929 resultados para Cyclic code


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This report gives an overview, background and progress on the implementation of the Veterans Counseling Program established pursuant to Iowa Code 35.12, as enacted by 2007 Iowa Acts, House FIle 817.

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Background: Maturation of amplitude-integrated electroencephalogram (aEEG) activity is influenced by both gestational age (GA) and postmenstrual age. It is not fully known how this process is influenced by cerebral lesions. Objective: To compare early aEEG developmental changes between preterm newborns with different degrees of cerebral lesions on cranial ultrasound (cUS). Methods: Prospective cohort study on preterm newborns with GA <32.0 weeks, undergoing continuous aEEG recording during the first 84 h after birth. aEEG characteristics were qualitatively and quantitatively evaluated using pre-established criteria. Based on cUS findings three groups were formed: normal (n = 78), mild (n = 20), and severe cerebral lesions (n = 6). Linear mixed models for repeated measures were used to analyze aEEG maturational trajectories. Results: 104 newborns with a mean GA (range) 29.5 (24.4-31.7) weeks, and birth weight 1,220 (580-2,020) g were recruited. Newborns with severe brain lesions started with similar aEEG scores and tendentially lower aEEG amplitudes than newborns without brain lesions, and showed a slower development of the cyclic activity (p < 0.001), but a more rapid increase of the maximum and minimum aEEG amplitudes (p = 0.002 and p = 0.04). Conclusions: Preterm infants with severe cerebral lesions manifest a maturational delay in the aEEG cyclic activity already early after birth, but show a catch-up of aEEG amplitudes to that of newborns without cerebral lesions. Changes in the maturational aEEG pattern may be a marker of severe neurological lesions in the preterm infant.

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Partint d'un projecte anterior anomenat Code, els objectius d'aquest projecte són: integrar l'aplicació en una eina de software, incorporar les noves versions de les llibreries GWT i Java, i escabilitzar l'aplicació a través de la tecnologia cloud computing concretament amb la infraestructura de Google App Engine