cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8192742
title: Proof-of-concept AO telemetry data using the AOT standard format

description: Dataset containing a demonstration of AO telemetry data using the AOT standard format. Contains data from 5 different systems (CIAO, ERIS, GALACSI, NAOMI and PAPYRUS). The data is as follows: 4 CIAO files "CIAO#_*.fits" where # indicates the AT where the data was produced. 2 ERIS files, one in LGS (LTAO) mode and another in NGS (SCAO) mode. 1 GALACSI file. 4 NAOMI files "NAOMI#_*.fits" where # indicates the AT where the data was produced. 2 PAPYRUS files, one using a Shack-Hartmann wavefront sensor (SHWFS) and another using a Pyramid wavefront sensor (PWFS). GALACSI, CIAO, NAOMI and ERIS data were gathered under ESO's program IDs 60.A-9278(B), 60.A-9278(C), 60.A-9278(D) and 60.A-9278(E) respectively. The data was translated via the functions provided in the Python package <em>aotpy</em> (10.5281/zenodo.8187230). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101004719 (OPTICON–RadioNet Pilot).
DOI: 10.22021/bbldntz202308
title: The Linked Open British National Bibliography – Books. 1950/2023-08 – N-Triples
DOI: 10.22021/bbldrdfz202308
title: The Linked Open British National Bibliography – Books. 1950/2023-08 – RDF/XML
DOI: 10.5281/zenodo.8310089
title: Datasets for article "Robot Self-Calibration Using Actuated 3D Sensors"

description: Real and sythetic datasets used in artilcle "Robot Self-Calibration Using Actuated 3D Sensors". For each recodring of a calibration scene is there is a ROS bag file holding a single message of type vision_3d_msgs/Actuated3dRecording.
DOI: 10.5281/zenodo.8310088
title: Datasets for article "Robot Self-Calibration Using Actuated 3D Sensors"

description: Real and sythetic datasets used in artilcle "Robot Self-Calibration Using Actuated 3D Sensors". For each recodring of a calibration scene is there is a ROS bag file holding a single message of type vision_3d_msgs/Actuated3dRecording.
DOI: 10.22021/bsldntz202308
title: The Linked Open British National Bibliography – Serials. 1950/2023-08 – N-Triples
DOI: 10.22021/bsldrdfz202308
title: The Linked Open British National Bibliography – Serials. 1950/2023-08 – RDF/XML
DOI: 10.22021/bcldntz202308
title: The Linked Open British National Bibliography – Forthcoming Books. 2023-08 – N-Triples
DOI: 10.22021/bcldrdfz202308
title: The Linked Open British National Bibliography – Forthcoming Books. 2023-08 – RDF/XML
DOI: 10.5281/zenodo.8316266
title: Figure Data for "Continuous Estimates of Glacier Mass Balance in High Mountain Asia Based on ICESat-1,2 and GRACE/GRACE Follow-On"

description: Figure Data for "Continuous Estimates of Glacier Mass Balance in High Mountain Asia Based on ICESat-1,2 and GRACE/GRACE Follow-On" Data"
DOI: 10.5281/zenodo.8316265
title: Figure Data for "Continuous Estimates of Glacier Mass Balance in High Mountain Asia Based on ICESat-1,2 and GRACE/GRACE Follow-On"

description: Figure Data for "Continuous Estimates of Glacier Mass Balance in High Mountain Asia Based on ICESat-1,2 and GRACE/GRACE Follow-On" Data"
DOI: 10.34740/kaggle/dsv/6414979
title: MoviesDatasets
DOI: 10.5281/zenodo.8316278
title: Data: Behavioral and ecological responses of an invasive freshwater mussel to noise pollution

description: Here you will find the results after analyzing images of mussel aggregates, films of valvar activity and algae counts.<br> You will also find the R script used to process this data in order to publish in a peer-reviewed journal.
DOI: 10.5281/zenodo.8316277
title: Data: Behavioral and ecological responses of an invasive freshwater mussel to noise pollution

description: Here you will find the results after analyzing images of mussel aggregates, films of valvar activity and algae counts.<br> You will also find the R script used to process this data in order to publish in a peer-reviewed journal.
DOI: 10.6084/m9.figshare.22680646.v2
title: Formato para Programa Analítico (actualizado 04-09-2023)

