cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10425328
title: The relationship between visual acuity loss and GABAergic inhibition dissociates subtypes of human amblyopia

description: Original data for neuroimaging experiment presented in the article "The relationship between visual acuity loss and GABAergic inhibition dissociates subtypes of human amblyopia" by I. Betina Ip, William T. Clarke, Abigail Wyllie, Kathleen Tracey, Jacek Matuszewski, Saad Jbabdi,  Lucy Starling, Sophie Templer, Hanna Willis, Laura Breach, Andrew J. Parker, Holly Bridge.

The rawdata found in this repository was analysed using code available at https://git.fmrib.ox.ac.uk/betinaip/fmrs-amblyopia.

The specific files included for each participant are: 

sub-001├── anat│   └── sub-001_anat_defaced.nii.gz├── func│   └── sub-001_task.nii.gz└── mrs    ├── pcc    │   ├── sub-001_pccrest.nii.gz    │   ├── sub-001_pccrest_wref1.nii.gz    │   ├── sub-001_pccrest_wref3.nii.gz    │   └── sub-001_pccrest_wref_phasecorr.nii.gz    └── v1        ├── sub-001_v1botheyes.nii.gz        ├── sub-001_v1botheyes_wref1.nii.gz        ├── sub-001_v1botheyes_wref3.nii.gz        ├── sub-001_v1botheyes_wref_phasecorr.nii.gz        ├── sub-001_v1lefteye.nii.gz        ├── sub-001_v1lefteye_wref1.nii.gz        ├── sub-001_v1lefteye_wref3.nii.gz        ├── sub-001_v1lefteye_wref_phasecorr.nii.gz        ├── sub-001_v1rest.nii.gz        ├── sub-001_v1rest_wref1.nii.gz        ├── sub-001_v1rest_wref3.nii.gz        ├── sub-001_v1rest_wref_phasecorr.nii.gz        ├── sub-001_v1righteye.nii.gz        ├── sub-001_v1righteye_wref1.nii.gz        ├── sub-001_v1righteye_wref3.nii.gz        └── sub-001_v1righteye_wref_phasecorr.nii.gz

Partial data:

sub-017 - no sub-017_task.nii.gz, sub-017_v1botheyes, sub-017_v1lefteye or sub-017_v1righteye data due to display error

sub-022 - sub-022_v1lefteye data missing due to data transfer error

Further notes:

sub-022 - has two anatomy images. Use sub-022_anat_2_defaced.nii.gz

If you use this data, please cite the original study.
DOI: 10.5281/zenodo.10425329
title: The relationship between visual acuity loss and GABAergic inhibition dissociates subtypes of human amblyopia

description: Original data for neuroimaging experiment presented in the article "The relationship between visual acuity loss and GABAergic inhibition dissociates subtypes of human amblyopia" by I. Betina Ip, William T. Clarke, Abigail Wyllie, Kathleen Tracey, Jacek Matuszewski, Saad Jbabdi,  Lucy Starling, Sophie Templer, Hanna Willis, Laura Breach, Andrew J. Parker, Holly Bridge.

The rawdata found in this repository was analysed using code available at https://git.fmrib.ox.ac.uk/betinaip/fmrs-amblyopia.

The specific files included for each participant are: 

sub-001├── anat│   └── sub-001_anat_defaced.nii.gz├── func│   └── sub-001_task.nii.gz└── mrs    ├── pcc    │   ├── sub-001_pccrest.nii.gz    │   ├── sub-001_pccrest_wref1.nii.gz    │   ├── sub-001_pccrest_wref3.nii.gz    │   └── sub-001_pccrest_wref_phasecorr.nii.gz    └── v1        ├── sub-001_v1botheyes.nii.gz        ├── sub-001_v1botheyes_wref1.nii.gz        ├── sub-001_v1botheyes_wref3.nii.gz        ├── sub-001_v1botheyes_wref_phasecorr.nii.gz        ├── sub-001_v1lefteye.nii.gz        ├── sub-001_v1lefteye_wref1.nii.gz        ├── sub-001_v1lefteye_wref3.nii.gz        ├── sub-001_v1lefteye_wref_phasecorr.nii.gz        ├── sub-001_v1rest.nii.gz        ├── sub-001_v1rest_wref1.nii.gz        ├── sub-001_v1rest_wref3.nii.gz        ├── sub-001_v1rest_wref_phasecorr.nii.gz        ├── sub-001_v1righteye.nii.gz        ├── sub-001_v1righteye_wref1.nii.gz        ├── sub-001_v1righteye_wref3.nii.gz        └── sub-001_v1righteye_wref_phasecorr.nii.gz

Partial data:

sub-017 - no sub-017_task.nii.gz, sub-017_v1botheyes, sub-017_v1lefteye or sub-017_v1righteye data due to display error

sub-022 - sub-022_v1lefteye data missing due to data transfer error

Further notes:

sub-022 - has two anatomy images. Use sub-022_anat_2_defaced.nii.gz

If you use this data, please cite the original study.
DOI: 10.5281/zenodo.10424334
title: TNO DGM5/VELMOD31 UTM31 xarray datasets

description: Contains the DGM5 geological model and the VELMOD 3.1 velocity model as xarray datasets in UTM31 coordinates.

