cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25592/uhhfdm.17016
title: Prediction error-related memory enhancement depends on the neural state surrounding the prediction error event

description: Prediction errors (PEs) can enhance memory for preceding events. While such PE-related memory enhancements are critical for understanding adaptive memory, their underlying mechanisms are not fully understood. Using electroencephalography (EEG) and neuro-navigated transcranial magnetic stimulation (TMS) in combination with multivariate pattern analysis, this pre-registered study aimed to elucidate the brain mechanisms underlying PE effects on memory. Specifically, we tested whether PEs trigger a neural reactivation of the preceding stimulus and whether the PE-induced effects on memory depend on a specific neural state before the PE. We also examined whether inhibitory TMS over the superior parietal cortex (SPC) reduces PE effects on memory. A total of 118 participants (male and female) received sham or inhibitory theta-burst stimulation over the SPC before completing an incidental encoding-fear learning task. In this task, participants learned trial-unique stimuli and predicted whether these would be followed by an electric shock, while EEG was recorded. Recognition memory was tested 24 hours later. Our findings show that signed PEs enhance subsequent memory, depending on theta and alpha oscillations as well as neural stimulus (category) reactivation shortly before the PE. Moreover, this memory enhancement was associated with post-PE theta but not with PE-driven stimulus (category) reinstatement. Theta-burst stimulation over the SPC led to a more conservative mnemonic response bias but left the PE effect on memory unaffected. Together, our findings reveal that PE effects on memory formation are influenced by neural states and representations surrounding the PE, providing new insights into the neural mechanisms of adaptive memory formation.
description: Analysis folder contains all relevant scripts for data analysis. Study materials folder includes materials and experimental task. Questionnaire data includes questionnaire data from all subjects in one file + explanations. Raw data is chunked into folders of mulitple subjects and includes EEG data, SCR data and behavioral data of each subject.
DOI: 10.18112/openneuro.ds005811.v1.0.5
title: NOD-EEG
DOI: 10.5281/zenodo.14849162
title: Step_by_Step_Proof_of_the_Goldbach_Conjecture_Using_the_Extended_Number_x__1_.pdf

description: Goldbach Detailed Proof Updated
DOI: 10.5281/zenodo.14849163
title: Step_by_Step_Proof_of_the_Goldbach_Conjecture_Using_the_Extended_Number_x__1_.pdf

description: Goldbach Detailed Proof Updated
DOI: 10.6084/m9.figshare.28387934
title: chapter3 B subtilis for pulcherrimin production

description: supplementary materials for <b>Developing </b><b><i>Bacillus subtilis</i></b><b> as cell factory for the production of the natural biocontrol compound pulcherrimin</b>
DOI: 10.6084/m9.figshare.28387934.v2
title: chapter3 B subtilis for pulcherrimin production

description: supplementary materials for <b>Developing </b><b><i>Bacillus subtilis</i></b><b> as cell factory for the production of the natural biocontrol compound pulcherrimin</b>
DOI: 10.6084/m9.figshare.28387934.v1
title: chapter3 B subtilis for pulcherrimin production

description: supplementary materials for <b>Developing </b><b><i>Bacillus subtilis</i></b><b> as cell factory for the production of the natural biocontrol compound pulcherrimin</b>
DOI: 10.18112/openneuro.ds005810.v1.0.2
title: NOD-MEG
DOI: 10.15468/dl.k7kycq
title: Occurrence Download

description: A dataset containing 67711 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chelydra serpentina (Linnaeus, 1758)"
 ]
}

 The dataset includes 67711 records from 204 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023342-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7w8eb4
title: Occurrence Download

description: A dataset containing 57025 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chinese Taipei",
 "TaxonKey is Duttaphrynus melanostictus (Schneider, 1799)"
 ]
}

 The dataset includes 57025 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023320-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10721006
title: e-IPO Indonesia Data - Investment
DOI: 10.15468/dl.zzxymt
title: Occurrence Download

description: A dataset containing 942 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lasiodiplodia theobromae (Pat.) Griffon & Maubl."
 ]
}

 The dataset includes 942 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023350-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ex8akn
title: Occurrence Download

description: A dataset containing 1072 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Forcipomyia Meigen, 1818"
 ]
}

 The dataset includes 1072 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023348-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mytfy6
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cymothoe zombana Bethune-Baker, 1926"
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023349-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wqa3n3
title: Occurrence Download

description: A dataset containing 1370 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ukraine",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is CR",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 1370 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023351-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brskc7
title: Occurrence Download

description: A dataset containing 3308363 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Coleoptera"
 ]
}

 The dataset includes 3308363 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023346-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14712437
title: GEDI total tree cover footprint Iberian Peninsula - 2019-2021

description: This is the data used or generated in the paper, "Canopy height and biomass distribution across the forests of Iberian Peninsula".

Authors

Yang Su a, b, c, Martin Schwartz b, Ibrahim Fayad b, García Alonso Mariano d, Miguel A. Zavala e, Julián Tijerín-Triviño e, Julen Astigarraga e, Verónica Cruz f, Siyu Liu g, Xianglin Zhang c, h, Songchao Chen h,i, François Ritter b, Nikola Besic j, Alexandre d'Aspremont a, Philippe Ciais b

 

Affiliations

a Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France

b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France

c UMR ECOSYS, INRAE AgroParisTech, Université Paris-Saclay, 91120 Palaiseau, France

d University of Alcalá, Department of Geology, Geography and the Environment, Enviromental Remote Sensing Research Group, 28801 Alcalá de Henares, Spain

e University of Alcalá, Department of Life Sciences, 28801 Alcalá de Henares, Spain

f Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, 28040 Madrid, Spain

g Department of Geosciences and Natural Resource Management, Copenhagen University, 1958 Frederiksberg, Denmark

h College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China

i ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311215 Hangzhou, China

j IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France

 

Corresponding Author

Yang Su

yang.su@ens.fr

+33 1 89 10 07 67

École normale supérieure - PSL

 

To use the model and data, please contact the corresponding author for more details.

 

The maps of canopy height and above-ground biomass provided by this study can be found on Zenodo, detailed information about how to access those datasets can be found in Table 2 in this study. A preview of those maps can be found here: https://ens-yangsu-forest-spain-als.projects.earthengine.app/view/ai4forest-iberian-peninsula




Funding



Artificial Intelligence for forest monitoring from space – AI4Forests

Agence Nationale de la Recherche
Find out more...

 

MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41).

MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42). 

VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship.
DOI: 10.5281/zenodo.14712438
title: GEDI total tree cover footprint Iberian Peninsula - 2019-2021

description: This is the data used or generated in the paper, "Canopy height and biomass distribution across the forests of Iberian Peninsula".

Authors

Yang Su a, b, c, Martin Schwartz b, Ibrahim Fayad b, García Alonso Mariano d, Miguel A. Zavala e, Julián Tijerín-Triviño e, Julen Astigarraga e, Verónica Cruz f, Siyu Liu g, Xianglin Zhang c, h, Songchao Chen h,i, François Ritter b, Nikola Besic j, Alexandre d'Aspremont a, Philippe Ciais b

 

Affiliations

a Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France

b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France

c UMR ECOSYS, INRAE AgroParisTech, Université Paris-Saclay, 91120 Palaiseau, France

d University of Alcalá, Department of Geology, Geography and the Environment, Enviromental Remote Sensing Research Group, 28801 Alcalá de Henares, Spain

e University of Alcalá, Department of Life Sciences, 28801 Alcalá de Henares, Spain

f Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, 28040 Madrid, Spain

g Department of Geosciences and Natural Resource Management, Copenhagen University, 1958 Frederiksberg, Denmark

h College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China

i ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311215 Hangzhou, China

j IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France

 

Corresponding Author

Yang Su

yang.su@ens.fr

+33 1 89 10 07 67

École normale supérieure - PSL

 

To use the model and data, please contact the corresponding author for more details.

 

The maps of canopy height and above-ground biomass provided by this study can be found on Zenodo, detailed information about how to access those datasets can be found in Table 2 in this study. A preview of those maps can be found here: https://ens-yangsu-forest-spain-als.projects.earthengine.app/view/ai4forest-iberian-peninsula




Funding



Artificial Intelligence for forest monitoring from space – AI4Forests

Agence Nationale de la Recherche
Find out more...

 

MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41).

MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42). 

VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship.
DOI: 10.6084/m9.figshare.28388048
title: IPC10 - 2019, Dunedin, New Zealand - Abstracts

description: Abstracts for the 10th International Penguin Conference (IPC10) held in Dunedin, New Zealand, 24-28 August 2019.
DOI: 10.5281/zenodo.14670677
title: Sentinel 2 part 3 Iberian Peninsula - 2021 - part 2

description: This is the data used or generated in the paper, "Canopy height and biomass distribution across the forests of Iberian Peninsula".

Authors

Yang Su a, b, c, Martin Schwartz b, Ibrahim Fayad b, García Alonso Mariano d, Miguel A. Zavala e, Julián Tijerín-Triviño e, Julen Astigarraga e, Verónica Cruz f, Siyu Liu g, Xianglin Zhang c, h, Songchao Chen h,i, François Ritter b, Nikola Besic j, Alexandre d'Aspremont a, Philippe Ciais b

 

Affiliations

a Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France

b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France

c UMR ECOSYS, INRAE AgroParisTech, Université Paris-Saclay, 91120 Palaiseau, France

d University of Alcalá, Department of Geology, Geography and the Environment, Enviromental Remote Sensing Research Group, 28801 Alcalá de Henares, Spain

e University of Alcalá, Department of Life Sciences, 28801 Alcalá de Henares, Spain

f Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, 28040 Madrid, Spain

g Department of Geosciences and Natural Resource Management, Copenhagen University, 1958 Frederiksberg, Denmark

h College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China

i ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311215 Hangzhou, China

j IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France

 

Corresponding Author

Yang Su

yang.su@ens.fr

+33 1 89 10 07 67

École normale supérieure - PSL

 

To use the model and data, please contact the corresponding author for more details.

 

The maps of canopy height and above-ground biomass provided by this study can be found on Zenodo, detailed information about how to access those datasets can be found in Table 2 in this study. A preview of those maps can be found here: https://ens-yangsu-forest-spain-als.projects.earthengine.app/view/ai4forest-iberian-peninsula




Funding



Artificial Intelligence for forest monitoring from space – AI4Forests

Agence Nationale de la Recherche
Find out more...

 

MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41).

MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42). 

VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship.
DOI: 10.5281/zenodo.14670678
title: Sentinel 2 part 3 Iberian Peninsula - 2021 - part 2

description: This is the data used or generated in the paper, "Canopy height and biomass distribution across the forests of Iberian Peninsula".

Authors

Yang Su a, b, c, Martin Schwartz b, Ibrahim Fayad b, García Alonso Mariano d, Miguel A. Zavala e, Julián Tijerín-Triviño e, Julen Astigarraga e, Verónica Cruz f, Siyu Liu g, Xianglin Zhang c, h, Songchao Chen h,i, François Ritter b, Nikola Besic j, Alexandre d'Aspremont a, Philippe Ciais b

 

Affiliations

a Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France

b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France

c UMR ECOSYS, INRAE AgroParisTech, Université Paris-Saclay, 91120 Palaiseau, France

d University of Alcalá, Department of Geology, Geography and the Environment, Enviromental Remote Sensing Research Group, 28801 Alcalá de Henares, Spain

e University of Alcalá, Department of Life Sciences, 28801 Alcalá de Henares, Spain

f Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, 28040 Madrid, Spain

g Department of Geosciences and Natural Resource Management, Copenhagen University, 1958 Frederiksberg, Denmark

h College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China

i ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311215 Hangzhou, China

j IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France

 

Corresponding Author

Yang Su

yang.su@ens.fr

+33 1 89 10 07 67

École normale supérieure - PSL

 

To use the model and data, please contact the corresponding author for more details.

 

The maps of canopy height and above-ground biomass provided by this study can be found on Zenodo, detailed information about how to access those datasets can be found in Table 2 in this study. A preview of those maps can be found here: https://ens-yangsu-forest-spain-als.projects.earthengine.app/view/ai4forest-iberian-peninsula




Funding



Artificial Intelligence for forest monitoring from space – AI4Forests

Agence Nationale de la Recherche
Find out more...

 

MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41).

MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42). 

VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship.
DOI: 10.5281/zenodo.14670234
title: Sentinel 2 part 3 Iberian Peninsula - 2021 - part 1

description: This is the data used or generated in the paper, "Canopy height and biomass distribution across the forests of Iberian Peninsula".

Authors

Yang Su a, b, c, Martin Schwartz b, Ibrahim Fayad b, García Alonso Mariano d, Miguel A. Zavala e, Julián Tijerín-Triviño e, Julen Astigarraga e, Verónica Cruz f, Siyu Liu g, Xianglin Zhang c, h, Songchao Chen h,i, François Ritter b, Nikola Besic j, Alexandre d'Aspremont a, Philippe Ciais b

 

Affiliations

a Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France

b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France

c UMR ECOSYS, INRAE AgroParisTech, Université Paris-Saclay, 91120 Palaiseau, France

d University of Alcalá, Department of Geology, Geography and the Environment, Enviromental Remote Sensing Research Group, 28801 Alcalá de Henares, Spain

e University of Alcalá, Department of Life Sciences, 28801 Alcalá de Henares, Spain

f Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, 28040 Madrid, Spain

g Department of Geosciences and Natural Resource Management, Copenhagen University, 1958 Frederiksberg, Denmark

h College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China

i ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311215 Hangzhou, China

j IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France

 

Corresponding Author

Yang Su

yang.su@ens.fr

+33 1 89 10 07 67

École normale supérieure - PSL

 

To use the model and data, please contact the corresponding author for more details.

 

The maps of canopy height and above-ground biomass provided by this study can be found on Zenodo, detailed information about how to access those datasets can be found in Table 2 in this study. A preview of those maps can be found here: https://ens-yangsu-forest-spain-als.projects.earthengine.app/view/ai4forest-iberian-peninsula




Funding



Artificial Intelligence for forest monitoring from space – AI4Forests

Agence Nationale de la Recherche
Find out more...

 

MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41).

MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42). 

VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship.
DOI: 10.5281/zenodo.14670235
title: Sentinel 2 part 3 Iberian Peninsula - 2021 - part 1

description: This is the data used or generated in the paper, "Canopy height and biomass distribution across the forests of Iberian Peninsula".

Authors

Yang Su a, b, c, Martin Schwartz b, Ibrahim Fayad b, García Alonso Mariano d, Miguel A. Zavala e, Julián Tijerín-Triviño e, Julen Astigarraga e, Verónica Cruz f, Siyu Liu g, Xianglin Zhang c, h, Songchao Chen h,i, François Ritter b, Nikola Besic j, Alexandre d'Aspremont a, Philippe Ciais b

 

Affiliations

a Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France

b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France

c UMR ECOSYS, INRAE AgroParisTech, Université Paris-Saclay, 91120 Palaiseau, France

d University of Alcalá, Department of Geology, Geography and the Environment, Enviromental Remote Sensing Research Group, 28801 Alcalá de Henares, Spain

e University of Alcalá, Department of Life Sciences, 28801 Alcalá de Henares, Spain

f Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, 28040 Madrid, Spain

g Department of Geosciences and Natural Resource Management, Copenhagen University, 1958 Frederiksberg, Denmark

h College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China

i ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311215 Hangzhou, China

j IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France

 

Corresponding Author

Yang Su

yang.su@ens.fr

+33 1 89 10 07 67

École normale supérieure - PSL

 

To use the model and data, please contact the corresponding author for more details.

 

The maps of canopy height and above-ground biomass provided by this study can be found on Zenodo, detailed information about how to access those datasets can be found in Table 2 in this study. A preview of those maps can be found here: https://ens-yangsu-forest-spain-als.projects.earthengine.app/view/ai4forest-iberian-peninsula




Funding



Artificial Intelligence for forest monitoring from space – AI4Forests

Agence Nationale de la Recherche
Find out more...

 

MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41).

MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42). 

VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship.