MULTIPLE MODEL EVALUATION ABSENT THE GOLD STANDARD VIA MODEL COMBINATION

We describe a method for evaluating an ensemble of predictive models given a sample of observations comprising the model predictions and the outcome event measured with error. Our formulation allows us to simultaneously estimate measurement error parameters, true outcome — aka the gold standard — and a relative weighting of the predictive scores. We describe conditions necessary to estimate the gold standard and for these estimates to be calibrated and detail how our approach is related to, but distinct from, standard model combination techniques. We apply our approach to data from a study to evaluate a collection of BRCA1/BRCA2 gene mutation prediction scores. In this example, genotype is measured with error by one or more genetic assays. We estimate true genotype for each individual in the dataset, operating characteristics of the commonly used genotyping procedures and a relative weighting of the scores. Finally, we compare the scores against the gold standard genotype and find that Mendelian scores are, on average, the more refined and better calibrated of those considered and that the comparison is sensitive to measurement error in the gold standard.

An entrepreneurial model of economic and environmental co-evolution

A basic tenet of ecological economics is that economic growth and development are ultimately constrained by environmental carrying capacities. It is from this basis that notions of a sustainable economy and of sustainable economic development emerge to undergird the “standard model” of ecological economics. However, the belief in “hard” environmental constraints may be obscuring the important role of the entrepreneur in the co-evolution of economic and environmental relations, and hence limiting or distorting the analytic focus of ecological economics and the range of policy options that are considered for sustainable economic development. This paper outlines a co-evolutionary model of the dynamics of economic and ecological systems as connected by entrepreneurial behaviour. We then discuss some of the key analytic and policy implications.

Locally weighted learning model predictivek control for elastic joint robots

This paper proposes an efficient and online learning control system that uses the successful Model Predictive Control (MPC) method in a model based locally weighted learning framework. The new approach named Locally Weighted Learning Model Predictive Control (LWL-MPC) has been proposed as a solution to learn to control complex and nonlinear Elastic Joint Robots (EJR). Elastic Joint Robots are generally difficult to learn to control due to their elastic properties preventing standard model learning techniques from being used, such as learning computed torque control. This paper demonstrates the capability of LWL-MPC to perform online and incremental learning while controlling the joint positions of a real three Degree of Freedom (DoF) EJR. An experiment on a real EJR is presented and LWL-MPC is shown to successfully learn to control the system to follow two different figure of eight trajectories.

Collaborative learning model of infrastructure construction: A capability perspective

Purpose Performance heterogeneity between collaborative infrastructure projects is typically examined by considering procurement systems and their governance mechanisms at static points in time. The literature neglects to consider the impact of dynamic learning capability, which is thought to reconfigure governance mechanisms over time in response to evolving market conditions. This conceptual paper proposes a new model to show how continuous joint learning of participant organisations improves project performance. Design/methodology/approach There are two stages of conceptual development. In the first stage, the management literature is analysed to explain the Standard Model of dynamic learning capability that emphasises three learning phases for organisations. This Standard Model is extended to derive a novel Circular Model of dynamic learning capability that shows a new feedback loop between performance and learning. In the second stage, the construction management literature is consulted, adding project lifecycle, stakeholder diversity and three organisational levels to the analysis, to arrive at the Collaborative Model of dynamic learning capability. Findings The Collaborative Model should enable construction organisations to successfully adapt and perform under changing market conditions. The complexity of learning cycles results in capabilities that are imperfectly imitable between organisations, explaining performance heterogeneity on projects. Originality/value The Collaborative Model provides a theoretically substantiated description of project performance, driven by the evolution of procurement systems and governance mechanisms. The Model’s empirical value will be tested in future research.

Flow Generated By Pitched Blade Turbines Ii: Simulation Using Κ-Ε Model

Experimental data on average velocity and turbulence intensity generated by pitched blade downflow turbines (PTD) were presented in Part I of this paper. Part II presents the results of the simulation of flow generated by PTD The standard κ-ε model along with the boundary conditions developed in the Part 1 have been employed to predict the flow generated by PTD in cylindrical baffled vessel. This part describes the new software FIAT (Flow In Agitated Tanks) for the prediction of three dimensional flow in stirred tanks. The basis of this software has been described adequately. The influence of grid size, impeller boundary conditions and values of model parameters on the predicted flow have been analysed. The model predictions successfully reproduce the three dimensionality and the other essential characteristics of the flow. The model can be used to improve the overall understanding about the relative distribution of turbulence by PTD in the agitated tank

Implications of Higgs boson to diphoton decay rate in the bilinear R-parity violating supersymmetric model

The Large Hadron Collider has recently discovered a Higgs-like particle having a mass around 125 GeVand also indicated that there is an enhancement in the Higgs to diphoton decay rate as compared to that in the standard model. We have studied implications of these discoveries in the bilinear R-parity violating supersymmetric model, whose main motivation is to explain the nonzero masses for neutrinos. The R-parity violating parameters in this model are epsilon and b(epsilon), and these parameters determine the scale of neutrino masses. If the enhancement in the Higgs to diphoton decay rate is true, then we have found epsilon greater than or similar to 0.01 GeV and b epsilon similar to 1 GeV2 in order to be compatible with the neutrino oscillation data. Also, in the above mentioned analysis, we can determine the soft masses of sleptons (m(L)) and CP-odd Higgs boson mass (mA). We have estimated that m(L) greater than or similar to 300 GeV and m(A) greater than or similar to 700 GeV. We have also commented on the allowed values of epsilon and b(epsilon), in case there is no enhancement in the Higgs to diphoton decay rate. Finally, we present a model to explain the smallness of epsilon and b(epsilon).

