An efficient particle filter for color-based tracking in complex scenes

In this paper, we introduce an efficient method for particle selection in tracking objects in complex scenes. Firstly, we improve the proposal distribution function of the tracking algorithm, including current observation, reducing the cost of evaluating particles with a very low likelihood. In addition, we use a partitioned sampling approach to decompose the dynamic state in several stages. It enables to deal with high-dimensional states without an excessive computational cost. To represent the color distribution, the appearance of the tracked object is modelled by sampled pixels. Based on this representation, the probability of any observation is estimated using non-parametric techniques in color space. As a result, we obtain a Probability color Density Image (PDI) where each pixel points its membership to the target color model. In this way, the evaluation of all particles is accelerated by computing the likelihood p(z|x) using the Integral Image of the PDI.

Improving multi-site benefit functions via Bayesian model averaging: A new approach to benefit transfer

A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. This has the advantage that more efficient estimates are obtained, but it relies on the assumption that the heterogeneity between sites is appropriately captured in the benefit transfer model. A more expensive alternative to estimate WTP is to analyze only data from the policy site in question while ignoring information from other sites. We make use of the fact that these two choices can be viewed as a model selection problem and extend the set of models to allow for the hypothesis that the benefit function is only applicable to a subset of sites. We show how Bayesian model averaging (BMA) techniques can be used to optimally combine information from all models. The Bayesian algorithm searches for the set of sites that can form the basis for estimating a benefit function and reveals whether such information can be transferred to new sites for which only a small data set is available. We illustrate the method with a sample of 42 forests from U.K. and Ireland. We find that BMA benefit function transfer produces reliable estimates and can increase about 8 times the information content of a small sample when the forest is 'poolable'. © 2008 Elsevier Inc. All rights reserved.

The up-regulation of voltage-gated sodium channels subtypes coincides with an increased sodium current in hippocampal neuronal culture model

Voltage-gated sodium channels (VGSC) have been linked to inherited forms of epilepsy. The expression and biophysical properties of VGSC in the hippocampal neuronal culture model have not been clarified. In order to evaluate mechanisms of epileptogenesis that are related to VGSC, we examined the expression and function of VGSC in the hippocampal neuronal culture model in vitro and spontaneously epileptic rats (SER) in vivo. Our data showed that the peak amplitude of transient, rapidly–inactivating Na+ current (INa,T) in model neurons was significantly increased compared with control neurons, and the activation curve was shifted to the negative potentials in model neurons in whole cell recording by patch–clamp. In addition, channel activity of persistent, non-inactivating Na+ current (INa,P) was obviously increased in the hippocampal neuronal culture model as judged by single–channel patch–clamp recording. Furthermore, VGSC subtypes NaV1.1, NaV1.2 and NaV1.3 were up-regulated at the protein expression level in model neurons and SER as assessed by Western blotting. Four subtypes of VGSC proteins in SER were clearly present throughout the hippocampus, including CA1, CA3 and dentate gyrus regions, and neurons expressing VGSC immunoreactivity were also detected in hippocampal neuronal culture model by immunofluorescence. These findings suggested that the up-regulation of voltage-gated sodium channels subtypes in neurons coincided with an increased sodium current in the hippocampal neuronal culture model, providing a possible explanation for the observed seizure discharge and enhanced excitability in epilepsy.

2D simulations of the double-detonation model for thermonuclear transients from low-mass carbon-oxygen white dwarfs

Thermonuclear explosions may arise in binary star systems in which a carbon-oxygen (CO) white dwarf (WD) accretes helium-rich material from a companion star. If the accretion rate allows a sufficiently large mass of helium to accumulate prior to ignition of nuclear burning, the helium surface layer may detonate, giving rise to an astrophysical transient. Detonation of the accreted helium layer generates shock waves that propagate into the underlying CO WD. This might directly ignite a detonation of the CO WD at its surface (an edge-lit secondary detonation) or compress the core of the WD sufficiently to trigger a CO detonation near the centre. If either of these ignition mechanisms works, the two detonations (helium and CO) can then release sufficient energy to completely unbind the WD. These 'double-detonation' scenarios for thermonuclear explosion of WDs have previously been investigated as a potential channel for the production of Type Ia supernovae from WDs of ~ 1 M . Here we extend our 2D studies of the double-detonation model to significantly less massive CO WDs, the explosion of which could produce fainter, more rapidly evolving transients. We investigate the feasibility of triggering a secondary core detonation by shock convergence in low-mass CO WDs and the observable consequences of such a detonation. Our results suggest that core detonation is probable, even for the lowest CO core masses that are likely to be realized in nature. To quantify the observable signatures of core detonation, we compute spectra and light curves for models in which either an edge-lit or compression-triggered CO detonation is assumed to occur. We compare these to synthetic observables for models in which no CO detonation was allowed to occur. If significant shock compression of the CO WD occurs prior to detonation, explosion of the CO WD can produce a sufficiently large mass of radioactive iron-group nuclei to significantly affect the light curves. In particular, this can lead to relatively slow post-maximum decline. If the secondary detonation is edge-lit, however, the CO WD explosion primarily yields intermediate-mass elements that affect the observables more subtly. In this case, near-infrared observations and detailed spectroscopic analysis would be needed to determine whether a core detonation occurred. We comment on the implications of our results for understanding peculiar astrophysical transients including SN 2002bj, SN 2010X and SN 2005E. © 2012 The Authors Monthly Notices of the Royal Astronomical Society © 2012 RAS.

