cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/2e472483-255b-4468-b5a2-beb413746b48
title: Landelijk Grondgebruik Nederland 2021 (LGN2021)

description: LGN2021 is a grid file that shows Dutch land use in 2021 with a spatial resolution of 5m. The legend consists of 50 land use classes. Compared to the previous LGN version (LGN2020), the class solar parks was added, the LGN class 25 'Hoofdwegen en spoorwegen' was split into 3 classes, the LGN class 24 'Kale grond inprimair bebouwd gebied' was removed and LGN class 45 got a different definition and the name changed into 'Natuurlijk beheerde agrarische graslanden'. LGN2021 is distinguishing the main agricultural crops, forest, water, nature and urban classes. LGN2021 is a continuation of the LGN 2018-2020 versions. However, theproduction method has been modified.The following files were used to create LGN2021: Top10NL (version November 2021), Basis Registratie Percelen 2021 (BRP2021), Bestand BodemGebruik 2015 (BBG2015), Beheertypen Information Model Nature 2021 (IMNa2021) and the Algemeen Hoogtemodel Nederland (AHN3/4). In additionsatellite images (particularly Sentinel-2) and aerial photos from 2021 have been used in the classification of nature.<br>The dataset is public since May 2023 which is made possible by WOT Natuur & Milieu, Het Waterschapshuis,Interprovinciaal Overleg, RIVM and Wageningen Environmental Research.
DOI: 10.4121/2e472483-255b-4468-b5a2-beb413746b48.v1
title: Landelijk Grondgebruik Nederland 2021 (LGN2021)

description: LGN2021 is a grid file that shows Dutch land use in 2021 with a spatial resolution of 5m. The legend consists of 50 land use classes. Compared to the previous LGN version (LGN2020), the class solar parks was added, the LGN class 25 'Hoofdwegen en spoorwegen' was split into 3 classes, the LGN class 24 'Kale grond inprimair bebouwd gebied' was removed and LGN class 45 got a different definition and the name changed into 'Natuurlijk beheerde agrarische graslanden'. LGN2021 is distinguishing the main agricultural crops, forest, water, nature and urban classes. LGN2021 is a continuation of the LGN 2018-2020 versions. However, theproduction method has been modified.The following files were used to create LGN2021: Top10NL (version November 2021), Basis Registratie Percelen 2021 (BRP2021), Bestand BodemGebruik 2015 (BBG2015), Beheertypen Information Model Nature 2021 (IMNa2021) and the Algemeen Hoogtemodel Nederland (AHN3/4). In additionsatellite images (particularly Sentinel-2) and aerial photos from 2021 have been used in the classification of nature.<br>The dataset is public since May 2023 which is made possible by WOT Natuur & Milieu, Het Waterschapshuis,Interprovinciaal Overleg, RIVM and Wageningen Environmental Research.
DOI: 10.4121/eeeecfeb-dc78-4831-823a-d857ff7bab89
title: Landelijk Grondgebruik Nederland versie 5 (LGN5)

description: The LGN5 database is gridfile with a resolution of 25m*25m. The database provides the Dutch land use for the reference years 2003 (eastern part of NL) and 2004 (western part of NL). The legend consist of 39 land use classes divided about the main classes of agricultural area, forests, water, urban area and nature. The database is based on satellite images from the years 2003 and 2004. Besides satellite images, there is information from Top10 vector SE, CBS agricultural statistics, aerial photos, Basisregistratie Percelen (BRP), Eco-management map, data from Natuurmonumenten, Staatsbosbeheer and Provinciale Landscapes, and LGN4 used in the production of LGN5.<br>The dataset is since May 2023 public which is made possible by WOT Natuur & Milieu, Het Waterschapshuis, Interprovinciaal Overleg, RIVM and Wageningen Environmental Research.
DOI: 10.4121/eeeecfeb-dc78-4831-823a-d857ff7bab89.v1
title: Landelijk Grondgebruik Nederland versie 5 (LGN5)

description: The LGN5 database is gridfile with a resolution of 25m*25m. The database provides the Dutch land use for the reference years 2003 (eastern part of NL) and 2004 (western part of NL). The legend consist of 39 land use classes divided about the main classes of agricultural area, forests, water, urban area and nature. The database is based on satellite images from the years 2003 and 2004. Besides satellite images, there is information from Top10 vector SE, CBS agricultural statistics, aerial photos, Basisregistratie Percelen (BRP), Eco-management map, data from Natuurmonumenten, Staatsbosbeheer and Provinciale Landscapes, and LGN4 used in the production of LGN5.<br>The dataset is since May 2023 public which is made possible by WOT Natuur & Milieu, Het Waterschapshuis, Interprovinciaal Overleg, RIVM and Wageningen Environmental Research.
DOI: 10.4121/9a7f257e-1132-4c34-ae96-b1a0b815789e
title: Landelijk Grondgebruik Nederland versie 6 (LGN6)

