18 resultados para Design and Geometry


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Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.

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Personalized medicine is a challenging research area in paediatric treatments. Elaborating new paediatric formulations when no commercial forms are available is a common practice in pharmacy laboratories; among these, oral liquid formulations are the most common. But due to the lack of specialized equipment, frequently studies to assure the efficiency and safety of the final medicine cannot be carried out. Thus the purpose of this work was the development, characterization and stability evaluation of two oral formulations of sildenafil for the treatment of neonatal persistent pulmonary hypertension. After the establishment of a standard operating procedure (SOP) and elaboration, the physicochemical stability parameters appearance, pH, particle size, rheological behaviour and drug content of formulations were evaluated at three different temperatures for 90 days. Equally, prediction of long term stability, as well as, microbiological stability was performed. Formulations resulted in a suspension and a solution slightly coloured exhibiting fruity odour. Formulation I (suspension) exhibited the best physicochemical properties including Newtonian behaviour and uniformity of API content above 90% to assure an exact dosification process.

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Depression is a major cause of disability and disease with significant costs to the health system and for the whole society. Regarding the treatment, in recent years has questioned the effectiveness of antidepressant drugs, with a recognition that although depressive disorders tend to improve with these treatments, residual symptoms seems to be still the norm, which is associated with the risk of new episodes or relapses, and faster its appearance. Otherwise many of the specialized clinical guidelines, propose a based on stepped-care model intervention, prioritizing less intrusive actions, including low-intensity psychosocial-interventions.