Mathematical models of magnetospheric convection and its coupling to the ionosphere

Mathematical models of magnetospheric convection and its coupling to ionospher

Decreasing intensity of open-ocean convection in the Greenland and Iceland seas

The air–sea transfer of heat and fresh water plays a critical role in the global climate system. This is particularly true for the Greenland and Iceland seas, where these fluxes drive ocean convection that contributes to Denmark Strait overflow water, the densest component of the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). Here we show that the wintertime retreat of sea ice in the region, combined with different rates of warming for the atmosphere and sea surface of the Greenland and Iceland seas, has resulted in statistically significant reductions of approximately 20% in the magnitude of the winter air–sea heat fluxes since 1979. We also show that modes of climate variability other than the North Atlantic Oscillation (NAO) are required to fully characterize the regional air–sea interaction. Mixed-layer model simulations imply that further decreases in atmospheric forcing will exceed a threshold for the Greenland Sea whereby convection will become depth limited, reducing the ventilation of mid-depth waters in the Nordic seas. In the Iceland Sea, further reductions have the potential to decrease the supply of the densest overflow waters to the AMOC

Planet Populations as a Function of Stellar Properties

Exoplanets around different types of stars provide a window into the diverse environments in which planets form. This chapter describes the observed relations between exoplanet populations and stellar properties and how they connect to planet formation in protoplanetary disks. Giant planets occur more frequently around more metal-rich and more massive stars. These findings support the core accretion theory of planet formation, in which the cores of giant planets form more rapidly in more metal-rich and more massive protoplanetary disks. Smaller planets, those with sizes roughly between Earth and Neptune, exhibit different scaling relations with stellar properties. These planets are found around stars with a wide range of metallicities and occur more frequently around lower mass stars. This indicates that planet formation takes place in a wide range of environments, yet it is not clear why planets form more efficiently around low mass stars. Going forward, exoplanet surveys targeting M dwarfs will characterize the exoplanet population around the lowest mass stars. In combination with ongoing stellar characterization, this will help us understand the formation of planets in a large range of environments.Comment: Accepted for Publication in the Handbook of Exoplanet

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

The Crystal Structure of 5-Aminouracil and the Ambiguity of Alternative Polymorphs

The nucleobase derivative 5-aminouracil (AUr, C4H5N3O2) is of interest for its biological activity, yet the solid state structure of this compound has remained elusive owing to its propensity to crystallize as aggregates of microcrystalline particles. Here we report the first single-crystal structure of AUr determined from synchrotron x-ray diffraction data. An early crystal structure prediction effort, which assumed that AUr was rigid in the isolated molecule optimized conformation, provided several poor matches to the simulated PXRD pattern. Revisiting these crystal structures, by periodic electronic level modelling (PBE-TS optimization) gave more realistic relative lattice energies, but a good match to the experimental powder pattern required using the experimental cell parameters. PXRD and Raman spectroscopy suggest that phase impurities may be present in the bulk crystallization product, though the identity of alternative polymorphs could not be confirmed on the basis of the data available

Coordinated optimization of visual cortical maps (II) Numerical studies

It is an attractive hypothesis that the spatial structure of visual cortical architecture can be explained by the coordinated optimization of multiple visual cortical maps representing orientation preference (OP), ocular dominance (OD), spatial frequency, or direction preference. In part (I) of this study we defined a class of analytically tractable coordinated optimization models and solved representative examples in which a spatially complex organization of the orientation preference map is induced by inter-map interactions. We found that attractor solutions near symmetry breaking threshold predict a highly ordered map layout and require a substantial OD bias for OP pinwheel stabilization. Here we examine in numerical simulations whether such models exhibit biologically more realistic spatially irregular solutions at a finite distance from threshold and when transients towards attractor states are considered. We also examine whether model behavior qualitatively changes when the spatial periodicities of the two maps are detuned and when considering more than 2 feature dimensions. Our numerical results support the view that neither minimal energy states nor intermediate transient states of our coordinated optimization models successfully explain the spatially irregular architecture of the visual cortex. We discuss several alternative scenarios and additional factors that may improve the agreement between model solutions and biological observations.Comment: 55 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:1102.335

