cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5519/0070476
title: Lincolnshire Plants: Past and Future

description: Lincolnshire Plants: Past and Future (popularly known as ‘LoveLincsPlants’) is a National Lottery Heritage Fund (NLHF) supported project in collaboration with the Lincolnshire Wildlife Trust (LWT), Sir Joseph Banks Society (SJBS), the Lincolnshire Naturalists’ Union (LNU) and the University of Lincoln. The main delivery phase ran from 2017-2021 and the five-year legacy phase of the project runs from 2022-2026. Born initially from the desire to secure the future of the LNU’s historical herbarium of c. 12,000 specimens, but with the aspiration to make a contemporary collection and in so doing training the botanists of the future. The historical herbarium, primarily the collections of the Rev. E.A. Woodruffe-Peacock (1858-1922) and those of the author of the first county flora, E. Joan Gibbons (1902-1988), but with some significant earlier collections dating back to the 1800s, is the largest repository of material from what is, in national collections, an under-represented county. These items have been re-curated, digitised and incorporated into the British & Irish herbarium at the NHM, the specimen data and images made publicly accessible. Since 2017, NHM project staff have delivered training to local volunteers in plant identification, specimen preparation and collections care to enable the creation of a new herbarium for Lincolnshire. Through these activities we have promoted an understanding of the value of collections and their uses. The project has engaged with over 27,000 people, re-connecting people with plants, enabling people to rediscover their local natural heritage and be better informed about biodiversity and the environment. Knowledge of plant science is declining in the wider community and Lincolnshire is acutely short of younger skilled botanists, at a time when environmental concerns and awareness of the value of the natural environment and its appreciation is growing. To address this need, project partners have worked with the University of Lincoln on the development and delivery of their BSc Ecology and Conservation degree course while developing a core group of 18-35 year-old botanists in Lincolnshire. By making a contemporary herbarium collection, part of which is curated at the Sir Joseph Banks Centre in Horncastle, we hope to build capacity within the botanical sector and raise awareness more generally. During the legacy phase, we will continue to develop a contemporary herbarium with Lincolnshire volunteers and our partners. The dataset includes both specimens from the LNU’s historical herbarium together with specimens housed at the NHM acquired as part of the project. A guide to searching the dataset can be found [here.](https://data.nhm.ac.uk/dataset/lincs-plants/resource/c39f77ec-3583-4648-b810-0a6872e2832a)
DOI: 10.5281/zenodo.6688451
title: Super Short NIRCam GRISM256 Simulation

description: <pre>MIRAGE Time Series Tests</pre> A super short data set, for the long-wavelength and the short-wavelength on NIRCam, using the SUBGRISM256 array. Useful for testing the jtow pipeline (https://jtow.readthedocs.io/en/latest/index.html).
DOI: 10.5281/zenodo.6688450
title: Super Short NIRCam GRISM256 Simulation

description: <pre>MIRAGE Time Series Tests</pre> A super short data set, for the long-wavelength and the short-wavelength on NIRCam, using the SUBGRISM256 array. Useful for testing the jtow pipeline (https://jtow.readthedocs.io/en/latest/index.html).
DOI: 10.6084/m9.figshare.20137220
title: Dataset: Spiritual Intelligence and Personality

description: A dataset of Spiritual Intelligence (SISRI-24) and Personalty Traits (HEXACO) measures for N = 240 college students at a mid-sized private Chirstian university in the West South-Central United States.
DOI: 10.5517/ccdc.csd.cc26jxym
title: CCDC 2042061: Experimental Crystal Structure Determination

description: Related Article: Yanwei Gu, Victor Vega-Mayoral, Saül Garcia-Orrit, Dieter Schollmeyer, Akimitsu Narita, Juan Cabanillas-González, Zijie Qiu, Klaus Müllen|2022|Angew.Chem.,Int.Ed.|61|e202201088|doi:10.1002/anie.202201088
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.cc27r6x4
title: CCDC 2077896: Experimental Crystal Structure Determination

