cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20115719
title: Dominant toxin hypothesis: unravelling the venom phenotype across micro and macroevolution

description: Supplementary fasta files for of toxins in multiple sea anemones species and populations. This includes actiniarian toxin protein sequences from the families: Actinoporins, neurotoxins such as Nematocyte Expressed Protein 3 (NEP3), sodium channel modulators (NaTx), and potassium channel toxins (KTx type 1, 2, 3 and 5 families) and proteases such as NEP6 Astacins. <br> This also includes fasta files for toxin families NaTx and KTx3 for Actinia equina (AEQU), Nematostella vectensis (NVEC) and Scolanthus callimorphus (SCAL) at the DNA, mRNA and CDS and amino acid level. <br> The diversity of Nv1 was explored across different populations of N. vectensis using transcriptomic, amplicon and genomic sequencing. We include fasta files for the CDS and amplicon DNA sequenceing of Nv1. We also a fasta of contigs that include Nv1 haplotype generated using long-read sequencing
DOI: 10.57745/p6bdhz
title: Supplementary_Chapt2_TablesS2.ods

description: :unav
DOI: 10.57745/rsjryx
title: Supplementary_Chapt2_TablesS3.ods

description: :unav
DOI: 10.57745/gk1fra
title: Supplementary_Chapt2_TablesS1.ods

description: :unav
DOI: 10.57745/9lh8wq
title: Supplementary_Chapt2_TablesS5.ods

description: :unav
DOI: 10.57745/ur6ae1
title: Supplementary_Chapt2_TablesS4.ods

description: :unav
DOI: 10.57745/p7ulps
title: Supplementary_Chapt2_TablesS6.ods

description: :unav
DOI: 10.57745/anlth0
title: Supplementary_Chapt2_TablesS8.ods

description: :unav
DOI: 10.57745/vsnuld
title: Supplementary_Chapt2_TablesS9.ods

description: :unav
DOI: 10.57745/d0rqlh
title: Supplementary_Chapt2_TablesS7.ods

description: :unav
DOI: 10.57745/v8llkm
title: Supplementary_Chapt2_TablesS12.ods

description: :unav
DOI: 10.57745/zogw7v
title: Supplementary_Chapt2_TablesS13.ods

description: :unav
DOI: 10.57745/zbaon3
title: Supplementary_Chapt2_TablesS11.ods

description: :unav
DOI: 10.57745/vnefck
title: Supplementary_Chapt2_TablesS10.ods

description: :unav
DOI: 10.6084/m9.figshare.21717503
title: C-iTRACE d18O Ocean

description: Ocean d18O from an isotope enabled coarse resolution (3˚), ocean-only simulation run from the LGM (22ka) to present day using iPOP2. Reprocessed original netcdf3 file to netcdf4 using Xarray
DOI: 10.6084/m9.figshare.21717503.v1
title: C-iTRACE d18O Ocean

description: Ocean d18O from an isotope enabled coarse resolution (3˚), ocean-only simulation run from the LGM (22ka) to present day using iPOP2. Reprocessed original netcdf3 file to netcdf4 using Xarray
DOI: 10.5281/zenodo.6040054
title: San Francisco Bay Area Kappa

description: This dataset contains....
DOI: 10.57833/cidacs/ji2zkh
title: Cobertura da Atenção Básica (AB) - julho de 2007 a dezembro de 2020

description: Histórico da cobertura populacional estimada das equipes de saúde da família (eSF) e das equipes de atenção básica (eAB) no Brasil, macrorregiões, estados, regiões e municípios a partir de julho de 2007 até dezembro de 2020.
DOI: 10.57833/cidacs/jgnkph
title: Cobertura da Atenção Primária à Saúde (APS) - a partir de 2021

description: Histórico da cobertura populacional estimada das equipes de saúde da família (eSF) e das equipes de atenção primária (eAP) nos municípios do Brasil a partir de janeiro de 2021.
DOI: 10.57833/cidacs/mxm1ei
title: Cobertura de Agentes Comunitários de Saúde (ACS) - julho de 2007 a dezembro de 2018

