Anticipated versus inferred politeness

A number of researchers have recently argued that politeness is not always inferred in the form of an implicature as claimed by Brown and Levinson (1987), but rather can be anticipated by addressees when it involves expected behaviour. The distinction between anticipated and inferred politeness is thus an important area for further development of politeness theory. In this paper, the way in which the notion of ‘expectations’ is related to politeness is first considered, before outlining the distinction between anticipated and inferred politeness in some detail. It is then argued that discourse politeness theory (Usami, 1998, 2001a, b, 2002) shows greater promise for deepening our understanding of this distinction than the proposals made thus far by relevance theorists. It is concluded that any investigation of the distinction between anticipating and inferring politeness must ultimately be grounded in empirical studies of politeness phenomena

Flat Field Anomalies in an X-ray CCD Camera Measured Using a Manson X-ray Source (HTPD 08 paper)

The Static X-ray Imager (SXI) is a diagnostic used at the National Ignition Facility (NIF) to measure the position of the X-rays produced by lasers hitting a gold foil target. The intensity distribution taken by the SXI camera during a NIF shot is used to determine how accurately NIF can aim laser beams. This is critical to proper NIF operation. Imagers are located at the top and the bottom of the NIF target chamber. The CCD chip is an X-ray sensitive silicon sensor, with a large format array (2k x 2k), 24 {micro}m square pixels, and 15 {micro}m thick. A multi-anode Manson X-ray source, operating up to 10kV and 10W, was used to characterize and calibrate the imagers. The output beam is heavily filtered to narrow the spectral beam width, giving a typical resolution E/{Delta}E {approx} 10. The X-ray beam intensity was measured using an absolute photodiode that has accuracy better than 1% up to the Si K edge and better than 5% at higher energies. The X-ray beam provides full CCD illumination and is flat, within {+-}1% maximum to minimum. The spectral efficiency was measured at 10 energy bands ranging from 930 eV to 8470 eV. We observed an energy dependent pixel sensitivity variation that showed continuous change over a large portion of the CCD. The maximum sensitivity variation occurred at 8470 eV. The geometric pattern did not change at lower energies, but the maximum contrast decreased and was not observable below 4 keV. We were also able to observe debris, damage, and surface defects on the CCD chip. The Manson source is a powerful tool for characterizing the imaging errors of an X-ray CCD imager. These errors are quite different from those found in a visible CCD imager

Quantitative analysis of B-lymphocyte migration directed by CXCL13

B-lymphocyte migration, directed by chemokine gradients, is essential for homing to sites of antigen presentation

Flat Field Anomalies in an X-ray CCD Camera Measured Using a Manson X-ray Source

The Static X-ray Imager (SXI) is a diagnostic used at the National Ignition Facility (NIF) to measure the position of the X-rays produced by lasers hitting a gold foil target. The intensity distribution taken by the SXI camera during a NIF shot is used to determine how accurately NIF can aim laser beams. This is critical to proper NIF operation. Imagers are located at the top and the bottom of the NIF target chamber. The CCD chip is an X-ray sensitive silicon sensor, with a large format array (2k x 2k), 24 μm square pixels, and 15 μm thick. A multi-anode Manson X-ray source, operating up to 10kV and 10W, was used to characterize and calibrate the imagers. The output beam is heavily filtered to narrow the spectral beam width, giving a typical resolution E/ΔE≈10. The X-ray beam intensity was measured using an absolute photodiode that has accuracy better than 1% up to the Si K edge and better than 5% at higher energies. The X-ray beam provides full CCD illumination and is flat, within ±1% maximum to minimum. The spectral efficiency was measured at 10 energy bands ranging from 930 eV to 8470 eV. We observed an energy dependent pixel sensitivity variation that showed continuous change over a large portion of the CCD. The maximum sensitivity variation occurred at 8470 eV. The geometric pattern did not change at lower energies, but the maximum contrast decreased and was not observable below 4 keV. We were also able to observe debris, damage, and surface defects on the CCD chip. The Manson source is a powerful tool for characterizing the imaging errors of an X-ray CCD imager. These errors are quite different from those found in a visible CCD imager

Second Order Perturbations in the Randall-Sundrum Infinite Brane-World Model

We discuss the non-linear gravitational interactions in the Randall-Sundrum single brane model. If we naively write down the 4-dimensional effective action integrating over the fifth dimension with the aid of the decomposition with respect to eigen modes of 4-dimensional d'Alembertian, the Kaluza-Klein mode coupling seems to be ill-defined. We carefully analyze second order perturbations of the gravitational field induced on the 3-brane under the assumption of the static and axial-symmetric 5-dimensional metric. It is shown that there remains no pathological feature in the Kaluza-Klein mode coupling after the summation over all different mass modes. Furthermore, the leading Kaluza-Klein corrections are shown to be sufficiently suppressed in comparison with the leading order term which is obtained by the zero mode truncation. We confirm that the 4-dimensional Einstein gravity is approximately recovered on the 3-brane up to second order perturbations.Comment: 15 pages, 2 figures, comment and reference added, typos correcte

Feedback control architecture and the bacterial chemotaxis network.

