cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10552666
title: Evaluation of bitumen's fatigue resistance - a comparative study within Weave-UNISONO 2021 project, NCN project No 2021/03/Y/ST8/00079, and GACR project GA22-04047K

description: Summary:

Three asphalt binders were tested, two paving grade bitumens 35/50 and 50/70 and PMB 25/55-60. Basic characteristics were determined for all binders in three stages: original and after short-term and long-term ageing. The short-term ageing was performed using the RTFOT procedure, and the long-term ageing was performed using the PAV method. The shear stress Superpave fatigue tests, long-time-sweep, and LAS were conducted using a Dynamic Shear Rheometer (DSR) with parallel plates of 8 mm in diameter and a gap of 2 mm in a long-term PAV-aged state.

 

 

The dataset includes:

Basic characteristics of bituminous binder (R&B Temperatur, Penetration, Viscosity), CSV raw data:



01 - R&B and Pen.csv

02 - Dynamic Viscosity.csv


FATIGUE parameters:

Superpave fatigue factor G*·sin& after PAV:





03 - DSR PAV Superpave fatigue factor.csv



Fatigue time-sweep test:



04.1 - 35_50_1 DSR PAV fatigue time-sweep test.csv

04.2 - 35_50_2 DSR PAV fatigue time-sweep test.csv

04.3 - 50_70_1 DSR PAV fatigue time-sweep test.csv

04.4 - 50_70_2 DSR PAV fatigue time-sweep test.csv

04.5 - PMB25_55-60_1 DSR PAV fatigue time-sweep test.csv

04.6 - PMB25_55-60_2 DSR PAV fatigue time-sweep test.csv


Linear amplitude sweep (LAS):



05.1 LAS fatigue 35_50.zip

05.2 LAS fatigue 50_70.zip

05.3 LAS fatigue PMB 25_55-60.zip
description: This research was conceptualised and developed as part of activities related to project No. 2021/03/Y/ST8/00079, funded by the Polish National Science Centre (NCN), and project GA22-04047K funded by The Czech Scientific Foundation (GACR), under the Weave-UNISONO 2021. The dataset was used for analyses for the journal paper titled "Evaluation of bitumen's fatigue resistance - a comparative study", which is available on https://doi.org/10.1016/j.trpro.2023.11.206
DOI: 10.6084/m9.figshare.21977834
title: PBL_CyTOF

description: Peripheral blood leukocyte (PBL) CyTOF dataset from healthy controls, ulcerative colitis patients on aminosalicylates, and ulcerative colitis patients on vedolizumab. Normalized fcs files for each patient from PBL samples. CD45+ cells were used for unsupervised analysis using Cyclone pipeline
DOI: 10.6084/m9.figshare.21977834.v1
title: PBL_CyTOF

description: Peripheral blood leukocyte (PBL) CyTOF dataset from healthy controls, ulcerative colitis patients on aminosalicylates, and ulcerative colitis patients on vedolizumab. Normalized fcs files for each patient from PBL samples. CD45+ cells were used for unsupervised analysis using Cyclone pipeline
DOI: 10.6084/m9.figshare.21977798
title: Biopsy_CyTOF

description: CyTOF of colonic biopsies from healthy controls, UC patients on aminosalicylates, and UC patients on Vedolizumab. Normalized fcs files for each patient from biopsy samples. Live cells were used for unsupervised analysis using Cyclone pipeline
DOI: 10.6084/m9.figshare.21977798.v1
title: Biopsy_CyTOF

description: CyTOF of colonic biopsies from healthy controls, UC patients on aminosalicylates, and UC patients on Vedolizumab. Normalized fcs files for each patient from biopsy samples. Live cells were used for unsupervised analysis using Cyclone pipeline
DOI: 10.6084/m9.figshare.23902065
title: PBMC_remission and Biopsy_remission

