Effects of home environment and center-based child care quality on children’s

This study examined the joint effects of home environment and center-based child care quality on children’s language, communication, and early literacy development, while also considering prior developmental level. Participants were 95 children (46 boys), assessed as toddlers (mean age = 26.33 months;Time 1) and preschoolers (mean age = 68.71 months; Time 2) and their families. At both times, children attended center-based child care classrooms in the metropolitan area of Porto, Portugal. Results from hierarchical linear models indicated that home environment and preschool quality, but not center-based toddler child care quality, were associated with children’s language and literacy outcomes at Time 2. Moreover, the quality of preschool classrooms moderated the association between home environment quality and children’s language and early literacy skills – but not communication skills – at Time 2, suggesting the positive cumulative effects of home environment and preschool quality. Findings further support the existence of a detrimental effect of low preschool quality on children’s language and early literacy outcomes: positive associations among home environment quality and children’s developmental outcomes were found to reduce substantially when children attended low-quality preschool classrooms.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Reported missing - learners in SLA/EFL research

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