cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4604850
title: Data_WP2_4_Emission inventory for the whole of Europe data set

description: This dataset includes model-ready gridded sector-specific emissions at a high spatial resolution for six standard air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, SO2) and GHGs (CO2, CO, N2O, CH4) for 2015, 2020 and 2030 using a top-down approach for the spatial distribution. Gridded sector-specific emissions for the standard air pollutants are stored in the subfolder named “Air_pollutants” while gridded emissions for GHHs are stored in the sub-folder called “GHG”. These emission inventories were used as input for the<br> atmospheric pollution models applied in WP3. The dataset is available in txt format (semicolon separated) as it is best suited for project internal data exchange (especially as input for the atmospheric pollution models applied in WP3).
DOI: 10.5281/zenodo.4607391
title: Data_WP2_2_Future activity-emission factor matrices for the whole of Europe

description: The dataset includes data on future activity-emission factor matrices for the whole of Europe for the classical air pollutants (NH<sub>3</sub>, NMVOC, NO<sub>X</sub>, PM<sub>10</sub>, PM<sub>2.5</sub>, CO, SO<sub>2, </sub>BC and OC), GHGs (CO<sub>2</sub>, CO, N<sub>2</sub>O, CH<sub>4</sub>), heavy metals, PAHs and dioxins, relevant to the years 2015, 2020 and 2030. A detailed description of the structure of the (detailed) DB and all relevant data sources can be found in deliverable D2.2 freely downloadable from the ICARUS website. The data are available in MS-Access format (accdb) to maximise the interoperability for use with a variety of analytical software.<br> Sectoral emission data are publicly freely available to anyone with the expectation that both the ICARUS project and the European Commission’s Horizon 2020 as the funding program are properly cited. Additionally, aggregated activity data and emission factors on sector level are included for most sectors. Industry, Agriculture, Waste and the sector “Other emissions (solvent use etc.)” are characterized by a diverse activity structure that does not allow any reasonable aggregation of the raw data.<br> Raw datasets relevant to activity-emission factor matrices cannot be made available to the public due to potential licensing conflicts with the original datasets
DOI: 10.5281/zenodo.4607390
title: Data_WP2_2_Future activity-emission factor matrices for the whole of Europe

description: The dataset includes data on future activity-emission factor matrices for the whole of Europe for the classical air pollutants (NH<sub>3</sub>, NMVOC, NO<sub>X</sub>, PM<sub>10</sub>, PM<sub>2.5</sub>, CO, SO<sub>2, </sub>BC and OC), GHGs (CO<sub>2</sub>, CO, N<sub>2</sub>O, CH<sub>4</sub>), heavy metals, PAHs and dioxins, relevant to the years 2015, 2020 and 2030. A detailed description of the structure of the (detailed) DB and all relevant data sources can be found in deliverable D2.2 freely downloadable from the ICARUS website. The data are available in MS-Access format (accdb) to maximise the interoperability for use with a variety of analytical software.<br> Sectoral emission data are publicly freely available to anyone with the expectation that both the ICARUS project and the European Commission’s Horizon 2020 as the funding program are properly cited. Additionally, aggregated activity data and emission factors on sector level are included for most sectors. Industry, Agriculture, Waste and the sector “Other emissions (solvent use etc.)” are characterized by a diverse activity structure that does not allow any reasonable aggregation of the raw data.<br> Raw datasets relevant to activity-emission factor matrices cannot be made available to the public due to potential licensing conflicts with the original datasets
DOI: 10.25678/0003n6
title: Data for: Unraveling the riverine antibiotic resistome: the downstream fate of anthropogenic inputs

description: River networks are one of the main routes by which the public could be exposed to environmental sources of antibiotic resistance, that may be introduced e.g. via treated wastewater. In this study, we applied a comprehensive integrated analysis encompassing mass-flow concepts, chemistry, bacterial plate counts, resistance gene quantification and shotgun metagenomics to track the fate of the resistome (collective antibiotic resistance genes (ARGs) in a microbial community) of treated wastewater in two Swiss rivers at the kilometer scale. The levels of certain ARGs and the class 1 integron integrase gene (intI1) commonly associated with anthropogenic sources of ARGs decreased quickly over short distances (2-2.5 km) downstream of wastewater discharge points. Mass-flow analysis based on conservative tracers suggested this decrease was attributable mainly to dilution but ARG loadings frequently also decreased (e.g., 55.0-98.5 % for ermB and tetW) over the longest studied distances (6.8 and 13.7 km downstream). Metagenomic analysis confirmed that ARG of wastewater-origin did not persist in rivers after 5 ∼ 6.8 km downstream distance. sul1 and intI1 levels and loadings were more variable and even increased sharply at 5 ∼ 6.8 km downstream distance on one occasion. While input from agriculture and in-situ positive selection pressure for organisms carrying ARGs cannot be excluded, in-system growth of biomass is a more probable explanation. The potential for direct human exposure to the resistome of wastewater-origin thus appeared to typically abate rapidly in the studied rivers. However, the riverine aquatic resistome was also dynamic, as evidenced by the increase of certain gene markers downstream, without obvious sources of anthropogenic contamination. This study provides new insight into drivers of riverine resistomes and pinpoints key monitoring targets indicative of where human sources and exposures are likely to be most acute.
DOI: 10.5281/zenodo.4605878
title: Data_WP6_1_Visions for smart green and healthy cities

description: This dataset consists of narrative visions of ICARUS smart, green and healthy city developed in the frame of WP6 for all the ICARUS cities. The narrative-based visions have been updated through participatory expert and stakeholder workshops, literature review and horizon scanning. Supporting data in the development of visions include videos made at workshops as part of the ICARUS project. The dataset includes the steps towards the development of a transition pathway and how the transition from the current state to different city visions can be managed. The file includes data and information for each ICARUS city resulting from the interactions with local stakeholders. The data set is available pdf format. Supporting document (i.e. three videos) are available in mp4 format
DOI: 10.5281/zenodo.4605877
title: Data_WP6_1_Visions for smart green and healthy cities

description: This dataset consists of narrative visions of ICARUS smart, green and healthy city developed in the frame of WP6 for all the ICARUS cities. The narrative-based visions have been updated through participatory expert and stakeholder workshops, literature review and horizon scanning. Supporting data in the development of visions include videos made at workshops as part of the ICARUS project. The dataset includes the steps towards the development of a transition pathway and how the transition from the current state to different city visions can be managed. The file includes data and information for each ICARUS city resulting from the interactions with local stakeholders. The data set is available pdf format. Supporting document (i.e. three videos) are available in mp4 format
DOI: 10.5281/zenodo.4605802
title: Data_WP5_3_Monetary valuation of impacts and cost-benefit analysis

description: This dataset includes the results of the cost-effectiveness and cost-benefit analysis performed for each of the policy/measure options defined in Task 5.1. As such it complements the dataset “Data_WP5_2_Health effects at the community level data set” in providing the assessment of the economic dimension for the same policies/measures. Cost-effectiveness analysis examined the costs of these options and calculated for example the cost per ton of CO2eq. For the cost-benefit analysis the dataset includes all benefits, damages and costs and the non-monetary (intangible) items which were transformed into monetary values (where possible) including social costs, monetized health impacts, monetized contributions to climate change, utility and gain losses.<br> The full dataset is organized in three different files according to the sector addressed by the policy/measure options analyzed.<br> In this light, the file named “CBA active transport” includes the full results for the active transport policies; the file named “CBA alternative fuel vehicles” results for all the alternative fuel vehicles policies; and the file “CBA energy efficiency” for the<br> energy efficiency policies. Every single file includes multiple worksheets which respectively encompasses a summary of all the CBA results for the policy sector addressed, as well as other worksheets including the detailed results for each specific policy<br> up to the year 2040. The data are available either in MS–Excel xls(x) format to ensure full interoperability allowing easy parsing and information exchange.
DOI: 10.5281/zenodo.4605801
title: Data_WP5_3_Monetary valuation of impacts and cost-benefit analysis