description: Peripheral blood mononuclear cells (PBMCs) and biopsy CyTOF dataset from healthy controls and ulcerative colitis largely in remission. Normalized fcs files for each patient from PBL and biopsy samples. CyTOF on biopsies was conducted on two separate pools each one containing one location. Pool 1 was run twice (labeled as pool1 and pool1_2).
DOI: 10.6084/m9.figshare.23902065.v1
title: PBMC_remission and Biopsy_remission

description: Peripheral blood mononuclear cells (PBMCs) and biopsy CyTOF dataset from healthy controls and ulcerative colitis largely in remission. Normalized fcs files for each patient from PBL and biopsy samples. CyTOF on biopsies was conducted on two separate pools each one containing one location. Pool 1 was run twice (labeled as pool1 and pool1_2).
DOI: 10.5281/zenodo.10552762
title: Data for sensitivity analysis of Hübler, M., M. Wiese, M. Braun and J. Damster (2023): The distributional effects of CO2 pricing at home and at the border on German income groups

description: This dataset contains the output files used in the sensitivity analysis of the computable general equilibrium (CGE) model developed in Hübler et al. (2023). Each folder is labeled with the respective set of sector-level elasticity of substitution parameters considered in the analysis: elasticities between domestically produced versus imported goods (esubd), Armington elasticities (esubm) and elasticities between production factors (esubva).

For each set of parameters, we generate 1000 random draws from a +-10 % interval around each of the sector-specific elasticities, resulting in 1000 sets of sectoral parameter values. Each .xlsx output file located in a dedicated subfolder corresponds to a model run with a specific set of parameter values. In addition, we conduct sensitivity analyses of two individual parameters, namely the CO2 target (CO2factor) considered in our policy scenarios and the elasticity of substitution in consumption (esub_cons).

The sensitivity analysis is carried out using the Snakeflow workflow management system, and R code for generating parameter spaces and processing the output files is available on GitHub.
DOI: 10.5281/zenodo.8304636
title: Data for sensitivity analysis of Hübler, M., M. Wiese, M. Braun and J. Damster (2023): The distributional effects of CO2 pricing at home and at the border on German income groups

description: This dataset contains the output files used in the sensitivity analysis of the computable general equilibrium (CGE) model developed in Hübler et al. (2023). Each folder is labeled with the respective set of sector-level elasticity of substitution parameters considered in the analysis: elasticities between domestically produced versus imported goods (esubd), Armington elasticities (esubm) and elasticities between production factors (esubva).

For each set of parameters, we generate 1000 random draws from a +-10 % interval around each of the sector-specific elasticities, resulting in 1000 sets of sectoral parameter values. Each .xlsx output file located in a dedicated subfolder corresponds to a model run with a specific set of parameter values. In addition, we conduct sensitivity analyses of two individual parameters, namely the CO2 target (CO2factor) considered in our policy scenarios and the elasticity of substitution in consumption (esub_cons).

The sensitivity analysis is carried out using the Snakeflow workflow management system, and R code for generating parameter spaces and processing the output files is available on GitHub.
DOI: 10.5281/zenodo.8304637
title: Data for sensitivity analysis of Hübler, M., M. Wiese, M. Braun and J. Damster (2022): The distributional effects of CO2 pricing at home and at the border on German income groups

description: This dataset contains the output files used in the sensitivity analysis of the computable general equilibrium (CGE) model developed in Hübler et al. (2022). Each folder is labeled with the respective set of sector-level elasticity of substitution parameters considered in the analysis: elasticities between domestically produced versus imported goods (esubd), Armington elasticities (esubm) and elasticities between production factors (esubva). For each set of parameters, we generate 1000 random draws from a +-10 % interval around each of the sector-specific elasticities, resulting in 1000 sets of sectoral parameter values. Each .xlsx output file located in a dedicated subfolder corresponds to a model run with a specific set of parameter values. The sensitivity analysis is carried out using the Snakeflow workflow management system, and R code for generating parameter spaces and processing the output files is available on GitHub.
description: {"references": ["H\u00fcbler, M., M. Wiese, M. Braun and J. Damster (2022), The distributional effects of CO2 pricing at home and at the border on German income groups. Available at SSRN: http://dx.doi.org/10.2139/ssrn.4432033"]}
DOI: 10.18112/openneuro.ds004798.v1.0.3
title: Multimodal brain responses during movie watching: single-neuron, intracranial EEG, and fMRI in human patients
DOI: 10.48577/jpl.5enorp
title: Enabling Space Exploration by Autonomous Smart Microwave Radiometers Onboard Small Satellites