A simplified model for dark matter interacting primarily with gluons

We consider a simple renormalizable model providing a UV completion for dark matter whose interactions with the Standard Model are primarily via the gluons. The model consists of scalar dark matter interacting with scalar colored mediator particles. A novel feature is the fact that (in contrast to more typical models containing dark matter whose interactions are mediated via colored scalars) the colored scalars typically decay into multi-quark final states, with no associated missing energy. We construct this class of models and examine associated phenomena related to dark matter annihilation, scattering with nuclei, and production at colliders.

Multi-model inference ranking and applications to physics at the Large Hadron Collider

In the measurement of the Higgs Boson decaying into two photons the parametrization of an appropriate background model is essential for fitting the Higgs signal mass peak over a continuous background. This diphoton background modeling is crucial in the statistical process of calculating exclusion limits and the significance of observations in comparison to a background-only hypothesis. It is therefore ideal to obtain knowledge of the physical shape for the background mass distribution as the use of an improper function can lead to biases in the observed limits. Using an Information-Theoretic (I-T) approach for valid inference we apply Akaike Information Criterion (AIC) as a measure of the separation for a fitting model from the data. We then implement a multi-model inference ranking method to build a fit-model that closest represents the Standard Model background in 2013 diphoton data recorded by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC). Potential applications and extensions of this model-selection technique are discussed with reference to CMS detector performance measurements as well as in potential physics analyses at future detectors.

International Transmission of the Business Cycle in a Multi-Sector Model.

Multi-country models have not been very successful in replicating important features of the international transmission of business cycles. Standard models predict cross-country correlations of output and consumption which are respectively too low and too high. In this paper, we build a multi-country model of the business cycle with multiple sectors in order to analyze the role of sectoral shocks in the international transmission of the business cycle. We find that a model with multiple sectors generates a higher cross-country correlation of output than standard one-sector models, and a lower cross-country correlation of consumption. In addition, it predicts cross-country correlations of employment and investment that are closer to the data than the standard model. We also analyze the relative effects of multiple sectors, trade in intermediate goods, imperfect substitution between domestic and foreign goods, home preference, capital adjustment costs, and capital depreciation on the international transmission of the business cycle.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Neutral Higgs bosons in the SU(3)(L)circle times U(1)(N) model

The SU(3)(L)circle times U(1)(N) electroweak model predicts new Higgs bosons beyond the one of the standard model. In this work we investigate the signature and production of neutral SU(3)(L)circle times U(1)(N) Higgs bosons in the e(-)e(+) Next Linear Collider and in the CERN Linear Collider . We compute the branching ratios of two of the SU(3)(L)circle times U(1)(N) neutral Higgs bosons and study the possibility to detect them and the Z' extra neutral boson of the model.

Probing doubly charged Higgs bosons in e(+)e(-) colliders at the ILC and the CLIC in a 3-3-1 model

The SU(3)(L) circle times U(1)(N) electroweak model predicts new Higgs bosons beyond the one of the standard model. In this work we investigate the signature and production of doubly charged Higgs bosons in the e(+)e(-) International Linear Collider and in the CERN Linear Collider. We compute the branching ratios for the doubly charged gauge bosons of the model.

SU(5)circle times Z(13) grand unification model

We propose an SU(5) grand unified model with an invisible axion and the unification of the three coupling constants which is in agreement with the values, at M(Z), of alpha, alpha(s), and sin(2)theta(W). A discrete, anomalous, Z(13) symmetry implies that the Peccei-Quinn symmetry is an automatic symmetry of the classical Lagrangian protecting, at the same time, the invisible axion against possible semiclassical gravity effects. Although the unification scale is of the order of the Peccei-Quinn scale the proton is stabilized by the fact that in this model the standard model fields form the SU(5) multiplets completed by new exotic fields and, also, because it is protected by the Z(13) symmetry.

Supersymmetric 3-3-1 model

We build a complete supersymmetric version of a 3-3-1 gauge model using the superfield formalism. We point out that a discrete symmetry, similar to R symmetry in the minimal supersymmetric standard model, is possible to be defined in this model. Hence we have both R-conservina and R-violating possibilities. Analysis of the mass spectrum of the neutral real scalar fields show that in this model the lightest scalar Higgs boson has a mass upper limit, and at the tree level it is 124.5 GeV for a given illustrative set of parameters.

Lepton masses in a supersymmetric 3-3-1 model

We consider the mass generation for both charginos and neutralinos in a 3-3-1 supersymmetric model. We show that R-parity breaking interactions leave the electron and one of the neutrinos massless at the tree level. However, the same interactions induce masses for these particles at the 1-loop level. Unlike the similar situation in the minimal supersymmetric standard model, the masses of the neutralinos are related to the masses of the charginos.