cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/fw0r-p668
title: Parkes observations for project P1162 semester 2022OCTS_10

description: Pulsar timing is a powerful tool in studying pulsar physics. Discovering more exotic pulsar systems or timing pulsars with higher precision is an essential part of pulsar astronomy. As a recently discovered millisecond pulsar, PSR J1402+13 is an interesting source for follow-up timing observations. First, its spin-down rate is the highest among known millisecond pulsars according to initial data. This spin-down rate, if confirmed, will place stringent constraints on the spin-up process predicted by pulsar recycling theories. Second, and more importantly, J1402+13 is a very promising candidate for pulsar timing arrays, with an achievable precision at the level of 6 nanoseconds for 60 minutes observation with Parkes. We thus apply for 18.7 hours to conduct dedicated timing observations of J1402+13 over the period of half a year (and more observations in the future semesters). This project will derive an ephemeris of the system, which is valuable to understand its formation and evolution history. Furthermore, the observations will allow us to evaluate the timing performance of J1402+13 and its suitability to be included in pulsar timing arrays.
DOI: 10.25345/c5125qk6m
title: MassIVE MSV000091667 - TMEM175-LAMP quantitative proteomics
title: TMEM175-LAMP quantitative proteomics all replicates
DOI: 10.25919/wfzv-fn61
title: Parkes observations for project P1165 semester 2022OCTS_06

description: We propose to confirm and time five pulsar candidates recently discovered by the Five-hundred-meter Aperture Spherical Telescope (FAST). These candidates were discovered during a pilot survey of an intermediate Galactic latitude region with six-minute pointings. One candidate, J1826-0049, has already been confirmed to be a 4.59 ms pulsar in a binary system with an orbital period of ~6.3 hr. The superior sensitivity of FAST has the potential to discover pulsars in compact binary systems and we propose to use Parkes to confirm the nature of these candidates. We also propose to time two of the brightest candidates with Parkes and measure their spin and orbital parameters. These observations have the potential to open new opportunities to probe exciting physics with these newly discovered pulsars.
DOI: 10.15468/dl.55kfem
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query: { "TaxonKey" : [ "is Cymbidium micranthum Z.J.Liu & S.C.Chen" ] } The dataset includes 0 records from 0 constituent datasets:
DOI: 10.6084/m9.figshare.22580263
title: Dental Panoramic Scan

description: Introduction <br> The dataset consists of 1488 orthopantomogram (OPG) images collected from a dental clinic in India. The images were taken using a digital OPG machine, which captures a panoramic view of the patient's teeth and jaws. The dataset does not contain any personal information about the patients, as it has been deleted for privacy reasons. Additionally, the data does not have any labels or annotations. <br> Data Collection <br> The OPG images were collected over a period of six months from patients who visited the dental clinic for routine check-ups or specific dental problems. The images were captured using a digital OPG machine that uses X-rays to create a panoramic view of the patient's teeth and jaws. The machine is designed to capture high-quality images with minimal radiation exposure to the patient. <br> Data Preprocessing <br> Before being added to the dataset, each OPG image was checked for quality and clarity. Images that were blurry or had artifacts were removed from the dataset. Additionally, all personal information about the patients was deleted from the images to ensure privacy. <br> Data Description <br> The dataset contains 1488 OPG images in JPEG format. Each image has a resolution of 2400 x 1200 pixels and is grayscale. The size of each image ranges from 900 KB to 1.1 MB, depending on its complexity. <br> The OPG images in this dataset show different types of dental problems such as cavities, gum disease, impacted teeth, and fractures. Some images also show normal healthy teeth and jaws.
DOI: 10.15468/dl.286j4r
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query: { "TaxonKey" : [ "is Cymbidium ×oblancifolium Z.J.Liu & S.C.Chen" ] } The dataset includes 0 records from 0 constituent datasets:
DOI: 10.13140/rg.2.2.15424.61445
title: Етапи розвитку обчислювальної техніки
DOI: 10.15468/dl.c4r5qp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query: { "TaxonKey" : [ "is Cymbidium ×rosefieldense Rolfe" ] } The dataset includes 0 records from 0 constituent datasets:
DOI: 10.13140/rg.2.2.12908.03201
title: Binomial distribution in industrial metrology
DOI: 10.15468/dl.p276me
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query: { "TaxonKey" : [ "is Cymbidium ×woodlandense Rolfe" ] } The dataset includes 0 records from 0 constituent datasets:
DOI: 10.25919/g8b4-0384
title: Parkes observations for project P1162 semester 2022OCTS_10