Original data:

Details DGM-diep V5 | NLOG

Velmod-3.1 | NLOG

Format:

Xarray documentation
DOI: 10.5281/zenodo.10424335
title: TNO DGM5/VELMOD31 UTM31 xarray datasets

description: Contains the DGM5 geological model and the VELMOD 3.1 velocity model as xarray datasets in UTM31 coordinates.

Original data:

Details DGM-diep V5 | NLOG

Velmod-3.1 | NLOG

Format:

Xarray documentation
DOI: 10.5281/zenodo.10425411
title: TNO DGM5/VELMOD31 UTM31 xarray datasets

description: Contains the DGM5 geological model and the VELMOD 3.1 velocity model as xarray datasets in UTM31 coordinates.

Original data:

Details DGM-diep V5 | NLOG

Velmod-3.1 | NLOG

Format:

Xarray documentation
DOI: 10.6084/m9.figshare.24758082
title: Code examples for slimr manuscript, along with all data needed to run them.

description: This is all of the code and required data to run all example found in the manuscript describing the R package slimr. slimr is an R package designed to smoothly link the statistical and data processing power of R with the standalone population genomics simulation software SLiM.
DOI: 10.6084/m9.figshare.24758082.v1
title: Code examples for slimr manuscript, along with all data needed to run them.

description: This is all of the code and required data to run all example found in the manuscript describing the R package slimr. slimr is an R package designed to smoothly link the statistical and data processing power of R with the standalone population genomics simulation software SLiM.
DOI: 10.48432/0lu9c8
title: Caracterização da avicultura no Brasil a partir do Censo Agropecuário 2017 do IBGE.

description: O objetivo deste conjunto de dados é dimensionar e caracterizar a avicultura no Brasil a partir dos resultados definitivos do Censo Agropecuário 2017, realizado pelo Instituto Brasileiro de Geografia e Estatística (IBGE). A partir do conjunto de dados é possível quantificar os diferentes segmentos da avicultura no Brasil, nas suas grandes regiões geográficas e unidades da federação, por grupos de cabeças e por sistema de criação, bem como caracterizar suas principais dimensões socioeconômicas (área, uso da terra, produção e rebanhos, tipologia do produtor, acesso e origem da orientação técnica, o número de trabalhadores e receita bruta agropecuária e da avicultura). Considerou-se nas tabulações especiais quatro diferentes sistemas de criação (produtores de frangos de corte, produtores de ovos para consumo, produtores de ovos para incubação ou com rebanho de matrizes e outros sistemas) e 11 grupos de cabeças de galináceos (total, de 1 a 100, de 101 a 200, de 201 a 500, de 501 a 1.000, de 1.001 a 5.000, de 5.001 a 10.000, de 10.001 a 50.000, de 50.001 a 100.000, de 100.001 e mais cabeças e sem rebanho na data de referência), abrangendo 33 níveis territoriais (Brasil, Grandes Regiões e Unidades da Federação e Distrito Federal). As variáveis de estoque como rebanho e área são da data de referência do censo que foi 30/09/2017, e as variáveis de fluxo como ovos e cabeças vendidas e valor das vendas são do período de referência do censo que foi o ano-safra de outubro de 2016 a setembro de 2017.
DOI: 10.5281/zenodo.10424442
title: 3D reconstruction of plants using probabilistic voxel carving

description: This is a companion dataset for the paper titled "3D reconstruction of plants using probabilistic voxel carving." by Feng, J., Saadati, M., Jubery, T., Jignasu, A., Balu, A., Li, Y., Attigala, L., Schnable, P.S., Sarkar, S., Ganapathysubramanian, B. and Krishnamurthy, A., published in Computers and Electronics in Agriculture, 213, p.108248, 2023.

 
description: We propose a probabilistic voxel carving algorithm to efficiently reconstruct 3D models of maize plants and extract leaf traits for phenotyping. Traditional voxel carving algorithm is restricted to a limited number of views and usually requires multiple coordinated cameras in the imaging setup. They are also not robust small movements of the object, which introduce noise into the data. These imperfections in data collection can lead to large regions of the object being carved away during the voxel carving process, leading to incomplete and disjoint objects. We have developed a probabilistic voxel carving algorithm to overcome these challenges. In this approach, instead of carving out or keeping a voxel in a binary manner, we associate a probability of a voxel corresponding to it being part of the plant. We then use a user-defined probability cutoff to obtain the final voxelized plant geometry. We optimize the  data collection procedure by adopting a rotating base to hold the plant and then capturing videos of the rotating plants, thereby obtaining an arbitrary number of views by extracting the image frames. Additionally, we leverage GPU computing to implement our voxel carving and trait extraction pipeline for a large dataset with over 1000 maize plants with high voxel resolutions (such as 10243). Our results demonstrate that our algorithm is robust and can handle an arbitrary number of views, and can automatically extract plant traits such as the number of leaves and leaf angles. Our approach shows that  3D reconstructions of plants from multi-view images can accurately extract multiple phenotypic traits, enabling better plant breeding programs.
DOI: 10.5281/zenodo.10424443
title: 3D reconstruction of plants using probabilistic voxel carving

description: This is a companion dataset for the paper titled "3D reconstruction of plants using probabilistic voxel carving." by Feng, J., Saadati, M., Jubery, T., Jignasu, A., Balu, A., Li, Y., Attigala, L., Schnable, P.S., Sarkar, S., Ganapathysubramanian, B. and Krishnamurthy, A., published in Computers and Electronics in Agriculture, 213, p.108248, 2023.

 
description: We propose a probabilistic voxel carving algorithm to efficiently reconstruct 3D models of maize plants and extract leaf traits for phenotyping. Traditional voxel carving algorithm is restricted to a limited number of views and usually requires multiple coordinated cameras in the imaging setup. They are also not robust small movements of the object, which introduce noise into the data. These imperfections in data collection can lead to large regions of the object being carved away during the voxel carving process, leading to incomplete and disjoint objects. We have developed a probabilistic voxel carving algorithm to overcome these challenges. In this approach, instead of carving out or keeping a voxel in a binary manner, we associate a probability of a voxel corresponding to it being part of the plant. We then use a user-defined probability cutoff to obtain the final voxelized plant geometry. We optimize the  data collection procedure by adopting a rotating base to hold the plant and then capturing videos of the rotating plants, thereby obtaining an arbitrary number of views by extracting the image frames. Additionally, we leverage GPU computing to implement our voxel carving and trait extraction pipeline for a large dataset with over 1000 maize plants with high voxel resolutions (such as 10243). Our results demonstrate that our algorithm is robust and can handle an arbitrary number of views, and can automatically extract plant traits such as the number of leaves and leaf angles. Our approach shows that  3D reconstructions of plants from multi-view images can accurately extract multiple phenotypic traits, enabling better plant breeding programs.
DOI: 10.6084/m9.figshare.24894927
title: Code of Geographical Pattern Interaction

description: This is the data and code related to the paper submitted to IJGIS titled '<b><i>Measuring Univariate Effects in the Interaction of Geographical Patterns</i></b>.' It comprises the following three folders:**Data: Australia Homelessness Risk****GPI Codes:** - `GPImodel.Rmd`: The code for GPI. It depends on two functions: - `Fun_treeall.R`: Calculates the global effects of GPI. - `Fun_treeall_map.R`: Calculates the local effects of GPI.**Sensitivity Analysis:**Conduct the sensitivity analysis of GPI applied in the case study (Australia Homelessness Risk).
DOI: 10.6084/m9.figshare.24894927.v1
title: Code of Geographical Pattern Interaction

description: This is the data and code related to the paper submitted to IJGIS titled '<b><i>Measuring Univariate Effects in the Interaction of Geographical Patterns</i></b>.' It comprises the following three folders:**Data: Australia Homelessness Risk****GPI Codes:** - `GPImodel.Rmd`: The code for GPI. It depends on two functions: - `Fun_treeall.R`: Calculates the global effects of GPI. - `Fun_treeall_map.R`: Calculates the local effects of GPI.**Sensitivity Analysis:**Conduct the sensitivity analysis of GPI applied in the case study (Australia Homelessness Risk).
DOI: 10.25345/c59w0991h
title: MassIVE MSV000093721 - Structure and function of the UFM1 E3 ligase in recycling of 60S ribosomal subunits from ER translocons
title: Supporting MS data for paper (doi: TBD) by DaRosa P.A., Penchev I. et al., titled "Structure and function of the UFM1 E3 ligase in recycling of 60S ribosomal subunits from ER translocons". Index of MS supporting files uploaded: Related to Figure 1C,D (xb01004(UFM1), xb01005(SBP-UFM1): LFQ IP-MS (Unimod: 35; 4)). See also MSV000093510
DOI: 10.5281/zenodo.5210260
title: The State of the Urban Forest in New York City - Supplemental Datasets

description: Summary:


