cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p98pvdbw
title: Soil and Water Assessment Tool (SWAT) models for the Cape Fear River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections

description: As part of the Coastal Carolinas Focus Area Study of the U.S. Geological Survey National Water Census Program, the Soil and Water Assessment Tool (SWAT) was used to develop models for the Cape Fear River Basin, North Carolina, to simulate future streamflow and irrigation demand based on land use, climate, and water demand projections. SWAT is a basin-scale, process-based watershed model with the capability of simulating water-management scenarios. Model basins were divided into approximately two-square mile subbasins and subsequently divided into smaller, discrete hydrologic response units based on land use, slope, and soil type. The calibration period for the historic model was 2000 to 2014. The best available data on water-use from this time period were used, including public water supply, industrial water use, irrigation needs and golf courses. Six future scenario models simulated streamflow during the period 2055 to 2065 based on incorporation of two alternative land use projections, an ensemble of three global climate models, and water demand forecasts. This USGS data release contains all the input and output files for the simulations described in the associated model documentation report (https://doi.org/10.3133/sir20235036).
DOI: 10.5281/zenodo.3871497
title: Malaria in High-Resolution: Modelling and Mapping Plasmodium falciparum Parasite Rate using Very-High-Resolution Satellite Derived Indicators in Sub-Saharan African Cities

description: Metadata, results and supplementary material of the following article. The Out of Bag error of the Kampala Land use product is 18,57%. The Out of Bag error of the Dar es Salaam land use product is 16%. More information on the LC products can be found in here and here. This research is funded by the Belgian Science Policy through the REACT project.
DOI: 10.5281/zenodo.4518374
title: Genotyping of 4,506 bread wheat accessions with the TaBW410K SNP array

description: <strong>Genotyping data of 4,506 bread wheat accessions obtained with the TaBW410K SNP array.</strong> The 4,506 bread wheat accessions (Balfourier et al. Science Advances 2019) were genotyped using a high-density Affymetrix Axiom SNP array containing 409,695 SNPs (Kitt et al., in prep). Genotyping was conducted on the Affymetrix GeneTitan system according to the procedure described by Affymetrix (Axiom 2.0 Assay Manual Workflow User Guide Rev3). Allele calling was carried out using a modified version of the Affymetrix proprietary software packages Affymetrix Power Tools and SNPolisher (www.affymetrix.com/estore/partners_programs/programs/developer/tools/devnettools.affx) to take into account the specificities of the wheat genome. For all SNPs, HomRO, and HomFLD were calculated (http://media.affymetrix.com/support/developer/downloads/<br> Tools/SNPolisher_User_Guide.pdf). The HomFLD filter was set to 3.6. As a first step, all the probesets were processed with a mild<br> inbred penalty equal to four on all samples. As a second step, the SNPs failing the quality check criteria (“Other” and “NoMinorHom”)<br> were reprocessed using an inbred penalty of 16. Probesets classified as OTVs by SNPolisher were analyzed with OTV_caller in two<br> steps. SNPs were classified in six main categories according to cluster patterns produced by the Affymetrix software: PHR, OTV, monomorphic high resolution, no minor homozygous, call rate below threshold, and others. For further analyses, only PHRs and OTVs were selected. This dataset contains three files: Collection_geznotyping_matrix_410k.map: map file of 239,100 markers (PHRs or OTVs) to be used with PLINK Collection_geznotyping_matrix_410k.map: bed file of 239,100 markers (PHRs or OTVs) to be used with PLINK SNP_positions_410k.txt: position of 225,771 SNPs
DOI: 10.5281/zenodo.8192161
title: The daily gridded precipitation observations (0.5° × 0.5°) in central and eastern China (1961-2021)

description: The daily observed gridded precipitation data were obtained from the China Meteorological Data Service Center (http://www.nmic.cn/en) on 04-08-2021 but are currently not available at this website. These data have 128 columns and 72 rows with longitude and latitude starting from 72°E and 18°N, respectively. Spatial resolution is 0.5°×0.5°. Here, we provide these data during 1961-2021 in two study regions: central China (111°-116°E, 32°-37°N) and eastern China (118°-123°E, 28°-34°N). To make it easier for everyone to reuse the data, we select these data with adding two degrees in each direction of two regions. The selected data have 19 columns and 19 rows (21 columns and 19 rows) in central (eastern) China with the grid center's longitude and latitude ranging from (109°-118°E, 30°-39°N) to (116°-125°E, 26°-36°N).
DOI: 10.57982/821t-ff93
title: Consortium on Safe Labor

