Sewage sludge treated with metal nanomaterials inhibits earthworm reproduction more strongly than sludge treated with metal metals in bulk/salt forms

Earthworms were exposed to soils amended with sewage sludges from a wastewater treatment plant (WWTP) treated with nanomaterials (ENMs) or metal/ionic salts. Sewage sludges were generated with either no metal added to the WWTP influent (control), ionic ZnO, AgNO3 and bulk (micron sized) TiO2 added (ionic metal-treated) or ZnO, Ag and TiO2 ENMs added (ENM-treated). A sandy-loam soil was amended with the treated sewage sludge and aged in outdoor lysimeters for six months. Earthworms were exposed to the aged mixtures and a dilution of the mixtures (using control soil–sludge mix). Separate earthworm exposures to as-synthesized ENM and ionic metals salts (Zn/Ag singly) were carried out in the same soil. Earthworm reproduction was depressed by 90% in the high-metal ENM treatment and by 22–27% in the ionic metal and low-metal ENM soil–sludge treatments. Based on total metal concentrations in the soil–sludges the as-synthesised metal salt and ENM exposures predicted Zn was driving observed toxicity in the soil–sludge more than Ag. Earthworms from the high-metal ENM treatment accumulated significantly more Ag than other treatments whereas total Zn concentrations in the earthworms were within the range for earthworm Zn regulation for all treatments. This study suggests that current Zn limits set to provide protection against ionic metal forms may not protect soil biota where metals are input to WWTP in the ENM form

Inclusion Bayes factors for mixed hierarchical diffusion decision models

Cognitive models provide a substantively meaningful quantitative description of latent cognitive processes. The quantitative formulation of these models supports cumulative theory building and enables strong empirical tests. However, the nonlinearity of these models and pervasive correlations among model parameters pose special challenges when applying cognitive models to data. Firstly, estimating cognitive models typically requires large hierarchical data sets that need to be accommodated by an appropriate statistical structure within the model. Secondly, statistical inference needs to appropriately account for model uncertainty to avoid overconfidence and biased parameter estimates. In the present work, we show how these challenges can be addressed through a combination of Bayesian hierarchical modeling and Bayesian model averaging. To illustrate these techniques, we apply the popular diffusion decision model to data from a collaborative selective influence study

From Naples 1963 to Rome 2013 - A brief review of how the International Research Group on Ostracoda (IRGO) developed as a social communication system

The 1st International Symposium on Ostracoda (ISO) was held in Naples (1963). The philosophy behind this symposium and the logical outcome of what is now known as the International Research Group on Ostracoda (IRGO) is here reviewed, namely ostracodology over the last 50 years is sociologically analysed. Three different and important historic moments for the scientific achievements of this domain are recognised. The first one, between about 1963-1983, is related to applied research for the oil industry as well as to the great interest in the better description of the marine environment by both zoologists and palaeontologists. Another important aspect during this period was the work by researchers dealing with Palaeozoic ostracods, who had their own discussion group, IRGPO. Gradually, the merger of this latter group with those dealing with post-Palaeozoic ostracods at various meetings improved communication between the two groups of specialists. A second period was approximately delineated between 1983 and 2003. During this time-slice, more emphasis was addressed to environmental research with topics such as the study of global events and long-term climate change. Ostracodologists profited also from the research "politics" within national and international programmes. Large international research teams emerged using new research methods. During the third period (2003-2013), communication and collaborative research reached a global dimension. Amongst the topics of research we cite the reconstruction of palaeoclimate using transfer functions, the building of large datasets of ostracod distributions for regional and intercontinental studies, and the implementation of actions that should lead to taxonomic harmonisation. Projects within which molecular biological techniques are routinely used, combined with sophisticated morphological information, expanded now in their importance. The documentation of the ostracod description improved through new techniques to visualise morphological details, which stimulated also communication between ostracodologists. Efforts of making available ostracod information through newsletters and electronic media are evoked

OSARI, an Open-Source Anticipated Response Inhibition Task

The stop-signal paradigm has become ubiquitous in investigations of inhibitory control. Tasks inspired by the paradigm, referredto as stop-signal tasks, require participants to make responses on go trials and to inhibit those responses when presented with astop-signal on stop trials. Currently, the most popular version of the stop-signal task is the ‘choice-reaction’ variant, whereparticipants make choice responses, but must inhibit those responses when presented with a stop-signal. An alternative to thechoice-reaction variant of the stop-signal task is the ‘anticipated response inhibition’ task. In anticipated response inhibition tasks,participants are required to make a planned response that coincides with a predictably timed event (such as lifting a finger from acomputer key to stop a filling bar at a predefined target). Anticipated response inhibition tasks have some advantages over themore traditional choice-reaction stop-signal tasks and are becoming increasingly popular. However, currently, there are noopenly available versions of the anticipated response inhibition task, limiting potential uptake. Here, we present an open-source,free, and ready-to-use version of the anticipated response inhibition task, which we refer to as the OSARI (the Open-SourceAnticipated Response Inhibition) task