cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7588702
title: CalcAMP: A new machine learning model for the accurate pre-diction of antimicrobial activity of peptides

description: Datasets used for the publication: CalcAMP: A new machine learning model for the accurate prediction of antimicrobial activity of peptides
DOI: 10.5281/zenodo.7588701
title: CalcAMP: A new machine learning model for the accurate pre-diction of antimicrobial activity of peptides

description: Datasets used for the publication: CalcAMP: A new machine learning model for the accurate prediction of antimicrobial activity of peptides
DOI: 10.5281/zenodo.7588723
title: Clean Sky 2 - SALUTE H2020 Project : 2D smart liner data

description: This data concerns all obtained measurment in paper :In flow acoustic characterisation of a 2D active liner with local and non<br> local strategies. K. Billon, E. De Bono, M. Perez , E. Salze, G. Mattenand al, Applied Acoustics 191 (2022) 108655, https://doi.org/10.1016/j.apacoust.2022.108655
DOI: 10.5281/zenodo.7588722
title: Clean Sky 2 - SALUTE H2020 Project : 2D smart liner data

description: This data concerns all obtained measurment in paper :In flow acoustic characterisation of a 2D active liner with local and non<br> local strategies. K. Billon, E. De Bono, M. Perez , E. Salze, G. Mattenand al, Applied Acoustics 191 (2022) 108655, https://doi.org/10.1016/j.apacoust.2022.108655
DOI: 10.17632/d6929dgh3c.1
title: Proteomics of ATP1B1 Interacting Proteins in A549 Cells

description: The A549 cell line is one of the most common models for alveolar epithelium in vitro. In our study, A549 cells were used to explore the molecular mechanism of ATP1B1 in alveolar epithelial cells. We applied an AP/co-IP-MS-based proteomic analysis to analyze the interacting proteins of ATP1B1 in A549 cells and also analyzed the interaction and enrichment of these proteins. Total proteins were extracted from A549 cells, and the proteomics was carried out using an antibody against the ATP1B1 or IgG. We identified 2876 peptides and 593 proteins, and 523 proteins were retained after filtering. Protein enrichment classification information for comparison ATP1B1-IgG was displayed in a Venn diagram. Three parts of the Venn diagram corresponded to test enriched (T), control enriched (C), and none enriched (T&C). This dataset included the significant proteins in the three parts and their results of GO & KEGG enrichment analysis and protein-protein interaction (PPI) analysis, respectively.
DOI: 10.17632/8kmksy24rg.3
title: Pesticide Use Behavior, Cognitive Dysfunction and The Model of Safety Standard of Pesticide Use among farmworker in Indonesia

description: dataset for pesticide use behavior, cognitive dysfunction and the model of safety standard of pesticide use among famworker in indonesia
DOI: 10.5281/zenodo.7586030
title: Code and data used for the study: 'BioDeepTime: a database of biodiversity time series for modern and fossil assemblages'

description: The repository includes code and data to reproduce the results in the manuscript ‘BioDeepTime: a database of biodiversity time series for modern and fossil assemblages' by Smith et al. (<code>analysis_biodeeptime.zip</code>).
DOI: 10.5281/zenodo.7586029
title: Code and data used for the study: 'BioDeepTime: a database of biodiversity time series for modern and fossil assemblages'

description: The repository includes code and data to reproduce the results in the manuscript ‘BioDeepTime: a database of biodiversity time series for modern and fossil assemblages' by Smith et al. (<code>analysis_biodeeptime.zip</code>).
DOI: 10.5519/qd.gthnixp6
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (796 records)
DOI: 10.5281/zenodo.7586257
title: Assets for Renier et al. "Transparency, Traceability And Deforestation In The Ivorian Cocoa Supply Chain"

description: Assets to run the Google Earth Engine scripts provided here: https://doi.org/10.5281/zenodo.7503845 Required to reproduce figures and stats quoted in Renier C, Vandromme M, Meyfroidt P, Ribeiro V, Kalischek N, zu Ermgassen E K H J 2023. Transparency, traceability and deforestation in the Ivorian cocoa supply chain. Envir. Res. Let. doi:10.1088/1748-9326/acad8e
DOI: 10.5281/zenodo.7586256
title: Assets for Renier et al. "Transparency, Traceability And Deforestation In The Ivorian Cocoa Supply Chain"

