cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc26kcnt
title: CCDC 2042486: Experimental Crystal Structure Determination

description: Related Article: Juan P. Vizuet, Gregory T. McCandless, and Kenneth J. Balkus Jr.|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26kcqw
title: CCDC 2042488: Experimental Crystal Structure Determination

description: Related Article: Leslaw Sieron|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26kcsy
title: CCDC 2042490: Experimental Crystal Structure Determination

description: Related Article: Marie L. Mortensen, Gregory T. McCandless, Kenneth J. Jr. Balkus|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26kn2j
title: CCDC 2042747: Experimental Crystal Structure Determination

description: Related Article: Andrew Peloquin|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26krj2
title: CCDC 2042854: Experimental Crystal Structure Determination

description: Related Article: Kedar U Narvekar, Bikshandarkoil R Srinivasan|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26krk3
title: CCDC 2042855: Experimental Crystal Structure Determination

description: Related Article: Kedar U Narvekar, Bikshandarkoil R Srinivasan|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26ksp8
title: CCDC 2042890: Experimental Crystal Structure Determination

description: Related Article: Leslaw Sieron|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26kw2r
title: CCDC 2042964: Experimental Crystal Structure Determination

description: Related Article: Leslaw Sieron|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26kwth
title: CCDC 2042987: Experimental Crystal Structure Determination

description: Related Article: Eileen Theuergarten, Atta M. Arif, and Richard D. Ernst|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26kwwk
title: CCDC 2042989: Experimental Crystal Structure Determination

description: Related Article: Eileen Theuergarten, Atta M. Arif, and Richard D. Ernst|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26kwym
title: CCDC 2042991: Experimental Crystal Structure Determination

description: Related Article: Catherine G. Fitzgerald, Jonathan M. White|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26l1mh
title: CCDC 2043136: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy and Pamela Maher|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26l1nj
title: CCDC 2043137: Experimental Crystal Structure Determination

description: Related Article: Heinz-Jürgen Winkler, Armin Berndt, Werner Massa|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26l1vq
title: CCDC 2043143: Experimental Crystal Structure Determination

description: Related Article: Alan R. Kennedy and Pamela Maher|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26l22z
title: CCDC 2043150: Experimental Crystal Structure Determination

description: Related Article: Robin D. Rogers|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26l263
title: CCDC 2043154: Experimental Crystal Structure Determination

description: Related Article: Robin Rogers|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26l803
title: CCDC 2043334: Experimental Crystal Structure Determination

description: Related Article: Eunsang Kwon|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26l814
title: CCDC 2043335: Experimental Crystal Structure Determination

description: Related Article: Eunsang Kwon|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc24902k
title: CCDC 1974857: Experimental Crystal Structure Determination

description: Related Article: Lijun Shi|2020|CSD Communication|||
DOI: 10.5281/zenodo.4293880
title: Recent and local hyperdiversification of Central American rainforests

description: Phylogenetic trees in nexus format to be visualised in e.g. FigTree Scripts and input data to reproduce the diversification analyses (LTT plots and GeoSSE) presented in this study
DOI: 10.6084/m9.figshare.8289938
title: Application of the Random Encounter Model in citizen science projects to monitor animal densities

description: Data containing camera trap and spotlight data collected between 2016-2018 from urban (n=5) and rural (n=4) surveys in England (United Kingdom) to estimate population densities of the European hedgehog (<em>Erinaceus europaeus</em>)<br>1. Camera trap data<br><strong>Footage.xlsx </strong>contains all the records of hedgehogs across all surveys (n=9), including date, time, camera location, and the camera detection parameters for each video<strong>Cameras_deployment_file.xlsx </strong>contains information related to the number of trapping nights per camera and the location<br>2. Encounter history data extracted from spotlight surveys<br><strong>SCRdata.xlsx</strong> includes the detectors information and capture history files for all surveys<br>3. Example data required to run the analysis using the R code provided in the supplementary material<br><strong>activity.xlsx </strong>includes time-of-day data required to obtain activity levels from camera trap data<strong>camDat.xlsx </strong>contains the number of videos and camera detection parameters for each camera location <br>
DOI: 10.6084/m9.figshare.8289938.v1
title: Application of the Random Encounter Model in citizen science projects to monitor animal densities

description: Data containing camera trap and spotlight data collected between 2016-2018 from urban (n=5) and rural (n=4) surveys in England (United Kingdom) to estimate population densities of the European hedgehog (<em>Erinaceus europaeus</em>)<br>1. Camera trap data<br><strong>Footage.xlsx </strong>contains all the records of hedgehogs across all surveys (n=9), including date, time, camera location, and the camera detection parameters for each video<strong>Cameras_deployment_file.xlsx </strong>contains information related to the number of trapping nights per camera and the location<br>2. Encounter history data extracted from spotlight surveys<br><strong>SCRdata.xlsx</strong> includes the detectors information and capture history files for all surveys<br>3. Example data required to run the analysis using the R code provided in the supplementary material<br><strong>activity.xlsx </strong>includes time-of-day data required to obtain activity levels from camera trap data<strong>camDat.xlsx </strong>contains the number of videos and camera detection parameters for each camera location <br>
DOI: 10.25646/8111
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.6084/m9.figshare.12639713
title: Antimicrobial activity of necklace orchids is phylogenetically clustered and can be predicted with a biological response method

description: Necklace orchids (Coelogyninae, Epidendroideae) have been used for traditional medicine practices for centuries. Previously carried out bioassays on a subset of unrelated species showed promising antimicrobial, anti-inflammatory, and anti-oxidant activity, providing experimental proof for medicinal properties as recorded in traditional uses. However, none of these species have been investigated ethno-botanically in a phylogenetic context yet. This study aimed to carry out comparative bioprospecting of a group of wild orchids using EBDCS (the Economic Botany Data Collection Standards) organ targeted and biological response methods. Traditional medicinal use of necklace orchids was recorded from books and journals published between 1984 and 2016. Bioassays with a selection of human pathogen microbes were carried out in triplicate on various extractants of leaves and pseudobulbs of <i>Coelogyne cristata</i> and <i>Coelogyne fimbriata</i> cultivated indoors or outdoors. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS and plastid <i>matK </i>DNA sequences obtained from 148 species, was reconstructed with Bayesian Inference using MrBayes. Bioprospecting comparison of EBDCS and biological response was carried out using customized R scripts. Ethanolic extracts obtained from leaves of <i>C. cristata</i> and <i>C. fimbriata</i> were found to inhibit growth of <i>Bacillus cereus</i>, <i>Staphylococcus aureus</i>,<i> </i>and <i>Yersenia enterocollitica </i>and confirmed traditional antimicrobial uses recorded in the literature. Leaf extracts were found to have stronger antimicrobial properties for plants cultivated outdoors than indoors. Two hot nodes with high potency for antimicrobial activities were detected for the EBDCS organ targeted classification method whereas four hot nodes were detected for the biological response classification method. The biological response classification method was found to be more effective in uncovering hot nodes leading to clades of species with high medicinal potential as compared with the EBDCS classification method.<b></b>
DOI: 10.6084/m9.figshare.12639713.v2
title: Antimicrobial activity of necklace orchids is phylogenetically clustered and can be predicted with a biological response method

description: Necklace orchids (Coelogyninae, Epidendroideae) have been used for traditional medicine practices for centuries. Previously carried out bioassays on a subset of unrelated species showed promising antimicrobial, anti-inflammatory, and anti-oxidant activity, providing experimental proof for medicinal properties as recorded in traditional uses. However, none of these species have been investigated ethno-botanically in a phylogenetic context yet. This study aimed to carry out comparative bioprospecting of a group of wild orchids using EBDCS (the Economic Botany Data Collection Standards) organ targeted and biological response methods. Traditional medicinal use of necklace orchids was recorded from books and journals published between 1984 and 2016. Bioassays with a selection of human pathogen microbes were carried out in triplicate on various extractants of leaves and pseudobulbs of <i>Coelogyne cristata</i> and <i>Coelogyne fimbriata</i> cultivated indoors or outdoors. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS and plastid <i>matK </i>DNA sequences obtained from 148 species, was reconstructed with Bayesian Inference using MrBayes. Bioprospecting comparison of EBDCS and biological response was carried out using customized R scripts. Ethanolic extracts obtained from leaves of <i>C. cristata</i> and <i>C. fimbriata</i> were found to inhibit growth of <i>Bacillus cereus</i>, <i>Staphylococcus aureus</i>,<i> </i>and <i>Yersenia enterocollitica </i>and confirmed traditional antimicrobial uses recorded in the literature. Leaf extracts were found to have stronger antimicrobial properties for plants cultivated outdoors than indoors. Two hot nodes with high potency for antimicrobial activities were detected for the EBDCS organ targeted classification method whereas four hot nodes were detected for the biological response classification method. The biological response classification method was found to be more effective in uncovering hot nodes leading to clades of species with high medicinal potential as compared with the EBDCS classification method.<b></b>
DOI: 10.6084/m9.figshare.12639713.v1
title: Antimicrobial activity of necklace orchids is phylogenetically clustered and can be predicted with a biological response method

