cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p9qsqpuu
title: Sagebrush Distribution within the Biome Range Extent, as Derived from Classified Landsat Imagery

description: This raster portrays the distribution of sagebrush within the geographic extent of the sagebrush biome in the United States. It was created for the Western Association of Fish and Wildlife Agency's (WAFWA) Sagebrush Conservation Strategy publication as a visual for the schematic figures and to calculate summary statistics. This distribution incorporates the most recently available sagebrush cover mapping (Xian et al. 2015, Rigge et al. 2019) and classified LANDFIRE EVT (Department of Ecosystem Science, University of Wyoming 2016). Both datasets were rigorously evaluated and extensive ground measurements taken to evaluate accuracy by the respective authors. We created a combined binary sagebrush distribution by classifying the Rigge et al. (2019) product to a binary form where sagebrush cover was greater than 5%, which is equal to the root mean squared error of the analysis (RMSE = 5.09). The Rigge et al. (2019) raster is not complete across the sagebrush biome, so we filled in the areas of NoData with the 'Sagebrush-dominated Ecological Systems' pixels from binary sagebrush raster (Department of Ecosystem Science, University of Wyoming 2016) to create a continuous raster across the sagebrush biome. The input layers are informative to conditions circa the beginning of 2015. Xian, G., Homer, C., Rigge, M., Shi, H., and Meyer, D. (2015). Characterization of shrubland ecosystem components as continuous fields in the northwest United States. Remote sensing of environment, 168, 286-300. https://doi.org/10.1016/j.rse.2015.07.014. Department of Ecosystem Science, University of Wyoming. (2016). Western United States Sagebrush Cover Raster, https://www.sciencebase.gov/catalog/item/57a26dbbe4b006cb45553f78. Rigge, M., Shi, H., Homer, C., Danielson, P., and Granneman, B. (2019). Long-term trajectories of fractional component change in the Northern Great Basin, USA. Ecosphere, 10(6):e02762, https://doi.org/10.1002/ecs2.2762.
DOI: 10.6084/m9.figshare.14254112
title: NERModel.rar

description: Bert_NER_Model
DOI: 10.6084/m9.figshare.14254112.v1
title: NERModel.rar

description: Bert_NER_Model
DOI: 10.25919/349k-cy90
title: Parkes observations for project P1038 semester 2020OCTS_17

description: PSR~J1759-2402 is one of a small handful of pulsars which are in orbit about high mass stars. Its orbital period is 8.3 years and the orbit is highly eccentric with periastron expected in 2021 March. Although discovered at Parkes, the Lovell telescope has been monitoring the pulsar over many years. However, it’s restricted bandwidth, maintenance schedule and poorer polarization capability make it unsuitable to follow the pulsar as it enters and leaves the eclipse by the companion. In contrast, the UWL on Parkes with its wide- band and excellent polarization characteristics means that we can determine scattering, polarization, dispersion measure and rotation measure changes as the pulsar enters its companion wind. We request a continuation of our weekly observations of the pulsar to track its progress around the orbit.
DOI: 10.17632/jdspb3s4yr.1
title: Data for: Wildfires and Wood stoves: Woodsmoke Toxicity and Chemical Characterization Study in the North-Western United States

description: Measured concentrations (&uncertainties) of PM2.5, CO, BC, UV, ozone, VOC and SVOC from Method TO-15 and TO-13A between August 2018 and May 2019 in Lacey, WA.
DOI: 10.6084/m9.figshare.14254205
title: Data matrix used in this meta-analysis

description: Data matrix used in "Differential effects of altered precipitation regimes on soil carbon dynamics in arid <i>vs</i>. humid terrestrial ecosystems"
DOI: 10.6084/m9.figshare.14254205.v1
title: Data matrix used in this meta-analysis

description: Data matrix used in "Differential effects of altered precipitation regimes on soil carbon dynamics in arid <i>vs</i>. humid terrestrial ecosystems"
DOI: 10.6084/m9.figshare.14254211
title: Fulton County Absentee Votes

description: Time series data for Fulton County absentee votes.
DOI: 10.6084/m9.figshare.14254211.v1
title: Fulton County Absentee Votes

description: Time series data for Fulton County absentee votes.
DOI: 10.6084/m9.figshare.14254229
title: Semantic2vec.rar

description: Algorithm and raw data<br>
DOI: 10.6084/m9.figshare.14254229.v1
title: Semantic2vec.rar

description: Algorithm and raw data<br>
DOI: 10.5281/zenodo.4625288
title: Replication package for "Escaping the Time Pit: Pitfalls and Guidelines for Using Time-Based Git Data"

