cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34740/kaggle/dsv/14994466
title: Daftar Pengadilan Indonesia
DOI: 10.34740/kaggle/dsv/14994344
title: HICP – Food, Alcohol and Tobacco (TEICP260)
DOI: 10.5281/zenodo.18815542
title: naja_kaouthia_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18815541
title: naja_kaouthia_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18815532
title: naja_fuxi_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18815533
title: naja_fuxi_decontaminated_FSCR.fasta.gz
DOI: 10.25431/11380_1178608
title: Actual checklist of Tardigrada species

description: More than one thousand Tardigrada species were included in the published checklist (Guidetti, R. & Bertolani, R. 2005. Tardigrade taxonomy: an updated check list of the taxa and a list of characters for their identification. Zootaxa, 845, 1?46.) plus the additions and corrections to this checklist (Degma, P. & Guidetti, R. 2007. Notes to the current checklist of Tardigrada. Zootaxa, 1579, 41?53.). For practical reasons, we have joined these two papers (without comments added to particular taxa as well as without references published in these papers) into an accurate combined version of the checklists. We incorporated all taxonomical novelties in the current edition of the Checklist even if they were published just online. Then, following the International Code of Zoological Nomenclature, we corrected the year of a taxon description in its print edition. This checklist is free for all users, but utilization of it requires the citation of the two original papers. This checklist is the platform for occasional upgrades (date of latest upgrade is in the title). The changings respect to the previous version of the checklist have yellow background.
If you also use these changes, please also cite this checklist (Degma, P. & Guidetti, R. Actual checklist of Tardigrada species. DOI: 10.25431/11380_1178608. Accessed date).
This checklist collects the taxonomic and systematic information available in the bibliography, so the authors do not necessarily share what is reported in the articles used for the composition of this list.
 Currently there are 35 families, 164 genera, 1508 species and 16 additional subspecies/forms included in the checklist. 
Please write us if you find any mistake or missing data in this checklist. Your help in its improvement will be acknowledged.
DOI: 10.25431/11380_1184020
title: Multi-hazard, exposure and vulnerability in Italian municipalities

description: The dataset includes data on multiple hazards (earthquakes, landslides, and floods) across Italy (data by municipality) and the results of the Multi-Hazard Index and of the cluster analysis, elaborated by: "Pagliacci and Russo (2019), 'Multi-hazard, exposure and vulnerability in Italian municipalities'. In: Resilience and Urban Disasters, edited by Kamila Borsekova and Peter Nijkamp, pages 175-198 Edward Elgar Publishing." It also returns data on exposure (total population) and social and material vulnerability of the Italian municipalities.
DOI: 10.5281/zenodo.16409256
title: In-house WGS Datasets (VCF) Generated for GenRiskPro Project 2025

description: A total of 275 TR individuals (154 males, 121 females) from 180 distinct families were recruited between January 2022 and June 2023 in the first phase of the Anatolian Precision Medicine Initiative (APMI).

The goal of this study is to investigate genetic variation in the Turkish population through whole-genome sequencing data. By analyzing data from healthy individuals and patients with various diseases, the study aims to improve understanding of disease risk, diagnosis, and treatment at the individual level. This research is part of the Anatolian Precision Medicine Initiative and supports the development of precision medicine in Turkey. The findings will contribute to global reference data and help identify population-specific genetic patterns that are important for public health and clinical care.

Blood samples were collected from all 275 individuals to perform WGS analysis. A 5-ml venous EDTA blood samples were obtained from each participant and transferred to a sequencing laboratory using a transport box chilled (4–10 °C) with ice packs. To purify total genomic DNA from human whole blood samples, an automated extractor, QIASYMPHONY (Qiagen, Germany), was used. The manual extraction of nucleic acids was conducted for the samples for which the isolation kits were not compatible with QIASYMPHONY. The quality and quantity of DNA samples were initially assessed spectrophotometrically with NanoDrop (Thermo Fisher, USA). Before the library prep, gDNA samples were quantified more precisely fluorometrically with the Qubit Broad Range dsDNA quantitation kit (Waltham, MA, USA). From the gDNA samples with sufficient quality and quantity, PCR-free NGS libraries were constructed with the Illumina DNA PCR-free Prep kit with the input of 300-400 ng. The sequencing was performed on the Illumina NovaSeq 6000 platform. Raw sequence data in Binary Base Call (BCL) format was demultiplexed and converted to FASTQ with DRAGEN Software v3.9.5. Paired-end reads were then aligned to the NCBI reference sequence (GRCh38) by using the Burrows-Wheeler Aligner (BWA). The variant calling was performed by the Germline Small Variant Caller from the Dragen server V3 (Illumina) with the default hard filter applied. The MultiQC reports were generated to evaluate the sequencing quality.