description: Collected detailed information from electronic medical records for 228,438 deliveries in 19 U.S. hospitals. Primary objectives were to explore the underlying causes of the high cesarean rate in the U.S. population, describe contemporary labor progression at the national level, and determine when is the more appropriate time to perform a cesarean delivery in women with labor protraction and arrest. 
NOTE: Data requesters should refer to the "CSL Read Me" PDF describing data caveats.
DOI: 10.6084/m9.figshare.22093559
title: Supplementary Material for: Metastasis of ovarian cancer to the descending colon

description: Colonic metastasis from ovarian cancer is extremely rare, with only seven reported cases. A 77-year-old woman who had previously undergone surgery for ovarian cancer was admitted to a local hospital with anal bleeding. Histopathological analysis confirmed the presence of adenocarcinoma. Colonoscopy revealed a descending colon tumor. The patient was diagnosed with Union for International Cancer Control T3N0M0 descending colon cancer or colon metastasis of the ovarian cancer. Laparoscopic left colectomy was performed; intraoperative frozen section diagnosis confirmed metastasis from ovarian cancer, and the absence of invasion to the serosal surface suggested hematogenous metastasis. This is the first case of colonic metastasis from ovarian cancer that was diagnosed using intraoperative frozen section and laparoscopically treated.
DOI: 10.6084/m9.figshare.23978217
title: Supplementary Material for: The effect of postnatal cytomegalovirus infection on (micro)structural cerebral development in very preterm infants at term-equivalent age

description: Introduction: There are some data indicating a negative impact of postnatal cytomegalovirus (CMV) infection on long-term neurodevelopmental outcome of preterm infants. So far, there is only little knowledge about a cerebral imaging correlate of these neurodevelopmental alterations induced by postnatal CMV infection in preterm infants. The aim of the current study is to investigate the effect of postnatal CMV infection on the incidence of brain injury and on microstructural brain maturation in very preterm infants at term-equivalent age. Methods: Infants &lt;32 gestational weeks (02/2011- 11/2018) received cerebral MRI including axial diffusion-weighted images at term-equivalent age. All infants were screened for CMV infection using urine/saliva samples, and infection was regarded as acquired postnatal if a sample became positive &gt;5 postnatal days. We compared brain injury as well as fractional anisotropy and apparent diffusion coefficient in 14 defined cerebral regions between infants with and without postnatal CMV infection. Results: 401 infants were eligible, of whom 18 (4.5%) infants had a postnatal CMV infection. There were no significant differences in rates of brain injury, nor in microstructural brain development between both groups. This applied equally to the subgroup of infants &lt;28 gestational weeks. Conclusion: Although infants with postnatal CMV infection were born more immature and more frequently suffered from complications related to immaturity, we neither observed a higher rate of preterm brain injury nor disadvantageous alterations in microstructural brain maturation at term-equivalent age.
DOI: 10.6084/m9.figshare.24004098
title: Supplementary Material for: Intra-abdominal paraganglioma and primary thyroid lymphoma in a single patient: the first case report

description: Rare diseases such as primary thyroid lymphoma (PTL) and paragangliomas exist. Although only 0.5% of patients experience a transformation from thyroiditis to PTL, patients with Hashimoto's thyroiditis have a higher risk of developing PTL than the general population. Primary non-Hodgkin lymphoma of the thyroid is rare. Paragangliomas are neuroendocrine tumors that originate from chromaffin cells situated along the sympathetic and parasympathetic chains. This paper reports the first case of primary diffuse large B-cell lymphoma with nonfunctional paraganglioma. A 29-year-old female, presented with an enlarged neck and recurring compressive symptoms. Ultrasonography (US) results showed a nodule in the right lobe of the thyroid gland. Emergency thyroidectomy was performed after obtaining inconclusive fine-needle aspiration (FNA) results. Immunohistopathology of the biopsy specimen confirmed the presence of a large diffuse B-cell lymphoma. Computed tomography revealed a non-functional mass in the adrenal gland. The team then proceeded with the appropriate treatment.
DOI: 10.6084/m9.figshare.24013914
title: Supplementary Material for: Usefulness and Educational Benefit of a Virtual Scale Endoscope in Measuring Colorectal Polyp Size

