cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8419068
title: SMRT PacBio Sequel sequencing of 12 Silene herbarium specimens

description: The folder includes reads sequenced with SMRT PacBio Sequel from twelve Silene herbarium specimens. Both demultiplexed and non demultiplexed reads are included. The demultiplexed reads are in folder called "demultiplexed.zip", in files starting with "Barcodenumber_speciesnamesamplingyear.fastq". The barcode number and sequence can be found below, in the description. The non demultiplexed reads are in file called "ps_248_001.ccsreads.fastq.gz". #NebNext Barcodes<br> #Adapter('Barcode 1 (forward)',<br> # start_sequence=('BC01', 'CGTGAT'),<br> # end_sequence=('BC01_rev', 'ATCACG')),<br> #Adapter('Barcode 2 (forward)',<br> # start_sequence=('BC02', 'ACATCG'),<br> # end_sequence=('BC02_rev', 'CGATGT')),<br> #Adapter('Barcode 3 (forward)',<br> # start_sequence=('BC03', 'GCCTAA'),<br> # end_sequence=('BC03_rev', 'TTAGGC')),<br> #Adapter('Barcode 4 (forward)',<br> # start_sequence=('BC04', 'TGGTCA'),<br> # end_sequence=('BC04_rev', 'TGACCA')),<br> #Adapter('Barcode 5 (forward)',<br> # start_sequence=('BC05', 'CACTGT'),<br> # end_sequence=('BC05_rev', 'ACAGTG')),<br> #Adapter('Barcode 6 (forward)',<br> # start_sequence=('BC06', 'ATTGGC'),<br> # end_sequence=('BC06_rev', 'GCCAAT')),<br> #Adapter('Barcode 7 (forward)',<br> # start_sequence=('BC07', 'GATCTG'),<br> # end_sequence=('BC07_rev', 'CAGATC')),<br> #Adapter('Barcode 8 (forward)',<br> # start_sequence=('BC08', 'TCAAGT'),<br> # end_sequence=('BC08_rev', 'ACTTGA')),<br> #Adapter('Barcode 9 (forward)',<br> # start_sequence=('BC09', 'CTGATC'),<br> # end_sequence=('BC09_rev', 'GATCAG')),<br> #Adapter('Barcode 10 (forward)',<br> # start_sequence=('BC10', 'AAGCTA'),<br> # end_sequence=('BC10_rev', 'TAGCTT')),<br> #Adapter('Barcode 11 (forward)',<br> # start_sequence=('BC11', 'GTAGCC'),<br> # end_sequence=('BC11_rev', 'GGCTAC')),<br> #Adapter('Barcode 12 (forward)',<br> # start_sequence=('BC12', 'TACAAG'),<br> # end_sequence=('BC12_rev', 'CTTGTA')),]
DOI: 10.5281/zenodo.8356621
title: Stakeholder consultation analysis for the project "Proposal of a terminology of medication adherence enabling and supporting activities" (ENABLE terminology)

description: These documents relate to the stakeholder consultation performed within the ENABLE COST action (European Network to Advance Best practices & technoLogy on medication adherencE, CA 19132) regarding a new terminology of medication adherence enabling and supporting activities. They include the data and quantitative analysis of the eDelphi survey performed in Malaga, Spain in May 2022, as part of this consultation.
DOI: 10.5281/zenodo.8356620
title: Stakeholder consultation analysis for the project "Proposal of a terminology of medication adherence enabling and supporting activities" (ENABLE terminology)

description: These documents relate to the stakeholder consultation performed within the ENABLE COST action (European Network to Advance Best practices & technoLogy on medication adherencE, CA 19132) regarding a new terminology of medication adherence enabling and supporting activities. They include the data and quantitative analysis of the eDelphi survey performed in Malaga, Spain in May 2022, as part of this consultation.
DOI: 10.5517/ccdc.csd.cc2fnymp
title: CCDC 2254463: Experimental Crystal Structure Determination