description: Related Article: Eduarda C. Queiroz, Chris H.J. Franco, Monica S. Ferreira, Ricardo O. Freire, Flávia C. Machado|2022|J.Lumin.|249|118990|doi:10.1016/j.jlumin.2022.118990
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.cc27r6y5
title: CCDC 2077897: Experimental Crystal Structure Determination

description: Related Article: Eduarda C. Queiroz, Chris H.J. Franco, Monica S. Ferreira, Ricardo O. Freire, Flávia C. Machado|2022|J.Lumin.|249|118990|doi:10.1016/j.jlumin.2022.118990
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.cc27r6z6
title: CCDC 2077898: Experimental Crystal Structure Determination

description: Related Article: Eduarda C. Queiroz, Chris H.J. Franco, Monica S. Ferreira, Ricardo O. Freire, Flávia C. Machado|2022|J.Lumin.|249|118990|doi:10.1016/j.jlumin.2022.118990
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: 10.6084/m9.figshare.20134091
title: Charite_01/2021_3T

description: Multiple structural sequences scanned from my brain with a focus on subcortical structures (total ~3.5 scan hours with various anatomical sequences acquired in a single session).
DOI: 10.6084/m9.figshare.20132678.v1
title: primary ATRT RNA-seq: matrix of raw counts

description: Matrix of raw counts of RNA-seq data from 49 primary ATRT samples were generated using an in-house pipeline developed at the Institut Curie Bioinformatics Core Facility (available at https://github.com/bioinfo-pf-curie/RNA-seq) and the human reference genome hg19. Except, the first column which contains the gene name, columns correspond to samples and named by the patient ID.
DOI: 10.6084/m9.figshare.19706659
title: Autonomous scanning droplet cell supporting datasets

description: Electrochemical corrosion datasets accompanying https://arxiv.org/abs/2203.17049 <br> * AlNiTi dataset [[https://dx.doi.org/10.1021/acscombsci.9b00215][10.1021/acscombsci.9b00215]] ** e-chem data ** e-chem analysis <br> * TiNbTa dataset ** XRF composition map ** synchrotron XRD *** manual phase annotations *** williamson-hall analysis ** e-chem dataset <br> * electrodeposition datasets ** Cu deposition ** NiCo calibration series <br>
DOI: 10.6084/m9.figshare.19706659.v1
title: Autonomous scanning droplet cell supporting datasets

description: Electrochemical corrosion datasets accompanying https://arxiv.org/abs/2203.17049 <br> * AlNiTi dataset [[https://dx.doi.org/10.1021/acscombsci.9b00215][10.1021/acscombsci.9b00215]] ** e-chem data ** e-chem analysis <br> * TiNbTa dataset ** XRF composition map ** synchrotron XRD *** manual phase annotations *** williamson-hall analysis ** e-chem dataset <br> * electrodeposition datasets ** Cu deposition ** NiCo calibration series <br>
DOI: 10.6084/m9.figshare.16526631
title: MAGeCK gene summary files

description: MAGeck gene summary files for cancer cells - dmso vs drug treatment - CRISPR/Cas9 vs CRISPR activation screens
DOI: 10.6084/m9.figshare.16526631.v1
title: MAGeCK gene summary files

description: MAGeck gene summary files for cancer cells - dmso vs drug treatment - CRISPR/Cas9 vs CRISPR activation screens
DOI: 10.6084/m9.figshare.16527381
title: CRISPR read count files

description: Raw read counts for all CRISPR screens
DOI: 10.25500/edata.bham.00000856
title: Research data supporting "A study on the performance of low-cost sensors for source apportionment at an urban background site"

description: Measurements from low-cost sensors and regulatory grade instruments
DOI: 10.5281/zenodo.6308780
title: The Hume Vocal Burst Competition Dataset (H-VB) | Raw Data [ExVo: updated 02.28.22]

