cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2k2fqt
title: CCDC 2355836: Experimental Crystal Structure Determination

description: Related Article: Tomoyo Misawa-Suzuki, Yusuke Kataoka, Sota Mafune, Teresa Niwa, Hirotaka Nagao|2025|Dalton Trans.|54|2937|doi:10.1039/D4DT02833C
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.cc2lnnwt
title: CCDC 2403147: Experimental Crystal Structure Determination

description: Related Article: Arno Estival, Luis E. Blancarte, Loïc Pinto, Romane Pointis, Nathan Galas, Alix Sournia-Saquet, Laure Vendier, Rosa Santillan, Norberto Farfán, Jean-Baptiste Sortais, Mary Grellier, Antoine Simonneau|2025|Dalton Trans.|54|2860|doi:10.1039/D4DT03264K
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.cc2lnp10
title: CCDC 2403152: Experimental Crystal Structure Determination

description: Related Article: Arno Estival, Luis E. Blancarte, Loïc Pinto, Romane Pointis, Nathan Galas, Alix Sournia-Saquet, Laure Vendier, Rosa Santillan, Norberto Farfán, Jean-Baptiste Sortais, Mary Grellier, Antoine Simonneau|2025|Dalton Trans.|54|2860|doi:10.1039/D4DT03264K
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.cc2lnnyw
title: CCDC 2403149: Experimental Crystal Structure Determination

description: Related Article: Arno Estival, Luis E. Blancarte, Loïc Pinto, Romane Pointis, Nathan Galas, Alix Sournia-Saquet, Laure Vendier, Rosa Santillan, Norberto Farfán, Jean-Baptiste Sortais, Mary Grellier, Antoine Simonneau|2025|Dalton Trans.|54|2860|doi:10.1039/D4DT03264K
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.cc2k2frv
title: CCDC 2355837: Experimental Crystal Structure Determination

description: Related Article: Tomoyo Misawa-Suzuki, Yusuke Kataoka, Sota Mafune, Teresa Niwa, Hirotaka Nagao|2025|Dalton Trans.|54|2937|doi:10.1039/D4DT02833C
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.cc2k2fsw
title: CCDC 2355838: Experimental Crystal Structure Determination

description: Related Article: Tomoyo Misawa-Suzuki, Yusuke Kataoka, Sota Mafune, Teresa Niwa, Hirotaka Nagao|2025|Dalton Trans.|54|2937|doi:10.1039/D4DT02833C
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.cc2k2ftx
title: CCDC 2355839: Experimental Crystal Structure Determination

description: Related Article: Tomoyo Misawa-Suzuki, Yusuke Kataoka, Sota Mafune, Teresa Niwa, Hirotaka Nagao|2025|Dalton Trans.|54|2937|doi:10.1039/D4DT02833C
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.cc2k2fvy
title: CCDC 2355840: Experimental Crystal Structure Determination

description: Related Article: Tomoyo Misawa-Suzuki, Yusuke Kataoka, Sota Mafune, Teresa Niwa, Hirotaka Nagao|2025|Dalton Trans.|54|2937|doi:10.1039/D4DT02833C
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.14850175
title: Data Availability Statement
DOI: 10.15161/oar.it/212166
title: Carta Geologica d'Italia alla scala 1:50.000, F. 301 Fabriano

description: Foglio geologico alla scala 1:50.000 basato su rilevamenti alla scala 1:10.000 (eseguiti tra il 1973 e il 1977) comprensivo di legenda, schemi a cornice, sezioni geologiche.
DOI: 10.15161/oar.it/212167
title: Carta Geologica d'Italia alla scala 1:50.000, F. 301 Fabriano

description: Foglio geologico alla scala 1:50.000 basato su rilevamenti alla scala 1:10.000 (eseguiti tra il 1973 e il 1977) comprensivo di legenda, schemi a cornice, sezioni geologiche.
DOI: 10.21227/5mrz-7q54
title: OCT OMNIBUS

