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    Correlating the ancient Maya and modern european calendars with high-precision AMS 14C dating
    (London : Nature Publishing Group, 2013) Kennett, D.J.; Hajdas, I.; Culleton, B.J.; Belmecheri, S.; Martin, S.; Neff, H.; Awe, J.; Graham, H.V.; Freeman, K.H.; Newsom, L.; Lentz, D.L.; Anselmetti, F.S.; Robinson, M.; Marwan, N.; Southon, J.; Hodell, D.A.; Haug, G.H.
    The reasons for the development and collapse of Maya civilization remain controversial and historical events carved on stone monuments throughout this region provide a remarkable source of data about the rise and fall of these complex polities. Use of these records depends on correlating the Maya and European calendars so that they can be compared with climate and environmental datasets. Correlation constants can vary up to 1000 years and remain controversial.Wereport a series of high-resolution AMS14C dates on a wooden lintel collected from the Classic Period city of Tikal bearing Maya calendar dates. The radiocarbon dates were calibrated using a Bayesian statistical model and indicate that the dates were carved on the lintel betweenAD 658-696. This strongly supports the Goodman-Mart?nez-Thompson (GMT) correlation and the hypothesis that climate change played an important role in the development and demise of this complex civilization.
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    Probing the Statistical Properties of Unknown Texts: Application to the Voynich Manuscript
    (San Francisco, CA : Public Library of Science (PLoS), 2013) Amancio, D.R.; Altmann, E.G.; Rybski, D.; Oliveira Jr., O.N.; da Costa, L.F.
    While the use of statistical physics methods to analyze large corpora has been useful to unveil many patterns in texts, no comprehensive investigation has been performed on the interdependence between syntactic and semantic factors. In this study we propose a framework for determining whether a text (e.g., written in an unknown alphabet) is compatible with a natural language and to which language it could belong. The approach is based on three types of statistical measurements, i.e. obtained from first-order statistics of word properties in a text, from the topology of complex networks representing texts, and from intermittency concepts where text is treated as a time series. Comparative experiments were performed with the New Testament in 15 different languages and with distinct books in English and Portuguese in order to quantify the dependency of the different measurements on the language and on the story being told in the book. The metrics found to be informative in distinguishing real texts from their shuffled versions include assortativity, degree and selectivity of words. As an illustration, we analyze an undeciphered medieval manuscript known as the Voynich Manuscript. We show that it is mostly compatible with natural languages and incompatible with random texts. We also obtain candidates for keywords of the Voynich Manuscript which could be helpful in the effort of deciphering it. Because we were able to identify statistical measurements that are more dependent on the syntax than on the semantics, the framework may also serve for text analysis in language-dependent applications.
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    Change in the embedding dimension as an indicator of an approaching transition
    (San Francisco, CA : Public Library of Science (PLoS), 2014) Neuman, Y.; Marwan, N.; Cohen, Y.
    Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point.