description: This dataset includes the results of the cost-effectiveness and cost-benefit analysis performed for each of the policy/measure options defined in Task 5.1. As such it complements the dataset “Data_WP5_2_Health effects at the community level data set” in providing the assessment of the economic dimension for the same policies/measures. Cost-effectiveness analysis examined the costs of these options and calculated for example the cost per ton of CO2eq. For the cost-benefit analysis the dataset includes all benefits, damages and costs and the non-monetary (intangible) items which were transformed into monetary values (where possible) including social costs, monetized health impacts, monetized contributions to climate change, utility and gain losses.<br> The full dataset is organized in three different files according to the sector addressed by the policy/measure options analyzed.<br> In this light, the file named “CBA active transport” includes the full results for the active transport policies; the file named “CBA alternative fuel vehicles” results for all the alternative fuel vehicles policies; and the file “CBA energy efficiency” for the<br> energy efficiency policies. Every single file includes multiple worksheets which respectively encompasses a summary of all the CBA results for the policy sector addressed, as well as other worksheets including the detailed results for each specific policy<br> up to the year 2040. The data are available either in MS–Excel xls(x) format to ensure full interoperability allowing easy parsing and information exchange.
DOI: 10.5281/zenodo.4605678
title: Data_WP5_1_Feasible mitigation and abatement options

description: This dataset consists of databases where all the policies and measures options initially identified in all the cities are reported. Based on the discussions with the city stakeholders this list was then narrowed down to 5 policies per city which have been then integrally assessed in Task 5.4 according to the ICARUS paradigm. Both technical (e.g., changing emission factors due to the penetration of more environment-friendly technologies) and non-technical measures (that influence the citizens behavior) are covered and both short term measures that can be implemented in the immediate future and mediumterm measures which entail for instance changes of infrastructure or a certain time for market penetration and will be thus fully effective only after 2020 will be considered. Data is stored as MS Excel xlsx format. In the MS Word file named “Overview of policies andmeasures_documentation.docs“ the description of the content of MS excel file is reported.
DOI: 10.5281/zenodo.4605677
title: Data_WP5_1_Feasible mitigation and abatement options

description: This dataset consists of databases where all the policies and measures options initially identified in all the cities are reported. Based on the discussions with the city stakeholders this list was then narrowed down to 5 policies per city which have been then integrally assessed in Task 5.4 according to the ICARUS paradigm. Both technical (e.g., changing emission factors due to the penetration of more environment-friendly technologies) and non-technical measures (that influence the citizens behavior) are covered and both short term measures that can be implemented in the immediate future and mediumterm measures which entail for instance changes of infrastructure or a certain time for market penetration and will be thus fully effective only after 2020 will be considered. Data is stored as MS Excel xlsx format. In the MS Word file named “Overview of policies andmeasures_documentation.docs“ the description of the content of MS excel file is reported.
DOI: 10.5281/zenodo.4601511
title: Data_WP3_4_Light Manned Aircraft (LMA) measurements for selected cities

description: The dataset contains air quality (VOCs) and GHGs (CO2, N2O, CH4, SF6) data at different height profiles collected in the frame<br> of the ICARUS aerial campaigns. The aircraft operated at different height profiles above three European cities (Athens, Thessaloniki and Ljubljana) over sites with different characteristics (urban, suburban, rural) providing measurements of air pollutants and GHGs concentrations using sensor technologies as well as special sampling instrumentation. The data are stored in a single MS-Excel file named “Aerial_campaign_data.xlsx” which encompasses two worksheets: one named “Airplane_GHGs” which includes GHGs concentration levels measured over the 3 cities and the second named “Airplane_VOC's_Conc” which includes VOCs (benzene, toluene, o – Xylene, and m,p – Xylenes) concentrations measured over the 3 cities. Data are reported as average concentrations respectively above and below the atmospheric mixing layer.
DOI: 10.5281/zenodo.4601510
title: Data_WP3_4_Light Manned Aircraft (LMA) measurements for selected cities

