Meson properties in an extended nonlocal NJL model

We consider a non-local version of the NJL model, based on a separable quark-quark interaction. The interaction is extended to include terms that bind vector and axial-vector mesons. The non-locality means that no further regulator is required. Moreover the model is able to confine the quarks by generating a quark propagator without poles at real energies. Working in the ladder approximation, we calculate amplitudes in Euclidean space and discuss features of their continuation to Minkowski energies. Conserved currents are constructed and we demonstrate their consistency with various Ward identities. Various meson masses are calculated, along with their strong and electromagnetic decay amplitudes. We also calculate the electromagnetic form factor of the pion, as well as form factors associated with the processes γγ* → π0 and ω → π0γ*. The results are found to lead to a satisfactory phenomenology and lend some dynamical support to the idea of vector-meson dominance.

Meson properties in an extended nonlocal NJL model

A nonlocal version of the NJL model is investigated. It is based on a separable quark-quark interaction, as suggested by the instanton liquid picture of the QCD vacuum. The interaction is extended to include terms that bind vector and axial-vector mesons. The nonlocality means that no further regulator is required. Moreover the model is able to confine the quarks by generating a quark propagator without poles at real energies. Features of the continuation of amplitudes from Euclidean space to Minkowski energies are discussed. These features lead to restrictions on the model parameters as well as on the range of applicability of the model. Conserved currents are constructed, and their consistency with various Ward identities is demonstrated. In particular, the Gell-Mann-Oakes-Renner relation is derived both in the ladder approximation and at meson loop level. The importance of maintaining chiral symmetry in the calculations is stressed throughout. Calculations with the model are performed to all orders in momentum. Meson masses are determined, along with their strong and electromagnetic decay amplitudes. Also calculated are the electromagnetic form factor of the pion and form factors associated with the processes gamma gamma* --> pi0 and omega --> pi0 gamma*. The results are found to lead to a satisfactory phenomenology and demonstrate a possible dynamical origin for vector-meson dominance. In addition, the results produced at meson loop level validate the use of 1/Nc as an expansion parameter and indicate that a light and broad scalar state is inherent in models of the NJL type.

Mechanisms of inverse agonist action at D-2 dopamine receptors

1 Mechanisms of inverse agonist action at the D-2(short) dopamine receptor have been examined. 2 Discrimination of G-protein-coupled and -uncoupled forms of the receptor by inverse agonists was examined in competition ligand-binding studies versus the agonist [H-3]NPA at a concentration labelling both G-protein-coupled and -uncoupled receptors. 3 Competition of inverse agonists versus [H-3] NPA gave data that were fitted best by a two-binding site model in the absence of GTP but by a one-binding site model in the presence of GTP. K-i values were derived from the competition data for binding of the inverse agonists to G-protein-uncoupled and -coupled receptors. K-coupled and K-uncoupled were statistically different for the set of compounds tested ( ANOVA) but the individual values were different in a post hoc test only for (+)-butaclamol. 4 These observations were supported by simulations of these competition experiments according to the extended ternary complex model. 5 Inverse agonist efficacy of the ligands was assessed from their ability to reduce agonist-independent [S-35]GTPγ S binding to varying degrees in concentration-response curves. Inverse agonism by (+)-butaclamol and spiperone occurred at higher potency when GDP was added to assays, whereas the potency of (-)-sulpiride was unaffected. 6 These data show that some inverse agonists ((+)-butaclamol, spiperone) achieve inverse agonism by stabilising the uncoupled form of the receptor at the expense of the coupled form. For other compounds tested, we were unable to define the mechanism.

