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152 results for “accidents”
Prevention of Posttraumatic Stress Symptoms and Behavioral Problems in Children After Road Traffic Accidents: a Randomized Controlled Trial
ClinicalTrials.gov study NCT00296842. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Comparison of Accidents and Their Circumstances With Oral Anticoagulants
ClinicalTrials.gov study NCT02376777. IPD Sharing: Not stated. Countries: 1. Publications: 14.
Slashing Two-wheeled Accidents by Leveraging Eyecare
ClinicalTrials.gov study NCT05466955. IPD Sharing: YES. Countries: 1. Publications: 41.
SelFIT: Internet-based Treatment for Adjustment Problems After an Accident
ClinicalTrials.gov study NCT03785912. IPD Sharing: NO. Countries: 1. Publications: 1.
The Efficacy and Safety of Non-resistance Manual Therapy in Inpatients With Acute Neck Pain Caused by Traffic Accidents: a Randomised Controlled Trial
ClinicalTrials.gov study NCT04660175. IPD Sharing: NO. Countries: 1. Publications: 2.
Scientific Protocol for the Study of Thyroid Cancer and Other Thyroid Disease in Belarus Following the Chernobyl Accident
ClinicalTrials.gov study NCT00339716. IPD Sharing: Not stated. Countries: 1. Publications: 3.
DEPITAC : Short Screening Scale for Psychotraumatic Disorders After Motor Vehicle Accident
ClinicalTrials.gov study NCT01200628. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Evaluation of the Use of the Atalante Exoskeleton in Patients Presenting an Hemiplegia Due to Cerebrovascular Accident
ClinicalTrials.gov study NCT04694001. IPD Sharing: Not stated. Countries: 3. Publications: 1.
Evaluation of a Video-ludic Re-education of the Paretic Upper Limb in Chronic Hemipartic Patients Post Cerebral Vascular Accident
ClinicalTrials.gov study NCT03166020. IPD Sharing: NO. Countries: 1. Publications: 1.
10-years Nationwide Alpine Accidents in Austria
ClinicalTrials.gov study NCT03405467. IPD Sharing: NO. Countries: 1. Publications: 1.
A 13-years Nationwide Study of Alpine Accidents in Austria
ClinicalTrials.gov study NCT03755050. IPD Sharing: NO. Countries: 1. Publications: 1.
Improving the Detection of Active Tuberculosis in Accident and Emergency Departments
ClinicalTrials.gov study NCT02512484. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Sleep apnea, sleep debt and daytime sleepiness are independently associated with road accidents: a cross-sectional study on truck drivers
Open the record for dataset details and reuse information.
Pulp and paper risk accident classification in Colombia
<p>This is a dataset of risk accident assesment in pulp and paper industry in a colombian city.</p> <p>The principal matrix is the original assesment and the second file is a arff format file for DM analysis.</p>
Supplementary material of 3D transient CFD simulation of an in-vessel Loss-Of-Coolant Accident in the EU DEMO fusion reactor
<p>Supplementary material associated to publication "3D transient CFD simulation of an in-vessel Loss-Of-Coolant Accident in the EU DEMO fusion reactor": videos showing time evolution of distribution of</p> <ul> <li>Mach number</li> <li>Temperature</li> <li>Speed</li> </ul> <p>close to the break during an in-vessel LOCA in a helium-cooled EU DEMO.</p>
Table 10 Priorities of factor to reduce the rate of motorcycle accidents in Malaysia
<p>Priorities of factor to reduce the rate of motorcycle accidents in Malaysia</p>
Data from: Do failures in non-technical skills contribute to fatal medical accidents in Japan? A review of the 2010–2013 national accident reports
Objectives: We sought to clarify how large a proportion of fatal medical accidents can be considered to be caused by poor Non-Technical Skills, and to support development of a policy to reduce numbers of such accidents by making recommendations about possible training requirements. Design: Summaries of reports of fatal medical accidents, published by the Japan Medical Safety Research Organization, were reviewed individually. Three experienced clinicians and one patient safety expert conducted the reviews to determine the cause of death. Views of the patient safety expert were given additional weight in the overall determination. Setting: A total of 73 summary reports of fatal medical accidents were reviewed. These reports had been submitted by healthcare organisations across Japan to the Japan Medical Safety Research Organization between April 2010 and March 2013. Primary and secondary outcome measures: The cause of death in fatal medical accidents, categorised into technical skills, non-technical skills, and inevitable progress of disease were evaluated. Non-technical skills were further sub-divided into situation awareness, decision-making, communication, team working, leadership, managing stress, and coping with fatigue. Results: Overall, the cause of death was identified as non-technical skills in 34 cases (46.6%), disease progression in 33 cases (45.2%), and technical skills in two cases (5.5%). In two cases, no consensual determination could be achieved. Further categorisation of cases of non-technical skills were identified 14 cases (41.2%) of problems with situation awareness, eight (23.5%) with team-working, and three (8.8%) with decision-making. These three sub-categories, or combinations of them, were identified as the cause of death in 33 cases (97.1%). Conclusions: Poor non-technical skills were considered to be a significant cause of adverse events in nearly half of the fatal medical accidents examined. Improving non-technical skills may be effective for reducing accidents, and training in particular sub-categories of non-technical skills may be especially relevant.
