cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7689627
title: CancerMine

description: This describes the output files for the CancerMine project. These files are loaded directly by the CancerMine viewer. The code for this viewer is available in the CancerMine Github repo if you want to run it independently. Each file is a tab-delimited file with a header, no comments and no quoting. You likely want <strong>cancermine_collated.tsv</strong> if you just want the list of cancer gene roles. If you want the supporting sentences, look at <strong>cancermine_sentences.tsv</strong>. You can use the <em>matching_id</em> column to connect the two files. If you want to dig further and are okay with a higher false positive rate, look at <strong>cancermine_unfiltered.tsv</strong>. <strong>cancermine_collated.tsv:</strong> This contains the cancer gene roles with citation counts supporting them. It contains the normalized cancer and gene names along with IDs for HUGO, Entrez Gene and the Disease Ontology. <strong>cancermine_sentences.tsv:</strong> This contains the supporting sentences for the cancer gene roles in the collated file. Each row is a single supporting sentence for one cancer gene role. This file contains information on the source publication (e.g. journal, publication date, etc), the actual sentence and the cancer gene role extracted. <strong>cancermine_unfiltered.tsv:</strong> This is the raw output of the applyModelsToSentences.py script across all of PubMed, Pubmed Central Open Access and PubMed Central Author Manuscript Collection. It contains every predicted relation with a prediction score above 0.5. So this may contain many false positives. Each row contain information on the publication (e.g. journal, publication date, etc) along with the sentence and the specific cancer gene role extracted (with HUGO, Entrez Gene and Disease Ontology IDs). This file is further processed to create the other two.
DOI: 10.5281/zenodo.7686542
title: Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound - Elastic Wave Simulations (Closed Scanning Paths)

description: <strong>Elastic Wave Simulations - Closed Scanning Paths</strong> This dataset is part of a larger repository (DOI: 10.5281/zenodo.5248082) which houses links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" (Reardon et al., 2023). If you use these simulated data please cite our publication (http://www.science.org/doi/10.1126/sciadv.adf2037) and the software package k-Wave (DOI: 10.1109/ULTSYM.2014.0037). This dataset contains the normal shear surface velocity in a cylindrical slab of tissue-like material excited by an acoustic source with a Gaussian spatial profile simulated via a pseudo-spectral numerical method. The data is provided as .mat files. The files are separated by the type of scanning path, the scanning speed of the acoustic source, and the parameters of the scanning path. Details of the simulation parameters can be found in our publication. <strong>Circle Paths</strong> - The acoustic source was scanned at a constant linear speed along a circular trajectories with two different diameters - 1 cm and 3 cm (indicated in the filename) and for at least 2 pattern repetitions. The linear scanning speed ranged from 2 to 20 m/s and is designated in the filename. <strong>Square Paths</strong> - The acoustic source was scanned at a constant speed along square trajectories with two different edge lengths - 1 cm and 3 cm (indicated in the filename) and for at least 2 pattern repetitions. The scan speed ranged from 2 m/s to 10 m/s and is designated in the filename. <strong>Data Fields</strong> <strong>surfaceData</strong> (NxNxM) - 3D array containing the normal shear velocity of the simulated medium (in m/s) on a NxN Cartesian grid of locations at M timepoints. The simulated tissue medium was cylindrical, so locations outside the circular top surface are NaN <strong>sourceSignals</strong> (NxNxQ) - 3D array containing the acoustic source distribution on the NxN Cartesian grid of locations used to excite the surface of the simulated tissue medium for Q timepoints <strong>sourceEnvelope</strong> (Qx1) - Vector containing the amplitude envelope that was applied to sourceSignals at each timestep <strong>nCycles</strong> - Number of pattern repetitions <strong>dt</strong> - The time between adjacent timepoints in seconds (i.e. fs = 1/dt) <strong>dx/dy</strong> - The distance between adjacent grid locations in the x/y direction of the Cartesian grid (in m)
DOI: 10.5281/zenodo.7686541
title: Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound - Elastic Wave Simulations (Closed Scanning Paths)

description: <strong>Elastic Wave Simulations - Closed Scanning Paths</strong> This dataset is part of a larger repository (DOI: 10.5281/zenodo.5248082) which houses links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" (Reardon et al., 2023). If you use these simulated data please cite our publication (http://www.science.org/doi/10.1126/sciadv.adf2037) and the software package k-Wave (DOI: 10.1109/ULTSYM.2014.0037). This dataset contains the normal shear surface velocity in a cylindrical slab of tissue-like material excited by an acoustic source with a Gaussian spatial profile simulated via a pseudo-spectral numerical method. The data is provided as .mat files. The files are separated by the type of scanning path, the scanning speed of the acoustic source, and the parameters of the scanning path. Details of the simulation parameters can be found in our publication. <strong>Circle Paths</strong> - The acoustic source was scanned at a constant linear speed along a circular trajectories with two different diameters - 1 cm and 3 cm (indicated in the filename) and for at least 2 pattern repetitions. The linear scanning speed ranged from 2 to 20 m/s and is designated in the filename. <strong>Square Paths</strong> - The acoustic source was scanned at a constant speed along square trajectories with two different edge lengths - 1 cm and 3 cm (indicated in the filename) and for at least 2 pattern repetitions. The scan speed ranged from 2 m/s to 10 m/s and is designated in the filename. <strong>Data Fields</strong> <strong>surfaceData</strong> (NxNxM) - 3D array containing the normal shear velocity of the simulated medium (in m/s) on a NxN Cartesian grid of locations at M timepoints. The simulated tissue medium was cylindrical, so locations outside the circular top surface are NaN <strong>sourceSignals</strong> (NxNxQ) - 3D array containing the acoustic source distribution on the NxN Cartesian grid of locations used to excite the surface of the simulated tissue medium for Q timepoints <strong>sourceEnvelope</strong> (Qx1) - Vector containing the amplitude envelope that was applied to sourceSignals at each timestep <strong>nCycles</strong> - Number of pattern repetitions <strong>dt</strong> - The time between adjacent timepoints in seconds (i.e. fs = 1/dt) <strong>dx/dy</strong> - The distance between adjacent grid locations in the x/y direction of the Cartesian grid (in m)
DOI: 10.34740/kaggle/dsv/5089860
title: Nigerian Presidential Election 2023 Tweets
DOI: 10.5281/zenodo.7689509
title: Synthetic Nodules for Evaluation of 3D Deep Learning Segmentation Attribution

description: Both the algorithm used to generate this dataset as well as the comprehensive evaluation metric for visual explanations are detailed in the paper "Attribution of 3D Deep Learning Segmentation in Medical Imaging". This is a synthetic dataset developed to enable the comprehensive evaluation of visual explanation methods applied to deep learning segmentation predictions. The data provided here include 100 training and 100 testing volumes, binary segmentation labels for model training, and explanation segmentation labels for explanation evaluation. The intended workflow for this dataset is: 1) Train a deep learning segmentation model using the 100 training volumes and binary segmentation labels. 2) Use a method of visual explanation to explain the trained model's segmentation decisions on the 100 testing volumes. 3) Use the explanation labels to evaluate the generated explanations. The folders <em>imagesTr</em> and <em>imagesTs</em> contain the training and testing image volumes, respectively. A <em>dataset.json</em> file has also been generated for the images to enable training using the nnUNet pipeline. The folders <em>labelsTr</em> and <em>labelsTs</em> contain the training and testing binary segmentation labels. In both cases, 1 indicates foreground voxels (spiculated nodule) and 0 indicates background voxels. The folders <em>labelsTr_full</em> and <em>labelsTs_full</em> contain the training and testing explanation labels. In both cases, 1 indicates non-spiculated nodule, 2 indicates spiculation structure (discriminating background), 3 indicates spiculated nodule body (segmentation foreground), and 0 indicates background.
DOI: 10.5281/zenodo.7689508
title: Synthetic Nodules for Evaluation of 3D Deep Learning Segmentation Attribution

