cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7937101
title: HotBin composter temperature measurements

description: This is a CSV data table with temperature measurements of a HotBin composter, as displayed by the thermometer on its top. Environment temperature, rain is also recorded. A home-made heater unit is installed near the lid of the HotBin, this is a simple kettle that boils the water when a button is pressed, then heats up the water to boiling temperature and does no more heating until the button is pressed again. The composter is fed mainly with kitchen waste, occasionally with garden waste.
description: New in v1.2.0: Column names improved. Records continued till 2023-MAY-24. Two new columns added (addedAmount, addedMaterial) and filled in retrospectively. The sec± new column shows the accuracy of the dateTime.
DOI: 10.5281/zenodo.7953731
title: HotBin composter temperature measurements

description: This is a CSV data table with temperature measurements of a HotBin composter, as displayed by the thermometer on its top. Environment temperature, rain is also recorded. A home-made heater unit is installed near the lid of the HotBin, this is a simple kettle that boils the water when a button is pressed, then heats up the water to boiling temperature and does no more heating until the button is pressed again. The composter is fed mainly with kitchen waste.
description: New in v1.1.0: ℉ temperatures of fence and of composter wall. Records continued till 2023-MAY-20.
DOI: 10.5281/zenodo.7965410
title: Database of fields of education, with explanatory note

description: In addition to respondents’ highest educational qualification, some surveys also collect data on their main field of education. Current measurement practice involves either a closed question with highly aggregated response categories, which are difficult to use for respondents, or an open question, requiring expensive post-coding. Therefore, a measurement tool for fields of education was developed in the SERISS-project in work package 8, Task 8.3. In deliverable D8.9 we provide a database of fields of education and training in 34 languages, including the definition of a search tree interface to facilitate navigation of categories for respondents. All 120 standard categories and classification codes are taken from UNESCO's International Standard Classification of Education for Fields of Education and Training (ISCED-F). For most languages, detailed 3-digit information is available. The database, including a live search feature, is available at the surveycodings website at https://surveycodings.org/articles/codings/fields-of-education. The search tree can be used for respondents’ self-identification of fields of education and training in computer-assisted surveys. The live search feature can also be used for post-coding open answers in already collected data.
DOI: 10.5281/zenodo.7965409
title: Database of fields of education, with explanatory note

description: In addition to respondents’ highest educational qualification, some surveys also collect data on their main field of education. Current measurement practice involves either a closed question with highly aggregated response categories, which are difficult to use for respondents, or an open question, requiring expensive post-coding. Therefore, a measurement tool for fields of education was developed in the SERISS-project in work package 8, Task 8.3. In deliverable D8.9 we provide a database of fields of education and training in 34 languages, including the definition of a search tree interface to facilitate navigation of categories for respondents. All 120 standard categories and classification codes are taken from UNESCO's International Standard Classification of Education for Fields of Education and Training (ISCED-F). For most languages, detailed 3-digit information is available. The database, including a live search feature, is available at the surveycodings website at https://surveycodings.org/articles/codings/fields-of-education. The search tree can be used for respondents’ self-identification of fields of education and training in computer-assisted surveys. The live search feature can also be used for post-coding open answers in already collected data.
DOI: 10.6084/m9.figshare.23118794
title: The genome assembly and annotation data of Pennisetum giganteum

description: Genome assembly and annotation results of <em>Pennisetum giganteum</em>
DOI: 10.5281/zenodo.7732562
title: A New Dataset of People Flow in an Industrial Site with UWB and Motion Capture Systems