description: Un formato personal del Programa Analítico de Estudio, acorde al Plan de Estudio 2022.
DOI: 10.5517/ccdc.csd.cc24vnvj
title: CCDC 1991838: Experimental Crystal Structure Determination

description: Related Article: XiangSheng Cheng, Weihong Fei, Zihao Luo, Jianjun Li, Zhen Wang, Weijun Yao|2023|CSD Communication|||
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.cc25tsvn
title: CCDC 2020792: Experimental Crystal Structure Determination

description: Related Article: Jiangong Yang|2023|CSD Communication|||
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.cc25tszs
title: CCDC 2020796: Experimental Crystal Structure Determination

description: Related Article: Jiangong Yang|2023|CSD Communication|||
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.cc2c0b91
title: CCDC 2175062: Experimental Crystal Structure Determination

description: Related Article: Duhao Sun, Bing Zhou, Lanqin Liu, Xiaoyun Chen, Hong Hou, Ying Han, Chaoguo Yan, Yaocheng Shi, Shaoqun Zhu|2023|Org.Lett.|25|4677|doi:10.1021/acs.orglett.3c01551
description: Related Article: Qi Cheng|2023|CSD Communication|||
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.24081906
title: Raw_data_NIHSS_article_#86688

description: The data set includes clinical, neurological, and volumetric measures collected from a sample of 35 patients with middle cerebral artery infractions.
DOI: 10.6084/m9.figshare.24081906.v1
title: Raw_data_NIHSS_article_#86688

description: The data set includes clinical, neurological, and volumetric measures collected from a sample of 35 patients with middle cerebral artery infractions.
DOI: 10.6084/m9.figshare.24081936
title: SEX - SCHOOL

description: Sexuality Education goes to school
DOI: 10.6084/m9.figshare.24081936.v1
title: SEX - SCHOOL

description: Sexuality Education goes to school
DOI: 10.5517/ccdc.csd.cc2cj402
title: CCDC 2190243: Experimental Crystal Structure Determination

description: Related Article: Ji-Jun Chen, Jia-Heng Fang, Xuan-Yi Du, Jia-Yong Zhang, Jun-Qian Bian, Fu-Li Wang, Cheng Luan, Wei-Long Liu, Ji-Ren Liu, Xiao-Yang Dong, Zhong-Liang Li, Qiang-Shuai Gu, Zhe Dong, Xin-Yuan Liu|2023|CSD Communication|||
description: Related Article: Ji-Jun Chen, Jia-Heng Fang, Xuan-Yi Du, Jia-Yong Zhang, Jun-Qian Bian, Fu-Li Wang, Cheng Luan, Wei-Long Liu, Ji-Ren Liu, Xiao-Yang Dong, Zhong-Liang Li, Qiang-Shuai Gu, Zhe Dong, Xin-Yuan Liu|2023|Nature (London)|618|294|doi:10.1038/s41586-023-05950-8
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.cc2d1b1v
title: CCDC 2205806: Experimental Crystal Structure Determination

description: Related Article: LiJuan Liu|2023|CSD Communication|||
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.cc28pmcz
title: CCDC 2106151: Experimental Crystal Structure Determination

description: Related Article: Ping Lu|2023|CSD Communication|||
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.cc28pmd0
title: CCDC 2106152: Experimental Crystal Structure Determination

description: Related Article: Ping Lu|2023|CSD Communication|||
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.cc2fxnkl
title: CCDC 2261870: Experimental Crystal Structure Determination

description: Related Article: hao zheng|2023|CSD Communication|||
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.cc2fxxcn
title: CCDC 2262112: Experimental Crystal Structure Determination

description: Related Article: Shwetha JC|2023|CSD Communication|||
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.cc2fy2hz
title: CCDC 2262271: Experimental Crystal Structure Determination

description: Related Article: Nai-Chen Hsueh, Pin-Hsien Chen, Meng-Yang Chang|2023|Tetrahedron|143|133552|doi:10.1016/j.tet.2023.133552
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.cc2fy2j0
title: CCDC 2262272: Experimental Crystal Structure Determination

description: Related Article: Nai-Chen Hsueh, Pin-Hsien Chen, Meng-Yang Chang|2023|Tetrahedron|143|133552|doi:10.1016/j.tet.2023.133552
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.cc2fy88y
title: CCDC 2262450: Experimental Crystal Structure Determination