Mechanisms of inverse agonist action at D-2 dopamine receptors

1 Mechanisms of inverse agonist action at the D-2(short) dopamine receptor have been examined. 2 Discrimination of G-protein-coupled and -uncoupled forms of the receptor by inverse agonists was examined in competition ligand-binding studies versus the agonist [H-3]NPA at a concentration labelling both G-protein-coupled and -uncoupled receptors. 3 Competition of inverse agonists versus [H-3] NPA gave data that were fitted best by a two-binding site model in the absence of GTP but by a one-binding site model in the presence of GTP. K-i values were derived from the competition data for binding of the inverse agonists to G-protein-uncoupled and -coupled receptors. K-coupled and K-uncoupled were statistically different for the set of compounds tested ( ANOVA) but the individual values were different in a post hoc test only for (+)-butaclamol. 4 These observations were supported by simulations of these competition experiments according to the extended ternary complex model. 5 Inverse agonist efficacy of the ligands was assessed from their ability to reduce agonist-independent [S-35]GTPγ S binding to varying degrees in concentration-response curves. Inverse agonism by (+)-butaclamol and spiperone occurred at higher potency when GDP was added to assays, whereas the potency of (-)-sulpiride was unaffected. 6 These data show that some inverse agonists ((+)-butaclamol, spiperone) achieve inverse agonism by stabilising the uncoupled form of the receptor at the expense of the coupled form. For other compounds tested, we were unable to define the mechanism.

A statistical mechanical approach for the computation of the climatic response to general forcings

The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. In this paper we show for the first time how the Ruelle linear response theory, developed for studying rigorously the impact of perturbations on general observables of non-equilibrium statistical mechanical systems, can be applied with great success to analyze the climatic response to general forcings. The crucial value of the Ruelle theory lies in the fact that it allows to compute the response of the system in terms of expectation values of explicit and computable functions of the phase space averaged over the invariant measure of the unperturbed state. We choose as test bed a classical version of the Lorenz 96 model, which, in spite of its simplicity, has a well-recognized prototypical value as it is a spatially extended one-dimensional model and presents the basic ingredients, such as dissipation, advection and the presence of an external forcing, of the actual atmosphere. We recapitulate the main aspects of the general response theory and propose some new general results. We then analyze the frequency dependence of the response of both local and global observables to perturbations having localized as well as global spatial patterns. We derive analytically several properties of the corresponding susceptibilities, such as asymptotic behavior, validity of Kramers-Kronig relations, and sum rules, whose main ingredient is the causality principle. We show that all the coefficients of the leading asymptotic expansions as well as the integral constraints can be written as linear function of parameters that describe the unperturbed properties of the system, such as its average energy. Some newly obtained empirical closure equations for such parameters allow to define such properties as an explicit function of the unperturbed forcing parameter alone for a general class of chaotic Lorenz 96 models. We then verify the theoretical predictions from the outputs of the simulations up to a high degree of precision. The theory is used to explain differences in the response of local and global observables, to define the intensive properties of the system, which do not depend on the spatial resolution of the Lorenz 96 model, and to generalize the concept of climate sensitivity to all time scales. We also show how to reconstruct the linear Green function, which maps perturbations of general time patterns into changes in the expectation value of the considered observable for finite as well as infinite time. Finally, we propose a simple yet general methodology to study general Climate Change problems on virtually any time scale by resorting to only well selected simulations, and by taking full advantage of ensemble methods. The specific case of globally averaged surface temperature response to a general pattern of change of the CO2 concentration is discussed. We believe that the proposed approach may constitute a mathematically rigorous and practically very effective way to approach the problem of climate sensitivity, climate prediction, and climate change from a radically new perspective.