description: This dataset includes scripts, text files, and JSON files used to generate all analysis and results from the paper. A README.md file is included for details on using the scripts - though all of the data the scripts generate should already be cached as JSON or txt files and none of the scripts actually need run. It also includes a spreadsheet containing the paper survey results and manual judgements. The scripts are also on GitHub: https://github.com/psybers/msr21-timestudy
DOI: 10.5281/zenodo.4435249
title: Replication package for "Escaping the Time Pit: Pitfalls and Guidelines for Using Time-Based Git Data"

description: This dataset includes scripts, text files, and JSON files used to generate all analysis and results from the paper. A README.md file is included for details on using the scripts - though all of the data the scripts generate should already be cached as JSON or txt files and none of the scripts actually need run. It also includes a spreadsheet containing the paper survey results and manual judgements. The scripts are also on GitHub: https://github.com/psybers/msr21-timestudy
DOI: 10.21227/8658-gq26
title: Day-Ahead Forecasting using LSTM with rolling windows

description: The project involves day-ahead forecasting which takes a model fit into historical data and predicts future demand of electricity. Time series forecasting methods are used as the dataset contains an explicit order dependence between observations, i.e. a time dimension which makes the problem difficult to handle but makes the prediction more accurate. Various machine learning and deep learning algorithms were used to accomplish this work. Results obtained by autoregressive integrated moving average(ARIMA), autoregressive moving average with explanatory variable(ARIMAX), seasonal autoregressive moving average(SARIMA), seasonal autoregressive moving average(SARIMAX) and long short term memory(LSTM) recurrent neural networks with rolling windows were compared and the one with least error, i.e. LSTM with rolling windows was used for time series prediction.
DOI: 10.5281/zenodo.4625299
title: Citations to invalid DOI-identified entities obtained from processing DOI-to-DOI citations to add in COCI

description: This dataset contains a two-column CSV file, where the first column ("Valid_citing_DOI") contains the DOI of a citing entity retrieved in Crossref, while the second column ("Invalid_cited_DOI") contains the invalid DOI of a cited entity identified by looking at the field "reference" in the JSON document returned by querying the Crossref API with the citing DOI. These citations to invalid DOIs have been retrieved while processing Crossref data for adding open citations in COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations. The citations listed in the present dataset have not been added in COCI since they point to a non-resolvable cited document.
DOI: 10.6084/m9.figshare.14254226
title: Vaccination Attitudes Among Sunshine Coast Parents (Dataset)

description: The data includes several variables that predict parental attitudes towards vaccination among Sunshine Coast parents. Cross-sectional design was implemented using a hierarchical multiple regression. Predictor variables include - conspiratorial thinking, psychological reactance, health beliefs, and trust in government. Outcome variable was 'attitude towards vaccination' which combined the variables - vaccine views and vaccine concerns. Ethical approval for data collection was approved by The University of the Sunshine Coast Human Ethics Committee.
DOI: 10.21227/88tg-qa68
title: January-23-Basu-Sukanta

description: January-23-Basu-Sukanta
DOI: 10.25919/3k08-5908
title: Parkes observations for project PX500 semester 2020OCTS_14

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.
DOI: 10.5281/zenodo.4625262
title: Data from: Optimising glyphosate tolerance in rapeseed (Brassica napus L.) by CRISPR/Cas9-based geminiviral donor DNA replicon system with Csy4-based single-guide RNA processing

description: The files were the vector sequence and annotationin used in the Journal article "Optimising glyphosate tolerance in rapeseed (<em>Brassica napus</em> L.) by CRISPR/Cas9-based geminiviral donor DNA replicon system with Csy4-based single-guide RNA processing" (Manuscript Number: JEXBOT/2020/300772), which will publish on the Journal of Experimental Botany. The sequence of original vectors (pTRANS_221, pMOD_A0501, pMOD_B2103, pMOD_C2515, and pKSE401) was downloaded from Addgene. We cloned the <em>BnC04EPSPS </em>(BnC04g56880D)gene from the rapeseed cultivar 627R, and used overlapping PCR to make <em>BnC04EPSPS </em> Donor templates containing TIPS or LFGAAGMCRL mutations. Finally, SnapGene 3.2.1 were used to annotate all the modified vectors. Nine vectors were included in this dataset.
DOI: 10.5281/zenodo.4625261
title: Data from: Optimising glyphosate tolerance in rapeseed (Brassica napus L.) by CRISPR/Cas9-based geminiviral donor DNA replicon system with Csy4-based single-guide RNA processing