description: Related Article: Ka-Ming Tong, Jessica Toigo, Brian O. Patrick, Michael O. Wolf|2023|Inorg.Chem.|62|13662|doi:10.1021/acs.inorgchem.3c02124
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.cc2fy89z
title: CCDC 2262451: Experimental Crystal Structure Determination

description: Related Article: Ka-Ming Tong, Jessica Toigo, Brian O. Patrick, Michael O. Wolf|2023|Inorg.Chem.|62|13662|doi:10.1021/acs.inorgchem.3c02124
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.cc2479qf
title: CCDC 1973234: Experimental Crystal Structure Determination

description: Related Article: Qi Cheng|2023|CSD Communication|||
description: Related Article: Duhao Sun, Bing Zhou, Lanqin Liu, Xiaoyun Chen, Hong Hou, Ying Han, Chaoguo Yan, Yaocheng Shi, Shaoqun Zhu|2023|Org.Lett.|25|4677|doi:10.1021/acs.orglett.3c01551
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.cc2fz9wm
title: CCDC 2263461: Experimental Crystal Structure Determination

description: Related Article: Somnath Arjun Borade, Sushma Naharwal, Himanshi Bhambri, Sanjay K. Mandal, Kiran Bajaj, Deepak Chitkara, Rajeev Sakhuja|2023|Org.Biomol.Chem.|21|6719|doi:10.1039/D3OB00916E
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.24081894
title: Long-term trends of local bird populations based on monitoring schemes: are they suitable for justifying management measures?

description: R workspace files containing list-type objects with the count data of the birds species analysed in <i>unmarked</i> format for each study site, La Muela and Carrascoy, respectively. Count data are composed the point sites in each study area in rows and the surveys in columns (corresponding to 2 visits per year).
DOI: 10.5281/zenodo.8316341
title: Crop orientations over 10 french departments

description: The dataset contains the data that have been used and generated in the frame of the publication "Determination of Crop Orientation from Very High Resolution Images" submitted by Lonjou V. et al in 2023 to Remote Sensing MDPI. It includes, for 10 french departments (1 folder per department), the plot definition with the associated crop type based on GPR, the parcel centroids and orientations (&gt; 190,000 records), and the ground truth that we manually established over more 1000 plots.
DOI: 10.5281/zenodo.8316340
title: Crop orientations over 10 french departments

description: The dataset contains the data that have been used and generated in the frame of the publication "Determination of Crop Orientation from Very High Resolution Images" submitted by Lonjou V. et al in 2023 to Remote Sensing MDPI. It includes, for 10 french departments (1 folder per department), the plot definition with the associated crop type based on GPR, the parcel centroids and orientations (&gt; 190,000 records), and the ground truth that we manually established over more 1000 plots.
DOI: 10.34740/kaggle/dsv/6414703
title: Online Retail busniess
DOI: 10.48490/pnhk-9z33
title: AR6 WGII Data for Figure TS.5(b): Global distribution of biodiversity loss
DOI: 10.5281/zenodo.8316298
title: CIFAR-10-R dataset

description: Towards Realistic Out-of-Distribution Detection: A Novel Evaluation Framework for Improving Generalization in OOD Detection: This paper presents a novel evaluation framework for Out-of-Distribution (OOD) detection that aims to assess the performance of machine learning models in more realistic settings. We observed that the real-world requirements for testing OOD detection methods are not satisfied by the current testing protocols. They usually encourage methods to have a strong bias towards a low level of diversity in normal data. To address this limitation, we propose new OOD test datasets (CIFAR-10-R, CIFAR-100-R, and ImageNet-30-R) that can allow researchers to benchmark OOD detection performance under realistic distribution shifts. Additionally, we introduce a Generalizability Score (GS) to measure the generalization ability of a model during OOD detection. Our experiments demonstrate that improving the performance on existing benchmark datasets does not necessarily improve the usability of OOD detection models in real-world scenarios. While leveraging deep pre-trained features has been identified as a promising avenue for OOD detection research, our experiments show that state-of-the-art pre-trained models tested on our proposed datasets suffer a significant drop in performance. To address this issue, we propose a post-processing stage for adapting pre-trained features under these distribution shifts before calculating the OOD scores, which significantly enhances the performance of state-of-the-art pre-trained models on our benchmarks.
DOI: 10.5281/zenodo.8316297
title: CIFAR-10-R dataset