description: Related Article: Gottam Sreenivasulu, Balasubramanian Sridhar, Galla V. Karunakar|2023|Org.Biomol.Chem.|21|7799|doi:10.1039/D3OB01079A
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: 10.5517/ccdc.csd.cc2gqvpr
title: CCDC 2286085: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Li, Yu-Shi Jiang, Li-Ning Chen, Dan-Na Chen, Xue-Ling Luo, Cheng-Xue Pan, Peng-Ju Xia|2023|Org.Lett.|25|7009|doi:10.1021/acs.orglett.3c02584
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: 10.14469/hpc/13167
title: Acetyl chloride + methanol + water, IRC

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13168
title: Acetyl chloride + methylamine + water.

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13169
title: Acetyl chloride + methylamine + water, IRC

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13170
title: Acetyl chloride + methylamine + water, ==&gt; PT,G = -785.735731

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13172
title: Acetyl chloride + HF + water, IRC

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13173
title: Acetyl chloride + methylamine + water, PT, IRC

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13178
title: Acetyl chloride + carbon ylid IRC

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13179
title: Acetyl chloride + MeSH, G = -1128.549307, IRC

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13244
title: Acetyl chloride + carbon S-ylid, IRC, G = -1130.636481

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13267
title: Acetyl chloride + carbon P-ylid, IRC, G = -1113.737325

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/13175
title: Acetyl chloride + carbon ylid, IRC

description: Gaussian 16 (C01) calculation
DOI: 10.15468/jth3pz
title: 2015 Marine Biological Association of the UK (MBA) Yealm Estuary Devon Transect Survey of Crassostrea gigas

description: As an invasive non-native, C. gigas may have an economic and ecological impact in intertidal regions and estuaries. These surveys are to monitor its UK distribution and abundance.
DOI: 10.7488/ds/7524
title: Testing a non-destructive assay to track Plasmodium sporozoites in mosquitoes over time

description: The extrinsic incubation period (EIP), defined as the time it takes for malaria parasites in a mosquito to become infectious to a vertebrate host, is one of the most influential parameters for malaria transmission but remains poorly understood. The EIP is usually estimated by quantifying salivary gland sporozoites in subsets of mosquitoes, which requires terminal sampling. However, assays that allow repeated sampling of individual mosquitoes over time could provide better resolution of the EIP. We tested a non-destructive assay to quantify sporozoites of two rodent malaria species, Plasmodium chabaudi and Plasmodium berghei, expelled throughout 24hr windows, from sugar-feeding substrates using quantitative PCR. The assay can quantify sporozoites from sugar-feeding substrates, but the prevalence of parasite positive substrates is low. Multiple methods to increase the detection of expelled parasites (running additional technical replicates; using groups rather than individual mosquitoes) did not increase the detection rate, suggesting that expulsion of sporozoites is variable and infrequent. We reveal successful detection of expelled sporozoites from sugar-feeding substrates. However, investigations of the biological causes underlying the low detection rate of sporozoites (e.g., mosquito feeding behaviour, frequency of sporozoite expulsion, or sporozoite clumping) are needed to maximise the utility of using non-destructive assays to quantify sporozoite dynamics. Increasing detection rates will facilitate the detailed investigation on infection dynamics within mosquitoes, which is necessary to explain Plasmodium's highly variable EIP and improve understanding of malaria transmission dynamics. The dataset relates to the upcoming publication 'Testing a non-destructive assay to track Plasmodium sporozoites in mosquitoes over time' by Catherine E Oke, Sarah E Reece and Petra Schneider.
DOI: 10.5281/zenodo.8298156
title: Datasets used for benchmarking of JOINTLY.

