cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8108894
title: Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"

description: Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (https://doi.org/10.1016/j.ymben.2022.03.013). In line with the standards of open science, the ARBRE toolbox is freely available to the scientific community on gitHub (https://github.com/EPFL-LCSB/ARBRE) and we also provide the web-version at http://lcsb-databases.epfl.ch/arbre/ ARBRE: Aromatic compounds RetroBiosynthesis Repository and Explorer is a new computational resource consisting of a comprehensive biochemical reaction network centered around aromatic amino acid biosynthesis and a computational toolbox for navigating this network. ARBRE encompasses over 33′000 known and 390′000 novel reactions predicted with generalized enzymatic reactions rules and over 74′000 compounds, of which 19′000 are known to biochemical databases and 55′000 only to PubChem. Over 1′000 molecules that were solely part of the PubChem database before and were previously impossible to integrate into a biochemical network are included in the ARBRE reaction network by assigning enzymatic reactions. ARBRE can be applied for pathway search, enzyme annotation, pathway ranking, visualization, and network expansion around known biochemical pathways and products of lignin degradation to predict valuable compound derivations. Supplementary files are organized as follows: - 1-s2.0-S1096717622000490-mmc4.docx contains Supplementary Figures 1-4 and Tables 1, 2, and 4. - 1-s2.0-S1096717622000490-mmc2.xlsx contains Supplementary Table 3. - 1-s2.0-S1096717622000490-mmc1.xlsx contains Supplementary Table 5 - 1-s2.0-S1096717622000490-mmc3.xlsx contains Supplementary Table 6
DOI: 10.5281/zenodo.8108895
title: Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"

description: Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (https://doi.org/10.1016/j.ymben.2022.03.013). In line with the standards of open science, the ARBRE toolbox is freely available to the scientific community on gitHub (https://github.com/EPFL-LCSB/ARBRE) and we also provide the web-version at http://lcsb-databases.epfl.ch/arbre/ ARBRE: Aromatic compounds RetroBiosynthesis Repository and Explorer is a new computational resource consisting of a comprehensive biochemical reaction network centered around aromatic amino acid biosynthesis and a computational toolbox for navigating this network. ARBRE encompasses over 33′000 known and 390′000 novel reactions predicted with generalized enzymatic reactions rules and over 74′000 compounds, of which 19′000 are known to biochemical databases and 55′000 only to PubChem. Over 1′000 molecules that were solely part of the PubChem database before and were previously impossible to integrate into a biochemical network are included in the ARBRE reaction network by assigning enzymatic reactions. ARBRE can be applied for pathway search, enzyme annotation, pathway ranking, visualization, and network expansion around known biochemical pathways and products of lignin degradation to predict valuable compound derivations. Supplementary files are organized as follows: - 1-s2.0-S1096717622000490-mmc4.docx contains Supplementary Figures 1-4 and Tables 1, 2, and 4. - 1-s2.0-S1096717622000490-mmc2.xlsx contains Supplementary Table 3. - 1-s2.0-S1096717622000490-mmc1.xlsx contains Supplementary Table 5 - 1-s2.0-S1096717622000490-mmc3.xlsx contains Supplementary Table 6
DOI: 10.6084/m9.figshare.23623077.v1
title: Supplementary data

description: Datasets used to test the performance of the platform in the manuscript.
DOI: 10.5281/zenodo.8112774
title: EGMP 2023 Offtake Assessment for the Svalbard Population of Pink-footed Goose

description: Data and model files for the 2023 EGMP offtake assessment of the Svalbard Population of Pink-footed Goose. https://gitlab.com/aewa-egmp/svalbard-population-of-pink-footed-goose/harvest-assessment-2023
description: {"references": ["Jensen, G.H., Johnson, F.A., Baveco, H., Koffijberg, K., Goedhart, P.W. and Madsen, J. (2023) Population Status and Assessment Report 2023. EGMP Technical Report No. 21 Bonn, Germany"]}
DOI: 10.5281/zenodo.8112773
title: EGMP 2023 Offtake Assessment for the Svalbard Population of Pink-footed Goose

description: Data and model files for the 2023 EGMP offtake assessment of the Svalbard Population of Pink-footed Goose. https://gitlab.com/aewa-egmp/svalbard-population-of-pink-footed-goose/harvest-assessment-2023
description: {"references": ["Jensen, G.H., Johnson, F.A., Baveco, H., Koffijberg, K., Goedhart, P.W. and Madsen, J. (2023) Population Status and Assessment Report 2023. EGMP Technical Report No. 21 Bonn, Germany"]}
DOI: 10.6084/m9.figshare.23608158
title: Sequencing data from the second sampling campaign of: "Validation of eDNA-based method for fish and crustaceous communities inventories in French West Indies’ rivers."

description: Run: Compressed file containing: Forward and Reverse sequence files obtained using fish (teleo, Valentini et al. 2016) and crustaceans primers (MiCrust, Komai et al., 2019) Metadata: A table with 1)Library name, 2)Sampling site, 3)PCR sample name, 4)Tag, 5)Forward primer, 6)Reverse primer
DOI: 10.6084/m9.figshare.23608158.v1
title: Sequencing data from the second sampling campaign of: "Validation of eDNA-based method for fish and crustaceous communities inventories in French West Indies’ rivers."

description: Run: Compressed file containing: Forward and Reverse sequence files obtained using fish (teleo, Valentini et al. 2016) and crustaceans primers (MiCrust, Komai et al., 2019) Metadata: A table with 1)Library name, 2)Sampling site, 3)PCR sample name, 4)Tag, 5)Forward primer, 6)Reverse primer
DOI: 10.7910/dvn/ldvae3
title: Replication Data for: Drivers of Political Participation: The Role of Partisanship, Identity and Incentives in Mobilizing Zambian Citizens

description: This dataset provides all the variables needed to replicate the results in the journal article "Drivers of Political Participation: The Role of Partisanship, Identity and Incentives in Mobilizing Zambian Citizens", published in Comparative Political Studies. The dataset contains variables from the Zambian Election Panel Study (ZEPS), including data from a survey experiment on ethnicity, partisanship and political participation around the 2021 general elections. The data was merged with data on party strongholds in the 2016 and 2021 general elections from the Electoral Commission in Zambia.
DOI: 10.5281/zenodo.8112860
title: EGMP 2023 Offtake Assessment for Finland and NW Russia / Sweden, Denmark and Germany population of Taiga Bean Goose (former Central MU)

description: Data and model files for the 2023 EGMP offtake assessment for Finland and NW Russia / Sweden, Denmark and Germany population of Taiga Bean Goose (former Central MU). https://gitlab.com/aewa-egmp/taiga-bean-goose/harvest-assessment-2023
description: {"references": ["Jensen, G.H., Johnson, F.A., Baveco, H., Koffijberg, K., Goedhart, P.W. and Madsen, J. (2023) Population Status and Assessment Report 2023. EGMP Technical Report No. 21 Bonn, Germany"]}
DOI: 10.5281/zenodo.8112859
title: EGMP 2023 Offtake Assessment for Finland and NW Russia / Sweden, Denmark and Germany population of Taiga Bean Goose (former Central MU)

description: Data and model files for the 2023 EGMP offtake assessment for Finland and NW Russia / Sweden, Denmark and Germany population of Taiga Bean Goose (former Central MU). https://gitlab.com/aewa-egmp/taiga-bean-goose/harvest-assessment-2023
description: {"references": ["Jensen, G.H., Johnson, F.A., Baveco, H., Koffijberg, K., Goedhart, P.W. and Madsen, J. (2023) Population Status and Assessment Report 2023. EGMP Technical Report No. 21 Bonn, Germany"]}
DOI: 10.17031/64a3efa3c86be
title: North Pacific CPR data for PLET from 2001 to 2022

