A study on the friendship paradox – quantitative analysis and relationship with assortative mixing

The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first study local metrics to capture the strength of the paradox and the direction of the paradox from the perspective of individual nodes, i.e., an indication of whether the individual is more or less popular than its friends. These local metrics are aggregated, and global metrics are proposed to express the phenomenon on a network-wide level. Theoretical results show that the defined metrics are well-behaved enough to capture the friendship paradox. We also theoretically analyze the behavior of the friendship paradox for popular network models in order to understand regimes where friendship paradox occurs. These theoretical findings are complemented by experimental results on both network models and real-world networks. By conducting a correlation study between the proposed metrics and degree assortativity, we experimentally demonstrate that the phenomenon of the friendship paradox is related to the well-known phenomenon of assortative mixing

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

Lessons from non-canonical splicing

Recent improvements in experimental and computational techniques that are used to study the transcriptome have enabled an unprecedented view of RNA processing, revealing many previously unknown non-canonical splicing events. This includes cryptic events located far from the currently annotated exons and unconventional splicing mechanisms that have important roles in regulating gene expression. These non-canonical splicing events are a major source of newly emerging transcripts during evolution, especially when they involve sequences derived from transposable elements. They are therefore under precise regulation and quality control, which minimizes their potential to disrupt gene expression. We explain how non-canonical splicing can lead to aberrant transcripts that cause many diseases, and also how it can be exploited for new therapeutic strategies

Monopole antenna radiation into a parallel-plate waveguide

A rigorous solution of coaxially fed monopole antenna radiation into a parallel-plate waveguide is obtained. The Fourier transform/series representations are used to represent scattered fields and the boundary conditions are enforced to obtain the simultaneous equations for discrete modal coefficients. Fast convergent series of the reflection coefficient is obtained and compared with other existing results.close8

Organic alkalinity produced by phytoplankton and its effect on computations of ocean carbon parameters

In seawater dissolved organic acids produced by phytoplankton dissociate into conjugate bases and an amount of hydrogen ions that maintain electroneutrality, leaving the seawater alkalinity (A(gamma)) unchanged. However, the resulting conjugate bases react with protons during seawater titration and thereby contribute to the titration alkalinity (A(gamma-ORG)) whereas the contributions of other species (e.g., CO32-, B(OH)(4)(-)) to A gamma are proportionally lowered. Production of such dissolved organic acids was confirmed in each of six phytoplankton cultures and in a coastal environment. In phytoplankton monocultures with initial concentrations of similar to 70 mu M nitrate and similar to 5 mu M phosphate, the contribution of organic acids to the seawater alkalinity (A(gamma-ORG)) was found to be 15-40 mu mol kg(-1) on the complete consumption of added nutrients, with the magnitude of A(gamma-ORG) depending on the phytoplankton species involved. In the coastal environment the contribution of A(gamma-ORG) was as high as 15 mu mol kg(-1). Analysis of back titration data of culture and coastal samples further enabled identification of the functional groups responsible, which included two distinct charge groups (pK(a1) = 4.4-4.9; pK(a2) = 6.1-6.9). Thus, if the effect of organic acids on seawater A(gamma) is not accounted for, the concentrations of inorganic carbon components calculated from pairs of carbon parameters, including A(gamma), will be inaccurate in culture studies and in studies of productive coastal environments.1143Nsciescopu

Multiple detection of food-borne pathogenic bacteria using a novel 16S rDNA-based oligonucleotide signature chip

There have been many attempts to develop sensitive and accurate techniques for the detection and diagnosis of pathogenic bacteria using nucleic acid-based technology. To achieve efficient multiple detection of seven selected food-borne pathogens, we assessed the respective 16S rDNA pathogen specific sequences using an oligonucleotide-based signature array. Strategic optimal design of specific capture probes was achieved by using the characteristic first variable region. To assess the specificity of this pathogen detection system, we employed a two-step experimental strategy. Under conditions established through experiments with chemically synthesized model targets comprising both conserved and variable regions of 16S rDNA, we confirmed the validity of this system using real 16S rDNA targets. Detection with real targets was successfully performed using our system, and better specificity was obtained compared to experiments with model targets. Moreover, the subtypes of Vibrio pathogens were successfully classified. We developed a two-dimensional visualization plot tool for positive control and specific spots, which allowed facile and minute differentiation between spot intensities. Repeated array formats were employed to ensure experimental uniformity, and included the statistical p-value criterion for pathogen discrimination. The present results thus indicate that our novel oligonucleotide-based signature chip detection system can be employed for the effective detection of multiple pathogens. (c) 2006 Elsevier B.V. All rights reserved.X1143sciescopu