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This study presents the impact of uncertain data on the solution obtained by using a superstructure-based optimization approach in synthesis and design of biorefinery processing networks.
Moreover, the information encoded in the NMR and CD spectra of Ln3+ complexes may be used to extract original data on the solution stereochemistry of organic molecules used as ligands.
The blue dotted SAXS profile in Fig. 2b (second from top panel) was obtained on a solution of G1T-duplex with essentially the same DNA concentration (≈240 mg ml−1) as for the data on the solution of G20T-duplex shown in the same panel.
Data on the solution samples were measured in fluorescence mode using a Canberra 30-element solid-state Ge detector.
Fe K-edge XAS data on the solution samples were measured on beamline 7-3, whish is the standard biological solution XAS beamline at SSRL under standard ring conditions of 3 GeV and ∼350 mA ring current.
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In this section, we will present some results on the boundedness, uniqueness, and continuous dependence on initial data of the solutions of the Volterra-Fredholm type difference equation shown in (1).
The investigation in [1] showed that the continuous dependence on the initial data of the solutions to the compressible Navier-Stokes equations with vacuum failed.
Then, in Section 3, we investigate a certain fractional differential equation, in which the boundedness, uniqueness, and continuous dependence on initial data for the solution to the fractional differential equation are investigated by use of the generalized Gronwall-type inequalities established.
We solve it by a branch-and-bound algorithm based on a piecewise-linear overestimate of the objective function and a heuristic algorithm which iteratively applies the standard fixed-demand model and a demand-estimation model, feeding each one with data based on the solution obtained from the other one at the previous iteration.
Because the statistics relating the input data to the solution depend on the measured quantity, SNAPHU incorporates three built-in statistical models, for topography data, deformation data, and smooth generic data.
end{aligned} This implies the continuous dependence on the initial data for the solution which generates a continuous process ({tilde{U}(cdot,cdot )}).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com