description: Histórico da cobertura populacional estimada dos agentes comunitários de saúde na atenção básica no Brasil, macrorregiões, estados, regiões de saúde e municípios a partir de julho de 2007 até dezembro de 2018.
DOI: 10.57745/jbh6fo
title: Supplementary_Chpt3_TablesS4.ods

description: :unav
DOI: 10.7479/aeth-rz39
title: Sammlungs- und Dokumentationsprofil Historische Bild- und Schriftgutsammlungen

description: Das Archiv des Museums für Naturkunde Berlin überliefert als Forschungs- und Informationsinfrastruktur mit seinen Beständen Vergangenheit und Gegenwart des Museums für die Zukunft. Es sichert die Dokumentation seines kulturellen und wissenschaftlichen Erbes. Mit ihrem Schwerpunkt auf der Geschichte der Naturwissenschaften ermöglichen die Bestände die Beforschung gesellschaftlich relevanter Forschungsfragen der Wissenschafts-, aber auch Institutions-, Museums- und Globalgeschichte. Seine breit gefächerten Inhalte und Medien erlauben verschiedenste disziplinären Perspektiven, innovative Zugriffe und Transfermöglichkeiten im Analogen wie im Digitalen. Das Archiv betreut sämtliche Schritte des Dokumentenlebenszyklus von der Beratung der abgebenden Stellen zu Abgabepflicht und –kriterien, über die Bewertung und Übernahme, inhaltliche Erschließung, Zugänglichmachung und Nutzung bis hin zur Langzeitsicherung. Die Grundlage einer gezielten und transparenten Überlieferungsbildung bildet das vorliegende Sammlungs- bzw. Dokumentationsprofil. Als Stiftung öffentlichen Rechts des Landes Berlin unterliegt das Museum für Naturkunde dem Archivgesetz (§ 2 (4) ArchBG) und damit der Vorgabe sein (amtliches) Verwaltungsschriftgut archivfachlich zu überliefern. Über die Dokumentationspflicht hinaus werden die einzigartigen Bestände in ihrer inhaltlichen und medialen Vielfalt durch die aktive Übernahme von Sammlungsgut ergänzt.
DOI: 10.5281/zenodo.7433605
title: PERTEMUAN 11_14 DESEMBER 2022_ANALISIS INVESTASI SEKTOR PUBLIK_MANAJEMEN KEUANGAM SEKTOR PUBLIK_STIESIA SURABAYA_JAM 18.00-20.30

description: <strong>Capaian Pembelajaran Mata Kuliah (CPMK)</strong> Mahasiswa mampu menganalisis pelaporan keuangan sektor publik dan mengevaluasi penerapan kebijakan manajemen keuangan dalam proses pengambilan keputusan di berbagai kegiatan sektor publik dan terampil merancang dan mengimplementasikan berbagai taktik dalam manajemen keuangan sektor publik secara mandiri dan bertanggung jawab Mahasiswa mampu menilai aspek kelayakan investasi, faktor-faktor yang memengaruhi investasi dan teknik dasar penilaian investasi
description: PERTEMUAN 11_14 DESEMBER 2022_ANALISIS INVESTASI SEKTOR PUBLIK_MANAJEMEN KEUANGAM SEKTOR PUBLIK_STIESIA SURABAYA_JAM 18.00-20.30
DOI: 10.5281/zenodo.7433604
title: PERTEMUAN 11_14 DESEMBER 2022_ANALISIS INVESTASI SEKTOR PUBLIK_MANAJEMEN KEUANGAM SEKTOR PUBLIK_STIESIA SURABAYA_JAM 18.00-20.30

