Direct dispersion of SWNTs in highly conductive solvent-enhanced PEDOT:PSS films

Poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) is shown to be an effective dispersant for single-wall carbon nanotubes (SWNTs), enabling uniform aqueous suspensions to be obtained at weight loadings of up to 0.23 mg/ml (>1% by weight relative to PEDOT:PSS) without recourse to additional surfactants. Thin films spin-coated from PEDOT:PSS/SWNT suspensions exhibited sheet resistances of 90 Ω/sq. at 80 % transmittance, slightly higher than equivalent films of pure PEDOT:PSS which exhibited sheet resistances of 70 Ω/sq. at the same transmittance

Seeds Buffering for Information Spreading Processes

Seeding strategies for influence maximization in social networks have been studied for more than a decade. They have mainly relied on the activation of all resources (seeds) simultaneously in the beginning; yet, it has been shown that sequential seeding strategies are commonly better. This research focuses on studying sequential seeding with buffering, which is an extension to basic sequential seeding concept. The proposed method avoids choosing nodes that will be activated through the natural diffusion process, which is leading to better use of the budget for activating seed nodes in the social influence process. This approach was compared with sequential seeding without buffering and single stage seeding. The results on both real and artificial social networks confirm that the buffer-based consecutive seeding is a good trade-off between the final coverage and the time to reach it. It performs significantly better than its rivals for a fixed budget. The gain is obtained by dynamic rankings and the ability to detect network areas with nodes that are not yet activated and have high potential of activating their neighbours.Comment: Jankowski, J., Br\'odka, P., Michalski, R., & Kazienko, P. (2017, September). Seeds Buffering for Information Spreading Processes. In International Conference on Social Informatics (pp. 628-641). Springe

Monitoring and evaluating capacity building activities in low and middle income countries: challenges and opportunities.

BACKGROUND: Lower and middle income countries (LMICs) are home to >80% of the global population, but mental health researchers and LMIC investigator led publications are concentrated in 10% of LMICs. Increasing research and research outputs, such as in the form of peer reviewed publications, require increased capacity building (CB) opportunities in LMICs. The National Institute of Mental Health (NIMH) initiative, Collaborative Hubs for International Research on Mental Health reaches across five regional 'hubs' established in LMICs, to provide training and support for emerging researchers through hub-specific CB activities. This paper describes the range of CB activities, the process of monitoring, and the early outcomes of CB activities conducted by the five research hubs. METHODS: The indicators used to describe the nature, the monitoring, and the early outcomes of CB activities were developed collectively by the members of an inter-hub CB workgroup representing all five hubs. These indicators included but were not limited to courses, publications, and grants. RESULTS: Results for all indicators demonstrate a wide range of feasible CB activities. The five hubs were successful in providing at least one and the majority several courses; 13 CB recipient-led articles were accepted for publication; and nine grant applications were successful. CONCLUSIONS: The hubs were successful in providing CB recipients with a wide range of CB activities. The challenge remains to ensure ongoing CB of mental health researchers in LMICs, and in particular, to sustain the CB efforts of the five hubs after the termination of NIMH funding

Emergence d’une spécialité scientifique dans l’espace - La réparation de l’ADN

International audienceIn the study of science, the specialty is seen as the ideal level of analysis to understand the genesis and development of scientific communities. This article uses bibliometric data to analyze the emergence of DNA repair by testing a hybrid method to identify the specialty’s appearance in geographical space by focusing on the geographical trajectories of the pioneers in this field. We try to identify the professional mobility of researchers using these bibliometric data, and if possible to highlight the structural networks of places during the emergence stage of the specialty. These networks determine places as much as they are built by individual trajectories. In this way, we try to make a place for the geography of science in the field of social studies of science.Dans l’étude des sciences, la spécialité est perçue comme le niveau d’analyse idéal pour comprendre la genèse et le développement des collectifs scientifiques. Cet article utilise des données bibliométriques pour analyser l’émergence de la Réparation de l’ADN en expérimentant une méthode mixte pour repérer son apparition dans l’espace géographique. En nous concentrant sur les trajectoires géographiques de pionniers dans cedomaine, nous tâchons de repérer leur mobilité professionnelle à l’aide de données bibliométriques dans la perspective de mettre en évidence les réseaux de lieux structurants dans la phase d’émergence de la spécialité. Ces réseaux de lieux déterminent autant qu’ils sont construits par les trajectoires individuelles. Nous essayons ainsi de faire une place à la géographie des sciences dans le domaine des études sociales des sciences

The Citation Field of Evolutionary Economics

Evolutionary economics has developed into an academic field of its own, institutionalized around, amongst others, the Journal of Evolutionary Economics (JEE). This paper analyzes the way and extent to which evolutionary economics has become an interdisciplinary journal, as its aim was: a journal that is indispensable in the exchange of expert knowledge on topics and using approaches that relate naturally with it. Analyzing citation data for the relevant academic field for the Journal of Evolutionary Economics, we use insights from scientometrics and social network analysis to find that, indeed, the JEE is a central player in this interdisciplinary field aiming mostly at understanding technological and regional dynamics. It does not, however, link firmly with the natural sciences (including biology) nor to management sciences, entrepreneurship, and organization studies. Another journal that could be perceived to have evolutionary acumen, the Journal of Economic Issues, does relate to heterodox economics journals and is relatively more involved in discussing issues of firm and industry organization. The JEE seems most keen to develop theoretical insights

Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

Who is the best player ever? A complex network analysis of the history of professional tennis

We consider all matches played by professional tennis players between 1968 and 2010, and, on the basis of this data set, construct a directed and weighted network of contacts. The resulting graph shows complex features, typical of many real networked systems studied in literature. We develop a diffusion algorithm and apply it to the tennis contact network in order to rank professional players. Jimmy Connors is identified as the best player of the history of tennis according to our ranking procedure. We perform a complete analysis by determining the best players on specific playing surfaces as well as the best ones in each of the years covered by the data set. The results of our technique are compared to those of two other well established methods. In general, we observe that our ranking method performs better: it has a higher predictive power and does not require the arbitrary introduction of external criteria for the correct assessment of the quality of players. The present work provides a novel evidence of the utility of tools and methods of network theory in real applications.Comment: 10 pages, 4 figures, 4 table

Characterizing and modeling citation dynamics

Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.Comment: 8 pages, 5 figure