cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6356420.v17
title: HELIO4CAST Interplanetary Coronal Mass Ejection Catalog v2.1

description: This is the HELIO4CAST interplanetary coronal mass ejection (ICME) catalog, based on in situ magnetic field and bulk plasma observations in the heliosphere.<b>This is version 2.1, released 2021-November-29, updated 2023-September-1.</b><b>See also: </b><b>https://helioforecast.space/icmecat</b><br><br>The catalog is available as python pandas dataframe (pickle), python numpy structured array (pickle), json, csv, xlsx, txt, hdf5, html, plus a header txt file with parameter descriptions.<b>Rules:</b> If results are produced with this catalog for peer-reviewed scientific publications, please contact chris.moestl@outlook.com for possible co-authorship.Number of events in ICMECAT: 1252ICME observatories: Solar Orbiter, Parker Solar Probe (PSP), BepiColombo, Wind, MAVEN, STEREO-A, STEREO-B, Venus Express (VEX), MESSENGER, Ulysses.Time range: January 1995 - August 2023.<b>Authors:</b><b> </b>Christian Möstl (1), Eva Weiler (1), Emma E. Davies (1), Rachel L. Bailey (1,2), Martin A. Reiss (3), Andreas J. Weiss (4)<br>(1) Austrian Space Weather Office, GeoSphere Austria, Graz, Austria. (2) Conrad Observatory, GeoSphere Austria, Vienna, Austria. (3) NASA CCMC, USA. (4) NASA GSFC, USA.<b>Contributors:</b> Tarik Mohammad Salman, Peter Boakes, Alexey Isavnin, Emilia Kilpua, David Stansby, Reka Winslow, Brian Anderson, Lydia Philpott, Vratislav Krupar, Jonathan Eastwood, Simon Good, Lan Jian, Teresa Nieves-Chinchilla, Cyril Simon Wedlund, Jingnan Guo, Mateja Dumbovic, Johan von Forstner, Benoit Lavraud.<br>
DOI: 10.6084/m9.figshare.6356420.v16
title: HELIO4CAST Interplanetary Coronal Mass Ejection Catalog v2.1

description: This is the HELIO4CAST interplanetary coronal mass ejection (ICME) catalog, based on in situ magnetic field and bulk plasma observations in the heliosphere.<b>This is version 2.1, released 2021-November-29, updated 2023-September-1.</b><b>See also: </b><b>https://helioforecast.space/icmecat</b><br><br>The catalog is available as python pandas dataframe (pickle), python numpy structured array (pickle), json, csv, xlsx, txt, hdf5, html, plus a header txt file with parameter descriptions.<b>Rules:</b> If results are produced with this catalog for peer-reviewed scientific publications, please contact chris.moestl@outlook.com for possible co-authorship.Number of events in ICMECAT: 1252ICME observatories: Solar Orbiter, Parker Solar Probe (PSP), BepiColombo, Wind, MAVEN, STEREO-A, STEREO-B, Venus Express (VEX), MESSENGER, Ulysses.Time range: January 1995 - August 2023.<b>Authors:</b><b> </b>Christian Möstl (1), Eva Weiler (1), Emma E. Davies (1), Rachel L. Bailey (1,2), Martin A. Reiss (3), Andreas J. Weiss (4)<br>(1) Austrian Space Weather Office, GeoSphere Austria, Graz, Austria. (2) Conrad Observatory, GeoSphere Austria, Vienna, Austria. (3) NASA CCMC, USA. (4) NASA GSFC, USA.<b>Contributors:</b> Tarik Mohammad Salman, Peter Boakes, Alexey Isavnin, Emilia Kilpua, David Stansby, Reka Winslow, Brian Anderson, Lydia Philpott, Vratislav Krupar, Jonathan Eastwood, Simon Good, Lan Jian, Teresa Nieves-Chinchilla, Cyril Simon Wedlund, Jingnan Guo, Mateja Dumbovic, Johan von Forstner, Benoit Lavraud.<br>
DOI: 10.5281/zenodo.8308453
title: PITS Apparent Depth Profiles for Mars Global Cave Candidate Catalog (MGC3) Features

