A tunable radial basis function model for nonlinear system identification using particle swarm optimisation

A tunable radial basis function (RBF) network model is proposed for nonlinear system identification using particle swarm optimisation (PSO). At each stage of orthogonal forward regression (OFR) model construction, PSO optimises one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is computationally more efficient.

A flexible cost function model with risk

In examining bank cost efficiency in banking inclusion of risk-taking of banks is very important. In this paper we depart from the standard modeling approach and view risk intimately related to the technology. Thus, instead of controlling for risk by viewing them as covariates in the standard cost function we argue that the technology differs with risk, thereby meaning that the parameters of the parametric cost function changes with risk in a fully flexible manner. This is accomplished by viewing the parameters of the cost function as nonparametric functions of risk. We also control for country-specific effects in a fully flexible manner by using them as arguments of the nonparametric functions along with the risk variable. The resulting cost function then becomes semiparametric. The standard parametric model becomes a special case of our semiparametric model. We use the above modeling approach for banks in the EU countries. Actually, European financial integration is seen as a stepping stone for the development of a competitive single EU market that promotes efficiency and increases consumer welfare, changing the risk profile of the European banks. Particularly, financial integration allows more risk diversification and permits banks to use more advanced risk management instruments and systems, however it has at the same time increased the probability of systematic risks. Financial integration has increased the risk of contagion and changed its nature and scope. Consequently the bank’s risk seems to be an important issue to be investigated.

Form follows function:model-driven engineering for clinical trials

We argue that, for certain constrained domains, elaborate model transformation technologies-implemented from scratch in general-purpose programming languages-are unnecessary for model-driven engineering; instead, lightweight configuration of commercial off-the-shelf productivity tools suffices. In particular, in the CancerGrid project, we have been developing model-driven techniques for the generation of software tools to support clinical trials. A domain metamodel captures the community's best practice in trial design. A scientist authors a trial protocol, modelling their trial by instantiating the metamodel; customized software artifacts to support trial execution are generated automatically from the scientist's model. The metamodel is expressed as an XML Schema, in such a way that it can be instantiated by completing a form to generate a conformant XML document. The same process works at a second level for trial execution: among the artifacts generated from the protocol are models of the data to be collected, and the clinician conducting the trial instantiates such models in reporting observations-again by completing a form to create a conformant XML document, representing the data gathered during that observation. Simple standard form management tools are all that is needed. Our approach is applicable to a wide variety of information-modelling domains: not just clinical trials, but also electronic public sector computing, customer relationship management, document workflow, and so on. © 2012 Springer-Verlag.

Global relativistic folding optical potential and the relativistic Green's function model

Optical potentials provide critical input for calculations on a wide variety of nuclear reactions, in particular, for neutrino-nucleus reactions, which are of great interest in the light of the new neutrino oscillation experiments. We present the global relativistic folding optical potential (GRFOP) fits to elastic proton scattering data from C-12 nucleus at energies between 20 and 1040 MeV. We estimate observables, such as the differential cross section, the analyzing power, and the spin rotation parameter, in elastic proton scattering within the relativistic impulse approximation. The new GRFOP potential is employed within the relativistic Green's function model for inclusive quasielastic electron scattering and for (anti) neutrino-nucleus scattering at MiniBooNE kinematics.

An R package for simulating metapopulation dynamics and range expansion under environmental change

The metapopulation paradigm is central in ecology and conservation biology to understand the dynamics of spatially-structured populations in fragmented landscapes. Metapopulations are often studied using simulation modelling, and there is an increasing demand of user-friendly software tools to simulate metapopulation responses to environmental change. Here we describe the MetaLandSim R package, mwhich integrates ideas from metapopulation and graph theories to simulate the dynamics of real and virtual metapopulations. The package offers tools to (i) estimate metapopulation parameters from empirical data, (ii) to predict variation in patch occupancy over time in static and dynamic landscapes, either real or virtual, and (iii) to quantify the patterns and speed of metapopulation expansion into empty landscapes. MetaLandSim thus provides detailed information on metapopulation processes, which can be easily combined with land use and climate change scenarios to predict metapopulation dynamics and range expansion for a variety of taxa and ecological systems.

