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6,704 results for “reports”
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Italy
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Istituto Zooprofilattico Sperimentale delle Regioni Lazio e Toscana</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – North Macedonia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Faculty of Veterinary Medicine - Skopje.</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Iceland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Icelandic Food and Veterinary Authority</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Slovenia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Ministry for Agriculture, Forestry and Food</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Denmark
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: National Food Institute - The Technical University of Denmark</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Latvia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Assessment and Registration Agency of Food and Veterinary Service of Latvia</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Switzerland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Federal Food Safety and Veterinary Office</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Croatia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Croatian Veterinary Institute</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Portugal
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Instituto Nacional de Investigação Agrária e Veterinária</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Hungary
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: National Food Chain Safety Office</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Norway
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Norwegian Veterinary Institute</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Slovakia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: State Veterinary and Food Institute</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Ireland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: The Food Safety Authority of Ireland</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – The United Kingdom
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Animal and Plant Health Agency</p>
Catalogues for 2021 zoonoses data reporting
<p>The EFSA catalogues applied for the 2021 zoonoses data reporting are made available in Excel format for easier use and reference.</p>
Development of Cost-Effective High-Modulus Asphalt 5. Report Date Aug. 2021 Concrete (HMAC) Mixtures Using Crumb Rubber and Local Construction Materials in Louisiana
<p>One of the emerging solutions to enhance the durability of asphalt pavements is the use of a French asphalt mix<br> known as “High-Modulus Asphalt Concrete (HMAC).” This mix uses a hard asphalt binder, high binder content<br> (about 6%), and low air voids content as compared to Superpave mixtures. The key objective of this study was<br> to develop a cost-effective HMAC mixture using crumb rubber and local materials in Louisiana. To achieve this<br> objective, four HMAC mixtures were prepared using two asphalt binders (PG 82-22 and PG 76-22 plus 10%<br> crumb rubber) and two Reclaimed Asphalt Pavement (RAP) contents (20% and 40%); additionally, a<br> conventional Superpave mixture in Louisiana was prepared as a control mixture. The laboratory performance<br> of these five mixtures was evaluated in terms of workability, dynamic modulus, rutting resistance, and cracking<br> resistance. The AASHTOWare Pavement ME Design software was also used to estimate the long-term field<br> performance of these mixtures. Results indicated that the HMAC mixture prepared with 10% crumb rubber and<br> 20% RAP successfully met the French mix design specifications for HMAC and LaDOTD specifications. This<br> HMAC mix outperformed the control Superpave mix in terms of dynamic modulus, rutting resistance, and<br> cracking resistance. Additionally, this HMAC mixture can reduce the required asphalt thickness by 1.5 or 2<br> inches based on traffic level. The cost-effectiveness analysis indicated that this HMAC mixture was more costeffective<br> than conventional Superpave mixtures in Louisiana. In addition, this mixture is environmentallyfriendly<br> since it can reduce the disposal of scrap tires in landfills.</p>
Dataset from 'Klever, L., Mamassian, P., & Billino, J. (2022). Age-related differences in visual confidence are driven by individual differences in cognitive control capacities. Scientific Reports, 12, 1-13. doi: 10.1038/s41598-022-09939-7
<p>We provide two files; one data file contains data on which analyses are based, the other one gives the column labels for the data file.</p> <p>___________________________________________<br> For further questions, please contact:<br> lena.klever[at]psychol.uni-giessen.de</p>
Fig. 1 in First Report Of Arthropod Fauna In Flooded Plains Of Northern Patagonia (38° S, Araucania Region Chile)
Fig. 1. Map of study sites (obtained by R package "dismo", Hijmans et al., 2011).
Reports about the tools for georeferencing IFC delivered within the GeoBIM benchmark 2019 - Task 2
<p>Answers delivered through the online forms, about the tests performed by participants within the Task 2 - georeferencing IFC files of the GeoBIM benchmark 2019, funded as a Scientific Initiative 2019 by the International Society of Photogrammetry and Remote Sensing (ISPRS) and co-funded by the European association for Spatial Data Research (EuroSDR).</p> <p>Full details and additional resources about the project are available in the project website: https://3d.bk.tudelft.nl/projects/geobim-benchmark/</p> <p>The dataset results from the collaboration of the authors with all the participants to the benchmark, listed at https://3d.bk.tudelft.nl/projects/geobim-benchmark/participants.html</p> <p>It is composed by 2 files:</p> <p>- the answers to the delivered online forms, organised in excel sheet;</p> <p>- the same answers organised in a more human-readable PDF, with reliable images and links.</p>
Accompanying data for the report data.europa.eu and Citizen-generated Data: Opportunities and challenges associated to the inclusion of citizen-generated data in data.europa.eu
<p>Accompanying data for the report data.europa.eu and Citizen-generated Data: Opportunities and challenges associated to the inclusion of citizen-generated data in data.europa.eu. This includes the catalogue of papers that have been revised in the course of generating this report, as well as a file with the analysis of datasets from different open data portals in Europe, with respect to their inclusion of Citizen-Generated Data.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.