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From the literature, it was noted that the observed frontier energy values of these compounds are encouragingly matching to the frontier energy values of perylene diimide (PDI) and indandione derivative based non-fullerene acceptors, thus, these compounds pave the way for their potential applications in solar cells.
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While SFA is a parametric technique which uses a regression model to estimate the production or cost frontier, DEA is a non-parametric method that uses linear programming techniques to construct a piecewise frontier over the observed data.
Two estimation methods are used: 1) minimizing the squared difference between the observed records and the modeled biological frontier and 2) using extreme value theory to estimate the biological frontier that maximizes the probability of observing the existing world records by age.
The efficiency of each observation is measured by calculating the distance between the observed level of production and the production frontier as solutions of a linear programming problem.
In the context of this paper, the null hypothesis states that, regarding the observed metric, two different algorithms produce equivalent Pareto frontiers.
The actual cost efficiency measure (CE) is derived by the radial distance between the observed hospital's resources-services correspondence to the "best practice" frontier.
As we illustrate in Algorithm 1, we traverse the frontier starting from the plan that uses minimum resources and at each step we try to improve the observed makespan and monetary cost.
The observed changes seem clear.
The mutation cosegregated with the observed phenotype.
The observed eGFP decay kinetic was heterogeneous.
The observed differences were not statistically significant.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com