cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.b4aey4
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyperus fuscus L., Cyperus calidus A.Kern., Cyperus compressus Krock., Cyperus diandrus Biv., 1838, Cyperus ferrugineus Forssk., Cyperus forskaolii A.Dietr., Cyperus forskhalii A.Dietr., 1832, Cyperus forsskalii A.Dietr., Cyperus fuscus f. calidus (A.Kern.) Asch. & Graebn., Cyperus fuscus f. fuscus, Cyperus fuscus f. serotinus Bolzon, Cyperus fuscus f. virescens (Hoffm.) Vahl, Cyperus fuscus subsp. virescens (Hoffm.) Arcang., Cyperus fuscus subsp. virescens (Hoffm.) K.Richt., Cyperus fuscus var. condensatus Kük., Cyperus fuscus var. nigricans Neilr., Cyperus fuscus var. pallescens Husn., Cyperus fuscus var. subjuncellus Kük., Cyperus fuscus var. virescens (Hoffm.) Dumort., Cyperus fuscus var. virescens (Hoffm.) Schrad., Cyperus fuscus var. virescens (Hoffm.) Vahl, Cyperus fuscus var. vulgaris Schrad., Cyperus haworthii Gray, Cyperus protractus Delile, Cyperus sabaudus Billet, Cyperus sabaudus Billet ex Gave, Cyperus virescens Hoffm., Cyperus viridis Krock., Eucyperus fuscus (L.) Rikli)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Geometry POLYGON((16.26355 48.15358,16.48014 48.15358,16.48014 48.27418,16.26355 48.27418,16.26355 48.15358))",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to January",
 "Month is less than or equal to September"
 ]
}

 The dataset includes 11 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019372-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2hb7dh
title: CCDC 2303746: Experimental Crystal Structure Determination

description: Related Article: Zhang|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.g87qv7
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aaptosyax grypus Rainboth, 1991"
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019374-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g2f5ah
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Erysimum diffusum Ehrh., Cheiranthus alpinus Jacq., Cheiranthus integerrimus Steud., Cheiranthus integrifolius Mill., Cheiranthus pallidus Pall., Cheirinia canescens Link, Crucifera canescens E.H.L.Krause, Erysimastrum canescens (Roth) Rupr., Erysimum andrzejowscianum Besser, Erysimum andrzejowskianum Besser, Erysimum canescens var. subintegerrimum Trautv., Erysimum canescens var. subruncinatum Trautv., Erysimum platyphyllum Schur, Erysimum schultesii Schrad.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Geometry POLYGON((16.26355 48.15358,16.48014 48.15358,16.48014 48.27418,16.26355 48.27418,16.26355 48.15358))",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to January",
 "Month is less than or equal to September"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019375-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13627489
title: pop-cosmos: Galaxy property and redshift catalog for COSMOS2020

description: This record contains data products associated with the paper "pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model" by Thorp et al. (2024).

The included products are derived from spectral energy distribution (SED) fits to 26-band COSMOS2020 photometry, using the 16-parameter SPS model described in Thorp et al. (2024), and the pop-cosmos prior from Alsing et al. (2024). All results are based on Markov Chain Monte Carlo (MCMC) runs using the configuration described in Thorp et al. (2024). Results correspond to v2.1 of the COSMOS2020 catalog.

The current release includes the following files:



README.txt: Detailed information about how to read the other files in the record.

summaries.txt: Plain text file (space delimited) containing summaries of the posteriors estimated from the MCMC chains.


If you make use of any of these products, please cite this repository and the linked paper. Please also cite the pop-cosmos overview paper by Alsing et al. (2024). If you make use of any COSMOS data products, please cite the relevant publications.

If you spot any issues or have any requests, please contact the corresponding author (Stephen Thorp) using the details in the README.
DOI: 10.5281/zenodo.13820043
title: pop-cosmos: Galaxy property and redshift catalog for COSMOS2020

description: This record contains data products associated with the paper "pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model" by Thorp et al. (2024).

The included products are derived from spectral energy distribution (SED) fits to 26-band COSMOS2020 photometry, using the 16-parameter SPS model described in Thorp et al. (2024), and the pop-cosmos prior from Alsing et al. (2024). All results are based on Markov Chain Monte Carlo (MCMC) runs using the configuration described in Thorp et al. (2024). Results correspond to v2.1 of the COSMOS2020 catalog.

The current release includes the following files:



README.txt: Detailed information about how to read the other files in the record.

summaries.txt: Plain text file (space delimited) with summaries of the posteriors estimated from the MCMC chains.

chains.h5.zip: Full MCMC chains in HDF5 format (zipped).


If you make use of any of these products, please cite this repository and the linked paper. Please also cite the pop-cosmos overview paper by Alsing et al. (2024). If you make use of any COSMOS data products, please cite Weaver et al. (2022) and any other relevant publications.

If you spot any issues or have any requests, please contact the corresponding author (Stephen Thorp) using the details in the README.

References:



Alsing et al. (2024). ApJS 274, 12. [arXiv:2402.00935][doi]

Thorp et al. (2024). ApJ 975, 145. [arXiv:2406.19437][doi]

Weaver et al. (2022). ApJS 258, 11. [arXiv:2110.13923][doi]
DOI: 10.5281/zenodo.14012588
title: pop-cosmos: Galaxy property and redshift catalog for COSMOS2020

description: This record contains data products associated with the paper "pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model" by Thorp et al. (2024).

The included products are derived from spectral energy distribution (SED) fits to 26-band COSMOS2020 photometry, using the 16-parameter SPS model described in Thorp et al. (2024), and the pop-cosmos prior from Alsing et al. (2024). All results are based on Markov Chain Monte Carlo (MCMC) runs using the configuration described in Thorp et al. (2024). Results correspond to v2.1 of the COSMOS2020 catalog.

The current release includes the following files:



README.txt: Detailed information about how to read the other files in the record.

summaries.txt: Plain text file (space delimited) with summaries of the posteriors estimated from the MCMC chains.

chains.h5.zip: Full MCMC chains in HDF5 format (zipped).


If you make use of any of these products, please cite this repository and the linked paper. Please also cite the pop-cosmos overview paper by Alsing et al. (2024). If you make use of any COSMOS data products, please cite Weaver et al. (2022) and any other relevant publications.

If you spot any issues or have any requests, please contact the corresponding author (Stephen Thorp) using the details in the README.

References:



Alsing et al. (2024). ApJS 274, 12. [arXiv:2402.00935][doi]

Thorp et al. (2024). ApJ 975, 145. [arXiv:2406.19437][doi]

Weaver et al. (2022). ApJS 258, 11. [arXiv:2110.13923][doi]
DOI: 10.5281/zenodo.14367115
title: pop-cosmos: Galaxy property and redshift catalog for COSMOS2020

description: This record contains data products associated with the paper "pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model" by Thorp et al. (2024).

The included products are derived from spectral energy distribution (SED) fits to 26-band COSMOS2020 photometry, using the 16-parameter SPS model described in Thorp et al. (2024), and the pop-cosmos prior from Alsing et al. (2024). All results are based on Markov Chain Monte Carlo (MCMC) runs using the configuration described in Thorp et al. (2024). Results correspond to v2.1 of the COSMOS2020 catalog.

The current release includes the following files:



README.txt: Detailed information about how to read the other files in the record.

summaries.txt: Plain text file with summaries of the posteriors estimated from the MCMC chains.

chains.h5.zip: Full MCMC chains in HDF5 format (zipped).


If you make use of any of these products, please cite this repository and the linked paper. Please also cite the pop-cosmos overview paper by Alsing et al. (2024). If you make use of any COSMOS data products, please cite Weaver et al. (2022) and any other relevant publications.

If you spot any issues or have any requests, please contact the corresponding author (Stephen Thorp) using the details in the README.

References:



Alsing et al. (2024). ApJS 274, 12. [arXiv:2402.00935][doi]

Thorp et al. (2024). ApJ 975, 145. [arXiv:2406.19437][doi]

Weaver et al. (2022). ApJS 258, 11. [arXiv:2110.13923][doi]
DOI: 10.5281/zenodo.14832248
title: pop-cosmos: Galaxy property and redshift catalog for COSMOS2020

description: This record contains data products associated with the paper "pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model" by Thorp et al. (2024).

The included products are derived from spectral energy distribution (SED) fits to 26-band COSMOS2020 photometry, using the 16-parameter SPS model described in Thorp et al. (2024), and the pop-cosmos prior from Alsing et al. (2024). All results are based on Markov Chain Monte Carlo (MCMC) runs using the configuration described in Thorp et al. (2024). Results correspond to v2.1 of the COSMOS2020 catalog.

The current release includes the following files:



README.txt: Detailed information about how to read the other files in the record.

summaries.txt: Plain text file with summaries of the posteriors estimated from the MCMC chains.

chains.h5.zip: Full MCMC chains in HDF5 format (zipped).

ln_priors.h5.zip: Prior probabilities of MCMC samples in HDF5 format (zipped).


If you make use of any of these products, please cite this repository and the linked paper. Please also cite the pop-cosmos overview paper by Alsing et al. (2024). If you make use of any COSMOS data products, please cite Weaver et al. (2022) and any other relevant publications.

If you spot any issues or have any requests, please contact the corresponding author (Stephen Thorp) using the details in the README.

References:



Alsing et al. (2024). ApJS 274, 12. [arXiv:2402.00935][doi]

Thorp et al. (2024). ApJ 975, 145. [arXiv:2406.19437][doi]

Weaver et al. (2022). ApJS 258, 11. [arXiv:2110.13923][doi]
DOI: 10.26050/wdcc/pmmxmc1tdir1111
title: PalMod2 MPI-M MPI-ESM1-2-1-CR transient-deglaciation-interactive (r1i1p1f1)

description: Project: PalMod2 - From the last interglacial to the anthropocene - modeling a complete glacial cycle.
The PalMod project (https://www.palmod.de/) aims for a better understanding of how slow feedbacks in the Earth system operate.
Using the new insights into Earth system dynamics, PalMod will also make projections of the future
climate over the next few millennia. The project PalMod is in the second phase and funded by the German Federal Ministry of Education and Research as a Research for Sustainability Initiative.
Summary: The transient simulation was performed with the Max Planck Institute for Meteorology Earth System Model version 1.2 in coarse resolution (MPI-ESM-CR) coupled to the ice-sheet model mPISM and the solid-earth model VILMA. MPI-ESM includes the spectral atmospheric model ECHAM6.3 at T31 horizontal resolution (approx. 3.75°) and 31 vertical levels, the land surface vegetation model JSBACH3.2, and the primitive equation ocean model MPIOM1.6 with a nominal resolution of 3°. Embedded into MPIOM1.6 is an Eulerian iceberg model (Erokhina and Mikolajewicz 2024). mPISM is based on PISM0.7.3. and was employed using a polar stereographic grid with a resolution of 10 km in the northern hemisphere and 15 km for Antarctica. VILMA was used in its 1D configuration and discretized on a Gaussian F128 grid with a nominal resolution of 0.7°. The applied setup was introduced in detail in Mikolajewicz et al. (2024).
Following an asynchronous spin-up from 46 ka to 26ka during which MPI-ESM was run with an acceleration factor of 10, the model was integrated without acceleration from a glacial state at 26 ka to the year 1950 with prescribed atmospheric greenhouse gas concentrations (Köhler et al., 2017) and insolation (Berger & Loutre, 1991). This simulation used climatological volcanic forcing representing PI conditions. Forcing fields between MPI-ESM, mPISM, and VILMA as well as changes in the topography, glacier mask, river pathways, ocean bathymetry, and land-sea mask were updated every 10 years. The experiment was performed as part of a model ensemble that contains simulations differing in terms of their tuning parameters, parameterizations, bug fixes and volcanic boundary forcing. These differences are described according to the CMIP6 nomenclature, where r denotes the realization, i the initialization method, p differences in the physics and f in the forcing. The ensemble is described in detail in Mikolajewicz et al. (2024). This particular simulation corresponds to the simulation D1.1 in Mikolajewicz et al. (2024).
Note that the time runs with an offset of +25001 years, meaning that the year range 1-25000 of the data set equals the years 25000-1 BP (Before Present). All data are global datasets with the exception of output from the ice sheet model where regional northern hemispheric and southern hemispheric domains are used.
DOI: 10.15468/dl.eghqp3
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Euphorbia falcata L., Esula falcata (L.) Haw., Euphorbia arvensis Kit., Euphorbia falcata subsp. acuminata Simonk., Euphorbia falcata var. genuina Maire, Euphorbia falcata var. latifolia FontQuer, Galarhoeus falcatus (L.) Prokh., Keraselma falcatum (L.) Raf., Tithymalus falcatus (L.) Klotzsch & Garcke)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Geometry POLYGON((16.26355 48.15358,16.48014 48.15358,16.48014 48.27418,16.26355 48.27418,16.26355 48.15358))",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to January",
 "Month is less than or equal to September"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019376-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ysvwk5
title: Occurrence Download

description: A dataset containing 440 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-5.0423 48.43269,-4.95122 48.3678,-4.87902 48.33901,-4.84125 48.3331,-4.82681 48.36115,-4.90012 48.39509,-4.92689 48.39451,-4.98892 48.44019,-5.0423 48.43269))",
 "HasGeospatialIssue is false",
 "TaxonKey is Mollusca"
 ]
}

 The dataset includes 440 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019378-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/925vh63h53
title: Impact of the continuous and periodic assessment of a buffer replenishment on the DDMRP method

description: Like Kanban or classic inventory management, Demand Driven Material Requirements Planning (DDMRP) assumes that an order is created when the stock level drops below a given level. The assessment of this level can be continuous or periodic. A periodic evaluation can force better repartition of the load over time. DDMRP characterizes the demand for a product by its average daily demand, an aggregation that specifies neither the average size of the elementary demands nor the average duration between two elementary demands. Based on a discrete event simulation model, this study suggests that, at least for a flow-shop organization, the DDMRP method, with continuous order generation, is suitable for large mean time between elementary orders, while periodic observation improves the method for small values of it.
DOI: 10.26050/wdcc/pmmxmc1tdir1112
title: PalMod2 MPI-M MPI-ESM1-2-1-CR transient-deglaciation-interactive (r1i1p1f2)

description: Project: PalMod2 - From the last interglacial to the anthropocene - modeling a complete glacial cycle.
The PalMod project (https://www.palmod.de/) aims for a better understanding of how slow feedbacks in the Earth system operate.
Using the new insights into Earth system dynamics, PalMod will also make projections of the future
climate over the next few millennia. The project PalMod is in the second phase and funded by the German Federal Ministry of Education and Research as a Research for Sustainability Initiative.
Summary: The transient simulation was performed with the Max Planck Institute for Meteorology Earth System Model version 1.2 in coarse resolution (MPI-ESM-CR) coupled to the ice-sheet model mPISM and the solid-earth model VILMA. MPI-ESM includes the spectral atmospheric model ECHAM6.3 at T31 horizontal resolution (approx. 3.75°) and 31 vertical levels, the land surface vegetation model JSBACH3.2, and the primitive equation ocean model MPIOM1.6 with a nominal resolution of 3°. Embedded into MPIOM1.6 is an Eulerian iceberg model (Erokhina and Mikolajewicz 2024). mPISM is based on PISM0.7.3. and was employed using a polar stereographic grid with a resolution of 10 km in the northern hemisphere and 15 km for Antarctica. VILMA was used in its 1D configuration and discretized on a Gaussian F128 grid with a nominal resolution of 0.7°. The applied setup was introduced in detail in Mikolajewicz et al. (2024).
Following an asynchronous spin-up from 46 ka to 26ka during which MPI-ESM was run with an acceleration factor of 10, the model was integrated without acceleration from a glacial state at 26 ka to the year 1950 with prescribed atmospheric greenhouse gas concentrations (Köhler et al., 2017) and insolation (Berger & Loutre, 1991). This simulation used annualy varying volcanic forcing (Schindlbeck-Belo et al., 2024). Forcing fields between MPI-ESM, mPISM, and VILMA as well as changes in the topography, glacier mask, river pathways, ocean bathymetry, and land-sea mask were updated every 10 years. The experiment was performed as part of a model ensemble that contains simulations differing in terms of their tuning parameters, parameterizations, bug fixes and volcanic boundary forcing. These differences are described according to the CMIP6 nomenclature, where r denotes the realization, i the initialization method, p differences in the physics and f in the forcing. The ensemble is described in detail in Mikolajewicz et al. (2024). This particular simulation corresponds to the simulation D1.4 in Mikolajewicz et al. (2024).
Note that the time runs with an offset of +24051 years, meaning that the year range 50-25000 of the data set equals the years 25000-50 BP (Before Present). All data are global datasets with the exception of output from the ice sheet model where regional northern hemispheric and southern hemispheric domains are used.
DOI: 10.5281/zenodo.14831847
title: Dataset related to the article: "The longevity-associated BPIFB4 gene guarantees vascular homeostasis and immune protection through platelets"

description: Abstract Beyond their activity in hemostasis and thrombosis, recent advances attribute platelets a pro-youthful role capable to attenuate immune senescence and age-related neuroinflammation. Previous studies from our group associated a polymorphic haplotype variant in the BPIFB4 gene (LAVBPIFB4) with exceptional longevity. Transfer of the LAV-BPIFB4 in preclinical models has proved strategic to cope with frailty conditions, agingrelated events, e.g., cardiovascular ones, and immunedysfunction mainly through a favorable conditioning of the immune system. However, whether platelets participate in LAV-BPIFB4 therapeutic action is currently unknown. Herein, we discovered that platelets were instrumental in boosting the favorable health outcomes of the systemic AAV-LAV-BPIFB4 gene transfer in vivo, as the α-CD42b platelet depletion completely abolished the vascular protective action of LAV-BPIFB4 and suppressed its pro-resolutive CD206 + anti-/CD86 + pro-inflammatory Ly6C + monocyte skewing to LPS stimulation. Of note, this is associated with a huge drop in the protective levels of BPIFB4 in the plasma of AAV-LAVBPIFB4- injected C57BL/6 mice, indicating that plasma circulating platelets may be a reservoir of the BPIFB4 protein. Indeed, we noticed that BPIFB4 was released by human platelets, a process that isamplified in LAV-allele carrier donors. Accordingly, lentivirus-mediated overexpression of human LAV-BPIFB4 isoform, but not WT-BPIFB4 isoform was able in leading differentiated megakaryocytes to release more platelet-like-particles enriched for BPIFB4. In addition, in vitro, the M2 macrophage polarization increased when releasate from platelets, and even more from LAV pre-stimulated once, was added in monocyte cell culture. Our data suggest that platelet release of BPIFB4 and of yet-to-be-determined unidentified factors mediates the therapeutic efficacy of LAV-BPIFB4 treatment.