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VAMDC extraction with identifier = 6609d3b9-0ecd-4cda-9693-8aed0f044d7c
<div>This is a dataset extracted from http://vald.astro.uu.se/atoms-12.07/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( IonCharge = '1' ) </div><div> Data source version: 2018-04-04</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 6609d3b9-0ecd-4cda-9693-8aed0f044d7c</div>
Deprecated - VAMDC extraction with query token = tipbase:ccfb5ac9-82d6-4ab2-9ec0-3aa8051a32c1:head
<p>Deprecated because the file upload was corrupted.</p> <p>This dataset comes from the VAMDC(Virtual Atomic and Molecular Data Center) node named http://tipbase.obspm.fr/12.07/vamdc/tap/ by doing these queries: (query=select * where ( atomsymbol = 'fe' ); ) . The corresponding dataset is versioned on 2017-01-30 with the XSAMS 12.07 format. This data is associated with a unique identifier uuid=a9a38253-7788-496f-b12c-b5c44751535f. Bibliographic references are: N.N. (2018). Storey, P. J. and Zeippen, C. J. and Le Dourneuf, M. (2002). Atomic data from the IRON Project. LI. Electron impact excitation of Fe IX. Astronomy and Astrophysics. Butler, K. and Zeippen, C. J. (2001). Atomic data from the IRON Project. L. Electron impact excitation of Fe xix. Astronomy and Astrophysics. Butler, K. and Zeippen, C. J. (2001). Atomic data from the IRON Project. XLIX. Electron impact excitation of Fexx. Astronomy and Astrophysics. Pelan, J. C. and Berrington, K. A. (2001). Atomic data from the IRON project. XLVI. Electron excitation of 3s3p6 and 3s23p43d fine-structure transitions in Fe x. Astronomy and Astrophysics. Chen, Guo Xin and Pradhan, Anil K. (2000). Atomic data from the Iron Project. XLIV. Transition probabilities and line ratios for Fe VI with fluorescent excitation in planetary nebulae. Astronomy and Astrophysics Supplement Series. Chidichimo, M. C. and Zeman, V. and Tully, J. A. and Berrington, K. A. (2000). Erratum: Atomic Data from the IRON Project. Astronomy and Astrophysics Supplement Series. Storey, P. J. and Mason, H. E. and Young, P. R. (2000). Atomic data from the IRON Project. XL. Electron impact excitation of the Fe XIV EUV transitions. Astronomy and Astrophysics Supplement Series. Chidichimo, M. C. and Zeman, V. and Tully, J. A. and Berrington, K. A. (1999). Atomic data from the IRON Project. XXXVI. Electron excitation of Be-like Fe XXIII between 1s(2 2l_1 2l_2 SLJ) and 1s(2 2l_3 2l_4 S'L'J'). Astronomy and Astrophysics Supplement Series. Eissner, W. and Galavis, M. E. and Mendoza, C. and Zeippen, C. J. (1999). Atomic data from the IRON Project. XXXVIII. Electron impact excitation of the fine-structure transitions in the n=3 complex of Fe XV. Astronomy and Astrophysics Supplement Series. Chen, G. X. and Pradhan, A. K. (1999). Atomic data from the Iron Project. XXXVII. Electron impact excitation collision strengths and rate coefficients for Fe VI. Astronomy and Astrophysics Supplement Series. Eissner, W. and Galavis, M. E. and Mendoza, C. and Zeippen, C. J. (1999). Atomic data from the IRON Project. XXXIV. Electron impact excitation of Fe XVI. Astronomy and Astrophysics Supplement Series. Nahar, S. N. and Pradhan, A. K. (1999). Atomic data from the Iron Project. XXXV. Relativistic fine structure oscillator strengths for Fe XXIV and Fe XXV. Astronomy and Astrophysics Supplement Series. Galavis, M. E. and Mendoza, C. and Zeippen, C. J. (1998). Atomic data from the IRON Project. XXXII. On the accuracy of the effective collision strength for the electron impact excitation of the quadrupole transition in AR III. Astronomy and Astrophysics Supplement Series. Binello, A. M. and Mason, H. E. and Storey, P. J. (1998). Atomic data from the IRON project. XXXI. Electron impact excitation of optically allowed and intercombination electric dipole transitions in Fe XII. Astronomy and Astrophysics Supplement Series. Berrington, K. A. and Saraph, H. E. and Tully, J. A. (1998). Atomic data from the IRON Project. XXVIII. Electron excitation of the ^2P_(3/2) deg -> ^2P_(1/2) deg fine structure transition in fluorine-like ions at higher temperatures. Astronomy and Astrophysics Supplement Series. Binello, A. M. and Mason, H. E. and Storey, P. J. (1998). Atomic data from the IRON Project. XXV. Electron impact excitation of fine-structure transitions in the ground configuration of Fe XII. Astronomy and Astrophysics Supplement Series. Zhang, H. L. and Pradhan, A. K. (1997). Atomic data from the Iron Project. XXVII. Electron impact excitation collision strengths and rate coefficients for Fe IV. Astronomy and Astrophysics Supplement Series. Berrington, K. A. and Tully, J. A. (1997). Atomic data from the IRON Project. XXIV. Electron excitation of Li-like Fe XXIV between the N = 2 and n' = 2, 3, 4 fine-structure levels. Astronomy and Astrophysics Supplement Series. Zhang, H. L. and Pradhan, A. K. (1997). Atomic data from the IRON Project. XXIII. Relativistic excitation rate coefficients for Fe XXII with inclusion of radiation damping. Astronomy and Astrophysics Supplement Series. Zhang, H. (1996). Atomic data from the Iron Project. XVIII. Electron impact excitation collision strengths and rate coefficients for Fe III.. Astronomy and Astrophysics Supplement Series. Berrington, K. A. and Pelan, J. (1996). Erratum: "Atomic data from the IRON Project. XII. Electron excitation of forbidden transitions in V-like ions Mn III, Fe IV, Co V and Ni VI" [Astron. Astrophys., Suppl. Ser., Vol. 114, No. 2, p. 367 - 371 (Dec 1995)].. Astronomy and Astrophysics Supplement Series. Storey, P. J. and Mason, H. E. and Saraph, H. E. (1996). Atomic data from the IRON Project. XIV. Electron impact excitation of the Fe XIV fine-structure transition ^2^P^o^_1/2_-^2^P^o^_3/2_. Astronomy and Astrophysics. Bautista, M. A. and Pradhan, A. K. (1996). Atomic data from the Iron project. XIII. Electron excitation rates and emissivity ratios for forbidden transitions in NI II and Fe II.. Astronomy and Astrophysics Supplement Series. Berrington, K. A. and Pelan, J. C. (1995). Atomic data from the IRON Project. XII. Electron excitation of forbidden transitions in V-like ions MN III, Fe IV, CO V and NI VI.. Astronomy and Astrophysics Supplement Series. Galavis, M. E. and Mendoza, C. and Zeippen, C. J. (1995). Atomic data from the IRON Project. X. Effective collision strengths for infrared transitions in silicon- and sulphur-like ions.. Astronomy and Astrophysics Supplement Series. Pelan, J. and Berrington, K. A. (1995). Atomic data from the IRON Project. IX. Electron excitation of the ^2^P^0^_3/2_-^2^P^0^_1/2_ fine-structure transition in chlorine-like ions, from AR II to NI XII.. Astronomy and Astrophysics Supplement Series. Berrington, K. A. (1995). Atomic data from the IRON Project. VIII. Electron excitation of the 3d^4^ ^5^D_J_ ground state fine-structure transitions in Ti-like ions V II, CR III, MN IV, Fe V, CO VI and NI VII.. Astronomy and Astrophysics Supplement Series. Zhang, H. L. and Pradhan, A. K. (1995). Atomic data from the Iron Project. VI. Collision strengths and rate coefficients for Fe II.. Astronomy and Astrophysics. Edlen, Bengt (1983). Comparison of Theoretical and Experimental Level Values of the n = 2 Configurations in the Boron Isoelectronic Sequence. Physica Scripta. Jupen, C. and Isler, R. C. and Trabert, E. (1993). Solar Identifications of Fex-Fexiv Based on Comparison with Beam-Foil Tokamak and Laser-Produced Plasma Spectra. Monthly Notices of the Royal Astronomical Society. Shirai T. and Sugar J. and Musgrove (2000). Spectral Data for Highly Ionized Atoms: TI, V, Cr, Mn, Fe, Ni, Cu, Kr, and Mo. Journal of Physical and Chemical Reference Data monograph 8. Shirai T. and Sugar J. and Musgrove (1985). Atomic Energy Levels of the Iron Period Elements: Potassium through Nickel. J. Phys. Chem. Ref. Data 14, Supplement No. 2. Reader, Joseph and Sugar, Jack and Acquista, Nicolo and Bahr, Raymond (1994). Laser-produced and tokamak spectra of lithiumlike iron, Fe23 +. Journal of the Optical Society of America B: Optical Physics. Ballance, C. P. and Badnell, N. R. and Berrington, K. A. (2002). Electron-impact excitation of H-like Fe at high temperatures. Journal of Physics B Atomic Molecular Physics. Ekberg, J. O. (1981). Term Analysis of Fe VII. Physica Scripta. Churilov, S. S. and Levashov, V. E. (1993). The 3p23d and 3s3d2 configurations in aluminium-like KV VII-Ni XVI. Physica Scripta. Churilov, S. S. and Levashov, V. E. and Wyart, J. F. (1989). Extended analysis of the 3d2-3p3d transitions in the sequence K VIII-Cu XVIII and isoelectronic trends in Mg-like ions through Kr XXV. Physica Scripta. Churilov, S. S. and Kononov, E. Ya and Ryabtsev, A. N. and Zayikin, Yu F. (1985). A Detailed