cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccz7krh
title: CCDC 901007: Experimental Crystal Structure Determination

description: Related Article: Ya-Guang Sun, Ke-Long Li, Zhen-He Xu, Tian-Yi Lv, Shu-Ju Wang, Li-Xin You, Fu Ding|2013|J.Coord.Chem.|66|2455|doi:10.1080/00958972.2013.806655
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.ccz7v56
title: CCDC 901268: Experimental Crystal Structure Determination

description: Related Article: Yancheng Han, Qiyun Feng, Yongfang Zhang, Yunping Zhang, Wei Yao|2017|Polyhedron|121|206|doi:10.1016/j.poly.2016.10.010
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/ccz7ztz
title: CCDC 901412: Experimental Crystal Structure Determination

description: Related Article: Motoko Akita, Hideyuki Seto, Reiko Aoyama, Junko Kimura and Keiji Kobayashi|2012|Molecules|17|13879|doi:10.3390/molecules171213879
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/ccz7zv0
title: CCDC 901413: Experimental Crystal Structure Determination

description: Related Article: Motoko Akita, Hideyuki Seto, Reiko Aoyama, Junko Kimura and Keiji Kobayashi|2012|Molecules|17|13879|doi:10.3390/molecules171213879
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/ccz7zsy
title: CCDC 901411: Experimental Crystal Structure Determination

description: Related Article: Motoko Akita, Hideyuki Seto, Reiko Aoyama, Junko Kimura and Keiji Kobayashi|2012|Molecules|17|13879|doi:10.3390/molecules171213879
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/ccz7zqw
title: CCDC 901409: Experimental Crystal Structure Determination

description: Related Article: Motoko Akita, Hideyuki Seto, Reiko Aoyama, Junko Kimura and Keiji Kobayashi|2012|Molecules|17|13879|doi:10.3390/molecules171213879
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/ccz7zrx
title: CCDC 901410: Experimental Crystal Structure Determination

description: Related Article: Motoko Akita, Hideyuki Seto, Reiko Aoyama, Junko Kimura and Keiji Kobayashi|2012|Molecules|17|13879|doi:10.3390/molecules171213879
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/ccz8csc
title: CCDC 901783: Experimental Crystal Structure Determination

description: Related Article: Nicole D. Harrold, Gregory L. Hillhouse|2013|Chemical Science|4|4011|doi:10.1039/C3SC51517F
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/ccz8cq9
title: CCDC 901781: Experimental Crystal Structure Determination

description: Related Article: Nicole D. Harrold, Gregory L. Hillhouse|2013|Chemical Science|4|4011|doi:10.1039/C3SC51517F
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/ccz8crb
title: CCDC 901782: Experimental Crystal Structure Determination

description: Related Article: Nicole D. Harrold, Gregory L. Hillhouse|2013|Chemical Science|4|4011|doi:10.1039/C3SC51517F
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/ccz8cn7
title: CCDC 901779: Experimental Crystal Structure Determination

description: Related Article: Nicole D. Harrold, Gregory L. Hillhouse|2013|Chemical Science|4|4011|doi:10.1039/C3SC51517F
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/ccz8cp8
title: CCDC 901780: Experimental Crystal Structure Determination

description: Related Article: Nicole D. Harrold, Gregory L. Hillhouse|2013|Chemical Science|4|4011|doi:10.1039/C3SC51517F
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/ccz927k
title: CCDC 902448: Experimental Crystal Structure Determination

description: Related Article: Zhenhua Zhang, Lina Chang, Shaozhong Wang, Huaqin Wang, Zhu-Jun Yao|2013|RSC Advances|3|18446|doi:10.1039/C3RA43075H
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/ccz97zg
title: CCDC 902626: Experimental Crystal Structure Determination

description: Related Article: Yi Zhao, Li-Li Liang, Kai Chen, Ting Zhang, Xin Xiao, Yun-Qian Zhang, Zhu Tao, Sai-Feng Xue, Qian-Jiang Zhu|2013|CrystEngComm|15|7987|doi:10.1039/C3CE40568K
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: 10.15468/dl.8adlxg
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057384-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.feo2rm
title: Occurrence Download

description: A dataset containing 894692671 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 894692671 records from 16457 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023920-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aub2qc
title: Occurrence Download

description: A dataset containing 4116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Lophura diardi (Bonaparte, 1856)"
 ]
}

