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|Title:||Isoenzyme variability of five principal triatomine vector species of Chagas disease in Mexico|
|Abstract:||In order to improve the performance of solar energy systems, accurate modeling of current vs. voltage (I-V) characteristics of solar cells has attracted the attention of various researches. The main drawback in accurate modeling is the lack of information about the precise parameter values which indeed characterize the solar cell. Since such parameters cannot be extracted from the datasheet specifications, an optimization technique is necessary to adjust experimental data to the solar cell model. Considering the I-V characteristics of solar cells, the optimization task involves the solution of complex non-linear and multi-modal objective functions. Several optimization approaches have been proposed to identify the parameters of solar cells. However, most of them obtain sub-optimal solutions due to their premature convergence and their difficulty to overcome local minima in multi-modal problems. This paper proposes the use of the ABC (artificial bee colony) algorithm to accurately identify the solar cells' parameters. The ABC algorithm is an evolutionary method inspired by the intelligent foraging behavior of honey bees. In comparison with other evolutionary algorithms, ABC exhibits a better search capacity to face multi-modal objective functions. In order to illustrate the proficiency of the proposed approach, it is compared to other well-known optimization methods. Experimental results demonstrate the high performance of the proposed method in terms of robustness and accuracy. " 2014 Elsevier Ltd.",,,,,,"10.1016/j.energy.2014.05.011",,,"http://hdl.handle.net/20.500.12104/43477","http://www.scopus.com/inward/record.url?eid=2-s2.0-84904191803&partnerID=40&md5=e4e35d3291c937ca11b55871ad3ede84",,,,,,,,"Energy",,"93|
WOS",,,,,,"Artificial bee colony; Photo voltaic cells; Solar cell modeling",,,,,,"Parameter identification of solar cells using artificial bee colony optimization",,"Article" "44188","123456789/35008",,"Flores, A., UNAM, Inst. Invest. Biomed., AP 70228, C., México, Mexico; Gastélum, E.M., Universidad de Guadalajara, Depto. Salud Pub. Ctro. Univ. C., Jalisco, Mexico; Bosseno, M.-F., Inst. Rech. pour le D., UR 008, Pathogenie T., Montpellier, France; Ordoñez, R., Ctr. for Infectious Disease Research, Natl. Inst. Pub. Hlth., C., Morelos, Mexico; Kasten, F.L., Universidad de Guadalajara, Depto. Salud Pub. Ctro. Univ. C., Jalisco, Mexico; Espinoza, B., UNAM, Inst. Invest. Biomed., AP 70228, C., México, Mexico; Ramsey, J., Ctr. for Infectious Disease Research, Natl. Inst. Pub. Hlth., C., Morelos, Mexico; Breni-re, S.F., Inst. Rech. pour le D., UR 008, Pathogenie T., Montpellier, France",,"Flores, A.
Breniere, S.F.",,"2001",,"Triatoma barberi, T. dimidiata, T. longipennis, T. pallidipennis and T. picturata, all key Chagas disease vectors in Mexico, were analysed by multilocus enzyme electrophoresis (MLEE) at 17 putative loci. The majority of insect specimens studied were collected from domestic and peridomestic structures from multiple geographic locations while others were collected from sylvatic areas. T. barberi was the least polymorphic species (P(0.95)=0.18), with polymorphism rates of the other species ranging from 0.29 to 0.50. T. barberi, a member of the protracta complex, clustered apart from the other studied species by Nei's genetic distance with >1.36, and at least eight loci were found to be diagnostic for this species. T. dimidiata was more related to T. longipennis, T. pallidipennis and T. picturata (phyllosoma complex) than to T. barberi, with a genetic distance averaging 0.36 with the phyllosoma complex species. In contrast, the genetic distances between the three phyllosoma complex species were not significantly different from zero, and there were no species-specific loci differentiating among them. The results strongly support the grouping of these three species in one complex, separate from the two other species studied. " 2001 Elsevier Science B.V.
|Appears in Collections:||Producción científica UdeG|
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