cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14987070.v1
title: How does climate change adaptation policy in India consider gender? An analysis of 28 state action plans

description: Gender mediates climate vulnerability and adaptation action. Consequently, climate change adaptation policy has seen a push towards ‘mainstreaming’ gender and prioritizing ‘gender-responsive’ climate action. However, it is unclear to what extent this mainstreaming advances or obscures gender considerations and whether current climate policies reflect developments in the gender and climate change literature. This paper explores how gender is operationalized in adaptation policy in India through a policy review of 28 State Action Plans on Climate Change. We juxtapose normative goals around reducing differential vulnerability with policy approaches to mainstreaming gender and propose entry points that link advances in gender and feminist studies with climate change adaptation policy. Our analysis indicates that most subnational climate policies in India explicitly mention gender as a mediator of vulnerability and adaptive capacity but operationalize it inadequately and unevenly. We also reflect on how the heuristics of mainstreaming get operationalized in policies (gender-blind, gender-sensitive, to gender-transformative approaches) and what that means for addressing gendered vulnerability. <b>Key policy insights</b>While explicitly mentioned, gender concerns are unevenly operationalized in India's subnational climate policy.In most State Action Plans on Climate Change in India, gaps exist between normative goals such as reducing differential vulnerability and empowering women, and policy approaches (namely gender-blind, -neutral, -specific, -sensitive, and -transformative approaches).To be effective, the conceptualization of gender must expand beyond focussing on differences between women and men to engaging more with intersections of sex, caste, class, and resources. While explicitly mentioned, gender concerns are unevenly operationalized in India's subnational climate policy. In most State Action Plans on Climate Change in India, gaps exist between normative goals such as reducing differential vulnerability and empowering women, and policy approaches (namely gender-blind, -neutral, -specific, -sensitive, and -transformative approaches). To be effective, the conceptualization of gender must expand beyond focussing on differences between women and men to engaging more with intersections of sex, caste, class, and resources.
DOI: 10.5517/ccdc.csd.cc24srj7
title: CCDC 1989999: Experimental Crystal Structure Determination

description: Related Article: Vikki N. Shinde, Krishnan Rangan, Dalip Kumar, Anil Kumar|2021|J.Org.Chem.|86|9755|doi:10.1021/acs.joc.1c01097
DOI: 10.5517/ccdc.csd.cc25mw90
title: CCDC 2015102: Experimental Crystal Structure Determination

description: Related Article: Aldo S. Estrada-Montaño, Daniel Espinobarro-Velázquez, Ernesto Rivera, Alejandro Camacho-Dávila, Gerardo Zaragoza- Galán|2021|J.Mol.Struct.|1245|130987|doi:10.1016/j.molstruc.2021.130987
DOI: 10.5517/ccdc.csd.cc25xgq9
title: CCDC 2023361: Experimental Crystal Structure Determination

description: Related Article: Xiaojia Wang, Guiying Qiao, Gaihong Zhu, Jian Li, Xiaoyu Guo, Yu Liang, Yunyin Niu|2021|Environ.Res.|202|111689|doi:10.1016/j.envres.2021.111689
DOI: 10.6084/m9.figshare.15082042.v1
title: A Dictyostelium model for BPAN disease reveals a functional relationship between the WDR45/WIPI4 homolog Wdr45l and Vmp1 in the regulation of autophagy-associated PtdIns3P and ER stress

description: PROPPINs are conserved PtdIns3P-binding proteins required for autophagosome biogenesis that fold into a characteristic group of seven-bladed beta-propellers. Mutations in WDR45/WIPI4, a human member of this family, lead to BPAN, a rare form of neurodegeneration. We have generated mutants for the two PROPPIN proteins present in the model system <i>Dictyostelium discoideum</i> (Atg18 and Wdr45l) and characterized their function. Lack of Wdr45l greatly impairs autophagy, while Atg18 only causes subtle defects in the maturation of autolysosomes. The strong phenotype of the Wdr45l mutant is strikingly similar to that observed in <i>Dictyostelium</i> cells lacking Vmp1, an ER protein required for omegasome formation. Common phenotypes include impaired growth in axenic medium, lack of aggregation, and local enrichment of PtdIns3P as determined by the use of lipid reporters. In addition, Vmp1 and Wdr45l mutants show a chronically active response to ER stress. For both mutants, this altered PtdIns3P localization can be prevented by the additional mutation of the upstream regulator Atg1, which also leads to recovery of axenic growth and reduction of ER stress. We propose that, in addition to an autophagy defect, local autophagy-associated PtdIns3P accumulation might contribute to the pathogenesis of BPAN by disrupting ER homeostasis. The introduction of BPAN-associated mutations in <i>Dictyostelium</i> Wdr45l reveals the impact of pathogenic residues on the function and localization of the protein.
DOI: 10.5517/ccdc.csd.cc25xgvf
title: CCDC 2023365: Experimental Crystal Structure Determination

