cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21335/nmdc-1220066972
title: Marine CO2 system and inorganic nutrients in the water column along the Gimsøy- section in the Norwegian Sea in 2020

description: Marine CO2 system data (total alkalinity, and total dissolved inorganic carbon) and nutrients were collected from full water column on the IMR repeat sections in the Norwegian Sea; Gimsøy-NW onboard the RV Kristine Bonnevie on cruise 2020608. The seawater samples were collected in 250 ml borosilicate bottles with glass stoppers from a CTD-Rosette (12-Niskin bottle) following standard procedures. The samples were preserved with 50 µL of saturated mercuric chloride (HgCl2) solution immediately after sampling and stored cool and dark until analysis within 6 months at Institute of Marine Research, Tromsø, Norway. DIC was determined using gas extraction of acidified samples followed by coulometric titration and photometric detection using a Versatile Instrument for the Determination of Titration carbonate (VINDTA 3D, Marianda, Germany). determined by potentiometric titration with 0.1 N hydrochloric acid using a Versatile Instrument for the Determination of Titration Alkalinity (VINDTA 3S, Marianda, Germany). Routine analyses of Certified Reference Materials (CRM, provided by A. G. Dickson, Scripps Institution of Oceanography, United States) ensured the accuracy of the measurements, which was better than ±2 and ±2 µmol kg-1 for DIC and AT, respectively. Description of the analytical methods can be found as a summary in the data file, as well as in the annual reports by Chierici et al., 2012:2017, and Jones et al., 2018. Sea water samples for the macronutrients nitrate+nitrite [NO3–+NO2-], phosphate [PO43–], and silicic acid [Si(OH)4] were drawn from the Niskin bottles into 20 mL vials, preserved with chloroform and stored at 4 °C. Analysis were carried out using a Flow Solution IV analyzer from O.I. Analytical, United States, following Grasshof et al. (2009) at the Institute of Marine Research, Bergen, Norway. The analyser was calibrated using reference seawater from Ocean Scientific International Ltd., United Kingdom. The uncertainty based on QUASIMEME ring-test were 0.4 µmol kg-1 for [NO3-+NO2–], 0.06 µmol kg-1 for [PO43–] and 0.7 µmol kg-1 for Si(OH)4, respectively. This study is a contribution to the project Monitoring ocean acidification in Norwegian waters/Havforsuringsovervåking i norske farvann” funded by the Norwegian Environment Agency (Miljødirektoratet) project# 17078007. Data is also published in Vannmiljø as well as contributes to SDG 14.3.1 Indicator: Average marine acidity (pH)
DOI: 10.21335/nmdc-866711466
title: Marine CO2 system and inorganic nutrients in the water column along the Svinøy- section in the Norwegian Sea in January and April 2020

description: Marine CO2 system data (total alkalinity, and total dissolved inorganic carbon) and nutrients were collected from full water column on the IMR repeat Svinøy-NW section in the Norwegian Sea. Sampling were performed on two cruises; in January on board the RV Johan Hjort (cruise# 2020202) and in April onboard RV Kristine Bonnevie (cruise# 2020622). The seawater samples were collected in 250 ml borosilicate bottles with glass stoppers from a CTD-Rosette (12-Niskin bottle) following standard procedures. The samples were preserved with 50 µL of saturated mercuric chloride (HgCl2) solution immediately after sampling and stored cool and dark until analysis within 6 months at Institute of Marine Research, Tromsø, Norway. DIC was determined using gas extraction of acidified samples followed by coulometric titration and photometric detection using a Versatile Instrument for the Determination of Titration carbonate (VINDTA 3D, Marianda, Germany). determined by potentiometric titration with 0.1 N hydrochloric acid using a Versatile Instrument for the Determination of Titration Alkalinity (VINDTA 3S, Marianda, Germany). Routine analyses of Certified Reference Materials (CRM, provided by A. G. Dickson, Scripps Institution of Oceanography, United States) ensured the accuracy of the measurements, which was better than ±2 and ±2 µmol kg-1 for DIC and AT, respectively. Description of the analytical methods can be found as a summary in the data file, as well as in the annual reports by Chierici et al., 2012 to 2017, Jones et al., 2018 to 2020, Skjelvan et al., 2021. Sea water samples for the macronutrients nitrate+nitrite [NO3–+NO2-], phosphate [PO43–], and silicic acid [Si(OH)4] were drawn from the Niskin bottles into 20 mL vials, preserved with chloroform and stored at 4 °C. Analysis were carried out using a Flow Solution IV analyzer from O.I. Analytical, United States, following Grasshof et al. (2009) at the Institute of Marine Research, Bergen, Norway. The analyser was calibrated using reference seawater from Ocean Scientific International Ltd., United Kingdom. The uncertainty based on QUASIMEME ring-test were 0.4 µmol kg-1 for [NO3-+NO2–], 0.06 µmol kg-1 for [PO43–] and 0.7 µmol kg-1 for Si(OH)4, respectively. This study is a contribution to the project Monitoring ocean acidification in Norwegian waters/Havforsuringsovervåking i norske farvann” funded by the Norwegian Environment Agency (Miljødirektoratet) project# 17078007. Data is also published in Vannmiljø as well as contributes to SDG 14.3.1 Indicator: Average marine acidity (pH)
DOI: 10.21335/nmdc-1384839634
title: Marine CO2 system and inorganic nutrients in the water column along the Fugløya-Bjørnøya section in the Barents Sea in 2020

