Brigida Teixeira

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We have improved the ArtiSynth biomechanical modeling toolkit to meet new challenges in oral, pharyngeal and laryngeal modeling. Our team’s current research efforts have focused on four important developments: 1. patient specific modeling, 2. updating the ArtiSynth simulation engine to support integrated soft and hard tissue models, 3. inverse modeling(More)
BACKGROUND Intravenous pantoprazole is often administered inappropriately to hospitalized patients who can take oral medications. AIM To compare the antisecretory effects of oral rabeprazole and intravenous pantoprazole in healthy subjects. METHODS In a double-blind, double-dummy, two-way crossover study, 38 Helicobacter pylori-negative volunteers were(More)
This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players' characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market(More)
e19503 Background: New Tx options, including IMiDs [thalidomide, lenalidomide (Revlimid)] and bortezomib (Bz) (Velcade), have in the last few years become available on the market or as investigational agents in Canada for relapsed or refractory MM. These new agents are changing the Tx pattern and the clinical outcome of this disease. METHODS This(More)
e19535 Background: New Tx options have become available on the market or as investigational agents in Canada for relapsed/refractory MM in the last few years. These new Tx options include IMiDs [thalidomide, lenalidomide (Revlimid)] and a proteosome inhibitor [bortezomib (Velcade)]. These new agents are changing both the Tx patterns as well as the clinical(More)
This paper presents a proposal for the use of the Hybrid Fuzzy Inference System algorithm (HyFIS) as solar intensity forecast mechanism. Fuzzy Inference Systems (FIS) are used to solve regression problems in various contexts. The HyFIS is a method based on FIS with the particular advantage of combining fuzzy concepts with Artificial Neural Networks (ANN),(More)
Forecasting the electricity consumption is one of the most challenging tasks for energy domain stakeholders. Having reliable electricity consumption forecasts can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study regarding the forecast of electricity consumption using a(More)
Reliable consumption forecasts are crucial in several aspects of power and energy systems, e.g. to take advantage of the full potential of flexibility from consumers and to support the management from operators. With this need, several methodologies for electricity forecasting have emerged. However, the study of correlated external variables, such as(More)
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