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A comprehensive dynamic model for the manipulator is derived with the assumed modes approach and the Lagrangian formulation.
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Molecular descriptors were computed following the TOPological Substructural MOlecular DEsign (TOPS-MODE) approach and correlated with β-CD complex stability constants by linear multivariate data analysis.
Numerical results (non-linear frequencies, vibration amplitudes and basic function contributions) of infinite shells associated to the first four mode shapes of free vibrations, are obtained, using a multi-mode approach and are summarized in tables.
The neural controller is designed as the main controller via dynamic sliding-mode approach, and the exponential compensator is designed to obtain a faster reaching time and a good robustness.
By making use of a normal mode approach and assuming specific forms for the product densities (characterizing the expected arrival rate of the impulses and their correlation) the formulae for the variances and cross-covariances of modal responses are derived.
The nonlinear equations of motion are obtained by the Lagrange equations with multi-mode approach, and are studied by using a code based on the pseudo-arclength continuation method.
The assumed mode approach and the Rayleigh Ritz approach are both used; the trial functions used in the mode expansion are the mode shapes of the vibrations in a vacuum and the solution is obtained as that of an eigenvalue problem.
By retaining the use of trypsin in the present study, the protein mixtures can be subjected to tryptic digestion, then split into two samples: one for traditional bottom-up/positive mode approach and the other processed in parallel using the carbamylation/negative mode UVPD strategy.
Full "rectification" of the QCSE occurs and the eigen values and eigen modes approach that of a square QW.
As the separation distance increases, the mode effective indices of the even and odd modes approach that of a single waveguide, leading to the smaller difference of mode effective indices for the even and odd modes.
The modes approach is based on Traxler et al. (2001).
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