description: This package includes the raw data for a subset of the Hume Vocal Burst (Hume-VB) dataset used for the ExVo 2022 Competition.<br> <br> <strong>The competition is now over</strong>, please fill out this form to request access to the full Hume VB dataset. More information on the competition and dataset can be found in the competition white paper.<br> -- <br> This dataset contains <strong>59,201 audio recordings of vocal bursts from 1,702 speakers</strong>, from 4 cultures, the <strong>U.S.A, South Africa, China, </strong>and<strong> Venezuela</strong>, ranging in age from <strong>20 to 39.5 years old</strong>. The total duration of data in this version of <strong>Hume-VB is 36 Hours </strong> (Mean: 02.23 sec). A subset of 10 emotional intensity labels is also available. Data has been partitioned into equal training, validation, and test sets, and the test set is blind. <strong>Emotion Labels: </strong><br> <em>Awe, Excitement, Amusement, Awkwardness, Fear, Horror, Distress, Triumph, Sadness, Surprise</em><br> <br>
DOI: 10.5281/zenodo.6171790
title: The Hume Vocal Burst Competition Dataset (H-VB) | Raw Data [ExVo: updated 02.28.22]

description: This package includes the raw data for a subset of the Hume Vocal Burst (Hume-VB) dataset used for the ExVo 2022 Competition.<br> <br> <strong>The competition is now over</strong>, please fill out this form to request access to the full Hume VB dataset. More information on the competition and dataset can be found in the competition white paper.<br> -- <br> This dataset contains <strong>59,201 audio recordings of vocal bursts from 1,702 speakers</strong>, from 4 cultures, the <strong>U.S.A, South Africa, China, </strong>and<strong> Venezuela</strong>, ranging in age from <strong>20 to 39.5 years old</strong>. The total duration of data in this version of <strong>Hume-VB is 36 Hours </strong> (Mean: 02.23 sec). A subset of 10 emotional intensity labels is also available. Data has been partitioned into equal training, validation, and test sets, and the test set is blind. <strong>Emotion Labels: </strong><br> <em>Awe, Excitement, Amusement, Awkwardness, Fear, Horror, Distress, Triumph, Sadness, Surprise</em><br> <br>
DOI: 10.5281/zenodo.6709790
title: Data for RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks

description: Data for RAPPPID, a method for the Regularised Automative Prediction of Protein-Protein Interactions using Deep Learning. These datasets are in a format that RAPPPID is ready to read.<br> <br> <strong>Comparatives Dataset</strong><br> These datasets were derived from the STRING v11 <em>H. sapiens</em> dataset, according to the C1, C2, and C3 procedures outlined by Park and Marcotte, 2012. Negative samples are sampled randomly from the space of proteins not known to interact. See Szymborski & Emad for details.<br> <br> <strong>Repeatability Datasets</strong><br> The following datasets are all derived from STRING in the manner as the comparatives dataset, but three different random seeds are used for drawing proteins.<br> <br> <strong>References</strong><br> Park,Y. and Marcotte,E.M. (2012) Flaws in evaluation schemes for pair-input computational predictions. Nat Methods, 9, 1134–1136. Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., Jensen, L. J., and Mering, C. (2019). String v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613.<br> <br> Szymborski,J. and Emad,A. (2021) RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks. bioRxiv https://doi.org/10.1101/2021.08.13.456309
DOI: 10.5281/zenodo.6709789
title: Data for RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks

description: Data for RAPPPID, a method for the Regularised Automative Prediction of Protein-Protein Interactions using Deep Learning. These datasets are in a format that RAPPPID is ready to read.<br> <br> <strong>Comparatives Dataset</strong><br> These datasets were derived from the STRING v11 <em>H. sapiens</em> dataset, according to the C1, C2, and C3 procedures outlined by Park and Marcotte, 2012. Negative samples are sampled randomly from the space of proteins not known to interact. See Szymborski & Emad for details.<br> <br> <strong>Repeatability Datasets</strong><br> The following datasets are all derived from STRING in the manner as the comparatives dataset, but three different random seeds are used for drawing proteins.<br> <br> <strong>References</strong><br> Park,Y. and Marcotte,E.M. (2012) Flaws in evaluation schemes for pair-input computational predictions. Nat Methods, 9, 1134–1136. Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., Jensen, L. J., and Mering, C. (2019). String v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613.<br> <br> Szymborski,J. and Emad,A. (2021) RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks. bioRxiv https://doi.org/10.1101/2021.08.13.456309
DOI: 10.6084/m9.figshare.20137259
title: Charite_05/2019_3T_fMRI

