Network robustness depth and topology management of networked dynamic systems

Networked control systems are subject to adversary conditions that affect their network topologies. To ensure reliable system operations, network topologies need to be characterized and managed for their impact on the overall system performance. This paper introduces the concept of network robustness depth for this pursuit. Discrete event systems are used as a foundation to model dynamic behavior of network topologies, support their analysis, and carry out their management. Stochastic analysis relates the link reliability probabilities to a probabilistic characterization of network robustness depth. Several topology management strategies are discussed, including passive methods, random strategies, and optimization methodologies. Their respective benefits and limitations are quantified. By using platoon control as a platform of hybrid (continuous and discrete event) systems and packet erasure channels as a communication protocol, the results are demonstrated with case studies.     

A complex of Shc and Ran-GTPase localises to the cell nucleus

The three isoforms of the adaptor protein Shc play diverse roles in cell signalling. For example, the observation of p46 Shc in the nuclei of hepatocellular carcinoma cells suggests a function quite distinct from the better characterised cytoplasmic role. Ligands responsible for the transport of various Shc isoforms into organelles such as the nucleus have yet to be reported. To identify such ligands a far western approach was used to determine the p52 Shc interactome. The Ran-GTPase nuclear transport protein was identified and found to bind to p52 Shc in vitro with low micromolar affinity. Co-immunoprecipitation, pull down and fluorescence lifetime imaging microscopy experiments in stable cells confirmed cellular interaction and nuclear localisation. The nuclear transport factor protein NTF2, which functions in cohort with Ran, was shown to form a complex with both RAN and Shc, suggesting a mechanism for Shc entry into the nucleus as part of a tertiary complex. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Received 20 October 2008; received after revision 04 December 2008; accepted 15 December 2008     

Lung cancer susceptibility locus at 5p15.33

We carried out a genome-wide association study of lung cancer (3,259 cases and 4,159 controls), followed by replication in 2,899 cases and 5,573 controls. Two uncorrelated disease markers at 5p15.33, rs402710 and rs2736100 were detected by the genome-wide data (P = 2 x 10(-7) and P = 4 x 10(-6)) and replicated by the independent study series (P = 7 x 10(-5) and P = 0.016). The susceptibility region contains two genes, TERT and CLPTM1L, suggesting that one or both may have a role in lung cancer etiology.     

Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease

We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 × 10?? and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.     

Zoogeography of Great Basin butterflies: patterns of distribution and differentiation

The butterflies of the Great Basin exhibit general patterns of distribution and speciation similar to those found for other taxa, particularly birds. Two major centers of infraspecific differentiation and coinciding distribution limits of taxa are identified, each with three subregions. Great Basin butterflies are characterized by pallidity and substantial endemism below the species level.     

On “the application of science to science itself:” chemistry,instruments, and the scientific labor process

The “Instrumental Revolution” in chemistry refers to a transitional period in the mid-20th century during which sophisticated instrumentation based on physical principles was introduced to solve chemical problems. Historical and philosophical reflection on whether the revolution was a scientific one has been dominated by general models of scientific revolution, in particular, those proposed by Thomas Kuhn, I. B. Cohen and Ian Hacking. In this article I propose that the Industrial Revolution is a useful model for understanding the transformation wrought by the increasingly important role of machines in chemical research. Drawing on Marx's analysis of that event, I argue that that the Instrumental Revolution bears a striking resemblance to the industrial one. I offer grounds for thinking that the resemblance is not fortuitous, but rather reflects a general pattern of development involving the mechanization of the labor process. It is suggested that the cognitive consequences of radical changes in the means of production, as exemplified in the Instrumental Revolution, warrant the consideration of whether the latter is an instance of a kind of revolution in science rather than a singular episode.     

Assessing time series models for forecasting international migration: Lessons from the United Kingdom

Migration is one of the most unpredictable demographic processes. The aim of this article is to provide a blueprint for assessing various possible forecasting approaches in order to help safeguard producers and users of official migration statistics against misguided forecasts. To achieve that, we first evaluate the various existing approaches to modelling and forecasting of international migration flows. Subsequently, we present an empirical comparison of ex post performance of various forecasting methods, applied to international migration to and from the United Kingdom. The overarching goal is to assess the uncertainty of forecasts produced by using different forecasting methods, both in terms of their errors (biases) and calibration of uncertainty. The empirical assessment, comparing the results of various forecasting models against past migration estimates, confirms the intuition about weak predictability of migration, but also highlights varying levels of forecast errors for different migration streams. There is no single forecasting approach that would be well suited for different flows. We therefore recommend adopting a tailored approach to forecasts, and applying a risk management framework to their results, taking into account the levels of uncertainty of the individual flows, as well as the differences in their potential societal impact.     

The heterochronic maize mutant Corngrass1 results from overexpression of a tandem microRNA

Retention of juvenile traits in the adult reproductive phase characterizes a process known as neoteny, and speculation exists over whether it has contributed to the evolution of new species. The dominant Corngrass1 (Cg1) mutant of maize is a neotenic mutation that results in phenotypes that may be present in the grass-like ancestors of maize. We cloned Cg1 and found that it encodes two tandem miR156 genes that are overexpressed in the meristem and lateral organs. Furthermore, a target of Cg1 is teosinte glume architecture1 (tga1), a gene known to have had a role in the domestication of maize from teosinte. Cg1 mutant plants overexpressing miR156 have lower levels of mir172, a microRNA that targets genes controlling juvenile development. By altering the relative levels of both microRNAs, it is possible to either prolong or shorten juvenile development in maize, thus providing a mechanism for how species-level heterochronic changes can occur in nature.     

A road map for efficient and reliable human genome epidemiology

Networks of investigators have begun sharing best practices, tools and methods for analysis of associations between genetic variation and common diseases. A Network of Investigator Networks has been set up to drive the process, sponsored by the Human Genome Epidemiology Network. A workshop is planned to develop consensus guidelines for reporting results of genetic association studies. Published literature databases will be integrated, and unpublished data, including 'negative' studies, will be captured by online journals and through investigator networks. Systematic reviews will be expanded to include more meta-analyses of individual-level data and prospective meta-analyses. Field synopses will offer regularly updated overviews.