description: Both the algorithm used to generate this dataset as well as the comprehensive evaluation metric for visual explanations are detailed in the paper "Attribution of 3D Deep Learning Segmentation in Medical Imaging". This is a synthetic dataset developed to enable the comprehensive evaluation of visual explanation methods applied to deep learning segmentation predictions. The data provided here include 100 training and 100 testing volumes, binary segmentation labels for model training, and explanation segmentation labels for explanation evaluation. The intended workflow for this dataset is: 1) Train a deep learning segmentation model using the 100 training volumes and binary segmentation labels. 2) Use a method of visual explanation to explain the trained model's segmentation decisions on the 100 testing volumes. 3) Use the explanation labels to evaluate the generated explanations. The folders <em>imagesTr</em> and <em>imagesTs</em> contain the training and testing image volumes, respectively. A <em>dataset.json</em> file has also been generated for the images to enable training using the nnUNet pipeline. The folders <em>labelsTr</em> and <em>labelsTs</em> contain the training and testing binary segmentation labels. In both cases, 1 indicates foreground voxels (spiculated nodule) and 0 indicates background voxels. The folders <em>labelsTr_full</em> and <em>labelsTs_full</em> contain the training and testing explanation labels. In both cases, 1 indicates non-spiculated nodule, 2 indicates spiculation structure (discriminating background), 3 indicates spiculated nodule body (segmentation foreground), and 0 indicates background.
DOI: 10.25345/c5q52fp4s
title: MassIVE MSV000091384 - 20230301_LCICPMS_BaarsLab_Scopulariopsis
title: LC separation was performed on a Thermo Dionex Ultimate 3000 UPLC system using an ACE excel 1.7 super C18 2.1 x 100 mm UPLC column with a flow rate of 0.35 mL/min. Solvent A was MilliQ water with 5 mM ammonium formate adjusted to pH 6.5 using ammonium hydroxide. Solvent B was 95:5 ACN:MilliQ water with 5 mM ammonium formate adjusted to pH 6.5 using ammonium hydroxide. Solvent was held at 0% B for 2 minutes and then a gradient of 0 - 100% B over 15 minutes was run and brought back down to 0% B at 15.2 minutes. For each sample, 20 uL of a 1 mg/mL solution was injected. The LC flow was connected to a computer-controlled Thermo iCAP RQ ICPMS controlled by QTEGRA and operating in LC mode for ICP-MS data collection. Additional oxygen gas flow to the inlet was set to 4.50%, cool gas 14.00 L/min, auxiliary gas 0.80 L/min, plasma power 1550.0 W. Plasma exhaust was 0.34 mbar and plasma cooling water flow was 0.68 L/min. The Q-Cell collision gas was 4.708 mL/min. The isotopes chosen for analysis were 48Ti, 55Mn, 57Fe, 56Fe, 59Co, 60Ni, 63Cu, 64Zn, 65Cu, 66Zn, and 95Mo, because these transition metals have been found chelated to microbial ionophores.
DOI: 10.25345/c5kd1qw0n
title: MassIVE MSV000091385 - 20230301_LCMSMS_pairedwithLCICPMS_scopulariopsis
title: High resolution LC-MS/MS data for pooled biological replicates (N=3) was collected on a Bruker compact qTOF in positive mode with the detection window set from 100 - 2000 Da on an ACE excel 1.7 super C18 2.1 x 100 mm UPLC column with a flow rate of 0.35 mL/min. Agilent ESI TOF mix calibrant was injected via divert valve from minute 0.04 to minute 0.30 during the LC run. Solvent A was MilliQ water with 5 mM ammonium formate adjusted to pH 6.5 using ammonium hydroxide. Solvent B was 95.5 ACN:MilliQ water with 5 mM ammonium formate adjusted to pH 6.5 using ammonium hydroxide. Solvent was held at 0% B for 2 minutes and then a gradient of 0 - 100% B over 15 minutes was run and brought back down to 0 % at 15.2 minutes. For each sample, 20 uL of a 1 mg/mL solution was injected. The ESI conditions were set with a capillary voltage at 4.5 kV. For MS/MS, dynamic exclusion was used, and the top nine precursor ions from each MS1 scan were subjected to collision energies scaled according to mass and charge state for a total of nine data dependent MS/MS events per MS1.
DOI: 10.5281/zenodo.7686555
title: Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound - Vibrometry Measurements with Elastomer Plate

