cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7193501
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 391 m^2/kg Blaine, w/c=0.35)

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.raw greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details.
DOI: 10.5281/zenodo.7275149
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 391 m^2/kg Blaine, w/c=0.50) in TIFF format

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details. Note that the same dataset stored in *raw format is available from https://doi.org/10.5281/zenodo.7193798
DOI: 10.5281/zenodo.7193797
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 391 m^2/kg Blaine, w/c=0.50) in TIFF format

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details. Note that the same dataset stored in *raw format is available from https://doi.org/10.5281/zenodo.7193798
DOI: 10.5281/zenodo.7193798
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 391 m^2/kg Blaine, w/c=0.50)

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.raw greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details.
DOI: 10.6084/m9.figshare.21583209
title: Supplementary Material for: LncRNA HOXA-AS2 facilitates prostate cancer progression by inhibiting miR-885-5p to upregulate KDM5B

description: Background: The regulatory network of competing endogenous RNAs (ceRNAs) affects tumorigenesis. In this study, we aimed to investigate the mechanism by which long non-coding RNA (lncRNA) HOXA-AS2 promotes prostate cancer (PCa) progression. Methods: The expression levels of HOXA-AS2, miR-885-5p, and KDM5B in PCa tissues and cell lines were evaluated by qRT-PCR or western blotting. CCK-8 assay, caspase-3 activity assay, flow cytometry, and scratch test revealed changes in cell proliferation, caspase-3 activity, apoptosis, and migration, respectively. Luciferase and radioimmunoprecipitation assays were used to evaluate the correlation among HOXA-AS2, miR-885-5p, and KDM5B expression profiles. Results: HOXA-AS2 expression level was elevated in PCa tissues and cells. Silencing of HOXA-AS2 suppressed proliferation and migration and facilitated apoptosis in PCa cells. HOXA-AS2 competitively adsorbed miR-885-5p, thereby blocking the effect of HOXA-AS2 knockdown by the miR-885-5p inhibitor in PCa cells. Moreover, KDM5B, a target of miR-885-5p, neutralized the function of miR-885-5p in PCa cells. Conclusions: This study revealed a potential ceRNA regulatory pathway in which HOXA-AS2 affects KDM5B expression levels by sponging miR-885-5p to promote PCa development and progression.
DOI: 10.5281/zenodo.7275158
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.35) in TIFF format

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details. Note that the same dataset stored in *raw format is available from https://doi.org/10.5281/zenodo.7193808
DOI: 10.5281/zenodo.7193807
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.35) in TIFF format

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details. Note that the same dataset stored in *raw format is available from https://doi.org/10.5281/zenodo.7193808
DOI: 10.5281/zenodo.7193808
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.35)

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.raw greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details.
DOI: 10.5281/zenodo.7275174
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.50) in TIFF format

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details. Note that the same dataset stored in *raw format is available from https://doi.org/10.5281/zenodo.7193819
DOI: 10.5281/zenodo.7193818
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.50) in TIFF format

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.tif greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details. Note that the same dataset stored in *raw format is available from https://doi.org/10.5281/zenodo.7193819
DOI: 10.5281/zenodo.7193819
title: Three-dimensional dataset of hydrating cement paste (CEM I Ladce, 273 m^2/kg Blaine, w/c=0.50)

description: A detailed description of this dataset can be found in https://doi.org/10.1016/j.dib.2023.108903. This dataset contains a collection of digitized three-dimensional hardened cement paste microstructures obtained from X-ray micro-computed tomography, screened after approx. 1, 2, 3, 4, 7, 14, and 28 days of elapsed hydration at 20˚C in saturated conditions. Each paste specimen had a cylindrical shape (with a diameter of ~1 mm) and was screened at a designated time (as specified in the file name, e.g. “t23hrs”=23 hours of elapsed hydration) and finally saved as an uncompressed and unprocessed *.raw greyscale image data file in 16-bit image depth (as unsigned integers) using a little-endian byte sequence. The dataset contains two sets of images: - “full-sized” digital images stored in a three-dimensional voxel-based matrix with a fixed size of 1100x1100x1100 voxels, denoted as “CEM_I_Ladce_*” in the file name; each file size amounts to ~2.5 GB and contains the whole screened specimen with a variable voxel size in the range 1.0913 − 1.1174 µm depending on the particular specimen (as specified in the file name, e.g. “1d1174um”=1.1174 µm/voxel) - smaller image subvolumes, denoted as Region Of Interest (ROI), extracted from the interior of the full-sized specimen from an arbitrary location, and denoted as “filteredROI_*” in the file name; this cropped ROI has a cubic shape and stores a three-dimensional voxel-based matrix with a fixed size of 500x500x500 µm<sup>3</sup> constituted by a variable voxel count (given the fluctuating voxel size for each specimen, see above). Both the exact voxel count (i.e. three-dimensional matrix dimensions) and voxel size are further specified in each file name. A sequence of imaging filters was sequentially applied to this ROI to further enhance the contrast among the different microstructural phases, see 10.1016/j.cemconcomp.2022.104798 for details.
DOI: 10.5281/zenodo.7547702
title: DeepGeoStat WP5 Solar Panel Trained Network

description: This dataset contains the weights of a convolutional neural network (CNN) trained to recognize the presence of solar panels on aerial photos. In particular, it contains the saved state of a ResNet50 CNN that has been trained on a dataset containing annotated high-resolution aerial images of two regions in the south of the Netherlands. Many photos in this dataset have been annotated multiple times, and the annotations are not always unanimous. The dataset of aerial images together with annotations can be downloaded from here. The model for detecting whether solar panels are present in aerial photos has been developed under the DeepSolaris and DeepGeoStat projects. Corresponding Pytorch code can be found here. The code also demonstrates how to load the saved state into a ResNet50 model, and use it for detecting solar panels on aerial photos. This research was conducted under: ESS action 'Merging Geostatistics and Geospatial Information in Member States' (grant agreement no.: 08143.2017.001-2017.408), ESS topic B5674-2020-GEOS (project 101033951 2020-NL-GEOS-DEEP-GEO-STAT), a research program of Statistics Netherlands (https://www.cbs.nl)