cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24174973.v1
title: Raw data_1 from A tumour-spheroid manufacturing and cryopreservation process that yields a highly reproducible product ready for direct use in drug screening assays

description: If it were possible to purchase tumour-spheroids as a standardized product, ready for direct use in assays, this may contribute to greater research reproducibly, potentially reducing costs. Herein, we describe a workflow where uniformly sized cancer tumour-spheroids are mass-produced using microwell culture, cryopreserved with high viability, and then cultured in neutral buoyancy media for drug testing. C4-2B prostate cancer or MCF-7 breast cancer cells amalgamated into uniform tumour-spheroids after 48 h of culture. Tumour-spheroids formed from 100 cells each tolerated the cryopreservation process marginally better than tumour-spheroids formed from 200 or 400 cells. Post-thaw, tumour-spheroid metabolic activity was significantly reduced, suggesting mitochondrial damage. Metabolic function was rescued by thawing the tumour-spheroids into medium supplemented with 10 µM <i>N</i>-Acetyl-l-cysteine (NAC). Following thaw, the neutral buoyancy media, Happy Cell, was used to maintain tumour-spheroids as discrete tissues during drug testing. Fresh and cryopreserved C4-2B or MCF-7 tumour-spheroids responded similarly to titrations of Docetaxel. This protocol will contribute to a future where tumour-spheroids will be available for purchase as reliable and reproducible products, allowing laboratories to efficiently replicate and build on published research, in many cases making tumour-spheroids simply another cell culture reagent.
DOI: 10.25422/azu.data.21997601.v1
title: Steward Observatory LEO Satellite Photometric Survey

description: The Steward Observatory LEO Satellite Photometric Survey is a comprehensive observational survey to characterize the apparent brightness of the Starlink and OneWeb low Earth orbit satellites and evaluate the potential impact to astronomy. Included are the photometric and astrometric measurements for each satellite observed from May 2020 to December 2022. Only satellites with measured position error of less than 0.5 degrees are included.In addition to visual magnitudes, we also present two new metrics: the expected photon flux and the effective albedo. The expected photon flux metric assesses the potential impact to astronomy sensors by predicting the flux for a satellite trail in an image from a theoretical 1-meter class telescope and sensor. The effective albedo metric assesses where a satellite is more reflective than baseline, which ties to the physical structure of the satellite and indicates the potential for brightness-reducing design changes.Please see the published article for a complete explanation of the observational survey and dataset creation.<i><br></i><i>For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu</i><br>
DOI: 10.25422/azu.data.21997601
title: Steward Observatory LEO Satellite Photometric Survey

description: The Steward Observatory LEO Satellite Photometric Survey is a comprehensive observational survey to characterize the apparent brightness of the Starlink and OneWeb low Earth orbit satellites and evaluate the potential impact to astronomy. Included are the photometric and astrometric measurements for each satellite observed from May 2020 to December 2022. Only satellites with measured position error of less than 0.5 degrees are included.In addition to visual magnitudes, we also present two new metrics: the expected photon flux and the effective albedo. The expected photon flux metric assesses the potential impact to astronomy sensors by predicting the flux for a satellite trail in an image from a theoretical 1-meter class telescope and sensor. The effective albedo metric assesses where a satellite is more reflective than baseline, which ties to the physical structure of the satellite and indicates the potential for brightness-reducing design changes.Please see the published article for a complete explanation of the observational survey and dataset creation.<i><br></i><i>For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu</i><br>
DOI: 10.5281/zenodo.8367400
title: Data for the study: Decision-Making Support for Data Integration in Cyber-Physical-System Architectures

description: The folder contains the scripts and models used in this study
DOI: 10.5281/zenodo.8367399
title: Data for the study: Decision-Making Support for Data Integration in Cyber-Physical-System Architectures

description: The folder contains the scripts and models used in this study
DOI: 10.5281/zenodo.8367372
title: Contextual power vs. place attachment

description: This study focuses on investigating pro-environmental behavior in the context of tourism, and therefore, the target population consists of individuals who have participated in tourism activities. A questionnaire survey was employed as the research method, and data was collected through online electronic surveys and other means. The survey was conducted from May 1, 2023, to June 1, 2023, and a total of 400 questionnaires were collected. After eliminating invalid responses, a total of 355 valid questionnaires were included in the analysis.
DOI: 10.5281/zenodo.8367371
title: Contextual power vs. place attachment