description: Apparent depth profiles calculated by the Pit Topography from Shadows (PITS) tool for the majority of the features in the Mars Global Cave Candidate Catalog (MGC<sup>3</sup>). PITS is a Python framework for automatically calculating apparent depth profiles for Martian and Lunar pits from just a single cropped satellite image. These images can also be single- or multi-band, such as in the case of the Mars Reconnaissance Orbiter (MRO) HiRISE camera. You can learn more about PITS by reading its journal article in RAS Techniques and Instruments, going to its GitHub repository or reading the following post. Since not all catalogued cave candidates on Mars will be pits, PITS has so far been applied to the following MGC<sup>3</sup> subcategories: Atypical Pit Craters (APCs). With plans to extend this to: Lava tube skylights, small rimless pits, generic, amorphous pits, and polar pits. This totals 123 apparent depth profiles in CSV format, which have been derived automatically by PITS for 88 APCs. Therefore, these profiles can be plotted as the user prefers, and/or used in combination with other data to reveal more about this particular APC on the surface of Mars. Each depth profile's CSV file is named according to the HiRISE Reduced Data Record Version 1.1. (RDRV11) that it was calculated upon (e.g. ESP_011386_2065_RED_profile.csv for the red-band version of the HiRISE image ESP_011386_2065). Where there are multiple MGC3 APCs contained within a single image, the file names are numbered generally from the most northern to southernmost, or most westerly to easterly. ESRI shapefiles for the location of all APCs in each HiRISE image have been provided in polygon (containing the extents used to crop the larger HiRISE product) and point format in order to give context in these intances. As the headers suggest, the first four columns represent the shadow length (<em>\(L\)</em>), apparent depth (<em>\(h\)</em>), and the upper/lower bounds of \(\Delta h\), respectively, before they have been corrected for non-zero emission angles (\(\varepsilon\)) at the time of image acquisition. Whereas the latter four columns represent the same quantities after \(\varepsilon\)-correction. How this correction is derived and applied is explained in the PITS journal article linked above.
description: {"references": ["Le Corre D., Mary D., Mason N., Bernard-Salas J., Cox N. (2023) Automatically calculating the apparent depths of pits using the Pit Topography from Shadows (PITS) tool, RAS Techniques and Instruments, Volume 2, Issue 1, January 2023, Pages 492\u2013509, https://doi.org/10.1093/rasti/rzad037"]}
DOI: 10.5281/zenodo.8308454
title: PITS Apparent Depth Profiles for Mars Global Cave Candidate Catalog (MGC3) Features

description: Apparent depth profiles calculated by the Pit Topography from Shadows (PITS) tool for the majority of the features in the Mars Global Cave Candidate Catalog (MGC<sup>3</sup>). PITS is a Python framework for automatically calculating apparent depth profiles for Martian and Lunar pits from just a single cropped satellite image. These images can also be single- or multi-band, such as in the case of the Mars Reconnaissance Orbiter (MRO) HiRISE camera. You can learn more about PITS by reading its journal article in RAS Techniques and Instruments, going to its GitHub repository or reading the following post. Since not all catalogued cave candidates on Mars will be pits, PITS has so far been applied to the following MGC<sup>3</sup> subcategories: Atypical Pit Craters (APCs). With plans to extend this to: Lava tube skylights, small rimless pits, generic, amorphous pits, and polar pits. This totals 123 apparent depth profiles in CSV format, which have been derived automatically by PITS for 88 APCs. Therefore, these profiles can be plotted as the user prefers, and/or used in combination with other data to reveal more about this particular APC on the surface of Mars. Each depth profile's CSV file is named according to the HiRISE Reduced Data Record Version 1.1. (RDRV11) that it was calculated upon (e.g. ESP_011386_2065_RED_profile.csv for the red-band version of the HiRISE image ESP_011386_2065). Where there are multiple MGC3 APCs contained within a single image, the file names are numbered generally from the most northern to southernmost, or most westerly to easterly. ESRI shapefiles for the location of all APCs in each HiRISE image have been provided in polygon (containing the extents used to crop the larger HiRISE product) and point format in order to give context in these intances. As the headers suggest, the first four columns represent the shadow length (<em>\(L\)</em>), apparent depth (<em>\(h\)</em>), and the upper/lower bounds of \(\Delta h\), respectively, before they have been corrected for non-zero emission angles (\(\varepsilon\)) at the time of image acquisition. Whereas the latter four columns represent the same quantities after \(\varepsilon\)-correction. How this correction is derived and applied is explained in the PITS journal article linked above.
description: {"references": ["Le Corre D., Mary D., Mason N., Bernard-Salas J., Cox N. (2023) Automatically calculating the apparent depths of pits using the Pit Topography from Shadows (PITS) tool, RAS Techniques and Instruments, Volume 2, Issue 1, January 2023, Pages 492\u2013509, https://doi.org/10.1093/rasti/rzad037"]}
DOI: 10.25934/pr00009077
title: Predictors of PSP disease progression