description: Enabling Space Exploration by Autonomous Smart Microwave Radiometers Onboard Small Satellites
DOI: 10.57967/hf/1670
title: Feature_Extractor
DOI: 10.5281/zenodo.10552662
title: Mouse RNASeq data for "An explainable graph neural framework to identify cancer-associated intratumoral microbial communities"

description: These data are RNA sequencing FASTQs for mouse tumor samples. A total of 22 C57BL/6J mice were administered an antibiotic cocktail in their drinking water for five days to deplete the resident microbiome, followed by two days of regular water. This cycle was repeated three times in succession, first with a low-absorption cocktail (ertapenem (1 mg/mL; Merck and Co., Inc., Whitehouse Station, NJ, USA) Neomycin (1 mg/mL; Fagron, Inc.), and Vancomycin (1 mg/mL; Mylan Institutional LLC, Rockford, IL, USA)), then a high-absorption cocktail (ampicillin (1mg/mL; Sandoz, Inc., Austria), cefoperazone (1 mg/mL; Thermo scientific, USA), and clindamycin (1 mg/mL; Major Pharmaceuticals, Inc., NJ, USA)), followed by the low-absorption cocktail a second time. Three days before the end of the antibiotic course, 1e6 mc38 cells were injected subcutaneously in the right flank. Following the antibiotic course, mice were gavaged with 200 uL stool slurry (1g healthy donor stool in 5 mL de-gassed phosphate-buffered saline) with (n=10) or without (n=12) 1e7 CFU B. massiliensis strain FDAARGOS three days after cancer cell injection. Ten days after the start of tumor growth, mice were treated with either 5mg/kg anti-PD1 Ab (clone RMP1-14; BioXCell, USA) or isotype control (IgG) (clone 2A3, BioXCell, USA). The experiment was ended 21 days after mc38 injection. To evaluate the presence of microbes in tumors, the tumor samples were sterilely dissected upon euthanization.  RNA was purified using an AllPrep kit (QIAGEN) following the manufacturer’s instructions, with the addition of a bead-beating lysis step. Specifically, tumors were minced by scalpel and then beaten in lysis buffer with 100 mg ceramic beads at 2000 rpm for two minutes on a Powerlyzer 24 (QIAGEN). Human and mouse RNA was depleted using a KAPA RNA Hyperprep kit (Roche). Samples were sequenced 2x150nt on a NextSeq 2000 to a depth of 50M reads.
DOI: 10.5281/zenodo.10552663
title: Mouse RNASeq data for "An explainable graph neural framework to identify cancer-associated intratumoral microbial communities"

description: These data are RNA sequencing FASTQs for mouse tumor samples. A total of 22 C57BL/6J mice were administered an antibiotic cocktail in their drinking water for five days to deplete the resident microbiome, followed by two days of regular water. This cycle was repeated three times in succession, first with a low-absorption cocktail (ertapenem (1 mg/mL; Merck and Co., Inc., Whitehouse Station, NJ, USA) Neomycin (1 mg/mL; Fagron, Inc.), and Vancomycin (1 mg/mL; Mylan Institutional LLC, Rockford, IL, USA)), then a high-absorption cocktail (ampicillin (1mg/mL; Sandoz, Inc., Austria), cefoperazone (1 mg/mL; Thermo scientific, USA), and clindamycin (1 mg/mL; Major Pharmaceuticals, Inc., NJ, USA)), followed by the low-absorption cocktail a second time. Three days before the end of the antibiotic course, 1e6 mc38 cells were injected subcutaneously in the right flank. Following the antibiotic course, mice were gavaged with 200 uL stool slurry (1g healthy donor stool in 5 mL de-gassed phosphate-buffered saline) with (n=10) or without (n=12) 1e7 CFU B. massiliensis strain FDAARGOS three days after cancer cell injection. Ten days after the start of tumor growth, mice were treated with either 5mg/kg anti-PD1 Ab (clone RMP1-14; BioXCell, USA) or isotype control (IgG) (clone 2A3, BioXCell, USA). The experiment was ended 21 days after mc38 injection. To evaluate the presence of microbes in tumors, the tumor samples were sterilely dissected upon euthanization.  RNA was purified using an AllPrep kit (QIAGEN) following the manufacturer’s instructions, with the addition of a bead-beating lysis step. Specifically, tumors were minced by scalpel and then beaten in lysis buffer with 100 mg ceramic beads at 2000 rpm for two minutes on a Powerlyzer 24 (QIAGEN). Human and mouse RNA was depleted using a KAPA RNA Hyperprep kit (Roche). Samples were sequenced 2x150nt on a NextSeq 2000 to a depth of 50M reads.
DOI: 10.5281/zenodo.10552787
title: Strategies for achieving net-zero greenhouse gas emissions in the EU: impacts of technology availability, sector policies and behavioral change

description: This package contains the data and plot routines used in preparation for the paper "Strategies for achieving net-zero greenhouse gas emissions in the EU: impacts of technology availability, sector policies and behavioral change" by Jessica Strefler et al.
description: The research leading to these results has received funding from the German Federal Ministry of Education and Research (BMBF, grant number 01LA1809A, DIPOL project). This work was supported by the European Union’s Horizon 2020 research and innovation program under grant number 821124561 (NAVIGATE project) and by the BMBF under grant number 03SFK5A (ARIADNE project).
DOI: 10.5281/zenodo.10552788
title: Strategies for achieving net-zero greenhouse gas emissions in the EU: impacts of technology availability, sector policies and behavioral change

description: This package contains the data and plot routines used in preparation for the paper "Strategies for achieving net-zero greenhouse gas emissions in the EU: impacts of technology availability, sector policies and behavioral change" by Jessica Strefler et al.
description: The research leading to these results has received funding from the German Federal Ministry of Education and Research (BMBF, grant number 01LA1809A, DIPOL project). This work was supported by the European Union’s Horizon 2020 research and innovation program under grant number 821124561 (NAVIGATE project) and by the BMBF under grant number 03SFK5A (ARIADNE project).
DOI: 10.5517/ccdc.csd.cc2d3cb7
title: CCDC 2207768: Experimental Crystal Structure Determination

description: Related Article: Xuze Pan, Xuezhen Si, Xiaoying Zhang, Qingxia Yao, Yunwu Li, Wenzeng Duan, Yi Qiu, Jie Su, Xianqiang Huang|2023|Dalton Trans.|52|3896|doi:10.1039/D2DT03158B
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.cc2g5g8d
title: CCDC 2269363: Experimental Crystal Structure Determination

description: Related Article: Jun-hao Shi, Hong-lei Xia, Si-wei Song, Si-tong Chen, Zi-wu Cai, Yu-teng Cao, Wen-quan Zhang|2023|Energetic Materials Frontiers|4|194|doi:10.1016/j.enmf.2023.08.002
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.cc2g6xwh
title: CCDC 2270777: Experimental Crystal Structure Determination

description: Related Article: Jun-hao Shi, Hong-lei Xia, Si-wei Song, Si-tong Chen, Zi-wu Cai, Yu-teng Cao, Wen-quan Zhang|2023|Energetic Materials Frontiers|4|194|doi:10.1016/j.enmf.2023.08.002
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.cc2g8bvy
title: CCDC 2272140: Experimental Crystal Structure Determination

