cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2c3qks
title: CCDC 2178325: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qlt
title: CCDC 2178326: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qmv
title: CCDC 2178327: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qnw
title: CCDC 2178328: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qpx
title: CCDC 2178329: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qqy
title: CCDC 2178330: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qrz
title: CCDC 2178331: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qs0
title: CCDC 2178332: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qt1
title: CCDC 2178333: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qv2
title: CCDC 2178334: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qw3
title: CCDC 2178335: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qx4
title: CCDC 2178336: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qy5
title: CCDC 2178337: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3qz6
title: CCDC 2178338: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3r08
title: CCDC 2178339: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3r19
title: CCDC 2178340: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3r2b
title: CCDC 2178341: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3r3c
title: CCDC 2178342: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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.cc2c3r4d
title: CCDC 2178343: Experimental Crystal Structure Determination

description: Related Article: Damian Paliwoda, Laure Vendier, William Nicolazzi, Gábor Molnár, Azzedine Bousseksou|2022|Inorg.Chem.|61|15991|doi:10.1021/acs.inorgchem.2c02286
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: 10.21427/dwpw-1d69
title: Taxonomic Word Embeddings - Trained on English WordNet Random Walk Pseudo-Corpora
DOI: 10.6084/m9.figshare.21293730
title: Data

description: These are data we used in this paper
DOI: 10.6084/m9.figshare.21293730.v1
title: Data

description: These are data we used in this paper
DOI: 10.5281/zenodo.7185663
title: Non-acoustic speech sensing system based on flexible piezoelectric

description: The non-acoustic speech sensing system based on flexible piezoelectric is designed to satisfy specific needs around testing device models (in high-noise, complex environments). The system collected vibration signals from the jaws of six males and five females containing ten different control commands at 90 dB of background noise. The dataset is reliable with high intelligibility and is able to achieve 93.7% recognition accuracy by calculation. In general, this paper provides a non-acoustic speech dataset for Mandarin, including the parts collected, the number of people collected, and the environment. <br> The dataset is available at: https://doi.org/10.5281/zenodo.7185663 <br> The data descriptor paper with details of data collection and cleaning process is under submission. For proper citation of the manuscript, please refer to the latest version of this dataset which includes the details. This dataset and its descriptor paper were created by: Shiji Yuan, Ying Sun, Shuai Wang, Xinlei Chen,Ying Ding,Dezhi Zheng , Shangchun Fan For questions or suggestions, please e-mail Shuai Wang &lt;wangshuai@buaa.edu.cn&gt; <br> <strong>Description:</strong><br> Ten common words were chosen as the core of the vocabulary in this dataset. These ten command words can be used for commands in IoT or robotics applications: "forward", "backward", "right", "left", "stop", "up", "down", "draw", "drop", and "reset". The recording was carried on by software named Adobe Audition2022. We set monophonic recording, 16-bit storage format, and 16 kHz sampling frequency before recording and saved the recorded voice in wav format. The dataset is provided with two storage rules, which are stored by subject number and command number as classification. In the first rule, the speech data of 11 subjects were stored in different folders with the subject serial number as the folder name. Each folder contains subfolders categorized by command. In the second rule, the speech data of ten commands are stored in different folders, and the names of the folders are the command contents. The subject number, command number and record order are given for each data entry. For example, the data obtained when subject 1 recorded command 10 for the first time was labeled as "1-10_1". After the data collection process, a filtering algorithm for automatic detection of low non-acoustic speech data was designed to remove problematic data that were very short or very quiet.The script of the data filtering algorithm is provided in this repository. For specific detail of the data filtering process, please refer to the script (speech data filtering algorithm in MATLAB) in this repository and the data descriptor paper. The dataset in this repository is the processed version. The raw dataset and removed audio files are not included in this repository. <br> <br> <strong>File list:</strong><br> <br> Non-acoustic Speech Dataset.zip speech data filtering algorithm.zip Readme.txt <br>
DOI: 10.5281/zenodo.7185662
title: Non-acoustic speech sensing system based on flexible piezoelectric