description: Pulsar timing is a powerful tool in studying pulsar physics. Discovering more exotic pulsar systems or timing pulsars with higher precision is an essential part of pulsar astronomy. As a recently discovered millisecond pulsar, PSR J1402+13 is an interesting source for follow-up timing observations. First, its spin-down rate is the highest among known millisecond pulsars according to initial data. This spin-down rate, if confirmed, will place stringent constraints on the spin-up process predicted by pulsar recycling theories. Second, and more importantly, J1402+13 is a very promising candidate for pulsar timing arrays, with an achievable precision at the level of 6 nanoseconds for 60 minutes observation with Parkes. We thus apply for 18.7 hours to conduct dedicated timing observations of J1402+13 over the period of half a year (and more observations in the future semesters). This project will derive an ephemeris of the system, which is valuable to understand its formation and evolution history. Furthermore, the observations will allow us to evaluate the timing performance of J1402+13 and its suitability to be included in pulsar timing arrays.
DOI: 10.25919/z7xc-zj48
title: Parkes observations for project P1162 semester 2022OCTS_10

description: Pulsar timing is a powerful tool in studying pulsar physics. Discovering more exotic pulsar systems or timing pulsars with higher precision is an essential part of pulsar astronomy. As a recently discovered millisecond pulsar, PSR J1402+13 is an interesting source for follow-up timing observations. First, its spin-down rate is the highest among known millisecond pulsars according to initial data. This spin-down rate, if confirmed, will place stringent constraints on the spin-up process predicted by pulsar recycling theories. Second, and more importantly, J1402+13 is a very promising candidate for pulsar timing arrays, with an achievable precision at the level of 6 nanoseconds for 60 minutes observation with Parkes. We thus apply for 18.7 hours to conduct dedicated timing observations of J1402+13 over the period of half a year (and more observations in the future semesters). This project will derive an ephemeris of the system, which is valuable to understand its formation and evolution history. Furthermore, the observations will allow us to evaluate the timing performance of J1402+13 and its suitability to be included in pulsar timing arrays.
DOI: 10.5281/zenodo.7812157
title: A catalog of associated, machine-learning-derived phase arrival times for ten days of seismic data in the Yellowstone region

description: This dataset contains the associated phase picks and event information from applying a deep learning phase picker to continuous data recorded over March 25 – April 3, 2014, on 20 three-component stations and 14 vertical-component stations in the Yellowstone region. This 10-day period contains an M<sub>w</sub> 4.8 event, the largest earthquake in the Yellowstone region since 1980. The catalog and deep learning phase picker are described in Armstrong et al. (submitted). The arrivals were associated using the method described by Baker et al. (2021) and located using HypoInverse2000 (Klein, 2002). There are 1,053 events in this catalog, including 855 that were previously unidentified. Events that also appear in the University of Utah Seismograph Stations catalog have an event identifier (evid) beginning with “6”, while new events begin with “9”. Columns include: A simple event number the network, station, channel, and location code for the arrival time the arrival time in UTC (arrival_time) and Unix (arrival_time_epoch) format any static correction applied to the arrival time the P-pick first motion polarity as determined by a machine learning model - up (1), down (-1), or unknown (0) the arrival time residual the take off angle in degrees the event latitude and longitude in degrees the event depth in km the event origin time in UTC (origin_time) and Unix (origin_time_epoch) format the azimuthal gap of the event in degrees the root mean square error (RMS) of the event location the event identifier (evid) - begins with a “6” for events in the UUSS catalog and a “9” for new events
description: {"references": ["Baker, B., M. M. Holt, K. L. Pankow, K. D. Koper, and J. Farrell (2021). Monitoring the 2020 Magna, Utah, earthquake sequence with nodal seismometers and machine learning, Seismol. Res. Lett. 92, 787\u2013801.", "Klein, F. W. (2002). User's guide to HYPOINVERSE-2000, a Fortran program to solve for earthquake locations and magnitudes 4/2002 version, U. S. Geol. Surv. Open File Rept. 02-171 Version 1.0, 123 pp."]}
DOI: 10.5281/zenodo.7812156
title: A catalog of associated, machine-learning-derived phase arrival times for ten days of seismic data in the Yellowstone region

