cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14839845
title: unimpeded: rlcdm planck_2018_plik_nolens+sn.pantheon

description: cosmological model:rlcdm, dataset:planck_2018_plik_nolens+sn.pantheon
DOI: 10.5281/zenodo.14839846
title: unimpeded: rlcdm planck_2018_plik_nolens+sn.pantheon

description: cosmological model:rlcdm, dataset:planck_2018_plik_nolens+sn.pantheon
DOI: 10.5281/zenodo.14845837
title: 4DHydro_Results_Tetis_Smap_Po_15sec_daily_SC11_20191110_20191231

description: Modeling results with TETIS software, for Po River with a spatial resolution of 15 sec, and temporal resolution daily. Experiment SC11. Earth observation Smap.

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2


Additional, a .csv file with discharge values at certain points, for each day in cubic meters per second.
DOI: 10.5281/zenodo.14845838
title: 4DHydro_Results_Tetis_Smap_Po_15sec_daily_SC11_20191110_20191231

description: Modeling results with TETIS software, for Po River with a spatial resolution of 15 sec, and temporal resolution daily. Experiment SC11. Earth observation Smap.

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2


Additional, a .csv file with discharge values at certain points, for each day in cubic meters per second.
DOI: 10.5281/zenodo.14845814
title: Raw data of the paper: Deceived by the Fick principle: blood flow distribution in heart failure

description: Abstract



Aims: The Fick principle states that oxygen uptake (V̇O2) is cardiac output (Qc) * arterial-venous O2 content difference [ΔC(a-v)O2]. Blood flow distribution is hidden in Fick principle, and its relevance during exercise in heart failure (HF) is undefined. To highlight the role of blood flow distribution, we evaluated peak exercise V̇O2, Qc, and ΔC(a-v)O2, before and after HF therapeutic interventions.

Methods and results: Symptom-limited cardiopulmonary exercise tests with Qc measurement (inert gas rebreathing) was performed in 234 HF patients before and 6 months after successful exercise training, cardiac resynchronization therapy, or percutaneous edge-to-edge mitral valve repair. Considering all tests (n = 468), a direct correlation between peakV̇O2 and peakQc (R2 = 0.47) and workload (R2 = 0.70) was observed. Patients were grouped according to treatment efficacy in Group 1 (peakV̇O2 increase >10%, n = 93), Group 2 (peakV̇O2 change between 0 and 10%, n = 60), and Group 3 (reduction in peakV̇O2, n = 81). Post-treatment peakV̇O2 changes poorly correlated with peakQc and peakΔC(a-v)O2 changes. Differently, post-procedure peakQc vs. peakΔC(a-v)O2 changes showed a close negative correlation (R2 = 0.46), becoming stronger grouping patients according to peakV̇O2 improvement (R2 = 0.64, 0.79, and 0.58 in Groups 1, 2, and 3, respectively). In 76% of patients, peakQc and ΔC(a-v)O2 changes diverged regardless of treatment.

Conclusion: The bulk of these data suggests that blood flow distribution plays a pivotal role on peakV̇O2 determination regardless of HF treatment strategies. Accordingly, for assessing HF treatment efficacy on exercise performance, the sole peakV̇O2 may be deceptive and the combination of V̇O2, Qc and ΔC(a-v)O2, must be considered.
DOI: 10.5281/zenodo.14845815
title: Raw data of the paper: Deceived by the Fick principle: blood flow distribution in heart failure

description: Abstract



Aims: The Fick principle states that oxygen uptake (V̇O2) is cardiac output (Qc) * arterial-venous O2 content difference [ΔC(a-v)O2]. Blood flow distribution is hidden in Fick principle, and its relevance during exercise in heart failure (HF) is undefined. To highlight the role of blood flow distribution, we evaluated peak exercise V̇O2, Qc, and ΔC(a-v)O2, before and after HF therapeutic interventions.

Methods and results: Symptom-limited cardiopulmonary exercise tests with Qc measurement (inert gas rebreathing) was performed in 234 HF patients before and 6 months after successful exercise training, cardiac resynchronization therapy, or percutaneous edge-to-edge mitral valve repair. Considering all tests (n = 468), a direct correlation between peakV̇O2 and peakQc (R2 = 0.47) and workload (R2 = 0.70) was observed. Patients were grouped according to treatment efficacy in Group 1 (peakV̇O2 increase >10%, n = 93), Group 2 (peakV̇O2 change between 0 and 10%, n = 60), and Group 3 (reduction in peakV̇O2, n = 81). Post-treatment peakV̇O2 changes poorly correlated with peakQc and peakΔC(a-v)O2 changes. Differently, post-procedure peakQc vs. peakΔC(a-v)O2 changes showed a close negative correlation (R2 = 0.46), becoming stronger grouping patients according to peakV̇O2 improvement (R2 = 0.64, 0.79, and 0.58 in Groups 1, 2, and 3, respectively). In 76% of patients, peakQc and ΔC(a-v)O2 changes diverged regardless of treatment.

