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By means of a factorial design, the variables with more influence in the sampling have been optimized: sampling temperature, sampling flow and composition of the adsorbent.
sample_temperature is the temperature sampling function, decreasing with k.
To address these variations, a proper scheme of temperature sampling needs to be used.
At the Teakettle Experimental Forest we set up 17 individual temperature sampling locations for calibration and 29 temperature sampling locations for verification using HOBO® (Onset, http://www.onsetcomp.com) data loggers to record temperature every 10 minutes beginning in August 2011.
This part discusses the details of the important functions and configurations of Algorithm 3. sample_temperature is the temperature sampling function, decreasing with k.
Spatial autocorrelation among the temperature sampling locations was evaluated for dispersion and clustering patterns with respect to distance using Ripley's K function with 99 permutations (Bailey and Gatrell 1995; Boots and Getis 1988).
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Different sampling temperatures, sampling times and elution solvents were investigated.
At every temperature sampled removing the strap results in an acceleration of closure compared to WT and an overall loss in temperature dependence.
Several finite-temperature sampling methods, including parallel tempering Monte Carlo and flat-histogram approaches, can also be used efficiently to locate low-energy structures.
To avoid pseudoreplication, we analyzed temperatures sampled repeatedly from the same individuals in linear mixed effect models with a random effect "Individual" [63].
The optimum sintering temperature samples were selected for characterization.
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