description: <strong>Vibrometry Measurements with Elastomer Plate</strong> This dataset is part of a larger repository (DOI: 10.5281/zenodo.5248082) which houses links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" (Reardon et al., 2023). If you use these data please cite our publication (http://www.science.org/doi/10.1126/sciadv.adf2037). This dataset contains the response of a tissue phantom (Gelatin #2, Humimic) to focused ultrasound (UHEV1, Ultrahaptics). The data is provided as .mat files. The files are separated by scanning path (linear and zigzag trajectories) and scanning speed. Details about our experimental procedure can be found in our publication. IMPORTANT - The data provided is the unprocessed output from a laser doppler vibrometer (Ometron, model 8330). The data is NOT time-aligned and must be reconstructed using the reference signal and the map of the measurement locations. <strong>Line Paths</strong> - Focused ultrasound scanned along a linear path on the surface of the tissue phantom at one of 5 speeds - 2 m/s, 4 m/s, 7 m/s, 11 m/s, and 15 m/s. The scanning speed is designated in the filename. <strong>Zigzag Paths</strong> - Focused ultrasound scanned along a zigzag path on the surface of the tissue phantom with longitudinal scanning speed <em>v<sub>l</sub></em> = 3, 5 m/s. At both speeds, the ultrasound focus was modulated transverse to its primary motion direction at a speed, <em>v<sub>mod</sub></em>, of +-2.5 m/s yielding a zigzag path (2 cm path width). The longitudinal scanning speed is designated in the filename. <strong>Data Fields</strong> <strong>y</strong> (MxN) - 2D array containing the tissue phantom velocity normal to the laser doppler vibrometer (in mm/s) for N measurement locations. All repetitions are included as a single time-domain signal of M timepoints <strong>ref</strong> (MxN) - 2D array containing a reference voltage signal taken from the ultrasound phased array. Each of the N measured locations has a reference signal. The beginning of the reference signal identifies the start of a new repetition. <strong>nRepetitions</strong> - Number of stimulus repetitions (reps can be averaged to improve the measurement signal-to-noise ratio). <strong>fs</strong> - Laser doppler vibrometer sampling rate (in Hz) <strong>measurementLocations</strong> (Nx2) - 2D measurement locations on the gelatin surface (x,y; in m) for each of N measurement locations
DOI: 10.5281/zenodo.7686554
title: Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound - Vibrometry Measurements with Elastomer Plate