description: This dataset contains the associated phase picks and event information from applying a deep learning phase picker to continuous data recorded over March 25 – April 3, 2014, on 20 three-component stations and 14 vertical-component stations in the Yellowstone region. This 10-day period contains an M<sub>w</sub> 4.8 event, the largest earthquake in the Yellowstone region since 1980. The catalog and deep learning phase picker are described in Armstrong et al. (submitted). The arrivals were associated using the method described by Baker et al. (2021) and located using HypoInverse2000 (Klein, 2002). There are 1,053 events in this catalog, including 855 that were previously unidentified. Events that also appear in the University of Utah Seismograph Stations catalog have an event identifier (evid) beginning with “6”, while new events begin with “9”. Columns include: A simple event number the network, station, channel, and location code for the arrival time the arrival time in UTC (arrival_time) and Unix (arrival_time_epoch) format any static correction applied to the arrival time the P-pick first motion polarity as determined by a machine learning model - up (1), down (-1), or unknown (0) the arrival time residual the take off angle in degrees the event latitude and longitude in degrees the event depth in km the event origin time in UTC (origin_time) and Unix (origin_time_epoch) format the azimuthal gap of the event in degrees the root mean square error (RMS) of the event location the event identifier (evid) - begins with a “6” for events in the UUSS catalog and a “9” for new events
description: {"references": ["Baker, B., M. M. Holt, K. L. Pankow, K. D. Koper, and J. Farrell (2021). Monitoring the 2020 Magna, Utah, earthquake sequence with nodal seismometers and machine learning, Seismol. Res. Lett. 92, 787\u2013801.", "Klein, F. W. (2002). User's guide to HYPOINVERSE-2000, a Fortran program to solve for earthquake locations and magnitudes 4/2002 version, U. S. Geol. Surv. Open File Rept. 02-171 Version 1.0, 123 pp."]}
DOI: 10.5517/ccdc.csd.cc2d6vdw
title: CCDC 2211118: Experimental Crystal Structure Determination

description: Related Article: Wen-Shuai Dong, Yong Hu, Zu-jia Lu, Chao Zhang, Xiaowei Wu, Jian-Guo Zhang|2023|Cryst.Growth Des.|23|2721|doi:10.1021/acs.cgd.2c01507
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.cc2d6vgy
title: CCDC 2211120: Experimental Crystal Structure Determination

description: Related Article: Wen-Shuai Dong, Yong Hu, Zu-jia Lu, Chao Zhang, Xiaowei Wu, Jian-Guo Zhang|2023|Cryst.Growth Des.|23|2721|doi:10.1021/acs.cgd.2c01507
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.cc2d6vhz
title: CCDC 2211121: Experimental Crystal Structure Determination

description: Related Article: Wen-Shuai Dong, Yong Hu, Zu-jia Lu, Chao Zhang, Xiaowei Wu, Jian-Guo Zhang|2023|Cryst.Growth Des.|23|2721|doi:10.1021/acs.cgd.2c01507
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.cc2d6vj0
title: CCDC 2211122: Experimental Crystal Structure Determination

description: Related Article: Wen-Shuai Dong, Yong Hu, Zu-jia Lu, Chao Zhang, Xiaowei Wu, Jian-Guo Zhang|2023|Cryst.Growth Des.|23|2721|doi:10.1021/acs.cgd.2c01507
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: 10.5281/zenodo.7812221
title: trichoglossus_johnstoniae_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7812220
title: trichoglossus_johnstoniae_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7812260
title: Phytochemical analysis of antibacterial components in crude saps extracted from several medicinal plants

description: raw data
DOI: 10.5281/zenodo.7812259
title: Phytochemical analysis of antibacterial components in crude saps extracted from several medicinal plants

description: raw data
DOI: 10.5517/ccdc.csd.cc2dbqfx
title: CCDC 2214839: Experimental Crystal Structure Determination

description: Related Article: Meng Wang, Jin Long Li, Xiao Yu Tang, Qing Lin Guan, Feng Ying Bai, Yong Heng Xing, Yu Fei Wang|2023|Inorg.Chem.|62|5145|doi:10.1021/acs.inorgchem.2c04422
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.cc2dcy4w
title: CCDC 2216008: Experimental Crystal Structure Determination