NGII Data Set for Black Ice Traffic Accident Prediction
<p>NGII Data Set for Black Ice Traffic Accident Prediction</p> <p> </p> <p> </p>
Spatial Distribution and Cluster Analysis of Road Traffic Accidents in Nepal
Open the record for dataset details and reuse information.
DATABASE FOR THE ANALYSIS OF ROAD ACCIDENTS IN EUROPE
<p>This database that can be used for macro-level analysis of road accidents on interurban roads in Europe. Through the variables it contains, road accidents can be explained using variables related to economic resources invested in roads, traffic, road network, socioeconomic characteristics, legislative measures and meteorology. This repository contains the data used for the analysis carried out in the papers:</p> <p>1. Calvo-Poyo F., Navarro-Moreno J., de Oña J. (2020) Road Investment and Traffic Safety: An International Study. Sustainability 12:6332. https://doi.org/10.3390/su12166332</p> <p>2. Navarro-Moreno J., Calvo-Poyo F., de Oña J. (2022) Influence of road investment and maintenance expenses on injured traffic crashes in European roads. Int J Sustain Transp 1–11. https://doi.org/10.1080/15568318.2022.2082344</p> <p>3. Navarro-Moreno, J., Calvo-Poyo, F., de Oña, J. (2022) Investment in roads and traffic safety: linked to economic development? A European comparison. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-022-22567</p> <p>The file with the database is available in excel.</p> <p><strong>DATA SOURCES</strong></p> <p>The database presents data from 1998 up to 2016 from 20 european countries: Austria, Belgium, Croatia, Czechia, Denmark, Estonia, Finland, France, Germany, Ireland, Italy, Latvia, Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden and United Kingdom. Crash data were obtained from the United Nations Economic Commission for Europe (UNECE) [2], which offers enough level of disaggregation between crashes occurring inside versus outside built-up areas.</p> <p>With reference to the data on economic resources invested in roadways, deserving mention –given its extensive coverage—is the database of the Organisation for Economic Cooperation and Development (OECD), managed by the International Transport Forum (ITF) [1], which collects data on investment in the construction of roads and expenditure on their maintenance, following the definitions of the United Nations System of National Accounts (2008 SNA). Despite some data gaps, the time series present consistency from one country to the next. Moreover, to confirm the consistency and complete missing data, diverse additional sources, mainly the national Transport Ministries of the respective countries were consulted. All the monetary values were converted to constant prices in 2015 using the OECD price index.</p> <p>To obtain the rest of the variables in the database, as well as to ensure consistency in the time series and complete missing data, the following national and international sources were consulted:</p> <ul> <li>Eurostat [3]</li> <li>Directorate-General for Mobility and Transport (DG MOVE). European Union [4]</li> <li>The World Bank [5]</li> <li>World Health Organization (WHO) [6]</li> <li>European Transport Safety Council (ETSC) [7]</li> <li>European Road Safety Observatory (ERSO) [8]</li> <li>European Climatic Energy Mixes (ECEM) of the Copernicus Climate Change [9]</li> <li>EU BestPoint-Project [10]</li> <li><em>Ministerstvo dopravy</em>, República Checa [11]</li> <li><em>Bundesministerium für Verkehr und digitale Infrastruktur</em>, Alemania [12]</li> <li><em>Ministerie van Infrastructuur en Waterstaat</em>, Países Bajos [13]</li> <li><em>National Statistics Office</em>, Malta [14]</li> <li><em>Ministério da Economia e Transição Digital</em>, Portugal [15]</li> <li><em>Ministerio de Fomento</em>, España [16]</li> <li><em>Trafikverket</em>, Suecia [17]</li> <li><em>Ministère de l’environnement de l’énergie et de la mer</em>, Francia [18]</li> <li><em>Ministero delle Infrastrutture e dei Trasporti</em>, Italia [19–25]</li> <li><em>Statistisk sentralbyrå</em>, Noruega [26-29]</li> <li><em>Instituto Nacional de Estatística</em>, Portugal [30]</li> <li><em>Infraestruturas de Portugal S.A.</em>, Portugal [31–35]</li> <li><em>Road Safety Authority (</em><em>RSA</em><em>)</em>, Ireland [36]</li> </ul> <p> </p> <p><strong>DATA BASE DESCRIPTION</strong></p> <p>The database was made trying to combine the longest possible time period with the maximum number of countries with complete dataset (some countries like Lithuania, Luxemburg, Malta and Norway were eliminated from the definitive dataset owing to a lack of data or breaks in the time series of records). Taking into account the above, the definitive database is made up of 19 variables, and contains data from 20 countries during the period between 1998 and 2016. Table 1 shows the coding of the variables, as well as their definition and unit of measure.</p> <p> </p> <p>Table. Database metadata</p> <table> <tbody> <tr> <td> <p><strong>Code</strong></p> </td> <td> <p><strong>Variable and unit</strong></p> </td> </tr> <tr> <td> <p>fatal_pc_km</p> </td> <td> <p>Fatalities per billion passenger-km</p> </td> </tr> <tr> <td> <p>fatal_mIn</p> </td> <td> <p>Fatalities per million inhabitants</p> </td> </tr> <tr> <td> <p>accid_adj_pc_km</p> </td> <td> <p>Accidents per billion passenger-km</p> </td> </tr> <tr> <td> <p>p_km</p> </td> <td> <p>Billions of passenger-km</p> </td> </tr> <tr> <td> <p>croad_inv_km</p> </td> <td> <p>Investment in roads construction per kilometer, €/km (2015 constant prices)</p> </td> </tr> <tr> <td> <p>croad_maint_km</p> </td> <td> <p>Expenditure on roads maintenance per kilometer €/km (2015 constant prices)</p> </td> </tr> <tr> <td> <p>prop_motorwa</p> </td> <td> <p>Proportion of motorways over the total road network (%)</p> </td> </tr> <tr> <td> <p>populat</p> </td> <td> <p>Population, in millions of inhabitants</p> </td> </tr> <tr> <td> <p>unemploy</p> </td> <td> <p>Unemployment rate (%)</p> </td> </tr> <tr> <td> <p>petro_car</p> </td> <td> <p>Consumption of gasolina and petrol derivatives (tons), per tourism</p> </td> </tr> <tr> <td> <p>alcohol</p> </td> <td> <p>Alcohol consumption, in liters per capita (age > 15)</p> </td> </tr> <tr> <td> <p>mot_index</p> </td> <td> <p>Motorization index, in cars per 1,000 inhabitants</p> </td> </tr> <tr> <td> <p>den_populat</p> </td> <td> <p>Population density, inhabitants/km<sup>2</sup></p> </td> </tr> <tr> <td> <p>cgdp</p> </td> <td> <p>Gross Domestic Product (GDP), in € (2015 constant prices)</p> </td> </tr> <tr> <td> <p>cgdp_cap</p> </td> <td> <p>GDP per capita, in € (2015 constant prices)</p> </td> </tr> <tr> <td> <p>precipit</p> </td> <td> <p>Average depth of rain water during a year (mm)</p> </td> </tr> <tr> <td> <p>prop_elder</p> </td> <td> <p>Proportion of people over 65 years (%)</p> </td> </tr> <tr> <td> <p>dps</p> </td> <td> <p>Demerit Point System, dummy variable (0: no; 1: yes)</p> </td> </tr> <tr> <td> <p>freight</p> </td> <td> <p>Freight transport, in billions of ton-km</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>ACKNOWLEDGEMENTS</strong></p> <p>This database was carried out in the framework of the project “Inversión en carreteras y seguridad vial: un análisis internacional (INCASE)”, financed by: FEDER/Ministerio de Ciencia, Innovación y Universidades–Agencia Estatal de Investigación/Proyecto RTI2018-101770-B-I00, within Spain´s National Program of R+D+i Oriented to Societal Challenges.</p> <p>Moreover, the authors would like to express their gratitude to the Ministry of Transport, Mobility and Urban Agenda of Spain (MITMA), and the Federal Ministry of Transport and Digital Infrastructure of Germany (BMVI) for providing data for this study.</p> <p> </p> <p><strong>REFERENCES</strong></p> <p> </p> <p>1. International Transport Forum OECD iLibrary | Transport infrastructure investment and maintenance.</p> <p>2. United Nations Economic Commission for Europe UNECE Statistical Database Available online: https://w3.unece.org/PXWeb2015/pxweb/en/STAT/STAT__40-TRTRANS/?rxid=18ad5d0d-bd5e-476f-ab7c-40545e802eeb (accessed on Apr 28, 2020).</p> <p>3. European Commission Database - Eurostat Available online: https://ec.europa.eu/eurostat/data/database (accessed on Apr 28, 2021).</p> <p>4. Directorate-General for Mobility and Transport. European Commission EU Transport in figures - Statistical Pocketbooks Available online: https://ec.europa.eu/transport/facts-fundings/statistics_en (accessed on Apr 28, 2021).</p> <p>5. World Bank Group World Bank Open Data | Data Available online: https://data.worldbank.org/ (accessed on Apr 30, 2021).</p> <p>6. World Health Organization (WHO) WHO Global Information System on Alcohol and Health Available online: https://apps.who.int/gho/data/node.main.GISAH?lang=en (accessed on Apr 29, 2021).</p> <p>7. European Transport Safety Council (ETSC) <em>Traffic Law Enforcement across the EU - Tackling the Three Main Killers on Europe’s Roads</em>; Brussels, Belgium, 2011;</p> <p>8. Copernicus Climate Change Service Climate data for the European energy sector from 1979 to 2016 derived from ERA-Interim Available online: https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-european-energy-sector?tab=overview (accessed on Apr 29, 2021).</p> <p>9. Klipp, S.; Eichel, K.; Billard, A.; Chalika, E.; Loranc, M.D.; Farrugia, B.; Jost, G.; Møller, M.; Munnelly, M.; Kallberg, V.P.; et al. European Demerit Point Systems : Overview of their main features and expert opinions. <em>EU BestPoint-Project</em> <strong>2011</strong>, 1–237.</p> <p>10. Ministerstvo dopravy <em>Serie: Ročenka dopravy</em>; Ročenka dopravy; Centrum dopravního výzkumu: Prague, Czech Republic;</p> <p>11. Bundesministerium für Verkehr und digitale Infrastruktur <em>Verkehr in Zahlen 2003/2004</em>; Hamburg, Germany, 2004; ISBN 3871542946.</p> <p>12. Bundesministerium für Verkehr und digitale Infrastruktur Verkehr in Zahlen 2018/2019. In <em>Verkehrsdynamik</em>; Flensburg, Germany, 2018 ISBN 9783000612947.</p> <p>13. Ministerie van Infrastructuur en Waterstaat <em>Rijksjaarverslag 2018 a Infrastructuurfonds</em>; The Hague, Netherlands, 2019; ISBN 0921-7371.