description: Improving performance and safety conditions at industrial sites remain key elements of the Group's strategy. Major issues require the ability to dynamically locate people and assets on the site. Currently, the security and regulation of access to areas with different characteristics (types of tasks, level of risk, or confidentiality...) are often carried out with badge doors or barriers. These means present several weaknesses in the face of inappropriate movements of people, but also of objects or tools. Also, there is increasing use of technological devices requiring precise localization in the industrial environment such as AGVs (mobile robots or drones) or augmented reality devices. It is therefore becoming essential to have tools to dynamically manage these flows of people or goods associated with precise location technologies. An Ultra-Wide-Band solution will be employed to quickly and efficiently identify persons who may find themselves in unauthorized areas or perform tasks for which they are uninstructed. Besides dynamic people tracking, this solution can overcome problems of moving objects and tools in production workshops. We propose a new dataset to have information about workers' displacement and evaluate workers' performance and safety. The dataset is available at this link: IndoorIndustrialLocalisationDataset: https://github.com/vauchey/IndoorInsdustrialLocalisationDataset/ Paper : Mickael Delamare<sup>1</sup>, Fabrice Duval<sup>2</sup>, Remi Boutteau<sup>3</sup>. <sup>1</sup>cesi, CESI,Rouen campus, 76000 ROUEN, France,mdelamare@cesi.fr<br> <sup>2</sup> LINEACT CESI, LINEACT CESI, Rouen campus,76000 ROUEN, France, fduval@cesi.fr<br> <sup>3</sup> ESIGELEC , IRSEEM, Rouen, France, Normandie Univ, UNIROUEN, remi.boutteau@univ-rouen.fr, Link : https://www.mdpi.com/1424-8220/20/16/4511 DOI : https://doi.org/10.3390/s20164511 Accepted to the journal Sensors (MDPI)
DOI: 10.5281/zenodo.7732563
title: A New Dataset of People Flow in an Industrial Site with UWB and Motion Capture Systems

description: Improving performance and safety conditions at industrial sites remain key elements of the Group's strategy. Major issues require the ability to dynamically locate people and assets on the site. Currently, the security and regulation of access to areas with different characteristics (types of tasks, level of risk, or confidentiality...) are often carried out with badge doors or barriers. These means present several weaknesses in the face of inappropriate movements of people, but also of objects or tools. Also, there is increasing use of technological devices requiring precise localization in the industrial environment such as AGVs (mobile robots or drones) or augmented reality devices. It is therefore becoming essential to have tools to dynamically manage these flows of people or goods associated with precise location technologies. An Ultra-Wide-Band solution will be employed to quickly and efficiently identify persons who may find themselves in unauthorized areas or perform tasks for which they are uninstructed. Besides dynamic people tracking, this solution can overcome problems of moving objects and tools in production workshops. We propose a new dataset to have information about workers' displacement and evaluate workers' performance and safety. The dataset is available at this link: IndoorIndustrialLocalisationDataset: https://github.com/vauchey/IndoorInsdustrialLocalisationDataset/ Paper : Mickael Delamare<sup>1</sup>, Fabrice Duval<sup>2</sup>, Remi Boutteau<sup>3</sup>. <sup>1</sup>cesi, CESI,Rouen campus, 76000 ROUEN, France,mdelamare@cesi.fr<br> <sup>2</sup> LINEACT CESI, LINEACT CESI, Rouen campus,76000 ROUEN, France, fduval@cesi.fr<br> <sup>3</sup> ESIGELEC , IRSEEM, Rouen, France, Normandie Univ, UNIROUEN, remi.boutteau@univ-rouen.fr, Link : https://www.mdpi.com/1424-8220/20/16/4511 DOI : https://doi.org/10.3390/s20164511 Accepted to the journal Sensors (MDPI)
DOI: 10.57745/ihylig
title: Table S1A P34 Interactome.tab

description: Table containing a list of the cellular interactome for ASFV BA71 P34 protein
DOI: 10.57745/3nxbfp
title: Table S1C MGF360-15R Interactome.tab

description: Table containing a list of the cellular interactome for ASFV BA71 MGF360-15R protein
DOI: 10.57745/qwsde6
title: Table S1B E199L Interactome.tab

description: Table containing a list of the cellular interactome for ASFV BA71 E199L protein
DOI: 10.57745/xplcqq
title: Table S1D E248R Interactome.tab