An approximate method for the solution of an influence function foil rolling model

Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

A presumed joint pdf model for turbulent combustion with varying equivalence ratio

Modeling of the joint probability density function of the mixture fraction and progress variable with a given covariance value is studied. This modeling is validated using experimental and direct numerical simulation (DNS) data. A very good agreement with experimental data of turbulent stratified flames and DNS data of a lifted hydrogen jet flame is obtained. The effect of using this joint pdf modeling to calculate the mean reaction rate with a flamelet closure in Reynolds averaged Navier-Stokes (RANS) calculation of stratified flames is studied. The covariance effect is observed to be large within the flame brush. The results obtained from RANS calculations using this modeling for stratified jet- and rod-stabilized V-flames are discussed and compared to the measurements as a posteriori validation for the joint probability density function model with the flamelet closure. The agreement between the computed and measured values of flame and turbulence quantities is found to be good. © 2012 Copyright Taylor and Francis Group, LLC.

Ecology of testate amoebae in an Amazonian peatland and development of a transfer function for palaeohydrological reconstruction

Tropical peatlands represent globally important carbon sinks with a unique biodiversity and are currently threatened by climate change and human activities. It is now imperative that proxy methods are developed to understand the ecohydrological dynamics of these systems and for testing peatland development models. Testate amoebae have been used as environmental indicators in ecological and palaeoecological studies of peatlands, primarily in ombrotrophic Sphagnum-dominated peatlands in the mid- and high-latitudes. We present the first ecological analysis of testate amoebae in a tropical peatland, a nutrient-poor domed bog in western (Peruvian) Amazonia. Litter samples were collected from different hydrological microforms (hummock to pool) along a transect from the edge to the interior of the peatland. We recorded 47 taxa from 21 genera. The most common taxa are Cryptodifflugia oviformis, Euglypha rotunda type, Phryganella acropodia, Pseudodifflugia fulva type and Trinema lineare. One species found only in the southern hemisphere, Argynnia spicata, is present. Arcella spp., Centropyxis aculeata and Lesqueresia spiralis are indicators of pools containing standing water. Canonical correspondence analysis and non-metric multidimensional scaling illustrate that water table depth is a significant control on the distribution of testate amoebae, similar to the results from mid- and high-latitude peatlands. A transfer function model for water table based on weighted averaging partial least-squares (WAPLS) regression is presented and performs well under cross-validation (r 2apparent=0.76,RMSE=4.29;r2jack=0.68,RMSEP=5.18. The transfer function was applied to a 1-m peat core, and sample-specific reconstruction errors were generated using bootstrapping. The reconstruction generally suggests near-surface water tables over the last 3,000 years, with a shift to drier conditions at c. cal. 1218-1273 AD

Évaluation de l'impact clinique et économique du développement d'un traitement pour la schizophrénie

Contexte : Les stratégies pharmacologiques pour traiter la schizophrénie reçoivent une attention croissante due au développement de nouvelles pharmacothérapies plus efficaces, mieux tolérées mais plus coûteuses. La schizophrénie est une maladie chronique présentant différents états spécifiques et définis par leur sévérité. Objectifs : Ce programme de recherche vise à: 1) Évaluer les facteurs associés au risque d'être dans un état spécifique de la schizophrénie, afin de construire les fonctions de risque de la modélisation du cours naturel de la schizophrénie; 2) Développer et valider un modèle de Markov avec microsimulations de Monte-Carlo, afin de simuler l'évolution naturelle des patients qui sont nouvellement diagnostiqués pour la schizophrénie, en fonction du profil individuel des facteurs de risque; 3) Estimer le coût direct de la schizophrénie (pour les soins de santé et autres non reliés aux soins de santé) dans la perspective gouvernementale et simuler l’impact clinique et économique du développement d’un traitement dans une cohorte de patients nouvellement diagnostiqués avec la schizophrénie, suivis pendant les cinq premières années post-diagnostic. Méthode : Pour le premier objectif de ce programme de recherche, un total de 14 320 patients nouvellement diagnostiqués avec la schizophrénie ont été identifiés dans les bases de données de la RAMQ et de Med-Echo. Les six états spécifiques de la schizophrénie ont été définis : le premier épisode (FE), l'état de dépendance faible (LDS), l’état de dépendance élevée (HDS), l’état stable (Stable), l’état de bien-être (Well) et l'état de décès (Death). Pour évaluer les facteurs associés au risque de se trouver dans chacun des états spécifiques de la schizophrénie, nous avons construit 4 fonctions de risque en se basant sur l'analyse de risque proportionnel de Cox pour des risques compétitifs. Pour le deuxième objectif, nous avons élaboré et validé un modèle de Markov avec microsimulations de Monte-Carlo intégrant les six états spécifiques de la schizophrénie. Dans le modèle, chaque sujet avait ses propres probabilités de transition entre les états spécifiques de la schizophrénie. Ces probabilités ont été estimées en utilisant la méthode de la fonction d'incidence cumulée. Pour le troisième objectif, nous avons utilisé le modèle de Markov développé précédemment. Ce modèle inclut les coûts directs de soins de santé, estimés en utilisant les bases de données de la Régie de l'assurance maladie du Québec et Med-Echo, et les coûts directs autres que pour les soins de santé, estimés à partir des enquêtes et publications de Statistique Canada. Résultats : Un total de 14 320 personnes nouvellement diagnostiquées avec la schizophrénie ont été identifiées dans la cohorte à l'étude. Le suivi moyen des sujets était de 4,4 (± 2,6) ans. Parmi les facteurs associés à l’évolution de la schizophrénie, on peut énumérer l’âge, le sexe, le traitement pour la schizophrénie et les comorbidités. Après une période de cinq ans, nos résultats montrent que 41% des patients seront considérés guéris, 13% seront dans un état stable et 3,4% seront décédés. Au cours des 5 premières années après le diagnostic de schizophrénie, le coût direct moyen de soins de santé et autres que les soins de santé a été estimé à 36 701 $ canadiens (CAN) (95% CI: 36 264-37 138). Le coût des soins de santé a représenté 56,2% du coût direct, le coût de l'aide sociale 34,6% et le coût associé à l’institutionnalisation dans les établissements de soins de longue durée 9,2%. Si un nouveau traitement était disponible et offrait une augmentation de 20% de l'efficacité thérapeutique, le coût direct des soins de santé et autres que les soins de santé pourrait être réduit jusqu’à 14,2%. Conclusion : Nous avons identifié des facteurs associés à l’évolution de la schizophrénie. Le modèle de Markov que nous avons développé est le premier modèle canadien intégrant des probabilités de transition ajustées pour le profil individuel des facteurs de risque, en utilisant des données réelles. Le modèle montre une bonne validité interne et externe. Nos résultats indiquent qu’un nouveau traitement pourrait éventuellement réduire les hospitalisations et le coût associé aux établissements de soins de longue durée, augmenter les chances des patients de retourner sur le marché du travail et ainsi contribuer à la réduction du coût de l'aide sociale.

A morphological model for sexing nestling peregrine falcons (Falco Peregrinus Macropus) verified through genetic analysis

Adult peregrine falcons (Falco peregrinus macropus) have monotypic plumage and display strong reversed sexual dimorphism, with females significantly larger than males. Reversed sexual dimorphism is measurable among nestlings in the latter stages of their development and can therefore be used to differentiate between sexes. In the early stages of development, however, nestlings cannot be sexed with any degree of certainty because morphological differentiation between the sexes is not well developed. During this study we developed a model for sexing younger nestlings based on genetic analysis and morphometric data collected as part of a long-term banding study of this species. A discriminant function model based on morphological characteristics was developed for determining the sex of nestlings (n = 150) in the field and was shown to be 96.0% accurate. This predictive model was further tested against an independent morphometric dataset taken from a second group of nestlings (n = 131). The model correctly allocated sex to 96.2% of this second group of nestlings. Sex can reliably be determined (98.6% accurate) for nestlings that have a wing length of at least 9 cm using this model. Application of this model, therefore, allows the banding of younger nestlings and, as such, significantly increases the period of time over which banding can occur. Another important implication of this model is that by banding nestlings earlier, they are less likely to jump from the nest, therefore reducing the risk of injury to both the brood and the bander.