Analysis of the n=3 - n'=3 Transitions in the Mg-like Ions FeXV, CoXVI and NiXVII. Physica Scripta. Whiteford, A. D. and Badnell, N. R. and Ballance, C. P. and O'Mullane, M. G. and Summers, H. P. and Thomas, A. L. (2001). A radiation-damped <strong>R</strong>-matrix approach to the electron-impact excitation of helium-like ions for diagnostic application to fusion and astrophysical plasmas. Journal of Physics B Atomic Molecular Physics. Redfors, Andreas and Litzèn, Ulf (1989). Extended analysis of spectra and term systems in aluminumlike Ca viii-Ni xvi. Journal of the Optical Society of America B Optical Physics. Redfors, Andreas (1988). The 3d2 configuration in Ca IX-Zn XIX. Physica Scripta. Litzèn, Ulf and Redfors, Andreas (1987). Revised and extended analysis of transitions and energy levels in the n = 3 complex of Mg-like Ca IX-Ge XXI. Physica Scripta.</p>
VAMDC extraction with identifier = 17053a9a-e56e-451b-9bd2-8e0cddda0d5d
<div>This is a dataset extracted from http://stark-b.obspm.fr/12.07/vamdc/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( atomsymbol = 'li' and ioncharge = 0 ); </div><div> Data source version: 2017-06-23</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 17053a9a-e56e-451b-9bd2-8e0cddda0d5d</div>
VAMDC extraction with identifier = 9ca8e9a9-b6d7-4f5e-a510-13cb8bf4b759
<div>This is a dataset extracted from http://vamdc.icb.cnrs.fr/mecasda-12.07/tap/ VAMDC node.</div><div>Query originating this dataset: query=select species; </div><div> Data source version: 1</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 9ca8e9a9-b6d7-4f5e-a510-13cb8bf4b759</div>
VAMDC extraction with identifier = 955c9268-d40a-4427-9bea-7b715f978769
<div>This is a dataset extracted from http://vald.astro.uu.se/atoms-12.07/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( atomsymbol = 'he' and radtranswavelength < 600 and radtranswavelength > 500 ); </div><div> Data source version: 2018-04-04</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 955c9268-d40a-4427-9bea-7b715f978769</div>
Extracted Heuristics for SoS Design
<p>Extracted Heuristics for SoS Design</p>
Extracted SoS heuristics
<p>Extracted SoS Heuristics</p>
Extraction Forms about Challenges and Problems of Software Processes in the Context of Global Software Development: A Systematic Mapping Study
<p>Extraction Forms of the Systematic Mapping Study about Challenges and Problems of Software Processes in the Context of Global Software Development. 50 papers were analized.</p>
Dataset and code for 'AI-based Knowledge Extraction from the Bioprinting Literature for identifying technology trends'
<p>Zip file containing the dataset and code for the paper 'AI-based Knowledge Extraction from the Bioprinting Literature for identifying technology trends'. The dataset is composed of:</p> <ul> <li>A train_data.csv file, containing all annotated keywords used for classifier training.</li> <li>A filt_ls.pkl file, containing the sentences used to train the embeddings model.</li> <li>A train.py file, to train the composite keyword annotation model.</li> </ul> <p>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.</p>
Seismic attenuation extraction from traffic signals recorded by a single seismic station (2/3)
<p>This repository contains the raw field data and corresponding codes for the West Coast Highway site in the manuscript entitled "Seismic attenuation extraction from traffic signals recorded by a single seismic station " by Yumin Zhao, Enhedelihai Nilot, Bei Li, Yunyue Elita Li, and Gang Fang. </p>
Seismic attenuation extraction from traffic signals recorded by a single seismic station (1/3)
<p>This repository contains the raw field data and corresponding codes for the NUS exit site in the manuscript entitled "Seismic attenuation extraction from traffic signals recorded by a single seismic station " by Yumin Zhao, Enhedelihai Nilot, Bei Li, Yunyue Elita Li, and Gang Fang. </p>
An ArcGIS Pro workflow to extract vegetation indices from aerial imagery of small‐plot turfgrass research
