cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0928724.09fu
title: SH0928724.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0928725.09fu
title: SH0928725.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0928726.09fu
title: SH0928726.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0928727.09fu
title: SH0928727.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0928728.09fu
title: SH0928728.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0928729.09fu
title: SH0928729.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0928730.09fu
title: SH0928730.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.18112/openneuro.ds001439.v1.2.0
title: A role for the medial temporal lobe subsystem in guiding prosociality: the effect of episodic processes on willingness to help others
DOI: 10.5281/zenodo.2555468
title: Binary black-hole simulation SXS:BBH:1430

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2555469
title: Binary black-hole simulation SXS:BBH:1430

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/2pfc7jdyfj.2
title: Wi-Fi spatial clusters

description: The data consists of Wi-Fi scan records for 606 spatial clusters, represented by the circle of with 350m radius. Scan records contain information about recording time, spatial distance of the record from the cluster centre (metres) and normalized Wi-Fi signal strength for each detected MAS adress. Data for each cluster in a separate file, the number of columns (unique MACs) differs. Variable desription: "ts" - the number of seconds from the beginning of the 14-day measurement. 0 = beginning, 60*60*24*14 = 1209600 = end "macn" - the number of unique MACs in the scan "gpsn" - number of location points used for the determination of the scan location "d" - the distance from the place center, in meters "week" - the week of the measurement, first (1) or second (2) "m1" to "mn" - normalized Wi-Fi signal strength. 0 = no signal, 1 = max signal. "m" column for each MAC detected in cluster.
DOI: 10.17632/cpc43d2pny.1
title: Developing meaningful communication with a youth audience through co-design: the case of youth in Cape Town, South Africa

description: The youth faces unique challenges due to constant movement within the global economic and technological contexts. A digitally oversaturated world with constant access to globalised, mass information makes it challenging for communication designers to reach this audience on important matters. The South African context further complicates matters as youth unemployment is at an all-time high, a lack of quality schooling continues to feed poverty and inequality, exposure to gangs, violence, trauma and sexual abuse contribute to antisocial behaviour and drug and alcohol abuse increase risky sexual behaviour. It is therefore important to connect with the youth on these matters. The need to explore the mechanisms and content which will successfully connect with a South African youth audience was identified. In response to this, this study explored what the youth considers to be meaningful communication. The main objective of this research was to explore what types of visual communication have meaning for the youth to enable communication designers to connect with the South African youth market. The study used case study methodology and data was collected qualitatively through a questionnaire and participatory methods, including two co-design workshops (with 20 participants, aged 20-27) and a small group discussion (with 5 participants). The study featured a co-design approach, which focused on collaborative meaning-making through the visualisation of communication pieces. The study identified several interconnected themes which relate to a bigger category of association. Three major categories of understanding were identified: perception (how the youth see their world); engagement (how the youth experience their world); and relevance (how the youth relate to their world). These themes provide visual communication designers with valuable insights relating to the youth audience.
DOI: 10.5281/zenodo.2555083
title: SINS database - Node 4 - Daily activities in a home environment recorded using a Acoustic Sensor Network

description: The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br>
<br>
To obtain more information on the database please visit this website and read the published paper.<br>
<strong>Please read to license file (available in this repository) before using the database.</strong><br>
<br>
When using this database you should <strong>cite the following paper</strong>:<br>
Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.
description: {"references": ["G. Dekkers, S. Lauwereins, B. Thoen, M. W. Adhana, H. Brouckxon, T. van Waterschoot, B. Vanrumste, M. Verhelst, and P. Karsmakers, \"The SINS database for detection of daily activities in a home environment using an acoustic sensor network,\" in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), Munich, Germany, November 2017, pp. 32\u201336."]}
DOI: 10.5281/zenodo.2555084
title: SINS database - Node 4 - Daily activities in a home environment recorded using a Acoustic Sensor Network

description: The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br>
<br>
To obtain more information on the database please visit this website and read the published paper.<br>
<strong>Please read to license file (available in this repository) before using the database.</strong><br>
<br>
When using this database you should <strong>cite the following paper</strong>:<br>
Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.
description: {"references": ["G. Dekkers, S. Lauwereins, B. Thoen, M. W. Adhana, H. Brouckxon, T. van Waterschoot, B. Vanrumste, M. Verhelst, and P. Karsmakers, \"The SINS database for detection of daily activities in a home environment using an acoustic sensor network,\" in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), Munich, Germany, November 2017, pp. 32\u201336."]}
DOI: 10.5281/zenodo.2555177
title: Screw and hole detection output results dataset in an autonomous screwing operation

description: This dataset contains a set of csv files containing the results of a screwing and hole detection developed for a screwing mobile robot. It also contains a set of images representing the inputs, the outputs and some relevant images in the hole detection algorithm.