description: Assets to run the Google Earth Engine scripts provided here: https://doi.org/10.5281/zenodo.7503845 Required to reproduce figures and stats quoted in Renier C, Vandromme M, Meyfroidt P, Ribeiro V, Kalischek N, zu Ermgassen E K H J 2023. Transparency, traceability and deforestation in the Ivorian cocoa supply chain. Envir. Res. Let. doi:10.1088/1748-9326/acad8e
DOI: 10.6084/m9.figshare.21977039
title: remaining mouse CT scans (tibial epiphysis)

description: CT stacks of male CBA and STRort. Age and specimen number indicated in scan name. <br> Voxel size = 0.005 mm <br> Ethical approval for the animal procedures was carried out in accordance with the Animals (Scientific Procedures) Act 1986, an Act of Parliament of the United Kingdom, approved by the Royal Veterinary College Ethical Review Committee and the United Kingdom Government Home Office
DOI: 10.6084/m9.figshare.21977039.v1
title: STRort mouse epiphysis (male, 9w, #22.4.12-LT)

description: CT stack <br> Voxel size = 0.005 mm <br> Ethical approval for the animal procedures was carried out in accordance with the Animals (Scientific Procedures) Act 1986, an Act of Parliament of the United Kingdom, approved by the Royal Veterinary College Ethical Review Committee and the United Kingdom Government Home Office
DOI: 10.5281/zenodo.7588738
title: Computation of contrast-enhanced perfusion using only two CT scan phases: a proof-of-concept study on abdominal organs

description: Cressoni M, Cozzi A, Schiaffino S, Cadringher P, Vitali P, Basso G, Ippolito D, Sardanelli F. Computation of contrast-enhanced perfusion using only two CT scan phases: a proof-of-concept study on abdominal organs. Eur Radiol Exp. 2022 Aug 29;6(1):37. doi: 10.1186/s41747-022-00292-y. PMID: 36031643; PMCID: PMC9420683. Abstract <strong>Background: </strong>Computed tomography perfusion imaging (CTPI) by repeated scanning has clinical relevance but implies relatively high radiation exposure. We present a method to measure perfusion from two CT scan phases only, considering tissue enhancement, feeding vessel (aortic) peak enhancement, and bolus shape. <strong>Methods: </strong>CTPI scans (each with 40 frames acquired every 1.5 s) of 11 patients with advanced hepatocellular carcinoma (HCC) enrolled between 2012 and 2016 were retrospectively analysed (aged 69 ± 9 years, 8/11 males). Perfusion was defined as the maximal slope of the time-enhancement curve divided by the peak enhancement of the feeding vessel (aorta). Perfusion was computed two times, first using the maximum slope derived from all data points and then using the peak tissue enhancement and the bolus shape obtained from the aortic curve. <strong>Results: </strong>Perfusion values from the two methods were linearly related (r<sup>2</sup> = 0.92, p &lt; 0.001; Bland-Altman analysis bias -0.12). The mathematical model showed that the perfusion ratio of two ROIs with the same feeding vessel (aorta) corresponds to their peak enhancement ratio (r<sup>2</sup> = 0.55, p &lt; 0.001; Bland-Altman analysis bias -0.68). The relationship between perfusion and tissue enhancement is predicted to be linear in the clinical range of interest, being only function of perfusion, peak feeding vessel enhancement, and bolus shape. <strong>Conclusions: </strong>This proof-of-concept study showed that perfusion values of HCC, kidney, and pancreas could be computed using enhancement measured only with two CT scan phases, if aortic peak enhancement and bolus shape are known.
DOI: 10.5281/zenodo.7588737
title: Computation of contrast-enhanced perfusion using only two CT scan phases: a proof-of-concept study on abdominal organs

