cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.a2qp46
title: Occurrence Download

description: A dataset containing 352 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "DatasetKey is one of (Banco de Datos de la Biodiversidad de la Comunitat Valenciana, Colección de plantas vasculares del herbario de la Universitat de València (VAL), Herbario HSS Finca La Orden-Valdesequera (CICYTEX). Junta de Extremadura, Col·lecció de plantes de l'herbari de la Universitat de Barcelona, Colección de plantas vasculares del Herbario \"Jaime Andrés Rodríguez\". LEB)",
 "Geometry POLYGON((-1.65598 43.57276,-9.52997 44.18223,-9.42428 41.74644,-7.25761 41.707,-7.57469 35.949,-2.55436 35.949,0.61638 38.55646,0.19361 39.62286,3.73427 41.39061,3.52289 42.76338,-1.65598 43.57276))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Senecio lividus"
 ]
}

 The dataset includes 352 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004890-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/oo5utz
title: Intercropping_In_row_REDN11_20240408_144324.jpg

description: :unav
DOI: 10.57745/ynwy2e
title: Pure_tri_TS_HUAP30_20240408_142712_mask.png

description: :unav
DOI: 10.57745/1hlt61
title: Intercropping_Mixed_HUAP30_20240408_151237_mask.png

description: :unav
DOI: 10.57745/cy9hjn
title: Pure_Faba_A12_20240408_153232_mask.png

description: :unav
DOI: 10.57745/uswtsh
title: Pure_tri_0N_REDN11_20240422_153843.jpg

description: :unav
DOI: 10.57745/wf5lar
title: Pure_Faba_HUAP30_20240321_142948_mask.png

description: :unav
DOI: 10.57745/znqmei
title: Intercropping_Mixed_REDN11_20240408_151641.jpg

description: :unav
DOI: 10.57745/ffnjjg
title: Pure_tri_TS_HUAP30_20240321_153856_mask.png

description: :unav
DOI: 10.57745/xyixi5
title: Pure_Faba_REDN11_20240321_143107.jpg

description: :unav
DOI: 10.57745/rvikea
title: Pure_Tri_0N_A12_20240321_143409_mask.png

description: :unav
DOI: 10.57745/om5wd2
title: Intercropping_Mixed_HUAP30_20240408_151404_mask.png

description: :unav
DOI: 10.57745/6wligq
title: Intercropping_Mixed_REDN11_20240321_160257_mask.png

description: :unav
DOI: 10.57745/rwfx0u
title: Pure_Faba_REDN11_20240321_142048.jpg

description: :unav
DOI: 10.57745/40wmb8
title: Intercropping_Mixed_A12_20240321_155503.jpg

description: :unav
DOI: 10.15468/dl.jnmt3w
title: Occurrence Download

description: A dataset containing 352 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "DatasetKey is one of (Banco de Datos de la Biodiversidad de la Comunitat Valenciana, Colección de plantas vasculares del herbario de la Universitat de València (VAL), Herbario HSS Finca La Orden-Valdesequera (CICYTEX). Junta de Extremadura, Col·lecció de plantes de l'herbari de la Universitat de Barcelona, Colección de plantas vasculares del Herbario \"Jaime Andrés Rodríguez\". LEB)",
 "Geometry POLYGON((-9.37628 43.39507,-10.54329 42.71491,-9.38221 41.11666,-10.42719 39.38885,-9.73054 36.59864,-7.29226 36.55201,-7.35032 35.80225,-5.26037 35.94338,-1.83517 36.22487,0.83532 38.44028,0.19672 39.47852,0.89337 40.19178,2.98926 40.89911,4.38256 42.97176,2.29261 42.97176,0.43487 43.05666,-0.72621 43.35287,-1.88729 43.56357,-2.87421 43.77354,-3.68697 43.94098,-5.71887 44.02453,-7.5766 44.23288,-8.67963 43.85732,-9.37628 43.39507))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Senecio lividus"
 ]
}