Thee different scenarios were built, and a total of 25 missions were executed in order to build the datasets presented in appendix 5.7. The first scenario (missions 1 to 15), represents a normal operation procedure, meaning, a screwing 6 hole screwing and 5 screws refilling. The second scenario (missions 16 to 20), represents an operation with an exception handling during the refill (the second, third and fourth screws are missing in the refill support). Lastly, the third scenario (missions 21 to 25) has another exception handling, this time on both hole and screw detections (the third, fourth and fifth holes are already screwed, and the screwdriver trigger is not pressed, so the screw is not tightened resulting in a screw detecting after the refilling phase.

Also three different group of csv files can be found:


	<em>hole_detection_mission_xx.csv</em><sup><em><sup>1</sup></em></sup>: contains the hole detection result (detected or non detected) and the located hole coordinates (u,v), in pixels;
	
	<em>detect_screw_screwing_result_mission_xx</em>.csv: contains the screw detection result performed after a screwing to detect if the screw was screwed successfully. 1 means the screwing was ok (there is no screw on the screwdriver), 0 means the screwing was not ok (there was a screw on the screwdriver);
	
	
	<em>detect_screw_refill_mission_xx</em>.csv: contains the screw detection result performed after a refill attempt, to check if there was any screw missing in the refill support. 0 means that no screw was missing on the refill support (there was a screw on the screwdriver), 1 means there was a screw missing on the support (there was no screw on the screwdriver).
	


The <em>mission_xx</em> suffix represents which mission file (rosbag) the mission was acquired in and, each csv file contains the timestamp in which it happens.

1 xx represents the mission number
DOI: 10.5281/zenodo.2555470
title: Binary black-hole simulation SXS:BBH:1431

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2555471
title: Binary black-hole simulation SXS:BBH:1431

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5517/ccdc.csd.cc1zlfvv
title: CCDC 1834978: Experimental Crystal Structure Determination

description: Related Article: Jakub Iwanejko, Anna Brol, Bartłomiej Szyja, Marek Daszkiewicz, Elżbieta Wojaczyńska, Tomasz K. Olszewski|2019|Tetrahedron|75|1431|doi:10.1016/j.tet.2019.01.062
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.cc1zlvt7
title: CCDC 1835380: Experimental Crystal Structure Determination

description: Related Article: Guo-Bin Xiao, Xiao-Qiang Yao, Hua Xie, Heng-Chang Ma, Pen-Ji Yan, Dong-Dong Qin|2019|Polyhedron|162|39|doi:10.1016/j.poly.2019.01.048
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.cc20bqmq
title: CCDC 1857353: Experimental Crystal Structure Determination

description: Related Article: Tengfei Kang, Weidi Cao, Liuzhen Hou, Qiong Tang, Sijia Zou, Xiaohua Liu, Xiaoming Feng|2019|Angew.Chem.,Int.Ed.|58|2464|doi:10.1002/anie.201810961
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.cc20bqps
title: CCDC 1857355: Experimental Crystal Structure Determination

description: Related Article: Tengfei Kang, Weidi Cao, Liuzhen Hou, Qiong Tang, Sijia Zou, Xiaohua Liu, Xiaoming Feng|2019|Angew.Chem.,Int.Ed.|58|2464|doi:10.1002/anie.201810961
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.cc20bqwz
title: CCDC 1857361: Experimental Crystal Structure Determination

description: Related Article: Tengfei Kang, Weidi Cao, Liuzhen Hou, Qiong Tang, Sijia Zou, Xiaohua Liu, Xiaoming Feng|2019|Angew.Chem.,Int.Ed.|58|2464|doi:10.1002/anie.201810961
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: 10.5281/zenodo.2555079
title: SINS database - Node 9 - Daily activities in a home environment recorded using a Acoustic Sensor Network

description: The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br>
<br>
To obtain more information on the database please visit this website and read the published paper.<br>
<strong>Please read to license file (available in this repository) before using the database.</strong><br>
<br>
When using this database you should <strong>cite the following paper</strong>:<br>
Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.
description: {"references": ["G. Dekkers, S. Lauwereins, B. Thoen, M. W. Adhana, H. Brouckxon, T. van Waterschoot, B. Vanrumste, M. Verhelst, and P. Karsmakers, \"The SINS database for detection of daily activities in a home environment using an acoustic sensor network,\" in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), Munich, Germany, November 2017, pp. 32\u201336."]}
DOI: 10.5281/zenodo.2555080
title: SINS database - Node 9 - Daily activities in a home environment recorded using a Acoustic Sensor Network

description: The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br>
<br>
To obtain more information on the database please visit this website and read the published paper.<br>
<strong>Please read to license file (available in this repository) before using the database.</strong><br>
<br>
When using this database you should <strong>cite the following paper</strong>:<br>
Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.
description: {"references": ["G. Dekkers, S. Lauwereins, B. Thoen, M. W. Adhana, H. Brouckxon, T. van Waterschoot, B. Vanrumste, M. Verhelst, and P. Karsmakers, \"The SINS database for detection of daily activities in a home environment using an acoustic sensor network,\" in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), Munich, Germany, November 2017, pp. 32\u201336."]}