cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7643956
title: Data for the article "Organic farming increases functional diversity and ecosystem service provision of spontaneous vegetation in Mediterranean vineyards"

description: Research data for the article "<strong>Organic farming increases functional diversity and ecosystem service provision of spontaneous vegetation in Mediterranean vineyards</strong>" made by Roser Rotchés-Ribalta, Joan Marull and Joan Pino published in Ecological Indicators. It includes: - Species and functional diversities of spontaneous plant species in the different plots surveyed per field - The cover of each species per plot in each field - The functional traits used for each species - The physico-chemical soil data of each plot per field
DOI: 10.6084/m9.figshare.22097993.v1
title: Profile soil data at the pit level

description: ECOPICS Project : Profile Soil Data Field campaign Abril 2017 to March 2018 Last modification : April 2022 by Beatriz E. Marín Castro and Christina D. Siebe The description of the profiles was made according to the description manual of Siebe C., Jahn R. and K. Stahr. 2016. Manual para la descripción y evaluación ecológica de suelos en el campo. Sociedad Mexicana de la Ciencia del Suelo A.C. <em>Raw physicochemical data:</em> <br> Contains the soil data at the pit level Units of physicochemical properties :Ntot (%), MO (%), pH water, Phosphorus for Bray-Kurtz, (mg/kg), CEC (cmol/kg), Base saturation estimade and determined in laboratory (%), Fe, Al and Si for Oxides extracted with ammonium oxalate (mg/g) These data have to be correlated with the altitudinal gradient analysis. The pits, one per altitudinal level, samples were taken from different soil horizons.
DOI: 10.7284/128155
title: Splitbeam Echosounder data collected during research cruise SKQ201713S using a Kongsberg EK60 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.5281/zenodo.7644125
title: Supplemental files for manuscript "The circulating phageome reflects bacterial infections"

description: These are the supplemental files associated with the manuscript "The circulating phageome reflects bacterial infections". These include: 1. Supplemental File 1 (Phage Dictionary).csv which is a dictionary connecting bacteriophage accession numbers to their known taxonomic data as well as the taxonomic data of their host if known. 2. Supplemental File 2 (Coliphage Characteristics).csv which is a dictionary for phages which infect <em>Escherichia coli</em> including host information to strain if known and characteristics of any known strains. 3. Supplemental File 3 (Metadata).xlsx which includes a metadata table for the plasma cfDNA samples sequenced in the associated study, including infection etiology. 4. Supplemental File 4 (Negative Controls).xlsx which includes the sequences and identities of short reads from our negative sequencing controls (PBS, Water)
DOI: 10.5281/zenodo.7644124
title: Supplemental files for manuscript "The circulating phageome reflects bacterial infections"

description: These are the supplemental files associated with the manuscript "The circulating phageome reflects bacterial infections". These include: 1. Supplemental File 1 (Phage Dictionary).csv which is a dictionary connecting bacteriophage accession numbers to their known taxonomic data as well as the taxonomic data of their host if known. 2. Supplemental File 2 (Coliphage Characteristics).csv which is a dictionary for phages which infect <em>Escherichia coli</em> including host information to strain if known and characteristics of any known strains. 3. Supplemental File 3 (Metadata).xlsx which includes a metadata table for the plasma cfDNA samples sequenced in the associated study, including infection etiology. 4. Supplemental File 4 (Negative Controls).xlsx which includes the sequences and identities of short reads from our negative sequencing controls (PBS, Water)
DOI: 10.7284/128148
title: Singlebeam Echosounder data collected during research cruise SKQ201713S using a Kongsberg TOPAS PS-18 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128134
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise SKQ201713S using a Hawaii UHDAS instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/137600
title: Anemometer data collected during research cruise SKQ201713S using a RMYoung 85004 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/137601
title: Anemometer data collected during research cruise SKQ201713S using a RMYoung 85004 instrument system onboard the platform RV Sikuliaq

description: Processed data created by vessel technician during a Field_expedition
DOI: 10.7284/137754
title: Anemometer data collected during research cruise SKQ201713S using a RMYoung 85004 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/137755
title: Anemometer data collected during research cruise SKQ201713S using a RMYoung 85004 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128136
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise SKQ201713S using a SeaBird SBE-911+ instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.5281/zenodo.7644147
title: Microhabitat selection of meadow and steppe vipers enlightened by digital photography and image processing to describe grassland vegetation structure