description: Table containing a list of the cellular interactome for ASFV BA71 E248R protein
DOI: 10.24385/54785
title: Dataset: The evolution of violence in primates
DOI: 10.5281/zenodo.7965440
title: Database of educational attainment, with explanatory note

description: Most social surveys collect data on respondents’ educational attainment. Current measurement practice involves a closed question with country-specific response options, which are needed because of the differences between educational systems. However, these are quite difficult to compare across countries. This is a challenge for both migrant and international surveys. Therefore, a measurement tool for educational attainment that was initially developed for German migrant surveys in the CAMCES project (Schneider, Briceno-Rosas, Herzing, et al. 2018; Schneider, Briceno-Rosas, Ortmanns, et al. 2018) was extended in the SERISS-project in work package 8, Task 8.3. In deliverable D8.8, we provide a database of educational qualifications and levels for 100 countries, including the definition of a search tree interface to facilitate the navigation of categories for respondents in computer-assisted surveys. All country-specific categories are linked to 3-digit codes of UNESCO's International Standard Classification of Education 2011 for Educational Attainment (ISCED-A), as well as to the education coding scheme used in the European Social Survey (ESS), "edulvlb". A live search of the database via two different interfaces, a search box (for a limited set of countries) and a search tree (for all countries), is available at the surveycodings website at https://surveycodings.org/articles/codings/levels-of-education. The search box and search tree can be implemented in survey questionnaires and thereby be used for respondents’ self-classification in computer-assisted surveys. The live search feature can also be used for post-coding open answers in already collected data.
DOI: 10.5281/zenodo.7965439
title: Database of educational attainment, with explanatory note

description: Most social surveys collect data on respondents’ educational attainment. Current measurement practice involves a closed question with country-specific response options, which are needed because of the differences between educational systems. However, these are quite difficult to compare across countries. This is a challenge for both migrant and international surveys. Therefore, a measurement tool for educational attainment that was initially developed for German migrant surveys in the CAMCES project (Schneider, Briceno-Rosas, Herzing, et al. 2018; Schneider, Briceno-Rosas, Ortmanns, et al. 2018) was extended in the SERISS-project in work package 8, Task 8.3. In deliverable D8.8, we provide a database of educational qualifications and levels for 100 countries, including the definition of a search tree interface to facilitate the navigation of categories for respondents in computer-assisted surveys. All country-specific categories are linked to 3-digit codes of UNESCO's International Standard Classification of Education 2011 for Educational Attainment (ISCED-A), as well as to the education coding scheme used in the European Social Survey (ESS), "edulvlb". A live search of the database via two different interfaces, a search box (for a limited set of countries) and a search tree (for all countries), is available at the surveycodings website at https://surveycodings.org/articles/codings/levels-of-education. The search box and search tree can be implemented in survey questionnaires and thereby be used for respondents’ self-classification in computer-assisted surveys. The live search feature can also be used for post-coding open answers in already collected data.
DOI: 10.25345/c5rr1px4m
title: MassIVE MSV000092024 - GNPS Rumex sanguineus stems, leaves and roots
title: Analysis and molecular characterization of the secondary metabolite profile of different organs of Rumex sanguineus: roots, leaves and stems
DOI: 10.7303/syn43685982.2
title: AKTIVES - A physiological signal database of children with neurodevelopmental disorders for stress recognition
DOI: 10.5281/zenodo.7457013
title: Raw data for: Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity

description: This repository contains raw data and code related to "Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity" by Goretzki et al. Included are molecular dynamics parameter files, initial structures after system equilibration, production trajectories, and final structures of simulations of:<br> 1. coarse-grained IDRs on membrane, and force and position data for restrained c-termini. Trajectories are subsampled with one frame every 50 ns.<br> 2. The tetrameric TRPV4 core in a POPC in atomistic resolution. Trajectories are sampled with one frame every 1 ns. <br> 3. The isolated ARD in solution in atomistic resolution. Trajectories are subsampled with one frame every 1 ns. Contact information:<br> Name: Stefan L. Schaefer<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: stefan.schaefer@biophys.mpg.de Name: Ainara Claveras Cabezudo<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: ainara.claveras@biophys.mpg.de
description: This work was supported by the Max Planck Society and the Collaborative Research Center 1507 funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). We also thank the Max Planck Computing and Data Facility (MPCDF) for computational resources.
DOI: 10.5281/zenodo.7457014
title: Raw data for: Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity

description: This repository contains raw data and code related to "Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity" by Goretzki et al. Included are molecular dynamics parameter files, initial structures after system equilibration, production trajectories of IDRs on membrane, and force and position data for restrained c-termini. Trajectories are subsampled with one frame every 50 ns. Contact information:<br> Name: Stefan L. Schaefer<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: stefan.schaefer@biophys.mpg.de
description: This work was supported by the Max Planck Society and the Collaborative Research Center 1507 funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). We also thank the Max Planck Computing and Data Facility (MPCDF) for computational resources.
DOI: 10.5281/zenodo.7778197
title: Raw data for: Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity

description: <strong>Despite the name, the compression format is tar.gz </strong> This repository contains raw data and code related to "Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity" by Goretzki et al. Included are molecular dynamics parameter files, initial structures after system equilibration, production trajectories of:<br> 1. coarse-grained IDRs on membrane, and force and position data for restrained c-termini. Trajectories are subsampled with one frame every 50 ns.<br> 2. The tetrameric TRPV4 core in a POPC in atomistic resolution. Trajectories are sampled with one frame every 1 ns. <br> 3. The isolated ARD in solution in atomistic resolution. Trajectories are subsampled with one frame every 1 ns. Contact information:<br> Name: Stefan L. Schaefer<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: stefan.schaefer@biophys.mpg.de Name: Ainara Claveras Cabezudo<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: ainara.claveras@biophys.mpg.de
description: This work was supported by the Max Planck Society and the Collaborative Research Center 1507 funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). We also thank the Max Planck Computing and Data Facility (MPCDF) for computational resources.
DOI: 10.5281/zenodo.7957940
title: Raw data for: Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity

description: This repository contains raw data and code related to "Crosstalk between regulatory elements in the disordered TRPV4 N-terminus modulates lipid-dependent channel activity" by Goretzki et al. Included are molecular dynamics parameter files, initial structures after system equilibration, production trajectories, and final structures of simulations of:<br> 1. coarse-grained IDRs on membrane, and force and position data for restrained c-termini. Trajectories are subsampled with one frame every 50 ns.<br> 2. The tetrameric TRPV4 core in a POPC in atomistic resolution. Trajectories are sampled with one frame every 1 ns. <br> 3. The isolated ARD in solution in atomistic resolution. Trajectories are subsampled with one frame every 1 ns. Contact information:<br> Name: Stefan L. Schaefer<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: stefan.schaefer@biophys.mpg.de Name: Ainara Claveras Cabezudo<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: ainara.claveras@biophys.mpg.de
description: This work was supported by the Max Planck Society and the Collaborative Research Center 1507 funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). We also thank the Max Planck Computing and Data Facility (MPCDF) for computational resources.
DOI: 10.34740/kaggle/dsv/5761975
title: AutoXGB
DOI: 10.6084/m9.figshare.23127494
title: Prudent burrow site selection in a landscape of fear (Data and R code)