description: The files were the vector sequence and annotationin used in the Journal article "Optimising glyphosate tolerance in rapeseed (<em>Brassica napus</em> L.) by CRISPR/Cas9-based geminiviral donor DNA replicon system with Csy4-based single-guide RNA processing" (Manuscript Number: JEXBOT/2020/300772), which will publish on the Journal of Experimental Botany. The sequence of original vectors (pTRANS_221, pMOD_A0501, pMOD_B2103, pMOD_C2515, and pKSE401) was downloaded from Addgene. We cloned the <em>BnC04EPSPS </em>(BnC04g56880D)gene from the rapeseed cultivar 627R, and used overlapping PCR to make <em>BnC04EPSPS </em> Donor templates containing TIPS or LFGAAGMCRL mutations. Finally, SnapGene 3.2.1 were used to annotate all the modified vectors. Nine vectors were included in this dataset.
DOI: 10.5517/ccdc.csd.cc25kx5v
title: CCDC 2013207: Experimental Crystal Structure Determination

description: Related Article: Feng Chen, Xiu-Hua Xu, Feng-Ling Qing|2021|Org.Lett.|23|2364|doi:10.1021/acs.orglett.1c00639
DOI: 10.5517/ccdc.csd.cc26r347
title: CCDC 2047988: Experimental Crystal Structure Determination

description: Related Article: Nuan Chen, Ting Zhou, Hong Zhang, Yuqi Zhu, Ming Lang, Jian Wang, Shiyong Peng|2021|J.Org.Chem.|86|4714|doi:10.1021/acs.joc.1c00104
DOI: 10.5517/ccdc.csd.cc26r9t3
title: CCDC 2048195: Experimental Crystal Structure Determination

description: Related Article: Nuan Chen, Ting Zhou, Hong Zhang, Yuqi Zhu, Ming Lang, Jian Wang, Shiyong Peng|2021|J.Org.Chem.|86|4714|doi:10.1021/acs.joc.1c00104
DOI: 10.5517/ccdc.csd.cc26r9v4
title: CCDC 2048196: Experimental Crystal Structure Determination

description: Related Article: Nuan Chen, Ting Zhou, Hong Zhang, Yuqi Zhu, Ming Lang, Jian Wang, Shiyong Peng|2021|J.Org.Chem.|86|4714|doi:10.1021/acs.joc.1c00104
DOI: 10.5517/ccdc.csd.cc26r9w5
title: CCDC 2048197: Experimental Crystal Structure Determination

description: Related Article: Nuan Chen, Ting Zhou, Hong Zhang, Yuqi Zhu, Ming Lang, Jian Wang, Shiyong Peng|2021|J.Org.Chem.|86|4714|doi:10.1021/acs.joc.1c00104
DOI: 10.5517/ccdc.csd.cc26r9x6
title: CCDC 2048198: Experimental Crystal Structure Determination

description: Related Article: Nuan Chen, Ting Zhou, Hong Zhang, Yuqi Zhu, Ming Lang, Jian Wang, Shiyong Peng|2021|J.Org.Chem.|86|4714|doi:10.1021/acs.joc.1c00104
DOI: 10.5517/ccdc.csd.cc26rw73
title: CCDC 2048735: Experimental Crystal Structure Determination

description: Related Article: Ricardo Molina Betancourt, Phannarath Phansavath, Virginie Ratovelomanana-Vidal|2021|Org.Lett.|23|1621|doi:10.1021/acs.orglett.1c00047
DOI: 10.5517/ccdc.csd.cc26v0jm
title: CCDC 2050790: Experimental Crystal Structure Determination

description: Related Article: Christopher C. V. Jones, Jignesh J. Patel, Ross D. Jansen-van Vuuren, Gregory M. Ross, Bernd O. Keller, Francoise Sauriol, Gabriele Schatte, Erin R. Johnson, Victor Snieckus|2021|Org.Lett.|23|1966|doi:10.1021/acs.orglett.1c00521
DOI: 10.5517/ccdc.csd.cc26v0kn
title: CCDC 2050791: Experimental Crystal Structure Determination

description: Related Article: Christopher C. V. Jones, Jignesh J. Patel, Ross D. Jansen-van Vuuren, Gregory M. Ross, Bernd O. Keller, Francoise Sauriol, Gabriele Schatte, Erin R. Johnson, Victor Snieckus|2021|Org.Lett.|23|1966|doi:10.1021/acs.orglett.1c00521
DOI: 10.5517/ccdc.csd.cc26z0nw
title: CCDC 2054638: Experimental Crystal Structure Determination