description: Related Article: Yao Xie, Zhuo-Hao Jiao, Jie Dong, Sheng-Li Hou, Bin Zhao|2023|Inorg.Chem.|62|5168|doi:10.1021/acs.inorgchem.3c00019
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.cc2dzb1s
title: CCDC 2233675: Experimental Crystal Structure Determination

description: Related Article: Wen-Shuai Dong, Yong Hu, Zu-jia Lu, Chao Zhang, Xiaowei Wu, Jian-Guo Zhang|2023|Cryst.Growth Des.|23|2721|doi:10.1021/acs.cgd.2c01507
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.cc2dpyfh
title: CCDC 2225627: Experimental Crystal Structure Determination

description: Related Article: Jonas Gosch, Diletta Morelli Venturi, Erik Svensson Grape, Cesare Atzori, Lorenzo Donà, Felix Steinke, Tobias Otto, Tim Tjardts, Bartolomeo Civalleri, Kirill A. Lomachenko, A. Ken Inge, Ferdinando Costantino, Norbert Stock|2023|Inorg.Chem.|62|5176|doi:10.1021/acs.inorgchem.3c00049
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.22304557
title: Revised supplemental data figure for L-00382-2022

description: Revised supplemental data figure for L-00382-2022
DOI: 10.5281/zenodo.7811204
title: MUSES Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) 8-Day Global 500m SIN Grid in 2008

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FAPAR product at 500m spatial resolution and 8-day temporal resolution. The MUSES FAPAR product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500m resolution and other ancillary information using the complement to unity of the transmittance of PAR through the entire canopy (Xiao <em>et al</em>., 2015). The MUSES FAPAR values are the instantaneous values at 10:30 am local time, close approximation of daily average PAPAR values, and they are physically consistent with the corresponding MUSES LAI values. The MUSES FAPAR product is spatially complete and temporally continuous. This dataset is the MUSES FAPAR product in 2008. <em>Please <strong>click here</strong> to download the MUSES FAPAR product <strong>in 2007</strong></em>, and <em><strong>click here</strong> to download the MUSES FAPAR product <strong>in 2009</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2008 Spatial Resolution: 500m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>., Estimating the fraction of absorbed photosynthetically active radiation from the MODIS databased GLASS leaf area index product. <em>Remote Sensing of Environment</em>, 171,105-117, 2015. Xiao Zhiqiang, <em>et al</em>., Evaluation of Three Long Time Series for Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 56, 5509-5524, 2018. Zheng Y., Xiao Z., Li J., Yang H., Song J., Evaluation of Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products at 500 m Spatial Resolution. <em>Remote Sensing</em>, 14, 3304, 2022. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7811203
title: MUSES Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) 8-Day Global 500m SIN Grid in 2008

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FAPAR product at 500m spatial resolution and 8-day temporal resolution. The MUSES FAPAR product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500m resolution and other ancillary information using the complement to unity of the transmittance of PAR through the entire canopy (Xiao <em>et al</em>., 2015). The MUSES FAPAR values are the instantaneous values at 10:30 am local time, close approximation of daily average PAPAR values, and they are physically consistent with the corresponding MUSES LAI values. The MUSES FAPAR product is spatially complete and temporally continuous. This dataset is the MUSES FAPAR product in 2008. <em>Please <strong>click here</strong> to download the MUSES FAPAR product <strong>in 2007</strong></em>, and <em><strong>click here</strong> to download the MUSES FAPAR product <strong>in 2009</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2008 Spatial Resolution: 500m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>., Estimating the fraction of absorbed photosynthetically active radiation from the MODIS databased GLASS leaf area index product. <em>Remote Sensing of Environment</em>, 171,105-117, 2015. Xiao Zhiqiang, <em>et al</em>., Evaluation of Three Long Time Series for Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 56, 5509-5524, 2018. Zheng Y., Xiao Z., Li J., Yang H., Song J., Evaluation of Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products at 500 m Spatial Resolution. <em>Remote Sensing</em>, 14, 3304, 2022. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.34740/kaggle/dsv/5357475
title: #ChatGPT 1000 Daily 🐦 Tweets
DOI: 10.25345/c5w950z23
title: MassIVE MSV000091668 - TMEM175-LAMP1 crosslinking proteomics
title: Raw files of crosslinking proteomics of TMEM175-LAMP1 complex.