Resource allocation analysis of the stochastic diffusion search

The Stochastic Diffusion Search (SDS) was developed as a solution to the best-fit search problem. Thus, as a special case it is capable of solving the transform invariant pattern recognition problem. SDS is efficient and, although inherently probabilistic, produces very reliable solutions in widely ranging search conditions. However, to date a systematic formal investigation of its properties has not been carried out. This thesis addresses this problem. The thesis reports results pertaining to the global convergence of SDS as well as characterising its time complexity. However, the main emphasis of the work, reports on the resource allocation aspect of the Stochastic Diffusion Search operations. The thesis introduces a novel model of the algorithm, generalising an Ehrenfest Urn Model from statistical physics. This approach makes it possible to obtain a thorough characterisation of the response of the algorithm in terms of the parameters describing the search conditions in case of a unique best-fit pattern in the search space. This model is further generalised in order to account for different search conditions: two solutions in the search space and search for a unique solution in a noisy search space. Also an approximate solution in the case of two alternative solutions is proposed and compared with predictions of the extended Ehrenfest Urn model. The analysis performed enabled a quantitative characterisation of the Stochastic Diffusion Search in terms of exploration and exploitation of the search space. It appeared that SDS is biased towards the latter mode of operation. This novel perspective on the Stochastic Diffusion Search lead to an investigation of extensions of the standard SDS, which would strike a different balance between these two modes of search space processing. Thus, two novel algorithms were derived from the standard Stochastic Diffusion Search, ‘context-free’ and ‘context-sensitive’ SDS, and their properties were analysed with respect to resource allocation. It appeared that they shared some of the desired features of their predecessor but also possessed some properties not present in the classic SDS. The theory developed in the thesis was illustrated throughout with carefully chosen simulations of a best-fit search for a string pattern, a simple but representative domain, enabling careful control of search conditions.

A neurofuzzy network knowledge extraction and extended gram-Schmidt algorithm for model subspace decomposition

This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

The climatology of the middle atmosphere in a vertically extended version of the Met Office's climate model. Part I: mean state

The climatology of a stratosphere-resolving version of the Met Office’s climate model is studied and validated against ECMWF reanalysis data. Ensemble integrations are carried out at two different horizontal resolutions. Along with a realistic climatology and annual cycle in zonal mean zonal wind and temperature, several physical effects are noted in the model. The time of final warming of the winter polar vortex is found to descend monotonically in the Southern Hemisphere, as would be expected for purely radiative forcing. In the Northern Hemisphere, however, the time of final warming is driven largely by dynamical effects in the lower stratosphere and radiative effects in the upper stratosphere, leading to the earliest transition to westward winds being seen in the midstratosphere. A realistic annual cycle in stratospheric water vapor concentrations—the tropical “tape recorder”—is captured. Tropical variability in the zonal mean zonal wind is found to be in better agreement with the reanalysis for the model run at higher horizontal resolution because the simulated quasi-biennial oscillation has a more realistic amplitude. Unexpectedly, variability in the extratropics becomes less realistic under increased resolution because of reduced resolved wave drag and increased orographic gravity wave drag. Overall, the differences in climatology between the simulations at high and moderate horizontal resolution are found to be small.

In vitro assessment of the bioaccessibility of brominated flame retardants in indoor dust using a colon extended model of the human gastrointestinal tract

An in vitro colon extended physiologically based extraction test (CEPBET) which incorporates human gastrointestinal tract (GIT) parameters (including pH and chemistry, solid-to-fluid ratio, mixing and emptying rates) was applied for the first time to study the bioaccessibility of brominated flame retardants (BFRs) from the 3 main GIT compartments (stomach, small intestine and colon) following ingestion of indoor dust. Results revealed the bioaccessibility of γ-HBCD (72%) was less than that for α- and β-isomers (92% and 80% respectively) which may be attributed to the lower aqueous solubility of the γ-isomer (2 μg L−1) compared to the α- and β-isomers (45 and 15 μg L−1 respectively). No significant change in the enantiomeric fractions of HBCDs was observed in any of the studied samples. However, this does not completely exclude the possibility of in vivo enantioselective absorption of HBCDs, as the GIT cell lining and bacterial flora – which may act enantioselectively – are not included in the current CE-PBET model. While TBBP-A was almost completely (94%) bioaccessible, BDE-209 was the least (14%) bioaccessible of the studied BFRs. Bioaccessibility of tri-hepta BDEs ranged from 32–58%. No decrease in the bioaccessibility with increasing level of bromination was observed in the studied PBDEs.

