cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/t9hyz48796
title: MOF–Metal Ion Adsorption Capacity Dataset (Aqueous Systems; N=209, 10 studies)

description: This dataset contains n = 209 observations of equilibrium adsorption capacity for metal ions adsorbed by metal–organic frameworks (MOFs) in aqueous systems, obtained from 10 peer-reviewed studies. Each row corresponds to a unique experimental condition (MOF, metal ion, solution pH, initial concentration C₀, adsorbent dose). Input parameters span three descriptor groups used for machine-learning modeling and interpretability:
MOF structural: BET (m² g⁻¹), PoreSize (nm), PoreVolume (cm³ g⁻¹), pHpzc
Experimental: pH, C₀ (mg L⁻¹), AdsorbentDose(g L⁻¹)
Ion properties: OxidationState, AtomicMass (g mol⁻¹), Electronegativity, IonizationEnergy (eV), AtomicRadius (Å)

Intended use. Interpretable ML (e.g., XGBoost + SHAP) to predict metal ion adsorption capacity of MOFs and to identify governing factors across materials and operating conditions. Extrapolation beyond observed ranges is discouraged.

Files in this deposit:
dataset.xlsx (human-readable) and dataset.csv (UTF-8, machine-readable)
README.md (context, usage)
data_dictionary.md (definitions/units/ranges)
references.docx and references.csv (StudyID ↔ full citation ↔ DOI mapping)
code/train_ML_shap.py and requirements.txt
mof-adsorption-dataset-v1.zip (all the files zipped together for one-click download)
DOI: 10.17632/t9hyz48796.1
title: MOF–Metal Ion Adsorption Capacity Dataset (Aqueous Systems; N=209, 10 studies)

description: This dataset contains n = 209 observations of equilibrium adsorption capacity for metal ions adsorbed by metal–organic frameworks (MOFs) in aqueous systems, obtained from 10 peer-reviewed studies. Each row corresponds to a unique experimental condition (MOF, metal ion, solution pH, initial concentration C₀, adsorbent dose). Input parameters span three descriptor groups used for machine-learning modeling and interpretability:
MOF structural: BET (m² g⁻¹), PoreSize (nm), PoreVolume (cm³ g⁻¹), pHpzc
Experimental: pH, C₀ (mg L⁻¹), AdsorbentDose(g L⁻¹)
Ion properties: OxidationState, AtomicMass (g mol⁻¹), Electronegativity, IonizationEnergy (eV), AtomicRadius (Å)

Intended use. Interpretable ML (e.g., XGBoost + SHAP) to predict metal ion adsorption capacity of MOFs and to identify governing factors across materials and operating conditions. Extrapolation beyond observed ranges is discouraged.

Files in this deposit:
dataset.xlsx (human-readable) and dataset.csv (UTF-8, machine-readable)
README.md (context, usage)
data_dictionary.md (definitions/units/ranges)
references.docx and references.csv (StudyID ↔ full citation ↔ DOI mapping)
code/train_ML_shap.py and requirements.txt
mof-adsorption-dataset-v1.zip (all the files zipped together for one-click download)
DOI: 10.17026/ar/ijamlj
title: PAN-00139545 - wire brooch with angular bow variant A1

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00139545&lt;/p&gt;
description: Modified: 2025-05-08T14:16:06+02:00
DOI: 10.17632/nnvps9rnxt
title: Synergistic Coastal Resilience: Optimizing Storm Surge Barriers and Adaptive Shoreline Defenses for Macao Under Sea-Level Rise

description: This dataset contains the key numerical model results from the study "Synergistic Coastal Resilience: Optimizing Storm Surge Barriers and Adaptive Shoreline Defenses for Macao Under Sea-Level Rise."
The dataset is organized into three main components, which were critical for validating the model's accuracy against real-world measurements:
1. Modeled_storm_tide_used_for_Figure_5_validation: Time-series data of water levels (combining tide and storm surge) at four tidal gauge stations in the Pearl River Estuary.
2. Modeled_significant_wave_height_used_for_Figure_6_validation: Time-series data of significant wave height at a buoy location in the estuary.
3. Modeled_inundation_depth_used_for_Figure_7_validation: Spatial data of flood depths across the Macao Peninsula at specific survey points.
DOI: 10.17632/nnvps9rnxt.1
title: Synergistic Coastal Resilience: Optimizing Storm Surge Barriers and Adaptive Shoreline Defenses for Macao Under Sea-Level Rise