description: CPR monthly abundance counts and Phytoplankton Colour within the North Pacific from 2001 to 2022. The Continuous Plankton Recorder (CPR) is a marine sampler that is towed behind volunteer ships of opportunity at speeds of up to ∼20 knots and samples at a depth of ∼7 m below the surface. The CPR unit is a metal casing in the shape of a ∼1 m torpedo that houses a roll of silk which automatically rotates using a geared propeller system. The seawater enters the front aperture where plankton and small particles are captured onto the rotating silk, which has a mesh size of 270 µm. This silk is stored in 4 % buffered formalin to preserve the sample until microscopic analysis at the laboratory in Plymouth. The silk is cut into pre-defined sections that represent one sample and equate to 10 nautical miles of tow. Phytoplankton and zooplankton are identified and counted at different stages of the microscopic analysis: semi-quantitative count of phytoplankton across 20 fields of view per sample, quantitative count of all zooplankton >= 2 mm (these are picked off the silk for identification), and semi-quantitative traverse count of all zooplankton 2 mm. For a more in-depth description of the sampling methodology please refer to Richardson et al. (2006). Ostle, C., et al. This paper describes how the lifeform tool works: The Plankton Lifeform Extraction Tool: A digital tool to increase the discoverability and usability of plankton time-series data, Earth Syst. Sci. Data Discuss. https://doi.org/10.5194/essd-2021-171, 2021. The Phytoplankton Colour Index is a record of the colour gradient of the mesh as one of 4 colour categories (0,1,2,6.5) and has been shown to relate to the chlorophyll content of the water, including organisms not visible in the sample (Raitsos et al., 2013, Raitsos, D.E., Walne, A., Lavender, S.J., Licandro, P., Reid, P.C., and Edwards, M. 2013. A 60-year ocean colour data set from the Continuous Plankton Recorder. Journal of Plankton Research, 35(1): 158–164). NOTE: Only selected taxa have been included in this data extract, for specific taxa requirements please email claost@mba.ac.uk.
DOI: 10.22024/unikent/01.01.487
title: John Hartigan, '3 Perspectives on fables; theoretical, ethnographic, and novelistic' (chair: Lisa Jean Moore)

description: The keynote speech for the first workshop for the AHRC-funded networking project, 'Rethinking fables in the Age of Global Environmental Crisis', led by Dr. Kaori Nagai (University of Kent).
DOI: 10.5523/bris.3pr5xcknxlt8h21sibqmnc73s1
title: Cognitive Development A Novel Approach

description: Data and analysis associated with Jarrold, Li, & Wang, "A Novel Approach to Measuring the Developmental Interactions Between Working Memory and Inhibitory Control in Young Children", Cognitive Development
DOI: 10.5281/zenodo.7003916
title: The role of the intraspecific variability of hydraulic traits for modelling the plant water use in different European forest ecosystems: scripts, model output, and parameter files

description: This repository contains the model outputs and R scripts used to process the data to analyze the impact of the plant hydraulic parameterization of the manuscript: "The role of the intraspecific variability of hydraulic traits for modelling the plant water use in different European forest ecosystems". The following is a detailed description of the content of this repository: model_output.zip: This compressed file contains the results of all the individual numerical experiments per experimental site as produced by the Comunity Land Model version 5. The files are stored in NETCDF format per year. The folder is arranged with subfolders containing the individual results from each experimental site as follows: rc: model output with the results of the resistant configuration of experiment 1 (RC) vc: model output with the results of the vulnerable configuration of experiment 1 (VC) k_dc: model output with the results of the default configuration used for experiments 1 and 2 (DC or DC<em>k</em><sub>max</sub>) k_rc: model output with the results of the low plant hydraulic conductance (L<em>k</em><sub>max</sub>) for experiment 2 k_irc: model output with the results of the intermediate low plant hydraulic conductance (IL<em>k</em><sub>max</sub>) for experiment 2 k_vc: model output with the results of the high plant hydraulic conductance (H<em>k</em><sub>max</sub>) for experiment 2 k_ivc: model output with the results of the intermediate high plant hydraulic conductance (IH<em>k</em><sub>max</sub>) for experiment 2 k_iirc: model output with the results of the additional intermediate low plant hydraulic conductance (IIL<em>k</em><sub>max</sub>) for experiment 2 ko_dc: model output with the results of the best <em>k</em><sub>max</sub> and the default configuration of the PVC used in experiment 3 ko_rc: model output with the results of the best <em>k</em><sub>max</sub> and the resistant configuration of the PVC used in experiment 3 ko_vc: model output with the results of the best <em>k</em><sub>max</sub> and the vulnerable configuration of the PVC used in experiment 3 The scripts were written for use in RStudio, and each contains a detailed description of the data requirements and outputs. Each script was developed to read directly the netcdf files of the model output and the csv files containing the transpiration estimates calculated from the SAPFLUXNET per experimental site (script 1).
description: This work is supported by the Luxembourg National Research Fund (FNR) CORE program (grant no. C19/SR/13652816/CAPACITY).
DOI: 10.5281/zenodo.7003917
title: The role of the intraspecific variability of hydraulic traits for modelling the plant water use in different European forest ecosystems: scripts, model output, and parameter files

