225 research outputs found

    The evolution of early cellular systems viewed through the lens of biological interactions.

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    The minimal cell concept represents a pragmatic approach to the question of how few genes are required to run a cell. This is a helpful way to build a parts-list, and has been more successful than attempts to deduce a minimal gene set for life by inferring the gene repertoire of the last universal common ancestor, as few genes trace back to this hypothetical ancestral state. However, the study of minimal cellular systems is the study of biological outliers where, by practical necessity, coevolutionary interactions are minimized or ignored. In this paper, we consider the biological context from which minimal genomes have been removed. For instance, some of the most reduced genomes are from endosymbionts and are the result of coevolutionary interactions with a host; few such organisms are &quot;free-living.&quot; As few, if any, biological systems exist in complete isolation, we expect that, as with modern life, early biological systems were part of an ecosystem, replete with organismal interactions. We favor refocusing discussions of the evolution of cellular systems on processes rather than gene counts. We therefore draw a distinction between a pragmatic minimal cell (an interesting engineering problem), a distributed genome (a system resulting from an evolutionary transition involving more than one cell) and the looser coevolutionary interactions that are ubiquitous in ecosystems. Finally, we consider the distributed genome and coevolutionary interactions between genomic entities in the context of early evolution.</p

    Inferring Population Preferences via Mixtures of Spatial Voting Models

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    Understanding political phenomena requires measuring the political preferences of society. We introduce a model based on mixtures of spatial voting models that infers the underlying distribution of political preferences of voters with only voting records of the population and political positions of candidates in an election. Beyond offering a cost-effective alternative to surveys, this method projects the political preferences of voters and candidates into a shared latent preference space. This projection allows us to directly compare the preferences of the two groups, which is desirable for political science but difficult with traditional survey methods. After validating the aggregated-level inferences of this model against results of related work and on simple prediction tasks, we apply the model to better understand the phenomenon of political polarization in the Texas, New York, and Ohio electorates. Taken at face value, inferences drawn from our model indicate that the electorates in these states may be less bimodal than the distribution of candidates, but that the electorates are comparatively more extreme in their variance. We conclude with a discussion of limitations of our method and potential future directions for research.Comment: To be published in the 8th International Conference on Social Informatics (SocInfo) 201

    Measuring and Comparing Party Ideology and Heterogeneity

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    Estimates of party ideological positions in Western Democracies yield useful party-level information, but lack the ability to provide insight into intraparty politics. In this paper, we generate comparable measures of latent individual policy positions from elite survey data which enable analysis of elite-level party ideology and heterogeneity. This approach has advantages over both expert surveys and approaches based on behavioral data, such as roll call voting and is directly relevant to the study of party cohesion. We generate a measure of elite positions for several European countries using a common space scaling approach and demonstrate its validity as a measure of party ideology. We then apply these data to determine the sources of party heterogeneity, focusing on the role of intraparty competition in electoral systems, nomination rules, and party goals. We find that policy-seeking parties and centralized party nomination rules reduce party heterogeneity. While intraparty competition has no effect, the presence of these electoral rules conditions the effect of district magnitude

    Nanoscale Dynamics of Phase Flipping in Water near its Hypothesized Liquid-Liquid Critical Point

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    Achieving a coherent understanding of the many thermodynamic and dynamic anomalies of water is among the most important unsolved puzzles in physics, chemistry, and biology. One hypothesized explanation imagines the existence of a line of first order phase transitions separating two liquid phases and terminating at a novel "liquid-liquid" critical point in a region of low temperature (T250KT \approx 250 \rm{K}) and high pressure (P200MPaP \approx 200 \rm{MPa}). Here we analyze a common model of water, the ST2 model, and find that the entire system flips between liquid states of high and low density. Further, we find that in the critical region crystallites melt on a time scale of nanoseconds. We perform a finite-size scaling analysis that accurately locates both the liquid-liquid coexistence line and its associated liquid-liquid critical point.Comment: 22 pages, 5 figure

    Computational fact checking from knowledge networks

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    Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation

    Competing for the Platform: How Organized Interests affect Party Positioning in the United States

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    What explains which groups are included in a party coalition in any given election cycle? Recent advances in political party theory suggest that policy demanders comprise parties, and that the composition of a party coalition varies from election to election. We theorize three conditions under which parties articulate an interest group?s preferred positions in its quadrennial platform: when groups are ideologically proximate to the party median, when groups display party loyalty, and when groups are flush with resources. Using computer-assisted content analysis on a unique and rich data source, we examine three cycles of testimony that 80 organized groups provided to the Democratic Party. The analysis compares group requests with the content of Democratic and Republican National Committee platforms in 1996, 2000, and 2004. Results show that parties reward loyal groups and those that are ideologically proximate to the party, but offer no confirmation of a resource effect

    Firsthand Experience and The Subsequent Role of Reflected Knowledge in Cultivating Trust in Global Collaboration

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    While scholars contend that firsthand experience - time spent onsite observing the people, places, and norms of a distant locale - is crucial in globally distributed collaboration, how such experience actually affects interpersonal dynamics is poorly understood. Based on 47 semistructured interviews and 140 survey responses in a global chemical company, this paper explores the effects of firsthand experience on intersite trust. We find firsthand experience leads not just to direct knowledge of the other, but also knowledge of the self as seen through the eyes of the other - what we call “reflected knowledge”. Reflected and direct knowledge, in turn, affect trust through identification, adaptation, and reduced misunderstandings
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