description: Necklace orchids (Coelogyninae, Epidendroideae) have been used for traditional medicine practices for centuries. Previously carried out bioassays on a subset of unrelated species showed promising antimicrobial, anti-inflammatory, and anti-oxidant activity, providing experimental proof for medicinal properties as recorded in traditional uses. However, none of these species have been investigated ethno-botanically in a phylogenetic context yet. This study aimed to carry out comparative bioprospecting of a group of wild orchids using EBDCS (the Economic Botany Data Collection Standards) organ targeted and biological response methods. Traditional medicinal use of necklace orchids was recorded from books and journals published between 1984 and 2016. Bioassays with a selection of human pathogen microbes were carried out in triplicate on various extractants of leaves and pseudobulbs of <i>Coelogyne cristata</i> and <i>Coelogyne fimbriata</i> cultivated indoors or outdoors. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS and plastid <i>matK </i>DNA sequences obtained from 148 species, was reconstructed with Bayesian Inference using MrBayes. Bioprospecting comparison of EBDCS and biological response was carried out using customized R scripts. Ethanolic extracts obtained from leaves of <i>C. cristata</i> and <i>C. fimbriata</i> were found to inhibit growth of <i>Bacillus cereus</i>, <i>Staphylococcus aureus</i>,<i> </i>and <i>Yersenia enterocollitica </i>and confirmed traditional antimicrobial uses recorded in the literature. Leaf extracts were found to have stronger antimicrobial properties for plants cultivated outdoors than indoors. Two hot nodes with high potency for antimicrobial activities were detected for the EBDCS organ targeted classification method whereas four hot nodes were detected for the biological response classification method. The biological response classification method was found to be more effective in uncovering hot nodes leading to clades of species with high medicinal potential as compared with the EBDCS classification method.<b></b>
DOI: 10.6084/m9.figshare.13071893
title: Antimicrobial activity of necklace orchids is phylogenetically clustered and can be predicted with a biological response method

description: Necklace orchids (Coelogyninae, Epidendroideae) have been used in traditional medicine practices for centuries. Previous studies on a subset of unrelated orchid species utilized in these traditional practices revealed they possessed antimicrobial, anti-inflammatory, and anti-oxidant activity, providing experimental proof for their medicinal properties. To date however none of these species have been investigated ethno-botanically in a phylogenetic context. This study thus carried out comparative bioprospecting for a group of wild orchids using EBDCS (the Economic Botany Data Collection Standards) organ targeted and biological response methods. The traditional medicinal use of necklace orchids was recorded from books and journals published between 1984 and 2016. Two orchids, <i>Coelogyne cristata</i> and <i>Coelogyne fimbriata</i>, were selected, cultivated both indoors and outdoors, and the antimicrobial properties on extracts from their leaves and pseudobulbs tested against a selection of human pathogens. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS and plastid <i>matK </i>DNA sequences obtained from 148 species was reconstructed with Maximum Likelihood (ML) using RAxML, Maximum Parsimony (MP) using PAUP, and Bayesian Inference using MrBayes. Bioprospecting comparison of EBDCS and biological response was carried out using customized R scripts. Ethanolic extracts obtained from leaves of <i>C. fimbriata</i> inhibited growth of <i>Bacillus cereus</i>, <i>Staphylococcus aureus</i>,<i> </i>and <i>Yersinia enterocolitica, </i>confirming the antimicrobial properties of these extracts. Leaf extracts were found to have slightly stronger antimicrobial properties for plants cultivated outdoors than indoors. These differences were not found to be statistically significant though. Three hot nodes with high potency for antimicrobial activities were detected with the EBDCS organ targeted classification method, and eight hot nodes were detected with the biological response classification method. The biological response classification method is thus a more effective tool in finding hot nodes amongst clades of species with high medicinal potential.<b></b>
DOI: 10.6084/m9.figshare.13071893.v2
title: Antimicrobial activity of necklace orchids is phylogenetically clustered and can be predicted with a biological response method