 The dataset includes 4116 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015298-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/jxu6dc
title: Data for "Surfacing Semantic Orthogonality Across Model Safety Benchmarks: A Multi-Dimensional Analysis"

description: Various AI safety datasets have been developed to measure LLMs against evolving
interpretations of harm. Our evaluation of five recently published open-source safety
benchmarks reveals distinct semantic clusters using UMAP dimensionality reduction and kmeans clustering (silhouette score: 0.470). We identify six primary harm categories with varying benchmark representation. GretelAI, for example, focuses heavily on privacy concerns, while WildGuardMix emphasizes self-harm scenarios. Significant differences in prompt length distribution suggests confounds to data collection and interpretations of harm as well as offer possible context. Our analysis quantifies benchmark orthogonality among AI benchmarks, allowing for transparency in coverage gaps despite topical similarities. Our quantitative framework for analyzing semantic orthogonality across safety benchmarks enables more targeted development of datasets that comprehensively address the evolving landscape of harms in AI use, however that is defined in the future.
description: This dataset follows the steps for calculating sample size and is the concatenated dataset of benchmarks that have sampled the minimal rows for statistical significance of said calculations in differences between datasets, with all assumptions noted in the paper.
DOI: 10.5522/04/27929868
title: Data underpinning "Zero-shot ML Equalization in Coherent Optical Transmission: a First Experimental Demonstration"

description: All data files are *.txt files in a space-delimited format. The first row are the column titles, and subsequent rows are data.fig5_loss_curve.txt: Data for Figure 5 describing the MSE loss in simulation and experimental Q-factor (at optimal launch power) during the training process. The "epoch" column contains the training epoch, the "loss" column contains the MSE loss in simulation, and "qs" contain the experimental Q-factor.fig6_fibres.txt: Data for Figure 6 showing the experimental Q-factor vs launch power for different fibres. Each column title is in the format of "FIBRE-ml" for the Q-factor achieved by the neural network, and "FIBRE-conv" for the Q-factor achieved by the conventional linear DSP. "FIBRE" is one of: SSMF, NZDSF, PSCF, GI-MMF, each describing the Q-factor achieved over standard single-mode fibre, non-zero dispersion-shifted fibre, pure silica-core fibre, and graded-index multi-mode fibre respectively. Lastly, there is the "LP" column denoting the launch power in dBm.fig7_freqs.txt: Data for Figure 7 showing the experimental Q-factor vs launch power for different transmission frequencies over SSMF. Each column title is in the format of "FREQ-ml" for the Q-factor achieved by the neural network, and "FREQ-conv" for the Q-factor achieved by the conventional linear DSP. "FREQ" is one of 191.556, 192.175, 192.788, 193.414, 194.045, 194.67, and 195.31, each denoting the transmission frequency in THz. Lastly, there is the "LP" column denoting the launch power in dBm.fig8_pol_skew.txt: Data for Figure 8 showing the experimental Q-factor vs launch power for different polarisation skew introduced at the transmitter. Each column is in the format "Xps", where "X" can take the value of 7, 5, 3, 1, 0.7, 0.3, and 0, each denoting the polarisation skew in picoseconds. Lastly, there is the "LP" column denoting the launch power in dBm.fig9_ps_size: Data for Figure 9 showing the experimental Q-factor vs launch power for different training sequence sizes. This folder contains multiple space-delimited text files title "psN", where N denotes the length of the pilot sequence in symbols . Each column is titled with one of SSMF, NZDSF, GI-MMF, or PSCF to denote the different fibres, and contains a "LP" column to denote the launch power in dBm.<br>
DOI: 10.5522/04/27929868.v1
title: Data underpinning "Zero-shot ML Equalization in Coherent Optical Transmission: a First Experimental Demonstration"

