2 resultados para Random Number Generation

em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal


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Protein-based polymers are present in a wide variety of organisms fulfilling structural and mechanical roles. Advances in protein engineering and recombinant DNA technology allow the design and production of recombinant protein-based polymers (rPBPs) with an absolute control of its composition. Although the application of recombinant proteins as biomaterials is still an emerging technology, the possibilities are limitless and far superior to natural or synthetic materials, as the complexity of the structural design can be fully customized. In this work, we report the electrospinning of two new genetically engineered silk-elastin-like proteins (SELPs) consisting of alternate silk- and elastin-like blocks. Electrospinning was performed with formic acid and aqueous solutions at different concentrations without addition of further agents. The size and morphology of the electrospun structures was characterized by scanning electron microscopy showing to be dependent of concentration and solvent used. Treatment with air saturated with methanol was employed to stabilize the structure and promote water insolubility through a time-dependent conversion of random coils into β-sheets (FTIR). The resultant methanol-treated electrospun mats were characterized for swelling degree (570-720%), water vapour transmission rate (1083 g/m2/day) and mechanical properties (modulus of elasticity of ~126 MPa). Furthermore, the methanol-treated SELP fiber mats showed no cytotoxicity and were able to support adhesion and proliferation of normal human skin fibroblasts. Adhesion was characterized by a filopodia-mediated mechanism. These results demonstrate that SELP fiber mats can provide promising solutions for the development of novel biomaterials suitable for tissue engineering applications.

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The paper proposes a methodology especially focused on the generation of strategic plans of action, emphasizing the relevance of having a structured timeframe classification for the actions. The methodology explicitly recognizes the relevance of long-term goals as strategic drivers, which must insure that the complex system is capable to effectively respond to changes in the environment. In addition, the methodology employs engineering systems techniques in order to understand the inner working of the system and to build up alternative plans of action. Due to these different aspects, the proposed approach features higher flexibility compared to traditional methods. The validity and effectiveness of the methodology has been demonstrated by analyzing an airline company composed by 5 subsystems with the aim of defining a plan of action for the next 5 years, which can either: improve efficiency, redefine mission or increase revenues.