<p>Collection of multispectral imagery from an aerial sensor is a means to obtain plot-level vegetation index (VI) values; however, post-capture image processing and analysis remain a challenge for small-plot researchers. An ArcGIS Pro workflow of two task items was developed with established routines and commands to extract plot-level VI values (Normalized Difference VI, Ratio VI, and Chlorophyll Index-Red Edge) from multispectral aerial imagery of small-plot turfgrass experiments. Users can access and download task item(s) from the ArcGIS Online platform for use in ArcGIS Pro. The workflow standardizes the processing of aerial imagery to ensure repeatability between sampling dates and across site locations. A guided workflow saves time with assigned commands, ultimately allowing users to obtain a table with plot descriptions and index values within a .csv file for statistical analysis. The workflow was used to analyze aerial imagery from a small-plot turfgrass research study evaluating herbicide effects on St. Augustinegrass [<em>Stenotaphrum secundatum</em> (Walt.) Kuntze] grow-in. To compare methods, index values were extracted from the same aerial imagery by TurfScout, LLC and were obtained by handheld sensor. Index values from the three methods were correlated with visual percentage cover to determine the sensitivity (i.e., the ability to detect differences) of the different methodologies.</p>
Evaluation of SPIRES on Chemical-Disease-Relation extraction task 2023-01
<p>SPIRES CDR evaluation results.</p> <p>See https://github.com/monarch-initiative/ontogpt</p>
Extraction of Crossref datadump for benchmarking purpose (small version)
<p> Several aggregation of Crossref datadump to amplify the size for benchmarking purpose.</p>
Dataset of research about Potential of Purwoceng Extract (Pimpinella pruatjan Molkenb.) as Anti-Nicotine Therapy against Viability, Spermatozoa Membrane Integrity, and Organogenesis
<p>The dataset included:</p> <p>1. Ethical test certificate</p> <p>2. Description of ethical clearance</p> <p>3. List of figures of tools and goods used for this study</p> <p>4. Result of active ingredient purwoceng test certificates</p> <p>5. Results of Observation of Viability and Integrity of Spermatozoa Membranes appendices</p>
Training and test dataset for CNN-LSTM model for GW waveform extraction
<p>This repository contains training and test samples corresponding to the paper, 'Extraction of binary black hole gravitational wave signals from detector data using deep learning', Chatterjee et al., Phys. Rev. D <strong>104</strong>, 064046 (2021).</p>
Graph of the dependence of the pH of the aqueous extract of the leather tissue of sheepskins in the canning process
<p>Graph of the dependence of the pH of the aqueous extract of the leather tissue of sheepskins in the canning process</p>
Amery Ice Shelf Grounding Line Datapoints Extraction from Airborne Ice-penetrating Radar
<p>We present a new grounding line product for Amery Ice Shelf - the ice-penetrating radar-derived grounding line points. The 137 grounding line points were identified by 53 survey lines from 2017 to 2020 and classified into three categories. The 'Class 1' points are extracted by significant echo reflection changes between ice-bed and ice-seawater interfaces along survey lines with continuous signal and have the highest accuracy. The 'Class2' and 'Class 3' points were derived from survey lines with 'fuzzy region' with lower accuracy. The mean interval of radar-derived points is 16.4 km. The 'best case' radar-derived positions (Class 1) and those from satellite data reveals a mean separation of 1.00±1.16 km. Two products are available: (1) ice thickness data of Amery Ice Shelf from ice-penetrating radar lines; (2) radar-derived grounding line position (137 points). The ice thickness was calculated by ice surface and bottom signal and the unit is m. The radar-derived grounding line position have six fields, latitude, longitude, id, ice thickness, date (for collecting the radar data) and Class (the category of point).</p>
Our processed LoveDA dataset for "LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing Images"
<p>Our processed LoveDA dataset is used for the paper "<a href="https://doi.org/10.7717/peerj-cs.1467">LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing Images</a>"</p>
Our processed CITY_OSM dataset for "LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing Images"
<p>Our processed CITY_OSM dataset is used for the paper "<a href="https://doi.org/10.7717/peerj-cs.1467">LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing Images</a>".</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.