description: Ultrafast single-slice fMRI acquisition of a single coronal slice.
DOI: 10.6084/m9.figshare.20137259.v1
title: Charite_05/2019_3T_fMRI

description: Ultrafast single-slice fMRI acquisition of a single coronal slice.
DOI: 10.6084/m9.figshare.13570562
title: Infant Emotional Mimicry of Strangers_Database.sav

description: One hundred and seventeen parent-infant dyads (51 six-month-olds, 66 twelve-month-olds) were observed during dynamic video presentation of strangers’ happy, sad, angry, and fearful faces. Infant and parent emotional mimicry (i.e., facial expressions valence-congruent to the video) and their mutual attention (i.e., simultaneous gaze at one another) were systematically coded second-by-second. Parent empathy was assessed via self-report. <br>
DOI: 10.6084/m9.figshare.13570562.v3
title: Infant Emotional Mimicry of Strangers_Database.sav

description: One hundred and seventeen parent-infant dyads (51 six-month-olds, 66 twelve-month-olds) were observed during dynamic video presentation of strangers’ happy, sad, angry, and fearful faces. Infant and parent emotional mimicry (i.e., facial expressions valence-congruent to the video) and their mutual attention (i.e., simultaneous gaze at one another) were systematically coded second-by-second. Parent empathy was assessed via self-report. <br>
DOI: 10.6084/m9.figshare.13570562.v2
title: Infant Emotional Mimicry of Strangers_Database.sav

description: One hundred and seventeen parent-infant dyads (51 six-month-olds, 66 twelve-month-olds) were observed during dynamic video presentation of strangers’ happy, sad, angry, and fearful faces. Infant and parent emotional mimicry (i.e., facial expressions valence-congruent to the video) and their mutual attention (i.e., simultaneous gaze at one another) were systematically coded second-by-second. Parent empathy was assessed via self-report. <br>
DOI: 10.25612/837.l3mzeyg0m0v4
title: Solar Panels

description: Residential and Business Solar Panels in the Houston Area.
DOI: 10.6084/m9.figshare.20137313.v1
title: Does the position of the third molar have an influence on the location of mandibular fractures

description: Joao supplementary file 1 Revised. This is supplementary material from the article entitled "Does the position of the third molar have an influence on the location of mandibular fractures?"
DOI: 10.5517/ccdc.csd.cc28qkm6
title: CCDC 2107058: Experimental Crystal Structure Determination

description: Related Article: Xue‐Rui Tian, Xiao‐Lei Jiang, Sheng‐Li Hou, Zhuo‐Hao Jiao, Jie Han, Bin Zhao|2022|Angew.Chem.,Int.Ed.|61|e202200123|doi:10.1002/anie.202200123
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.cc28qksc
title: CCDC 2107063: Experimental Crystal Structure Determination

description: Related Article: Xue‐Rui Tian, Xiao‐Lei Jiang, Sheng‐Li Hou, Zhuo‐Hao Jiao, Jie Han, Bin Zhao|2022|Angew.Chem.,Int.Ed.|61|e202200123|doi:10.1002/anie.202200123
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: 10.7298/c883-s773
title: Data from: An in silico-in vitro pipeline for drug cardiotoxicity screening identifies ionic proarrhythmia mechanisms
DOI: 10.6084/m9.figshare.20132678.v2
title: primary ATRT RNA-seq: matrix of raw counts

description: Matrix of raw counts of RNA-seq data from 49 primary ATRT samples were generated using an in-house pipeline developed at the Institut Curie Bioinformatics Core Facility (available at https://github.com/bioinfo-pf-curie/RNA-seq) and the human reference genome hg19. Except, the first column which contains the gene name, columns correspond to samples and named by the patient ID.
DOI: 10.6084/m9.figshare.20137427
title: The Body Adiposity Index is Not Applicable to the Brazilian Adult Population