description: This dataset contains the key numerical model results from the study "Synergistic Coastal Resilience: Optimizing Storm Surge Barriers and Adaptive Shoreline Defenses for Macao Under Sea-Level Rise."
The dataset is organized into three main components, which were critical for validating the model's accuracy against real-world measurements:
1. Modeled_storm_tide_used_for_Figure_5_validation: Time-series data of water levels (combining tide and storm surge) at four tidal gauge stations in the Pearl River Estuary.
2. Modeled_significant_wave_height_used_for_Figure_6_validation: Time-series data of significant wave height at a buoy location in the estuary.
3. Modeled_inundation_depth_used_for_Figure_7_validation: Spatial data of flood depths across the Macao Peninsula at specific survey points.
DOI: 10.17632/xh4sfmcb8p
title: dataset_Initial water content in pyroxenes constrained by experimental and numerical simulations: reassessment of clinopyroxene as a standard for estimating water content in the Earth’s upper mantle

description: Figure data for "Initial water content in pyroxenes constrained by experimental and numerical simulations: reassessment of clinopyroxene as a standard for estimating water content in the Earth’s upper mantle"
DOI: 10.17632/xh4sfmcb8p.3
title: dataset_Initial water content in pyroxenes constrained by experimental and numerical simulations: reassessment of clinopyroxene as a standard for estimating water content in the Earth’s upper mantle

description: Figure data for "Initial water content in pyroxenes constrained by experimental and numerical simulations: reassessment of clinopyroxene as a standard for estimating water content in the Earth’s upper mantle"
DOI: 10.17026/ar/d5w8ln
title: PAN-00104345 - coin/coin-related, Constans (337-350), nummus

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00104345&lt;/p&gt;
description: Modified: 2025-04-28T11:40:03+02:00
DOI: 10.5281/zenodo.17202043
title: Dataset of a study about consumer acceptance of snacks with addition of mushrooms

description: Dataset of a consumer study conducted in Denmark, Spain and Poland, to determine perception of a new product made with mushrooms.
DOI: 10.5281/zenodo.17202044
title: Dataset of a study about consumer acceptance of snacks with addition of mushrooms

description: Dataset of a consumer study conducted in Denmark, Spain and Poland, to determine perception of a new product made with mushrooms.
DOI: 10.34847/nkl.6c7c663m
title: FRA2020_0006

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.9ff583l7
title: FRA2020_0007

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.bde6a430
title: FRA2020_0004

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.dd4bve02
title: FRA2020_0005

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.dd4e50sr
title: FRA2020_0008

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.dff70hx1
title: FRA2020_0011

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.e0cf257b
title: FRA2020_0010

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.fbae0552
title: FRA2020_0009

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.3613ff7q
title: FRA2020_0012

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.36f7ez92
title: FRA2020_0015

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.7f9f57w1
title: FRA2020_0016

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.bbafe253
title: FRA2020_0014

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.34847/nkl.fbdbk0bq
title: FRA2020_0013

description: Fichier dérivé (TEI).
description: Fichier source (TGD).
description: Fichier source (WAV).
DOI: 10.17026/ar/ra7z5v
title: PAN-00010645 - Roman biconical spindle whorl (metal)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00010645&lt;/p&gt;
description: Modified: 2025-07-10T14:39:59+02:00
DOI: 10.17026/ar/ajy9w2
title: PAN-00136892 - arched bow brooch A

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00136892&lt;/p&gt;
description: Modified: 2025-06-03T12:20:58+02:00
DOI: 10.17632/5vspmpvg38
title: LINF_270029900

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/5vspmpvg38.1
title: LINF_270029900

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/8rbvffdsvs
title: LINF_270029500

description: Zinc finger (RanBP2-type)-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/8rbvffdsvs.1
title: LINF_270029500

description: Zinc finger (RanBP2-type)-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/9z95n5hhs7
title: LINF_270029600

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17026/ar/1lmwft
title: PAN-00105693 - coin/coin-related, Gallië (Vindex ?), denarius

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00105693&lt;/p&gt;
description: Modified: 2025-07-07T07:19:11+02:00
DOI: 10.21227/zz4t-va92
title: "Diagonal Hessian-Based Regularization in Multi-Head Continual Learning"

description: "This dataset contains the complete collection of empirical results and ancillary data for the article, \"Diagonal Hessian-Based Regularization in Multi-Head Continual Learning.\" The paper investigates the ability of a diagonal Hessian approximation to\/from be used as a parameter importance estimation in order to reduce catastrophic forgetting in a neural network. The data presented here provides evidence to support the paper's main assertion that using a diagonal Hessian method, in conjunction with a multi-head architecture that decouples task-specific networks, is a more stable and effective method than traditional Fisher Information Matrix (FIM) based methods like Elastic Weight Consolidation (EWC). The experiments were performed on three standard continual learning benchmarks: Split Fashion-MNIST, Split CIFAR-10, and the more difficult Split CIFAR-100, using ResNet-18 networks. The results within this dataset highlight significant performance improvements including 7x less forgetting on Split CIFAR-100 with EWC. This dataset is provided in order to allow the reader to directly reproduce the findings of the paper, for the purposes of establishing a strong baseline for future regularization-based continual learning research, and to hope for wider dissemination and additional research into the properties of second-source importance metrics."
DOI: 10.17632/9z95n5hhs7.1
title: LINF_270029600

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/wkkkv6twgk
title: GTS: A Python toolkit for building Gibbs thermodynamic surface with application to obtain high-pressure melting data

description: Various methods are commonly applied for data acquisition in the melting process of substances under high pressure. However, throughout the application of these methods, challenges persist, including significant time and computational requirements, as well as issues related to hysteresis effects. We introduce the GTS package, a Python toolkit based on the work of J. W. Gibbs to obtain melting data at high pressures in a geometrical manner. We outline the theory behind constructing the Gibbs thermodynamic surface, which includes regions representing the solid and liquid phases. Several examples are presented to demonstrate program execution and validate accuracy by comparing results with prior studies. GTS is openly accessible on GitHub: https://github.com/computation-mineral-physics-group/GTS.
DOI: 10.17632/wkkkv6twgk.1
title: GTS: A Python toolkit for building Gibbs thermodynamic surface with application to obtain high-pressure melting data

description: Various methods are commonly applied for data acquisition in the melting process of substances under high pressure. However, throughout the application of these methods, challenges persist, including significant time and computational requirements, as well as issues related to hysteresis effects. We introduce the GTS package, a Python toolkit based on the work of J. W. Gibbs to obtain melting data at high pressures in a geometrical manner. We outline the theory behind constructing the Gibbs thermodynamic surface, which includes regions representing the solid and liquid phases. Several examples are presented to demonstrate program execution and validate accuracy by comparing results with prior studies. GTS is openly accessible on GitHub: https://github.com/computation-mineral-physics-group/GTS.
DOI: 10.17632/srdxk6f77w
title: Packing3D.jl: An open-source analytical framework for computing packing density and mixing indices using partial spherical volumes

description: Accurate quantification of local packing density and mixing in simulations of particulate systems is essential for many industrial applications. Traditional methods which simply count the number of particle centres within a given volume of space (cell) introduce discontinuities at cell boundaries, leading to unreliable measurements of packing density. We introduce Packing3D.jl, an open-source Julia package providing analytic partial-volume calculations for spheres intersecting Cartesian and cylindrical meshes. We derive closed-form solutions for single, double and triple spherical-cap intersections, plus sphere-cylinder overlaps. We implement efficient mesh-generation routines, principal-cell indexing, and data-splitting functions for time-series analyses. Performance and accuracy were validated against simple cubic and face-centred cubic lattices and via boundary-shift continuity tests. Packing3D.jl converges exactly to theoretical lattice densities, eliminates discontinuities at sub-particle resolution, and scales linearly with particle count. Memory usage remains modest (40 B per particle, 48 B per cell). Packing3D.jl provides researchers with continuous, reproducible volume-fraction fields and robust mixing indices at high performance, facilitating sensitivity analyses and optimisation in granular process engineering.
DOI: 10.15156/bio/sh0179060.10fu
title: SH0179060.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0179061.10fu
title: SH0179061.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0179062.10fu
title: SH0179062.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0179063.10fu
title: SH0179063.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0179064.10fu
title: SH0179064.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0179065.10fu
title: SH0179065.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0179066.10fu
title: SH0179066.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0179067.10fu
title: SH0179067.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.