Lingüística de corpus e estudos da tradução

O objectivo principal deste ensaio é discutir o interesse crescente que os Estudos da Tradução tem expressado acerca da Lingüística de Corpus e seu importante papel para a investigação do fenómeno tradutório. O ensaio apresenta os primeiros trabalhos na interface entre corpora e tradução e como a disciplina dos Estudos da Tradução de base em corpus evoluiu na última década. Uma atenção mais pontual é dada à noção de estudos em corpus de pequena dimensão e sua influência no campo das pesquisas em tradução no Brasil. Além disso, o ensaio explora como o conceito de representatividade tem recebido definições diferentes nos estudos dos fenómenos tradutórios de base em corpus.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.