MIGUEL NAKAMURA
Biographic Data
| ID | 7360598 |
|---|---|
| NAME | MIGUEL NAKAMURA |
| GIVEN NAMES | MIGUEL |
| FAMILY NAME | NAKAMURA |
| SIGNATURE | NAKAMURA M |
| AFFILIATIONS | Mathematics Research Center |
| ORCID | 0000-0002-4254-9355 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2006 |
| LATEST PUBLICATION YEAR | 2012 |
| H-INDEX | 0 |
A prospective cohort study to evaluate peridomestic infection as a determinant of dengue transmission
Results indicating a high infection rate among the exposed subjects would justify the application of peridomestic control measures and call for an evaluation of alternate causes for insufficient program impact. On the other hand, a low incidence of peridomestic-infected subjects would support the hypothesis that infection occurs outside the domicile, and would thus explain why the vector control measures applied in the past have exerted such a li…
Original Article
Aim Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful pr…
Novel methods improve prediction of species’ distributions from occurrence data
Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, c…
No prominent works on this page.
Novel methods improve prediction of species’ distributions from occurrence data
Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, c…
Original Article
Aim Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful pr…
A prospective cohort study to evaluate peridomestic infection as a determinant of dengue transmission
Results indicating a high infection rate among the exposed subjects would justify the application of peridomestic control measures and call for an evaluation of alternate causes for insufficient program impact. On the other hand, a low incidence of peridomestic-infected subjects would support the hypothesis that infection occurs outside the domicile, and would thus explain why the vector control measures applied in the past have exerted such a li…
Biology (2 works) · Computer Science (2 works) · Ecology (2 works) · Ecology and Vegetation Dynamics Studies (2 works) · Environmental niche modelling (2 works) · Habitat (2 works) · Species distribution (2 works) · Species Distribution and Climate Change (2 works) · Artificial Intelligence (1 work) · Asymptomatic (1 work)