Polymer Nanocomposites Based on Poly(ε-caprolactone), Hydroxyapatite and Graphene Oxide

Standard and hybrid polymer nanocomposites based on poly(ɛ-caprolactone) (PCL), hydroxyapatite (HAp) and graphene oxide (GO). The GO synthetized here is made up of multilayer graphene oxide (mGO), in which up to five layers are stacked and lateral size around of 1 µm. The nanocomposites (PCL/Hap, PCL/mGO and PCL/HAp/mGO) were prepared by melt mixing in a twin-screw extruder and characterized by mechanical test, transmission electron microscopy (TEM), infrared spectroscopy (FTIR), X-ray diffraction (XRD), contact angle (CA), surface zeta potential by streaming and cell proliferation. The HAp content was maintained at 20% (w/w) while mGO was used at three levels of content (0.05, 0.1, and 0.3 w/w). In terms of bulk properties, the presence of mGO even in very low content (0.05 to 0.3%) was very effective in order to increase mechanical properties of PCL (stress and strain at beak and tenacity) while HAp tends to decrease them. When the two fillers are inserted mGO act to recover the properties lost by the presence of HAp. TEM images showed single GO sheets very well dispersed alone or combined with HAp. For surface properties, significant changes have been achieved by the presence of mGO, HAp and mGO/HAp. The water contact angle drops to values below 90° for all nanocomposites making the material hydrophilic, but again by the presence of only 0.05% of mGO it was reached easily. Surface ξ-potential for all nanocomposite was lower than neat PCL. As a consequence of surface modifications improvements in cell proliferation ability could be also observed. All modification by the presence of GO point out these materials as excellent candidates to resorbable suture, drug delivery system, and bone graft substitutes.28331342COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP88887.310339/2018–002014/22840–3; 2012/50259–8; 2015/16591–

Uma proposta para a geração de amostras aleatórias nos problemas de simulação em modelos de planejamento A proposal for random sample generation in simulation problems of planning models

Um modelo de predição do preço da celulose foi ajustado usando-se o tempo e o preço defasado como co-variáveis. A partir das estimativas dos parâmetros obtidas, foram propostas 48 possíveis tendências futuras para o preço da celulose. Posteriormente, três métodos de simulação foram usados para predizer os valores futuros definidos pelas várias tendências: M1<FONT FACE=Symbol>Þ</FONT> Pcel.f = µ; M2 <FONT FACE=Symbol>Þ</FONT> Pcel.f = µ + épsilonf, e M3 µf + épsilonf, em que m é a parte sistemática do modelo, e e f corresponde ao componente estocástico. Para as simulações foram usados o método de Monte Carlo e a distribuição triangular. Para comparar os valores simulados pelos três métodos com os conhecidos valores futuros nas várias tendências, foi usada a diferença relativa média entre os valores. No caso da ausência de tendência, os métodos M1 e M2 foram satisfatórios, apesar de o método M2 incluir distúrbios ao redor da média. No caso de haver tendência real, o método M3 teve a melhor "performance", mesmo sendo influenciado pela acurácia na predição da tendência.<br>A cellulose price prediction model was adjusted using time and lagged price as covariates. From the model parameter estimates, 48 possible trends were proposed for future cellulose price. Following, three simulation methods were used to predict the future values defined by the various trends: M1<FONT FACE=Symbol>Þ</FONT> Pcel.f = µ; M2 <FONT FACE=Symbol>Þ</FONT> Pcel.f = µ + epsilonf, e M3 µf + epsilonf, where m is the systematic part and e f is the stochastic component. The Monte Carlo method and a triangular distribution were used for the simulation. To compare the values simulated by the methods and the future values of the various trends, the Average Relative Difference was used. In case of no trend, M1 and M2 were satisfactory, although M2 included disturbances around the mean. In the case of a real trend, M3 had the best performance, though it was influenced by the accuracy in the predicted trend