Large-scale dynamics of the mesosphere and lower thermosphere: an analysis using the extended Canadian Middle Atmosphere Model

The extended Canadian Middle Atmosphere Model is used to investigate the large-scale dynamics of the mesosphere and lower thermosphere (MLT). It is shown that the 4-day wave is substantially amplified in southern polar winter in the presence of instabilities arising from strong vertical shears in the MLT zonal mean zonal winds brought about by parameterized nonorographic gravity wave drag. A weaker 4-day wave in northern polar winter is attributed to the weaker wind shears that result from weaker parameterized wave drag. The 2-day wave also exhibits a strong dependence on zonal wind shears, in agreement with previous modeling studies. In the equatorial upper mesosphere, the migrating diurnal tide provides most of the resolved westward wave forcing, which varies semiannually in conjunction with the tide itself; resolved forcing by eastward traveling disturbances is dominated by smaller scales. Nonmigrating tides and other planetary-scale waves play only a minor role in the zonal mean zonal momentum budget in the tropics at these heights. Resolved waves are shown to play a significant role in the zonal mean meridional momentum budget in the MLT, impacting significantly on gradient wind balance. Balance fails at low latitudes as a result of a strong Reynolds stress associated with the migrating diurnal tide, an effect which is most pronounced at equinox when the tide is strongest. Resolved and parameterized waves account for most of the imbalance at higher latitudes in summer. This results in the gradient wind underestimating the actual eastward wind reversal by up to 40%.

Extended Canadian middle atmosphere model: zonal-mean climatology and physical parameterizations

This paper describes the energetics and zonal-mean state of the upward extension of the Canadian Middle Atmosphere Model, which extends from the ground to ~210 km. The model includes realistic parameterizations of the major physical processes from the ground up to the lower thermosphere and exhibits a broad spectrum of geophysical variability. The rationale for the extended model is to examine the nature of the physical and dynamical processes in the mesosphere/lower thermosphere (MLT) region without the artificial effects of an imposed sponge layer which can modify the circulation in an unrealistic manner. The zonal-mean distributions of temperature and zonal wind are found to be in reasonable agreement with observations in most parts of the model domain below ~150 km. Analysis of the global-average energy and momentum budgets reveals a balance between solar extreme ultraviolet heating and molecular diffusion and a thermally direct viscous meridional circulation above 130 km, with the viscosity coming from molecular diffusion and ion drag. Below 70 km, radiative equilibrium prevails in the global mean. In the MLT region between ~70 and 120 km, many processes contribute to the global energy budget. At solstice, there is a thermally indirect meridional circulation driven mainly by parameterized nonorographic gravity-wave drag. This circulation provides a net global cooling of up to 25 K d^-1.

Advances in Model-Based Traffic Vision

Model based vision allows use of prior knowledge of the shape and appearance of specific objects to be used in the interpretation of a visual scene; it provides a powerful and natural way to enforce the view consistency constraint. A model based vision system has been developed within ESPRIT VIEWS: P2152 which is able to classify and track moving objects (cars and other vehicles) in complex, cluttered traffic scenes. The fundamental basis of the method has been previously reported. This paper presents recent developments which have extended the scope of the system to include (i) multiple cameras, (ii) variable camera geometry, and (iii) articulated objects. All three enhancements have easily been accommodated within the original model-based approach

Stratospheric Memory and Skill of Extended-Range Weather Forecasts

We use an empirical statistical model to demonstrate significant skill in making extended-range forecasts of the monthly-mean Arctic Oscillation (AO). Forecast skill derives from persistent circulation anomalies in the lowermost stratosphere and is greatest during boreal winter. A comparison to the Southern Hemisphere provides evidence that both the time scale and predictability of the AO depend on the presence of persistent circulation anomalies just above the tropopause. These circulation anomalies most likely affect the troposphere through changes to waves in the upper troposphere, which induce surface pressure changes that correspond to the AO.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.