cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25582/data.2023-01.2707325/2302644
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709690/2302645
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710706/2302646
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.25224078
title: Supplementary Tables from Dual stressors of infection and warming can destabilize host microbiomes

description: Table S1 16S samples from lab-adapted hosts Table S2 16S samples from wild isolates Table S3 Alpha-diversity results Table S4 Microbiome dominance level Table S5 Beta-dissimilarity distance Table S6 Species pairwise smetana scores Table S7 Species pairwise MIP/MRO scores Table S8 Community-level MIP/MRO scores Table S9 Species co-occurrence coefficient Table S10 Differentially enriched species Table S11 List of hypothesis and statistical test results
DOI: 10.6084/m9.figshare.25224078.v1
title: Supplementary Tables from Dual stressors of infection and warming can destabilize host microbiomes

description: Table S1 16S samples from lab-adapted hosts Table S2 16S samples from wild isolates Table S3 Alpha-diversity results Table S4 Microbiome dominance level Table S5 Beta-dissimilarity distance Table S6 Species pairwise smetana scores Table S7 Species pairwise MIP/MRO scores Table S8 Community-level MIP/MRO scores Table S9 Species co-occurrence coefficient Table S10 Differentially enriched species Table S11 List of hypothesis and statistical test results
DOI: 10.25582/data.2023-01.2711166/2302647
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710819/2302648
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709551/2302649
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732324/2302650
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2732412/2302651
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2707632/2302652
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710565/2302653
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2707019/2302654
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709507/2302655
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2715519/2302656
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706031/2302657
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708359/2302658
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709714/2302659
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706669/2302660
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710465/2302661
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706041/2302662
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706208/2302663
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706522/2302664
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706986/2302665
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710383/2302666
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711051/2302667
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711097/2302668
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708796/2302669
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709937/2302670
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710275/2302671
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732801/2302672
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2705476/2302673
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710246/2302674
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706472/2302675
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2707004/2302676
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.25224074
title: xiezhi_20231026

description: A unique new species,<i> </i><i>Oreocharis scutifolia</i><i> </i>Z. Xie, Miao Zhang & H. H. Kong, endemic to the Dry and Hot Valley of Jinsha River Basin, Yunnan, China, is described and illustrated here. It is similar to <i>O. cordatula</i> (Craib) Pellegr. and <i>O. aurantiaca</i> Baill. in some morphological characters, but differs in its unique peltate, ovate to oblong leaf blades with emarginated apex, places and types of indumentum, length of peduncles and corolla, also have significant differences in these species. Molecular phylogenetic analysis based on transcriptome data strongly supported <i>O. scutifolia</i> as a new species, while it forms a sister group with <i>O. henryana</i> Oliv., <i>O. cordatula</i> (Craib) Pellegr., <i>O. minor</i> Pellegr. and <i>O. aurantiaca</i> Baill. (ML = 100). Due to its tiny population, narrow distribution range, and the serious threat from human activities, invasive plants and damaged habitat, the new species is assessed as "critically endangered" following the IUCN categories and criteria.Here, we are willing to introduce a dataset consisting of 125 samples, including 6 species from Gesneriaceae as outgroups of the genus <i>Oreocharis</i> and 119 members of the same genus. This dataset is provided as supplementary material to the nature notes "<i>Oreocharis scutifolia</i> (Gesneriaceae) , a unique new species from the Dry and Hot Valley of Jinsha River Basin, Yunnan, China" submitted to <i>Ecology and Evolution</i>.
DOI: 10.6084/m9.figshare.25224074.v1
title: xiezhi_20231026

description: A unique new species,<i> </i><i>Oreocharis scutifolia</i><i> </i>Z. Xie, Miao Zhang & H. H. Kong, endemic to the Dry and Hot Valley of Jinsha River Basin, Yunnan, China, is described and illustrated here. It is similar to <i>O. cordatula</i> (Craib) Pellegr. and <i>O. aurantiaca</i> Baill. in some morphological characters, but differs in its unique peltate, ovate to oblong leaf blades with emarginated apex, places and types of indumentum, length of peduncles and corolla, also have significant differences in these species. Molecular phylogenetic analysis based on transcriptome data strongly supported <i>O. scutifolia</i> as a new species, while it forms a sister group with <i>O. henryana</i> Oliv., <i>O. cordatula</i> (Craib) Pellegr., <i>O. minor</i> Pellegr. and <i>O. aurantiaca</i> Baill. (ML = 100). Due to its tiny population, narrow distribution range, and the serious threat from human activities, invasive plants and damaged habitat, the new species is assessed as "critically endangered" following the IUCN categories and criteria.Here, we are willing to introduce a dataset consisting of 125 samples, including 6 species from Gesneriaceae as outgroups of the genus <i>Oreocharis</i> and 119 members of the same genus. This dataset is provided as supplementary material to the nature notes "<i>Oreocharis scutifolia</i> (Gesneriaceae) , a unique new species from the Dry and Hot Valley of Jinsha River Basin, Yunnan, China" submitted to <i>Ecology and Evolution</i>.
DOI: 10.25582/data.2023-01.2706076/2302677
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708699/2302678
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732808/2302679
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2710469/2302680
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710814/2302681
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2715251/2302682
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2733264/2302683
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2710424/2302684
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709500/2302685
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710445/2302686
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711252/2302687
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710942/2302688
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708665/2302689
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709956/2302690
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709864/2302691
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710121/2302692
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732582/2302693
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2710830/2302694
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2715651/2302695
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710054/2302696
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706046/2302697
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732397/2302698
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2732713/2302699
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2732729/2302700
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2709665/2302701
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711259/2302702
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2712168/2302703
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706936/2302704
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2733146/2302705
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2706948/2302706
title: Data for EMSL Project 51287 from January 2023
DOI: 10.5281/zenodo.7009229
title: Iron Nitride Nanoparticles for Rapid Dechlorination of Mixed Chlorinated Ethene Contamination: DFT Calculations

description: This dataset contains input and output files of density functional theory calculations on which the computational part of the peer-reviewed article "Iron nitride nanoparticles for rapid dechlorination of mixed chlorinated ethene contamination" by M. Brumovský et al., doi 10.1016/j.jhazmat.2022.129988, is based. Please cite this article when using the dataset.


The dataset includes:
*  Structures and energies of adsorbed cis-DCE and PCE molecules on the Fe(110), Fe4N(001), and FeS(001) surfaces in the folder "Adsorption_calculations", including structures and energies of adsorbed TCE on the FeS(001) surface
*  cis-DCE and PCE homolytic bond dissociation energies calculated using VASP and TURBOMOLE in the folder "BDE_calculations"
*  Relaxed structures of dechlorinated intermediates on the Fe(110), Fe4N(001), and FeS(001) surfaces in the folder "Intermediates"
*  Transition state calculations of chloroethene dechlorination reactions, including frequency calculations of transitions states, in the folder "NEB_calculations"
*  Energies of reactants, products, and transitions states calculated with the inclusion of the solvent effect in the folder "VASPsol_calculations"


The final geometries and energies calculated using VASP are reported in the CONTCAR and OUTCAR files, respectively. Note that the POTCAR files are not allowed to be made publicly accessible. However, their description is given in the OUTCAR files. Please consult VASP/TURBOMOLE manual for more information regarding input and output files.


The fully relaxed unit cells of Fe, Fe4N, and FeS, as well as adsorption calculations of TCE, and transition state calculations of TCE chemisorption and its first dechlorination step on the Fe4N(001) surface are accessible in a previously published dataset, doi 10.5281/zenodo.6338412.


Funding: This work was supported by the Austrian Science Fund (FWF) project M 2892-N. The Vienna Scientific Cluster (Project No. 70544) is gratefully acknowledged for providing computational resources.


Terms of use: These data are provided "as is", without any warranty. The data are provided under the Creative Commons Attribution 4.0 International license.
DOI: 10.5281/zenodo.7009230
title: Iron Nitride Nanoparticles for Rapid Dechlorination of Mixed Chlorinated Ethene Contamination: DFT Calculations

description: This dataset contains input and output files of density functional theory calculations on which the computational part of the peer-reviewed article "Iron nitride nanoparticles for rapid dechlorination of mixed chlorinated ethene contamination" by M. Brumovský et al., doi 10.1016/j.jhazmat.2022.129988, is based. Please cite this article when using the dataset.


The dataset includes:
*  Structures and energies of adsorbed cis-DCE and PCE molecules on the Fe(110), Fe4N(001), and FeS(001) surfaces in the folder "Adsorption_calculations", including structures and energies of adsorbed TCE on the FeS(001) surface
*  cis-DCE and PCE homolytic bond dissociation energies calculated using VASP and TURBOMOLE in the folder "BDE_calculations"
*  Relaxed structures of dechlorinated intermediates on the Fe(110), Fe4N(001), and FeS(001) surfaces in the folder "Intermediates"
*  Transition state calculations of chloroethene dechlorination reactions, including frequency calculations of transitions states, in the folder "NEB_calculations"
*  Energies of reactants, products, and transitions states calculated with the inclusion of the solvent effect in the folder "VASPsol_calculations"


The final geometries and energies calculated using VASP are reported in the CONTCAR and OUTCAR files, respectively. Note that the POTCAR files are not allowed to be made publicly accessible. However, their description is given in the OUTCAR files. Please consult VASP/TURBOMOLE manual for more information regarding input and output files.


The fully relaxed unit cells of Fe, Fe4N, and FeS, as well as adsorption calculations of TCE, and transition state calculations of TCE chemisorption and its first dechlorination step on the Fe4N(001) surface are accessible in a previously published dataset, doi 10.5281/zenodo.6338412.


Funding: This work was supported by the Austrian Science Fund (FWF) project M 2892-N. The Vienna Scientific Cluster (Project No. 70544) is gratefully acknowledged for providing computational resources.


Terms of use: These data are provided "as is", without any warranty. The data are provided under the Creative Commons Attribution 4.0 International license.
DOI: 10.25582/data.2023-01.2708406/2302707
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708836/2302708
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706957/2302709
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711116/2302710
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710199/2302711
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711198/2302712
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2707100/2302713
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2715903/2302714
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2712388/2302715
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710132/2302716
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2715800/2302717
title: Data for EMSL Project 51287 from January 2023
DOI: 10.5281/zenodo.6338411
title: Iron Nitride Nanoparticles for Enhanced Reductive Dechlorination of Trichloroethylene: DFT Calculations

description: This dataset contains input and output files of density functional theory calculations on which the computational part of the peer-reviewed article "Iron Nitride Nanoparticles for Enhanced Reductive Dechlorination of Trichloroethylene" by M. Brumovský et al., doi 10.1021/acs.est.1c08282, is based. Please cite this article when using the dataset.


The dataset includes:
*  Fully relaxed unit cells of Fe, Fe4N, and FeS in the folder "Unit_cells"
*  Structures and energies of adsorbed TCE and H2O molecules on the Fe(110), Fe4N(001), and FeS(001) surfaces in the folder "Adsorption_calculations"
*  Transition state calculations of TCE chemisorption and the first dechlorination step on the Fe4N(001) surface, including frequency calculations of transitions states, in the folder "NEB_calculations_on_Fe4N"
*  TCE homolytic bond dissociation energies calculated using VASP and TURBOMOLE in the folder "BDE_calculations"
*  Energies of reactants, products, and transitions states calculated with the inclusion of the solvent effect in the folder "VASPsol_calculations"


The final geometries and energies calculated using VASP are reported in the CONTCAR and OUTCAR files, respectively. Note that the POTCAR files are not allowed to be made publicly accessible. However, their description is given in the OUTCAR files. Please consult VASP/TURBOMOLE manual for more information regarding input and output files. 


Funding: This work was supported by the Austrian Science Fund (FWF) project M 2892-N and the University of Ostrava (IRP201826, SGS06/PrF/2021). The Vienna Scientific Cluster (Project No. 70544) and IT4 Innovations National Supercomputing Center (LM2015070) are gratefully acknowledged for providing computational resources. 


Terms of use: These data are provided "as is", without any warranty. The data are provided under the Creative Commons Attribution 4.0 International license.
DOI: 10.5281/zenodo.6338412
title: Iron Nitride Nanoparticles for Enhanced Reductive Dechlorination of Trichloroethylene: DFT Calculations

description: This dataset contains input and output files of density functional theory calculations on which the computational part of the peer-reviewed article "Iron Nitride Nanoparticles for Enhanced Reductive Dechlorination of Trichloroethylene" by M. Brumovský et al., doi 10.1021/acs.est.1c08282, is based. Please cite this article when using the dataset.


The dataset includes:
*  Fully relaxed unit cells of Fe, Fe4N, and FeS in the folder "Unit_cells"
*  Structures and energies of adsorbed TCE and H2O molecules on the Fe(110), Fe4N(001), and FeS(001) surfaces in the folder "Adsorption_calculations"
*  Transition state calculations of TCE chemisorption and the first dechlorination step on the Fe4N(001) surface, including frequency calculations of transitions states, in the folder "NEB_calculations_on_Fe4N"
*  TCE homolytic bond dissociation energies calculated using VASP and TURBOMOLE in the folder "BDE_calculations"
*  Energies of reactants, products, and transitions states calculated with the inclusion of the solvent effect in the folder "VASPsol_calculations"


The final geometries and energies calculated using VASP are reported in the CONTCAR and OUTCAR files, respectively. Note that the POTCAR files are not allowed to be made publicly accessible. However, their description is given in the OUTCAR files. Please consult VASP/TURBOMOLE manual for more information regarding input and output files. 


Funding: This work was supported by the Austrian Science Fund (FWF) project M 2892-N and the University of Ostrava (IRP201826, SGS06/PrF/2021). The Vienna Scientific Cluster (Project No. 70544) and IT4 Innovations National Supercomputing Center (LM2015070) are gratefully acknowledged for providing computational resources. 


Terms of use: These data are provided "as is", without any warranty. The data are provided under the Creative Commons Attribution 4.0 International license.
DOI: 10.25582/data.2023-02.2732422/2302718
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2708350/2302719
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711187/2302720
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709882/2302721
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2733081/2302722
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2711076/2302723
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708965/2302724
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708970/2302725
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709739/2302726
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710610/2302727
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710653/2302728
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709954/2302729
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710392/2302730
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709866/2302731
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710893/2302732
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708316/2302733
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2705908/2302734
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711468/2302735
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710361/2302736
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732359/2302737
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2708675/2302738
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710327/2302739
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711038/2302740
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732386/2302741
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2733248/2302742
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2711013/2302743
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711115/2302744
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711327/2302745
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708939/2302746
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732255/2302747
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2709957/2302748
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710225/2302749
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709729/2302750
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706623/2302751
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710601/2302752
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710821/2302753
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706526/2302754
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711359/2302755
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710348/2302756
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706126/2302757
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710510/2302758
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710708/2302759
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710141/2302760
title: Data for EMSL Project 51287 from January 2023