description: Introduction: The virtual scale endoscope (VSE) is a newly introduced endoscope that helps endoscopists in measuring colorectal polyp size (CPS) during colonoscopy by displaying a virtual scale. This study aimed to determine the usefulness of the VSE for CPS measurement and the educational benefit of using VSE images to improve CPS estimation accuracy. Methods: This study included 42 colorectal polyps in 26 patients treated at Hiroshima University Hospital. In Study 1, CPS measured using a VSE before endoscopic mucosal resection was compared with CPS measured on resected specimens, and the agreement between the two measurement methods was evaluated via Bland–Altman analysis. In Study 2, 14 endoscopists (5 beginners, 5 intermediates, and 4 experts) took a pre-test to determine the size of 42 polyps. After the pre-test, a lecture on CPS measurement using VSE images was given. One month later, the endoscopists took a post-test to compare CPS accuracy before and after the lecture. Results: In Study 1, Bland–Altman analysis revealed no fixed or proportional errors. The mean bias ± 95% limits of agreement (±1.96 standard deviations) of the measurement error was -0.05 ± 0.21 mm, indicating that the agreement between two measurement methods was sufficient. In Study 2, the accuracy of CPS measurement was significantly higher among beginners (59.5% vs. 26.7%, p &lt; 0.01) and intermediates (65.2% vs. 44.3%, p &lt; 0.05) in the post-test than in the pre-test. Conclusion: The VSE accurately measures CPS before resection, and its images are useful teaching tools for beginner and intermediate endoscopists.
DOI: 10.6084/m9.figshare.24131670
title: Short Tandem Repeat Analysis of the REH cell line.

description: Short Tandem Repeat Analysis of the REH cell line.
DOI: 10.18462/iir.gl.2020.1146
title: Active latent heat storage using biowax in a central heating system of a ZEB living lab.
DOI: 10.5281/zenodo.1291389
title: Dakar Land Use Map At Street Block Level

description: This datatset contains a land use classification of Dakar (Senegal) at the street block level. It was created following the methodology presented in [1].

Description of the files:


	"Dakar_landuse_shapefile.zip" : Shapefile of the street blocks extracted from OpenStreetMap using [2] with classification results in the attribute table.
	"Dakar_landuse_style.zip" : Files for style of the shapefile.


Attribute table content:


	"CAT", "GID" : ID of the street block
	"PROB_ACS" : Probability to belong to class ACS
	"PROB_AGRI" : Probability to belong to class AGRI
	"PROB_BARE" : Probability to belong to class BARE
	"PROB_DEPR" : Probability to belong to class DEPR
	"PROB_PLAN" : Probability to belong to class PLAN
	"PROB_VEG" : Probability to belong to class VEG
	"FIRST_LABE" : Class with the highest classification probability
	"SEC_LABEL" : Class with the second highest classification probability
	"FIRST_PROB" : Value of the highest classification probability
	"SEC_PROB" : Value of the second highest classification probability
	"UNCERTAIN" : Difference between "FIRST_PROB" and "SEC_PROB"
	"BUILT_PERC" : Percentage of the street blocks covered by built-up (from land cover map)
	"MAP_LABEL" : Final classification label with uncertainty and different density classes


Legend classes label:


	"AGRI" : Agricultural vegetation
	"VEG" : Natural vegetation
	"BARE" : Bare soils
	"ACS" : Non-residential built-up (administrative, commercial, services, etc.)
	"PLAN" : Planned residential built-up
	"PLAN_LD" : Planned residential low density built-up
	"DEPR" : Deprived residential built-up
	"UNCERT" : Uncertain classification


References:

[1] Grippa, Tais, 2018, "Mapping urban land use at street block level using OpenStreetMap, remote sensing data and spatial metrics", <em>ISPRS Int. J. Geo-Inf.</em> <strong>2018</strong>, <em>7</em>(7), 246. https://doi.org/10.3390/ijgi7070246 

[2] Grippa, Tais. 2018. “Osm Street Blocks Extraction.” Zenodo. https://doi.org/10.5281/zenodo.1290637.

Funding: 

This dataset was produced in the frame of two research project : MAUPP (http://maupp.ulb.ac.be) and REACT (http://react.ulb.be), funded by the Belgian Federal Science Policy Office (BELSPO).
description: The production of this dataset was founded by BELSPO (Belgian Federal Science Policy Office) in the frame of the
STEREO III program, as part of the MAUPP (SR/00/304) and REACT (SR/00/337) project (http://maupp.ulb.ac.be
and http://react.ulb.be/).
DOI: 10.5281/zenodo.3238302
title: Ouagadougou land use map at street block level