description: All data files are *.txt files in a space-delimited format. The first row are the column titles, and subsequent rows are data.fig5_loss_curve.txt: Data for Figure 5 describing the MSE loss in simulation and experimental Q-factor (at optimal launch power) during the training process. The "epoch" column contains the training epoch, the "loss" column contains the MSE loss in simulation, and "qs" contain the experimental Q-factor.fig6_fibres.txt: Data for Figure 6 showing the experimental Q-factor vs launch power for different fibres. Each column title is in the format of "FIBRE-ml" for the Q-factor achieved by the neural network, and "FIBRE-conv" for the Q-factor achieved by the conventional linear DSP. "FIBRE" is one of: SSMF, NZDSF, PSCF, GI-MMF, each describing the Q-factor achieved over standard single-mode fibre, non-zero dispersion-shifted fibre, pure silica-core fibre, and graded-index multi-mode fibre respectively. Lastly, there is the "LP" column denoting the launch power in dBm.fig7_freqs.txt: Data for Figure 7 showing the experimental Q-factor vs launch power for different transmission frequencies over SSMF. Each column title is in the format of "FREQ-ml" for the Q-factor achieved by the neural network, and "FREQ-conv" for the Q-factor achieved by the conventional linear DSP. "FREQ" is one of 191.556, 192.175, 192.788, 193.414, 194.045, 194.67, and 195.31, each denoting the transmission frequency in THz. Lastly, there is the "LP" column denoting the launch power in dBm.fig8_pol_skew.txt: Data for Figure 8 showing the experimental Q-factor vs launch power for different polarisation skew introduced at the transmitter. Each column is in the format "Xps", where "X" can take the value of 7, 5, 3, 1, 0.7, 0.3, and 0, each denoting the polarisation skew in picoseconds. Lastly, there is the "LP" column denoting the launch power in dBm.fig9_ps_size: Data for Figure 9 showing the experimental Q-factor vs launch power for different training sequence sizes. This folder contains multiple space-delimited text files title "psN", where N denotes the length of the pilot sequence in symbols . Each column is titled with one of SSMF, NZDSF, GI-MMF, or PSCF to denote the different fibres, and contains a "LP" column to denote the launch power in dBm.<br>
DOI: 10.6084/m9.figshare.29135207
title: A Closer Look at Magnesium Supplementation in Normo-magnesemic Patients- Does Formulation Make a Difference?-anonymus.xlsx

description: A Closer Look at Magnesium Supplementation in Normomagnesemic Patients: Does Formulation Make a Difference? study excel data.
DOI: 10.6084/m9.figshare.29135207.v1
title: A Closer Look at Magnesium Supplementation in Normo-magnesemic Patients- Does Formulation Make a Difference?-anonymus.xlsx

description: A Closer Look at Magnesium Supplementation in Normomagnesemic Patients: Does Formulation Make a Difference? study excel data.
DOI: 10.15468/dl.jva4ad
title: Occurrence Download

description: A dataset containing 9226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Polanisia Raf."
 ]
}

 The dataset includes 9226 records from 196 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015299-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29134823
title: <b>Multi-object detection method based on YOLOv9 for labor protection equipment</b><b> </b><b>wear</b><b>ing</b><b> </b><b>condition </b><b>of offshore platform operators</b>

description: Based on the work process monitoring requirements of offshore platform operators, the multi-object detection method for labor protection equipment wearing condition based on YOLOv9 model is proposed, the optimization method for YOLOv9 model based on CBAM attention mechanism and Focaler-iou bounding box loss function is studied, and the superiority of the optimized model is confirmed by a series of ablation experiments. Aiming at the missed detection problem of small targets of labor protection equipment, SAHI algorithm is introduced to slice the input image into multiple pieces, and the very small labor protection targets has been detected by the slicing detection method. A positive and negative samples combined detection method is designed to effectively reduce the false detection or missed detection rate of each labor protection equipment. The pictures with real labor protection samples in offshore platform operating scenes are used to train and test the models, and the research results have been successfully applied in the offshore platform, and the ideal detection results have been achieved.
DOI: 10.6084/m9.figshare.29134823.v1
title: <b>Multi-object detection method based on YOLOv9 for labor protection equipment</b><b> </b><b>wear</b><b>ing</b><b> </b><b>condition </b><b>of offshore platform operators</b>