description: Dataset Understanding animals’ selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterisation of microhabitats, especially for vegetation structure. We studied microhabitat selection of <em>Vipera</em> snakes by comparing grassland vegetation structure between viper occurrence points and random points in three grassland ecosystems: <em>V. graeca</em> in mountain meadows of Albania, <em>V. renardi</em> in loess steppes of Ukraine, and <em>V. ursinii</em> in sand grasslands in Hungary. We quantified vegetation structure in an objective manner by automated processing of images taken of the vegetation against a vegetation profile board under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data obtained in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD). Generalized linear mixed models revealed that snake occurrence was positively related to HCV in <em>V. graeca</em>, to LA in <em>V. renardi</em> and to LA and MHC in <em>V. ursinii</em>, and negatively to to HCV in <em>V. ursinii</em>. Our results demonstrate that vegetation structure variables derived from automated image processing significantly influence viper microhabitat selection. Our method minimises the risk of subjectivity in measuring vegetation structure, allows upscaling if neighbouring pixels are combined, and is suitable for comparison of or extrapolation across different grasslands, vegetation types or ecosystems.
DOI: 10.5281/zenodo.7644154
title: Microhabitat selection of meadow and steppe vipers enlightened by digital photography and image processing to describe grassland vegetation structure

description: Dataset Understanding animals’ selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterisation of microhabitats, especially for vegetation structure. We studied microhabitat selection of <em>Vipera</em> snakes by comparing grassland vegetation structure between viper occurrence points and random points in three grassland ecosystems: <em>V. graeca</em> in mountain meadows of Albania, <em>V. renardi</em> in loess steppes of Ukraine, and <em>V. ursinii</em> in sand grasslands in Hungary. We quantified vegetation structure in an objective manner by automated processing of images taken of the vegetation against a vegetation profile board under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data obtained in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD). Generalized linear mixed models revealed that snake occurrence was positively related to HCV in <em>V. graeca</em>, to LA in <em>V. renardi</em> and to LA and MHC in <em>V. ursinii</em>, and negatively to to HCV in <em>V. ursinii</em>. Our results demonstrate that vegetation structure variables derived from automated image processing significantly influence viper microhabitat selection. Our method minimises the risk of subjectivity in measuring vegetation structure, allows upscaling if neighbouring pixels are combined, and is suitable for comparison of or extrapolation across different grasslands, vegetation types or ecosystems.
DOI: 10.5281/zenodo.7644146
title: Microhabitat selection of meadow and steppe vipers enlightened by digital photography and image processing to describe grassland vegetation structure

description: Dataset Understanding animals’ selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterisation of microhabitats, especially for vegetation structure. We studied microhabitat selection of <em>Vipera</em> snakes by comparing grassland vegetation structure between viper occurrence points and random points in three grassland ecosystems: <em>V. graeca</em> in mountain meadows of Albania, <em>V. renardi</em> in loess steppes of Ukraine, and <em>V. ursinii</em> in sand grasslands in Hungary. We quantified vegetation structure in an objective manner by automated processing of images taken of the vegetation against a vegetation profile board under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data obtained in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD). Generalized linear mixed models revealed that snake occurrence was positively related to HCV in <em>V. graeca</em>, to LA in <em>V. renardi</em> and to LA and MHC in <em>V. ursinii</em>, and negatively to to HCV in <em>V. ursinii</em>. Our results demonstrate that vegetation structure variables derived from automated image processing significantly influence viper microhabitat selection. Our method minimises the risk of subjectivity in measuring vegetation structure, allows upscaling if neighbouring pixels are combined, and is suitable for comparison of or extrapolation across different grasslands, vegetation types or ecosystems.
DOI: 10.5281/zenodo.7644037
title: Dataset for surgical workflow and context recognition

