Sentence examples for flexibility for modification from inspiring English sources

Exact(5)

In the module design, flexibility for modification is maximized through the use of Complex Programmable Logic Devices.

This protocol allows for flexibility for modification of formulae and parameters without using anything more complicated than Microsoft Excel.

On the other hand, low transfection efficiency of nonviral vectors undermines their high flexibility for modification, low immunogenicity, and easy preparation.

The main advantages of OLP are its reusable code, flexibility for modification, ability to generate complex paths, and reduction in production downtime in the programming phase for setup of a new part.

Recombinant retroviruses provide highly efficient gene delivery and the potential for sustained gene expression, but suffer from significant disadvantages including low titer, expensive production, poor stability and limited flexibility for modification of tropism.

Similar(54)

The more flexibility for modifications is allowed, the more likely a model will be adopted by the beneficiaries and community.

We developed a semi structured interview guide for the FGDs with appropriate flexibility for modifications for the different groups (Table  4).

The model system has been re-designed to increase its flexibility for the modification and extension of its component models.

The flexibility for chemical modification imparted by the PEG structure and its nontoxic nature can be effectively manipulated to fabricate mechanically stable biomimetic hybrid scaffolds based on natural polymers for TE applications.

Robust topology design methods are used not only to design material topologies that are relatively insensitive to manufacturing-related imperfections but also to systematically and intentionally create topological designs with built-in flexibility for subsequent modification.

The subdivision of the complete modeling process in QSAR modeling workflow architecture provides several advantages including (a) it reduces the complexity of modeling framework (b) improves the understanding of the implemented machine learning procedure and (c) increases the flexibility for future modification of the workflow.

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