description: Related Article: Xin‐Ming Xu, Sen Chen, Wenzhong Li, Xuesi Zhang, Zhongyuan Zhao, Xinyue Cao, Yuhang Yao, Xiangmin Wang, Zu‐Li Wang|2024|Adv.Synth.Catal.|366|36|doi:10.1002/adsc.202300908
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.cc1kkmyp
title: CCDC 1446923: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
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.cc2g33b1
title: CCDC 2267102: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
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.cc2c64sj
title: CCDC 2180657: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
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.cc2g33c2
title: CCDC 2267103: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
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.cc2ghbht
title: CCDC 2278856: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
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.cc2ghbjv
title: CCDC 2278857: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
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.24570049
title: ICESat-2 Bathymetry Retrievability Index

description: GeoTiff Files for ICESat-2 Retrievability Index datasets from the publication:<br><br>Dietrich J, Reese ARR, Gibbons A, Magruder LA, Parrish C. 2023. Analysis of ICESat-2 Data Acquisition Algorithm Parameter Enhancements to Improve Worldwide Bathymetric Coverage. ESS Open Archive (Preprint) DOI: 10.22541/essoar.169447414.45310708/v1All data are based on VIIRS KD490 Monthly Climatologies:NASA OB.DAAC. 2022. Visible and Infrared Imager/Radiometer Suite (VIIRS) Level-3 Mapped Downwelling Diffuse Attenuation Coefficient, Version 2022. DOI: 10.5067/NOAA-20/VIIRS/L3M/KD/2022File List:IS2_Retreivability_01_ETOPO - <i>ETOPO2022 30-arcsec raster from 1 to -41 m depth</i>IS2_Retreivability_02_Monthly_SecchiDepth_Jan_JunIS2_Retreivability_02_Monthly_SecchiDepth_Jul_Dec<br><i>- Monthly Secchi Depths Calculated for 532 nm, KD490 converted to KD532 &gt; Secchi Depth (See Linked Article)</i>IS2_Retreivability_03_ICESat2_RetreivabilityIndex<br><i>- </i><i>Final ICESAt-2 Bathymetric Retrievability Index Raster, </i><i>12-month average - number of visible months (0-12). Included are 1.25 Secchi depths (used in the paper), 1.1 Secchi depths, and 1.0 Secchi Depths</i><br>
DOI: 10.6084/m9.figshare.24570049.v2
title: ICESat-2 Retrievability Index

description: GeoTiff Files for ICESat-2 Retrievability Index datasets from the publication:<br><br>Dietrich J, Reese ARR, Gibbons A, Magruder LA, Parrish C. 2023. Analysis of ICESat-2 Data Acquisition Algorithm Parameter Enhancements to Improve Worldwide Bathymetric Coverage. ESS Open Archive (Preprint) DOI: 10.22541/essoar.169447414.45310708/v1All data are based on VIIRS KD490 Monthly Climatologies:NASA OB.DAAC. 2022. Visible and Infrared Imager/Radiometer Suite (VIIRS) Level-3 Mapped Downwelling Diffuse Attenuation Coefficient, Version 2022. DOI: 10.5067/NOAA-20/VIIRS/L3M/KD/2022File List:IS2_Retreivability_01_ETOPO - <i>ETOPO2022 30-arcsec raster from 1 to -41 m depth</i>IS2_Retreivability_02_Monthly_SecchiDepth_Jan_JunIS2_Retreivability_02_Monthly_SecchiDepth_Jul_Dec<br><i>- Monthly Secchi Depths Calculated for 532 nm, KD490 converted to KD532 &gt; Secchi Depth (See Linked Article)</i>IS2_Retreivability_03_ICESat2_RetreivabilityIndex<br><i>- </i><i>Final ICESAt-2 Bathymetric Retrievability Index Raster, </i><i>12-month average - number of visible months (0-12). Included are 1.25 Secchi depths (used in the paper), 1.1 Secchi depths, and 1.0 Secchi Depths</i><br>
DOI: 10.21227/ew8v-dk57
title: IEEEXtreme 11: Math Challenge

description: This dataset contains a total of 9045 submissions, with 1% correct solutions and 57% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/7df0da0b0477307be410f4772c739528/ See the included PDF document for details about the original challenge.