description: Progressive Supranuclear Palsy (PSP) is a rare disorder related to Parkinson's disease and Frontotemporal Dementia affecting approximately 2-3/100,000 persons in the US.  It is a neurological disease that causes impaired eye movements, speech, balance and falls and rapidly progresses to disability and death. There are currently no treatments for PSP and very few studies using patient reported outcomes measures in PSP.  The PSP- Quality of Life scale (PSP-QoL) was first published in 2006, however there have been no studies looking at how the scale changes over time.  Importantly, the PSP-QoL has not been compared to the validated PSP Rating Scale (PSPRS, Golbe 2007) except in a small single center cross-sectional cohort study. Validating the PSP-QoL as a patient-reported outcome measure would be extremely important for developing new treatments for this disease.
DOI: 10.48366/r609288
title: A Catalog of the Wizard LLM series

description: WizardLM is a LLM based on LLaMA trained using a new method, called Evol-Instruct, on complex instruction data. By using AI to "evolve" instructions, WizardLM outperforms similar LLaMA-based LLMs trained on simpler instruction data. On the 6th of July, 2023, WizardLM V1.1 was released with significantly improved performance. This comparison juxtaposes all Wizard LLM variants based on their salient properties
DOI: 10.34770/zztk-f783
title: bitKlavier Grand Sample Library—Binaural Mic Image

description: The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications. Binaural: Neumann KU100 This is the binaural head placed in the same location as a seated pianist. It accurately captures what the player would hear while playing the instrument. File Naming Convention: C4 = middle C. Main note names: [note name][octave]v[velocity].wav -- e.g., “D#5v13.wav”. Release resonance notes: harm[note name][octave]v[velocity].wav -- e.g., “harmC2v2.wav”. Hammer samples: rel[1-88].wav (one per key) -- e.g., “rel23.wav”. Pedal samples: pedal[D/U][velocity].wav -- e.g., “pedalU2.wav” =&gt; pedal release (U = up), velocity = 2 (quicker release than velocity = 1).
DOI: 10.6084/m9.figshare.23822589
title: Dataset and analyses of Common Spadefoot Toads breeding migrations and phenological shift

description: Dataset and analyses presented in the article "Effects of temperature and precipitation changes on shifts in breeding phenology of an endangered toad", by Andrea Dalpasso, Daniele Seglie, Paolo Eusebio Bergò, Andrea Ciracì, Mariachiara Compostella, Lorenzo Laddaga, Milo Manica, Gaia Marino, Irene Pandolfo, Giovanni Soldato, Mattia Falaschi<br>Factors_of_migration.txt: Dataset used to assess the factors related to the number of Common Spadefoot Toads migrating to breeding wetlands. All the values of the variable used in the model are standardized with mean = 0 and variance = 1 to improve convergence and allow the comparison of the effect sizes.<br>Phenological_shift.txt: Dataset used to assess the factors related to the observed shift in Common Spadefoot Toad breeding migration. All the values of the variable used in the model are standardized with mean = 0 and variance = 1 to improve convergence and allow the comparison of the effect sizes.<br>Common Spadefoot Toad Analyses.R: Script to run the analyses presented in the manuscript, including "Analysis of factors related to breeding phenology", "Analysis on the shift in breeding phenology", "Analysis on the factors retetad to the shift in breeding phenology", and "Model analysing abundance over time".
DOI: 10.34740/kaggle/dsv/6400460
title: Formula 2 Championship (updated after every race)
DOI: 10.6084/m9.figshare.24073785
title: NAEP student survey and assessment state-level aggregated data on remote learning conditions and outcomes