description: Datasets used for benchmarking of JOINTLY with associated labels, intermediary results and final results. Version 2 holds the datasets used in the final manuscript.
DOI: 10.5281/zenodo.8298157
title: Datasets used for benchmarking of JOINTLY

description: Datasets used for benchmarking of JOINTLY with associated labels, intermediary results and final results.
DOI: 10.5281/zenodo.8434958
title: Datasets used for benchmarking of JOINTLY.

description: Datasets used for benchmarking of JOINTLY with associated labels, intermediary results and final results. Version 2 holds the datasets used in the final manuscript.
DOI: 10.6084/m9.figshare.24298246
title: DATA.xlsx

description: In kidney transplant recipients, many drugs should be used to preserve the transplanted organ and to treat other associated conditions. Some of these drugs can interact with each other, which can lead to unwanted consequences. The identification of drugs encountered in such combinations, as well as other risk factors, gives clinicians the opportunity to avoid these unwanted consequences by changing therapeutic protocols. In this research, it was established that tamsulosin, urapidil and cyclosporin are the drugs that most often appear in combinations that can have the most significant clinical consequences. Such combinations are more often recorded in older male kidney transplant recipients who take a larger number of medications.
DOI: 10.5281/zenodo.8427306
title: Italian GloVe models

description: Italian GloVe models trained from scratch on a dataset composed of: - <strong>wiki</strong>: a dump of Italian Wikipedia (as of December 15, 2022), comprising 25,548,651 sentences and 526,640,982 words (3.2 GB of raw text);<br> - <strong>webz</strong>: a dataset of Italian news (159,226 documents) from the webz.io platform, crawled in October 2015, containing 44,041,823 sentences and 44,544,385 words (244 MB);<br> - a dataset of 5,510 Italian news articles from the newspaper ModenaToday (<strong>MT</strong>) or 15,115 documents from the Italian version of Reuters (<strong>RCV2</strong>). <strong>glv_wiki_wbz_mt_20_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and MT for 20 epochs <strong>glv_wiki_wbz_mt_50_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and MT for 50 epochs <strong>glv_wiki_wbz_reut_20_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and RCV2 for 20 epochs <strong>glv_wiki_wbz_reut_50_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and RCV2 for 50 epochs
DOI: 10.5281/zenodo.8427305
title: Italian GloVe models

description: Italian GloVe models trained from scratch on a dataset composed of: - <strong>wiki</strong>: a dump of Italian Wikipedia (as of December 15, 2022), comprising 25,548,651 sentences and 526,640,982 words (3.2 GB of raw text);<br> - <strong>webz</strong>: a dataset of Italian news (159,226 documents) from the webz.io platform, crawled in October 2015, containing 44,041,823 sentences and 44,544,385 words (244 MB);<br> - a dataset of 5,510 Italian news articles from the newspaper ModenaToday (<strong>MT</strong>) or 15,115 documents from the Italian version of Reuters (<strong>RCV2</strong>). <strong>glv_wiki_wbz_mt_20_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and MT for 20 epochs <strong>glv_wiki_wbz_mt_50_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and MT for 50 epochs <strong>glv_wiki_wbz_reut_20_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and RCV2 for 20 epochs <strong>glv_wiki_wbz_reut_50_epochs.zip</strong>: GloVe model trained on the dataset consisting of wiki, webz, and RCV2 for 50 epochs
DOI: 10.5281/zenodo.8431710
title: All-atomic simulation of DMPC bilayer with PME and with RFZ

description: We have performed simulations of DMPC to check if the <strong>reaction-field-zero</strong> mode of calculating electrostatics is a good substitute for PME if we want to avoid PME for some reasons (e.g. for stress calculations). We started this simulation from the configuration deposited by Matti Javanainen (10.5281/zenodo.6943413). We performed two simulations of about 500 ns with the same protocol but at 313 K. Protocol for reaction-field-zero is supplemented as well. POPE simulated with the same RFZ protocol is deposited in a separate dataset (10.5281/zenodo.8435138).
DOI: 10.5281/zenodo.8431709
title: All-atomic simulation of DMPC bilayer with PME and with RFZ