description: <strong>Vibrometry Measurements with Elastomer Plate</strong> This dataset is part of a larger repository (DOI: 10.5281/zenodo.5248082) which houses links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" (Reardon et al., 2023). If you use these data please cite our publication (http://www.science.org/doi/10.1126/sciadv.adf2037). This dataset contains the response of a tissue phantom (Gelatin #2, Humimic) to focused ultrasound (UHEV1, Ultrahaptics). The data is provided as .mat files. The files are separated by scanning path (linear and zigzag trajectories) and scanning speed. Details about our experimental procedure can be found in our publication. IMPORTANT - The data provided is the unprocessed output from a laser doppler vibrometer (Ometron, model 8330). The data is NOT time-aligned and must be reconstructed using the reference signal and the map of the measurement locations. <strong>Line Paths</strong> - Focused ultrasound scanned along a linear path on the surface of the tissue phantom at one of 5 speeds - 2 m/s, 4 m/s, 7 m/s, 11 m/s, and 15 m/s. The scanning speed is designated in the filename. <strong>Zigzag Paths</strong> - Focused ultrasound scanned along a zigzag path on the surface of the tissue phantom with longitudinal scanning speed <em>v<sub>l</sub></em> = 3, 5 m/s. At both speeds, the ultrasound focus was modulated transverse to its primary motion direction at a speed, <em>v<sub>mod</sub></em>, of +-2.5 m/s yielding a zigzag path (2 cm path width). The longitudinal scanning speed is designated in the filename. <strong>Data Fields</strong> <strong>y</strong> (MxN) - 2D array containing the tissue phantom velocity normal to the laser doppler vibrometer (in mm/s) for N measurement locations. All repetitions are included as a single time-domain signal of M timepoints <strong>ref</strong> (MxN) - 2D array containing a reference voltage signal taken from the ultrasound phased array. Each of the N measured locations has a reference signal. The beginning of the reference signal identifies the start of a new repetition. <strong>nRepetitions</strong> - Number of stimulus repetitions (reps can be averaged to improve the measurement signal-to-noise ratio). <strong>fs</strong> - Laser doppler vibrometer sampling rate (in Hz) <strong>measurementLocations</strong> (Nx2) - 2D measurement locations on the gelatin surface (x,y; in m) for each of N measurement locations
DOI: 10.5517/ccdc.csd.cc2dqk5w
title: CCDC 2226208: Experimental Crystal Structure Determination

description: Related Article: Pengquan Chen, Mei-Jun Lv, Jun Kee Cheng, Shao-Hua Xiang, Xiang-Zhong Ren, Junmin Zhang, Bin Tan|2023|Chemical Science|14|2330|doi:10.1039/D2SC07103G
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.cc2dxkd9
title: CCDC 2231981: Experimental Crystal Structure Determination

description: Related Article: Ludwig Zapf, Melanie Riethmann, Steffen A. Föhrenbacher, Maik Finze, Udo Radius|2023|Chemical Science|14|2275|doi:10.1039/D3SC00037K
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.cc2dzy1d
title: CCDC 2234264: Experimental Crystal Structure Determination

description: Related Article: V. Milašinović, V. Vuković, A. Krawczuk, K. Molčanov, C. Hennig, M. Bodensteiner|2023|IUCrJ|10|156|doi:10.1107/S2052252523000052
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.cc2c4c85
title: CCDC 2178936: Experimental Crystal Structure Determination

description: Related Article: J. Sun, Y. Wang, W. Tang, J. Gong|2023|IUCrJ|10|164|doi:10.1107/S2052252523000118
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.cc2c4d75
title: CCDC 2178966: Experimental Crystal Structure Determination

description: Related Article: J. Sun, Y. Wang, W. Tang, J. Gong|2023|IUCrJ|10|164|doi:10.1107/S2052252523000118
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.cc2cls5y
title: CCDC 2192790: Experimental Crystal Structure Determination

description: Related Article: J. Sun, Y. Wang, W. Tang, J. Gong|2023|IUCrJ|10|164|doi:10.1107/S2052252523000118
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.cc2c4g22
title: CCDC 2179023: Experimental Crystal Structure Determination

description: Related Article: J. Sun, Y. Wang, W. Tang, J. Gong|2023|IUCrJ|10|164|doi:10.1107/S2052252523000118
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.cc2c4d42
title: CCDC 2178963: Experimental Crystal Structure Determination

description: Related Article: J. Sun, Y. Wang, W. Tang, J. Gong|2023|IUCrJ|10|164|doi:10.1107/S2052252523000118
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.cc2c4djg
title: CCDC 2178975: Experimental Crystal Structure Determination

description: Related Article: J. Sun, Y. Wang, W. Tang, J. Gong|2023|IUCrJ|10|164|doi:10.1107/S2052252523000118
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.