description: This study focuses on investigating pro-environmental behavior in the context of tourism, and therefore, the target population consists of individuals who have participated in tourism activities. A questionnaire survey was employed as the research method, and data was collected through online electronic surveys and other means. The survey was conducted from May 1, 2023, to June 1, 2023, and a total of 400 questionnaires were collected. After eliminating invalid responses, a total of 355 valid questionnaires were included in the analysis.
DOI: 10.5517/ccdc.csd.cc25z5r3
title: CCDC 2025005: Experimental Crystal Structure Determination

description: Related Article: Jorge Lozano-Juste, Lourdes Infantes, Irene Garcia-Maquilon, Rafael Ruiz-Partida, Ebe Merilo, Juan Luis Benavente, Adrian Velazquez-Campoy, Alberto Coego, Mar Bono, Javier Forment, Begoña Pampín, Paolo Destito, Adrián Monteiro, Ramón Rodríguez, Jacobo Cruces, Pedro L. Rodriguez, Armando Albert|2023|Sci. Adv.|9|eade994|doi:10.1126/sciadv.ade9948
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.cc25z5s4
title: CCDC 2025006: Experimental Crystal Structure Determination

description: Related Article: Jorge Lozano-Juste, Lourdes Infantes, Irene Garcia-Maquilon, Rafael Ruiz-Partida, Ebe Merilo, Juan Luis Benavente, Adrian Velazquez-Campoy, Alberto Coego, Mar Bono, Javier Forment, Begoña Pampín, Paolo Destito, Adrián Monteiro, Ramón Rodríguez, Jacobo Cruces, Pedro L. Rodriguez, Armando Albert|2023|Sci. Adv.|9|eade994|doi:10.1126/sciadv.ade9948
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.cc25z5t5
title: CCDC 2025007: Experimental Crystal Structure Determination

description: Related Article: Jorge Lozano-Juste, Lourdes Infantes, Irene Garcia-Maquilon, Rafael Ruiz-Partida, Ebe Merilo, Juan Luis Benavente, Adrian Velazquez-Campoy, Alberto Coego, Mar Bono, Javier Forment, Begoña Pampín, Paolo Destito, Adrián Monteiro, Ramón Rodríguez, Jacobo Cruces, Pedro L. Rodriguez, Armando Albert|2023|Sci. Adv.|9|eade994|doi:10.1126/sciadv.ade9948
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.cc2713s6
title: CCDC 2056657: Experimental Crystal Structure Determination

description: Related Article: Guorong Lei, Ye Zhong, Yiqiang Xu, Fan Yang, Jiandong Bai, Zhimin Li, Jianguo Zhang, Tonglai Zhang|2021|Chin.J.Chem.|39|1193|doi:10.1002/cjoc.202000672
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.cc2713t7
title: CCDC 2056658: Experimental Crystal Structure Determination

description: Related Article: Guorong Lei, Ye Zhong, Yiqiang Xu, Fan Yang, Jiandong Bai, Zhimin Li, Jianguo Zhang, Tonglai Zhang|2021|Chin.J.Chem.|39|1193|doi:10.1002/cjoc.202000672
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.cc2713v8
title: CCDC 2056659: Experimental Crystal Structure Determination

description: Related Article: Guorong Lei, Ye Zhong, Yiqiang Xu, Fan Yang, Jiandong Bai, Zhimin Li, Jianguo Zhang, Tonglai Zhang|2021|Chin.J.Chem.|39|1193|doi:10.1002/cjoc.202000672
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.cc29cpn1
title: CCDC 2126403: Experimental Crystal Structure Determination

description: Related Article: Dai Lei|2023|CSD Communication|||
description: Related Article: Lei Dai, Jiami Guo, Qingqin Huang, Yixin Lu|2022|Sci. Adv.|8|eadd2574|doi:10.1126/sciadv.add2574
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.8367244
title: Occurrence data download from GBIF for 115 tree species in Burundi

description: Cleaned occurrence data from GBIF for 115 tree species in Burundi
DOI: 10.5281/zenodo.8367243
title: Occurrence data download from GBIF for 115 tree species in Burundi

description: Cleaned occurrence data from GBIF for 115 tree species in Burundi
DOI: 10.6084/m9.figshare.24174930
title: <b>Datasets of phylogenetic relationships </b><b>within</b><b> the core eudicots based on multi-copy SOGs and </b><b>single-copy SOGs</b>.