In this prelimery repo, we included the first 100 (1-100) samples from the projects, with the full tabular outputs from the pipeline, including genetic risk (for major rare and complex diseases, mapped using ClinVar and in-sillico predictions scores), PGx, GWAS and traits. The full dataset are available upon request. The full dataset will be soon avaialbe under The European Genome-phenome Archive (EGA).
DOI: 10.5281/zenodo.16409257
title: In-house WGS Datasets (VCF) Generated for GenRiskPro Project 2025

description: A total of 275 TR individuals (154 males, 121 females) from 180 distinct families were recruited between January 2022 and June 2023 in the first phase of the Anatolian Precision Medicine Initiative (APMI).

The goal of this study is to investigate genetic variation in the Turkish population through whole-genome sequencing data. By analyzing data from healthy individuals and patients with various diseases, the study aims to improve understanding of disease risk, diagnosis, and treatment at the individual level. This research is part of the Anatolian Precision Medicine Initiative and supports the development of precision medicine in Turkey. The findings will contribute to global reference data and help identify population-specific genetic patterns that are important for public health and clinical care.

Blood samples were collected from all 275 individuals to perform WGS analysis. A 5-ml venous EDTA blood samples were obtained from each participant and transferred to a sequencing laboratory using a transport box chilled (4–10 °C) with ice packs. To purify total genomic DNA from human whole blood samples, an automated extractor, QIASYMPHONY (Qiagen, Germany), was used. The manual extraction of nucleic acids was conducted for the samples for which the isolation kits were not compatible with QIASYMPHONY. The quality and quantity of DNA samples were initially assessed spectrophotometrically with NanoDrop (Thermo Fisher, USA). Before the library prep, gDNA samples were quantified more precisely fluorometrically with the Qubit Broad Range dsDNA quantitation kit (Waltham, MA, USA). From the gDNA samples with sufficient quality and quantity, PCR-free NGS libraries were constructed with the Illumina DNA PCR-free Prep kit with the input of 300-400 ng. The sequencing was performed on the Illumina NovaSeq 6000 platform. Raw sequence data in Binary Base Call (BCL) format was demultiplexed and converted to FASTQ with DRAGEN Software v3.9.5. Paired-end reads were then aligned to the NCBI reference sequence (GRCh38) by using the Burrows-Wheeler Aligner (BWA). The variant calling was performed by the Germline Small Variant Caller from the Dragen server V3 (Illumina) with the default hard filter applied. The MultiQC reports were generated to evaluate the sequencing quality.

In this prelimery repo, we included the first 100 (1-100) samples from the projects, with the full tabular outputs from the pipeline, including genetic risk (for major rare and complex diseases, mapped using ClinVar and in-sillico predictions scores), PGx, GWAS and traits. The full dataset are available upon request. The full dataset will be soon avaialbe under The European Genome-phenome Archive (EGA).
DOI: 10.6084/m9.figshare.31313812
title: Fluorescent dopamine sensing using high-performance g-C<sub>3</sub>N<sub>4</sub>/ZnO nanocomposites

description: The practical and facile detection of dopamine in human biofluids, such as urine, saliva, or blood, is of great importance due to its close correlation with various neurological and metabolic disorders. In this work, the performance of a nanocomposite of g-C<sub>3</sub>N<sub>4</sub> nanosheets and ZnO nanorods for the fluorescence sensing of dopamine is studied. The morphology, chemical composition, and electronic structure of the nanocomposite was investigated by SEM and AFM analyses. Its optical properties were explored through UV-vis and fluorescence measurements. A progressive quenching of photoluminescent emission intensity upon the addition of dopamine was found, with the highest sensitivity of 2.4×10<sup>9 </sup>M<sup>-1</sup> and a remarkable detection limit of 5 pM. The sensor demonstrates excellent selectivity toward dopamine against common interfering species in human serum. Finally, the nanocomposite is successful in the quantitative detection of dopamine in physiologically relevant serum samples, confirming its strong potential for future point-of-care diagnostic applications.
DOI: 10.6084/m9.figshare.31313812.v1
title: Fluorescent dopamine sensing using high-performance g-C<sub>3</sub>N<sub>4</sub>/ZnO nanocomposites

