Hierarchical self-assembly of new age surfactants, surface-active ionic liquids (SAILs) has attracted increasing interests because of its close resemblance to membrane mimetic structure and its application in drug delivery. Among these self-assembled structures, thermodynamically stable vesicular nanoaggregates are of great importance due to its structure that can carry both, hydrophilic and hydrophobic molecules within its core and bilayers, respectively. Here, we report the ester functionalized SAILs to synergistically interact with cholesterol, the natural sterol to transform the micellar nano-aggregates to the vesicular nano-aggregates with outstanding stability with dilution, pH, and temperature. The molecular self-assembly formed was studied through state of the art analytical techniques including small-angle neutron scattering (SANS) and fluorescence resonance energy transfer (FRET) upon varying the cholesterol/SAIL ratio. The thermodynamically stable vesicular nano-aggregates were further used as the nano-vehicles for the encapsulation and sustained release of the anticancer drugs, curcumin and 5-flurouracil. Results of the present study could pave way for the realistic drug delivery applications of these thermodynamically stable nano-aggregates and replace the traditional lipid based vesicle systems.
This paper describes Dimensional Ant Colony Optimization (DACO), a distributed algorithm that will be applied to solve traveling salesman problem (TSP). In an Any Colony System (ACS), a set of co-operating agents called ants co-operate to find the good solutions of TSPs. Ants co-operate using an indirect form of communication that is mediated by pheromone they deposited on the edges of the TSP graph when building solutions. The proposed system (Dimensional ACO) based on basic ACO algorithm with well defined distribution strategy in which entire search space area is initially being divided into N numbers of hyper-cubic quadrants where N is the dimension of entire search space area for updation of heuristic parameter of ACO and to improve the performance while solving TSP. From our experiments, this proposed algorithm has better performance than other standard bench mark algorithms.
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