description: gene trees on multi-copy SOGs and single-copy SOGs, and alignments on multi-copy SOGs and single-copy SOGs
DOI: 10.25345/c5q81534h
title: MassIVE MSV000092920 - Jatropha curcas root and leaf metabolomic analysis
title: This work present a large data set related to a non-target LC-MS/MS high-resolution metabolome analysis of the leaves and roots of Jatropha curcas. Besides its high protein contents, the seeds of J. curcas are also rich in oil, so the seeds are considered a potential source of raw material to produce biodiesel and a source of food for farm animals. The full exploitation of these potentials is hampered by the presence of a highly toxic class of diterpenoids, the phorbol esters (PE), both in the oil and in the seedcake derived from the extraction of the oil. The seeds are known to possess 6 different PE, and although their structures have been known for almost 30 years, the biosynthetic pathway of each one remains undetermined. However, there are indications that the enzyme casbene synthase is responsible for the first biosynthetic step. The leaves and roots of this species are also rich in several classes of diterpenes which by themselves have pharmacological potential not yet explored. For our analysis, we used two genotypes that are contrasting regarding the contents of phorbol esters: One genotype has a high level of phorbol esters (HPE), while the other has low levels of phorbol esters in the seeds (LPE). We were able to detect a total of 2032 features and applied multivariate statistical methods, such as PCA and heatmap with hierarchical clustering to analyze and visualize the deposition pattern of metabolites, with a focus on terpenoids. Our analysis allowed us to several new findings regarding the synthesis of PE in J. curcas, such as that only in HPE genotypes roots are found diterpenes with the tigliane skeleton. In contrast, the LPE genotype has a higher concentration and diversity of sesquiterpenes. Taking into consideration the results of our previous proteome analysis of seeds, roots, and leaves and the metabolome data presented in the manuscript, we suggest that the absence of PE in the LPE genotype may be the result of the absence of the enzymes responsible for the final biosynthetic steps, which in turn lead to the accumulation of sesquiterpenes this genotype.
DOI: 10.6084/m9.figshare.24175026
title: Phylogenetic Matrix and Character List

description: This dataset contains a morphological character matrix used for phylogenetic analyses testing the placement of a new fossil albatross.
DOI: 10.6084/m9.figshare.24175026.v1
title: Phylogenetic Matrix and Character List

description: This dataset contains a morphological character matrix used for phylogenetic analyses testing the placement of a new fossil albatross.
DOI: 10.5281/zenodo.8322104
title: ONERA Numerical Database Configuration A1 (static propeller)

description: This database contains the numerical results obtained by ONERA on the configuration A1, using ZDES mode 2 and ZDES mode 3 methods. The ZDES mode 3 approach offers an explicit resolution of the turbulent scales present in the outer region of the flat plate boundary layer and their interaction with the propeller.
DOI: 10.5281/zenodo.8322105
title: ONERA Numerical Database Configuration A1 (static propeller)

description: This database contains the numerical results obtained by ONERA on the configuration A1, using ZDES mode 2 and ZDES mode 3 methods. The ZDES mode 3 approach offers an explicit resolution of the turbulent scales present in the outer region of the flat plate boundary layer and their interaction with the propeller.
DOI: 10.5281/zenodo.8358761
title: H2020 ENODISE: UR3 Aeroacoustic processing Configuration A1

description: This database encompasses post-processing results derived from experiments conducted at the University of Bristol, specifically focusing on configuration A1. In this research, two distinct boundary layer thicknesses were taken into account, with an analysis comparing the performance of 3-bladed and 5-bladed propellers. The freestream velocity maintained a constant value of 20 m/s, and the chosen advance ratio (J) spanned the range of [0.56, 0.98]. The dataset includes information such as the Overall Sound Pressure Level, Haystacking Maps, and Spectra Scaling. These metrics are provided for four different scenarios, each involving variations in the number of blades and boundary layer thickness.
DOI: 10.5281/zenodo.8358762
title: H2020 ENODISE: UR3 Aeroacoustic processing Configuration A1

description: This database encompasses post-processing results derived from experiments conducted at the University of Bristol, specifically focusing on configuration A1. In this research, two distinct boundary layer thicknesses were taken into account, with an analysis comparing the performance of 3-bladed and 5-bladed propellers. The freestream velocity maintained a constant value of 20 m/s, and the chosen advance ratio (J) spanned the range of [0.56, 0.98]. The dataset includes information such as the Overall Sound Pressure Level, Haystacking Maps, and Spectra Scaling. These metrics are provided for four different scenarios, each involving variations in the number of blades and boundary layer thickness.
DOI: 10.5517/ccdc.csd.cc296ygy
title: CCDC 2121840: Experimental Crystal Structure Determination

description: Related Article: Daniela R. Ferreira, Paula C. Alves, Alexander M. Kirillov, Patrícia Rijo, Vânia André|2022|Frontiers in Chemistry|9|815827|doi:10.3389/fchem.2021.815827
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.cc296yhz
title: CCDC 2121841: Experimental Crystal Structure Determination

description: Related Article: Daniela R. Ferreira, Paula C. Alves, Alexander M. Kirillov, Patrícia Rijo, Vânia André|2022|Frontiers in Chemistry|9|815827|doi:10.3389/fchem.2021.815827
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.7697379
title: Ensemble BLUP, Machine Learning, and Deep Learning Models Predict Maize Yield Better Than Each Model Alone.