Coordinated optimization of visual cortical maps (I) Symmetry-based analysis

In the primary visual cortex of primates and carnivores, functional architecture can be characterized by maps of various stimulus features such as orientation preference (OP), ocular dominance (OD), and spatial frequency. It is a long-standing question in theoretical neuroscience whether the observed maps should be interpreted as optima of a specific energy functional that summarizes the design principles of cortical functional architecture. A rigorous evaluation of this optimization hypothesis is particularly demanded by recent evidence that the functional architecture of OP columns precisely follows species invariant quantitative laws. Because it would be desirable to infer the form of such an optimization principle from the biological data, the optimization approach to explain cortical functional architecture raises the following questions: i) What are the genuine ground states of candidate energy functionals and how can they be calculated with precision and rigor? ii) How do differences in candidate optimization principles impact on the predicted map structure and conversely what can be learned about an hypothetical underlying optimization principle from observations on map structure? iii) Is there a way to analyze the coordinated organization of cortical maps predicted by optimization principles in general? To answer these questions we developed a general dynamical systems approach to the combined optimization of visual cortical maps of OP and another scalar feature such as OD or spatial frequency preference.Comment: 90 pages, 16 figure

Spatio-temporal Models of Lymphangiogenesis in Wound Healing

Several studies suggest that one possible cause of impaired wound healing is failed or insufficient lymphangiogenesis, that is the formation of new lymphatic capillaries. Although many mathematical models have been developed to describe the formation of blood capillaries (angiogenesis), very few have been proposed for the regeneration of the lymphatic network. Lymphangiogenesis is a markedly different process from angiogenesis, occurring at different times and in response to different chemical stimuli. Two main hypotheses have been proposed: 1) lymphatic capillaries sprout from existing interrupted ones at the edge of the wound in analogy to the blood angiogenesis case; 2) lymphatic endothelial cells first pool in the wound region following the lymph flow and then, once sufficiently populated, start to form a network. Here we present two PDE models describing lymphangiogenesis according to these two different hypotheses. Further, we include the effect of advection due to interstitial flow and lymph flow coming from open capillaries. The variables represent different cell densities and growth factor concentrations, and where possible the parameters are estimated from biological data. The models are then solved numerically and the results are compared with the available biological literature.Comment: 29 pages, 9 Figures, 6 Tables (39 figure files in total

Cluster randomised trial of a tailored intervention to improve the management of overweight and obesity in primary care in England

Background: Tailoring is a frequent component of approaches for implementing clinical practice guidelines, although evidence on how to maximise the effectiveness of tailoring is limited. In England, overweight and obesity are common, and national guidelines have been produced by the National Institute for Health and Care Excellence. However, the guidelines are not routinely followed in primary care. Methods: A tailored implementation intervention was developed following an analysis of the determinants of practice influencing the implementation of the guidelines on obesity and the selection of strategies to address the determinants. General practices in the East Midlands of England were invited to take part in a cluster randomised controlled trial of the intervention. The primary outcome measure was the proportion of overweight or obese patients offered a weight loss intervention. Secondary outcomes were the proportions of patients with (1) a BMI or waist circumference recorded, (2) record of lifestyle assessment, (3) referred to weight loss services, and (4) any change in weight during the study period. We also assessed the mean weight change over the study period. Follow-up was for 9 months after the intervention. A process evaluation was undertaken, involving interviews of samples of participating health professionals. Results: There were 16 general practices in the control group, and 12 in the intervention group. At follow-up, 15. 08 % in the control group and 13.19 % in the intervention group had been offered a weight loss intervention, odds ratio (OR) 1.16, 95 % confidence interval (CI) (0.72, 1.89). BMI/waist circumference measurement 42.71 % control, 39.56 % intervention, OR 1.15 (CI 0.89, 1.48), referral to weight loss services 5.10 % control, 3.67 % intervention, OR 1.45 (CI 0.81, 2.63), weight management in the practice 9.59 % control, 8.73 % intervention, OR 1.09 (CI 0.55, 2.15), lifestyle assessment 23.05 % control, 23.86 % intervention, OR 0.98 (CI 0.76, 1.26), weight loss of at least 1 kg 42.22 % control, 41.65 % intervention, OR 0.98 (CI 0.87, 1.09). Health professionals reported the interventions as increasing their confidence in managing obesity and providing them with practical resources. Conclusions: The tailored intervention did not improve the implementation of the guidelines on obesity, despite systematic approaches to the identification of the determinants of practice. The methods of tailoring require further development to ensure that interventions target those determinants that most influence implementation

Four theorems on the psychometric function

In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, Δx. This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull "slope" parameter, β, can be approximated by [Formula: see text], where [Formula: see text] is the β of the Weibull function that fits best to the cumulative noise distribution, and [Formula: see text] depends on the transducer. We derive general expressions for [Formula: see text] and [Formula: see text], from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when [Formula: see text], [Formula: see text]. We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4-0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull β reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of β for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian