Clara Cordeiro

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Polymeric nanoparticles have revealed very effective in transmucosal delivery of proteins. Polysaccharides are among the most used materials for the production of these carriers, owing to their structural flexibility and propensity to evidence biocompatibility and biodegradability. In parallel, there is a preference for the use of mild methods for their(More)
Background Misuse of antibiotics gives rise to numerous individual and societal problems, among which antimicrobial resistance is currently a major worldwide concern. Understanding cultural features in the public’s attitudes and behaviours regarding antibiotics and their use is a prerequisite to developing effective educational interventions. Objective To(More)
Chitosan/carrageenan/tripolyphosphate nanoparticles were previously presented as holding potential for an application in transmucosal delivery of macromolecules, with tripolyphosphate demonstrating to contribute for both size reduction and stabilisation of the nanoparticles. This work was aimed at evaluating the capacity of the nanoparticles as protein(More)
The bootstrap methodology, initially proposed in independent situations, has revealed inefficient in the context of dependent data. Here, the estimation of population characteristics is more complex. This is what happens in the context of time series. There has been a great development in the area of resampling methods for dependent data. A revision of(More)
In this article the authors expose an automatic procedure that combines a very popular resampling technique, the Bootstrap methodology, with one of the most widely used forecasting methods, the exponential smoothing. The merge of these two approaches originates the Boot.EXPOS. The algorithm can be summarized as follow: Given a time series, it starts by(More)
The European Space Agency has acquired 10 years of data on the temporal and spatial distribution of phytoplankton biomass from the MEdium Resolution Imaging Spectrometer (MERIS) sensor for ocean color. The phytoplankton biomass was estimated with the MERIS product Algal Pigment Index 1 (API 1). Seasonal-Trend decomposition of time series based on Loess(More)
One of the main goals in times series analysis is to forecast future values. Many forecasting methods have been developed and the most successful are based on the concept of exponential smoothing, based on the principle of obtaining forecasts as weighted combinations of past observations. Classical procedures to obtain forecast intervals assume a known(More)
Time series analysis deals with records that are collected over time. The objectives of time series analysis depend on the applications, but one of the main goals is to predict future values of the series. These values depend, usually in a stochastic manner, on the observations available at present. Such dependence has to be considered when predicting the(More)
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