cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21332750.v1
title: Additional file 2 of Molecular insights into the heat shock proteins of the human parasitic blood fluke Schistosoma mansoni

description: Additional file 2: Dataset S2. Expression of HSP genes in different developmental stages of Schistosoma mansoni. Data are presented as raw normalised gene expression and as percentages of the highest gene expression value.
DOI: 10.6084/m9.figshare.21332753
title: Additional file 3 of Molecular insights into the heat shock proteins of the human parasitic blood fluke Schistosoma mansoni

description: Additional file 3: Dataset S3. Putative protein-protein interactions (nodes) for HSP family members. Six tabs are included, one for each HSP family and one for all HSP families combined.
DOI: 10.6084/m9.figshare.21332753.v1
title: Additional file 3 of Molecular insights into the heat shock proteins of the human parasitic blood fluke Schistosoma mansoni

description: Additional file 3: Dataset S3. Putative protein-protein interactions (nodes) for HSP family members. Six tabs are included, one for each HSP family and one for all HSP families combined.
DOI: 10.6084/m9.figshare.21332759
title: Additional file 5 of Molecular insights into the heat shock proteins of the human parasitic blood fluke Schistosoma mansoni

description: Additional file 5: Dataset S4. Phosphorylation sites within Schistosoma mansoni HSPs, mined from the S. mansoni phosphoprotein dataset, and motifs identified with HPRD and PHOSIDA. Six tabs are included, representing (i) the identified phosphorylation sites; (ii) sequence (+/− six amino acids) surrounding the phosphorylation site; and (iii–vi) motifs identified within HSPs 40, 60, 70, and 90.
DOI: 10.6084/m9.figshare.21332759.v1
title: Additional file 5 of Molecular insights into the heat shock proteins of the human parasitic blood fluke Schistosoma mansoni

description: Additional file 5: Dataset S4. Phosphorylation sites within Schistosoma mansoni HSPs, mined from the S. mansoni phosphoprotein dataset, and motifs identified with HPRD and PHOSIDA. Six tabs are included, representing (i) the identified phosphorylation sites; (ii) sequence (+/− six amino acids) surrounding the phosphorylation site; and (iii–vi) motifs identified within HSPs 40, 60, 70, and 90.
DOI: 10.6084/m9.figshare.21332881
title: Additional file 1 of Risk factors of delayed hemorrhage after LigaSure hemorrhoidectomy

description: Supplementary Table 1. Entire study cohort
DOI: 10.6084/m9.figshare.21332881.v1
title: Additional file 1 of Risk factors of delayed hemorrhage after LigaSure hemorrhoidectomy

description: Supplementary Table 1. Entire study cohort
DOI: 10.25934/pr00006051.12
title: Available IPD datapackage for study 'A Phase III, Open-Label, Randomized Study of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody) in Combination With Carboplatin+Paclitaxel With or Without Bevacizumab Compared With Carboplatin + Paclitaxel + Bevacizumab in Chemotherapy-Naïve Patients With Stage IV Non-Squamous Non-Small Cell Lung Cancer'

description: This randomized, open-label study will evaluate the safety and efficacy of atezolizumab (an engineered anti-programmed death-ligand 1 [PD-L1] antibody) in combination with carboplatin+paclitaxel with or without bevacizumab compared with treatment with carboplatin+paclitaxel+bevacizumab in chemotherapy-naïve participants with Stage IV non-squamous NSCLC. Participants will be randomized in a 1:1:1 ratio to Arm A (Atezolizumab+Carboplatin+Paclitaxel), Arm B (Atezolizumab+Carboplatin+Paclitaxel+Bevacizumab), or Arm C (Carboplatin+Paclitaxel+Bevacizumab).
DOI: 10.5281/zenodo.7195936
title: Data set for "Optical multiplexing of metrological time and frequency signals in a single 100 GHz-grid optical channel"

description: Here we share the relevant data of the manuscript “Optical multiplexing of metrological time and frequency signals in a single 100 GHz-grid optical channel”. Files: Opt_Fr_stability_part1.txt Opt_Fr_stability_part2.txt contain the data used for evaluation of optical frequency transfer stability (Fig. 7 in the paper). The measurements were done with 8-channels K+K phase/frequency recorder. Column 1 contains date, col. 2: time, col. 5: in-loop beatnote phase, col. 6: out-of-loop beatnote phase. The phase is recorded in cycles. In case of out-of-loop beatnote it was divided by factor of two before recording, therefore the data from col. 6 should be multiplied by two to obtain true values of the optical phase fluctuations. File: RF_stability.txt contains the data used for evaluation of RF frequency transfer stability (Fig. 8 in the paper). Column 1 contains time in hours, and col. 2 RF phase fluctuations in seconds.
description: This work has been funded by European Union (EU), Horizon 2020, EMPIR, 18SIB06, TiFOON, Advanced time/frequency comparison and dissemination through optical telecommunication networks.
DOI: 10.5281/zenodo.7195935
title: Data set for "Optical multiplexing of metrological time and frequency signals in a single 100 GHz-grid optical channel"

