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6,704 results for “reports”
Food and waterborne outbreaks data complementing the European Union One Health 2018 Zoonoses Report
<p>Food and waterborne outbreaks data reported under the framework of Directive 2003/99/EC and in accordance with the update of the technical specifications for harmonised reporting of FBOs through the EU reporting system in accordance with Directive 2003/99/EC. This dataset includes the number of outbreaks, as well as the number of human cases, hospitalisations and deaths, per causative agent. In addition, other information can include data on causative agents, food vehicles, and the factors in food preparation and handling that contributed to the food-borne outbreaks. Reporting countries can also provide information on the nature of the evidence supporting the suspicion of the food vehicle. This evidence can be epidemiological, microbiological, descriptive environmental, or based on product tracing investigations. </p>
Sample based prevalence data complementing the European Union One Health 2018 Zoonoses Report
<p>This dataset contains monitoring sample based data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agentsin foodstuffs. Relevant EU legislation is:Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014. </p>
International Labour Office Historical Studies and Reports English
<p>This is a collection of English texts based on historical reports from the International Labour Office from the 20th century. The original documents can be found at <a href="https://www.ilo.org/public/libdoc/ilo/ILO-SR/">https://www.ilo.org/public/libdoc/ilo/ILO-SR/</a></p> <p>This collection may be used and distributed provided that the International Labour Office is always duly acknowledged as the original source and that the use is non-commercial.</p> <p>The collection was created with the tools <a href="https://curl.haxx.se/">curl</a>, <a href="https://ocrmypdf.readthedocs.io/">OCRmyPDF</a>, <a href="https://poppler.freedesktop.org/">Poppler</a> and the following script on Debian GNU/Linux.</p> <pre><code class="language-bash">curl https://www.ilo.org/public/libdoc/ilo/ILO-SR/ | grep -o 'ILO[^"]*engl[^"><\/]*' | uniq | sed 's,ILO,https://www.ilo.org/public/libdoc/ilo/ILO-SR/ILO,g' > list_of_files.txt xargs -n 1 curl -O < list_of_files.txt rm list_of_files.txt find . -name '*.pdf' -exec ocrmypdf --language eng --deskew --clean '{}' '{}' \; && find . -name '*.pdf' -exec pdftotext '{}' '{}.txt' \; rm *.pdf</code></pre>
NGS-MSTB - Example output Web report
<p><a href="https://github.com/ngs-mstb/micgent">NGS-MSTB</a> Docker image ships with the pre-computed example of assembling a set of complete RSV genomes. This dataset includes the Web report of the assembly results. It is used when building the Docker image.</p>
Patient-reported outcomes predict return to work and health-related quality of life 6 months after cardiac rehabilitation: Results from a German multi-centre registry (OutCaRe): dataset
<p>This is the resulting data set from the prospective observational study (available cases at the time of follow up monitoring) OutCaRe, that is the basis of all results presented in the article "Patient-reported outcomes predict return to work and health-related quality of life 6 months after cardiac rehabilitation: Results from a German multi-centre registry (OutCaRe)".</p> <p>OutCaRe is a registered study (https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00011418).</p>
S46 | PFASNTREV19 | List of PFAS reported in Non-Target HRMS Studies (Liu et al 2019)
<p>This is the collection associated with list S46 PFASNTREV2019 on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S46 | PFASNTREV19 | <strong>List of PFAS reported in Non-Target HRMS Studies (Liu <em>et al</em> 2019)</strong></p> <p>Table 1 from Liu et al as <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/220319Update/Liu_etal_2019_HRMS_PFAS_1-s2.0-S0165993618306253-Table1.pdf">PDF</a><br> MS-ready form in <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/080419Update/PFASNTREV19_Liu_etal_17042019.xlsx">XLSX</a> (formatted) and <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/080419Update/PFASNTREV19_Liu_etal_17042019.csv">CSV</a> (17/04/2019)<br> CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/PFASNTREV19">PFASNTREV19 List</a></p> <p>PFASNTREV19 <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/080419Update/PFASNTREV19_InChIKeys_17042019.txt">InChIKeys</a> (17/04/2019)</p> <p>List compiled in the non-target HRMS PFAS review by Liu et al 2019, DOI: <a href="https://doi.org/10.1016/j.trac.2019.02.021">10.1016/j.trac.2019.02.021</a>. MS-ready list prepared by Yanna Liu, Lisa D’Agostino, Emma Schymanski and Jon Martin. Note not all entries have structures.</p> <p>Update Feb 6, 2020: minor SMILES corrections to CSV for PubChem upload.</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - 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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_IE_20200204: >> The Food Safety Authority of Ireland</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Sweden
<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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_SE_20200204: >> National Veterinary Institute, Swedish Zoonosis Centre</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - 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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_LV_20200204: >> Assessment and Registration Agency of Food and Veterinary Service of Latvia</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Spain