description: Necklace orchids (Coelogyninae, Epidendroideae) have been used in traditional medicine practices for centuries. Previous studies on a subset of unrelated orchid species utilized in these traditional practices revealed they possessed antimicrobial, anti-inflammatory, and anti-oxidant activity, providing experimental proof for their medicinal properties. To date however none of these species have been investigated ethno-botanically in a phylogenetic context. This study thus carried out comparative bioprospecting for a group of wild orchids using EBDCS (the Economic Botany Data Collection Standards) organ targeted and biological response methods. The traditional medicinal use of necklace orchids was recorded from books and journals published between 1984 and 2016. Two orchids, <i>Coelogyne cristata</i> and <i>Coelogyne fimbriata</i>, were selected, cultivated both indoors and outdoors, and the antimicrobial properties on extracts from their leaves and pseudobulbs tested against a selection of human pathogens. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS and plastid <i>matK </i>DNA sequences obtained from 148 species was reconstructed with Maximum Likelihood (ML) using RAxML, Maximum Parsimony (MP) using PAUP, and Bayesian Inference using MrBayes. Bioprospecting comparison of EBDCS and biological response was carried out using customized R scripts. Ethanolic extracts obtained from leaves of <i>C. fimbriata</i> inhibited growth of <i>Bacillus cereus</i>, <i>Staphylococcus aureus</i>,<i> </i>and <i>Yersinia enterocolitica, </i>confirming the antimicrobial properties of these extracts. Leaf extracts were found to have slightly stronger antimicrobial properties for plants cultivated outdoors than indoors. These differences were not found to be statistically significant though. Three hot nodes with high potency for antimicrobial activities were detected with the EBDCS organ targeted classification method, and eight hot nodes were detected with the biological response classification method. The biological response classification method is thus a more effective tool in finding hot nodes amongst clades of species with high medicinal potential.<b></b>
DOI: 10.6084/m9.figshare.13071893.v1
title: Antimicrobial activity of necklace orchids is phylogenetically clustered and can be predicted with a biological response method

description: Necklace orchids (Coelogyninae, Epidendroideae) have been used in traditional medicine practices for centuries. Previous studies on a subset of unrelated orchid species utilized in these traditional practices revealed they possessed antimicrobial, anti-inflammatory, and anti-oxidant activity, providing experimental proof for their medicinal properties. To date however none of these species have been investigated ethno-botanically in a phylogenetic context. This study thus carried out comparative bioprospecting for a group of wild orchids using EBDCS (the Economic Botany Data Collection Standards) organ targeted and biological response methods. The traditional medicinal use of necklace orchids was recorded from books and journals published between 1984 and 2016. Two orchids, <i>Coelogyne cristata</i> and <i>Coelogyne fimbriata</i>, were selected, cultivated both indoors and outdoors, and the antimicrobial properties on extracts from their leaves and pseudobulbs tested against a selection of human pathogens. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS and plastid <i>matK </i>DNA sequences obtained from 148 species was reconstructed with Maximum Likelihood (ML) using RAxML, Maximum Parsimony (MP) using PAUP, and Bayesian Inference using MrBayes. Bioprospecting comparison of EBDCS and biological response was carried out using customized R scripts. Ethanolic extracts obtained from leaves of <i>C. fimbriata</i> inhibited growth of <i>Bacillus cereus</i>, <i>Staphylococcus aureus</i>,<i> </i>and <i>Yersinia enterocolitica, </i>confirming the antimicrobial properties of these extracts. Leaf extracts were found to have slightly stronger antimicrobial properties for plants cultivated outdoors than indoors. These differences were not found to be statistically significant though. Three hot nodes with high potency for antimicrobial activities were detected with the EBDCS organ targeted classification method, and eight hot nodes were detected with the biological response classification method. The biological response classification method is thus a more effective tool in finding hot nodes amongst clades of species with high medicinal potential.<b></b>
DOI: 10.6084/m9.figshare.14160599
title: “Economic Dispatch of Wind-hydro-thermal Power Systems Considering Reservoir Flexibility” Case Data

