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glycerylmonooleate (GMO), Glycerylmonolinoleate (GML), Plurol® (polyglycerol 3-dioleate), Soya phosphatidylcholine (Soya PC), Dipalmitoyl-phosphatidylcholine (DPPC) and Dipalmitoyl- phosphatidylglycerol (DPPG) were screened for their ability to form cubosomes and the formed particles were optimized for controlled delivery using ondansetron as a model drug.
The drilling parameters such as feed rate, spindle speed, drill material and wt.% of B4C particles were optimized based on multiple performance characteristics including thrust force, torque and surface roughness.
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For each application, the injected dosage of the particles was optimized.
The ideal content of nano-CaCO3 particles was optimized through the morphologies observation.
The horizontal distance between two metal particles is optimized in simulations and a perfect absorption resonance peak is achieved due to the strong coupling of LSP modes.
Influence of process variables during polymer particle formation were optimized by using half-factorial design.
Particle characteristics were optimized to keep the encapsulated PCs viable for at least two weeks.
Afterward, the coefficients associated with the parameters in the NLRA model were optimized using optimization particle swarm-genetic algorithm.
An optimization mathematical model of cutting parameters was also established for cutting efficiency, operation parameters were optimized by particle swarm optimization, and the pump output was also optimized.
The deposition parameters, including the nanofluid solvent, additive, particle size, current, and voltage were optimized using test flat substrates of T91 ferritic martensitic steel.
Two operating solvent extraction conditions, i.e. average particle size and extraction time, were optimized by a response surface method using Box Behnken design to obtain high oil yields.
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CEO of Professional Science Editing for Scientists @ prosciediting.com