 The dataset includes 352 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004889-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qdh2tv
title: Occurrence Download

description: A dataset containing 346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "DatasetKey is one of (Banco de Datos de la Biodiversidad de la Comunitat Valenciana, Colección de plantas vasculares del herbario de la Universitat de València (VAL), Herbario HSS Finca La Orden-Valdesequera (CICYTEX). Junta de Extremadura, Col·lecció de plantes de l'herbari de la Universitat de Barcelona, Colección de plantas vasculares del Herbario \"Jaime Andrés Rodríguez\". LEB)",
 "Geometry POLYGON((-2.02379 43.59244,-5.78367 44.02087,-7.76255 43.98529,-9.39513 43.2691,-8.94988 42.28872,-8.00991 42.14216,-6.971 41.99526,-6.03103 41.73737,-6.22892 41.21846,-6.67417 40.84527,-6.67417 40.0547,-7.16889 39.59878,-6.82258 39.13984,-7.02047 38.52323,-6.82258 38.05727,-7.3173 37.6667,-7.21836 36.99798,-5.48684 36.00381,-4.54687 36.28346,-2.41957 36.28346,-0.29227 37.58833,0.94453 39.06305,1.5382 39.75109,3.6655 42.14216,3.17078 42.61724,2.37922 42.72636,1.58767 42.94403,0.99401 43.01642,0.35087 42.98024,-0.78699 43.23307,-2.02379 43.59244))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Senecio lividus"
 ]
}

 The dataset includes 346 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004886-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/3euoqa
title: Pure_Faba_HUAP30_20240408_152022.jpg

description: :unav
DOI: 10.57745/gbowqr
title: Pure_tri_TS_REDN11_20240422_155307.jpg

description: :unav
DOI: 10.57745/wttcd5
title: Pure_tri_TS_A12_20240422_155043_mask.png

description: :unav
DOI: 10.57745/dcodoi
title: Pure_Faba_REDN11_20240422_163816.jpg

description: :unav
DOI: 10.15468/dl.dbxgy8
title: Occurrence Download

description: A dataset containing 348 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "DatasetKey is one of (Banco de Datos de la Biodiversidad de la Comunitat Valenciana, Colección de plantas vasculares del herbario de la Universitat de València (VAL), Herbario HSS Finca La Orden-Valdesequera (CICYTEX). Junta de Extremadura, Col·lecció de plantes de l'herbari de la Universitat de Barcelona, Colección de plantas vasculares del Herbario \"Jaime Andrés Rodríguez\". LEB)",
 "Geometry POLYGON((-9.54323 43.21819,-8.04896 41.92814,-6.34859 41.50506,-7.37912 39.74538,-6.81233 38.98853,-7.12149 38.1425,-7.63675 36.95786,-6.03943 36.17155,-5.31806 36.17155,-2.02037 36.83424,-0.62916 37.61378,0.34984 38.82815,-0.26848 39.1885,0.60747 40.68965,3.13226 41.77461,3.38989 42.50057,-2.0719 43.48047,-7.68828 43.89034,-9.54323 43.21819))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Senecio lividus"
 ]
}

 The dataset includes 348 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004888-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5wabtm
title: Occurrence Download

description: A dataset containing 178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Madagascar",
 "TaxonKey is Amegilla antimena (Saussure, 1890)"
 ]
}

 The dataset includes 178 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024998-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/crngfmfzsb
title: Mother-cord blood-infant DENV, CHIKV NT_Banpong Hospital, Thailand

description: The file shows DENV1-4 and CHIK NT from 141 mother-infant pairs
DOI: 10.17632/crngfmfzsb.1
title: Mother-cord blood-infant DENV, CHIKV NT_Banpong Hospital, Thailand

description: The file shows DENV1-4 and CHIK NT from 141 mother-infant pairs
DOI: 10.17632/zn5nhpjm36.1
title: Kinetics of methanethiol oxidation by oxygen under aqueous conditions

description: This dataset contains all the data used in 'Kinetics of Methanethiol Oxidation by Oxygen under Aqueous Conditions,' including experimental conditions and solution compositions.
DOI: 10.17632/zn5nhpjm36.2
title: Kinetics of methanethiol oxidation by oxygen under aqueous conditions

description: This dataset contains all the data used in 'Kinetics of Methanethiol Oxidation by Oxygen under Aqueous Conditions,' including experimental conditions and solution compositions.
DOI: 10.17632/3xpcbpxyc9.1
title: DATASET_INTERLIMB_CRTMS2024

description: Dataset of experiment to investigate the effect of rTMS over cerebellum on visuomotor learning during inter-limb coordination task.
DOI: 10.5281/zenodo.15077269
title: OPSIN PubMed Names
DOI: 10.5281/zenodo.15077270
title: OPSIN PubMed Names
DOI: 10.17632/xjpbk78wx9
title: Species Description of Sporisorium enterogonipteri R Knop., Hammerb., & T Bose, sp. nov.

description: ITS, LSU, and concatented (ITS+LSU) alignments and tree files for the species description of Sporisorium enterogonipteri
DOI: 10.17632/xjpbk78wx9.1
title: Species Description of Sporisorium enterogonipteri R Knop., Hammerb., & T Bose, sp. nov.

description: ITS, LSU, and concatented (ITS+LSU) alignments and tree files for the species description of Sporisorium enterogonipteri
DOI: 10.17632/f2hvx5vs5n.1
title: Phosphorescence-based oxygen sensing reveals size-dependent survival and motility of metastatic prostate cancer cells in severely hypoxic conditions. Zhao et al.

description: This dataset contains data collected for analyzing cell movement under hypoxic conditions.
DOI: 10.17632/f2hvx5vs5n.2
title: Phosphorescence-based O2 sensing reveals size-dependent survival and motility of metastatic prostate cancer cells in self-generated hypoxia. Hosny et al.

description: This dataset contains data collected for analyzing cell movement under hypoxic conditions.
DOI: 10.17632/hchdb3vkhw.1
title: Design Files for Fin Cooling

description: This data set contains the preliminary computational files which are used to determine the efficiency and effectiveness of a novel fin-based passive cooling device for screw-based material extrusion additive manufacturing.
DOI: 10.17632/p527hfpnkb.2
title: Dataset of Patient Mrs. Shashi Bisen (Hyper immune- ANCA-associated Vasculities (Granulomatosis with Polyangiitis); lungs and renal diseases.)

description: This dataset is generated for analyzing the reports of patient Mrs. Shashi Bisen, who is suffereing from the ANCA-associated Vasculities (Granulomatosis with Polyangiitis); lungs and renal diseases. This datasets is for resercah and analysis of AAVs diseases. This datasets will be used for writing a scientific reports or article on the advancement of resrach. Mrs. Shashi Bisen is also conributor in this dataset. Patient Shashi Bisen has given his written consent for analysising and utilizing of these datasets for advancment of resercah and scientifc contribution for the advancment and betterment of AAVs treatment. Dr. Ravindra Verma and Prof. (Dr.) Prakash S Bisen are the wellknown meidical biotechnologist. We all declare no competing interests. There is no financial involment of any agency, labortaory and hospitals. All datasets are owned by Mr. Shashi Bisen and Prof. (Dr.) Prakash S Bisen. These datasets are only for research puropose.
DOI: 10.17632/85p9mh3zmp.1
title: How to Select the Leader in a One-Shot Public Goods Game: Evidence from the Laboratory

description: We experimentally study how leadership selection mechanisms influence public goods provision in a random-pairing repeated one-shot public goods game. The central hypothesis is that the way leaders are chosen—whether through random selection or through voluntary self-selection—affects group cooperation through signaling and reciprocity. In particular, we predicted that Voluntary leadership from a randomly selected candidate (VL-RC) is a promising endogenous leadership selection mechanism, primarily because assuming leadership by revealed preference signals cooperative play, the absence of leadership leaves the possibility of unlucky cooperative candidates, and sole leadership removes the leader’s free-riding incentives.
 One hundred and sixty college students from Tsinghua University participated in the public goods game. In each period, we randomly assigned subjects into groups of four, and subjects were endowed with a fixed number of tokens, which they could either keep privately or contribute to a public account. We used a random pairing design, ensuring each interaction was a fresh, one-shot decision. We tested five treatments: a baseline control with simultaneous contributions and four leadership treatments—Random Leadership (RL), Voluntary Leadership (VL), Random Leadership from Voluntary Candidates (RL-VC), and Voluntary Leadership from a Random Candidate (VL-RC). 
 The data revealed several notable findings. First, introducing a leadership role did not consistently boost overall contributions compared with the control, and the pure voluntary mechanism (VL) performed the worst. Groups without any leader contributed significantly less than those with a leader. VL-RC was the most effective endogenous mechanism: Imposing a higher barrier to leadership, it reduced the diffusion of responsibility and free-riding among potential leaders. In contrast, mechanisms allowing multiple leaders (VL and RL-VC) tended to induce more selfish behavior, as evidenced by lower average contributions from leaders in these settings. Additionally, leaders generally contributed more than followers. However, the strength of the leader-follower influence varied across treatments. There was a significant positive correlation between leader and follower contributions in VL but not in other treatments.
 The findings suggest that the informativeness of signaling and reciprocity of leadership selection mechanisms is crucial for public goods provision. Policymakers and organizational leaders shall create barriers in selecting candidates and privately encourage the candidate who values the common good the most to lead by example voluntarily.
DOI: 10.5281/zenodo.13348979
title: Synthetic data (Part 2) for HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields

description: #############

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields, CVPR 2024

#############

Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis.

Affiliation: EPFL

Date: June, 2024

Link to the CVPR article: https://openaccess.thecvf.com/content/CVPR2024/papers/Qi_HOISDF_Constraining_3D_Hand-Object_Pose_Estimation_with_Global_Signed_Distance_CVPR_2024_paper.pdf

Link to the Arxiv article: https://arxiv.org/abs/2402.17062

--------------------------------



Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the rendered images and the segmentation masks that we use to train our model on HO3Dv2 dataset. 


The overall structure of the data is:


├── render_sdf_ho3d.zip                              - Contains the rendered images for HO3Dv2.

 


The code to reproduce the results is available at: https://github.com/amathislab/HOISDF

 

--------------------------------


If you find our code, weights, predictions or ideas useful, please cite:

@inproceedings{qi2024hoisdf,  title={HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields},  author={Qi, Haozhe and Zhao, Chen and Salzmann, Mathieu and Mathis, Alexander},  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},  pages={10392--10402},  year={2024}}
DOI: 10.5281/zenodo.13348980
title: HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields: Synthetic data

description: #############

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields, CVPR 2024

#############

Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis.

Affiliation: EPFL

Date: June, 2024

Link to the CVPR article: https://openaccess.thecvf.com/content/CVPR2024/papers/Qi_HOISDF_Constraining_3D_Hand-Object_Pose_Estimation_with_Global_Signed_Distance_CVPR_2024_paper.pdf

Link to the Arxiv article: https://arxiv.org/abs/2402.17062

--------------------------------



Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the rendered images and the segmentation masks that we use to train our model on HO3Dv2 dataset. 


The overall structure of the data is:


├── render_sdf_ho3d.zip                              - Contains the rendered images for HO3Dv2.

 


The code to reproduce the results is available at: https://github.com/amathislab/HOISDF

 

--------------------------------


If you find our code, weights, predictions or ideas useful, please cite:

@inproceedings{qi2024hoisdf,  title={HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields},  author={Qi, Haozhe and Zhao, Chen and Salzmann, Mathieu and Mathis, Alexander},  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},  pages={10392--10402},  year={2024}}
DOI: 10.5281/zenodo.15077294
title: Synthetic data (Part 2) for HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields

description: #############

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields, CVPR 2024

#############

Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis.

Affiliation: EPFL

Date: June, 2024

Link to the CVPR article: https://openaccess.thecvf.com/content/CVPR2024/papers/Qi_HOISDF_Constraining_3D_Hand-Object_Pose_Estimation_with_Global_Signed_Distance_CVPR_2024_paper.pdf

Link to the Arxiv article: https://arxiv.org/abs/2402.17062

--------------------------------



Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the rendered images and the segmentation masks that we use to train our model on HO3Dv2 dataset. 