description: The LGN6 database is a grid file with a resolution of 25*25 m. The database provides the Dutch land use for one reference year, the years 2007 (eastern NL) and 2008 (western NL). The legend consists of 39 land use classes, distinguishing the main agricultural crops, forest, water, nature and urban classes. Compared to LGN5 somethematic changes in class content were applied. In LGN6, the following land use classes have disappeared:– deciduous forest in built-up areas (LGN5 class 20)– coniferous forest in built-up areas (LGN5 class 21)– forest in densely built-up areas (LGN5 class 22)– peat meadows / veenweidegebied (LGN5 class 44)– bare ground in nature areas (LGN5 class 46)<br>The LGN5 classes 20, 21 and 22 have been merged and classified as forest in primary or secondary built-up area, respectively class 20 and 22. New classes are tree nurseriers, fruit cultivation and grassland in secundary built-up areas.<br>The LGN6 database has used the following data sources:• Top10NL (version 2006)• Bestand BodemGebruik 2003 (BBG2003)• Begrenzing Bebouwd Gebied (BG2003)• Basiskaart Natuur 2007 (BKN2007)• Landelijk Grondgebruik Nederland versie 5 (LGN5)• CBS landbouwstatistiek• BasisRegistratie Percelen 2007/2008 (BRP2007/2008)• Aerial photos and satellite imagery<br>The dataset is since May 2023 public which is made possible by WOT Natuur & Milieu, Het Waterschapshuis,Interprovinciaal Overleg, RIVM and Wageningen Environmental Research.
DOI: 10.4121/9a7f257e-1132-4c34-ae96-b1a0b815789e.v1
title: Landelijk Grondgebruik Nederland versie 6 (LGN6)

description: The LGN6 database is a grid file with a resolution of 25*25 m. The database provides the Dutch land use for one reference year, the years 2007 (eastern NL) and 2008 (western NL). The legend consists of 39 land use classes, distinguishing the main agricultural crops, forest, water, nature and urban classes. Compared to LGN5 somethematic changes in class content were applied. In LGN6, the following land use classes have disappeared:– deciduous forest in built-up areas (LGN5 class 20)– coniferous forest in built-up areas (LGN5 class 21)– forest in densely built-up areas (LGN5 class 22)– peat meadows / veenweidegebied (LGN5 class 44)– bare ground in nature areas (LGN5 class 46)<br>The LGN5 classes 20, 21 and 22 have been merged and classified as forest in primary or secondary built-up area, respectively class 20 and 22. New classes are tree nurseriers, fruit cultivation and grassland in secundary built-up areas.<br>The LGN6 database has used the following data sources:• Top10NL (version 2006)• Bestand BodemGebruik 2003 (BBG2003)• Begrenzing Bebouwd Gebied (BG2003)• Basiskaart Natuur 2007 (BKN2007)• Landelijk Grondgebruik Nederland versie 5 (LGN5)• CBS landbouwstatistiek• BasisRegistratie Percelen 2007/2008 (BRP2007/2008)• Aerial photos and satellite imagery<br>The dataset is since May 2023 public which is made possible by WOT Natuur & Milieu, Het Waterschapshuis,Interprovinciaal Overleg, RIVM and Wageningen Environmental Research.
DOI: 10.4121/6dfe7bd5-16f7-4e8d-9ab7-f8203b902310
title: Supplementary data for the paper 'Should an External Human-Machine Interface Flash or Just Show Text? A Study with a Gaze-Contingent Setup'