description: We have performed simulations of DMPC to check if the <strong>reaction-field-zero</strong> mode of calculating electrostatics is a good substitute for PME if we want to avoid PME for some reasons (e.g. for stress calculations). We started this simulation from the configuration deposited by Matti Javanainen (10.5281/zenodo.6943413). We performed two simulations of about 500 ns with the same protocol but at 313 K. Protocol for reaction-field-zero is supplemented as well. POPE simulated with the same RFZ protocol is deposited in a separate dataset (10.5281/zenodo.8435138).
DOI: 10.6084/m9.figshare.24298225
title: wrinkle_angle_datasets

description: Dataset of cloth folds and corner points, including labels for cloth folds and corner points.
DOI: 10.34740/kaggle/dsv/6675390
title: 2021 World Population (updated daily)
DOI: 10.34740/kaggle/dsv/6675389
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.24298036
title: Replication Package

description: This is the replication package containing the dataset for code detection of AIGC Detectors, code to setup and run AIGC Detectors and the results from AIGC Detectors
DOI: 10.5281/zenodo.7985736
title: Austrian Science Fund (FWF) Open Access Compliance Monitoring 2022

description: I. Executive summary The Austrian Science Fund (FWF), which is Austria's main funding organisation for basic research, encourages and helps all project leaders and project staff members to make their peer-reviewed research results freely available on the Internet. Any exceptions must be clearly indicated and justified. For projects that started after 1 January 2015, open access has been compulsory for all peer-reviewed publications. All principal investigators in FWF-funded projects are obliged to submit a final report within four months of completing their projects. In 2022, a total of 575 final reports were submitted to the FWF, 38 of which could not report any publications so far. The publications and other data mentioned in those reports are archived and analysed by the FWF. This report examines the state of compliance with open access requirements for peer-reviewed publications on the basis of final project reports submitted in the year 2022. Main findings: -A total of 8,312 publications were listed in the final project reports submitted in 2022. -Of those publications, 6,631 were conclusively identified as peer-reviewed. -Regarding compliance with the FWF's Open Access Policy, the analysis shows that 85% of the peer-reviewed publications listed in the final project reports submitted in 2022 were openly accessible (2015: 83%, 2016: 92%, 2017: 90%, 2018: 92%, 2019: 89%, 2020: 84%, 2021 82%). -The most frequently chosen option was hybrid open access (36%). The share of gold open access was 29%, the share of green open access 20%, and no open access 15%. -The majority of peer-reviewed publications submitted were journal articles (85%), 86% of which were openly accessible. -The lowest rate of compliance with the FWF's Open Access Policy could be found in editions, contributions to edited volumes, and monographs 41%). -The absolute number of publications listed in final reports in 2022 included 354 publications that were mentioned several times in different projects; however, those repetitions did not affect the relative share of open access publications (85%). II. Bias All publications were submitted to the FWF via a research documentation system (provided by ©Researchfish), in which FWF-funded researchers are able to enter and update their research data on an ongoing basis. The last check of the open access status was performed in March 2023. In some cases, the embargo period may have already expired, and publications labelled ‘closed’ in the FWF’s database may now be accessible through green open access. Whenever the status ‘peer-reviewed’ could not be clearly identified according to the FWF’s guidelines, the publications were classified as non-peer reviewed. Openly available non-peer reviewed publications were entered as 'openly available’.
DOI: 10.5281/zenodo.7985737
title: Austrian Science Fund (FWF) Open Access Compliance Monitoring 2022