Self-reported teamwork in family health team practices in Ontario:Organizational and cultural predictors of team climate

Objective: To determine the organizational predictors of higher scores on team climate measures as an indicator of the functioning of a family health team (FHT). Design: Cross-sectional study using a mailed survey. Setting: Family health teams in Ontario. Participants: Twenty-one of 144 consecutively approached FHTs; 628 team members were surveyed. Main outcome measures: Scores on the team climate inventory, which assessed organizational culture type (group, developmental, rational, or hierarchical); leadership perceptions; and organizational factors, such as use of electronic medical records (EMRs), team composition, governance of the FHT, location, meetings, and time since FHT initiation. All analyses were adjusted for clustering of respondents within the FHT using a mixed random-intercepts model. Results: The response rate was 65.8% (413 of 628); 2 were excluded from analysis, for a total of 411 participants. At the time of survey completion, there was a median of 4 physicians, 11 other health professionals, and 4 management and clerical staff per FHT. The average team climate score was 3.8 out of a possible 5. In multivariable regression analysis, leadership score, group and developmental culture types, and use of more EMR capabilities were associated with higher team climate scores. Other organizational factors, such as number of sites and size of group, were not associated with the team climate score. Conclusion: Culture, leadership, and EMR functionality, rather than organizational composition of the teams (eg, number of professionals on staff, practice size), were the most important factors in predicting climate in primary care teams.

Modified Information Criteria and Selection of Long Memory Time Series Models

The problem of model selection of a univariate long memory time series is investigated once a semi parametric estimator for the long memory parameter has been used. Standard information criteria are not consistent in this case. A Modified Information Criterion (MIC) that overcomes these difficulties is introduced and proofs that show its asymptotic validity are provided. The results are general and cover a wide range of short memory processes. Simulation evidence compares the new and existing methodologies and empirical applications in monthly inflation and daily realized volatility are presented.

Role of Predalors, Habitat Attributes, and Spatial Autocorrelation on the Distribution of Eggs in the Northern Spectacled Salamander (Salamandrina perspicillata)

We predicted that the probability of egg occurrence of salamander Salamandrina perspicillata depended on stream features and predation by native crayfish Austropotamobius fulcisianus and the introduced trout Salmo trutta. We assessed the presence of S. perspicillata at 54 sites within a natural reserve of southern Tuscany, Italy. Generalized linear models with binomial errors were constructed using egg presence/absence and altitude, stream mean size and slope, electrical conductivity, water pH and temperature, and a predation factor, defined according to the presence/absence of crayfish and trout. Some competing models also included an autocovariate term, which estimated how much the response variable at any one sampling point reflected response values at surrounding points. The resulting models were compared using Akaike's information criterion. Model selection led to a subset of 14 models with Delta AIC(c) <7 (i.e., models ranging from substantial support to considerably less support), and all but one of these included an effect of predation. Models with the autocovariate term had considerably more support than those without the term. According to multimodel inference, the presence of trout and crayfish reduced the probability of egg occurrence from a mean level of 0.90 (SE limits: 0.98-0.55) to 0.12 (SE limits: 0.34-0.04). The presence of crayfish alone had no detectable effects (SE limits: 0.86-0.39). The results suggest that introduced trout have a detrimental effect on the reproductive output of S. perspicillata and confirm the fundamental importance of distinguishing the roles of endogenous and exogenous forces that act on population distribution.

Photosynthetic pigments in soils from northern Victoria Land (continental Antarctica) as proxies for soil algal community structure and function

Although soil algae are among the main primary producers in most terrestrial ecosystems of continental Antarctica, there are very few quantitative studies on their relative proportion in the main algal groups and on how their distribution is affected by biotic and abiotic factors. Such knowledge is essential for understanding the functioning of Antarctic terrestrial ecosystems. We therefore analyzed biological soil crusts from northern Victoria Land to determine their pH, electrical conductivity (EC) water content (W), total and organic C (TC and TOC) and total N (TN) contents, and the presence and abundance of photosynthetic pigments. In particular, the latter were tested as proxies for biomass and coarse-resolution community structure. Soil samples were collected from five sites with known soil algal communities and the distribution of pigments was shown to reflect differences in the relative proportions of Chlorophyta, Cyanophyta and Bacillariophyta in these sites. Multivariate and univariate models strongly indicated that almost all soil variables (EC, W, TOC and TN) were important environmental correlates of pigment distribution. However, a significant amount of variation is independent of these soil variables and may be ascribed to local variability such as changes in microclimate at varying spatial and temporal scales. There are at least five possible sources of local variation: pigment preservation, temporal variations in water availability, temporal and spatial interactions among environmental and biological components, the local-scale patchiness of organism distribution, and biotic interactions. (C) 2009 Elsevier Ltd. All rights reserved.