description: “Economic Dispatch of Wind-hydro-thermal Power Systems Considering Reservoir Flexibility” Case Data
DOI: 10.6084/m9.figshare.14160599.v1
title: “Economic Dispatch of Wind-hydro-thermal Power Systems Considering Reservoir Flexibility” Case Data

description: “Economic Dispatch of Wind-hydro-thermal Power Systems Considering Reservoir Flexibility” Case Data
DOI: 10.6084/m9.figshare.14160590
title: Example dataset annotated with bacannot

description: This dataset represents the https://github.com/PacificBiosciences/DevNet/wiki/8-plex-Ecoli-Multiplexed-Microbial-Assembly pacbio dataset already assembled and annotated so that users that want to skip some steps of the tutorial can do it by downloading this dataset.<br>
DOI: 10.6084/m9.figshare.14160590.v1
title: Example dataset annotated with bacannot

description: This dataset represents the https://github.com/PacificBiosciences/DevNet/wiki/8-plex-Ecoli-Multiplexed-Microbial-Assembly pacbio dataset already assembled and annotated so that users that want to skip some steps of the tutorial can do it by downloading this dataset.<br>
DOI: 10.5517/ccdc.csd.cc23cggf
title: CCDC 1947434: Experimental Crystal Structure Determination

description: Related Article: Weiwei Gao, Xiaodong Wang, Linbin Yao, Bencan Tang, Guohao Mu, Tao Shi, Zhen Wang|2021|Org.Biomol.Chem.|19|1748|doi:10.1039/D0OB02399J
DOI: 10.5517/ccdc.csd.cc24mfv2
title: CCDC 1984894: Experimental Crystal Structure Determination

description: Related Article: Weiyao Zhang, Curtis E. Moore, Shiyu Zhang|2021|Chemical Science|12|2986|doi:10.1039/D0SC05441K
DOI: 10.5517/ccdc.csd.cc24mfw3
title: CCDC 1984895: Experimental Crystal Structure Determination

description: Related Article: Weiyao Zhang, Curtis E. Moore, Shiyu Zhang|2021|Chemical Science|12|2986|doi:10.1039/D0SC05441K
DOI: 10.5517/ccdc.csd.cc24v1qs
title: CCDC 1991245: Experimental Crystal Structure Determination

description: Related Article: Jasimuddin Ahmed, Paramita Datta, Arpan Das, Stephy Jomy, Swadhin K. Mandal|2021|Chemical Science|12|3039|doi:10.1039/D0SC05972B
DOI: 10.5517/ccdc.csd.cc24v1rt
title: CCDC 1991246: Experimental Crystal Structure Determination

description: Related Article: Jasimuddin Ahmed, Paramita Datta, Arpan Das, Stephy Jomy, Swadhin K. Mandal|2021|Chemical Science|12|3039|doi:10.1039/D0SC05972B
DOI: 10.5517/ccdc.csd.cc24wz23
title: CCDC 1993085: Experimental Crystal Structure Determination

description: Related Article: Daisuke Uraguchi, Kohsuke Kato, Takashi Ooi|2021|Chemical Science|12|2778|doi:10.1039/D0SC06240E
DOI: 10.5517/ccdc.csd.cc24wz34
title: CCDC 1993086: Experimental Crystal Structure Determination

description: Related Article: Daisuke Uraguchi, Kohsuke Kato, Takashi Ooi|2021|Chemical Science|12|2778|doi:10.1039/D0SC06240E
DOI: 10.5517/ccdc.csd.cc24wz45
title: CCDC 1993087: Experimental Crystal Structure Determination

description: Related Article: Daisuke Uraguchi, Kohsuke Kato, Takashi Ooi|2021|Chemical Science|12|2778|doi:10.1039/D0SC06240E