A novel vortex flow reactor for the purification of B-phycoerythrin from Porphyridium cruentum

The purification of B-phycoerythrin from a concentrated extract of disrupted Porphyridium cruentum cells was carried out using a new vortex flow reactor design for protein purification. The reactor behaved as an expanded bed in the laminar vortices flow regime where the Streamline DEAE resin was expanded by the axial flow and stabilized by the vortex flow. After the broth culture was centrifuged and resuspended in the adsorption buffer, the concentrated extract of disrupted cells was directly loaded into the vortex flow reactor. The purification of B-phycoerythrin was carried out in two steps: adsorption in the expanded bed and elution from the settled bed. 142.0 mg of B-phycoerythrin was eluted representing a total recovery yield of 86.6%. Prior to B-phycoerythrin purification, the protein adsorption of the vortex flow reactor was characterized through hydrodynamic studies and a dynamic capacity measurement using a standard protein.

Multi-objective ant colony optimization for requirements selection

The selection of a set of requirements between all the requirements previously defined by customers is an important process, repeated at the beginning of each development step when an incremental or agile software development approach is adopted. The set of selected requirements will be developed during the actual iteration. This selection problem can be reformulated as a search problem, allowing its treatment with metaheuristic optimization techniques. This paper studies how to apply Ant Colony Optimization algorithms to select requirements. First, we describe this problem formally extending an earlier version of the problem, and introduce a method based on Ant Colony System to find a variety of efficient solutions. The performance achieved by the Ant Colony System is compared with that of Greedy Randomized Adaptive Search Procedure and Non-dominated Sorting Genetic Algorithm, by means of computational experiments carried out on two instances of the problem constructed from data provided by the experts.