The overall structure of the data is:


├── render_sdf_ho3d.zip                              - Contains the rendered images for HO3Dv2.

 


The code to reproduce the results is available at: https://github.com/amathislab/HOISDF

 

--------------------------------


If you find our code, weights, predictions or ideas useful, please cite:

@inproceedings{qi2024hoisdf,  title={HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields},  author={Qi, Haozhe and Zhao, Chen and Salzmann, Mathieu and Mathis, Alexander},  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},  pages={10392--10402},  year={2024}}
DOI: 10.17632/85p9mh3zmp.2
title: How to Select the Leader in a One-Shot Public Goods Game: Evidence from the Laboratory

description: We experimentally study how leadership selection mechanisms influence public goods provision in a random-pairing repeated one-shot public goods game. The central hypothesis is that the way leaders are chosen—whether through random selection or through voluntary self-selection—affects group cooperation through signaling and reciprocity. In particular, we predicted that Voluntary leadership from a randomly selected candidate (VL-RC) is a promising endogenous leadership selection mechanism, primarily because assuming leadership by revealed preference signals cooperative play, the absence of leadership leaves the possibility of unlucky cooperative candidates, and sole leadership removes the leader’s free-riding incentives.
 One hundred and sixty college students from Tsinghua University participated in the public goods game. In each period, we randomly assigned subjects into groups of four, and subjects were endowed with a fixed number of tokens, which they could either keep privately or contribute to a public account. We used a random pairing design, ensuring each interaction was a fresh, one-shot decision. We tested five treatments: a baseline control with simultaneous contributions and four leadership treatments—Random Leadership (RL), Voluntary Leadership (VL), Random Leadership from Voluntary Candidates (RL-VC), and Voluntary Leadership from a Random Candidate (VL-RC). 
 The data revealed several notable findings. First, introducing a leadership role did not consistently boost overall contributions compared with the control, and the pure voluntary mechanism (VL) performed the worst. Groups without any leader contributed significantly less than those with a leader. VL-RC was the most effective endogenous mechanism: Imposing a higher barrier to leadership, it reduced the diffusion of responsibility and free-riding among potential leaders. In contrast, mechanisms allowing multiple leaders (VL and RL-VC) tended to induce more selfish behavior, as evidenced by lower average contributions from leaders in these settings. Additionally, leaders generally contributed more than followers. However, the strength of the leader-follower influence varied across treatments. There was a significant positive correlation between leader and follower contributions in VL but not in other treatments.
 The findings suggest that the informativeness of signaling and reciprocity of leadership selection mechanisms is crucial for public goods provision. Policymakers and organizational leaders shall create barriers in selecting candidates and privately encourage the candidate who values the common good the most to lead by example voluntarily.
DOI: 10.5281/zenodo.13228002
title: Synthetic data (Part 1) for "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields"

description: #############

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields, CVPR 2024

#############

Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis.

Affiliation: EPFL

Date: June, 2024

Link to the CVPR article: https://openaccess.thecvf.com/content/CVPR2024/papers/Qi_HOISDF_Constraining_3D_Hand-Object_Pose_Estimation_with_Global_Signed_Distance_CVPR_2024_paper.pdf

Link to the Arxiv article: https://arxiv.org/abs/2402.17062

--------------------------------



Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the preprocessed SDF samples. Meanwhile, we also include rendered data for HO3Dv2 here. 


The overall structure of the data is:


├── render_sdf_ho3d.zip                              - Contains the processed SDF files for HO3Dv2 rendered images.

├── train_ho3d.zip                                       - Contains the processed SDF files for HO3Dv2 training set.

├── full_test_dexycb.zip                               - Contains the processed SDF files for DexYCB full test set.

 


The code to reproduce the results is available at: https://github.com/amathislab/HOISDF

 

--------------------------------


If you find our code, weights, predictions or ideas useful, please cite:

@inproceedings{qi2024hoisdf,  title={HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields},  author={Qi, Haozhe and Zhao, Chen and Salzmann, Mathieu and Mathis, Alexander},  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},  pages={10392--10402},  year={2024}}