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      Experience has a limited effect on humans’ ability to predict the outcome of social interactions in children, dogs and macaques

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          Abstract

          The ability to predict others’ behaviour represents a crucial mechanism which allows individuals to react faster and more appropriately. To date, several studies have investigated humans’ ability to predict conspecifics’ behaviour, but little is known on our ability to predict behaviour in other species. Here, we aimed to test humans’ ability to predict social behaviour in dogs, macaques and humans, and assess the role played by experience and evolution on the emergence of this ability. For this purpose, we presented participants with short videoclips of real-life social interactions in dog, child and macaque dyads, and then asked them to predict the outcome of the observed interactions (i.e. aggressive, neutral or playful). Participants were selected according to their previous species-specific experience with dogs, children and non-human primates. Our results showed a limited effect of experience on the ability to predict the outcome of social interactions, which was mainly restricted to macaques. Moreover, we found no support to the co-domestication hypothesis, in that participants were not especially skilled at predicting dog behaviour. Finally, aggressive outcomes in dogs were predicted significantly worse than playful or neutral ones. Based on our findings, we suggest possible lines for future research, like the inclusion of other primate species and the assessment of cultural factors on the ability to predict behaviour across species.

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          glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling

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            Occurrence of the potent mutagens 2- nitrobenzanthrone and 3-nitrobenzanthrone in fine airborne particles

            Polycyclic aromatic compounds (PACs) are known due to their mutagenic activity. Among them, 2-nitrobenzanthrone (2-NBA) and 3-nitrobenzanthrone (3-NBA) are considered as two of the most potent mutagens found in atmospheric particles. In the present study 2-NBA, 3-NBA and selected PAHs and Nitro-PAHs were determined in fine particle samples (PM 2.5) collected in a bus station and an outdoor site. The fuel used by buses was a diesel-biodiesel (96:4) blend and light-duty vehicles run with any ethanol-to-gasoline proportion. The concentrations of 2-NBA and 3-NBA were, on average, under 14.8 µg g−1 and 4.39 µg g−1, respectively. In order to access the main sources and formation routes of these compounds, we performed ternary correlations and multivariate statistical analyses. The main sources for the studied compounds in the bus station were diesel/biodiesel exhaust followed by floor resuspension. In the coastal site, vehicular emission, photochemical formation and wood combustion were the main sources for 2-NBA and 3-NBA as well as the other PACs. Incremental lifetime cancer risk (ILCR) were calculated for both places, which presented low values, showing low cancer risk incidence although the ILCR values for the bus station were around 2.5 times higher than the ILCR from the coastal site.
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              Random effects structure for confirmatory hypothesis testing: Keep it maximal.

              Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F 1 and F 2 tests, and in many cases, even worse than F 1 alone. Maximal LMEMs should be the 'gold standard' for confirmatory hypothesis testing in psycholinguistics and beyond.
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                Author and article information

                Contributors
                amici@eva.mpg.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                4 December 2020
                4 December 2020
                2020
                : 10
                : 21240
                Affiliations
                [1 ]GRID grid.5319.e, ISNI 0000 0001 2179 7512, Fundació UdG: Innovació I Formació, , Universitat de Girona, ; Carrer Pic de Peguera 11, 17003 Girona, Spain
                [2 ]GRID grid.9613.d, ISNI 0000 0001 1939 2794, Institute of Psychology, , Friedrich Schiller University Jena, ; Leutragraben 1, 07743 Jena, Germany
                [3 ]GRID grid.419526.d, ISNI 0000 0000 9859 7917, Max Planck Research Group ‘Naturalistic Social Cognition’, , Max Planck Institute for Human Development, ; Berlin, Germany
                [4 ]GRID grid.469873.7, ISNI 0000 0004 4914 1197, Max-Planck-Institute for the Science of Human History, ; Jena, Germany
                [5 ]GRID grid.419518.0, ISNI 0000 0001 2159 1813, Department of Human Behavior, Ecology and Culture, Research Group “Primate Behavioural Ecology”, , Max Planck Institute for Evolutionary Anthropology, ; Leipzig, Germany
                [6 ]GRID grid.9647.c, ISNI 0000 0004 7669 9786, Institute of Biology, Behavioral Ecology Research Group, , University of Leipzig Faculty of Life Science, ; Leipzig, Germany
                Article
                78275
                10.1038/s41598-020-78275-5
                7718882
                33277580
                720e6cab-592f-4671-9800-5c70a6d06842
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 July 2020
                : 23 November 2020
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, Germany
                Award ID: AM 409/4-1
                Award Recipient :
                Funded by: Projekt DEAL
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                coevolution,animal behaviour
                Uncategorized
                coevolution, animal behaviour

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