description: <strong>Capaian Pembelajaran Mata Kuliah (CPMK)</strong> Mahasiswa mampu menganalisis pelaporan keuangan sektor publik dan mengevaluasi penerapan kebijakan manajemen keuangan dalam proses pengambilan keputusan di berbagai kegiatan sektor publik dan terampil merancang dan mengimplementasikan berbagai taktik dalam manajemen keuangan sektor publik secara mandiri dan bertanggung jawab Mahasiswa mampu menilai aspek kelayakan investasi, faktor-faktor yang memengaruhi investasi dan teknik dasar penilaian investasi
description: PERTEMUAN 11_14 DESEMBER 2022_ANALISIS INVESTASI SEKTOR PUBLIK_MANAJEMEN KEUANGAM SEKTOR PUBLIK_STIESIA SURABAYA_JAM 18.00-20.30
DOI: 10.5281/zenodo.4279775
title: North Atlantic basin-scale multi-criteria assessment database to inform management recommendations to protect Vulnerable Marine Ecosystems

description: We applied the International Council for the Exploration of the Sea (ICES) multi criteria assessment (MCA) method for identifying VMEs in the North-East Atlantic (ICES, 2016a,b; Morato et al., 2018) from ATLAS VME database to provide the first North Atlantic Ocean basin-scale VME assessment. This MCA is a taxa-dependent spatial method that incorporates the fact that not all VME indicators have the same vulnerability to human impacts, and thus should not be weighted equally. By including a measure of the confidence associated with each VME record, this methodology also considers some of the uncertainties associated with the sampling methodologies, the reported taxonomy, and data quality issues. Equally important, this dataset highlights areas in the North Atlantic that have been poorly sampled and that require further attention. Finally, this methodology also allows for the evaluation and comparison of the VME likelihood with spatial fisheries data that may directly generate significant adverse impacts on VMEs. In the data report, we made the “North Atlantic basin-scale VME index dataset” publicly, thus allowing its consultation and use by scientists, managers, or other relevant stakeholders.
description: This work contributes to the European Union's Horizon 2020 research and innovation programme under grant agreement No 678760 (ATLAS). This output reflects only the authors' views and the European Union cannot be held responsible for any use that may be made of the information contained therein. TM was supported by Program Investigador FCT (IF/01194/2013), IFCT Exploratory Project (IF/01194/2013/CP1199/CT0002) from the Fundação para a Ciência e Tecnologia (POPH and QREN), PO2020 MapGes (Acores-01-0145-FEDER-000056). TM, CKP, LF, CDC, LR, JMGI, GHT, and MCS also acknowledge funds provided by the Fundação para a Ciência e a Tecnologia (FCT) through the plurennial strategic project (UIDB/05634/2020) granted to Okeanos.
DOI: 10.5281/zenodo.4279776
title: North Atlantic basin-scale multi-criteria assessment database to inform management recommendations to protect Vulnerable Marine Ecosystems

description: We applied the International Council for the Exploration of the Sea (ICES) multi criteria assessment (MCA) method for identifying VMEs in the North-East Atlantic (ICES, 2016a,b; Morato et al., 2018) from ATLAS VME database to provide the first North Atlantic Ocean basin-scale VME assessment. This MCA is a taxa-dependent spatial method that incorporates the fact that not all VME indicators have the same vulnerability to human impacts, and thus should not be weighted equally. By including a measure of the confidence associated with each VME record, this methodology also considers some of the uncertainties associated with the sampling methodologies, the reported taxonomy, and data quality issues. Equally important, this dataset highlights areas in the North Atlantic that have been poorly sampled and that require further attention. Finally, this methodology also allows for the evaluation and comparison of the VME likelihood with spatial fisheries data that may directly generate significant adverse impacts on VMEs. In the data report, we made the “North Atlantic basin-scale VME index dataset” publicly, thus allowing its consultation and use by scientists, managers, or other relevant stakeholders.
description: This work contributes to the European Union's Horizon 2020 research and innovation programme under grant agreement No 678760 (ATLAS). This output reflects only the authors' views and the European Union cannot be held responsible for any use that may be made of the information contained therein. TM was supported by Program Investigador FCT (IF/01194/2013), IFCT Exploratory Project (IF/01194/2013/CP1199/CT0002) from the Fundação para a Ciência e Tecnologia (POPH and QREN), PO2020 MapGes (Acores-01-0145-FEDER-000056). TM, CKP, LF, CDC, LR, JMGI, GHT, and MCS also acknowledge funds provided by the Fundação para a Ciência e a Tecnologia (FCT) through the plurennial strategic project (UIDB/05634/2020) granted to Okeanos.
DOI: 10.5281/zenodo.4727163
title: Blue Azores Program Expedition 2018, Station 57, Dive 15: annotation of Paragorgia johnsoni Gray, 1862

description: Annotation of <em>Paragorgia johnsoni </em>Gray, 1862 colonies from underwater video footage recorded during the Blue Azores 2018 Expedition with the ROV <em>Luso</em> onboard the NRP <em>Almirante Gago Coutinho</em>, Station 57, Dive 15 (June 23<sup>rd</sup>, 2018). The images correspond to the octocoral garden discovered between 545 and 595 m depth on the slopes of a small ridge-like structure located on the Mid-Atlantic Ridge, in the Azores region.
description: This dataset contributes to the Blue Azores Program of the Azores Regional Government in partnership with the Oceano Azul Foundation, the Waitt Institute and IMAR & Okeanos Research Center of the Azores University, as well as to the European Union's Horizon 2020 research and innovation programme under grant agreement No 678760 (ATLAS) and the Azores Government PO2020 MapGES project (Acores-01-0145-FEDER-000056). This output reflects only the authors' views and the European Union cannot be held responsible for any use that may be made of the information contained therein. TM was also supported by Program Investigador from the Fundação para a Ciência e Tecnologia (FCT) (IF/01194/2013) and IFCT (POPH and QREN) Exploratory Project (IF/01194/2013/CP1199/CT0002). TM and MCS were also supported by Program Stimulus of Scientific Employment (CCCIND/03345/2020 and CCCIND/03346/2020, respectively) from the FCT and by the H2020 programme No 689518 (MERCES) and No 818123 (iAtlantic). CD-C was supported by the Azores Government PO2020 project DeepWalls (ACORES-01-0145-FEDER-000124). MR was supported by FCT PhD grant (PD/BD/111953/2015) and GHT by the Azores Government DRCT PhD grant (M3.1.a/F/052/2015). TM, CDC, MR, LR, GHT, LF and MCS also acknowledge funds provided by the FCT through the plurennial strategic project (UIDB/05634/2020) granted to Okeanos. The authors would like to thank the Portuguese Hydrographic Institute and the Portuguese Navy for the multibeam bathymetry data collected and the crew of the NRP Almirante Gago Coutinho and the ROV Luso team for their committed interest.
DOI: 10.5281/zenodo.4727164
title: Blue Azores Program Expedition 2018, Station 57, Dive 15: annotation of Paragorgia johnsoni Gray, 1862

description: Annotation of <em>Paragorgia johnsoni </em>Gray, 1862 colonies from underwater video footage recorded during the Blue Azores 2018 Expedition with the ROV <em>Luso</em> onboard the NRP <em>Almirante Gago Coutinho</em>, Station 57, Dive 15 (June 23<sup>rd</sup>, 2018). The images correspond to the octocoral garden discovered between 545 and 595 m depth on the slopes of a small ridge-like structure located on the Mid-Atlantic Ridge, in the Azores region.
description: This dataset contributes to the Blue Azores Program of the Azores Regional Government in partnership with the Oceano Azul Foundation, the Waitt Institute and IMAR & Okeanos Research Center of the Azores University, as well as to the European Union's Horizon 2020 research and innovation programme under grant agreement No 678760 (ATLAS) and the Azores Government PO2020 MapGES project (Acores-01-0145-FEDER-000056). This output reflects only the authors' views and the European Union cannot be held responsible for any use that may be made of the information contained therein. TM was also supported by Program Investigador from the Fundação para a Ciência e Tecnologia (FCT) (IF/01194/2013) and IFCT (POPH and QREN) Exploratory Project (IF/01194/2013/CP1199/CT0002). TM and MCS were also supported by Program Stimulus of Scientific Employment (CCCIND/03345/2020 and CCCIND/03346/2020, respectively) from the FCT and by the H2020 programme No 689518 (MERCES) and No 818123 (iAtlantic). CD-C was supported by the Azores Government PO2020 project DeepWalls (ACORES-01-0145-FEDER-000124). MR was supported by FCT PhD grant (PD/BD/111953/2015) and GHT by the Azores Government DRCT PhD grant (M3.1.a/F/052/2015). TM, CDC, MR, LR, GHT, LF and MCS also acknowledge funds provided by the FCT through the plurennial strategic project (UIDB/05634/2020) granted to Okeanos. The authors would like to thank the Portuguese Hydrographic Institute and the Portuguese Navy for the multibeam bathymetry data collected and the crew of the NRP Almirante Gago Coutinho and the ROV Luso team for their committed interest.
DOI: 10.26106/ns2q-k734
title: Proteomic profiling of exosomes derived from pancreatic beta-cells cultured under hyperglycemia - concept 
title: Proteomics of EVs from human beta-cells
DOI: 10.25318/1310085901-eng
title: Nursing and residential care facilities, source of operating revenue by industry, annual

description: Percentages of nursing and residential care facility operating revenue by activity, by 2017 NAICS (North American Industry Classification System), for Canada, provinces and territories, annual.
DOI: 10.6084/m9.figshare.21717527
title: RaMP Database MySQL Dump v2.2.0 20221213

description: This is a MySQL sql file dump of the RaMP Database version 2.2.0. This version has updated data from our data sources with update date of 12/13/2022. This version extends to include secondary HMDB IDs and a process to connect metabolites within the database having the same inchi key prefix.
DOI: 10.6084/m9.figshare.21717527.v1
title: RaMP Database MySQL Dump v2.2.0 20221213

description: This is a MySQL sql file dump of the RaMP Database version 2.2.0. This version has updated data from our data sources with update date of 12/13/2022. This version extends to include secondary HMDB IDs and a process to connect metabolites within the database having the same inchi key prefix.
DOI: 10.3886/e112444v1-131285
title: Replication data for: From Financial Crash to Debt Crisis

description: Newly developed historical time series on public debt, along with data on external debts, allow a deeper analysis of the debt cycles underlying serial debt and banking crises. We test three related hypotheses at both "world" aggregate levels and on an individual country basis. First, external debt surges are an antecedent to banking crises. Second, banking crises (domestic and those in financial centers) often precede or accompany sovereign debt crises; we find they help predict them. Third, public borrowing surges ahead of external sovereign default, as governments have "hidden domestic debts" that exceed the better documented levels of external debt. (JEL E44, F34, F44, G01, H63, N20)
DOI: 10.25318/1310085901-fra
title: Établissements de soins infirmiers et de soins pour bénéficiaires internes, source des revenus d'exploitation par industrie, annuel

description: Pourcentages des revenus d'exploitation par activtié, par SCIAN 2017 (Système de classification des industries de l'Amérique du Nord), pour le Canada, provinces et territoires, annuel.
DOI: 10.6084/m9.figshare.21717776
title: Working dogs in dynamic on-duty environments

description: Data on the latency to start a task, the duration of the task and task accuracy before during and after exposure to three different light and acoustic distractors during dog training.
DOI: 10.25318/1310086001-eng
title: Nursing and residential care facilities, type of employee by industry and employee status, annual

description: Totals and percentages of nursing and residential care facility employees for nurses, physicians and therapists, direct care support workers, and indirect care employees, by 2017 NAICS (North American Industry Classification System), for Canada, provinces and territories, annual.
DOI: 10.25318/1310086001-fra
title: Établissements de soins infirmiers et de soins pour bénéficiaires internes, type d'employé par industrie et statut des employés, annuel

description: Totaux et pourcentages d'employés infirmiers, médecins et thérapeutes, employés de soutien aux soins directs et soins indirects dans les établissements de soins infirmiers et de soins pour bénéficiaires internes, par SCIAN 2017 (Système de classification des industries de l'Amérique du Nord), pour le Canada, provinces et territoires, annuel.
DOI: 10.5281/zenodo.7433623
title: Build and measurements of Linux kernel configurations across different versions

description: With large scale and complex configurable systems, it is hard for users to choose the right combination of options (i.e., configurations) in order to obtain the wanted trade-off between functionality and performance goals such as speed or size. Machine learning can help in relating these goals to the configurable system options, and thus, predict the effect of options on the outcome, typically after a costly training step. However, many configurable systems evolve at such a rapid pace that it is impractical to retrain a new model from scratch for each new version. Taking the extreme case of the Linux kernel with its ≈ 14, 500 configuration options, we investigate how binary size predictions of kernel size degrade over successive versions (and how transfer learning can be adapted and applied to mitigate this degradation). We used and are sharing a unique and large dataset constituted of the binary sizes (compressed and non-compressed) of thousands of configurations for different versions of the kernel, spanning three years (4.13, 4.15, 4.20, 5.0, 5.4, 5.7, and 5.8). Overall, around 200K configurations over 10K+ options/features and 6 versions. This dataset has been used in the Transactions of Software Engineering (TSE) article "Transfer Learning Across Variants and Versions: The Case of Linux Kernel Size" (preprint: https://hal.inria.fr/hal-03358817)
description: works at least on pandas version : 1.4.3 (for the pickle)
DOI: 10.5281/zenodo.7433622
title: Build and measurements of Linux kernel configurations across different versions

description: With large scale and complex configurable systems, it is hard for users to choose the right combination of options (i.e., configurations) in order to obtain the wanted trade-off between functionality and performance goals such as speed or size. Machine learning can help in relating these goals to the configurable system options, and thus, predict the effect of options on the outcome, typically after a costly training step. However, many configurable systems evolve at such a rapid pace that it is impractical to retrain a new model from scratch for each new version. Taking the extreme case of the Linux kernel with its ≈ 14, 500 configuration options, we investigate how binary size predictions of kernel size degrade over successive versions (and how transfer learning can be adapted and applied to mitigate this degradation). We used and are sharing a unique and large dataset constituted of the binary sizes (compressed and non-compressed) of thousands of configurations for different versions of the kernel, spanning three years (4.13, 4.15, 4.20, 5.0, 5.4, 5.7, and 5.8). Overall, around 200K configurations over 10K+ options/features and 6 versions. This dataset has been used in the Transactions of Software Engineering (TSE) article "Transfer Learning Across Variants and Versions: The Case of Linux Kernel Size" (preprint: https://hal.inria.fr/hal-03358817)
description: works at least on pandas version : 1.4.3 (for the pickle)
DOI: 10.5281/zenodo.7433747
title: abacopteris_gymnopteridifrons_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7433746
title: abacopteris_gymnopteridifrons_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7225970
title: How Ornithopters Can Perch Autonomously On A Branch

description: Data used in the publication "How Ornithopters Can Perch Autonomously On A Branch", including both design and experimental data.
DOI: 10.5281/zenodo.7225969
title: How Ornithopters Can Perch Autonomously On A Branch

description: Data used in the publication "How Ornithopters Can Perch Autonomously On A Branch", including both design and experimental data.
DOI: 10.5287/bodleian:orboa40y2
title: WEALTHPOL Inheritance Tax Dataset
DOI: 10.25318/1310086201-eng
title: Nursing and residential care facilities, type of service offered by industry, annual

description: Totals and percentages of nursing and residential care facility services offered, for health and medical services, counselling and mental health services, and personal care and wellbeing services, by 2017 NAICS (North American Industry Classification System), for Canada, provinces and territories, annual.