description: The dataset contains air quality (VOCs) and GHGs (CO2, N2O, CH4, SF6) data at different height profiles collected in the frame<br> of the ICARUS aerial campaigns. The aircraft operated at different height profiles above three European cities (Athens, Thessaloniki and Ljubljana) over sites with different characteristics (urban, suburban, rural) providing measurements of air pollutants and GHGs concentrations using sensor technologies as well as special sampling instrumentation. The data are stored in a single MS-Excel file named “Aerial_campaign_data.xlsx” which encompasses two worksheets: one named “Airplane_GHGs” which includes GHGs concentration levels measured over the 3 cities and the second named “Airplane_VOC's_Conc” which includes VOCs (benzene, toluene, o – Xylene, and m,p – Xylenes) concentrations measured over the 3 cities. Data are reported as average concentrations respectively above and below the atmospheric mixing layer.
DOI: 10.6084/m9.figshare.14261372
title: Radiocarbon dates from Central Yakutia, v.1.0

description: Quaternary history of Central Yakutia, including permafrost history, is still a major challenge for the researchers in the region. The origin and development of ice-rich permafrost, referenced as 'Ice Complex', is debated. Further discussion is fuelled by the evident reaction of this extremely particular cryoarid environment of Central Yakutia to the ongoing and forecasted climate change.<br>This dataset compiles 254 <sup>14</sup>C dates from Central Yakutia. Significant part of the collection was published in 1970s and 1980s by the researchers of Melnikov Permafrost Institute SB RAS. Multiple dates (n = 25) are compiled for the extensively studied Mamontova Gora outcrop on the Aldan R., and the Khara-Bulgunnyakh alas site, where repeated surveys were performed in 2010s after major studies in the 1980s.<br>[Upd] The Google Earth kmz file marks the majority of referenced locations.
DOI: 10.17632/ht9k5p3vdb.1
title: The 100 Largest Hydropower Plants in the Greater Mekong Subregion

description: China plays an increasingly large role in global energy and electricity sector development through its overseas investment. The Chinese hydropower industry has come to dominate global hydropower development, particularly in the Greater Mekong Subregion (GMS), which consists of the countries along the mainstream Mekong River – Laos, Myanmar, Vietnam, Thailand, and Cambodia. In order to investigate patterns of Chinese and other overseas hydropower developers in the GMS region, we assembled a dataset of hydropower projects in the five GMS countries excluding China. This unit-level dataset was initialized by merging four datasets: the Platts World Electric Power Plants database, the Stimson Center Mekong Infrastructure Tracker, Boston University China’s Global Power Database, and the WRI Global Power Plant Database. Each of these databases has varying technological and financial information at the plant level. We first aggregated the Platts database by plant rather than unit for uniformity. Then we used a Ruby script to build a concordance table, which matched plant names used in different databases. The script iterates through all databases except WRI’s GPPD, applying each of four strategies to the plant name string to find matches across data sources: 1) manual overrides, 2) naive string match, 3) ignoring suffixes, 4) using alternates. Next, the script iterates through the unmatched plant names and aggregates plants by phase. If one source has a project aggregated by phase where other sources list each phase separately, the phases are added to the concordance table to match the aggregated project name. Then the WRI GPPD is incorporated into the concordance table by matching on Platts database ID or plant name where no ID is available. Finally, a merged database including all attributes across data sources was constructed using the concordance table, where capacity is summed when aggregation is required. We selected the 100 largest hydropower plants, in terms of capacity, for verification and collection of additional data. When not already identified by the Platts data, we performed a web search to identify the company name and country of origin for developer companies, their parent companies, and construction companies for each plant. Where there was a discrepancy between the four datasets on basic characteristics of the plant – namely, capacity, status, or year, we performed a web search to find a reliable and recent source of information to confirm the data. We also used a literature review and web search to fill in data on key features related to the size of the associated dam and reservoir for each plant. For discrepancies and missing data, we welcome feedback and contributions from users of this dataset.
DOI: 10.17632/wphgmsdp9f.1
title: Numerical LMI solutions for State Feedback with Polynomial Lyapunov Functions