PMCID: PMC3088647This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Bacteria move towards favourable and away from toxic environments by changing their swimming pattern. This response is regulated by the chemotaxis signalling pathway, which has an important feature: it uses feedback to 'reset' (adapt) the bacterial sensing ability, which allows the bacteria to sense a range of background environmental changes. The role of this feedback has been studied extensively in the simple chemotaxis pathway of Escherichia coli. However it has been recently found that the majority of bacteria have multiple chemotaxis homologues of the E. coli proteins, resulting in more complex pathways. In this paper we investigate the configuration and role of feedback in Rhodobacter sphaeroides, a bacterium containing multiple homologues of the chemotaxis proteins found in E. coli. Multiple proteins could produce different possible feedback configurations, each having different chemotactic performance qualities and levels of robustness to variations and uncertainties in biological parameters and to intracellular noise. We develop four models corresponding to different feedback configurations. Using a series of carefully designed experiments we discriminate between these models and invalidate three of them. When these models are examined in terms of robustness to noise and parametric uncertainties, we find that the non-invalidated model is superior to the others. Moreover, it has a 'cascade control' feedback architecture which is used extensively in engineering to improve system performance, including robustness. Given that the majority of bacteria are known to have multiple chemotaxis pathways, in this paper we show that some feedback architectures allow them to have better performance than others. In particular, cascade control may be an important feature in achieving robust functionality in more complex signalling pathways and in improving their performance

Computational and Mathematical Modelling of the EGF Receptor System

This chapter gives an overview of computational and mathematical modelling of the EGF receptor system. It begins with a survey of motivations for producing such models, then describes the main approaches that are taken to carrying out such modelling, viz. differential equations and individual-based modelling. Finally, a number of projects that applying modelling and simulation techniques to various aspects of the EGF receptor system are described

Development of a tandem affinity phosphoproteomic method with motif selectivity and its application in analysis of signal transduction networks

Phosphorylation is an important post-translational modification that is involved in regulating many signaling pathways. Of particular interest are the growth factor mediated Ras and phosphoinositide 3-kinase (PI3K) signaling pathways which, if misregulated, can contribute to the progression of cancer. Phosphoproteomic methods have been developed to study regulation of signaling pathways; however, due to the low stoichiometry of phosphorylation, understanding these pathways is still a challenge. In this study, we have developed a multi-dimensional method incorporating electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) with tandem IMAC-TiO2 enrichment for subsequent phosphopeptide identification by LC/MS/MS. We applied this method to PDGF-stimulated NIH 3T3 cells to provide over 11,000 unique phosphopeptide identifications. Upon motif analysis, IMAC was found to enrich for basophilic kinase substrates while the subsequent TiO2 step enriched for acidophilic kinase substrates, suggesting that both enrichment methods are necessary to capture the full complement of kinase substrates. Biological functions that were over-represented at each PDGF stimulation time point, together with the phosphorylation dynamics of several phosphopeptides containing known kinase phosphorylation sites illustrate the feasibility of this approach in quantitative phosphoproteomic studies

The fidelity of dynamic signaling by noisy biomolecular networks

This is the final version of the article. Available from Public Library of Science via the DOI in this record.Cells live in changing, dynamic environments. To understand cellular decision-making, we must therefore understand how fluctuating inputs are processed by noisy biomolecular networks. Here we present a general methodology for analyzing the fidelity with which different statistics of a fluctuating input are represented, or encoded, in the output of a signaling system over time. We identify two orthogonal sources of error that corrupt perfect representation of the signal: dynamical error, which occurs when the network responds on average to other features of the input trajectory as well as to the signal of interest, and mechanistic error, which occurs because biochemical reactions comprising the signaling mechanism are stochastic. Trade-offs between these two errors can determine the system's fidelity. By developing mathematical approaches to derive dynamics conditional on input trajectories we can show, for example, that increased biochemical noise (mechanistic error) can improve fidelity and that both negative and positive feedback degrade fidelity, for standard models of genetic autoregulation. For a group of cells, the fidelity of the collective output exceeds that of an individual cell and negative feedback then typically becomes beneficial. We can also predict the dynamic signal for which a given system has highest fidelity and, conversely, how to modify the network design to maximize fidelity for a given dynamic signal. Our approach is general, has applications to both systems and synthetic biology, and will help underpin studies of cellular behavior in natural, dynamic environments.We acknowledge support from a Medical Research Council and Engineering and Physical Sciences Council funded Fellowship in Biomedical Informatics (CGB) and a Scottish Universities Life Sciences Alliance chair in Systems Biology (PSS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript