3,038 research outputs found

    Prevalence, intensity, and effect of a nematode (Philometra saltatrix) in the ovaries of bluefish (Pomatomus saltatrix)

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    Examination of 203 adult bluefish (Pomatomus saltatrix) from Long Island, New York, in 2002 and 2003 and 66 from the Outer Banks, North Carolina, in 2003 revealed the presence of dracunculoid nematodes (Philometra saltatrix) in the ovaries of female fish. Percent prevalence reached 88% in July and then decreased after the peak of the spawning season. Bluefish contained up to 100 parasites per fish. Infection was associated with a range of disorders, including hemorrhage, inf lammation, edema, prenecrotic and necrotic changes, and follicular atresia, that may prevent proper development of oocytes and probably affect bluefish fecundity. Historical occurrences, life cycle, and geographical distribution of this nematode remain largely unknown, but may play important roles in recruitment processes of bluefish

    Assessing candidate preference through web browsing history

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    Predicting election outcomes is of considerable interest to candidates, political scientists, and the public at large. We propose the use of Web browsing history as a new indicator of candidate preference among the electorate, one that has potential to overcome a number of the drawbacks of election polls. However, there are a number of challenges that must be overcome to effectively use Web browsing for assessing candidate preference—including the lack of suitable ground truth data and the heterogeneity of user populations in time and space. We address these challenges, and show that the resulting methods can shed considerable light on the dynamics of voters’ candidate preferences in ways that are difficult to achieve using polls.Accepted manuscrip

    Partisan Asymmetries in Online Political Activity

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    We examine partisan differences in the behavior, communication patterns and social interactions of more than 18,000 politically-active Twitter users to produce evidence that points to changing levels of partisan engagement with the American online political landscape. Analysis of a network defined by the communication activity of these users in proximity to the 2010 midterm congressional elections reveals a highly segregated, well clustered partisan community structure. Using cluster membership as a high-fidelity (87% accuracy) proxy for political affiliation, we characterize a wide range of differences in the behavior, communication and social connectivity of left- and right-leaning Twitter users. We find that in contrast to the online political dynamics of the 2008 campaign, right-leaning Twitter users exhibit greater levels of political activity, a more tightly interconnected social structure, and a communication network topology that facilitates the rapid and broad dissemination of political information.Comment: 17 pages, 10 figures, 6 table

    Portraits of Complex Networks

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    We propose a method for characterizing large complex networks by introducing a new matrix structure, unique for a given network, which encodes structural information; provides useful visualization, even for very large networks; and allows for rigorous statistical comparison between networks. Dynamic processes such as percolation can be visualized using animations. Applications to graph theory are discussed, as are generalizations to weighted networks, real-world network similarity testing, and applicability to the graph isomorphism problem.Comment: 6 pages, 9 figure

    A Group-Based Yule Model for Bipartite Author-Paper Networks

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    This paper presents a novel model for author-paper networks, which is based on the assumption that authors are organized into groups and that, for each research topic, the number of papers published by a group is based on a success-breeds-success model. Collaboration between groups is modeled as random invitations from a group to an outside member. To analyze the model, a number of different metrics that can be obtained in author-paper networks were extracted. A simulation example shows that this model can effectively mimic the behavior of a real-world author-paper network, extracted from a collection of 900 journal papers in the field of complex networks.Comment: 13 pages (preprint format), 7 figure

    Geometric and dynamic perspectives on phase-coherent and noncoherent chaos

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    Statistically distinguishing between phase-coherent and noncoherent chaotic dynamics from time series is a contemporary problem in nonlinear sciences. In this work, we propose different measures based on recurrence properties of recorded trajectories, which characterize the underlying systems from both geometric and dynamic viewpoints. The potentials of the individual measures for discriminating phase-coherent and noncoherent chaotic oscillations are discussed. A detailed numerical analysis is performed for the chaotic R\"ossler system, which displays both types of chaos as one control parameter is varied, and the Mackey-Glass system as an example of a time-delay system with noncoherent chaos. Our results demonstrate that especially geometric measures from recurrence network analysis are well suited for tracing transitions between spiral- and screw-type chaos, a common route from phase-coherent to noncoherent chaos also found in other nonlinear oscillators. A detailed explanation of the observed behavior in terms of attractor geometry is given.Comment: 12 pages, 13 figure

    Dancing to the Partisan Beat: A First Analysis of Political Communication on TikTok

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    TikTok is a video-sharing social networking service, whose popularity is increasing rapidly. It was the world's second-most downloaded app in 2019. Although the platform is known for having users posting videos of themselves dancing, lip-syncing, or showcasing other talents, user-videos expressing political views have seen a recent spurt. This study aims to perform a primary evaluation of political communication on TikTok. We collect a set of US partisan Republican and Democratic videos to investigate how users communicated with each other about political issues. With the help of computer vision, natural language processing, and statistical tools, we illustrate that political communication on TikTok is much more interactive in comparison to other social media platforms, with users combining multiple information channels to spread their messages. We show that political communication takes place in the form of communication trees since users generate branches of responses to existing content. In terms of user demographics, we find that users belonging to both the US parties are young and behave similarly on the platform. However, Republican users generated more political content and their videos received more responses; on the other hand, Democratic users engaged significantly more in cross-partisan discussions.Comment: Accepted as a full paper at the 12th International ACM Web Science Conference (WebSci 2020). Please cite the WebSci version; Second version includes corrected typo

    Class I Gap-formation in Highly-viscous Glass-ionomer Restorations: Delayed vs Immediate Polishing

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    This in vitro study evaluated the effects of delayed versus immediate polishing to permit maturation of interfacial gap-formation around highly viscous conventional glass-ionomer cement (HV-GIC) in Class I restorations, together with determining the associated mechanical properties. Cavity preparations were made on the occlusal surfaces of premolars. Three HV-GICs (Fuji IX GP, GlasIonomer FX-II and Ketac Molar) and one conventional glass-ionomer cement (C-GIC, Fuji II, as a control) were studied, with specimen subgroups (n=10) for each property measured. After polishing, either immediately (six minutes) after setting or after 24 hours storage, the restored teeth were sectioned in a mesiodistal direction through the center of the model Class I restorations. The presence or absence of interfacial-gaps was measured at 1000× magnification at 14 points (each 0.5-mm apart) along the cavity restoration interface (n=10; total points measured per group = 140). Marginal gaps were similarly measured in Teflon molds as swelling data, together with shear-bond-strength to enamel and dentin, flexural strength and moduli. For three HV-GICs and one C-GIC, significant differences (p<0.05) in gap-incidence were observed between polishing immediately and after one-day storage. In the former case, 80–100 gaps were found. In the latter case, only 9–21 gaps were observed. For all materials, their shear-bond-strengths, flexural strength and moduli increased significantly after 24-hour storage.</p

    Twitter-based analysis of the dynamics of collective attention to political parties

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    Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON

    Optical spectroscopy of 20 Be/X-ray Binaries in the Small Magellanic Cloud

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    We present a large sample (20 in total) of optical spectra of Small Magellanic Cloud (SMC) High-Mass X-ray Binaries obtained with the 2dF spectrograph at the Anglo-Australian Telescope. All of these sources are found to be Be/X-ray binaries (Be-XRBs), while for 5 sources we present original classifications. Several statistical tests on this expanded sample support previous findings for similar spectral-type distributions of Be-XRBs and Be field stars in the SMC, and of Be-XRBs in the Large Magellanic Cloud and the Milky Way, although this could be the result of small samples. On the other hand, we find that Be-XRBs follow a different distribution than Be stars in the Galaxy, also in agreement with previous studies. In addition, we find similar Be spectral type distributions between the Magellanic Clouds samples. These results reinforce the relation between the orbital period and the equivalent width of the Halpha line that holds for Be-XRBs. SMC Be stars have larger Halpha equivalent widths when compared to Be-XRBs, supporting the notion of circumstellar disk truncation by the compact object.Comment: 26 pages, 8 figures, accepted for publication in Ap
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