description: Description of Key Variables and Data Sources<b>Reading Achievement:</b> Percentages of grade 4 and grade 8 students whose NAEP 2015 reading achievement is at or above basic achievement level.<b>Math Achievement: </b>Percentages of grade 4 and grade 8 students whose NAEP 2015 math achievement is at or above the basic achievement level.<b>Student Enrollment in Instructional Modes</b>: Percentages of grade 4 and grade 8 students enrolled in different instructional delivery modes during Jan- May, 2021 (i.e., in-person, hybrid, or remote learning mode each). Data source: NAEP school survey 2021<b>Remote Learning Environment and Engagement</b>: The following set of NAEP student survey items were used to measure remote learning environment and engagement in ELA or math during the COVID-19 pandemic period. Data source: NAEP student survey 2022.Student’s experience of remote learning during last year (% yes)Student’s perceived difficulty of remote learning (% a lot or somewhat more difficult)Students’ self-efficacy to find online resources for remote learning (% probably or definitely can)Students’ self-efficacy to ask for help in remote learning (% probably or definitely can)Teacher’s availability to help with remote learning (% everyday or once/twice a week)Students’ access to digital/computing devices at home (% all the time or some of the time)Students’ access to high-speed Internet at home (% all the time)
DOI: 10.26300/pqpe-fe67
title: Data for Four Decades of Remote and In Situ Sea Surface Temperature Variability in Narragansett Bay
DOI: 10.5517/ccdc.csd.cc2744g0
title: CCDC 2059561: Experimental Crystal Structure Determination

description: Related Article: Dai Oyama, Takatoshi Kanno, Tsugiko Takase|2021|Dalton Trans.|50|7759|doi:10.1039/D1DT00678A
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.cc2g6sfx
title: CCDC 2270639: Experimental Crystal Structure Determination

description: Related Article: Rajata Kumar Sahoo, Sagrika Rajput, Sneha Dutta, Kasturi Sahu, Sharanappa Nembenna|2023|Organometallics|42|2293|doi:10.1021/acs.organomet.3c00281
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.cc2gj0df
title: CCDC 2279504: Experimental Crystal Structure Determination

description: Related Article: Xu-Feng Liu, Shao-Jie Wang, Pei-Hua Zhao|2023|J.Mol.Struct.|1294|136454|doi:10.1016/j.molstruc.2023.136454
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.cc2gj0fg
title: CCDC 2279505: Experimental Crystal Structure Determination

description: Related Article: Xu-Feng Liu, Shao-Jie Wang, Pei-Hua Zhao|2023|J.Mol.Struct.|1294|136454|doi:10.1016/j.molstruc.2023.136454
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.cc2gj0gh
title: CCDC 2279506: Experimental Crystal Structure Determination

description: Related Article: Xu-Feng Liu, Shao-Jie Wang, Pei-Hua Zhao|2023|J.Mol.Struct.|1294|136454|doi:10.1016/j.molstruc.2023.136454
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.cc2g58tr
title: CCDC 2269194: Experimental Crystal Structure Determination

description: Related Article: Yuanpeng Cheng, Junjie Xin, Libang Xiao, Xuejiao Wang, Xu Zhou, Danyang Li, Bo Gui, Junliang Sun, Cheng Wang|2023|J.Am.Chem.Soc.|145|18737|doi:10.1021/jacs.3c06159
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.cc2g5943
title: CCDC 2269204: Experimental Crystal Structure Determination

