Neonate movement is synchronized with adult speech: interactional participation and language acquisition

As early as the first day of life, the human neonate moves in precise and sustained segments of movement that are synchronous with the articulated structure of adult speech. These observations suggest a view of development of the infant as a participant at the outset in multiple forms of interactional organization, rather than as an isolate.     

U-Pb ages from the neoproterozoic Doushantuo Formation, China

U-Pb zircon dates from volcanic ash beds within the Doushantuo Formation (China) indicate that its deposition occurred between 635 and 551 million years ago. The base records termination of the global-scale Marinoan glaciation and is coeval with similar dated rocks from Namibia, indicating synchronous deglaciation. Carbon isotopic and sequence-stratigraphic data imply that the spectacular animal fossils of the Doushantuo Formation are for the most part younger than 580 million years old. The uppermost Doushantuo Formation contains a pronounced negative carbonate carbon isotopic excursion, which we interpret as a global event at circa 551 million years ago.     

Discrimination of lithogenic and anthropogenic influences on topsoil magnetic susceptibility in Central Europe

The study was performed on the area of the three countries involved in the MAGPROX project (Poland, Czech Rep., Germany). In the first stage the basic map of magnetic susceptibility based on the field topsoil measurement was compiled with an average grid density of 10 km. In the second stage of the study, vertical distribution of magnetic susceptibility of ca. 600 topsoil cores (0.3 m long), collected over central Europe, was examined with respect to the anthropogenic or lithogenic influence on magnetic susceptibility of the soil surface, with the focus being on the interpretation of the areas showing high surface susceptibility values. The maximum values were mostly observed in depths of 3–4 cm. In general seven different types of susceptibility profiles from forest areas and one typical for urban soil are presented. They are a result of a combination of natural (litho- and pedogenic) and anthropogenic contributions. Our results prove that soil profiles, dominated by anthropogenic influence due to atmospherically deposited dust, are characterized by magnetically enhanced humuous layer, corresponding to layer with the highest concentration of heavy metals. Moreover, forest soils show in these cases higher magnetic susceptibility than soils in open areas (grassland, meadows or arable soils).     

Estimation of infection prevalence from correlated binomial samples

Infection prevalence in a population often is estimated from grouped binary data expressed as proportions. The groups can be families, herds, flocks, farms, etc. The observed number of cases generally is assumed to have a Binomial distribution and the estimate of prevalence is then the sample proportion of cases. However, the individual binary observations might not be independent--leading to overdispersion. The goal of this paper was to demonstrate random-effects models for the estimation of infection prevalence from data which are correlated and in particular, to illustrate a nonparametric random-effects model for this purpose. The nonparametric approach is a relatively recent addition to the random-effects class of models and does not appear to have been discussed previously in the veterinary epidemiology literature. The assumptions for a logistic-regression model with a nonparametric random effect were outlined. In a demonstration of the method on data relating to Salmonella infection in Irish pig herds, the nonparametric method resulted in the classification of herds into a small number of distinct prevalence groups (i.e. low, medium and high prevalence) and also estimated the relative frequency of each prevalence category in the population. We compared the estimates from a logistic model with a nonparametric distribution for the random effects with four alternative models: a logistic-regression model with no random effects, a marginal model using a generalised estimating equation (GEE) and two methods of fitting a Normally distributed random effect (the GLIMMIX macro and the NLMIXED procedure both in SAS). Parameter estimates from random-effects models are not readily interpretable in terms of prevalences. Therefore, we outlined two methods for calculating population-averaged estimates of prevalence from random-effects models: one using numerical integration and the other using Monte Carlo simulation.