description: I. Executive summary The Austrian Science Fund (FWF), which is Austria's main funding organisation for basic research, encourages and helps all project leaders and project staff members to make their peer-reviewed research results freely available on the Internet. Any exceptions must be clearly indicated and justified. For projects that started after 1 January 2015, open access has been compulsory for all peer-reviewed publications. All principal investigators in FWF-funded projects are obliged to submit a final report within four months of completing their projects. In 2022, a total of 575 final reports were submitted to the FWF, 38 of which could not report any publications so far. The publications and other data mentioned in those reports are archived and analysed by the FWF. This report examines the state of compliance with open access requirements for peer-reviewed publications on the basis of final project reports submitted in the year 2022. Main findings: -A total of 8,312 publications were listed in the final project reports submitted in 2022. -Of those publications, 6,631 were conclusively identified as peer-reviewed. -Regarding compliance with the FWF's Open Access Policy, the analysis shows that 85% of the peer-reviewed publications listed in the final project reports submitted in 2022 were openly accessible (2015: 83%, 2016: 92%, 2017: 90%, 2018: 92%, 2019: 89%, 2020: 84%, 2021 82%). -The most frequently chosen option was hybrid open access (36%). The share of gold open access was 29%, the share of green open access 20%, and no open access 15%. -The majority of peer-reviewed publications submitted were journal articles (85%), 86% of which were openly accessible. -The lowest rate of compliance with the FWF's Open Access Policy could be found in editions, contributions to edited volumes, and monographs 41%). -The absolute number of publications listed in final reports in 2022 included 354 publications that were mentioned several times in different projects; however, those repetitions did not affect the relative share of open access publications (85%). II. Bias All publications were submitted to the FWF via a research documentation system (provided by ©Researchfish), in which FWF-funded researchers are able to enter and update their research data on an ongoing basis. The last check of the open access status was performed in March 2023. In some cases, the embargo period may have already expired, and publications labelled ‘closed’ in the FWF’s database may now be accessible through green open access. Whenever the status ‘peer-reviewed’ could not be clearly identified according to the FWF’s guidelines, the publications were classified as non-peer reviewed. Openly available non-peer reviewed publications were entered as 'openly available’.
DOI: 10.5281/zenodo.8424628
title: SEVIRI AOD/COD Product [DUST2MSG]

description: In the framework of the DUST2MSG ESA project, the CISAR algorithm, originally developed by Rayference for the joint retrieval of surface reflectance, aerosol and cloud single scattering properties, has been applied to SEVIRI observations acquired from both MSG1 and MSG4 from March to August 2020 to obtain a dust product. This Dataset includes hourly atmospheric products. Specification on the filename convention, format and content of the products can be found on the Product User Manual (PUM)
description: {"references": ["Govaerts and Luffarelli (2018), Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space \u2013 Part 1: theoretical concept, https://amt.copernicus.org/articles/11/6589/2018/", "Luffarelli and Govaerts (2019), Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space \u2013 Part 2: application to geostationary and polar-orbiting satellite observations, https://amt.copernicus.org/articles/12/791/2019/", "Luffarelli et al (2022), Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations, https://www.mdpi.com/2073-4433/13/5/691"]}
DOI: 10.5281/zenodo.8424627
title: SEVIRI AOD/COD Product [DUST2MSG]

description: In the framework of the DUST2MSG ESA project, the CISAR algorithm, originally developed by Rayference for the joint retrieval of surface reflectance, aerosol and cloud single scattering properties, has been applied to SEVIRI observations acquired from both MSG1 and MSG4 from March to August 2020 to obtain a dust product. This Dataset includes hourly atmospheric products. Specification on the filename convention, format and content of the products can be found on the Product User Manual (PUM)
description: {"references": ["Govaerts and Luffarelli (2018), Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space \u2013 Part 1: theoretical concept, https://amt.copernicus.org/articles/11/6589/2018/", "Luffarelli and Govaerts (2019), Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space \u2013 Part 2: application to geostationary and polar-orbiting satellite observations, https://amt.copernicus.org/articles/12/791/2019/", "Luffarelli et al (2022), Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations, https://www.mdpi.com/2073-4433/13/5/691"]}