description: Related Article: Yuanpeng Cheng, Junjie Xin, Libang Xiao, Xuejiao Wang, Xu Zhou, Danyang Li, Bo Gui, Junliang Sun, Cheng Wang|2023|J.Am.Chem.Soc.|145|18737|doi:10.1021/jacs.3c06159
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.cc2gt0lx
title: CCDC 2288159: Experimental Crystal Structure Determination

description: Related Article: E.Z. Huseynov, M. Akkurt, I. Brito, A. Bhattarai, F.N. Naghiyev, K.A. Asadov, A.M. Maharramov|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|808|doi:10.1107/S2056989023007090
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: 10.34740/kaggle/dsv/6400535
title: Top-Anime
DOI: 10.5522/04/24039399
title: Cell growth profile of Escherichia coli BL21 in various MOPS concentration and pH values at 37 C (pH 7.00 to 7.75, 0.25 increment, in LB with MOPS buffer)

description: This dataset was generated on 24th March 2023 as Appendix B for the BENG0046 project entitled "Development of automatic and miniaturized continuous cell culture system for improvement of cellular strains". <br> The raw dataset of Escherichia coli BL21 growth at 37 C in pH-modified LB media (MOPS: pH 7.00, 7.25, 7.50, 7,75). The samples were measured by OD<sub>600</sub> for 72 hours, every 5 minutes, in CLARIOstar Plus microplate reader.
DOI: 10.5522/04/24039399.v1
title: Cell growth profile of Escherichia coli BL21 in various MOPS concentration and pH values at 37 C (pH 7.00 to 7.75, 0.25 increment, in LB with MOPS buffer)

description: This dataset was generated on 24th March 2023 as Appendix B for the BENG0046 project entitled "Development of automatic and miniaturized continuous cell culture system for improvement of cellular strains". <br> The raw dataset of Escherichia coli BL21 growth at 37 C in pH-modified LB media (MOPS: pH 7.00, 7.25, 7.50, 7,75). The samples were measured by OD<sub>600</sub> for 72 hours, every 5 minutes, in CLARIOstar Plus microplate reader.
DOI: 10.5522/04/24039387
title: Cell growth profile of Escherichia coli BL21 in various MOPS concentration and pH values at 25 C (pH 7.00 to 7.75, 0.25 increment, in LB with MOPS buffer)

description: This dataset was generated on 26th June 2023 as Appendix B for the BENG0046 project entitled "Development of automatic and miniaturized continuous cell culture system for improvement of cellular strains". <br> The raw dataset of Escherichia coli BL21 growth at 25 C in pH-modified LB media (MOPS: pH 7.00, 7.25, 7.50, 7,75). The samples were measured by OD<sub>600</sub> for 72 hours, every 5 minutes, in CLARIOstar Plus microplate reader.
DOI: 10.5522/04/24039387.v1
title: Cell growth profile of Escherichia coli BL21 in various MOPS concentration and pH values at 25 C (pH 7.00 to 7.75, 0.25 increment, in LB with MOPS buffer)

description: This dataset was generated on 26th June 2023 as Appendix B for the BENG0046 project entitled "Development of automatic and miniaturized continuous cell culture system for improvement of cellular strains". <br> The raw dataset of Escherichia coli BL21 growth at 25 C in pH-modified LB media (MOPS: pH 7.00, 7.25, 7.50, 7,75). The samples were measured by OD<sub>600</sub> for 72 hours, every 5 minutes, in CLARIOstar Plus microplate reader.
DOI: 10.5522/04/24039384
title: Cell growth profile of Escherichia coli BL21 in various pH values (pH 7.00 to 10.00, 0.25 increment, in LB with three different buffers)

description: This dataset was generated on 16th March 2023 as Appendix A for the BENG0046 project entitled "Development of automatic and miniaturized continuous cell culture system for improvement of cellular strains". <br> The raw dataset of Escherichia coli BL21 growth at 37 C in pH-modified LB media (MOPS: pH 7.00, 7.25, 7.50, 7,75 / TRIS: 8.00, 8.25, 8.50, 8,75 / CAPSO: 9.00, 9.25, 9.50, 9,75, and 10.00). The samples were measured by OD<sub>600</sub> for 72 hours, every 5 minutes, in CLARIOstar Plus microplate reader.