description: The database compiled for this study is a comprehensive and meticulously curated repository designed to evaluate the efficacy of anti-VEGF therapy in patients with Diabetic Macular Edema (DME). It includes clinical and imaging data from 193 diabetic patients, aged 18-70 years, who participated in a single-center, randomized, parallelgroup, double-masked clinical trial. The database encompasses detailed demographic and clinical information, such as age, gender, medical history, duration of diabetes, and baseline measurements like blood pressure and intraocular pressure. Pre-treatment data acquisition includes high-resolution Optical Coherence Tomography (OCT) images obtained using the Heidelberg Spectralis OCT system, providing detailed retinal morphology and macular thickness measurements. Key parameters such as Central Macular Thickness (CMT), baseline Best Corrected Visual Acuity (BCVA), plasma VEGFR-2 concentrations, and the duration of disease were recorded to establish baseline disease severity. Treatment data documents intervention details, including three consecutive monthly doses of Ranibizumab followed by laser photocoagulation, and control group data involving sham injections and laser therapy. Post-treatment data highlights visual acuity improvements, reduction in CMT, responder classification based on BCVA and CMT thresholds, and adverse event monitoring. The OCT imaging protocol followed a 20°×20° volume scan with 6 µm axial resolution over a 6×6 mm macular region, with derived numerical measurements for analysis. Data was processed and used to train a hybrid AI model using LSTM networks for clinical parameters, to predict treatment outcomes. The database adheres to strict anonymization and encryption standards to ensure data security and patient privacy. Its applications include research and development of predictive AI models, clinical decision support for personalized DME therapy, and education in AI-based ophthalmic analysis. This database serves as a robust foundation for advancing precision medicine and improving patient outcomes in retinal disease management.
DOI: 10.15151/esrf-dc-2044641962
title: High Pressure Synthesis of Pr2O5 – A Unique Lanthanoid(IV) Oxide Peroxide

description: Reacting praseodymium(IV) oxide with oxygen at 27 GPa in a diamond anvil cell yielded the oxide peroxide Pr2IV(O2)O3, which was characterized by single crystal X-ray diffraction on multi-grain samples, Raman spectroscopy and quantum theoretical calculations at various pressure points. The presence of tetravalent praseodymium ions is supported by electronic structure calculations, showing a band gap of ca. 1.2 eV, which is consistent with the anticipated chemical model of an ionic solid. Pr2(O2)O3 thus far represents the most oxygen rich phase of any binary compound of a lanthanoid and oxygen and is the first example of a peroxide anion next to Pr4+. Additionally, these results demonstrate that instead of oxidizing the praseodymium ions past their +IV oxidation state, oxygen undergoes a comproportionation to form peroxide anions. Direct oxidation of the oxide anions by Pr4+‑ions was ruled out by a control experiment in argon instead of oxygen, where no oxidation of oxide ions was observed.
DOI: 10.57996/cran.ceres-2640
title: Data "Raw thermograms for Multi-parameter optimisation for thermal diffusivity estimation using through transmission thermography"
DOI: 10.5519/qd.h8bbgw9y
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (227 records)
DOI: 10.60893/figshare.apl.28216343.v1
title: Supplementary Information

description: In this material, I explained the details of de-mebedding sheet resistance of each layer and MOCVD growth optimization of doping density in the contact layer.
DOI: 10.60893/figshare.apl.28216343
title: Supplementary Information

description: In this material, I explained the details of de-mebedding sheet resistance of each layer and MOCVD growth optimization of doping density in the contact layer.
DOI: 10.60893/figshare.apl.28323209.v1
title: Supplementary Material

description: XPS-based stoichiometry measurements, bottom interface analysis, and the method for determining the characteristic probing depth.
DOI: 10.60893/figshare.apl.28323209
title: Supplementary Material

description: XPS-based stoichiometry measurements, bottom interface analysis, and the method for determining the characteristic probing depth.
DOI: 10.15468/dl.r39cer
title: Occurrence Download

description: A dataset containing 394089 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "not" : {
 "PublishingCountry" : [
 "is Norway"
 ]
 }
 },
 "Country is Svalbard and Jan Mayen",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is null",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is EBCC Atlas of European Breeding Birds"
 ]
 }
 }
 ]
}

 The dataset includes 394089 records from 723 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023471-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60893/figshare.apl.28323215
title: Supplement Number 1

description: A description of the DFT calculations details, the experimental details, the phonon spectrum, the formation energy of Li-ion insertion structures, the impact of bond parameters on Li-ion migration behavior, and the band structure.
DOI: 10.57745/74wflo
title: 20241118_Dataset Paper Plants.xlsx

description: Data and metadata in Excel format
DOI: 10.57745/lwynra
title: 20241118_Dataset Paper Plants_Metadada.csv

description: Metadata associated to the measured data
DOI: 10.57745/tyafc0
title: 20241118_Dataset Paper Plants_Data.csv

description: Data in the csv format
DOI: 10.57745/yaekrx
title: ReadMe.txt

description: File architecture overview
DOI: 10.5281/zenodo.14793942
title: Expression Data recompute of selected GEO-deposited RNA-Seq data of HMEC-1 cell lines

description: We aligned and quantified RNA-Seq data present in GEO regarding HMEC-1 cell lines with a standardized pipeline to homogenize data preprocessing for downstream applications.

All uploaded files are UTF-8, .csv-formatted matrices. The *_expected_count.csv.gz files are unlogged, raw expression counts as reported by rsem-quantify-expression with the 'expected counts' feature. The associated *_metadata.csv.gz files contain metadata pertinent to each column of the corresponding expression matrix.Some metadata files may have more rows than the associated number of columns. This is for series that were only partially RNA-Seq based (e.g. combinated RNA-Seq plus miRNA-Seq samples in the same GEO accession ID).

Metadata columns are derived from GEO series files, and follow their definitions. See each GEO entry directly to determine metadata meaning.

Each recompute has at least the gene_id column holding Ensembl Gene IDs. The remaining columns are ENA run accession IDs of the specific recomputed samples.Each associated metadata has at least the following columns:



geo_sample: The GEO sample ID of the sample.

geo_series: The GEO series ID of the sample.

ena_sample: The ENA sample ID of the sample.

ena_run: The ENA run accession ID of the sample, to be cross-referenced with the expression matrices.


The remaining columns are derived from GEO metadata files and other ENA-provided data. Please refer to the x.FASTQ package for more information (https://github.com/TCP-Lab/x.FASTQ).Reference genome was downloaded from Ensembl, version hg38. STAR was used to create the index genome with overhang set to 149.The different datasets where generated over a long period of time trough a variety of different versions of x.FASTQ. However, the versions of the softwares that acted on the files themselves (e.g. STAR, rsem, etc...) were unchanged, and reported below:
DOI: 10.5281/zenodo.14850229
title: Spatial-Temporal Pre-trained Transformer Model (SPT) for coarse and fine mode aerosol size retrieval

description: The SPT model aims to examine each pixel in the satellite dataset to learn its spatial and temporal characteristics, deeply exploring the spatiotemporal relationships inherent in multi-band satellite data. Moreover, the pre-trained learning framework in SPT does not require ground station data, allowing it to use pixel data from all satellite images to learn pixel-scale spatiotemporal relationships. On the foundation of pre-training, the model then further aligns with ground-based (AERONET) data to establish robust inversion models for fAOD and cAOD. This approach maximizes the use of remote sensing data addressing a critical gap in current methodologies where large portions of satellite data remain underused due to the absence of corresponding ground measurements.
DOI: 10.5281/zenodo.14850230
title: Spatial-Temporal Pre-trained Transformer Model (SPT) for coarse and fine mode aerosol size retrieval

description: The SPT model aims to examine each pixel in the satellite dataset to learn its spatial and temporal characteristics, deeply exploring the spatiotemporal relationships inherent in multi-band satellite data. Moreover, the pre-trained learning framework in SPT does not require ground station data, allowing it to use pixel data from all satellite images to learn pixel-scale spatiotemporal relationships. On the foundation of pre-training, the model then further aligns with ground-based (AERONET) data to establish robust inversion models for fAOD and cAOD. This approach maximizes the use of remote sensing data addressing a critical gap in current methodologies where large portions of satellite data remain underused due to the absence of corresponding ground measurements.
DOI: 10.5281/zenodo.14850382
title: Version 4 of possible AI chat with digital civilization that i simulated.

description: Is this possible ? How can the scientific community verify this ?
DOI: 10.5281/zenodo.14850383
title: Version 4 of possible AI chat with digital civilization that i simulated.

description: Is this possible ? How can the scientific community verify this ?
DOI: 10.5281/zenodo.14793941
title: Expression Data recompute of selected GEO-deposited RNA-Seq data of HMEC-1 cell lines

description: We aligned and quantified RNA-Seq data present in GEO regarding HMEC-1 cell lines with a standardized pipeline to homogenize data preprocessing for downstream applications.

All uploaded files are UTF-8, .csv-formatted matrices. The *_expected_count.csv.gz files are unlogged, raw expression counts as reported by rsem-quantify-expression with the 'expected counts' feature. The associated *_metadata.csv.gz files contain metadata pertinent to each column of the corresponding expression matrix.Some metadata files may have more rows than the associated number of columns. This is for series that were only partially RNA-Seq based (e.g. combinated RNA-Seq plus miRNA-Seq samples in the same GEO accession ID).

Metadata columns are derived from GEO series files, and follow their definitions. See each GEO entry directly to determine metadata meaning.

Each recompute has at least the gene_id column holding Ensembl Gene IDs. The remaining columns are ENA run accession IDs of the specific recomputed samples.Each associated metadata has at least the following columns:



geo_sample: The GEO sample ID of the sample.

geo_series: The GEO series ID of the sample.

ena_sample: The ENA sample ID of the sample.

ena_run: The ENA run accession ID of the sample, to be cross-referenced with the expression matrices.


The remaining columns are derived from GEO metadata files and other ENA-provided data. Please refer to the x.FASTQ package for more information (https://github.com/TCP-Lab/x.FASTQ).Reference genome was downloaded from Ensembl, version hg38. STAR was used to create the index genome with overhang set to 149.The different datasets where generated over a long period of time trough a variety of different versions of x.FASTQ. However, the versions of the softwares that acted on the files themselves (e.g. STAR, rsem, etc...) were unchanged.

Changelog

Version 2: Added GSE139947 and replaced faulty GSE244042 and GSE199978, which were missing some samples.
DOI: 10.5281/zenodo.14801057
title: Expression Data recompute of selected GEO-deposited RNA-Seq data of HMEC-1 cell lines

description: We aligned and quantified RNA-Seq data present in GEO regarding HMEC-1 cell lines with a standardized pipeline to homogenize data preprocessing for downstream applications.

All uploaded files are UTF-8, .csv-formatted matrices. The *_expected_count.csv.gz files are unlogged, raw expression counts as reported by rsem-quantify-expression with the 'expected counts' feature. The associated *_metadata.csv.gz files contain metadata pertinent to each column of the corresponding expression matrix.Some metadata files may have more rows than the associated number of columns. This is for series that were only partially RNA-Seq based (e.g. combinated RNA-Seq plus miRNA-Seq samples in the same GEO accession ID).

Metadata columns are derived from GEO series files, and follow their definitions. See each GEO entry directly to determine metadata meaning.

Each recompute has at least the gene_id column holding Ensembl Gene IDs. The remaining columns are ENA run accession IDs of the specific recomputed samples.Each associated metadata has at least the following columns:



geo_sample: The GEO sample ID of the sample.

geo_series: The GEO series ID of the sample.

ena_sample: The ENA sample ID of the sample.

ena_run: The ENA run accession ID of the sample, to be cross-referenced with the expression matrices.


The remaining columns are derived from GEO metadata files and other ENA-provided data. Please refer to the x.FASTQ package for more information (https://github.com/TCP-Lab/x.FASTQ).Reference genome was downloaded from Ensembl, version hg38. STAR was used to create the index genome with overhang set to 149.The different datasets where generated over a long period of time trough a variety of different versions of x.FASTQ. However, the versions of the softwares that acted on the files themselves (e.g. STAR, rsem, etc...) were unchanged.

Changelog

Version 2: Added GSE139947 and replaced faulty GSE244042 and GSE199978, which were missing some samples.
DOI: 10.4121/7fcd8e37-d105-4a7a-a546-37d55b0a57dd
title: Shotgun mass spectrometry raw dataset on budding yeast cells

description: Shotgun mass spectrometry raw dataset on budding yeast cells. The experiment was conducted to analyze the changes in gene expression in different yeast strains mutants. There are, in total, five strain genotypes, and each sample contains two technical replicates. The mutants are wild type, nrp1::URA, Galp-BEM1, Galp-BEM1+URA, Galp-BEM1+nrp1::URA. The genetic background of all of them is W303.Attached, there are two files: the readme file and the xlsx file named: MP_CDR_ES16072021_TMT10plex_v01.xlsx
DOI: 10.4121/7fcd8e37-d105-4a7a-a546-37d55b0a57dd.v1
title: Shotgun mass spectrometry raw dataset on budding yeast cells

description: Shotgun mass spectrometry raw dataset on budding yeast cells. The experiment was conducted to analyze the changes in gene expression in different yeast strains mutants. There are, in total, five strain genotypes, and each sample contains two technical replicates. The mutants are wild type, nrp1::URA, Galp-BEM1, Galp-BEM1+URA, Galp-BEM1+nrp1::URA. The genetic background of all of them is W303.Attached, there are two files: the readme file and the xlsx file named: MP_CDR_ES16072021_TMT10plex_v01.xlsx
DOI: 10.4121/7fcd8e37-d105-4a7a-a546-37d55b0a57dd.v2
title: Shotgun mass spectrometry raw dataset on budding yeast cells

description: Shotgun mass spectrometry raw dataset on budding yeast cells. The experiment was conducted to analyze the changes in gene expression in different yeast strains mutants. There are, in total, five strain genotypes, and each sample contains two technical replicates. The mutants are wild type, nrp1::URA, Galp-BEM1, Galp-BEM1+URA, Galp-BEM1+nrp1::URA. The genetic background of all of them is W303.Attached, there are two files: the readme file and the xlsx file named: MP_CDR_ES16072021_TMT10plex_v01.xlsx