Characterization of middle-ear condition of Oporto daycare children up-to 3 years-old: A cross sectional study

Objective The aim of this study was to determine tympanometric values of children who attend Oporto daycare centers and further analyze any relations with host and environmental factors. Methods Cross sectional study in a randomly selected sample of 117 daycare children up-to 3-years old from Oporto. Tympanometric measures were collected. Results Children presented in left ear (LE) a mean peak pressure (PP) of −156.53 daPa and a mean compliance of 0.16 cm3. Right ear (RE) revealed a PP of −145.61 daPa and a compliance of 0.19 cm3. Normal tympanograms (type A) had a lower frequency than abnormal tympanograms (type B and type C). There was a positive association between age and compliance (LE: p = 0.016; RE: p = 0.013) and between the presence of rhinorrhea and PP (LE: p = 0.002; RE: p < 0.05). Abnormal tympanograms were more frequent in Spring (RE: p = 0.009), in younger children (LE: p = 0.03) and in children that had rhinorrhea (LE: p = 0.002; RE: p = 0.044). Healthy children had a mean PP of −125.19 daPa and a mean compliance of 0.21 cm3 in LE and a mean PP of −144.27 daPa and a mean compliance of 0.22 cm3 in RE. Conclusion Tympanometric measures presented in this paper may be applicable to Oporto daycare children up-to 3 years-old. Most of daycare children revealed abnormal tympanograms. Age, rhinorrhea and season influenced children's middle-ear condition.

Numerical and experimental analyses of biocomposites reinforced with natural fibres

n the last decades the biocomposites have been widely used in the construction, automobile and aerospace industries. Not only the interface transition zone (ITZ) but also the heterogeneity of natural fibres affects the mechanical behaviour of these composites. This work focuses on the numerical and experimental analyses of a polymeric composite fabricated with epoxy resin and unidirectional sisal and banana fibres. A three-dimensional model was set to analyze the composites using the elastic properties of the individual phases. In addition, a two-dimensional model was set taking into account the effective composite properties obtained by micromechanical models. A tensile testing was performed to validate the numerical analyses and evaluating the interface condition of the constitutive phases.

Reason Maintenance Systems: Tools for Foundations-based Belief Revision

Dynamic and distributed environments are hard to model since they suffer from unexpected changes, incomplete knowledge, and conflicting perspectives and, thus, call for appropriate knowledge representation and reasoning (KRR) systems. Such KRR systems must handle sets of dynamic beliefs, be sensitive to communicated and perceived changes in the environment and, consequently, may have to drop current beliefs in face of new findings or disregard any new data that conflicts with stronger convictions held by the system. Not only do they need to represent and reason with beliefs, but also they must perform belief revision to maintain the overall consistency of the knowledge base. One way of developing such systems is to use reason maintenance systems (RMS). In this paper we provide an overview of the most representative types of RMS, which are also known as truth maintenance systems (TMS), which are computational instances of the foundations-based theory of belief revision. An RMS module works together with a problem solver. The latter feeds the RMS with assumptions (core beliefs) and conclusions (derived beliefs), which are accompanied by their respective foundations. The role of the RMS module is to store the beliefs, associate with each belief (core or derived belief) the corresponding set of supporting foundations and maintain the consistency of the overall reasoning by keeping, for each represented belief, the current supporting justifications. Two major approaches are used to reason maintenance: single-and multiple-context reasoning systems. Although in the single-context systems, each belief is associated to the beliefs that directly generated it—the justification-based TMS (JTMS) or the logic-based TMS (LTMS), in the multiple context counterparts, each belief is associated with the minimal set of assumptions from which it can be inferred—the assumption-based TMS (ATMS) or the multiple belief reasoner (MBR).