description: This repository contains the model outputs, parameter files, and R scripts used by the manuscript: "The role of the intraspecific variability of hydraulic traits for modelling the plant water use in different European forest ecosystems". The following is a detailed description of the content of this repository: model_output.zip: This compressed file contains the results of all the individual numerical experiments per experimental site as produced by the Comunity Land Model version 5. The files are stored in NETCDF format per year. parameters.zip: This compressed file contains the parameterization of each site. The scripts were written for its use in RStudio, and each script contains a detailed description of the data requirements and outputs.
description: This work is supported by the Luxembourg National Research Fund (FNR) CORE program (grant no. C19/SR/13652816/CAPACITY).
DOI: 10.5281/zenodo.8019682
title: The role of the intraspecific variability of hydraulic traits for modelling the plant water use in different European forest ecosystems: scripts, model output, and parameter files

description: This repository contains the model outputs and R scripts used to process the data to analyze the impact of the plant hydraulic parameterization of the manuscript: "The role of the intraspecific variability of hydraulic traits for modelling the plant water use in different European forest ecosystems". The following is a detailed description of the content of this repository: model_output.zip: This compressed file contains the results of all the individual numerical experiments per experimental site as produced by the Comunity Land Model version 5. The files are stored in NETCDF format per year. The folder is arranged with subfolders containing the individual results from each experimental site as follows: rc: model output with the results of the resistant configuration of experiment 1 (RC) vc: model output with the results of the vulnerable configuration of experiment 1 (VC) k_dc: model output with the results of the default configuration used for experiments 1 and 2 (DC or DC<em>k</em><sub>max</sub>) k_rc: model output with the results of the low plant hydraulic conductance (L<em>k</em><sub>max</sub>) for experiment 2 k_irc: model output with the results of the intermediate low plant hydraulic conductance (IL<em>k</em><sub>max</sub>) for experiment 2 k_vc: model output with the results of the high plant hydraulic conductance (H<em>k</em><sub>max</sub>) for experiment 2 k_ivc: model output with the results of the intermediate high plant hydraulic conductance (IH<em>k</em><sub>max</sub>) for experiment 2 k_iirc: model output with the results of the additional intermediate low plant hydraulic conductance (IIL<em>k</em><sub>max</sub>) for experiment 2 ko_dc: model output with the results of the best <em>k</em><sub>max</sub> and the default configuration of the PVC used in experiment 3 ko_rc: model output with the results of the best <em>k</em><sub>max</sub> and the resistant configuration of the PVC used in experiment 3 ko_vc: model output with the results of the best <em>k</em><sub>max</sub> and the vulnerable configuration of the PVC used in experiment 3 The scripts were written for use in RStudio, and each contains a detailed description of the data requirements and outputs. Each script was developed to read directly the netcdf files of the model output and the csv files containing the transpiration estimates calculated from the SAPFLUXNET per experimental site (script 1).
description: This work is supported by the Luxembourg National Research Fund (FNR) CORE program (grant no. C19/SR/13652816/CAPACITY).
DOI: 10.5281/zenodo.8108363
title: Multiparameter Water Quality Monitoring System for Continuous Monitoring of Fresh Waters Calibration and Measurement Data Set

description: This data set contains calibration data for all sensors incorporated in the sensor node. It provides comparison measurements of TPL fluorescence taken by the node and reference spectrofluorimeter. Initial test measurements, as well as site measurements, are also provided. Finally, data from a heuristic method of TPL detection in the presence of algae and mud are also given.
DOI: 10.5281/zenodo.8108364
title: Multiparameter Water Quality Monitoring System for Continuous Monitoring of Fresh Waters Calibration and Measurement Data Set

description: This data set contains calibration data for all sensors incorporated in the sensor node. It provides comparison measurements of TPL fluorescence taken by the node and reference spectrofluorimeter. Initial test measurements, as well as site measurements, are also provided. Finally, data from a heuristic method of TPL detection in the presence of algae and mud are also given.
DOI: 10.5281/zenodo.8071508
title: A Novel Approach to Heart Failure Prediction and Classification through Advanced Deep Learning Model

description: A Novel Approach to Heart Failure Prediction and Classification through Advanced Deep Learning Model
DOI: 10.5281/zenodo.8071507
title: A Novel Approach to Heart Failure Prediction and Classification through Advanced Deep Learning Model

