, small cell lung carcinoma; SM, spleen metastasis; sp, spontaneous without tamoxifen (TAM); Tom, tdTomato; *, sacrificed due to illness; **, days after TAM treatment; @, age (days) when examined.
DOI: 10.5281/zenodo.7437374
title: Ethnographic Object Provenance Data

description: <strong>This REPO contains the following:</strong> Data TRiG ShEx Shape for data Model ShapeMap queries for validation SPARQL Queries against competency questions Validation tool used: RDFshape<br>
DOI: 10.5281/zenodo.7437375
title: Ethnographic Object Provenance Data

description: <strong>This REPO contains the following:</strong> Data TRiG ShEx Shape for data Model ShapeMap queries for validation SPARQL Queries against competency questions Validation tool used: RDFshape<br>