Automated Author ProfileLuiz Antonio Da Costa Rodrigues
Luiz Antonio Da Costa Rodrigues
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.9 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
ABSTRACT The potential risk of exposure of populations to Chemical, Biological, Radioactive and Nuclear agents (CBRN), either by intentional causes or not, is a matter of national security and demands a constant improvement in its management. The models of atmospheric dispersion have been gaining prominence as a tool to support the management of risks to CBRN agents. The objective of this research was to identify and evaluate studies that used the Hysplit model in the context of CBRN events. For this purpose, an integrative literature review of published articles was conducted between 2014 and 2018, from the PubMed, Scopus, Web of Science and Lilacs databases. The analysis of the selected articles revealed the potential of the Hysplit model, as a mathematical model, to understand the transport, dispersion and deposition of CBRN threats released into the atmosphere. The data produced by the simulations generated by this code can reveal which areas will be potentially impacted in a given event or the region of origin of elements dispersed in the air. In addition, Hysplit can be aggregated as a decisions support tool in the different phases of CBRN event management.
Authors
- Pereira, Adriana Paula Macedo Ferreira ;
- Luiz Antonio Da Costa Rodrigues ;
- Santos, Elaine Alves Dos ;
- Cardoso, Telma Abdalla De Oliveira ;
- Cohen, Simone Cynamon
ABSTRACT The potential risk of exposure of populations to Chemical, Biological, Radioactive and Nuclear agents (CBRN), either by intentional causes or not, is a matter of national security and demands a constant improvement in its management. The models of atmospheric dispersion have been gaining prominence as a tool to support the management of risks to CBRN agents. The objective of this research was to identify and evaluate studies that used the Hysplit model in the context of CBRN events. For this purpose, an integrative literature review of published articles was conducted between 2014 and 2018, from the PubMed, Scopus, Web of Science and Lilacs databases. The analysis of the selected articles revealed the potential of the Hysplit model, as a mathematical model, to understand the transport, dispersion and deposition of CBRN threats released into the atmosphere. The data produced by the simulations generated by this code can reveal which areas will be potentially impacted in a given event or the region of origin of elements dispersed in the air. In addition, Hysplit can be aggregated as a decisions support tool in the different phases of CBRN event management.
Authors
- Pereira, Adriana Paula Macedo Ferreira ;
- Luiz Antonio Da Costa Rodrigues ;
- Santos, Elaine Alves Dos ;
- Cardoso, Telma Abdalla De Oliveira ;
- Cohen, Simone Cynamon