description: The practical and facile detection of dopamine in human biofluids, such as urine, saliva, or blood, is of great importance due to its close correlation with various neurological and metabolic disorders. In this work, the performance of a nanocomposite of g-C<sub>3</sub>N<sub>4</sub> nanosheets and ZnO nanorods for the fluorescence sensing of dopamine is studied. The morphology, chemical composition, and electronic structure of the nanocomposite was investigated by SEM and AFM analyses. Its optical properties were explored through UV-vis and fluorescence measurements. A progressive quenching of photoluminescent emission intensity upon the addition of dopamine was found, with the highest sensitivity of 2.4×10<sup>9 </sup>M<sup>-1</sup> and a remarkable detection limit of 5 pM. The sensor demonstrates excellent selectivity toward dopamine against common interfering species in human serum. Finally, the nanocomposite is successful in the quantitative detection of dopamine in physiologically relevant serum samples, confirming its strong potential for future point-of-care diagnostic applications.
DOI: 10.5281/zenodo.18815669
title: Structural, Kinetic and Dynamic Basis of Recognition of a sub-Nanomolar β-Lactamase Inhibitor

description: The supporting data includes the initial input files for the  simulations and the generated trajectories.
DOI: 10.5281/zenodo.18815670
title: Structural, Kinetic and Dynamic Basis of Recognition of a sub-Nanomolar β-Lactamase Inhibitor

description: The supporting data includes the initial input files for the  simulations and the generated trajectories.
DOI: 10.5281/zenodo.18737417
title: Anonymous Khmer TTS dataset

description: This is an anonymous Khmer TTS dataset submitted for double blind review process of Interspeech 2026.

This part of the code only contain the train/test/eval file. Actual audio wavs are host at different Zenodo repository, please download and merge the part to get the full wav folder.



Part1: zenodo.org/records/18768142

Part2: zenodo.org/records/18797296

Part3: zenodo.org/records/18815731
DOI: 10.5281/zenodo.18737416
title: Anonymous Khmer TTS dataset

description: This is an anonymous Khmer TTS dataset submitted for double blind review process of Interspeech 2026.

This part of the code only contain the train/test/eval file. Actual audio wavs are host at different Zenodo repository, please download and merge the part to get the full wav folder.



Part1: zenodo.org/records/18768142

Part2: zenodo.org/records/18797296

Part3: zenodo.org/records/18815731
DOI: 10.5281/zenodo.18597964
title: Hydrogen Abstraction Reaction Data

description: A collection of aydrogen abstraction reactions, stored in SDF format. Each SDF contains the transition state molecule, the reactants and product molecules. Additional information about each molecule is provided as properties in the SDF.

Always-required properties (present for every record)





reaction (string)Unique reaction identifier used to link all records belonging to the same reaction.




type (string)Record role within the reaction. One of:r1, r1h (donor heavy atom / donor + abstracted H),r2, r2h (acceptor heavy atom / acceptor + abstracted H),ts (transition state).




rmg_smiles (string)Canonical RMG SMILES representation (unmapped).




rmg_adjacency_list (string)RMG adjacency list describing the molecular graph.




ordered_mapped_smiles (string)Atom-mapped SMILES with a stable atom ordering. Atom map numbers define the canonical mapping used for role assignment.




role_mapnums (JSON)Mapping from role keys (e.g., r1h_a, r1h_h, r2h_a, r2h_h) to atom map numbers (from ordered_mapped_smiles).




role_mapidx (JSON)Mapping from the same role keys to RDKit atom indices (0-based).




mol_properties (JSON)Per-atom metadata keyed by RDKit atom index (0-based, stored as strings).Each entry contains:





label: one of donor, acceptor, d_hydrogen, a_hydrogen, or TS path tags *0 … *4




atom_type: RMG atom type (e.g., Cs, Cd, O2s, H0)






multiplicity (int)Spin multiplicity.




spin_multiplicity (float)Numeric form of spin multiplicity (redundant, used by some downstream tools).




level_of_theory (string)Combined method/basis label (e.g., wb97xd/def2tzvp).




lot_method (string)Electronic structure method only (e.g., wb97xd).




lot_basis (string)Basis set only (e.g., def2tzvp).




optical_isomers (float)Number of optical isomers.



 

Arkane-derived thermochemistry (present when available)

These properties are included when Arkane parsing succeeds; otherwise they may be absent or set to null.





frequencies_cm1_list (list of float)Vibrational frequencies in cm⁻¹.




ts_imag_freq_cm1 (float or null)Imaginary frequency for transition states; null for non-TS records.