description: Dataset based on 6 procedures of radical prostatectomy with lymphadenectomy using da Vinci Xi surgical system (Intuitive Surgical Inc., USA) at European Institute of Oncology (IEO, Milan, Italy). <br> <br> It is divided into 6 folders concerning the step of the procedure: Clips, Dissection, Irrigation, Suction, Suturing, Traction Each step is then divided into the four phases of the procedure: Collapse of the peritoneum, Prostate removal, Lymphadenectomy, Anastomosis Each frame is labeled as follows: PatientNumber_camera_step_NumberOfTheFrame for example, for the first frame of patient 1, left lens of the Da Vinci endoscope, in the dissection step we have:<br> pa1_L_dissection_000000 In the folders concerning the step there are also collected the text files created on anvil (ground truth labels) We appreciate Alice Pierini, Eleonora Pollini, and Raffaella Salama's efforts in making this dataset.
DOI: 10.5281/zenodo.7644036
title: Dataset for surgical workflow and context recognition

description: Dataset based on 6 procedures of radical prostatectomy with lymphadenectomy using da Vinci Xi surgical system (Intuitive Surgical Inc., USA) at European Institute of Oncology (IEO, Milan, Italy). <br> <br> It is divided into 6 folders concerning the step of the procedure: Clips, Dissection, Irrigation, Suction, Suturing, Traction Each step is then divided into the four phases of the procedure: Collapse of the peritoneum, Prostate removal, Lymphadenectomy, Anastomosis Each frame is labeled as follows: PatientNumber_camera_step_NumberOfTheFrame for example, for the first frame of patient 1, left lens of the Da Vinci endoscope, in the dissection step we have:<br> pa1_L_dissection_000000 In the folders concerning the step there are also collected the text files created on anvil (ground truth labels) We appreciate Alice Pierini, Eleonora Pollini, and Raffaella Salama's efforts in making this dataset.
DOI: 10.5281/zenodo.7644170
title: simalia_tracyae_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.7644169
title: simalia_tracyae_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5517/ccdc.csd.cc28t4y6
title: CCDC 2109548: Experimental Crystal Structure Determination

description: Related Article: Julia B. Curley, Clayton Hert, Wesley H. Bernskoetter, Nilay Hazari, Brandon Q. Mercado|2022|Inorg.Chem.|61|643|doi:10.1021/acs.inorgchem.1c03372
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.cc28t4z7
title: CCDC 2109549: Experimental Crystal Structure Determination

description: Related Article: Julia B. Curley, Clayton Hert, Wesley H. Bernskoetter, Nilay Hazari, Brandon Q. Mercado|2022|Inorg.Chem.|61|643|doi:10.1021/acs.inorgchem.1c03372
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.cc28tbr6
title: CCDC 2109728: Experimental Crystal Structure Determination

description: Related Article: S. V. Gutorova, P. I. Matveev, P. S. Lemport, A. L. Trigub, A. S. Pozdeev, A. V. Yatsenko, B. N. Tarasevich, E. A. Konopkina, E. K. Khult, V. A. Roznyatovsky, Yu. V. Nelyubina, K. L. Isakovskaya, V. N. Khrustalev, V. S. Petrov, A. S. Aldoshin, Yu. A. Ustynyuk, V. G. Petrov, S. N. Kalmykov, V. G. Nenajdenko|2022|Inorg.Chem.|61|384|doi:10.1021/acs.inorgchem.1c02982
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.cc28tcdw
title: CCDC 2109748: Experimental Crystal Structure Determination

description: Related Article: S. V. Gutorova, P. I. Matveev, P. S. Lemport, A. L. Trigub, A. S. Pozdeev, A. V. Yatsenko, B. N. Tarasevich, E. A. Konopkina, E. K. Khult, V. A. Roznyatovsky, Yu. V. Nelyubina, K. L. Isakovskaya, V. N. Khrustalev, V. S. Petrov, A. S. Aldoshin, Yu. A. Ustynyuk, V. G. Petrov, S. N. Kalmykov, V. G. Nenajdenko|2022|Inorg.Chem.|61|384|doi:10.1021/acs.inorgchem.1c02982
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.cc28tbv9
title: CCDC 2109731: Experimental Crystal Structure Determination