description: Related Article: Lin-Lin Teng, Rong-Fang Mu, Yan-Chun Liu, Chao-Jiang Xiao, De-Sen Li, Jian-Xiong Gao, Kai Guo, Xiao-Nian Li, Yan Liu, Fang Zeng, Sheng-Hong Li|2021|Org.Lett.|23|2232|doi:10.1021/acs.orglett.1c00369
DOI: 10.5517/ccdc.csd.cc26z0rz
title: CCDC 2054641: Experimental Crystal Structure Determination

description: Related Article: Lin-Lin Teng, Rong-Fang Mu, Yan-Chun Liu, Chao-Jiang Xiao, De-Sen Li, Jian-Xiong Gao, Kai Guo, Xiao-Nian Li, Yan Liu, Fang Zeng, Sheng-Hong Li|2021|Org.Lett.|23|2232|doi:10.1021/acs.orglett.1c00369
DOI: 10.5517/ccdc.csd.cc270swy
title: CCDC 2056350: Experimental Crystal Structure Determination

description: Related Article: Guzhou Chen, Peng-Yu Liu, Huanhuan Zou, Jiadong Hu, Xiaowu Fang, Dongyang Xu, Yu-Peng He, Hongbo Wei, Weiqing Xie|2021|Org.Lett.|23|2279|doi:10.1021/acs.orglett.1c00411
DOI: 10.5517/ccdc.csd.cc270sxz
title: CCDC 2056351: Experimental Crystal Structure Determination

description: Related Article: Guzhou Chen, Peng-Yu Liu, Huanhuan Zou, Jiadong Hu, Xiaowu Fang, Dongyang Xu, Yu-Peng He, Hongbo Wei, Weiqing Xie|2021|Org.Lett.|23|2279|doi:10.1021/acs.orglett.1c00411
DOI: 10.15161/oar.it/73596
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.21227/4mxh-k630
title: Load forecasting with mixture of experts

description: Submission 23-Jan
DOI: 10.21227/1rae-3566
title: Forecast Result for January 23

description: This csv file contains the load forecasts on Jan-23, conducted by Hongqiao Peng.
DOI: 10.6084/m9.figshare.14254316
title: Genome-wide epistatic interactions of litter size at birth in Chinese indigenous pigs

description: Improving litter size at birth (TNB) and the number of piglets born alive (NBA) are the main breeding goals related to litter traits, which are economically important. A better understanding of genetic architecture underlying TNB and NBA traits could increase pig production efficiency. However, most previous studies on these traits focus on additive genetic effects, while epistatic interactions underlying TNB and NBA traits has not yet been well investigated, which are essential to understand how traits-related genes interact. Herein, we conducted genome scans of epistatic interactions underlying TNB and NBA traits in a total of 150 Chinese indigenous pigs (75 Jinhua and 75 Shengxian Plotted pigs) with high throughput genomic data. Based on SNPs with high interaction values and connectivity scores, we identified eight promising candidate genes, namely <i>AKT2</i>, <i>TSC1</i>, <i>MTOR</i>, <i>PIK3R5</i>, <i>TIAM1</i>, <i>FGF14</i>, <i>RALB</i>, and <i>ROR2</i>, potentially associated with litter traits in pigs. Moreover, the underlying pathways, e.g., calcium ion transport, pointed out their roles in litter size related-traits. Our findings provide new insight into genetic architecture of litter traits in pigs and will benefit economic profits in pig production.
DOI: 10.6084/m9.figshare.14254316.v1
title: Genome-wide epistatic interactions of litter size at birth in Chinese indigenous pigs

description: Improving litter size at birth (TNB) and the number of piglets born alive (NBA) are the main breeding goals related to litter traits, which are economically important. A better understanding of genetic architecture underlying TNB and NBA traits could increase pig production efficiency. However, most previous studies on these traits focus on additive genetic effects, while epistatic interactions underlying TNB and NBA traits has not yet been well investigated, which are essential to understand how traits-related genes interact. Herein, we conducted genome scans of epistatic interactions underlying TNB and NBA traits in a total of 150 Chinese indigenous pigs (75 Jinhua and 75 Shengxian Plotted pigs) with high throughput genomic data. Based on SNPs with high interaction values and connectivity scores, we identified eight promising candidate genes, namely <i>AKT2</i>, <i>TSC1</i>, <i>MTOR</i>, <i>PIK3R5</i>, <i>TIAM1</i>, <i>FGF14</i>, <i>RALB</i>, and <i>ROR2</i>, potentially associated with litter traits in pigs. Moreover, the underlying pathways, e.g., calcium ion transport, pointed out their roles in litter size related-traits. Our findings provide new insight into genetic architecture of litter traits in pigs and will benefit economic profits in pig production.
DOI: 10.6084/m9.figshare.12717188
title: EuroRun_day_night_dataset.csv

description: In a field survey, 16 teams from 11 European countries measured day- and night-time carbon dioxide fluxes in 34 streams. The measurements were performed in October 2016, January 2017, April 2017, and July 2017. Carbon dioxide fluxes with floating chambers equipped with carbon dioxide loggers were measured together with other biogeochemical parameters starting at midday (11am GMT) and midnight (11pm GMT).
DOI: 10.5281/zenodo.4625437
title: pull out test

description: data set of pull out mechanical test
DOI: 10.5281/zenodo.4625436
title: pull out test

description: data set of pull out mechanical test
DOI: 10.6084/m9.figshare.14254397
title: Calibration samples 706（400-1000 nm）.xlsx

description: This is a dataset for review.
DOI: 10.6084/m9.figshare.14254397.v1
title: Calibration samples 706（400-1000 nm）.xlsx

description: This is a dataset for review.
DOI: 10.5281/zenodo.4625480
title: Gap-filling Satellite Land Surface Temperature Over Heatwave Periods with Machine Learning

description: The frequency of heatwave events has increased in recent decades because of global warming. Satellite observed Land Surface Temperature (LST) is a widely used parameter for assessing heatwaves. It provides a wide spatial coverage compared to surface air temperature measured at weather stations. However, LST quality is limited by cloud contamination. Because heatwaves have a limited temporal frame, having a full and cloud-free complement of LST for that period is necessary. In this letter, we explore gap-filling of LST using spatial features like land cover, elevation and vegetation indices in a machine learning approach. We use a seamless open and free daily vegetation index product which is paramount to the success of our study. We create a Random Forest model that provides a ranking of features relevant for predicting LST. We compare the output of our model to an established spatiotemporal gap-filling algorithm to validate the predictive capability of our model. This study validates machine learning as a suitable tool for filling gaps in satellite LST. In addition, we acknowledge that while time is an important factor in predicting LST, additional information on vegetation can improve the predictions of a model This dataset covers gap-filled MODIS LST using machine learning for three heatwave periods in Estonia. The RMSE of the model on the test data is 1.37. Jupyter notebooks used in this project can be found at https://github.com/kwazineutin/Gapfilling-Satellite-LST-with-ML
DOI: 10.5281/zenodo.4625486
title: RosENet preprocessed training and validation datasets

description: Preprocessed protein-ligand voxels used in training and validation of RosENet https://doi.org/10.1021/acs.jcim.0c00075
description: {"references": ["Hussein Hassan-Harrirou, Ce Zhang, and Thomas Lemmin RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks"]}
DOI: 10.5281/zenodo.4625485
title: RosENet preprocessed training and validation datasets

description: Preprocessed protein-ligand voxels used in training and validation of RosENet https://doi.org/10.1021/acs.jcim.0c00075
description: {"references": ["Hussein Hassan-Harrirou, Ce Zhang, and Thomas Lemmin RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks"]}
DOI: 10.6084/m9.figshare.13635305
title: Data from: Early warning indicators of population collapse in a seasonal environment

description: Bi-seasonal (breeding, <b>b</b>, and <b>non-breeding</b>, <b>nb</b>) abundances (<b>count</b>) from experimental population of <i>Drosophila melanogaster</i> exposed to chronic season-specific habitat loss. Populations were exposed to habitat loss in either the breeding or non-breeding period (<b>seasonT</b>), and were subject to one of two rates of loss: 10% or 20% per generation (<b>lossT</b>). In addition, a subset of individuals were measured from half of the replicate populations (<b>rep</b>; <b>treat_rep</b>). From each individual, measures of locomotion (<b>activity</b>; <b>crosses</b>) were collected using a Drosophila activity monitor, in which the movements of individual flies are autonomously recorded using infrared light beams. These individuals were then frozen, dried, and weighed (<b>weight</b>). <br><b>See readme.txt for definitions of variables in both datasets.<br></b><br>The abundance data has been used to determine whether populations losing breeding and non-breeding habitat decline in different ways and whether the season of decline is detectable in simple vital rates. By combining the abundance and phenotype data, we explored whether the production of trait-based early warning indicators of population collapse differs between populations losing breeding and non-breeding habitat.