description: Here we share the relevant data of the manuscript “Optical multiplexing of metrological time and frequency signals in a single 100 GHz-grid optical channel”. Files: Opt_Fr_stability_part1.txt Opt_Fr_stability_part2.txt contain the data used for evaluation of optical frequency transfer stability (Fig. 7 in the paper). The measurements were done with 8-channels K+K phase/frequency recorder. Column 1 contains date, col. 2: time, col. 5: in-loop beatnote phase, col. 6: out-of-loop beatnote phase. The phase is recorded in cycles. In case of out-of-loop beatnote it was divided by factor of two before recording, therefore the data from col. 6 should be multiplied by two to obtain true values of the optical phase fluctuations. File: RF_stability.txt contains the data used for evaluation of RF frequency transfer stability (Fig. 8 in the paper). Column 1 contains time in hours, and col. 2 RF phase fluctuations in seconds.
description: This work has been funded by European Union (EU), Horizon 2020, EMPIR, 18SIB06, TiFOON, Advanced time/frequency comparison and dissemination through optical telecommunication networks.
DOI: 10.34740/kaggle/dsv/4325907
title: Ukraine Conflict Twitter Dataset (53.39M tweets)
DOI: 10.5281/zenodo.7193138
title: Data set for "Stability limitations of optical frequency transfer in telecommunication DWDM networks"

description: Here we share the relevant data of the manuscript “Stability limitations of optical frequency transfer in telecommunication DWDM networks”. The files: “fig_2a_total.txt” “fig_2a_diff.txt” contains respectively the timeseries data of phase fluctuations of total delay and differential delay between two fibers in 50 km-long soil-deployed cable. Same results for 110 km-long aerial cable are in files: “fig_2b_total.txt” “fig_2b_diff.txt” The files: “fig_3_aerial_MDEV_points.txt” “fig_3_soil_MDEV_points.txt” contains respectively points of modify Allan deviation of the differential delay fluctuations in 110 km-long aerial and 70 km-long soil-deployed cable. For short averaging the stability is limited by the noise of time interval counter (MTC 108). Before MDEV calculations the differential delay fluctuations was divided by factor of two, as a half of these fluctuations is present at the output of a stabilized system. The files: “fig_4_soil_MDEV_points_CW-total.txt” “fig_4_soil_MDEV_points_CW-diff.txt” contains respectively points of modify Allan deviation of the total and differential delay fluctuations in 70km soil-deployed cable, measured with the unmodulated coherent optical carrier. The files: “fig_7a_EDFA_phase.txt” and “fig_7a_EDFA_temp.txt” “fig_7b_Raman_phase.txt” and “fig_7b_Raman_temp.txt” “fig_7c_ROADM_phase.txt” and “fig_7c_ROADM_temp.txt” contains the timeseries data of simultaneous measurement of phase and temperature changes in individual cards (modules) of the DWDM system: EDFA amplifier, card containing the Raman module, as well as ROADM (Reconfigurable Optical Add Drop Multiplexer) module. Time series data of the fluctuations of the total and differential propagation delay of the signal transfer in the unmodified DWDM system (over 1500 km long route) include files: “fig_9_total_phase_fluct_part1”, “fig_9_total_phase_fluct_part2”, “fig_9_total_phase_fluct_part1” “fig_9_diff_phase_fluct_part1”, “fig_9_diff_phase_fluct_part2”, “fig_9_diff_phase_fluct_part3” The files: “fig_10_mdev_acusticNOISE.txt” “fig_10_mdev_air-conditioning_ON.txt” “fig_10_mdev_air-conditioning_MODIFIED.txt” contains points of modify Allan deviation that shows respectively: the influence of acoustic noise, stability of the frequency transfer in DWDM network in the case of sub-optimal (asymmetric) cooling within a single ILA node, while the last file shows the stability of the transfer after optimizing the airflow within this node.
description: Funding: European Union (EU), Horizon 2020, EMPIR, 18SIB06, TiFOON, Advanced time/frequency comparison and dissemination through optical telecommunication networks
DOI: 10.5281/zenodo.7193139
title: Data set for "Stability limitations of optical frequency transfer in telecommunication DWDM networks"

description: Here we share the relevant data of the manuscript “Stability limitations of optical frequency transfer in telecommunication DWDM networks”. The files: “fig_2a_total.txt” “fig_2a_diff.txt” contains respectively the timeseries data of phase fluctuations of total delay and differential delay between two fibers in 50 km-long soil-deployed cable. Same results for 110 km-long aerial cable are in files: “fig_2b_total.txt” “fig_2b_diff.txt” The files: “fig_3_aerial_MDEV_points.txt” “fig_3_soil_MDEV_points.txt” contains respectively points of modify Allan deviation of the differential delay fluctuations in 110 km-long aerial and 70 km-long soil-deployed cable. For short averaging the stability is limited by the noise of time interval counter (MTC 108). Before MDEV calculations the differential delay fluctuations was divided by factor of two, as a half of these fluctuations is present at the output of a stabilized system. The files: “fig_4_soil_MDEV_points_CW-total.txt” “fig_4_soil_MDEV_points_CW-diff.txt” contains respectively points of modify Allan deviation of the total and differential delay fluctuations in 70km soil-deployed cable, measured with the unmodulated coherent optical carrier. The files: “fig_7a_EDFA_phase.txt” and “fig_7a_EDFA_temp.txt” “fig_7b_Raman_phase.txt” and “fig_7b_Raman_temp.txt” “fig_7c_ROADM_phase.txt” and “fig_7c_ROADM_temp.txt” contains the timeseries data of simultaneous measurement of phase and temperature changes in individual cards (modules) of the DWDM system: EDFA amplifier, card containing the Raman module, as well as ROADM (Reconfigurable Optical Add Drop Multiplexer) module. Time series data of the fluctuations of the total and differential propagation delay of the signal transfer in the unmodified DWDM system (over 1500 km long route) include files: “fig_9_total_phase_fluct_part1”, “fig_9_total_phase_fluct_part2”, “fig_9_total_phase_fluct_part1” “fig_9_diff_phase_fluct_part1”, “fig_9_diff_phase_fluct_part2”, “fig_9_diff_phase_fluct_part3” The files: “fig_10_mdev_acusticNOISE.txt” “fig_10_mdev_air-conditioning_ON.txt” “fig_10_mdev_air-conditioning_MODIFIED.txt” contains points of modify Allan deviation that shows respectively: the influence of acoustic noise, stability of the frequency transfer in DWDM network in the case of sub-optimal (asymmetric) cooling within a single ILA node, while the last file shows the stability of the transfer after optimizing the airflow within this node.
description: Funding: European Union (EU), Horizon 2020, EMPIR, 18SIB06, TiFOON, Advanced time/frequency comparison and dissemination through optical telecommunication networks
DOI: 10.48425/0027333
title: V_heath_vascular_plant_abundance_experimental

description: Vascular plant abundance in herbivore exclosures and control plots in heath sites. The dataset includes three different types of files and all files (except the readme) are saved as ;-separated txt-files: * One data file per year (_YEAR.txt) * One coordinate file with coordinates of all sites included in the dataset (_coordinates.txt) * One auxiliary file with information about which sites are included in the dataset and when (_aux.txt) * One readme file with additional information about the variables included in the study design (_readme.pdf) The data is not publicly available yet.
DOI: 10.5281/zenodo.7197222
title: Forecast of the competitiveness of EU regions in the conditions of climate change

description: The database contains forecasts of the values of climate change competitiveness (Regional Climate Change Competitiveness Index) of EU regions (NUTS2) and countries. The calculations were made for the period 2022-2032 and for period 2022-2100 using the ARIMA method. The Regional Climate Change Competitiveness Index is a mean to evaluate the ability of a region to use factors of competitiveness for the formation of a competitive position of the region under climate change conditions.The structure of the index stems from the premise that it constitutes a function of pillars that can be grouped into six broad sub-indexes: Basic, Natural, Efficiency, Innovation, Sectoral, and Social.Twenty-eight pillars were used in order to determine the main index. The higher the value of Regional Climate Change Competitiveness Index, the higher the level of regional competitiveness. For detailed methodology see: Karman, A.; Miszczuk, A.; Bronisz, U. Regional Climate Change Competitiveness—Modelling Approach. Energies 2021, 14, 3704. https://doi.org/10.3390/en14123704. The forecast can be used by regional authorities to model regional policy (policy-mix, tools, measures) against the climate change. Funding: National Science Centre Poland, „Modelling of climate change impacts on regional competitiveness” 2019/35/B/HS5/01548
description: Funding: National Science Centre Poland, "Modelling of climate change impacts on regional competitiveness" 2019/35/B/HS5/01548
DOI: 10.5281/zenodo.7197221
title: Forecast of the competitiveness of EU regions in the conditions of climate change

description: The database contains forecasts of the values of climate change competitiveness (Regional Climate Change Competitiveness Index) of EU regions (NUTS2) and countries. The calculations were made for the period 2022-2032 and for period 2022-2100 using the ARIMA method. The Regional Climate Change Competitiveness Index is a mean to evaluate the ability of a region to use factors of competitiveness for the formation of a competitive position of the region under climate change conditions.The structure of the index stems from the premise that it constitutes a function of pillars that can be grouped into six broad sub-indexes: Basic, Natural, Efficiency, Innovation, Sectoral, and Social.Twenty-eight pillars were used in order to determine the main index. The higher the value of Regional Climate Change Competitiveness Index, the higher the level of regional competitiveness. For detailed methodology see: Karman, A.; Miszczuk, A.; Bronisz, U. Regional Climate Change Competitiveness—Modelling Approach. Energies 2021, 14, 3704. https://doi.org/10.3390/en14123704. The forecast can be used by regional authorities to model regional policy (policy-mix, tools, measures) against the climate change. Funding: National Science Centre Poland, „Modelling of climate change impacts on regional competitiveness” 2019/35/B/HS5/01548
description: Funding: National Science Centre Poland, "Modelling of climate change impacts on regional competitiveness" 2019/35/B/HS5/01548
DOI: 10.5281/zenodo.7197136
title: NMR titration experiments that study binding of a NIR emitting osmium polypyridyl probe to cMYC and hTel G-quadruplex DNA

description: 1D and 2D NMR spectra of cMYC and hTel G-quadruplex DNA and their complexes with Λ-<strong> </strong>and Δ<strong>-</strong>enantiomers of the osmium polypyridyl probe [Os(TAP)<sub>2</sub>(dppz)]<sup>2+</sup>. Spectra were recorded on a 600 MHz NMR spectrometer with 70 mM KCl, 20 or 25 mM K-phosphate buffer, pH 7, 298 K, in 90% H<sub>2</sub>O and 10% D<sub>2</sub>O at 25 °C.
DOI: 10.5281/zenodo.7197135
title: NMR titration experiments that study binding of a NIR emitting osmium polypyridyl probe to cMYC and hTel G-quadruplex DNA

description: 1D and 2D NMR spectra of cMYC and hTel G-quadruplex DNA and their complexes with Λ-<strong> </strong>and Δ<strong>-</strong>enantiomers of the osmium polypyridyl probe [Os(TAP)<sub>2</sub>(dppz)]<sup>2+</sup>. Spectra were recorded on a 600 MHz NMR spectrometer with 70 mM KCl, 20 or 25 mM K-phosphate buffer, pH 7, 298 K, in 90% H<sub>2</sub>O and 10% D<sub>2</sub>O at 25 °C.
DOI: 10.6084/m9.figshare.19679367
title: Meta-data

description: Mate-data
DOI: 10.48425/o0p6gvhp
title: protocol_plant_measurements_heath_and_meadow_varanger

description: Protocol for plant measurements (point intercept frequency, species composition and shrub height) in heath and meadow sites on the Varanger peninsula. The following datasets are based on this protocol: * V_meadow_vascular_plant_abundance_observational * V_heath_vascular_plant_abundance_observational * V_meadow_plant_species_composition_observational * V_heath_plant_species_composition_observational * V_meadow_ground_cover_observational * V_heath_ground_cover_observational * V_tall_shrub_shrub_height_observational * V_heath_shrub_height_observational * V_meadow_vascular_plant_abundance_experimental * V_heath_vascular_plant_abundance_experimental * V_meadow_plant_species_composition_experimental * V_heath_plant_species_composition_experimental * V_meadow_ground_cover_experimental * V_heath_ground_cover_experimental * V_tall_shrub_shrub_height_experimental * V_heath_shrub_height_experimental
DOI: 10.5281/zenodo.7158404
title: Data and code for: Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent

description: Code and data to reproduce figures in manuscript entitled "Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent" published in Hydrology and Earth System Sciences (https://hess.copernicus.org/preprints/hess-2022-136/). The contents include three folders, "Codes", "Data", and "Figures". In "Codes" folder, R scripts are listed in the order needed to reproduce the figures. All code is written in R version 4.2.0. Data sets needed to reproduce figures are provided in "Data" folder (Rdata format). The pdf files in "Figures" folder are outputs generated from the corresponding R scripts. Note that final figures in the article were produced by combining multiple figures using a vector graphics software (Inkscape) or PowerPoint. Please contact Eunsang Cho (eunsang.cho@nasa.gov) with any questions. Preferred citation: Cho, E., Vuyovich, C. M., Kumar, S. V., Wrzesien, M. L., Kim, R. S., and Jacobs, J. M. (2022). Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent, Hydrol. Earth Syst. Sci., https://doi.org/10.5194/hess-2022-136. Corresponding author: Eunsang Cho (eunsang.cho@nasa.gov; escho@umd.edu)
description: This work has been supported by the NASA Terrestrial Hydrology Program (NNH16ZDA001N)
description: {"references": ["Cho, E., Vuyovich, C. M., Kumar, S. V., Wrzesien, M. L., Kim, R. S., and Jacobs, J. M. (2022). Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent, Hydrol. Earth Syst. Sci., https://doi.org/10.5194/hess-2022-136"]}
DOI: 10.5281/zenodo.7158403
title: Data and code for: Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent

description: Code and data to reproduce figures in manuscript entitled "Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent" published in Hydrology and Earth System Sciences (https://hess.copernicus.org/preprints/hess-2022-136/). The contents include three folders, "Codes", "Data", and "Figures". In "Codes" folder, R scripts are listed in the order needed to reproduce the figures. All code is written in R version 4.2.0. Data sets needed to reproduce figures are provided in "Data" folder (Rdata format). The pdf files in "Figures" folder are outputs generated from the corresponding R scripts. Note that final figures in the article were produced by combining multiple figures using a vector graphics software (Inkscape) or PowerPoint. Please contact Eunsang Cho (eunsang.cho@nasa.gov) with any questions. Preferred citation: Cho, E., Vuyovich, C. M., Kumar, S. V., Wrzesien, M. L., Kim, R. S., and Jacobs, J. M. (2022). Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent, Hydrol. Earth Syst. Sci., https://doi.org/10.5194/hess-2022-136. Corresponding author: Eunsang Cho (eunsang.cho@nasa.gov; escho@umd.edu)
description: This work has been supported by the NASA Terrestrial Hydrology Program (NNH16ZDA001N)
description: {"references": ["Cho, E., Vuyovich, C. M., Kumar, S. V., Wrzesien, M. L., Kim, R. S., and Jacobs, J. M. (2022). Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent, Hydrol. Earth Syst. Sci., https://doi.org/10.5194/hess-2022-136"]}
DOI: 10.5517/ccdc.csd.cc2bxpcb
title: CCDC 2172522: Experimental Crystal Structure Determination

description: Related Article: Girbide Amitkumar Ramakant, Naushad Ahmed, Ibtesham Tarannum, Sakshi Mehta, Muneshwar Nandeshwar, Abhishake Mondal, Saurabh Kumar Singh, Ganesan Prabusankar|2022|Cryst.Growth Des.|22|6046|doi:10.1021/acs.cgd.2c00674
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.cc2bxpdc
title: CCDC 2172523: Experimental Crystal Structure Determination

description: Related Article: Girbide Amitkumar Ramakant, Naushad Ahmed, Ibtesham Tarannum, Sakshi Mehta, Muneshwar Nandeshwar, Abhishake Mondal, Saurabh Kumar Singh, Ganesan Prabusankar|2022|Cryst.Growth Des.|22|6046|doi:10.1021/acs.cgd.2c00674
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.cc2bxpfd
title: CCDC 2172524: Experimental Crystal Structure Determination

description: Related Article: Girbide Amitkumar Ramakant, Naushad Ahmed, Ibtesham Tarannum, Sakshi Mehta, Muneshwar Nandeshwar, Abhishake Mondal, Saurabh Kumar Singh, Ganesan Prabusankar|2022|Cryst.Growth Des.|22|6046|doi:10.1021/acs.cgd.2c00674
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.cc2c4b51
title: CCDC 2178902: Experimental Crystal Structure Determination

description: Related Article: Kazuki Komatsubara, Yusuke Inagaki, Wataru Setaka|2022|J.Org.Chem.|87|12783|doi:10.1021/acs.joc.2c01398
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.