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At full flowering, floral visitor insects were sampled using an entomological net.
Cell-autonomous bistable networks have been previously sampled using an evolutionary algorithm.
Climbers, trees, shrubs and herbs were sampled using an adapted cover pin frame approach.
In this paper we demonstrate that multi-modal probability distribution functions (PDFs) may be efficiently sampled using an algorithm originally developed for numerical integration by Monte Carlo methods.
Speed data regarding individual drivers traveling on selected two-lane rural road sections were sampled using an on-board GPS system.
In the case of BP B, the foam was sampled using an inspection shaft, whereas in the case of BP C, both the outlet of the recirculation pump and the drain of every digester were employed.
Similar(34)
Households were then systematically sampled using a random starting point and sampling interval of n = 3.
Villages were sampled using a randomized cluster design.
During the course of the experiment, peritoneal fluid and blood were sampled using a standardized protocol.
Twenty maternity colonies were sampled using a non-invasive approach based on droppings.
The posterior parameter pdf is sampled using a parallel and adaptive Markov Chain Monte Carlo (MCMC) algorithm.
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