description: Simulation and LMI codes for the problem of state feedback design for nonlinear systems using polynomial Lyapunov functions. The LMIs are solved with MATLAB toolboxes, Sedumi and Yalmip. We provide the LMI conditions, the programs and simulation schemes to make it easier to reproduce two numerical problems.
DOI: 10.17632/bxp7jh6yw5.1
title: 5-hydroxymethylcytosine is Dynamically Regulated During Forebrain Organoid Development and Aberrantly Altered in Forebrain Organoids of Alzheimer’s Disease . Kuehner et al

description: Raw images labeled as shown in the main and supplementary figures. The actual regions used in the figures were highlighted with a red box.
DOI: 10.17632/pfjnh9wb55.1
title: Dataset to test the relationship between Measuring Supply Chain Information Systems, SC agility, SC Collaboration, and SC Performance.

description: Dataset to test the relationship between Measuring Supply Chain Information Systems, SC agility, SC Collaboration, and SC Performance.
DOI: 10.17632/3cvrz42tyg.4
title: Genomic epidemiology identifies emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States. Washington et al.

description: Number of positive tests, SGTF dropouts and B117 sequences at Helix from Oct 15, 2020 to Feb 19, 2021. The testing data has been filtered to include only those days with &gt;= 3 tests to protect patient privacy. Inquiries can be made to Helix for additional details if they want to enter into a data transfer agreement.
DOI: 10.17632/9j7wm22cgn.1
title: Py-Conjugated: Quantitative Morphology Data for Organic Photovoltaics

description: This dataset contains 3 sub-sets of data, all of which describe a series of P3HT:PCBM OPV cells that have received different thermal annealing treatments. By annealing to alter the morphology of the thin films in this well-studied system, a workflow for extracting, reporting, and applying machine learning to quantitative morphology data are validated. The subsets of data are: 1) A .csv containing the extracted and distilled quantitative morphology descriptors for each of the 3 phases in the P3HT:PCBM bulk heterojunction (polymer-rich, fullerene-rich, and mixed) 2) A directory that contains .npy files of the m2py (10.1021/acs.jcim.0c00308) labeled morphologies of the OPV active layers. These are used to generate subset #1 3) A directory that contains the cleaned .npy files containing fast force-distance microscopy images of the OPV active layers. These are used to generate subset #2 Also contained in this dataset are .csv files that list the train-test split used in machine learning model training/validation.
DOI: 10.17632/cs942c8rw3.1
title: TBARS_BEEF

description: The TBARS values are expresed as percentage malonodialdehyde (MDA mg/kg) changes during storage of meat samples at different temperatures.
DOI: 10.17632/69jfdsv8w4.1
title: TBARS_PORK_MEAT

description: The TBARS (%) changes in meat during storage.
DOI: 10.17632/p4cnd87hxh.4
title: QLQ-C30 -QLQ-BR23 Universidad del Valle

description: 80 answers to the QLQ-C30 and QLQ-BR- 23 questionnaire. Some sociodemographic variables were considered, the research team is estimating which variables affect the quality of life by means of Bayesian models and structural equations.
DOI: 10.17632/bgxfwsg3sb.2
title: A comprehensive analysis and resource to use CRISPR-Cas13 for broad-spectrum targeting of RNA viruses. Lin et al.

description: The COVID-19 pandemic caused by SARS-CoV-2 and variants has led to significant mortality. We recently reported that an RNA-targeting CRISPR-Cas13 system, termed prophylactic antiviral CRISPR in human (PAC-MAN), offered an antiviral strategy against SARS-CoV-2 and influenza A virus. Here, we expand in silico analysis to use PAC-MAN to target a broad spectrum of human- or livestock-infectious RNA viruses with high specificity, coverage, and predicted efficiency. Our analysis reveals that a minimal set of 14 crRNAs is able to target &gt;90% of human-infectious viruses across 10 RNA virus families. We predict that a set of 5 experimentally validated crRNAs can target new SARS-CoV-2 variant sequences with 0 mismatches. We also build an online resource (crispr-pacman.stanford.edu) to support community use of CRISPR-Cas13 for broad-spectrum RNA virus targeting. Our work provides a new bioinformatic resource for using CRISPR-Cas13 to target diverse RNA viruses in order to facilitate development of CRISPR-based antivirals.