description: Related Article: Xiaojia Wang, Guiying Qiao, Gaihong Zhu, Jian Li, Xiaoyu Guo, Yu Liang, Yunyin Niu|2021|Environ.Res.|202|111689|doi:10.1016/j.envres.2021.111689
DOI: 10.5517/ccdc.csd.cc25xh0m
title: CCDC 2023370: Experimental Crystal Structure Determination

description: Related Article: Xiaojia Wang, Guiying Qiao, Gaihong Zhu, Jian Li, Xiaoyu Guo, Yu Liang, Yunyin Niu|2021|Environ.Res.|202|111689|doi:10.1016/j.envres.2021.111689
DOI: 10.5517/ccdc.csd.cc25xh1n
title: CCDC 2023371: Experimental Crystal Structure Determination

description: Related Article: Xiaojia Wang, Guiying Qiao, Gaihong Zhu, Jian Li, Xiaoyu Guo, Yu Liang, Yunyin Niu|2021|Environ.Res.|202|111689|doi:10.1016/j.envres.2021.111689
DOI: 10.5517/ccdc.csd.cc24st81
title: CCDC 1990053: Experimental Crystal Structure Determination

description: Related Article: Giacomo Tedeschi, Susana Guzman-Puyol, Luca Ceseracciu, José J. Benitez, Luca Goldoni, Andreas Koschella, Thomas Heinze, Gabriella Cavallo, Valentina Dichiarante, Giancarlo Terraneo, Athanassia Athanassiou, Pierangelo Metrangolo, José A. Heredia-Guerrero|2021|Carbohydrate Polymers|271|118031|doi:10.1016/j.carbpol.2021.118031
DOI: 10.5517/ccdc.csd.cc269tkx
title: CCDC 2035229: Experimental Crystal Structure Determination

description: Related Article: Dong-Fei Lu, Zhi-Wen Wang, Fei Wang, Jian Zhang|2021|Inorg.Chem.|60|10075|doi:10.1021/acs.inorgchem.0c03232
DOI: 10.5517/ccdc.csd.cc26kgw4
title: CCDC 2042586: Experimental Crystal Structure Determination

description: Related Article: M. Dhanalakshmi, C. Balakrishnan, S. Rafi Ahamed, G. Vinitha, S. Parthiban|2021|J.Mol.Struct.|1245|131092|doi:10.1016/j.molstruc.2021.131092
DOI: 10.5517/ccdc.csd.cc26kgx5
title: CCDC 2042587: Experimental Crystal Structure Determination

description: Related Article: M. Dhanalakshmi, C. Balakrishnan, S. Rafi Ahamed, G. Vinitha, S. Parthiban|2021|J.Mol.Struct.|1245|131092|doi:10.1016/j.molstruc.2021.131092
DOI: 10.5517/ccdc.csd.cc26lvb0
title: CCDC 2043902: Experimental Crystal Structure Determination

description: Related Article: Malose J. Mphahlele, Sizwe J. Zamisa, Tarek M. El-Gogary|2021|J.Mol.Struct.|1245|131090|doi:10.1016/j.molstruc.2021.131090
DOI: 10.5517/ccdc.csd.cc270hd5
title: CCDC 2056056: Experimental Crystal Structure Determination

description: Related Article: Yu-Tao He, Ayumu Karimata, Olga Gladkovskaya, Eugene Khaskin, Robert R. Fayzullin, Abir Sarbajna, Julia R. Khusnutdinova|2021|Organometallics|40|2320|doi:10.1021/acs.organomet.1c00047
DOI: 10.5517/ccdc.csd.cc270hf6
title: CCDC 2056057: Experimental Crystal Structure Determination

description: Related Article: Yu-Tao He, Ayumu Karimata, Olga Gladkovskaya, Eugene Khaskin, Robert R. Fayzullin, Abir Sarbajna, Julia R. Khusnutdinova|2021|Organometallics|40|2320|doi:10.1021/acs.organomet.1c00047
DOI: 10.5517/ccdc.csd.cc271cl8
title: CCDC 2056899: Experimental Crystal Structure Determination

description: Related Article: Yu-Tao He, Ayumu Karimata, Olga Gladkovskaya, Eugene Khaskin, Robert R. Fayzullin, Abir Sarbajna, Julia R. Khusnutdinova|2021|Organometallics|40|2320|doi:10.1021/acs.organomet.1c00047
DOI: 10.17632/rt7rbtzvt2.1
title: Utilizing SAR, GIS, and Deep Learning for Flood Susceptibility Mapping: A Case Study of a Flood in Mozambique

description: This study integrated the geographic information system, SAR data, and two deep learning techniques; namely, the convolutional neural network (CNN) and Group Method of Data Handling (GMDH) network model techniques, to generate a flood susceptibility map (FSM).
DOI: 10.17632/g7fhs8z7ww.1
title: Code for Monetary policy surprises and their transmission through term premia and expected interest rates

description: Replication files for Monetary policy surprises and their transmission through term premia and expected interest rates Iryna Kaminska Haroon Mumtaz Roman Šustek
DOI: 10.17632/gt7hdfwxzz.1
title: Original data of "Deletion of Galectin-1 in mice results in the attenuation of bone formation via impaired osteogenic differentiation potential of BMSCs"

description: Original data of "Deletion of Galectin-1 in mice results in the attenuation of bone formation via impaired osteogenic differentiation potential of BMSCs"
DOI: 10.17632/459f33wxf6.3
title: PEN-Method: Predictor model and Validation Data

description: This Data contains the PEN-Predictor-Keras-Model as well as the 100 validation data sets.
DOI: 10.25326/238
title: GOES-16 ABI movies (VIS+IR) with cold pool tagging

description: Satellite movies based on GOES-16 ABI infrared and visible imagery overlayed with radiosondes and dropsondes with a cold pool tagging. Cold pools are detected with a method based on the height of the mixed layer, described in Touzé-Peiffer, Rochetin and Vogel (2021). Cold pools are marked in blue when they fall in a cold pool, in red when they fall out of cold pools, and in grey when they are in the buffer zone between the two (as defined in Touzé-Peiffer, 2021) and are thus not classified.

Reference : Touzé-Peiffer, Ludovic, Raphaela Vogel, and Nicolas Rochetin. "Detecting cold pools from soundings during EUREC4A." arXiv preprint arXiv:2104.09146 (2021).
DOI: 10.17632/kd4gv52mvx.1
title: Golestan-FSM dataset

description: Golestan flood mapping dataset
DOI: 10.17632/gm683h9tsx.1
title: LINF_160017600

description: coatomer delta subunit-like protein Leishmania infantum (strain JPCM5)
DOI: 10.17632/cngtztnv7y.1
title: LINF_160016100

description: ubiquitin fold modifier protein | UFM1 Leishmania infantum (strain JPCM5)
DOI: 10.17632/f6z64cs37g.1
title: LINF_160015900

description: Protein of unknown function (DUF3184) Leishmania infantum (strain JPCM5)
DOI: 10.17632/rr4st7jdmb.1
title: LINF_160015850

description: Protein of unknown function (DUF3184) Leishmania infantum (strain JPCM5)
DOI: 10.17632/96jt894stz.2
title: Preferences of adolescents – A dataset containing linked experimental task measures and register data

description: Supplementary files for the article "Gender differences in preferences of adolescents: evidence from a large-scale classroom experiment" and its accompanying data article.
DOI: 10.17632/mbf837fmmx.1
title: Mozambique Flood

description: The data that support the findings of the study were derived from the following resources available in the public domain: DEM from [scihub.copernicus.eu/] and Sentinel-1 from [https://earthexplorer.usgs.gov/].
DOI: 10.34740/kaggle/dsv/2480190
title: 2021 World Population (updated daily)
DOI: 10.48493/rmyd-cm27
title: CIMA: Compendium Isotoporum Medii Aevi
DOI: 10.5281/zenodo.5139626
title: Supplementary Dataset for Saeed et al. 2021: Evolution and Functions of Plant U-box proteins (PUBs): From protein quality control to signalling

description: This record contains additional information and a supplementary dataset of sequence alignment files and phylograms that support the publication: Saeed B, Trenner J, Monaghan J, Quint M, Shabek N, Trujillo M. 2021. Evolution and Functions of Plant U-box proteins (PUBs): From protein quality control to signalling. (submitted to Annual Review of Plant Biology) included files: <em>Additional information.pdf</em> This file contains Supplementary Methods and References for the phylogenetic analyses. <br> <em>Ubox_full_protein_maximum_likelihood_phylogram_linear.pdf</em> A multiple protein sequence alignment by <em>MAFFT</em> (22) of 1121 U-box protein sequences from 21 species and four outgroup sequences containing a RING finger domain (<em>A. thaliana</em> RBX1, <em>A. thaliana</em> RMA1, <em>S. cerevisiae</em> RAD18, <em>Homo sapiens</em> TRAF6 ) was used to infer a phylogenetic tree by maximum likelihood with <em>IQ-TREE</em> (31, 32). The implemented ultrafast bootstrap approximation, set to 2000 bootstrap samples, was used for branch support (17). The consensus tree was annotated using <em>iTOL</em> (25). <em>Ubox_domain_maximum_likelihood_phylogram_linear.pdf</em> In order to analyse specifically the evolution of the U-box domain, the U-box domain of the final 1121 U-box protein sequences as well as the RING finger domain of the four outgroup sequences were isolated and aligned by <em>MAFFT</em> (22). The U-box domain alignment was then used to infer a phylogenetic tree by maximum likelihood with <em>IQ-TREE</em> (31, 32). The implemented ultrafast bootstrap approximation, set to 2000 bootstrap samples, was used for branch support (17). The consensus tree was annotated using iTOL (25). This tree was used to interpret the evolutionary history of U-box proteins in the main text. <em>MAFFT_alignment _1121seqs_Ubox_full_protein_plus_4seqs_RING_outgroup.fasta</em> Multiple protein sequences alignment by MAFFT (22) of 1121 U-box full length protein sequences and four RING finger protein sequences, FASTA formatted. <em>MAFFT_alignment _1121seqs_Ubox_domain_plus_4seqs_RING_outgroup.fasta</em> Multiple protein sequences alignment by MAFFT (22) of U-box domain sequences of 1121 U-box protein and four RING finger domain sequences of outgroup sequences, FASTA formatted. <br> <em>Ubox_protein_sequences_information.xlsx</em> Spreadsheet with sequence ID information and source databases.
DOI: 10.5522/04/13686247
title: Cholesteryl Ester Transfer Protein (CETP) as a Drug Target for Cardiovascular Disease

description: Contains data and computer scripts to generate the figures underlying the manuscript: Cholesteryl Ester Transfer Protein (CETP) as a Drug Target for Cardiovascular Disease.<br>The README.md:# Scripts and deposited data <br>This directory contains R and python scripts along with the data necessary to generate the results described in the manuscript: 'cholesteryl ester transferprotein (CETP) as a drug target for cardiovascular disease'. <br>## Directory content <br>.├── README.md├── scripts├── figures├── MR_data├── TRIAL_data└── PICKLED_data<br>The `scripts` directory contains the computer codes necessary to generate the figures which get saved to the `figures` directory.<br>The scripts source data from the `MR_data` and `TRIAL_data` directories. The `PICKLED_data` directory contains the python pickled files from which we extracted the .csv files in `MR_data` -- these files can be ignored. <br>## Computer scripts<br>The directory root contains various R (.R) and python (.py) scripts that will process the data files. <br>It also contains a `cetp_conda_env.yml` file to conda install the necessary R and python modules:<br>```cd scriptsconda env create -f cetp_conda_env.yml ```<br>This creates the `cetp` conda environment. <br>To generate the figures, please run the following `bash` script:<br>```# run from the scripts directory./run_scripts.sh```<br>### Input and output<br>* scripts/MR_heatmap.py: Takes the MR_data .tsv files and returns Figures 2 and 5.* scripts/MR_metabolites.R: Takes the MR_data .tsv/csv files and returns Figure 4.* scripts/MR_forestplots.R: Takes the MR_data .tsv files and returns Figure 3.* scripts/RCT_forestplots.R: Takes the TRIAL_data .xlsx files and returns Figure 1.<br><br>## Contact<br>Please contact Floriaan Schmidt for any queries: amand.schmidt@ucl.ac.uk . <br>
DOI: 10.5522/04/13686247.v3
title: Cholesteryl Ester Transfer Protein (CETP) as a Drug Target for Cardiovascular Disease

description: Contains data and computer scripts to generate the figures underlying the manuscript: Cholesteryl Ester Transfer Protein (CETP) as a Drug Target for Cardiovascular Disease.<br>The README.md:# Scripts and deposited data <br>This directory contains R and python scripts along with the data necessary to generate the results described in the manuscript: 'cholesteryl ester transferprotein (CETP) as a drug target for cardiovascular disease'. <br>## Directory content <br>.├── README.md├── scripts├── figures├── MR_data├── TRIAL_data└── PICKLED_data<br>The `scripts` directory contains the computer codes necessary to generate the figures which get saved to the `figures` directory.<br>The scripts source data from the `MR_data` and `TRIAL_data` directories. The `PICKLED_data` directory contains the python pickled files from which we extracted the .csv files in `MR_data` -- these files can be ignored. <br>## Computer scripts<br>The directory root contains various R (.R) and python (.py) scripts that will process the data files. <br>It also contains a `cetp_conda_env.yml` file to conda install the necessary R and python modules:<br>```cd scriptsconda env create -f cetp_conda_env.yml ```<br>This creates the `cetp` conda environment. <br>To generate the figures, please run the following `bash` script:<br>```# run from the scripts directory./run_scripts.sh```<br>### Input and output<br>* scripts/MR_heatmap.py: Takes the MR_data .tsv files and returns Figures 2 and 5.* scripts/MR_metabolites.R: Takes the MR_data .tsv/csv files and returns Figure 4.* scripts/MR_forestplots.R: Takes the MR_data .tsv files and returns Figure 3.* scripts/RCT_forestplots.R: Takes the TRIAL_data .xlsx files and returns Figure 1.<br><br>## Contact<br>Please contact Floriaan Schmidt for any queries: amand.schmidt@ucl.ac.uk . <br>
DOI: 10.5522/04/13686247.v2
title: Cholesteryl Ester Transfer Protein (CETP) as a Drug Target for Cardiovascular Disease

description: Contains data and computer scripts to generate the figures underlying the manuscript: Cholesteryl Ester Transfer Protein (CETP) as a Drug Target for Cardiovascular Disease.<br>The README.md:---------------------------------------------------------------------------------------------------------# Scripts and deposited data <br>This directory contains R and python scripts along with the data necessary to generate the results described in the manuscript: 'cholesteryl ester transferprotein (CETP) as a drug target for cardiovascular disease'. <br>## Directory content <br>.├── README.md├── scripts├── figures├── MR_data├── TRIAL_data└── PICKLED_data<br>The `scripts` directory contains the computer codes necessary to generate the figures which get saved to the `figures` directory.<br>The script source data from the `MR_data` and `TRIAL_data` directories. The `PICKLED_data` directory contains the python pickled files from which we extracted the .csv files in `MR_data` -- these pickled filescan be ignored. <br>## Computer scripts<br>The directory root contains various R (.R) and python (.py) scripts that will process the data files. <br>It also contains a `cetp_conda_env.yml` file to conda install the necessary R and python modules:<br>```cd scriptsconda env create -f cetp_conda_env.yml ```<br>This creates the `cetp` conda environment. <br>To generate the figures, please run the following `bash` script:<br>```# run from the scripts directory./run_scripts.sh```<br>### Input and output<br>* scripts/MR_heatmap.py: Takes the MR_data .csv files and returns Figures 2 and 5.* scripts/MR_metabolites.R: Takes the MR_data .csv files and returns Figure 4.* scripts/MR_forestplots.R: Takes the MR_data .csv files and returns Figure 3.* scripts/RCT_forestplots.R: Takes the TRIAL_data .xlsx files and returns Figure 1.<br><br>## Contact<br>Please contact Floriaan Schmidt for any queries: amand.schmidt@ucl.ac.uk . <br>
DOI: 10.48370/ofd/zqnwry/gtpqce
title: HMW_Bupleurum_falcatum_L._H_7735.jpg

description: :unav
DOI: 10.48370/ofd/zqnwry
title: Przewiercień sierpowaty (Bupleurum falcatum L.), 7735

description: Herbarium
DOI: 10.34740/kaggle/dsv/2480232
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.48370/ofd/bcdjhk/wg46cd
title: HMW_Bupleurum_falcatum_L._H_4105.jpg

description: :unav
DOI: 10.48370/ofd/bcdjhk
title: Przewiercień sierpowaty (Bupleurum falcatum L.), 4105

description: Herbarium
DOI: 10.48370/ofd/kjw1cj/ojxk6h
title: HMW_Bupleurum_falcatum_L._H_3943.jpg

description: :unav
DOI: 10.48370/ofd/kjw1cj
title: Przewiercień sierpowaty (Bupleurum falcatum L.), 3943

description: Herbarium
DOI: 10.48370/ofd/wal4pz/x9qg8i
title: HMW_Bupleurum_falcatum_L._H_3877.jpg

description: :unav
DOI: 10.48370/ofd/wal4pz
title: Przewiercień sierpowaty (Bupleurum falcatum L.), 3877

description: Herbarium
DOI: 10.48370/ofd/tixhqy/8qclf5
title: HMW_Bupleurum_falcatum_L._H_3817.jpg

description: :unav
DOI: 10.48370/ofd/tixhqy
title: Przewiercień sierpowaty (Bupleurum falcatum L.), 3817

description: Herbarium
DOI: 10.48370/ofd/q6yxbe/ecnr2a
title: HMW_Bupleurum_ranunculoides_L._H_1837.jpg

description: :unav
DOI: 10.48370/ofd/q6yxbe
title: Przewiercień jaskrowaty (Bupleurum ranunculoides L.), 1837

description: Herbarium
DOI: 10.48370/ofd/zrqf16/xb3m8f
title: HMW_Bryonia_alba_L._H_02542.jpg

description: :unav
DOI: 10.48370/ofd/zrqf16
title: Przestęp biały (Bryonia alba L.), 2542

description: Herbarium
DOI: 10.25824/redu/udzzs8
title: RC_columns_fire-R0.py

description: Python script to compute the displacements and the failure of RC columns subjected to fire.
DOI: 10.25824/redu/pui8rg
title: RC_column_fire.xlsx

description: Excel spreadsheet to compute the displacements and the failure of RC columns subjected to fire. The analyses assume a concentric load (no initial eccentricity) or an equivalent axial load to take into account first and second order effects. The displacements are estimated by the introduction of a simplified bilinear constitutive law that takes into account the Load induced Thermal Strain (LITS) as a reciprocal to the modulus of elasticity. Failure is predicted with the adoption of the nominal stiffness method (EN 1992-1-2, 2004) to take into account the second order effects and an equivalent axial load to replace the axial-bending force.
DOI: 10.25824/redu/ojkofn
title: Prediction of the structural behavior of RC columns in fire

description: Python script to compute the displacements and the failure of RC columns subjected to fire. The analyses assume a concentric load (no initial eccentricity) or an equivalent axial load to take into account first and second order effects. The displacements are estimated by the introduction of EN 1992-1-2 (2004) stress-strain curves and a simplified bilinear constitutive law that takes into account the Load induced Thermal Strain (LITS) as a reciprocal to the modulus of elasticity. Failure is predicted with the adoption of the nominal stiffness method (EN 1992-1-2, 2004) to take into account the second order effects and an equivalent axial load to replace the axial-bending force.
DOI: 10.48370/ofd/2xyp4d/aspqma
title: HMW_Anthyllis_vulneraria_L._H_0828.jpg

description: :unav
DOI: 10.48370/ofd/2xyp4d
title: Przelot pospolity (Anthyllis vulneraria L.), 828

description: Herbarium
DOI: 10.48370/ofd/nkhw89/chss5v
title: HMW_Anthyllis_vulneraria_L._H_5511.jpg

description: :unav
DOI: 10.48370/ofd/nkhw89
title: Przelot pospolity (Anthyllis vulneraria L.), 5511

description: Herbarium
DOI: 10.48370/ofd/vkrbtc/gksgfu
title: HMW_Anthyllis_vulneraria_L._H_3462.jpg

description: :unav
DOI: 10.48370/ofd/vkrbtc
title: Przelot pospolity (Anthyllis vulneraria L.), 3462

description: Herbarium
DOI: 10.48370/ofd/pwv6w8/quvmmj
title: HMW_Anthyllis_vulneraria_L._H_3408.jpg

description: :unav
DOI: 10.48370/ofd/pwv6w8
title: Przelot pospolity (Anthyllis vulneraria L.), 3408

description: Herbarium
DOI: 10.48370/ofd/juqgmw/kyrbpr
title: HMW_Anthyllis_vulneraria_L._H_1004.jpg

description: :unav