Conclusion: The bulk of these data suggests that blood flow distribution plays a pivotal role on peakV̇O2 determination regardless of HF treatment strategies. Accordingly, for assessing HF treatment efficacy on exercise performance, the sole peakV̇O2 may be deceptive and the combination of V̇O2, Qc and ΔC(a-v)O2, must be considered.
DOI: 10.5281/zenodo.14839801
title: unimpeded: mlcdm bao.sdss_dr16+planck_2018_CamSpec

description: cosmological model:mlcdm, dataset:bao.sdss_dr16+planck_2018_CamSpec
DOI: 10.5281/zenodo.14839802
title: unimpeded: mlcdm bao.sdss_dr16+planck_2018_CamSpec

description: cosmological model:mlcdm, dataset:bao.sdss_dr16+planck_2018_CamSpec
DOI: 10.5281/zenodo.14845843
title: 4DHydro_Results_Tetis_Smap_Po_7p5sec_daily_SC11_20191110_20191231

description: Description



Modeling results with TETIS software, for Po River with a spatial resolution of 7.5 sec, and temporal resolution daily. Experiment SC11. Earth observation Smap.

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2


Additional, a .csv file with discharge values at certain points, for each day in cubic meters per second.
DOI: 10.5281/zenodo.14845844
title: 4DHydro_Results_Tetis_Smap_Po_7p5sec_daily_SC11_20191110_20191231

description: Description



Modeling results with TETIS software, for Po River with a spatial resolution of 7.5 sec, and temporal resolution daily. Experiment SC11. Earth observation Smap.

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2


Additional, a .csv file with discharge values at certain points, for each day in cubic meters per second.
DOI: 10.25377/sussex.28368689
title: Synthesizer test grid

description: [Temporary test record to evaluate integration with external software]<br>Test grid used by the Synthesizer synthetic observations pipeline.https://github.com/flaresimulations/synthesizer<br><br>
DOI: 10.25377/sussex.28368689.v1
title: Synthesizer test grid

description: [Temporary test record to evaluate integration with external software]<br>Test grid used by the Synthesizer synthetic observations pipeline.https://github.com/flaresimulations/synthesizer<br><br>
DOI: 10.15468/dl.sr9ctb
title: Occurrence Download

description: A dataset containing 10635 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "DatasetKey is Centralisation des observations floristiques dans le cadre du SINP - Observations floristiques - plateforme SINP régionale SILENE PACA",
 "TaxonKey is Pinus halepensis Mill."
 ]
}

 The dataset includes 10635 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0229597-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11068022
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_49LC

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068023
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_49LC

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068034
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_55LC

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068035
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_55LC

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068030
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_49LD

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068031
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_49LD

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068036
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_55LD

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068037
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_55LD

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.6084/m9.figshare.25283009
title: Programmable intratumoral drug delivery to breast cancer using wireless bioelectronic device with electrochemical actuation

description: Breast cancer is a global health concern that demands attention. In our contribution to addressing this disease, our study focuses on investigating a wireless micro-device for intratumoral drug delivery, utilizing electrochemical actuation. Microdevices have emerged as a promising approach in this field due to their ability to enable controlled injections in various applications. Our study is conducted within a computational framework, employing models that simulate the behavior of the microdevice and drug discharge based on the principles of the ideal gas law. Furthermore, the distribution of the drug within the tissue is simulated, considering both diffusion and convection mechanisms. To predict the therapeutic response, a pharmacodynamic model is utilized, considering the chemotherapeutic effects and cell proliferation. The findings demonstrate that an effective current of 3 mA, along with an initial gas volume equal to the drug volume in the microdevice, optimizes drug delivery. Microdevices with multiple injection capabilities exhibit enhanced therapeutic efficacy, effectively suppressing cell proliferation. Additionally, tumors with lower microvascular density experience higher drug concentrations in the extracellular space, resulting in significant cell death in hypoxic regions. Achieving an efficient therapeutic response involves considering both the characteristics of the tumor microenvironment and the frequency of injections within a specific time frame.
DOI: 10.6084/m9.figshare.25283009.v1
title: Programmable intratumoral drug delivery to breast cancer using wireless bioelectronic device with electrochemical actuation

description: Breast cancer is a global health concern that demands attention. In our contribution to addressing this disease, our study focuses on investigating a wireless micro-device for intratumoral drug delivery, utilizing electrochemical actuation. Microdevices have emerged as a promising approach in this field due to their ability to enable controlled injections in various applications. Our study is conducted within a computational framework, employing models that simulate the behavior of the microdevice and drug discharge based on the principles of the ideal gas law. Furthermore, the distribution of the drug within the tissue is simulated, considering both diffusion and convection mechanisms. To predict the therapeutic response, a pharmacodynamic model is utilized, considering the chemotherapeutic effects and cell proliferation. The findings demonstrate that an effective current of 3 mA, along with an initial gas volume equal to the drug volume in the microdevice, optimizes drug delivery. Microdevices with multiple injection capabilities exhibit enhanced therapeutic efficacy, effectively suppressing cell proliferation. Additionally, tumors with lower microvascular density experience higher drug concentrations in the extracellular space, resulting in significant cell death in hypoxic regions. Achieving an efficient therapeutic response involves considering both the characteristics of the tumor microenvironment and the frequency of injections within a specific time frame.
DOI: 10.5281/zenodo.10942680
title: Europe Gross Primary Productivity (GPP) Dataset 2018 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2018 

Region: Europe

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy (used in generation) classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.10942681
title: Europe Gross Primary Productivity (GPP) Dataset 2018 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2018 

Region: Europe

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy (used in generation) classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.11068043
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_56LB

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068044
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_56LB

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.10948200
title: Europe Gross Primary Productivity (GPP) Dataset 2019 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2019

Region: Europe

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy (used in generation) classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.10948201
title: Europe Gross Primary Productivity (GPP) Dataset 2019 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2019

Region: Europe

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy (used in generation) classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.11067784
title: Northern Cameroon daily interpolated rainfall, 1948-2022, combined dataset obtained via ordinary kriging

description: Description: This dataset provides daily interpolated rainfall maps for Northern Cameroon, including North and Extreme North provinces, for the period 1948-2022, at 0.01° resolution, derived from daily rain gauge data observations.

Dataset Preparation Methods: This dataset was created by combining maps obtained by performing interpolation from daily rain gauge data (NoCORA - Northern Cameroon Observed Rainfall Archive dataset) , using ordinary kriging with fitting of Circular variogram models and ordinary kriging with fitting of Spherical variogram models. The maps produced by the Spherical variogram models were taken as base of the combined dataset. Dates that could not be produced by the Spherical variogram models, but were produced by the Circular variogram models, were added to the combined dataset. Equally, dates produced by the Spherical variogram models containing negative values, but containing positive values when produced by the Circular variogram models, were replaced. The Mean Error calculated for both variogram models showed a similar bias and a paired t-test showed no significant difference. Resolution of interpolation is 0.01°. The daily results were assembled into daily geotiff files.

Funding: This project was funded by the DESIRA INNOVACC project.

Authors Contributions:



Data treatment: Clara Knops.

Documentation: Jérémy Lavarenne, Clara Knops.


Changelog: 



v1.0.0 : initial submission
DOI: 10.5281/zenodo.11067785
title: Northern Cameroon daily interpolated rainfall, 1948-2022, combined dataset obtained via ordinary kriging

description: Description: This dataset provides daily interpolated rainfall maps for Northern Cameroon, including North and Extreme North provinces, for the period 1948-2022, at 0.01° resolution, derived from daily rain gauge data observations.

Dataset Preparation Methods: This dataset was created by combining maps obtained by performing interpolation from daily rain gauge data (NoCORA - Northern Cameroon Observed Rainfall Archive dataset) , using ordinary kriging with fitting of Circular variogram models and ordinary kriging with fitting of Spherical variogram models. The maps produced by the Spherical variogram models were taken as base of the combined dataset. Dates that could not be produced by the Spherical variogram models, but were produced by the Circular variogram models, were added to the combined dataset. Equally, dates produced by the Spherical variogram models containing negative values, but containing positive values when produced by the Circular variogram models, were replaced. The Mean Error calculated for both variogram models showed a similar bias and a paired t-test showed no significant difference. Resolution of interpolation is 0.01°. The daily results were assembled into daily geotiff files.

Funding: This project was funded by the DESIRA INNOVACC project.

Authors Contributions:



Data treatment: Clara Knops.

Documentation: Jérémy Lavarenne, Clara Knops.


Changelog: 



v1.0.0 : initial submission
DOI: 10.5281/zenodo.11068047
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_57LD

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.11068048
title: FRACTESUS_SCK CEN_A533BLUS L_KJC_-20_57LD

description: Fractesus project. Fracture test mini-CT. Raw data A533B LUS. SCK CEN.
DOI: 10.5281/zenodo.10948257
title: Europe Gross Primary Productivity (GPP) Dataset 2020 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2020

Region: Europe

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy (used in generation) classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.10948258
title: Europe Gross Primary Productivity (GPP) Dataset 2020 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2020

Region: Europe

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy (used in generation) classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.10948336
title: Amazon Gross Primary Productivity (GPP) Dataset 2018 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2018 

Region: Amazon 

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publication: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.10948337
title: Amazon Gross Primary Productivity (GPP) Dataset 2018 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2018 

Region: Amazon 

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publication: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.10948717
title: Australia Gross Primary Productivity (GPP) Dataset 2019 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2019

Region: Australia

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publication: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.
DOI: 10.5281/zenodo.10948718
title: Australia Gross Primary Productivity (GPP) Dataset 2019 (GeoTIFF) - ZIP file

description: Product: Gross Primary Productivity (GPP)

Year: 2019

Region: Australia

Temporal Scale: 8 Days

Spatial Resolution: 500 meters

Method: Light-use-efficiency (LUE) approach.

Referred Publication: https://www.sciencedirect.com/science/article/pii/S0048969718307149

https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261

This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. 

NOTE: As ArcPy classifies 'no data' pixels as very low negative values, users should mask all data values below 0 to prevent these affecting statistics.