E0_value, E0_units (float, string)Zero-point corrected energy.




H298_value, H298_units (float, string)Standard enthalpy at 298 K.




S298_value, S298_units (float, string)Standard entropy at 298 K.




Cp_T_value_list, Cp_T_units (list, string)Heat capacities at tabulated temperatures.




T_list, T_units (list, string)Temperature grid corresponding to tabulated properties.




polynomials (JSON)NASA polynomial coefficients and validity ranges.




ZPE_kJmol (float)Zero-point energy in kJ/mol.




E_elec_kJmol (float)Electronic energy.




Convenience fields (float)Rounded or unit-converted summaries such as E0_kJmol, H298_kJmol.
DOI: 10.5281/zenodo.18597963
title: Hydrogen Abstraction Reaction Data

description: A collection of aydrogen abstraction reactions, stored in SDF format. Each SDF contains the transition state molecule, the reactants and product molecules. Additional information about each molecule is provided as properties in the SDF.

Always-required properties (present for every record)





reaction (string)Unique reaction identifier used to link all records belonging to the same reaction.




type (string)Record role within the reaction. One of:r1, r1h (donor heavy atom / donor + abstracted H),r2, r2h (acceptor heavy atom / acceptor + abstracted H),ts (transition state).




rmg_smiles (string)Canonical RMG SMILES representation (unmapped).




rmg_adjacency_list (string)RMG adjacency list describing the molecular graph.




ordered_mapped_smiles (string)Atom-mapped SMILES with a stable atom ordering. Atom map numbers define the canonical mapping used for role assignment.




role_mapnums (JSON)Mapping from role keys (e.g., r1h_a, r1h_h, r2h_a, r2h_h) to atom map numbers (from ordered_mapped_smiles).




role_mapidx (JSON)Mapping from the same role keys to RDKit atom indices (0-based).




mol_properties (JSON)Per-atom metadata keyed by RDKit atom index (0-based, stored as strings).Each entry contains:





label: one of donor, acceptor, d_hydrogen, a_hydrogen, or TS path tags *0 … *4




atom_type: RMG atom type (e.g., Cs, Cd, O2s, H0)






multiplicity (int)Spin multiplicity.




spin_multiplicity (float)Numeric form of spin multiplicity (redundant, used by some downstream tools).




level_of_theory (string)Combined method/basis label (e.g., wb97xd/def2tzvp).




lot_method (string)Electronic structure method only (e.g., wb97xd).




lot_basis (string)Basis set only (e.g., def2tzvp).




optical_isomers (float)Number of optical isomers.



 

Arkane-derived thermochemistry (present when available)

These properties are included when Arkane parsing succeeds; otherwise they may be absent or set to null.





frequencies_cm1_list (list of float)Vibrational frequencies in cm⁻¹.




ts_imag_freq_cm1 (float or null)Imaginary frequency for transition states; null for non-TS records.




E0_value, E0_units (float, string)Zero-point corrected energy.




H298_value, H298_units (float, string)Standard enthalpy at 298 K.




S298_value, S298_units (float, string)Standard entropy at 298 K.




Cp_T_value_list, Cp_T_units (list, string)Heat capacities at tabulated temperatures.




T_list, T_units (list, string)Temperature grid corresponding to tabulated properties.




polynomials (JSON)NASA polynomial coefficients and validity ranges.




ZPE_kJmol (float)Zero-point energy in kJ/mol.




E_elec_kJmol (float)Electronic energy.




Convenience fields (float)Rounded or unit-converted summaries such as E0_kJmol, H298_kJmol.
DOI: 10.5281/zenodo.18814482
title: Origin of Frequency Clusters and Robust Triplet Locking in the Kuramoto Model with Inertia
DOI: 10.5281/zenodo.18814483
title: Origin of Frequency Clusters and Robust Triplet Locking in the Kuramoto Model with Inertia
DOI: 10.5281/zenodo.18815720
title: THE ROLE AND IMPORTANCE OF THE SUPPLY CHAIN IN CONSTRUCTION

description: This topic will highlight the importance of effective supply chain management in the construction industry. It will analyze the role of the supply chain in the timely delivery of construction materials, equipment, and resources, and its impact on project duration and cost.
DOI: 10.5281/zenodo.18815721
title: THE ROLE AND IMPORTANCE OF THE SUPPLY CHAIN IN CONSTRUCTION