</p> <p>14. Ministerie van Infrastructuur en Milieu <em>Rijksjaarverslag 2014 a Infrastructuurfonds</em>; The Hague, Netherlands, 2015; ISBN 0921- 7371.</p> <p>15. Ministério da Economia e Transição Digital Base de Dados de Infraestruturas - GEE Available online: https://www.gee.gov.pt/pt/publicacoes/indicadores-e-estatisticas/base-de-dados-de-infraestruturas (accessed on Apr 29, 2021).</p> <p>16. Ministerio de Fomento. Dirección General de Programación Económica y Presupuestos. Subdirección General de Estudios Económicos y Estadísticas <em>Serie: Anuario estadístico</em>; NIPO 161-13-171-0; Centro de Publicaciones. Secretaría General Técnica. Ministerio de Fomento: Madrid, Spain;</p> <p>17. Trafikverket <em>The Swedish Transport Administration Annual report: 2017</em>; 2018; ISBN 978-91-7725-272-6.</p> <p>18. Ministère de l’Équipement, du T. et de la M. <em>Mémento de statistiques des transports 2003</em>; Ministère de l’environnement de l’énergie et de la mer, 2005;</p> <p>19. Ministero delle Infrastrutture e dei Trasporti <em>Conto Nazionale delle Infrastrutture e dei Trasporti Anno 2000</em>; Istituto Poligrafico e Zecca dello Stato: Roma, Italy, 2001;</p> <p>20. Ministero delle Infrastrutture e dei Trasporti Conto nazionale dei trasporti 1999. <strong>2000</strong>.</p> <p>21. Generale, D.; Informativi, S. delle Infrastrutture e dei Trasporti Anno 2004.</p> <p>22. Ministero delle Infrastrutture e dei Trasporti <em>Conto Nazionale delle Infrastrutture e dei Trasporti Anno 2001</em>; 2002;</p> <p>23. Ministero delle Infrastrutture e dei Trasporti Conto Nazionale delle Infrastrutture e dei Trasporti Anni 2007-2008. <strong>2009</strong>.</p> <p>24. Ministero delle Infrastrutture e dei Trasporti Conto Nazionale delle Infrastrutture e dei Trasporti Anni 2016-2017. <strong>2018</strong>.</p> <p>25. Ministero delle Infrastrutture e dei Trasporti <em>Conto Nazionale delle Infrastrutture e dei Trasporti. Anni 2014-2015</em>; 2016;</p> <p>26. Statistics Norway <em>Statistical Yearbook of Norway 2000</em>; Ad Notam Gyldendal: Oslo, Norway, 2000; ISBN 82-537-4820-5.</p> <p>27. Statistics Norway <em>Statistical Yearbook of Norway 2001</em>; Gnist.Akademika: Oslo, Norway, 2001; ISBN 8253749600.</p> <p>28. Statistics Norway <em>Statistical Yearbook of Norway 2002</em>; Gnist.Akadernika: Oslo, Norway, 2002; ISBN 8253750927.</p> <p>29. Statistics Norway <em>Statistical Yearbook of Norway 2004</em>; Gnist.Akademika: Oslo, Norway, 2004; ISBN 82-537-6616-5.</p> <p>30. Instituto Nacional de Estatística <em>Estatísticas dos transportes e comunicações 2000</em>; Instituto Nacional de Estatística: Lisbon, Portugal, 2002;</p> <p>31. Estradas de Portugal S.A. <em>Relatório e Contas 2011</em>; Almada, Portugal, 2012;</p> <p>32. Estradas de Portugal S.A. <em>Relatório e Contas 2012</em>; Lisboa, Portugal, 2013;</p> <p>33. Estradas de Portugal S.A. <em>Relatório e Contas 2010</em>; Lisboa, Portugal, 2011;</p> <p>34. Infraestruturas de Portugal S.A. <em>Relatório e Contas 2015</em>; Pragal, Portugal, 2016;</p> <p>35. Infraestruturas de Portugal S.A. <em>Relatório e Contas 2018</em>; Almada, Portugal, 2019;</p> <p>36. Road Safety Authority <em>Road Collision Factbook</em>; Ballina, Ireland;</p> <p> </p> <p> </p>
ScienceDex guides
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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)
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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.