description: The non-acoustic speech sensing system based on flexible piezoelectric is designed to satisfy specific needs around testing device models (in high-noise, complex environments). The system collected vibration signals from the jaws of six males and five females containing ten different control commands at 90 dB of background noise. The dataset is reliable with high intelligibility and is able to achieve 93.7% recognition accuracy by calculation. In general, this paper provides a non-acoustic speech dataset for Mandarin, including the parts collected, the number of people collected, and the environment. <br> The dataset is available at: https://doi.org/10.5281/zenodo.7185663 <br> The data descriptor paper with details of data collection and cleaning process is under submission. For proper citation of the manuscript, please refer to the latest version of this dataset which includes the details. This dataset and its descriptor paper were created by: Shiji Yuan, Ying Sun, Shuai Wang, Xinlei Chen,Ying Ding,Dezhi Zheng , Shangchun Fan For questions or suggestions, please e-mail Shuai Wang &lt;wangshuai@buaa.edu.cn&gt; <br> <strong>Description:</strong><br> Ten common words were chosen as the core of the vocabulary in this dataset. These ten command words can be used for commands in IoT or robotics applications: "forward", "backward", "right", "left", "stop", "up", "down", "draw", "drop", and "reset". The recording was carried on by software named Adobe Audition2022. We set monophonic recording, 16-bit storage format, and 16 kHz sampling frequency before recording and saved the recorded voice in wav format. The dataset is provided with two storage rules, which are stored by subject number and command number as classification. In the first rule, the speech data of 11 subjects were stored in different folders with the subject serial number as the folder name. Each folder contains subfolders categorized by command. In the second rule, the speech data of ten commands are stored in different folders, and the names of the folders are the command contents. The subject number, command number and record order are given for each data entry. For example, the data obtained when subject 1 recorded command 10 for the first time was labeled as "1-10_1". After the data collection process, a filtering algorithm for automatic detection of low non-acoustic speech data was designed to remove problematic data that were very short or very quiet.The script of the data filtering algorithm is provided in this repository. For specific detail of the data filtering process, please refer to the script (speech data filtering algorithm in MATLAB) in this repository and the data descriptor paper. The dataset in this repository is the processed version. The raw dataset and removed audio files are not included in this repository. <br> <br> <strong>File list:</strong><br> <br> Non-acoustic Speech Dataset.zip speech data filtering algorithm.zip Readme.txt <br>
DOI: 10.7910/dvn/8swwhg
title: Replication Data for: Across the Boards: Explaining Firm Support for Climate Policy

description: When do corporations stop ignoring or opposing climate action and start to go green? We focus on the role of corporate boards of directors, which shape firms' positions on internal and external issues of corporate governance and public policy. We argue that board decisions to engage constructively on climate issues are likely to be influenced by the choices and experiences of other firms. Learning, socialization, and competitive dynamics are especially important in highly salient and rapidly evolving policy areas, like climate change. To test this theory, we construct the network of board memberships for America's public corporations and uncover robust evidence that climate innovations diffuse among companies that share board members in common, and among companies whose board members interact at separate boards. Understanding the unfolding dynamics of corporate climate action requires examining corporate boards and their social context.
DOI: 10.5281/zenodo.7024006
title: Dataset for 'A deep learning-based quality control loop of the extrusion-based bioprinting process'

description: Zip file containing the dataset for the paper 'A deep learning-based quality control loop of the extrusion-based bioprinting process' (available at https://ijb.whioce.com/index.php/int-j-bioprinting/article/view/620). The dataset is composed of: A series of video folders, each having a unique ID, and containing the processed video frames. A master.csv file containing all the metadata for each video. The authors acknowledge the supported by the European Union’s Horizon 2020 research and innovation program under the project GIOTTO: “Giotto: Active ageing and osteoporosis: The next challenge for smart nanobiomaterials and 3D technologies,” grant agreement no. 814410.
DOI: 10.5281/zenodo.7024007
title: Dataset for 'A deep learning-based quality control loop of the extrusion-based bioprinting process'

description: Zip file containing the dataset for the paper 'A deep learning-based quality control loop of the extrusion-based bioprinting process' (available at https://ijb.whioce.com/index.php/int-j-bioprinting/article/view/620). The dataset is composed of: A series of video folders, each having a unique ID, and containing the processed video frames. A master.csv file containing all the metadata for each video. The authors acknowledge the supported by the European Union’s Horizon 2020 research and innovation program under the project GIOTTO: “Giotto: Active ageing and osteoporosis: The next challenge for smart nanobiomaterials and 3D technologies,” grant agreement no. 814410.
DOI: 10.5258/soton/d2398
title: Dataset in support of the journal article "A practical approach to modelling railway vehicle interior acoustics"

description: Dataset for the paper "A practical approach to modelling railway vehicle interior acoustics" accepted in Journal "Applied Acoustics" https://doi.org/10.1016/j.apacoust.2022.109055 This dataset contains: Data relating to all figures the data from each figure is given in a separate tab in the Excel file. Each curve is listed as a separate column
DOI: 10.5281/zenodo.7015011
title: Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster: scripts and files

description: Pipeline and analysis scripts as well as final data files
DOI: 10.5281/zenodo.7015010
title: Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster: scripts and files

description: Pipeline and analysis scripts as well as final data files
DOI: 10.5281/zenodo.6805560
title: RadarPWN

description: RadarPWN is a comprehensive, easy-to-use, and documented dataset, including cyberattacks against radar communication in modern Integrated Bridge Systems. RadarPWN was recorded using a simulation environment consisting of the BridgeCommand ship simulator, our Radar Attack Tool and the OpenCPN chart plotter. The resulting data consists of Navico BR24 and NMEA 0183 network traffic in benign and "attack" scenarios.<br> <br> The dataset is available in two forms: <em>radarpwn-x-y-z</em> contains all network captures as pcaps as well as configuration files used for the simulation runs and logs <em>radarpwn-x-y-z-screen-captures </em>contains all of the above in addition to screen recording videos of all of the simulation runs showing the chart plotter, the radar screen and the logs of the Radar Attack Tool, which can be helpful to visualize the attacks contained in the network captures. For more details on the structure and content of the dataset, please consult the provided README.md (or README.html)