description: Cressoni M, Cozzi A, Schiaffino S, Cadringher P, Vitali P, Basso G, Ippolito D, Sardanelli F. Computation of contrast-enhanced perfusion using only two CT scan phases: a proof-of-concept study on abdominal organs. Eur Radiol Exp. 2022 Aug 29;6(1):37. doi: 10.1186/s41747-022-00292-y. PMID: 36031643; PMCID: PMC9420683. Abstract <strong>Background: </strong>Computed tomography perfusion imaging (CTPI) by repeated scanning has clinical relevance but implies relatively high radiation exposure. We present a method to measure perfusion from two CT scan phases only, considering tissue enhancement, feeding vessel (aortic) peak enhancement, and bolus shape. <strong>Methods: </strong>CTPI scans (each with 40 frames acquired every 1.5 s) of 11 patients with advanced hepatocellular carcinoma (HCC) enrolled between 2012 and 2016 were retrospectively analysed (aged 69 ± 9 years, 8/11 males). Perfusion was defined as the maximal slope of the time-enhancement curve divided by the peak enhancement of the feeding vessel (aorta). Perfusion was computed two times, first using the maximum slope derived from all data points and then using the peak tissue enhancement and the bolus shape obtained from the aortic curve. <strong>Results: </strong>Perfusion values from the two methods were linearly related (r<sup>2</sup> = 0.92, p &lt; 0.001; Bland-Altman analysis bias -0.12). The mathematical model showed that the perfusion ratio of two ROIs with the same feeding vessel (aorta) corresponds to their peak enhancement ratio (r<sup>2</sup> = 0.55, p &lt; 0.001; Bland-Altman analysis bias -0.68). The relationship between perfusion and tissue enhancement is predicted to be linear in the clinical range of interest, being only function of perfusion, peak feeding vessel enhancement, and bolus shape. <strong>Conclusions: </strong>This proof-of-concept study showed that perfusion values of HCC, kidney, and pancreas could be computed using enhancement measured only with two CT scan phases, if aortic peak enhancement and bolus shape are known.
DOI: 10.6084/m9.figshare.20046053
title: SystemData

description: Four test systems are provided.
DOI: 10.6084/m9.figshare.20046053.v2
title: SystemData

description: Four test systems are provided.
DOI: 10.6084/m9.figshare.20046053.v3
title: SystemData

description: Four test systems are provided.
DOI: 10.6084/m9.figshare.21981533
title: Housing adequacy elements

description: Universal housing adequacy model to compare different elements and categories of housing. <br> Model compiled from a qualitative study using a grounded theory approach, where the official housing regulations/ legislation/ policy/ code/ and standards of 42 countries were analysed. The data was analysed by coding according to reflective thematic analysis, and was compared to the elements in existing theories. The source documents represented a range of countries from developed to developing; and countries ranging from high to low income based on per capita Gross National Investment (GNI). The study established that a general definition of housing adequacy included 27 elements that can be divided into five categories—Accessibility, Protection from the elements, Internal habitability, Service provision and Sustainability.
DOI: 10.6084/m9.figshare.21981533.v1
title: Housing adequacy elements

description: Universal housing adequacy model to compare different elements and categories of housing. <br> Model compiled from a qualitative study using a grounded theory approach, where the official housing regulations/ legislation/ policy/ code/ and standards of 42 countries were analysed. The data was analysed by coding according to reflective thematic analysis, and was compared to the elements in existing theories. The source documents represented a range of countries from developed to developing; and countries ranging from high to low income based on per capita Gross National Investment (GNI). The study established that a general definition of housing adequacy included 27 elements that can be divided into five categories—Accessibility, Protection from the elements, Internal habitability, Service provision and Sustainability.
DOI: 10.5517/ccdc.csd.cc20bch7
title: CCDC 1857008: Experimental Crystal Structure Determination

description: Related Article: Michael B. Pastor, Chao Feng, Yi-Ju Tsai, Amelia Watson, Qinliang Zhao|2021|Tetrahedron|84|131995|doi:10.1016/j.tet.2021.131995
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc21zg7r
title: CCDC 1906104: Experimental Crystal Structure Determination

description: Related Article: Zhu-Ming Qian, Kai-Li Zuo, Zhi Guan, Yan-Hong He|2021|Tetrahedron|83|131999|doi:10.1016/j.tet.2021.131999
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc26mdlv
title: CCDC 2044437: Experimental Crystal Structure Determination

description: Related Article: Boris V. Lichitsky, Valeriya G. Melekhina, Andrey N. Komogortsev, Vasily A. Migulin, Yulia V. Nelyubina, Artem N. Fakhrutdinov, Elena D. Daeva, Arkady A. Dudinov|2021|Tetrahedron|83|131980|doi:10.1016/j.tet.2021.131980
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21981536
title: ProjecTILs human reference atlas of CD4+ tumor-infiltrating T cells, version 1

description: ProjecTILs human reference atlas of CD4+ tumor-infiltrating T cells, generated by semi-supervised STACAS integration of 20 scRNA-seq datasets spanning 7 cancer types. The datasets were obtained from the collection by Zheng et al. Science 2021). The dataset is available as a Seurat object, with subtype labels (functional cluster), sample of origin and several other measurement for each cell stored in the object metadata. The object can be loaded into an R session using the readRDS() function, and directly used as a reference atlas for ProjecTILs (Andreatta et al. Nat Comms 2021).
DOI: 10.5281/zenodo.7587686
title: MUSES Leaf Area Index (LAI) 8-Day Global 1km SIN Grid in 2003