description: Data and scripts exploring ensembling strategies using the models developed in Kick et al., 2023 (see also 1, 2). Download all files to a single directory then run setup.sh or manually unzip using tar. <strong>Filename</strong> <strong>Description</strong> setup.sh Simple script that unzips zipped directories ext_data Reduced data from Kick et al. 2023 ext_data_notebooks Contains python notebooks containing analysis and R markdown file containing visualization of results. Python and R data objects are written to allow results to be read in instead of re-generated. output Folder containing a placeholder file. This research used resources provided by the United States Department of Agriculture’s Agricultural Research Service (project number 5070-21000-041-000-D). The SCINet project of the USDA Agricultural Research Service (project number 0500-00093-001-00-D) was instrumental in the training of the models used in this work. In addition, we would like to acknowledge those presently and historically involved in generating data for the Genomes to Fields Initiative.
DOI: 10.5281/zenodo.7697380
title: Ensemble BLUP, Machine Learning, and Deep Learning Models Predict Maize Yield Better Than Each Model Alone.

description: Data and scripts exploring ensembling strategies using the models developed in Kick et al., 2023 (see also 1, 2). Download all files to a single directory then run setup.sh or manually unzip using tar. <strong>Filename</strong> <strong>Description</strong> setup.sh Simple script that unzips zipped directories ext_data Reduced data from Kick et al. 2023 ext_data_notebooks Contains python notebooks containing analysis and R markdown file containing visualization of results. Python and R data objects are written to allow results to be read in instead of re-generated. output Folder containing a placeholder file. This research used resources provided by the United States Department of Agriculture’s Agricultural Research Service (project number 5070-21000-041-000-D). The SCINet project of the USDA Agricultural Research Service (project number 0500-00093-001-00-D) was instrumental in the training of the models used in this work. In addition, we would like to acknowledge those presently and historically involved in generating data for the Genomes to Fields Initiative.
DOI: 10.5281/zenodo.8183953
title: Ensemble BLUP, Machine Learning, and Deep Learning Models Predict Maize Yield Better Than Each Model Alone.

description: Data and scripts exploring ensembling strategies using the models developed in Kick et al., 2023 (see also 1, 2). Download all files to a single directory then run setup.sh or manually unzip using tar. <strong>Filename</strong> <strong>Description</strong> setup.sh Simple script that unzips zipped directories ext_data Reduced data from Kick et al. 2023 ext_data_notebooks Contains python notebooks containing analysis and R markdown file containing visualization of results. Python and R data objects are written to allow results to be read in instead of re-generated. output Folder containing a placeholder file. This research used resources provided by the United States Department of Agriculture’s Agricultural Research Service (project number 5070-21000-041-000-D). The SCINet project of the USDA Agricultural Research Service (project number 0500-00093-001-00-D) was instrumental in the training of the models used in this work. In addition, we would like to acknowledge those presently and historically involved in generating data for the Genomes to Fields Initiative.
DOI: 10.5281/zenodo.8367235
title: Ensemble BLUP, Machine Learning, and Deep Learning Models Predict Maize Yield Better Than Each Model Alone.

description: Data and scripts exploring ensembling strategies using the models developed in Kick et al., 2023 (see also 1, 2). Download all files to a single directory then run setup.sh or manually unzip using tar. <strong>Filename</strong> <strong>Description</strong> setup.sh Simple script that unzips zipped directories ext_data Reduced data from Kick et al. 2023 ext_data_notebooks Contains python notebooks containing analysis and R markdown file containing visualization of results. Python and R data objects are written to allow results to be read in instead of re-generated. output Folder containing a placeholder file. This research used resources provided by the United States Department of Agriculture’s Agricultural Research Service (project number 5070-21000-041-000-D). The SCINet project of the USDA Agricultural Research Service (project number 0500-00093-001-00-D) was instrumental in the training of the models used in this work. In addition, we would like to acknowledge those presently and historically involved in generating data for the Genomes to Fields Initiative.