description: Related Article: S. V. Gutorova, P. I. Matveev, P. S. Lemport, A. L. Trigub, A. S. Pozdeev, A. V. Yatsenko, B. N. Tarasevich, E. A. Konopkina, E. K. Khult, V. A. Roznyatovsky, Yu. V. Nelyubina, K. L. Isakovskaya, V. N. Khrustalev, V. S. Petrov, A. S. Aldoshin, Yu. A. Ustynyuk, V. G. Petrov, S. N. Kalmykov, V. G. Nenajdenko|2022|Inorg.Chem.|61|384|doi:10.1021/acs.inorgchem.1c02982
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.cc27xcr9
title: CCDC 2082851: Experimental Crystal Structure Determination

description: Related Article: Celisnolia M. Leite, João Honorato, Ana Carolina B. M. Martin, Rafael G. Silveira, Felippe M. Colombari, Jéssica C. Amaral, Analu R. Costa, Márcia R. Cominetti, Ana M. Plutín, Debora de Aguiar, Boniek G. Vaz, Alzir A. Batista|2022|Inorg.Chem.|61|664|doi:10.1021/acs.inorgchem.1c03389
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.cc28tkrf
title: CCDC 2109945: Experimental Crystal Structure Determination

description: Related Article: Sylvio Indris, Thomas Bredow, Björn Schwarz, Andreas Eichhöfer|2022|Inorg.Chem.|61|554|doi:10.1021/acs.inorgchem.1c03237
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.cc28tksg
title: CCDC 2109946: Experimental Crystal Structure Determination

description: Related Article: Sylvio Indris, Thomas Bredow, Björn Schwarz, Andreas Eichhöfer|2022|Inorg.Chem.|61|554|doi:10.1021/acs.inorgchem.1c03237
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.cc28k4yy
title: CCDC 2101860: Experimental Crystal Structure Determination

description: Related Article: Yuji Mikata, Yuri Aono, Chihiro Yamamoto, Hiromi Nakayama, Arimasa Matsumoto, Fukue Kotegawa, Masafumi Harada, Hajime Katano, Yoshio Kobayashi, Sachiko Yanagisawa, Minoru Kubo, Atsushi Kajiwara, Masahito Kodera|2022|Inorg.Chem.|61|786|doi:10.1021/acs.inorgchem.1c02699
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.cc28k501
title: CCDC 2101862: Experimental Crystal Structure Determination

description: Related Article: Yuji Mikata, Yuri Aono, Chihiro Yamamoto, Hiromi Nakayama, Arimasa Matsumoto, Fukue Kotegawa, Masafumi Harada, Hajime Katano, Yoshio Kobayashi, Sachiko Yanagisawa, Minoru Kubo, Atsushi Kajiwara, Masahito Kodera|2022|Inorg.Chem.|61|786|doi:10.1021/acs.inorgchem.1c02699
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.cc27xcq8
title: CCDC 2082850: Experimental Crystal Structure Determination

description: Related Article: Celisnolia M. Leite, João Honorato, Ana Carolina B. M. Martin, Rafael G. Silveira, Felippe M. Colombari, Jéssica C. Amaral, Analu R. Costa, Márcia R. Cominetti, Ana M. Plutín, Debora de Aguiar, Boniek G. Vaz, Alzir A. Batista|2022|Inorg.Chem.|61|664|doi:10.1021/acs.inorgchem.1c03389
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.cc26lq7s
title: CCDC 2043775: Experimental Crystal Structure Determination

description: Related Article: Ovender Singh, Ji Min Lee, Yi Young Kang, Seung Hoo Jung, Gui Tae Park, Om Prakash, Ji Yeon Ryu, Junseong Lee|2022|Inorg.Chem.|61|32|doi:10.1021/acs.inorgchem.1c03391
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.cc26lq9v
title: CCDC 2043777: Experimental Crystal Structure Determination

description: Related Article: Ovender Singh, Ji Min Lee, Yi Young Kang, Seung Hoo Jung, Gui Tae Park, Om Prakash, Ji Yeon Ryu, Junseong Lee|2022|Inorg.Chem.|61|32|doi:10.1021/acs.inorgchem.1c03391
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.cc28bnt3
title: CCDC 2095625: Experimental Crystal Structure Determination

description: Related Article: Ovender Singh, Ji Min Lee, Yi Young Kang, Seung Hoo Jung, Gui Tae Park, Om Prakash, Ji Yeon Ryu, Junseong Lee|2022|Inorg.Chem.|61|32|doi:10.1021/acs.inorgchem.1c03391
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.