description: Marine CO2 system data (total alkalinity, and total dissolved inorganic carbon) and nutrients were collected from full water column on the IMR repeat section between Fugløya-Bjørnøya in the Barents Sea Opening onboard the RV Johan Hjort on cruise number 2020202. The seawater samples were collected in 250 ml borosilicate bottles with glass stoppers from a CTD-Rosette (12-Niskin bottle) following standard procedures. The samples were preserved with 50 µL of saturated mercuric chloride (HgCl2) solution immediately after sampling and stored cool and dark until analysis within 6 months at Institute of Marine Research, Tromsø, Norway. DIC was determined using gas extraction of acidified samples followed by coulometric titration and photometric detection using a Versatile Instrument for the Determination of Titration carbonate (VINDTA 3D, Marianda, Germany). determined by potentiometric titration with 0.1 N hydrochloric acid using a Versatile Instrument for the Determination of Titration Alkalinity (VINDTA 3S, Marianda, Germany). Routine analyses of Certified Reference Materials (CRM, provided by A. G. Dickson, Scripps Institution of Oceanography, United States) ensured the accuracy of the measurements, which was better than ±2 and ±2 µmol kg-1 for DIC and AT, respectively. Description of the analytical methods can be found as a summary in the data file, as well as in the annual reports by Chierici et al., 2012:2017, and Jones et al., 2018. Sea water samples for the macronutrients nitrate+nitrite [NO3–+NO2-], phosphate [PO43–], and silicic acid [Si(OH)4] were drawn from the Niskin bottles into 20 mL vials, preserved with chloroform and stored at 4 °C. Analysis were carried out using a Flow Solution IV analyzer from O.I. Analytical, United States, following Grasshof et al. (2009) at the Institute of Marine Research, Bergen, Norway. The analyser was calibrated using reference seawater from Ocean Scientific International Ltd., United Kingdom. The uncertainty based on QUASIMEME ring-test were 0.4 µmol kg-1 for [NO3-+NO2–], 0.06 µmol kg-1 for [PO43–] and 0.7 µmol kg-1 for Si(OH)4, respectively. This study is a contribution to the project Monitoring ocean acidification in Norwegian waters/Havforsuringsovervåking i norske farvann” funded by the Norwegian Environment Agency (Miljødirektoratet) project# 17078007. Data is also published in Vannmiljø as well as contributes to SDG 14.3.1 Indicator: Average marine acidity (pH)
DOI: 10.21335/nmdc-1996337184
title: Marine CO2 system and inorganic nutrients in the water column along the Torungen- Hirtshals section in the Skagerrak in 2020

description: Marine CO2 system data (total alkalinity, and total dissolved inorganic carbon) and nutrients were collected from full water column on the IMR repeat Torungen-Hirtshals section in the Skagerrak. Sampling was performed in January on board RV GM Dannevig. The seawater samples were collected from a CTD-Rosette (12-Niskin bottle) following standard procedures and analyzed at Institute of Marine Research, Tromsø, Norway after the cruises following the method described in Dickson et al. (2007). DIC was determined using gas extraction of acidified samples followed by coulometric titration and photometric detection using a Versatile Instrument for the Determination of Titration carbonate (VINDTA 3D, Marianda, Germany). determined by potentiometric titration with 0.1 N hydrochloric acid using a Versatile Instrument for the Determination of Titration Alkalinity (VINDTA 3S, Marianda, Germany). Routine analyses of Certified Reference Materials (CRM, provided by A. G. Dickson, Scripps Institution of Oceanography, United States) ensured the accuracy of the measurements, which was better than ±2 and ±2 µmol kg-1 for DIC and AT, respectively. Description of the analytical methods can be found as a summary in the data file, as well as in the annual reports by Chierici et al., 2012 to 2017, Jones et al., 2018 to 2020, Skjelvan et al., 2021. Water samples for analysis of nutrients [NO2, NO-, Si(OH)4, PO4] were preserved with 250 µL chloroform until post-cruise analysis following standard methods (Grasshoff et al., 2009) at the chemical laboratory at IMR, Bergen. Three replicates were analyzed for each sample. This study is a contribution to the project Monitoring ocean acidification in Norwegian waters/Havforsuringsovervåking i norske farvann” funded by the Norwegian Environment Agency (Miljødirektoratet) project# 17078007. Data is also published in Vannmiljø as well as contributes to SDG 14.3.1 Indicator: Average marine acidity (pH)
DOI: 10.17036/researchdata.aston.ac.uk.00000532
title: Readers Responding to Mary Borden's 'Belgium'
DOI: 10.48370/ofd/mlmbcl/uibyox
title: Betula litwinowii_pąki - ekstrakt substancji lotnych.pdf

description: :unav
DOI: 10.48370/ofd/mlmbcl
title: Betula litwinowii_pąki - ekstrakt substancji lotnych

description: ekstrakt substancji lotnych
DOI: 10.48370/ofd/47o8no/9bblmy
title: Betula maximowicziana_pąki - ekstrakt substancji lotnych.pdf

description: :unav
DOI: 10.48370/ofd/47o8no
title: Betula maximowicziana_pąki - ekstrakt substancji lotnych

description: ekstrakt substancji lotnych
DOI: 10.6084/m9.figshare.16681771.v1
title: The Brief Emotional Experience Scale (BEES): A new measure for mood monitoring

description: Raw data for paper titled: The Brief Emotional Experience Scale (BEES): A new measure for mood monitoring
DOI: 10.5281/zenodo.5763754
title: What Makes a Good Commit Message?

description: <strong>What-Makes-a-Good-Commit-Message?</strong> This repository contains the main data and scripts used in "What Makes a Good Commit Message" <strong>Dataset:</strong> The folder dataset contains the following files. literature survery.xlsx It contains the data of 46 relevant literature reviewed in this study (Section 3.2). Questionnaire.pdf It is the questionnaire sent to experienced contributors. It contains three questions. It also contains an example of the initialized questionnaire. Frequency.pdf It describes the number and proportion of occurrences of a category/subcategory. posts list.xlsx It contains all posts we studied in Sec. 3.2. sampled messages.csv It contains meta-information of 1649 labeled commit messages. label = 0 means a commit message contains "Why and What". label = 1 means a commit message contains "Neither Why nor What". label = 2 means a commit message contains "No What". label = 3 means a commit message contains "No Why". if_mulit_commit = 1 means a commit is non-atomic. new_message1 means a message after preprocessing. maintenance type and expression way.xlsx It contains the results of our RQ2: the expression ways of Why and What, as well as links to maintenance types. <strong>CommitMessage (Scripts):</strong> The folder contains the following scripts files. Preprocessor It contains the preprocessing of commit messages, including the replacement of token in the message, etc. ModelTraining It contains the code for our model training, that is, the implementation of different classification techniques.
DOI: 10.6084/m9.figshare.16681771.v2
title: The Brief Emotional Experience Scale (BEES): A measure of positive and negative emotion for mood monitoring

description: Raw data for paper titled: The Brief Emotional Experience Scale (BEES): Reliability and validity as a measure of positive and negative emotion for mood monitoring
DOI: 10.5281/zenodo.5763708
title: What Makes a Good Commit Message?

description: <strong>What-Makes-a-Good-Commit-Message?</strong> This repository contains the main data and scripts used in "What Makes a Good Commit Message" <strong>Dataset:</strong> The folder dataset contains the following files. literature survery.xlsx It contains the data of 46 relevant literature reviewed in this study (Section 3.2). Questionnaire.pdf It is the questionnaire sent to experienced contributors. It contains three questions. It also contains an example of the initialized questionnaire. Frequency.pdf It describes the number and proportion of occurrences of a category/subcategory. posts list.xlsx It contains all posts we studied in Sec. 3.2. sampled messages.csv It contains meta-information of 1649 labeled commit messages. label = 0 means a commit message contains "Why and What". label = 1 means a commit message contains "Neither Why nor What". label = 2 means a commit message contains "No What". label = 3 means a commit message contains "No Why". if_mulit_commit = 1 means a commit is non-atomic. new_message1 means a message after preprocessing. maintenance type and expression way.xlsx It contains the results of our RQ2: the expression ways of Why and What, as well as links to maintenance types. <strong>CommitMessage (Scripts):</strong> The folder contains the following scripts files. Preprocessor It contains the preprocessing of commit messages, including the replacement of token in the message, etc. ModelTraining It contains the code for our model training, that is, the implementation of different classification techniques.
DOI: 10.5281/zenodo.5760335
title: What Makes a Good Commit Message?

description: <strong>What-Makes-a-Good-Commit-Message?</strong> This repository contains the main data and scripts used in "What Makes a Good Commit Message" <strong>Dataset:</strong> The folder dataset contains the following files. literature survery.xlsx It contains the data of 46 relevant literature reviewed in this study (Section 3.2). Questionnaire.pdf It is the questionnaire sent to experienced contributors. It contains three questions. It also contains an example of the initialized questionnaire. Frequency.pdf It describes the number and proportion of occurrences of a category/subcategory. posts list.xlsx It contains all posts we studied in Sec. 3.2. sampled messages.csv It contains meta-information of 1649 labeled commit messages. label = 0 means a commit message contains "Why and What". label = 1 means a commit message contains "Neither Why nor What". label = 2 means a commit message contains "No What". label = 3 means a commit message contains "No Why". if_mulit_commit = 1 means a commit is non-atomic. new_message1 means a message after preprocessing. maintenance type and expression way.xlsx It contains the results of our RQ2: the expression ways of Why and What, as well as links to maintenance types. <strong>CommitMessage (Scripts):</strong> The folder contains the following scripts files. Preprocessor It contains the preprocessing of commit messages, including the replacement of token in the message, etc. ModelTraining It contains the code for our model training, that is, the implementation of different classification techniques.
DOI: 10.6084/m9.figshare.17134787
title: BITUMEN DATA

description: Matlab codes + data of measured water properties
DOI: 10.5281/zenodo.5763768
title: ERAI corresponding to NCEP initializations

description: ERAI corresponding to NCEP initializations
DOI: 10.5281/zenodo.5763767
title: ERAI corresponding to NCEP initializations

description: ERAI corresponding to NCEP initializations
DOI: 10.5281/zenodo.5763764
title: Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)

description: This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”
DOI: 10.5281/zenodo.5763763
title: Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)

description: This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”
DOI: 10.5281/zenodo.5763720
title: Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)

description: This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”
DOI: 10.5281/zenodo.5296467
title: Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)

description: This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”
DOI: 10.48370/ofd/hojj7p/3t1qbt
title: Betula pubescens_pąki - ekstrakt substancji lotnych.pdf

description: :unav
DOI: 10.48370/ofd/hojj7p
title: Betula pubescens_pąki - ekstrakt substancji lotnych

description: ekstrakt substancji lotnych
DOI: 10.5281/zenodo.5189263
title: SARS-CoV-2 raw fastq files

description: Illumina paired end FASTQ files from MiSeq. Sequenced at the African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State. Training data
DOI: 10.5281/zenodo.5189262
title: SARS-CoV-2 raw fastq files

description: Illumina paired end FASTQ files from MiSeq. Sequenced at the African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State. Training data
DOI: 10.6084/m9.figshare.17134778
title: Test data

description: Test data for Alpha-Tri & Alpha-XIC, see https://github.com/YuAirLab/Alpha-Tri
DOI: 10.6084/m9.figshare.17134778.v2
title: Test data

description: Test data for Alpha-Tri & Alpha-XIC, see https://github.com/YuAirLab/Alpha-Tri
DOI: 10.6084/m9.figshare.17134778.v1
title: HeLa-1h.mzML

description: Test data for Alpha-Tri & Alpha-XIC, see https://github.com/YuAirLab/Alpha-Tri
DOI: 10.5281/zenodo.5468290
title: Crystal Structure and Energetics of Arsenic(III)-oxide Intercalates with Rubidium Chloride and Their Comparison with Isostructural Intercalates of Potassium Halides. Raw diffraction data