description: <strong>Data Description</strong> <br> Isopods from a natural population visited safe and risky burrows created by introducing scorpion predators near some isopod burrows. Their preferences were quantified by observing whether they entered the burrow or not, and if they did enter by recording the time they spent inside a burrow. Finally, individual quality was measured by weighing them at the end of the trial. Data were collected starting from between 1300 to 1400 hours to 1600 to 1700 hours. The R file titled '<strong>pram_prud_fig.R</strong>' has all the code used to run all the analyses and the plots. <br> <strong>Data availability Statements</strong> The file titled<strong> ‘pram_data_fig.csv’ </strong>has all the relevant data. It has the following columns: Individual.code – Individual identity of each male. Date – The date when the trial was conducted. Time – The time when the observation was made. date_time – Previous two columns combined. Duration – The duration for which the action mentioned in the current row lasted. Action – The behaviour performed by the isopod, written as a code (the table below has details of what the code means). Burrow.block – The block of safe and risky burrows. Burrows.visited – The specific burrows visited within the block. Observer.name – Name of the human observer. Terrace.no. – The terrace on which the block was designed. Sex – Sex of the individual Weight – Body weight of the individual Burrow.already.occupied.by – Which individual was already occupying the burrow when the focal individual visited. Collected.at.end.of.sampling – Was the isopod still occupying the burrow at the end of the 2 days of trial? 1 for yes, blank for no. Fight.with.whom – With which isopod from inside the burrow did the focal individual fight with? <br> <strong>Details of the code used to describe isopod behaviour at and inside the burrow</strong> <br> <strong>1 - </strong>Rejects burrow <strong>2 - </strong>Samples burrow <strong>3 - </strong>Occupies burrow <strong>4 - </strong>Starts digging <strong>5 - </strong>Samples scorpion burrow <strong>6 - </strong>Mild competition with sampling isopod <strong>7 - </strong>Aggressive competition with sampling isopod <strong>8 - </strong>Leaves burrow <strong>9 - </strong>Enters burrow <strong>10 - </strong>flipped orientation <strong>11 - </strong>Collected
DOI: 10.6084/m9.figshare.23127494.v2
title: Prudent burrow site selection in a landscape of fear (Data and R code)

description: <strong>Data Description</strong> <br> Isopods from a natural population visited safe and risky burrows created by introducing scorpion predators near some isopod burrows. Their preferences were quantified by observing whether they entered the burrow or not, and if they did enter by recording the time they spent inside a burrow. Finally, individual quality was measured by weighing them at the end of the trial. Data were collected starting from between 1300 to 1400 hours to 1600 to 1700 hours. The R file titled '<strong>pram_prud_fig.R</strong>' has all the code used to run all the analyses and the plots. <br> <strong>Data availability Statements</strong> The file titled<strong> ‘pram_data_fig.csv’ </strong>has all the relevant data. It has the following columns: Individual.code – Individual identity of each male. Date – The date when the trial was conducted. Time – The time when the observation was made. date_time – Previous two columns combined. Duration – The duration for which the action mentioned in the current row lasted. Action – The behaviour performed by the isopod, written as a code (the table below has details of what the code means). Burrow.block – The block of safe and risky burrows. Burrows.visited – The specific burrows visited within the block. Observer.name – Name of the human observer. Terrace.no. – The terrace on which the block was designed. Sex – Sex of the individual Weight – Body weight of the individual Burrow.already.occupied.by – Which individual was already occupying the burrow when the focal individual visited. Collected.at.end.of.sampling – Was the isopod still occupying the burrow at the end of the 2 days of trial? 1 for yes, blank for no. Fight.with.whom – With which isopod from inside the burrow did the focal individual fight with? <br> <strong>Details of the code used to describe isopod behaviour at and inside the burrow</strong> <br> <strong>1 - </strong>Rejects burrow <strong>2 - </strong>Samples burrow <strong>3 - </strong>Occupies burrow <strong>4 - </strong>Starts digging <strong>5 - </strong>Samples scorpion burrow <strong>6 - </strong>Mild competition with sampling isopod <strong>7 - </strong>Aggressive competition with sampling isopod <strong>8 - </strong>Leaves burrow <strong>9 - </strong>Enters burrow <strong>10 - </strong>flipped orientation <strong>11 - </strong>Collected