Genetic diversity among air yam (dioscorea bulbifera) varieties based on single sequence repeat markers

Dioscorea is the largest genus in the Dioscoreaceae family, and includes a number of economically important species including the air yam, D. bulbifera L. This study aimed to develop new single sequence repeat primers and characterize the genetic diversity of local varieties that originated in several municipalities of Brazil. We developed an enriched genomic library for D. bulbifera resulting in seven primers, six of which were polymorphic, and added four polymorphic loci developed for other Dioscorea species. This resulted in 10 polymorphic primers to evaluate 42 air yam accessions. Thirty-three alleles (bands) were found, with an average of 3.3 alleles per locus. The discrimination power ranged from 0.113 to 0.834, with an average of 0.595. Both principal coordinate and cluster analyses (using the Jaccard Index) failed to clearly separate the accessions according to their origins. However, the 13 accessions from Conceição dos Ouros, Minas Gerais State were clustered above zero on the principal coordinate 2 axis, and were also clustered into one subgroup in the cluster analysis. Accessions from Ubatuba, São Paulo State were clustered below zero on the same principal coordinate 2 axis, except for one accession, although they were scattered in several subgroups in the cluster analysis. Therefore, we found little spatial structure in the accessions, although those from Conceição dos Ouros and Ubatuba exhibited some spatial structure, and that there is a considerable level of genetic diversity in D. bulbifera maintained by traditional farmers in Brazil152CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPnão tem2007/04805-

Efficient exploration of availability models guided by failure distances

Recently, a method to bound the steady-state availability using the failure distance concept has been proposed. In this paper we refine that method by introducing state space exploration techniques. In the methods proposed here, the state space is incrementally generated based on the contributions to the steady-state availability band of the states in the frontier of the currently generated state space. Several state space exploration algorithms are evaluated in terms of bounds quality and memory and CPU time requirements. The more efficient seems to be a waved algorithm which expands transition groups. We compare our new methods with the method based on the failure distance concept without state exploration and a method proposed by Souza e Silva and Ochoa which uses state space exploration but does not use the failure distance concept. Using typical examples we show that the methods proposed here can be significantly more efficient than any of the previous methods.Postprint (published version

Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs

International audienceGravitational wave (GW) events detectable by LIGO and Virgo have several possible progenitors, including black hole mergers, neutron star mergers, black hole–neutron star mergers, supernovae, and cosmic string cusps. A subset of GW events is expected to produce electromagnetic (EM) emission that, once detected, will provide complementary information about their astrophysical context. To that end, the LIGO–Virgo Collaboration (LVC) sends GW candidate alerts to the astronomical community so that searches for their EM counterparts can be pursued. The DESGW group, consisting of members of the Dark Energy Survey (DES), the LVC, and other members of the astronomical community, uses the Dark Energy Camera (DECam) to perform a search and discovery program for optical signatures of LVC GW events. DESGW aims to use a sample of GW events as standard sirens for cosmology. Due to the short decay timescale of the expected EM counterparts and the need to quickly eliminate survey areas with no counterpart candidates, it is critical to complete the initial analysis of each night’s images as quickly as possible. We discuss our search area determination, imaging pipeline, and candidate selection processes. We review results from the DESGW program during the first two LIGO–Virgo observing campaigns and introduce other science applications that our pipeline enables