description: <strong>Background</strong>: Obesity is a serious disease that burdens public health systems around the world. It is a risk factor for the development of several non-communicable chronic diseases that are related to the amount and distribution of body fat. Body composition assessment using simple and low-cost techniques can help in the early detection of excess fat, allowing for the prevention and treatment of both obesity and associated diseases. Thus, identifying and proposing valid anthropometric indices for this purpose can be a great ally of health programs. <strong>Objective</strong>: To verify the validity of the Body Adiposity Index (BAI) in relation to Dual Energy X-Ray Absorptiometry (DXA) for estimating body fat percentage in Brazilian adults, as well as proposing a new mathematical model to estimate the fat-free mass of this population. <strong>Methods</strong>: In a cross-sectional study, 424 subjects (220 women), aged between 20 and 59 years, were evaluated by BAI and DXA, then randomly divided subjects into two groups stratified by sex: the development group (n = 283) and cross-validation group (n = 141). Statistical analyses to test the validity of BAI as a predictor of fat mass, in addition to proposing a new mathematical model for estimating fat-free mass, using DXA as a reference method. Analysis included paired-t test, stepwise multiple regression, coefficient of concordance correlation and Bland-Altman plots. <strong>Results</strong>: The BAI validity analysis showed a low correlation coefficient of agreement [CCC = 0.626; ρ (precision) = 0.795; Cb(accuracy) = 0.787]; in addition, the mean difference in the Bland-Altman plot was different from zero in the cross-validation group (p &lt; 0.01) and limits of agreement (LOA) ranged between -8.0 and 14.4 kg, indicating a poor agreement between the BAI and the reference method. The new mathematical model for estimating FFM showed a high correlation coefficient of agreement (CCC = 0.952; ρ = 0.953; Cb = 0.999), in addition to acceptable LOA in the Bland-Altman plot (-6.7 and 6.7). <strong>Conclusion</strong>: In the studied sample, the BAI showed low validity for estimating body fat, while the new proposed model was found to be a good option to assess the body composition of Brazilian adults.
DOI: 10.6084/m9.figshare.20137427.v1
title: The Body Adiposity Index is Not Applicable to the Brazilian Adult Population

description: <strong>Background</strong>: Obesity is a serious disease that burdens public health systems around the world. It is a risk factor for the development of several non-communicable chronic diseases that are related to the amount and distribution of body fat. Body composition assessment using simple and low-cost techniques can help in the early detection of excess fat, allowing for the prevention and treatment of both obesity and associated diseases. Thus, identifying and proposing valid anthropometric indices for this purpose can be a great ally of health programs. <strong>Objective</strong>: To verify the validity of the Body Adiposity Index (BAI) in relation to Dual Energy X-Ray Absorptiometry (DXA) for estimating body fat percentage in Brazilian adults, as well as proposing a new mathematical model to estimate the fat-free mass of this population. <strong>Methods</strong>: In a cross-sectional study, 424 subjects (220 women), aged between 20 and 59 years, were evaluated by BAI and DXA, then randomly divided subjects into two groups stratified by sex: the development group (n = 283) and cross-validation group (n = 141). Statistical analyses to test the validity of BAI as a predictor of fat mass, in addition to proposing a new mathematical model for estimating fat-free mass, using DXA as a reference method. Analysis included paired-t test, stepwise multiple regression, coefficient of concordance correlation and Bland-Altman plots. <strong>Results</strong>: The BAI validity analysis showed a low correlation coefficient of agreement [CCC = 0.626; ρ (precision) = 0.795; Cb(accuracy) = 0.787]; in addition, the mean difference in the Bland-Altman plot was different from zero in the cross-validation group (p &lt; 0.01) and limits of agreement (LOA) ranged between -8.0 and 14.4 kg, indicating a poor agreement between the BAI and the reference method. The new mathematical model for estimating FFM showed a high correlation coefficient of agreement (CCC = 0.952; ρ = 0.953; Cb = 0.999), in addition to acceptable LOA in the Bland-Altman plot (-6.7 and 6.7). <strong>Conclusion</strong>: In the studied sample, the BAI showed low validity for estimating body fat, while the new proposed model was found to be a good option to assess the body composition of Brazilian adults.