description: Based on the work process monitoring requirements of offshore platform operators, the multi-object detection method for labor protection equipment wearing condition based on YOLOv9 model is proposed, the optimization method for YOLOv9 model based on CBAM attention mechanism and Focaler-iou bounding box loss function is studied, and the superiority of the optimized model is confirmed by a series of ablation experiments. Aiming at the missed detection problem of small targets of labor protection equipment, SAHI algorithm is introduced to slice the input image into multiple pieces, and the very small labor protection targets has been detected by the slicing detection method. A positive and negative samples combined detection method is designed to effectively reduce the false detection or missed detection rate of each labor protection equipment. The pictures with real labor protection samples in offshore platform operating scenes are used to train and test the models, and the research results have been successfully applied in the offshore platform, and the ideal detection results have been achieved.
DOI: 10.4121/2d14c7a1-e707-4adb-939d-1556a19d9f76.v1
title: Dataset for 'Novel miniaturised microbial electrosynthesis reactor: A study on replicability'

description: The analysed data and full scripts for the ECSA determination, onset potential determination, micro-CT data analysis and DTW distance calculation used in the paper 'Novel Miniaturised Microbial Electrosynthesis Reactor: A Study on Replicability'.Python version 3.10.13 with packages numpy, pandas, os, scipy.optimize, scipy.stats, sklearn.metrics, dtaidistance, math, skfda, kneed, matplotlib.pyplot are required to run the .py files. Ensure all packages are installed before running the scripts. Data files required to run the code (.xlsx and .csv format) are included in the relevant folders.
DOI: 10.15468/dl.vvmxa8
title: Occurrence Download

description: A dataset containing 39307 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Puccinia urticata (Link) F.Kern, Puccinia caricina DC., Clasterosporium caricinum Schwein., Trichonectria hyalocristata Scheuer, Anthomyza neglecta Collin, 1944, Anagnota bicolor (Meigen, 1838), Acanthophiobolus helicosporus (Berk. & Broome) J.Walker, Arthrinium sporophleum Kunze, Belonopsis asteroma (Fuckel) Aebi, Arthrinium caricicola Kunze & J.C.Schmidt, Apiospora montagnei Sacc., Anthostomella limitata Sacc., Ceriophora palustris (Sacc.) Höhn., Anthostomella punctulata (Roberge ex Desm.) Sacc., Arthrinium puccinioides Kunze, Ciboria aschersoniana (Henn. & Plöttn.) Whetzel, Didymella proximella (P.Karst.) Sacc., Massarina igniaria (C.Booth) Aptroot, Micropeziza cornea (Berk. & Broome) Nannf., Mollisia dactyligluma Cooke, Periconia atra Corda, Neottiospora caricina (Desm.) Höhn., Periconia digitata (Cooke) Sacc., Periconia curta (Berk.) E.W.Mason & M.B.Ellis, Niesslia exosporioides (Desm.) G.Winter, Periconia laminella E.W.Mason & M.B.Ellis, Periconia hispidula (Pers.) E.W.Mason & M.B.Ellis, Periconia funerea (Ces.) E.W.Mason & M.B.Ellis, Psilachnum lateritioalbum (P.Karst.) Höhn., Stagonospora caricis (Oudem.) Sacc., Stagonospora macropycnidia Cunnell, Stagonospora anglica Cunnell, Stagonospora caricinella Brunaud, Taphrophila cornu-capreoli Scheuer, Stagonospora paludosa (Sacc. & Speg.) Sacc., Volutella arundinis Desm., Volutella melaloma Berk. & Broome, Epithele typhae (Pers.) Pat., Cerodontha eucaricis Nowakowski, 1967, Donacia impressa Paykull, 1799, Donacia aquatica (Linnaeus, 1758), Physalospora scirpi (Gutner) Arx, Myrothecium cinctum (Corda) Sacc., Farysia thuemenii (A.A.Fisch.Waldh.) Nannf., Puccinia urticata var. urticae-acutiformis (Kleb.) Zwetko, Oedancala dorsalis (Say, 1831), Coenonympha oedippus Fabricius, 1787, Cicadula longiventris (Sahlberg, 1871), Kelisia praecox Haupt, 1935, Wagneriala incisa (Then, 1897))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 39307 records from 669 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015300-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29135177
title: uci_har_and_capture24

description: This is the processed uci_har and capture24 dataset. Please extract theme under "notebooks -&gt; data' folder so that the folder "notebooks/data/uci_har" and "notebooks/data/capture24" exists. The final folder structure should look like this <br>notebooks/data/├── speech_commands/├── FashionMNIST/├── capture24/├── uci_har/├── MNIST/├── cifar-100-python/└── cifar-10-batches-py/