description: This datatset contains a land use classification of Ouagadougou (Burkina Faso) at the street block level. It was created following the methodology presented in [1]. Description of the files: "Ouagadougou_landuse.gpkg" : GeoPackage with two layers: (1) layer of the street blocks extracted from OpenStreetMap using [2] with classification results in the attribute table. (2) layer with manual correction made by GEORGANOS Stefanos (sgeorganos@ulb.ac.be). "Ouagadougou_landuse_style_QGIS.zip" : Files for style for rendering in QGIS. Attribute table content: "CAT", "GID" : ID of the street block "PROB_ACS" : Probability to belong to class ACS "PROB_BARE" : Probability to belong to class BARE "PROB_PLAN" : Probability to belong to class PLAN "PROB_UNPLA" : Probability to belong to class UNPLAN "PROB_VEG" : Probability to belong to class VEG "FIRST_LABE" : Class with the highest classification probability "SEC_LABEL" : Class with the second highest classification probability "FIRST_PROB" : Value of the highest classification probability "SEC_PROB" : Value of the second highest classification probability "UNCERTAIN" : Difference between "FIRST_PROB" and "SEC_PROB" "BUILT_PERC" : Percentage of the street blocks covered by built-up (from land cover map) "MAP_LABEL" : Final classification label with uncertainty and different density classes. Depending on the layer, the label is with or without manual corrections Legend classes label: "VEG" : Vegetation "BARE" : Bare soils "ACS" : Non-residential built-up (administrative, commercial, services, etc.) "PLAN" : Planned residential built-up "PLAN_LD" : Planned residential low density built-up "UNPLAN" : Unplanned residential built-up "UNPLAN_LD" : Unplanned residential low density built-up "UNCERT" : Uncertain classification "WET" : Wetlands "AGRI" : Agricultural land References: [1] Grippa, Tais, 2018, "Mapping urban land use at street block level using OpenStreetMap, remote sensing data and spatial metrics", <em>ISPRS Int. J. Geo-Inf.</em> <strong>2018</strong>, <em>7</em>(7), 246. https://doi.org/10.3390/ijgi7070246 [2] Grippa, Tais. 2018. “Osm Street Blocks Extraction.” Zenodo. https://doi.org/10.5281/zenodo.1290637. Funding: This dataset was produced in the frame of two research project : MAUPP (http://maupp.ulb.ac.be) and REACT (http://react.ulb.be), funded by the Belgian Federal Science Policy Office (BELSPO).
description: The production of this dataset was founded by BELSPO (Belgian Federal Science Policy Office) in the frame of the STEREO III program, as part of the MAUPP (SR/00/304) and REACT (SR/00/337) project (http://maupp.ulb.ac.be and http://react.ulb.be/).
DOI: 10.57745/f86myp
title: Mare_motifs_Mare_transcriptome.tab

description: :unav
DOI: 10.57745/hrlcci
title: transcripts_Mare-1.tab

description: :unav
DOI: 10.57745/q9dxu1
title: transcripts_Mare.tab

description: :unav
DOI: 10.25582/data.2021-09.2340718/2095762
title: Data for EMSL Project 51241 from September 2021
DOI: 10.25582/data.2021-09.2340865/2095763
title: Data for EMSL Project 51241 from September 2021
DOI: 10.18462/iir.nh3-co2.2021.0021
title: A cold thermal energy storage unit for CO2 refrigeration using phase change material: First experimental results.
DOI: 10.5281/zenodo.1290654
title: Ouagadougou Very-High Resolution Land Cover Map

description: This land cover map of Ouagadougou (Burkina Faso) was created from a WorldView3 very-high resolution imagery with a spatial resolution of 0.5 meter. The methodology followed a open-source semi-automated framework [1] that rely on GRASS GIS using a local unsupervised optimization approach for the segmentation part [2-3].

Description of the files:


	"Landcover.zip" : The direct output from the supervised classification using the Random Forest classifier.
	"Landcover_Postclassif_Level5_Splitbuildings.zip" : Post-processed version of the previous map ("Landcover"), with reduced misclassifications from the original classification (rule-based used to reclassify the errors, with a focus on built-up classes).
	"Landcover_Postclassif_Level5_modalfilter3.zip" : Smoothed version of the previous product (modal filter with window 3x3 applied on the "Landcover_Postclassif_Level5_Splitbuildings"). 
	"Landcover_Postclassif_Level6_Shadowsback.zip" : Corresponds to the "level5_Splitbuildings" with shadows coming from the original classification.
	"Ouaga_legend_colors.txt" : Text file providing the correspondance between the value of the pixels and the legend labels and a proposition of color to be used.


 

References:

[1] Grippa, Taïs, Moritz Lennert, Benjamin Beaumont, Sabine Vanhuysse, Nathalie Stephenne, and Eléonore Wolff. 2017. “An Open-Source Semi-Automated Processing Chain for Urban Object-Based Classification.” <em>Remote Sensing</em> 9 (4): 358. https://doi.org/10.3390/rs9040358.

[2] Grippa, Tais, Stefanos Georganos, Sabine G. Vanhuysse, Moritz Lennert, and Eléonore Wolff. 2017. “A Local Segmentation Parameter Optimization Approach for Mapping Heterogeneous Urban Environments Using VHR Imagery.” In <em>Proceedings Volume 10431, Remote Sensing Technologies and Applications in Urban Environments II.</em>, edited by Wieke Heldens, Nektarios Chrysoulakis, Thilo Erbertseder, and Ying Zhang, 20. SPIE. https://doi.org/10.1117/12.2278422.

[3] Georganos, Stefanos, Taïs Grippa, Moritz Lennert, Sabine Vanhuysse, and Eleonore Wolff. 2017. “SPUSPO: Spatially Partitioned Unsupervised Segmentation Parameter Optimization for Efficiently Segmenting Large Heterogeneous Areas.” In <em>Proceedings of the 2017 Conference on Big Data from Space (BiDS’17)</em>.

 

Founding: 

This dataset was produced in the frame of two research project : MAUPP (http://maupp.ulb.ac.be) and REACT (http://react.ulb.be), funded by the Belgian Federal Science Policy Office (BELSPO).
description: The production of this dataset was founded by BELSPO (Belgian Federal Science Policy Office) in the frame of the
STEREO III program, as part of the MAUPP (SR/00/304) and REACT (SR/00/337) project (http://maupp.ulb.ac.be
and http://react.ulb.be/).
DOI: 10.5281/zenodo.1290800
title: Dakar Very-High Resolution Land Cover Map

description: This land cover map of Dakar (Senegal) was created from a Pléiades very-high resolution imagery with a spatial resolution of 0.5 meter. The methodology followed a open-source semi-automated framework [1] that rely on GRASS GIS using a local unsupervised optimization approach for the segmentation part [2-3].

Description of the files:


	"Landcover.zip" : The direct output from the supervised classification using the Random Forest classifier.
	"Landcover_Postclassif_Level8_Splitbuildings.zip" : Post-processed version of the previous map ("Landcover"), with reduced misclassifications from the original classification (rule-based used to reclassify the errors, with a focus on built-up classes).
	"Landcover_Postclassif_Level8_modalfilter3.zip" : Smoothed version of the previous product (modal filter with window 3x3 applied on the "Landcover_Postclassif_Level8_Splitbuildings"). 
	"Landcover_Postclassif_Level9_Shadowsback.zip" : Corresponds to the "level8_Splitbuildings" with shadows coming from the original classification.
	"Dakar_legend_colors.txt" : Text file providing the correspondance between the value of the pixels and the legend labels and a proposition of color to be used.


 

References:

[1] Grippa, Taïs, Moritz Lennert, Benjamin Beaumont, Sabine Vanhuysse, Nathalie Stephenne, and Eléonore Wolff. 2017. “An Open-Source Semi-Automated Processing Chain for Urban Object-Based Classification.” <em>Remote Sensing</em> 9 (4): 358. https://doi.org/10.3390/rs9040358.

[2] Grippa, Tais, Stefanos Georganos, Sabine G. Vanhuysse, Moritz Lennert, and Eléonore Wolff. 2017. “A Local Segmentation Parameter Optimization Approach for Mapping Heterogeneous Urban Environments Using VHR Imagery.” In <em>Proceedings Volume 10431, Remote Sensing Technologies and Applications in Urban Environments II.</em>, edited by Wieke Heldens, Nektarios Chrysoulakis, Thilo Erbertseder, and Ying Zhang, 20. SPIE. https://doi.org/10.1117/12.2278422.

[3] Georganos, Stefanos, Taïs Grippa, Moritz Lennert, Sabine Vanhuysse, and Eleonore Wolff. 2017. “SPUSPO: Spatially Partitioned Unsupervised Segmentation Parameter Optimization for Efficiently Segmenting Large Heterogeneous Areas.” In <em>Proceedings of the 2017 Conference on Big Data from Space (BiDS’17)</em>.

 

Founding: 

This dataset was produced in the frame of two research project : MAUPP (http://maupp.ulb.ac.be) and REACT (http://react.ulb.be), funded by the Belgian Federal Science Policy Office (BELSPO).
description: The production of this dataset was founded by BELSPO (Belgian Federal Science Policy Office) in the frame of the
STEREO III program, as part of the MAUPP (SR/00/304) and REACT (SR/00/337) project (http://maupp.ulb.ac.be
and http://react.ulb.be/).