Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both

On pure-strategy Nash equilibria in a duopolistic market share model

This paper develops a duopolistic discounted marketing model with linear advertising costs and advertised prices for mature markets still in expansion. Generic and predatory advertising effects are combined together in the model. We characterize a class of advertising models with some lowered production costs. For such a class of models, advertising investments have a no-free-riding strict Nash equilibrium in pure strategies if discount rates are small. We discuss the entity of this efficiency at varying of parameters of our advertising model. We provide a computational framework in which market shares can be computed at equilibrium, too. We analyze market share dynamics for an asymmetrical numerical scenario where one of the two firms is more effective in generic and predatory advertising. Several numerical insights on market share dynamics are obtained. Our computational framework allows for different scenarios in practical applications and it is developed, thanks to Mathematica software

Modelling gas flow pressure gradients in Gelcast ceramic foam diesel particulate filters

New mathematical models are proposed that predict fluid flow pressure gradients in gelcast ceramic foam diesel exhaust particulate filters by considering the foam structure conceptually as serially connected orifices. The resulting multiple orifice mathematical (MOM) model is based on the sum of a viscous term derived from an extended Ergun model and the kinetic energy loss derived from the Bernoulli and conservation of mass equations. The MOM model was calibrated using experimental data obtained from measuring the air flowrate and pressure drop across a physical large-scale three-dimensional model of a cellular foam structure produced using rapid manufacturing techniques. The calibrated model was then validated using fluid flow data obtained from gelcast ceramic foam filters of various cell sizes and was found to require no empirical recalibration for each gelcast ceramic foam sample. The MOM model for clean filters was extended to predict pressure gradients of filters loaded with particulate matter (PM). The prediction of pressure gradients through gelcast ceramic filters using the MOM model for clean and PM-loaded cases was shown to be in reasonable agreement with experimental data. The models were finally applied to design a filter for a turbocharged, charge-cooled, 2.0 l, fourstroke, common rail, direct injection passenger car diesel engine

Prospects for e+e- physics at Frascati between the phi and the psi

We present a detailed study, done in the framework of the INFN 2006 Roadmap, of the prospects for e+e- physics at the Frascati National Laboratories. The physics case for an e+e- collider running at high luminosity at the phi resonance energy and also reaching a maximum center of mass energy of 2.5 GeV is discussed, together with the specific aspects of a very high luminosity tau-charm factory. Subjects connected to Kaon decay physics are not discussed here, being part of another INFN Roadmap working group. The significance of the project and the impact on INFN are also discussed. All the documentation related to the activities of the working group can be found in http://www.roma1.infn.it/people/bini/roadmap.html.Comment: INFN Roadmap Report: 86 pages, 25 figures, 9 table

Physics with the KLOE-2 experiment at the upgraded DAϕ\phiNE

Investigation at a $\phi$--factory can shed light on several debated issues in particle physics. We discuss: i) recent theoretical development and experimental progress in kaon physics relevant for the Standard Model tests in the flavor sector, ii) the sensitivity we can reach in probing CPT and Quantum Mechanics from time evolution of entangled kaon states, iii) the interest for improving on the present measurements of non-leptonic and radiative decays of kaons and eta/eta$^\prime$ mesons, iv) the contribution to understand the nature of light scalar mesons, and v) the opportunity to search for narrow di-lepton resonances suggested by recent models proposing a hidden dark-matter sector. We also report on the $e^+ e^-$ physics in the continuum with the measurements of (multi)hadronic cross sections and the study of gamma gamma processes.Comment: 60 pages, 41 figures; added affiliation for one of the authors; added reference to section

The construction, interpretation and analysis of divisia monetary aggregates for the UK

Available from British Library Document Supply Centre- DSC:D79495 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

Forecasting Economic Data with Neural Networks

neural networks, nonlinear regression, economic data modeling, economic data forecasting,

Microwave calorimetry using X-rays

An alternative approach for microwave calorimetry is proposed which relies on the synchrotron radiation powder diffraction technique as well as on the Grüneisen formalism for the analysis of thermal expansion. Cobalt was selected as suitable magnetic material for the present evaluation of the method. First results are reported concerning the calorimetric assessment of the HCP (hexagonal close-packed) to FCC (face centered cubic) transition of cobalt from in situ time-resolved X-ray diffraction experiments performed during magnetic (H-field) microwave heating. The X-ray calorimetry method yields specific heat capacity estimations that compare well with results from conventional differential scanning calorimetry measurements. In the presence of the 2.45 GHz microwave H-field, an 'anomalous' behaviour of the heat capacity across the structural phase transition is detected, which can be correlated with the magnetic spin reorientation transition of cobalt in the same temperature range. © 2011 Elsevier B.V. All rights reserved.We kindly acknowledge the help of Fabia Gozzo, Antonio Cervellino and the team at the MS X04SA beamline at the Swiss Light Source. This work was jointly supported by the Swiss National Science Foundation (SNSF) and by the German Science Foundation (DFG), Project "Calorimetry of phase transitions in ultrafast conventional and electromagnetic heating", SNSF Grant 20PA21-129123 and DFG Grant SCHI331/21-1.Nicula, R.; Stir, M.; Wurm, A.; Catalá Civera, JM.; Ishizaki, K.; Vaucher, S.; Zhuravlev, E.... (2011). Microwave calorimetry using X-rays. Thermochimica Acta. 526(1):137-142. https://doi.org/10.1016/j.tca.2011.09.007S137142526