The files available here contain summary data for the urban forest of New York City, associated with the report, The State of the Urban Forest in New York City, developed by The Nature Conservancy and released in 2021. Methods and data used in development of these files are described in Appendix 1 of the report. and additional details and supplemental code are available at https://github.com/tnc-ny-science/NYC_StateOfUrbanForest_Docs. If you do not find what you are looking for here, you may contact Michael Treglia at michael.treglia@tnc.org.


 


Terms of Use


© The Nature Conservancy. This material is provided as-is, without warranty under a Creative Commons Attribution-NonCommercial-ShareAlike License as set forth in our Conservation Gateway Terms of Use (available at: http://conservationgateway.org/Pages/Terms-of-Use.aspx)


If using these data, please cite the both the report and the data, based on the following recommended citations.


Recommended citation for the report:


Treglia, M.L., Acosta-Morel, M., Crabtree, D., Galbo, K., Lin-Moges, T., Van Slooten, A., Maxwell, E.N. 2021. The State of the Urban Forest in New York City. The Nature Conservancy. doi: 10.5281/zenodo.5532876


Recommended citation for the data is:


Treglia, M.L., Acosta-Morel, M., Crabtree, D., Galbo, K., Lin-Moges, T., Van Slooten, A., Maxwell, E.N. 2021. The State of the Urban Forest in New York City - Supplemental Datasets. The Nature Conservancy. doi: 10.5281/zenodo.5210261


 


Contents


canopy_jurisdiction_landuse_borough.zip - Zipped folder with comma separated values (.csv) file of land and canopy area summaries by approximated general ownership type, land use categories, and natural/developed breakdown, with Data Dictionary files in .docx and .html formats.


canopy_streettree_summaries.zip - Zipped folder containing GeoPackage, Esri File Geodatabase, and comma separated values (.csv) files with canopy and street tree summary data at the scales of Neighborhood Tabulation Area, Community District, City Council District, and Borough, with Data Dictionary files in .docx and .html formats.


equity_data.zip - Zipped folder containing GeoPackage, Esri File Geodatabase, and comma separated values (.csv) files with data used for equity analyses at the scale of Neighborhood Tabulation Area, with Data Dictionary files in .docx and .html formats.


naturalareas_canopy_jurisdiction_borough.zip - Zipped folder with comma separated values (.csv) file of summaries of natural area canopy data by approximated general ownership type and by borough, with Data Dictionary files in .docx and .html formats.


 


*Note for the contents of equity_data.zip: For data in this .zip folder, the column named "relativecanopychange_percent" represents relative canopy change from 2010 to 2017 as proportions, not percentages. To convert these numbers to percentages, values can be multiplied by 100. The data are accurately depicted in the report, and column names are otherwise accurate in this repository.
DOI: 10.5281/zenodo.5210261
title: The State of the Urban Forest in New York City - Supplemental Datasets

description: Summary:


The files available here contain summary data for the urban forest of New York City, associated with the report, The State of the Urban Forest in New York City, developed by The Nature Conservancy and released in 2021. Methods and data used in development of these files are described in Appendix 1 of the report. and additional details and supplemental code are available at https://github.com/tnc-ny-science/NYC_StateOfUrbanForest_Docs. If you do not find what you are looking for here, you may contact Michael Treglia at michael.treglia@tnc.org.


 


Terms of Use


© The Nature Conservancy. This material is provided as-is, without warranty under a Creative Commons Attribution-NonCommercial-ShareAlike License as set forth in our Conservation Gateway Terms of Use (available at: http://conservationgateway.org/Pages/Terms-of-Use.aspx)


If using these data, please cite the both the report and the data, based on the following recommended citations.