description: Automated vehicles need to prioritize pedestrian safety. One way to achieve this is through external human-machine interfaces (eHMIs) that send visual signals to pedestrians. eHMIs can be either text-based or light-based. However, there has been limited research on the effects of these types of eHMI on human information processing and attention allocation. This study aimed to fill this gap by using a gaze-contingent approach, which blurs the view outside a circular aperture, to test the hypothesis that text-based eHMIs, which require focused or foveal attention, result in longer response times compared to light-based eHMIs, which can be understood using peripheral vision. In this study, 23 participants watched animated video clips of traffic situations involving automated vehicles with either no eHMI, a flashing-light eHMI, or a text-based eHMI. Their eye movements were tracked, and they were asked to press the spacebar when they felt it was safe to cross the road. The results showed faster response times when an eHMI was present, with no significant difference between the two types of eHMIs. Further analysis suggested that the flashing-light eHMI captured attention briefly, while the text-based eHMI held attention for a longer period. When no eHMI was present, participants focused on the approaching vehicle for the longest time. The gaze-contingent window resulted in fewer eye movements and slower response times. In conclusion, the study showed that the gaze-contingent window negatively affected response times and eye movements, emphasizing the importance of considering peripheral vision when designing eHMIs for pedestrian safety.
DOI: 10.4121/6dfe7bd5-16f7-4e8d-9ab7-f8203b902310.v1
title: Supplementary data for the paper 'Should an External Human-Machine Interface Flash or Just Show Text? A Study with a Gaze-Contingent Setup'

description: Automated vehicles need to prioritize pedestrian safety. One way to achieve this is through external human-machine interfaces (eHMIs) that send visual signals to pedestrians. eHMIs can be either text-based or light-based. However, there has been limited research on the effects of these types of eHMI on human information processing and attention allocation. This study aimed to fill this gap by using a gaze-contingent approach, which blurs the view outside a circular aperture, to test the hypothesis that text-based eHMIs, which require focused or foveal attention, result in longer response times compared to light-based eHMIs, which can be understood using peripheral vision. In this study, 23 participants watched animated video clips of traffic situations involving automated vehicles with either no eHMI, a flashing-light eHMI, or a text-based eHMI. Their eye movements were tracked, and they were asked to press the spacebar when they felt it was safe to cross the road. The results showed faster response times when an eHMI was present, with no significant difference between the two types of eHMIs. Further analysis suggested that the flashing-light eHMI captured attention briefly, while the text-based eHMI held attention for a longer period. When no eHMI was present, participants focused on the approaching vehicle for the longest time. The gaze-contingent window resulted in fewer eye movements and slower response times. In conclusion, the study showed that the gaze-contingent window negatively affected response times and eye movements, emphasizing the importance of considering peripheral vision when designing eHMIs for pedestrian safety.
DOI: 10.5517/ccdc.csd.cc2f8192
title: CCDC 2242053: Experimental Crystal Structure Determination

description: Related Article: Zhixin Zheng|2023|CSD Communication|||
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: 10.48323/h07f4-qzd17
title: UIBK Avalanche Dataset

description: UIBK Avalanche Dataset
Dataset of 4090 labelled avalanche photographs. Each photograph in the dataset was assigned to one of four categories: glide, loose, slab, or none. These labels refer to the different avalanche release mechanisms: glide, loose-snow, and slab, with none indicating the absence of avalanches. In addition,  avalanche experts outlined each visible avalanche with a polygonal bounding box and assigned it a single label of glide, loose, or slab. 
The photographs were taken in the field in the winters of 2000/2001 - 2021/2022 and each image has the date and approximate location at which it was taken in the image name. Most photographs in the dataset were taken from the ground: additional images from low-flying helicopters were included only if the annotators deemed that they could feasibly have been taken by webcams.
Accompanying code for training ResNet, VGG, and YOLOv3 models to detect avalanches is available at github.com/j-f-ox/avalanche-detection
Folders

annotations      # Polygonal and rectangular bounding boxes for each avalanche image

glide
loose
slab
images             # The .jpg images sorted by overall image label

glide
loose
none
slab
test.txt              # Test images
train.txt             # Training images
 
Label Distribution 

The images folder contains 716 glide, 416 loose, and 1887 slab avalanche photographs and a further 1071 "none" images without visible avalanche regions
The dataset contains a total of 2489 annotated glide avalanches, 1827 loose-snow avalanches, and 2912 slab avalanches
DOI: 10.6084/m9.figshare.23633988
title: Maximum likelihood phylogeny of TfoX N terminal domain

description: Proteins containing the TfoX N-terminal domain were identified using EMBL SMART. These amino acid sequences were aligned with MAFFT, and a phylogeny generated with Fasttree2 using default settings. Proteins were assigned to bacterial Families using the NCBI Taxonomy.
DOI: 10.6084/m9.figshare.23633988.v1
title: Maximum likelihood phylogeny of TfoX N terminal domain

description: Proteins containing the TfoX N-terminal domain were identified using EMBL SMART. These amino acid sequences were aligned with MAFFT, and a phylogeny generated with Fasttree2 using default settings. Proteins were assigned to bacterial Families using the NCBI Taxonomy.
DOI: 10.15151/esrf-es-1215135018
title: Selenate reduction in environmental geomedia

description: Long-term safety assessment of the underground repository for the high-level and long-lived radioactive waste requires a characterization at the molecular level of the processes that can take place onto the involved solid surfaces and the considered radioactive pollutants. Among them, the 79Se isotope (∼3.27 × 105 years half-life time) is considered as one of the main radionuclides contributing to the dose-to-man after final disposal. Reductive precipitation of oxidized (mobile) species of selenium by redox-active Fe(II)-phases is one of the main mechanisms that can help to decrease the mobility of selenium in these systems. Here, we aim to check whether the presence of sulfate and carbonate, two common ions in the clayey formation hosting the French repository, pose some limitations for the electron transfer from the Fe(II)-bearing solids magnetite (a common corrosion product of steel canisters) and pyrite (a common Fe(II)-solid in the Cox formation).
DOI: 10.6084/m9.figshare.23652420
title: Vertebrate Scavenger Experiment Data

description: Data supporting the findings of the study 'Super-scavengers: Vertebrates outperform invertebrates and microbes at removing carrion from a tropical forest' by Bhavya Iyer, Sutirtha Dutta, Qamar Qureshi, Yadvendradev V. Jhala, Wildlife Institute of India, Chandrabani, Dehradun, 248001, India. <br>
DOI: 10.6084/m9.figshare.23652420.v2
title: Vertebrate Scavenger Experiment Data

description: Data supporting the findings of the study 'Super-scavengers: Vertebrates outperform invertebrates and microbes at removing carrion from a tropical forest' by Bhavya Iyer, Sutirtha Dutta, Qamar Qureshi, Yadvendradev V. Jhala, Wildlife Institute of India, Chandrabani, Dehradun, 248001, India. <br>
DOI: 10.6084/m9.figshare.23652420.v1
title: Vertebrate Scavenger Experiment Data

description: Data supporting the findings of the study 'Super-scavengers: Vertebrates outperform invertebrates and microbes at removing carrion from a tropical forest' by Bhavya Iyer, Sutirtha Dutta, Qamar Qureshi, Yadvendradev V. Jhala, Wildlife Institute of India, Chandrabani, Dehradun, 248001, India. <br>
DOI: 10.3217/rb5e1-s4534
title: Illuminating the inner workings of a natural protein switch: Blue-light sensing in LOV-activated diguanylate cyclases

description: Corresponding raw data files for individual figure panels
DOI: 10.21227/qtgd-5t05
title: TP-GCN

description: Forum-java is a log dataset that we collected in an open source java-based web forum system {https://github.com/Qbian61/forum-java.}. It is a Java-based forum platform developed by a technology company and widely used for social media and programming technique sharing it contains abundant and diverse functions, like posting articles, creating FAQs, etc., which can satisfy most of the requirements of users. In order to generate negative samples, we imitate the real bug situation and inject some faults from real industrial cases into the normal system, namely call change, condition change, argument change, and chain change.This dataset contains tens of millions of log data collected by the web servers during system operation, and every log records a series of dynamic system behaviors generated during the operation of the forum system. This dataset contains 172,443 dynamic session networks based on trace IDs, which contain 56,080 abnormal negative samples, with an abnormal proportion of 32.5%. Each node in the network represents a log event and contains features about call status, duration, and exceptions. Each edge denotes that the event occurs after the previous event.
DOI: 10.17617/4.cj
title: 2-Sulfonylpyrimidines as Privileged Warheads for the Development of S. aureus Sortase A Inhibitors

description: This contains the Mass Spectrometry Raw Data of: Barthels, F.; Meyr, J.; Hammerschmidt, S. J.; Marciniak, T.; Räder, H.-J.; Ziebuhr, W.; Engels, B.; Schirmeister, T.: 2-Sulfonylpyrimidines as Privileged Warheads for the Development of S. aureus Sortase A Inhibitors. Frontiers in Molecular Biosciences 2022, 8, 804970. 10.3389/fmolb.2021.804970 No other data was collected at the MPIP.
DOI: 10.25919/3r0m-t350
title: Parkes observations for project P1183 semester 2023APRS_12

description: A new energetic repeating FRB 20220529 can be observed by both FAST and Parkes telescopes and the simultaneous observing time is up to one hour. We have observed this source using Parkes UWL green time and in total 21 bursts have been detected. Two bursts of them have the corresponding simultaneous FAST observations. Only one burst has 4-pol datasets and is bright enough to analyse the polarization properties. Therefore, we propose to continue the monitoring of the source of FRB 20220529 using the Parkes UWL with high-time resolution and 4-pol observation. The new proposed observation aims to: (1)detect more bursts by Parkes UWL with full polarization information; (2) detect more bursts by Parkes UWL with corresponding simultaneous FAST observations; (3) study the radiation spectrum by more bursts detected in simultaneous observations of Parkes and FAST; (4) study the burst microstructure using high time resolution datasets, and (5) study the frequency ranges changes of the repeating bursts.
DOI: 10.5281/zenodo.8129250
title: Data for "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed"

description: This folder holds the data for the paper "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed" (in submission) More information regarding this paper and the data is given in the GitHub repository (https://github.com/sgielis/WT1_TCR) The raw folder contains all MiXCR files for the two studied WT1 epitopes and two VZV epitopes. The VZV epitopes were not taken into account in this paper, but were used to build VZV-specific TCRex models for another paper [in submission]. Since all TCRs for the 4 epitopes were sequences together, this data was used for quality control purposes as explained in the paper. Following 4 folders are present: run1: TCR data from the first run for WT1-126, WT1-37 and IE62 run1_orf18: TCR data from the first run for ORF18 run2: WT1-37 data filtered on high and low threshold gating. run 3: extra TCR data for WT1-126, WT1-37 aligned with MiXCR
description: This work was supported in part by research grants of the Special Research Fund of the University of Antwerp (Small Research Grants ID36379, BOF-KP2018 P.M. and ID41605, Concerted Research Action) and the Methusalem financing program of the Flemish Government to the Antwerp University, the Cellular Therapy Fund from the Antwerp University Hospital (UZA) and UZA Foundation (Belgium), iBOF Project "Modulating Immunity and the Microbiome for Effective CRC Immunotherapy" (MIMICRY) and the public utility foundation Stichting ME TO YOU (Belgium). D.F. was supported by the ''Cellular Immunotherapy'' grant from the Baillet Latour Fund (Belgium), and an Emmanuel van der Schueren fellowship from Kom op tegen Kanker (KotK, Belgium), followed by a DOCPRO PhD grant of the Special Research Fund (Grant MulTplex). S.G. and M.V. were supported by an SB fellowship from the FWO (S.G. grant 1S48819N, M.V. grant 1S24517N). E.B. and S.v.d.H. were supported via a clinical investigator fellowship from the Research Foundation-Flanders (FWO, Belgium) of B.O. (grant 1861219N). D.C.D. and H.D.R. were supported by grant G053518N from the FWO.
DOI: 10.5281/zenodo.8129249
title: Data for "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed"

description: This folder holds the data for the paper "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed" (in submission) More information regarding this paper and the data is given in the GitHub repository (https://github.com/sgielis/WT1_TCR) The raw folder contains all MiXCR files for the two studied WT1 epitopes and two VZV epitopes. The VZV epitopes were not taken into account in this paper, but were used to build VZV-specific TCRex models for another paper [in submission]. Since all TCRs for the 4 epitopes were sequences together, this data was used for quality control purposes as explained in the paper. Following 4 folders are present: run1: TCR data from the first run for WT1-126, WT1-37 and IE62 run1_orf18: TCR data from the first run for ORF18 run2: WT1-37 data filtered on high and low threshold gating. run 3: extra TCR data for WT1-126, WT1-37 aligned with MiXCR
description: This work was supported in part by research grants of the Special Research Fund of the University of Antwerp (Small Research Grants ID36379, BOF-KP2018 P.M. and ID41605, Concerted Research Action) and the Methusalem financing program of the Flemish Government to the Antwerp University, the Cellular Therapy Fund from the Antwerp University Hospital (UZA) and UZA Foundation (Belgium), iBOF Project "Modulating Immunity and the Microbiome for Effective CRC Immunotherapy" (MIMICRY) and the public utility foundation Stichting ME TO YOU (Belgium). D.F. was supported by the ''Cellular Immunotherapy'' grant from the Baillet Latour Fund (Belgium), and an Emmanuel van der Schueren fellowship from Kom op tegen Kanker (KotK, Belgium), followed by a DOCPRO PhD grant of the Special Research Fund (Grant MulTplex). S.G. and M.V. were supported by an SB fellowship from the FWO (S.G. grant 1S48819N, M.V. grant 1S24517N). E.B. and S.v.d.H. were supported via a clinical investigator fellowship from the Research Foundation-Flanders (FWO, Belgium) of B.O. (grant 1861219N). D.C.D. and H.D.R. were supported by grant G053518N from the FWO.