299 research outputs found

    Combinatorial Bounds and Characterizations of Splitting Authentication Codes

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    We present several generalizations of results for splitting authentication codes by studying the aspect of multi-fold security. As the two primary results, we prove a combinatorial lower bound on the number of encoding rules and a combinatorial characterization of optimal splitting authentication codes that are multi-fold secure against spoofing attacks. The characterization is based on a new type of combinatorial designs, which we introduce and for which basic necessary conditions are given regarding their existence.Comment: 13 pages; to appear in "Cryptography and Communications

    Immigrant community integration in world cities

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    As a consequence of the accelerated globalization process, today major cities all over the world are characterized by an increasing multiculturalism. The integration of immigrant communities may be affected by social polarization and spatial segregation. How are these dynamics evolving over time? To what extent the different policies launched to tackle these problems are working? These are critical questions traditionally addressed by studies based on surveys and census data. Such sources are safe to avoid spurious biases, but the data collection becomes an intensive and rather expensive work. Here, we conduct a comprehensive study on immigrant integration in 53 world cities by introducing an innovative approach: an analysis of the spatio-temporal communication patterns of immigrant and local communities based on language detection in Twitter and on novel metrics of spatial integration. We quantify the "Power of Integration" of cities --their capacity to spatially integrate diverse cultures-- and characterize the relations between different cultures when acting as hosts or immigrants.Comment: 13 pages, 5 figures + Appendi

    Copula Eigenfaces with Attributes: Semiparametric Principal Component Analysis for a Combined Color, Shape and Attribute Model

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    Principal component analysis is a ubiquitous method in parametric appearance modeling for describing dependency and variance in datasets. The method requires the observed data to be Gaussian-distributed. We show that this requirement is not fulfilled in the context of analysis and synthesis of facial appearance. The model mismatch leads to unnatural artifacts which are severe to human perception. As a remedy, we use a semiparametric Gaussian copula model, where dependency and variance are modeled separately. This model enables us to use arbitrary Gaussian and non-Gaussian marginal distributions. Moreover, facial color, shape and continuous or categorical attributes can be analyzed in an unified way. Accounting for the joint dependency between all modalities leads to a more specific face model. In practice, the proposed model can enhance performance of principal component analysis in existing pipelines: The steps for analysis and synthesis can be implemented as convenient pre- and post-processing steps

    Recovering Dietary Information from Extant and Extinct Primates Using Plant Microremains

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    When reconstructing the diets of primates, researchers often rely on several well established methods, such as direct observation, studies of discarded plant parts, and analysis of macrobotanical remains in fecal matter. Most of these studies can be performed only on living primate groups, however, and the diets of extinct, subfossil, and fossil groups are known only from proxy methods. Plant microremains, tiny plant structures with distinctive morphologies, can record the exact plant foods that an individual consumed. They can be recovered from recently deceased and fossil primate samples, and can also be used to supplement traditional dietary analyses in living groups. Here I briefly introduce plant microremains, provide examples of how they have been successfully used to reconstruct the diets of humans and other species, and describe methods for their application in studies of primate dietary ecology

    Cheating on the Edge

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    We present the results of an individual agent-based model of antibiotic resistance in bacteria. Our model examines antibiotic resistance when two strategies exist: “producers”–who secrete a substance that breaks down antibiotics–and nonproducers (“cheats”) who do not secrete, or carry the machinery associated with secretion. The model allows for populations of up to 10,000, in which bacteria are affected by their nearest neighbors, and we assume cheaters die when there are no producers in their neighborhood. Each of 10,000 slots on our grid (a torus) could be occupied by a producer or a nonproducer, or could (temporarily) be unoccupied. The most surprising and dramatic result we uncovered is that when producers and nonproducers coexist at equilibrium, nonproducers are almost always found on the edges of clusters of producers

    A Direct Comparison of Two Densely Sampled HIV Epidemics: The UK and Switzerland

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    Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes

    Integrative inference of gene-regulatory networks in Escherichia coli using information theoretic concepts and sequence analysis

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    <p>Abstract</p> <p>Background</p> <p>Although <it>Escherichia coli </it>is one of the best studied model organisms, a comprehensive understanding of its gene regulation is not yet achieved. There exist many approaches to reconstruct regulatory interaction networks from gene expression experiments. Mutual information based approaches are most useful for large-scale network inference.</p> <p>Results</p> <p>We used a three-step approach in which we combined gene regulatory network inference based on directed information (DTI) and sequence analysis. DTI values were calculated on a set of gene expression profiles from 19 time course experiments extracted from the Many Microbes Microarray Database. Focusing on influences between pairs of genes in which one partner encodes a transcription factor (TF) we derived a network which contains 878 TF - gene interactions of which 166 are known according to RegulonDB. Afterward, we selected a subset of 109 interactions that could be confirmed by the presence of a phylogenetically conserved binding site of the respective regulator. By this second step, the fraction of known interactions increased from 19% to 60%. In the last step, we checked the 44 of the 109 interactions not yet included in RegulonDB for functional relationships between the regulator and the target and, thus, obtained ten TF - target gene interactions. Five of them concern the regulator LexA and have already been reported in the literature. The remaining five influences describe regulations by Fis (with two novel targets), PhdR, PhoP, and KdgR. For the validation of our approach, one of them, the regulation of lipoate synthase (LipA) by the pyruvate-sensing pyruvate dehydrogenate repressor (PdhR), was experimentally checked and confirmed.</p> <p>Conclusions</p> <p>We predicted a set of five novel TF - target gene interactions in <it>E. coli</it>. One of them, the regulation of <it>lipA </it>by the transcriptional regulator PdhR was validated experimentally. Furthermore, we developed DTInfer, a new R-package for the inference of gene-regulatory networks from microarrays using directed information.</p

    Cooperation and virulence in acute Pseudomonas aeruginosa infections

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    BACKGROUND: Efficient host exploitation by parasites is frequently likely to depend on cooperative behaviour. Under these conditions, mixed-strain infections are predicted to show lower virulence (host mortality) than are single-clone infections, due to competition favouring non-contributing social 'cheats' whose presence will reduce within-host growth. We tested this hypothesis using the cooperative production of iron-scavenging siderophores by the pathogenic bacterium Pseudomonas aeruginosa in an insect host. RESULTS: We found that infection by siderophore-producing bacteria (cooperators) results in more rapid host death than does infection by non-producers (cheats), and that mixtures of both result in intermediate levels of virulence. Within-host bacterial growth rates exhibited the same pattern. Crucially, cheats were more successful in mixed infections compared with single-clone infections, while the opposite was true of cooperators. CONCLUSION: These data demonstrate that mixed clone infections can favour the evolution of social cheats, and thus decrease virulence when parasite growth is dependent on cooperative behaviours
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