Recommended citation for the report:


Treglia, M.L., Acosta-Morel, M., Crabtree, D., Galbo, K., Lin-Moges, T., Van Slooten, A., Maxwell, E.N. 2021. The State of the Urban Forest in New York City. The Nature Conservancy. doi: 10.5281/zenodo.5532876


Recommended citation for the data is:


Treglia, M.L., Acosta-Morel, M., Crabtree, D., Galbo, K., Lin-Moges, T., Van Slooten, A., Maxwell, E.N. 2021. The State of the Urban Forest in New York City - Supplemental Datasets. The Nature Conservancy. doi: 10.5281/zenodo.5210261


 


Contents


canopy_jurisdiction_landuse_borough.zip - Zipped folder with comma separated values (.csv) file of land and canopy area summaries by approximated general ownership type, land use categories, and natural/developed breakdown, with Data Dictionary files in .docx and .html formats.


canopy_streettree_summaries.zip - Zipped folder containing GeoPackage, Esri File Geodatabase, and comma separated values (.csv) files with canopy and street tree summary data at the scales of Neighborhood Tabulation Area, Community District, City Council District, and Borough, with Data Dictionary files in .docx and .html formats.


equity_data.zip - Zipped folder containing GeoPackage, Esri File Geodatabase, and comma separated values (.csv) files with data used for equity analyses at the scale of Neighborhood Tabulation Area, with Data Dictionary files in .docx and .html formats.


naturalareas_canopy_jurisdiction_borough.zip - Zipped folder with comma separated values (.csv) file of summaries of natural area canopy data by approximated general ownership type and by borough, with Data Dictionary files in .docx and .html formats.


 


*Note for the contents of equity_data.zip: For data in this .zip folder, the column named "relativecanopychange_percent" represents relative canopy change from 2010 to 2017 as proportions, not percentages. To convert these numbers to percentages, values can be multiplied by 100. The data are accurately depicted in the report, and column names are otherwise accurate in this repository.
DOI: 10.6084/m9.figshare.24894921.v1
title: Gospel across the millennium:Confucian cultureand innovation in China

description: Confucian culture has had a significant impact on contemporary Chinese society for thousands of years. However, whether it is a "gospel" or a "curse" for science and technology innovation in contemporary China is still controversial. To measure the extent of Confucian culture, we use the density of Confucian cultural sites and test its causal relationship with innovation. The data suggests that regions with a strong influence of Confucian culture have higher levels of innovation. This finding remains consistent even after conducting instrumental variable regression and multiple robustness tests. Mechanistic analyses demonstrate that Confucian culture can promote innovation by reinforcing good governance, improving education, and enhancing intellectual property protection. The study reveals that Confucianism has a stronger impact in regions with lower business credit. Additionally, it suggests that Confucianism and formal institutions can be interchangeable. Moreover, foreign cultures may diminish the influence of Confucianism in fostering innovation.
DOI: 10.48432/n6iquo
title: Caracterização da suinocultura no Brasil a partir do Censo Agropecuário 2017 do IBGE.

description: O objetivo deste conjunto de dados é dimensionar e caracterizar a suinocultura no Brasil a partir dos resultados definitivos do Censo Agropecuário 2017, realizado pelo Instituto Brasileiro de Geografia e Estatística (IBGE). A partir do conjunto de dados é possível quantificar os diferentes segmentos da suinocultura no Brasil, nas suas grandes regiões geográficas e unidades da federação, por grupos de cabeças e por sistema de criação, bem como caracterizar suas principais dimensões socioeconômicas (área, uso da terra, produção e rebanhos, tipologia do produtor, acesso e origem da orientação técnica, o número de trabalhadores e receita bruta agropecuária e da avicultura). Considerou-se nas tabulações especiais três diferentes sistemas de criação (produtores de leitões e em ciclo completo com matrizes reprodutoras, produtores de crescimento e terminação que fazem a engoda e outros sistemas) e dez grupos de cabeças de suínos (total, de 1 a 10, de 11 a 50, de 51 a 100, de 101 a 200, de 201 a 500, de 501 a 1.000, de 1.001 a 5.000, de 5.001 e mais cabeças e sem rebanho na data de referência), abrangendo 33 níveis territoriais (Brasil, Grandes Regiões e Unidades da Federação e Distrito Federal). As variáveis de estoque como rebanho e área são da data de referência do censo que foi 30/09/2017, e as variáveis de fluxo como cabeças vendidas e valor das vendas são do período de referência do censo que foi o ano-safra de outubro de 2016 a setembro de 2017. (2017-09-30)
DOI: 10.57745/tix2ql
title: EXPD.tab

description: Data of the experiment D (.csv)
DOI: 10.57745/zeniv4
title: Metadata.docx

description: Metadata - description of the data sets and experimental protocols
DOI: 10.57745/bpszmm
title: EXPB.tab

description: Data of the experiment B (.csv)
DOI: 10.57745/73gpk3
title: EXPC.tab

description: Data of the experiment C (.csv)
DOI: 10.57745/f7ntng
title: EXPA.tab

description: Data of the experiment A (.csv)
DOI: 10.57745/jzownl
title: ANNEXES Graphs.docx

description: Visualization of milk production and persistency of the 4 experiments