Large-scale spatial patterns in the distribution of Collembola (Hexapoda) species in Antarctic terrestrial ecosystems

We tested whether the distribution of three common springtail species (Gressittacantha terranova, Gomphiocephalus hodgsoni and Friesea grisea) in Victoria Land (Antarctica) could be modelled as a function of latitude, longitude, altitude and distance from the sea.

Victoria Land, Ross Dependency, Antarctica.

Generalized linear models were constructed using species presence/absence data relative to geographical features (latitude, longitude, altitude, distance from sea) across the species' entire ranges. Model results were then integrated with the known phylogeography of each species and hypotheses were generated on the role of climate as a major driver of Antarctic springtail distribution.

Based on model selection using Akaike's information criterion, the species' distributions were: hump-shaped relative to longitude and monotonic with altitude for Gressittacantha terranova; hump-shaped relative to latitude and monotonic with altitude for Gomphiocephalus hodgsoni; and hump-shaped relative to longitude and monotonic with latitude, altitude and distance from the sea for Friesea grisea.

No single distributional pattern was shared by the three species. While distributions were partially a response to climatic spatial clines, the patterns observed strongly suggest that past geological events have influenced the observed distributions. Accordingly, present-day spatial patterns are likely to have arisen from the interaction of historical and environmental drivers. Future studies will need to integrate a range of spatial and temporal scales to further quantify their respective roles.

A multi-output two-stage locally regularized model construction method using the extreme learning machine

This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

Bandwidth selection by cross-validation for forecasting long memory financial time series

The paper addresses the issue of choice of bandwidth in the application of semiparametric estimation of the long memory parameter in a univariate time series process. The focus is on the properties of forecasts from the long memory model. A variety of cross-validation methods based on out of sample forecasting properties are proposed. These procedures are used for the choice of bandwidth and subsequent model selection. Simulation evidence is presented that demonstrates the advantage of the proposed new methodology.

Universal tight binding model for chemical reactions in solution and at surfaces. III. Stoichiometric and reduced surfaces of titania and the adsorption of water

We demonstrate a model for stoichiometric and reduced titanium dioxide intended for use in molecular dynamics and other atomistic simulations and based in the polarizable ion tight binding theory. This extends the model introduced in two previous papers from molecular and liquid applications into the solid state, thus completing the task of providing a comprehensive and unified scheme for studying chemical reactions, particularly aimed at problems in catalysis and electrochemistry. As before, experimental results are given priority over theoretical ones in selecting targets for model fitting, for which we used crystal parameters and band gaps of titania bulk polymorphs, rutile and anatase. The model is applied to six low index titania surfaces, with and without oxygen vacancies and adsorbed water molecules, both in dissociated and non-dissociated states. Finally, we present the results of molecular dynamics simulation of an anatase cluster with a number of adsorbed water molecules and discuss the role of edge and corner atoms of the cluster. (C) 2014 AIP Publishing LLC.

Modelling Static and Dynamic FRP-Concrete Bond Behaviour Using a Local Concrete Damage Model

This paper presents a study on the bond behaviour of FRP-concrete bonded joints under static and dynamic loadings, by developing a meso-scale finite element model using the K&C concrete damage model in LS-DYNA. A significant number of single shear experiments under static pull-off loading were modelled with an extensive parametric study covering key factors in the K&C model, including the crack band width, the compressive fracture energy and the shear dilatation factor. It is demonstrated that the developed model can satisfactorily simulate the static debonding behaviour, in terms of mesh objectivity, the load-carrying capacity and the local bond-slip behaviour, provided that proper consideration is given to the selection of crack band width and shear dilatation factor. A preliminary study of the effect of the dynamic loading rate on the debonding behaviour was also conducted by considering a dynamic increase factor (DIF) for the concrete strength as a function of strain rate. It is shown that a higher loading rate leads to a higher load-carrying capacity, a longer effective bond length, and a larger damaged area of concrete in the single shear loading scenario.

On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables

Influence diagrams are intuitive and concise representations of structured decision problems. When the problem is non-Markovian, an optimal strategy can be exponentially large in the size of the diagram. We can avoid the inherent intractability by constraining the size of admissible strategies, giving rise to limited memory influence diagrams. A valuable question is then how small do strategies need to be to enable efficient optimal planning. Arguably, the smallest strategies one can conceive simply prescribe an action for each time step, without considering past decisions or observations. Previous work has shown that finding such optimal strategies even for polytree-shaped diagrams with ternary variables and a single value node is NP-hard, but the case of binary variables was left open. In this paper we address such a case, by first noting that optimal strategies can be obtained in polynomial time for polytree-shaped diagrams with binary variables and a single value node. We then show that the same problem is NP-hard if the diagram has multiple value nodes. These two results close the fixed-parameter complexity analysis of optimal strategy selection in influence diagrams parametrized by the shape of the diagram, the number of value nodes and the maximum variable cardinality.