description: Towards Realistic Out-of-Distribution Detection: A Novel Evaluation Framework for Improving Generalization in OOD Detection: This paper presents a novel evaluation framework for Out-of-Distribution (OOD) detection that aims to assess the performance of machine learning models in more realistic settings. We observed that the real-world requirements for testing OOD detection methods are not satisfied by the current testing protocols. They usually encourage methods to have a strong bias towards a low level of diversity in normal data. To address this limitation, we propose new OOD test datasets (CIFAR-10-R, CIFAR-100-R, and ImageNet-30-R) that can allow researchers to benchmark OOD detection performance under realistic distribution shifts. Additionally, we introduce a Generalizability Score (GS) to measure the generalization ability of a model during OOD detection. Our experiments demonstrate that improving the performance on existing benchmark datasets does not necessarily improve the usability of OOD detection models in real-world scenarios. While leveraging deep pre-trained features has been identified as a promising avenue for OOD detection research, our experiments show that state-of-the-art pre-trained models tested on our proposed datasets suffer a significant drop in performance. To address this issue, we propose a post-processing stage for adapting pre-trained features under these distribution shifts before calculating the OOD scores, which significantly enhances the performance of state-of-the-art pre-trained models on our benchmarks.
DOI: 10.6084/m9.figshare.24081996
title: Virulence Factors Acidovorax avenae subsp. avenae

description: File contains data used for statistical analysis of different virulence factors of Acidovorax avenae subsp. avenae.
DOI: 10.6084/m9.figshare.24081996.v1
title: Virulence Factors Acidovorax avenae subsp. avenae

description: File contains data used for statistical analysis of different virulence factors of Acidovorax avenae subsp. avenae.
DOI: 10.5281/zenodo.8301542
title: Set of land subsidence model parameters and ensemble predictions in Kawajima (Japan)

description: Data and Python codes used to create all figures in the Akitaya & Aichi manuscript (submitted to Journal of Geophysical Research: Solid Earth). The Python codes reproduce most of the figures in the manuscript, but the figure details were modified by Adobe Illustrator from pdf files output by the codes.
DOI: 10.5281/zenodo.8301541
title: Data observed at Kawajima land subsidence observatory (Japan) and ensemble model

description: This data set contains all data necessary to reproduce the results of the manuscript submitted by Akitaya & Aichi. The data set includes hydraulic head and land subsidence data observed at the Kawajima land subsidence observatory (Japan), and an ensemble model parameter set constructed using the evolutionary multimodal algorithm, ensemble simulation results, and predictive uncertainty analysis results obtained through ensemble model output statistics. Please refer to the "readme.txt" file provided in each individual folder for detailed instructions on how to read the data.
DOI: 10.5281/zenodo.8316450
title: Data observed at Kawajima land subsidence observatory (Japan) and ensemble model

description: This data set contains all data necessary to reproduce the results of the manuscript submitted by Akitaya & Aichi. The data set includes hydraulic head and land subsidence data observed at the Kawajima land subsidence observatory (Japan), and an ensemble model parameter set constructed using the evolutionary multimodal algorithm, ensemble simulation results, and predictive uncertainty analysis results obtained through ensemble model output statistics. Please refer to the "readme.txt" file provided in each individual folder for detailed instructions on how to read the data.
DOI: 10.6084/m9.figshare.24081966
title: rawdata.vcf.gz

description: VCF with unfiltered SNPs. Distinct list of SNPs can be used to generate datasets used in the manuscript.
DOI: 10.6084/m9.figshare.24081984
title: snps.popstr.txt

description: List of SNPs used in population structure analyses.
DOI: 10.6084/m9.figshare.24081984.v1
title: snps.popstr.txt

description: List of SNPs used in population structure analyses.
DOI: 10.6084/m9.figshare.24081987
title: snps.fsc.txt

description: List of SNPs used in demographic modelling.
DOI: 10.6084/m9.figshare.24081987.v1
title: snps.fsc.txt

description: List of SNPs used in demographic modelling.
DOI: 10.6084/m9.figshare.24081990
title: snps.introgression.txt

description: List of SNPs used in crop introgression analyses.
DOI: 10.6084/m9.figshare.24081990.v1
title: snps.introgression.txt

description: List of SNPs used in crop introgression analyses.