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 1km spatial resolution and 8-day temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2003. <em>Please <strong>click here</strong> to download the MUSES LAI product<strong> in 2002</strong></em>, and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2003 Spatial Resolution: 1km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7587685
title: MUSES Leaf Area Index (LAI) 8-Day Global 1km SIN Grid in 2003

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 1km spatial resolution and 8-day temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2003. <em>Please <strong>click here</strong> to download the MUSES LAI product<strong> in 2002</strong></em>, and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2003 Spatial Resolution: 1km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7503845
title: Data and code for Renier et al. "Transparency, Traceability And Deforestation In The Ivorian Cocoa Supply Chain"

description: Data and code required to reproduce figures and stats quoted in Renier C, Vandromme M, Meyfroidt P, Ribeiro V, Kalischek N, zu Ermgassen E K H J 2023. Transparency, traceability and deforestation in the Ivorian cocoa supply chain. Envir. Res. Let. doi:10.1088/1748-9326/acad8e These data refer to SEI-PCS Côte d’Ivoire Cocoa v1.1.0 Find assets required for the GEE scripts at : https://doi.org/10.5281/zenodo.7586257
DOI: 10.5281/zenodo.7503844
title: Data and code for Renier et al. "Transparency, Traceability And Deforestation In The Ivorian Cocoa Supply Chain"

description: Data and code required to reproduce figures and stats quoted in Renier C, Vandromme M, Meyfroidt P, Ribeiro V, Kalischek N, zu Ermgassen E K H J 2023. Transparency, traceability and deforestation in the Ivorian cocoa supply chain. Envir. Res. Let. doi:10.1088/1748-9326/acad8e These data refer to SEI-PCS Côte d’Ivoire Cocoa v1.1.0 Find assets required for the GEE scripts at : https://doi.org/10.5281/zenodo.7586257
DOI: 10.5519/qd.93blcv26
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (799 records)
DOI: 10.5281/zenodo.7588839
title: Psoas Cross-Sectional Measurements Using Manual CT Segmentation before and after Endovascular Aortic Repair (EVAR).

description: Monti CB, Righini P, Bonanno MC, Capra D, Mazzaccaro D, Giannetta M, Nicolino GM, Nano G, Sardanelli F, Marrocco-Trischitta MM, Secchi F. Psoas Cross-Sectional Measurements Using Manual CT Segmentation before and after Endovascular Aortic Repair (EVAR). J Clin Med. 2022 Jul 12;11(14):4023. doi: 10.3390/jcm11144023. PMID: 35887786; PMCID: PMC9325160. Abstract Sarcopenia has been associated with an increased incidence of adverse outcomes, including higher mortality, after endovascular aortic repair (EVAR). We aim to use computed tomography (CT) to quantify changes in total psoas muscles area (PMA) and psoas muscle density (PMD) after EVAR, and to evaluate the reproducibility of both measurements. PMA and PMD were assessed via manual segmentation of the psoas muscle on pre- and post-operative CT scans belonging to consecutive patients who underwent EVAR. Wilcoxon test was used to compare PMA and PMD before and after EVAR, and inter- and intra-reader agreements of both methods were evaluated through Bland-Altman analysis. A total of 50 patients, 42 of them males (84%), were included in the study. PMA changes from 1243 mm<sup>2</sup> (1006-1445 mm<sup>2</sup>) to 1102 mm<sup>2</sup> (IQR 937-1331 mm<sup>2</sup>), after EVAR (<em>p</em> &lt; 0.001). PMD did not vary between pre-EVAR (33 HU, IQR 26.5-38.7 HU) and post-EVAR (32 HU, IQR 26-37 HU, <em>p</em> = 0.630). At inter-reader Bland-Altman analysis, PMA showed a bias of 64.0 mm<sup>2</sup> and a coefficient of repeatability (CoR) of 359.2 mm<sup>2</sup>, whereas PMD showed a bias of -2.43 HU and a CoR of 6.19 HU. At intra-reader Bland-Altman analysis, PMA showed a bias of -81.1 mm<sup>2</sup> and a CoR of 394.6 mm<sup>2</sup>, whereas PMD showed a bias of 1.41 HU and a CoR of 6.36 HU. In conclusion, PMA decreases after EVAR. A good intra and inter-reader reproducibility was observed for both PMA and PMD. We thus propose to use PMA during the follow-up of patients who underwent EVAR to monitor muscle depletion after surgery.