description: Raw diffraction data for: intercalate <strong>P<sub>RbCl</sub></strong> - pg152 intercalate <strong>Y'<sub>RbCl</sub></strong> measurement of a small crystal - pg149 measurement of a large crystal - pg153 CSD 2073008-2073009. Crystal structures published in a Crystal Growth & Design article DOI: 10.1021/acs.cgd.1c01220
description: Funding by the Polish National Science Center (project no. 2020/39/D/ST4/00128) and Warsaw University of Technology (NCHEM.1) is gratefully acknowledged.
DOI: 10.5281/zenodo.5468289
title: Crystal Structure and Energetics of Arsenic(III)-oxide Intercalates with Rubidium Chloride and Their Comparison with Isostructural Intercalates of Potassium Halides. Raw diffraction data

description: Raw diffraction data for: intercalate <strong>P<sub>RbCl</sub></strong> - pg152 intercalate <strong>Y'<sub>RbCl</sub></strong> measurement of a small crystal - pg149 measurement of a large crystal - pg153 CSD 2073008-2073009. Crystal structures published in a Crystal Growth & Design article DOI: 10.1021/acs.cgd.1c01220
description: Funding by the Polish National Science Center (project no. 2020/39/D/ST4/00128) and Warsaw University of Technology (NCHEM.1) is gratefully acknowledged.
DOI: 10.3886/e149861v1-103700
title: The Pleasure Study 2020-2021

description: The pleasure study was collected in 2020 and 2021. It collect data on Millennials gender and sexual experiences. The data set collects data on gender, sexuality, race, sexualexperiences, sexual partners, orgasm, religiosity, sexual function, gender dysphoria andsexual empowerment.
description: A focus on collecting trans, non-binary, and intersex respondents as well as cis men and cis women.
description: web-based survey;
DOI: 10.5281/zenodo.5763811
title: Supplemental Material Surveillance Improves Outcomes for Carriers of SDHB Pathogenic Variants

description: <strong>Supplemental table for Surveillance improves outcomes for carriers of <em>SDHB</em> pathogenic variants: a multi-center study</strong>
DOI: 10.21227/v3wq-0s51
title: Roundabout Curvature Bounding box Data

description: 2D Map is collection of pure lines which are connected to form different features like roundabouts, culdisec, buildings, special figures..etc. In real Maps these lines are created using the latitude and longitude. The idea in this letter identify and validate the roundabouts using the geometry of the Map features by spline technique where the geometries is pass over the non rational uniform B spline function to get the knot vectors and hence the new control points, then the curvature($\kappa$) is calculated and hence the radius. Validation of the roundabout is done using a technique where bounding box of roundabout geometry is created and best fitted Eclipse or circle is carved.In case of eclipse, two radius are considered and average out. Finally, radius is bounded in between the threshold and checked with the calculated once. With threshold of 10 meters around 92.2 % of roundabouts in Europe were validated. Improvement of approx. 12.2 % in the deterministic technique have been achieved with reference to prior art, which detect the roundabout in determinitic way to 80 %.This dataset is the comparision between the splines radius and the bounding box approach(describes above) for few admins from western Europe and Eastern europe.
DOI: 10.5281/zenodo.5763818
title: Supplemental Material Surveillance Improves Outcomes for Carriers of SDHB Pathogenic Variants

description: <strong>Supplemental table for Surveillance improves outcomes for carriers of <em>SDHB</em> pathogenic variants: a multi-center study</strong>
DOI: 10.5517/ccdc.csd.cc2693yl
title: CCDC 2034559: Experimental Crystal Structure Determination

description: Related Article: QuanQing Xu|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc278tmz
title: CCDC 2064061: Experimental Crystal Structure Determination

description: Related Article: Wei Fang|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28h8z1
title: CCDC 2100063: Experimental Crystal Structure Determination

description: Related Article: CHANGHUO XU|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28kj4j
title: CCDC 2102207: Experimental Crystal Structure Determination

description: Related Article: Zhikuan Zhou|2021|CSD Communication|||
description: Related Article: Siyang Feng, Zhirong Qu, Zhikuan Zhou, Jiaying Chen, Lizhi Gai, Hua Lu|2021|Chem.Commun.|57|11689|doi:10.1039/D1CC04687J
DOI: 10.5517/ccdc.csd.cc28l00x
title: CCDC 2102668: Experimental Crystal Structure Determination

description: Related Article: Maofu Pang|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28l01y
title: CCDC 2102669: Experimental Crystal Structure Determination

description: Related Article: Maofu Pang|2021|CSD Communication|||