description: A Novel Approach to Heart Failure Prediction and Classification through Advanced Deep Learning Model
DOI: 10.5281/zenodo.8112996
title: A Novel Approach to Heart Failure Prediction and Classification through Advanced Deep Learning Model

description: A Novel Approach to Heart Failure Prediction and Classification through Advanced Deep Learning Model
DOI: 10.6084/m9.figshare.23614809
title: An Open Dataset and an Algorithm for Niacin Skin-flushing Segmentation with Application in Psychiatric Disorders Classification

description: <strong>About the Dataset</strong> <strong>Summary:</strong> The dataset includes images associated with the Niacin Skin-Flushing Response (NSR), a physiological response connected with mental illnesses such as Depression (DP), Bipolar Disorder (BP), and Schizophrenia (SZ), in addition to images from a healthy control group (HC). The data was initially part of a larger dataset collected from inpatients diagnosed according to the International Classification of Diseases, 10th Revision (ICD10). The HC group includes individuals with no lifetime history of psychiatric illness. A subset of images was selected from the original dataset to create an AI screening tool. These images had areas of interest cut out, and the NSR areas were annotated by five students. A pixel was marked as a flushing pixel if at least two students marked it as such. While source files for the developing segmentation algorithms cannot be provided due to IP issues, the results can be viewed on the benchmark page. For collaboration interests, feel free to get in touch. <strong>Dataset Details:</strong> The dataset includes: Number of images: 600 (Formatted as 1.png, 2.png, ... 600.png) Format of images: PNG Contents of the original image: A common label for reference size and four flushing areas Marked images: Images with human-determined skin-flushing areas (Formatted as 1-marked.png, ..., 600-marked.png) Reference score (info.csv): A human-determined relative size of the flushing area compared to the label. <strong>Ethical Considerations:</strong> The data collection process followed guidelines set by the local ethics committee, with all participants having signed informed consent forms. Strict inclusion criteria were followed to ensure the health and safety of participants. The data has been anonymized and does not contain any personally identifiable information.
DOI: 10.6084/m9.figshare.23623185
title: datafiles for incremental research.rar

description: Wall following robot navigation data. <br> This file contain all the data used, for sensor 2, 4, 24 file, the original files are available in: Freire, Veloso, & Barreto. (2009). UCI Machine Learning Repository: Wall-Following Robot Navigation Data Data Set. UCI Machine Learning Repository: Wall-Following Robot Navigation Data Data Set. Retrieved 2017, from https://archive.ics.uci.edu/ml/datasets/Wall-Following+Robot+Navigation+Data in our research we reduced all original files using Condensed Nearest Neighbors CNN instance selection algorithm We used reduced files as training files, we removed all training instances from the original file and used the remaining data as test files to avoid data leakage. <br> for gathered data, we used the same method of gathering as the other files, labelled them, reduced them using CNN then finally prepared separate training and test files. <br> for additional information please contact: eng.s.madi@gmail.com
DOI: 10.5281/zenodo.7352558
title: MeCareNWL - baseline data concerning the psychosocial and occupational impact of COVID-19 among NHS and social care staff in NW London

description: Online survey data collected at baseline for participants enrolled in the MeCareNWL study - see MeCareNWL (nihr.ac.uk). Data extracted from the Qualtrics database on 13 July 2021. Some additional post-processing to satisfy anonymisation requirements.
description: Data has been anonymised as per Safe Harbor requirements
DOI: 10.5281/zenodo.7352557
title: MeCareNWL - baseline data concerning the psychosocial and occupational impact of COVID-19 among NHS and social care staff in NW London

description: Online survey data collected at baseline for participants enrolled in the MeCareNWL study - see MeCareNWL (nihr.ac.uk). Data extracted from the Qualtrics database on 13 July 2021. Some additional post-processing to satisfy anonymisation requirements. A pdf copy of the survey and the completed STROBE reporting checklist are also included.
description: Data has been anonymised as per Safe Harbor requirements
DOI: 10.5281/zenodo.7418449
title: MeCareNWL - baseline data concerning the psychosocial and occupational impact of COVID-19 among NHS and social care staff in NW London

description: Online survey data collected at baseline for participants enrolled in the MeCareNWL study - see MeCareNWL (nihr.ac.uk). Data extracted from the Qualtrics database on 13 July 2021. Some additional post-processing to satisfy anonymisation requirements. A pdf copy of the survey is also included.
description: Data has been anonymised as per Safe Harbor requirements