<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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_ES_20200204: >> Agencia Espaola de Consumo, Seguridad Alimentaria y Nutricin >> Ministerio de Agricultura, Pesca y Alimentacin</p>
Specific monitoring results of ESBL-/AmpC-/carbapenemase-producing bacteria and specific monitoring of carbapenemase-producing bacteria, in the absence of isolates detected complementing the European Union Overview Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2017/2018
<p>This dataset derives from the specific monitoring of E. coli producers of ESBLs/AmpC/carbapenemases, as well as the specific monitoring of carbapenemase-producers (voluntary reporting), in the absence of any isolates detected. This dataset contains only data when Total units positive equals zero '0'.</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Cyprus
<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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_CY_20200204: >> Ministry of Agriculture, Natural Resources and Evironment - Veterinary Services</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - 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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_IS_20200204: >> Icelandic Food and Veterinary Authority</p>
Data set for: Adjustable Deterministic Pseudonymization of Speech Listening Experiment, Report of listening experiments
<p>Data set used in "Adjustable Deterministic Pseudonymization of Speech Listening Experiment". Includes Rmarkdown script.</p> <p> </p>
In-hospital patient safety events, healthcare costs and utilization: an analysis of data from the incident reporting system in an academic medical center
<p>Raw Datasets for the study 'In-hospital patient safety events, healthcare costs and utilization: an analysis of data from the incident reporting system in an academic medical center'.</p>
MarTREC Data Set for Report: Developing and Applying an Analysis Methodology to Identify Flow Generation Influences between Vessel and Truck Shipments
<p>Truck activity is logically connected to vessel activity at a port. In turn, vessel activity is also influenced by truck shipments. Although one might expect a direct and straightforward relation between these two types of shipments, that is rarely the case. For instance, many maritime containers carry consolidated cargos that have multiple and different final destinations. Also, different truck capacities, customs clearance and regulations play a critical role in determining the actual relation between these two types of shipments. This project aims at shedding light on the nuances of maritime and roadway flow relations by quantitatively analyzing the linkages between these two types of shipments.</p> <p>The study performed a statistical analysis to determine the probability distributions of vessel and truck activity, and then explore the correlation of each activity with the other. The analysis yielded coefficients that function as explanatory values for specific truck flows.</p> <p>The ultimate purpose of this study is to provide a clearer and quantitative understanding of the relationship between maritime and truck shipments, and by doing so, to provide tools to develop a system for managing trucks that maximizes efficiency for industry, while minimizing industry’s negative impacts on a region.</p> <p>For this purpose, the study selected the Port Freeport as a case study.</p>
SPEC RG Technical Report: A Review of Serverless Use Cases and their Characteristics - Dataset
<p><strong><em>PrettyDataset.xlsx</em></strong></p> <p>Our data set of 89 serverless use cases and their mapping to 24 characteristics. In form of an Excel file to simplify manual inspection. Columns represent characteristics, rows represent use cases.</p> <p><em><strong>Dataset.csv</strong></em></p> <p>Raw version of our data set of 89 serverless use cases and their mapping to 24 characteristics as a CSV file for automated analysis. Columns represent characteristics, rows represent use cases.</p> <p><em><strong>Initial Characterizations.csv</strong></em></p> <p>Reviewer characterizations prior to the discussion and consolidation phase. Required for the calculation of the fleiss kappa score.</p> <p><em><strong>CalculateKappa.py</strong></em></p> <p>Python script for the calculation of the fleiss kappa score shown in the technical report. Requires Python 3.6.</p> <p><em><strong>GenerateFigures.py</strong></em></p> <p>Python script for the generation of all figures shown in the technical report. Requires Python 3.6.</p>
Figure 21 in First report of the Asian jumping spider Menemerus nigli (Araneae: Salticidae: Chrysillini) in Brazil
Figure 21. Additional record of Menemerus nigli in the state of Rio de Janeiro (OCT 2017). This immature or female spider was found at site 2, on a wall of a house. Photography by Fernando Vinícius Gomes de Moraes, used with permission.
Figure 17 in First report of the Asian jumping spider Menemerus nigli (Araneae: Salticidae: Chrysillini) in Brazil
Figure 17. Epigynum of two female Menemerus nigli from Rio de Janeiro, Brazil. 1-2, Specimens in alcohol, with anterior toward the top of the page. 3-4, Ventral view of cleared epigynum. 5-6, Dorsal view of cleared epigynum.
Figure 1 in First report of the Asian jumping spider Menemerus nigli (Araneae: Salticidae: Chrysillini) in Brazil
Figure 1. Known distribution of Menemerus nigli. The Brazilian sites (5, at lower left) are far removed from other localities where this species has been found in southern and southeastern Asia (1-4, at upper right).
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.