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Exposure to LTE 2600 MHz microwaves is increasing very fast as new technologies and become accessible worldwide, and the smartphones being the main source of these waves. The aim of this study is to assess the thermal effect of 4G signals on rats. Forty adult Albino rats were used throughout the study, assigned as control and exposed groups, equally. Rats were kept in Plexiglas cages with intermittent exposure to LTE mobile-phone like signals at an average of 2h/day for up to 30 continuous days with SAR value of 0.982 W/kg. Infrared images were snapped immediately after the end of the exposure time, then one hour, two hours, and four hours later at a rate one collection/week during the study. IR images were analyzed by FLIR Tools software. The results exhibited variation in reflected skin temperatures in the exposed group compared to control images. Furthermore, the analysis of collected data revealed significant variations over the course of the study compared to the first week. The rise in skin temperature observed in response to exposure in the first week, which decreased gradually increased exposure and this drop in reflected skin temperature was significantly related to amount of exposure. The study concludes that the LTE 2600 MHz exposure under controlled laboratory conditions has a thermal effect on the rats.

We investigated the evolution and transformation of scientific knowledge in the early modern period, analyzing more than 350 different editions of textbooks used for teaching astronomy in European universities from the late fifteenth century to mid-seventeenth century. These historical sources constitute the Sphaera Corpus. By examining different semantic relations among individual parts of each edition on record, we built a multiplex network consisting of six layers, as well as the aggregated network built from the superposition of all the layers. The network analysis reveals the emergence of five different communities. The contribution of each layer in shaping the communities and the properties of each community are studied. The most influential books in the corpus are found by calculating the average age of all the out-going and in-coming links for each book. A small group of editions is identified as a transmitter of knowledge as they bridge past knowledge to the future through a long temporal interval. Our analysis, moreover, identifies the most disruptive books. These books introduce new knowledge that is then adopted by almost all the books published afterwards until the end of the whole period of study. The historical research on the content of the identified books, as an empirical test, finally corroborates the results of all our analyses. Comment: 19 pages, 9 figures

We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved. We present the approach by explaining its core paradigm that consists in pairing specific types of LRs with specific exercises, by detailing both its strengths and challenges, and by discussing how much these challenges have been addressed at present. Accordingly, we also report on on-going proof-of-concept efforts aiming at developing the first prototypical implementation of the approach in order to correct and extend an LR called ConceptNet based on the input crowdsourced from language learners. We then present an international network called the European Network for Combining Language Learning with Crowdsourcing Techniques (enetCollect) that provides the context to accelerate the implementation of the generic approach. Finally, we exemplify how it can be used in several language learning scenarios to produce a multitude of NLP resources and how it can therefore alleviate the long-standing NLP issue of the lack of LRs. peer-reviewed