description: This topic will highlight the importance of effective supply chain management in the construction industry. It will analyze the role of the supply chain in the timely delivery of construction materials, equipment, and resources, and its impact on project duration and cost.
DOI: 10.6084/m9.figshare.31399215
title: input_figure_1_c

description: This dataset contains the data used to generate <b>Figure 1C</b> in Almansour et al. (2026). It includes the complete dataset generated from raw high-throughput confocal microscopy images using the HiTIPS image analysis software. This dataset can be used to regenerate <b>Figure 1C</b> using the corresponding R script.The dataset name matches the plot shown in the figure and its corresponding R script. The corresponding R script supports two execution modes: (1) using this input folder when placed locally in the script working directory, or (2) running the script directly, which triggers retrieval of the input data from the Figshare link.<b>Resources</b><b>Almansour et al. (2026):</b> PMID: 41446082 | PMCID: PMC12724616 | DOI: 10.64898/2025.12.13.694158<b>HiTIPS:</b> https://github.com/CBIIT/HiTIPS<b>R script:</b> https://github.com/CBIIT/mistelilab-tad-ge<br>
DOI: 10.6084/m9.figshare.31399215.v2
title: input_figure_1_c

description: This dataset contains the data used to generate <b>Figure 1C</b> in Almansour et al. (2026). It includes the complete dataset generated from raw high-throughput confocal microscopy images using the HiTIPS image analysis software. This dataset can be used to regenerate <b>Figure 1C</b> using the corresponding GitHub R script.The dataset name matches the plot shown in the figure and its corresponding GitHub R script. The corresponding GitHub R script supports two execution modes: (1) using this input folder when placed locally in the script working directory, or (2) running the script directly, which triggers retrieval of the input data from the Figshare link.<b>Resources</b><b>Almansour et al. (2026):</b> PMID: 41446082 | PMCID: PMC12724616 | DOI: 10.64898/2025.12.13.694158<b>HiTIPS:</b> https://github.com/CBIIT/HiTIPS<b>GitHub R script:</b> https://github.com/CBIIT/mistelilab-tad-ge
DOI: 10.6084/m9.figshare.31399215.v3
title: input_figure_1_c

description: This dataset contains the data used to generate <b>Figure 1C</b> in Almansour et al. (2026). It includes the complete dataset generated from raw high-throughput confocal microscopy images using the HiTIPS image analysis software. This dataset can be used to regenerate <b>Figure 1C</b> using the corresponding R script.The dataset name matches the plot shown in the figure and its corresponding R script. The corresponding R script supports two execution modes: (1) using this input folder when placed locally in the script working directory, or (2) running the script directly, which triggers retrieval of the input data from the Figshare link.<b>Resources</b><b>Almansour et al. (2026):</b> PMID: 41446082 | PMCID: PMC12724616 | DOI: 10.64898/2025.12.13.694158<b>HiTIPS:</b> https://github.com/CBIIT/HiTIPS<b>R script:</b> https://github.com/CBIIT/mistelilab-tad-ge<br>
DOI: 10.5281/zenodo.18815786
title: THE ARTISTIC IMAGE IN THE STORIES OF USMON AZIM

description: This article analyzes the mastery of creating artistic images in Usmon Azim’s stories. Through examples from some of the writer’s works, it is shown how the characters’ psychological experiences, life lessons, and inner world are revealed by means of artistic devices. The study also examines the author’s individual style in image creation, the degree of realism in the symbols, and their distinctive artistic features.
DOI: 10.5281/zenodo.18815787
title: THE ARTISTIC IMAGE IN THE STORIES OF USMON AZIM

description: This article analyzes the mastery of creating artistic images in Usmon Azim’s stories. Through examples from some of the writer’s works, it is shown how the characters’ psychological experiences, life lessons, and inner world are revealed by means of artistic devices. The study also examines the author’s individual style in image creation, the degree of realism in the symbols, and their distinctive artistic features.
DOI: 10.34740/kaggle/dsv/14994599
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.34804/supra.20210928313
title: Supramolecular interaction of cucurbit[n]urils and coptisine by spectrofluorimetry and its analytical application

description: null
DOI: 10.5281/zenodo.18815680
title: Evaluation of the Effects of Long-Term Recombinant Growth Hormone Therapy on Retinal Microvasculature Using OCTAVA
DOI: 10.5281/zenodo.18815681
title: Evaluation of the Effects of Long-Term Recombinant Growth Hormone Therapy on Retinal Microvasculature Using OCTAVA