Influence of casting condition on the anisotropy of the fracture properties of Steel Fibre Reinforced Self-Compacting Concrete (SFRSCC)

Identification of the tensile constitutive behaviour of Fibre Reinforced Concrete (FRC) represents an important aspect of the design of structural elements using this material. Although an important step has been made with the introduction of guidance for the design with regular FRC in the recently published fib Model Code 2010, a better understanding of the behaviour of this material is still necessary, mainly for that with self-compacting properties. This work presents an experimental investigation employing Steel Fibre Self-Compacting Concrete (SFRSCC) to cast thin structural elements. A new test method is proposed for assessing the post-cracking behaviour and the results obtained with the proposed test method are compared with the ones resulted from the standard three-point bending tests (3PBT). Specimens extracted from a sandwich panel consisting of SFRSCC layers are also tested. The mechanical properties of SFRSCC are correlated to the fibre distribution by analysing the results obtained with the different tests. Finally, the stress-crack width constitutive law proposed by the fib Model Code 2010 is analysed in light of the experimental results.

Influence of river ecological condition on changes in physico-chemical water parameters along rivers

Dissertação de mestrado em Ecology

Postpartum Depression: Is it a condition affecting the mother-infant interaction and the development of the child across the first year of life?

Noting that maternal depression is common during a baby's first year, this study examined the interaction of depressed and non-depressed mother-child dyads. A sample of 26 first-time mothers with postpartum depression at the third month after birth and their 3-month-old infants was compared to a sample of 25 first-time mothers with no postpartum depression at the third month after birth and their 3-month-old infants. The observations were repeated at 6 months and again at 12 months postpartum. The samples were compared for differences in mother interaction behavior, mother's infant care, mother's concern with the baby, infant behavioral difficulties, infant mental and motor development, and infant behavior with the observer. Among the findings are the following: (1) depressed mothers' interaction behavior and care of their infants are less adequate than the non-depressed mothers' interaction behavior and care of their infants at 3, 6, and 12 months postpartum; (2) infants' interaction behaviors during feeding and face-to-face interaction with depressed mothers are less adequate than infants' interactions with non-depressed mothers at 3, 6, and 12 months postpartum; (3) mother-infant interactions are less adequate in the depressed mother dyads than the non-depressed dyads at 3, 6, and 12 months postpartum; (4) depressed mothers are less concerned about their infants than non-depressed mothers at 3, 6, and 12 months postpartum; (5) infants of depressed mothers have more behavioral difficulties at 3, 6, and 12 months postpartum than infants of non-depressed mothers; (6) infants of depressed mothers had lower mental and motor development rates at 6 and 12 months postpartum than infants of non-depressed mothers; and (7) infants of non-depressed mothers behaved in a more positive way with the observer than the infants of depressed mothers. (AS)

A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.