02151nas a2200193   4500008004100000020001400041245007300055210006900128300001400197490000600211520154100217100002601758700002901784700002301813700002201836700002301858700003001881856004601911       2018                        eng d  a2432-272500aFrom neuroscience to computer science: a topical approach on Twitter0 aFrom neuroscience to computer science a topical approach on Twit  a187–2080 v13 aTwitter is perhaps the most influential microblogging service, with 271 million regular users producing approximately 500 million tweets per day. Previous studies of tweets discussing scientific topics are limited to local surveys or may not be representative geographically. This indicates a need to harvest and analyse tweets with the aim of understanding the level of dissemination of science related topics worldwide. In this study, we use Twitter as case of study and explore the hypothesis of science popularization via the social stream. We present and discuss tweets related to popular science around the world using eleven keywords. We analyze a sample of 306,163 tweets posted by 91,557 users with the aim of identifying tweets and those categories formed around temporally similar topics. We systematically examined the data to track and analyze the online activity around users tweeting about popular science. In addition, we identify locations of high Twitter activity that occur in several places around the world. We also examine which sources (mobile devices, apps, and other social networks) are used to share popular science related links. Furthermore, this study provides insights into the geographic density of popular science tweets worldwide. We show that emergent topics related to popular science are important because they could help to explore how science becomes of public interest. The study also offers some important insights for studying the type of scientific content that users are more likely to tweet.1 aPiña-García, C., A.1 aSiqueiros-García, Mario1 aRobles-Belmont, E.1 aCarreón, Gustavo1 aGershenson, Carlos1 aLópez, Julio, Amador Dí  uhttps://doi.org/10.1007/s42001-017-0002-902214nas a2200157   4500008004100000245014100041210006900182260003400251300000900285490000700294520164000301100002201941700002301963700002101986856004902007       2017                        eng d00aImproving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding0 aImproving public transportation systems with selforganization A   bPublic Library of Sciencec12  a1-200 v123 aThe equal headway instability—the fact that a configuration with regular time intervals between vehicles tends to be volatile—is a common regulation problem in public transportation systems. An unsatisfactory regulation results in low efficiency and possible collapses of the service. Computational simulations have shown that self-organizing methods can regulate the headway adaptively beyond the theoretical optimum. In this work, we develop a computer simulation for metro systems fed with real data from the Mexico City Metro to test the current regulatory method with a novel self-organizing approach. The current model considers overall system’s data such as minimum and maximum waiting times at stations, while the self-organizing method regulates the headway in a decentralized manner using local information such as the passenger’s inflow and the positions of neighboring trains. The simulation shows that the self-organizing method improves the performance over the current one as it adapts to environmental changes at the timescale they occur. The correlation between the simulation of the current model and empirical observations carried out in the Mexico City Metro provides a base to calculate the expected performance of the self-organizing method in case it is implemented in the real system. We also performed a pilot study at the Balderas station to regulate the alighting and boarding of passengers through guide signs on platforms. The analysis of empirical data shows a delay reduction of the waiting time of trains at stations. Finally, we provide recommendations to improve public transportation systems.1 aCarreón, Gustavo1 aGershenson, Carlos1 aPineda, Luis, A.  uhttps://doi.org/10.1371/journal.pone.0190100